From 53b76e347a6a2a67928d21229561eddb524007ac Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Sat, 1 Nov 2025 19:01:05 +0700 Subject: [PATCH 01/42] :sparkles:feat: some change --- examples/house_prices.py | 19 +++++++++++++------ plexe/agents/conversational.py | 28 ++++++++++++++++++++++++++-- plexe/main.py | 9 +++++++++ plexe/tools/conversation.py | 28 ++++++++++++++++++++++------ 4 files changed, 70 insertions(+), 14 deletions(-) diff --git a/examples/house_prices.py b/examples/house_prices.py index e721eaaf..1fcb4b42 100644 --- a/examples/house_prices.py +++ b/examples/house_prices.py @@ -28,16 +28,23 @@ # Note: for conciseness we leave the input schema empty and let plexe infer it model = ModelBuilder( provider=ProviderConfig( - default_provider="openai/gpt-4o", - orchestrator_provider="anthropic/claude-sonnet-4-20250514", - research_provider="openai/gpt-4o", - engineer_provider="anthropic/claude-3-7-sonnet-20250219", - ops_provider="anthropic/claude-3-7-sonnet-20250219", - tool_provider="openai/gpt-4o", + # default_provider="openai/gpt-4o", + # orchestrator_provider="anthropic/claude-sonnet-4-20250514", + # research_provider="openai/gpt-4o", + # engineer_provider="anthropic/claude-3-7-sonnet-20250219", + # ops_provider="anthropic/claude-3-7-sonnet-20250219", + # tool_provider="openai/gpt-4o", + default_provider="gemini/gemini-2.5-flash", + orchestrator_provider="gemini/gemini-2.5-flash", + research_provider="gemini/gemini-2.5-flash", + engineer_provider="gemini/gemini-2.5-flash", + ops_provider="gemini/gemini-2.5-flash", + tool_provider="gemini/gemini-2.5-flash", ), verbose=False, ) + # Step 2: Build the model using the training dataset # 2B: Build the model with the dataset # NOTE: In order to run this example, you will need to download the dataset from Kaggle diff --git a/plexe/agents/conversational.py b/plexe/agents/conversational.py index 683cf432..2acfcbfe 100644 --- a/plexe/agents/conversational.py +++ b/plexe/agents/conversational.py @@ -7,6 +7,7 @@ """ import logging +import os from smolagents import ToolCallingAgent, LiteLLMModel @@ -28,7 +29,7 @@ class ConversationalAgent: def __init__( self, - model_id: str = "anthropic/claude-sonnet-4-20250514", + model_id: str | None = None, verbose: bool = False, ): """ @@ -38,7 +39,30 @@ def __init__( model_id: Model ID for the LLM to use for conversation verbose: Whether to display detailed agent logs """ - self.model_id = model_id + # Choose model id with this precedence: + # 1. explicit `model_id` argument + # 2. env var `PLEXE_CONVERSATIONAL_MODEL` + # 3. automatic selection based on available API keys + # - GEMINI -> gemini/gemini-2.5-flash + # - OPENAI -> openai/gpt-4o-mini + # - ANTHROPIC -> anthropic/claude-sonnet-4-20250514 + # 4. fallback to anthropic default + env_model = os.environ.get("PLEXE_CONVERSATIONAL_MODEL") + + if model_id: + self.model_id = model_id + elif env_model: + self.model_id = env_model + else: + # Auto-detect from available API keys + if os.environ.get("GEMINI_API_KEY"): + self.model_id = "gemini/gemini-2.5-flash" + elif os.environ.get("OPENAI_API_KEY"): + self.model_id = "openai/gpt-4o-mini" + elif os.environ.get("ANTHROPIC_API_KEY"): + self.model_id = "anthropic/claude-sonnet-4-20250514" + else: + self.model_id = "anthropic/claude-sonnet-4-20250514" self.verbose = verbose # Set verbosity level diff --git a/plexe/main.py b/plexe/main.py index 9e6c79a5..6d1b813e 100644 --- a/plexe/main.py +++ b/plexe/main.py @@ -6,6 +6,7 @@ import time import webbrowser import logging +import os import uvicorn @@ -18,6 +19,14 @@ def main(): host = "127.0.0.1" port = 8000 + # If the user exported GEMINI_API_KEY but not GOOGLE_API_KEY, map it so + # litellm/Google provider can pick it up (common naming mismatch). + # This does not persist anything to disk and only affects the current process. + gemini_key = os.environ.get("GEMINI_API_KEY") + if gemini_key and not os.environ.get("GOOGLE_API_KEY") and not os.environ.get("GOOGLE_APPLICATION_CREDENTIALS"): + os.environ["GOOGLE_API_KEY"] = gemini_key + logging.getLogger(__name__).info("Mapped GEMINI_API_KEY -> GOOGLE_API_KEY for this process") + # Configure uvicorn to run in a thread config = uvicorn.Config("plexe.server:app", host=host, port=port, log_level="info", reload=False) server = uvicorn.Server(config) diff --git a/plexe/tools/conversation.py b/plexe/tools/conversation.py index e9dce7ab..17a0956d 100644 --- a/plexe/tools/conversation.py +++ b/plexe/tools/conversation.py @@ -125,15 +125,31 @@ def initiate_model_build( from plexe.model_builder import ModelBuilder # Create ModelBuilder instance with loaded DataFrames + # model_builder = ModelBuilder( + # provider=ProviderConfig( + # default_provider="openai/gpt-4o", + # orchestrator_provider="anthropic/claude-3-7-sonnet-20250219", + # research_provider="openai/gpt-4o", + # engineer_provider="anthropic/claude-sonnet-4-20250514", + # ops_provider="anthropic/claude-sonnet-4-20250514", + # tool_provider="openai/gpt-4o", + # ), + # ) + + gemini_model = "gemini/gemini-2.5-flash" # or your specific Gemini model + model_builder = ModelBuilder( provider=ProviderConfig( - default_provider="openai/gpt-4o", - orchestrator_provider="anthropic/claude-3-7-sonnet-20250219", - research_provider="openai/gpt-4o", - engineer_provider="anthropic/claude-sonnet-4-20250514", - ops_provider="anthropic/claude-sonnet-4-20250514", - tool_provider="openai/gpt-4o", + # Use Gemini for all roles since it's our only available provider + default_provider=gemini_model, + orchestrator_provider=gemini_model, + research_provider=gemini_model, + engineer_provider=gemini_model, + ops_provider=gemini_model, + tool_provider=gemini_model, ), + # Add working_dir to ensure model artifacts are saved + working_dir="./workdir/chat-session/", ) # Start the build process From 30671844ba46874763d3787a593037e1c25d33f9 Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Sat, 15 Nov 2025 00:04:00 +0700 Subject: [PATCH 02/42] Fix formatting/lint: run pre-commit hooks --- .env.example | 12 ++ docker-compose.yml | 42 +++++++ docs/postgres.md | 67 ++++++++++ examples/house_prices.py | 52 ++++++-- examples/test_saved_model.py | 115 ++++++++++++++++++ feature_transformer.py | 104 ++++++++++++++++ feature_transformer_code.py | 104 ++++++++++++++++ mlflow.db | Bin 0 -> 385024 bytes plexe/agents/agents.py | 21 +++- plexe/agents/dataset_analyser.py | 3 +- plexe/internal/common/provider.py | 4 +- plexe/internal/models/feature_handling.py | 58 +++++++++ plexe/main.py | 3 +- plexe/model_builder.py | 8 +- plexe/models.py | 2 +- tests/integration/test_ray_integration.py | 2 +- .../internal/models/callbacks/test_mlflow.py | 4 +- 17 files changed, 576 insertions(+), 25 deletions(-) create mode 100644 .env.example create mode 100644 docker-compose.yml create mode 100644 docs/postgres.md create mode 100644 examples/test_saved_model.py create mode 100644 feature_transformer.py create mode 100644 feature_transformer_code.py create mode 100644 mlflow.db create mode 100644 plexe/internal/models/feature_handling.py diff --git a/.env.example b/.env.example new file mode 100644 index 00000000..d9c07c08 --- /dev/null +++ b/.env.example @@ -0,0 +1,12 @@ +# Postgres +POSTGRES_USER=mlflow +POSTGRES_PASSWORD=mlflow +POSTGRES_DB=mlflow_db + +# MLflow backend store URI (used by client apps if you want to override) +# Example: postgresql+psycopg2://mlflow:mlflow@localhost:5432/mlflow_db +MLFLOW_BACKEND_STORE_URI=postgresql+psycopg2://mlflow:mlflow@postgres:5432/mlflow_db + +# pgAdmin credentials +PGADMIN_EMAIL=admin@example.com +PGADMIN_PASSWORD=admin diff --git a/docker-compose.yml b/docker-compose.yml new file mode 100644 index 00000000..4a601b72 --- /dev/null +++ b/docker-compose.yml @@ -0,0 +1,42 @@ +version: '3.8' + +services: + postgres: + image: postgres:15 + restart: unless-stopped + environment: + POSTGRES_USER: ${POSTGRES_USER:-mlflow} + POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-mlflow} + POSTGRES_DB: ${POSTGRES_DB:-mlflow_db} + volumes: + - postgres_data:/var/lib/postgresql/data + ports: + - "5432:5432" + + mlflow: + image: python:3.11-slim + restart: unless-stopped + depends_on: + - postgres + environment: + # backend store used by mlflow server (connects to the postgres service) + BACKEND_STORE_URI: ${MLFLOW_BACKEND_STORE_URI:-postgresql+psycopg2://mlflow:mlflow@postgres:5432/mlflow_db} + # default artifact root inside the container (mounted to host ./mlruns) + ARTIFACT_ROOT: /mlruns + volumes: + - ./mlruns:/mlruns + ports: + - "5000:5000" + command: ["/bin/sh", "-c", "pip install --no-cache-dir mlflow psycopg2-binary && mlflow server --backend-store-uri $BACKEND_STORE_URI --default-artifact-root $ARTIFACT_ROOT --host 0.0.0.0 --port 5000"] + + pgadmin: + image: dpage/pgadmin4:7 + restart: unless-stopped + environment: + PGADMIN_DEFAULT_EMAIL: ${PGADMIN_EMAIL:-admin@example.com} + PGADMIN_DEFAULT_PASSWORD: ${PGADMIN_PASSWORD:-admin} + ports: + - "8080:80" + +volumes: + postgres_data: diff --git a/docs/postgres.md b/docs/postgres.md new file mode 100644 index 00000000..ca34f677 --- /dev/null +++ b/docs/postgres.md @@ -0,0 +1,67 @@ +## Running PostgreSQL (and MLflow) with Docker + +This project uses MLflow and optionally can use PostgreSQL as a backing store. The repository includes a ready-to-run `docker-compose.yml` that starts: + +- PostgreSQL 15 +- MLflow server (configured to use Postgres for the backend store) +- pgAdmin (optional UI for managing the database) + +Files added: + +- `docker-compose.yml` — launches the services +- `.env.example` — example environment variables (copy to `.env` and edit) + +Quick start + +1. Copy the example env file and edit if you want different credentials: + +```bash +cp .env.example .env +# edit .env if necessary +``` + +2. Start the stack: + +```bash +docker compose up -d +``` + +3. Confirm services are running: + +```bash +docker compose ps +``` + +4. MLflow UI will be available at http://localhost:5000 + +5. pgAdmin will be available at http://localhost:8080 (use credentials from `.env`). + +How MLflow is configured + +The compose uses an environment variable `MLFLOW_BACKEND_STORE_URI` pointing to Postgres: + +``` +postgresql+psycopg2://:@postgres:5432/ +``` + +MLflow stores metadata (experiments, runs) in Postgres and artifacts under the `./mlruns` folder mounted from the host. + +Pointing Plexe to the MLflow server + +The repo contains an MLflow callback at `plexe/internal/models/callbacks/mlflow.py` that sets the MLflow tracking URI via `mlflow.set_tracking_uri(...)` when the callback is initialized. You can either: + +- Set the environment variable `MLFLOW_TRACKING_URI` before running your code, e.g. `export MLFLOW_TRACKING_URI=http://localhost:5000`. +- Or in Python set `mlflow.set_tracking_uri('http://localhost:5000')` before creating the `MLFlowCallback`. + +Example — run a script with MLflow tracking enabled: + +```bash +export MLFLOW_TRACKING_URI=http://localhost:5000 +python examples/test_saved_model.py +``` + +Notes & tips + +- The compose installs `psycopg2-binary` inside the `mlflow` container at startup for convenience. For production, build a small image with pinned deps. +- If you already have Postgres running locally, you can point `MLFLOW_BACKEND_STORE_URI` to it and remove the `postgres` service. +- To persist the DB data, `postgres_data` volume is created by compose. diff --git a/examples/house_prices.py b/examples/house_prices.py index 1fcb4b42..5c99095c 100644 --- a/examples/house_prices.py +++ b/examples/house_prices.py @@ -16,6 +16,7 @@ # NOTE: you must download the dataset from Kaggle for this example to work from datetime import datetime +import os import pandas as pd import plexe @@ -48,6 +49,17 @@ # Step 2: Build the model using the training dataset # 2B: Build the model with the dataset # NOTE: In order to run this example, you will need to download the dataset from Kaggle +# Make MLflow callback optional. Set ENABLE_MLFLOW=1 in the environment to enable MLflow integration. +callbacks_list = [] +if os.environ.get("ENABLE_MLFLOW", "0") == "1": + callbacks_list = [ + MLFlowCallback( + tracking_uri="http://127.0.0.1:8080", + experiment_name=f"house-prices-{datetime.now().strftime('%Y%m%d-%H%M%S')}", + ) + ] + + m = model.build( datasets=[pd.read_csv("examples/datasets/house-prices-train.csv")], intent=( @@ -61,24 +73,44 @@ max_iterations=2, timeout=1800, # 30 minute timeout run_timeout=180, - callbacks=[ - MLFlowCallback( - tracking_uri="http://127.0.0.1:8080", - experiment_name=f"house-prices-{datetime.now().strftime('%Y%m%d-%H%M%S') }", - ) - ], + callbacks=callbacks_list, ) -# Step 3: Save the model +# Step 3: Save the model and handle test data transformation plexe.save_model(m, "house-prices.tar.gz") -# Step 4: Run a prediction on the built model +# Step 4: Load and prepare test data +print("\nPreparing test data for predictions...") test_df = pd.read_csv("examples/datasets/house-prices-test.csv").sample(10) -predictions = pd.DataFrame.from_records([m.predict(x) for x in test_df.to_dict(orient="records")]) -# Step 5: print a sample of predictions +# Get the predictor's transform method if available +if hasattr(m.predictor, "transform"): + print("Found transform method in predictor, applying transformations...") + try: + # Use the predictor's built-in transform method + transformed_test = m.predictor.transform(test_df) + predictions = pd.DataFrame.from_records([m.predict(x) for x in transformed_test.to_dict(orient="records")]) + except Exception as e: + print(f"Error during transformation: {str(e)}") + print("Falling back to raw predictions (warning: may be incorrect)") + predictions = pd.DataFrame.from_records([m.predict(x) for x in test_df.to_dict(orient="records")]) +else: + print("No transformation method found, using raw test data (warning: may cause incorrect predictions)") + predictions = pd.DataFrame.from_records([m.predict(x) for x in test_df.to_dict(orient="records")]) + +# Step 5: Print a sample of predictions +print("\nPredictions:") print(predictions) # Step 6: Print model description +print("\nModel description:") description = m.describe() print(description.as_text()) + +# Optional: Print available model artifacts and generated code +print("\nGenerated artifacts and code:") +print(f"Model artifacts: {m.artifacts}") +print(f"Training code available: {bool(m.trainer_source)}") +print(f"Feature transformer code available: {bool(m.feature_transformer_source)}") +print(f"Testing code available: {bool(m.testing_source)}") +print(f"Dataset splitter code available: {bool(m.dataset_splitter_source)}") diff --git a/examples/test_saved_model.py b/examples/test_saved_model.py new file mode 100644 index 00000000..084a6236 --- /dev/null +++ b/examples/test_saved_model.py @@ -0,0 +1,115 @@ +""" +Script to test a saved Plexe model by loading it and running predictions. +""" + +import pandas as pd +import numpy as np +from sklearn.preprocessing import LabelEncoder +import plexe + +# Load the saved model +print("Loading saved model from house-prices.tar.gz...") +model = plexe.load_model("house-prices.tar.gz") +print("\nModel loaded successfully!") + +# Print and save transformer code if available +if model.feature_transformer_source: + print("\nFeature transformer code found:") + print("-" * 80) + print(model.feature_transformer_source) + print("-" * 80) + + # Save transformer code for inspection + with open("feature_transformer_code.py", "w") as f: + f.write(model.feature_transformer_source) + print("\nSaved transformer code to 'feature_transformer_code.py'") + +# Load and prepare test data +print("\nLoading test data...") +test_df = pd.read_csv("examples/datasets/house-prices-test.csv").sample(10) +original_test = test_df.copy() # Keep original for comparison +print(f"Test data shape: {test_df.shape}") + +# Basic preprocessing for categorical columns +print("\nPreprocessing categorical columns...") +categorical_columns = test_df.select_dtypes(include=["object"]).columns +for col in categorical_columns: + # First try ordinal encoding + le = LabelEncoder() + try: + test_df[col] = le.fit_transform(test_df[col].astype(str)) + except Exception: + # If fails, try one-hot encoding + print(f"Using one-hot encoding for {col}") + dummies = pd.get_dummies(test_df[col], prefix=col) + test_df = pd.concat([test_df, dummies], axis=1) + test_df.drop(col, axis=1, inplace=True) + +# Fill missing values +print("Handling missing values...") +numeric_columns = test_df.select_dtypes(include=[np.number]).columns +test_df[numeric_columns] = test_df[numeric_columns].fillna(test_df[numeric_columns].mean()) + +# Try to transform test data if possible +print("\nPreparing test data for predictions...") +try: + if hasattr(model.predictor, "transform"): + print("Found transform method, applying model's transformations...") + transformed_test = model.predictor.transform(original_test) # Try with original data first + print("Data transformed successfully by model's transformer!") + predictions = pd.DataFrame.from_records([model.predict(x) for x in transformed_test.to_dict(orient="records")]) + else: + print("Using manually preprocessed data...") + predictions = pd.DataFrame.from_records([model.predict(x) for x in test_df.to_dict(orient="records")]) +except Exception as e: + print(f"\nError with model's transformer: {str(e)}") + print("Attempting prediction with manually preprocessed data...") + try: + predictions = pd.DataFrame.from_records([model.predict(x) for x in test_df.to_dict(orient="records")]) + except Exception as e: + print(f"Error during prediction: {str(e)}") + raise + +# Print results +print("\nPredictions:") +print(predictions) + +print("\nModel description:") +description = model.describe() +print(description.as_text()) + +# Print feature importance if available in model metadata +if hasattr(model, "metadata") and "feature_importance" in model.metadata: + print("\nFeature Importance:") + print(model.metadata["feature_importance"]) + +# Print available components +print("\nModel components available:") +print(f"Training code available: {bool(model.trainer_source)}") +print(f"Feature transformer code available: {bool(model.feature_transformer_source)}") +print(f"Testing code available: {bool(model.testing_source)}") +print(f"Dataset splitter code available: {bool(model.dataset_splitter_source)}") + +# If we have the original test data with SalePrice, show comparison +if "SalePrice" in original_test.columns: + print("\nSample comparison (actual vs predicted):") + comparison = pd.DataFrame( + { + "Actual": original_test["SalePrice"], + "Predicted": predictions["SalePrice"] if "SalePrice" in predictions.columns else predictions.iloc[:, 0], + } + ) + print(comparison) + + # Calculate error metrics + errors = comparison["Actual"] - comparison["Predicted"] + metrics = { + "Mean Absolute Error": abs(errors).mean(), + "Mean Squared Error": (errors**2).mean(), + "Root Mean Squared Error": (errors**2).mean() ** 0.5, + "Mean Absolute Percentage Error": (abs(errors) / comparison["Actual"]).mean() * 100, + } + + print("\nError Metrics:") + for metric_name, value in metrics.items(): + print(f"{metric_name}: {value:.2f}") diff --git a/feature_transformer.py b/feature_transformer.py new file mode 100644 index 00000000..00f7c03d --- /dev/null +++ b/feature_transformer.py @@ -0,0 +1,104 @@ +import pandas as pd +import numpy as np +from sklearn.preprocessing import StandardScaler, OneHotEncoder +from sklearn.compose import ColumnTransformer +from plexe.core.interfaces.feature_transformer import FeatureTransformer + + +class FeatureTransformerImplementation(FeatureTransformer): + + def transform(self, inputs: pd.DataFrame) -> pd.DataFrame: + df = inputs.copy() + + target_variable = "SalePrice" + + # 1. Target Variable Transformation + if target_variable in df.columns: + df[target_variable] = np.log1p(df[target_variable]) + print(f"Applied log1p transformation to target variable '{target_variable}'.") + else: + print(f"Target variable '{target_variable}' not found in DataFrame. Skipping transformation.") + + # Separate features and target for transformation (if target is present) + if target_variable in df.columns: + X = df.drop(columns=[target_variable]) + y = df[target_variable] + else: + X = df + y = None # No target present + + # Identify numerical and categorical features based on dtypes + + # Define features for specific missing value imputation based on EDA + numerical_features_with_nan_specific = ["LotFrontage", "MasVnrArea", "GarageYrBlt"] + categorical_features_with_nan_specific = [ + "BsmtQual", + "BsmtCond", + "BsmtExposure", + "BsmtFinType1", + "BsmtFinType2", + "FireplaceQu", + "GarageType", + "GarageFinish", + "GarageQual", + "GarageCond", + ] + + # Step 1: Impute numerical missing values using median + for col in numerical_features_with_nan_specific: + if col in X.columns: + median_val = X[col].median() + X[col] = X[col].fillna(median_val) + print(f"Imputed missing values in numerical feature '{col}' with median: {median_val}.") + + # Step 2: Impute categorical missing values using 'NA' + for col in categorical_features_with_nan_specific: + if col in X.columns: + X[col] = X[col].fillna("NA") + print(f"Imputed missing values in categorical feature '{col}' with 'NA'.") + + # Re-identify numerical and categorical features after imputation + # This is important in case dtypes changed or columns were entirely removed/added (not in this case) + final_numerical_features = X.select_dtypes(include=np.number).columns.tolist() + final_categorical_features = X.select_dtypes(include="object").columns.tolist() + + # Define the ColumnTransformer for scaling numerical features and encoding categorical features + # StandardScaler for numerical features + # OneHotEncoder for categorical features (handle_unknown='ignore' for robustness) + preprocessor = ColumnTransformer( + transformers=[ + ("num_scaler", StandardScaler(), final_numerical_features), + ( + "cat_encoder", + OneHotEncoder(handle_unknown="ignore", sparse_output=False), + final_categorical_features, + ), + ], + remainder="drop", # Drop any columns not explicitly transformed + ) + + # Fit and transform the features + X_transformed_array = preprocessor.fit_transform(X) + + # Get feature names after one-hot encoding + # This requires fitting the one-hot encoder and then getting names + # Extract the one-hot encoder from the column transformer + ohe = preprocessor.named_transformers_["cat_encoder"] + feature_names_ohe = ohe.get_feature_names_out(final_categorical_features) + + # Combine all feature names + transformed_feature_names = final_numerical_features + list(feature_names_ohe) + + # Create a new DataFrame from the transformed array + X_transformed = pd.DataFrame(X_transformed_array, columns=transformed_feature_names, index=X.index) + print("Features scaled and encoded.") + + # Recombine with target variable if it was present + if y is not None: + transformed_df = pd.concat([X_transformed, y], axis=1) + print("Transformed features recombined with transformed target variable.") + else: + transformed_df = X_transformed + print("Transformed features returned without target variable.") + + return transformed_df diff --git a/feature_transformer_code.py b/feature_transformer_code.py new file mode 100644 index 00000000..00f7c03d --- /dev/null +++ b/feature_transformer_code.py @@ -0,0 +1,104 @@ +import pandas as pd +import numpy as np +from sklearn.preprocessing import StandardScaler, OneHotEncoder +from sklearn.compose import ColumnTransformer +from plexe.core.interfaces.feature_transformer import FeatureTransformer + + +class FeatureTransformerImplementation(FeatureTransformer): + + def transform(self, inputs: pd.DataFrame) -> pd.DataFrame: + df = inputs.copy() + + target_variable = "SalePrice" + + # 1. Target Variable Transformation + if target_variable in df.columns: + df[target_variable] = np.log1p(df[target_variable]) + print(f"Applied log1p transformation to target variable '{target_variable}'.") + else: + print(f"Target variable '{target_variable}' not found in DataFrame. Skipping transformation.") + + # Separate features and target for transformation (if target is present) + if target_variable in df.columns: + X = df.drop(columns=[target_variable]) + y = df[target_variable] + else: + X = df + y = None # No target present + + # Identify numerical and categorical features based on dtypes + + # Define features for specific missing value imputation based on EDA + numerical_features_with_nan_specific = ["LotFrontage", "MasVnrArea", "GarageYrBlt"] + categorical_features_with_nan_specific = [ + "BsmtQual", + "BsmtCond", + "BsmtExposure", + "BsmtFinType1", + "BsmtFinType2", + "FireplaceQu", + "GarageType", + "GarageFinish", + "GarageQual", + "GarageCond", + ] + + # Step 1: Impute numerical missing values using median + for col in numerical_features_with_nan_specific: + if col in X.columns: + median_val = X[col].median() + X[col] = X[col].fillna(median_val) + print(f"Imputed missing values in numerical feature '{col}' with median: {median_val}.") + + # Step 2: Impute categorical missing values using 'NA' + for col in categorical_features_with_nan_specific: + if col in X.columns: + X[col] = X[col].fillna("NA") + print(f"Imputed missing values in categorical feature '{col}' with 'NA'.") + + # Re-identify numerical and categorical features after imputation + # This is important in case dtypes changed or columns were entirely removed/added (not in this case) + final_numerical_features = X.select_dtypes(include=np.number).columns.tolist() + final_categorical_features = X.select_dtypes(include="object").columns.tolist() + + # Define the ColumnTransformer for scaling numerical features and encoding categorical features + # StandardScaler for numerical features + # OneHotEncoder for categorical features (handle_unknown='ignore' for robustness) + preprocessor = ColumnTransformer( + transformers=[ + ("num_scaler", StandardScaler(), final_numerical_features), + ( + "cat_encoder", + OneHotEncoder(handle_unknown="ignore", sparse_output=False), + final_categorical_features, + ), + ], + remainder="drop", # Drop any columns not explicitly transformed + ) + + # Fit and transform the features + X_transformed_array = preprocessor.fit_transform(X) + + # Get feature names after one-hot encoding + # This requires fitting the one-hot encoder and then getting names + # Extract the one-hot encoder from the column transformer + ohe = preprocessor.named_transformers_["cat_encoder"] + feature_names_ohe = ohe.get_feature_names_out(final_categorical_features) + + # Combine all feature names + transformed_feature_names = final_numerical_features + list(feature_names_ohe) + + # Create a new DataFrame from the transformed array + X_transformed = pd.DataFrame(X_transformed_array, columns=transformed_feature_names, index=X.index) + print("Features scaled and encoded.") + + # Recombine with target variable if it was present + if y is not None: + transformed_df = pd.concat([X_transformed, y], axis=1) + print("Transformed features recombined with transformed target variable.") + else: + transformed_df = X_transformed + print("Transformed features returned without target variable.") + + return transformed_df diff --git a/mlflow.db b/mlflow.db new file mode 100644 index 0000000000000000000000000000000000000000..a179de85e485765da1ba0342309dac356c049c89 GIT binary patch literal 385024 zcmeFa3w&HxbuX-uMjFlAPU6UpaWb((Y&DiN=QZb?7-LIg*%pyxTe6)52-EY}N1Avv zBhQTNm|QN{1X@}iEiJUoM<2KS^=pCqwU;(++Cm|11C-L+%cF%-Qa*Yq6iP3J7D9T{ zhP(Ee*Eyrn?4vV+o5wQ5md;sg?X~}V?bq6Cud{e&HeV$vt5jamswtswTVEj1cQlpi z>+Aap{P!yOukq&|_#xQ%1^x{~*bn?mCj~lVzb3_0U zKm-s0L;w*$1P}p401-e05CKF05!ea@#uq`#$PxJK#=Y_6ANCE!KRb}vnRp}_Pm;td zxECA4~F`tPwfIFN^2D|wpz{`q%y{*d5PoF{20ecqNK0{i<(i* zUm{fE?O&<=eRqJ$rIqU_H_h>aD6-^oErs8m-5GfJ=zF)l@_c_+g+Z{y%PhfsL*b+E z`Q#Ol3xA&<=qi`vcv)0ga)pN6sZY)40SNdTOzCKk<`e<`p=7=<`JH4w`B%wDl0TI! z_b3wC5dlO15kLeG0Ym^1Km-s0L;w*$1Q3B2E&{^?I|9@hGng8f4s>>0)EpwgZUod( zFt9N}%|p?D%fNKFa}hP)NMvC5aNVyHr!BJWh1)Dxb3_0UKm-s0L;w*$1P}p401-e0 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self, + # orchestrator_model_id: str = "anthropic/claude-3-7-sonnet-20250219", + # ml_researcher_model_id: str = "openai/gpt-4o", + # ml_engineer_model_id: str = "anthropic/claude-3-7-sonnet-20250219", + # ml_ops_engineer_model_id: str = "anthropic/claude-3-7-sonnet-20250219", + # tool_model_id: str = "openai/gpt-4o", + # verbose: bool = False, + # max_steps: int = 50, + # distributed: bool = False, + # chain_of_thought_callable: Optional[Callable] = None, + # max_solutions: int = 1, self, - orchestrator_model_id: str = "anthropic/claude-3-7-sonnet-20250219", - ml_researcher_model_id: str = "openai/gpt-4o", - ml_engineer_model_id: str = "anthropic/claude-3-7-sonnet-20250219", - ml_ops_engineer_model_id: str = "anthropic/claude-3-7-sonnet-20250219", - tool_model_id: str = "openai/gpt-4o", + orchestrator_model_id: str = "gemini/gemini-2.5-flash", + ml_researcher_model_id: str = "gemini/gemini-2.5-flash", + ml_engineer_model_id: str = "agemini/gemini-2.5-flash", + ml_ops_engineer_model_id: str = "gemini/gemini-2.5-flash", + tool_model_id: str = "gemini/gemini-2.5-flash", verbose: bool = False, max_steps: int = 50, distributed: bool = False, diff --git a/plexe/agents/dataset_analyser.py b/plexe/agents/dataset_analyser.py index c6291ba1..37eff26d 100644 --- a/plexe/agents/dataset_analyser.py +++ b/plexe/agents/dataset_analyser.py @@ -29,7 +29,8 @@ class EdaAgent: def __init__( self, - model_id: str = "openai/gpt-4o", + # model_id: str = "openai/gpt-4o", + model_id: str = "gemini/gemini-2.5-flash", verbose: bool = False, chain_of_thought_callable: Callable = None, ): diff --git a/plexe/internal/common/provider.py b/plexe/internal/common/provider.py index 5c1030db..43ebcad9 100644 --- a/plexe/internal/common/provider.py +++ b/plexe/internal/common/provider.py @@ -34,7 +34,7 @@ class ProviderConfig: def __init__( self, - default_provider: str = "openai/gpt-4o-mini", + default_provider: str = "gemini/gemini-2.5-flash", orchestrator_provider: Optional[str] = None, research_provider: Optional[str] = None, engineer_provider: Optional[str] = None, @@ -70,7 +70,7 @@ class Provider: """ def __init__(self, model: str = None): - default_model = "openai/gpt-4o-mini" + default_model = "gemini/gemini-2.5-flash" self.model = model or default_model if "/" not in self.model: self.model = default_model diff --git a/plexe/internal/models/feature_handling.py b/plexe/internal/models/feature_handling.py new file mode 100644 index 00000000..be00d9d5 --- /dev/null +++ b/plexe/internal/models/feature_handling.py @@ -0,0 +1,58 @@ +""" +Helper functions for handling features in model prediction. +""" + +from typing import Dict, List, Any +import logging + +import pandas as pd + +logger = logging.getLogger(__name__) + + +def get_required_features(training_data: pd.DataFrame) -> List[str]: + """Get list of all features required for prediction based on training data.""" + categorical_cols = training_data.select_dtypes(include=["object", "category"]).columns + numerical_cols = training_data.select_dtypes(include=["int64", "float64"]).columns + + # Get all one-hot encoded column names for categorical features + onehot_cols = [] + for col in categorical_cols: + unique_values = training_data[col].unique() + onehot_cols.extend([f"{col}_{val}" for val in unique_values]) + + return list(numerical_cols) + onehot_cols + + +def ensure_features_present(input_data: Dict[str, Any], required_features: List[str]) -> Dict[str, Any]: + """ + Ensure all required features are present in input data. + Args: + input_data: Input dictionary for prediction + required_features: List of features that should be present + Returns: + Dict with all required features (missing ones set to 0) + """ + processed = input_data.copy() + + # Add missing features with default value 0 + for feature in required_features: + if feature not in processed: + processed[feature] = 0 + logger.debug(f"Added missing feature '{feature}' with default value 0") + + return processed + + +def validate_required_features(input_data: Dict[str, Any], required_features: List[str]) -> None: + """ + Validate that input data has all strictly required features (non-one-hot). + Raises ValueError if any required feature is missing. + """ + # Identify base features (before one-hot encoding) + base_features = {f.split("_")[0] for f in required_features} + + # Check for missing base features + missing = [f for f in base_features if not any(k.startswith(f) for k in input_data.keys())] + if missing: + raise ValueError(f"Missing required base features: {missing}") diff --git a/plexe/main.py b/plexe/main.py index 6d1b813e..a4f23713 100644 --- a/plexe/main.py +++ b/plexe/main.py @@ -4,7 +4,6 @@ import threading import time -import webbrowser import logging import os @@ -41,7 +40,7 @@ def main(): # Open the browser url = f"http://{host}:{port}" logger.info(f"Opening browser at {url}") - webbrowser.open(url) + # webbrowser.open(url) # Keep the main thread alive try: diff --git a/plexe/model_builder.py b/plexe/model_builder.py index 0d4dffd7..c2cf9e18 100644 --- a/plexe/model_builder.py +++ b/plexe/model_builder.py @@ -36,7 +36,7 @@ class ModelBuilder: def __init__( self, - provider: str | ProviderConfig = "openai/gpt-4o-mini", + provider: str | ProviderConfig = "gemini/gemini-2.5-flash", verbose: bool = False, distributed: bool = False, working_dir: Optional[str] = None, @@ -96,6 +96,12 @@ def build( object_registry = ObjectRegistry() object_registry.clear() + if (datasets is None) or (len(datasets) == 0): + print("No datasets provided") + raise ValueError("At least one dataset must be provided for model building") + else: + print(f"Building model with {len(datasets)} dataset(s)") + # Validate parameters if timeout is None and max_iterations is None: raise ValueError("At least one of 'timeout' or 'max_iterations' must be set") diff --git a/plexe/models.py b/plexe/models.py index dfab6512..464cdcfd 100644 --- a/plexe/models.py +++ b/plexe/models.py @@ -141,7 +141,7 @@ def __init__( def build( self, datasets: List[pd.DataFrame | DatasetGenerator], - provider: str | ProviderConfig = "openai/gpt-4o-mini", + provider: str | ProviderConfig = "gemini/gemini-2.5-flash", timeout: int = None, max_iterations: int = None, run_timeout: int = 1800, diff --git a/tests/integration/test_ray_integration.py b/tests/integration/test_ray_integration.py index 1b20942e..d8f98336 100644 --- a/tests/integration/test_ray_integration.py +++ b/tests/integration/test_ray_integration.py @@ -38,7 +38,7 @@ def test_model_with_ray(sample_dataset): # Set a short timeout for testing model.build( datasets=[sample_dataset], - provider="openai/gpt-4o-mini", + provider="gemini/gemini-2.5-flash", timeout=300, # 5 minutes max run_timeout=60, # 1 minute per run ) diff --git a/tests/unit/internal/models/callbacks/test_mlflow.py b/tests/unit/internal/models/callbacks/test_mlflow.py index a24e4c88..422a6ab1 100644 --- a/tests/unit/internal/models/callbacks/test_mlflow.py +++ b/tests/unit/internal/models/callbacks/test_mlflow.py @@ -45,7 +45,7 @@ class OutputSchema(BaseModel): # Create build info for different stages build_info = BuildStateInfo( intent="Predict house prices", - provider="openai/gpt-4o-mini", + provider="gemini/gemini-2.5-flash", input_schema=InputSchema, output_schema=OutputSchema, run_timeout=300, @@ -57,7 +57,7 @@ class OutputSchema(BaseModel): # Create iteration info with node iteration_info = BuildStateInfo( intent="Predict house prices", - provider="openai/gpt-4o-mini", + provider="gemini/gemini-2.5-flash", input_schema=InputSchema, output_schema=OutputSchema, run_timeout=300, From 8a04937867a65fdbbbe7eb80087df093a7cc0d1b Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Sun, 16 Nov 2025 12:36:02 +0700 Subject: [PATCH 03/42] Fix MLflow allowed hosts configuration for Docker --- .dockerignore | 49 ++ .env.example | 12 +- .gitignore | 102 +++ DOCKER_QUICKSTART.md | 225 +++++ Dockerfile | 54 ++ Dockerfile.dev | 44 + Dockerfile.mlflow | 7 + docker-compose.dev.yml | 79 ++ docker-compose.yml | 36 +- docs/docker-build-issues.md | 246 ++++++ docs/docker-performance.md | 188 ++++ docs/docker.md | 284 ++++++ model-from-chat.tar.gz | Bin 0 -> 68059 bytes plexe/server.py | 23 +- plexe/tools/conversation.py | 14 + plexe/ui/frontend/.dockerignore | 8 + plexe/ui/frontend/Dockerfile | 30 + plexe/ui/frontend/README.md | 72 ++ plexe/ui/frontend/index.html | 12 + plexe/ui/frontend/nginx.conf | 50 ++ plexe/ui/frontend/package-lock.json | 998 ++++++++++++++++++++++ plexe/ui/frontend/package.json | 18 + plexe/ui/frontend/src/App.jsx | 39 + plexe/ui/frontend/src/components/Chat.jsx | 58 ++ plexe/ui/frontend/src/main.jsx | 10 + plexe/ui/frontend/src/styles.css | 93 ++ plexe/ui/frontend/vite.config.js | 21 + 27 files changed, 2763 insertions(+), 9 deletions(-) create mode 100644 .dockerignore create mode 100644 DOCKER_QUICKSTART.md create mode 100644 Dockerfile create mode 100644 Dockerfile.dev create mode 100644 Dockerfile.mlflow create mode 100644 docker-compose.dev.yml create mode 100644 docs/docker-build-issues.md create mode 100644 docs/docker-performance.md create mode 100644 docs/docker.md create mode 100644 model-from-chat.tar.gz create mode 100644 plexe/ui/frontend/.dockerignore create mode 100644 plexe/ui/frontend/Dockerfile create mode 100644 plexe/ui/frontend/README.md create mode 100644 plexe/ui/frontend/index.html create mode 100644 plexe/ui/frontend/nginx.conf create mode 100644 plexe/ui/frontend/package-lock.json create mode 100644 plexe/ui/frontend/package.json create mode 100644 plexe/ui/frontend/src/App.jsx create mode 100644 plexe/ui/frontend/src/components/Chat.jsx create mode 100644 plexe/ui/frontend/src/main.jsx create mode 100644 plexe/ui/frontend/src/styles.css create mode 100644 plexe/ui/frontend/vite.config.js diff --git a/.dockerignore b/.dockerignore new file mode 100644 index 00000000..f456dca7 --- /dev/null +++ b/.dockerignore @@ -0,0 +1,49 @@ +# Python +__pycache__ +*.py[cod] +*$py.class +*.so +.Python +env/ +venv/ +*.egg-info/ +dist/ +build/ + +# IDEs +.vscode +.idea +*.swp +*.swo +*~ + +# OS +.DS_Store +.env +.env.local + +# Docker +.dockerignore +Dockerfile + +# Git +.git +.gitignore + +# Frontend (don't need for backend build) +node_modules/ +plexe/ui/frontend/dist/ +npm-debug.log + +# Test & coverage +.pytest_cache +.coverage +htmlcov/ + +# MLflow +mlruns/ + +# Misc +*.log +.cache/ +workdir/ diff --git a/.env.example b/.env.example index d9c07c08..b4d2785f 100644 --- a/.env.example +++ b/.env.example @@ -3,10 +3,18 @@ POSTGRES_USER=mlflow POSTGRES_PASSWORD=mlflow POSTGRES_DB=mlflow_db -# MLflow backend store URI (used by client apps if you want to override) +# MLflow backend store URI (used by mlflow server and backend if you want to track experiments) # Example: postgresql+psycopg2://mlflow:mlflow@localhost:5432/mlflow_db MLFLOW_BACKEND_STORE_URI=postgresql+psycopg2://mlflow:mlflow@postgres:5432/mlflow_db +# MLflow tracking URI (URL where mlflow server is running) +MLFLOW_TRACKING_URI=http://mlflow:5000 +MLFLOW_SERVER_ALLOWED_HOSTS=mlflow,localhost,127.0.0.1,localhost:5000,127.0.0.1:5000,mlflow:5000 + +# Frontend environment +# API URL for React frontend to connect to backend (adjust for your deployment) +REACT_APP_API_URL=http://localhost:8000 + # pgAdmin credentials PGADMIN_EMAIL=admin@example.com -PGADMIN_PASSWORD=admin +PGADMIN_PASSWORD=admin \ No newline at end of file diff --git a/.gitignore b/.gitignore index 325f22e2..cef29a98 100644 --- a/.gitignore +++ b/.gitignore @@ -168,6 +168,34 @@ cython_debug/ # option (not recommended) you can uncomment the following to ignore the entire idea folder. #.idea/ +# VSCode +.vscode/ +*.code-workspace + +# Sublime Text +*.sublime-project +*.sublime-workspace + +# Vim +*.swp +*.swo +*~ +.vim/ + +# Emacs +*~ +\#*\# +.\#* + +# OS files +.DS_Store +.DS_Store? +._* +.Spotlight-V100 +.Trashes +ehthumbs.db +Thumbs.db + # PyPI configuration file .pypirc @@ -198,4 +226,78 @@ examples/datasets/* experiments/ notebooks/ +# ============== DOCKER RELATED ============== +# Docker build artifacts +.docker/ +docker-compose.override.yml + +# ============== FRONTEND (NODE/REACT) ============== +# Dependencies +node_modules/ +plexe/ui/frontend/node_modules/ + +# Production build +plexe/ui/frontend/dist/ +plexe/ui/frontend/build/ + +# Misc frontend +plexe/ui/frontend/.env.local +plexe/ui/frontend/.env.*.local +npm-debug.log* +yarn-debug.log* +yarn-error.log* +lerna-debug.log* + +# Frontend IDE +plexe/ui/frontend/.idea/ +plexe/ui/frontend/.vscode/ +plexe/ui/frontend/*.swp + +# ============== BACKEND ARTIFACTS ============== +# Generated model files +*.pkl +*.joblib +*.h5 +*.pt +*.pth +*.onnx + +# Temporary files +*.tmp +*.temp +*.bak +*.backup + +# ============== DATABASE ============== +# SQLite databases +*.sqlite +*.sqlite3 +*.db + +# ============== CREDENTIALS & SECRETS ============== +# Environment files (but keep .env.example) +.env +.env.local +.env.*.local +.env.prod + +# API keys and secrets +.aws/ +.gcloud/ +credentials.json +secrets/ + +# ============== PYTHON VIRTUAL ENVIRONMENTS ============== +venv/ +env/ +ENV/ +.venv + +# ============== PACKAGE MANAGER LOCK FILES ============== +# poetry.lock is typically committed, but you can ignore if preferred +# poetry.lock + +# Keep poetry.lock for reproducible builds +# (uncomment below if you prefer to ignore it) +# poetry.lock **/.claude/settings.local.json diff --git a/DOCKER_QUICKSTART.md b/DOCKER_QUICKSTART.md new file mode 100644 index 00000000..48a957e1 --- /dev/null +++ b/DOCKER_QUICKSTART.md @@ -0,0 +1,225 @@ +# Quick Start Guide - Plexe with Docker + +## 🚀 Fastest Way to Run Plexe + +### Option A: Development Build (Recommended for Quick Start) + +**Faster (2-3 min), but no torch/transformers:** + +```bash +cd /home/admin1/plexe-clone + +# Build with dev config (fast, no torch) +docker compose -f docker-compose.dev.yml build + +# Start services +docker compose -f docker-compose.dev.yml up -d + +# Access services (same ports as production) +# Frontend: http://localhost:3000 +# Backend: http://localhost:8000 +``` + +### Option B: Production Build (Full Features) + +**Slower (5-10 min), but includes torch/transformers:** + +```bash +cd /home/admin1/plexe-clone + +# Build with prod config (full features) +docker compose build + +# Start services +docker compose up -d +``` + +### Step 3: Access + +Open in browser: +- **Frontend**: http://localhost:3000 +- **Backend API**: http://localhost:8000 +- **MLflow**: http://localhost:5000 +- **pgAdmin**: http://localhost:8080 (admin@example.com / admin) + +### Step 4: Check Status + +```bash +# See all containers +docker compose ps +# or for dev: +docker compose -f docker-compose.dev.yml ps + +# See logs +docker compose logs -f frontend +# or for dev: +docker compose -f docker-compose.dev.yml logs -f frontend + +# Check if backend is healthy +curl http://localhost:8000/health +``` + +## 🛑 Stop Services + +```bash +# Stop all (data persists) +docker compose down + +# Stop and remove volumes (⚠️ deletes data) +docker compose down -v +``` + +## 🔄 Development Workflow + +### When You Change Python Code + +```bash +# Rebuild backend (fast, uses cache) +docker compose build backend +docker compose up -d +``` + +### When You Change Frontend Code + +```bash +# Rebuild frontend +docker compose build frontend +docker compose up -d +``` + +### When You Change pyproject.toml + +```bash +# Rebuild backend (includes dependency install) +docker compose build --no-cache backend +docker compose up -d +``` + +### Local Frontend Dev (Hot Reload) + +```bash +# In terminal 1: Start backend + database only +docker compose up postgres mlflow pgadmin + +# In terminal 2: Run frontend with hot reload +cd plexe/ui/frontend +npm install +npm run dev +# Opens http://localhost:5173 +``` + +## 📦 What's Running + +| Service | URL | Port | Purpose | +|---------|-----|------|---------| +| Frontend | http://localhost:3000 | 3000 | React UI | +| Backend | http://localhost:8000 | 8000 | FastAPI + /ws | +| MLflow | http://localhost:5000 | 5000 | Experiment tracking | +| pgAdmin | http://localhost:8080 | 8080 | Database UI | +| Postgres | localhost:5432 | 5432 | Database | + +## 🔗 How Services Connect + +``` +Browser (localhost:3000) + ↓ +Frontend (nginx, port 3000) + ├─→ /ws ──→ nginx proxy ──→ Backend (port 8000) + ├─→ /api ──→ nginx proxy ──→ Backend (port 8000) + └─→ /static ──→ Serve React files + ↓ +Backend (FastAPI, port 8000) + ├─→ Postgres (port 5432) + └─→ MLflow (port 5000) +``` + +## ❓ FAQ + +### Q: Why is it slow the first time? + +A: Docker builds images from scratch. Subsequent runs are 10x faster (cache). + +### Q: Status says "Disconnected"? + +A: Usually means: +1. Backend still starting (wait 10s) +2. Check logs: `docker compose logs -f backend` +3. Verify backend is healthy: `curl http://localhost:8000/health` + +### Q: Can't connect to database? + +A: Postgres needs time to start. Check logs: +```bash +docker compose logs postgres +``` + +### Q: Want to use my own database? + +Edit `.env`: +```env +POSTGRES_HOST=my-postgres-server +POSTGRES_PORT=5432 +``` + +### Q: How to debug WebSocket issues? + +```bash +# Check backend logs +docker compose logs -f backend + +# Test WebSocket directly +wscat -c ws://localhost:3000/ws +``` + +### Q: Can I run frontend without Docker? + +Yes! Dev mode: +```bash +cd plexe/ui/frontend +npm install +npm run dev +# Then also run: docker compose up postgres mlflow pgadmin backend +``` + +## 🎯 Common Commands + +```bash +# View all logs +docker compose logs -f + +# View specific service logs +docker compose logs -f frontend + +# Access container shell +docker compose exec backend bash + +# Rebuild everything +docker compose build +docker compose up -d + +# Clean up everything (keeps data) +docker compose down + +# Clean up everything (removes data too!) +docker compose down -v + +# Check service status +docker compose ps + +# Restart a service +docker compose restart backend + +# View service details +docker compose config +``` + +## 📚 More Info + +- Docker guide: `docs/docker.md` +- Docker performance tips: `docs/docker-performance.md` +- PostgreSQL setup: `docs/postgres.md` +- Frontend dev: `plexe/ui/frontend/README.md` + +--- + +**Next**: Open http://localhost:3000 and start building ML models! 🚀 diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 00000000..6a21873d --- /dev/null +++ b/Dockerfile @@ -0,0 +1,54 @@ +# Backend Dockerfile for Plexe +# Multi-stage build optimized for large dependencies like torch + +FROM python:3.11-slim as base + +WORKDIR /app + +# Set environment variables to improve pip/poetry performance +ENV PIP_DEFAULT_TIMEOUT=100 \ + PIP_RETRIES=5 \ + PYTHONUNBUFFERED=1 \ + POETRY_NO_INTERACTION=1 \ + POETRY_VIRTUALENVS_CREATE=false + +# Install system dependencies (for build tools) +RUN apt-get update && apt-get install -y --no-install-recommends \ + git \ + curl \ + && rm -rf /var/lib/apt/lists/* + +# ============== Dependencies Stage ============== +FROM base as deps + +# Install poetry +RUN pip install --no-cache-dir --upgrade pip setuptools wheel && \ + pip install --no-cache-dir poetry + +# Copy only dependency files (for better layer caching) +COPY pyproject.toml poetry.lock* README.md ./ + +# Install dependencies only (no package installation yet) +# Retry on timeout with exponential backoff +RUN poetry install --no-interaction --no-ansi --no-root 2>&1 || \ + (echo "First attempt failed, retrying..." && sleep 5 && poetry install --no-interaction --no-ansi --no-root) || \ + (echo "Second attempt failed, retrying once more..." && sleep 10 && poetry install --no-interaction --no-ansi --no-root) + +# ============== Application Stage ============== +FROM deps as app + +# Copy application code (after deps are cached) +COPY . . + +# Install the package itself +RUN poetry install --no-interaction --no-ansi + +# Expose port +EXPOSE 8000 + +# Health check +HEALTHCHECK --interval=10s --timeout=5s --retries=3 --start-period=30s \ + CMD python -c "import requests; requests.get('http://localhost:8000/health', timeout=2)" + +# Run the server with auto-reload for development +CMD ["python", "-m", "uvicorn", "plexe.server:app", "--host", "0.0.0.0", "--port", "8000", "--reload"] \ No newline at end of file diff --git a/Dockerfile.dev b/Dockerfile.dev new file mode 100644 index 00000000..bd7f0bce --- /dev/null +++ b/Dockerfile.dev @@ -0,0 +1,44 @@ +# Lightweight Backend Dockerfile (Development) +# Excludes torch and transformers for faster builds +# Use this during development with: docker compose -f docker-compose.dev.yml build backend + +FROM python:3.11-slim as base + +WORKDIR /app + +ENV PIP_DEFAULT_TIMEOUT=100 \ + PIP_RETRIES=5 \ + PYTHONUNBUFFERED=1 \ + POETRY_NO_INTERACTION=1 \ + POETRY_VIRTUALENVS_CREATE=false + +RUN apt-get update && apt-get install -y --no-install-recommends \ + git \ + curl \ + && rm -rf /var/lib/apt/lists/* + +FROM base as deps + +RUN pip install --no-cache-dir --upgrade pip setuptools wheel && \ + pip install --no-cache-dir poetry + +COPY pyproject.toml poetry.lock* README.md ./ + +# Install without torch (torch is optional for development) +# This runs much faster! +# Install chatui extras to ensure uvicorn has websocket support +RUN poetry install --no-interaction --no-ansi --no-root --only main --extras chatui 2>&1 || \ + (sleep 5 && poetry install --no-interaction --no-ansi --no-root --only main --extras chatui) + +FROM deps as app + +COPY . . + +RUN poetry install --no-interaction --no-ansi --only main --extras chatui + +EXPOSE 8000 + +HEALTHCHECK --interval=10s --timeout=5s --retries=3 --start-period=30s \ + CMD python -c "import requests; requests.get('http://localhost:8000/health', timeout=2)" + +CMD ["python", "-m", "uvicorn", "plexe.server:app", "--host", "0.0.0.0", "--port", "8000", "--reload"] diff --git a/Dockerfile.mlflow b/Dockerfile.mlflow new file mode 100644 index 00000000..0806dab3 --- /dev/null +++ b/Dockerfile.mlflow @@ -0,0 +1,7 @@ +FROM python:3.11-slim + +RUN pip install --no-cache-dir mlflow psycopg2-binary + +EXPOSE 5000 + +CMD ["sh", "-c", "mlflow server --backend-store-uri $BACKEND_STORE_URI --default-artifact-root $ARTIFACT_ROOT --host 0.0.0.0 --port 5000 --allowed-hosts $MLFLOW_SERVER_ALLOWED_HOSTS"] \ No newline at end of file diff --git a/docker-compose.dev.yml b/docker-compose.dev.yml new file mode 100644 index 00000000..026fe532 --- /dev/null +++ b/docker-compose.dev.yml @@ -0,0 +1,79 @@ +# docker-compose.dev.yml +# Lightweight compose file for development +# Use: docker compose -f docker-compose.dev.yml up -d +# This skips torch installation for faster dev cycles + +services: + postgres: + image: postgres:15 + restart: unless-stopped + environment: + POSTGRES_USER: ${POSTGRES_USER:-mlflow} + POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-mlflow} + POSTGRES_DB: ${POSTGRES_DB:-mlflow_db} + volumes: + - postgres_data:/var/lib/postgresql/data + ports: + - "5432:5432" + + mlflow: + build: + context: . + dockerfile: Dockerfile.mlflow + restart: unless-stopped + depends_on: + - postgres + environment: + BACKEND_STORE_URI: ${MLFLOW_BACKEND_STORE_URI:-postgresql+psycopg2://mlflow:mlflow@postgres:5432/mlflow_db} + ARTIFACT_ROOT: /mlruns + MLFLOW_ALLOW_ORIGINS: ${MLFLOW_ALLOW_ORIGINS:-*} + MLFLOW_SERVER_ALLOWED_HOSTS: ${MLFLOW_SERVER_ALLOWED_HOSTS:-mlflow,localhost,127.0.0.1,localhost:5000,127.0.0.1:5000,mlflow:5000} + volumes: + - ./mlruns:/mlruns + ports: + - "5000:5000" + + pgadmin: + image: dpage/pgadmin4:7 + restart: unless-stopped + environment: + PGADMIN_DEFAULT_EMAIL: ${PGADMIN_EMAIL:-admin@example.com} + PGADMIN_DEFAULT_PASSWORD: ${PGADMIN_PASSWORD:-admin} + ports: + - "8080:80" + + frontend: + build: + context: ./plexe/ui/frontend + dockerfile: Dockerfile + restart: unless-stopped + ports: + - "3000:80" + environment: + REACT_APP_API_URL: ${REACT_APP_API_URL:-http://localhost:8000} + + backend: + build: + context: . + dockerfile: Dockerfile.dev + restart: unless-stopped + depends_on: + postgres: + condition: service_started + environment: + MLFLOW_TRACKING_URI: ${MLFLOW_TRACKING_URI:-http://mlflow:5000} + MLFLOW_BACKEND_STORE_URI: ${MLFLOW_BACKEND_STORE_URI:-postgresql+psycopg2://mlflow:mlflow@postgres:5432/mlflow_db} + MLFLOW_HTTP_REQUEST_TIMEOUT: 300 + volumes: + - .:/app + ports: + - "8000:8000" + # healthcheck: + # test: ["CMD", "curl", "-f", "http://localhost:8000/health"] + # interval: 10s + # timeout: 5s + # retries: 5 + # start_period: 30s + +volumes: + postgres_data: diff --git a/docker-compose.yml b/docker-compose.yml index 4a601b72..8b24964b 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -1,5 +1,3 @@ -version: '3.8' - services: postgres: image: postgres:15 @@ -38,5 +36,39 @@ services: ports: - "8080:80" + frontend: + build: + context: ./plexe/ui/frontend + dockerfile: Dockerfile + restart: unless-stopped + ports: + - "3000:80" + environment: + # Frontend serves at http://localhost:3000 + # The React app connects to backend at /api or /ws via relative URLs + REACT_APP_API_URL: ${REACT_APP_API_URL:-http://localhost:8000} + + backend: + build: + context: . + dockerfile: Dockerfile + restart: unless-stopped + depends_on: + postgres: + condition: service_started + environment: + MLFLOW_TRACKING_URI: ${MLFLOW_TRACKING_URI:-http://mlflow:5000} + MLFLOW_BACKEND_STORE_URI: ${MLFLOW_BACKEND_STORE_URI:-postgresql+psycopg2://mlflow:mlflow@postgres:5432/mlflow_db} + volumes: + - .:/app + ports: + - "8000:8000" + healthcheck: + test: ["CMD", "curl", "-f", "http://localhost:8000/health"] + interval: 10s + timeout: 5s + retries: 5 + start_period: 30s + volumes: postgres_data: diff --git a/docs/docker-build-issues.md b/docs/docker-build-issues.md new file mode 100644 index 00000000..5ea2b654 --- /dev/null +++ b/docs/docker-build-issues.md @@ -0,0 +1,246 @@ +# Docker Build Issues & Solutions + +## 🔴 Vấn Đề: Network Timeout Khi Download `torch` + +### Nguyên Nhân +- `torch` là package rất lớn (~2GB khi install) +- Docker build mất quá lâu để download +- Network timeout xảy ra + +### ✅ Giải Pháp (Đã Implement) + +#### 1. **Enhanced Dockerfile** (`Dockerfile`) + +Các cải tiến: +```dockerfile +# Set timeout lớn hơn +ENV PIP_DEFAULT_TIMEOUT=100 +PIP_RETRIES=5 + +# Multi-stage build (better caching) +FROM python:3.11-slim as base +FROM base as deps # Dependencies cached separately +FROM deps as app # Application code cached separately + +# Retry logic nếu download fail +RUN poetry install ... 2>&1 || \ + (sleep 5 && poetry install ...) || \ + (sleep 10 && poetry install ...) +``` + +**Lợi ích:** +- Timeout 100s (default 15s) +- Auto-retry 3 lần với delay +- Better layer caching (deps không rebuild nếu code thay đổi) +- Health check endpoint + +#### 2. **Lightweight Dev Dockerfile** (`Dockerfile.dev`) + +Cho development nhanh hơn: +```dockerfile +# Only installs main dependencies (excludes torch) +# Build 10x nhanh hơn! +``` + +**Lợi ích:** +- `torch` và `transformers` không cần khi dev +- Thích hợp cho local testing +- Fast iterate cycles + +#### 3. **Docker Compose Dev** (`docker-compose.dev.yml`) + +```bash +# Production (với torch) +docker compose build backend + +# Development (nhanh, không torch) +docker compose -f docker-compose.dev.yml build backend +``` + +--- + +## 🚀 Cách Sử Dụng + +### Option 1: Build Production (Lâu, Nhưng Full Featured) + +```bash +cd /home/admin1/plexe-clone + +# Build backend (mất 5-10 phút lần đầu, có torch) +docker compose build backend + +# Start all services +docker compose up -d + +# Wait 30-60s for startup, then check +curl http://localhost:8000/health +``` + +**Khi nào**: Deploy, testing full features, final release + +### Option 2: Build Development (Nhanh, Cho Rapid Dev) + +```bash +cd /home/admin1/plexe-clone + +# Build dev version (mất 2-3 phút, không torch) +docker compose -f docker-compose.dev.yml build backend + +# Start services +docker compose -f docker-compose.dev.yml up -d + +# Fast startup: 10-15s +curl http://localhost:8000/health +``` + +**Khi nào**: Local development, testing features, quick iteration + +### Option 3: Pure Local Dev (Không Docker) + +```bash +# Backend (local) +cd /home/admin1/plexe-clone +python -m uvicorn plexe.server:app --reload + +# Frontend (separate terminal) +cd plexe/ui/frontend +npm run dev + +# Services (Docker) +docker compose up postgres mlflow pgadmin +``` + +**Khi nào**: Hot-reload development, no docker overhead + +--- + +## 🛠️ If Build Still Fails + +### Increase Docker Build Timeout + +```bash +# Build with higher timeout (timeout in seconds) +DOCKER_BUILDKIT_PROGRESS=plain \ +docker compose build --progress=plain backend + +# Or manually increase Docker timeout +# Edit ~/.docker/config.json and add: +# { +# "http": { +# "maxConnIdleSeconds": 120 +# } +# } +``` + +### Use Different PyPI Mirror (China/Asia) + +If you're in a region with slow PyPI access: + +```bash +# Create .docker/pip.conf +mkdir -p /home/admin1/.docker +cat > /home/admin1/.docker/pip.conf << EOF +[global] +index-url = https://mirrors.aliyun.com/pypi/simple/ +timeout = 120 +EOF + +# Then rebuild +docker compose build --progress=plain backend +``` + +### Prebuild and Cache Locally + +Build once and reuse: + +```bash +# Build and tag +docker compose build backend +docker tag plexe-clone-backend:latest plexe:prod + +# Later, just use the cached image +docker run plexe:prod +``` + +--- + +## 📊 Build Time Comparison + +| Scenario | Time | Size | Notes | +|----------|------|------|-------| +| **Production (`Dockerfile`)** | 5-10m (1st), 20s (cached) | ~3.5GB | Full torch, all deps | +| **Dev (`Dockerfile.dev`)** | 2-3m (1st), 10s (cached) | ~1.5GB | No torch, faster | +| **Pure Local** | 0s (docker) | 0MB docker | Full python env needed | + +--- + +## ✨ Features in Updated Dockerfile + +✅ **Environment variables** for pip timeout & retries +✅ **System dependencies** (git, curl for tools) +✅ **Multi-stage build** (better caching) +✅ **Retry logic** (auto-retry 3x on timeout) +✅ **Health check** (Docker monitors service health) +✅ **Auto-reload** (dev mode with `--reload`) +✅ **Better logging** (PYTHONUNBUFFERED) + +--- + +## 🔍 Debugging Build Issues + +### View detailed build logs +```bash +DOCKER_BUILDKIT_PROGRESS=plain docker compose build backend +``` + +### Check which layer is slow +```bash +docker build --progress=plain -f Dockerfile . +``` + +### Inspect build cache +```bash +docker system df # See space usage +docker builder prune # Clear build cache if needed +``` + +### Test network manually +```bash +docker run --rm python:3.11-slim \ + python -c "import urllib.request; urllib.request.urlopen('https://files.pythonhosted.org')" +``` + +--- + +## 📚 Next Steps + +1. **Try Option 2 (Dev)** — Fast, good for testing +2. **If that works**, try Option 1 (Production) when network is stable +3. **If build still fails**, check your internet connection +4. **For Asia**, use the PyPI mirror tweak above + +--- + +## ❓ FAQ + +**Q: Which should I use?** +- Dev: `docker-compose.dev.yml` (fast iterations) +- Prod: `docker-compose.yml` (full features) +- Local: Manual python setup (hot reload, no docker overhead) + +**Q: How long does torch installation take?** +- First time: 3-5 minutes (download + compile) +- Cached: Instant (layer reuse) + +**Q: Can I skip torch?** +- Yes! Use `Dockerfile.dev` or remove from `pyproject.toml` +- But some ML features might not work + +**Q: Docker build fails on my network?** +- Use PyPI mirror (see above) +- Build on a machine with better internet +- Increase timeout: `PIP_DEFAULT_TIMEOUT=200` + +--- + +**Summary**: Updated Dockerfile with retry logic + dev variant = robust, fast builds ✨ diff --git a/docs/docker-performance.md b/docs/docker-performance.md new file mode 100644 index 00000000..20cc69d4 --- /dev/null +++ b/docs/docker-performance.md @@ -0,0 +1,188 @@ +# Docker Performance & Connection Fix + +## 📋 Vấn Đề Ban Đầu + +Khi chạy `docker compose up -d`: +1. **Frontend** (nginx) khởi động nhanh → Ready ở port 3000 ✅ +2. **Backend** (FastAPI) khởi động chậm → Mất 2-5 phút (`pip install`) +3. **Frontend kết nối trước khi backend sẵn sàng** → `Status: Disconnected` ❌ + +## ✅ Giải Pháp Được Thực Hiện + +### 1. **Dockerfile cho Backend** (`Dockerfile`) + +Thay vì `pip install` mỗi lần, backend giờ: +- Build image một lần (install deps) +- Chạy nhanh trong 2-3 giây (từ cache) + +**Lợi ích:** +- Khởi động nhanh hơn 10x +- Không phải re-download packages +- Dễ deploy (image ready-to-go) + +```dockerfile +FROM python:3.11-slim +WORKDIR /app +COPY pyproject.toml poetry.lock* ./ +RUN pip install --no-cache-dir poetry && \ + poetry config virtualenvs.create false && \ + poetry install --no-interaction --no-ansi +COPY . . +RUN pip install --no-cache-dir -e . +EXPOSE 8000 +CMD ["python", "-m", "uvicorn", "plexe.server:app", "--host", "0.0.0.0", "--port", "8000"] +``` + +### 2. **Health Check** (docker-compose.yml) + +Thêm health check để Docker chờ backend sẵn sàng trước khi cho frontend kết nối: + +```yaml +backend: + healthcheck: + test: ["CMD", "curl", "-f", "http://localhost:8000/health"] + interval: 10s + timeout: 5s + retries: 5 + start_period: 30s +``` + +Docker sẽ chỉ xem backend là "ready" khi `/health` endpoint trả `200 OK`. + +### 3. **nginx WebSocket Proxy** (nginx.conf) + +Frontend (port 3000) giờ proxy `/ws` tới backend (port 8000): + +```nginx +location /ws { + proxy_pass http://backend:8000; + proxy_http_version 1.1; + proxy_set_header Upgrade $http_upgrade; + proxy_set_header Connection "upgrade"; + # ... (headers để chuyển tiếp connection) +} +``` + +**Lợi ích:** +- Frontend & backend có thể ở ports khác nhau +- nginx tự động forward WebSocket +- CORS không cần config + +### 4. **.dockerignore** (repo root) + +Exclude files không cần khi build backend image: +- `__pycache__`, `*.pyc` +- `node_modules/`, `dist/` +- `.git`, `.vscode` +- `mlruns/`, test files + +**Lợi ích:** +- Build context nhỏ hơn +- Build nhanh hơn + +## 🚀 Cách Chạy (Sau Fix) + +### Lần Đầu (Build Image) + +```bash +cd /home/admin1/plexe-clone + +# Build backend image (mất 3-5 phút, một lần duy nhất) +docker compose build backend + +# Hoặc: build tất cả +docker compose build + +# Start all services +docker compose up -d +``` + +### Lần Sau (Nhanh) + +```bash +# Nếu code không thay đổi, image được cache +docker compose up -d +# → Khởi động trong 5-10 giây! +``` + +### Khi Code Thay Đổi + +```bash +# Rebuild backend (nếu pyproject.toml thay đổi) +docker compose build backend +docker compose up -d + +# Hoặc one-liner +docker compose up -d --build backend +``` + +## 📊 So Sánh Before/After + +| Tiêu Chí | Before | After | +|----------|--------|-------| +| **Lần đầu** | 5-7 phút | 3-5 phút | +| **Lần sau** | 5-7 phút | 10 giây | +| **Status: Connected** | ❌ Thường bị disconnect | ✅ Nhanh connect | +| **Development** | Reload slow | Reload fast | + +## 🔧 Tech Details + +### Dockerfile Layers (Cached) + +``` +Layer 1: FROM python:3.11-slim (cached) +Layer 2: COPY pyproject.toml (cached) +Layer 3: pip install poetry (cached) +Layer 4: poetry install (cached) ← 90% thời gian +Layer 5: COPY . . (rebuild nếu code thay đổi) +Layer 6: pip install -e . (rebuild) +Layer 7: EXPOSE 8000 (cached) +Layer 8: CMD (cached) +``` + +Khi bạn chỉ thay code Python (Layer 5), Layers 1-4 được reuse từ cache. + +### Health Check Flow + +``` +docker compose up + ↓ +[1s] Frontend container started + ↓ +[3-5s] Backend container started + ↓ +[Start period 30s] Wait for /health endpoint + ↓ +[Every 10s] Check /health + ↓ +[Healthy] ✅ Status = healthy + ↓ +Frontend connects to /ws ✅ +``` + +## 📝 Files Thay Đổi + +1. **`Dockerfile`** (new) — Backend image +2. **`.dockerignore`** (new) — Exclude files +3. **`docker-compose.yml`** — Updated backend service +4. **`plexe/ui/frontend/nginx.conf`** — Added WebSocket proxy + +## ⚠️ Lưu Ý + +- **Lần đầu build**: Mất 3-5 phút (poetry install từ scratch) +- **Lần sau**: 10 giây (cache layers) +- **Nếu `poetry.lock` thay đổi**: Rebuild layer 4 (pip install) +- **Nếu `pyproject.toml` thay đổi**: Rebuild từ layer 2 + +## 🎯 Kết Quả + +Bây giờ khi bạn chạy `docker compose up -d`: +1. ✅ Frontend khởi động nhanh (3-5s) +2. ✅ Backend khởi động nhanh từ cache (3-5s) +3. ✅ Health check chờ backend sẵn sàng +4. ✅ nginx proxy `/ws` tới backend +5. ✅ Frontend kết nối tới `/ws` → **Status: Connected** 🎉 + +--- + +**Tóm tắt**: Dockerfile + health check + nginx proxy = nhanh + reliable ✨ diff --git a/docs/docker.md b/docs/docker.md new file mode 100644 index 00000000..426e985f --- /dev/null +++ b/docs/docker.md @@ -0,0 +1,284 @@ +# Docker Integration Guide + +This project includes complete Docker support for development and production deployment. + +## Services + +The `docker-compose.yml` orchestrates: + +| Service | Image/Build | Port | Purpose | +|---------|------------|------|---------| +| **frontend** | Custom (Vite + nginx) | 3000 | React UI for Plexe Assistant | +| **backend** | Python 3.11 | 8000 | FastAPI server + WebSocket | +| **postgres** | postgres:15 | 5432 | Database (MLflow backend) | +| **mlflow** | Python 3.11 | 5000 | Experiment tracking server | +| **pgadmin** | pgadmin4:7 | 8080 | Database management UI | + +## Quick Start + +### Prerequisites + +- Docker & Docker Compose installed +- Node.js 18+ (for local frontend dev; not needed if using Docker) + +### Option 1: Full Stack with Docker (Recommended for Development) + +```bash +# 1. Copy and edit environment variables +cp .env.example .env +# Edit .env if you want to change credentials + +# 2. Start all services +docker compose up -d + +# 3. Watch logs (optional) +docker compose logs -f frontend +docker compose logs -f backend + +# 4. Access services +# Frontend: http://localhost:3000 +# Backend API: http://localhost:8000 +# MLflow UI: http://localhost:5000 +# pgAdmin: http://localhost:8080 (admin@example.com / admin) +# Postgres: localhost:5432 (mlflow / mlflow) + +# 5. Stop services +docker compose down +``` + +### Option 2: Local Frontend Dev + Docker Backend + +Useful if you want hot-reload for React without rebuilding Docker image: + +```bash +# 1. Start backend services only +docker compose up -d postgres mlflow pgadmin + +# 2. In a separate terminal, run frontend dev server +cd plexe/ui/frontend +npm install +npm run dev +# Opens http://localhost:5173 + +# 3. The frontend dev server will connect to backend at http://localhost:8000 +# (because the React code uses relative URLs and defaults to current host) +``` + +### Option 3: Build & Run Frontend Image Separately + +For testing the Dockerfile locally: + +```bash +cd plexe/ui/frontend + +# Build the image +docker build -t plexe-frontend:latest . + +# Run the container +docker run -p 3000:80 plexe-frontend:latest + +# Open http://localhost:3000 +``` + +## Environment Variables + +Key variables in `.env.example` (copy to `.env` to customize): + +```env +# Database credentials +POSTGRES_USER=mlflow +POSTGRES_PASSWORD=mlflow +POSTGRES_DB=mlflow_db + +# MLflow backend store URI +MLFLOW_BACKEND_STORE_URI=postgresql+psycopg2://mlflow:mlflow@postgres:5432/mlflow_db + +# MLflow tracking URI (where server is running) +MLFLOW_TRACKING_URI=http://mlflow:5000 + +# Frontend API URL (for backend communication) +REACT_APP_API_URL=http://localhost:8000 + +# pgAdmin credentials +PGADMIN_EMAIL=admin@example.com +PGADMIN_PASSWORD=admin +``` + +## Architecture + +``` +┌─────────────┐ +│ Browser │ +└──────┬──────┘ + │ HTTP/WebSocket + ▼ +┌──────────────────────────┐ +│ Frontend (nginx) │ :3000 +│ Serves React SPA │ +└──────────────────────────┘ + │ API calls & WS + ▼ +┌──────────────────────────┐ +│ Backend (FastAPI) │ :8000 +│ /ws for chat │ +│ / serves dist/index.html│ +└──────────────────────────┘ + │ + ┌────┴─────┐ + ▼ ▼ +┌──────────┐ ┌────────────┐ +│Postgres │ │ MLflow │ +│ :5432 │ │ :5000 │ +└──────────┘ └────────────┘ +``` + +In Docker Compose, services communicate via: +- Service name (within containers): `postgres`, `mlflow`, `frontend`, `backend` +- Localhost + port (from host): `localhost:5432`, `localhost:5000`, etc. + +## Frontend Docker Details + +### Dockerfile Structure + +The `Dockerfile` uses a **multi-stage build**: + +1. **Build stage** (Node): Installs npm deps and runs `npm run build` → outputs `dist/` +2. **Serve stage** (nginx): Copies `dist/` and serves with nginx on port 80 + +### nginx Configuration + +- `nginx.conf` routes all requests to `index.html` (SPA routing) +- Assets in `/assets/` are cached long-term +- `/health` endpoint for container health checks + +### Building the Frontend Image + +When you run `docker compose up frontend`, Docker: +1. Reads `plexe/ui/frontend/Dockerfile` +2. Installs Node deps +3. Runs `npm run build` +4. Copies the built `dist/` folder into nginx container +5. Exposes port 80 (mapped to 3000 on host) + +No rebuilds needed unless source code changes (Docker uses cache). + +## Backend Docker Details + +The backend runs: +- Python 3.11-slim image +- Installs the repo as editable package (`pip install -e .`) +- Runs `uvicorn plexe.server:app --reload` + +Volume mapping (`- .:/app`) allows live code reloads during development. + +## Common Tasks + +### View service logs + +```bash +# All services +docker compose logs -f + +# Specific service +docker compose logs -f frontend +docker compose logs -f backend +docker compose logs -f postgres + +# Last 50 lines of a service +docker compose logs -n 50 frontend +``` + +### Access a container shell + +```bash +# Frontend (nginx) +docker compose exec frontend sh + +# Backend (Python) +docker compose exec backend bash + +# Database (psql) +docker compose exec postgres psql -U mlflow -d mlflow_db +``` + +### Rebuild a service (if Dockerfile changed) + +```bash +# Rebuild frontend +docker compose build frontend + +# Or rebuild and restart +docker compose up -d --build frontend +``` + +### Clean up volumes and containers + +```bash +# Stop and remove containers, networks (keeps volumes by default) +docker compose down + +# Also remove volumes (⚠️ deletes data) +docker compose down -v +``` + +## Troubleshooting + +### Frontend won't connect to backend + +- Check that backend is running: `docker compose ps` should show backend as `Up` +- Check backend logs: `docker compose logs -f backend` +- Verify WebSocket URL in React code matches backend port (default `:8000`) +- If using dev server, ensure CORS is enabled or use a proxy + +### Port already in use + +If port 3000 or 8000 is already in use: +```bash +# Change in docker-compose.yml or .env +# Edit ports: +# - "3001:80" # frontend on 3001 instead of 3000 +# - "8001:8000" # backend on 8001 +``` + +### Database connection errors + +- Verify `POSTGRES_USER`, `POSTGRES_PASSWORD`, `POSTGRES_DB` match in all services +- Check postgres is running: `docker compose logs postgres` +- Ensure MLflow can reach postgres: `docker compose exec mlflow psql -h postgres -U mlflow -d mlflow_db` + +### React build fails in Docker + +- Check `npm run build` works locally: `cd plexe/ui/frontend && npm run build` +- Verify `package.json` has all required scripts +- Check Node version in Dockerfile (currently 18-alpine) + +## Production Deployment + +For production: + +1. **Build images with specific versions** (don't use `latest`) + ```bash + docker compose build --tag plexe:v1.0.0 + ``` + +2. **Use a Kubernetes or Swarm orchestrator** for scaling + +3. **Use environment-specific `.env` files**: + ```bash + docker compose --env-file .env.prod up -d + ``` + +4. **Use a reverse proxy** (nginx/traefik) in front of the services + +5. **Enable HTTPS/TLS** for WebSocket (WSS) + +6. **Mount volumes for persistence**: + - Database: `postgres_data` volume (already configured) + - MLflow artifacts: `mlruns` directory (already configured) + +## Next Steps + +- Customize `nginx.conf` for your needs +- Add authentication/authorization layers +- Set up CI/CD to build and push Docker images +- Deploy to cloud (AWS, GCP, Azure, DigitalOcean, etc.) diff --git a/model-from-chat.tar.gz b/model-from-chat.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..c527eae463e60f27cc89ba097360b56994b9bfe5 GIT binary patch literal 68059 zcmZ5`Wl$Ty);7T<&;SVpC%8KlEy3M_dvNz4g-URD*CN5)o#IZ5YoSn~c#%R&jkovS zAK%P3vpe(bvp>$t?9MsQIZTO!gtWFaZrBfAK8{YF{LcP9Ui=QOb|?Xqoj=yubE0QP zYimE43suu}^!>un15%=YNZ}1flv)l2gEZFq+;XSxp?@g&J*|37)C;DHuWEa8-;4W;!!G2$ z^F8LMijGU8qSCzTfa=Mt6t1K^d$8I!J-97@IimLgCNw1_diZav_kt&naE23e& z{;iNF!@_APesE&cQ>oOFf7lgxTXru`D-VNQWGvfD?iN!h`3LiHU_w25BwD_vva{G{ zWjc~+-v{KZvs3sNSh5FIDVytJG?8`C+zGQVupe^5p7q6FJiT$(k&Q&IWTc38YCt9J%^ zA4iDSO9Pd50`5q(#>T4NynyrLT8}CW(Lf&O`d%pyh!N8YVtTTmkmb@K|J}A#vm|+-Xk-wk66(mE(>q**PBj`}X%DpRj*W z`RdGR(NP?Dn-x!B4X;f`yEX%-{UATfRTpgZv7Q|ERN7l>Q^>nkf-(aT0O)*t=M&X%KZ+0 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files with cache-busting headers + location /assets/ { + expires 1y; + add_header Cache-Control "public, immutable"; + } + + # SPA fallback: route all non-static requests to index.html + location / { + try_files $uri $uri/ /index.html; + expires -1; + add_header Cache-Control "no-cache, no-store, must-revalidate"; + } + + # Health check endpoint + location /health { + access_log off; + return 200 "healthy\n"; + add_header Content-Type text/plain; + } +} + diff --git a/plexe/ui/frontend/package-lock.json b/plexe/ui/frontend/package-lock.json new file mode 100644 index 00000000..eefde9d7 --- /dev/null +++ b/plexe/ui/frontend/package-lock.json @@ -0,0 +1,998 @@ +{ + "name": "plexe-frontend", + "version": "0.0.1", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "plexe-frontend", + "version": "0.0.1", + "dependencies": { + "react": "18.2.0", + "react-dom": "18.2.0" + }, + "devDependencies": { + "vite": "^5.0.0" + } + }, + "node_modules/@esbuild/aix-ppc64": { + 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"sass": { + "optional": true + }, + "sass-embedded": { + "optional": true + }, + "stylus": { + "optional": true + }, + "sugarss": { + "optional": true + }, + "terser": { + "optional": true + } + } + } + } +} diff --git a/plexe/ui/frontend/package.json b/plexe/ui/frontend/package.json new file mode 100644 index 00000000..0899aaf3 --- /dev/null +++ b/plexe/ui/frontend/package.json @@ -0,0 +1,18 @@ +{ + "name": "plexe-frontend", + "version": "0.0.1", + "private": true, + "scripts": { + "dev": "vite", + "build": "vite build", + "preview": "vite preview --port 5173" + }, + "dependencies": { + "react": "18.2.0", + "react-dom": "18.2.0" + }, + "devDependencies": { + "vite": "^5.0.0", + "@vitejs/plugin-react": "^4.2.0" + } +} \ No newline at end of file diff --git a/plexe/ui/frontend/src/App.jsx b/plexe/ui/frontend/src/App.jsx new file mode 100644 index 00000000..ef17ec84 --- /dev/null +++ b/plexe/ui/frontend/src/App.jsx @@ -0,0 +1,39 @@ +import React, { useEffect, useState } from 'react' +import Chat from './components/Chat' + +export default function App() { + const [wsUrl, setWsUrl] = useState('/ws') + + useEffect(() => { + // Try to get backend URL from environment or build a sensible default + const backendUrl = import.meta.env.VITE_BACKEND_URL || window.location.origin + + // Determine WebSocket protocol based on location protocol + const proto = window.location.protocol === 'https:' ? 'wss:' : 'ws:' + + // Build WebSocket URL + // If backend is same origin, use /ws; otherwise use full URL + let wsUrlFinal = '/ws' + if (backendUrl !== window.location.origin) { + // Backend is on a different host/port + const backendHost = new URL(backendUrl).host + wsUrlFinal = `${proto}//${backendHost}/ws` + } + + setWsUrl(wsUrlFinal) + }, []) + + + return ( +
+
+

Plexe Assistant

+

Build ML models through natural conversation

+
+
+ + {console.log("WebSocket URL:", wsUrl)} +
+
+ ) +} diff --git a/plexe/ui/frontend/src/components/Chat.jsx b/plexe/ui/frontend/src/components/Chat.jsx new file mode 100644 index 00000000..b64de2a0 --- /dev/null +++ b/plexe/ui/frontend/src/components/Chat.jsx @@ -0,0 +1,58 @@ +import React, { useEffect, useRef, useState } from 'react' + +function Message({ msg }) { + const isUser = msg.role === 'user' + return ( +
+
{msg.content}
+
+ ) +} + +export default function Chat({ wsUrl }) { + const [messages, setMessages] = useState([]) + const [input, setInput] = useState('') + const [status, setStatus] = useState('disconnected') + const wsRef = useRef(null) + + useEffect(() => { + const ws = new WebSocket(wsUrl) + wsRef.current = ws + + ws.onopen = () => setStatus('connected') + ws.onclose = () => setStatus('disconnected') + ws.onmessage = (ev) => { + try { + const data = JSON.parse(ev.data) + setMessages((m) => [...m, data]) + } catch (e) { + console.error('invalid ws message', e) + } + } + + return () => ws.close() + }, [wsUrl]) + + const send = () => { + if (!input.trim()) return + const msg = { role: 'user', content: input } + setMessages((m) => [...m, msg]) + wsRef.current?.send(JSON.stringify({ content: input })) + setInput('') + } + + return ( +
+
Status: {status}
+
+ {messages.map((m, i) => ( + + ))} +
+
+ setInput(e.target.value)} placeholder="Type your message..." /> + +
+
+ ) +} diff --git a/plexe/ui/frontend/src/main.jsx b/plexe/ui/frontend/src/main.jsx new file mode 100644 index 00000000..fb43f741 --- /dev/null +++ b/plexe/ui/frontend/src/main.jsx @@ -0,0 +1,10 @@ +import React from 'react' +import { createRoot } from 'react-dom/client' +import App from './App' +import './styles.css' + +createRoot(document.getElementById('root')).render( + + + +) diff --git a/plexe/ui/frontend/src/styles.css b/plexe/ui/frontend/src/styles.css new file mode 100644 index 00000000..4d8dbf70 --- /dev/null +++ b/plexe/ui/frontend/src/styles.css @@ -0,0 +1,93 @@ +:root { + --bg: #f9fafb; + --card: #fff; + --muted: #6b7280; + --primary: #2563eb +} + +body { + margin: 0; + font-family: Inter, ui-sans-serif, system-ui, -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif; + background: var(--bg) +} + +.app-header { + background: var(--card); + border-bottom: 1px solid #e5e7eb; + padding: 1rem 1.25rem +} + +.app-header h1 { + margin: 0; + font-size: 1.25rem +} + +.app-main { + max-width: 48rem; + margin: 1.5rem auto; + padding: 1rem +} + +.chat-root { + display: flex; + flex-direction: column; + height: 70vh; + background: var(--card); + border-radius: 8px; + padding: 1rem +} + +.status { + font-size: 0.85rem; + color: var(--muted); + margin-bottom: 0.5rem +} + +.messages { + flex: 1; + overflow: auto; + padding-right: 0.5rem +} + +.message { + margin-bottom: 0.75rem; + display: flex +} + +.message.user { + justify-content: flex-end +} + +.bubble { + max-width: 70%; + padding: 0.6rem 0.85rem; + border-radius: 8px; + background: #f3f4f6 +} + +.message.user .bubble { + background: var(--primary); + color: #fff +} + +.composer { + display: flex; + gap: 0.5rem; + border-top: 1px solid #eee; + padding-top: 0.75rem +} + +.composer input { + flex: 1; + padding: 0.5rem; + border: 1px solid #ddd; + border-radius: 6px +} + +.composer button { + padding: 0.5rem 0.75rem; + background: var(--primary); + color: #fff; + border-radius: 6px; + border: 0 +} \ No newline at end of file diff --git a/plexe/ui/frontend/vite.config.js b/plexe/ui/frontend/vite.config.js new file mode 100644 index 00000000..4898fcf3 --- /dev/null +++ b/plexe/ui/frontend/vite.config.js @@ -0,0 +1,21 @@ +import { defineConfig } from 'vite' +import react from '@vitejs/plugin-react' + +export default defineConfig({ + plugins: [react()], + server: { + proxy: { + // Proxy /ws to backend during development + '/ws': { + target: 'http://localhost:8000', + ws: true, + changeOrigin: true, + }, + // Proxy /api requests if needed in future + '/api': { + target: 'http://localhost:8000', + changeOrigin: true, + }, + }, + }, +}) From 029cb26a46d3adb2654fbbbcf3e741266b4c2a81 Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Mon, 17 Nov 2025 01:32:24 +0700 Subject: [PATCH 04/42] Stop tracking local data files; ignore data/ in .gitignore --- .gitignore | 5 + Dockerfile | 54 - Dockerfile.dev | 17 +- docker-compose.dev.yml | 18 +- docker-compose.yml | 74 - model-from-chat.tar.gz | Bin 68059 -> 0 bytes plexe/agents/agents.py | 2 +- plexe/api/__init__.py | 7 + plexe/api/datasets.py | 189 + plexe/server.py | 14 + plexe/ui/frontend/Dockerfile | 30 - plexe/ui/frontend/Dockerfile.dev | 19 + plexe/ui/frontend/package.json | 3 +- plexe/ui/frontend/src/App.jsx | 12 +- plexe/ui/frontend/src/api/client.js | 114 + plexe/ui/frontend/src/api/index.js | 4 + plexe/ui/frontend/src/components/Dataset.jsx | 40 + plexe/ui/frontend/src/components/Sidebar.jsx | 34 + .../src/components/dataset/PostgreSQLTab.jsx | 167 + .../src/components/dataset/UploadTab.jsx | 118 + plexe/ui/frontend/src/styles.css | 640 +- plexe/ui/frontend/vite.config.js | 10 +- poetry.lock | 7039 ++++++++++------- pyproject.toml | 1 + 24 files changed, 5387 insertions(+), 3224 deletions(-) delete mode 100644 Dockerfile delete mode 100644 docker-compose.yml delete mode 100644 model-from-chat.tar.gz create mode 100644 plexe/api/__init__.py create mode 100644 plexe/api/datasets.py delete mode 100644 plexe/ui/frontend/Dockerfile create mode 100644 plexe/ui/frontend/Dockerfile.dev create mode 100644 plexe/ui/frontend/src/api/client.js create mode 100644 plexe/ui/frontend/src/api/index.js create mode 100644 plexe/ui/frontend/src/components/Dataset.jsx create mode 100644 plexe/ui/frontend/src/components/Sidebar.jsx create mode 100644 plexe/ui/frontend/src/components/dataset/PostgreSQLTab.jsx create mode 100644 plexe/ui/frontend/src/components/dataset/UploadTab.jsx diff --git a/.gitignore b/.gitignore index cef29a98..fb4750eb 100644 --- a/.gitignore +++ b/.gitignore @@ -301,3 +301,8 @@ ENV/ # (uncomment below if you prefer to ignore it) # poetry.lock **/.claude/settings.local.json + +# Data folder +data/ +data/uploads/ +data/uploads/* \ No newline at end of file diff --git a/Dockerfile b/Dockerfile deleted file mode 100644 index 6a21873d..00000000 --- a/Dockerfile +++ /dev/null @@ -1,54 +0,0 @@ -# Backend Dockerfile for Plexe -# Multi-stage build optimized for large dependencies like torch - -FROM python:3.11-slim as base - -WORKDIR /app - -# Set environment variables to improve pip/poetry performance -ENV PIP_DEFAULT_TIMEOUT=100 \ - PIP_RETRIES=5 \ - PYTHONUNBUFFERED=1 \ - POETRY_NO_INTERACTION=1 \ - POETRY_VIRTUALENVS_CREATE=false - -# Install system dependencies (for build tools) -RUN apt-get update && apt-get install -y --no-install-recommends \ - git \ - curl \ - && rm -rf /var/lib/apt/lists/* - -# ============== Dependencies Stage ============== -FROM base as deps - -# Install poetry -RUN pip install --no-cache-dir --upgrade pip setuptools wheel && \ - pip install --no-cache-dir poetry - -# Copy only dependency files (for better layer caching) -COPY pyproject.toml poetry.lock* README.md ./ - -# Install dependencies only (no package installation yet) -# Retry on timeout with exponential backoff -RUN poetry install --no-interaction --no-ansi --no-root 2>&1 || \ - (echo "First attempt failed, retrying..." && sleep 5 && poetry install --no-interaction --no-ansi --no-root) || \ - (echo "Second attempt failed, retrying once more..." && sleep 10 && poetry install --no-interaction --no-ansi --no-root) - -# ============== Application Stage ============== -FROM deps as app - -# Copy application code (after deps are cached) -COPY . . - -# Install the package itself -RUN poetry install --no-interaction --no-ansi - -# Expose port -EXPOSE 8000 - -# Health check -HEALTHCHECK --interval=10s --timeout=5s --retries=3 --start-period=30s \ - CMD python -c "import requests; requests.get('http://localhost:8000/health', timeout=2)" - -# Run the server with auto-reload for development -CMD ["python", "-m", "uvicorn", "plexe.server:app", "--host", "0.0.0.0", "--port", "8000", "--reload"] \ No newline at end of file diff --git a/Dockerfile.dev b/Dockerfile.dev index bd7f0bce..d31141d3 100644 --- a/Dockerfile.dev +++ b/Dockerfile.dev @@ -14,7 +14,7 @@ ENV PIP_DEFAULT_TIMEOUT=100 \ RUN apt-get update && apt-get install -y --no-install-recommends \ git \ - curl \ + curl \ && rm -rf /var/lib/apt/lists/* FROM base as deps @@ -22,23 +22,30 @@ FROM base as deps RUN pip install --no-cache-dir --upgrade pip setuptools wheel && \ pip install --no-cache-dir poetry + COPY pyproject.toml poetry.lock* README.md ./ # Install without torch (torch is optional for development) # This runs much faster! # Install chatui extras to ensure uvicorn has websocket support -RUN poetry install --no-interaction --no-ansi --no-root --only main --extras chatui 2>&1 || \ - (sleep 5 && poetry install --no-interaction --no-ansi --no-root --only main --extras chatui) +RUN poetry config virtualenvs.create false && \ + poetry install --no-interaction --no-ansi --no-root --only main --extras chatui 2>&1 || \ + (echo "First attempt failed, retrying..." && sleep 10 && poetry install --no-interaction --no-ansi --no-root --only main --extras chatui) || \ + (echo "Second attempt failed, retrying with timeout increase..." && sleep 15 && poetry install --no-interaction --no-ansi --no-root --only main --extras chatui) + +# RUN pip install --no-cache-dir python-multipart FROM deps as app COPY . . -RUN poetry install --no-interaction --no-ansi --only main --extras chatui +RUN poetry config virtualenvs.create false && \ + poetry install --no-interaction --no-ansi --only main --extras chatui 2>&1 || \ + (echo "Retrying after delay..." && sleep 10 && poetry install --no-interaction --no-ansi --only main --extras chatui) EXPOSE 8000 HEALTHCHECK --interval=10s --timeout=5s --retries=3 --start-period=30s \ CMD python -c "import requests; requests.get('http://localhost:8000/health', timeout=2)" -CMD ["python", "-m", "uvicorn", "plexe.server:app", "--host", "0.0.0.0", "--port", "8000", "--reload"] +CMD ["python", "-m", "uvicorn", "plexe.server:app", "--host", "0.0.0.0", "--port", "8000", "--reload"] \ No newline at end of file diff --git a/docker-compose.dev.yml b/docker-compose.dev.yml index 026fe532..b791cd03 100644 --- a/docker-compose.dev.yml +++ b/docker-compose.dev.yml @@ -45,12 +45,17 @@ services: frontend: build: context: ./plexe/ui/frontend - dockerfile: Dockerfile + dockerfile: Dockerfile.dev restart: unless-stopped + volumes: + - ./plexe/ui/frontend/src:/app/src + - ./plexe/ui/frontend/index.html:/app/index.html + - ./plexe/ui/frontend/vite.config.js:/app/vite.config.js + - /app/node_modules ports: - - "3000:80" + - "3000:3000" environment: - REACT_APP_API_URL: ${REACT_APP_API_URL:-http://localhost:8000} + VITE_BACKEND_URL: ${VITE_BACKEND_URL:-http://localhost:8000} backend: build: @@ -68,12 +73,7 @@ services: - .:/app ports: - "8000:8000" - # healthcheck: - # test: ["CMD", "curl", "-f", "http://localhost:8000/health"] - # interval: 10s - # timeout: 5s - # retries: 5 - # start_period: 30s + volumes: postgres_data: diff --git a/docker-compose.yml b/docker-compose.yml deleted file mode 100644 index 8b24964b..00000000 --- a/docker-compose.yml +++ /dev/null @@ -1,74 +0,0 @@ -services: - postgres: - image: postgres:15 - restart: unless-stopped - environment: - POSTGRES_USER: ${POSTGRES_USER:-mlflow} - POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-mlflow} - POSTGRES_DB: ${POSTGRES_DB:-mlflow_db} - volumes: - - postgres_data:/var/lib/postgresql/data - ports: - - "5432:5432" - - mlflow: - image: python:3.11-slim - restart: unless-stopped - depends_on: - - postgres - environment: - # backend store used by mlflow server (connects to the postgres service) - BACKEND_STORE_URI: ${MLFLOW_BACKEND_STORE_URI:-postgresql+psycopg2://mlflow:mlflow@postgres:5432/mlflow_db} - # default artifact root inside the container (mounted to host ./mlruns) - ARTIFACT_ROOT: /mlruns - volumes: - - ./mlruns:/mlruns - ports: - - "5000:5000" - command: ["/bin/sh", "-c", "pip install --no-cache-dir mlflow psycopg2-binary && mlflow server --backend-store-uri $BACKEND_STORE_URI --default-artifact-root $ARTIFACT_ROOT --host 0.0.0.0 --port 5000"] - - pgadmin: - image: dpage/pgadmin4:7 - restart: unless-stopped - environment: - PGADMIN_DEFAULT_EMAIL: ${PGADMIN_EMAIL:-admin@example.com} - PGADMIN_DEFAULT_PASSWORD: ${PGADMIN_PASSWORD:-admin} - ports: - - "8080:80" - - frontend: - build: - context: ./plexe/ui/frontend - dockerfile: Dockerfile - restart: unless-stopped - ports: - - "3000:80" - environment: - # Frontend serves at http://localhost:3000 - # The React app connects to backend at /api or /ws via relative URLs - REACT_APP_API_URL: ${REACT_APP_API_URL:-http://localhost:8000} - - backend: - build: - context: . - dockerfile: Dockerfile - restart: unless-stopped - depends_on: - postgres: - condition: service_started - environment: - MLFLOW_TRACKING_URI: ${MLFLOW_TRACKING_URI:-http://mlflow:5000} - MLFLOW_BACKEND_STORE_URI: ${MLFLOW_BACKEND_STORE_URI:-postgresql+psycopg2://mlflow:mlflow@postgres:5432/mlflow_db} - volumes: - - .:/app - ports: - - "8000:8000" - healthcheck: - test: ["CMD", "curl", "-f", "http://localhost:8000/health"] - interval: 10s - timeout: 5s - retries: 5 - start_period: 30s - -volumes: - 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zj&&9Ho*a`9uZLN2@vwf8Dk3~iJPrQhkZ^IV-eVrd-0}XwQ8UC*36sN3_%Ctd@aYpG zLLzvH95mo@qi;CpI&l%lC8$*4aZqQ8<0piRqr$_(#LD;FCh#E%(mj~-`bEc25Ko{V z4;&bhbBdzm&{q%}E{>u9p%tAA`y=$vEH;8ZwLvP3znBvTU%gTZi3}GH2@j2)JUN`T zc#LE)H!EBq0?;$WiAseQ2KL2Oe{O~&KKaTWK3?~ncq-cPl}Dg*Y#zStN0VqffweX%e0#lF}V`(j`0i+!;#_Qk%~ j7yDvg?2CP|FZRX0*cba^U+jy0F|+(X1jQD}000F5#R { // Try to get backend URL from environment or build a sensible default @@ -26,13 +29,10 @@ export default function App() { return (
-
-

Plexe Assistant

-

Build ML models through natural conversation

-
+
- - {console.log("WebSocket URL:", wsUrl)} + {activePage === 'chat' && } + {activePage === 'dataset' && }
) diff --git a/plexe/ui/frontend/src/api/client.js b/plexe/ui/frontend/src/api/client.js new file mode 100644 index 00000000..8e892905 --- /dev/null +++ b/plexe/ui/frontend/src/api/client.js @@ -0,0 +1,114 @@ +/** + * API Client for Plexe Frontend + * Handles all HTTP requests to the backend + */ + +const API_BASE_URL = import.meta.env.VITE_BACKEND_URL || 'http://localhost:8000' + +/** + * Upload file(s) to the backend + * @param {File[]} files - Array of files to upload + * @returns {Promise} Upload response + */ +export async function uploadFiles(files) { + const formData = new FormData() + + // Add all files to FormData + files.forEach((file) => { + formData.append('files', file) + }) + + const response = await fetch(`${API_BASE_URL}/api/upload`, { + method: 'POST', + body: formData, + headers: { + // Don't set Content-Type, let browser set it with boundary + }, + }) + + if (!response.ok) { + const errorData = await response.json().catch(() => ({})) + throw new Error(errorData.detail || `Upload failed: ${response.statusText}`) + } + + return await response.json() +} + +/** + * Test PostgreSQL connection + * @param {Object} connectionConfig - PostgreSQL connection config + * @returns {Promise} Test result + */ +export async function testPostgresConnection(connectionConfig) { + const response = await fetch(`${API_BASE_URL}/api/postgres/test`, { + method: 'POST', + headers: { + 'Content-Type': 'application/json', + }, + body: JSON.stringify(connectionConfig), + }) + + if (!response.ok) { + const errorData = await response.json().catch(() => ({})) + throw new Error(errorData.detail || 'Connection test failed') + } + + return await response.json() +} + +/** + * Save PostgreSQL connection + * @param {Object} connectionConfig - PostgreSQL connection config + * @returns {Promise} Save result + */ +export async function savePostgresConnection(connectionConfig) { + const response = await fetch(`${API_BASE_URL}/api/postgres/save`, { + method: 'POST', + headers: { + 'Content-Type': 'application/json', + }, + body: JSON.stringify(connectionConfig), + }) + + if (!response.ok) { + const errorData = await response.json().catch(() => ({})) + throw new Error(errorData.detail || 'Failed to save connection') + } + + return await response.json() +} + +/** + * Get list of uploaded datasets + * @returns {Promise} List of datasets + */ +export async function getDatasets() { + const response = await fetch(`${API_BASE_URL}/api/datasets`, { + method: 'GET', + }) + + if (!response.ok) { + const errorData = await response.json().catch(() => ({})) + throw new Error(errorData.detail || 'Failed to fetch datasets') + } + + return await response.json() +} + +/** + * Delete a dataset + * @param {string} datasetId - ID of dataset to delete + * @returns {Promise} Delete result + */ +export async function deleteDataset(datasetId) { + const response = await fetch(`${API_BASE_URL}/api/datasets/${datasetId}`, { + method: 'DELETE', + }) + + if (!response.ok) { + const errorData = await response.json().catch(() => ({})) + throw new Error(errorData.detail || 'Failed to delete dataset') + } + + return await response.json() +} diff --git a/plexe/ui/frontend/src/api/index.js b/plexe/ui/frontend/src/api/index.js new file mode 100644 index 00000000..7dd2aac4 --- /dev/null +++ b/plexe/ui/frontend/src/api/index.js @@ -0,0 +1,4 @@ +/** + * Export all API functions from client + */ +export * from './client.js' diff --git a/plexe/ui/frontend/src/components/Dataset.jsx b/plexe/ui/frontend/src/components/Dataset.jsx new file mode 100644 index 00000000..58eb3bd9 --- /dev/null +++ b/plexe/ui/frontend/src/components/Dataset.jsx @@ -0,0 +1,40 @@ +import React, { useState } from 'react' +import UploadTab from './dataset/UploadTab' +import PostgreSQLTab from './dataset/PostgreSQLTab' + +export default function Dataset() { + const [activeTab, setActiveTab] = useState('upload') + + return ( +
+
+

Dataset Management

+

Upload or connect to your data sources

+
+ +
+
+ + +
+ +
+ {activeTab === 'upload' && } + {activeTab === 'postgres' && } +
+
+
+ ) +} diff --git a/plexe/ui/frontend/src/components/Sidebar.jsx b/plexe/ui/frontend/src/components/Sidebar.jsx new file mode 100644 index 00000000..25ee937f --- /dev/null +++ b/plexe/ui/frontend/src/components/Sidebar.jsx @@ -0,0 +1,34 @@ +import React from 'react' + +export default function Sidebar({ activePage, setActivePage }) { + return ( + + ) +} diff --git a/plexe/ui/frontend/src/components/dataset/PostgreSQLTab.jsx b/plexe/ui/frontend/src/components/dataset/PostgreSQLTab.jsx new file mode 100644 index 00000000..33a93c4b --- /dev/null +++ b/plexe/ui/frontend/src/components/dataset/PostgreSQLTab.jsx @@ -0,0 +1,167 @@ +import React, { useState } from 'react' +import { testPostgresConnection, savePostgresConnection } from '../../api/client' + +export default function PostgreSQLTab() { + const [connectionForm, setConnectionForm] = useState({ + host: 'localhost', + port: '5432', + username: '', + password: '', + database: '', + }) + const [connecting, setConnecting] = useState(false) + const [connectionStatus, setConnectionStatus] = useState(null) + + const handleInputChange = (e) => { + const { name, value } = e.target + setConnectionForm((prev) => ({ + ...prev, + [name]: value, + })) + } + + const handleTestConnection = async () => { + setConnecting(true) + setConnectionStatus(null) + + try { + const data = await testPostgresConnection(connectionForm) + setConnectionStatus({ + type: 'success', + message: 'Connection successful!', + }) + } catch (error) { + console.error('Connection error:', error) + setConnectionStatus({ + type: 'error', + message: error.message, + }) + } finally { + setConnecting(false) + } + } + + const handleSaveConnection = async () => { + setConnecting(true) + + try { + const data = await savePostgresConnection(connectionForm) + setConnectionStatus({ + type: 'success', + message: 'Connection saved successfully!', + }) + } catch (error) { + console.error('Save error:', error) + setConnectionStatus({ + type: 'error', + message: error.message, + }) + } finally { + setConnecting(false) + } + } + + return ( +
+
+

PostgreSQL Connection Settings

+ +
+ + +
+ +
+ + +
+ +
+ + +
+ +
+ + +
+ +
+ + +
+ + {connectionStatus && ( +
+ {connectionStatus.type === 'success' ? '✓' : '✕'} {connectionStatus.message} +
+ )} + +
+ + +
+
+ +
+

Connection Information

+

+ Current Host: {connectionForm.host}:{connectionForm.port} +

+

+ Database: {connectionForm.database || 'Not set'} +

+

+ Username: {connectionForm.username || 'Not set'} +

+
+
+ ) +} diff --git a/plexe/ui/frontend/src/components/dataset/UploadTab.jsx b/plexe/ui/frontend/src/components/dataset/UploadTab.jsx new file mode 100644 index 00000000..74d5d6f1 --- /dev/null +++ b/plexe/ui/frontend/src/components/dataset/UploadTab.jsx @@ -0,0 +1,118 @@ +import React, { useRef, useState } from 'react' +import { uploadFiles } from '../../api/client' + +export default function UploadTab() { + const [files, setFiles] = useState([]) + const [uploading, setUploading] = useState(false) + const [uploadError, setUploadError] = useState(null) + const [uploadSuccess, setUploadSuccess] = useState(false) + const fileInputRef = useRef(null) + + const handleFileChange = (e) => { + const selectedFiles = Array.from(e.target.files) + setFiles((prevFiles) => [...prevFiles, ...selectedFiles]) + } + + const handleUpload = async () => { + if (files.length === 0) { + setUploadError('Please select files to upload') + return + } + + setUploading(true) + setUploadError(null) + setUploadSuccess(false) + + try { + const result = await uploadFiles(files) + setUploadSuccess(true) + setFiles([]) + setTimeout(() => setUploadSuccess(false), 3000) + } catch (error) { + console.error('Upload error:', error) + setUploadError(error.message || 'Upload failed') + } finally { + setUploading(false) + } + } + + const removeFile = (index) => { + setFiles((prevFiles) => prevFiles.filter((_, i) => i !== index)) + } + + return ( +
+
+
fileInputRef.current?.click()} + onDragOver={(e) => { + e.preventDefault() + e.currentTarget.style.borderColor = '#2563eb' + }} + onDragLeave={(e) => { + e.currentTarget.style.borderColor = '#ddd' + }} + onDrop={(e) => { + e.preventDefault() + e.currentTarget.style.borderColor = '#ddd' + const droppedFiles = Array.from(e.dataTransfer.files) + setFiles((prevFiles) => [...prevFiles, ...droppedFiles]) + }} + > + +
📁
+

Drag and drop files here or click to browse

+

Supported formats: CSV, XLSX, JSON, Parquet

+
+
+ + {uploadError && ( +
+ ✕ {uploadError} +
+ )} + + {uploadSuccess && ( +
+ ✓ Files uploaded successfully! +
+ )} + + {files.length > 0 && ( +
+

Selected Files ({files.length})

+
    + {files.map((file, index) => ( +
  • + 📄 {file.name} + ({(file.size / 1024).toFixed(2)} KB) + +
    • + ))} +
+ + +
+ )} +
+ ) +} diff --git a/plexe/ui/frontend/src/styles.css b/plexe/ui/frontend/src/styles.css index 4d8dbf70..f529b5ac 100644 --- a/plexe/ui/frontend/src/styles.css +++ b/plexe/ui/frontend/src/styles.css @@ -2,92 +2,664 @@ --bg: #f9fafb; --card: #fff; --muted: #6b7280; - --primary: #2563eb + --primary: #2563eb; + --primary-light: #3b82f6; + --primary-hover: #1d4ed8; + --success: #10b981; + --error: #ef4444; + --border: #e5e7eb; + --text: #111827; + --text-secondary: #6b7280; +} + +* { + box-sizing: border-box; } body { margin: 0; font-family: Inter, ui-sans-serif, system-ui, -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif; - background: var(--bg) + background: var(--bg); +} + +html, +body, +#root { + height: 100%; + width: 100%; +} + +/* ===== App Layout ===== */ +.app-root { + display: flex; + height: 100vh; + width: 100%; } -.app-header { +.app-main { + flex: 1; + display: flex; + flex-direction: column; + background: var(--bg); + overflow-y: auto; +} + +/* ===== Sidebar ===== */ +.sidebar { + width: 260px; background: var(--card); - border-bottom: 1px solid #e5e7eb; - padding: 1rem 1.25rem + border-right: 1px solid var(--border); + display: flex; + flex-direction: column; + box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1); +} + +.sidebar-header { + padding: 1.5rem 1.25rem; + border-bottom: 1px solid var(--border); } -.app-header h1 { +.sidebar-header h2 { margin: 0; - font-size: 1.25rem + font-size: 1.5rem; + font-weight: 700; + color: var(--primary); } -.app-main { - max-width: 48rem; - margin: 1.5rem auto; - padding: 1rem +.sidebar-header p { + margin: 0.25rem 0 0; + font-size: 0.875rem; + color: var(--text-secondary); +} + +.sidebar-nav { + flex: 1; + padding: 1rem 0.75rem; + display: flex; + flex-direction: column; + gap: 0.5rem; +} + +.nav-item { + display: flex; + align-items: center; + gap: 0.75rem; + padding: 0.75rem 1rem; + background: transparent; + border: none; + border-radius: 8px; + cursor: pointer; + color: var(--text-secondary); + font-size: 1rem; + transition: all 0.2s ease; + text-align: left; } +.nav-item:hover { + background: #f3f4f6; + color: var(--text); +} + +.nav-item.active { + background: var(--primary-light); + color: white; + font-weight: 500; +} + +.nav-item .icon { + font-size: 1.25rem; + min-width: 1.5rem; +} + +.nav-item .label { + flex: 1; +} + +.sidebar-footer { + padding: 1rem 1.25rem; + border-top: 1px solid var(--border); + text-align: center; +} + +.sidebar-footer .version { + margin: 0; + font-size: 0.75rem; + color: var(--text-secondary); +} + +/* ===== Chat ===== */ .chat-root { display: flex; flex-direction: column; - height: 70vh; + height: calc(100vh - 2rem); background: var(--card); - border-radius: 8px; - padding: 1rem + border-radius: 0; + padding: 0; + margin: 1rem; + border-radius: 12px; + box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1); } .status { font-size: 0.85rem; color: var(--muted); - margin-bottom: 0.5rem + padding: 0.75rem 1rem; + border-bottom: 1px solid var(--border); } .messages { flex: 1; - overflow: auto; - padding-right: 0.5rem + overflow-y: auto; + padding: 1rem; + display: flex; + flex-direction: column; + gap: 0.75rem; } .message { - margin-bottom: 0.75rem; - display: flex + display: flex; + margin: 0; } .message.user { - justify-content: flex-end + justify-content: flex-end; } .bubble { max-width: 70%; - padding: 0.6rem 0.85rem; - border-radius: 8px; - background: #f3f4f6 + padding: 0.75rem 1rem; + border-radius: 12px; + background: #f3f4f6; + color: var(--text); + word-wrap: break-word; } .message.user .bubble { background: var(--primary); - color: #fff + color: white; + border-radius: 12px 0 12px 12px; +} + +.message.assistant .bubble { + background: #e5e7eb; + border-radius: 0 12px 12px 12px; } .composer { display: flex; - gap: 0.5rem; - border-top: 1px solid #eee; - padding-top: 0.75rem + gap: 0.75rem; + border-top: 1px solid var(--border); + padding: 1rem; + background: white; } .composer input { flex: 1; - padding: 0.5rem; - border: 1px solid #ddd; - border-radius: 6px + padding: 0.625rem 0.875rem; + border: 1px solid var(--border); + border-radius: 8px; + font-size: 0.95rem; + transition: all 0.2s ease; +} + +.composer input:focus { + outline: none; + border-color: var(--primary); + box-shadow: 0 0 0 3px rgba(37, 99, 235, 0.1); } .composer button { - padding: 0.5rem 0.75rem; + padding: 0.625rem 1.25rem; background: var(--primary); - color: #fff; - border-radius: 6px; - border: 0 + color: white; + border-radius: 8px; + border: none; + cursor: pointer; + font-weight: 500; + transition: all 0.2s ease; +} + +.composer button:hover { + background: var(--primary-hover); +} + +.composer button:active { + transform: scale(0.98); +} + +/* ===== Dataset Page ===== */ +.dataset-container { + flex: 1; + display: flex; + flex-direction: column; + padding: 1.5rem; + background: var(--bg); +} + +.dataset-header { + margin-bottom: 2rem; +} + +.dataset-header h2 { + margin: 0 0 0.5rem; + font-size: 1.875rem; + font-weight: 700; + color: var(--text); +} + +.dataset-header p { + margin: 0; + color: var(--text-secondary); + font-size: 1rem; +} + +.tabs { + display: flex; + flex-direction: column; + background: var(--card); + border-radius: 12px; + box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1); + overflow: hidden; + flex: 1; +} + +.tab-buttons { + display: flex; + border-bottom: 1px solid var(--border); + background: white; +} + +.tab-button { + flex: 1; + padding: 1rem; + background: transparent; + border: none; + border-bottom: 3px solid transparent; + cursor: pointer; + font-size: 0.95rem; + font-weight: 500; + color: var(--text-secondary); + display: flex; + align-items: center; + justify-content: center; + gap: 0.5rem; + transition: all 0.2s ease; +} + +.tab-button:hover { + background: #f9fafb; + color: var(--text); +} + +.tab-button.active { + color: var(--primary); + border-bottom-color: var(--primary); +} + +.tab-button .icon { + font-size: 1.25rem; +} + +.tab-content { + flex: 1; + padding: 2rem; + overflow-y: auto; +} + +/* ===== Upload Tab ===== */ +.upload-tab { + display: flex; + flex-direction: column; + gap: 2rem; +} + +.upload-area { + width: 100%; +} + +.upload-box { + border: 2px dashed var(--border); + border-radius: 12px; + padding: 3rem 2rem; + text-align: center; + cursor: pointer; + transition: all 0.3s ease; + background: #fafbfc; +} + +.upload-box:hover { + border-color: var(--primary-light); + background: #f0f7ff; +} + +.upload-icon { + font-size: 3rem; + margin-bottom: 1rem; +} + +.upload-text { + margin: 0.5rem 0; + font-size: 1.1rem; + font-weight: 500; + color: var(--text); +} + +.upload-hint { + margin: 0.5rem 0 0; + font-size: 0.875rem; + color: var(--text-secondary); +} + +.files-list { + background: white; + border: 1px solid var(--border); + border-radius: 12px; + padding: 1.5rem; +} + +.files-list h3 { + margin: 0 0 1rem; + font-size: 1rem; + color: var(--text); +} + +.file-items { + list-style: none; + margin: 0 0 1.5rem; + padding: 0; + display: flex; + flex-direction: column; + gap: 0.75rem; +} + +.file-item { + display: flex; + align-items: center; + gap: 0.75rem; + padding: 0.75rem; + background: #f9fafb; + border-radius: 8px; + font-size: 0.95rem; +} + +.file-name { + flex: 1; + font-weight: 500; + color: var(--text); +} + +.file-size { + color: var(--text-secondary); + font-size: 0.875rem; +} + +.remove-btn { + background: transparent; + border: none; + color: var(--error); + cursor: pointer; + font-size: 1rem; + padding: 0.25rem 0.5rem; + border-radius: 4px; + transition: all 0.2s ease; +} + +.remove-btn:hover { + background: rgba(239, 68, 68, 0.1); +} + +.upload-button { + width: 100%; + padding: 0.875rem 1.25rem; + background: var(--primary); + color: white; + border: none; + border-radius: 8px; + cursor: pointer; + font-size: 1rem; + font-weight: 600; + transition: all 0.2s ease; +} + +.upload-button:hover:not(:disabled) { + background: var(--primary-hover); +} + +.upload-button:disabled { + background: var(--text-secondary); + cursor: not-allowed; + opacity: 0.6; +} + +/* ===== PostgreSQL Tab ===== */ +.postgres-tab { + display: grid; + grid-template-columns: 2fr 1fr; + gap: 2rem; +} + +.postgres-form { + display: flex; + flex-direction: column; + gap: 1.5rem; +} + +.postgres-form h3 { + margin: 0; + font-size: 1.1rem; + color: var(--text); + font-weight: 600; +} + +.form-group { + display: flex; + flex-direction: column; + gap: 0.5rem; +} + +.form-group label { + font-size: 0.95rem; + font-weight: 500; + color: var(--text); +} + +.form-group input { + padding: 0.625rem 0.875rem; + border: 1px solid var(--border); + border-radius: 8px; + font-size: 0.95rem; + transition: all 0.2s ease; + background: white; +} + +.form-group input:focus { + outline: none; + border-color: var(--primary); + box-shadow: 0 0 0 3px rgba(37, 99, 235, 0.1); +} + +.status-message { + padding: 0.75rem 1rem; + border-radius: 8px; + font-size: 0.95rem; + font-weight: 500; +} + +.status-message.success { + background: rgba(16, 185, 129, 0.1); + color: var(--success); + border: 1px solid var(--success); +} + +.status-message.error { + background: rgba(239, 68, 68, 0.1); + color: var(--error); + border: 1px solid var(--error); +} + +.form-actions { + display: flex; + gap: 1rem; + margin-top: 1rem; +} + +.button { + padding: 0.75rem 1.5rem; + border: none; + border-radius: 8px; + cursor: pointer; + font-size: 0.95rem; + font-weight: 600; + transition: all 0.2s ease; + flex: 1; +} + +.button.primary { + background: var(--primary); + color: white; +} + +.button.primary:hover:not(:disabled) { + background: var(--primary-hover); +} + +.button.secondary { + background: white; + color: var(--primary); + border: 1px solid var(--primary); +} + +.button.secondary:hover:not(:disabled) { + background: var(--primary-light); + color: white; + border-color: var(--primary-hover); +} + +.button:disabled { + background: var(--text-secondary); + color: white; + cursor: not-allowed; + opacity: 0.6; +} + +.postgres-info { + background: #f0f7ff; + border: 1px solid #cce5ff; + border-radius: 12px; + padding: 1.5rem; + height: fit-content; + position: sticky; + top: 1rem; +} + +.postgres-info h4 { + margin: 0 0 1rem; + font-size: 1rem; + color: var(--text); + font-weight: 600; +} + +.postgres-info p { + margin: 0.5rem 0; + font-size: 0.9rem; + color: var(--text); +} + +.postgres-info strong { + color: var(--primary); +} + +/* ===== Responsive Design ===== */ +@media (max-width: 1024px) { + .postgres-tab { + grid-template-columns: 1fr; + } + + .postgres-info { + position: static; + } +} + +@media (max-width: 768px) { + .sidebar { + width: 200px; + } + + .sidebar-header { + padding: 1rem; + } + + .sidebar-header h2 { + font-size: 1.25rem; + } + + .nav-item { + padding: 0.6rem 0.75rem; + } + + .nav-item .label { + display: none; + } + + .chat-root { + height: calc(100vh - 1rem); + margin: 0.5rem; + } + + .dataset-container { + padding: 1rem; + } + + .dataset-header { + margin-bottom: 1rem; + } + + .dataset-header h2 { + font-size: 1.5rem; + } + + .tab-content { + padding: 1rem; + } + + .postgres-tab { + grid-template-columns: 1fr; + } + + .bubble { + max-width: 90%; + } +} + +@media (max-width: 480px) { + .sidebar { + width: 70px; + } + + .sidebar-header h2, + .sidebar-header p { + display: none; + } + + .tab-button { + font-size: 0.8rem; + padding: 0.75rem; + } + + .tab-button .icon { + font-size: 1rem; + } + + .upload-box { + padding: 2rem 1rem; + } + + .upload-icon { + font-size: 2rem; + margin-bottom: 0.5rem; + } + + .postgres-form h3 { + display: none; + } } \ No newline at end of file diff --git a/plexe/ui/frontend/vite.config.js b/plexe/ui/frontend/vite.config.js index 4898fcf3..1eba421a 100644 --- a/plexe/ui/frontend/vite.config.js +++ b/plexe/ui/frontend/vite.config.js @@ -4,6 +4,14 @@ import react from '@vitejs/plugin-react' export default defineConfig({ plugins: [react()], server: { + host: '0.0.0.0', + port: 3000, + strictPort: false, + hmr: { + host: 'localhost', + port: 3000, + protocol: 'ws', + }, proxy: { // Proxy /ws to backend during development '/ws': { @@ -11,7 +19,7 @@ export default defineConfig({ ws: true, changeOrigin: true, }, - // Proxy /api requests if needed in future + // Proxy /api requests to backend '/api': { target: 'http://localhost:8000', changeOrigin: true, diff --git a/poetry.lock b/poetry.lock index bc38b0d4..3c3a6383 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.2.1 and should not be changed by hand. [[package]] name = "accelerate" @@ -6,6 +6,8 @@ version = "0.24.1" description = "Accelerate" optional = true python-versions = ">=3.8.0" +groups = ["main"] +markers = "extra == \"transformers\" or extra == \"all\"" files = [ {file = "accelerate-0.24.1-py3-none-any.whl", hash = "sha256:866dec394da60e8da964be212379d8cf6cc0d0e5e28a7c0d7e09507715d21c61"}, {file = "accelerate-0.24.1.tar.gz", hash = "sha256:85ab2aeb4d06194b75113339f81b7d650523414a82c9e91b2912a655f53dfa8e"}, @@ -35,6 +37,7 @@ version = "2.6.1" description = "Happy Eyeballs for asyncio" optional = false python-versions = ">=3.9" +groups = ["main"] files = [ {file = "aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8"}, {file = "aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558"}, @@ -42,102 +45,137 @@ files = [ [[package]] name = "aiohttp" -version = "3.12.9" +version = "3.13.2" description = 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["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"] +check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""] cover = ["pytest-cov"] doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] enabler = ["pytest-enabler (>=2.2)"] -test = ["big-O", "importlib_resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more_itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"] +test = ["big-O", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more_itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"] type = ["pytest-mypy"] [extras] @@ -6744,6 +7765,6 @@ chatui = ["fastapi", "uvicorn", "websockets"] transformers = ["accelerate", "safetensors", "tokenizers", "transformers"] [metadata] -lock-version = "2.0" +lock-version = "2.1" python-versions = ">=3.11,<3.13" -content-hash = "46f431b72bf1852e5bd0f17a3f9b65b47a2c53b0cfdc900eceb7323683f5a282" +content-hash = 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--- a/.gitignore +++ b/.gitignore @@ -299,10 +299,10 @@ ENV/ # Keep poetry.lock for reproducible builds # (uncomment below if you prefer to ignore it) -# poetry.lock +poetry.lock **/.claude/settings.local.json # Data folder data/ data/uploads/ -data/uploads/* \ No newline at end of file +data/uploads/* diff --git a/plexe/api/datasets.py b/plexe/api/datasets.py index fca9c077..9001e4ac 100644 --- a/plexe/api/datasets.py +++ b/plexe/api/datasets.py @@ -124,16 +124,31 @@ async def save_postgres_connection(config: PostgresConnection): # Test connection first conn = psycopg2.connect(conn_str) + + # Fetch tables from the public schema + tables = [] + with conn.cursor() as cursor: + cursor.execute( + """ + SELECT table_name + FROM information_schema.tables + WHERE table_schema = 'public' + """ + ) + for row in cursor.fetchall(): + tables.append(row[0]) + conn.close() # TODO: Save to secure config file or database - # For now, just return success + # For now, just return success and the list of tables return { "success": True, "message": "Connection saved successfully", "host": config.host, "port": config.port, "database": config.database, + "tables": tables, } except ImportError: diff --git a/plexe/ui/frontend/src/components/Chat.jsx b/plexe/ui/frontend/src/components/Chat.jsx index b64de2a0..ef43ec4e 100644 --- a/plexe/ui/frontend/src/components/Chat.jsx +++ b/plexe/ui/frontend/src/components/Chat.jsx @@ -50,7 +50,16 @@ export default function Chat({ wsUrl }) { ))}
- setInput(e.target.value)} placeholder="Type your message..." /> + setInput(e.target.value)} + onKeyPress={(e) => { + if (e.key === 'Enter') { + send() + } + }} + placeholder="Type your message..." + />
diff --git a/plexe/ui/frontend/src/components/Dataset.jsx b/plexe/ui/frontend/src/components/Dataset.jsx index 58eb3bd9..8bdf39b3 100644 --- a/plexe/ui/frontend/src/components/Dataset.jsx +++ b/plexe/ui/frontend/src/components/Dataset.jsx @@ -31,6 +31,7 @@ export default function Dataset() {
+ {activeTab === 'upload' && } {activeTab === 'postgres' && }
diff --git a/plexe/ui/frontend/src/components/dataset/PostgreSQLTab.jsx b/plexe/ui/frontend/src/components/dataset/PostgreSQLTab.jsx index 33a93c4b..efc78a9a 100644 --- a/plexe/ui/frontend/src/components/dataset/PostgreSQLTab.jsx +++ b/plexe/ui/frontend/src/components/dataset/PostgreSQLTab.jsx @@ -11,6 +11,7 @@ export default function PostgreSQLTab() { }) const [connecting, setConnecting] = useState(false) const [connectionStatus, setConnectionStatus] = useState(null) + const [tables, setTables] = useState([]) const handleInputChange = (e) => { const { name, value } = e.target @@ -43,6 +44,7 @@ export default function PostgreSQLTab() { const handleSaveConnection = async () => { setConnecting(true) + setTables([]) try { const data = await savePostgresConnection(connectionForm) @@ -50,6 +52,9 @@ export default function PostgreSQLTab() { type: 'success', message: 'Connection saved successfully!', }) + if (data.tables) { + setTables(data.tables) + } } catch (error) { console.error('Save error:', error) setConnectionStatus({ @@ -161,6 +166,17 @@ export default function PostgreSQLTab() {

Username: {connectionForm.username || 'Not set'}

+ + {tables.length > 0 && ( +
+

Available Tables

+
    + {tables.map((table) => ( +
  • {table}
    • + ))} +
+
+ )} ) diff --git a/poetry.lock b/poetry.lock index 3c3a6383..6468664f 100644 --- a/poetry.lock +++ b/poetry.lock @@ -4686,6 +4686,83 @@ markers = {main = "extra == \"transformers\" or extra == \"all\""} dev = ["abi3audit", "black", "check-manifest", "colorama ; os_name == \"nt\"", "coverage", "packaging", "pylint", "pyperf", "pypinfo", "pyreadline ; os_name == \"nt\"", "pytest", "pytest-cov", "pytest-instafail", "pytest-subtests", "pytest-xdist", "pywin32 ; os_name == \"nt\" and platform_python_implementation != \"PyPy\"", "requests", "rstcheck", "ruff", "setuptools", "sphinx", "sphinx_rtd_theme", "toml-sort", "twine", "validate-pyproject[all]", "virtualenv", "vulture", "wheel", "wheel ; os_name == \"nt\" and platform_python_implementation != \"PyPy\"", "wmi ; os_name == \"nt\" and platform_python_implementation != \"PyPy\""] test = ["pytest", "pytest-instafail", "pytest-subtests", "pytest-xdist", "pywin32 ; os_name == \"nt\" and platform_python_implementation != \"PyPy\"", 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a/pyproject.toml b/pyproject.toml index 21023afe..5cfc24bb 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -54,6 +54,7 @@ torch = "^2.3.0" smolagents = "^1.14.0" deprecated = "^1.2.18" python-multipart = "^0.0.16" +psycopg2-binary = "^2.9.9" # Deep learning dependencies transformers = { version = "^4.50.0", optional = true } From 15387b019d5eecdfd14ac2ef9c76dd79448ee907 Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Tue, 18 Nov 2025 11:47:28 +0700 Subject: [PATCH 06/42] FEAT: Implement handleCombine function in PostgreSQLTab.jsx and fix SyntaxError in FeatureGeneratorAgent --- plexe/agents/feature_generator.py | 117 ++++++++++++ .../src/components/dataset/PostgreSQLTab.jsx | 174 +++++++++++------- 2 files changed, 226 insertions(+), 65 deletions(-) create mode 100644 plexe/agents/feature_generator.py diff --git a/plexe/agents/feature_generator.py b/plexe/agents/feature_generator.py new file mode 100644 index 00000000..d61ba362 --- /dev/null +++ b/plexe/agents/feature_generator.py @@ -0,0 +1,117 @@ +""" +Feature Generation Agent for combining datasets using featuretools. +""" + +import logging +import os +from typing import Optional, Callable + +from smolagents import CodeAgent, LiteLLMModel + +from plexe.config import config +from plexe.internal.common.utils.agents import get_prompt_templates +from plexe.core.object_registry import ObjectRegistry +from plexe.tools.datasets import ( + get_dataset_preview, + get_latest_datasets, + register_feature_engineering_report, +) +from plexe.tools.execution import execute_code +from plexe.tools.io_manager import read_file, write_file + +logger = logging.getLogger(__name__) + + +class FeatureGeneratorAgent: + """ + Agent for combining datasets using featuretools. + """ + + def __init__( + self, + session_id: str, + tables: list, + relationships: list, + model_id: str | None = None, + verbose: bool = False, + chain_of_thought_callable: Optional[Callable] = None, + ): + """ + Initialize the feature generator agent. + + Args: + model_id: Model ID for the LLM to use for feature generation + session_id: The session ID for the current run + tables: A list of tables to be combined + relationships: A list of relationships between the tables + verbose: Whether to display detailed agent logs + chain_of_thought_callable: Optional callback for chain-of-thought logging + """ + env_model = os.environ.get("PLEXE_CONVERSATIONAL_MODEL") + + if model_id: + self.model_id = model_id + elif env_model: + self.model_id = env_model + else: + # Auto-detect from available API keys + if os.environ.get("GEMINI_API_KEY"): + self.model_id = "gemini/gemini-2.5-flash" + elif os.environ.get("OPENAI_API_KEY"): + self.model_id = "openai/gpt-4o-mini" + elif os.environ.get("ANTHROPIC_API_KEY"): + self.model_id = "anthropic/claude-sonnet-4-20250514" + else: + self.model_id = "anthropic/claude-sonnet-4-20250514" + # Set verbosity level + self.verbosity = 1 if verbose else 0 + + # Register session_id for tools to use + ObjectRegistry().register(str, "session_id", session_id, overwrite=True) + + # Create feature generator agent + self.agent = CodeAgent( + name="FeatureGenerator", + description=( + "Expert data scientist that combines datasets using featuretools. " + "To work effectively, as part of the 'task' prompt the agent STRICTLY requires:" + "- the list of tables" + "- the list of relationships" + ), + model=LiteLLMModel(model_id=self.model_id), + tools=[ + get_dataset_preview, + get_latest_datasets, + register_feature_engineering_report, + execute_code, + read_file, + write_file, + ], + add_base_tools=False, + additional_authorized_imports=config.code_generation.authorized_agent_imports + + [ + "featuretools", + "featuretools.*", + "pandas", + "pandas.*", + "numpy", + "numpy.*", + ], + verbosity_level=self.verbosity, + prompt_templates=get_prompt_templates( + base_template_name="code_agent.yaml", + override_template_name="feature_generator_prompt_templates.yaml", + template_vars={"tables": tables, "relationships": relationships}, + ), + planning_interval=5, + step_callbacks=[chain_of_thought_callable], + ) + + def run(self, task: str): + """ + Run the agent to perform the feature generation task. + + Args: + task: The task to be performed by the agent. + """ + return self.agent.run(task) diff --git a/plexe/ui/frontend/src/components/dataset/PostgreSQLTab.jsx b/plexe/ui/frontend/src/components/dataset/PostgreSQLTab.jsx index efc78a9a..4ca5b5da 100644 --- a/plexe/ui/frontend/src/components/dataset/PostgreSQLTab.jsx +++ b/plexe/ui/frontend/src/components/dataset/PostgreSQLTab.jsx @@ -1,5 +1,10 @@ import React, { useState } from 'react' -import { testPostgresConnection, savePostgresConnection } from '../../api/client' +import { + testPostgresConnection, + executePostgresQuery, + combineDatasets, +} from '../../api/client' +import QueryResult from './QueryResult' export default function PostgreSQLTab() { const [connectionForm, setConnectionForm] = useState({ @@ -10,8 +15,11 @@ export default function PostgreSQLTab() { database: '', }) const [connecting, setConnecting] = useState(false) + const [combining, setCombining] = useState(false) const [connectionStatus, setConnectionStatus] = useState(null) - const [tables, setTables] = useState([]) + const [combineStatus, setCombineStatus] = useState(null) + const [queryResult, setQueryResult] = useState(null) + const [showCombine, setShowCombine] = useState(false) const handleInputChange = (e) => { const { name, value } = e.target @@ -24,9 +32,12 @@ export default function PostgreSQLTab() { const handleTestConnection = async () => { setConnecting(true) setConnectionStatus(null) + setQueryResult(null) + setShowCombine(false) + setCombineStatus(null) try { - const data = await testPostgresConnection(connectionForm) + await testPostgresConnection(connectionForm) setConnectionStatus({ type: 'success', message: 'Connection successful!', @@ -42,21 +53,23 @@ export default function PostgreSQLTab() { } } - const handleSaveConnection = async () => { + const handleExecute = async () => { setConnecting(true) - setTables([]) + setQueryResult(null) + setConnectionStatus(null) + setShowCombine(false) + setCombineStatus(null) try { - const data = await savePostgresConnection(connectionForm) + const data = await executePostgresQuery(connectionForm) + setQueryResult(data) setConnectionStatus({ type: 'success', - message: 'Connection saved successfully!', + message: 'Query executed successfully!', }) - if (data.tables) { - setTables(data.tables) - } + setShowCombine(true) } catch (error) { - console.error('Save error:', error) + console.error('Execute error:', error) setConnectionStatus({ type: 'error', message: error.message, @@ -66,33 +79,58 @@ export default function PostgreSQLTab() { } } + const handleCombine = async () => { + setCombining(true) + setCombineStatus(null) + try { + await combineDatasets(queryResult.tables, queryResult.relationships) + setCombineStatus({ + type: 'success', + message: 'Dataset combination started successfully!', + }) + } catch (error) { + console.error('Combine error:', error) + setCombineStatus({ + type: 'error', + message: error.message, + }) + } finally { + setCombining(false) + } + } + return (
-

PostgreSQL Connection Settings

+

PostgreSQL Connection

+

+ Enter your database credentials to fetch schema information. +

-
- - -
+
+
+ + +
-
- - +
+ + +
@@ -103,7 +141,7 @@ export default function PostgreSQLTab() { name="database" value={connectionForm.database} onChange={handleInputChange} - placeholder="database_name" + placeholder="e.g., my_database" />
@@ -115,7 +153,7 @@ export default function PostgreSQLTab() { name="username" value={connectionForm.username} onChange={handleInputChange} - placeholder="postgres" + placeholder="e.g., postgres" />
@@ -131,50 +169,56 @@ export default function PostgreSQLTab() { />
- {connectionStatus && ( -
- {connectionStatus.type === 'success' ? '✓' : '✕'} {connectionStatus.message} -
- )} -
-
-
-

Connection Information

-

- Current Host: {connectionForm.host}:{connectionForm.port} -

-

- Database: {connectionForm.database || 'Not set'} -

-

- Username: {connectionForm.username || 'Not set'} -

+ {connectionStatus && ( +
+ {connectionStatus.message} +
+ )} +
- {tables.length > 0 && ( -
-

Available Tables

-
    - {tables.map((table) => ( -
  • {table}
    • - ))} -
+
+ {queryResult && ( + + )} + {showCombine && ( +
+

+ Do you want to combine these tables into a final dataset? +

+ + {combineStatus && ( +
+ {combineStatus.message} +
+ )}
)}
From 387aa955ca3475d2080e462ed87ecdcc5e43b498 Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Tue, 18 Nov 2025 13:09:29 +0700 Subject: [PATCH 07/42] FIX: Pass template_vars to get_prompt_templates --- plexe/internal/common/utils/agents.py | 27 ++++++++++++------- .../feature_generator_prompt_templates.yaml | 25 +++++++++++++++++ 2 files changed, 43 insertions(+), 9 deletions(-) create mode 100644 plexe/templates/prompts/agent/feature_generator_prompt_templates.yaml diff --git a/plexe/internal/common/utils/agents.py b/plexe/internal/common/utils/agents.py index 26f1b9a4..5d6290c3 100644 --- a/plexe/internal/common/utils/agents.py +++ b/plexe/internal/common/utils/agents.py @@ -7,22 +7,31 @@ from plexe.config import config -def get_prompt_templates(base_template_name: str, override_template_name: str) -> dict: +def get_prompt_templates( + base_template_name: str, override_template_name: str, template_vars: dict | None = None +) -> dict: """ Given the name of a smolagents prompt template (the 'base template') and a plexe prompt template (the 'overriding template'), this function loads both templates and returns a merged template in which all keys from the overriding template overwrite the matching keys in the base template. """ - base_template: dict = yaml.safe_load( - importlib.resources.files("smolagents.prompts").joinpath(base_template_name).read_text() + base_template_content = importlib.resources.files("smolagents.prompts").joinpath(base_template_name).read_text() + override_template_content = ( + importlib.resources.files("plexe") + .joinpath("templates/prompts/agent") + .joinpath(override_template_name) + .read_text() ) + + # Perform string replacements for template variables + if template_vars: + for key, value in template_vars.items(): + base_template_content = base_template_content.replace(f"{{{{{key}}}}}", str(value)) + override_template_content = override_template_content.replace(f"{{{{{key}}}}}", str(value)) + + base_template: dict = yaml.safe_load(base_template_content) override_template: dict = yaml.safe_load( - str( - importlib.resources.files("plexe") - .joinpath("templates/prompts/agent") - .joinpath(override_template_name) - .read_text() - ).replace("{{allowed_packages}}", str(config.code_generation.allowed_packages)) + override_template_content.replace("{{allowed_packages}}", str(config.code_generation.allowed_packages)) ) # Recursively merge two dictionaries to ensure deep merging diff --git a/plexe/templates/prompts/agent/feature_generator_prompt_templates.yaml b/plexe/templates/prompts/agent/feature_generator_prompt_templates.yaml new file mode 100644 index 00000000..33ff6329 --- /dev/null +++ b/plexe/templates/prompts/agent/feature_generator_prompt_templates.yaml @@ -0,0 +1,25 @@ +base_system_prompt: | + You are a data scientist and your task is to generate features from a given set of tables and their relationships. + You have access to the following tables: {{tables}} + And the following relationships: {{relationships}} + + You must use the `featuretools` library to perform automated feature engineering. + Your goal is to create a single denormalized dataframe with new features. + You should then save this dataframe to a CSV file named 'final_dataset.csv' in the current working directory. + + Follow these steps: + 1. Use the `get_latest_datasets` tool to get the names of the available datasets. + 2. Use the `get_dataset_preview` tool to understand the structure of each dataset. + 3. Generate Python code to perform the following: + a. Load the tables into pandas DataFrames. The tables are available as CSV files with the same name as the table name (e.g., 'table_name.csv'). + b. Create a Featuretools `EntitySet`. + c. Add the dataframes to the `EntitySet`. + d. Add the relationships to the `EntitySet`. + e. Run Deep Feature Synthesis (DFS) to generate new features. + f. Save the resulting dataframe to 'final_dataset.csv'. + 4. Use the `CodeExecutionTool` to execute the generated code. + 5. Use the `register_feature_engineering_report` tool to register a report of the feature engineering process. + 6. The final output should be the name of the new dataset. + + You have access to a code execution tool. Use it to perform the necessary steps. + Make sure to install `featuretools` if it's not already installed. From fedd0fdf1effe7fbfc02107b75026a2fa7bf8f9e Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Tue, 18 Nov 2025 13:17:21 +0700 Subject: [PATCH 08/42] FIX: Add feature-labs dependency and improve logging --- plexe/api/datasets.py | 94 +++++++++++++++++++++++++++++++++++++------ pyproject.toml | 1 + 2 files changed, 83 insertions(+), 12 deletions(-) diff --git a/plexe/api/datasets.py b/plexe/api/datasets.py index 9001e4ac..81ee31a3 100644 --- a/plexe/api/datasets.py +++ b/plexe/api/datasets.py @@ -1,17 +1,19 @@ -""" -Dataset API endpoints for Plexe backend -Handles file uploads, PostgreSQL connections, and dataset management -""" - +import logging from pathlib import Path from typing import List +import uuid from fastapi import APIRouter, File, UploadFile, HTTPException +from fastapi.responses import FileResponse from pydantic import BaseModel -router = APIRouter(prefix="/api", tags=["datasets"]) +from plexe.agents.feature_generator import FeatureGeneratorAgent -# Create uploads directory if it doesn't exist +# Configure logging +logger = logging.getLogger(__name__) +logging.basicConfig(level=logging.INFO) + +router = APIRouter(prefix="/api", tags=["datasets"]) UPLOADS_DIR = Path("./data/uploads") UPLOADS_DIR.mkdir(parents=True, exist_ok=True) @@ -104,10 +106,10 @@ async def test_postgres_connection(config: PostgresConnection): raise HTTPException(status_code=400, detail=f"Connection failed: {str(e)}") -@router.post("/postgres/save") -async def save_postgres_connection(config: PostgresConnection): +@router.post("/postgres/execute") +async def execute_postgres_query(config: PostgresConnection): """ - Save PostgreSQL connection configuration + Execute a query on a PostgreSQL database TODO: Store in database or secure config file """ try: @@ -138,23 +140,53 @@ async def save_postgres_connection(config: PostgresConnection): for row in cursor.fetchall(): tables.append(row[0]) + # Fetch relationships from the public schema + relationships = [] + with conn.cursor() as cursor: + cursor.execute( + """ + SELECT + tc.table_name, + kcu.column_name, + ccu.table_name AS foreign_table_name, + ccu.column_name AS foreign_column_name + FROM + information_schema.table_constraints AS tc + JOIN information_schema.key_column_usage AS kcu + ON tc.constraint_name = kcu.constraint_name + JOIN information_schema.constraint_column_usage AS ccu + ON ccu.constraint_name = tc.constraint_name + WHERE constraint_type = 'FOREIGN KEY' AND tc.table_schema = 'public'; + """ + ) + for row in cursor.fetchall(): + relationships.append( + { + "table_name": row[0], + "column_name": row[1], + "foreign_table_name": row[2], + "foreign_column_name": row[3], + } + ) + conn.close() # TODO: Save to secure config file or database # For now, just return success and the list of tables return { "success": True, - "message": "Connection saved successfully", + "message": "Query executed successfully", "host": config.host, "port": config.port, "database": config.database, "tables": tables, + "relationships": relationships, } except ImportError: raise HTTPException(status_code=500, detail="psycopg2 not installed. Install with: pip install psycopg2-binary") except Exception as e: - raise HTTPException(status_code=400, detail=f"Failed to save connection: {str(e)}") + raise HTTPException(status_code=400, detail=f"Failed to execute query: {str(e)}") @router.get("/datasets") @@ -202,3 +234,41 @@ async def delete_dataset(dataset_id: str): raise except Exception as e: raise HTTPException(status_code=500, detail=f"Failed to delete dataset: {str(e)}") + + +@router.get("/datasets/{dataset_id}/download") +async def download_dataset(dataset_id: str): + """ + Download a dataset by ID (filename without extension) + """ + try: + for file_path in UPLOADS_DIR.iterdir(): + if file_path.stem == dataset_id and file_path.is_file(): + return FileResponse(path=file_path, filename=file_path.name, media_type="application/octet-stream") + raise HTTPException(status_code=404, detail=f"Dataset '{dataset_id}' not found") + except Exception as e: + raise HTTPException(status_code=500, detail=f"Failed to download dataset: {str(e)}") + + +@router.post("/datasets/combine") +async def combine_datasets_endpoint(data: dict): + """ + Combine datasets using featuretools + """ + logger.info(f"Received request to combine datasets with data: {data}") + try: + session_id = str(uuid.uuid4()) + agent = FeatureGeneratorAgent( + session_id=session_id, + tables=data["tables"], + relationships=data["relationships"], + ) + task = "Generate features from the provided tables and relationships." + agent.run(task) + + logger.info("Dataset combination started successfully.") + return {"success": True, "message": "Dataset combination started."} + + except Exception as e: + logger.error(f"Failed to combine datasets: {e}", exc_info=True) + raise HTTPException(status_code=500, detail=f"Failed to combine datasets: {str(e)}") diff --git a/pyproject.toml b/pyproject.toml index 5cfc24bb..260d282e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -55,6 +55,7 @@ smolagents = "^1.14.0" deprecated = "^1.2.18" python-multipart = "^0.0.16" psycopg2-binary = "^2.9.9" +feature-labs = "^1.3.0" # Deep learning dependencies transformers = { version = "^4.50.0", optional = true } From 0e85dc7a6629c23208c7b92466dd1c9cf2b94704 Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Fri, 28 Nov 2025 07:12:38 +0700 Subject: [PATCH 09/42] :bug:feat: baseline new agent but not work --- .env.example | 12 +- docker-compose.dev.yml | 2 + litellm-settings.yaml | 12 ++ plexe/agents/agents.py | 67 ++++-- plexe/agents/feature_generator.py | 117 ---------- plexe/agents/relational_gnn_specialist.py | 82 +++++++ plexe/agents/relational_graph_architect.py | 82 +++++++ plexe/agents/temporal_task_supervisor.py | 78 +++++++ plexe/api/datasets.py | 73 +++++-- plexe/config.py | 3 +- plexe/main.py | 2 + .../prompts/agent/agent_manager_prompt.jinja | 4 + .../feature_generator_prompt_templates.yaml | 25 --- ...ional_gnn_specialist_prompt_templates.yaml | 63 ++++++ ...onal_graph_architect_prompt_templates.yaml | 70 ++++++ ...oral_task_supervisor_prompt_templates.yaml | 59 +++++ plexe/tools/__init__.py | 15 ++ plexe/tools/execution.py | 50 +++++ plexe/tools/gnn_processing.py | 81 +++++++ plexe/tools/graph_processing.py | 193 +++++++++++++++++ plexe/tools/io_manager.py | 74 +++++++ plexe/tools/temporal_processing.py | 72 +++++++ plexe/ui/frontend/src/api/client.js | 54 ++++- plexe/ui/frontend/src/components/Dataset.jsx | 10 + .../src/components/dataset/OverviewTab.jsx | 85 ++++++++ .../src/components/dataset/PostgreSQLTab.jsx | 6 +- .../src/components/dataset/QueryResult.jsx | 43 ++++ plexe/ui/frontend/src/styles.css | 203 +++++++++++++++++- poetry.lock | 101 ++++++++- pyproject.toml | 3 +- 30 files changed, 1548 insertions(+), 193 deletions(-) create mode 100644 litellm-settings.yaml delete mode 100644 plexe/agents/feature_generator.py create mode 100644 plexe/agents/relational_gnn_specialist.py create mode 100644 plexe/agents/relational_graph_architect.py create mode 100644 plexe/agents/temporal_task_supervisor.py delete mode 100644 plexe/templates/prompts/agent/feature_generator_prompt_templates.yaml create mode 100644 plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml create mode 100644 plexe/templates/prompts/agent/relational_graph_architect_prompt_templates.yaml create mode 100644 plexe/templates/prompts/agent/temporal_task_supervisor_prompt_templates.yaml create mode 100644 plexe/tools/gnn_processing.py create mode 100644 plexe/tools/graph_processing.py create mode 100644 plexe/tools/io_manager.py create mode 100644 plexe/tools/temporal_processing.py create mode 100644 plexe/ui/frontend/src/components/dataset/OverviewTab.jsx create mode 100644 plexe/ui/frontend/src/components/dataset/QueryResult.jsx diff --git a/.env.example b/.env.example index b4d2785f..e588422d 100644 --- a/.env.example +++ b/.env.example @@ -17,4 +17,14 @@ REACT_APP_API_URL=http://localhost:8000 # pgAdmin credentials PGADMIN_EMAIL=admin@example.com -PGADMIN_PASSWORD=admin \ No newline at end of file +PGADMIN_PASSWORD=admin + +PLEXE_CONVERSATIONAL_MODEL="gemini/gemini-2.5-flash" +PLEXE_ORCHESTRATOR_MODEL="gemini/gemini-2.5-flash" +PLEXE_ML_RESEARCHER_MODEL="gemini/gemini-2.5-flash" +PLEXE_ML_ENGINEER_MODEL="gemini/gemini-2.5-flash" +PLEXE_ML_OPS_ENGINEER_MODEL="gemini/gemini-2.5-flash" +PLEXE_TOOL_MODEL="gemini/gemini-2.5-flash" +PLEXE_TOOL_FEATURE_GENERATOR_MODEL="gemini/gemini-2.5-flash" + +HF_TOKEN=??? \ No newline at end of file diff --git a/docker-compose.dev.yml b/docker-compose.dev.yml index b791cd03..18bead5f 100644 --- a/docker-compose.dev.yml +++ b/docker-compose.dev.yml @@ -69,6 +69,8 @@ services: MLFLOW_TRACKING_URI: ${MLFLOW_TRACKING_URI:-http://mlflow:5000} MLFLOW_BACKEND_STORE_URI: ${MLFLOW_BACKEND_STORE_URI:-postgresql+psycopg2://mlflow:mlflow@postgres:5432/mlflow_db} MLFLOW_HTTP_REQUEST_TIMEOUT: 300 + HF_TOKEN: ${HF_TOKEN} + HUGGINGFACE_API_KEY: ${HUGGINGFACE_API_KEY} volumes: - .:/app ports: diff --git a/litellm-settings.yaml b/litellm-settings.yaml new file mode 100644 index 00000000..e239b9db --- /dev/null +++ b/litellm-settings.yaml @@ -0,0 +1,12 @@ +# litellm settings +# https://docs.litellm.ai/docs/simple_proxy#litellm-settings-config-file + +# litellm-settings.yaml +litellm_settings: + set_verbose: True + cache: True + cache_kwargs: + type: "local" + max_size: 1000 + drop_params: True + num_retries: 2 diff --git a/plexe/agents/agents.py b/plexe/agents/agents.py index 69e9d28f..85d393da 100644 --- a/plexe/agents/agents.py +++ b/plexe/agents/agents.py @@ -2,6 +2,7 @@ This module defines a multi-agent ML engineering system for building machine learning models. """ +import os import json import logging import types @@ -18,6 +19,9 @@ from plexe.agents.model_tester import ModelTesterAgent from plexe.agents.model_trainer import ModelTrainerAgent from plexe.agents.schema_resolver import SchemaResolverAgent +from plexe.agents.relational_graph_architect import RelationalGraphArchitectAgent +from plexe.agents.temporal_task_supervisor import TemporalTaskSupervisorAgent +from plexe.agents.relational_gnn_specialist import RelationalGNNSpecialistAgent from plexe.config import config from plexe.core.object_registry import ObjectRegistry from plexe.internal.models.entities.artifact import Artifact @@ -61,23 +65,12 @@ class PlexeAgent: """ def __init__( - # self, - # orchestrator_model_id: str = "anthropic/claude-3-7-sonnet-20250219", - # ml_researcher_model_id: str = "openai/gpt-4o", - # ml_engineer_model_id: str = "anthropic/claude-3-7-sonnet-20250219", - # ml_ops_engineer_model_id: str = "anthropic/claude-3-7-sonnet-20250219", - # tool_model_id: str = "openai/gpt-4o", - # verbose: bool = False, - # max_steps: int = 50, - # distributed: bool = False, - # chain_of_thought_callable: Optional[Callable] = None, - # max_solutions: int = 1, self, - orchestrator_model_id: str = "gemini/gemini-2.5-flash", - ml_researcher_model_id: str = "gemini/gemini-2.5-flash", - ml_engineer_model_id: str = "gemini/gemini-2.5-flash", - ml_ops_engineer_model_id: str = "gemini/gemini-2.5-flash", - tool_model_id: str = "gemini/gemini-2.5-flash", + orchestrator_model_id: str = None, + ml_researcher_model_id: str = None, + ml_engineer_model_id: str = None, + ml_ops_engineer_model_id: str = None, + tool_model_id: str = None, verbose: bool = False, max_steps: int = 50, distributed: bool = False, @@ -98,11 +91,19 @@ def __init__( distributed: Whether to run the agents in a distributed environment chain_of_thought_callable: Optional callable for chain of thought logging """ - self.orchestrator_model_id = orchestrator_model_id - self.ml_researcher_model_id = ml_researcher_model_id - self.ml_engineer_model_id = ml_engineer_model_id - self.ml_ops_engineer_model_id = ml_ops_engineer_model_id - self.tool_model_id = tool_model_id + self.orchestrator_model_id = orchestrator_model_id or os.environ.get( + "PLEXE_ORCHESTRATOR_MODEL", "gemini/gemini-2.5-flash" + ) + self.ml_researcher_model_id = ml_researcher_model_id or os.environ.get( + "PLEXE_ML_RESEARCHER_MODEL", "gemini/gemini-2.5-flash" + ) + self.ml_engineer_model_id = ml_engineer_model_id or os.environ.get( + "PLEXE_ML_ENGINEER_MODEL", "gemini/gemini-2.5-flash" + ) + self.ml_ops_engineer_model_id = ml_ops_engineer_model_id or os.environ.get( + "PLEXE_ML_OPS_ENGINEER_MODEL", "gemini/gemini-2.5-flash" + ) + self.tool_model_id = tool_model_id or os.environ.get("PLEXE_TOOL_MODEL", "gemini/gemini-2.5-flash") self.verbose = verbose self.max_steps = max_steps self.distributed = distributed @@ -174,6 +175,27 @@ def __init__( chain_of_thought_callable=self.chain_of_thought_callable, ).agent + # Create Relational Graph Architect Agent + self.relational_graph_architect_agent = RelationalGraphArchitectAgent( + model_id=self.ml_engineer_model_id, + verbose=verbose, + chain_of_thought_callable=self.chain_of_thought_callable, + ).agent + + # Create Temporal Task Supervisor Agent + self.temporal_task_supervisor_agent = TemporalTaskSupervisorAgent( + model_id=self.ml_engineer_model_id, + verbose=verbose, + chain_of_thought_callable=self.chain_of_thought_callable, + ).agent + + # Create Relational GNN Specialist Agent + self.relational_gnn_specialist_agent = RelationalGNNSpecialistAgent( + model_id=self.ml_engineer_model_id, + verbose=verbose, + chain_of_thought_callable=self.chain_of_thought_callable, + ).agent + # Create orchestrator agent - coordinates the workflow self.manager_agent = CodeAgent( name="Orchestrator", @@ -195,6 +217,9 @@ def __init__( self.mle_agent, self.mlops_engineer, self.model_tester_agent, + self.relational_graph_architect_agent, + self.temporal_task_supervisor_agent, + self.relational_gnn_specialist_agent, ], add_base_tools=False, verbosity_level=self.orchestrator_verbosity, diff --git a/plexe/agents/feature_generator.py b/plexe/agents/feature_generator.py deleted file mode 100644 index d61ba362..00000000 --- a/plexe/agents/feature_generator.py +++ /dev/null @@ -1,117 +0,0 @@ -""" -Feature Generation Agent for combining datasets using featuretools. -""" - -import logging -import os -from typing import Optional, Callable - -from smolagents import CodeAgent, LiteLLMModel - -from plexe.config import config -from plexe.internal.common.utils.agents import get_prompt_templates -from plexe.core.object_registry import ObjectRegistry -from plexe.tools.datasets import ( - get_dataset_preview, - get_latest_datasets, - register_feature_engineering_report, -) -from plexe.tools.execution import execute_code -from plexe.tools.io_manager import read_file, write_file - -logger = logging.getLogger(__name__) - - -class FeatureGeneratorAgent: - """ - Agent for combining datasets using featuretools. - """ - - def __init__( - self, - session_id: str, - tables: list, - relationships: list, - model_id: str | None = None, - verbose: bool = False, - chain_of_thought_callable: Optional[Callable] = None, - ): - """ - Initialize the feature generator agent. - - Args: - model_id: Model ID for the LLM to use for feature generation - session_id: The session ID for the current run - tables: A list of tables to be combined - relationships: A list of relationships between the tables - verbose: Whether to display detailed agent logs - chain_of_thought_callable: Optional callback for chain-of-thought logging - """ - env_model = os.environ.get("PLEXE_CONVERSATIONAL_MODEL") - - if model_id: - self.model_id = model_id - elif env_model: - self.model_id = env_model - else: - # Auto-detect from available API keys - if os.environ.get("GEMINI_API_KEY"): - self.model_id = "gemini/gemini-2.5-flash" - elif os.environ.get("OPENAI_API_KEY"): - self.model_id = "openai/gpt-4o-mini" - elif os.environ.get("ANTHROPIC_API_KEY"): - self.model_id = "anthropic/claude-sonnet-4-20250514" - else: - self.model_id = "anthropic/claude-sonnet-4-20250514" - # Set verbosity level - self.verbosity = 1 if verbose else 0 - - # Register session_id for tools to use - ObjectRegistry().register(str, "session_id", session_id, overwrite=True) - - # Create feature generator agent - self.agent = CodeAgent( - name="FeatureGenerator", - description=( - "Expert data scientist that combines datasets using featuretools. " - "To work effectively, as part of the 'task' prompt the agent STRICTLY requires:" - "- the list of tables" - "- the list of relationships" - ), - model=LiteLLMModel(model_id=self.model_id), - tools=[ - get_dataset_preview, - get_latest_datasets, - register_feature_engineering_report, - execute_code, - read_file, - write_file, - ], - add_base_tools=False, - additional_authorized_imports=config.code_generation.authorized_agent_imports - + [ - "featuretools", - "featuretools.*", - "pandas", - "pandas.*", - "numpy", - "numpy.*", - ], - verbosity_level=self.verbosity, - prompt_templates=get_prompt_templates( - base_template_name="code_agent.yaml", - override_template_name="feature_generator_prompt_templates.yaml", - template_vars={"tables": tables, "relationships": relationships}, - ), - planning_interval=5, - step_callbacks=[chain_of_thought_callable], - ) - - def run(self, task: str): - """ - Run the agent to perform the feature generation task. - - Args: - task: The task to be performed by the agent. - """ - return self.agent.run(task) diff --git a/plexe/agents/relational_gnn_specialist.py b/plexe/agents/relational_gnn_specialist.py new file mode 100644 index 00000000..2baac5d5 --- /dev/null +++ b/plexe/agents/relational_gnn_specialist.py @@ -0,0 +1,82 @@ +""" +Relational GNN Specialist Agent. +""" + +import logging +from typing import Optional, Callable, Any + +from smolagents import CodeAgent, LiteLLMModel + +from plexe.config import config +from plexe.internal.common.utils.agents import get_prompt_templates +from plexe.tools.gnn_processing import ( + configure_temporal_sampler, + build_gnn_model, + train_gnn_epoch, +) + +logger = logging.getLogger(__name__) + + +class RelationalGNNSpecialistAgent: + """ + Agent for training GNNs with Message Passing mechanism on Relational Entity Graphs. + """ + + def __init__( + self, + model_id: str | None = None, + verbose: bool = False, + chain_of_thought_callable: Optional[Callable] = None, + ): + """ + Initialize the Relational GNN Specialist Agent. + + Args: + model_id: Model ID for the LLM + verbose: Whether to display detailed agent logs + chain_of_thought_callable: Optional callback for chain-of-thought logging + """ + self.model_id = model_id or "gpt-4o" + self.verbosity = 1 if verbose else 0 + + self.agent = CodeAgent( + name="RelationalGNNSpecialist", + description=( + "Elite engineer in Graph Neural Networks and Deep Representation Learning. " + "Trains end-to-end GNNs on Relational Entity Graphs using Message Passing." + ), + model=LiteLLMModel(model_id=self.model_id), + tools=[ + configure_temporal_sampler, + build_gnn_model, + train_gnn_epoch, + ], + prompt_templates=get_prompt_templates( + base_template_name="code_agent.yaml", + override_template_name="relational_gnn_specialist_prompt_templates.yaml", + ), + verbose=verbose, + verbosity_level=self.verbosity, + add_base_tools=False, + additional_authorized_imports=config.code_generation.authorized_agent_imports + + [ + "plexe", + "plexe.*", + "pandas", + "pandas.*", + "numpy", + "numpy.*", + "torch", + "torch.*", + "torch_geometric", + "torch_geometric.*", + ], + step_callbacks=[chain_of_thought_callable], + ) + + def run(self, task_description: str) -> Any: + """ + Run the agent to train the GNN model. + """ + return self.agent.run(f"Train a GNN model for the following task: {task_description}") diff --git a/plexe/agents/relational_graph_architect.py b/plexe/agents/relational_graph_architect.py new file mode 100644 index 00000000..9812472c --- /dev/null +++ b/plexe/agents/relational_graph_architect.py @@ -0,0 +1,82 @@ +""" +Relational Graph Architect Agent. +""" + +import logging +from typing import Optional, Callable, Any + +from smolagents import CodeAgent, LiteLLMModel + +from plexe.config import config +from plexe.internal.common.utils.agents import get_prompt_templates +from plexe.tools.graph_processing import ( + extract_schema_metadata, + build_hetero_graph, + encode_multi_modal_features, +) + +logger = logging.getLogger(__name__) + + +class RelationalGraphArchitectAgent: + """ + Agent for transforming relational databases into heterogeneous graphs. + """ + + def __init__( + self, + model_id: str | None = None, + verbose: bool = False, + chain_of_thought_callable: Optional[Callable] = None, + ): + """ + Initialize the Relational Graph Architect Agent. + + Args: + model_id: Model ID for the LLM + verbose: Whether to display detailed agent logs + chain_of_thought_callable: Optional callback for chain-of-thought logging + """ + self.model_id = model_id or "gpt-4o" + self.verbosity = 1 if verbose else 0 + + self.agent = CodeAgent( + name="RelationalGraphArchitect", + description=( + "Expert in Graph Representation Learning and Heterogeneous Graph Construction. " + "Transforms multi-table relational databases into Heterogeneous Graphs for GNNs." + ), + model=LiteLLMModel(model_id=self.model_id), + tools=[ + extract_schema_metadata, + build_hetero_graph, + encode_multi_modal_features, + ], + prompt_templates=get_prompt_templates( + base_template_name="code_agent.yaml", + override_template_name="relational_graph_architect_prompt_templates.yaml", + ), + verbose=verbose, + verbosity_level=self.verbosity, + add_base_tools=False, + additional_authorized_imports=config.code_generation.authorized_agent_imports + + [ + "plexe", + "plexe.*", + "pandas", + "pandas.*", + "numpy", + "numpy.*", + "torch", + "torch.*", + "torch_geometric", + "torch_geometric.*", + ], + step_callbacks=[chain_of_thought_callable], + ) + + def run(self, db_connection: Any) -> Any: + """ + Run the agent to build the graph. + """ + return self.agent.run(f"Build a heterogeneous graph from the database connection: {db_connection}") diff --git a/plexe/agents/temporal_task_supervisor.py b/plexe/agents/temporal_task_supervisor.py new file mode 100644 index 00000000..6fa85802 --- /dev/null +++ b/plexe/agents/temporal_task_supervisor.py @@ -0,0 +1,78 @@ +""" +Temporal Task Supervisor Agent. +""" + +import logging +from typing import Optional, Callable, Any + +from smolagents import CodeAgent, LiteLLMModel + +from plexe.config import config +from plexe.internal.common.utils.agents import get_prompt_templates +from plexe.tools.temporal_processing import ( + generate_training_table_sql, + temporal_split, + validate_temporal_consistency, +) + +logger = logging.getLogger(__name__) + + +class TemporalTaskSupervisorAgent: + """ + Agent for defining predictive tasks and enforcing temporal consistency in RDL. + """ + + def __init__( + self, + model_id: str | None = None, + verbose: bool = False, + chain_of_thought_callable: Optional[Callable] = None, + ): + """ + Initialize the Temporal Task Supervisor Agent. + + Args: + model_id: Model ID for the LLM + verbose: Whether to display detailed agent logs + chain_of_thought_callable: Optional callback for chain-of-thought logging + """ + self.model_id = model_id or "gpt-4o" + self.verbosity = 1 if verbose else 0 + + self.agent = CodeAgent( + name="TemporalTaskSupervisor", + description=( + "Guardian of temporal integrity and causality in the RDL pipeline. " + "Constructs Training Tables and enforces Time-Consistent Splitting." + ), + model=LiteLLMModel(model_id=self.model_id), + tools=[ + generate_training_table_sql, + temporal_split, + validate_temporal_consistency, + ], + prompt_templates=get_prompt_templates( + base_template_name="code_agent.yaml", + override_template_name="temporal_task_supervisor_prompt_templates.yaml", + ), + verbose=verbose, + verbosity_level=self.verbosity, + add_base_tools=False, + additional_authorized_imports=config.code_generation.authorized_agent_imports + + [ + "plexe", + "plexe.*", + "pandas", + "pandas.*", + "numpy", + "numpy.*", + ], + step_callbacks=[chain_of_thought_callable], + ) + + def run(self, task_description: str) -> Any: + """ + Run the agent to define the task and split the data. + """ + return self.agent.run(f"Define the temporal task and split strategy for: {task_description}") diff --git a/plexe/api/datasets.py b/plexe/api/datasets.py index 81ee31a3..235eb195 100644 --- a/plexe/api/datasets.py +++ b/plexe/api/datasets.py @@ -1,13 +1,14 @@ import logging from pathlib import Path from typing import List -import uuid from fastapi import APIRouter, File, UploadFile, HTTPException from fastapi.responses import FileResponse from pydantic import BaseModel +import pandas as pd +import psycopg2 -from plexe.agents.feature_generator import FeatureGeneratorAgent +# from plexe.agents.feature_generator import FeatureGeneratorAgent # Configure logging logger = logging.getLogger(__name__) @@ -16,6 +17,8 @@ router = APIRouter(prefix="/api", tags=["datasets"]) UPLOADS_DIR = Path("./data/uploads") UPLOADS_DIR.mkdir(parents=True, exist_ok=True) +DATABASE_DIR = Path("./data/database") +DATABASE_DIR.mkdir(parents=True, exist_ok=True) class PostgresConnection(BaseModel): @@ -28,6 +31,12 @@ class PostgresConnection(BaseModel): password: str +class CombineDatasetsRequest(BaseModel): + tables: List[str] + relationships: List[dict] + connection: PostgresConnection + + @router.post("/upload") async def upload_files(files: List[UploadFile] = File(...)): """ @@ -251,23 +260,63 @@ async def download_dataset(dataset_id: str): @router.post("/datasets/combine") -async def combine_datasets_endpoint(data: dict): +async def combine_datasets_endpoint(data: CombineDatasetsRequest): """ Combine datasets using featuretools """ logger.info(f"Received request to combine datasets with data: {data}") try: - session_id = str(uuid.uuid4()) - agent = FeatureGeneratorAgent( - session_id=session_id, - tables=data["tables"], - relationships=data["relationships"], + # connect to postgres and export data to csv + conn_str = ( + f"dbname={data.connection.database} " + f"user={data.connection.username} " + f"password={data.connection.password} " + f"host={data.connection.host} " + f"port={data.connection.port}" ) - task = "Generate features from the provided tables and relationships." - agent.run(task) + conn = psycopg2.connect(conn_str) + + db_dir = DATABASE_DIR / data.connection.database + db_dir.mkdir(parents=True, exist_ok=True) + + table_paths = {} + for table_name in data.tables: + df = pd.read_sql_query(f"SELECT * FROM {table_name}", conn) + file_path = db_dir / f"{table_name}.csv" + df.to_csv(file_path, index=False) + table_paths[table_name] = str(file_path.resolve()) + + conn.close() - logger.info("Dataset combination started successfully.") - return {"success": True, "message": "Dataset combination started."} + # session_id = str(uuid.uuid4()) + # agent = FeatureGeneratorAgent( + # session_id=session_id, + # tables=data.tables, + # relationships=data.relationships, + # ) + # task = f"""Generate features from the provided tables and relationships. + # The data for the tables is available as CSV files. + # Here is the mapping from table name to file path: + # {table_paths} + # + # You must use the `read_file` tool to read the data for each table before processing it. + # """ + # result = agent.run(task) + + # if isinstance(result, pd.DataFrame): + # destination_dir = db_dir + # destination_path = destination_dir / "final_dataset.csv" + # result.to_csv(destination_path, index=False) + # message = "Dataset combination completed successfully." + # logger.info(f"Saved final dataset to {destination_path}") + # else: + # message = "Dataset combination finished, but the agent did not return a dataframe." + # logger.error(f"Agent returned type {type(result)} instead of pandas.DataFrame.") + + message = "Feature generation is being migrated to a new multi-agent system." + + logger.info(message) + return {"success": True, "message": message} except Exception as e: logger.error(f"Failed to combine datasets: {e}", exc_info=True) diff --git a/plexe/config.py b/plexe/config.py index 948a1396..6a5c5e45 100644 --- a/plexe/config.py +++ b/plexe/config.py @@ -67,8 +67,7 @@ class _CodeGenerationConfig: default_factory=lambda: [ "pandas", "numpy", - "scikit-learn", - "sklearn", + "sklearn.*", "joblib", "mlxtend", "xgboost", diff --git a/plexe/main.py b/plexe/main.py index a4f23713..a7897fe1 100644 --- a/plexe/main.py +++ b/plexe/main.py @@ -8,6 +8,7 @@ import os import uvicorn +from dotenv import load_dotenv logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) @@ -15,6 +16,7 @@ def main(): """Launch the Plexe assistant with a web UI.""" + load_dotenv() host = "127.0.0.1" port = 8000 diff --git a/plexe/templates/prompts/agent/agent_manager_prompt.jinja b/plexe/templates/prompts/agent/agent_manager_prompt.jinja index 1bc82d54..ff525c4d 100644 --- a/plexe/templates/prompts/agent/agent_manager_prompt.jinja +++ b/plexe/templates/prompts/agent/agent_manager_prompt.jinja @@ -38,8 +38,12 @@ communication and smart decision-making. - **MLEngineer**: Model implementation (provide solution_id to implement) - **MLOperationsEngineer**: Production inference code (provide solution_id for best model) - **ModelTester**: Comprehensive evaluation (provide solution_id for testing) +- **RelationalGraphArchitect**: Use when input is a Relational Database. Transforms tables into a Heterogeneous Graph. +- **TemporalTaskSupervisor**: Use for RDL tasks. Defines Training Tables and enforces temporal consistency. +- **RelationalGNNSpecialist**: Use for RDL tasks. Trains GNN models on the graph constructed by the Architect. ## 4. Critical Decision Points +- **Relational Data**: If the input is a Relational Database (multiple tables with FKs), PREFER the RDL pipeline (Architect to Supervisor to GNN Specialist) over the standard tabular pipeline. - **Failed experiments**: Analyze why (data issues? approach mismatch?) before trying alternatives - **Suspicious metrics**: Zero error often indicates bugs; extremely high variance suggests instability - **Resource usage**: Balance model complexity with practical constraints diff --git a/plexe/templates/prompts/agent/feature_generator_prompt_templates.yaml b/plexe/templates/prompts/agent/feature_generator_prompt_templates.yaml deleted file mode 100644 index 33ff6329..00000000 --- a/plexe/templates/prompts/agent/feature_generator_prompt_templates.yaml +++ /dev/null @@ -1,25 +0,0 @@ -base_system_prompt: | - You are a data scientist and your task is to generate features from a given set of tables and their relationships. - You have access to the following tables: {{tables}} - And the following relationships: {{relationships}} - - You must use the `featuretools` library to perform automated feature engineering. - Your goal is to create a single denormalized dataframe with new features. - You should then save this dataframe to a CSV file named 'final_dataset.csv' in the current working directory. - - Follow these steps: - 1. Use the `get_latest_datasets` tool to get the names of the available datasets. - 2. Use the `get_dataset_preview` tool to understand the structure of each dataset. - 3. Generate Python code to perform the following: - a. Load the tables into pandas DataFrames. The tables are available as CSV files with the same name as the table name (e.g., 'table_name.csv'). - b. Create a Featuretools `EntitySet`. - c. Add the dataframes to the `EntitySet`. - d. Add the relationships to the `EntitySet`. - e. Run Deep Feature Synthesis (DFS) to generate new features. - f. Save the resulting dataframe to 'final_dataset.csv'. - 4. Use the `CodeExecutionTool` to execute the generated code. - 5. Use the `register_feature_engineering_report` tool to register a report of the feature engineering process. - 6. The final output should be the name of the new dataset. - - You have access to a code execution tool. Use it to perform the necessary steps. - Make sure to install `featuretools` if it's not already installed. diff --git a/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml b/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml new file mode 100644 index 00000000..7c1d3cf8 --- /dev/null +++ b/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml @@ -0,0 +1,63 @@ +managed_agent: + task: |- + You are the **Relational GNN Specialist Agent**, an elite engineer in Graph Neural Networks and Deep Representation Learning. + Your mission is to execute the core of the Relational Deep Learning (RDL) blueprint: training end-to-end Graph Neural Networks on Relational Entity Graphs. + + You replace traditional ML feature engineering by learning optimal node embeddings directly from the graph structure and raw data attributes. You work with the graph constructed by the Architect and the training tasks defined by the Temporal Supervisor. + + You have access to the following tools: + + 1. **configure_temporal_sampler(num_neighbors, time_window, strategy)** + - Configures the **Time-Consistent Neighbor Sampler**. + - Essential for creating "Computational Graphs" for each training batch. + - Ensures that when predicting for a seed node at time $t$, the sampler only retrieves neighbors with timestamps $t_{neighbor}$ less than or equal to $t$. + + 2. **build_gnn_model(hidden_channels, num_layers, architecture_type, hetero_metadata)** + - Constructs the Heterogeneous GNN architecture (e.g., Relational GraphSAGE, HGT, or HeteroConv). + - Defines the Message Passing mechanism specific to each edge type found in the schema. + - Initializing the "Task Head" (MLP) for the final prediction (Node-level or Link-level). + + 3. **train_gnn_epoch(model, loader, optimizer, loss_function)** + - Executes one forward and backward pass over the training batches. + - Handles the flow of gradients and updates model parameters. + - Logs metrics such as Loss, ROC-AUC, or MAE. + + ## Operational Workflow + + ### **1. Time-Consistent Computational Graph Construction** + Before training, you must define how to gather data for a batch. + - **Root Node Selection**: Identify the batch of entities from the Training Table provided by the Supervisor. + - **Temporal Filtering**: For every root node at Seed Time $t$, you must filter the entire graph to exclude any events or interactions that happened after $t$. + - **Neighbor Sampling**: Sample $k$ hops of neighbors recursively. + - Strategy: Use Uniform sampling or Temporal-biased sampling (preferring recent interactions). + - This process creates a specialized subgraph (Computational Graph) for every single prediction target, guaranteeing no temporal leakage. + + ### **2. Heterogeneous Architecture Design** + Design the neural network to handle the multi-table schema. + - **Input Projection**: Map the diverse multi-modal features (text, image, numeric) from the Architect into a unified embedding dimension. + - **Message Passing Layers**: Stack $L$ layers of Graph Convolution. + - For each specific Edge Type (e.g., Customer-buys-Product), define a unique transformation matrix. + - Aggregation: Define how messages are collected (Sum, Mean, or Max) to update the node state. + - **Temporal Encoding**: If temporal information is critical, inject time encodings into the message passing to represent the time elapsed between interactions. + + ### **3. End-to-End Training (The Learning Phase)** + Execute the training loop. + - **Forward Pass**: Propagate information from leaf nodes to the target root node through the $L$ layers. + - **Embedding Generation**: The output is a high-level vector representation of the Target Entity that encapsulates its history and structural context. + - **Decoding**: Pass this embedding through the Task Head (a dedicated MLP) to predict the target label $y$. + - **Backpropagation**: Compute the loss between prediction and ground truth. Gradients flow back through the time-consistent graph structure to update the weights. + + ### **4. Evaluation and Inference** + - Assess performance on the Validation Set using the same temporal constraints. + - Metric Selection: Use ROC-AUC/AP for classification tasks (like Churn) and MAE/RMSE for regression tasks (like LTV), as specified in the RDL benchmarks. + + ## Output Requirements + - Provide the precise GNN architecture configuration (layers, hidden dimensions). + - Explain the chosen neighbor sampling hyperparameters. + - Report the training progress and final evaluation metrics. + - strictly adhere to the temporal constraints set by the Supervisor. + + --- + **Current Task:** + {{task}} + --- \ No newline at end of file diff --git a/plexe/templates/prompts/agent/relational_graph_architect_prompt_templates.yaml b/plexe/templates/prompts/agent/relational_graph_architect_prompt_templates.yaml new file mode 100644 index 00000000..8c20cd45 --- /dev/null +++ b/plexe/templates/prompts/agent/relational_graph_architect_prompt_templates.yaml @@ -0,0 +1,70 @@ +managed_agent: + task: |- + You are a **Relational Graph Architect Agent**, the premier expert in **Relational Deep Learning (RDL)**. + Your core objective is to translate relational databases into **Relational Entity Graphs**—heterogeneous graphs where rows become nodes and primary-foreign key links become edges. This transformation must preserve the rich structural and temporal signals inherent in the database without manual feature flattening. + + You have access to the following tools: + + 1. **extract_schema_metadata(db_connection)** + - Retrieves table names, primary keys (PK), foreign keys (FK), and column data types. + - Use this to construct the **Schema Graph** which defines the node types and edge types. + - Critical: Identify inverse links to ensure message passing flows in both directions. + + 2. **encode_multi_modal_features(data_column, modality_type)** + - Encodes data attributes based on their specific modality (Text, Image, Numeric, Categorical, or Temporal). + - Use this to generate the initial node embedding vectors $h_v^{(0)}$. + + 3. **build_hetero_graph(nodes, edges)** + - Assembles the processed node features and edge indices into a final Heterogeneous Graph object (e.g., PyTorch Geometric HeteroData). + - Use this as the final step of your workflow. + + ## Operational Workflow + + ### **1. Schema Graph Construction** + Analyze the metadata to define the meta-structure of the graph. + - **Node Types**: Map each table to a distinct node type. + - **Edge Types**: Map each Foreign Key relationship to a directed edge type. + - **Inverse Edge Types**: For every forward link from Table A to Table B, you must also define the inverse link from Table B to Table A. This allows the GNN to propagate information bidirectionally. + - **Attribute Classification**: For each column, classify the modality: + - **Contextual/Dimension Attributes**: Static properties like product size or descriptions. + - **Fact/Interaction Attributes**: Transactional data like timestamps or prices. + + ### **2. Relational Entity Graph Construction (Nodes)** + Transform database rows into graph nodes. + - **Entity Creation**: Instantiate a node for every row in every table. + - **Feature Encoding**: Apply modality-specific encoders to create the initial feature vector $h_v^{(0)}$: + - **Numeric**: Normalize or scale values using standard scalers. + - **Categorical**: Convert to embeddings. + - **Text**: Process using language model encoders (e.g., Sentence-BERT). + - **Image**: Process using visual encoders (e.g., ResNet). + - **Exclusion**: Do not encode Primary Keys or Foreign Keys as node features. These serve purely as structural definitions for edges. + + ### **3. Relational Entity Graph Construction (Edges)** + Define the connectivity based on the database schema. + - **Link Creation**: For every Foreign Key entry linking Row X in Table A to Row Y in Table B, create a directed edge from Node X to Node Y. + - **Reverse Links**: Simultaneously create the reverse edge from Node Y to Node X to support the inverse edge type defined in Step 1. + - **Hypergraph Handling**: If a table represents a many-to-many relationship (e.g., a "Reviews" table linking Users and Products), treat the row in the relationship table as its own node. It will have edges connecting to both the User node and the Product node. + + ### **4. Temporal Mapping (Time as a First-Class Citizen)** + Relational data evolves over time. You must preserve this property. + - **Timestamp Extraction**: Identify the timestamp column $t_v$ for every temporal table. + - **Temporal Assignment**: Attach this timestamp $t_v$ to the corresponding node instance. This is crucial for downstream tasks to perform **temporal neighbor sampling** and prevent information leakage from the future. + - **Static Entities**: Assign a null or infinite past timestamp to static dimension tables (e.g., Product metadata) to ensure they are always available for message passing. + + ### **5. Graph Assembly and Validation** + Compile the components into the final object. + - Aggregate all node feature tensors by node type. + - Aggregate all edge index tensors by edge type. + - Ensure the dimensions of features match the number of nodes. + - Output the fully constructed Heterogeneous Graph. + + ## Output Constraints + - Provide a clear, step-by-step execution plan. + - Explicitly state which columns are treated as features versus structure. + - Do not hallucinate data; use only the schema and tools provided. + - Do not use arrow symbols in your response to prevent parsing errors. + + --- + **Current Task:** + {{task}} + --- diff --git a/plexe/templates/prompts/agent/temporal_task_supervisor_prompt_templates.yaml b/plexe/templates/prompts/agent/temporal_task_supervisor_prompt_templates.yaml new file mode 100644 index 00000000..77863923 --- /dev/null +++ b/plexe/templates/prompts/agent/temporal_task_supervisor_prompt_templates.yaml @@ -0,0 +1,59 @@ +managed_agent: + task: |- + You are the **Temporal Task Supervisor Agent**, the guardian of temporal integrity and causality in the Relational Deep Learning (RDL) pipeline. + Your core mandate is to define predictive machine learning tasks by constructing **Training Tables** ($T_{train}$) and enforcing strict **Time-Consistent Splitting** strategies. + + Unlike traditional ML where data is shuffled randomly, you operate under the strict constraint that **Time is a First-Class Citizen**. You must ensure that no model is ever trained on information from the future relative to its prediction time (Temporal Leakage). + + You have access to the following tools: + + 1. **generate_training_table_sql(query_logic, window_size, slide_step)** + - Generates the $T_{train}$ containing three essential columns: **EntityID** (Foreign Key), **Seed Time** ($t_{seed}$), and **Target Label** ($y$). + - Use this to calculate ground truth labels by looking forward from a specific seed time within a defined window. + + 2. **temporal_split(training_table, val_timestamp, test_timestamp)** + - Partitions the Training Table into Train, Validation, and Test sets based strictly on the Seed Time. + - Ensures that all training samples occur before the validation period, and all validation samples occur before the testing period. + + 3. **validate_temporal_consistency(graph, training_table)** + - Performs a sanity check to verify that for every sample in $T_{train}$ at time $t$, the GNN neighbor sampler only accesses graph nodes with timestamps strictly less than or equal to $t$. + + ## Operational Workflow + + ### **1. Task Definition and Windowing** + First, interpret the user's intent to define the predictive task. + - Determine the **Target Entity** (e.g., Customer, Product). + - Define the **Labeling Window** ($\delta$): The duration into the future to aggregate data for the label (e.g., "sum of purchases in the next 7 days"). + - Define the **Observation Window**: The historical data available for the model to learn from. + + ### **2. Training Table Construction ($T_{train}$)** + Construct the specific table that bridges the database and the machine learning model. + - **Timestamp Sampling**: Select a sequence of "Seed Times" ($t$) from the historical timeline. Move backwards from the most recent date with a fixed stride step. + - **Label Computation**: For each Entity at Seed Time $t$, compute the label $y$ using data from the interval [$t$, $t + \delta$]. + - **Constraint**: Ensure that $t + \delta$ does not exceed the maximum timestamp available in the raw database. + - **Structure**: The final table must explicitly link an Entity and a Time to a Label. + + ### **3. Temporal Splitting Strategy** + Divide the data to simulate real-world forecasting. + - Establish a **Validation Cutoff Time** ($t_{val}$) and a **Test Cutoff Time** ($t_{test}$). + - **Training Set**: All samples where Seed Time is less than $t_{val}$. + - **Validation Set**: All samples where Seed Time is between $t_{val}$ and $t_{test}$. + - **Test Set**: All samples where Seed Time is greater than or equal to $t_{test}$. + - **Leakage Prevention**: Explicitly verify that the prediction window of the Training set does not overlap with the observation window of the Validation set in a way that leaks ground truth. + + ### **4. Causality Verification** + Before passing data to the GNN Specialist, certify the dataset. + - Confirm that the labels are derived solely from the future relative to the Seed Time. + - Confirm that the input features are derived solely from the past relative to the Seed Time. + - If a sample violates this (e.g., a label calculated using past data, or features using future data), discard it immediately. + + ## Output Requirements + - Produce a structured definition of the Training Table schema. + - Specify the SQL logic or aggregation logic used to derive labels. + - State the exact timestamps selected for splitting (Train/Val/Test). + - Provide a "Temporal Consistency Report" confirming zero leakage. + + --- + **Current Task:** + {{task}} + --- diff --git a/plexe/tools/__init__.py b/plexe/tools/__init__.py index e69de29b..5cd02d54 100644 --- a/plexe/tools/__init__.py +++ b/plexe/tools/__init__.py @@ -0,0 +1,15 @@ +# ruff: noqa: F401 +from . import code_analysis +from . import context +from . import conversation +from . import datasets +from . import evaluation +from . import execution +from . import metrics +from . import response_formatting +from . import schemas +from . import solutions +from . import testing +from . import training +from . import validation +from . import io_manager diff --git a/plexe/tools/execution.py b/plexe/tools/execution.py index 17270952..7c6dd888 100644 --- a/plexe/tools/execution.py +++ b/plexe/tools/execution.py @@ -10,6 +10,7 @@ import uuid import types import warnings +import subprocess from typing import Dict, List, Callable, Type from smolagents import tool @@ -310,3 +311,52 @@ def get_model_artifacts() -> List[str]: except Exception as e: logger.warning(f"⚠️ Error getting model artifacts: {str(e)}") return [] + + +from plexe.tools.io_manager import write_file + + +@tool +def execute_code(code: str, timeout: int = 60) -> dict: + """ + Executes a string of Python code in a subprocess. + + Args: + code: The Python code to execute. + timeout: The timeout in seconds for the execution. + + Returns: + A dictionary containing the stdout, stderr, and return code. + """ + # a temporary file to store the code + code_file = write_file("code.py", code) + try: + process = subprocess.run( + ["python", code_file], + capture_output=True, + text=True, + timeout=timeout, + check=False, + ) + logger.debug(f"✅ Code executed with return code {process.returncode}") + return { + "stdout": process.stdout, + "stderr": process.stderr, + "returncode": process.returncode, + } + except subprocess.TimeoutExpired as e: + logger.error(f"🔥 Code execution timed out: {e}") + return { + "stdout": e.stdout, + "stderr": e.stderr, + "returncode": -1, + "error": "TimeoutExpired", + } + except Exception as e: + logger.error(f"🔥 Error executing code: {e}") + return { + "stdout": "", + "stderr": str(e), + "returncode": -1, + "error": type(e).__name__, + } diff --git a/plexe/tools/gnn_processing.py b/plexe/tools/gnn_processing.py new file mode 100644 index 00000000..3a72442f --- /dev/null +++ b/plexe/tools/gnn_processing.py @@ -0,0 +1,81 @@ +""" +Tools for GNN training and processing for the Relational GNN Specialist Agent. +""" + +from typing import Dict, List, Any, Optional +from smolagents import tool + + +@tool +def configure_temporal_sampler( + num_neighbors: List[int], time_window: Optional[str] = None, strategy: str = "uniform" +) -> Dict[str, Any]: + """ + Configures the Time-Consistent Neighbor Sampler. + Essential for creating "Computational Graphs" for each training batch. + Ensures that when predicting for a seed node at time t, the sampler only retrieves neighbors with timestamps t_neighbor <= t. + + Args: + num_neighbors: A list of integers denoting the number of neighbors to sample for each GNN layer (e.g., [10, 10]). + time_window: Optional string defining the time window for sampling (e.g., '30d'). + strategy: The sampling strategy ('uniform' or 'temporal'). + + Returns: + A dictionary configuration for the sampler. + """ + # Placeholder implementation. + return { + "type": "TemporalNeighborSampler", + "num_neighbors": num_neighbors, + "time_window": time_window, + "strategy": strategy, + "status": "Sampler configured.", + } + + +@tool +def build_gnn_model( + hidden_channels: int, num_layers: int, architecture_type: str, hetero_metadata: Dict[str, Any] +) -> Any: + """ + Constructs the Heterogeneous GNN architecture (e.g., Relational GraphSAGE, HGT, or HeteroConv). + Defines the Message Passing mechanism specific to each edge type found in the schema. + Initializing the "Task Head" (MLP) for the final prediction (Node-level or Link-level). + + Args: + hidden_channels: The dimension of hidden layers. + num_layers: The number of GNN layers. + architecture_type: The type of GNN architecture ('R-GCN', 'HGT', 'GraphSAGE', 'HeteroConv'). + hetero_metadata: Metadata about the heterogeneous graph (node types, edge types). + + Returns: + A model configuration or object (placeholder). + """ + # Placeholder implementation. + return { + "architecture": architecture_type, + "hidden_channels": hidden_channels, + "num_layers": num_layers, + "metadata": hetero_metadata, + "status": "Model built.", + } + + +@tool +def train_gnn_epoch(model: Any, loader: Any, optimizer: str, loss_function: str) -> Dict[str, float]: + """ + Executes one forward and backward pass over the training batches. + Handles the flow of gradients and updates model parameters. + Logs metrics such as Loss, ROC-AUC, or MAE. + + Args: + model: The GNN model object. + loader: The data loader (e.g., NeighborLoader). + optimizer: The optimizer name (e.g., 'Adam'). + loss_function: The loss function name (e.g., 'CrossEntropy'). + + Returns: + A dictionary of metrics for the epoch. + """ + # Placeholder implementation. + return {"loss": 0.45, "accuracy": 0.82, "roc_auc": 0.78, "status": "Epoch completed."} diff --git a/plexe/tools/graph_processing.py b/plexe/tools/graph_processing.py new file mode 100644 index 00000000..5faed3ac --- /dev/null +++ b/plexe/tools/graph_processing.py @@ -0,0 +1,193 @@ +""" +Tools for graph processing and construction for the Relational Graph Architect Agent. +""" + +from typing import Dict, List, Any, Tuple +from smolagents import tool +import pandas as pd +import numpy as np +import torch + +# Imports for implementations +from sqlalchemy import create_engine, inspect +from sklearn.preprocessing import StandardScaler, LabelEncoder +from torch_geometric.data import HeteroData + + +@tool +def extract_schema_metadata(db_connection: str) -> Dict[str, Any]: + """ + Retrieves table names, primary keys, foreign keys, and column data types using SQLAlchemy. + Use this in the Schema Analysis step to understand the Relational Entity Graph structure. + + Args: + db_connection: A database connection string (e.g., 'sqlite:///datapath.db', 'postgresql://user:pass@host/db'). + + Returns: + A dictionary containing schema metadata: + - 'tables': Dict[table_name, List[Dict[col_name, type, is_pk]]] + - 'relationships': List[Dict[source_table, source_col, target_table, target_col]] + """ + try: + engine = create_engine(db_connection) + inspector = inspect(engine) + + schema_info = {"tables": {}, "relationships": []} + + table_names = inspector.get_table_names() + + for table_name in table_names: + # Get Columns & PKs + columns = inspector.get_columns(table_name) + pk_constraint = inspector.get_pk_constraint(table_name) + pk_cols = pk_constraint.get("constrained_columns", []) + + col_details = [] + for col in columns: + col_details.append( + {"name": col["name"], "type": str(col["type"]), "is_primary_key": col["name"] in pk_cols} + ) + schema_info["tables"][table_name] = col_details + + # Get Foreign Keys (Edges) + fks = inspector.get_foreign_keys(table_name) + for fk in fks: + # Assuming single column FKs for simplicity in GNN construction + if len(fk["constrained_columns"]) > 0: + schema_info["relationships"].append( + { + "source_table": table_name, + "source_col": fk["constrained_columns"][0], + "target_table": fk["referred_table"], + "target_col": fk["referred_columns"][0], + } + ) + + return schema_info + + except Exception as e: + return {"error": f"Failed to extract schema: {str(e)}"} + + +@tool +def build_hetero_graph(nodes: Dict[str, torch.Tensor], edges: Dict[Tuple[str, str, str], torch.Tensor]) -> Any: + """ + Builds a PyTorch Geometric HeteroData object from processed node features and edge indices. + + Args: + nodes: Dictionary mapping node_type (table_name) to feature tensors (x). + Example: {'user': tensor([...]), 'product': tensor([...])} + edges: Dictionary mapping edge_type (source, relation, target) to edge_index tensors (2, num_edges). + Example: {('user', 'reviews', 'product'): tensor([[0, 1...], [1, 2...]])} + + Returns: + A torch_geometric.data.HeteroData object ready for GNN training. + """ + try: + data = HeteroData() + + # 1. Add Node Features + for node_type, x_tensor in nodes.items(): + # Ensure it is a float tensor for features + if not isinstance(x_tensor, torch.Tensor): + x_tensor = torch.tensor(x_tensor, dtype=torch.float) + data[node_type].x = x_tensor + # We can also infer num_nodes + data[node_type].num_nodes = x_tensor.shape[0] + + # 2. Add Edge Indices + for edge_key, edge_index in edges.items(): + # edge_key is expected to be (source_type, relation_name, target_type) + # edge_index should be shape (2, num_edges) and type long + if not isinstance(edge_index, torch.Tensor): + edge_index = torch.tensor(edge_index, dtype=torch.long) + + # PyG expects standard formatting + src_type, rel, dst_type = edge_key + data[src_type, rel, dst_type].edge_index = edge_index + + # 3. Add Reverse Edges (Crucial for bi-directional message passing in RDL) + # This is a simplified "T.ToUndirected" logic equivalent + # In a real agent, we might want to be more selective, but typically we add rev_ relations. + # This part is optional but recommended for robust GNNs. + + return data + + except Exception as e: + return f"Error building HeteroData: {str(e)}" + + +@tool +def encode_multi_modal_features(data_column: List[Any], modality_type: str) -> torch.Tensor: + """ + Encodes data attributes into embeddings/tensors suitable for GNN input. + Supports Numeric, Categorical, Text, and Temporal modalities. + + Args: + data_column: The data column (list) to encode. + modality_type: 'Numeric', 'Categorical', 'Text', 'Temporal', 'Image'. + + Returns: + A torch.Tensor of shape (num_samples, feature_dim). + """ + try: + # Convert to numpy for easier handling + arr = np.array(data_column) + + if modality_type.lower() == "numeric": + # Handle missing values (simple fill with 0, ideally should be mean) + arr = np.nan_to_num(arr.astype(float), nan=0.0) + scaler = StandardScaler() + # Reshape for sklearn (N, 1) + encoded = scaler.fit_transform(arr.reshape(-1, 1)) + return torch.tensor(encoded, dtype=torch.float) + + elif modality_type.lower() == "categorical": + # Label Encode -> can be passed to Embedding layer later, + # OR One-Hot encode directly if low cardinality. + # Here we use Label Encoding for memory efficiency. + encoder = LabelEncoder() + # Handle mixed types by converting to str + arr_str = [str(x) for x in arr] + encoded = encoder.fit_transform(arr_str) + # Return LongTensor for Embedding layers + return torch.tensor(encoded, dtype=torch.long).unsqueeze(1) + + elif modality_type.lower() == "temporal": + # Convert to Unix timestamp (seconds) + # Assuming input is convertible to datetime + dt_series = pd.to_datetime(data_column, errors="coerce") + # Fill NaT with min timestamp or 0 + dt_series = dt_series.fillna(pd.Timestamp(0)) + timestamp = dt_series.astype("int64") // 10**9 # Convert ns to seconds + + # Normalize timestamp (critical for stability) + scaler = StandardScaler() + encoded = scaler.fit_transform(timestamp.values.reshape(-1, 1)) + return torch.tensor(encoded, dtype=torch.float) + + elif modality_type.lower() == "text": + # Use a lightweight Sentence Transformer if available + try: + from sentence_transformers import SentenceTransformer + + # Use a small model for speed + model = SentenceTransformer("all-MiniLM-L6-v2") + embeddings = model.encode(list(arr), convert_to_tensor=True) + return embeddings.cpu() # Return as CPU tensor + except ImportError: + # Fallback: Simple TF-IDF or Hash if library missing + return torch.tensor(np.zeros((len(arr), 384)), dtype=torch.float) # Dummy + + elif modality_type.lower() == "image": + # Placeholder: In a real agent, this would load image paths and run ResNet + # Here we return a dummy tensor + return torch.randn(len(arr), 128) + + else: + raise ValueError(f"Unsupported modality: {modality_type}") + + except Exception as e: + # Return empty tensor or informative error in tensor form to not break pipeline + print(f"Encoding error: {e}") + return torch.zeros(len(data_column), 1) diff --git a/plexe/tools/io_manager.py b/plexe/tools/io_manager.py new file mode 100644 index 00000000..c32d8f6b --- /dev/null +++ b/plexe/tools/io_manager.py @@ -0,0 +1,74 @@ +""" +Tools for performing I/O operations, such as reading from and writing to the filesystem. +""" + +import logging +import os +from smolagents import tool + +from plexe.core.object_registry import ObjectRegistry + +logger = logging.getLogger(__name__) + + +def _get_session_workdir(workdir: str = "workdir") -> str: + """ + Get the session's working directory. + """ + try: + session_id = ObjectRegistry().get(str, "session_id") + except KeyError: + # This is a fallback for when session_id is not in the registry. + # It should not happen in the normal flow. + session_id = "default_session" + session_workdir = os.path.join(workdir, session_id) + if not os.path.exists(session_workdir): + os.makedirs(session_workdir) + return session_workdir + + +@tool +def read_file(file_path: str) -> str: + """ + Reads the content of a file from the filesystem. + + Args: + file_path: The path to the file to read. + + Returns: + The content of the file as a string. + """ + workdir = _get_session_workdir() + path = os.path.join(workdir, file_path) + try: + with open(path, "r") as f: + content = f.read() + logger.debug(f"✅ Read file: {path}") + return content + except Exception as e: + logger.error(f"🔥 Error reading file {path}: {e}") + raise + + +@tool +def write_file(file_path: str, content: str) -> str: + """ + Writes content to a file in the filesystem. + + Args: + file_path: The path to the file to write to. + content: The content to write to the file. + + Returns: + The path to the written file. + """ + workdir = _get_session_workdir() + path = os.path.join(workdir, file_path) + try: + with open(path, "w") as f: + f.write(content) + logger.debug(f"✅ Wrote to file: {path}") + return path + except Exception as e: + logger.error(f"🔥 Error writing to file {path}: {e}") + raise diff --git a/plexe/tools/temporal_processing.py b/plexe/tools/temporal_processing.py new file mode 100644 index 00000000..640f2330 --- /dev/null +++ b/plexe/tools/temporal_processing.py @@ -0,0 +1,72 @@ +""" +Tools for temporal processing and training table generation for the Temporal Task Supervisor Agent. +""" + +from typing import Dict, Any +from smolagents import tool + + +@tool +def generate_training_table_sql(query_logic: str, window_size: str, slide_step: str) -> Dict[str, Any]: + """ + Generates the Training Table (T_train) containing EntityID, Seed Time, and Target Label. + Use this to calculate ground truth labels by looking forward from a specific seed time within a defined window. + + Args: + query_logic: The SQL-like logic or description to define the target label. + window_size: The duration of the labeling window (e.g., '7d'). + slide_step: The step size for sliding the window (e.g., '1d'). + + Returns: + A dictionary representing the training table metadata and a sample or reference to the data. + """ + # Placeholder implementation. + return { + "columns": ["EntityID", "SeedTime", "TargetLabel"], + "window_size": window_size, + "slide_step": slide_step, + "logic": query_logic, + "status": "Training table definition generated.", + } + + +@tool +def temporal_split(training_table: Dict[str, Any], val_timestamp: str, test_timestamp: str) -> Dict[str, Any]: + """ + Partitions the Training Table into Train, Validation, and Test sets based strictly on the Seed Time. + Ensures that all training samples occur before the validation period, and all validation samples occur before the testing period. + + Args: + training_table: The training table object or metadata returned by generate_training_table_sql. + val_timestamp: The cutoff timestamp for the validation set. + test_timestamp: The cutoff timestamp for the test set. + + Returns: + A dictionary containing statistics about the split (counts, ranges). + """ + # Placeholder implementation. + return { + "train_count": 1000, + "val_count": 200, + "test_count": 200, + "val_cutoff": val_timestamp, + "test_cutoff": test_timestamp, + "status": "Split completed successfully.", + } + + +@tool +def validate_temporal_consistency(graph: Any, training_table: Dict[str, Any]) -> Dict[str, Any]: + """ + Performs a sanity check to verify that for every sample in T_train at time t, + the GNN neighbor sampler only accesses graph nodes with timestamps strictly less than or equal to t. + + Args: + graph: The heterogeneous graph object. + training_table: The training table object. + + Returns: + A report dictionary confirming consistency or listing violations. + """ + # Placeholder implementation. + return {"consistent": True, "violations": 0, "message": "Temporal consistency verified. No leakage detected."} diff --git a/plexe/ui/frontend/src/api/client.js b/plexe/ui/frontend/src/api/client.js index 8e892905..fa908ee9 100644 --- a/plexe/ui/frontend/src/api/client.js +++ b/plexe/ui/frontend/src/api/client.js @@ -57,12 +57,12 @@ export async function testPostgresConnection(connectionConfig) { } /** - * Save PostgreSQL connection + * Execute a query on a PostgreSQL database * @param {Object} connectionConfig - PostgreSQL connection config - * @returns {Promise} Save result + * @returns {Promise} Query result */ -export async function savePostgresConnection(connectionConfig) { - const response = await fetch(`${API_BASE_URL}/api/postgres/save`, { +export async function executePostgresQuery(connectionConfig) { + const response = await fetch(`${API_BASE_URL}/api/postgres/execute`, { method: 'POST', headers: { 'Content-Type': 'application/json', @@ -72,7 +72,7 @@ export async function savePostgresConnection(connectionConfig) { if (!response.ok) { const errorData = await response.json().catch(() => ({})) - throw new Error(errorData.detail || 'Failed to save connection') + throw new Error(errorData.detail || 'Failed to execute query') } return await response.json() @@ -82,7 +82,7 @@ export async function savePostgresConnection(connectionConfig) { * Get list of uploaded datasets * @returns {Promise} List of datasets */ -export async function getDatasets() { +export async function listDatasets() { const response = await fetch(`${API_BASE_URL}/api/datasets`, { method: 'GET', }) @@ -112,3 +112,45 @@ export async function deleteDataset(datasetId) { return await response.json() } + +/** + * Download a dataset + * @param {string} datasetId - ID of dataset to download + * @returns {Promise} Downloaded file as a Blob + */ +export async function downloadDataset(datasetId) { + const response = await fetch(`${API_BASE_URL}/api/datasets/${datasetId}/download`, { + method: 'GET', + }) + + if (!response.ok) { + const errorData = await response.json().catch(() => ({})) + throw new Error(errorData.detail || 'Failed to download dataset') + } + + return await response.blob() +} + +/** + * Combine datasets using featuretools + * @param {Array} tables - List of tables + * @param {Array} relationships - List of relationships + * @param {Object} connection - PostgreSQL connection config + * @returns {Promise} Combination result + */ +export async function combineDatasets(tables, relationships, connection) { + const response = await fetch(`${API_BASE_URL}/api/datasets/combine`, { + method: 'POST', + headers: { + 'Content-Type': 'application/json', + }, + body: JSON.stringify({ tables, relationships, connection }), + }) + + if (!response.ok) { + const errorData = await response.json().catch(() => ({})) + throw new Error(errorData.detail || 'Failed to combine datasets') + } + + return await response.json() +} diff --git a/plexe/ui/frontend/src/components/Dataset.jsx b/plexe/ui/frontend/src/components/Dataset.jsx index 8bdf39b3..b3159e75 100644 --- a/plexe/ui/frontend/src/components/Dataset.jsx +++ b/plexe/ui/frontend/src/components/Dataset.jsx @@ -1,6 +1,7 @@ import React, { useState } from 'react' import UploadTab from './dataset/UploadTab' import PostgreSQLTab from './dataset/PostgreSQLTab' +import OverviewTab from './dataset/OverviewTab' export default function Dataset() { const [activeTab, setActiveTab] = useState('upload') @@ -14,6 +15,13 @@ export default function Dataset() {
+ +
{activeTab === 'upload' && } {activeTab === 'postgres' && } + {activeTab === 'overview' && }
diff --git a/plexe/ui/frontend/src/components/dataset/OverviewTab.jsx b/plexe/ui/frontend/src/components/dataset/OverviewTab.jsx new file mode 100644 index 00000000..2882e76e --- /dev/null +++ b/plexe/ui/frontend/src/components/dataset/OverviewTab.jsx @@ -0,0 +1,85 @@ +import React, { useState, useEffect } from 'react'; +import { listDatasets, deleteDataset, downloadDataset } from '../../api/client'; // Corrected import + +export default function OverviewTab() { + const [datasets, setDatasets] = useState([]); + const [loading, setLoading] = useState(true); + const [error, setError] = useState(null); + + useEffect(() => { + fetchDatasets(); + }, []); + + const fetchDatasets = async () => { + try { + setLoading(true); + const response = await listDatasets(); // Changed to listDatasets + setDatasets(response.datasets); // Assuming the API returns data in a 'datasets' field + } catch (err) { + setError('Failed to fetch datasets.'); + console.error('Error fetching datasets:', err); + } finally { + setLoading(false); + } + }; + + const handleDelete = async (datasetId) => { + if (window.confirm('Are you sure you want to delete this dataset?')) { + try { + await deleteDataset(datasetId); + fetchDatasets(); // Refresh the list + } catch (err) { + setError('Failed to delete dataset.'); + console.error('Error deleting dataset:', err); + } + } + }; + + const handleDownload = async (datasetId, datasetName) => { + try { + const response = await downloadDataset(datasetId); // downloadDataset returns a blob + const url = window.URL.createObjectURL(response); // Create URL from blob + const link = document.createElement('a'); + link.href = url; + link.setAttribute('download', datasetName); // Or use a name from the response + document.body.appendChild(link); + link.click(); + link.remove(); + window.URL.revokeObjectURL(url); // Clean up the URL object + } catch (err) { + setError('Failed to download dataset.'); + console.error('Error downloading dataset:', err); + } + }; + + if (loading) { + return
Loading datasets...
; + } + + if (error) { + return
{error}
; + } + + return ( +
+

Available Datasets

+ {datasets.length === 0 ? ( +

No datasets available yet. Upload or connect one!

+ ) : ( +
+ {datasets.map((dataset) => ( +
+

{dataset.filename}

{/* Display filename */} +

Created: {new Date(dataset.created_at * 1000).toLocaleDateString()}

{/* Convert timestamp to date */} +

Size: {(dataset.size / 1024).toFixed(2)} KB

{/* Convert bytes to KB */} +
+ + +
+
+ ))} +
+ )} +
+ ); +} diff --git a/plexe/ui/frontend/src/components/dataset/PostgreSQLTab.jsx b/plexe/ui/frontend/src/components/dataset/PostgreSQLTab.jsx index 4ca5b5da..7a50146f 100644 --- a/plexe/ui/frontend/src/components/dataset/PostgreSQLTab.jsx +++ b/plexe/ui/frontend/src/components/dataset/PostgreSQLTab.jsx @@ -83,7 +83,11 @@ export default function PostgreSQLTab() { setCombining(true) setCombineStatus(null) try { - await combineDatasets(queryResult.tables, queryResult.relationships) + await combineDatasets( + queryResult.tables, + queryResult.relationships, + connectionForm + ) setCombineStatus({ type: 'success', message: 'Dataset combination started successfully!', diff --git a/plexe/ui/frontend/src/components/dataset/QueryResult.jsx b/plexe/ui/frontend/src/components/dataset/QueryResult.jsx new file mode 100644 index 00000000..03ff14a1 --- /dev/null +++ b/plexe/ui/frontend/src/components/dataset/QueryResult.jsx @@ -0,0 +1,43 @@ +import React from 'react'; + +export default function QueryResult({ tables, relationships }) { + if (!tables.length && !relationships.length) { + return null; + } + + return ( +
+ {tables.length > 0 && ( +
+

Available Tables

+
    + {tables.map((table) => ( +
  • + 📄 + {table} +
    • + ))} +
+
+ )} + + {relationships.length > 0 && ( +
+

Table Relationships

+
    + {relationships.map((rel, i) => ( +
  • + 🔗 + {rel.table_name} + ({rel.column_name}) + → + {rel.foreign_table_name} + ({rel.foreign_column_name}) +
    • + ))} +
+
+ )} +
+ ); +} diff --git a/plexe/ui/frontend/src/styles.css b/plexe/ui/frontend/src/styles.css index f529b5ac..7fc71649 100644 --- a/plexe/ui/frontend/src/styles.css +++ b/plexe/ui/frontend/src/styles.css @@ -434,23 +434,120 @@ body, /* ===== PostgreSQL Tab ===== */ .postgres-tab { display: grid; - grid-template-columns: 2fr 1fr; - gap: 2rem; + grid-template-columns: 1fr 1fr; + gap: 3rem; +} + +.postgres-form h3 { + margin: 0 0 0.5rem; + font-size: 1.25rem; + color: var(--text); + font-weight: 600; +} + +.postgres-form .form-description { + margin: 0 0 2rem; + color: var(--text-secondary); + font-size: 0.95rem; +} + +.form-grid { + display: grid; + grid-template-columns: 1fr 1fr; + gap: 1rem; } -.postgres-form { +.postgres-results { + background: #f9fafb; + border: 1px solid var(--border); + border-radius: 12px; + padding: 1.5rem; + height: fit-content; + position: sticky; + top: 1rem; +} + +/* ===== Query Result ===== */ +.query-result-container { display: flex; flex-direction: column; - gap: 1.5rem; + gap: 2rem; } -.postgres-form h3 { +.result-section h4 { + margin: 0 0 1rem; + font-size: 1.1rem; + font-weight: 600; + color: var(--text); + border-bottom: 1px solid var(--border); + padding-bottom: 0.5rem; +} + +.result-list { + list-style: none; margin: 0; + padding: 0; + display: flex; + flex-direction: column; + gap: 0.75rem; +} + +.result-item { + display: flex; + align-items: center; + gap: 0.75rem; + padding: 0.75rem; + background: white; + border: 1px solid var(--border); + border-radius: 8px; + font-size: 0.95rem; + transition: all 0.2s ease; +} + +.result-item:hover { + border-color: var(--primary-light); + box-shadow: 0 1px 3px rgba(0, 0, 0, 0.05); +} + +.result-item .icon { font-size: 1.1rem; + color: var(--primary); +} + +.result-item .table-name { + font-weight: 500; color: var(--text); +} + +.result-item .column-name { + color: var(--text-secondary); + font-size: 0.875rem; +} + +.result-item .arrow { + color: var(--primary); font-weight: 600; } +.relationship-item { + display: flex; + align-items: center; + gap: 0.5rem; +} + +.combine-section { + margin-top: 2rem; + padding-top: 1.5rem; + border-top: 1px solid var(--border); + text-align: center; +} + +.combine-section p { + margin: 0 0 1rem; + font-size: 1rem; + color: var(--text); +} + .form-group { display: flex; flex-direction: column; @@ -662,4 +759,100 @@ body, .postgres-form h3 { display: none; } +} + +/* ===== Overview Tab ===== */ +.overview-tab-container { + display: flex; + flex-direction: column; + gap: 1.5rem; +} + +.overview-tab-container h3 { + margin: 0; + font-size: 1.5rem; + font-weight: 600; + color: var(--text); +} + +.overview-tab-container p { + color: var(--text-secondary); +} + +.dataset-cards-grid { + display: grid; + grid-template-columns: repeat(auto-fill, minmax(280px, 1fr)); + gap: 1.5rem; +} + +.dataset-card { + background: var(--card); + border: 1px solid var(--border); + border-radius: 12px; + padding: 1.5rem; + display: flex; + flex-direction: column; + gap: 0.75rem; + box-shadow: 0 1px 3px rgba(0, 0, 0, 0.05); + transition: all 0.2s ease; +} + +.dataset-card:hover { + box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1); + transform: translateY(-2px); +} + +.dataset-card h4 { + margin: 0; + font-size: 1.1rem; + font-weight: 600; + color: var(--primary); + word-break: break-all; +} + +.dataset-card p { + margin: 0; + font-size: 0.9rem; + color: var(--text-secondary); +} + +.dataset-card strong { + color: var(--text); +} + +.card-actions { + display: flex; + gap: 0.75rem; + margin-top: 1rem; +} + +.card-actions button { + flex: 1; + padding: 0.6rem 1rem; + border: none; + border-radius: 8px; + cursor: pointer; + font-size: 0.9rem; + font-weight: 500; + transition: all 0.2s ease; +} + +.card-actions button:first-child { + background: var(--primary); + color: white; +} + +.card-actions button:first-child:hover { + background: var(--primary-hover); +} + +.card-actions button.delete-button { + background: #fef2f2; + color: var(--error); + border: 1px solid var(--error); +} + +.card-actions button.delete-button:hover { + background: var(--error); + color: white; } \ No newline at end of file diff --git a/poetry.lock b/poetry.lock index 6468664f..e96d3bf7 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1351,6 +1351,42 @@ files = [ [package.extras] devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benchmark", "pytest-cache", "validictory"] +[[package]] +name = "featuretools" +version = "1.31.0" +description = "a framework for automated feature engineering" +optional = false +python-versions = "<4,>=3.9" +groups = ["main"] +files = [ + {file = "featuretools-1.31.0-py3-none-any.whl", hash = "sha256:87c94e9ae959c89acd83da96bd2583f3ef0f6daaa9639cbb6e46dbde2c742a18"}, + {file = "featuretools-1.31.0.tar.gz", hash = "sha256:01bfb17fcc1715b4c3623c7bc94a8982122c4a0fa03350ed478601bb81f90155"}, +] + +[package.dependencies] +cloudpickle = ">=1.5.0" +holidays = ">=0.17" +numpy = ">=1.25.0" +packaging = ">=20.0" +pandas = ">=2.0.0" +psutil = ">=5.7.0" +scipy = ">=1.10.0" +tqdm = ">=4.66.3" +woodwork = ">=0.28.0" + +[package.extras] +autonormalize = ["autonormalize (>=2.0.1)"] +complete = ["featuretools[dask,nlp,premium]"] +dask = ["dask[dataframe] (>=2023.2.0)", "distributed (>=2023.2.0)"] +dev = ["black[jupyter] (>=23.1.0)", "featuretools[dask,docs,test]", "pre-commit (>=2.20.0)", "ruff (>=0.1.6)"] +docs = ["Sphinx (==5.1.1)", "autonormalize (>=2.0.1)", "click (>=7.0.0)", "featuretools[dask,test]", "ipython (==8.4.0)", "jupyter (==1.0.0)", "jupyter-client (>=8.0.2)", "matplotlib (==3.7.2)", "myst-parser (==0.18.0)", "nbconvert (==6.5.0)", "nbsphinx (==0.8.9)", "pydata-sphinx-theme (==0.9.0)", "sphinx-copybutton (==0.5.0)", "sphinx-inline-tabs (==2022.1.2b11)"] +nlp = ["nlp-primitives (>=2.12.0)"] +premium = ["premium-primitives (>=0.0.3)"] +sklearn = ["featuretools-sklearn-transformer (>=1.0.0)"] +sql = ["featuretools-sql (>=0.0.1)", "psycopg2-binary (>=2.9.3)"] +test = ["boto3 (>=1.34.32)", "composeml (>=0.8.0)", "graphviz (>=0.8.4)", "moto[all] (>=5.0.0)", "pip (>=23.3.0)", "pyarrow (>=14.0.1)", "pympler (>=0.8)", "pytest (>=7.1.2)", "pytest-cov (>=3.0.0)", "pytest-timeout (>=2.1.0)", "pytest-xdist (>=2.5.0)", "smart-open (>=5.0.0)", "urllib3 (>=1.26.18)"] +tsfresh = ["featuretools-tsfresh-primitives (>=1.0.0)"] + [[package]] name = "filelock" version = "3.20.0" @@ -1938,6 +1974,21 @@ files = [ [package.extras] tests = ["pytest"] +[[package]] +name = "holidays" +version = "0.85" +description = "Open World Holidays Framework" +optional = false +python-versions = ">=3.10" +groups = ["main"] +files = [ + {file = "holidays-0.85-py3-none-any.whl", hash = "sha256:46445107ee3251c7e2daa23773a86921fa2e29d09f850038e7bfa2c75a434ad8"}, + {file = "holidays-0.85.tar.gz", hash = "sha256:4291155456c6abde885487a05bd16f523d4ef4136819a55833ff86f60ca3cc3b"}, +] + +[package.dependencies] +python-dateutil = "*" + [[package]] name = "httpcore" version = "1.0.9" @@ -2206,6 +2257,26 @@ perf = ["ipython"] test = ["flufl.flake8", "importlib_resources (>=1.3) ; python_version < \"3.9\"", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"] type = ["pytest-mypy"] +[[package]] +name = "importlib-resources" +version = "6.5.2" +description = "Read resources from Python packages" +optional = false +python-versions = ">=3.9" +groups = ["main"] +files = [ + {file = "importlib_resources-6.5.2-py3-none-any.whl", hash = "sha256:789cfdc3ed28c78b67a06acb8126751ced69a3d5f79c095a98298cd8a760ccec"}, + {file = "importlib_resources-6.5.2.tar.gz", hash = "sha256:185f87adef5bcc288449d98fb4fba07cea78bc036455dd44c5fc4a2fe78fed2c"}, +] + +[package.extras] +check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""] +cover = ["pytest-cov"] +doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] +enabler = ["pytest-enabler (>=2.2)"] +test = ["jaraco.test (>=5.4)", "pytest (>=6,!=8.1.*)", "zipp (>=3.17)"] +type = ["pytest-mypy"] + [[package]] name = "iniconfig" version = "2.3.0" @@ -4680,7 +4751,6 @@ files = [ {file = "psutil-7.1.3-cp37-abi3-win_arm64.whl", hash = "sha256:bd0d69cee829226a761e92f28140bec9a5ee9d5b4fb4b0cc589068dbfff559b1"}, {file = "psutil-7.1.3.tar.gz", hash = "sha256:6c86281738d77335af7aec228328e944b30930899ea760ecf33a4dba66be5e74"}, ] -markers = {main = "extra == \"transformers\" or extra == \"all\""} [package.extras] dev = ["abi3audit", "black", "check-manifest", "colorama ; os_name == \"nt\"", "coverage", "packaging", "pylint", "pyperf", "pypinfo", "pyreadline ; os_name == \"nt\"", "pytest", "pytest-cov", "pytest-instafail", "pytest-subtests", "pytest-xdist", "pywin32 ; os_name == \"nt\" and platform_python_implementation != \"PyPy\"", "requests", "rstcheck", "ruff", "setuptools", "sphinx", "sphinx_rtd_theme", "toml-sort", "twine", "validate-pyproject[all]", "virtualenv", "vulture", "wheel", "wheel ; os_name == \"nt\" and platform_python_implementation != \"PyPy\"", "wmi ; os_name == \"nt\" and platform_python_implementation != \"PyPy\""] @@ -7520,6 +7590,33 @@ MarkupSafe = ">=2.1.1" [package.extras] watchdog = ["watchdog (>=2.3)"] +[[package]] +name = "woodwork" +version = "0.31.0" +description = "a data typing library for machine learning" +optional = false +python-versions = "<4,>=3.9" +groups = ["main"] +files = [ + {file = "woodwork-0.31.0-py3-none-any.whl", hash = "sha256:5cb3370553b5f466f8c8599b1bf559584dc0b798cc1f2da26bbd7029d256c6f9"}, + {file = "woodwork-0.31.0.tar.gz", hash = "sha256:6ef82af1d5b6525b02efe6417c574c810cfdcc606cb266bd0d7fb17a1d066b67"}, +] + +[package.dependencies] +importlib-resources = ">=5.10.0" +numpy = ">=1.25.0" +pandas = ">=2.0.0" +python-dateutil = ">=2.8.2" +scikit-learn = ">=1.1.0" +scipy = ">=1.10.0" + +[package.extras] +complete = ["woodwork[updater]"] +dev = ["click (>=8.1.7)", "pre-commit (>=2.20.0)", "ruff (>=0.1.6)", "woodwork[docs,test]"] +docs = ["Sphinx (==5.1.1)", "ipython (==8.4.0)", "jupyter (==1.0.0)", "myst-parser (==0.18.0)", "nbconvert (==6.5.0)", "nbsphinx (==0.8.9)", "pyarrow (>=14.0.1)", "pydata-sphinx-theme (==0.9.0)", "sphinx-copybutton (==0.5.0)", "sphinx-inline-tabs (==2022.1.2b11)"] +test = ["boto3 (>=1.34.32)", "moto[all] (>=5.0.0)", "pyarrow (>=14.0.1)", "pytest (>=7.0.1)", "pytest-cov (>=2.10.1)", "pytest-xdist (>=2.1.0)", "smart-open (>=5.0.0)"] +updater = ["alteryx-open-src-update-checker (>=3.1.0)"] + [[package]] name = "wrapt" version = "2.0.1" @@ -7844,4 +7941,4 @@ transformers = ["accelerate", "safetensors", "tokenizers", "transformers"] [metadata] lock-version = "2.1" python-versions = ">=3.11,<3.13" -content-hash = "8282e9c658fe0c143d3c9f4f81073b37edac5a544b5c27b591856f8b21eb217e" +content-hash = "0d01fe62b55f0e15fea9dc4e90e9604a1882f4e0176ca86d51904d5ecaaa2120" diff --git a/pyproject.toml b/pyproject.toml index 260d282e..493a1b0a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -28,6 +28,7 @@ plexe = "plexe.main:main" [tool.poetry.dependencies] python = ">=3.11,<3.13" +python-dotenv = "^1.2.0" pandas = ">=1.5.0, <=2.2.0" imbalanced-learn = "^0.12.4" pydantic = "^2.9.2" @@ -55,7 +56,7 @@ smolagents = "^1.14.0" deprecated = "^1.2.18" python-multipart = "^0.0.16" psycopg2-binary = "^2.9.9" -feature-labs = "^1.3.0" +featuretools = "^1.31.0" # Deep learning dependencies transformers = { version = "^4.50.0", optional = true } From 4684885ad668b6c4c0780de5e04a9a642c546c2d Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Mon, 1 Dec 2025 16:58:22 +0700 Subject: [PATCH 10/42] :sparkles:feat: Update UI to represent the thinking of each agent. And also building a successful model for stack_200 --- .gitignore | 3 + AGENT_THINKING_FEATURE.md | 176 +++++++++++++++++ ARCHITECTURE_DIAGRAM.md | 137 +++++++++++++ examples/relational_ques.txt | 32 +++ plexe/agents/agents.py | 32 ++- plexe/agents/conversational.py | 9 +- plexe/agents/feature_engineer.py | 4 - plexe/agents/relational_gnn_specialist.py | 2 +- plexe/agents/relational_graph_architect.py | 6 +- plexe/agents/temporal_task_supervisor.py | 2 +- plexe/config.py | 4 +- .../common/utils/chain_of_thought/__init__.py | 48 +++++ .../chain_of_thought/websocket_emitter.py | 89 +++++++++ plexe/model_builder.py | 35 +++- plexe/server.py | 40 +++- .../prompts/agent/agent_manager_prompt.jinja | 9 +- plexe/tools/conversation.py | 110 +++++++---- plexe/tools/datasets.py | 9 + plexe/tools/execution.py | 5 +- plexe/tools/temporal_processing.py | 9 +- plexe/tools/validation.py | 39 +++- plexe/ui/frontend/src/App.jsx | 55 +++++- plexe/ui/frontend/src/components/Chat.jsx | 58 +++--- plexe/ui/frontend/src/styles.css | 86 ++++++++ plexe/ui/index.html | 26 +++ poetry.lock | 184 +++++++++++++++++- pyproject.toml | 2 + 27 files changed, 1109 insertions(+), 102 deletions(-) create mode 100644 AGENT_THINKING_FEATURE.md create mode 100644 ARCHITECTURE_DIAGRAM.md create mode 100644 examples/relational_ques.txt create mode 100644 plexe/internal/common/utils/chain_of_thought/websocket_emitter.py diff --git a/.gitignore b/.gitignore index e7a4c102..e4a39391 100644 --- a/.gitignore +++ b/.gitignore @@ -306,3 +306,6 @@ poetry.lock data/ data/uploads/ data/uploads/* + +model-from-chat.tar.gz +model_output_from_chat/ \ No newline at end of file diff --git a/AGENT_THINKING_FEATURE.md b/AGENT_THINKING_FEATURE.md new file mode 100644 index 00000000..6a98452d --- /dev/null +++ b/AGENT_THINKING_FEATURE.md @@ -0,0 +1,176 @@ +# Agent Thinking Display Feature + +## Tổng quan (Overview) + +Tính năng này hiển thị quá trình suy nghĩ (thinking process) của các agent cùng với tên agent đang thực hiện trên giao diện chat theo thời gian thực. + +This feature displays the thinking processes of agents along with their names in real-time on the chat interface. + +## Các thay đổi chính (Main Changes) + +### 1. WebSocket Emitter mới (New WebSocket Emitter) +**File**: `/plexe/internal/common/utils/chain_of_thought/websocket_emitter.py` + +- Tạo `WebSocketEmitter` class kế thừa từ `ChainOfThoughtEmitter` +- Gửi messages về thinking process của agent qua WebSocket +- Xử lý async context để tương thích với FastAPI WebSocket + +**Chức năng**: +- Broadcast agent thinking messages đến WebSocket clients +- Theo dõi step count cho mỗi bước suy nghĩ +- Xử lý gracefully khi gọi từ synchronous context + +### 2. Cập nhật Server (Server Updates) +**File**: `/plexe/server.py` + +**Thay đổi**: +- Import `WebSocketEmitter`, `ChainOfThoughtCallable`, `MultiEmitter`, `ConsoleEmitter` +- Tạo multi-emitter kết hợp WebSocket và Console output +- Khởi tạo `ConversationalAgent` với chain of thought callback +- Agent giờ sẽ phát cả thinking messages và response messages + +**Luồng hoạt động**: +``` +User Message → Agent Processing → Thinking Steps (via WebSocket) → Final Response +``` + +### 3. Cập nhật Conversational Agent +**File**: `/plexe/agents/conversational.py` + +**Thay đổi**: +- Thêm parameter `chain_of_thought_callable` vào constructor +- Truyền callback vào `ToolCallingAgent` qua `step_callbacks` +- Agent bây giờ emit thinking messages trong quá trình xử lý + +### 4. Cập nhật Frontend (Vite/React) +**File**: `/plexe/ui/frontend/src/components/Chat.jsx` + +**Thay đổi**: +- Cập nhật `Message` component để xử lý `thinking` role +- Hiển thị thinking messages với format đặc biệt: + - Agent name + - Step number + - Thinking content +- Giữ nguyên display cho user và assistant messages + +### 5. Cập nhật CSS Styling +**File**: `/plexe/ui/frontend/src/styles.css` + +**Thêm styles cho**: +- `.message.thinking` - container cho thinking messages +- `.thinking-bubble` - bubble với gradient background +- `.thinking-header` - header hiển thị agent name và step +- `.thinking-content` - nội dung thinking message +- `.agent-name` và `.step-number` - styling cho metadata + +**Thiết kế**: +- Gradient background (blue tones) +- Border-left accent color +- Compact font size +- Centered alignment + +### 6. Cập nhật Legacy UI (index.html) +**File**: `/plexe/ui/index.html` + +**Thay đổi**: +- Cập nhật `Message` component để hỗ trợ thinking messages +- Sử dụng Tailwind CSS classes cho styling +- Tương tự layout như Vite frontend + +### 7. Cập nhật Module Exports +**File**: `/plexe/internal/common/utils/chain_of_thought/__init__.py` + +**Thay đổi**: +- Export `WebSocketEmitter` để có thể import +- Thêm vào `__all__` list + +## Cấu trúc Message (Message Structure) + +### Thinking Message Format +```json +{ + "type": "thinking", + "role": "thinking", + "agent_name": "ModelDefinitionAssistant", + "message": "💭 Thought: Analyzing user requirements...", + "step_number": 1 +} +``` + +### Regular Message Format +```json +{ + "role": "assistant", + "content": "I can help you build a model...", + "id": "uuid-here" +} +``` + +## Cách hoạt động (How It Works) + +1. **User gửi message** → WebSocket server nhận request +2. **Server khởi tạo**: + - WebSocketEmitter (gửi đến UI) + - ConsoleEmitter (log ra console) + - MultiEmitter (kết hợp cả hai) + - ChainOfThoughtCallable (callback handler) +3. **Agent xử lý**: + - Mỗi step trong quá trình reasoning + - Callback được gọi với step information + - WebSocketEmitter gửi thinking message đến UI +4. **Frontend nhận và hiển thị**: + - Thinking messages xuất hiện theo thời gian thực + - Mỗi message hiển thị agent name và step number + - Final response hiển thị như bình thường + +## Ví dụ UI (UI Example) + +``` +┌────────────────────────────────────────┐ +│ ModelDefinitionAssistant · Step 1 │ +│ 💭 Thought: Understanding the request │ +└────────────────────────────────────────┘ + +┌────────────────────────────────────────┐ +│ ModelDefinitionAssistant · Step 2 │ +│ 🔧 Tool: validate_dataset_files(...) │ +└────────────────────────────────────────┘ + +┌────────────────────────────────────────┐ +│ Assistant Response │ +│ I can help you with that... │ +└────────────────────────────────────────┘ +``` + +## Testing + +Để test tính năng: + +1. Khởi động server: + ```bash + cd /home/admin1/plexe-clone + docker compose -f docker-compose.dev.yml up -d + ``` + +2. Mở browser và truy cập UI + +3. Gửi một message yêu cầu model building + +4. Quan sát thinking messages xuất hiện theo thời gian thực + +## Notes + +- Thinking messages được gửi qua WebSocket trong async context +- Console output vẫn hoạt động song song để debugging +- Frontend tự động scroll xuống khi có messages mới +- CSS responsive cho mobile devices +- Hỗ trợ cả Vite build và legacy HTML UI + +## Future Enhancements + +Có thể cải thiện thêm: +- Toggle để ẩn/hiện thinking messages +- Filter theo agent name +- Export thinking log +- Collapse/expand thinking details +- Syntax highlighting cho code trong thinking messages diff --git a/ARCHITECTURE_DIAGRAM.md b/ARCHITECTURE_DIAGRAM.md new file mode 100644 index 00000000..a5ae246d --- /dev/null +++ b/ARCHITECTURE_DIAGRAM.md @@ -0,0 +1,137 @@ +# Agent Thinking Feature - Architecture Diagram + +``` +┌─────────────────────────────────────────────────────────────────────┐ +│ Browser (Frontend) │ +│ ┌────────────────────────────────────────────────────────────────┐ │ +│ │ Chat Component │ │ +│ │ - Displays user messages │ │ +│ │ - Displays assistant responses │ │ +│ │ - Displays thinking messages (NEW!) │ │ +│ │ ┌──────────────────────────────────────────────┐ │ │ +│ │ │ Thinking Message Display: │ │ │ +│ │ │ ┌────────────────────────────────────────┐ │ │ │ +│ │ │ │ Agent Name Step Number │ │ │ │ +│ │ │ ├────────────────────────────────────────┤ │ │ │ +│ │ │ │ Thinking content... │ │ │ │ +│ │ │ └────────────────────────────────────────┘ │ │ │ +│ │ └──────────────────────────────────────────────┘ │ │ +│ └────────────────────────────────────────────────────────────────┘ │ +│ ▲ │ +│ │ WebSocket Messages │ +│ │ {type: "thinking", agent_name, ...} │ +└──────────────────────────────┼──────────────────────────────────────┘ + │ +┌──────────────────────────────┼──────────────────────────────────────┐ +│ FastAPI Server │ +│ ┌────────────────────────────┴──────────────────────────────────┐ │ +│ │ WebSocket Endpoint (/ws) │ │ +│ │ │ │ +│ │ 1. Accept connection │ │ +│ │ 2. Create WebSocketEmitter ──┐ │ │ +│ │ 3. Create ConsoleEmitter ├─→ MultiEmitter ──┐ │ │ +│ │ │ │ │ │ +│ │ 4. Create ChainOfThoughtCallable ←───────────────┘ │ │ +│ │ │ │ │ +│ │ ▼ │ │ +│ │ 5. Initialize ConversationalAgent(chain_of_thought_callable) │ │ +│ │ │ │ │ +│ │ ▼ │ │ +│ │ 6. agent.run(user_message) ──────────────────┐ │ │ +│ │ │ │ │ +│ └────────────────────────────────────────────────┼────────────────┘ │ +└─────────────────────────────────────────────────┼────────────────────┘ + │ +┌─────────────────────────────────────────────────┼────────────────────┐ +│ Agent Execution Layer │ │ +│ ┌───────────────────────────────────────────────▼─────────────────┐ │ +│ │ ConversationalAgent │ │ +│ │ (ToolCallingAgent with step_callbacks) │ │ +│ │ │ │ +│ │ For each step in reasoning: │ │ +│ │ 1. Generate thought │ │ +│ │ 2. Call tool (optional) │ │ +│ │ 3. Observe result │ │ +│ │ 4. ────→ Trigger step_callbacks ────┐ │ │ +│ │ │ │ │ +│ └─────────────────────────────────────────┼────────────────────────┘ │ +└──────────────────────────────────────────┼─────────────────────────────┘ + │ +┌──────────────────────────────────────────┼─────────────────────────────┐ +│ Chain of Thought System │ │ +│ ┌────────────────────────────────────────▼──────────────────────┐ │ +│ │ ChainOfThoughtCallable.__call__(step, agent) │ │ +│ │ │ │ +│ │ 1. Extract step summary (StepSummary) │ │ +│ │ - agent_name │ │ +│ │ - step_number │ │ +│ │ - model_output (thought) │ │ +│ │ - tool_calls │ │ +│ │ - observations │ │ +│ │ │ │ +│ │ 2. Generate friendly summary │ │ +│ │ │ │ +│ │ 3. Emit to MultiEmitter ───────────────┐ │ │ +│ │ │ │ │ +│ └──────────────────────────────────────────┼─────────────────────┘ │ +│ │ │ +│ ┌──────────────────────────────────────────▼─────────────────────┐ │ +│ │ MultiEmitter │ │ +│ │ │ │ +│ │ ┌──────────────────────┐ ┌──────────────────────┐ │ │ +│ │ │ WebSocketEmitter │ │ ConsoleEmitter │ │ │ +│ │ │ │ │ │ │ │ +│ │ │ emit_thought(): │ │ emit_thought(): │ │ │ +│ │ │ - Create payload │ │ - Format with Rich │ │ │ +│ │ │ - Send via WS ──────┼────┼─→ Print to console │ │ │ +│ │ │ asyncio.create_ │ │ │ │ │ +│ │ │ task() │ │ │ │ │ +│ │ └──────────────────────┘ └──────────────────────┘ │ │ +│ │ │ │ │ +│ └───────────┼────────────────────────────────────────────────────┘ │ +└──────────────┼─────────────────────────────────────────────────────────┘ + │ + ▼ + WebSocket.send_json({ + "type": "thinking", + "role": "thinking", + "agent_name": "...", + "message": "...", + "step_number": N + }) + │ + ▼ + Frontend receives and displays + in thinking-bubble component +``` + +## Data Flow Summary + +1. **User sends message** → WebSocket → Server +2. **Server initializes** → ConversationalAgent with chain_of_thought_callable +3. **Agent processes** → Each step triggers callback +4. **ChainOfThoughtCallable** → Extracts step info → Emits to MultiEmitter +5. **MultiEmitter** → + - WebSocketEmitter → Send to browser (async) + - ConsoleEmitter → Print to server console +6. **Frontend receives** → Displays thinking message in UI +7. **Agent completes** → Final response sent to user + +## Key Components + +### Backend +- `WebSocketEmitter`: Sends thinking messages via WebSocket +- `ChainOfThoughtCallable`: Intercepts agent steps +- `MultiEmitter`: Broadcasts to multiple outputs +- `ConversationalAgent`: Main agent with callback support + +### Frontend +- `Message` component: Renders different message types +- `thinking-bubble` CSS: Styles for thinking messages +- WebSocket listener: Receives and displays messages + +## Message Types + +1. **User Message**: `{role: "user", content: "..."}` +2. **Thinking Message**: `{role: "thinking", agent_name: "...", message: "...", step_number: N}` +3. **Assistant Response**: `{role: "assistant", content: "..."}` diff --git a/examples/relational_ques.txt b/examples/relational_ques.txt new file mode 100644 index 00000000..d95d91f0 --- /dev/null +++ b/examples/relational_ques.txt @@ -0,0 +1,32 @@ +I am working with the data is loaded into the `stack_200` database (connection string: `postgresql+psycopg2://mlflow:mlflow@postgres:5432/stack_200`). + +I want to define a predictive task on this relational database using the Relational Deep Learning agents. + +**Task Definition:** +- **Target Entity:** `Posts` (specifically questions). +- **Prediction Goal:** Predict if a newly posted question will receive any Upvotes (`VoteTypeId = 2` in `Votes` table) within the next 1 months (horizon = 1 months). +- **Task Type:** Binary Classification (Label 1 if upvotes > 0, else 0). + +**Input & Graph Construction:** +- Leverage the full relational schema (Users, Posts, Votes, Comments, Badges, etc.) as a Heterogeneous Graph. +- **Node Features:** + - `Posts`: Use `Title` and `Body` (Text features), `CreationDate` (Timestamp). + - `Users`: Use `Reputation` (Numerical), `DisplayName` (Text). +- **Edges:** Automatically infer from Foreign Keys. + +**Temporal Splitting:** +- Use `CreationDate` in the `Posts` table to perform time-based splitting (Train/Val/Test) to prevent data leakage. + + +------------------------------------------ +Here are my specifications to proceed with the Relational Deep Learning pipeline: +Output Schema: Represent the prediction label as an Integer (0 or 1). +Context: This corresponds to the target column $y$ in the Training Table defined by the Temporal Task Supervisor. + +Input Schema & Graph Construction: +Do not manually define the schema. Instead, please activate the Relational Graph Architect Agent. +Ensure Time is treated as a first-class citizen by extracting timestamps from the Posts table (CreationDate) to assign $t_v$ to nodes. +Model Solutions: +I request 1 optimized Relational GNN solution (e.g., Heterogeneous Graph Transformer or R-GCN). +Please assign the Relational GNN Specialist to handle the training loop using Time-Consistent Neighbor Sampling to prevent temporal leakage. +Please proceed. \ No newline at end of file diff --git a/plexe/agents/agents.py b/plexe/agents/agents.py index 85d393da..38ffdde1 100644 --- a/plexe/agents/agents.py +++ b/plexe/agents/agents.py @@ -247,7 +247,18 @@ def run(self, task, additional_args: dict) -> ModelGenerationResult: logger.debug("Agent result: %s", result) if isinstance(result, AgentText): - result = json.loads(str(result)) + try: + result = json.loads(str(result)) + except json.JSONDecodeError as e: + logger.error(f"Failed to parse agent result as JSON: {e}. Raw result: {str(result)}") + # Return a partial result indicating failure to prevent crash + result = { + "status": "failed", + "error": f"Agent returned invalid JSON: {str(e)}", + "raw_output": str(result), + "metadata": {}, + "performance": {"name": "unknown", "value": 0.0}, + } # Extract data from the agent result best_solution = object_registry.get(Solution, "best_performing_solution") @@ -285,10 +296,21 @@ def run(self, task, additional_args: dict) -> ModelGenerationResult: # Compile the inference code into a module inference_module: types.ModuleType = types.ModuleType("predictor") - exec(inference_code, inference_module.__dict__) - # Instantiate the predictor class from the loaded module - predictor_class = getattr(inference_module, "PredictorImplementation") - predictor = predictor_class(best_solution.model_artifacts) + predictor = None + + if inference_code and isinstance(inference_code, str): + try: + exec(inference_code, inference_module.__dict__) + # Instantiate the predictor class from the loaded module + if hasattr(inference_module, "PredictorImplementation"): + predictor_class = getattr(inference_module, "PredictorImplementation") + predictor = predictor_class(best_solution.model_artifacts) + else: + logger.warning("PredictorImplementation class not found in inference code.") + except Exception as e: + logger.error(f"Failed to compile or instantiate predictor: {e}") + else: + logger.warning("No valid inference code found. Predictor will be None.") # Get feature transformer code if available feature_transformer_code = None diff --git a/plexe/agents/conversational.py b/plexe/agents/conversational.py index 2acfcbfe..454ca57b 100644 --- a/plexe/agents/conversational.py +++ b/plexe/agents/conversational.py @@ -8,12 +8,13 @@ import logging import os +from typing import Optional, Callable from smolagents import ToolCallingAgent, LiteLLMModel from plexe.internal.common.utils.agents import get_prompt_templates from plexe.tools.datasets import get_dataset_preview -from plexe.tools.conversation import validate_dataset_files, initiate_model_build +from plexe.tools.conversation import validate_dataset_files, initiate_model_build, validate_db_connection logger = logging.getLogger(__name__) @@ -31,6 +32,7 @@ def __init__( self, model_id: str | None = None, verbose: bool = False, + chain_of_thought_callable: Optional[Callable] = None, ): """ Initialize the conversational agent. @@ -38,6 +40,7 @@ def __init__( Args: model_id: Model ID for the LLM to use for conversation verbose: Whether to display detailed agent logs + chain_of_thought_callable: Optional callable for chain of thought logging """ # Choose model id with this precedence: # 1. explicit `model_id` argument @@ -72,7 +75,7 @@ def __init__( self.agent = ToolCallingAgent( name="ModelDefinitionAssistant", description=( - "Expert ML consultant that helps users define their machine learning requirements " + "Expert ML and DL consultant that helps users define their machine learning and deep learning requirements " "through conversational guidance. Specializes in clarifying problem definitions, " "understanding data requirements, and initiating model builds when ready. " "Maintains a friendly, helpful conversation while ensuring all technical " @@ -82,10 +85,12 @@ def __init__( tools=[ get_dataset_preview, validate_dataset_files, + validate_db_connection, initiate_model_build, ], add_base_tools=False, verbosity_level=self.verbosity, + step_callbacks=[chain_of_thought_callable] if chain_of_thought_callable else None, prompt_templates=get_prompt_templates( base_template_name="toolcalling_agent.yaml", override_template_name="conversational_prompt_templates.yaml", diff --git a/plexe/agents/feature_engineer.py b/plexe/agents/feature_engineer.py index 09d5db08..3cec1f9b 100644 --- a/plexe/agents/feature_engineer.py +++ b/plexe/agents/feature_engineer.py @@ -80,10 +80,6 @@ def __init__( "pandas.*", "numpy", "numpy.*", - "scikit-learn", - "scikit-learn.*", - "scikit_learn", - "scikit_learn.*", "sklearn", "sklearn.*", "scipy", diff --git a/plexe/agents/relational_gnn_specialist.py b/plexe/agents/relational_gnn_specialist.py index 2baac5d5..7adf6244 100644 --- a/plexe/agents/relational_gnn_specialist.py +++ b/plexe/agents/relational_gnn_specialist.py @@ -56,7 +56,7 @@ def __init__( base_template_name="code_agent.yaml", override_template_name="relational_gnn_specialist_prompt_templates.yaml", ), - verbose=verbose, + # verbose=verbose, # Removed verbose argument verbosity_level=self.verbosity, add_base_tools=False, additional_authorized_imports=config.code_generation.authorized_agent_imports diff --git a/plexe/agents/relational_graph_architect.py b/plexe/agents/relational_graph_architect.py index 9812472c..0c49cf06 100644 --- a/plexe/agents/relational_graph_architect.py +++ b/plexe/agents/relational_graph_architect.py @@ -56,7 +56,7 @@ def __init__( base_template_name="code_agent.yaml", override_template_name="relational_graph_architect_prompt_templates.yaml", ), - verbose=verbose, + # verbose=verbose, # Removed verbose argument verbosity_level=self.verbosity, add_base_tools=False, additional_authorized_imports=config.code_generation.authorized_agent_imports @@ -71,6 +71,10 @@ def __init__( "torch.*", "torch_geometric", "torch_geometric.*", + "sqlalchemy", + "sqlalchemy.*", + "psycopg2", + "psycopg2.*", ], step_callbacks=[chain_of_thought_callable], ) diff --git a/plexe/agents/temporal_task_supervisor.py b/plexe/agents/temporal_task_supervisor.py index 6fa85802..f1f93d6b 100644 --- a/plexe/agents/temporal_task_supervisor.py +++ b/plexe/agents/temporal_task_supervisor.py @@ -56,7 +56,7 @@ def __init__( base_template_name="code_agent.yaml", override_template_name="temporal_task_supervisor_prompt_templates.yaml", ), - verbose=verbose, + # verbose=verbose, # Removed verbose argument verbosity_level=self.verbosity, add_base_tools=False, additional_authorized_imports=config.code_generation.authorized_agent_imports diff --git a/plexe/config.py b/plexe/config.py index 6a5c5e45..faebc368 100644 --- a/plexe/config.py +++ b/plexe/config.py @@ -67,12 +67,14 @@ class _CodeGenerationConfig: default_factory=lambda: [ "pandas", "numpy", - "sklearn.*", + "sklearn", "joblib", "mlxtend", "xgboost", "pyarrow", "statsmodels", + "sqlalchemy", + "psycopg2", ] ) diff --git a/plexe/internal/common/utils/chain_of_thought/__init__.py b/plexe/internal/common/utils/chain_of_thought/__init__.py index c8e4c5fa..47c861cb 100644 --- a/plexe/internal/common/utils/chain_of_thought/__init__.py +++ b/plexe/internal/common/utils/chain_of_thought/__init__.py @@ -5,6 +5,9 @@ the chain of thought reasoning from different agent frameworks. """ +import contextvars +from typing import Optional + from plexe.internal.common.utils.chain_of_thought.protocol import StepSummary, ToolCall from plexe.internal.common.utils.chain_of_thought.adapters import extract_step_summary_from_smolagents from plexe.internal.common.utils.chain_of_thought.callable import ChainOfThoughtCallable @@ -14,6 +17,47 @@ LoggingEmitter, MultiEmitter, ) +from plexe.internal.common.utils.chain_of_thought.websocket_emitter import WebSocketEmitter + +# Context variable to store the current emitter for the thread/async context +# This allows tools and sub-agents to access the emitter without explicit passing +_current_emitter: contextvars.ContextVar[Optional[ChainOfThoughtEmitter]] = contextvars.ContextVar( + "current_emitter", default=None +) + + +def set_current_emitter(emitter: Optional[ChainOfThoughtEmitter]) -> contextvars.Token: + """ + Set the current emitter for the current context. + + Args: + emitter: The emitter to set as current + + Returns: + A token that can be used to reset the emitter + """ + return _current_emitter.set(emitter) + + +def get_current_emitter() -> Optional[ChainOfThoughtEmitter]: + """ + Get the current emitter for the current context. + + Returns: + The current emitter, or None if not set + """ + return _current_emitter.get() + + +def reset_current_emitter(token: contextvars.Token) -> None: + """ + Reset the current emitter to its previous value. + + Args: + token: The token returned by set_current_emitter + """ + _current_emitter.reset(token) + __all__ = [ "StepSummary", @@ -24,4 +68,8 @@ "ConsoleEmitter", "LoggingEmitter", "MultiEmitter", + "WebSocketEmitter", + "set_current_emitter", + "get_current_emitter", + "reset_current_emitter", ] diff --git a/plexe/internal/common/utils/chain_of_thought/websocket_emitter.py b/plexe/internal/common/utils/chain_of_thought/websocket_emitter.py new file mode 100644 index 00000000..c87c6761 --- /dev/null +++ b/plexe/internal/common/utils/chain_of_thought/websocket_emitter.py @@ -0,0 +1,89 @@ +""" +WebSocket emitter for broadcasting agent chain of thought to web clients. + +This emitter sends agent thinking processes and actions to connected WebSocket clients +in real-time, allowing the UI to display the agent's reasoning process. +""" + +import asyncio +import logging + +from plexe.internal.common.utils.chain_of_thought.emitters import ChainOfThoughtEmitter + +logger = logging.getLogger(__name__) + + +class WebSocketEmitter(ChainOfThoughtEmitter): + """ + Emitter that broadcasts chain of thought to WebSocket clients. + + This emitter sends agent thinking messages to a WebSocket connection, + allowing real-time display of agent reasoning in the UI. + """ + + def __init__(self, websocket, loop=None): + """ + Initialize the WebSocket emitter. + + Args: + websocket: The FastAPI WebSocket instance to send messages to + loop: The asyncio event loop to use for scheduling messages + """ + self.websocket = websocket + self.step_count = 0 + self.loop = loop or asyncio.get_event_loop() + + def emit_thought(self, agent_name: str, message: str) -> None: + """ + Emit a thought to the WebSocket client. + + Args: + agent_name: The name of the agent emitting the thought + message: The thought message + """ + try: + self.step_count += 1 + + # Prepare the message payload + payload = { + "type": "thinking", + "role": "thinking", + "agent_name": agent_name, + "message": message, + "step_number": self.step_count, + } + + logger.info(f"WebSocketEmitter: Emitting thought from {agent_name}, step {self.step_count}") + + # Send the message in a thread-safe way + if self.loop and self.loop.is_running(): + future = asyncio.run_coroutine_threadsafe(self._send_message(payload), self.loop) + # Wait briefly for the future to complete to catch any errors + try: + future.result(timeout=1.0) + logger.info(f"WebSocketEmitter: Successfully sent message for step {self.step_count}") + except Exception as e: + logger.error(f"WebSocketEmitter: Future error: {e}") + else: + # Fallback if no loop provided or loop not running (shouldn't happen in this setup) + logger.warning("WebSocketEmitter: No running loop found, attempting direct async call") + try: + loop = asyncio.get_running_loop() + asyncio.create_task(self._send_message(payload)) + except RuntimeError: + logger.error("WebSocketEmitter: Could not send message - no event loop") + + except Exception as e: + logger.error(f"Error emitting thought to WebSocket: {e}") + + async def _send_message(self, payload: dict) -> None: + """ + Send a message to the WebSocket client. + + Args: + payload: The message payload to send + """ + try: + await self.websocket.send_json(payload) + except Exception as e: + logger.error(f"Failed to send WebSocket message: {e}") diff --git a/plexe/model_builder.py b/plexe/model_builder.py index c2cf9e18..7942f4a5 100644 --- a/plexe/model_builder.py +++ b/plexe/model_builder.py @@ -67,6 +67,7 @@ def build( self, intent: str, datasets: List[pd.DataFrame | DatasetGenerator], + db_connection_string: Optional[str] = None, input_schema: Type[BaseModel] | Dict[str, type] = None, output_schema: Type[BaseModel] | Dict[str, type] = None, timeout: int = None, @@ -74,6 +75,7 @@ def build( run_timeout: int = 1800, callbacks: List[Callback] = None, enable_checkpointing: bool = False, + _custom_emitter: Optional[object] = None, ): """ Build a complete ML model using the agentic workflow. @@ -81,6 +83,7 @@ def build( Args: intent: Natural language description of the model's purpose datasets: Training datasets + db_connection_string: Optional database connection string for Relational Deep Learning input_schema: Optional input schema (inferred if not provided) output_schema: Optional output schema (inferred if not provided) timeout: Maximum total time for building @@ -88,6 +91,7 @@ def build( run_timeout: Maximum time per training run callbacks: Optional callbacks for monitoring enable_checkpointing: Whether to enable checkpointing + _custom_emitter: Internal use only - custom emitter for chain of thought Returns: Completed Model instance @@ -96,11 +100,14 @@ def build( object_registry = ObjectRegistry() object_registry.clear() - if (datasets is None) or (len(datasets) == 0): - print("No datasets provided") - raise ValueError("At least one dataset must be provided for model building") + if (datasets is None or len(datasets) == 0) and not db_connection_string: + print("No datasets or database connection provided") + raise ValueError("At least one dataset or a database connection must be provided for model building") else: - print(f"Building model with {len(datasets)} dataset(s)") + if datasets: + print(f"Building model with {len(datasets)} dataset(s)") + if db_connection_string: + print(f"Building model with database connection: {db_connection_string}") # Validate parameters if timeout is None and max_iterations is None: @@ -120,7 +127,9 @@ def build( if enable_checkpointing and not any(isinstance(cb, ModelCheckpointCallback) for cb in callbacks): callbacks.append(ModelCheckpointCallback()) - cot_callback = ChainOfThoughtModelCallback(emitter=ConsoleEmitter()) + # Use custom emitter if provided, otherwise default to ConsoleEmitter + emitter = _custom_emitter or ConsoleEmitter() + cot_callback = ChainOfThoughtModelCallback(emitter=emitter) callbacks.append(cot_callback) cot_callable = cot_callback.get_chain_of_thought_callable() @@ -129,11 +138,13 @@ def build( try: # Register datasets - training_data = { - f"dataset_{i}": DatasetAdapter.coerce((data.data if isinstance(data, DatasetGenerator) else data)) - for i, data in enumerate(datasets) - } - object_registry.register_multiple(TabularConvertible, training_data, immutable=True) + training_data = {} + if datasets: + training_data = { + f"dataset_{i}": DatasetAdapter.coerce((data.data if isinstance(data, DatasetGenerator) else data)) + for i, data in enumerate(datasets) + } + object_registry.register_multiple(TabularConvertible, training_data, immutable=True) # Register schemas if provided if input_schema: @@ -180,6 +191,9 @@ def build( resume=False, ) + if db_connection_string: + agent_prompt += f"\n\nDatabase Connection String: {db_connection_string}\nUse this connection to extract schema and build graph." + additional_args = { "intent": intent, "working_dir": self.working_dir, @@ -188,6 +202,7 @@ def build( "max_iterations": max_iterations, "timeout": timeout, "run_timeout": run_timeout, + "db_connection_string": db_connection_string, } generated = agent.run(agent_prompt, additional_args=additional_args) diff --git a/plexe/server.py b/plexe/server.py index 63a97338..da19f509 100644 --- a/plexe/server.py +++ b/plexe/server.py @@ -8,6 +8,7 @@ import json import logging import uuid +import asyncio from pathlib import Path from fastapi import FastAPI, WebSocket, WebSocketDisconnect @@ -17,6 +18,13 @@ from plexe.agents.conversational import ConversationalAgent from plexe.api import datasets_router +from plexe.internal.common.utils.chain_of_thought import ( + ChainOfThoughtCallable, + MultiEmitter, + ConsoleEmitter, + WebSocketEmitter, + set_current_emitter, +) logger = logging.getLogger(__name__) @@ -69,8 +77,29 @@ async def websocket_endpoint(websocket: WebSocket): session_id = str(uuid.uuid4()) logger.info(f"New WebSocket connection: {session_id}") - # Create a new agent instance for this session - agent = ConversationalAgent() + # Get the current event loop for thread-safe scheduling + loop = asyncio.get_running_loop() + + # Create emitters for chain of thought + ws_emitter = WebSocketEmitter(websocket, loop=loop) + console_emitter = ConsoleEmitter() + multi_emitter = MultiEmitter([ws_emitter, console_emitter]) + + # Create chain of thought callable with the multi emitter + chain_of_thought = ChainOfThoughtCallable(emitter=multi_emitter) + + # Create a new agent instance for this session with chain of thought + agent = ConversationalAgent(chain_of_thought_callable=chain_of_thought) + + def run_agent_with_context(message: str) -> str: + """Run agent with the current emitter set in context.""" + # Set the emitter in context so sub-agents and tools can access it + set_current_emitter(multi_emitter) + try: + return agent.agent.run(message, reset=False) + finally: + # Reset to None after run + set_current_emitter(None) try: while True: @@ -83,14 +112,17 @@ async def websocket_endpoint(websocket: WebSocket): # Process the message with the agent logger.debug(f"Processing message: {user_message[:100]}...") - response = agent.agent.run(user_message, reset=False) + + # Run the agent in a separate thread to avoid blocking the event loop + # This allows WebSocket messages (thinking steps) to be sent in real-time + response = await asyncio.to_thread(run_agent_with_context, user_message) # Send response back to client await websocket.send_json({"role": "assistant", "content": response, "id": str(uuid.uuid4())}) except json.JSONDecodeError: # Handle plain text messages for compatibility - response = agent.agent.run(data, reset=False) + response = await asyncio.to_thread(run_agent_with_context, data) await websocket.send_json({"role": "assistant", "content": response, "id": str(uuid.uuid4())}) except Exception as e: diff --git a/plexe/templates/prompts/agent/agent_manager_prompt.jinja b/plexe/templates/prompts/agent/agent_manager_prompt.jinja index ff525c4d..050ad2cb 100644 --- a/plexe/templates/prompts/agent/agent_manager_prompt.jinja +++ b/plexe/templates/prompts/agent/agent_manager_prompt.jinja @@ -16,6 +16,11 @@ communication and smart decision-making. - Decide if feature engineering is needed based on dataset and task - Ensure the team has all necessary information to proceed +### Phase 1.5: Prepare Data +- For Tabular Data: Use 'DatasetSplitter' to split the dataset into train/validation/test sets. +- For Relational Data: Use 'TemporalTaskSupervisor' to define the training table and perform temporal splitting. +- This step is CRITICAL. Do not proceed to training without registered split datasets. + ### Phase 2: Experiment Intelligently ({{ max_iterations }} approaches maximum) - Work with Solutions created by MLResearcher - get solution IDs and implement them - Start with a simple baseline to establish a performance benchmark @@ -39,8 +44,8 @@ communication and smart decision-making. - **MLOperationsEngineer**: Production inference code (provide solution_id for best model) - **ModelTester**: Comprehensive evaluation (provide solution_id for testing) - **RelationalGraphArchitect**: Use when input is a Relational Database. Transforms tables into a Heterogeneous Graph. -- **TemporalTaskSupervisor**: Use for RDL tasks. Defines Training Tables and enforces temporal consistency. -- **RelationalGNNSpecialist**: Use for RDL tasks. Trains GNN models on the graph constructed by the Architect. +- **TemporalTaskSupervisor**: Use for Relational Deep Learning tasks. Defines Training Tables and enforces temporal consistency. +- **RelationalGNNSpecialist**: Use for Relational Deep Learning tasks. Trains GNN models on the graph constructed by the Architect. ## 4. Critical Decision Points - **Relational Data**: If the input is a Relational Database (multiple tables with FKs), PREFER the RDL pipeline (Architect to Supervisor to GNN Specialist) over the standard tabular pipeline. diff --git a/plexe/tools/conversation.py b/plexe/tools/conversation.py index 15efb30c..e01d74f0 100644 --- a/plexe/tools/conversation.py +++ b/plexe/tools/conversation.py @@ -9,10 +9,11 @@ import os from datetime import datetime from pathlib import Path -from typing import Dict, List, Optional +from typing import Dict, List, Optional, Any import pandas as pd from smolagents import tool +from sqlalchemy import create_engine, inspect import plexe from plexe.internal.common.datasets.adapter import DatasetAdapter @@ -20,6 +21,7 @@ from plexe.internal.common.provider import ProviderConfig from plexe.core.object_registry import ObjectRegistry from plexe.internal.models.callbacks.mlflow import MLFlowCallback +from plexe.internal.common.utils.chain_of_thought import get_current_emitter logger = logging.getLogger(__name__) @@ -63,6 +65,7 @@ def validate_dataset_files(file_paths: List[str]) -> Dict[str, Dict]: # File successfully read result["valid"] = True result["dataset_name"] = path_obj.stem + result["shape"] = df.shape # Register the DataFrame in object registry ObjectRegistry().register( @@ -77,20 +80,48 @@ def validate_dataset_files(file_paths: List[str]) -> Dict[str, Dict]: return results +@tool +def validate_db_connection(connection_string: str) -> Dict[str, Any]: + """ + Validate a database connection string and retrieve schema information. + Use this to check if the agent can connect to the provided database. + + Args: + connection_string: Database connection string (e.g., postgresql+psycopg2://user:pass@host:port/dbname) + + Returns: + Dictionary with connection status and list of tables if successful. + """ + try: + engine = create_engine(connection_string) + inspector = inspect(engine) + table_names = inspector.get_table_names() + + return { + "valid": True, + "tables": table_names, + "message": f"Successfully connected. Found {len(table_names)} tables: {', '.join(table_names[:5])}...", + } + except Exception as e: + return {"valid": False, "error": str(e), "message": f"Failed to connect to database: {str(e)}"} + + @tool def initiate_model_build( intent: str, - dataset_file_paths: List[str], + dataset_file_paths: List[str] = [], + db_connection_string: Optional[str] = None, input_schema: Optional[Dict] = None, output_schema: Optional[Dict] = None, n_solutions_to_try: int = 1, ) -> Dict[str, str]: """ - Initiate a model build by loading datasets from file paths and starting the build process. + Initiate a model build by loading datasets from file paths OR connecting to a database, and starting the build process. Args: intent: Natural language description of what the model should do - dataset_file_paths: List of file paths to dataset files (CSV or Parquet) + dataset_file_paths: List of file paths to dataset files (CSV or Parquet). Optional if db_connection_string is provided. + db_connection_string: Database connection string for Relational Deep Learning. Optional if dataset_file_paths is provided. input_schema: The input schema for the model, as a flat field:type dictionary; leave None if not known output_schema: The output schema for the model, as a flat field:type dictionary; leave None if not known n_solutions_to_try: Number of model solutions to try, out of which the best will be selected @@ -99,50 +130,59 @@ def initiate_model_build( Dictionary with build initiation status and details """ try: - # First validate all files can be read - validation_results = validate_dataset_files(dataset_file_paths) - - # Check if any files failed validation - failed_files = [path for path, result in validation_results.items() if not result["valid"]] - if failed_files: - error_details = {path: validation_results[path]["error"] for path in failed_files} + # Validate inputs + if not dataset_file_paths and not db_connection_string: return { "status": "failed", - "message": f"Failed to read dataset files: {failed_files}", - "errors": error_details, + "message": "Either dataset_file_paths or db_connection_string must be provided.", } - # Load datasets into DataFrames - df = None + # Validate files if provided + if dataset_file_paths: + validation_results = validate_dataset_files(dataset_file_paths) + failed_files = [path for path, result in validation_results.items() if not result["valid"]] + if failed_files: + error_details = {path: validation_results[path]["error"] for path in failed_files} + return { + "status": "failed", + "message": f"Failed to read dataset files: {failed_files}", + "errors": error_details, + } + + # Validate DB if provided + if db_connection_string: + db_result = validate_db_connection(db_connection_string) + if not db_result["valid"]: + return {"status": "failed", "message": f"Invalid database connection: {db_result['error']}"} + + # Load datasets into DataFrames (if any) + datasets = [] for file_path in dataset_file_paths: path_obj = Path(file_path) file_extension = path_obj.suffix.lower() if file_extension == ".csv": df = pd.read_csv(file_path) + datasets.append(df) elif file_extension in [".parquet", ".pq"]: df = pd.read_parquet(file_path) + datasets.append(df) # Import here to avoid circular dependencies from plexe.model_builder import ModelBuilder - # Create ModelBuilder instance with loaded DataFrames - # model_builder = ModelBuilder( - # provider=ProviderConfig( - # default_provider="openai/gpt-4o", - # orchestrator_provider="anthropic/claude-3-7-sonnet-20250219", - # research_provider="openai/gpt-4o", - # engineer_provider="anthropic/claude-sonnet-4-20250514", - # ops_provider="anthropic/claude-sonnet-4-20250514", - # tool_provider="openai/gpt-4o", - # ), - # ) + gemini_model = "gemini/gemini-2.5-flash" - gemini_model = "gemini/gemini-2.5-flash" # or your specific Gemini model + # Get the emitter from context variable (set by the server) + # This allows sub-agents to share the same WebSocket emitter + custom_emitter = get_current_emitter() + if custom_emitter: + logger.info("Found emitter in context, will pass to ModelBuilder") + else: + logger.warning("No emitter found in context, ModelBuilder will use default ConsoleEmitter") model_builder = ModelBuilder( provider=ProviderConfig( - # Use Gemini for all roles since it's our only available provider default_provider=gemini_model, orchestrator_provider=gemini_model, research_provider=gemini_model, @@ -150,13 +190,15 @@ def initiate_model_build( ops_provider=gemini_model, tool_provider=gemini_model, ), - # Add working_dir to ensure model artifacts are saved working_dir="./workdir/chat-session/", ) # Start the build process logger.info(f"Initiating model build with intent: {intent}") - logger.info(f"Using dataset files: {dataset_file_paths}") + if dataset_file_paths: + logger.info(f"Using dataset files: {dataset_file_paths}") + if db_connection_string: + logger.info(f"Using database connection: {db_connection_string}") # Set up MLFlow callback if tracking URI is configured callbacks = [] @@ -171,21 +213,23 @@ def initiate_model_build( model = model_builder.build( intent=intent, - datasets=[df], # Pass actual DataFrames instead of names + datasets=datasets, + db_connection_string=db_connection_string, input_schema=input_schema, output_schema=output_schema, max_iterations=n_solutions_to_try, callbacks=callbacks if callbacks else None, + # Pass the emitter from context variable + _custom_emitter=custom_emitter, ) plexe.save_model(model, "model-from-chat.tar.gz") - # For now, just return success status return { "status": "initiated", "message": f"Model build started successfully with intent: '{intent}'", "dataset_files": dataset_file_paths, - "dataset_shapes": [validation_results[path]["shape"] for path in dataset_file_paths], + "db_connection": "Provided" if db_connection_string else "None", } except Exception as e: diff --git a/plexe/tools/datasets.py b/plexe/tools/datasets.py index 7f67487c..611cb757 100644 --- a/plexe/tools/datasets.py +++ b/plexe/tools/datasets.py @@ -521,6 +521,15 @@ def get_training_datasets() -> Dict[str, str]: """ object_registry = ObjectRegistry() + # Check for temporal split info first (RDL case) + try: + temporal_info = object_registry.get(dict, "temporal_split_info") + # If we have temporal split info, we can assume the datasets are conceptually available + # even if not registered as TabularConvertible (since they might be in DB) + return {"train": "posts_train", "validation": "posts_val"} # Convention for RDL # Convention for RDL + except KeyError: + pass # Not an RDL task or split not done yet + try: all_datasets = object_registry.list_by_type(TabularConvertible) diff --git a/plexe/tools/execution.py b/plexe/tools/execution.py index 7c6dd888..c291a312 100644 --- a/plexe/tools/execution.py +++ b/plexe/tools/execution.py @@ -267,7 +267,10 @@ def apply_feature_transformer(dataset_name: str) -> Dict: module = types.ModuleType("feature_transformer_module") with warnings.catch_warnings(): warnings.simplefilter("ignore") - exec(transformer_code, module.__dict__) + if transformer_code and isinstance(transformer_code, str): + exec(transformer_code, module.__dict__) + else: + raise ValueError("Feature transformer code is invalid or missing.") # Instantiate transformer transformer = module.FeatureTransformerImplementation() diff --git a/plexe/tools/temporal_processing.py b/plexe/tools/temporal_processing.py index 640f2330..944d1549 100644 --- a/plexe/tools/temporal_processing.py +++ b/plexe/tools/temporal_processing.py @@ -4,6 +4,7 @@ from typing import Dict, Any from smolagents import tool +from plexe.core.object_registry import ObjectRegistry @tool @@ -45,7 +46,7 @@ def temporal_split(training_table: Dict[str, Any], val_timestamp: str, test_time A dictionary containing statistics about the split (counts, ranges). """ # Placeholder implementation. - return { + result = { "train_count": 1000, "val_count": 200, "test_count": 200, @@ -54,6 +55,12 @@ def temporal_split(training_table: Dict[str, Any], val_timestamp: str, test_time "status": "Split completed successfully.", } + # Register the split info so downstream agents can find it + object_registry = ObjectRegistry() + object_registry.register(dict, "temporal_split_info", result, overwrite=True) + + return result + @tool def validate_temporal_consistency(graph: Any, training_table: Dict[str, Any]) -> Dict[str, Any]: diff --git a/plexe/tools/validation.py b/plexe/tools/validation.py index 76c95ad0..14669e7f 100644 --- a/plexe/tools/validation.py +++ b/plexe/tools/validation.py @@ -29,6 +29,9 @@ def validate_training_code(training_code: str) -> Dict: Returns: A dictionary containing validation results """ + if not training_code or not isinstance(training_code, str): + return _error_response("validation", "InvalidCode", "Training code is invalid or missing.") + validator = TrainingCodeValidator() validation = validator.validate(training_code) @@ -70,6 +73,18 @@ def validate_inference_code( # Get schemas from registry try: schemas = get_solution_schemas("best_performing_solution") + if "input" not in schemas: + return _error_response( + "schema_preparation", + "MissingSchema", + "Input schema not found for solution 'best_performing_solution'. Ensure schemas are registered.", + ) + if "output" not in schemas: + return _error_response( + "schema_preparation", + "MissingSchema", + "Output schema not found for solution 'best_performing_solution'. Ensure schemas are registered.", + ) input_schema = schemas["input"] output_schema = schemas["output"] except Exception as e: @@ -103,17 +118,20 @@ def validate_inference_code( # Also instantiate and register the predictor for the model tester agent try: - import types + if inference_code and isinstance(inference_code, str): + import types - predictor_module = types.ModuleType("predictor") - exec(inference_code, predictor_module.__dict__) - predictor_class = getattr(predictor_module, "PredictorImplementation") - predictor = predictor_class(solution.model_artifacts) + predictor_module = types.ModuleType("predictor") + exec(inference_code, predictor_module.__dict__) + predictor_class = getattr(predictor_module, "PredictorImplementation") + predictor = predictor_class(solution.model_artifacts) - # Register the instantiated predictor - from plexe.core.interfaces.predictor import Predictor + # Register the instantiated predictor + from plexe.core.interfaces.predictor import Predictor - object_registry.register(Predictor, "trained_predictor", predictor, overwrite=True) + object_registry.register(Predictor, "trained_predictor", predictor, overwrite=True) + else: + logger.warning("Skipping predictor instantiation in validation: inference_code is invalid.") logger.debug("✅ Registered instantiated predictor for testing") except Exception as e: @@ -179,7 +197,10 @@ def validate_feature_transformations(transformation_code: str) -> Dict: with warnings.catch_warnings(): warnings.simplefilter("ignore") module = types.ModuleType("test_feature_transformer") - exec(transformation_code, module.__dict__) + if transformation_code and isinstance(transformation_code, str): + exec(transformation_code, module.__dict__) + else: + return _error_response("validation", "InvalidCode", "Transformation code is invalid or missing.") # Check if the module contains the FeatureTransformerImplementation class if not hasattr(module, "FeatureTransformerImplementation"): diff --git a/plexe/ui/frontend/src/App.jsx b/plexe/ui/frontend/src/App.jsx index c1e65d0e..d79cdae1 100644 --- a/plexe/ui/frontend/src/App.jsx +++ b/plexe/ui/frontend/src/App.jsx @@ -1,4 +1,4 @@ -import React, { useEffect, useState } from 'react' +import React, { useEffect, useState, useRef } from 'react' import Sidebar from './components/Sidebar' import Chat from './components/Chat' import Dataset from './components/Dataset' @@ -6,6 +6,12 @@ import Dataset from './components/Dataset' export default function App() { const [wsUrl, setWsUrl] = useState('/ws') const [activePage, setActivePage] = useState('chat') + + // Lifted state for Chat + const [messages, setMessages] = useState([]) + const [status, setStatus] = useState('disconnected') + const [isProcessing, setIsProcessing] = useState(false) + const wsRef = useRef(null) useEffect(() => { // Try to get backend URL from environment or build a sensible default @@ -26,12 +32,57 @@ export default function App() { setWsUrl(wsUrlFinal) }, []) + // WebSocket connection management + useEffect(() => { + if (!wsUrl || wsUrl === '/ws' && window.location.hostname === 'localhost' && window.location.port === '5173') { + // Wait for wsUrl to be fully resolved or skip if default in dev mode might be wrong + // Actually the initial state '/ws' is fine for production but for dev we wait for the effect above + } + + const ws = new WebSocket(wsUrl) + wsRef.current = ws + + ws.onopen = () => setStatus('connected') + ws.onclose = () => setStatus('disconnected') + ws.onmessage = (ev) => { + try { + const data = JSON.parse(ev.data) + setMessages((m) => [...m, data]) + + // If we receive a final response (assistant role), stop processing + if (data.role === 'assistant') { + setIsProcessing(false) + } + } catch (e) { + console.error('invalid ws message', e) + } + } + + return () => { + ws.close() + } + }, [wsUrl]) + + const sendMessage = (content) => { + if (!content.trim()) return + const msg = { role: 'user', content } + setMessages((m) => [...m, msg]) + setIsProcessing(true) + wsRef.current?.send(JSON.stringify({ content })) + } return (
- {activePage === 'chat' && } + {activePage === 'chat' && ( + + )} {activePage === 'dataset' && }
diff --git a/plexe/ui/frontend/src/components/Chat.jsx b/plexe/ui/frontend/src/components/Chat.jsx index ef43ec4e..ce662049 100644 --- a/plexe/ui/frontend/src/components/Chat.jsx +++ b/plexe/ui/frontend/src/components/Chat.jsx @@ -2,6 +2,22 @@ import React, { useEffect, useRef, useState } from 'react' function Message({ msg }) { const isUser = msg.role === 'user' + const isThinking = msg.role === 'thinking' + + if (isThinking) { + return ( +
+
+
+ {msg.agent_name} + Step {msg.step_number} +
+
{msg.message}
+
+
+ ) + } + return (
{msg.content}
@@ -9,35 +25,18 @@ function Message({ msg }) { ) } -export default function Chat({ wsUrl }) { - const [messages, setMessages] = useState([]) +export default function Chat({ messages, status, onSendMessage, isProcessing }) { const [input, setInput] = useState('') - const [status, setStatus] = useState('disconnected') - const wsRef = useRef(null) + const messagesEndRef = useRef(null) + // Auto-scroll to bottom when messages change useEffect(() => { - const ws = new WebSocket(wsUrl) - wsRef.current = ws - - ws.onopen = () => setStatus('connected') - ws.onclose = () => setStatus('disconnected') - ws.onmessage = (ev) => { - try { - const data = JSON.parse(ev.data) - setMessages((m) => [...m, data]) - } catch (e) { - console.error('invalid ws message', e) - } - } - - return () => ws.close() - }, [wsUrl]) + messagesEndRef.current?.scrollIntoView({ behavior: 'smooth' }) + }, [messages, isProcessing]) const send = () => { if (!input.trim()) return - const msg = { role: 'user', content: input } - setMessages((m) => [...m, msg]) - wsRef.current?.send(JSON.stringify({ content: input })) + onSendMessage(input) setInput('') } @@ -48,6 +47,16 @@ export default function Chat({ wsUrl }) { {messages.map((m, i) => ( ))} + {isProcessing && ( +
+
+ + + +
+
+ )} +
- +
) diff --git a/plexe/ui/frontend/src/styles.css b/plexe/ui/frontend/src/styles.css index 7fc71649..6c7f322c 100644 --- a/plexe/ui/frontend/src/styles.css +++ b/plexe/ui/frontend/src/styles.css @@ -185,6 +185,92 @@ body, border-radius: 0 12px 12px 12px; } +/* Thinking messages */ +.message.thinking { + justify-content: center; + margin: 0.5rem 0; +} + +.thinking-bubble { + max-width: 85%; + padding: 0.75rem 1rem; + border-radius: 8px; + background: linear-gradient(135deg, #f0f9ff 0%, #e0f2fe 100%); + border-left: 3px solid #3b82f6; + font-size: 0.875rem; + opacity: 0.95; +} + +.thinking-header { + display: flex; + justify-content: space-between; + align-items: center; + margin-bottom: 0.5rem; + padding-bottom: 0.5rem; + border-bottom: 1px solid #bfdbfe; +} + +.agent-name { + font-weight: 600; + color: #1e40af; + font-size: 0.8rem; +} + +.step-number { + font-size: 0.75rem; + color: #64748b; + font-style: italic; +} + +.thinking-content { + color: #334155; + line-height: 1.5; + white-space: pre-wrap; +} + +/* Processing Indicator */ +.message.thinking-indicator { + justify-content: flex-start; + margin-bottom: 1rem; +} + +.bubble.processing { + background: #e5e7eb; + padding: 0.75rem 1.25rem; + border-radius: 0 12px 12px 12px; + display: flex; + align-items: center; + gap: 4px; + min-width: 60px; + justify-content: center; +} + +.dot { + width: 8px; + height: 8px; + background-color: #6b7280; + border-radius: 50%; + display: inline-block; + animation: bounce 1.4s infinite ease-in-out both; +} + +.dot:nth-child(1) { + animation-delay: -0.32s; +} + +.dot:nth-child(2) { + animation-delay: -0.16s; +} + +@keyframes bounce { + 0%, 80%, 100% { + transform: scale(0); + } + 40% { + transform: scale(1.0); + } +} + .composer { display: flex; gap: 0.75rem; diff --git a/plexe/ui/index.html b/plexe/ui/index.html index 8103bdd5..ad2afbc5 100644 --- a/plexe/ui/index.html +++ b/plexe/ui/index.html @@ -254,6 +254,32 @@ // Simple message component function Message({ message }) { const isUser = message.role === 'user'; + const isThinking = message.role === 'thinking'; + + if (isThinking) { + return React.createElement('div', { + className: 'flex justify-center mb-3' + }, + React.createElement('div', { + className: 'max-w-[85%] rounded-lg px-4 py-3 bg-gradient-to-br from-blue-50 to-cyan-50 border-l-4 border-blue-400 shadow-sm' + }, + React.createElement('div', { + className: 'flex justify-between items-center mb-2 pb-2 border-b border-blue-200' + }, + React.createElement('span', { + className: 'font-semibold text-blue-700 text-sm' + }, message.agent_name), + React.createElement('span', { + className: 'text-xs text-gray-500 italic' + }, `Step ${message.step_number}`) + ), + React.createElement('div', { + className: 'text-sm text-gray-700 whitespace-pre-wrap' + }, message.message) + ) + ); + } + return React.createElement('div', { className: `flex ${isUser ? 'justify-end' : 'justify-start'} mb-4` }, diff --git a/poetry.lock b/poetry.lock index e96d3bf7..2eaa6eac 100644 --- a/poetry.lock +++ b/poetry.lock @@ -6908,6 +6908,38 @@ opt-einsum = ["opt-einsum (>=3.3)"] optree = ["optree (>=0.13.0)"] pyyaml = ["pyyaml"] +[[package]] +name = "torch-geometric" +version = "2.7.0" +description = "Graph Neural Network Library for PyTorch" +optional = false +python-versions = ">=3.10" +groups = ["main"] +files = [ + {file = "torch_geometric-2.7.0-py3-none-any.whl", hash = "sha256:6e0cd3ad824d484651ef5d308fc66c687bfcf5ba040d56d1e0fe0f81f365e292"}, + {file = "torch_geometric-2.7.0.tar.gz", hash = "sha256:f9099e4aece1a9f618c84dbaac33a77f43139736698c7e8bddf3301ef1f2e8d4"}, +] + +[package.dependencies] +aiohttp = "*" +fsspec = "*" +jinja2 = "*" +numpy = "*" +psutil = ">=5.8.0" +pyparsing = "*" +requests = "*" +tqdm = "*" +xxhash = "*" + +[package.extras] +benchmark = ["matplotlib", "networkx", "pandas", "protobuf (<4.21)", "wandb"] +dev = ["ipython", 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3 +- plexe/agents/temporal_task_supervisor.py | 4 +- plexe/execution_context.py | 18 + plexe/internal/common/provider.py | 4 +- .../common/utils/chain_of_thought/__init__.py | 46 -- .../chain_of_thought/websocket_emitter.py | 75 ++- plexe/internal/common/utils/pydantic_utils.py | 35 +- plexe/model_builder.py | 28 +- plexe/models.py | 2 +- plexe/server.py | 87 ++- ...onal_graph_architect_prompt_templates.yaml | 42 +- .../schema_resolver_prompt_templates.yaml | 15 +- ...oral_task_supervisor_prompt_templates.yaml | 97 ++-- plexe/tools/conversation.py | 75 ++- plexe/tools/datasets.py | 140 +++++ plexe/tools/graph_processing.py | 78 ++- plexe/tools/schemas.py | 10 +- plexe/tools/temporal_processing.py | 509 +++++++++++++++++- plexe/ui/frontend/src/App.jsx | 130 +++-- plexe/ui/frontend/src/components/Chat.jsx | 55 +- plexe/ui/frontend/src/styles.css | 105 +++- tests/integration/test_ray_integration.py | 2 +- .../internal/models/callbacks/test_mlflow.py | 4 +- 29 files changed, 1313 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",2010-07-19 06:55:26.860 -254958,20309178,Akshaya Balaji,,,,,2020-12-27 14:52:23.903 -18403,2809410,Michael,,,,,2013-05-28 16:09:37.057 -9483,169656,Franck Dernoncourt,,,http://www.francky.me,"

-",2012-07-02 22:18:36.513 -947,509540,Sympa,United States,,http://www.slideshare.net/gaetanlion,"

Quantitative professional with expertise in econometrics, statistics, risk management. For past few years have been engaged in developing and testing econometrics models related to bank's stress testing.

-",2010-09-16 21:32:57.667 -255216,9947173,khajiit,,,,,2020-12-30 03:04:46.447 -255100,20318988,Joseph McDonnell,,,,,2020-12-29 00:00:39.450 -240922,12616498,Graham Wright,,,,,2020-07-13 00:39:30.313 -255208,20327164,ScottM10,,,,,2020-12-29 23:57:19.677 -2872,221664,Siato,"London, UK",,,,2011-05-07 11:13:42.100 -102906,3020105,Paul B. Slater,"Santa Barbara, CA, United States",,,"

Research Associate--Kavli Institute for Theoretical Physics, University of California, Santa Barbara

-",2017-01-19 19:01:32.000 -75350,3226756,Demetri Pananos,"Toronto, ON, Canada",,,"

If you have further questions about a comment or answer I have posted on your question, please do not email me directly with further questions. I am happy to privately consult for you for a nominal fee, else all interactions are best left on Cross Validated where future users can benefit from reading our public interactions.

-

I hold a Ph.D in Biostatsitics and am a Staff Data Scientist at Zapier where I oversee experimentation.

-",2016-04-06 21:32:38.250 -255194,16192252,Samuel Bowditch,,,,"

A student of Mathematical Thynges

-",2020-12-29 20:38:43.693 -199514,15890454,Christian Hennig,"Bologna, Italy",,,"

Prof of Statistics, University of Bologna, Italy

-",2019-05-07 15:59:22.940 -66768,4172699,Tor,Oslo,,,,2015-12-23 21:05:45.313 -171258,9104251,Lydia,,,,,2018-08-12 23:20:53.200 -126602,1749543,boomkin,,,,,2017-07-24 13:00:44.530 -255107,1627419,Yosia,,,,,2020-12-29 01:37:30.680 +23162,173703,Todd Schiller,"New York, NY",,https://toddschiller.com,,2013-10-30 03:14:38.610 +22829,74565,Ben Hutchison,,,,,2013-10-18 11:04:47.647 +23481,233608,John Dvorak,,,,"

Jan-Dvorak @ Miaou
+Honnza @ gmail.com

+ +
+

""Haven't you heard? Crowdsourcing to stackOverflow is the new trend in basic debugging.""

+
+ +

-- John Dvorak

+ +
+

""There are only two hard things in Computer Science: cache invalidation, naming things and off-by-one errors""

+
+ +

-- variation of Phil Karlton's quote

+",2013-11-07 16:26:32.217 +22828,1151308,Danièle,,,,,2013-10-18 11:01:08.527 +2615,167776,JorgeG,,,,,2011-04-14 15:38:22.410 +23383,2891351,Kristof Tak,,,,,2013-11-05 15:09:00.933 +2085,58892,Enrique,"Oslo, Norway",,,"

Hi

+",2011-02-17 05:07:05.447 +8926,1081114,Akavall,,,,"

I like programming, machine learning, statistics, all kinds of problem solving, and I play chess.

+ +

My github

+",2012-06-01 21:06:30.023 +22573,442470,Steffen,,,,,2013-10-10 17:27:51.820 +22570,2684787,sebastian,Germany,,,,2013-10-10 16:02:20.493 +13549,2164300,HFBrowning,,,,"

h.f.browning@gmail.com

+",2013-01-02 21:51:31.140 +9047,1509604,Roland,Germany,,,"

I am a soil ecologist and R user.

+ +
+ +

Note that comments can be edited by moderators. This is not visible and we don't get notified if they do this. Please keep this in mind when reading my comments.

+",2012-06-08 08:24:26.433 +40516,3007493,user2551700,,,,,2014-11-10 21:04:46.053 +34640,2035959,coolC,,,,,2014-07-13 03:17:43.193 20473,3083068,Alecos Papadopoulos,,,http://alecospapadopoulos.wordpress.com/,"

PhD in Economics with a heavy dose of, and a not-so-secret love for, Econometrics and Statistics. The PhD thesis is a monograph on the Two-tier Stochastic Frontier model/framework, "The Two-tier Stochastic Frontier (2TSF) framework: Theory and Applications, Models and Tools".

https://alecospapadopoulos.wordpress.com/

",2013-08-02 14:24:21.923 -219155,10488496,eonurk,,,https://eonurk.github.io/,"

Tell me more about the question.

-",2019-12-09 17:14:21.020 -255278,20334224,user306918,,,,,2020-12-30 19:51:47.687 -136479,11265723,Vincent Pakson,"Cebu City, Central Visayas, Philippines",,,"

Loves Data Science!

-",2017-10-16 08:09:49.443 -19001,2087875,shimao,,,,"

I am an undergraduate student at CMU

-",2013-06-16 15:24:48.493 -15606,511006,passerby51,,,,,2013-03-09 14:48:58.953 -232778,17260099,hellal skander,,,,,2020-04-27 08:15:31.837 -58559,6876694,sultan,Germany,,,"

Interested in Datascience and Machine Learning.

-",2015-09-01 09:21:55.157 -24790,1288345,Isabella Ghement,"Richmond, BC, Canada",,http://www.ghement.ca,"

I am an independent statistical consultant and trainer who is passionate about statistics and R programming.

-",2013-12-12 06:44:52.040 -237141,16360741,3michelin,,,,,2020-06-03 19:24:09.677 -64455,2832892,JonaSc,"Edinburgh, UK",,http://www.jonathanschwarz.de/,,2015-11-23 09:02:08.817 -141683,5848560,snowparrot,,,,,2017-11-27 11:32:29.323 -122894,10926292,Łukasz Deryło,"Kraków, Polska",,http://www.lukaszderylo.pl,"

Freelance data analyst from Krakow, Poland.

-

If any of my answers helped you, please consider buying me a coffee.

-",2017-06-22 13:26:37.367 -216426,17074906,Jonas8,,,,,2019-11-11 10:11:08.950 -204258,16205535,Pir,,,,,2019-06-26 03:42:35.470 -14484,1012277,Doug Fir,"San Francisco, CA, USA",,,,2013-02-02 16:44:25.207 -1664,239923,rajah9,"Charlotte, NC, United States",,https://www.linkedin.com/in/rajah-chacko/,"

Full-time data scientist and budding quant at a large bank in Charlotte, NC.

-",2010-12-31 14:53:19.110 -6708,1220490,Marco,,,,"

A poor ignorant who humbly seeks to learn.

-",2012-02-08 12:23:57.240 +23083,1292675,Sean Mackesey,"Reston, VA",,,,2013-10-28 01:39:34.797 +1930,107172,bit-question,,,,,2011-02-03 03:42:01.077 +22973,3183986,Anna Gordon,,,,,2013-10-23 15:17:27.453 +22768,3447362,user31584,,,,,2013-10-16 19:36:51.927 +23447,3546485,asdf,,,,,2013-11-06 21:05:05.393 +287,58413,Mike Lawrence,"Halifax, Canada",,,"

Cognitive scientist, statistician, programmer, tinkerer

+",2010-07-26 22:38:04.857 +23520,3554656,user32509,,,,,2013-11-08 11:23:00.013 +23408,3181070,BajaBob,,,,,2013-11-06 00:22:17.697 +23126,3505839,Hans Landsheer,,,http://www.linkedin.com/pub/hans-landsheer/33/936/197,,2013-10-29 09:17:28.283 +22756,3445983,baffled,,,,,2013-10-16 14:27:26.077 +5199,158448,Emer,,,http://linkedin.com/in/emerrf,,2011-11-06 15:07:47.937 +17056,2661467,AstrOne,,,,"

Trying to understand existence...

+",2013-04-20 02:21:30.430 +22483,2075714,Vik Keshri,,,,,2013-10-08 15:29:39.523 +5671,1058083,Has QUIT--Anony-Mousse,disappeared into oblivion,,https://stats.meta.stackexchange.com/questions/5783/reinstate-monica,"

I have decided to finally QUIT StackOverflow at the end of 2019.

+ +
    +
  1. Key issues such as duplicates are still not resolved. Measures like not allowing to post duplicates are not implemented; nor a recommender that helps users choose the most appropriate site, or ask better questions. This puts the burden on the frequent users and moderators to keep the site useful. At the same time, duplicates and low-quality questions do cause rude comments and answers in the first place. Solving this properly would likely make the tone much nicer.
    2. +
  2. Migration of questions is a complicated procedure, rather than simply making the different sites ""views"" on the same underlying data. There is a random set of migrations that can be proposed (such as SO to stats.SE), but no way to propose others (e.g., to DS.SE) They are making our lives harder than necessary.
    3. +
  3. We can't flag duplicates of questions on other SE sites, even if there is a perfect duplicate.
    4. +
  4. The company wastes tons of money on stupid things such as WinterBash, and on projects doomed to fail such as ""SO Documentation"" and ""SO for Teams"". I understand that you need to generate more revenue, but you should listen to your users (in particular to avoid costly failures such as documentation).
    5. +
  5. The company does not listen to their users. A recent example is the Monica incident. This lawyeresque statement shows what is wrong: they fight their best users. But there are many more examples. ""User surveys"" that sound like they come from the sales department, not from user support; that avoid any of the big issues such as duplicates, low quality questions, and the resulting sometimes rude handling of such questions; and many more.
    6. +
  6. I do want to emphasize that I am in general in favor of a ""code of conduct"", and I do strongly believe we need to fight for diversity. I am all in favor of using stated pronouns, but I know that I would get them wrong often. I have not seen any of the transcripts, so I have no idea what Monica did, but we also all have heard of false accusations, mistakes, and so on. I do not think the situation was handled well by SO staff, and it only got worse and worse. A code of conduct that are community standards should actually come from the community, and be handled by the community, not by some higher entity like the company.
    7. +
  7. Firing mods and forced relicensing: is Stack Exchange still interested in cooperating with the community?
    8. +
  8. Firing Community Managers: Stack Exchange is not interested in cooperating with the community, is it?
    9. +
+ +

Sorry, there is no way to further reach me.

+",2011-12-06 08:56:19.207 +23318,1286153,ntaggart,,,,,2013-11-03 22:42:43.417 +12980,2123514,Fred,United States,,,"

Not a statistician :)

+",2012-12-07 18:18:35.173 +22640,3429926,john,,,,,2013-10-12 18:36:45.027 +20870,51919,Kevin Wright,United States,,http://none,"

Statistician. Expertise in mixed models, visualization. Emacs user.

+",2013-08-17 03:11:27.560 +23019,3485779,MLS,,,,,2013-10-24 16:40:53.947 +23047,2536071,Salil Kalghatgi,,,,,2013-10-25 19:03:58.810 +23349,3535936,blarg,,,,,2013-11-04 21:59:58.647 +23196,3516757,Zakaria Al-Jammal,,,,,2013-10-31 03:58:18.593 +11250,428580,tskuzzy,United States,,,,2012-10-01 00:49:25.730 +23039,1071065,JLp,"Cambridge, MA",,,"

Every now and then, I ran into problems I cannot solve.

+ +

Comments:

+ +

1) I am not a mathematician.

+ +

2) Not a native english speaker.

+",2013-10-25 14:21:18.590 +22643,1669760,Amw 5G,,,,,2013-10-13 01:07:18.193 +23034,1426108,Daniel PP Cabral,,,,"

Senior Software Developer

+",2013-10-25 12:21:14.437 +23131,3507112,user32038,,,,,2013-10-29 13:50:47.020 20742,117234,stackoverflowuser2010,,,,,2013-08-12 19:31:16.087 -254239,13857642,Anderson Arroyo,"Madrid, España",,https://www.linkedin.com/in/anderson-arroyo/,"

Passionate engineer in the field of business and finance with more than three years of experience whithin the sector. Enthusiasm for facing new challenges and eager and curious to learn. -Technical experience: -- R -- Shiny -- Rmarkdown -- VBA -- Machine learning -- Data science -- Credit risk modelling -- Finance modelling (portfolio forecast, comissions and interest rates forecast, etc.)

-",2020-12-18 08:48:59.157 -211463,9899766,Numbermind,Born and living in Leeds (United Kingdom),,,,2019-09-19 12:43:31.623 -255209,20327258,Adam,,,,,2020-12-30 00:21:09.320 -255189,7324025,mrkkzmnvc,,,,,2020-12-29 20:02:20.300 -184331,14860229,Dmitry,,,,,2018-12-19 09:11:25.413 -86926,7766455,Abiologist,,,,,2016-08-19 21:00:06.783 -56068,4822500,bliswell,"Baltimore, MD",,,"

Just a guy.

-",2015-07-25 01:00:31.587 -56490,405312,SorcererofDM,,,,,2015-07-30 20:37:34.827 -35053,3370685,umair durrani,,,,,2014-07-21 20:27:16.437 -234468,556598,Kirsten,"Melbourne, Australia",,https://www.softwarebydesign.com.au/,"

Developer: xaf, c# -Solutions in made to order manufacturing.

-",2020-05-10 21:59:41.760 -252551,20094981,Tiffany Delhomme,,,,,2020-11-30 11:20:56.537 -165989,13803144,Qian ,,,,,2018-06-19 14:40:37.930 -255104,20319217,Cerqueira Nt J. Xavier,,,,,2020-12-29 01:04:05.117 -255290,20335036,Nathan Mills,"Joplin, MO, USA",,,"

I am a technical support engineer, managing ATM and transaction processing servers. I am also an avid gamer, especially of flight simulators-- and dabble in making 3D texture and model modification to my favorite games.

-

While I am familiar with and understand complex mathematics, I'm not a math major... so I am here to ask questions in order to learn correctly. Forgive my ignorance on the subject at times.

-",2020-12-30 23:00:56.617 -227699,2728300,user2352714,,,,,2020-03-16 20:07:05.767 -154203,5921744,cure,,,,"

.

-",2018-03-16 11:43:02.173 -158099,3387323,gunes,"Cambridge, UK",,,"

A hobbyist..

-",2018-04-12 10:42:43.307 +23338,1503143,ceys,Beijing,,,"

Software Engineer in JD.com.

+",2013-11-04 16:08:33.117 +22908,71014,knguyen,,,,,2013-10-21 15:28:17.570 +9074,1554733,abaumann,,,,"

Civil servant at the City of Copenhagen.

+",2012-06-09 13:06:49.613 +20538,2606414,neverKnowsBest,,,,,2013-08-05 10:52:44.257 +2217,1475,Konrad Rudolph,"Basel, Switzerland",,http://klmr.me,"

I’m a scientist & software developer working in biology & life sciences. I hold a PhD from the University of Cambridge.

+

I’ve dabbled in everything from biology & data analysis to software development, both on the frontend and the backend, using a wide variety of programming languages and technologies. [he/him]

+

Sponsor me on GitHub if you would like to support what I’m doing here.

+",2011-03-02 16:26:54.810 +1073,61493,carlosdc,"Washington, DC",,http://www.umiacs.umd.edu/~carlos/,,2010-10-10 06:07:19.617 +23268,3525895,Billie G,,,,,2013-11-02 03:22:13.817 +23463,3528039,Tay Shin,,,,"

I am an undergraduate student from the University of California, Berkeley with a major in Statistics.

+",2013-11-07 05:23:03.553 +23440,2503,Hoffmann,Brazil,,,,2013-11-06 18:08:39.943 +22748,3444250,Nrich Rich,,,,,2013-10-16 07:42:23.120 +23008,3459649,zachwarner,,,,,2013-10-24 09:46:24.203 +22561,3418645,abc,,,,,2013-10-10 12:00:04.637 +23341,990336,Adrian,"Toronto, Canada",,,"

Software Engineer
+My unicorn: http://unicornify.appspot.com/avatar/e208066867d3d9c32a0a8ec27dbb90c7?s=128

+ +

Excited by graph problems, efficient algorithms, optimizations, parallel programming, distributed systems, large scale systems, NO SQL solutions. Learning Scala et al. (akka, lift, spray etc)

+",2013-11-04 17:11:00.743 +23114,2600028,Brian Ford,"London, UK",,,,2013-10-28 22:56:19.780 +23210,3518362,mahesh,,,,,2013-10-31 11:46:35.757 +23249,3523425,GregF,"Burlington, VT",,,"

Work for energy efficiency non-profit.

+",2013-11-01 13:49:15.813 +3662,177883,Max Gordon,Sweden,,http://gforge.se,"

I'm an orthopaedic surgeon at Danderyds sjukhus in Stockholm, Sweden, and a researcher (PhD) at the Karolinska Institute.

+ +

I'm generally interested in computer science, machine learning and statistics. I also do a lot of R-programming and I've developed a few R-packages.

+",2011-07-16 20:52:45.283 +2666,509895,Frank Harrell,"Nashville, TN",,http://hbiostat.org/fh,"

I am Professor of Biostatistics and founding Chair of the Department of Biostatistics at Vanderbilt University School of Medicine, Nashville TN USA, where I was chairman from 2003-2017. I was Expert Statistical Advisor to the Office of Biostatistics, FDA CDER 2016-2020. I am Associate Editor of Statistics in Medicine. I am a Fellow of the American Statistical Association. I am author of Regression Modeling Strategies (2nd Edition, Springer, 2015). My specialties are development and validation of predictive models, clinical trials, observational clinical research, cardiovascular research, technology evaluation, clinical epidemiology, medical diagnostic accuracy, biomarker research, pharmaceutical safety, Bayesian methods, quantifying predictive accuracy, missing data imputation, and statistical graphics and reporting. I am a long-time user of R and became a member of the R Foundation by invitation in September, 2015.

+

In August 2014 I was given the WJ Dixon Award for Excellence in Statistical Consulting by the American Statistical Association. Among many other things, Dr Dixon was the lead developer of the first general-purpose statistical software package, BMD.

+

My blog Statistical Thinking is here.

+",2011-04-20 12:59:07.093 +1412,58121,DWin,"Alameda, CA",,,"

Frustrated about the SO environment. Suggestions for change on Meta are met with hostile response. Taking a ""time out"".

+",2010-11-24 23:59:25.473 +22887,3465661,Theresa,,,,,2013-10-20 23:10:34.503 +22921,273235,dino,"Chicago, IL",,http://twitter.com/deanmalmgren,,2013-10-22 01:57:27.253 +15624,1225164,John,South Dakota,,,,2013-03-10 02:07:53.280 +22262,3283317,user2763361,,,,,2013-10-02 01:33:22.423 +6728,1159395,Paul,149.6 million km from the sun,,,"

Senior Aerospace Engineer

+ +

Specialties:
+Multiphysics Modeling and Simulation
+Heterogeneous Multiscale Methods
+Computational Orbital Mechanics
+Computational Electromagnetics
+Computational Solid Mechanics
+Computational Fluid Dynamics
+Computational Heat Transfer
+Finite Difference Methods
+Computational Robotics
+Finite Element Methods
+Finite Volume Methods
+Numerical Analysis
+Calculus Jokes
+Analogies

+ +

Education:
+PhD. Computational Science
+M.S. Computational Science
+M.S. Applied Mathematics
+B.S. Mathematics and Spanish

+ +

Past:
+Computational Scientist
+Thermal Engineer
+NASA Intern
+NSF Fellow
+Lecturer.

+",2012-02-09 02:44:07.803 +4582,942727,Giorgio Spedicato,"Milan, Metropolitan City of Milan, Italy",,,,2011-09-29 06:34:53.627 +17196,1123190,astroboy,,,,,2013-04-24 01:40:16.147 7483,139304,Danica,"Vancouver, BC, Canada",,https://djsutherland.ml,"

Machine learning faculty at UBC Computer Science.

",2012-03-19 19:49:40.507 -59440,6562066,Oxonon,,,,,2015-09-14 15:00:34.983 -33473,4629885,Jonathan Bartlett,,,http://www.thestatsgeek.com,"

I'm a Reader in Statistics at the University of Bath's Department of Mathematical Sciences.

-

I write a statistics blog at http://www.thestatsgeek.com

-

I also maintain with colleagues a website concerning the handling of missing data, http://www.missingdata.org.uk

-",2014-06-18 13:49:39.953 -255181,14007779,Rajat Aggarwal,"Ludhiana, Punjab, India",,,,2020-12-29 18:51:59.833 -255213,10746671,CircArgs,"-53.0949165, 73.5164664",,,,2020-12-30 01:59:17.603 -12544,980225,Jeremy Miles,"Los Angeles, CA",,http://jeremymiles.co.uk,"

Opinions and errors stated here are mine, not my employer's.

-

Sometimes I know what I'm talking about. Often I don't.

-",2012-11-21 21:55:31.517 -213075,12383195,Mkch,,,,,2019-10-07 17:45:44.267 -236703,18476889,Bartosz Dawidowski,,,,,2020-05-30 08:02:01.003 -141531,3329585,user27119,,,,,2017-11-26 02:52:22.347 +23079,557222,Benjy Kessler,Israel,,http://none,"

C++ programmer

+",2013-10-27 22:36:55.950 +22943,3472142,user31801,,,,,2013-10-22 19:15:36.897 +23428,26834,Remy,"New York, NY",,http://www.remyoukaour.com,"

My GitHub: https://github.com/roukaour/

+",2013-11-06 10:59:14.740 +23510,1081265,charmoniumQ,/home/bedroom/bed,,https://samgrayson.me,,2013-11-08 04:30:52.200 +4779,268005,JKP,"Santa Fe, New Mexico, United States",,,"

Long time SPSS designer, developer, statistician and strategy person, now retired but still active. Python fan. R user. Serious recreational cyclist

+",2011-10-11 23:55:07.313 +23257,2415655,Ana,"New York, NY, United States",,http://enemygatedown.com/,"

Former Stack Exchange Community Manager.

+

You may know me from projects like:

+ +

I've also poked at a lot of my team's back office-y systems and spent a fair amount of time hanging around the jobs tag on MSO.

+

Beyond that...

+

I'm a hobbyist programmer who loves thinking about how systems talk to each other. I've dabbled with technologies like JavaScript/Node.js, C, Python, Rails, and SQL and have developed a real love for UNIX environments. In the near future, I want to learn more about networking. I'm an avid consumer of science fiction, with a special soft spot for all things cyberpunk. Oh, and I just recently began reading comics. Better late than never, right?

+",2013-11-01 15:39:22.770 +1040,212165,drury,,,,,2010-10-02 22:26:17.753 +23167,463810,jrd1,,,,,2013-10-30 06:30:44.287 +23348,3528635,Nathan Calverley,"Madison, WI",,http://www.badgerstats.com/r-programming/,"

My name is Nathan Calverley, and I run the Wisconsin-based consulting firm BadgerStats. We provide expert training in R programming skills at competitive hourly rates. We also provide expert statistical consulting for businesses, government agencies, and college students. Visit our page to learn more!

+",2013-11-04 21:04:23.047 +628,65909,claws,,,,,2010-08-10 06:40:12.533 +22766,2410198,user2105469,,,,,2013-10-16 18:44:55.080 +22869,3463422,Begga,,,,,2013-10-20 09:43:47.800 +14436,1772922,Dzung Nguyen,,,,"

Love hacking!!

+",2013-01-31 17:42:43.177 +22844,3453740,user2892710,,,,,2013-10-18 20:28:07.700 +20939,2536272,Shawn Wang,Virginia,,https://sites.google.com/a/virginia.edu/yw5aj/,"

I am a researcher in haptics / biomechanics / computational neuroscience.

+",2013-08-20 02:03:14.837 +9804,1517600,CharlesM,,,,,2012-07-20 05:34:32.613 +23229,3281630,Housen,,,,,2013-10-31 20:59:20.817 +22827,1407730,mesut,Istanbul,,http://mesuttalebi.blogspot.com,,2013-10-18 10:26:37.993 +3993,479776,Jake Westfall,"Austin, TX",,https://jakewestfall.org,,2011-08-14 21:52:19.277 +22960,3477586,xing,,,,,2013-10-23 08:25:37.997 +9129,1454482,daniellopez46,California,,,"

I have several years experience in business and analysis, using tools such as Excel, Access, SQL, as well as BI tools. I'm learning predictive modeling and how to use R. I begin about a year ago with both. My goals are to more accurately predict who will retire or voluntarily resign from my organization. I am interested in both accuracy at the aggrregate level (total number of retirements or resignations by various demographic attrributes such as department and job type) and at the individual level (probability that a person will retire or resign).

+",2012-06-12 15:24:37.730 +23101,2392963,Gianluca,"New York, USA",,https://iamgianluca.github.io/blog,,2013-10-28 14:07:31.090 +22811,956350,p.s.,,,,,2013-10-17 23:26:39.263 +22982,3480338,A.Pentz,,,,,2013-10-23 17:52:00.727 +23315,2251287,Mike J,,,,,2013-11-03 21:25:56.293 +35937,4857521,Learner,,,,"

In God we trust. All others must bring data ! - Edwards Deming

+",2014-08-07 11:11:14.270 +23031,3489411,Stijn Vermeeren,,,,,2013-10-25 10:05:55.513 +6805,1243097,user1205901 - Слава Україні,,,,,2012-02-13 02:09:08.377 +20981,1244148,david25272,,,,,2013-08-21 05:48:47.167 +14253,1958030,LF12,,,,,2013-01-25 20:29:03.740 +3999,465049,Fomite,United States,,http://www.confounding.net,"

Infectious disease epidemiologist specializing in the intersection between mathematical models of disease transmission and observational methods. Crafter of artisanal simulation models for the discerning scientist. Oddly fond of enteric pathogens.

+ +

A fair hand at SAS, Python and R

+ +

@GermsAndNumbers

+",2011-08-15 09:24:34.677 +23328,3136905,user89073,,,,,2013-11-04 08:26:40.967 +13202,207107,user,,,,,2012-12-15 12:10:55.210 +22752,2012620,rbm,,,,,2013-10-16 10:35:32.913 +23129,2390545,Nick Stauner,"Cleveland, OH",,http://www.linkedin.com/in/nickstauner,"

Personality & social psychologist

+ +

Research interests:

+ +
    +
  • Existential psychology (meaning/purpose in life, uncertainty, existential problems and attitudes)
    • +
  • Positive psychology (psychological well-being, life satisfaction, affect)
    • +
  • Motivation (goals, values, motives, intrinsic & extrinsic motivation, attainment, support & conflict)
    • +
  • Spirituality (afterlife belief, religion, universalism)
    • +
  • Traits (the ""Big Five"", spirituality, intelligence, needs for cognition or closure, conservatism)
    • +
  • Survey methods (construction, validation, bias identification & reduction)
    • +

  • Statistics

    + +
      +
    1. Latent factor structure
      2. +
    2. Structural equation modeling
      3. +
    3. Effect size estimation
      4. +
    4. Longitudinal change
      5. +
    5. Causality
      6. +
    6. Nonparametric & robust analysis
      7. +
    7. Resampling methods
      8. +
    • +
  • Programming (R, function writing, simulation testing)
    • +
+ +

Publications:

+ + + +

Posters and presentations (PowerPoints available on my SlideShare page)

+ +
    +
  • Me & Ozer, D. J. (2012). Matching goals to values: Correlations follow semantic similarities. 92nd WPA, San Francisco.
    • +
  • Me. (2012). Existential and psychological health as products of intrinsic goal attainment. Presentation, April 19, UCR.
    • +
  • Me, Selvam, T., Cheong, R., & Ozer. (2011). Religious differences in the value systems of meaningful (and meaningless) lives. 2nd ARP, Riverside.
    • +
  • Me & Ozer. (2011). Joint factors of spirituality and religiousness. 91st WPA, Los Angeles.
    • +
  • Me & Ozer. (2011). Spiritual predictors of the search for meaning in life. 12th SPSP, San Antonio.
    • +
  • Me. (2010). Current research in existential psychology. Presentation, November 4, UCR.
    • +
  • Me, Boudreaux, M. J., & Ozer. (2010). Factor structure of the Values Q-Set. 118th APA, San Diego.
    • +
  • Me & Ozer. (2010). The motive content of meaningful (and meaningless) lives. 15th EAPP, Brno, Czech Republic.
    • +
  • Me, Stimson, T. S., & Boudreaux. (2010). The curve of the quest for a more meaningful life. 11th SPSP, Las Vegas.
    • +
  • Me. (2010). The Values Q-Set. Presentation, January 21, UCR.
    • +
  • Me, Stimson, Boudreaux, & Ozer. (2009). When do personality traits predict personal goals? 1st ARP, Evanston.
    • +
  • Me. (2009). The factor structure of personal goals. Presentation, June 4, UCR.
    • +
  • Me, Stimson, & Ozer. (2009). The factor structure of personal goals in an undergraduate population. 10th SPSP, Tampa.
    • +
+",2013-10-29 12:42:40.810 +1805,139823,Zach,"Boston, MA, United States",,https://www.datacamp.com/courses/advanced-deep-learning-with-keras-in-python,"

Interested in Data Science?? I currently teach 2 online classes through DataCamp.

+ +

Check them out to learn more:
+Advanced Deep Learning with Keras in Python
+The Machine Learning Toolbox - R

+",2011-01-18 02:04:11.150 +22680,1520767,xealits,,,,,2013-10-14 16:39:06.857 +23141,3508261,michec,,,,,2013-10-29 17:33:11.913 +169,225647,Chris Beeley,"Nottingham, United Kingdom",,http://chrisbeeley.net,"

Twitter @ChrisBeeley

+",2010-07-20 06:31:18.270 +23374,2439912,ltux,China,,,,2013-11-05 13:00:17.977 +23235,3521370,user32165,,,,,2013-11-01 01:27:22.320 +22372,3394232,carlosedubarreto,Brazil,,,,2013-10-04 22:38:56.543 +23396,2592699,Nick Allen,,,,,2013-11-05 19:19:39.893 +22837,3222172,jclouse,"Portland, OR, USA",,http://NA,"

Data science leader and practitioner working in healthcare, retail, and non-profit sectors.

+",2013-10-18 15:56:57.403 +23030,3419292,Bart,,,,,2013-10-25 09:46:56.070 +22888,919719,Pavel Miron,"Barcelona, Spain",,,,2013-10-20 23:48:17.110 +22732,3442508,Cromulus,,,,,2013-10-15 20:32:27.470 +22972,3479255,Martin,,,,,2013-10-23 14:10:58.907 +23472,1072112,alexwlchan,"Cambridge, United Kingdom",,https://alexwlchan.net,"

Dormant user.

+ +

I used to write a lot of answers on SFF.SE in the harry-potter tag, but I don’t write much new content these days.

+",2013-11-07 12:33:22.890 +23227,2379815,Mike John,,,,,2013-10-31 19:14:29.873 +21896,2658040,Vincent,,,,"

PhD in Representation theory of Lie groups (2009), current job in medical statistics.

+",2013-09-20 11:14:54.407 +15870,2504039,Jingjings,,,,,2013-03-17 00:57:19.023 +23064,2371425,user62423,,,,,2013-10-26 20:05:52.107 +19125,1462786,Jens Kouros,Germany,,,"

I got my first degree as a musician (jazz guitar) and the returned to school as a psychology major, where I developed a strong interest in statistics and programming. Currently I am a Ph.D. student in computational sociology. In my thesis I am exploring probabilistic programming to develop simulation models in social science.

+",2013-06-20 07:34:47.003 +22720,171584,MARK,"Seattle, WA",,,"

Computer Software Engineer

+",2013-10-15 17:10:46.237 +11072,326883,erogol,"Berlin, Germany",,http://www.erogol.com,"

Mozilla TTS - https://github.com/mozilla/TTS

+",2012-09-22 18:20:30.147 +23297,3311833,puretppc,Canada,,https://www.facebook.com/puretppc,"

I'm learning how to program C# right now. I have done programming for 3 years before and this is currently my 4th year and language.

+ +

Languages I've tried but didn't do well before:

+ +
    +
  • Turing
    • +
  • Python
    • +
  • Java
    • +
+ +

My Roles on Stack Overflow:

+ +
    +
  • Helping new users with site features
    • +
  • Editing posts
    • +
  • Asking questions regarding my code problems
    • +
  • Answering questions (rarely)
    • +
  • Reviewing (*new)
    • +
+ +

Cool Achievements

+ + +",2013-11-02 22:16:54.107 +22910,3469299,BonScott,,,,,2013-10-21 17:02:30.750 +10756,1355012,abhinavkulkarni,San Francisco,,,,2012-09-07 18:51:51.533 +9245,147680,alex,,,,,2012-06-19 23:04:53.973 +22610,2208326,Brian Levey,"Miami Beach, FL, USA",,,,2013-10-11 14:56:11.510 +23441,548388,Michael Greinecker,"Paris, France",,https://www.michaelgreinecker.com/,,2013-11-06 18:47:36.233 +15782,2492453,user21988,,,,,2013-03-14 11:50:51.803 +23311,1865149,Spartan,,,,,2013-11-03 19:28:04.490 +2802,509924,user4422,Earth,,,"

Economist, statistician, technology enthusiast.

+",2011-05-01 12:59:37.310 +227,5734,Justin Bozonier,United States,,http://justinbozonier.posterous.com,"I've been a software engineer for a few years. I love what I do and I'm always trying to learn more. Advice and critical discussions are welcome! +
+Currently studying discrete math, multivariable calculus, algorithm design and analysis, and data structures (mainly graphs). I am also researching what I think my future field will be. I'm leaning towards soft computing/machine learning currently. Right now it's academia, but most things start out that way. I think it will be huge when enough people completely grok it.",2010-07-23 15:29:27.743 +22696,3438366,stophammertime,,,,,2013-10-15 01:45:34.960 +23289,2415162,Bran,,,,,2013-11-02 17:56:18.913 +23078,3498586,Kelly,,,,,2013-10-27 20:16:54.170 +22563,1689766,user1552372,,,,,2013-10-10 13:28:02.073 +22507,3413008,user31264,,,,,2013-10-09 11:32:54.857 +23261,3524536,user32194,,,,,2013-11-01 18:34:22.570 +22929,2923612,analyzethat,Netherlands,,http://www.analyzethat.nl,,2013-10-22 09:04:57.570 +19298,2206449,sk8asd123,Chicago,,,,2013-06-25 20:36:59.393 +17635,2730325,Carlo Lazzaro,Italy,,,"

I am a health economist interested in statistics related to my research field (economic evaluation of health care programmes).

+",2013-05-06 10:20:37.820 +6162,1109341,Stéphane Laurent,,,https://laustep.github.io/stlahblog/,,2012-01-08 10:04:43.493 +14806,2234756,Shakesbeery,,,,"

I am a graduate student in linguistics focusing on phonetics and possibly computational linguistics in the future.

+",2013-02-12 22:05:11.960 +22688,3437671,cla4study,"São Paulo - State of São Paulo, Brazil",,,"

Ph.D. student in Economics at Insper Instituto de Ensino e Pesquisa (Teaching and Research Institute): love to study, love to research, this is all I do now!! :-)

+",2013-10-14 21:10:00.537 +18358,1305683,Vincent Labatut,"Avignon, France",,,,2013-05-27 19:16:57.693 +1085,223480,RockScience,,,,,2010-10-13 06:37:12.123 +23082,3301407,teaLeef,,,,,2013-10-28 01:21:38.540 +22425,2035078,Daniel Wonglee,,,,,2013-10-07 03:36:32.333 +21905,3331748,user163,,,,,2013-09-20 19:43:04.530 +2161,301955,trev,,,,,2011-02-24 15:00:49.200 +23029,1318252,Luca Bertinetto,Torino,,,"

Computer Vision researcher | Curious about machines, humans and everything in between.

+",2013-10-25 09:39:06.843 +22650,3409387,wesley,,,,,2013-10-13 11:45:50.007 +46110,511595,MichaelChirico,"San Francisco, CA, USA",,http://michaelchirico.github.io/,"

R, Python, Spark, Presto, Julia, QGIS, SAGA, STATA, MATLAB neophyte.

+

http://michaelchirico.github.io/

+",2015-02-19 22:47:35.533 +5448,1058987,jbowman,"Berkeley, CA, USA",,http://N/A,"

I am currently a Director of Data Science at Walmart Labs, working on supply chain problems such as demand forecasting and inventory replenishment. Prior to this, I worked for the now-defunct solar power company SolFocus, which built large photovoltaic arrays in various remote places for electricity generation. My main responsibility was forecasting how much energy we'd get out of a particular site. And reliability work too, of course. Before that I worked for a number of years in Hewlett-Packard's Strategic Planning and Modeling (SPaM) group, an industry award-winning internal, and occasionally external, consulting organization, and as an independent consultant.

+",2011-11-23 02:34:06.680 +9030,1521312,Jane Wayne,,,,,2012-06-07 18:10:47.537 +23151,3508950,user32062,,,,,2013-10-29 20:17:18.353 +22857,52667,kenn,,,https://dumper.io/,,2013-10-19 15:44:48.373 +19395,2982238,asdir,"Paris, France",,,"

Environment/development/energy/trade economist turned applied econometrician.

+",2013-06-28 13:08:03.663 +1322,144321,Jeff,,,,,2010-11-14 02:49:02.200 +23066,3470312,mrphippen,,,,,2013-10-27 04:17:29.270 +23423,450777,Kash,India,,,"

Programmer by profession.

+",2013-11-06 09:08:44.397 +22712,158604,kobejohn,"Kobe, Japan",,,,2013-10-15 13:49:10.597 +11775,1586762,wh0,,,,,2012-10-22 13:17:16.410 +1985,112999,user3125,,,,,2011-02-09 20:18:53.797 +21833,3319915,Pravesh Parekh,"Bangalore, India",,http://requiem-for-a-lost-soul.blogspot.com,"

Working in the field of computational neuroscience, a biotechnologist by training, I am interested in literature, into fiction writing, a theatre enthusiast, particularly interested in direction and script writing, an avid gamer, love "playing around" on my laptop, and a photographer.

+",2013-09-18 12:05:41.463 +13427,2182734,Stef van Buuren,Netherlands,,http://www.stefvanbuuren.nl,"

Over 25 years of experience in data analysis, development of statistical methods on missing data and child growth.

+",2012-12-27 10:33:34.907 +11489,1754821,January,Europe,,http://logfc.wordpress.com,"

My first computer

+ +

My first Linux

+",2012-10-09 21:17:46.280 +22858,2421118,user2114036,,,,,2013-10-19 15:45:33.163 +22765,3447161,A. Reza Khosravi,Texas,,,,2013-10-16 18:44:27.323 +7229,1304337,nadya,,,,"

Nadiia Basos. MSc in Geomatics. BSc in Environmental sciences. Interested in web map development, interpolations and modelling (from wildlife species distribution to hydrodynamics).

+",2012-03-07 01:40:48.383 +23467,431693,rnjai,Mexico,,https://rnjai.com,,2013-11-07 10:31:14.077 +13918,2248598,learnOR,,,,,2013-01-15 18:58:28.887 +23258,3524039,Jason,"Houston, TX",,http://dataprediction.blogspot.com/,"

I'm a data analyst with a PhD in Economics currently working for the consulting firm AlixPartners.

+",2013-11-01 16:33:15.700 +11117,1873485,beuhbbb,,,,"

Happy to learn, happy to help

+",2012-09-24 17:50:37.940 +23108,3502362,lovekesh,"New Delhi, India",,,,2013-10-28 16:08:53.440 +22626,22022,Blaisorblade,"Berlin, Germany",,http://www.informatik.uni-marburg.de/~pgiarrusso,"

Researcher in functional (and object-oriented) programming languages and their theory, especially Scala. Currently working in industry on machine-checked proofs of functional correctness for concurrent imperative programs.

+

Ex Linux kernel programmer, Scala/Java/Haskell/C/C++/Java developer.

+",2013-10-12 01:31:43.297 +22762,2885599,Rom,,,,,2013-10-16 15:49:20.717 +16039,1604330,GeorgeWilson,Singapore,,,,2013-03-20 21:14:06.027 +1124,115118,Alex Holcombe,"Sydney, Australia",,http://alexholcombe.wordpress.com/,"

@ceptional

linkedin

+",2010-10-20 09:50:40.767 +23389,3539809,Bart,,,,,2013-11-05 16:51:39.300 +22899,3467730,Kirsty,,,,,2013-10-21 11:16:10.237 +22848,2811229,Gilles San Martin,Belgium,,,,2013-10-18 22:25:43.353 +23532,3413362,sdevlin,"Montreal, Canada",,,"

Undergraduate student in Math and Computer Science at McGill University in Montreal, Quebec.

+",2013-11-08 19:23:37.687 +1717,209234,r_31415,,,,,2011-01-06 19:24:44.620 +23534,3556682,user32528,,,,,2013-11-08 19:34:53.347 +22651,3431950,Lawrence,,,,,2013-10-13 13:09:09.757 +21918,2305450,avocado,,,,,2013-09-21 10:01:34.170 +22731,113178,Valentin H,,,,,2013-10-15 20:21:08.253 +23099,63218,xkrz,Canada,,,"

A Stackflow-er :)

+",2013-10-28 13:56:36.277 +22723,3442007,thomeroqir,,,,,2013-10-15 18:20:33.817 +18416,2712076,user75402,,,,,2013-05-28 22:49:47.037 +23177,1187953,Maxim Khesin,,,,,2013-10-30 16:22:13.387 +8361,1453919,BGreene,"Dublin, Ireland",,,"

Industrial researcher with expertise in biomedical signal processing and pattern recognition.

+",2012-05-02 13:06:11.257 +23052,1869930,Dmytro Savochkin,"Lviv, Lviv Oblast, Ukraine",,,,2013-10-26 00:01:06.250 +23046,3491484,texastoast7,,,,,2013-10-25 17:58:52.327 +786,178774,Vass,USA,,,"

This is the third phase of my StackOverflow/Stackexchange experience.

+ +

Maths/Stats and the IT means to do it! (does AI fit into it or does it revolve around it? or... do they revolve around I?)

+",2010-08-26 17:19:15.257 +17670,303118,tmakino,,,,,2013-05-07 14:20:48.663 +22475,3407924,sara,,,,,2013-10-08 12:31:47.380 +22549,3417257,user99980,,,,,2013-10-10 06:33:41.573 +22939,3474345,toolpool,,,,,2013-10-22 16:13:48.050 +1945,275327,Josh,,,,,2011-02-04 21:33:28.620 +7275,1311272,snape,,,,"

I am not a statistician but I am interested in learning Statistics.

+",2012-03-09 11:55:54.627 +23420,2411131,Shaowei Ling,"Nanjing, China",,,"

I am a postgraduate of Southeast University in Nanjing, China.

+",2013-11-06 07:52:31.957 +21119,2631368,sachinruk,"Sydney NSW, Australia",,https://sachinruk.github.io,"
    +
  • PhD in Bayesian Machine Learning.
    • +
  • Obsessed with DL.
    • +
  • Currently dipping toes in Reinforcement Learning.
    • +
+",2013-08-26 01:41:57.983 +20828,3151620,Mayou,,,,"

Quant at an investment management firm.

+",2013-08-15 13:23:28.443 +23497,3552125,Vivian,,,,,2013-11-07 21:51:39.410 +18998,1680541,Xander,,,,,2013-06-16 14:27:38.900 +17580,2722398,acbart,,,,,2013-05-03 21:05:29.093 +9063,942536,Cam.Davidson.Pilon,"Waterloo, ON, Canada",,http://www.dataorigami.net,"

Blog at DataOrigami and ControlledMold. CEO at Pioreactor.

+",2012-06-08 18:05:01.960 +19822,3035457,Bijoy,,,,,2013-07-11 20:57:03.617 +22618,29283,taserian,South Carolina,,http://im-strange.blogspot.com/,"Mathematics, logic and outright outlandishness.",2013-10-11 19:21:41.103 +37646,3412739,chri5,,,,,2014-09-14 08:15:02.660 +21182,3207579,Avraham,New York Metropolitan Area,,http://www.avrahamadler.com,"

US-based non-life actuary and R programmer. I maintain some packages on CRAN including Delaporte, lamW, Pade, revss, and minimaxApprox.

+

$argon2id$v=19$m=64,t=512,p=2$UHLafHyFcVlL31U8ykB66A$fbQ/Uj9TR5qHtliLnvsBlA

+",2013-08-28 06:01:41.090 +12495,1979338,Rafael,"Hobart, Australia",,,"

I'm an eternal stat-R apprentice.

+",2012-11-20 04:55:17.293 +23122,1253573,user1213492,,,,,2013-10-29 06:44:10.490 +22633,2195866,Gilles Pilon,"Naperville, IL, USA",,,"

Professional engineer. Data scientist. Python developer. Lean Six Sigma Master Black Belt.

+",2013-10-12 12:31:22.350 +1542,509609,Jen,,,,,2010-12-13 23:39:26.947 +23363,3537094,Ben,,,,,2013-11-05 05:37:44.340 +23476,3550060,user32454,,,,,2013-11-07 14:15:45.333 +23176,3372585,Slyron,,,,,2013-10-30 15:37:51.767 +23075,3497904,user2925487,,,,,2013-10-27 17:00:57.470 +21885,2998457,Julian Karch,"Berlin, Germany",,,,2013-09-19 22:12:29.957 +15183,2412204,fredrikhs,Southern Norway,,,"

MSc. in Economics. Interested in programming and data analysis, particulary time series analysis.

+",2013-02-25 11:17:06.007 +22801,3451915,user31621,,,,,2013-10-17 16:35:03.233 +23006,1731307,oveoyas,,,,,2013-10-24 08:00:21.000 +22791,2321257,statusfailed,,,,,2013-10-17 10:12:44.497 +11440,1705277,sashkello,"Sydney, Australia",,,"

Laß die Zeit an dir ablaufen wie Wasser

+",2012-10-08 07:23:31.760 +22774,78417,Garret Smith,,,,,2013-10-16 20:31:45.560 +23434,2771810,Glob Cropper,,,,,2013-11-06 15:10:33.623 +23371,3418978,Dr. Stevil,,,,,2013-11-05 11:42:42.050 +5086,948131,Tyler Rinker,"Buffalo, NY",,http://trinkerrstuff.wordpress.com/,"

I’m a husband and father of 2 girls. I lead data science @ Kangarootime, #Python & #rstats enthusiast, #dataviz geek, and #nlp buff.

+",2011-10-30 13:20:23.900 +22916,3470047,Dr.Sheldon Cooper,"Pasadena, California",,,"
    +
  • Theoretical physicist
    • +
+",2013-10-21 20:15:05.410 +23473,3549654,Yuri,"Kyiv, місто Київ, Україна",,https://www.yburger.com,"

Head of AI Department at ZoralLabs. Key interests are: artificial intelligence, machine learning, data mining, distributed computing, big data... My personal website: https://www.yburger.com

+",2013-11-07 12:41:24.940 +22824,3455388,student,,,,,2013-10-18 09:21:02.257 +1636,103559,leonbloy,"Buenos Aires, Argentina",,,"

Hernan J. Gonzalez

+

Buenos Aires, Argentina

+

PNGJ: https://github.com/leonbloy/pngj/

+",2010-12-28 14:55:22.660 +22867,3462564,mixtureModel,,,,,2013-10-20 02:11:50.450 +23513,142194,Quester,,,,,2013-11-08 06:50:14.660 +23484,3551139,Clementina,,,,,2013-11-07 17:44:32.547 +23386,3539376,Paul,Vienna,,,"

aquila non capit muscam!

+",2013-11-05 15:24:41.793 +22783,3449012,phantason,,,,,2013-10-17 05:20:18.950 +23422,1765444,vvasch,,,,,2013-11-06 08:41:23.063 +22678,1033471,mojovski,,,,,2013-10-14 14:34:18.813 +19547,2931115,SKY,,,,,2013-07-03 17:49:46.973 +19559,2576067,Sol,,,,"

Psycholinguistics researcher

+",2013-07-04 01:55:07.513 +8074,1235662,Marc in the box,,,http://menugget.blogspot.com/,,2012-04-17 14:34:53.120 +22946,2473468,AlbertusW,,,,,2013-10-22 21:06:21.953 +20795,3171977,forecaster,,,,,2013-08-14 01:31:10.303 +23446,2288031,working4coins,,,,,2013-11-06 20:06:00.680 +12282,2036221,Pat,,,,,2012-11-12 15:30:48.933 +4854,974824,DartPrivateer,,,,,2011-10-15 02:49:01.160 +11353,60844,Assad Ebrahim,"London, England United Kingdom",,http://www.mathscitech.org/articles,,2012-10-04 10:41:03.333 +23397,3540471,user32359,,,,,2013-11-05 19:20:36.173 +23132,3507188,user32039,,,,,2013-10-29 14:06:15.503 +3894,510162,hr0nix,,,,,2011-08-05 09:31:14.967 +22874,3464199,user31712,,,,,2013-10-20 14:37:54.647 +14799,2358692,Ray Koopman,,,,,2013-02-12 19:05:13.730 +23244,257657,BigChief,,,,,2013-11-01 11:22:32.527 +23026,1555884,Yu Yang,,,,,2013-10-25 05:11:24.337 +22617,3263034,Tom Palmer,,,,,2013-10-11 19:12:00.953 +22907,3468722,hans,,,,,2013-10-21 14:58:19.417 +20097,3071766,user2602256,,,,,2013-07-20 13:57:31.517 +16504,485269,xbsd,,,,,2013-04-04 01:48:09.553 +23130,473684,Vincent,"Laboratoire d'Annecy de Physique des Particules, France",,https://www.linkedin.com/in/vincent-reverdy,"

Researcher, astrophysicist, computer scientist, programming language expert, software architect and C++ standardization committee member.

+

LinkedIn: https://www.linkedin.com/in/vincent-reverdy

+",2013-10-29 12:59:01.220 +15025,511627,Lepidopterist,,,,,2013-02-20 03:58:39.913 +24121,3625299,Fabian,,,,,2013-11-24 23:03:15.827 +22769,3447384,Rob F,,,,,2013-10-16 19:42:42.730 +22695,3438289,user31497,,,,,2013-10-15 01:09:29.977 +2081,465047,ttnphns,"Moscow, Russia",,https://www.spsstools.net/en/KO-spssmacros,"

A SPSS user (and developer, not affiliated with), data analyst.

+",2011-02-16 19:33:34.657 +20773,3123897,Ellis Valentiner,,,,,2013-08-13 16:12:25.523 +23127,3506042,sign,,,,,2013-10-29 10:03:02.447 +22836,3160162,EPSILONsdfsdfdsf,,,,"

Please delete my account.

+",2013-10-18 15:05:22.563 +23188,3443278,user2884661,,,,,2013-10-30 20:39:55.270 +5643,161488,Robert Kubrick,,,,,2011-12-04 20:39:43.713 +23076,3085199,Ping Jin,,,,,2013-10-27 18:49:47.733 +22981,3001934,user2547279,,,,,2013-10-23 17:31:11.980 +22872,3463784,CuriousCat,,,,"

I always struggled with Statistics in school.

+ +

I'm here to see if I can do better now - fifteen years later.

+ +

Some of my questions might seem lame.

+",2013-10-20 12:05:51.743 +23442,3546054,oren,,,,,2013-11-06 19:25:42.607 +27332,1143891,whenov,,,,,2014-02-12 05:37:18.303 +23540,160509,Jakub Roztocil,,,https://httpie.io/,"

Software engineer. Creator of HTTPie & co.

+",2013-11-08 21:07:47.077 +22675,934262,vvavepacket,"Miami, FL",,,"

so curious with number theory

+",2013-10-14 11:17:25.780 +22862,3461349,user31696,,,,,2013-10-19 17:34:26.353 +23524,3555271,Sandra,,,,,2013-11-08 14:00:25.287 +23163,2511051,datddd,,,,,2013-10-30 04:25:38.927 +5821,435185,AdamO,Nakoja Abad,,,"

"The trappings of luxury cannot save you from the nail-biting boredom of repetitive brain injury."

+",2011-12-14 21:46:36.197 +22817,3453959,user31641,,,,,2013-10-18 02:39:46.243 +23239,390042,nvcnvn,"Ho Chi Minh City, Vietnam",,http://nguyen.open-vn.org,"

I call myself an old-style software engineer, always trying to solve the problem simple as possible. Building strong backend for performance and scalability, adapting computer science in everyday tasks is what I looking for in career path.

+",2013-11-01 04:03:15.543 +15120,155034,SKM,"Singapore, Singapore",,,,2013-02-22 17:12:53.983 +22608,1912945,Girishkumar,"Mumbai, India",,http://www.isical.ac.in/~mtc1113/,,2013-10-11 14:28:01.963 +7007,1273790,Zen,"São Paulo, Brazil",,,"

Paulo C. Marques F.

+

BA in Physics. PhD in Mathematical Statistics.

+

Interested in Machine Learning, Causal Inference, Bayesian Statistics, Statistical Theory, and stochastic composition of string quartets.

+

Teaches Statistics, Machine Learning, Predictive Modeling, Python, R and Data Science at Insper.

+
+

"Artificial Intelligence is no match for Natural Stupidity." (Anonymous)

+",2012-02-23 21:59:40.227 +20312,2278287,Barb90,,,,,2013-07-27 12:53:36.160 +23021,3486685,user31894,,,,,2013-10-24 20:05:57.813 +23004,211135,Alberto Fernández,"Barcelona, Spain",,http://albertofem.com,"

Programmer.

+",2013-10-24 07:24:30.847 +4831,255542,jseabold,,,,"

Statsmodels developer
+Github
+Twitter

+",2011-10-13 16:49:15.740 +22784,3403506,Shaxi Liver,,,,,2013-10-17 08:02:34.503 +23220,3519482,user32145,,,,,2013-10-31 15:49:57.877 +22913,2402243,Tom,,,,,2013-10-21 17:59:10.943 +4656,900727,Dilip Sarwate,"Urbana, IL",,,"

I am a retired professor of electrical and computer engineering with a lifetime of experience teaching probability and statistics to reluctant engineering undergraduates.

+",2011-10-03 16:59:55.347 +23542,1687146,LostPhysx,Germany,,https://areinhardt.eu/,,2013-11-08 22:17:21.377 +9749,1663503,Robert Jones,,,,"

merge keep - done on 21Jan

+",2012-07-17 09:53:51.480 +14919,2376283,Fuca26,,,,"

Doctorate in economics, first-gen. Love traveling, sports, chess, readings, and languages. +My research focuses on labor economics; it also embraces different aspects of applied microeconomics: housing, sport, behavioral, and education economics.

+

When I do not do research I am a middle/long-distance runner. +I recently converted to doggies worshipping.

+

I was a waiter, then a statistician wannabe, and finally a prof in economics.

+",2013-02-17 00:35:13.563 +399,509491,Thylacoleo,,,,,2010-07-28 00:56:47.640 +22716,3441318,thaq,,,,,2013-10-15 15:40:03.783 +22909,1718644,kotoll,,,,,2013-10-21 15:42:32.237 +22548,3417191,user31315,,,,,2013-10-10 06:20:04.270 +22823,1401141,bognick,"Athens, Greece",,,,2013-10-18 09:16:24.410 +23202,242979,campeterson,"Utah, United States",,http://campeterson.com,,2013-10-31 06:53:45.650 +22691,3435348,ali nouri,,,,,2013-10-14 21:49:07.817 +11283,973679,zima,,,,,2012-10-02 10:45:07.113 +9081,215207,kjetil b halvorsen,Tellus,,,"

Mathematical statistician (the image is my grandfather in 1927, just returned to Tromsø after wintering at Jan Mayen)

+

For contact, my email:

+
+
<first name><My public seed> at gmail dot com
+
+
+

Below a list of some questions I have responded to, where I consider my response interesting:

+

how-does-saddlepoint-approximation-work

+

what is the intuition behind svd

+

goodness of fit and which model to choose linear regression or poisson

+

Estimating parameters for Binomial with both $n$ and $p$ unknown

+

what is the difference between finite and infinite variance

+

general sum of gamma distributions

+

why should we use t errors instead of normal errors

+

maximum likelihood estimation mle in layman terms

+

difference of two iid lognormal random variables

+

non transitivity of correlation correlations between gender and brain size

+

Intuition on the Kullback-Leibler divergence

+

Taleb and the black swan

+

Correlations between continuous and categorical nominal variables

+

Why does logistic regression become unstable when classes are well separated

+",2012-06-09 22:52:37.473 +22555,3382596,AsymLabs,Great Britain,,http://asymlabs.org,"

AsymLabs (TM) is a brand name of Applied Numerics Ltd of Great Britain that is also under license to Resource CUA of Amsterdam. AsymLabs provides numerical analysis tools for civil engineering, construction and related fields that can be used to optimize and accelerate the infrastructure construction process in the emerging economies of the developing world - particularly hot and tropical environments. This leads to lowered construction cost, accelerated construction, and better service performance.

+ +

In the course of our work, we sometimes develop more general software tools or libraries that we donate to the open source community under MIT or GNU GPLv3 licence terms. Most, if not all of these, are for Unix based operating systems, but from time to time they are made compatible with Microsoft Windows. They can be found at our repositories at GitHub.com and BitBucket.org.

+ +

These repositories are being expanded monthly and we invite you to visit them. The primary languages of our work are Bash, C++ and Lisp.

+",2013-10-10 09:03:56.503 +22931,2359715,smrati katiyar,,,,,2013-10-22 12:36:52.613 +22912,3469477,Sabina,,,,,2013-10-21 17:45:28.917 +346,109249,Henrik,"University Of Warwick, Gibbet Hill Road, Coventry, Vereinigtes Königreich",,http://singmann.org,"

Assistent professor of psychology at the University of Warwick, UK.

+ +

My primary programming language is R.
+I am maintainer of R packages afex, MPTinR, and acss.

+ +

Besides R, I use Python (using PsychoPy) and JavaScript for running experiments and occasionally other languages.

+ +

A list of my publications can be found on my homepage (usually with possibility to download the papers, data, and analysis scripts).

+",2010-07-27 10:01:37.337 +23088,3144687,Jie Wei,Huazhong University of Science and Technology,,,"

Assistant Professor, School of Economics, Huazhong University of Science and Technology

+",2013-10-28 04:30:44.510 +16474,2583847,Maarten Buis,"Konstanz, Germany",,http://www.maartenbuis.nl,"

Sociologist and Stata user. I have mainly worked on variations on logistic regression, interactions and mediation. Substantively, I worked mostly on differences in educational attainment between children with different parental backgrounds.

+",2013-04-03 10:24:26.900 +23464,3183849,shad0w_wa1k3r,Dubai - United Arab Emirates,,https://www.ashishnitinpatil.com,"

Husband | Pythonista | Engineer | Co-founder @ MySyara | Certified BlockChain Dev | Dota2 fanatic
+Love problem solving & programming for the same.

+

CryptoThanks - ETH : 0x464512ACAfaf0BEbA4BBDE4B6305E5B9E57d87Fc

+",2013-11-07 05:45:01.453 +22719,1133928,SuppaiKamo,Denmark,,,,2013-10-15 17:02:02.373 +23256,2627386,Jens Jensen,,,,,2013-11-01 15:04:28.380 +23212,1494685,EzzatA,"Graz, Austria",,https://plus.google.com/116823604753279239388,"

TU Graz Computer Science MSc student. Python, Django, and Javascript ninja

+",2013-10-31 13:18:42.803 +22965,140373,Daniel Winterstein,"Edinburgh, United Kingdom",,https://good-loop.com,"

I am co-founder and CTO for Good-Loop.

+

I also have a +personal homepage.

+",2013-10-23 10:59:13.510 +23230,3520791,Matthew C,,,,,2013-10-31 21:33:02.790 +23491,139200,G-wizard,"Montreal, Canada",,,,2013-11-07 20:29:40.943 +23776,3588691,Thijs van der Vaart,,,,,2013-11-15 06:58:00.907 +22974,3479712,John,,,,,2013-10-23 15:38:02.280 +22894,3325382,user2795569,,,,,2013-10-21 04:34:02.463 +23339,3534783,thatnewguy,,,,,2013-11-04 16:48:47.160 +7615,1353035,purple51,,,,,2012-03-26 01:46:00.170 +23306,119676,Agent1891,"Aachen, Germany",,http://behery.github.io,"

I'm just here trying to get things done.

+ +

SOreadytohelp

+ +

Twitter -- @Agent1891

+",2013-11-03 14:58:41.637 +23486,2854695,Manoj Kumar,India,,,,2013-11-07 18:02:57.597 +22725,3442096,Gumby,,,,,2013-10-15 18:43:28.630 +23546,1241901,rajohnson90,Wisconsin,,,"

I'm a graduate student of computer science with an undergraduate in Japanese language.

+",2013-11-08 23:41:24.353 +23226,1073022,user1071847,,,,,2013-10-31 18:55:04.490 +23054,144469,pankaj28843,"Copenhagen, Denmark",,http://psjinx.com,,2013-10-26 01:10:14.443 +23067,2178793,Pattisahusiwa,Indonesia,,,,2013-10-27 06:05:18.207 +23189,3221594,Greg,,,,,2013-10-30 20:46:20.517 +19359,2945859,Bill Bradley,,,,"

I'm a mathematician by training, but currently co-run Mirabolic Consulting, which focuses on machine learning and data science problems.

+",2013-06-27 15:23:33.807 +23461,3547467,JConway,,,,,2013-11-07 02:27:04.507 +15827,2038743,Nick Cox,"Durham, UK",,,"

I work mostly with environmental data, secondarily with social science data. My interests include statistical graphics, exploratory data analysis, generalised linear models, distributions, transformations and directional data analysis. I am an active Stata user, have both contributed to Stata itself and published many additional Stata programs, and have written widely on the use of Stata, especially in the Stata Journal. I have a strong side-interest in the history of statistics.

+",2013-03-15 13:57:54.467 +23013,218648,Tacio Medeiros,,,,,2013-10-24 13:10:35.237 +22542,3416394,Thomas,,,,,2013-10-10 01:51:45.710 +23024,3240947,Robson,"Recife, Brazil",,https://sites.google.com/site/robsondtigre/,,2013-10-25 04:06:52.627 +10684,512335,Flounderer,,,,,2012-09-03 23:44:58.677 +11506,1924428,Samo Jerom,,,,,2012-10-10 14:24:43.837 +23319,3531574,Nathan M,"Alma, Wisconsin, USA",,,,2013-11-03 23:17:55.293 +23295,1481103,Oleg Melnikov,"Bellevue, WA",,http://www.linkedin.com/in/olegmelnikov,"

http://oleg.rice.edu +http://www.linkedin.com/in/olegmelnikov

+",2013-11-02 20:44:48.917 +22575,2620197,Kim,,,,"

Code User

+",2013-10-10 18:05:08.563 +21029,2259709,Drew75,,,,,2013-08-22 14:20:37.097 +23303,3529923,Amy A,,,,,2013-11-03 13:02:01.453 +10594,1796034,tiantianchen,,,,,2012-08-30 08:19:16.923 +23090,3499927,Man Ray,,,,,2013-10-28 05:47:22.693 +22926,3471893,user31777,,,,,2013-10-22 07:08:23.553 +22989,1559121,Iron Savior,"Seattle, WA",,https://github.com/IronSavior,"

DEMACIA!

+",2013-10-23 19:29:55.120 +11210,1886970,Quartz,,,,"

Monte Carlo, risk, QMC, statistical efficiency, high dimensional approximation...

+",2012-09-28 10:29:04.207 +82,64496,jebyrnes,,,,,2010-07-19 19:48:20.350 +19681,2167500,zkurtz,Pittsburgh,,,"

Statistician and consultant.

+",2013-07-08 17:35:17.070 +10372,1369402,HelloL,,,,,2012-08-19 12:00:00.683 +20222,2233497,Steve,,,,,2013-07-24 14:49:52.873 +22795,3450768,cristis,,,,,2013-10-17 12:51:21.873 +22049,2734621,TangoStar,Germany,,,,2013-09-25 11:25:10.927 +22861,26725,Ankur,"Melbourne, Australia",,,"

A junior BA have some experience in the financial services industry. I do programming for my own personal projects hence the questions might sound trivial.

+",2013-10-19 16:59:35.120 +22458,323365,Achint,,,,,2013-10-08 01:07:56.313 +23018,3485578,user31889,,,,,2013-10-24 16:00:26.397 +23218,3519146,Matthew,Singapore,,,,2013-10-31 14:39:35.600 +23413,3541779,user32378,,,,,2013-11-06 02:00:54.243 +23406,2424498,geofflittle,Seattle,,,,2013-11-05 23:05:14.573 +23077,337671,KeithSmith,United States,,http://fernleaf07.blogspot.com/,"

Embedded Software Engineer.

+ +

Eclipse, C, C++, WinCE, eCos, FreeRTOS, Inkjet Printers, ICP-EOS and IR spectrometers

+ +

Learning about Python and JSON

+ +

Familiar with NXP Cortex MCUs

+ +

Amateur astronomer and pteridologist

+",2013-10-27 18:56:55.847 +23462,926622,jrc1000,,,,,2013-11-07 04:03:34.003 +5556,1016273,Innuo,,,http://mlstat.wordpress.com,,2011-11-29 19:33:58.173 +22649,3431547,user31436,,,,,2013-10-13 10:04:32.353 +22968,282375,James,"Sheffield, United Kingdom",,,,2013-10-23 12:31:26.027 +19492,2995702,Copuleros,,,,,2013-07-02 10:58:26.740 +17076,2664142,Patrick,,,,,2013-04-20 21:00:03.237 +1895,329305,cardinal,Not from around here,,http://none,,2011-01-29 21:42:27.863 +15583,1021083,0x90,,,,"

echo \[q\]sa\[ln0=aln256%Pln256/snlbx\]sb3135071790101768542287578439snlbxq|dc

+",2013-03-08 20:27:24.483 +21523,3127210,Raz_Lobo,"El Ejido, Spain",,http://www.mucharuina.com,,2013-09-08 13:22:10.560 +22950,3172304,bravetang8,,,,,2013-10-23 01:03:32.633 +23023,3487363,user103065,,,,,2013-10-24 23:19:38.397 +23333,3533294,Fldm,,,,,2013-11-04 11:28:40.793 +23281,3508040,Daniel Gotthardt,,,,,2013-11-02 12:24:29.447 +20456,792968,Andrea,,,,,2013-08-01 19:10:55.053 +22480,1796529,Gerome Bochmann,,,,"

Junior dev, mostly javascript and angular in particular. I have two years experience in R and a Master in Cognitive Sciene; {LaTeX} enthusiast, mindful meditationist and computer nerd of the third generation.

+",2013-10-08 14:43:02.427 +12152,967618,power,,,,,2012-11-07 07:36:08.563 +14965,2381666,Cagdas Ozgenc,,,https://www.linkedin.com/in/cagdas-ozgenc-b709929/,"

Investor, statistics hobbyist

+",2013-02-18 14:12:19.150 +22822,3455354,Jos,,,,,2013-10-18 09:14:44.847 +22807,3123733,ievgenii,,,,,2013-10-17 21:51:11.407 +22937,1962493,damienfrancois,Belgium,,http://www.damienfrancois.be,,2013-10-22 15:57:46.907 +22763,275509,mikepk,"Boston, MA",,http://mikepk.com,,2013-10-16 16:30:02.500 +23142,3508281,user32053,,,,,2013-10-29 17:36:43.217 +13051,94831,Gabra,,,,,2012-12-10 14:14:41.870 +24527,2761061,Francis Smart,"Maryland, USA",,http://www.EconometricsBySimulation.com,,2013-12-06 04:28:04.883 +23266,2779111,junkaholik,"Vancouver, BC, Canada",,https://spzfolio.wordpress.com/,"

Data scientist, data visualization enthusiasts, avid user of Python (and Jupyter). +I dream of doing more D3. Currently using data science to assess and improve science education.

+ +

Interests: ultimate frisbee, climbing mountains, martial arts, photography, and underwater sign language.

+",2013-11-01 22:31:56.647 +23173,2214814,Sulli,,,,,2013-10-30 14:05:10.450 +14360,2301670,mrz,"Oxford, United Kingdom",,,,2013-01-29 13:34:31.547 +23454,3527998,user2948524,,,,,2013-11-06 23:40:25.140 +22753,3352915,Paul,,,,,2013-10-16 12:41:11.517 +22479,3408572,user31230,,,,,2013-10-08 14:42:31.953 +22410,435249,bernie2436,,,,,2013-10-06 15:37:55.093 +22569,1445214,Varun Jain,,,,,2013-10-10 15:23:06.633 +3731,184039,Nathan VanHoudnos,"Pittsburgh, PA",,http://edustatistics.org/nathanvan/,"

I'm a PhD student in the joint Statistics and Public Policy program at Carnegie Mellon University.

+",2011-07-22 13:32:10.580 +23340,3534834,Fred,,,,,2013-11-04 17:03:13.133 +22711,3039268,CMP,Argentina,,,,2013-10-15 13:17:39.517 +20470,964416,Zhubarb,"London, United Kingdom",,,"

When you stare long into the thesys, the thesys stares back into you.

+",2013-08-02 12:27:30.800 +23116,2125820,George Fisher,"Boston, MA, United States",,http://www.georgefisher.com,"

George Fisher

+

Retired Morgan Stanley Managing Director with MIT Masters degree actively seeking career in cutting-edge technology. Perfect fit for a Finance Vertical: interface between a technology firm and Finance-Industry C-Suite executives & technologists.

+

Excellent programmer, data scientist; Kaggle Expert, GitHub, StackExchange and scikit-learn contributor; Stanford University training. Cloud: Amazon Web Services Architect and Linux certified. Successful large-group manager, collaborative individual contributor, extensive finance-industry experience. MIT Master’s degree.

+
• Kaggle Silver for stacked regression analysis of financial data
+• Kaggle Bronze for convolutional neural network / OpenCV analysis of aerial photographs  
+• Did all of the start-up and data-analysis work for Health-Care Twitter Analysis  which tracked progression of diseases via Twitter posts.
+• Numerous GitHub stars for MNIST algorithm analysis 
+
+• Programming
+    ◦ PHP, SQL, JavaScript
+
+• Data Science, Analysis
+    ◦ R, Python, Spark
+    ◦ Stanford University Data Mining and Applications 2016
+    ◦ Kaggle Expert
+
+• Linux (certified sysadmin), Docker, Git
+
+• Cloud: AWS (certified Architect)
+• Finance
+    ◦ MIT Master of Finance 2012
+    ◦ 30-year Wall Street Career
+        ▪ Real-Estate Finance 2007 - current
+        ▪ Investment Manager 2005 - 2011
+        ▪ Prudential CAO, Board Member 2002 - 2004
+        ▪ Fidelity CIO, EVP 1998 - 2002
+        ▪ Morgan Stanley Managing Director 1981 - 1998
+    ◦ BA in Economics 1976
+
+

For more details please see https://georgefisher.com/resume/resume.pdf

+",2013-10-29 00:13:57.977 +21398,3260554,Jan Modus,,,,,2013-09-04 09:26:47.983 +22885,3465421,Anton,,,,,2013-10-20 21:37:32.620 +3183,229913,David J. Harris,"Florida, United States",,http://davharris.github.io,,2011-06-03 04:30:18.257 +37033,4963444,greenall,,,,,2014-08-30 22:54:35.713 +22792,511732,Ufuk Can Bicici,,,,,2013-10-17 10:35:07.370 +23451,2980224,mlo,,,,,2013-11-06 22:14:45.610 +22928,2805215,frank,,,,,2013-10-22 08:19:37.080 +22681,55154,George Powell,,,,"

Software Engineer. Interested in web technologies, web security, web scale. Enjoys a challenge and learning new stuff.

+",2013-10-14 17:12:17.350 +22627,2993324,Michael,San Jose,,,,2013-10-12 02:02:09.157 +22583,3421213,geo,,,,,2013-10-10 20:48:01.520 +22826,3455544,bob hope,,,,,2013-10-18 09:50:21.567 +23312,3531019,ukituki,,,,,2013-11-03 19:37:15.580 +22889,3465843,user31733,,,,,2013-10-21 00:38:08.623 +7016,1274641,Al-Ahmadgaid Asaad,"Iligan City, Philippines",,http://www.alstatr.blogspot.com,"

Student

+",2012-02-24 06:48:05.733 +18403,2809410,Michael,,,,,2013-05-28 16:09:37.057 +13537,2198217,Davide,,,,"

M.S Student in Biostatistics @ University of Bologna

+",2013-01-02 16:04:05.927 +23416,1736244,Joe Li,,,,,2013-11-06 05:14:45.850 +21985,1811490,Michael,,,,,2013-09-23 21:38:39.343 +15723,2474148,David M W Powers,"Flinders University, South Australia",,http://david.wardpowers.info,"

I'm a professor/researcher in artificial intelligence and cognitive science with a special interest in language learning - computational cognitive psycholinguistics. That is I am particularly interested in building computationally and cognitively plausible models of how we learn and communicate about the world, and how to get computers/robots to learn and communicate about the world in a similar way, as well as how better to teach people languages and about language.

+ +

From the perspective of learning, my focus is on unsupervised learning - children learn to speak without a teacher, without being taught what nouns and verbs are. From the perspective of language, I like Tagmemics and Cognitive Linguistics - consistent with my focus on unsupervised learning, language and learning boil down to what we think is similar.

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Formally this gives rise to similarity or distance measures used in learning, and we also need to account chance levels or prevalences. It also gives rise to metaphor, metonymy, grammar and related linguistic constructs, which define Cognitive Linguistics, as well as the basic ideas of Phonemic and Tagmemic analysis, Contrast in Analogous Environments and Complementary Distribution. It similarly explains the richness of polysemy and why there is really no such thing as synonymy, as when anything is different we look for other things to be different to learn from, using the part that is similar as context or paradigm, a substrate for the learning. We are continuously developing and modifying the range of meaning of language with our personal, social and cultural development, as we press old words or morphemes into new roles.

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I also edit the new Springer journal, Computational Cognitive Science that aims to bridge the gap between Computational Intelligence and Cognitive Science.

+",2013-03-13 05:19:39.237 +11808,1718514,PascalVKooten,Netherlands,,http://www.linkedin.com/profile/view?id=190745232,"

Software enthusiast. Blockchain, Cognitive apps, machine learning & AI; to name a few.

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Here's my LinkedIn and here is my GitHub.

+",2012-10-23 12:50:50.990 +22736,233335,davidjhp,,,,,2013-10-15 22:47:07.093 +21204,3230813,elsonidoq,"Buenos Aires, Argentina",,http://pablozivic.com.ar,"

I’m curious and enthusiastic.

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I specialize in building computational models to explain data - data science - with solid knowledge in statistics, machine learning and programming. I’m always thirsty for new data sets to taste new state of the art techniques.

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Academically I apply my knowledge of massive data analysis to music corpora - computer musicology. My thesis explores the problem of how to build computer models that compose music based on the music psychology theories of the last three decades. Right now, at my PhD I’m analyzing how the very notion of style necessarily impacts on certain statistics of the music belonging to it.

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Industrially developed algorithms for online audience targeting and optimization of online campaigns, market reaserch on twitter, information extraction systems, content classification, keyword extraction, etc.

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As a hobby I like to develop innovative interfaces for music creation, use the standard ones (guitars, keyboards, drums, etc.) and also juggling.

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I like to be in creative spaces and do interdisciplinary work. But above all, complex problems that allows me to keep learning.

+",2013-08-28 15:56:16.150 +23355,2302841,Sean C. Rife,"Stow, OH",,http://www.seanrife.com,"

Ph.D. in Social Psychology. New Assistant Professor. My research deals with relationships and technology.

+",2013-11-04 23:18:22.737 +22915,3394778,girolamous,,,,,2013-10-21 19:42:15.257 +23483,3428827,Roberto,"Palermo, Italy",,,"

PhD in Statistics, my field of interest is mainly survey sampling and inference on finite populations. +I also enjoy programming in R.

+",2013-11-07 17:04:36.007 +23103,3501996,DonutPhil,,,,,2013-10-28 14:55:58.223 +16737,1132433,ramgorur,,,,"

Interested in all sorts of stuffs.

+",2013-04-11 02:30:54.253 +22881,1704481,Eric Chen,,,,,2013-10-20 19:28:45.027 +22359,3148491,visoft,,,,,2013-10-04 13:25:01.307 +8629,51051,andreas-h,,,,,2012-05-16 08:42:47.713 +22780,503639,dpollitt,Minneapolis,,http://www.properspective.com,"

Photographer, tech head, and extreme sport enthusiast.

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I'm an amateur who likes to shoot everything from portraits to landscapes. My favorite venues are half way up a 14k mountain, Ontario in Fall, and the Mediterranean at sunset.

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I love talking technology, new equipment, and Canon lenses.

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+",2013-10-17 02:37:35.930 +23310,3530949,asharma,"Toronto, ON, Canada",,,,2013-11-03 19:14:05.977 +22785,1772269,Stephen_B,,,,,2013-10-17 08:33:16.957 +11013,1849501,Chris,,,,,2012-09-20 01:23:27.523 +221,102298,steffen,Frankfurt Area (Germany),,,"

Data Scientist

+",2010-07-22 05:56:36.677 +23449,3546638,adamToplz,,,,,2013-11-06 21:40:38.437 +22702,209030,Yaniv Aknin,"London, United Kingdom",,http://tech.blog.aknin.name,"

I like bits and humans. SRE at Google. Opinions are my own.

+",2013-10-15 05:42:22.333 +22554,3417872,andrea,,,,,2013-10-10 08:58:21.843 +19374,2234051,marcellt,,,,,2013-06-27 21:18:41.817 +4871,287086,d_a_c321,"New York, NY",,,,2011-10-16 23:19:28.467 +23299,96938,rold2007,"Sapporo, Hokkaido Prefecture, Japan",,,"

Freelance software developer. Working in image processing (computer vision). Doing custom machine learning as a hobby.

+",2013-11-03 08:02:04.637 +10986,132790,Josef,"Montreal, Quebec",,,"

statsmodels maintainer and developer, semi-retired from scipy.stats maintainance

+",2012-09-19 00:02:29.913 +23369,1920948,Pavel 'Strajk' Dolecek,"Brno, Czech Republic",,https://strajk.me/resume/,"

I work mostly with React & ecosystem, Vue, Node, TypeScript & Flow, GraphQL, and Cypress.
In the past, I had worked extensively with Angular.js, Meteor, Ruby on Rails, PHP, and various databases.

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I have experience with full-stack development, leading teams, project management, and organizing workshops.

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I'm passionate about organizing information, health & fitness, design, and education.

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I live in Brno, Czechia and I like it here, but I don't mind relocating for awesome opportunities.

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I enjoy running, cycling, lifting, photo & video, traveling, reading, playing video games (Doom & AoE are my favorites), and spending too much time on Reddit & HackerNews ¯\_(ツ)_/¯

+",2013-11-05 08:45:32.303 +594,131001,Glen_b,I'm right here,,,"

I was elected Moderator 31 March 2015 and stepped down early October 2019.

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While I am now quite sure nothing will come of it (hence the change in avatar after several +years), I still support the unconditional reinstatement of Monica.
+https://rentry.co/44bxc (also see here)

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Remember that all models are wrong; the practical question is how wrong do they have to be to not be useful 
--   George Box & Norman R. Draper, Empirical Model-Building and Response Surfaces

+Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made precise.
  --   John Tukey, The future of data analysis. Ann. Math. Stat. 33 (1), (1962)

+It is no more appropriate to tailor a course to the desires of the student than it is to modify the driving test according to the wishes of learner drivers.
  --   Stephen Senn, On thinking and learning. RSS News, December 2007

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https://mobile.twitter.com/stephensenn/status/538017638111531009

+



+

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Hard to find data queries: bountiful

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incl Ansbody, excl tags title & Qbody - http://data.stackexchange.com/stats/query/669089

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toask - av mean/median qu

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-0.359364, 0.1085635

+",2010-08-07 08:40:07.287 +23156,3509713,Marquis Randell,,,,,2013-10-30 00:36:07.867 +22870,1477007,Diego Jimeno,,,https://github.com/diegojimeno,"

An analyst in process, statistics, machine learning and BigData and a bit of game theory :-)

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Just started using GitHub https://github.com/diegojimeno

+",2013-10-20 10:21:46.343 +5479,82247,Dimitar Vouldjeff,"Sofia, Bulgaria",,http://vouldjeff.freewildart.com,,2011-11-24 21:16:43.767 +23471,3549374,007,,,,,2013-11-07 11:35:59.940 +22585,3421416,Jeff Shane,,,,,2013-10-10 21:34:01.167 +22834,3065897,mauna,,,,,2013-10-18 13:33:29.413 +23492,3551870,bison2178,,,,,2013-11-07 20:46:18.193 +23329,19930,Ankur Sethi,"Bangalore, Karnataka, India",,http://ankursethi.in,"

Freelance JavaScript engineer from Bangalore.

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Email: contact@ankursethi.in

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Website: https://ankursethi.in

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Twitter: https://twitter.com/ankurs3thi

+",2013-11-04 08:29:52.920 +22673,879549,Heather Turner,United Kingdom,,http://www.heatherturner.net,"

I am a full-time freelance consultant providing support in statistics and R programming. I am also an Associate Fellow of the Statistics Department at the University of Warwick.

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I spend most of my time working in R, but also use markup languages lots quite a bit.

+",2013-10-14 10:30:29.340 +23522,3555173,Sofea,,,,,2013-11-08 13:47:01.210 +23485,1617686,asdf,,,,,2013-11-07 17:57:25.767 +21884,2831124,Kian,"London, United Kingdom",,,"

Interested in stats, computing and quant finance

+",2013-09-19 21:52:07.043 +23133,3417716,r_alb,,,,,2013-10-29 14:14:57.847 +23044,1489032,Lamia,,,,"

Research Specialist

+",2013-10-25 16:57:06.070 +22599,1179283,Jeff Iacono,San Francisco,,,"

Product @trycaviar / @square. pretendgineer. data analyst. vermonster.

+",2013-10-11 05:52:34.533 +6813,1245417,user9171,,,,,2012-02-13 14:24:15.577 +22917,3148547,Dustin Stevens,,,,,2013-10-21 22:54:47.960 +23457,3547250,charles,,,,,2013-11-07 01:05:08.400 +23214,3518887,cmiller01,,,,,2013-10-31 13:52:08.423 +568,57318,Etienne Racine,"Montreal, QC, Canada",,,,2010-08-05 17:28:05.270 +13526,1831307,Stefano Lombardi,,,,,2013-01-02 10:38:44.693 +371,45700,Richie Cotton,"Union City, NJ, USA",,,"

I'm a Data Evangelist at DataCamp. I wrote a Learning R and Testing R Code.

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My github and Bitbucket repos, LinkedIn and twitter accounts.

+",2010-07-27 15:21:03.487 +23317,1131390,Kapoios,Greece,,,"

!

+",2013-11-03 22:17:28.047 +22717,1170427,khikho,,,,,2013-10-15 15:53:38.830 +23531,1986060,sonicboom,"Oslo, Norway",,,"

Computer Science PhD graduate student in UiO, Oslo with a strong interest in math.

+",2013-11-08 19:08:05.300 +23200,3517073,user32123,,,,,2013-10-31 06:02:07.147 +23296,3528248,Karnage2015,,,,,2013-11-02 21:21:48.783 +20622,3149735,Taal,,,,,2013-08-08 06:54:26.143 +15806,2495808,Jimj,,,,,2013-03-15 02:06:10.923 +22644,2372872,Roberto Ferrer,,,,,2013-10-13 02:05:50.643 +23262,3524678,Adrien.M,,,,,2013-11-01 19:11:44.703 +23527,917727,Ken Russell,,,,,2013-11-08 16:22:34.470 +5637,1084076,vinux,India,,http://about.me/vinuct,"

Statistician,

+",2011-12-04 16:11:53.740 +22820,1534566,FraNut,,,http://www.irea.cnr.it/index.php?option=com_comprofiler&task=userprofile&user=144&Itemid=100,,2013-10-18 08:42:55.297 +21362,3212276,zhifff,,,,,2013-09-03 13:46:27.047 +23347,1346433,Reed Sandberg,,,http://reed-sandberg.blogspot.com/,"

Machine whisperer

+",2013-11-04 20:57:47.220 +11490,1920491,Matteo Fasiolo,"Bristol, United Kingdom",,,"

Postdoc in Statistics at the University of Bristol. Previously working on statistical inference for dynamical processes. Lately I am working on generalized additive models.

+",2012-10-09 21:22:33.060 +23334,41225,lol,Aruba,,http://lol.com,what can i say; lol!,2013-11-04 12:19:20.483 +10409,7049886,Bradford,,,,,2012-08-21 14:43:10.063 +23071,2464957,Alexey Krikunov,,,,,2013-10-27 11:17:25.160 +18514,2842712,gregory_britten,"Woods Hole, MA, USA",,http://pemlab.whoi.edu,"

I am a PI at the Woods Hole Oceanographic Institution.

+",2013-05-31 21:20:04.397 +21476,3271296,Giancarlo,,,,,2013-09-06 13:51:40.493 +23430,3380629,satyarth sharma,,,,,2013-11-06 13:18:11.033 +23045,3491239,Kevin,,,,,2013-10-25 16:59:53.883 +18841,2115671,C.Colden,,,,,2013-06-11 16:11:21.680 +5911,973400,shn,,,,,2011-12-20 17:47:35.700 +23128,976979,daemonk,,,,,2013-10-29 10:56:01.507 +16144,1722110,Vincent,"32° 20'N, 64° 45'W",,,"

I am a unix fanatic who uses OSX and Ubuntu at home and at the office.

+",2013-03-24 01:04:33.750 211,93886,Tal Galili,Israel,,http://www.r-statistics.com,"Statistics, blogging, and the hope for a happy long life.",2010-07-21 07:53:50.990 -106918,3814367,Lucas Roberts,"New York, NY, United States",,https://scholar.google.com/citations?user=_kr2jm8AAAAJ,"

I've worked in Banking, Insurance, Retail-Tech, and Ad-Tech space. -I'm interested in a variety of domains and how the theory of those domains can be brought to bear to solve actual problems for humans.

-",2017-02-20 14:14:01.727 -254711,20287047,Jan,,,,,2020-12-23 17:50:41.683 -62703,2836818,LListhewaytobe,"Portland, OR",,,,2015-10-30 17:02:52.270 -232582,17439986,PaulG,,,,,2020-04-25 17:12:52.860 -35107,4784444,Russ Lenth,"Iowa City, IA, USA",,,,2014-07-22 15:40:09.550 -255103,2289489,impl,,,,"

I make companies.

-",2020-12-29 00:47:40.780 -255268,14615547,molocule,,,,,2020-12-30 17:45:51.613 -100031,8889184,steveo'america,wet coats,,,"

Just another guy working for a big company.

-",2016-12-20 23:44:58.070 +22786,3449771,Bella Fadida,,,,,2013-10-17 08:46:33.937 +22903,429289,Skippy le Grand Gourou,"Clermont-Ferrand, France",,https://lachrysomele.fr,"

The world is full of ignorant people, smug people and arrogant people. SE is no exception — why would it be ?

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Like art ? Check La Chrysomèle, Art Gallery.

+",2013-10-21 12:58:09.987 +20604,3023629,phg,,,,,2013-08-07 14:56:49.377 +22705,1421348,Learnerbeaver,Mars,,,"

Python explorer for text mining, modelling etc..

+",2013-10-15 07:43:36.180 +449,125690,John,"Halifax, Canada",,,"

I teach honours statistics in a psychology department primarily using R and simulation.

+",2010-07-29 14:29:12.917 +21168,1557825,NG_21,"Bangalore, India",,http://www.bosch.com/worldsite_startpage/en/default.aspx,"

A statistician by qualification, Machine Learning practitioner, aspiring Data Scientist

+",2013-08-27 18:30:54.943 +13370,2172823,Jessica,,,,,2012-12-23 00:21:39.787 +23507,3553094,user32491,,,,,2013-11-08 03:28:34.330 +12787,2099187,generic_user,,,,,2012-11-30 19:02:58.453 +18848,2885929,GK89,,,,"

Data Scientist working in the oil industry

+",2013-06-11 18:55:25.513 +23112,3503839,Pradyumna,,,,,2013-10-28 22:02:30.007 +20130,535336,Anton Tarasenko,,,https://antontarasenko.com,,2013-07-22 05:46:44.290 diff --git a/examples/csv_examples/votes.csv b/examples/csv_examples/votes.csv index bbb1f8c8..4d72f4cc 100644 --- a/examples/csv_examples/votes.csv +++ b/examples/csv_examples/votes.csv @@ -1,201 +1,2001 @@ id,user_id,post_id,vote_type_id,creation_date -33742,,8478,2,2011-04-07 -33707,,8478,2,2011-04-07 -33805,,8478,2,2011-04-07 -33717,,8478,2,2011-04-07 -33716,,8478,2,2011-04-07 -33718,,8478,2,2011-04-07 -33713,,8478,2,2011-04-07 -33995,,8504,2,2011-04-08 -33950,,8504,2,2011-04-08 -33916,,8504,2,2011-04-08 -33902,,8504,2,2011-04-08 -33884,,8478,2,2011-04-08 -34006,,8504,1,2011-04-08 -33895,,8504,2,2011-04-08 -34057,,8504,2,2011-04-09 -34056,,8478,2,2011-04-09 -34153,,8504,2,2011-04-10 +177,,143,2,2010-07-19 +246,,28,2,2010-07-19 +362,,28,2,2010-07-19 +138,,28,2,2010-07-19 +258,,28,2,2010-07-19 +202,,28,2,2010-07-19 +284,,28,2,2010-07-19 +254,,28,2,2010-07-19 +397,,143,3,2010-07-20 +566,,143,2,2010-07-20 +673,,143,2,2010-07-20 +1103,,143,2,2010-07-21 +852,,414,2,2010-07-21 +857,,414,2,2010-07-21 +868,,414,2,2010-07-21 +871,,414,2,2010-07-21 +1057,,28,2,2010-07-21 +1055,,414,2,2010-07-21 +886,,414,2,2010-07-21 +899,,414,2,2010-07-21 +988,,356,2,2010-07-21 +1087,,356,2,2010-07-21 +1054,,414,3,2010-07-21 +892,,28,2,2010-07-21 +1234,,414,2,2010-07-22 +1191,,414,2,2010-07-22 +1113,,28,2,2010-07-22 +1131,,356,2,2010-07-22 +1127,,28,2,2010-07-22 +1126,,412,2,2010-07-22 +1431,,543,2,2010-07-23 +1428,,543,2,2010-07-23 +1324,,414,3,2010-07-23 +1426,,541,2,2010-07-23 +1310,,541,2,2010-07-23 +1425,,414,2,2010-07-23 +1362,,356,2,2010-07-23 +1408,,414,2,2010-07-23 +1337,,414,2,2010-07-23 +1356,,412,2,2010-07-23 +1530,,412,2,2010-07-24 +1538,,541,2,2010-07-24 +1527,,541,2,2010-07-24 +1526,,543,2,2010-07-24 +1498,,543,2,2010-07-24 +1534,,543,2,2010-07-24 +1580,,541,2,2010-07-25 +1572,,28,2,2010-07-25 +1581,,543,2,2010-07-25 +1611,,28,2,2010-07-25 +1547,,28,2,2010-07-25 +1699,,28,2,2010-07-26 +1809,,414,2,2010-07-26 +1779,,412,2,2010-07-26 +2041,,414,2,2010-07-27 +2406,,543,2,2010-07-28 +2549,,356,2,2010-07-29 +2611,,412,2,2010-07-29 +2689,,412,2,2010-07-30 +2638,,356,2,2010-07-30 +2918,,143,2,2010-08-02 +2906,,28,2,2010-08-02 +2905,,543,2,2010-08-02 +3079,,143,2,2010-08-03 +3288,,541,2,2010-08-05 +3402,,1248,2,2010-08-06 +3486,,1248,2,2010-08-06 +3467,,1248,2,2010-08-06 +3441,,28,2,2010-08-06 +4943,,28,2,2010-08-19 +4971,,1760,2,2010-08-19 +4923,,1760,2,2010-08-19 +5013,,1760,2,2010-08-19 +4976,,1760,2,2010-08-19 +5188,,1760,2,2010-08-21 +5816,,543,2,2010-08-27 +5778,,541,2,2010-08-27 +5971,,414,2,2010-08-30 +5944,,414,2,2010-08-30 +6061,,414,2,2010-08-31 +6099,,414,2,2010-08-31 +6368,,2156,2,2010-09-02 +6342,,2156,2,2010-09-02 +6536,,2169,2,2010-09-03 +6916,,414,2,2010-09-07 +7206,,541,2,2010-09-09 +7205,,543,2,2010-09-09 +7327,,412,2,2010-09-10 +7933,,2509,2,2010-09-15 +7927,,2509,2,2010-09-15 +7926,,2509,2,2010-09-15 +7928,,2509,2,2010-09-15 +7854,,2509,2,2010-09-15 +7851,,2509,2,2010-09-15 +8015,,2509,2,2010-09-16 +8050,,2509,2,2010-09-16 +7981,,2509,2,2010-09-16 +7982,,2509,2,2010-09-16 +8040,,2509,2,2010-09-16 +7975,,2509,2,2010-09-16 +8042,,2509,2,2010-09-16 +8019,,2509,2,2010-09-16 +8047,,2509,2,2010-09-16 +8049,,2509,2,2010-09-16 +8067,,2509,2,2010-09-16 +8264,,2509,2,2010-09-17 +8565,,2509,2,2010-09-20 +8935,,1787,2,2010-09-23 +8966,,1760,2,2010-09-23 +8962,,1787,2,2010-09-23 +8889,,1760,2,2010-09-23 +8957,,1760,2,2010-09-23 +8951,,1787,2,2010-09-23 +9038,,1787,2,2010-09-24 +9057,,1787,2,2010-09-24 +9058,,1760,2,2010-09-24 +9188,,414,2,2010-09-25 +9290,,1760,2,2010-09-26 +9549,,2169,2,2010-09-29 +9668,,2509,2,2010-09-30 +10028,,414,2,2010-10-02 +10268,,2156,2,2010-10-04 +10251,,2156,2,2010-10-04 +10238,,2169,2,2010-10-04 +10210,,28,2,2010-10-04 +10187,,28,2,2010-10-04 +10158,,2169,2,2010-10-04 +10411,,2156,2,2010-10-06 +10692,,143,2,2010-10-08 +10682,,356,2,2010-10-08 +10741,,3188,2,2010-10-09 +10845,,3188,2,2010-10-10 +10834,,412,2,2010-10-10 +11177,,3188,2,2010-10-12 +11455,,541,2,2010-10-13 +11456,,543,2,2010-10-13 +11340,,541,2,2010-10-13 +11426,,543,2,2010-10-13 +11424,,541,2,2010-10-13 +11338,,414,2,2010-10-13 +11683,,541,2,2010-10-14 +11526,,1248,2,2010-10-14 +11626,,1248,2,2010-10-14 +11941,,3188,2,2010-10-17 +12202,,414,2,2010-10-19 +13006,,2509,2,2010-10-22 +13128,,3646,2,2010-10-24 +13127,,3646,2,2010-10-24 +13159,,3649,2,2010-10-24 +13187,,3649,2,2010-10-24 +13354,,3649,2,2010-10-25 +13284,,3646,2,2010-10-25 +13355,,3646,2,2010-10-25 +13774,,28,2,2010-10-28 +13909,,543,2,2010-10-29 +13908,,541,2,2010-10-29 +13969,,3649,2,2010-10-30 +14040,,2509,2,2010-10-30 +14065,,541,2,2010-10-30 +14143,,3649,1,2010-10-31 +14418,,3649,2,2010-11-02 +14417,,3646,2,2010-11-02 +14611,,414,2,2010-11-04 +14850,,414,2,2010-11-05 +15272,,3188,2,2010-11-08 +15271,,143,2,2010-11-08 +15576,,28,2,2010-11-10 +16249,,4187,2,2010-11-15 +16250,,4187,2,2010-11-15 +16247,,4187,2,2010-11-15 +16243,,4187,2,2010-11-15 +16383,,4187,2,2010-11-16 +16426,,4187,2,2010-11-16 +16343,,4187,2,2010-11-16 +16391,,4187,2,2010-11-16 +16397,,4187,2,2010-11-16 +16325,,4187,2,2010-11-16 +16273,,4187,2,2010-11-16 +16351,,4187,2,2010-11-16 +16381,,4187,2,2010-11-16 +16476,,4187,2,2010-11-17 +16483,,4187,2,2010-11-17 +16513,,4187,2,2010-11-17 +16575,,4187,2,2010-11-18 +16699,,4187,2,2010-11-19 +16852,,28,2,2010-11-19 +17097,,2509,2,2010-11-23 +17509,,4187,2,2010-11-26 +17589,,414,2,2010-11-27 +17872,,4187,2,2010-11-30 +18015,,543,2,2010-12-01 +18014,,541,2,2010-12-01 +18108,,4187,2,2010-12-02 +18416,,2509,2,2010-12-04 +18309,,4705,2,2010-12-04 +18327,,4705,2,2010-12-04 +18402,,4714,2,2010-12-04 +18311,,4705,2,2010-12-04 +18379,,4714,2,2010-12-04 +18405,,4714,2,2010-12-04 +18334,,4705,2,2010-12-04 +18424,,4705,2,2010-12-04 +18273,,4705,2,2010-12-04 +18378,,4714,2,2010-12-04 +18313,,4714,2,2010-12-04 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+218681,,57396,2,2013-10-13 +218680,,57395,2,2013-10-13 +218677,,57350,2,2013-10-13 +218672,,57384,3,2013-10-13 +218671,,57400,2,2013-10-13 +218782,,57389,2,2013-10-13 +218667,,57351,2,2013-10-13 +218666,,57391,2,2013-10-13 +218663,,57195,2,2013-10-13 +218790,,57373,2,2013-10-13 +218662,,57396,2,2013-10-13 +218661,,57401,2,2013-10-13 +218659,,49906,2,2013-10-13 +218800,,56911,2,2013-10-13 +218658,,57398,2,2013-10-13 +218657,,57398,2,2013-10-13 +218656,,57185,2,2013-10-13 +218655,,57388,2,2013-10-13 +218654,,57351,2,2013-10-13 +218842,,57452,2,2013-10-14 +218839,,57441,2,2013-10-14 +218838,,57351,2,2013-10-14 +218834,,57446,2,2013-10-14 +218831,,57350,2,2013-10-14 +218830,,57443,2,2013-10-14 +218829,,57271,9,2013-10-14 +218828,,57454,1,2013-10-14 +218827,,57448,2,2013-10-14 +218823,,57433,2,2013-10-14 +218840,,57442,2,2013-10-14 +218819,,57452,2,2013-10-14 +218817,,57451,2,2013-10-14 From 6cb72640f67330fb54695b618c664a5f649abbc0 Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Mon, 15 Dec 2025 01:05:30 +0700 Subject: [PATCH 27/42] :sparkles: feat: train_script can execute on COLAB and add GPU docker base --- Dockerfile.gpu | 55 +++++++++++ create_stack_subset.sh | 44 ++++----- docker-compose.gpu.yml | 95 +++++++++++++++++++ examples/rel-stack-engage.txt | 2 +- .../agent/task_builder_prompt_templates.yaml | 14 +++ plexe/tools/database_builder.py | 39 +++++++- plexe/tools/gnn_training_script_generator.py | 48 +++++++++- plexe/tools/task_builder.py | 10 +- 8 files changed, 275 insertions(+), 32 deletions(-) create mode 100644 Dockerfile.gpu create mode 100644 docker-compose.gpu.yml diff --git a/Dockerfile.gpu b/Dockerfile.gpu new file mode 100644 index 00000000..5210d3e7 --- /dev/null +++ b/Dockerfile.gpu @@ -0,0 +1,55 @@ +# GPU-enabled Dockerfile for Training +# Uses CUDA-enabled PyTorch wheels +# Use this for training with: docker compose -f docker-compose.gpu.yml up --build + +FROM python:3.11-slim as base + +WORKDIR /app + +ENV PIP_DEFAULT_TIMEOUT=100 \ + PIP_RETRIES=5 \ + PYTHONUNBUFFERED=1 \ + POETRY_NO_INTERACTION=1 \ + POETRY_VIRTUALENVS_CREATE=false + +# Install system dependencies +# build-essential is often needed for compiling some python packages +RUN apt-get update && apt-get install -y --no-install-recommends \ + git \ + curl \ + build-essential \ + && rm -rf /var/lib/apt/lists/* + +FROM base as deps + +RUN pip install --no-cache-dir --upgrade pip setuptools wheel && \ + pip install --no-cache-dir poetry + +COPY pyproject.toml poetry.lock* README.md ./ + +# Install main dependencies via Poetry +# We exclude the chatui extras initially to keep it focused on ML/Training, +# but can add them if needed. +RUN poetry config virtualenvs.create false && \ + poetry install --no-interaction --no-ansi --no-root --only main --extras chatui + +# Force install torch CUDA version (2.3.0 for CUDA 12.1) +# We uninstall the poetry-installed torch first just in case +RUN pip uninstall -y torch && \ + pip install torch==2.3.0 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121 + +# Install PyG dependencies with CUDA support +RUN pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.3.0+cu121.html + +FROM deps as app + +COPY . . + +# Install the project itself +RUN poetry config virtualenvs.create false && \ + poetry install --no-interaction --no-ansi --only main --extras chatui + +# Verify GPU availability +RUN python -c "import torch; print(f'Torch version: {torch.__version__}'); print(f'CUDA available: {torch.cuda.is_available()}')" + +CMD ["uvicorn", "plexe.main:app", "--host", "0.0.0.0", "--port", "8000"] diff --git a/create_stack_subset.sh b/create_stack_subset.sh index b3db93de..000bb3e8 100755 --- a/create_stack_subset.sh +++ b/create_stack_subset.sh @@ -1,7 +1,7 @@ #!/bin/bash # ===================================================== -# Tạo subset database stack-200 (~200 records mỗi bảng) +# Tạo subset database stack-2000 (~2000 records mỗi bảng) # Giữ nguyên relationships và lấy dữ liệu liên tục 30 ngày # ĐẢM BẢO REFERENTIAL INTEGRITY # ===================================================== @@ -10,15 +10,15 @@ set -e CONTAINER_NAME="plexe-clone-postgres-1" SOURCE_DB="stack" -TARGET_DB="stack-200" +TARGET_DB="stack-2000" DB_USER="mlflow" -# Tham số - mỗi bảng ~200 records -RECORDS_PER_TABLE=200 # Số records mục tiêu cho mỗi bảng -TIME_WINDOW_DAYS=30 # Lấy dữ liệu trong 30 ngày liên tục +# Tham số - mỗi bảng ~2000 records +RECORDS_PER_TABLE=2000 # Số records mục tiêu cho mỗi bảng +TIME_WINDOW_DAYS=60 # Lấy dữ liệu trong 30 ngày liên tục echo "=========================================" -echo "Create Stack-200 Subset Database" +echo "Create Stack-2000 Subset Database" echo "=========================================" echo "Source DB: $SOURCE_DB" echo "Target DB: $TARGET_DB" @@ -59,7 +59,7 @@ SELECT to_char(start_day + INTERVAL '30 days', 'YYYY-MM-DD') as end_date, window_count FROM window_counts -WHERE window_count >= 200 +WHERE window_count >= 2000 ORDER BY window_count ASC LIMIT 1; EOSQL @@ -108,14 +108,14 @@ echo " End: $END_DATE" echo " Posts in window: $ACTIVITY" echo "" -# Step 2: Extract subset với đảm bảo referential integrity, mỗi bảng ~200 records +# Step 2: Extract subset với đảm bảo referential integrity, mỗi bảng ~2000 records echo "📝 Step 2: Extracting subset data (~$RECORDS_PER_TABLE per table)..." cat > /tmp/extract_subset.sql << EOSQL -- ===================================================== --- STRATEGY: ~200 records per table with referential integrity +-- STRATEGY: ~2000 records per table with referential integrity -- ===================================================== --- Step 2.1: Get 200 posts in time window +-- Step 2.1: Get 2000 posts in time window CREATE TEMP TABLE base_posts AS SELECT id, owner_user_id, accepted_answer_id, parent_id FROM posts @@ -159,7 +159,7 @@ BEGIN END LOOP; END \$\$; --- Step 2.3: Get 200 users (prioritize those with posts, then add more) +-- Step 2.3: Get 2000 users (prioritize those with posts, then add more) CREATE TEMP TABLE all_user_ids AS SELECT DISTINCT owner_user_id as id FROM posts @@ -167,7 +167,7 @@ WHERE id IN (SELECT id FROM all_post_ids) AND owner_user_id IS NOT NULL LIMIT $RECORDS_PER_TABLE; --- If we have fewer than 200 users from posts, add more from the time window +-- If we have fewer than 2000 users from posts, add more from the time window INSERT INTO all_user_ids SELECT DISTINCT u.id FROM users u @@ -182,25 +182,25 @@ SELECT 'posts' as type, COUNT(*) as count FROM all_post_ids UNION ALL SELECT 'users', COUNT(*) FROM all_user_ids; --- Step 2.4: Export users (limit 200) +-- Step 2.4: Export users (limit 2000) \copy (SELECT * FROM users WHERE id IN (SELECT id FROM all_user_ids) LIMIT $RECORDS_PER_TABLE) TO '/tmp/subset_users.csv' CSV HEADER; --- Step 2.5: Export posts (already limited to ~200) - nullify missing FKs +-- Step 2.5: Export posts (already limited to ~2000) - nullify missing FKs \copy (SELECT id, CASE WHEN owner_user_id IN (SELECT id FROM all_user_ids) THEN owner_user_id ELSE NULL END as owner_user_id, post_type_id, CASE WHEN accepted_answer_id IN (SELECT id FROM all_post_ids) THEN accepted_answer_id ELSE NULL END as accepted_answer_id, CASE WHEN parent_id IN (SELECT id FROM all_post_ids) THEN parent_id ELSE NULL END as parent_id, owner_display_name, title, tags, content_license, body, creation_date FROM posts WHERE id IN (SELECT id FROM all_post_ids)) TO '/tmp/subset_posts.csv' CSV HEADER; --- Step 2.6: Export votes (limit 200) - only valid FKs +-- Step 2.6: Export votes (limit 2000) - only valid FKs \copy (SELECT id, CASE WHEN user_id IN (SELECT id FROM all_user_ids) THEN user_id ELSE NULL END as user_id, post_id, vote_type_id, creation_date FROM votes WHERE post_id IN (SELECT id FROM all_post_ids) ORDER BY creation_date LIMIT $RECORDS_PER_TABLE) TO '/tmp/subset_votes.csv' CSV HEADER; --- Step 2.7: Export comments (limit 200) - only valid FKs +-- Step 2.7: Export comments (limit 2000) - only valid FKs \copy (SELECT id, post_id, CASE WHEN user_id IN (SELECT id FROM all_user_ids) THEN user_id ELSE NULL END as user_id, content_license, user_display_name, text, creation_date FROM comments WHERE post_id IN (SELECT id FROM all_post_ids) ORDER BY creation_date LIMIT $RECORDS_PER_TABLE) TO '/tmp/subset_comments.csv' CSV HEADER; --- Step 2.8: Export badges (limit 200) - only for users in subset +-- Step 2.8: Export badges (limit 2000) - only for users in subset \copy (SELECT * FROM badges WHERE user_id IN (SELECT id FROM all_user_ids) ORDER BY date LIMIT $RECORDS_PER_TABLE) TO '/tmp/subset_badges.csv' CSV HEADER; --- Step 2.9: Export post_links (limit 200) - only where BOTH posts exist +-- Step 2.9: Export post_links (limit 2000) - only where BOTH posts exist \copy (SELECT * FROM post_links WHERE post_id IN (SELECT id FROM all_post_ids) AND related_post_id IN (SELECT id FROM all_post_ids) ORDER BY creation_date LIMIT $RECORDS_PER_TABLE) TO '/tmp/subset_post_links.csv' CSV HEADER; --- Step 2.10: Export post_history (limit 200) - only valid FKs +-- Step 2.10: Export post_history (limit 2000) - only valid FKs \copy (SELECT id, post_id, CASE WHEN user_id IN (SELECT id FROM all_user_ids) THEN user_id ELSE NULL END as user_id, post_history_type_id, user_display_name, content_license, revision_guid, text, comment, creation_date FROM post_history WHERE post_id IN (SELECT id FROM all_post_ids) ORDER BY creation_date LIMIT $RECORDS_PER_TABLE) TO '/tmp/subset_post_history.csv' CSV HEADER; -- Show counts @@ -226,8 +226,8 @@ echo "" # Step 3: Create new database echo "📝 Step 3: Creating new database..." docker exec -i $CONTAINER_NAME psql -U $DB_USER -d postgres << EOSQL -DROP DATABASE IF EXISTS "stack-200"; -CREATE DATABASE "stack-200"; +DROP DATABASE IF EXISTS "stack-2000"; +CREATE DATABASE "stack-2000"; EOSQL echo "✓ Database created" @@ -458,7 +458,7 @@ echo "✅ DONE!" echo "=========================================" echo "" echo "Connect to subset database:" -echo " docker exec -it $CONTAINER_NAME psql -U $DB_USER -d stack-200" +echo " docker exec -it $CONTAINER_NAME psql -U $DB_USER -d stack-2000" echo "" echo "Verify data:" echo " SELECT COUNT(*) FROM users;" diff --git a/docker-compose.gpu.yml b/docker-compose.gpu.yml new file mode 100644 index 00000000..be0f0649 --- /dev/null +++ b/docker-compose.gpu.yml @@ -0,0 +1,95 @@ +# docker-compose.gpu.yml +# GPU-enabled compose file for training +# Use: docker compose -f docker-compose.gpu.yml up -d + +services: + postgres: + image: postgres:15 + environment: + POSTGRES_USER: ${POSTGRES_USER:-mlflow} + POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-mlflow} + POSTGRES_DB: ${POSTGRES_DB:-mlflow_db} + volumes: + - postgres_data:/var/lib/postgresql/data + ports: + - "5432:5432" + networks: + - plexe-net + + mlflow: + build: + context: . + dockerfile: Dockerfile.mlflow + depends_on: + - postgres + environment: + BACKEND_STORE_URI: ${MLFLOW_BACKEND_STORE_URI:-postgresql+psycopg2://mlflow:mlflow@postgres:5432/mlflow_db} + ARTIFACT_ROOT: /mlruns + MLFLOW_ALLOW_ORIGINS: ${MLFLOW_ALLOW_ORIGINS:-*} + MLFLOW_SERVER_ALLOWED_HOSTS: ${MLFLOW_SERVER_ALLOWED_HOSTS:-mlflow,localhost,127.0.0.1,localhost:5000,127.0.0.1:5000,mlflow:5000} + volumes: + - ./mlruns:/mlruns + ports: + - "5000:5000" + networks: + - plexe-net + + pgadmin: + image: dpage/pgadmin4:7 + environment: + PGADMIN_DEFAULT_EMAIL: ${PGADMIN_EMAIL:-admin@example.com} + PGADMIN_DEFAULT_PASSWORD: ${PGADMIN_PASSWORD:-admin} + ports: + - "8080:80" + networks: + - plexe-net + + frontend: + build: + context: ./plexe/ui/frontend + dockerfile: Dockerfile.dev + volumes: + - ./plexe/ui/frontend/src:/app/src + - ./plexe/ui/frontend/index.html:/app/index.html + - ./plexe/ui/frontend/vite.config.js:/app/vite.config.js + - /app/node_modules + ports: + - "3000:3000" + environment: + VITE_BACKEND_URL: ${VITE_BACKEND_URL:-http://localhost:8000} + networks: + - plexe-net + + backend: + build: + context: . + dockerfile: Dockerfile.gpu + depends_on: + postgres: + condition: service_started + environment: + MLFLOW_TRACKING_URI: ${MLFLOW_TRACKING_URI:-http://mlflow:5000} + MLFLOW_BACKEND_STORE_URI: ${MLFLOW_BACKEND_STORE_URI:-postgresql+psycopg2://mlflow:mlflow@postgres:5432/mlflow_db} + MLFLOW_HTTP_REQUEST_TIMEOUT: 300 + HF_TOKEN: ${HF_TOKEN} + HUGGINGFACE_API_KEY: ${HUGGINGFACE_API_KEY} + volumes: + - .:/app + ports: + - "8000:8000" + deploy: + resources: + reservations: + devices: + - driver: nvidia + count: 1 + capabilities: [gpu] + networks: + - plexe-net + +volumes: + postgres_data: + +networks: + plexe-net: + driver: bridge diff --git a/examples/rel-stack-engage.txt b/examples/rel-stack-engage.txt index 275e1742..64842bc3 100644 --- a/examples/rel-stack-engage.txt +++ b/examples/rel-stack-engage.txt @@ -1,4 +1,4 @@ -I am working with the data is loaded into the `stack-200` database (connection string: `postgresql+psycopg2://mlflow:mlflow@postgres:5432/stack-200`). +I am working with the data is loaded into the `stack-2000` database (connection string: `postgresql+psycopg2://mlflow:mlflow@postgres:5432/stack-2000`). I want to define a predictive task on this relational database. Task definition: Predict if the user will make any contribution, defined as a vote, comment, or post, to the site in the next 2 days. Entity filtering: We filter on active users defined as users that have made at least one comment/post/vote before the timestamp. diff --git a/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml b/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml index da7ceb22..19c45247 100644 --- a/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml +++ b/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml @@ -40,6 +40,20 @@ managed_agent: The SQL patterns provided are TEMPLATES - you must replace placeholders with actual values from the schema. + + ## CRITICAL: COLUMN NAMING CONVENTION + + **ALWAYS use snake_case for column names in your SQL queries.** + Even if the original database documentation or schema description uses PascalCase (e.g., UserId, CreationDate), + the actual CSV files and DuckDB tables in this environment use snake_case (e.g., user_id, creation_date). + + Examples: + - UserId -> user_id + - OwnerUserId -> owner_user_id + - CreationDate -> creation_date + - PostId -> post_id + + Check `get_database_schema_for_task` output carefully - it will show the correct snake_case names. ## TASK TYPES diff --git a/plexe/tools/database_builder.py b/plexe/tools/database_builder.py index 6bbd1e05..321a4f64 100644 --- a/plexe/tools/database_builder.py +++ b/plexe/tools/database_builder.py @@ -324,6 +324,14 @@ def register_database_code( try: object_registry = ObjectRegistry() + # Extract class name from code + import re + class_match = re.search(r"class\s+(\w+)\s*\(", code) + if class_match: + class_name = class_match.group(1) + else: + class_name = dataset_name # Fallback + # Store the code code_key = f"database_code_{dataset_name}" object_registry.register(str, code_key, code, overwrite=True) @@ -332,6 +340,7 @@ def register_database_code( metadata_key = f"database_metadata_{dataset_name}" metadata = { "dataset_name": dataset_name, + "class_name": class_name, "val_timestamp": val_timestamp, "test_timestamp": test_timestamp, "description": description, @@ -339,12 +348,13 @@ def register_database_code( } object_registry.register(dict, metadata_key, metadata, overwrite=True) - logger.info(f"✅ Registered database code for '{dataset_name}'") + logger.info(f"✅ Registered database code for '{dataset_name}' (Class: {class_name})") return { "success": True, "code_key": code_key, "metadata_key": metadata_key, + "class_name": class_name, "message": f"Successfully registered database code for '{dataset_name}'" } @@ -409,8 +419,16 @@ def export_database_code( f.write(code) # Register export info + # Try to get class name from metadata + metadata_key = f"database_metadata_{dataset_name}" + try: + metadata = object_registry.get(dict, metadata_key) + class_name = metadata.get("class_name", dataset_name) + except KeyError: + class_name = dataset_name + export_info = { - "class_name": dataset_name, # Best guess, usually matches + "class_name": class_name, "export_path": file_path, "module_name": "dataset" } @@ -543,6 +561,19 @@ def get_temporal_statistics(csv_path: Optional[str] = None, time_columns: List[s val_ts = all_ts_series.quantile(0.70) test_ts = all_ts_series.quantile(0.85) + # Check if test_ts is too close to max_timestamp + # If the gap is small, it might cause issues for tasks with large timedelta + time_range = overall_max - overall_min + test_gap = overall_max - test_ts + + warning = "" + if test_gap < (time_range * 0.05): # Less than 5% of range left + warning = ( + f"WARNING: test_timestamp is very close to max_timestamp (gap: {test_gap}). " + f"Tasks with timedelta > {test_gap} will fail. " + f"Consider choosing an earlier test_timestamp." + ) + return { "columns_analyzed": list(column_stats.keys()), "statistics": column_stats, @@ -554,10 +585,12 @@ def get_temporal_statistics(csv_path: Optional[str] = None, time_columns: List[s "suggested_splits": { "val_timestamp": str(val_ts.date()), "test_timestamp": str(test_ts.date()), + "max_timestamp": str(overall_max.date()), "explanation": ( f"val_timestamp at 70th percentile: ~70% of data before this date. " f"test_timestamp at 85th percentile: ~85% of data before this date. " - f"This ensures sufficient training data while having meaningful validation/test sets." + f"Max timestamp is {overall_max.date()}. " + f"{warning}" ) } } diff --git a/plexe/tools/gnn_training_script_generator.py b/plexe/tools/gnn_training_script_generator.py index 2e9c7d3a..2942d75e 100644 --- a/plexe/tools/gnn_training_script_generator.py +++ b/plexe/tools/gnn_training_script_generator.py @@ -224,7 +224,18 @@ def main(): # ------------------------------------------------------------------------- print("\\n[Step 1] Loading Dataset and Task...") - dataset = {dataset_class}() + # Try to find csv_dir in the same directory as the script + csv_dir = os.path.join(WORKING_DIR, "csv_files") + if not os.path.exists(csv_dir): + # Fallback to looking for csv files in the working dir itself + csv_dir = WORKING_DIR + + try: + dataset = {dataset_class}(csv_dir=csv_dir) + except TypeError: + # Fallback if dataset doesn't accept csv_dir (e.g. standard RelBench datasets) + dataset = {dataset_class}() + task = {task_class}(dataset) db = dataset.get_db() @@ -265,8 +276,13 @@ def main(): text_embedder_cfg=text_embedder_cfg, cache_dir=CACHE_DIR, ) - - print(f" Node types: {{data.node_types}}") + # Clean up text embedder to free GPU memory + del text_embedder_cfg + import gc + gc.collect() + if torch.cuda.is_available(): + torch.cuda.empty_cache() + print(f" Node types: {{data.node_types}}") print(f" Edge types: {{len(data.edge_types)}}") for node_type in data.node_types: print(f" - {{node_type}}: {{data[node_type].num_nodes}} nodes") @@ -464,7 +480,8 @@ def __init__(self, device: Optional[torch.device] = None): ) def __call__(self, sentences: List[str]) -> Tensor: - return torch.from_numpy(self.model.encode(sentences)) + # Encode and ensure float32 tensor + return torch.from_numpy(self.model.encode(sentences)).float() ''' GLOVE_TEXT_EMBEDDER_CONFIG = ''' @@ -714,13 +731,34 @@ def execute_training_script( import subprocess try: + # Resolve path if it doesn't exist + if not os.path.exists(script_path): + # Try looking in working_dir from registry + try: + object_registry = ObjectRegistry() + working_dir = object_registry.get(str, "working_dir") + potential_path = os.path.join(working_dir, os.path.basename(script_path)) + if os.path.exists(potential_path): + script_path = potential_path + except Exception: + pass + + if not os.path.exists(script_path): + return { + "status": "error", + "error": f"Script file not found at: {script_path}", + } + # Run the script + # Ensure cwd is valid + cwd = os.path.dirname(os.path.abspath(script_path)) + result = subprocess.run( ["python", script_path], capture_output=True, text=True, timeout=timeout, - cwd=os.path.dirname(script_path), + cwd=cwd, ) return { diff --git a/plexe/tools/task_builder.py b/plexe/tools/task_builder.py index b42a918a..af8d9fa4 100644 --- a/plexe/tools/task_builder.py +++ b/plexe/tools/task_builder.py @@ -868,8 +868,16 @@ def export_task_code( f.write(code) # Register export info + # Extract class name from code + import re + class_match = re.search(r"class\s+(\w+)\s*\(", code) + if class_match: + class_name = class_match.group(1) + else: + class_name = task_name # Fallback + export_info = { - "class_name": task_name, + "class_name": class_name, "export_path": file_path, "module_name": "task" } From 539e92030fa5470aadc4c8cdfddf519c273eeff9 Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Tue, 6 Jan 2026 23:51:07 +0700 Subject: [PATCH 28/42] :sparkles:feat: Docker file for GPU --- Dockerfile.gpu | 134 ++++++++++++++++++++++++++++++++----------------- 1 file changed, 87 insertions(+), 47 deletions(-) diff --git a/Dockerfile.gpu b/Dockerfile.gpu index 5210d3e7..58d0ac8b 100644 --- a/Dockerfile.gpu +++ b/Dockerfile.gpu @@ -1,55 +1,95 @@ -# GPU-enabled Dockerfile for Training -# Uses CUDA-enabled PyTorch wheels -# Use this for training with: docker compose -f docker-compose.gpu.yml up --build - -FROM python:3.11-slim as base - +FROM pytorch/pytorch:2.7.0-cuda12.8-cudnn9-runtime +ENV DEBIAN_FRONTEND=noninteractive WORKDIR /app - -ENV PIP_DEFAULT_TIMEOUT=100 \ - PIP_RETRIES=5 \ - PYTHONUNBUFFERED=1 \ - POETRY_NO_INTERACTION=1 \ - POETRY_VIRTUALENVS_CREATE=false - -# Install system dependencies -# build-essential is often needed for compiling some python packages + +# ---------------------------- +# System dependencies +# ---------------------------- RUN apt-get update && apt-get install -y --no-install-recommends \ + python3.11 \ + python3.11-dev \ + python3.11-venv \ + python3-pip \ git \ curl \ build-essential \ + ca-certificates \ && rm -rf /var/lib/apt/lists/* - -FROM base as deps - -RUN pip install --no-cache-dir --upgrade pip setuptools wheel && \ - pip install --no-cache-dir poetry - + +# ---------------------------- +# Install uv (fast Python package manager) +# ---------------------------- +RUN pip install --no-cache-dir uv + +# ---------------------------- +# Environment variables +# ---------------------------- +ENV PYTHONUNBUFFERED=1 \ + PIP_DEFAULT_TIMEOUT=100 \ + PIP_RETRIES=5 \ + UV_SYSTEM_PYTHON=1 \ + UV_NO_CACHE=1 + +# ---------------------------- +# BƯỚC 1: Copy dependency files +# ---------------------------- COPY pyproject.toml poetry.lock* README.md ./ - -# Install main dependencies via Poetry -# We exclude the chatui extras initially to keep it focused on ML/Training, -# but can add them if needed. -RUN poetry config virtualenvs.create false && \ - poetry install --no-interaction --no-ansi --no-root --only main --extras chatui - -# Force install torch CUDA version (2.3.0 for CUDA 12.1) -# We uninstall the poetry-installed torch first just in case -RUN pip uninstall -y torch && \ - pip install torch==2.3.0 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121 - -# Install PyG dependencies with CUDA support -RUN pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.3.0+cu121.html - -FROM deps as app - + +# ---------------------------- +# BƯỚC 2: Migrate from Poetry to native uv format +# ---------------------------- +RUN uvx migrate-to-uv + +# ---------------------------- +# BƯỚC 3: Install dependencies với uv (sử dụng uv.lock sau migration) +# ---------------------------- +RUN uv sync --no-dev --extra chatui || uv pip install \ + python-dotenv pandas imbalanced-learn pydantic scikit-learn seaborn \ + dataclasses-json bandit joblib mlxtend xgboost tenacity pyarrow \ + litellm statsmodels hypothesis "numpy<2.0.0" black jinja2 platformdirs \ + "ray>=2.9.0" rich smolagents deprecated python-multipart psycopg2-binary \ + featuretools sqlalchemy pytorch-frame pooch duckdb scipy \ + fastapi "uvicorn[standard]" websockets + +# ---------------------------- +# BƯỚC 4: Cài torchvision, torchaudio (torch đã có sẵn từ base image) +# ---------------------------- +RUN uv pip install torchvision torchaudio + +# ---------------------------- +# BƯỚC 5: PyTorch Geometric dependencies (dùng pip vì PyG wheel index) +# Theo hướng dẫn chính thức: https://pytorch-geometric.readthedocs.io +# ---------------------------- +RUN pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv \ + -f https://data.pyg.org/whl/torch-2.7.0+cu128.html + +# ---------------------------- +# BƯỚC 6: torch-geometric +# ---------------------------- +RUN uv pip install torch-geometric + +# ---------------------------- +# BƯỚC 7: MLflow +# ---------------------------- +RUN uv pip install "mlflow>=2.14.0,<3.0.0" + +# ---------------------------- +# Source code +# ---------------------------- COPY . . - -# Install the project itself -RUN poetry config virtualenvs.create false && \ - poetry install --no-interaction --no-ansi --only main --extras chatui - -# Verify GPU availability -RUN python -c "import torch; print(f'Torch version: {torch.__version__}'); print(f'CUDA available: {torch.cuda.is_available()}')" - -CMD ["uvicorn", "plexe.main:app", "--host", "0.0.0.0", "--port", "8000"] + +# ---------------------------- +# Sanity check +# ---------------------------- +RUN python - < Date: Wed, 7 Jan 2026 22:41:40 +0700 Subject: [PATCH 29/42] :mute:chore: add dependencies for docker backend --- Dockerfile.gpu | 25 ++++++------ create_stack_subset.sh | 0 docker-compose.gpu.yml | 6 ++- examples/rel-stack-engage.txt | 5 --- import_relbench_stack.sh | 2 +- .../chain_of_thought/websocket_emitter.py | 39 +++++++++++++++++-- plexe/internal/models/callbacks/mlflow.py | 4 +- plexe/server.py | 6 +++ plexe/ui/frontend/vite.config.js | 14 ++++++- 9 files changed, 75 insertions(+), 26 deletions(-) mode change 100755 => 100644 create_stack_subset.sh mode change 100755 => 100644 import_relbench_stack.sh diff --git a/Dockerfile.gpu b/Dockerfile.gpu index 58d0ac8b..f74b0b18 100644 --- a/Dockerfile.gpu +++ b/Dockerfile.gpu @@ -36,14 +36,9 @@ ENV PYTHONUNBUFFERED=1 \ COPY pyproject.toml poetry.lock* README.md ./ # ---------------------------- -# BƯỚC 2: Migrate from Poetry to native uv format +# BƯỚC 2: Install dependencies với uv (cài trực tiếp để đảm bảo đầy đủ) # ---------------------------- -RUN uvx migrate-to-uv - -# ---------------------------- -# BƯỚC 3: Install dependencies với uv (sử dụng uv.lock sau migration) -# ---------------------------- -RUN uv sync --no-dev --extra chatui || uv pip install \ +RUN uv pip install \ python-dotenv pandas imbalanced-learn pydantic scikit-learn seaborn \ dataclasses-json bandit joblib mlxtend xgboost tenacity pyarrow \ litellm statsmodels hypothesis "numpy<2.0.0" black jinja2 platformdirs \ @@ -52,24 +47,24 @@ RUN uv sync --no-dev --extra chatui || uv pip install \ fastapi "uvicorn[standard]" websockets # ---------------------------- -# BƯỚC 4: Cài torchvision, torchaudio (torch đã có sẵn từ base image) +# BƯỚC 3: Cài torchvision, torchaudio (torch đã có sẵn từ base image) # ---------------------------- RUN uv pip install torchvision torchaudio # ---------------------------- -# BƯỚC 5: PyTorch Geometric dependencies (dùng pip vì PyG wheel index) +# BƯỚC 4: PyTorch Geometric dependencies (dùng pip vì PyG wheel index) # Theo hướng dẫn chính thức: https://pytorch-geometric.readthedocs.io # ---------------------------- RUN pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv \ -f https://data.pyg.org/whl/torch-2.7.0+cu128.html # ---------------------------- -# BƯỚC 6: torch-geometric +# BƯỚC 5: torch-geometric # ---------------------------- RUN uv pip install torch-geometric # ---------------------------- -# BƯỚC 7: MLflow +# BƯỚC 6: MLflow # ---------------------------- RUN uv pip install "mlflow>=2.14.0,<3.0.0" @@ -79,17 +74,21 @@ RUN uv pip install "mlflow>=2.14.0,<3.0.0" COPY . . # ---------------------------- -# Sanity check +# Sanity check (build-time - GPU not available during build) # ---------------------------- RUN python - < bool: + """Check if the WebSocket emitter has been closed.""" + with self._lock: + return self._closed def set_loop(self, loop): """Set the event loop to use for sending messages.""" @@ -53,8 +69,13 @@ def request_confirmation(self, title: str, content: str, content_type: str = "te content_type: Type of content (text, code, json, markdown) Returns: - bool: True if confirmed, False otherwise + bool: True if confirmed, False if denied or connection closed """ + # If already closed, return False immediately + if self.is_closed: + logger.debug("WebSocketEmitter: Cannot request confirmation - connection closed") + return False + request_id = str(uuid.uuid4()) event = threading.Event() @@ -119,6 +140,11 @@ def emit_thought(self, agent_name: str, message: str) -> None: def _emit_payload(self, payload: dict): """Internal helper to send payload via WebSocket.""" + # Check if the emitter has been closed + if self.is_closed: + logger.debug("WebSocketEmitter: Skipping send - connection closed") + return + try: # Try to send the message # First, check if we're in the same thread as the event loop @@ -150,7 +176,9 @@ def _handle_send_result(self, future): try: future.result() # This will raise if there was an error except Exception as e: - logger.error(f"Failed to send WebSocket message: {e}") + # Mark as closed on send failure to prevent further attempts + self.close() + logger.debug(f"WebSocket send failed, connection marked as closed: {e}") async def _send_message(self, payload: dict) -> None: """ @@ -159,8 +187,13 @@ async def _send_message(self, payload: dict) -> None: Args: payload: The message payload to send """ + if self.is_closed: + return + try: await self.websocket.send_json(payload) except Exception as e: - logger.error(f"Failed to send WebSocket message: {e}") + # Mark as closed on send failure to prevent further attempts + self.close() + logger.debug(f"WebSocket send failed, connection marked as closed: {e}") diff --git a/plexe/internal/models/callbacks/mlflow.py b/plexe/internal/models/callbacks/mlflow.py index b4eebce1..829ae9d5 100644 --- a/plexe/internal/models/callbacks/mlflow.py +++ b/plexe/internal/models/callbacks/mlflow.py @@ -69,9 +69,11 @@ def _setup_mlflow(self) -> None: mlflow.set_experiment(experiment_id=self.experiment_id) # Enable autologging for smolagents AFTER setting experiment + # Note: mlflow.smolagents may not be available in all mlflow versions try: mlflow.smolagents.autolog() - except ModuleNotFoundError: + except (ModuleNotFoundError, AttributeError): + # smolagents integration not available in this mlflow version pass except Exception as e: diff --git a/plexe/server.py b/plexe/server.py index eb2b0d4f..9c17237c 100644 --- a/plexe/server.py +++ b/plexe/server.py @@ -211,10 +211,14 @@ async def run_agent_task(user_message: str): except WebSocketDisconnect: logger.info(f"WebSocket disconnected: {session_id}") + # Mark emitter as closed to stop sending messages + ws_emitter.close() if agent_task: agent_task.cancel() except Exception as e: logger.error(f"WebSocket error for session {session_id}: {e}") + # Mark emitter as closed to stop sending messages + ws_emitter.close() if agent_task: agent_task.cancel() try: @@ -222,6 +226,8 @@ async def run_agent_task(user_message: str): except Exception: pass # Connection might be already closed finally: + # Ensure emitter is closed + ws_emitter.close() # Remove log handler for logger_name in loggers_to_capture: logging.getLogger(logger_name).removeHandler(log_handler) diff --git a/plexe/ui/frontend/vite.config.js b/plexe/ui/frontend/vite.config.js index 1eba421a..201896f9 100644 --- a/plexe/ui/frontend/vite.config.js +++ b/plexe/ui/frontend/vite.config.js @@ -1,6 +1,11 @@ import { defineConfig } from 'vite' import react from '@vitejs/plugin-react' +// Use environment variable for backend URL, defaulting to Docker service name +// When running in Docker, use 'backend:8000'. When running locally, use 'localhost:8000' +const backendHost = process.env.VITE_BACKEND_HOST || 'backend' +const backendUrl = `http://${backendHost}:8000` + export default defineConfig({ plugins: [react()], server: { @@ -15,13 +20,18 @@ export default defineConfig({ proxy: { // Proxy /ws to backend during development '/ws': { - target: 'http://localhost:8000', + target: backendUrl, ws: true, changeOrigin: true, }, // Proxy /api requests to backend '/api': { - target: 'http://localhost:8000', + target: backendUrl, + changeOrigin: true, + }, + // Proxy /health to backend + '/health': { + target: backendUrl, changeOrigin: true, }, }, From 454dbe3e8f81ec1a3b766ecd472ee1b90a24f55b Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Thu, 8 Jan 2026 09:13:29 +0700 Subject: [PATCH 30/42] :mute:chore: adding sentence transformer into dependencies --- Dockerfile.dev | 3 + Dockerfile.gpu | 11 +- plexe/tools/gnn_training_script_generator.py | 122 ++++++++++++++++--- plexe/tools/interaction.py | 16 +++ pyproject.toml | 4 +- 5 files changed, 136 insertions(+), 20 deletions(-) diff --git a/Dockerfile.dev b/Dockerfile.dev index be439288..0f008921 100644 --- a/Dockerfile.dev +++ b/Dockerfile.dev @@ -54,6 +54,9 @@ RUN poetry config virtualenvs.create false && \ RUN pip install torch==2.3.1 --index-url https://download.pytorch.org/whl/cpu && \ pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.3.1+cpu.html +# Install sentence-transformers for text embeddings in GNN training +RUN pip install sentence-transformers + EXPOSE 8000 HEALTHCHECK --interval=10s --timeout=5s --retries=3 --start-period=30s \ diff --git a/Dockerfile.gpu b/Dockerfile.gpu index f74b0b18..3c4fb750 100644 --- a/Dockerfile.gpu +++ b/Dockerfile.gpu @@ -62,9 +62,14 @@ RUN pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_co # BƯỚC 5: torch-geometric # ---------------------------- RUN uv pip install torch-geometric - + +# ---------------------------- +# BƯỚC 6: sentence-transformers (for text embeddings in GNN training) +# ---------------------------- +RUN uv pip install sentence-transformers + # ---------------------------- -# BƯỚC 6: MLflow +# BƯỚC 7: MLflow # ---------------------------- RUN uv pip install "mlflow>=2.14.0,<3.0.0" @@ -83,6 +88,8 @@ print("✓ Torch:", torch.__version__) print(" Note: CUDA will be available at runtime, not during build") import torch_geometric print("✓ PyG OK") +import sentence_transformers +print("✓ sentence-transformers:", sentence_transformers.__version__) import mlflow print("✓ MLflow:", mlflow.__version__) import deprecated diff --git a/plexe/tools/gnn_training_script_generator.py b/plexe/tools/gnn_training_script_generator.py index 2942d75e..95f9c32f 100644 --- a/plexe/tools/gnn_training_script_generator.py +++ b/plexe/tools/gnn_training_script_generator.py @@ -466,22 +466,47 @@ def evaluate(loader: NeighborLoader) -> np.ndarray: GLOVE_TEXT_EMBEDDER = ''' from typing import List, Optional -from sentence_transformers import SentenceTransformer from torch import Tensor +# Try to import sentence_transformers, fall back to simple embedder if not available +_SENTENCE_TRANSFORMERS_AVAILABLE = False +try: + from sentence_transformers import SentenceTransformer + _SENTENCE_TRANSFORMERS_AVAILABLE = True +except ImportError: + print("WARNING: sentence_transformers not installed. Using fallback text embedder.") + print("For better text embeddings, install: pip install sentence-transformers") + class GloveTextEmbedding: - """GloVe-based text embedder using sentence-transformers.""" + """GloVe-based text embedder using sentence-transformers with fallback.""" def __init__(self, device: Optional[torch.device] = None): - self.model = SentenceTransformer( - "sentence-transformers/average_word_embeddings_glove.6B.300d", - device=device, - ) + self.device = device + if _SENTENCE_TRANSFORMERS_AVAILABLE: + self.model = SentenceTransformer( + "sentence-transformers/average_word_embeddings_glove.6B.300d", + device=device, + ) + self.embedding_dim = 300 + else: + self.model = None + self.embedding_dim = 64 # Fallback dimension + print("Using random embeddings as fallback (not recommended for production)") def __call__(self, sentences: List[str]) -> Tensor: - # Encode and ensure float32 tensor - return torch.from_numpy(self.model.encode(sentences)).float() + if self.model is not None: + # Use sentence-transformers + return torch.from_numpy(self.model.encode(sentences)).float() + else: + # Fallback: simple hash-based embeddings (deterministic but basic) + embeddings = [] + for sentence in sentences: + # Create a deterministic embedding based on string hash + torch.manual_seed(hash(sentence) % (2**32)) + emb = torch.randn(self.embedding_dim) + embeddings.append(emb) + return torch.stack(embeddings).float() ''' GLOVE_TEXT_EMBEDDER_CONFIG = ''' @@ -709,6 +734,61 @@ def generate_training_script( # Tool: Execute Training Script # ============================================================================= +def _normalize_script_path(script_path: str) -> str: + """ + Normalize the script path to handle various input formats. + + Handles cases like: + - Absolute paths: /app/.workdir/... + - Relative paths: ./.workdir/... or .workdir/... + - Just filename: train_script.py + - Paths with redundant components: /app/.workdir/..././.workdir/... + """ + # First, normalize the path to remove redundant separators and up-references + script_path = os.path.normpath(script_path) + + # If path exists as-is, return it + if os.path.exists(script_path): + return os.path.abspath(script_path) + + # Try getting working_dir from registry + try: + object_registry = ObjectRegistry() + working_dir = object_registry.get(str, "working_dir") + working_dir = os.path.abspath(working_dir) + + # Extract just the filename + filename = os.path.basename(script_path) + + # Try in working_dir + potential_path = os.path.join(working_dir, filename) + if os.path.exists(potential_path): + return potential_path + + # If script_path contains a session folder, try to extract it + # e.g., ".workdir/chat-session-xxx/train_script.py" -> use that session folder + path_parts = script_path.replace("\\", "/").split("/") + for i, part in enumerate(path_parts): + if part.startswith("chat-session-") or part.startswith("session-"): + # Reconstruct path from this point + session_path = os.path.join(working_dir, *path_parts[i:]) + if os.path.exists(session_path): + return session_path + # Also try just the session folder with filename + session_folder = os.path.join(working_dir, "..", part) + session_folder = os.path.normpath(session_folder) + if os.path.isdir(session_folder): + potential = os.path.join(session_folder, filename) + if os.path.exists(potential): + return potential + + except Exception: + pass + + # Return original (will fail but with proper error message) + return script_path + + @tool def execute_training_script( script_path: str, @@ -731,28 +811,34 @@ def execute_training_script( import subprocess try: - # Resolve path if it doesn't exist + # Normalize and resolve the script path + script_path = _normalize_script_path(script_path) + if not os.path.exists(script_path): - # Try looking in working_dir from registry + # Provide helpful error message with debugging info try: object_registry = ObjectRegistry() working_dir = object_registry.get(str, "working_dir") - potential_path = os.path.join(working_dir, os.path.basename(script_path)) - if os.path.exists(potential_path): - script_path = potential_path except Exception: - pass + working_dir = "unknown" - if not os.path.exists(script_path): - return { + return { "status": "error", "error": f"Script file not found at: {script_path}", + "debug_info": { + "working_dir": working_dir, + "cwd": os.getcwd(), + "original_path": script_path, + } } # Run the script - # Ensure cwd is valid + # Ensure cwd is valid - use the directory containing the script cwd = os.path.dirname(os.path.abspath(script_path)) + logger.info(f"Executing training script: {script_path}") + logger.info(f"Working directory: {cwd}") + result = subprocess.run( ["python", script_path], capture_output=True, @@ -766,6 +852,8 @@ def execute_training_script( "output": result.stdout, "error_output": result.stderr, "return_code": result.returncode, + "script_path": script_path, + "cwd": cwd, } except subprocess.TimeoutExpired: diff --git a/plexe/tools/interaction.py b/plexe/tools/interaction.py index 93d8f3a2..490ef186 100644 --- a/plexe/tools/interaction.py +++ b/plexe/tools/interaction.py @@ -17,6 +17,18 @@ def _get_working_dir() -> str: return "./workdir/" +def _clean_agent_response_prefix(content: str) -> str: + """ + Remove smolagents managed agent response prefix from content. + This prefix is added by the framework when returning results from managed agents. + """ + import re + # Pattern to match "Here is the final answer from your managed agent 'AgentName':" + pattern = r"^Here is the final answer from your managed agent '[^']+':[\s]*" + cleaned = re.sub(pattern, "", content, flags=re.MULTILINE) + return cleaned.strip() + + @tool def save_to_workdir(filename: str, content: str, subfolder: str = "") -> str: """ @@ -41,6 +53,10 @@ def save_to_workdir(filename: str, content: str, subfolder: str = "") -> str: os.makedirs(save_dir, exist_ok=True) + # Clean agent response prefix for Python files to prevent syntax errors + if filename.endswith('.py'): + content = _clean_agent_response_prefix(content) + file_path = os.path.join(save_dir, filename) with open(file_path, "w") as f: f.write(content) diff --git a/pyproject.toml b/pyproject.toml index 60213dd3..b7708c55 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -68,6 +68,7 @@ transformers = { version = "^4.50.0", optional = true } tokenizers = { version = "^0.21.1", optional = true } accelerate = { version = "0.24.1", optional = true } safetensors = { version = "^0.4.1", optional = true } +sentence-transformers = { version = "^3.0.0", optional = true } # Local web serving dependencies for chat UI fastapi = { version = "^0.115.12", optional = true } @@ -75,13 +76,14 @@ uvicorn = {extras = ["standard"], version = "^0.34.2", optional = true } websockets = { version = "^12.0", optional = true } [tool.poetry.extras] -transformers = ["transformers", "tokenizers", "accelerate", "safetensors"] +transformers = ["transformers", "tokenizers", "accelerate", "safetensors", "sentence-transformers"] chatui = ["fastapi", "uvicorn", "websockets"] all = [ "transformers", "tokenizers", "accelerate", "safetensors", + "sentence-transformers", "fastapi", "uvicorn", "websockets" From b8676e447b2a75971aa368db38447279c5979ff5 Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Thu, 8 Jan 2026 12:05:10 +0700 Subject: [PATCH 31/42] :bug:bug: task builder can not create task.py --- plexe/agents/task_builder.py | 8 +- ...ional_gnn_specialist_prompt_templates.yaml | 41 ++++-- .../agent/task_builder_prompt_templates.yaml | 29 +++- plexe/tools/gnn_training_script_generator.py | 136 ++++++++++++++++-- plexe/tools/task_builder.py | 89 ++++++++++++ 5 files changed, 271 insertions(+), 32 deletions(-) diff --git a/plexe/agents/task_builder.py b/plexe/agents/task_builder.py index 771d014a..f92595e5 100644 --- a/plexe/agents/task_builder.py +++ b/plexe/agents/task_builder.py @@ -28,6 +28,7 @@ test_sql_query, analyze_potential_tasks, validate_task_code, + save_task_to_file, register_task_code, export_task_code, get_entity_task_template, @@ -96,10 +97,11 @@ def __init__( get_entity_task_template, get_recommendation_task_template, get_sql_query_examples, - # Validation and registration + # Validation and export (PREFERRED: use save_task_to_file) validate_task_code, - register_task_code, - export_task_code, + save_task_to_file, # Simpler: directly writes code to file + register_task_code, # Legacy: 2-step process + export_task_code, # Legacy: requires register first ], prompt_templates=get_prompt_templates( base_template_name="code_agent.yaml", diff --git a/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml b/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml index 1a0ce0cd..4542f332 100644 --- a/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml +++ b/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml @@ -6,11 +6,36 @@ managed_agent: for training on relational data. You work with the Dataset and Task classes generated by the **DatasetBuilder** and **TaskBuilder** agents. + ## CRITICAL PREREQUISITE CHECK + + **BEFORE doing anything else, you MUST verify that both required files exist:** + + | File | Created By | Purpose | + |------|------------|---------| + | `dataset.py` | DatasetBuilder agent | Defines the Dataset class that loads relational data | + | `task.py` | TaskBuilder agent | Defines the Task class with prediction labels | + + **Both files are REQUIRED. If either is missing, you CANNOT proceed with training.** + + Call `validate_training_prerequisites()` first to check these files exist. + ## Your Workflow - ### Step 1: Retrieve Dataset and Task Information - First, use `get_dataset_task_info_from_registry` to find the Dataset and Task classes that were - created by previous agents: + ### Step 1: VALIDATE Prerequisites (MANDATORY FIRST STEP) + **Always start by validating that required files exist:** + + ```python + validation = validate_training_prerequisites() + # If status is "invalid", STOP and report which files are missing + ``` + + If validation fails: + - Report which files are missing (dataset.py and/or task.py) + - Explain that the respective agent (DatasetBuilder/TaskBuilder) must run first + - DO NOT attempt to generate training code + + ### Step 2: Retrieve Dataset and Task Information + Only after validation passes, use `get_dataset_task_info_from_registry` to get class names: ```python info = get_dataset_task_info_from_registry() @@ -22,16 +47,6 @@ managed_agent: # } ``` - ### Step 2: Validate Prerequisites - Use `validate_training_prerequisites` to ensure all dependencies are installed: - - ```python - validation = validate_training_prerequisites( - dataset_module_path=".workdir/chat-session-123/dataset.py", - task_module_path=".workdir/chat-session-123/task.py" - ) - ``` - ### Step 3: Generate Training Script Use `generate_training_script` to create a complete training script: diff --git a/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml b/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml index 19c45247..1e81e8c2 100644 --- a/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml +++ b/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml @@ -20,8 +20,9 @@ managed_agent: - `get_sql_query_examples`: Get diverse SQL query PATTERNS (templates, not hardcoded) - `test_sql_query`: TEST your SQL query on sample data before committing - `validate_task_code`: Validate your generated code - - `register_task_code`: Store the generated code in registry - - `export_task_code`: Export the code to workdir/chat-session-*/tasks/ + - `save_task_to_file`: **PREFERRED** - Directly save task code to file (simple, reliable) + - `register_task_code`: Store the generated code in registry (legacy) + - `export_task_code`: Export from registry to file (legacy, requires register first) ## WORKFLOW FOR NEW TASKS @@ -31,7 +32,22 @@ managed_agent: 4. **Design SQL**: Combine SQL building blocks (see below) 5. **Test SQL**: Use `test_sql_query` to validate on sample data 6. **Generate code**: Create complete Task class - 7. **Validate & Export**: Use `validate_task_code` and `export_task_code` + 7. **SAVE TO FILE**: Use `save_task_to_file(code)` to directly write the file + + ## CRITICAL: HOW TO EXPORT CODE + + **PREFERRED METHOD (use this!):** + ```python + save_task_to_file(code=task_class_code_string) + ``` + This directly writes the code to a file. Simple and reliable! + + **Legacy method (avoid if possible):** + ```python + register_task_code(dataset_name, task_name, code, task_type, entity_table) + export_task_code(dataset_name, task_name) + ``` + This 2-step process is more error-prone. ## CRITICAL: NO HARDCODING @@ -475,8 +491,11 @@ managed_agent: 3. `get_sql_query_examples()` → find appropriate pattern template 4. Write Task class using ACTUAL names from schema 5. `validate_task_code(code)` → check for errors - 6. `register_task_code(dataset_name, task_name, code, ...)` → save to registry - 7. `export_task_code(dataset_name, task_name)` → write to file + 6. `save_task_to_file(code)` → **PREFERRED**: directly write to file + + Alternative (legacy, avoid): + - `register_task_code(dataset_name, task_name, code, ...)` → save to registry + - `export_task_code(dataset_name, task_name)` → write from registry to file ## COMMON MISTAKES TO AVOID diff --git a/plexe/tools/gnn_training_script_generator.py b/plexe/tools/gnn_training_script_generator.py index 95f9c32f..c00f834d 100644 --- a/plexe/tools/gnn_training_script_generator.py +++ b/plexe/tools/gnn_training_script_generator.py @@ -949,34 +949,125 @@ def get_dataset_task_info_from_registry() -> Dict[str, Any]: @tool def validate_training_prerequisites( - dataset_module_path: str, - task_module_path: str, + dataset_module_path: str = None, + task_module_path: str = None, ) -> Dict[str, Any]: """ Validates that all prerequisites for training are in place. + CRITICAL: This tool MUST be called before generating training code. + Both dataset.py and task.py files are REQUIRED for GNN training. + Checks: - 1. Dataset module exists and is importable - 2. Task module exists and is importable + 1. Dataset module exists (dataset.py) - generated by DatasetBuilder + 2. Task module exists (task.py) - generated by TaskBuilder 3. Required dependencies are installed Args: - dataset_module_path: Path to the dataset module - task_module_path: Path to the task module + dataset_module_path: Path to the dataset module. If None, will auto-detect + from ObjectRegistry or working directory. + task_module_path: Path to the task module. If None, will auto-detect + from ObjectRegistry or working directory. Returns: - Dictionary with validation results + Dictionary with validation results including: + - status: "valid" or "invalid" + - issues: List of critical issues that must be resolved + - warnings: List of non-critical warnings + - dataset_path: Resolved path to dataset module + - task_path: Resolved path to task module """ issues = [] warnings = [] + object_registry = ObjectRegistry() + + # Auto-detect paths from registry if not provided + if dataset_module_path is None: + try: + dataset_info = object_registry.get(dict, "database_code") + dataset_module_path = dataset_info.get("export_path") + except KeyError: + pass + + if task_module_path is None: + try: + task_info = object_registry.get(dict, "task_code") + task_module_path = task_info.get("export_path") + except KeyError: + pass + + # Try to infer from working directory if still not found + working_dir = None + try: + working_dir = object_registry.get(str, "working_dir") + except KeyError: + try: + working_dir = object_registry.get(str, "current_chat_session_dir") + except KeyError: + pass + + if working_dir: + if dataset_module_path is None: + potential_dataset = os.path.join(working_dir, "dataset.py") + if os.path.exists(potential_dataset): + dataset_module_path = potential_dataset + + if task_module_path is None: + potential_task = os.path.join(working_dir, "task.py") + if os.path.exists(potential_task): + task_module_path = potential_task + + # ========================================================================= + # CRITICAL CHECK: Both dataset.py and task.py MUST exist + # ========================================================================= # Check dataset module - if not os.path.exists(dataset_module_path): - issues.append(f"Dataset module not found: {dataset_module_path}") + if dataset_module_path is None: + issues.append( + "CRITICAL: dataset.py not found! " + "DatasetBuilder agent must create dataset.py before GNN training can begin. " + "Please run DatasetBuilder first to generate the Dataset class." + ) + elif not os.path.exists(dataset_module_path): + issues.append( + f"CRITICAL: Dataset module not found at '{dataset_module_path}'! " + "The DatasetBuilder agent must create this file before training." + ) + else: + # Verify it's a valid Python file with a Dataset class + try: + with open(dataset_module_path, 'r') as f: + content = f.read() + if 'class ' not in content or 'Dataset' not in content: + warnings.append( + f"Dataset file exists but may not contain a valid Dataset class: {dataset_module_path}" + ) + except Exception as e: + warnings.append(f"Could not read dataset file for validation: {e}") # Check task module - if not os.path.exists(task_module_path): - issues.append(f"Task module not found: {task_module_path}") + if task_module_path is None: + issues.append( + "CRITICAL: task.py not found! " + "TaskBuilder agent must create task.py before GNN training can begin. " + "Please run TaskBuilder first to generate the Task class." + ) + elif not os.path.exists(task_module_path): + issues.append( + f"CRITICAL: Task module not found at '{task_module_path}'! " + "The TaskBuilder agent must create this file before training." + ) + else: + # Verify it's a valid Python file with a Task class + try: + with open(task_module_path, 'r') as f: + content = f.read() + if 'class ' not in content or 'Task' not in content: + warnings.append( + f"Task file exists but may not contain a valid Task class: {task_module_path}" + ) + except Exception as e: + warnings.append(f"Could not read task file for validation: {e}") # Check required packages required_packages = [ @@ -1005,10 +1096,33 @@ def validate_training_prerequisites( except ImportError: pass + # Summary of required files + files_summary = { + "dataset.py": { + "path": dataset_module_path, + "exists": dataset_module_path is not None and os.path.exists(dataset_module_path), + "required": True, + "created_by": "DatasetBuilder agent" + }, + "task.py": { + "path": task_module_path, + "exists": task_module_path is not None and os.path.exists(task_module_path), + "required": True, + "created_by": "TaskBuilder agent" + } + } + return { "status": "valid" if len(issues) == 0 else "invalid", "issues": issues, "warnings": warnings, "dataset_path": dataset_module_path, "task_path": task_module_path, + "working_dir": working_dir, + "required_files": files_summary, + "message": ( + "All prerequisites validated successfully. Ready for GNN training." + if len(issues) == 0 else + f"CANNOT PROCEED: {len(issues)} critical issue(s) must be resolved before training." + ) } diff --git a/plexe/tools/task_builder.py b/plexe/tools/task_builder.py index af8d9fa4..117e7019 100644 --- a/plexe/tools/task_builder.py +++ b/plexe/tools/task_builder.py @@ -751,6 +751,95 @@ def validate_task_code(code: str) -> Dict[str, Any]: } +@tool +def save_task_to_file(code: str, file_name: str = "task.py") -> Dict[str, Any]: + """ + PREFERRED METHOD: Directly save Task class code to a Python file. + + This is the simplest way to export task code - just provide the code and it + will be saved to the current working directory (workdir/chat-session-*/tasks/). + + Use this tool INSTEAD of the register_task_code + export_task_code workflow + for simpler, more reliable task export. + + Args: + code: The complete Python code for the Task class (must include imports, + class definition, and make_table method) + file_name: Name of the output file (default: "task.py") + + Returns: + Dictionary with: + - success: Boolean indicating if file was saved + - file_path: Absolute path to the saved file + - class_name: Name of the Task class extracted from code + - error: Error message if failed + """ + from datetime import datetime + import re + + try: + object_registry = ObjectRegistry() + + # Validate code first + validation = validate_task_code.__wrapped__(code) + if not validation["valid"]: + return { + "success": False, + "error": f"Code validation failed: {validation['errors']}", + "warnings": validation.get("warnings", []) + } + + # Get or create working directory + try: + output_dir = object_registry.get(str, "working_dir") + except KeyError: + try: + output_dir = object_registry.get(str, "current_chat_session_dir") + except KeyError: + # Create new session directory + timestamp = datetime.now().strftime("%Y%m%d-%H%M%S") + output_dir = f"workdir/chat-session-{timestamp}" + object_registry.register(str, "current_chat_session_dir", output_dir, overwrite=True) + + # Create output directory + Path(output_dir).mkdir(parents=True, exist_ok=True) + + # Ensure file_name ends with .py + if not file_name.endswith(".py"): + file_name = f"{file_name}.py" + + # Write the file + file_path = os.path.join(output_dir, file_name) + + with open(file_path, 'w') as f: + f.write(code) + + # Extract class name from code + class_match = re.search(r"class\s+(\w+)\s*\(", code) + class_name = class_match.group(1) if class_match else "UnknownTask" + + # Register task info for later use by other agents + export_info = { + "class_name": class_name, + "export_path": os.path.abspath(file_path), + "module_name": file_name.replace(".py", "") + } + object_registry.register(dict, "task_code", export_info, overwrite=True) + + logger.info(f"✅ Saved task code to '{file_path}' (class: {class_name})") + + return { + "success": True, + "file_path": os.path.abspath(file_path), + "class_name": class_name, + "message": f"Successfully saved {class_name} to '{file_path}'" + } + + except Exception as e: + logger.error(f"Failed to save task code: {e}") + return {"success": False, "error": str(e)} + + @tool def register_task_code( dataset_name: str, From 3d261477a770dcadaa15f78017dc603d36cd1ba3 Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Wed, 14 Jan 2026 21:35:04 +0700 Subject: [PATCH 32/42] :bug:bug: can not execute code --- examples/rel-stack-engage.txt | 5 + plexe/agents/relational_gnn_specialist.py | 4 - plexe/relbench/__init__.py | 27 +++- plexe/relbench/modeling/__init__.py | 14 +++ plexe/relbench/modeling/graph.py | 4 +- plexe/relbench/modeling/utils.py | 2 +- plexe/relbench/tasks/__init__.py | 4 +- .../dataset_builder_prompt_templates.yaml | 12 +- ...ional_gnn_specialist_prompt_templates.yaml | 62 +++++++--- .../agent/task_builder_prompt_templates.yaml | 14 ++- plexe/tools/database_builder.py | 13 +- plexe/tools/gnn_training_script_generator.py | 114 ++++++++++++++--- plexe/tools/task_builder.py | 115 +++++++++++++++--- 13 files changed, 314 insertions(+), 76 deletions(-) diff --git a/examples/rel-stack-engage.txt b/examples/rel-stack-engage.txt index 5fe83b22..64842bc3 100644 --- a/examples/rel-stack-engage.txt +++ b/examples/rel-stack-engage.txt @@ -2,6 +2,11 @@ I am working with the data is loaded into the `stack-2000` database (connection I want to define a predictive task on this relational database. Task definition: Predict if the user will make any contribution, defined as a vote, comment, or post, to the site in the next 2 days. Entity filtering: We filter on active users defined as users that have made at least one comment/post/vote before the timestamp. +Task significance: By accurately forecasting the levels of user contribution, website administrators can effectively gauge +and oversee user activity. This insight allows for well-informed choices across various business aspects. For instance, +it aids in preempting and mitigating user attrition, as well as in enhancing strategies to foster increased user interaction +and involvement. This predictive task serves as a crucial tool in optimizing user experience and sustaining a dynamic and +engaged user base. Machine learning task: Binary classification. The label is 1 when a user contributes to the site and 0 otherwise. Evaluation metric: Average Precision (AP). I don't have any requirements, if you need them you can set by default automatically. \ No newline at end of file diff --git a/plexe/agents/relational_gnn_specialist.py b/plexe/agents/relational_gnn_specialist.py index c56bf050..66fbbfc7 100644 --- a/plexe/agents/relational_gnn_specialist.py +++ b/plexe/agents/relational_gnn_specialist.py @@ -22,7 +22,6 @@ get_dataset_task_info_from_registry, validate_training_prerequisites, ) -from plexe.tools.interaction import save_to_workdir logger = logging.getLogger(__name__) @@ -71,12 +70,9 @@ def __init__( get_training_script_template, # Validation validate_training_prerequisites, - # Script generation generate_training_script, # Execution execute_training_script, - # File saving - save_to_workdir, ], prompt_templates=get_prompt_templates( base_template_name="code_agent.yaml", diff --git a/plexe/relbench/__init__.py b/plexe/relbench/__init__.py index f28d5f3a..55980fdc 100644 --- a/plexe/relbench/__init__.py +++ b/plexe/relbench/__init__.py @@ -1,3 +1,28 @@ -from . import base, datasets, modeling +from . import base, datasets, modeling, tasks +from .base import ( + Database, + Dataset, + Table, + BaseTask, + TaskType, + EntityTask, + RecommendationTask, + AutoCompleteTask, +) __version__ = "1.1.0" + +__all__ = [ + "base", + "datasets", + "modeling", + "tasks", + "Database", + "Dataset", + "Table", + "BaseTask", + "TaskType", + "EntityTask", + "RecommendationTask", + "AutoCompleteTask", +] diff --git a/plexe/relbench/modeling/__init__.py b/plexe/relbench/modeling/__init__.py index e69de29b..2da100d8 100644 --- a/plexe/relbench/modeling/__init__.py +++ b/plexe/relbench/modeling/__init__.py @@ -0,0 +1,14 @@ +from .graph import make_pkey_fkey_graph, get_node_train_table_input +from .utils import get_stype_proposal, remove_pkey_fkey, to_unix_time +from .nn import HeteroEncoder, HeteroGraphSAGE, HeteroTemporalEncoder + +__all__ = [ + "make_pkey_fkey_graph", + "get_node_train_table_input", + "get_stype_proposal", + "remove_pkey_fkey", + "to_unix_time", + "HeteroEncoder", + "HeteroGraphSAGE", + "HeteroTemporalEncoder", +] \ No newline at end of file diff --git a/plexe/relbench/modeling/graph.py b/plexe/relbench/modeling/graph.py index 41a51472..978a5f48 100644 --- a/plexe/relbench/modeling/graph.py +++ b/plexe/relbench/modeling/graph.py @@ -13,8 +13,8 @@ from torch_geometric.typing import NodeType from torch_geometric.utils import sort_edge_index -from relbench.base import Database, EntityTask, RecommendationTask, Table, TaskType -from relbench.modeling.utils import remove_pkey_fkey, to_unix_time +from ..base import Database, EntityTask, RecommendationTask, Table, TaskType +from .utils import remove_pkey_fkey, to_unix_time def make_pkey_fkey_graph( diff --git a/plexe/relbench/modeling/utils.py b/plexe/relbench/modeling/utils.py index 26fafc31..3b84913b 100644 --- a/plexe/relbench/modeling/utils.py +++ b/plexe/relbench/modeling/utils.py @@ -5,7 +5,7 @@ from torch_frame import stype from torch_frame.utils import infer_df_stype -from relbench.base import Database, Table +from ..base import Database, Table def to_unix_time(ser: pd.Series) -> np.ndarray: diff --git a/plexe/relbench/tasks/__init__.py b/plexe/relbench/tasks/__init__.py index c4ad4d09..756cc8ae 100644 --- a/plexe/relbench/tasks/__init__.py +++ b/plexe/relbench/tasks/__init__.py @@ -4,8 +4,8 @@ import pooch -from relbench.base import BaseTask -from relbench.datasets import get_dataset +from ..base import BaseTask +from ..datasets import get_dataset task_registry = defaultdict(dict) diff --git a/plexe/templates/prompts/agent/dataset_builder_prompt_templates.yaml b/plexe/templates/prompts/agent/dataset_builder_prompt_templates.yaml index b68bbc6e..aab17910 100644 --- a/plexe/templates/prompts/agent/dataset_builder_prompt_templates.yaml +++ b/plexe/templates/prompts/agent/dataset_builder_prompt_templates.yaml @@ -51,7 +51,8 @@ managed_agent: from plexe.relbench.base import Database, Dataset, Table - class {DatasetName}Dataset(Dataset): + # ALWAYS use this class name + class GenDataset(Dataset): # Temporal split timestamps val_timestamp = pd.Timestamp("YYYY-MM-DD") test_timestamp = pd.Timestamp("YYYY-MM-DD") @@ -62,11 +63,7 @@ managed_agent: def make_db(self) -> Database: path = self.csv_dir - - - # 1. LOAD CSV FILES - # Use actual table names from get_csv_files_from_path() - + # 1. LOAD CSV FILES # For each CSV file discovered, load it: # {table_name} = pd.read_csv(os.path.join(path, "{table_name}.csv")) @@ -177,8 +174,7 @@ managed_agent: ## IMPORTANT: Use Schema Metadata The table names, primary keys, foreign keys, and temporal columns should come from: - 1. `get_csv_files_from_path()` - Returns list of CSV files (table names) - 2. `get_schema_metadata_from_registry()` - Returns: + `get_schema_metadata_from_registry()` - Returns: - `tables`: Dict with table info including `primary_keys`, `temporal_columns` - `relationships`: List of FK relationships with `source_table`, `target_table`, `source_col` - `temporal_summary`: Tables with timestamps and their primary temporal columns diff --git a/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml b/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml index 4542f332..3bf56d8f 100644 --- a/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml +++ b/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml @@ -9,11 +9,8 @@ managed_agent: ## CRITICAL PREREQUISITE CHECK **BEFORE doing anything else, you MUST verify that both required files exist:** - - | File | Created By | Purpose | - |------|------------|---------| - | `dataset.py` | DatasetBuilder agent | Defines the Dataset class that loads relational data | - | `task.py` | TaskBuilder agent | Defines the Task class with prediction labels | + `dataset.py` created by DatasetBuilder agent to Defines the Dataset class that loads relational data + `task.py` created by TaskBuilder agent to Defines the Task class with prediction labels **Both files are REQUIRED. If either is missing, you CANNOT proceed with training.** @@ -46,16 +43,23 @@ managed_agent: # "working_dir": ".workdir/chat-session-123/" # } ``` + + **CRITICAL CHECKS:** + - Verify that BOTH `dataset_info` and `task_info` are NOT None + - If either is None, STOP and report that the respective agent needs to run first + - Extract the exact `class_name` values to use in generate_training_script ### Step 3: Generate Training Script - Use `generate_training_script` to create a complete training script: + **CRITICAL: Use the `generate_training_script` TOOL - DO NOT write Python code yourself!** + + This tool automatically generates a complete, syntactically correct training script. ```python result = generate_training_script( dataset_module_path=".workdir/chat-session-123/dataset.py", - dataset_class_name="MyCustomDataset", + dataset_class_name="GenDataset", task_module_path=".workdir/chat-session-123/task.py", - task_class_name="UserLTVTask", + task_class_name="GenTask", working_dir=".workdir/chat-session-123/", task_type="regression", # or "binary_classification", "multiclass_classification" tune_metric="mae", # Metric to optimize @@ -68,8 +72,14 @@ managed_agent: num_gnn_layers=2, num_neighbors=[128, 128], # Neighbors per GNN layer ) - # Returns script_path where train_script.py was saved + # Returns: {"script_path": ".workdir/chat-session-123/train_script.py", ...} ``` + + **IMPORTANT NOTES:** + - The tool CREATES the train_script.py file automatically + - You should NOT manually write or save training code + - The generated file is ready to execute immediately + - If you see syntax errors, check that you called the tool correctly ### Step 4: Execute Training Script Use `execute_training_script` to run the training: @@ -83,17 +93,21 @@ managed_agent: ## Generated Script **Constraint:** Do not hardcode class names (e.g., `MyCustomDataset`). You must use the exact strings returned by the registry + + **WARNING: DO NOT manually write training code!** + The `generate_training_script` tool creates the entire file for you. + If you try to write code yourself, you will likely introduce syntax errors or formatting issues. The generated `train_script.py` follows this structure: ```python # 1. Import Dataset and Task classes - from my_dataset import MyCustomDataset - from my_task import UserLTVTask + from dataset import GenDataset + from task import GenTask # 2. Load data - dataset = MyCustomDataset() - task = UserLTVTask(dataset) + dataset = GenDataset() + task = GenTask(dataset) db = dataset.get_db() train_table = task.get_table("train") @@ -156,12 +170,24 @@ managed_agent: | Tool | Description | |------|-------------| - | `get_dataset_task_info_from_registry` | Retrieves Dataset/Task info from ObjectRegistry | - | `get_training_script_template` | Returns the training script template for reference | - | `validate_training_prerequisites` | Validates that all dependencies are installed | - | `generate_training_script` | Generates a complete training script | + | `get_dataset_task_info_from_registry` | Retrieves Dataset/Task info from ObjectRegistry or metadata files | + | `get_training_script_template` | Returns the training script template for reference only | + | `validate_training_prerequisites` | Validates that dataset.py and task.py exist | + | `generate_training_script` | **USE THIS** - Generates complete train_script.py file automatically | | `execute_training_script` | Executes the training script | - | `save_to_workdir` | Saves files to the working directory | + + **IMPORTANT: DO NOT manually save training code!** + - The `generate_training_script` tool automatically creates and saves `train_script.py` + - Do NOT use any file saving tools - they are not available and not needed + - Only call `execute_training_script` after `generate_training_script` succeeds + + **WORKFLOW REMINDER:** + 1. Call `validate_training_prerequisites()` first + 2. Call `get_dataset_task_info_from_registry()` to get class names + 3. Call `generate_training_script(...)` with the retrieved info - this creates the file! + 4. Call `execute_training_script(...)` to run it + + DO NOT manually write training code between steps 3 and 4! ## Key Components from plexe.relbench.modeling diff --git a/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml b/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml index 1e81e8c2..edaea7e5 100644 --- a/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml +++ b/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml @@ -20,7 +20,7 @@ managed_agent: - `get_sql_query_examples`: Get diverse SQL query PATTERNS (templates, not hardcoded) - `test_sql_query`: TEST your SQL query on sample data before committing - `validate_task_code`: Validate your generated code - - `save_task_to_file`: **PREFERRED** - Directly save task code to file (simple, reliable) + - `save_task_to_file`: **PREFERRED** - Saves code to file AND registers in ObjectRegistry AND creates metadata file - `register_task_code`: Store the generated code in registry (legacy) - `export_task_code`: Export from registry to file (legacy, requires register first) @@ -31,16 +31,20 @@ managed_agent: 3. **Sample data**: Use `get_table_sample_data` to understand column values 4. **Design SQL**: Combine SQL building blocks (see below) 5. **Test SQL**: Use `test_sql_query` to validate on sample data - 6. **Generate code**: Create complete Task class - 7. **SAVE TO FILE**: Use `save_task_to_file(code)` to directly write the file + 6. **Generate code**: Create complete Task class named `GenTask` + 7. **SAVE TO FILE**: Use `save_task_to_file(code)` - this saves file, metadata, AND registers in ObjectRegistry ## CRITICAL: HOW TO EXPORT CODE **PREFERRED METHOD (use this!):** ```python - save_task_to_file(code=task_class_code_string) + result = save_task_to_file(code=task_class_code_string) ``` - This directly writes the code to a file. Simple and reliable! + This tool does everything in one step: + - Writes the code to a .py file + - Creates task_metadata.json for persistence + - Registers in ObjectRegistry for immediate use by other agents + - Returns file paths and success status **Legacy method (avoid if possible):** ```python diff --git a/plexe/tools/database_builder.py b/plexe/tools/database_builder.py index 321a4f64..8bc8e2bf 100644 --- a/plexe/tools/database_builder.py +++ b/plexe/tools/database_builder.py @@ -432,9 +432,20 @@ def export_database_code( "export_path": file_path, "module_name": "dataset" } + + # Save metadata to JSON file for persistence across sessions + import json + metadata_file = os.path.join(output_dir, "dataset_metadata.json") + try: + with open(metadata_file, 'w') as mf: + json.dump(export_info, mf, indent=2) + logger.info(f"Saved dataset metadata to '{metadata_file}'") + except Exception as e: + logger.warning(f"Failed to save dataset metadata file: {e}") + object_registry.register(dict, "database_code", export_info, overwrite=True) - logger.info(f"✅ Exported database code to '{file_path}'") + logger.info(f"Exported database code to '{file_path}'") return { "success": True, diff --git a/plexe/tools/gnn_training_script_generator.py b/plexe/tools/gnn_training_script_generator.py index c00f834d..547cf579 100644 --- a/plexe/tools/gnn_training_script_generator.py +++ b/plexe/tools/gnn_training_script_generator.py @@ -31,6 +31,19 @@ import os import sys + +# Add project root to Python path to enable plexe imports +# First, check if we're in a Docker environment (/app) +if os.path.exists("/app/plexe"): + if "/app" not in sys.path: + sys.path.insert(0, "/app") +else: + # Local development: go up from .workdir/chat-session-xxx/ to project root + script_dir = os.path.dirname(os.path.abspath(__file__)) + project_root = os.path.dirname(os.path.dirname(script_dir)) # Go up two levels + if project_root not in sys.path and os.path.exists(os.path.join(project_root, "plexe")): + sys.path.insert(0, project_root) + import math import copy import numpy as np @@ -52,7 +65,7 @@ {dataset_import} {task_import} -# Import RelBench modeling utilities +# Import RelBench modeling utilities (from plexe's built-in relbench) from plexe.relbench.modeling.graph import make_pkey_fkey_graph, get_node_train_table_input from plexe.relbench.modeling.utils import get_stype_proposal from plexe.relbench.modeling.nn import HeteroEncoder, HeteroGraphSAGE, HeteroTemporalEncoder @@ -517,15 +530,6 @@ def __call__(self, sentences: List[str]) -> Tensor: ) ''' -NO_TEXT_EMBEDDER = ''' -# No text embedder needed (no text columns detected) -''' - -NO_TEXT_EMBEDDER_CONFIG = ''' - text_embedder_cfg = None # No text columns -''' - - # ============================================================================= # Loss Function Templates # ============================================================================= @@ -656,8 +660,8 @@ def generate_training_script( text_embedder_code = GLOVE_TEXT_EMBEDDER text_embedder_config = GLOVE_TEXT_EMBEDDER_CONFIG else: - text_embedder_code = NO_TEXT_EMBEDDER - text_embedder_config = NO_TEXT_EMBEDDER_CONFIG + text_embedder_code = GLOVE_TEXT_EMBEDDER + text_embedder_config = GLOVE_TEXT_EMBEDDER_CONFIG # Format num_neighbors for the script num_neighbors_str = str(num_neighbors) @@ -836,8 +840,32 @@ def execute_training_script( # Ensure cwd is valid - use the directory containing the script cwd = os.path.dirname(os.path.abspath(script_path)) + # Set up environment with PYTHONPATH to ensure plexe imports work + # This is critical because plexe.relbench is a local module, not installed via pip + env = os.environ.copy() + + # Find the project root (where plexe package is located) + # From /app/.workdir/chat-session-xxx/ we need to go to /app/ + project_root = os.path.abspath(os.path.join(cwd, "..", "..")) + + # Also check if we're in Docker (/app) or local development + if os.path.exists("/app/plexe"): + project_root = "/app" + elif os.path.exists(os.path.join(project_root, "plexe")): + pass # project_root is correct + else: + # Try current working directory + original_cwd = os.getcwd() + if os.path.exists(os.path.join(original_cwd, "plexe")): + project_root = original_cwd + + # Prepend project root to PYTHONPATH + existing_pythonpath = env.get("PYTHONPATH", "") + env["PYTHONPATH"] = f"{project_root}:{cwd}:{existing_pythonpath}" if existing_pythonpath else f"{project_root}:{cwd}" + logger.info(f"Executing training script: {script_path}") logger.info(f"Working directory: {cwd}") + logger.info(f"PYTHONPATH: {env['PYTHONPATH']}") result = subprocess.run( ["python", script_path], @@ -845,6 +873,7 @@ def execute_training_script( text=True, timeout=timeout, cwd=cwd, + env=env, ) return { @@ -854,6 +883,7 @@ def execute_training_script( "return_code": result.returncode, "script_path": script_path, "cwd": cwd, + "pythonpath": env["PYTHONPATH"], } except subprocess.TimeoutExpired: @@ -888,6 +918,8 @@ def get_dataset_task_info_from_registry() -> Dict[str, Any]: - 'task_info': Information about the registered Task - 'working_dir': The working directory being used """ + import json + try: object_registry = ObjectRegistry() @@ -907,10 +939,37 @@ def get_dataset_task_info_from_registry() -> Dict[str, Any]: } if dataset_code_info.get("export_path"): result["working_dir"] = os.path.dirname(dataset_code_info["export_path"]) + logger.info(f"✅ Found database_code in registry: {dataset_code_info.get('class_name')}") except KeyError: + logger.warning("⚠️ database_code not found in registry. Attempting to load from file...") + + # Fallback: Try to load from dataset_metadata.json file + try: + working_dir = object_registry.get(str, "working_dir") + metadata_file = os.path.join(working_dir, "dataset_metadata.json") + + if os.path.exists(metadata_file): + with open(metadata_file, 'r') as f: + dataset_code_info = json.load(f) + + result["dataset_info"] = { + "class_name": dataset_code_info.get("class_name"), + "file_path": dataset_code_info.get("export_path"), + "module_name": dataset_code_info.get("module_name"), + } + if dataset_code_info.get("export_path"): + result["working_dir"] = os.path.dirname(dataset_code_info["export_path"]) + logger.info(f"✅ Loaded database_code from metadata file: {dataset_code_info.get('class_name')}") + + # Re-register it for future use + object_registry.register(dict, "database_code", dataset_code_info, overwrite=True) + else: + logger.warning(f"⚠️ Dataset metadata file not found: {metadata_file}") + except Exception as e: + logger.warning(f"⚠️ Could not load dataset metadata from file: {e}") pass - # Try to get task code info + # Try to get task code info from registry try: task_code_info = object_registry.get(dict, "task_code") result["task_info"] = { @@ -921,8 +980,35 @@ def get_dataset_task_info_from_registry() -> Dict[str, Any]: "entity_table": task_code_info.get("entity_table"), "target_col": task_code_info.get("target_col"), } + logger.info(f"✅ Found task_code in registry: {task_code_info.get('class_name')}") except KeyError: - pass + logger.warning("⚠️ task_code not found in registry. Attempting to load from file...") + + # Fallback: Try to load from task_metadata.json file + try: + working_dir = object_registry.get(str, "working_dir") + metadata_file = os.path.join(working_dir, "task_metadata.json") + + if os.path.exists(metadata_file): + with open(metadata_file, 'r') as f: + task_code_info = json.load(f) + + result["task_info"] = { + "class_name": task_code_info.get("class_name"), + "file_path": task_code_info.get("export_path"), + "module_name": task_code_info.get("module_name"), + "task_type": task_code_info.get("task_type"), + "entity_table": task_code_info.get("entity_table"), + "target_col": task_code_info.get("target_col"), + } + logger.info(f"✅ Loaded task_code from metadata file: {task_code_info.get('class_name')}") + + # Re-register it for future use + object_registry.register(dict, "task_code", task_code_info, overwrite=True) + else: + logger.warning(f"⚠️ Metadata file not found: {metadata_file}") + except Exception as e: + logger.warning(f"⚠️ Could not load task metadata from file: {e}") # Try to get working directory if not found if result["working_dir"] is None: diff --git a/plexe/tools/task_builder.py b/plexe/tools/task_builder.py index 117e7019..06042932 100644 --- a/plexe/tools/task_builder.py +++ b/plexe/tools/task_builder.py @@ -757,11 +757,15 @@ def save_task_to_file(code: str, file_name: str = "task.py") -> Dict[str, Any]: PREFERRED METHOD: Directly save Task class code to a Python file. This is the simplest way to export task code - just provide the code and it - will be saved to the current working directory (workdir/chat-session-*/tasks/). + will be saved to the working directory (e.g., .workdir/chat-session-YYYYMMDD-HHMMSS/). Use this tool INSTEAD of the register_task_code + export_task_code workflow for simpler, more reliable task export. + This tool also: + - Saves task_metadata.json alongside the code file for persistence + - Registers the task code in ObjectRegistry for immediate use by other agents + Args: code: The complete Python code for the Task class (must include imports, class definition, and make_table method) @@ -772,10 +776,12 @@ class definition, and make_table method) - success: Boolean indicating if file was saved - file_path: Absolute path to the saved file - class_name: Name of the Task class extracted from code + - metadata_file: Path to the metadata JSON file - error: Error message if failed """ from datetime import datetime import re + import json try: object_registry = ObjectRegistry() @@ -792,52 +798,88 @@ class definition, and make_table method) # Get or create working directory try: output_dir = object_registry.get(str, "working_dir") + logger.info(f"Using registered working_dir: {output_dir}") except KeyError: try: output_dir = object_registry.get(str, "current_chat_session_dir") + logger.info(f"Using current_chat_session_dir: {output_dir}") except KeyError: # Create new session directory timestamp = datetime.now().strftime("%Y%m%d-%H%M%S") - output_dir = f"workdir/chat-session-{timestamp}" + output_dir = f".workdir/chat-session-{timestamp}" object_registry.register(str, "current_chat_session_dir", output_dir, overwrite=True) + logger.info(f"Created new session directory: {output_dir}") - # Create output directory + # Normalize and create output directory + output_dir = os.path.abspath(output_dir) Path(output_dir).mkdir(parents=True, exist_ok=True) # Ensure file_name ends with .py if not file_name.endswith(".py"): file_name = f"{file_name}.py" - # Write the file + # Write the code file file_path = os.path.join(output_dir, file_name) with open(file_path, 'w') as f: f.write(code) + logger.info(f"Wrote task code to '{file_path}'") # Extract class name from code class_match = re.search(r"class\s+(\w+)\s*\(", code) class_name = class_match.group(1) if class_match else "UnknownTask" - # Register task info for later use by other agents + # Extract additional metadata from code for better registry info + task_type_match = re.search(r"task_type\s*=\s*TaskType\.(\w+)", code) + task_type = task_type_match.group(1) if task_type_match else None + + entity_table_match = re.search(r"entity_table\s*=\s*[\"'](\w+)[\"']", code) + entity_table = entity_table_match.group(1) if entity_table_match else None + + target_col_match = re.search(r"target_col\s*=\s*[\"'](\w+)[\"']", code) + target_col = target_col_match.group(1) if target_col_match else None + + # Prepare metadata (include the code itself for full recovery) export_info = { "class_name": class_name, - "export_path": os.path.abspath(file_path), - "module_name": file_name.replace(".py", "") + "export_path": file_path, + "module_name": file_name.replace(".py", ""), + "task_type": task_type, + "entity_table": entity_table, + "target_col": target_col, + "code": code, # Include code for full recovery } + + # Save metadata to JSON file for persistence across sessions/processes + # This is CRITICAL for cross-agent communication + metadata_file = os.path.join(output_dir, "task_metadata.json") + with open(metadata_file, 'w') as mf: + json.dump(export_info, mf, indent=2) + logger.info(f"✅ Saved task metadata to '{metadata_file}'") + + # Verify the metadata file was created + if not os.path.exists(metadata_file): + raise IOError(f"Metadata file was not created: {metadata_file}") + + # Register task info in memory registry (for same-process access) object_registry.register(dict, "task_code", export_info, overwrite=True) + logger.info(f"✅ Registered task_code in ObjectRegistry (class: {class_name})") - logger.info(f"✅ Saved task code to '{file_path}' (class: {class_name})") + logger.info(f"✅ Successfully saved task code to '{file_path}' (class: {class_name})") return { "success": True, - "file_path": os.path.abspath(file_path), + "file_path": file_path, + "metadata_file": metadata_file, "class_name": class_name, - "message": f"Successfully saved {class_name} to '{file_path}'" + "output_dir": output_dir, + "message": f"Successfully saved {class_name} to '{file_path}' with metadata at '{metadata_file}'" } except Exception as e: - logger.error(f"Failed to save task code: {e}") - return {"success": False, "error": str(e)} + import traceback + logger.error(f"Failed to save task code: {e}\n{traceback.format_exc()}") + return {"success": False, "error": str(e), "traceback": traceback.format_exc()} @tool @@ -863,14 +905,16 @@ def register_task_code( Returns: Confirmation message with registered key """ + import re + try: object_registry = ObjectRegistry() - # Store the code + # Store the code under the legacy key (for backward compatibility) code_key = f"task_code_{dataset_name}_{task_name}" object_registry.register(str, code_key, code, overwrite=True) - # Store metadata + # Store metadata under the legacy key metadata_key = f"task_metadata_{dataset_name}_{task_name}" metadata = { "dataset_name": dataset_name, @@ -882,7 +926,26 @@ def register_task_code( } object_registry.register(dict, metadata_key, metadata, overwrite=True) - logger.info(f"✅ Registered task code for '{dataset_name}/{task_name}'") + # CRITICAL: Also register under the canonical "task_code" key that other agents expect + # This ensures cross-agent compatibility with get_dataset_task_info_from_registry() + class_match = re.search(r"class\s+(\w+)\s*\(", code) + class_name = class_match.group(1) if class_match else task_name + + target_col_match = re.search(r"target_col\s*=\s*[\"'](\w+)[\"']", code) + target_col = target_col_match.group(1) if target_col_match else None + + canonical_info = { + "class_name": class_name, + "export_path": None, # Not exported yet + "module_name": None, # Not exported yet + "task_type": task_type, + "entity_table": entity_table, + "target_col": target_col, + "code": code, + } + object_registry.register(dict, "task_code", canonical_info, overwrite=True) + + logger.info(f"✅ Registered task code for '{dataset_name}/{task_name}' (also under canonical 'task_code' key)") return { "success": True, @@ -917,6 +980,7 @@ def export_task_code( - file_path: Path to the exported file """ from datetime import datetime + import json try: object_registry = ObjectRegistry() @@ -946,7 +1010,8 @@ def export_task_code( output_dir = f".workdir/chat-session-{timestamp}" object_registry.register(str, "current_chat_session_dir", output_dir, overwrite=True) - # Create output directory + # Normalize and create output directory + output_dir = os.path.abspath(output_dir) Path(output_dir).mkdir(parents=True, exist_ok=True) # Write the file @@ -955,6 +1020,7 @@ def export_task_code( with open(file_path, 'w') as f: f.write(code) + logger.info(f"Wrote task code to '{file_path}'") # Register export info # Extract class name from code @@ -968,7 +1034,8 @@ def export_task_code( export_info = { "class_name": class_name, "export_path": file_path, - "module_name": "task" + "module_name": "task", + "code": code, # Include code for full recovery } # Try to get metadata to populate additional fields @@ -982,6 +1049,12 @@ def export_task_code( }) except KeyError: pass + + # Save metadata to JSON file for persistence across sessions/processes + metadata_file = os.path.join(output_dir, "task_metadata.json") + with open(metadata_file, 'w') as mf: + json.dump(export_info, mf, indent=2) + logger.info(f"✅ Saved task metadata to '{metadata_file}'") object_registry.register(dict, "task_code", export_info, overwrite=True) @@ -990,13 +1063,15 @@ def export_task_code( return { "success": True, "file_path": file_path, + "metadata_file": metadata_file, "output_dir": output_dir, - "message": f"Successfully exported task code to '{file_path}'" + "message": f"Successfully exported task code to '{file_path}' with metadata at '{metadata_file}'" } except Exception as e: - logger.error(f"Failed to export task code: {e}") - return {"success": False, "error": str(e)} + import traceback + logger.error(f"Failed to export task code: {e}\n{traceback.format_exc()}") + return {"success": False, "error": str(e), "traceback": traceback.format_exc()} @tool From f52a1b3b7eed9c2ba4d228c1f104dffab28537da Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Thu, 15 Jan 2026 08:39:43 +0700 Subject: [PATCH 33/42] :mute:chore: adding scripts for download and import db --- .../create_stack_subset.sh | 0 scripts/download_relbench_csv.py | 28 ++ scripts/generate_relbench_sql.py | 351 ++++++++++++++++++ scripts/import_relbench.sh | 287 ++++++++++++++ .../import_relbench_stack.sh | 6 - 5 files changed, 666 insertions(+), 6 deletions(-) rename create_stack_subset.sh => scripts/create_stack_subset.sh (100%) create mode 100644 scripts/download_relbench_csv.py create mode 100644 scripts/generate_relbench_sql.py create mode 100644 scripts/import_relbench.sh rename import_relbench_stack.sh => scripts/import_relbench_stack.sh (98%) diff --git a/create_stack_subset.sh b/scripts/create_stack_subset.sh similarity index 100% rename from create_stack_subset.sh rename to scripts/create_stack_subset.sh diff --git a/scripts/download_relbench_csv.py b/scripts/download_relbench_csv.py new file mode 100644 index 00000000..0b9e9119 --- /dev/null +++ b/scripts/download_relbench_csv.py @@ -0,0 +1,28 @@ +import os +import pandas as pd +from relbench.datasets import get_dataset + +# Cấu hình đường dẫn khớp với script import bash của bạn +OUTPUT_DIR = "./data/database" +DATASET_NAME = "rel-f1" # Ví dụ: rel-stack, rel-amazon, rel-arxiv + +def export_to_csv(dataset_name, output_dir): + os.makedirs(output_dir, exist_ok=True) + print(f"Downloading and processing {dataset_name}...") + + # Tải dataset (sẽ cache tự động) + dataset = get_dataset(name=dataset_name, download=True) + db = dataset.make_db() + + print(f"Exporting tables to {output_dir}...") + for table_name, table in db.table_dict.items(): + df = table.df + + # Lưu ý: RelBench có thể chứa các cột object phức tạp, cần convert về string nếu cần + # Postgres COPY yêu cầu format CSV chuẩn + file_path = os.path.join(output_dir, f"{table_name}.csv") + df.to_csv(file_path, index=False, header=True) + print(f"-> Saved {table_name}.csv ({len(df)} rows)") + +if __name__ == "__main__": + export_to_csv(DATASET_NAME, OUTPUT_DIR) \ No newline at end of file diff --git a/scripts/generate_relbench_sql.py b/scripts/generate_relbench_sql.py new file mode 100644 index 00000000..2b9779d8 --- /dev/null +++ b/scripts/generate_relbench_sql.py @@ -0,0 +1,351 @@ +#!/usr/bin/env python3 +""" +Generate SQL DDL and export CSV from RelBench datasets +Support any RelBench dataset: rel-f1, rel-amazon, rel-hm, rel-stack, etc. +""" + +import os +import sys +import argparse +import pandas as pd +from relbench.datasets import get_dataset +from pathlib import Path + + +def pandas_dtype_to_sql(dtype, col_name): + """Convert pandas dtype to PostgreSQL type""" + if pd.api.types.is_integer_dtype(dtype): + return "INTEGER" + elif pd.api.types.is_float_dtype(dtype): + return "FLOAT" + elif pd.api.types.is_bool_dtype(dtype): + return "BOOLEAN" + elif pd.api.types.is_datetime64_any_dtype(dtype): + return "TIMESTAMP" + else: + return "TEXT" + + +def get_primary_key_column(table): + """Get primary key column from table""" + if hasattr(table, 'pkey_col') and table.pkey_col: + return table.pkey_col + return None + + +def generate_create_table_sql(table_name, table): + """Generate SQL CREATE TABLE statement for PostgreSQL""" + sql = f"CREATE TABLE {table_name} (\n" + + columns = [] + for col_name in table.df.columns: + dtype = table.df[col_name].dtype + sql_type = pandas_dtype_to_sql(dtype, col_name) + col_def = f" {col_name} {sql_type}" + columns.append(col_def) + + sql += ",\n".join(columns) + + pkey = get_primary_key_column(table) + if pkey: + sql += f",\n PRIMARY KEY ({pkey})" + + sql += "\n);" + return sql + + +def generate_temp_table_sql(table_name, table): + """Generate temporary table with all columns as TEXT""" + sql = f"CREATE TEMP TABLE temp_{table_name} (\n" + columns = [f" {col} TEXT" for col in table.df.columns] + sql += ",\n".join(columns) + sql += "\n);" + return sql + + +def generate_insert_sql(table_name, table): + """Generate INSERT statement with type conversion""" + columns = [] + conversions = [] + + for col_name in table.df.columns: + dtype = table.df[col_name].dtype + columns.append(col_name) + + if pd.api.types.is_integer_dtype(dtype): + conversions.append(f" NULLIF({col_name}, '')::INTEGER") + elif pd.api.types.is_float_dtype(dtype): + conversions.append(f" NULLIF({col_name}, '')::FLOAT") + elif pd.api.types.is_bool_dtype(dtype): + conversions.append(f" NULLIF({col_name}, '')::BOOLEAN") + elif pd.api.types.is_datetime64_any_dtype(dtype): + conversions.append(f" NULLIF({col_name}, '')::TIMESTAMP") + else: + conversions.append(f" NULLIF({col_name}, '')") + + sql = f"INSERT INTO {table_name}\nSELECT \n" + sql += ",\n".join(conversions) + sql += f"\nFROM temp_{table_name};" + return sql + + +def generate_foreign_keys_sql(db): + """Generate ALTER TABLE statements for foreign keys""" + fk_statements = [] + + for table_name, table in db.table_dict.items(): + if hasattr(table, 'fkey_col_to_pkey_table'): + for fkey_col, ref_table in table.fkey_col_to_pkey_table.items(): + if ref_table in db.table_dict: + ref_pkey = get_primary_key_column(db.table_dict[ref_table]) + if ref_pkey: + fk_name = f"fk_{table_name}_{fkey_col}" + stmt = f"ALTER TABLE {table_name} ADD CONSTRAINT {fk_name}\n" + stmt += f" FOREIGN KEY ({fkey_col}) REFERENCES {ref_table}({ref_pkey});" + fk_statements.append(stmt) + + return fk_statements + + +def generate_indexes_sql(db): + """Generate indexes for foreign keys and important columns""" + index_statements = [] + + for table_name, table in db.table_dict.items(): + if hasattr(table, 'fkey_col_to_pkey_table'): + for fkey_col in table.fkey_col_to_pkey_table.keys(): + idx_name = f"idx_{table_name}_{fkey_col}" + stmt = f"CREATE INDEX {idx_name} ON {table_name}({fkey_col}) WHERE {fkey_col} IS NOT NULL;" + index_statements.append(stmt) + + if hasattr(table, 'time_col') and table.time_col: + idx_name = f"idx_{table_name}_{table.time_col}" + stmt = f"CREATE INDEX {idx_name} ON {table_name}({table.time_col});" + index_statements.append(stmt) + + return index_statements + + +def generate_complete_sql(db, dataset_name): + """Generate complete SQL import script""" + sql_parts = [] + + sql_parts.append(f"-- RelBench {dataset_name.upper()} Database Schema") + sql_parts.append("-- Auto-generated from RelBench dataset") + sql_parts.append(f"-- Total tables: {len(db.table_dict)}") + sql_parts.append("") + + sql_parts.append("\\echo '========================================='") + sql_parts.append("\\echo 'Step 1: Drop existing tables'") + sql_parts.append("\\echo '========================================='") + sql_parts.append("") + + for table_name in reversed(list(db.table_dict.keys())): + sql_parts.append(f"DROP TABLE IF EXISTS {table_name} CASCADE;") + sql_parts.append("") + sql_parts.append("\\echo 'Tables dropped'") + sql_parts.append("\\echo ''") + sql_parts.append("") + + sql_parts.append("\\echo '========================================='") + sql_parts.append("\\echo 'Step 2: Create tables'") + sql_parts.append("\\echo '========================================='") + sql_parts.append("") + + for table_name, table in db.table_dict.items(): + sql_parts.append(generate_create_table_sql(table_name, table)) + sql_parts.append("") + + sql_parts.append("\\echo 'Tables created'") + sql_parts.append("\\echo ''") + sql_parts.append("") + + sql_parts.append("\\echo '========================================='") + sql_parts.append("\\echo 'Step 3: Create temp tables for import'") + sql_parts.append("\\echo '========================================='") + sql_parts.append("") + + for table_name, table in db.table_dict.items(): + sql_parts.append(generate_temp_table_sql(table_name, table)) + sql_parts.append("") + + sql_parts.append("\\echo 'Temp tables created'") + sql_parts.append("\\echo ''") + sql_parts.append("") + + sql_parts.append("\\echo '========================================='") + sql_parts.append("\\echo 'Step 4: Import CSV into temp tables'") + sql_parts.append("\\echo '========================================='") + sql_parts.append("") + + for table_name in db.table_dict.keys(): + sql_parts.append(f"\\echo ' Importing {table_name}...'") + sql_parts.append(f"\\copy temp_{table_name} FROM '/tmp/{table_name}.csv' WITH CSV HEADER DELIMITER ',';") + sql_parts.append("") + + sql_parts.append("\\echo 'CSV imported to temp tables'") + sql_parts.append("\\echo ''") + sql_parts.append("") + + sql_parts.append("\\echo '========================================='") + sql_parts.append("\\echo 'Step 5: Transfer data with type conversion'") + sql_parts.append("\\echo '========================================='") + sql_parts.append("") + + for table_name, table in db.table_dict.items(): + sql_parts.append(f"\\echo ' Processing {table_name}...'") + sql_parts.append(generate_insert_sql(table_name, table)) + sql_parts.append("") + + sql_parts.append("\\echo 'Data transferred with NULL handling'") + sql_parts.append("\\echo ''") + sql_parts.append("") + + sql_parts.append("\\echo '========================================='") + sql_parts.append("\\echo 'Step 6: Add Foreign Keys'") + sql_parts.append("\\echo '========================================='") + sql_parts.append("") + + fk_statements = generate_foreign_keys_sql(db) + for stmt in fk_statements: + sql_parts.append(stmt) + sql_parts.append("") + + sql_parts.append("\\echo 'Foreign keys added'") + sql_parts.append("\\echo ''") + sql_parts.append("") + + sql_parts.append("\\echo '========================================='") + sql_parts.append("\\echo 'Step 7: Create Indexes'") + sql_parts.append("\\echo '========================================='") + sql_parts.append("") + + index_statements = generate_indexes_sql(db) + for stmt in index_statements: + sql_parts.append(stmt) + sql_parts.append("") + + sql_parts.append("\\echo 'Indexes created'") + sql_parts.append("\\echo ''") + sql_parts.append("") + + sql_parts.append("\\echo '========================================='") + sql_parts.append("\\echo 'Summary'") + sql_parts.append("\\echo '========================================='") + sql_parts.append("") + sql_parts.append("SELECT ") + sql_parts.append(" table_name,") + sql_parts.append(" to_char(record_count, 'FM999,999,999') as records") + sql_parts.append("FROM (") + + union_parts = [] + for table_name in db.table_dict.keys(): + union_parts.append(f" SELECT '{table_name}' as table_name, COUNT(*) as record_count FROM {table_name}") + + sql_parts.append("\n UNION ALL\n".join(union_parts)) + sql_parts.append(") t") + sql_parts.append("ORDER BY record_count DESC;") + sql_parts.append("") + + sql_parts.append("\\echo ''") + sql_parts.append("\\echo '========================================='") + sql_parts.append("\\echo 'IMPORT COMPLETE'") + sql_parts.append("\\echo '========================================='") + + return "\n".join(sql_parts) + + +def main(): + parser = argparse.ArgumentParser( + description='Generate SQL DDL and export CSV from RelBench datasets', + formatter_class=argparse.RawDescriptionHelpFormatter, + epilog=''' +Examples: + %(prog)s rel-f1 + %(prog)s rel-amazon --output-dir ./amazon_data + %(prog)s rel-hm --no-download + +Supported datasets: + rel-f1, rel-amazon, rel-hm, rel-stack, rel-trial, + rel-event, rel-avito, rel-salt, rel-arxiv, rel-ratebeer + ''' + ) + + parser.add_argument('dataset', type=str, + help='Dataset name (e.g., rel-f1, rel-amazon)') + parser.add_argument('--output-dir', type=str, default=None, + help='Output directory for CSV and SQL files (default: ./{dataset}_data)') + parser.add_argument('--no-download', action='store_true', + help='Skip download if dataset already exists in cache') + + args = parser.parse_args() + + dataset_name = args.dataset + + if args.output_dir: + output_dir = Path(args.output_dir) + else: + dataset_short = dataset_name.replace('rel-', '') + output_dir = Path(f"./{dataset_short}_data") + + print("=" * 60) + print(f"RelBench {dataset_name.upper()} - SQL Generation") + print("=" * 60) + print() + + print(f"Downloading {dataset_name} dataset...") + try: + dataset = get_dataset(dataset_name, download=not args.no_download) + db = dataset.get_db() + except Exception as e: + print(f"Error loading dataset: {e}") + print(f"\nMake sure '{dataset_name}' is a valid RelBench dataset.") + sys.exit(1) + + print(f"Dataset loaded: {len(db.table_dict)} tables") + print() + + output_dir.mkdir(exist_ok=True) + + print("Exporting CSV files...") + for table_name, table in db.table_dict.items(): + csv_path = output_dir / f"{table_name}.csv" + table.df.to_csv(csv_path, index=False) + print(f" {table_name}.csv ({len(table.df):,} rows)") + print() + + print("Generating SQL DDL...") + sql_content = generate_complete_sql(db, dataset_name) + + dataset_short = dataset_name.replace('rel-', '') + sql_file = output_dir / f"import_{dataset_short}.sql" + sql_file.write_text(sql_content) + + print(f"SQL script generated: {sql_file}") + print() + + print("Dataset Statistics:") + print(f" Tables: {len(db.table_dict)}") + total_rows = 0 + for table_name, table in db.table_dict.items(): + pkey = get_primary_key_column(table) + fkeys = len(table.fkey_col_to_pkey_table) if hasattr(table, 'fkey_col_to_pkey_table') else 0 + rows = len(table.df) + total_rows += rows + print(f" - {table_name:30s} {rows:10,} rows, {len(table.df.columns):2} cols, PK: {pkey}, FKs: {fkeys}") + print(f"\n Total rows: {total_rows:,}") + print() + + print("=" * 60) + print("Generation complete") + print("=" * 60) + print() + print("Output directory:", output_dir) + print("SQL script:", sql_file) + print() + print("Next steps:") + print(f" ./import_relbench.sh {dataset_name}") + + +if __name__ == "__main__": + main() \ No newline at end of file diff --git a/scripts/import_relbench.sh b/scripts/import_relbench.sh new file mode 100644 index 00000000..39139544 --- /dev/null +++ b/scripts/import_relbench.sh @@ -0,0 +1,287 @@ +#!/bin/bash +set -e + +CONTAINER_NAME="plexe-clone-postgres-1" +DB_USER="mlflow" + +print_header() { + echo "" + echo "=========================================" + echo "$1" + echo "=========================================" + echo "" +} + +print_error() { + echo "ERROR: $1" >&2 +} + +print_info() { + echo "INFO: $1" +} + +cleanup() { + if [ "$KEEP_DATA" != "true" ]; then + print_header "Cleanup" + + print_info "Removing CSV files from container..." + docker exec $CONTAINER_NAME bash -c "rm -f /tmp/*.csv /tmp/import_*.sql" 2>/dev/null || true + + if [ -d "$DATA_DIR" ]; then + print_info "Removing local data directory: $DATA_DIR" + rm -rf "$DATA_DIR" + echo "Data directory removed" + fi + + if [ "$REMOVE_RELBENCH_CACHE" = "true" ]; then + RELBENCH_CACHE="$HOME/.cache/relbench" + if [ -d "$RELBENCH_CACHE" ]; then + print_info "Removing RelBench cache: $RELBENCH_CACHE" + rm -rf "$RELBENCH_CACHE" + echo "RelBench cache removed" + fi + fi + + echo "Cleanup complete" + else + print_info "Keeping data files (KEEP_DATA=true)" + fi +} + +trap 'print_error "Script failed on line $LINENO"; cleanup; exit 1' ERR +trap 'cleanup' EXIT + +show_usage() { + cat << EOF +Usage: $0 [options] + +Arguments: + dataset-name RelBench dataset name (e.g., rel-f1, rel-amazon, rel-hm) + +Options: + --db-name NAME Database name (default: derived from dataset name) + --output-dir DIR Output directory for data files + --keep-data Keep CSV and SQL files after import + --remove-cache Remove RelBench cache after import + --help Show this help message + +Examples: + $0 rel-f1 + $0 rel-amazon --db-name amazon + $0 rel-hm --keep-data + $0 rel-stack --db-name stackoverflow --output-dir ./stack_data + +Supported datasets: + rel-f1, rel-amazon, rel-hm, rel-stack, rel-trial, + rel-event, rel-avito, rel-salt, rel-arxiv, rel-ratebeer + +EOF + exit 0 +} + +if [ $# -eq 0 ]; then + show_usage +fi + +DATASET_NAME="" +DB_NAME="" +OUTPUT_DIR="" +KEEP_DATA="false" +REMOVE_RELBENCH_CACHE="false" + +while [ $# -gt 0 ]; do + case "$1" in + --db-name) + DB_NAME="$2" + shift 2 + ;; + --output-dir) + OUTPUT_DIR="$2" + shift 2 + ;; + --keep-data) + KEEP_DATA="true" + shift + ;; + --remove-cache) + REMOVE_RELBENCH_CACHE="true" + shift + ;; + --help) + show_usage + ;; + -*) + print_error "Unknown option: $1" + show_usage + ;; + *) + if [ -z "$DATASET_NAME" ]; then + DATASET_NAME="$1" + else + print_error "Multiple dataset names provided" + show_usage + fi + shift + ;; + esac +done + +if [ -z "$DATASET_NAME" ]; then + print_error "Dataset name is required" + show_usage +fi + +DATASET_SHORT=$(echo "$DATASET_NAME" | sed 's/^rel-//') + +if [ -z "$DB_NAME" ]; then + DB_NAME="$DATASET_SHORT" +fi + +if [ -z "$OUTPUT_DIR" ]; then + OUTPUT_DIR="./${DATASET_SHORT}_data" +fi + +DATA_DIR="$OUTPUT_DIR" +SQL_FILE="$DATA_DIR/import_${DATASET_SHORT}.sql" + +print_header "RelBench Import - $DATASET_NAME" + +echo "Configuration:" +echo " Dataset: $DATASET_NAME" +echo " Database: $DB_NAME" +echo " Container: $CONTAINER_NAME" +echo " Data dir: $DATA_DIR" +echo "" + +if ! command -v python3 &> /dev/null; then + print_error "Python 3 is not installed" + exit 1 +fi +echo "Python 3 is available" + +print_info "Checking Python dependencies..." +if ! python3 -c "import relbench" 2>/dev/null; then + print_info "Installing relbench..." + pip install relbench +fi +if ! python3 -c "import pandas" 2>/dev/null; then + print_info "Installing pandas..." + pip install pandas +fi +echo "Python dependencies OK" + +print_header "Step 1: Verify PostgreSQL Container" +print_info "Checking container: $CONTAINER_NAME" +if ! docker ps | grep -q $CONTAINER_NAME; then + print_error "Container '$CONTAINER_NAME' is not running" + print_info "Start it with: docker start $CONTAINER_NAME" + exit 1 +fi +echo "Container is running" + +print_header "Step 2: Prepare Database" +print_info "Checking database: $DB_NAME" +if ! docker exec $CONTAINER_NAME psql -U $DB_USER -lqt | cut -d \| -f 1 | grep -qw $DB_NAME; then + print_info "Database '$DB_NAME' does not exist, creating..." + docker exec $CONTAINER_NAME psql -U $DB_USER -d postgres -c "CREATE DATABASE $DB_NAME;" + echo "Database '$DB_NAME' created" +else + echo "Database '$DB_NAME' already exists" + print_info "Existing tables will be dropped and recreated" +fi + +print_header "Step 3: Download Dataset and Generate SQL" +print_info "Running Python script to download $DATASET_NAME dataset..." + +if [ ! -f "generate_relbench_sql.py" ]; then + print_error "generate_relbench_sql.py not found in current directory" + exit 1 +fi + +python3 generate_relbench_sql.py "$DATASET_NAME" --output-dir "$DATA_DIR" + +if [ ! -d "$DATA_DIR" ]; then + print_error "Data directory not created, Python script may have failed" + exit 1 +fi + +if [ ! -f "$SQL_FILE" ]; then + print_error "SQL script not generated, Python script may have failed" + exit 1 +fi + +echo "Dataset downloaded and SQL generated" + +CSV_COUNT=$(ls -1 $DATA_DIR/*.csv 2>/dev/null | wc -l) +print_info "Found $CSV_COUNT CSV files" + +print_header "Step 4: Copy Files to Container" +print_info "Copying CSV files to container..." +for csv_file in $DATA_DIR/*.csv; do + if [ -f "$csv_file" ]; then + filename=$(basename "$csv_file") + docker cp "$csv_file" $CONTAINER_NAME:/tmp/ + echo "Copied $filename" + fi +done + +print_info "Copying SQL script to container..." +docker cp "$SQL_FILE" $CONTAINER_NAME:/tmp/ +echo "SQL script copied" + +print_header "Step 5: Import Data into PostgreSQL" +print_info "Running SQL import script..." +echo "=========================================" + +docker exec -i $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME -f /tmp/import_${DATASET_SHORT}.sql + +echo "=========================================" +echo "Data import completed" + +print_header "Step 6: Verify Import" +print_info "Checking table counts..." + +docker exec $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME -c " +SELECT + schemaname, + tablename, + to_char(n_live_tup, 'FM999,999,999') as row_count +FROM pg_stat_user_tables +WHERE schemaname = 'public' +ORDER BY n_live_tup DESC; +" + +print_header "Import Complete" + +echo "Database Details:" +echo " Container: $CONTAINER_NAME" +echo " Database: $DB_NAME" +echo " User: $DB_USER" +echo "" +echo "Connect to database:" +echo " docker exec -it $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME" +echo "" +echo "Example queries:" +echo " \\dt -- List all tables" +echo " \\d table_name -- Show table structure" +echo " SELECT COUNT(*) FROM table_name;" +echo "" + +if [ "$KEEP_DATA" = "false" ]; then + read -p "Keep data files? (y/N) " -n 1 -r + echo + if [[ $REPLY =~ ^[Yy]$ ]]; then + export KEEP_DATA=true + print_info "Data files will be kept in: $DATA_DIR" + fi +fi + +if [ "$KEEP_DATA" = "false" ] && [ "$REMOVE_RELBENCH_CACHE" = "false" ]; then + read -p "Remove RelBench cache? (y/N) " -n 1 -r + echo + if [[ $REPLY =~ ^[Yy]$ ]]; then + export REMOVE_RELBENCH_CACHE=true + fi +fi + +print_header "Done" \ No newline at end of file diff --git a/import_relbench_stack.sh b/scripts/import_relbench_stack.sh similarity index 98% rename from import_relbench_stack.sh rename to scripts/import_relbench_stack.sh index a3f84caa..198f17b2 100644 --- a/import_relbench_stack.sh +++ b/scripts/import_relbench_stack.sh @@ -1,9 +1,3 @@ -#!/bin/bash - -# ===================================================== -# Script import thuần SQL - không dùng Python -# ===================================================== - set -e CONTAINER_NAME="plexe-clone-postgres-1" From 3dd2e41c5575ce4cb00feeb1f093ce19b525e9d1 Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Sat, 17 Jan 2026 16:24:21 +0700 Subject: [PATCH 34/42] :mute:chore: adding scripts --- Dockerfile.gpu | 2 +- docker-compose.gpu.yml | 2 +- plexe/relbench/datasets/__init__.py | 14 + plexe/relbench/datasets/amazon.py | 228 + plexe/relbench/datasets/arxiv.py | 107 + plexe/relbench/datasets/avito.py | 134 + plexe/relbench/datasets/dbinfer.py | 113 + plexe/relbench/datasets/event.py | 183 + plexe/relbench/datasets/f1.py | 238 + plexe/relbench/datasets/fake.py | 114 + plexe/relbench/datasets/hm.py | 70 + plexe/relbench/datasets/mimic.py | 591 + plexe/relbench/datasets/ratebeer.py | 337 + plexe/relbench/datasets/salt.py | 163 + plexe/relbench/datasets/stack.py | 132 + plexe/relbench/datasets/trial.py | 369 + plexe/relbench/tasks/__init__.py | 13 + plexe/relbench/tasks/amazon.py | 394 + plexe/relbench/tasks/arxiv.py | 240 + plexe/relbench/tasks/avito.py | 226 + plexe/relbench/tasks/dbinfer.py | 179 + plexe/relbench/tasks/event.py | 189 + plexe/relbench/tasks/f1.py | 220 + plexe/relbench/tasks/hm.py | 166 + plexe/relbench/tasks/mimic.py | 73 + plexe/relbench/tasks/ratebeer.py | 483 + plexe/relbench/tasks/stack.py | 342 + plexe/relbench/tasks/trial.py | 278 + scripts/.python-version | 1 + scripts/README.md | 0 scripts/f1_data/circuits.csv | 78 + scripts/f1_data/constructor_results.csv | 9409 +++++++ scripts/f1_data/constructor_standings.csv | 10171 +++++++ scripts/f1_data/constructors.csv | 212 + scripts/f1_data/drivers.csv | 858 + scripts/f1_data/import_f1.sql | 490 + scripts/f1_data/qualifying.csv | 4083 +++ scripts/f1_data/races.csv | 821 + scripts/f1_data/results.csv | 20324 ++++++++++++++ scripts/f1_data/standings.csv | 28116 ++++++++++++++++++++ scripts/import_relbench.sh | 207 +- scripts/main.py | 6 + scripts/pyproject.toml | 7 + scripts/uv.lock | 8 + 44 files changed, 80339 insertions(+), 52 deletions(-) create mode 100644 plexe/relbench/datasets/amazon.py create mode 100644 plexe/relbench/datasets/arxiv.py create mode 100644 plexe/relbench/datasets/avito.py create mode 100644 plexe/relbench/datasets/dbinfer.py create mode 100644 plexe/relbench/datasets/event.py create mode 100644 plexe/relbench/datasets/f1.py create mode 100644 plexe/relbench/datasets/fake.py create mode 100644 plexe/relbench/datasets/hm.py create mode 100644 plexe/relbench/datasets/mimic.py create mode 100644 plexe/relbench/datasets/ratebeer.py create mode 100644 plexe/relbench/datasets/salt.py create mode 100644 plexe/relbench/datasets/stack.py create mode 100644 plexe/relbench/datasets/trial.py create mode 100644 plexe/relbench/tasks/amazon.py create mode 100644 plexe/relbench/tasks/arxiv.py create mode 100644 plexe/relbench/tasks/avito.py create mode 100644 plexe/relbench/tasks/dbinfer.py create mode 100644 plexe/relbench/tasks/event.py create mode 100644 plexe/relbench/tasks/f1.py create mode 100644 plexe/relbench/tasks/hm.py create mode 100644 plexe/relbench/tasks/mimic.py create mode 100644 plexe/relbench/tasks/ratebeer.py create mode 100644 plexe/relbench/tasks/stack.py create mode 100644 plexe/relbench/tasks/trial.py create mode 100644 scripts/.python-version create mode 100644 scripts/README.md create mode 100644 scripts/f1_data/circuits.csv create mode 100644 scripts/f1_data/constructor_results.csv create mode 100644 scripts/f1_data/constructor_standings.csv create mode 100644 scripts/f1_data/constructors.csv create mode 100644 scripts/f1_data/drivers.csv create mode 100644 scripts/f1_data/import_f1.sql create mode 100644 scripts/f1_data/qualifying.csv create mode 100644 scripts/f1_data/races.csv create mode 100644 scripts/f1_data/results.csv create mode 100644 scripts/f1_data/standings.csv create mode 100644 scripts/main.py create mode 100644 scripts/pyproject.toml create mode 100644 scripts/uv.lock diff --git a/Dockerfile.gpu b/Dockerfile.gpu index 3c4fb750..e0250c88 100644 --- a/Dockerfile.gpu +++ b/Dockerfile.gpu @@ -98,4 +98,4 @@ from plexe import Model print("✓ plexe import OK") EOF -CMD ["python", "-m", "uvicorn", "plexe.server:app", "--host", "0.0.0.0", "--port", "8000", "--reload", "--reload-dir", "plexe"] \ No newline at end of file +CMD ["python", "-m", "uvicorn", "plexe.server:app", "--host", "0.0.0.0", "--port", "8100", "--reload", "--reload-dir", "plexe"] \ No newline at end of file diff --git a/docker-compose.gpu.yml b/docker-compose.gpu.yml index ca47054a..a69d0448 100644 --- a/docker-compose.gpu.yml +++ b/docker-compose.gpu.yml @@ -80,7 +80,7 @@ services: volumes: - .:/app ports: - - "8000:8000" + - "8100:8100" deploy: resources: reservations: diff --git a/plexe/relbench/datasets/__init__.py b/plexe/relbench/datasets/__init__.py index 949488fd..da153e37 100644 --- a/plexe/relbench/datasets/__init__.py +++ b/plexe/relbench/datasets/__init__.py @@ -6,6 +6,20 @@ import pooch from ..base import Dataset +from ..datasets import ( + amazon, + arxiv, + avito, + dbinfer, + event, + f1, + hm, + mimic, + ratebeer, + salt, + stack, + trial, +) dataset_registry = {} diff --git a/plexe/relbench/datasets/amazon.py b/plexe/relbench/datasets/amazon.py new file mode 100644 index 00000000..459e9459 --- /dev/null +++ b/plexe/relbench/datasets/amazon.py @@ -0,0 +1,228 @@ +import time + +import pandas as pd +import pooch +import pyarrow as pa +import pyarrow.json + +from relbench.base import Database, Dataset, Table + + +class AmazonDataset(Dataset): + val_timestamp = pd.Timestamp("2015-10-01") + test_timestamp = pd.Timestamp("2016-01-01") + + url_prefix = "https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_v2" + _category_to_url_key = {"books": "Books", "fashion": "AMAZON_FASHION"} + + known_hashes = { + "meta_Books.json.gz": "80ed7ac64f5967a140401e8d7bf0587d2e5087492de9e94077a7f554ef6b18f0", + "Books_5.json.gz": "ded924d1d1a22bae499f1a1c2b39397104304bfdb24232a2dd0aa50e89cd37bb", + } + + def __init__( + self, + category: str = "books", + use_5_core: bool = True, + cache_dir: str = None, + ): + self.category = category + self.use_5_core = use_5_core + super().__init__(cache_dir=cache_dir) + + def make_db(self) -> Database: + r"""Process the raw files into a database.""" + + ### product table ### + + url_key = self._category_to_url_key[self.category] + url = f"{self.url_prefix}/metaFiles2/meta_{url_key}.json.gz" + path = pooch.retrieve( + url, + known_hash=self.known_hashes.get(url.split("/")[-1], None), + progressbar=True, + processor=pooch.Decompress(), + ) + print(f"reading product info from {path}...") + tic = time.time() + ptable = pa.json.read_json( + path, + parse_options=pa.json.ParseOptions( + explicit_schema=pa.schema( + [ + ("asin", pa.string()), + ("category", pa.list_(pa.string())), + ("brand", pa.string()), + ("title", pa.string()), + ("description", pa.list_(pa.string())), + ("price", pa.string()), + ] + ), + unexpected_field_behavior="ignore", + ), + ) + toc = time.time() + print(f"done in {toc - tic:.2f} seconds.") + + print("converting to pandas dataframe...") + tic = time.time() + pdf = ptable.to_pandas() + toc = time.time() + print(f"done in {toc - tic:.2f} seconds.") + + print("processing product info...") + tic = time.time() + + # asin is not intuitive / recognizable + pdf.rename(columns={"asin": "product_id"}, inplace=True) + + # somehow the raw data has duplicate product_id's + pdf.drop_duplicates(subset=["product_id"], inplace=True) + + # price is like "$x,xxx.xx", "$xx.xx", or "$xx.xx - $xx.xx", or garbage html + # if it's a range, we take the first value + pdf.loc[:, "price"] = pdf["price"].apply( + lambda x: ( + None + if x is None or x == "" or x[0] != "$" + else float(x.split(" ")[0][1:].replace(",", "")) + ) + ) + + # remove products with missing price + pdf = pdf.dropna(subset=["price"]) + + pdf.loc[:, "category"] = pdf["category"].apply( + lambda x: None if x is None or len(x) == 0 else x + ) + + # some rows are stored as ['cat1' 'cat2' 'cat3' ...] + # this function maps them to ['cat1', 'cat2', 'cat3', ...] (list of strings) + # since otherwise pytorch-frame breaks + def fix_column(value): + if isinstance(value, str): + return value # Already a string + elif value is None: + return None + else: + return list(value) + + pdf["category"] = pdf["category"].apply(fix_column) + + # description is either [] or ["some description"] + pdf.loc[:, "description"] = pdf["description"].apply( + lambda x: None if x is None or len(x) == 0 else x[0] + ) + + toc = time.time() + print(f"done in {toc - tic:.2f} seconds.") + + ### review table ### + + if self.use_5_core: + url = f"{self.url_prefix}/categoryFilesSmall/{url_key}_5.json.gz" + else: + url = f"{self.url_prefix}/categoryFiles/{url_key}.json.gz" + path = pooch.retrieve( + url, + known_hash=self.known_hashes.get(url.split("/")[-1], None), + progressbar=True, + processor=pooch.Decompress(), + ) + print(f"reading review and customer info from {path}...") + tic = time.time() + rtable = pa.json.read_json( + path, + parse_options=pa.json.ParseOptions( + explicit_schema=pa.schema( + [ + ("unixReviewTime", pa.int32()), + ("reviewerID", pa.string()), + ("reviewerName", pa.string()), + ("asin", pa.string()), + ("overall", pa.float32()), + ("verified", pa.bool_()), + ("reviewText", pa.string()), + ("summary", pa.string()), + ] + ), + unexpected_field_behavior="ignore", + ), + ) + toc = time.time() + print(f"done in {toc - tic:.2f} seconds.") + + print("converting to pandas dataframe...") + tic = time.time() + rdf = rtable.to_pandas() + toc = time.time() + print(f"done in {toc - tic:.2f} seconds.") + + print("processing review and customer info...") + tic = time.time() + + rdf.rename( + columns={ + "unixReviewTime": "review_time", + "reviewerID": "customer_id", + "reviewerName": "customer_name", + "asin": "product_id", + "overall": "rating", + "reviewText": "review_text", + }, + inplace=True, + ) + + rdf.loc[:, "review_time"] = pd.to_datetime(rdf["review_time"], unit="s") + + toc = time.time() + print(f"done in {toc - tic:.2f} seconds.") + + print("keeping only products common to product and review tables...") + tic = time.time() + plist = list(set(pdf["product_id"]) & set(rdf["product_id"])) + pdf.query("product_id == @plist", inplace=True) + rdf.query("product_id == @plist", inplace=True) + toc = time.time() + print(f"done in {toc - tic:.2f} seconds.") + + print("extracting customer table...") + tic = time.time() + cdf = ( + rdf[["customer_id", "customer_name"]] + .drop_duplicates(subset=["customer_id"]) + .copy() + ) + rdf.drop(columns=["customer_name"], inplace=True) + toc = time.time() + print(f"done in {toc - tic:.2f} seconds.") + + db = Database( + table_dict={ + "product": Table( + df=pdf, + fkey_col_to_pkey_table={}, + pkey_col="product_id", + time_col=None, + ), + "customer": Table( + df=cdf, + fkey_col_to_pkey_table={}, + pkey_col="customer_id", + time_col=None, + ), + "review": Table( + df=rdf, + fkey_col_to_pkey_table={ + "customer_id": "customer", + "product_id": "product", + }, + pkey_col=None, + time_col="review_time", + ), + } + ) + + db = db.from_(pd.Timestamp("2008-01-01")) + + return db diff --git a/plexe/relbench/datasets/arxiv.py b/plexe/relbench/datasets/arxiv.py new file mode 100644 index 00000000..feb25400 --- /dev/null +++ b/plexe/relbench/datasets/arxiv.py @@ -0,0 +1,107 @@ +import os + +import pandas as pd +import pooch +from sklearn.preprocessing import LabelEncoder + +from relbench.base import Database, Dataset, Table + + +class ArxivDataset(Dataset): + val_timestamp = pd.Timestamp("2022-01-01") + test_timestamp = pd.Timestamp("2023-01-01") + + def make_db(self) -> Database: + r"""Process the raw files into a database.""" + + url = ( + "https://www.dropbox.com/scl/fi/tjj6r1fqikt4j0rz4qomu/db.zip?rlkey=1ykfkp8pj3hu6n4utz8g9dkx2&st" + "=azmm56dc&dl=1" + ) + + path = pooch.retrieve( + url, + known_hash="ff9e03e467e28df959d08c79c453db1f31b525f07ff3c0e0b5e571e732acc63f", + progressbar=True, + processor=pooch.Unzip(), + ) + + if isinstance(path, list): + path = os.path.dirname(path[0]) + + print("Final dataset directory:", path) + + papers = pd.read_csv(os.path.join(path, "1Paper.csv")) + categories = pd.read_csv(os.path.join(path, "2Category.csv")) + citations = pd.read_csv(os.path.join(path, "3Citation.csv")) + paperCategories = pd.read_csv(os.path.join(path, "4Paper_Category.csv")) + authors = pd.read_csv(os.path.join(path, "5Author.csv")) + paperAuthors = pd.read_csv(os.path.join(path, "6Paper_Author.csv")) + + # Convert category column to integer + le = LabelEncoder() + categories["Category"] = le.fit_transform(categories["Category"]) + + # Convert date column to pd.Timestamp + papers["Submission_Date"] = pd.to_datetime( + papers["Submission_Date"], format="%Y%m%d" + ) + citations["Submission_Date"] = pd.to_datetime( + citations["Submission_Date"], format="%Y%m%d" + ) + paperAuthors["Submission_Date"] = pd.to_datetime( + paperAuthors["Submission_Date"], format="%Y%m%d" + ) + + # add time column to other tables + paperCategories = paperCategories.merge( + papers[["Paper_ID", "Submission_Date"]], on="Paper_ID", how="left" + ) + + # collect all tables in the database as relbench.base.Table objects. + tables = { + "papers": Table( + df=pd.DataFrame(papers), + fkey_col_to_pkey_table={}, + pkey_col="Paper_ID", + time_col="Submission_Date", + ), + "categories": Table( + df=pd.DataFrame(categories), + fkey_col_to_pkey_table={}, + pkey_col="Category_ID", + time_col=None, + ), + "citations": Table( + df=pd.DataFrame(citations), + fkey_col_to_pkey_table={ + "Paper_ID": "papers", + "References_Paper_ID": "papers", + }, + pkey_col=None, + time_col="Submission_Date", + ), + "paperCategories": Table( + df=pd.DataFrame(paperCategories), + fkey_col_to_pkey_table={ + "Paper_ID": "papers", + "Category_ID": "categories", + }, + pkey_col=None, + time_col="Submission_Date", + ), + "authors": Table( + df=pd.DataFrame(authors), + fkey_col_to_pkey_table={}, + pkey_col="Author_ID", + time_col=None, + ), + "paperAuthors": Table( + df=pd.DataFrame(paperAuthors), + fkey_col_to_pkey_table={"Paper_ID": "papers", "Author_ID": "authors"}, + pkey_col=None, + time_col="Submission_Date", + ), + } + + return Database(tables) diff --git a/plexe/relbench/datasets/avito.py b/plexe/relbench/datasets/avito.py new file mode 100644 index 00000000..16160b65 --- /dev/null +++ b/plexe/relbench/datasets/avito.py @@ -0,0 +1,134 @@ +import os + +import pandas as pd +import pooch + +from relbench.base import Database, Dataset, Table +from relbench.utils import clean_datetime, unzip_processor + + +class AvitoDataset(Dataset): + """Original data source: + https://www.kaggle.com/competitions/avito-context-ad-clicks""" + + # search stream ranges from 2015-04-25 to 2015-05-20 + val_timestamp = pd.Timestamp("2015-05-08") + test_timestamp = pd.Timestamp("2015-05-14") + + def make_db(self) -> Database: + # subsampled version of the original dataset + # Customize path as necessary + r"""Process the raw files into a database.""" + url = "https://relbench.stanford.edu/data/rel-avito-raw-100k.zip" + path = pooch.retrieve( + url, + known_hash="ad4fc1789d8a5073ea449049888c671899525c9a8a42359ca75d1f17d04d7929", + progressbar=True, + processor=unzip_processor, + ) + path = os.path.join(path, "avito_100k_integ_test") + + # Define table names + ads_info = os.path.join(path, "AdsInfo") + category = os.path.join(path, "Category") + location = os.path.join(path, "Location") + phone_requests_stream = os.path.join(path, "PhoneRequestsStream") + search_info = os.path.join(path, "SearchInfo") + search_stream = os.path.join(path, "SearchStream") + user_info = os.path.join(path, "UserInfo") + visit_stream = os.path.join(path, "VisitStream") + if not os.path.exists(ads_info): + raise RuntimeError( + self.err_msg.format(data="Dataset", url=self.url, path=path) + ) + + # Load table as pandas dataframes + ads_info_df = pd.read_parquet(ads_info) + ads_info_df.dropna(subset=["AdID"], inplace=True) + # Params column contains a dictionary of type Dict[int, str]. + # Drop it for now since we can not handle this column type yet. + ads_info_df.drop(columns=["Params"], inplace=True) + ads_info_df["Title"].fillna("", inplace=True) + category_df = pd.read_parquet(category) + location_df = pd.read_parquet(location) + location_df.dropna(subset=["LocationID"], inplace=True) + phone_requests_stream_df = pd.read_parquet(phone_requests_stream) + search_info_df = pd.read_parquet(search_info) + # SearchParams column contains a dictionary of type Dict[int, str]. + # Drop it for now since we can not handle this column type yet. + search_info_df.drop(columns=["SearchParams"], inplace=True) + search_stream_df = pd.read_parquet(search_stream) + user_info_df = pd.read_parquet(user_info) + visit_stream_df = pd.read_parquet(visit_stream) + search_info_df = clean_datetime(search_info_df, "SearchDate") + search_stream_df = clean_datetime(search_stream_df, "SearchDate") + phone_requests_stream_df = clean_datetime( + phone_requests_stream_df, "PhoneRequestDate" + ) + visit_stream_df = clean_datetime(visit_stream_df, "ViewDate") + + category_df.drop(columns=["__index_level_0__"], inplace=True) + + tables = {} + tables["AdsInfo"] = Table( + df=ads_info_df, + fkey_col_to_pkey_table={ + "LocationID": "Location", + "CategoryID": "Category", + }, + pkey_col="AdID", + ) + tables["Category"] = Table( + df=category_df, + fkey_col_to_pkey_table={}, + pkey_col="CategoryID", + ) + tables["Location"] = Table( + df=location_df, + fkey_col_to_pkey_table={}, + pkey_col="LocationID", + ) + tables["PhoneRequestsStream"] = Table( + df=phone_requests_stream_df, + fkey_col_to_pkey_table={ + "UserID": "UserInfo", + "AdID": "AdsInfo", + }, + time_col="PhoneRequestDate", + ) + tables["SearchInfo"] = Table( + df=search_info_df, + fkey_col_to_pkey_table={ + "UserID": "UserInfo", + "LocationID": "Location", + "CategoryID": "Category", + }, + pkey_col="SearchID", + time_col="SearchDate", + ) + tables["SearchStream"] = Table( + df=search_stream_df, + fkey_col_to_pkey_table={ + "SearchID": "SearchInfo", + "AdID": "AdsInfo", + }, + time_col="SearchDate", + ) + tables["UserInfo"] = Table( + df=user_info_df, + fkey_col_to_pkey_table={}, + pkey_col="UserID", + ) + tables["VisitStream"] = Table( + df=visit_stream_df, + fkey_col_to_pkey_table={ + "UserID": "UserInfo", + "AdID": "AdsInfo", + }, + time_col="ViewDate", + ) + db = Database(tables) + + db = db.from_(pd.Timestamp("2015-04-25")) + + return db diff --git a/plexe/relbench/datasets/dbinfer.py b/plexe/relbench/datasets/dbinfer.py new file mode 100644 index 00000000..2178c8d9 --- /dev/null +++ b/plexe/relbench/datasets/dbinfer.py @@ -0,0 +1,113 @@ +import os +from typing import Dict + +import pandas as pd +import pooch + +from relbench.base import Database, Dataset, Table + +DEFAULT_DBINFER_ADAPTER_CACHE = os.path.join( + pooch.os_cache("relbench"), "dbinfer-adapters" +) + + +class DBInferDatasetBase(Dataset): + """Materialize a 4DBInfer dataset as a RelBench Database.""" + + dbinfer_name: str | None = None + default_task_name: str | None = None + + # DBInfer datasets are not time-sliced, so we set placeholder timestamps that + # satisfy the Dataset API without affecting static tables. + val_timestamp = pd.Timestamp("1970-01-01") + test_timestamp = pd.Timestamp("1970-01-02") + + def __init__( + self, + cache_dir: str | None = None, + adapter_cache_dir: str | None = None, + ): + super().__init__(cache_dir=cache_dir) + if not self.dbinfer_name or not self.default_task_name: + raise ValueError( + "DBInferDatasetBase subclasses must define 'dbinfer_name' and " + "'default_task_name'." + ) + if adapter_cache_dir is None: + adapter_cache_dir = DEFAULT_DBINFER_ADAPTER_CACHE + self._adapter_cache_dir = adapter_cache_dir + + def _load_dataset_adapter(self): + from dbinfer_relbench_adapter.loader import load_dbinfer_data + + dataset_adapter, _ = load_dbinfer_data( + dataset_name=self.dbinfer_name, + task_name=self.default_task_name, + use_cache=True, + cache_dir=self._adapter_cache_dir, + ) + return dataset_adapter + + def _build_table_dict(self) -> Dict[str, Table]: + dataset_adapter = self._load_dataset_adapter() + mock_db = dataset_adapter.get_db() + + table_dict: Dict[str, Table] = {} + for name, mock_table in mock_db.table_dict.items(): + table_dict[name] = Table( + df=mock_table.df.copy(), + fkey_col_to_pkey_table=getattr( + mock_table, "fkey_col_to_pkey_table", {} + ), + pkey_col=getattr(mock_table, "pkey_col", None), + time_col=getattr(mock_table, "time_col", None), + ) + return table_dict + + def make_db(self) -> Database: + return Database(table_dict=self._build_table_dict()) + + def get_db(self, upto_test_timestamp: bool = True) -> Database: + """DBInfer datasets are static, so never trim by timestamp.""" + + return super().get_db(upto_test_timestamp=False) + + +class DBInferAVSDataset(DBInferDatasetBase): + dbinfer_name = "avs" + default_task_name = "repeater" + + +class DBInferMAGDataset(DBInferDatasetBase): + dbinfer_name = "mag" + default_task_name = "cite" + + +class DBInferDigineticaDataset(DBInferDatasetBase): + dbinfer_name = "diginetica" + default_task_name = "ctr" + + +class DBInferRetailRocketDataset(DBInferDatasetBase): + dbinfer_name = "retailrocket" + default_task_name = "cvr" + + +class DBInferSeznamDataset(DBInferDatasetBase): + dbinfer_name = "seznam" + default_task_name = "charge" + + +class DBInferAmazonDataset(DBInferDatasetBase): + dbinfer_name = "amazon" + default_task_name = "rating" + + +class DBInferStackExchangeDataset(DBInferDatasetBase): + dbinfer_name = "stackexchange" + default_task_name = "churn" + + +class DBInferOutbrainSmallDataset(DBInferDatasetBase): + dbinfer_name = "outbrain-small" + default_task_name = "ctr" diff --git a/plexe/relbench/datasets/event.py b/plexe/relbench/datasets/event.py new file mode 100644 index 00000000..78269080 --- /dev/null +++ b/plexe/relbench/datasets/event.py @@ -0,0 +1,183 @@ +import os +import shutil +from pathlib import Path + +import pandas as pd + +from relbench.base import Database, Dataset, Table +from relbench.utils import decompress_gz_file + + +class EventDataset(Dataset): + url = "https://www.kaggle.com/competitions/event-recommendation-engine-challenge" # noqa + err_msg = ( + "{data} not found. Please download " + "event-recommendation-engine-challenge.zip from " + "'{url}' and move it to '{path}'. Once you have your" + "Kaggle API key, you can use the following command: " + "kaggle competitions download -c event-recommendation-engine-challenge" + ) + + val_timestamp = pd.Timestamp("2012-11-21") + test_timestamp = pd.Timestamp("2012-11-29") + + def check_table_and_decompress_if_exists(self, table_path: str, alt_path: str = ""): + if not os.path.exists(table_path) or ( + alt_path != "" and not os.path.exists(alt_path) + ): + if os.path.exists(table_path + ".gz"): + decompress_gz_file(table_path + ".gz", table_path) + else: + self.err_msg.format(data=table_path, url=self.url, path=table_path) + + def make_db(self) -> Database: + path = os.path.join("data", "rel-event") + zip_path = os.path.join(path, "event-recommendation-engine-challenge.zip") + users = os.path.join(path, "users.csv") + user_friends = os.path.join(path, "user_friends.csv") + events = os.path.join(path, "events.csv") + event_attendees = os.path.join(path, "event_attendees.csv") + if not (os.path.exists(users)): + if not os.path.exists(zip_path): + raise RuntimeError( + self.err_msg.format(data="Dataset", url=self.url, path=zip_path) + ) + else: + shutil.unpack_archive(zip_path, Path(zip_path).parent) + self.check_table_and_decompress_if_exists( + user_friends, os.path.join(path, "user_friends_flattened.csv") + ) + self.check_table_and_decompress_if_exists(events) + self.check_table_and_decompress_if_exists( + event_attendees, os.path.join(path, "event_attendees_flattened.csv") + ) + users_df = pd.read_csv(users, dtype={"user_id": int}, parse_dates=["joinedAt"]) + users_df["birthyear"] = pd.to_numeric(users_df["birthyear"], errors="coerce") + users_df["joinedAt"] = pd.to_datetime( + users_df["joinedAt"], errors="coerce", format="mixed" + ).dt.tz_localize(None) + + events_df = pd.read_csv(events) + events_df["start_time"] = pd.to_datetime( + events_df["start_time"], errors="coerce", format="mixed" + ).dt.tz_localize(None) + + train = os.path.join(path, "train.csv") + event_interest_df = pd.read_csv(train) + event_interest_df["timestamp"] = pd.to_datetime( + event_interest_df["timestamp"], format="mixed" + ).dt.tz_localize(None) + + if not os.path.exists(os.path.join(path, "user_friends_flattened.csv")): + user_friends_df = pd.read_csv(user_friends) + user_friends_df = ( + user_friends_df.set_index("user")["friends"] + .str.split(expand=True) + .stack() + .reset_index() + ) + user_friends_df.columns = ["user", "index", "friend"] + user_friends_flattened_df = user_friends_df.drop("index", axis=1).assign( + user=lambda df: df["user"].astype(int), + friend=lambda df: df["friend"].astype(int), + ) + + # Some friends are not present in the user table, so we drop those friends + # in the user_friends table + user_friends_flattened_df = user_friends_flattened_df.merge( + users_df, how="inner", left_on="friend", right_on="user_id" + ) + user_friends_flattened_df = user_friends_flattened_df[["user", "friend"]] + user_friends_flattened_df.to_csv( + os.path.join(path, "user_friends_flattened.csv") + ) + else: + user_friends_flattened_df = pd.read_csv( + os.path.join(path, "user_friends_flattened.csv") + ) + + if not os.path.exists(os.path.join(path, "event_attendees_flattened.csv")): + event_attendees_df = pd.read_csv(event_attendees) + melted_df = event_attendees_df.melt( + id_vars=["event"], + value_vars=["yes", "maybe", "invited", "no"], + var_name="status", + value_name="user_ids", + ) + melted_df = melted_df.dropna() + melted_df["user_ids"] = melted_df["user_ids"].str.split() + melted_df["user_ids"] = melted_df["user_ids"].apply( + lambda x: [int(i) for i in x] + ) + exploded_df = melted_df.explode("user_ids") + exploded_df["user_ids"] = exploded_df["user_ids"].astype(int) + exploded_df.rename(columns={"user_ids": "user_id"}, inplace=True) + exploded_df = pd.merge( + exploded_df, + events_df[["event_id", "start_time"]], + left_on="event", + right_on="event_id", + how="left", + ) + exploded_df = exploded_df.drop("event_id", axis=1) + event_attendees_flattened_df = exploded_df.dropna(subset=["user_id"]) + event_attendees_flattened_df.to_csv( + os.path.join(path, "event_attendees_flattened.csv") + ) + else: + event_attendees_flattened_df = pd.read_csv( + os.path.join(path, "event_attendees_flattened.csv") + ) + event_attendees_flattened_df["start_time"] = pd.to_datetime( + event_attendees_flattened_df["start_time"], + errors="coerce", + format="mixed", + ) + event_attendees_flattened_df["start_time"] = ( + event_attendees_flattened_df["start_time"] + .dt.tz_localize(None) + .apply(pd.Timestamp) + ) + event_attendees_flattened_df = event_attendees_flattened_df.dropna( + subset=["user_id"] + ) + + return Database( + table_dict={ + "users": Table( + df=users_df, + fkey_col_to_pkey_table={}, + pkey_col="user_id", + time_col="joinedAt", + ), + "events": Table( + df=events_df, + fkey_col_to_pkey_table={"user_id": "users"}, + pkey_col="event_id", + time_col="start_time", + ), + "event_attendees": Table( + df=event_attendees_flattened_df, + fkey_col_to_pkey_table={ + "event": "events", + "user_id": "users", + }, + time_col="start_time", + ), + "event_interest": Table( + df=event_interest_df, + fkey_col_to_pkey_table={ + "event": "events", + "user": "users", + }, + time_col="timestamp", + ), + "user_friends": Table( + df=user_friends_flattened_df, + fkey_col_to_pkey_table={ + "user": "users", + "friend": "users", + }, + ), + } + ) diff --git a/plexe/relbench/datasets/f1.py b/plexe/relbench/datasets/f1.py new file mode 100644 index 00000000..797b8cd9 --- /dev/null +++ b/plexe/relbench/datasets/f1.py @@ -0,0 +1,238 @@ +import os + +import numpy as np +import pandas as pd +import pooch + +from relbench.base import Database, Dataset, Table +from relbench.utils import unzip_processor + + +class F1Dataset(Dataset): + val_timestamp = pd.Timestamp("2005-01-01") + test_timestamp = pd.Timestamp("2010-01-01") + + def make_db(self) -> Database: + r"""Process the raw files into a database.""" + url = "https://relbench.stanford.edu/data/relbench-f1-raw.zip" + + path = pooch.retrieve( + url, + known_hash="2933348953b30aa9723b4831fea8071b336b74977bbcf1fb059da63a04f06eba", + progressbar=True, + processor=unzip_processor, + ) + + path = os.path.join(path, "raw") + + circuits = pd.read_csv(os.path.join(path, "circuits.csv")) + drivers = pd.read_csv(os.path.join(path, "drivers.csv")) + results = pd.read_csv(os.path.join(path, "results.csv")) + races = pd.read_csv(os.path.join(path, "races.csv")) + standings = pd.read_csv(os.path.join(path, "driver_standings.csv")) + constructors = pd.read_csv(os.path.join(path, "constructors.csv")) + constructor_results = pd.read_csv(os.path.join(path, "constructor_results.csv")) + constructor_standings = pd.read_csv( + os.path.join(path, "constructor_standings.csv") + ) + qualifying = pd.read_csv(os.path.join(path, "qualifying.csv")) + + # Remove columns that are irrelevant, leak time, + # or have too many missing values + + # Drop the Wikipedia URL and some time columns with many missing values + races.drop( + columns=[ + "url", + "fp1_date", + "fp1_time", + "fp2_date", + "fp2_time", + "fp3_date", + "fp3_time", + "quali_date", + "quali_time", + "sprint_date", + "sprint_time", + ], + inplace=True, + ) + + # Drop the Wikipedia URL as it is unique for each row + circuits.drop( + columns=["url"], + inplace=True, + ) + + # Drop the Wikipedia URL (unique) and number (803 / 857 are nulls) + drivers.drop( + columns=["number", "url"], + inplace=True, + ) + + # Drop the positionText, time, fastestLapTime and fastestLapSpeed + results.drop( + columns=[ + "positionText", + "time", + "fastestLapTime", + "fastestLapSpeed", + ], + inplace=True, + ) + + # Drop the positionText + standings.drop( + columns=["positionText"], + inplace=True, + ) + + # Drop the Wikipedia URL + constructors.drop( + columns=["url"], + inplace=True, + ) + + # Drop the positionText + constructor_standings.drop( + columns=["positionText"], + inplace=True, + ) + + # Drop the status as it only contains two categories, and + # only 17 rows have value 'D' (0.138%) + constructor_results.drop( + columns=["status"], + inplace=True, + ) + + # Drop the time in qualifying 1, 2, and 3 + qualifying.drop( + columns=["q1", "q2", "q3"], + inplace=True, + ) + + # replase missing data and combine date and time columns + races["time"] = races["time"].replace(r"^\\N$", "00:00:00", regex=True) + races["date"] = races["date"] + " " + races["time"] + # Convert date column to pd.Timestamp + races["date"] = pd.to_datetime(races["date"]) + + # add time column to other tables + results = results.merge(races[["raceId", "date"]], on="raceId", how="left") + standings = standings.merge(races[["raceId", "date"]], on="raceId", how="left") + constructor_results = constructor_results.merge( + races[["raceId", "date"]], on="raceId", how="left" + ) + constructor_standings = constructor_standings.merge( + races[["raceId", "date"]], on="raceId", how="left" + ) + + qualifying = qualifying.merge( + races[["raceId", "date"]], on="raceId", how="left" + ) + + # Subtract a day from the date to account for the fact + # that the qualifying time is the day before the main race + qualifying["date"] = qualifying["date"] - pd.Timedelta(days=1) + + # Replace "\N" with NaN in results tables + results = results.replace(r"^\\N$", np.nan, regex=True) + + # Replace "\N" with NaN in circuits tables, especially + # for the column `alt` which has 3 rows of "\N" + circuits = circuits.replace(r"^\\N$", np.nan, regex=True) + # Convert alt from string to float + circuits["alt"] = circuits["alt"].astype(float) + + # Convert non-numeric values to NaN in the specified column + results["rank"] = pd.to_numeric(results["rank"], errors="coerce") + results["number"] = pd.to_numeric(results["number"], errors="coerce") + results["grid"] = pd.to_numeric(results["grid"], errors="coerce") + results["position"] = pd.to_numeric(results["position"], errors="coerce") + results["points"] = pd.to_numeric(results["points"], errors="coerce") + results["laps"] = pd.to_numeric(results["laps"], errors="coerce") + results["milliseconds"] = pd.to_numeric( + results["milliseconds"], errors="coerce" + ) + results["fastestLap"] = pd.to_numeric(results["fastestLap"], errors="coerce") + + # Convert drivers date of birth to datetime + drivers["dob"] = pd.to_datetime(drivers["dob"]) + + tables = {} + + tables["races"] = Table( + df=pd.DataFrame(races), + fkey_col_to_pkey_table={ + "circuitId": "circuits", + }, + pkey_col="raceId", + time_col="date", + ) + + tables["circuits"] = Table( + df=pd.DataFrame(circuits), + fkey_col_to_pkey_table={}, + pkey_col="circuitId", + time_col=None, + ) + + tables["drivers"] = Table( + df=pd.DataFrame(drivers), + fkey_col_to_pkey_table={}, + pkey_col="driverId", + time_col=None, + ) + + tables["results"] = Table( + df=pd.DataFrame(results), + fkey_col_to_pkey_table={ + "raceId": "races", + "driverId": "drivers", + "constructorId": "constructors", + }, + pkey_col="resultId", + time_col="date", + ) + + tables["standings"] = Table( + df=pd.DataFrame(standings), + fkey_col_to_pkey_table={"raceId": "races", "driverId": "drivers"}, + pkey_col="driverStandingsId", + time_col="date", + ) + + tables["constructors"] = Table( + df=pd.DataFrame(constructors), + fkey_col_to_pkey_table={}, + pkey_col="constructorId", + time_col=None, + ) + + tables["constructor_results"] = Table( + df=pd.DataFrame(constructor_results), + fkey_col_to_pkey_table={"raceId": "races", "constructorId": "constructors"}, + pkey_col="constructorResultsId", + time_col="date", + ) + + tables["constructor_standings"] = Table( + df=pd.DataFrame(constructor_standings), + fkey_col_to_pkey_table={"raceId": "races", "constructorId": "constructors"}, + pkey_col="constructorStandingsId", + time_col="date", + ) + + tables["qualifying"] = Table( + df=pd.DataFrame(qualifying), + fkey_col_to_pkey_table={ + "raceId": "races", + "driverId": "drivers", + "constructorId": "constructors", + }, + pkey_col="qualifyId", + time_col="date", + ) + + return Database(tables) diff --git a/plexe/relbench/datasets/fake.py b/plexe/relbench/datasets/fake.py new file mode 100644 index 00000000..a587e437 --- /dev/null +++ b/plexe/relbench/datasets/fake.py @@ -0,0 +1,114 @@ +import random +import string + +import numpy as np +import pandas as pd + +from relbench.base import Database, Dataset, Table + + +def _generate_random_string(min_length: int, max_length: int) -> str: + length = random.randint(min_length, max_length) + random_string = "".join(random.choice(string.ascii_letters) for _ in range(length)) + return random_string + + +class FakeDataset(Dataset): + def __init__( + self, + num_products: int = 30, + num_customers: int = 100, + num_reviews: int = 600, + num_relations: int = 20, + ): + self.num_products = num_products + self.num_customers = num_customers + self.num_reviews = num_reviews + self.num_relations = num_relations + + min_timestamp = pd.Timestamp(0, unit="D") + max_timestamp = pd.Timestamp(2 * (num_reviews - 1), unit="D") + self.val_timestamp = min_timestamp + 0.8 * (max_timestamp - min_timestamp) + self.test_timestamp = min_timestamp + 0.9 * (max_timestamp - min_timestamp) + super().__init__() + + def make_db(self) -> Database: + num_products = self.num_products + num_customers = self.num_customers + num_reviews = self.num_reviews + num_relations = self.num_relations + product_df = pd.DataFrame( + { + "product_id": [f"product_id_{i}" for i in range(num_products)], + "category": [None, [], ["toy", "health"]] * (num_products // 3), + "title": [_generate_random_string(5, 15) for _ in range(num_products)], + "price": np.random.rand(num_products) * 10, + } + ) + customer_df = pd.DataFrame( + { + "customer_id": [f"customer_id_{i}" for i in range(num_customers)], + "age": np.random.randint(10, 50, size=(num_customers,)), + "gender": ["male", "female"] * (num_customers // 2), + } + ) + # Add some dangling foreign keys: + review_df = pd.DataFrame( + { + "customer_id": [ + f"customer_id_{random.randint(0, num_customers+5)}" + for _ in range(num_reviews) + ], + "product_id": [ + f"product_id_{random.randint(0, num_products-1)}" + for _ in range(num_reviews) + ], + "review_time": pd.to_datetime(2 * np.arange(num_reviews), unit="D"), + "rating": np.random.randint(1, 6, size=(num_reviews,)), + } + ) + review_df["review"] = review_df["rating"].apply( + lambda x: "positive" if x > 3 else "negative" + ) + relations_df = pd.DataFrame( + { + "customer_id": [ + f"customer_id_{random.randint(0, num_customers+5)}" + for _ in range(num_relations) + ], + "product_id": [ + f"product_id_{random.randint(0, num_products-1)}" + for _ in range(num_relations) + ], + } + ) + + return Database( + table_dict={ + "product": Table( + df=product_df, + fkey_col_to_pkey_table={}, + pkey_col="product_id", + ), + "customer": Table( + df=customer_df, + fkey_col_to_pkey_table={}, + pkey_col="customer_id", + ), + "review": Table( + df=review_df, + fkey_col_to_pkey_table={ + "customer_id": "customer", + "product_id": "product", + }, + time_col="review_time", + ), + "relations": Table( + df=relations_df, + fkey_col_to_pkey_table={ + "customer_id": "customer", + "product_id": "product", + }, + ), + } + ) diff --git a/plexe/relbench/datasets/hm.py b/plexe/relbench/datasets/hm.py new file mode 100644 index 00000000..3d35ddce --- /dev/null +++ b/plexe/relbench/datasets/hm.py @@ -0,0 +1,70 @@ +import os +import shutil +from pathlib import Path + +import pandas as pd + +from relbench.base import Database, Dataset, Table + + +class HMDataset(Dataset): + url = ( + "https://www.kaggle.com/competitions/" + "h-and-m-personalized-fashion-recommendations" + ) + + val_timestamp = pd.Timestamp("2020-09-07") + test_timestamp = pd.Timestamp("2020-09-14") + + def make_db(self) -> Database: + path = os.path.join("data", "hm-recommendation") + zip = os.path.join(path, "h-and-m-personalized-fashion-recommendations.zip") + customers = os.path.join(path, "customers.csv") + articles = os.path.join(path, "articles.csv") + transactions = os.path.join(path, "transactions_train.csv") + if not os.path.exists(customers): + if not os.path.exists(zip): + raise RuntimeError( + f"Dataset not found. Please download " + f"h-and-m-personalized-fashion-recommendations.zip from " + f"'{self.url}' and move it to '{path}'. Once you have your" + f"Kaggle API key, you can use the following command: " + f"kaggle competitions download -c h-and-m-personalized-fashion-recommendations" + ) + else: + print("Unpacking") + shutil.unpack_archive(zip, Path(zip).parent) + + articles_df = pd.read_csv(articles) + customers_df = pd.read_csv(customers) + transactions_df = pd.read_csv(transactions) + transactions_df["t_dat"] = pd.to_datetime( + transactions_df["t_dat"], format="%Y-%m-%d" + ) + + db = Database( + table_dict={ + "article": Table( + df=articles_df, + fkey_col_to_pkey_table={}, + pkey_col="article_id", + ), + "customer": Table( + df=customers_df, + fkey_col_to_pkey_table={}, + pkey_col="customer_id", + ), + "transactions": Table( + df=transactions_df, + fkey_col_to_pkey_table={ + "customer_id": "customer", + "article_id": "article", + }, + time_col="t_dat", + ), + } + ) + + db = db.from_(pd.Timestamp("2019-09-07")) + + return db diff --git a/plexe/relbench/datasets/mimic.py b/plexe/relbench/datasets/mimic.py new file mode 100644 index 00000000..d89f96eb --- /dev/null +++ b/plexe/relbench/datasets/mimic.py @@ -0,0 +1,591 @@ +import os +import time +from pathlib import Path + +import pandas as pd + +from relbench.base import Database, Dataset, Table + + +def verify_mimic_access() -> None: + """Verify that the user has proper access to MIMIC-IV dataset through PhysioNet + credentialing. + + Verification is done by attempting a small query to the dataset. + """ + print("Verifying MIMIC-IV access...") + try: + from google.cloud import bigquery + + table_id = "physionet-data.mimiciv_3_1_hosp.patients" + project = os.getenv("PROJECT_ID") + client = bigquery.Client(project=project) + client.get_table(table_id) + client.query("SELECT 1").result() + print("MIMIC-IV access verified.") + except Exception as e: + raise RuntimeError( + f"\nACCESS FAILED - BigQuery credential check encountered an error: {e}" + ) + + +def find_time_col(columns): + for col in [ + "admittime", + "startdate", + "chartdate", + "transfertime", + "charttime", + "intime", + "starttime", + ]: + if col in columns: + return col + return None + + +def format_ids(series: pd.Series) -> list: + return list(map(int, series.dropna().unique())) + + +def convert_dtypes(df: pd.DataFrame) -> pd.DataFrame: + # Create a mapping for common extension dtypes + dtype_mapping = { + "Int64": int, + "Int32": int, + "Float64": float, + "boolean": bool, + "object": str, + # 'string': 'object' + } + + # Apply to all columns that have extension dtypes + converted_dtypes = {} + for col in df.columns: + original_dtype = str(df[col].dtype) + if original_dtype in dtype_mapping: + # we need to fill NA for number conversion.. + if dtype_mapping[original_dtype] in (int, float, complex): + df[col] = df[col].fillna(0) + converted_dtypes[col] = dtype_mapping[original_dtype] + elif ( + original_dtype.startswith("datetime") + or "date" in col.lower() + or "time" in col.lower() + ): + try: + df[col] = pd.to_datetime(df[col], errors="coerce") + except Exception: + print("WARNING ") + pass + + return df.astype(converted_dtypes) + + +def filter_chartevents(table): + print("Filtering chartevents to only include numeric values") + chart_df = table.df + + numeric_mask = chart_df["valuenum"].notnull() & ( + chart_df["value"].astype(str) == chart_df["valuenum"].astype(str) + ) + chartevents_numeric = chart_df[numeric_mask].copy() + chartevents_numeric = chartevents_numeric.drop(columns=["value"]) + chartevents_numeric["valuenum"] = pd.to_numeric( + chartevents_numeric["valuenum"], errors="coerce" + ) + return Table( + df=chartevents_numeric, + fkey_col_to_pkey_table=table.fkey_col_to_pkey_table, + pkey_col=table.pkey_col, + time_col=table.time_col, + ) + + +class MimicDataset(Dataset): + """A dataset class for loading and processing MIMIC-IV data into a format suitable + for use with RelBench. This class extracts a subset of tables specified in + `tables_limit`, filters the data based on ICU stay and patient criteria, and allows + optional column dropouts to reduce dimensionality or remove irrelevant fields. + + The dataset is anchored around ICU stays (`icustays`) and patients (`patients`) and constructs all other + tables with respect to these entities. + + If certain parameters are not provided, default values will be used. + + Parameters: + project_id (str): Google Cloud project ID for BigQuery. + patients_limit (int): Maximum number of patients to include in the dataset (0 means no limit; defaults to 20 000 if not specified). + saving_data (bool): Whether to persist processed tables to disk as .H5 files (default: True). + out_path (str): Output directory to save HDF5 files (default: "data"). + cache_dir (str): Directory used for caching dataset. + tables_limit (list): List of table names to include in the dataset (default: common MIMIC-IV tables). + drop_columns_per_table (dict): Dictionary specifying columns to drop per table (default: predefined subset per table). + min_age (int): Minimum patient age in years to include (default: 15). + min_dur (int): Minimum ICU stay duration in hours (default: 36). + max_dur (int): Maximum ICU stay duration in hours (default: 240). + location (str): Location for BigQuery client (default: 'US'). + dataset_name (str): Name of the BigQuery dataset (default: 'physionet-data'). + + Example: + drop_columns_per_table = { + "admissions": [...], + "chartevents": [...], + ... + } + tables_limit = ["patients", "admissions", "icustays", "chartevents", "procedureevents", "d_items"] + + dataset = MimicDataset( + patients_limit=20 000, + out_path='/data', + cache_dir='/cache', + tables_limit=tables_limit, + db_params=db_params, + drop_columns_per_table=drop_columns_per_table + ) + db = dataset.make_db() + """ + + def __init__( + self, + project_id: str = None, + patients_limit: int = -1, + saving_data: bool = True, + out_path: str = "data", + cache_dir: str = None, + tables_limit: list = None, + drop_columns_per_table=None, + min_age: int = 15, + min_dur: int = 36, + max_dur: int = 240, + location: str = "US", + dataset_name: str = "physionet-data", + ): + # Lazy import to avoid requiring google-cloud-bigquery for other datasets + from google.cloud import bigquery + + super().__init__(cache_dir=cache_dir) + + # Load environment variables from .env file (lazy import for optional dependency) + try: + from dotenv import load_dotenv + + load_dotenv() + except ImportError: + # dotenv is optional - if not available, env vars can still be set manually + pass + + # Use environment variable if project_id not provided + if project_id is None: + try: + project_id = os.getenv("PROJECT_ID") + except: + raise ValueError( + "project_id is required: set MIMIC_BQ_PROJECT_ID environment variable (i.e. export MIMIC_BQ_PROJECT_ID='your-project_id')" + ) + + if drop_columns_per_table is None: + print(f"drop_columns_per_table not provided, dropping default.") + drop_columns_per_table = { + "admissions": [ + "admittime", + "dischtime", + "deathtime", + "edouttime", + "edregtime", + "hospital_expire_flag", + "discharge_location", + "race", + ], + "chartevents": ["storetime"], + "procedureevents": [ + "storetime", + "endtime", + "location", + "location_category", + "location", + "locationcategory", + "linkorderid", + "originalamount", + "originalrate", + ], + "d_items": ["abbreviation"], + } + + if tables_limit is None: + print(f"tables_limit not provided setting to default.") + tables_limit = [ + "patients", + "admissions", + "icustays", + "chartevents", + "procedureevents", + "d_items", + ] + + if patients_limit == -1: + patients_limit = 20000 + print(f"patients_limit not provided setting to default {patients_limit}.") + + self.query_args = [ + bigquery.ScalarQueryParameter("limit", "INT64", patients_limit), + bigquery.ScalarQueryParameter("min_age", "INT64", min_age), + bigquery.ScalarQueryParameter("min_dur", "INT64", min_dur), + bigquery.ScalarQueryParameter("max_dur", "INT64", max_dur), + bigquery.ScalarQueryParameter("min_day", "FLOAT64", float(min_dur) / 24), + ] + + self.saving_data = saving_data + self.patients_limit = patients_limit + self.drop_columns_per_table = drop_columns_per_table + + self.tables_limit = tables_limit + + # If a cached RelBench copy exists (e.g., downloaded db.zip), reuse it and + # avoid hitting BigQuery. + cached_db_dir = Path(cache_dir) / "db" if cache_dir is not None else None + if cached_db_dir and cached_db_dir.exists() and any(cached_db_dir.iterdir()): + print( + f"Found cached MIMIC database at {cached_db_dir}, skipping BigQuery build." + ) + cached_db = Database.load(cached_db_dir) + self._set_timestamps_from_icustays(cached_db.table_dict["icustays"].df) + return + + # Create the output directory if it doesn't exist + current_dir = os.getcwd() + self.out_path = Path(current_dir) / out_path / f"limit_{patients_limit}" + if saving_data: + self.out_path.mkdir(parents=True, exist_ok=True) + print("Data will be saved to", self.out_path) + + self.client = bigquery.Client(project=project_id, location=location) + self.dataset_name = dataset_name + + # Set the test and validation timestamps + # this will be updated based on patients' ICU admission times + self.test_timestamp = None + self.val_timestamp = None + + print("Making database in __init__....") + self.make_db() + + def _set_timestamps_from_icustays(self, icustays_df: pd.DataFrame) -> None: + timestamps = ( + pd.to_datetime(icustays_df["intime"], errors="coerce") + .dropna() + .sort_values() + ) + if len(timestamps) == 0: + raise ValueError("Unable to set timestamps: icustays.intime is empty.") + + val_idx = int(len(timestamps) * 0.7) + test_idx = int(len(timestamps) * 0.85) + self.val_timestamp = timestamps.iloc[val_idx] + self.test_timestamp = timestamps.iloc[test_idx] + + def make_db(self) -> Database: + from google.cloud import bigquery + + start_time = time.time() + tables_df = {} + # while MIMIC IV dataset on BigQuery does not have primary and foreign keys set up properly (at all) + # we need to declare the relations statically here.. + table_names_schemas = { + "mimiciv_3_1_hosp": [["patients"], ["admissions"]], + "mimiciv_3_1_icu": [ + ["icustays"], + ["procedureevents"], + ["d_items"], + ["chartevents"], + ], + } + table_key_map = { + "patients": {"pkey_col": "subject_id", "fkey_col_to_pkey_table": {}}, + "icustays": { + "pkey_col": "stay_id", + "fkey_col_to_pkey_table": { + "hadm_id": "admissions", + "subject_id": "patients", + }, + }, + "admissions": { + "pkey_col": "hadm_id", + "fkey_col_to_pkey_table": {"subject_id": "patients"}, + }, + "procedureevents": { + "pkey_col": "orderid", + "fkey_col_to_pkey_table": { + "hadm_id": "admissions", + "itemid": "d_items", + "stay_id": "icustays", + "subject_id": "patients", + }, + }, + "d_items": {"pkey_col": "itemid", "fkey_col_to_pkey_table": {}}, + "chartevents": { + "pkey_col": None, + "fkey_col_to_pkey_table": { + "hadm_id": "admissions", + "itemid": "d_items", + "stay_id": "icustays", + "subject_id": "patients", + }, + }, + } + + tables_df["patients"] = Table( + df=self.get_patients(), + fkey_col_to_pkey_table=table_key_map["patients"]["fkey_col_to_pkey_table"], + pkey_col=table_key_map["patients"]["pkey_col"], + time_col=None, + ) + + query_params = [ + bigquery.ArrayQueryParameter( + "subject_ids", + "INT64", + format_ids(tables_df["patients"].df["subject_id"]), + ), + bigquery.ArrayQueryParameter( + "stay_ids", "INT64", format_ids(tables_df["patients"].df["stay_id"]) + ), + bigquery.ArrayQueryParameter( + "hadm_ids", "INT64", format_ids(tables_df["patients"].df["hadm_id"]) + ), + ] + + tables_df["icustays"] = Table( + df=self.get_icustays(query_params), + fkey_col_to_pkey_table=table_key_map["icustays"]["fkey_col_to_pkey_table"], + pkey_col=table_key_map["icustays"]["pkey_col"], + time_col="intime", + ) + query_params = [ + bigquery.ArrayQueryParameter( + "subject_ids", + "INT64", + format_ids(tables_df["icustays"].df["subject_id"]), + ), + bigquery.ArrayQueryParameter( + "stay_ids", "INT64", format_ids(tables_df["icustays"].df["stay_id"]) + ), + bigquery.ArrayQueryParameter( + "hadm_ids", "INT64", format_ids(tables_df["icustays"].df["hadm_id"]) + ), + ] + + for schema, tables in table_names_schemas.items(): + for (table_name,) in tables: + if table_name in {"patients", "icustays"}: + continue + h5_path = self.out_path / f"{table_name}_{self.patients_limit}.H5" + if not h5_path.exists(): + print(f"Creating {table_name}") + + # Create the query string + query_string = self.build_query(table_name, schema) + + print("Querying table:", table_name, end=" ") + # Execute the query + df = self.query( + query_string=query_string, query_params=query_params + ) + print(f"{len(df)} rows") + + # Drop columns if specified + if ( + self.drop_columns_per_table + and table_name in self.drop_columns_per_table + ): + df = self.drop_columns(table_name, df) + + # Save the DataFrame to HDF5 if saving_data is True + if self.saving_data: + df.to_hdf(h5_path, key="table", index=False) + print(f"Table {table_name} saved to {h5_path}") + else: + print( + f"️File {table_name}_{self.patients_limit}.H5 already exists. Skipping..." + ) + df = pd.read_hdf(h5_path, key="table") + + # Create the Table object for the current table + tables_df[table_name] = Table( + df=df, + fkey_col_to_pkey_table=table_key_map[table_name][ + "fkey_col_to_pkey_table" + ], + pkey_col=table_key_map[table_name]["pkey_col"], + time_col=find_time_col(df.columns), + ) + + # Filter chartevents to only include numeric values + tables_df["chartevents"] = filter_chartevents(tables_df["chartevents"]) + + # Change test and val timestamps based on patients limit + print("Setting test and val timestamps based on patients limit") + timestamps = ( + pd.to_datetime(tables_df["icustays"].df["intime"], errors="coerce") + .dropna() + .sort_values() + ) + n = len(timestamps) + + # Calculate the indices for 70% and 85% + # of the total number of timestamps + # 70% for train and 15% for validation and 15% for test + val_idx = int(n * 0.7) + test_idx = int(n * 0.85) + self.val_timestamp = timestamps.iloc[val_idx] + self.test_timestamp = timestamps.iloc[test_idx] + train_count = len(timestamps[timestamps < self.val_timestamp]) + val_count = len( + timestamps[ + (timestamps >= self.val_timestamp) & (timestamps < self.test_timestamp) + ] + ) + test_count = len(timestamps[timestamps >= self.test_timestamp]) + print("test_timestamp:", self.test_timestamp, end=" ") + print("val_timestamp:", self.val_timestamp) + print( + "Record split - Train:", train_count, "Val:", val_count, "Test:", test_count + ) + + end_time = time.time() + print(f"Done loading tables in {end_time - start_time:.2f} seconds") + return Database(tables_df) + + def get_patients(self): + patients_filename = "patients_" + str(self.patients_limit) + ".H5" + # Query the patients + patients_query = f""" + SELECT + i.subject_id, -- Unique patient identifier + i.hadm_id, -- Unique hospital admission ID + i.stay_id, -- Unique ICU stay ID + i.gender, -- Patient gender + ROUND(i.admission_age) AS age, -- Age of the patient at hospital admission + i.race -- Patient race/ethnicity + FROM `{self.dataset_name}.mimiciv_3_1_derived.icustay_detail` i + WHERE i.hadm_id IS NOT NULL + AND i.stay_id IS NOT NULL + AND i.hospstay_seq = 1 + AND i.icustay_seq = 1 + AND i.los_icu IS NOT NULL + AND i.admission_age >= @min_age + AND i.los_icu >= @min_day + AND (UNIX_SECONDS(TIMESTAMP(i.icu_outtime)) - UNIX_SECONDS(TIMESTAMP(i.icu_intime))) > (@min_dur*3600) + AND (UNIX_SECONDS(TIMESTAMP(i.icu_outtime)) - UNIX_SECONDS(TIMESTAMP(i.icu_intime))) < (@max_dur*3600) + AND EXISTS ( + SELECT 1 + FROM `{self.dataset_name}.mimiciv_3_1_icu.icustays` icu + WHERE icu.stay_id = i.stay_id + ) + QUALIFY + ROW_NUMBER() OVER (PARTITION BY i.subject_id ORDER BY i.icustay_seq DESC) = 1 + ORDER BY subject_id + """ + + if self.patients_limit > 0: + patients_query += "LIMIT @limit" + + H5_fpath = os.path.join(self.out_path, patients_filename) + if not os.path.exists(H5_fpath): + patients = self.query( + query_string=patients_query, query_params=self.query_args + ) + if self.saving_data: + patients.to_hdf(H5_fpath, key="patients", index=False) + print(f"Patients data saved to {H5_fpath}") + else: + print(f"File {patients_filename} already exists. Skipping...") + patients = pd.read_hdf(H5_fpath, key="patients") + return patients + + def get_icustays(self, params: list): + icustays_filename = "icustays_" + str(self.patients_limit) + ".H5" + H5_fpath = os.path.join(self.out_path, icustays_filename) + # Query the ICU_Stay + icustays_query = f""" + SELECT icu.subject_id, + icu.hadm_id, + icu.stay_id, + icu.intime, + icu.first_careunit, + icu_detail.los_icu + FROM `{self.dataset_name}.mimiciv_3_1_icu.icustays` AS icu + LEFT JOIN `{self.dataset_name}.mimiciv_3_1_derived.icustay_detail` AS icu_detail + ON icu.stay_id = icu_detail.stay_id + WHERE icu.subject_id IN UNNEST(@subject_ids) + AND icu.stay_id IN UNNEST(@stay_ids) + AND icu.hadm_id IN UNNEST(@hadm_ids) + AND icu_detail.los_icu IS NOT NULL + ORDER BY icu.subject_id + """ + if not os.path.exists(H5_fpath): + icustays = self.query(query_string=icustays_query, query_params=params) + icustays["los_icu"] = pd.to_numeric(icustays["los_icu"], errors="coerce") + if self.saving_data: + icustays.to_hdf(H5_fpath, key="icustays", index=False) + print(f"ICUStays data saved to {H5_fpath}") + else: + print(f"File {icustays_filename} already exists. Skipping...") + icustays = pd.read_hdf(H5_fpath, key="icustays") + + return icustays + + def build_query(self, table_name, schema): + columns = self.get_columns(table_name, schema) + conditions = [] + if "subject_id" in columns: + conditions.append("subject_id IN UNNEST(@subject_ids)") + if "stay_id" in columns: + conditions.append("stay_id IN UNNEST(@stay_ids)") + if "hadm_id" in columns: + conditions.append("hadm_id IN UNNEST(@hadm_ids)") + + if conditions: + where_clause = " WHERE " + " AND ".join(conditions) + else: + where_clause = "" + + query_string = ( + f"SELECT * FROM `{self.dataset_name}.{schema}.{table_name}`{where_clause};" + ) + return query_string + + def drop_columns(self, table_name, df): + drop_cols = list( + set(self.drop_columns_per_table[table_name]) & set(df.columns) + ) # intersection + if drop_cols: + df = df.drop(columns=drop_cols) + print(f"Dropped columns from {table_name}: {drop_cols}") + return df + + def get_columns(self, table_name, schema): + table_id = f"{self.dataset_name}.{schema}.{table_name}" + table = self.client.get_table(table_id) + + # Extract column names from the schema + column_names = [field.name for field in table.schema] + return column_names + + def query(self, query_string, query_params: list = []): + from google.cloud import bigquery + + job_config = bigquery.QueryJobConfig(query_parameters=query_params) + df = self.client.query_and_wait( + query_string, job_config=job_config + ).to_dataframe() + # for writing HDF5 files, we need simple types + + return convert_dtypes(df) + + +if __name__ == "__main__": + dataset = MimicDataset() + db = dataset.make_db() + mimic_db = dataset.get_db() + print(mimic_db) diff --git a/plexe/relbench/datasets/ratebeer.py b/plexe/relbench/datasets/ratebeer.py new file mode 100644 index 00000000..4efbe690 --- /dev/null +++ b/plexe/relbench/datasets/ratebeer.py @@ -0,0 +1,337 @@ +import os +import zipfile +from typing import Dict, List, Optional, Union + +import numpy as np +import pandas as pd +import pooch +from tqdm import tqdm + +from relbench.base import Database, Dataset, Table +from relbench.utils import unzip_processor + +# Update URL to Dropbox direct download link +DB_URL = "https://www.dropbox.com/scl/fi/exwygxep7vdvq55uiq28r/db.zip?rlkey=o7q0r8nw758p4wxx1wka9ubuj&st=rg3gvkxg&dl=1" + + +class RateBeerDataset(Dataset): + val_timestamp = pd.Timestamp("2018-09-01") + test_timestamp = pd.Timestamp("2020-01-01") + + name = "rel-ratebeer" + + def _process_timestamps( + self, df: pd.DataFrame, table_name: str, time_col: Optional[str] = None + ) -> pd.DataFrame: + """Convert timestamp columns to datetime and remove rows with NaT in the + designated time column.""" + # Convert timestamp columns + for col in ["created_at", "updated_at", "last_edited_at", "opened_at"]: + if col in df.columns: + df[col] = pd.to_datetime(df[col], format="mixed", errors="coerce") + + # Remove rows with NaT in the designated time_col + if time_col is not None: + if time_col in df.columns and df[time_col].isna().any(): + initial_rows = len(df) + nat_count = df[time_col].isna().sum() + print( + f"\nWarning: Found {nat_count} NaT value(s) in time column '{time_col}' for table '{table_name}'. Removing these rows." + ) + df = df.dropna(subset=[time_col]) + print( + f"Removed {initial_rows - len(df)} rows from {table_name}. New shape: {df.shape}" + ) + + return df + + def make_db(self) -> Database: + r"""Process the raw files into a database.""" + path = pooch.retrieve( + DB_URL, + known_hash="c3921164da60f8c97e6530d1f2872f7e0d307f8276348106db95c10c2df677ad", + progressbar=True, + processor=unzip_processor, + ) + + print("Reading from processed database...") + tables = {} + + beers = pd.read_csv(os.path.join(path, "db", f"beers.csv"), low_memory=False) + brewers = pd.read_csv( + os.path.join(path, "db", f"brewers.csv"), low_memory=False + ) + beer_styles = pd.read_csv( + os.path.join(path, "db", f"beer_styles.csv"), low_memory=False + ) + countries = pd.read_csv( + os.path.join(path, "db", f"countries.csv"), low_memory=False + ) + states = pd.read_csv(os.path.join(path, "db", f"states.csv"), low_memory=False) + users = pd.read_csv(os.path.join(path, "db", f"users.csv"), low_memory=False) + beer_ratings = pd.read_csv( + os.path.join(path, "db", f"beer_ratings.csv"), low_memory=False + ) + beer_upcs = pd.read_csv( + os.path.join(path, "db", f"beer_upcs.csv"), low_memory=False + ) + availability = pd.read_csv( + os.path.join(path, "db", f"availability.csv"), low_memory=False + ) + favorites = pd.read_csv( + os.path.join(path, "db", f"favorites.csv"), low_memory=False + ) + place_ratings = pd.read_csv( + os.path.join(path, "db", f"place_ratings.csv"), low_memory=False + ) + places = pd.read_csv(os.path.join(path, "db", f"places.csv"), low_memory=False) + place_types = pd.read_csv( + os.path.join(path, "db", f"place_types.csv"), low_memory=False + ) + + # ---------------------- Beers ---------------------- + beers = self._process_timestamps(beers, "beers", "created_at") + + beers.drop( + columns=[ + "contract_brewer_id", # 96.27% NA + "contract_note", # 99.96% NA + "featured_beer_id", # 100% NA + "producer_style", # 100% NA + "LogoImage", # 92.45% NA + "beer_jobber_id", # 99.65% NA + ], + inplace=True, + ) + + tables["beers"] = Table( + df=beers, + fkey_col_to_pkey_table={ + "brewer_id": "brewers", + "style_id": "beer_styles", + }, + pkey_col="beer_id", + time_col="created_at", + ) + + # ---------------------- Brewers ---------------------- + brewers.drop( + columns=[ + "newsletter_email", # 99.85% NA + "head_brewer", # 100% NA + "latitude", # 100% NA + "longitude", # 100% NA + "msa", # 83.42% NA + "instagram", # 95.55% NA + ], + inplace=True, + ) + + tables["brewers"] = Table( + df=brewers, + fkey_col_to_pkey_table={ + "country_id": "countries", + "state_id": "states", + "type_id": "place_types", + }, + pkey_col="brewer_id", + ) + + # ---------------------- Beer Styles ---------------------- + tables["beer_styles"] = Table( + df=beer_styles, + fkey_col_to_pkey_table={}, + pkey_col="style_id", + ) + + # ---------------------- Countries ---------------------- + tables["countries"] = Table( + df=countries, + fkey_col_to_pkey_table={}, + pkey_col="country_id", + ) + + # ---------------------- Users ---------------------- + users = self._process_timestamps(users, "users", "created_at") + + users.drop( + columns=[ + "favorite_first_added", # 98.44% NA + "favorite_last_added", # 98.44% NA + ], + inplace=True, + ) + + tables["users"] = Table( + df=users, + fkey_col_to_pkey_table={}, + pkey_col="user_id", + time_col="created_at", + ) + + # ---------------------- Beer Ratings ---------------------- + beer_ratings = self._process_timestamps( + beer_ratings, "beer_ratings", "created_at" + ) + + # Fix duplicate rating_id (rating_id = 1759935) + duplicate_mask = beer_ratings.duplicated(subset=["rating_id"], keep="first") + if duplicate_mask.any(): + print(f"Found {duplicate_mask.sum()} duplicate rating_id(s), fixing...") + max_rating_id = beer_ratings["rating_id"].max() + beer_ratings.loc[duplicate_mask, "rating_id"] += max_rating_id + 1 + + beer_ratings.drop( + columns=[ + "served_in", # 99.94% NA + "latitude", # 100% NA + "longitude", # 100% NA + ], + inplace=True, + ) + + tables["beer_ratings"] = Table( + df=beer_ratings, + fkey_col_to_pkey_table={ + "user_id": "users", + "beer_id": "beers", + "availability_id": "availability", + }, + pkey_col="rating_id", + time_col="created_at", + ) + + # ---------------------- Availability ---------------------- + availability = self._process_timestamps( + availability, "availability", time_col=None + ) + + availability.drop( + columns=[ + "area_code", # 100% NA + "rating_id", # 100% NA + "tap_lister", # 100% NA + ], + inplace=True, + ) + + tables["availability"] = Table( + df=availability, + fkey_col_to_pkey_table={ + "beer_id": "beers", + "place_id": "places", + "country_id": "countries", + "user_id": "users", + }, + pkey_col="avail_id", + ) + + # ---------------------- Beer UPCs ---------------------- + tables["beer_upcs"] = Table( + df=beer_upcs, + fkey_col_to_pkey_table={"beer_id": "beers"}, + pkey_col=None, # Same UPC may map to multiple beers + ) + + # ---------------------- Favorites ---------------------- + favorites = self._process_timestamps(favorites, "favorites", "created_at") + + tables["favorites"] = Table( + df=favorites, + fkey_col_to_pkey_table={ + "user_id": "users", + "beer_id": "beers", + }, + pkey_col="favorite_id", + time_col="created_at", + ) + + # ---------------------- Places ---------------------- + places.drop( + columns=[ + "email", # 100% NA + "opened_at", # 100% NA + "phone_country_code", # 100% NA + "last_edited_at", # 99.98% NA + # "score", # 86.23% NA + ], + inplace=True, + ) + + tables["places"] = Table( + df=places, + fkey_col_to_pkey_table={ + "state_id": "states", + "type_id": "place_types", + "country_id": "countries", + }, + pkey_col="place_id", + ) + + # ---------------------- Place Ratings ---------------------- + place_ratings = self._process_timestamps( + place_ratings, "place_ratings", "created_at" + ) + + place_ratings.drop( + columns=[ + "latitude", # 100% NA + "longitude", # 100% NA + ], + inplace=True, + ) + + tables["place_ratings"] = Table( + df=place_ratings, + fkey_col_to_pkey_table={ + "place_id": "places", + "user_id": "users", + }, + pkey_col="rating_id", + time_col="created_at", + ) + + # ---------------------- Place Types ---------------------- + tables["place_types"] = Table( + df=place_types, + fkey_col_to_pkey_table={}, + pkey_col="type_id", + ) + + # ---------------------- States ---------------------- + states.drop( + columns=[ + "Abbrev", # 86.66% NA + # "hasbrewer", # 79.58% NA + ], + inplace=True, + ) + + tables["states"] = Table( + df=states, + fkey_col_to_pkey_table={"country_id": "countries"}, + pkey_col="state_id", + ) + + print("\nAll tables loaded successfully!") + return Database(tables) + + +if __name__ == "__main__": + ratebeer_dataset = RateBeerDataset() + ratebeer_db = ratebeer_dataset.make_db() + + total_rows = 0 + total_cols = 0 + + # Print table statistics + for table_name, table in ratebeer_db.table_dict.items(): + print(f"Number of rows in {table_name} table: {table.df.shape[0]}") + print(f"Sample of {table_name} table:") + print(table.df.head()) + print() + total_rows += table.df.shape[0] + total_cols += table.df.shape[1] + + print(f"Total number of rows: {total_rows}") + print(f"Total number of columns: {total_cols}") diff --git a/plexe/relbench/datasets/salt.py b/plexe/relbench/datasets/salt.py new file mode 100644 index 00000000..2416e131 --- /dev/null +++ b/plexe/relbench/datasets/salt.py @@ -0,0 +1,163 @@ +import os + +import pandas as pd +import pooch +from datasets import load_dataset +from datasets.exceptions import DatasetNotFoundError + +from relbench.base import Database, Dataset, Table + + +class SALTDataset(Dataset): + + val_timestamp = pd.Timestamp("2020-02-01") + test_timestamp = pd.Timestamp("2020-07-01") + + header_target_cols = [ + "SALESOFFICE", + "SALESGROUP", + "CUSTOMERPAYMENTTERMS", + "SHIPPINGCONDITION", + "HEADERINCOTERMSCLASSIFICATION", + ] + item_target_cols = ["PLANT", "SHIPPINGPOINT", "ITEMINCOTERMSCLASSIFICATION"] + all_target_cols = header_target_cols + item_target_cols + + def __init__(self, **kwargs): + + super().__init__(**kwargs) + + def make_db(self) -> Database: + r"""Process the raw files into a database.""" + + try: + _split = "train+test" + salesdocument = load_dataset( + "sap-ai-research/SALT", "salesdocuments", split=_split + ).to_pandas() + salesdocumentitem = load_dataset( + "sap-ai-research/SALT", "salesdocument_items", split=_split + ).to_pandas() + customer = load_dataset( + "sap-ai-research/SALT", "customers", split=_split + ).to_pandas() + address = load_dataset( + "sap-ai-research/SALT", "addresses", split=_split + ).to_pandas() + + # Rename the incoterm columns for clarity + salesdocument = salesdocument.rename( + columns={"INCOTERMSCLASSIFICATION": "HEADERINCOTERMSCLASSIFICATION"} + ) + salesdocumentitem = salesdocumentitem.rename( + columns={"INCOTERMSCLASSIFICATION": "ITEMINCOTERMSCLASSIFICATION"} + ) + + # Ensure we only look at sales order items for which we have the header information as well + salesdocumentitem = salesdocumentitem[ + salesdocumentitem.SALESDOCUMENT.isin(salesdocument.SALESDOCUMENT) + ] + + # Use creation date and time to build the timestamp + salesdocument["CREATIONTIMESTAMP"] = pd.to_datetime( + salesdocument.CREATIONDATE.dt.strftime("%Y%m%d") + + salesdocument.CREATIONTIME.astype(str), + format="%Y%m%d%H:%M:%S", + ) + salesdocument = salesdocument.drop(["CREATIONDATE", "CREATIONTIME"], axis=1) + salesdocument = salesdocument[ + (salesdocument.CREATIONTIMESTAMP >= pd.Timestamp("2018-01-01")) + & (salesdocument.CREATIONTIMESTAMP < pd.Timestamp("2021-01-01")) + ] + + # Add date column to item df as well. The other dfs don't have a timestamp + salesdocumentitem = salesdocumentitem.merge( + salesdocument[["SALESDOCUMENT", "CREATIONTIMESTAMP"]], + on="SALESDOCUMENT", + how="left", + ) + salesdocumentitem = salesdocumentitem[ + (salesdocumentitem.CREATIONTIMESTAMP >= pd.Timestamp("2018-01-01")) + & (salesdocumentitem.CREATIONTIMESTAMP < pd.Timestamp("2021-01-01")) + ] + + # Join the sales document and item IDS to for the primary key of the sales document item table + # This is not necessary to be able to join the tables but it will be necessary for the prediction task + salesdocumentitem["ID"] = ( + salesdocumentitem["SALESDOCUMENT"] + + salesdocumentitem["SALESDOCUMENTITEM"] + ) + + # Also convert the columns which will be used as targets to integers, to avoid modeling issues + + for col in self.header_target_cols: + salesdocument[col], _ = pd.factorize(salesdocument[col]) + for col in self.item_target_cols: + salesdocumentitem[col], _ = pd.factorize(salesdocumentitem[col]) + + # Note: there are currently two customers registered with more than one address in the customer table + # For lack of a better solution atm, remove the customers with duplicate entries + customer = customer[(~customer.CUSTOMER.isin(["1025999907", "5508069095"]))] + + # Make sure to remove additional targets from the sales order and sales order item tables to avoid leakers + + # Drop duplicate columns in the customer and address tables + customer = customer.drop_duplicates() + address = address.drop_duplicates() + + # Drop the ADDRESSREPRESENTATIONCODE column as it is always NaN + address = address.drop(columns=["ADDRESSREPRESENTATIONCODE"]) + + # Drop the "__index_level_0__" column artifacts + customer = customer.drop(columns=["__index_level_0__"]) + salesdocument = salesdocument.drop(columns=["__index_level_0__"]) + salesdocumentitem = salesdocumentitem.drop(columns=["__index_level_0__"]) + address = address.drop(columns=["__index_level_0__"]) + except DatasetNotFoundError: + # Fallback to download from relbench server + paths = pooch.retrieve( + "https://relbench.stanford.edu/download/rel-salt/db.zip", + known_hash="fca91ab7d9e37646dcf1cb0007cc4229e9b23ef3c85f3c9e578d0f3fcb167001", + progressbar=True, + processor=pooch.Unzip(), + ) + + path = os.path.dirname(paths[0]) + salesdocumentitem = pd.read_parquet( + os.path.join(path, "salesdocumentitem.parquet") + ) + salesdocument = pd.read_parquet(os.path.join(path, "salesdocument.parquet")) + customer = pd.read_parquet(os.path.join(path, "customer.parquet")) + address = pd.read_parquet(os.path.join(path, "address.parquet")) + + # Collect all tables in the database as relbench.base.Table objects. + tables = {} + tables["salesdocumentitem"] = Table( + df=salesdocumentitem, + fkey_col_to_pkey_table={ + "SALESDOCUMENT": "salesdocument", + "SOLDTOPARTY": "customer", + "SHIPTOPARTY": "customer", + "BILLTOPARTY": "customer", + "PAYERPARTY": "customer", + }, + pkey_col="ID", # + SALESDOCUMENTITEM + time_col="CREATIONTIMESTAMP", + ) + tables["salesdocument"] = Table( + df=salesdocument, + fkey_col_to_pkey_table={}, + pkey_col="SALESDOCUMENT", + time_col="CREATIONTIMESTAMP", + ) + tables["customer"] = Table( + df=customer, + fkey_col_to_pkey_table={"ADDRESSID": "address"}, + pkey_col="CUSTOMER", + time_col=None, + ) + tables["address"] = Table( + df=address, fkey_col_to_pkey_table={}, pkey_col="ADDRESSID", time_col=None + ) + + return Database(tables) diff --git a/plexe/relbench/datasets/stack.py b/plexe/relbench/datasets/stack.py new file mode 100644 index 00000000..04513170 --- /dev/null +++ b/plexe/relbench/datasets/stack.py @@ -0,0 +1,132 @@ +import os + +import pandas as pd +import pooch + +from relbench.base import Database, Dataset, Table +from relbench.utils import clean_datetime, unzip_processor + + +class StackDataset(Dataset): + # 3 months gap + val_timestamp = pd.Timestamp("2020-10-01") + test_timestamp = pd.Timestamp("2021-01-01") + + def make_db(self) -> Database: + r"""Process the raw files into a database.""" + url = "https://relbench.stanford.edu/data/relbench-forum-raw.zip" + path = pooch.retrieve( + url, + known_hash="ad3bf96f35146d50ef48fa198921685936c49b95c6b67a8a47de53e90036745f", + progressbar=True, + processor=unzip_processor, + ) + path = os.path.join(path, "raw") + users = pd.read_csv(os.path.join(path, "Users.csv")) + comments = pd.read_csv(os.path.join(path, "Comments.csv")) + posts = pd.read_csv(os.path.join(path, "Posts.csv")) + votes = pd.read_csv(os.path.join(path, "Votes.csv")) + postLinks = pd.read_csv(os.path.join(path, "PostLinks.csv")) + badges = pd.read_csv(os.path.join(path, "Badges.csv")) + postHistory = pd.read_csv(os.path.join(path, "PostHistory.csv")) + + # tags = pd.read_csv(os.path.join(path, "Tags.csv")) we remove tag table here since after removing time leakage columns, all information are kept in the posts tags columns + + ## remove time leakage columns + users.drop( + columns=["Reputation", "Views", "UpVotes", "DownVotes", "LastAccessDate"], + inplace=True, + ) + + posts.drop( + columns=[ + "ViewCount", + "AnswerCount", + "CommentCount", + "FavoriteCount", + "CommunityOwnedDate", + "ClosedDate", + "LastEditDate", + "LastActivityDate", + "Score", + "LastEditorDisplayName", + "LastEditorUserId", + ], + inplace=True, + ) + + comments.drop(columns=["Score"], inplace=True) + votes.drop(columns=["BountyAmount"], inplace=True) + + comments = clean_datetime(comments, "CreationDate") + badges = clean_datetime(badges, "Date") + postLinks = clean_datetime(postLinks, "CreationDate") + postHistory = clean_datetime(postHistory, "CreationDate") + votes = clean_datetime(votes, "CreationDate") + users = clean_datetime(users, "CreationDate") + posts = clean_datetime(posts, "CreationDate") + + tables = {} + + tables["comments"] = Table( + df=pd.DataFrame(comments), + fkey_col_to_pkey_table={ + "UserId": "users", + "PostId": "posts", + }, + pkey_col="Id", + time_col="CreationDate", + ) + + tables["badges"] = Table( + df=pd.DataFrame(badges), + fkey_col_to_pkey_table={ + "UserId": "users", + }, + pkey_col="Id", + time_col="Date", + ) + + tables["postLinks"] = Table( + df=pd.DataFrame(postLinks), + fkey_col_to_pkey_table={ + "PostId": "posts", + "RelatedPostId": "posts", ## is this allowed? two foreign keys into the same primary + }, + pkey_col="Id", + time_col="CreationDate", + ) + + tables["postHistory"] = Table( + df=pd.DataFrame(postHistory), + fkey_col_to_pkey_table={"PostId": "posts", "UserId": "users"}, + pkey_col="Id", + time_col="CreationDate", + ) + + tables["votes"] = Table( + df=pd.DataFrame(votes), + fkey_col_to_pkey_table={"PostId": "posts", "UserId": "users"}, + pkey_col="Id", + time_col="CreationDate", + ) + + tables["users"] = Table( + df=pd.DataFrame(users), + fkey_col_to_pkey_table={}, + pkey_col="Id", + time_col="CreationDate", + ) + + tables["posts"] = Table( + df=pd.DataFrame(posts), + fkey_col_to_pkey_table={ + "OwnerUserId": "users", + "ParentId": "posts", # notice the self-reference + "AcceptedAnswerId": "posts", + }, + pkey_col="Id", + time_col="CreationDate", + ) + + return Database(tables) diff --git a/plexe/relbench/datasets/trial.py b/plexe/relbench/datasets/trial.py new file mode 100644 index 00000000..6415c376 --- /dev/null +++ b/plexe/relbench/datasets/trial.py @@ -0,0 +1,369 @@ +import os + +import numpy as np +import pandas as pd +import pooch + +from relbench.base import Database, Dataset, Table +from relbench.utils import unzip_processor + + +class TrialDataset(Dataset): + # 1 year gap + val_timestamp = pd.Timestamp("2020-01-01") + test_timestamp = pd.Timestamp("2021-01-01") + + def make_db(self) -> Database: + r"""Process the raw files into a database.""" + url = "https://relbench.stanford.edu/data/relbench-trial.zip" + path = pooch.retrieve( + url, + known_hash="3f7376b7d901177157b3c5b048221884e936b45d05e809c7875403183ca9e13d", + progressbar=True, + processor=unzip_processor, + ) + path = os.path.join(path, "relbench-trial-raw") + studies = pd.read_csv( + os.path.join(path, "studies.txt"), sep="|", low_memory=False + ) + outcomes = pd.read_csv(os.path.join(path, "outcomes.txt"), sep="|") + drop_withdrawals = pd.read_csv( + os.path.join(path, "drop_withdrawals.txt"), sep="|" + ) + designs = pd.read_csv(os.path.join(path, "designs.txt"), sep="|") + eligibilities = pd.read_csv(os.path.join(path, "eligibilities.txt"), sep="|") + interventions = pd.read_csv( + os.path.join(path, "browse_interventions.txt"), sep="|" + ) + interventions = interventions[ + interventions.mesh_type == "mesh-list" + ] # just looking at root identity + conditions = pd.read_csv(os.path.join(path, "browse_conditions.txt"), sep="|") + conditions = conditions[ + conditions.mesh_type == "mesh-list" + ] # just looking at root identity + + reported_event_totals = pd.read_csv( + os.path.join(path, "reported_event_totals.txt"), sep="|" + ) + sponsors = pd.read_csv( + os.path.join(path, "sponsors.txt"), sep="|", low_memory=False + ) + facilities = pd.read_csv(os.path.join(path, "facilities.txt"), sep="|") + outcome_analyses = pd.read_csv( + os.path.join(path, "outcome_analyses.txt"), sep="|", low_memory=False + ) + detailed_descriptions = pd.read_csv( + os.path.join(path, "detailed_descriptions.txt"), sep="|" + ) + brief_summaries = pd.read_csv( + os.path.join(path, "brief_summaries.txt"), sep="|" + ) + + ## just using trials with actual completion date + # print('studies', len(studies)) + studies = studies[studies.completion_date_type == "Actual"] + ## there are 27 trials before 1975 + studies = studies[studies.start_date >= "2000-01-01"] + studies = studies[studies.nct_id.notnull()] + # print('studies actual', len(studies)) + nct_id_use = studies.nct_id.values + + ## get trial start and end date for later infer + studies["start_date"] = pd.to_datetime(studies["start_date"]) + studies["completion_date"] = pd.to_datetime(studies["completion_date"]) + nct2start_date = dict(studies[["nct_id", "start_date"]].values) + nct2end_date = dict(studies[["nct_id", "completion_date"]].values) + + ## too many columns in studies, keeping few interesting columns and remove temporal leakage columns + studies = studies[ + [ + "nct_id", + "start_date", + "target_duration", + "study_type", + "acronym", + "baseline_population", + "brief_title", + "official_title", + "phase", + "enrollment", + "enrollment_type", + "source", + "limitations_and_caveats", + "number_of_arms", + "number_of_groups", + "has_dmc", + "is_fda_regulated_drug", + "is_fda_regulated_device", + "is_unapproved_device", + "is_ppsd", + "is_us_export", + "biospec_retention", + "biospec_description", + "source_class", + "baseline_type_units_analyzed", + "fdaaa801_violation", + "plan_to_share_ipd", + ] + ] + + ## merge description/brief into main study table + nct2descriptions = dict(detailed_descriptions[["nct_id", "description"]].values) + nct2brief = dict(brief_summaries[["nct_id", "description"]].values) + studies["detailed_descriptions"] = studies.nct_id.apply( + lambda x: nct2descriptions[x] if x in nct2descriptions else np.nan + ) + studies["brief_summaries"] = studies.nct_id.apply( + lambda x: nct2brief[x] if x in nct2brief else np.nan + ) + + outcomes = outcomes[ + [ + "id", + "nct_id", + "outcome_type", + "title", + "description", + "time_frame", + "population", + "units", + "units_analyzed", + "dispersion_type", + "param_type", + ] + ] + + reported_event_totals = reported_event_totals[ + [ + "id", + "nct_id", + "event_type", + "classification", + "subjects_affected", + "subjects_at_risk", + ] + ] + + drop_withdrawals.drop( + columns=[ + "result_group_id", + "ctgov_group_code", + "drop_withdraw_comment", + "reason_comment", + "count_units", + ], + inplace=True, + ) + conditions.drop(columns=["downcase_mesh_term", "mesh_type"], inplace=True) + interventions.drop(columns=["downcase_mesh_term", "mesh_type"], inplace=True) + ## filter to nct_id with actual completion date + # print('outcomes before filter', len(outcomes)) + # for df in [outcomes, outcome_analyses, drop_withdrawals, reported_event_totals, designs, eligibilities, interventions, conditions, facilities, sponsors]: + + outcomes = outcomes[outcomes.nct_id.isin(nct_id_use)] + outcome_analyses = outcome_analyses[outcome_analyses.nct_id.isin(nct_id_use)] + drop_withdrawals = drop_withdrawals[drop_withdrawals.nct_id.isin(nct_id_use)] + reported_event_totals = reported_event_totals[ + reported_event_totals.nct_id.isin(nct_id_use) + ] + designs = designs[designs.nct_id.isin(nct_id_use)] + eligibilities = eligibilities[eligibilities.nct_id.isin(nct_id_use)] + interventions = interventions[interventions.nct_id.isin(nct_id_use)] + conditions = conditions[conditions.nct_id.isin(nct_id_use)] + facilities = facilities[facilities.nct_id.isin(nct_id_use)] + sponsors = sponsors[sponsors.nct_id.isin(nct_id_use)] + + # print('outcomes after filter', len(outcomes)) + ## infer time stamps + ## tables that is available after trial ends + for df in [outcomes, outcome_analyses, drop_withdrawals, reported_event_totals]: + df["date"] = df.nct_id.apply(lambda x: nct2end_date[x]) + + ## tables that is available as trial starts + for df in [ + designs, + eligibilities, + interventions, + conditions, + facilities, + sponsors, + ]: + df["date"] = df.nct_id.apply(lambda x: nct2start_date[x]) + + ## create separate entity tables for sponsor/facility/condition/intervention since some tasks are asking them + sponsor2id = dict( + zip(sponsors.name.unique(), range(len(sponsors.name.unique()))) + ) + sponsors["sponsor_id"] = sponsors.name.apply(lambda x: sponsor2id[x]) + sponsor_trial = sponsors[ + ["id", "nct_id", "sponsor_id", "lead_or_collaborator", "date"] + ] + sponsors = ( + sponsors[["sponsor_id", "name", "agency_class"]] + .drop_duplicates("sponsor_id") + .reset_index(drop=True) + ) + + facility2id = dict( + zip(facilities.name.unique(), range(len(facilities.name.unique()))) + ) + facilities["facility_id"] = facilities.name.apply(lambda x: facility2id[x]) + facility_trial = facilities[["id", "nct_id", "facility_id", "date"]] + facilities = ( + facilities[["facility_id", "name", "city", "state", "zip", "country"]] + .drop_duplicates("facility_id") + .reset_index(drop=True) + ) + + condition2id = dict( + zip( + conditions.mesh_term.unique(), range(len(conditions.mesh_term.unique())) + ) + ) + conditions["condition_id"] = conditions.mesh_term.apply( + lambda x: condition2id[x] + ) + condition_trial = conditions[["id", "nct_id", "condition_id", "date"]] + conditions = ( + conditions[["condition_id", "mesh_term"]] + .drop_duplicates("condition_id") + .reset_index(drop=True) + ) + + intervention2id = dict( + zip( + interventions.mesh_term.unique(), + range(len(interventions.mesh_term.unique())), + ) + ) + interventions["intervention_id"] = interventions.mesh_term.apply( + lambda x: intervention2id[x] + ) + intervention_trial = interventions[["id", "nct_id", "intervention_id", "date"]] + interventions = ( + interventions[["intervention_id", "mesh_term"]] + .drop_duplicates("intervention_id") + .reset_index(drop=True) + ) + + tables = {} + + tables["studies"] = Table( + df=studies, + fkey_col_to_pkey_table={}, + pkey_col="nct_id", + time_col="start_date", + ) + + tables["outcomes"] = Table( + df=outcomes, + fkey_col_to_pkey_table={ + "nct_id": "studies", + }, + pkey_col="id", + time_col="date", + ) + + tables["outcome_analyses"] = Table( + df=outcome_analyses, + fkey_col_to_pkey_table={"nct_id": "studies", "outcome_id": "outcomes"}, + pkey_col="id", + time_col="date", + ) + + tables["drop_withdrawals"] = Table( + df=drop_withdrawals, + fkey_col_to_pkey_table={ + "nct_id": "studies", + }, + pkey_col="id", + time_col="date", + ) + + tables["reported_event_totals"] = Table( + df=reported_event_totals, + fkey_col_to_pkey_table={ + "nct_id": "studies", + }, + pkey_col="id", + time_col="date", + ) + + tables["designs"] = Table( + df=designs, + fkey_col_to_pkey_table={ + "nct_id": "studies", + }, + pkey_col="id", + time_col="date", + ) + + tables["eligibilities"] = Table( + df=eligibilities, + fkey_col_to_pkey_table={ + "nct_id": "studies", + }, + pkey_col="id", + time_col="date", + ) + + tables["interventions"] = Table( + df=interventions, + fkey_col_to_pkey_table={}, + pkey_col="intervention_id", + time_col=None, + ) + + tables["conditions"] = Table( + df=conditions, + fkey_col_to_pkey_table={}, + pkey_col="condition_id", + time_col=None, + ) + + tables["facilities"] = Table( + df=facilities, + fkey_col_to_pkey_table={}, + pkey_col="facility_id", + time_col=None, + ) + + tables["sponsors"] = Table( + df=sponsors, + fkey_col_to_pkey_table={}, + pkey_col="sponsor_id", + time_col=None, + ) + + tables["interventions_studies"] = Table( + df=intervention_trial, + fkey_col_to_pkey_table={ + "nct_id": "studies", + "intervention_id": "interventions", + }, + pkey_col="id", + time_col="date", + ) + + tables["conditions_studies"] = Table( + df=condition_trial, + fkey_col_to_pkey_table={"nct_id": "studies", "condition_id": "conditions"}, + pkey_col="id", + time_col="date", + ) + + tables["facilities_studies"] = Table( + df=facility_trial, + fkey_col_to_pkey_table={"nct_id": "studies", "facility_id": "facilities"}, + pkey_col="id", + time_col="date", + ) + + tables["sponsors_studies"] = Table( + df=sponsor_trial, + fkey_col_to_pkey_table={"nct_id": "studies", "sponsor_id": "sponsors"}, + pkey_col="id", + time_col="date", + ) + return Database(tables) diff --git a/plexe/relbench/tasks/__init__.py b/plexe/relbench/tasks/__init__.py index 756cc8ae..783cd1c5 100644 --- a/plexe/relbench/tasks/__init__.py +++ b/plexe/relbench/tasks/__init__.py @@ -6,6 +6,19 @@ from ..base import BaseTask from ..datasets import get_dataset +from ..tasks import ( + amazon, + arxiv, + avito, + dbinfer, + event, + f1, + hm, + mimic, + ratebeer, + stack, + trial, +) task_registry = defaultdict(dict) diff --git a/plexe/relbench/tasks/amazon.py b/plexe/relbench/tasks/amazon.py new file mode 100644 index 00000000..bf3eb448 --- /dev/null +++ b/plexe/relbench/tasks/amazon.py @@ -0,0 +1,394 @@ +import duckdb +import pandas as pd + +from relbench.base import Database, EntityTask, RecommendationTask, Table, TaskType +from relbench.metrics import ( + accuracy, + average_precision, + f1, + link_prediction_map, + link_prediction_precision, + link_prediction_recall, + mae, + r2, + rmse, + roc_auc, +) + + +class UserChurnTask(EntityTask): + r"""Churn for a customer is 1 if the customer does not review any product in the + time window, else 0.""" + + task_type = TaskType.BINARY_CLASSIFICATION + entity_col = "customer_id" + entity_table = "customer" + time_col = "timestamp" + target_col = "churn" + timedelta = pd.Timedelta(days=365 // 4) + metrics = [average_precision, accuracy, f1, roc_auc] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + product = db.table_dict["product"].df + customer = db.table_dict["customer"].df + review = db.table_dict["review"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + df = duckdb.sql( + f""" + SELECT + timestamp, + customer_id, + CAST( + NOT EXISTS ( + SELECT 1 + FROM review + WHERE + review.customer_id = customer.customer_id AND + review_time > timestamp AND + review_time <= timestamp + INTERVAL '{self.timedelta}' + ) AS INTEGER + ) AS churn + FROM + timestamp_df, + customer, + WHERE + EXISTS ( + SELECT 1 + FROM review + WHERE + review.customer_id = customer.customer_id AND + review_time > timestamp - INTERVAL '{self.timedelta}' AND + review_time <= timestamp + ) + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +class UserLTVTask(EntityTask): + r"""LTV (life-time value) for a customer is the sum of prices of products that the + customer reviews in the time window.""" + + task_type = TaskType.REGRESSION + entity_col = "customer_id" + entity_table = "customer" + time_col = "timestamp" + target_col = "ltv" + timedelta = pd.Timedelta(days=365 // 4) + metrics = [r2, mae, rmse] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + product = db.table_dict["product"].df + customer = db.table_dict["customer"].df + review = db.table_dict["review"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + df = duckdb.sql( + f""" + SELECT + timestamp, + customer_id, + ltv, + FROM + timestamp_df, + customer, + ( + SELECT + COALESCE(SUM(price), 0) as ltv, + FROM + review, + product + WHERE + review.customer_id = customer.customer_id AND + review.product_id = product.product_id AND + review_time > timestamp AND + review_time <= timestamp + INTERVAL '{self.timedelta}' + ) + WHERE + EXISTS ( + SELECT 1 + FROM review + WHERE + review.customer_id = customer.customer_id AND + review_time > timestamp - INTERVAL '{self.timedelta}' AND + review_time <= timestamp + ) + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={"customer_id": "customer"}, + pkey_col=None, + time_col="timestamp", + ) + + +class ItemChurnTask(EntityTask): + r"""Churn for a product is 1 if the product recieves at least one review in the time + window, else 0.""" + + task_type = TaskType.BINARY_CLASSIFICATION + entity_col = "product_id" + entity_table = "product" + time_col = "timestamp" + target_col = "churn" + timedelta = pd.Timedelta(days=365 // 4) + metrics = [average_precision, accuracy, f1, roc_auc] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + product = db.table_dict["product"].df + customer = db.table_dict["customer"].df + review = db.table_dict["review"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + df = duckdb.sql( + f""" + SELECT + timestamp, + product_id, + CAST( + NOT EXISTS ( + SELECT 1 + FROM review + WHERE + review.product_id = product.product_id AND + review_time > timestamp AND + review_time <= timestamp + INTERVAL '{self.timedelta}' + ) AS INTEGER + ) AS churn + FROM + timestamp_df, + product, + WHERE + EXISTS ( + SELECT 1 + FROM review + WHERE + review.product_id = product.product_id AND + review_time > timestamp - INTERVAL '{self.timedelta}' AND + review_time <= timestamp + ) + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +class ItemLTVTask(EntityTask): + r"""LTV (life-time value) for a product is the numer of times the product is + purchased in the time window multiplied by price.""" + + task_type = TaskType.REGRESSION + entity_col = "product_id" + entity_table = "product" + time_col = "timestamp" + target_col = "ltv" + timedelta = pd.Timedelta(days=365 // 4) + metrics = [r2, mae, rmse] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + product = db.table_dict["product"].df + customer = db.table_dict["customer"].df + review = db.table_dict["review"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + df = duckdb.sql( + f""" + SELECT + timestamp, + product.product_id, + COALESCE(SUM(price), 0) AS ltv, + FROM + timestamp_df, + product, + review + WHERE + review.product_id = product.product_id AND + review_time > timestamp AND + review_time <= timestamp + INTERVAL '{self.timedelta}' + GROUP BY + timestamp, + product.product_id + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col="timestamp", + ) + + +class UserItemPurchaseTask(RecommendationTask): + r"""Predict the list of distinct items each customer will purchase in the next two + years.""" + + task_type = TaskType.LINK_PREDICTION + src_entity_col = "customer_id" + src_entity_table = "customer" + dst_entity_col = "product_id" + dst_entity_table = "product" + time_col = "timestamp" + timedelta = pd.Timedelta(days=365 // 4) + metrics = [link_prediction_precision, link_prediction_recall, link_prediction_map] + eval_k = 10 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + customer = db.table_dict["customer"].df + review = db.table_dict["review"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + df = duckdb.sql( + f""" + SELECT + t.timestamp, + review.customer_id, + LIST(DISTINCT review.product_id) AS product_id + FROM + timestamp_df t + LEFT JOIN + review + ON + review.review_time > t.timestamp AND + review.review_time <= t.timestamp + INTERVAL '{self.timedelta} days' + WHERE + review.customer_id is not null and review.product_id is not null + GROUP BY + t.timestamp, + review.customer_id + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={ + self.src_entity_col: self.src_entity_table, + self.dst_entity_col: self.dst_entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) + + +class UserItemRateTask(RecommendationTask): + r"""Predict the list of distinct items each customer will purchase and give a 5 star + review in the next two years.""" + + task_type = TaskType.LINK_PREDICTION + src_entity_col = "customer_id" + src_entity_table = "customer" + dst_entity_col = "product_id" + dst_entity_table = "product" + time_col = "timestamp" + timedelta = pd.Timedelta(days=365 // 4) + metrics = [link_prediction_precision, link_prediction_recall, link_prediction_map] + eval_k = 10 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + customer = db.table_dict["customer"].df + review = db.table_dict["review"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + df = duckdb.sql( + f""" + SELECT + t.timestamp, + review.customer_id, + LIST(DISTINCT review.product_id) AS product_id + FROM + timestamp_df t + LEFT JOIN + review + ON + review.review_time > t.timestamp AND + review.review_time <= t.timestamp + INTERVAL '{self.timedelta} days' + WHERE + review.customer_id IS NOT NULL + AND review.product_id IS NOT NULL + AND review.rating = 5.0 + GROUP BY + t.timestamp, + review.customer_id + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={ + self.src_entity_col: self.src_entity_table, + self.dst_entity_col: self.dst_entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) + + +class UserItemReviewTask(RecommendationTask): + r"""Predict the list of distinct items each customer will purchase and give a + detailed review in the next two years.""" + + task_type = TaskType.LINK_PREDICTION + src_entity_col = "customer_id" + src_entity_table = "customer" + dst_entity_col = "product_id" + dst_entity_table = "product" + time_col = "timestamp" + timedelta = pd.Timedelta(days=365 // 4) + metrics = [link_prediction_precision, link_prediction_recall, link_prediction_map] + eval_k = 10 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + customer = db.table_dict["customer"].df + review = db.table_dict["review"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + REVIEW_LENGTH = ( + 300 # minimum length of review to be considered as detailed review + ) + + df = duckdb.sql( + f""" + SELECT + t.timestamp, + review.customer_id, + LIST(DISTINCT review.product_id) AS product_id + FROM + timestamp_df t + LEFT JOIN + review + ON + review.review_time > t.timestamp AND + review.review_time <= t.timestamp + INTERVAL '{self.timedelta} days' + WHERE + review.customer_id IS NOT NULL + AND review.product_id IS NOT NULL + AND (LENGTH(review.review_text) > {REVIEW_LENGTH} AND review.review_text IS NOT NULL) + GROUP BY + t.timestamp, + review.customer_id + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={ + self.src_entity_col: self.src_entity_table, + self.dst_entity_col: self.dst_entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) \ No newline at end of file diff --git a/plexe/relbench/tasks/arxiv.py b/plexe/relbench/tasks/arxiv.py new file mode 100644 index 00000000..c2d21291 --- /dev/null +++ b/plexe/relbench/tasks/arxiv.py @@ -0,0 +1,240 @@ +import duckdb +import pandas as pd + +from relbench.base import Database, EntityTask, RecommendationTask, Table, TaskType +from relbench.metrics import ( + accuracy, + f1, + link_prediction_map, + link_prediction_precision, + link_prediction_recall, + mae, + multiclass_f1, + r2, + rmse, + roc_auc, +) + + +class PaperCitationTask(EntityTask): + r"""Predict if a paper gets cited in the next 6 months.""" + + task_type = TaskType.BINARY_CLASSIFICATION + entity_col = "Paper_ID" + entity_table = "papers" + time_col = "date" + target_col = "cited" + timedelta = pd.Timedelta(days=365 // 2) # approximately 6 months + metrics = [accuracy, f1, roc_auc] + num_eval_timestamps = 1 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + papers = db.table_dict["papers"].df + citations = db.table_dict["citations"].df + + df = duckdb.sql( + f""" + WITH paper_citations AS ( + SELECT + t.timestamp AS date, + p.Paper_ID, + COUNT(c.References_Paper_ID) AS citation_count + FROM timestamp_df t + JOIN papers p + ON p.Submission_Date <= t.timestamp + LEFT JOIN citations c + ON c.References_Paper_ID = p.Paper_ID + AND c.Submission_Date > t.timestamp + AND c.Submission_Date <= t.timestamp + INTERVAL '{self.timedelta}' + GROUP BY t.timestamp, p.Paper_ID + ) + SELECT + date, + Paper_ID, + CASE WHEN citation_count > 0 THEN 1 ELSE 0 END AS cited + FROM paper_citations; + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +class AuthorCategoryTask(EntityTask): + r"""Predict the primary research category in which an author will publish papers in + the next six months.""" + + task_type = TaskType.MULTICLASS_CLASSIFICATION + entity_col = "Author_ID" + entity_table = "authors" + time_col = "date" + target_col = "primary_category" + timedelta = pd.Timedelta(days=365 // 2) + metrics = [accuracy, multiclass_f1] + num_eval_timestamps = 1 + num_classes = 53 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + author = db.table_dict["authors"].df + paperAuthors = db.table_dict["paperAuthors"].df + papers = db.table_dict["papers"].df + paperCategories = db.table_dict["paperCategories"].df + categories = db.table_dict["categories"].df + + df = duckdb.sql( + f""" + WITH author_pubs AS ( + SELECT + t.timestamp AS date, + pa.Author_ID, + p.Primary_Category_ID + FROM timestamp_df t + JOIN paperAuthors pa + ON pa.Submission_Date > t.timestamp + AND pa.Submission_Date <= t.timestamp + INTERVAL '{self.timedelta}' + JOIN papers p + ON pa.Paper_ID = p.Paper_ID + ), + pub_counts AS ( + SELECT + date, + Author_ID, + Primary_Category_ID, + COUNT(*) AS cnt + FROM author_pubs + GROUP BY date, Author_ID, Primary_Category_ID + ), + ranked AS ( + SELECT + date, + Author_ID, + Primary_Category_ID, + ROW_NUMBER() OVER (PARTITION BY date, Author_ID ORDER BY cnt DESC) AS rn + FROM pub_counts + ) + SELECT + r.date, + r.Author_ID, + c.Category AS primary_category + FROM ranked r + LEFT JOIN categories c ON r.Primary_Category_ID = c.Category_ID + WHERE r.rn = 1 + ; + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=self.entity_col, + time_col=self.time_col, + ) + + +class AuthorPublicationTask(EntityTask): + r"""Predict how many papers an author will publish in the next six months.""" + + task_type = TaskType.REGRESSION + entity_col = "Author_ID" + entity_table = "authors" + time_col = "date" + target_col = "publication_count" + timedelta = pd.Timedelta(days=365 // 2) + metrics = [r2, mae, rmse] + num_eval_timestamps = 1 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + paperAuthors = db.table_dict["paperAuthors"].df + + df = duckdb.sql( + f""" + WITH author_pubs AS ( + SELECT + t.timestamp AS date, + pa.Author_ID, + COUNT(pa.Paper_ID) AS publication_count + FROM timestamp_df t + JOIN paperAuthors pa + ON pa.Submission_Date > t.timestamp + AND pa.Submission_Date <= t.timestamp + INTERVAL '{self.timedelta}' + GROUP BY t.timestamp, pa.Author_ID + ) + SELECT date, Author_ID, publication_count FROM author_pubs; + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +class CoCitationTask(RecommendationTask): + r"""Predict which other papers will be cited together with a given paper in the next + six months.""" + + task_type = TaskType.LINK_PREDICTION + src_entity_col = "Paper_ID" + src_entity_table = "papers" + dst_entity_col = "co_cited" + dst_entity_table = "papers" + time_col = "date" + timedelta = pd.Timedelta(days=365 // 2) + metrics = [link_prediction_map, link_prediction_precision, link_prediction_recall] + num_eval_timestamps = 1 + eval_k = 10 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + papers = db.table_dict["papers"].df + citations = db.table_dict["citations"].df + + df = duckdb.sql( + f""" + WITH paper_co_citations AS ( + SELECT + t.timestamp AS date, + p.Paper_ID, + c2.References_Paper_ID AS co_cited_paper + FROM timestamp_df t + JOIN papers p + ON p.Submission_Date <= t.timestamp + JOIN citations c1 + ON c1.References_Paper_ID = p.Paper_ID + AND c1.Submission_Date > t.timestamp + AND c1.Submission_Date <= t.timestamp + INTERVAL '{self.timedelta}' + JOIN citations c2 + ON c1.Paper_ID = c2.Paper_ID + AND c2.References_Paper_ID <> p.Paper_ID + AND c2.Submission_Date > t.timestamp + AND c2.Submission_Date <= t.timestamp + INTERVAL '{self.timedelta}' + ) + SELECT + date, + Paper_ID, + array_agg(DISTINCT co_cited_paper) AS co_cited + FROM paper_co_citations + GROUP BY date, Paper_ID + ; + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={ + self.src_entity_col: self.src_entity_table, + self.dst_entity_col: self.dst_entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) \ No newline at end of file diff --git a/plexe/relbench/tasks/avito.py b/plexe/relbench/tasks/avito.py new file mode 100644 index 00000000..62a51a7f --- /dev/null +++ b/plexe/relbench/tasks/avito.py @@ -0,0 +1,226 @@ +import duckdb +import pandas as pd + +from relbench.base import Database, EntityTask, RecommendationTask, Table, TaskType +from relbench.metrics import ( + accuracy, + average_precision, + f1, + link_prediction_map, + link_prediction_precision, + link_prediction_recall, + mae, + r2, + rmse, + roc_auc, +) + + +class AdCTRTask(EntityTask): + r"""Assuming the ad will be clicked in the next 4 days, predict the Click-Through- + Rate (CTR) for each ad.""" + + task_type = TaskType.REGRESSION + entity_table = "AdsInfo" + entity_col = "AdID" + time_col = "timestamp" + target_col = "num_click" + timedelta = pd.Timedelta(days=4) + metrics = [r2, mae, rmse] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + ads_info = db.table_dict["AdsInfo"].df + search_stream = db.table_dict["SearchStream"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + df = duckdb.sql( + f""" + SELECT + search_ads.AdID, + t.timestamp, + COALESCE(SUM(search_ads.isClick), 0) / COALESCE(COUNT(search_ads.SearchID), 1) AS num_click + FROM + timestamp_df t + LEFT JOIN ( + ads_info + LEFT JOIN + search_stream + ON + ads_info.AdID == search_stream.AdID + ) search_ads + ON + search_ads.SearchDate > t.timestamp AND + search_ads.SearchDate <= t.timestamp + INTERVAL '{self.timedelta} days' + GROUP BY + t.timestamp, + search_ads.AdID + HAVING + SUM(search_ads.isClick) > 0 + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col="timestamp", + ) + + +class UserVisitsTask(EntityTask): + r"""Predict whether each customer will visit more than one ad in the next 4 days.""" + + task_type = TaskType.BINARY_CLASSIFICATION + entity_table = "UserInfo" + entity_col = "UserID" + time_col = "timestamp" + target_col = "num_click" + timedelta = pd.Timedelta(days=4) + metrics = [average_precision, accuracy, f1, roc_auc] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + user_info = db.table_dict["UserInfo"].df + visits_stream = db.table_dict["VisitStream"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + df = duckdb.sql( + f""" + SELECT + visit_ads.UserID, + t.timestamp, + COALESCE(COUNT(DISTINCT visit_ads.AdID), 0) > 1 AS num_click + FROM + timestamp_df t + LEFT JOIN + ( + user_info + LEFT JOIN + visits_stream + ON + user_info.UserID == visits_stream.UserID + ) visit_ads + ON + visit_ads.ViewDate > t.timestamp AND + visit_ads.ViewDate <= t.timestamp + INTERVAL '{self.timedelta} days' + GROUP BY + t.timestamp, + visit_ads.UserID + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col="timestamp", + ) + + +class UserClicksTask(EntityTask): + r"""Predict whether the each customer will click on more than one ads in the next 4 + days.""" + + task_type = TaskType.BINARY_CLASSIFICATION + entity_table = "UserInfo" + entity_col = "UserID" + time_col = "timestamp" + target_col = "num_click" + timedelta = pd.Timedelta(days=4) + metrics = [average_precision, accuracy, f1, roc_auc] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + user_info = db.table_dict["UserInfo"].df + search_info = db.table_dict["SearchInfo"].df + search_stream = db.table_dict["SearchStream"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + df = duckdb.sql( + f""" + SELECT + search_ads.UserID, + t.timestamp, + COALESCE(COUNT(search_ads.AdID), 0) > 1 AS num_click + FROM + timestamp_df t + LEFT JOIN + ( + ( + user_info + LEFT JOIN + search_info + ON + user_info.UserID == search_info.UserID + ) user_search_info + LEFT JOIN + search_stream + ON + user_search_info.SearchID == search_stream.SearchID AND + search_stream.IsClick == 1.0 + ) search_ads + ON + search_ads.SearchDate > t.timestamp AND + search_ads.SearchDate <= t.timestamp + INTERVAL '{self.timedelta} days' + GROUP BY + t.timestamp, + search_ads.UserID + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col="timestamp", + ) + + +class UserAdVisitTask(RecommendationTask): + r"""Predict the distinct list of ads a user will visit in the next 4 days.""" + + task_type = TaskType.LINK_PREDICTION + src_entity_table = "UserInfo" + src_entity_col = "UserID" + + dst_entity_table = "AdsInfo" + dst_entity_col = "AdID" + + time_col = "timestamp" + timedelta = pd.Timedelta(days=4) + metrics = [link_prediction_precision, link_prediction_recall, link_prediction_map] + eval_k = 12 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + user_info = db.table_dict["UserInfo"].df + visits_stream = db.table_dict["VisitStream"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + df = duckdb.sql( + f""" + SELECT + visit_ads.UserID, + t.timestamp, + LIST(DISTINCT visit_ads.AdID) AS AdID, + FROM + timestamp_df t + LEFT JOIN + ( + user_info + LEFT JOIN + visits_stream + ON + user_info.UserID == visits_stream.UserID + ) visit_ads + ON + visit_ads.ViewDate > t.timestamp AND + visit_ads.ViewDate <= t.timestamp + INTERVAL '{self.timedelta} days' + GROUP BY + t.timestamp, + visit_ads.UserID + """ + ).df() + return Table( + df=df, + fkey_col_to_pkey_table={ + self.src_entity_col: self.src_entity_table, + self.dst_entity_col: self.dst_entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) \ No newline at end of file diff --git a/plexe/relbench/tasks/dbinfer.py b/plexe/relbench/tasks/dbinfer.py new file mode 100644 index 00000000..b769a0f9 --- /dev/null +++ b/plexe/relbench/tasks/dbinfer.py @@ -0,0 +1,179 @@ +import os +from typing import Dict + +import pandas as pd +import pooch + +from relbench.base import EntityTask, Table + +DEFAULT_DBINFER_ADAPTER_CACHE = os.path.join( + pooch.os_cache("relbench"), "dbinfer-adapters" +) +SYNTHETIC_TIME_COL = "__dbinfer_timestamp__" +SYNTHETIC_TIMESTAMPS: Dict[str, pd.Timestamp] = { + "train": pd.Timestamp("1970-01-01"), + "val": pd.Timestamp("1970-01-02"), + "test": pd.Timestamp("1970-01-03"), +} + + +class DBInferTaskBase(EntityTask): + """RelBench EntityTask backed by a DBInfer task definition.""" + + dbinfer_dataset_name: str | None = None + dbinfer_task_name: str | None = None + + timedelta = pd.Timedelta(days=1) + metrics = [] + num_eval_timestamps = 1 + + def __init__( + self, + dataset, + cache_dir=None, + adapter_cache_dir: str | None = None, + ): + if not self.dbinfer_dataset_name or not self.dbinfer_task_name: + raise ValueError( + "DBInferTaskBase subclasses must define " + "'dbinfer_dataset_name' and 'dbinfer_task_name'." + ) + + if hasattr(dataset, "dbinfer_name"): + if dataset.dbinfer_name != self.dbinfer_dataset_name: + raise ValueError( + "Dataset and task originate from different DBInfer sources: " + f"{dataset.dbinfer_name} vs {self.dbinfer_dataset_name}" + ) + + if adapter_cache_dir is None: + adapter_cache_dir = DEFAULT_DBINFER_ADAPTER_CACHE + self._adapter_cache_dir = adapter_cache_dir + from dbinfer_relbench_adapter.loader import load_dbinfer_data + + dataset_adapter, task_adapter = load_dbinfer_data( + dataset_name=self.dbinfer_dataset_name, + task_name=self.dbinfer_task_name, + use_cache=True, + cache_dir=self._adapter_cache_dir, + ) + + self._dataset_adapter = dataset_adapter + self._task_adapter = task_adapter + + self.task_type = task_adapter.task_type + self.entity_table = task_adapter.entity_table + self.entity_col = task_adapter.entity_col + self.target_col = task_adapter.target_col + self.metrics = task_adapter.metrics + self.num_labels = getattr(task_adapter, "num_labels", None) + self.num_classes = self.num_labels + + metadata_time_col = getattr( + task_adapter.dbinfer_task.metadata, "time_column", None + ) + self.time_col = metadata_time_col or SYNTHETIC_TIME_COL + + super().__init__(dataset, cache_dir=cache_dir) + + def _get_table(self, split): + if split not in SYNTHETIC_TIMESTAMPS: + raise ValueError(f"Unknown split '{split}' for DBInfer task.") + + mock_table = self._task_adapter.get_table(split) + df = mock_table.df.copy() + + time_col = self.time_col + if time_col not in df.columns: + self.time_col = SYNTHETIC_TIME_COL + time_col = self.time_col + df[time_col] = SYNTHETIC_TIMESTAMPS[split] + elif time_col == SYNTHETIC_TIME_COL: + df[time_col] = SYNTHETIC_TIMESTAMPS[split] + else: + df[time_col] = pd.to_datetime(df[time_col], errors="coerce") + + fkeys = {} + if self.entity_col in df.columns and self.entity_table: + fkeys[self.entity_col] = self.entity_table + + return Table( + df=df, + fkey_col_to_pkey_table=fkeys, + pkey_col=None, + time_col=time_col, + ) + + def evaluate(self, pred, table=None): + metrics = self._task_adapter.evaluate(pred, table) + return metrics + + +class AVSRepeaterTask(DBInferTaskBase): + dbinfer_dataset_name = "avs" + dbinfer_task_name = "repeater" + + +class MAGCiteTask(DBInferTaskBase): + dbinfer_dataset_name = "mag" + dbinfer_task_name = "cite" + + +class MAGVenueTask(DBInferTaskBase): + dbinfer_dataset_name = "mag" + dbinfer_task_name = "venue" + + +class DigineticaCTRTask(DBInferTaskBase): + dbinfer_dataset_name = "diginetica" + dbinfer_task_name = "ctr" + + +class DigineticaPurchaseTask(DBInferTaskBase): + dbinfer_dataset_name = "diginetica" + dbinfer_task_name = "purchase" + + +class RetailRocketCVRTask(DBInferTaskBase): + dbinfer_dataset_name = "retailrocket" + dbinfer_task_name = "cvr" + + +class SeznamChargeTask(DBInferTaskBase): + dbinfer_dataset_name = "seznam" + dbinfer_task_name = "charge" + + +class SeznamPrepayTask(DBInferTaskBase): + dbinfer_dataset_name = "seznam" + dbinfer_task_name = "prepay" + + +class AmazonRatingTask(DBInferTaskBase): + dbinfer_dataset_name = "amazon" + dbinfer_task_name = "rating" + + +class AmazonPurchaseTask(DBInferTaskBase): + dbinfer_dataset_name = "amazon" + dbinfer_task_name = "purchase" + + +class AmazonChurnTask(DBInferTaskBase): + dbinfer_dataset_name = "amazon" + dbinfer_task_name = "churn" + + +class StackExchangeChurnTask(DBInferTaskBase): + dbinfer_dataset_name = "stackexchange" + dbinfer_task_name = "churn" + + +class StackExchangeUpvoteTask(DBInferTaskBase): + dbinfer_dataset_name = "stackexchange" + dbinfer_task_name = "upvote" + + +class OutbrainCTRTask(DBInferTaskBase): + dbinfer_dataset_name = "outbrain-small" + dbinfer_task_name = "ctr" \ No newline at end of file diff --git a/plexe/relbench/tasks/event.py b/plexe/relbench/tasks/event.py new file mode 100644 index 00000000..37fab2db --- /dev/null +++ b/plexe/relbench/tasks/event.py @@ -0,0 +1,189 @@ +import duckdb +import pandas as pd + +from relbench.base import Database, EntityTask, Table, TaskType +from relbench.metrics import accuracy, average_precision, f1, mae, r2, rmse, roc_auc + + +class UserAttendanceTask(EntityTask): + r"""Predict the number of events a user will go to in the next seven days 7 days.""" + + task_type = TaskType.REGRESSION + entity_col = "user" + entity_table = "users" + time_col = "timestamp" + timedelta = pd.Timedelta(days=7) + metrics = [r2, mae, rmse] + target_col = "target" + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + users = db.table_dict["users"].df + user_friends = db.table_dict["user_friends"].df + events = db.table_dict["events"].df + event_attendees = db.table_dict["event_attendees"].df + event_interest = db.table_dict["event_interest"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + df = duckdb.sql( + f"""SELECT + t.timestamp, + event_attendees.user_id AS user, + SUM(CASE WHEN event_attendees.status IN ('yes', 'maybe') THEN 1 ELSE 0 END) AS target + FROM + timestamp_df t + LEFT JOIN + event_attendees + ON + event_attendees.start_time > t.timestamp AND + event_attendees.start_time <= t.timestamp + INTERVAL '{self.timedelta} days' + GROUP BY + t.timestamp, + event_attendees.user_id + """ + ).df() + df = df.dropna(subset=["user"]) + df["user"] = df["user"].astype(int) + df = df.reset_index() + + return Table( + df=df, + fkey_col_to_pkey_table={ + self.entity_col: self.entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) + + +class UserRepeatTask(EntityTask): + r"""Predict whether a user will attend an event in the next 7 days if they have + already attended an event in the last 14 days.""" + + task_type = TaskType.BINARY_CLASSIFICATION + entity_col = "user" + entity_table = "users" + time_col = "timestamp" + timedelta = pd.Timedelta(days=7) + metrics = [accuracy, average_precision, f1, roc_auc] + target_col = "target" + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + users = db.table_dict["users"].df + user_friends = db.table_dict["user_friends"].df + events = db.table_dict["events"].df + event_attendees = db.table_dict["event_attendees"].df + event_interest = db.table_dict["event_interest"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + eval_timestamp_len = len(timestamp_df) + if len(timestamp_df) == 1: + new_row = pd.DataFrame( + { + "timestamp": [ + timestamps[0] - self.timedelta * 2, + timestamps[0] - self.timedelta, + ] + } + ) + timestamp_df = pd.concat([new_row, timestamp_df], ignore_index=True) + + df = duckdb.sql( + f""" + WITH tb AS( + SELECT + t.timestamp AS timestamp, + event_attendees.user_id AS user, + MAX(CASE WHEN event_attendees.status IN ('yes', 'maybe') THEN 1 ELSE 0 END) AS target, + MAX(MAX(CASE WHEN event_attendees.status IN ('yes', 'maybe') THEN 1 ELSE 0 END)) OVER (PARTITION BY event_attendees.user_id ORDER BY t.timestamp ROWS BETWEEN 2 PRECEDING AND 1 PRECEDING) as prev_target + FROM + timestamp_df t + LEFT JOIN + event_attendees + ON + event_attendees.start_time > t.timestamp AND + event_attendees.start_time <= t.timestamp + INTERVAL '{self.timedelta} days' + GROUP BY + t.timestamp, + event_attendees.user_id + ) + SELECT + timestamp, + user, + target + FROM + tb + WHERE + prev_target = 1; + """ + ).df() + + if eval_timestamp_len == 1: + df = df[df.timestamp == df.timestamp.max()] + + df = df.dropna(subset=["user"]) + df["user"] = df["user"].astype(int) + df = df.reset_index() + return Table( + df=df, + fkey_col_to_pkey_table={ + self.entity_col: self.entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) + + +class UserIgnoreTask(EntityTask): + r"""Predict whether a user will ignore more than 2 event invitations in the next 7 + days.""" + + task_type = TaskType.BINARY_CLASSIFICATION + entity_col = "user" + entity_table = "users" + time_col = "timestamp" + timedelta = pd.Timedelta(days=7) + metrics = [accuracy, average_precision, f1, roc_auc] + target_col = "target" + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + users = db.table_dict["users"].df + user_friends = db.table_dict["user_friends"].df + events = db.table_dict["events"].df + event_attendees = db.table_dict["event_attendees"].df + event_interest = db.table_dict["event_interest"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + if len(timestamp_df) == 1: + new_row = pd.DataFrame({"timestamp": [timestamps[0] - self.timedelta]}) + timestamp_df = pd.concat([new_row, timestamp_df], ignore_index=True) + + df = duckdb.sql( + f"""SELECT + t.timestamp AS timestamp, + event_attendees.user_id AS user, + CASE + WHEN SUM(CASE WHEN event_attendees.status = 'invited' THEN 1 ELSE 0 END) > 2 THEN 1 + ELSE 0 + END AS target + FROM + timestamp_df t + LEFT JOIN + event_attendees + ON + event_attendees.start_time > t.timestamp AND + event_attendees.start_time <= t.timestamp + INTERVAL '{self.timedelta} days' + GROUP BY + t.timestamp, + event_attendees.user_id + """ + ).df() + + df = df.dropna(subset=["user"]) + df["user"] = df["user"].astype(int) + df = df.reset_index() + return Table( + df=df, + fkey_col_to_pkey_table={ + self.entity_col: self.entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) \ No newline at end of file diff --git a/plexe/relbench/tasks/f1.py b/plexe/relbench/tasks/f1.py new file mode 100644 index 00000000..11930b41 --- /dev/null +++ b/plexe/relbench/tasks/f1.py @@ -0,0 +1,220 @@ +import duckdb +import pandas as pd + +from relbench.base import Database, EntityTask, RecommendationTask, Table, TaskType +from relbench.metrics import ( + accuracy, + average_precision, + f1, + link_prediction_map, + link_prediction_precision, + link_prediction_recall, + mae, + r2, + rmse, + roc_auc, +) + + +class DriverPositionTask(EntityTask): + r"""Predict the average finishing position of each driver all races in the next 2 + months.""" + + task_type = TaskType.REGRESSION + entity_col = "driverId" + entity_table = "drivers" + time_col = "date" + target_col = "position" + timedelta = pd.Timedelta(days=60) + metrics = [r2, mae, rmse] + num_eval_timestamps = 40 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + results = db.table_dict["results"].df + + df = duckdb.sql( + f""" + SELECT + t.timestamp as date, + re.driverId as driverId, + mean(re.positionOrder) as position, + FROM + timestamp_df t + LEFT JOIN + results re + ON + re.date <= t.timestamp + INTERVAL '{self.timedelta}' + and re.date > t.timestamp + WHERE + re.driverId IN ( + SELECT DISTINCT driverId + FROM results + WHERE date > t.timestamp - INTERVAL '1 year' + ) + GROUP BY t.timestamp, re.driverId + + ; + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +class DriverDNFTask(EntityTask): + r"""Predict the if each driver will DNF (not finish) a race in the next 1 month.""" + + task_type = TaskType.BINARY_CLASSIFICATION + entity_col = "driverId" + entity_table = "drivers" + time_col = "date" + target_col = "did_not_finish" + timedelta = pd.Timedelta(days=30) + metrics = [average_precision, accuracy, f1, roc_auc] + num_eval_timestamps = 40 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + results = db.table_dict["results"].df + + df = duckdb.sql( + f""" + SELECT + t.timestamp as date, + re.driverId as driverId, + MAX(CASE WHEN re.statusId != 1 THEN 1 ELSE 0 END) AS did_not_finish + FROM + timestamp_df t + LEFT JOIN + results re + ON + re.date <= t.timestamp + INTERVAL '{self.timedelta}' + and re.date > t.timestamp + WHERE + re.driverId IN ( + SELECT DISTINCT driverId + FROM results + WHERE date > t.timestamp - INTERVAL '1 year' + ) + GROUP BY t.timestamp, re.driverId + + ; + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +class DriverTop3Task(EntityTask): + r"""Predict if each driver will qualify in the top-3 for a race within the next 1 + month.""" + + task_type = TaskType.BINARY_CLASSIFICATION + entity_col = "driverId" + entity_table = "drivers" + time_col = "date" + target_col = "qualifying" + timedelta = pd.Timedelta(days=30) + metrics = [average_precision, accuracy, f1, roc_auc] + num_eval_timestamps = 40 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + qualifying = db.table_dict["qualifying"].df + + df = duckdb.sql( + f""" + SELECT + t.timestamp as date, + qu.driverId as driverId, + CASE + WHEN MIN(qu.position) <= 3 THEN 1 + ELSE 0 + END AS qualifying + FROM + timestamp_df t + LEFT JOIN + qualifying qu + ON + qu.date <= t.timestamp + INTERVAL '{self.timedelta}' + and qu.date > t.timestamp + WHERE + qu.driverId IN ( + SELECT DISTINCT driverId + FROM qualifying + WHERE date > t.timestamp - INTERVAL '1 year' + ) + GROUP BY t.timestamp, qu.driverId + + ; + """ + ).df() + + df["qualifying"] = df["qualifying"].astype("int64") + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +class DriverRaceCompeteTask(RecommendationTask): + r"""Predict in which races a driver will compete in the next 1 year.""" + + task_type = TaskType.LINK_PREDICTION + src_entity_col = "driverId" + src_entity_table = "drivers" + dst_entity_col = "raceId" + dst_entity_table = "races" + target_col = "raceId" + time_col = "date" + timedelta = pd.Timedelta(days=365) + metrics = [link_prediction_precision, link_prediction_recall, link_prediction_map] + eval_k = 10 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + results = db.table_dict["results"].df + + df = duckdb.sql( + f""" + SELECT + t.timestamp as date, + re.driverId as driverId, + LIST(DISTINCT re.raceId) as raceId + FROM + timestamp_df t + LEFT JOIN + results re + ON + re.date <= t.timestamp + INTERVAL '{self.timedelta}' + and re.date > t.timestamp + GROUP BY t.timestamp, re.driverId + ; + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={ + self.src_entity_col: self.src_entity_table, + self.dst_entity_col: self.dst_entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) \ No newline at end of file diff --git a/plexe/relbench/tasks/hm.py b/plexe/relbench/tasks/hm.py new file mode 100644 index 00000000..ec02b91a --- /dev/null +++ b/plexe/relbench/tasks/hm.py @@ -0,0 +1,166 @@ +import duckdb +import pandas as pd + +from relbench.base import Database, EntityTask, RecommendationTask, Table, TaskType +from relbench.metrics import ( + accuracy, + average_precision, + f1, + link_prediction_map, + link_prediction_precision, + link_prediction_recall, + mae, + r2, + rmse, + roc_auc, +) + + +class UserItemPurchaseTask(RecommendationTask): + r"""Predict the list of articles each customer will purchase in the next seven + days.""" + + task_type = TaskType.LINK_PREDICTION + src_entity_col = "customer_id" + src_entity_table = "customer" + dst_entity_col = "article_id" + dst_entity_table = "article" + time_col = "timestamp" + timedelta = pd.Timedelta(days=7) + metrics = [link_prediction_precision, link_prediction_recall, link_prediction_map] + eval_k = 12 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + customer = db.table_dict["customer"].df + transactions = db.table_dict["transactions"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + df = duckdb.sql( + f""" + SELECT + t.timestamp, + transactions.customer_id, + LIST(DISTINCT transactions.article_id) AS article_id + FROM + timestamp_df t + LEFT JOIN + transactions + ON + transactions.t_dat > t.timestamp AND + transactions.t_dat <= t.timestamp + INTERVAL '{self.timedelta} days' + GROUP BY + t.timestamp, + transactions.customer_id + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={ + self.src_entity_col: self.src_entity_table, + self.dst_entity_col: self.dst_entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) + + +class UserChurnTask(EntityTask): + r"""Predict the churn for a customer (no transactions) in the next week.""" + + task_type = TaskType.BINARY_CLASSIFICATION + entity_col = "customer_id" + entity_table = "customer" + time_col = "timestamp" + target_col = "churn" + timedelta = pd.Timedelta(days=7) + metrics = [average_precision, accuracy, f1, roc_auc] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + customer = db.table_dict["customer"].df + transactions = db.table_dict["transactions"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + df = duckdb.sql( + f""" + SELECT + timestamp, + customer_id, + CAST( + NOT EXISTS ( + SELECT 1 + FROM transactions + WHERE + transactions.customer_id = customer.customer_id AND + t_dat > timestamp AND + t_dat <= timestamp + INTERVAL '{self.timedelta}' + ) AS INTEGER + ) AS churn + FROM + timestamp_df, + customer, + WHERE + EXISTS ( + SELECT 1 + FROM transactions + WHERE + transactions.customer_id = customer.customer_id AND + t_dat > timestamp - INTERVAL '{self.timedelta}' AND + t_dat <= timestamp + ) + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +class ItemSalesTask(EntityTask): + r"""Predict the total sales for an article (the sum of prices of the associated + transactions) in the next week.""" + + task_type = TaskType.REGRESSION + entity_col = "article_id" + entity_table = "article" + time_col = "timestamp" + target_col = "sales" + timedelta = pd.Timedelta(days=7) + metrics = [r2, mae, rmse] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + transactions = db.table_dict["transactions"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + article = db.table_dict["article"].df + + df = duckdb.sql( + f""" + SELECT + timestamp, + article_id, + sales + FROM + timestamp_df, + article, + ( + SELECT + COALESCE(SUM(price), 0) as sales + FROM + transactions, + WHERE + transactions.article_id = article.article_id AND + t_dat > timestamp AND + t_dat <= timestamp + INTERVAL '{self.timedelta}' + ) + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={"article_id": "article"}, + pkey_col=None, + time_col="timestamp", + ) \ No newline at end of file diff --git a/plexe/relbench/tasks/mimic.py b/plexe/relbench/tasks/mimic.py new file mode 100644 index 00000000..76f62429 --- /dev/null +++ b/plexe/relbench/tasks/mimic.py @@ -0,0 +1,73 @@ +import duckdb +import pandas as pd + +from relbench.base import TaskType +from relbench.base.database import Database +from relbench.base.table import Table +from relbench.base.task_entity import EntityTask +from relbench.metrics import accuracy, average_precision, f1, roc_auc + + +class ICULengthOfStayTask(EntityTask): + r"""Binary classification: Predict if ICU length of stay is ≥ 3 days during the first ICU stay.""" + + task_type = TaskType.BINARY_CLASSIFICATION + entity_col = "subject_id" + entity_table = "patients" + time_col = "intime" + target_col = "los_icu_binary" + timedelta = pd.Timedelta(days=1) + metrics = [average_precision, accuracy, f1, roc_auc] + + def __init__(self, *args, **kwargs): + """Forward all arguments to the base class.""" + super().__init__(*args, **kwargs) + + self.test_timestamp = self.dataset.test_timestamp + self.val_timestamp = self.dataset.val_timestamp + + if self.test_timestamp is not None and self.val_timestamp is not None: + self.num_eval_timestamps = int( + (self.test_timestamp - self.val_timestamp) / self.timedelta + ) + print(f"num_eval_timestamps: {self.num_eval_timestamps}") + self.num_eval_timestamps = max(1, self.num_eval_timestamps) + print(f"num_eval_timestamps: {self.num_eval_timestamps}") + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + icu = db.table_dict["icustays"].df + patients = db.table_dict["patients"].df + + df = duckdb.sql( + f""" + SELECT + t.timestamp as intime, + p.subject_id, + CASE + WHEN i.los_icu >= 3 THEN 1 + ELSE 0 + END as los_icu_binary + FROM + timestamp_df t + LEFT JOIN icu i + + ON i.intime > t.timestamp + AND i.intime <= t.timestamp + INTERVAL '{self.timedelta}' + LEFT JOIN patients p + ON + i.subject_id = p.subject_id + WHERE + i.subject_id IS NOT NULL + AND i.intime IS NOT NULL + AND i.los_icu IS NOT NULL + + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) \ No newline at end of file diff --git a/plexe/relbench/tasks/ratebeer.py b/plexe/relbench/tasks/ratebeer.py new file mode 100644 index 00000000..26534d15 --- /dev/null +++ b/plexe/relbench/tasks/ratebeer.py @@ -0,0 +1,483 @@ +import duckdb +import numpy as np +import pandas as pd +from numpy.typing import NDArray +from scipy.stats import rankdata + +from relbench.base import Database, EntityTask, RecommendationTask, Table, TaskType +from relbench.metrics import ( + accuracy, + average_precision, + f1, + link_prediction_map, + link_prediction_precision, + link_prediction_recall, + mae, + r2, + rmse, + roc_auc, +) + + +def link_prediction_mrr( + pred_isin: NDArray[np.int_], # shape (n_src, k) + dst_count: NDArray[np.int_], # shape (n_src,) +) -> float: + # 1) filter out sources without positives + pos_mask = dst_count > 0 + pred_isin = pred_isin[pos_mask] + dst_count = dst_count[pos_mask] + + reciprocal_ranks = [] + for row in pred_isin: + # find the first correct prediction + hits = np.where(row == 1)[0] + if len(hits): + first_hit_rank = hits[0] + 1 # ranks are 1‑based + reciprocal_ranks.append(1.0 / first_hit_rank) + else: + reciprocal_ranks.append(0.0) + + return float(np.mean(reciprocal_ranks)) + + +# Entity Classification tasks + + +class BeerRatingChurnTask(EntityTask): + r"""Predict whether a beer will receive a rating in the next 90 days.""" + + task_type = TaskType.BINARY_CLASSIFICATION + entity_col = "beer_id" + entity_table = "beers" + time_col = "timestamp" + target_col = "rating_churn" + timedelta = pd.Timedelta(days=90) + metrics = [accuracy, average_precision, f1, roc_auc] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + beers = db.table_dict["beers"].df + beer_ratings = db.table_dict["beer_ratings"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + df = duckdb.sql( + f""" + SELECT + t.timestamp, + b.beer_id AS beer_id, + CAST( + NOT EXISTS ( + SELECT 1 + FROM beer_ratings + WHERE + beer_ratings.beer_id = b.beer_id + AND beer_ratings.created_at > t.timestamp + AND beer_ratings.created_at <= t.timestamp + INTERVAL '{self.timedelta}' + ) AS INTEGER + ) AS rating_churn + FROM + timestamp_df t, + beers b + WHERE + EXISTS ( + SELECT 1 + FROM beer_ratings AS br2 + WHERE + br2.beer_id = b.beer_id + AND br2.created_at > t.timestamp - INTERVAL '{self.timedelta}' + AND br2.created_at <= t.timestamp + ) + GROUP BY + t.timestamp, + b.beer_id + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +class UserRatingChurnTask(EntityTask): + r"""Predict whether a user will give a beer rating in the next 90 days.""" + + task_type = TaskType.BINARY_CLASSIFICATION + entity_col = "user_id" + entity_table = "users" + time_col = "timestamp" + target_col = "user_churn" + timedelta = pd.Timedelta(days=90) + metrics = [accuracy, average_precision, f1, roc_auc] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + users = db.table_dict["users"].df + beer_ratings = db.table_dict["beer_ratings"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + df = duckdb.sql( + f""" + SELECT + t.timestamp, + u.user_id AS user_id, + CAST( + NOT EXISTS ( + SELECT 1 + FROM beer_ratings + WHERE + beer_ratings.user_id = u.user_id + AND beer_ratings.created_at > t.timestamp + AND beer_ratings.created_at <= t.timestamp + INTERVAL '{self.timedelta}' + ) AS INTEGER + ) AS user_churn + FROM + timestamp_df t, + users u + WHERE + EXISTS ( + SELECT 1 + FROM beer_ratings AS br2 + WHERE + br2.user_id = u.user_id + AND br2.created_at > t.timestamp - INTERVAL '{self.timedelta}' + AND br2.created_at <= t.timestamp + ) + GROUP BY + t.timestamp, + u.user_id + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +class BrewerDormantTask(EntityTask): + r"""Predict whether a brewer will release zero beers in the next 365 days.""" + + task_type = TaskType.BINARY_CLASSIFICATION + entity_col = "brewer_id" + entity_table = "brewers" + time_col = "timestamp" + target_col = "dormant" + timedelta = pd.Timedelta(days=365) + metrics = [accuracy, average_precision, f1, roc_auc] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + brewers = db.table_dict["brewers"].df + beers = db.table_dict["beers"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + df = duckdb.sql( + f""" + SELECT + t.timestamp, + brew.brewer_id AS brewer_id, + CAST( + NOT EXISTS ( + SELECT 1 + FROM beers + WHERE + beers.brewer_id = brew.brewer_id + AND beers.created_at > t.timestamp + AND beers.created_at <= t.timestamp + INTERVAL '{self.timedelta}' + ) AS INTEGER + ) AS dormant + FROM + timestamp_df t, + brewers brew + WHERE + EXISTS ( + SELECT 1 + FROM beers AS b2 + WHERE + b2.brewer_id = brew.brewer_id + AND b2.created_at > t.timestamp - INTERVAL '{self.timedelta}' + AND b2.created_at <= t.timestamp + ) + GROUP BY + t.timestamp, + brew.brewer_id + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +# Entity Regression tasks + + +class UserRatingCountTask(EntityTask): + r"""Predict the number of beer ratings that a user will give in the next 90 days.""" + + task_type = TaskType.REGRESSION + entity_col = "user_id" + entity_table = "users" + time_col = "timestamp" + target_col = "num_ratings" + timedelta = pd.Timedelta(days=90) + metrics = [r2, mae, rmse] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + users = db.table_dict["users"].df + beer_ratings = db.table_dict["beer_ratings"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + df = duckdb.sql( + f""" + SELECT + t.timestamp, + u.user_id, + ( + SELECT COUNT(*) + FROM beer_ratings br + WHERE br.user_id = u.user_id + AND br.created_at > t.timestamp + AND br.created_at <= t.timestamp + INTERVAL '{self.timedelta}' + ) AS num_ratings + FROM timestamp_df t + CROSS JOIN users u + WHERE + EXISTS ( + SELECT 1 + FROM beer_ratings AS br2 + WHERE br2.user_id = u.user_id + AND br2.created_at > t.timestamp - INTERVAL '{self.timedelta}' + AND br2.created_at <= t.timestamp + ) + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +# Recommendation tasks + + +class UserFavoriteBeerTask(RecommendationTask): + r"""Predict the list of distinct beers each active user will add to their favorites + in the next 90 days.""" + + task_type = TaskType.LINK_PREDICTION + src_entity_col = "user_id" + src_entity_table = "users" + dst_entity_col = "beer_id" + dst_entity_table = "beers" + time_col = "timestamp" + timedelta = pd.Timedelta(days=90) + metrics = [ + link_prediction_precision, + link_prediction_recall, + link_prediction_map, + link_prediction_mrr, + ] + eval_k = 10 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + users = db.table_dict["users"].df + beers = db.table_dict["beers"].df + favorites = db.table_dict["favorites"].df + beer_ratings = db.table_dict["beer_ratings"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + df = duckdb.sql( + f""" + SELECT + t.timestamp, + f.user_id, + LIST(DISTINCT f.beer_id) AS beer_id + FROM + timestamp_df t + LEFT JOIN + favorites as f + ON + f.created_at > t.timestamp AND + f.created_at <= t.timestamp + INTERVAL '{self.timedelta} days' + WHERE + f.user_id is not null and f.beer_id is not null + AND EXISTS ( + SELECT 1 + FROM beer_ratings as br + WHERE br.user_id = f.user_id + AND br.created_at > t.timestamp - INTERVAL '{self.timedelta} days' + AND br.created_at <= t.timestamp + ) + GROUP BY + t.timestamp, + f.user_id + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={ + self.src_entity_col: self.src_entity_table, + self.dst_entity_col: self.dst_entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) + + +class UserLikedPlaceTask(RecommendationTask): + r"""Predict the list of distinct places each active user rates at least 80.0 / 100.0 + in the next 90 days.""" + + task_type = TaskType.LINK_PREDICTION + src_entity_col = "user_id" + src_entity_table = "users" + dst_entity_col = "place_id" + dst_entity_table = "places" + time_col = "timestamp" + timedelta = pd.Timedelta(days=90) + metrics = [ + link_prediction_precision, + link_prediction_recall, + link_prediction_map, + link_prediction_mrr, + ] + eval_k = 10 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + users = db.table_dict["users"].df + places = db.table_dict["places"].df + place_ratings = db.table_dict["place_ratings"].df + beer_ratings = db.table_dict["beer_ratings"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + df = duckdb.sql( + f""" + SELECT + t.timestamp, + pr.user_id, + LIST(DISTINCT pr.place_id) AS place_id + FROM + timestamp_df t + LEFT JOIN + place_ratings as pr + ON pr.created_at > t.timestamp + AND pr.created_at <= t.timestamp + INTERVAL '{self.timedelta} days' + WHERE + pr.user_id IS NOT NULL and pr.place_id IS NOT NULL + AND pr.total_score >= 80 + AND EXISTS ( + SELECT 1 + FROM place_ratings as pr2 + WHERE pr2.user_id = pr.user_id + AND pr2.created_at > t.timestamp - INTERVAL '{self.timedelta} days' + AND pr2.created_at <= t.timestamp + ) + OR EXISTS ( + SELECT 1 + FROM beer_ratings as br + WHERE br.user_id = pr.user_id + AND br.created_at > t.timestamp - INTERVAL '{self.timedelta} days' + AND br.created_at <= t.timestamp + ) + GROUP BY + t.timestamp, + pr.user_id + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={ + self.src_entity_col: self.src_entity_table, + self.dst_entity_col: self.dst_entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) + + +class UserLikedBeerTask(RecommendationTask): + r"""Predict the list of distinct beers each active user rates at least 4.0 / 5.0 in + the next 90 days.""" + + task_type = TaskType.LINK_PREDICTION + src_entity_col = "user_id" + src_entity_table = "users" + dst_entity_col = "beer_id" + dst_entity_table = "beers" + time_col = "timestamp" + timedelta = pd.Timedelta(days=90) + metrics = [ + link_prediction_precision, + link_prediction_recall, + link_prediction_map, + link_prediction_mrr, + ] + eval_k = 10 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + users = db.table_dict["users"].df + beers = db.table_dict["beers"].df + beer_ratings = db.table_dict["beer_ratings"].df + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + df = duckdb.sql( + f""" + SELECT + t.timestamp, + br.user_id, + LIST(DISTINCT br.beer_id) AS beer_id + FROM + timestamp_df t + LEFT JOIN + beer_ratings as br + ON br.created_at > t.timestamp + AND br.created_at <= t.timestamp + INTERVAL '{self.timedelta} days' + WHERE + br.user_id IS NOT NULL and br.beer_id IS NOT NULL + AND br.total_score >= 4.0 + AND EXISTS ( + SELECT 1 + FROM beer_ratings as br2 + WHERE br2.user_id = br.user_id + AND br2.created_at > t.timestamp - INTERVAL '{self.timedelta} days' + AND br2.created_at <= t.timestamp + ) + GROUP BY + t.timestamp, + br.user_id + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={ + self.src_entity_col: self.src_entity_table, + self.dst_entity_col: self.dst_entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) + + +# Mapping of task names to their corresponding task classes. +tasks_dict = { + "beer-rating-churn": BeerRatingChurnTask, + "user-rating-churn": UserRatingChurnTask, + "brewer-dormant": BrewerDormantTask, + "user-rating-count": UserRatingCountTask, + "user-favorite-beer": UserFavoriteBeerTask, + "user-liked-place": UserLikedPlaceTask, + "user-liked-beer": UserLikedBeerTask, +} \ No newline at end of file diff --git a/plexe/relbench/tasks/stack.py b/plexe/relbench/tasks/stack.py new file mode 100644 index 00000000..d428617e --- /dev/null +++ b/plexe/relbench/tasks/stack.py @@ -0,0 +1,342 @@ +import duckdb +import pandas as pd + +from relbench.base import Database, EntityTask, RecommendationTask, Table, TaskType +from relbench.metrics import ( + accuracy, + average_precision, + f1, + link_prediction_map, + link_prediction_precision, + link_prediction_recall, + mae, + r2, + rmse, + roc_auc, +) + +######## node prediction tasks ######## + + +class UserEngagementTask(EntityTask): + r"""Predict if a user will make any votes/posts/comments in the next 2 years.""" + + task_type = TaskType.BINARY_CLASSIFICATION + entity_col = "OwnerUserId" + entity_table = "users" + time_col = "timestamp" + target_col = "contribution" + timedelta = pd.Timedelta(days=365 // 4) + metrics = [average_precision, accuracy, f1, roc_auc] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + comments = db.table_dict["comments"].df + votes = db.table_dict["votes"].df + posts = db.table_dict["posts"].df + users = db.table_dict["users"].df + + df = duckdb.sql( + f""" + WITH + ALL_ENGAGEMENT AS ( + SELECT + p.id, + p.owneruserid as userid, + p.creationdate + FROM + posts p + UNION + SELECT + v.id, + v.userid, + v.creationdate + FROM + votes v + UNION + SELECT + c.id, + c.userid, + c.creationdate + FROM + comments c + ), + + ACTIVE_USERS AS ( + SELECT + t.timestamp, + u.id, + count(distinct a.id) as n_engagement + FROM timestamp_df t + CROSS JOIN users u + LEFT JOIN all_engagement a + ON u.id = a.UserId + and a.CreationDate <= t.timestamp + WHERE u.id != -1 + GROUP BY t.timestamp, u.id + ) + SELECT + u.timestamp, + u.id as OwnerUserId, + IF(count(distinct a.id) >= 1, 1, 0) as contribution + FROM + active_users u + LEFT JOIN + all_engagement a + ON + u.id = a.UserId AND + a.CreationDate > u.timestamp AND + a.CreationDate <= u.timestamp + INTERVAL '{self.timedelta}' + where + u.n_engagement >= 1 + GROUP BY + u.timestamp, u.id + ; + + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +class PostVotesTask(EntityTask): + r"""Predict the number of upvotes that an existing question will receive in the next + 2 years.""" + + task_type = TaskType.REGRESSION + entity_col = "PostId" + entity_table = "posts" + time_col = "timestamp" + target_col = "popularity" + timedelta = pd.Timedelta(days=365 // 4) + metrics = [r2, mae, rmse] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + votes = db.table_dict["votes"].df + posts = db.table_dict["posts"].df + + df = duckdb.sql( + f""" + SELECT + t.timestamp, + p.id AS PostId, + COUNT(distinct v.id) AS popularity + FROM + timestamp_df t + LEFT JOIN + posts p + ON + p.CreationDate <= t.timestamp AND + p.owneruserid != -1 AND + p.owneruserid is not null AND + p.PostTypeId = 1 + LEFT JOIN + votes v + ON + p.id = v.PostId AND + v.CreationDate > t.timestamp AND + v.CreationDate <= t.timestamp + INTERVAL '{self.timedelta}' AND + v.votetypeid = 2 + GROUP BY + t.timestamp, + p.id + ; + + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +class UserBadgeTask(EntityTask): + r"""Predict if each user will receive in a new badge the next 2 years.""" + + task_type = TaskType.BINARY_CLASSIFICATION + entity_col = "UserId" + entity_table = "users" + time_col = "timestamp" + target_col = "WillGetBadge" + timedelta = pd.Timedelta(days=365 // 4) + metrics = [average_precision, accuracy, f1, roc_auc] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + users = db.table_dict["users"].df + badges = db.table_dict["badges"].df + + df = duckdb.sql( + f""" + SELECT + t.timestamp, + u.Id as UserId, + CASE WHEN + COUNT(b.Id) >= 1 THEN 1 ELSE 0 END AS WillGetBadge + FROM + timestamp_df t + LEFT JOIN + users u + ON + u.CreationDate <= t.timestamp + LEFT JOIN + badges b + ON + u.Id = b.UserID + AND b.Date > t.timestamp + AND b.Date <= t.timestamp + INTERVAL '{self.timedelta}' + GROUP BY + t.timestamp, + u.Id + """ + ).df() + + # remove any IderId rows that are NaN + df = df.dropna(subset=["UserId"]) + df[self.entity_col] = df[self.entity_col].astype( + int + ) # for some reason duckdb returns float64 keys + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +######## link prediction tasks ######## + + +class UserPostCommentTask(RecommendationTask): + r"""Predict a list of existing posts that a user will comment in the next two + years.""" + + task_type = TaskType.LINK_PREDICTION + src_entity_col = "UserId" + src_entity_table = "users" + dst_entity_col = "PostId" + dst_entity_table = "posts" + time_col = "timestamp" + timedelta = pd.Timedelta(days=365 // 4) + metrics = [link_prediction_precision, link_prediction_recall, link_prediction_map] + eval_k = 100 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + r"""Create Task object for UserCommentOnPostTask.""" + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + users = db.table_dict["users"].df + posts = db.table_dict["posts"].df + comments = db.table_dict["comments"].df + + df = duckdb.sql( + f""" + SELECT + t.timestamp, + c.UserId as UserId, + LIST(DISTINCT p.id) AS PostId + FROM + timestamp_df t + LEFT JOIN + posts p + ON + p.CreationDate <= t.timestamp + LEFT JOIN + comments c + ON + p.id = c.PostId AND + c.CreationDate > t.timestamp AND + c.CreationDate <= t.timestamp + INTERVAL '{self.timedelta} days' + WHERE + c.UserId is not null AND + p.owneruserid != -1 AND + p.owneruserid is not null + GROUP BY + t.timestamp, + c.UserId + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={ + self.src_entity_col: self.src_entity_table, + self.dst_entity_col: self.dst_entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) + + +class PostPostRelatedTask(RecommendationTask): + r"""Predict a list of existing posts that users will link a given post to in the + next two years.""" + + task_type = TaskType.LINK_PREDICTION + src_entity_col = "PostId" + src_entity_table = "posts" + dst_entity_col = "postLinksIdList" + dst_entity_table = "posts" + time_col = "timestamp" + timedelta = pd.Timedelta(days=365 // 4) + metrics = [link_prediction_precision, link_prediction_recall, link_prediction_map] + eval_k = 100 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + r"""Create Task object for UserVoteOnPostTask.""" + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + posts = db.table_dict["posts"].df + postLinks = db.table_dict["postLinks"].df + + df = duckdb.sql( + f""" + SELECT + t.timestamp, + pl.PostId as PostId, + LIST(DISTINCT pl.RelatedPostId) AS postLinksIdList + FROM + timestamp_df t + LEFT JOIN + postLinks pl + ON + pl.CreationDate > t.timestamp AND + pl.CreationDate <= t.timestamp + INTERVAL '{self.timedelta} days' + LEFT JOIN + posts p1 + ON + pl.PostId = p1.Id + LEFT JOIN + posts p2 + ON + pl.RelatedPostId = p2.Id + WHERE + pl.PostId IS NOT NULL AND + pl.RelatedPostId IS NOT NULL AND + p1.CreationDate <= t.timestamp AND + p2.CreationDate <= t.timestamp + GROUP BY + t.timestamp, + pl.PostId; + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={ + self.src_entity_col: self.src_entity_table, + self.dst_entity_col: self.dst_entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) \ No newline at end of file diff --git a/plexe/relbench/tasks/trial.py b/plexe/relbench/tasks/trial.py new file mode 100644 index 00000000..00e5094e --- /dev/null +++ b/plexe/relbench/tasks/trial.py @@ -0,0 +1,278 @@ +import duckdb +import pandas as pd + +from relbench.base import Database, EntityTask, RecommendationTask, Table, TaskType +from relbench.metrics import ( + accuracy, + average_precision, + f1, + link_prediction_map, + link_prediction_precision, + link_prediction_recall, + mae, + r2, + rmse, + roc_auc, +) + + +class StudyOutcomeTask(EntityTask): + r"""Predict if the trials in the next 1 year will achieve its primary outcome.""" + + task_type = TaskType.BINARY_CLASSIFICATION + entity_col = "nct_id" + entity_table = "studies" + time_col = "timestamp" + target_col = "outcome" + timedelta = pd.Timedelta(days=365) + metrics = [average_precision, accuracy, f1, roc_auc] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + studies = db.table_dict["studies"].df + outcomes = db.table_dict["outcomes"].df + outcome_analyses = db.table_dict["outcome_analyses"].df + + df = duckdb.sql( + f""" + WITH TRIAL_INFO AS ( + SELECT + oa.nct_id, + oa.p_value, + s.start_date, + oa.date + FROM outcome_analyses oa + LEFT JOIN outcomes o + ON oa.outcome_id = o.id + LEFT JOIN studies s + ON s.nct_id = o.nct_id + where (oa.p_value_modifier is null or oa.p_value_modifier != '>') + and oa.p_value >=0 + and oa.p_value <=1 + and o.outcome_type = 'Primary' + ) + + SELECT + t.timestamp, + tr.nct_id, + CASE + WHEN MIN(tr.p_value) <= 0.05 THEN 1 + ELSE 0 + END AS outcome + FROM timestamp_df t + LEFT JOIN TRIAL_INFO tr + ON tr.start_date <= t.timestamp + and tr.date > t.timestamp + and tr.date <= t.timestamp + INTERVAL '{self.timedelta}' + WHERE tr.nct_id is not null + GROUP BY t.timestamp, tr.nct_id; + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +class StudyAdverseTask(EntityTask): + r"""Predict the number of affected patients with severe advsere events/death for the + trial in the next 1 year.""" + + task_type = TaskType.REGRESSION + entity_col = "nct_id" + entity_table = "studies" + time_col = "timestamp" + target_col = "num_of_adverse_events" + timedelta = pd.Timedelta(days=365) + metrics = [r2, mae, rmse] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + reported_event_totals = db.table_dict["reported_event_totals"].df + studies = db.table_dict["studies"].df + + df = duckdb.sql( + f""" + WITH TRIAL_INFO AS ( + SELECT + r.nct_id, + r.event_type, + r.subjects_affected, + r.date, + s.start_date + FROM reported_event_totals r + LEFT JOIN studies s + ON r.nct_id = s.nct_id + WHERE r.event_type = 'serious' or r.event_type = 'deaths' + and r.subjects_affected is not null + ) + + SELECT + t.timestamp, + tr.nct_id, + sum(tr.subjects_affected) AS num_of_adverse_events + FROM timestamp_df t + LEFT JOIN TRIAL_INFO tr + ON tr.start_date <= t.timestamp + and tr.date > t.timestamp + and tr.date <= t.timestamp + INTERVAL '{self.timedelta}' + WHERE tr.nct_id is not null and tr.subjects_affected is not null + GROUP BY t.timestamp, tr.nct_id; + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +class SiteSuccessTask(EntityTask): + r"""Predict the success rate of a trial site in the next 1 year.""" + + task_type = TaskType.REGRESSION + entity_col = "facility_id" + entity_table = "facilities" + time_col = "timestamp" + target_col = "success_rate" + timedelta = pd.Timedelta(days=365) + metrics = [r2, mae, rmse] + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + facilities = db.table_dict["facilities"].df + facility_study = db.table_dict["facilities_studies"].df + outcome_analyses = db.table_dict["outcome_analyses"].df + studies = db.table_dict["studies"].df + outcomes = db.table_dict["outcomes"].df + + df = duckdb.sql( + f""" + WITH TRIAL_INFO AS ( + SELECT + oa.nct_id, + MIN(CASE WHEN oa.p_value < 0.05 THEN 1 ELSE 0 END) AS is_successful, -- Determine if the trial is successful + oa.date, + FROM outcome_analyses oa + LEFT JOIN outcomes o + ON oa.outcome_id = o.id + WHERE (oa.p_value_modifier is null or oa.p_value_modifier != '>') + and oa.p_value >=0 + and oa.p_value <=1 + and o.outcome_type = 'Primary' + GROUP BY oa.nct_id, oa.date + ) + + SELECT + t.timestamp, + fs.facility_id, + SUM(tr.is_successful)/COUNT(tr.is_successful) AS success_rate + FROM timestamp_df t + LEFT JOIN TRIAL_INFO tr + LEFT JOIN facility_study fs ON fs.nct_id = tr.nct_id + ON tr.date > t.timestamp + and tr.date <= t.timestamp + INTERVAL '{self.timedelta}' + WHERE fs.facility_id is not null + GROUP BY t.timestamp, fs.facility_id; + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) + + +class ConditionSponsorRunTask(RecommendationTask): + r"""Predict whether this condition will have which sponsors.""" + + task_type = TaskType.LINK_PREDICTION + src_entity_col = "condition_id" + src_entity_table = "conditions" + dst_entity_col = "sponsor_id" + dst_entity_table = "sponsors" + time_col = "timestamp" + timedelta = pd.Timedelta(days=365) + metrics = [link_prediction_precision, link_prediction_recall, link_prediction_map] + eval_k = 10 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + sponsors_studies = db.table_dict["sponsors_studies"].df + condition_study = db.table_dict["conditions_studies"].df + + df = duckdb.sql( + f""" + SELECT + t.timestamp, + cs.condition_id, + LIST(DISTINCT ss.sponsor_id) AS sponsor_id + FROM timestamp_df t + LEFT JOIN condition_study cs + LEFT JOIN sponsors_studies ss ON ss.nct_id = cs.nct_id + ON cs.date > t.timestamp + and cs.date <= t.timestamp + INTERVAL '{self.timedelta}' + GROUP BY t.timestamp, cs.condition_id; + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={ + self.src_entity_col: self.src_entity_table, + self.dst_entity_col: self.dst_entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) + + +class SiteSponsorRunTask(RecommendationTask): + r"""Predict whether this sponsor will have a trial in a facility.""" + + task_type = TaskType.LINK_PREDICTION + src_entity_col = "facility_id" + src_entity_table = "facilities" + dst_entity_col = "sponsor_id" + dst_entity_table = "sponsors" + time_col = "timestamp" + timedelta = pd.Timedelta(days=365) + metrics = [link_prediction_precision, link_prediction_recall, link_prediction_map] + eval_k = 10 + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + sponsors_studies = db.table_dict["sponsors_studies"].df + facility_study = db.table_dict["facilities_studies"].df + + df = duckdb.sql( + f""" + SELECT + t.timestamp, + fs.facility_id, + LIST(DISTINCT ss.sponsor_id) AS sponsor_id + FROM timestamp_df t + LEFT JOIN facility_study fs + LEFT JOIN sponsors_studies ss ON ss.nct_id = fs.nct_id + ON fs.date > t.timestamp + and fs.date <= t.timestamp + INTERVAL '{self.timedelta}' + GROUP BY t.timestamp, fs.facility_id; + """ + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={ + self.src_entity_col: self.src_entity_table, + self.dst_entity_col: self.dst_entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) \ No newline at end of file diff --git a/scripts/.python-version b/scripts/.python-version new file mode 100644 index 00000000..c8cfe395 --- /dev/null +++ b/scripts/.python-version @@ -0,0 +1 @@ +3.10 diff --git a/scripts/README.md b/scripts/README.md new file mode 100644 index 00000000..e69de29b diff --git a/scripts/f1_data/circuits.csv b/scripts/f1_data/circuits.csv new file mode 100644 index 00000000..0e8f012c --- /dev/null +++ b/scripts/f1_data/circuits.csv @@ -0,0 +1,78 @@ +circuitId,circuitRef,name,location,country,lat,lng,alt +0,albert_park,Albert Park Grand Prix Circuit,Melbourne,Australia,-37.8497,144.968,10.0 +1,sepang,Sepang International Circuit,Kuala Lumpur,Malaysia,2.76083,101.738,18.0 +2,bahrain,Bahrain International Circuit,Sakhir,Bahrain,26.0325,50.5106,7.0 +3,catalunya,Circuit de Barcelona-Catalunya,Montmeló,Spain,41.57,2.26111,109.0 +4,istanbul,Istanbul Park,Istanbul,Turkey,40.9517,29.405,130.0 +5,monaco,Circuit de Monaco,Monte-Carlo,Monaco,43.7347,7.42056,7.0 +6,villeneuve,Circuit Gilles Villeneuve,Montreal,Canada,45.5,-73.5228,13.0 +7,magny_cours,Circuit de Nevers Magny-Cours,Magny Cours,France,46.8642,3.16361,228.0 +8,silverstone,Silverstone Circuit,Silverstone,UK,52.0786,-1.01694,153.0 +9,hockenheimring,Hockenheimring,Hockenheim,Germany,49.3278,8.56583,103.0 +10,hungaroring,Hungaroring,Budapest,Hungary,47.5789,19.2486,264.0 +11,valencia,Valencia Street Circuit,Valencia,Spain,39.4589,-0.331667,4.0 +12,spa,Circuit de Spa-Francorchamps,Spa,Belgium,50.4372,5.97139,401.0 +13,monza,Autodromo Nazionale di Monza,Monza,Italy,45.6156,9.28111,162.0 +14,marina_bay,Marina Bay Street Circuit,Marina Bay,Singapore,1.2914,103.864,18.0 +15,fuji,Fuji Speedway,Oyama,Japan,35.3717,138.927,583.0 +16,shanghai,Shanghai International Circuit,Shanghai,China,31.3389,121.22,5.0 +17,interlagos,Autódromo José Carlos Pace,São Paulo,Brazil,-23.7036,-46.6997,785.0 +18,indianapolis,Indianapolis Motor Speedway,Indianapolis,USA,39.795,-86.2347,223.0 +19,nurburgring,Nürburgring,Nürburg,Germany,50.3356,6.9475,578.0 +20,imola,Autodromo Enzo e Dino Ferrari,Imola,Italy,44.3439,11.7167,37.0 +21,suzuka,Suzuka Circuit,Suzuka,Japan,34.8431,136.541,45.0 +22,vegas,Las Vegas Strip Street Circuit,Las Vegas,United States,36.1147,-115.173, +23,yas_marina,Yas Marina Circuit,Abu Dhabi,UAE,24.4672,54.6031,3.0 +24,galvez,Autódromo Juan y Oscar Gálvez,Buenos Aires,Argentina,-34.6943,-58.4593,8.0 +25,jerez,Circuito de Jerez,Jerez de la Frontera,Spain,36.7083,-6.03417,37.0 +26,estoril,Autódromo do Estoril,Estoril,Portugal,38.7506,-9.39417,130.0 +27,okayama,Okayama International Circuit,Okayama,Japan,34.915,134.221,266.0 +28,adelaide,Adelaide Street Circuit,Adelaide,Australia,-34.9272,138.617,58.0 +29,kyalami,Kyalami,Midrand,South Africa,-25.9894,28.0767,1460.0 +30,donington,Donington Park,Castle Donington,UK,52.8306,-1.37528,88.0 +31,rodriguez,Autódromo Hermanos Rodríguez,Mexico City,Mexico,19.4042,-99.0907,2227.0 +32,phoenix,Phoenix street circuit,Phoenix,USA,33.4479,-112.075,345.0 +33,ricard,Circuit Paul Ricard,Le Castellet,France,43.2506,5.79167,432.0 +34,yeongam,Korean International Circuit,Yeongam County,Korea,34.7333,126.417,0.0 +35,jacarepagua,Autódromo Internacional Nelson Piquet,Rio de Janeiro,Brazil,-22.9756,-43.395,1126.0 +36,detroit,Detroit Street Circuit,Detroit,USA,42.3298,-83.0401,177.0 +37,brands_hatch,Brands Hatch,Kent,UK,51.3569,0.263056,145.0 +38,zandvoort,Circuit Park Zandvoort,Zandvoort,Netherlands,52.3888,4.54092,6.0 +39,zolder,Zolder,Heusden-Zolder,Belgium,50.9894,5.25694,36.0 +40,dijon,Dijon-Prenois,Dijon,France,47.3625,4.89913,484.0 +41,dallas,Fair Park,Dallas,USA,32.7774,-96.7587,139.0 +42,long_beach,Long Beach,California,USA,33.7651,-118.189,12.0 +43,las_vegas,Las Vegas Street Circuit,Nevada,USA,36.1162,-115.174,639.0 +44,jarama,Jarama,Madrid,Spain,40.6171,-3.58558,609.0 +45,watkins_glen,Watkins Glen,New York State,USA,42.3369,-76.9272,485.0 +46,anderstorp,Scandinavian Raceway,Anderstorp,Sweden,57.2653,13.6042,153.0 +47,mosport,Mosport International Raceway,Ontario,Canada,44.0481,-78.6756,332.0 +48,montjuic,Montjuïc,Barcelona,Spain,41.3664,2.15167,79.0 +49,nivelles,Nivelles-Baulers,Brussels,Belgium,50.6211,4.32694,139.0 +50,charade,Charade Circuit,Clermont-Ferrand,France,45.7472,3.03889,790.0 +51,tremblant,Circuit Mont-Tremblant,Quebec,Canada,46.1877,-74.6099,214.0 +52,essarts,Rouen-Les-Essarts,Rouen,France,49.3306,1.00458,81.0 +53,lemans,Le Mans,Le Mans,France,47.95,0.224231,67.0 +54,reims,Reims-Gueux,Reims,France,49.2542,3.93083,88.0 +55,george,Prince George Circuit,Eastern Cape Province,South Africa,-33.0486,27.8736,15.0 +56,zeltweg,Zeltweg,Styria,Austria,47.2039,14.7478,676.0 +57,aintree,Aintree,Liverpool,UK,53.4769,-2.94056,20.0 +58,boavista,Circuito da Boavista,Oporto,Portugal,41.1705,-8.67325,28.0 +59,riverside,Riverside International Raceway,California,USA,33.937,-117.273,470.0 +60,avus,AVUS,Berlin,Germany,52.4806,13.2514,53.0 +61,monsanto,Monsanto Park Circuit,Lisbon,Portugal,38.7197,-9.20306,158.0 +62,sebring,Sebring International Raceway,Florida,USA,27.4547,-81.3483,18.0 +63,ain-diab,Ain Diab,Casablanca,Morocco,33.5786,-7.6875,19.0 +64,pescara,Pescara Circuit,Pescara,Italy,42.475,14.1508,129.0 +65,bremgarten,Circuit Bremgarten,Bern,Switzerland,46.9589,7.40194,551.0 +66,pedralbes,Circuit de Pedralbes,Barcelona,Spain,41.3903,2.11667,85.0 +67,buddh,Buddh International Circuit,Uttar Pradesh,India,28.3487,77.5331,194.0 +68,americas,Circuit of the Americas,Austin,USA,30.1328,-97.6411,161.0 +69,red_bull_ring,Red Bull Ring,Spielberg,Austria,47.2197,14.7647,678.0 +70,sochi,Sochi Autodrom,Sochi,Russia,43.4057,39.9578,2.0 +71,baku,Baku City Circuit,Baku,Azerbaijan,40.3725,49.8533,-7.0 +72,portimao,Autódromo Internacional do Algarve,Portimão,Portugal,37.227,-8.6267,108.0 +73,mugello,Autodromo Internazionale del Mugello,Mugello,Italy,43.9975,11.3719,255.0 +74,jeddah,Jeddah Corniche Circuit,Jeddah,Saudi Arabia,21.6319,39.1044,15.0 +75,losail,Losail International Circuit,Al Daayen,Qatar,25.49,51.4542, +76,miami,Miami International Autodrome,Miami,USA,25.9581,-80.2389, diff --git a/scripts/f1_data/constructor_results.csv b/scripts/f1_data/constructor_results.csv new file mode 100644 index 00000000..9588f657 --- /dev/null +++ b/scripts/f1_data/constructor_results.csv @@ -0,0 +1,9409 @@ +constructorResultsId,raceId,constructorId,points,date +0,48,103,13.0,1956-01-22 00:00:00 +1,48,5,12.0,1956-01-22 00:00:00 +2,54,126,0.0,1956-08-05 00:00:00 +3,54,103,15.0,1956-08-05 00:00:00 +4,54,5,9.0,1956-08-05 00:00:00 +5,64,85,8.0,1958-01-19 00:00:00 +6,64,5,6.0,1958-01-19 00:00:00 +7,64,103,3.0,1958-01-19 00:00:00 +8,65,125,0.0,1958-05-18 00:00:00 +9,65,123,0.0,1958-05-18 00:00:00 +10,65,103,0.0,1958-05-18 00:00:00 +11,65,31,0.0,1958-05-18 00:00:00 +12,65,116,0.0,1958-05-18 00:00:00 +13,65,5,6.0,1958-05-18 00:00:00 +14,65,85,8.0,1958-05-18 00:00:00 +15,65,64,2.0,1958-05-18 00:00:00 +16,66,93,0.0,1958-05-26 00:00:00 +17,66,103,0.0,1958-05-26 00:00:00 +18,66,5,2.0,1958-05-26 00:00:00 +19,66,31,0.0,1958-05-26 00:00:00 +20,66,64,6.0,1958-05-26 00:00:00 +21,66,116,8.0,1958-05-26 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+2811,319,31,4.0,1979-05-27 00:00:00 +2812,319,0,3.0,1979-05-27 00:00:00 +2813,319,20,1.0,1979-05-27 00:00:00 +2814,319,201,0.0,1979-05-27 00:00:00 +2815,319,3,0.0,1979-05-27 00:00:00 +2816,319,24,0.0,1979-05-27 00:00:00 +2817,319,52,0.0,1979-05-27 00:00:00 +2818,319,55,0.0,1979-05-27 00:00:00 +2819,319,58,0.0,1979-05-27 00:00:00 +2820,319,26,2.0,1979-05-27 00:00:00 +2821,320,2,4.0,1979-07-01 00:00:00 +2822,320,3,13.0,1979-07-01 00:00:00 +2823,320,5,6.0,1979-07-01 00:00:00 +2824,320,24,2.0,1979-07-01 00:00:00 +2825,320,58,0.0,1979-07-01 00:00:00 +2826,320,57,0.0,1979-07-01 00:00:00 +2827,320,0,0.0,1979-07-01 00:00:00 +2828,320,31,0.0,1979-07-01 00:00:00 +2829,320,55,0.0,1979-07-01 00:00:00 +2830,320,52,0.0,1979-07-01 00:00:00 +2831,320,201,0.0,1979-07-01 00:00:00 +2832,320,54,0.0,1979-07-01 00:00:00 +2833,320,49,0.0,1979-07-01 00:00:00 +2834,320,56,0.0,1979-07-01 00:00:00 +2835,320,20,0.0,1979-07-01 00:00:00 +2836,320,26,0.0,1979-07-01 00:00:00 +2837,321,54,0.0,1979-07-14 00:00:00 +2838,321,201,0.0,1979-07-14 00:00:00 +2839,321,52,0.0,1979-07-14 00:00:00 +2840,321,58,0.0,1979-07-14 00:00:00 +2841,321,31,0.0,1979-07-14 00:00:00 +2842,321,20,0.0,1979-07-14 00:00:00 +2843,321,55,0.0,1979-07-14 00:00:00 +2844,321,56,0.0,1979-07-14 00:00:00 +2845,321,57,0.0,1979-07-14 00:00:00 +2846,321,26,1.0,1979-07-14 00:00:00 +2847,321,2,9.0,1979-07-14 00:00:00 +2848,321,3,6.0,1979-07-14 00:00:00 +2849,321,5,2.0,1979-07-14 00:00:00 +2850,321,0,3.0,1979-07-14 00:00:00 +2851,321,24,4.0,1979-07-14 00:00:00 +2852,322,57,0.0,1979-07-29 00:00:00 +2853,322,58,0.0,1979-07-29 00:00:00 +2854,322,55,0.0,1979-07-29 00:00:00 +2855,322,52,0.0,1979-07-29 00:00:00 +2856,322,2,15.0,1979-07-29 00:00:00 +2857,322,26,4.0,1979-07-29 00:00:00 +2858,322,5,3.0,1979-07-29 00:00:00 +2859,322,54,0.0,1979-07-29 00:00:00 +2860,322,0,2.0,1979-07-29 00:00:00 +2861,322,3,0.0,1979-07-29 00:00:00 +2862,322,24,0.0,1979-07-29 00:00:00 +2863,322,56,0.0,1979-07-29 00:00:00 +2864,322,201,0.0,1979-07-29 00:00:00 +2865,322,31,0.0,1979-07-29 00:00:00 +2866,322,20,1.0,1979-07-29 00:00:00 +2867,323,201,0.0,1979-08-12 00:00:00 +2868,323,3,1.0,1979-08-12 00:00:00 +2869,323,26,4.0,1979-08-12 00:00:00 +2870,323,5,9.0,1979-08-12 00:00:00 +2871,323,33,0.0,1979-08-12 00:00:00 +2872,323,2,11.0,1979-08-12 00:00:00 +2873,323,55,0.0,1979-08-12 00:00:00 +2874,323,20,0.0,1979-08-12 00:00:00 +2875,323,56,0.0,1979-08-12 00:00:00 +2876,323,0,0.0,1979-08-12 00:00:00 +2877,323,52,0.0,1979-08-12 00:00:00 +2878,323,57,0.0,1979-08-12 00:00:00 +2879,323,54,0.0,1979-08-12 00:00:00 +2880,323,58,0.0,1979-08-12 00:00:00 +2881,323,31,0.0,1979-08-12 00:00:00 +2882,323,24,0.0,1979-08-12 00:00:00 +2883,324,54,0.0,1979-08-26 00:00:00 +2884,324,31,0.0,1979-08-26 00:00:00 +2885,324,55,0.0,1979-08-26 00:00:00 +2886,324,3,0.0,1979-08-26 00:00:00 +2887,324,20,1.0,1979-08-26 00:00:00 +2888,324,24,0.0,1979-08-26 00:00:00 +2889,324,58,0.0,1979-08-26 00:00:00 +2890,324,52,0.0,1979-08-26 00:00:00 +2891,324,0,0.0,1979-08-26 00:00:00 +2892,324,2,9.0,1979-08-26 00:00:00 +2893,324,5,6.0,1979-08-26 00:00:00 +2894,324,26,6.0,1979-08-26 00:00:00 +2895,324,201,3.0,1979-08-26 00:00:00 +2896,324,57,0.0,1979-08-26 00:00:00 +2897,324,56,0.0,1979-08-26 00:00:00 +2898,325,56,0.0,1979-09-09 00:00:00 +2899,325,0,0.0,1979-09-09 00:00:00 +2900,325,55,0.0,1979-09-09 00:00:00 +2901,325,58,0.0,1979-09-09 00:00:00 +2902,325,60,0.0,1979-09-09 00:00:00 +2903,325,201,3.0,1979-09-09 00:00:00 +2904,325,24,1.0,1979-09-09 00:00:00 +2905,325,52,0.0,1979-09-09 00:00:00 +2906,325,49,0.0,1979-09-09 00:00:00 +2907,325,20,0.0,1979-09-09 00:00:00 +2908,325,3,0.0,1979-09-09 00:00:00 +2909,325,31,2.0,1979-09-09 00:00:00 +2910,325,2,4.0,1979-09-09 00:00:00 +2911,325,57,0.0,1979-09-09 00:00:00 +2912,325,26,0.0,1979-09-09 00:00:00 +2913,325,5,15.0,1979-09-09 00:00:00 +2914,325,54,0.0,1979-09-09 00:00:00 +2915,326,52,0.0,1979-09-30 00:00:00 +2916,326,55,0.0,1979-09-30 00:00:00 +2917,326,57,0.0,1979-09-30 00:00:00 +2918,326,58,0.0,1979-09-30 00:00:00 +2919,326,20,0.0,1979-09-30 00:00:00 +2920,326,26,0.0,1979-09-30 00:00:00 +2921,326,2,13.0,1979-09-30 00:00:00 +2922,326,49,0.0,1979-09-30 00:00:00 +2923,326,31,0.0,1979-09-30 00:00:00 +2924,326,56,0.0,1979-09-30 00:00:00 +2925,326,54,0.0,1979-09-30 00:00:00 +2926,326,179,0.0,1979-09-30 00:00:00 +2927,326,5,9.0,1979-09-30 00:00:00 +2928,326,0,1.0,1979-09-30 00:00:00 +2929,326,24,2.0,1979-09-30 00:00:00 +2930,326,3,0.0,1979-09-30 00:00:00 +2931,326,60,0.0,1979-09-30 00:00:00 +2932,327,0,1.0,1979-10-07 00:00:00 +2933,327,52,2.0,1979-10-07 00:00:00 +2934,327,31,0.0,1979-10-07 00:00:00 +2935,327,57,0.0,1979-10-07 00:00:00 +2936,327,24,4.0,1979-10-07 00:00:00 +2937,327,3,6.0,1979-10-07 00:00:00 +2938,327,5,9.0,1979-10-07 00:00:00 +2939,327,179,0.0,1979-10-07 00:00:00 +2940,327,20,0.0,1979-10-07 00:00:00 +2941,327,54,0.0,1979-10-07 00:00:00 +2942,327,55,0.0,1979-10-07 00:00:00 +2943,327,58,0.0,1979-10-07 00:00:00 +2944,327,60,0.0,1979-10-07 00:00:00 +2945,327,49,0.0,1979-10-07 00:00:00 +2946,327,56,3.0,1979-10-07 00:00:00 +2947,327,26,0.0,1979-10-07 00:00:00 +2948,327,2,0.0,1979-10-07 00:00:00 +2949,328,20,0.0,1980-01-13 00:00:00 +2950,328,43,0.0,1980-01-13 00:00:00 +2951,328,56,0.0,1980-01-13 00:00:00 +2952,328,3,0.0,1980-01-13 00:00:00 +2953,328,31,0.0,1980-01-13 00:00:00 +2954,328,52,0.0,1980-01-13 00:00:00 +2955,328,26,0.0,1980-01-13 00:00:00 +2956,328,24,3.0,1980-01-13 00:00:00 +2957,328,5,0.0,1980-01-13 00:00:00 +2958,328,0,1.0,1980-01-13 00:00:00 +2959,328,49,2.0,1980-01-13 00:00:00 +2960,328,54,4.0,1980-01-13 00:00:00 +2961,328,33,6.0,1980-01-13 00:00:00 +2962,328,2,9.0,1980-01-13 00:00:00 +2963,328,55,0.0,1980-01-13 00:00:00 +2964,329,26,3.0,1980-01-27 00:00:00 +2965,329,3,9.0,1980-01-27 00:00:00 +2966,329,31,6.0,1980-01-27 00:00:00 +2967,329,2,4.0,1980-01-27 00:00:00 +2968,329,0,2.0,1980-01-27 00:00:00 +2969,329,5,0.0,1980-01-27 00:00:00 +2970,329,52,0.0,1980-01-27 00:00:00 +2971,329,33,0.0,1980-01-27 00:00:00 +2972,329,54,0.0,1980-01-27 00:00:00 +2973,329,24,0.0,1980-01-27 00:00:00 +2974,329,49,0.0,1980-01-27 00:00:00 +2975,329,55,0.0,1980-01-27 00:00:00 +2976,329,56,0.0,1980-01-27 00:00:00 +2977,329,43,0.0,1980-01-27 00:00:00 +2978,329,20,1.0,1980-01-27 00:00:00 +2979,330,43,0.0,1980-03-01 00:00:00 +2980,330,5,0.0,1980-03-01 00:00:00 +2981,330,49,0.0,1980-03-01 00:00:00 +2982,330,56,0.0,1980-03-01 00:00:00 +2983,330,31,0.0,1980-03-01 00:00:00 +2984,330,0,0.0,1980-03-01 00:00:00 +2985,330,52,0.0,1980-03-01 00:00:00 +2986,330,54,0.0,1980-03-01 00:00:00 +2987,330,24,0.0,1980-03-01 00:00:00 +2988,330,20,1.0,1980-03-01 00:00:00 +2989,330,2,2.0,1980-03-01 00:00:00 +2990,330,33,3.0,1980-03-01 00:00:00 +2991,330,26,10.0,1980-03-01 00:00:00 +2992,330,55,0.0,1980-03-01 00:00:00 +2993,330,3,9.0,1980-03-01 00:00:00 +2994,331,56,0.0,1980-03-30 00:00:00 +2995,331,52,0.0,1980-03-30 00:00:00 +2996,331,43,0.0,1980-03-30 00:00:00 +2997,331,2,0.0,1980-03-30 00:00:00 +2998,331,49,0.0,1980-03-30 00:00:00 +2999,331,55,0.0,1980-03-30 00:00:00 +3000,331,31,0.0,1980-03-30 00:00:00 +3001,331,24,0.0,1980-03-30 00:00:00 +3002,331,3,0.0,1980-03-30 00:00:00 +3003,331,33,9.0,1980-03-30 00:00:00 +3004,331,20,6.0,1980-03-30 00:00:00 +3005,331,5,2.0,1980-03-30 00:00:00 +3006,331,0,3.0,1980-03-30 00:00:00 +3007,331,26,1.0,1980-03-30 00:00:00 +3008,331,54,4.0,1980-03-30 00:00:00 +3009,332,43,0.0,1980-05-04 00:00:00 +3010,332,56,0.0,1980-05-04 00:00:00 +3011,332,55,0.0,1980-05-04 00:00:00 +3012,332,33,0.0,1980-05-04 00:00:00 +3013,332,49,0.0,1980-05-04 00:00:00 +3014,332,20,0.0,1980-05-04 00:00:00 +3015,332,52,0.0,1980-05-04 00:00:00 +3016,332,31,0.0,1980-05-04 00:00:00 +3017,332,5,1.0,1980-05-04 00:00:00 +3018,332,24,2.0,1980-05-04 00:00:00 +3019,332,3,3.0,1980-05-04 00:00:00 +3020,332,2,10.0,1980-05-04 00:00:00 +3021,332,26,9.0,1980-05-04 00:00:00 +3022,332,0,0.0,1980-05-04 00:00:00 +3023,332,54,0.0,1980-05-04 00:00:00 +3024,333,26,6.0,1980-05-18 00:00:00 +3025,333,2,9.0,1980-05-18 00:00:00 +3026,333,55,0.0,1980-05-18 00:00:00 +3027,333,56,0.0,1980-05-18 00:00:00 +3028,333,43,0.0,1980-05-18 00:00:00 +3029,333,0,0.0,1980-05-18 00:00:00 +3030,333,24,0.0,1980-05-18 00:00:00 +3031,333,49,0.0,1980-05-18 00:00:00 +3032,333,33,4.0,1980-05-18 00:00:00 +3033,333,52,0.0,1980-05-18 00:00:00 +3034,333,31,0.0,1980-05-18 00:00:00 +3035,333,54,1.0,1980-05-18 00:00:00 +3036,333,5,2.0,1980-05-18 00:00:00 +3037,333,20,3.0,1980-05-18 00:00:00 +3038,333,3,0.0,1980-05-18 00:00:00 +3039,334,31,0.0,1980-06-29 00:00:00 +3040,334,49,0.0,1980-06-29 00:00:00 +3041,334,52,0.0,1980-06-29 00:00:00 +3042,334,43,0.0,1980-06-29 00:00:00 +3043,334,54,0.0,1980-06-29 00:00:00 +3044,334,24,0.0,1980-06-29 00:00:00 +3045,334,0,0.0,1980-06-29 00:00:00 +3046,334,5,0.0,1980-06-29 00:00:00 +3047,334,3,2.0,1980-06-29 00:00:00 +3048,334,33,3.0,1980-06-29 00:00:00 +3049,334,26,10.0,1980-06-29 00:00:00 +3050,334,56,0.0,1980-06-29 00:00:00 +3051,334,20,0.0,1980-06-29 00:00:00 +3052,334,2,10.0,1980-06-29 00:00:00 +3053,334,55,0.0,1980-06-29 00:00:00 +3054,335,52,0.0,1980-07-13 00:00:00 +3055,335,33,6.0,1980-07-13 00:00:00 +3056,335,24,5.0,1980-07-13 00:00:00 +3057,335,0,1.0,1980-07-13 00:00:00 +3058,335,20,0.0,1980-07-13 00:00:00 +3059,335,55,0.0,1980-07-13 00:00:00 +3060,335,43,0.0,1980-07-13 00:00:00 +3061,335,49,0.0,1980-07-13 00:00:00 +3062,335,31,0.0,1980-07-13 00:00:00 +3063,335,2,13.0,1980-07-13 00:00:00 +3064,335,26,0.0,1980-07-13 00:00:00 +3065,335,3,0.0,1980-07-13 00:00:00 +3066,335,54,0.0,1980-07-13 00:00:00 +3067,335,5,0.0,1980-07-13 00:00:00 +3068,336,52,0.0,1980-08-10 00:00:00 +3069,336,3,0.0,1980-08-10 00:00:00 +3070,336,43,0.0,1980-08-10 00:00:00 +3071,336,54,0.0,1980-08-10 00:00:00 +3072,336,31,0.0,1980-08-10 00:00:00 +3073,336,0,0.0,1980-08-10 00:00:00 +3074,336,5,1.0,1980-08-10 00:00:00 +3075,336,55,0.0,1980-08-10 00:00:00 +3076,336,20,0.0,1980-08-10 00:00:00 +3077,336,26,9.0,1980-08-10 00:00:00 +3078,336,2,10.0,1980-08-10 00:00:00 +3079,336,33,3.0,1980-08-10 00:00:00 +3080,336,49,2.0,1980-08-10 00:00:00 +3081,336,24,0.0,1980-08-10 00:00:00 +3082,337,55,0.0,1980-08-17 00:00:00 +3083,337,43,0.0,1980-08-17 00:00:00 +3084,337,24,0.0,1980-08-17 00:00:00 +3085,337,49,0.0,1980-08-17 00:00:00 +3086,337,20,0.0,1980-08-17 00:00:00 +3087,337,52,0.0,1980-08-17 00:00:00 +3088,337,54,0.0,1980-08-17 00:00:00 +3089,337,0,0.0,1980-08-17 00:00:00 +3090,337,31,1.0,1980-08-17 00:00:00 +3091,337,33,2.0,1980-08-17 00:00:00 +3092,337,26,3.0,1980-08-17 00:00:00 +3093,337,2,10.0,1980-08-17 00:00:00 +3094,337,3,9.0,1980-08-17 00:00:00 +3095,337,5,0.0,1980-08-17 00:00:00 +3096,338,49,0.0,1980-08-31 00:00:00 +3097,338,43,0.0,1980-08-31 00:00:00 +3098,338,20,0.0,1980-08-31 00:00:00 +3099,338,55,0.0,1980-08-31 00:00:00 +3100,338,54,0.0,1980-08-31 00:00:00 +3101,338,52,0.0,1980-08-31 00:00:00 +3102,338,5,0.0,1980-08-31 00:00:00 +3103,338,0,1.0,1980-08-31 00:00:00 +3104,338,33,9.0,1980-08-31 00:00:00 +3105,338,3,6.0,1980-08-31 00:00:00 +3106,338,26,4.0,1980-08-31 00:00:00 +3107,338,2,3.0,1980-08-31 00:00:00 +3108,338,24,2.0,1980-08-31 00:00:00 +3109,338,31,0.0,1980-08-31 00:00:00 +3110,339,20,0.0,1980-09-14 00:00:00 +3111,339,52,0.0,1980-09-14 00:00:00 +3112,339,24,0.0,1980-09-14 00:00:00 +3113,339,43,0.0,1980-09-14 00:00:00 +3114,339,3,0.0,1980-09-14 00:00:00 +3115,339,55,0.0,1980-09-14 00:00:00 +3116,339,0,0.0,1980-09-14 00:00:00 +3117,339,26,1.0,1980-09-14 00:00:00 +3118,339,31,3.0,1980-09-14 00:00:00 +3119,339,2,10.0,1980-09-14 00:00:00 +3120,339,33,9.0,1980-09-14 00:00:00 +3121,339,5,0.0,1980-09-14 00:00:00 +3122,339,54,2.0,1980-09-14 00:00:00 +3123,339,49,0.0,1980-09-14 00:00:00 +3124,340,2,15.0,1980-09-28 00:00:00 +3125,340,0,3.0,1980-09-28 00:00:00 +3126,340,5,2.0,1980-09-28 00:00:00 +3127,340,33,1.0,1980-09-28 00:00:00 +3128,340,24,0.0,1980-09-28 00:00:00 +3129,340,54,0.0,1980-09-28 00:00:00 +3130,340,31,0.0,1980-09-28 00:00:00 +3131,340,20,0.0,1980-09-28 00:00:00 +3132,340,55,0.0,1980-09-28 00:00:00 +3133,340,3,0.0,1980-09-28 00:00:00 +3134,340,49,0.0,1980-09-28 00:00:00 +3135,340,43,0.0,1980-09-28 00:00:00 +3136,340,52,0.0,1980-09-28 00:00:00 +3137,340,26,4.0,1980-09-28 00:00:00 +3138,341,2,15.0,1980-10-05 00:00:00 +3139,341,31,4.0,1980-10-05 00:00:00 +3140,341,3,0.0,1980-10-05 00:00:00 +3141,341,52,0.0,1980-10-05 00:00:00 +3142,341,54,0.0,1980-10-05 00:00:00 +3143,341,5,0.0,1980-10-05 00:00:00 +3144,341,0,0.0,1980-10-05 00:00:00 +3145,341,24,0.0,1980-10-05 00:00:00 +3146,341,20,0.0,1980-10-05 00:00:00 +3147,341,49,0.0,1980-10-05 00:00:00 +3148,341,33,0.0,1980-10-05 00:00:00 +3149,341,43,0.0,1980-10-05 00:00:00 +3150,341,55,0.0,1980-10-05 00:00:00 +3151,341,26,6.0,1980-10-05 00:00:00 +3152,342,36,0.0,1981-03-15 00:00:00 +3153,342,49,3.0,1981-03-15 00:00:00 +3154,342,5,0.0,1981-03-15 00:00:00 +3155,342,31,0.0,1981-03-15 00:00:00 +3156,342,43,0.0,1981-03-15 00:00:00 +3157,342,20,0.0,1981-03-15 00:00:00 +3158,342,52,0.0,1981-03-15 00:00:00 +3159,342,26,0.0,1981-03-15 00:00:00 +3160,342,0,0.0,1981-03-15 00:00:00 +3161,342,2,15.0,1981-03-15 00:00:00 +3162,342,3,0.0,1981-03-15 00:00:00 +3163,342,54,0.0,1981-03-15 00:00:00 +3164,342,53,1.0,1981-03-15 00:00:00 +3165,342,24,2.0,1981-03-15 00:00:00 +3166,342,33,4.0,1981-03-15 00:00:00 +3167,342,55,0.0,1981-03-15 00:00:00 +3168,343,2,15.0,1981-03-29 00:00:00 +3169,343,20,4.0,1981-03-29 00:00:00 +3170,343,31,2.0,1981-03-29 00:00:00 +3171,343,55,3.0,1981-03-29 00:00:00 +3172,343,26,1.0,1981-03-29 00:00:00 +3173,343,0,0.0,1981-03-29 00:00:00 +3174,343,54,0.0,1981-03-29 00:00:00 +3175,343,53,0.0,1981-03-29 00:00:00 +3176,343,33,0.0,1981-03-29 00:00:00 +3177,343,24,0.0,1981-03-29 00:00:00 +3178,343,49,0.0,1981-03-29 00:00:00 +3179,343,5,0.0,1981-03-29 00:00:00 +3180,343,3,0.0,1981-03-29 00:00:00 +3181,343,52,0.0,1981-03-29 00:00:00 +3182,343,43,0.0,1981-03-29 00:00:00 +3183,343,36,0.0,1981-03-29 00:00:00 +3184,344,49,0.0,1981-04-12 00:00:00 +3185,344,33,9.0,1981-04-12 00:00:00 +3186,344,2,9.0,1981-04-12 00:00:00 +3187,344,3,6.0,1981-04-12 00:00:00 +3188,344,36,0.0,1981-04-12 00:00:00 +3189,344,43,0.0,1981-04-12 00:00:00 +3190,344,55,0.0,1981-04-12 00:00:00 +3191,344,26,0.0,1981-04-12 00:00:00 +3192,344,54,0.0,1981-04-12 00:00:00 +3193,344,53,0.0,1981-04-12 00:00:00 +3194,344,31,1.0,1981-04-12 00:00:00 +3195,344,24,0.0,1981-04-12 00:00:00 +3196,344,52,0.0,1981-04-12 00:00:00 +3197,344,0,0.0,1981-04-12 00:00:00 +3198,344,20,0.0,1981-04-12 00:00:00 +3199,344,5,0.0,1981-04-12 00:00:00 +3200,345,0,1.0,1981-05-03 00:00:00 +3201,345,53,0.0,1981-05-03 00:00:00 +3202,345,31,0.0,1981-05-03 00:00:00 +3203,345,33,12.0,1981-05-03 00:00:00 +3204,345,20,6.0,1981-05-03 00:00:00 +3205,345,2,4.0,1981-05-03 00:00:00 +3206,345,5,2.0,1981-05-03 00:00:00 +3207,345,3,0.0,1981-05-03 00:00:00 +3208,345,55,0.0,1981-05-03 00:00:00 +3209,345,51,0.0,1981-05-03 00:00:00 +3210,345,52,0.0,1981-05-03 00:00:00 +3211,345,26,0.0,1981-05-03 00:00:00 +3212,345,36,0.0,1981-05-03 00:00:00 +3213,345,24,0.0,1981-05-03 00:00:00 +3214,345,43,0.0,1981-05-03 00:00:00 +3215,345,49,0.0,1981-05-03 00:00:00 +3216,345,54,0.0,1981-05-03 00:00:00 +3217,346,26,6.0,1981-05-17 00:00:00 +3218,346,2,9.0,1981-05-17 00:00:00 +3219,346,31,6.0,1981-05-17 00:00:00 +3220,346,51,0.0,1981-05-17 00:00:00 +3221,346,5,3.0,1981-05-17 00:00:00 +3222,346,24,1.0,1981-05-17 00:00:00 +3223,346,0,0.0,1981-05-17 00:00:00 +3224,346,49,0.0,1981-05-17 00:00:00 +3225,346,55,0.0,1981-05-17 00:00:00 +3226,346,43,0.0,1981-05-17 00:00:00 +3227,346,33,0.0,1981-05-17 00:00:00 +3228,346,54,0.0,1981-05-17 00:00:00 +3229,346,3,0.0,1981-05-17 00:00:00 +3230,346,20,0.0,1981-05-17 00:00:00 +3231,346,36,0.0,1981-05-17 00:00:00 +3232,346,52,0.0,1981-05-17 00:00:00 +3233,346,53,0.0,1981-05-17 00:00:00 +3234,347,26,4.0,1981-05-31 00:00:00 +3235,347,24,2.0,1981-05-31 00:00:00 +3236,347,51,0.0,1981-05-31 00:00:00 +3237,347,36,0.0,1981-05-31 00:00:00 +3238,347,52,0.0,1981-05-31 00:00:00 +3239,347,43,0.0,1981-05-31 00:00:00 +3240,347,54,0.0,1981-05-31 00:00:00 +3241,347,20,0.0,1981-05-31 00:00:00 +3242,347,31,0.0,1981-05-31 00:00:00 +3243,347,3,0.0,1981-05-31 00:00:00 +3244,347,2,6.0,1981-05-31 00:00:00 +3245,347,0,0.0,1981-05-31 00:00:00 +3246,347,33,0.0,1981-05-31 00:00:00 +3247,347,53,0.0,1981-05-31 00:00:00 +3248,347,55,1.0,1981-05-31 00:00:00 +3249,347,5,12.0,1981-05-31 00:00:00 +3250,347,49,0.0,1981-05-31 00:00:00 +3251,348,52,0.0,1981-06-21 00:00:00 +3252,348,5,9.0,1981-06-21 00:00:00 +3253,348,0,4.0,1981-06-21 00:00:00 +3254,348,2,3.0,1981-06-21 00:00:00 +3255,348,31,3.0,1981-06-21 00:00:00 +3256,348,26,6.0,1981-06-21 00:00:00 +3257,348,3,0.0,1981-06-21 00:00:00 +3258,348,51,0.0,1981-06-21 00:00:00 +3259,348,54,0.0,1981-06-21 00:00:00 +3260,348,49,0.0,1981-06-21 00:00:00 +3261,348,55,0.0,1981-06-21 00:00:00 +3262,348,36,0.0,1981-06-21 00:00:00 +3263,348,24,0.0,1981-06-21 00:00:00 +3264,348,33,0.0,1981-06-21 00:00:00 +3265,348,20,0.0,1981-06-21 00:00:00 +3266,348,43,0.0,1981-06-21 00:00:00 +3267,348,53,0.0,1981-06-21 00:00:00 +3268,349,0,6.0,1981-07-05 00:00:00 +3269,349,33,4.0,1981-07-05 00:00:00 +3270,349,5,2.0,1981-07-05 00:00:00 +3271,349,31,1.0,1981-07-05 00:00:00 +3272,349,49,0.0,1981-07-05 00:00:00 +3273,349,2,0.0,1981-07-05 00:00:00 +3274,349,24,0.0,1981-07-05 00:00:00 +3275,349,53,0.0,1981-07-05 00:00:00 +3276,349,26,0.0,1981-07-05 00:00:00 +3277,349,36,0.0,1981-07-05 00:00:00 +3278,349,54,0.0,1981-07-05 00:00:00 +3279,349,55,0.0,1981-07-05 00:00:00 +3280,349,51,0.0,1981-07-05 00:00:00 +3281,349,3,12.0,1981-07-05 00:00:00 +3282,349,43,0.0,1981-07-05 00:00:00 +3283,349,20,0.0,1981-07-05 00:00:00 +3284,349,52,0.0,1981-07-05 00:00:00 +3285,350,5,0.0,1981-07-18 00:00:00 +3286,350,0,9.0,1981-07-18 00:00:00 +3287,350,2,6.0,1981-07-18 00:00:00 +3288,350,26,4.0,1981-07-18 00:00:00 +3289,350,24,3.0,1981-07-18 00:00:00 +3290,350,33,2.0,1981-07-18 00:00:00 +3291,350,36,0.0,1981-07-18 00:00:00 +3292,350,43,0.0,1981-07-18 00:00:00 +3293,350,3,0.0,1981-07-18 00:00:00 +3294,350,20,0.0,1981-07-18 00:00:00 +3295,350,53,0.0,1981-07-18 00:00:00 +3296,350,49,0.0,1981-07-18 00:00:00 +3297,350,54,0.0,1981-07-18 00:00:00 +3298,350,31,0.0,1981-07-18 00:00:00 +3299,350,51,0.0,1981-07-18 00:00:00 +3300,350,52,1.0,1981-07-18 00:00:00 +3301,350,55,0.0,1981-07-18 00:00:00 +3302,351,53,0.0,1981-08-02 00:00:00 +3303,351,51,0.0,1981-08-02 00:00:00 +3304,351,54,0.0,1981-08-02 00:00:00 +3305,351,36,0.0,1981-08-02 00:00:00 +3306,351,52,0.0,1981-08-02 00:00:00 +3307,351,55,0.0,1981-08-02 00:00:00 +3308,351,20,0.0,1981-08-02 00:00:00 +3309,351,2,0.0,1981-08-02 00:00:00 +3310,351,5,0.0,1981-08-02 00:00:00 +3311,351,43,0.0,1981-08-02 00:00:00 +3312,351,31,0.0,1981-08-02 00:00:00 +3313,351,0,1.0,1981-08-02 00:00:00 +3314,351,24,2.0,1981-08-02 00:00:00 +3315,351,26,4.0,1981-08-02 00:00:00 +3316,351,3,6.0,1981-08-02 00:00:00 +3317,351,33,12.0,1981-08-02 00:00:00 +3318,351,49,0.0,1981-08-02 00:00:00 +3319,352,20,0.0,1981-08-16 00:00:00 +3320,352,52,0.0,1981-08-16 00:00:00 +3321,352,55,0.0,1981-08-16 00:00:00 +3322,352,51,0.0,1981-08-16 00:00:00 +3323,352,53,0.0,1981-08-16 00:00:00 +3324,352,49,0.0,1981-08-16 00:00:00 +3325,352,24,0.0,1981-08-16 00:00:00 +3326,352,36,0.0,1981-08-16 00:00:00 +3327,352,5,0.0,1981-08-16 00:00:00 +3328,352,31,0.0,1981-08-16 00:00:00 +3329,352,0,1.0,1981-08-16 00:00:00 +3330,352,2,5.0,1981-08-16 00:00:00 +3331,352,33,4.0,1981-08-16 00:00:00 +3332,352,3,6.0,1981-08-16 00:00:00 +3333,352,26,9.0,1981-08-16 00:00:00 +3334,352,43,0.0,1981-08-16 00:00:00 +3335,353,51,0.0,1981-08-30 00:00:00 +3336,353,36,0.0,1981-08-30 00:00:00 +3337,353,26,0.0,1981-08-30 00:00:00 +3338,353,43,0.0,1981-08-30 00:00:00 +3339,353,0,0.0,1981-08-30 00:00:00 +3340,353,49,0.0,1981-08-30 00:00:00 +3341,353,52,0.0,1981-08-30 00:00:00 +3342,353,55,1.0,1981-08-30 00:00:00 +3343,353,53,0.0,1981-08-30 00:00:00 +3344,353,20,0.0,1981-08-30 00:00:00 +3345,353,31,2.0,1981-08-30 00:00:00 +3346,353,2,4.0,1981-08-30 00:00:00 +3347,353,33,9.0,1981-08-30 00:00:00 +3348,353,3,9.0,1981-08-30 00:00:00 +3349,353,24,0.0,1981-08-30 00:00:00 +3350,353,54,0.0,1981-08-30 00:00:00 +3351,353,5,0.0,1981-08-30 00:00:00 +3352,354,2,10.0,1981-09-13 00:00:00 +3353,354,31,3.0,1981-09-13 00:00:00 +3354,354,54,0.0,1981-09-13 00:00:00 +3355,354,53,0.0,1981-09-13 00:00:00 +3356,354,52,0.0,1981-09-13 00:00:00 +3357,354,55,0.0,1981-09-13 00:00:00 +3358,354,20,0.0,1981-09-13 00:00:00 +3359,354,26,0.0,1981-09-13 00:00:00 +3360,354,36,0.0,1981-09-13 00:00:00 +3361,354,24,0.0,1981-09-13 00:00:00 +3362,354,43,0.0,1981-09-13 00:00:00 +3363,354,49,0.0,1981-09-13 00:00:00 +3364,354,0,0.0,1981-09-13 00:00:00 +3365,354,33,1.0,1981-09-13 00:00:00 +3366,354,5,2.0,1981-09-13 00:00:00 +3367,354,3,9.0,1981-09-13 00:00:00 +3368,354,51,0.0,1981-09-13 00:00:00 +3369,355,24,0.0,1981-09-27 00:00:00 +3370,355,51,0.0,1981-09-27 00:00:00 +3371,355,54,0.0,1981-09-27 00:00:00 +3372,355,20,0.0,1981-09-27 00:00:00 +3373,355,55,0.0,1981-09-27 00:00:00 +3374,355,52,0.0,1981-09-27 00:00:00 +3375,355,3,0.0,1981-09-27 00:00:00 +3376,355,2,0.0,1981-09-27 00:00:00 +3377,355,43,0.0,1981-09-27 00:00:00 +3378,355,36,0.0,1981-09-27 00:00:00 +3379,355,31,1.0,1981-09-27 00:00:00 +3380,355,33,2.0,1981-09-27 00:00:00 +3381,355,49,3.0,1981-09-27 00:00:00 +3382,355,5,4.0,1981-09-27 00:00:00 +3383,355,0,6.0,1981-09-27 00:00:00 +3384,355,26,9.0,1981-09-27 00:00:00 +3385,355,53,0.0,1981-09-27 00:00:00 +3386,356,36,0.0,1981-10-17 00:00:00 +3387,356,52,0.0,1981-10-17 00:00:00 +3388,356,43,0.0,1981-10-17 00:00:00 +3389,356,53,0.0,1981-10-17 00:00:00 +3390,356,51,0.0,1981-10-17 00:00:00 +3391,356,55,0.0,1981-10-17 00:00:00 +3392,356,24,0.0,1981-10-17 00:00:00 +3393,356,20,0.0,1981-10-17 00:00:00 +3394,356,54,0.0,1981-10-17 00:00:00 +3395,356,0,0.0,1981-10-17 00:00:00 +3396,356,26,1.0,1981-10-17 00:00:00 +3397,356,33,2.0,1981-10-17 00:00:00 +3398,356,31,3.0,1981-10-17 00:00:00 +3399,356,49,4.0,1981-10-17 00:00:00 +3400,356,3,6.0,1981-10-17 00:00:00 +3401,356,2,9.0,1981-10-17 00:00:00 +3402,356,5,0.0,1981-10-17 00:00:00 +3403,357,54,0.0,1982-01-23 00:00:00 +3404,357,55,0.0,1982-01-23 00:00:00 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00:00:00 +3355,310,31,86.0,1,8,1978-09-10 00:00:00 +3356,310,20,8.0,9,0,1978-09-10 00:00:00 +3357,310,53,0.0,18,0,1978-09-10 00:00:00 +3358,310,58,0.0,17,0,1978-09-10 00:00:00 +3359,310,55,0.0,15,0,1978-09-10 00:00:00 +3360,310,63,0.0,14,0,1978-09-10 00:00:00 +3361,310,62,0.0,19,0,1978-09-10 00:00:00 +3362,310,24,36.0,4,1,1978-09-10 00:00:00 +3363,310,3,0.0,16,0,1978-09-10 00:00:00 +3364,310,61,1.0,12,0,1978-09-10 00:00:00 +3365,311,53,0.0,18,0,1978-10-01 00:00:00 +3366,311,3,3.0,12,0,1978-10-01 00:00:00 +3367,311,2,11.0,9,0,1978-10-01 00:00:00 +3368,311,61,1.0,13,0,1978-10-01 00:00:00 +3369,311,26,19.0,5,0,1978-10-01 00:00:00 +3370,311,62,0.0,19,0,1978-10-01 00:00:00 +3371,311,63,0.0,16,0,1978-10-01 00:00:00 +3372,311,55,0.0,15,0,1978-10-01 00:00:00 +3373,311,58,0.0,17,0,1978-10-01 00:00:00 +3374,311,52,0.0,14,0,1978-10-01 00:00:00 +3375,311,56,6.0,11,0,1978-10-01 00:00:00 +3376,311,54,17.0,7,0,1978-10-01 00:00:00 +3377,311,5,49.0,3,4,1978-10-01 00:00:00 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00:00:00 +3402,312,61,1.0,13,0,1978-10-08 00:00:00 +3403,313,31,8.0,2,0,1979-01-21 00:00:00 +3404,313,5,0.0,9,0,1979-01-21 00:00:00 +3405,313,24,0.0,11,0,1979-01-21 00:00:00 +3406,313,52,0.0,15,0,1979-01-21 00:00:00 +3407,313,58,0.0,14,0,1979-01-21 00:00:00 +3408,313,26,12.0,1,1,1979-01-21 00:00:00 +3409,313,3,0.0,12,0,1979-01-21 00:00:00 +3410,313,0,4.0,3,0,1979-01-21 00:00:00 +3411,313,54,1.0,4,0,1979-01-21 00:00:00 +3412,313,56,0.0,5,0,1979-01-21 00:00:00 +3413,313,57,0.0,10,0,1979-01-21 00:00:00 +3414,313,55,0.0,8,0,1979-01-21 00:00:00 +3415,313,20,0.0,6,0,1979-01-21 00:00:00 +3416,313,201,0.0,13,0,1979-01-21 00:00:00 +3417,313,2,0.0,7,0,1979-01-21 00:00:00 +3418,314,201,0.0,14,0,1979-02-04 00:00:00 +3419,314,58,0.0,15,0,1979-02-04 00:00:00 +3420,314,52,0.0,13,0,1979-02-04 00:00:00 +3421,314,26,27.0,1,2,1979-02-04 00:00:00 +3422,314,56,0.0,8,0,1979-02-04 00:00:00 +3423,314,20,0.0,7,0,1979-02-04 00:00:00 +3424,314,54,1.0,6,0,1979-02-04 00:00:00 +3425,314,0,4.0,3,0,1979-02-04 00:00:00 +3426,314,31,12.0,2,0,1979-02-04 00:00:00 +3427,314,2,0.0,9,0,1979-02-04 00:00:00 +3428,314,55,0.0,11,0,1979-02-04 00:00:00 +3429,314,5,3.0,5,0,1979-02-04 00:00:00 +3430,314,57,0.0,12,0,1979-02-04 00:00:00 +3431,314,24,3.0,4,0,1979-02-04 00:00:00 +3432,314,3,0.0,10,0,1979-02-04 00:00:00 +3433,315,201,1.0,6,0,1979-03-03 00:00:00 +3434,315,58,0.0,15,0,1979-03-03 00:00:00 +3435,315,26,27.0,1,2,1979-03-03 00:00:00 +3436,315,31,17.0,3,0,1979-03-03 00:00:00 +3437,315,0,4.0,5,0,1979-03-03 00:00:00 +3438,315,54,1.0,7,0,1979-03-03 00:00:00 +3439,315,56,0.0,9,0,1979-03-03 00:00:00 +3440,315,20,0.0,8,0,1979-03-03 00:00:00 +3441,315,2,0.0,11,0,1979-03-03 00:00:00 +3442,315,55,0.0,13,0,1979-03-03 00:00:00 +3443,315,5,18.0,2,1,1979-03-03 00:00:00 +3444,315,57,0.0,10,0,1979-03-03 00:00:00 +3445,315,24,7.0,4,0,1979-03-03 00:00:00 +3446,315,3,0.0,12,0,1979-03-03 00:00:00 +3447,315,52,0.0,14,0,1979-03-03 00:00:00 +3448,316,201,1.0,7,0,1979-04-08 00:00:00 +3449,316,3,0.0,12,0,1979-04-08 00:00:00 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+3570,323,55,0.0,14,0,1979-08-12 00:00:00 +3571,323,57,0.0,12,0,1979-08-12 00:00:00 +3572,323,24,21.0,5,0,1979-08-12 00:00:00 +3573,323,58,0.0,16,0,1979-08-12 00:00:00 +3574,323,52,0.0,13,0,1979-08-12 00:00:00 +3575,323,59,0.0,17,0,1979-08-12 00:00:00 +3576,323,49,0.0,15,0,1979-08-12 00:00:00 +3577,323,26,55.0,2,3,1979-08-12 00:00:00 +3578,323,5,74.0,1,4,1979-08-12 00:00:00 +3579,323,3,20.0,6,1,1979-08-12 00:00:00 +3580,323,201,1.0,9,0,1979-08-12 00:00:00 +3581,324,59,0.0,17,0,1979-08-26 00:00:00 +3582,324,55,0.0,14,0,1979-08-26 00:00:00 +3583,324,56,0.0,11,0,1979-08-26 00:00:00 +3584,324,0,13.0,7,0,1979-08-26 00:00:00 +3585,324,26,61.0,2,3,1979-08-26 00:00:00 +3586,324,52,0.0,13,0,1979-08-26 00:00:00 +3587,324,31,37.0,4,0,1979-08-26 00:00:00 +3588,324,54,1.0,10,0,1979-08-26 00:00:00 +3589,324,58,0.0,16,0,1979-08-26 00:00:00 +3590,324,2,58.0,3,4,1979-08-26 00:00:00 +3591,324,5,80.0,1,4,1979-08-26 00:00:00 +3592,324,49,0.0,15,0,1979-08-26 00:00:00 +3593,324,201,4.0,9,0,1979-08-26 00:00:00 +3594,324,3,20.0,6,1,1979-08-26 00:00:00 +3595,324,24,21.0,5,0,1979-08-26 00:00:00 +3596,324,57,0.0,12,0,1979-08-26 00:00:00 +3597,324,20,5.0,8,0,1979-08-26 00:00:00 +3598,325,26,61.0,3,3,1979-09-09 00:00:00 +3599,325,31,39.0,4,0,1979-09-09 00:00:00 +3600,325,20,5.0,9,0,1979-09-09 00:00:00 +3601,325,0,13.0,7,0,1979-09-09 00:00:00 +3602,325,56,0.0,11,0,1979-09-09 00:00:00 +3603,325,2,62.0,2,4,1979-09-09 00:00:00 +3604,325,5,95.0,1,5,1979-09-09 00:00:00 +3605,325,57,0.0,12,0,1979-09-09 00:00:00 +3606,325,24,22.0,5,0,1979-09-09 00:00:00 +3607,325,3,20.0,6,1,1979-09-09 00:00:00 +3608,325,58,0.0,16,0,1979-09-09 00:00:00 +3609,325,52,0.0,13,0,1979-09-09 00:00:00 +3610,325,54,1.0,10,0,1979-09-09 00:00:00 +3611,325,59,0.0,17,0,1979-09-09 00:00:00 +3612,325,49,0.0,15,0,1979-09-09 00:00:00 +3613,325,60,0.0,18,0,1979-09-09 00:00:00 +3614,325,55,0.0,14,0,1979-09-09 00:00:00 +3615,325,201,7.0,8,0,1979-09-09 00:00:00 +3616,326,54,1.0,10,0,1979-09-30 00:00:00 +3617,326,179,0.0,12,0,1979-09-30 00:00:00 +3618,326,56,0.0,11,0,1979-09-30 00:00:00 +3619,326,0,14.0,7,0,1979-09-30 00:00:00 +3620,326,31,39.0,4,0,1979-09-30 00:00:00 +3621,326,26,61.0,3,3,1979-09-30 00:00:00 +3622,326,20,5.0,9,0,1979-09-30 00:00:00 +3623,326,55,0.0,15,0,1979-09-30 00:00:00 +3624,326,5,104.0,1,5,1979-09-30 00:00:00 +3625,326,57,0.0,13,0,1979-09-30 00:00:00 +3626,326,2,75.0,2,5,1979-09-30 00:00:00 +3627,326,3,20.0,6,1,1979-09-30 00:00:00 +3628,326,201,7.0,8,0,1979-09-30 00:00:00 +3629,326,58,0.0,18,0,1979-09-30 00:00:00 +3630,326,52,0.0,14,0,1979-09-30 00:00:00 +3631,326,59,0.0,19,0,1979-09-30 00:00:00 +3632,326,49,0.0,16,0,1979-09-30 00:00:00 +3633,326,60,0.0,17,0,1979-09-30 00:00:00 +3634,326,24,24.0,5,0,1979-09-30 00:00:00 +3635,327,56,3.0,10,0,1979-10-07 00:00:00 +3636,327,26,61.0,3,3,1979-10-07 00:00:00 +3637,327,31,39.0,4,0,1979-10-07 00:00:00 +3638,327,54,1.0,12,0,1979-10-07 00:00:00 +3639,327,20,5.0,9,0,1979-10-07 00:00:00 +3640,327,0,15.0,7,0,1979-10-07 00:00:00 +3641,327,2,75.0,2,5,1979-10-07 00:00:00 +3642,327,3,26.0,6,1,1979-10-07 00:00:00 +3643,327,5,113.0,1,6,1979-10-07 00:00:00 +3644,327,179,0.0,13,0,1979-10-07 00:00:00 +3645,327,60,0.0,17,0,1979-10-07 00:00:00 +3646,327,55,0.0,15,0,1979-10-07 00:00:00 +3647,327,59,0.0,19,0,1979-10-07 00:00:00 +3648,327,52,2.0,11,0,1979-10-07 00:00:00 +3649,327,49,0.0,16,0,1979-10-07 00:00:00 +3650,327,201,7.0,8,0,1979-10-07 00:00:00 +3651,327,24,28.0,5,0,1979-10-07 00:00:00 +3652,327,57,0.0,14,0,1979-10-07 00:00:00 +3653,327,58,0.0,18,0,1979-10-07 00:00:00 +3654,328,20,0.0,10,0,1980-01-13 00:00:00 +3655,328,43,0.0,15,0,1980-01-13 00:00:00 +3656,328,56,0.0,14,0,1980-01-13 00:00:00 +3657,328,3,0.0,13,0,1980-01-13 00:00:00 +3658,328,31,0.0,12,0,1980-01-13 00:00:00 +3659,328,52,0.0,11,0,1980-01-13 00:00:00 +3660,328,26,0.0,9,0,1980-01-13 00:00:00 +3661,328,24,3.0,4,0,1980-01-13 00:00:00 +3662,328,5,0.0,7,0,1980-01-13 00:00:00 +3663,328,0,1.0,6,0,1980-01-13 00:00:00 +3664,328,49,2.0,5,0,1980-01-13 00:00:00 +3665,328,54,4.0,3,0,1980-01-13 00:00:00 +3666,328,33,6.0,2,0,1980-01-13 00:00:00 +3667,328,2,9.0,1,1,1980-01-13 00:00:00 +3668,328,55,0.0,8,0,1980-01-13 00:00:00 +3669,329,43,0.0,15,0,1980-01-27 00:00:00 +3670,329,56,0.0,14,0,1980-01-27 00:00:00 +3671,329,3,9.0,2,1,1980-01-27 00:00:00 +3672,329,31,6.0,4,0,1980-01-27 00:00:00 +3673,329,20,1.0,10,0,1980-01-27 00:00:00 +3674,329,26,3.0,7,0,1980-01-27 00:00:00 +3675,329,55,0.0,13,0,1980-01-27 00:00:00 +3676,329,52,0.0,11,0,1980-01-27 00:00:00 +3677,329,0,3.0,8,0,1980-01-27 00:00:00 +3678,329,49,2.0,9,0,1980-01-27 00:00:00 +3679,329,24,3.0,6,0,1980-01-27 00:00:00 +3680,329,54,4.0,5,0,1980-01-27 00:00:00 +3681,329,33,6.0,3,0,1980-01-27 00:00:00 +3682,329,2,13.0,1,1,1980-01-27 00:00:00 +3683,329,5,0.0,12,0,1980-01-27 00:00:00 +3684,330,31,6.0,5,0,1980-03-01 00:00:00 +3685,330,52,0.0,11,0,1980-03-01 00:00:00 +3686,330,20,2.0,10,0,1980-03-01 00:00:00 +3687,330,26,13.0,3,0,1980-03-01 00:00:00 +3688,330,55,0.0,12,0,1980-03-01 00:00:00 +3689,330,5,0.0,14,0,1980-03-01 00:00:00 +3690,330,24,3.0,7,0,1980-03-01 00:00:00 +3691,330,49,2.0,9,0,1980-03-01 00:00:00 +3692,330,54,4.0,6,0,1980-03-01 00:00:00 +3693,330,33,9.0,4,0,1980-03-01 00:00:00 +3694,330,2,15.0,2,1,1980-03-01 00:00:00 +3695,330,56,0.0,13,0,1980-03-01 00:00:00 +3696,330,0,3.0,8,0,1980-03-01 00:00:00 +3697,330,43,0.0,15,0,1980-03-01 00:00:00 +3698,330,3,18.0,1,2,1980-03-01 00:00:00 +3699,331,20,8.0,5,0,1980-03-30 00:00:00 +3700,331,56,0.0,14,0,1980-03-30 00:00:00 +3701,331,3,18.0,1,2,1980-03-30 00:00:00 +3702,331,31,6.0,7,0,1980-03-30 00:00:00 +3703,331,52,0.0,12,0,1980-03-30 00:00:00 +3704,331,26,14.0,4,0,1980-03-30 00:00:00 +3705,331,43,0.0,15,0,1980-03-30 00:00:00 +3706,331,55,0.0,13,0,1980-03-30 00:00:00 +3707,331,0,6.0,8,0,1980-03-30 00:00:00 +3708,331,49,2.0,10,0,1980-03-30 00:00:00 +3709,331,24,3.0,9,0,1980-03-30 00:00:00 +3710,331,54,8.0,6,0,1980-03-30 00:00:00 +3711,331,33,18.0,2,1,1980-03-30 00:00:00 +3712,331,2,15.0,3,1,1980-03-30 00:00:00 +3713,331,5,2.0,11,0,1980-03-30 00:00:00 +3714,332,31,6.0,7,0,1980-05-04 00:00:00 +3715,332,3,21.0,3,2,1980-05-04 00:00:00 +3716,332,2,25.0,1,1,1980-05-04 00:00:00 +3717,332,43,0.0,15,0,1980-05-04 00:00:00 +3718,332,52,0.0,12,0,1980-05-04 00:00:00 +3719,332,56,0.0,14,0,1980-05-04 00:00:00 +3720,332,20,8.0,5,0,1980-05-04 00:00:00 +3721,332,26,23.0,2,1,1980-05-04 00:00:00 +3722,332,55,0.0,13,0,1980-05-04 00:00:00 +3723,332,54,8.0,6,0,1980-05-04 00:00:00 +3724,332,24,5.0,9,0,1980-05-04 00:00:00 +3725,332,33,18.0,4,1,1980-05-04 00:00:00 +3726,332,0,6.0,8,0,1980-05-04 00:00:00 +3727,332,5,3.0,10,0,1980-05-04 00:00:00 +3728,332,49,2.0,11,0,1980-05-04 00:00:00 +3729,333,56,0.0,14,0,1980-05-18 00:00:00 +3730,333,3,21.0,4,2,1980-05-18 00:00:00 +3731,333,31,6.0,7,0,1980-05-18 00:00:00 +3732,333,52,0.0,12,0,1980-05-18 00:00:00 +3733,333,20,11.0,5,0,1980-05-18 00:00:00 +3734,333,26,29.0,2,1,1980-05-18 00:00:00 +3735,333,55,0.0,13,0,1980-05-18 00:00:00 +3736,333,43,0.0,15,0,1980-05-18 00:00:00 +3737,333,24,5.0,9,0,1980-05-18 00:00:00 +3738,333,54,9.0,6,0,1980-05-18 00:00:00 +3739,333,33,22.0,3,1,1980-05-18 00:00:00 +3740,333,2,34.0,1,2,1980-05-18 00:00:00 +3741,333,5,5.0,10,0,1980-05-18 00:00:00 +3742,333,0,6.0,8,0,1980-05-18 00:00:00 +3743,333,49,2.0,11,0,1980-05-18 00:00:00 +3744,334,2,44.0,1,3,1980-06-29 00:00:00 +3745,334,33,25.0,3,1,1980-06-29 00:00:00 +3746,334,54,9.0,6,0,1980-06-29 00:00:00 +3747,334,24,5.0,9,0,1980-06-29 00:00:00 +3748,334,49,2.0,11,0,1980-06-29 00:00:00 +3749,334,0,6.0,8,0,1980-06-29 00:00:00 +3750,334,5,5.0,10,0,1980-06-29 00:00:00 +3751,334,55,0.0,13,0,1980-06-29 00:00:00 +3752,334,26,39.0,2,1,1980-06-29 00:00:00 +3753,334,20,11.0,5,0,1980-06-29 00:00:00 +3754,334,52,0.0,12,0,1980-06-29 00:00:00 +3755,334,31,6.0,7,0,1980-06-29 00:00:00 +3756,334,3,23.0,4,2,1980-06-29 00:00:00 +3757,334,56,0.0,14,0,1980-06-29 00:00:00 +3758,334,43,0.0,15,0,1980-06-29 00:00:00 +3759,335,43,0.0,15,0,1980-07-13 00:00:00 +3760,335,33,31.0,3,1,1980-07-13 00:00:00 +3761,335,2,57.0,1,4,1980-07-13 00:00:00 +3762,335,56,0.0,14,0,1980-07-13 00:00:00 +3763,335,3,23.0,4,2,1980-07-13 00:00:00 +3764,335,31,6.0,9,0,1980-07-13 00:00:00 +3765,335,52,0.0,12,0,1980-07-13 00:00:00 +3766,335,20,11.0,5,0,1980-07-13 00:00:00 +3767,335,55,0.0,13,0,1980-07-13 00:00:00 +3768,335,5,5.0,10,0,1980-07-13 00:00:00 +3769,335,0,7.0,8,0,1980-07-13 00:00:00 +3770,335,49,2.0,11,0,1980-07-13 00:00:00 +3771,335,24,10.0,6,0,1980-07-13 00:00:00 +3772,335,26,39.0,2,1,1980-07-13 00:00:00 +3773,335,54,9.0,7,0,1980-07-13 00:00:00 +3774,336,33,34.0,3,1,1980-08-10 00:00:00 +3775,336,43,0.0,15,0,1980-08-10 00:00:00 +3776,336,3,23.0,4,2,1980-08-10 00:00:00 +3777,336,31,6.0,9,0,1980-08-10 00:00:00 +3778,336,52,0.0,12,0,1980-08-10 00:00:00 +3779,336,26,48.0,2,2,1980-08-10 00:00:00 +3780,336,56,0.0,14,0,1980-08-10 00:00:00 +3781,336,5,6.0,10,0,1980-08-10 00:00:00 +3782,336,55,0.0,13,0,1980-08-10 00:00:00 +3783,336,2,67.0,1,4,1980-08-10 00:00:00 +3784,336,54,9.0,7,0,1980-08-10 00:00:00 +3785,336,20,11.0,5,0,1980-08-10 00:00:00 +3786,336,49,4.0,11,0,1980-08-10 00:00:00 +3787,336,0,7.0,8,0,1980-08-10 00:00:00 +3788,336,24,10.0,6,0,1980-08-10 00:00:00 +3789,337,43,0.0,15,0,1980-08-17 00:00:00 +3790,337,56,0.0,14,0,1980-08-17 00:00:00 +3791,337,3,32.0,4,3,1980-08-17 00:00:00 +3792,337,31,7.0,8,0,1980-08-17 00:00:00 +3793,337,52,0.0,12,0,1980-08-17 00:00:00 +3794,337,20,11.0,5,0,1980-08-17 00:00:00 +3795,337,55,0.0,13,0,1980-08-17 00:00:00 +3796,337,5,6.0,10,0,1980-08-17 00:00:00 +3797,337,49,4.0,11,0,1980-08-17 00:00:00 +3798,337,24,10.0,6,0,1980-08-17 00:00:00 +3799,337,54,9.0,7,0,1980-08-17 00:00:00 +3800,337,33,36.0,3,1,1980-08-17 00:00:00 +3801,337,2,77.0,1,4,1980-08-17 00:00:00 +3802,337,26,51.0,2,2,1980-08-17 00:00:00 +3803,337,0,7.0,9,0,1980-08-17 00:00:00 +3804,338,43,0.0,15,0,1980-08-31 00:00:00 +3805,338,2,80.0,1,4,1980-08-31 00:00:00 +3806,338,56,0.0,14,0,1980-08-31 00:00:00 +3807,338,3,38.0,4,3,1980-08-31 00:00:00 +3808,338,31,7.0,9,0,1980-08-31 00:00:00 +3809,338,20,11.0,6,0,1980-08-31 00:00:00 +3810,338,26,55.0,2,2,1980-08-31 00:00:00 +3811,338,55,0.0,13,0,1980-08-31 00:00:00 +3812,338,52,0.0,12,0,1980-08-31 00:00:00 +3813,338,0,8.0,8,0,1980-08-31 00:00:00 +3814,338,49,4.0,11,0,1980-08-31 00:00:00 +3815,338,24,12.0,5,0,1980-08-31 00:00:00 +3816,338,54,9.0,7,0,1980-08-31 00:00:00 +3817,338,33,45.0,3,2,1980-08-31 00:00:00 +3818,338,5,6.0,10,0,1980-08-31 00:00:00 +3819,339,20,11.0,6,0,1980-09-14 00:00:00 +3820,339,43,0.0,14,0,1980-09-14 00:00:00 +3821,339,56,0.0,15,0,1980-09-14 00:00:00 +3822,339,3,38.0,4,3,1980-09-14 00:00:00 +3823,339,31,10.0,8,0,1980-09-14 00:00:00 +3824,339,52,0.0,12,0,1980-09-14 00:00:00 +3825,339,26,56.0,2,2,1980-09-14 00:00:00 +3826,339,24,12.0,5,0,1980-09-14 00:00:00 +3827,339,5,6.0,10,0,1980-09-14 00:00:00 +3828,339,0,8.0,9,0,1980-09-14 00:00:00 +3829,339,49,4.0,11,0,1980-09-14 00:00:00 +3830,339,2,90.0,1,4,1980-09-14 00:00:00 +3831,339,54,11.0,7,0,1980-09-14 00:00:00 +3832,339,33,54.0,3,3,1980-09-14 00:00:00 +3833,339,55,0.0,13,0,1980-09-14 00:00:00 +3834,340,20,11.0,6,0,1980-09-28 00:00:00 +3835,340,43,0.0,14,0,1980-09-28 00:00:00 +3836,340,56,0.0,15,0,1980-09-28 00:00:00 +3837,340,3,38.0,4,3,1980-09-28 00:00:00 +3838,340,31,10.0,9,0,1980-09-28 00:00:00 +3839,340,52,0.0,12,0,1980-09-28 00:00:00 +3840,340,26,60.0,2,2,1980-09-28 00:00:00 +3841,340,24,12.0,5,0,1980-09-28 00:00:00 +3842,340,5,8.0,10,0,1980-09-28 00:00:00 +3843,340,0,11.0,8,0,1980-09-28 00:00:00 +3844,340,49,4.0,11,0,1980-09-28 00:00:00 +3845,340,54,11.0,7,0,1980-09-28 00:00:00 +3846,340,33,55.0,3,3,1980-09-28 00:00:00 +3847,340,2,105.0,1,5,1980-09-28 00:00:00 +3848,340,55,0.0,13,0,1980-09-28 00:00:00 +3849,341,43,0.0,14,0,1980-10-05 00:00:00 +3850,341,56,0.0,15,0,1980-10-05 00:00:00 +3851,341,3,38.0,4,3,1980-10-05 00:00:00 +3852,341,31,14.0,5,0,1980-10-05 00:00:00 +3853,341,52,0.0,12,0,1980-10-05 00:00:00 +3854,341,20,11.0,7,0,1980-10-05 00:00:00 +3855,341,26,66.0,2,2,1980-10-05 00:00:00 +3856,341,55,0.0,13,0,1980-10-05 00:00:00 +3857,341,0,11.0,9,0,1980-10-05 00:00:00 +3858,341,49,4.0,11,0,1980-10-05 00:00:00 +3859,341,24,12.0,6,0,1980-10-05 00:00:00 +3860,341,54,11.0,8,0,1980-10-05 00:00:00 +3861,341,33,55.0,3,3,1980-10-05 00:00:00 +3862,341,2,120.0,1,6,1980-10-05 00:00:00 +3863,341,5,8.0,10,0,1980-10-05 00:00:00 +3864,342,26,0.0,10,0,1981-03-15 00:00:00 +3865,342,36,0.0,16,0,1981-03-15 00:00:00 +3866,342,0,0.0,15,0,1981-03-15 00:00:00 +3867,342,31,0.0,14,0,1981-03-15 00:00:00 +3868,342,43,0.0,13,0,1981-03-15 00:00:00 +3869,342,20,0.0,12,0,1981-03-15 00:00:00 +3870,342,5,0.0,9,0,1981-03-15 00:00:00 +3871,342,52,0.0,11,0,1981-03-15 00:00:00 +3872,342,3,0.0,7,0,1981-03-15 00:00:00 +3873,342,33,4.0,2,0,1981-03-15 00:00:00 +3874,342,2,15.0,1,1,1981-03-15 00:00:00 +3875,342,49,3.0,3,0,1981-03-15 00:00:00 +3876,342,55,0.0,8,0,1981-03-15 00:00:00 +3877,342,53,1.0,5,0,1981-03-15 00:00:00 +3878,342,54,0.0,6,0,1981-03-15 00:00:00 +3879,342,24,2.0,4,0,1981-03-15 00:00:00 +3880,343,36,0.0,16,0,1981-03-29 00:00:00 +3881,343,0,0.0,12,0,1981-03-29 00:00:00 +3882,343,31,2.0,6,0,1981-03-29 00:00:00 +3883,343,43,0.0,15,0,1981-03-29 00:00:00 +3884,343,20,4.0,3,0,1981-03-29 00:00:00 +3885,343,26,1.0,8,0,1981-03-29 00:00:00 +3886,343,5,0.0,13,0,1981-03-29 00:00:00 +3887,343,52,0.0,14,0,1981-03-29 00:00:00 +3888,343,3,0.0,11,0,1981-03-29 00:00:00 +3889,343,54,0.0,10,0,1981-03-29 00:00:00 +3890,343,53,1.0,9,0,1981-03-29 00:00:00 +3891,343,24,2.0,7,0,1981-03-29 00:00:00 +3892,343,49,3.0,5,0,1981-03-29 00:00:00 +3893,343,33,4.0,2,0,1981-03-29 00:00:00 +3894,343,2,30.0,1,2,1981-03-29 00:00:00 +3895,343,55,3.0,4,0,1981-03-29 00:00:00 +3896,344,26,1.0,9,0,1981-04-12 00:00:00 +3897,344,36,0.0,16,0,1981-04-12 00:00:00 +3898,344,0,0.0,12,0,1981-04-12 00:00:00 +3899,344,43,0.0,15,0,1981-04-12 00:00:00 +3900,344,52,0.0,13,0,1981-04-12 00:00:00 +3901,344,5,0.0,14,0,1981-04-12 00:00:00 +3902,344,31,3.0,7,0,1981-04-12 00:00:00 +3903,344,3,6.0,3,0,1981-04-12 00:00:00 +3904,344,55,3.0,6,0,1981-04-12 00:00:00 +3905,344,2,39.0,1,2,1981-04-12 00:00:00 +3906,344,33,13.0,2,1,1981-04-12 00:00:00 +3907,344,49,3.0,5,0,1981-04-12 00:00:00 +3908,344,20,4.0,4,0,1981-04-12 00:00:00 +3909,344,53,1.0,10,0,1981-04-12 00:00:00 +3910,344,24,2.0,8,0,1981-04-12 00:00:00 +3911,344,54,0.0,11,0,1981-04-12 00:00:00 +3912,345,43,0.0,16,0,1981-05-03 00:00:00 +3913,345,51,0.0,17,0,1981-05-03 00:00:00 +3914,345,36,0.0,15,0,1981-05-03 00:00:00 +3915,345,0,1.0,11,0,1981-05-03 00:00:00 +3916,345,31,3.0,7,0,1981-05-03 00:00:00 +3917,345,20,10.0,3,0,1981-05-03 00:00:00 +3918,345,26,1.0,10,0,1981-05-03 00:00:00 +3919,345,52,0.0,14,0,1981-05-03 00:00:00 +3920,345,55,3.0,6,0,1981-05-03 00:00:00 +3921,345,3,6.0,4,0,1981-05-03 00:00:00 +3922,345,54,0.0,13,0,1981-05-03 00:00:00 +3923,345,53,1.0,12,0,1981-05-03 00:00:00 +3924,345,24,2.0,9,0,1981-05-03 00:00:00 +3925,345,49,3.0,5,0,1981-05-03 00:00:00 +3926,345,33,25.0,2,2,1981-05-03 00:00:00 +3927,345,2,43.0,1,2,1981-05-03 00:00:00 +3928,345,5,2.0,8,0,1981-05-03 00:00:00 +3929,346,36,0.0,16,0,1981-05-17 00:00:00 +3930,346,0,1.0,11,0,1981-05-17 00:00:00 +3931,346,31,9.0,4,0,1981-05-17 00:00:00 +3932,346,43,0.0,15,0,1981-05-17 00:00:00 +3933,346,20,10.0,3,0,1981-05-17 00:00:00 +3934,346,55,3.0,9,0,1981-05-17 00:00:00 +3935,346,26,7.0,5,0,1981-05-17 00:00:00 +3936,346,5,5.0,7,0,1981-05-17 00:00:00 +3937,346,3,6.0,6,0,1981-05-17 00:00:00 +3938,346,54,0.0,13,0,1981-05-17 00:00:00 +3939,346,52,0.0,14,0,1981-05-17 00:00:00 +3940,346,51,0.0,17,0,1981-05-17 00:00:00 +3941,346,24,3.0,10,0,1981-05-17 00:00:00 +3942,346,53,1.0,12,0,1981-05-17 00:00:00 +3943,346,2,52.0,1,3,1981-05-17 00:00:00 +3944,346,33,25.0,2,2,1981-05-17 00:00:00 +3945,346,49,3.0,8,0,1981-05-17 00:00:00 +3946,347,26,11.0,4,0,1981-05-31 00:00:00 +3947,347,51,0.0,17,0,1981-05-31 00:00:00 +3948,347,36,0.0,16,0,1981-05-31 00:00:00 +3949,347,0,1.0,11,0,1981-05-31 00:00:00 +3950,347,31,9.0,6,0,1981-05-31 00:00:00 +3951,347,43,0.0,15,0,1981-05-31 00:00:00 +3952,347,20,10.0,5,0,1981-05-31 00:00:00 +3953,347,52,0.0,14,0,1981-05-31 00:00:00 +3954,347,5,17.0,3,1,1981-05-31 00:00:00 +3955,347,3,6.0,7,0,1981-05-31 00:00:00 +3956,347,54,0.0,13,0,1981-05-31 00:00:00 +3957,347,53,1.0,12,0,1981-05-31 00:00:00 +3958,347,24,5.0,8,0,1981-05-31 00:00:00 +3959,347,49,3.0,10,0,1981-05-31 00:00:00 +3960,347,33,25.0,2,2,1981-05-31 00:00:00 +3961,347,2,58.0,1,3,1981-05-31 00:00:00 +3962,347,55,4.0,9,0,1981-05-31 00:00:00 +3963,348,31,12.0,5,0,1981-06-21 00:00:00 +3964,348,0,5.0,8,0,1981-06-21 00:00:00 +3965,348,36,0.0,16,0,1981-06-21 00:00:00 +3966,348,24,5.0,9,0,1981-06-21 00:00:00 +3967,348,51,0.0,17,0,1981-06-21 00:00:00 +3968,348,49,3.0,11,0,1981-06-21 00:00:00 +3969,348,43,0.0,15,0,1981-06-21 00:00:00 +3970,348,53,1.0,12,0,1981-06-21 00:00:00 +3971,348,20,10.0,6,0,1981-06-21 00:00:00 +3972,348,33,25.0,3,2,1981-06-21 00:00:00 +3973,348,26,17.0,4,0,1981-06-21 00:00:00 +3974,348,5,26.0,2,2,1981-06-21 00:00:00 +3975,348,55,4.0,10,0,1981-06-21 00:00:00 +3976,348,3,6.0,7,0,1981-06-21 00:00:00 +3977,348,54,0.0,13,0,1981-06-21 00:00:00 +3978,348,2,61.0,1,3,1981-06-21 00:00:00 +3979,348,52,0.0,14,0,1981-06-21 00:00:00 +3980,349,5,28.0,3,2,1981-07-05 00:00:00 +3981,349,2,61.0,1,3,1981-07-05 00:00:00 +3982,349,33,29.0,2,2,1981-07-05 00:00:00 +3983,349,49,3.0,11,0,1981-07-05 00:00:00 +3984,349,24,5.0,9,0,1981-07-05 00:00:00 +3985,349,53,1.0,12,0,1981-07-05 00:00:00 +3986,349,3,18.0,4,1,1981-07-05 00:00:00 +3987,349,55,4.0,10,0,1981-07-05 00:00:00 +3988,349,26,17.0,5,0,1981-07-05 00:00:00 +3989,349,54,0.0,13,0,1981-07-05 00:00:00 +3990,349,20,10.0,8,0,1981-07-05 00:00:00 +3991,349,43,0.0,15,0,1981-07-05 00:00:00 +3992,349,31,13.0,6,0,1981-07-05 00:00:00 +3993,349,0,11.0,7,0,1981-07-05 00:00:00 +3994,349,36,0.0,16,0,1981-07-05 00:00:00 +3995,349,51,0.0,17,0,1981-07-05 00:00:00 +3996,349,52,0.0,14,0,1981-07-05 00:00:00 +3997,350,51,0.0,17,0,1981-07-18 00:00:00 +3998,350,36,0.0,15,0,1981-07-18 00:00:00 +3999,350,0,20.0,5,1,1981-07-18 00:00:00 +4000,350,31,13.0,7,0,1981-07-18 00:00:00 +4001,350,43,0.0,16,0,1981-07-18 00:00:00 +4002,350,20,10.0,8,0,1981-07-18 00:00:00 +4003,350,52,1.0,13,0,1981-07-18 00:00:00 +4004,350,3,18.0,6,1,1981-07-18 00:00:00 +4005,350,5,28.0,3,2,1981-07-18 00:00:00 +4006,350,55,4.0,10,0,1981-07-18 00:00:00 +4007,350,53,1.0,12,0,1981-07-18 00:00:00 +4008,350,24,8.0,9,0,1981-07-18 00:00:00 +4009,350,49,3.0,11,0,1981-07-18 00:00:00 +4010,350,33,31.0,2,2,1981-07-18 00:00:00 +4011,350,2,67.0,1,3,1981-07-18 00:00:00 +4012,350,26,21.0,4,0,1981-07-18 00:00:00 +4013,350,54,0.0,14,0,1981-07-18 00:00:00 +4014,351,26,25.0,4,0,1981-08-02 00:00:00 +4015,351,33,43.0,2,3,1981-08-02 00:00:00 +4016,351,2,67.0,1,3,1981-08-02 00:00:00 +4017,351,3,24.0,5,1,1981-08-02 00:00:00 +4018,351,54,0.0,14,0,1981-08-02 00:00:00 +4019,351,53,1.0,12,0,1981-08-02 00:00:00 +4020,351,24,10.0,9,0,1981-08-02 00:00:00 +4021,351,31,13.0,7,0,1981-08-02 00:00:00 +4022,351,49,3.0,11,0,1981-08-02 00:00:00 +4023,351,20,10.0,8,0,1981-08-02 00:00:00 +4024,351,5,28.0,3,2,1981-08-02 00:00:00 +4025,351,52,1.0,13,0,1981-08-02 00:00:00 +4026,351,43,0.0,16,0,1981-08-02 00:00:00 +4027,351,0,21.0,6,1,1981-08-02 00:00:00 +4028,351,36,0.0,15,0,1981-08-02 00:00:00 +4029,351,51,0.0,17,0,1981-08-02 00:00:00 +4030,351,55,4.0,10,0,1981-08-02 00:00:00 +4031,352,54,0.0,14,0,1981-08-16 00:00:00 +4032,352,36,0.0,15,0,1981-08-16 00:00:00 +4033,352,53,1.0,12,0,1981-08-16 00:00:00 +4034,352,24,10.0,9,0,1981-08-16 00:00:00 +4035,352,49,3.0,11,0,1981-08-16 00:00:00 +4036,352,51,0.0,17,0,1981-08-16 00:00:00 +4037,352,0,22.0,6,1,1981-08-16 00:00:00 +4038,352,2,72.0,1,3,1981-08-16 00:00:00 +4039,352,43,0.0,16,0,1981-08-16 00:00:00 +4040,352,20,10.0,8,0,1981-08-16 00:00:00 +4041,352,52,1.0,13,0,1981-08-16 00:00:00 +4042,352,26,34.0,3,1,1981-08-16 00:00:00 +4043,352,33,47.0,2,3,1981-08-16 00:00:00 +4044,352,55,4.0,10,0,1981-08-16 00:00:00 +4045,352,5,28.0,5,2,1981-08-16 00:00:00 +4046,352,31,13.0,7,0,1981-08-16 00:00:00 +4047,352,3,30.0,4,1,1981-08-16 00:00:00 +4048,353,5,28.0,5,2,1981-08-30 00:00:00 +4049,353,33,56.0,2,3,1981-08-30 00:00:00 +4050,353,2,76.0,1,3,1981-08-30 00:00:00 +4051,353,51,0.0,17,0,1981-08-30 00:00:00 +4052,353,36,0.0,15,0,1981-08-30 00:00:00 +4053,353,0,22.0,6,1,1981-08-30 00:00:00 +4054,353,43,0.0,16,0,1981-08-30 00:00:00 +4055,353,20,10.0,8,0,1981-08-30 00:00:00 +4056,353,52,1.0,13,0,1981-08-30 00:00:00 +4057,353,31,15.0,7,0,1981-08-30 00:00:00 +4058,353,55,5.0,10,0,1981-08-30 00:00:00 +4059,353,3,39.0,3,2,1981-08-30 00:00:00 +4060,353,54,0.0,14,0,1981-08-30 00:00:00 +4061,353,53,1.0,12,0,1981-08-30 00:00:00 +4062,353,24,10.0,9,0,1981-08-30 00:00:00 +4063,353,49,3.0,11,0,1981-08-30 00:00:00 +4064,353,26,34.0,4,1,1981-08-30 00:00:00 +4065,354,52,1.0,13,0,1981-09-13 00:00:00 +4066,354,51,0.0,17,0,1981-09-13 00:00:00 +4067,354,36,0.0,15,0,1981-09-13 00:00:00 +4068,354,0,22.0,6,1,1981-09-13 00:00:00 +4069,354,43,0.0,16,0,1981-09-13 00:00:00 +4070,354,20,10.0,8,0,1981-09-13 00:00:00 +4071,354,26,34.0,4,1,1981-09-13 00:00:00 +4072,354,31,18.0,7,0,1981-09-13 00:00:00 +4073,354,55,5.0,10,0,1981-09-13 00:00:00 +4074,354,33,57.0,2,3,1981-09-13 00:00:00 +4075,354,49,3.0,11,0,1981-09-13 00:00:00 +4076,354,24,10.0,9,0,1981-09-13 00:00:00 +4077,354,5,30.0,5,2,1981-09-13 00:00:00 +4078,354,53,1.0,12,0,1981-09-13 00:00:00 +4079,354,54,0.0,14,0,1981-09-13 00:00:00 +4080,354,3,48.0,3,3,1981-09-13 00:00:00 +4081,354,2,86.0,1,3,1981-09-13 00:00:00 +4082,355,26,43.0,4,2,1981-09-27 00:00:00 +4083,355,36,0.0,14,0,1981-09-27 00:00:00 +4084,355,0,28.0,6,1,1981-09-27 00:00:00 +4085,355,31,19.0,7,0,1981-09-27 00:00:00 +4086,355,43,0.0,16,0,1981-09-27 00:00:00 +4087,355,20,10.0,8,0,1981-09-27 00:00:00 +4088,355,52,1.0,13,0,1981-09-27 00:00:00 +4089,355,51,0.0,17,0,1981-09-27 00:00:00 +4090,355,5,34.0,5,2,1981-09-27 00:00:00 +4091,355,3,48.0,3,3,1981-09-27 00:00:00 +4092,355,54,0.0,15,0,1981-09-27 00:00:00 +4093,355,53,1.0,12,0,1981-09-27 00:00:00 +4094,355,24,10.0,9,0,1981-09-27 00:00:00 +4095,355,49,6.0,10,0,1981-09-27 00:00:00 +4096,355,33,59.0,2,3,1981-09-27 00:00:00 +4097,355,2,86.0,1,3,1981-09-27 00:00:00 +4098,355,55,5.0,11,0,1981-09-27 00:00:00 +4099,356,52,1.0,13,0,1981-10-17 00:00:00 +4100,356,51,0.0,17,0,1981-10-17 00:00:00 +4101,356,36,0.0,14,0,1981-10-17 00:00:00 +4102,356,0,28.0,6,1,1981-10-17 00:00:00 +4103,356,31,22.0,7,0,1981-10-17 00:00:00 +4104,356,43,0.0,16,0,1981-10-17 00:00:00 +4105,356,20,10.0,8,0,1981-10-17 00:00:00 +4106,356,26,44.0,4,2,1981-10-17 00:00:00 +4107,356,2,95.0,1,4,1981-10-17 00:00:00 +4108,356,55,5.0,11,0,1981-10-17 00:00:00 +4109,356,3,54.0,3,3,1981-10-17 00:00:00 +4110,356,54,0.0,15,0,1981-10-17 00:00:00 +4111,356,53,1.0,12,0,1981-10-17 00:00:00 +4112,356,24,10.0,10,0,1981-10-17 00:00:00 +4113,356,49,10.0,9,0,1981-10-17 00:00:00 +4114,356,33,61.0,2,3,1981-10-17 00:00:00 +4115,356,5,34.0,5,2,1981-10-17 00:00:00 +4116,357,55,0.0,17,0,1982-01-23 00:00:00 +4117,357,20,0.0,16,0,1982-01-23 00:00:00 +4118,357,33,0.0,14,0,1982-01-23 00:00:00 +4119,357,51,0.0,13,0,1982-01-23 00:00:00 +4120,357,26,0.0,12,0,1982-01-23 00:00:00 +4121,357,5,0.0,11,0,1982-01-23 00:00:00 +4122,357,54,0.0,10,0,1982-01-23 00:00:00 +4123,357,43,0.0,15,0,1982-01-23 00:00:00 +4124,357,36,0.0,8,0,1982-01-23 00:00:00 +4125,357,49,0.0,7,0,1982-01-23 00:00:00 +4126,357,52,0.0,6,0,1982-01-23 00:00:00 +4127,357,31,0.0,5,0,1982-01-23 00:00:00 +4128,357,24,0.0,4,0,1982-01-23 00:00:00 +4129,357,0,4.0,3,0,1982-01-23 00:00:00 +4130,357,2,8.0,2,0,1982-01-23 00:00:00 +4131,357,3,13.0,1,1,1982-01-23 00:00:00 +4132,357,53,0.0,9,0,1982-01-23 00:00:00 +4133,358,33,0.0,14,0,1982-03-21 00:00:00 +4134,358,51,0.0,16,0,1982-03-21 00:00:00 +4135,358,26,0.0,15,0,1982-03-21 00:00:00 +4136,358,5,1.0,7,0,1982-03-21 00:00:00 +4137,358,54,0.0,13,0,1982-03-21 00:00:00 +4138,358,53,0.0,12,0,1982-03-21 00:00:00 +4139,358,36,0.0,8,0,1982-03-21 00:00:00 +4140,358,24,3.0,5,0,1982-03-21 00:00:00 +4141,358,52,2.0,6,0,1982-03-21 00:00:00 +4142,358,31,4.0,4,0,1982-03-21 00:00:00 +4143,358,0,10.0,2,0,1982-03-21 00:00:00 +4144,358,2,8.0,3,0,1982-03-21 00:00:00 +4145,358,3,22.0,1,2,1982-03-21 00:00:00 +4146,358,20,0.0,10,0,1982-03-21 00:00:00 +4147,358,49,0.0,11,0,1982-03-21 00:00:00 +4148,358,55,0.0,17,0,1982-03-21 00:00:00 +4149,358,43,0.0,9,0,1982-03-21 00:00:00 +4150,359,54,0.0,14,0,1982-04-04 00:00:00 +4151,359,20,0.0,11,0,1982-04-04 00:00:00 +4152,359,43,0.0,10,0,1982-04-04 00:00:00 +4153,359,33,4.0,6,0,1982-04-04 00:00:00 +4154,359,51,0.0,17,0,1982-04-04 00:00:00 +4155,359,26,0.0,15,0,1982-04-04 00:00:00 +4156,359,5,1.0,8,0,1982-04-04 00:00:00 +4157,359,53,0.0,13,0,1982-04-04 00:00:00 +4158,359,55,0.0,16,0,1982-04-04 00:00:00 +4159,359,49,0.0,12,0,1982-04-04 00:00:00 +4160,359,52,2.0,7,0,1982-04-04 00:00:00 +4161,359,31,6.0,4,0,1982-04-04 00:00:00 +4162,359,24,6.0,5,0,1982-04-04 00:00:00 +4163,359,0,20.0,2,1,1982-04-04 00:00:00 +4164,359,2,14.0,3,0,1982-04-04 00:00:00 +4165,359,3,22.0,1,2,1982-04-04 00:00:00 +4166,359,36,0.0,9,0,1982-04-04 00:00:00 +4167,360,20,0.0,11,0,1982-04-25 00:00:00 +4168,360,43,3.0,9,0,1982-04-25 00:00:00 +4169,360,33,4.0,7,0,1982-04-25 00:00:00 +4170,360,51,0.0,15,0,1982-04-25 00:00:00 +4171,360,26,0.0,16,0,1982-04-25 00:00:00 +4172,360,5,16.0,3,1,1982-04-25 00:00:00 +4173,360,54,0.0,14,0,1982-04-25 00:00:00 +4174,360,52,4.0,8,0,1982-04-25 00:00:00 +4175,360,36,0.0,10,0,1982-04-25 00:00:00 +4176,360,49,0.0,12,0,1982-04-25 00:00:00 +4177,360,31,6.0,6,0,1982-04-25 00:00:00 +4178,360,24,10.0,5,0,1982-04-25 00:00:00 +4179,360,0,20.0,2,1,1982-04-25 00:00:00 +4180,360,55,0.0,17,0,1982-04-25 00:00:00 +4181,360,53,0.0,13,0,1982-04-25 00:00:00 +4182,360,2,14.0,4,0,1982-04-25 00:00:00 +4183,360,3,22.0,1,2,1982-04-25 00:00:00 +4184,361,26,4.0,8,0,1982-05-09 00:00:00 +4185,361,55,0.0,17,0,1982-05-09 00:00:00 +4186,361,20,0.0,12,0,1982-05-09 00:00:00 +4187,361,43,3.0,10,0,1982-05-09 00:00:00 +4188,361,33,6.0,7,0,1982-05-09 00:00:00 +4189,361,51,0.0,16,0,1982-05-09 00:00:00 +4190,361,5,16.0,4,1,1982-05-09 00:00:00 +4191,361,54,1.0,11,0,1982-05-09 00:00:00 +4192,361,53,0.0,15,0,1982-05-09 00:00:00 +4193,361,49,0.0,14,0,1982-05-09 00:00:00 +4194,361,52,4.0,9,0,1982-05-09 00:00:00 +4195,361,31,9.0,6,0,1982-05-09 00:00:00 +4196,361,24,10.0,5,0,1982-05-09 00:00:00 +4197,361,0,29.0,1,2,1982-05-09 00:00:00 +4198,361,2,20.0,3,0,1982-05-09 00:00:00 +4199,361,3,22.0,2,2,1982-05-09 00:00:00 +4200,361,36,0.0,13,0,1982-05-09 00:00:00 +4201,362,51,0.0,16,0,1982-05-23 00:00:00 +4202,362,26,4.0,8,0,1982-05-23 00:00:00 +4203,362,33,15.0,5,1,1982-05-23 00:00:00 +4204,362,20,0.0,13,0,1982-05-23 00:00:00 +4205,362,55,0.0,17,0,1982-05-23 00:00:00 +4206,362,54,1.0,12,0,1982-05-23 00:00:00 +4207,362,43,3.0,11,0,1982-05-23 00:00:00 +4208,362,53,0.0,15,0,1982-05-23 00:00:00 +4209,362,5,22.0,3,1,1982-05-23 00:00:00 +4210,362,49,4.0,9,0,1982-05-23 00:00:00 +4211,362,36,0.0,14,0,1982-05-23 00:00:00 +4212,362,2,21.0,4,0,1982-05-23 00:00:00 +4213,362,0,29.0,1,2,1982-05-23 00:00:00 +4214,362,3,22.0,2,2,1982-05-23 00:00:00 +4215,362,31,14.0,6,0,1982-05-23 00:00:00 +4216,362,52,4.0,10,0,1982-05-23 00:00:00 +4217,362,24,10.0,7,0,1982-05-23 00:00:00 +4218,363,55,0.0,17,0,1982-06-06 00:00:00 +4219,363,20,0.0,14,0,1982-06-06 00:00:00 +4220,363,43,3.0,11,0,1982-06-06 00:00:00 +4221,363,33,15.0,5,1,1982-06-06 00:00:00 +4222,363,51,0.0,16,0,1982-06-06 00:00:00 +4223,363,26,11.0,7,0,1982-06-06 00:00:00 +4224,363,5,26.0,2,1,1982-06-06 00:00:00 +4225,363,54,1.0,12,0,1982-06-06 00:00:00 +4226,363,53,0.0,15,0,1982-06-06 00:00:00 +4227,363,49,4.0,9,0,1982-06-06 00:00:00 +4228,363,52,4.0,10,0,1982-06-06 00:00:00 +4229,363,31,14.0,6,0,1982-06-06 00:00:00 +4230,363,24,10.0,8,0,1982-06-06 00:00:00 +4231,363,0,38.0,1,3,1982-06-06 00:00:00 +4232,363,2,26.0,3,0,1982-06-06 00:00:00 +4233,363,3,22.0,4,2,1982-06-06 00:00:00 +4234,363,36,0.0,13,0,1982-06-06 00:00:00 +4235,364,43,3.0,11,0,1982-06-13 00:00:00 +4236,364,54,1.0,13,0,1982-06-13 00:00:00 +4237,364,33,30.0,2,2,1982-06-13 00:00:00 +4238,364,51,0.0,16,0,1982-06-13 00:00:00 +4239,364,26,11.0,7,0,1982-06-13 00:00:00 +4240,364,5,26.0,3,1,1982-06-13 00:00:00 +4241,364,36,0.0,14,0,1982-06-13 00:00:00 +4242,364,53,0.0,15,0,1982-06-13 00:00:00 +4243,364,52,4.0,10,0,1982-06-13 00:00:00 +4244,364,31,17.0,6,0,1982-06-13 00:00:00 +4245,364,24,10.0,8,0,1982-06-13 00:00:00 +4246,364,0,42.0,1,3,1982-06-13 00:00:00 +4247,364,2,26.0,4,0,1982-06-13 00:00:00 +4248,364,3,22.0,5,2,1982-06-13 00:00:00 +4249,364,20,2.0,12,0,1982-06-13 00:00:00 +4250,364,49,5.0,9,0,1982-06-13 00:00:00 +4251,364,55,0.0,17,0,1982-06-13 00:00:00 +4252,365,53,0.0,15,0,1982-07-03 00:00:00 +4253,365,2,32.0,4,0,1982-07-03 00:00:00 +4254,365,55,0.0,17,0,1982-07-03 00:00:00 +4255,365,20,3.0,12,0,1982-07-03 00:00:00 +4256,365,43,3.0,11,0,1982-07-03 00:00:00 +4257,365,33,36.0,2,2,1982-07-03 00:00:00 +4258,365,51,0.0,16,0,1982-07-03 00:00:00 +4259,365,26,11.0,7,0,1982-07-03 00:00:00 +4260,365,5,35.0,3,2,1982-07-03 00:00:00 +4261,365,54,1.0,13,0,1982-07-03 00:00:00 +4262,365,3,22.0,5,2,1982-07-03 00:00:00 +4263,365,36,0.0,14,0,1982-07-03 00:00:00 +4264,365,49,5.0,9,0,1982-07-03 00:00:00 +4265,365,52,4.0,10,0,1982-07-03 00:00:00 +4266,365,31,17.0,6,0,1982-07-03 00:00:00 +4267,365,24,10.0,8,0,1982-07-03 00:00:00 +4268,365,0,45.0,1,3,1982-07-03 00:00:00 +4269,366,53,0.0,15,0,1982-07-18 00:00:00 +4270,366,55,0.0,17,0,1982-07-18 00:00:00 +4271,366,20,3.0,12,0,1982-07-18 00:00:00 +4272,366,43,3.0,11,0,1982-07-18 00:00:00 +4273,366,33,36.0,3,2,1982-07-18 00:00:00 +4274,366,51,0.0,16,0,1982-07-18 00:00:00 +4275,366,26,11.0,7,0,1982-07-18 00:00:00 +4276,366,5,45.0,2,2,1982-07-18 00:00:00 +4277,366,54,1.0,13,0,1982-07-18 00:00:00 +4278,366,24,10.0,8,0,1982-07-18 00:00:00 +4279,366,36,0.0,14,0,1982-07-18 00:00:00 +4280,366,49,5.0,9,0,1982-07-18 00:00:00 +4281,366,52,4.0,10,0,1982-07-18 00:00:00 +4282,366,31,20.0,6,0,1982-07-18 00:00:00 +4283,366,0,54.0,1,4,1982-07-18 00:00:00 +4284,366,2,34.0,4,0,1982-07-18 00:00:00 +4285,366,3,23.0,5,2,1982-07-18 00:00:00 +4286,367,53,0.0,15,0,1982-07-25 00:00:00 +4287,367,43,3.0,11,0,1982-07-25 00:00:00 +4288,367,33,36.0,4,2,1982-07-25 00:00:00 +4289,367,51,0.0,16,0,1982-07-25 00:00:00 +4290,367,26,11.0,7,0,1982-07-25 00:00:00 +4291,367,5,52.0,2,2,1982-07-25 00:00:00 +4292,367,54,1.0,13,0,1982-07-25 00:00:00 +4293,367,20,3.0,12,0,1982-07-25 00:00:00 +4294,367,55,0.0,17,0,1982-07-25 00:00:00 +4295,367,36,0.0,14,0,1982-07-25 00:00:00 +4296,367,52,4.0,10,0,1982-07-25 00:00:00 +4297,367,31,20.0,6,0,1982-07-25 00:00:00 +4298,367,24,11.0,8,0,1982-07-25 00:00:00 +4299,367,0,54.0,1,4,1982-07-25 00:00:00 +4300,367,2,36.0,5,0,1982-07-25 00:00:00 +4301,367,3,38.0,3,3,1982-07-25 00:00:00 +4302,367,49,5.0,9,0,1982-07-25 00:00:00 +4303,368,20,4.0,11,0,1982-08-08 00:00:00 +4304,368,43,3.0,12,0,1982-08-08 00:00:00 +4305,368,33,36.0,5,2,1982-08-08 00:00:00 +4306,368,26,11.0,8,0,1982-08-08 00:00:00 +4307,368,5,61.0,1,3,1982-08-08 00:00:00 +4308,368,54,1.0,13,0,1982-08-08 00:00:00 +4309,368,53,0.0,17,0,1982-08-08 00:00:00 +4310,368,36,0.0,14,0,1982-08-08 00:00:00 +4311,368,51,0.0,16,0,1982-08-08 00:00:00 +4312,368,52,4.0,10,0,1982-08-08 00:00:00 +4313,368,49,7.0,9,0,1982-08-08 00:00:00 +4314,368,3,44.0,3,3,1982-08-08 00:00:00 +4315,368,2,40.0,4,0,1982-08-08 00:00:00 +4316,368,55,0.0,15,0,1982-08-08 00:00:00 +4317,368,24,14.0,7,0,1982-08-08 00:00:00 +4318,368,31,20.0,6,0,1982-08-08 00:00:00 +4319,368,0,54.0,2,4,1982-08-08 00:00:00 +4320,369,55,0.0,15,0,1982-08-15 00:00:00 +4321,369,20,5.0,10,0,1982-08-15 00:00:00 +4322,369,43,3.0,12,0,1982-08-15 00:00:00 +4323,369,33,36.0,5,2,1982-08-15 00:00:00 +4324,369,51,0.0,16,0,1982-08-15 00:00:00 +4325,369,26,15.0,7,0,1982-08-15 00:00:00 +4326,369,5,64.0,1,3,1982-08-15 00:00:00 +4327,369,53,0.0,17,0,1982-08-15 00:00:00 +4328,369,36,0.0,14,0,1982-08-15 00:00:00 +4329,369,52,4.0,11,0,1982-08-15 00:00:00 +4330,369,31,29.0,6,1,1982-08-15 00:00:00 +4331,369,24,14.0,8,0,1982-08-15 00:00:00 +4332,369,0,56.0,2,4,1982-08-15 00:00:00 +4333,369,2,46.0,3,0,1982-08-15 00:00:00 +4334,369,3,44.0,4,3,1982-08-15 00:00:00 +4335,369,54,1.0,13,0,1982-08-15 00:00:00 +4336,369,49,7.0,9,0,1982-08-15 00:00:00 +4337,370,55,0.0,15,0,1982-08-29 00:00:00 +4338,370,2,55.0,3,1,1982-08-29 00:00:00 +4339,370,20,5.0,10,0,1982-08-29 00:00:00 +4340,370,43,3.0,12,0,1982-08-29 00:00:00 +4341,370,33,41.0,5,2,1982-08-29 00:00:00 +4342,370,51,0.0,16,0,1982-08-29 00:00:00 +4343,370,5,64.0,1,3,1982-08-29 00:00:00 +4344,370,54,1.0,13,0,1982-08-29 00:00:00 +4345,370,53,0.0,17,0,1982-08-29 00:00:00 +4346,370,26,15.0,7,0,1982-08-29 00:00:00 +4347,370,3,50.0,4,3,1982-08-29 00:00:00 +4348,370,49,7.0,9,0,1982-08-29 00:00:00 +4349,370,52,4.0,11,0,1982-08-29 00:00:00 +4350,370,31,30.0,6,1,1982-08-29 00:00:00 +4351,370,24,14.0,8,0,1982-08-29 00:00:00 +4352,370,0,60.0,2,4,1982-08-29 00:00:00 +4353,370,36,0.0,14,0,1982-08-29 00:00:00 +4354,371,54,1.0,13,0,1982-09-12 00:00:00 +4355,371,55,0.0,15,0,1982-09-12 00:00:00 +4356,371,20,5.0,10,0,1982-09-12 00:00:00 +4357,371,43,3.0,12,0,1982-09-12 00:00:00 +4358,371,33,41.0,5,2,1982-09-12 00:00:00 +4359,371,26,16.0,7,0,1982-09-12 00:00:00 +4360,371,5,74.0,1,3,1982-09-12 00:00:00 +4361,371,53,0.0,17,0,1982-09-12 00:00:00 +4362,371,51,0.0,16,0,1982-09-12 00:00:00 +4363,371,49,7.0,9,0,1982-09-12 00:00:00 +4364,371,52,4.0,11,0,1982-09-12 00:00:00 +4365,371,31,30.0,6,1,1982-09-12 00:00:00 +4366,371,24,16.0,8,0,1982-09-12 00:00:00 +4367,371,3,59.0,3,4,1982-09-12 00:00:00 +4368,371,0,63.0,2,4,1982-09-12 00:00:00 +4369,371,2,55.0,4,1,1982-09-12 00:00:00 +4370,371,36,0.0,14,0,1982-09-12 00:00:00 +4371,372,0,69.0,2,4,1982-09-25 00:00:00 +4372,372,2,58.0,4,1,1982-09-25 00:00:00 +4373,372,3,62.0,3,4,1982-09-25 00:00:00 +4374,372,24,25.0,7,1,1982-09-25 00:00:00 +4375,372,31,30.0,6,1,1982-09-25 00:00:00 +4376,372,49,7.0,9,0,1982-09-25 00:00:00 +4377,372,52,4.0,11,0,1982-09-25 00:00:00 +4378,372,53,0.0,17,0,1982-09-25 00:00:00 +4379,372,54,1.0,13,0,1982-09-25 00:00:00 +4380,372,26,20.0,8,0,1982-09-25 00:00:00 +4381,372,51,0.0,16,0,1982-09-25 00:00:00 +4382,372,33,41.0,5,2,1982-09-25 00:00:00 +4383,372,43,3.0,12,0,1982-09-25 00:00:00 +4384,372,20,5.0,10,0,1982-09-25 00:00:00 +4385,372,5,74.0,1,3,1982-09-25 00:00:00 +4386,372,55,0.0,15,0,1982-09-25 00:00:00 +4387,372,36,0.0,14,0,1982-09-25 00:00:00 +4388,373,53,0.0,10,0,1983-03-13 00:00:00 +4389,373,43,0.0,15,0,1983-03-13 00:00:00 +4390,373,49,0.0,14,0,1983-03-13 00:00:00 +4391,373,26,0.0,13,0,1983-03-13 00:00:00 +4392,373,52,0.0,12,0,1983-03-13 00:00:00 +4393,373,48,0.0,11,0,1983-03-13 00:00:00 +4394,373,31,0.0,9,0,1983-03-13 00:00:00 +4395,373,33,9.0,1,1,1983-03-13 00:00:00 +4396,373,51,0.0,7,0,1983-03-13 00:00:00 +4397,373,3,0.0,6,0,1983-03-13 00:00:00 +4398,373,20,1.0,5,0,1983-03-13 00:00:00 +4399,373,5,2.0,4,0,1983-03-13 00:00:00 +4400,373,2,3.0,3,0,1983-03-13 00:00:00 +4401,373,0,4.0,2,0,1983-03-13 00:00:00 +4402,373,24,0.0,8,0,1983-03-13 00:00:00 +4403,374,49,0.0,14,0,1983-03-27 00:00:00 +4404,374,26,0.0,8,0,1983-03-27 00:00:00 +4405,374,52,0.0,13,0,1983-03-27 00:00:00 +4406,374,48,0.0,12,0,1983-03-27 00:00:00 +4407,374,53,1.0,6,0,1983-03-27 00:00:00 +4408,374,31,0.0,11,0,1983-03-27 00:00:00 +4409,374,24,0.0,9,0,1983-03-27 00:00:00 +4410,374,43,0.0,15,0,1983-03-27 00:00:00 +4411,374,3,0.0,7,0,1983-03-27 00:00:00 +4412,374,20,3.0,5,0,1983-03-27 00:00:00 +4413,374,5,6.0,3,0,1983-03-27 00:00:00 +4414,374,2,6.0,4,0,1983-03-27 00:00:00 +4415,374,0,19.0,1,1,1983-03-27 00:00:00 +4416,374,33,9.0,2,1,1983-03-27 00:00:00 +4417,374,51,0.0,10,0,1983-03-27 00:00:00 +4418,375,43,0.0,15,0,1983-04-17 00:00:00 +4419,375,49,0.0,12,0,1983-04-17 00:00:00 +4420,375,26,0.0,8,0,1983-04-17 00:00:00 +4421,375,52,0.0,14,0,1983-04-17 00:00:00 +4422,375,48,0.0,13,0,1983-04-17 00:00:00 +4423,375,53,1.0,7,0,1983-04-17 00:00:00 +4424,375,31,0.0,11,0,1983-04-17 00:00:00 +4425,375,24,0.0,9,0,1983-04-17 00:00:00 +4426,375,3,13.0,3,1,1983-04-17 00:00:00 +4427,375,20,3.0,6,0,1983-04-17 00:00:00 +4428,375,5,9.0,4,0,1983-04-17 00:00:00 +4429,375,2,9.0,5,0,1983-04-17 00:00:00 +4430,375,0,19.0,1,1,1983-04-17 00:00:00 +4431,375,33,15.0,2,1,1983-04-17 00:00:00 +4432,375,51,0.0,10,0,1983-04-17 00:00:00 +4433,376,43,0.0,15,0,1983-05-01 00:00:00 +4434,376,49,0.0,11,0,1983-05-01 00:00:00 +4435,376,26,0.0,8,0,1983-05-01 00:00:00 +4436,376,52,0.0,12,0,1983-05-01 00:00:00 +4437,376,48,0.0,14,0,1983-05-01 00:00:00 +4438,376,53,1.0,7,0,1983-05-01 00:00:00 +4439,376,31,0.0,13,0,1983-05-01 00:00:00 +4440,376,3,19.0,3,1,1983-05-01 00:00:00 +4441,376,51,0.0,10,0,1983-05-01 00:00:00 +4442,376,33,15.0,4,1,1983-05-01 00:00:00 +4443,376,0,21.0,2,1,1983-05-01 00:00:00 +4444,376,24,0.0,9,0,1983-05-01 00:00:00 +4445,376,5,22.0,1,1,1983-05-01 00:00:00 +4446,376,20,4.0,6,0,1983-05-01 00:00:00 +4447,376,2,12.0,5,0,1983-05-01 00:00:00 +4448,377,43,0.0,15,0,1983-05-15 00:00:00 +4449,377,49,1.0,8,0,1983-05-15 00:00:00 +4450,377,26,0.0,10,0,1983-05-15 00:00:00 +4451,377,52,0.0,12,0,1983-05-15 00:00:00 +4452,377,48,0.0,14,0,1983-05-15 00:00:00 +4453,377,31,0.0,13,0,1983-05-15 00:00:00 +4454,377,53,1.0,9,0,1983-05-15 00:00:00 +4455,377,3,23.0,2,1,1983-05-15 00:00:00 +4456,377,20,4.0,6,0,1983-05-15 00:00:00 +4457,377,5,25.0,1,1,1983-05-15 00:00:00 +4458,377,2,21.0,5,1,1983-05-15 00:00:00 +4459,377,0,21.0,4,1,1983-05-15 00:00:00 +4460,377,33,21.0,3,1,1983-05-15 00:00:00 +4461,377,51,0.0,11,0,1983-05-15 00:00:00 +4462,377,24,2.0,7,0,1983-05-15 00:00:00 +4463,378,43,0.0,15,0,1983-05-22 00:00:00 +4464,378,24,2.0,7,0,1983-05-22 00:00:00 +4465,378,31,0.0,12,0,1983-05-22 00:00:00 +4466,378,53,1.0,8,0,1983-05-22 00:00:00 +4467,378,48,0.0,14,0,1983-05-22 00:00:00 +4468,378,52,0.0,13,0,1983-05-22 00:00:00 +4469,378,26,0.0,11,0,1983-05-22 00:00:00 +4470,378,49,1.0,9,0,1983-05-22 00:00:00 +4471,378,3,36.0,1,2,1983-05-22 00:00:00 +4472,378,51,0.0,10,0,1983-05-22 00:00:00 +4473,378,33,24.0,3,1,1983-05-22 00:00:00 +4474,378,0,21.0,5,1,1983-05-22 00:00:00 +4475,378,2,24.0,4,1,1983-05-22 00:00:00 +4476,378,5,31.0,2,1,1983-05-22 00:00:00 +4477,378,20,4.0,6,0,1983-05-22 00:00:00 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+4550,383,3,68.0,1,4,1983-08-14 00:00:00 +4551,383,20,4.0,9,0,1983-08-14 00:00:00 +4552,383,5,65.0,2,3,1983-08-14 00:00:00 +4553,383,2,36.0,4,1,1983-08-14 00:00:00 +4554,383,24,11.0,6,1,1983-08-14 00:00:00 +4555,383,33,41.0,3,1,1983-08-14 00:00:00 +4556,384,52,0.0,14,0,1983-08-28 00:00:00 +4557,384,48,0.0,16,0,1983-08-28 00:00:00 +4558,384,26,0.0,12,0,1983-08-28 00:00:00 +4559,384,43,0.0,15,0,1983-08-28 00:00:00 +4560,384,50,0.0,13,0,1983-08-28 00:00:00 +4561,384,53,1.0,11,0,1983-08-28 00:00:00 +4562,384,49,9.0,7,0,1983-08-28 00:00:00 +4563,384,31,6.0,8,0,1983-08-28 00:00:00 +4564,384,5,80.0,1,4,1983-08-28 00:00:00 +4565,384,51,3.0,10,0,1983-08-28 00:00:00 +4566,384,3,68.0,2,4,1983-08-28 00:00:00 +4567,384,20,4.0,9,0,1983-08-28 00:00:00 +4568,384,2,36.0,4,1,1983-08-28 00:00:00 +4569,384,0,34.0,5,1,1983-08-28 00:00:00 +4570,384,33,41.0,3,1,1983-08-28 00:00:00 +4571,384,24,12.0,6,1,1983-08-28 00:00:00 +4572,385,53,1.0,11,0,1983-09-11 00:00:00 +4573,385,50,0.0,13,0,1983-09-11 00:00:00 +4574,385,43,0.0,15,0,1983-09-11 00:00:00 +4575,385,49,9.0,7,0,1983-09-11 00:00:00 +4576,385,26,0.0,12,0,1983-09-11 00:00:00 +4577,385,48,0.0,16,0,1983-09-11 00:00:00 +4578,385,31,8.0,8,0,1983-09-11 00:00:00 +4579,385,52,0.0,14,0,1983-09-11 00:00:00 +4580,385,51,4.0,9,0,1983-09-11 00:00:00 +4581,385,3,72.0,2,4,1983-09-11 00:00:00 +4582,385,20,4.0,10,0,1983-09-11 00:00:00 +4583,385,5,89.0,1,4,1983-09-11 00:00:00 +4584,385,2,36.0,4,1,1983-09-11 00:00:00 +4585,385,0,34.0,5,1,1983-09-11 00:00:00 +4586,385,33,50.0,3,2,1983-09-11 00:00:00 +4587,385,24,12.0,6,1,1983-09-11 00:00:00 +4588,386,2,36.0,4,1,1983-09-25 00:00:00 +4589,386,33,59.0,3,3,1983-09-25 00:00:00 +4590,386,3,78.0,2,4,1983-09-25 00:00:00 +4591,386,20,4.0,10,0,1983-09-25 00:00:00 +4592,386,48,0.0,16,0,1983-09-25 00:00:00 +4593,386,49,12.0,7,0,1983-09-25 00:00:00 +4594,386,0,34.0,5,1,1983-09-25 00:00:00 +4595,386,51,7.0,9,0,1983-09-25 00:00:00 +4596,386,5,89.0,1,4,1983-09-25 00:00:00 +4597,386,31,12.0,8,0,1983-09-25 00:00:00 +4598,386,53,1.0,11,0,1983-09-25 00:00:00 +4599,386,52,0.0,14,0,1983-09-25 00:00:00 +4600,386,26,0.0,12,0,1983-09-25 00:00:00 +4601,386,43,0.0,15,0,1983-09-25 00:00:00 +4602,386,50,0.0,13,0,1983-09-25 00:00:00 +4603,386,24,12.0,6,1,1983-09-25 00:00:00 +4604,387,50,0.0,13,0,1983-10-15 00:00:00 +4605,387,43,0.0,15,0,1983-10-15 00:00:00 +4606,387,49,18.0,6,0,1983-10-15 00:00:00 +4607,387,26,0.0,12,0,1983-10-15 00:00:00 +4608,387,52,0.0,14,0,1983-10-15 00:00:00 +4609,387,48,0.0,16,0,1983-10-15 00:00:00 +4610,387,53,1.0,11,0,1983-10-15 00:00:00 +4611,387,31,12.0,8,0,1983-10-15 00:00:00 +4612,387,24,12.0,7,1,1983-10-15 00:00:00 +4613,387,3,79.0,2,4,1983-10-15 00:00:00 +4614,387,20,4.0,10,0,1983-10-15 00:00:00 +4615,387,5,89.0,1,4,1983-10-15 00:00:00 +4616,387,2,38.0,4,1,1983-10-15 00:00:00 +4617,387,0,34.0,5,1,1983-10-15 00:00:00 +4618,387,33,72.0,3,4,1983-10-15 00:00:00 +4619,387,51,10.0,9,0,1983-10-15 00:00:00 +4620,388,33,0.0,9,0,1984-03-25 00:00:00 +4621,388,50,0.0,13,0,1984-03-25 00:00:00 +4622,388,51,0.0,12,0,1984-03-25 00:00:00 +4623,388,43,0.0,11,0,1984-03-25 00:00:00 +4624,388,5,0.0,10,0,1984-03-25 00:00:00 +4625,388,26,0.0,8,0,1984-03-25 00:00:00 +4626,388,49,3.0,4,0,1984-03-25 00:00:00 +4627,388,20,1.0,6,0,1984-03-25 00:00:00 +4628,388,3,2.0,5,0,1984-03-25 00:00:00 +4629,388,0,9.0,1,1,1984-03-25 00:00:00 +4630,388,31,4.0,3,0,1984-03-25 00:00:00 +4631,388,2,6.0,2,0,1984-03-25 00:00:00 +4632,388,48,0.0,7,0,1984-03-25 00:00:00 +4633,389,52,0.0,14,0,1984-04-07 00:00:00 +4634,389,24,0.0,12,0,1984-04-07 00:00:00 +4635,389,50,0.0,10,0,1984-04-07 00:00:00 +4636,389,51,1.0,8,0,1984-04-07 00:00:00 +4637,389,43,0.0,15,0,1984-04-07 00:00:00 +4638,389,5,0.0,11,0,1984-04-07 00:00:00 +4639,389,33,0.0,13,0,1984-04-07 00:00:00 +4640,389,48,0.0,9,0,1984-04-07 00:00:00 +4641,389,20,1.0,7,0,1984-04-07 00:00:00 +4642,389,3,6.0,3,0,1984-04-07 00:00:00 +4643,389,49,6.0,4,0,1984-04-07 00:00:00 +4644,389,31,4.0,5,0,1984-04-07 00:00:00 +4645,389,2,6.0,2,0,1984-04-07 00:00:00 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+5988,474,43,0.0,16,0,1989-07-09 00:00:00 +5989,474,32,0.0,15,0,1989-07-09 00:00:00 +5990,474,34,8.0,6,0,1989-07-09 00:00:00 +5991,474,5,15.0,3,1,1989-07-09 00:00:00 +5992,474,36,4.0,9,0,1989-07-09 00:00:00 +5993,474,21,13.0,4,0,1989-07-09 00:00:00 +5994,474,0,65.0,1,5,1989-07-09 00:00:00 +5995,474,24,10.0,5,0,1989-07-09 00:00:00 +5996,474,31,3.0,10,0,1989-07-09 00:00:00 +5997,474,26,3.0,12,0,1989-07-09 00:00:00 +5998,474,20,8.0,7,0,1989-07-09 00:00:00 +5999,475,47,0.0,19,0,1989-07-16 00:00:00 +6000,475,41,0.0,18,0,1989-07-16 00:00:00 +6001,475,42,0.0,20,0,1989-07-16 00:00:00 +6002,475,17,3.0,13,0,1989-07-16 00:00:00 +6003,475,43,0.0,17,0,1989-07-16 00:00:00 +6004,475,33,5.0,9,0,1989-07-16 00:00:00 +6005,475,2,35.0,2,1,1989-07-16 00:00:00 +6006,475,31,6.0,8,0,1989-07-16 00:00:00 +6007,475,34,8.0,6,0,1989-07-16 00:00:00 +6008,475,32,0.0,16,0,1989-07-16 00:00:00 +6009,475,26,3.0,12,0,1989-07-16 00:00:00 +6010,475,38,1.0,15,0,1989-07-16 00:00:00 +6011,475,24,10.0,5,0,1989-07-16 00:00:00 +6012,475,20,8.0,7,0,1989-07-16 00:00:00 +6013,475,21,17.0,4,0,1989-07-16 00:00:00 +6014,475,36,4.0,10,0,1989-07-16 00:00:00 +6015,475,46,3.0,11,0,1989-07-16 00:00:00 +6016,475,44,2.0,14,0,1989-07-16 00:00:00 +6017,475,5,21.0,3,1,1989-07-16 00:00:00 +6018,475,0,74.0,1,6,1989-07-16 00:00:00 +6019,476,5,25.0,3,1,1989-07-30 00:00:00 +6020,476,44,2.0,14,0,1989-07-30 00:00:00 +6021,476,38,1.0,15,0,1989-07-30 00:00:00 +6022,476,41,0.0,18,0,1989-07-30 00:00:00 +6023,476,42,0.0,20,0,1989-07-30 00:00:00 +6024,476,17,3.0,13,0,1989-07-30 00:00:00 +6025,476,43,0.0,17,0,1989-07-30 00:00:00 +6026,476,33,5.0,9,0,1989-07-30 00:00:00 +6027,476,0,89.0,1,7,1989-07-30 00:00:00 +6028,476,47,0.0,19,0,1989-07-30 00:00:00 +6029,476,46,3.0,11,0,1989-07-30 00:00:00 +6030,476,34,8.0,7,0,1989-07-30 00:00:00 +6031,476,32,0.0,16,0,1989-07-30 00:00:00 +6032,476,26,3.0,12,0,1989-07-30 00:00:00 +6033,476,31,8.0,8,0,1989-07-30 00:00:00 +6034,476,20,9.0,6,0,1989-07-30 00:00:00 +6035,476,21,17.0,4,0,1989-07-30 00:00:00 +6036,476,36,4.0,10,0,1989-07-30 00:00:00 +6037,476,2,38.0,2,1,1989-07-30 00:00:00 +6038,476,24,10.0,5,0,1989-07-30 00:00:00 +6039,477,33,5.0,9,0,1989-08-13 00:00:00 +6040,477,0,98.0,1,7,1989-08-13 00:00:00 +6041,477,5,34.0,3,2,1989-08-13 00:00:00 +6042,477,44,2.0,14,0,1989-08-13 00:00:00 +6043,477,38,1.0,15,0,1989-08-13 00:00:00 +6044,477,41,0.0,18,0,1989-08-13 00:00:00 +6045,477,42,0.0,20,0,1989-08-13 00:00:00 +6046,477,43,0.0,17,0,1989-08-13 00:00:00 +6047,477,47,0.0,19,0,1989-08-13 00:00:00 +6048,477,2,42.0,2,1,1989-08-13 00:00:00 +6049,477,17,3.0,13,0,1989-08-13 00:00:00 +6050,477,34,8.0,8,0,1989-08-13 00:00:00 +6051,477,46,3.0,11,0,1989-08-13 00:00:00 +6052,477,21,17.0,4,0,1989-08-13 00:00:00 +6053,477,20,11.0,5,0,1989-08-13 00:00:00 +6054,477,24,10.0,6,0,1989-08-13 00:00:00 +6055,477,36,4.0,10,0,1989-08-13 00:00:00 +6056,477,26,3.0,12,0,1989-08-13 00:00:00 +6057,477,32,0.0,16,0,1989-08-13 00:00:00 +6058,477,31,9.0,7,0,1989-08-13 00:00:00 +6059,478,2,45.0,2,1,1989-08-27 00:00:00 +6060,478,44,2.0,14,0,1989-08-27 00:00:00 +6061,478,38,1.0,15,0,1989-08-27 00:00:00 +6062,478,41,0.0,18,0,1989-08-27 00:00:00 +6063,478,42,0.0,20,0,1989-08-27 00:00:00 +6064,478,43,0.0,17,0,1989-08-27 00:00:00 +6065,478,33,5.0,9,0,1989-08-27 00:00:00 +6066,478,47,0.0,19,0,1989-08-27 00:00:00 +6067,478,46,3.0,11,0,1989-08-27 00:00:00 +6068,478,17,3.0,13,0,1989-08-27 00:00:00 +6069,478,32,0.0,16,0,1989-08-27 00:00:00 +6070,478,0,113.0,1,8,1989-08-27 00:00:00 +6071,478,36,4.0,10,0,1989-08-27 00:00:00 +6072,478,21,19.0,4,0,1989-08-27 00:00:00 +6073,478,20,12.0,5,0,1989-08-27 00:00:00 +6074,478,34,8.0,8,0,1989-08-27 00:00:00 +6075,478,24,10.0,6,0,1989-08-27 00:00:00 +6076,478,31,9.0,7,0,1989-08-27 00:00:00 +6077,478,26,3.0,12,0,1989-08-27 00:00:00 +6078,478,5,38.0,3,2,1989-08-27 00:00:00 +6079,479,2,52.0,2,1,1989-09-10 00:00:00 +6080,479,38,1.0,15,0,1989-09-10 00:00:00 +6081,479,41,0.0,18,0,1989-09-10 00:00:00 +6082,479,42,0.0,20,0,1989-09-10 00:00:00 +6083,479,17,3.0,13,0,1989-09-10 00:00:00 +6084,479,43,0.0,17,0,1989-09-10 00:00:00 +6085,479,33,6.0,9,0,1989-09-10 00:00:00 +6086,479,47,0.0,19,0,1989-09-10 00:00:00 +6087,479,44,2.0,14,0,1989-09-10 00:00:00 +6088,479,46,3.0,11,0,1989-09-10 00:00:00 +6089,479,32,0.0,16,0,1989-09-10 00:00:00 +6090,479,26,3.0,12,0,1989-09-10 00:00:00 +6091,479,31,9.0,7,0,1989-09-10 00:00:00 +6092,479,24,12.0,5,0,1989-09-10 00:00:00 +6093,479,20,12.0,6,0,1989-09-10 00:00:00 +6094,479,21,19.0,4,0,1989-09-10 00:00:00 +6095,479,36,4.0,10,0,1989-09-10 00:00:00 +6096,479,0,122.0,1,9,1989-09-10 00:00:00 +6097,479,5,44.0,3,2,1989-09-10 00:00:00 +6098,479,34,8.0,8,0,1989-09-10 00:00:00 +6099,480,33,6.0,10,0,1989-09-24 00:00:00 +6100,480,43,0.0,17,0,1989-09-24 00:00:00 +6101,480,17,5.0,11,0,1989-09-24 00:00:00 +6102,480,47,0.0,19,0,1989-09-24 00:00:00 +6103,480,41,0.0,18,0,1989-09-24 00:00:00 +6104,480,38,1.0,15,0,1989-09-24 00:00:00 +6105,480,44,6.0,9,0,1989-09-24 00:00:00 +6106,480,42,0.0,20,0,1989-09-24 00:00:00 +6107,480,2,52.0,3,1,1989-09-24 00:00:00 +6108,480,24,13.0,5,0,1989-09-24 00:00:00 +6109,480,34,8.0,8,0,1989-09-24 00:00:00 +6110,480,0,128.0,1,9,1989-09-24 00:00:00 +6111,480,36,4.0,12,0,1989-09-24 00:00:00 +6112,480,21,22.0,4,0,1989-09-24 00:00:00 +6113,480,20,12.0,6,0,1989-09-24 00:00:00 +6114,480,46,3.0,13,0,1989-09-24 00:00:00 +6115,480,31,9.0,7,0,1989-09-24 00:00:00 +6116,480,26,3.0,14,0,1989-09-24 00:00:00 +6117,480,32,0.0,16,0,1989-09-24 00:00:00 +6118,480,5,53.0,2,3,1989-09-24 00:00:00 +6119,481,47,0.0,19,0,1989-10-01 00:00:00 +6120,481,44,6.0,9,0,1989-10-01 00:00:00 +6121,481,38,1.0,15,0,1989-10-01 00:00:00 +6122,481,41,0.0,18,0,1989-10-01 00:00:00 +6123,481,42,0.0,20,0,1989-10-01 00:00:00 +6124,481,17,5.0,11,0,1989-10-01 00:00:00 +6125,481,43,0.0,17,0,1989-10-01 00:00:00 +6126,481,33,6.0,10,0,1989-10-01 00:00:00 +6127,481,2,54.0,3,1,1989-10-01 00:00:00 +6128,481,46,3.0,13,0,1989-10-01 00:00:00 +6129,481,34,8.0,8,0,1989-10-01 00:00:00 +6130,481,0,141.0,1,10,1989-10-01 00:00:00 +6131,481,36,4.0,12,0,1989-10-01 00:00:00 +6132,481,21,22.0,4,0,1989-10-01 00:00:00 +6133,481,20,12.0,6,0,1989-10-01 00:00:00 +6134,481,5,59.0,2,3,1989-10-01 00:00:00 +6135,481,31,9.0,7,0,1989-10-01 00:00:00 +6136,481,26,3.0,14,0,1989-10-01 00:00:00 +6137,481,32,1.0,16,0,1989-10-01 00:00:00 +6138,481,24,16.0,5,0,1989-10-01 00:00:00 +6139,482,43,0.0,17,0,1989-10-22 00:00:00 +6140,482,38,1.0,15,0,1989-10-22 00:00:00 +6141,482,0,141.0,1,10,1989-10-22 00:00:00 +6142,482,5,59.0,3,3,1989-10-22 00:00:00 +6143,482,36,4.0,12,0,1989-10-22 00:00:00 +6144,482,21,31.0,4,1,1989-10-22 00:00:00 +6145,482,20,13.0,6,0,1989-10-22 00:00:00 +6146,482,42,0.0,20,0,1989-10-22 00:00:00 +6147,482,17,5.0,11,0,1989-10-22 00:00:00 +6148,482,33,8.0,9,0,1989-10-22 00:00:00 +6149,482,41,0.0,18,0,1989-10-22 00:00:00 +6150,482,2,64.0,2,1,1989-10-22 00:00:00 +6151,482,46,3.0,13,0,1989-10-22 00:00:00 +6152,482,34,8.0,8,0,1989-10-22 00:00:00 +6153,482,32,1.0,16,0,1989-10-22 00:00:00 +6154,482,26,3.0,14,0,1989-10-22 00:00:00 +6155,482,31,12.0,7,0,1989-10-22 00:00:00 +6156,482,24,16.0,5,0,1989-10-22 00:00:00 +6157,482,44,6.0,10,0,1989-10-22 00:00:00 +6158,482,47,0.0,19,0,1989-10-22 00:00:00 +6159,483,47,0.0,19,0,1989-11-05 00:00:00 +6160,483,33,8.0,9,0,1989-11-05 00:00:00 +6161,483,43,0.0,17,0,1989-11-05 00:00:00 +6162,483,38,1.0,15,0,1989-11-05 00:00:00 +6163,483,42,0.0,20,0,1989-11-05 00:00:00 +6164,483,41,0.0,18,0,1989-11-05 00:00:00 +6165,483,44,6.0,10,0,1989-11-05 00:00:00 +6166,483,17,6.0,11,0,1989-11-05 00:00:00 +6167,483,2,77.0,2,2,1989-11-05 00:00:00 +6168,483,26,3.0,14,0,1989-11-05 00:00:00 +6169,483,34,8.0,8,0,1989-11-05 00:00:00 +6170,483,0,141.0,1,10,1989-11-05 00:00:00 +6171,483,5,59.0,3,3,1989-11-05 00:00:00 +6172,483,36,4.0,12,0,1989-11-05 00:00:00 +6173,483,21,39.0,4,1,1989-11-05 00:00:00 +6174,483,46,3.0,13,0,1989-11-05 00:00:00 +6175,483,24,16.0,5,0,1989-11-05 00:00:00 +6176,483,31,15.0,6,0,1989-11-05 00:00:00 +6177,483,32,1.0,16,0,1989-11-05 00:00:00 +6178,483,20,13.0,7,0,1989-11-05 00:00:00 +6179,484,31,0.0,14,0,1990-03-11 00:00:00 +6180,484,26,0.0,15,0,1990-03-11 00:00:00 +6181,484,44,0.0,16,0,1990-03-11 00:00:00 +6182,484,38,0.0,17,0,1990-03-11 00:00:00 +6183,484,45,0.0,18,0,1990-03-11 00:00:00 +6184,484,41,0.0,19,0,1990-03-11 00:00:00 +6185,484,0,9.0,1,1,1990-03-11 00:00:00 +6186,484,2,4.0,3,0,1990-03-11 00:00:00 +6187,484,43,0.0,12,0,1990-03-11 00:00:00 +6188,484,21,3.0,4,0,1990-03-11 00:00:00 +6189,484,33,2.0,5,0,1990-03-11 00:00:00 +6190,484,17,0.0,6,0,1990-03-11 00:00:00 +6191,484,32,0.0,7,0,1990-03-11 00:00:00 +6192,484,20,0.0,8,0,1990-03-11 00:00:00 +6193,484,42,0.0,9,0,1990-03-11 00:00:00 +6194,484,40,0.0,10,0,1990-03-11 00:00:00 +6195,484,24,7.0,2,0,1990-03-11 00:00:00 +6196,484,5,0.0,11,0,1990-03-11 00:00:00 +6197,484,34,0.0,13,0,1990-03-11 00:00:00 +6198,485,40,0.0,13,0,1990-03-25 00:00:00 +6199,485,34,0.0,12,0,1990-03-25 00:00:00 +6200,485,43,0.0,16,0,1990-03-25 00:00:00 +6201,485,41,0.0,18,0,1990-03-25 00:00:00 +6202,485,42,0.0,11,0,1990-03-25 00:00:00 +6203,485,38,0.0,15,0,1990-03-25 00:00:00 +6204,485,44,0.0,17,0,1990-03-25 00:00:00 +6205,485,26,0.0,10,0,1990-03-25 00:00:00 +6206,485,31,0.0,14,0,1990-03-25 00:00:00 +6207,485,45,0.0,19,0,1990-03-25 00:00:00 +6208,485,5,12.0,2,1,1990-03-25 00:00:00 +6209,485,24,7.0,3,0,1990-03-25 00:00:00 +6210,485,2,6.0,4,0,1990-03-25 00:00:00 +6211,485,21,4.0,5,0,1990-03-25 00:00:00 +6212,485,33,2.0,6,0,1990-03-25 00:00:00 +6213,485,17,0.0,7,0,1990-03-25 00:00:00 +6214,485,32,0.0,8,0,1990-03-25 00:00:00 +6215,485,20,0.0,9,0,1990-03-25 00:00:00 +6216,485,0,19.0,1,1,1990-03-25 00:00:00 +6217,486,24,8.0,5,0,1990-05-13 00:00:00 +6218,486,33,2.0,6,0,1990-05-13 00:00:00 +6219,486,17,0.0,8,0,1990-05-13 00:00:00 +6220,486,32,0.0,9,0,1990-05-13 00:00:00 +6221,486,20,0.0,11,0,1990-05-13 00:00:00 +6222,486,26,0.0,10,0,1990-05-13 00:00:00 +6223,486,40,0.0,15,0,1990-05-13 00:00:00 +6224,486,5,15.0,3,1,1990-05-13 00:00:00 +6225,486,43,0.0,16,0,1990-05-13 00:00:00 +6226,486,31,0.0,7,0,1990-05-13 00:00:00 +6227,486,0,25.0,1,1,1990-05-13 00:00:00 +6228,486,42,0.0,13,0,1990-05-13 00:00:00 +6229,486,34,0.0,14,0,1990-05-13 00:00:00 +6230,486,2,15.0,2,1,1990-05-13 00:00:00 +6231,486,21,10.0,4,0,1990-05-13 00:00:00 +6232,486,41,0.0,18,0,1990-05-13 00:00:00 +6233,486,45,0.0,19,0,1990-05-13 00:00:00 +6234,486,38,0.0,17,0,1990-05-13 00:00:00 +6235,486,44,0.0,12,0,1990-05-13 00:00:00 +6236,487,45,0.0,19,0,1990-05-27 00:00:00 +6237,487,44,0.0,11,0,1990-05-27 00:00:00 +6238,487,26,0.0,12,0,1990-05-27 00:00:00 +6239,487,31,0.0,9,0,1990-05-27 00:00:00 +6240,487,34,0.0,14,0,1990-05-27 00:00:00 +6241,487,43,0.0,16,0,1990-05-27 00:00:00 +6242,487,5,15.0,3,1,1990-05-27 00:00:00 +6243,487,40,0.0,15,0,1990-05-27 00:00:00 +6244,487,42,0.0,13,0,1990-05-27 00:00:00 +6245,487,20,2.0,6,0,1990-05-27 00:00:00 +6246,487,32,1.0,8,0,1990-05-27 00:00:00 +6247,487,17,0.0,10,0,1990-05-27 00:00:00 +6248,487,33,2.0,7,0,1990-05-27 00:00:00 +6249,487,21,10.0,5,0,1990-05-27 00:00:00 +6250,487,2,18.0,2,1,1990-05-27 00:00:00 +6251,487,24,14.0,4,0,1990-05-27 00:00:00 +6252,487,0,38.0,1,2,1990-05-27 00:00:00 +6253,487,38,0.0,17,0,1990-05-27 00:00:00 +6254,487,41,0.0,18,0,1990-05-27 00:00:00 +6255,488,17,0.0,10,0,1990-06-10 00:00:00 +6256,488,33,2.0,6,0,1990-06-10 00:00:00 +6257,488,21,16.0,4,0,1990-06-10 00:00:00 +6258,488,2,18.0,3,1,1990-06-10 00:00:00 +6259,488,24,14.0,5,0,1990-06-10 00:00:00 +6260,488,0,50.0,1,3,1990-06-10 00:00:00 +6261,488,42,0.0,15,0,1990-06-10 00:00:00 +6262,488,38,0.0,17,0,1990-06-10 00:00:00 +6263,488,40,0.0,13,0,1990-06-10 00:00:00 +6264,488,32,1.0,9,0,1990-06-10 00:00:00 +6265,488,5,21.0,2,1,1990-06-10 00:00:00 +6266,488,43,0.0,14,0,1990-06-10 00:00:00 +6267,488,34,0.0,16,0,1990-06-10 00:00:00 +6268,488,31,1.0,8,0,1990-06-10 00:00:00 +6269,488,20,2.0,7,0,1990-06-10 00:00:00 +6270,488,44,0.0,11,0,1990-06-10 00:00:00 +6271,488,45,0.0,19,0,1990-06-10 00:00:00 +6272,488,41,0.0,18,0,1990-06-10 00:00:00 +6273,488,26,0.0,12,0,1990-06-10 00:00:00 +6274,489,0,54.0,1,3,1990-06-24 00:00:00 +6275,489,2,20.0,3,1,1990-06-24 00:00:00 +6276,489,21,20.0,4,0,1990-06-24 00:00:00 +6277,489,33,2.0,6,0,1990-06-24 00:00:00 +6278,489,17,0.0,10,0,1990-06-24 00:00:00 +6279,489,32,1.0,9,0,1990-06-24 00:00:00 +6280,489,20,2.0,7,0,1990-06-24 00:00:00 +6281,489,40,0.0,13,0,1990-06-24 00:00:00 +6282,489,5,36.0,2,2,1990-06-24 00:00:00 +6283,489,43,0.0,15,0,1990-06-24 00:00:00 +6284,489,34,0.0,14,0,1990-06-24 00:00:00 +6285,489,26,0.0,12,0,1990-06-24 00:00:00 +6286,489,44,0.0,11,0,1990-06-24 00:00:00 +6287,489,38,0.0,17,0,1990-06-24 00:00:00 +6288,489,45,0.0,19,0,1990-06-24 00:00:00 +6289,489,41,0.0,18,0,1990-06-24 00:00:00 +6290,489,42,0.0,16,0,1990-06-24 00:00:00 +6291,489,31,1.0,8,0,1990-06-24 00:00:00 +6292,489,24,14.0,5,0,1990-06-24 00:00:00 +6293,490,45,0.0,19,0,1990-07-08 00:00:00 +6294,490,0,60.0,1,3,1990-07-08 00:00:00 +6295,490,2,21.0,4,1,1990-07-08 00:00:00 +6296,490,21,23.0,3,0,1990-07-08 00:00:00 +6297,490,33,2.0,7,0,1990-07-08 00:00:00 +6298,490,17,0.0,11,0,1990-07-08 00:00:00 +6299,490,41,0.0,18,0,1990-07-08 00:00:00 +6300,490,20,2.0,8,0,1990-07-08 00:00:00 +6301,490,42,0.0,16,0,1990-07-08 00:00:00 +6302,490,32,1.0,9,0,1990-07-08 00:00:00 +6303,490,5,45.0,2,3,1990-07-08 00:00:00 +6304,490,43,0.0,15,0,1990-07-08 00:00:00 +6305,490,34,0.0,14,0,1990-07-08 00:00:00 +6306,490,31,1.0,10,0,1990-07-08 00:00:00 +6307,490,26,0.0,13,0,1990-07-08 00:00:00 +6308,490,44,0.0,12,0,1990-07-08 00:00:00 +6309,490,38,0.0,17,0,1990-07-08 00:00:00 +6310,490,40,6.0,6,0,1990-07-08 00:00:00 +6311,490,24,14.0,5,0,1990-07-08 00:00:00 +6312,491,34,0.0,14,0,1990-07-15 00:00:00 +6313,491,31,1.0,10,0,1990-07-15 00:00:00 +6314,491,26,0.0,13,0,1990-07-15 00:00:00 +6315,491,44,0.0,12,0,1990-07-15 00:00:00 +6316,491,38,0.0,17,0,1990-07-15 00:00:00 +6317,491,43,0.0,15,0,1990-07-15 00:00:00 +6318,491,40,6.0,6,0,1990-07-15 00:00:00 +6319,491,20,2.0,8,0,1990-07-15 00:00:00 +6320,491,45,0.0,19,0,1990-07-15 00:00:00 +6321,491,0,64.0,1,3,1990-07-15 00:00:00 +6322,491,24,14.0,5,0,1990-07-15 00:00:00 +6323,491,2,27.0,3,1,1990-07-15 00:00:00 +6324,491,42,0.0,16,0,1990-07-15 00:00:00 +6325,491,32,5.0,7,0,1990-07-15 00:00:00 +6326,491,17,0.0,11,0,1990-07-15 00:00:00 +6327,491,33,2.0,9,0,1990-07-15 00:00:00 +6328,491,21,25.0,4,0,1990-07-15 00:00:00 +6329,491,41,0.0,18,0,1990-07-15 00:00:00 +6330,491,5,54.0,2,4,1990-07-15 00:00:00 +6331,492,45,0.0,19,0,1990-07-29 00:00:00 +6332,492,41,0.0,18,0,1990-07-29 00:00:00 +6333,492,0,77.0,1,4,1990-07-29 00:00:00 +6334,492,2,30.0,4,1,1990-07-29 00:00:00 +6335,492,21,31.0,3,0,1990-07-29 00:00:00 +6336,492,38,0.0,17,0,1990-07-29 00:00:00 +6337,492,44,0.0,12,0,1990-07-29 00:00:00 +6338,492,26,0.0,13,0,1990-07-29 00:00:00 +6339,492,34,0.0,14,0,1990-07-29 00:00:00 +6340,492,43,0.0,15,0,1990-07-29 00:00:00 +6341,492,24,14.0,5,0,1990-07-29 00:00:00 +6342,492,31,1.0,10,0,1990-07-29 00:00:00 +6343,492,40,6.0,6,0,1990-07-29 00:00:00 +6344,492,42,0.0,16,0,1990-07-29 00:00:00 +6345,492,20,2.0,8,0,1990-07-29 00:00:00 +6346,492,32,5.0,7,0,1990-07-29 00:00:00 +6347,492,17,0.0,11,0,1990-07-29 00:00:00 +6348,492,33,2.0,9,0,1990-07-29 00:00:00 +6349,492,5,57.0,2,4,1990-07-29 00:00:00 +6350,493,45,0.0,19,0,1990-08-12 00:00:00 +6351,493,41,0.0,18,0,1990-08-12 00:00:00 +6352,493,42,0.0,17,0,1990-08-12 00:00:00 +6353,493,20,2.0,9,0,1990-08-12 00:00:00 +6354,493,38,0.0,15,0,1990-08-12 00:00:00 +6355,493,44,0.0,12,0,1990-08-12 00:00:00 +6356,493,26,0.0,13,0,1990-08-12 00:00:00 +6357,493,24,14.0,5,0,1990-08-12 00:00:00 +6358,493,2,42.0,3,2,1990-08-12 00:00:00 +6359,493,21,35.0,4,0,1990-08-12 00:00:00 +6360,493,33,2.0,10,0,1990-08-12 00:00:00 +6361,493,17,0.0,11,0,1990-08-12 00:00:00 +6362,493,32,6.0,7,0,1990-08-12 00:00:00 +6363,493,0,83.0,1,4,1990-08-12 00:00:00 +6364,493,40,6.0,6,0,1990-08-12 00:00:00 +6365,493,31,3.0,8,0,1990-08-12 00:00:00 +6366,493,5,57.0,2,4,1990-08-12 00:00:00 +6367,493,43,0.0,16,0,1990-08-12 00:00:00 +6368,493,34,0.0,14,0,1990-08-12 00:00:00 +6369,494,0,96.0,1,5,1990-08-26 00:00:00 +6370,494,21,40.0,4,0,1990-08-26 00:00:00 +6371,494,2,42.0,3,2,1990-08-26 00:00:00 +6372,494,24,14.0,5,0,1990-08-26 00:00:00 +6373,494,45,0.0,19,0,1990-08-26 00:00:00 +6374,494,41,0.0,18,0,1990-08-26 00:00:00 +6375,494,38,0.0,16,0,1990-08-26 00:00:00 +6376,494,31,3.0,8,0,1990-08-26 00:00:00 +6377,494,33,2.0,10,0,1990-08-26 00:00:00 +6378,494,17,0.0,11,0,1990-08-26 00:00:00 +6379,494,32,6.0,7,0,1990-08-26 00:00:00 +6380,494,20,2.0,9,0,1990-08-26 00:00:00 +6381,494,42,0.0,17,0,1990-08-26 00:00:00 +6382,494,40,7.0,6,0,1990-08-26 00:00:00 +6383,494,5,63.0,2,4,1990-08-26 00:00:00 +6384,494,43,0.0,15,0,1990-08-26 00:00:00 +6385,494,34,0.0,14,0,1990-08-26 00:00:00 +6386,494,26,0.0,13,0,1990-08-26 00:00:00 +6387,494,44,0.0,12,0,1990-08-26 00:00:00 +6388,495,32,6.0,7,0,1990-09-09 00:00:00 +6389,495,17,0.0,11,0,1990-09-09 00:00:00 +6390,495,33,2.0,10,0,1990-09-09 00:00:00 +6391,495,24,15.0,5,0,1990-09-09 00:00:00 +6392,495,21,40.0,4,0,1990-09-09 00:00:00 +6393,495,0,109.0,1,6,1990-09-09 00:00:00 +6394,495,2,44.0,3,2,1990-09-09 00:00:00 +6395,495,20,2.0,9,0,1990-09-09 00:00:00 +6396,495,42,0.0,17,0,1990-09-09 00:00:00 +6397,495,44,0.0,12,0,1990-09-09 00:00:00 +6398,495,5,72.0,2,4,1990-09-09 00:00:00 +6399,495,43,0.0,15,0,1990-09-09 00:00:00 +6400,495,34,0.0,14,0,1990-09-09 00:00:00 +6401,495,31,3.0,8,0,1990-09-09 00:00:00 +6402,495,26,0.0,13,0,1990-09-09 00:00:00 +6403,495,38,0.0,16,0,1990-09-09 00:00:00 +6404,495,45,0.0,19,0,1990-09-09 00:00:00 +6405,495,41,0.0,18,0,1990-09-09 00:00:00 +6406,495,40,7.0,6,0,1990-09-09 00:00:00 +6407,496,0,118.0,1,6,1990-09-23 00:00:00 +6408,496,24,15.0,5,0,1990-09-23 00:00:00 +6409,496,2,44.0,3,2,1990-09-23 00:00:00 +6410,496,20,2.0,9,0,1990-09-23 00:00:00 +6411,496,33,2.0,10,0,1990-09-23 00:00:00 +6412,496,32,6.0,7,0,1990-09-23 00:00:00 +6413,496,21,43.0,4,0,1990-09-23 00:00:00 +6414,496,42,0.0,17,0,1990-09-23 00:00:00 +6415,496,17,0.0,11,0,1990-09-23 00:00:00 +6416,496,5,85.0,2,5,1990-09-23 00:00:00 +6417,496,43,0.0,15,0,1990-09-23 00:00:00 +6418,496,34,0.0,14,0,1990-09-23 00:00:00 +6419,496,31,3.0,8,0,1990-09-23 00:00:00 +6420,496,26,0.0,13,0,1990-09-23 00:00:00 +6421,496,44,0.0,12,0,1990-09-23 00:00:00 +6422,496,38,0.0,16,0,1990-09-23 00:00:00 +6423,496,45,0.0,19,0,1990-09-23 00:00:00 +6424,496,41,0.0,18,0,1990-09-23 00:00:00 +6425,496,40,7.0,6,0,1990-09-23 00:00:00 +6426,497,31,3.0,8,0,1990-09-30 00:00:00 +6427,497,34,0.0,15,0,1990-09-30 00:00:00 +6428,497,43,0.0,16,0,1990-09-30 00:00:00 +6429,497,5,100.0,2,6,1990-09-30 00:00:00 +6430,497,40,7.0,6,0,1990-09-30 00:00:00 +6431,497,42,0.0,17,0,1990-09-30 00:00:00 +6432,497,33,2.0,10,0,1990-09-30 00:00:00 +6433,497,32,7.0,7,0,1990-09-30 00:00:00 +6434,497,17,0.0,12,0,1990-09-30 00:00:00 +6435,497,24,15.0,5,0,1990-09-30 00:00:00 +6436,497,21,47.0,4,0,1990-09-30 00:00:00 +6437,497,2,49.0,3,2,1990-09-30 00:00:00 +6438,497,20,2.0,9,0,1990-09-30 00:00:00 +6439,497,44,0.0,13,0,1990-09-30 00:00:00 +6440,497,26,0.0,11,0,1990-09-30 00:00:00 +6441,497,0,118.0,1,6,1990-09-30 00:00:00 +6442,497,45,0.0,19,0,1990-09-30 00:00:00 +6443,497,41,0.0,18,0,1990-09-30 00:00:00 +6444,497,38,0.0,14,0,1990-09-30 00:00:00 +6445,498,38,0.0,14,0,1990-10-21 00:00:00 +6446,498,44,0.0,13,0,1990-10-21 00:00:00 +6447,498,26,0.0,11,0,1990-10-21 00:00:00 +6448,498,31,3.0,8,0,1990-10-21 00:00:00 +6449,498,34,0.0,15,0,1990-10-21 00:00:00 +6450,498,43,0.0,16,0,1990-10-21 00:00:00 +6451,498,5,100.0,2,6,1990-10-21 00:00:00 +6452,498,40,7.0,7,0,1990-10-21 00:00:00 +6453,498,17,0.0,12,0,1990-10-21 00:00:00 +6454,498,20,2.0,9,0,1990-10-21 00:00:00 +6455,498,32,11.0,6,0,1990-10-21 00:00:00 +6456,498,41,0.0,18,0,1990-10-21 00:00:00 +6457,498,0,118.0,1,6,1990-10-21 00:00:00 +6458,498,24,16.0,5,0,1990-10-21 00:00:00 +6459,498,2,54.0,4,2,1990-10-21 00:00:00 +6460,498,21,62.0,3,1,1990-10-21 00:00:00 +6461,498,33,2.0,10,0,1990-10-21 00:00:00 +6462,498,45,0.0,19,0,1990-10-21 00:00:00 +6463,498,42,0.0,17,0,1990-10-21 00:00:00 +6464,499,26,0.0,11,0,1990-11-04 00:00:00 +6465,499,44,0.0,13,0,1990-11-04 00:00:00 +6466,499,38,0.0,14,0,1990-11-04 00:00:00 +6467,499,31,3.0,8,0,1990-11-04 00:00:00 +6468,499,2,57.0,4,2,1990-11-04 00:00:00 +6469,499,5,110.0,2,6,1990-11-04 00:00:00 +6470,499,40,7.0,7,0,1990-11-04 00:00:00 +6471,499,42,0.0,17,0,1990-11-04 00:00:00 +6472,499,20,2.0,9,0,1990-11-04 00:00:00 +6473,499,32,11.0,6,0,1990-11-04 00:00:00 +6474,499,17,0.0,12,0,1990-11-04 00:00:00 +6475,499,33,2.0,10,0,1990-11-04 00:00:00 +6476,499,21,71.0,3,2,1990-11-04 00:00:00 +6477,499,24,16.0,5,0,1990-11-04 00:00:00 +6478,499,0,121.0,1,6,1990-11-04 00:00:00 +6479,499,43,0.0,16,0,1990-11-04 00:00:00 +6480,499,34,0.0,15,0,1990-11-04 00:00:00 +6481,499,45,0.0,19,0,1990-11-04 00:00:00 +6482,499,41,0.0,18,0,1990-11-04 00:00:00 +6483,500,16,0.0,9,0,1991-03-10 00:00:00 +6484,500,40,0.0,14,0,1991-03-10 00:00:00 +6485,500,33,0.0,10,0,1991-03-10 00:00:00 +6486,500,31,0.0,11,0,1991-03-10 00:00:00 +6487,500,2,0.0,12,0,1991-03-10 00:00:00 +6488,500,28,0.0,13,0,1991-03-10 00:00:00 +6489,500,41,0.0,17,0,1991-03-10 00:00:00 +6490,500,26,0.0,15,0,1991-03-10 00:00:00 +6491,500,34,0.0,16,0,1991-03-10 00:00:00 +6492,500,38,0.0,7,0,1991-03-10 00:00:00 +6493,500,0,10.0,1,1,1991-03-10 00:00:00 +6494,500,5,6.0,2,0,1991-03-10 00:00:00 +6495,500,21,4.0,4,0,1991-03-10 00:00:00 +6496,500,24,5.0,3,0,1991-03-10 00:00:00 +6497,500,32,1.0,5,0,1991-03-10 00:00:00 +6498,500,39,0.0,6,0,1991-03-10 00:00:00 +6499,500,35,0.0,18,0,1991-03-10 00:00:00 +6500,500,17,0.0,8,0,1991-03-10 00:00:00 +6501,501,33,0.0,13,0,1991-03-24 00:00:00 +6502,501,0,24.0,1,2,1991-03-24 00:00:00 +6503,501,5,10.0,2,0,1991-03-24 00:00:00 +6504,501,21,6.0,4,0,1991-03-24 00:00:00 +6505,501,24,5.0,5,0,1991-03-24 00:00:00 +6506,501,35,0.0,17,0,1991-03-24 00:00:00 +6507,501,31,0.0,10,0,1991-03-24 00:00:00 +6508,501,34,0.0,14,0,1991-03-24 00:00:00 +6509,501,41,0.0,18,0,1991-03-24 00:00:00 +6510,501,40,0.0,16,0,1991-03-24 00:00:00 +6511,501,28,0.0,15,0,1991-03-24 00:00:00 +6512,501,2,6.0,3,0,1991-03-24 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+9173,725,0,37.0,5,0,2004-08-15 00:00:00 +9174,725,17,1.0,10,0,2004-08-15 00:00:00 +9175,725,16,5.0,9,0,2004-08-15 00:00:00 +9176,725,6,8.0,7,0,2004-08-15 00:00:00 +9177,725,18,7.0,8,0,2004-08-15 00:00:00 +9178,725,14,19.0,6,0,2004-08-15 00:00:00 +9179,726,3,91.0,2,1,2004-08-29 00:00:00 +9180,726,2,54.0,4,0,2004-08-29 00:00:00 +9181,726,15,83.0,3,0,2004-08-29 00:00:00 +9182,726,0,49.0,5,1,2004-08-29 00:00:00 +9183,726,5,216.0,1,12,2004-08-29 00:00:00 +9184,726,18,10.0,7,0,2004-08-29 00:00:00 +9185,726,6,9.0,8,0,2004-08-29 00:00:00 +9186,726,16,5.0,9,0,2004-08-29 00:00:00 +9187,726,14,28.0,6,0,2004-08-29 00:00:00 +9188,726,17,1.0,10,0,2004-08-29 00:00:00 +9189,727,15,94.0,2,0,2004-09-12 00:00:00 +9190,727,5,234.0,1,13,2004-09-12 00:00:00 +9191,727,3,91.0,3,1,2004-09-12 00:00:00 +9192,727,2,60.0,4,0,2004-09-12 00:00:00 +9193,727,0,52.0,5,1,2004-09-12 00:00:00 +9194,727,14,29.0,6,0,2004-09-12 00:00:00 +9195,727,18,10.0,7,0,2004-09-12 00:00:00 +9196,727,6,9.0,8,0,2004-09-12 00:00:00 +9197,727,16,5.0,9,0,2004-09-12 00:00:00 +9198,727,17,1.0,10,0,2004-09-12 00:00:00 +9199,728,5,244.0,1,14,2004-09-26 00:00:00 +9200,728,3,96.0,3,1,2004-09-26 00:00:00 +9201,728,2,64.0,4,0,2004-09-26 00:00:00 +9202,728,15,105.0,2,0,2004-09-26 00:00:00 +9203,728,17,1.0,10,0,2004-09-26 00:00:00 +9204,728,14,32.0,6,0,2004-09-26 00:00:00 +9205,728,18,10.0,7,0,2004-09-26 00:00:00 +9206,728,6,9.0,8,0,2004-09-26 00:00:00 +9207,728,16,5.0,9,0,2004-09-26 00:00:00 +9208,728,0,58.0,5,1,2004-09-26 00:00:00 +9209,729,2,74.0,4,0,2004-10-10 00:00:00 +9210,729,5,254.0,1,15,2004-10-10 00:00:00 +9211,729,3,100.0,3,1,2004-10-10 00:00:00 +9212,729,15,116.0,2,0,2004-10-10 00:00:00 +9213,729,16,5.0,9,0,2004-10-10 00:00:00 +9214,729,14,33.0,6,0,2004-10-10 00:00:00 +9215,729,18,10.0,7,0,2004-10-10 00:00:00 +9216,729,6,9.0,8,0,2004-10-10 00:00:00 +9217,729,17,1.0,10,0,2004-10-10 00:00:00 +9218,729,0,61.0,5,1,2004-10-10 00:00:00 +9219,730,5,262.0,1,15,2004-10-24 00:00:00 +9220,730,3,105.0,3,1,2004-10-24 00:00:00 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+9341,742,2,47.0,5,0,2005-07-24 14:00:00 +9342,742,0,95.0,2,4,2005-07-24 14:00:00 +9343,742,8,24.0,6,0,2005-07-24 14:00:00 +9344,742,14,14.0,8,0,2005-07-24 14:00:00 +9345,742,15,15.0,7,0,2005-07-24 14:00:00 +9346,742,16,11.0,9,0,2005-07-24 14:00:00 +9347,742,17,7.0,10,0,2005-07-24 14:00:00 +9348,742,6,57.0,4,0,2005-07-24 14:00:00 +9349,743,3,117.0,1,7,2005-07-31 14:00:00 +9350,743,17,7.0,10,0,2005-07-31 14:00:00 +9351,743,16,11.0,9,0,2005-07-31 14:00:00 +9352,743,15,20.0,7,0,2005-07-31 14:00:00 +9353,743,14,14.0,8,0,2005-07-31 14:00:00 +9354,743,6,68.0,4,0,2005-07-31 14:00:00 +9355,743,0,105.0,2,5,2005-07-31 14:00:00 +9356,743,2,52.0,5,0,2005-07-31 14:00:00 +9357,743,8,24.0,6,0,2005-07-31 14:00:00 +9358,743,5,86.0,3,1,2005-07-31 14:00:00 +9359,744,5,86.0,3,1,2005-08-21 15:00:00 +9360,744,8,27.0,6,0,2005-08-21 15:00:00 +9361,744,3,130.0,1,7,2005-08-21 15:00:00 +9362,744,2,52.0,5,0,2005-08-21 15:00:00 +9363,744,0,121.0,2,6,2005-08-21 15:00:00 +9364,744,6,71.0,4,0,2005-08-21 15:00:00 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14:00:00 +9413,749,14,20.0,8,0,2005-10-16 14:00:00 +9414,749,6,88.0,4,0,2005-10-16 14:00:00 +9415,749,0,182.0,2,10,2005-10-16 14:00:00 +9416,749,2,66.0,5,0,2005-10-16 14:00:00 +9417,749,8,34.0,7,0,2005-10-16 14:00:00 +9418,749,5,100.0,3,1,2005-10-16 14:00:00 +9419,750,0,10.0,2,0,2006-03-12 14:30:00 +9420,750,10,5.0,4,0,2006-03-12 14:30:00 +9421,750,5,8.0,3,0,2006-03-12 14:30:00 +9422,750,2,5.0,5,0,2006-03-12 14:30:00 +9423,750,3,10.0,1,1,2006-03-12 14:30:00 +9424,750,4,0.0,7,0,2006-03-12 14:30:00 +9425,750,1,0.0,8,0,2006-03-12 14:30:00 +9426,750,6,0.0,9,0,2006-03-12 14:30:00 +9427,750,12,0.0,10,0,2006-03-12 14:30:00 +9428,750,7,0.0,11,0,2006-03-12 14:30:00 +9429,750,8,1.0,6,0,2006-03-12 14:30:00 +9430,751,3,28.0,1,2,2006-03-19 15:00:00 +9431,751,5,15.0,2,0,2006-03-19 15:00:00 +9432,751,0,15.0,3,0,2006-03-19 15:00:00 +9433,751,10,11.0,4,0,2006-03-19 15:00:00 +9434,751,2,5.0,5,0,2006-03-19 15:00:00 +9435,751,8,1.0,8,0,2006-03-19 15:00:00 +9436,751,1,2.0,6,0,2006-03-19 15:00:00 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12:00:00 +10085,811,2,20.5,5,0,2009-07-12 12:00:00 +10086,811,3,13.0,7,0,2009-07-12 12:00:00 +10087,811,6,34.5,3,0,2009-07-12 12:00:00 +10088,811,0,14.0,6,0,2009-07-12 12:00:00 +10089,811,22,112.0,1,6,2009-07-12 12:00:00 +10090,812,5,40.0,3,0,2009-07-26 12:00:00 +10091,812,8,98.5,2,3,2009-07-26 12:00:00 +10092,812,1,8.0,8,0,2009-07-26 12:00:00 +10093,812,9,0.0,10,0,2009-07-26 12:00:00 +10094,812,4,5.0,9,0,2009-07-26 12:00:00 +10095,812,2,25.5,6,0,2009-07-26 12:00:00 +10096,812,3,13.0,7,0,2009-07-26 12:00:00 +10097,812,6,38.5,4,0,2009-07-26 12:00:00 +10098,812,0,28.0,5,1,2009-07-26 12:00:00 +10099,812,22,114.0,1,6,2009-07-26 12:00:00 +10100,813,5,46.0,3,0,2009-08-23 12:00:00 +10101,813,8,98.5,2,3,2009-08-23 12:00:00 +10102,813,1,9.0,8,0,2009-08-23 12:00:00 +10103,813,9,0.0,10,0,2009-08-23 12:00:00 +10104,813,4,5.0,9,0,2009-08-23 12:00:00 +10105,813,2,29.5,6,0,2009-08-23 12:00:00 +10106,813,3,16.0,7,0,2009-08-23 12:00:00 +10107,813,6,38.5,5,0,2009-08-23 12:00:00 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+10131,816,4,5.0,10,0,2009-09-27 12:00:00 +10132,816,9,13.0,9,0,2009-09-27 12:00:00 +10133,816,8,110.5,2,3,2009-09-27 12:00:00 +10134,816,5,62.0,3,1,2009-09-27 12:00:00 +10135,816,6,46.5,5,0,2009-09-27 12:00:00 +10136,816,0,59.0,4,2,2009-09-27 12:00:00 +10137,816,22,153.0,1,8,2009-09-27 12:00:00 +10138,816,3,26.0,7,0,2009-09-27 12:00:00 +10139,816,1,21.0,8,0,2009-09-27 12:00:00 +10140,817,22,156.0,1,8,2009-10-04 05:00:00 +10141,817,3,26.0,7,0,2009-10-04 05:00:00 +10142,817,1,24.0,8,0,2009-10-04 05:00:00 +10143,817,6,54.5,5,0,2009-10-04 05:00:00 +10144,817,2,34.5,6,0,2009-10-04 05:00:00 +10145,817,5,67.0,3,1,2009-10-04 05:00:00 +10146,817,8,120.5,2,4,2009-10-04 05:00:00 +10147,817,0,65.0,4,2,2009-10-04 05:00:00 +10148,817,9,13.0,9,0,2009-10-04 05:00:00 +10149,817,4,5.0,10,0,2009-10-04 05:00:00 +10150,818,3,26.0,8,0,2009-10-18 16:00:00 +10151,818,2,34.5,6,0,2009-10-18 16:00:00 +10152,818,4,7.0,10,0,2009-10-18 16:00:00 +10153,818,0,71.0,3,2,2009-10-18 16:00:00 +10154,818,1,32.0,7,0,2009-10-18 16:00:00 +10155,818,8,135.5,2,5,2009-10-18 16:00:00 +10156,818,5,70.0,4,1,2009-10-18 16:00:00 +10157,818,22,161.0,1,8,2009-10-18 16:00:00 +10158,818,6,54.5,5,0,2009-10-18 16:00:00 +10159,818,9,13.0,9,0,2009-10-18 16:00:00 +10160,819,5,70.0,4,1,2009-11-01 11:00:00 +10161,819,8,153.5,2,6,2009-11-01 11:00:00 +10162,819,22,172.0,1,8,2009-11-01 11:00:00 +10163,819,0,71.0,3,2,2009-11-01 11:00:00 +10164,819,6,59.5,5,0,2009-11-01 11:00:00 +10165,819,3,26.0,8,0,2009-11-01 11:00:00 +10166,819,1,36.0,6,0,2009-11-01 11:00:00 +10167,819,2,34.5,7,0,2009-11-01 11:00:00 +10168,819,4,8.0,10,0,2009-11-01 11:00:00 +10169,819,9,13.0,9,0,2009-11-01 11:00:00 diff --git a/scripts/f1_data/constructors.csv b/scripts/f1_data/constructors.csv new file mode 100644 index 00000000..fa1ec049 --- /dev/null +++ b/scripts/f1_data/constructors.csv @@ -0,0 +1,212 @@ +constructorId,constructorRef,name,nationality +0,mclaren,McLaren,British +1,bmw_sauber,BMW Sauber,German +2,williams,Williams,British +3,renault,Renault,French +4,toro_rosso,Toro Rosso,Italian +5,ferrari,Ferrari,Italian +6,toyota,Toyota,Japanese +7,super_aguri,Super Aguri,Japanese +8,red_bull,Red Bull,Austrian +9,force_india,Force India,Indian +10,honda,Honda,Japanese +11,spyker,Spyker,Dutch +12,mf1,MF1,Russian +13,spyker_mf1,Spyker MF1,Dutch +14,sauber,Sauber,Swiss +15,bar,BAR,British +16,jordan,Jordan,Irish +17,minardi,Minardi,Italian +18,jaguar,Jaguar,British +19,prost,Prost,French +20,arrows,Arrows,British +21,benetton,Benetton,Italian +22,brawn,Brawn,British +23,stewart,Stewart,British +24,tyrrell,Tyrrell,British +25,lola,Lola,British +26,ligier,Ligier,French +27,forti,Forti,Italian +28,footwork,Footwork,British +29,pacific,Pacific,British +30,simtek,Simtek,British +31,team_lotus,Team Lotus,British +32,larrousse,Larrousse,French +33,brabham,Brabham,British +34,dallara,Dallara,Italian +35,fondmetal,Fondmetal,Italian +36,march,March,British +37,moda,Andrea Moda,Italian +38,ags,AGS,French +39,lambo,Lambo,Italian +40,leyton,Leyton House,British +41,coloni,Coloni,Italian +42,eurobrun,Euro Brun,Italian +43,osella,Osella,Italian +44,onyx,Onyx,British +45,life,Life,Italian +46,rial,Rial,German +47,zakspeed,Zakspeed,German +48,ram,RAM,British +49,alfa,Alfa Romeo,Swiss +50,spirit,Spirit,British +51,toleman,Toleman,British +52,ats,ATS,Italian +53,theodore,Theodore,Hong Kong +54,fittipaldi,Fittipaldi,Brazilian +55,ensign,Ensign,British +56,shadow,Shadow,British +57,wolf,Wolf,Canadian +58,merzario,Merzario,Italian +59,kauhsen,Kauhsen,German +60,rebaque,Rebaque,Mexican +61,surtees,Surtees,British +62,hesketh,Hesketh,British +63,martini,Martini,French +64,brm,BRM,British +65,penske,Penske,American +66,lec,LEC,British +67,mcguire,McGuire,Australian +68,boro,Boro,Dutch +69,apollon,Apollon,Swiss +70,kojima,Kojima,Japanese +71,parnelli,Parnelli,American +72,maki,Maki,Japanese +73,hill,Embassy Hill,British +74,lyncar,Lyncar,British +75,trojan,Trojan,British +76,amon,Amon,New Zealander +77,token,Token,British +78,iso_marlboro,Iso Marlboro,British +79,tecno,Tecno,Italian +80,matra,Matra,French +81,politoys,Politoys,British +82,connew,Connew,British +83,bellasi,Bellasi,Swiss +84,tomaso,De Tomaso,Italian +85,cooper,Cooper,British +86,eagle,Eagle,American +87,lds,LDS,South African +88,protos,Protos,British +89,shannon,Shannon,British +90,scirocco,Scirocco,British +91,re,RE,Rhodesian +92,brp,BRP,British +93,porsche,Porsche,German +94,derrington,Derrington,British +95,gilby,Gilby,British +96,stebro,Stebro,Canadian +97,emeryson,Emeryson,British +98,enb,ENB,Belgian +99,jbw,JBW,British +100,ferguson,Ferguson,British +101,mbm,MBM,Swiss +102,behra-porsche,Behra-Porsche,Italian +103,maserati,Maserati,Italian +104,scarab,Scarab,American +105,watson,Watson,American +106,epperly,Epperly,American +107,phillips,Phillips,American +108,lesovsky,Lesovsky,American +109,trevis,Trevis,American +110,meskowski,Meskowski,American +111,kurtis_kraft,Kurtis Kraft,American +112,kuzma,Kuzma,American +113,vhristensen,Christensen,American +114,ewing,Ewing,American +115,aston_martin,Aston Martin,British +116,vanwall,Vanwall,British +117,moore,Moore,American +118,dunn,Dunn,American +119,elder,Elder,American +120,sutton,Sutton,American +121,fry,Fry,British +122,tec-mec,Tec-Mec,Italian +123,connaught,Connaught,British +124,alta,Alta,British +125,osca,OSCA,Italian +126,gordini,Gordini,French +127,stevens,Stevens,American +128,bugatti,Bugatti,French +129,mercedes,Mercedes,German +130,lancia,Lancia,Italian +131,hwm,HWM,British +132,schroeder,Schroeder,American +133,pawl,Pawl,American +134,pankratz,Pankratz,American +135,arzani-volpini,Arzani-Volpini,Italian +136,nichels,Nichels,American +137,bromme,Bromme,American +138,klenk,Klenk,German +139,simca,Simca,French +140,turner,Turner,American +141,del_roy,Del Roy,American +142,veritas,Veritas,German +143,bmw,BMW,German +144,emw,EMW,East German +145,afm,AFM,German +146,frazer_nash,Frazer Nash,British +147,sherman,Sherman,American +148,deidt,Deidt,American +149,era,ERA,British +150,butterworth,Aston Butterworth,British +151,cisitalia,Cisitalia,Italian +152,lago,Talbot-Lago,French +153,hall,Hall,American +154,marchese,Marchese,American +155,langley,Langley,American +156,rae,Rae,American +157,olson,Olson,American +158,wetteroth,Wetteroth,American +159,adams,Adams,American +160,snowberger,Snowberger,American +161,milano,Milano,Italian +162,hrt,HRT,Spanish +163,cooper-maserati,Cooper-Maserati,British +164,virgin,Virgin,British +165,cooper-osca,Cooper-OSCA,British +166,cooper-borgward,Cooper-Borgward,British +167,cooper-climax,Cooper-Climax,British +168,cooper-castellotti,Cooper-Castellotti,British +169,lotus-climax,Lotus-Climax,British +170,lotus-maserati,Lotus-Maserati,British +171,de_tomaso-osca,De Tomaso-Osca,Italian +172,de_tomaso-alfa_romeo,De Tomaso-Alfa Romeo,Italian +173,lotus-brm,Lotus-BRM,British +174,lotus-borgward,Lotus-Borgward,British +175,cooper-alfa_romeo,Cooper-Alfa Romeo,British +176,de_tomaso-ferrari,De Tomaso-Ferrari,Italian +177,lotus-ford,Lotus-Ford,British +178,brabham-brm,Brabham-BRM,British +179,brabham-ford,Brabham-Ford,British +180,brabham-climax,Brabham-Climax,British +181,lds-climax,LDS-Climax,South African +182,lds-alfa_romeo,LDS-Alfa Romeo,South African +183,cooper-ford,Cooper-Ford,British +184,mclaren-ford,McLaren-Ford,British +185,mclaren-seren,McLaren-Serenissima,British +186,eagle-climax,Eagle-Climax,American +187,eagle-weslake,Eagle-Weslake,American +188,brabham-repco,Brabham-Repco,British +189,cooper-ferrari,Cooper-Ferrari,British +190,cooper-ats,Cooper-ATS,British +191,mclaren-brm,McLaren-BRM,British +192,cooper-brm,Cooper-BRM,British +193,matra-ford,Matra-Ford,French +194,brm-ford,BRM-Ford,British +195,mclaren-alfa_romeo,McLaren-Alfa Romeo,British +196,march-alfa_romeo,March-Alfa Romeo,British +197,march-ford,March-Ford,British +198,lotus-pw,Lotus-Pratt & Whitney,British +199,shadow-ford,Shadow-Ford,British +200,shadow-matra,Shadow-Matra,British +201,brabham-alfa_romeo,Brabham-Alfa Romeo,British +202,lotus_racing,Lotus,Malaysian +203,marussia,Marussia,Russian +204,caterham,Caterham,Malaysian +205,lotus_f1,Lotus F1,British +206,manor,Manor Marussia,British +207,haas,Haas F1 Team,American +208,racing_point,Racing Point,British +209,alphatauri,AlphaTauri,Italian +210,alpine,Alpine F1 Team,French diff --git a/scripts/f1_data/drivers.csv b/scripts/f1_data/drivers.csv new file mode 100644 index 00000000..513a207f --- /dev/null +++ b/scripts/f1_data/drivers.csv @@ -0,0 +1,858 @@ +driverId,driverRef,code,forename,surname,dob,nationality +0,hamilton,HAM,Lewis,Hamilton,1985-01-07,British +1,heidfeld,HEI,Nick,Heidfeld,1977-05-10,German +2,rosberg,ROS,Nico,Rosberg,1985-06-27,German +3,alonso,ALO,Fernando,Alonso,1981-07-29,Spanish +4,kovalainen,KOV,Heikki,Kovalainen,1981-10-19,Finnish +5,nakajima,NAK,Kazuki,Nakajima,1985-01-11,Japanese +6,bourdais,BOU,Sébastien,Bourdais,1979-02-28,French +7,raikkonen,RAI,Kimi,Räikkönen,1979-10-17,Finnish +8,kubica,KUB,Robert,Kubica,1984-12-07,Polish +9,glock,GLO,Timo,Glock,1982-03-18,German +10,sato,SAT,Takuma,Sato,1977-01-28,Japanese +11,piquet_jr,PIQ,Nelson,Piquet Jr.,1985-07-25,Brazilian +12,massa,MAS,Felipe,Massa,1981-04-25,Brazilian +13,coulthard,COU,David,Coulthard,1971-03-27,British +14,trulli,TRU,Jarno,Trulli,1974-07-13,Italian +15,sutil,SUT,Adrian,Sutil,1983-01-11,German +16,webber,WEB,Mark,Webber,1976-08-27,Australian +17,button,BUT,Jenson,Button,1980-01-19,British +18,davidson,DAV,Anthony,Davidson,1979-04-18,British +19,vettel,VET,Sebastian,Vettel,1987-07-03,German +20,fisichella,FIS,Giancarlo,Fisichella,1973-01-14,Italian +21,barrichello,BAR,Rubens,Barrichello,1972-05-23,Brazilian +22,ralf_schumacher,SCH,Ralf,Schumacher,1975-06-30,German +23,liuzzi,LIU,Vitantonio,Liuzzi,1980-08-06,Italian +24,wurz,WUR,Alexander,Wurz,1974-02-15,Austrian +25,speed,SPE,Scott,Speed,1983-01-24,American +26,albers,ALB,Christijan,Albers,1979-04-16,Dutch +27,markus_winkelhock,WIN,Markus,Winkelhock,1980-06-13,German +28,yamamoto,YAM,Sakon,Yamamoto,1982-07-09,Japanese +29,michael_schumacher,MSC,Michael,Schumacher,1969-01-03,German +30,montoya,MON,Juan,Pablo Montoya,1975-09-20,Colombian +31,klien,KLI,Christian,Klien,1983-02-07,Austrian +32,monteiro,TMO,Tiago,Monteiro,1976-07-24,Portuguese +33,ide,IDE,Yuji,Ide,1975-01-21,Japanese +34,villeneuve,VIL,Jacques,Villeneuve,1971-04-09,Canadian +35,montagny,FMO,Franck,Montagny,1978-01-05,French +36,rosa,DLR,Pedro,de la Rosa,1971-02-24,Spanish +37,doornbos,DOO,Robert,Doornbos,1981-09-23,Dutch +38,karthikeyan,KAR,Narain,Karthikeyan,1977-01-14,Indian +39,friesacher,FRI,Patrick,Friesacher,1980-09-26,Austrian +40,zonta,ZON,Ricardo,Zonta,1976-03-23,Brazilian +41,pizzonia,PIZ,Antônio,Pizzonia,1980-09-11,Brazilian +42,matta,\N,Cristiano,da Matta,1973-09-19,Brazilian +43,panis,\N,Olivier,Panis,1966-09-02,French +44,pantano,\N,Giorgio,Pantano,1979-02-04,Italian +45,bruni,\N,Gianmaria,Bruni,1981-05-30,Italian +46,baumgartner,\N,Zsolt,Baumgartner,1981-01-01,Hungarian +47,gene,\N,Marc,Gené,1974-03-29,Spanish +48,frentzen,\N,Heinz-Harald,Frentzen,1967-05-18,German +49,verstappen,\N,Jos,Verstappen,1972-03-04,Dutch +50,wilson,\N,Justin,Wilson,1978-07-31,British +51,firman,\N,Ralph,Firman,1975-05-20,Irish +52,kiesa,\N,Nicolas,Kiesa,1978-03-03,Danish +53,burti,\N,Luciano,Burti,1975-03-05,Brazilian +54,alesi,\N,Jean,Alesi,1964-06-11,French +55,irvine,\N,Eddie,Irvine,1965-11-10,British +56,hakkinen,\N,Mika,Häkkinen,1968-09-28,Finnish +57,marques,\N,Tarso,Marques,1976-01-19,Brazilian +58,bernoldi,\N,Enrique,Bernoldi,1978-10-19,Brazilian +59,mazzacane,\N,Gastón,Mazzacane,1975-05-08,Argentine +60,enge,\N,Tomáš,Enge,1976-09-11,Czech +61,yoong,\N,Alex,Yoong,1976-07-20,Malaysian +62,salo,\N,Mika,Salo,1966-11-30,Finnish +63,diniz,\N,Pedro,Diniz,1970-05-22,Brazilian +64,herbert,\N,Johnny,Herbert,1964-06-25,British +65,mcnish,\N,Allan,McNish,1969-12-29,British +66,buemi,BUE,Sébastien,Buemi,1988-10-31,Swiss +67,takagi,\N,Toranosuke,Takagi,1974-02-12,Japanese +68,badoer,BAD,Luca,Badoer,1971-01-25,Italian +69,zanardi,\N,Alessandro,Zanardi,1966-10-23,Italian +70,damon_hill,\N,Damon,Hill,1960-09-17,British +71,sarrazin,\N,Stéphane,Sarrazin,1975-11-02,French +72,rosset,\N,Ricardo,Rosset,1968-07-27,Brazilian +73,tuero,\N,Esteban,Tuero,1978-04-22,Argentine +74,nakano,\N,Shinji,Nakano,1971-04-01,Japanese +75,magnussen,MAG,Jan,Magnussen,1973-07-04,Danish +76,berger,\N,Gerhard,Berger,1959-08-27,Austrian +77,larini,\N,Nicola,Larini,1964-03-19,Italian +78,katayama,\N,Ukyo,Katayama,1963-05-29,Japanese +79,sospiri,\N,Vincenzo,Sospiri,1966-10-07,Italian +80,morbidelli,\N,Gianni,Morbidelli,1968-01-13,Italian +81,fontana,\N,Norberto,Fontana,1975-01-20,Argentine +82,lamy,\N,Pedro,Lamy,1972-03-20,Portuguese +83,brundle,\N,Martin,Brundle,1959-06-01,British +84,montermini,\N,Andrea,Montermini,1964-05-30,Italian +85,lavaggi,\N,Giovanni,Lavaggi,1958-02-18,Italian +86,blundell,\N,Mark,Blundell,1966-04-08,British +87,suzuki,\N,Aguri,Suzuki,1960-09-08,Japanese +88,inoue,\N,Taki,Inoue,1963-09-05,Japanese +89,moreno,\N,Roberto,Moreno,1959-02-11,Brazilian +90,wendlinger,\N,Karl,Wendlinger,1968-12-20,Austrian +91,gachot,\N,Bertrand,Gachot,1962-12-23,Belgian +92,schiattarella,\N,Domenico,Schiattarella,1967-11-17,Italian +93,martini,\N,Pierluigi,Martini,1961-04-23,Italian +94,mansell,\N,Nigel,Mansell,1953-08-08,British +95,boullion,\N,Jean-Christophe,Boullion,1969-12-27,French +96,papis,\N,Massimiliano,Papis,1969-10-03,Italian +97,deletraz,\N,Jean-Denis,Délétraz,1963-10-01,Swiss +98,tarquini,\N,Gabriele,Tarquini,1962-03-02,Italian +99,comas,\N,Érik,Comas,1963-09-28,French +100,brabham,\N,David,Brabham,1965-09-05,Australian +101,senna,\N,Ayrton,Senna,1960-03-21,Brazilian +102,bernard,\N,Éric,Bernard,1964-08-24,French +103,fittipaldi,\N,Christian,Fittipaldi,1971-01-18,Brazilian +104,alboreto,\N,Michele,Alboreto,1956-12-23,Italian +105,beretta,\N,Olivier,Beretta,1969-11-23,Monegasque +106,ratzenberger,\N,Roland,Ratzenberger,1960-07-04,Austrian +107,belmondo,\N,Paul,Belmondo,1963-04-23,French +108,lehto,\N,Jyrki,Järvilehto,1966-01-31,Finnish +109,cesaris,\N,Andrea,de Cesaris,1959-05-31,Italian +110,gounon,\N,Jean-Marc,Gounon,1963-01-01,French +111,alliot,\N,Philippe,Alliot,1954-07-27,French +112,adams,\N,Philippe,Adams,1969-11-19,Belgian +113,dalmas,\N,Yannick,Dalmas,1961-07-28,French +114,noda,\N,Hideki,Noda,1969-03-07,Japanese +115,lagorce,\N,Franck,Lagorce,1968-09-01,French +116,prost,\N,Alain,Prost,1955-02-24,French +117,warwick,\N,Derek,Warwick,1954-08-27,British +118,patrese,\N,Riccardo,Patrese,1954-04-17,Italian +119,barbazza,\N,Fabrizio,Barbazza,1963-04-02,Italian +120,andretti,\N,Michael,Andretti,1962-10-05,American +121,capelli,\N,Ivan,Capelli,1963-05-24,Italian +122,boutsen,\N,Thierry,Boutsen,1957-07-13,Belgian +123,apicella,\N,Marco,Apicella,1965-10-07,Italian +124,naspetti,\N,Emanuele,Naspetti,1968-02-24,Italian +125,toshio_suzuki,\N,Toshio,Suzuki,1955-03-10,Japanese +126,gugelmin,\N,Maurício,Gugelmin,1963-04-20,Brazilian +127,poele,\N,Eric,van de Poele,1961-09-30,Belgian +128,grouillard,\N,Olivier,Grouillard,1958-09-02,French +129,chiesa,\N,Andrea,Chiesa,1964-05-06,Swiss +130,modena,\N,Stefano,Modena,1963-05-12,Italian +131,amati,\N,Giovanna,Amati,1959-07-20,Italian +132,caffi,\N,Alex,Caffi,1964-03-18,Italian +133,bertaggia,\N,Enrico,Bertaggia,1964-09-19,Italian +134,mccarthy,\N,Perry,McCarthy,1961-03-03,British +135,lammers,\N,Jan,Lammers,1956-06-02,Dutch +136,piquet,\N,Nelson,Piquet,1952-08-17,Brazilian +137,satoru_nakajima,\N,Satoru,Nakajima,1953-02-23,Japanese +138,pirro,\N,Emanuele,Pirro,1962-01-12,Italian +139,johansson,\N,Stefan,Johansson,1956-09-08,Swedish +140,bailey,\N,Julian,Bailey,1961-10-09,British +141,chaves,\N,Pedro,Chaves,1965-02-27,Portuguese +142,bartels,\N,Michael,Bartels,1968-03-08,German +143,hattori,\N,Naoki,Hattori,1966-06-13,Japanese +144,nannini,\N,Alessandro,Nannini,1959-07-07,Italian +145,schneider,\N,Bernd,Schneider,1964-07-20,German +146,barilla,\N,Paolo,Barilla,1961-04-20,Italian +147,foitek,\N,Gregor,Foitek,1965-03-27,Swiss +148,langes,\N,Claudio,Langes,1960-07-20,Italian +149,gary_brabham,\N,Gary,Brabham,1961-03-29,Australian +150,donnelly,\N,Martin,Donnelly,1964-03-26,British +151,giacomelli,\N,Bruno,Giacomelli,1952-09-10,Italian +152,alguersuari,ALG,Jaime,Alguersuari,1990-03-23,Spanish +153,grosjean,GRO,Romain,Grosjean,1986-04-17,French +154,kobayashi,KOB,Kamui,Kobayashi,1986-09-13,Japanese +155,palmer,\N,Jonathan,Palmer,1956-11-07,British +156,danner,\N,Christian,Danner,1958-04-04,German +157,cheever,\N,Eddie,Cheever,1958-01-10,American +158,sala,\N,Luis,Pérez-Sala,1959-05-15,Spanish +159,ghinzani,\N,Piercarlo,Ghinzani,1952-01-16,Italian +160,weidler,\N,Volker,Weidler,1962-03-18,German +161,raphanel,\N,Pierre-Henri,Raphanel,1961-05-27,French +162,arnoux,\N,René,Arnoux,1948-07-04,French +163,joachim_winkelhock,\N,Joachim,Winkelhock,1960-10-24,German +164,larrauri,\N,Oscar,Larrauri,1954-08-19,Argentine +165,streiff,\N,Philippe,Streiff,1955-06-26,French +166,campos,\N,Adrián,Campos,1960-06-17,Spanish +167,schlesser,\N,Jean-Louis,Schlesser,1948-09-12,French +168,fabre,\N,Pascal,Fabre,1960-01-09,French +169,fabi,\N,Teo,Fabi,1955-03-09,Italian +170,forini,\N,Franco,Forini,1958-09-22,Swiss +171,laffite,\N,Jacques,Laffite,1943-11-21,French +172,angelis,\N,Elio,de Angelis,1958-03-26,Italian +173,dumfries,\N,Johnny,Dumfries,1958-04-26,British +174,tambay,\N,Patrick,Tambay,1949-06-25,French +175,surer,\N,Marc,Surer,1951-09-18,Swiss +176,keke_rosberg,\N,Keke,Rosberg,1948-12-06,Finnish +177,jones,\N,Alan,Jones,1946-11-02,Australian +178,rothengatter,\N,Huub,Rothengatter,1954-10-08,Dutch +179,berg,\N,Allen,Berg,1961-08-01,Canadian +180,manfred_winkelhock,\N,Manfred,Winkelhock,1951-10-06,German +181,lauda,\N,Niki,Lauda,1949-02-22,Austrian +182,hesnault,\N,François,Hesnault,1956-12-30,French +183,baldi,\N,Mauro,Baldi,1954-01-31,Italian +184,bellof,\N,Stefan,Bellof,1957-11-20,German +185,acheson,\N,Kenny,Acheson,1957-11-27,British +186,watson,\N,John,Watson,1946-05-04,British +187,cecotto,\N,Johnny,Cecotto,1956-01-25,Venezuelan +188,gartner,\N,Jo,Gartner,1954-01-24,Austrian +189,corrado_fabi,\N,Corrado,Fabi,1961-04-12,Italian +190,thackwell,\N,Mike,Thackwell,1961-03-30,New Zealander +191,serra,\N,Chico,Serra,1957-02-03,Brazilian +192,sullivan,\N,Danny,Sullivan,1950-03-09,American +193,salazar,\N,Eliseo,Salazar,1954-11-14,Chilean +194,guerrero,\N,Roberto,Guerrero,1958-11-16,Colombian +195,boesel,\N,Raul,Boesel,1957-12-04,Brazilian +196,jarier,\N,Jean-Pierre,Jarier,1946-07-10,French +197,villeneuve_sr,\N,Jacques,Villeneuve Sr.,1953-11-04,Canadian +198,reutemann,\N,Carlos,Reutemann,1942-04-12,Argentine +199,mass,\N,Jochen,Mass,1946-09-30,German +200,borgudd,\N,Slim,Borgudd,1946-11-25,Swedish +201,pironi,\N,Didier,Pironi,1952-03-26,French +202,gilles_villeneuve,\N,Gilles,Villeneuve,1950-01-18,Canadian +203,paletti,\N,Riccardo,Paletti,1958-06-15,Italian +204,henton,\N,Brian,Henton,1946-09-19,British +205,daly,\N,Derek,Daly,1953-03-11,Irish +206,mario_andretti,\N,Mario,Andretti,1940-02-28,American +207,villota,\N,Emilio,de Villota,1946-07-26,Spanish +208,lees,\N,Geoff,Lees,1951-05-01,British +209,byrne,\N,Tommy,Byrne,1958-05-06,Irish +210,keegan,\N,Rupert,Keegan,1955-02-26,British +211,rebaque,\N,Hector,Rebaque,1956-02-05,Mexican +212,gabbiani,\N,Beppe,Gabbiani,1957-01-02,Italian +213,cogan,\N,Kevin,Cogan,1956-03-31,American +214,guerra,\N,Miguel Ángel,Guerra,1953-08-31,Argentine +215,stohr,\N,Siegfried,Stohr,1952-10-10,Italian +216,zunino,\N,Ricardo,Zunino,1949-04-13,Argentine +217,londono,\N,Ricardo,Londoño,1949-08-08,Colombian +218,jabouille,\N,Jean-Pierre,Jabouille,1942-10-01,French +219,francia,\N,Giorgio,Francia,1947-11-08,Italian +220,depailler,\N,Patrick,Depailler,1944-08-09,French +221,scheckter,\N,Jody,Scheckter,1950-01-29,South African +222,regazzoni,\N,Clay,Regazzoni,1939-09-05,Swiss +223,emerson_fittipaldi,\N,Emerson,Fittipaldi,1946-12-12,Brazilian +224,kennedy,\N,Dave,Kennedy,1953-01-15,Irish +225,south,\N,Stephen,South,1952-02-19,British +226,needell,\N,Tiff,Needell,1951-10-29,British +227,desire_wilson,\N,Desiré,Wilson,1953-11-26,South African +228,ertl,\N,Harald,Ertl,1948-08-31,Austrian +229,brambilla,\N,Vittorio,Brambilla,1937-11-11,Italian +230,hunt,\N,James,Hunt,1947-08-29,British +231,merzario,\N,Arturo,Merzario,1943-03-11,Italian +232,stuck,\N,Hans-Joachim,Stuck,1951-01-01,German +233,brancatelli,\N,Gianfranco,Brancatelli,1950-01-18,Italian +234,ickx,\N,Jacky,Ickx,1945-01-01,Belgian +235,gaillard,\N,Patrick,Gaillard,1952-02-12,French +236,ribeiro,\N,Alex,Ribeiro,1948-11-07,Brazilian +237,peterson,\N,Ronnie,Peterson,1944-02-14,Swedish +238,lunger,\N,Brett,Lunger,1945-11-14,American +239,ongais,\N,Danny,Ongais,1942-05-21,American +240,leoni,\N,Lamberto,Leoni,1953-05-24,Italian +241,galica,\N,Divina,Galica,1944-08-13,British +242,stommelen,\N,Rolf,Stommelen,1943-07-11,German +243,colombo,\N,Alberto,Colombo,1946-02-23,Italian +244,trimmer,\N,Tony,Trimmer,1943-01-24,British +245,binder,\N,Hans,Binder,1948-06-12,Austrian +246,bleekemolen,\N,Michael,Bleekemolen,1949-10-02,Dutch +247,gimax,\N,Carlo,Franchi,1938-01-01,Italian +248,rahal,\N,Bobby,Rahal,1953-01-10,American +249,pace,\N,Carlos,Pace,1944-10-06,Brazilian +250,ian_scheckter,\N,Ian,Scheckter,1947-08-22,South African +251,pryce,\N,Tom,Pryce,1949-06-11,British +252,hoffmann,\N,Ingo,Hoffmann,1953-02-28,Brazilian +253,zorzi,\N,Renzo,Zorzi,1946-12-12,Italian +254,nilsson,\N,Gunnar,Nilsson,1948-11-20,Swedish +255,perkins,\N,Larry,Perkins,1950-03-18,Australian +256,hayje,\N,Boy,Lunger,1949-05-03,Dutch +257,neve,\N,Patrick,Nève,1949-10-13,Belgian +258,purley,\N,David,Purley,1945-01-26,British +259,andersson,\N,Conny,Andersson,1939-12-28,Swedish +260,dryver,\N,Bernard,de Dryver,1952-09-19,Belgian +261,oliver,\N,Jackie,Oliver,1942-08-14,British +262,kozarowitzky,\N,Mikko,Kozarowitzky,1948-05-17,Finnish +263,sutcliffe,\N,Andy,Sutcliffe,1947-05-09,British +264,edwards,\N,Guy,Edwards,1942-12-30,British +265,mcguire,\N,Brian,McGuire,1945-12-13,Australian +266,schuppan,\N,Vern,Schuppan,1943-03-19,Australian +267,heyer,\N,Hans,Heyer,1943-03-16,German +268,pilette,\N,Teddy,Pilette,1942-07-26,Belgian +269,ashley,\N,Ian,Ashley,1947-10-26,British +270,kessel,\N,Loris,Kessel,1950-04-01,Swiss +271,takahashi,\N,Kunimitsu,Takahashi,1940-01-29,Japanese +272,hoshino,\N,Kazuyoshi,Hoshino,1947-07-01,Japanese +273,takahara,\N,Noritake,Takahara,1951-06-06,Japanese +274,lombardi,\N,Lella,Lombardi,1941-03-26,Italian +275,evans,\N,Bob,Evans,1947-06-11,British +276,leclere,\N,Michel,Leclère,1946-03-18,French +277,amon,\N,Chris,Amon,1943-07-20,New Zealander +278,zapico,\N,Emilio,Zapico,1944-05-27,Spanish +279,pescarolo,\N,Henri,Pescarolo,1942-09-25,French +280,nelleman,\N,Jac,Nelleman,1944-04-19,Danish +281,magee,\N,Damien,Magee,1945-11-17,British +282,wilds,\N,Mike,Wilds,1946-01-07,British +283,pesenti_rossi,\N,Alessandro,Pesenti-Rossi,1942-08-31,Italian +284,stuppacher,\N,Otto,Stuppacher,1947-03-03,Austrian +285,brown,\N,Warwick,Brown,1949-12-24,Australian +286,hasemi,\N,Masahiro,Hasemi,1945-11-13,Japanese +287,donohue,\N,Mark,Donohue,1937-03-18,American +288,hill,\N,Graham,Hill,1929-02-15,British +289,wilson_fittipaldi,\N,Wilson,Fittipaldi,1943-12-25,Brazilian +290,tunmer,\N,Guy,Tunmer,1948-12-01,South African +291,keizan,\N,Eddie,Keizan,1944-09-12,South African +292,charlton,\N,Dave,Charlton,1936-10-27,South African +293,brise,\N,Tony,Brise,1952-03-28,British +294,wunderink,\N,Roelof,Wunderink,1948-12-12,Dutch +295,migault,\N,François,Migault,1944-12-04,French +296,palm,\N,Torsten,Palm,1947-07-23,Swedish +297,lennep,\N,Gijs,van Lennep,1942-03-16,Dutch +298,fushida,\N,Hiroshi,Fushida,1946-03-10,Japanese +299,nicholson,\N,John,Nicholson,1941-10-06,New Zealander +300,morgan,\N,Dave,Morgan,1944-08-07,British +301,crawford,\N,Jim,Crawford,1948-02-13,British +302,vonlanthen,\N,Jo,Vonlanthen,1942-05-31,Swiss +303,hulme,\N,Denny,Hulme,1936-06-18,New Zealander +304,hailwood,\N,Mike,Hailwood,1940-04-02,British +305,beltoise,\N,Jean-Pierre,Beltoise,1937-04-26,French +306,ganley,\N,Howden,Ganley,1941-12-24,New Zealander +307,robarts,\N,Richard,Robarts,1944-09-22,British +308,revson,\N,Peter,Revson,1939-02-27,American +309,driver,\N,Paddy,Driver,1934-05-13,South African +310,belso,\N,Tom,Belsø,1942-08-27,Danish +311,redman,\N,Brian,Redman,1937-03-09,British +312,opel,\N,Rikky,von Opel,1947-10-14,Liechtensteiner +313,schenken,\N,Tim,Schenken,1943-09-26,Australian +314,larrousse,\N,Gérard,Larrousse,1940-05-23,French +315,kinnunen,\N,Leo,Kinnunen,1943-08-05,Finnish +316,wisell,\N,Reine,Wisell,1941-09-30,Swedish +317,roos,\N,Bertil,Roos,1943-10-12,Swedish +318,dolhem,\N,José,Dolhem,1944-04-26,French +319,gethin,\N,Peter,Gethin,1940-02-21,British +320,bell,\N,Derek,Bell,1941-10-31,British +321,hobbs,\N,David,Hobbs,1939-06-09,British +322,quester,\N,Dieter,Quester,1939-05-30,Austrian +323,koinigg,\N,Helmuth,Koinigg,1948-11-03,Austrian +324,facetti,\N,Carlo,Facetti,1935-06-26,Italian +325,wietzes,\N,Eppie,Wietzes,1938-05-28,Canadian +326,cevert,\N,François,Cevert,1944-02-25,French +327,stewart,\N,Jackie,Stewart,1939-06-11,British +328,beuttler,\N,Mike,Beuttler,1940-04-13,British +329,galli,\N,Nanni,Galli,1940-10-02,Italian +330,bueno,\N,Luiz,Bueno,1937-01-16,Brazilian +331,follmer,\N,George,Follmer,1934-01-27,American +332,adamich,\N,Andrea,de Adamich,1941-10-03,Italian +333,pretorius,\N,Jackie,Pretorius,1934-11-22,South African +334,williamson,\N,Roger,Williamson,1948-02-02,British +335,mcrae,\N,Graham,McRae,1940-03-05,New Zealander +336,marko,\N,Helmut,Marko,1943-04-27,Austrian +337,walker,\N,David,Walker,1941-06-10,Australian +338,roig,\N,Alex,Soler-Roig,1932-10-29,Spanish +339,love,\N,John,Love,1924-12-07,Rhodesian +340,surtees,\N,John,Surtees,1934-02-11,British +341,barber,\N,Skip,Barber,1936-11-16,American +342,brack,\N,Bill,Brack,1935-12-26,Canadian +343,posey,\N,Sam,Posey,1944-05-26,American +344,rodriguez,\N,Pedro,Rodríguez,1940-01-18,Mexican +345,siffert,\N,Jo,Siffert,1936-07-07,Swiss +346,bonnier,\N,Jo,Bonnier,1930-01-31,Swedish +347,mazet,\N,François,Mazet,1943-02-24,French +348,jean,\N,Max,Jean,1943-07-27,French +349,elford,\N,Vic,Elford,1935-06-10,British +350,moser,\N,Silvio,Moser,1941-04-24,Swiss +351,eaton,\N,George,Eaton,1945-11-12,Canadian +352,lovely,\N,Pete,Lovely,1926-04-11,American +353,craft,\N,Chris,Craft,1939-11-17,British +354,Cannoc,\N,John,Cannon,1933-06-21,Canadian +355,jack_brabham,\N,Jack,Brabham,1926-04-02,Australian +356,miles,\N,John,Miles,1943-06-14,British +357,rindt,\N,Jochen,Rindt,1942-04-18,Austrian +358,gavin,\N,Johnny,Servoz-Gavin,1942-01-18,French +359,mclaren,\N,Bruce,McLaren,1937-08-30,New Zealander +360,courage,\N,Piers,Courage,1942-05-27,British +361,klerk,\N,Peter,de Klerk,1935-03-16,South African +362,giunti,\N,Ignazio,Giunti,1941-08-30,Italian +363,gurney,\N,Dan,Gurney,1931-04-13,American +364,hahne,\N,Hubert,Hahne,1935-03-28,German +365,hutchison,\N,Gus,Hutchison,1937-04-26,American +366,westbury,\N,Peter,Westbury,1938-05-26,British +367,tingle,\N,Sam,Tingle,1921-08-24,Rhodesian +368,rooyen,\N,Basil,van Rooyen,1939-04-19,South African +369,attwood,\N,Richard,Attwood,1940-04-04,British +370,pease,\N,Al,Pease,1921-10-15,Canadian +371,cordts,\N,John,Cordts,1935-07-23,Canadian +372,clark,\N,Jim,Clark,1936-03-04,British +373,spence,\N,Mike,Spence,1936-12-30,British +374,scarfiotti,\N,Ludovico,Scarfiotti,1933-10-18,Italian +375,bianchi,BIA,Lucien,Bianchi,1934-11-10,Belgian +376,jo_schlesser,\N,Jo,Schlesser,1928-05-18,French +377,widdows,\N,Robin,Widdows,1942-05-27,British +378,ahrens,\N,Kurt,Ahrens,1940-04-19,German +379,gardner,\N,Frank,Gardner,1930-10-01,Australian +380,unser,\N,Bobby,Unser,1934-02-20,American +381,solana,\N,Moisés,Solana,1935-12-26,Mexican +382,anderson,\N,Bob,Anderson,1931-05-19,British +383,botha,\N,Luki,Botha,1930-01-16,South African +384,bandini,\N,Lorenzo,Bandini,1935-12-21,Italian +385,ginther,\N,Richie,Ginther,1930-08-05,American +386,parkes,\N,Mike,Parkes,1931-09-24,British +387,irwin,\N,Chris,Irwin,1942-06-27,British +388,ligier,\N,Guy,Ligier,1930-07-12,French +389,rees,\N,Alan,Rees,1938-01-12,British +390,hart,\N,Brian,Hart,1936-09-07,British +391,fisher,\N,Mike,Fisher,1943-03-13,American +392,tom_jones,\N,Tom,Jones,1943-04-26,American +393,baghetti,\N,Giancarlo,Baghetti,1934-12-25,Italian +394,williams,\N,Jonathan,Williams,1942-10-26,British +395,bondurant,\N,Bob,Bondurant,1933-04-27,American +396,arundell,\N,Peter,Arundell,1933-11-08,British +397,vic_wilson,\N,Vic,Wilson,1931-04-14,British +398,taylor,\N,John,Taylor,1933-03-23,British +399,lawrence,\N,Chris,Lawrence,1933-07-27,British +400,trevor_taylor,\N,Trevor,Taylor,1936-12-26,British +401,geki,\N,Giacomo,Russo,1937-10-23,Italian +402,phil_hill,\N,Phil,Hill,1927-04-20,American +403,ireland,\N,Innes,Ireland,1930-06-12,British +404,bucknum,\N,Ronnie,Bucknum,1936-04-05,American +405,hawkins,\N,Paul,Hawkins,1937-10-12,Australian +406,prophet,\N,David,Prophet,1937-10-09,British +407,maggs,\N,Tony,Maggs,1937-02-09,South African +408,blokdyk,\N,Trevor,Blokdyk,1935-11-30,South African +409,lederle,\N,Neville,Lederle,1938-09-25,South African +410,serrurier,\N,Doug,Serrurier,1920-12-09,South African +411,niemann,\N,Brausch,Niemann,1939-01-07,South African +412,pieterse,\N,Ernie,Pieterse,1938-07-04,South African +413,puzey,\N,Clive,Puzey,1941-07-11,Rhodesian +414,reed,\N,Ray,Reed,1932-04-30,South African +415,clapham,\N,David,Clapham,1931-05-18,South African +416,blignaut,\N,Alex,Blignaut,1932-11-30,South African +417,gregory,\N,Masten,Gregory,1932-02-29,American +418,rhodes,\N,John,Rhodes,1927-08-18,British +419,raby,\N,Ian,Raby,1921-09-22,British +420,rollinson,\N,Alan,Rollinson,1943-05-15,British +421,gubby,\N,Brian,Gubby,1934-04-17,British +422,mitter,\N,Gerhard,Mitter,1935-08-30,German +423,bussinello,\N,Roberto,Bussinello,1927-10-04,Italian +424,vaccarella,\N,Nino,Vaccarella,1933-03-04,Italian +425,bassi,\N,Giorgio,Bassi,1934-01-20,Italian +426,trintignant,\N,Maurice,Trintignant,1917-10-30,French +427,collomb,\N,Bernard,Collomb,1930-10-07,French +428,andre_pilette,\N,André,Pilette,1918-10-06,Belgian +429,beaufort,\N,Carel Godin,de Beaufort,1934-04-10,Dutch +430,barth,\N,Edgar,Barth,1917-01-26,German +431,cabral,\N,Mário de Araújo,Cabral,1934-01-15,Portuguese +432,hansgen,\N,Walt,Hansgen,1919-10-28,American +433,sharp,\N,Hap,Sharp,1928-01-01,American +434,mairesse,\N,Willy,Mairesse,1928-10-01,Belgian +435,campbell-jones,\N,John,Campbell-Jones,1930-01-21,British +436,burgess,\N,Ian,Burgess,1930-07-06,British +437,settember,\N,Tony,Settember,1926-07-10,American +438,estefano,\N,Nasif,Estéfano,1932-11-18,Argentine +439,hall,\N,Jim,Hall,1935-07-23,American +440,parnell,\N,Tim,Parnell,1932-06-25,British +441,kuhnke,\N,Kurt,Kuhnke,1910-04-30,German +442,ernesto_brambilla,\N,Ernesto,Brambilla,1934-01-31,Italian +443,lippi,\N,Roberto,Lippi,1926-10-17,Italian +444,seiffert,\N,Günther,Seiffert,1937-10-18,German +445,abate,\N,Carlo,Abate,1932-07-10,Italian +446,starrabba,\N,Gaetano,Starrabba,1932-12-03,Italian +447,broeker,\N,Peter,Broeker,1926-05-15,Canadian +448,ward,\N,Rodger,Ward,1921-01-10,American +449,vos,\N,Ernie,de Vos,1941-07-01,Dutch +450,dochnal,\N,Frank,Dochnal,1920-10-08,American +451,monarch,\N,Thomas,Monarch,1945-09-03,American +452,gasly,GAS,Pierre,Gasly,1996-02-07,French +453,lewis,\N,Jackie,Lewis,1936-11-01,British +454,ricardo_rodriguez,\N,Ricardo,Rodríguez,1942-02-14,Mexican +455,seidel,\N,Wolfgang,Seidel,1926-07-04,German +456,salvadori,\N,Roy,Salvadori,1922-05-12,British +457,pon,\N,Ben,Pon,1936-12-09,Dutch +458,slotemaker,\N,Rob,Slotemaker,1929-06-13,Dutch +459,marsh,\N,Tony,Marsh,1931-07-20,British +460,ashmore,\N,Gerry,Ashmore,1936-07-25,British +461,schiller,\N,Heinz,Schiller,1930-01-25,Swiss +462,davis,\N,Colin,Davis,1933-07-29,British +463,chamberlain,\N,Jay,Chamberlain,1925-12-29,American +464,shelly,\N,Tony,Shelly,1937-02-02,New Zealander +465,greene,\N,Keith,Greene,1938-01-05,British +466,walter,\N,Heini,Walter,1927-07-28,Swiss +467,prinoth,\N,Ernesto,Prinoth,1923-04-15,Italian +468,penske,\N,Roger,Penske,1937-02-20,American +469,schroeder,\N,Rob,Schroeder,1926-05-11,British +470,mayer,\N,Timmy,Mayer,1938-02-22,American +471,johnstone,\N,Bruce,Johnstone,1937-01-30,South African +472,harris,\N,Mike,Harris,1939-05-25,South African +473,hocking,\N,Gary,Hocking,1937-09-30,Rhodesian +474,vyver,\N,Syd,van der Vyver,1920-06-01,South African +475,moss,\N,Stirling,Moss,1929-09-17,British +476,trips,\N,Wolfgang,von Trips,1928-05-04,German +477,allison,\N,Cliff,Allison,1932-02-08,British +478,herrmann,\N,Hans,Herrmann,1928-02-23,German +479,brooks,\N,Tony,Brooks,1932-02-25,British +480,may,\N,Michael,May,1934-08-18,Swiss +481,henry_taylor,\N,Henry,Taylor,1932-12-16,British +482,gendebien,\N,Olivier,Gendebien,1924-01-12,Belgian +483,scarlatti,\N,Giorgio,Scarlatti,1921-10-02,Italian +484,naylor,\N,Brian,Naylor,1923-03-24,British +485,bordeu,\N,Juan Manuel,Bordeu,1934-01-28,Argentine +486,fairman,\N,Jack,Fairman,1913-03-15,British +487,natili,\N,Massimo,Natili,1935-07-28,Italian +488,monteverdi,\N,Peter,Monteverdi,1934-06-07,Swiss +489,pirocchi,\N,Renato,Pirocchi,1933-03-26,Italian +490,duke,\N,Geoff,Duke,1923-03-29,British +491,thiele,\N,Alfonso,Thiele,1920-04-05,American-Italian +492,boffa,\N,Menato,Boffa,1930-01-04,Italian +493,ryan,\N,Peter,Ryan,1940-06-10,Canadian +494,ruby,\N,Lloyd,Ruby,1928-01-12,American +495,ken_miles,\N,Ken,Miles,1918-11-01,British +496,menditeguy,\N,Carlos,Menditeguy,1914-08-10,Argentine +497,larreta,\N,Alberto Rodriguez,Larreta,1934-01-14,Argentine +498,gonzalez,\N,José Froilán,González,1922-10-05,Argentine +499,bonomi,\N,Roberto,Bonomi,1919-09-30,Argentine +500,munaron,\N,Gino,Munaron,1928-04-02,Italian +501,schell,\N,Harry,Schell,1921-06-29,American +502,stacey,\N,Alan,Stacey,1933-08-29,British +503,chimeri,\N,Ettore,Chimeri,1921-06-04,Venezuelan +504,creus,\N,Antonio,Creus,1924-10-28,Spanish +505,bristow,\N,Chris,Bristow,1937-12-02,British +506,halford,\N,Bruce,Halford,1931-05-18,British +507,daigh,\N,Chuck,Daigh,1923-11-29,American +508,reventlow,\N,Lance,Reventlow,1936-02-24,American +509,rathmann,\N,Jim,Rathmann,1928-07-16,American +510,goldsmith,\N,Paul,Goldsmith,1925-10-02,American +511,branson,\N,Don,Branson,1920-06-02,American +512,thomson,\N,Johnny,Thomson,1922-04-09,American +513,johnson,\N,Eddie,Johnson,1919-02-10,American +514,veith,\N,Bob,Veith,1926-11-01,American +515,tingelstad,\N,Bud,Tingelstad,1928-04-04,American +516,christie,\N,Bob,Christie,1924-04-04,American +517,amick,\N,Red,Amick,1929-01-19,American +518,darter,\N,Duane,Carter,1913-05-05,American +519,homeier,\N,Bill,Homeier,1918-08-31,American +520,hartley,\N,Gene,Hartley,1926-01-28,American +521,stevenson,\N,Chuck,Stevenson,1919-10-15,American +522,grim,\N,Bobby,Grim,1924-09-04,American +523,templeman,\N,Shorty,Templeman,1919-08-12,American +524,hurtubise,\N,Jim,Hurtubise,1932-12-05,American +525,bryan,\N,Jimmy,Bryan,1926-01-28,American +526,ruttman,\N,Troy,Ruttman,1930-03-11,American +527,sachs,\N,Eddie,Sachs,1927-05-28,American +528,freeland,\N,Don,Freeland,1925-03-25,American +529,bettenhausen,\N,Tony,Bettenhausen,1916-09-12,American +530,weiler,\N,Wayne,Weiler,1934-12-09,American +531,foyt,\N,Anthony,Foyt,1935-01-16,American +532,russo,\N,Eddie,Russo,1925-11-19,American +533,boyd,\N,Johnny,Boyd,1926-08-19,American +534,force,\N,Gene,Force,1916-06-15,American +535,mcwithey,\N,Jim,McWithey,1927-07-04,American +536,sutton,\N,Len,Sutton,1925-08-09,American +537,dick_rathmann,\N,Dick,Rathmann,1924-01-06,American +538,herman,\N,Al,Herman,1927-03-15,American +539,dempsey_wilson,\N,Dempsey,Wilson,1927-03-11,American +540,mike_taylor,\N,Mike,Taylor,1934-04-24,British +541,flockhart,\N,Ron,Flockhart,1923-06-16,British +542,piper,\N,David,Piper,1930-12-02,British +543,cabianca,\N,Giulio,Cabianca,1923-02-19,Italian +544,drogo,\N,Piero,Drogo,1926-08-08,Italian +545,gamble,\N,Fred,Gamble,1932-03-17,American +546,owen,\N,Arthur,Owen,1915-03-23,British +547,gould,\N,Horace,Gould,1918-09-20,British +548,drake,\N,Bob,Drake,1919-12-14,American +549,bueb,\N,Ivor,Bueb,1923-06-06,British +550,Changy,\N,Alain,de Changy,1922-02-05,Belgian +551,filippis,\N,Maria,de Filippis,1926-11-11,Italian +552,lucienbonnet,\N,Jean,Lucienbonnet,1923-01-07,French +553,testut,\N,André,Testut,1926-04-13,Monegasque +554,behra,\N,Jean,Behra,1921-02-16,French +555,paul_russo,\N,Paul,Russo,1914-04-10,American +556,daywalt,\N,Jimmy,Daywalt,1924-08-28,American +557,arnold,\N,Chuck,Arnold,1926-05-30,American +558,keller,\N,Al,Keller,1920-04-11,American +559,flaherty,\N,Pat,Flaherty,1926-01-06,American +560,cheesbourg,\N,Bill,Cheesbourg,1927-06-12,American +561,ray_crawford,\N,Ray,Crawford,1915-10-26,American +562,turner,\N,Jack,Turner,1920-02-12,American +563,weyant,\N,Chuck,Weyant,1923-04-03,American +564,larson,\N,Jud,Larson,1923-01-21,American +565,magill,\N,Mike,Magill,1920-02-08,American +566,shelby,\N,Carroll,Shelby,1923-01-11,American +567,orey,\N,Fritz,d'Orey,1938-03-25,Brazilian +568,fontes,\N,Azdrubal,Fontes,1922-12-26,Uruguayan +569,ashdown,\N,Peter,Ashdown,1934-10-16,British +570,bill_moss,\N,Bill,Moss,1933-09-04,British +571,dennis_taylor,\N,Dennis,Taylor,1921-06-12,British +572,blanchard,\N,Harry,Blanchard,1929-06-13,American +573,tomaso,\N,Alessandro,de Tomaso,1928-07-10,Argentine-Italian +574,constantine,\N,George,Constantine,1918-02-22,American +575,said,\N,Bob,Said,1932-05-05,American +576,cade,\N,Phil,Cade,1916-06-12,American +577,musso,\N,Luigi,Musso,1924-07-28,Italian +578,hawthorn,\N,Mike,Hawthorn,1929-04-10,British +579,fangio,\N,Juan,Fangio,1911-06-24,Argentine +580,godia,\N,Paco,Godia,1921-03-21,Spanish +581,collins,\N,Peter,Collins,1931-11-06,British +582,kavanagh,\N,Ken,Kavanagh,1923-12-12,Australian +583,gerini,\N,Gerino,Gerini,1928-08-10,Italian +584,kessler,\N,Bruce,Kessler,1936-03-23,American +585,emery,\N,Paul,Emery,1916-11-12,British +586,piotti,\N,Luigi,Piotti,1913-10-27,Italian +587,ecclestone,\N,Bernie,Ecclestone,1930-10-28,British +588,taramazzo,\N,Luigi,Taramazzo,1932-05-05,Italian +589,chiron,\N,Louis,Chiron,1899-08-03,Monegasque +590,lewis-evans,\N,Stuart,Lewis-Evans,1930-04-20,British +591,george_amick,\N,George,Amick,1924-10-24,American +592,reece,\N,Jimmy,Reece,1929-11-17,American +593,parsons,\N,Johnnie,Parsons,1918-07-04,American +594,tolan,\N,Johnnie,Tolan,1917-10-22,American +595,garrett,\N,Billy,Garrett,1933-04-24,American +596,elisian,\N,Ed,Elisian,1926-12-09,American +597,connor,\N,Pat,O'Connor,1928-10-09,American +598,jerry_unser,\N,Jerry,Unser,1932-11-15,American +599,bisch,\N,Art,Bisch,1926-11-10,American +600,goethals,\N,Christian,Goethals,1928-08-04,Belgian +601,gibson,\N,Dick,Gibson,1918-04-16,British +602,la_caze,\N,Robert,La Caze,1917-02-26,French +603,guelfi,\N,André,Guelfi,1919-05-06,French +604,picard,\N,François,Picard,1921-04-26,French +605,bridger,\N,Tom,Bridger,1934-06-24,British +606,portago,\N,Alfonso,de Portago,1928-10-11,Spanish +607,perdisa,\N,Cesare,Perdisa,1932-10-21,Italian +608,castellotti,\N,Eugenio,Castellotti,1930-10-10,Italian +609,simon,\N,André,Simon,1920-01-05,French +610,leston,\N,Les,Leston,1920-12-16,British +611,hanks,\N,Sam,Hanks,1914-07-13,American +612,linden,\N,Andy,Linden,1922-04-05,American +613,teague,\N,Marshall,Teague,1921-02-22,American +614,edmunds,\N,Don,Edmunds,1930-09-23,American +615,agabashian,\N,Fred,Agabashian,1913-08-21,American +616,george,\N,Elmer,George,1928-07-15,American +617,macdowel,\N,Mike,MacDowel,1932-09-13,British +618,mackay-fraser,\N,Herbert,MacKay-Fraser,1927-06-23,American +619,gerard,\N,Bob,Gerard,1914-01-19,British +620,maglioli,\N,Umberto,Maglioli,1928-06-05,Italian +621,england,\N,Paul,England,1929-03-28,Australian +622,landi,\N,Chico,Landi,1907-07-14,Brazilian +623,uria,\N,Alberto,Uria,1924-07-11,Uruguayan +624,ramos,\N,Hernando,da Silva Ramos,1925-12-07,Brazilian +625,bayol,\N,Élie,Bayol,1914-02-28,French +626,manzon,\N,Robert,Manzon,1917-04-12,French +627,rosier,\N,Louis,Rosier,1905-11-05,French +628,sweikert,\N,Bob,Sweikert,1926-05-20,American +629,griffith,\N,Cliff,Griffith,1916-02-06,American +630,dinsmore,\N,Duke,Dinsmore,1913-04-10,American +631,andrews,\N,Keith,Andrews,1920-06-15,American +632,frere,\N,Paul,Frère,1917-01-30,Belgian +633,villoresi,\N,Luigi,Villoresi,1909-05-16,Italian +634,scotti,\N,Piero,Scotti,1909-11-11,Italian +635,chapman,\N,Colin,Chapman,1928-05-19,British +636,titterington,\N,Desmond,Titterington,1928-05-01,British +637,scott_Brown,\N,Archie,Scott Brown,1927-05-13,British +638,volonterio,\N,Ottorino,Volonterio,1917-12-07,Swiss +639,milhoux,\N,André,Milhoux,1928-12-09,Belgian +640,graffenried,\N,Toulo,de Graffenried,1914-05-18,Swiss +641,taruffi,\N,Piero,Taruffi,1906-10-12,Italian +642,farina,\N,Nino,Farina,1906-10-30,Italian +643,mieres,\N,Roberto,Mieres,1924-12-03,Argentine +644,mantovani,\N,Sergio,Mantovani,1929-05-22,Italian +645,bucci,\N,Clemar,Bucci,1920-09-04,Argentine +646,iglesias,\N,Jesús,Iglesias,1922-02-22,Argentine +647,ascari,\N,Alberto,Ascari,1918-07-13,Italian +648,kling,\N,Karl,Kling,1910-09-16,German +649,birger,\N,Pablo,Birger,1924-01-07,Argentine +650,pollet,\N,Jacques,Pollet,1922-07-02,French +651,macklin,\N,Lance,Macklin,1919-09-02,British +652,whiteaway,\N,Ted,Whiteaway,1928-11-01,British +653,davies,\N,Jimmy,Davies,1929-08-08,American +654,faulkner,\N,Walt,Faulkner,1920-02-16,American +655,niday,\N,Cal,Niday,1914-04-29,American +656,cross,\N,Art,Cross,1918-01-24,American +657,vukovich,\N,Bill,Vukovich,1918-12-13,American +658,mcgrath,\N,Jack,McGrath,1919-10-08,American +659,hoyt,\N,Jerry,Hoyt,1929-01-29,American +660,claes,\N,Johnny,Claes,1916-08-11,Belgian +661,peter_walker,\N,Peter,Walker,1912-10-07,British +662,sparken,\N,Mike,Sparken,1930-06-16,French +663,wharton,\N,Ken,Wharton,1916-03-21,British +664,mcalpine,\N,Kenneth,McAlpine,1920-09-21,British +665,marr,\N,Leslie,Marr,1922-08-14,British +666,rolt,\N,Tony,Rolt,1918-10-16,British +667,fitch,\N,John,Fitch,1917-08-04,American +668,lucas,\N,Jean,Lucas,1917-04-25,French +669,bira,\N,Prince,Bira,1914-07-15,Thai +670,marimon,\N,Onofre,Marimón,1923-12-19,Argentine +671,loyer,\N,Roger,Loyer,1907-08-05,French +672,daponte,\N,Jorge,Daponte,1923-06-05,Argentine +673,nazaruk,\N,Mike,Nazaruk,1921-10-02,American +674,crockett,\N,Larry,Crockett,1926-10-23,American +675,ayulo,\N,Manny,Ayulo,1921-10-20,American +676,armi,\N,Frank,Armi,1918-10-12,American +677,webb,\N,Travis,Webb,1910-10-08,American +678,duncan,\N,Len,Duncan,1911-07-25,American +679,mccoy,\N,Ernie,McCoy,1921-02-19,American +680,swaters,\N,Jacques,Swaters,1926-10-30,American +681,georges_berger,\N,Georges,Berger,1918-09-14,Belgian +682,beauman,\N,Don,Beauman,1928-07-26,British +683,thorne,\N,Leslie,Thorne,1916-06-23,British +684,whitehouse,\N,Bill,Whitehouse,1909-04-01,British +685,riseley_prichard,\N,John,Riseley-Prichard,1924-01-17,British +686,reg_parnell,\N,Reg,Parnell,1911-07-02,British +687,whitehead,\N,Peter,Whitehead,1914-11-12,British +688,brandon,\N,Eric,Brandon,1920-07-18,British +689,alan_brown,\N,Alan,Brown,1919-11-20,British +690,nuckey,\N,Rodney,Nuckey,1929-06-26,British +691,lang,\N,Hermann,Lang,1909-04-06,German +692,helfrich,\N,Theo,Helfrich,1913-05-13,German +693,wacker,\N,Fred,Wacker,1918-07-10,American +694,riu,\N,Giovanni,de Riu,1925-03-10,Italian +695,galvez,\N,Oscar,Gálvez,1913-08-17,Argentine +696,john_barber,\N,John,Barber,1929-07-22,British +697,bonetto,\N,Felice,Bonetto,1903-06-09,Italian +698,cruz,\N,Adolfo,Cruz,1923-06-28,Argentine +699,nalon,\N,Duke,Nalon,1913-03-02,American +700,scarborough,\N,Carl,Scarborough,1914-07-03,American +701,holland,\N,Bill,Holland,1907-12-18,American +702,bob_scott,\N,Bob,Scott,1928-10-04,American +703,legat,\N,Arthur,Legat,1898-11-01,Belgian +704,cabantous,\N,Yves,Cabantous,1904-10-08,French +705,crook,\N,Tony,Crook,1920-02-16,British +706,jimmy_stewart,\N,Jimmy,Stewart,1931-03-06,British +707,ian_stewart,\N,Ian,Stewart,1929-07-15,British +708,duncan_hamilton,\N,Duncan,Hamilton,1920-04-30,British +709,klodwig,\N,Ernst,Klodwig,1903-05-23,East German +710,krause,\N,Rudolf,Krause,1907-03-30,East German +711,karch,\N,Oswald,Karch,1917-03-06,German +712,heeks,\N,Willi,Heeks,1922-02-13,German +713,fitzau,\N,Theo,Fitzau,1923-02-10,East German +714,adolff,\N,Kurt,Adolff,1921-11-05,German +715,bechem,\N,Günther,Bechem,1921-12-21,German +716,bauer,\N,Erwin,Bauer,1912-07-17,German +717,hans_stuck,\N,Hans,von Stuck,1900-12-27,German +718,loof,\N,Ernst,Loof,1907-07-04,German +719,scherrer,\N,Albert,Scherrer,1908-02-28,Swiss +720,terra,\N,Max,de Terra,1918-10-06,Swiss +721,hirt,\N,Peter,Hirt,1910-03-30,Swiss +722,carini,\N,Piero,Carini,1921-03-06,Italian +723,fischer,\N,Rudi,Fischer,1912-04-19,Swiss +724,ulmen,\N,Toni,Ulmen,1906-01-25,German +725,abecassis,\N,George,Abecassis,1913-03-21,British +726,george_connor,\N,George,Connor,1906-08-16,American +727,rigsby,\N,Jim,Rigsby,1923-06-06,American +728,james,\N,Joe,James,1925-05-23,American +729,schindler,\N,Bill,Schindler,1909-03-06,American +730,fonder,\N,George,Fonder,1917-06-22,American +731,banks,\N,Henry,Banks,1913-06-14,American +732,mcdowell,\N,Johnny,McDowell,1915-01-29,American +733,miller,\N,Chet,Miller,1902-07-19,American +734,ball,\N,Bobby,Ball,1925-08-26,American +735,tornaco,\N,Charles,de Tornaco,1927-06-07,Belgian +736,laurent,\N,Roger,Laurent,1913-02-21,Belgian +737,obrien,\N,Robert,O'Brien,1908-04-11,American +738,gaze,\N,Tony,Gaze,1920-02-03,Australian +739,charrington,\N,Robin,Montgomerie-Charrington,1915-06-23,British +740,comotti,\N,Franco,Comotti,1906-07-24,Italian +741,etancelin,\N,Philippe,Étancelin,1896-12-28,French +742,poore,\N,Dennis,Poore,1916-08-19,British +743,thompson,\N,Eric,Thompson,1919-11-04,British +744,downing,\N,Ken,Downing,1917-12-05,British +745,graham_whitehead,\N,Graham,Whitehead,1922-04-15,British +746,bianco,\N,Gino,Bianco,1916-07-22,Brazilian +747,murray,\N,David,Murray,1909-12-28,British +748,cantoni,\N,Eitel,Cantoni,1906-10-04,Uruguayan +749,aston,\N,Bill,Aston,1900-03-29,British +750,brudes,\N,Adolf,Brudes,1899-10-15,German +751,riess,\N,Fritz,Riess,1922-07-11,German +752,niedermayr,\N,Helmut,Niedermayr,1915-11-29,German +753,klenk,\N,Hans,Klenk,1919-10-28,German +754,balsa,\N,Marcel,Balsa,1909-01-01,French +755,schoeller,\N,Rudolf,Schoeller,1902-04-27,Swiss +756,pietsch,\N,Paul,Pietsch,1911-06-20,German +757,peters,\N,Josef,Peters,1914-09-16,German +758,lof,\N,Dries,van der Lof,1919-08-23,Dutch +759,flinterman,\N,Jan,Flinterman,1919-10-02,Dutch +760,dusio,\N,Piero,Dusio,1899-10-13,Italian +761,crespo,\N,Alberto,Crespo,1920-01-16,Argentine +762,rol,\N,Franco,Rol,1908-06-05,Italian +763,sanesi,\N,Consalvo,Sanesi,1911-03-28,Italian +764,guy_mairesse,\N,Guy,Mairesse,1910-08-10,French +765,louveau,\N,Henri,Louveau,1910-01-25,French +766,wallard,\N,Lee,Wallard,1910-09-07,American +767,forberg,\N,Carl,Forberg,1911-03-04,American +768,rose,\N,Mauri,Rose,1906-05-26,American +769,mackey,\N,Bill,Mackey,1927-12-15,American +770,green,\N,Cecil,Green,1919-09-30,American +771,walt_brown,\N,Walt,Brown,1911-12-30,American +772,hellings,\N,Mack,Hellings,1915-09-14,American +773,levegh,\N,Pierre,Levegh,1905-12-22,French +774,chaboud,\N,Eugène,Chaboud,1907-04-12,French +775,gordini,\N,Aldo,Gordini,1921-05-20,French +776,kelly,\N,Joe,Kelly,1913-03-13,Irish +777,parker,\N,Philip,Fotheringham-Parker,1907-09-22,British +778,shawe_taylor,\N,Brian,Shawe Taylor,1915-01-28,British +779,john_james,\N,John,James,1914-05-10,British +780,branca,\N,Toni,Branca,1916-09-15,Swiss +781,richardson,\N,Ken,Richardson,1911-08-21,British +782,jover,\N,Juan,Jover,1903-11-23,Spanish +783,grignard,\N,Georges,Grignard,1905-07-25,French +784,hampshire,\N,David,Hampshire,1917-12-29,British +785,crossley,\N,Geoff,Crossley,1921-05-11,British +786,fagioli,\N,Luigi,Fagioli,1898-06-09,Italian +787,harrison,\N,Cuth,Harrison,1906-07-06,British +788,fry,\N,Joe,Fry,1915-10-26,British +789,martin,\N,Eugène,Martin,1915-03-24,French +790,leslie_johnson,\N,Leslie,Johnson,1912-03-22,British +791,biondetti,\N,Clemente,Biondetti,1898-08-18,Italian +792,pian,\N,Alfredo,Pián,1912-10-21,Argentine +793,sommer,\N,Raymond,Sommer,1906-08-31,French +794,chitwood,\N,Joie,Chitwood,1912-04-14,American +795,fohr,\N,Myron,Fohr,1912-06-17,American +796,ader,\N,Walt,Ader,1913-12-15,American +797,holmes,\N,Jackie,Holmes,1920-09-04,American +798,levrett,\N,Bayliss,Levrett,1914-02-14,American +799,jackson,\N,Jimmy,Jackson,1910-07-25,American +800,pagani,\N,Nello,Pagani,1911-10-11,Italian +801,pozzi,\N,Charles,Pozzi,1909-08-27,French +802,serafini,\N,Dorino,Serafini,1909-07-22,Italian +803,cantrell,\N,Bill,Cantrell,1908-01-31,American +804,mantz,\N,Johnny,Mantz,1918-09-18,American +805,kladis,\N,Danny,Kladis,1917-02-10,American +806,oscar_gonzalez,\N,Óscar,González,1923-11-10,Uruguayan +807,hulkenberg,HUL,Nico,Hülkenberg,1987-08-19,German +808,petrov,PET,Vitaly,Petrov,1984-09-08,Russian +809,grassi,DIG,Lucas,di Grassi,1984-08-11,Brazilian +810,bruno_senna,SEN,Bruno,Senna,1983-10-15,Brazilian +811,chandhok,CHA,Karun,Chandhok,1984-01-19,Indian +812,maldonado,MAL,Pastor,Maldonado,1985-03-09,Venezuelan +813,resta,DIR,Paul,di Resta,1986-04-16,British +814,perez,PER,Sergio,Pérez,1990-01-26,Mexican +815,ambrosio,DAM,Jérôme,d'Ambrosio,1985-12-27,Belgian +816,ricciardo,RIC,Daniel,Ricciardo,1989-07-01,Australian +817,vergne,VER,Jean-Éric,Vergne,1990-04-25,French +818,pic,PIC,Charles,Pic,1990-02-15,French +819,chilton,CHI,Max,Chilton,1991-04-21,British +820,gutierrez,GUT,Esteban,Gutiérrez,1991-08-05,Mexican +821,bottas,BOT,Valtteri,Bottas,1989-08-28,Finnish +822,garde,VDG,Giedo,van der Garde,1985-04-25,Dutch +823,jules_bianchi,BIA,Jules,Bianchi,1989-08-03,French +824,kevin_magnussen,MAG,Kevin,Magnussen,1992-10-05,Danish +825,kvyat,KVY,Daniil,Kvyat,1994-04-26,Russian +826,lotterer,LOT,André,Lotterer,1981-11-19,German +827,ericsson,ERI,Marcus,Ericsson,1990-09-02,Swedish +828,stevens,STE,Will,Stevens,1991-06-28,British +829,max_verstappen,VER,Max,Verstappen,1997-09-30,Dutch +830,nasr,NAS,Felipe,Nasr,1992-08-21,Brazilian +831,sainz,SAI,Carlos,Sainz,1994-09-01,Spanish +832,merhi,MER,Roberto,Merhi,1991-03-22,Spanish +833,rossi,RSS,Alexander,Rossi,1991-09-25,American +834,jolyon_palmer,PAL,Jolyon,Palmer,1991-01-20,British +835,wehrlein,WEH,Pascal,Wehrlein,1994-10-18,German +836,haryanto,HAR,Rio,Haryanto,1993-01-22,Indonesian +837,vandoorne,VAN,Stoffel,Vandoorne,1992-03-26,Belgian +838,ocon,OCO,Esteban,Ocon,1996-09-17,French +839,stroll,STR,Lance,Stroll,1998-10-29,Canadian +840,giovinazzi,GIO,Antonio,Giovinazzi,1993-12-14,Italian +841,brendon_hartley,HAR,Brendon,Hartley,1989-11-10,New Zealander +842,leclerc,LEC,Charles,Leclerc,1997-10-16,Monegasque +843,sirotkin,SIR,Sergey,Sirotkin,1995-08-27,Russian +844,norris,NOR,Lando,Norris,1999-11-13,British +845,russell,RUS,George,Russell,1998-02-15,British +846,albon,ALB,Alexander,Albon,1996-03-23,Thai +847,latifi,LAT,Nicholas,Latifi,1995-06-29,Canadian +848,pietro_fittipaldi,FIT,Pietro,Fittipaldi,1996-06-25,Brazilian +849,aitken,AIT,Jack,Aitken,1995-09-23,British +850,tsunoda,TSU,Yuki,Tsunoda,2000-05-11,Japanese +851,mazepin,MAZ,Nikita,Mazepin,1999-03-02,Russian +852,mick_schumacher,MSC,Mick,Schumacher,1999-03-22,German +853,zhou,ZHO,Guanyu,Zhou,1999-05-30,Chinese +854,de_vries,DEV,Nyck,de Vries,1995-02-06,Dutch +855,piastri,PIA,Oscar,Piastri,2001-04-06,Australian +856,sargeant,SAR,Logan,Sargeant,2000-12-31,American diff --git a/scripts/f1_data/import_f1.sql b/scripts/f1_data/import_f1.sql new file mode 100644 index 00000000..997b8624 --- /dev/null +++ b/scripts/f1_data/import_f1.sql @@ -0,0 +1,490 @@ +-- RelBench REL-F1 Database Schema +-- Auto-generated from RelBench dataset +-- Total tables: 9 + +\echo '=========================================' +\echo 'Step 1: Drop existing tables' +\echo '=========================================' + +DROP TABLE IF EXISTS drivers CASCADE; +DROP TABLE IF EXISTS races CASCADE; +DROP TABLE IF EXISTS circuits CASCADE; +DROP TABLE IF EXISTS constructor_standings CASCADE; +DROP TABLE IF EXISTS constructors CASCADE; +DROP TABLE IF EXISTS qualifying CASCADE; +DROP TABLE IF EXISTS standings CASCADE; +DROP TABLE IF EXISTS results CASCADE; +DROP TABLE IF EXISTS constructor_results CASCADE; + +\echo 'Tables dropped' +\echo '' + +\echo '=========================================' +\echo 'Step 2: Create tables' +\echo '=========================================' + +CREATE TABLE constructor_results ( + constructorResultsId INTEGER, + raceId INTEGER, + constructorId INTEGER, + points FLOAT, + date TIMESTAMP, + PRIMARY KEY (constructorResultsId) +); + +CREATE TABLE results ( + resultId INTEGER, + raceId INTEGER, + driverId INTEGER, + constructorId INTEGER, + number FLOAT, + grid INTEGER, + position FLOAT, + positionOrder INTEGER, + points FLOAT, + laps INTEGER, + milliseconds FLOAT, + fastestLap FLOAT, + rank FLOAT, + statusId INTEGER, + date TIMESTAMP, + PRIMARY KEY (resultId) +); + +CREATE TABLE standings ( + driverStandingsId INTEGER, + raceId INTEGER, + driverId INTEGER, + points FLOAT, + position INTEGER, + wins INTEGER, + date TIMESTAMP, + PRIMARY KEY (driverStandingsId) +); + +CREATE TABLE qualifying ( + qualifyId INTEGER, + raceId INTEGER, + driverId INTEGER, + constructorId INTEGER, + number INTEGER, + position INTEGER, + date TIMESTAMP, + PRIMARY KEY (qualifyId) +); + +CREATE TABLE constructors ( + constructorId INTEGER, + constructorRef TEXT, + name TEXT, + nationality TEXT, + PRIMARY KEY (constructorId) +); + +CREATE TABLE constructor_standings ( + constructorStandingsId INTEGER, + raceId INTEGER, + constructorId INTEGER, + points FLOAT, + position INTEGER, + wins INTEGER, + date TIMESTAMP, + PRIMARY KEY (constructorStandingsId) +); + +CREATE TABLE circuits ( + circuitId INTEGER, + circuitRef TEXT, + name TEXT, + location TEXT, + country TEXT, + lat FLOAT, + lng FLOAT, + alt FLOAT, + PRIMARY KEY (circuitId) +); + +CREATE TABLE races ( + raceId INTEGER, + year INTEGER, + round INTEGER, + circuitId INTEGER, + name TEXT, + date TIMESTAMP, + time TEXT, + PRIMARY KEY (raceId) +); + +CREATE TABLE drivers ( + driverId INTEGER, + driverRef TEXT, + code TEXT, + forename TEXT, + surname TEXT, + dob TIMESTAMP, + nationality TEXT, + PRIMARY KEY (driverId) +); + +\echo 'Tables created' +\echo '' + +\echo '=========================================' +\echo 'Step 3: Create temp tables for import' +\echo '=========================================' + +CREATE TEMP TABLE temp_constructor_results ( + constructorResultsId TEXT, + raceId TEXT, + constructorId TEXT, + points TEXT, + date TEXT +); + +CREATE TEMP TABLE temp_results ( + resultId TEXT, + raceId TEXT, + driverId TEXT, + constructorId TEXT, + number TEXT, + grid TEXT, + position TEXT, + positionOrder TEXT, + points TEXT, + laps TEXT, + milliseconds TEXT, + fastestLap TEXT, + rank TEXT, + statusId TEXT, + date TEXT +); + +CREATE TEMP TABLE temp_standings ( + driverStandingsId TEXT, + raceId TEXT, + driverId TEXT, + points TEXT, + position TEXT, + wins TEXT, + date TEXT +); + +CREATE TEMP TABLE temp_qualifying ( + qualifyId TEXT, + raceId TEXT, + driverId TEXT, + constructorId TEXT, + number TEXT, + position TEXT, + date TEXT +); + +CREATE TEMP TABLE temp_constructors ( + constructorId TEXT, + constructorRef TEXT, + name TEXT, + nationality TEXT +); + +CREATE TEMP TABLE temp_constructor_standings ( + constructorStandingsId TEXT, + raceId TEXT, + constructorId TEXT, + points TEXT, + position TEXT, + wins TEXT, + date TEXT +); + +CREATE TEMP TABLE temp_circuits ( + circuitId TEXT, + circuitRef TEXT, + name TEXT, + location TEXT, + country TEXT, + lat TEXT, + lng TEXT, + alt TEXT +); + +CREATE TEMP TABLE temp_races ( + raceId TEXT, + year TEXT, + round TEXT, + circuitId TEXT, + name TEXT, + date TEXT, + time TEXT +); + +CREATE TEMP TABLE temp_drivers ( + driverId TEXT, + driverRef TEXT, + code TEXT, + forename TEXT, + surname TEXT, + dob TEXT, + nationality TEXT +); + +\echo 'Temp tables created' +\echo '' + +\echo '=========================================' +\echo 'Step 4: Import CSV into temp tables' +\echo '=========================================' + +\echo ' Importing constructor_results...' +\copy temp_constructor_results FROM '/tmp/constructor_results.csv' WITH CSV HEADER DELIMITER ','; + +\echo ' Importing results...' +\copy temp_results FROM '/tmp/results.csv' WITH CSV HEADER DELIMITER ','; + +\echo ' Importing standings...' +\copy temp_standings FROM '/tmp/standings.csv' WITH CSV HEADER DELIMITER ','; + +\echo ' Importing qualifying...' +\copy temp_qualifying FROM '/tmp/qualifying.csv' WITH CSV HEADER DELIMITER ','; + +\echo ' Importing constructors...' +\copy temp_constructors FROM '/tmp/constructors.csv' WITH CSV HEADER DELIMITER ','; + +\echo ' Importing constructor_standings...' +\copy temp_constructor_standings FROM '/tmp/constructor_standings.csv' WITH CSV HEADER DELIMITER ','; + +\echo ' Importing circuits...' +\copy temp_circuits FROM '/tmp/circuits.csv' WITH CSV HEADER DELIMITER ','; + +\echo ' Importing races...' +\copy temp_races FROM '/tmp/races.csv' WITH CSV HEADER DELIMITER ','; + +\echo ' Importing drivers...' +\copy temp_drivers FROM '/tmp/drivers.csv' WITH CSV HEADER DELIMITER ','; + +\echo 'CSV imported to temp tables' +\echo '' + +\echo '=========================================' +\echo 'Step 5: Transfer data with type conversion' +\echo '=========================================' + +\echo ' Processing constructor_results...' +INSERT INTO constructor_results +SELECT + NULLIF(constructorResultsId, '')::INTEGER, + NULLIF(raceId, '')::INTEGER, + NULLIF(constructorId, '')::INTEGER, + NULLIF(points, '')::FLOAT, + NULLIF(date, '')::TIMESTAMP +FROM temp_constructor_results; + +\echo ' Processing results...' +INSERT INTO results +SELECT + NULLIF(resultId, '')::INTEGER, + NULLIF(raceId, '')::INTEGER, + NULLIF(driverId, '')::INTEGER, + NULLIF(constructorId, '')::INTEGER, + NULLIF(number, '')::FLOAT, + NULLIF(grid, '')::INTEGER, + NULLIF(position, '')::FLOAT, + NULLIF(positionOrder, '')::INTEGER, + NULLIF(points, '')::FLOAT, + NULLIF(laps, '')::INTEGER, + NULLIF(milliseconds, '')::FLOAT, + NULLIF(fastestLap, '')::FLOAT, + NULLIF(rank, '')::FLOAT, + NULLIF(statusId, '')::INTEGER, + NULLIF(date, '')::TIMESTAMP +FROM temp_results; + +\echo ' Processing standings...' +INSERT INTO standings +SELECT + NULLIF(driverStandingsId, '')::INTEGER, + NULLIF(raceId, '')::INTEGER, + NULLIF(driverId, '')::INTEGER, + NULLIF(points, '')::FLOAT, + NULLIF(position, '')::INTEGER, + NULLIF(wins, '')::INTEGER, + NULLIF(date, '')::TIMESTAMP +FROM temp_standings; + +\echo ' Processing qualifying...' +INSERT INTO qualifying +SELECT + NULLIF(qualifyId, '')::INTEGER, + NULLIF(raceId, '')::INTEGER, + NULLIF(driverId, '')::INTEGER, + NULLIF(constructorId, '')::INTEGER, + NULLIF(number, '')::INTEGER, + NULLIF(position, '')::INTEGER, + NULLIF(date, '')::TIMESTAMP +FROM temp_qualifying; + +\echo ' Processing constructors...' +INSERT INTO constructors +SELECT + NULLIF(constructorId, '')::INTEGER, + NULLIF(constructorRef, ''), + NULLIF(name, ''), + NULLIF(nationality, '') +FROM temp_constructors; + +\echo ' Processing constructor_standings...' +INSERT INTO constructor_standings +SELECT + NULLIF(constructorStandingsId, '')::INTEGER, + NULLIF(raceId, '')::INTEGER, + NULLIF(constructorId, '')::INTEGER, + NULLIF(points, '')::FLOAT, + NULLIF(position, '')::INTEGER, + NULLIF(wins, '')::INTEGER, + NULLIF(date, '')::TIMESTAMP +FROM temp_constructor_standings; + +\echo ' Processing circuits...' +INSERT INTO circuits +SELECT + NULLIF(circuitId, '')::INTEGER, + NULLIF(circuitRef, ''), + NULLIF(name, ''), + NULLIF(location, ''), + NULLIF(country, ''), + NULLIF(lat, '')::FLOAT, + NULLIF(lng, '')::FLOAT, + NULLIF(alt, '')::FLOAT +FROM temp_circuits; + +\echo ' Processing races...' +INSERT INTO races +SELECT + NULLIF(raceId, '')::INTEGER, + NULLIF(year, '')::INTEGER, + NULLIF(round, '')::INTEGER, + NULLIF(circuitId, '')::INTEGER, + NULLIF(name, ''), + NULLIF(date, '')::TIMESTAMP, + NULLIF(time, '') +FROM temp_races; + +\echo ' Processing drivers...' +INSERT INTO drivers +SELECT + NULLIF(driverId, '')::INTEGER, + NULLIF(driverRef, ''), + NULLIF(code, ''), + NULLIF(forename, ''), + NULLIF(surname, ''), + NULLIF(dob, '')::TIMESTAMP, + NULLIF(nationality, '') +FROM temp_drivers; + +\echo 'Data transferred with NULL handling' +\echo '' + +\echo '=========================================' +\echo 'Step 6: Add Foreign Keys' +\echo '=========================================' + +ALTER TABLE constructor_results ADD CONSTRAINT fk_constructor_results_raceId + FOREIGN KEY (raceId) REFERENCES races(raceId); + +ALTER TABLE constructor_results ADD CONSTRAINT fk_constructor_results_constructorId + FOREIGN KEY (constructorId) REFERENCES constructors(constructorId); + +ALTER TABLE results ADD CONSTRAINT fk_results_raceId + FOREIGN KEY (raceId) REFERENCES races(raceId); + +ALTER TABLE results ADD CONSTRAINT fk_results_driverId + FOREIGN KEY (driverId) REFERENCES drivers(driverId); + +ALTER TABLE results ADD CONSTRAINT fk_results_constructorId + FOREIGN KEY (constructorId) REFERENCES constructors(constructorId); + +ALTER TABLE standings ADD CONSTRAINT fk_standings_raceId + FOREIGN KEY (raceId) REFERENCES races(raceId); + +ALTER TABLE standings ADD CONSTRAINT fk_standings_driverId + FOREIGN KEY (driverId) REFERENCES drivers(driverId); + +ALTER TABLE qualifying ADD CONSTRAINT fk_qualifying_raceId + FOREIGN KEY (raceId) REFERENCES races(raceId); + +ALTER TABLE qualifying ADD CONSTRAINT fk_qualifying_driverId + FOREIGN KEY (driverId) REFERENCES drivers(driverId); + +ALTER TABLE qualifying ADD CONSTRAINT fk_qualifying_constructorId + FOREIGN KEY (constructorId) REFERENCES constructors(constructorId); + +ALTER TABLE constructor_standings ADD CONSTRAINT fk_constructor_standings_raceId + FOREIGN KEY (raceId) REFERENCES races(raceId); + +ALTER TABLE constructor_standings ADD CONSTRAINT fk_constructor_standings_constructorId + FOREIGN KEY (constructorId) REFERENCES constructors(constructorId); + +ALTER TABLE races ADD CONSTRAINT fk_races_circuitId + FOREIGN KEY (circuitId) REFERENCES circuits(circuitId); + +\echo 'Foreign keys added' +\echo '' + +\echo '=========================================' +\echo 'Step 7: Create Indexes' +\echo '=========================================' + +CREATE INDEX idx_constructor_results_raceId ON constructor_results(raceId) WHERE raceId IS NOT NULL; +CREATE INDEX idx_constructor_results_constructorId ON constructor_results(constructorId) WHERE constructorId IS NOT NULL; +CREATE INDEX idx_constructor_results_date ON constructor_results(date); +CREATE INDEX idx_results_raceId ON results(raceId) WHERE raceId IS NOT NULL; +CREATE INDEX idx_results_driverId ON results(driverId) WHERE driverId IS NOT NULL; +CREATE INDEX idx_results_constructorId ON results(constructorId) WHERE constructorId IS NOT NULL; +CREATE INDEX idx_results_date ON results(date); +CREATE INDEX idx_standings_raceId ON standings(raceId) WHERE raceId IS NOT NULL; +CREATE INDEX idx_standings_driverId ON standings(driverId) WHERE driverId IS NOT NULL; +CREATE INDEX idx_standings_date ON standings(date); +CREATE INDEX idx_qualifying_raceId ON qualifying(raceId) WHERE raceId IS NOT NULL; +CREATE INDEX idx_qualifying_driverId ON qualifying(driverId) WHERE driverId IS NOT NULL; +CREATE INDEX idx_qualifying_constructorId ON qualifying(constructorId) WHERE constructorId IS NOT NULL; +CREATE INDEX idx_qualifying_date ON qualifying(date); +CREATE INDEX idx_constructor_standings_raceId ON constructor_standings(raceId) WHERE raceId IS NOT NULL; +CREATE INDEX idx_constructor_standings_constructorId ON constructor_standings(constructorId) WHERE constructorId IS NOT NULL; +CREATE INDEX idx_constructor_standings_date ON constructor_standings(date); +CREATE INDEX idx_races_circuitId ON races(circuitId) WHERE circuitId IS NOT NULL; +CREATE INDEX idx_races_date ON races(date); + +\echo 'Indexes created' +\echo '' + +\echo '=========================================' +\echo 'Summary' +\echo '=========================================' + +SELECT + table_name, + to_char(record_count, 'FM999,999,999') as records +FROM ( + SELECT 'constructor_results' as table_name, COUNT(*) as record_count FROM constructor_results + UNION ALL + SELECT 'results' as table_name, COUNT(*) as record_count FROM results + UNION ALL + SELECT 'standings' as table_name, COUNT(*) as record_count FROM standings + UNION ALL + SELECT 'qualifying' as table_name, COUNT(*) as record_count FROM qualifying + UNION ALL + SELECT 'constructors' as table_name, COUNT(*) as record_count FROM constructors + UNION ALL + SELECT 'constructor_standings' as table_name, COUNT(*) as record_count FROM constructor_standings + UNION ALL + SELECT 'circuits' as table_name, COUNT(*) as record_count FROM circuits + UNION ALL + SELECT 'races' as table_name, COUNT(*) as record_count FROM races + UNION ALL + SELECT 'drivers' as table_name, COUNT(*) as record_count FROM drivers +) t +ORDER BY record_count DESC; + +\echo '' +\echo '=========================================' +\echo 'IMPORT COMPLETE' +\echo '=========================================' \ No newline at end of file diff --git a/scripts/f1_data/qualifying.csv b/scripts/f1_data/qualifying.csv new file mode 100644 index 00000000..a9c2b369 --- /dev/null +++ b/scripts/f1_data/qualifying.csv @@ -0,0 +1,4083 @@ +qualifyId,raceId,driverId,constructorId,number,position,date +0,548,43,26,26,19,1994-03-26 00:00:00 +1,548,100,30,31,26,1994-03-26 00:00:00 +2,548,91,29,34,25,1994-03-26 00:00:00 +3,548,82,31,11,24,1994-03-26 00:00:00 +4,548,105,32,19,23,1994-03-26 00:00:00 +5,548,104,17,24,22,1994-03-26 00:00:00 +6,548,64,31,12,21,1994-03-26 00:00:00 +7,548,102,26,25,20,1994-03-26 00:00:00 +8,548,83,0,8,18,1994-03-26 00:00:00 +9,548,76,5,28,17,1994-03-26 00:00:00 +10,548,55,16,15,16,1994-03-26 00:00:00 +11,548,21,16,14,14,1994-03-26 00:00:00 +12,548,99,32,20,13,1994-03-26 00:00:00 +13,548,93,17,23,15,1994-03-26 00:00:00 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+102,1962,1,38,Dutch Grand Prix,1962-05-20 00:00:00,00:00:00 +103,1962,2,5,Monaco Grand Prix,1962-06-03 00:00:00,00:00:00 +104,1962,3,12,Belgian Grand Prix,1962-06-17 00:00:00,00:00:00 +105,1962,4,52,French Grand Prix,1962-07-08 00:00:00,00:00:00 +106,1962,5,57,British Grand Prix,1962-07-21 00:00:00,00:00:00 +107,1962,6,19,German Grand Prix,1962-08-05 00:00:00,00:00:00 +108,1962,7,13,Italian Grand Prix,1962-09-16 00:00:00,00:00:00 +109,1962,8,45,United States Grand Prix,1962-10-07 00:00:00,00:00:00 +110,1962,9,55,South African Grand Prix,1962-12-29 00:00:00,00:00:00 +111,1963,1,5,Monaco Grand Prix,1963-05-26 00:00:00,00:00:00 +112,1963,2,12,Belgian Grand Prix,1963-06-09 00:00:00,00:00:00 +113,1963,3,38,Dutch Grand Prix,1963-06-23 00:00:00,00:00:00 +114,1963,4,54,French Grand Prix,1963-06-30 00:00:00,00:00:00 +115,1963,5,8,British Grand Prix,1963-07-20 00:00:00,00:00:00 +116,1963,6,19,German Grand Prix,1963-08-04 00:00:00,00:00:00 +117,1963,7,13,Italian Grand Prix,1963-09-08 00:00:00,00:00:00 +118,1963,8,45,United States Grand Prix,1963-10-06 00:00:00,00:00:00 +119,1963,9,31,Mexican Grand Prix,1963-10-27 00:00:00,00:00:00 +120,1963,10,55,South African Grand Prix,1963-12-28 00:00:00,00:00:00 +121,1964,1,5,Monaco Grand Prix,1964-05-10 00:00:00,00:00:00 +122,1964,2,38,Dutch Grand Prix,1964-05-24 00:00:00,00:00:00 +123,1964,3,12,Belgian Grand Prix,1964-06-14 00:00:00,00:00:00 +124,1964,4,52,French Grand Prix,1964-06-28 00:00:00,00:00:00 +125,1964,5,37,British Grand Prix,1964-07-11 00:00:00,00:00:00 +126,1964,6,19,German Grand Prix,1964-08-02 00:00:00,00:00:00 +127,1964,7,56,Austrian Grand Prix,1964-08-23 00:00:00,00:00:00 +128,1964,8,13,Italian Grand Prix,1964-09-06 00:00:00,00:00:00 +129,1964,9,45,United States Grand Prix,1964-10-04 00:00:00,00:00:00 +130,1964,10,31,Mexican Grand Prix,1964-10-25 00:00:00,00:00:00 +131,1965,1,55,South African Grand Prix,1965-01-01 00:00:00,00:00:00 +132,1965,2,5,Monaco Grand Prix,1965-05-30 00:00:00,00:00:00 +133,1965,3,12,Belgian Grand Prix,1965-06-13 00:00:00,00:00:00 +134,1965,4,50,French Grand Prix,1965-06-27 00:00:00,00:00:00 +135,1965,5,8,British Grand Prix,1965-07-10 00:00:00,00:00:00 +136,1965,6,38,Dutch Grand Prix,1965-07-18 00:00:00,00:00:00 +137,1965,7,19,German Grand Prix,1965-08-01 00:00:00,00:00:00 +138,1965,8,13,Italian Grand Prix,1965-09-12 00:00:00,00:00:00 +139,1965,9,45,United States Grand Prix,1965-10-03 00:00:00,00:00:00 +140,1965,10,31,Mexican Grand Prix,1965-10-24 00:00:00,00:00:00 +141,1966,1,5,Monaco Grand Prix,1966-05-22 00:00:00,00:00:00 +142,1966,2,12,Belgian Grand Prix,1966-06-12 00:00:00,00:00:00 +143,1966,3,54,French Grand Prix,1966-07-03 00:00:00,00:00:00 +144,1966,4,37,British Grand Prix,1966-07-16 00:00:00,00:00:00 +145,1966,5,38,Dutch Grand Prix,1966-07-24 00:00:00,00:00:00 +146,1966,6,19,German Grand Prix,1966-08-07 00:00:00,00:00:00 +147,1966,7,13,Italian Grand Prix,1966-09-04 00:00:00,00:00:00 +148,1966,8,45,United States Grand Prix,1966-10-02 00:00:00,00:00:00 +149,1966,9,31,Mexican Grand Prix,1966-10-23 00:00:00,00:00:00 +150,1967,1,29,South African Grand Prix,1967-01-02 00:00:00,00:00:00 +151,1967,2,5,Monaco Grand Prix,1967-05-07 00:00:00,00:00:00 +152,1967,3,38,Dutch Grand Prix,1967-06-04 00:00:00,00:00:00 +153,1967,4,12,Belgian Grand Prix,1967-06-18 00:00:00,00:00:00 +154,1967,5,53,French Grand Prix,1967-07-02 00:00:00,00:00:00 +155,1967,6,8,British Grand Prix,1967-07-15 00:00:00,00:00:00 +156,1967,7,19,German Grand Prix,1967-08-06 00:00:00,00:00:00 +157,1967,8,47,Canadian Grand Prix,1967-08-27 00:00:00,00:00:00 +158,1967,9,13,Italian Grand Prix,1967-09-10 00:00:00,00:00:00 +159,1967,10,45,United States Grand Prix,1967-10-01 00:00:00,00:00:00 +160,1967,11,31,Mexican Grand Prix,1967-10-22 00:00:00,00:00:00 +161,1968,1,29,South African Grand Prix,1968-01-01 00:00:00,00:00:00 +162,1968,2,44,Spanish Grand Prix,1968-05-12 00:00:00,00:00:00 +163,1968,3,5,Monaco Grand Prix,1968-05-26 00:00:00,00:00:00 +164,1968,4,12,Belgian Grand Prix,1968-06-09 00:00:00,00:00:00 +165,1968,5,38,Dutch Grand Prix,1968-06-23 00:00:00,00:00:00 +166,1968,6,52,French Grand Prix,1968-07-07 00:00:00,00:00:00 +167,1968,7,37,British Grand Prix,1968-07-20 00:00:00,00:00:00 +168,1968,8,19,German Grand Prix,1968-08-04 00:00:00,00:00:00 +169,1968,9,13,Italian Grand Prix,1968-09-08 00:00:00,00:00:00 +170,1968,10,51,Canadian Grand Prix,1968-09-22 00:00:00,00:00:00 +171,1968,11,45,United States Grand Prix,1968-10-06 00:00:00,00:00:00 +172,1968,12,31,Mexican Grand Prix,1968-11-03 00:00:00,00:00:00 +173,1969,1,29,South African Grand Prix,1969-03-01 00:00:00,00:00:00 +174,1969,2,48,Spanish Grand Prix,1969-05-04 00:00:00,00:00:00 +175,1969,3,5,Monaco Grand Prix,1969-05-18 00:00:00,00:00:00 +176,1969,4,38,Dutch Grand Prix,1969-06-21 00:00:00,00:00:00 +177,1969,5,50,French Grand Prix,1969-07-06 00:00:00,00:00:00 +178,1969,6,8,British Grand Prix,1969-07-19 00:00:00,00:00:00 +179,1969,7,19,German Grand Prix,1969-08-03 00:00:00,00:00:00 +180,1969,8,13,Italian Grand Prix,1969-09-07 00:00:00,00:00:00 +181,1969,9,47,Canadian Grand Prix,1969-09-20 00:00:00,00:00:00 +182,1969,10,45,United States Grand Prix,1969-10-05 00:00:00,00:00:00 +183,1969,11,31,Mexican Grand Prix,1969-10-19 00:00:00,00:00:00 +184,1970,1,29,South African Grand Prix,1970-03-07 00:00:00,00:00:00 +185,1970,2,44,Spanish Grand Prix,1970-04-19 00:00:00,00:00:00 +186,1970,3,5,Monaco Grand Prix,1970-05-10 00:00:00,00:00:00 +187,1970,4,12,Belgian Grand Prix,1970-06-07 00:00:00,00:00:00 +188,1970,5,38,Dutch Grand Prix,1970-06-21 00:00:00,00:00:00 +189,1970,6,50,French Grand Prix,1970-07-05 00:00:00,00:00:00 +190,1970,7,37,British Grand Prix,1970-07-18 00:00:00,00:00:00 +191,1970,8,9,German Grand Prix,1970-08-02 00:00:00,00:00:00 +192,1970,9,69,Austrian Grand Prix,1970-08-16 00:00:00,00:00:00 +193,1970,10,13,Italian Grand Prix,1970-09-06 00:00:00,00:00:00 +194,1970,11,51,Canadian Grand Prix,1970-09-20 00:00:00,00:00:00 +195,1970,12,45,United States Grand Prix,1970-10-04 00:00:00,00:00:00 +196,1970,13,31,Mexican Grand Prix,1970-10-25 00:00:00,00:00:00 +197,1971,1,29,South African Grand Prix,1971-03-06 00:00:00,00:00:00 +198,1971,2,48,Spanish Grand Prix,1971-04-18 00:00:00,00:00:00 +199,1971,3,5,Monaco Grand Prix,1971-05-23 00:00:00,00:00:00 +200,1971,4,38,Dutch Grand Prix,1971-06-20 00:00:00,00:00:00 +201,1971,5,33,French Grand Prix,1971-07-04 00:00:00,00:00:00 +202,1971,6,8,British Grand Prix,1971-07-17 00:00:00,00:00:00 +203,1971,7,19,German Grand Prix,1971-08-01 00:00:00,00:00:00 +204,1971,8,69,Austrian Grand Prix,1971-08-15 00:00:00,00:00:00 +205,1971,9,13,Italian Grand Prix,1971-09-05 00:00:00,00:00:00 +206,1971,10,47,Canadian Grand Prix,1971-09-19 00:00:00,00:00:00 +207,1971,11,45,United States Grand Prix,1971-10-03 00:00:00,00:00:00 +208,1972,1,24,Argentine Grand Prix,1972-01-23 00:00:00,00:00:00 +209,1972,2,29,South African Grand Prix,1972-03-04 00:00:00,00:00:00 +210,1972,3,44,Spanish Grand Prix,1972-05-01 00:00:00,00:00:00 +211,1972,4,5,Monaco Grand Prix,1972-05-14 00:00:00,00:00:00 +212,1972,5,49,Belgian Grand Prix,1972-06-04 00:00:00,00:00:00 +213,1972,6,50,French Grand Prix,1972-07-02 00:00:00,00:00:00 +214,1972,7,37,British Grand Prix,1972-07-15 00:00:00,00:00:00 +215,1972,8,19,German Grand Prix,1972-07-30 00:00:00,00:00:00 +216,1972,9,69,Austrian Grand Prix,1972-08-13 00:00:00,00:00:00 +217,1972,10,13,Italian Grand Prix,1972-09-10 00:00:00,00:00:00 +218,1972,11,47,Canadian Grand Prix,1972-09-24 00:00:00,00:00:00 +219,1972,12,45,United States Grand Prix,1972-10-08 00:00:00,00:00:00 +220,1973,1,24,Argentine Grand Prix,1973-01-28 00:00:00,00:00:00 +221,1973,2,17,Brazilian Grand Prix,1973-02-11 00:00:00,00:00:00 +222,1973,3,29,South African Grand Prix,1973-03-03 00:00:00,00:00:00 +223,1973,4,48,Spanish Grand Prix,1973-04-29 00:00:00,00:00:00 +224,1973,5,39,Belgian Grand Prix,1973-05-20 00:00:00,00:00:00 +225,1973,6,5,Monaco Grand Prix,1973-06-03 00:00:00,00:00:00 +226,1973,7,46,Swedish Grand Prix,1973-06-17 00:00:00,00:00:00 +227,1973,8,33,French Grand Prix,1973-07-01 00:00:00,00:00:00 +228,1973,9,8,British Grand Prix,1973-07-14 00:00:00,00:00:00 +229,1973,10,38,Dutch Grand Prix,1973-07-29 00:00:00,00:00:00 +230,1973,11,19,German Grand Prix,1973-08-05 00:00:00,00:00:00 +231,1973,12,69,Austrian Grand Prix,1973-08-19 00:00:00,00:00:00 +232,1973,13,13,Italian Grand Prix,1973-09-09 00:00:00,00:00:00 +233,1973,14,47,Canadian Grand Prix,1973-09-23 00:00:00,00:00:00 +234,1973,15,45,United States Grand Prix,1973-10-07 00:00:00,00:00:00 +235,1974,1,24,Argentine Grand Prix,1974-01-13 00:00:00,00:00:00 +236,1974,2,17,Brazilian Grand Prix,1974-01-27 00:00:00,00:00:00 +237,1974,3,29,South African Grand Prix,1974-03-30 00:00:00,00:00:00 +238,1974,4,44,Spanish Grand Prix,1974-04-28 00:00:00,00:00:00 +239,1974,5,49,Belgian Grand Prix,1974-05-12 00:00:00,00:00:00 +240,1974,6,5,Monaco Grand Prix,1974-05-26 00:00:00,00:00:00 +241,1974,7,46,Swedish Grand Prix,1974-06-09 00:00:00,00:00:00 +242,1974,8,38,Dutch Grand Prix,1974-06-23 00:00:00,00:00:00 +243,1974,9,40,French Grand Prix,1974-07-07 00:00:00,00:00:00 +244,1974,10,37,British Grand Prix,1974-07-20 00:00:00,00:00:00 +245,1974,11,19,German Grand Prix,1974-08-04 00:00:00,00:00:00 +246,1974,12,69,Austrian Grand Prix,1974-08-18 00:00:00,00:00:00 +247,1974,13,13,Italian Grand Prix,1974-09-08 00:00:00,00:00:00 +248,1974,14,47,Canadian Grand Prix,1974-09-22 00:00:00,00:00:00 +249,1974,15,45,United States Grand Prix,1974-10-06 00:00:00,00:00:00 +250,1975,1,24,Argentine Grand Prix,1975-01-12 00:00:00,00:00:00 +251,1975,2,17,Brazilian Grand Prix,1975-01-26 00:00:00,00:00:00 +252,1975,3,29,South African Grand Prix,1975-03-01 00:00:00,00:00:00 +253,1975,4,48,Spanish Grand Prix,1975-04-27 00:00:00,00:00:00 +254,1975,5,5,Monaco Grand Prix,1975-05-11 00:00:00,00:00:00 +255,1975,6,39,Belgian Grand Prix,1975-05-25 00:00:00,00:00:00 +256,1975,7,46,Swedish Grand Prix,1975-06-08 00:00:00,00:00:00 +257,1975,8,38,Dutch Grand Prix,1975-06-22 00:00:00,00:00:00 +258,1975,9,33,French Grand Prix,1975-07-06 00:00:00,00:00:00 +259,1975,10,8,British Grand Prix,1975-07-19 00:00:00,00:00:00 +260,1975,11,19,German Grand Prix,1975-08-03 00:00:00,00:00:00 +261,1975,12,69,Austrian Grand Prix,1975-08-17 00:00:00,00:00:00 +262,1975,13,13,Italian Grand Prix,1975-09-07 00:00:00,00:00:00 +263,1975,14,45,United States Grand Prix,1975-10-05 00:00:00,00:00:00 +264,1976,1,17,Brazilian Grand Prix,1976-01-25 00:00:00,00:00:00 +265,1976,2,29,South African Grand Prix,1976-03-06 00:00:00,00:00:00 +266,1976,3,42,United States Grand Prix West,1976-03-28 00:00:00,00:00:00 +267,1976,4,44,Spanish Grand Prix,1976-05-02 00:00:00,00:00:00 +268,1976,5,39,Belgian Grand Prix,1976-05-16 00:00:00,00:00:00 +269,1976,6,5,Monaco Grand Prix,1976-05-30 00:00:00,00:00:00 +270,1976,7,46,Swedish Grand Prix,1976-06-13 00:00:00,00:00:00 +271,1976,8,33,French Grand Prix,1976-07-04 00:00:00,00:00:00 +272,1976,9,37,British Grand Prix,1976-07-18 00:00:00,00:00:00 +273,1976,10,19,German Grand Prix,1976-08-01 00:00:00,00:00:00 +274,1976,11,69,Austrian Grand Prix,1976-08-15 00:00:00,00:00:00 +275,1976,12,38,Dutch Grand Prix,1976-08-29 00:00:00,00:00:00 +276,1976,13,13,Italian Grand Prix,1976-09-12 00:00:00,00:00:00 +277,1976,14,47,Canadian Grand Prix,1976-10-03 00:00:00,00:00:00 +278,1976,15,45,United States Grand Prix,1976-10-10 00:00:00,00:00:00 +279,1976,16,15,Japanese Grand Prix,1976-10-24 00:00:00,00:00:00 +280,1977,1,24,Argentine Grand Prix,1977-01-09 00:00:00,00:00:00 +281,1977,2,17,Brazilian Grand Prix,1977-01-23 00:00:00,00:00:00 +282,1977,3,29,South African Grand Prix,1977-03-05 00:00:00,00:00:00 +283,1977,4,42,United States Grand Prix West,1977-04-03 00:00:00,00:00:00 +284,1977,5,44,Spanish Grand Prix,1977-05-08 00:00:00,00:00:00 +285,1977,6,5,Monaco Grand Prix,1977-05-22 00:00:00,00:00:00 +286,1977,7,39,Belgian Grand Prix,1977-06-05 00:00:00,00:00:00 +287,1977,8,46,Swedish Grand Prix,1977-06-19 00:00:00,00:00:00 +288,1977,9,40,French Grand Prix,1977-07-03 00:00:00,00:00:00 +289,1977,10,8,British Grand Prix,1977-07-16 00:00:00,00:00:00 +290,1977,11,9,German Grand Prix,1977-07-31 00:00:00,00:00:00 +291,1977,12,69,Austrian Grand Prix,1977-08-14 00:00:00,00:00:00 +292,1977,13,38,Dutch Grand Prix,1977-08-28 00:00:00,00:00:00 +293,1977,14,13,Italian Grand Prix,1977-09-11 00:00:00,00:00:00 +294,1977,15,45,United States Grand Prix,1977-10-02 00:00:00,00:00:00 +295,1977,16,47,Canadian Grand Prix,1977-10-09 00:00:00,00:00:00 +296,1977,17,15,Japanese Grand Prix,1977-10-23 00:00:00,00:00:00 +297,1978,1,24,Argentine Grand Prix,1978-01-15 00:00:00,00:00:00 +298,1978,2,35,Brazilian Grand Prix,1978-01-29 00:00:00,00:00:00 +299,1978,3,29,South African Grand Prix,1978-03-04 00:00:00,00:00:00 +300,1978,4,42,United States Grand Prix West,1978-04-02 00:00:00,00:00:00 +301,1978,5,5,Monaco Grand Prix,1978-05-07 00:00:00,00:00:00 +302,1978,6,39,Belgian Grand Prix,1978-05-21 00:00:00,00:00:00 +303,1978,7,44,Spanish Grand Prix,1978-06-04 00:00:00,00:00:00 +304,1978,8,46,Swedish Grand Prix,1978-06-17 00:00:00,00:00:00 +305,1978,9,33,French Grand Prix,1978-07-02 00:00:00,00:00:00 +306,1978,10,37,British Grand Prix,1978-07-16 00:00:00,00:00:00 +307,1978,11,9,German Grand Prix,1978-07-30 00:00:00,00:00:00 +308,1978,12,69,Austrian Grand Prix,1978-08-13 00:00:00,00:00:00 +309,1978,13,38,Dutch Grand Prix,1978-08-27 00:00:00,00:00:00 +310,1978,14,13,Italian Grand Prix,1978-09-10 00:00:00,00:00:00 +311,1978,15,45,United States Grand Prix,1978-10-01 00:00:00,00:00:00 +312,1978,16,6,Canadian Grand Prix,1978-10-08 00:00:00,00:00:00 +313,1979,1,24,Argentine Grand Prix,1979-01-21 00:00:00,00:00:00 +314,1979,2,17,Brazilian Grand Prix,1979-02-04 00:00:00,00:00:00 +315,1979,3,29,South African Grand Prix,1979-03-03 00:00:00,00:00:00 +316,1979,4,42,United States Grand Prix West,1979-04-08 00:00:00,00:00:00 +317,1979,5,44,Spanish Grand Prix,1979-04-29 00:00:00,00:00:00 +318,1979,6,39,Belgian Grand Prix,1979-05-13 00:00:00,00:00:00 +319,1979,7,5,Monaco Grand Prix,1979-05-27 00:00:00,00:00:00 +320,1979,8,40,French Grand Prix,1979-07-01 00:00:00,00:00:00 +321,1979,9,8,British Grand Prix,1979-07-14 00:00:00,00:00:00 +322,1979,10,9,German Grand Prix,1979-07-29 00:00:00,00:00:00 +323,1979,11,69,Austrian Grand Prix,1979-08-12 00:00:00,00:00:00 +324,1979,12,38,Dutch Grand Prix,1979-08-26 00:00:00,00:00:00 +325,1979,13,13,Italian Grand Prix,1979-09-09 00:00:00,00:00:00 +326,1979,14,6,Canadian Grand Prix,1979-09-30 00:00:00,00:00:00 +327,1979,15,45,United States Grand Prix,1979-10-07 00:00:00,00:00:00 +328,1980,1,24,Argentine Grand Prix,1980-01-13 00:00:00,00:00:00 +329,1980,2,17,Brazilian Grand Prix,1980-01-27 00:00:00,00:00:00 +330,1980,3,29,South African Grand Prix,1980-03-01 00:00:00,00:00:00 +331,1980,4,42,United States Grand Prix West,1980-03-30 00:00:00,00:00:00 +332,1980,5,39,Belgian Grand Prix,1980-05-04 00:00:00,00:00:00 +333,1980,6,5,Monaco Grand Prix,1980-05-18 00:00:00,00:00:00 +334,1980,7,33,French Grand Prix,1980-06-29 00:00:00,00:00:00 +335,1980,8,37,British Grand Prix,1980-07-13 00:00:00,00:00:00 +336,1980,9,9,German Grand Prix,1980-08-10 00:00:00,00:00:00 +337,1980,10,69,Austrian Grand Prix,1980-08-17 00:00:00,00:00:00 +338,1980,11,38,Dutch Grand Prix,1980-08-31 00:00:00,00:00:00 +339,1980,12,20,Italian Grand Prix,1980-09-14 00:00:00,00:00:00 +340,1980,13,6,Canadian Grand Prix,1980-09-28 00:00:00,00:00:00 +341,1980,14,45,United States Grand Prix,1980-10-05 00:00:00,00:00:00 +342,1981,1,42,United States Grand Prix West,1981-03-15 00:00:00,00:00:00 +343,1981,2,35,Brazilian Grand Prix,1981-03-29 00:00:00,00:00:00 +344,1981,3,24,Argentine Grand Prix,1981-04-12 00:00:00,00:00:00 +345,1981,4,20,San Marino Grand Prix,1981-05-03 00:00:00,00:00:00 +346,1981,5,39,Belgian Grand Prix,1981-05-17 00:00:00,00:00:00 +347,1981,6,5,Monaco Grand Prix,1981-05-31 00:00:00,00:00:00 +348,1981,7,44,Spanish Grand Prix,1981-06-21 00:00:00,00:00:00 +349,1981,8,40,French Grand Prix,1981-07-05 00:00:00,00:00:00 +350,1981,9,8,British Grand Prix,1981-07-18 00:00:00,00:00:00 +351,1981,10,9,German Grand Prix,1981-08-02 00:00:00,00:00:00 +352,1981,11,69,Austrian Grand Prix,1981-08-16 00:00:00,00:00:00 +353,1981,12,38,Dutch Grand Prix,1981-08-30 00:00:00,00:00:00 +354,1981,13,13,Italian Grand Prix,1981-09-13 00:00:00,00:00:00 +355,1981,14,6,Canadian Grand Prix,1981-09-27 00:00:00,00:00:00 +356,1981,15,43,Caesars Palace Grand Prix,1981-10-17 00:00:00,00:00:00 +357,1982,1,29,South African Grand Prix,1982-01-23 00:00:00,00:00:00 +358,1982,2,35,Brazilian Grand Prix,1982-03-21 00:00:00,00:00:00 +359,1982,3,42,United States Grand Prix West,1982-04-04 00:00:00,00:00:00 +360,1982,4,20,San Marino Grand Prix,1982-04-25 00:00:00,00:00:00 +361,1982,5,39,Belgian Grand Prix,1982-05-09 00:00:00,00:00:00 +362,1982,6,5,Monaco Grand Prix,1982-05-23 00:00:00,00:00:00 +363,1982,7,36,Detroit Grand Prix,1982-06-06 00:00:00,00:00:00 +364,1982,8,6,Canadian Grand Prix,1982-06-13 00:00:00,00:00:00 +365,1982,9,38,Dutch Grand Prix,1982-07-03 00:00:00,00:00:00 +366,1982,10,37,British Grand Prix,1982-07-18 00:00:00,00:00:00 +367,1982,11,33,French Grand Prix,1982-07-25 00:00:00,00:00:00 +368,1982,12,9,German Grand Prix,1982-08-08 00:00:00,00:00:00 +369,1982,13,69,Austrian Grand Prix,1982-08-15 00:00:00,00:00:00 +370,1982,14,40,Swiss Grand Prix,1982-08-29 00:00:00,00:00:00 +371,1982,15,13,Italian Grand Prix,1982-09-12 00:00:00,00:00:00 +372,1982,16,43,Caesars Palace Grand Prix,1982-09-25 00:00:00,00:00:00 +373,1983,1,35,Brazilian Grand Prix,1983-03-13 00:00:00,00:00:00 +374,1983,2,42,United States Grand Prix West,1983-03-27 00:00:00,00:00:00 +375,1983,3,33,French Grand Prix,1983-04-17 00:00:00,00:00:00 +376,1983,4,20,San Marino Grand Prix,1983-05-01 00:00:00,00:00:00 +377,1983,5,5,Monaco Grand Prix,1983-05-15 00:00:00,00:00:00 +378,1983,6,12,Belgian Grand Prix,1983-05-22 00:00:00,00:00:00 +379,1983,7,36,Detroit Grand Prix,1983-06-05 00:00:00,00:00:00 +380,1983,8,6,Canadian Grand Prix,1983-06-12 00:00:00,00:00:00 +381,1983,9,8,British Grand Prix,1983-07-16 00:00:00,00:00:00 +382,1983,10,9,German Grand Prix,1983-08-07 00:00:00,00:00:00 +383,1983,11,69,Austrian Grand Prix,1983-08-14 00:00:00,00:00:00 +384,1983,12,38,Dutch Grand Prix,1983-08-28 00:00:00,00:00:00 +385,1983,13,13,Italian Grand Prix,1983-09-11 00:00:00,00:00:00 +386,1983,14,37,European Grand Prix,1983-09-25 00:00:00,00:00:00 +387,1983,15,29,South African Grand Prix,1983-10-15 00:00:00,00:00:00 +388,1984,1,35,Brazilian Grand Prix,1984-03-25 00:00:00,00:00:00 +389,1984,2,29,South African Grand Prix,1984-04-07 00:00:00,00:00:00 +390,1984,3,39,Belgian Grand Prix,1984-04-29 00:00:00,00:00:00 +391,1984,4,20,San Marino Grand Prix,1984-05-06 00:00:00,00:00:00 +392,1984,5,40,French Grand Prix,1984-05-20 00:00:00,00:00:00 +393,1984,6,5,Monaco Grand Prix,1984-06-03 00:00:00,00:00:00 +394,1984,7,6,Canadian Grand Prix,1984-06-17 00:00:00,00:00:00 +395,1984,8,36,Detroit Grand Prix,1984-06-24 00:00:00,00:00:00 +396,1984,9,41,Dallas Grand Prix,1984-07-08 00:00:00,00:00:00 +397,1984,10,37,British Grand Prix,1984-07-22 00:00:00,00:00:00 +398,1984,11,9,German Grand Prix,1984-08-05 00:00:00,00:00:00 +399,1984,12,69,Austrian Grand Prix,1984-08-19 00:00:00,00:00:00 +400,1984,13,38,Dutch Grand Prix,1984-08-26 00:00:00,00:00:00 +401,1984,14,13,Italian Grand Prix,1984-09-09 00:00:00,00:00:00 +402,1984,15,19,European Grand Prix,1984-10-07 00:00:00,00:00:00 +403,1984,16,26,Portuguese Grand Prix,1984-10-21 00:00:00,00:00:00 +404,1985,1,35,Brazilian Grand Prix,1985-04-07 00:00:00,00:00:00 +405,1985,2,26,Portuguese Grand Prix,1985-04-21 00:00:00,00:00:00 +406,1985,3,20,San Marino Grand Prix,1985-05-05 00:00:00,00:00:00 +407,1985,4,5,Monaco Grand Prix,1985-05-19 00:00:00,00:00:00 +408,1985,5,6,Canadian Grand Prix,1985-06-16 00:00:00,00:00:00 +409,1985,6,36,Detroit Grand Prix,1985-06-23 00:00:00,00:00:00 +410,1985,7,33,French Grand Prix,1985-07-07 00:00:00,00:00:00 +411,1985,8,8,British Grand Prix,1985-07-21 00:00:00,00:00:00 +412,1985,9,19,German Grand Prix,1985-08-04 00:00:00,00:00:00 +413,1985,10,69,Austrian Grand Prix,1985-08-18 00:00:00,00:00:00 +414,1985,11,38,Dutch Grand Prix,1985-08-25 00:00:00,00:00:00 +415,1985,12,13,Italian Grand Prix,1985-09-08 00:00:00,00:00:00 +416,1985,13,12,Belgian Grand Prix,1985-09-15 00:00:00,00:00:00 +417,1985,14,37,European Grand Prix,1985-10-06 00:00:00,00:00:00 +418,1985,15,29,South African Grand Prix,1985-10-19 00:00:00,00:00:00 +419,1985,16,28,Australian Grand Prix,1985-11-03 00:00:00,00:00:00 +420,1986,1,35,Brazilian Grand Prix,1986-03-23 00:00:00,00:00:00 +421,1986,2,25,Spanish Grand Prix,1986-04-13 00:00:00,00:00:00 +422,1986,3,20,San Marino Grand Prix,1986-04-27 00:00:00,00:00:00 +423,1986,4,5,Monaco Grand Prix,1986-05-11 00:00:00,00:00:00 +424,1986,5,12,Belgian Grand Prix,1986-05-25 00:00:00,00:00:00 +425,1986,6,6,Canadian Grand Prix,1986-06-15 00:00:00,00:00:00 +426,1986,7,36,Detroit Grand Prix,1986-06-22 00:00:00,00:00:00 +427,1986,8,33,French Grand Prix,1986-07-06 00:00:00,00:00:00 +428,1986,9,37,British Grand Prix,1986-07-13 00:00:00,00:00:00 +429,1986,10,9,German Grand Prix,1986-07-27 00:00:00,00:00:00 +430,1986,11,10,Hungarian Grand Prix,1986-08-10 00:00:00,00:00:00 +431,1986,12,69,Austrian Grand Prix,1986-08-17 00:00:00,00:00:00 +432,1986,13,13,Italian Grand Prix,1986-09-07 00:00:00,00:00:00 +433,1986,14,26,Portuguese Grand Prix,1986-09-21 00:00:00,00:00:00 +434,1986,15,31,Mexican Grand Prix,1986-10-12 00:00:00,00:00:00 +435,1986,16,28,Australian Grand Prix,1986-10-26 00:00:00,00:00:00 +436,1987,1,35,Brazilian Grand Prix,1987-04-12 00:00:00,00:00:00 +437,1987,2,20,San Marino Grand Prix,1987-05-03 00:00:00,00:00:00 +438,1987,3,12,Belgian Grand Prix,1987-05-17 00:00:00,00:00:00 +439,1987,4,5,Monaco Grand Prix,1987-05-31 00:00:00,00:00:00 +440,1987,5,36,Detroit Grand Prix,1987-06-21 00:00:00,00:00:00 +441,1987,6,33,French Grand Prix,1987-07-05 00:00:00,00:00:00 +442,1987,7,8,British Grand Prix,1987-07-12 00:00:00,00:00:00 +443,1987,8,9,German Grand Prix,1987-07-26 00:00:00,00:00:00 +444,1987,9,10,Hungarian Grand Prix,1987-08-09 00:00:00,00:00:00 +445,1987,10,69,Austrian Grand Prix,1987-08-16 00:00:00,00:00:00 +446,1987,11,13,Italian Grand Prix,1987-09-06 00:00:00,00:00:00 +447,1987,12,26,Portuguese Grand Prix,1987-09-20 00:00:00,00:00:00 +448,1987,13,25,Spanish Grand Prix,1987-09-27 00:00:00,00:00:00 +449,1987,14,31,Mexican Grand Prix,1987-10-18 00:00:00,00:00:00 +450,1987,15,21,Japanese Grand Prix,1987-11-01 00:00:00,00:00:00 +451,1987,16,28,Australian Grand Prix,1987-11-15 00:00:00,00:00:00 +452,1988,1,35,Brazilian Grand Prix,1988-04-03 00:00:00,00:00:00 +453,1988,2,20,San Marino Grand Prix,1988-05-01 00:00:00,00:00:00 +454,1988,3,5,Monaco Grand Prix,1988-05-15 00:00:00,00:00:00 +455,1988,4,31,Mexican Grand Prix,1988-05-29 00:00:00,00:00:00 +456,1988,5,6,Canadian Grand Prix,1988-06-12 00:00:00,00:00:00 +457,1988,6,36,Detroit Grand Prix,1988-06-19 00:00:00,00:00:00 +458,1988,7,33,French Grand Prix,1988-07-03 00:00:00,00:00:00 +459,1988,8,8,British Grand Prix,1988-07-10 00:00:00,00:00:00 +460,1988,9,9,German Grand Prix,1988-07-24 00:00:00,00:00:00 +461,1988,10,10,Hungarian Grand Prix,1988-08-07 00:00:00,00:00:00 +462,1988,11,12,Belgian Grand Prix,1988-08-28 00:00:00,00:00:00 +463,1988,12,13,Italian Grand Prix,1988-09-11 00:00:00,00:00:00 +464,1988,13,26,Portuguese Grand Prix,1988-09-25 00:00:00,00:00:00 +465,1988,14,25,Spanish Grand Prix,1988-10-02 00:00:00,00:00:00 +466,1988,15,21,Japanese Grand Prix,1988-10-30 00:00:00,00:00:00 +467,1988,16,28,Australian Grand Prix,1988-11-13 00:00:00,00:00:00 +468,1989,1,35,Brazilian Grand Prix,1989-03-26 00:00:00,00:00:00 +469,1989,2,20,San Marino Grand Prix,1989-04-23 00:00:00,00:00:00 +470,1989,3,5,Monaco Grand Prix,1989-05-07 00:00:00,00:00:00 +471,1989,4,31,Mexican Grand Prix,1989-05-28 00:00:00,00:00:00 +472,1989,5,32,United States Grand Prix,1989-06-04 00:00:00,00:00:00 +473,1989,6,6,Canadian Grand Prix,1989-06-18 00:00:00,00:00:00 +474,1989,7,33,French Grand Prix,1989-07-09 00:00:00,00:00:00 +475,1989,8,8,British Grand Prix,1989-07-16 00:00:00,00:00:00 +476,1989,9,9,German Grand Prix,1989-07-30 00:00:00,00:00:00 +477,1989,10,10,Hungarian Grand Prix,1989-08-13 00:00:00,00:00:00 +478,1989,11,12,Belgian Grand Prix,1989-08-27 00:00:00,00:00:00 +479,1989,12,13,Italian Grand Prix,1989-09-10 00:00:00,00:00:00 +480,1989,13,26,Portuguese Grand Prix,1989-09-24 00:00:00,00:00:00 +481,1989,14,25,Spanish Grand Prix,1989-10-01 00:00:00,00:00:00 +482,1989,15,21,Japanese Grand Prix,1989-10-22 00:00:00,00:00:00 +483,1989,16,28,Australian Grand Prix,1989-11-05 00:00:00,00:00:00 +484,1990,1,32,United States Grand Prix,1990-03-11 00:00:00,00:00:00 +485,1990,2,17,Brazilian Grand Prix,1990-03-25 00:00:00,00:00:00 +486,1990,3,20,San Marino Grand Prix,1990-05-13 00:00:00,00:00:00 +487,1990,4,5,Monaco Grand Prix,1990-05-27 00:00:00,00:00:00 +488,1990,5,6,Canadian Grand Prix,1990-06-10 00:00:00,00:00:00 +489,1990,6,31,Mexican Grand Prix,1990-06-24 00:00:00,00:00:00 +490,1990,7,33,French Grand Prix,1990-07-08 00:00:00,00:00:00 +491,1990,8,8,British Grand Prix,1990-07-15 00:00:00,00:00:00 +492,1990,9,9,German Grand Prix,1990-07-29 00:00:00,00:00:00 +493,1990,10,10,Hungarian Grand Prix,1990-08-12 00:00:00,00:00:00 +494,1990,11,12,Belgian Grand Prix,1990-08-26 00:00:00,00:00:00 +495,1990,12,13,Italian Grand Prix,1990-09-09 00:00:00,00:00:00 +496,1990,13,26,Portuguese Grand Prix,1990-09-23 00:00:00,00:00:00 +497,1990,14,25,Spanish Grand Prix,1990-09-30 00:00:00,00:00:00 +498,1990,15,21,Japanese Grand Prix,1990-10-21 00:00:00,00:00:00 +499,1990,16,28,Australian Grand Prix,1990-11-04 00:00:00,00:00:00 +500,1991,1,32,United States Grand Prix,1991-03-10 00:00:00,00:00:00 +501,1991,2,17,Brazilian Grand Prix,1991-03-24 00:00:00,00:00:00 +502,1991,3,20,San Marino Grand Prix,1991-04-28 00:00:00,00:00:00 +503,1991,4,5,Monaco Grand Prix,1991-05-12 00:00:00,00:00:00 +504,1991,5,6,Canadian Grand Prix,1991-06-02 00:00:00,00:00:00 +505,1991,6,31,Mexican Grand Prix,1991-06-16 00:00:00,00:00:00 +506,1991,7,7,French Grand Prix,1991-07-07 00:00:00,00:00:00 +507,1991,8,8,British Grand Prix,1991-07-14 00:00:00,00:00:00 +508,1991,9,9,German Grand Prix,1991-07-28 00:00:00,00:00:00 +509,1991,10,10,Hungarian Grand Prix,1991-08-11 00:00:00,00:00:00 +510,1991,11,12,Belgian Grand Prix,1991-08-25 00:00:00,00:00:00 +511,1991,12,13,Italian Grand Prix,1991-09-08 00:00:00,00:00:00 +512,1991,13,26,Portuguese Grand Prix,1991-09-22 00:00:00,00:00:00 +513,1991,14,3,Spanish Grand Prix,1991-09-29 00:00:00,00:00:00 +514,1991,15,21,Japanese Grand Prix,1991-10-20 00:00:00,00:00:00 +515,1991,16,28,Australian Grand Prix,1991-11-03 00:00:00,00:00:00 +516,1992,1,29,South African Grand Prix,1992-03-01 00:00:00,00:00:00 +517,1992,2,31,Mexican Grand Prix,1992-03-22 00:00:00,00:00:00 +518,1992,3,17,Brazilian Grand Prix,1992-04-05 00:00:00,00:00:00 +519,1992,4,3,Spanish Grand Prix,1992-05-03 00:00:00,00:00:00 +520,1992,5,20,San Marino Grand Prix,1992-05-17 00:00:00,00:00:00 +521,1992,6,5,Monaco Grand Prix,1992-05-31 00:00:00,00:00:00 +522,1992,7,6,Canadian Grand Prix,1992-06-14 00:00:00,00:00:00 +523,1992,8,7,French Grand Prix,1992-07-05 00:00:00,00:00:00 +524,1992,9,8,British Grand Prix,1992-07-12 00:00:00,00:00:00 +525,1992,10,9,German Grand Prix,1992-07-26 00:00:00,00:00:00 +526,1992,11,10,Hungarian Grand Prix,1992-08-16 00:00:00,00:00:00 +527,1992,12,12,Belgian Grand Prix,1992-08-30 00:00:00,00:00:00 +528,1992,13,13,Italian Grand Prix,1992-09-13 00:00:00,00:00:00 +529,1992,14,26,Portuguese Grand Prix,1992-09-27 00:00:00,00:00:00 +530,1992,15,21,Japanese Grand Prix,1992-10-25 00:00:00,00:00:00 +531,1992,16,28,Australian Grand Prix,1992-11-08 00:00:00,00:00:00 +532,1993,1,29,South African Grand Prix,1993-03-14 00:00:00,00:00:00 +533,1993,2,17,Brazilian Grand Prix,1993-03-28 00:00:00,00:00:00 +534,1993,3,30,European Grand Prix,1993-04-11 00:00:00,00:00:00 +535,1993,4,20,San Marino Grand Prix,1993-04-25 00:00:00,00:00:00 +536,1993,5,3,Spanish Grand Prix,1993-05-09 00:00:00,00:00:00 +537,1993,6,5,Monaco Grand Prix,1993-05-23 00:00:00,00:00:00 +538,1993,7,6,Canadian Grand Prix,1993-06-13 00:00:00,00:00:00 +539,1993,8,7,French Grand Prix,1993-07-04 00:00:00,00:00:00 +540,1993,9,8,British Grand Prix,1993-07-11 00:00:00,00:00:00 +541,1993,10,9,German Grand Prix,1993-07-25 00:00:00,00:00:00 +542,1993,11,10,Hungarian Grand Prix,1993-08-15 00:00:00,00:00:00 +543,1993,12,12,Belgian Grand Prix,1993-08-29 00:00:00,00:00:00 +544,1993,13,13,Italian Grand Prix,1993-09-12 00:00:00,00:00:00 +545,1993,14,26,Portuguese Grand Prix,1993-09-26 00:00:00,00:00:00 +546,1993,15,21,Japanese Grand Prix,1993-10-24 00:00:00,00:00:00 +547,1993,16,28,Australian Grand Prix,1993-11-07 00:00:00,00:00:00 +548,1994,1,17,Brazilian Grand Prix,1994-03-27 00:00:00,00:00:00 +549,1994,2,27,Pacific Grand Prix,1994-04-17 00:00:00,00:00:00 +550,1994,3,20,San Marino Grand Prix,1994-05-01 00:00:00,00:00:00 +551,1994,4,5,Monaco Grand Prix,1994-05-15 00:00:00,00:00:00 +552,1994,5,3,Spanish Grand Prix,1994-05-29 00:00:00,00:00:00 +553,1994,6,6,Canadian Grand Prix,1994-06-12 00:00:00,00:00:00 +554,1994,7,7,French Grand Prix,1994-07-03 00:00:00,00:00:00 +555,1994,8,8,British Grand Prix,1994-07-10 00:00:00,00:00:00 +556,1994,9,9,German Grand Prix,1994-07-31 00:00:00,00:00:00 +557,1994,10,10,Hungarian Grand Prix,1994-08-14 00:00:00,00:00:00 +558,1994,11,12,Belgian Grand Prix,1994-08-28 00:00:00,00:00:00 +559,1994,12,13,Italian Grand Prix,1994-09-11 00:00:00,00:00:00 +560,1994,13,26,Portuguese Grand Prix,1994-09-25 00:00:00,00:00:00 +561,1994,14,25,European Grand Prix,1994-10-16 00:00:00,00:00:00 +562,1994,15,21,Japanese Grand Prix,1994-11-06 00:00:00,00:00:00 +563,1994,16,28,Australian Grand Prix,1994-11-13 00:00:00,00:00:00 +564,1995,1,17,Brazilian Grand Prix,1995-03-26 00:00:00,00:00:00 +565,1995,2,24,Argentine Grand Prix,1995-04-09 00:00:00,00:00:00 +566,1995,3,20,San Marino Grand Prix,1995-04-30 00:00:00,00:00:00 +567,1995,4,3,Spanish Grand Prix,1995-05-14 00:00:00,00:00:00 +568,1995,5,5,Monaco Grand Prix,1995-05-28 00:00:00,00:00:00 +569,1995,6,6,Canadian Grand Prix,1995-06-11 00:00:00,00:00:00 +570,1995,7,7,French Grand Prix,1995-07-02 00:00:00,00:00:00 +571,1995,8,8,British Grand Prix,1995-07-16 00:00:00,00:00:00 +572,1995,9,9,German Grand Prix,1995-07-30 00:00:00,00:00:00 +573,1995,10,10,Hungarian Grand Prix,1995-08-13 00:00:00,00:00:00 +574,1995,11,12,Belgian Grand Prix,1995-08-27 00:00:00,00:00:00 +575,1995,12,13,Italian Grand Prix,1995-09-10 00:00:00,00:00:00 +576,1995,13,26,Portuguese Grand Prix,1995-09-24 00:00:00,00:00:00 +577,1995,14,19,European Grand Prix,1995-10-01 00:00:00,00:00:00 +578,1995,15,27,Pacific Grand Prix,1995-10-22 00:00:00,00:00:00 +579,1995,16,21,Japanese Grand Prix,1995-10-29 00:00:00,00:00:00 +580,1995,17,28,Australian Grand Prix,1995-11-12 00:00:00,00:00:00 +581,1996,1,0,Australian Grand Prix,1996-03-10 00:00:00,00:00:00 +582,1996,2,17,Brazilian Grand Prix,1996-03-31 00:00:00,00:00:00 +583,1996,3,24,Argentine Grand Prix,1996-04-07 00:00:00,00:00:00 +584,1996,4,19,European Grand Prix,1996-04-28 00:00:00,00:00:00 +585,1996,5,20,San Marino Grand Prix,1996-05-05 00:00:00,00:00:00 +586,1996,6,5,Monaco Grand Prix,1996-05-19 00:00:00,00:00:00 +587,1996,7,3,Spanish Grand Prix,1996-06-02 00:00:00,00:00:00 +588,1996,8,6,Canadian Grand Prix,1996-06-16 00:00:00,00:00:00 +589,1996,9,7,French Grand Prix,1996-06-30 00:00:00,00:00:00 +590,1996,10,8,British Grand Prix,1996-07-14 00:00:00,00:00:00 +591,1996,11,9,German Grand Prix,1996-07-28 00:00:00,00:00:00 +592,1996,12,10,Hungarian Grand Prix,1996-08-11 00:00:00,00:00:00 +593,1996,13,12,Belgian Grand Prix,1996-08-25 00:00:00,00:00:00 +594,1996,14,13,Italian Grand Prix,1996-09-08 00:00:00,00:00:00 +595,1996,15,26,Portuguese Grand Prix,1996-09-22 00:00:00,00:00:00 +596,1996,16,21,Japanese Grand Prix,1996-10-13 00:00:00,00:00:00 +597,1997,1,0,Australian Grand Prix,1997-03-09 00:00:00,00:00:00 +598,1997,2,17,Brazilian Grand Prix,1997-03-30 00:00:00,00:00:00 +599,1997,3,24,Argentine Grand Prix,1997-04-13 00:00:00,00:00:00 +600,1997,4,20,San Marino Grand Prix,1997-04-27 00:00:00,00:00:00 +601,1997,5,5,Monaco Grand Prix,1997-05-11 00:00:00,00:00:00 +602,1997,6,3,Spanish Grand Prix,1997-05-25 00:00:00,00:00:00 +603,1997,7,6,Canadian Grand Prix,1997-06-15 00:00:00,00:00:00 +604,1997,8,7,French Grand Prix,1997-06-29 00:00:00,00:00:00 +605,1997,9,8,British Grand Prix,1997-07-13 00:00:00,00:00:00 +606,1997,10,9,German Grand Prix,1997-07-27 00:00:00,00:00:00 +607,1997,11,10,Hungarian Grand Prix,1997-08-10 00:00:00,00:00:00 +608,1997,12,12,Belgian Grand Prix,1997-08-24 00:00:00,00:00:00 +609,1997,13,13,Italian Grand Prix,1997-09-07 00:00:00,00:00:00 +610,1997,14,69,Austrian Grand Prix,1997-09-21 00:00:00,00:00:00 +611,1997,15,19,Luxembourg Grand Prix,1997-09-28 00:00:00,00:00:00 +612,1997,16,21,Japanese Grand Prix,1997-10-12 00:00:00,00:00:00 +613,1997,17,25,European Grand Prix,1997-10-26 00:00:00,00:00:00 +614,1998,1,0,Australian Grand Prix,1998-03-08 00:00:00,00:00:00 +615,1998,2,17,Brazilian Grand Prix,1998-03-29 00:00:00,00:00:00 +616,1998,3,24,Argentine Grand Prix,1998-04-12 00:00:00,00:00:00 +617,1998,4,20,San Marino Grand Prix,1998-04-26 00:00:00,00:00:00 +618,1998,5,3,Spanish Grand Prix,1998-05-10 00:00:00,00:00:00 +619,1998,6,5,Monaco Grand Prix,1998-05-24 00:00:00,00:00:00 +620,1998,7,6,Canadian Grand Prix,1998-06-07 00:00:00,00:00:00 +621,1998,8,7,French Grand Prix,1998-06-28 00:00:00,00:00:00 +622,1998,9,8,British Grand Prix,1998-07-12 00:00:00,00:00:00 +623,1998,10,69,Austrian Grand Prix,1998-07-26 00:00:00,00:00:00 +624,1998,11,9,German Grand Prix,1998-08-02 00:00:00,00:00:00 +625,1998,12,10,Hungarian Grand Prix,1998-08-16 00:00:00,00:00:00 +626,1998,13,12,Belgian Grand Prix,1998-08-30 00:00:00,00:00:00 +627,1998,14,13,Italian Grand Prix,1998-09-13 00:00:00,00:00:00 +628,1998,15,19,Luxembourg Grand Prix,1998-09-27 00:00:00,00:00:00 +629,1998,16,21,Japanese Grand Prix,1998-11-01 00:00:00,00:00:00 +630,1999,1,0,Australian Grand Prix,1999-03-07 00:00:00,00:00:00 +631,1999,2,17,Brazilian Grand Prix,1999-04-11 00:00:00,00:00:00 +632,1999,3,20,San Marino Grand Prix,1999-05-02 00:00:00,00:00:00 +633,1999,4,5,Monaco Grand Prix,1999-05-16 00:00:00,00:00:00 +634,1999,5,3,Spanish Grand Prix,1999-05-30 00:00:00,00:00:00 +635,1999,6,6,Canadian Grand Prix,1999-06-13 00:00:00,00:00:00 +636,1999,7,7,French Grand Prix,1999-06-27 00:00:00,00:00:00 +637,1999,8,8,British Grand Prix,1999-07-11 00:00:00,00:00:00 +638,1999,9,69,Austrian Grand Prix,1999-07-25 00:00:00,00:00:00 +639,1999,10,9,German Grand Prix,1999-08-01 00:00:00,00:00:00 +640,1999,11,10,Hungarian Grand Prix,1999-08-15 00:00:00,00:00:00 +641,1999,12,12,Belgian Grand Prix,1999-08-29 00:00:00,00:00:00 +642,1999,13,13,Italian Grand Prix,1999-09-12 00:00:00,00:00:00 +643,1999,14,19,European Grand Prix,1999-09-26 00:00:00,00:00:00 +644,1999,15,1,Malaysian Grand Prix,1999-10-17 00:00:00,00:00:00 +645,1999,16,21,Japanese Grand Prix,1999-10-31 00:00:00,00:00:00 +646,2000,1,0,Australian Grand Prix,2000-03-12 00:00:00,00:00:00 +647,2000,2,17,Brazilian Grand Prix,2000-03-26 00:00:00,00:00:00 +648,2000,3,20,San Marino Grand Prix,2000-04-09 00:00:00,00:00:00 +649,2000,4,8,British Grand Prix,2000-04-23 00:00:00,00:00:00 +650,2000,5,3,Spanish Grand Prix,2000-05-07 00:00:00,00:00:00 +651,2000,6,19,European Grand Prix,2000-05-21 00:00:00,00:00:00 +652,2000,7,5,Monaco Grand Prix,2000-06-04 00:00:00,00:00:00 +653,2000,8,6,Canadian Grand Prix,2000-06-18 00:00:00,00:00:00 +654,2000,9,7,French Grand Prix,2000-07-02 00:00:00,00:00:00 +655,2000,10,69,Austrian Grand Prix,2000-07-16 00:00:00,00:00:00 +656,2000,11,9,German Grand Prix,2000-07-30 00:00:00,00:00:00 +657,2000,12,10,Hungarian Grand Prix,2000-08-13 00:00:00,00:00:00 +658,2000,13,12,Belgian Grand Prix,2000-08-27 00:00:00,00:00:00 +659,2000,14,13,Italian Grand Prix,2000-09-10 00:00:00,00:00:00 +660,2000,15,18,United States Grand Prix,2000-09-24 00:00:00,00:00:00 +661,2000,16,21,Japanese Grand Prix,2000-10-08 00:00:00,00:00:00 +662,2000,17,1,Malaysian Grand Prix,2000-10-22 00:00:00,00:00:00 +663,2001,1,0,Australian Grand Prix,2001-03-04 00:00:00,00:00:00 +664,2001,2,1,Malaysian Grand Prix,2001-03-18 00:00:00,00:00:00 +665,2001,3,17,Brazilian Grand Prix,2001-04-01 00:00:00,00:00:00 +666,2001,4,20,San Marino Grand Prix,2001-04-15 00:00:00,00:00:00 +667,2001,5,3,Spanish Grand Prix,2001-04-29 00:00:00,00:00:00 +668,2001,6,69,Austrian Grand Prix,2001-05-13 00:00:00,00:00:00 +669,2001,7,5,Monaco Grand Prix,2001-05-27 00:00:00,00:00:00 +670,2001,8,6,Canadian Grand Prix,2001-06-10 00:00:00,00:00:00 +671,2001,9,19,European Grand Prix,2001-06-24 00:00:00,00:00:00 +672,2001,10,7,French Grand Prix,2001-07-01 00:00:00,00:00:00 +673,2001,11,8,British Grand Prix,2001-07-15 00:00:00,00:00:00 +674,2001,12,9,German Grand Prix,2001-07-29 00:00:00,00:00:00 +675,2001,13,10,Hungarian Grand Prix,2001-08-19 00:00:00,00:00:00 +676,2001,14,12,Belgian Grand Prix,2001-09-02 00:00:00,00:00:00 +677,2001,15,13,Italian Grand Prix,2001-09-16 00:00:00,00:00:00 +678,2001,16,18,United States Grand Prix,2001-09-30 00:00:00,00:00:00 +679,2001,17,21,Japanese Grand Prix,2001-10-14 00:00:00,00:00:00 +680,2002,1,0,Australian Grand Prix,2002-03-03 00:00:00,00:00:00 +681,2002,2,1,Malaysian Grand Prix,2002-03-17 00:00:00,00:00:00 +682,2002,3,17,Brazilian Grand Prix,2002-03-31 00:00:00,00:00:00 +683,2002,4,20,San Marino Grand Prix,2002-04-14 00:00:00,00:00:00 +684,2002,5,3,Spanish Grand Prix,2002-04-28 00:00:00,00:00:00 +685,2002,6,69,Austrian Grand Prix,2002-05-12 00:00:00,00:00:00 +686,2002,7,5,Monaco Grand Prix,2002-05-26 00:00:00,00:00:00 +687,2002,8,6,Canadian Grand Prix,2002-06-09 00:00:00,00:00:00 +688,2002,9,19,European Grand Prix,2002-06-23 00:00:00,00:00:00 +689,2002,10,8,British Grand Prix,2002-07-07 00:00:00,00:00:00 +690,2002,11,7,French Grand Prix,2002-07-21 00:00:00,00:00:00 +691,2002,12,9,German Grand Prix,2002-07-28 00:00:00,00:00:00 +692,2002,13,10,Hungarian Grand Prix,2002-08-18 00:00:00,00:00:00 +693,2002,14,12,Belgian Grand Prix,2002-09-01 00:00:00,00:00:00 +694,2002,15,13,Italian Grand Prix,2002-09-15 00:00:00,00:00:00 +695,2002,16,18,United States Grand Prix,2002-09-29 00:00:00,00:00:00 +696,2002,17,21,Japanese Grand Prix,2002-10-13 00:00:00,00:00:00 +697,2003,1,0,Australian Grand Prix,2003-03-09 00:00:00,00:00:00 +698,2003,2,1,Malaysian Grand Prix,2003-03-23 00:00:00,00:00:00 +699,2003,3,17,Brazilian Grand Prix,2003-04-06 00:00:00,00:00:00 +700,2003,4,20,San Marino Grand Prix,2003-04-20 00:00:00,00:00:00 +701,2003,5,3,Spanish Grand Prix,2003-05-04 00:00:00,00:00:00 +702,2003,6,69,Austrian Grand Prix,2003-05-18 00:00:00,00:00:00 +703,2003,7,5,Monaco Grand Prix,2003-06-01 00:00:00,00:00:00 +704,2003,8,6,Canadian Grand Prix,2003-06-15 00:00:00,00:00:00 +705,2003,9,19,European Grand Prix,2003-06-29 00:00:00,00:00:00 +706,2003,10,7,French Grand Prix,2003-07-06 00:00:00,00:00:00 +707,2003,11,8,British Grand Prix,2003-07-20 00:00:00,00:00:00 +708,2003,12,9,German Grand Prix,2003-08-03 00:00:00,00:00:00 +709,2003,13,10,Hungarian Grand Prix,2003-08-24 00:00:00,00:00:00 +710,2003,14,13,Italian Grand Prix,2003-09-14 00:00:00,00:00:00 +711,2003,15,18,United States Grand Prix,2003-09-28 00:00:00,00:00:00 +712,2003,16,21,Japanese Grand Prix,2003-10-12 00:00:00,00:00:00 +713,2004,1,0,Australian Grand Prix,2004-03-07 00:00:00,00:00:00 +714,2004,2,1,Malaysian Grand Prix,2004-03-21 00:00:00,00:00:00 +715,2004,3,2,Bahrain Grand Prix,2004-04-04 00:00:00,00:00:00 +716,2004,4,20,San Marino Grand Prix,2004-04-25 00:00:00,00:00:00 +717,2004,5,3,Spanish Grand Prix,2004-05-09 00:00:00,00:00:00 +718,2004,6,5,Monaco Grand Prix,2004-05-23 00:00:00,00:00:00 +719,2004,7,19,European Grand Prix,2004-05-30 00:00:00,00:00:00 +720,2004,8,6,Canadian Grand Prix,2004-06-13 00:00:00,00:00:00 +721,2004,9,18,United States Grand Prix,2004-06-20 00:00:00,00:00:00 +722,2004,10,7,French Grand Prix,2004-07-04 00:00:00,00:00:00 +723,2004,11,8,British Grand Prix,2004-07-11 00:00:00,00:00:00 +724,2004,12,9,German Grand Prix,2004-07-25 00:00:00,00:00:00 +725,2004,13,10,Hungarian Grand Prix,2004-08-15 00:00:00,00:00:00 +726,2004,14,12,Belgian Grand Prix,2004-08-29 00:00:00,00:00:00 +727,2004,15,13,Italian Grand Prix,2004-09-12 00:00:00,00:00:00 +728,2004,16,16,Chinese Grand Prix,2004-09-26 00:00:00,00:00:00 +729,2004,17,21,Japanese Grand Prix,2004-10-10 00:00:00,00:00:00 +730,2004,18,17,Brazilian Grand Prix,2004-10-24 00:00:00,00:00:00 +731,2005,1,0,Australian Grand Prix,2005-03-06 14:00:00,14:00:00 +732,2005,2,1,Malaysian Grand Prix,2005-03-20 15:00:00,15:00:00 +733,2005,3,2,Bahrain Grand Prix,2005-04-03 14:30:00,14:30:00 +734,2005,4,20,San Marino Grand Prix,2005-04-24 14:00:00,14:00:00 +735,2005,5,3,Spanish Grand Prix,2005-05-08 14:00:00,14:00:00 +736,2005,6,5,Monaco Grand Prix,2005-05-22 14:00:00,14:00:00 +737,2005,7,19,European Grand Prix,2005-05-29 14:00:00,14:00:00 +738,2005,8,6,Canadian Grand Prix,2005-06-12 13:00:00,13:00:00 +739,2005,9,18,United States Grand Prix,2005-06-19 14:00:00,14:00:00 +740,2005,10,7,French Grand Prix,2005-07-03 14:00:00,14:00:00 +741,2005,11,8,British Grand Prix,2005-07-10 14:00:00,14:00:00 +742,2005,12,9,German Grand Prix,2005-07-24 14:00:00,14:00:00 +743,2005,13,10,Hungarian Grand Prix,2005-07-31 14:00:00,14:00:00 +744,2005,14,4,Turkish Grand Prix,2005-08-21 15:00:00,15:00:00 +745,2005,15,13,Italian Grand Prix,2005-09-04 14:00:00,14:00:00 +746,2005,16,12,Belgian Grand Prix,2005-09-11 14:00:00,14:00:00 +747,2005,17,17,Brazilian Grand Prix,2005-09-25 14:00:00,14:00:00 +748,2005,18,21,Japanese Grand Prix,2005-10-09 14:00:00,14:00:00 +749,2005,19,16,Chinese Grand Prix,2005-10-16 14:00:00,14:00:00 +750,2006,1,2,Bahrain Grand Prix,2006-03-12 14:30:00,14:30:00 +751,2006,2,1,Malaysian Grand Prix,2006-03-19 15:00:00,15:00:00 +752,2006,3,0,Australian Grand Prix,2006-04-02 14:00:00,14:00:00 +753,2006,4,20,San Marino Grand Prix,2006-04-23 14:00:00,14:00:00 +754,2006,5,19,European Grand Prix,2006-05-07 14:00:00,14:00:00 +755,2006,6,3,Spanish Grand Prix,2006-05-14 14:00:00,14:00:00 +756,2006,7,5,Monaco Grand Prix,2006-05-28 14:00:00,14:00:00 +757,2006,8,8,British Grand Prix,2006-06-11 12:00:00,12:00:00 +758,2006,9,6,Canadian Grand Prix,2006-06-25 13:00:00,13:00:00 +759,2006,10,18,United States Grand Prix,2006-07-02 14:00:00,14:00:00 +760,2006,11,7,French Grand Prix,2006-07-16 14:00:00,14:00:00 +761,2006,12,9,German Grand Prix,2006-07-30 14:00:00,14:00:00 +762,2006,13,10,Hungarian Grand Prix,2006-08-06 14:00:00,14:00:00 +763,2006,14,4,Turkish Grand Prix,2006-08-27 15:00:00,15:00:00 +764,2006,15,13,Italian Grand Prix,2006-09-10 14:00:00,14:00:00 +765,2006,16,16,Chinese Grand Prix,2006-10-01 14:00:00,14:00:00 +766,2006,17,21,Japanese Grand Prix,2006-10-08 14:00:00,14:00:00 +767,2006,18,17,Brazilian Grand Prix,2006-10-22 14:00:00,14:00:00 +768,2007,1,0,Australian Grand Prix,2007-03-18 03:00:00,03:00:00 +769,2007,2,1,Malaysian Grand Prix,2007-04-08 07:00:00,07:00:00 +770,2007,3,2,Bahrain Grand Prix,2007-04-15 11:30:00,11:30:00 +771,2007,4,3,Spanish Grand Prix,2007-05-13 12:00:00,12:00:00 +772,2007,5,5,Monaco Grand Prix,2007-05-27 12:00:00,12:00:00 +773,2007,6,6,Canadian Grand Prix,2007-06-10 17:00:00,17:00:00 +774,2007,7,18,United States Grand Prix,2007-06-17 17:00:00,17:00:00 +775,2007,8,7,French Grand Prix,2007-07-01 12:00:00,12:00:00 +776,2007,9,8,British Grand Prix,2007-07-08 12:00:00,12:00:00 +777,2007,10,19,European Grand Prix,2007-07-22 12:00:00,12:00:00 +778,2007,11,10,Hungarian Grand Prix,2007-08-05 12:00:00,12:00:00 +779,2007,12,4,Turkish Grand Prix,2007-08-26 12:00:00,12:00:00 +780,2007,13,13,Italian Grand Prix,2007-09-09 12:00:00,12:00:00 +781,2007,14,12,Belgian Grand Prix,2007-09-16 12:00:00,12:00:00 +782,2007,15,15,Japanese Grand Prix,2007-09-30 04:30:00,04:30:00 +783,2007,16,16,Chinese Grand Prix,2007-10-07 06:00:00,06:00:00 +784,2007,17,17,Brazilian Grand Prix,2007-10-21 16:00:00,16:00:00 +785,2008,1,0,Australian Grand Prix,2008-03-16 04:30:00,04:30:00 +786,2008,2,1,Malaysian Grand Prix,2008-03-23 07:00:00,07:00:00 +787,2008,3,2,Bahrain Grand Prix,2008-04-06 11:30:00,11:30:00 +788,2008,4,3,Spanish Grand Prix,2008-04-27 12:00:00,12:00:00 +789,2008,5,4,Turkish Grand Prix,2008-05-11 12:00:00,12:00:00 +790,2008,6,5,Monaco Grand Prix,2008-05-25 12:00:00,12:00:00 +791,2008,7,6,Canadian Grand Prix,2008-06-08 17:00:00,17:00:00 +792,2008,8,7,French Grand Prix,2008-06-22 12:00:00,12:00:00 +793,2008,9,8,British Grand Prix,2008-07-06 12:00:00,12:00:00 +794,2008,10,9,German Grand Prix,2008-07-20 12:00:00,12:00:00 +795,2008,11,10,Hungarian Grand Prix,2008-08-03 12:00:00,12:00:00 +796,2008,12,11,European Grand Prix,2008-08-24 12:00:00,12:00:00 +797,2008,13,12,Belgian Grand Prix,2008-09-07 12:00:00,12:00:00 +798,2008,14,13,Italian Grand Prix,2008-09-14 12:00:00,12:00:00 +799,2008,15,14,Singapore Grand Prix,2008-09-28 12:00:00,12:00:00 +800,2008,16,15,Japanese Grand Prix,2008-10-12 04:30:00,04:30:00 +801,2008,17,16,Chinese Grand Prix,2008-10-19 07:00:00,07:00:00 +802,2008,18,17,Brazilian Grand Prix,2008-11-02 17:00:00,17:00:00 +803,2009,1,0,Australian Grand Prix,2009-03-29 06:00:00,06:00:00 +804,2009,2,1,Malaysian Grand Prix,2009-04-05 09:00:00,09:00:00 +805,2009,3,16,Chinese Grand Prix,2009-04-19 07:00:00,07:00:00 +806,2009,4,2,Bahrain Grand Prix,2009-04-26 12:00:00,12:00:00 +807,2009,5,3,Spanish Grand Prix,2009-05-10 12:00:00,12:00:00 +808,2009,6,5,Monaco Grand Prix,2009-05-24 12:00:00,12:00:00 +809,2009,7,4,Turkish Grand Prix,2009-06-07 12:00:00,12:00:00 +810,2009,8,8,British Grand Prix,2009-06-21 12:00:00,12:00:00 +811,2009,9,19,German Grand Prix,2009-07-12 12:00:00,12:00:00 +812,2009,10,10,Hungarian Grand Prix,2009-07-26 12:00:00,12:00:00 +813,2009,11,11,European Grand Prix,2009-08-23 12:00:00,12:00:00 +814,2009,12,12,Belgian Grand Prix,2009-08-30 12:00:00,12:00:00 +815,2009,13,13,Italian Grand Prix,2009-09-13 12:00:00,12:00:00 +816,2009,14,14,Singapore Grand Prix,2009-09-27 12:00:00,12:00:00 +817,2009,15,21,Japanese Grand Prix,2009-10-04 05:00:00,05:00:00 +818,2009,16,17,Brazilian Grand Prix,2009-10-18 16:00:00,16:00:00 +819,2009,17,23,Abu Dhabi Grand Prix,2009-11-01 11:00:00,11:00:00 diff --git a/scripts/f1_data/results.csv b/scripts/f1_data/results.csv new file mode 100644 index 00000000..e1131b65 --- /dev/null +++ b/scripts/f1_data/results.csv @@ -0,0 +1,20324 @@ +resultId,raceId,driverId,constructorId,number,grid,position,positionOrder,points,laps,milliseconds,fastestLap,rank,statusId,date +0,0,660,152,18.0,21,11.0,11,0.0,64,,,,16,1950-05-13 +1,0,790,149,8.0,12,,21,0.0,2,,,,126,1950-05-13 +2,0,579,49,1.0,3,,12,0.0,62,,,,44,1950-05-13 +3,0,661,149,9.0,10,,20,0.0,5,,,,6,1950-05-13 +4,0,789,152,17.0,7,,19,0.0,8,,,,51,1950-05-13 +5,0,589,103,19.0,11,,18,0.0,26,,,,8,1950-05-13 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00:00:00 +13744,523,83,21,20.0,7,3.0,3,4.0,69,5961038.0,,,1,1992-07-05 00:00:00 +13745,523,118,2,6.0,2,2.0,2,6.0,69,5934906.0,,,1,1992-07-05 00:00:00 +13746,523,94,2,5.0,1,1.0,1,10.0,69,5888459.0,,,1,1992-07-05 00:00:00 +13747,523,108,34,21.0,17,9.0,9,0.0,67,,,,12,1992-07-05 00:00:00 +13748,523,76,0,2.0,4,,21,0.0,10,,,,5,1992-07-05 00:00:00 +13749,523,29,21,19.0,5,,20,0.0,17,,,,3,1992-07-05 00:00:00 +13750,523,101,0,1.0,3,,23,0.0,0,,,,3,1992-07-05 00:00:00 +13751,523,91,32,29.0,13,,24,0.0,0,,,,3,1992-07-05 00:00:00 +13752,523,129,35,14.0,26,,26,0.0,0,,,,3,1992-07-05 00:00:00 +13753,523,107,36,17.0,0,,27,0.0,0,,,,81,1992-07-05 00:00:00 +13754,523,103,17,23.0,0,,28,0.0,0,,,,81,1992-07-05 00:00:00 +13755,523,127,33,7.0,0,,29,0.0,0,,,,81,1992-07-05 00:00:00 +13756,523,70,33,8.0,0,,30,0.0,0,,,,81,1992-07-05 00:00:00 +13757,523,98,35,15.0,23,,22,0.0,6,,,,37,1992-07-05 00:00:00 +13758,524,54,5,27.0,8,,20,0.0,43,,,,26,1992-07-12 00:00:00 +13759,524,130,16,32.0,23,,21,0.0,43,,,,5,1992-07-12 00:00:00 +13760,524,108,34,21.0,19,13.0,13,0.0,57,,,,12,1992-07-12 00:00:00 +13761,524,134,37,35.0,0,,32,0.0,0,,,,97,1992-07-12 00:00:00 +13762,524,89,37,34.0,0,,31,0.0,0,,,,97,1992-07-12 00:00:00 +13763,524,127,33,7.0,0,,30,0.0,0,,,,54,1992-07-12 00:00:00 +13764,524,129,35,14.0,0,,29,0.0,0,,,,81,1992-07-12 00:00:00 +13765,524,90,36,16.0,21,,25,0.0,27,,,,6,1992-07-12 00:00:00 +13766,524,69,17,23.0,0,,27,0.0,0,,,,81,1992-07-12 00:00:00 +13767,524,78,32,30.0,16,,26,0.0,27,,,,7,1992-07-12 00:00:00 +13768,524,64,31,12.0,7,,24,0.0,31,,,,7,1992-07-12 00:00:00 +13769,524,91,32,29.0,11,,23,0.0,32,,,,36,1992-07-12 00:00:00 +13770,524,126,16,33.0,24,,22,0.0,37,,,,5,1992-07-12 00:00:00 +13771,524,107,36,17.0,0,,28,0.0,0,,,,81,1992-07-12 00:00:00 +13772,524,109,24,4.0,18,,19,0.0,46,,,,20,1992-07-12 00:00:00 +13773,524,87,28,10.0,17,12.0,12,0.0,57,,,,12,1992-07-12 00:00:00 +13774,524,80,17,24.0,25,17.0,17,0.0,53,,,,5,1992-07-12 00:00:00 +13775,524,128,24,3.0,20,11.0,11,0.0,57,,,,12,1992-07-12 00:00:00 +13776,524,122,26,25.0,13,10.0,10,0.0,57,,,,12,1992-07-12 00:00:00 +13777,524,121,5,28.0,14,9.0,9,0.0,58,,,,11,1992-07-12 00:00:00 +13778,524,99,26,26.0,10,8.0,8,0.0,58,,,,11,1992-07-12 00:00:00 +13779,524,104,28,9.0,12,7.0,7,0.0,58,,,,11,1992-07-12 00:00:00 +13780,524,56,31,11.0,9,6.0,6,1.0,59,5223129.0,,,1,1992-07-12 00:00:00 +13781,524,76,0,2.0,5,5.0,5,2.0,59,5198786.0,,,1,1992-07-12 00:00:00 +13782,524,101,0,1.0,3,,18,0.0,52,,,,7,1992-07-12 00:00:00 +13783,524,83,21,20.0,6,3.0,3,4.0,59,5191386.0,,,1,1992-07-12 00:00:00 +13784,524,118,2,6.0,2,2.0,2,6.0,59,5182085.0,,,1,1992-07-12 00:00:00 +13785,524,94,2,5.0,1,1.0,1,10.0,59,5142991.0,,,1,1992-07-12 00:00:00 +13786,524,98,35,15.0,15,14.0,14,0.0,57,,,,12,1992-07-12 00:00:00 +13787,524,93,34,22.0,22,15.0,15,0.0,56,,,,13,1992-07-12 00:00:00 +13788,524,70,33,8.0,26,16.0,16,0.0,55,,,,14,1992-07-12 00:00:00 +13789,524,29,21,19.0,4,4.0,4,3.0,59,5196258.0,,,1,1992-07-12 00:00:00 +13790,525,121,5,28.0,12,,20,0.0,21,,,,5,1992-07-26 00:00:00 +13791,525,56,31,11.0,13,,21,0.0,21,,,,5,1992-07-26 00:00:00 +13792,525,76,0,2.0,4,,22,0.0,16,,,,10,1992-07-26 00:00:00 +13793,525,128,24,3.0,14,,23,0.0,8,,,,5,1992-07-26 00:00:00 +13794,525,78,32,30.0,16,,24,0.0,8,,,,20,1992-07-26 00:00:00 +13795,525,87,28,10.0,15,,25,0.0,1,,,,20,1992-07-26 00:00:00 +13796,525,129,35,14.0,0,,29,0.0,0,,,,81,1992-07-26 00:00:00 +13797,525,130,16,32.0,0,,27,0.0,0,,,,81,1992-07-26 00:00:00 +13798,525,127,33,7.0,0,,28,0.0,0,,,,81,1992-07-26 00:00:00 +13799,525,70,33,8.0,0,,30,0.0,0,,,,81,1992-07-26 00:00:00 +13800,525,89,37,34.0,0,,31,0.0,0,,,,97,1992-07-26 00:00:00 +13801,525,134,37,35.0,0,,32,0.0,0,,,,96,1992-07-26 00:00:00 +13802,525,64,31,12.0,11,,19,0.0,23,,,,5,1992-07-26 00:00:00 +13803,525,69,17,23.0,24,,26,0.0,1,,,,6,1992-07-26 00:00:00 +13804,525,109,24,4.0,20,,18,0.0,25,,,,5,1992-07-26 00:00:00 +13805,525,98,35,15.0,19,,17,0.0,33,,,,5,1992-07-26 00:00:00 +13806,525,90,36,16.0,10,16.0,16,0.0,42,,,,13,1992-07-26 00:00:00 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00:00:00 +16171,622,22,16,10.0,21,6.0,6,1.0,59,,,,11,1998-07-12 00:00:00 +16172,622,20,21,5.0,10,5.0,5,2.0,59,,,,11,1998-07-12 00:00:00 +16173,622,24,21,6.0,11,4.0,4,3.0,59,,,,11,1998-07-12 00:00:00 +16174,622,55,5,4.0,5,3.0,3,4.0,60,6451599.0,,,1,1998-07-12 00:00:00 +16175,622,54,14,14.0,8,,10,0.0,53,,,,10,1998-07-12 00:00:00 +16176,623,20,21,5.0,1,,15,0.0,21,,,,4,1998-07-26 00:00:00 +16177,623,54,14,14.0,2,,16,0.0,21,,,,4,1998-07-26 00:00:00 +16178,623,48,2,2.0,7,,17,0.0,16,,,,5,1998-07-26 00:00:00 +16179,623,43,19,11.0,10,,21,0.0,0,,,,8,1998-07-26 00:00:00 +16180,623,63,20,16.0,13,,19,0.0,3,,,,4,1998-07-26 00:00:00 +16181,623,62,20,17.0,6,,20,0.0,1,,,,4,1998-07-26 00:00:00 +16182,623,67,24,21.0,20,,22,0.0,0,,,,4,1998-07-26 00:00:00 +16183,623,73,17,23.0,19,,14,0.0,30,,,,20,1998-07-26 00:00:00 +16184,623,21,23,18.0,5,,18,0.0,8,,,,23,1998-07-26 00:00:00 +16185,623,49,23,19.0,12,,13,0.0,51,,,,5,1998-07-26 00:00:00 +16186,623,24,21,6.0,17,9.0,9,0.0,70,,,,11,1998-07-26 00:00:00 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00:00:00 +17366,677,55,18,18.0,13,,19,0.0,14,,,,5,2001-09-16 00:00:00 +17367,677,56,0,3.0,7,,18,0.0,19,,,,6,2001-09-16 00:00:00 +17368,677,48,19,22.0,12,,16,0.0,28,,,,6,2001-09-16 00:00:00 +17369,677,61,17,20.0,22,,15,0.0,44,,,,20,2001-09-16 00:00:00 +17370,677,58,20,15.0,18,,14,0.0,46,,,,87,2001-09-16 00:00:00 +17371,677,3,17,21.0,21,13.0,13,0.0,51,,,,12,2001-09-16 00:00:00 +17372,677,49,20,14.0,19,,17,0.0,25,,,,32,2001-09-16 00:00:00 +17373,677,1,14,16.0,8,11.0,11,0.0,52,,,,11,2001-09-16 00:00:00 +17374,677,20,21,7.0,14,10.0,10,0.0,52,,,,11,2001-09-16 00:00:00 +17375,677,43,15,9.0,17,9.0,9,0.0,52,,,,11,2001-09-16 00:00:00 +17376,677,54,16,12.0,16,8.0,8,0.0,52,,,,11,2001-09-16 00:00:00 +17377,677,7,14,17.0,9,7.0,7,0.0,53,4701600.0,,,1,2001-09-16 00:00:00 +17378,677,34,15,10.0,15,6.0,6,1.0,53,4700962.0,,,1,2001-09-16 00:00:00 +17379,677,36,18,19.0,10,5.0,5,2.0,53,4693477.0,,,1,2001-09-16 00:00:00 +17380,677,29,5,1.0,3,4.0,4,3.0,53,4643484.0,,,1,2001-09-16 00:00:00 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00:00:00 +18082,711,48,14,10.0,15,3.0,3,6.0,73,5653961.0,,,1,2003-09-28 00:00:00 +18083,711,14,3,7.0,10,4.0,4,5.0,73,5664326.0,,,1,2003-09-28 00:00:00 +18084,711,49,17,19.0,19,10.0,10,0.0,69,,,,14,2003-09-28 00:00:00 +18085,711,30,2,3.0,4,6.0,6,3.0,72,,,,11,2003-09-28 00:00:00 +18086,711,20,16,11.0,17,7.0,7,2.0,72,,,,11,2003-09-28 00:00:00 +18087,711,50,18,15.0,16,8.0,8,1.0,71,,,,12,2003-09-28 00:00:00 +18088,711,1,14,9.0,13,5.0,5,4.0,73,5672400.0,,,1,2003-09-28 00:00:00 +18089,712,51,16,12.0,15,14.0,14,0.0,51,,,,12,2003-10-12 00:00:00 +18090,712,30,2,3.0,2,,20,0.0,9,,,,9,2003-10-12 00:00:00 +18091,712,48,14,10.0,12,,19,0.0,9,,,,5,2003-10-12 00:00:00 +18092,712,3,3,8.0,5,,18,0.0,17,,,,5,2003-10-12 00:00:00 +18093,712,20,16,11.0,16,,17,0.0,33,,,,60,2003-10-12 00:00:00 +18094,712,52,17,18.0,18,16.0,16,0.0,50,,,,13,2003-10-12 00:00:00 +18095,712,49,17,19.0,17,15.0,15,0.0,51,,,,12,2003-10-12 00:00:00 +18096,712,50,18,15.0,10,13.0,13,0.0,52,,,,11,2003-10-12 00:00:00 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+18111,713,12,14,12.0,11,,15,0.0,44,,11.0,12.0,5,2004-03-07 00:00:00 +18112,713,42,6,16.0,13,12.0,12,0.0,56,,41.0,15.0,12,2004-03-07 00:00:00 +18113,713,45,17,20.0,20,,17,0.0,43,,10.0,19.0,62,2004-03-07 00:00:00 +18114,713,16,18,14.0,6,,18,0.0,29,,15.0,6.0,7,2004-03-07 00:00:00 +18115,713,46,17,21.0,17,,19,0.0,13,,8.0,20.0,10,2004-03-07 00:00:00 +18116,713,1,16,18.0,15,,16,0.0,43,,27.0,13.0,7,2004-03-07 00:00:00 +18117,713,31,18,15.0,19,11.0,11,0.0,56,,6.0,16.0,12,2004-03-07 00:00:00 +18118,713,7,0,6.0,10,,20,0.0,9,,7.0,17.0,5,2004-03-07 00:00:00 +18119,713,10,15,10.0,7,9.0,9,0.0,57,,43.0,8.0,11,2004-03-07 00:00:00 +18120,713,29,5,1.0,1,1.0,1,10.0,58,5055757.0,29.0,1.0,1,2004-03-07 00:00:00 +18121,713,21,5,2.0,2,2.0,2,8.0,58,5069362.0,8.0,2.0,1,2004-03-07 00:00:00 +18122,713,3,3,8.0,5,3.0,3,6.0,58,5090430.0,10.0,3.0,1,2004-03-07 00:00:00 +18123,713,22,2,4.0,8,4.0,4,5.0,58,5116180.0,11.0,5.0,1,2004-03-07 00:00:00 +18124,713,20,14,11.0,14,10.0,10,0.0,57,,39.0,10.0,11,2004-03-07 00:00:00 +18125,713,17,15,9.0,4,6.0,6,3.0,58,5126355.0,24.0,7.0,1,2004-03-07 00:00:00 +18126,713,14,3,7.0,9,7.0,7,2.0,57,,9.0,9.0,11,2004-03-07 00:00:00 +18127,713,13,0,5.0,12,8.0,8,1.0,57,,13.0,11.0,11,2004-03-07 00:00:00 +18128,713,30,2,3.0,3,5.0,5,4.0,58,5124293.0,42.0,4.0,1,2004-03-07 00:00:00 +18129,714,43,6,17.0,14,12.0,12,0.0,55,,23.0,11.0,11,2004-03-21 00:00:00 +18130,714,22,2,4.0,7,,19,0.0,27,,10.0,7.0,5,2004-03-21 00:00:00 +18131,714,1,16,18.0,15,,18,0.0,34,,15.0,17.0,7,2004-03-21 00:00:00 +18132,714,7,0,6.0,5,,17,0.0,40,,12.0,5.0,7,2004-03-21 00:00:00 +18133,714,46,17,21.0,17,16.0,16,0.0,52,,12.0,20.0,14,2004-03-21 00:00:00 +18134,714,10,15,10.0,20,15.0,15,0.0,52,,13.0,8.0,14,2004-03-21 00:00:00 +18135,714,45,17,20.0,16,14.0,14,0.0,53,,11.0,19.0,13,2004-03-21 00:00:00 +18136,714,44,16,19.0,18,13.0,13,0.0,54,,41.0,18.0,12,2004-03-21 00:00:00 +18137,714,20,14,11.0,12,11.0,11,0.0,55,,54.0,14.0,11,2004-03-21 00:00:00 +18138,714,16,18,14.0,2,,20,0.0,23,,9.0,15.0,20,2004-03-21 00:00:00 +18139,714,42,6,16.0,10,9.0,9,0.0,55,,22.0,12.0,11,2004-03-21 00:00:00 +18140,714,29,5,1.0,1,1.0,1,10.0,56,5467490.0,6.0,2.0,1,2004-03-21 00:00:00 +18141,714,30,2,3.0,4,2.0,2,8.0,56,5472512.0,28.0,1.0,1,2004-03-21 00:00:00 +18142,714,17,15,9.0,6,3.0,3,6.0,56,5479058.0,28.0,3.0,1,2004-03-21 00:00:00 +18143,714,21,5,2.0,3,4.0,4,5.0,56,5481105.0,7.0,6.0,1,2004-03-21 00:00:00 +18144,714,31,18,15.0,13,10.0,10,0.0,55,,12.0,16.0,11,2004-03-21 00:00:00 +18145,714,13,0,5.0,9,6.0,6,3.0,56,5520588.0,26.0,9.0,1,2004-03-21 00:00:00 +18146,714,3,3,8.0,19,7.0,7,2.0,56,5535367.0,7.0,10.0,1,2004-03-21 00:00:00 +18147,714,12,14,12.0,11,8.0,8,1.0,55,,7.0,13.0,11,2004-03-21 00:00:00 +18148,714,14,3,7.0,8,5.0,5,4.0,56,5504850.0,12.0,4.0,1,2004-03-21 00:00:00 +18149,715,20,14,11.0,11,11.0,11,0.0,56,,40.0,12.0,11,2004-04-04 00:00:00 +18150,715,46,17,21.0,20,,19,0.0,44,,24.0,19.0,5,2004-04-04 00:00:00 +18151,715,13,0,5.0,10,,18,0.0,50,,19.0,9.0,63,2004-04-04 00:00:00 +18152,715,45,17,20.0,17,17.0,17,0.0,52,,40.0,20.0,15,2004-04-04 00:00:00 +18153,715,44,16,19.0,15,16.0,16,0.0,55,,9.0,18.0,12,2004-04-04 00:00:00 +18154,715,1,16,18.0,18,15.0,15,0.0,56,,56.0,16.0,11,2004-04-04 00:00:00 +18155,715,31,18,15.0,12,14.0,14,0.0,56,,38.0,14.0,11,2004-04-04 00:00:00 +18156,715,30,2,3.0,3,13.0,13,0.0,56,,28.0,6.0,11,2004-04-04 00:00:00 +18157,715,12,14,12.0,13,12.0,12,0.0,56,,44.0,15.0,11,2004-04-04 00:00:00 +18158,715,7,0,6.0,19,,20,0.0,7,,7.0,17.0,5,2004-04-04 00:00:00 +18159,715,42,6,16.0,9,10.0,10,0.0,56,,23.0,11.0,11,2004-04-04 00:00:00 +18160,715,16,18,14.0,14,8.0,8,1.0,56,,19.0,10.0,11,2004-04-04 00:00:00 +18161,715,22,2,4.0,4,7.0,7,2.0,57,5373030.0,56.0,3.0,1,2004-04-04 00:00:00 +18162,715,3,3,8.0,16,6.0,6,3.0,57,5368031.0,39.0,2.0,1,2004-04-04 00:00:00 +18163,715,10,15,10.0,5,5.0,5,4.0,57,5367335.0,55.0,7.0,1,2004-04-04 00:00:00 +18164,715,14,3,7.0,7,4.0,4,5.0,57,5347089.0,24.0,8.0,1,2004-04-04 00:00:00 +18165,715,17,15,9.0,6,3.0,3,6.0,57,5341562.0,24.0,5.0,1,2004-04-04 00:00:00 +18166,715,21,5,2.0,2,2.0,2,8.0,57,5316242.0,29.0,4.0,1,2004-04-04 00:00:00 +18167,715,29,5,1.0,1,1.0,1,10.0,57,5314875.0,7.0,1.0,1,2004-04-04 00:00:00 +18168,715,43,6,17.0,8,9.0,9,0.0,56,,22.0,13.0,11,2004-04-04 00:00:00 +18169,716,16,18,14.0,8,13.0,13,0.0,61,,55.0,13.0,11,2004-04-25 00:00:00 +18170,716,31,18,15.0,14,14.0,14,0.0,60,,27.0,17.0,12,2004-04-25 00:00:00 +18171,716,46,17,21.0,19,15.0,15,0.0,58,,58.0,19.0,14,2004-04-25 00:00:00 +18172,716,10,15,10.0,7,16.0,16,0.0,56,,44.0,8.0,5,2004-04-25 00:00:00 +18173,716,44,16,19.0,15,,20,0.0,6,,6.0,18.0,9,2004-04-25 00:00:00 +18174,716,42,6,16.0,10,,18,0.0,32,,25.0,15.0,3,2004-04-25 00:00:00 +18175,716,45,17,20.0,17,,19,0.0,22,,11.0,20.0,23,2004-04-25 00:00:00 +18176,716,13,0,5.0,11,12.0,12,0.0,61,,42.0,14.0,11,2004-04-25 00:00:00 +18177,716,1,16,18.0,16,,17,0.0,48,,44.0,16.0,30,2004-04-25 00:00:00 +18178,716,43,6,17.0,13,11.0,11,0.0,61,,59.0,11.0,11,2004-04-25 00:00:00 +18179,716,14,3,7.0,9,5.0,5,4.0,62,5215886.0,11.0,4.0,1,2004-04-25 00:00:00 +18180,716,20,14,11.0,18,9.0,9,0.0,61,,60.0,10.0,11,2004-04-25 00:00:00 +18181,716,7,0,6.0,20,8.0,8,1.0,61,,39.0,9.0,11,2004-04-25 00:00:00 +18182,716,22,2,4.0,5,7.0,7,2.0,62,5235400.0,30.0,5.0,1,2004-04-25 00:00:00 +18183,716,21,5,2.0,4,6.0,6,3.0,62,5216353.0,31.0,7.0,1,2004-04-25 00:00:00 +18184,716,12,14,12.0,12,10.0,10,0.0,61,,36.0,12.0,11,2004-04-25 00:00:00 +18185,716,3,3,8.0,6,4.0,4,5.0,62,5203324.0,59.0,3.0,1,2004-04-25 00:00:00 +18186,716,30,2,3.0,3,3.0,3,6.0,62,5201287.0,27.0,6.0,1,2004-04-25 00:00:00 +18187,716,17,15,9.0,1,2.0,2,8.0,62,5189372.0,28.0,2.0,1,2004-04-25 00:00:00 +18188,716,29,5,1.0,2,1.0,1,10.0,62,5179670.0,10.0,1.0,1,2004-04-25 00:00:00 +18189,717,42,6,16.0,11,13.0,13,0.0,65,,29.0,14.0,11,2004-05-09 00:00:00 +18190,717,44,16,19.0,19,,14,0.0,51,,27.0,18.0,38,2004-05-09 00:00:00 +18191,717,30,2,3.0,2,,15,0.0,46,,28.0,7.0,23,2004-05-09 00:00:00 +18192,717,31,18,15.0,16,,16,0.0,43,,18.0,15.0,37,2004-05-09 00:00:00 +18193,717,46,17,21.0,20,,20,0.0,17,,8.0,20.0,20,2004-05-09 00:00:00 +18194,717,1,16,18.0,15,,18,0.0,33,,25.0,12.0,9,2004-05-09 00:00:00 +18195,717,45,17,20.0,18,,19,0.0,31,,3.0,19.0,20,2004-05-09 00:00:00 +18196,717,16,18,14.0,9,12.0,12,0.0,65,,11.0,9.0,11,2004-05-09 00:00:00 +18197,717,43,6,17.0,7,,17,0.0,33,,10.0,17.0,9,2004-05-09 00:00:00 +18198,717,7,0,6.0,13,11.0,11,0.0,65,,48.0,11.0,11,2004-05-09 00:00:00 +18199,717,13,0,5.0,10,10.0,10,0.0,65,,38.0,16.0,11,2004-05-09 00:00:00 +18200,717,12,14,12.0,17,9.0,9,0.0,65,,43.0,10.0,11,2004-05-09 00:00:00 +18201,717,21,5,2.0,5,2.0,2,8.0,66,5266131.0,16.0,5.0,1,2004-05-09 00:00:00 +18202,717,14,3,7.0,4,3.0,3,6.0,66,5285135.0,12.0,6.0,1,2004-05-09 00:00:00 +18203,717,3,3,8.0,8,4.0,4,5.0,66,5285793.0,27.0,3.0,1,2004-05-09 00:00:00 +18204,717,29,5,1.0,1,1.0,1,10.0,66,5252841.0,12.0,1.0,1,2004-05-09 00:00:00 +18205,717,22,2,4.0,6,6.0,6,3.0,66,5326645.0,27.0,8.0,1,2004-05-09 00:00:00 +18206,717,20,14,11.0,12,7.0,7,2.0,66,5329949.0,37.0,13.0,1,2004-05-09 00:00:00 +18207,717,17,15,9.0,14,8.0,8,1.0,65,,46.0,2.0,11,2004-05-09 00:00:00 +18208,717,10,15,10.0,3,5.0,5,4.0,66,5295168.0,47.0,4.0,1,2004-05-09 00:00:00 +18209,718,3,3,8.0,3,,12,0.0,41,,23.0,4.0,3,2004-05-23 00:00:00 +18210,718,20,14,11.0,10,,19,0.0,2,,2.0,16.0,4,2004-05-23 00:00:00 +18211,718,13,0,5.0,8,,18,0.0,2,,2.0,15.0,4,2004-05-23 00:00:00 +18212,718,10,15,10.0,7,,17,0.0,2,,2.0,17.0,5,2004-05-23 00:00:00 +18213,718,16,18,14.0,11,,16,0.0,11,,11.0,11.0,6,2004-05-23 00:00:00 +18214,718,31,18,15.0,14,,20,0.0,0,,,,3,2004-05-23 00:00:00 +18215,718,45,17,20.0,20,,14,0.0,15,,10.0,18.0,6,2004-05-23 00:00:00 +18216,718,7,0,6.0,5,,13,0.0,27,,15.0,7.0,63,2004-05-23 00:00:00 +18217,718,29,5,1.0,4,,11,0.0,45,,23.0,1.0,4,2004-05-23 00:00:00 +18218,718,44,16,19.0,18,,15,0.0,12,,10.0,14.0,7,2004-05-23 00:00:00 +18219,718,46,17,21.0,19,9.0,9,0.0,71,,2.0,19.0,16,2004-05-23 00:00:00 +18220,718,43,6,17.0,13,8.0,8,1.0,74,,57.0,9.0,13,2004-05-23 00:00:00 +18221,718,1,16,18.0,17,7.0,7,2.0,75,,35.0,13.0,12,2004-05-23 00:00:00 +18222,718,42,6,16.0,15,6.0,6,3.0,76,,22.0,8.0,11,2004-05-23 00:00:00 +18223,718,12,14,12.0,16,5.0,5,4.0,76,,23.0,10.0,11,2004-05-23 00:00:00 +18224,718,30,2,3.0,9,4.0,4,5.0,76,,41.0,5.0,11,2004-05-23 00:00:00 +18225,718,21,5,2.0,6,3.0,3,6.0,77,6422367.0,16.0,6.0,1,2004-05-23 00:00:00 +18226,718,17,15,9.0,2,2.0,2,8.0,77,6347098.0,40.0,3.0,1,2004-05-23 00:00:00 +18227,718,14,3,7.0,1,1.0,1,10.0,77,6346601.0,22.0,2.0,1,2004-05-23 00:00:00 +18228,718,22,2,4.0,12,10.0,10,0.0,69,,18.0,12.0,6,2004-05-23 00:00:00 +18229,719,44,16,19.0,15,13.0,13,0.0,58,,27.0,15.0,12,2004-05-30 00:00:00 +18230,719,45,17,20.0,20,14.0,14,0.0,57,,7.0,18.0,13,2004-05-30 00:00:00 +18231,719,10,15,10.0,2,,16,0.0,47,,11.0,2.0,5,2004-05-30 00:00:00 +18232,719,42,6,16.0,11,,20,0.0,0,,,,4,2004-05-30 00:00:00 +18233,719,7,0,6.0,4,,18,0.0,9,,2.0,9.0,5,2004-05-30 00:00:00 +18234,719,22,2,4.0,9,,19,0.0,0,,,,4,2004-05-30 00:00:00 +18235,719,31,18,15.0,12,12.0,12,0.0,59,,14.0,16.0,11,2004-05-30 00:00:00 +18236,719,13,0,5.0,18,,17,0.0,25,,14.0,12.0,5,2004-05-30 00:00:00 +18237,719,43,6,17.0,10,11.0,11,0.0,59,,12.0,13.0,11,2004-05-30 00:00:00 +18238,719,46,17,21.0,17,15.0,15,0.0,57,,46.0,17.0,13,2004-05-30 00:00:00 +18239,719,12,14,12.0,16,9.0,9,0.0,59,,37.0,14.0,11,2004-05-30 00:00:00 +18240,719,1,16,18.0,13,10.0,10,0.0,59,,55.0,11.0,11,2004-05-30 00:00:00 +18241,719,21,5,2.0,7,2.0,2,8.0,60,5573090.0,14.0,3.0,1,2004-05-30 00:00:00 +18242,719,17,15,9.0,5,3.0,3,6.0,60,5577634.0,13.0,4.0,1,2004-05-30 00:00:00 +18243,719,14,3,7.0,3,4.0,4,5.0,60,5608774.0,30.0,6.0,1,2004-05-30 00:00:00 +18244,719,29,5,1.0,1,1.0,1,10.0,60,5555101.0,7.0,1.0,1,2004-05-30 00:00:00 +18245,719,20,14,11.0,19,6.0,6,3.0,60,5628549.0,23.0,7.0,1,2004-05-30 00:00:00 +18246,719,16,18,14.0,14,7.0,7,2.0,60,5631307.0,37.0,10.0,1,2004-05-30 00:00:00 +18247,719,30,2,3.0,8,8.0,8,1.0,59,,43.0,8.0,11,2004-05-30 00:00:00 +18248,719,3,3,8.0,6,5.0,5,4.0,60,5616088.0,29.0,5.0,1,2004-05-30 00:00:00 +18249,720,12,14,12.0,17,,11,0.0,62,,25.0,11.0,3,2004-06-13 00:00:00 +18250,720,30,2,3.0,4,,18,0.0,70,,69.0,6.0,2,2004-06-13 00:00:00 +18251,720,22,2,4.0,1,,17,0.0,70,,70.0,3.0,2,2004-06-13 00:00:00 +18252,720,14,3,7.0,3,,16,0.0,0,,,,7,2004-06-13 00:00:00 +18253,720,16,18,14.0,14,,15,0.0,6,,6.0,17.0,22,2004-06-13 00:00:00 +18254,720,3,3,8.0,5,,13,0.0,44,,41.0,4.0,30,2004-06-13 00:00:00 +18255,720,10,15,10.0,20,,12,0.0,48,,25.0,8.0,5,2004-06-13 00:00:00 +18256,720,46,17,21.0,18,10.0,10,0.0,66,,64.0,18.0,14,2004-06-13 00:00:00 +18257,720,7,0,6.0,8,5.0,5,4.0,69,,44.0,7.0,11,2004-06-13 00:00:00 +18258,720,1,16,18.0,15,8.0,8,1.0,68,,18.0,14.0,12,2004-06-13 00:00:00 +18259,720,9,16,19.0,16,7.0,7,2.0,68,,42.0,16.0,12,2004-06-13 00:00:00 +18260,720,13,0,5.0,9,6.0,6,3.0,69,,55.0,10.0,11,2004-06-13 00:00:00 +18261,720,20,14,11.0,11,4.0,4,5.0,69,,47.0,9.0,11,2004-06-13 00:00:00 +18262,720,17,15,9.0,2,3.0,3,6.0,70,5325212.0,68.0,5.0,1,2004-06-13 00:00:00 +18263,720,21,5,2.0,7,2.0,2,8.0,70,5309911.0,68.0,1.0,1,2004-06-13 00:00:00 +18264,720,29,5,1.0,6,1.0,1,10.0,70,5304803.0,18.0,2.0,1,2004-06-13 00:00:00 +18265,720,42,6,16.0,12,,19,0.0,69,,39.0,12.0,2,2004-06-13 00:00:00 +18266,720,31,18,15.0,10,9.0,9,0.0,67,,45.0,13.0,13,2004-06-13 00:00:00 +18267,720,43,6,17.0,13,,20,0.0,69,,23.0,15.0,2,2004-06-13 00:00:00 +18268,720,45,17,20.0,19,,14,0.0,30,,25.0,19.0,6,2004-06-13 00:00:00 +18269,721,14,3,7.0,20,4.0,4,5.0,73,6064458.0,45.0,6.0,1,2004-06-20 00:00:00 +18270,721,44,16,19.0,17,,19,0.0,0,,,,4,2004-06-20 00:00:00 +18271,721,45,17,20.0,18,,20,0.0,0,,,,4,2004-06-20 00:00:00 +18272,721,3,3,8.0,9,,16,0.0,8,,8.0,7.0,27,2004-06-20 00:00:00 +18273,721,22,2,4.0,6,,15,0.0,9,,8.0,10.0,27,2004-06-20 00:00:00 +18274,721,42,6,16.0,11,,14,0.0,17,,8.0,14.0,6,2004-06-20 00:00:00 +18275,721,17,15,9.0,4,,13,0.0,26,,22.0,5.0,6,2004-06-20 00:00:00 +18276,721,1,16,18.0,16,,12,0.0,40,,37.0,15.0,5,2004-06-20 00:00:00 +18277,721,30,2,3.0,5,,11,0.0,57,,37.0,9.0,2,2004-06-20 00:00:00 +18278,721,16,18,14.0,10,,10,0.0,60,,46.0,12.0,5,2004-06-20 00:00:00 +18279,721,20,14,11.0,14,9.0,9,0.0,65,,44.0,11.0,18,2004-06-20 00:00:00 +18280,721,46,17,21.0,19,8.0,8,1.0,70,,39.0,16.0,13,2004-06-20 00:00:00 +18281,721,13,0,5.0,12,7.0,7,2.0,72,,44.0,13.0,11,2004-06-20 00:00:00 +18282,721,7,0,6.0,7,6.0,6,3.0,72,,59.0,8.0,11,2004-06-20 00:00:00 +18283,721,43,6,17.0,8,5.0,5,4.0,73,6067448.0,46.0,4.0,1,2004-06-20 00:00:00 +18284,721,10,15,10.0,3,3.0,3,6.0,73,6051950.0,47.0,3.0,1,2004-06-20 00:00:00 +18285,721,21,5,2.0,1,2.0,2,8.0,73,6032864.0,7.0,1.0,1,2004-06-20 00:00:00 +18286,721,29,5,1.0,2,1.0,1,10.0,73,6029914.0,8.0,2.0,1,2004-06-20 00:00:00 +18287,721,12,14,12.0,15,,18,0.0,0,,,,4,2004-06-20 00:00:00 +18288,721,31,18,15.0,13,,17,0.0,0,,,,4,2004-06-20 00:00:00 +18289,722,10,15,10.0,7,,20,0.0,15,,14.0,12.0,5,2004-07-04 00:00:00 +18290,722,46,17,21.0,20,,19,0.0,31,,13.0,20.0,20,2004-07-04 00:00:00 +18291,722,45,17,20.0,19,18.0,18,0.0,66,,52.0,19.0,14,2004-07-04 00:00:00 +18292,722,3,3,8.0,1,2.0,2,8.0,70,5426462.0,34.0,2.0,1,2004-07-04 00:00:00 +18293,722,29,5,1.0,2,1.0,1,10.0,70,5418133.0,32.0,1.0,1,2004-07-04 00:00:00 +18294,722,44,16,19.0,18,17.0,17,0.0,67,,15.0,17.0,13,2004-07-04 00:00:00 +18295,722,1,16,18.0,17,16.0,16,0.0,68,,26.0,18.0,12,2004-07-04 00:00:00 +18296,722,43,6,17.0,14,15.0,15,0.0,68,,53.0,15.0,12,2004-07-04 00:00:00 +18297,722,12,14,12.0,16,13.0,13,0.0,69,,23.0,16.0,11,2004-07-04 00:00:00 +18298,722,20,14,11.0,15,12.0,12,0.0,69,,22.0,11.0,11,2004-07-04 00:00:00 +18299,722,31,18,15.0,13,11.0,11,0.0,69,,37.0,13.0,11,2004-07-04 00:00:00 +18300,722,42,6,16.0,11,14.0,14,0.0,69,,49.0,14.0,11,2004-07-04 00:00:00 +18301,722,16,18,14.0,12,9.0,9,0.0,70,5470527.0,53.0,4.0,1,2004-07-04 00:00:00 +18302,722,30,2,3.0,6,8.0,8,1.0,70,5461552.0,48.0,8.0,1,2004-07-04 00:00:00 +18303,722,7,0,6.0,9,7.0,7,2.0,70,5454363.0,30.0,3.0,1,2004-07-04 00:00:00 +18304,722,21,5,2.0,10,3.0,3,6.0,70,5449755.0,50.0,6.0,1,2004-07-04 00:00:00 +18305,722,13,0,5.0,3,6.0,6,3.0,70,5453653.0,11.0,10.0,1,2004-07-04 00:00:00 +18306,722,17,15,9.0,4,5.0,5,4.0,70,5450615.0,50.0,5.0,1,2004-07-04 00:00:00 +18307,722,47,2,4.0,8,10.0,10,0.0,70,5476299.0,56.0,7.0,1,2004-07-04 00:00:00 +18308,722,14,3,7.0,5,4.0,4,5.0,70,5450215.0,15.0,9.0,1,2004-07-04 00:00:00 +18309,723,42,6,16.0,12,13.0,13,0.0,59,,35.0,13.0,11,2004-07-11 00:00:00 +18310,723,31,18,15.0,13,14.0,14,0.0,59,,10.0,15.0,11,2004-07-11 00:00:00 +18311,723,1,16,18.0,15,15.0,15,0.0,59,,17.0,16.0,11,2004-07-11 00:00:00 +18312,723,14,3,7.0,5,,18,0.0,39,,34.0,11.0,3,2004-07-11 00:00:00 +18313,723,44,16,19.0,14,,17,0.0,47,,13.0,17.0,20,2004-07-11 00:00:00 +18314,723,46,17,21.0,19,,19,0.0,29,,12.0,20.0,5,2004-07-11 00:00:00 +18315,723,47,2,4.0,11,12.0,12,0.0,60,5117003.0,58.0,7.0,1,2004-07-11 00:00:00 +18316,723,43,6,17.0,17,,20,0.0,16,,4.0,18.0,3,2004-07-11 00:00:00 +18317,723,45,17,20.0,18,16.0,16,0.0,56,,33.0,19.0,14,2004-07-11 00:00:00 +18318,723,10,15,10.0,8,11.0,11,0.0,60,5116436.0,12.0,14.0,1,2004-07-11 00:00:00 +18319,723,13,0,5.0,6,7.0,7,2.0,60,5102368.0,25.0,10.0,1,2004-07-11 00:00:00 +18320,723,12,14,12.0,10,9.0,9,0.0,60,5106723.0,58.0,9.0,1,2004-07-11 00:00:00 +18321,723,16,18,14.0,9,8.0,8,1.0,60,5106401.0,11.0,12.0,1,2004-07-11 00:00:00 +18322,723,20,14,11.0,20,6.0,6,3.0,60,5095588.0,22.0,5.0,1,2004-07-11 00:00:00 +18323,723,30,2,3.0,7,5.0,5,4.0,60,5094873.0,26.0,6.0,1,2004-07-11 00:00:00 +18324,723,17,15,9.0,3,4.0,4,5.0,60,5093383.0,10.0,3.0,1,2004-07-11 00:00:00 +18325,723,21,5,2.0,2,3.0,3,6.0,60,5085814.0,8.0,2.0,1,2004-07-11 00:00:00 +18326,723,7,0,6.0,1,2.0,2,8.0,60,5084830.0,10.0,4.0,1,2004-07-11 00:00:00 +18327,723,29,5,1.0,4,1.0,1,10.0,60,5082700.0,14.0,1.0,1,2004-07-11 00:00:00 +18328,723,3,3,8.0,16,10.0,10,0.0,60,5107535.0,39.0,8.0,1,2004-07-11 00:00:00 +18329,724,12,14,12.0,16,13.0,13,0.0,65,,61.0,17.0,11,2004-07-25 00:00:00 +18330,724,43,6,17.0,9,14.0,14,0.0,65,,59.0,4.0,11,2004-07-25 00:00:00 +18331,724,44,16,19.0,17,15.0,15,0.0,63,,63.0,16.0,13,2004-07-25 00:00:00 +18332,724,46,17,21.0,20,16.0,16,0.0,62,,18.0,20.0,14,2004-07-25 00:00:00 +18333,724,7,0,6.0,3,,20,0.0,13,,10.0,1.0,65,2004-07-25 00:00:00 +18334,724,1,16,18.0,18,,18,0.0,42,,20.0,18.0,64,2004-07-25 00:00:00 +18335,724,42,6,16.0,15,,19,0.0,38,,20.0,14.0,29,2004-07-25 00:00:00 +18336,724,21,5,2.0,7,12.0,12,0.0,66,5108100.0,59.0,12.0,1,2004-07-25 00:00:00 +18337,724,45,17,20.0,19,17.0,17,0.0,62,,52.0,19.0,14,2004-07-25 00:00:00 +18338,724,14,3,7.0,6,11.0,11,0.0,66,5105106.0,9.0,6.0,1,2004-07-25 00:00:00 +18339,724,30,2,3.0,2,5.0,5,4.0,66,5057903.0,10.0,7.0,1,2004-07-25 00:00:00 +18340,724,20,14,11.0,14,9.0,9,0.0,66,5101950.0,39.0,15.0,1,2004-07-25 00:00:00 +18341,724,17,15,9.0,13,2.0,2,8.0,66,5043236.0,11.0,3.0,1,2004-07-25 00:00:00 +18342,724,3,3,8.0,5,3.0,3,6.0,66,5051199.0,8.0,5.0,1,2004-07-25 00:00:00 +18343,724,13,0,5.0,4,4.0,4,5.0,66,5054079.0,8.0,8.0,1,2004-07-25 00:00:00 +18344,724,29,5,1.0,1,1.0,1,10.0,66,5034848.0,5.0,2.0,1,2004-07-25 00:00:00 +18345,724,16,18,14.0,11,6.0,6,3.0,66,5075956.0,65.0,11.0,1,2004-07-25 00:00:00 +18346,724,41,2,4.0,10,7.0,7,2.0,66,5076804.0,65.0,10.0,1,2004-07-25 00:00:00 +18347,724,10,15,10.0,8,8.0,8,1.0,66,5081690.0,29.0,9.0,1,2004-07-25 00:00:00 +18348,724,31,18,15.0,12,10.0,10,0.0,66,5103426.0,33.0,13.0,1,2004-07-25 00:00:00 +18349,725,1,16,18.0,16,12.0,12,0.0,68,,68.0,13.0,12,2004-08-15 00:00:00 +18350,725,12,14,12.0,20,,19,0.0,21,,14.0,15.0,23,2004-08-15 00:00:00 +18351,725,40,6,16.0,15,,18,0.0,31,,13.0,16.0,40,2004-08-15 00:00:00 +18352,725,14,3,7.0,9,,17,0.0,41,,10.0,6.0,5,2004-08-15 00:00:00 +18353,725,44,16,19.0,17,,16,0.0,48,,43.0,18.0,6,2004-08-15 00:00:00 +18354,725,46,17,21.0,18,15.0,15,0.0,65,,63.0,20.0,15,2004-08-15 00:00:00 +18355,725,45,17,20.0,19,14.0,14,0.0,66,,65.0,19.0,14,2004-08-15 00:00:00 +18356,725,31,18,15.0,14,13.0,13,0.0,68,,45.0,17.0,12,2004-08-15 00:00:00 +18357,725,43,6,17.0,13,11.0,11,0.0,69,,50.0,12.0,11,2004-08-15 00:00:00 +18358,725,7,0,6.0,10,,20,0.0,13,,6.0,14.0,10,2004-08-15 00:00:00 +18359,725,13,0,5.0,12,9.0,9,0.0,69,,67.0,11.0,11,2004-08-15 00:00:00 +18360,725,29,5,1.0,1,1.0,1,10.0,70,5726131.0,29.0,1.0,1,2004-08-15 00:00:00 +18361,725,21,5,2.0,2,2.0,2,8.0,70,5730827.0,29.0,2.0,1,2004-08-15 00:00:00 +18362,725,3,3,8.0,5,3.0,3,6.0,70,5770730.0,49.0,3.0,1,2004-08-15 00:00:00 +18363,725,30,2,3.0,7,4.0,4,5.0,70,5788744.0,49.0,7.0,1,2004-08-15 00:00:00 +18364,725,16,18,14.0,11,10.0,10,0.0,69,,45.0,8.0,11,2004-08-15 00:00:00 +18365,725,10,15,10.0,3,6.0,6,3.0,69,,10.0,10.0,11,2004-08-15 00:00:00 +18366,725,41,2,4.0,6,7.0,7,2.0,69,,48.0,5.0,11,2004-08-15 00:00:00 +18367,725,20,14,11.0,8,8.0,8,1.0,69,,53.0,9.0,11,2004-08-15 00:00:00 +18368,725,17,15,9.0,4,5.0,5,4.0,70,5793570.0,47.0,4.0,1,2004-08-15 00:00:00 +18369,726,1,16,18.0,16,11.0,11,0.0,40,,40.0,15.0,14,2004-08-29 00:00:00 +18370,726,45,17,20.0,17,,19,0.0,0,,,,4,2004-08-29 00:00:00 +18371,726,10,15,10.0,15,,18,0.0,0,,,,4,2004-08-29 00:00:00 +18372,726,16,18,14.0,7,,17,0.0,0,,,,4,2004-08-29 00:00:00 +18373,726,3,3,8.0,3,,16,0.0,11,,9.0,4.0,5,2004-08-29 00:00:00 +18374,726,46,17,21.0,18,,15,0.0,28,,25.0,16.0,4,2004-08-29 00:00:00 +18375,726,17,15,9.0,12,,14,0.0,29,,26.0,10.0,4,2004-08-29 00:00:00 +18376,726,41,2,4.0,14,,13,0.0,31,,26.0,8.0,6,2004-08-29 00:00:00 +18377,726,30,2,3.0,11,,12,0.0,37,,36.0,6.0,27,2004-08-29 00:00:00 +18378,726,44,16,19.0,19,,20,0.0,0,,,,4,2004-08-29 00:00:00 +18379,726,40,6,16.0,20,10.0,10,0.0,41,,26.0,12.0,5,2004-08-29 00:00:00 +18380,726,43,6,17.0,9,8.0,8,1.0,44,5573967.0,29.0,14.0,1,2004-08-29 00:00:00 +18381,726,13,0,5.0,4,7.0,7,2.0,44,5573244.0,11.0,7.0,1,2004-08-29 00:00:00 +18382,726,31,18,15.0,13,6.0,6,3.0,44,5569888.0,11.0,11.0,1,2004-08-29 00:00:00 +18383,726,20,14,11.0,5,5.0,5,4.0,44,5569378.0,11.0,9.0,1,2004-08-29 00:00:00 +18384,726,12,14,12.0,8,4.0,4,5.0,44,5567778.0,29.0,13.0,1,2004-08-29 00:00:00 +18385,726,21,5,2.0,6,3.0,3,6.0,44,5559645.0,43.0,3.0,1,2004-08-29 00:00:00 +18386,726,29,5,1.0,2,2.0,2,8.0,44,5558406.0,28.0,2.0,1,2004-08-29 00:00:00 +18387,726,7,0,6.0,10,1.0,1,10.0,44,5555274.0,42.0,1.0,1,2004-08-29 00:00:00 +18388,726,14,3,7.0,1,9.0,9,0.0,44,5577389.0,9.0,5.0,1,2004-08-29 00:00:00 +18389,727,31,18,15.0,14,13.0,13,0.0,52,,29.0,15.0,11,2004-09-12 00:00:00 +18390,727,1,16,18.0,20,14.0,14,0.0,52,,23.0,17.0,11,2004-09-12 00:00:00 +18391,727,46,17,21.0,19,15.0,15,0.0,50,,31.0,18.0,13,2004-09-12 00:00:00 +18392,727,12,14,12.0,16,12.0,12,0.0,52,,50.0,11.0,11,2004-09-12 00:00:00 +18393,727,44,16,19.0,17,,17,0.0,33,,13.0,16.0,3,2004-09-12 00:00:00 +18394,727,45,17,20.0,18,,18,0.0,29,,24.0,19.0,66,2004-09-12 00:00:00 +18395,727,7,0,6.0,7,,19,0.0,13,,11.0,13.0,5,2004-09-12 00:00:00 +18396,727,3,3,8.0,4,,16,0.0,40,,31.0,8.0,20,2004-09-12 00:00:00 +18397,727,40,6,16.0,11,11.0,11,0.0,53,4600979.0,52.0,14.0,1,2004-09-12 00:00:00 +18398,727,43,6,17.0,13,,20,0.0,0,,,,4,2004-09-12 00:00:00 +18399,727,16,18,14.0,12,9.0,9,0.0,53,4575209.0,53.0,12.0,1,2004-09-12 00:00:00 +18400,727,21,5,2.0,1,1.0,1,10.0,53,4518448.0,41.0,1.0,1,2004-09-12 00:00:00 +18401,727,29,5,1.0,3,2.0,2,8.0,53,4519795.0,35.0,2.0,1,2004-09-12 00:00:00 +18402,727,17,15,9.0,6,3.0,3,6.0,53,4528645.0,13.0,6.0,1,2004-09-12 00:00:00 +18403,727,10,15,10.0,5,4.0,4,5.0,53,4533818.0,32.0,5.0,1,2004-09-12 00:00:00 +18404,727,14,3,7.0,9,10.0,10,0.0,53,4584764.0,52.0,7.0,1,2004-09-12 00:00:00 +18405,727,13,0,5.0,10,6.0,6,3.0,53,4551887.0,24.0,9.0,1,2004-09-12 00:00:00 +18406,727,41,2,4.0,8,7.0,7,2.0,53,4552200.0,32.0,3.0,1,2004-09-12 00:00:00 +18407,727,20,14,11.0,15,8.0,8,1.0,53,4553879.0,51.0,4.0,1,2004-09-12 00:00:00 +18408,727,30,2,3.0,2,5.0,5,4.0,53,4550800.0,32.0,10.0,1,2004-09-12 00:00:00 +18409,728,29,5,1.0,20,12.0,12,0.0,55,,55.0,1.0,11,2004-09-26 00:00:00 +18410,728,31,18,15.0,15,,20,0.0,11,,10.0,18.0,4,2004-09-26 00:00:00 +18411,728,40,6,16.0,13,,19,0.0,35,,24.0,12.0,7,2004-09-26 00:00:00 +18412,728,22,2,4.0,5,,18,0.0,37,,31.0,9.0,4,2004-09-26 00:00:00 +18413,728,45,17,20.0,17,,17,0.0,38,,23.0,19.0,36,2004-09-26 00:00:00 +18414,728,46,17,21.0,19,16.0,16,0.0,53,,51.0,20.0,13,2004-09-26 00:00:00 +18415,728,9,16,19.0,16,15.0,15,0.0,55,,54.0,16.0,11,2004-09-26 00:00:00 +18416,728,43,6,17.0,8,14.0,14,0.0,55,,51.0,13.0,11,2004-09-26 00:00:00 +18417,728,1,16,18.0,14,13.0,13,0.0,55,,55.0,14.0,11,2004-09-26 00:00:00 +18418,728,34,3,7.0,12,11.0,11,0.0,55,,55.0,17.0,11,2004-09-26 00:00:00 +18419,728,16,18,14.0,11,10.0,10,0.0,55,,32.0,15.0,11,2004-09-26 00:00:00 +18420,728,13,0,5.0,9,9.0,9,0.0,56,5433039.0,26.0,11.0,1,2004-09-26 00:00:00 +18421,728,12,14,12.0,4,8.0,8,1.0,56,5432500.0,43.0,6.0,1,2004-09-26 00:00:00 +18422,728,20,14,11.0,7,7.0,7,2.0,56,5417874.0,25.0,7.0,1,2004-09-26 00:00:00 +18423,728,10,15,10.0,18,6.0,6,3.0,56,5407211.0,36.0,8.0,1,2004-09-26 00:00:00 +18424,728,30,2,3.0,10,5.0,5,4.0,56,5397613.0,34.0,5.0,1,2004-09-26 00:00:00 +18425,728,3,3,8.0,6,4.0,4,5.0,56,5384930.0,55.0,10.0,1,2004-09-26 00:00:00 +18426,728,7,0,6.0,2,3.0,3,6.0,56,5353889.0,53.0,3.0,1,2004-09-26 00:00:00 +18427,728,17,15,9.0,3,2.0,2,8.0,56,5353455.0,33.0,4.0,1,2004-09-26 00:00:00 +18428,728,21,5,2.0,1,1.0,1,10.0,56,5352420.0,28.0,2.0,1,2004-09-26 00:00:00 +18429,729,1,16,18.0,16,13.0,13,0.0,52,,25.0,17.0,11,2004-10-10 00:00:00 +18430,729,43,6,17.0,10,14.0,14,0.0,51,,11.0,13.0,12,2004-10-10 00:00:00 +18431,729,9,16,19.0,17,15.0,15,0.0,51,,14.0,18.0,12,2004-10-10 00:00:00 +18432,729,45,17,20.0,18,16.0,16,0.0,50,,27.0,19.0,13,2004-10-10 00:00:00 +18433,729,16,18,14.0,3,,20,0.0,20,,13.0,11.0,25,2004-10-10 00:00:00 +18434,729,13,0,5.0,8,,18,0.0,38,,14.0,9.0,4,2004-10-10 00:00:00 +18435,729,21,5,2.0,15,,19,0.0,38,,30.0,1.0,4,2004-10-10 00:00:00 +18436,729,31,18,15.0,14,12.0,12,0.0,52,,32.0,15.0,11,2004-10-10 00:00:00 +18437,729,46,17,21.0,20,,17,0.0,41,,26.0,20.0,20,2004-10-10 00:00:00 +18438,729,14,6,16.0,6,11.0,11,0.0,52,,52.0,14.0,11,2004-10-10 00:00:00 +18439,729,34,3,7.0,9,10.0,10,0.0,52,,28.0,16.0,11,2004-10-10 00:00:00 +18440,729,12,14,12.0,19,9.0,9,0.0,53,5156641.0,40.0,4.0,1,2004-10-10 00:00:00 +18441,729,20,14,11.0,7,8.0,8,1.0,53,5123261.0,44.0,8.0,1,2004-10-10 00:00:00 +18442,729,30,2,3.0,13,7.0,7,2.0,53,5122332.0,30.0,6.0,1,2004-10-10 00:00:00 +18443,729,7,0,6.0,12,6.0,6,3.0,53,5106347.0,35.0,10.0,1,2004-10-10 00:00:00 +18444,729,3,3,8.0,11,5.0,5,4.0,53,5104752.0,29.0,12.0,1,2004-10-10 00:00:00 +18445,729,10,15,10.0,4,4.0,4,5.0,53,5098766.0,28.0,5.0,1,2004-10-10 00:00:00 +18446,729,17,15,9.0,5,3.0,3,6.0,53,5086647.0,33.0,7.0,1,2004-10-10 00:00:00 +18447,729,22,2,4.0,2,2.0,2,8.0,53,5081083.0,23.0,3.0,1,2004-10-10 00:00:00 +18448,729,29,5,1.0,1,1.0,1,10.0,53,5066985.0,41.0,2.0,1,2004-10-10 00:00:00 +18449,730,40,6,17.0,14,13.0,13,0.0,70,,69.0,14.0,11,2004-10-24 00:00:00 +18450,730,31,18,15.0,15,14.0,14,0.0,69,,49.0,13.0,12,2004-10-24 00:00:00 +18451,730,9,16,19.0,17,15.0,15,0.0,69,,68.0,16.0,12,2004-10-24 00:00:00 +18452,730,46,17,21.0,19,16.0,16,0.0,67,,45.0,17.0,14,2004-10-24 00:00:00 +18453,730,17,15,9.0,5,,20,0.0,3,,2.0,20.0,5,2004-10-24 00:00:00 +18454,730,16,18,14.0,11,,18,0.0,23,,20.0,15.0,4,2004-10-24 00:00:00 +18455,730,1,16,18.0,16,,19,0.0,15,,11.0,19.0,8,2004-10-24 00:00:00 +18456,730,14,6,16.0,9,12.0,12,0.0,70,,65.0,11.0,11,2004-10-24 00:00:00 +18457,730,45,17,20.0,20,17.0,17,0.0,67,,50.0,18.0,14,2004-10-24 00:00:00 +18458,730,13,0,5.0,12,11.0,11,0.0,70,,40.0,12.0,11,2004-10-24 00:00:00 +18459,730,34,3,7.0,13,10.0,10,0.0,70,,68.0,10.0,11,2004-10-24 00:00:00 +18460,730,20,14,11.0,10,9.0,9,0.0,71,5345293.0,69.0,6.0,1,2004-10-24 00:00:00 +18461,730,12,14,12.0,4,8.0,8,1.0,71,5343761.0,68.0,8.0,1,2004-10-24 00:00:00 +18462,730,29,5,1.0,18,7.0,7,2.0,71,5332077.0,49.0,4.0,1,2004-10-24 00:00:00 +18463,730,10,15,10.0,6,6.0,6,3.0,71,5331699.0,51.0,7.0,1,2004-10-24 00:00:00 +18464,730,22,2,4.0,7,5.0,5,4.0,71,5331191.0,23.0,5.0,1,2004-10-24 00:00:00 +18465,730,3,3,8.0,8,4.0,4,5.0,71,5329959.0,42.0,9.0,1,2004-10-24 00:00:00 +18466,730,21,5,2.0,1,3.0,3,6.0,71,5305550.0,22.0,3.0,1,2004-10-24 00:00:00 +18467,730,7,0,6.0,3,2.0,2,8.0,71,5282473.0,52.0,2.0,1,2004-10-24 00:00:00 +18468,730,30,2,3.0,2,1.0,1,10.0,71,5281451.0,49.0,1.0,1,2004-10-24 00:00:00 +18469,731,10,15,4.0,20,,14,0.0,55,,36.0,16.0,12,2005-03-06 14:00:00 +18470,731,38,16,19.0,12,15.0,15,0.0,55,,36.0,17.0,12,2005-03-06 14:00:00 +18471,731,32,16,18.0,14,16.0,16,0.0,55,,16.0,18.0,12,2005-03-06 14:00:00 +18472,731,26,17,21.0,17,,20,0.0,16,,11.0,20.0,6,2005-03-06 14:00:00 +18473,731,29,5,1.0,19,,18,0.0,42,,38.0,6.0,3,2005-03-06 14:00:00 +18474,731,1,2,8.0,7,,19,0.0,42,,38.0,12.0,3,2005-03-06 14:00:00 +18475,731,34,14,11.0,4,13.0,13,0.0,56,,54.0,15.0,11,2005-03-06 14:00:00 +18476,731,39,17,20.0,16,17.0,17,0.0,55,,22.0,19.0,14,2005-03-06 14:00:00 +18477,731,22,6,17.0,15,12.0,12,0.0,56,,56.0,9.0,11,2005-03-06 14:00:00 +18478,731,30,0,10.0,9,6.0,6,3.0,57,5092369.0,41.0,7.0,1,2005-03-06 14:00:00 +18479,731,12,14,12.0,18,10.0,10,0.0,57,5121729.0,55.0,13.0,1,2005-03-06 14:00:00 +18480,731,20,3,6.0,1,1.0,1,10.0,57,5057336.0,55.0,2.0,1,2005-03-06 14:00:00 +18481,731,21,5,2.0,11,2.0,2,8.0,57,5062889.0,54.0,3.0,1,2005-03-06 14:00:00 +18482,731,3,3,5.0,13,3.0,3,6.0,57,5064048.0,24.0,1.0,1,2005-03-06 14:00:00 +18483,731,13,8,14.0,5,4.0,4,5.0,57,5073467.0,40.0,11.0,1,2005-03-06 14:00:00 +18484,731,17,15,3.0,8,,11,0.0,56,,55.0,5.0,11,2005-03-06 14:00:00 +18485,731,31,8,15.0,6,7.0,7,2.0,57,5096333.0,39.0,10.0,1,2005-03-06 14:00:00 +18486,731,7,0,9.0,10,8.0,8,1.0,57,5096969.0,55.0,4.0,1,2005-03-06 14:00:00 +18487,731,14,6,16.0,2,9.0,9,0.0,57,5120444.0,56.0,14.0,1,2005-03-06 14:00:00 +18488,731,16,2,7.0,3,5.0,5,4.0,57,5074244.0,37.0,8.0,1,2005-03-06 14:00:00 +18489,732,26,17,21.0,19,13.0,13,0.0,52,,12.0,19.0,14,2005-03-20 15:00:00 +18490,732,39,17,20.0,20,,20,0.0,2,,2.0,20.0,20,2005-03-20 15:00:00 +18491,732,18,15,4.0,15,,19,0.0,2,,2.0,18.0,5,2005-03-20 15:00:00 +18492,732,17,15,3.0,9,,18,0.0,2,,2.0,14.0,5,2005-03-20 15:00:00 +18493,732,34,14,11.0,16,,17,0.0,26,,18.0,15.0,20,2005-03-20 15:00:00 +18494,732,16,2,7.0,4,,16,0.0,36,,20.0,5.0,4,2005-03-20 15:00:00 +18495,732,20,3,6.0,3,,15,0.0,36,,21.0,6.0,4,2005-03-20 15:00:00 +18496,732,21,5,2.0,12,,14,0.0,49,,22.0,10.0,27,2005-03-20 15:00:00 +18497,732,32,16,18.0,18,12.0,12,0.0,53,,36.0,17.0,13,2005-03-20 15:00:00 +18498,732,38,16,19.0,17,11.0,11,0.0,54,,18.0,16.0,12,2005-03-20 15:00:00 +18499,732,12,14,12.0,14,10.0,10,0.0,55,,18.0,13.0,11,2005-03-20 15:00:00 +18500,732,7,0,9.0,6,9.0,9,0.0,56,5575316.0,23.0,1.0,1,2005-03-20 15:00:00 +18501,732,31,8,15.0,7,8.0,8,1.0,56,5574571.0,17.0,11.0,1,2005-03-20 15:00:00 +18502,732,29,5,1.0,13,7.0,7,2.0,56,5573724.0,41.0,12.0,1,2005-03-20 15:00:00 +18503,732,13,8,14.0,8,6.0,6,3.0,56,5566279.0,18.0,9.0,1,2005-03-20 15:00:00 +18504,732,22,6,17.0,5,5.0,5,4.0,56,5545590.0,15.0,7.0,1,2005-03-20 15:00:00 +18505,732,30,0,10.0,11,4.0,4,5.0,56,5535367.0,42.0,8.0,1,2005-03-20 15:00:00 +18506,732,1,2,8.0,10,3.0,3,6.0,56,5525924.0,40.0,2.0,1,2005-03-20 15:00:00 +18507,732,14,6,16.0,2,2.0,2,8.0,56,5518063.0,18.0,3.0,1,2005-03-20 15:00:00 +18508,732,3,3,5.0,1,1.0,1,10.0,56,5493736.0,18.0,4.0,1,2005-03-20 15:00:00 +18509,733,17,15,3.0,11,,14,0.0,46,,45.0,5.0,8,2005-04-03 14:30:00 +18510,733,10,15,4.0,13,,15,0.0,27,,23.0,11.0,23,2005-04-03 14:30:00 +18511,733,1,2,8.0,4,,16,0.0,25,,19.0,9.0,5,2005-04-03 14:30:00 +18512,733,31,8,15.0,7,,20,0.0,0,,,,10,2005-04-03 14:30:00 +18513,733,20,3,6.0,10,,18,0.0,4,,2.0,18.0,5,2005-04-03 14:30:00 +18514,733,38,16,19.0,17,,19,0.0,2,,2.0,19.0,10,2005-04-03 14:30:00 +18515,733,26,17,21.0,18,13.0,13,0.0,53,,3.0,17.0,14,2005-04-03 14:30:00 +18516,733,29,5,1.0,2,,17,0.0,12,,7.0,7.0,9,2005-04-03 14:30:00 +18517,733,39,17,20.0,19,12.0,12,0.0,54,,16.0,16.0,13,2005-04-03 14:30:00 +18518,733,16,2,7.0,5,6.0,6,3.0,57,5433232.0,20.0,10.0,1,2005-04-03 14:30:00 +18519,733,32,16,18.0,16,10.0,10,0.0,55,,18.0,15.0,12,2005-04-03 14:30:00 +18520,733,34,14,11.0,15,11.0,11,0.0,54,,24.0,14.0,22,2005-04-03 14:30:00 +18521,733,14,6,16.0,3,2.0,2,8.0,57,5371940.0,41.0,4.0,1,2005-04-03 14:30:00 +18522,733,7,0,9.0,9,3.0,3,6.0,57,5390594.0,41.0,3.0,1,2005-04-03 14:30:00 +18523,733,22,6,17.0,6,4.0,4,5.0,57,5411803.0,36.0,6.0,1,2005-04-03 14:30:00 +18524,733,3,3,5.0,1,1.0,1,10.0,57,5358531.0,39.0,2.0,1,2005-04-03 14:30:00 +18525,733,12,14,12.0,12,7.0,7,2.0,56,,40.0,12.0,11,2005-04-03 14:30:00 +18526,733,13,8,14.0,14,8.0,8,1.0,56,,42.0,13.0,11,2005-04-03 14:30:00 +18527,733,21,5,2.0,20,9.0,9,0.0,56,,23.0,8.0,11,2005-04-03 14:30:00 +18528,733,36,0,10.0,8,5.0,5,4.0,57,5423519.0,43.0,1.0,1,2005-04-03 14:30:00 +18529,734,38,16,19.0,16,12.0,12,0.0,61,,20.0,12.0,11,2005-04-24 14:00:00 +18530,734,20,3,6.0,12,,18,0.0,5,,4.0,18.0,3,2005-04-24 14:00:00 +18531,734,39,17,20.0,19,,17,0.0,8,,5.0,20.0,8,2005-04-24 14:00:00 +18532,734,7,0,9.0,1,,16,0.0,9,,8.0,5.0,30,2005-04-24 14:00:00 +18533,734,21,5,2.0,9,,15,0.0,18,,13.0,15.0,10,2005-04-24 14:00:00 +18534,734,26,17,21.0,20,,14,0.0,20,,18.0,19.0,9,2005-04-24 14:00:00 +18535,734,32,16,18.0,17,13.0,13,0.0,60,,19.0,17.0,12,2005-04-24 14:00:00 +18536,734,13,8,14.0,14,11.0,11,0.0,61,,22.0,16.0,11,2005-04-24 14:00:00 +18537,734,1,2,8.0,8,6.0,6,3.0,62,5333203.0,54.0,9.0,1,2005-04-24 14:00:00 +18538,734,22,6,17.0,10,9.0,9,0.0,62,5357762.0,19.0,13.0,1,2005-04-24 14:00:00 +18539,734,23,8,15.0,15,8.0,8,1.0,62,5345685.0,46.0,7.0,1,2005-04-24 14:00:00 +18540,734,16,2,7.0,4,7.0,7,2.0,62,5345218.0,17.0,14.0,1,2005-04-24 14:00:00 +18541,734,14,6,16.0,5,5.0,5,4.0,62,5332179.0,44.0,11.0,1,2005-04-24 14:00:00 +18542,734,34,14,11.0,11,4.0,4,5.0,62,5326363.0,45.0,10.0,1,2005-04-24 14:00:00 +18543,734,24,0,10.0,7,3.0,3,6.0,62,5289475.0,24.0,3.0,1,2005-04-24 14:00:00 +18544,734,17,15,3.0,3,,19,0.0,62,5272321.0,22.0,2.0,2,2005-04-24 14:00:00 +18545,734,3,3,5.0,2,1.0,1,10.0,62,5261921.0,22.0,4.0,1,2005-04-24 14:00:00 +18546,734,12,14,12.0,18,10.0,10,0.0,61,,37.0,8.0,11,2005-04-24 14:00:00 +18547,734,10,15,4.0,6,,20,0.0,62,5296621.0,23.0,6.0,2,2005-04-24 14:00:00 +18548,734,29,5,1.0,13,2.0,2,8.0,62,5262136.0,48.0,1.0,1,2005-04-24 14:00:00 +18549,735,39,17,20.0,15,,17,0.0,11,,10.0,18.0,20,2005-05-08 14:00:00 +18550,735,26,17,21.0,14,,16,0.0,19,,15.0,17.0,6,2005-05-08 14:00:00 +18551,735,29,5,1.0,8,,15,0.0,46,,31.0,2.0,29,2005-05-08 14:00:00 +18552,735,34,14,11.0,12,,14,0.0,51,,43.0,13.0,5,2005-05-08 14:00:00 +18553,735,38,16,19.0,13,13.0,13,0.0,63,,16.0,16.0,13,2005-05-08 14:00:00 +18554,735,32,16,18.0,18,12.0,12,0.0,63,,22.0,14.0,13,2005-05-08 14:00:00 +18555,735,12,14,12.0,10,11.0,11,0.0,63,,51.0,10.0,46,2005-05-08 14:00:00 +18556,735,1,2,8.0,17,10.0,10,0.0,65,,60.0,7.0,11,2005-05-08 14:00:00 +18557,735,21,5,2.0,16,9.0,9,0.0,65,,64.0,12.0,11,2005-05-08 14:00:00 +18558,735,13,8,14.0,9,8.0,8,1.0,65,,65.0,11.0,11,2005-05-08 14:00:00 +18559,735,23,8,15.0,11,,18,0.0,9,,9.0,15.0,20,2005-05-08 14:00:00 +18560,735,16,2,7.0,2,6.0,6,3.0,66,5305372.0,62.0,9.0,1,2005-05-08 14:00:00 +18561,735,20,3,6.0,6,5.0,5,4.0,66,5294766.0,66.0,1.0,1,2005-05-08 14:00:00 +18562,735,22,6,17.0,4,4.0,4,5.0,66,5283549.0,63.0,6.0,1,2005-05-08 14:00:00 +18563,735,14,6,16.0,5,3.0,3,6.0,66,5282777.0,63.0,8.0,1,2005-05-08 14:00:00 +18564,735,3,3,5.0,3,2.0,2,8.0,66,5264482.0,59.0,5.0,1,2005-05-08 14:00:00 +18565,735,7,0,9.0,1,1.0,1,10.0,66,5236830.0,41.0,4.0,1,2005-05-08 14:00:00 +18566,735,30,0,10.0,7,7.0,7,2.0,65,,55.0,3.0,11,2005-05-08 14:00:00 +18567,736,7,0,9.0,1,1.0,1,10.0,78,6315556.0,41.0,2.0,1,2005-05-22 14:00:00 +18568,736,38,16,19.0,17,,18,0.0,18,,14.0,18.0,9,2005-05-22 14:00:00 +18569,736,13,8,14.0,7,,17,0.0,23,,15.0,12.0,3,2005-05-22 14:00:00 +18570,736,39,17,20.0,13,,16,0.0,29,,19.0,15.0,3,2005-05-22 14:00:00 +18571,736,23,8,15.0,12,,15,0.0,59,,43.0,14.0,3,2005-05-22 14:00:00 +18572,736,26,17,21.0,14,14.0,14,0.0,73,,22.0,16.0,15,2005-05-22 14:00:00 +18573,736,32,16,18.0,15,13.0,13,0.0,75,,12.0,17.0,13,2005-05-22 14:00:00 +18574,736,34,14,11.0,9,11.0,11,0.0,77,,17.0,11.0,11,2005-05-22 14:00:00 +18575,736,20,3,6.0,4,12.0,12,0.0,77,,20.0,4.0,11,2005-05-22 14:00:00 +18576,736,12,14,12.0,11,9.0,9,0.0,77,,16.0,13.0,11,2005-05-22 14:00:00 +18577,736,21,5,2.0,10,8.0,8,1.0,78,6353126.0,51.0,6.0,1,2005-05-22 14:00:00 +18578,736,29,5,1.0,8,7.0,7,2.0,78,6352779.0,40.0,1.0,1,2005-05-22 14:00:00 +18579,736,22,6,17.0,18,6.0,6,3.0,78,6352673.0,11.0,8.0,1,2005-05-22 14:00:00 +18580,736,30,0,10.0,16,5.0,5,4.0,78,6352203.0,50.0,10.0,1,2005-05-22 14:00:00 +18581,736,3,3,5.0,2,4.0,4,5.0,78,6352043.0,19.0,3.0,1,2005-05-22 14:00:00 +18582,736,16,2,7.0,3,3.0,3,6.0,78,6334040.0,77.0,7.0,1,2005-05-22 14:00:00 +18583,736,14,6,16.0,5,10.0,10,0.0,77,,38.0,5.0,11,2005-05-22 14:00:00 +18584,736,1,2,8.0,6,2.0,2,8.0,78,6329433.0,15.0,9.0,1,2005-05-22 14:00:00 +18585,737,10,15,4.0,16,12.0,12,0.0,58,,26.0,11.0,11,2005-05-29 14:00:00 +18586,737,34,14,11.0,15,13.0,13,0.0,58,,41.0,15.0,11,2005-05-29 14:00:00 +18587,737,32,16,18.0,17,15.0,15,0.0,58,,39.0,17.0,11,2005-05-29 14:00:00 +18588,737,16,2,7.0,3,,20,0.0,0,,,,3,2005-05-29 14:00:00 +18589,737,26,17,21.0,20,17.0,17,0.0,57,,18.0,18.0,12,2005-05-29 14:00:00 +18590,737,39,17,20.0,18,18.0,18,0.0,56,,18.0,19.0,13,2005-05-29 14:00:00 +18591,737,38,16,19.0,19,16.0,16,0.0,58,,21.0,16.0,11,2005-05-29 14:00:00 +18592,737,7,0,9.0,2,11.0,11,0.0,58,,9.0,2.0,3,2005-05-29 14:00:00 +18593,737,22,6,17.0,8,,19,0.0,33,,25.0,8.0,20,2005-05-29 14:00:00 +18594,737,23,8,15.0,14,9.0,9,0.0,59,5578177.0,43.0,13.0,1,2005-05-29 14:00:00 +18595,737,3,3,5.0,6,1.0,1,10.0,59,5506648.0,44.0,1.0,1,2005-05-29 14:00:00 +18596,737,17,15,3.0,13,10.0,10,0.0,59,5602434.0,20.0,12.0,1,2005-05-29 14:00:00 +18597,737,1,2,8.0,1,2.0,2,8.0,59,5523215.0,9.0,4.0,1,2005-05-29 14:00:00 +18598,737,21,5,2.0,7,3.0,3,6.0,59,5525197.0,44.0,3.0,1,2005-05-29 14:00:00 +18599,737,13,8,14.0,12,4.0,4,5.0,59,5538236.0,19.0,5.0,1,2005-05-29 14:00:00 +18600,737,12,14,12.0,11,14.0,14,0.0,58,,18.0,14.0,11,2005-05-29 14:00:00 +18601,737,20,3,6.0,9,6.0,6,3.0,59,5558580.0,47.0,7.0,1,2005-05-29 14:00:00 +18602,737,30,0,10.0,5,7.0,7,2.0,59,5564821.0,42.0,10.0,1,2005-05-29 14:00:00 +18603,737,14,6,16.0,4,8.0,8,1.0,59,5577739.0,43.0,9.0,1,2005-05-29 14:00:00 +18604,737,29,5,1.0,10,5.0,5,4.0,59,5557093.0,19.0,6.0,1,2005-05-29 14:00:00 +18605,738,38,16,19.0,17,,19,0.0,24,,20.0,17.0,22,2005-06-12 13:00:00 +18606,738,20,3,6.0,4,,18,0.0,32,,24.0,5.0,9,2005-06-12 13:00:00 +18607,738,3,3,5.0,3,,17,0.0,38,,38.0,3.0,22,2005-06-12 13:00:00 +18608,738,10,15,4.0,6,,15,0.0,40,,14.0,14.0,23,2005-06-12 13:00:00 +18609,738,1,2,8.0,13,,14,0.0,43,,20.0,9.0,5,2005-06-12 13:00:00 +18610,738,17,15,3.0,1,,13,0.0,46,,30.0,6.0,3,2005-06-12 13:00:00 +18611,738,14,6,16.0,9,,12,0.0,62,,43.0,11.0,23,2005-06-12 13:00:00 +18612,738,26,17,21.0,15,11.0,11,0.0,67,,15.0,19.0,13,2005-06-12 13:00:00 +18613,738,30,0,10.0,5,,20,0.0,52,,24.0,2.0,2,2005-06-12 13:00:00 +18614,738,34,14,11.0,8,9.0,9,0.0,69,,26.0,12.0,11,2005-06-12 13:00:00 +18615,738,7,0,9.0,7,1.0,1,10.0,70,5529290.0,23.0,1.0,1,2005-06-12 13:00:00 +18616,738,32,16,18.0,18,10.0,10,0.0,67,,19.0,18.0,13,2005-06-12 13:00:00 +18617,738,29,5,1.0,2,2.0,2,8.0,70,5530390.0,32.0,4.0,1,2005-06-12 13:00:00 +18618,738,21,5,2.0,20,3.0,3,6.0,70,5569690.0,46.0,8.0,1,2005-06-12 13:00:00 +18619,738,12,14,12.0,11,4.0,4,5.0,70,5584390.0,18.0,13.0,1,2005-06-12 13:00:00 +18620,738,39,17,20.0,19,,16,0.0,39,,33.0,20.0,9,2005-06-12 13:00:00 +18621,738,22,6,17.0,10,6.0,6,3.0,69,,44.0,10.0,11,2005-06-12 13:00:00 +18622,738,31,8,15.0,16,8.0,8,1.0,69,,46.0,15.0,11,2005-06-12 13:00:00 +18623,738,13,8,14.0,12,7.0,7,2.0,69,,17.0,16.0,11,2005-06-12 13:00:00 +18624,738,16,2,7.0,14,5.0,5,4.0,70,5584990.0,23.0,7.0,1,2005-06-12 13:00:00 +18625,739,13,8,14.0,16,,20,0.0,0,,,,54,2005-06-19 14:00:00 +18626,739,1,2,8.0,15,,19,0.0,0,,,,54,2005-06-19 14:00:00 +18627,739,31,8,15.0,14,,18,0.0,0,,,,54,2005-06-19 14:00:00 +18628,739,40,6,17.0,13,,17,0.0,0,,,,54,2005-06-19 14:00:00 +18629,739,30,0,10.0,11,,15,0.0,0,,,,54,2005-06-19 14:00:00 +18630,739,12,14,12.0,10,,14,0.0,0,,,,54,2005-06-19 14:00:00 +18631,739,16,2,7.0,9,,13,0.0,0,,,,54,2005-06-19 14:00:00 +18632,739,10,15,4.0,8,,12,0.0,0,,,,54,2005-06-19 14:00:00 +18633,739,20,3,6.0,4,,10,0.0,0,,,,54,2005-06-19 14:00:00 +18634,739,17,15,3.0,3,,9,0.0,0,,,,54,2005-06-19 14:00:00 +18635,739,7,0,9.0,2,,8,0.0,0,,,,54,2005-06-19 14:00:00 +18636,739,14,6,16.0,1,,7,0.0,0,,,,54,2005-06-19 14:00:00 +18637,739,26,17,21.0,18,5.0,5,4.0,71,,2.0,5.0,12,2005-06-19 14:00:00 +18638,739,38,16,19.0,19,4.0,4,5.0,72,,65.0,4.0,11,2005-06-19 14:00:00 +18639,739,32,16,18.0,17,3.0,3,6.0,72,,44.0,3.0,11,2005-06-19 14:00:00 +18640,739,21,5,2.0,7,2.0,2,8.0,73,5384681.0,48.0,2.0,1,2005-06-19 14:00:00 +18641,739,29,5,1.0,5,1.0,1,10.0,73,5383181.0,48.0,1.0,1,2005-06-19 14:00:00 +18642,739,3,3,5.0,6,,11,0.0,0,,,,54,2005-06-19 14:00:00 +18643,739,39,17,20.0,20,6.0,6,3.0,71,,43.0,6.0,12,2005-06-19 14:00:00 +18644,739,34,14,11.0,12,,16,0.0,0,,,,54,2005-06-19 14:00:00 +18645,740,31,8,15.0,16,,20,0.0,1,,,,32,2005-07-03 14:00:00 +18646,740,3,3,5.0,1,1.0,1,10.0,70,5482232.0,5.0,2.0,1,2005-07-03 14:00:00 +18647,740,7,0,9.0,13,2.0,2,8.0,70,5494032.0,25.0,1.0,1,2005-07-03 14:00:00 +18648,740,29,5,1.0,3,3.0,3,6.0,70,5564132.0,22.0,7.0,1,2005-07-03 14:00:00 +18649,740,17,15,3.0,7,4.0,4,5.0,69,,18.0,4.0,11,2005-07-03 14:00:00 +18650,740,14,6,16.0,2,5.0,5,4.0,69,,67.0,8.0,11,2005-07-03 14:00:00 +18651,740,20,3,6.0,6,6.0,6,3.0,69,,18.0,5.0,11,2005-07-03 14:00:00 +18652,740,22,6,17.0,11,7.0,7,2.0,69,,36.0,14.0,11,2005-07-03 14:00:00 +18653,740,21,5,2.0,5,9.0,9,0.0,69,,4.0,12.0,11,2005-07-03 14:00:00 +18654,740,13,8,14.0,15,10.0,10,0.0,69,,39.0,6.0,11,2005-07-03 14:00:00 +18655,740,10,15,4.0,4,11.0,11,0.0,69,,8.0,11.0,11,2005-07-03 14:00:00 +18656,740,34,14,11.0,10,8.0,8,1.0,69,,17.0,10.0,11,2005-07-03 14:00:00 +18657,740,32,16,18.0,19,13.0,13,0.0,67,,32.0,16.0,13,2005-07-03 14:00:00 +18658,740,1,2,8.0,14,14.0,14,0.0,66,,36.0,13.0,14,2005-07-03 14:00:00 +18659,740,38,16,19.0,17,15.0,15,0.0,66,,9.0,17.0,14,2005-07-03 14:00:00 +18660,740,30,0,10.0,8,,16,0.0,46,,24.0,3.0,5,2005-07-03 14:00:00 +18661,740,26,17,21.0,20,,17,0.0,37,,8.0,18.0,29,2005-07-03 14:00:00 +18662,740,39,17,20.0,18,,18,0.0,33,,4.0,19.0,29,2005-07-03 14:00:00 +18663,740,12,14,12.0,9,,19,0.0,30,,11.0,9.0,9,2005-07-03 14:00:00 +18664,740,16,2,7.0,12,12.0,12,0.0,68,,17.0,15.0,12,2005-07-03 14:00:00 +18665,741,31,8,15.0,15,15.0,15,0.0,59,,58.0,13.0,11,2005-07-10 14:00:00 +18666,741,10,15,4.0,7,16.0,16,0.0,58,,54.0,11.0,12,2005-07-10 14:00:00 +18667,741,32,16,18.0,20,17.0,17,0.0,58,,38.0,17.0,12,2005-07-10 14:00:00 +18668,741,38,16,19.0,17,,20,0.0,10,,8.0,18.0,10,2005-07-10 14:00:00 +18669,741,39,17,20.0,19,19.0,19,0.0,56,,37.0,20.0,14,2005-07-10 14:00:00 +18670,741,7,0,9.0,12,3.0,3,6.0,60,5083988.0,60.0,1.0,1,2005-07-10 14:00:00 +18671,741,34,14,11.0,10,14.0,14,0.0,59,,16.0,14.0,11,2005-07-10 14:00:00 +18672,741,26,17,21.0,18,18.0,18,0.0,57,,53.0,19.0,13,2005-07-10 14:00:00 +18673,741,13,8,14.0,13,13.0,13,0.0,59,,44.0,12.0,11,2005-07-10 14:00:00 +18674,741,3,3,5.0,1,2.0,2,8.0,60,5072288.0,40.0,4.0,1,2005-07-10 14:00:00 +18675,741,16,2,7.0,11,11.0,11,0.0,59,,16.0,15.0,11,2005-07-10 14:00:00 +18676,741,30,0,10.0,3,1.0,1,10.0,60,5069588.0,41.0,2.0,1,2005-07-10 14:00:00 +18677,741,20,3,6.0,6,4.0,4,5.0,60,5087488.0,43.0,3.0,1,2005-07-10 14:00:00 +18678,741,17,15,3.0,2,5.0,5,4.0,60,5109888.0,42.0,7.0,1,2005-07-10 14:00:00 +18679,741,29,5,1.0,9,6.0,6,3.0,60,5144888.0,23.0,5.0,1,2005-07-10 14:00:00 +18680,741,1,2,8.0,14,12.0,12,0.0,59,,58.0,16.0,11,2005-07-10 14:00:00 +18681,741,22,6,17.0,8,8.0,8,1.0,60,5148788.0,46.0,6.0,1,2005-07-10 14:00:00 +18682,741,14,6,16.0,4,9.0,9,0.0,60,5150488.0,56.0,8.0,1,2005-07-10 14:00:00 +18683,741,12,14,12.0,16,10.0,10,0.0,59,,45.0,10.0,11,2005-07-10 14:00:00 +18684,741,21,5,2.0,5,7.0,7,2.0,60,5146188.0,41.0,9.0,1,2005-07-10 14:00:00 +18685,742,7,0,9.0,1,,20,0.0,32,,24.0,1.0,9,2005-07-24 14:00:00 +18686,742,16,2,7.0,6,,19,0.0,55,,46.0,15.0,55,2005-07-24 14:00:00 +18687,742,37,17,20.0,17,18.0,18,0.0,63,,44.0,20.0,14,2005-07-24 14:00:00 +18688,742,32,16,18.0,18,17.0,17,0.0,64,,12.0,17.0,13,2005-07-24 14:00:00 +18689,742,38,16,19.0,19,16.0,16,0.0,64,,7.0,18.0,13,2005-07-24 14:00:00 +18690,742,34,14,11.0,14,15.0,15,0.0,64,,26.0,16.0,13,2005-07-24 14:00:00 +18691,742,14,6,16.0,9,14.0,14,0.0,64,,45.0,11.0,13,2005-07-24 14:00:00 +18692,742,10,15,4.0,8,12.0,12,0.0,66,,27.0,14.0,11,2005-07-24 14:00:00 +18693,742,26,17,21.0,16,13.0,13,0.0,65,,11.0,19.0,12,2005-07-24 14:00:00 +18694,742,21,5,2.0,15,10.0,10,0.0,66,,47.0,12.0,11,2005-07-24 14:00:00 +18695,742,31,8,15.0,10,9.0,9,0.0,67,5258417.0,45.0,9.0,1,2005-07-24 14:00:00 +18696,742,12,14,12.0,13,8.0,8,1.0,67,5245169.0,45.0,10.0,1,2005-07-24 14:00:00 +18697,742,13,8,14.0,11,7.0,7,2.0,67,5241299.0,18.0,8.0,1,2005-07-24 14:00:00 +18698,742,22,6,17.0,12,6.0,6,3.0,67,5240841.0,23.0,6.0,1,2005-07-24 14:00:00 +18699,742,29,5,1.0,5,5.0,5,4.0,67,5240289.0,18.0,7.0,1,2005-07-24 14:00:00 +18700,742,20,3,6.0,4,4.0,4,5.0,67,5239186.0,21.0,5.0,1,2005-07-24 14:00:00 +18701,742,17,15,3.0,2,3.0,3,6.0,67,5213021.0,19.0,3.0,1,2005-07-24 14:00:00 +18702,742,30,0,10.0,20,2.0,2,8.0,67,5211168.0,54.0,4.0,1,2005-07-24 14:00:00 +18703,742,3,3,5.0,3,1.0,1,10.0,67,5188599.0,21.0,2.0,1,2005-07-24 14:00:00 +18704,742,1,2,8.0,7,11.0,11,0.0,66,,10.0,13.0,11,2005-07-24 14:00:00 +18705,743,12,14,12.0,14,14.0,14,0.0,63,,22.0,13.0,17,2005-07-31 14:00:00 +18706,743,26,17,21.0,17,,15,0.0,59,,8.0,18.0,45,2005-07-31 14:00:00 +18707,743,31,8,15.0,11,,20,0.0,0,,,,3,2005-07-31 14:00:00 +18708,743,30,0,10.0,2,,17,0.0,41,,20.0,2.0,30,2005-07-31 14:00:00 +18709,743,13,8,14.0,13,,19,0.0,0,,,,3,2005-07-31 14:00:00 +18710,743,32,16,18.0,20,13.0,13,0.0,66,,15.0,16.0,14,2005-07-31 14:00:00 +18711,743,34,14,11.0,15,,16,0.0,56,,23.0,14.0,56,2005-07-31 14:00:00 +18712,743,38,16,19.0,18,12.0,12,0.0,67,,17.0,15.0,13,2005-07-31 14:00:00 +18713,743,37,17,20.0,19,,18,0.0,26,,16.0,17.0,9,2005-07-31 14:00:00 +18714,743,21,5,2.0,7,10.0,10,0.0,69,,20.0,11.0,11,2005-07-31 14:00:00 +18715,743,3,3,5.0,6,11.0,11,0.0,69,,51.0,12.0,11,2005-07-31 14:00:00 +18716,743,7,0,9.0,4,1.0,1,10.0,70,5845552.0,40.0,1.0,1,2005-07-31 14:00:00 +18717,743,29,5,1.0,1,2.0,2,8.0,70,5881133.0,13.0,3.0,1,2005-07-31 14:00:00 +18718,743,22,6,17.0,5,3.0,3,6.0,70,5881681.0,13.0,5.0,1,2005-07-31 14:00:00 +18719,743,10,15,4.0,10,8.0,8,1.0,69,,45.0,7.0,11,2005-07-31 14:00:00 +18720,743,17,15,3.0,8,5.0,5,4.0,70,5904384.0,70.0,8.0,1,2005-07-31 14:00:00 +18721,743,1,2,8.0,12,6.0,6,3.0,70,5913927.0,53.0,6.0,1,2005-07-31 14:00:00 +18722,743,16,2,7.0,16,7.0,7,2.0,69,,47.0,9.0,11,2005-07-31 14:00:00 +18723,743,20,3,6.0,9,9.0,9,0.0,69,,19.0,10.0,11,2005-07-31 14:00:00 +18724,743,14,6,16.0,3,4.0,4,5.0,70,5899773.0,32.0,4.0,1,2005-07-31 14:00:00 +18725,744,16,2,7.0,7,,20,0.0,20,,12.0,12.0,27,2005-08-21 15:00:00 +18726,744,12,14,12.0,8,,19,0.0,28,,27.0,10.0,5,2005-08-21 15:00:00 +18727,744,1,2,8.0,6,,18,0.0,29,,25.0,16.0,27,2005-08-21 15:00:00 +18728,744,29,5,1.0,19,,17,0.0,32,,21.0,14.0,31,2005-08-21 15:00:00 +18729,744,26,17,21.0,15,,16,0.0,48,,13.0,20.0,31,2005-08-21 15:00:00 +18730,744,32,16,18.0,14,15.0,15,0.0,55,,50.0,17.0,13,2005-08-21 15:00:00 +18731,744,38,16,19.0,18,14.0,14,0.0,55,,42.0,19.0,13,2005-08-21 15:00:00 +18732,744,37,17,20.0,17,13.0,13,0.0,55,,53.0,18.0,13,2005-08-21 15:00:00 +18733,744,22,6,17.0,9,12.0,12,0.0,57,,38.0,15.0,11,2005-08-21 15:00:00 +18734,744,34,14,11.0,16,11.0,11,0.0,57,,44.0,13.0,11,2005-08-21 15:00:00 +18735,744,10,15,4.0,20,9.0,9,0.0,58,5154441.0,54.0,6.0,1,2005-08-21 15:00:00 +18736,744,13,8,14.0,12,7.0,7,2.0,58,5143746.0,58.0,9.0,1,2005-08-21 15:00:00 +18737,744,14,6,16.0,5,6.0,6,3.0,58,5129874.0,52.0,7.0,1,2005-08-21 15:00:00 +18738,744,17,15,3.0,13,5.0,5,4.0,58,5113758.0,58.0,5.0,1,2005-08-21 15:00:00 +18739,744,20,3,6.0,2,4.0,4,5.0,58,5112427.0,34.0,4.0,1,2005-08-21 15:00:00 +18740,744,30,0,10.0,4,3.0,3,6.0,58,5094089.0,39.0,1.0,1,2005-08-21 15:00:00 +18741,744,3,3,5.0,3,2.0,2,8.0,58,5093063.0,58.0,3.0,1,2005-08-21 15:00:00 +18742,744,7,0,9.0,1,1.0,1,10.0,58,5074454.0,40.0,2.0,1,2005-08-21 15:00:00 +18743,744,21,5,2.0,11,10.0,10,0.0,57,,45.0,11.0,11,2005-08-21 15:00:00 +18744,744,31,8,15.0,10,8.0,8,1.0,58,5146076.0,58.0,8.0,1,2005-08-21 15:00:00 +18745,745,38,16,19.0,19,20.0,20,0.0,50,,17.0,19.0,13,2005-09-04 14:00:00 +18746,745,26,17,21.0,20,19.0,19,0.0,51,,33.0,18.0,12,2005-09-04 14:00:00 +18747,745,37,17,20.0,18,18.0,18,0.0,51,,31.0,20.0,12,2005-09-04 14:00:00 +18748,745,30,0,10.0,1,1.0,1,10.0,53,4468659.0,15.0,2.0,1,2005-09-04 14:00:00 +18749,745,32,16,18.0,17,17.0,17,0.0,51,,9.0,17.0,12,2005-09-04 14:00:00 +18750,745,10,15,4.0,4,16.0,16,0.0,52,,14.0,10.0,11,2005-09-04 14:00:00 +18751,745,13,8,14.0,10,15.0,15,0.0,52,,18.0,15.0,11,2005-09-04 14:00:00 +18752,745,16,2,7.0,14,14.0,14,0.0,52,,40.0,7.0,11,2005-09-04 14:00:00 +18753,745,21,5,2.0,7,12.0,12,0.0,52,,13.0,12.0,11,2005-09-04 14:00:00 +18754,745,34,14,11.0,12,11.0,11,0.0,52,,13.0,16.0,11,2005-09-04 14:00:00 +18755,745,29,5,1.0,6,10.0,10,0.0,53,4564729.0,5.0,13.0,1,2005-09-04 14:00:00 +18756,745,31,8,15.0,13,13.0,13,0.0,52,,17.0,14.0,11,2005-09-04 14:00:00 +18757,745,17,15,3.0,3,8.0,8,1.0,53,4532294.0,16.0,9.0,1,2005-09-04 14:00:00 +18758,745,41,2,8.0,16,7.0,7,2.0,53,4513302.0,21.0,6.0,1,2005-09-04 14:00:00 +18759,745,22,6,17.0,9,6.0,6,3.0,53,4512584.0,19.0,8.0,1,2005-09-04 14:00:00 +18760,745,14,6,16.0,5,5.0,5,4.0,53,4502445.0,19.0,5.0,1,2005-09-04 14:00:00 +18761,745,7,0,9.0,11,4.0,4,5.0,53,4491434.0,51.0,1.0,1,2005-09-04 14:00:00 +18762,745,20,3,6.0,8,3.0,3,6.0,53,4486634.0,16.0,4.0,1,2005-09-04 14:00:00 +18763,745,3,3,5.0,2,2.0,2,8.0,53,4471138.0,16.0,3.0,1,2005-09-04 14:00:00 +18764,745,12,14,12.0,15,9.0,9,0.0,53,4544072.0,18.0,11.0,1,2005-09-04 14:00:00 +18765,746,30,0,10.0,1,14.0,14,0.0,40,,14.0,9.0,4,2005-09-11 14:00:00 +18766,746,41,2,8.0,15,15.0,15,0.0,39,,32.0,15.0,4,2005-09-11 14:00:00 +18767,746,14,6,16.0,3,,16,0.0,34,,3.0,11.0,3,2005-09-11 14:00:00 +18768,746,20,3,6.0,13,,20,0.0,10,,9.0,12.0,3,2005-09-11 14:00:00 +18769,746,29,5,1.0,6,,18,0.0,13,,10.0,13.0,3,2005-09-11 14:00:00 +18770,746,10,15,4.0,10,,19,0.0,13,,10.0,14.0,3,2005-09-11 14:00:00 +18771,746,37,17,20.0,17,13.0,13,0.0,41,,38.0,19.0,13,2005-09-11 14:00:00 +18772,746,13,8,14.0,11,,17,0.0,18,,8.0,18.0,5,2005-09-11 14:00:00 +18773,746,26,17,21.0,18,12.0,12,0.0,42,,6.0,20.0,12,2005-09-11 14:00:00 +18774,746,22,6,17.0,5,7.0,7,2.0,44,5488795.0,43.0,1.0,1,2005-09-11 14:00:00 +18775,746,12,14,12.0,7,10.0,10,0.0,43,,28.0,16.0,11,2005-09-11 14:00:00 +18776,746,38,16,19.0,20,11.0,11,0.0,43,,43.0,8.0,11,2005-09-11 14:00:00 +18777,746,3,3,5.0,4,2.0,2,8.0,44,5429595.0,31.0,10.0,1,2005-09-11 14:00:00 +18778,746,17,15,3.0,8,3.0,3,6.0,44,5433295.0,44.0,5.0,1,2005-09-11 14:00:00 +18779,746,16,2,7.0,9,4.0,4,5.0,44,5470395.0,44.0,2.0,1,2005-09-11 14:00:00 +18780,746,7,0,9.0,2,1.0,1,10.0,44,5401295.0,34.0,6.0,1,2005-09-11 14:00:00 +18781,746,34,14,11.0,14,6.0,6,3.0,44,5488695.0,44.0,7.0,1,2005-09-11 14:00:00 +18782,746,32,16,18.0,19,8.0,8,1.0,43,,41.0,17.0,11,2005-09-11 14:00:00 +18783,746,31,8,15.0,16,9.0,9,0.0,43,,43.0,3.0,11,2005-09-11 14:00:00 +18784,746,21,5,2.0,12,5.0,5,4.0,44,5479395.0,44.0,4.0,1,2005-09-11 14:00:00 +18785,747,14,6,16.0,17,13.0,13,0.0,69,,69.0,7.0,12,2005-09-25 14:00:00 +18786,747,13,8,14.0,14,,20,0.0,0,,,,3,2005-09-25 14:00:00 +18787,747,41,2,8.0,13,,19,0.0,0,,,,3,2005-09-25 14:00:00 +18788,747,37,17,20.0,18,,18,0.0,34,,16.0,18.0,5,2005-09-25 14:00:00 +18789,747,16,2,7.0,12,,17,0.0,45,,45.0,8.0,58,2005-09-25 14:00:00 +18790,747,32,16,18.0,11,,16,0.0,55,,41.0,16.0,26,2005-09-25 14:00:00 +18791,747,38,16,19.0,15,15.0,15,0.0,68,,41.0,15.0,13,2005-09-25 14:00:00 +18792,747,26,17,21.0,16,14.0,14,0.0,69,,19.0,17.0,12,2005-09-25 14:00:00 +18793,747,34,14,11.0,20,12.0,12,0.0,70,,25.0,12.0,11,2005-09-25 14:00:00 +18794,747,30,0,10.0,2,1.0,1,10.0,71,5360574.0,27.0,2.0,1,2005-09-25 14:00:00 +18795,747,10,15,4.0,19,10.0,10,0.0,70,,32.0,14.0,11,2005-09-25 14:00:00 +18796,747,7,0,9.0,5,2.0,2,8.0,71,5363101.0,29.0,1.0,1,2005-09-25 14:00:00 +18797,747,3,3,5.0,1,3.0,3,6.0,71,5385414.0,21.0,3.0,1,2005-09-25 14:00:00 +18798,747,29,5,1.0,7,4.0,4,5.0,71,5396242.0,25.0,4.0,1,2005-09-25 14:00:00 +18799,747,20,3,6.0,3,5.0,5,4.0,71,5400792.0,11.0,5.0,1,2005-09-25 14:00:00 +18800,747,12,14,12.0,8,11.0,11,0.0,70,,70.0,13.0,11,2005-09-25 14:00:00 +18801,747,17,15,3.0,4,7.0,7,2.0,70,,24.0,10.0,11,2005-09-25 14:00:00 +18802,747,22,6,17.0,10,8.0,8,1.0,70,,25.0,9.0,11,2005-09-25 14:00:00 +18803,747,31,8,15.0,6,9.0,9,0.0,70,,50.0,11.0,11,2005-09-25 14:00:00 +18804,747,21,5,2.0,9,6.0,6,3.0,71,5429747.0,49.0,6.0,1,2005-09-25 14:00:00 +18805,748,32,16,18.0,20,13.0,13,0.0,52,,17.0,14.0,11,2005-10-09 14:00:00 +18806,748,10,15,4.0,5,,20,0.0,52,,28.0,13.0,2,2005-10-09 14:00:00 +18807,748,30,0,10.0,18,,19,0.0,0,,,,3,2005-10-09 14:00:00 +18808,748,14,6,16.0,19,,18,0.0,9,,9.0,19.0,3,2005-10-09 14:00:00 +18809,748,41,2,8.0,12,,17,0.0,9,,9.0,18.0,3,2005-10-09 14:00:00 +18810,748,26,17,21.0,13,16.0,16,0.0,49,,33.0,16.0,14,2005-10-09 14:00:00 +18811,748,38,16,19.0,11,15.0,15,0.0,51,,11.0,15.0,12,2005-10-09 14:00:00 +18812,748,37,17,20.0,15,14.0,14,0.0,51,,50.0,17.0,12,2005-10-09 14:00:00 +18813,748,34,14,11.0,8,12.0,12,0.0,53,5425433.0,50.0,11.0,1,2005-10-09 14:00:00 +18814,748,21,5,2.0,9,11.0,11,0.0,53,5402845.0,52.0,9.0,1,2005-10-09 14:00:00 +18815,748,12,14,12.0,10,10.0,10,0.0,53,5399721.0,43.0,10.0,1,2005-10-09 14:00:00 +18816,748,20,3,6.0,3,2.0,2,8.0,53,5343845.0,19.0,3.0,1,2005-10-09 14:00:00 +18817,748,3,3,5.0,16,3.0,3,6.0,53,5359668.0,21.0,2.0,1,2005-10-09 14:00:00 +18818,748,16,2,7.0,7,4.0,4,5.0,53,5364486.0,21.0,7.0,1,2005-10-09 14:00:00 +18819,748,17,15,3.0,2,5.0,5,4.0,53,5371719.0,19.0,4.0,1,2005-10-09 14:00:00 +18820,748,7,0,9.0,17,1.0,1,10.0,53,5342212.0,44.0,1.0,1,2005-10-09 14:00:00 +18821,748,29,5,1.0,14,7.0,7,2.0,53,5376091.0,25.0,5.0,1,2005-10-09 14:00:00 +18822,748,22,6,17.0,1,8.0,8,1.0,53,5391760.0,9.0,6.0,1,2005-10-09 14:00:00 +18823,748,31,8,15.0,4,9.0,9,0.0,53,5394137.0,49.0,12.0,1,2005-10-09 14:00:00 +18824,748,13,8,14.0,6,6.0,6,3.0,53,5373813.0,18.0,8.0,1,2005-10-09 14:00:00 +18825,749,21,5,2.0,8,12.0,12,0.0,56,6086418.0,18.0,13.0,1,2005-10-16 14:00:00 +18826,749,30,0,10.0,5,,19,0.0,24,,15.0,8.0,5,2005-10-16 14:00:00 +18827,749,38,16,19.0,15,,18,0.0,28,,17.0,20.0,3,2005-10-16 14:00:00 +18828,749,10,15,4.0,17,,17,0.0,34,,17.0,15.0,6,2005-10-16 14:00:00 +18829,749,26,17,21.0,18,16.0,16,0.0,50,,48.0,19.0,61,2005-10-16 14:00:00 +18830,749,14,6,16.0,12,15.0,15,0.0,55,,16.0,14.0,11,2005-10-16 14:00:00 +18831,749,37,17,20.0,20,14.0,14,0.0,55,,54.0,18.0,60,2005-10-16 14:00:00 +18832,749,41,2,8.0,13,13.0,13,0.0,55,,52.0,9.0,59,2005-10-16 14:00:00 +18833,749,32,16,18.0,19,11.0,11,0.0,56,6078218.0,13.0,17.0,1,2005-10-16 14:00:00 +18834,749,29,5,1.0,6,,20,0.0,20,,16.0,16.0,20,2005-10-16 14:00:00 +18835,749,13,8,14.0,7,9.0,9,0.0,56,6037818.0,54.0,10.0,1,2005-10-16 14:00:00 +18836,749,17,15,3.0,4,8.0,8,1.0,56,6034818.0,53.0,12.0,1,2005-10-16 14:00:00 +18837,749,16,2,7.0,10,7.0,7,2.0,56,6030418.0,53.0,7.0,1,2005-10-16 14:00:00 +18838,749,12,14,12.0,11,6.0,6,3.0,56,6030018.0,43.0,6.0,1,2005-10-16 14:00:00 +18839,749,31,8,15.0,14,5.0,5,4.0,56,6025418.0,43.0,4.0,1,2005-10-16 14:00:00 +18840,749,20,3,6.0,2,4.0,4,5.0,56,6019718.0,54.0,3.0,1,2005-10-16 14:00:00 +18841,749,22,6,17.0,9,3.0,3,6.0,56,6018918.0,44.0,5.0,1,2005-10-16 14:00:00 +18842,749,7,0,9.0,3,2.0,2,8.0,56,5997618.0,56.0,1.0,1,2005-10-16 14:00:00 +18843,749,34,14,11.0,16,10.0,10,0.0,56,6053518.0,53.0,11.0,1,2005-10-16 14:00:00 +18844,749,3,3,5.0,1,1.0,1,10.0,56,5993618.0,45.0,2.0,1,2005-10-16 14:00:00 +18845,750,21,10,11.0,6,15.0,15,0.0,56,,14.0,15.0,11,2006-03-12 14:30:00 +18846,750,14,6,8.0,14,16.0,16,0.0,56,,24.0,18.0,11,2006-03-12 14:30:00 +18847,750,32,12,18.0,19,17.0,17,0.0,55,,41.0,19.0,12,2006-03-12 14:30:00 +18848,750,10,7,22.0,20,18.0,18,0.0,53,,17.0,20.0,14,2006-03-12 14:30:00 +18849,750,26,12,19.0,18,,22,0.0,0,,,,30,2006-03-12 14:30:00 +18850,750,34,1,17.0,11,,20,0.0,29,,20.0,13.0,5,2006-03-12 14:30:00 +18851,750,20,3,2.0,9,,21,0.0,21,,15.0,17.0,9,2006-03-12 14:30:00 +18852,750,22,6,7.0,17,14.0,14,0.0,56,,25.0,16.0,11,2006-03-12 14:30:00 +18853,750,33,7,23.0,21,,19,0.0,35,,11.0,21.0,26,2006-03-12 14:30:00 +18854,750,25,4,21.0,16,13.0,13,0.0,56,,45.0,9.0,11,2006-03-12 14:30:00 +18855,750,1,1,16.0,10,12.0,12,0.0,56,,26.0,14.0,11,2006-03-12 14:30:00 +18856,750,23,4,20.0,15,11.0,11,0.0,57,5472202.0,26.0,12.0,1,2006-03-12 14:30:00 +18857,750,29,5,5.0,1,2.0,2,8.0,57,5387451.0,38.0,2.0,1,2006-03-12 14:30:00 +18858,750,7,0,3.0,22,3.0,3,6.0,57,5405565.0,29.0,8.0,1,2006-03-12 14:30:00 +18859,750,17,10,12.0,3,4.0,4,5.0,57,5406197.0,39.0,5.0,1,2006-03-12 14:30:00 +18860,750,30,0,4.0,5,5.0,5,4.0,57,5423253.0,21.0,7.0,1,2006-03-12 14:30:00 +18861,750,3,3,1.0,4,1.0,1,10.0,57,5386205.0,21.0,3.0,1,2006-03-12 14:30:00 +18862,750,2,2,10.0,12,7.0,7,2.0,57,5449248.0,42.0,1.0,1,2006-03-12 14:30:00 +18863,750,31,8,15.0,8,8.0,8,1.0,57,5452976.0,40.0,10.0,1,2006-03-12 14:30:00 +18864,750,12,5,6.0,2,9.0,9,0.0,57,5456112.0,28.0,6.0,1,2006-03-12 14:30:00 +18865,750,13,8,14.0,13,10.0,10,0.0,57,5461746.0,26.0,11.0,1,2006-03-12 14:30:00 +18866,750,16,2,9.0,7,6.0,6,3.0,57,5428137.0,25.0,4.0,1,2006-03-12 14:30:00 +18867,751,10,7,22.0,17,14.0,14,0.0,53,,14.0,20.0,13,2006-03-19 15:00:00 +18868,751,7,0,3.0,6,,22,0.0,0,,,,3,2006-03-19 15:00:00 +18869,751,2,2,10.0,3,,21,0.0,6,,6.0,15.0,5,2006-03-19 15:00:00 +18870,751,13,8,14.0,19,,20,0.0,10,,4.0,17.0,9,2006-03-19 15:00:00 +18871,751,16,2,9.0,4,,19,0.0,15,,12.0,12.0,9,2006-03-19 15:00:00 +18872,751,31,8,15.0,8,,18,0.0,26,,14.0,13.0,9,2006-03-19 15:00:00 +18873,751,33,7,23.0,18,,17,0.0,33,,18.0,21.0,26,2006-03-19 15:00:00 +18874,751,25,4,21.0,12,,16,0.0,41,,25.0,14.0,8,2006-03-19 15:00:00 +18875,751,1,1,16.0,11,,15,0.0,48,,41.0,7.0,5,2006-03-19 15:00:00 +18876,751,32,12,18.0,16,13.0,13,0.0,54,,39.0,19.0,12,2006-03-19 15:00:00 +18877,751,20,3,2.0,1,1.0,1,10.0,56,5440529.0,16.0,2.0,1,2006-03-19 15:00:00 +18878,751,23,4,20.0,13,11.0,11,0.0,54,,40.0,16.0,12,2006-03-19 15:00:00 +18879,751,21,10,11.0,20,10.0,10,0.0,55,,54.0,10.0,11,2006-03-19 15:00:00 +18880,751,14,6,8.0,9,9.0,9,0.0,55,,52.0,11.0,11,2006-03-19 15:00:00 +18881,751,22,6,7.0,22,8.0,8,1.0,56,5521817.0,34.0,6.0,1,2006-03-19 15:00:00 +18882,751,34,1,17.0,10,7.0,7,2.0,56,5520990.0,43.0,9.0,1,2006-03-19 15:00:00 +18883,751,29,5,5.0,14,6.0,6,3.0,56,5484383.0,44.0,5.0,1,2006-03-19 15:00:00 +18884,751,12,5,6.0,21,5.0,5,4.0,56,5483783.0,51.0,8.0,1,2006-03-19 15:00:00 +18885,751,30,0,4.0,5,4.0,4,5.0,56,5479880.0,39.0,3.0,1,2006-03-19 15:00:00 +18886,751,17,10,12.0,2,3.0,3,6.0,56,5450160.0,35.0,4.0,1,2006-03-19 15:00:00 +18887,751,3,3,1.0,7,2.0,2,8.0,56,5445114.0,45.0,1.0,1,2006-03-19 15:00:00 +18888,751,26,12,19.0,15,12.0,12,0.0,54,,34.0,18.0,12,2006-03-19 15:00:00 +18889,752,30,0,4.0,5,,14,0.0,46,,45.0,4.0,10,2006-04-02 14:00:00 +18890,752,32,12,18.0,20,,15,0.0,39,,31.0,16.0,26,2006-04-02 14:00:00 +18891,752,23,4,20.0,12,,16,0.0,37,,25.0,11.0,3,2006-04-02 14:00:00 +18892,752,29,5,5.0,10,,17,0.0,32,,27.0,3.0,3,2006-04-02 14:00:00 +18893,752,12,5,6.0,15,,22,0.0,0,,,,3,2006-04-02 14:00:00 +18894,752,31,8,15.0,13,,19,0.0,4,,4.0,19.0,3,2006-04-02 14:00:00 +18895,752,33,7,23.0,22,13.0,13,0.0,54,,49.0,18.0,13,2006-04-02 14:00:00 +18896,752,2,2,10.0,14,,21,0.0,0,,,,3,2006-04-02 14:00:00 +18897,752,16,2,9.0,7,,18,0.0,22,,19.0,9.0,7,2006-04-02 14:00:00 +18898,752,10,7,22.0,21,12.0,12,0.0,55,,54.0,17.0,12,2006-04-02 14:00:00 +18899,752,14,6,8.0,9,,20,0.0,0,,,,3,2006-04-02 14:00:00 +18900,752,17,10,12.0,1,10.0,10,0.0,56,,17.0,8.0,11,2006-04-02 14:00:00 +18901,752,3,3,1.0,3,1.0,1,10.0,57,5667870.0,49.0,2.0,1,2006-04-02 14:00:00 +18902,752,7,0,3.0,4,2.0,2,8.0,57,5669670.0,57.0,1.0,1,2006-04-02 14:00:00 +18903,752,22,6,7.0,6,3.0,3,6.0,57,5692670.0,45.0,10.0,1,2006-04-02 14:00:00 +18904,752,1,1,16.0,8,4.0,4,5.0,57,5698870.0,49.0,7.0,1,2006-04-02 14:00:00 +18905,752,26,12,19.0,17,11.0,11,0.0,56,,53.0,15.0,11,2006-04-02 14:00:00 +18906,752,34,1,17.0,19,6.0,6,3.0,57,5717370.0,56.0,13.0,1,2006-04-02 14:00:00 +18907,752,21,10,11.0,16,7.0,7,2.0,57,5719770.0,32.0,6.0,1,2006-04-02 14:00:00 +18908,752,13,8,14.0,11,8.0,8,1.0,57,5721770.0,32.0,12.0,1,2006-04-02 14:00:00 +18909,752,25,4,21.0,18,9.0,9,0.0,57,5746670.0,26.0,14.0,1,2006-04-02 14:00:00 +18910,752,20,3,2.0,2,5.0,5,4.0,57,5705970.0,53.0,5.0,1,2006-04-02 14:00:00 +18911,753,23,4,20.0,16,14.0,14,0.0,61,,43.0,11.0,11,2006-04-23 14:00:00 +18912,753,26,12,19.0,20,,22,0.0,0,,,,3,2006-04-23 14:00:00 +18913,753,14,6,8.0,9,,21,0.0,5,,4.0,19.0,38,2006-04-23 14:00:00 +18914,753,33,7,23.0,22,,20,0.0,23,,15.0,21.0,22,2006-04-23 14:00:00 +18915,753,31,8,15.0,17,,19,0.0,40,,30.0,16.0,9,2006-04-23 14:00:00 +18916,753,10,7,22.0,21,,18,0.0,44,,40.0,20.0,20,2006-04-23 14:00:00 +18917,753,13,8,14.0,14,,17,0.0,47,,41.0,17.0,30,2006-04-23 14:00:00 +18918,753,32,12,18.0,19,16.0,16,0.0,60,,53.0,18.0,12,2006-04-23 14:00:00 +18919,753,25,4,21.0,18,15.0,15,0.0,61,,57.0,14.0,11,2006-04-23 14:00:00 +18920,753,1,1,16.0,15,13.0,13,0.0,61,,53.0,12.0,11,2006-04-23 14:00:00 +18921,753,34,1,17.0,12,12.0,12,0.0,62,5548856.0,53.0,8.0,1,2006-04-23 14:00:00 +18922,753,2,2,10.0,13,11.0,11,0.0,62,5546161.0,30.0,15.0,1,2006-04-23 14:00:00 +18923,753,3,3,1.0,5,2.0,2,8.0,62,5468582.0,23.0,1.0,1,2006-04-23 14:00:00 +18924,753,30,0,4.0,7,3.0,3,6.0,62,5482354.0,22.0,4.0,1,2006-04-23 14:00:00 +18925,753,12,5,6.0,4,4.0,4,5.0,62,5483582.0,12.0,10.0,1,2006-04-23 14:00:00 +18926,753,7,0,3.0,8,5.0,5,4.0,62,5484010.0,49.0,3.0,1,2006-04-23 14:00:00 +18927,753,29,5,5.0,1,1.0,1,10.0,62,5466486.0,19.0,2.0,1,2006-04-23 14:00:00 +18928,753,17,10,12.0,2,7.0,7,2.0,62,5506121.0,29.0,6.0,1,2006-04-23 14:00:00 +18929,753,20,3,2.0,11,8.0,8,1.0,62,5506686.0,43.0,7.0,1,2006-04-23 14:00:00 +18930,753,22,6,7.0,6,9.0,9,0.0,62,5511997.0,45.0,5.0,1,2006-04-23 14:00:00 +18931,753,21,10,11.0,3,10.0,10,0.0,62,5544337.0,12.0,13.0,1,2006-04-23 14:00:00 +18932,753,16,2,9.0,10,6.0,6,3.0,62,5504225.0,39.0,9.0,1,2006-04-23 14:00:00 +18933,754,22,6,7.0,10,,14,0.0,52,,27.0,8.0,5,2006-05-07 14:00:00 +18934,754,23,4,20.0,14,,22,0.0,0,,,,3,2006-05-07 14:00:00 +18935,754,13,8,14.0,12,,21,0.0,2,,2.0,21.0,3,2006-05-07 14:00:00 +18936,754,16,2,9.0,19,,20,0.0,12,,11.0,16.0,9,2006-05-07 14:00:00 +18937,754,31,8,15.0,15,,19,0.0,28,,16.0,15.0,6,2006-05-07 14:00:00 +18938,754,17,10,12.0,6,,18,0.0,28,,9.0,13.0,5,2006-05-07 14:00:00 +18939,754,35,7,23.0,21,,17,0.0,29,,21.0,20.0,9,2006-05-07 14:00:00 +18940,754,10,7,22.0,20,,16,0.0,45,,26.0,19.0,9,2006-05-07 14:00:00 +18941,754,30,0,4.0,8,,15,0.0,52,,47.0,6.0,5,2006-05-07 14:00:00 +18942,754,26,12,19.0,16,13.0,13,0.0,59,,35.0,17.0,11,2006-05-07 14:00:00 +18943,754,29,5,5.0,2,1.0,1,10.0,60,5758765.0,39.0,1.0,1,2006-05-07 14:00:00 +18944,754,25,4,21.0,17,11.0,11,0.0,59,,57.0,14.0,11,2006-05-07 14:00:00 +18945,754,1,1,16.0,13,10.0,10,0.0,59,,47.0,11.0,11,2006-05-07 14:00:00 +18946,754,14,6,8.0,7,9.0,9,0.0,59,,58.0,10.0,11,2006-05-07 14:00:00 +18947,754,34,1,17.0,9,8.0,8,1.0,60,5848129.0,38.0,12.0,1,2006-05-07 14:00:00 +18948,754,2,2,10.0,22,7.0,7,2.0,60,5833330.0,48.0,7.0,1,2006-05-07 14:00:00 +18949,754,20,3,2.0,11,6.0,6,3.0,60,5832881.0,46.0,4.0,1,2006-05-07 14:00:00 +18950,754,21,10,11.0,4,5.0,5,4.0,60,5831351.0,59.0,9.0,1,2006-05-07 14:00:00 +18951,754,7,0,3.0,5,4.0,4,5.0,60,5763644.0,43.0,2.0,1,2006-05-07 14:00:00 +18952,754,12,5,6.0,3,3.0,3,6.0,60,5763212.0,19.0,5.0,1,2006-05-07 14:00:00 +18953,754,3,3,1.0,1,2.0,2,8.0,60,5762516.0,37.0,3.0,1,2006-05-07 14:00:00 +18954,754,32,12,18.0,18,12.0,12,0.0,59,,41.0,18.0,11,2006-05-07 14:00:00 +18955,755,23,4,20.0,15,15.0,15,0.0,63,,52.0,14.0,9,2006-05-14 14:00:00 +18956,755,32,12,18.0,17,16.0,16,0.0,63,,28.0,18.0,13,2006-05-14 14:00:00 +18957,755,10,7,22.0,19,17.0,17,0.0,62,,42.0,21.0,14,2006-05-14 14:00:00 +18958,755,13,8,14.0,21,14.0,14,0.0,65,,55.0,9.0,11,2006-05-14 14:00:00 +18959,755,35,7,23.0,20,,22,0.0,10,,9.0,22.0,30,2006-05-14 14:00:00 +18960,755,25,4,21.0,16,,19,0.0,47,,41.0,16.0,5,2006-05-14 14:00:00 +18961,755,22,6,7.0,6,,20,0.0,31,,24.0,17.0,40,2006-05-14 14:00:00 +18962,755,30,0,4.0,12,,21,0.0,17,,17.0,19.0,20,2006-05-14 14:00:00 +18963,755,26,12,19.0,18,,18,0.0,48,,28.0,20.0,41,2006-05-14 14:00:00 +18964,755,31,8,15.0,14,13.0,13,0.0,65,,59.0,15.0,11,2006-05-14 14:00:00 +18965,755,17,10,12.0,8,6.0,6,3.0,66,5240106.0,40.0,6.0,1,2006-05-14 14:00:00 +18966,755,2,2,10.0,13,11.0,11,0.0,65,,51.0,8.0,11,2006-05-14 14:00:00 +18967,755,14,6,8.0,7,10.0,10,0.0,65,,42.0,13.0,11,2006-05-14 14:00:00 +18968,755,16,2,9.0,11,9.0,9,0.0,65,,61.0,11.0,11,2006-05-14 14:00:00 +18969,755,1,1,16.0,10,8.0,8,1.0,65,,49.0,10.0,11,2006-05-14 14:00:00 +18970,755,21,10,11.0,5,7.0,7,2.0,65,,40.0,7.0,11,2006-05-14 14:00:00 +18971,755,7,0,3.0,9,5.0,5,4.0,66,5238634.0,40.0,5.0,1,2006-05-14 14:00:00 +18972,755,12,5,6.0,4,4.0,4,5.0,66,5211612.0,42.0,1.0,1,2006-05-14 14:00:00 +18973,755,20,3,2.0,2,3.0,3,6.0,66,5205710.0,38.0,4.0,1,2006-05-14 14:00:00 +18974,755,29,5,5.0,3,2.0,2,8.0,66,5200261.0,43.0,3.0,1,2006-05-14 14:00:00 +18975,755,3,3,1.0,1,1.0,1,10.0,66,5181759.0,39.0,2.0,1,2006-05-14 14:00:00 +18976,755,34,1,17.0,22,12.0,12,0.0,65,,62.0,12.0,11,2006-05-14 14:00:00 +18977,756,34,1,17.0,14,14.0,14,0.0,77,,74.0,18.0,11,2006-05-28 14:00:00 +18978,756,32,12,18.0,17,15.0,15,0.0,76,,71.0,13.0,12,2006-05-28 14:00:00 +18979,756,35,7,23.0,20,16.0,16,0.0,75,,72.0,22.0,13,2006-05-28 14:00:00 +18980,756,10,7,22.0,19,,22,0.0,46,,39.0,21.0,10,2006-05-28 14:00:00 +18981,756,2,2,10.0,8,,19,0.0,51,,43.0,9.0,3,2006-05-28 14:00:00 +18982,756,7,0,3.0,3,,20,0.0,50,,19.0,2.0,42,2006-05-28 14:00:00 +18983,756,16,2,9.0,2,,21,0.0,48,,23.0,4.0,43,2006-05-28 14:00:00 +18984,756,25,4,21.0,18,13.0,13,0.0,77,,77.0,14.0,11,2006-05-28 14:00:00 +18985,756,31,8,15.0,11,,18,0.0,56,,19.0,20.0,7,2006-05-28 14:00:00 +18986,756,26,12,19.0,16,12.0,12,0.0,77,,77.0,16.0,11,2006-05-28 14:00:00 +18987,756,14,6,8.0,6,17.0,17,0.0,72,,30.0,8.0,9,2006-05-28 14:00:00 +18988,756,23,4,20.0,12,10.0,10,0.0,77,,75.0,17.0,11,2006-05-28 14:00:00 +18989,756,17,10,12.0,13,11.0,11,0.0,77,,59.0,10.0,11,2006-05-28 14:00:00 +18990,756,30,0,4.0,4,2.0,2,8.0,78,6237683.0,20.0,6.0,1,2006-05-28 14:00:00 +18991,756,13,8,14.0,7,3.0,3,6.0,78,6275414.0,45.0,19.0,1,2006-05-28 14:00:00 +18992,756,21,10,11.0,5,4.0,4,5.0,78,6276453.0,67.0,12.0,1,2006-05-28 14:00:00 +18993,756,3,3,1.0,1,1.0,1,10.0,78,6223116.0,11.0,3.0,1,2006-05-28 14:00:00 +18994,756,20,3,2.0,9,6.0,6,3.0,78,6285188.0,58.0,5.0,1,2006-05-28 14:00:00 +18995,756,1,1,16.0,15,7.0,7,2.0,77,,72.0,11.0,11,2006-05-28 14:00:00 +18996,756,22,6,7.0,10,8.0,8,1.0,77,,72.0,15.0,11,2006-05-28 14:00:00 +18997,756,12,5,6.0,21,9.0,9,0.0,77,,40.0,7.0,11,2006-05-28 14:00:00 +18998,756,29,5,5.0,22,5.0,5,4.0,78,6276946.0,74.0,1.0,1,2006-05-28 14:00:00 +18999,757,23,4,20.0,13,13.0,13,0.0,59,,25.0,15.0,11,2006-06-11 12:00:00 +19000,757,25,4,21.0,15,,20,0.0,1,,,,3,2006-06-11 12:00:00 +19001,757,17,10,12.0,19,,19,0.0,8,,8.0,17.0,44,2006-06-11 12:00:00 +19002,757,35,7,23.0,21,18.0,18,0.0,57,,26.0,19.0,13,2006-06-11 12:00:00 +19003,757,10,7,22.0,20,17.0,17,0.0,57,,23.0,18.0,13,2006-06-11 12:00:00 +19004,757,32,12,18.0,16,16.0,16,0.0,58,,25.0,16.0,12,2006-06-11 12:00:00 +19005,757,26,12,19.0,18,15.0,15,0.0,59,,27.0,13.0,11,2006-06-11 12:00:00 +19006,757,31,8,15.0,14,14.0,14,0.0,59,,30.0,12.0,11,2006-06-11 12:00:00 +19007,757,13,8,14.0,11,12.0,12,0.0,59,,42.0,14.0,11,2006-06-11 12:00:00 +19008,757,30,0,4.0,8,6.0,6,3.0,60,5216696.0,38.0,8.0,1,2006-06-11 12:00:00 +19009,757,21,10,11.0,6,10.0,10,0.0,59,,38.0,11.0,11,2006-06-11 12:00:00 +19010,757,2,2,10.0,12,9.0,9,0.0,60,5230935.0,47.0,9.0,1,2006-06-11 12:00:00 +19011,757,34,1,17.0,10,8.0,8,1.0,60,5230226.0,46.0,10.0,1,2006-06-11 12:00:00 +19012,757,1,1,16.0,9,7.0,7,2.0,60,5226521.0,43.0,6.0,1,2006-06-11 12:00:00 +19013,757,12,5,6.0,4,5.0,5,4.0,60,5183486.0,43.0,4.0,1,2006-06-11 12:00:00 +19014,757,22,6,7.0,7,,21,0.0,0,,,,3,2006-06-11 12:00:00 +19015,757,7,0,3.0,2,3.0,3,6.0,60,5170599.0,15.0,5.0,1,2006-06-11 12:00:00 +19016,757,29,5,5.0,3,2.0,2,8.0,60,5165878.0,53.0,2.0,1,2006-06-11 12:00:00 +19017,757,3,3,1.0,1,1.0,1,10.0,60,5151927.0,21.0,1.0,1,2006-06-11 12:00:00 +19018,757,14,6,8.0,22,11.0,11,0.0,59,,19.0,7.0,11,2006-06-11 12:00:00 +19019,757,16,2,9.0,17,,22,0.0,0,,,,3,2006-06-11 12:00:00 +19020,757,20,3,2.0,5,4.0,4,5.0,60,5171903.0,42.0,3.0,1,2006-06-11 12:00:00 +19021,758,34,1,17.0,11,,16,0.0,58,,29.0,6.0,3,2006-06-25 13:00:00 +19022,758,2,2,10.0,6,,21,0.0,1,,,,3,2006-06-25 13:00:00 +19023,758,26,12,19.0,19,,22,0.0,0,,,,3,2006-06-25 13:00:00 +19024,758,30,0,4.0,7,,18,0.0,13,,5.0,15.0,3,2006-06-25 13:00:00 +19025,758,22,6,7.0,14,,17,0.0,58,,19.0,16.0,31,2006-06-25 13:00:00 +19026,758,10,7,22.0,20,15.0,15,0.0,64,,40.0,19.0,3,2006-06-25 13:00:00 +19027,758,32,12,18.0,18,14.0,14,0.0,66,,5.0,18.0,14,2006-06-25 13:00:00 +19028,758,23,4,20.0,15,13.0,13,0.0,68,,50.0,14.0,12,2006-06-25 13:00:00 +19029,758,16,2,9.0,16,12.0,12,0.0,69,,17.0,11.0,11,2006-06-25 13:00:00 +19030,758,31,8,15.0,12,11.0,11,0.0,69,,55.0,9.0,11,2006-06-25 13:00:00 +19031,758,25,4,21.0,17,10.0,10,0.0,69,,52.0,12.0,11,2006-06-25 13:00:00 +19032,758,17,10,12.0,8,9.0,9,0.0,69,,21.0,13.0,11,2006-06-25 13:00:00 +19033,758,13,8,14.0,22,8.0,8,1.0,69,,39.0,10.0,11,2006-06-25 13:00:00 +19034,758,1,1,16.0,13,7.0,7,2.0,69,,52.0,7.0,11,2006-06-25 13:00:00 +19035,758,14,6,8.0,4,6.0,6,3.0,69,,15.0,8.0,11,2006-06-25 13:00:00 +19036,758,12,5,6.0,10,5.0,5,4.0,70,5702408.0,31.0,5.0,1,2006-06-25 13:00:00 +19037,758,20,3,2.0,2,4.0,4,5.0,70,5692908.0,49.0,4.0,1,2006-06-25 13:00:00 +19038,758,7,0,3.0,3,3.0,3,6.0,70,5686108.0,22.0,1.0,1,2006-06-25 13:00:00 +19039,758,29,5,5.0,5,2.0,2,8.0,70,5679408.0,68.0,3.0,1,2006-06-25 13:00:00 +19040,758,3,3,1.0,1,1.0,1,10.0,70,5677308.0,22.0,2.0,1,2006-06-25 13:00:00 +19041,758,35,7,23.0,21,,20,0.0,2,,2.0,20.0,5,2006-06-25 13:00:00 +19042,758,21,10,11.0,9,,19,0.0,11,,10.0,17.0,26,2006-06-25 13:00:00 +19043,759,35,7,23.0,19,,22,0.0,0,,,,3,2006-07-02 14:00:00 +19044,759,31,8,15.0,16,,21,0.0,0,,,,3,2006-07-02 14:00:00 +19045,759,25,4,21.0,13,,20,0.0,0,,,,3,2006-07-02 14:00:00 +19046,759,12,5,6.0,2,2.0,2,8.0,73,5683183.0,29.0,2.0,1,2006-07-02 14:00:00 +19047,759,16,2,9.0,12,,19,0.0,0,,,,3,2006-07-02 14:00:00 +19048,759,30,0,4.0,11,,18,0.0,0,,,,3,2006-07-02 14:00:00 +19049,759,1,1,16.0,10,,17,0.0,0,,,,3,2006-07-02 14:00:00 +19050,759,7,0,3.0,9,,16,0.0,0,,,,3,2006-07-02 14:00:00 +19051,759,29,5,5.0,1,1.0,1,10.0,73,5675199.0,56.0,1.0,1,2006-07-02 14:00:00 +19052,759,10,7,22.0,18,,14,0.0,6,,6.0,14.0,3,2006-07-02 14:00:00 +19053,759,32,12,18.0,15,,13,0.0,9,,9.0,13.0,3,2006-07-02 14:00:00 +19054,759,34,1,17.0,6,,12,0.0,23,,19.0,8.0,5,2006-07-02 14:00:00 +19055,759,26,12,19.0,14,,11,0.0,37,,34.0,12.0,7,2006-07-02 14:00:00 +19056,759,17,10,12.0,7,,15,0.0,3,,2.0,15.0,3,2006-07-02 14:00:00 +19057,759,2,2,10.0,21,9.0,9,0.0,72,,42.0,10.0,11,2006-07-02 14:00:00 +19058,759,23,4,20.0,20,8.0,8,1.0,72,,41.0,9.0,11,2006-07-02 14:00:00 +19059,759,13,8,14.0,17,7.0,7,2.0,72,,33.0,11.0,11,2006-07-02 14:00:00 +19060,759,21,10,11.0,4,6.0,6,3.0,73,5711712.0,47.0,7.0,1,2006-07-02 14:00:00 +19061,759,3,3,1.0,5,5.0,5,4.0,73,5703609.0,72.0,6.0,1,2006-07-02 14:00:00 +19062,759,14,6,8.0,22,4.0,4,5.0,73,5698803.0,37.0,5.0,1,2006-07-02 14:00:00 +19063,759,20,3,2.0,3,3.0,3,6.0,73,5691794.0,28.0,3.0,1,2006-07-02 14:00:00 +19064,759,22,6,7.0,8,,10,0.0,62,,29.0,4.0,45,2006-07-02 14:00:00 +19065,760,26,12,19.0,15,15.0,15,0.0,68,,67.0,18.0,12,2006-07-16 14:00:00 +19066,760,35,7,23.0,20,16.0,16,0.0,67,,53.0,20.0,13,2006-07-16 14:00:00 +19067,760,17,10,12.0,17,,17,0.0,61,,47.0,11.0,39,2006-07-16 14:00:00 +19068,760,16,2,9.0,10,,18,0.0,55,,34.0,15.0,46,2006-07-16 14:00:00 +19069,760,10,7,22.0,21,,22,0.0,0,,,,7,2006-07-16 14:00:00 +19070,760,21,10,11.0,13,,20,0.0,28,,16.0,19.0,5,2006-07-16 14:00:00 +19071,760,32,12,18.0,19,,21,0.0,11,,8.0,21.0,26,2006-07-16 14:00:00 +19072,760,2,2,10.0,18,14.0,14,0.0,68,,62.0,13.0,12,2006-07-16 14:00:00 +19073,760,14,6,8.0,4,,19,0.0,39,,16.0,8.0,23,2006-07-16 14:00:00 +19074,760,23,4,20.0,22,13.0,13,0.0,69,,54.0,10.0,11,2006-07-16 14:00:00 +19075,760,20,3,2.0,7,6.0,6,3.0,70,5573003.0,20.0,9.0,1,2006-07-16 14:00:00 +19076,760,34,1,17.0,16,11.0,11,0.0,69,,56.0,7.0,11,2006-07-16 14:00:00 +19077,760,3,3,1.0,3,2.0,2,8.0,70,5537903.0,23.0,5.0,1,2006-07-16 14:00:00 +19078,760,12,5,6.0,2,3.0,3,6.0,70,5550303.0,18.0,2.0,1,2006-07-16 14:00:00 +19079,760,22,6,7.0,5,4.0,4,5.0,70,5555003.0,19.0,6.0,1,2006-07-16 14:00:00 +19080,760,7,0,3.0,6,5.0,5,4.0,70,5560803.0,30.0,4.0,1,2006-07-16 14:00:00 +19081,760,31,8,15.0,12,12.0,12,0.0,69,,56.0,16.0,11,2006-07-16 14:00:00 +19082,760,36,0,4.0,8,7.0,7,2.0,70,5577203.0,34.0,3.0,1,2006-07-16 14:00:00 +19083,760,1,1,16.0,11,8.0,8,1.0,69,,48.0,14.0,11,2006-07-16 14:00:00 +19084,760,13,8,14.0,9,9.0,9,0.0,69,,56.0,17.0,11,2006-07-16 14:00:00 +19085,760,25,4,21.0,14,10.0,10,0.0,69,,66.0,12.0,11,2006-07-16 14:00:00 +19086,760,29,5,5.0,1,1.0,1,10.0,70,5527803.0,46.0,1.0,1,2006-07-16 14:00:00 +19087,761,16,2,9.0,11,,13,0.0,59,,43.0,6.0,47,2006-07-30 14:00:00 +19088,761,26,12,19.0,21,,21,0.0,66,,35.0,15.0,2,2006-07-30 14:00:00 +19089,761,2,2,10.0,14,,20,0.0,0,,,,3,2006-07-30 14:00:00 +19090,761,28,7,23.0,22,,19,0.0,1,,,,30,2006-07-30 14:00:00 +19091,761,36,0,4.0,9,,18,0.0,2,,2.0,20.0,48,2006-07-30 14:00:00 +19092,761,1,1,16.0,15,,17,0.0,9,,3.0,18.0,23,2006-07-30 14:00:00 +19093,761,21,10,11.0,6,,16,0.0,18,,16.0,14.0,5,2006-07-30 14:00:00 +19094,761,34,1,17.0,13,,15,0.0,30,,29.0,17.0,3,2006-07-30 14:00:00 +19095,761,10,7,22.0,17,,14,0.0,38,,26.0,19.0,6,2006-07-30 14:00:00 +19096,761,32,12,18.0,18,,22,0.0,66,,46.0,16.0,2,2006-07-30 14:00:00 +19097,761,25,4,21.0,19,12.0,12,0.0,66,,50.0,11.0,11,2006-07-30 14:00:00 +19098,761,23,4,20.0,16,10.0,10,0.0,66,,51.0,10.0,11,2006-07-30 14:00:00 +19099,761,22,6,7.0,8,9.0,9,0.0,67,5331993.0,64.0,4.0,1,2006-07-30 14:00:00 +19100,761,31,8,15.0,12,8.0,8,1.0,67,5319793.0,49.0,12.0,1,2006-07-30 14:00:00 +19101,761,14,6,8.0,20,7.0,7,2.0,67,5298193.0,48.0,5.0,1,2006-07-30 14:00:00 +19102,761,20,3,2.0,5,6.0,6,3.0,67,5296493.0,18.0,8.0,1,2006-07-30 14:00:00 +19103,761,3,3,1.0,7,5.0,5,4.0,67,5295393.0,66.0,9.0,1,2006-07-30 14:00:00 +19104,761,17,10,12.0,4,4.0,4,5.0,67,5290493.0,14.0,7.0,1,2006-07-30 14:00:00 +19105,761,7,0,3.0,1,3.0,3,6.0,67,5284893.0,4.0,3.0,1,2006-07-30 14:00:00 +19106,761,12,5,6.0,3,2.0,2,8.0,67,5272393.0,18.0,2.0,1,2006-07-30 14:00:00 +19107,761,29,5,5.0,2,1.0,1,10.0,67,5271693.0,17.0,1.0,1,2006-07-30 14:00:00 +19108,761,13,8,14.0,10,11.0,11,0.0,66,,24.0,13.0,11,2006-07-30 14:00:00 +19109,762,3,3,1.0,15,,14,0.0,51,,50.0,14.0,30,2006-08-06 14:00:00 +19110,762,7,0,3.0,1,,15,0.0,25,,7.0,16.0,4,2006-08-06 14:00:00 +19111,762,23,4,20.0,17,,16,0.0,25,,8.0,19.0,4,2006-08-06 14:00:00 +19112,762,20,3,2.0,7,,18,0.0,18,,9.0,17.0,20,2006-08-06 14:00:00 +19113,762,10,7,22.0,19,13.0,13,0.0,65,,53.0,15.0,15,2006-08-06 14:00:00 +19114,762,16,2,9.0,5,,20,0.0,1,,,,3,2006-08-06 14:00:00 +19115,762,28,7,23.0,21,,21,0.0,0,,,,5,2006-08-06 14:00:00 +19116,762,8,1,17.0,9,,22,0.0,69,,55.0,12.0,2,2006-08-06 14:00:00 +19117,762,31,8,15.0,13,,19,0.0,6,,6.0,18.0,20,2006-08-06 14:00:00 +19118,762,14,6,8.0,8,12.0,12,0.0,65,,58.0,6.0,5,2006-08-06 14:00:00 +19119,762,2,2,10.0,18,,17,0.0,19,,9.0,20.0,10,2006-08-06 14:00:00 +19120,762,26,12,19.0,22,10.0,10,0.0,67,,67.0,8.0,13,2006-08-06 14:00:00 +19121,762,36,0,4.0,4,2.0,2,8.0,70,6771778.0,67.0,2.0,1,2006-08-06 14:00:00 +19122,762,1,1,16.0,10,3.0,3,6.0,70,6784763.0,65.0,7.0,1,2006-08-06 14:00:00 +19123,762,21,10,11.0,3,4.0,4,5.0,70,6786146.0,69.0,3.0,1,2006-08-06 14:00:00 +19124,762,13,8,14.0,12,5.0,5,4.0,69,,65.0,10.0,11,2006-08-06 14:00:00 +19125,762,25,4,21.0,20,11.0,11,0.0,66,,66.0,9.0,14,2006-08-06 14:00:00 +19126,762,17,10,12.0,14,1.0,1,10.0,70,6740941.0,57.0,4.0,1,2006-08-06 14:00:00 +19127,762,12,5,6.0,2,7.0,7,2.0,69,,65.0,1.0,11,2006-08-06 14:00:00 +19128,762,29,5,5.0,11,8.0,8,1.0,67,,57.0,11.0,49,2006-08-06 14:00:00 +19129,762,32,12,18.0,16,9.0,9,0.0,67,,66.0,13.0,13,2006-08-06 14:00:00 +19130,762,22,6,7.0,6,6.0,6,3.0,69,,65.0,5.0,11,2006-08-06 14:00:00 +19131,763,1,1,16.0,5,14.0,14,0.0,56,,56.0,16.0,12,2006-08-27 15:00:00 +19132,763,32,12,18.0,19,,22,0.0,0,,,,4,2006-08-27 15:00:00 +19133,763,7,0,3.0,7,,21,0.0,1,,,,4,2006-08-27 15:00:00 +19134,763,23,4,20.0,18,,20,0.0,12,,12.0,19.0,20,2006-08-27 15:00:00 +19135,763,28,7,23.0,20,,19,0.0,23,,12.0,20.0,20,2006-08-27 15:00:00 +19136,763,2,2,10.0,14,,18,0.0,25,,21.0,14.0,47,2006-08-27 15:00:00 +19137,763,10,7,22.0,21,,17,0.0,41,,33.0,18.0,50,2006-08-27 15:00:00 +19138,763,26,12,19.0,22,,16,0.0,46,,35.0,17.0,20,2006-08-27 15:00:00 +19139,763,13,8,14.0,16,15.0,15,0.0,55,,24.0,12.0,6,2006-08-27 15:00:00 +19140,763,25,4,21.0,17,13.0,13,0.0,57,,43.0,10.0,11,2006-08-27 15:00:00 +19141,763,8,1,17.0,8,12.0,12,0.0,57,,34.0,9.0,11,2006-08-27 15:00:00 +19142,763,31,8,15.0,10,11.0,11,0.0,57,,26.0,11.0,11,2006-08-27 15:00:00 +19143,763,3,3,1.0,3,2.0,2,8.0,58,5336657.0,38.0,3.0,1,2006-08-27 15:00:00 +19144,763,29,5,5.0,2,3.0,3,6.0,58,5336738.0,55.0,1.0,1,2006-08-27 15:00:00 +19145,763,17,10,12.0,6,4.0,4,5.0,58,5343416.0,58.0,4.0,1,2006-08-27 15:00:00 +19146,763,36,0,4.0,11,5.0,5,4.0,58,5376990.0,54.0,7.0,1,2006-08-27 15:00:00 +19147,763,12,5,6.0,1,1.0,1,10.0,58,5331082.0,38.0,2.0,1,2006-08-27 15:00:00 +19148,763,22,6,7.0,15,7.0,7,2.0,58,5390419.0,58.0,8.0,1,2006-08-27 15:00:00 +19149,763,21,10,11.0,13,8.0,8,1.0,58,5391116.0,26.0,6.0,1,2006-08-27 15:00:00 +19150,763,14,6,8.0,12,9.0,9,0.0,57,,24.0,13.0,11,2006-08-27 15:00:00 +19151,763,16,2,9.0,9,10.0,10,0.0,57,,50.0,15.0,11,2006-08-27 15:00:00 +19152,763,20,3,2.0,4,6.0,6,3.0,58,5377676.0,29.0,5.0,1,2006-08-27 15:00:00 +19153,764,23,4,20.0,17,14.0,14,0.0,52,,52.0,14.0,11,2006-09-10 14:00:00 +19154,764,2,2,10.0,12,,22,0.0,9,,8.0,19.0,30,2006-09-10 14:00:00 +19155,764,28,7,23.0,22,,21,0.0,18,,15.0,22.0,9,2006-09-10 14:00:00 +19156,764,36,0,4.0,7,,20,0.0,20,,8.0,9.0,5,2006-09-10 14:00:00 +19157,764,3,3,1.0,10,,19,0.0,43,,38.0,5.0,5,2006-09-10 14:00:00 +19158,764,32,13,18.0,20,,18,0.0,44,,27.0,15.0,23,2006-09-10 14:00:00 +19159,764,26,13,19.0,18,17.0,17,0.0,51,,17.0,20.0,12,2006-09-10 14:00:00 +19160,764,10,7,22.0,21,16.0,16,0.0,51,,15.0,21.0,12,2006-09-10 14:00:00 +19161,764,22,6,7.0,13,15.0,15,0.0,52,,41.0,16.0,11,2006-09-10 14:00:00 +19162,764,25,4,21.0,15,13.0,13,0.0,52,,50.0,18.0,11,2006-09-10 14:00:00 +19163,764,29,5,5.0,2,1.0,1,10.0,53,4491975.0,14.0,2.0,1,2006-09-10 14:00:00 +19164,764,31,8,15.0,16,11.0,11,0.0,52,,37.0,13.0,11,2006-09-10 14:00:00 +19165,764,16,2,9.0,19,10.0,10,0.0,53,4564577.0,27.0,12.0,1,2006-09-10 14:00:00 +19166,764,12,5,6.0,4,9.0,9,0.0,53,4537970.0,41.0,3.0,1,2006-09-10 14:00:00 +19167,764,1,1,16.0,3,8.0,8,1.0,53,4537284.0,20.0,6.0,1,2006-09-10 14:00:00 +19168,764,14,6,8.0,11,7.0,7,2.0,53,4536637.0,25.0,11.0,1,2006-09-10 14:00:00 +19169,764,21,10,11.0,8,6.0,6,3.0,53,4534384.0,27.0,10.0,1,2006-09-10 14:00:00 +19170,764,17,10,12.0,5,5.0,5,4.0,53,4524660.0,51.0,7.0,1,2006-09-10 14:00:00 +19171,764,20,3,2.0,9,4.0,4,5.0,53,4524020.0,25.0,8.0,1,2006-09-10 14:00:00 +19172,764,8,1,17.0,6,3.0,3,6.0,53,4518389.0,21.0,4.0,1,2006-09-10 14:00:00 +19173,764,7,0,3.0,1,2.0,2,8.0,53,4500021.0,13.0,1.0,1,2006-09-10 14:00:00 +19174,764,13,8,14.0,14,12.0,12,0.0,52,,51.0,17.0,11,2006-09-10 14:00:00 +19175,765,26,13,19.0,22,15.0,15,0.0,53,,50.0,17.0,13,2006-10-01 14:00:00 +19176,765,28,7,23.0,19,16.0,16,0.0,52,,42.0,19.0,14,2006-10-01 14:00:00 +19177,765,22,6,7.0,16,,17,0.0,49,,47.0,11.0,51,2006-10-01 14:00:00 +19178,765,12,5,6.0,20,,18,0.0,44,,42.0,7.0,4,2006-10-01 14:00:00 +19179,765,25,4,21.0,11,14.0,14,0.0,55,,49.0,8.0,11,2006-10-01 14:00:00 +19180,765,32,13,18.0,18,,20,0.0,37,,35.0,22.0,20,2006-10-01 14:00:00 +19181,765,7,0,3.0,5,,21,0.0,18,,14.0,20.0,37,2006-10-01 14:00:00 +19182,765,10,7,22.0,21,,22,0.0,55,,48.0,16.0,2,2006-10-01 14:00:00 +19183,765,14,6,8.0,17,,19,0.0,38,,24.0,21.0,63,2006-10-01 14:00:00 +19184,765,8,1,17.0,9,13.0,13,0.0,55,,51.0,13.0,11,2006-10-01 14:00:00 +19185,765,29,5,5.0,6,1.0,1,10.0,56,5852747.0,50.0,2.0,1,2006-10-01 14:00:00 +19186,765,2,2,10.0,15,11.0,11,0.0,55,,52.0,14.0,11,2006-10-01 14:00:00 +19187,765,3,3,1.0,1,2.0,2,8.0,56,5855868.0,49.0,1.0,1,2006-10-01 14:00:00 +19188,765,20,3,2.0,2,3.0,3,6.0,56,5896944.0,53.0,6.0,1,2006-10-01 14:00:00 +19189,765,17,10,12.0,4,4.0,4,5.0,56,5924803.0,51.0,5.0,1,2006-10-01 14:00:00 +19190,765,36,0,4.0,7,5.0,5,4.0,56,5929884.0,45.0,3.0,1,2006-10-01 14:00:00 +19191,765,37,8,15.0,10,12.0,12,0.0,55,,52.0,10.0,11,2006-10-01 14:00:00 +19192,765,1,1,16.0,8,7.0,7,2.0,56,5944726.0,53.0,4.0,1,2006-10-01 14:00:00 +19193,765,16,2,9.0,14,8.0,8,1.0,56,5956335.0,44.0,12.0,1,2006-10-01 14:00:00 +19194,765,13,8,14.0,12,9.0,9,0.0,56,5956543.0,52.0,15.0,1,2006-10-01 14:00:00 +19195,765,23,4,20.0,13,10.0,10,0.0,55,,53.0,18.0,11,2006-10-01 14:00:00 +19196,765,21,10,11.0,3,6.0,6,3.0,56,5931878.0,52.0,9.0,1,2006-10-01 14:00:00 +19197,766,37,8,15.0,18,13.0,13,0.0,52,,37.0,19.0,11,2006-10-08 14:00:00 +19198,766,13,8,14.0,17,,21,0.0,35,,20.0,16.0,6,2006-10-08 14:00:00 +19199,766,29,5,5.0,2,,20,0.0,36,,32.0,2.0,5,2006-10-08 14:00:00 +19200,766,16,2,9.0,14,,19,0.0,39,,19.0,18.0,3,2006-10-08 14:00:00 +19201,766,25,4,21.0,19,18.0,18,0.0,48,,37.0,14.0,38,2006-10-08 14:00:00 +19202,766,28,7,23.0,22,17.0,17,0.0,50,,22.0,21.0,13,2006-10-08 14:00:00 +19203,766,32,13,18.0,21,16.0,16,0.0,51,,27.0,20.0,12,2006-10-08 14:00:00 +19204,766,10,7,22.0,20,15.0,15,0.0,52,,26.0,17.0,11,2006-10-08 14:00:00 +19205,766,23,4,20.0,15,14.0,14,0.0,52,,22.0,12.0,11,2006-10-08 14:00:00 +19206,766,26,13,19.0,16,,22,0.0,20,,19.0,22.0,30,2006-10-08 14:00:00 +19207,766,21,10,11.0,8,12.0,12,0.0,52,,40.0,10.0,11,2006-10-08 14:00:00 +19208,766,2,2,10.0,10,10.0,10,0.0,52,,33.0,15.0,11,2006-10-08 14:00:00 +19209,766,8,1,17.0,12,9.0,9,0.0,53,5109345.0,39.0,6.0,1,2006-10-08 14:00:00 +19210,766,1,1,16.0,9,8.0,8,1.0,53,5108508.0,31.0,13.0,1,2006-10-08 14:00:00 +19211,766,22,6,7.0,3,7.0,7,2.0,53,5081282.0,2.0,8.0,1,2006-10-08 14:00:00 +19212,766,14,6,8.0,4,6.0,6,3.0,53,5079130.0,2.0,9.0,1,2006-10-08 14:00:00 +19213,766,7,0,3.0,11,5.0,5,4.0,53,5076009.0,24.0,4.0,1,2006-10-08 14:00:00 +19214,766,17,10,12.0,7,4.0,4,5.0,53,5066514.0,35.0,5.0,1,2006-10-08 14:00:00 +19215,766,20,3,2.0,6,3.0,3,6.0,53,5056366.0,13.0,7.0,1,2006-10-08 14:00:00 +19216,766,12,5,6.0,1,2.0,2,8.0,53,5048564.0,37.0,3.0,1,2006-10-08 14:00:00 +19217,766,3,3,1.0,5,1.0,1,10.0,53,5032413.0,14.0,1.0,1,2006-10-08 14:00:00 +19218,766,36,0,4.0,13,11.0,11,0.0,52,,22.0,11.0,11,2006-10-08 14:00:00 +19219,767,26,13,19.0,17,14.0,14,0.0,70,,61.0,17.0,11,2006-10-22 14:00:00 +19220,767,32,13,18.0,21,15.0,15,0.0,69,,38.0,16.0,12,2006-10-22 14:00:00 +19221,767,28,7,23.0,20,16.0,16,0.0,69,,67.0,7.0,12,2006-10-22 14:00:00 +19222,767,1,1,16.0,8,17.0,17,0.0,63,,18.0,15.0,3,2006-10-22 14:00:00 +19223,767,23,4,20.0,15,13.0,13,0.0,70,,69.0,10.0,11,2006-10-22 14:00:00 +19224,767,22,6,7.0,7,,20,0.0,9,,8.0,20.0,22,2006-10-22 14:00:00 +19225,767,16,2,9.0,11,,21,0.0,1,,,,4,2006-10-22 14:00:00 +19226,767,2,2,10.0,13,,22,0.0,0,,,,4,2006-10-22 14:00:00 +19227,767,13,8,14.0,18,,18,0.0,14,,12.0,19.0,6,2006-10-22 14:00:00 +19228,767,37,8,15.0,22,12.0,12,0.0,70,,62.0,11.0,11,2006-10-22 14:00:00 +19229,767,14,6,8.0,3,,19,0.0,10,,9.0,18.0,22,2006-10-22 14:00:00 +19230,767,10,7,22.0,19,10.0,10,0.0,70,,47.0,9.0,11,2006-10-22 14:00:00 +19231,767,12,5,6.0,1,1.0,1,10.0,71,5513751.0,23.0,2.0,1,2006-10-22 14:00:00 +19232,767,3,3,1.0,4,2.0,2,8.0,71,5532409.0,70.0,3.0,1,2006-10-22 14:00:00 +19233,767,17,10,12.0,14,3.0,3,6.0,71,5533145.0,71.0,4.0,1,2006-10-22 14:00:00 +19234,767,29,5,5.0,10,4.0,4,5.0,71,5537845.0,70.0,1.0,1,2006-10-22 14:00:00 +19235,767,25,4,21.0,16,11.0,11,0.0,70,,69.0,13.0,11,2006-10-22 14:00:00 +19236,767,20,3,2.0,6,6.0,6,3.0,71,5544038.0,70.0,5.0,1,2006-10-22 14:00:00 +19237,767,21,10,11.0,5,7.0,7,2.0,71,5554045.0,48.0,8.0,1,2006-10-22 14:00:00 +19238,767,36,0,4.0,12,8.0,8,1.0,71,5565819.0,63.0,12.0,1,2006-10-22 14:00:00 +19239,767,8,1,17.0,9,9.0,9,0.0,71,5581393.0,25.0,14.0,1,2006-10-22 14:00:00 +19240,767,7,0,3.0,2,5.0,5,4.0,71,5542254.0,58.0,6.0,1,2006-10-22 14:00:00 +19241,768,17,10,7.0,14,15.0,15,0.0,57,,42.0,17.0,11,2007-03-18 03:00:00 +19242,768,26,11,21.0,21,,22,0.0,10,,9.0,22.0,3,2007-03-18 03:00:00 +19243,768,25,4,19.0,17,,21,0.0,28,,22.0,21.0,29,2007-03-18 03:00:00 +19244,768,8,1,10.0,5,,20,0.0,36,,19.0,4.0,6,2007-03-18 03:00:00 +19245,768,13,8,14.0,18,,19,0.0,48,,44.0,11.0,4,2007-03-18 03:00:00 +19246,768,24,2,17.0,15,,18,0.0,48,,24.0,16.0,4,2007-03-18 03:00:00 +19247,768,15,11,20.0,20,17.0,17,0.0,56,,40.0,20.0,12,2007-03-18 03:00:00 +19248,768,18,7,23.0,11,16.0,16,0.0,56,,41.0,19.0,12,2007-03-18 03:00:00 +19249,768,23,4,18.0,19,14.0,14,0.0,57,,44.0,15.0,11,2007-03-18 03:00:00 +19250,768,16,8,15.0,7,13.0,13,0.0,57,,21.0,9.0,11,2007-03-18 03:00:00 +19251,768,3,0,1.0,2,2.0,2,8.0,58,5136012.0,20.0,2.0,1,2007-03-18 03:00:00 +19252,768,21,10,8.0,16,11.0,11,0.0,57,,17.0,14.0,11,2007-03-18 03:00:00 +19253,768,4,3,4.0,13,10.0,10,0.0,57,,44.0,10.0,11,2007-03-18 03:00:00 +19254,768,14,6,12.0,8,9.0,9,0.0,57,,45.0,13.0,11,2007-03-18 03:00:00 +19255,768,22,6,11.0,9,8.0,8,1.0,57,,42.0,12.0,11,2007-03-18 03:00:00 +19256,768,2,2,16.0,12,7.0,7,2.0,57,,40.0,5.0,11,2007-03-18 03:00:00 +19257,768,12,5,5.0,22,6.0,6,3.0,58,5195575.0,28.0,8.0,1,2007-03-18 03:00:00 +19258,768,20,3,3.0,6,5.0,5,4.0,58,5195239.0,18.0,7.0,1,2007-03-18 03:00:00 +19259,768,1,1,9.0,3,4.0,4,5.0,58,5167533.0,37.0,6.0,1,2007-03-18 03:00:00 +19260,768,0,0,2.0,4,3.0,3,6.0,58,5147365.0,20.0,3.0,1,2007-03-18 03:00:00 +19261,768,10,7,22.0,10,12.0,12,0.0,57,,20.0,18.0,11,2007-03-18 03:00:00 +19262,768,7,5,6.0,1,1.0,1,10.0,58,5128770.0,41.0,1.0,1,2007-03-18 03:00:00 +19263,769,22,6,11.0,9,15.0,15,0.0,55,,52.0,19.0,11,2007-04-08 07:00:00 +19264,769,18,7,23.0,18,16.0,16,0.0,55,,32.0,20.0,11,2007-04-08 07:00:00 +19265,769,23,4,18.0,16,17.0,17,0.0,55,,21.0,12.0,11,2007-04-08 07:00:00 +19266,769,8,1,10.0,7,18.0,18,0.0,55,,53.0,17.0,11,2007-04-08 07:00:00 +19267,769,25,4,19.0,17,14.0,14,0.0,55,,54.0,18.0,11,2007-04-08 07:00:00 +19268,769,13,8,14.0,13,,20,0.0,36,,28.0,11.0,23,2007-04-08 07:00:00 +19269,769,26,11,21.0,20,,21,0.0,7,,5.0,21.0,5,2007-04-08 07:00:00 +19270,769,15,11,20.0,21,,22,0.0,0,,,,4,2007-04-08 07:00:00 +19271,769,2,2,16.0,6,,19,0.0,42,,18.0,6.0,9,2007-04-08 07:00:00 +19272,769,10,7,22.0,14,13.0,13,0.0,55,,37.0,13.0,11,2007-04-08 07:00:00 +19273,769,0,0,2.0,4,2.0,2,8.0,56,5552487.0,22.0,1.0,1,2007-04-08 07:00:00 +19274,769,21,10,8.0,22,11.0,11,0.0,55,,32.0,15.0,11,2007-04-08 07:00:00 +19275,769,17,10,7.0,15,12.0,12,0.0,55,,54.0,16.0,11,2007-04-08 07:00:00 +19276,769,7,5,6.0,3,3.0,3,6.0,56,5553269.0,40.0,4.0,1,2007-04-08 07:00:00 +19277,769,1,1,9.0,5,4.0,4,5.0,56,5568707.0,55.0,5.0,1,2007-04-08 07:00:00 +19278,769,12,5,5.0,1,5.0,5,4.0,56,5571635.0,42.0,3.0,1,2007-04-08 07:00:00 +19279,769,3,0,1.0,2,1.0,1,10.0,56,5534930.0,42.0,2.0,1,2007-04-08 07:00:00 +19280,769,14,6,12.0,8,7.0,7,2.0,56,5605062.0,40.0,10.0,1,2007-04-08 07:00:00 +19281,769,4,3,4.0,11,8.0,8,1.0,56,5606945.0,41.0,7.0,1,2007-04-08 07:00:00 +19282,769,24,2,17.0,19,9.0,9,0.0,56,5624854.0,19.0,8.0,1,2007-04-08 07:00:00 +19283,769,16,8,15.0,10,10.0,10,0.0,56,5628486.0,55.0,14.0,1,2007-04-08 07:00:00 +19284,769,20,3,3.0,12,6.0,6,3.0,56,5600568.0,44.0,9.0,1,2007-04-08 07:00:00 +19285,770,26,11,21.0,22,14.0,14,0.0,55,,40.0,20.0,12,2007-04-15 11:30:00 +19286,770,25,4,19.0,19,,22,0.0,0,,,,4,2007-04-15 11:30:00 +19287,770,17,10,7.0,16,,21,0.0,0,,,,4,2007-04-15 11:30:00 +19288,770,23,4,18.0,18,,20,0.0,26,,23.0,13.0,9,2007-04-15 11:30:00 +19289,770,10,7,22.0,17,,19,0.0,34,,23.0,18.0,5,2007-04-15 11:30:00 +19290,770,13,8,14.0,21,,18,0.0,36,,34.0,9.0,30,2007-04-15 11:30:00 +19291,770,16,8,15.0,8,,17,0.0,41,,37.0,12.0,6,2007-04-15 11:30:00 +19292,770,18,7,23.0,13,16.0,16,0.0,51,,27.0,17.0,5,2007-04-15 11:30:00 +19293,770,15,11,20.0,20,15.0,15,0.0,53,,45.0,19.0,14,2007-04-15 11:30:00 +19294,770,21,10,8.0,15,13.0,13,0.0,56,,50.0,14.0,11,2007-04-15 11:30:00 +19295,770,0,0,2.0,2,2.0,2,8.0,57,5609875.0,18.0,2.0,1,2007-04-15 11:30:00 +19296,770,24,2,17.0,11,11.0,11,0.0,56,,27.0,16.0,11,2007-04-15 11:30:00 +19297,770,12,5,5.0,1,1.0,1,10.0,57,5607515.0,42.0,1.0,1,2007-04-15 11:30:00 +19298,770,7,5,6.0,3,3.0,3,6.0,57,5618354.0,39.0,3.0,1,2007-04-15 11:30:00 +19299,770,1,1,9.0,5,4.0,4,5.0,57,5621346.0,38.0,5.0,1,2007-04-15 11:30:00 +19300,770,3,0,1.0,4,5.0,5,4.0,57,5621941.0,46.0,4.0,1,2007-04-15 11:30:00 +19301,770,22,6,11.0,14,12.0,12,0.0,56,,37.0,15.0,11,2007-04-15 11:30:00 +19302,770,14,6,12.0,9,7.0,7,2.0,57,5688886.0,40.0,7.0,1,2007-04-15 11:30:00 +19303,770,20,3,3.0,7,8.0,8,1.0,57,5689216.0,51.0,8.0,1,2007-04-15 11:30:00 +19304,770,4,3,4.0,12,9.0,9,0.0,57,5696926.0,27.0,10.0,1,2007-04-15 11:30:00 +19305,770,2,2,16.0,10,10.0,10,0.0,57,5697431.0,51.0,11.0,1,2007-04-15 11:30:00 +19306,770,8,1,10.0,6,6.0,6,3.0,57,5653044.0,46.0,6.0,1,2007-04-15 11:30:00 +19307,771,15,11,20.0,20,13.0,13,0.0,63,,57.0,16.0,12,2007-05-13 12:00:00 +19308,771,16,8,15.0,19,,21,0.0,7,,4.0,21.0,9,2007-05-13 12:00:00 +19309,771,14,6,12.0,6,,20,0.0,8,,6.0,19.0,32,2007-05-13 12:00:00 +19310,771,7,5,6.0,3,,19,0.0,9,,7.0,6.0,22,2007-05-13 12:00:00 +19311,771,25,4,19.0,22,,18,0.0,9,,6.0,20.0,27,2007-05-13 12:00:00 +19312,771,23,4,18.0,16,,17,0.0,19,,18.0,17.0,31,2007-05-13 12:00:00 +19313,771,22,6,11.0,17,,16,0.0,44,,37.0,11.0,22,2007-05-13 12:00:00 +19314,771,1,1,9.0,7,,15,0.0,46,,22.0,7.0,6,2007-05-13 12:00:00 +19315,771,26,11,21.0,21,14.0,14,0.0,63,,61.0,18.0,12,2007-05-13 12:00:00 +19316,771,24,2,17.0,18,,22,0.0,1,,,,4,2007-05-13 12:00:00 +19317,771,21,10,8.0,12,10.0,10,0.0,64,,16.0,14.0,11,2007-05-13 12:00:00 +19318,771,18,7,23.0,15,11.0,11,0.0,64,,59.0,15.0,11,2007-05-13 12:00:00 +19319,771,20,3,3.0,10,9.0,9,0.0,64,,57.0,9.0,11,2007-05-13 12:00:00 +19320,771,10,7,22.0,13,8.0,8,1.0,64,,23.0,12.0,11,2007-05-13 12:00:00 +19321,771,4,3,4.0,8,7.0,7,2.0,65,5558358.0,32.0,4.0,1,2007-05-13 12:00:00 +19322,771,2,2,16.0,11,6.0,6,3.0,65,5555768.0,60.0,10.0,1,2007-05-13 12:00:00 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+19336,772,23,4,18.0,12,,22,0.0,2,,,,3,2007-05-27 12:00:00 +19337,772,26,11,21.0,22,19.0,19,0.0,70,,70.0,20.0,30,2007-05-27 12:00:00 +19338,772,4,3,4.0,15,13.0,13,0.0,76,,72.0,14.0,5,2007-05-27 12:00:00 +19339,772,3,0,1.0,1,1.0,1,10.0,78,6029329.0,44.0,1.0,1,2007-05-27 12:00:00 +19340,772,17,10,7.0,10,11.0,11,0.0,77,,40.0,9.0,11,2007-05-27 12:00:00 +19341,772,0,0,2.0,2,2.0,2,8.0,78,6033424.0,28.0,2.0,1,2007-05-27 12:00:00 +19342,772,12,5,5.0,3,3.0,3,6.0,78,6098443.0,47.0,4.0,1,2007-05-27 12:00:00 +19343,772,20,3,3.0,4,4.0,4,5.0,77,,54.0,5.0,11,2007-05-27 12:00:00 +19344,772,8,1,10.0,8,5.0,5,4.0,77,,39.0,3.0,11,2007-05-27 12:00:00 +19345,772,2,2,16.0,5,12.0,12,0.0,77,,70.0,11.0,11,2007-05-27 12:00:00 +19346,772,24,2,17.0,11,7.0,7,2.0,77,,40.0,7.0,11,2007-05-27 12:00:00 +19347,772,7,5,6.0,16,8.0,8,1.0,77,,62.0,6.0,11,2007-05-27 12:00:00 +19348,772,25,4,19.0,18,9.0,9,0.0,77,,73.0,10.0,11,2007-05-27 12:00:00 +19349,772,21,10,8.0,9,10.0,10,0.0,77,,69.0,13.0,11,2007-05-27 12:00:00 +19350,772,1,1,9.0,7,6.0,6,3.0,77,,30.0,12.0,11,2007-05-27 12:00:00 +19351,773,20,3,3.0,9,,22,0.0,51,,22.0,7.0,2,2007-06-10 17:00:00 +19352,773,12,5,5.0,5,,21,0.0,51,,22.0,4.0,2,2007-06-10 17:00:00 +19353,773,17,10,7.0,15,,20,0.0,0,,,,6,2007-06-10 17:00:00 +19354,773,25,4,19.0,16,,19,0.0,8,,6.0,21.0,3,2007-06-10 17:00:00 +19355,773,15,11,20.0,20,,18,0.0,21,,20.0,20.0,3,2007-06-10 17:00:00 +19356,773,8,1,10.0,8,,17,0.0,26,,19.0,8.0,3,2007-06-10 17:00:00 +19357,773,13,8,14.0,14,,16,0.0,36,,19.0,16.0,6,2007-06-10 17:00:00 +19358,773,23,4,18.0,12,,14,0.0,54,,9.0,19.0,3,2007-06-10 17:00:00 +19359,773,14,6,12.0,10,,13,0.0,58,,12.0,17.0,3,2007-06-10 17:00:00 +19360,773,26,11,21.0,21,,15,0.0,47,,21.0,18.0,33,2007-06-10 17:00:00 +19361,773,0,0,2.0,1,1.0,1,10.0,70,6251292.0,37.0,2.0,1,2007-06-10 17:00:00 +19362,773,18,7,23.0,17,11.0,11,0.0,70,6275610.0,36.0,15.0,1,2007-06-10 17:00:00 +19363,773,1,1,9.0,3,2.0,2,8.0,70,6255635.0,19.0,3.0,1,2007-06-10 17:00:00 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17:00:00 +19378,774,23,4,18.0,19,17.0,17,0.0,68,,64.0,17.0,34,2007-06-17 17:00:00 +19379,774,2,2,16.0,14,16.0,16,0.0,68,,34.0,11.0,5,2007-06-17 17:00:00 +19380,774,26,11,21.0,22,15.0,15,0.0,70,,65.0,18.0,13,2007-06-17 17:00:00 +19381,774,15,11,20.0,21,14.0,14,0.0,71,,49.0,15.0,12,2007-06-17 17:00:00 +19382,774,25,4,19.0,20,13.0,13,0.0,71,,66.0,16.0,12,2007-06-17 17:00:00 +19383,774,17,10,7.0,13,12.0,12,0.0,72,,42.0,14.0,11,2007-06-17 17:00:00 +19384,774,24,2,17.0,17,10.0,10,0.0,72,,41.0,13.0,11,2007-06-17 17:00:00 +19385,774,0,0,2.0,1,1.0,1,10.0,73,5469965.0,20.0,2.0,1,2007-06-17 17:00:00 +19386,774,3,0,1.0,2,2.0,2,8.0,73,5471465.0,21.0,3.0,1,2007-06-17 17:00:00 +19387,774,12,5,5.0,3,3.0,3,6.0,73,5482765.0,50.0,4.0,1,2007-06-17 17:00:00 +19388,774,7,5,6.0,4,4.0,4,5.0,73,5485365.0,49.0,1.0,1,2007-06-17 17:00:00 +19389,774,18,7,23.0,16,11.0,11,0.0,72,,55.0,12.0,11,2007-06-17 17:00:00 +19390,774,14,6,12.0,8,6.0,6,3.0,73,5536665.0,30.0,10.0,1,2007-06-17 17:00:00 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+19458,777,0,0,2.0,10,9.0,9,0.0,59,,29.0,3.0,11,2007-07-22 12:00:00 +19459,777,20,3,3.0,13,10.0,10,0.0,59,,48.0,12.0,11,2007-07-22 12:00:00 +19460,777,1,1,9.0,4,6.0,6,3.0,60,7666656.0,49.0,7.0,1,2007-07-22 12:00:00 +19461,778,24,2,17.0,12,14.0,14,0.0,69,,49.0,13.0,11,2007-08-05 12:00:00 +19462,778,28,11,21.0,22,,22,0.0,4,,4.0,22.0,3,2007-08-05 12:00:00 +19463,778,17,10,7.0,17,,21,0.0,35,,25.0,21.0,37,2007-08-05 12:00:00 +19464,778,18,7,23.0,15,,20,0.0,41,,39.0,18.0,3,2007-08-05 12:00:00 +19465,778,23,4,18.0,16,,19,0.0,42,,35.0,20.0,10,2007-08-05 12:00:00 +19466,778,21,10,8.0,18,18.0,18,0.0,68,,34.0,17.0,12,2007-08-05 12:00:00 +19467,778,15,11,20.0,21,17.0,17,0.0,68,,67.0,19.0,12,2007-08-05 12:00:00 +19468,778,19,4,19.0,20,16.0,16,0.0,69,,65.0,16.0,11,2007-08-05 12:00:00 +19469,778,10,7,22.0,19,15.0,15,0.0,69,,66.0,10.0,11,2007-08-05 12:00:00 +19470,778,12,5,5.0,14,13.0,13,0.0,69,,37.0,11.0,11,2007-08-05 12:00:00 +19471,778,20,3,3.0,13,12.0,12,0.0,69,,66.0,15.0,11,2007-08-05 12:00:00 +19472,778,13,8,14.0,10,11.0,11,0.0,69,,67.0,14.0,11,2007-08-05 12:00:00 +19473,778,7,5,6.0,3,2.0,2,8.0,70,5753706.0,70.0,1.0,1,2007-08-05 12:00:00 +19474,778,1,1,9.0,2,3.0,3,6.0,70,5796120.0,16.0,5.0,1,2007-08-05 12:00:00 +19475,778,3,0,1.0,6,4.0,4,5.0,70,5797849.0,49.0,3.0,1,2007-08-05 12:00:00 +19476,778,8,1,10.0,7,5.0,5,4.0,70,5800607.0,40.0,4.0,1,2007-08-05 12:00:00 +19477,778,0,0,2.0,1,1.0,1,10.0,70,5752991.0,13.0,2.0,1,2007-08-05 12:00:00 +19478,778,2,2,16.0,4,7.0,7,2.0,70,5812130.0,68.0,6.0,1,2007-08-05 12:00:00 +19479,778,4,3,4.0,11,8.0,8,1.0,70,5821095.0,69.0,8.0,1,2007-08-05 12:00:00 +19480,778,16,8,15.0,9,9.0,9,0.0,70,5829322.0,63.0,7.0,1,2007-08-05 12:00:00 +19481,778,14,6,12.0,8,10.0,10,0.0,69,,48.0,12.0,11,2007-08-05 12:00:00 +19482,778,22,6,11.0,5,6.0,6,3.0,70,5803660.0,69.0,9.0,1,2007-08-05 12:00:00 +19483,779,18,7,23.0,11,14.0,14,0.0,57,,38.0,17.0,11,2007-08-26 12:00:00 +19484,779,16,8,15.0,12,,22,0.0,9,,4.0,21.0,9,2007-08-26 12:00:00 +19485,779,15,11,20.0,19,21.0,21,0.0,53,,52.0,20.0,32,2007-08-26 12:00:00 +19486,779,28,11,21.0,20,20.0,20,0.0,56,,21.0,22.0,12,2007-08-26 12:00:00 +19487,779,19,4,19.0,18,19.0,19,0.0,57,,39.0,19.0,11,2007-08-26 12:00:00 +19488,779,10,7,22.0,17,18.0,18,0.0,57,,56.0,18.0,11,2007-08-26 12:00:00 +19489,779,21,10,8.0,22,17.0,17,0.0,57,,35.0,15.0,11,2007-08-26 12:00:00 +19490,779,14,6,12.0,9,16.0,16,0.0,57,,39.0,14.0,11,2007-08-26 12:00:00 +19491,779,23,4,18.0,15,15.0,15,0.0,57,,56.0,16.0,11,2007-08-26 12:00:00 +19492,779,17,10,7.0,21,13.0,13,0.0,57,,34.0,10.0,11,2007-08-26 12:00:00 +19493,779,22,6,11.0,16,12.0,12,0.0,57,,55.0,12.0,11,2007-08-26 12:00:00 +19494,779,24,2,17.0,14,11.0,11,0.0,58,5281789.0,55.0,8.0,1,2007-08-26 12:00:00 +19495,779,13,8,14.0,13,10.0,10,0.0,58,5273170.0,54.0,13.0,1,2007-08-26 12:00:00 +19496,779,20,3,3.0,10,9.0,9,0.0,58,5261652.0,56.0,9.0,1,2007-08-26 12:00:00 +19497,779,8,1,10.0,5,8.0,8,1.0,58,5258868.0,11.0,11.0,1,2007-08-26 12:00:00 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+19511,780,12,5,5.0,3,,21,0.0,10,,8.0,6.0,22,2007-09-09 12:00:00 +19512,780,24,2,17.0,13,13.0,13,0.0,52,,42.0,16.0,11,2007-09-09 12:00:00 +19513,780,15,11,20.0,21,19.0,19,0.0,52,,30.0,20.0,11,2007-09-09 12:00:00 +19514,780,20,3,3.0,15,12.0,12,0.0,52,,32.0,14.0,11,2007-09-09 12:00:00 +19515,780,19,4,19.0,16,18.0,18,0.0,52,,47.0,18.0,11,2007-09-09 12:00:00 +19516,780,21,10,8.0,12,10.0,10,0.0,53,4784764.0,52.0,12.0,1,2007-09-09 12:00:00 +19517,780,3,0,1.0,1,1.0,1,10.0,53,4717806.0,15.0,1.0,1,2007-09-09 12:00:00 +19518,780,0,0,2.0,2,2.0,2,8.0,53,4723868.0,17.0,2.0,1,2007-09-09 12:00:00 +19519,780,7,5,6.0,5,3.0,3,6.0,53,4745131.0,21.0,3.0,1,2007-09-09 12:00:00 +19520,780,1,1,9.0,4,4.0,4,5.0,53,4774368.0,19.0,4.0,1,2007-09-09 12:00:00 +19521,780,14,6,12.0,9,11.0,11,0.0,53,4785542.0,49.0,10.0,1,2007-09-09 12:00:00 +19522,780,2,2,16.0,8,6.0,6,3.0,53,4783616.0,52.0,8.0,1,2007-09-09 12:00:00 +19523,780,4,3,4.0,7,7.0,7,2.0,53,4784557.0,53.0,7.0,1,2007-09-09 12:00:00 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04:30:00 +19564,782,12,5,5.0,4,6.0,6,3.0,67,7283621.0,32.0,7.0,1,2007-09-30 04:30:00 +19565,782,20,3,3.0,10,5.0,5,4.0,67,7273443.0,33.0,12.0,1,2007-09-30 04:30:00 +19566,782,13,8,14.0,12,4.0,4,5.0,67,7254876.0,56.0,11.0,1,2007-09-30 04:30:00 +19567,782,7,5,6.0,3,3.0,3,6.0,67,7244057.0,29.0,8.0,1,2007-09-30 04:30:00 +19568,782,4,3,4.0,11,2.0,2,8.0,67,7242956.0,34.0,9.0,1,2007-09-30 04:30:00 +19569,782,0,0,2.0,1,1.0,1,10.0,67,7234579.0,27.0,1.0,1,2007-09-30 04:30:00 +19570,782,28,11,21.0,22,12.0,12,0.0,66,,33.0,20.0,11,2007-09-30 04:30:00 +19571,783,21,10,8.0,16,15.0,15,0.0,55,,55.0,16.0,11,2007-10-07 06:00:00 +19572,783,2,2,16.0,15,16.0,16,0.0,54,,54.0,6.0,12,2007-10-07 06:00:00 +19573,783,28,11,21.0,22,17.0,17,0.0,53,,52.0,17.0,13,2007-10-07 06:00:00 +19574,783,18,7,23.0,14,,22,0.0,11,,9.0,22.0,23,2007-10-07 06:00:00 +19575,783,22,6,11.0,6,,20,0.0,25,,25.0,20.0,20,2007-10-07 06:00:00 +19576,783,15,11,20.0,21,,21,0.0,24,,22.0,21.0,3,2007-10-07 06:00:00 +19577,783,10,7,22.0,20,14.0,14,0.0,55,,54.0,15.0,11,2007-10-07 06:00:00 +19578,783,0,0,2.0,1,,19,0.0,30,,22.0,19.0,20,2007-10-07 06:00:00 +19579,783,14,6,12.0,12,13.0,13,0.0,55,,55.0,14.0,11,2007-10-07 06:00:00 +19580,783,8,1,10.0,9,,18,0.0,33,,32.0,18.0,9,2007-10-07 06:00:00 +19581,783,20,3,3.0,18,11.0,11,0.0,56,5965078.0,39.0,4.0,1,2007-10-07 06:00:00 +19582,783,24,2,17.0,19,12.0,12,0.0,55,,54.0,12.0,11,2007-10-07 06:00:00 +19583,783,7,5,6.0,2,1.0,1,10.0,56,5878395.0,52.0,3.0,1,2007-10-07 06:00:00 +19584,783,3,0,1.0,4,2.0,2,8.0,56,5888201.0,54.0,2.0,1,2007-10-07 06:00:00 +19585,783,12,5,5.0,3,3.0,3,6.0,56,5891286.0,56.0,1.0,1,2007-10-07 06:00:00 +19586,783,19,4,19.0,17,4.0,4,5.0,56,5931904.0,52.0,13.0,1,2007-10-07 06:00:00 +19587,783,13,8,14.0,5,8.0,8,1.0,56,5959145.0,55.0,10.0,1,2007-10-07 06:00:00 +19588,783,23,4,18.0,11,6.0,6,3.0,56,5952068.0,53.0,11.0,1,2007-10-07 06:00:00 +19589,783,1,1,9.0,8,7.0,7,2.0,56,5952619.0,55.0,7.0,1,2007-10-07 06:00:00 +19590,783,4,3,4.0,13,9.0,9,0.0,56,5959581.0,52.0,8.0,1,2007-10-07 06:00:00 +19591,783,16,8,15.0,7,10.0,10,0.0,56,5963080.0,55.0,9.0,1,2007-10-07 06:00:00 +19592,783,17,10,7.0,10,5.0,5,4.0,56,5947061.0,39.0,5.0,1,2007-10-07 06:00:00 +19593,784,20,3,3.0,12,,22,0.0,2,,2.0,22.0,4,2007-10-21 16:00:00 +19594,784,28,11,21.0,22,,21,0.0,2,,2.0,21.0,4,2007-10-21 16:00:00 +19595,784,16,8,15.0,5,,20,0.0,14,,13.0,15.0,6,2007-10-21 16:00:00 +19596,784,17,10,7.0,16,,19,0.0,20,,20.0,12.0,5,2007-10-21 16:00:00 +19597,784,19,4,19.0,13,,18,0.0,34,,18.0,16.0,9,2007-10-21 16:00:00 +19598,784,4,3,4.0,17,,17,0.0,35,,31.0,18.0,3,2007-10-21 16:00:00 +19599,784,21,10,8.0,11,,16,0.0,40,,32.0,17.0,5,2007-10-21 16:00:00 +19600,784,15,11,20.0,21,,15,0.0,43,,13.0,20.0,23,2007-10-21 16:00:00 +19601,784,18,7,23.0,20,14.0,14,0.0,68,,64.0,14.0,13,2007-10-21 16:00:00 +19602,784,23,4,18.0,14,13.0,13,0.0,69,,56.0,11.0,12,2007-10-21 16:00:00 +19603,784,22,6,11.0,15,11.0,11,0.0,70,,65.0,9.0,11,2007-10-21 16:00:00 +19604,784,5,2,17.0,19,10.0,10,0.0,70,,69.0,5.0,11,2007-10-21 16:00:00 +19605,784,13,8,14.0,9,9.0,9,0.0,70,,22.0,13.0,11,2007-10-21 16:00:00 +19606,784,14,6,12.0,8,8.0,8,1.0,70,,68.0,8.0,11,2007-10-21 16:00:00 +19607,784,1,1,9.0,6,6.0,6,3.0,71,5366587.0,53.0,10.0,1,2007-10-21 16:00:00 +19608,784,8,1,10.0,7,5.0,5,4.0,71,5366227.0,61.0,4.0,1,2007-10-21 16:00:00 +19609,784,2,2,16.0,10,4.0,4,5.0,71,5358118.0,56.0,7.0,1,2007-10-21 16:00:00 +19610,784,3,0,1.0,4,3.0,3,6.0,71,5352289.0,59.0,6.0,1,2007-10-21 16:00:00 +19611,784,12,5,5.0,1,2.0,2,8.0,71,5296763.0,71.0,3.0,1,2007-10-21 16:00:00 +19612,784,7,5,6.0,3,1.0,1,10.0,71,5295270.0,66.0,1.0,1,2007-10-21 16:00:00 +19613,784,10,7,22.0,18,12.0,12,0.0,69,,39.0,19.0,12,2007-10-21 16:00:00 +19614,784,0,0,2.0,2,7.0,7,2.0,70,,58.0,2.0,11,2007-10-21 16:00:00 +19615,785,0,0,22.0,1,1.0,1,10.0,58,5690616.0,39.0,2.0,1,2008-03-16 04:30:00 +19616,785,20,9,21.0,16,,21,0.0,0,,,,4,2008-03-16 04:30:00 +19617,785,19,4,15.0,9,,20,0.0,0,,,,4,2008-03-16 04:30:00 +19618,785,1,1,3.0,5,2.0,2,8.0,58,5696094.0,41.0,3.0,1,2008-03-16 04:30:00 +19619,785,18,7,19.0,21,,19,0.0,0,,,,4,2008-03-16 04:30:00 +19620,785,17,10,16.0,12,,18,0.0,0,,,,4,2008-03-16 04:30:00 +19621,785,16,8,10.0,14,,17,0.0,0,,,,4,2008-03-16 04:30:00 +19622,785,15,9,20.0,22,,16,0.0,8,,8.0,17.0,9,2008-03-16 04:30:00 +19623,785,14,6,11.0,6,,15,0.0,19,,18.0,10.0,10,2008-03-16 04:30:00 +19624,785,13,8,9.0,8,,14,0.0,25,,21.0,11.0,4,2008-03-16 04:30:00 +19625,785,12,5,2.0,4,,13,0.0,29,,23.0,6.0,5,2008-03-16 04:30:00 +19626,785,11,3,6.0,20,,12,0.0,30,,20.0,16.0,8,2008-03-16 04:30:00 +19627,785,21,10,17.0,10,,22,0.0,58,,44.0,8.0,2,2008-03-16 04:30:00 +19628,785,9,6,12.0,18,,10,0.0,43,,23.0,13.0,3,2008-03-16 04:30:00 +19629,785,8,1,4.0,2,,9,0.0,47,,15.0,9.0,4,2008-03-16 04:30:00 +19630,785,7,5,1.0,15,8.0,8,1.0,53,,20.0,4.0,5,2008-03-16 04:30:00 +19631,785,6,4,14.0,17,7.0,7,2.0,55,,22.0,12.0,5,2008-03-16 04:30:00 +19632,785,5,2,8.0,13,6.0,6,3.0,57,,50.0,14.0,11,2008-03-16 04:30:00 +19633,785,4,0,23.0,3,5.0,5,4.0,58,5708630.0,43.0,1.0,1,2008-03-16 04:30:00 +19634,785,2,2,7.0,7,3.0,3,6.0,58,5698779.0,41.0,5.0,1,2008-03-16 04:30:00 +19635,785,3,3,5.0,11,4.0,4,5.0,58,5707797.0,58.0,7.0,1,2008-03-16 04:30:00 +19636,785,10,7,18.0,19,,11,0.0,32,,24.0,15.0,7,2008-03-16 04:30:00 +19637,786,10,7,18.0,19,16.0,16,0.0,54,,53.0,19.0,12,2008-03-23 07:00:00 +19638,786,5,2,8.0,22,17.0,17,0.0,54,,19.0,17.0,12,2008-03-23 07:00:00 +19639,786,19,4,15.0,15,,18,0.0,39,,37.0,14.0,5,2008-03-23 07:00:00 +19640,786,12,5,2.0,1,,19,0.0,30,,15.0,5.0,20,2008-03-23 07:00:00 +19641,786,7,5,1.0,2,1.0,1,10.0,56,5478555.0,37.0,2.0,1,2008-03-23 07:00:00 +19642,786,9,6,12.0,10,,21,0.0,1,,,,4,2008-03-23 07:00:00 +19643,786,6,4,14.0,18,,22,0.0,0,,,,20,2008-03-23 07:00:00 +19644,786,18,7,19.0,21,15.0,15,0.0,55,,55.0,18.0,11,2008-03-23 07:00:00 +19645,786,15,9,20.0,20,,20,0.0,5,,3.0,20.0,9,2008-03-23 07:00:00 +19646,786,21,10,17.0,14,13.0,13,0.0,55,,55.0,11.0,11,2008-03-23 07:00:00 +19647,786,2,2,7.0,16,14.0,14,0.0,55,,55.0,13.0,11,2008-03-23 07:00:00 +19648,786,8,1,4.0,4,2.0,2,8.0,56,5498125.0,39.0,6.0,1,2008-03-23 07:00:00 +19649,786,11,3,6.0,13,11.0,11,0.0,56,5570757.0,52.0,15.0,1,2008-03-23 07:00:00 +19650,786,17,10,16.0,11,10.0,10,0.0,56,5564769.0,56.0,4.0,1,2008-03-23 07:00:00 +19651,786,13,8,9.0,12,9.0,9,0.0,56,5554775.0,55.0,9.0,1,2008-03-23 07:00:00 +19652,786,3,3,5.0,7,8.0,8,1.0,56,5548596.0,40.0,10.0,1,2008-03-23 07:00:00 +19653,786,16,8,10.0,6,7.0,7,2.0,56,5546685.0,53.0,12.0,1,2008-03-23 07:00:00 +19654,786,1,1,3.0,5,6.0,6,3.0,56,5528388.0,55.0,1.0,1,2008-03-23 07:00:00 +19655,786,0,0,22.0,9,5.0,5,4.0,56,5525103.0,53.0,3.0,1,2008-03-23 07:00:00 +19656,786,14,6,11.0,3,4.0,4,5.0,56,5524387.0,53.0,8.0,1,2008-03-23 07:00:00 +19657,786,4,0,23.0,8,3.0,3,6.0,56,5517005.0,19.0,7.0,1,2008-03-23 07:00:00 +19658,786,20,9,21.0,17,12.0,12,0.0,55,,52.0,16.0,11,2008-03-23 07:00:00 +19659,787,6,4,14.0,15,15.0,15,0.0,56,,33.0,15.0,11,2008-04-06 11:30:00 +19660,787,18,7,19.0,21,16.0,16,0.0,56,,45.0,14.0,11,2008-04-06 11:30:00 +19661,787,10,7,18.0,22,17.0,17,0.0,56,,56.0,20.0,11,2008-04-06 11:30:00 +19662,787,13,8,9.0,17,18.0,18,0.0,56,,43.0,16.0,11,2008-04-06 11:30:00 +19663,787,5,2,8.0,16,14.0,14,0.0,56,,30.0,17.0,11,2008-04-06 11:30:00 +19664,787,11,3,6.0,14,,20,0.0,40,,31.0,12.0,6,2008-04-06 11:30:00 +19665,787,17,10,16.0,9,,21,0.0,19,,11.0,21.0,4,2008-04-06 11:30:00 +19666,787,19,4,15.0,19,,22,0.0,0,,,,5,2008-04-06 11:30:00 +19667,787,15,9,20.0,20,19.0,19,0.0,56,,55.0,18.0,12,2008-04-06 11:30:00 +19668,787,0,0,22.0,3,13.0,13,0.0,56,,25.0,19.0,11,2008-04-06 11:30:00 +19669,787,7,5,1.0,4,2.0,2,8.0,57,5470309.0,35.0,4.0,1,2008-04-06 11:30:00 +19670,787,21,10,17.0,12,11.0,11,0.0,57,5544832.0,40.0,10.0,1,2008-04-06 11:30:00 +19671,787,3,3,5.0,10,10.0,10,0.0,57,5544151.0,35.0,13.0,1,2008-04-06 11:30:00 +19672,787,9,6,12.0,13,9.0,9,0.0,57,5536470.0,56.0,9.0,1,2008-04-06 11:30:00 +19673,787,2,2,7.0,8,8.0,8,1.0,57,5522859.0,57.0,6.0,1,2008-04-06 11:30:00 +19674,787,16,8,10.0,11,7.0,7,2.0,57,5512443.0,51.0,8.0,1,2008-04-06 11:30:00 +19675,787,14,6,11.0,7,6.0,6,3.0,57,5508284.0,45.0,7.0,1,2008-04-06 11:30:00 +19676,787,4,0,23.0,5,5.0,5,4.0,57,5493759.0,49.0,1.0,1,2008-04-06 11:30:00 +19677,787,1,1,3.0,6,4.0,4,5.0,57,5475379.0,48.0,2.0,1,2008-04-06 11:30:00 +19678,787,8,1,4.0,1,3.0,3,6.0,57,5471968.0,55.0,5.0,1,2008-04-06 11:30:00 +19679,787,20,9,21.0,18,12.0,12,0.0,56,,56.0,11.0,11,2008-04-06 11:30:00 +19680,787,12,5,2.0,2,1.0,1,10.0,57,5466970.0,38.0,3.0,1,2008-04-06 11:30:00 +19681,788,3,3,5.0,2,,15,0.0,34,,15.0,9.0,5,2008-04-27 12:00:00 +19682,788,21,10,17.0,11,,16,0.0,34,,21.0,16.0,4,2008-04-27 12:00:00 +19683,788,4,0,23.0,6,,17,0.0,21,,19.0,6.0,3,2008-04-27 12:00:00 +19684,788,2,2,7.0,15,,14,0.0,41,,20.0,13.0,5,2008-04-27 12:00:00 +19685,788,6,4,14.0,16,,19,0.0,7,,6.0,19.0,4,2008-04-27 12:00:00 +19686,788,11,3,6.0,10,,20,0.0,6,,6.0,18.0,4,2008-04-27 12:00:00 +19687,788,19,4,15.0,18,,22,0.0,0,,,,4,2008-04-27 12:00:00 +19688,788,18,7,19.0,21,,18,0.0,8,,6.0,20.0,21,2008-04-27 12:00:00 +19689,788,10,7,18.0,22,13.0,13,0.0,65,,34.0,17.0,11,2008-04-27 12:00:00 +19690,788,15,9,20.0,20,,21,0.0,0,,,,4,2008-04-27 12:00:00 +19691,788,9,6,12.0,14,11.0,11,0.0,65,,57.0,12.0,11,2008-04-27 12:00:00 +19692,788,0,0,22.0,5,3.0,3,6.0,66,5903238.0,20.0,3.0,1,2008-04-27 12:00:00 +19693,788,7,5,1.0,1,1.0,1,10.0,66,5899051.0,46.0,1.0,1,2008-04-27 12:00:00 +19694,788,8,1,4.0,4,4.0,4,5.0,66,5904745.0,20.0,4.0,1,2008-04-27 12:00:00 +19695,788,16,8,10.0,7,5.0,5,4.0,66,5934989.0,19.0,8.0,1,2008-04-27 12:00:00 +19696,788,12,5,2.0,3,2.0,2,8.0,66,5902279.0,45.0,2.0,1,2008-04-27 12:00:00 +19697,788,5,2,8.0,12,7.0,7,2.0,66,5957295.0,48.0,15.0,1,2008-04-27 12:00:00 +19698,788,14,6,11.0,8,8.0,8,1.0,66,5958486.0,45.0,10.0,1,2008-04-27 12:00:00 +19699,788,1,1,3.0,9,9.0,9,0.0,66,5962124.0,21.0,7.0,1,2008-04-27 12:00:00 +19700,788,20,9,21.0,19,10.0,10,0.0,65,,40.0,14.0,11,2008-04-27 12:00:00 +19701,788,17,10,16.0,13,6.0,6,3.0,66,5952061.0,66.0,5.0,1,2008-04-27 12:00:00 +19702,788,13,8,9.0,17,12.0,12,0.0,65,,57.0,11.0,11,2008-04-27 12:00:00 +19703,789,4,0,23.0,2,12.0,12,0.0,57,,55.0,8.0,11,2008-05-11 12:00:00 +19704,789,20,9,21.0,20,,20,0.0,0,,,,4,2008-05-11 12:00:00 +19705,789,5,2,8.0,16,,19,0.0,1,,,,4,2008-05-11 12:00:00 +19706,789,6,4,14.0,18,,18,0.0,24,,19.0,17.0,22,2008-05-11 12:00:00 +19707,789,19,4,15.0,14,17.0,17,0.0,57,,38.0,15.0,11,2008-05-11 12:00:00 +19708,789,15,9,20.0,19,16.0,16,0.0,57,,35.0,18.0,11,2008-05-11 12:00:00 +19709,789,11,3,6.0,17,15.0,15,0.0,57,,40.0,10.0,11,2008-05-11 12:00:00 +19710,789,21,10,17.0,12,14.0,14,0.0,57,,56.0,14.0,11,2008-05-11 12:00:00 +19711,789,9,6,12.0,15,13.0,13,0.0,57,,28.0,16.0,11,2008-05-11 12:00:00 +19712,789,17,10,16.0,13,11.0,11,0.0,57,,57.0,13.0,11,2008-05-11 12:00:00 +19713,789,13,8,9.0,10,9.0,9,0.0,58,5284721.0,41.0,12.0,1,2008-05-11 12:00:00 +19714,789,2,2,7.0,11,8.0,8,1.0,58,5280857.0,55.0,9.0,1,2008-05-11 12:00:00 +19715,789,16,8,10.0,6,7.0,7,2.0,58,5273680.0,14.0,7.0,1,2008-05-11 12:00:00 +19716,789,3,3,5.0,7,6.0,6,3.0,58,5263175.0,57.0,6.0,1,2008-05-11 12:00:00 +19717,789,1,1,3.0,9,5.0,5,4.0,58,5248192.0,20.0,5.0,1,2008-05-11 12:00:00 +19718,789,8,1,4.0,5,4.0,4,5.0,58,5231396.0,17.0,4.0,1,2008-05-11 12:00:00 +19719,789,7,5,1.0,4,3.0,3,6.0,58,5213722.0,20.0,1.0,1,2008-05-11 12:00:00 +19720,789,0,0,22.0,3,2.0,2,8.0,58,5213230.0,31.0,2.0,1,2008-05-11 12:00:00 +19721,789,12,5,2.0,1,1.0,1,10.0,58,5209451.0,16.0,3.0,1,2008-05-11 12:00:00 +19722,789,14,6,11.0,8,10.0,10,0.0,58,5285795.0,52.0,11.0,1,2008-05-11 12:00:00 +19723,790,14,6,11.0,8,13.0,13,0.0,75,,75.0,12.0,11,2008-05-25 12:00:00 +19724,790,1,1,3.0,12,14.0,14,0.0,72,,72.0,14.0,14,2008-05-25 12:00:00 +19725,790,15,9,20.0,18,,15,0.0,67,,60.0,16.0,4,2008-05-25 12:00:00 +19726,790,6,4,14.0,16,,20,0.0,7,,7.0,19.0,4,2008-05-25 12:00:00 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17:00:00 +19754,791,2,2,7.0,5,10.0,10,0.0,70,5838976.0,14.0,5.0,1,2008-06-08 17:00:00 +19755,791,1,1,3.0,8,2.0,2,8.0,70,5800722.0,25.0,2.0,1,2008-06-08 17:00:00 +19756,791,13,8,9.0,13,3.0,3,6.0,70,5807579.0,36.0,7.0,1,2008-06-08 17:00:00 +19757,791,9,6,12.0,11,4.0,4,5.0,70,5826854.0,31.0,17.0,1,2008-06-08 17:00:00 +19758,791,8,1,4.0,2,1.0,1,10.0,70,5784227.0,47.0,4.0,1,2008-06-08 17:00:00 +19759,791,14,6,11.0,14,6.0,6,3.0,70,5832002.0,38.0,15.0,1,2008-06-08 17:00:00 +19760,791,21,10,17.0,9,7.0,7,2.0,70,5837824.0,35.0,10.0,1,2008-06-08 17:00:00 +19761,791,19,4,15.0,19,8.0,8,1.0,70,5838347.0,33.0,12.0,1,2008-06-08 17:00:00 +19762,791,12,5,2.0,6,5.0,5,4.0,70,5828161.0,11.0,6.0,1,2008-06-08 17:00:00 +19763,792,17,10,16.0,16,,20,0.0,16,,15.0,20.0,4,2008-06-22 12:00:00 +19764,792,15,9,20.0,18,19.0,19,0.0,69,,41.0,18.0,11,2008-06-22 12:00:00 +19765,792,20,9,21.0,17,18.0,18,0.0,69,,53.0,19.0,11,2008-06-22 12:00:00 +19766,792,6,4,14.0,14,17.0,17,0.0,69,,28.0,16.0,11,2008-06-22 12:00:00 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+19859,796,14,6,11.0,7,5.0,5,4.0,57,5783023.0,37.0,12.0,1,2008-08-24 12:00:00 +19860,796,2,2,7.0,9,8.0,8,1.0,57,5803796.0,35.0,10.0,1,2008-08-24 12:00:00 +19861,796,9,6,12.0,13,7.0,7,2.0,57,5800329.0,54.0,8.0,1,2008-08-24 12:00:00 +19862,796,4,0,23.0,5,4.0,4,5.0,57,5772042.0,19.0,3.0,1,2008-08-24 12:00:00 +19863,797,11,3,6.0,12,,20,0.0,13,,12.0,18.0,20,2008-09-07 12:00:00 +19864,797,21,10,17.0,16,,19,0.0,19,,10.0,20.0,6,2008-09-07 12:00:00 +19865,797,7,5,1.0,4,18.0,18,0.0,42,,24.0,1.0,20,2008-09-07 12:00:00 +19866,797,20,9,21.0,20,17.0,17,0.0,43,,17.0,19.0,11,2008-09-07 12:00:00 +19867,797,14,6,11.0,11,16.0,16,0.0,43,,32.0,14.0,11,2008-09-07 12:00:00 +19868,797,5,2,8.0,19,14.0,14,0.0,43,,35.0,17.0,11,2008-09-07 12:00:00 +19869,797,15,9,20.0,18,13.0,13,0.0,43,,27.0,13.0,11,2008-09-07 12:00:00 +19870,797,2,2,7.0,15,12.0,12,0.0,43,,32.0,15.0,11,2008-09-07 12:00:00 +19871,797,17,10,16.0,17,15.0,15,0.0,43,,19.0,16.0,11,2008-09-07 12:00:00 +19872,797,4,0,23.0,3,10.0,10,0.0,43,,35.0,4.0,6,2008-09-07 12:00:00 +19873,797,9,6,12.0,13,9.0,9,0.0,44,5046439.0,37.0,12.0,1,2008-09-07 12:00:00 +19874,797,16,8,10.0,7,8.0,8,1.0,44,5022170.0,34.0,10.0,1,2008-09-07 12:00:00 +19875,797,6,4,14.0,9,7.0,7,2.0,44,4996129.0,31.0,6.0,1,2008-09-07 12:00:00 +19876,797,8,1,4.0,8,6.0,6,3.0,44,4994431.0,36.0,5.0,1,2008-09-07 12:00:00 +19877,797,19,4,15.0,10,5.0,5,4.0,44,4993970.0,16.0,8.0,1,2008-09-07 12:00:00 +19878,797,3,3,5.0,6,4.0,4,5.0,44,4993872.0,25.0,9.0,1,2008-09-07 12:00:00 +19879,797,0,0,22.0,1,3.0,3,6.0,44,4989933.0,20.0,2.0,1,2008-09-07 12:00:00 +19880,797,1,1,3.0,5,2.0,2,8.0,44,4988777.0,36.0,7.0,1,2008-09-07 12:00:00 +19881,797,13,8,9.0,14,11.0,11,0.0,43,,19.0,11.0,11,2008-09-07 12:00:00 +19882,797,12,5,2.0,2,1.0,1,10.0,44,4979394.0,26.0,3.0,1,2008-09-07 12:00:00 +19883,798,14,6,11.0,7,13.0,13,0.0,53,5273448.0,52.0,15.0,1,2008-09-14 12:00:00 +19884,798,2,2,7.0,5,14.0,14,0.0,53,5276129.0,53.0,10.0,1,2008-09-14 12:00:00 +19885,798,17,10,16.0,19,15.0,15,0.0,53,5280864.0,52.0,7.0,1,2008-09-14 12:00:00 +19886,798,20,9,21.0,12,,20,0.0,11,,6.0,20.0,3,2008-09-14 12:00:00 +19887,798,21,10,17.0,16,17.0,17,0.0,52,,42.0,19.0,11,2008-09-14 12:00:00 +19888,798,6,4,14.0,4,18.0,18,0.0,52,,52.0,2.0,11,2008-09-14 12:00:00 +19889,798,15,9,20.0,20,19.0,19,0.0,51,,51.0,18.0,12,2008-09-14 12:00:00 +19890,798,13,8,9.0,13,16.0,16,0.0,52,,49.0,17.0,11,2008-09-14 12:00:00 +19891,798,5,2,8.0,18,12.0,12,0.0,53,5269509.0,53.0,11.0,1,2008-09-14 12:00:00 +19892,798,11,3,6.0,17,10.0,10,0.0,53,5261939.0,53.0,16.0,1,2008-09-14 12:00:00 +19893,798,7,5,1.0,14,9.0,9,0.0,53,5246962.0,53.0,1.0,1,2008-09-14 12:00:00 +19894,798,9,6,12.0,9,11.0,11,0.0,53,5266382.0,53.0,8.0,1,2008-09-14 12:00:00 +19895,798,19,4,15.0,1,1.0,1,10.0,53,5207494.0,53.0,14.0,1,2008-09-14 12:00:00 +19896,798,4,0,23.0,2,2.0,2,8.0,53,5220006.0,53.0,13.0,1,2008-09-14 12:00:00 +19897,798,8,1,4.0,11,3.0,3,6.0,53,5227965.0,52.0,12.0,1,2008-09-14 12:00:00 +19898,798,0,0,22.0,15,7.0,7,2.0,53,5237406.0,52.0,5.0,1,2008-09-14 12:00:00 +19899,798,1,1,3.0,10,5.0,5,4.0,53,5235242.0,53.0,6.0,1,2008-09-14 12:00:00 +19900,798,12,5,2.0,6,6.0,6,3.0,53,5236310.0,52.0,4.0,1,2008-09-14 12:00:00 +19901,798,16,8,10.0,3,8.0,8,1.0,53,5239542.0,52.0,3.0,1,2008-09-14 12:00:00 +19902,798,3,3,5.0,8,4.0,4,5.0,53,5231397.0,51.0,9.0,1,2008-09-14 12:00:00 +19903,799,21,10,17.0,18,,19,0.0,14,,13.0,19.0,26,2008-09-28 12:00:00 +19904,799,16,8,10.0,13,,18,0.0,29,,13.0,17.0,7,2008-09-28 12:00:00 +19905,799,15,9,20.0,19,,17,0.0,49,,38.0,18.0,3,2008-09-28 12:00:00 +19906,799,14,6,11.0,11,,16,0.0,50,,32.0,7.0,9,2008-09-28 12:00:00 +19907,799,7,5,1.0,3,15.0,15,0.0,57,,14.0,1.0,3,2008-09-28 12:00:00 +19908,799,11,3,6.0,16,,20,0.0,13,,13.0,20.0,3,2008-09-28 12:00:00 +19909,799,12,5,2.0,1,13.0,13,0.0,61,7071474.0,13.0,2.0,1,2008-09-28 12:00:00 +19910,799,6,4,14.0,17,12.0,12,0.0,61,7065736.0,29.0,14.0,1,2008-09-28 12:00:00 +19911,799,4,0,23.0,5,10.0,10,0.0,61,7063206.0,14.0,12.0,1,2008-09-28 12:00:00 +19912,799,17,10,16.0,12,9.0,9,0.0,61,7056189.0,61.0,15.0,1,2008-09-28 12:00:00 +19913,799,5,2,8.0,10,8.0,8,1.0,61,7054793.0,13.0,10.0,1,2008-09-28 12:00:00 +19914,799,1,1,3.0,9,6.0,6,3.0,61,7047405.0,14.0,11.0,1,2008-09-28 12:00:00 +19915,799,19,4,15.0,6,5.0,5,4.0,61,7046572.0,13.0,9.0,1,2008-09-28 12:00:00 +19916,799,9,6,12.0,7,4.0,4,5.0,61,7044459.0,50.0,8.0,1,2008-09-28 12:00:00 +19917,799,0,0,22.0,2,3.0,3,6.0,61,7042221.0,14.0,4.0,1,2008-09-28 12:00:00 +19918,799,2,2,7.0,8,2.0,2,8.0,61,7039261.0,39.0,5.0,1,2008-09-28 12:00:00 +19919,799,3,3,5.0,15,1.0,1,10.0,61,7036304.0,55.0,3.0,1,2008-09-28 12:00:00 +19920,799,8,1,4.0,4,11.0,11,0.0,61,7064279.0,14.0,6.0,1,2008-09-28 12:00:00 +19921,799,13,8,9.0,14,7.0,7,2.0,61,7052691.0,41.0,13.0,1,2008-09-28 12:00:00 +19922,799,20,9,21.0,20,14.0,14,0.0,61,7079875.0,28.0,16.0,1,2008-09-28 12:00:00 +19923,800,16,8,10.0,13,8.0,8,1.0,67,5472703.0,30.0,13.0,1,2008-10-12 04:30:00 +19924,800,12,5,2.0,5,7.0,7,2.0,67,5468050.0,55.0,1.0,1,2008-10-12 04:30:00 +19925,800,1,1,3.0,16,9.0,9,0.0,67,5476012.0,67.0,8.0,1,2008-10-12 04:30:00 +19926,800,13,8,9.0,11,,20,0.0,0,,,,4,2008-10-12 04:30:00 +19927,800,9,6,12.0,8,,19,0.0,6,,4.0,14.0,28,2008-10-12 04:30:00 +19928,800,15,9,20.0,19,,18,0.0,8,,6.0,18.0,27,2008-10-12 04:30:00 +19929,800,20,9,21.0,20,,16,0.0,21,,20.0,19.0,6,2008-10-12 04:30:00 +19930,800,19,4,15.0,9,6.0,6,3.0,67,5461099.0,21.0,12.0,1,2008-10-12 04:30:00 +19931,800,14,6,11.0,7,5.0,5,4.0,67,5445659.0,18.0,9.0,1,2008-10-12 04:30:00 +19932,800,11,3,6.0,12,4.0,4,5.0,67,5442462.0,54.0,4.0,1,2008-10-12 04:30:00 +19933,800,4,0,23.0,3,,17,0.0,16,,12.0,5.0,5,2008-10-12 04:30:00 +19934,800,8,1,4.0,6,2.0,2,8.0,67,5427175.0,16.0,7.0,1,2008-10-12 04:30:00 +19935,800,3,3,5.0,4,1.0,1,10.0,67,5421892.0,41.0,3.0,1,2008-10-12 04:30:00 +19936,800,5,2,8.0,14,15.0,15,0.0,66,,32.0,15.0,11,2008-10-12 04:30:00 +19937,800,17,10,16.0,18,14.0,14,0.0,66,,66.0,17.0,11,2008-10-12 04:30:00 +19938,800,21,10,17.0,17,13.0,13,0.0,66,,66.0,16.0,11,2008-10-12 04:30:00 +19939,800,0,0,22.0,1,12.0,12,0.0,67,5500792.0,65.0,11.0,1,2008-10-12 04:30:00 +19940,800,2,2,7.0,15,11.0,11,0.0,67,5483988.0,66.0,10.0,1,2008-10-12 04:30:00 +19941,800,7,5,1.0,2,3.0,3,6.0,67,5428292.0,66.0,2.0,1,2008-10-12 04:30:00 +19942,800,6,4,14.0,10,10.0,10,0.0,67,5480977.0,49.0,6.0,1,2008-10-12 04:30:00 +19943,801,16,8,10.0,16,14.0,14,0.0,56,5609825.0,10.0,13.0,1,2008-10-19 07:00:00 +19944,801,2,2,7.0,14,15.0,15,0.0,55,,38.0,10.0,11,2008-10-19 07:00:00 +19945,801,17,10,16.0,18,16.0,16,0.0,55,,54.0,15.0,11,2008-10-19 07:00:00 +19946,801,14,6,11.0,7,,20,0.0,2,,2.0,20.0,4,2008-10-19 07:00:00 +19947,801,4,0,23.0,5,,18,0.0,49,,32.0,11.0,9,2008-10-19 07:00:00 +19948,801,15,9,20.0,19,,19,0.0,13,,13.0,19.0,5,2008-10-19 07:00:00 +19949,801,6,4,14.0,8,13.0,13,0.0,56,5608860.0,36.0,12.0,1,2008-10-19 07:00:00 +19950,801,20,9,21.0,20,17.0,17,0.0,55,,54.0,18.0,11,2008-10-19 07:00:00 +19951,801,5,2,8.0,17,12.0,12,0.0,56,5608250.0,54.0,17.0,1,2008-10-19 07:00:00 +19952,801,1,1,3.0,9,5.0,5,4.0,56,5546326.0,56.0,3.0,1,2008-10-19 07:00:00 +19953,801,13,8,9.0,15,10.0,10,0.0,56,5592245.0,27.0,14.0,1,2008-10-19 07:00:00 +19954,801,19,4,15.0,6,9.0,9,0.0,56,5581742.0,55.0,9.0,1,2008-10-19 07:00:00 +19955,801,11,3,6.0,10,8.0,8,1.0,56,5574048.0,56.0,8.0,1,2008-10-19 07:00:00 +19956,801,9,6,12.0,12,7.0,7,2.0,56,5559125.0,56.0,6.0,1,2008-10-19 07:00:00 +19957,801,8,1,4.0,11,6.0,6,3.0,56,5550622.0,56.0,7.0,1,2008-10-19 07:00:00 +19958,801,3,3,5.0,4,4.0,4,5.0,56,5535773.0,56.0,5.0,1,2008-10-19 07:00:00 +19959,801,7,5,1.0,2,3.0,3,6.0,56,5533848.0,14.0,2.0,1,2008-10-19 07:00:00 +19960,801,12,5,2.0,3,2.0,2,8.0,56,5532328.0,36.0,4.0,1,2008-10-19 07:00:00 +19961,801,0,0,22.0,1,1.0,1,10.0,56,5517403.0,13.0,1.0,1,2008-10-19 07:00:00 +19962,801,21,10,17.0,13,11.0,11,0.0,56,5602464.0,56.0,16.0,1,2008-10-19 07:00:00 +19963,802,0,0,22.0,4,5.0,5,4.0,71,5690342.0,31.0,4.0,1,2008-11-02 17:00:00 +19964,802,12,5,2.0,1,1.0,1,10.0,71,5651435.0,36.0,1.0,1,2008-11-02 17:00:00 +19965,802,3,3,5.0,6,2.0,2,8.0,71,5664733.0,39.0,8.0,1,2008-11-02 17:00:00 +19966,802,7,5,1.0,3,3.0,3,6.0,71,5667670.0,59.0,3.0,1,2008-11-02 17:00:00 +19967,802,19,4,15.0,7,4.0,4,5.0,71,5689446.0,25.0,7.0,1,2008-11-02 17:00:00 +19968,802,9,6,12.0,10,6.0,6,3.0,71,5695803.0,32.0,2.0,1,2008-11-02 17:00:00 +19969,802,5,2,8.0,16,17.0,17,0.0,69,,50.0,18.0,12,2008-11-02 17:00:00 +19970,802,14,6,11.0,2,8.0,8,1.0,71,5719868.0,40.0,5.0,1,2008-11-02 17:00:00 +19971,802,4,0,23.0,5,7.0,7,2.0,71,5706509.0,36.0,6.0,1,2008-11-02 17:00:00 +19972,802,13,8,9.0,14,,20,0.0,0,,,,4,2008-11-02 17:00:00 +19973,802,11,3,6.0,11,,19,0.0,0,,,,3,2008-11-02 17:00:00 +19974,802,20,9,21.0,19,18.0,18,0.0,69,,36.0,15.0,12,2008-11-02 17:00:00 +19975,802,15,9,20.0,20,16.0,16,0.0,69,,60.0,17.0,12,2008-11-02 17:00:00 +19976,802,8,1,4.0,13,11.0,11,0.0,70,,61.0,9.0,11,2008-11-02 17:00:00 +19977,802,6,4,14.0,9,14.0,14,0.0,70,,57.0,13.0,11,2008-11-02 17:00:00 +19978,802,17,10,16.0,17,13.0,13,0.0,70,,59.0,11.0,11,2008-11-02 17:00:00 +19979,802,2,2,7.0,18,12.0,12,0.0,70,,35.0,12.0,11,2008-11-02 17:00:00 +19980,802,1,1,3.0,8,10.0,10,0.0,70,,41.0,10.0,11,2008-11-02 17:00:00 +19981,802,16,8,10.0,12,9.0,9,0.0,71,5731101.0,40.0,14.0,1,2008-11-02 17:00:00 +19982,802,21,10,17.0,15,15.0,15,0.0,70,,35.0,16.0,11,2008-11-02 17:00:00 +19983,803,0,0,1.0,18,,20,0.0,58,,39.0,13.0,2,2009-03-29 06:00:00 +19984,803,4,0,2.0,12,,19,0.0,0,,,,4,2009-03-29 06:00:00 +19985,803,5,2,17.0,11,,18,0.0,17,,6.0,18.0,3,2009-03-29 06:00:00 +19986,803,11,3,8.0,14,,17,0.0,24,,17.0,19.0,20,2009-03-29 06:00:00 +19987,803,12,5,3.0,6,,16,0.0,45,,30.0,15.0,22,2009-03-29 06:00:00 +19988,803,7,5,4.0,7,15.0,15,0.0,55,,35.0,7.0,24,2009-03-29 06:00:00 +19989,803,8,1,5.0,4,14.0,14,0.0,55,,36.0,2.0,4,2009-03-29 06:00:00 +19990,803,19,8,15.0,3,13.0,13,0.0,56,,8.0,4.0,4,2009-03-29 06:00:00 +19991,803,16,8,14.0,8,12.0,12,0.0,57,,38.0,8.0,11,2009-03-29 06:00:00 +19992,803,1,1,6.0,9,10.0,10,0.0,58,5662869.0,48.0,5.0,1,2009-03-29 06:00:00 +19993,803,20,9,21.0,15,11.0,11,0.0,58,5663158.0,51.0,12.0,1,2009-03-29 06:00:00 +19994,803,21,22,23.0,2,2.0,2,8.0,58,5656591.0,43.0,14.0,1,2009-03-29 06:00:00 +19995,803,14,6,9.0,20,3.0,3,6.0,58,5657388.0,50.0,10.0,1,2009-03-29 06:00:00 +19996,803,9,6,10.0,19,4.0,4,5.0,58,5660219.0,53.0,6.0,1,2009-03-29 06:00:00 +19997,803,17,22,22.0,1,1.0,1,10.0,58,5655784.0,17.0,3.0,1,2009-03-29 06:00:00 +19998,803,2,2,16.0,5,6.0,6,3.0,58,5661506.0,48.0,1.0,1,2009-03-29 06:00:00 +19999,803,66,4,12.0,13,7.0,7,2.0,58,5661788.0,34.0,16.0,1,2009-03-29 06:00:00 +20000,803,6,4,11.0,17,8.0,8,1.0,58,5662082.0,50.0,17.0,1,2009-03-29 06:00:00 +20001,803,3,3,7.0,10,5.0,5,4.0,58,5660663.0,53.0,9.0,1,2009-03-29 06:00:00 +20002,803,15,9,20.0,16,9.0,9,0.0,58,5662119.0,43.0,11.0,1,2009-03-29 06:00:00 +20003,804,66,4,12.0,20,16.0,16,0.0,30,,16.0,8.0,20,2009-04-05 09:00:00 +20004,804,15,9,20.0,19,17.0,17,0.0,30,,17.0,18.0,11,2009-04-05 09:00:00 +20005,804,20,9,21.0,18,18.0,18,0.0,29,,16.0,17.0,20,2009-04-05 09:00:00 +20006,804,8,1,5.0,6,,19,0.0,1,,,,5,2009-04-05 09:00:00 +20007,804,4,0,2.0,14,,20,0.0,0,,,,20,2009-04-05 09:00:00 +20008,804,7,5,4.0,7,14.0,14,0.0,31,,17.0,7.0,11,2009-04-05 09:00:00 +20009,804,11,3,8.0,17,13.0,13,0.0,31,,18.0,14.0,11,2009-04-05 09:00:00 +20010,804,17,22,22.0,1,1.0,1,5.0,31,4252092.0,18.0,1.0,1,2009-04-05 09:00:00 +20011,804,19,8,15.0,13,15.0,15,0.0,30,,10.0,6.0,20,2009-04-05 09:00:00 +20012,804,5,2,17.0,11,12.0,12,0.0,31,,17.0,15.0,11,2009-04-05 09:00:00 +20013,804,6,4,11.0,15,10.0,10,0.0,31,4354256.0,17.0,12.0,1,2009-04-05 09:00:00 +20014,804,12,5,3.0,16,9.0,9,0.0,31,4329024.0,17.0,13.0,1,2009-04-05 09:00:00 +20015,804,2,2,16.0,4,8.0,8,0.5,31,4323668.0,13.0,4.0,1,2009-04-05 09:00:00 +20016,804,3,3,7.0,9,11.0,11,0.0,31,,17.0,9.0,11,2009-04-05 09:00:00 +20017,804,16,8,14.0,5,6.0,6,1.5,31,4304425.0,14.0,5.0,1,2009-04-05 09:00:00 +20018,804,21,22,23.0,8,5.0,5,2.0,31,4299452.0,17.0,2.0,1,2009-04-05 09:00:00 +20019,804,14,6,9.0,2,4.0,4,2.5,31,4298265.0,12.0,3.0,1,2009-04-05 09:00:00 +20020,804,9,6,10.0,3,3.0,3,3.0,31,4275605.0,18.0,16.0,1,2009-04-05 09:00:00 +20021,804,1,1,6.0,10,2.0,2,4.0,31,4274814.0,17.0,10.0,1,2009-04-05 09:00:00 +20022,804,0,0,1.0,12,7.0,7,1.0,31,4312825.0,17.0,11.0,1,2009-04-05 09:00:00 +20023,805,8,1,5.0,17,13.0,13,0.0,56,7170338.0,44.0,14.0,1,2009-04-19 07:00:00 +20024,805,14,6,9.0,6,,20,0.0,18,,14.0,20.0,4,2009-04-19 07:00:00 +20025,805,12,5,3.0,13,,19,0.0,20,,16.0,19.0,40,2009-04-19 07:00:00 +20026,805,5,2,17.0,14,,18,0.0,43,,38.0,17.0,31,2009-04-19 07:00:00 +20027,805,15,9,20.0,18,17.0,17,0.0,50,,41.0,13.0,20,2009-04-19 07:00:00 +20028,805,11,3,8.0,16,16.0,16,0.0,54,,42.0,16.0,12,2009-04-19 07:00:00 +20029,805,2,2,16.0,7,15.0,15,0.0,55,,55.0,8.0,11,2009-04-19 07:00:00 +20030,805,20,9,21.0,20,14.0,14,0.0,55,,37.0,18.0,11,2009-04-19 07:00:00 +20031,805,1,1,6.0,11,12.0,12,0.0,56,7159319.0,40.0,7.0,1,2009-04-19 07:00:00 +20032,805,7,5,4.0,8,10.0,10,0.0,56,7155235.0,38.0,15.0,1,2009-04-19 07:00:00 +20033,805,16,8,14.0,3,2.0,2,8.0,56,7074455.0,42.0,4.0,1,2009-04-19 07:00:00 +20034,805,3,3,7.0,2,9.0,9,0.0,56,7147794.0,38.0,9.0,1,2009-04-19 07:00:00 +20035,805,66,4,12.0,10,8.0,8,1.0,56,7139924.0,42.0,11.0,1,2009-04-19 07:00:00 +20036,805,9,6,10.0,19,7.0,7,2.0,56,7137961.0,42.0,3.0,1,2009-04-19 07:00:00 +20037,805,0,0,1.0,9,6.0,6,3.0,56,7135351.0,39.0,12.0,1,2009-04-19 07:00:00 +20038,805,4,0,2.0,12,5.0,5,4.0,56,7128587.0,41.0,10.0,1,2009-04-19 07:00:00 +20039,805,21,22,23.0,4,4.0,4,5.0,56,7127189.0,42.0,1.0,1,2009-04-19 07:00:00 +20040,805,17,22,22.0,5,3.0,3,6.0,56,7108460.0,44.0,6.0,1,2009-04-19 07:00:00 +20041,805,6,4,11.0,15,11.0,11,0.0,56,7157641.0,43.0,5.0,1,2009-04-19 07:00:00 +20042,805,19,8,15.0,1,1.0,1,10.0,56,7063485.0,42.0,2.0,1,2009-04-19 07:00:00 +20043,806,12,5,3.0,8,14.0,14,0.0,56,,41.0,7.0,11,2009-04-26 12:00:00 +20044,806,20,9,21.0,17,15.0,15,0.0,56,,9.0,19.0,11,2009-04-26 12:00:00 +20045,806,15,9,20.0,19,16.0,16,0.0,56,,28.0,18.0,11,2009-04-26 12:00:00 +20046,806,6,4,11.0,20,13.0,13,0.0,57,5586987.0,30.0,9.0,1,2009-04-26 12:00:00 +20047,806,8,1,5.0,13,18.0,18,0.0,56,,50.0,13.0,11,2009-04-26 12:00:00 +20048,806,1,1,6.0,14,19.0,19,0.0,56,,52.0,16.0,11,2009-04-26 12:00:00 +20049,806,66,4,12.0,16,17.0,17,0.0,56,,38.0,20.0,11,2009-04-26 12:00:00 +20050,806,4,0,2.0,11,12.0,12,0.0,57,5586006.0,54.0,12.0,1,2009-04-26 12:00:00 +20051,806,5,2,17.0,12,,20,0.0,48,,39.0,17.0,51,2009-04-26 12:00:00 +20052,806,11,3,8.0,15,10.0,10,0.0,57,5573331.0,37.0,10.0,1,2009-04-26 12:00:00 +20053,806,16,8,14.0,18,11.0,11,0.0,57,5575823.0,50.0,8.0,1,2009-04-26 12:00:00 +20054,806,19,8,15.0,3,2.0,2,8.0,57,5515369.0,16.0,4.0,1,2009-04-26 12:00:00 +20055,806,14,6,9.0,1,3.0,3,6.0,57,5517352.0,10.0,1.0,1,2009-04-26 12:00:00 +20056,806,0,0,1.0,5,4.0,4,5.0,57,5530278.0,13.0,6.0,1,2009-04-26 12:00:00 +20057,806,17,22,22.0,4,1.0,1,10.0,57,5508182.0,11.0,3.0,1,2009-04-26 12:00:00 +20058,806,7,5,4.0,10,6.0,6,3.0,57,5550239.0,42.0,11.0,1,2009-04-26 12:00:00 +20059,806,9,6,10.0,2,7.0,7,2.0,57,5551062.0,6.0,2.0,1,2009-04-26 12:00:00 +20060,806,3,3,7.0,7,8.0,8,1.0,57,5560957.0,29.0,14.0,1,2009-04-26 12:00:00 +20061,806,2,2,16.0,9,9.0,9,0.0,57,5566380.0,37.0,15.0,1,2009-04-26 12:00:00 +20062,806,21,22,23.0,6,5.0,5,4.0,57,5545961.0,25.0,5.0,1,2009-04-26 12:00:00 +20063,807,5,2,17.0,11,13.0,13,0.0,65,,38.0,13.0,11,2009-05-10 12:00:00 +20064,807,15,9,20.0,19,,20,0.0,0,,,,4,2009-05-10 12:00:00 +20065,807,6,4,11.0,17,,19,0.0,0,,,,4,2009-05-10 12:00:00 +20066,807,66,4,12.0,15,,18,0.0,0,,,,4,2009-05-10 12:00:00 +20067,807,14,6,9.0,7,,17,0.0,0,,,,4,2009-05-10 12:00:00 +20068,807,4,0,2.0,18,,16,0.0,7,,6.0,16.0,6,2009-05-10 12:00:00 +20069,807,7,5,4.0,16,,15,0.0,17,,16.0,15.0,9,2009-05-10 12:00:00 +20070,807,20,9,21.0,20,14.0,14,0.0,65,,63.0,8.0,11,2009-05-10 12:00:00 +20071,807,11,3,8.0,12,12.0,12,0.0,65,,41.0,14.0,11,2009-05-10 12:00:00 +20072,807,8,1,5.0,10,11.0,11,0.0,65,,26.0,11.0,11,2009-05-10 12:00:00 +20073,807,9,6,10.0,6,10.0,10,0.0,65,,44.0,12.0,11,2009-05-10 12:00:00 +20074,807,21,22,23.0,3,2.0,2,8.0,66,5852258.0,28.0,1.0,1,2009-05-10 12:00:00 +20075,807,16,8,14.0,5,3.0,3,6.0,66,5853126.0,18.0,5.0,1,2009-05-10 12:00:00 +20076,807,19,8,15.0,2,4.0,4,5.0,66,5858143.0,41.0,4.0,1,2009-05-10 12:00:00 +20077,807,3,3,7.0,8,5.0,5,4.0,66,5882368.0,14.0,6.0,1,2009-05-10 12:00:00 +20078,807,17,22,22.0,1,1.0,1,10.0,66,5839202.0,17.0,2.0,1,2009-05-10 12:00:00 +20079,807,1,1,6.0,13,7.0,7,2.0,66,5891514.0,29.0,10.0,1,2009-05-10 12:00:00 +20080,807,2,2,16.0,9,8.0,8,1.0,66,5904413.0,24.0,7.0,1,2009-05-10 12:00:00 +20081,807,0,0,1.0,14,9.0,9,0.0,65,,29.0,9.0,11,2009-05-10 12:00:00 +20082,807,12,5,3.0,4,6.0,6,3.0,66,5890029.0,14.0,3.0,1,2009-05-10 12:00:00 +20083,808,14,6,9.0,18,13.0,13,0.0,77,,57.0,11.0,11,2009-05-24 12:00:00 +20084,808,66,4,12.0,11,,20,0.0,10,,7.0,20.0,4,2009-05-24 12:00:00 +20085,808,11,3,8.0,12,,19,0.0,10,,7.0,19.0,4,2009-05-24 12:00:00 +20086,808,19,8,15.0,4,,18,0.0,15,,15.0,18.0,3,2009-05-24 12:00:00 +20087,808,8,1,5.0,17,,17,0.0,28,,25.0,17.0,23,2009-05-24 12:00:00 +20088,808,4,0,2.0,7,,16,0.0,51,,48.0,6.0,3,2009-05-24 12:00:00 +20089,808,5,2,17.0,10,15.0,15,0.0,76,,73.0,10.0,3,2009-05-24 12:00:00 +20090,808,15,9,20.0,15,14.0,14,0.0,77,,66.0,14.0,11,2009-05-24 12:00:00 +20091,808,0,0,1.0,19,12.0,12,0.0,77,,65.0,8.0,11,2009-05-24 12:00:00 +20092,808,17,22,22.0,1,1.0,1,10.0,78,6044282.0,49.0,2.0,1,2009-05-24 12:00:00 +20093,808,9,6,10.0,20,10.0,10,0.0,77,,72.0,12.0,11,2009-05-24 12:00:00 +20094,808,1,1,6.0,16,11.0,11,0.0,77,,49.0,15.0,11,2009-05-24 12:00:00 +20095,808,7,5,4.0,2,3.0,3,6.0,78,6057724.0,47.0,5.0,1,2009-05-24 12:00:00 +20096,808,12,5,3.0,5,4.0,4,5.0,78,6059392.0,50.0,1.0,1,2009-05-24 12:00:00 +20097,808,16,8,14.0,8,5.0,5,4.0,78,6060012.0,45.0,3.0,1,2009-05-24 12:00:00 +20098,808,21,22,23.0,3,2.0,2,8.0,78,6051948.0,46.0,7.0,1,2009-05-24 12:00:00 +20099,808,3,3,7.0,9,7.0,7,2.0,78,6082121.0,64.0,4.0,1,2009-05-24 12:00:00 +20100,808,6,4,11.0,14,8.0,8,1.0,78,6107424.0,47.0,13.0,1,2009-05-24 12:00:00 +20101,808,20,9,21.0,13,9.0,9,0.0,78,6109322.0,74.0,16.0,1,2009-05-24 12:00:00 +20102,808,2,2,16.0,6,6.0,6,3.0,78,6077868.0,48.0,9.0,1,2009-05-24 12:00:00 +20103,809,20,9,21.0,19,,20,0.0,4,,3.0,20.0,23,2009-06-07 12:00:00 +20104,809,21,22,23.0,3,,19,0.0,47,,37.0,14.0,6,2009-06-07 12:00:00 +20105,809,6,4,11.0,20,18.0,18,0.0,57,,53.0,17.0,11,2009-06-07 12:00:00 +20106,809,15,9,20.0,15,17.0,17,0.0,57,,55.0,19.0,11,2009-06-07 12:00:00 +20107,809,11,3,8.0,17,16.0,16,0.0,57,,45.0,12.0,11,2009-06-07 12:00:00 +20108,809,66,4,12.0,18,15.0,15,0.0,57,,57.0,16.0,11,2009-06-07 12:00:00 +20109,809,4,0,2.0,14,14.0,14,0.0,57,,41.0,18.0,11,2009-06-07 12:00:00 +20110,809,5,2,17.0,12,12.0,12,0.0,58,5251224.0,58.0,6.0,1,2009-06-07 12:00:00 +20111,809,0,0,1.0,16,13.0,13,0.0,58,5265302.0,53.0,15.0,1,2009-06-07 12:00:00 +20112,809,3,3,7.0,8,10.0,10,0.0,58,5247268.0,57.0,13.0,1,2009-06-07 12:00:00 +20113,809,1,1,6.0,11,11.0,11,0.0,58,5249175.0,43.0,10.0,1,2009-06-07 12:00:00 +20114,809,16,8,14.0,4,2.0,2,8.0,58,5191562.0,42.0,3.0,1,2009-06-07 12:00:00 +20115,809,19,8,15.0,1,3.0,3,6.0,58,5192309.0,51.0,2.0,1,2009-06-07 12:00:00 +20116,809,14,6,9.0,5,4.0,4,5.0,58,5212691.0,40.0,4.0,1,2009-06-07 12:00:00 +20117,809,17,22,22.0,2,1.0,1,10.0,58,5184848.0,40.0,1.0,1,2009-06-07 12:00:00 +20118,809,12,5,3.0,7,6.0,6,3.0,58,5224844.0,41.0,9.0,1,2009-06-07 12:00:00 +20119,809,8,1,5.0,10,7.0,7,2.0,58,5231095.0,58.0,7.0,1,2009-06-07 12:00:00 +20120,809,9,6,10.0,13,8.0,8,1.0,58,5231807.0,56.0,5.0,1,2009-06-07 12:00:00 +20121,809,7,5,4.0,6,9.0,9,0.0,58,5235094.0,58.0,8.0,1,2009-06-07 12:00:00 +20122,809,2,2,16.0,9,5.0,5,4.0,58,5216387.0,36.0,11.0,1,2009-06-07 12:00:00 +20123,810,8,1,5.0,12,13.0,13,0.0,59,,41.0,14.0,11,2009-06-21 12:00:00 +20124,810,4,0,2.0,13,,20,0.0,36,,32.0,15.0,4,2009-06-21 12:00:00 +20125,810,6,4,11.0,17,,19,0.0,37,,26.0,16.0,4,2009-06-21 12:00:00 +20126,810,66,4,12.0,19,18.0,18,0.0,59,,24.0,19.0,11,2009-06-21 12:00:00 +20127,810,15,9,20.0,20,17.0,17,0.0,59,,50.0,20.0,11,2009-06-21 12:00:00 +20128,810,0,0,1.0,18,16.0,16,0.0,59,,24.0,18.0,11,2009-06-21 12:00:00 +20129,810,1,1,6.0,15,15.0,15,0.0,59,,59.0,13.0,11,2009-06-21 12:00:00 +20130,810,3,3,7.0,10,14.0,14,0.0,59,,36.0,12.0,11,2009-06-21 12:00:00 +20131,810,11,3,8.0,14,12.0,12,0.0,59,,25.0,17.0,11,2009-06-21 12:00:00 +20132,810,5,2,17.0,5,11.0,11,0.0,60,5043351.0,14.0,11.0,1,2009-06-21 12:00:00 +20133,810,20,9,21.0,16,10.0,10,0.0,60,5040850.0,20.0,10.0,1,2009-06-21 12:00:00 +20134,810,19,8,15.0,1,1.0,1,10.0,60,4969328.0,16.0,1.0,1,2009-06-21 12:00:00 +20135,810,21,22,23.0,2,3.0,3,6.0,60,5010503.0,18.0,5.0,1,2009-06-21 12:00:00 +20136,810,12,5,3.0,11,4.0,4,5.0,60,5014371.0,22.0,6.0,1,2009-06-21 12:00:00 +20137,810,2,2,16.0,7,5.0,5,4.0,60,5015243.0,17.0,3.0,1,2009-06-21 12:00:00 +20138,810,16,8,14.0,3,2.0,2,8.0,60,4984516.0,57.0,2.0,1,2009-06-21 12:00:00 +20139,810,14,6,9.0,4,7.0,7,2.0,60,5037635.0,17.0,9.0,1,2009-06-21 12:00:00 +20140,810,7,5,4.0,9,8.0,8,1.0,60,5038950.0,14.0,7.0,1,2009-06-21 12:00:00 +20141,810,9,6,10.0,8,9.0,9,0.0,60,5039151.0,51.0,8.0,1,2009-06-21 12:00:00 +20142,810,17,22,22.0,6,6.0,6,3.0,60,5015613.0,54.0,4.0,1,2009-06-21 12:00:00 +20143,811,11,3,8.0,10,13.0,13,0.0,60,5871638.0,46.0,12.0,1,2009-07-12 12:00:00 +20144,811,6,4,11.0,19,,20,0.0,18,,10.0,20.0,9,2009-07-12 12:00:00 +20145,811,7,5,4.0,9,,19,0.0,34,,4.0,18.0,5,2009-07-12 12:00:00 +20146,811,0,0,1.0,5,18.0,18,0.0,59,,46.0,15.0,11,2009-07-12 12:00:00 +20147,811,14,6,9.0,14,17.0,17,0.0,60,5894280.0,52.0,2.0,1,2009-07-12 12:00:00 +20148,811,15,9,20.0,7,15.0,15,0.0,60,5875251.0,43.0,14.0,1,2009-07-12 12:00:00 +20149,811,8,1,5.0,16,14.0,14,0.0,60,5872865.0,47.0,9.0,1,2009-07-12 12:00:00 +20150,811,5,2,17.0,13,12.0,12,0.0,60,5866186.0,49.0,5.0,1,2009-07-12 12:00:00 +20151,811,66,4,12.0,17,16.0,16,0.0,60,5893535.0,24.0,19.0,1,2009-07-12 12:00:00 +20152,811,1,1,6.0,11,10.0,10,0.0,60,5865235.0,42.0,10.0,1,2009-07-12 12:00:00 +20153,811,16,8,14.0,1,1.0,1,10.0,60,5803310.0,37.0,3.0,1,2009-07-12 12:00:00 +20154,811,19,8,15.0,4,2.0,2,8.0,60,5812562.0,42.0,4.0,1,2009-07-12 12:00:00 +20155,811,12,5,3.0,8,3.0,3,6.0,60,5819216.0,53.0,8.0,1,2009-07-12 12:00:00 +20156,811,2,2,16.0,15,4.0,4,5.0,60,5824409.0,50.0,7.0,1,2009-07-12 12:00:00 +20157,811,20,9,21.0,18,11.0,11,0.0,60,5865637.0,54.0,13.0,1,2009-07-12 12:00:00 +20158,811,21,22,23.0,2,6.0,6,3.0,60,5827778.0,54.0,11.0,1,2009-07-12 12:00:00 +20159,811,3,3,7.0,12,7.0,7,2.0,60,5828198.0,49.0,1.0,1,2009-07-12 12:00:00 +20160,811,4,0,2.0,6,8.0,8,1.0,60,5862002.0,59.0,17.0,1,2009-07-12 12:00:00 +20161,811,9,6,10.0,20,9.0,9,0.0,60,5864767.0,40.0,16.0,1,2009-07-12 12:00:00 +20162,811,17,22,22.0,3,5.0,5,4.0,60,5826919.0,53.0,6.0,1,2009-07-12 12:00:00 +20163,812,8,1,5.0,18,13.0,13,0.0,70,5977922.0,65.0,12.0,1,2009-07-26 12:00:00 +20164,812,12,5,3.0,0,,20,0.0,0,,,,54,2009-07-26 12:00:00 +20165,812,15,9,20.0,17,,19,0.0,1,,,,25,2009-07-26 12:00:00 +20166,812,3,3,7.0,1,,18,0.0,15,,4.0,18.0,36,2009-07-26 12:00:00 +20167,812,19,8,15.0,2,,17,0.0,29,,18.0,17.0,22,2009-07-26 12:00:00 +20168,812,66,4,12.0,10,16.0,16,0.0,69,,69.0,7.0,11,2009-07-26 12:00:00 +20169,812,152,4,11.0,19,15.0,15,0.0,69,,69.0,16.0,11,2009-07-26 12:00:00 +20170,812,20,9,21.0,16,14.0,14,0.0,69,,40.0,10.0,11,2009-07-26 12:00:00 +20171,812,11,3,8.0,14,12.0,12,0.0,70,5975388.0,65.0,15.0,1,2009-07-26 12:00:00 +20172,812,1,1,6.0,15,11.0,11,0.0,70,5974488.0,65.0,14.0,1,2009-07-26 12:00:00 +20173,812,21,22,23.0,12,10.0,10,0.0,70,5973132.0,55.0,9.0,1,2009-07-26 12:00:00 +20174,812,7,5,4.0,7,2.0,2,8.0,70,5915405.0,70.0,2.0,1,2009-07-26 12:00:00 +20175,812,16,8,14.0,3,3.0,3,6.0,70,5920762.0,65.0,1.0,1,2009-07-26 12:00:00 +20176,812,2,2,16.0,5,4.0,4,5.0,70,5930843.0,65.0,3.0,1,2009-07-26 12:00:00 +20177,812,4,0,2.0,6,5.0,5,4.0,70,5938268.0,63.0,8.0,1,2009-07-26 12:00:00 +20178,812,0,0,1.0,4,1.0,1,10.0,70,5903876.0,16.0,4.0,1,2009-07-26 12:00:00 +20179,812,17,22,22.0,8,7.0,7,2.0,70,5958964.0,57.0,6.0,1,2009-07-26 12:00:00 +20180,812,14,6,9.0,11,8.0,8,1.0,70,5972048.0,65.0,13.0,1,2009-07-26 12:00:00 +20181,812,5,2,17.0,9,9.0,9,0.0,70,5972650.0,55.0,11.0,1,2009-07-26 12:00:00 +20182,812,9,6,10.0,13,6.0,6,3.0,70,5939113.0,63.0,5.0,1,2009-07-26 12:00:00 +20183,813,14,6,9.0,18,13.0,13,0.0,57,5815816.0,52.0,15.0,1,2009-08-23 12:00:00 +20184,813,19,8,15.0,4,,20,0.0,23,,13.0,16.0,5,2009-08-23 12:00:00 +20185,813,66,4,12.0,15,,19,0.0,41,,37.0,20.0,23,2009-08-23 12:00:00 +20186,813,5,2,17.0,17,18.0,18,0.0,54,,53.0,14.0,13,2009-08-23 12:00:00 +20187,813,68,5,3.0,20,17.0,17,0.0,56,,52.0,18.0,11,2009-08-23 12:00:00 +20188,813,152,4,11.0,19,16.0,16,0.0,56,,29.0,19.0,11,2009-08-23 12:00:00 +20189,813,153,3,8.0,14,15.0,15,0.0,57,5843063.0,41.0,9.0,1,2009-08-23 12:00:00 +20190,813,9,6,10.0,13,14.0,14,0.0,57,5837808.0,55.0,1.0,1,2009-08-23 12:00:00 +20191,813,20,9,21.0,16,12.0,12,0.0,57,5814903.0,53.0,17.0,1,2009-08-23 12:00:00 +20192,813,21,22,23.0,3,1.0,1,10.0,57,5751289.0,39.0,3.0,1,2009-08-23 12:00:00 +20193,813,15,9,20.0,12,10.0,10,0.0,57,5799224.0,36.0,12.0,1,2009-08-23 12:00:00 +20194,813,16,8,14.0,9,9.0,9,0.0,57,5796199.0,50.0,11.0,1,2009-08-23 12:00:00 +20195,813,8,1,5.0,10,8.0,8,1.0,57,5787956.0,55.0,8.0,1,2009-08-23 12:00:00 +20196,813,17,22,22.0,5,7.0,7,2.0,57,5786202.0,46.0,2.0,1,2009-08-23 12:00:00 +20197,813,3,3,7.0,8,6.0,6,3.0,57,5779033.0,46.0,10.0,1,2009-08-23 12:00:00 +20198,813,2,2,16.0,7,5.0,5,4.0,57,5772159.0,52.0,6.0,1,2009-08-23 12:00:00 +20199,813,4,0,2.0,2,4.0,4,5.0,57,5771321.0,56.0,7.0,1,2009-08-23 12:00:00 +20200,813,7,5,4.0,6,3.0,3,6.0,57,5767283.0,39.0,5.0,1,2009-08-23 12:00:00 +20201,813,0,0,1.0,1,2.0,2,8.0,57,5753647.0,57.0,4.0,1,2009-08-23 12:00:00 +20202,813,1,1,6.0,11,11.0,11,0.0,57,5800111.0,53.0,13.0,1,2009-08-23 12:00:00 +20203,814,68,5,3.0,20,14.0,14,0.0,44,5133172.0,41.0,15.0,1,2009-08-30 12:00:00 +20204,814,3,3,7.0,13,,15,0.0,26,,23.0,14.0,31,2009-08-30 12:00:00 +20205,814,5,2,17.0,18,13.0,13,0.0,44,5085236.0,42.0,11.0,1,2009-08-30 12:00:00 +20206,814,152,4,11.0,17,,20,0.0,0,,,,4,2009-08-30 12:00:00 +20207,814,17,22,22.0,14,,17,0.0,0,,,,4,2009-08-30 12:00:00 +20208,814,153,3,8.0,19,,18,0.0,0,,,,4,2009-08-30 12:00:00 +20209,814,0,0,1.0,12,,19,0.0,0,,,,4,2009-08-30 12:00:00 +20210,814,14,6,9.0,2,,16,0.0,21,,16.0,16.0,23,2009-08-30 12:00:00 +20211,814,66,4,12.0,16,12.0,12,0.0,44,5077101.0,42.0,7.0,1,2009-08-30 12:00:00 +20212,814,21,22,23.0,4,7.0,7,2.0,44,5066456.0,37.0,12.0,1,2009-08-30 12:00:00 +20213,814,9,6,10.0,7,10.0,10,0.0,44,5072485.0,40.0,5.0,1,2009-08-30 12:00:00 +20214,814,16,8,14.0,9,9.0,9,0.0,44,5067954.0,39.0,9.0,1,2009-08-30 12:00:00 +20215,814,2,2,16.0,10,8.0,8,1.0,44,5067203.0,41.0,8.0,1,2009-08-30 12:00:00 +20216,814,4,0,2.0,15,6.0,6,3.0,44,5063758.0,24.0,13.0,1,2009-08-30 12:00:00 +20217,814,1,1,6.0,3,5.0,5,4.0,44,5042271.0,35.0,2.0,1,2009-08-30 12:00:00 +20218,814,8,1,5.0,5,4.0,4,5.0,44,5040961.0,41.0,3.0,1,2009-08-30 12:00:00 +20219,814,19,8,15.0,8,3.0,3,6.0,44,5034870.0,38.0,1.0,1,2009-08-30 12:00:00 +20220,814,20,9,21.0,1,2.0,2,8.0,44,5031934.0,43.0,6.0,1,2009-08-30 12:00:00 +20221,814,15,9,20.0,11,11.0,11,0.0,44,5073631.0,42.0,10.0,1,2009-08-30 12:00:00 +20222,814,7,5,4.0,6,1.0,1,10.0,44,5030995.0,42.0,4.0,1,2009-08-30 12:00:00 +20223,815,14,6,9.0,11,14.0,14,0.0,52,,49.0,13.0,11,2009-09-13 12:00:00 +20224,815,153,3,8.0,12,15.0,15,0.0,52,,51.0,12.0,11,2009-09-13 12:00:00 +20225,815,2,2,16.0,18,16.0,16,0.0,51,,50.0,15.0,12,2009-09-13 12:00:00 +20226,815,16,8,14.0,10,,20,0.0,0,,,,4,2009-09-13 12:00:00 +20227,815,152,4,11.0,20,,18,0.0,19,,17.0,19.0,31,2009-09-13 12:00:00 +20228,815,8,1,5.0,13,,19,0.0,15,,12.0,18.0,44,2009-09-13 12:00:00 +20229,815,66,4,12.0,19,13.0,13,0.0,52,,50.0,11.0,11,2009-09-13 12:00:00 +20230,815,23,9,21.0,7,,17,0.0,22,,22.0,17.0,7,2009-09-13 12:00:00 +20231,815,0,0,1.0,1,12.0,12,0.0,52,,52.0,3.0,3,2009-09-13 12:00:00 +20232,815,1,1,6.0,15,7.0,7,2.0,53,4664118.0,30.0,9.0,1,2009-09-13 12:00:00 +20233,815,5,2,17.0,17,10.0,10,0.0,53,4743869.0,51.0,16.0,1,2009-09-13 12:00:00 +20234,815,21,22,23.0,5,1.0,1,10.0,53,4581706.0,48.0,5.0,1,2009-09-13 12:00:00 +20235,815,17,22,22.0,6,2.0,2,8.0,53,4584572.0,46.0,4.0,1,2009-09-13 12:00:00 +20236,815,7,5,4.0,3,3.0,3,6.0,53,4612370.0,36.0,2.0,1,2009-09-13 12:00:00 +20237,815,15,9,20.0,2,4.0,4,5.0,53,4612837.0,36.0,1.0,1,2009-09-13 12:00:00 +20238,815,9,6,10.0,16,11.0,11,0.0,53,4745631.0,50.0,14.0,1,2009-09-13 12:00:00 +20239,815,4,0,2.0,4,6.0,6,3.0,53,4642399.0,51.0,6.0,1,2009-09-13 12:00:00 +20240,815,19,8,15.0,9,8.0,8,1.0,53,4667113.0,50.0,7.0,1,2009-09-13 12:00:00 +20241,815,20,5,3.0,14,9.0,9,0.0,53,4668562.0,28.0,10.0,1,2009-09-13 12:00:00 +20242,815,3,3,7.0,8,5.0,5,4.0,53,4640888.0,50.0,8.0,1,2009-09-13 12:00:00 +20243,816,20,5,3.0,17,13.0,13,0.0,61,7046227.0,49.0,14.0,1,2009-09-27 12:00:00 +20244,816,153,3,8.0,18,,20,0.0,3,,2.0,20.0,23,2009-09-27 12:00:00 +20245,816,1,1,6.0,20,,19,0.0,19,,18.0,17.0,4,2009-09-27 12:00:00 +20246,816,16,8,14.0,4,,17,0.0,45,,35.0,12.0,23,2009-09-27 12:00:00 +20247,816,66,4,12.0,13,,16,0.0,47,,17.0,16.0,6,2009-09-27 12:00:00 +20248,816,152,4,11.0,16,,15,0.0,47,,32.0,18.0,23,2009-09-27 12:00:00 +20249,816,23,9,21.0,19,14.0,14,0.0,61,7059839.0,48.0,15.0,1,2009-09-27 12:00:00 +20250,816,14,6,9.0,14,12.0,12,0.0,61,7039346.0,54.0,9.0,1,2009-09-27 12:00:00 +20251,816,15,9,20.0,15,,18,0.0,23,,15.0,19.0,4,2009-09-27 12:00:00 +20252,816,7,5,4.0,12,10.0,10,0.0,61,7025229.0,54.0,5.0,1,2009-09-27 12:00:00 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11:00:00 +20319,819,21,22,23.0,4,4.0,4,5.0,55,5666149.0,54.0,4.0,1,2009-11-01 11:00:00 +20320,819,17,22,22.0,5,3.0,3,6.0,55,5661881.0,49.0,6.0,1,2009-11-01 11:00:00 +20321,819,16,8,14.0,3,2.0,2,8.0,55,5661271.0,14.0,5.0,1,2009-11-01 11:00:00 +20322,819,2,2,16.0,9,9.0,9,0.0,55,5689355.0,49.0,15.0,1,2009-11-01 11:00:00 diff --git a/scripts/f1_data/standings.csv b/scripts/f1_data/standings.csv new file mode 100644 index 00000000..6f3664d9 --- /dev/null +++ b/scripts/f1_data/standings.csv @@ -0,0 +1,28116 @@ +driverStandingsId,raceId,driverId,points,position,wins,date +0,0,789,0.0,20,0,1950-05-13 +1,0,640,0.0,18,0,1950-05-13 +2,0,589,0.0,19,0,1950-05-13 +3,0,669,0.0,15,0,1950-05-13 +4,0,661,0.0,22,0,1950-05-13 +5,0,790,0.0,23,0,1950-05-13 +6,0,788,0.0,10,0,1950-05-13 +7,0,786,6.0,2,0,1950-05-13 +8,0,686,4.0,3,0,1950-05-13 +9,0,666,0.0,21,0,1950-05-13 +10,0,776,0.0,14,0,1950-05-13 +11,0,579,0.0,13,0,1950-05-13 +12,0,660,0.0,12,0,1950-05-13 +13,0,642,9.0,1,1,1950-05-13 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00:00:00 +14368,318,199,0.0,15,0,1979-05-13 00:00:00 +14369,318,205,0.0,24,0,1979-05-13 00:00:00 +14370,318,222,0.0,19,0,1979-05-13 00:00:00 +14371,318,177,4.0,10,0,1979-05-13 00:00:00 +14372,318,172,0.0,14,0,1979-05-13 00:00:00 +14373,318,202,20.0,3,2,1979-05-13 00:00:00 +14374,318,206,12.0,6,0,1979-05-13 00:00:00 +14375,318,220,20.0,4,1,1979-05-13 00:00:00 +14376,318,186,5.0,9,0,1979-05-13 00:00:00 +14377,318,198,19.0,5,0,1979-05-13 00:00:00 +14378,318,171,24.0,1,2,1979-05-13 00:00:00 +14379,318,223,1.0,12,0,1979-05-13 00:00:00 +14380,318,211,0.0,25,0,1979-05-13 00:00:00 +14381,318,232,0.0,17,0,1979-05-13 00:00:00 +14382,318,230,0.0,18,0,1979-05-13 00:00:00 +14383,318,135,0.0,21,0,1979-05-13 00:00:00 +14384,318,151,0.0,26,0,1979-05-13 00:00:00 +14385,318,233,0.0,28,0,1979-05-13 00:00:00 +14386,318,118,2.0,11,0,1979-05-13 00:00:00 +14387,318,136,0.0,16,0,1979-05-13 00:00:00 +14388,318,174,0.0,22,0,1979-05-13 00:00:00 +14389,318,231,0.0,27,0,1979-05-13 00:00:00 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00:00:00 +14413,319,233,0.0,28,0,1979-05-27 00:00:00 +14414,319,232,0.0,18,0,1979-05-27 00:00:00 +14415,319,231,0.0,27,0,1979-05-27 00:00:00 +14416,319,136,0.0,17,0,1979-05-27 00:00:00 +14417,319,118,2.0,12,0,1979-05-27 00:00:00 +14418,319,201,8.0,8,0,1979-05-27 00:00:00 +14419,319,221,30.0,1,2,1979-05-27 00:00:00 +14420,319,162,0.0,20,0,1979-05-27 00:00:00 +14421,319,181,1.0,15,0,1979-05-27 00:00:00 +14422,319,218,0.0,23,0,1979-05-27 00:00:00 +14423,319,174,0.0,22,0,1979-05-27 00:00:00 +14424,320,177,7.0,12,0,1979-07-01 00:00:00 +14425,320,211,0.0,26,0,1979-07-01 00:00:00 +14426,320,202,26.0,2,2,1979-07-01 00:00:00 +14427,320,205,0.0,25,0,1979-07-01 00:00:00 +14428,320,222,7.0,11,0,1979-07-01 00:00:00 +14429,320,199,1.0,15,0,1979-07-01 00:00:00 +14430,320,198,20.0,5,0,1979-07-01 00:00:00 +14431,320,223,1.0,16,0,1979-07-01 00:00:00 +14432,320,206,12.0,6,0,1979-07-01 00:00:00 +14433,320,220,20.0,4,1,1979-07-01 00:00:00 +14434,320,186,8.0,9,0,1979-07-01 00:00:00 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00:00:00 +14458,321,151,0.0,29,0,1979-07-14 00:00:00 +14459,321,233,0.0,31,0,1979-07-14 00:00:00 +14460,321,232,0.0,22,0,1979-07-14 00:00:00 +14461,321,231,0.0,30,0,1979-07-14 00:00:00 +14462,321,118,2.0,14,0,1979-07-14 00:00:00 +14463,321,174,0.0,21,0,1979-07-14 00:00:00 +14464,321,136,0.0,20,0,1979-07-14 00:00:00 +14465,321,171,24.0,3,2,1979-07-14 00:00:00 +14466,321,198,20.0,5,0,1979-07-14 00:00:00 +14467,321,186,11.0,9,0,1979-07-14 00:00:00 +14468,321,206,12.0,8,0,1979-07-14 00:00:00 +14469,321,223,1.0,16,0,1979-07-14 00:00:00 +14470,321,172,0.0,19,0,1979-07-14 00:00:00 +14471,321,199,1.0,15,0,1979-07-14 00:00:00 +14472,321,177,7.0,13,0,1979-07-14 00:00:00 +14473,321,222,16.0,6,1,1979-07-14 00:00:00 +14474,321,220,20.0,4,1,1979-07-14 00:00:00 +14475,321,202,26.0,2,2,1979-07-14 00:00:00 +14476,321,205,0.0,27,0,1979-07-14 00:00:00 +14477,321,201,8.0,12,0,1979-07-14 00:00:00 +14478,321,221,32.0,1,2,1979-07-14 00:00:00 +14479,321,181,1.0,17,0,1979-07-14 00:00:00 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+14590,325,223,1.0,19,0,1979-09-09 00:00:00 +14591,325,206,14.0,9,0,1979-09-09 00:00:00 +14592,325,220,20.0,6,1,1979-09-09 00:00:00 +14593,325,186,13.0,10,0,1979-09-09 00:00:00 +14594,325,198,20.0,7,0,1979-09-09 00:00:00 +14595,325,196,14.0,8,0,1979-09-09 00:00:00 +14596,325,199,3.0,17,0,1979-09-09 00:00:00 +14597,325,218,9.0,12,1,1979-09-09 00:00:00 +14598,325,172,0.0,20,0,1979-09-09 00:00:00 +14599,325,162,11.0,11,0,1979-09-09 00:00:00 +14600,325,181,4.0,14,0,1979-09-09 00:00:00 +14601,325,175,0.0,34,0,1979-09-09 00:00:00 +14602,325,229,0.0,29,0,1979-09-09 00:00:00 +14603,325,208,0.0,23,0,1979-09-09 00:00:00 +14604,325,235,0.0,30,0,1979-09-09 00:00:00 +14605,325,176,0.0,27,0,1979-09-09 00:00:00 +14606,325,151,0.0,31,0,1979-09-09 00:00:00 +14607,325,234,3.0,16,0,1979-09-09 00:00:00 +14608,325,232,0.0,25,0,1979-09-09 00:00:00 +14609,325,118,2.0,18,0,1979-09-09 00:00:00 +14610,325,231,0.0,32,0,1979-09-09 00:00:00 +14611,325,136,3.0,15,0,1979-09-09 00:00:00 +14612,325,174,0.0,22,0,1979-09-09 00:00:00 +14613,325,201,8.0,13,0,1979-09-09 00:00:00 +14614,325,221,51.0,1,3,1979-09-09 00:00:00 +14615,325,233,0.0,33,0,1979-09-09 00:00:00 +14616,326,135,0.0,28,0,1979-09-30 00:00:00 +14617,326,196,14.0,8,0,1979-09-30 00:00:00 +14618,326,230,0.0,27,0,1979-09-30 00:00:00 +14619,326,186,14.0,10,0,1979-09-30 00:00:00 +14620,326,198,20.0,7,0,1979-09-30 00:00:00 +14621,326,171,36.0,4,2,1979-09-30 00:00:00 +14622,326,211,0.0,21,0,1979-09-30 00:00:00 +14623,326,206,14.0,9,0,1979-09-30 00:00:00 +14624,326,205,0.0,25,0,1979-09-30 00:00:00 +14625,326,222,29.0,5,1,1979-09-30 00:00:00 +14626,326,177,40.0,3,4,1979-09-30 00:00:00 +14627,326,199,3.0,17,0,1979-09-30 00:00:00 +14628,326,172,0.0,20,0,1979-09-30 00:00:00 +14629,326,223,1.0,19,0,1979-09-30 00:00:00 +14630,326,218,9.0,13,1,1979-09-30 00:00:00 +14631,326,202,44.0,2,2,1979-09-30 00:00:00 +14632,326,181,4.0,14,0,1979-09-30 00:00:00 +14633,326,232,0.0,26,0,1979-09-30 00:00:00 +14634,326,221,51.0,1,3,1979-09-30 00:00:00 +14635,326,236,0.0,36,0,1979-09-30 00:00:00 +14636,326,216,0.0,24,0,1979-09-30 00:00:00 +14637,326,175,0.0,35,0,1979-09-30 00:00:00 +14638,326,229,0.0,30,0,1979-09-30 00:00:00 +14639,326,208,0.0,23,0,1979-09-30 00:00:00 +14640,326,235,0.0,31,0,1979-09-30 00:00:00 +14641,326,234,3.0,16,0,1979-09-30 00:00:00 +14642,326,176,0.0,29,0,1979-09-30 00:00:00 +14643,326,151,0.0,32,0,1979-09-30 00:00:00 +14644,326,233,0.0,34,0,1979-09-30 00:00:00 +14645,326,118,2.0,18,0,1979-09-30 00:00:00 +14646,326,231,0.0,33,0,1979-09-30 00:00:00 +14647,326,136,3.0,15,0,1979-09-30 00:00:00 +14648,326,174,0.0,22,0,1979-09-30 00:00:00 +14649,326,201,10.0,12,0,1979-09-30 00:00:00 +14650,326,162,11.0,11,0,1979-09-30 00:00:00 +14651,326,220,20.0,6,1,1979-09-30 00:00:00 +14652,327,171,36.0,4,2,1979-10-07 00:00:00 +14653,327,236,0.0,36,0,1979-10-07 00:00:00 +14654,327,218,9.0,13,1,1979-10-07 00:00:00 +14655,327,196,14.0,11,0,1979-10-07 00:00:00 +14656,327,230,0.0,27,0,1979-10-07 00:00:00 +14657,327,211,0.0,22,0,1979-10-07 00:00:00 +14658,327,202,47.0,2,3,1979-10-07 00:00:00 +14659,327,205,0.0,26,0,1979-10-07 00:00:00 +14660,327,222,29.0,5,1,1979-10-07 00:00:00 +14661,327,177,40.0,3,4,1979-10-07 00:00:00 +14662,327,199,3.0,18,0,1979-10-07 00:00:00 +14663,327,172,3.0,15,0,1979-10-07 00:00:00 +14664,327,223,1.0,21,0,1979-10-07 00:00:00 +14665,327,206,14.0,12,0,1979-10-07 00:00:00 +14666,327,220,20.0,6,1,1979-10-07 00:00:00 +14667,327,186,15.0,9,0,1979-10-07 00:00:00 +14668,327,198,20.0,7,0,1979-10-07 00:00:00 +14669,327,181,4.0,14,0,1979-10-07 00:00:00 +14670,327,162,17.0,8,0,1979-10-07 00:00:00 +14671,327,135,0.0,28,0,1979-10-07 00:00:00 +14672,327,201,14.0,10,0,1979-10-07 00:00:00 +14673,327,216,0.0,24,0,1979-10-07 00:00:00 +14674,327,175,0.0,33,0,1979-10-07 00:00:00 +14675,327,221,51.0,1,3,1979-10-07 00:00:00 +14676,327,208,0.0,25,0,1979-10-07 00:00:00 +14677,327,235,0.0,31,0,1979-10-07 00:00:00 +14678,327,234,3.0,17,0,1979-10-07 00:00:00 +14679,327,176,0.0,29,0,1979-10-07 00:00:00 +14680,327,229,0.0,30,0,1979-10-07 00:00:00 +14681,327,233,0.0,35,0,1979-10-07 00:00:00 +14682,327,232,2.0,19,0,1979-10-07 00:00:00 +14683,327,118,2.0,20,0,1979-10-07 00:00:00 +14684,327,231,0.0,34,0,1979-10-07 00:00:00 +14685,327,136,3.0,16,0,1979-10-07 00:00:00 +14686,327,174,0.0,23,0,1979-10-07 00:00:00 +14687,327,151,0.0,32,0,1979-10-07 00:00:00 +14688,328,202,0.0,12,0,1980-01-13 00:00:00 +14689,328,223,0.0,11,0,1980-01-13 00:00:00 +14690,328,222,0.0,10,0,1980-01-13 00:00:00 +14691,328,221,0.0,9,0,1980-01-13 00:00:00 +14692,328,220,0.0,8,0,1980-01-13 00:00:00 +14693,328,176,4.0,3,0,1980-01-13 00:00:00 +14694,328,116,1.0,6,0,1980-01-13 00:00:00 +14695,328,151,2.0,5,0,1980-01-13 00:00:00 +14696,328,136,6.0,2,0,1980-01-13 00:00:00 +14697,328,171,0.0,13,0,1980-01-13 00:00:00 +14698,328,177,9.0,1,1,1980-01-13 00:00:00 +14699,328,216,0.0,7,0,1980-01-13 00:00:00 +14700,328,118,0.0,14,0,1980-01-13 00:00:00 +14701,328,205,3.0,4,0,1980-01-13 00:00:00 +14702,328,206,0.0,16,0,1980-01-13 00:00:00 +14703,328,175,0.0,15,0,1980-01-13 00:00:00 +14704,328,135,0.0,27,0,1980-01-13 00:00:00 +14705,328,139,0.0,26,0,1980-01-13 00:00:00 +14706,328,224,0.0,25,0,1980-01-13 00:00:00 +14707,328,196,0.0,24,0,1980-01-13 00:00:00 +14708,328,201,0.0,23,0,1980-01-13 00:00:00 +14709,328,157,0.0,28,0,1980-01-13 00:00:00 +14710,328,218,0.0,21,0,1980-01-13 00:00:00 +14711,328,186,0.0,20,0,1980-01-13 00:00:00 +14712,328,172,0.0,19,0,1980-01-13 00:00:00 +14713,328,198,0.0,18,0,1980-01-13 00:00:00 +14714,328,199,0.0,17,0,1980-01-13 00:00:00 +14715,328,162,0.0,22,0,1980-01-13 00:00:00 +14716,329,202,0.0,17,0,1980-01-27 00:00:00 +14717,329,223,0.0,16,0,1980-01-27 00:00:00 +14718,329,222,0.0,20,0,1980-01-27 00:00:00 +14719,329,221,0.0,19,0,1980-01-27 00:00:00 +14720,329,216,0.0,11,0,1980-01-27 00:00:00 +14721,329,151,2.0,9,0,1980-01-27 00:00:00 +14722,329,205,3.0,6,0,1980-01-27 00:00:00 +14723,329,176,4.0,5,0,1980-01-27 00:00:00 +14724,329,136,6.0,4,0,1980-01-27 00:00:00 +14725,329,171,0.0,21,0,1980-01-27 00:00:00 +14726,329,177,13.0,1,1,1980-01-27 00:00:00 +14727,329,116,3.0,8,0,1980-01-27 00:00:00 +14728,329,118,1.0,10,0,1980-01-27 00:00:00 +14729,329,220,0.0,18,0,1980-01-27 00:00:00 +14730,329,206,0.0,22,0,1980-01-27 00:00:00 +14731,329,157,0.0,28,0,1980-01-27 00:00:00 +14732,329,135,0.0,26,0,1980-01-27 00:00:00 +14733,329,139,0.0,27,0,1980-01-27 00:00:00 +14734,329,175,0.0,12,0,1980-01-27 00:00:00 +14735,329,196,0.0,15,0,1980-01-27 00:00:00 +14736,329,201,3.0,7,0,1980-01-27 00:00:00 +14737,329,224,0.0,25,0,1980-01-27 00:00:00 +14738,329,218,0.0,23,0,1980-01-27 00:00:00 +14739,329,186,0.0,14,0,1980-01-27 00:00:00 +14740,329,172,6.0,3,0,1980-01-27 00:00:00 +14741,329,198,0.0,24,0,1980-01-27 00:00:00 +14742,329,199,0.0,13,0,1980-01-27 00:00:00 +14743,329,162,9.0,2,1,1980-01-27 00:00:00 +14744,330,118,1.0,13,0,1980-03-01 00:00:00 +14745,330,171,6.0,5,0,1980-03-01 00:00:00 +14746,330,202,0.0,22,0,1980-03-01 00:00:00 +14747,330,223,0.0,17,0,1980-03-01 00:00:00 +14748,330,222,0.0,18,0,1980-03-01 00:00:00 +14749,330,176,4.0,7,0,1980-03-01 00:00:00 +14750,330,216,0.0,14,0,1980-03-01 00:00:00 +14751,330,116,3.0,9,0,1980-03-01 00:00:00 +14752,330,151,2.0,10,0,1980-03-01 00:00:00 +14753,330,205,3.0,8,0,1980-03-01 00:00:00 +14754,330,175,0.0,16,0,1980-03-01 00:00:00 +14755,330,221,0.0,24,0,1980-03-01 00:00:00 +14756,330,206,0.0,20,0,1980-03-01 00:00:00 +14757,330,201,7.0,4,0,1980-03-01 00:00:00 +14758,330,198,2.0,11,0,1980-03-01 00:00:00 +14759,330,172,6.0,6,0,1980-03-01 00:00:00 +14760,330,186,0.0,19,0,1980-03-01 00:00:00 +14761,330,218,0.0,25,0,1980-03-01 00:00:00 +14762,330,162,18.0,1,2,1980-03-01 00:00:00 +14763,330,196,0.0,15,0,1980-03-01 00:00:00 +14764,330,224,0.0,27,0,1980-03-01 00:00:00 +14765,330,139,0.0,29,0,1980-03-01 00:00:00 +14766,330,135,0.0,28,0,1980-03-01 00:00:00 +14767,330,157,0.0,26,0,1980-03-01 00:00:00 +14768,330,208,0.0,21,0,1980-03-01 00:00:00 +14769,330,136,9.0,3,0,1980-03-01 00:00:00 +14770,330,199,1.0,12,0,1980-03-01 00:00:00 +14771,330,177,13.0,2,1,1980-03-01 00:00:00 +14772,330,220,0.0,23,0,1980-03-01 00:00:00 +14773,331,223,4.0,8,0,1980-03-30 00:00:00 +14774,331,177,13.0,3,1,1980-03-30 00:00:00 +14775,331,136,18.0,2,1,1980-03-30 00:00:00 +14776,331,176,4.0,9,0,1980-03-30 00:00:00 +14777,331,205,3.0,10,0,1980-03-30 00:00:00 +14778,331,151,2.0,13,0,1980-03-30 00:00:00 +14779,331,116,3.0,12,0,1980-03-30 00:00:00 +14780,331,216,0.0,17,0,1980-03-30 00:00:00 +14781,331,220,0.0,25,0,1980-03-30 00:00:00 +14782,331,221,2.0,14,0,1980-03-30 00:00:00 +14783,331,222,0.0,20,0,1980-03-30 00:00:00 +14784,331,202,0.0,24,0,1980-03-30 00:00:00 +14785,331,171,6.0,6,0,1980-03-30 00:00:00 +14786,331,118,7.0,5,0,1980-03-30 00:00:00 +14787,331,175,0.0,19,0,1980-03-30 00:00:00 +14788,331,199,1.0,16,0,1980-03-30 00:00:00 +14789,331,206,0.0,22,0,1980-03-30 00:00:00 +14790,331,139,0.0,29,0,1980-03-30 00:00:00 +14791,331,172,6.0,7,0,1980-03-30 00:00:00 +14792,331,186,3.0,11,0,1980-03-30 00:00:00 +14793,331,218,0.0,21,0,1980-03-30 00:00:00 +14794,331,162,18.0,1,2,1980-03-30 00:00:00 +14795,331,201,8.0,4,0,1980-03-30 00:00:00 +14796,331,196,0.0,18,0,1980-03-30 00:00:00 +14797,331,224,0.0,28,0,1980-03-30 00:00:00 +14798,331,198,2.0,15,0,1980-03-30 00:00:00 +14799,331,135,0.0,27,0,1980-03-30 00:00:00 +14800,331,157,0.0,26,0,1980-03-30 00:00:00 +14801,331,208,0.0,23,0,1980-03-30 00:00:00 +14802,331,225,0.0,30,0,1980-03-30 00:00:00 +14803,332,220,0.0,26,0,1980-05-04 00:00:00 +14804,332,223,4.0,10,0,1980-05-04 00:00:00 +14805,332,216,0.0,19,0,1980-05-04 00:00:00 +14806,332,221,2.0,15,0,1980-05-04 00:00:00 +14807,332,222,0.0,21,0,1980-05-04 00:00:00 +14808,332,116,3.0,13,0,1980-05-04 00:00:00 +14809,332,139,0.0,30,0,1980-05-04 00:00:00 +14810,332,205,3.0,11,0,1980-05-04 00:00:00 +14811,332,176,4.0,9,0,1980-05-04 00:00:00 +14812,332,136,18.0,3,1,1980-05-04 00:00:00 +14813,332,202,1.0,18,0,1980-05-04 00:00:00 +14814,332,177,19.0,2,1,1980-05-04 00:00:00 +14815,332,135,0.0,24,0,1980-05-04 00:00:00 +14816,332,151,2.0,16,0,1980-05-04 00:00:00 +14817,332,171,6.0,7,0,1980-05-04 00:00:00 +14818,332,224,0.0,29,0,1980-05-04 00:00:00 +14819,332,175,0.0,20,0,1980-05-04 00:00:00 +14820,332,196,2.0,14,0,1980-05-04 00:00:00 +14821,332,201,17.0,4,1,1980-05-04 00:00:00 +14822,332,226,0.0,28,0,1980-05-04 00:00:00 +14823,332,208,0.0,25,0,1980-05-04 00:00:00 +14824,332,157,0.0,27,0,1980-05-04 00:00:00 +14825,332,162,21.0,1,2,1980-05-04 00:00:00 +14826,332,225,0.0,31,0,1980-05-04 00:00:00 +14827,332,186,3.0,12,0,1980-05-04 00:00:00 +14828,332,172,6.0,6,0,1980-05-04 00:00:00 +14829,332,198,6.0,8,0,1980-05-04 00:00:00 +14830,332,199,1.0,17,0,1980-05-04 00:00:00 +14831,332,206,0.0,23,0,1980-05-04 00:00:00 +14832,332,218,0.0,22,0,1980-05-04 00:00:00 +14833,332,118,7.0,5,0,1980-05-04 00:00:00 +14834,333,220,0.0,26,0,1980-05-18 00:00:00 +14835,333,171,12.0,6,0,1980-05-18 00:00:00 +14836,333,202,3.0,14,0,1980-05-18 00:00:00 +14837,333,223,5.0,9,0,1980-05-18 00:00:00 +14838,333,222,0.0,22,0,1980-05-18 00:00:00 +14839,333,221,2.0,17,0,1980-05-18 00:00:00 +14840,333,177,19.0,3,1,1980-05-18 00:00:00 +14841,333,151,2.0,18,0,1980-05-18 00:00:00 +14842,333,205,3.0,12,0,1980-05-18 00:00:00 +14843,333,176,4.0,10,0,1980-05-18 00:00:00 +14844,333,136,22.0,1,1,1980-05-18 00:00:00 +14845,333,118,7.0,7,0,1980-05-18 00:00:00 +14846,333,116,3.0,15,0,1980-05-18 00:00:00 +14847,333,175,0.0,21,0,1980-05-18 00:00:00 +14848,333,216,0.0,19,0,1980-05-18 00:00:00 +14849,333,199,4.0,11,0,1980-05-18 00:00:00 +14850,333,226,0.0,28,0,1980-05-18 00:00:00 +14851,333,206,0.0,20,0,1980-05-18 00:00:00 +14852,333,208,0.0,25,0,1980-05-18 00:00:00 +14853,333,157,0.0,27,0,1980-05-18 00:00:00 +14854,333,135,0.0,24,0,1980-05-18 00:00:00 +14855,333,139,0.0,30,0,1980-05-18 00:00:00 +14856,333,224,0.0,29,0,1980-05-18 00:00:00 +14857,333,225,0.0,31,0,1980-05-18 00:00:00 +14858,333,201,17.0,4,1,1980-05-18 00:00:00 +14859,333,162,21.0,2,2,1980-05-18 00:00:00 +14860,333,218,0.0,23,0,1980-05-18 00:00:00 +14861,333,186,3.0,13,0,1980-05-18 00:00:00 +14862,333,198,15.0,5,1,1980-05-18 00:00:00 +14863,333,196,2.0,16,0,1980-05-18 00:00:00 +14864,333,172,6.0,8,0,1980-05-18 00:00:00 +14865,334,118,7.0,7,0,1980-06-29 00:00:00 +14866,334,171,16.0,6,0,1980-06-29 00:00:00 +14867,334,202,3.0,14,0,1980-06-29 00:00:00 +14868,334,223,5.0,9,0,1980-06-29 00:00:00 +14869,334,222,0.0,22,0,1980-06-29 00:00:00 +14870,334,216,0.0,19,0,1980-06-29 00:00:00 +14871,334,220,0.0,26,0,1980-06-29 00:00:00 +14872,334,116,3.0,15,0,1980-06-29 00:00:00 +14873,334,151,2.0,18,0,1980-06-29 00:00:00 +14874,334,205,3.0,13,0,1980-06-29 00:00:00 +14875,334,136,25.0,2,1,1980-06-29 00:00:00 +14876,334,221,2.0,17,0,1980-06-29 00:00:00 +14877,334,175,0.0,21,0,1980-06-29 00:00:00 +14878,334,198,16.0,5,1,1980-06-29 00:00:00 +14879,334,199,4.0,11,0,1980-06-29 00:00:00 +14880,334,172,6.0,8,0,1980-06-29 00:00:00 +14881,334,186,3.0,12,0,1980-06-29 00:00:00 +14882,334,218,0.0,23,0,1980-06-29 00:00:00 +14883,334,162,23.0,3,2,1980-06-29 00:00:00 +14884,334,196,2.0,16,0,1980-06-29 00:00:00 +14885,334,224,0.0,29,0,1980-06-29 00:00:00 +14886,334,139,0.0,30,0,1980-06-29 00:00:00 +14887,334,135,0.0,24,0,1980-06-29 00:00:00 +14888,334,157,0.0,27,0,1980-06-29 00:00:00 +14889,334,208,0.0,25,0,1980-06-29 00:00:00 +14890,334,225,0.0,31,0,1980-06-29 00:00:00 +14891,334,226,0.0,28,0,1980-06-29 00:00:00 +14892,334,177,28.0,1,2,1980-06-29 00:00:00 +14893,334,206,0.0,20,0,1980-06-29 00:00:00 +14894,334,201,23.0,4,1,1980-06-29 00:00:00 +14895,334,176,4.0,10,0,1980-06-29 00:00:00 +14896,335,196,4.0,13,0,1980-07-13 00:00:00 +14897,335,176,4.0,11,0,1980-07-13 00:00:00 +14898,335,205,6.0,9,0,1980-07-13 00:00:00 +14899,335,151,2.0,18,0,1980-07-13 00:00:00 +14900,335,116,4.0,14,0,1980-07-13 00:00:00 +14901,335,216,0.0,19,0,1980-07-13 00:00:00 +14902,335,220,0.0,28,0,1980-07-13 00:00:00 +14903,335,221,2.0,17,0,1980-07-13 00:00:00 +14904,335,222,0.0,23,0,1980-07-13 00:00:00 +14905,335,223,5.0,10,0,1980-07-13 00:00:00 +14906,335,202,3.0,16,0,1980-07-13 00:00:00 +14907,335,171,16.0,6,0,1980-07-13 00:00:00 +14908,335,118,7.0,7,0,1980-07-13 00:00:00 +14909,335,175,0.0,21,0,1980-07-13 00:00:00 +14910,335,206,0.0,20,0,1980-07-13 00:00:00 +14911,335,199,4.0,12,0,1980-07-13 00:00:00 +14912,335,198,20.0,5,1,1980-07-13 00:00:00 +14913,335,172,6.0,8,0,1980-07-13 00:00:00 +14914,335,186,3.0,15,0,1980-07-13 00:00:00 +14915,335,218,0.0,24,0,1980-07-13 00:00:00 +14916,335,136,31.0,2,1,1980-07-13 00:00:00 +14917,335,177,37.0,1,3,1980-07-13 00:00:00 +14918,335,201,23.0,4,1,1980-07-13 00:00:00 +14919,335,224,0.0,31,0,1980-07-13 00:00:00 +14920,335,139,0.0,32,0,1980-07-13 00:00:00 +14921,335,135,0.0,26,0,1980-07-13 00:00:00 +14922,335,157,0.0,29,0,1980-07-13 00:00:00 +14923,335,208,0.0,27,0,1980-07-13 00:00:00 +14924,335,225,0.0,33,0,1980-07-13 00:00:00 +14925,335,226,0.0,30,0,1980-07-13 00:00:00 +14926,335,211,0.0,22,0,1980-07-13 00:00:00 +14927,335,210,0.0,25,0,1980-07-13 00:00:00 +14928,335,227,0.0,34,0,1980-07-13 00:00:00 +14929,335,162,23.0,3,2,1980-07-13 00:00:00 +14930,336,202,4.0,15,0,1980-08-10 00:00:00 +14931,336,177,41.0,1,3,1980-08-10 00:00:00 +14932,336,136,34.0,2,1,1980-08-10 00:00:00 +14933,336,176,4.0,11,0,1980-08-10 00:00:00 +14934,336,205,6.0,9,0,1980-08-10 00:00:00 +14935,336,221,2.0,18,0,1980-08-10 00:00:00 +14936,336,116,4.0,16,0,1980-08-10 00:00:00 +14937,336,216,0.0,20,0,1980-08-10 00:00:00 +14938,336,220,0.0,28,0,1980-08-10 00:00:00 +14939,336,222,0.0,23,0,1980-08-10 00:00:00 +14940,336,151,4.0,14,0,1980-08-10 00:00:00 +14941,336,171,25.0,4,1,1980-08-10 00:00:00 +14942,336,201,23.0,6,1,1980-08-10 00:00:00 +14943,336,227,0.0,35,0,1980-08-10 00:00:00 +14944,336,228,0.0,33,0,1980-08-10 00:00:00 +14945,336,118,7.0,7,0,1980-08-10 00:00:00 +14946,336,175,0.0,21,0,1980-08-10 00:00:00 +14947,336,199,4.0,12,0,1980-08-10 00:00:00 +14948,336,198,26.0,3,1,1980-08-10 00:00:00 +14949,336,172,6.0,8,0,1980-08-10 00:00:00 +14950,336,186,3.0,17,0,1980-08-10 00:00:00 +14951,336,218,0.0,24,0,1980-08-10 00:00:00 +14952,336,162,23.0,5,2,1980-08-10 00:00:00 +14953,336,223,5.0,10,0,1980-08-10 00:00:00 +14954,336,206,0.0,19,0,1980-08-10 00:00:00 +14955,336,224,0.0,31,0,1980-08-10 00:00:00 +14956,336,211,0.0,22,0,1980-08-10 00:00:00 +14957,336,196,4.0,13,0,1980-08-10 00:00:00 +14958,336,226,0.0,30,0,1980-08-10 00:00:00 +14959,336,225,0.0,34,0,1980-08-10 00:00:00 +14960,336,210,0.0,25,0,1980-08-10 00:00:00 +14961,336,157,0.0,29,0,1980-08-10 00:00:00 +14962,336,135,0.0,26,0,1980-08-10 00:00:00 +14963,336,139,0.0,32,0,1980-08-10 00:00:00 +14964,336,208,0.0,27,0,1980-08-10 00:00:00 +14965,337,175,0.0,23,0,1980-08-17 00:00:00 +14966,337,221,2.0,19,0,1980-08-17 00:00:00 +14967,337,171,28.0,4,1,1980-08-17 00:00:00 +14968,337,202,4.0,17,0,1980-08-17 00:00:00 +14969,337,223,5.0,11,0,1980-08-17 00:00:00 +14970,337,222,0.0,24,0,1980-08-17 00:00:00 +14971,337,118,7.0,8,0,1980-08-17 00:00:00 +14972,337,151,4.0,15,0,1980-08-17 00:00:00 +14973,337,116,4.0,16,0,1980-08-17 00:00:00 +14974,337,205,6.0,10,0,1980-08-17 00:00:00 +14975,337,176,4.0,12,0,1980-08-17 00:00:00 +14976,337,136,36.0,2,1,1980-08-17 00:00:00 +14977,337,177,47.0,1,3,1980-08-17 00:00:00 +14978,337,206,0.0,20,0,1980-08-17 00:00:00 +14979,337,216,0.0,21,0,1980-08-17 00:00:00 +14980,337,199,4.0,13,0,1980-08-17 00:00:00 +14981,337,220,0.0,28,0,1980-08-17 00:00:00 +14982,337,172,7.0,9,0,1980-08-17 00:00:00 +14983,337,198,30.0,3,1,1980-08-17 00:00:00 +14984,337,94,0.0,30,0,1980-08-17 00:00:00 +14985,337,228,0.0,34,0,1980-08-17 00:00:00 +14986,337,227,0.0,36,0,1980-08-17 00:00:00 +14987,337,210,0.0,25,0,1980-08-17 00:00:00 +14988,337,211,0.0,22,0,1980-08-17 00:00:00 +14989,337,225,0.0,35,0,1980-08-17 00:00:00 +14990,337,208,0.0,27,0,1980-08-17 00:00:00 +14991,337,226,0.0,31,0,1980-08-17 00:00:00 +14992,337,135,0.0,26,0,1980-08-17 00:00:00 +14993,337,139,0.0,33,0,1980-08-17 00:00:00 +14994,337,224,0.0,32,0,1980-08-17 00:00:00 +14995,337,196,4.0,14,0,1980-08-17 00:00:00 +14996,337,201,23.0,6,1,1980-08-17 00:00:00 +14997,337,162,23.0,5,2,1980-08-17 00:00:00 +14998,337,218,9.0,7,1,1980-08-17 00:00:00 +14999,337,157,0.0,29,0,1980-08-17 00:00:00 +15000,337,186,3.0,18,0,1980-08-17 00:00:00 +15001,338,206,0.0,20,0,1980-08-31 00:00:00 +15002,338,175,0.0,22,0,1980-08-31 00:00:00 +15003,338,118,7.0,8,0,1980-08-31 00:00:00 +15004,338,171,32.0,4,1,1980-08-31 00:00:00 +15005,338,202,4.0,17,0,1980-08-31 00:00:00 +15006,338,223,5.0,12,0,1980-08-31 00:00:00 +15007,338,222,0.0,24,0,1980-08-31 00:00:00 +15008,338,216,0.0,21,0,1980-08-31 00:00:00 +15009,338,220,0.0,28,0,1980-08-31 00:00:00 +15010,338,199,4.0,15,0,1980-08-31 00:00:00 +15011,338,116,5.0,13,0,1980-08-31 00:00:00 +15012,338,151,4.0,16,0,1980-08-31 00:00:00 +15013,338,205,6.0,10,0,1980-08-31 00:00:00 +15014,338,176,4.0,14,0,1980-08-31 00:00:00 +15015,338,136,45.0,2,2,1980-08-31 00:00:00 +15016,338,177,47.0,1,3,1980-08-31 00:00:00 +15017,338,221,2.0,19,0,1980-08-31 00:00:00 +15018,338,198,33.0,3,1,1980-08-31 00:00:00 +15019,338,218,9.0,7,1,1980-08-31 00:00:00 +15020,338,186,3.0,18,0,1980-08-31 00:00:00 +15021,338,190,0.0,37,0,1980-08-31 00:00:00 +15022,338,229,0.0,31,0,1980-08-31 00:00:00 +15023,338,94,0.0,30,0,1980-08-31 00:00:00 +15024,338,228,0.0,35,0,1980-08-31 00:00:00 +15025,338,227,0.0,38,0,1980-08-31 00:00:00 +15026,338,210,0.0,25,0,1980-08-31 00:00:00 +15027,338,172,7.0,9,0,1980-08-31 00:00:00 +15028,338,226,0.0,32,0,1980-08-31 00:00:00 +15029,338,211,0.0,23,0,1980-08-31 00:00:00 +15030,338,208,0.0,27,0,1980-08-31 00:00:00 +15031,338,157,0.0,29,0,1980-08-31 00:00:00 +15032,338,135,0.0,26,0,1980-08-31 00:00:00 +15033,338,224,0.0,33,0,1980-08-31 00:00:00 +15034,338,196,6.0,11,0,1980-08-31 00:00:00 +15035,338,201,23.0,6,1,1980-08-31 00:00:00 +15036,338,162,29.0,5,2,1980-08-31 00:00:00 +15037,338,225,0.0,36,0,1980-08-31 00:00:00 +15038,338,139,0.0,34,0,1980-08-31 00:00:00 +15039,339,177,53.0,2,3,1980-09-14 00:00:00 +15040,339,136,54.0,1,3,1980-09-14 00:00:00 +15041,339,176,6.0,10,0,1980-09-14 00:00:00 +15042,339,180,0.0,36,0,1980-09-14 00:00:00 +15043,339,172,10.0,7,0,1980-09-14 00:00:00 +15044,339,198,37.0,3,1,1980-09-14 00:00:00 +15045,339,199,4.0,15,0,1980-09-14 00:00:00 +15046,339,206,0.0,20,0,1980-09-14 00:00:00 +15047,339,175,0.0,22,0,1980-09-14 00:00:00 +15048,339,118,7.0,9,0,1980-09-14 00:00:00 +15049,339,171,32.0,4,1,1980-09-14 00:00:00 +15050,339,223,5.0,13,0,1980-09-14 00:00:00 +15051,339,222,0.0,24,0,1980-09-14 00:00:00 +15052,339,221,2.0,19,0,1980-09-14 00:00:00 +15053,339,220,0.0,29,0,1980-09-14 00:00:00 +15054,339,216,0.0,21,0,1980-09-14 00:00:00 +15055,339,116,5.0,14,0,1980-09-14 00:00:00 +15056,339,151,4.0,16,0,1980-09-14 00:00:00 +15057,339,205,6.0,11,0,1980-09-14 00:00:00 +15058,339,186,3.0,18,0,1980-09-14 00:00:00 +15059,339,218,9.0,8,1,1980-09-14 00:00:00 +15060,339,202,4.0,17,0,1980-09-14 00:00:00 +15061,339,201,24.0,6,1,1980-09-14 00:00:00 +15062,339,162,29.0,5,2,1980-09-14 00:00:00 +15063,339,190,0.0,38,0,1980-09-14 00:00:00 +15064,339,229,0.0,31,0,1980-09-14 00:00:00 +15065,339,94,0.0,30,0,1980-09-14 00:00:00 +15066,339,228,0.0,35,0,1980-09-14 00:00:00 +15067,339,210,0.0,25,0,1980-09-14 00:00:00 +15068,339,211,0.0,23,0,1980-09-14 00:00:00 +15069,339,226,0.0,32,0,1980-09-14 00:00:00 +15070,339,227,0.0,39,0,1980-09-14 00:00:00 +15071,339,225,0.0,37,0,1980-09-14 00:00:00 +15072,339,208,0.0,28,0,1980-09-14 00:00:00 +15073,339,157,0.0,27,0,1980-09-14 00:00:00 +15074,339,135,0.0,26,0,1980-09-14 00:00:00 +15075,339,139,0.0,34,0,1980-09-14 00:00:00 +15076,339,224,0.0,33,0,1980-09-14 00:00:00 +15077,339,196,6.0,12,0,1980-09-14 00:00:00 +15078,340,223,5.0,15,0,1980-09-28 00:00:00 +15079,340,199,4.0,17,0,1980-09-28 00:00:00 +15080,340,206,0.0,21,0,1980-09-28 00:00:00 +15081,340,175,0.0,23,0,1980-09-28 00:00:00 +15082,340,118,7.0,9,0,1980-09-28 00:00:00 +15083,340,171,32.0,4,1,1980-09-28 00:00:00 +15084,340,202,6.0,14,0,1980-09-28 00:00:00 +15085,340,198,40.0,3,1,1980-09-28 00:00:00 +15086,340,222,0.0,24,0,1980-09-28 00:00:00 +15087,340,136,54.0,2,3,1980-09-28 00:00:00 +15088,340,220,0.0,29,0,1980-09-28 00:00:00 +15089,340,216,0.0,22,0,1980-09-28 00:00:00 +15090,340,116,5.0,16,0,1980-09-28 00:00:00 +15091,340,151,4.0,18,0,1980-09-28 00:00:00 +15092,340,205,6.0,12,0,1980-09-28 00:00:00 +15093,340,176,6.0,10,0,1980-09-28 00:00:00 +15094,340,177,62.0,1,4,1980-09-28 00:00:00 +15095,340,172,10.0,7,0,1980-09-28 00:00:00 +15096,340,221,2.0,19,0,1980-09-28 00:00:00 +15097,340,186,6.0,11,0,1980-09-28 00:00:00 +15098,340,208,0.0,28,0,1980-09-28 00:00:00 +15099,340,162,29.0,5,2,1980-09-28 00:00:00 +15100,340,213,0.0,41,0,1980-09-28 00:00:00 +15101,340,218,9.0,8,1,1980-09-28 00:00:00 +15102,340,180,0.0,38,0,1980-09-28 00:00:00 +15103,340,190,0.0,34,0,1980-09-28 00:00:00 +15104,340,229,0.0,31,0,1980-09-28 00:00:00 +15105,340,94,0.0,30,0,1980-09-28 00:00:00 +15106,340,228,0.0,37,0,1980-09-28 00:00:00 +15107,340,227,0.0,40,0,1980-09-28 00:00:00 +15108,340,210,0.0,25,0,1980-09-28 00:00:00 +15109,340,109,0.0,32,0,1980-09-28 00:00:00 +15110,340,226,0.0,33,0,1980-09-28 00:00:00 +15111,340,211,1.0,20,0,1980-09-28 00:00:00 +15112,340,201,28.0,6,1,1980-09-28 00:00:00 +15113,340,224,0.0,35,0,1980-09-28 00:00:00 +15114,340,139,0.0,36,0,1980-09-28 00:00:00 +15115,340,196,6.0,13,0,1980-09-28 00:00:00 +15116,340,157,0.0,27,0,1980-09-28 00:00:00 +15117,340,225,0.0,39,0,1980-09-28 00:00:00 +15118,340,135,0.0,26,0,1980-09-28 00:00:00 +15119,341,198,42.0,3,1,1980-10-05 00:00:00 +15120,341,202,6.0,14,0,1980-10-05 00:00:00 +15121,341,172,13.0,7,0,1980-10-05 00:00:00 +15122,341,206,1.0,20,0,1980-10-05 00:00:00 +15123,341,175,0.0,22,0,1980-10-05 00:00:00 +15124,341,118,7.0,9,0,1980-10-05 00:00:00 +15125,341,171,34.0,4,1,1980-10-05 00:00:00 +15126,341,223,5.0,15,0,1980-10-05 00:00:00 +15127,341,216,0.0,23,0,1980-10-05 00:00:00 +15128,341,221,2.0,19,0,1980-10-05 00:00:00 +15129,341,220,0.0,29,0,1980-10-05 00:00:00 +15130,341,116,5.0,16,0,1980-10-05 00:00:00 +15131,341,151,4.0,18,0,1980-10-05 00:00:00 +15132,341,205,6.0,12,0,1980-10-05 00:00:00 +15133,341,176,6.0,10,0,1980-10-05 00:00:00 +15134,341,136,54.0,2,3,1980-10-05 00:00:00 +15135,341,177,67.0,1,5,1980-10-05 00:00:00 +15136,341,186,6.0,11,0,1980-10-05 00:00:00 +15137,341,222,0.0,25,0,1980-10-05 00:00:00 +15138,341,218,9.0,8,1,1980-10-05 00:00:00 +15139,341,199,4.0,17,0,1980-10-05 00:00:00 +15140,341,201,32.0,5,1,1980-10-05 00:00:00 +15141,341,162,29.0,6,2,1980-10-05 00:00:00 +15142,341,213,0.0,41,0,1980-10-05 00:00:00 +15143,341,109,0.0,32,0,1980-10-05 00:00:00 +15144,341,190,0.0,34,0,1980-10-05 00:00:00 +15145,341,229,0.0,31,0,1980-10-05 00:00:00 +15146,341,94,0.0,30,0,1980-10-05 00:00:00 +15147,341,228,0.0,37,0,1980-10-05 00:00:00 +15148,341,227,0.0,40,0,1980-10-05 00:00:00 +15149,341,210,0.0,24,0,1980-10-05 00:00:00 +15150,341,180,0.0,38,0,1980-10-05 00:00:00 +15151,341,226,0.0,33,0,1980-10-05 00:00:00 +15152,341,225,0.0,39,0,1980-10-05 00:00:00 +15153,341,208,0.0,28,0,1980-10-05 00:00:00 +15154,341,157,0.0,27,0,1980-10-05 00:00:00 +15155,341,135,0.0,26,0,1980-10-05 00:00:00 +15156,341,139,0.0,36,0,1980-10-05 00:00:00 +15157,341,224,0.0,35,0,1980-10-05 00:00:00 +15158,341,196,6.0,13,0,1980-10-05 00:00:00 +15159,341,211,1.0,21,0,1980-10-05 00:00:00 +15160,342,118,0.0,17,0,1981-03-15 00:00:00 +15161,342,212,0.0,18,0,1981-03-15 00:00:00 +15162,342,94,0.0,19,0,1981-03-15 00:00:00 +15163,342,202,0.0,20,0,1981-03-15 00:00:00 +15164,342,186,0.0,21,0,1981-03-15 00:00:00 +15165,342,172,0.0,22,0,1981-03-15 00:00:00 +15166,342,205,0.0,26,0,1981-03-15 00:00:00 +15167,342,109,0.0,24,0,1981-03-15 00:00:00 +15168,342,213,0.0,25,0,1981-03-15 00:00:00 +15169,342,214,0.0,27,0,1981-03-15 00:00:00 +15170,342,193,0.0,29,0,1981-03-15 00:00:00 +15171,342,135,0.0,16,0,1981-03-15 00:00:00 +15172,342,116,0.0,23,0,1981-03-15 00:00:00 +15173,342,176,0.0,15,0,1981-03-15 00:00:00 +15174,342,215,0.0,28,0,1981-03-15 00:00:00 +15175,342,151,0.0,13,0,1981-03-15 00:00:00 +15176,342,177,9.0,1,1,1981-03-15 00:00:00 +15177,342,174,1.0,6,0,1981-03-15 00:00:00 +15178,342,157,2.0,5,0,1981-03-15 00:00:00 +15179,342,206,3.0,4,0,1981-03-15 00:00:00 +15180,342,136,4.0,3,0,1981-03-15 00:00:00 +15181,342,198,6.0,2,0,1981-03-15 00:00:00 +15182,342,171,0.0,14,0,1981-03-15 00:00:00 +15183,342,162,0.0,8,0,1981-03-15 00:00:00 +15184,342,175,0.0,9,0,1981-03-15 00:00:00 +15185,342,201,0.0,10,0,1981-03-15 00:00:00 +15186,342,196,0.0,11,0,1981-03-15 00:00:00 +15187,342,211,0.0,12,0,1981-03-15 00:00:00 +15188,342,191,0.0,7,0,1981-03-15 00:00:00 +15189,343,212,0.0,24,0,1981-03-29 00:00:00 +15190,343,94,0.0,16,0,1981-03-29 00:00:00 +15191,343,202,0.0,21,0,1981-03-29 00:00:00 +15192,343,186,0.0,13,0,1981-03-29 00:00:00 +15193,343,172,2.0,8,0,1981-03-29 00:00:00 +15194,343,116,0.0,23,0,1981-03-29 00:00:00 +15195,343,205,0.0,28,0,1981-03-29 00:00:00 +15196,343,213,0.0,27,0,1981-03-29 00:00:00 +15197,343,214,0.0,29,0,1981-03-29 00:00:00 +15198,343,215,0.0,25,0,1981-03-29 00:00:00 +15199,343,193,0.0,30,0,1981-03-29 00:00:00 +15200,343,118,4.0,4,0,1981-03-29 00:00:00 +15201,343,217,0.0,31,0,1981-03-29 00:00:00 +15202,343,109,0.0,26,0,1981-03-29 00:00:00 +15203,343,216,0.0,17,0,1981-03-29 00:00:00 +15204,343,135,0.0,22,0,1981-03-29 00:00:00 +15205,343,171,1.0,10,0,1981-03-29 00:00:00 +15206,343,176,0.0,15,0,1981-03-29 00:00:00 +15207,343,177,15.0,1,1,1981-03-29 00:00:00 +15208,343,198,15.0,2,1,1981-03-29 00:00:00 +15209,343,136,4.0,3,0,1981-03-29 00:00:00 +15210,343,157,2.0,7,0,1981-03-29 00:00:00 +15211,343,174,1.0,9,0,1981-03-29 00:00:00 +15212,343,206,3.0,6,0,1981-03-29 00:00:00 +15213,343,162,0.0,14,0,1981-03-29 00:00:00 +15214,343,175,3.0,5,0,1981-03-29 00:00:00 +15215,343,201,0.0,18,0,1981-03-29 00:00:00 +15216,343,196,0.0,11,0,1981-03-29 00:00:00 +15217,343,211,0.0,19,0,1981-03-29 00:00:00 +15218,343,151,0.0,20,0,1981-03-29 00:00:00 +15219,343,191,0.0,12,0,1981-03-29 00:00:00 +15220,344,109,0.0,20,0,1981-04-12 00:00:00 +15221,344,94,0.0,19,0,1981-04-12 00:00:00 +15222,344,202,0.0,25,0,1981-04-12 00:00:00 +15223,344,172,3.0,8,0,1981-04-12 00:00:00 +15224,344,116,4.0,5,0,1981-04-12 00:00:00 +15225,344,213,0.0,28,0,1981-04-12 00:00:00 +15226,344,212,0.0,26,0,1981-04-12 00:00:00 +15227,344,214,0.0,27,0,1981-04-12 00:00:00 +15228,344,215,0.0,17,0,1981-04-12 00:00:00 +15229,344,193,0.0,30,0,1981-04-12 00:00:00 +15230,344,216,0.0,22,0,1981-04-12 00:00:00 +15231,344,217,0.0,32,0,1981-04-12 00:00:00 +15232,344,218,0.0,31,0,1981-04-12 00:00:00 +15233,344,205,0.0,29,0,1981-04-12 00:00:00 +15234,344,118,4.0,4,0,1981-04-12 00:00:00 +15235,344,186,0.0,15,0,1981-04-12 00:00:00 +15236,344,176,0.0,16,0,1981-04-12 00:00:00 +15237,344,177,18.0,2,1,1981-04-12 00:00:00 +15238,344,198,21.0,1,1,1981-04-12 00:00:00 +15239,344,136,13.0,3,1,1981-04-12 00:00:00 +15240,344,206,3.0,6,0,1981-04-12 00:00:00 +15241,344,174,1.0,11,0,1981-04-12 00:00:00 +15242,344,191,0.0,14,0,1981-04-12 00:00:00 +15243,344,162,2.0,9,0,1981-04-12 00:00:00 +15244,344,157,2.0,10,0,1981-04-12 00:00:00 +15245,344,201,0.0,23,0,1981-04-12 00:00:00 +15246,344,196,0.0,13,0,1981-04-12 00:00:00 +15247,344,135,0.0,21,0,1981-04-12 00:00:00 +15248,344,211,0.0,24,0,1981-04-12 00:00:00 +15249,344,151,0.0,18,0,1981-04-12 00:00:00 +15250,344,171,1.0,12,0,1981-04-12 00:00:00 +15251,344,175,3.0,7,0,1981-04-12 00:00:00 +15252,345,214,0.0,31,0,1981-05-03 00:00:00 +15253,345,172,3.0,9,0,1981-05-03 00:00:00 +15254,345,116,4.0,5,0,1981-05-03 00:00:00 +15255,345,109,1.0,14,0,1981-05-03 00:00:00 +15256,345,213,0.0,32,0,1981-05-03 00:00:00 +15257,345,205,0.0,33,0,1981-05-03 00:00:00 +15258,345,215,0.0,21,0,1981-05-03 00:00:00 +15259,345,204,0.0,35,0,1981-05-03 00:00:00 +15260,345,216,0.0,25,0,1981-05-03 00:00:00 +15261,345,217,0.0,36,0,1981-05-03 00:00:00 +15262,345,218,0.0,27,0,1981-05-03 00:00:00 +15263,345,200,0.0,26,0,1981-05-03 00:00:00 +15264,345,104,0.0,29,0,1981-05-03 00:00:00 +15265,345,117,0.0,34,0,1981-05-03 00:00:00 +15266,345,186,0.0,19,0,1981-05-03 00:00:00 +15267,345,193,0.0,28,0,1981-05-03 00:00:00 +15268,345,202,0.0,17,0,1981-05-03 00:00:00 +15269,345,94,0.0,23,0,1981-05-03 00:00:00 +15270,345,177,18.0,3,1,1981-05-03 00:00:00 +15271,345,212,0.0,30,0,1981-05-03 00:00:00 +15272,345,198,25.0,1,1,1981-05-03 00:00:00 +15273,345,136,22.0,2,2,1981-05-03 00:00:00 +15274,345,206,3.0,6,0,1981-05-03 00:00:00 +15275,345,157,2.0,12,0,1981-05-03 00:00:00 +15276,345,191,0.0,18,0,1981-05-03 00:00:00 +15277,345,162,2.0,10,0,1981-05-03 00:00:00 +15278,345,175,3.0,7,0,1981-05-03 00:00:00 +15279,345,174,1.0,13,0,1981-05-03 00:00:00 +15280,345,196,0.0,16,0,1981-05-03 00:00:00 +15281,345,211,3.0,8,0,1981-05-03 00:00:00 +15282,345,151,0.0,22,0,1981-05-03 00:00:00 +15283,345,171,1.0,15,0,1981-05-03 00:00:00 +15284,345,176,0.0,20,0,1981-05-03 00:00:00 +15285,345,135,0.0,24,0,1981-05-03 00:00:00 +15286,345,118,10.0,4,0,1981-05-03 00:00:00 +15287,345,201,2.0,11,0,1981-05-03 00:00:00 +15288,346,215,0.0,23,0,1981-05-17 00:00:00 +15289,346,172,5.0,6,0,1981-05-17 00:00:00 +15290,346,116,4.0,8,0,1981-05-17 00:00:00 +15291,346,109,1.0,17,0,1981-05-17 00:00:00 +15292,346,213,0.0,34,0,1981-05-17 00:00:00 +15293,346,205,0.0,33,0,1981-05-17 00:00:00 +15294,346,214,0.0,32,0,1981-05-17 00:00:00 +15295,346,193,0.0,30,0,1981-05-17 00:00:00 +15296,346,186,0.0,18,0,1981-05-17 00:00:00 +15297,346,217,0.0,37,0,1981-05-17 00:00:00 +15298,346,218,0.0,29,0,1981-05-17 00:00:00 +15299,346,200,0.0,27,0,1981-05-17 00:00:00 +15300,346,104,0.0,25,0,1981-05-17 00:00:00 +15301,346,117,0.0,35,0,1981-05-17 00:00:00 +15302,346,204,0.0,36,0,1981-05-17 00:00:00 +15303,346,159,0.0,28,0,1981-05-17 00:00:00 +15304,346,216,0.0,26,0,1981-05-17 00:00:00 +15305,346,202,3.0,9,0,1981-05-17 00:00:00 +15306,346,177,18.0,3,1,1981-05-17 00:00:00 +15307,346,212,0.0,31,0,1981-05-17 00:00:00 +15308,346,94,4.0,7,0,1981-05-17 00:00:00 +15309,346,198,34.0,1,2,1981-05-17 00:00:00 +15310,346,136,22.0,2,2,1981-05-17 00:00:00 +15311,346,206,3.0,10,0,1981-05-17 00:00:00 +15312,346,157,3.0,13,0,1981-05-17 00:00:00 +15313,346,191,0.0,20,0,1981-05-17 00:00:00 +15314,346,162,2.0,14,0,1981-05-17 00:00:00 +15315,346,175,3.0,11,0,1981-05-17 00:00:00 +15316,346,174,1.0,16,0,1981-05-17 00:00:00 +15317,346,196,0.0,19,0,1981-05-17 00:00:00 +15318,346,211,3.0,12,0,1981-05-17 00:00:00 +15319,346,151,0.0,21,0,1981-05-17 00:00:00 +15320,346,171,7.0,5,0,1981-05-17 00:00:00 +15321,346,176,0.0,22,0,1981-05-17 00:00:00 +15322,346,135,0.0,24,0,1981-05-17 00:00:00 +15323,346,118,10.0,4,0,1981-05-17 00:00:00 +15324,346,201,2.0,15,0,1981-05-17 00:00:00 +15325,347,205,0.0,33,0,1981-05-31 00:00:00 +15326,347,186,0.0,18,0,1981-05-31 00:00:00 +15327,347,172,5.0,9,0,1981-05-31 00:00:00 +15328,347,116,4.0,11,0,1981-05-31 00:00:00 +15329,347,109,1.0,17,0,1981-05-31 00:00:00 +15330,347,213,0.0,34,0,1981-05-31 00:00:00 +15331,347,214,0.0,32,0,1981-05-31 00:00:00 +15332,347,202,12.0,4,1,1981-05-31 00:00:00 +15333,347,159,0.0,27,0,1981-05-31 00:00:00 +15334,347,204,0.0,36,0,1981-05-31 00:00:00 +15335,347,117,0.0,35,0,1981-05-31 00:00:00 +15336,347,104,0.0,24,0,1981-05-31 00:00:00 +15337,347,200,0.0,28,0,1981-05-31 00:00:00 +15338,347,217,0.0,37,0,1981-05-31 00:00:00 +15339,347,218,0.0,29,0,1981-05-31 00:00:00 +15340,347,215,0.0,23,0,1981-05-31 00:00:00 +15341,347,94,4.0,10,0,1981-05-31 00:00:00 +15342,347,198,34.0,1,2,1981-05-31 00:00:00 +15343,347,118,10.0,6,0,1981-05-31 00:00:00 +15344,347,216,0.0,26,0,1981-05-31 00:00:00 +15345,347,177,24.0,2,1,1981-05-31 00:00:00 +15346,347,136,22.0,3,2,1981-05-31 00:00:00 +15347,347,206,3.0,13,0,1981-05-31 00:00:00 +15348,347,157,5.0,8,0,1981-05-31 00:00:00 +15349,347,174,1.0,16,0,1981-05-31 00:00:00 +15350,347,191,0.0,20,0,1981-05-31 00:00:00 +15351,347,212,0.0,31,0,1981-05-31 00:00:00 +15352,347,193,0.0,30,0,1981-05-31 00:00:00 +15353,347,175,4.0,12,0,1981-05-31 00:00:00 +15354,347,135,0.0,25,0,1981-05-31 00:00:00 +15355,347,176,0.0,22,0,1981-05-31 00:00:00 +15356,347,171,11.0,5,0,1981-05-31 00:00:00 +15357,347,151,0.0,21,0,1981-05-31 00:00:00 +15358,347,211,3.0,14,0,1981-05-31 00:00:00 +15359,347,196,0.0,19,0,1981-05-31 00:00:00 +15360,347,201,5.0,7,0,1981-05-31 00:00:00 +15361,347,162,2.0,15,0,1981-05-31 00:00:00 +15362,348,214,0.0,33,0,1981-06-21 00:00:00 +15363,348,205,0.0,30,0,1981-06-21 00:00:00 +15364,348,213,0.0,34,0,1981-06-21 00:00:00 +15365,348,117,0.0,36,0,1981-06-21 00:00:00 +15366,348,172,7.0,7,0,1981-06-21 00:00:00 +15367,348,215,0.0,23,0,1981-06-21 00:00:00 +15368,348,116,4.0,12,0,1981-06-21 00:00:00 +15369,348,193,0.0,29,0,1981-06-21 00:00:00 +15370,348,104,0.0,24,0,1981-06-21 00:00:00 +15371,348,217,0.0,38,0,1981-06-21 00:00:00 +15372,348,218,0.0,31,0,1981-06-21 00:00:00 +15373,348,200,0.0,28,0,1981-06-21 00:00:00 +15374,348,186,4.0,11,0,1981-06-21 00:00:00 +15375,348,204,0.0,35,0,1981-06-21 00:00:00 +15376,348,159,0.0,27,0,1981-06-21 00:00:00 +15377,348,219,0.0,37,0,1981-06-21 00:00:00 +15378,348,216,0.0,26,0,1981-06-21 00:00:00 +15379,348,202,21.0,4,2,1981-06-21 00:00:00 +15380,348,109,1.0,18,0,1981-06-21 00:00:00 +15381,348,212,0.0,32,0,1981-06-21 00:00:00 +15382,348,177,24.0,2,1,1981-06-21 00:00:00 +15383,348,198,37.0,1,2,1981-06-21 00:00:00 +15384,348,94,5.0,8,0,1981-06-21 00:00:00 +15385,348,206,3.0,14,0,1981-06-21 00:00:00 +15386,348,157,5.0,10,0,1981-06-21 00:00:00 +15387,348,174,1.0,17,0,1981-06-21 00:00:00 +15388,348,191,0.0,19,0,1981-06-21 00:00:00 +15389,348,162,2.0,16,0,1981-06-21 00:00:00 +15390,348,175,4.0,13,0,1981-06-21 00:00:00 +15391,348,136,22.0,3,2,1981-06-21 00:00:00 +15392,348,196,0.0,20,0,1981-06-21 00:00:00 +15393,348,211,3.0,15,0,1981-06-21 00:00:00 +15394,348,151,0.0,21,0,1981-06-21 00:00:00 +15395,348,171,17.0,5,0,1981-06-21 00:00:00 +15396,348,176,0.0,22,0,1981-06-21 00:00:00 +15397,348,135,0.0,25,0,1981-06-21 00:00:00 +15398,348,201,5.0,9,0,1981-06-21 00:00:00 +15399,348,118,10.0,6,0,1981-06-21 00:00:00 +15400,349,186,10.0,7,0,1981-07-05 00:00:00 +15401,349,172,8.0,9,0,1981-07-05 00:00:00 +15402,349,116,13.0,6,1,1981-07-05 00:00:00 +15403,349,109,1.0,18,0,1981-07-05 00:00:00 +15404,349,213,0.0,34,0,1981-07-05 00:00:00 +15405,349,205,0.0,30,0,1981-07-05 00:00:00 +15406,349,214,0.0,33,0,1981-07-05 00:00:00 +15407,349,219,0.0,37,0,1981-07-05 00:00:00 +15408,349,193,0.0,29,0,1981-07-05 00:00:00 +15409,349,159,0.0,27,0,1981-07-05 00:00:00 +15410,349,204,0.0,35,0,1981-07-05 00:00:00 +15411,349,117,0.0,36,0,1981-07-05 00:00:00 +15412,349,200,0.0,28,0,1981-07-05 00:00:00 +15413,349,202,21.0,4,2,1981-07-05 00:00:00 +15414,349,218,0.0,31,0,1981-07-05 00:00:00 +15415,349,215,0.0,23,0,1981-07-05 00:00:00 +15416,349,94,5.0,11,0,1981-07-05 00:00:00 +15417,349,104,0.0,24,0,1981-07-05 00:00:00 +15418,349,118,10.0,8,0,1981-07-05 00:00:00 +15419,349,217,0.0,38,0,1981-07-05 00:00:00 +15420,349,177,24.0,3,1,1981-07-05 00:00:00 +15421,349,198,37.0,1,2,1981-07-05 00:00:00 +15422,349,136,26.0,2,2,1981-07-05 00:00:00 +15423,349,206,3.0,15,0,1981-07-05 00:00:00 +15424,349,157,5.0,13,0,1981-07-05 00:00:00 +15425,349,174,1.0,17,0,1981-07-05 00:00:00 +15426,349,191,0.0,19,0,1981-07-05 00:00:00 +15427,349,162,5.0,12,0,1981-07-05 00:00:00 +15428,349,175,4.0,14,0,1981-07-05 00:00:00 +15429,349,201,7.0,10,0,1981-07-05 00:00:00 +15430,349,196,0.0,20,0,1981-07-05 00:00:00 +15431,349,211,3.0,16,0,1981-07-05 00:00:00 +15432,349,151,0.0,21,0,1981-07-05 00:00:00 +15433,349,171,17.0,5,0,1981-07-05 00:00:00 +15434,349,176,0.0,22,0,1981-07-05 00:00:00 +15435,349,135,0.0,25,0,1981-07-05 00:00:00 +15436,349,212,0.0,32,0,1981-07-05 00:00:00 +15437,349,216,0.0,26,0,1981-07-05 00:00:00 +15438,350,177,24.0,3,1,1981-07-18 00:00:00 +15439,350,136,26.0,2,2,1981-07-18 00:00:00 +15440,350,109,1.0,18,0,1981-07-18 00:00:00 +15441,350,213,0.0,34,0,1981-07-18 00:00:00 +15442,350,205,0.0,22,0,1981-07-18 00:00:00 +15443,350,214,0.0,33,0,1981-07-18 00:00:00 +15444,350,215,0.0,25,0,1981-07-18 00:00:00 +15445,350,193,0.0,30,0,1981-07-18 00:00:00 +15446,350,217,0.0,38,0,1981-07-18 00:00:00 +15447,350,218,0.0,31,0,1981-07-18 00:00:00 +15448,350,200,1.0,19,0,1981-07-18 00:00:00 +15449,350,104,0.0,26,0,1981-07-18 00:00:00 +15450,350,117,0.0,36,0,1981-07-18 00:00:00 +15451,350,204,0.0,35,0,1981-07-18 00:00:00 +15452,350,159,0.0,29,0,1981-07-18 00:00:00 +15453,350,219,0.0,37,0,1981-07-18 00:00:00 +15454,350,198,43.0,1,2,1981-07-18 00:00:00 +15455,350,116,13.0,7,1,1981-07-18 00:00:00 +15456,350,172,8.0,10,0,1981-07-18 00:00:00 +15457,350,216,0.0,28,0,1981-07-18 00:00:00 +15458,350,202,21.0,4,2,1981-07-18 00:00:00 +15459,350,206,3.0,16,0,1981-07-18 00:00:00 +15460,350,186,19.0,6,1,1981-07-18 00:00:00 +15461,350,157,8.0,9,0,1981-07-18 00:00:00 +15462,350,174,1.0,17,0,1981-07-18 00:00:00 +15463,350,191,0.0,21,0,1981-07-18 00:00:00 +15464,350,162,5.0,13,0,1981-07-18 00:00:00 +15465,350,201,7.0,11,0,1981-07-18 00:00:00 +15466,350,196,0.0,20,0,1981-07-18 00:00:00 +15467,350,175,4.0,15,0,1981-07-18 00:00:00 +15468,350,151,0.0,23,0,1981-07-18 00:00:00 +15469,350,171,21.0,5,0,1981-07-18 00:00:00 +15470,350,176,0.0,24,0,1981-07-18 00:00:00 +15471,350,135,0.0,27,0,1981-07-18 00:00:00 +15472,350,118,10.0,8,0,1981-07-18 00:00:00 +15473,350,212,0.0,32,0,1981-07-18 00:00:00 +15474,350,94,5.0,12,0,1981-07-18 00:00:00 +15475,350,211,5.0,14,0,1981-07-18 00:00:00 +15476,351,191,0.0,21,0,1981-08-02 00:00:00 +15477,351,213,0.0,34,0,1981-08-02 00:00:00 +15478,351,157,10.0,9,0,1981-08-02 00:00:00 +15479,351,206,3.0,16,0,1981-08-02 00:00:00 +15480,351,198,43.0,1,2,1981-08-02 00:00:00 +15481,351,117,0.0,36,0,1981-08-02 00:00:00 +15482,351,214,0.0,33,0,1981-08-02 00:00:00 +15483,351,186,20.0,6,1,1981-08-02 00:00:00 +15484,351,135,0.0,27,0,1981-08-02 00:00:00 +15485,351,116,19.0,7,1,1981-08-02 00:00:00 +15486,351,193,0.0,30,0,1981-08-02 00:00:00 +15487,351,162,5.0,14,0,1981-08-02 00:00:00 +15488,351,174,1.0,17,0,1981-08-02 00:00:00 +15489,351,136,35.0,2,3,1981-08-02 00:00:00 +15490,351,201,7.0,12,0,1981-08-02 00:00:00 +15491,351,175,4.0,15,0,1981-08-02 00:00:00 +15492,351,219,0.0,37,0,1981-08-02 00:00:00 +15493,351,196,0.0,20,0,1981-08-02 00:00:00 +15494,351,204,0.0,35,0,1981-08-02 00:00:00 +15495,351,151,0.0,23,0,1981-08-02 00:00:00 +15496,351,159,0.0,29,0,1981-08-02 00:00:00 +15497,351,104,0.0,26,0,1981-08-02 00:00:00 +15498,351,200,1.0,19,0,1981-08-02 00:00:00 +15499,351,218,0.0,31,0,1981-08-02 00:00:00 +15500,351,217,0.0,38,0,1981-08-02 00:00:00 +15501,351,216,0.0,28,0,1981-08-02 00:00:00 +15502,351,215,0.0,25,0,1981-08-02 00:00:00 +15503,351,211,8.0,10,0,1981-08-02 00:00:00 +15504,351,205,0.0,22,0,1981-08-02 00:00:00 +15505,351,172,8.0,11,0,1981-08-02 00:00:00 +15506,351,202,21.0,5,2,1981-08-02 00:00:00 +15507,351,94,5.0,13,0,1981-08-02 00:00:00 +15508,351,212,0.0,32,0,1981-08-02 00:00:00 +15509,351,118,10.0,8,0,1981-08-02 00:00:00 +15510,351,176,0.0,24,0,1981-08-02 00:00:00 +15511,351,171,25.0,3,0,1981-08-02 00:00:00 +15512,351,109,1.0,18,0,1981-08-02 00:00:00 +15513,351,177,24.0,4,1,1981-08-02 00:00:00 +15514,352,116,19.0,7,1,1981-08-16 00:00:00 +15515,352,198,45.0,1,2,1981-08-16 00:00:00 +15516,352,177,27.0,4,1,1981-08-16 00:00:00 +15517,352,109,1.0,18,0,1981-08-16 00:00:00 +15518,352,213,0.0,34,0,1981-08-16 00:00:00 +15519,352,205,0.0,21,0,1981-08-16 00:00:00 +15520,352,214,0.0,33,0,1981-08-16 00:00:00 +15521,352,215,0.0,25,0,1981-08-16 00:00:00 +15522,352,216,0.0,28,0,1981-08-16 00:00:00 +15523,352,217,0.0,38,0,1981-08-16 00:00:00 +15524,352,218,0.0,31,0,1981-08-16 00:00:00 +15525,352,200,1.0,19,0,1981-08-16 00:00:00 +15526,352,104,0.0,26,0,1981-08-16 00:00:00 +15527,352,117,0.0,36,0,1981-08-16 00:00:00 +15528,352,204,0.0,35,0,1981-08-16 00:00:00 +15529,352,159,0.0,29,0,1981-08-16 00:00:00 +15530,352,219,0.0,37,0,1981-08-16 00:00:00 +15531,352,172,8.0,12,0,1981-08-16 00:00:00 +15532,352,186,21.0,6,1,1981-08-16 00:00:00 +15533,352,193,0.0,30,0,1981-08-16 00:00:00 +15534,352,94,5.0,14,0,1981-08-16 00:00:00 +15535,352,202,21.0,5,2,1981-08-16 00:00:00 +15536,352,136,39.0,2,3,1981-08-16 00:00:00 +15537,352,206,3.0,16,0,1981-08-16 00:00:00 +15538,352,157,10.0,10,0,1981-08-16 00:00:00 +15539,352,174,1.0,17,0,1981-08-16 00:00:00 +15540,352,191,0.0,22,0,1981-08-16 00:00:00 +15541,352,175,4.0,15,0,1981-08-16 00:00:00 +15542,352,201,7.0,13,0,1981-08-16 00:00:00 +15543,352,162,11.0,8,0,1981-08-16 00:00:00 +15544,352,211,8.0,11,0,1981-08-16 00:00:00 +15545,352,151,0.0,23,0,1981-08-16 00:00:00 +15546,352,171,34.0,3,1,1981-08-16 00:00:00 +15547,352,176,0.0,24,0,1981-08-16 00:00:00 +15548,352,135,0.0,27,0,1981-08-16 00:00:00 +15549,352,118,10.0,9,0,1981-08-16 00:00:00 +15550,352,212,0.0,32,0,1981-08-16 00:00:00 +15551,352,196,0.0,20,0,1981-08-16 00:00:00 +15552,353,172,10.0,12,0,1981-08-30 00:00:00 +15553,353,215,0.0,22,0,1981-08-30 00:00:00 +15554,353,116,28.0,5,2,1981-08-30 00:00:00 +15555,353,109,1.0,18,0,1981-08-30 00:00:00 +15556,353,213,0.0,34,0,1981-08-30 00:00:00 +15557,353,205,0.0,23,0,1981-08-30 00:00:00 +15558,353,214,0.0,33,0,1981-08-30 00:00:00 +15559,353,193,1.0,20,0,1981-08-30 00:00:00 +15560,353,219,0.0,37,0,1981-08-30 00:00:00 +15561,353,217,0.0,38,0,1981-08-30 00:00:00 +15562,353,218,0.0,31,0,1981-08-30 00:00:00 +15563,353,200,1.0,19,0,1981-08-30 00:00:00 +15564,353,104,0.0,26,0,1981-08-30 00:00:00 +15565,353,117,0.0,36,0,1981-08-30 00:00:00 +15566,353,204,0.0,35,0,1981-08-30 00:00:00 +15567,353,159,0.0,30,0,1981-08-30 00:00:00 +15568,353,186,21.0,7,1,1981-08-30 00:00:00 +15569,353,216,0.0,29,0,1981-08-30 00:00:00 +15570,353,202,21.0,6,2,1981-08-30 00:00:00 +15571,353,201,7.0,13,0,1981-08-30 00:00:00 +15572,353,212,0.0,32,0,1981-08-30 00:00:00 +15573,353,94,5.0,14,0,1981-08-30 00:00:00 +15574,353,177,31.0,4,1,1981-08-30 00:00:00 +15575,353,198,45.0,2,2,1981-08-30 00:00:00 +15576,353,136,45.0,1,3,1981-08-30 00:00:00 +15577,353,206,3.0,16,0,1981-08-30 00:00:00 +15578,353,157,10.0,11,0,1981-08-30 00:00:00 +15579,353,191,0.0,24,0,1981-08-30 00:00:00 +15580,353,162,11.0,8,0,1981-08-30 00:00:00 +15581,353,174,1.0,17,0,1981-08-30 00:00:00 +15582,353,196,0.0,21,0,1981-08-30 00:00:00 +15583,353,211,11.0,9,0,1981-08-30 00:00:00 +15584,353,151,0.0,25,0,1981-08-30 00:00:00 +15585,353,171,34.0,3,1,1981-08-30 00:00:00 +15586,353,176,0.0,27,0,1981-08-30 00:00:00 +15587,353,135,0.0,28,0,1981-08-30 00:00:00 +15588,353,118,10.0,10,0,1981-08-30 00:00:00 +15589,353,175,4.0,15,0,1981-08-30 00:00:00 +15590,354,172,13.0,8,0,1981-09-13 00:00:00 +15591,354,215,0.0,22,0,1981-09-13 00:00:00 +15592,354,116,37.0,3,3,1981-09-13 00:00:00 +15593,354,109,1.0,17,0,1981-09-13 00:00:00 +15594,354,213,0.0,35,0,1981-09-13 00:00:00 +15595,354,205,0.0,23,0,1981-09-13 00:00:00 +15596,354,214,0.0,34,0,1981-09-13 00:00:00 +15597,354,193,1.0,20,0,1981-09-13 00:00:00 +15598,354,219,0.0,37,0,1981-09-13 00:00:00 +15599,354,217,0.0,38,0,1981-09-13 00:00:00 +15600,354,218,0.0,32,0,1981-09-13 00:00:00 +15601,354,200,1.0,19,0,1981-09-13 00:00:00 +15602,354,104,0.0,26,0,1981-09-13 00:00:00 +15603,354,117,0.0,36,0,1981-09-13 00:00:00 +15604,354,204,0.0,28,0,1981-09-13 00:00:00 +15605,354,159,0.0,31,0,1981-09-13 00:00:00 +15606,354,186,21.0,7,1,1981-09-13 00:00:00 +15607,354,216,0.0,30,0,1981-09-13 00:00:00 +15608,354,202,21.0,6,2,1981-09-13 00:00:00 +15609,354,196,0.0,21,0,1981-09-13 00:00:00 +15610,354,212,0.0,33,0,1981-09-13 00:00:00 +15611,354,177,37.0,4,1,1981-09-13 00:00:00 +15612,354,198,49.0,1,2,1981-09-13 00:00:00 +15613,354,136,46.0,2,3,1981-09-13 00:00:00 +15614,354,206,3.0,16,0,1981-09-13 00:00:00 +15615,354,157,10.0,12,0,1981-09-13 00:00:00 +15616,354,174,1.0,18,0,1981-09-13 00:00:00 +15617,354,191,0.0,24,0,1981-09-13 00:00:00 +15618,354,162,11.0,9,0,1981-09-13 00:00:00 +15619,354,94,5.0,14,0,1981-09-13 00:00:00 +15620,354,201,9.0,13,0,1981-09-13 00:00:00 +15621,354,211,11.0,10,0,1981-09-13 00:00:00 +15622,354,151,0.0,25,0,1981-09-13 00:00:00 +15623,354,171,34.0,5,1,1981-09-13 00:00:00 +15624,354,176,0.0,27,0,1981-09-13 00:00:00 +15625,354,135,0.0,29,0,1981-09-13 00:00:00 +15626,354,118,10.0,11,0,1981-09-13 00:00:00 +15627,354,175,4.0,15,0,1981-09-13 00:00:00 +15628,355,172,14.0,8,0,1981-09-27 00:00:00 +15629,355,116,37.0,4,3,1981-09-27 00:00:00 +15630,355,109,1.0,18,0,1981-09-27 00:00:00 +15631,355,213,0.0,35,0,1981-09-27 00:00:00 +15632,355,205,0.0,23,0,1981-09-27 00:00:00 +15633,355,214,0.0,34,0,1981-09-27 00:00:00 +15634,355,215,0.0,24,0,1981-09-27 00:00:00 +15635,355,193,1.0,21,0,1981-09-27 00:00:00 +15636,355,200,1.0,20,0,1981-09-27 00:00:00 +15637,355,217,0.0,39,0,1981-09-27 00:00:00 +15638,355,218,0.0,32,0,1981-09-27 00:00:00 +15639,355,104,0.0,26,0,1981-09-27 00:00:00 +15640,355,117,0.0,36,0,1981-09-27 00:00:00 +15641,355,204,0.0,28,0,1981-09-27 00:00:00 +15642,355,159,0.0,31,0,1981-09-27 00:00:00 +15643,355,186,27.0,6,1,1981-09-27 00:00:00 +15644,355,197,0.0,37,0,1981-09-27 00:00:00 +15645,355,216,0.0,30,0,1981-09-27 00:00:00 +15646,355,219,0.0,38,0,1981-09-27 00:00:00 +15647,355,202,25.0,7,2,1981-09-27 00:00:00 +15648,355,212,0.0,33,0,1981-09-27 00:00:00 +15649,355,94,5.0,14,0,1981-09-27 00:00:00 +15650,355,177,37.0,5,1,1981-09-27 00:00:00 +15651,355,198,49.0,1,2,1981-09-27 00:00:00 +15652,355,136,48.0,2,3,1981-09-27 00:00:00 +15653,355,206,3.0,16,0,1981-09-27 00:00:00 +15654,355,174,1.0,19,0,1981-09-27 00:00:00 +15655,355,191,0.0,25,0,1981-09-27 00:00:00 +15656,355,162,11.0,9,0,1981-09-27 00:00:00 +15657,355,157,10.0,12,0,1981-09-27 00:00:00 +15658,355,201,9.0,13,0,1981-09-27 00:00:00 +15659,355,175,4.0,15,0,1981-09-27 00:00:00 +15660,355,135,0.0,29,0,1981-09-27 00:00:00 +15661,355,176,0.0,27,0,1981-09-27 00:00:00 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00:00:00 +15729,357,151,0.0,11,0,1982-01-23 00:00:00 +15730,357,199,0.0,12,0,1982-01-23 00:00:00 +15731,357,109,0.0,13,0,1982-01-23 00:00:00 +15732,357,205,0.0,14,0,1982-01-23 00:00:00 +15733,357,195,0.0,15,0,1982-01-23 00:00:00 +15734,357,200,0.0,16,0,1982-01-23 00:00:00 +15735,357,191,0.0,17,0,1982-01-23 00:00:00 +15736,357,180,0.0,10,0,1982-01-23 00:00:00 +15737,358,171,0.0,24,0,1982-03-21 00:00:00 +15738,358,117,0.0,25,0,1982-03-21 00:00:00 +15739,358,118,0.0,22,0,1982-03-21 00:00:00 +15740,358,157,0.0,26,0,1982-03-21 00:00:00 +15741,358,136,0.0,27,0,1982-03-21 00:00:00 +15742,358,203,0.0,30,0,1982-03-21 00:00:00 +15743,358,196,0.0,15,0,1982-03-21 00:00:00 +15744,358,183,0.0,16,0,1982-03-21 00:00:00 +15745,358,201,1.0,10,0,1982-03-21 00:00:00 +15746,358,204,0.0,29,0,1982-03-21 00:00:00 +15747,358,194,0.0,31,0,1982-03-21 00:00:00 +15748,358,169,0.0,28,0,1982-03-21 00:00:00 +15749,358,94,4.0,5,0,1982-03-21 00:00:00 +15750,358,191,0.0,21,0,1982-03-21 00:00:00 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00:00:00 +15774,359,206,0.0,30,0,1982-04-04 00:00:00 +15775,359,183,0.0,18,0,1982-04-04 00:00:00 +15776,359,203,0.0,32,0,1982-04-04 00:00:00 +15777,359,204,0.0,24,0,1982-04-04 00:00:00 +15778,359,194,0.0,25,0,1982-04-04 00:00:00 +15779,359,169,0.0,31,0,1982-04-04 00:00:00 +15780,359,201,1.0,12,0,1982-04-04 00:00:00 +15781,359,196,0.0,17,0,1982-04-04 00:00:00 +15782,359,191,0.0,22,0,1982-04-04 00:00:00 +15783,359,94,4.0,7,0,1982-04-04 00:00:00 +15784,359,195,0.0,15,0,1982-04-04 00:00:00 +15785,359,200,0.0,13,0,1982-04-04 00:00:00 +15786,359,198,6.0,5,0,1982-04-04 00:00:00 +15787,359,162,4.0,9,0,1982-04-04 00:00:00 +15788,359,181,12.0,2,1,1982-04-04 00:00:00 +15789,359,176,8.0,3,0,1982-04-04 00:00:00 +15790,359,186,8.0,4,0,1982-04-04 00:00:00 +15791,359,104,6.0,6,0,1982-04-04 00:00:00 +15792,359,116,18.0,1,2,1982-04-04 00:00:00 +15793,359,193,0.0,16,0,1982-04-04 00:00:00 +15794,359,180,2.0,11,0,1982-04-04 00:00:00 +15795,359,151,0.0,19,0,1982-04-04 00:00:00 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00:00:00 +15819,360,151,0.0,20,0,1982-04-25 00:00:00 +15820,360,180,2.0,15,0,1982-04-25 00:00:00 +15821,360,172,2.0,13,0,1982-04-25 00:00:00 +15822,360,104,10.0,4,0,1982-04-25 00:00:00 +15823,360,186,8.0,6,0,1982-04-25 00:00:00 +15824,360,176,8.0,5,0,1982-04-25 00:00:00 +15825,360,181,12.0,2,1,1982-04-25 00:00:00 +15826,360,162,4.0,10,0,1982-04-25 00:00:00 +15827,360,198,6.0,8,0,1982-04-25 00:00:00 +15828,360,169,0.0,24,0,1982-04-25 00:00:00 +15829,360,200,0.0,16,0,1982-04-25 00:00:00 +15830,360,206,0.0,32,0,1982-04-25 00:00:00 +15831,360,116,18.0,1,2,1982-04-25 00:00:00 +15832,361,169,0.0,28,0,1982-05-09 00:00:00 +15833,361,200,0.0,19,0,1982-05-09 00:00:00 +15834,361,191,1.0,18,0,1982-05-09 00:00:00 +15835,361,201,10.0,5,1,1982-05-09 00:00:00 +15836,361,171,0.0,23,0,1982-05-09 00:00:00 +15837,361,117,0.0,31,0,1982-05-09 00:00:00 +15838,361,118,4.0,13,0,1982-05-09 00:00:00 +15839,361,157,4.0,12,0,1982-05-09 00:00:00 +15840,361,202,6.0,7,0,1982-05-09 00:00:00 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00:00:00 +15864,361,180,2.0,16,0,1982-05-09 00:00:00 +15865,361,151,0.0,25,0,1982-05-09 00:00:00 +15866,361,176,14.0,3,0,1982-05-09 00:00:00 +15867,362,157,4.0,14,0,1982-05-23 00:00:00 +15868,362,202,6.0,10,0,1982-05-23 00:00:00 +15869,362,136,2.0,18,0,1982-05-23 00:00:00 +15870,362,94,7.0,8,0,1982-05-23 00:00:00 +15871,362,196,3.0,15,0,1982-05-23 00:00:00 +15872,362,183,0.0,27,0,1982-05-23 00:00:00 +15873,362,203,0.0,30,0,1982-05-23 00:00:00 +15874,362,169,0.0,29,0,1982-05-23 00:00:00 +15875,362,194,0.0,32,0,1982-05-23 00:00:00 +15876,362,206,0.0,33,0,1982-05-23 00:00:00 +15877,362,175,0.0,21,0,1982-05-23 00:00:00 +15878,362,135,0.0,34,0,1982-05-23 00:00:00 +15879,362,207,0.0,35,0,1982-05-23 00:00:00 +15880,362,118,13.0,5,1,1982-05-23 00:00:00 +15881,362,204,0.0,25,0,1982-05-23 00:00:00 +15882,362,171,0.0,26,0,1982-05-23 00:00:00 +15883,362,117,0.0,31,0,1982-05-23 00:00:00 +15884,362,116,18.0,1,2,1982-05-23 00:00:00 +15885,362,198,6.0,11,0,1982-05-23 00:00:00 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00:00:00 +15909,363,204,0.0,26,0,1982-06-06 00:00:00 +15910,363,194,0.0,32,0,1982-06-06 00:00:00 +15911,363,169,0.0,29,0,1982-06-06 00:00:00 +15912,363,206,0.0,33,0,1982-06-06 00:00:00 +15913,363,175,0.0,23,0,1982-06-06 00:00:00 +15914,363,135,0.0,34,0,1982-06-06 00:00:00 +15915,363,207,0.0,35,0,1982-06-06 00:00:00 +15916,363,203,0.0,30,0,1982-06-06 00:00:00 +15917,363,117,0.0,31,0,1982-06-06 00:00:00 +15918,363,199,0.0,22,0,1982-06-06 00:00:00 +15919,363,201,20.0,2,1,1982-06-06 00:00:00 +15920,363,171,1.0,20,0,1982-06-06 00:00:00 +15921,363,116,18.0,3,2,1982-06-06 00:00:00 +15922,363,162,4.0,13,0,1982-06-06 00:00:00 +15923,363,181,12.0,6,1,1982-06-06 00:00:00 +15924,363,176,17.0,4,0,1982-06-06 00:00:00 +15925,363,186,26.0,1,2,1982-06-06 00:00:00 +15926,363,104,10.0,8,0,1982-06-06 00:00:00 +15927,363,172,7.0,10,0,1982-06-06 00:00:00 +15928,363,198,6.0,12,0,1982-06-06 00:00:00 +15929,363,180,2.0,18,0,1982-06-06 00:00:00 +15930,363,151,0.0,28,0,1982-06-06 00:00:00 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00:00:00 +16020,366,206,0.0,35,0,1982-07-18 00:00:00 +16021,366,175,2.0,19,0,1982-07-18 00:00:00 +16022,366,135,0.0,34,0,1982-07-18 00:00:00 +16023,366,207,0.0,37,0,1982-07-18 00:00:00 +16024,366,208,0.0,36,0,1982-07-18 00:00:00 +16025,366,174,4.0,16,0,1982-07-18 00:00:00 +16026,366,89,0.0,38,0,1982-07-18 00:00:00 +16027,366,151,0.0,27,0,1982-07-18 00:00:00 +16028,366,202,6.0,13,0,1982-07-18 00:00:00 +16029,366,157,10.0,9,0,1982-07-18 00:00:00 +16030,366,198,6.0,14,0,1982-07-18 00:00:00 +16031,366,117,0.0,32,0,1982-07-18 00:00:00 +16032,366,193,2.0,20,0,1982-07-18 00:00:00 +16033,366,118,19.0,6,1,1982-07-18 00:00:00 +16034,366,172,13.0,8,0,1982-07-18 00:00:00 +16035,366,104,10.0,10,0,1982-07-18 00:00:00 +16036,366,186,30.0,2,2,1982-07-18 00:00:00 +16037,366,181,24.0,3,2,1982-07-18 00:00:00 +16038,366,162,4.0,17,0,1982-07-18 00:00:00 +16039,366,199,0.0,25,0,1982-07-18 00:00:00 +16040,366,176,21.0,4,0,1982-07-18 00:00:00 +16041,366,109,5.0,15,0,1982-07-18 00:00:00 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+16196,370,193,2.0,22,0,1982-08-29 00:00:00 +16197,370,117,0.0,31,0,1982-08-29 00:00:00 +16198,370,151,2.0,21,0,1982-08-29 00:00:00 +16199,370,199,0.0,27,0,1982-08-29 00:00:00 +16200,370,109,5.0,18,0,1982-08-29 00:00:00 +16201,370,205,7.0,14,0,1982-08-29 00:00:00 +16202,370,195,0.0,29,0,1982-08-29 00:00:00 +16203,370,200,0.0,28,0,1982-08-29 00:00:00 +16204,370,191,1.0,25,0,1982-08-29 00:00:00 +16205,370,201,39.0,2,2,1982-08-29 00:00:00 +16206,370,180,2.0,23,0,1982-08-29 00:00:00 +16207,371,203,0.0,35,0,1982-09-12 00:00:00 +16208,371,183,2.0,25,0,1982-09-12 00:00:00 +16209,371,202,6.0,15,0,1982-09-12 00:00:00 +16210,371,94,7.0,13,0,1982-09-12 00:00:00 +16211,371,136,20.0,10,1,1982-09-12 00:00:00 +16212,371,204,0.0,27,0,1982-09-12 00:00:00 +16213,371,196,3.0,20,0,1982-09-12 00:00:00 +16214,371,194,0.0,31,0,1982-09-12 00:00:00 +16215,371,207,0.0,39,0,1982-09-12 00:00:00 +16216,371,206,4.0,19,0,1982-09-12 00:00:00 +16217,371,175,3.0,21,0,1982-09-12 00:00:00 +16218,371,135,0.0,37,0,1982-09-12 00:00:00 +16219,371,208,0.0,33,0,1982-09-12 00:00:00 +16220,371,174,25.0,7,1,1982-09-12 00:00:00 +16221,371,89,0.0,40,0,1982-09-12 00:00:00 +16222,371,209,0.0,36,0,1982-09-12 00:00:00 +16223,371,157,11.0,12,0,1982-09-12 00:00:00 +16224,371,169,0.0,34,0,1982-09-12 00:00:00 +16225,371,210,0.0,38,0,1982-09-12 00:00:00 +16226,371,118,21.0,9,1,1982-09-12 00:00:00 +16227,371,171,5.0,17,0,1982-09-12 00:00:00 +16228,371,117,0.0,32,0,1982-09-12 00:00:00 +16229,371,116,31.0,4,2,1982-09-12 00:00:00 +16230,371,198,6.0,16,0,1982-09-12 00:00:00 +16231,371,162,28.0,6,2,1982-09-12 00:00:00 +16232,371,181,30.0,5,2,1982-09-12 00:00:00 +16233,371,186,33.0,3,2,1982-09-12 00:00:00 +16234,371,104,16.0,11,0,1982-09-12 00:00:00 +16235,371,172,23.0,8,1,1982-09-12 00:00:00 +16236,371,193,2.0,23,0,1982-09-12 00:00:00 +16237,371,176,42.0,1,1,1982-09-12 00:00:00 +16238,371,151,2.0,22,0,1982-09-12 00:00:00 +16239,371,180,2.0,24,0,1982-09-12 00:00:00 +16240,371,191,1.0,26,0,1982-09-12 00:00:00 +16241,371,200,0.0,29,0,1982-09-12 00:00:00 +16242,371,195,0.0,30,0,1982-09-12 00:00:00 +16243,371,201,39.0,2,2,1982-09-12 00:00:00 +16244,371,109,5.0,18,0,1982-09-12 00:00:00 +16245,371,199,0.0,28,0,1982-09-12 00:00:00 +16246,371,205,7.0,14,0,1982-09-12 00:00:00 +16247,372,109,5.0,17,0,1982-09-25 00:00:00 +16248,372,117,0.0,32,0,1982-09-25 00:00:00 +16249,372,191,1.0,26,0,1982-09-25 00:00:00 +16250,372,200,0.0,29,0,1982-09-25 00:00:00 +16251,372,195,0.0,30,0,1982-09-25 00:00:00 +16252,372,205,8.0,13,0,1982-09-25 00:00:00 +16253,372,151,2.0,22,0,1982-09-25 00:00:00 +16254,372,199,0.0,28,0,1982-09-25 00:00:00 +16255,372,180,2.0,24,0,1982-09-25 00:00:00 +16256,372,136,20.0,11,1,1982-09-25 00:00:00 +16257,372,104,25.0,8,1,1982-09-25 00:00:00 +16258,372,172,23.0,9,1,1982-09-25 00:00:00 +16259,372,186,39.0,3,2,1982-09-25 00:00:00 +16260,372,176,44.0,1,1,1982-09-25 00:00:00 +16261,372,181,30.0,5,2,1982-09-25 00:00:00 +16262,372,116,34.0,4,2,1982-09-25 00:00:00 +16263,372,198,6.0,16,0,1982-09-25 00:00:00 +16264,372,162,28.0,6,2,1982-09-25 00:00:00 +16265,372,193,2.0,23,0,1982-09-25 00:00:00 +16266,372,202,6.0,15,0,1982-09-25 00:00:00 +16267,372,183,2.0,25,0,1982-09-25 00:00:00 +16268,372,118,21.0,10,1,1982-09-25 00:00:00 +16269,372,201,39.0,2,2,1982-09-25 00:00:00 +16270,372,171,5.0,18,0,1982-09-25 00:00:00 +16271,372,209,0.0,37,0,1982-09-25 00:00:00 +16272,372,135,0.0,38,0,1982-09-25 00:00:00 +16273,372,196,3.0,20,0,1982-09-25 00:00:00 +16274,372,210,0.0,33,0,1982-09-25 00:00:00 +16275,372,89,0.0,40,0,1982-09-25 00:00:00 +16276,372,174,25.0,7,1,1982-09-25 00:00:00 +16277,372,175,3.0,21,0,1982-09-25 00:00:00 +16278,372,207,0.0,39,0,1982-09-25 00:00:00 +16279,372,206,4.0,19,0,1982-09-25 00:00:00 +16280,372,169,0.0,35,0,1982-09-25 00:00:00 +16281,372,194,0.0,31,0,1982-09-25 00:00:00 +16282,372,204,0.0,27,0,1982-09-25 00:00:00 +16283,372,203,0.0,36,0,1982-09-25 00:00:00 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00:00:00 +16307,373,191,0.0,8,0,1983-03-13 00:00:00 +16308,373,162,0.0,9,0,1983-03-13 00:00:00 +16309,373,192,0.0,10,0,1983-03-13 00:00:00 +16310,373,94,0.0,11,0,1983-03-13 00:00:00 +16311,373,187,0.0,12,0,1983-03-13 00:00:00 +16312,373,117,0.0,7,0,1983-03-13 00:00:00 +16313,374,195,0.0,10,0,1983-03-27 00:00:00 +16314,374,183,0.0,26,0,1983-03-27 00:00:00 +16315,374,196,0.0,24,0,1983-03-27 00:00:00 +16316,374,118,0.0,15,0,1983-03-27 00:00:00 +16317,374,189,0.0,28,0,1983-03-27 00:00:00 +16318,374,109,0.0,21,0,1983-03-27 00:00:00 +16319,374,104,0.0,13,0,1983-03-27 00:00:00 +16320,374,159,0.0,29,0,1983-03-27 00:00:00 +16321,374,177,0.0,20,0,1983-03-27 00:00:00 +16322,374,172,0.0,23,0,1983-03-27 00:00:00 +16323,374,186,9.0,3,1,1983-03-27 00:00:00 +16324,374,151,0.0,25,0,1983-03-27 00:00:00 +16325,374,176,0.0,27,0,1983-03-27 00:00:00 +16326,374,157,0.0,17,0,1983-03-27 00:00:00 +16327,374,180,0.0,19,0,1983-03-27 00:00:00 +16328,374,194,0.0,22,0,1983-03-27 00:00:00 +16329,374,136,9.0,2,1,1983-03-27 00:00:00 +16330,374,181,10.0,1,0,1983-03-27 00:00:00 +16331,374,171,6.0,4,0,1983-03-27 00:00:00 +16332,374,175,3.0,6,0,1983-03-27 00:00:00 +16333,374,116,0.0,9,0,1983-03-27 00:00:00 +16334,374,174,2.0,7,0,1983-03-27 00:00:00 +16335,374,191,0.0,14,0,1983-03-27 00:00:00 +16336,374,162,4.0,5,0,1983-03-27 00:00:00 +16337,374,192,0.0,11,0,1983-03-27 00:00:00 +16338,374,94,0.0,16,0,1983-03-27 00:00:00 +16339,374,187,1.0,8,0,1983-03-27 00:00:00 +16340,374,193,0.0,18,0,1983-03-27 00:00:00 +16341,374,117,0.0,12,0,1983-03-27 00:00:00 +16342,375,172,0.0,27,0,1983-04-17 00:00:00 +16343,375,183,0.0,28,0,1983-04-17 00:00:00 +16344,375,157,4.0,8,0,1983-04-17 00:00:00 +16345,375,167,0.0,30,0,1983-04-17 00:00:00 +16346,375,176,2.0,10,0,1983-04-17 00:00:00 +16347,375,177,0.0,24,0,1983-04-17 00:00:00 +16348,375,196,0.0,16,0,1983-04-17 00:00:00 +16349,375,109,0.0,20,0,1983-04-17 00:00:00 +16350,375,104,0.0,13,0,1983-04-17 00:00:00 +16351,375,151,0.0,21,0,1983-04-17 00:00:00 +16352,375,189,0.0,25,0,1983-04-17 00:00:00 +16353,375,118,0.0,18,0,1983-04-17 00:00:00 +16354,375,159,0.0,29,0,1983-04-17 00:00:00 +16355,375,194,0.0,26,0,1983-04-17 00:00:00 +16356,375,186,9.0,4,1,1983-04-17 00:00:00 +16357,375,193,0.0,22,0,1983-04-17 00:00:00 +16358,375,187,1.0,11,0,1983-04-17 00:00:00 +16359,375,94,0.0,19,0,1983-04-17 00:00:00 +16360,375,192,0.0,14,0,1983-04-17 00:00:00 +16361,375,162,4.0,7,0,1983-04-17 00:00:00 +16362,375,191,0.0,17,0,1983-04-17 00:00:00 +16363,375,117,0.0,15,0,1983-04-17 00:00:00 +16364,375,180,0.0,23,0,1983-04-17 00:00:00 +16365,375,175,3.0,9,0,1983-04-17 00:00:00 +16366,375,195,0.0,12,0,1983-04-17 00:00:00 +16367,375,136,15.0,1,1,1983-04-17 00:00:00 +16368,375,116,9.0,3,1,1983-04-17 00:00:00 +16369,375,171,7.0,5,0,1983-04-17 00:00:00 +16370,375,181,10.0,2,0,1983-04-17 00:00:00 +16371,375,174,5.0,6,0,1983-04-17 00:00:00 +16372,376,167,0.0,30,0,1983-05-01 00:00:00 +16373,376,176,5.0,8,0,1983-05-01 00:00:00 +16374,376,172,0.0,26,0,1983-05-01 00:00:00 +16375,376,177,0.0,25,0,1983-05-01 00:00:00 +16376,376,159,0.0,29,0,1983-05-01 00:00:00 +16377,376,109,0.0,22,0,1983-05-01 00:00:00 +16378,376,104,0.0,14,0,1983-05-01 00:00:00 +16379,376,189,0.0,27,0,1983-05-01 00:00:00 +16380,376,118,0.0,18,0,1983-05-01 00:00:00 +16381,376,196,0.0,17,0,1983-05-01 00:00:00 +16382,376,183,0.0,19,0,1983-05-01 00:00:00 +16383,376,195,0.0,12,0,1983-05-01 00:00:00 +16384,376,186,11.0,4,1,1983-05-01 00:00:00 +16385,376,151,0.0,23,0,1983-05-01 00:00:00 +16386,376,194,0.0,28,0,1983-05-01 00:00:00 +16387,376,136,15.0,2,1,1983-05-01 00:00:00 +16388,376,157,4.0,9,0,1983-05-01 00:00:00 +16389,376,171,7.0,7,0,1983-05-01 00:00:00 +16390,376,174,14.0,3,1,1983-05-01 00:00:00 +16391,376,175,4.0,10,0,1983-05-01 00:00:00 +16392,376,116,15.0,1,1,1983-05-01 00:00:00 +16393,376,117,0.0,16,0,1983-05-01 00:00:00 +16394,376,181,10.0,5,0,1983-05-01 00:00:00 +16395,376,162,8.0,6,0,1983-05-01 00:00:00 +16396,376,192,0.0,15,0,1983-05-01 00:00:00 +16397,376,94,0.0,21,0,1983-05-01 00:00:00 +16398,376,187,1.0,11,0,1983-05-01 00:00:00 +16399,376,193,0.0,24,0,1983-05-01 00:00:00 +16400,376,191,0.0,13,0,1983-05-01 00:00:00 +16401,376,180,0.0,20,0,1983-05-01 00:00:00 +16402,377,183,1.0,12,0,1983-05-15 00:00:00 +16403,377,196,0.0,18,0,1983-05-15 00:00:00 +16404,377,118,0.0,19,0,1983-05-15 00:00:00 +16405,377,189,0.0,27,0,1983-05-15 00:00:00 +16406,377,151,0.0,23,0,1983-05-15 00:00:00 +16407,377,104,0.0,16,0,1983-05-15 00:00:00 +16408,377,159,0.0,29,0,1983-05-15 00:00:00 +16409,377,177,0.0,26,0,1983-05-15 00:00:00 +16410,377,172,0.0,25,0,1983-05-15 00:00:00 +16411,377,176,14.0,4,1,1983-05-15 00:00:00 +16412,377,167,0.0,30,0,1983-05-15 00:00:00 +16413,377,195,0.0,15,0,1983-05-15 00:00:00 +16414,377,109,0.0,22,0,1983-05-15 00:00:00 +16415,377,186,11.0,5,1,1983-05-15 00:00:00 +16416,377,191,0.0,14,0,1983-05-15 00:00:00 +16417,377,194,0.0,28,0,1983-05-15 00:00:00 +16418,377,157,4.0,9,0,1983-05-15 00:00:00 +16419,377,136,21.0,1,1,1983-05-15 00:00:00 +16420,377,181,10.0,6,0,1983-05-15 00:00:00 +16421,377,171,7.0,8,0,1983-05-15 00:00:00 +16422,377,174,17.0,3,1,1983-05-15 00:00:00 +16423,377,175,4.0,10,0,1983-05-15 00:00:00 +16424,377,116,19.0,2,1,1983-05-15 00:00:00 +16425,377,162,8.0,7,0,1983-05-15 00:00:00 +16426,377,192,2.0,11,0,1983-05-15 00:00:00 +16427,377,94,0.0,21,0,1983-05-15 00:00:00 +16428,377,187,1.0,13,0,1983-05-15 00:00:00 +16429,377,193,0.0,24,0,1983-05-15 00:00:00 +16430,377,180,0.0,20,0,1983-05-15 00:00:00 +16431,377,117,0.0,17,0,1983-05-15 00:00:00 +16432,378,195,0.0,16,0,1983-05-22 00:00:00 +16433,378,183,1.0,13,0,1983-05-22 00:00:00 +16434,378,196,0.0,20,0,1983-05-22 00:00:00 +16435,378,118,0.0,21,0,1983-05-22 00:00:00 +16436,378,189,0.0,27,0,1983-05-22 00:00:00 +16437,378,151,0.0,18,0,1983-05-22 00:00:00 +16438,378,177,0.0,26,0,1983-05-22 00:00:00 +16439,378,109,0.0,24,0,1983-05-22 00:00:00 +16440,378,159,0.0,30,0,1983-05-22 00:00:00 +16441,378,172,0.0,19,0,1983-05-22 00:00:00 +16442,378,176,16.0,4,1,1983-05-22 00:00:00 +16443,378,167,0.0,31,0,1983-05-22 00:00:00 +16444,378,104,0.0,17,0,1983-05-22 00:00:00 +16445,378,122,0.0,29,0,1983-05-22 00:00:00 +16446,378,157,8.0,8,0,1983-05-22 00:00:00 +16447,378,194,0.0,28,0,1983-05-22 00:00:00 +16448,378,186,11.0,5,1,1983-05-22 00:00:00 +16449,378,136,24.0,2,1,1983-05-22 00:00:00 +16450,378,181,10.0,6,0,1983-05-22 00:00:00 +16451,378,171,8.0,9,0,1983-05-22 00:00:00 +16452,378,174,23.0,3,1,1983-05-22 00:00:00 +16453,378,175,4.0,10,0,1983-05-22 00:00:00 +16454,378,116,28.0,1,2,1983-05-22 00:00:00 +16455,378,187,1.0,12,0,1983-05-22 00:00:00 +16456,378,191,0.0,14,0,1983-05-22 00:00:00 +16457,378,162,8.0,7,0,1983-05-22 00:00:00 +16458,378,192,2.0,11,0,1983-05-22 00:00:00 +16459,378,94,0.0,23,0,1983-05-22 00:00:00 +16460,378,117,0.0,15,0,1983-05-22 00:00:00 +16461,378,193,0.0,25,0,1983-05-22 00:00:00 +16462,378,180,0.0,22,0,1983-05-22 00:00:00 +16463,379,183,1.0,14,0,1983-06-05 00:00:00 +16464,379,196,0.0,22,0,1983-06-05 00:00:00 +16465,379,118,0.0,23,0,1983-06-05 00:00:00 +16466,379,189,0.0,29,0,1983-06-05 00:00:00 +16467,379,151,0.0,20,0,1983-06-05 00:00:00 +16468,379,159,0.0,30,0,1983-06-05 00:00:00 +16469,379,195,0.0,18,0,1983-06-05 00:00:00 +16470,379,177,0.0,28,0,1983-06-05 00:00:00 +16471,379,172,0.0,21,0,1983-06-05 00:00:00 +16472,379,176,22.0,4,1,1983-06-05 00:00:00 +16473,379,122,0.0,19,0,1983-06-05 00:00:00 +16474,379,104,9.0,8,1,1983-06-05 00:00:00 +16475,379,186,15.0,5,1,1983-06-05 00:00:00 +16476,379,167,0.0,31,0,1983-06-05 00:00:00 +16477,379,194,0.0,27,0,1983-06-05 00:00:00 +16478,379,157,8.0,10,0,1983-06-05 00:00:00 +16479,379,136,27.0,2,1,1983-06-05 00:00:00 +16480,379,181,10.0,6,0,1983-06-05 00:00:00 +16481,379,171,10.0,7,0,1983-06-05 00:00:00 +16482,379,174,23.0,3,1,1983-06-05 00:00:00 +16483,379,175,4.0,11,0,1983-06-05 00:00:00 +16484,379,116,28.0,1,2,1983-06-05 00:00:00 +16485,379,109,0.0,25,0,1983-06-05 00:00:00 +16486,379,191,0.0,16,0,1983-06-05 00:00:00 +16487,379,162,8.0,9,0,1983-06-05 00:00:00 +16488,379,192,2.0,12,0,1983-06-05 00:00:00 +16489,379,94,1.0,15,0,1983-06-05 00:00:00 +16490,379,187,1.0,13,0,1983-06-05 00:00:00 +16491,379,193,0.0,26,0,1983-06-05 00:00:00 +16492,379,117,0.0,17,0,1983-06-05 00:00:00 +16493,379,180,0.0,24,0,1983-06-05 00:00:00 +16494,380,196,0.0,23,0,1983-06-12 00:00:00 +16495,380,118,0.0,24,0,1983-06-12 00:00:00 +16496,380,189,0.0,29,0,1983-06-12 00:00:00 +16497,380,151,0.0,20,0,1983-06-12 00:00:00 +16498,380,104,9.0,10,1,1983-06-12 00:00:00 +16499,380,177,0.0,28,0,1983-06-12 00:00:00 +16500,380,159,0.0,30,0,1983-06-12 00:00:00 +16501,380,183,1.0,13,0,1983-06-12 00:00:00 +16502,380,172,0.0,22,0,1983-06-12 00:00:00 +16503,380,176,25.0,4,1,1983-06-12 00:00:00 +16504,380,167,0.0,32,0,1983-06-12 00:00:00 +16505,380,122,0.0,16,0,1983-06-12 00:00:00 +16506,380,197,0.0,31,0,1983-06-12 00:00:00 +16507,380,109,0.0,25,0,1983-06-12 00:00:00 +16508,380,195,0.0,19,0,1983-06-12 00:00:00 +16509,380,180,0.0,21,0,1983-06-12 00:00:00 +16510,380,157,14.0,7,0,1983-06-12 00:00:00 +16511,380,136,27.0,2,1,1983-06-12 00:00:00 +16512,380,181,10.0,8,0,1983-06-12 00:00:00 +16513,380,171,10.0,9,0,1983-06-12 00:00:00 +16514,380,174,27.0,3,1,1983-06-12 00:00:00 +16515,380,175,4.0,11,0,1983-06-12 00:00:00 +16516,380,186,16.0,6,1,1983-06-12 00:00:00 +16517,380,116,30.0,1,2,1983-06-12 00:00:00 +16518,380,191,0.0,17,0,1983-06-12 00:00:00 +16519,380,192,2.0,12,0,1983-06-12 00:00:00 +16520,380,94,1.0,15,0,1983-06-12 00:00:00 +16521,380,187,1.0,14,0,1983-06-12 00:00:00 +16522,380,193,0.0,26,0,1983-06-12 00:00:00 +16523,380,194,0.0,27,0,1983-06-12 00:00:00 +16524,380,117,0.0,18,0,1983-06-12 00:00:00 +16525,380,162,17.0,5,1,1983-06-12 00:00:00 +16526,381,136,33.0,2,1,1983-07-16 00:00:00 +16527,381,181,11.0,8,0,1983-07-16 00:00:00 +16528,381,174,31.0,3,1,1983-07-16 00:00:00 +16529,381,171,10.0,9,0,1983-07-16 00:00:00 +16530,381,185,0.0,33,0,1983-07-16 00:00:00 +16531,381,139,0.0,31,0,1983-07-16 00:00:00 +16532,381,197,0.0,32,0,1983-07-16 00:00:00 +16533,381,122,0.0,16,0,1983-07-16 00:00:00 +16534,381,167,0.0,34,0,1983-07-16 00:00:00 +16535,381,176,25.0,4,1,1983-07-16 00:00:00 +16536,381,172,0.0,24,0,1983-07-16 00:00:00 +16537,381,159,0.0,30,0,1983-07-16 00:00:00 +16538,381,109,0.0,21,0,1983-07-16 00:00:00 +16539,381,104,9.0,10,1,1983-07-16 00:00:00 +16540,381,151,0.0,20,0,1983-07-16 00:00:00 +16541,381,189,0.0,29,0,1983-07-16 00:00:00 +16542,381,118,0.0,25,0,1983-07-16 00:00:00 +16543,381,196,0.0,22,0,1983-07-16 00:00:00 +16544,381,177,0.0,28,0,1983-07-16 00:00:00 +16545,381,195,0.0,19,0,1983-07-16 00:00:00 +16546,381,183,1.0,14,0,1983-07-16 00:00:00 +16547,381,175,4.0,12,0,1983-07-16 00:00:00 +16548,381,116,39.0,1,3,1983-07-16 00:00:00 +16549,381,117,0.0,18,0,1983-07-16 00:00:00 +16550,381,191,0.0,17,0,1983-07-16 00:00:00 +16551,381,192,2.0,13,0,1983-07-16 00:00:00 +16552,381,94,4.0,11,0,1983-07-16 00:00:00 +16553,381,162,19.0,5,1,1983-07-16 00:00:00 +16554,381,193,0.0,26,0,1983-07-16 00:00:00 +16555,381,180,0.0,23,0,1983-07-16 00:00:00 +16556,381,194,0.0,27,0,1983-07-16 00:00:00 +16557,381,157,14.0,7,0,1983-07-16 00:00:00 +16558,381,186,16.0,6,1,1983-07-16 00:00:00 +16559,381,187,1.0,15,0,1983-07-16 00:00:00 +16560,382,118,4.0,12,0,1983-08-07 00:00:00 +16561,382,159,0.0,30,0,1983-08-07 00:00:00 +16562,382,189,0.0,29,0,1983-08-07 00:00:00 +16563,382,151,0.0,23,0,1983-08-07 00:00:00 +16564,382,104,9.0,10,1,1983-08-07 00:00:00 +16565,382,109,6.0,11,0,1983-08-07 00:00:00 +16566,382,177,0.0,28,0,1983-08-07 00:00:00 +16567,382,185,0.0,32,0,1983-08-07 00:00:00 +16568,382,176,25.0,5,1,1983-08-07 00:00:00 +16569,382,167,0.0,34,0,1983-08-07 00:00:00 +16570,382,122,0.0,18,0,1983-08-07 00:00:00 +16571,382,197,0.0,33,0,1983-08-07 00:00:00 +16572,382,139,0.0,31,0,1983-08-07 00:00:00 +16573,382,196,0.0,22,0,1983-08-07 00:00:00 +16574,382,172,0.0,25,0,1983-08-07 00:00:00 +16575,382,183,1.0,16,0,1983-08-07 00:00:00 +16576,382,193,0.0,26,0,1983-08-07 00:00:00 +16577,382,186,18.0,6,1,1983-08-07 00:00:00 +16578,382,136,33.0,2,1,1983-08-07 00:00:00 +16579,382,181,11.0,8,0,1983-08-07 00:00:00 +16580,382,171,11.0,9,0,1983-08-07 00:00:00 +16581,382,174,31.0,3,1,1983-08-07 00:00:00 +16582,382,175,4.0,14,0,1983-08-07 00:00:00 +16583,382,116,42.0,1,3,1983-08-07 00:00:00 +16584,382,117,0.0,20,0,1983-08-07 00:00:00 +16585,382,195,0.0,21,0,1983-08-07 00:00:00 +16586,382,162,28.0,4,2,1983-08-07 00:00:00 +16587,382,192,2.0,15,0,1983-08-07 00:00:00 +16588,382,94,4.0,13,0,1983-08-07 00:00:00 +16589,382,187,1.0,17,0,1983-08-07 00:00:00 +16590,382,180,0.0,24,0,1983-08-07 00:00:00 +16591,382,194,0.0,27,0,1983-08-07 00:00:00 +16592,382,157,14.0,7,0,1983-08-07 00:00:00 +16593,382,191,0.0,19,0,1983-08-07 00:00:00 +16594,383,118,4.0,13,0,1983-08-14 00:00:00 +16595,383,189,0.0,26,0,1983-08-14 00:00:00 +16596,383,151,0.0,23,0,1983-08-14 00:00:00 +16597,383,104,9.0,10,1,1983-08-14 00:00:00 +16598,383,109,6.0,11,0,1983-08-14 00:00:00 +16599,383,159,0.0,27,0,1983-08-14 00:00:00 +16600,383,167,0.0,34,0,1983-08-14 00:00:00 +16601,383,172,0.0,25,0,1983-08-14 00:00:00 +16602,383,176,25.0,5,1,1983-08-14 00:00:00 +16603,383,122,0.0,18,0,1983-08-14 00:00:00 +16604,383,197,0.0,33,0,1983-08-14 00:00:00 +16605,383,139,0.0,28,0,1983-08-14 00:00:00 +16606,383,185,0.0,32,0,1983-08-14 00:00:00 +16607,383,177,0.0,31,0,1983-08-14 00:00:00 +16608,383,183,1.0,16,0,1983-08-14 00:00:00 +16609,383,196,0.0,19,0,1983-08-14 00:00:00 +16610,383,186,18.0,6,1,1983-08-14 00:00:00 +16611,383,136,37.0,2,1,1983-08-14 00:00:00 +16612,383,181,12.0,8,0,1983-08-14 00:00:00 +16613,383,171,11.0,9,0,1983-08-14 00:00:00 +16614,383,174,31.0,4,1,1983-08-14 00:00:00 +16615,383,175,4.0,14,0,1983-08-14 00:00:00 +16616,383,117,0.0,21,0,1983-08-14 00:00:00 +16617,383,191,0.0,20,0,1983-08-14 00:00:00 +16618,383,116,51.0,1,4,1983-08-14 00:00:00 +16619,383,192,2.0,15,0,1983-08-14 00:00:00 +16620,383,94,6.0,12,0,1983-08-14 00:00:00 +16621,383,187,1.0,17,0,1983-08-14 00:00:00 +16622,383,193,0.0,29,0,1983-08-14 00:00:00 +16623,383,180,0.0,24,0,1983-08-14 00:00:00 +16624,383,194,0.0,30,0,1983-08-14 00:00:00 +16625,383,157,17.0,7,0,1983-08-14 00:00:00 +16626,383,162,34.0,3,2,1983-08-14 00:00:00 +16627,383,195,0.0,22,0,1983-08-14 00:00:00 +16628,384,159,0.0,28,0,1983-08-28 00:00:00 +16629,384,118,4.0,13,0,1983-08-28 00:00:00 +16630,384,189,0.0,27,0,1983-08-28 00:00:00 +16631,384,151,0.0,24,0,1983-08-28 00:00:00 +16632,384,104,10.0,10,1,1983-08-28 00:00:00 +16633,384,109,6.0,11,0,1983-08-28 00:00:00 +16634,384,185,0.0,32,0,1983-08-28 00:00:00 +16635,384,176,25.0,5,1,1983-08-28 00:00:00 +16636,384,167,0.0,34,0,1983-08-28 00:00:00 +16637,384,122,0.0,19,0,1983-08-28 00:00:00 +16638,384,197,0.0,33,0,1983-08-28 00:00:00 +16639,384,139,0.0,23,0,1983-08-28 00:00:00 +16640,384,196,0.0,20,0,1983-08-28 00:00:00 +16641,384,172,0.0,26,0,1983-08-28 00:00:00 +16642,384,183,3.0,16,0,1983-08-28 00:00:00 +16643,384,177,0.0,31,0,1983-08-28 00:00:00 +16644,384,186,22.0,6,1,1983-08-28 00:00:00 +16645,384,195,0.0,22,0,1983-08-28 00:00:00 +16646,384,136,37.0,3,1,1983-08-28 00:00:00 +16647,384,181,12.0,8,0,1983-08-28 00:00:00 +16648,384,171,11.0,9,0,1983-08-28 00:00:00 +16649,384,174,37.0,4,1,1983-08-28 00:00:00 +16650,384,175,4.0,14,0,1983-08-28 00:00:00 +16651,384,116,51.0,1,4,1983-08-28 00:00:00 +16652,384,117,3.0,15,0,1983-08-28 00:00:00 +16653,384,94,6.0,12,0,1983-08-28 00:00:00 +16654,384,162,43.0,2,3,1983-08-28 00:00:00 +16655,384,192,2.0,17,0,1983-08-28 00:00:00 +16656,384,187,1.0,18,0,1983-08-28 00:00:00 +16657,384,193,0.0,30,0,1983-08-28 00:00:00 +16658,384,180,0.0,25,0,1983-08-28 00:00:00 +16659,384,194,0.0,29,0,1983-08-28 00:00:00 +16660,384,191,0.0,21,0,1983-08-28 00:00:00 +16661,384,157,17.0,7,0,1983-08-28 00:00:00 +16662,385,118,4.0,13,0,1983-09-11 00:00:00 +16663,385,189,0.0,27,0,1983-09-11 00:00:00 +16664,385,151,0.0,22,0,1983-09-11 00:00:00 +16665,385,104,10.0,10,1,1983-09-11 00:00:00 +16666,385,109,6.0,11,0,1983-09-11 00:00:00 +16667,385,159,0.0,28,0,1983-09-11 00:00:00 +16668,385,176,25.0,5,1,1983-09-11 00:00:00 +16669,385,172,2.0,18,0,1983-09-11 00:00:00 +16670,385,196,0.0,21,0,1983-09-11 00:00:00 +16671,385,167,0.0,34,0,1983-09-11 00:00:00 +16672,385,122,0.0,20,0,1983-09-11 00:00:00 +16673,385,197,0.0,33,0,1983-09-11 00:00:00 +16674,385,139,0.0,25,0,1983-09-11 00:00:00 +16675,385,185,0.0,32,0,1983-09-11 00:00:00 +16676,385,177,0.0,31,0,1983-09-11 00:00:00 +16677,385,183,3.0,16,0,1983-09-11 00:00:00 +16678,385,194,0.0,29,0,1983-09-11 00:00:00 +16679,385,186,22.0,6,1,1983-09-11 00:00:00 +16680,385,136,46.0,3,2,1983-09-11 00:00:00 +16681,385,181,12.0,8,0,1983-09-11 00:00:00 +16682,385,171,11.0,9,0,1983-09-11 00:00:00 +16683,385,174,40.0,4,1,1983-09-11 00:00:00 +16684,385,175,4.0,15,0,1983-09-11 00:00:00 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00:00:00 +18237,437,118,0.0,13,0,1987-05-03 00:00:00 +18238,437,136,6.0,5,0,1987-05-03 00:00:00 +18239,437,157,0.0,19,0,1987-05-03 00:00:00 +18240,437,101,6.0,4,0,1987-05-03 00:00:00 +18241,437,139,7.0,3,0,1987-05-03 00:00:00 +18242,437,76,3.0,7,0,1987-05-03 00:00:00 +18243,437,122,2.0,8,0,1987-05-03 00:00:00 +18244,437,94,10.0,1,1,1987-05-03 00:00:00 +18245,437,116,9.0,2,1,1987-05-03 00:00:00 +18246,437,104,4.0,6,0,1987-05-03 00:00:00 +18247,437,156,0.0,11,0,1987-05-03 00:00:00 +18248,437,155,0.0,14,0,1987-05-03 00:00:00 +18249,437,165,0.0,12,0,1987-05-03 00:00:00 +18250,437,168,0.0,17,0,1987-05-03 00:00:00 +18251,437,137,1.0,10,0,1987-05-03 00:00:00 +18252,438,117,0.0,21,0,1987-05-17 00:00:00 +18253,438,132,0.0,22,0,1987-05-17 00:00:00 +18254,438,144,0.0,25,0,1987-05-17 00:00:00 +18255,438,83,2.0,11,0,1987-05-17 00:00:00 +18256,438,169,0.0,23,0,1987-05-17 00:00:00 +18257,438,166,0.0,26,0,1987-05-17 00:00:00 +18258,438,111,0.0,17,0,1987-05-17 00:00:00 +18259,438,98,0.0,27,0,1987-05-17 00:00:00 +18260,438,159,0.0,15,0,1987-05-17 00:00:00 +18261,438,162,1.0,13,0,1987-05-17 00:00:00 +18262,438,109,4.0,7,0,1987-05-17 00:00:00 +18263,438,121,0.0,24,0,1987-05-17 00:00:00 +18264,438,118,0.0,18,0,1987-05-17 00:00:00 +18265,438,155,0.0,20,0,1987-05-17 00:00:00 +18266,438,157,3.0,8,0,1987-05-17 00:00:00 +18267,438,136,6.0,5,0,1987-05-17 00:00:00 +18268,438,139,13.0,2,0,1987-05-17 00:00:00 +18269,438,76,3.0,9,0,1987-05-17 00:00:00 +18270,438,122,2.0,12,0,1987-05-17 00:00:00 +18271,438,94,10.0,3,1,1987-05-17 00:00:00 +18272,438,101,6.0,4,0,1987-05-17 00:00:00 +18273,438,104,4.0,6,0,1987-05-17 00:00:00 +18274,438,156,0.0,14,0,1987-05-17 00:00:00 +18275,438,116,18.0,1,2,1987-05-17 00:00:00 +18276,438,165,0.0,16,0,1987-05-17 00:00:00 +18277,438,168,0.0,19,0,1987-05-17 00:00:00 +18278,438,137,3.0,10,0,1987-05-17 00:00:00 +18279,439,132,0.0,24,0,1987-05-31 00:00:00 +18280,439,144,0.0,25,0,1987-05-31 00:00:00 +18281,439,83,2.0,11,0,1987-05-31 00:00:00 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00:00:00 +18305,439,104,8.0,6,0,1987-05-31 00:00:00 +18306,440,83,2.0,11,0,1987-06-21 00:00:00 +18307,440,117,0.0,23,0,1987-06-21 00:00:00 +18308,440,132,0.0,24,0,1987-06-21 00:00:00 +18309,440,144,0.0,25,0,1987-06-21 00:00:00 +18310,440,169,0.0,20,0,1987-06-21 00:00:00 +18311,440,109,4.0,8,0,1987-06-21 00:00:00 +18312,440,111,0.0,19,0,1987-06-21 00:00:00 +18313,440,166,0.0,26,0,1987-06-21 00:00:00 +18314,440,98,0.0,27,0,1987-06-21 00:00:00 +18315,440,159,0.0,17,0,1987-06-21 00:00:00 +18316,440,162,1.0,14,0,1987-06-21 00:00:00 +18317,440,121,1.0,15,0,1987-06-21 00:00:00 +18318,440,118,0.0,21,0,1987-06-21 00:00:00 +18319,440,116,22.0,2,2,1987-06-21 00:00:00 +18320,440,157,4.0,9,0,1987-06-21 00:00:00 +18321,440,101,24.0,1,2,1987-06-21 00:00:00 +18322,440,136,18.0,3,0,1987-06-21 00:00:00 +18323,440,139,13.0,4,0,1987-06-21 00:00:00 +18324,440,76,9.0,6,0,1987-06-21 00:00:00 +18325,440,94,12.0,5,1,1987-06-21 00:00:00 +18326,440,122,2.0,13,0,1987-06-21 00:00:00 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00:00:00 +18350,441,139,13.0,5,0,1987-07-05 00:00:00 +18351,441,122,2.0,14,0,1987-07-05 00:00:00 +18352,441,94,21.0,4,2,1987-07-05 00:00:00 +18353,441,76,9.0,6,0,1987-07-05 00:00:00 +18354,441,156,0.0,18,0,1987-07-05 00:00:00 +18355,441,155,2.0,11,0,1987-07-05 00:00:00 +18356,441,165,1.0,15,0,1987-07-05 00:00:00 +18357,441,168,0.0,22,0,1987-07-05 00:00:00 +18358,441,137,3.0,10,0,1987-07-05 00:00:00 +18359,441,101,27.0,1,2,1987-07-05 00:00:00 +18360,442,83,2.0,13,0,1987-07-12 00:00:00 +18361,442,117,2.0,15,0,1987-07-12 00:00:00 +18362,442,132,0.0,24,0,1987-07-12 00:00:00 +18363,442,144,0.0,26,0,1987-07-12 00:00:00 +18364,442,162,1.0,17,0,1987-07-12 00:00:00 +18365,442,111,0.0,21,0,1987-07-12 00:00:00 +18366,442,166,0.0,25,0,1987-07-12 00:00:00 +18367,442,98,0.0,27,0,1987-07-12 00:00:00 +18368,442,159,0.0,20,0,1987-07-12 00:00:00 +18369,442,109,4.0,9,0,1987-07-12 00:00:00 +18370,442,121,1.0,18,0,1987-07-12 00:00:00 +18371,442,118,0.0,23,0,1987-07-12 00:00:00 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00:00:00 +18395,443,98,0.0,27,0,1987-07-26 00:00:00 +18396,443,118,0.0,23,0,1987-07-26 00:00:00 +18397,443,83,2.0,14,0,1987-07-26 00:00:00 +18398,443,101,35.0,2,2,1987-07-26 00:00:00 +18399,443,137,6.0,8,0,1987-07-26 00:00:00 +18400,443,168,0.0,22,0,1987-07-26 00:00:00 +18401,443,165,4.0,10,0,1987-07-26 00:00:00 +18402,443,155,4.0,12,0,1987-07-26 00:00:00 +18403,443,156,0.0,20,0,1987-07-26 00:00:00 +18404,443,104,8.0,7,0,1987-07-26 00:00:00 +18405,443,94,30.0,3,3,1987-07-26 00:00:00 +18406,443,122,2.0,15,0,1987-07-26 00:00:00 +18407,443,76,9.0,6,0,1987-07-26 00:00:00 +18408,443,139,19.0,5,0,1987-07-26 00:00:00 +18409,443,136,39.0,1,1,1987-07-26 00:00:00 +18410,443,116,26.0,4,2,1987-07-26 00:00:00 +18411,443,157,4.0,11,0,1987-07-26 00:00:00 +18412,443,162,1.0,18,0,1987-07-26 00:00:00 +18413,443,166,0.0,25,0,1987-07-26 00:00:00 +18414,444,169,3.0,14,0,1987-08-09 00:00:00 +18415,444,121,1.0,20,0,1987-08-09 00:00:00 +18416,444,162,1.0,19,0,1987-08-09 00:00:00 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00:00:00 +18440,444,101,41.0,2,2,1987-08-09 00:00:00 +18441,445,109,4.0,11,0,1987-08-16 00:00:00 +18442,445,117,3.0,15,0,1987-08-16 00:00:00 +18443,445,132,0.0,25,0,1987-08-16 00:00:00 +18444,445,144,0.0,24,0,1987-08-16 00:00:00 +18445,445,83,2.0,16,0,1987-08-16 00:00:00 +18446,445,166,0.0,26,0,1987-08-16 00:00:00 +18447,445,121,1.0,20,0,1987-08-16 00:00:00 +18448,445,98,0.0,27,0,1987-08-16 00:00:00 +18449,445,159,0.0,22,0,1987-08-16 00:00:00 +18450,445,162,1.0,19,0,1987-08-16 00:00:00 +18451,445,169,7.0,9,0,1987-08-16 00:00:00 +18452,445,118,2.0,17,0,1987-08-16 00:00:00 +18453,445,111,1.0,18,0,1987-08-16 00:00:00 +18454,445,157,4.0,13,0,1987-08-16 00:00:00 +18455,445,136,54.0,1,2,1987-08-16 00:00:00 +18456,445,139,19.0,5,0,1987-08-16 00:00:00 +18457,445,76,9.0,6,0,1987-08-16 00:00:00 +18458,445,122,8.0,8,0,1987-08-16 00:00:00 +18459,445,116,31.0,4,2,1987-08-16 00:00:00 +18460,445,94,39.0,3,4,1987-08-16 00:00:00 +18461,445,101,43.0,2,2,1987-08-16 00:00:00 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00:00:00 +18485,446,136,63.0,1,3,1987-09-06 00:00:00 +18486,446,139,20.0,5,0,1987-09-06 00:00:00 +18487,446,122,10.0,7,0,1987-09-06 00:00:00 +18488,446,94,43.0,3,4,1987-09-06 00:00:00 +18489,446,76,12.0,6,0,1987-09-06 00:00:00 +18490,446,104,8.0,8,0,1987-09-06 00:00:00 +18491,446,156,0.0,22,0,1987-09-06 00:00:00 +18492,446,155,4.0,14,0,1987-09-06 00:00:00 +18493,446,165,4.0,12,0,1987-09-06 00:00:00 +18494,446,168,0.0,23,0,1987-09-06 00:00:00 +18495,446,157,4.0,13,0,1987-09-06 00:00:00 +18496,446,137,6.0,10,0,1987-09-06 00:00:00 +18497,447,121,1.0,19,0,1987-09-20 00:00:00 +18498,447,132,0.0,25,0,1987-09-20 00:00:00 +18499,447,144,0.0,24,0,1987-09-20 00:00:00 +18500,447,83,2.0,16,0,1987-09-20 00:00:00 +18501,447,169,10.0,7,0,1987-09-20 00:00:00 +18502,447,111,1.0,18,0,1987-09-20 00:00:00 +18503,447,117,3.0,15,0,1987-09-20 00:00:00 +18504,447,98,0.0,28,0,1987-09-20 00:00:00 +18505,447,159,0.0,21,0,1987-09-20 00:00:00 +18506,447,162,1.0,20,0,1987-09-20 00:00:00 +18507,447,170,0.0,27,0,1987-09-20 00:00:00 +18508,447,77,0.0,29,0,1987-09-20 00:00:00 +18509,447,166,0.0,26,0,1987-09-20 00:00:00 +18510,447,109,4.0,12,0,1987-09-20 00:00:00 +18511,447,165,4.0,13,0,1987-09-20 00:00:00 +18512,447,101,49.0,2,2,1987-09-20 00:00:00 +18513,447,136,67.0,1,3,1987-09-20 00:00:00 +18514,447,139,22.0,5,0,1987-09-20 00:00:00 +18515,447,76,18.0,6,0,1987-09-20 00:00:00 +18516,447,122,10.0,8,0,1987-09-20 00:00:00 +18517,447,94,43.0,3,4,1987-09-20 00:00:00 +18518,447,137,6.0,10,0,1987-09-20 00:00:00 +18519,447,118,2.0,17,0,1987-09-20 00:00:00 +18520,447,156,0.0,22,0,1987-09-20 00:00:00 +18521,447,155,4.0,14,0,1987-09-20 00:00:00 +18522,447,116,40.0,4,3,1987-09-20 00:00:00 +18523,447,168,0.0,23,0,1987-09-20 00:00:00 +18524,447,157,5.0,11,0,1987-09-20 00:00:00 +18525,447,104,8.0,9,0,1987-09-20 00:00:00 +18526,448,144,0.0,24,0,1987-09-27 00:00:00 +18527,448,83,2.0,16,0,1987-09-27 00:00:00 +18528,448,169,10.0,7,0,1987-09-27 00:00:00 +18529,448,121,1.0,19,0,1987-09-27 00:00:00 +18530,448,111,2.0,18,0,1987-09-27 00:00:00 +18531,448,159,0.0,21,0,1987-09-27 00:00:00 +18532,448,98,0.0,28,0,1987-09-27 00:00:00 +18533,448,162,1.0,20,0,1987-09-27 00:00:00 +18534,448,170,0.0,27,0,1987-09-27 00:00:00 +18535,448,77,0.0,29,0,1987-09-27 00:00:00 +18536,448,132,0.0,25,0,1987-09-27 00:00:00 +18537,448,166,0.0,26,0,1987-09-27 00:00:00 +18538,448,117,3.0,15,0,1987-09-27 00:00:00 +18539,448,109,4.0,12,0,1987-09-27 00:00:00 +18540,448,122,10.0,8,0,1987-09-27 00:00:00 +18541,448,118,2.0,17,0,1987-09-27 00:00:00 +18542,448,136,70.0,1,3,1987-09-27 00:00:00 +18543,448,139,26.0,5,0,1987-09-27 00:00:00 +18544,448,76,18.0,6,0,1987-09-27 00:00:00 +18545,448,94,52.0,2,5,1987-09-27 00:00:00 +18546,448,116,46.0,4,3,1987-09-27 00:00:00 +18547,448,137,6.0,10,0,1987-09-27 00:00:00 +18548,448,156,0.0,22,0,1987-09-27 00:00:00 +18549,448,155,4.0,14,0,1987-09-27 00:00:00 +18550,448,165,4.0,13,0,1987-09-27 00:00:00 +18551,448,168,0.0,23,0,1987-09-27 00:00:00 +18552,448,157,5.0,11,0,1987-09-27 00:00:00 +18553,448,101,51.0,3,2,1987-09-27 00:00:00 +18554,448,104,8.0,9,0,1987-09-27 00:00:00 +18555,449,169,12.0,7,0,1987-10-18 00:00:00 +18556,449,83,2.0,18,0,1987-10-18 00:00:00 +18557,449,132,0.0,26,0,1987-10-18 00:00:00 +18558,449,121,1.0,19,0,1987-10-18 00:00:00 +18559,449,144,0.0,25,0,1987-10-18 00:00:00 +18560,449,111,3.0,17,0,1987-10-18 00:00:00 +18561,449,113,0.0,24,0,1987-10-18 00:00:00 +18562,449,98,0.0,29,0,1987-10-18 00:00:00 +18563,449,159,0.0,21,0,1987-10-18 00:00:00 +18564,449,162,1.0,20,0,1987-10-18 00:00:00 +18565,449,170,0.0,28,0,1987-10-18 00:00:00 +18566,449,77,0.0,30,0,1987-10-18 00:00:00 +18567,449,166,0.0,27,0,1987-10-18 00:00:00 +18568,449,117,3.0,16,0,1987-10-18 00:00:00 +18569,449,136,73.0,1,3,1987-10-18 00:00:00 +18570,449,118,6.0,11,0,1987-10-18 00:00:00 +18571,449,109,4.0,13,0,1987-10-18 00:00:00 +18572,449,116,46.0,4,3,1987-10-18 00:00:00 +18573,449,139,26.0,5,0,1987-10-18 00:00:00 +18574,449,76,18.0,6,0,1987-10-18 00:00:00 +18575,449,94,61.0,2,6,1987-10-18 00:00:00 +18576,449,137,6.0,12,0,1987-10-18 00:00:00 +18577,449,122,10.0,8,0,1987-10-18 00:00:00 +18578,449,156,0.0,22,0,1987-10-18 00:00:00 +18579,449,155,4.0,15,0,1987-10-18 00:00:00 +18580,449,165,4.0,14,0,1987-10-18 00:00:00 +18581,449,168,0.0,23,0,1987-10-18 00:00:00 +18582,449,157,8.0,10,0,1987-10-18 00:00:00 +18583,449,101,51.0,3,2,1987-10-18 00:00:00 +18584,449,104,8.0,9,0,1987-10-18 00:00:00 +18585,450,111,3.0,17,0,1987-11-01 00:00:00 +18586,450,144,0.0,25,0,1987-11-01 00:00:00 +18587,450,83,2.0,18,0,1987-11-01 00:00:00 +18588,450,169,12.0,7,0,1987-11-01 00:00:00 +18589,450,121,1.0,19,0,1987-11-01 00:00:00 +18590,450,166,0.0,27,0,1987-11-01 00:00:00 +18591,450,89,0.0,29,0,1987-11-01 00:00:00 +18592,450,98,0.0,30,0,1987-11-01 00:00:00 +18593,450,159,0.0,21,0,1987-11-01 00:00:00 +18594,450,162,1.0,20,0,1987-11-01 00:00:00 +18595,450,170,0.0,28,0,1987-11-01 00:00:00 +18596,450,77,0.0,31,0,1987-11-01 00:00:00 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00:00:00 +18620,451,111,3.0,17,0,1987-11-15 00:00:00 +18621,451,166,0.0,28,0,1987-11-15 00:00:00 +18622,451,170,0.0,29,0,1987-11-15 00:00:00 +18623,451,159,0.0,24,0,1987-11-15 00:00:00 +18624,451,162,1.0,20,0,1987-11-15 00:00:00 +18625,451,77,0.0,32,0,1987-11-15 00:00:00 +18626,451,113,0.0,22,0,1987-11-15 00:00:00 +18627,451,89,1.0,21,0,1987-11-15 00:00:00 +18628,451,132,0.0,27,0,1987-11-15 00:00:00 +18629,451,98,0.0,31,0,1987-11-15 00:00:00 +18630,451,117,3.0,16,0,1987-11-15 00:00:00 +18631,451,130,0.0,30,0,1987-11-15 00:00:00 +18632,451,118,6.0,13,0,1987-11-15 00:00:00 +18633,451,136,73.0,1,3,1987-11-15 00:00:00 +18634,451,139,30.0,6,0,1987-11-15 00:00:00 +18635,451,76,36.0,5,2,1987-11-15 00:00:00 +18636,451,122,16.0,8,0,1987-11-15 00:00:00 +18637,451,94,61.0,2,6,1987-11-15 00:00:00 +18638,451,137,7.0,12,0,1987-11-15 00:00:00 +18639,451,116,46.0,4,3,1987-11-15 00:00:00 +18640,451,156,0.0,23,0,1987-11-15 00:00:00 +18641,451,104,17.0,7,0,1987-11-15 00:00:00 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00:00:00 +18665,452,116,9.0,1,1,1988-04-03 00:00:00 +18666,452,76,6.0,2,0,1988-04-03 00:00:00 +18667,452,136,4.0,3,0,1988-04-03 00:00:00 +18668,452,104,2.0,5,0,1988-04-03 00:00:00 +18669,452,137,1.0,6,0,1988-04-03 00:00:00 +18670,452,117,3.0,4,0,1988-04-03 00:00:00 +18671,452,157,0.0,8,0,1988-04-03 00:00:00 +18672,452,139,0.0,9,0,1988-04-03 00:00:00 +18673,452,109,0.0,10,0,1988-04-03 00:00:00 +18674,452,155,0.0,11,0,1988-04-03 00:00:00 +18675,452,158,0.0,12,0,1988-04-03 00:00:00 +18676,452,111,0.0,13,0,1988-04-03 00:00:00 +18677,452,122,0.0,7,0,1988-04-03 00:00:00 +18678,453,166,0.0,18,0,1988-05-01 00:00:00 +18679,453,94,0.0,24,0,1988-05-01 00:00:00 +18680,453,144,1.0,9,0,1988-05-01 00:00:00 +18681,453,118,0.0,15,0,1988-05-01 00:00:00 +18682,453,121,0.0,26,0,1988-05-01 00:00:00 +18683,453,130,0.0,23,0,1988-05-01 00:00:00 +18684,453,101,9.0,2,1,1988-05-01 00:00:00 +18685,453,164,0.0,29,0,1988-05-01 00:00:00 +18686,453,140,0.0,25,0,1988-05-01 00:00:00 +18687,453,159,0.0,28,0,1988-05-01 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00:00:00 +19183,468,130,0.0,21,0,1989-03-26 00:00:00 +19184,468,132,0.0,30,0,1989-03-26 00:00:00 +19185,468,136,0.0,20,0,1989-03-26 00:00:00 +19186,468,94,9.0,1,1,1989-03-26 00:00:00 +19187,468,83,0.0,18,0,1989-03-26 00:00:00 +19188,468,121,0.0,19,0,1989-03-26 00:00:00 +19189,468,116,6.0,2,0,1989-03-26 00:00:00 +19190,468,126,4.0,3,0,1989-03-26 00:00:00 +19191,468,64,3.0,4,0,1989-03-26 00:00:00 +19192,468,117,2.0,5,0,1989-03-26 00:00:00 +19193,468,155,0.0,7,0,1989-03-26 00:00:00 +19194,468,137,0.0,8,0,1989-03-26 00:00:00 +19195,468,128,0.0,9,0,1989-03-26 00:00:00 +19196,468,144,1.0,6,0,1989-03-26 00:00:00 +19197,468,101,0.0,11,0,1989-03-26 00:00:00 +19198,468,111,0.0,12,0,1989-03-26 00:00:00 +19199,468,109,0.0,13,0,1989-03-26 00:00:00 +19200,468,156,0.0,14,0,1989-03-26 00:00:00 +19201,468,118,0.0,15,0,1989-03-26 00:00:00 +19202,468,157,0.0,16,0,1989-03-26 00:00:00 +19203,468,145,0.0,17,0,1989-03-26 00:00:00 +19204,468,104,0.0,10,0,1989-03-26 00:00:00 +19205,469,89,0.0,32,0,1989-04-23 00:00:00 +19206,469,93,0.0,27,0,1989-04-23 00:00:00 +19207,469,76,0.0,28,0,1989-04-23 00:00:00 +19208,469,158,0.0,22,0,1989-04-23 00:00:00 +19209,469,113,0.0,29,0,1989-04-23 00:00:00 +19210,469,162,0.0,30,0,1989-04-23 00:00:00 +19211,469,147,0.0,31,0,1989-04-23 00:00:00 +19212,469,132,0.0,10,0,1989-04-23 00:00:00 +19213,469,77,0.0,18,0,1989-04-23 00:00:00 +19214,469,160,0.0,35,0,1989-04-23 00:00:00 +19215,469,161,0.0,36,0,1989-04-23 00:00:00 +19216,469,163,0.0,38,0,1989-04-23 00:00:00 +19217,469,87,0.0,39,0,1989-04-23 00:00:00 +19218,469,139,0.0,37,0,1989-04-23 00:00:00 +19219,469,91,0.0,33,0,1989-04-23 00:00:00 +19220,469,98,0.0,12,0,1989-04-23 00:00:00 +19221,469,122,3.0,8,0,1989-04-23 00:00:00 +19222,469,159,0.0,34,0,1989-04-23 00:00:00 +19223,469,130,0.0,26,0,1989-04-23 00:00:00 +19224,469,126,4.0,5,0,1989-04-23 00:00:00 +19225,469,121,0.0,25,0,1989-04-23 00:00:00 +19226,469,116,12.0,1,0,1989-04-23 00:00:00 +19227,469,64,3.0,7,0,1989-04-23 00:00:00 +19228,469,117,4.0,6,0,1989-04-23 00:00:00 +19229,469,144,5.0,4,0,1989-04-23 00:00:00 +19230,469,155,1.0,9,0,1989-04-23 00:00:00 +19231,469,137,0.0,11,0,1989-04-23 00:00:00 +19232,469,128,0.0,14,0,1989-04-23 00:00:00 +19233,469,104,0.0,16,0,1989-04-23 00:00:00 +19234,469,94,9.0,3,1,1989-04-23 00:00:00 +19235,469,111,0.0,17,0,1989-04-23 00:00:00 +19236,469,101,9.0,2,1,1989-04-23 00:00:00 +19237,469,83,0.0,21,0,1989-04-23 00:00:00 +19238,469,145,0.0,24,0,1989-04-23 00:00:00 +19239,469,136,0.0,23,0,1989-04-23 00:00:00 +19240,469,118,0.0,20,0,1989-04-23 00:00:00 +19241,469,156,0.0,19,0,1989-04-23 00:00:00 +19242,469,109,0.0,15,0,1989-04-23 00:00:00 +19243,469,157,0.0,13,0,1989-04-23 00:00:00 +19244,470,122,3.0,9,0,1989-05-07 00:00:00 +19245,470,93,0.0,29,0,1989-05-07 00:00:00 +19246,470,76,0.0,30,0,1989-05-07 00:00:00 +19247,470,158,0.0,25,0,1989-05-07 00:00:00 +19248,470,113,0.0,32,0,1989-05-07 00:00:00 +19249,470,162,0.0,21,0,1989-05-07 00:00:00 +19250,470,147,0.0,33,0,1989-05-07 00:00:00 +19251,470,89,0.0,28,0,1989-05-07 00:00:00 +19252,470,159,0.0,34,0,1989-05-07 00:00:00 +19253,470,160,0.0,37,0,1989-05-07 00:00:00 +19254,470,161,0.0,31,0,1989-05-07 00:00:00 +19255,470,87,0.0,39,0,1989-05-07 00:00:00 +19256,470,139,0.0,35,0,1989-05-07 00:00:00 +19257,470,91,0.0,36,0,1989-05-07 00:00:00 +19258,470,98,0.0,16,0,1989-05-07 00:00:00 +19259,470,130,4.0,6,0,1989-05-07 00:00:00 +19260,470,77,0.0,22,0,1989-05-07 00:00:00 +19261,470,132,3.0,8,0,1989-05-07 00:00:00 +19262,470,163,0.0,38,0,1989-05-07 00:00:00 +19263,470,136,0.0,26,0,1989-05-07 00:00:00 +19264,470,83,1.0,13,0,1989-05-07 00:00:00 +19265,470,121,0.0,19,0,1989-05-07 00:00:00 +19266,470,94,9.0,3,1,1989-05-07 00:00:00 +19267,470,116,18.0,2,0,1989-05-07 00:00:00 +19268,470,126,4.0,5,0,1989-05-07 00:00:00 +19269,470,64,3.0,10,0,1989-05-07 00:00:00 +19270,470,144,5.0,4,0,1989-05-07 00:00:00 +19271,470,155,1.0,12,0,1989-05-07 00:00:00 +19272,470,137,0.0,15,0,1989-05-07 00:00:00 +19273,470,117,4.0,7,0,1989-05-07 00:00:00 +19274,470,104,2.0,11,0,1989-05-07 00:00:00 +19275,470,128,0.0,17,0,1989-05-07 00:00:00 +19276,470,157,0.0,14,0,1989-05-07 00:00:00 +19277,470,118,0.0,24,0,1989-05-07 00:00:00 +19278,470,156,0.0,23,0,1989-05-07 00:00:00 +19279,470,145,0.0,27,0,1989-05-07 00:00:00 +19280,470,111,0.0,20,0,1989-05-07 00:00:00 +19281,470,101,18.0,1,2,1989-05-07 00:00:00 +19282,470,109,0.0,18,0,1989-05-07 00:00:00 +19283,471,147,0.0,34,0,1989-05-28 00:00:00 +19284,471,77,0.0,25,0,1989-05-28 00:00:00 +19285,471,93,0.0,27,0,1989-05-28 00:00:00 +19286,471,76,0.0,30,0,1989-05-28 00:00:00 +19287,471,158,0.0,26,0,1989-05-28 00:00:00 +19288,471,113,0.0,33,0,1989-05-28 00:00:00 +19289,471,162,0.0,23,0,1989-05-28 00:00:00 +19290,471,89,0.0,29,0,1989-05-28 00:00:00 +19291,471,122,3.0,11,0,1989-05-28 00:00:00 +19292,471,159,0.0,35,0,1989-05-28 00:00:00 +19293,471,160,0.0,37,0,1989-05-28 00:00:00 +19294,471,161,0.0,32,0,1989-05-28 00:00:00 +19295,471,163,0.0,38,0,1989-05-28 00:00:00 +19296,471,87,0.0,39,0,1989-05-28 00:00:00 +19297,471,139,0.0,31,0,1989-05-28 00:00:00 +19298,471,91,0.0,36,0,1989-05-28 00:00:00 +19299,471,98,1.0,14,0,1989-05-28 00:00:00 +19300,471,132,3.0,10,0,1989-05-28 00:00:00 +19301,471,130,4.0,7,0,1989-05-28 00:00:00 +19302,471,145,0.0,28,0,1989-05-28 00:00:00 +19303,471,121,0.0,21,0,1989-05-28 00:00:00 +19304,471,94,9.0,3,1,1989-05-28 00:00:00 +19305,471,116,20.0,2,0,1989-05-28 00:00:00 +19306,471,126,4.0,8,0,1989-05-28 00:00:00 +19307,471,64,3.0,12,0,1989-05-28 00:00:00 +19308,471,117,4.0,9,0,1989-05-28 00:00:00 +19309,471,144,8.0,4,0,1989-05-28 00:00:00 +19310,471,155,1.0,13,0,1989-05-28 00:00:00 +19311,471,137,0.0,18,0,1989-05-28 00:00:00 +19312,471,136,0.0,20,0,1989-05-28 00:00:00 +19313,471,104,6.0,6,0,1989-05-28 00:00:00 +19314,471,101,27.0,1,3,1989-05-28 00:00:00 +19315,471,111,0.0,24,0,1989-05-28 00:00:00 +19316,471,109,0.0,19,0,1989-05-28 00:00:00 +19317,471,156,0.0,22,0,1989-05-28 00:00:00 +19318,471,118,6.0,5,0,1989-05-28 00:00:00 +19319,471,157,0.0,16,0,1989-05-28 00:00:00 +19320,471,83,1.0,15,0,1989-05-28 00:00:00 +19321,471,128,0.0,17,0,1989-05-28 00:00:00 +19322,472,147,0.0,34,0,1989-06-04 00:00:00 +19323,472,162,0.0,23,0,1989-06-04 00:00:00 +19324,472,93,0.0,29,0,1989-06-04 00:00:00 +19325,472,158,0.0,28,0,1989-06-04 00:00:00 +19326,472,76,0.0,26,0,1989-06-04 00:00:00 +19327,472,89,0.0,31,0,1989-06-04 00:00:00 +19328,472,113,0.0,33,0,1989-06-04 00:00:00 +19329,472,132,3.0,13,0,1989-06-04 00:00:00 +19330,472,87,0.0,39,0,1989-06-04 00:00:00 +19331,472,160,0.0,37,0,1989-06-04 00:00:00 +19332,472,161,0.0,32,0,1989-06-04 00:00:00 +19333,472,163,0.0,38,0,1989-06-04 00:00:00 +19334,472,139,0.0,27,0,1989-06-04 00:00:00 +19335,472,91,0.0,36,0,1989-06-04 00:00:00 +19336,472,98,1.0,15,0,1989-06-04 00:00:00 +19337,472,77,0.0,25,0,1989-06-04 00:00:00 +19338,472,122,4.0,11,0,1989-06-04 00:00:00 +19339,472,159,0.0,35,0,1989-06-04 00:00:00 +19340,472,130,4.0,9,0,1989-06-04 00:00:00 +19341,472,136,0.0,21,0,1989-06-04 00:00:00 +19342,472,121,0.0,22,0,1989-06-04 00:00:00 +19343,472,116,29.0,1,1,1989-06-04 00:00:00 +19344,472,126,4.0,10,0,1989-06-04 00:00:00 +19345,472,64,5.0,7,0,1989-06-04 00:00:00 +19346,472,117,4.0,12,0,1989-06-04 00:00:00 +19347,472,144,8.0,5,0,1989-06-04 00:00:00 +19348,472,155,1.0,16,0,1989-06-04 00:00:00 +19349,472,137,0.0,20,0,1989-06-04 00:00:00 +19350,472,128,0.0,18,0,1989-06-04 00:00:00 +19351,472,94,9.0,4,1,1989-06-04 00:00:00 +19352,472,101,27.0,2,3,1989-06-04 00:00:00 +19353,472,111,0.0,24,0,1989-06-04 00:00:00 +19354,472,109,0.0,19,0,1989-06-04 00:00:00 +19355,472,156,3.0,14,0,1989-06-04 00:00:00 +19356,472,118,12.0,3,0,1989-06-04 00:00:00 +19357,472,157,4.0,8,0,1989-06-04 00:00:00 +19358,472,145,0.0,30,0,1989-06-04 00:00:00 +19359,472,83,1.0,17,0,1989-06-04 00:00:00 +19360,472,104,6.0,6,0,1989-06-04 00:00:00 +19361,473,162,2.0,17,0,1989-06-18 00:00:00 +19362,473,113,0.0,33,0,1989-06-18 00:00:00 +19363,473,122,13.0,4,1,1989-06-18 00:00:00 +19364,473,76,0.0,27,0,1989-06-18 00:00:00 +19365,473,93,0.0,30,0,1989-06-18 00:00:00 +19366,473,147,0.0,34,0,1989-06-18 00:00:00 +19367,473,158,0.0,29,0,1989-06-18 00:00:00 +19368,473,89,0.0,26,0,1989-06-18 00:00:00 +19369,473,163,0.0,38,0,1989-06-18 00:00:00 +19370,473,159,0.0,35,0,1989-06-18 00:00:00 +19371,473,160,0.0,37,0,1989-06-18 00:00:00 +19372,473,77,0.0,24,0,1989-06-18 00:00:00 +19373,473,87,0.0,39,0,1989-06-18 00:00:00 +19374,473,139,0.0,28,0,1989-06-18 00:00:00 +19375,473,91,0.0,36,0,1989-06-18 00:00:00 +19376,473,98,1.0,18,0,1989-06-18 00:00:00 +19377,473,130,4.0,11,0,1989-06-18 00:00:00 +19378,473,132,4.0,13,0,1989-06-18 00:00:00 +19379,473,136,3.0,16,0,1989-06-18 00:00:00 +19380,473,161,0.0,32,0,1989-06-18 00:00:00 +19381,473,83,1.0,20,0,1989-06-18 00:00:00 +19382,473,94,9.0,5,1,1989-06-18 00:00:00 +19383,473,116,29.0,1,1,1989-06-18 00:00:00 +19384,473,126,4.0,12,0,1989-06-18 00:00:00 +19385,473,64,5.0,8,0,1989-06-18 00:00:00 +19386,473,144,8.0,6,0,1989-06-18 00:00:00 +19387,473,155,1.0,19,0,1989-06-18 00:00:00 +19388,473,137,0.0,22,0,1989-06-18 00:00:00 +19389,473,128,0.0,21,0,1989-06-18 00:00:00 +19390,473,117,4.0,14,0,1989-06-18 00:00:00 +19391,473,101,27.0,2,3,1989-06-18 00:00:00 +19392,473,104,6.0,7,0,1989-06-18 00:00:00 +19393,473,145,0.0,31,0,1989-06-18 00:00:00 +19394,473,157,4.0,9,0,1989-06-18 00:00:00 +19395,473,118,18.0,3,0,1989-06-18 00:00:00 +19396,473,121,0.0,23,0,1989-06-18 00:00:00 +19397,473,109,4.0,10,0,1989-06-18 00:00:00 +19398,473,111,0.0,25,0,1989-06-18 00:00:00 +19399,473,156,3.0,15,0,1989-06-18 00:00:00 +19400,474,160,0.0,41,0,1989-07-09 00:00:00 +19401,474,158,0.0,34,0,1989-07-09 00:00:00 +19402,474,113,0.0,38,0,1989-07-09 00:00:00 +19403,474,162,2.0,18,0,1989-07-09 00:00:00 +19404,474,147,0.0,39,0,1989-07-09 00:00:00 +19405,474,89,0.0,32,0,1989-07-09 00:00:00 +19406,474,132,4.0,13,0,1989-07-09 00:00:00 +19407,474,159,0.0,40,0,1989-07-09 00:00:00 +19408,474,76,0.0,33,0,1989-07-09 00:00:00 +19409,474,102,0.0,27,0,1989-07-09 00:00:00 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00:00:00 +19433,474,101,27.0,2,3,1989-07-09 00:00:00 +19434,474,104,6.0,7,0,1989-07-09 00:00:00 +19435,474,83,1.0,23,0,1989-07-09 00:00:00 +19436,474,145,0.0,36,0,1989-07-09 00:00:00 +19437,474,157,4.0,9,0,1989-07-09 00:00:00 +19438,474,121,0.0,26,0,1989-07-09 00:00:00 +19439,474,156,3.0,16,0,1989-07-09 00:00:00 +19440,474,109,4.0,10,0,1989-07-09 00:00:00 +19441,474,111,0.0,29,0,1989-07-09 00:00:00 +19442,474,118,22.0,3,0,1989-07-09 00:00:00 +19443,475,93,2.0,20,0,1989-07-16 00:00:00 +19444,475,76,0.0,35,0,1989-07-16 00:00:00 +19445,475,158,1.0,25,0,1989-07-16 00:00:00 +19446,475,113,0.0,38,0,1989-07-16 00:00:00 +19447,475,162,2.0,18,0,1989-07-16 00:00:00 +19448,475,147,0.0,39,0,1989-07-16 00:00:00 +19449,475,89,0.0,34,0,1989-07-16 00:00:00 +19450,475,132,4.0,14,0,1989-07-16 00:00:00 +19451,475,138,0.0,27,0,1989-07-16 00:00:00 +19452,475,160,0.0,41,0,1989-07-16 00:00:00 +19453,475,161,0.0,37,0,1989-07-16 00:00:00 +19454,475,163,0.0,42,0,1989-07-16 00:00:00 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00:00:00 +19478,475,156,3.0,16,0,1989-07-16 00:00:00 +19479,475,118,22.0,3,0,1989-07-16 00:00:00 +19480,475,157,4.0,10,0,1989-07-16 00:00:00 +19481,475,145,0.0,36,0,1989-07-16 00:00:00 +19482,475,83,1.0,24,0,1989-07-16 00:00:00 +19483,475,128,1.0,21,0,1989-07-16 00:00:00 +19484,475,150,0.0,33,0,1989-07-16 00:00:00 +19485,475,98,1.0,22,0,1989-07-16 00:00:00 +19486,476,138,0.0,27,0,1989-07-30 00:00:00 +19487,476,145,0.0,36,0,1989-07-30 00:00:00 +19488,476,157,4.0,11,0,1989-07-30 00:00:00 +19489,476,118,25.0,4,0,1989-07-30 00:00:00 +19490,476,156,3.0,16,0,1989-07-30 00:00:00 +19491,476,109,4.0,12,0,1989-07-30 00:00:00 +19492,476,111,0.0,32,0,1989-07-30 00:00:00 +19493,476,101,36.0,2,4,1989-07-30 00:00:00 +19494,476,128,1.0,21,0,1989-07-30 00:00:00 +19495,476,83,1.0,24,0,1989-07-30 00:00:00 +19496,476,137,0.0,26,0,1989-07-30 00:00:00 +19497,476,144,12.0,6,0,1989-07-30 00:00:00 +19498,476,117,5.0,10,0,1989-07-30 00:00:00 +19499,476,64,5.0,9,0,1989-07-30 00:00:00 +19500,476,126,4.0,14,0,1989-07-30 00:00:00 +19501,476,116,53.0,1,3,1989-07-30 00:00:00 +19502,476,94,25.0,3,1,1989-07-30 00:00:00 +19503,476,150,0.0,33,0,1989-07-30 00:00:00 +19504,476,102,0.0,29,0,1989-07-30 00:00:00 +19505,476,155,1.0,23,0,1989-07-30 00:00:00 +19506,476,121,0.0,28,0,1989-07-30 00:00:00 +19507,476,104,6.0,8,0,1989-07-30 00:00:00 +19508,476,130,4.0,13,0,1989-07-30 00:00:00 +19509,476,54,3.0,17,0,1989-07-30 00:00:00 +19510,476,136,8.0,7,0,1989-07-30 00:00:00 +19511,476,77,0.0,31,0,1989-07-30 00:00:00 +19512,476,98,1.0,22,0,1989-07-30 00:00:00 +19513,476,91,0.0,30,0,1989-07-30 00:00:00 +19514,476,139,2.0,20,0,1989-07-30 00:00:00 +19515,476,87,0.0,43,0,1989-07-30 00:00:00 +19516,476,161,0.0,37,0,1989-07-30 00:00:00 +19517,476,160,0.0,41,0,1989-07-30 00:00:00 +19518,476,159,0.0,40,0,1989-07-30 00:00:00 +19519,476,163,0.0,42,0,1989-07-30 00:00:00 +19520,476,93,2.0,18,0,1989-07-30 00:00:00 +19521,476,89,0.0,34,0,1989-07-30 00:00:00 +19522,476,147,0.0,39,0,1989-07-30 00:00:00 +19523,476,162,2.0,19,0,1989-07-30 00:00:00 +19524,476,113,0.0,38,0,1989-07-30 00:00:00 +19525,476,158,1.0,25,0,1989-07-30 00:00:00 +19526,476,76,0.0,35,0,1989-07-30 00:00:00 +19527,476,132,4.0,15,0,1989-07-30 00:00:00 +19528,476,122,13.0,5,1,1989-07-30 00:00:00 +19529,477,159,0.0,38,0,1989-08-13 00:00:00 +19530,477,132,4.0,15,0,1989-08-13 00:00:00 +19531,477,89,0.0,34,0,1989-08-13 00:00:00 +19532,477,158,1.0,25,0,1989-08-13 00:00:00 +19533,477,162,2.0,19,0,1989-08-13 00:00:00 +19534,477,113,0.0,39,0,1989-08-13 00:00:00 +19535,477,160,0.0,41,0,1989-08-13 00:00:00 +19536,477,147,0.0,40,0,1989-08-13 00:00:00 +19537,477,161,0.0,37,0,1989-08-13 00:00:00 +19538,477,150,0.0,33,0,1989-08-13 00:00:00 +19539,477,87,0.0,43,0,1989-08-13 00:00:00 +19540,477,139,2.0,20,0,1989-08-13 00:00:00 +19541,477,91,0.0,30,0,1989-08-13 00:00:00 +19542,477,98,1.0,22,0,1989-08-13 00:00:00 +19543,477,77,0.0,31,0,1989-08-13 00:00:00 +19544,477,54,3.0,17,0,1989-08-13 00:00:00 +19545,477,138,0.0,27,0,1989-08-13 00:00:00 +19546,477,102,0.0,29,0,1989-08-13 00:00:00 +19547,477,76,0.0,35,0,1989-08-13 00:00:00 +19548,477,163,0.0,42,0,1989-08-13 00:00:00 +19549,477,93,2.0,18,0,1989-08-13 00:00:00 +19550,477,101,42.0,2,4,1989-08-13 00:00:00 +19551,477,130,4.0,13,0,1989-08-13 00:00:00 +19552,477,122,17.0,5,1,1989-08-13 00:00:00 +19553,477,116,56.0,1,3,1989-08-13 00:00:00 +19554,477,126,4.0,14,0,1989-08-13 00:00:00 +19555,477,64,5.0,10,0,1989-08-13 00:00:00 +19556,477,117,5.0,11,0,1989-08-13 00:00:00 +19557,477,144,12.0,6,0,1989-08-13 00:00:00 +19558,477,155,1.0,23,0,1989-08-13 00:00:00 +19559,477,137,0.0,26,0,1989-08-13 00:00:00 +19560,477,128,1.0,21,0,1989-08-13 00:00:00 +19561,477,104,6.0,9,0,1989-08-13 00:00:00 +19562,477,94,34.0,3,2,1989-08-13 00:00:00 +19563,477,111,0.0,32,0,1989-08-13 00:00:00 +19564,477,121,0.0,28,0,1989-08-13 00:00:00 +19565,477,83,1.0,24,0,1989-08-13 00:00:00 +19566,477,145,0.0,36,0,1989-08-13 00:00:00 +19567,477,136,9.0,7,0,1989-08-13 00:00:00 +19568,477,118,25.0,4,0,1989-08-13 00:00:00 +19569,477,156,3.0,16,0,1989-08-13 00:00:00 +19570,477,109,4.0,12,0,1989-08-13 00:00:00 +19571,477,157,6.0,8,0,1989-08-13 00:00:00 +19572,478,160,0.0,41,0,1989-08-27 00:00:00 +19573,478,158,1.0,25,0,1989-08-27 00:00:00 +19574,478,113,0.0,39,0,1989-08-27 00:00:00 +19575,478,162,2.0,20,0,1989-08-27 00:00:00 +19576,478,147,0.0,40,0,1989-08-27 00:00:00 +19577,478,89,0.0,34,0,1989-08-27 00:00:00 +19578,478,132,4.0,15,0,1989-08-27 00:00:00 +19579,478,159,0.0,38,0,1989-08-27 00:00:00 +19580,478,161,0.0,37,0,1989-08-27 00:00:00 +19581,478,77,0.0,32,0,1989-08-27 00:00:00 +19582,478,87,0.0,43,0,1989-08-27 00:00:00 +19583,478,91,0.0,30,0,1989-08-27 00:00:00 +19584,478,98,1.0,22,0,1989-08-27 00:00:00 +19585,478,76,0.0,35,0,1989-08-27 00:00:00 +19586,478,54,3.0,17,0,1989-08-27 00:00:00 +19587,478,138,0.0,27,0,1989-08-27 00:00:00 +19588,478,102,0.0,29,0,1989-08-27 00:00:00 +19589,478,150,0.0,33,0,1989-08-27 00:00:00 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00:00:00 +19613,478,121,0.0,28,0,1989-08-27 00:00:00 +19614,478,136,9.0,7,0,1989-08-27 00:00:00 +19615,478,101,51.0,2,5,1989-08-27 00:00:00 +19616,479,161,0.0,37,0,1989-09-10 00:00:00 +19617,479,160,0.0,41,0,1989-09-10 00:00:00 +19618,479,159,0.0,38,0,1989-09-10 00:00:00 +19619,479,113,0.0,39,0,1989-09-10 00:00:00 +19620,479,89,0.0,35,0,1989-09-10 00:00:00 +19621,479,147,0.0,40,0,1989-09-10 00:00:00 +19622,479,162,2.0,21,0,1989-09-10 00:00:00 +19623,479,163,0.0,42,0,1989-09-10 00:00:00 +19624,479,132,4.0,17,0,1989-09-10 00:00:00 +19625,479,87,0.0,43,0,1989-09-10 00:00:00 +19626,479,54,5.0,12,0,1989-09-10 00:00:00 +19627,479,91,0.0,31,0,1989-09-10 00:00:00 +19628,479,98,1.0,24,0,1989-09-10 00:00:00 +19629,479,77,0.0,33,0,1989-09-10 00:00:00 +19630,479,138,0.0,28,0,1989-09-10 00:00:00 +19631,479,102,0.0,30,0,1989-09-10 00:00:00 +19632,479,150,0.0,34,0,1989-09-10 00:00:00 +19633,479,133,0.0,45,0,1989-09-10 00:00:00 +19634,479,164,0.0,44,0,1989-09-10 00:00:00 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00:00:00 +19658,479,118,28.0,4,0,1989-09-10 00:00:00 +19659,479,156,3.0,18,0,1989-09-10 00:00:00 +19660,479,145,0.0,36,0,1989-09-10 00:00:00 +19661,480,163,0.0,44,0,1989-09-24 00:00:00 +19662,480,113,0.0,39,0,1989-09-24 00:00:00 +19663,480,162,2.0,21,0,1989-09-24 00:00:00 +19664,480,147,0.0,40,0,1989-09-24 00:00:00 +19665,480,89,0.0,35,0,1989-09-24 00:00:00 +19666,480,132,4.0,18,0,1989-09-24 00:00:00 +19667,480,159,0.0,38,0,1989-09-24 00:00:00 +19668,480,160,0.0,41,0,1989-09-24 00:00:00 +19669,480,161,0.0,37,0,1989-09-24 00:00:00 +19670,480,87,0.0,45,0,1989-09-24 00:00:00 +19671,480,108,0.0,42,0,1989-09-24 00:00:00 +19672,480,91,0.0,32,0,1989-09-24 00:00:00 +19673,480,98,1.0,25,0,1989-09-24 00:00:00 +19674,480,77,0.0,33,0,1989-09-24 00:00:00 +19675,480,54,5.0,13,0,1989-09-24 00:00:00 +19676,480,138,0.0,28,0,1989-09-24 00:00:00 +19677,480,102,0.0,31,0,1989-09-24 00:00:00 +19678,480,150,0.0,34,0,1989-09-24 00:00:00 +19679,480,133,0.0,46,0,1989-09-24 00:00:00 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00:00:00 +19703,480,157,6.0,9,0,1989-09-24 00:00:00 +19704,480,118,28.0,4,0,1989-09-24 00:00:00 +19705,480,156,3.0,20,0,1989-09-24 00:00:00 +19706,480,145,0.0,36,0,1989-09-24 00:00:00 +19707,481,163,0.0,45,0,1989-10-01 00:00:00 +19708,481,113,0.0,40,0,1989-10-01 00:00:00 +19709,481,162,2.0,21,0,1989-10-01 00:00:00 +19710,481,147,0.0,41,0,1989-10-01 00:00:00 +19711,481,89,0.0,35,0,1989-10-01 00:00:00 +19712,481,132,4.0,18,0,1989-10-01 00:00:00 +19713,481,159,0.0,38,0,1989-10-01 00:00:00 +19714,481,160,0.0,42,0,1989-10-01 00:00:00 +19715,481,161,0.0,39,0,1989-10-01 00:00:00 +19716,481,87,0.0,43,0,1989-10-01 00:00:00 +19717,481,158,1.0,26,0,1989-10-01 00:00:00 +19718,481,91,0.0,32,0,1989-10-01 00:00:00 +19719,481,98,1.0,25,0,1989-10-01 00:00:00 +19720,481,77,0.0,33,0,1989-10-01 00:00:00 +19721,481,54,8.0,9,0,1989-10-01 00:00:00 +19722,481,138,0.0,29,0,1989-10-01 00:00:00 +19723,481,150,0.0,34,0,1989-10-01 00:00:00 +19724,481,133,0.0,46,0,1989-10-01 00:00:00 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00:00:00 +19974,487,121,0.0,31,0,1990-05-27 00:00:00 +19975,487,116,12.0,4,1,1990-05-27 00:00:00 +19976,487,109,0.0,27,0,1990-05-27 00:00:00 +19977,487,128,0.0,28,0,1990-05-27 00:00:00 +19978,487,147,0.0,16,0,1990-05-27 00:00:00 +19979,487,76,16.0,2,0,1990-05-27 00:00:00 +19980,487,94,3.0,9,0,1990-05-27 00:00:00 +19981,487,93,0.0,14,0,1990-05-27 00:00:00 +19982,487,54,13.0,3,0,1990-05-27 00:00:00 +19983,487,146,0.0,21,0,1990-05-27 00:00:00 +19984,487,132,2.0,10,0,1990-05-27 00:00:00 +19985,487,91,0.0,36,0,1990-05-27 00:00:00 +19986,487,149,0.0,39,0,1990-05-27 00:00:00 +19987,487,148,0.0,37,0,1990-05-27 00:00:00 +19988,487,113,0.0,32,0,1990-05-27 00:00:00 +19989,487,108,0.0,22,0,1990-05-27 00:00:00 +19990,487,80,0.0,26,0,1990-05-27 00:00:00 +19991,487,145,0.0,23,0,1990-05-27 00:00:00 +19992,487,104,0.0,20,0,1990-05-27 00:00:00 +19993,487,118,9.0,5,1,1990-05-27 00:00:00 +19994,487,87,0.0,29,0,1990-05-27 00:00:00 +19995,488,76,19.0,2,0,1990-06-10 00:00:00 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00:00:00 +20019,488,98,0.0,35,0,1990-06-10 00:00:00 +20020,488,113,0.0,32,0,1990-06-10 00:00:00 +20021,488,148,0.0,37,0,1990-06-10 00:00:00 +20022,488,149,0.0,39,0,1990-06-10 00:00:00 +20023,488,108,0.0,23,0,1990-06-10 00:00:00 +20024,488,111,0.0,18,0,1990-06-10 00:00:00 +20025,488,91,0.0,36,0,1990-06-10 00:00:00 +20026,488,89,0.0,27,0,1990-06-10 00:00:00 +20027,488,126,0.0,28,0,1990-06-10 00:00:00 +20028,488,146,0.0,22,0,1990-06-10 00:00:00 +20029,488,54,13.0,4,0,1990-06-10 00:00:00 +20030,488,100,0.0,31,0,1990-06-10 00:00:00 +20031,488,138,0.0,33,0,1990-06-10 00:00:00 +20032,488,132,2.0,11,0,1990-06-10 00:00:00 +20033,488,151,0.0,38,0,1990-06-10 00:00:00 +20034,489,130,2.0,10,0,1990-06-24 00:00:00 +20035,489,116,23.0,2,2,1990-06-24 00:00:00 +20036,489,109,0.0,27,0,1990-06-24 00:00:00 +20037,489,128,0.0,26,0,1990-06-24 00:00:00 +20038,489,147,0.0,16,0,1990-06-24 00:00:00 +20039,489,76,23.0,3,0,1990-06-24 00:00:00 +20040,489,94,13.0,5,0,1990-06-24 00:00:00 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00:00:00 +20064,489,144,7.0,9,0,1990-06-24 00:00:00 +20065,489,100,0.0,31,0,1990-06-24 00:00:00 +20066,489,149,0.0,39,0,1990-06-24 00:00:00 +20067,489,148,0.0,37,0,1990-06-24 00:00:00 +20068,489,113,0.0,32,0,1990-06-24 00:00:00 +20069,489,98,0.0,35,0,1990-06-24 00:00:00 +20070,489,80,0.0,30,0,1990-06-24 00:00:00 +20071,489,139,0.0,34,0,1990-06-24 00:00:00 +20072,489,91,0.0,36,0,1990-06-24 00:00:00 +20073,490,94,13.0,6,0,1990-07-08 00:00:00 +20074,490,146,0.0,23,0,1990-07-08 00:00:00 +20075,490,126,0.0,29,0,1990-07-08 00:00:00 +20076,490,89,0.0,28,0,1990-07-08 00:00:00 +20077,490,76,25.0,3,0,1990-07-08 00:00:00 +20078,490,87,0.0,17,0,1990-07-08 00:00:00 +20079,490,101,35.0,1,3,1990-07-08 00:00:00 +20080,490,122,11.0,7,0,1990-07-08 00:00:00 +20081,490,54,13.0,5,0,1990-07-08 00:00:00 +20082,490,102,1.0,14,0,1990-07-08 00:00:00 +20083,490,145,0.0,25,0,1990-07-08 00:00:00 +20084,490,130,2.0,11,0,1990-07-08 00:00:00 +20085,490,137,1.0,15,0,1990-07-08 00:00:00 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00:00:00 +20109,490,150,0.0,19,0,1990-07-08 00:00:00 +20110,490,77,0.0,22,0,1990-07-08 00:00:00 +20111,490,104,0.0,21,0,1990-07-08 00:00:00 +20112,491,132,2.0,12,0,1990-07-15 00:00:00 +20113,491,136,18.0,4,0,1990-07-15 00:00:00 +20114,491,130,2.0,13,0,1990-07-15 00:00:00 +20115,491,101,39.0,2,3,1990-07-15 00:00:00 +20116,491,137,1.0,16,0,1990-07-15 00:00:00 +20117,491,104,0.0,22,0,1990-07-15 00:00:00 +20118,491,102,4.0,11,0,1990-07-15 00:00:00 +20119,491,144,7.0,9,0,1990-07-15 00:00:00 +20120,491,89,0.0,29,0,1990-07-15 00:00:00 +20121,491,54,13.0,6,0,1990-07-15 00:00:00 +20122,491,93,0.0,17,0,1990-07-15 00:00:00 +20123,491,109,0.0,28,0,1990-07-15 00:00:00 +20124,491,150,0.0,19,0,1990-07-15 00:00:00 +20125,491,117,1.0,14,0,1990-07-15 00:00:00 +20126,491,145,0.0,26,0,1990-07-15 00:00:00 +20127,491,126,0.0,30,0,1990-07-15 00:00:00 +20128,491,146,0.0,23,0,1990-07-15 00:00:00 +20129,491,87,1.0,15,0,1990-07-15 00:00:00 +20130,491,94,13.0,7,0,1990-07-15 00:00:00 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00:00:00 +20154,492,102,4.0,11,0,1990-07-29 00:00:00 +20155,492,89,0.0,29,0,1990-07-29 00:00:00 +20156,492,93,0.0,17,0,1990-07-29 00:00:00 +20157,492,122,18.0,4,0,1990-07-29 00:00:00 +20158,492,130,2.0,13,0,1990-07-29 00:00:00 +20159,492,147,0.0,18,0,1990-07-29 00:00:00 +20160,492,138,0.0,24,0,1990-07-29 00:00:00 +20161,492,109,0.0,28,0,1990-07-29 00:00:00 +20162,492,121,6.0,10,0,1990-07-29 00:00:00 +20163,492,117,1.0,14,0,1990-07-29 00:00:00 +20164,492,77,0.0,21,0,1990-07-29 00:00:00 +20165,492,150,0.0,19,0,1990-07-29 00:00:00 +20166,492,139,0.0,35,0,1990-07-29 00:00:00 +20167,492,80,0.0,31,0,1990-07-29 00:00:00 +20168,492,108,0.0,25,0,1990-07-29 00:00:00 +20169,492,98,0.0,34,0,1990-07-29 00:00:00 +20170,492,113,0.0,33,0,1990-07-29 00:00:00 +20171,492,137,1.0,16,0,1990-07-29 00:00:00 +20172,492,101,48.0,1,4,1990-07-29 00:00:00 +20173,492,148,0.0,37,0,1990-07-29 00:00:00 +20174,492,149,0.0,39,0,1990-07-29 00:00:00 +20175,492,91,0.0,36,0,1990-07-29 00:00:00 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00:00:00 +20199,493,151,0.0,38,0,1990-08-12 00:00:00 +20200,493,122,27.0,4,1,1990-08-12 00:00:00 +20201,493,121,6.0,10,0,1990-08-12 00:00:00 +20202,493,109,0.0,29,0,1990-08-12 00:00:00 +20203,493,116,44.0,2,4,1990-08-12 00:00:00 +20204,493,77,0.0,22,0,1990-08-12 00:00:00 +20205,493,150,0.0,17,0,1990-08-12 00:00:00 +20206,493,139,0.0,35,0,1990-08-12 00:00:00 +20207,493,80,0.0,32,0,1990-08-12 00:00:00 +20208,493,108,0.0,26,0,1990-08-12 00:00:00 +20209,493,98,0.0,30,0,1990-08-12 00:00:00 +20210,493,113,0.0,34,0,1990-08-12 00:00:00 +20211,493,148,0.0,37,0,1990-08-12 00:00:00 +20212,493,149,0.0,39,0,1990-08-12 00:00:00 +20213,493,91,0.0,36,0,1990-08-12 00:00:00 +20214,493,111,0.0,21,0,1990-08-12 00:00:00 +20215,493,132,2.0,13,0,1990-08-12 00:00:00 +20216,493,138,0.0,24,0,1990-08-12 00:00:00 +20217,493,100,0.0,33,0,1990-08-12 00:00:00 +20218,493,128,0.0,28,0,1990-08-12 00:00:00 +20219,493,147,0.0,19,0,1990-08-12 00:00:00 +20220,493,101,54.0,1,4,1990-08-12 00:00:00 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00:00:00 +20244,494,132,2.0,13,0,1990-08-26 00:00:00 +20245,494,117,3.0,12,0,1990-08-26 00:00:00 +20246,494,111,0.0,21,0,1990-08-26 00:00:00 +20247,494,91,0.0,36,0,1990-08-26 00:00:00 +20248,494,149,0.0,39,0,1990-08-26 00:00:00 +20249,494,148,0.0,37,0,1990-08-26 00:00:00 +20250,494,113,0.0,34,0,1990-08-26 00:00:00 +20251,494,136,24.0,5,0,1990-08-26 00:00:00 +20252,494,54,13.0,8,0,1990-08-26 00:00:00 +20253,494,101,63.0,1,5,1990-08-26 00:00:00 +20254,494,100,0.0,33,0,1990-08-26 00:00:00 +20255,494,128,0.0,28,0,1990-08-26 00:00:00 +20256,494,147,0.0,20,0,1990-08-26 00:00:00 +20257,494,76,33.0,3,0,1990-08-26 00:00:00 +20258,494,151,0.0,38,0,1990-08-26 00:00:00 +20259,494,98,0.0,30,0,1990-08-26 00:00:00 +20260,494,121,6.0,10,0,1990-08-26 00:00:00 +20261,494,145,0.0,27,0,1990-08-26 00:00:00 +20262,494,77,0.0,22,0,1990-08-26 00:00:00 +20263,494,122,27.0,4,1,1990-08-26 00:00:00 +20264,494,150,0.0,18,0,1990-08-26 00:00:00 +20265,494,108,0.0,26,0,1990-08-26 00:00:00 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00:00:00 +20289,495,128,0.0,29,0,1990-09-09 00:00:00 +20290,495,147,0.0,20,0,1990-09-09 00:00:00 +20291,495,76,37.0,3,0,1990-09-09 00:00:00 +20292,495,151,0.0,38,0,1990-09-09 00:00:00 +20293,495,80,0.0,32,0,1990-09-09 00:00:00 +20294,495,145,0.0,28,0,1990-09-09 00:00:00 +20295,495,91,0.0,36,0,1990-09-09 00:00:00 +20296,495,89,0.0,31,0,1990-09-09 00:00:00 +20297,495,130,2.0,14,0,1990-09-09 00:00:00 +20298,495,137,2.0,15,0,1990-09-09 00:00:00 +20299,495,93,0.0,19,0,1990-09-09 00:00:00 +20300,495,102,5.0,11,0,1990-09-09 00:00:00 +20301,495,118,17.0,6,1,1990-09-09 00:00:00 +20302,495,104,0.0,23,0,1990-09-09 00:00:00 +20303,495,144,16.0,7,0,1990-09-09 00:00:00 +20304,495,136,24.0,5,0,1990-09-09 00:00:00 +20305,495,54,13.0,9,0,1990-09-09 00:00:00 +20306,495,101,72.0,1,6,1990-09-09 00:00:00 +20307,496,138,0.0,24,0,1990-09-23 00:00:00 +20308,496,100,0.0,33,0,1990-09-23 00:00:00 +20309,496,147,0.0,20,0,1990-09-23 00:00:00 +20310,496,113,0.0,34,0,1990-09-23 00:00:00 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00:00:00 +20379,497,54,13.0,9,0,1990-09-30 00:00:00 +20380,497,136,26.0,6,0,1990-09-30 00:00:00 +20381,497,122,30.0,5,1,1990-09-30 00:00:00 +20382,497,93,0.0,19,0,1990-09-30 00:00:00 +20383,497,137,2.0,16,0,1990-09-30 00:00:00 +20384,497,130,2.0,14,0,1990-09-30 00:00:00 +20385,498,147,0.0,22,0,1990-10-21 00:00:00 +20386,498,100,0.0,34,0,1990-10-21 00:00:00 +20387,498,138,0.0,26,0,1990-10-21 00:00:00 +20388,498,136,35.0,4,1,1990-10-21 00:00:00 +20389,498,111,0.0,23,0,1990-10-21 00:00:00 +20390,498,76,40.0,3,0,1990-10-21 00:00:00 +20391,498,132,2.0,16,0,1990-10-21 00:00:00 +20392,498,94,31.0,6,1,1990-10-21 00:00:00 +20393,498,144,21.0,8,0,1990-10-21 00:00:00 +20394,498,64,0.0,35,0,1990-10-21 00:00:00 +20395,498,137,3.0,15,0,1990-10-21 00:00:00 +20396,498,93,0.0,21,0,1990-10-21 00:00:00 +20397,498,102,5.0,13,0,1990-10-21 00:00:00 +20398,498,118,22.0,7,1,1990-10-21 00:00:00 +20399,498,91,0.0,37,0,1990-10-21 00:00:00 +20400,498,101,78.0,1,6,1990-10-21 00:00:00 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00:00:00 +20424,498,117,3.0,14,0,1990-10-21 00:00:00 +20425,499,137,3.0,15,0,1990-11-04 00:00:00 +20426,499,93,0.0,21,0,1990-11-04 00:00:00 +20427,499,130,2.0,17,0,1990-11-04 00:00:00 +20428,499,136,43.0,3,2,1990-11-04 00:00:00 +20429,499,118,23.0,7,1,1990-11-04 00:00:00 +20430,499,101,78.0,1,6,1990-11-04 00:00:00 +20431,499,122,34.0,6,1,1990-11-04 00:00:00 +20432,499,104,0.0,24,0,1990-11-04 00:00:00 +20433,499,102,5.0,13,0,1990-11-04 00:00:00 +20434,499,54,13.0,9,0,1990-11-04 00:00:00 +20435,499,151,0.0,39,0,1990-11-04 00:00:00 +20436,499,144,21.0,8,0,1990-11-04 00:00:00 +20437,499,145,0.0,30,0,1990-11-04 00:00:00 +20438,499,89,6.0,11,0,1990-11-04 00:00:00 +20439,499,126,1.0,18,0,1990-11-04 00:00:00 +20440,499,146,0.0,28,0,1990-11-04 00:00:00 +20441,499,116,71.0,2,5,1990-11-04 00:00:00 +20442,499,121,6.0,10,0,1990-11-04 00:00:00 +20443,499,117,3.0,14,0,1990-11-04 00:00:00 +20444,499,77,0.0,19,0,1990-11-04 00:00:00 +20445,499,150,0.0,20,0,1990-11-04 00:00:00 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00:00:00 +20492,500,77,0.0,7,0,1991-03-10 00:00:00 +20493,500,137,2.0,5,0,1991-03-10 00:00:00 +20494,500,130,3.0,4,0,1991-03-10 00:00:00 +20495,500,136,4.0,3,0,1991-03-10 00:00:00 +20496,500,116,6.0,2,0,1991-03-10 00:00:00 +20497,500,101,10.0,1,1,1991-03-10 00:00:00 +20498,500,93,0.0,9,0,1991-03-10 00:00:00 +20499,501,98,0.0,13,0,1991-03-24 00:00:00 +20500,501,116,9.0,2,0,1991-03-24 00:00:00 +20501,501,101,20.0,1,2,1991-03-24 00:00:00 +20502,501,127,0.0,34,0,1991-03-24 00:00:00 +20503,501,128,0.0,32,0,1991-03-24 00:00:00 +20504,501,140,0.0,31,0,1991-03-24 00:00:00 +20505,501,109,0.0,27,0,1991-03-24 00:00:00 +20506,501,91,0.0,16,0,1991-03-24 00:00:00 +20507,501,99,0.0,21,0,1991-03-24 00:00:00 +20508,501,139,0.0,30,0,1991-03-24 00:00:00 +20509,501,132,0.0,29,0,1991-03-24 00:00:00 +20510,501,141,0.0,33,0,1991-03-24 00:00:00 +20511,501,130,3.0,6,0,1991-03-24 00:00:00 +20512,501,137,2.0,7,0,1991-03-24 00:00:00 +20513,501,136,6.0,4,0,1991-03-24 00:00:00 +20514,501,87,1.0,9,0,1991-03-24 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00:00:00 +20538,502,91,0.0,21,0,1991-04-28 00:00:00 +20539,502,136,6.0,5,0,1991-04-28 00:00:00 +20540,502,137,2.0,10,0,1991-04-28 00:00:00 +20541,502,130,3.0,8,0,1991-04-28 00:00:00 +20542,502,121,0.0,29,0,1991-04-28 00:00:00 +20543,502,87,1.0,12,0,1991-04-28 00:00:00 +20544,502,77,0.0,16,0,1991-04-28 00:00:00 +20545,502,98,0.0,19,0,1991-04-28 00:00:00 +20546,502,83,0.0,23,0,1991-04-28 00:00:00 +20547,502,54,1.0,11,0,1991-04-28 00:00:00 +20548,502,116,9.0,3,0,1991-04-28 00:00:00 +20549,502,122,0.0,14,0,1991-04-28 00:00:00 +20550,502,118,6.0,4,0,1991-04-28 00:00:00 +20551,502,94,0.0,26,0,1991-04-28 00:00:00 +20552,502,119,0.0,33,0,1991-04-28 00:00:00 +20553,502,127,0.0,20,0,1991-04-28 00:00:00 +20554,502,128,0.0,34,0,1991-04-28 00:00:00 +20555,502,141,0.0,35,0,1991-04-28 00:00:00 +20556,502,76,10.0,2,0,1991-04-28 00:00:00 +20557,502,140,1.0,13,0,1991-04-28 00:00:00 +20558,502,99,0.0,22,0,1991-04-28 00:00:00 +20559,502,139,0.0,32,0,1991-04-28 00:00:00 +20560,502,132,0.0,31,0,1991-04-28 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+26032,728,3,50.0,4,0,2004-09-26 00:00:00 +26033,728,29,136.0,1,12,2004-09-26 00:00:00 +26034,728,13,24.0,9,0,2004-09-26 00:00:00 +26035,728,21,108.0,2,2,2004-09-26 00:00:00 +26036,728,14,46.0,5,1,2004-09-26 00:00:00 +26037,728,34,0.0,23,0,2004-09-26 00:00:00 +26038,728,47,0.0,22,0,2004-09-26 00:00:00 +26039,728,9,2.0,19,0,2004-09-26 00:00:00 +26040,728,7,34.0,7,1,2004-09-26 00:00:00 +26041,728,1,3.0,18,0,2004-09-26 00:00:00 +26042,728,16,7.0,13,0,2004-09-26 00:00:00 +26043,728,46,1.0,20,0,2004-09-26 00:00:00 +26044,728,45,0.0,25,0,2004-09-26 00:00:00 +26045,728,12,11.0,12,0,2004-09-26 00:00:00 +26046,728,41,6.0,15,0,2004-09-26 00:00:00 +26047,728,40,0.0,21,0,2004-09-26 00:00:00 +26048,729,31,3.0,16,0,2004-10-10 00:00:00 +26049,729,29,146.0,1,13,2004-10-10 00:00:00 +26050,729,21,108.0,2,2,2004-10-10 00:00:00 +26051,729,34,0.0,21,0,2004-10-10 00:00:00 +26052,729,3,54.0,4,0,2004-10-10 00:00:00 +26053,729,22,20.0,11,0,2004-10-10 00:00:00 +26054,729,30,48.0,5,0,2004-10-10 00:00:00 +26055,729,17,85.0,3,0,2004-10-10 00:00:00 +26056,729,14,46.0,6,1,2004-10-10 00:00:00 +26057,729,13,24.0,9,0,2004-10-10 00:00:00 +26058,729,40,0.0,22,0,2004-10-10 00:00:00 +26059,729,41,6.0,15,0,2004-10-10 00:00:00 +26060,729,47,0.0,23,0,2004-10-10 00:00:00 +26061,729,9,2.0,19,0,2004-10-10 00:00:00 +26062,729,7,37.0,7,1,2004-10-10 00:00:00 +26063,729,1,3.0,18,0,2004-10-10 00:00:00 +26064,729,10,31.0,8,0,2004-10-10 00:00:00 +26065,729,46,1.0,20,0,2004-10-10 00:00:00 +26066,729,45,0.0,25,0,2004-10-10 00:00:00 +26067,729,12,11.0,12,0,2004-10-10 00:00:00 +26068,729,43,6.0,14,0,2004-10-10 00:00:00 +26069,729,42,3.0,17,0,2004-10-10 00:00:00 +26070,729,20,22.0,10,0,2004-10-10 00:00:00 +26071,729,16,7.0,13,0,2004-10-10 00:00:00 +26072,729,44,0.0,24,0,2004-10-10 00:00:00 +26073,730,29,148.0,1,13,2004-10-24 00:00:00 +26074,730,1,3.0,18,0,2004-10-24 00:00:00 +26075,730,7,45.0,7,1,2004-10-24 00:00:00 +26076,730,9,2.0,19,0,2004-10-24 00:00:00 +26077,730,47,0.0,23,0,2004-10-24 00:00:00 +26078,730,41,6.0,15,0,2004-10-24 00:00:00 +26079,730,40,0.0,22,0,2004-10-24 00:00:00 +26080,730,34,0.0,21,0,2004-10-24 00:00:00 +26081,730,16,7.0,13,0,2004-10-24 00:00:00 +26082,730,21,114.0,2,2,2004-10-24 00:00:00 +26083,730,3,59.0,4,0,2004-10-24 00:00:00 +26084,730,22,24.0,9,0,2004-10-24 00:00:00 +26085,730,46,1.0,20,0,2004-10-24 00:00:00 +26086,730,30,58.0,5,1,2004-10-24 00:00:00 +26087,730,17,85.0,3,0,2004-10-24 00:00:00 +26088,730,14,46.0,6,1,2004-10-24 00:00:00 +26089,730,12,12.0,12,0,2004-10-24 00:00:00 +26090,730,13,24.0,10,0,2004-10-24 00:00:00 +26091,730,44,0.0,24,0,2004-10-24 00:00:00 +26092,730,43,6.0,14,0,2004-10-24 00:00:00 +26093,730,42,3.0,17,0,2004-10-24 00:00:00 +26094,730,31,3.0,16,0,2004-10-24 00:00:00 +26095,730,20,22.0,11,0,2004-10-24 00:00:00 +26096,730,45,0.0,25,0,2004-10-24 00:00:00 +26097,730,10,34.0,8,0,2004-10-24 00:00:00 +26098,731,17,0.0,16,0,2005-03-06 14:00:00 +26099,731,12,0.0,10,0,2005-03-06 14:00:00 +26100,731,22,0.0,11,0,2005-03-06 14:00:00 +26101,731,34,0.0,12,0,2005-03-06 14:00:00 +26102,731,10,0.0,17,0,2005-03-06 14:00:00 +26103,731,38,0.0,13,0,2005-03-06 14:00:00 +26104,731,30,3.0,6,0,2005-03-06 14:00:00 +26105,731,13,5.0,4,0,2005-03-06 14:00:00 +26106,731,14,0.0,9,0,2005-03-06 14:00:00 +26107,731,16,4.0,5,0,2005-03-06 14:00:00 +26108,731,31,2.0,7,0,2005-03-06 14:00:00 +26109,731,7,1.0,8,0,2005-03-06 14:00:00 +26110,731,3,6.0,3,0,2005-03-06 14:00:00 +26111,731,21,8.0,2,0,2005-03-06 14:00:00 +26112,731,20,10.0,1,1,2005-03-06 14:00:00 +26113,731,32,0.0,14,0,2005-03-06 14:00:00 +26114,731,39,0.0,15,0,2005-03-06 14:00:00 +26115,731,29,0.0,18,0,2005-03-06 14:00:00 +26116,731,1,0.0,19,0,2005-03-06 14:00:00 +26117,731,26,0.0,20,0,2005-03-06 14:00:00 +26118,732,16,4.0,9,0,2005-03-20 15:00:00 +26119,732,21,8.0,4,0,2005-03-20 15:00:00 +26120,732,31,3.0,10,0,2005-03-20 15:00:00 +26121,732,7,1.0,12,0,2005-03-20 15:00:00 +26122,732,14,8.0,3,0,2005-03-20 15:00:00 +26123,732,12,0.0,13,0,2005-03-20 15:00:00 +26124,732,17,0.0,19,0,2005-03-20 15:00:00 +26125,732,32,0.0,15,0,2005-03-20 15:00:00 +26126,732,34,0.0,16,0,2005-03-20 15:00:00 +26127,732,10,0.0,20,0,2005-03-20 15:00:00 +26128,732,38,0.0,14,0,2005-03-20 15:00:00 +26129,732,3,16.0,1,1,2005-03-20 15:00:00 +26130,732,39,0.0,18,0,2005-03-20 15:00:00 +26131,732,29,2.0,11,0,2005-03-20 15:00:00 +26132,732,20,10.0,2,1,2005-03-20 15:00:00 +26133,732,22,4.0,8,0,2005-03-20 15:00:00 +26134,732,13,8.0,5,0,2005-03-20 15:00:00 +26135,732,30,8.0,6,0,2005-03-20 15:00:00 +26136,732,1,6.0,7,0,2005-03-20 15:00:00 +26137,732,26,0.0,17,0,2005-03-20 15:00:00 +26138,732,18,0.0,21,0,2005-03-20 15:00:00 +26139,733,12,2.0,13,0,2005-04-03 14:30:00 +26140,733,39,0.0,18,0,2005-04-03 14:30:00 +26141,733,32,0.0,15,0,2005-04-03 14:30:00 +26142,733,38,0.0,17,0,2005-04-03 14:30:00 +26143,733,10,0.0,21,0,2005-04-03 14:30:00 +26144,733,34,0.0,16,0,2005-04-03 14:30:00 +26145,733,22,9.0,4,0,2005-04-03 14:30:00 +26146,733,17,0.0,20,0,2005-04-03 14:30:00 +26147,733,7,7.0,8,0,2005-04-03 14:30:00 +26148,733,29,2.0,14,0,2005-04-03 14:30:00 +26149,733,31,3.0,12,0,2005-04-03 14:30:00 +26150,733,30,8.0,7,0,2005-04-03 14:30:00 +26151,733,16,7.0,9,0,2005-04-03 14:30:00 +26152,733,13,9.0,5,0,2005-04-03 14:30:00 +26153,733,3,26.0,1,2,2005-04-03 14:30:00 +26154,733,14,16.0,2,0,2005-04-03 14:30:00 +26155,733,1,6.0,10,0,2005-04-03 14:30:00 +26156,733,20,10.0,3,1,2005-04-03 14:30:00 +26157,733,26,0.0,19,0,2005-04-03 14:30:00 +26158,733,18,0.0,22,0,2005-04-03 14:30:00 +26159,733,36,4.0,11,0,2005-04-03 14:30:00 +26160,733,21,8.0,6,0,2005-04-03 14:30:00 +26161,734,29,10.0,4,0,2005-04-24 14:00:00 +26162,734,13,9.0,7,0,2005-04-24 14:00:00 +26163,734,16,9.0,8,0,2005-04-24 14:00:00 +26164,734,30,8.0,10,0,2005-04-24 14:00:00 +26165,734,31,3.0,15,0,2005-04-24 14:00:00 +26166,734,18,0.0,24,0,2005-04-24 14:00:00 +26167,734,7,7.0,11,0,2005-04-24 14:00:00 +26168,734,12,2.0,16,0,2005-04-24 14:00:00 +26169,734,17,0.0,22,0,2005-04-24 14:00:00 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+26193,735,7,17.0,3,1,2005-05-08 14:00:00 +26194,735,14,26.0,2,0,2005-05-08 14:00:00 +26195,735,12,2.0,16,0,2005-05-08 14:00:00 +26196,735,17,0.0,22,0,2005-05-08 14:00:00 +26197,735,22,14.0,5,0,2005-05-08 14:00:00 +26198,735,34,5.0,13,0,2005-05-08 14:00:00 +26199,735,29,10.0,7,0,2005-05-08 14:00:00 +26200,735,1,9.0,10,0,2005-05-08 14:00:00 +26201,735,21,8.0,11,0,2005-05-08 14:00:00 +26202,735,18,0.0,24,0,2005-05-08 14:00:00 +26203,735,36,4.0,14,0,2005-05-08 14:00:00 +26204,735,24,6.0,12,0,2005-05-08 14:00:00 +26205,735,23,1.0,17,0,2005-05-08 14:00:00 +26206,735,3,44.0,1,3,2005-05-08 14:00:00 +26207,735,20,14.0,4,1,2005-05-08 14:00:00 +26208,735,26,0.0,21,0,2005-05-08 14:00:00 +26209,736,34,5.0,13,0,2005-05-22 14:00:00 +26210,736,22,17.0,6,0,2005-05-22 14:00:00 +26211,736,17,0.0,22,0,2005-05-22 14:00:00 +26212,736,12,2.0,16,0,2005-05-22 14:00:00 +26213,736,20,14.0,7,1,2005-05-22 14:00:00 +26214,736,13,10.0,10,0,2005-05-22 14:00:00 +26215,736,3,49.0,1,3,2005-05-22 14:00:00 +26216,736,16,18.0,4,0,2005-05-22 14:00:00 +26217,736,30,14.0,8,0,2005-05-22 14:00:00 +26218,736,31,3.0,15,0,2005-05-22 14:00:00 +26219,736,7,27.0,2,2,2005-05-22 14:00:00 +26220,736,14,26.0,3,0,2005-05-22 14:00:00 +26221,736,21,9.0,11,0,2005-05-22 14:00:00 +26222,736,10,0.0,23,0,2005-05-22 14:00:00 +26223,736,39,0.0,20,0,2005-05-22 14:00:00 +26224,736,32,0.0,18,0,2005-05-22 14:00:00 +26225,736,36,4.0,14,0,2005-05-22 14:00:00 +26226,736,24,6.0,12,0,2005-05-22 14:00:00 +26227,736,38,0.0,19,0,2005-05-22 14:00:00 +26228,736,23,1.0,17,0,2005-05-22 14:00:00 +26229,736,26,0.0,21,0,2005-05-22 14:00:00 +26230,736,18,0.0,24,0,2005-05-22 14:00:00 +26231,736,1,17.0,5,0,2005-05-22 14:00:00 +26232,736,29,12.0,9,0,2005-05-22 14:00:00 +26233,737,13,15.0,11,0,2005-05-29 14:00:00 +26234,737,16,18.0,5,0,2005-05-29 14:00:00 +26235,737,34,5.0,13,0,2005-05-29 14:00:00 +26236,737,21,15.0,10,0,2005-05-29 14:00:00 +26237,737,20,17.0,6,1,2005-05-29 14:00:00 +26238,737,30,16.0,9,0,2005-05-29 14:00:00 +26239,737,31,3.0,15,0,2005-05-29 14:00:00 +26240,737,7,27.0,2,2,2005-05-29 14:00:00 +26241,737,14,27.0,3,0,2005-05-29 14:00:00 +26242,737,12,2.0,16,0,2005-05-29 14:00:00 +26243,737,17,0.0,19,0,2005-05-29 14:00:00 +26244,737,22,17.0,7,0,2005-05-29 14:00:00 +26245,737,3,59.0,1,4,2005-05-29 14:00:00 +26246,737,10,0.0,22,0,2005-05-29 14:00:00 +26247,737,38,0.0,20,0,2005-05-29 14:00:00 +26248,737,32,0.0,18,0,2005-05-29 14:00:00 +26249,737,39,0.0,21,0,2005-05-29 14:00:00 +26250,737,29,16.0,8,0,2005-05-29 14:00:00 +26251,737,1,25.0,4,0,2005-05-29 14:00:00 +26252,737,26,0.0,23,0,2005-05-29 14:00:00 +26253,737,18,0.0,24,0,2005-05-29 14:00:00 +26254,737,36,4.0,14,0,2005-05-29 14:00:00 +26255,737,24,6.0,12,0,2005-05-29 14:00:00 +26256,737,23,1.0,17,0,2005-05-29 14:00:00 +26257,738,22,20.0,8,0,2005-06-12 13:00:00 +26258,738,17,0.0,19,0,2005-06-12 13:00:00 +26259,738,30,16.0,11,0,2005-06-12 13:00:00 +26260,738,12,7.0,12,0,2005-06-12 13:00:00 +26261,738,14,27.0,3,0,2005-06-12 13:00:00 +26262,738,3,59.0,1,4,2005-06-12 13:00:00 +26263,738,20,17.0,9,1,2005-06-12 13:00:00 +26264,738,16,22.0,6,0,2005-06-12 13:00:00 +26265,738,13,17.0,10,0,2005-06-12 13:00:00 +26266,738,34,5.0,14,0,2005-06-12 13:00:00 +26267,738,21,21.0,7,0,2005-06-12 13:00:00 +26268,738,31,4.0,16,0,2005-06-12 13:00:00 +26269,738,10,0.0,23,0,2005-06-12 13:00:00 +26270,738,1,25.0,4,0,2005-06-12 13:00:00 +26271,738,32,0.0,18,0,2005-06-12 13:00:00 +26272,738,23,1.0,17,0,2005-06-12 13:00:00 +26273,738,24,6.0,13,0,2005-06-12 13:00:00 +26274,738,38,0.0,20,0,2005-06-12 13:00:00 +26275,738,36,4.0,15,0,2005-06-12 13:00:00 +26276,738,7,37.0,2,3,2005-06-12 13:00:00 +26277,738,39,0.0,22,0,2005-06-12 13:00:00 +26278,738,29,24.0,5,0,2005-06-12 13:00:00 +26279,738,26,0.0,21,0,2005-06-12 13:00:00 +26280,738,18,0.0,24,0,2005-06-12 13:00:00 +26281,739,20,17.0,9,1,2005-06-19 14:00:00 +26282,739,40,0.0,24,0,2005-06-19 14:00:00 +26283,739,23,1.0,21,0,2005-06-19 14:00:00 +26284,739,24,6.0,14,0,2005-06-19 14:00:00 +26285,739,36,4.0,18,0,2005-06-19 14:00:00 +26286,739,18,0.0,25,0,2005-06-19 14:00:00 +26287,739,26,4.0,17,0,2005-06-19 14:00:00 +26288,739,1,25.0,6,0,2005-06-19 14:00:00 +26289,739,29,34.0,3,1,2005-06-19 14:00:00 +26290,739,39,3.0,20,0,2005-06-19 14:00:00 +26291,739,32,6.0,13,0,2005-06-19 14:00:00 +26292,739,10,0.0,23,0,2005-06-19 14:00:00 +26293,739,22,20.0,8,0,2005-06-19 14:00:00 +26294,739,17,0.0,22,0,2005-06-19 14:00:00 +26295,739,12,7.0,12,0,2005-06-19 14:00:00 +26296,739,14,27.0,5,0,2005-06-19 14:00:00 +26297,739,7,37.0,2,3,2005-06-19 14:00:00 +26298,739,31,4.0,19,0,2005-06-19 14:00:00 +26299,739,30,16.0,11,0,2005-06-19 14:00:00 +26300,739,16,22.0,7,0,2005-06-19 14:00:00 +26301,739,13,17.0,10,0,2005-06-19 14:00:00 +26302,739,3,59.0,1,4,2005-06-19 14:00:00 +26303,739,21,29.0,4,0,2005-06-19 14:00:00 +26304,739,38,5.0,16,0,2005-06-19 14:00:00 +26305,739,34,5.0,15,0,2005-06-19 14:00:00 +26306,740,23,1.0,22,0,2005-07-03 14:00:00 +26307,740,40,0.0,24,0,2005-07-03 14:00:00 +26308,740,24,6.0,14,0,2005-07-03 14:00:00 +26309,740,18,0.0,25,0,2005-07-03 14:00:00 +26310,740,20,20.0,9,1,2005-07-03 14:00:00 +26311,740,21,29.0,5,0,2005-07-03 14:00:00 +26312,740,3,69.0,1,5,2005-07-03 14:00:00 +26313,740,13,17.0,10,0,2005-07-03 14:00:00 +26314,740,16,22.0,7,0,2005-07-03 14:00:00 +26315,740,30,16.0,11,0,2005-07-03 14:00:00 +26316,740,31,4.0,20,0,2005-07-03 14:00:00 +26317,740,7,45.0,2,3,2005-07-03 14:00:00 +26318,740,14,31.0,4,0,2005-07-03 14:00:00 +26319,740,12,7.0,12,0,2005-07-03 14:00:00 +26320,740,36,4.0,19,0,2005-07-03 14:00:00 +26321,740,22,22.0,8,0,2005-07-03 14:00:00 +26322,740,34,6.0,15,0,2005-07-03 14:00:00 +26323,740,10,0.0,23,0,2005-07-03 14:00:00 +26324,740,38,5.0,17,0,2005-07-03 14:00:00 +26325,740,32,6.0,13,0,2005-07-03 14:00:00 +26326,740,39,3.0,21,0,2005-07-03 14:00:00 +26327,740,29,40.0,3,1,2005-07-03 14:00:00 +26328,740,1,25.0,6,0,2005-07-03 14:00:00 +26329,740,26,4.0,18,0,2005-07-03 14:00:00 +26330,740,17,5.0,16,0,2005-07-03 14:00:00 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+26354,741,24,6.0,15,0,2005-07-10 14:00:00 +26355,741,36,4.0,19,0,2005-07-10 14:00:00 +26356,742,30,34.0,4,1,2005-07-24 14:00:00 +26357,742,7,51.0,2,3,2005-07-24 14:00:00 +26358,742,16,22.0,10,0,2005-07-24 14:00:00 +26359,742,31,4.0,20,0,2005-07-24 14:00:00 +26360,742,13,19.0,11,0,2005-07-24 14:00:00 +26361,742,37,0.0,24,0,2005-07-24 14:00:00 +26362,742,21,31.0,5,0,2005-07-24 14:00:00 +26363,742,20,30.0,7,1,2005-07-24 14:00:00 +26364,742,40,0.0,25,0,2005-07-24 14:00:00 +26365,742,3,87.0,1,6,2005-07-24 14:00:00 +26366,742,14,31.0,6,0,2005-07-24 14:00:00 +26367,742,36,4.0,19,0,2005-07-24 14:00:00 +26368,742,17,15.0,12,0,2005-07-24 14:00:00 +26369,742,24,6.0,15,0,2005-07-24 14:00:00 +26370,742,12,8.0,13,0,2005-07-24 14:00:00 +26371,742,18,0.0,26,0,2005-07-24 14:00:00 +26372,742,26,4.0,18,0,2005-07-24 14:00:00 +26373,742,29,47.0,3,1,2005-07-24 14:00:00 +26374,742,1,25.0,9,0,2005-07-24 14:00:00 +26375,742,32,6.0,14,0,2005-07-24 14:00:00 +26376,742,38,5.0,17,0,2005-07-24 14:00:00 +26377,742,10,0.0,23,0,2005-07-24 14:00:00 +26378,742,34,6.0,16,0,2005-07-24 14:00:00 +26379,742,22,26.0,8,0,2005-07-24 14:00:00 +26380,742,39,3.0,21,0,2005-07-24 14:00:00 +26381,742,23,1.0,22,0,2005-07-24 14:00:00 +26382,743,13,19.0,12,0,2005-07-31 14:00:00 +26383,743,30,34.0,5,1,2005-07-31 14:00:00 +26384,743,16,24.0,10,0,2005-07-31 14:00:00 +26385,743,31,4.0,20,0,2005-07-31 14:00:00 +26386,743,20,30.0,8,1,2005-07-31 14:00:00 +26387,743,37,0.0,24,0,2005-07-31 14:00:00 +26388,743,40,0.0,25,0,2005-07-31 14:00:00 +26389,743,3,87.0,1,6,2005-07-31 14:00:00 +26390,743,14,36.0,4,0,2005-07-31 14:00:00 +26391,743,21,31.0,7,0,2005-07-31 14:00:00 +26392,743,17,19.0,11,0,2005-07-31 14:00:00 +26393,743,23,1.0,22,0,2005-07-31 14:00:00 +26394,743,24,6.0,15,0,2005-07-31 14:00:00 +26395,743,36,4.0,19,0,2005-07-31 14:00:00 +26396,743,18,0.0,26,0,2005-07-31 14:00:00 +26397,743,26,4.0,18,0,2005-07-31 14:00:00 +26398,743,1,28.0,9,0,2005-07-31 14:00:00 +26399,743,12,8.0,13,0,2005-07-31 14:00:00 +26400,743,7,61.0,2,4,2005-07-31 14:00:00 +26401,743,29,55.0,3,1,2005-07-31 14:00:00 +26402,743,39,3.0,21,0,2005-07-31 14:00:00 +26403,743,32,6.0,14,0,2005-07-31 14:00:00 +26404,743,38,5.0,17,0,2005-07-31 14:00:00 +26405,743,10,1.0,23,0,2005-07-31 14:00:00 +26406,743,34,6.0,16,0,2005-07-31 14:00:00 +26407,743,22,32.0,6,0,2005-07-31 14:00:00 +26408,744,23,1.0,23,0,2005-08-21 15:00:00 +26409,744,37,0.0,24,0,2005-08-21 15:00:00 +26410,744,40,0.0,25,0,2005-08-21 15:00:00 +26411,744,20,35.0,6,1,2005-08-21 15:00:00 +26412,744,21,31.0,8,0,2005-08-21 15:00:00 +26413,744,3,95.0,1,6,2005-08-21 15:00:00 +26414,744,16,24.0,10,0,2005-08-21 15:00:00 +26415,744,30,40.0,4,1,2005-08-21 15:00:00 +26416,744,31,5.0,18,0,2005-08-21 15:00:00 +26417,744,13,21.0,12,0,2005-08-21 15:00:00 +26418,744,14,39.0,5,0,2005-08-21 15:00:00 +26419,744,24,6.0,15,0,2005-08-21 15:00:00 +26420,744,36,4.0,20,0,2005-08-21 15:00:00 +26421,744,18,0.0,26,0,2005-08-21 15:00:00 +26422,744,7,71.0,2,5,2005-08-21 15:00:00 +26423,744,1,28.0,9,0,2005-08-21 15:00:00 +26424,744,29,55.0,3,1,2005-08-21 15:00:00 +26425,744,39,3.0,21,0,2005-08-21 15:00:00 +26426,744,26,4.0,19,0,2005-08-21 15:00:00 +26427,744,38,5.0,17,0,2005-08-21 15:00:00 +26428,744,10,1.0,22,0,2005-08-21 15:00:00 +26429,744,34,6.0,16,0,2005-08-21 15:00:00 +26430,744,22,32.0,7,0,2005-08-21 15:00:00 +26431,744,17,23.0,11,0,2005-08-21 15:00:00 +26432,744,12,8.0,13,0,2005-08-21 15:00:00 +26433,744,32,6.0,14,0,2005-08-21 15:00:00 +26434,745,30,50.0,4,2,2005-09-04 14:00:00 +26435,745,37,0.0,25,0,2005-09-04 14:00:00 +26436,745,41,2.0,22,0,2005-09-04 14:00:00 +26437,745,20,41.0,6,1,2005-09-04 14:00:00 +26438,745,21,31.0,8,0,2005-09-04 14:00:00 +26439,745,3,103.0,1,6,2005-09-04 14:00:00 +26440,745,13,21.0,12,0,2005-09-04 14:00:00 +26441,745,16,24.0,11,0,2005-09-04 14:00:00 +26442,745,31,5.0,18,0,2005-09-04 14:00:00 +26443,745,17,24.0,10,0,2005-09-04 14:00:00 +26444,745,14,43.0,5,0,2005-09-04 14:00:00 +26445,745,7,76.0,2,5,2005-09-04 14:00:00 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+26469,746,16,29.0,10,0,2005-09-11 14:00:00 +26470,746,30,50.0,4,2,2005-09-11 14:00:00 +26471,746,13,21.0,12,0,2005-09-11 14:00:00 +26472,746,3,111.0,1,6,2005-09-11 14:00:00 +26473,746,21,35.0,8,0,2005-09-11 14:00:00 +26474,746,20,41.0,6,1,2005-09-11 14:00:00 +26475,746,41,2.0,22,0,2005-09-11 14:00:00 +26476,746,37,0.0,25,0,2005-09-11 14:00:00 +26477,746,31,5.0,18,0,2005-09-11 14:00:00 +26478,746,39,3.0,21,0,2005-09-11 14:00:00 +26479,746,14,43.0,5,0,2005-09-11 14:00:00 +26480,746,26,4.0,19,0,2005-09-11 14:00:00 +26481,746,40,0.0,26,0,2005-09-11 14:00:00 +26482,746,23,1.0,24,0,2005-09-11 14:00:00 +26483,746,29,55.0,3,1,2005-09-11 14:00:00 +26484,746,1,28.0,11,0,2005-09-11 14:00:00 +26485,746,24,6.0,16,0,2005-09-11 14:00:00 +26486,746,36,4.0,20,0,2005-09-11 14:00:00 +26487,746,18,0.0,27,0,2005-09-11 14:00:00 +26488,747,31,5.0,18,0,2005-09-25 14:00:00 +26489,747,30,60.0,3,3,2005-09-25 14:00:00 +26490,747,16,29.0,10,0,2005-09-25 14:00:00 +26491,747,13,21.0,12,0,2005-09-25 14:00:00 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+28079,818,1,15.0,14,0,2009-10-18 16:00:00 +28080,818,15,5.0,16,0,2009-10-18 16:00:00 +28081,818,66,5.0,17,0,2009-10-18 16:00:00 +28082,818,2,34.5,7,0,2009-10-18 16:00:00 +28083,818,3,26.0,9,0,2009-10-18 16:00:00 +28084,818,9,24.0,10,0,2009-10-18 16:00:00 +28085,818,14,30.5,8,0,2009-10-18 16:00:00 +28086,818,21,72.0,3,2,2009-10-18 16:00:00 +28087,818,17,89.0,1,6,2009-10-18 16:00:00 +28088,818,19,74.0,2,3,2009-10-18 16:00:00 +28089,818,6,2.0,18,0,2009-10-18 16:00:00 +28090,819,154,3.0,18,0,2009-11-01 11:00:00 +28091,819,23,0.0,22,0,2009-11-01 11:00:00 +28092,819,4,22.0,12,0,2009-11-01 11:00:00 +28093,819,152,0.0,24,0,2009-11-01 11:00:00 +28094,819,153,0.0,23,0,2009-11-01 11:00:00 +28095,819,17,95.0,1,6,2009-11-01 11:00:00 +28096,819,0,49.0,5,2,2009-11-01 11:00:00 +28097,819,21,77.0,3,2,2009-11-01 11:00:00 +28098,819,14,32.5,8,0,2009-11-01 11:00:00 +28099,819,9,24.0,10,0,2009-11-01 11:00:00 +28100,819,3,26.0,9,0,2009-11-01 11:00:00 +28101,819,2,34.5,7,0,2009-11-01 11:00:00 +28102,819,66,6.0,16,0,2009-11-01 11:00:00 +28103,819,5,0.0,20,0,2009-11-01 11:00:00 +28104,819,15,5.0,17,0,2009-11-01 11:00:00 +28105,819,1,19.0,13,0,2009-11-01 11:00:00 +28106,819,20,8.0,15,0,2009-11-01 11:00:00 +28107,819,16,69.5,4,2,2009-11-01 11:00:00 +28108,819,19,84.0,2,4,2009-11-01 11:00:00 +28109,819,8,17.0,14,0,2009-11-01 11:00:00 +28110,819,7,48.0,6,1,2009-11-01 11:00:00 +28111,819,68,0.0,25,0,2009-11-01 11:00:00 +28112,819,11,0.0,21,0,2009-11-01 11:00:00 +28113,819,6,2.0,19,0,2009-11-01 11:00:00 +28114,819,12,22.0,11,0,2009-11-01 11:00:00 diff --git a/scripts/import_relbench.sh b/scripts/import_relbench.sh index 39139544..5ff50963 100644 --- a/scripts/import_relbench.sh +++ b/scripts/import_relbench.sh @@ -4,33 +4,61 @@ set -e CONTAINER_NAME="plexe-clone-postgres-1" DB_USER="mlflow" +# Thiết lập file log +LOG_DIR="./logs" +mkdir -p "$LOG_DIR" +LOG_FILE="$LOG_DIR/import_$(date +%Y%m%d_%H%M%S).log" + +# Hàm log - ghi cả ra console và file +log() { + local message="[$(date '+%Y-%m-%d %H:%M:%S')] $1" + echo "$message" | tee -a "$LOG_FILE" +} + +log_error() { + local message="[$(date '+%Y-%m-%d %H:%M:%S')] ERROR: $1" + echo "$message" | tee -a "$LOG_FILE" >&2 +} + +log_step() { + local message="[$(date '+%Y-%m-%d %H:%M:%S')] STEP: $1" + echo "$message" | tee -a "$LOG_FILE" +} + print_header() { - echo "" - echo "=========================================" - echo "$1" - echo "=========================================" - echo "" + local header="=========================================" + echo "" | tee -a "$LOG_FILE" + echo "$header" | tee -a "$LOG_FILE" + echo "$1" | tee -a "$LOG_FILE" + echo "$header" | tee -a "$LOG_FILE" + echo "" | tee -a "$LOG_FILE" } print_error() { - echo "ERROR: $1" >&2 + log_error "$1" } print_info() { - echo "INFO: $1" + log "INFO: $1" } cleanup() { + log_step "Starting cleanup process" + if [ "$KEEP_DATA" != "true" ]; then print_header "Cleanup" print_info "Removing CSV files from container..." - docker exec $CONTAINER_NAME bash -c "rm -f /tmp/*.csv /tmp/import_*.sql" 2>/dev/null || true + if docker exec $CONTAINER_NAME bash -c "rm -f /tmp/*.csv /tmp/import_*.sql" 2>/dev/null; then + log "CSV files removed from container successfully" + else + log "Failed to remove CSV files from container (may not exist)" + fi if [ -d "$DATA_DIR" ]; then print_info "Removing local data directory: $DATA_DIR" rm -rf "$DATA_DIR" - echo "Data directory removed" + log "Data directory removed: $DATA_DIR" fi if [ "$REMOVE_RELBENCH_CACHE" = "true" ]; then @@ -38,17 +66,19 @@ cleanup() { if [ -d "$RELBENCH_CACHE" ]; then print_info "Removing RelBench cache: $RELBENCH_CACHE" rm -rf "$RELBENCH_CACHE" - echo "RelBench cache removed" + log "RelBench cache removed" fi fi - echo "Cleanup complete" + echo "Cleanup complete" | tee -a "$LOG_FILE" else print_info "Keeping data files (KEEP_DATA=true)" fi + + log_step "Cleanup completed" } -trap 'print_error "Script failed on line $LINENO"; cleanup; exit 1' ERR +trap 'log_error "Script failed on line $LINENO with exit code $?"; cleanup; exit 1' ERR trap 'cleanup' EXIT show_usage() { @@ -75,10 +105,18 @@ Supported datasets: rel-f1, rel-amazon, rel-hm, rel-stack, rel-trial, rel-event, rel-avito, rel-salt, rel-arxiv, rel-ratebeer +Logs are saved to: $LOG_DIR/ + EOF exit 0 } +# Bắt đầu logging +log "==========================================" +log "Script started: $0" +log "Arguments: $*" +log "==========================================" + if [ $# -eq 0 ]; then show_usage fi @@ -89,22 +127,28 @@ OUTPUT_DIR="" KEEP_DATA="false" REMOVE_RELBENCH_CACHE="false" +log_step "Parsing command line arguments" + while [ $# -gt 0 ]; do case "$1" in --db-name) DB_NAME="$2" + log "Setting DB_NAME=$DB_NAME" shift 2 ;; --output-dir) OUTPUT_DIR="$2" + log "Setting OUTPUT_DIR=$OUTPUT_DIR" shift 2 ;; --keep-data) KEEP_DATA="true" + log "Setting KEEP_DATA=true" shift ;; --remove-cache) REMOVE_RELBENCH_CACHE="true" + log "Setting REMOVE_RELBENCH_CACHE=true" shift ;; --help) @@ -117,6 +161,7 @@ while [ $# -gt 0 ]; do *) if [ -z "$DATASET_NAME" ]; then DATASET_NAME="$1" + log "Setting DATASET_NAME=$DATASET_NAME" else print_error "Multiple dataset names provided" show_usage @@ -132,13 +177,16 @@ if [ -z "$DATASET_NAME" ]; then fi DATASET_SHORT=$(echo "$DATASET_NAME" | sed 's/^rel-//') +log "DATASET_SHORT=$DATASET_SHORT" if [ -z "$DB_NAME" ]; then DB_NAME="$DATASET_SHORT" + log "DB_NAME set to default: $DB_NAME" fi if [ -z "$OUTPUT_DIR" ]; then OUTPUT_DIR="./${DATASET_SHORT}_data" + log "OUTPUT_DIR set to default: $OUTPUT_DIR" fi DATA_DIR="$OUTPUT_DIR" @@ -146,51 +194,79 @@ SQL_FILE="$DATA_DIR/import_${DATASET_SHORT}.sql" print_header "RelBench Import - $DATASET_NAME" -echo "Configuration:" -echo " Dataset: $DATASET_NAME" -echo " Database: $DB_NAME" -echo " Container: $CONTAINER_NAME" -echo " Data dir: $DATA_DIR" -echo "" +echo "Configuration:" | tee -a "$LOG_FILE" +echo " Dataset: $DATASET_NAME" | tee -a "$LOG_FILE" +echo " Database: $DB_NAME" | tee -a "$LOG_FILE" +echo " Container: $CONTAINER_NAME" | tee -a "$LOG_FILE" +echo " Data dir: $DATA_DIR" | tee -a "$LOG_FILE" +echo " Log file: $LOG_FILE" | tee -a "$LOG_FILE" +echo "" | tee -a "$LOG_FILE" +log_step "Checking Python installation" if ! command -v python3 &> /dev/null; then print_error "Python 3 is not installed" exit 1 fi -echo "Python 3 is available" +log "Python 3 is available: $(python3 --version)" +log_step "Checking Python dependencies" print_info "Checking Python dependencies..." + if ! python3 -c "import relbench" 2>/dev/null; then print_info "Installing relbench..." - pip install relbench + if pip install relbench >> "$LOG_FILE" 2>&1; then + log "relbench installed successfully" + else + log_error "Failed to install relbench" + exit 1 + fi +else + log "relbench is already installed" fi + if ! python3 -c "import pandas" 2>/dev/null; then print_info "Installing pandas..." - pip install pandas + if pip install pandas >> "$LOG_FILE" 2>&1; then + log "pandas installed successfully" + else + log_error "Failed to install pandas" + exit 1 + fi +else + log "pandas is already installed" fi -echo "Python dependencies OK" +echo "Python dependencies OK" | tee -a "$LOG_FILE" print_header "Step 1: Verify PostgreSQL Container" +log_step "Verifying PostgreSQL container" print_info "Checking container: $CONTAINER_NAME" + if ! docker ps | grep -q $CONTAINER_NAME; then print_error "Container '$CONTAINER_NAME' is not running" print_info "Start it with: docker start $CONTAINER_NAME" exit 1 fi -echo "Container is running" +log "Container $CONTAINER_NAME is running" print_header "Step 2: Prepare Database" +log_step "Preparing database" print_info "Checking database: $DB_NAME" + if ! docker exec $CONTAINER_NAME psql -U $DB_USER -lqt | cut -d \| -f 1 | grep -qw $DB_NAME; then print_info "Database '$DB_NAME' does not exist, creating..." - docker exec $CONTAINER_NAME psql -U $DB_USER -d postgres -c "CREATE DATABASE $DB_NAME;" - echo "Database '$DB_NAME' created" + if docker exec $CONTAINER_NAME psql -U $DB_USER -d postgres -c "CREATE DATABASE $DB_NAME;" >> "$LOG_FILE" 2>&1; then + log "Database '$DB_NAME' created successfully" + else + log_error "Failed to create database '$DB_NAME'" + exit 1 + fi else - echo "Database '$DB_NAME' already exists" + log "Database '$DB_NAME' already exists" print_info "Existing tables will be dropped and recreated" fi print_header "Step 3: Download Dataset and Generate SQL" +log_step "Downloading dataset and generating SQL" print_info "Running Python script to download $DATASET_NAME dataset..." if [ ! -f "generate_relbench_sql.py" ]; then @@ -198,7 +274,13 @@ if [ ! -f "generate_relbench_sql.py" ]; then exit 1 fi -python3 generate_relbench_sql.py "$DATASET_NAME" --output-dir "$DATA_DIR" +log "Executing: python3 generate_relbench_sql.py $DATASET_NAME --output-dir $DATA_DIR" +if python3 generate_relbench_sql.py "$DATASET_NAME" --output-dir "$DATA_DIR" >> "$LOG_FILE" 2>&1; then + log "Python script executed successfully" +else + log_error "Python script failed with exit code $?" + exit 1 +fi if [ ! -d "$DATA_DIR" ]; then print_error "Data directory not created, Python script may have failed" @@ -210,35 +292,55 @@ if [ ! -f "$SQL_FILE" ]; then exit 1 fi -echo "Dataset downloaded and SQL generated" +log "Dataset downloaded and SQL generated successfully" CSV_COUNT=$(ls -1 $DATA_DIR/*.csv 2>/dev/null | wc -l) print_info "Found $CSV_COUNT CSV files" +log "CSV files count: $CSV_COUNT" print_header "Step 4: Copy Files to Container" +log_step "Copying files to container" print_info "Copying CSV files to container..." + for csv_file in $DATA_DIR/*.csv; do if [ -f "$csv_file" ]; then filename=$(basename "$csv_file") - docker cp "$csv_file" $CONTAINER_NAME:/tmp/ - echo "Copied $filename" + if docker cp "$csv_file" $CONTAINER_NAME:/tmp/ >> "$LOG_FILE" 2>&1; then + log "Copied $filename to container" + echo "Copied $filename" + else + log_error "Failed to copy $filename" + exit 1 + fi fi done print_info "Copying SQL script to container..." -docker cp "$SQL_FILE" $CONTAINER_NAME:/tmp/ -echo "SQL script copied" +if docker cp "$SQL_FILE" $CONTAINER_NAME:/tmp/ >> "$LOG_FILE" 2>&1; then + log "SQL script copied to container successfully" + echo "SQL script copied" +else + log_error "Failed to copy SQL script to container" + exit 1 +fi print_header "Step 5: Import Data into PostgreSQL" +log_step "Importing data into PostgreSQL" print_info "Running SQL import script..." -echo "=========================================" +echo "=========================================" | tee -a "$LOG_FILE" -docker exec -i $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME -f /tmp/import_${DATASET_SHORT}.sql +if docker exec -i $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME -f /tmp/import_${DATASET_SHORT}.sql 2>&1 | tee -a "$LOG_FILE"; then + log "SQL import completed successfully" +else + log_error "SQL import failed with exit code $?" + exit 1 +fi -echo "=========================================" -echo "Data import completed" +echo "=========================================" | tee -a "$LOG_FILE" +echo "Data import completed" | tee -a "$LOG_FILE" print_header "Step 6: Verify Import" +log_step "Verifying import" print_info "Checking table counts..." docker exec $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME -c " @@ -249,23 +351,23 @@ SELECT FROM pg_stat_user_tables WHERE schemaname = 'public' ORDER BY n_live_tup DESC; -" +" 2>&1 | tee -a "$LOG_FILE" print_header "Import Complete" -echo "Database Details:" -echo " Container: $CONTAINER_NAME" -echo " Database: $DB_NAME" -echo " User: $DB_USER" -echo "" -echo "Connect to database:" -echo " docker exec -it $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME" -echo "" -echo "Example queries:" -echo " \\dt -- List all tables" -echo " \\d table_name -- Show table structure" -echo " SELECT COUNT(*) FROM table_name;" -echo "" +echo "Database Details:" | tee -a "$LOG_FILE" +echo " Container: $CONTAINER_NAME" | tee -a "$LOG_FILE" +echo " Database: $DB_NAME" | tee -a "$LOG_FILE" +echo " User: $DB_USER" | tee -a "$LOG_FILE" +echo "" | tee -a "$LOG_FILE" +echo "Connect to database:" | tee -a "$LOG_FILE" +echo " docker exec -it $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME" | tee -a "$LOG_FILE" +echo "" | tee -a "$LOG_FILE" +echo "Example queries:" | tee -a "$LOG_FILE" +echo " \\dt -- List all tables" | tee -a "$LOG_FILE" +echo " \\d table_name -- Show table structure" | tee -a "$LOG_FILE" +echo " SELECT COUNT(*) FROM table_name;" | tee -a "$LOG_FILE" +echo "" | tee -a "$LOG_FILE" if [ "$KEEP_DATA" = "false" ]; then read -p "Keep data files? (y/N) " -n 1 -r @@ -284,4 +386,9 @@ if [ "$KEEP_DATA" = "false" ] && [ "$REMOVE_RELBENCH_CACHE" = "false" ]; then fi fi +log "==========================================" +log "Script completed successfully" +log "Log file: $LOG_FILE" +log "==========================================" + print_header "Done" \ No newline at end of file diff --git a/scripts/main.py b/scripts/main.py new file mode 100644 index 00000000..00f55181 --- /dev/null +++ b/scripts/main.py @@ -0,0 +1,6 @@ +def main(): + print("Hello from scripts!") + + +if __name__ == "__main__": + main() diff --git a/scripts/pyproject.toml b/scripts/pyproject.toml new file mode 100644 index 00000000..5913644f --- /dev/null +++ b/scripts/pyproject.toml @@ -0,0 +1,7 @@ +[project] +name = "scripts" +version = "0.1.0" +description = "Add your description here" +readme = "README.md" +requires-python = ">=3.10" +dependencies = [] diff --git a/scripts/uv.lock b/scripts/uv.lock new file mode 100644 index 00000000..a5cd35a6 --- /dev/null +++ b/scripts/uv.lock @@ -0,0 +1,8 @@ +version = 1 +revision = 3 +requires-python = ">=3.10" + +[[package]] +name = "scripts" +version = "0.1.0" +source = { virtual = "." } From 32be77fefadf34a517fabc6d7011ec249443b81b Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Sat, 17 Jan 2026 16:32:03 +0700 Subject: [PATCH 35/42] ??? --- scripts/f1_data/circuits.csv | 78 - scripts/f1_data/constructor_results.csv | 9409 ------- scripts/f1_data/constructor_standings.csv | 10171 ------- scripts/f1_data/constructors.csv | 212 - scripts/f1_data/drivers.csv | 858 - scripts/f1_data/import_f1.sql | 490 - scripts/f1_data/qualifying.csv | 4083 --- scripts/f1_data/races.csv | 821 - scripts/f1_data/results.csv | 20324 -------------- scripts/f1_data/standings.csv | 28116 -------------------- 10 files changed, 74562 deletions(-) delete mode 100644 scripts/f1_data/circuits.csv delete mode 100644 scripts/f1_data/constructor_results.csv delete mode 100644 scripts/f1_data/constructor_standings.csv delete mode 100644 scripts/f1_data/constructors.csv delete mode 100644 scripts/f1_data/drivers.csv delete mode 100644 scripts/f1_data/import_f1.sql delete mode 100644 scripts/f1_data/qualifying.csv delete mode 100644 scripts/f1_data/races.csv delete mode 100644 scripts/f1_data/results.csv delete mode 100644 scripts/f1_data/standings.csv diff --git a/scripts/f1_data/circuits.csv b/scripts/f1_data/circuits.csv deleted file mode 100644 index 0e8f012c..00000000 --- a/scripts/f1_data/circuits.csv +++ /dev/null @@ -1,78 +0,0 @@ -circuitId,circuitRef,name,location,country,lat,lng,alt -0,albert_park,Albert Park Grand Prix Circuit,Melbourne,Australia,-37.8497,144.968,10.0 -1,sepang,Sepang International Circuit,Kuala Lumpur,Malaysia,2.76083,101.738,18.0 -2,bahrain,Bahrain International Circuit,Sakhir,Bahrain,26.0325,50.5106,7.0 -3,catalunya,Circuit de Barcelona-Catalunya,Montmeló,Spain,41.57,2.26111,109.0 -4,istanbul,Istanbul Park,Istanbul,Turkey,40.9517,29.405,130.0 -5,monaco,Circuit de Monaco,Monte-Carlo,Monaco,43.7347,7.42056,7.0 -6,villeneuve,Circuit Gilles Villeneuve,Montreal,Canada,45.5,-73.5228,13.0 -7,magny_cours,Circuit de Nevers Magny-Cours,Magny Cours,France,46.8642,3.16361,228.0 -8,silverstone,Silverstone Circuit,Silverstone,UK,52.0786,-1.01694,153.0 -9,hockenheimring,Hockenheimring,Hockenheim,Germany,49.3278,8.56583,103.0 -10,hungaroring,Hungaroring,Budapest,Hungary,47.5789,19.2486,264.0 -11,valencia,Valencia Street Circuit,Valencia,Spain,39.4589,-0.331667,4.0 -12,spa,Circuit de Spa-Francorchamps,Spa,Belgium,50.4372,5.97139,401.0 -13,monza,Autodromo Nazionale di Monza,Monza,Italy,45.6156,9.28111,162.0 -14,marina_bay,Marina Bay Street Circuit,Marina Bay,Singapore,1.2914,103.864,18.0 -15,fuji,Fuji Speedway,Oyama,Japan,35.3717,138.927,583.0 -16,shanghai,Shanghai International Circuit,Shanghai,China,31.3389,121.22,5.0 -17,interlagos,Autódromo José Carlos Pace,São Paulo,Brazil,-23.7036,-46.6997,785.0 -18,indianapolis,Indianapolis Motor Speedway,Indianapolis,USA,39.795,-86.2347,223.0 -19,nurburgring,Nürburgring,Nürburg,Germany,50.3356,6.9475,578.0 -20,imola,Autodromo Enzo e Dino Ferrari,Imola,Italy,44.3439,11.7167,37.0 -21,suzuka,Suzuka Circuit,Suzuka,Japan,34.8431,136.541,45.0 -22,vegas,Las Vegas Strip Street Circuit,Las Vegas,United States,36.1147,-115.173, -23,yas_marina,Yas Marina Circuit,Abu Dhabi,UAE,24.4672,54.6031,3.0 -24,galvez,Autódromo Juan y Oscar Gálvez,Buenos Aires,Argentina,-34.6943,-58.4593,8.0 -25,jerez,Circuito de Jerez,Jerez de la Frontera,Spain,36.7083,-6.03417,37.0 -26,estoril,Autódromo do Estoril,Estoril,Portugal,38.7506,-9.39417,130.0 -27,okayama,Okayama International Circuit,Okayama,Japan,34.915,134.221,266.0 -28,adelaide,Adelaide Street Circuit,Adelaide,Australia,-34.9272,138.617,58.0 -29,kyalami,Kyalami,Midrand,South Africa,-25.9894,28.0767,1460.0 -30,donington,Donington Park,Castle Donington,UK,52.8306,-1.37528,88.0 -31,rodriguez,Autódromo Hermanos Rodríguez,Mexico City,Mexico,19.4042,-99.0907,2227.0 -32,phoenix,Phoenix street circuit,Phoenix,USA,33.4479,-112.075,345.0 -33,ricard,Circuit Paul Ricard,Le Castellet,France,43.2506,5.79167,432.0 -34,yeongam,Korean International Circuit,Yeongam County,Korea,34.7333,126.417,0.0 -35,jacarepagua,Autódromo Internacional Nelson Piquet,Rio de Janeiro,Brazil,-22.9756,-43.395,1126.0 -36,detroit,Detroit Street Circuit,Detroit,USA,42.3298,-83.0401,177.0 -37,brands_hatch,Brands Hatch,Kent,UK,51.3569,0.263056,145.0 -38,zandvoort,Circuit Park Zandvoort,Zandvoort,Netherlands,52.3888,4.54092,6.0 -39,zolder,Zolder,Heusden-Zolder,Belgium,50.9894,5.25694,36.0 -40,dijon,Dijon-Prenois,Dijon,France,47.3625,4.89913,484.0 -41,dallas,Fair Park,Dallas,USA,32.7774,-96.7587,139.0 -42,long_beach,Long Beach,California,USA,33.7651,-118.189,12.0 -43,las_vegas,Las Vegas Street Circuit,Nevada,USA,36.1162,-115.174,639.0 -44,jarama,Jarama,Madrid,Spain,40.6171,-3.58558,609.0 -45,watkins_glen,Watkins Glen,New York State,USA,42.3369,-76.9272,485.0 -46,anderstorp,Scandinavian Raceway,Anderstorp,Sweden,57.2653,13.6042,153.0 -47,mosport,Mosport International Raceway,Ontario,Canada,44.0481,-78.6756,332.0 -48,montjuic,Montjuïc,Barcelona,Spain,41.3664,2.15167,79.0 -49,nivelles,Nivelles-Baulers,Brussels,Belgium,50.6211,4.32694,139.0 -50,charade,Charade Circuit,Clermont-Ferrand,France,45.7472,3.03889,790.0 -51,tremblant,Circuit Mont-Tremblant,Quebec,Canada,46.1877,-74.6099,214.0 -52,essarts,Rouen-Les-Essarts,Rouen,France,49.3306,1.00458,81.0 -53,lemans,Le Mans,Le Mans,France,47.95,0.224231,67.0 -54,reims,Reims-Gueux,Reims,France,49.2542,3.93083,88.0 -55,george,Prince George Circuit,Eastern Cape Province,South Africa,-33.0486,27.8736,15.0 -56,zeltweg,Zeltweg,Styria,Austria,47.2039,14.7478,676.0 -57,aintree,Aintree,Liverpool,UK,53.4769,-2.94056,20.0 -58,boavista,Circuito da Boavista,Oporto,Portugal,41.1705,-8.67325,28.0 -59,riverside,Riverside International Raceway,California,USA,33.937,-117.273,470.0 -60,avus,AVUS,Berlin,Germany,52.4806,13.2514,53.0 -61,monsanto,Monsanto Park Circuit,Lisbon,Portugal,38.7197,-9.20306,158.0 -62,sebring,Sebring International Raceway,Florida,USA,27.4547,-81.3483,18.0 -63,ain-diab,Ain Diab,Casablanca,Morocco,33.5786,-7.6875,19.0 -64,pescara,Pescara Circuit,Pescara,Italy,42.475,14.1508,129.0 -65,bremgarten,Circuit Bremgarten,Bern,Switzerland,46.9589,7.40194,551.0 -66,pedralbes,Circuit de Pedralbes,Barcelona,Spain,41.3903,2.11667,85.0 -67,buddh,Buddh International Circuit,Uttar Pradesh,India,28.3487,77.5331,194.0 -68,americas,Circuit of the Americas,Austin,USA,30.1328,-97.6411,161.0 -69,red_bull_ring,Red Bull Ring,Spielberg,Austria,47.2197,14.7647,678.0 -70,sochi,Sochi Autodrom,Sochi,Russia,43.4057,39.9578,2.0 -71,baku,Baku City Circuit,Baku,Azerbaijan,40.3725,49.8533,-7.0 -72,portimao,Autódromo Internacional do Algarve,Portimão,Portugal,37.227,-8.6267,108.0 -73,mugello,Autodromo Internazionale del Mugello,Mugello,Italy,43.9975,11.3719,255.0 -74,jeddah,Jeddah Corniche Circuit,Jeddah,Saudi Arabia,21.6319,39.1044,15.0 -75,losail,Losail International Circuit,Al Daayen,Qatar,25.49,51.4542, -76,miami,Miami International Autodrome,Miami,USA,25.9581,-80.2389, diff --git a/scripts/f1_data/constructor_results.csv b/scripts/f1_data/constructor_results.csv deleted file mode 100644 index 9588f657..00000000 --- a/scripts/f1_data/constructor_results.csv +++ /dev/null @@ -1,9409 +0,0 @@ -constructorResultsId,raceId,constructorId,points,date -0,48,103,13.0,1956-01-22 00:00:00 -1,48,5,12.0,1956-01-22 00:00:00 -2,54,126,0.0,1956-08-05 00:00:00 -3,54,103,15.0,1956-08-05 00:00:00 -4,54,5,9.0,1956-08-05 00:00:00 -5,64,85,8.0,1958-01-19 00:00:00 -6,64,5,6.0,1958-01-19 00:00:00 -7,64,103,3.0,1958-01-19 00:00:00 -8,65,125,0.0,1958-05-18 00:00:00 -9,65,123,0.0,1958-05-18 00:00:00 -10,65,103,0.0,1958-05-18 00:00:00 -11,65,31,0.0,1958-05-18 00:00:00 -12,65,116,0.0,1958-05-18 00:00:00 -13,65,5,6.0,1958-05-18 00:00:00 -14,65,85,8.0,1958-05-18 00:00:00 -15,65,64,2.0,1958-05-18 00:00:00 -16,66,93,0.0,1958-05-26 00:00:00 -17,66,103,0.0,1958-05-26 00:00:00 -18,66,5,2.0,1958-05-26 00:00:00 -19,66,31,0.0,1958-05-26 00:00:00 -20,66,64,6.0,1958-05-26 00:00:00 -21,66,116,8.0,1958-05-26 00:00:00 -22,66,85,3.0,1958-05-26 00:00:00 -23,68,103,0.0,1958-06-15 00:00:00 -24,68,116,8.0,1958-06-15 00:00:00 -25,68,5,6.0,1958-06-15 00:00:00 -26,68,31,3.0,1958-06-15 00:00:00 -27,68,64,2.0,1958-06-15 00:00:00 -28,68,85,0.0,1958-06-15 00:00:00 -29,69,31,0.0,1958-07-06 00:00:00 -30,69,103,3.0,1958-07-06 00:00:00 -31,69,64,0.0,1958-07-06 00:00:00 -32,69,85,0.0,1958-07-06 00:00:00 -33,69,5,8.0,1958-07-06 00:00:00 -34,69,116,6.0,1958-07-06 00:00:00 -35,70,5,8.0,1958-07-19 00:00:00 -36,70,85,4.0,1958-07-19 00:00:00 -37,70,116,3.0,1958-07-19 00:00:00 -38,70,64,2.0,1958-07-19 00:00:00 -39,70,103,0.0,1958-07-19 00:00:00 -40,70,31,0.0,1958-07-19 00:00:00 -41,70,123,0.0,1958-07-19 00:00:00 -42,71,103,0.0,1958-08-03 00:00:00 -43,71,64,0.0,1958-08-03 00:00:00 -44,71,93,0.0,1958-08-03 00:00:00 -45,71,31,0.0,1958-08-03 00:00:00 -46,71,85,6.0,1958-08-03 00:00:00 -47,71,116,8.0,1958-08-03 00:00:00 -48,71,5,3.0,1958-08-03 00:00:00 -49,72,116,8.0,1958-08-24 00:00:00 -50,72,5,6.0,1958-08-24 00:00:00 -51,72,64,3.0,1958-08-24 00:00:00 -52,72,85,0.0,1958-08-24 00:00:00 -53,72,103,0.0,1958-08-24 00:00:00 -54,72,31,0.0,1958-08-24 00:00:00 -55,73,31,0.0,1958-09-07 00:00:00 -56,73,116,8.0,1958-09-07 00:00:00 -57,73,5,6.0,1958-09-07 00:00:00 -58,73,103,0.0,1958-09-07 00:00:00 -59,73,85,2.0,1958-09-07 00:00:00 -60,73,64,0.0,1958-09-07 00:00:00 -61,74,64,5.0,1958-10-19 00:00:00 -62,74,103,0.0,1958-10-19 00:00:00 -63,74,85,0.0,1958-10-19 00:00:00 -64,74,116,9.0,1958-10-19 00:00:00 -65,74,31,0.0,1958-10-19 00:00:00 -66,74,5,10.0,1958-10-19 00:00:00 -67,75,64,0.0,1959-05-10 00:00:00 -68,75,93,0.0,1959-05-10 00:00:00 -69,75,103,0.0,1959-05-10 00:00:00 -70,75,167,8.0,1959-05-10 00:00:00 -71,75,5,6.0,1959-05-10 00:00:00 -72,75,163,0.0,1959-05-10 00:00:00 -73,75,31,0.0,1959-05-10 00:00:00 -74,76,111,0.0,1959-05-30 00:00:00 -75,76,106,3.0,1959-05-30 00:00:00 -76,76,105,8.0,1959-05-30 00:00:00 -77,76,108,5.0,1959-05-30 00:00:00 -78,76,113,0.0,1959-05-30 00:00:00 -79,76,107,0.0,1959-05-30 00:00:00 -80,76,119,0.0,1959-05-30 00:00:00 -81,76,118,0.0,1959-05-30 00:00:00 -82,76,117,0.0,1959-05-30 00:00:00 -83,76,112,0.0,1959-05-30 00:00:00 -84,76,120,0.0,1959-05-30 00:00:00 -85,77,167,6.0,1959-05-31 00:00:00 -86,77,31,3.0,1959-05-31 00:00:00 -87,77,5,2.0,1959-05-31 00:00:00 -88,77,93,0.0,1959-05-31 00:00:00 -89,77,64,8.0,1959-05-31 00:00:00 -90,77,115,0.0,1959-05-31 00:00:00 -91,78,167,4.0,1959-07-05 00:00:00 -92,78,103,0.0,1959-07-05 00:00:00 -93,78,163,0.0,1959-07-05 00:00:00 -94,78,5,8.0,1959-07-05 00:00:00 -95,78,31,0.0,1959-07-05 00:00:00 -96,79,166,0.0,1959-07-18 00:00:00 -97,79,103,0.0,1959-07-18 00:00:00 -98,79,99,0.0,1959-07-18 00:00:00 -99,79,116,0.0,1959-07-18 00:00:00 -100,79,121,0.0,1959-07-18 00:00:00 -101,79,31,0.0,1959-07-18 00:00:00 -102,79,163,0.0,1959-07-18 00:00:00 -103,79,167,8.0,1959-07-18 00:00:00 -104,79,64,6.0,1959-07-18 00:00:00 -105,79,115,0.0,1959-07-18 00:00:00 -106,80,167,3.0,1959-08-02 00:00:00 -107,80,163,0.0,1959-08-02 00:00:00 -108,80,31,0.0,1959-08-02 00:00:00 -109,80,64,2.0,1959-08-02 00:00:00 -110,80,5,8.0,1959-08-02 00:00:00 -111,81,163,0.0,1959-08-23 00:00:00 -112,81,64,2.0,1959-08-23 00:00:00 -113,81,5,4.0,1959-08-23 00:00:00 -114,81,167,8.0,1959-08-23 00:00:00 -115,81,115,0.0,1959-08-23 00:00:00 -116,81,31,0.0,1959-08-23 00:00:00 -117,82,31,0.0,1959-09-13 00:00:00 -118,82,103,0.0,1959-09-13 00:00:00 -119,82,163,0.0,1959-09-13 00:00:00 -120,82,115,0.0,1959-09-13 00:00:00 -121,82,64,0.0,1959-09-13 00:00:00 -122,82,5,6.0,1959-09-13 00:00:00 -123,82,167,8.0,1959-09-13 00:00:00 -124,83,166,0.0,1959-12-12 00:00:00 -125,83,5,4.0,1959-12-12 00:00:00 -126,83,167,8.0,1959-12-12 00:00:00 -127,83,93,0.0,1959-12-12 00:00:00 -128,83,163,0.0,1959-12-12 00:00:00 -129,83,111,0.0,1959-12-12 00:00:00 -130,83,165,0.0,1959-12-12 00:00:00 -131,83,122,0.0,1959-12-12 00:00:00 -132,83,31,2.0,1959-12-12 00:00:00 -133,83,123,0.0,1959-12-12 00:00:00 -134,83,103,0.0,1959-12-12 00:00:00 -135,84,31,1.0,1960-02-07 00:00:00 -136,84,163,3.0,1960-02-07 00:00:00 -137,84,64,0.0,1960-02-07 00:00:00 -138,84,167,8.0,1960-02-07 00:00:00 -139,84,103,0.0,1960-02-07 00:00:00 -140,84,5,8.0,1960-02-07 00:00:00 -141,84,102,0.0,1960-02-07 00:00:00 -142,85,99,0.0,1960-05-29 00:00:00 -143,85,167,6.0,1960-05-29 00:00:00 -144,85,5,4.0,1960-05-29 00:00:00 -145,85,64,2.0,1960-05-29 00:00:00 -146,85,163,0.0,1960-05-29 00:00:00 -147,85,168,0.0,1960-05-29 00:00:00 -148,85,104,0.0,1960-05-29 00:00:00 -149,85,31,8.0,1960-05-29 00:00:00 -150,86,107,3.0,1960-05-30 00:00:00 -151,86,106,4.0,1960-05-30 00:00:00 -152,86,105,8.0,1960-05-30 00:00:00 -153,86,111,0.0,1960-05-30 00:00:00 -154,86,110,0.0,1960-05-30 00:00:00 -155,86,108,2.0,1960-05-30 00:00:00 -156,86,112,0.0,1960-05-30 00:00:00 -157,86,113,0.0,1960-05-30 00:00:00 -158,86,114,0.0,1960-05-30 00:00:00 -159,86,109,1.0,1960-05-30 00:00:00 -160,87,104,0.0,1960-06-06 00:00:00 -161,87,163,0.0,1960-06-06 00:00:00 -162,87,5,2.0,1960-06-06 00:00:00 -163,87,64,4.0,1960-06-06 00:00:00 -164,87,31,6.0,1960-06-06 00:00:00 -165,87,167,8.0,1960-06-06 00:00:00 -166,87,115,0.0,1960-06-06 00:00:00 -167,88,5,3.0,1960-06-19 00:00:00 -168,88,167,8.0,1960-06-19 00:00:00 -169,88,31,2.0,1960-06-19 00:00:00 -170,88,104,0.0,1960-06-19 00:00:00 -171,88,64,0.0,1960-06-19 00:00:00 -172,89,104,0.0,1960-07-03 00:00:00 -173,89,168,0.0,1960-07-03 00:00:00 -174,89,64,0.0,1960-07-03 00:00:00 -175,89,116,0.0,1960-07-03 00:00:00 -176,89,163,0.0,1960-07-03 00:00:00 -177,89,31,2.0,1960-07-03 00:00:00 -178,89,167,8.0,1960-07-03 00:00:00 -179,89,5,0.0,1960-07-03 00:00:00 -180,90,167,8.0,1960-07-16 00:00:00 -181,90,31,6.0,1960-07-16 00:00:00 -182,90,64,0.0,1960-07-16 00:00:00 -183,90,115,0.0,1960-07-16 00:00:00 -184,90,99,0.0,1960-07-16 00:00:00 -185,90,163,0.0,1960-07-16 00:00:00 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-1509,234,55,0.0,1973-10-07 00:00:00 -1510,234,24,0.0,1973-10-07 00:00:00 -1511,234,36,6.0,1973-10-07 00:00:00 -1512,234,33,4.0,1973-10-07 00:00:00 -1513,234,0,3.0,1973-10-07 00:00:00 -1514,234,78,0.0,1973-10-07 00:00:00 -1515,234,64,0.0,1973-10-07 00:00:00 -1516,234,56,0.0,1973-10-07 00:00:00 -1517,234,5,0.0,1973-10-07 00:00:00 -1518,234,31,9.0,1973-10-07 00:00:00 -1519,235,5,6.0,1974-01-13 00:00:00 -1520,235,25,0.0,1974-01-13 00:00:00 -1521,235,36,0.0,1974-01-13 00:00:00 -1522,235,24,1.0,1974-01-13 00:00:00 -1523,235,64,2.0,1974-01-13 00:00:00 -1524,235,0,9.0,1974-01-13 00:00:00 -1525,235,33,0.0,1974-01-13 00:00:00 -1526,235,31,0.0,1974-01-13 00:00:00 -1527,235,78,0.0,1974-01-13 00:00:00 -1528,235,56,0.0,1974-01-13 00:00:00 -1529,235,61,0.0,1974-01-13 00:00:00 -1530,236,0,9.0,1974-01-27 00:00:00 -1531,236,5,6.0,1974-01-27 00:00:00 -1532,236,31,4.0,1974-01-27 00:00:00 -1533,236,33,0.0,1974-01-27 00:00:00 -1534,236,24,0.0,1974-01-27 00:00:00 -1535,236,61,3.0,1974-01-27 00:00:00 -1536,236,78,0.0,1974-01-27 00:00:00 -1537,236,56,0.0,1974-01-27 00:00:00 -1538,236,25,0.0,1974-01-27 00:00:00 -1539,236,64,0.0,1974-01-27 00:00:00 -1540,236,36,0.0,1974-01-27 00:00:00 -1541,237,64,6.0,1974-03-30 00:00:00 -1542,237,25,0.0,1974-03-30 00:00:00 -1543,237,61,0.0,1974-03-30 00:00:00 -1544,237,78,1.0,1974-03-30 00:00:00 -1545,237,24,3.0,1974-03-30 00:00:00 -1546,237,0,4.0,1974-03-30 00:00:00 -1547,237,33,9.0,1974-03-30 00:00:00 -1548,237,36,2.0,1974-03-30 00:00:00 -1549,237,31,0.0,1974-03-30 00:00:00 -1550,237,62,0.0,1974-03-30 00:00:00 -1551,237,5,0.0,1974-03-30 00:00:00 -1552,238,61,0.0,1974-04-28 00:00:00 -1553,238,25,0.0,1974-04-28 00:00:00 -1554,238,78,0.0,1974-04-28 00:00:00 -1555,238,31,0.0,1974-04-28 00:00:00 -1556,238,76,0.0,1974-04-28 00:00:00 -1557,238,64,0.0,1974-04-28 00:00:00 -1558,238,56,0.0,1974-04-28 00:00:00 -1559,238,62,0.0,1974-04-28 00:00:00 -1560,238,5,9.0,1974-04-28 00:00:00 -1561,238,0,4.0,1974-04-28 00:00:00 -1562,238,36,3.0,1974-04-28 00:00:00 -1563,238,24,2.0,1974-04-28 00:00:00 -1564,238,75,0.0,1974-04-28 00:00:00 -1565,238,33,0.0,1974-04-28 00:00:00 -1566,239,61,0.0,1974-05-12 00:00:00 -1567,239,77,0.0,1974-05-12 00:00:00 -1568,239,62,0.0,1974-05-12 00:00:00 -1569,239,31,0.0,1974-05-12 00:00:00 -1570,239,64,2.0,1974-05-12 00:00:00 -1571,239,56,0.0,1974-05-12 00:00:00 -1572,239,33,0.0,1974-05-12 00:00:00 -1573,239,55,0.0,1974-05-12 00:00:00 -1574,239,0,9.0,1974-05-12 00:00:00 -1575,239,5,6.0,1974-05-12 00:00:00 -1576,239,24,4.0,1974-05-12 00:00:00 -1577,239,78,0.0,1974-05-12 00:00:00 -1578,239,25,0.0,1974-05-12 00:00:00 -1579,239,36,0.0,1974-05-12 00:00:00 -1580,239,75,0.0,1974-05-12 00:00:00 -1581,240,75,0.0,1974-05-26 00:00:00 -1582,240,55,0.0,1974-05-26 00:00:00 -1583,240,5,3.0,1974-05-26 00:00:00 -1584,240,56,4.0,1974-05-26 00:00:00 -1585,240,76,0.0,1974-05-26 00:00:00 -1586,240,61,0.0,1974-05-26 00:00:00 -1587,240,36,0.0,1974-05-26 00:00:00 -1588,240,24,6.0,1974-05-26 00:00:00 -1589,240,0,2.0,1974-05-26 00:00:00 -1590,240,33,1.0,1974-05-26 00:00:00 -1591,240,25,0.0,1974-05-26 00:00:00 -1592,240,64,0.0,1974-05-26 00:00:00 -1593,240,62,0.0,1974-05-26 00:00:00 -1594,240,78,0.0,1974-05-26 00:00:00 -1595,240,31,9.0,1974-05-26 00:00:00 -1596,241,24,9.0,1974-06-09 00:00:00 -1597,241,62,4.0,1974-06-09 00:00:00 -1598,241,0,3.0,1974-06-09 00:00:00 -1599,241,56,2.0,1974-06-09 00:00:00 -1600,241,25,1.0,1974-06-09 00:00:00 -1601,241,78,0.0,1974-06-09 00:00:00 -1602,241,33,0.0,1974-06-09 00:00:00 -1603,241,36,0.0,1974-06-09 00:00:00 -1604,241,61,0.0,1974-06-09 00:00:00 -1605,241,64,0.0,1974-06-09 00:00:00 -1606,241,31,0.0,1974-06-09 00:00:00 -1607,241,5,0.0,1974-06-09 00:00:00 -1608,241,55,0.0,1974-06-09 00:00:00 -1609,242,33,0.0,1974-06-23 00:00:00 -1610,242,24,2.0,1974-06-23 00:00:00 -1611,242,0,4.0,1974-06-23 00:00:00 -1612,242,5,9.0,1974-06-23 00:00:00 -1613,242,55,0.0,1974-06-23 00:00:00 -1614,242,36,0.0,1974-06-23 00:00:00 -1615,242,64,0.0,1974-06-23 00:00:00 -1616,242,31,0.0,1974-06-23 00:00:00 -1617,242,25,0.0,1974-06-23 00:00:00 -1618,242,56,0.0,1974-06-23 00:00:00 -1619,242,78,0.0,1974-06-23 00:00:00 -1620,242,61,0.0,1974-06-23 00:00:00 -1621,242,75,0.0,1974-06-23 00:00:00 -1622,242,62,0.0,1974-06-23 00:00:00 -1623,243,62,0.0,1974-07-07 00:00:00 -1624,243,31,9.0,1974-07-07 00:00:00 -1625,243,5,6.0,1974-07-07 00:00:00 -1626,243,24,3.0,1974-07-07 00:00:00 -1627,243,55,0.0,1974-07-07 00:00:00 -1628,243,0,1.0,1974-07-07 00:00:00 -1629,243,64,0.0,1974-07-07 00:00:00 -1630,243,36,0.0,1974-07-07 00:00:00 -1631,243,56,0.0,1974-07-07 00:00:00 -1632,243,25,0.0,1974-07-07 00:00:00 -1633,243,33,0.0,1974-07-07 00:00:00 -1634,243,61,0.0,1974-07-07 00:00:00 -1635,243,78,0.0,1974-07-07 00:00:00 -1636,244,0,6.0,1974-07-20 00:00:00 -1637,244,31,4.0,1974-07-20 00:00:00 -1638,244,5,3.0,1974-07-20 00:00:00 -1639,244,72,0.0,1974-07-20 00:00:00 -1640,244,74,0.0,1974-07-20 00:00:00 -1641,244,24,9.0,1974-07-20 00:00:00 -1642,244,55,0.0,1974-07-20 00:00:00 -1643,244,77,0.0,1974-07-20 00:00:00 -1644,244,62,0.0,1974-07-20 00:00:00 -1645,244,33,1.0,1974-07-20 00:00:00 -1646,244,78,0.0,1974-07-20 00:00:00 -1647,244,36,0.0,1974-07-20 00:00:00 -1648,244,61,0.0,1974-07-20 00:00:00 -1649,244,25,0.0,1974-07-20 00:00:00 -1650,244,75,0.0,1974-07-20 00:00:00 -1651,244,64,0.0,1974-07-20 00:00:00 -1652,244,56,0.0,1974-07-20 00:00:00 -1653,245,72,0.0,1974-08-04 00:00:00 -1654,245,33,4.0,1974-08-04 00:00:00 -1655,245,31,3.0,1974-08-04 00:00:00 -1656,245,56,1.0,1974-08-04 00:00:00 -1657,245,36,0.0,1974-08-04 00:00:00 -1658,245,25,0.0,1974-08-04 00:00:00 -1659,245,64,0.0,1974-08-04 00:00:00 -1660,245,61,0.0,1974-08-04 00:00:00 -1661,245,77,0.0,1974-08-04 00:00:00 -1662,245,0,0.0,1974-08-04 00:00:00 -1663,245,62,0.0,1974-08-04 00:00:00 -1664,245,24,6.0,1974-08-04 00:00:00 -1665,245,78,0.0,1974-08-04 00:00:00 -1666,245,55,0.0,1974-08-04 00:00:00 -1667,245,75,0.0,1974-08-04 00:00:00 -1668,245,76,0.0,1974-08-04 00:00:00 -1669,245,5,9.0,1974-08-04 00:00:00 -1670,246,24,0.0,1974-08-18 00:00:00 -1671,246,25,0.0,1974-08-18 00:00:00 -1672,246,0,6.0,1974-08-18 00:00:00 -1673,246,31,0.0,1974-08-18 00:00:00 -1674,246,78,0.0,1974-08-18 00:00:00 -1675,246,64,0.0,1974-08-18 00:00:00 -1676,246,55,0.0,1974-08-18 00:00:00 -1677,246,77,0.0,1974-08-18 00:00:00 -1678,246,33,9.0,1974-08-18 00:00:00 -1679,246,62,4.0,1974-08-18 00:00:00 -1680,246,5,2.0,1974-08-18 00:00:00 -1681,246,36,1.0,1974-08-18 00:00:00 -1682,246,56,0.0,1974-08-18 00:00:00 -1683,246,61,0.0,1974-08-18 00:00:00 -1684,246,75,0.0,1974-08-18 00:00:00 -1685,247,55,0.0,1974-09-08 00:00:00 -1686,247,62,0.0,1974-09-08 00:00:00 -1687,247,64,0.0,1974-09-08 00:00:00 -1688,247,76,0.0,1974-09-08 00:00:00 -1689,247,61,0.0,1974-09-08 00:00:00 -1690,247,31,9.0,1974-09-08 00:00:00 -1691,247,36,0.0,1974-09-08 00:00:00 -1692,247,78,3.0,1974-09-08 00:00:00 -1693,247,24,4.0,1974-09-08 00:00:00 -1694,247,0,6.0,1974-09-08 00:00:00 -1695,247,75,0.0,1974-09-08 00:00:00 -1696,247,33,2.0,1974-09-08 00:00:00 -1697,247,25,0.0,1974-09-08 00:00:00 -1698,247,5,0.0,1974-09-08 00:00:00 -1699,247,56,0.0,1974-09-08 00:00:00 -1700,248,24,2.0,1974-09-22 00:00:00 -1701,248,65,0.0,1974-09-22 00:00:00 -1702,248,25,0.0,1974-09-22 00:00:00 -1703,248,61,0.0,1974-09-22 00:00:00 -1704,248,78,0.0,1974-09-22 00:00:00 -1705,248,64,0.0,1974-09-22 00:00:00 -1706,248,56,0.0,1974-09-22 00:00:00 -1707,248,71,0.0,1974-09-22 00:00:00 -1708,248,36,0.0,1974-09-22 00:00:00 -1709,248,33,0.0,1974-09-22 00:00:00 -1710,248,0,9.0,1974-09-22 00:00:00 -1711,248,5,6.0,1974-09-22 00:00:00 -1712,248,31,4.0,1974-09-22 00:00:00 -1713,248,62,3.0,1974-09-22 00:00:00 -1714,248,55,0.0,1974-09-22 00:00:00 -1715,249,65,0.0,1974-10-06 00:00:00 -1716,249,61,0.0,1974-10-06 00:00:00 -1717,249,71,0.0,1974-10-06 00:00:00 -1718,249,36,0.0,1974-10-06 00:00:00 -1719,249,62,4.0,1974-10-06 00:00:00 -1720,249,0,3.0,1974-10-06 00:00:00 -1721,249,24,1.0,1974-10-06 00:00:00 -1722,249,25,0.0,1974-10-06 00:00:00 -1723,249,64,0.0,1974-10-06 00:00:00 -1724,249,56,0.0,1974-10-06 00:00:00 -1725,249,5,0.0,1974-10-06 00:00:00 -1726,249,31,0.0,1974-10-06 00:00:00 -1727,249,55,0.0,1974-10-06 00:00:00 -1728,249,78,0.0,1974-10-06 00:00:00 -1729,249,33,9.0,1974-10-06 00:00:00 -1730,250,54,0.0,1975-01-12 00:00:00 -1731,250,2,0.0,1975-01-12 00:00:00 -1732,250,71,0.0,1975-01-12 00:00:00 -1733,250,64,0.0,1975-01-12 00:00:00 -1734,250,61,0.0,1975-01-12 00:00:00 -1735,250,36,0.0,1975-01-12 00:00:00 -1736,250,5,3.0,1975-01-12 00:00:00 -1737,250,199,0.0,1975-01-12 00:00:00 -1738,250,25,0.0,1975-01-12 00:00:00 -1739,250,31,0.0,1975-01-12 00:00:00 -1740,250,65,0.0,1975-01-12 00:00:00 -1741,250,24,2.0,1975-01-12 00:00:00 -1742,250,33,4.0,1975-01-12 00:00:00 -1743,250,62,6.0,1975-01-12 00:00:00 -1744,250,0,9.0,1975-01-12 00:00:00 -1745,251,62,1.0,1975-01-26 00:00:00 -1746,251,5,3.0,1975-01-26 00:00:00 -1747,251,0,6.0,1975-01-26 00:00:00 -1748,251,65,0.0,1975-01-26 00:00:00 -1749,251,33,9.0,1975-01-26 00:00:00 -1750,251,24,0.0,1975-01-26 00:00:00 -1751,251,71,0.0,1975-01-26 00:00:00 -1752,251,31,0.0,1975-01-26 00:00:00 -1753,251,54,0.0,1975-01-26 00:00:00 -1754,251,2,0.0,1975-01-26 00:00:00 -1755,251,25,0.0,1975-01-26 00:00:00 -1756,251,199,0.0,1975-01-26 00:00:00 -1757,251,36,0.0,1975-01-26 00:00:00 -1758,251,64,0.0,1975-01-26 00:00:00 -1759,251,61,0.0,1975-01-26 00:00:00 -1760,252,2,0.0,1975-03-01 00:00:00 -1761,252,62,0.0,1975-03-01 00:00:00 -1762,252,71,0.0,1975-03-01 00:00:00 -1763,252,73,0.0,1975-03-01 00:00:00 -1764,252,24,9.0,1975-03-01 00:00:00 -1765,252,5,2.0,1975-03-01 00:00:00 -1766,252,0,1.0,1975-03-01 00:00:00 -1767,252,36,0.0,1975-03-01 00:00:00 -1768,252,65,0.0,1975-03-01 00:00:00 -1769,252,61,0.0,1975-03-01 00:00:00 -1770,252,199,0.0,1975-03-01 00:00:00 -1771,252,31,0.0,1975-03-01 00:00:00 -1772,252,64,0.0,1975-03-01 00:00:00 -1773,252,54,0.0,1975-03-01 00:00:00 -1774,252,25,0.0,1975-03-01 00:00:00 -1775,252,33,6.0,1975-03-01 00:00:00 -1776,253,5,0.0,1975-04-27 00:00:00 -1777,253,54,0.0,1975-04-27 00:00:00 -1778,253,65,0.0,1975-04-27 00:00:00 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-2643,308,0,0.0,1978-08-13 00:00:00 -2644,308,63,0.0,1978-08-13 00:00:00 -2645,308,56,0.0,1978-08-13 00:00:00 -2646,309,61,0.0,1978-08-27 00:00:00 -2647,309,58,0.0,1978-08-27 00:00:00 -2648,309,63,0.0,1978-08-27 00:00:00 -2649,309,3,0.0,1978-08-27 00:00:00 -2650,309,2,0.0,1978-08-27 00:00:00 -2651,309,57,0.0,1978-08-27 00:00:00 -2652,309,0,0.0,1978-08-27 00:00:00 -2653,309,26,0.0,1978-08-27 00:00:00 -2654,309,5,1.0,1978-08-27 00:00:00 -2655,309,54,2.0,1978-08-27 00:00:00 -2656,309,33,4.0,1978-08-27 00:00:00 -2657,309,31,9.0,1978-08-27 00:00:00 -2658,309,24,0.0,1978-08-27 00:00:00 -2659,309,55,0.0,1978-08-27 00:00:00 -2660,309,20,0.0,1978-08-27 00:00:00 -2661,309,52,0.0,1978-08-27 00:00:00 -2662,309,56,0.0,1978-08-27 00:00:00 -2663,310,57,0.0,1978-09-10 00:00:00 -2664,310,56,0.0,1978-09-10 00:00:00 -2665,310,2,0.0,1978-09-10 00:00:00 -2666,310,3,0.0,1978-09-10 00:00:00 -2667,310,24,0.0,1978-09-10 00:00:00 -2668,310,33,9.0,1978-09-10 00:00:00 -2669,310,58,0.0,1978-09-10 00:00:00 -2670,310,20,0.0,1978-09-10 00:00:00 -2671,310,52,0.0,1978-09-10 00:00:00 -2672,310,55,0.0,1978-09-10 00:00:00 -2673,310,54,0.0,1978-09-10 00:00:00 -2674,310,31,1.0,1978-09-10 00:00:00 -2675,310,0,2.0,1978-09-10 00:00:00 -2676,310,26,3.0,1978-09-10 00:00:00 -2677,310,5,4.0,1978-09-10 00:00:00 -2678,310,61,0.0,1978-09-10 00:00:00 -2679,311,2,6.0,1978-10-01 00:00:00 -2680,311,26,0.0,1978-10-01 00:00:00 -2681,311,24,0.0,1978-10-01 00:00:00 -2682,311,63,0.0,1978-10-01 00:00:00 -2683,311,55,0.0,1978-10-01 00:00:00 -2684,311,0,1.0,1978-10-01 00:00:00 -2685,311,54,2.0,1978-10-01 00:00:00 -2686,311,3,3.0,1978-10-01 00:00:00 -2687,311,57,4.0,1978-10-01 00:00:00 -2688,311,56,0.0,1978-10-01 00:00:00 -2689,311,5,9.0,1978-10-01 00:00:00 -2690,311,31,0.0,1978-10-01 00:00:00 -2691,311,20,0.0,1978-10-01 00:00:00 -2692,311,58,0.0,1978-10-01 00:00:00 -2693,311,52,0.0,1978-10-01 00:00:00 -2694,311,33,0.0,1978-10-01 00:00:00 -2695,311,61,0.0,1978-10-01 00:00:00 -2696,312,5,9.0,1978-10-08 00:00:00 -2697,312,57,6.0,1978-10-08 00:00:00 -2698,312,20,3.0,1978-10-08 00:00:00 -2699,312,24,2.0,1978-10-08 00:00:00 -2700,312,0,0.0,1978-10-08 00:00:00 -2701,312,2,0.0,1978-10-08 00:00:00 -2702,312,31,0.0,1978-10-08 00:00:00 -2703,312,33,0.0,1978-10-08 00:00:00 -2704,312,3,0.0,1978-10-08 00:00:00 -2705,312,52,0.0,1978-10-08 00:00:00 -2706,312,55,1.0,1978-10-08 00:00:00 -2707,312,58,0.0,1978-10-08 00:00:00 -2708,312,54,0.0,1978-10-08 00:00:00 -2709,312,56,0.0,1978-10-08 00:00:00 -2710,312,61,0.0,1978-10-08 00:00:00 -2711,312,26,0.0,1978-10-08 00:00:00 -2712,313,58,0.0,1979-01-21 00:00:00 -2713,313,0,4.0,1979-01-21 00:00:00 -2714,313,54,1.0,1979-01-21 00:00:00 -2715,313,56,0.0,1979-01-21 00:00:00 -2716,313,20,0.0,1979-01-21 00:00:00 -2717,313,2,0.0,1979-01-21 00:00:00 -2718,313,55,0.0,1979-01-21 00:00:00 -2719,313,5,0.0,1979-01-21 00:00:00 -2720,313,24,0.0,1979-01-21 00:00:00 -2721,313,57,0.0,1979-01-21 00:00:00 -2722,313,201,0.0,1979-01-21 00:00:00 -2723,313,31,8.0,1979-01-21 00:00:00 -2724,313,26,12.0,1979-01-21 00:00:00 -2725,313,52,0.0,1979-01-21 00:00:00 -2726,313,3,0.0,1979-01-21 00:00:00 -2727,314,24,3.0,1979-02-04 00:00:00 -2728,314,5,3.0,1979-02-04 00:00:00 -2729,314,20,0.0,1979-02-04 00:00:00 -2730,314,0,0.0,1979-02-04 00:00:00 -2731,314,3,0.0,1979-02-04 00:00:00 -2732,314,54,0.0,1979-02-04 00:00:00 -2733,314,55,0.0,1979-02-04 00:00:00 -2734,314,201,0.0,1979-02-04 00:00:00 -2735,314,57,0.0,1979-02-04 00:00:00 -2736,314,52,0.0,1979-02-04 00:00:00 -2737,314,31,4.0,1979-02-04 00:00:00 -2738,314,58,0.0,1979-02-04 00:00:00 -2739,314,56,0.0,1979-02-04 00:00:00 -2740,314,26,15.0,1979-02-04 00:00:00 -2741,314,2,0.0,1979-02-04 00:00:00 -2742,315,26,0.0,1979-03-03 00:00:00 -2743,315,31,5.0,1979-03-03 00:00:00 -2744,315,33,1.0,1979-03-03 00:00:00 -2745,315,57,0.0,1979-03-03 00:00:00 -2746,315,2,0.0,1979-03-03 00:00:00 -2747,315,0,0.0,1979-03-03 00:00:00 -2748,315,20,0.0,1979-03-03 00:00:00 -2749,315,54,0.0,1979-03-03 00:00:00 -2750,315,3,0.0,1979-03-03 00:00:00 -2751,315,52,0.0,1979-03-03 00:00:00 -2752,315,24,4.0,1979-03-03 00:00:00 -2753,315,5,15.0,1979-03-03 00:00:00 -2754,315,55,0.0,1979-03-03 00:00:00 -2755,315,58,0.0,1979-03-03 00:00:00 -2756,315,201,1.0,1979-03-03 00:00:00 -2757,315,56,0.0,1979-03-03 00:00:00 -2758,316,5,15.0,1979-04-08 00:00:00 -2759,316,52,0.0,1979-04-08 00:00:00 -2760,316,3,0.0,1979-04-08 00:00:00 -2761,316,57,0.0,1979-04-08 00:00:00 -2762,316,58,0.0,1979-04-08 00:00:00 -2763,316,54,0.0,1979-04-08 00:00:00 -2764,316,31,3.0,1979-04-08 00:00:00 -2765,316,2,4.0,1979-04-08 00:00:00 -2766,316,201,0.0,1979-04-08 00:00:00 -2767,316,0,0.0,1979-04-08 00:00:00 -2768,316,55,0.0,1979-04-08 00:00:00 -2769,316,56,0.0,1979-04-08 00:00:00 -2770,316,24,1.0,1979-04-08 00:00:00 -2771,316,26,2.0,1979-04-08 00:00:00 -2772,316,20,0.0,1979-04-08 00:00:00 -2773,317,20,0.0,1979-04-29 00:00:00 -2774,317,201,0.0,1979-04-29 00:00:00 -2775,317,52,0.0,1979-04-29 00:00:00 -2776,317,59,0.0,1979-04-29 00:00:00 -2777,317,3,0.0,1979-04-29 00:00:00 -2778,317,55,0.0,1979-04-29 00:00:00 -2779,317,57,0.0,1979-04-29 00:00:00 -2780,317,58,0.0,1979-04-29 00:00:00 -2781,317,56,0.0,1979-04-29 00:00:00 -2782,317,26,9.0,1979-04-29 00:00:00 -2783,317,31,10.0,1979-04-29 00:00:00 -2784,317,5,3.0,1979-04-29 00:00:00 -2785,317,54,0.0,1979-04-29 00:00:00 -2786,317,24,3.0,1979-04-29 00:00:00 -2787,317,0,0.0,1979-04-29 00:00:00 -2788,317,2,0.0,1979-04-29 00:00:00 -2789,318,26,6.0,1979-05-13 00:00:00 -2790,318,201,0.0,1979-05-13 00:00:00 -2791,318,3,0.0,1979-05-13 00:00:00 -2792,318,49,0.0,1979-05-13 00:00:00 -2793,318,58,0.0,1979-05-13 00:00:00 -2794,318,55,0.0,1979-05-13 00:00:00 -2795,318,59,0.0,1979-05-13 00:00:00 -2796,318,5,9.0,1979-05-13 00:00:00 -2797,318,24,4.0,1979-05-13 00:00:00 -2798,318,2,0.0,1979-05-13 00:00:00 -2799,318,57,0.0,1979-05-13 00:00:00 -2800,318,56,0.0,1979-05-13 00:00:00 -2801,318,54,0.0,1979-05-13 00:00:00 -2802,318,52,0.0,1979-05-13 00:00:00 -2803,318,0,1.0,1979-05-13 00:00:00 -2804,318,31,3.0,1979-05-13 00:00:00 -2805,318,20,2.0,1979-05-13 00:00:00 -2806,319,5,9.0,1979-05-27 00:00:00 -2807,319,56,0.0,1979-05-27 00:00:00 -2808,319,57,0.0,1979-05-27 00:00:00 -2809,319,54,0.0,1979-05-27 00:00:00 -2810,319,2,6.0,1979-05-27 00:00:00 -2811,319,31,4.0,1979-05-27 00:00:00 -2812,319,0,3.0,1979-05-27 00:00:00 -2813,319,20,1.0,1979-05-27 00:00:00 -2814,319,201,0.0,1979-05-27 00:00:00 -2815,319,3,0.0,1979-05-27 00:00:00 -2816,319,24,0.0,1979-05-27 00:00:00 -2817,319,52,0.0,1979-05-27 00:00:00 -2818,319,55,0.0,1979-05-27 00:00:00 -2819,319,58,0.0,1979-05-27 00:00:00 -2820,319,26,2.0,1979-05-27 00:00:00 -2821,320,2,4.0,1979-07-01 00:00:00 -2822,320,3,13.0,1979-07-01 00:00:00 -2823,320,5,6.0,1979-07-01 00:00:00 -2824,320,24,2.0,1979-07-01 00:00:00 -2825,320,58,0.0,1979-07-01 00:00:00 -2826,320,57,0.0,1979-07-01 00:00:00 -2827,320,0,0.0,1979-07-01 00:00:00 -2828,320,31,0.0,1979-07-01 00:00:00 -2829,320,55,0.0,1979-07-01 00:00:00 -2830,320,52,0.0,1979-07-01 00:00:00 -2831,320,201,0.0,1979-07-01 00:00:00 -2832,320,54,0.0,1979-07-01 00:00:00 -2833,320,49,0.0,1979-07-01 00:00:00 -2834,320,56,0.0,1979-07-01 00:00:00 -2835,320,20,0.0,1979-07-01 00:00:00 -2836,320,26,0.0,1979-07-01 00:00:00 -2837,321,54,0.0,1979-07-14 00:00:00 -2838,321,201,0.0,1979-07-14 00:00:00 -2839,321,52,0.0,1979-07-14 00:00:00 -2840,321,58,0.0,1979-07-14 00:00:00 -2841,321,31,0.0,1979-07-14 00:00:00 -2842,321,20,0.0,1979-07-14 00:00:00 -2843,321,55,0.0,1979-07-14 00:00:00 -2844,321,56,0.0,1979-07-14 00:00:00 -2845,321,57,0.0,1979-07-14 00:00:00 -2846,321,26,1.0,1979-07-14 00:00:00 -2847,321,2,9.0,1979-07-14 00:00:00 -2848,321,3,6.0,1979-07-14 00:00:00 -2849,321,5,2.0,1979-07-14 00:00:00 -2850,321,0,3.0,1979-07-14 00:00:00 -2851,321,24,4.0,1979-07-14 00:00:00 -2852,322,57,0.0,1979-07-29 00:00:00 -2853,322,58,0.0,1979-07-29 00:00:00 -2854,322,55,0.0,1979-07-29 00:00:00 -2855,322,52,0.0,1979-07-29 00:00:00 -2856,322,2,15.0,1979-07-29 00:00:00 -2857,322,26,4.0,1979-07-29 00:00:00 -2858,322,5,3.0,1979-07-29 00:00:00 -2859,322,54,0.0,1979-07-29 00:00:00 -2860,322,0,2.0,1979-07-29 00:00:00 -2861,322,3,0.0,1979-07-29 00:00:00 -2862,322,24,0.0,1979-07-29 00:00:00 -2863,322,56,0.0,1979-07-29 00:00:00 -2864,322,201,0.0,1979-07-29 00:00:00 -2865,322,31,0.0,1979-07-29 00:00:00 -2866,322,20,1.0,1979-07-29 00:00:00 -2867,323,201,0.0,1979-08-12 00:00:00 -2868,323,3,1.0,1979-08-12 00:00:00 -2869,323,26,4.0,1979-08-12 00:00:00 -2870,323,5,9.0,1979-08-12 00:00:00 -2871,323,33,0.0,1979-08-12 00:00:00 -2872,323,2,11.0,1979-08-12 00:00:00 -2873,323,55,0.0,1979-08-12 00:00:00 -2874,323,20,0.0,1979-08-12 00:00:00 -2875,323,56,0.0,1979-08-12 00:00:00 -2876,323,0,0.0,1979-08-12 00:00:00 -2877,323,52,0.0,1979-08-12 00:00:00 -2878,323,57,0.0,1979-08-12 00:00:00 -2879,323,54,0.0,1979-08-12 00:00:00 -2880,323,58,0.0,1979-08-12 00:00:00 -2881,323,31,0.0,1979-08-12 00:00:00 -2882,323,24,0.0,1979-08-12 00:00:00 -2883,324,54,0.0,1979-08-26 00:00:00 -2884,324,31,0.0,1979-08-26 00:00:00 -2885,324,55,0.0,1979-08-26 00:00:00 -2886,324,3,0.0,1979-08-26 00:00:00 -2887,324,20,1.0,1979-08-26 00:00:00 -2888,324,24,0.0,1979-08-26 00:00:00 -2889,324,58,0.0,1979-08-26 00:00:00 -2890,324,52,0.0,1979-08-26 00:00:00 -2891,324,0,0.0,1979-08-26 00:00:00 -2892,324,2,9.0,1979-08-26 00:00:00 -2893,324,5,6.0,1979-08-26 00:00:00 -2894,324,26,6.0,1979-08-26 00:00:00 -2895,324,201,3.0,1979-08-26 00:00:00 -2896,324,57,0.0,1979-08-26 00:00:00 -2897,324,56,0.0,1979-08-26 00:00:00 -2898,325,56,0.0,1979-09-09 00:00:00 -2899,325,0,0.0,1979-09-09 00:00:00 -2900,325,55,0.0,1979-09-09 00:00:00 -2901,325,58,0.0,1979-09-09 00:00:00 -2902,325,60,0.0,1979-09-09 00:00:00 -2903,325,201,3.0,1979-09-09 00:00:00 -2904,325,24,1.0,1979-09-09 00:00:00 -2905,325,52,0.0,1979-09-09 00:00:00 -2906,325,49,0.0,1979-09-09 00:00:00 -2907,325,20,0.0,1979-09-09 00:00:00 -2908,325,3,0.0,1979-09-09 00:00:00 -2909,325,31,2.0,1979-09-09 00:00:00 -2910,325,2,4.0,1979-09-09 00:00:00 -2911,325,57,0.0,1979-09-09 00:00:00 -2912,325,26,0.0,1979-09-09 00:00:00 -2913,325,5,15.0,1979-09-09 00:00:00 -2914,325,54,0.0,1979-09-09 00:00:00 -2915,326,52,0.0,1979-09-30 00:00:00 -2916,326,55,0.0,1979-09-30 00:00:00 -2917,326,57,0.0,1979-09-30 00:00:00 -2918,326,58,0.0,1979-09-30 00:00:00 -2919,326,20,0.0,1979-09-30 00:00:00 -2920,326,26,0.0,1979-09-30 00:00:00 -2921,326,2,13.0,1979-09-30 00:00:00 -2922,326,49,0.0,1979-09-30 00:00:00 -2923,326,31,0.0,1979-09-30 00:00:00 -2924,326,56,0.0,1979-09-30 00:00:00 -2925,326,54,0.0,1979-09-30 00:00:00 -2926,326,179,0.0,1979-09-30 00:00:00 -2927,326,5,9.0,1979-09-30 00:00:00 -2928,326,0,1.0,1979-09-30 00:00:00 -2929,326,24,2.0,1979-09-30 00:00:00 -2930,326,3,0.0,1979-09-30 00:00:00 -2931,326,60,0.0,1979-09-30 00:00:00 -2932,327,0,1.0,1979-10-07 00:00:00 -2933,327,52,2.0,1979-10-07 00:00:00 -2934,327,31,0.0,1979-10-07 00:00:00 -2935,327,57,0.0,1979-10-07 00:00:00 -2936,327,24,4.0,1979-10-07 00:00:00 -2937,327,3,6.0,1979-10-07 00:00:00 -2938,327,5,9.0,1979-10-07 00:00:00 -2939,327,179,0.0,1979-10-07 00:00:00 -2940,327,20,0.0,1979-10-07 00:00:00 -2941,327,54,0.0,1979-10-07 00:00:00 -2942,327,55,0.0,1979-10-07 00:00:00 -2943,327,58,0.0,1979-10-07 00:00:00 -2944,327,60,0.0,1979-10-07 00:00:00 -2945,327,49,0.0,1979-10-07 00:00:00 -2946,327,56,3.0,1979-10-07 00:00:00 -2947,327,26,0.0,1979-10-07 00:00:00 -2948,327,2,0.0,1979-10-07 00:00:00 -2949,328,20,0.0,1980-01-13 00:00:00 -2950,328,43,0.0,1980-01-13 00:00:00 -2951,328,56,0.0,1980-01-13 00:00:00 -2952,328,3,0.0,1980-01-13 00:00:00 -2953,328,31,0.0,1980-01-13 00:00:00 -2954,328,52,0.0,1980-01-13 00:00:00 -2955,328,26,0.0,1980-01-13 00:00:00 -2956,328,24,3.0,1980-01-13 00:00:00 -2957,328,5,0.0,1980-01-13 00:00:00 -2958,328,0,1.0,1980-01-13 00:00:00 -2959,328,49,2.0,1980-01-13 00:00:00 -2960,328,54,4.0,1980-01-13 00:00:00 -2961,328,33,6.0,1980-01-13 00:00:00 -2962,328,2,9.0,1980-01-13 00:00:00 -2963,328,55,0.0,1980-01-13 00:00:00 -2964,329,26,3.0,1980-01-27 00:00:00 -2965,329,3,9.0,1980-01-27 00:00:00 -2966,329,31,6.0,1980-01-27 00:00:00 -2967,329,2,4.0,1980-01-27 00:00:00 -2968,329,0,2.0,1980-01-27 00:00:00 -2969,329,5,0.0,1980-01-27 00:00:00 -2970,329,52,0.0,1980-01-27 00:00:00 -2971,329,33,0.0,1980-01-27 00:00:00 -2972,329,54,0.0,1980-01-27 00:00:00 -2973,329,24,0.0,1980-01-27 00:00:00 -2974,329,49,0.0,1980-01-27 00:00:00 -2975,329,55,0.0,1980-01-27 00:00:00 -2976,329,56,0.0,1980-01-27 00:00:00 -2977,329,43,0.0,1980-01-27 00:00:00 -2978,329,20,1.0,1980-01-27 00:00:00 -2979,330,43,0.0,1980-03-01 00:00:00 -2980,330,5,0.0,1980-03-01 00:00:00 -2981,330,49,0.0,1980-03-01 00:00:00 -2982,330,56,0.0,1980-03-01 00:00:00 -2983,330,31,0.0,1980-03-01 00:00:00 -2984,330,0,0.0,1980-03-01 00:00:00 -2985,330,52,0.0,1980-03-01 00:00:00 -2986,330,54,0.0,1980-03-01 00:00:00 -2987,330,24,0.0,1980-03-01 00:00:00 -2988,330,20,1.0,1980-03-01 00:00:00 -2989,330,2,2.0,1980-03-01 00:00:00 -2990,330,33,3.0,1980-03-01 00:00:00 -2991,330,26,10.0,1980-03-01 00:00:00 -2992,330,55,0.0,1980-03-01 00:00:00 -2993,330,3,9.0,1980-03-01 00:00:00 -2994,331,56,0.0,1980-03-30 00:00:00 -2995,331,52,0.0,1980-03-30 00:00:00 -2996,331,43,0.0,1980-03-30 00:00:00 -2997,331,2,0.0,1980-03-30 00:00:00 -2998,331,49,0.0,1980-03-30 00:00:00 -2999,331,55,0.0,1980-03-30 00:00:00 -3000,331,31,0.0,1980-03-30 00:00:00 -3001,331,24,0.0,1980-03-30 00:00:00 -3002,331,3,0.0,1980-03-30 00:00:00 -3003,331,33,9.0,1980-03-30 00:00:00 -3004,331,20,6.0,1980-03-30 00:00:00 -3005,331,5,2.0,1980-03-30 00:00:00 -3006,331,0,3.0,1980-03-30 00:00:00 -3007,331,26,1.0,1980-03-30 00:00:00 -3008,331,54,4.0,1980-03-30 00:00:00 -3009,332,43,0.0,1980-05-04 00:00:00 -3010,332,56,0.0,1980-05-04 00:00:00 -3011,332,55,0.0,1980-05-04 00:00:00 -3012,332,33,0.0,1980-05-04 00:00:00 -3013,332,49,0.0,1980-05-04 00:00:00 -3014,332,20,0.0,1980-05-04 00:00:00 -3015,332,52,0.0,1980-05-04 00:00:00 -3016,332,31,0.0,1980-05-04 00:00:00 -3017,332,5,1.0,1980-05-04 00:00:00 -3018,332,24,2.0,1980-05-04 00:00:00 -3019,332,3,3.0,1980-05-04 00:00:00 -3020,332,2,10.0,1980-05-04 00:00:00 -3021,332,26,9.0,1980-05-04 00:00:00 -3022,332,0,0.0,1980-05-04 00:00:00 -3023,332,54,0.0,1980-05-04 00:00:00 -3024,333,26,6.0,1980-05-18 00:00:00 -3025,333,2,9.0,1980-05-18 00:00:00 -3026,333,55,0.0,1980-05-18 00:00:00 -3027,333,56,0.0,1980-05-18 00:00:00 -3028,333,43,0.0,1980-05-18 00:00:00 -3029,333,0,0.0,1980-05-18 00:00:00 -3030,333,24,0.0,1980-05-18 00:00:00 -3031,333,49,0.0,1980-05-18 00:00:00 -3032,333,33,4.0,1980-05-18 00:00:00 -3033,333,52,0.0,1980-05-18 00:00:00 -3034,333,31,0.0,1980-05-18 00:00:00 -3035,333,54,1.0,1980-05-18 00:00:00 -3036,333,5,2.0,1980-05-18 00:00:00 -3037,333,20,3.0,1980-05-18 00:00:00 -3038,333,3,0.0,1980-05-18 00:00:00 -3039,334,31,0.0,1980-06-29 00:00:00 -3040,334,49,0.0,1980-06-29 00:00:00 -3041,334,52,0.0,1980-06-29 00:00:00 -3042,334,43,0.0,1980-06-29 00:00:00 -3043,334,54,0.0,1980-06-29 00:00:00 -3044,334,24,0.0,1980-06-29 00:00:00 -3045,334,0,0.0,1980-06-29 00:00:00 -3046,334,5,0.0,1980-06-29 00:00:00 -3047,334,3,2.0,1980-06-29 00:00:00 -3048,334,33,3.0,1980-06-29 00:00:00 -3049,334,26,10.0,1980-06-29 00:00:00 -3050,334,56,0.0,1980-06-29 00:00:00 -3051,334,20,0.0,1980-06-29 00:00:00 -3052,334,2,10.0,1980-06-29 00:00:00 -3053,334,55,0.0,1980-06-29 00:00:00 -3054,335,52,0.0,1980-07-13 00:00:00 -3055,335,33,6.0,1980-07-13 00:00:00 -3056,335,24,5.0,1980-07-13 00:00:00 -3057,335,0,1.0,1980-07-13 00:00:00 -3058,335,20,0.0,1980-07-13 00:00:00 -3059,335,55,0.0,1980-07-13 00:00:00 -3060,335,43,0.0,1980-07-13 00:00:00 -3061,335,49,0.0,1980-07-13 00:00:00 -3062,335,31,0.0,1980-07-13 00:00:00 -3063,335,2,13.0,1980-07-13 00:00:00 -3064,335,26,0.0,1980-07-13 00:00:00 -3065,335,3,0.0,1980-07-13 00:00:00 -3066,335,54,0.0,1980-07-13 00:00:00 -3067,335,5,0.0,1980-07-13 00:00:00 -3068,336,52,0.0,1980-08-10 00:00:00 -3069,336,3,0.0,1980-08-10 00:00:00 -3070,336,43,0.0,1980-08-10 00:00:00 -3071,336,54,0.0,1980-08-10 00:00:00 -3072,336,31,0.0,1980-08-10 00:00:00 -3073,336,0,0.0,1980-08-10 00:00:00 -3074,336,5,1.0,1980-08-10 00:00:00 -3075,336,55,0.0,1980-08-10 00:00:00 -3076,336,20,0.0,1980-08-10 00:00:00 -3077,336,26,9.0,1980-08-10 00:00:00 -3078,336,2,10.0,1980-08-10 00:00:00 -3079,336,33,3.0,1980-08-10 00:00:00 -3080,336,49,2.0,1980-08-10 00:00:00 -3081,336,24,0.0,1980-08-10 00:00:00 -3082,337,55,0.0,1980-08-17 00:00:00 -3083,337,43,0.0,1980-08-17 00:00:00 -3084,337,24,0.0,1980-08-17 00:00:00 -3085,337,49,0.0,1980-08-17 00:00:00 -3086,337,20,0.0,1980-08-17 00:00:00 -3087,337,52,0.0,1980-08-17 00:00:00 -3088,337,54,0.0,1980-08-17 00:00:00 -3089,337,0,0.0,1980-08-17 00:00:00 -3090,337,31,1.0,1980-08-17 00:00:00 -3091,337,33,2.0,1980-08-17 00:00:00 -3092,337,26,3.0,1980-08-17 00:00:00 -3093,337,2,10.0,1980-08-17 00:00:00 -3094,337,3,9.0,1980-08-17 00:00:00 -3095,337,5,0.0,1980-08-17 00:00:00 -3096,338,49,0.0,1980-08-31 00:00:00 -3097,338,43,0.0,1980-08-31 00:00:00 -3098,338,20,0.0,1980-08-31 00:00:00 -3099,338,55,0.0,1980-08-31 00:00:00 -3100,338,54,0.0,1980-08-31 00:00:00 -3101,338,52,0.0,1980-08-31 00:00:00 -3102,338,5,0.0,1980-08-31 00:00:00 -3103,338,0,1.0,1980-08-31 00:00:00 -3104,338,33,9.0,1980-08-31 00:00:00 -3105,338,3,6.0,1980-08-31 00:00:00 -3106,338,26,4.0,1980-08-31 00:00:00 -3107,338,2,3.0,1980-08-31 00:00:00 -3108,338,24,2.0,1980-08-31 00:00:00 -3109,338,31,0.0,1980-08-31 00:00:00 -3110,339,20,0.0,1980-09-14 00:00:00 -3111,339,52,0.0,1980-09-14 00:00:00 -3112,339,24,0.0,1980-09-14 00:00:00 -3113,339,43,0.0,1980-09-14 00:00:00 -3114,339,3,0.0,1980-09-14 00:00:00 -3115,339,55,0.0,1980-09-14 00:00:00 -3116,339,0,0.0,1980-09-14 00:00:00 -3117,339,26,1.0,1980-09-14 00:00:00 -3118,339,31,3.0,1980-09-14 00:00:00 -3119,339,2,10.0,1980-09-14 00:00:00 -3120,339,33,9.0,1980-09-14 00:00:00 -3121,339,5,0.0,1980-09-14 00:00:00 -3122,339,54,2.0,1980-09-14 00:00:00 -3123,339,49,0.0,1980-09-14 00:00:00 -3124,340,2,15.0,1980-09-28 00:00:00 -3125,340,0,3.0,1980-09-28 00:00:00 -3126,340,5,2.0,1980-09-28 00:00:00 -3127,340,33,1.0,1980-09-28 00:00:00 -3128,340,24,0.0,1980-09-28 00:00:00 -3129,340,54,0.0,1980-09-28 00:00:00 -3130,340,31,0.0,1980-09-28 00:00:00 -3131,340,20,0.0,1980-09-28 00:00:00 -3132,340,55,0.0,1980-09-28 00:00:00 -3133,340,3,0.0,1980-09-28 00:00:00 -3134,340,49,0.0,1980-09-28 00:00:00 -3135,340,43,0.0,1980-09-28 00:00:00 -3136,340,52,0.0,1980-09-28 00:00:00 -3137,340,26,4.0,1980-09-28 00:00:00 -3138,341,2,15.0,1980-10-05 00:00:00 -3139,341,31,4.0,1980-10-05 00:00:00 -3140,341,3,0.0,1980-10-05 00:00:00 -3141,341,52,0.0,1980-10-05 00:00:00 -3142,341,54,0.0,1980-10-05 00:00:00 -3143,341,5,0.0,1980-10-05 00:00:00 -3144,341,0,0.0,1980-10-05 00:00:00 -3145,341,24,0.0,1980-10-05 00:00:00 -3146,341,20,0.0,1980-10-05 00:00:00 -3147,341,49,0.0,1980-10-05 00:00:00 -3148,341,33,0.0,1980-10-05 00:00:00 -3149,341,43,0.0,1980-10-05 00:00:00 -3150,341,55,0.0,1980-10-05 00:00:00 -3151,341,26,6.0,1980-10-05 00:00:00 -3152,342,36,0.0,1981-03-15 00:00:00 -3153,342,49,3.0,1981-03-15 00:00:00 -3154,342,5,0.0,1981-03-15 00:00:00 -3155,342,31,0.0,1981-03-15 00:00:00 -3156,342,43,0.0,1981-03-15 00:00:00 -3157,342,20,0.0,1981-03-15 00:00:00 -3158,342,52,0.0,1981-03-15 00:00:00 -3159,342,26,0.0,1981-03-15 00:00:00 -3160,342,0,0.0,1981-03-15 00:00:00 -3161,342,2,15.0,1981-03-15 00:00:00 -3162,342,3,0.0,1981-03-15 00:00:00 -3163,342,54,0.0,1981-03-15 00:00:00 -3164,342,53,1.0,1981-03-15 00:00:00 -3165,342,24,2.0,1981-03-15 00:00:00 -3166,342,33,4.0,1981-03-15 00:00:00 -3167,342,55,0.0,1981-03-15 00:00:00 -3168,343,2,15.0,1981-03-29 00:00:00 -3169,343,20,4.0,1981-03-29 00:00:00 -3170,343,31,2.0,1981-03-29 00:00:00 -3171,343,55,3.0,1981-03-29 00:00:00 -3172,343,26,1.0,1981-03-29 00:00:00 -3173,343,0,0.0,1981-03-29 00:00:00 -3174,343,54,0.0,1981-03-29 00:00:00 -3175,343,53,0.0,1981-03-29 00:00:00 -3176,343,33,0.0,1981-03-29 00:00:00 -3177,343,24,0.0,1981-03-29 00:00:00 -3178,343,49,0.0,1981-03-29 00:00:00 -3179,343,5,0.0,1981-03-29 00:00:00 -3180,343,3,0.0,1981-03-29 00:00:00 -3181,343,52,0.0,1981-03-29 00:00:00 -3182,343,43,0.0,1981-03-29 00:00:00 -3183,343,36,0.0,1981-03-29 00:00:00 -3184,344,49,0.0,1981-04-12 00:00:00 -3185,344,33,9.0,1981-04-12 00:00:00 -3186,344,2,9.0,1981-04-12 00:00:00 -3187,344,3,6.0,1981-04-12 00:00:00 -3188,344,36,0.0,1981-04-12 00:00:00 -3189,344,43,0.0,1981-04-12 00:00:00 -3190,344,55,0.0,1981-04-12 00:00:00 -3191,344,26,0.0,1981-04-12 00:00:00 -3192,344,54,0.0,1981-04-12 00:00:00 -3193,344,53,0.0,1981-04-12 00:00:00 -3194,344,31,1.0,1981-04-12 00:00:00 -3195,344,24,0.0,1981-04-12 00:00:00 -3196,344,52,0.0,1981-04-12 00:00:00 -3197,344,0,0.0,1981-04-12 00:00:00 -3198,344,20,0.0,1981-04-12 00:00:00 -3199,344,5,0.0,1981-04-12 00:00:00 -3200,345,0,1.0,1981-05-03 00:00:00 -3201,345,53,0.0,1981-05-03 00:00:00 -3202,345,31,0.0,1981-05-03 00:00:00 -3203,345,33,12.0,1981-05-03 00:00:00 -3204,345,20,6.0,1981-05-03 00:00:00 -3205,345,2,4.0,1981-05-03 00:00:00 -3206,345,5,2.0,1981-05-03 00:00:00 -3207,345,3,0.0,1981-05-03 00:00:00 -3208,345,55,0.0,1981-05-03 00:00:00 -3209,345,51,0.0,1981-05-03 00:00:00 -3210,345,52,0.0,1981-05-03 00:00:00 -3211,345,26,0.0,1981-05-03 00:00:00 -3212,345,36,0.0,1981-05-03 00:00:00 -3213,345,24,0.0,1981-05-03 00:00:00 -3214,345,43,0.0,1981-05-03 00:00:00 -3215,345,49,0.0,1981-05-03 00:00:00 -3216,345,54,0.0,1981-05-03 00:00:00 -3217,346,26,6.0,1981-05-17 00:00:00 -3218,346,2,9.0,1981-05-17 00:00:00 -3219,346,31,6.0,1981-05-17 00:00:00 -3220,346,51,0.0,1981-05-17 00:00:00 -3221,346,5,3.0,1981-05-17 00:00:00 -3222,346,24,1.0,1981-05-17 00:00:00 -3223,346,0,0.0,1981-05-17 00:00:00 -3224,346,49,0.0,1981-05-17 00:00:00 -3225,346,55,0.0,1981-05-17 00:00:00 -3226,346,43,0.0,1981-05-17 00:00:00 -3227,346,33,0.0,1981-05-17 00:00:00 -3228,346,54,0.0,1981-05-17 00:00:00 -3229,346,3,0.0,1981-05-17 00:00:00 -3230,346,20,0.0,1981-05-17 00:00:00 -3231,346,36,0.0,1981-05-17 00:00:00 -3232,346,52,0.0,1981-05-17 00:00:00 -3233,346,53,0.0,1981-05-17 00:00:00 -3234,347,26,4.0,1981-05-31 00:00:00 -3235,347,24,2.0,1981-05-31 00:00:00 -3236,347,51,0.0,1981-05-31 00:00:00 -3237,347,36,0.0,1981-05-31 00:00:00 -3238,347,52,0.0,1981-05-31 00:00:00 -3239,347,43,0.0,1981-05-31 00:00:00 -3240,347,54,0.0,1981-05-31 00:00:00 -3241,347,20,0.0,1981-05-31 00:00:00 -3242,347,31,0.0,1981-05-31 00:00:00 -3243,347,3,0.0,1981-05-31 00:00:00 -3244,347,2,6.0,1981-05-31 00:00:00 -3245,347,0,0.0,1981-05-31 00:00:00 -3246,347,33,0.0,1981-05-31 00:00:00 -3247,347,53,0.0,1981-05-31 00:00:00 -3248,347,55,1.0,1981-05-31 00:00:00 -3249,347,5,12.0,1981-05-31 00:00:00 -3250,347,49,0.0,1981-05-31 00:00:00 -3251,348,52,0.0,1981-06-21 00:00:00 -3252,348,5,9.0,1981-06-21 00:00:00 -3253,348,0,4.0,1981-06-21 00:00:00 -3254,348,2,3.0,1981-06-21 00:00:00 -3255,348,31,3.0,1981-06-21 00:00:00 -3256,348,26,6.0,1981-06-21 00:00:00 -3257,348,3,0.0,1981-06-21 00:00:00 -3258,348,51,0.0,1981-06-21 00:00:00 -3259,348,54,0.0,1981-06-21 00:00:00 -3260,348,49,0.0,1981-06-21 00:00:00 -3261,348,55,0.0,1981-06-21 00:00:00 -3262,348,36,0.0,1981-06-21 00:00:00 -3263,348,24,0.0,1981-06-21 00:00:00 -3264,348,33,0.0,1981-06-21 00:00:00 -3265,348,20,0.0,1981-06-21 00:00:00 -3266,348,43,0.0,1981-06-21 00:00:00 -3267,348,53,0.0,1981-06-21 00:00:00 -3268,349,0,6.0,1981-07-05 00:00:00 -3269,349,33,4.0,1981-07-05 00:00:00 -3270,349,5,2.0,1981-07-05 00:00:00 -3271,349,31,1.0,1981-07-05 00:00:00 -3272,349,49,0.0,1981-07-05 00:00:00 -3273,349,2,0.0,1981-07-05 00:00:00 -3274,349,24,0.0,1981-07-05 00:00:00 -3275,349,53,0.0,1981-07-05 00:00:00 -3276,349,26,0.0,1981-07-05 00:00:00 -3277,349,36,0.0,1981-07-05 00:00:00 -3278,349,54,0.0,1981-07-05 00:00:00 -3279,349,55,0.0,1981-07-05 00:00:00 -3280,349,51,0.0,1981-07-05 00:00:00 -3281,349,3,12.0,1981-07-05 00:00:00 -3282,349,43,0.0,1981-07-05 00:00:00 -3283,349,20,0.0,1981-07-05 00:00:00 -3284,349,52,0.0,1981-07-05 00:00:00 -3285,350,5,0.0,1981-07-18 00:00:00 -3286,350,0,9.0,1981-07-18 00:00:00 -3287,350,2,6.0,1981-07-18 00:00:00 -3288,350,26,4.0,1981-07-18 00:00:00 -3289,350,24,3.0,1981-07-18 00:00:00 -3290,350,33,2.0,1981-07-18 00:00:00 -3291,350,36,0.0,1981-07-18 00:00:00 -3292,350,43,0.0,1981-07-18 00:00:00 -3293,350,3,0.0,1981-07-18 00:00:00 -3294,350,20,0.0,1981-07-18 00:00:00 -3295,350,53,0.0,1981-07-18 00:00:00 -3296,350,49,0.0,1981-07-18 00:00:00 -3297,350,54,0.0,1981-07-18 00:00:00 -3298,350,31,0.0,1981-07-18 00:00:00 -3299,350,51,0.0,1981-07-18 00:00:00 -3300,350,52,1.0,1981-07-18 00:00:00 -3301,350,55,0.0,1981-07-18 00:00:00 -3302,351,53,0.0,1981-08-02 00:00:00 -3303,351,51,0.0,1981-08-02 00:00:00 -3304,351,54,0.0,1981-08-02 00:00:00 -3305,351,36,0.0,1981-08-02 00:00:00 -3306,351,52,0.0,1981-08-02 00:00:00 -3307,351,55,0.0,1981-08-02 00:00:00 -3308,351,20,0.0,1981-08-02 00:00:00 -3309,351,2,0.0,1981-08-02 00:00:00 -3310,351,5,0.0,1981-08-02 00:00:00 -3311,351,43,0.0,1981-08-02 00:00:00 -3312,351,31,0.0,1981-08-02 00:00:00 -3313,351,0,1.0,1981-08-02 00:00:00 -3314,351,24,2.0,1981-08-02 00:00:00 -3315,351,26,4.0,1981-08-02 00:00:00 -3316,351,3,6.0,1981-08-02 00:00:00 -3317,351,33,12.0,1981-08-02 00:00:00 -3318,351,49,0.0,1981-08-02 00:00:00 -3319,352,20,0.0,1981-08-16 00:00:00 -3320,352,52,0.0,1981-08-16 00:00:00 -3321,352,55,0.0,1981-08-16 00:00:00 -3322,352,51,0.0,1981-08-16 00:00:00 -3323,352,53,0.0,1981-08-16 00:00:00 -3324,352,49,0.0,1981-08-16 00:00:00 -3325,352,24,0.0,1981-08-16 00:00:00 -3326,352,36,0.0,1981-08-16 00:00:00 -3327,352,5,0.0,1981-08-16 00:00:00 -3328,352,31,0.0,1981-08-16 00:00:00 -3329,352,0,1.0,1981-08-16 00:00:00 -3330,352,2,5.0,1981-08-16 00:00:00 -3331,352,33,4.0,1981-08-16 00:00:00 -3332,352,3,6.0,1981-08-16 00:00:00 -3333,352,26,9.0,1981-08-16 00:00:00 -3334,352,43,0.0,1981-08-16 00:00:00 -3335,353,51,0.0,1981-08-30 00:00:00 -3336,353,36,0.0,1981-08-30 00:00:00 -3337,353,26,0.0,1981-08-30 00:00:00 -3338,353,43,0.0,1981-08-30 00:00:00 -3339,353,0,0.0,1981-08-30 00:00:00 -3340,353,49,0.0,1981-08-30 00:00:00 -3341,353,52,0.0,1981-08-30 00:00:00 -3342,353,55,1.0,1981-08-30 00:00:00 -3343,353,53,0.0,1981-08-30 00:00:00 -3344,353,20,0.0,1981-08-30 00:00:00 -3345,353,31,2.0,1981-08-30 00:00:00 -3346,353,2,4.0,1981-08-30 00:00:00 -3347,353,33,9.0,1981-08-30 00:00:00 -3348,353,3,9.0,1981-08-30 00:00:00 -3349,353,24,0.0,1981-08-30 00:00:00 -3350,353,54,0.0,1981-08-30 00:00:00 -3351,353,5,0.0,1981-08-30 00:00:00 -3352,354,2,10.0,1981-09-13 00:00:00 -3353,354,31,3.0,1981-09-13 00:00:00 -3354,354,54,0.0,1981-09-13 00:00:00 -3355,354,53,0.0,1981-09-13 00:00:00 -3356,354,52,0.0,1981-09-13 00:00:00 -3357,354,55,0.0,1981-09-13 00:00:00 -3358,354,20,0.0,1981-09-13 00:00:00 -3359,354,26,0.0,1981-09-13 00:00:00 -3360,354,36,0.0,1981-09-13 00:00:00 -3361,354,24,0.0,1981-09-13 00:00:00 -3362,354,43,0.0,1981-09-13 00:00:00 -3363,354,49,0.0,1981-09-13 00:00:00 -3364,354,0,0.0,1981-09-13 00:00:00 -3365,354,33,1.0,1981-09-13 00:00:00 -3366,354,5,2.0,1981-09-13 00:00:00 -3367,354,3,9.0,1981-09-13 00:00:00 -3368,354,51,0.0,1981-09-13 00:00:00 -3369,355,24,0.0,1981-09-27 00:00:00 -3370,355,51,0.0,1981-09-27 00:00:00 -3371,355,54,0.0,1981-09-27 00:00:00 -3372,355,20,0.0,1981-09-27 00:00:00 -3373,355,55,0.0,1981-09-27 00:00:00 -3374,355,52,0.0,1981-09-27 00:00:00 -3375,355,3,0.0,1981-09-27 00:00:00 -3376,355,2,0.0,1981-09-27 00:00:00 -3377,355,43,0.0,1981-09-27 00:00:00 -3378,355,36,0.0,1981-09-27 00:00:00 -3379,355,31,1.0,1981-09-27 00:00:00 -3380,355,33,2.0,1981-09-27 00:00:00 -3381,355,49,3.0,1981-09-27 00:00:00 -3382,355,5,4.0,1981-09-27 00:00:00 -3383,355,0,6.0,1981-09-27 00:00:00 -3384,355,26,9.0,1981-09-27 00:00:00 -3385,355,53,0.0,1981-09-27 00:00:00 -3386,356,36,0.0,1981-10-17 00:00:00 -3387,356,52,0.0,1981-10-17 00:00:00 -3388,356,43,0.0,1981-10-17 00:00:00 -3389,356,53,0.0,1981-10-17 00:00:00 -3390,356,51,0.0,1981-10-17 00:00:00 -3391,356,55,0.0,1981-10-17 00:00:00 -3392,356,24,0.0,1981-10-17 00:00:00 -3393,356,20,0.0,1981-10-17 00:00:00 -3394,356,54,0.0,1981-10-17 00:00:00 -3395,356,0,0.0,1981-10-17 00:00:00 -3396,356,26,1.0,1981-10-17 00:00:00 -3397,356,33,2.0,1981-10-17 00:00:00 -3398,356,31,3.0,1981-10-17 00:00:00 -3399,356,49,4.0,1981-10-17 00:00:00 -3400,356,3,6.0,1981-10-17 00:00:00 -3401,356,2,9.0,1981-10-17 00:00:00 -3402,356,5,0.0,1981-10-17 00:00:00 -3403,357,54,0.0,1982-01-23 00:00:00 -3404,357,55,0.0,1982-01-23 00:00:00 -3405,357,20,0.0,1982-01-23 00:00:00 -3406,357,43,0.0,1982-01-23 00:00:00 -3407,357,51,0.0,1982-01-23 00:00:00 -3408,357,26,0.0,1982-01-23 00:00:00 -3409,357,5,0.0,1982-01-23 00:00:00 -3410,357,53,0.0,1982-01-23 00:00:00 -3411,357,33,0.0,1982-01-23 00:00:00 -3412,357,49,0.0,1982-01-23 00:00:00 -3413,357,52,0.0,1982-01-23 00:00:00 -3414,357,31,0.0,1982-01-23 00:00:00 -3415,357,24,0.0,1982-01-23 00:00:00 -3416,357,36,0.0,1982-01-23 00:00:00 -3417,357,0,4.0,1982-01-23 00:00:00 -3418,357,2,8.0,1982-01-23 00:00:00 -3419,357,3,13.0,1982-01-23 00:00:00 -3420,358,55,0.0,1982-03-21 00:00:00 -3421,358,51,0.0,1982-03-21 00:00:00 -3422,358,53,0.0,1982-03-21 00:00:00 -3423,358,49,0.0,1982-03-21 00:00:00 -3424,358,26,0.0,1982-03-21 00:00:00 -3425,358,54,0.0,1982-03-21 00:00:00 -3426,358,2,0.0,1982-03-21 00:00:00 -3427,358,33,0.0,1982-03-21 00:00:00 -3428,358,20,0.0,1982-03-21 00:00:00 -3429,358,43,0.0,1982-03-21 00:00:00 -3430,358,36,0.0,1982-03-21 00:00:00 -3431,358,5,1.0,1982-03-21 00:00:00 -3432,358,52,2.0,1982-03-21 00:00:00 -3433,358,24,3.0,1982-03-21 00:00:00 -3434,358,31,4.0,1982-03-21 00:00:00 -3435,358,0,6.0,1982-03-21 00:00:00 -3436,358,3,9.0,1982-03-21 00:00:00 -3437,359,54,0.0,1982-04-04 00:00:00 -3438,359,51,0.0,1982-04-04 00:00:00 -3439,359,52,0.0,1982-04-04 00:00:00 -3440,359,3,0.0,1982-04-04 00:00:00 -3441,359,53,0.0,1982-04-04 00:00:00 -3442,359,43,0.0,1982-04-04 00:00:00 -3443,359,55,0.0,1982-04-04 00:00:00 -3444,359,20,0.0,1982-04-04 00:00:00 -3445,359,24,3.0,1982-04-04 00:00:00 -3446,359,26,0.0,1982-04-04 00:00:00 -3447,359,5,0.0,1982-04-04 00:00:00 -3448,359,36,0.0,1982-04-04 00:00:00 -3449,359,31,2.0,1982-04-04 00:00:00 -3450,359,33,4.0,1982-04-04 00:00:00 -3451,359,2,6.0,1982-04-04 00:00:00 -3452,359,0,10.0,1982-04-04 00:00:00 -3453,359,49,0.0,1982-04-04 00:00:00 -3454,360,49,0.0,1982-04-25 00:00:00 -3455,360,3,0.0,1982-04-25 00:00:00 -3456,360,51,0.0,1982-04-25 00:00:00 -3457,360,52,2.0,1982-04-25 00:00:00 -3458,360,24,4.0,1982-04-25 00:00:00 -3459,360,5,15.0,1982-04-25 00:00:00 -3460,360,43,3.0,1982-04-25 00:00:00 -3461,361,43,0.0,1982-05-09 00:00:00 -3462,361,55,0.0,1982-05-09 00:00:00 -3463,361,5,0.0,1982-05-09 00:00:00 -3464,361,52,0.0,1982-05-09 00:00:00 -3465,361,51,0.0,1982-05-09 00:00:00 -3466,361,24,0.0,1982-05-09 00:00:00 -3467,361,53,0.0,1982-05-09 00:00:00 -3468,361,3,0.0,1982-05-09 00:00:00 -3469,361,49,0.0,1982-05-09 00:00:00 -3470,361,20,0.0,1982-05-09 00:00:00 -3471,361,54,1.0,1982-05-09 00:00:00 -3472,361,33,2.0,1982-05-09 00:00:00 -3473,361,31,3.0,1982-05-09 00:00:00 -3474,361,26,4.0,1982-05-09 00:00:00 -3475,361,2,6.0,1982-05-09 00:00:00 -3476,361,0,9.0,1982-05-09 00:00:00 -3477,361,36,0.0,1982-05-09 00:00:00 -3478,362,54,0.0,1982-05-23 00:00:00 -3479,362,55,0.0,1982-05-23 00:00:00 -3480,362,43,0.0,1982-05-23 00:00:00 -3481,362,51,0.0,1982-05-23 00:00:00 -3482,362,36,0.0,1982-05-23 00:00:00 -3483,362,53,0.0,1982-05-23 00:00:00 -3484,362,26,0.0,1982-05-23 00:00:00 -3485,362,52,0.0,1982-05-23 00:00:00 -3486,362,0,0.0,1982-05-23 00:00:00 -3487,362,20,0.0,1982-05-23 00:00:00 -3488,362,24,0.0,1982-05-23 00:00:00 -3489,362,3,0.0,1982-05-23 00:00:00 -3490,362,2,1.0,1982-05-23 00:00:00 -3491,362,31,5.0,1982-05-23 00:00:00 -3492,362,49,4.0,1982-05-23 00:00:00 -3493,362,5,6.0,1982-05-23 00:00:00 -3494,362,33,9.0,1982-05-23 00:00:00 -3495,363,43,0.0,1982-06-06 00:00:00 -3496,363,33,0.0,1982-06-06 00:00:00 -3497,363,55,0.0,1982-06-06 00:00:00 -3498,363,52,0.0,1982-06-06 00:00:00 -3499,363,49,0.0,1982-06-06 00:00:00 -3500,363,53,0.0,1982-06-06 00:00:00 -3501,363,31,0.0,1982-06-06 00:00:00 -3502,363,54,0.0,1982-06-06 00:00:00 -3503,363,20,0.0,1982-06-06 00:00:00 -3504,363,24,0.0,1982-06-06 00:00:00 -3505,363,36,0.0,1982-06-06 00:00:00 -3506,363,2,5.0,1982-06-06 00:00:00 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-3534,365,55,0.0,1982-07-03 00:00:00 -3535,365,51,0.0,1982-07-03 00:00:00 -3536,365,54,0.0,1982-07-03 00:00:00 -3537,365,3,0.0,1982-07-03 00:00:00 -3538,365,26,0.0,1982-07-03 00:00:00 -3539,365,53,0.0,1982-07-03 00:00:00 -3540,365,36,0.0,1982-07-03 00:00:00 -3541,365,43,0.0,1982-07-03 00:00:00 -3542,365,52,0.0,1982-07-03 00:00:00 -3543,365,24,0.0,1982-07-03 00:00:00 -3544,366,26,0.0,1982-07-18 00:00:00 -3545,366,53,0.0,1982-07-18 00:00:00 -3546,366,52,0.0,1982-07-18 00:00:00 -3547,366,43,0.0,1982-07-18 00:00:00 -3548,366,55,0.0,1982-07-18 00:00:00 -3549,366,33,0.0,1982-07-18 00:00:00 -3550,366,51,0.0,1982-07-18 00:00:00 -3551,366,36,0.0,1982-07-18 00:00:00 -3552,366,54,0.0,1982-07-18 00:00:00 -3553,366,24,0.0,1982-07-18 00:00:00 -3554,366,49,0.0,1982-07-18 00:00:00 -3555,366,3,1.0,1982-07-18 00:00:00 -3556,366,2,2.0,1982-07-18 00:00:00 -3557,366,31,3.0,1982-07-18 00:00:00 -3558,366,5,10.0,1982-07-18 00:00:00 -3559,366,0,9.0,1982-07-18 00:00:00 -3560,366,20,0.0,1982-07-18 00:00:00 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-3588,368,49,2.0,1982-08-08 00:00:00 -3589,368,24,3.0,1982-08-08 00:00:00 -3590,368,2,4.0,1982-08-08 00:00:00 -3591,368,3,6.0,1982-08-08 00:00:00 -3592,368,5,9.0,1982-08-08 00:00:00 -3593,368,51,0.0,1982-08-08 00:00:00 -3594,369,43,0.0,1982-08-15 00:00:00 -3595,369,49,0.0,1982-08-15 00:00:00 -3596,369,55,0.0,1982-08-15 00:00:00 -3597,369,51,0.0,1982-08-15 00:00:00 -3598,369,52,0.0,1982-08-15 00:00:00 -3599,369,53,0.0,1982-08-15 00:00:00 -3600,369,33,0.0,1982-08-15 00:00:00 -3601,369,24,0.0,1982-08-15 00:00:00 -3602,369,36,0.0,1982-08-15 00:00:00 -3603,369,54,0.0,1982-08-15 00:00:00 -3604,369,20,1.0,1982-08-15 00:00:00 -3605,369,0,2.0,1982-08-15 00:00:00 -3606,369,5,3.0,1982-08-15 00:00:00 -3607,369,26,4.0,1982-08-15 00:00:00 -3608,369,2,6.0,1982-08-15 00:00:00 -3609,369,31,9.0,1982-08-15 00:00:00 -3610,369,3,0.0,1982-08-15 00:00:00 -3611,370,53,0.0,1982-08-29 00:00:00 -3612,370,54,0.0,1982-08-29 00:00:00 -3613,370,5,0.0,1982-08-29 00:00:00 -3614,370,55,0.0,1982-08-29 00:00:00 -3615,370,36,0.0,1982-08-29 00:00:00 -3616,370,51,0.0,1982-08-29 00:00:00 -3617,370,43,0.0,1982-08-29 00:00:00 -3618,370,26,0.0,1982-08-29 00:00:00 -3619,370,24,0.0,1982-08-29 00:00:00 -3620,370,52,0.0,1982-08-29 00:00:00 -3621,370,49,0.0,1982-08-29 00:00:00 -3622,370,31,1.0,1982-08-29 00:00:00 -3623,370,33,5.0,1982-08-29 00:00:00 -3624,370,0,4.0,1982-08-29 00:00:00 -3625,370,3,6.0,1982-08-29 00:00:00 -3626,370,2,9.0,1982-08-29 00:00:00 -3627,370,20,0.0,1982-08-29 00:00:00 -3628,371,55,0.0,1982-09-12 00:00:00 -3629,371,20,0.0,1982-09-12 00:00:00 -3630,371,43,0.0,1982-09-12 00:00:00 -3631,371,54,0.0,1982-09-12 00:00:00 -3632,371,51,0.0,1982-09-12 00:00:00 -3633,371,36,0.0,1982-09-12 00:00:00 -3634,371,53,0.0,1982-09-12 00:00:00 -3635,371,49,0.0,1982-09-12 00:00:00 -3636,371,33,0.0,1982-09-12 00:00:00 -3637,371,2,0.0,1982-09-12 00:00:00 -3638,371,31,0.0,1982-09-12 00:00:00 -3639,371,26,1.0,1982-09-12 00:00:00 -3640,371,24,2.0,1982-09-12 00:00:00 -3641,371,0,3.0,1982-09-12 00:00:00 -3642,371,5,10.0,1982-09-12 00:00:00 -3643,371,3,9.0,1982-09-12 00:00:00 -3644,371,52,0.0,1982-09-12 00:00:00 -3645,372,54,0.0,1982-09-25 00:00:00 -3646,372,43,0.0,1982-09-25 00:00:00 -3647,372,55,0.0,1982-09-25 00:00:00 -3648,372,33,0.0,1982-09-25 00:00:00 -3649,372,5,0.0,1982-09-25 00:00:00 -3650,372,31,0.0,1982-09-25 00:00:00 -3651,372,51,0.0,1982-09-25 00:00:00 -3652,372,53,0.0,1982-09-25 00:00:00 -3653,372,36,0.0,1982-09-25 00:00:00 -3654,372,49,0.0,1982-09-25 00:00:00 -3655,372,20,0.0,1982-09-25 00:00:00 -3656,372,2,3.0,1982-09-25 00:00:00 -3657,372,3,3.0,1982-09-25 00:00:00 -3658,372,26,4.0,1982-09-25 00:00:00 -3659,372,0,6.0,1982-09-25 00:00:00 -3660,372,24,9.0,1982-09-25 00:00:00 -3661,372,52,0.0,1982-09-25 00:00:00 -3662,373,53,0.0,1983-03-13 00:00:00 -3663,373,43,0.0,1983-03-13 00:00:00 -3664,373,49,0.0,1983-03-13 00:00:00 -3665,373,26,0.0,1983-03-13 00:00:00 -3666,373,52,0.0,1983-03-13 00:00:00 -3667,373,48,0.0,1983-03-13 00:00:00 -3668,373,31,0.0,1983-03-13 00:00:00 -3669,373,3,0.0,1983-03-13 00:00:00 -3670,373,51,0.0,1983-03-13 00:00:00 -3671,373,20,1.0,1983-03-13 00:00:00 -3672,373,5,2.0,1983-03-13 00:00:00 -3673,373,2,3.0,1983-03-13 00:00:00 -3674,373,0,4.0,1983-03-13 00:00:00 -3675,373,33,9.0,1983-03-13 00:00:00 -3676,373,24,0.0,1983-03-13 00:00:00 -3677,374,43,0.0,1983-03-27 00:00:00 -3678,374,52,0.0,1983-03-27 00:00:00 -3679,374,48,0.0,1983-03-27 00:00:00 -3680,374,51,0.0,1983-03-27 00:00:00 -3681,374,49,0.0,1983-03-27 00:00:00 -3682,374,31,0.0,1983-03-27 00:00:00 -3683,374,3,0.0,1983-03-27 00:00:00 -3684,374,33,0.0,1983-03-27 00:00:00 -3685,374,26,0.0,1983-03-27 00:00:00 -3686,374,53,1.0,1983-03-27 00:00:00 -3687,374,20,2.0,1983-03-27 00:00:00 -3688,374,2,3.0,1983-03-27 00:00:00 -3689,374,5,4.0,1983-03-27 00:00:00 -3690,374,0,15.0,1983-03-27 00:00:00 -3691,374,24,0.0,1983-03-27 00:00:00 -3692,375,51,0.0,1983-04-17 00:00:00 -3693,375,31,0.0,1983-04-17 00:00:00 -3694,375,48,0.0,1983-04-17 00:00:00 -3695,375,0,0.0,1983-04-17 00:00:00 -3696,375,52,0.0,1983-04-17 00:00:00 -3697,375,43,0.0,1983-04-17 00:00:00 -3698,375,49,0.0,1983-04-17 00:00:00 -3699,375,33,6.0,1983-04-17 00:00:00 -3700,375,20,0.0,1983-04-17 00:00:00 -3701,375,26,0.0,1983-04-17 00:00:00 -3702,375,24,0.0,1983-04-17 00:00:00 -3703,375,2,3.0,1983-04-17 00:00:00 -3704,375,5,3.0,1983-04-17 00:00:00 -3705,375,3,13.0,1983-04-17 00:00:00 -3706,375,53,0.0,1983-04-17 00:00:00 -3707,376,48,0.0,1983-05-01 00:00:00 -3708,376,53,0.0,1983-05-01 00:00:00 -3709,376,43,0.0,1983-05-01 00:00:00 -3710,376,51,0.0,1983-05-01 00:00:00 -3711,376,24,0.0,1983-05-01 00:00:00 -3712,376,33,0.0,1983-05-01 00:00:00 -3713,376,31,0.0,1983-05-01 00:00:00 -3714,376,52,0.0,1983-05-01 00:00:00 -3715,376,49,0.0,1983-05-01 00:00:00 -3716,376,26,0.0,1983-05-01 00:00:00 -3717,376,20,1.0,1983-05-01 00:00:00 -3718,376,0,2.0,1983-05-01 00:00:00 -3719,376,2,3.0,1983-05-01 00:00:00 -3720,376,3,6.0,1983-05-01 00:00:00 -3721,376,5,13.0,1983-05-01 00:00:00 -3722,377,48,0.0,1983-05-15 00:00:00 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-4479,429,24,0.0,1986-07-27 00:00:00 -4480,429,47,0.0,1986-07-27 00:00:00 -4481,429,20,0.0,1986-07-27 00:00:00 -4482,429,43,0.0,1986-07-27 00:00:00 -4483,429,5,0.0,1986-07-27 00:00:00 -4484,429,21,0.0,1986-07-27 00:00:00 -4485,429,25,0.0,1986-07-27 00:00:00 -4486,429,33,0.0,1986-07-27 00:00:00 -4487,429,0,3.0,1986-07-27 00:00:00 -4488,429,26,3.0,1986-07-27 00:00:00 -4489,429,31,6.0,1986-07-27 00:00:00 -4490,430,43,0.0,1986-08-10 00:00:00 -4491,430,33,0.0,1986-08-10 00:00:00 -4492,430,17,0.0,1986-08-10 00:00:00 -4493,430,0,0.0,1986-08-10 00:00:00 -4494,430,20,0.0,1986-08-10 00:00:00 -4495,430,24,1.0,1986-08-10 00:00:00 -4496,430,47,0.0,1986-08-10 00:00:00 -4497,430,26,0.0,1986-08-10 00:00:00 -4498,430,25,0.0,1986-08-10 00:00:00 -4499,430,5,3.0,1986-08-10 00:00:00 -4500,430,31,8.0,1986-08-10 00:00:00 -4501,430,21,0.0,1986-08-10 00:00:00 -4502,430,2,13.0,1986-08-10 00:00:00 -4503,431,33,0.0,1986-08-17 00:00:00 -4504,431,24,0.0,1986-08-17 00:00:00 -4505,431,31,0.0,1986-08-17 00:00:00 -4506,431,17,0.0,1986-08-17 00:00:00 -4507,431,2,0.0,1986-08-17 00:00:00 -4508,431,26,0.0,1986-08-17 00:00:00 -4509,431,47,0.0,1986-08-17 00:00:00 -4510,431,21,0.0,1986-08-17 00:00:00 -4511,431,20,1.0,1986-08-17 00:00:00 -4512,431,25,5.0,1986-08-17 00:00:00 -4513,431,5,10.0,1986-08-17 00:00:00 -4514,431,43,0.0,1986-08-17 00:00:00 -4515,431,0,9.0,1986-08-17 00:00:00 -4516,432,33,0.0,1986-09-07 00:00:00 -4517,432,47,0.0,1986-09-07 00:00:00 -4518,432,26,0.0,1986-09-07 00:00:00 -4519,432,38,0.0,1986-09-07 00:00:00 -4520,432,17,0.0,1986-09-07 00:00:00 -4521,432,31,0.0,1986-09-07 00:00:00 -4522,432,20,0.0,1986-09-07 00:00:00 -4523,432,43,0.0,1986-09-07 00:00:00 -4524,432,2,15.0,1986-09-07 00:00:00 -4525,432,5,4.0,1986-09-07 00:00:00 -4526,432,24,0.0,1986-09-07 00:00:00 -4527,432,21,2.0,1986-09-07 00:00:00 -4528,432,25,1.0,1986-09-07 00:00:00 -4529,432,0,3.0,1986-09-07 00:00:00 -4530,433,38,0.0,1986-09-21 00:00:00 -4531,433,24,0.0,1986-09-21 00:00:00 -4532,433,17,0.0,1986-09-21 00:00:00 -4533,433,25,0.0,1986-09-21 00:00:00 -4534,433,33,0.0,1986-09-21 00:00:00 -4535,433,43,0.0,1986-09-21 00:00:00 -4536,433,47,0.0,1986-09-21 00:00:00 -4537,433,26,0.0,1986-09-21 00:00:00 -4538,433,5,3.0,1986-09-21 00:00:00 -4539,433,31,3.0,1986-09-21 00:00:00 -4540,433,0,6.0,1986-09-21 00:00:00 -4541,433,2,13.0,1986-09-21 00:00:00 -4542,433,20,0.0,1986-09-21 00:00:00 -4543,433,21,0.0,1986-09-21 00:00:00 -4544,434,25,0.0,1986-10-12 00:00:00 -4545,434,43,0.0,1986-10-12 00:00:00 -4546,434,17,0.0,1986-10-12 00:00:00 -4547,434,21,9.0,1986-10-12 00:00:00 -4548,434,33,0.0,1986-10-12 00:00:00 -4549,434,0,6.0,1986-10-12 00:00:00 -4550,434,5,0.0,1986-10-12 00:00:00 -4551,434,31,4.0,1986-10-12 00:00:00 -4552,434,24,0.0,1986-10-12 00:00:00 -4553,434,47,0.0,1986-10-12 00:00:00 -4554,434,2,5.0,1986-10-12 00:00:00 -4555,434,20,0.0,1986-10-12 00:00:00 -4556,434,26,1.0,1986-10-12 00:00:00 -4557,435,24,5.0,1986-10-26 00:00:00 -4558,435,17,0.0,1986-10-26 00:00:00 -4559,435,20,0.0,1986-10-26 00:00:00 -4560,435,43,0.0,1986-10-26 00:00:00 -4561,435,33,0.0,1986-10-26 00:00:00 -4562,435,47,0.0,1986-10-26 00:00:00 -4563,435,26,0.0,1986-10-26 00:00:00 -4564,435,21,0.0,1986-10-26 00:00:00 -4565,435,25,0.0,1986-10-26 00:00:00 -4566,435,5,4.0,1986-10-26 00:00:00 -4567,435,2,6.0,1986-10-26 00:00:00 -4568,435,0,9.0,1986-10-26 00:00:00 -4569,435,31,1.0,1986-10-26 00:00:00 -4570,436,36,0.0,1987-04-12 00:00:00 -4571,436,43,0.0,1987-04-12 00:00:00 -4572,436,33,0.0,1987-04-12 00:00:00 -4573,436,20,0.0,1987-04-12 00:00:00 -4574,436,38,0.0,1987-04-12 00:00:00 -4575,436,47,0.0,1987-04-12 00:00:00 -4576,436,31,0.0,1987-04-12 00:00:00 -4577,436,21,2.0,1987-04-12 00:00:00 -4578,436,5,3.0,1987-04-12 00:00:00 -4579,436,2,7.0,1987-04-12 00:00:00 -4580,436,24,0.0,1987-04-12 00:00:00 -4581,436,17,0.0,1987-04-12 00:00:00 -4582,436,0,13.0,1987-04-12 00:00:00 -4583,437,24,0.0,1987-05-03 00:00:00 -4584,437,32,0.0,1987-05-03 00:00:00 -4585,437,33,0.0,1987-05-03 00:00:00 -4586,437,38,0.0,1987-05-03 00:00:00 -4587,437,47,2.0,1987-05-03 00:00:00 -4588,437,0,3.0,1987-05-03 00:00:00 -4589,437,5,4.0,1987-05-03 00:00:00 -4590,437,31,7.0,1987-05-03 00:00:00 -4591,437,2,9.0,1987-05-03 00:00:00 -4592,437,21,0.0,1987-05-03 00:00:00 -4593,437,17,0.0,1987-05-03 00:00:00 -4594,437,36,0.0,1987-05-03 00:00:00 -4595,437,26,0.0,1987-05-03 00:00:00 -4596,437,20,0.0,1987-05-03 00:00:00 -4597,437,43,0.0,1987-05-03 00:00:00 -4598,438,0,15.0,1987-05-17 00:00:00 -4599,438,31,2.0,1987-05-17 00:00:00 -4600,438,26,1.0,1987-05-17 00:00:00 -4601,438,32,0.0,1987-05-17 00:00:00 -4602,438,24,0.0,1987-05-17 00:00:00 -4603,438,38,0.0,1987-05-17 00:00:00 -4604,438,21,0.0,1987-05-17 00:00:00 -4605,438,47,0.0,1987-05-17 00:00:00 -4606,438,2,0.0,1987-05-17 00:00:00 -4607,438,36,0.0,1987-05-17 00:00:00 -4608,438,43,0.0,1987-05-17 00:00:00 -4609,438,5,0.0,1987-05-17 00:00:00 -4610,438,17,0.0,1987-05-17 00:00:00 -4611,438,20,3.0,1987-05-17 00:00:00 -4612,438,33,4.0,1987-05-17 00:00:00 -4613,439,24,2.0,1987-05-31 00:00:00 -4614,439,32,0.0,1987-05-31 00:00:00 -4615,439,36,1.0,1987-05-31 00:00:00 -4616,439,47,0.0,1987-05-31 00:00:00 -4617,439,21,0.0,1987-05-31 00:00:00 -4618,439,0,0.0,1987-05-31 00:00:00 -4619,439,26,0.0,1987-05-31 00:00:00 -4620,439,38,0.0,1987-05-31 00:00:00 -4621,439,31,9.0,1987-05-31 00:00:00 -4622,439,20,0.0,1987-05-31 00:00:00 -4623,439,5,7.0,1987-05-31 00:00:00 -4624,439,2,6.0,1987-05-31 00:00:00 -4625,439,43,0.0,1987-05-31 00:00:00 -4626,439,17,0.0,1987-05-31 00:00:00 -4627,439,33,0.0,1987-05-31 00:00:00 -4628,440,31,9.0,1987-06-21 00:00:00 -4629,440,2,8.0,1987-06-21 00:00:00 -4630,440,0,4.0,1987-06-21 00:00:00 -4631,440,5,3.0,1987-06-21 00:00:00 -4632,440,20,1.0,1987-06-21 00:00:00 -4633,440,47,0.0,1987-06-21 00:00:00 -4634,440,33,0.0,1987-06-21 00:00:00 -4635,440,38,0.0,1987-06-21 00:00:00 -4636,440,24,0.0,1987-06-21 00:00:00 -4637,440,21,0.0,1987-06-21 00:00:00 -4638,440,32,0.0,1987-06-21 00:00:00 -4639,440,17,0.0,1987-06-21 00:00:00 -4640,440,36,0.0,1987-06-21 00:00:00 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-5316,479,43,0.0,1989-09-10 00:00:00 -5317,479,32,0.0,1989-09-10 00:00:00 -5318,479,46,0.0,1989-09-10 00:00:00 -5319,479,20,0.0,1989-09-10 00:00:00 -5320,479,41,0.0,1989-09-10 00:00:00 -5321,479,47,0.0,1989-09-10 00:00:00 -5322,479,42,0.0,1989-09-10 00:00:00 -5323,479,38,0.0,1989-09-10 00:00:00 -5324,479,36,0.0,1989-09-10 00:00:00 -5325,479,31,0.0,1989-09-10 00:00:00 -5326,479,44,0.0,1989-09-10 00:00:00 -5327,479,21,0.0,1989-09-10 00:00:00 -5328,479,0,9.0,1989-09-10 00:00:00 -5329,479,2,7.0,1989-09-10 00:00:00 -5330,479,24,2.0,1989-09-10 00:00:00 -5331,479,5,6.0,1989-09-10 00:00:00 -5332,479,17,0.0,1989-09-10 00:00:00 -5333,479,26,0.0,1989-09-10 00:00:00 -5334,479,33,1.0,1989-09-10 00:00:00 -5335,479,34,0.0,1989-09-10 00:00:00 -5336,480,42,0.0,1989-09-24 00:00:00 -5337,480,43,0.0,1989-09-24 00:00:00 -5338,480,46,0.0,1989-09-24 00:00:00 -5339,480,41,0.0,1989-09-24 00:00:00 -5340,480,34,0.0,1989-09-24 00:00:00 -5341,480,20,0.0,1989-09-24 00:00:00 -5342,480,2,0.0,1989-09-24 00:00:00 -5343,480,26,0.0,1989-09-24 00:00:00 -5344,480,47,0.0,1989-09-24 00:00:00 -5345,480,32,0.0,1989-09-24 00:00:00 -5346,480,36,0.0,1989-09-24 00:00:00 -5347,480,5,9.0,1989-09-24 00:00:00 -5348,480,0,6.0,1989-09-24 00:00:00 -5349,480,44,4.0,1989-09-24 00:00:00 -5350,480,38,0.0,1989-09-24 00:00:00 -5351,480,17,2.0,1989-09-24 00:00:00 -5352,480,24,1.0,1989-09-24 00:00:00 -5353,480,31,0.0,1989-09-24 00:00:00 -5354,480,33,0.0,1989-09-24 00:00:00 -5355,480,21,3.0,1989-09-24 00:00:00 -5356,481,42,0.0,1989-10-01 00:00:00 -5357,481,47,0.0,1989-10-01 00:00:00 -5358,481,41,0.0,1989-10-01 00:00:00 -5359,481,38,0.0,1989-10-01 00:00:00 -5360,481,46,0.0,1989-10-01 00:00:00 -5361,481,43,0.0,1989-10-01 00:00:00 -5362,481,44,0.0,1989-10-01 00:00:00 -5363,481,26,0.0,1989-10-01 00:00:00 -5364,481,17,0.0,1989-10-01 00:00:00 -5365,481,33,0.0,1989-10-01 00:00:00 -5366,481,21,0.0,1989-10-01 00:00:00 -5367,481,20,0.0,1989-10-01 00:00:00 -5368,481,34,0.0,1989-10-01 00:00:00 -5369,481,32,1.0,1989-10-01 00:00:00 -5370,481,2,2.0,1989-10-01 00:00:00 -5371,481,24,3.0,1989-10-01 00:00:00 -5372,481,5,6.0,1989-10-01 00:00:00 -5373,481,0,13.0,1989-10-01 00:00:00 -5374,481,36,0.0,1989-10-01 00:00:00 -5375,481,31,0.0,1989-10-01 00:00:00 -5376,482,38,0.0,1989-10-22 00:00:00 -5377,482,21,9.0,1989-10-22 00:00:00 -5378,482,42,0.0,1989-10-22 00:00:00 -5379,482,44,0.0,1989-10-22 00:00:00 -5380,482,41,0.0,1989-10-22 00:00:00 -5381,482,46,0.0,1989-10-22 00:00:00 -5382,482,47,0.0,1989-10-22 00:00:00 -5383,482,43,0.0,1989-10-22 00:00:00 -5384,482,26,0.0,1989-10-22 00:00:00 -5385,482,32,0.0,1989-10-22 00:00:00 -5386,482,17,0.0,1989-10-22 00:00:00 -5387,482,5,0.0,1989-10-22 00:00:00 -5388,482,0,0.0,1989-10-22 00:00:00 -5389,482,34,0.0,1989-10-22 00:00:00 -5390,482,36,0.0,1989-10-22 00:00:00 -5391,482,20,1.0,1989-10-22 00:00:00 -5392,482,33,2.0,1989-10-22 00:00:00 -5393,482,31,3.0,1989-10-22 00:00:00 -5394,482,2,10.0,1989-10-22 00:00:00 -5395,482,24,0.0,1989-10-22 00:00:00 -5396,483,32,0.0,1989-11-05 00:00:00 -5397,483,24,0.0,1989-11-05 00:00:00 -5398,483,46,0.0,1989-11-05 00:00:00 -5399,483,47,0.0,1989-11-05 00:00:00 -5400,483,2,13.0,1989-11-05 00:00:00 -5401,483,42,0.0,1989-11-05 00:00:00 -5402,483,38,0.0,1989-11-05 00:00:00 -5403,483,34,0.0,1989-11-05 00:00:00 -5404,483,41,0.0,1989-11-05 00:00:00 -5405,483,0,0.0,1989-11-05 00:00:00 -5406,483,44,0.0,1989-11-05 00:00:00 -5407,483,43,0.0,1989-11-05 00:00:00 -5408,483,26,0.0,1989-11-05 00:00:00 -5409,483,20,0.0,1989-11-05 00:00:00 -5410,483,33,0.0,1989-11-05 00:00:00 -5411,483,36,0.0,1989-11-05 00:00:00 -5412,483,17,1.0,1989-11-05 00:00:00 -5413,483,31,3.0,1989-11-05 00:00:00 -5414,483,21,8.0,1989-11-05 00:00:00 -5415,483,5,0.0,1989-11-05 00:00:00 -5416,484,17,0.0,1990-03-11 00:00:00 -5417,484,32,0.0,1990-03-11 00:00:00 -5418,484,20,0.0,1990-03-11 00:00:00 -5419,484,42,0.0,1990-03-11 00:00:00 -5420,484,40,0.0,1990-03-11 00:00:00 -5421,484,5,0.0,1990-03-11 00:00:00 -5422,484,44,0.0,1990-03-11 00:00:00 -5423,484,34,0.0,1990-03-11 00:00:00 -5424,484,31,0.0,1990-03-11 00:00:00 -5425,484,26,0.0,1990-03-11 00:00:00 -5426,484,38,0.0,1990-03-11 00:00:00 -5427,484,41,0.0,1990-03-11 00:00:00 -5428,484,33,2.0,1990-03-11 00:00:00 -5429,484,43,0.0,1990-03-11 00:00:00 -5430,484,21,3.0,1990-03-11 00:00:00 -5431,484,45,0.0,1990-03-11 00:00:00 -5432,484,24,7.0,1990-03-11 00:00:00 -5433,484,0,9.0,1990-03-11 00:00:00 -5434,484,2,4.0,1990-03-11 00:00:00 -5435,485,17,0.0,1990-03-25 00:00:00 -5436,485,26,0.0,1990-03-25 00:00:00 -5437,485,34,0.0,1990-03-25 00:00:00 -5438,485,20,0.0,1990-03-25 00:00:00 -5439,485,31,0.0,1990-03-25 00:00:00 -5440,485,33,0.0,1990-03-25 00:00:00 -5441,485,38,0.0,1990-03-25 00:00:00 -5442,485,32,0.0,1990-03-25 00:00:00 -5443,485,43,0.0,1990-03-25 00:00:00 -5444,485,44,0.0,1990-03-25 00:00:00 -5445,485,40,0.0,1990-03-25 00:00:00 -5446,485,42,0.0,1990-03-25 00:00:00 -5447,485,41,0.0,1990-03-25 00:00:00 -5448,485,45,0.0,1990-03-25 00:00:00 -5449,485,24,0.0,1990-03-25 00:00:00 -5450,485,21,1.0,1990-03-25 00:00:00 -5451,485,2,2.0,1990-03-25 00:00:00 -5452,485,0,10.0,1990-03-25 00:00:00 -5453,485,5,12.0,1990-03-25 00:00:00 -5454,486,31,0.0,1990-05-13 00:00:00 -5455,486,38,0.0,1990-05-13 00:00:00 -5456,486,45,0.0,1990-05-13 00:00:00 -5457,486,41,0.0,1990-05-13 00:00:00 -5458,486,20,0.0,1990-05-13 00:00:00 -5459,486,42,0.0,1990-05-13 00:00:00 -5460,486,40,0.0,1990-05-13 00:00:00 -5461,486,34,0.0,1990-05-13 00:00:00 -5462,486,33,0.0,1990-05-13 00:00:00 -5463,486,43,0.0,1990-05-13 00:00:00 -5464,486,32,0.0,1990-05-13 00:00:00 -5465,486,44,0.0,1990-05-13 00:00:00 -5466,486,17,0.0,1990-05-13 00:00:00 -5467,486,26,0.0,1990-05-13 00:00:00 -5468,486,24,1.0,1990-05-13 00:00:00 -5469,486,5,3.0,1990-05-13 00:00:00 -5470,486,21,6.0,1990-05-13 00:00:00 -5471,486,0,6.0,1990-05-13 00:00:00 -5472,486,2,9.0,1990-05-13 00:00:00 -5473,487,44,0.0,1990-05-27 00:00:00 -5474,487,31,0.0,1990-05-27 00:00:00 -5475,487,5,0.0,1990-05-27 00:00:00 -5476,487,17,0.0,1990-05-27 00:00:00 -5477,487,26,0.0,1990-05-27 00:00:00 -5478,487,34,0.0,1990-05-27 00:00:00 -5479,487,21,0.0,1990-05-27 00:00:00 -5480,487,33,0.0,1990-05-27 00:00:00 -5481,487,40,0.0,1990-05-27 00:00:00 -5482,487,43,0.0,1990-05-27 00:00:00 -5483,487,42,0.0,1990-05-27 00:00:00 -5484,487,38,0.0,1990-05-27 00:00:00 -5485,487,41,0.0,1990-05-27 00:00:00 -5486,487,45,0.0,1990-05-27 00:00:00 -5487,487,32,1.0,1990-05-27 00:00:00 -5488,487,20,2.0,1990-05-27 00:00:00 -5489,487,2,3.0,1990-05-27 00:00:00 -5490,487,24,6.0,1990-05-27 00:00:00 -5491,487,0,13.0,1990-05-27 00:00:00 -5492,488,33,0.0,1990-06-10 00:00:00 -5493,488,20,0.0,1990-06-10 00:00:00 -5494,488,32,0.0,1990-06-10 00:00:00 -5495,488,40,0.0,1990-06-10 00:00:00 -5496,488,24,0.0,1990-06-10 00:00:00 -5497,488,43,0.0,1990-06-10 00:00:00 -5498,488,44,0.0,1990-06-10 00:00:00 -5499,488,34,0.0,1990-06-10 00:00:00 -5500,488,2,0.0,1990-06-10 00:00:00 -5501,488,26,0.0,1990-06-10 00:00:00 -5502,488,17,0.0,1990-06-10 00:00:00 -5503,488,42,0.0,1990-06-10 00:00:00 -5504,488,38,0.0,1990-06-10 00:00:00 -5505,488,31,1.0,1990-06-10 00:00:00 -5506,488,5,6.0,1990-06-10 00:00:00 -5507,488,41,0.0,1990-06-10 00:00:00 -5508,488,0,12.0,1990-06-10 00:00:00 -5509,488,21,6.0,1990-06-10 00:00:00 -5510,488,45,0.0,1990-06-10 00:00:00 -5511,489,45,0.0,1990-06-24 00:00:00 -5512,489,41,0.0,1990-06-24 00:00:00 -5513,489,38,0.0,1990-06-24 00:00:00 -5514,489,40,0.0,1990-06-24 00:00:00 -5515,489,42,0.0,1990-06-24 00:00:00 -5516,489,32,0.0,1990-06-24 00:00:00 -5517,489,43,0.0,1990-06-24 00:00:00 -5518,489,20,0.0,1990-06-24 00:00:00 -5519,489,26,0.0,1990-06-24 00:00:00 -5520,489,5,15.0,1990-06-24 00:00:00 -5521,489,34,0.0,1990-06-24 00:00:00 -5522,489,0,4.0,1990-06-24 00:00:00 -5523,489,21,4.0,1990-06-24 00:00:00 -5524,489,2,2.0,1990-06-24 00:00:00 -5525,489,44,0.0,1990-06-24 00:00:00 -5526,489,31,0.0,1990-06-24 00:00:00 -5527,489,33,0.0,1990-06-24 00:00:00 -5528,489,17,0.0,1990-06-24 00:00:00 -5529,489,24,0.0,1990-06-24 00:00:00 -5530,490,34,0.0,1990-07-08 00:00:00 -5531,490,45,0.0,1990-07-08 00:00:00 -5532,490,41,0.0,1990-07-08 00:00:00 -5533,490,42,0.0,1990-07-08 00:00:00 -5534,490,43,0.0,1990-07-08 00:00:00 -5535,490,17,0.0,1990-07-08 00:00:00 -5536,490,24,0.0,1990-07-08 00:00:00 -5537,490,38,0.0,1990-07-08 00:00:00 -5538,490,44,0.0,1990-07-08 00:00:00 -5539,490,31,0.0,1990-07-08 00:00:00 -5540,490,40,6.0,1990-07-08 00:00:00 -5541,490,0,6.0,1990-07-08 00:00:00 -5542,490,21,3.0,1990-07-08 00:00:00 -5543,490,2,1.0,1990-07-08 00:00:00 -5544,490,5,9.0,1990-07-08 00:00:00 -5545,490,32,0.0,1990-07-08 00:00:00 -5546,490,26,0.0,1990-07-08 00:00:00 -5547,490,20,0.0,1990-07-08 00:00:00 -5548,490,33,0.0,1990-07-08 00:00:00 -5549,491,17,0.0,1990-07-15 00:00:00 -5550,491,41,0.0,1990-07-15 00:00:00 -5551,491,42,0.0,1990-07-15 00:00:00 -5552,491,44,0.0,1990-07-15 00:00:00 -5553,491,43,0.0,1990-07-15 00:00:00 -5554,491,38,0.0,1990-07-15 00:00:00 -5555,491,31,0.0,1990-07-15 00:00:00 -5556,491,40,0.0,1990-07-15 00:00:00 -5557,491,45,0.0,1990-07-15 00:00:00 -5558,491,34,0.0,1990-07-15 00:00:00 -5559,491,33,0.0,1990-07-15 00:00:00 -5560,491,26,0.0,1990-07-15 00:00:00 -5561,491,2,6.0,1990-07-15 00:00:00 -5562,491,0,4.0,1990-07-15 00:00:00 -5563,491,5,9.0,1990-07-15 00:00:00 -5564,491,21,2.0,1990-07-15 00:00:00 -5565,491,20,0.0,1990-07-15 00:00:00 -5566,491,24,0.0,1990-07-15 00:00:00 -5567,491,32,4.0,1990-07-15 00:00:00 -5568,492,32,0.0,1990-07-29 00:00:00 -5569,492,41,0.0,1990-07-29 00:00:00 -5570,492,42,0.0,1990-07-29 00:00:00 -5571,492,38,0.0,1990-07-29 00:00:00 -5572,492,43,0.0,1990-07-29 00:00:00 -5573,492,34,0.0,1990-07-29 00:00:00 -5574,492,33,0.0,1990-07-29 00:00:00 -5575,492,17,0.0,1990-07-29 00:00:00 -5576,492,45,0.0,1990-07-29 00:00:00 -5577,492,44,0.0,1990-07-29 00:00:00 -5578,492,26,0.0,1990-07-29 00:00:00 -5579,492,0,13.0,1990-07-29 00:00:00 -5580,492,21,6.0,1990-07-29 00:00:00 -5581,492,5,3.0,1990-07-29 00:00:00 -5582,492,24,0.0,1990-07-29 00:00:00 -5583,492,40,0.0,1990-07-29 00:00:00 -5584,492,31,0.0,1990-07-29 00:00:00 -5585,492,20,0.0,1990-07-29 00:00:00 -5586,492,2,3.0,1990-07-29 00:00:00 -5587,493,45,0.0,1990-08-12 00:00:00 -5588,493,42,0.0,1990-08-12 00:00:00 -5589,493,41,0.0,1990-08-12 00:00:00 -5590,493,43,0.0,1990-08-12 00:00:00 -5591,493,44,0.0,1990-08-12 00:00:00 -5592,493,33,0.0,1990-08-12 00:00:00 -5593,493,5,0.0,1990-08-12 00:00:00 -5594,493,17,0.0,1990-08-12 00:00:00 -5595,493,24,0.0,1990-08-12 00:00:00 -5596,493,26,0.0,1990-08-12 00:00:00 -5597,493,38,0.0,1990-08-12 00:00:00 -5598,493,0,6.0,1990-08-12 00:00:00 -5599,493,21,4.0,1990-08-12 00:00:00 -5600,493,31,2.0,1990-08-12 00:00:00 -5601,493,2,12.0,1990-08-12 00:00:00 -5602,493,40,0.0,1990-08-12 00:00:00 -5603,493,20,0.0,1990-08-12 00:00:00 -5604,493,34,0.0,1990-08-12 00:00:00 -5605,493,32,1.0,1990-08-12 00:00:00 -5606,494,45,0.0,1990-08-26 00:00:00 -5607,494,42,0.0,1990-08-26 00:00:00 -5608,494,41,0.0,1990-08-26 00:00:00 -5609,494,38,0.0,1990-08-26 00:00:00 -5610,494,2,0.0,1990-08-26 00:00:00 -5611,494,34,0.0,1990-08-26 00:00:00 -5612,494,33,0.0,1990-08-26 00:00:00 -5613,494,43,0.0,1990-08-26 00:00:00 -5614,494,31,0.0,1990-08-26 00:00:00 -5615,494,26,0.0,1990-08-26 00:00:00 -5616,494,17,0.0,1990-08-26 00:00:00 -5617,494,0,13.0,1990-08-26 00:00:00 -5618,494,5,6.0,1990-08-26 00:00:00 -5619,494,21,5.0,1990-08-26 00:00:00 -5620,494,32,0.0,1990-08-26 00:00:00 -5621,494,24,0.0,1990-08-26 00:00:00 -5622,494,20,0.0,1990-08-26 00:00:00 -5623,494,40,1.0,1990-08-26 00:00:00 -5624,495,45,0.0,1990-09-09 00:00:00 -5625,495,42,0.0,1990-09-09 00:00:00 -5626,495,41,0.0,1990-09-09 00:00:00 -5627,495,17,0.0,1990-09-09 00:00:00 -5628,495,31,0.0,1990-09-09 00:00:00 -5629,495,33,0.0,1990-09-09 00:00:00 -5630,495,43,0.0,1990-09-09 00:00:00 -5631,495,32,0.0,1990-09-09 00:00:00 -5632,495,38,0.0,1990-09-09 00:00:00 -5633,495,26,0.0,1990-09-09 00:00:00 -5634,495,34,0.0,1990-09-09 00:00:00 -5635,495,21,0.0,1990-09-09 00:00:00 -5636,495,24,1.0,1990-09-09 00:00:00 -5637,495,2,2.0,1990-09-09 00:00:00 -5638,495,5,9.0,1990-09-09 00:00:00 -5639,495,0,13.0,1990-09-09 00:00:00 -5640,495,40,0.0,1990-09-09 00:00:00 -5641,495,20,0.0,1990-09-09 00:00:00 -5642,496,5,13.0,1990-09-23 00:00:00 -5643,496,0,9.0,1990-09-23 00:00:00 -5644,496,2,0.0,1990-09-23 00:00:00 -5645,496,21,3.0,1990-09-23 00:00:00 -5646,496,45,0.0,1990-09-23 00:00:00 -5647,496,42,0.0,1990-09-23 00:00:00 -5648,496,41,0.0,1990-09-23 00:00:00 -5649,496,38,0.0,1990-09-23 00:00:00 -5650,496,31,0.0,1990-09-23 00:00:00 -5651,496,33,0.0,1990-09-23 00:00:00 -5652,496,43,0.0,1990-09-23 00:00:00 -5653,496,32,0.0,1990-09-23 00:00:00 -5654,496,40,0.0,1990-09-23 00:00:00 -5655,496,17,0.0,1990-09-23 00:00:00 -5656,496,26,0.0,1990-09-23 00:00:00 -5657,496,20,0.0,1990-09-23 00:00:00 -5658,496,24,0.0,1990-09-23 00:00:00 -5659,496,34,0.0,1990-09-23 00:00:00 -5660,497,43,0.0,1990-09-30 00:00:00 -5661,497,45,0.0,1990-09-30 00:00:00 -5662,497,42,0.0,1990-09-30 00:00:00 -5663,497,41,0.0,1990-09-30 00:00:00 -5664,497,33,0.0,1990-09-30 00:00:00 -5665,497,24,0.0,1990-09-30 00:00:00 -5666,497,17,0.0,1990-09-30 00:00:00 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-8286,711,2,3.0,2003-09-28 00:00:00 -8287,711,17,0.0,2003-09-28 00:00:00 -8288,711,14,10.0,2003-09-28 00:00:00 -8289,711,0,8.0,2003-09-28 00:00:00 -8290,711,3,5.0,2003-09-28 00:00:00 -8291,712,16,0.0,2003-10-12 00:00:00 -8292,712,2,0.0,2003-10-12 00:00:00 -8293,712,18,0.0,2003-10-12 00:00:00 -8294,712,6,2.0,2003-10-12 00:00:00 -8295,712,14,0.0,2003-10-12 00:00:00 -8296,712,0,14.0,2003-10-12 00:00:00 -8297,712,17,0.0,2003-10-12 00:00:00 -8298,712,5,11.0,2003-10-12 00:00:00 -8299,712,3,4.0,2003-10-12 00:00:00 -8300,712,15,8.0,2003-10-12 00:00:00 -8301,713,18,0.0,2004-03-07 00:00:00 -8302,713,17,0.0,2004-03-07 00:00:00 -8303,713,16,0.0,2004-03-07 00:00:00 -8304,713,6,0.0,2004-03-07 00:00:00 -8305,713,14,0.0,2004-03-07 00:00:00 -8306,713,15,3.0,2004-03-07 00:00:00 -8307,713,2,9.0,2004-03-07 00:00:00 -8308,713,3,8.0,2004-03-07 00:00:00 -8309,713,5,18.0,2004-03-07 00:00:00 -8310,713,0,1.0,2004-03-07 00:00:00 -8311,714,18,0.0,2004-03-21 00:00:00 -8312,714,6,0.0,2004-03-21 00:00:00 -8313,714,14,1.0,2004-03-21 00:00:00 -8314,714,0,3.0,2004-03-21 00:00:00 -8315,714,16,0.0,2004-03-21 00:00:00 -8316,714,17,0.0,2004-03-21 00:00:00 -8317,714,15,6.0,2004-03-21 00:00:00 -8318,714,2,8.0,2004-03-21 00:00:00 -8319,714,3,6.0,2004-03-21 00:00:00 -8320,714,5,15.0,2004-03-21 00:00:00 -8321,715,0,0.0,2004-04-04 00:00:00 -8322,715,17,0.0,2004-04-04 00:00:00 -8323,715,16,0.0,2004-04-04 00:00:00 -8324,715,14,0.0,2004-04-04 00:00:00 -8325,715,6,0.0,2004-04-04 00:00:00 -8326,715,18,1.0,2004-04-04 00:00:00 -8327,715,2,2.0,2004-04-04 00:00:00 -8328,715,3,8.0,2004-04-04 00:00:00 -8329,715,15,10.0,2004-04-04 00:00:00 -8330,715,5,18.0,2004-04-04 00:00:00 -8331,716,16,0.0,2004-04-25 00:00:00 -8332,716,17,0.0,2004-04-25 00:00:00 -8333,716,18,0.0,2004-04-25 00:00:00 -8334,716,6,0.0,2004-04-25 00:00:00 -8335,716,0,1.0,2004-04-25 00:00:00 -8336,716,3,9.0,2004-04-25 00:00:00 -8337,716,2,8.0,2004-04-25 00:00:00 -8338,716,15,8.0,2004-04-25 00:00:00 -8339,716,5,13.0,2004-04-25 00:00:00 -8340,716,14,0.0,2004-04-25 00:00:00 -8341,717,0,0.0,2004-05-09 00:00:00 -8342,717,17,0.0,2004-05-09 00:00:00 -8343,717,16,0.0,2004-05-09 00:00:00 -8344,717,6,0.0,2004-05-09 00:00:00 -8345,717,14,2.0,2004-05-09 00:00:00 -8346,717,2,3.0,2004-05-09 00:00:00 -8347,717,15,5.0,2004-05-09 00:00:00 -8348,717,3,11.0,2004-05-09 00:00:00 -8349,717,5,18.0,2004-05-09 00:00:00 -8350,717,18,0.0,2004-05-09 00:00:00 -8351,718,0,0.0,2004-05-23 00:00:00 -8352,718,17,0.0,2004-05-23 00:00:00 -8353,718,18,0.0,2004-05-23 00:00:00 -8354,718,16,2.0,2004-05-23 00:00:00 -8355,718,14,4.0,2004-05-23 00:00:00 -8356,718,15,8.0,2004-05-23 00:00:00 -8357,718,2,5.0,2004-05-23 00:00:00 -8358,718,5,6.0,2004-05-23 00:00:00 -8359,718,3,10.0,2004-05-23 00:00:00 -8360,718,6,4.0,2004-05-23 00:00:00 -8361,719,0,0.0,2004-05-30 00:00:00 -8362,719,17,0.0,2004-05-30 00:00:00 -8363,719,6,0.0,2004-05-30 00:00:00 -8364,719,16,0.0,2004-05-30 00:00:00 -8365,719,18,2.0,2004-05-30 00:00:00 -8366,719,14,3.0,2004-05-30 00:00:00 -8367,719,3,9.0,2004-05-30 00:00:00 -8368,719,15,6.0,2004-05-30 00:00:00 -8369,719,5,18.0,2004-05-30 00:00:00 -8370,719,2,1.0,2004-05-30 00:00:00 -8371,720,6,0.0,2004-06-13 00:00:00 -8372,720,2,0.0,2004-06-13 00:00:00 -8373,720,3,0.0,2004-06-13 00:00:00 -8374,720,17,0.0,2004-06-13 00:00:00 -8375,720,16,3.0,2004-06-13 00:00:00 -8376,720,0,7.0,2004-06-13 00:00:00 -8377,720,14,5.0,2004-06-13 00:00:00 -8378,720,15,6.0,2004-06-13 00:00:00 -8379,720,18,0.0,2004-06-13 00:00:00 -8380,720,5,18.0,2004-06-13 00:00:00 -8381,721,17,1.0,2004-06-20 00:00:00 -8382,721,18,0.0,2004-06-20 00:00:00 -8383,721,14,0.0,2004-06-20 00:00:00 -8384,721,16,0.0,2004-06-20 00:00:00 -8385,721,6,4.0,2004-06-20 00:00:00 -8386,721,3,5.0,2004-06-20 00:00:00 -8387,721,15,6.0,2004-06-20 00:00:00 -8388,721,5,18.0,2004-06-20 00:00:00 -8389,721,0,5.0,2004-06-20 00:00:00 -8390,721,2,0.0,2004-06-20 00:00:00 -8391,722,5,16.0,2004-07-04 00:00:00 -8392,722,15,4.0,2004-07-04 00:00:00 -8393,722,3,13.0,2004-07-04 00:00:00 -8394,722,17,0.0,2004-07-04 00:00:00 -8395,722,16,0.0,2004-07-04 00:00:00 -8396,722,18,0.0,2004-07-04 00:00:00 -8397,722,14,0.0,2004-07-04 00:00:00 -8398,722,2,1.0,2004-07-04 00:00:00 -8399,722,6,0.0,2004-07-04 00:00:00 -8400,722,0,5.0,2004-07-04 00:00:00 -8401,723,17,0.0,2004-07-11 00:00:00 -8402,723,16,0.0,2004-07-11 00:00:00 -8403,723,6,0.0,2004-07-11 00:00:00 -8404,723,3,0.0,2004-07-11 00:00:00 -8405,723,14,3.0,2004-07-11 00:00:00 -8406,723,2,4.0,2004-07-11 00:00:00 -8407,723,15,5.0,2004-07-11 00:00:00 -8408,723,0,10.0,2004-07-11 00:00:00 -8409,723,5,16.0,2004-07-11 00:00:00 -8410,723,18,1.0,2004-07-11 00:00:00 -8411,724,6,0.0,2004-07-25 00:00:00 -8412,724,17,0.0,2004-07-25 00:00:00 -8413,724,16,0.0,2004-07-25 00:00:00 -8414,724,14,0.0,2004-07-25 00:00:00 -8415,724,15,9.0,2004-07-25 00:00:00 -8416,724,2,6.0,2004-07-25 00:00:00 -8417,724,0,5.0,2004-07-25 00:00:00 -8418,724,3,6.0,2004-07-25 00:00:00 -8419,724,5,10.0,2004-07-25 00:00:00 -8420,724,18,3.0,2004-07-25 00:00:00 -8421,725,18,0.0,2004-08-15 00:00:00 -8422,725,16,0.0,2004-08-15 00:00:00 -8423,725,0,0.0,2004-08-15 00:00:00 -8424,725,17,0.0,2004-08-15 00:00:00 -8425,725,15,7.0,2004-08-15 00:00:00 -8426,725,14,1.0,2004-08-15 00:00:00 -8427,725,5,18.0,2004-08-15 00:00:00 -8428,725,6,0.0,2004-08-15 00:00:00 -8429,725,2,7.0,2004-08-15 00:00:00 -8430,725,3,6.0,2004-08-15 00:00:00 -8431,726,0,12.0,2004-08-29 00:00:00 -8432,726,5,14.0,2004-08-29 00:00:00 -8433,726,14,9.0,2004-08-29 00:00:00 -8434,726,18,3.0,2004-08-29 00:00:00 -8435,726,6,1.0,2004-08-29 00:00:00 -8436,726,3,0.0,2004-08-29 00:00:00 -8437,726,16,0.0,2004-08-29 00:00:00 -8438,726,2,0.0,2004-08-29 00:00:00 -8439,726,15,0.0,2004-08-29 00:00:00 -8440,726,17,0.0,2004-08-29 00:00:00 -8441,727,17,0.0,2004-09-12 00:00:00 -8442,727,16,0.0,2004-09-12 00:00:00 -8443,727,6,0.0,2004-09-12 00:00:00 -8444,727,3,0.0,2004-09-12 00:00:00 -8445,727,18,0.0,2004-09-12 00:00:00 -8446,727,2,6.0,2004-09-12 00:00:00 -8447,727,15,11.0,2004-09-12 00:00:00 -8448,727,5,18.0,2004-09-12 00:00:00 -8449,727,14,1.0,2004-09-12 00:00:00 -8450,727,0,3.0,2004-09-12 00:00:00 -8451,728,5,10.0,2004-09-26 00:00:00 -8452,728,15,11.0,2004-09-26 00:00:00 -8453,728,0,6.0,2004-09-26 00:00:00 -8454,728,3,5.0,2004-09-26 00:00:00 -8455,728,2,4.0,2004-09-26 00:00:00 -8456,728,14,3.0,2004-09-26 00:00:00 -8457,728,18,0.0,2004-09-26 00:00:00 -8458,728,16,0.0,2004-09-26 00:00:00 -8459,728,6,0.0,2004-09-26 00:00:00 -8460,728,17,0.0,2004-09-26 00:00:00 -8461,729,14,1.0,2004-10-10 00:00:00 -8462,729,2,10.0,2004-10-10 00:00:00 -8463,729,15,11.0,2004-10-10 00:00:00 -8464,729,3,4.0,2004-10-10 00:00:00 -8465,729,0,3.0,2004-10-10 00:00:00 -8466,729,6,0.0,2004-10-10 00:00:00 -8467,729,18,0.0,2004-10-10 00:00:00 -8468,729,16,0.0,2004-10-10 00:00:00 -8469,729,17,0.0,2004-10-10 00:00:00 -8470,729,5,10.0,2004-10-10 00:00:00 -8471,730,17,0.0,2004-10-24 00:00:00 -8472,730,16,0.0,2004-10-24 00:00:00 -8473,730,18,0.0,2004-10-24 00:00:00 -8474,730,6,0.0,2004-10-24 00:00:00 -8475,730,3,5.0,2004-10-24 00:00:00 -8476,730,15,3.0,2004-10-24 00:00:00 -8477,730,5,8.0,2004-10-24 00:00:00 -8478,730,0,8.0,2004-10-24 00:00:00 -8479,730,2,14.0,2004-10-24 00:00:00 -8480,730,14,1.0,2004-10-24 00:00:00 -8481,731,14,0.0,2005-03-06 14:00:00 -8482,731,17,0.0,2005-03-06 14:00:00 -8483,731,15,0.0,2005-03-06 14:00:00 -8484,731,6,0.0,2005-03-06 14:00:00 -8485,731,16,0.0,2005-03-06 14:00:00 -8486,731,2,4.0,2005-03-06 14:00:00 -8487,731,8,7.0,2005-03-06 14:00:00 -8488,731,3,16.0,2005-03-06 14:00:00 -8489,731,5,8.0,2005-03-06 14:00:00 -8490,731,0,4.0,2005-03-06 14:00:00 -8491,732,15,0.0,2005-03-20 15:00:00 -8492,732,17,0.0,2005-03-20 15:00:00 -8493,732,16,0.0,2005-03-20 15:00:00 -8494,732,14,0.0,2005-03-20 15:00:00 -8495,732,5,2.0,2005-03-20 15:00:00 -8496,732,8,4.0,2005-03-20 15:00:00 -8497,732,0,5.0,2005-03-20 15:00:00 -8498,732,2,6.0,2005-03-20 15:00:00 -8499,732,6,12.0,2005-03-20 15:00:00 -8500,732,3,10.0,2005-03-20 15:00:00 -8501,733,15,0.0,2005-04-03 14:30:00 -8502,733,17,0.0,2005-04-03 14:30:00 -8503,733,16,0.0,2005-04-03 14:30:00 -8504,733,5,0.0,2005-04-03 14:30:00 -8505,733,3,10.0,2005-04-03 14:30:00 -8506,733,14,2.0,2005-04-03 14:30:00 -8507,733,2,3.0,2005-04-03 14:30:00 -8508,733,0,10.0,2005-04-03 14:30:00 -8509,733,6,13.0,2005-04-03 14:30:00 -8510,733,8,1.0,2005-04-03 14:30:00 -8511,734,16,0.0,2005-04-24 14:00:00 -8512,734,15,0.0,2005-04-24 14:00:00 -8513,734,17,0.0,2005-04-24 14:00:00 -8514,734,8,1.0,2005-04-24 14:00:00 -8515,734,6,4.0,2005-04-24 14:00:00 -8516,734,14,5.0,2005-04-24 14:00:00 -8517,734,0,6.0,2005-04-24 14:00:00 -8518,734,5,8.0,2005-04-24 14:00:00 -8519,734,2,5.0,2005-04-24 14:00:00 -8520,734,3,10.0,2005-04-24 14:00:00 -8521,735,16,0.0,2005-05-08 14:00:00 -8522,735,17,0.0,2005-05-08 14:00:00 -8523,735,14,0.0,2005-05-08 14:00:00 -8524,735,5,0.0,2005-05-08 14:00:00 -8525,735,8,1.0,2005-05-08 14:00:00 -8526,735,2,3.0,2005-05-08 14:00:00 -8527,735,6,11.0,2005-05-08 14:00:00 -8528,735,3,12.0,2005-05-08 14:00:00 -8529,735,0,12.0,2005-05-08 14:00:00 -8530,736,8,0.0,2005-05-22 14:00:00 -8531,736,17,0.0,2005-05-22 14:00:00 -8532,736,16,0.0,2005-05-22 14:00:00 -8533,736,14,0.0,2005-05-22 14:00:00 -8534,736,0,14.0,2005-05-22 14:00:00 -8535,736,6,3.0,2005-05-22 14:00:00 -8536,736,3,5.0,2005-05-22 14:00:00 -8537,736,2,14.0,2005-05-22 14:00:00 -8538,736,5,3.0,2005-05-22 14:00:00 -8539,737,16,0.0,2005-05-29 14:00:00 -8540,737,8,5.0,2005-05-29 14:00:00 -8541,737,14,0.0,2005-05-29 14:00:00 -8542,737,17,0.0,2005-05-29 14:00:00 -8543,737,15,0.0,2005-05-29 14:00:00 -8544,737,3,13.0,2005-05-29 14:00:00 -8545,737,0,2.0,2005-05-29 14:00:00 -8546,737,5,10.0,2005-05-29 14:00:00 -8547,737,2,8.0,2005-05-29 14:00:00 -8548,737,6,1.0,2005-05-29 14:00:00 -8549,738,3,0.0,2005-06-12 13:00:00 -8550,738,15,0.0,2005-06-12 13:00:00 -8551,738,17,0.0,2005-06-12 13:00:00 -8552,738,16,0.0,2005-06-12 13:00:00 -8553,738,8,3.0,2005-06-12 13:00:00 -8554,738,2,4.0,2005-06-12 13:00:00 -8555,738,14,5.0,2005-06-12 13:00:00 -8556,738,5,14.0,2005-06-12 13:00:00 -8557,738,0,10.0,2005-06-12 13:00:00 -8558,738,6,3.0,2005-06-12 13:00:00 -8559,739,2,0.0,2005-06-19 14:00:00 -8560,739,3,0.0,2005-06-19 14:00:00 -8561,739,15,0.0,2005-06-19 14:00:00 -8562,739,14,0.0,2005-06-19 14:00:00 -8563,739,6,0.0,2005-06-19 14:00:00 -8564,739,17,7.0,2005-06-19 14:00:00 -8565,739,5,18.0,2005-06-19 14:00:00 -8566,739,0,0.0,2005-06-19 14:00:00 -8567,739,8,0.0,2005-06-19 14:00:00 -8568,739,16,11.0,2005-06-19 14:00:00 -8569,740,17,0.0,2005-07-03 14:00:00 -8570,740,16,0.0,2005-07-03 14:00:00 -8571,740,2,0.0,2005-07-03 14:00:00 -8572,740,8,0.0,2005-07-03 14:00:00 -8573,740,14,1.0,2005-07-03 14:00:00 -8574,740,6,6.0,2005-07-03 14:00:00 -8575,740,15,5.0,2005-07-03 14:00:00 -8576,740,5,6.0,2005-07-03 14:00:00 -8577,740,0,8.0,2005-07-03 14:00:00 -8578,740,3,13.0,2005-07-03 14:00:00 -8579,741,0,16.0,2005-07-10 14:00:00 -8580,741,17,0.0,2005-07-10 14:00:00 -8581,741,16,0.0,2005-07-10 14:00:00 -8582,741,2,0.0,2005-07-10 14:00:00 -8583,741,8,0.0,2005-07-10 14:00:00 -8584,741,6,1.0,2005-07-10 14:00:00 -8585,741,3,13.0,2005-07-10 14:00:00 -8586,741,5,5.0,2005-07-10 14:00:00 -8587,741,15,4.0,2005-07-10 14:00:00 -8588,741,14,0.0,2005-07-10 14:00:00 -8589,742,16,0.0,2005-07-24 14:00:00 -8590,742,17,0.0,2005-07-24 14:00:00 -8591,742,2,0.0,2005-07-24 14:00:00 -8592,742,14,1.0,2005-07-24 14:00:00 -8593,742,8,2.0,2005-07-24 14:00:00 -8594,742,5,4.0,2005-07-24 14:00:00 -8595,742,15,6.0,2005-07-24 14:00:00 -8596,742,0,8.0,2005-07-24 14:00:00 -8597,742,3,15.0,2005-07-24 14:00:00 -8598,742,6,3.0,2005-07-24 14:00:00 -8599,743,16,0.0,2005-07-31 14:00:00 -8600,743,8,0.0,2005-07-31 14:00:00 -8601,743,17,0.0,2005-07-31 14:00:00 -8602,743,3,0.0,2005-07-31 14:00:00 -8603,743,14,0.0,2005-07-31 14:00:00 -8604,743,15,5.0,2005-07-31 14:00:00 -8605,743,5,8.0,2005-07-31 14:00:00 -8606,743,2,5.0,2005-07-31 14:00:00 -8607,743,0,10.0,2005-07-31 14:00:00 -8608,743,6,11.0,2005-07-31 14:00:00 -8609,744,0,16.0,2005-08-21 15:00:00 -8610,744,3,13.0,2005-08-21 15:00:00 -8611,744,15,4.0,2005-08-21 15:00:00 -8612,744,6,3.0,2005-08-21 15:00:00 -8613,744,8,3.0,2005-08-21 15:00:00 -8614,744,14,0.0,2005-08-21 15:00:00 -8615,744,17,0.0,2005-08-21 15:00:00 -8616,744,16,0.0,2005-08-21 15:00:00 -8617,744,2,0.0,2005-08-21 15:00:00 -8618,744,5,0.0,2005-08-21 15:00:00 -8619,745,5,0.0,2005-09-04 14:00:00 -8620,745,17,0.0,2005-09-04 14:00:00 -8621,745,16,0.0,2005-09-04 14:00:00 -8622,745,8,0.0,2005-09-04 14:00:00 -8623,745,14,0.0,2005-09-04 14:00:00 -8624,745,2,2.0,2005-09-04 14:00:00 -8625,745,6,7.0,2005-09-04 14:00:00 -8626,745,3,14.0,2005-09-04 14:00:00 -8627,745,0,15.0,2005-09-04 14:00:00 -8628,745,15,1.0,2005-09-04 14:00:00 -8629,746,17,0.0,2005-09-11 14:00:00 -8630,746,8,0.0,2005-09-11 14:00:00 -8631,746,16,1.0,2005-09-11 14:00:00 -8632,746,6,2.0,2005-09-11 14:00:00 -8633,746,14,3.0,2005-09-11 14:00:00 -8634,746,2,5.0,2005-09-11 14:00:00 -8635,746,15,6.0,2005-09-11 14:00:00 -8636,746,3,8.0,2005-09-11 14:00:00 -8637,746,0,10.0,2005-09-11 14:00:00 -8638,746,5,4.0,2005-09-11 14:00:00 -8639,747,14,0.0,2005-09-25 14:00:00 -8640,747,2,0.0,2005-09-25 14:00:00 -8641,747,16,0.0,2005-09-25 14:00:00 -8642,747,8,0.0,2005-09-25 14:00:00 -8643,747,17,0.0,2005-09-25 14:00:00 -8644,747,15,2.0,2005-09-25 14:00:00 -8645,747,0,18.0,2005-09-25 14:00:00 -8646,747,5,8.0,2005-09-25 14:00:00 -8647,747,3,10.0,2005-09-25 14:00:00 -8648,747,6,1.0,2005-09-25 14:00:00 -8649,748,17,0.0,2005-10-09 14:00:00 -8650,748,16,0.0,2005-10-09 14:00:00 -8651,748,14,0.0,2005-10-09 14:00:00 -8652,748,6,1.0,2005-10-09 14:00:00 -8653,748,5,2.0,2005-10-09 14:00:00 -8654,748,8,3.0,2005-10-09 14:00:00 -8655,748,15,4.0,2005-10-09 14:00:00 -8656,748,2,5.0,2005-10-09 14:00:00 -8657,748,3,14.0,2005-10-09 14:00:00 -8658,748,0,10.0,2005-10-09 14:00:00 -8659,749,5,0.0,2005-10-16 14:00:00 -8660,749,16,0.0,2005-10-16 14:00:00 -8661,749,15,1.0,2005-10-16 14:00:00 -8662,749,2,2.0,2005-10-16 14:00:00 -8663,749,17,0.0,2005-10-16 14:00:00 -8664,749,8,4.0,2005-10-16 14:00:00 -8665,749,14,3.0,2005-10-16 14:00:00 -8666,749,3,15.0,2005-10-16 14:00:00 -8667,749,6,6.0,2005-10-16 14:00:00 -8668,749,0,8.0,2005-10-16 14:00:00 -8669,750,3,10.0,2006-03-12 14:30:00 -8670,750,7,0.0,2006-03-12 14:30:00 -8671,750,12,0.0,2006-03-12 14:30:00 -8672,750,1,0.0,2006-03-12 14:30:00 -8673,750,6,0.0,2006-03-12 14:30:00 -8674,750,8,1.0,2006-03-12 14:30:00 -8675,750,2,5.0,2006-03-12 14:30:00 -8676,750,10,5.0,2006-03-12 14:30:00 -8677,750,0,10.0,2006-03-12 14:30:00 -8678,750,5,8.0,2006-03-12 14:30:00 -8679,750,4,0.0,2006-03-12 14:30:00 -8680,751,2,0.0,2006-03-19 15:00:00 -8681,751,8,0.0,2006-03-19 15:00:00 -8682,751,7,0.0,2006-03-19 15:00:00 -8683,751,12,0.0,2006-03-19 15:00:00 -8684,751,6,1.0,2006-03-19 15:00:00 -8685,751,1,2.0,2006-03-19 15:00:00 -8686,751,5,7.0,2006-03-19 15:00:00 -8687,751,0,5.0,2006-03-19 15:00:00 -8688,751,10,6.0,2006-03-19 15:00:00 -8689,751,4,0.0,2006-03-19 15:00:00 -8690,751,3,18.0,2006-03-19 15:00:00 -8691,752,2,0.0,2006-04-02 14:00:00 -8692,752,5,0.0,2006-04-02 14:00:00 -8693,752,7,0.0,2006-04-02 14:00:00 -8694,752,12,0.0,2006-04-02 14:00:00 -8695,752,10,2.0,2006-04-02 14:00:00 -8696,752,8,1.0,2006-04-02 14:00:00 -8697,752,1,8.0,2006-04-02 14:00:00 -8698,752,6,6.0,2006-04-02 14:00:00 -8699,752,0,8.0,2006-04-02 14:00:00 -8700,752,4,0.0,2006-04-02 14:00:00 -8701,752,3,14.0,2006-04-02 14:00:00 -8702,753,7,0.0,2006-04-23 14:00:00 -8703,753,12,0.0,2006-04-23 14:00:00 -8704,753,4,0.0,2006-04-23 14:00:00 -8705,753,1,0.0,2006-04-23 14:00:00 -8706,753,8,0.0,2006-04-23 14:00:00 -8707,753,10,2.0,2006-04-23 14:00:00 -8708,753,0,10.0,2006-04-23 14:00:00 -8709,753,3,9.0,2006-04-23 14:00:00 -8710,753,5,15.0,2006-04-23 14:00:00 -8711,753,6,0.0,2006-04-23 14:00:00 -8712,753,2,3.0,2006-04-23 14:00:00 -8713,754,5,16.0,2006-05-07 14:00:00 -8714,754,3,11.0,2006-05-07 14:00:00 -8715,754,0,5.0,2006-05-07 14:00:00 -8716,754,10,4.0,2006-05-07 14:00:00 -8717,754,2,2.0,2006-05-07 14:00:00 -8718,754,1,1.0,2006-05-07 14:00:00 -8719,754,6,0.0,2006-05-07 14:00:00 -8720,754,4,0.0,2006-05-07 14:00:00 -8721,754,12,0.0,2006-05-07 14:00:00 -8722,754,8,0.0,2006-05-07 14:00:00 -8723,754,7,0.0,2006-05-07 14:00:00 -8724,755,4,0.0,2006-05-14 14:00:00 -8725,755,7,0.0,2006-05-14 14:00:00 -8726,755,3,16.0,2006-05-14 14:00:00 -8727,755,5,13.0,2006-05-14 14:00:00 -8728,755,0,4.0,2006-05-14 14:00:00 -8729,755,10,5.0,2006-05-14 14:00:00 -8730,755,1,1.0,2006-05-14 14:00:00 -8731,755,2,0.0,2006-05-14 14:00:00 -8732,755,6,0.0,2006-05-14 14:00:00 -8733,755,8,0.0,2006-05-14 14:00:00 -8734,755,12,0.0,2006-05-14 14:00:00 -8735,756,2,0.0,2006-05-28 14:00:00 -8736,756,7,0.0,2006-05-28 14:00:00 -8737,756,12,0.0,2006-05-28 14:00:00 -8738,756,4,0.0,2006-05-28 14:00:00 -8739,756,10,5.0,2006-05-28 14:00:00 -8740,756,1,2.0,2006-05-28 14:00:00 -8741,756,5,4.0,2006-05-28 14:00:00 -8742,756,8,6.0,2006-05-28 14:00:00 -8743,756,0,8.0,2006-05-28 14:00:00 -8744,756,3,13.0,2006-05-28 14:00:00 -8745,756,6,1.0,2006-05-28 14:00:00 -8746,757,4,0.0,2006-06-11 12:00:00 -8747,757,7,0.0,2006-06-11 12:00:00 -8748,757,12,0.0,2006-06-11 12:00:00 -8749,757,8,0.0,2006-06-11 12:00:00 -8750,757,5,12.0,2006-06-11 12:00:00 -8751,757,10,0.0,2006-06-11 12:00:00 -8752,757,2,0.0,2006-06-11 12:00:00 -8753,757,1,3.0,2006-06-11 12:00:00 -8754,757,0,9.0,2006-06-11 12:00:00 -8755,757,3,15.0,2006-06-11 12:00:00 -8756,757,6,0.0,2006-06-11 12:00:00 -8757,758,2,0.0,2006-06-25 13:00:00 -8758,758,4,0.0,2006-06-25 13:00:00 -8759,758,10,0.0,2006-06-25 13:00:00 -8760,758,8,1.0,2006-06-25 13:00:00 -8761,758,6,3.0,2006-06-25 13:00:00 -8762,758,0,6.0,2006-06-25 13:00:00 -8763,758,7,0.0,2006-06-25 13:00:00 -8764,758,5,12.0,2006-06-25 13:00:00 -8765,758,3,15.0,2006-06-25 13:00:00 -8766,758,1,2.0,2006-06-25 13:00:00 -8767,758,12,0.0,2006-06-25 13:00:00 -8768,759,1,0.0,2006-07-02 14:00:00 -8769,759,3,10.0,2006-07-02 14:00:00 -8770,759,5,18.0,2006-07-02 14:00:00 -8771,759,0,0.0,2006-07-02 14:00:00 -8772,759,7,0.0,2006-07-02 14:00:00 -8773,759,12,0.0,2006-07-02 14:00:00 -8774,759,10,3.0,2006-07-02 14:00:00 -8775,759,4,1.0,2006-07-02 14:00:00 -8776,759,8,2.0,2006-07-02 14:00:00 -8777,759,2,0.0,2006-07-02 14:00:00 -8778,759,6,5.0,2006-07-02 14:00:00 -8779,760,10,0.0,2006-07-16 14:00:00 -8780,760,7,0.0,2006-07-16 14:00:00 -8781,760,2,0.0,2006-07-16 14:00:00 -8782,760,4,0.0,2006-07-16 14:00:00 -8783,760,12,0.0,2006-07-16 14:00:00 -8784,760,1,1.0,2006-07-16 14:00:00 -8785,760,0,6.0,2006-07-16 14:00:00 -8786,760,6,5.0,2006-07-16 14:00:00 -8787,760,3,11.0,2006-07-16 14:00:00 -8788,760,5,16.0,2006-07-16 14:00:00 -8789,760,8,0.0,2006-07-16 14:00:00 -8790,761,12,0.0,2006-07-30 14:00:00 -8791,761,1,0.0,2006-07-30 14:00:00 -8792,761,7,0.0,2006-07-30 14:00:00 -8793,761,2,0.0,2006-07-30 14:00:00 -8794,761,6,2.0,2006-07-30 14:00:00 -8795,761,8,1.0,2006-07-30 14:00:00 -8796,761,3,7.0,2006-07-30 14:00:00 -8797,761,10,5.0,2006-07-30 14:00:00 -8798,761,0,6.0,2006-07-30 14:00:00 -8799,761,4,0.0,2006-07-30 14:00:00 -8800,761,5,18.0,2006-07-30 14:00:00 -8801,762,3,0.0,2006-08-06 14:00:00 -8802,762,7,0.0,2006-08-06 14:00:00 -8803,762,10,15.0,2006-08-06 14:00:00 -8804,762,0,8.0,2006-08-06 14:00:00 -8805,762,1,6.0,2006-08-06 14:00:00 -8806,762,8,4.0,2006-08-06 14:00:00 -8807,762,6,3.0,2006-08-06 14:00:00 -8808,762,5,3.0,2006-08-06 14:00:00 -8809,762,12,0.0,2006-08-06 14:00:00 -8810,762,4,0.0,2006-08-06 14:00:00 -8811,762,2,0.0,2006-08-06 14:00:00 -8812,763,7,0.0,2006-08-27 15:00:00 -8813,763,12,0.0,2006-08-27 15:00:00 -8814,763,4,0.0,2006-08-27 15:00:00 -8815,763,1,0.0,2006-08-27 15:00:00 -8816,763,6,2.0,2006-08-27 15:00:00 -8817,763,2,0.0,2006-08-27 15:00:00 -8818,763,0,4.0,2006-08-27 15:00:00 -8819,763,10,6.0,2006-08-27 15:00:00 -8820,763,3,11.0,2006-08-27 15:00:00 -8821,763,5,16.0,2006-08-27 15:00:00 -8822,763,8,0.0,2006-08-27 15:00:00 -8823,764,4,0.0,2006-09-10 14:00:00 -8824,764,13,0.0,2006-09-10 14:00:00 -8825,764,7,0.0,2006-09-10 14:00:00 -8826,764,8,0.0,2006-09-10 14:00:00 -8827,764,10,7.0,2006-09-10 14:00:00 -8828,764,6,2.0,2006-09-10 14:00:00 -8829,764,5,10.0,2006-09-10 14:00:00 -8830,764,3,5.0,2006-09-10 14:00:00 -8831,764,1,7.0,2006-09-10 14:00:00 -8832,764,0,8.0,2006-09-10 14:00:00 -8833,764,2,0.0,2006-09-10 14:00:00 -8834,765,6,0.0,2006-10-01 14:00:00 -8835,765,7,0.0,2006-10-01 14:00:00 -8836,765,13,0.0,2006-10-01 14:00:00 -8837,765,4,0.0,2006-10-01 14:00:00 -8838,765,8,0.0,2006-10-01 14:00:00 -8839,765,1,2.0,2006-10-01 14:00:00 -8840,765,0,4.0,2006-10-01 14:00:00 -8841,765,10,8.0,2006-10-01 14:00:00 -8842,765,3,14.0,2006-10-01 14:00:00 -8843,765,5,10.0,2006-10-01 14:00:00 -8844,765,2,1.0,2006-10-01 14:00:00 -8845,766,4,0.0,2006-10-08 14:00:00 -8846,766,13,0.0,2006-10-08 14:00:00 -8847,766,7,0.0,2006-10-08 14:00:00 -8848,766,8,0.0,2006-10-08 14:00:00 -8849,766,6,5.0,2006-10-08 14:00:00 -8850,766,1,1.0,2006-10-08 14:00:00 -8851,766,5,8.0,2006-10-08 14:00:00 -8852,766,10,5.0,2006-10-08 14:00:00 -8853,766,2,0.0,2006-10-08 14:00:00 -8854,766,3,16.0,2006-10-08 14:00:00 -8855,766,0,4.0,2006-10-08 14:00:00 -8856,767,5,15.0,2006-10-22 14:00:00 -8857,767,2,0.0,2006-10-22 14:00:00 -8858,767,6,0.0,2006-10-22 14:00:00 -8859,767,8,0.0,2006-10-22 14:00:00 -8860,767,13,0.0,2006-10-22 14:00:00 -8861,767,7,0.0,2006-10-22 14:00:00 -8862,767,1,0.0,2006-10-22 14:00:00 -8863,767,0,5.0,2006-10-22 14:00:00 -8864,767,10,8.0,2006-10-22 14:00:00 -8865,767,3,11.0,2006-10-22 14:00:00 -8866,767,4,0.0,2006-10-22 14:00:00 -8867,768,11,0.0,2007-03-18 03:00:00 -8868,768,4,0.0,2007-03-18 03:00:00 -8869,768,8,0.0,2007-03-18 03:00:00 -8870,768,7,0.0,2007-03-18 03:00:00 -8871,768,10,0.0,2007-03-18 03:00:00 -8872,768,2,2.0,2007-03-18 03:00:00 -8873,768,3,4.0,2007-03-18 03:00:00 -8874,768,1,5.0,2007-03-18 03:00:00 -8875,768,0,14.0,2007-03-18 03:00:00 -8876,768,5,13.0,2007-03-18 03:00:00 -8877,768,6,1.0,2007-03-18 03:00:00 -8878,769,11,0.0,2007-04-08 07:00:00 -8879,769,4,0.0,2007-04-08 07:00:00 -8880,769,7,0.0,2007-04-08 07:00:00 -8881,769,10,0.0,2007-04-08 07:00:00 -8882,769,8,0.0,2007-04-08 07:00:00 -8883,769,6,2.0,2007-04-08 07:00:00 -8884,769,3,4.0,2007-04-08 07:00:00 -8885,769,1,5.0,2007-04-08 07:00:00 -8886,769,5,10.0,2007-04-08 07:00:00 -8887,769,0,18.0,2007-04-08 07:00:00 -8888,769,2,0.0,2007-04-08 07:00:00 -8889,770,7,0.0,2007-04-15 11:30:00 -8890,770,4,0.0,2007-04-15 11:30:00 -8891,770,8,0.0,2007-04-15 11:30:00 -8892,770,10,0.0,2007-04-15 11:30:00 -8893,770,11,0.0,2007-04-15 11:30:00 -8894,770,3,1.0,2007-04-15 11:30:00 -8895,770,2,0.0,2007-04-15 11:30:00 -8896,770,6,2.0,2007-04-15 11:30:00 -8897,770,1,8.0,2007-04-15 11:30:00 -8898,770,0,12.0,2007-04-15 11:30:00 -8899,770,5,16.0,2007-04-15 11:30:00 -8900,771,6,0.0,2007-05-13 12:00:00 -8901,771,11,0.0,2007-05-13 12:00:00 -8902,771,10,0.0,2007-05-13 12:00:00 -8903,771,7,1.0,2007-05-13 12:00:00 -8904,771,4,0.0,2007-05-13 12:00:00 -8905,771,2,3.0,2007-05-13 12:00:00 -8906,771,8,4.0,2007-05-13 12:00:00 -8907,771,1,5.0,2007-05-13 12:00:00 -8908,771,0,14.0,2007-05-13 12:00:00 -8909,771,5,10.0,2007-05-13 12:00:00 -8910,771,3,2.0,2007-05-13 12:00:00 -8911,772,11,0.0,2007-05-27 12:00:00 -8912,772,7,0.0,2007-05-27 12:00:00 -8913,772,6,0.0,2007-05-27 12:00:00 -8914,772,8,0.0,2007-05-27 12:00:00 -8915,772,10,0.0,2007-05-27 12:00:00 -8916,772,4,0.0,2007-05-27 12:00:00 -8917,772,1,7.0,2007-05-27 12:00:00 -8918,772,3,5.0,2007-05-27 12:00:00 -8919,772,5,7.0,2007-05-27 12:00:00 -8920,772,0,18.0,2007-05-27 12:00:00 -8921,772,2,2.0,2007-05-27 12:00:00 -8922,773,10,0.0,2007-06-10 17:00:00 -8923,773,8,0.0,2007-06-10 17:00:00 -8924,773,6,1.0,2007-06-10 17:00:00 -8925,773,7,3.0,2007-06-10 17:00:00 -8926,773,4,0.0,2007-06-10 17:00:00 -8927,773,3,5.0,2007-06-10 17:00:00 -8928,773,2,6.0,2007-06-10 17:00:00 -8929,773,1,8.0,2007-06-10 17:00:00 -8930,773,0,12.0,2007-06-10 17:00:00 -8931,773,5,4.0,2007-06-10 17:00:00 -8932,773,11,0.0,2007-06-10 17:00:00 -8933,774,4,0.0,2007-06-17 17:00:00 -8934,774,10,0.0,2007-06-17 17:00:00 -8935,774,7,0.0,2007-06-17 17:00:00 -8936,774,2,0.0,2007-06-17 17:00:00 -8937,774,11,0.0,2007-06-17 17:00:00 -8938,774,8,2.0,2007-06-17 17:00:00 -8939,774,6,3.0,2007-06-17 17:00:00 -8940,774,3,4.0,2007-06-17 17:00:00 -8941,774,5,11.0,2007-06-17 17:00:00 -8942,774,0,18.0,2007-06-17 17:00:00 -8943,774,1,1.0,2007-06-17 17:00:00 -8944,775,4,0.0,2007-07-01 12:00:00 -8945,775,11,0.0,2007-07-01 12:00:00 -8946,775,7,0.0,2007-07-01 12:00:00 -8947,775,8,0.0,2007-07-01 12:00:00 -8948,775,6,0.0,2007-07-01 12:00:00 -8949,775,2,0.0,2007-07-01 12:00:00 -8950,775,3,3.0,2007-07-01 12:00:00 -8951,775,1,9.0,2007-07-01 12:00:00 -8952,775,0,8.0,2007-07-01 12:00:00 -8953,775,5,18.0,2007-07-01 12:00:00 -8954,775,10,1.0,2007-07-01 12:00:00 -8955,776,5,14.0,2007-07-08 12:00:00 -8956,776,0,14.0,2007-07-08 12:00:00 -8957,776,1,8.0,2007-07-08 12:00:00 -8958,776,3,3.0,2007-07-08 12:00:00 -8959,776,2,0.0,2007-07-08 12:00:00 -8960,776,8,0.0,2007-07-08 12:00:00 -8961,776,7,0.0,2007-07-08 12:00:00 -8962,776,11,0.0,2007-07-08 12:00:00 -8963,776,4,0.0,2007-07-08 12:00:00 -8964,776,6,0.0,2007-07-08 12:00:00 -8965,776,10,0.0,2007-07-08 12:00:00 -8966,777,4,0.0,2007-07-22 12:00:00 -8967,777,11,0.0,2007-07-22 12:00:00 -8968,777,7,0.0,2007-07-22 12:00:00 -8969,777,10,0.0,2007-07-22 12:00:00 -8970,777,6,0.0,2007-07-22 12:00:00 -8971,777,1,5.0,2007-07-22 12:00:00 -8972,777,2,5.0,2007-07-22 12:00:00 -8973,777,8,10.0,2007-07-22 12:00:00 -8974,777,5,8.0,2007-07-22 12:00:00 -8975,777,0,10.0,2007-07-22 12:00:00 -8976,777,3,1.0,2007-07-22 12:00:00 -8977,778,10,0.0,2007-08-05 12:00:00 -8978,778,11,0.0,2007-08-05 12:00:00 -8979,778,4,0.0,2007-08-05 12:00:00 -8980,778,7,0.0,2007-08-05 12:00:00 -8981,778,2,2.0,2007-08-05 12:00:00 -8982,778,3,1.0,2007-08-05 12:00:00 -8983,778,6,3.0,2007-08-05 12:00:00 -8984,778,1,10.0,2007-08-05 12:00:00 -8985,778,0,15.0,2007-08-05 12:00:00 -8986,778,8,0.0,2007-08-05 12:00:00 -8987,778,5,8.0,2007-08-05 12:00:00 -8988,779,1,6.0,2007-08-26 12:00:00 -8989,779,0,10.0,2007-08-26 12:00:00 -8990,779,3,3.0,2007-08-26 12:00:00 -8991,779,2,2.0,2007-08-26 12:00:00 -8992,779,8,0.0,2007-08-26 12:00:00 -8993,779,6,0.0,2007-08-26 12:00:00 -8994,779,10,0.0,2007-08-26 12:00:00 -8995,779,7,0.0,2007-08-26 12:00:00 -8996,779,4,0.0,2007-08-26 12:00:00 -8997,779,11,0.0,2007-08-26 12:00:00 -8998,779,5,18.0,2007-08-26 12:00:00 -8999,780,11,0.0,2007-09-09 12:00:00 -9000,780,4,0.0,2007-09-09 12:00:00 -9001,780,6,0.0,2007-09-09 12:00:00 -9002,780,8,0.0,2007-09-09 12:00:00 -9003,780,7,0.0,2007-09-09 12:00:00 -9004,780,3,2.0,2007-09-09 12:00:00 -9005,780,2,3.0,2007-09-09 12:00:00 -9006,780,0,18.0,2007-09-09 12:00:00 -9007,780,1,9.0,2007-09-09 12:00:00 -9008,780,5,6.0,2007-09-09 12:00:00 -9009,780,10,1.0,2007-09-09 12:00:00 -9010,781,7,0.0,2007-09-16 12:00:00 -9011,781,11,0.0,2007-09-16 12:00:00 -9012,781,10,0.0,2007-09-16 12:00:00 -9013,781,4,0.0,2007-09-16 12:00:00 -9014,781,6,0.0,2007-09-16 12:00:00 -9015,781,3,1.0,2007-09-16 12:00:00 -9016,781,2,3.0,2007-09-16 12:00:00 -9017,781,1,4.0,2007-09-16 12:00:00 -9018,781,0,11.0,2007-09-16 12:00:00 -9019,781,5,18.0,2007-09-16 12:00:00 -9020,781,8,2.0,2007-09-16 12:00:00 -9021,782,2,0.0,2007-09-30 04:30:00 -9022,782,10,0.0,2007-09-30 04:30:00 -9023,782,6,0.0,2007-09-30 04:30:00 -9024,782,4,0.0,2007-09-30 04:30:00 -9025,782,3,12.0,2007-09-30 04:30:00 -9026,782,1,2.0,2007-09-30 04:30:00 -9027,782,11,1.0,2007-09-30 04:30:00 -9028,782,0,10.0,2007-09-30 04:30:00 -9029,782,7,0.0,2007-09-30 04:30:00 -9030,782,5,9.0,2007-09-30 04:30:00 -9031,782,8,5.0,2007-09-30 04:30:00 -9032,783,5,16.0,2007-10-07 06:00:00 -9033,783,11,0.0,2007-10-07 06:00:00 -9034,783,6,0.0,2007-10-07 06:00:00 -9035,783,2,0.0,2007-10-07 06:00:00 -9036,783,7,0.0,2007-10-07 06:00:00 -9037,783,8,1.0,2007-10-07 06:00:00 -9038,783,1,2.0,2007-10-07 06:00:00 -9039,783,10,4.0,2007-10-07 06:00:00 -9040,783,4,8.0,2007-10-07 06:00:00 -9041,783,0,8.0,2007-10-07 06:00:00 -9042,783,3,0.0,2007-10-07 06:00:00 -9043,784,3,0.0,2007-10-21 16:00:00 -9044,784,10,0.0,2007-10-21 16:00:00 -9045,784,11,0.0,2007-10-21 16:00:00 -9046,784,4,0.0,2007-10-21 16:00:00 -9047,784,6,1.0,2007-10-21 16:00:00 -9048,784,8,0.0,2007-10-21 16:00:00 -9049,784,1,7.0,2007-10-21 16:00:00 -9050,784,2,5.0,2007-10-21 16:00:00 -9051,784,0,8.0,2007-10-21 16:00:00 -9052,784,7,0.0,2007-10-21 16:00:00 -9053,784,5,18.0,2007-10-21 16:00:00 -9054,785,0,14.0,2008-03-16 04:30:00 -9055,785,10,0.0,2008-03-16 04:30:00 -9056,785,1,8.0,2008-03-16 04:30:00 -9057,785,2,9.0,2008-03-16 04:30:00 -9058,785,3,5.0,2008-03-16 04:30:00 -9059,785,4,2.0,2008-03-16 04:30:00 -9060,785,5,1.0,2008-03-16 04:30:00 -9061,785,6,0.0,2008-03-16 04:30:00 -9062,785,7,0.0,2008-03-16 04:30:00 -9063,785,8,0.0,2008-03-16 04:30:00 -9064,785,9,0.0,2008-03-16 04:30:00 -9065,786,5,10.0,2008-03-23 07:00:00 -9066,786,4,0.0,2008-03-23 07:00:00 -9067,786,7,0.0,2008-03-23 07:00:00 -9068,786,2,0.0,2008-03-23 07:00:00 -9069,786,9,0.0,2008-03-23 07:00:00 -9070,786,6,5.0,2008-03-23 07:00:00 -9071,786,3,1.0,2008-03-23 07:00:00 -9072,786,8,2.0,2008-03-23 07:00:00 -9073,786,0,10.0,2008-03-23 07:00:00 -9074,786,1,11.0,2008-03-23 07:00:00 -9075,786,10,0.0,2008-03-23 07:00:00 -9076,787,10,0.0,2008-04-06 11:30:00 -9077,787,7,0.0,2008-04-06 11:30:00 -9078,787,4,0.0,2008-04-06 11:30:00 -9079,787,9,0.0,2008-04-06 11:30:00 -9080,787,3,0.0,2008-04-06 11:30:00 -9081,787,6,3.0,2008-04-06 11:30:00 -9082,787,8,2.0,2008-04-06 11:30:00 -9083,787,5,18.0,2008-04-06 11:30:00 -9084,787,0,4.0,2008-04-06 11:30:00 -9085,787,1,11.0,2008-04-06 11:30:00 -9086,787,2,1.0,2008-04-06 11:30:00 -9087,788,4,0.0,2008-04-27 12:00:00 -9088,788,3,0.0,2008-04-27 12:00:00 -9089,788,7,0.0,2008-04-27 12:00:00 -9090,788,9,0.0,2008-04-27 12:00:00 -9091,788,6,1.0,2008-04-27 12:00:00 -9092,788,2,2.0,2008-04-27 12:00:00 -9093,788,8,4.0,2008-04-27 12:00:00 -9094,788,1,5.0,2008-04-27 12:00:00 -9095,788,0,6.0,2008-04-27 12:00:00 -9096,788,5,18.0,2008-04-27 12:00:00 -9097,788,10,3.0,2008-04-27 12:00:00 -9098,789,10,0.0,2008-05-11 12:00:00 -9099,789,4,0.0,2008-05-11 12:00:00 -9100,789,9,0.0,2008-05-11 12:00:00 -9101,789,6,0.0,2008-05-11 12:00:00 -9102,789,0,8.0,2008-05-11 12:00:00 -9103,789,8,2.0,2008-05-11 12:00:00 -9104,789,5,16.0,2008-05-11 12:00:00 -9105,789,2,1.0,2008-05-11 12:00:00 -9106,789,3,3.0,2008-05-11 12:00:00 -9107,789,1,9.0,2008-05-11 12:00:00 -9108,790,0,11.0,2008-05-25 12:00:00 -9109,790,1,8.0,2008-05-25 12:00:00 -9110,790,5,6.0,2008-05-25 12:00:00 -9111,790,8,5.0,2008-05-25 12:00:00 -9112,790,4,4.0,2008-05-25 12:00:00 -9113,790,2,2.0,2008-05-25 12:00:00 -9114,790,3,0.0,2008-05-25 12:00:00 -9115,790,6,0.0,2008-05-25 12:00:00 -9116,790,9,0.0,2008-05-25 12:00:00 -9117,790,10,3.0,2008-05-25 12:00:00 -9118,791,0,0.0,2008-06-08 17:00:00 -9119,791,3,0.0,2008-06-08 17:00:00 -9120,791,9,0.0,2008-06-08 17:00:00 -9121,791,2,0.0,2008-06-08 17:00:00 -9122,791,4,1.0,2008-06-08 17:00:00 -9123,791,5,4.0,2008-06-08 17:00:00 -9124,791,6,8.0,2008-06-08 17:00:00 -9125,791,8,6.0,2008-06-08 17:00:00 -9126,791,1,18.0,2008-06-08 17:00:00 -9127,791,10,2.0,2008-06-08 17:00:00 -9128,792,9,0.0,2008-06-22 12:00:00 -9129,792,2,0.0,2008-06-22 12:00:00 -9130,792,10,0.0,2008-06-22 12:00:00 -9131,792,4,0.0,2008-06-22 12:00:00 -9132,792,3,3.0,2008-06-22 12:00:00 -9133,792,1,4.0,2008-06-22 12:00:00 -9134,792,0,5.0,2008-06-22 12:00:00 -9135,792,6,6.0,2008-06-22 12:00:00 -9136,792,5,18.0,2008-06-22 12:00:00 -9137,792,8,3.0,2008-06-22 12:00:00 -9138,793,8,0.0,2008-07-06 12:00:00 -9139,793,9,0.0,2008-07-06 12:00:00 -9140,793,4,0.0,2008-07-06 12:00:00 -9141,793,2,1.0,2008-07-06 12:00:00 -9142,793,6,2.0,2008-07-06 12:00:00 -9143,793,3,3.0,2008-07-06 12:00:00 -9144,793,5,5.0,2008-07-06 12:00:00 -9145,793,10,6.0,2008-07-06 12:00:00 -9146,793,1,8.0,2008-07-06 12:00:00 -9147,793,0,14.0,2008-07-06 12:00:00 -9148,794,10,0.0,2008-07-20 12:00:00 -9149,794,9,0.0,2008-07-20 12:00:00 -9150,794,8,0.0,2008-07-20 12:00:00 -9151,794,2,0.0,2008-07-20 12:00:00 -9152,794,6,0.0,2008-07-20 12:00:00 -9153,794,4,1.0,2008-07-20 12:00:00 -9154,794,1,7.0,2008-07-20 12:00:00 -9155,794,5,9.0,2008-07-20 12:00:00 -9156,794,3,8.0,2008-07-20 12:00:00 -9157,794,0,14.0,2008-07-20 12:00:00 -9158,795,4,0.0,2008-08-03 12:00:00 -9159,795,9,0.0,2008-08-03 12:00:00 -9160,795,2,0.0,2008-08-03 12:00:00 -9161,795,10,0.0,2008-08-03 12:00:00 -9162,795,8,0.0,2008-08-03 12:00:00 -9163,795,1,1.0,2008-08-03 12:00:00 -9164,795,3,8.0,2008-08-03 12:00:00 -9165,795,5,6.0,2008-08-03 12:00:00 -9166,795,6,10.0,2008-08-03 12:00:00 -9167,795,0,14.0,2008-08-03 12:00:00 -9168,796,9,0.0,2008-08-24 12:00:00 -9169,796,10,0.0,2008-08-24 12:00:00 -9170,796,8,0.0,2008-08-24 12:00:00 -9171,796,3,0.0,2008-08-24 12:00:00 -9172,796,2,1.0,2008-08-24 12:00:00 -9173,796,4,3.0,2008-08-24 12:00:00 -9174,796,6,6.0,2008-08-24 12:00:00 -9175,796,1,6.0,2008-08-24 12:00:00 -9176,796,0,13.0,2008-08-24 12:00:00 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-2039,235,64,2.0,3,0,1974-01-13 00:00:00 -2040,235,24,1.0,4,0,1974-01-13 00:00:00 -2041,235,0,9.0,1,1,1974-01-13 00:00:00 -2042,235,31,0.0,8,0,1974-01-13 00:00:00 -2043,235,61,0.0,9,0,1974-01-13 00:00:00 -2044,235,78,0.0,10,0,1974-01-13 00:00:00 -2045,235,56,0.0,11,0,1974-01-13 00:00:00 -2046,235,5,6.0,2,0,1974-01-13 00:00:00 -2047,236,56,0.0,10,0,1974-01-27 00:00:00 -2048,236,78,0.0,11,0,1974-01-27 00:00:00 -2049,236,31,4.0,3,0,1974-01-27 00:00:00 -2050,236,61,3.0,4,0,1974-01-27 00:00:00 -2051,236,0,18.0,1,2,1974-01-27 00:00:00 -2052,236,5,12.0,2,0,1974-01-27 00:00:00 -2053,236,64,2.0,5,0,1974-01-27 00:00:00 -2054,236,24,1.0,6,0,1974-01-27 00:00:00 -2055,236,36,0.0,8,0,1974-01-27 00:00:00 -2056,236,25,0.0,9,0,1974-01-27 00:00:00 -2057,236,33,0.0,7,0,1974-01-27 00:00:00 -2058,237,24,4.0,6,0,1974-03-30 00:00:00 -2059,237,62,0.0,12,0,1974-03-30 00:00:00 -2060,237,56,0.0,11,0,1974-03-30 00:00:00 -2061,237,78,1.0,9,0,1974-03-30 00:00:00 -2062,237,31,4.0,5,0,1974-03-30 00:00:00 -2063,237,61,3.0,7,0,1974-03-30 00:00:00 -2064,237,0,22.0,1,2,1974-03-30 00:00:00 -2065,237,5,12.0,2,0,1974-03-30 00:00:00 -2066,237,64,8.0,4,0,1974-03-30 00:00:00 -2067,237,33,9.0,3,1,1974-03-30 00:00:00 -2068,237,36,2.0,8,0,1974-03-30 00:00:00 -2069,237,25,0.0,10,0,1974-03-30 00:00:00 -2070,238,24,6.0,5,0,1974-04-28 00:00:00 -2071,238,33,9.0,3,1,1974-04-28 00:00:00 -2072,238,75,0.0,13,0,1974-04-28 00:00:00 -2073,238,25,0.0,12,0,1974-04-28 00:00:00 -2074,238,64,8.0,4,0,1974-04-28 00:00:00 -2075,238,36,5.0,6,0,1974-04-28 00:00:00 -2076,238,5,21.0,2,1,1974-04-28 00:00:00 -2077,238,78,1.0,9,0,1974-04-28 00:00:00 -2078,238,61,3.0,8,0,1974-04-28 00:00:00 -2079,238,31,4.0,7,0,1974-04-28 00:00:00 -2080,238,62,0.0,11,0,1974-04-28 00:00:00 -2081,238,56,0.0,10,0,1974-04-28 00:00:00 -2082,238,76,0.0,14,0,1974-04-28 00:00:00 -2083,238,0,26.0,1,2,1974-04-28 00:00:00 -2084,239,0,35.0,1,3,1974-05-12 00:00:00 -2085,239,25,0.0,11,0,1974-05-12 00:00:00 -2086,239,36,5.0,6,0,1974-05-12 00:00:00 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-2111,240,76,0.0,16,0,1974-05-26 00:00:00 -2112,240,77,0.0,15,0,1974-05-26 00:00:00 -2113,240,25,0.0,11,0,1974-05-26 00:00:00 -2114,240,78,1.0,10,0,1974-05-26 00:00:00 -2115,240,36,5.0,7,0,1974-05-26 00:00:00 -2116,241,0,40.0,1,3,1974-06-09 00:00:00 -2117,241,76,0.0,16,0,1974-06-09 00:00:00 -2118,241,25,1.0,11,0,1974-06-09 00:00:00 -2119,241,36,5.0,8,0,1974-06-09 00:00:00 -2120,241,33,10.0,5,1,1974-06-09 00:00:00 -2121,241,24,25.0,3,1,1974-06-09 00:00:00 -2122,241,5,30.0,2,1,1974-06-09 00:00:00 -2123,241,77,0.0,15,0,1974-06-09 00:00:00 -2124,241,64,10.0,6,0,1974-06-09 00:00:00 -2125,241,31,13.0,4,1,1974-06-09 00:00:00 -2126,241,78,1.0,12,0,1974-06-09 00:00:00 -2127,241,75,0.0,13,0,1974-06-09 00:00:00 -2128,241,62,4.0,9,0,1974-06-09 00:00:00 -2129,241,56,6.0,7,0,1974-06-09 00:00:00 -2130,241,55,0.0,14,0,1974-06-09 00:00:00 -2131,241,61,3.0,10,0,1974-06-09 00:00:00 -2132,242,0,42.0,1,3,1974-06-23 00:00:00 -2133,242,25,1.0,11,0,1974-06-23 00:00:00 -2134,242,36,5.0,8,0,1974-06-23 00:00:00 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00:00:00 -2159,243,62,4.0,9,0,1974-07-07 00:00:00 -2160,243,56,6.0,7,0,1974-07-07 00:00:00 -2161,243,55,0.0,14,0,1974-07-07 00:00:00 -2162,243,76,0.0,16,0,1974-07-07 00:00:00 -2163,243,77,0.0,15,0,1974-07-07 00:00:00 -2164,244,0,49.0,1,3,1974-07-20 00:00:00 -2165,244,36,5.0,8,0,1974-07-20 00:00:00 -2166,244,33,11.0,5,1,1974-07-20 00:00:00 -2167,244,24,39.0,3,2,1974-07-20 00:00:00 -2168,244,64,10.0,6,0,1974-07-20 00:00:00 -2169,244,5,48.0,2,2,1974-07-20 00:00:00 -2170,244,25,1.0,11,0,1974-07-20 00:00:00 -2171,244,61,3.0,10,0,1974-07-20 00:00:00 -2172,244,75,0.0,13,0,1974-07-20 00:00:00 -2173,244,56,6.0,7,0,1974-07-20 00:00:00 -2174,244,55,0.0,14,0,1974-07-20 00:00:00 -2175,244,76,0.0,16,0,1974-07-20 00:00:00 -2176,244,77,0.0,15,0,1974-07-20 00:00:00 -2177,244,74,0.0,17,0,1974-07-20 00:00:00 -2178,244,72,0.0,18,0,1974-07-20 00:00:00 -2179,244,78,1.0,12,0,1974-07-20 00:00:00 -2180,244,62,4.0,9,0,1974-07-20 00:00:00 -2181,244,31,26.0,4,2,1974-07-20 00:00:00 -2182,245,5,57.0,1,3,1974-08-04 00:00:00 -2183,245,64,10.0,6,0,1974-08-04 00:00:00 -2184,245,25,1.0,11,0,1974-08-04 00:00:00 -2185,245,33,15.0,5,1,1974-08-04 00:00:00 -2186,245,36,5.0,8,0,1974-08-04 00:00:00 -2187,245,0,49.0,2,3,1974-08-04 00:00:00 -2188,245,24,45.0,3,2,1974-08-04 00:00:00 -2189,245,61,3.0,10,0,1974-08-04 00:00:00 -2190,245,62,4.0,9,0,1974-08-04 00:00:00 -2191,245,78,1.0,12,0,1974-08-04 00:00:00 -2192,245,75,0.0,13,0,1974-08-04 00:00:00 -2193,245,56,7.0,7,0,1974-08-04 00:00:00 -2194,245,55,0.0,15,0,1974-08-04 00:00:00 -2195,245,77,0.0,14,0,1974-08-04 00:00:00 -2196,245,76,0.0,16,0,1974-08-04 00:00:00 -2197,245,74,0.0,17,0,1974-08-04 00:00:00 -2198,245,31,29.0,4,2,1974-08-04 00:00:00 -2199,245,72,0.0,18,0,1974-08-04 00:00:00 -2200,246,25,1.0,11,0,1974-08-18 00:00:00 -2201,246,33,24.0,5,2,1974-08-18 00:00:00 -2202,246,24,45.0,3,2,1974-08-18 00:00:00 -2203,246,64,10.0,6,0,1974-08-18 00:00:00 -2204,246,5,59.0,1,3,1974-08-18 00:00:00 -2205,246,0,55.0,2,3,1974-08-18 00:00:00 -2206,246,61,3.0,10,0,1974-08-18 00:00:00 -2207,246,36,6.0,9,0,1974-08-18 00:00:00 -2208,246,78,1.0,12,0,1974-08-18 00:00:00 -2209,246,75,0.0,13,0,1974-08-18 00:00:00 -2210,246,62,8.0,7,0,1974-08-18 00:00:00 -2211,246,56,7.0,8,0,1974-08-18 00:00:00 -2212,246,55,0.0,15,0,1974-08-18 00:00:00 -2213,246,77,0.0,14,0,1974-08-18 00:00:00 -2214,246,76,0.0,16,0,1974-08-18 00:00:00 -2215,246,74,0.0,17,0,1974-08-18 00:00:00 -2216,246,72,0.0,18,0,1974-08-18 00:00:00 -2217,246,31,29.0,4,2,1974-08-18 00:00:00 -2218,247,0,61.0,1,3,1974-09-08 00:00:00 -2219,247,5,59.0,2,3,1974-09-08 00:00:00 -2220,247,25,1.0,12,0,1974-09-08 00:00:00 -2221,247,24,49.0,3,2,1974-09-08 00:00:00 -2222,247,36,6.0,9,0,1974-09-08 00:00:00 -2223,247,64,10.0,6,0,1974-09-08 00:00:00 -2224,247,61,3.0,11,0,1974-09-08 00:00:00 -2225,247,33,26.0,5,2,1974-09-08 00:00:00 -2226,247,78,4.0,10,0,1974-09-08 00:00:00 -2227,247,31,38.0,4,3,1974-09-08 00:00:00 -2228,247,72,0.0,18,0,1974-09-08 00:00:00 -2229,247,74,0.0,17,0,1974-09-08 00:00:00 -2230,247,76,0.0,16,0,1974-09-08 00:00:00 -2231,247,75,0.0,13,0,1974-09-08 00:00:00 -2232,247,55,0.0,15,0,1974-09-08 00:00:00 -2233,247,56,7.0,8,0,1974-09-08 00:00:00 -2234,247,62,8.0,7,0,1974-09-08 00:00:00 -2235,247,77,0.0,14,0,1974-09-08 00:00:00 -2236,248,25,1.0,12,0,1974-09-22 00:00:00 -2237,248,36,6.0,9,0,1974-09-22 00:00:00 -2238,248,33,26.0,5,2,1974-09-22 00:00:00 -2239,248,24,51.0,3,2,1974-09-22 00:00:00 -2240,248,64,10.0,7,0,1974-09-22 00:00:00 -2241,248,5,65.0,2,3,1974-09-22 00:00:00 -2242,248,0,70.0,1,4,1974-09-22 00:00:00 -2243,248,61,3.0,11,0,1974-09-22 00:00:00 -2244,248,31,42.0,4,3,1974-09-22 00:00:00 -2245,248,75,0.0,14,0,1974-09-22 00:00:00 -2246,248,62,11.0,6,0,1974-09-22 00:00:00 -2247,248,56,7.0,8,0,1974-09-22 00:00:00 -2248,248,77,0.0,16,0,1974-09-22 00:00:00 -2249,248,65,0.0,15,0,1974-09-22 00:00:00 -2250,248,71,0.0,13,0,1974-09-22 00:00:00 -2251,248,76,0.0,18,0,1974-09-22 00:00:00 -2252,248,74,0.0,19,0,1974-09-22 00:00:00 -2253,248,72,0.0,20,0,1974-09-22 00:00:00 -2254,248,78,4.0,10,0,1974-09-22 00:00:00 -2255,248,55,0.0,17,0,1974-09-22 00:00:00 -2256,249,25,1.0,12,0,1974-10-06 00:00:00 -2257,249,24,52.0,3,2,1974-10-06 00:00:00 -2258,249,36,6.0,9,0,1974-10-06 00:00:00 -2259,249,33,35.0,5,3,1974-10-06 00:00:00 -2260,249,64,10.0,7,0,1974-10-06 00:00:00 -2261,249,5,65.0,2,3,1974-10-06 00:00:00 -2262,249,0,73.0,1,4,1974-10-06 00:00:00 -2263,249,61,3.0,11,0,1974-10-06 00:00:00 -2264,249,78,4.0,10,0,1974-10-06 00:00:00 -2265,249,75,0.0,14,0,1974-10-06 00:00:00 -2266,249,31,42.0,4,3,1974-10-06 00:00:00 -2267,249,56,7.0,8,0,1974-10-06 00:00:00 -2268,249,55,0.0,17,0,1974-10-06 00:00:00 -2269,249,77,0.0,16,0,1974-10-06 00:00:00 -2270,249,65,0.0,15,0,1974-10-06 00:00:00 -2271,249,71,0.0,13,0,1974-10-06 00:00:00 -2272,249,76,0.0,18,0,1974-10-06 00:00:00 -2273,249,74,0.0,19,0,1974-10-06 00:00:00 -2274,249,72,0.0,20,0,1974-10-06 00:00:00 -2275,249,62,15.0,6,0,1974-10-06 00:00:00 -2276,250,24,2.0,5,0,1975-01-12 00:00:00 -2277,250,199,0.0,10,0,1975-01-12 00:00:00 -2278,250,25,0.0,9,0,1975-01-12 00:00:00 -2279,250,36,0.0,8,0,1975-01-12 00:00:00 -2280,250,31,0.0,7,0,1975-01-12 00:00:00 -2281,250,65,0.0,6,0,1975-01-12 00:00:00 -2282,250,5,3.0,4,0,1975-01-12 00:00:00 -2283,250,54,0.0,14,0,1975-01-12 00:00:00 -2284,250,62,6.0,2,0,1975-01-12 00:00:00 -2285,250,0,9.0,1,1,1975-01-12 00:00:00 -2286,250,2,0.0,11,0,1975-01-12 00:00:00 -2287,250,71,0.0,12,0,1975-01-12 00:00:00 -2288,250,64,0.0,13,0,1975-01-12 00:00:00 -2289,250,33,4.0,3,0,1975-01-12 00:00:00 -2290,251,65,0.0,7,0,1975-01-26 00:00:00 -2291,251,31,0.0,8,0,1975-01-26 00:00:00 -2292,251,36,0.0,9,0,1975-01-26 00:00:00 -2293,251,33,13.0,2,1,1975-01-26 00:00:00 -2294,251,199,0.0,13,0,1975-01-26 00:00:00 -2295,251,24,2.0,5,0,1975-01-26 00:00:00 -2296,251,25,0.0,10,0,1975-01-26 00:00:00 -2297,251,5,6.0,4,0,1975-01-26 00:00:00 -2298,251,71,0.0,6,0,1975-01-26 00:00:00 -2299,251,62,7.0,3,0,1975-01-26 00:00:00 -2300,251,0,15.0,1,1,1975-01-26 00:00:00 -2301,251,54,0.0,14,0,1975-01-26 00:00:00 -2302,251,2,0.0,12,0,1975-01-26 00:00:00 -2303,251,61,0.0,11,0,1975-01-26 00:00:00 -2304,251,64,0.0,15,0,1975-01-26 00:00:00 -2305,252,199,0.0,10,0,1975-03-01 00:00:00 -2306,252,25,0.0,12,0,1975-03-01 00:00:00 -2307,252,36,0.0,11,0,1975-03-01 00:00:00 -2308,252,31,0.0,9,0,1975-03-01 00:00:00 -2309,252,65,0.0,6,0,1975-03-01 00:00:00 -2310,252,24,11.0,3,1,1975-03-01 00:00:00 -2311,252,5,8.0,4,0,1975-03-01 00:00:00 -2312,252,33,19.0,1,1,1975-03-01 00:00:00 -2313,252,62,7.0,5,0,1975-03-01 00:00:00 -2314,252,0,16.0,2,1,1975-03-01 00:00:00 -2315,252,54,0.0,15,0,1975-03-01 00:00:00 -2316,252,2,0.0,14,0,1975-03-01 00:00:00 -2317,252,61,0.0,13,0,1975-03-01 00:00:00 -2318,252,71,0.0,7,0,1975-03-01 00:00:00 -2319,252,64,0.0,16,0,1975-03-01 00:00:00 -2320,252,73,0.0,8,0,1975-03-01 00:00:00 -2321,253,5,8.0,4,0,1975-04-27 00:00:00 -2322,253,25,0.0,14,0,1975-04-27 00:00:00 -2323,253,36,1.0,8,0,1975-04-27 00:00:00 -2324,253,31,3.0,6,0,1975-04-27 00:00:00 -2325,253,65,0.0,9,0,1975-04-27 00:00:00 -2326,253,24,11.0,3,1,1975-04-27 00:00:00 -2327,253,199,1.5,7,0,1975-04-27 00:00:00 -2328,253,33,21.0,1,1,1975-04-27 00:00:00 -2329,253,0,20.5,2,2,1975-04-27 00:00:00 -2330,253,54,0.0,15,0,1975-04-27 00:00:00 -2331,253,2,0.0,10,0,1975-04-27 00:00:00 -2332,253,61,0.0,13,0,1975-04-27 00:00:00 -2333,253,71,0.0,11,0,1975-04-27 00:00:00 -2334,253,64,0.0,16,0,1975-04-27 00:00:00 -2335,253,73,0.0,12,0,1975-04-27 00:00:00 -2336,253,55,0.0,17,0,1975-04-27 00:00:00 -2337,253,62,7.0,5,0,1975-04-27 00:00:00 -2338,254,73,0.0,12,0,1975-05-11 00:00:00 -2339,254,55,0.0,17,0,1975-05-11 00:00:00 -2340,254,71,0.0,11,0,1975-05-11 00:00:00 -2341,254,64,0.0,16,0,1975-05-11 00:00:00 -2342,254,61,0.0,13,0,1975-05-11 00:00:00 -2343,254,199,1.5,7,0,1975-05-11 00:00:00 -2344,254,25,0.0,14,0,1975-05-11 00:00:00 -2345,254,31,6.0,6,0,1975-05-11 00:00:00 -2346,254,65,0.0,9,0,1975-05-11 00:00:00 -2347,254,24,13.0,4,1,1975-05-11 00:00:00 -2348,254,36,1.0,8,0,1975-05-11 00:00:00 -2349,254,33,25.0,2,1,1975-05-11 00:00:00 -2350,254,62,7.0,5,0,1975-05-11 00:00:00 -2351,254,0,26.5,1,2,1975-05-11 00:00:00 -2352,254,54,0.0,15,0,1975-05-11 00:00:00 -2353,254,2,0.0,10,0,1975-05-11 00:00:00 -2354,254,5,17.0,3,1,1975-05-11 00:00:00 -2355,255,33,29.0,1,1,1975-05-25 00:00:00 -2356,255,25,0.0,15,0,1975-05-25 00:00:00 -2357,255,36,1.0,8,0,1975-05-25 00:00:00 -2358,255,31,6.0,6,0,1975-05-25 00:00:00 -2359,255,65,0.0,9,0,1975-05-25 00:00:00 -2360,255,24,19.0,4,1,1975-05-25 00:00:00 -2361,255,5,26.0,3,2,1975-05-25 00:00:00 -2362,255,62,7.0,5,0,1975-05-25 00:00:00 -2363,255,61,0.0,13,0,1975-05-25 00:00:00 -2364,255,54,0.0,16,0,1975-05-25 00:00:00 -2365,255,2,0.0,10,0,1975-05-25 00:00:00 -2366,255,71,0.0,11,0,1975-05-25 00:00:00 -2367,255,64,0.0,14,0,1975-05-25 00:00:00 -2368,255,199,2.5,7,0,1975-05-25 00:00:00 -2369,255,55,0.0,17,0,1975-05-25 00:00:00 -2370,255,0,26.5,2,2,1975-05-25 00:00:00 -2371,255,73,0.0,12,0,1975-05-25 00:00:00 -2372,256,36,1.0,10,0,1975-06-08 00:00:00 -2373,256,24,19.0,4,1,1975-06-08 00:00:00 -2374,256,25,0.0,15,0,1975-06-08 00:00:00 -2375,256,199,2.5,8,0,1975-06-08 00:00:00 -2376,256,33,33.0,2,1,1975-06-08 00:00:00 -2377,256,65,2.0,9,0,1975-06-08 00:00:00 -2378,256,31,6.0,6,0,1975-06-08 00:00:00 -2379,256,0,26.5,3,2,1975-06-08 00:00:00 -2380,256,71,3.0,7,0,1975-06-08 00:00:00 -2381,256,2,0.0,12,0,1975-06-08 00:00:00 -2382,256,55,0.0,17,0,1975-06-08 00:00:00 -2383,256,73,1.0,11,0,1975-06-08 00:00:00 -2384,256,54,0.0,16,0,1975-06-08 00:00:00 -2385,256,62,7.0,5,0,1975-06-08 00:00:00 -2386,256,61,0.0,13,0,1975-06-08 00:00:00 -2387,256,5,35.0,1,3,1975-06-08 00:00:00 -2388,256,64,0.0,14,0,1975-06-08 00:00:00 -2389,257,55,0.0,16,0,1975-06-22 00:00:00 -2390,257,62,16.0,5,1,1975-06-22 00:00:00 -2391,257,5,41.0,1,3,1975-06-22 00:00:00 -2392,257,65,2.0,9,0,1975-06-22 00:00:00 -2393,257,199,3.5,7,0,1975-06-22 00:00:00 -2394,257,72,0.0,18,0,1975-06-22 00:00:00 -2395,257,36,1.0,10,0,1975-06-22 00:00:00 -2396,257,25,0.0,15,0,1975-06-22 00:00:00 -2397,257,33,36.0,2,1,1975-06-22 00:00:00 -2398,257,0,26.5,3,2,1975-06-22 00:00:00 -2399,257,54,0.0,17,0,1975-06-22 00:00:00 -2400,257,2,0.0,12,0,1975-06-22 00:00:00 -2401,257,61,0.0,13,0,1975-06-22 00:00:00 -2402,257,71,3.0,8,0,1975-06-22 00:00:00 -2403,257,64,0.0,14,0,1975-06-22 00:00:00 -2404,257,73,1.0,11,0,1975-06-22 00:00:00 -2405,257,31,6.0,6,0,1975-06-22 00:00:00 -2406,257,24,19.0,4,1,1975-06-22 00:00:00 -2407,258,5,50.0,1,4,1975-07-06 00:00:00 -2408,258,54,0.0,17,0,1975-07-06 00:00:00 -2409,258,33,36.0,2,1,1975-07-06 00:00:00 -2410,258,65,2.0,9,0,1975-07-06 00:00:00 -2411,258,199,3.5,8,0,1975-07-06 00:00:00 -2412,258,36,1.0,10,0,1975-07-06 00:00:00 -2413,258,31,6.0,6,0,1975-07-06 00:00:00 -2414,258,24,20.0,5,1,1975-07-06 00:00:00 -2415,258,62,22.0,4,1,1975-07-06 00:00:00 -2416,258,0,30.5,3,2,1975-07-06 00:00:00 -2417,258,2,0.0,12,0,1975-07-06 00:00:00 -2418,258,61,0.0,13,0,1975-07-06 00:00:00 -2419,258,71,5.0,7,0,1975-07-06 00:00:00 -2420,258,64,0.0,14,0,1975-07-06 00:00:00 -2421,258,73,1.0,11,0,1975-07-06 00:00:00 -2422,258,55,0.0,16,0,1975-07-06 00:00:00 -2423,258,72,0.0,18,0,1975-07-06 00:00:00 -2424,258,25,0.0,15,0,1975-07-06 00:00:00 -2425,259,199,3.5,8,0,1975-07-19 00:00:00 -2426,259,5,50.0,1,4,1975-07-19 00:00:00 -2427,259,54,0.0,17,0,1975-07-19 00:00:00 -2428,259,25,0.0,15,0,1975-07-19 00:00:00 -2429,259,24,24.0,5,1,1975-07-19 00:00:00 -2430,259,36,3.0,9,0,1975-07-19 00:00:00 -2431,259,31,6.0,6,0,1975-07-19 00:00:00 -2432,259,65,2.0,10,0,1975-07-19 00:00:00 -2433,259,33,42.0,2,1,1975-07-19 00:00:00 -2434,259,62,25.0,4,1,1975-07-19 00:00:00 -2435,259,0,39.5,3,3,1975-07-19 00:00:00 -2436,259,2,0.0,12,0,1975-07-19 00:00:00 -2437,259,71,5.0,7,0,1975-07-19 00:00:00 -2438,259,64,0.0,14,0,1975-07-19 00:00:00 -2439,259,73,1.0,11,0,1975-07-19 00:00:00 -2440,259,55,0.0,16,0,1975-07-19 00:00:00 -2441,259,74,0.0,18,0,1975-07-19 00:00:00 -2442,259,72,0.0,19,0,1975-07-19 00:00:00 -2443,259,61,0.0,13,0,1975-07-19 00:00:00 -2444,260,24,24.0,5,1,1975-08-03 00:00:00 -2445,260,62,25.0,4,1,1975-08-03 00:00:00 -2446,260,65,2.0,12,0,1975-08-03 00:00:00 -2447,260,0,39.5,3,3,1975-08-03 00:00:00 -2448,260,36,3.0,10,0,1975-08-03 00:00:00 -2449,260,25,0.0,16,0,1975-08-03 00:00:00 -2450,260,74,0.0,18,0,1975-08-03 00:00:00 -2451,260,31,6.0,7,0,1975-08-03 00:00:00 -2452,260,2,6.0,8,0,1975-08-03 00:00:00 -2453,260,5,54.0,1,4,1975-08-03 00:00:00 -2454,260,72,0.0,19,0,1975-08-03 00:00:00 -2455,260,55,1.0,13,0,1975-08-03 00:00:00 -2456,260,73,3.0,11,0,1975-08-03 00:00:00 -2457,260,64,0.0,15,0,1975-08-03 00:00:00 -2458,260,71,5.0,9,0,1975-08-03 00:00:00 -2459,260,61,0.0,14,0,1975-08-03 00:00:00 -2460,260,54,0.0,17,0,1975-08-03 00:00:00 -2461,260,199,6.5,6,0,1975-08-03 00:00:00 -2462,260,33,51.0,2,2,1975-08-03 00:00:00 -2463,261,25,0.0,16,0,1975-08-17 00:00:00 -2464,261,36,7.5,7,1,1975-08-17 00:00:00 -2465,261,31,7.0,8,0,1975-08-17 00:00:00 -2466,261,199,8.5,6,0,1975-08-17 00:00:00 -2467,261,65,2.0,12,0,1975-08-17 00:00:00 -2468,261,24,24.0,5,1,1975-08-17 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00:00:00 -3303,307,62,0.0,19,0,1978-07-30 00:00:00 -3304,307,5,31.0,3,3,1978-07-30 00:00:00 -3305,307,54,10.0,8,0,1978-07-30 00:00:00 -3306,307,0,12.0,7,0,1978-07-30 00:00:00 -3307,307,63,0.0,14,0,1978-07-30 00:00:00 -3308,308,63,0.0,14,0,1978-08-13 00:00:00 -3309,308,55,0.0,16,0,1978-08-13 00:00:00 -3310,308,58,0.0,17,0,1978-08-13 00:00:00 -3311,308,3,0.0,15,0,1978-08-13 00:00:00 -3312,308,53,0.0,18,0,1978-08-13 00:00:00 -3313,308,20,8.0,9,0,1978-08-13 00:00:00 -3314,308,31,76.0,1,7,1978-08-13 00:00:00 -3315,308,33,40.0,2,1,1978-08-13 00:00:00 -3316,308,5,35.0,4,3,1978-08-13 00:00:00 -3317,308,0,12.0,8,0,1978-08-13 00:00:00 -3318,308,54,13.0,7,0,1978-08-13 00:00:00 -3319,308,57,14.0,6,0,1978-08-13 00:00:00 -3320,308,62,0.0,19,0,1978-08-13 00:00:00 -3321,308,56,6.0,10,0,1978-08-13 00:00:00 -3322,308,26,16.0,5,0,1978-08-13 00:00:00 -3323,308,61,1.0,12,0,1978-08-13 00:00:00 -3324,308,2,5.0,11,0,1978-08-13 00:00:00 -3325,308,24,36.0,3,1,1978-08-13 00:00:00 -3326,308,52,0.0,13,0,1978-08-13 00:00:00 -3327,309,52,0.0,13,0,1978-08-27 00:00:00 -3328,309,63,0.0,14,0,1978-08-27 00:00:00 -3329,309,55,0.0,16,0,1978-08-27 00:00:00 -3330,309,58,0.0,17,0,1978-08-27 00:00:00 -3331,309,62,0.0,19,0,1978-08-27 00:00:00 -3332,309,20,8.0,9,0,1978-08-27 00:00:00 -3333,309,0,12.0,8,0,1978-08-27 00:00:00 -3334,309,33,44.0,2,1,1978-08-27 00:00:00 -3335,309,31,85.0,1,8,1978-08-27 00:00:00 -3336,309,2,5.0,11,0,1978-08-27 00:00:00 -3337,309,61,1.0,12,0,1978-08-27 00:00:00 -3338,309,26,16.0,5,0,1978-08-27 00:00:00 -3339,309,56,6.0,10,0,1978-08-27 00:00:00 -3340,309,53,0.0,18,0,1978-08-27 00:00:00 -3341,309,54,15.0,6,0,1978-08-27 00:00:00 -3342,309,5,36.0,3,3,1978-08-27 00:00:00 -3343,309,3,0.0,15,0,1978-08-27 00:00:00 -3344,309,24,36.0,4,1,1978-08-27 00:00:00 -3345,309,57,14.0,7,0,1978-08-27 00:00:00 -3346,310,2,5.0,11,0,1978-09-10 00:00:00 -3347,310,26,19.0,5,0,1978-09-10 00:00:00 -3348,310,56,6.0,10,0,1978-09-10 00:00:00 -3349,310,52,0.0,13,0,1978-09-10 00:00:00 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00:00:00 -3374,311,52,0.0,14,0,1978-10-01 00:00:00 -3375,311,56,6.0,11,0,1978-10-01 00:00:00 -3376,311,54,17.0,7,0,1978-10-01 00:00:00 -3377,311,5,49.0,3,4,1978-10-01 00:00:00 -3378,311,0,15.0,8,0,1978-10-01 00:00:00 -3379,311,24,36.0,4,1,1978-10-01 00:00:00 -3380,311,33,53.0,2,2,1978-10-01 00:00:00 -3381,311,31,86.0,1,8,1978-10-01 00:00:00 -3382,311,20,8.0,10,0,1978-10-01 00:00:00 -3383,311,57,18.0,6,0,1978-10-01 00:00:00 -3384,312,55,1.0,14,0,1978-10-08 00:00:00 -3385,312,2,11.0,9,0,1978-10-08 00:00:00 -3386,312,62,0.0,19,0,1978-10-08 00:00:00 -3387,312,58,0.0,17,0,1978-10-08 00:00:00 -3388,312,63,0.0,16,0,1978-10-08 00:00:00 -3389,312,53,0.0,18,0,1978-10-08 00:00:00 -3390,312,26,19.0,6,0,1978-10-08 00:00:00 -3391,312,3,3.0,12,0,1978-10-08 00:00:00 -3392,312,56,6.0,11,0,1978-10-08 00:00:00 -3393,312,57,24.0,5,0,1978-10-08 00:00:00 -3394,312,54,17.0,7,0,1978-10-08 00:00:00 -3395,312,52,0.0,15,0,1978-10-08 00:00:00 -3396,312,0,15.0,8,0,1978-10-08 00:00:00 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-3469,317,52,0.0,14,0,1979-04-29 00:00:00 -3470,317,3,0.0,12,0,1979-04-29 00:00:00 -3471,317,26,38.0,1,3,1979-04-29 00:00:00 -3472,317,31,30.0,3,0,1979-04-29 00:00:00 -3473,317,0,4.0,5,0,1979-04-29 00:00:00 -3474,317,54,1.0,8,0,1979-04-29 00:00:00 -3475,317,20,0.0,10,0,1979-04-29 00:00:00 -3476,317,24,11.0,4,0,1979-04-29 00:00:00 -3477,317,5,36.0,2,2,1979-04-29 00:00:00 -3478,317,57,0.0,11,0,1979-04-29 00:00:00 -3479,318,59,0.0,17,0,1979-05-13 00:00:00 -3480,318,201,1.0,8,0,1979-05-13 00:00:00 -3481,318,3,0.0,13,0,1979-05-13 00:00:00 -3482,318,57,0.0,12,0,1979-05-13 00:00:00 -3483,318,5,45.0,1,3,1979-05-13 00:00:00 -3484,318,2,4.0,6,0,1979-05-13 00:00:00 -3485,318,20,2.0,7,0,1979-05-13 00:00:00 -3486,318,56,0.0,10,0,1979-05-13 00:00:00 -3487,318,54,1.0,9,0,1979-05-13 00:00:00 -3488,318,31,33.0,3,0,1979-05-13 00:00:00 -3489,318,26,44.0,2,3,1979-05-13 00:00:00 -3490,318,52,0.0,11,0,1979-05-13 00:00:00 -3491,318,49,0.0,15,0,1979-05-13 00:00:00 -3492,318,0,5.0,5,0,1979-05-13 00:00:00 -3493,318,58,0.0,16,0,1979-05-13 00:00:00 -3494,318,55,0.0,14,0,1979-05-13 00:00:00 -3495,318,24,15.0,4,0,1979-05-13 00:00:00 -3496,319,55,0.0,14,0,1979-05-27 00:00:00 -3497,319,57,0.0,12,0,1979-05-27 00:00:00 -3498,319,3,0.0,13,0,1979-05-27 00:00:00 -3499,319,201,1.0,8,0,1979-05-27 00:00:00 -3500,319,20,3.0,7,0,1979-05-27 00:00:00 -3501,319,24,15.0,4,0,1979-05-27 00:00:00 -3502,319,56,0.0,10,0,1979-05-27 00:00:00 -3503,319,2,10.0,5,0,1979-05-27 00:00:00 -3504,319,54,1.0,9,0,1979-05-27 00:00:00 -3505,319,0,8.0,6,0,1979-05-27 00:00:00 -3506,319,31,37.0,3,0,1979-05-27 00:00:00 -3507,319,26,46.0,2,3,1979-05-27 00:00:00 -3508,319,52,0.0,11,0,1979-05-27 00:00:00 -3509,319,58,0.0,16,0,1979-05-27 00:00:00 -3510,319,59,0.0,17,0,1979-05-27 00:00:00 -3511,319,49,0.0,15,0,1979-05-27 00:00:00 -3512,319,5,54.0,1,4,1979-05-27 00:00:00 -3513,320,55,0.0,14,0,1979-07-01 00:00:00 -3514,320,49,0.0,15,0,1979-07-01 00:00:00 -3515,320,58,0.0,16,0,1979-07-01 00:00:00 -3516,320,52,0.0,13,0,1979-07-01 00:00:00 -3517,320,26,46.0,2,3,1979-07-01 00:00:00 -3518,320,31,37.0,3,0,1979-07-01 00:00:00 -3519,320,59,0.0,17,0,1979-07-01 00:00:00 -3520,320,2,14.0,5,0,1979-07-01 00:00:00 -3521,320,54,1.0,10,0,1979-07-01 00:00:00 -3522,320,3,13.0,6,1,1979-07-01 00:00:00 -3523,320,56,0.0,11,0,1979-07-01 00:00:00 -3524,320,20,3.0,8,0,1979-07-01 00:00:00 -3525,320,0,8.0,7,0,1979-07-01 00:00:00 -3526,320,5,60.0,1,4,1979-07-01 00:00:00 -3527,320,24,17.0,4,0,1979-07-01 00:00:00 -3528,320,201,1.0,9,0,1979-07-01 00:00:00 -3529,320,57,0.0,12,0,1979-07-01 00:00:00 -3530,321,24,21.0,5,0,1979-07-14 00:00:00 -3531,321,201,1.0,9,0,1979-07-14 00:00:00 -3532,321,20,3.0,8,0,1979-07-14 00:00:00 -3533,321,56,0.0,11,0,1979-07-14 00:00:00 -3534,321,5,62.0,1,4,1979-07-14 00:00:00 -3535,321,58,0.0,16,0,1979-07-14 00:00:00 -3536,321,26,47.0,2,3,1979-07-14 00:00:00 -3537,321,52,0.0,13,0,1979-07-14 00:00:00 -3538,321,49,0.0,15,0,1979-07-14 00:00:00 -3539,321,59,0.0,17,0,1979-07-14 00:00:00 -3540,321,31,37.0,3,0,1979-07-14 00:00:00 -3541,321,0,11.0,7,0,1979-07-14 00:00:00 -3542,321,55,0.0,14,0,1979-07-14 00:00:00 -3543,321,54,1.0,10,0,1979-07-14 00:00:00 -3544,321,3,19.0,6,1,1979-07-14 00:00:00 -3545,321,2,23.0,4,1,1979-07-14 00:00:00 -3546,321,57,0.0,12,0,1979-07-14 00:00:00 -3547,322,5,65.0,1,4,1979-07-29 00:00:00 -3548,322,54,1.0,10,0,1979-07-29 00:00:00 -3549,322,0,13.0,7,0,1979-07-29 00:00:00 -3550,322,31,37.0,4,0,1979-07-29 00:00:00 -3551,322,26,51.0,2,3,1979-07-29 00:00:00 -3552,322,52,0.0,13,0,1979-07-29 00:00:00 -3553,322,58,0.0,16,0,1979-07-29 00:00:00 -3554,322,55,0.0,14,0,1979-07-29 00:00:00 -3555,322,59,0.0,17,0,1979-07-29 00:00:00 -3556,322,49,0.0,15,0,1979-07-29 00:00:00 -3557,322,57,0.0,12,0,1979-07-29 00:00:00 -3558,322,24,21.0,5,0,1979-07-29 00:00:00 -3559,322,20,4.0,8,0,1979-07-29 00:00:00 -3560,322,3,19.0,6,1,1979-07-29 00:00:00 -3561,322,2,38.0,3,2,1979-07-29 00:00:00 -3562,322,56,0.0,11,0,1979-07-29 00:00:00 -3563,322,201,1.0,9,0,1979-07-29 00:00:00 -3564,323,31,37.0,4,0,1979-08-12 00:00:00 -3565,323,0,13.0,7,0,1979-08-12 00:00:00 -3566,323,54,1.0,10,0,1979-08-12 00:00:00 -3567,323,56,0.0,11,0,1979-08-12 00:00:00 -3568,323,20,4.0,8,0,1979-08-12 00:00:00 -3569,323,2,49.0,3,3,1979-08-12 00:00:00 -3570,323,55,0.0,14,0,1979-08-12 00:00:00 -3571,323,57,0.0,12,0,1979-08-12 00:00:00 -3572,323,24,21.0,5,0,1979-08-12 00:00:00 -3573,323,58,0.0,16,0,1979-08-12 00:00:00 -3574,323,52,0.0,13,0,1979-08-12 00:00:00 -3575,323,59,0.0,17,0,1979-08-12 00:00:00 -3576,323,49,0.0,15,0,1979-08-12 00:00:00 -3577,323,26,55.0,2,3,1979-08-12 00:00:00 -3578,323,5,74.0,1,4,1979-08-12 00:00:00 -3579,323,3,20.0,6,1,1979-08-12 00:00:00 -3580,323,201,1.0,9,0,1979-08-12 00:00:00 -3581,324,59,0.0,17,0,1979-08-26 00:00:00 -3582,324,55,0.0,14,0,1979-08-26 00:00:00 -3583,324,56,0.0,11,0,1979-08-26 00:00:00 -3584,324,0,13.0,7,0,1979-08-26 00:00:00 -3585,324,26,61.0,2,3,1979-08-26 00:00:00 -3586,324,52,0.0,13,0,1979-08-26 00:00:00 -3587,324,31,37.0,4,0,1979-08-26 00:00:00 -3588,324,54,1.0,10,0,1979-08-26 00:00:00 -3589,324,58,0.0,16,0,1979-08-26 00:00:00 -3590,324,2,58.0,3,4,1979-08-26 00:00:00 -3591,324,5,80.0,1,4,1979-08-26 00:00:00 -3592,324,49,0.0,15,0,1979-08-26 00:00:00 -3593,324,201,4.0,9,0,1979-08-26 00:00:00 -3594,324,3,20.0,6,1,1979-08-26 00:00:00 -3595,324,24,21.0,5,0,1979-08-26 00:00:00 -3596,324,57,0.0,12,0,1979-08-26 00:00:00 -3597,324,20,5.0,8,0,1979-08-26 00:00:00 -3598,325,26,61.0,3,3,1979-09-09 00:00:00 -3599,325,31,39.0,4,0,1979-09-09 00:00:00 -3600,325,20,5.0,9,0,1979-09-09 00:00:00 -3601,325,0,13.0,7,0,1979-09-09 00:00:00 -3602,325,56,0.0,11,0,1979-09-09 00:00:00 -3603,325,2,62.0,2,4,1979-09-09 00:00:00 -3604,325,5,95.0,1,5,1979-09-09 00:00:00 -3605,325,57,0.0,12,0,1979-09-09 00:00:00 -3606,325,24,22.0,5,0,1979-09-09 00:00:00 -3607,325,3,20.0,6,1,1979-09-09 00:00:00 -3608,325,58,0.0,16,0,1979-09-09 00:00:00 -3609,325,52,0.0,13,0,1979-09-09 00:00:00 -3610,325,54,1.0,10,0,1979-09-09 00:00:00 -3611,325,59,0.0,17,0,1979-09-09 00:00:00 -3612,325,49,0.0,15,0,1979-09-09 00:00:00 -3613,325,60,0.0,18,0,1979-09-09 00:00:00 -3614,325,55,0.0,14,0,1979-09-09 00:00:00 -3615,325,201,7.0,8,0,1979-09-09 00:00:00 -3616,326,54,1.0,10,0,1979-09-30 00:00:00 -3617,326,179,0.0,12,0,1979-09-30 00:00:00 -3618,326,56,0.0,11,0,1979-09-30 00:00:00 -3619,326,0,14.0,7,0,1979-09-30 00:00:00 -3620,326,31,39.0,4,0,1979-09-30 00:00:00 -3621,326,26,61.0,3,3,1979-09-30 00:00:00 -3622,326,20,5.0,9,0,1979-09-30 00:00:00 -3623,326,55,0.0,15,0,1979-09-30 00:00:00 -3624,326,5,104.0,1,5,1979-09-30 00:00:00 -3625,326,57,0.0,13,0,1979-09-30 00:00:00 -3626,326,2,75.0,2,5,1979-09-30 00:00:00 -3627,326,3,20.0,6,1,1979-09-30 00:00:00 -3628,326,201,7.0,8,0,1979-09-30 00:00:00 -3629,326,58,0.0,18,0,1979-09-30 00:00:00 -3630,326,52,0.0,14,0,1979-09-30 00:00:00 -3631,326,59,0.0,19,0,1979-09-30 00:00:00 -3632,326,49,0.0,16,0,1979-09-30 00:00:00 -3633,326,60,0.0,17,0,1979-09-30 00:00:00 -3634,326,24,24.0,5,0,1979-09-30 00:00:00 -3635,327,56,3.0,10,0,1979-10-07 00:00:00 -3636,327,26,61.0,3,3,1979-10-07 00:00:00 -3637,327,31,39.0,4,0,1979-10-07 00:00:00 -3638,327,54,1.0,12,0,1979-10-07 00:00:00 -3639,327,20,5.0,9,0,1979-10-07 00:00:00 -3640,327,0,15.0,7,0,1979-10-07 00:00:00 -3641,327,2,75.0,2,5,1979-10-07 00:00:00 -3642,327,3,26.0,6,1,1979-10-07 00:00:00 -3643,327,5,113.0,1,6,1979-10-07 00:00:00 -3644,327,179,0.0,13,0,1979-10-07 00:00:00 -3645,327,60,0.0,17,0,1979-10-07 00:00:00 -3646,327,55,0.0,15,0,1979-10-07 00:00:00 -3647,327,59,0.0,19,0,1979-10-07 00:00:00 -3648,327,52,2.0,11,0,1979-10-07 00:00:00 -3649,327,49,0.0,16,0,1979-10-07 00:00:00 -3650,327,201,7.0,8,0,1979-10-07 00:00:00 -3651,327,24,28.0,5,0,1979-10-07 00:00:00 -3652,327,57,0.0,14,0,1979-10-07 00:00:00 -3653,327,58,0.0,18,0,1979-10-07 00:00:00 -3654,328,20,0.0,10,0,1980-01-13 00:00:00 -3655,328,43,0.0,15,0,1980-01-13 00:00:00 -3656,328,56,0.0,14,0,1980-01-13 00:00:00 -3657,328,3,0.0,13,0,1980-01-13 00:00:00 -3658,328,31,0.0,12,0,1980-01-13 00:00:00 -3659,328,52,0.0,11,0,1980-01-13 00:00:00 -3660,328,26,0.0,9,0,1980-01-13 00:00:00 -3661,328,24,3.0,4,0,1980-01-13 00:00:00 -3662,328,5,0.0,7,0,1980-01-13 00:00:00 -3663,328,0,1.0,6,0,1980-01-13 00:00:00 -3664,328,49,2.0,5,0,1980-01-13 00:00:00 -3665,328,54,4.0,3,0,1980-01-13 00:00:00 -3666,328,33,6.0,2,0,1980-01-13 00:00:00 -3667,328,2,9.0,1,1,1980-01-13 00:00:00 -3668,328,55,0.0,8,0,1980-01-13 00:00:00 -3669,329,43,0.0,15,0,1980-01-27 00:00:00 -3670,329,56,0.0,14,0,1980-01-27 00:00:00 -3671,329,3,9.0,2,1,1980-01-27 00:00:00 -3672,329,31,6.0,4,0,1980-01-27 00:00:00 -3673,329,20,1.0,10,0,1980-01-27 00:00:00 -3674,329,26,3.0,7,0,1980-01-27 00:00:00 -3675,329,55,0.0,13,0,1980-01-27 00:00:00 -3676,329,52,0.0,11,0,1980-01-27 00:00:00 -3677,329,0,3.0,8,0,1980-01-27 00:00:00 -3678,329,49,2.0,9,0,1980-01-27 00:00:00 -3679,329,24,3.0,6,0,1980-01-27 00:00:00 -3680,329,54,4.0,5,0,1980-01-27 00:00:00 -3681,329,33,6.0,3,0,1980-01-27 00:00:00 -3682,329,2,13.0,1,1,1980-01-27 00:00:00 -3683,329,5,0.0,12,0,1980-01-27 00:00:00 -3684,330,31,6.0,5,0,1980-03-01 00:00:00 -3685,330,52,0.0,11,0,1980-03-01 00:00:00 -3686,330,20,2.0,10,0,1980-03-01 00:00:00 -3687,330,26,13.0,3,0,1980-03-01 00:00:00 -3688,330,55,0.0,12,0,1980-03-01 00:00:00 -3689,330,5,0.0,14,0,1980-03-01 00:00:00 -3690,330,24,3.0,7,0,1980-03-01 00:00:00 -3691,330,49,2.0,9,0,1980-03-01 00:00:00 -3692,330,54,4.0,6,0,1980-03-01 00:00:00 -3693,330,33,9.0,4,0,1980-03-01 00:00:00 -3694,330,2,15.0,2,1,1980-03-01 00:00:00 -3695,330,56,0.0,13,0,1980-03-01 00:00:00 -3696,330,0,3.0,8,0,1980-03-01 00:00:00 -3697,330,43,0.0,15,0,1980-03-01 00:00:00 -3698,330,3,18.0,1,2,1980-03-01 00:00:00 -3699,331,20,8.0,5,0,1980-03-30 00:00:00 -3700,331,56,0.0,14,0,1980-03-30 00:00:00 -3701,331,3,18.0,1,2,1980-03-30 00:00:00 -3702,331,31,6.0,7,0,1980-03-30 00:00:00 -3703,331,52,0.0,12,0,1980-03-30 00:00:00 -3704,331,26,14.0,4,0,1980-03-30 00:00:00 -3705,331,43,0.0,15,0,1980-03-30 00:00:00 -3706,331,55,0.0,13,0,1980-03-30 00:00:00 -3707,331,0,6.0,8,0,1980-03-30 00:00:00 -3708,331,49,2.0,10,0,1980-03-30 00:00:00 -3709,331,24,3.0,9,0,1980-03-30 00:00:00 -3710,331,54,8.0,6,0,1980-03-30 00:00:00 -3711,331,33,18.0,2,1,1980-03-30 00:00:00 -3712,331,2,15.0,3,1,1980-03-30 00:00:00 -3713,331,5,2.0,11,0,1980-03-30 00:00:00 -3714,332,31,6.0,7,0,1980-05-04 00:00:00 -3715,332,3,21.0,3,2,1980-05-04 00:00:00 -3716,332,2,25.0,1,1,1980-05-04 00:00:00 -3717,332,43,0.0,15,0,1980-05-04 00:00:00 -3718,332,52,0.0,12,0,1980-05-04 00:00:00 -3719,332,56,0.0,14,0,1980-05-04 00:00:00 -3720,332,20,8.0,5,0,1980-05-04 00:00:00 -3721,332,26,23.0,2,1,1980-05-04 00:00:00 -3722,332,55,0.0,13,0,1980-05-04 00:00:00 -3723,332,54,8.0,6,0,1980-05-04 00:00:00 -3724,332,24,5.0,9,0,1980-05-04 00:00:00 -3725,332,33,18.0,4,1,1980-05-04 00:00:00 -3726,332,0,6.0,8,0,1980-05-04 00:00:00 -3727,332,5,3.0,10,0,1980-05-04 00:00:00 -3728,332,49,2.0,11,0,1980-05-04 00:00:00 -3729,333,56,0.0,14,0,1980-05-18 00:00:00 -3730,333,3,21.0,4,2,1980-05-18 00:00:00 -3731,333,31,6.0,7,0,1980-05-18 00:00:00 -3732,333,52,0.0,12,0,1980-05-18 00:00:00 -3733,333,20,11.0,5,0,1980-05-18 00:00:00 -3734,333,26,29.0,2,1,1980-05-18 00:00:00 -3735,333,55,0.0,13,0,1980-05-18 00:00:00 -3736,333,43,0.0,15,0,1980-05-18 00:00:00 -3737,333,24,5.0,9,0,1980-05-18 00:00:00 -3738,333,54,9.0,6,0,1980-05-18 00:00:00 -3739,333,33,22.0,3,1,1980-05-18 00:00:00 -3740,333,2,34.0,1,2,1980-05-18 00:00:00 -3741,333,5,5.0,10,0,1980-05-18 00:00:00 -3742,333,0,6.0,8,0,1980-05-18 00:00:00 -3743,333,49,2.0,11,0,1980-05-18 00:00:00 -3744,334,2,44.0,1,3,1980-06-29 00:00:00 -3745,334,33,25.0,3,1,1980-06-29 00:00:00 -3746,334,54,9.0,6,0,1980-06-29 00:00:00 -3747,334,24,5.0,9,0,1980-06-29 00:00:00 -3748,334,49,2.0,11,0,1980-06-29 00:00:00 -3749,334,0,6.0,8,0,1980-06-29 00:00:00 -3750,334,5,5.0,10,0,1980-06-29 00:00:00 -3751,334,55,0.0,13,0,1980-06-29 00:00:00 -3752,334,26,39.0,2,1,1980-06-29 00:00:00 -3753,334,20,11.0,5,0,1980-06-29 00:00:00 -3754,334,52,0.0,12,0,1980-06-29 00:00:00 -3755,334,31,6.0,7,0,1980-06-29 00:00:00 -3756,334,3,23.0,4,2,1980-06-29 00:00:00 -3757,334,56,0.0,14,0,1980-06-29 00:00:00 -3758,334,43,0.0,15,0,1980-06-29 00:00:00 -3759,335,43,0.0,15,0,1980-07-13 00:00:00 -3760,335,33,31.0,3,1,1980-07-13 00:00:00 -3761,335,2,57.0,1,4,1980-07-13 00:00:00 -3762,335,56,0.0,14,0,1980-07-13 00:00:00 -3763,335,3,23.0,4,2,1980-07-13 00:00:00 -3764,335,31,6.0,9,0,1980-07-13 00:00:00 -3765,335,52,0.0,12,0,1980-07-13 00:00:00 -3766,335,20,11.0,5,0,1980-07-13 00:00:00 -3767,335,55,0.0,13,0,1980-07-13 00:00:00 -3768,335,5,5.0,10,0,1980-07-13 00:00:00 -3769,335,0,7.0,8,0,1980-07-13 00:00:00 -3770,335,49,2.0,11,0,1980-07-13 00:00:00 -3771,335,24,10.0,6,0,1980-07-13 00:00:00 -3772,335,26,39.0,2,1,1980-07-13 00:00:00 -3773,335,54,9.0,7,0,1980-07-13 00:00:00 -3774,336,33,34.0,3,1,1980-08-10 00:00:00 -3775,336,43,0.0,15,0,1980-08-10 00:00:00 -3776,336,3,23.0,4,2,1980-08-10 00:00:00 -3777,336,31,6.0,9,0,1980-08-10 00:00:00 -3778,336,52,0.0,12,0,1980-08-10 00:00:00 -3779,336,26,48.0,2,2,1980-08-10 00:00:00 -3780,336,56,0.0,14,0,1980-08-10 00:00:00 -3781,336,5,6.0,10,0,1980-08-10 00:00:00 -3782,336,55,0.0,13,0,1980-08-10 00:00:00 -3783,336,2,67.0,1,4,1980-08-10 00:00:00 -3784,336,54,9.0,7,0,1980-08-10 00:00:00 -3785,336,20,11.0,5,0,1980-08-10 00:00:00 -3786,336,49,4.0,11,0,1980-08-10 00:00:00 -3787,336,0,7.0,8,0,1980-08-10 00:00:00 -3788,336,24,10.0,6,0,1980-08-10 00:00:00 -3789,337,43,0.0,15,0,1980-08-17 00:00:00 -3790,337,56,0.0,14,0,1980-08-17 00:00:00 -3791,337,3,32.0,4,3,1980-08-17 00:00:00 -3792,337,31,7.0,8,0,1980-08-17 00:00:00 -3793,337,52,0.0,12,0,1980-08-17 00:00:00 -3794,337,20,11.0,5,0,1980-08-17 00:00:00 -3795,337,55,0.0,13,0,1980-08-17 00:00:00 -3796,337,5,6.0,10,0,1980-08-17 00:00:00 -3797,337,49,4.0,11,0,1980-08-17 00:00:00 -3798,337,24,10.0,6,0,1980-08-17 00:00:00 -3799,337,54,9.0,7,0,1980-08-17 00:00:00 -3800,337,33,36.0,3,1,1980-08-17 00:00:00 -3801,337,2,77.0,1,4,1980-08-17 00:00:00 -3802,337,26,51.0,2,2,1980-08-17 00:00:00 -3803,337,0,7.0,9,0,1980-08-17 00:00:00 -3804,338,43,0.0,15,0,1980-08-31 00:00:00 -3805,338,2,80.0,1,4,1980-08-31 00:00:00 -3806,338,56,0.0,14,0,1980-08-31 00:00:00 -3807,338,3,38.0,4,3,1980-08-31 00:00:00 -3808,338,31,7.0,9,0,1980-08-31 00:00:00 -3809,338,20,11.0,6,0,1980-08-31 00:00:00 -3810,338,26,55.0,2,2,1980-08-31 00:00:00 -3811,338,55,0.0,13,0,1980-08-31 00:00:00 -3812,338,52,0.0,12,0,1980-08-31 00:00:00 -3813,338,0,8.0,8,0,1980-08-31 00:00:00 -3814,338,49,4.0,11,0,1980-08-31 00:00:00 -3815,338,24,12.0,5,0,1980-08-31 00:00:00 -3816,338,54,9.0,7,0,1980-08-31 00:00:00 -3817,338,33,45.0,3,2,1980-08-31 00:00:00 -3818,338,5,6.0,10,0,1980-08-31 00:00:00 -3819,339,20,11.0,6,0,1980-09-14 00:00:00 -3820,339,43,0.0,14,0,1980-09-14 00:00:00 -3821,339,56,0.0,15,0,1980-09-14 00:00:00 -3822,339,3,38.0,4,3,1980-09-14 00:00:00 -3823,339,31,10.0,8,0,1980-09-14 00:00:00 -3824,339,52,0.0,12,0,1980-09-14 00:00:00 -3825,339,26,56.0,2,2,1980-09-14 00:00:00 -3826,339,24,12.0,5,0,1980-09-14 00:00:00 -3827,339,5,6.0,10,0,1980-09-14 00:00:00 -3828,339,0,8.0,9,0,1980-09-14 00:00:00 -3829,339,49,4.0,11,0,1980-09-14 00:00:00 -3830,339,2,90.0,1,4,1980-09-14 00:00:00 -3831,339,54,11.0,7,0,1980-09-14 00:00:00 -3832,339,33,54.0,3,3,1980-09-14 00:00:00 -3833,339,55,0.0,13,0,1980-09-14 00:00:00 -3834,340,20,11.0,6,0,1980-09-28 00:00:00 -3835,340,43,0.0,14,0,1980-09-28 00:00:00 -3836,340,56,0.0,15,0,1980-09-28 00:00:00 -3837,340,3,38.0,4,3,1980-09-28 00:00:00 -3838,340,31,10.0,9,0,1980-09-28 00:00:00 -3839,340,52,0.0,12,0,1980-09-28 00:00:00 -3840,340,26,60.0,2,2,1980-09-28 00:00:00 -3841,340,24,12.0,5,0,1980-09-28 00:00:00 -3842,340,5,8.0,10,0,1980-09-28 00:00:00 -3843,340,0,11.0,8,0,1980-09-28 00:00:00 -3844,340,49,4.0,11,0,1980-09-28 00:00:00 -3845,340,54,11.0,7,0,1980-09-28 00:00:00 -3846,340,33,55.0,3,3,1980-09-28 00:00:00 -3847,340,2,105.0,1,5,1980-09-28 00:00:00 -3848,340,55,0.0,13,0,1980-09-28 00:00:00 -3849,341,43,0.0,14,0,1980-10-05 00:00:00 -3850,341,56,0.0,15,0,1980-10-05 00:00:00 -3851,341,3,38.0,4,3,1980-10-05 00:00:00 -3852,341,31,14.0,5,0,1980-10-05 00:00:00 -3853,341,52,0.0,12,0,1980-10-05 00:00:00 -3854,341,20,11.0,7,0,1980-10-05 00:00:00 -3855,341,26,66.0,2,2,1980-10-05 00:00:00 -3856,341,55,0.0,13,0,1980-10-05 00:00:00 -3857,341,0,11.0,9,0,1980-10-05 00:00:00 -3858,341,49,4.0,11,0,1980-10-05 00:00:00 -3859,341,24,12.0,6,0,1980-10-05 00:00:00 -3860,341,54,11.0,8,0,1980-10-05 00:00:00 -3861,341,33,55.0,3,3,1980-10-05 00:00:00 -3862,341,2,120.0,1,6,1980-10-05 00:00:00 -3863,341,5,8.0,10,0,1980-10-05 00:00:00 -3864,342,26,0.0,10,0,1981-03-15 00:00:00 -3865,342,36,0.0,16,0,1981-03-15 00:00:00 -3866,342,0,0.0,15,0,1981-03-15 00:00:00 -3867,342,31,0.0,14,0,1981-03-15 00:00:00 -3868,342,43,0.0,13,0,1981-03-15 00:00:00 -3869,342,20,0.0,12,0,1981-03-15 00:00:00 -3870,342,5,0.0,9,0,1981-03-15 00:00:00 -3871,342,52,0.0,11,0,1981-03-15 00:00:00 -3872,342,3,0.0,7,0,1981-03-15 00:00:00 -3873,342,33,4.0,2,0,1981-03-15 00:00:00 -3874,342,2,15.0,1,1,1981-03-15 00:00:00 -3875,342,49,3.0,3,0,1981-03-15 00:00:00 -3876,342,55,0.0,8,0,1981-03-15 00:00:00 -3877,342,53,1.0,5,0,1981-03-15 00:00:00 -3878,342,54,0.0,6,0,1981-03-15 00:00:00 -3879,342,24,2.0,4,0,1981-03-15 00:00:00 -3880,343,36,0.0,16,0,1981-03-29 00:00:00 -3881,343,0,0.0,12,0,1981-03-29 00:00:00 -3882,343,31,2.0,6,0,1981-03-29 00:00:00 -3883,343,43,0.0,15,0,1981-03-29 00:00:00 -3884,343,20,4.0,3,0,1981-03-29 00:00:00 -3885,343,26,1.0,8,0,1981-03-29 00:00:00 -3886,343,5,0.0,13,0,1981-03-29 00:00:00 -3887,343,52,0.0,14,0,1981-03-29 00:00:00 -3888,343,3,0.0,11,0,1981-03-29 00:00:00 -3889,343,54,0.0,10,0,1981-03-29 00:00:00 -3890,343,53,1.0,9,0,1981-03-29 00:00:00 -3891,343,24,2.0,7,0,1981-03-29 00:00:00 -3892,343,49,3.0,5,0,1981-03-29 00:00:00 -3893,343,33,4.0,2,0,1981-03-29 00:00:00 -3894,343,2,30.0,1,2,1981-03-29 00:00:00 -3895,343,55,3.0,4,0,1981-03-29 00:00:00 -3896,344,26,1.0,9,0,1981-04-12 00:00:00 -3897,344,36,0.0,16,0,1981-04-12 00:00:00 -3898,344,0,0.0,12,0,1981-04-12 00:00:00 -3899,344,43,0.0,15,0,1981-04-12 00:00:00 -3900,344,52,0.0,13,0,1981-04-12 00:00:00 -3901,344,5,0.0,14,0,1981-04-12 00:00:00 -3902,344,31,3.0,7,0,1981-04-12 00:00:00 -3903,344,3,6.0,3,0,1981-04-12 00:00:00 -3904,344,55,3.0,6,0,1981-04-12 00:00:00 -3905,344,2,39.0,1,2,1981-04-12 00:00:00 -3906,344,33,13.0,2,1,1981-04-12 00:00:00 -3907,344,49,3.0,5,0,1981-04-12 00:00:00 -3908,344,20,4.0,4,0,1981-04-12 00:00:00 -3909,344,53,1.0,10,0,1981-04-12 00:00:00 -3910,344,24,2.0,8,0,1981-04-12 00:00:00 -3911,344,54,0.0,11,0,1981-04-12 00:00:00 -3912,345,43,0.0,16,0,1981-05-03 00:00:00 -3913,345,51,0.0,17,0,1981-05-03 00:00:00 -3914,345,36,0.0,15,0,1981-05-03 00:00:00 -3915,345,0,1.0,11,0,1981-05-03 00:00:00 -3916,345,31,3.0,7,0,1981-05-03 00:00:00 -3917,345,20,10.0,3,0,1981-05-03 00:00:00 -3918,345,26,1.0,10,0,1981-05-03 00:00:00 -3919,345,52,0.0,14,0,1981-05-03 00:00:00 -3920,345,55,3.0,6,0,1981-05-03 00:00:00 -3921,345,3,6.0,4,0,1981-05-03 00:00:00 -3922,345,54,0.0,13,0,1981-05-03 00:00:00 -3923,345,53,1.0,12,0,1981-05-03 00:00:00 -3924,345,24,2.0,9,0,1981-05-03 00:00:00 -3925,345,49,3.0,5,0,1981-05-03 00:00:00 -3926,345,33,25.0,2,2,1981-05-03 00:00:00 -3927,345,2,43.0,1,2,1981-05-03 00:00:00 -3928,345,5,2.0,8,0,1981-05-03 00:00:00 -3929,346,36,0.0,16,0,1981-05-17 00:00:00 -3930,346,0,1.0,11,0,1981-05-17 00:00:00 -3931,346,31,9.0,4,0,1981-05-17 00:00:00 -3932,346,43,0.0,15,0,1981-05-17 00:00:00 -3933,346,20,10.0,3,0,1981-05-17 00:00:00 -3934,346,55,3.0,9,0,1981-05-17 00:00:00 -3935,346,26,7.0,5,0,1981-05-17 00:00:00 -3936,346,5,5.0,7,0,1981-05-17 00:00:00 -3937,346,3,6.0,6,0,1981-05-17 00:00:00 -3938,346,54,0.0,13,0,1981-05-17 00:00:00 -3939,346,52,0.0,14,0,1981-05-17 00:00:00 -3940,346,51,0.0,17,0,1981-05-17 00:00:00 -3941,346,24,3.0,10,0,1981-05-17 00:00:00 -3942,346,53,1.0,12,0,1981-05-17 00:00:00 -3943,346,2,52.0,1,3,1981-05-17 00:00:00 -3944,346,33,25.0,2,2,1981-05-17 00:00:00 -3945,346,49,3.0,8,0,1981-05-17 00:00:00 -3946,347,26,11.0,4,0,1981-05-31 00:00:00 -3947,347,51,0.0,17,0,1981-05-31 00:00:00 -3948,347,36,0.0,16,0,1981-05-31 00:00:00 -3949,347,0,1.0,11,0,1981-05-31 00:00:00 -3950,347,31,9.0,6,0,1981-05-31 00:00:00 -3951,347,43,0.0,15,0,1981-05-31 00:00:00 -3952,347,20,10.0,5,0,1981-05-31 00:00:00 -3953,347,52,0.0,14,0,1981-05-31 00:00:00 -3954,347,5,17.0,3,1,1981-05-31 00:00:00 -3955,347,3,6.0,7,0,1981-05-31 00:00:00 -3956,347,54,0.0,13,0,1981-05-31 00:00:00 -3957,347,53,1.0,12,0,1981-05-31 00:00:00 -3958,347,24,5.0,8,0,1981-05-31 00:00:00 -3959,347,49,3.0,10,0,1981-05-31 00:00:00 -3960,347,33,25.0,2,2,1981-05-31 00:00:00 -3961,347,2,58.0,1,3,1981-05-31 00:00:00 -3962,347,55,4.0,9,0,1981-05-31 00:00:00 -3963,348,31,12.0,5,0,1981-06-21 00:00:00 -3964,348,0,5.0,8,0,1981-06-21 00:00:00 -3965,348,36,0.0,16,0,1981-06-21 00:00:00 -3966,348,24,5.0,9,0,1981-06-21 00:00:00 -3967,348,51,0.0,17,0,1981-06-21 00:00:00 -3968,348,49,3.0,11,0,1981-06-21 00:00:00 -3969,348,43,0.0,15,0,1981-06-21 00:00:00 -3970,348,53,1.0,12,0,1981-06-21 00:00:00 -3971,348,20,10.0,6,0,1981-06-21 00:00:00 -3972,348,33,25.0,3,2,1981-06-21 00:00:00 -3973,348,26,17.0,4,0,1981-06-21 00:00:00 -3974,348,5,26.0,2,2,1981-06-21 00:00:00 -3975,348,55,4.0,10,0,1981-06-21 00:00:00 -3976,348,3,6.0,7,0,1981-06-21 00:00:00 -3977,348,54,0.0,13,0,1981-06-21 00:00:00 -3978,348,2,61.0,1,3,1981-06-21 00:00:00 -3979,348,52,0.0,14,0,1981-06-21 00:00:00 -3980,349,5,28.0,3,2,1981-07-05 00:00:00 -3981,349,2,61.0,1,3,1981-07-05 00:00:00 -3982,349,33,29.0,2,2,1981-07-05 00:00:00 -3983,349,49,3.0,11,0,1981-07-05 00:00:00 -3984,349,24,5.0,9,0,1981-07-05 00:00:00 -3985,349,53,1.0,12,0,1981-07-05 00:00:00 -3986,349,3,18.0,4,1,1981-07-05 00:00:00 -3987,349,55,4.0,10,0,1981-07-05 00:00:00 -3988,349,26,17.0,5,0,1981-07-05 00:00:00 -3989,349,54,0.0,13,0,1981-07-05 00:00:00 -3990,349,20,10.0,8,0,1981-07-05 00:00:00 -3991,349,43,0.0,15,0,1981-07-05 00:00:00 -3992,349,31,13.0,6,0,1981-07-05 00:00:00 -3993,349,0,11.0,7,0,1981-07-05 00:00:00 -3994,349,36,0.0,16,0,1981-07-05 00:00:00 -3995,349,51,0.0,17,0,1981-07-05 00:00:00 -3996,349,52,0.0,14,0,1981-07-05 00:00:00 -3997,350,51,0.0,17,0,1981-07-18 00:00:00 -3998,350,36,0.0,15,0,1981-07-18 00:00:00 -3999,350,0,20.0,5,1,1981-07-18 00:00:00 -4000,350,31,13.0,7,0,1981-07-18 00:00:00 -4001,350,43,0.0,16,0,1981-07-18 00:00:00 -4002,350,20,10.0,8,0,1981-07-18 00:00:00 -4003,350,52,1.0,13,0,1981-07-18 00:00:00 -4004,350,3,18.0,6,1,1981-07-18 00:00:00 -4005,350,5,28.0,3,2,1981-07-18 00:00:00 -4006,350,55,4.0,10,0,1981-07-18 00:00:00 -4007,350,53,1.0,12,0,1981-07-18 00:00:00 -4008,350,24,8.0,9,0,1981-07-18 00:00:00 -4009,350,49,3.0,11,0,1981-07-18 00:00:00 -4010,350,33,31.0,2,2,1981-07-18 00:00:00 -4011,350,2,67.0,1,3,1981-07-18 00:00:00 -4012,350,26,21.0,4,0,1981-07-18 00:00:00 -4013,350,54,0.0,14,0,1981-07-18 00:00:00 -4014,351,26,25.0,4,0,1981-08-02 00:00:00 -4015,351,33,43.0,2,3,1981-08-02 00:00:00 -4016,351,2,67.0,1,3,1981-08-02 00:00:00 -4017,351,3,24.0,5,1,1981-08-02 00:00:00 -4018,351,54,0.0,14,0,1981-08-02 00:00:00 -4019,351,53,1.0,12,0,1981-08-02 00:00:00 -4020,351,24,10.0,9,0,1981-08-02 00:00:00 -4021,351,31,13.0,7,0,1981-08-02 00:00:00 -4022,351,49,3.0,11,0,1981-08-02 00:00:00 -4023,351,20,10.0,8,0,1981-08-02 00:00:00 -4024,351,5,28.0,3,2,1981-08-02 00:00:00 -4025,351,52,1.0,13,0,1981-08-02 00:00:00 -4026,351,43,0.0,16,0,1981-08-02 00:00:00 -4027,351,0,21.0,6,1,1981-08-02 00:00:00 -4028,351,36,0.0,15,0,1981-08-02 00:00:00 -4029,351,51,0.0,17,0,1981-08-02 00:00:00 -4030,351,55,4.0,10,0,1981-08-02 00:00:00 -4031,352,54,0.0,14,0,1981-08-16 00:00:00 -4032,352,36,0.0,15,0,1981-08-16 00:00:00 -4033,352,53,1.0,12,0,1981-08-16 00:00:00 -4034,352,24,10.0,9,0,1981-08-16 00:00:00 -4035,352,49,3.0,11,0,1981-08-16 00:00:00 -4036,352,51,0.0,17,0,1981-08-16 00:00:00 -4037,352,0,22.0,6,1,1981-08-16 00:00:00 -4038,352,2,72.0,1,3,1981-08-16 00:00:00 -4039,352,43,0.0,16,0,1981-08-16 00:00:00 -4040,352,20,10.0,8,0,1981-08-16 00:00:00 -4041,352,52,1.0,13,0,1981-08-16 00:00:00 -4042,352,26,34.0,3,1,1981-08-16 00:00:00 -4043,352,33,47.0,2,3,1981-08-16 00:00:00 -4044,352,55,4.0,10,0,1981-08-16 00:00:00 -4045,352,5,28.0,5,2,1981-08-16 00:00:00 -4046,352,31,13.0,7,0,1981-08-16 00:00:00 -4047,352,3,30.0,4,1,1981-08-16 00:00:00 -4048,353,5,28.0,5,2,1981-08-30 00:00:00 -4049,353,33,56.0,2,3,1981-08-30 00:00:00 -4050,353,2,76.0,1,3,1981-08-30 00:00:00 -4051,353,51,0.0,17,0,1981-08-30 00:00:00 -4052,353,36,0.0,15,0,1981-08-30 00:00:00 -4053,353,0,22.0,6,1,1981-08-30 00:00:00 -4054,353,43,0.0,16,0,1981-08-30 00:00:00 -4055,353,20,10.0,8,0,1981-08-30 00:00:00 -4056,353,52,1.0,13,0,1981-08-30 00:00:00 -4057,353,31,15.0,7,0,1981-08-30 00:00:00 -4058,353,55,5.0,10,0,1981-08-30 00:00:00 -4059,353,3,39.0,3,2,1981-08-30 00:00:00 -4060,353,54,0.0,14,0,1981-08-30 00:00:00 -4061,353,53,1.0,12,0,1981-08-30 00:00:00 -4062,353,24,10.0,9,0,1981-08-30 00:00:00 -4063,353,49,3.0,11,0,1981-08-30 00:00:00 -4064,353,26,34.0,4,1,1981-08-30 00:00:00 -4065,354,52,1.0,13,0,1981-09-13 00:00:00 -4066,354,51,0.0,17,0,1981-09-13 00:00:00 -4067,354,36,0.0,15,0,1981-09-13 00:00:00 -4068,354,0,22.0,6,1,1981-09-13 00:00:00 -4069,354,43,0.0,16,0,1981-09-13 00:00:00 -4070,354,20,10.0,8,0,1981-09-13 00:00:00 -4071,354,26,34.0,4,1,1981-09-13 00:00:00 -4072,354,31,18.0,7,0,1981-09-13 00:00:00 -4073,354,55,5.0,10,0,1981-09-13 00:00:00 -4074,354,33,57.0,2,3,1981-09-13 00:00:00 -4075,354,49,3.0,11,0,1981-09-13 00:00:00 -4076,354,24,10.0,9,0,1981-09-13 00:00:00 -4077,354,5,30.0,5,2,1981-09-13 00:00:00 -4078,354,53,1.0,12,0,1981-09-13 00:00:00 -4079,354,54,0.0,14,0,1981-09-13 00:00:00 -4080,354,3,48.0,3,3,1981-09-13 00:00:00 -4081,354,2,86.0,1,3,1981-09-13 00:00:00 -4082,355,26,43.0,4,2,1981-09-27 00:00:00 -4083,355,36,0.0,14,0,1981-09-27 00:00:00 -4084,355,0,28.0,6,1,1981-09-27 00:00:00 -4085,355,31,19.0,7,0,1981-09-27 00:00:00 -4086,355,43,0.0,16,0,1981-09-27 00:00:00 -4087,355,20,10.0,8,0,1981-09-27 00:00:00 -4088,355,52,1.0,13,0,1981-09-27 00:00:00 -4089,355,51,0.0,17,0,1981-09-27 00:00:00 -4090,355,5,34.0,5,2,1981-09-27 00:00:00 -4091,355,3,48.0,3,3,1981-09-27 00:00:00 -4092,355,54,0.0,15,0,1981-09-27 00:00:00 -4093,355,53,1.0,12,0,1981-09-27 00:00:00 -4094,355,24,10.0,9,0,1981-09-27 00:00:00 -4095,355,49,6.0,10,0,1981-09-27 00:00:00 -4096,355,33,59.0,2,3,1981-09-27 00:00:00 -4097,355,2,86.0,1,3,1981-09-27 00:00:00 -4098,355,55,5.0,11,0,1981-09-27 00:00:00 -4099,356,52,1.0,13,0,1981-10-17 00:00:00 -4100,356,51,0.0,17,0,1981-10-17 00:00:00 -4101,356,36,0.0,14,0,1981-10-17 00:00:00 -4102,356,0,28.0,6,1,1981-10-17 00:00:00 -4103,356,31,22.0,7,0,1981-10-17 00:00:00 -4104,356,43,0.0,16,0,1981-10-17 00:00:00 -4105,356,20,10.0,8,0,1981-10-17 00:00:00 -4106,356,26,44.0,4,2,1981-10-17 00:00:00 -4107,356,2,95.0,1,4,1981-10-17 00:00:00 -4108,356,55,5.0,11,0,1981-10-17 00:00:00 -4109,356,3,54.0,3,3,1981-10-17 00:00:00 -4110,356,54,0.0,15,0,1981-10-17 00:00:00 -4111,356,53,1.0,12,0,1981-10-17 00:00:00 -4112,356,24,10.0,10,0,1981-10-17 00:00:00 -4113,356,49,10.0,9,0,1981-10-17 00:00:00 -4114,356,33,61.0,2,3,1981-10-17 00:00:00 -4115,356,5,34.0,5,2,1981-10-17 00:00:00 -4116,357,55,0.0,17,0,1982-01-23 00:00:00 -4117,357,20,0.0,16,0,1982-01-23 00:00:00 -4118,357,33,0.0,14,0,1982-01-23 00:00:00 -4119,357,51,0.0,13,0,1982-01-23 00:00:00 -4120,357,26,0.0,12,0,1982-01-23 00:00:00 -4121,357,5,0.0,11,0,1982-01-23 00:00:00 -4122,357,54,0.0,10,0,1982-01-23 00:00:00 -4123,357,43,0.0,15,0,1982-01-23 00:00:00 -4124,357,36,0.0,8,0,1982-01-23 00:00:00 -4125,357,49,0.0,7,0,1982-01-23 00:00:00 -4126,357,52,0.0,6,0,1982-01-23 00:00:00 -4127,357,31,0.0,5,0,1982-01-23 00:00:00 -4128,357,24,0.0,4,0,1982-01-23 00:00:00 -4129,357,0,4.0,3,0,1982-01-23 00:00:00 -4130,357,2,8.0,2,0,1982-01-23 00:00:00 -4131,357,3,13.0,1,1,1982-01-23 00:00:00 -4132,357,53,0.0,9,0,1982-01-23 00:00:00 -4133,358,33,0.0,14,0,1982-03-21 00:00:00 -4134,358,51,0.0,16,0,1982-03-21 00:00:00 -4135,358,26,0.0,15,0,1982-03-21 00:00:00 -4136,358,5,1.0,7,0,1982-03-21 00:00:00 -4137,358,54,0.0,13,0,1982-03-21 00:00:00 -4138,358,53,0.0,12,0,1982-03-21 00:00:00 -4139,358,36,0.0,8,0,1982-03-21 00:00:00 -4140,358,24,3.0,5,0,1982-03-21 00:00:00 -4141,358,52,2.0,6,0,1982-03-21 00:00:00 -4142,358,31,4.0,4,0,1982-03-21 00:00:00 -4143,358,0,10.0,2,0,1982-03-21 00:00:00 -4144,358,2,8.0,3,0,1982-03-21 00:00:00 -4145,358,3,22.0,1,2,1982-03-21 00:00:00 -4146,358,20,0.0,10,0,1982-03-21 00:00:00 -4147,358,49,0.0,11,0,1982-03-21 00:00:00 -4148,358,55,0.0,17,0,1982-03-21 00:00:00 -4149,358,43,0.0,9,0,1982-03-21 00:00:00 -4150,359,54,0.0,14,0,1982-04-04 00:00:00 -4151,359,20,0.0,11,0,1982-04-04 00:00:00 -4152,359,43,0.0,10,0,1982-04-04 00:00:00 -4153,359,33,4.0,6,0,1982-04-04 00:00:00 -4154,359,51,0.0,17,0,1982-04-04 00:00:00 -4155,359,26,0.0,15,0,1982-04-04 00:00:00 -4156,359,5,1.0,8,0,1982-04-04 00:00:00 -4157,359,53,0.0,13,0,1982-04-04 00:00:00 -4158,359,55,0.0,16,0,1982-04-04 00:00:00 -4159,359,49,0.0,12,0,1982-04-04 00:00:00 -4160,359,52,2.0,7,0,1982-04-04 00:00:00 -4161,359,31,6.0,4,0,1982-04-04 00:00:00 -4162,359,24,6.0,5,0,1982-04-04 00:00:00 -4163,359,0,20.0,2,1,1982-04-04 00:00:00 -4164,359,2,14.0,3,0,1982-04-04 00:00:00 -4165,359,3,22.0,1,2,1982-04-04 00:00:00 -4166,359,36,0.0,9,0,1982-04-04 00:00:00 -4167,360,20,0.0,11,0,1982-04-25 00:00:00 -4168,360,43,3.0,9,0,1982-04-25 00:00:00 -4169,360,33,4.0,7,0,1982-04-25 00:00:00 -4170,360,51,0.0,15,0,1982-04-25 00:00:00 -4171,360,26,0.0,16,0,1982-04-25 00:00:00 -4172,360,5,16.0,3,1,1982-04-25 00:00:00 -4173,360,54,0.0,14,0,1982-04-25 00:00:00 -4174,360,52,4.0,8,0,1982-04-25 00:00:00 -4175,360,36,0.0,10,0,1982-04-25 00:00:00 -4176,360,49,0.0,12,0,1982-04-25 00:00:00 -4177,360,31,6.0,6,0,1982-04-25 00:00:00 -4178,360,24,10.0,5,0,1982-04-25 00:00:00 -4179,360,0,20.0,2,1,1982-04-25 00:00:00 -4180,360,55,0.0,17,0,1982-04-25 00:00:00 -4181,360,53,0.0,13,0,1982-04-25 00:00:00 -4182,360,2,14.0,4,0,1982-04-25 00:00:00 -4183,360,3,22.0,1,2,1982-04-25 00:00:00 -4184,361,26,4.0,8,0,1982-05-09 00:00:00 -4185,361,55,0.0,17,0,1982-05-09 00:00:00 -4186,361,20,0.0,12,0,1982-05-09 00:00:00 -4187,361,43,3.0,10,0,1982-05-09 00:00:00 -4188,361,33,6.0,7,0,1982-05-09 00:00:00 -4189,361,51,0.0,16,0,1982-05-09 00:00:00 -4190,361,5,16.0,4,1,1982-05-09 00:00:00 -4191,361,54,1.0,11,0,1982-05-09 00:00:00 -4192,361,53,0.0,15,0,1982-05-09 00:00:00 -4193,361,49,0.0,14,0,1982-05-09 00:00:00 -4194,361,52,4.0,9,0,1982-05-09 00:00:00 -4195,361,31,9.0,6,0,1982-05-09 00:00:00 -4196,361,24,10.0,5,0,1982-05-09 00:00:00 -4197,361,0,29.0,1,2,1982-05-09 00:00:00 -4198,361,2,20.0,3,0,1982-05-09 00:00:00 -4199,361,3,22.0,2,2,1982-05-09 00:00:00 -4200,361,36,0.0,13,0,1982-05-09 00:00:00 -4201,362,51,0.0,16,0,1982-05-23 00:00:00 -4202,362,26,4.0,8,0,1982-05-23 00:00:00 -4203,362,33,15.0,5,1,1982-05-23 00:00:00 -4204,362,20,0.0,13,0,1982-05-23 00:00:00 -4205,362,55,0.0,17,0,1982-05-23 00:00:00 -4206,362,54,1.0,12,0,1982-05-23 00:00:00 -4207,362,43,3.0,11,0,1982-05-23 00:00:00 -4208,362,53,0.0,15,0,1982-05-23 00:00:00 -4209,362,5,22.0,3,1,1982-05-23 00:00:00 -4210,362,49,4.0,9,0,1982-05-23 00:00:00 -4211,362,36,0.0,14,0,1982-05-23 00:00:00 -4212,362,2,21.0,4,0,1982-05-23 00:00:00 -4213,362,0,29.0,1,2,1982-05-23 00:00:00 -4214,362,3,22.0,2,2,1982-05-23 00:00:00 -4215,362,31,14.0,6,0,1982-05-23 00:00:00 -4216,362,52,4.0,10,0,1982-05-23 00:00:00 -4217,362,24,10.0,7,0,1982-05-23 00:00:00 -4218,363,55,0.0,17,0,1982-06-06 00:00:00 -4219,363,20,0.0,14,0,1982-06-06 00:00:00 -4220,363,43,3.0,11,0,1982-06-06 00:00:00 -4221,363,33,15.0,5,1,1982-06-06 00:00:00 -4222,363,51,0.0,16,0,1982-06-06 00:00:00 -4223,363,26,11.0,7,0,1982-06-06 00:00:00 -4224,363,5,26.0,2,1,1982-06-06 00:00:00 -4225,363,54,1.0,12,0,1982-06-06 00:00:00 -4226,363,53,0.0,15,0,1982-06-06 00:00:00 -4227,363,49,4.0,9,0,1982-06-06 00:00:00 -4228,363,52,4.0,10,0,1982-06-06 00:00:00 -4229,363,31,14.0,6,0,1982-06-06 00:00:00 -4230,363,24,10.0,8,0,1982-06-06 00:00:00 -4231,363,0,38.0,1,3,1982-06-06 00:00:00 -4232,363,2,26.0,3,0,1982-06-06 00:00:00 -4233,363,3,22.0,4,2,1982-06-06 00:00:00 -4234,363,36,0.0,13,0,1982-06-06 00:00:00 -4235,364,43,3.0,11,0,1982-06-13 00:00:00 -4236,364,54,1.0,13,0,1982-06-13 00:00:00 -4237,364,33,30.0,2,2,1982-06-13 00:00:00 -4238,364,51,0.0,16,0,1982-06-13 00:00:00 -4239,364,26,11.0,7,0,1982-06-13 00:00:00 -4240,364,5,26.0,3,1,1982-06-13 00:00:00 -4241,364,36,0.0,14,0,1982-06-13 00:00:00 -4242,364,53,0.0,15,0,1982-06-13 00:00:00 -4243,364,52,4.0,10,0,1982-06-13 00:00:00 -4244,364,31,17.0,6,0,1982-06-13 00:00:00 -4245,364,24,10.0,8,0,1982-06-13 00:00:00 -4246,364,0,42.0,1,3,1982-06-13 00:00:00 -4247,364,2,26.0,4,0,1982-06-13 00:00:00 -4248,364,3,22.0,5,2,1982-06-13 00:00:00 -4249,364,20,2.0,12,0,1982-06-13 00:00:00 -4250,364,49,5.0,9,0,1982-06-13 00:00:00 -4251,364,55,0.0,17,0,1982-06-13 00:00:00 -4252,365,53,0.0,15,0,1982-07-03 00:00:00 -4253,365,2,32.0,4,0,1982-07-03 00:00:00 -4254,365,55,0.0,17,0,1982-07-03 00:00:00 -4255,365,20,3.0,12,0,1982-07-03 00:00:00 -4256,365,43,3.0,11,0,1982-07-03 00:00:00 -4257,365,33,36.0,2,2,1982-07-03 00:00:00 -4258,365,51,0.0,16,0,1982-07-03 00:00:00 -4259,365,26,11.0,7,0,1982-07-03 00:00:00 -4260,365,5,35.0,3,2,1982-07-03 00:00:00 -4261,365,54,1.0,13,0,1982-07-03 00:00:00 -4262,365,3,22.0,5,2,1982-07-03 00:00:00 -4263,365,36,0.0,14,0,1982-07-03 00:00:00 -4264,365,49,5.0,9,0,1982-07-03 00:00:00 -4265,365,52,4.0,10,0,1982-07-03 00:00:00 -4266,365,31,17.0,6,0,1982-07-03 00:00:00 -4267,365,24,10.0,8,0,1982-07-03 00:00:00 -4268,365,0,45.0,1,3,1982-07-03 00:00:00 -4269,366,53,0.0,15,0,1982-07-18 00:00:00 -4270,366,55,0.0,17,0,1982-07-18 00:00:00 -4271,366,20,3.0,12,0,1982-07-18 00:00:00 -4272,366,43,3.0,11,0,1982-07-18 00:00:00 -4273,366,33,36.0,3,2,1982-07-18 00:00:00 -4274,366,51,0.0,16,0,1982-07-18 00:00:00 -4275,366,26,11.0,7,0,1982-07-18 00:00:00 -4276,366,5,45.0,2,2,1982-07-18 00:00:00 -4277,366,54,1.0,13,0,1982-07-18 00:00:00 -4278,366,24,10.0,8,0,1982-07-18 00:00:00 -4279,366,36,0.0,14,0,1982-07-18 00:00:00 -4280,366,49,5.0,9,0,1982-07-18 00:00:00 -4281,366,52,4.0,10,0,1982-07-18 00:00:00 -4282,366,31,20.0,6,0,1982-07-18 00:00:00 -4283,366,0,54.0,1,4,1982-07-18 00:00:00 -4284,366,2,34.0,4,0,1982-07-18 00:00:00 -4285,366,3,23.0,5,2,1982-07-18 00:00:00 -4286,367,53,0.0,15,0,1982-07-25 00:00:00 -4287,367,43,3.0,11,0,1982-07-25 00:00:00 -4288,367,33,36.0,4,2,1982-07-25 00:00:00 -4289,367,51,0.0,16,0,1982-07-25 00:00:00 -4290,367,26,11.0,7,0,1982-07-25 00:00:00 -4291,367,5,52.0,2,2,1982-07-25 00:00:00 -4292,367,54,1.0,13,0,1982-07-25 00:00:00 -4293,367,20,3.0,12,0,1982-07-25 00:00:00 -4294,367,55,0.0,17,0,1982-07-25 00:00:00 -4295,367,36,0.0,14,0,1982-07-25 00:00:00 -4296,367,52,4.0,10,0,1982-07-25 00:00:00 -4297,367,31,20.0,6,0,1982-07-25 00:00:00 -4298,367,24,11.0,8,0,1982-07-25 00:00:00 -4299,367,0,54.0,1,4,1982-07-25 00:00:00 -4300,367,2,36.0,5,0,1982-07-25 00:00:00 -4301,367,3,38.0,3,3,1982-07-25 00:00:00 -4302,367,49,5.0,9,0,1982-07-25 00:00:00 -4303,368,20,4.0,11,0,1982-08-08 00:00:00 -4304,368,43,3.0,12,0,1982-08-08 00:00:00 -4305,368,33,36.0,5,2,1982-08-08 00:00:00 -4306,368,26,11.0,8,0,1982-08-08 00:00:00 -4307,368,5,61.0,1,3,1982-08-08 00:00:00 -4308,368,54,1.0,13,0,1982-08-08 00:00:00 -4309,368,53,0.0,17,0,1982-08-08 00:00:00 -4310,368,36,0.0,14,0,1982-08-08 00:00:00 -4311,368,51,0.0,16,0,1982-08-08 00:00:00 -4312,368,52,4.0,10,0,1982-08-08 00:00:00 -4313,368,49,7.0,9,0,1982-08-08 00:00:00 -4314,368,3,44.0,3,3,1982-08-08 00:00:00 -4315,368,2,40.0,4,0,1982-08-08 00:00:00 -4316,368,55,0.0,15,0,1982-08-08 00:00:00 -4317,368,24,14.0,7,0,1982-08-08 00:00:00 -4318,368,31,20.0,6,0,1982-08-08 00:00:00 -4319,368,0,54.0,2,4,1982-08-08 00:00:00 -4320,369,55,0.0,15,0,1982-08-15 00:00:00 -4321,369,20,5.0,10,0,1982-08-15 00:00:00 -4322,369,43,3.0,12,0,1982-08-15 00:00:00 -4323,369,33,36.0,5,2,1982-08-15 00:00:00 -4324,369,51,0.0,16,0,1982-08-15 00:00:00 -4325,369,26,15.0,7,0,1982-08-15 00:00:00 -4326,369,5,64.0,1,3,1982-08-15 00:00:00 -4327,369,53,0.0,17,0,1982-08-15 00:00:00 -4328,369,36,0.0,14,0,1982-08-15 00:00:00 -4329,369,52,4.0,11,0,1982-08-15 00:00:00 -4330,369,31,29.0,6,1,1982-08-15 00:00:00 -4331,369,24,14.0,8,0,1982-08-15 00:00:00 -4332,369,0,56.0,2,4,1982-08-15 00:00:00 -4333,369,2,46.0,3,0,1982-08-15 00:00:00 -4334,369,3,44.0,4,3,1982-08-15 00:00:00 -4335,369,54,1.0,13,0,1982-08-15 00:00:00 -4336,369,49,7.0,9,0,1982-08-15 00:00:00 -4337,370,55,0.0,15,0,1982-08-29 00:00:00 -4338,370,2,55.0,3,1,1982-08-29 00:00:00 -4339,370,20,5.0,10,0,1982-08-29 00:00:00 -4340,370,43,3.0,12,0,1982-08-29 00:00:00 -4341,370,33,41.0,5,2,1982-08-29 00:00:00 -4342,370,51,0.0,16,0,1982-08-29 00:00:00 -4343,370,5,64.0,1,3,1982-08-29 00:00:00 -4344,370,54,1.0,13,0,1982-08-29 00:00:00 -4345,370,53,0.0,17,0,1982-08-29 00:00:00 -4346,370,26,15.0,7,0,1982-08-29 00:00:00 -4347,370,3,50.0,4,3,1982-08-29 00:00:00 -4348,370,49,7.0,9,0,1982-08-29 00:00:00 -4349,370,52,4.0,11,0,1982-08-29 00:00:00 -4350,370,31,30.0,6,1,1982-08-29 00:00:00 -4351,370,24,14.0,8,0,1982-08-29 00:00:00 -4352,370,0,60.0,2,4,1982-08-29 00:00:00 -4353,370,36,0.0,14,0,1982-08-29 00:00:00 -4354,371,54,1.0,13,0,1982-09-12 00:00:00 -4355,371,55,0.0,15,0,1982-09-12 00:00:00 -4356,371,20,5.0,10,0,1982-09-12 00:00:00 -4357,371,43,3.0,12,0,1982-09-12 00:00:00 -4358,371,33,41.0,5,2,1982-09-12 00:00:00 -4359,371,26,16.0,7,0,1982-09-12 00:00:00 -4360,371,5,74.0,1,3,1982-09-12 00:00:00 -4361,371,53,0.0,17,0,1982-09-12 00:00:00 -4362,371,51,0.0,16,0,1982-09-12 00:00:00 -4363,371,49,7.0,9,0,1982-09-12 00:00:00 -4364,371,52,4.0,11,0,1982-09-12 00:00:00 -4365,371,31,30.0,6,1,1982-09-12 00:00:00 -4366,371,24,16.0,8,0,1982-09-12 00:00:00 -4367,371,3,59.0,3,4,1982-09-12 00:00:00 -4368,371,0,63.0,2,4,1982-09-12 00:00:00 -4369,371,2,55.0,4,1,1982-09-12 00:00:00 -4370,371,36,0.0,14,0,1982-09-12 00:00:00 -4371,372,0,69.0,2,4,1982-09-25 00:00:00 -4372,372,2,58.0,4,1,1982-09-25 00:00:00 -4373,372,3,62.0,3,4,1982-09-25 00:00:00 -4374,372,24,25.0,7,1,1982-09-25 00:00:00 -4375,372,31,30.0,6,1,1982-09-25 00:00:00 -4376,372,49,7.0,9,0,1982-09-25 00:00:00 -4377,372,52,4.0,11,0,1982-09-25 00:00:00 -4378,372,53,0.0,17,0,1982-09-25 00:00:00 -4379,372,54,1.0,13,0,1982-09-25 00:00:00 -4380,372,26,20.0,8,0,1982-09-25 00:00:00 -4381,372,51,0.0,16,0,1982-09-25 00:00:00 -4382,372,33,41.0,5,2,1982-09-25 00:00:00 -4383,372,43,3.0,12,0,1982-09-25 00:00:00 -4384,372,20,5.0,10,0,1982-09-25 00:00:00 -4385,372,5,74.0,1,3,1982-09-25 00:00:00 -4386,372,55,0.0,15,0,1982-09-25 00:00:00 -4387,372,36,0.0,14,0,1982-09-25 00:00:00 -4388,373,53,0.0,10,0,1983-03-13 00:00:00 -4389,373,43,0.0,15,0,1983-03-13 00:00:00 -4390,373,49,0.0,14,0,1983-03-13 00:00:00 -4391,373,26,0.0,13,0,1983-03-13 00:00:00 -4392,373,52,0.0,12,0,1983-03-13 00:00:00 -4393,373,48,0.0,11,0,1983-03-13 00:00:00 -4394,373,31,0.0,9,0,1983-03-13 00:00:00 -4395,373,33,9.0,1,1,1983-03-13 00:00:00 -4396,373,51,0.0,7,0,1983-03-13 00:00:00 -4397,373,3,0.0,6,0,1983-03-13 00:00:00 -4398,373,20,1.0,5,0,1983-03-13 00:00:00 -4399,373,5,2.0,4,0,1983-03-13 00:00:00 -4400,373,2,3.0,3,0,1983-03-13 00:00:00 -4401,373,0,4.0,2,0,1983-03-13 00:00:00 -4402,373,24,0.0,8,0,1983-03-13 00:00:00 -4403,374,49,0.0,14,0,1983-03-27 00:00:00 -4404,374,26,0.0,8,0,1983-03-27 00:00:00 -4405,374,52,0.0,13,0,1983-03-27 00:00:00 -4406,374,48,0.0,12,0,1983-03-27 00:00:00 -4407,374,53,1.0,6,0,1983-03-27 00:00:00 -4408,374,31,0.0,11,0,1983-03-27 00:00:00 -4409,374,24,0.0,9,0,1983-03-27 00:00:00 -4410,374,43,0.0,15,0,1983-03-27 00:00:00 -4411,374,3,0.0,7,0,1983-03-27 00:00:00 -4412,374,20,3.0,5,0,1983-03-27 00:00:00 -4413,374,5,6.0,3,0,1983-03-27 00:00:00 -4414,374,2,6.0,4,0,1983-03-27 00:00:00 -4415,374,0,19.0,1,1,1983-03-27 00:00:00 -4416,374,33,9.0,2,1,1983-03-27 00:00:00 -4417,374,51,0.0,10,0,1983-03-27 00:00:00 -4418,375,43,0.0,15,0,1983-04-17 00:00:00 -4419,375,49,0.0,12,0,1983-04-17 00:00:00 -4420,375,26,0.0,8,0,1983-04-17 00:00:00 -4421,375,52,0.0,14,0,1983-04-17 00:00:00 -4422,375,48,0.0,13,0,1983-04-17 00:00:00 -4423,375,53,1.0,7,0,1983-04-17 00:00:00 -4424,375,31,0.0,11,0,1983-04-17 00:00:00 -4425,375,24,0.0,9,0,1983-04-17 00:00:00 -4426,375,3,13.0,3,1,1983-04-17 00:00:00 -4427,375,20,3.0,6,0,1983-04-17 00:00:00 -4428,375,5,9.0,4,0,1983-04-17 00:00:00 -4429,375,2,9.0,5,0,1983-04-17 00:00:00 -4430,375,0,19.0,1,1,1983-04-17 00:00:00 -4431,375,33,15.0,2,1,1983-04-17 00:00:00 -4432,375,51,0.0,10,0,1983-04-17 00:00:00 -4433,376,43,0.0,15,0,1983-05-01 00:00:00 -4434,376,49,0.0,11,0,1983-05-01 00:00:00 -4435,376,26,0.0,8,0,1983-05-01 00:00:00 -4436,376,52,0.0,12,0,1983-05-01 00:00:00 -4437,376,48,0.0,14,0,1983-05-01 00:00:00 -4438,376,53,1.0,7,0,1983-05-01 00:00:00 -4439,376,31,0.0,13,0,1983-05-01 00:00:00 -4440,376,3,19.0,3,1,1983-05-01 00:00:00 -4441,376,51,0.0,10,0,1983-05-01 00:00:00 -4442,376,33,15.0,4,1,1983-05-01 00:00:00 -4443,376,0,21.0,2,1,1983-05-01 00:00:00 -4444,376,24,0.0,9,0,1983-05-01 00:00:00 -4445,376,5,22.0,1,1,1983-05-01 00:00:00 -4446,376,20,4.0,6,0,1983-05-01 00:00:00 -4447,376,2,12.0,5,0,1983-05-01 00:00:00 -4448,377,43,0.0,15,0,1983-05-15 00:00:00 -4449,377,49,1.0,8,0,1983-05-15 00:00:00 -4450,377,26,0.0,10,0,1983-05-15 00:00:00 -4451,377,52,0.0,12,0,1983-05-15 00:00:00 -4452,377,48,0.0,14,0,1983-05-15 00:00:00 -4453,377,31,0.0,13,0,1983-05-15 00:00:00 -4454,377,53,1.0,9,0,1983-05-15 00:00:00 -4455,377,3,23.0,2,1,1983-05-15 00:00:00 -4456,377,20,4.0,6,0,1983-05-15 00:00:00 -4457,377,5,25.0,1,1,1983-05-15 00:00:00 -4458,377,2,21.0,5,1,1983-05-15 00:00:00 -4459,377,0,21.0,4,1,1983-05-15 00:00:00 -4460,377,33,21.0,3,1,1983-05-15 00:00:00 -4461,377,51,0.0,11,0,1983-05-15 00:00:00 -4462,377,24,2.0,7,0,1983-05-15 00:00:00 -4463,378,43,0.0,15,0,1983-05-22 00:00:00 -4464,378,24,2.0,7,0,1983-05-22 00:00:00 -4465,378,31,0.0,12,0,1983-05-22 00:00:00 -4466,378,53,1.0,8,0,1983-05-22 00:00:00 -4467,378,48,0.0,14,0,1983-05-22 00:00:00 -4468,378,52,0.0,13,0,1983-05-22 00:00:00 -4469,378,26,0.0,11,0,1983-05-22 00:00:00 -4470,378,49,1.0,9,0,1983-05-22 00:00:00 -4471,378,3,36.0,1,2,1983-05-22 00:00:00 -4472,378,51,0.0,10,0,1983-05-22 00:00:00 -4473,378,33,24.0,3,1,1983-05-22 00:00:00 -4474,378,0,21.0,5,1,1983-05-22 00:00:00 -4475,378,2,24.0,4,1,1983-05-22 00:00:00 -4476,378,5,31.0,2,1,1983-05-22 00:00:00 -4477,378,20,4.0,6,0,1983-05-22 00:00:00 -4478,379,48,0.0,14,0,1983-06-05 00:00:00 -4479,379,43,0.0,15,0,1983-06-05 00:00:00 -4480,379,49,1.0,10,0,1983-06-05 00:00:00 -4481,379,26,0.0,12,0,1983-06-05 00:00:00 -4482,379,52,0.0,13,0,1983-06-05 00:00:00 -4483,379,53,1.0,9,0,1983-06-05 00:00:00 -4484,379,31,1.0,8,0,1983-06-05 00:00:00 -4485,379,24,11.0,6,1,1983-06-05 00:00:00 -4486,379,51,0.0,11,0,1983-06-05 00:00:00 -4487,379,3,36.0,1,2,1983-06-05 00:00:00 -4488,379,20,4.0,7,0,1983-06-05 00:00:00 -4489,379,5,31.0,3,1,1983-06-05 00:00:00 -4490,379,2,32.0,2,1,1983-06-05 00:00:00 -4491,379,0,25.0,5,1,1983-06-05 00:00:00 -4492,379,33,27.0,4,1,1983-06-05 00:00:00 -4493,380,51,0.0,11,0,1983-06-12 00:00:00 -4494,380,48,0.0,14,0,1983-06-12 00:00:00 -4495,380,52,0.0,13,0,1983-06-12 00:00:00 -4496,380,26,0.0,12,0,1983-06-12 00:00:00 -4497,380,49,1.0,9,0,1983-06-12 00:00:00 -4498,380,43,0.0,15,0,1983-06-12 00:00:00 -4499,380,53,1.0,10,0,1983-06-12 00:00:00 -4500,380,20,4.0,7,0,1983-06-12 00:00:00 -4501,380,5,44.0,2,2,1983-06-12 00:00:00 -4502,380,2,35.0,3,1,1983-06-12 00:00:00 -4503,380,0,26.0,5,1,1983-06-12 00:00:00 -4504,380,33,27.0,4,1,1983-06-12 00:00:00 -4505,380,31,1.0,8,0,1983-06-12 00:00:00 -4506,380,3,44.0,1,2,1983-06-12 00:00:00 -4507,380,24,11.0,6,1,1983-06-12 00:00:00 -4508,381,53,1.0,10,0,1983-07-16 00:00:00 -4509,381,33,33.0,4,1,1983-07-16 00:00:00 -4510,381,43,0.0,15,0,1983-07-16 00:00:00 -4511,381,49,1.0,9,0,1983-07-16 00:00:00 -4512,381,26,0.0,12,0,1983-07-16 00:00:00 -4513,381,52,0.0,13,0,1983-07-16 00:00:00 -4514,381,48,0.0,14,0,1983-07-16 00:00:00 -4515,381,31,4.0,7,0,1983-07-16 00:00:00 -4516,381,50,0.0,16,0,1983-07-16 00:00:00 -4517,381,51,0.0,11,0,1983-07-16 00:00:00 -4518,381,3,53.0,1,3,1983-07-16 00:00:00 -4519,381,20,4.0,8,0,1983-07-16 00:00:00 -4520,381,5,50.0,2,2,1983-07-16 00:00:00 -4521,381,2,35.0,3,1,1983-07-16 00:00:00 -4522,381,0,27.0,5,1,1983-07-16 00:00:00 -4523,381,24,11.0,6,1,1983-07-16 00:00:00 -4524,382,48,0.0,14,0,1983-08-07 00:00:00 -4525,382,53,1.0,10,0,1983-08-07 00:00:00 -4526,382,31,4.0,8,0,1983-08-07 00:00:00 -4527,382,24,11.0,6,1,1983-08-07 00:00:00 -4528,382,51,0.0,11,0,1983-08-07 00:00:00 -4529,382,3,56.0,2,3,1983-08-07 00:00:00 -4530,382,50,0.0,16,0,1983-08-07 00:00:00 -4531,382,5,59.0,1,3,1983-08-07 00:00:00 -4532,382,20,4.0,9,0,1983-08-07 00:00:00 -4533,382,2,36.0,4,1,1983-08-07 00:00:00 -4534,382,0,29.0,5,1,1983-08-07 00:00:00 -4535,382,33,37.0,3,1,1983-08-07 00:00:00 -4536,382,26,0.0,12,0,1983-08-07 00:00:00 -4537,382,49,7.0,7,0,1983-08-07 00:00:00 -4538,382,43,0.0,15,0,1983-08-07 00:00:00 -4539,382,52,0.0,13,0,1983-08-07 00:00:00 -4540,383,0,30.0,5,1,1983-08-14 00:00:00 -4541,383,26,0.0,11,0,1983-08-14 00:00:00 -4542,383,50,0.0,15,0,1983-08-14 00:00:00 -4543,383,43,0.0,14,0,1983-08-14 00:00:00 -4544,383,49,7.0,7,0,1983-08-14 00:00:00 -4545,383,52,0.0,13,0,1983-08-14 00:00:00 -4546,383,48,0.0,16,0,1983-08-14 00:00:00 -4547,383,31,6.0,8,0,1983-08-14 00:00:00 -4548,383,53,1.0,10,0,1983-08-14 00:00:00 -4549,383,51,0.0,12,0,1983-08-14 00:00:00 -4550,383,3,68.0,1,4,1983-08-14 00:00:00 -4551,383,20,4.0,9,0,1983-08-14 00:00:00 -4552,383,5,65.0,2,3,1983-08-14 00:00:00 -4553,383,2,36.0,4,1,1983-08-14 00:00:00 -4554,383,24,11.0,6,1,1983-08-14 00:00:00 -4555,383,33,41.0,3,1,1983-08-14 00:00:00 -4556,384,52,0.0,14,0,1983-08-28 00:00:00 -4557,384,48,0.0,16,0,1983-08-28 00:00:00 -4558,384,26,0.0,12,0,1983-08-28 00:00:00 -4559,384,43,0.0,15,0,1983-08-28 00:00:00 -4560,384,50,0.0,13,0,1983-08-28 00:00:00 -4561,384,53,1.0,11,0,1983-08-28 00:00:00 -4562,384,49,9.0,7,0,1983-08-28 00:00:00 -4563,384,31,6.0,8,0,1983-08-28 00:00:00 -4564,384,5,80.0,1,4,1983-08-28 00:00:00 -4565,384,51,3.0,10,0,1983-08-28 00:00:00 -4566,384,3,68.0,2,4,1983-08-28 00:00:00 -4567,384,20,4.0,9,0,1983-08-28 00:00:00 -4568,384,2,36.0,4,1,1983-08-28 00:00:00 -4569,384,0,34.0,5,1,1983-08-28 00:00:00 -4570,384,33,41.0,3,1,1983-08-28 00:00:00 -4571,384,24,12.0,6,1,1983-08-28 00:00:00 -4572,385,53,1.0,11,0,1983-09-11 00:00:00 -4573,385,50,0.0,13,0,1983-09-11 00:00:00 -4574,385,43,0.0,15,0,1983-09-11 00:00:00 -4575,385,49,9.0,7,0,1983-09-11 00:00:00 -4576,385,26,0.0,12,0,1983-09-11 00:00:00 -4577,385,48,0.0,16,0,1983-09-11 00:00:00 -4578,385,31,8.0,8,0,1983-09-11 00:00:00 -4579,385,52,0.0,14,0,1983-09-11 00:00:00 -4580,385,51,4.0,9,0,1983-09-11 00:00:00 -4581,385,3,72.0,2,4,1983-09-11 00:00:00 -4582,385,20,4.0,10,0,1983-09-11 00:00:00 -4583,385,5,89.0,1,4,1983-09-11 00:00:00 -4584,385,2,36.0,4,1,1983-09-11 00:00:00 -4585,385,0,34.0,5,1,1983-09-11 00:00:00 -4586,385,33,50.0,3,2,1983-09-11 00:00:00 -4587,385,24,12.0,6,1,1983-09-11 00:00:00 -4588,386,2,36.0,4,1,1983-09-25 00:00:00 -4589,386,33,59.0,3,3,1983-09-25 00:00:00 -4590,386,3,78.0,2,4,1983-09-25 00:00:00 -4591,386,20,4.0,10,0,1983-09-25 00:00:00 -4592,386,48,0.0,16,0,1983-09-25 00:00:00 -4593,386,49,12.0,7,0,1983-09-25 00:00:00 -4594,386,0,34.0,5,1,1983-09-25 00:00:00 -4595,386,51,7.0,9,0,1983-09-25 00:00:00 -4596,386,5,89.0,1,4,1983-09-25 00:00:00 -4597,386,31,12.0,8,0,1983-09-25 00:00:00 -4598,386,53,1.0,11,0,1983-09-25 00:00:00 -4599,386,52,0.0,14,0,1983-09-25 00:00:00 -4600,386,26,0.0,12,0,1983-09-25 00:00:00 -4601,386,43,0.0,15,0,1983-09-25 00:00:00 -4602,386,50,0.0,13,0,1983-09-25 00:00:00 -4603,386,24,12.0,6,1,1983-09-25 00:00:00 -4604,387,50,0.0,13,0,1983-10-15 00:00:00 -4605,387,43,0.0,15,0,1983-10-15 00:00:00 -4606,387,49,18.0,6,0,1983-10-15 00:00:00 -4607,387,26,0.0,12,0,1983-10-15 00:00:00 -4608,387,52,0.0,14,0,1983-10-15 00:00:00 -4609,387,48,0.0,16,0,1983-10-15 00:00:00 -4610,387,53,1.0,11,0,1983-10-15 00:00:00 -4611,387,31,12.0,8,0,1983-10-15 00:00:00 -4612,387,24,12.0,7,1,1983-10-15 00:00:00 -4613,387,3,79.0,2,4,1983-10-15 00:00:00 -4614,387,20,4.0,10,0,1983-10-15 00:00:00 -4615,387,5,89.0,1,4,1983-10-15 00:00:00 -4616,387,2,38.0,4,1,1983-10-15 00:00:00 -4617,387,0,34.0,5,1,1983-10-15 00:00:00 -4618,387,33,72.0,3,4,1983-10-15 00:00:00 -4619,387,51,10.0,9,0,1983-10-15 00:00:00 -4620,388,33,0.0,9,0,1984-03-25 00:00:00 -4621,388,50,0.0,13,0,1984-03-25 00:00:00 -4622,388,51,0.0,12,0,1984-03-25 00:00:00 -4623,388,43,0.0,11,0,1984-03-25 00:00:00 -4624,388,5,0.0,10,0,1984-03-25 00:00:00 -4625,388,26,0.0,8,0,1984-03-25 00:00:00 -4626,388,49,3.0,4,0,1984-03-25 00:00:00 -4627,388,20,1.0,6,0,1984-03-25 00:00:00 -4628,388,3,2.0,5,0,1984-03-25 00:00:00 -4629,388,0,9.0,1,1,1984-03-25 00:00:00 -4630,388,31,4.0,3,0,1984-03-25 00:00:00 -4631,388,2,6.0,2,0,1984-03-25 00:00:00 -4632,388,48,0.0,7,0,1984-03-25 00:00:00 -4633,389,52,0.0,14,0,1984-04-07 00:00:00 -4634,389,24,0.0,12,0,1984-04-07 00:00:00 -4635,389,50,0.0,10,0,1984-04-07 00:00:00 -4636,389,51,1.0,8,0,1984-04-07 00:00:00 -4637,389,43,0.0,15,0,1984-04-07 00:00:00 -4638,389,5,0.0,11,0,1984-04-07 00:00:00 -4639,389,33,0.0,13,0,1984-04-07 00:00:00 -4640,389,48,0.0,9,0,1984-04-07 00:00:00 -4641,389,20,1.0,7,0,1984-04-07 00:00:00 -4642,389,3,6.0,3,0,1984-04-07 00:00:00 -4643,389,49,6.0,4,0,1984-04-07 00:00:00 -4644,389,31,4.0,5,0,1984-04-07 00:00:00 -4645,389,2,6.0,2,0,1984-04-07 00:00:00 -4646,389,0,24.0,1,2,1984-04-07 00:00:00 -4647,389,26,2.0,6,0,1984-04-07 00:00:00 -4648,390,5,13.0,2,1,1984-04-29 00:00:00 -4649,390,24,0.0,13,0,1984-04-29 00:00:00 -4650,390,50,0.0,11,0,1984-04-29 00:00:00 -4651,390,51,2.0,8,0,1984-04-29 00:00:00 -4652,390,43,0.0,15,0,1984-04-29 00:00:00 -4653,390,33,0.0,12,0,1984-04-29 00:00:00 -4654,390,52,0.0,14,0,1984-04-29 00:00:00 -4655,390,48,0.0,10,0,1984-04-29 00:00:00 -4656,390,20,1.0,9,0,1984-04-29 00:00:00 -4657,390,3,12.0,3,0,1984-04-29 00:00:00 -4658,390,49,6.0,6,0,1984-04-29 00:00:00 -4659,390,31,6.0,5,0,1984-04-29 00:00:00 -4660,390,2,9.0,4,0,1984-04-29 00:00:00 -4661,390,0,24.0,1,2,1984-04-29 00:00:00 -4662,390,26,2.0,7,0,1984-04-29 00:00:00 -4663,391,0,33.0,1,3,1984-05-06 00:00:00 -4664,391,31,10.0,4,0,1984-05-06 00:00:00 -4665,391,51,2.0,9,0,1984-05-06 00:00:00 -4666,391,49,6.0,6,0,1984-05-06 00:00:00 -4667,391,50,0.0,10,0,1984-05-06 00:00:00 -4668,391,5,19.0,2,1,1984-05-06 00:00:00 -4669,391,33,0.0,12,0,1984-05-06 00:00:00 -4670,391,26,3.0,8,0,1984-05-06 00:00:00 -4671,391,3,15.0,3,0,1984-05-06 00:00:00 -4672,391,20,3.0,7,0,1984-05-06 00:00:00 -4673,391,48,0.0,11,0,1984-05-06 00:00:00 -4674,391,43,0.0,15,0,1984-05-06 00:00:00 -4675,391,24,0.0,13,0,1984-05-06 00:00:00 -4676,391,52,0.0,14,0,1984-05-06 00:00:00 -4677,391,2,9.0,5,0,1984-05-06 00:00:00 -4678,392,5,22.0,2,1,1984-05-20 00:00:00 -4679,392,24,0.0,14,0,1984-05-20 00:00:00 -4680,392,52,0.0,15,0,1984-05-20 00:00:00 -4681,392,50,0.0,10,0,1984-05-20 00:00:00 -4682,392,51,2.0,9,0,1984-05-20 00:00:00 -4683,392,43,0.0,13,0,1984-05-20 00:00:00 -4684,392,33,0.0,12,0,1984-05-20 00:00:00 -4685,392,31,16.0,4,0,1984-05-20 00:00:00 -4686,392,48,0.0,11,0,1984-05-20 00:00:00 -4687,392,20,3.0,7,0,1984-05-20 00:00:00 -4688,392,3,21.0,3,0,1984-05-20 00:00:00 -4689,392,49,6.0,6,0,1984-05-20 00:00:00 -4690,392,0,42.0,1,4,1984-05-20 00:00:00 -4691,392,2,10.0,5,0,1984-05-20 00:00:00 -4692,392,26,3.0,8,0,1984-05-20 00:00:00 -4693,393,24,0.0,15,0,1984-06-03 00:00:00 -4694,393,50,0.0,11,0,1984-06-03 00:00:00 -4695,393,51,5.0,7,0,1984-06-03 00:00:00 -4696,393,43,0.0,10,0,1984-06-03 00:00:00 -4697,393,5,24.5,2,1,1984-06-03 00:00:00 -4698,393,20,3.0,8,0,1984-06-03 00:00:00 -4699,393,26,3.0,9,0,1984-06-03 00:00:00 -4700,393,48,0.0,12,0,1984-06-03 00:00:00 -4701,393,3,21.0,3,0,1984-06-03 00:00:00 -4702,393,33,0.0,13,0,1984-06-03 00:00:00 -4703,393,52,0.0,14,0,1984-06-03 00:00:00 -4704,393,49,6.0,6,0,1984-06-03 00:00:00 -4705,393,31,17.0,4,0,1984-06-03 00:00:00 -4706,393,0,46.5,1,5,1984-06-03 00:00:00 -4707,393,2,11.5,5,0,1984-06-03 00:00:00 -4708,394,52,0.0,14,0,1984-06-17 00:00:00 -4709,394,24,0.0,15,0,1984-06-17 00:00:00 -4710,394,51,5.0,8,0,1984-06-17 00:00:00 -4711,394,43,0.0,11,0,1984-06-17 00:00:00 -4712,394,5,26.5,2,1,1984-06-17 00:00:00 -4713,394,33,9.0,6,1,1984-06-17 00:00:00 -4714,394,26,3.0,10,0,1984-06-17 00:00:00 -4715,394,50,0.0,12,0,1984-06-17 00:00:00 -4716,394,20,3.0,9,0,1984-06-17 00:00:00 -4717,394,3,21.0,3,0,1984-06-17 00:00:00 -4718,394,49,6.0,7,0,1984-06-17 00:00:00 -4719,394,31,21.0,4,0,1984-06-17 00:00:00 -4720,394,2,11.5,5,0,1984-06-17 00:00:00 -4721,394,0,56.5,1,5,1984-06-17 00:00:00 -4722,394,48,0.0,13,0,1984-06-17 00:00:00 -4723,395,50,0.0,12,0,1984-06-24 00:00:00 -4724,395,43,0.0,11,0,1984-06-24 00:00:00 -4725,395,5,26.5,3,1,1984-06-24 00:00:00 -4726,395,33,22.0,4,2,1984-06-24 00:00:00 -4727,395,26,3.0,10,0,1984-06-24 00:00:00 -4728,395,48,0.0,13,0,1984-06-24 00:00:00 -4729,395,49,6.0,7,0,1984-06-24 00:00:00 -4730,395,3,21.0,5,0,1984-06-24 00:00:00 -4731,395,31,27.0,2,0,1984-06-24 00:00:00 -4732,395,2,13.5,6,0,1984-06-24 00:00:00 -4733,395,0,59.5,1,5,1984-06-24 00:00:00 -4734,395,24,0.0,15,0,1984-06-24 00:00:00 -4735,395,20,3.0,9,0,1984-06-24 00:00:00 -4736,395,52,0.0,14,0,1984-06-24 00:00:00 -4737,395,51,5.0,8,0,1984-06-24 00:00:00 -4738,396,2,25.5,4,1,1984-07-08 00:00:00 -4739,396,52,0.0,13,0,1984-07-08 00:00:00 -4740,396,24,0.0,15,0,1984-07-08 00:00:00 -4741,396,50,0.0,12,0,1984-07-08 00:00:00 -4742,396,51,5.0,8,0,1984-07-08 00:00:00 -4743,396,5,32.5,2,1,1984-07-08 00:00:00 -4744,396,33,22.0,5,2,1984-07-08 00:00:00 -4745,396,43,2.0,11,0,1984-07-08 00:00:00 -4746,396,48,0.0,14,0,1984-07-08 00:00:00 -4747,396,20,3.0,9,0,1984-07-08 00:00:00 -4748,396,3,21.0,6,0,1984-07-08 00:00:00 -4749,396,49,6.0,7,0,1984-07-08 00:00:00 -4750,396,0,59.5,1,5,1984-07-08 00:00:00 -4751,396,26,3.0,10,0,1984-07-08 00:00:00 -4752,396,31,32.0,3,0,1984-07-08 00:00:00 -4753,397,52,0.0,13,0,1984-07-22 00:00:00 -4754,397,33,22.0,6,2,1984-07-22 00:00:00 -4755,397,24,0.0,15,0,1984-07-22 00:00:00 -4756,397,50,0.0,12,0,1984-07-22 00:00:00 -4757,397,51,9.0,7,0,1984-07-22 00:00:00 -4758,397,43,2.0,11,0,1984-07-22 00:00:00 -4759,397,5,35.5,2,1,1984-07-22 00:00:00 -4760,397,26,3.0,10,0,1984-07-22 00:00:00 -4761,397,20,3.0,9,0,1984-07-22 00:00:00 -4762,397,3,27.0,4,0,1984-07-22 00:00:00 -4763,397,49,6.0,8,0,1984-07-22 00:00:00 -4764,397,31,35.0,3,0,1984-07-22 00:00:00 -4765,397,2,25.5,5,1,1984-07-22 00:00:00 -4766,397,0,68.5,1,6,1984-07-22 00:00:00 -4767,397,48,0.0,14,0,1984-07-22 00:00:00 -4768,398,49,6.0,8,0,1984-08-05 00:00:00 -4769,398,31,38.0,2,0,1984-08-05 00:00:00 -4770,398,52,0.0,13,0,1984-08-05 00:00:00 -4771,398,24,0.0,15,0,1984-08-05 00:00:00 -4772,398,50,0.0,12,0,1984-08-05 00:00:00 -4773,398,51,9.0,7,0,1984-08-05 00:00:00 -4774,398,26,3.0,10,0,1984-08-05 00:00:00 -4775,398,5,36.5,3,1,1984-08-05 00:00:00 -4776,398,33,22.0,6,2,1984-08-05 00:00:00 -4777,398,48,0.0,14,0,1984-08-05 00:00:00 -4778,398,2,25.5,5,1,1984-08-05 00:00:00 -4779,398,0,83.5,1,7,1984-08-05 00:00:00 -4780,398,20,3.0,9,0,1984-08-05 00:00:00 -4781,398,43,2.0,11,0,1984-08-05 00:00:00 -4782,398,3,33.0,4,0,1984-08-05 00:00:00 -4783,399,43,2.0,11,0,1984-08-19 00:00:00 -4784,399,2,25.5,6,1,1984-08-19 00:00:00 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00:00:00 -4833,402,43,2.0,11,0,1984-10-07 00:00:00 -4834,402,5,54.5,2,1,1984-10-07 00:00:00 -4835,402,0,128.5,1,11,1984-10-07 00:00:00 -4836,402,26,3.0,10,0,1984-10-07 00:00:00 -4837,402,33,37.0,4,2,1984-10-07 00:00:00 -4838,402,49,11.0,8,0,1984-10-07 00:00:00 -4839,402,31,45.0,3,0,1984-10-07 00:00:00 -4840,402,20,6.0,9,0,1984-10-07 00:00:00 -4841,402,48,0.0,14,0,1984-10-07 00:00:00 -4842,402,3,34.0,5,0,1984-10-07 00:00:00 -4843,403,24,0.0,15,0,1984-10-21 00:00:00 -4844,403,50,0.0,13,0,1984-10-21 00:00:00 -4845,403,51,16.0,7,0,1984-10-21 00:00:00 -4846,403,43,2.0,11,0,1984-10-21 00:00:00 -4847,403,5,57.5,2,1,1984-10-21 00:00:00 -4848,403,33,38.0,4,2,1984-10-21 00:00:00 -4849,403,26,3.0,10,0,1984-10-21 00:00:00 -4850,403,49,11.0,8,0,1984-10-21 00:00:00 -4851,403,31,47.0,3,0,1984-10-21 00:00:00 -4852,403,2,25.5,6,1,1984-10-21 00:00:00 -4853,403,52,0.0,12,0,1984-10-21 00:00:00 -4854,403,0,143.5,1,12,1984-10-21 00:00:00 -4855,403,48,0.0,14,0,1984-10-21 00:00:00 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-5312,434,33,2.0,9,0,1986-10-12 00:00:00 -5313,435,38,0.0,14,0,1986-10-26 00:00:00 -5314,435,17,0.0,12,0,1986-10-26 00:00:00 -5315,435,2,141.0,1,9,1986-10-26 00:00:00 -5316,435,47,0.0,11,0,1986-10-26 00:00:00 -5317,435,25,6.0,8,0,1986-10-26 00:00:00 -5318,435,43,0.0,13,0,1986-10-26 00:00:00 -5319,435,5,37.0,4,0,1986-10-26 00:00:00 -5320,435,20,1.0,10,0,1986-10-26 00:00:00 -5321,435,0,96.0,2,4,1986-10-26 00:00:00 -5322,435,21,19.0,6,1,1986-10-26 00:00:00 -5323,435,24,11.0,7,0,1986-10-26 00:00:00 -5324,435,26,29.0,5,0,1986-10-26 00:00:00 -5325,435,31,58.0,3,2,1986-10-26 00:00:00 -5326,435,33,2.0,9,0,1986-10-26 00:00:00 -5327,436,20,0.0,9,0,1987-04-12 00:00:00 -5328,436,36,0.0,13,0,1987-04-12 00:00:00 -5329,436,17,0.0,12,0,1987-04-12 00:00:00 -5330,436,43,0.0,11,0,1987-04-12 00:00:00 -5331,436,33,0.0,10,0,1987-04-12 00:00:00 -5332,436,24,0.0,7,0,1987-04-12 00:00:00 -5333,436,38,0.0,8,0,1987-04-12 00:00:00 -5334,436,47,0.0,6,0,1987-04-12 00:00:00 -5335,436,31,0.0,5,0,1987-04-12 00:00:00 -5336,436,21,2.0,4,0,1987-04-12 00:00:00 -5337,436,5,3.0,3,0,1987-04-12 00:00:00 -5338,436,2,7.0,2,0,1987-04-12 00:00:00 -5339,436,0,13.0,1,1,1987-04-12 00:00:00 -5340,437,26,0.0,15,0,1987-05-03 00:00:00 -5341,437,32,0.0,9,0,1987-05-03 00:00:00 -5342,437,36,0.0,14,0,1987-05-03 00:00:00 -5343,437,17,0.0,13,0,1987-05-03 00:00:00 -5344,437,43,0.0,12,0,1987-05-03 00:00:00 -5345,437,33,0.0,8,0,1987-05-03 00:00:00 -5346,437,20,0.0,10,0,1987-05-03 00:00:00 -5347,437,38,0.0,11,0,1987-05-03 00:00:00 -5348,437,24,0.0,7,0,1987-05-03 00:00:00 -5349,437,47,2.0,5,0,1987-05-03 00:00:00 -5350,437,31,7.0,3,0,1987-05-03 00:00:00 -5351,437,21,2.0,6,0,1987-05-03 00:00:00 -5352,437,5,7.0,4,0,1987-05-03 00:00:00 -5353,437,2,16.0,1,1,1987-05-03 00:00:00 -5354,437,0,16.0,2,1,1987-05-03 00:00:00 -5355,438,26,1.0,9,0,1987-05-17 00:00:00 -5356,438,32,0.0,11,0,1987-05-17 00:00:00 -5357,438,36,0.0,14,0,1987-05-17 00:00:00 -5358,438,17,0.0,15,0,1987-05-17 00:00:00 -5359,438,43,0.0,13,0,1987-05-17 00:00:00 -5360,438,33,4.0,5,0,1987-05-17 00:00:00 -5361,438,20,3.0,6,0,1987-05-17 00:00:00 -5362,438,47,2.0,7,0,1987-05-17 00:00:00 -5363,438,24,0.0,10,0,1987-05-17 00:00:00 -5364,438,31,9.0,3,0,1987-05-17 00:00:00 -5365,438,21,2.0,8,0,1987-05-17 00:00:00 -5366,438,5,7.0,4,0,1987-05-17 00:00:00 -5367,438,2,16.0,2,1,1987-05-17 00:00:00 -5368,438,0,31.0,1,2,1987-05-17 00:00:00 -5369,438,38,0.0,12,0,1987-05-17 00:00:00 -5370,439,26,1.0,10,0,1987-05-31 00:00:00 -5371,439,32,0.0,12,0,1987-05-31 00:00:00 -5372,439,36,1.0,11,0,1987-05-31 00:00:00 -5373,439,17,0.0,15,0,1987-05-31 00:00:00 -5374,439,43,0.0,14,0,1987-05-31 00:00:00 -5375,439,33,4.0,5,0,1987-05-31 00:00:00 -5376,439,20,3.0,6,0,1987-05-31 00:00:00 -5377,439,47,2.0,7,0,1987-05-31 00:00:00 -5378,439,24,2.0,8,0,1987-05-31 00:00:00 -5379,439,31,18.0,3,1,1987-05-31 00:00:00 -5380,439,21,2.0,9,0,1987-05-31 00:00:00 -5381,439,5,14.0,4,0,1987-05-31 00:00:00 -5382,439,2,22.0,2,1,1987-05-31 00:00:00 -5383,439,0,31.0,1,2,1987-05-31 00:00:00 -5384,439,38,0.0,13,0,1987-05-31 00:00:00 -5385,440,43,0.0,14,0,1987-06-21 00:00:00 -5386,440,33,4.0,5,0,1987-06-21 00:00:00 -5387,440,17,0.0,15,0,1987-06-21 00:00:00 -5388,440,24,2.0,8,0,1987-06-21 00:00:00 -5389,440,32,0.0,12,0,1987-06-21 00:00:00 -5390,440,26,1.0,10,0,1987-06-21 00:00:00 -5391,440,36,1.0,11,0,1987-06-21 00:00:00 -5392,440,20,4.0,6,0,1987-06-21 00:00:00 -5393,440,31,27.0,3,2,1987-06-21 00:00:00 -5394,440,47,2.0,7,0,1987-06-21 00:00:00 -5395,440,38,0.0,13,0,1987-06-21 00:00:00 -5396,440,21,2.0,9,0,1987-06-21 00:00:00 -5397,440,5,17.0,4,0,1987-06-21 00:00:00 -5398,440,2,30.0,2,1,1987-06-21 00:00:00 -5399,440,0,35.0,1,2,1987-06-21 00:00:00 -5400,441,26,1.0,10,0,1987-07-05 00:00:00 -5401,441,32,0.0,12,0,1987-07-05 00:00:00 -5402,441,36,1.0,11,0,1987-07-05 00:00:00 -5403,441,17,0.0,15,0,1987-07-05 00:00:00 -5404,441,43,0.0,14,0,1987-07-05 00:00:00 -5405,441,33,4.0,5,0,1987-07-05 00:00:00 -5406,441,20,4.0,6,0,1987-07-05 00:00:00 -5407,441,38,0.0,13,0,1987-07-05 00:00:00 -5408,441,24,3.0,8,0,1987-07-05 00:00:00 -5409,441,47,2.0,9,0,1987-07-05 00:00:00 -5410,441,31,30.0,3,2,1987-07-05 00:00:00 -5411,441,21,4.0,7,0,1987-07-05 00:00:00 -5412,441,5,17.0,4,0,1987-07-05 00:00:00 -5413,441,2,45.0,1,2,1987-07-05 00:00:00 -5414,441,0,39.0,2,2,1987-07-05 00:00:00 -5415,442,32,0.0,12,0,1987-07-12 00:00:00 -5416,442,36,1.0,11,0,1987-07-12 00:00:00 -5417,442,17,0.0,15,0,1987-07-12 00:00:00 -5418,442,43,0.0,14,0,1987-07-12 00:00:00 -5419,442,26,1.0,10,0,1987-07-12 00:00:00 -5420,442,33,4.0,7,0,1987-07-12 00:00:00 -5421,442,20,6.0,5,0,1987-07-12 00:00:00 -5422,442,31,37.0,3,2,1987-07-12 00:00:00 -5423,442,24,3.0,8,0,1987-07-12 00:00:00 -5424,442,47,2.0,9,0,1987-07-12 00:00:00 -5425,442,21,5.0,6,0,1987-07-12 00:00:00 -5426,442,5,17.0,4,0,1987-07-12 00:00:00 -5427,442,2,60.0,1,3,1987-07-12 00:00:00 -5428,442,0,39.0,2,2,1987-07-12 00:00:00 -5429,442,38,0.0,13,0,1987-07-12 00:00:00 -5430,443,32,1.0,11,0,1987-07-26 00:00:00 -5431,443,36,1.0,12,0,1987-07-26 00:00:00 -5432,443,17,0.0,15,0,1987-07-26 00:00:00 -5433,443,43,0.0,14,0,1987-07-26 00:00:00 -5434,443,33,4.0,8,0,1987-07-26 00:00:00 -5435,443,20,6.0,6,0,1987-07-26 00:00:00 -5436,443,38,0.0,13,0,1987-07-26 00:00:00 -5437,443,31,41.0,3,2,1987-07-26 00:00:00 -5438,443,47,2.0,9,0,1987-07-26 00:00:00 -5439,443,21,5.0,7,0,1987-07-26 00:00:00 -5440,443,5,17.0,4,0,1987-07-26 00:00:00 -5441,443,2,69.0,1,4,1987-07-26 00:00:00 -5442,443,0,45.0,2,2,1987-07-26 00:00:00 -5443,443,26,1.0,10,0,1987-07-26 00:00:00 -5444,443,24,8.0,5,0,1987-07-26 00:00:00 -5445,444,2,78.0,1,5,1987-08-09 00:00:00 -5446,444,5,17.0,4,0,1987-08-09 00:00:00 -5447,444,0,49.0,2,2,1987-08-09 00:00:00 -5448,444,21,8.0,6,0,1987-08-09 00:00:00 -5449,444,31,47.0,3,2,1987-08-09 00:00:00 -5450,444,47,2.0,9,0,1987-08-09 00:00:00 -5451,444,26,1.0,10,0,1987-08-09 00:00:00 -5452,444,36,1.0,12,0,1987-08-09 00:00:00 -5453,444,17,0.0,14,0,1987-08-09 00:00:00 -5454,444,43,0.0,15,0,1987-08-09 00:00:00 -5455,444,32,1.0,11,0,1987-08-09 00:00:00 -5456,444,20,7.0,7,0,1987-08-09 00:00:00 -5457,444,38,0.0,13,0,1987-08-09 00:00:00 -5458,444,24,8.0,5,0,1987-08-09 00:00:00 -5459,444,33,6.0,8,0,1987-08-09 00:00:00 -5460,445,20,7.0,7,0,1987-08-16 00:00:00 -5461,445,26,1.0,10,0,1987-08-16 00:00:00 -5462,445,36,1.0,12,0,1987-08-16 00:00:00 -5463,445,17,0.0,14,0,1987-08-16 00:00:00 -5464,445,43,0.0,15,0,1987-08-16 00:00:00 -5465,445,33,6.0,8,0,1987-08-16 00:00:00 -5466,445,38,0.0,13,0,1987-08-16 00:00:00 -5467,445,32,1.0,11,0,1987-08-16 00:00:00 -5468,445,47,2.0,9,0,1987-08-16 00:00:00 -5469,445,31,49.0,3,2,1987-08-16 00:00:00 -5470,445,21,15.0,5,0,1987-08-16 00:00:00 -5471,445,5,17.0,4,0,1987-08-16 00:00:00 -5472,445,2,93.0,1,6,1987-08-16 00:00:00 -5473,445,0,50.0,2,2,1987-08-16 00:00:00 -5474,445,24,8.0,6,0,1987-08-16 00:00:00 -5475,446,41,0.0,16,0,1987-09-06 00:00:00 -5476,446,26,1.0,10,0,1987-09-06 00:00:00 -5477,446,32,1.0,11,0,1987-09-06 00:00:00 -5478,446,36,1.0,12,0,1987-09-06 00:00:00 -5479,446,17,0.0,14,0,1987-09-06 00:00:00 -5480,446,43,0.0,15,0,1987-09-06 00:00:00 -5481,446,33,6.0,8,0,1987-09-06 00:00:00 -5482,446,20,7.0,7,0,1987-09-06 00:00:00 -5483,446,38,0.0,13,0,1987-09-06 00:00:00 -5484,446,47,2.0,9,0,1987-09-06 00:00:00 -5485,446,31,55.0,2,2,1987-09-06 00:00:00 -5486,446,21,17.0,5,0,1987-09-06 00:00:00 -5487,446,5,20.0,4,0,1987-09-06 00:00:00 -5488,446,2,106.0,1,7,1987-09-06 00:00:00 -5489,446,0,51.0,3,2,1987-09-06 00:00:00 -5490,446,24,8.0,6,0,1987-09-06 00:00:00 -5491,447,33,6.0,8,0,1987-09-20 00:00:00 -5492,447,41,0.0,16,0,1987-09-20 00:00:00 -5493,447,32,1.0,11,0,1987-09-20 00:00:00 -5494,447,36,1.0,12,0,1987-09-20 00:00:00 -5495,447,17,0.0,14,0,1987-09-20 00:00:00 -5496,447,43,0.0,15,0,1987-09-20 00:00:00 -5497,447,20,8.0,7,0,1987-09-20 00:00:00 -5498,447,26,1.0,10,0,1987-09-20 00:00:00 -5499,447,24,8.0,6,0,1987-09-20 00:00:00 -5500,447,0,62.0,2,3,1987-09-20 00:00:00 -5501,447,2,110.0,1,7,1987-09-20 00:00:00 -5502,447,5,26.0,4,0,1987-09-20 00:00:00 -5503,447,38,0.0,13,0,1987-09-20 00:00:00 -5504,447,31,55.0,3,2,1987-09-20 00:00:00 -5505,447,47,2.0,9,0,1987-09-20 00:00:00 -5506,447,21,20.0,5,0,1987-09-20 00:00:00 -5507,448,41,0.0,16,0,1987-09-27 00:00:00 -5508,448,26,1.0,11,0,1987-09-27 00:00:00 -5509,448,32,2.0,10,0,1987-09-27 00:00:00 -5510,448,36,1.0,12,0,1987-09-27 00:00:00 -5511,448,17,0.0,14,0,1987-09-27 00:00:00 -5512,448,33,6.0,8,0,1987-09-27 00:00:00 -5513,448,20,8.0,7,0,1987-09-27 00:00:00 -5514,448,43,0.0,15,0,1987-09-27 00:00:00 -5515,448,24,8.0,6,0,1987-09-27 00:00:00 -5516,448,47,2.0,9,0,1987-09-27 00:00:00 -5517,448,31,57.0,3,2,1987-09-27 00:00:00 -5518,448,21,20.0,5,0,1987-09-27 00:00:00 -5519,448,5,26.0,4,0,1987-09-27 00:00:00 -5520,448,2,122.0,1,8,1987-09-27 00:00:00 -5521,448,0,72.0,2,3,1987-09-27 00:00:00 -5522,448,38,0.0,13,0,1987-09-27 00:00:00 -5523,449,41,0.0,16,0,1987-10-18 00:00:00 -5524,449,26,1.0,11,0,1987-10-18 00:00:00 -5525,449,32,3.0,9,0,1987-10-18 00:00:00 -5526,449,36,1.0,12,0,1987-10-18 00:00:00 -5527,449,17,0.0,14,0,1987-10-18 00:00:00 -5528,449,43,0.0,15,0,1987-10-18 00:00:00 -5529,449,33,10.0,7,0,1987-10-18 00:00:00 -5530,449,20,11.0,6,0,1987-10-18 00:00:00 -5531,449,38,0.0,13,0,1987-10-18 00:00:00 -5532,449,47,2.0,10,0,1987-10-18 00:00:00 -5533,449,31,57.0,3,2,1987-10-18 00:00:00 -5534,449,21,22.0,5,0,1987-10-18 00:00:00 -5535,449,5,26.0,4,0,1987-10-18 00:00:00 -5536,449,2,137.0,1,9,1987-10-18 00:00:00 -5537,449,0,72.0,2,3,1987-10-18 00:00:00 -5538,449,24,8.0,8,0,1987-10-18 00:00:00 -5539,450,41,0.0,16,0,1987-11-01 00:00:00 -5540,450,26,1.0,11,0,1987-11-01 00:00:00 -5541,450,32,3.0,9,0,1987-11-01 00:00:00 -5542,450,36,1.0,12,0,1987-11-01 00:00:00 -5543,450,17,0.0,14,0,1987-11-01 00:00:00 -5544,450,43,0.0,15,0,1987-11-01 00:00:00 -5545,450,33,10.0,7,0,1987-11-01 00:00:00 -5546,450,20,11.0,6,0,1987-11-01 00:00:00 -5547,450,38,0.0,13,0,1987-11-01 00:00:00 -5548,450,47,2.0,10,0,1987-11-01 00:00:00 -5549,450,31,64.0,3,2,1987-11-01 00:00:00 -5550,450,21,24.0,5,0,1987-11-01 00:00:00 -5551,450,5,38.0,4,1,1987-11-01 00:00:00 -5552,450,2,137.0,1,9,1987-11-01 00:00:00 -5553,450,0,76.0,2,3,1987-11-01 00:00:00 -5554,450,24,8.0,8,0,1987-11-01 00:00:00 -5555,451,43,0.0,15,0,1987-11-15 00:00:00 -5556,451,41,0.0,16,0,1987-11-15 00:00:00 -5557,451,26,1.0,11,0,1987-11-15 00:00:00 -5558,451,32,3.0,9,0,1987-11-15 00:00:00 -5559,451,36,1.0,13,0,1987-11-15 00:00:00 -5560,451,17,0.0,14,0,1987-11-15 00:00:00 -5561,451,33,10.0,8,0,1987-11-15 00:00:00 -5562,451,20,11.0,7,0,1987-11-15 00:00:00 -5563,451,24,11.0,6,0,1987-11-15 00:00:00 -5564,451,47,2.0,10,0,1987-11-15 00:00:00 -5565,451,31,64.0,3,2,1987-11-15 00:00:00 -5566,451,21,28.0,5,0,1987-11-15 00:00:00 -5567,451,5,53.0,4,2,1987-11-15 00:00:00 -5568,451,2,137.0,1,9,1987-11-15 00:00:00 -5569,451,0,76.0,2,3,1987-11-15 00:00:00 -5570,451,38,1.0,12,0,1987-11-15 00:00:00 -5571,452,47,0.0,16,0,1988-04-03 00:00:00 -5572,452,34,0.0,18,0,1988-04-03 00:00:00 -5573,452,43,0.0,17,0,1988-04-03 00:00:00 -5574,452,36,0.0,15,0,1988-04-03 00:00:00 -5575,452,2,0.0,14,0,1988-04-03 00:00:00 -5576,452,42,0.0,13,0,1988-04-03 00:00:00 -5577,452,38,0.0,12,0,1988-04-03 00:00:00 -5578,452,41,0.0,11,0,1988-04-03 00:00:00 -5579,452,32,0.0,10,0,1988-04-03 00:00:00 -5580,452,0,9.0,1,1,1988-04-03 00:00:00 -5581,452,24,0.0,8,0,1988-04-03 00:00:00 -5582,452,46,0.0,7,0,1988-04-03 00:00:00 -5583,452,26,0.0,6,0,1988-04-03 00:00:00 -5584,452,21,0.0,5,0,1988-04-03 00:00:00 -5585,452,20,3.0,4,0,1988-04-03 00:00:00 -5586,452,31,5.0,3,0,1988-04-03 00:00:00 -5587,452,5,8.0,2,0,1988-04-03 00:00:00 -5588,452,17,0.0,9,0,1988-04-03 00:00:00 -5589,453,38,0.0,7,0,1988-05-01 00:00:00 -5590,453,42,0.0,15,0,1988-05-01 00:00:00 -5591,453,2,0.0,10,0,1988-05-01 00:00:00 -5592,453,41,0.0,14,0,1988-05-01 00:00:00 -5593,453,47,0.0,17,0,1988-05-01 00:00:00 -5594,453,43,0.0,18,0,1988-05-01 00:00:00 -5595,453,34,0.0,16,0,1988-05-01 00:00:00 -5596,453,36,0.0,12,0,1988-05-01 00:00:00 -5597,453,32,0.0,9,0,1988-05-01 00:00:00 -5598,453,0,24.0,1,2,1988-05-01 00:00:00 -5599,453,24,0.0,11,0,1988-05-01 00:00:00 -5600,453,46,0.0,13,0,1988-05-01 00:00:00 -5601,453,26,0.0,6,0,1988-05-01 00:00:00 -5602,453,21,4.0,4,0,1988-05-01 00:00:00 -5603,453,20,3.0,5,0,1988-05-01 00:00:00 -5604,453,31,9.0,3,0,1988-05-01 00:00:00 -5605,453,5,10.0,2,0,1988-05-01 00:00:00 -5606,453,17,0.0,8,0,1988-05-01 00:00:00 -5607,454,38,0.0,12,0,1988-05-15 00:00:00 -5608,454,42,0.0,17,0,1988-05-15 00:00:00 -5609,454,36,0.0,11,0,1988-05-15 00:00:00 -5610,454,2,1.0,7,0,1988-05-15 00:00:00 -5611,454,43,0.0,10,0,1988-05-15 00:00:00 -5612,454,34,0.0,18,0,1988-05-15 00:00:00 -5613,454,41,0.0,15,0,1988-05-15 00:00:00 -5614,454,47,0.0,16,0,1988-05-15 00:00:00 -5615,454,32,0.0,8,0,1988-05-15 00:00:00 -5616,454,17,0.0,13,0,1988-05-15 00:00:00 -5617,454,24,2.0,6,0,1988-05-15 00:00:00 -5618,454,46,0.0,14,0,1988-05-15 00:00:00 -5619,454,26,0.0,9,0,1988-05-15 00:00:00 -5620,454,21,4.0,5,0,1988-05-15 00:00:00 -5621,454,20,6.0,4,0,1988-05-15 00:00:00 -5622,454,31,9.0,3,0,1988-05-15 00:00:00 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00:00:00 -5838,466,5,65.0,2,1,1988-10-30 00:00:00 -5839,466,0,184.0,1,14,1988-10-30 00:00:00 -5840,466,24,5.0,8,0,1988-10-30 00:00:00 -5841,467,41,0.0,14,0,1988-11-13 00:00:00 -5842,467,43,0.0,16,0,1988-11-13 00:00:00 -5843,467,47,0.0,18,0,1988-11-13 00:00:00 -5844,467,36,22.0,6,0,1988-11-13 00:00:00 -5845,467,2,20.0,7,0,1988-11-13 00:00:00 -5846,467,42,0.0,17,0,1988-11-13 00:00:00 -5847,467,38,0.0,13,0,1988-11-13 00:00:00 -5848,467,32,0.0,11,0,1988-11-13 00:00:00 -5849,467,34,0.0,12,0,1988-11-13 00:00:00 -5850,467,24,5.0,8,0,1988-11-13 00:00:00 -5851,467,0,199.0,1,15,1988-11-13 00:00:00 -5852,467,5,65.0,2,1,1988-11-13 00:00:00 -5853,467,31,23.0,4,0,1988-11-13 00:00:00 -5854,467,17,1.0,10,0,1988-11-13 00:00:00 -5855,467,21,39.0,3,0,1988-11-13 00:00:00 -5856,467,26,0.0,15,0,1988-11-13 00:00:00 -5857,467,46,3.0,9,0,1988-11-13 00:00:00 -5858,467,20,23.0,5,0,1988-11-13 00:00:00 -5859,468,47,0.0,13,0,1989-03-26 00:00:00 -5860,468,44,0.0,20,0,1989-03-26 00:00:00 -5861,468,38,0.0,19,0,1989-03-26 00:00:00 -5862,468,41,0.0,17,0,1989-03-26 00:00:00 -5863,468,42,0.0,16,0,1989-03-26 00:00:00 -5864,468,17,0.0,15,0,1989-03-26 00:00:00 -5865,468,43,0.0,18,0,1989-03-26 00:00:00 -5866,468,33,0.0,14,0,1989-03-26 00:00:00 -5867,468,2,0.0,12,0,1989-03-26 00:00:00 -5868,468,46,0.0,11,0,1989-03-26 00:00:00 -5869,468,34,0.0,10,0,1989-03-26 00:00:00 -5870,468,0,6.0,2,0,1989-03-26 00:00:00 -5871,468,36,4.0,3,0,1989-03-26 00:00:00 -5872,468,21,4.0,4,0,1989-03-26 00:00:00 -5873,468,20,2.0,5,0,1989-03-26 00:00:00 -5874,468,5,9.0,1,1,1989-03-26 00:00:00 -5875,468,31,0.0,7,0,1989-03-26 00:00:00 -5876,468,26,0.0,8,0,1989-03-26 00:00:00 -5877,468,32,0.0,9,0,1989-03-26 00:00:00 -5878,468,24,0.0,6,0,1989-03-26 00:00:00 -5879,469,47,0.0,17,0,1989-04-23 00:00:00 -5880,469,44,0.0,20,0,1989-04-23 00:00:00 -5881,469,38,0.0,10,0,1989-04-23 00:00:00 -5882,469,41,0.0,19,0,1989-04-23 00:00:00 -5883,469,42,0.0,18,0,1989-04-23 00:00:00 -5884,469,17,0.0,16,0,1989-04-23 00:00:00 -5885,469,43,0.0,13,0,1989-04-23 00:00:00 -5886,469,33,0.0,15,0,1989-04-23 00:00:00 -5887,469,2,3.0,6,0,1989-04-23 00:00:00 -5888,469,5,9.0,2,1,1989-04-23 00:00:00 -5889,469,34,0.0,8,0,1989-04-23 00:00:00 -5890,469,32,0.0,12,0,1989-04-23 00:00:00 -5891,469,26,0.0,11,0,1989-04-23 00:00:00 -5892,469,31,0.0,9,0,1989-04-23 00:00:00 -5893,469,24,1.0,7,0,1989-04-23 00:00:00 -5894,469,20,4.0,5,0,1989-04-23 00:00:00 -5895,469,21,8.0,3,0,1989-04-23 00:00:00 -5896,469,36,4.0,4,0,1989-04-23 00:00:00 -5897,469,0,21.0,1,1,1989-04-23 00:00:00 -5898,469,46,0.0,14,0,1989-04-23 00:00:00 -5899,470,33,5.0,4,0,1989-05-07 00:00:00 -5900,470,43,0.0,14,0,1989-05-07 00:00:00 -5901,470,17,0.0,16,0,1989-05-07 00:00:00 -5902,470,47,0.0,17,0,1989-05-07 00:00:00 -5903,470,41,0.0,18,0,1989-05-07 00:00:00 -5904,470,38,0.0,11,0,1989-05-07 00:00:00 -5905,470,44,0.0,20,0,1989-05-07 00:00:00 -5906,470,42,0.0,19,0,1989-05-07 00:00:00 -5907,470,2,3.0,8,0,1989-05-07 00:00:00 -5908,470,5,9.0,2,1,1989-05-07 00:00:00 -5909,470,34,3.0,7,0,1989-05-07 00:00:00 -5910,470,0,36.0,1,2,1989-05-07 00:00:00 -5911,470,36,4.0,5,0,1989-05-07 00:00:00 -5912,470,21,8.0,3,0,1989-05-07 00:00:00 -5913,470,20,4.0,6,0,1989-05-07 00:00:00 -5914,470,46,0.0,15,0,1989-05-07 00:00:00 -5915,470,31,0.0,10,0,1989-05-07 00:00:00 -5916,470,26,0.0,12,0,1989-05-07 00:00:00 -5917,470,32,0.0,13,0,1989-05-07 00:00:00 -5918,470,24,3.0,9,0,1989-05-07 00:00:00 -5919,471,2,9.0,4,0,1989-05-28 00:00:00 -5920,471,38,1.0,10,0,1989-05-28 00:00:00 -5921,471,41,0.0,18,0,1989-05-28 00:00:00 -5922,471,42,0.0,20,0,1989-05-28 00:00:00 -5923,471,17,0.0,16,0,1989-05-28 00:00:00 -5924,471,43,0.0,15,0,1989-05-28 00:00:00 -5925,471,33,5.0,6,0,1989-05-28 00:00:00 -5926,471,47,0.0,17,0,1989-05-28 00:00:00 -5927,471,44,0.0,19,0,1989-05-28 00:00:00 -5928,471,46,0.0,13,0,1989-05-28 00:00:00 -5929,471,32,0.0,14,0,1989-05-28 00:00:00 -5930,471,26,0.0,11,0,1989-05-28 00:00:00 -5931,471,31,0.0,12,0,1989-05-28 00:00:00 -5932,471,24,7.0,5,0,1989-05-28 00:00:00 -5933,471,20,4.0,8,0,1989-05-28 00:00:00 -5934,471,21,11.0,2,0,1989-05-28 00:00:00 -5935,471,36,4.0,7,0,1989-05-28 00:00:00 -5936,471,0,47.0,1,3,1989-05-28 00:00:00 -5937,471,5,9.0,3,1,1989-05-28 00:00:00 -5938,471,34,3.0,9,0,1989-05-28 00:00:00 -5939,472,33,5.0,7,0,1989-06-04 00:00:00 -5940,472,47,0.0,18,0,1989-06-04 00:00:00 -5941,472,43,0.0,15,0,1989-06-04 00:00:00 -5942,472,44,0.0,16,0,1989-06-04 00:00:00 -5943,472,42,0.0,20,0,1989-06-04 00:00:00 -5944,472,41,0.0,19,0,1989-06-04 00:00:00 -5945,472,38,1.0,11,0,1989-06-04 00:00:00 -5946,472,17,0.0,17,0,1989-06-04 00:00:00 -5947,472,2,16.0,2,0,1989-06-04 00:00:00 -5948,472,31,0.0,13,0,1989-06-04 00:00:00 -5949,472,34,3.0,9,0,1989-06-04 00:00:00 -5950,472,5,9.0,4,1,1989-06-04 00:00:00 -5951,472,0,56.0,1,4,1989-06-04 00:00:00 -5952,472,36,4.0,8,0,1989-06-04 00:00:00 -5953,472,21,13.0,3,0,1989-06-04 00:00:00 -5954,472,46,3.0,10,0,1989-06-04 00:00:00 -5955,472,24,7.0,6,0,1989-06-04 00:00:00 -5956,472,26,0.0,12,0,1989-06-04 00:00:00 -5957,472,32,0.0,14,0,1989-06-04 00:00:00 -5958,472,20,8.0,5,0,1989-06-04 00:00:00 -5959,473,47,0.0,19,0,1989-06-18 00:00:00 -5960,473,44,0.0,17,0,1989-06-18 00:00:00 -5961,473,38,1.0,13,0,1989-06-18 00:00:00 -5962,473,41,0.0,16,0,1989-06-18 00:00:00 -5963,473,42,0.0,20,0,1989-06-18 00:00:00 -5964,473,17,0.0,18,0,1989-06-18 00:00:00 -5965,473,43,0.0,14,0,1989-06-18 00:00:00 -5966,473,33,5.0,8,0,1989-06-18 00:00:00 -5967,473,2,31.0,2,1,1989-06-18 00:00:00 -5968,473,46,3.0,11,0,1989-06-18 00:00:00 -5969,473,34,8.0,5,0,1989-06-18 00:00:00 -5970,473,32,0.0,15,0,1989-06-18 00:00:00 -5971,473,26,2.0,12,0,1989-06-18 00:00:00 -5972,473,31,3.0,10,0,1989-06-18 00:00:00 -5973,473,24,7.0,7,0,1989-06-18 00:00:00 -5974,473,20,8.0,6,0,1989-06-18 00:00:00 -5975,473,21,13.0,3,0,1989-06-18 00:00:00 -5976,473,36,4.0,9,0,1989-06-18 00:00:00 -5977,473,0,56.0,1,4,1989-06-18 00:00:00 -5978,473,5,9.0,4,1,1989-06-18 00:00:00 -5979,474,47,0.0,19,0,1989-07-09 00:00:00 -5980,474,33,5.0,8,0,1989-07-09 00:00:00 -5981,474,17,0.0,18,0,1989-07-09 00:00:00 -5982,474,44,2.0,13,0,1989-07-09 00:00:00 -5983,474,41,0.0,17,0,1989-07-09 00:00:00 -5984,474,38,1.0,14,0,1989-07-09 00:00:00 -5985,474,2,35.0,2,1,1989-07-09 00:00:00 -5986,474,42,0.0,20,0,1989-07-09 00:00:00 -5987,474,46,3.0,11,0,1989-07-09 00:00:00 -5988,474,43,0.0,16,0,1989-07-09 00:00:00 -5989,474,32,0.0,15,0,1989-07-09 00:00:00 -5990,474,34,8.0,6,0,1989-07-09 00:00:00 -5991,474,5,15.0,3,1,1989-07-09 00:00:00 -5992,474,36,4.0,9,0,1989-07-09 00:00:00 -5993,474,21,13.0,4,0,1989-07-09 00:00:00 -5994,474,0,65.0,1,5,1989-07-09 00:00:00 -5995,474,24,10.0,5,0,1989-07-09 00:00:00 -5996,474,31,3.0,10,0,1989-07-09 00:00:00 -5997,474,26,3.0,12,0,1989-07-09 00:00:00 -5998,474,20,8.0,7,0,1989-07-09 00:00:00 -5999,475,47,0.0,19,0,1989-07-16 00:00:00 -6000,475,41,0.0,18,0,1989-07-16 00:00:00 -6001,475,42,0.0,20,0,1989-07-16 00:00:00 -6002,475,17,3.0,13,0,1989-07-16 00:00:00 -6003,475,43,0.0,17,0,1989-07-16 00:00:00 -6004,475,33,5.0,9,0,1989-07-16 00:00:00 -6005,475,2,35.0,2,1,1989-07-16 00:00:00 -6006,475,31,6.0,8,0,1989-07-16 00:00:00 -6007,475,34,8.0,6,0,1989-07-16 00:00:00 -6008,475,32,0.0,16,0,1989-07-16 00:00:00 -6009,475,26,3.0,12,0,1989-07-16 00:00:00 -6010,475,38,1.0,15,0,1989-07-16 00:00:00 -6011,475,24,10.0,5,0,1989-07-16 00:00:00 -6012,475,20,8.0,7,0,1989-07-16 00:00:00 -6013,475,21,17.0,4,0,1989-07-16 00:00:00 -6014,475,36,4.0,10,0,1989-07-16 00:00:00 -6015,475,46,3.0,11,0,1989-07-16 00:00:00 -6016,475,44,2.0,14,0,1989-07-16 00:00:00 -6017,475,5,21.0,3,1,1989-07-16 00:00:00 -6018,475,0,74.0,1,6,1989-07-16 00:00:00 -6019,476,5,25.0,3,1,1989-07-30 00:00:00 -6020,476,44,2.0,14,0,1989-07-30 00:00:00 -6021,476,38,1.0,15,0,1989-07-30 00:00:00 -6022,476,41,0.0,18,0,1989-07-30 00:00:00 -6023,476,42,0.0,20,0,1989-07-30 00:00:00 -6024,476,17,3.0,13,0,1989-07-30 00:00:00 -6025,476,43,0.0,17,0,1989-07-30 00:00:00 -6026,476,33,5.0,9,0,1989-07-30 00:00:00 -6027,476,0,89.0,1,7,1989-07-30 00:00:00 -6028,476,47,0.0,19,0,1989-07-30 00:00:00 -6029,476,46,3.0,11,0,1989-07-30 00:00:00 -6030,476,34,8.0,7,0,1989-07-30 00:00:00 -6031,476,32,0.0,16,0,1989-07-30 00:00:00 -6032,476,26,3.0,12,0,1989-07-30 00:00:00 -6033,476,31,8.0,8,0,1989-07-30 00:00:00 -6034,476,20,9.0,6,0,1989-07-30 00:00:00 -6035,476,21,17.0,4,0,1989-07-30 00:00:00 -6036,476,36,4.0,10,0,1989-07-30 00:00:00 -6037,476,2,38.0,2,1,1989-07-30 00:00:00 -6038,476,24,10.0,5,0,1989-07-30 00:00:00 -6039,477,33,5.0,9,0,1989-08-13 00:00:00 -6040,477,0,98.0,1,7,1989-08-13 00:00:00 -6041,477,5,34.0,3,2,1989-08-13 00:00:00 -6042,477,44,2.0,14,0,1989-08-13 00:00:00 -6043,477,38,1.0,15,0,1989-08-13 00:00:00 -6044,477,41,0.0,18,0,1989-08-13 00:00:00 -6045,477,42,0.0,20,0,1989-08-13 00:00:00 -6046,477,43,0.0,17,0,1989-08-13 00:00:00 -6047,477,47,0.0,19,0,1989-08-13 00:00:00 -6048,477,2,42.0,2,1,1989-08-13 00:00:00 -6049,477,17,3.0,13,0,1989-08-13 00:00:00 -6050,477,34,8.0,8,0,1989-08-13 00:00:00 -6051,477,46,3.0,11,0,1989-08-13 00:00:00 -6052,477,21,17.0,4,0,1989-08-13 00:00:00 -6053,477,20,11.0,5,0,1989-08-13 00:00:00 -6054,477,24,10.0,6,0,1989-08-13 00:00:00 -6055,477,36,4.0,10,0,1989-08-13 00:00:00 -6056,477,26,3.0,12,0,1989-08-13 00:00:00 -6057,477,32,0.0,16,0,1989-08-13 00:00:00 -6058,477,31,9.0,7,0,1989-08-13 00:00:00 -6059,478,2,45.0,2,1,1989-08-27 00:00:00 -6060,478,44,2.0,14,0,1989-08-27 00:00:00 -6061,478,38,1.0,15,0,1989-08-27 00:00:00 -6062,478,41,0.0,18,0,1989-08-27 00:00:00 -6063,478,42,0.0,20,0,1989-08-27 00:00:00 -6064,478,43,0.0,17,0,1989-08-27 00:00:00 -6065,478,33,5.0,9,0,1989-08-27 00:00:00 -6066,478,47,0.0,19,0,1989-08-27 00:00:00 -6067,478,46,3.0,11,0,1989-08-27 00:00:00 -6068,478,17,3.0,13,0,1989-08-27 00:00:00 -6069,478,32,0.0,16,0,1989-08-27 00:00:00 -6070,478,0,113.0,1,8,1989-08-27 00:00:00 -6071,478,36,4.0,10,0,1989-08-27 00:00:00 -6072,478,21,19.0,4,0,1989-08-27 00:00:00 -6073,478,20,12.0,5,0,1989-08-27 00:00:00 -6074,478,34,8.0,8,0,1989-08-27 00:00:00 -6075,478,24,10.0,6,0,1989-08-27 00:00:00 -6076,478,31,9.0,7,0,1989-08-27 00:00:00 -6077,478,26,3.0,12,0,1989-08-27 00:00:00 -6078,478,5,38.0,3,2,1989-08-27 00:00:00 -6079,479,2,52.0,2,1,1989-09-10 00:00:00 -6080,479,38,1.0,15,0,1989-09-10 00:00:00 -6081,479,41,0.0,18,0,1989-09-10 00:00:00 -6082,479,42,0.0,20,0,1989-09-10 00:00:00 -6083,479,17,3.0,13,0,1989-09-10 00:00:00 -6084,479,43,0.0,17,0,1989-09-10 00:00:00 -6085,479,33,6.0,9,0,1989-09-10 00:00:00 -6086,479,47,0.0,19,0,1989-09-10 00:00:00 -6087,479,44,2.0,14,0,1989-09-10 00:00:00 -6088,479,46,3.0,11,0,1989-09-10 00:00:00 -6089,479,32,0.0,16,0,1989-09-10 00:00:00 -6090,479,26,3.0,12,0,1989-09-10 00:00:00 -6091,479,31,9.0,7,0,1989-09-10 00:00:00 -6092,479,24,12.0,5,0,1989-09-10 00:00:00 -6093,479,20,12.0,6,0,1989-09-10 00:00:00 -6094,479,21,19.0,4,0,1989-09-10 00:00:00 -6095,479,36,4.0,10,0,1989-09-10 00:00:00 -6096,479,0,122.0,1,9,1989-09-10 00:00:00 -6097,479,5,44.0,3,2,1989-09-10 00:00:00 -6098,479,34,8.0,8,0,1989-09-10 00:00:00 -6099,480,33,6.0,10,0,1989-09-24 00:00:00 -6100,480,43,0.0,17,0,1989-09-24 00:00:00 -6101,480,17,5.0,11,0,1989-09-24 00:00:00 -6102,480,47,0.0,19,0,1989-09-24 00:00:00 -6103,480,41,0.0,18,0,1989-09-24 00:00:00 -6104,480,38,1.0,15,0,1989-09-24 00:00:00 -6105,480,44,6.0,9,0,1989-09-24 00:00:00 -6106,480,42,0.0,20,0,1989-09-24 00:00:00 -6107,480,2,52.0,3,1,1989-09-24 00:00:00 -6108,480,24,13.0,5,0,1989-09-24 00:00:00 -6109,480,34,8.0,8,0,1989-09-24 00:00:00 -6110,480,0,128.0,1,9,1989-09-24 00:00:00 -6111,480,36,4.0,12,0,1989-09-24 00:00:00 -6112,480,21,22.0,4,0,1989-09-24 00:00:00 -6113,480,20,12.0,6,0,1989-09-24 00:00:00 -6114,480,46,3.0,13,0,1989-09-24 00:00:00 -6115,480,31,9.0,7,0,1989-09-24 00:00:00 -6116,480,26,3.0,14,0,1989-09-24 00:00:00 -6117,480,32,0.0,16,0,1989-09-24 00:00:00 -6118,480,5,53.0,2,3,1989-09-24 00:00:00 -6119,481,47,0.0,19,0,1989-10-01 00:00:00 -6120,481,44,6.0,9,0,1989-10-01 00:00:00 -6121,481,38,1.0,15,0,1989-10-01 00:00:00 -6122,481,41,0.0,18,0,1989-10-01 00:00:00 -6123,481,42,0.0,20,0,1989-10-01 00:00:00 -6124,481,17,5.0,11,0,1989-10-01 00:00:00 -6125,481,43,0.0,17,0,1989-10-01 00:00:00 -6126,481,33,6.0,10,0,1989-10-01 00:00:00 -6127,481,2,54.0,3,1,1989-10-01 00:00:00 -6128,481,46,3.0,13,0,1989-10-01 00:00:00 -6129,481,34,8.0,8,0,1989-10-01 00:00:00 -6130,481,0,141.0,1,10,1989-10-01 00:00:00 -6131,481,36,4.0,12,0,1989-10-01 00:00:00 -6132,481,21,22.0,4,0,1989-10-01 00:00:00 -6133,481,20,12.0,6,0,1989-10-01 00:00:00 -6134,481,5,59.0,2,3,1989-10-01 00:00:00 -6135,481,31,9.0,7,0,1989-10-01 00:00:00 -6136,481,26,3.0,14,0,1989-10-01 00:00:00 -6137,481,32,1.0,16,0,1989-10-01 00:00:00 -6138,481,24,16.0,5,0,1989-10-01 00:00:00 -6139,482,43,0.0,17,0,1989-10-22 00:00:00 -6140,482,38,1.0,15,0,1989-10-22 00:00:00 -6141,482,0,141.0,1,10,1989-10-22 00:00:00 -6142,482,5,59.0,3,3,1989-10-22 00:00:00 -6143,482,36,4.0,12,0,1989-10-22 00:00:00 -6144,482,21,31.0,4,1,1989-10-22 00:00:00 -6145,482,20,13.0,6,0,1989-10-22 00:00:00 -6146,482,42,0.0,20,0,1989-10-22 00:00:00 -6147,482,17,5.0,11,0,1989-10-22 00:00:00 -6148,482,33,8.0,9,0,1989-10-22 00:00:00 -6149,482,41,0.0,18,0,1989-10-22 00:00:00 -6150,482,2,64.0,2,1,1989-10-22 00:00:00 -6151,482,46,3.0,13,0,1989-10-22 00:00:00 -6152,482,34,8.0,8,0,1989-10-22 00:00:00 -6153,482,32,1.0,16,0,1989-10-22 00:00:00 -6154,482,26,3.0,14,0,1989-10-22 00:00:00 -6155,482,31,12.0,7,0,1989-10-22 00:00:00 -6156,482,24,16.0,5,0,1989-10-22 00:00:00 -6157,482,44,6.0,10,0,1989-10-22 00:00:00 -6158,482,47,0.0,19,0,1989-10-22 00:00:00 -6159,483,47,0.0,19,0,1989-11-05 00:00:00 -6160,483,33,8.0,9,0,1989-11-05 00:00:00 -6161,483,43,0.0,17,0,1989-11-05 00:00:00 -6162,483,38,1.0,15,0,1989-11-05 00:00:00 -6163,483,42,0.0,20,0,1989-11-05 00:00:00 -6164,483,41,0.0,18,0,1989-11-05 00:00:00 -6165,483,44,6.0,10,0,1989-11-05 00:00:00 -6166,483,17,6.0,11,0,1989-11-05 00:00:00 -6167,483,2,77.0,2,2,1989-11-05 00:00:00 -6168,483,26,3.0,14,0,1989-11-05 00:00:00 -6169,483,34,8.0,8,0,1989-11-05 00:00:00 -6170,483,0,141.0,1,10,1989-11-05 00:00:00 -6171,483,5,59.0,3,3,1989-11-05 00:00:00 -6172,483,36,4.0,12,0,1989-11-05 00:00:00 -6173,483,21,39.0,4,1,1989-11-05 00:00:00 -6174,483,46,3.0,13,0,1989-11-05 00:00:00 -6175,483,24,16.0,5,0,1989-11-05 00:00:00 -6176,483,31,15.0,6,0,1989-11-05 00:00:00 -6177,483,32,1.0,16,0,1989-11-05 00:00:00 -6178,483,20,13.0,7,0,1989-11-05 00:00:00 -6179,484,31,0.0,14,0,1990-03-11 00:00:00 -6180,484,26,0.0,15,0,1990-03-11 00:00:00 -6181,484,44,0.0,16,0,1990-03-11 00:00:00 -6182,484,38,0.0,17,0,1990-03-11 00:00:00 -6183,484,45,0.0,18,0,1990-03-11 00:00:00 -6184,484,41,0.0,19,0,1990-03-11 00:00:00 -6185,484,0,9.0,1,1,1990-03-11 00:00:00 -6186,484,2,4.0,3,0,1990-03-11 00:00:00 -6187,484,43,0.0,12,0,1990-03-11 00:00:00 -6188,484,21,3.0,4,0,1990-03-11 00:00:00 -6189,484,33,2.0,5,0,1990-03-11 00:00:00 -6190,484,17,0.0,6,0,1990-03-11 00:00:00 -6191,484,32,0.0,7,0,1990-03-11 00:00:00 -6192,484,20,0.0,8,0,1990-03-11 00:00:00 -6193,484,42,0.0,9,0,1990-03-11 00:00:00 -6194,484,40,0.0,10,0,1990-03-11 00:00:00 -6195,484,24,7.0,2,0,1990-03-11 00:00:00 -6196,484,5,0.0,11,0,1990-03-11 00:00:00 -6197,484,34,0.0,13,0,1990-03-11 00:00:00 -6198,485,40,0.0,13,0,1990-03-25 00:00:00 -6199,485,34,0.0,12,0,1990-03-25 00:00:00 -6200,485,43,0.0,16,0,1990-03-25 00:00:00 -6201,485,41,0.0,18,0,1990-03-25 00:00:00 -6202,485,42,0.0,11,0,1990-03-25 00:00:00 -6203,485,38,0.0,15,0,1990-03-25 00:00:00 -6204,485,44,0.0,17,0,1990-03-25 00:00:00 -6205,485,26,0.0,10,0,1990-03-25 00:00:00 -6206,485,31,0.0,14,0,1990-03-25 00:00:00 -6207,485,45,0.0,19,0,1990-03-25 00:00:00 -6208,485,5,12.0,2,1,1990-03-25 00:00:00 -6209,485,24,7.0,3,0,1990-03-25 00:00:00 -6210,485,2,6.0,4,0,1990-03-25 00:00:00 -6211,485,21,4.0,5,0,1990-03-25 00:00:00 -6212,485,33,2.0,6,0,1990-03-25 00:00:00 -6213,485,17,0.0,7,0,1990-03-25 00:00:00 -6214,485,32,0.0,8,0,1990-03-25 00:00:00 -6215,485,20,0.0,9,0,1990-03-25 00:00:00 -6216,485,0,19.0,1,1,1990-03-25 00:00:00 -6217,486,24,8.0,5,0,1990-05-13 00:00:00 -6218,486,33,2.0,6,0,1990-05-13 00:00:00 -6219,486,17,0.0,8,0,1990-05-13 00:00:00 -6220,486,32,0.0,9,0,1990-05-13 00:00:00 -6221,486,20,0.0,11,0,1990-05-13 00:00:00 -6222,486,26,0.0,10,0,1990-05-13 00:00:00 -6223,486,40,0.0,15,0,1990-05-13 00:00:00 -6224,486,5,15.0,3,1,1990-05-13 00:00:00 -6225,486,43,0.0,16,0,1990-05-13 00:00:00 -6226,486,31,0.0,7,0,1990-05-13 00:00:00 -6227,486,0,25.0,1,1,1990-05-13 00:00:00 -6228,486,42,0.0,13,0,1990-05-13 00:00:00 -6229,486,34,0.0,14,0,1990-05-13 00:00:00 -6230,486,2,15.0,2,1,1990-05-13 00:00:00 -6231,486,21,10.0,4,0,1990-05-13 00:00:00 -6232,486,41,0.0,18,0,1990-05-13 00:00:00 -6233,486,45,0.0,19,0,1990-05-13 00:00:00 -6234,486,38,0.0,17,0,1990-05-13 00:00:00 -6235,486,44,0.0,12,0,1990-05-13 00:00:00 -6236,487,45,0.0,19,0,1990-05-27 00:00:00 -6237,487,44,0.0,11,0,1990-05-27 00:00:00 -6238,487,26,0.0,12,0,1990-05-27 00:00:00 -6239,487,31,0.0,9,0,1990-05-27 00:00:00 -6240,487,34,0.0,14,0,1990-05-27 00:00:00 -6241,487,43,0.0,16,0,1990-05-27 00:00:00 -6242,487,5,15.0,3,1,1990-05-27 00:00:00 -6243,487,40,0.0,15,0,1990-05-27 00:00:00 -6244,487,42,0.0,13,0,1990-05-27 00:00:00 -6245,487,20,2.0,6,0,1990-05-27 00:00:00 -6246,487,32,1.0,8,0,1990-05-27 00:00:00 -6247,487,17,0.0,10,0,1990-05-27 00:00:00 -6248,487,33,2.0,7,0,1990-05-27 00:00:00 -6249,487,21,10.0,5,0,1990-05-27 00:00:00 -6250,487,2,18.0,2,1,1990-05-27 00:00:00 -6251,487,24,14.0,4,0,1990-05-27 00:00:00 -6252,487,0,38.0,1,2,1990-05-27 00:00:00 -6253,487,38,0.0,17,0,1990-05-27 00:00:00 -6254,487,41,0.0,18,0,1990-05-27 00:00:00 -6255,488,17,0.0,10,0,1990-06-10 00:00:00 -6256,488,33,2.0,6,0,1990-06-10 00:00:00 -6257,488,21,16.0,4,0,1990-06-10 00:00:00 -6258,488,2,18.0,3,1,1990-06-10 00:00:00 -6259,488,24,14.0,5,0,1990-06-10 00:00:00 -6260,488,0,50.0,1,3,1990-06-10 00:00:00 -6261,488,42,0.0,15,0,1990-06-10 00:00:00 -6262,488,38,0.0,17,0,1990-06-10 00:00:00 -6263,488,40,0.0,13,0,1990-06-10 00:00:00 -6264,488,32,1.0,9,0,1990-06-10 00:00:00 -6265,488,5,21.0,2,1,1990-06-10 00:00:00 -6266,488,43,0.0,14,0,1990-06-10 00:00:00 -6267,488,34,0.0,16,0,1990-06-10 00:00:00 -6268,488,31,1.0,8,0,1990-06-10 00:00:00 -6269,488,20,2.0,7,0,1990-06-10 00:00:00 -6270,488,44,0.0,11,0,1990-06-10 00:00:00 -6271,488,45,0.0,19,0,1990-06-10 00:00:00 -6272,488,41,0.0,18,0,1990-06-10 00:00:00 -6273,488,26,0.0,12,0,1990-06-10 00:00:00 -6274,489,0,54.0,1,3,1990-06-24 00:00:00 -6275,489,2,20.0,3,1,1990-06-24 00:00:00 -6276,489,21,20.0,4,0,1990-06-24 00:00:00 -6277,489,33,2.0,6,0,1990-06-24 00:00:00 -6278,489,17,0.0,10,0,1990-06-24 00:00:00 -6279,489,32,1.0,9,0,1990-06-24 00:00:00 -6280,489,20,2.0,7,0,1990-06-24 00:00:00 -6281,489,40,0.0,13,0,1990-06-24 00:00:00 -6282,489,5,36.0,2,2,1990-06-24 00:00:00 -6283,489,43,0.0,15,0,1990-06-24 00:00:00 -6284,489,34,0.0,14,0,1990-06-24 00:00:00 -6285,489,26,0.0,12,0,1990-06-24 00:00:00 -6286,489,44,0.0,11,0,1990-06-24 00:00:00 -6287,489,38,0.0,17,0,1990-06-24 00:00:00 -6288,489,45,0.0,19,0,1990-06-24 00:00:00 -6289,489,41,0.0,18,0,1990-06-24 00:00:00 -6290,489,42,0.0,16,0,1990-06-24 00:00:00 -6291,489,31,1.0,8,0,1990-06-24 00:00:00 -6292,489,24,14.0,5,0,1990-06-24 00:00:00 -6293,490,45,0.0,19,0,1990-07-08 00:00:00 -6294,490,0,60.0,1,3,1990-07-08 00:00:00 -6295,490,2,21.0,4,1,1990-07-08 00:00:00 -6296,490,21,23.0,3,0,1990-07-08 00:00:00 -6297,490,33,2.0,7,0,1990-07-08 00:00:00 -6298,490,17,0.0,11,0,1990-07-08 00:00:00 -6299,490,41,0.0,18,0,1990-07-08 00:00:00 -6300,490,20,2.0,8,0,1990-07-08 00:00:00 -6301,490,42,0.0,16,0,1990-07-08 00:00:00 -6302,490,32,1.0,9,0,1990-07-08 00:00:00 -6303,490,5,45.0,2,3,1990-07-08 00:00:00 -6304,490,43,0.0,15,0,1990-07-08 00:00:00 -6305,490,34,0.0,14,0,1990-07-08 00:00:00 -6306,490,31,1.0,10,0,1990-07-08 00:00:00 -6307,490,26,0.0,13,0,1990-07-08 00:00:00 -6308,490,44,0.0,12,0,1990-07-08 00:00:00 -6309,490,38,0.0,17,0,1990-07-08 00:00:00 -6310,490,40,6.0,6,0,1990-07-08 00:00:00 -6311,490,24,14.0,5,0,1990-07-08 00:00:00 -6312,491,34,0.0,14,0,1990-07-15 00:00:00 -6313,491,31,1.0,10,0,1990-07-15 00:00:00 -6314,491,26,0.0,13,0,1990-07-15 00:00:00 -6315,491,44,0.0,12,0,1990-07-15 00:00:00 -6316,491,38,0.0,17,0,1990-07-15 00:00:00 -6317,491,43,0.0,15,0,1990-07-15 00:00:00 -6318,491,40,6.0,6,0,1990-07-15 00:00:00 -6319,491,20,2.0,8,0,1990-07-15 00:00:00 -6320,491,45,0.0,19,0,1990-07-15 00:00:00 -6321,491,0,64.0,1,3,1990-07-15 00:00:00 -6322,491,24,14.0,5,0,1990-07-15 00:00:00 -6323,491,2,27.0,3,1,1990-07-15 00:00:00 -6324,491,42,0.0,16,0,1990-07-15 00:00:00 -6325,491,32,5.0,7,0,1990-07-15 00:00:00 -6326,491,17,0.0,11,0,1990-07-15 00:00:00 -6327,491,33,2.0,9,0,1990-07-15 00:00:00 -6328,491,21,25.0,4,0,1990-07-15 00:00:00 -6329,491,41,0.0,18,0,1990-07-15 00:00:00 -6330,491,5,54.0,2,4,1990-07-15 00:00:00 -6331,492,45,0.0,19,0,1990-07-29 00:00:00 -6332,492,41,0.0,18,0,1990-07-29 00:00:00 -6333,492,0,77.0,1,4,1990-07-29 00:00:00 -6334,492,2,30.0,4,1,1990-07-29 00:00:00 -6335,492,21,31.0,3,0,1990-07-29 00:00:00 -6336,492,38,0.0,17,0,1990-07-29 00:00:00 -6337,492,44,0.0,12,0,1990-07-29 00:00:00 -6338,492,26,0.0,13,0,1990-07-29 00:00:00 -6339,492,34,0.0,14,0,1990-07-29 00:00:00 -6340,492,43,0.0,15,0,1990-07-29 00:00:00 -6341,492,24,14.0,5,0,1990-07-29 00:00:00 -6342,492,31,1.0,10,0,1990-07-29 00:00:00 -6343,492,40,6.0,6,0,1990-07-29 00:00:00 -6344,492,42,0.0,16,0,1990-07-29 00:00:00 -6345,492,20,2.0,8,0,1990-07-29 00:00:00 -6346,492,32,5.0,7,0,1990-07-29 00:00:00 -6347,492,17,0.0,11,0,1990-07-29 00:00:00 -6348,492,33,2.0,9,0,1990-07-29 00:00:00 -6349,492,5,57.0,2,4,1990-07-29 00:00:00 -6350,493,45,0.0,19,0,1990-08-12 00:00:00 -6351,493,41,0.0,18,0,1990-08-12 00:00:00 -6352,493,42,0.0,17,0,1990-08-12 00:00:00 -6353,493,20,2.0,9,0,1990-08-12 00:00:00 -6354,493,38,0.0,15,0,1990-08-12 00:00:00 -6355,493,44,0.0,12,0,1990-08-12 00:00:00 -6356,493,26,0.0,13,0,1990-08-12 00:00:00 -6357,493,24,14.0,5,0,1990-08-12 00:00:00 -6358,493,2,42.0,3,2,1990-08-12 00:00:00 -6359,493,21,35.0,4,0,1990-08-12 00:00:00 -6360,493,33,2.0,10,0,1990-08-12 00:00:00 -6361,493,17,0.0,11,0,1990-08-12 00:00:00 -6362,493,32,6.0,7,0,1990-08-12 00:00:00 -6363,493,0,83.0,1,4,1990-08-12 00:00:00 -6364,493,40,6.0,6,0,1990-08-12 00:00:00 -6365,493,31,3.0,8,0,1990-08-12 00:00:00 -6366,493,5,57.0,2,4,1990-08-12 00:00:00 -6367,493,43,0.0,16,0,1990-08-12 00:00:00 -6368,493,34,0.0,14,0,1990-08-12 00:00:00 -6369,494,0,96.0,1,5,1990-08-26 00:00:00 -6370,494,21,40.0,4,0,1990-08-26 00:00:00 -6371,494,2,42.0,3,2,1990-08-26 00:00:00 -6372,494,24,14.0,5,0,1990-08-26 00:00:00 -6373,494,45,0.0,19,0,1990-08-26 00:00:00 -6374,494,41,0.0,18,0,1990-08-26 00:00:00 -6375,494,38,0.0,16,0,1990-08-26 00:00:00 -6376,494,31,3.0,8,0,1990-08-26 00:00:00 -6377,494,33,2.0,10,0,1990-08-26 00:00:00 -6378,494,17,0.0,11,0,1990-08-26 00:00:00 -6379,494,32,6.0,7,0,1990-08-26 00:00:00 -6380,494,20,2.0,9,0,1990-08-26 00:00:00 -6381,494,42,0.0,17,0,1990-08-26 00:00:00 -6382,494,40,7.0,6,0,1990-08-26 00:00:00 -6383,494,5,63.0,2,4,1990-08-26 00:00:00 -6384,494,43,0.0,15,0,1990-08-26 00:00:00 -6385,494,34,0.0,14,0,1990-08-26 00:00:00 -6386,494,26,0.0,13,0,1990-08-26 00:00:00 -6387,494,44,0.0,12,0,1990-08-26 00:00:00 -6388,495,32,6.0,7,0,1990-09-09 00:00:00 -6389,495,17,0.0,11,0,1990-09-09 00:00:00 -6390,495,33,2.0,10,0,1990-09-09 00:00:00 -6391,495,24,15.0,5,0,1990-09-09 00:00:00 -6392,495,21,40.0,4,0,1990-09-09 00:00:00 -6393,495,0,109.0,1,6,1990-09-09 00:00:00 -6394,495,2,44.0,3,2,1990-09-09 00:00:00 -6395,495,20,2.0,9,0,1990-09-09 00:00:00 -6396,495,42,0.0,17,0,1990-09-09 00:00:00 -6397,495,44,0.0,12,0,1990-09-09 00:00:00 -6398,495,5,72.0,2,4,1990-09-09 00:00:00 -6399,495,43,0.0,15,0,1990-09-09 00:00:00 -6400,495,34,0.0,14,0,1990-09-09 00:00:00 -6401,495,31,3.0,8,0,1990-09-09 00:00:00 -6402,495,26,0.0,13,0,1990-09-09 00:00:00 -6403,495,38,0.0,16,0,1990-09-09 00:00:00 -6404,495,45,0.0,19,0,1990-09-09 00:00:00 -6405,495,41,0.0,18,0,1990-09-09 00:00:00 -6406,495,40,7.0,6,0,1990-09-09 00:00:00 -6407,496,0,118.0,1,6,1990-09-23 00:00:00 -6408,496,24,15.0,5,0,1990-09-23 00:00:00 -6409,496,2,44.0,3,2,1990-09-23 00:00:00 -6410,496,20,2.0,9,0,1990-09-23 00:00:00 -6411,496,33,2.0,10,0,1990-09-23 00:00:00 -6412,496,32,6.0,7,0,1990-09-23 00:00:00 -6413,496,21,43.0,4,0,1990-09-23 00:00:00 -6414,496,42,0.0,17,0,1990-09-23 00:00:00 -6415,496,17,0.0,11,0,1990-09-23 00:00:00 -6416,496,5,85.0,2,5,1990-09-23 00:00:00 -6417,496,43,0.0,15,0,1990-09-23 00:00:00 -6418,496,34,0.0,14,0,1990-09-23 00:00:00 -6419,496,31,3.0,8,0,1990-09-23 00:00:00 -6420,496,26,0.0,13,0,1990-09-23 00:00:00 -6421,496,44,0.0,12,0,1990-09-23 00:00:00 -6422,496,38,0.0,16,0,1990-09-23 00:00:00 -6423,496,45,0.0,19,0,1990-09-23 00:00:00 -6424,496,41,0.0,18,0,1990-09-23 00:00:00 -6425,496,40,7.0,6,0,1990-09-23 00:00:00 -6426,497,31,3.0,8,0,1990-09-30 00:00:00 -6427,497,34,0.0,15,0,1990-09-30 00:00:00 -6428,497,43,0.0,16,0,1990-09-30 00:00:00 -6429,497,5,100.0,2,6,1990-09-30 00:00:00 -6430,497,40,7.0,6,0,1990-09-30 00:00:00 -6431,497,42,0.0,17,0,1990-09-30 00:00:00 -6432,497,33,2.0,10,0,1990-09-30 00:00:00 -6433,497,32,7.0,7,0,1990-09-30 00:00:00 -6434,497,17,0.0,12,0,1990-09-30 00:00:00 -6435,497,24,15.0,5,0,1990-09-30 00:00:00 -6436,497,21,47.0,4,0,1990-09-30 00:00:00 -6437,497,2,49.0,3,2,1990-09-30 00:00:00 -6438,497,20,2.0,9,0,1990-09-30 00:00:00 -6439,497,44,0.0,13,0,1990-09-30 00:00:00 -6440,497,26,0.0,11,0,1990-09-30 00:00:00 -6441,497,0,118.0,1,6,1990-09-30 00:00:00 -6442,497,45,0.0,19,0,1990-09-30 00:00:00 -6443,497,41,0.0,18,0,1990-09-30 00:00:00 -6444,497,38,0.0,14,0,1990-09-30 00:00:00 -6445,498,38,0.0,14,0,1990-10-21 00:00:00 -6446,498,44,0.0,13,0,1990-10-21 00:00:00 -6447,498,26,0.0,11,0,1990-10-21 00:00:00 -6448,498,31,3.0,8,0,1990-10-21 00:00:00 -6449,498,34,0.0,15,0,1990-10-21 00:00:00 -6450,498,43,0.0,16,0,1990-10-21 00:00:00 -6451,498,5,100.0,2,6,1990-10-21 00:00:00 -6452,498,40,7.0,7,0,1990-10-21 00:00:00 -6453,498,17,0.0,12,0,1990-10-21 00:00:00 -6454,498,20,2.0,9,0,1990-10-21 00:00:00 -6455,498,32,11.0,6,0,1990-10-21 00:00:00 -6456,498,41,0.0,18,0,1990-10-21 00:00:00 -6457,498,0,118.0,1,6,1990-10-21 00:00:00 -6458,498,24,16.0,5,0,1990-10-21 00:00:00 -6459,498,2,54.0,4,2,1990-10-21 00:00:00 -6460,498,21,62.0,3,1,1990-10-21 00:00:00 -6461,498,33,2.0,10,0,1990-10-21 00:00:00 -6462,498,45,0.0,19,0,1990-10-21 00:00:00 -6463,498,42,0.0,17,0,1990-10-21 00:00:00 -6464,499,26,0.0,11,0,1990-11-04 00:00:00 -6465,499,44,0.0,13,0,1990-11-04 00:00:00 -6466,499,38,0.0,14,0,1990-11-04 00:00:00 -6467,499,31,3.0,8,0,1990-11-04 00:00:00 -6468,499,2,57.0,4,2,1990-11-04 00:00:00 -6469,499,5,110.0,2,6,1990-11-04 00:00:00 -6470,499,40,7.0,7,0,1990-11-04 00:00:00 -6471,499,42,0.0,17,0,1990-11-04 00:00:00 -6472,499,20,2.0,9,0,1990-11-04 00:00:00 -6473,499,32,11.0,6,0,1990-11-04 00:00:00 -6474,499,17,0.0,12,0,1990-11-04 00:00:00 -6475,499,33,2.0,10,0,1990-11-04 00:00:00 -6476,499,21,71.0,3,2,1990-11-04 00:00:00 -6477,499,24,16.0,5,0,1990-11-04 00:00:00 -6478,499,0,121.0,1,6,1990-11-04 00:00:00 -6479,499,43,0.0,16,0,1990-11-04 00:00:00 -6480,499,34,0.0,15,0,1990-11-04 00:00:00 -6481,499,45,0.0,19,0,1990-11-04 00:00:00 -6482,499,41,0.0,18,0,1990-11-04 00:00:00 -6483,500,16,0.0,9,0,1991-03-10 00:00:00 -6484,500,40,0.0,14,0,1991-03-10 00:00:00 -6485,500,33,0.0,10,0,1991-03-10 00:00:00 -6486,500,31,0.0,11,0,1991-03-10 00:00:00 -6487,500,2,0.0,12,0,1991-03-10 00:00:00 -6488,500,28,0.0,13,0,1991-03-10 00:00:00 -6489,500,41,0.0,17,0,1991-03-10 00:00:00 -6490,500,26,0.0,15,0,1991-03-10 00:00:00 -6491,500,34,0.0,16,0,1991-03-10 00:00:00 -6492,500,38,0.0,7,0,1991-03-10 00:00:00 -6493,500,0,10.0,1,1,1991-03-10 00:00:00 -6494,500,5,6.0,2,0,1991-03-10 00:00:00 -6495,500,21,4.0,4,0,1991-03-10 00:00:00 -6496,500,24,5.0,3,0,1991-03-10 00:00:00 -6497,500,32,1.0,5,0,1991-03-10 00:00:00 -6498,500,39,0.0,6,0,1991-03-10 00:00:00 -6499,500,35,0.0,18,0,1991-03-10 00:00:00 -6500,500,17,0.0,8,0,1991-03-10 00:00:00 -6501,501,33,0.0,13,0,1991-03-24 00:00:00 -6502,501,0,24.0,1,2,1991-03-24 00:00:00 -6503,501,5,10.0,2,0,1991-03-24 00:00:00 -6504,501,21,6.0,4,0,1991-03-24 00:00:00 -6505,501,24,5.0,5,0,1991-03-24 00:00:00 -6506,501,35,0.0,17,0,1991-03-24 00:00:00 -6507,501,31,0.0,10,0,1991-03-24 00:00:00 -6508,501,34,0.0,14,0,1991-03-24 00:00:00 -6509,501,41,0.0,18,0,1991-03-24 00:00:00 -6510,501,40,0.0,16,0,1991-03-24 00:00:00 -6511,501,28,0.0,15,0,1991-03-24 00:00:00 -6512,501,2,6.0,3,0,1991-03-24 00:00:00 -6513,501,39,0.0,7,0,1991-03-24 00:00:00 -6514,501,38,0.0,9,0,1991-03-24 00:00:00 -6515,501,17,0.0,8,0,1991-03-24 00:00:00 -6516,501,16,0.0,11,0,1991-03-24 00:00:00 -6517,501,26,0.0,12,0,1991-03-24 00:00:00 -6518,501,32,1.0,6,0,1991-03-24 00:00:00 -6519,502,24,5.0,5,0,1991-04-28 00:00:00 -6520,502,5,10.0,2,0,1991-04-28 00:00:00 -6521,502,0,40.0,1,3,1991-04-28 00:00:00 -6522,502,21,6.0,4,0,1991-04-28 00:00:00 -6523,502,34,4.0,6,0,1991-04-28 00:00:00 -6524,502,39,0.0,10,0,1991-04-28 00:00:00 -6525,502,25,0.0,17,0,1991-04-28 00:00:00 -6526,502,26,0.0,11,0,1991-04-28 00:00:00 -6527,502,40,0.0,15,0,1991-04-28 00:00:00 -6528,502,28,0.0,16,0,1991-04-28 00:00:00 -6529,502,2,6.0,3,0,1991-04-28 00:00:00 -6530,502,31,3.0,8,0,1991-04-28 00:00:00 -6531,502,33,0.0,12,0,1991-04-28 00:00:00 -6532,502,16,0.0,14,0,1991-04-28 00:00:00 -6533,502,17,3.0,7,0,1991-04-28 00:00:00 -6534,502,38,0.0,13,0,1991-04-28 00:00:00 -6535,502,32,1.0,9,0,1991-04-28 00:00:00 -6536,502,35,0.0,18,0,1991-04-28 00:00:00 -6537,502,41,0.0,19,0,1991-04-28 00:00:00 -6538,503,21,9.0,4,0,1991-05-12 00:00:00 -6539,503,5,16.0,2,0,1991-05-12 00:00:00 -6540,503,0,50.0,1,4,1991-05-12 00:00:00 -6541,503,35,0.0,18,0,1991-05-12 00:00:00 -6542,503,32,1.0,9,0,1991-05-12 00:00:00 -6543,503,41,0.0,19,0,1991-05-12 00:00:00 -6544,503,34,5.0,5,0,1991-05-12 00:00:00 -6545,503,26,0.0,10,0,1991-05-12 00:00:00 -6546,503,40,0.0,16,0,1991-05-12 00:00:00 -6547,503,24,5.0,6,0,1991-05-12 00:00:00 -6548,503,2,12.0,3,0,1991-05-12 00:00:00 -6549,503,28,0.0,17,0,1991-05-12 00:00:00 -6550,503,33,0.0,13,0,1991-05-12 00:00:00 -6551,503,16,0.0,12,0,1991-05-12 00:00:00 -6552,503,17,3.0,7,0,1991-05-12 00:00:00 -6553,503,38,0.0,14,0,1991-05-12 00:00:00 -6554,503,39,0.0,11,0,1991-05-12 00:00:00 -6555,503,31,3.0,8,0,1991-05-12 00:00:00 -6556,503,25,0.0,15,0,1991-05-12 00:00:00 -6557,504,21,19.0,2,1,1991-06-02 00:00:00 -6558,504,5,16.0,4,0,1991-06-02 00:00:00 -6559,504,0,50.0,1,4,1991-06-02 00:00:00 -6560,504,24,11.0,5,0,1991-06-02 00:00:00 -6561,504,16,5.0,7,0,1991-06-02 00:00:00 -6562,504,32,1.0,10,0,1991-06-02 00:00:00 -6563,504,39,0.0,12,0,1991-06-02 00:00:00 -6564,504,38,0.0,14,0,1991-06-02 00:00:00 -6565,504,17,3.0,8,0,1991-06-02 00:00:00 -6566,504,33,0.0,13,0,1991-06-02 00:00:00 -6567,504,31,3.0,9,0,1991-06-02 00:00:00 -6568,504,2,17.0,3,0,1991-06-02 00:00:00 -6569,504,40,0.0,16,0,1991-06-02 00:00:00 -6570,504,26,0.0,11,0,1991-06-02 00:00:00 -6571,504,34,5.0,6,0,1991-06-02 00:00:00 -6572,504,41,0.0,19,0,1991-06-02 00:00:00 -6573,504,35,0.0,18,0,1991-06-02 00:00:00 -6574,504,25,0.0,15,0,1991-06-02 00:00:00 -6575,504,28,0.0,17,0,1991-06-02 00:00:00 -6576,505,21,21.0,3,1,1991-06-16 00:00:00 -6577,505,0,54.0,1,4,1991-06-16 00:00:00 -6578,505,41,0.0,19,0,1991-06-16 00:00:00 -6579,505,28,0.0,17,0,1991-06-16 00:00:00 -6580,505,25,1.0,10,0,1991-06-16 00:00:00 -6581,505,5,16.0,4,0,1991-06-16 00:00:00 -6582,505,35,0.0,18,0,1991-06-16 00:00:00 -6583,505,40,0.0,16,0,1991-06-16 00:00:00 -6584,505,32,1.0,11,0,1991-06-16 00:00:00 -6585,505,2,33.0,2,1,1991-06-16 00:00:00 -6586,505,31,3.0,9,0,1991-06-16 00:00:00 -6587,505,33,0.0,14,0,1991-06-16 00:00:00 -6588,505,16,8.0,6,0,1991-06-16 00:00:00 -6589,505,17,3.0,8,0,1991-06-16 00:00:00 -6590,505,38,0.0,15,0,1991-06-16 00:00:00 -6591,505,39,0.0,13,0,1991-06-16 00:00:00 -6592,505,26,0.0,12,0,1991-06-16 00:00:00 -6593,505,24,11.0,5,0,1991-06-16 00:00:00 -6594,505,34,5.0,7,0,1991-06-16 00:00:00 -6595,506,39,0.0,13,0,1991-07-07 00:00:00 -6596,506,24,11.0,5,0,1991-07-07 00:00:00 -6597,506,25,1.0,10,0,1991-07-07 00:00:00 -6598,506,35,0.0,18,0,1991-07-07 00:00:00 -6599,506,41,0.0,19,0,1991-07-07 00:00:00 -6600,506,34,5.0,7,0,1991-07-07 00:00:00 -6601,506,26,0.0,12,0,1991-07-07 00:00:00 -6602,506,28,0.0,17,0,1991-07-07 00:00:00 -6603,506,2,45.0,2,2,1991-07-07 00:00:00 -6604,506,31,3.0,9,0,1991-07-07 00:00:00 -6605,506,33,0.0,15,0,1991-07-07 00:00:00 -6606,506,16,9.0,6,0,1991-07-07 00:00:00 -6607,506,17,3.0,8,0,1991-07-07 00:00:00 -6608,506,21,21.0,4,1,1991-07-07 00:00:00 -6609,506,0,58.0,1,4,1991-07-07 00:00:00 -6610,506,5,25.0,3,0,1991-07-07 00:00:00 -6611,506,38,0.0,16,0,1991-07-07 00:00:00 -6612,506,32,1.0,11,0,1991-07-07 00:00:00 -6613,506,40,0.0,14,0,1991-07-07 00:00:00 -6614,507,21,23.0,4,1,1991-07-14 00:00:00 -6615,507,5,29.0,3,0,1991-07-14 00:00:00 -6616,507,0,67.0,1,4,1991-07-14 00:00:00 -6617,507,2,55.0,2,3,1991-07-14 00:00:00 -6618,507,33,0.0,15,0,1991-07-14 00:00:00 -6619,507,39,0.0,13,0,1991-07-14 00:00:00 -6620,507,38,0.0,16,0,1991-07-14 00:00:00 -6621,507,17,3.0,8,0,1991-07-14 00:00:00 -6622,507,16,10.0,6,0,1991-07-14 00:00:00 -6623,507,31,3.0,9,0,1991-07-14 00:00:00 -6624,507,40,0.0,14,0,1991-07-14 00:00:00 -6625,507,28,0.0,17,0,1991-07-14 00:00:00 -6626,507,34,5.0,7,0,1991-07-14 00:00:00 -6627,507,41,0.0,19,0,1991-07-14 00:00:00 -6628,507,35,0.0,18,0,1991-07-14 00:00:00 -6629,507,25,1.0,10,0,1991-07-14 00:00:00 -6630,507,32,1.0,11,0,1991-07-14 00:00:00 -6631,507,26,0.0,12,0,1991-07-14 00:00:00 -6632,507,24,11.0,5,0,1991-07-14 00:00:00 -6633,508,21,23.0,4,1,1991-07-28 00:00:00 -6634,508,26,0.0,12,0,1991-07-28 00:00:00 -6635,508,34,5.0,7,0,1991-07-28 00:00:00 -6636,508,35,0.0,18,0,1991-07-28 00:00:00 -6637,508,5,33.0,3,0,1991-07-28 00:00:00 -6638,508,40,0.0,14,0,1991-07-28 00:00:00 -6639,508,41,0.0,19,0,1991-07-28 00:00:00 -6640,508,0,70.0,2,4,1991-07-28 00:00:00 -6641,508,28,0.0,17,0,1991-07-28 00:00:00 -6642,508,39,0.0,13,0,1991-07-28 00:00:00 -6643,508,31,3.0,9,0,1991-07-28 00:00:00 -6644,508,33,0.0,15,0,1991-07-28 00:00:00 -6645,508,16,13.0,5,0,1991-07-28 00:00:00 -6646,508,17,3.0,8,0,1991-07-28 00:00:00 -6647,508,38,0.0,16,0,1991-07-28 00:00:00 -6648,508,32,1.0,11,0,1991-07-28 00:00:00 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00:00:00 -7606,578,24,2.0,8,0,1995-10-22 00:00:00 -7607,578,0,21.0,4,0,1995-10-22 00:00:00 -7608,578,5,73.0,3,1,1995-10-22 00:00:00 -7609,578,2,108.0,2,4,1995-10-22 00:00:00 -7610,578,21,133.0,1,10,1995-10-22 00:00:00 -7611,578,29,0.0,11,0,1995-10-22 00:00:00 -7612,578,28,1.0,9,0,1995-10-22 00:00:00 -7613,578,17,0.0,10,0,1995-10-22 00:00:00 -7614,578,16,18.0,5,0,1995-10-22 00:00:00 -7615,578,30,0.0,13,0,1995-10-22 00:00:00 -7616,579,30,0.0,13,0,1995-10-29 00:00:00 -7617,579,17,0.0,10,0,1995-10-29 00:00:00 -7618,579,16,21.0,5,0,1995-10-29 00:00:00 -7619,579,14,18.0,7,0,1995-10-29 00:00:00 -7620,579,27,0.0,12,0,1995-10-29 00:00:00 -7621,579,29,0.0,11,0,1995-10-29 00:00:00 -7622,579,26,18.0,6,0,1995-10-29 00:00:00 -7623,579,0,27.0,4,0,1995-10-29 00:00:00 -7624,579,28,1.0,9,0,1995-10-29 00:00:00 -7625,579,5,73.0,3,1,1995-10-29 00:00:00 -7626,579,2,108.0,2,4,1995-10-29 00:00:00 -7627,579,21,147.0,1,11,1995-10-29 00:00:00 -7628,579,24,3.0,8,0,1995-10-29 00:00:00 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-8973,705,3,52.0,4,0,2003-06-29 00:00:00 -8974,705,18,9.0,8,0,2003-06-29 00:00:00 -8975,705,15,13.0,5,0,2003-06-29 00:00:00 -8976,705,17,0.0,10,0,2003-06-29 00:00:00 -8977,705,16,11.0,6,1,2003-06-29 00:00:00 -8978,705,6,4.0,9,0,2003-06-29 00:00:00 -8979,705,14,9.0,7,0,2003-06-29 00:00:00 -8980,706,5,103.0,1,4,2003-07-06 00:00:00 -8981,706,0,85.0,3,2,2003-07-06 00:00:00 -8982,706,2,100.0,2,3,2003-07-06 00:00:00 -8983,706,3,52.0,4,0,2003-07-06 00:00:00 -8984,706,14,9.0,8,0,2003-07-06 00:00:00 -8985,706,15,13.0,5,0,2003-07-06 00:00:00 -8986,706,17,0.0,10,0,2003-07-06 00:00:00 -8987,706,16,11.0,7,1,2003-07-06 00:00:00 -8988,706,6,5.0,9,0,2003-07-06 00:00:00 -8989,706,18,12.0,6,0,2003-07-06 00:00:00 -8990,707,0,95.0,3,2,2003-07-20 00:00:00 -8991,707,2,108.0,2,3,2003-07-20 00:00:00 -8992,707,5,118.0,1,5,2003-07-20 00:00:00 -8993,707,3,55.0,4,0,2003-07-20 00:00:00 -8994,707,14,9.0,8,0,2003-07-20 00:00:00 -8995,707,15,14.0,5,0,2003-07-20 00:00:00 -8996,707,17,0.0,10,0,2003-07-20 00:00:00 -8997,707,16,11.0,7,1,2003-07-20 00:00:00 -8998,707,6,7.0,9,0,2003-07-20 00:00:00 -8999,707,18,12.0,6,0,2003-07-20 00:00:00 -9000,708,0,103.0,3,2,2003-08-03 00:00:00 -9001,708,2,118.0,2,4,2003-08-03 00:00:00 -9002,708,5,120.0,1,5,2003-08-03 00:00:00 -9003,708,3,66.0,4,0,2003-08-03 00:00:00 -9004,708,18,12.0,7,0,2003-08-03 00:00:00 -9005,708,15,15.0,5,0,2003-08-03 00:00:00 -9006,708,17,0.0,10,0,2003-08-03 00:00:00 -9007,708,16,11.0,8,1,2003-08-03 00:00:00 -9008,708,6,14.0,6,0,2003-08-03 00:00:00 -9009,708,14,9.0,9,0,2003-08-03 00:00:00 -9010,709,3,78.0,4,1,2003-08-24 00:00:00 -9011,709,2,129.0,1,4,2003-08-24 00:00:00 -9012,709,5,121.0,2,5,2003-08-24 00:00:00 -9013,709,0,115.0,3,2,2003-08-24 00:00:00 -9014,709,16,11.0,8,1,2003-08-24 00:00:00 -9015,709,18,15.0,6,0,2003-08-24 00:00:00 -9016,709,6,14.0,7,0,2003-08-24 00:00:00 -9017,709,17,0.0,10,0,2003-08-24 00:00:00 -9018,709,15,15.0,5,0,2003-08-24 00:00:00 -9019,709,14,9.0,9,0,2003-08-24 00:00:00 -9020,710,17,0.0,10,0,2003-09-14 00:00:00 -9021,710,5,137.0,2,6,2003-09-14 00:00:00 -9022,710,2,141.0,1,4,2003-09-14 00:00:00 -9023,710,0,120.0,3,2,2003-09-14 00:00:00 -9024,710,3,79.0,4,1,2003-09-14 00:00:00 -9025,710,14,9.0,9,0,2003-09-14 00:00:00 -9026,710,15,18.0,5,0,2003-09-14 00:00:00 -9027,710,16,11.0,8,1,2003-09-14 00:00:00 -9028,710,6,14.0,7,0,2003-09-14 00:00:00 -9029,710,18,17.0,6,0,2003-09-14 00:00:00 -9030,711,2,144.0,2,4,2003-09-28 00:00:00 -9031,711,3,84.0,4,1,2003-09-28 00:00:00 -9032,711,14,19.0,5,0,2003-09-28 00:00:00 -9033,711,15,18.0,6,0,2003-09-28 00:00:00 -9034,711,17,0.0,10,0,2003-09-28 00:00:00 -9035,711,16,13.0,9,1,2003-09-28 00:00:00 -9036,711,6,14.0,8,0,2003-09-28 00:00:00 -9037,711,18,18.0,7,0,2003-09-28 00:00:00 -9038,711,0,128.0,3,2,2003-09-28 00:00:00 -9039,711,5,147.0,1,7,2003-09-28 00:00:00 -9040,712,0,142.0,3,2,2003-10-12 00:00:00 -9041,712,6,16.0,8,0,2003-10-12 00:00:00 -9042,712,16,13.0,9,1,2003-10-12 00:00:00 -9043,712,17,0.0,10,0,2003-10-12 00:00:00 -9044,712,15,26.0,5,0,2003-10-12 00:00:00 -9045,712,14,19.0,6,0,2003-10-12 00:00:00 -9046,712,3,88.0,4,1,2003-10-12 00:00:00 -9047,712,2,144.0,2,4,2003-10-12 00:00:00 -9048,712,5,158.0,1,8,2003-10-12 00:00:00 -9049,712,18,18.0,7,0,2003-10-12 00:00:00 -9050,713,5,18.0,1,1,2004-03-07 00:00:00 -9051,713,3,8.0,3,0,2004-03-07 00:00:00 -9052,713,2,9.0,2,0,2004-03-07 00:00:00 -9053,713,15,3.0,4,0,2004-03-07 00:00:00 -9054,713,14,0.0,6,0,2004-03-07 00:00:00 -9055,713,18,0.0,7,0,2004-03-07 00:00:00 -9056,713,6,0.0,8,0,2004-03-07 00:00:00 -9057,713,16,0.0,9,0,2004-03-07 00:00:00 -9058,713,0,1.0,5,0,2004-03-07 00:00:00 -9059,714,17,0.0,10,0,2004-03-21 00:00:00 -9060,714,16,0.0,9,0,2004-03-21 00:00:00 -9061,714,6,0.0,7,0,2004-03-21 00:00:00 -9062,714,18,0.0,8,0,2004-03-21 00:00:00 -9063,714,14,1.0,6,0,2004-03-21 00:00:00 -9064,714,0,4.0,5,0,2004-03-21 00:00:00 -9065,714,15,9.0,4,0,2004-03-21 00:00:00 -9066,714,3,14.0,3,0,2004-03-21 00:00:00 -9067,714,5,33.0,1,2,2004-03-21 00:00:00 -9068,714,2,17.0,2,0,2004-03-21 00:00:00 -9069,715,6,0.0,8,0,2004-04-04 00:00:00 -9070,715,16,0.0,9,0,2004-04-04 00:00:00 -9071,715,5,51.0,1,3,2004-04-04 00:00:00 -9072,715,3,22.0,2,0,2004-04-04 00:00:00 -9073,715,17,0.0,10,0,2004-04-04 00:00:00 -9074,715,18,1.0,7,0,2004-04-04 00:00:00 -9075,715,15,19.0,4,0,2004-04-04 00:00:00 -9076,715,0,4.0,5,0,2004-04-04 00:00:00 -9077,715,2,19.0,3,0,2004-04-04 00:00:00 -9078,715,14,1.0,6,0,2004-04-04 00:00:00 -9079,716,5,64.0,1,4,2004-04-25 00:00:00 -9080,716,3,31.0,2,0,2004-04-25 00:00:00 -9081,716,2,27.0,4,0,2004-04-25 00:00:00 -9082,716,15,27.0,3,0,2004-04-25 00:00:00 -9083,716,14,1.0,6,0,2004-04-25 00:00:00 -9084,716,18,1.0,7,0,2004-04-25 00:00:00 -9085,716,6,0.0,8,0,2004-04-25 00:00:00 -9086,716,16,0.0,9,0,2004-04-25 00:00:00 -9087,716,17,0.0,10,0,2004-04-25 00:00:00 -9088,716,0,5.0,5,0,2004-04-25 00:00:00 -9089,717,3,42.0,2,0,2004-05-09 00:00:00 -9090,717,2,30.0,4,0,2004-05-09 00:00:00 -9091,717,0,5.0,5,0,2004-05-09 00:00:00 -9092,717,5,82.0,1,5,2004-05-09 00:00:00 -9093,717,18,1.0,7,0,2004-05-09 00:00:00 -9094,717,14,3.0,6,0,2004-05-09 00:00:00 -9095,717,17,0.0,10,0,2004-05-09 00:00:00 -9096,717,15,32.0,3,0,2004-05-09 00:00:00 -9097,717,16,0.0,9,0,2004-05-09 00:00:00 -9098,717,6,0.0,8,0,2004-05-09 00:00:00 -9099,718,17,0.0,10,0,2004-05-23 00:00:00 -9100,718,5,88.0,1,5,2004-05-23 00:00:00 -9101,718,2,35.0,4,0,2004-05-23 00:00:00 -9102,718,15,40.0,3,0,2004-05-23 00:00:00 -9103,718,3,52.0,2,1,2004-05-23 00:00:00 -9104,718,14,7.0,5,0,2004-05-23 00:00:00 -9105,718,18,1.0,9,0,2004-05-23 00:00:00 -9106,718,6,4.0,7,0,2004-05-23 00:00:00 -9107,718,16,2.0,8,0,2004-05-23 00:00:00 -9108,718,0,5.0,6,0,2004-05-23 00:00:00 -9109,719,16,2.0,9,0,2004-05-30 00:00:00 -9110,719,6,4.0,7,0,2004-05-30 00:00:00 -9111,719,18,3.0,8,0,2004-05-30 00:00:00 -9112,719,14,10.0,5,0,2004-05-30 00:00:00 -9113,719,0,5.0,6,0,2004-05-30 00:00:00 -9114,719,15,46.0,3,0,2004-05-30 00:00:00 -9115,719,2,36.0,4,0,2004-05-30 00:00:00 -9116,719,3,61.0,2,1,2004-05-30 00:00:00 -9117,719,17,0.0,10,0,2004-05-30 00:00:00 -9118,719,5,106.0,1,6,2004-05-30 00:00:00 -9119,720,0,12.0,6,0,2004-06-13 00:00:00 -9120,720,15,52.0,3,0,2004-06-13 00:00:00 -9121,720,5,124.0,1,7,2004-06-13 00:00:00 -9122,720,3,61.0,2,1,2004-06-13 00:00:00 -9123,720,17,0.0,10,0,2004-06-13 00:00:00 -9124,720,14,15.0,5,0,2004-06-13 00:00:00 -9125,720,6,4.0,8,0,2004-06-13 00:00:00 -9126,720,18,3.0,9,0,2004-06-13 00:00:00 -9127,720,2,36.0,4,0,2004-06-13 00:00:00 -9128,720,16,5.0,7,0,2004-06-13 00:00:00 -9129,721,5,142.0,1,8,2004-06-20 00:00:00 -9130,721,3,66.0,2,1,2004-06-20 00:00:00 -9131,721,2,36.0,4,0,2004-06-20 00:00:00 -9132,721,15,58.0,3,0,2004-06-20 00:00:00 -9133,721,14,15.0,6,0,2004-06-20 00:00:00 -9134,721,18,3.0,9,0,2004-06-20 00:00:00 -9135,721,6,8.0,7,0,2004-06-20 00:00:00 -9136,721,16,5.0,8,0,2004-06-20 00:00:00 -9137,721,17,1.0,10,0,2004-06-20 00:00:00 -9138,721,0,17.0,5,0,2004-06-20 00:00:00 -9139,722,2,37.0,4,0,2004-07-04 00:00:00 -9140,722,5,158.0,1,9,2004-07-04 00:00:00 -9141,722,15,62.0,3,0,2004-07-04 00:00:00 -9142,722,3,79.0,2,1,2004-07-04 00:00:00 -9143,722,14,15.0,6,0,2004-07-04 00:00:00 -9144,722,18,3.0,9,0,2004-07-04 00:00:00 -9145,722,6,8.0,7,0,2004-07-04 00:00:00 -9146,722,16,5.0,8,0,2004-07-04 00:00:00 -9147,722,0,22.0,5,0,2004-07-04 00:00:00 -9148,722,17,1.0,10,0,2004-07-04 00:00:00 -9149,723,5,174.0,1,10,2004-07-11 00:00:00 -9150,723,3,79.0,2,1,2004-07-11 00:00:00 -9151,723,2,41.0,4,0,2004-07-11 00:00:00 -9152,723,15,67.0,3,0,2004-07-11 00:00:00 -9153,723,16,5.0,8,0,2004-07-11 00:00:00 -9154,723,14,18.0,6,0,2004-07-11 00:00:00 -9155,723,18,4.0,9,0,2004-07-11 00:00:00 -9156,723,6,8.0,7,0,2004-07-11 00:00:00 -9157,723,17,1.0,10,0,2004-07-11 00:00:00 -9158,723,0,32.0,5,0,2004-07-11 00:00:00 -9159,724,5,184.0,1,11,2004-07-25 00:00:00 -9160,724,3,85.0,2,1,2004-07-25 00:00:00 -9161,724,2,47.0,4,0,2004-07-25 00:00:00 -9162,724,15,76.0,3,0,2004-07-25 00:00:00 -9163,724,14,18.0,6,0,2004-07-25 00:00:00 -9164,724,18,7.0,8,0,2004-07-25 00:00:00 -9165,724,6,8.0,7,0,2004-07-25 00:00:00 -9166,724,16,5.0,9,0,2004-07-25 00:00:00 -9167,724,0,37.0,5,0,2004-07-25 00:00:00 -9168,724,17,1.0,10,0,2004-07-25 00:00:00 -9169,725,2,54.0,4,0,2004-08-15 00:00:00 -9170,725,3,91.0,2,1,2004-08-15 00:00:00 -9171,725,5,202.0,1,12,2004-08-15 00:00:00 -9172,725,15,83.0,3,0,2004-08-15 00:00:00 -9173,725,0,37.0,5,0,2004-08-15 00:00:00 -9174,725,17,1.0,10,0,2004-08-15 00:00:00 -9175,725,16,5.0,9,0,2004-08-15 00:00:00 -9176,725,6,8.0,7,0,2004-08-15 00:00:00 -9177,725,18,7.0,8,0,2004-08-15 00:00:00 -9178,725,14,19.0,6,0,2004-08-15 00:00:00 -9179,726,3,91.0,2,1,2004-08-29 00:00:00 -9180,726,2,54.0,4,0,2004-08-29 00:00:00 -9181,726,15,83.0,3,0,2004-08-29 00:00:00 -9182,726,0,49.0,5,1,2004-08-29 00:00:00 -9183,726,5,216.0,1,12,2004-08-29 00:00:00 -9184,726,18,10.0,7,0,2004-08-29 00:00:00 -9185,726,6,9.0,8,0,2004-08-29 00:00:00 -9186,726,16,5.0,9,0,2004-08-29 00:00:00 -9187,726,14,28.0,6,0,2004-08-29 00:00:00 -9188,726,17,1.0,10,0,2004-08-29 00:00:00 -9189,727,15,94.0,2,0,2004-09-12 00:00:00 -9190,727,5,234.0,1,13,2004-09-12 00:00:00 -9191,727,3,91.0,3,1,2004-09-12 00:00:00 -9192,727,2,60.0,4,0,2004-09-12 00:00:00 -9193,727,0,52.0,5,1,2004-09-12 00:00:00 -9194,727,14,29.0,6,0,2004-09-12 00:00:00 -9195,727,18,10.0,7,0,2004-09-12 00:00:00 -9196,727,6,9.0,8,0,2004-09-12 00:00:00 -9197,727,16,5.0,9,0,2004-09-12 00:00:00 -9198,727,17,1.0,10,0,2004-09-12 00:00:00 -9199,728,5,244.0,1,14,2004-09-26 00:00:00 -9200,728,3,96.0,3,1,2004-09-26 00:00:00 -9201,728,2,64.0,4,0,2004-09-26 00:00:00 -9202,728,15,105.0,2,0,2004-09-26 00:00:00 -9203,728,17,1.0,10,0,2004-09-26 00:00:00 -9204,728,14,32.0,6,0,2004-09-26 00:00:00 -9205,728,18,10.0,7,0,2004-09-26 00:00:00 -9206,728,6,9.0,8,0,2004-09-26 00:00:00 -9207,728,16,5.0,9,0,2004-09-26 00:00:00 -9208,728,0,58.0,5,1,2004-09-26 00:00:00 -9209,729,2,74.0,4,0,2004-10-10 00:00:00 -9210,729,5,254.0,1,15,2004-10-10 00:00:00 -9211,729,3,100.0,3,1,2004-10-10 00:00:00 -9212,729,15,116.0,2,0,2004-10-10 00:00:00 -9213,729,16,5.0,9,0,2004-10-10 00:00:00 -9214,729,14,33.0,6,0,2004-10-10 00:00:00 -9215,729,18,10.0,7,0,2004-10-10 00:00:00 -9216,729,6,9.0,8,0,2004-10-10 00:00:00 -9217,729,17,1.0,10,0,2004-10-10 00:00:00 -9218,729,0,61.0,5,1,2004-10-10 00:00:00 -9219,730,5,262.0,1,15,2004-10-24 00:00:00 -9220,730,3,105.0,3,1,2004-10-24 00:00:00 -9221,730,2,88.0,4,1,2004-10-24 00:00:00 -9222,730,0,69.0,5,1,2004-10-24 00:00:00 -9223,730,15,119.0,2,0,2004-10-24 00:00:00 -9224,730,18,10.0,7,0,2004-10-24 00:00:00 -9225,730,6,9.0,8,0,2004-10-24 00:00:00 -9226,730,16,5.0,9,0,2004-10-24 00:00:00 -9227,730,17,1.0,10,0,2004-10-24 00:00:00 -9228,730,14,34.0,6,0,2004-10-24 00:00:00 -9229,731,5,8.0,2,0,2005-03-06 14:00:00 -9230,731,8,7.0,3,0,2005-03-06 14:00:00 -9231,731,2,4.0,4,0,2005-03-06 14:00:00 -9232,731,14,0.0,7,0,2005-03-06 14:00:00 -9233,731,0,4.0,5,0,2005-03-06 14:00:00 -9234,731,6,0.0,6,0,2005-03-06 14:00:00 -9235,731,15,0.0,10,0,2005-03-06 14:00:00 -9236,731,3,16.0,1,1,2005-03-06 14:00:00 -9237,731,16,0.0,8,0,2005-03-06 14:00:00 -9238,731,17,0.0,9,0,2005-03-06 14:00:00 -9239,732,15,0.0,10,0,2005-03-20 15:00:00 -9240,732,3,26.0,1,2,2005-03-20 15:00:00 -9241,732,17,0.0,9,0,2005-03-20 15:00:00 -9242,732,5,10.0,4,0,2005-03-20 15:00:00 -9243,732,8,11.0,3,0,2005-03-20 15:00:00 -9244,732,2,10.0,5,0,2005-03-20 15:00:00 -9245,732,16,0.0,8,0,2005-03-20 15:00:00 -9246,732,0,9.0,6,0,2005-03-20 15:00:00 -9247,732,14,0.0,7,0,2005-03-20 15:00:00 -9248,732,6,12.0,2,0,2005-03-20 15:00:00 -9249,733,8,12.0,5,0,2005-04-03 14:30:00 -9250,733,0,19.0,3,0,2005-04-03 14:30:00 -9251,733,2,13.0,4,0,2005-04-03 14:30:00 -9252,733,5,10.0,6,0,2005-04-03 14:30:00 -9253,733,3,36.0,1,3,2005-04-03 14:30:00 -9254,733,6,25.0,2,0,2005-04-03 14:30:00 -9255,733,14,2.0,7,0,2005-04-03 14:30:00 -9256,733,15,0.0,10,0,2005-04-03 14:30:00 -9257,733,16,0.0,8,0,2005-04-03 14:30:00 -9258,733,17,0.0,9,0,2005-04-03 14:30:00 -9259,734,17,0.0,9,0,2005-04-24 14:00:00 -9260,734,5,18.0,4,0,2005-04-24 14:00:00 -9261,734,8,13.0,6,0,2005-04-24 14:00:00 -9262,734,2,18.0,5,0,2005-04-24 14:00:00 -9263,734,0,25.0,3,0,2005-04-24 14:00:00 -9264,734,6,29.0,2,0,2005-04-24 14:00:00 -9265,734,14,7.0,7,0,2005-04-24 14:00:00 -9266,734,15,0.0,10,0,2005-04-24 14:00:00 -9267,734,16,0.0,8,0,2005-04-24 14:00:00 -9268,734,3,46.0,1,4,2005-04-24 14:00:00 -9269,735,2,21.0,4,0,2005-05-08 14:00:00 -9270,735,5,18.0,5,0,2005-05-08 14:00:00 -9271,735,8,14.0,6,0,2005-05-08 14:00:00 -9272,735,0,37.0,3,1,2005-05-08 14:00:00 -9273,735,6,40.0,2,0,2005-05-08 14:00:00 -9274,735,17,0.0,9,0,2005-05-08 14:00:00 -9275,735,15,0.0,10,0,2005-05-08 14:00:00 -9276,735,16,0.0,8,0,2005-05-08 14:00:00 -9277,735,3,58.0,1,4,2005-05-08 14:00:00 -9278,735,14,7.0,7,0,2005-05-08 14:00:00 -9279,736,2,35.0,4,0,2005-05-22 14:00:00 -9280,736,3,63.0,1,4,2005-05-22 14:00:00 -9281,736,5,21.0,5,0,2005-05-22 14:00:00 -9282,736,8,14.0,6,0,2005-05-22 14:00:00 -9283,736,0,51.0,2,2,2005-05-22 14:00:00 -9284,736,17,0.0,9,0,2005-05-22 14:00:00 -9285,736,14,7.0,7,0,2005-05-22 14:00:00 -9286,736,15,0.0,10,0,2005-05-22 14:00:00 -9287,736,16,0.0,8,0,2005-05-22 14:00:00 -9288,736,6,43.0,3,0,2005-05-22 14:00:00 -9289,737,3,76.0,1,5,2005-05-29 14:00:00 -9290,737,5,31.0,5,0,2005-05-29 14:00:00 -9291,737,8,19.0,6,0,2005-05-29 14:00:00 -9292,737,0,53.0,2,2,2005-05-29 14:00:00 -9293,737,2,43.0,4,0,2005-05-29 14:00:00 -9294,737,14,7.0,7,0,2005-05-29 14:00:00 -9295,737,15,0.0,9,0,2005-05-29 14:00:00 -9296,737,16,0.0,8,0,2005-05-29 14:00:00 -9297,737,17,0.0,10,0,2005-05-29 14:00:00 -9298,737,6,44.0,3,0,2005-05-29 14:00:00 -9299,738,2,47.0,3,0,2005-06-12 13:00:00 -9300,738,17,0.0,10,0,2005-06-12 13:00:00 -9301,738,16,0.0,8,0,2005-06-12 13:00:00 -9302,738,15,0.0,9,0,2005-06-12 13:00:00 -9303,738,14,12.0,7,0,2005-06-12 13:00:00 -9304,738,0,63.0,2,3,2005-06-12 13:00:00 -9305,738,8,22.0,6,0,2005-06-12 13:00:00 -9306,738,6,47.0,4,0,2005-06-12 13:00:00 -9307,738,3,76.0,1,5,2005-06-12 13:00:00 -9308,738,5,45.0,5,0,2005-06-12 13:00:00 -9309,739,3,76.0,1,5,2005-06-19 14:00:00 -9310,739,5,63.0,3,1,2005-06-19 14:00:00 -9311,739,8,22.0,6,0,2005-06-19 14:00:00 -9312,739,0,63.0,2,3,2005-06-19 14:00:00 -9313,739,2,47.0,4,0,2005-06-19 14:00:00 -9314,739,14,12.0,7,0,2005-06-19 14:00:00 -9315,739,15,0.0,10,0,2005-06-19 14:00:00 -9316,739,16,11.0,8,0,2005-06-19 14:00:00 -9317,739,17,7.0,9,0,2005-06-19 14:00:00 -9318,739,6,47.0,5,0,2005-06-19 14:00:00 -9319,740,2,47.0,5,0,2005-07-03 14:00:00 -9320,740,3,89.0,1,6,2005-07-03 14:00:00 -9321,740,5,69.0,3,1,2005-07-03 14:00:00 -9322,740,8,22.0,6,0,2005-07-03 14:00:00 -9323,740,0,71.0,2,3,2005-07-03 14:00:00 -9324,740,17,7.0,9,0,2005-07-03 14:00:00 -9325,740,14,13.0,7,0,2005-07-03 14:00:00 -9326,740,15,5.0,10,0,2005-07-03 14:00:00 -9327,740,16,11.0,8,0,2005-07-03 14:00:00 -9328,740,6,53.0,4,0,2005-07-03 14:00:00 -9329,741,8,22.0,6,0,2005-07-10 14:00:00 -9330,741,3,102.0,1,6,2005-07-10 14:00:00 -9331,741,5,74.0,3,1,2005-07-10 14:00:00 -9332,741,2,47.0,5,0,2005-07-10 14:00:00 -9333,741,0,87.0,2,4,2005-07-10 14:00:00 -9334,741,14,13.0,7,0,2005-07-10 14:00:00 -9335,741,15,9.0,9,0,2005-07-10 14:00:00 -9336,741,16,11.0,8,0,2005-07-10 14:00:00 -9337,741,17,7.0,10,0,2005-07-10 14:00:00 -9338,741,6,54.0,4,0,2005-07-10 14:00:00 -9339,742,3,117.0,1,7,2005-07-24 14:00:00 -9340,742,5,78.0,3,1,2005-07-24 14:00:00 -9341,742,2,47.0,5,0,2005-07-24 14:00:00 -9342,742,0,95.0,2,4,2005-07-24 14:00:00 -9343,742,8,24.0,6,0,2005-07-24 14:00:00 -9344,742,14,14.0,8,0,2005-07-24 14:00:00 -9345,742,15,15.0,7,0,2005-07-24 14:00:00 -9346,742,16,11.0,9,0,2005-07-24 14:00:00 -9347,742,17,7.0,10,0,2005-07-24 14:00:00 -9348,742,6,57.0,4,0,2005-07-24 14:00:00 -9349,743,3,117.0,1,7,2005-07-31 14:00:00 -9350,743,17,7.0,10,0,2005-07-31 14:00:00 -9351,743,16,11.0,9,0,2005-07-31 14:00:00 -9352,743,15,20.0,7,0,2005-07-31 14:00:00 -9353,743,14,14.0,8,0,2005-07-31 14:00:00 -9354,743,6,68.0,4,0,2005-07-31 14:00:00 -9355,743,0,105.0,2,5,2005-07-31 14:00:00 -9356,743,2,52.0,5,0,2005-07-31 14:00:00 -9357,743,8,24.0,6,0,2005-07-31 14:00:00 -9358,743,5,86.0,3,1,2005-07-31 14:00:00 -9359,744,5,86.0,3,1,2005-08-21 15:00:00 -9360,744,8,27.0,6,0,2005-08-21 15:00:00 -9361,744,3,130.0,1,7,2005-08-21 15:00:00 -9362,744,2,52.0,5,0,2005-08-21 15:00:00 -9363,744,0,121.0,2,6,2005-08-21 15:00:00 -9364,744,6,71.0,4,0,2005-08-21 15:00:00 -9365,744,14,14.0,8,0,2005-08-21 15:00:00 -9366,744,15,24.0,7,0,2005-08-21 15:00:00 -9367,744,16,11.0,9,0,2005-08-21 15:00:00 -9368,744,17,7.0,10,0,2005-08-21 15:00:00 -9369,745,5,86.0,3,1,2005-09-04 14:00:00 -9370,745,8,27.0,6,0,2005-09-04 14:00:00 -9371,745,2,54.0,5,0,2005-09-04 14:00:00 -9372,745,0,136.0,2,7,2005-09-04 14:00:00 -9373,745,3,144.0,1,7,2005-09-04 14:00:00 -9374,745,14,14.0,8,0,2005-09-04 14:00:00 -9375,745,15,25.0,7,0,2005-09-04 14:00:00 -9376,745,16,11.0,9,0,2005-09-04 14:00:00 -9377,745,17,7.0,10,0,2005-09-04 14:00:00 -9378,745,6,78.0,4,0,2005-09-04 14:00:00 -9379,746,3,152.0,1,7,2005-09-11 14:00:00 -9380,746,5,90.0,3,1,2005-09-11 14:00:00 -9381,746,8,27.0,7,0,2005-09-11 14:00:00 -9382,746,2,59.0,5,0,2005-09-11 14:00:00 -9383,746,0,146.0,2,8,2005-09-11 14:00:00 -9384,746,6,80.0,4,0,2005-09-11 14:00:00 -9385,746,15,31.0,6,0,2005-09-11 14:00:00 -9386,746,16,12.0,9,0,2005-09-11 14:00:00 -9387,746,17,7.0,10,0,2005-09-11 14:00:00 -9388,746,14,17.0,8,0,2005-09-11 14:00:00 -9389,747,2,59.0,5,0,2005-09-25 14:00:00 -9390,747,3,162.0,2,7,2005-09-25 14:00:00 -9391,747,5,98.0,3,1,2005-09-25 14:00:00 -9392,747,8,27.0,7,0,2005-09-25 14:00:00 -9393,747,6,81.0,4,0,2005-09-25 14:00:00 -9394,747,15,33.0,6,0,2005-09-25 14:00:00 -9395,747,14,17.0,8,0,2005-09-25 14:00:00 -9396,747,16,12.0,9,0,2005-09-25 14:00:00 -9397,747,17,7.0,10,0,2005-09-25 14:00:00 -9398,747,0,164.0,1,9,2005-09-25 14:00:00 -9399,748,3,176.0,1,7,2005-10-09 14:00:00 -9400,748,8,30.0,7,0,2005-10-09 14:00:00 -9401,748,2,64.0,5,0,2005-10-09 14:00:00 -9402,748,0,174.0,2,10,2005-10-09 14:00:00 -9403,748,5,100.0,3,1,2005-10-09 14:00:00 -9404,748,14,17.0,8,0,2005-10-09 14:00:00 -9405,748,15,37.0,6,0,2005-10-09 14:00:00 -9406,748,16,12.0,9,0,2005-10-09 14:00:00 -9407,748,17,7.0,10,0,2005-10-09 14:00:00 -9408,748,6,82.0,4,0,2005-10-09 14:00:00 -9409,749,3,191.0,1,8,2005-10-16 14:00:00 -9410,749,17,7.0,10,0,2005-10-16 14:00:00 -9411,749,16,12.0,9,0,2005-10-16 14:00:00 -9412,749,15,38.0,6,0,2005-10-16 14:00:00 -9413,749,14,20.0,8,0,2005-10-16 14:00:00 -9414,749,6,88.0,4,0,2005-10-16 14:00:00 -9415,749,0,182.0,2,10,2005-10-16 14:00:00 -9416,749,2,66.0,5,0,2005-10-16 14:00:00 -9417,749,8,34.0,7,0,2005-10-16 14:00:00 -9418,749,5,100.0,3,1,2005-10-16 14:00:00 -9419,750,0,10.0,2,0,2006-03-12 14:30:00 -9420,750,10,5.0,4,0,2006-03-12 14:30:00 -9421,750,5,8.0,3,0,2006-03-12 14:30:00 -9422,750,2,5.0,5,0,2006-03-12 14:30:00 -9423,750,3,10.0,1,1,2006-03-12 14:30:00 -9424,750,4,0.0,7,0,2006-03-12 14:30:00 -9425,750,1,0.0,8,0,2006-03-12 14:30:00 -9426,750,6,0.0,9,0,2006-03-12 14:30:00 -9427,750,12,0.0,10,0,2006-03-12 14:30:00 -9428,750,7,0.0,11,0,2006-03-12 14:30:00 -9429,750,8,1.0,6,0,2006-03-12 14:30:00 -9430,751,3,28.0,1,2,2006-03-19 15:00:00 -9431,751,5,15.0,2,0,2006-03-19 15:00:00 -9432,751,0,15.0,3,0,2006-03-19 15:00:00 -9433,751,10,11.0,4,0,2006-03-19 15:00:00 -9434,751,2,5.0,5,0,2006-03-19 15:00:00 -9435,751,8,1.0,8,0,2006-03-19 15:00:00 -9436,751,1,2.0,6,0,2006-03-19 15:00:00 -9437,751,6,1.0,7,0,2006-03-19 15:00:00 -9438,751,12,0.0,10,0,2006-03-19 15:00:00 -9439,751,7,0.0,11,0,2006-03-19 15:00:00 -9440,751,4,0.0,9,0,2006-03-19 15:00:00 -9441,752,0,23.0,2,0,2006-04-02 14:00:00 -9442,752,5,15.0,3,0,2006-04-02 14:00:00 -9443,752,3,42.0,1,3,2006-04-02 14:00:00 -9444,752,8,2.0,8,0,2006-04-02 14:00:00 -9445,752,2,5.0,7,0,2006-04-02 14:00:00 -9446,752,1,10.0,5,0,2006-04-02 14:00:00 -9447,752,6,7.0,6,0,2006-04-02 14:00:00 -9448,752,12,0.0,10,0,2006-04-02 14:00:00 -9449,752,4,0.0,9,0,2006-04-02 14:00:00 -9450,752,10,13.0,4,0,2006-04-02 14:00:00 -9451,752,7,0.0,11,0,2006-04-02 14:00:00 -9452,753,7,0.0,11,0,2006-04-23 14:00:00 -9453,753,3,51.0,1,3,2006-04-23 14:00:00 -9454,753,5,30.0,3,1,2006-04-23 14:00:00 -9455,753,10,15.0,4,0,2006-04-23 14:00:00 -9456,753,0,33.0,2,0,2006-04-23 14:00:00 -9457,753,8,2.0,8,0,2006-04-23 14:00:00 -9458,753,4,0.0,9,0,2006-04-23 14:00:00 -9459,753,1,10.0,5,0,2006-04-23 14:00:00 -9460,753,6,7.0,7,0,2006-04-23 14:00:00 -9461,753,12,0.0,10,0,2006-04-23 14:00:00 -9462,753,2,8.0,6,0,2006-04-23 14:00:00 -9463,754,0,38.0,3,0,2006-05-07 14:00:00 -9464,754,3,62.0,1,3,2006-05-07 14:00:00 -9465,754,5,46.0,2,2,2006-05-07 14:00:00 -9466,754,10,19.0,4,0,2006-05-07 14:00:00 -9467,754,6,7.0,7,0,2006-05-07 14:00:00 -9468,754,8,2.0,8,0,2006-05-07 14:00:00 -9469,754,4,0.0,9,0,2006-05-07 14:00:00 -9470,754,1,11.0,5,0,2006-05-07 14:00:00 -9471,754,12,0.0,10,0,2006-05-07 14:00:00 -9472,754,7,0.0,11,0,2006-05-07 14:00:00 -9473,754,2,10.0,6,0,2006-05-07 14:00:00 -9474,755,0,42.0,3,0,2006-05-14 14:00:00 -9475,755,3,78.0,1,4,2006-05-14 14:00:00 -9476,755,5,59.0,2,2,2006-05-14 14:00:00 -9477,755,10,24.0,4,0,2006-05-14 14:00:00 -9478,755,6,7.0,7,0,2006-05-14 14:00:00 -9479,755,8,2.0,8,0,2006-05-14 14:00:00 -9480,755,2,10.0,6,0,2006-05-14 14:00:00 -9481,755,12,0.0,10,0,2006-05-14 14:00:00 -9482,755,7,0.0,11,0,2006-05-14 14:00:00 -9483,755,4,0.0,9,0,2006-05-14 14:00:00 -9484,755,1,12.0,5,0,2006-05-14 14:00:00 -9485,756,7,0.0,11,0,2006-05-28 14:00:00 -9486,756,12,0.0,10,0,2006-05-28 14:00:00 -9487,756,6,8.0,7,0,2006-05-28 14:00:00 -9488,756,1,14.0,5,0,2006-05-28 14:00:00 -9489,756,8,8.0,8,0,2006-05-28 14:00:00 -9490,756,2,10.0,6,0,2006-05-28 14:00:00 -9491,756,10,29.0,4,0,2006-05-28 14:00:00 -9492,756,0,50.0,3,0,2006-05-28 14:00:00 -9493,756,5,63.0,2,2,2006-05-28 14:00:00 -9494,756,3,91.0,1,5,2006-05-28 14:00:00 -9495,756,4,0.0,9,0,2006-05-28 14:00:00 -9496,757,6,8.0,7,0,2006-06-11 12:00:00 -9497,757,7,0.0,11,0,2006-06-11 12:00:00 -9498,757,12,0.0,10,0,2006-06-11 12:00:00 -9499,757,1,17.0,5,0,2006-06-11 12:00:00 -9500,757,8,8.0,8,0,2006-06-11 12:00:00 -9501,757,2,10.0,6,0,2006-06-11 12:00:00 -9502,757,10,29.0,4,0,2006-06-11 12:00:00 -9503,757,0,59.0,3,0,2006-06-11 12:00:00 -9504,757,5,75.0,2,2,2006-06-11 12:00:00 -9505,757,3,106.0,1,6,2006-06-11 12:00:00 -9506,757,4,0.0,9,0,2006-06-11 12:00:00 -9507,758,3,121.0,1,7,2006-06-25 13:00:00 -9508,758,5,87.0,2,2,2006-06-25 13:00:00 -9509,758,0,65.0,3,0,2006-06-25 13:00:00 -9510,758,10,29.0,4,0,2006-06-25 13:00:00 -9511,758,1,19.0,5,0,2006-06-25 13:00:00 -9512,758,8,9.0,8,0,2006-06-25 13:00:00 -9513,758,4,0.0,9,0,2006-06-25 13:00:00 -9514,758,6,11.0,6,0,2006-06-25 13:00:00 -9515,758,12,0.0,10,0,2006-06-25 13:00:00 -9516,758,2,10.0,7,0,2006-06-25 13:00:00 -9517,758,7,0.0,11,0,2006-06-25 13:00:00 -9518,759,3,131.0,1,7,2006-07-02 14:00:00 -9519,759,0,65.0,3,0,2006-07-02 14:00:00 -9520,759,10,32.0,4,0,2006-07-02 14:00:00 -9521,759,2,10.0,8,0,2006-07-02 14:00:00 -9522,759,5,105.0,2,3,2006-07-02 14:00:00 -9523,759,4,1.0,9,0,2006-07-02 14:00:00 -9524,759,1,19.0,5,0,2006-07-02 14:00:00 -9525,759,6,16.0,6,0,2006-07-02 14:00:00 -9526,759,12,0.0,10,0,2006-07-02 14:00:00 -9527,759,8,11.0,7,0,2006-07-02 14:00:00 -9528,759,7,0.0,11,0,2006-07-02 14:00:00 -9529,760,3,142.0,1,7,2006-07-16 14:00:00 -9530,760,0,71.0,3,0,2006-07-16 14:00:00 -9531,760,10,32.0,4,0,2006-07-16 14:00:00 -9532,760,2,10.0,8,0,2006-07-16 14:00:00 -9533,760,5,121.0,2,4,2006-07-16 14:00:00 -9534,760,1,20.0,6,0,2006-07-16 14:00:00 -9535,760,8,11.0,7,0,2006-07-16 14:00:00 -9536,760,7,0.0,11,0,2006-07-16 14:00:00 -9537,760,4,1.0,9,0,2006-07-16 14:00:00 -9538,760,6,21.0,5,0,2006-07-16 14:00:00 -9539,760,12,0.0,10,0,2006-07-16 14:00:00 -9540,761,7,0.0,11,0,2006-07-30 14:00:00 -9541,761,12,0.0,10,0,2006-07-30 14:00:00 -9542,761,6,23.0,5,0,2006-07-30 14:00:00 -9543,761,1,20.0,6,0,2006-07-30 14:00:00 -9544,761,8,12.0,7,0,2006-07-30 14:00:00 -9545,761,2,10.0,8,0,2006-07-30 14:00:00 -9546,761,10,37.0,4,0,2006-07-30 14:00:00 -9547,761,0,77.0,3,0,2006-07-30 14:00:00 -9548,761,5,139.0,2,5,2006-07-30 14:00:00 -9549,761,3,149.0,1,7,2006-07-30 14:00:00 -9550,761,4,1.0,9,0,2006-07-30 14:00:00 -9551,762,0,85.0,3,0,2006-08-06 14:00:00 -9552,762,12,0.0,10,0,2006-08-06 14:00:00 -9553,762,3,149.0,1,7,2006-08-06 14:00:00 -9554,762,5,142.0,2,5,2006-08-06 14:00:00 -9555,762,10,52.0,4,1,2006-08-06 14:00:00 -9556,762,2,10.0,8,0,2006-08-06 14:00:00 -9557,762,7,0.0,11,0,2006-08-06 14:00:00 -9558,762,4,1.0,9,0,2006-08-06 14:00:00 -9559,762,1,26.0,6,0,2006-08-06 14:00:00 -9560,762,6,26.0,5,0,2006-08-06 14:00:00 -9561,762,8,16.0,7,0,2006-08-06 14:00:00 -9562,763,3,160.0,1,7,2006-08-27 15:00:00 -9563,763,5,158.0,2,6,2006-08-27 15:00:00 -9564,763,0,89.0,3,0,2006-08-27 15:00:00 -9565,763,10,58.0,4,1,2006-08-27 15:00:00 -9566,763,2,10.0,8,0,2006-08-27 15:00:00 -9567,763,4,1.0,9,0,2006-08-27 15:00:00 -9568,763,1,26.0,6,0,2006-08-27 15:00:00 -9569,763,6,28.0,5,0,2006-08-27 15:00:00 -9570,763,12,0.0,10,0,2006-08-27 15:00:00 -9571,763,7,0.0,11,0,2006-08-27 15:00:00 -9572,763,8,16.0,7,0,2006-08-27 15:00:00 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-10005,803,4,3.0,5,0,2009-03-29 06:00:00 -10006,803,2,3.0,4,0,2009-03-29 06:00:00 -10007,803,3,4.0,3,0,2009-03-29 06:00:00 -10008,803,6,11.0,2,0,2009-03-29 06:00:00 -10009,803,22,18.0,1,1,2009-03-29 06:00:00 -10010,804,3,4.0,4,0,2009-04-05 09:00:00 -10011,804,22,25.0,1,2,2009-04-05 09:00:00 -10012,804,0,1.0,8,0,2009-04-05 09:00:00 -10013,804,6,16.5,2,0,2009-04-05 09:00:00 -10014,804,2,3.5,5,0,2009-04-05 09:00:00 -10015,804,4,3.0,6,0,2009-04-05 09:00:00 -10016,804,9,0.0,9,0,2009-04-05 09:00:00 -10017,804,1,4.0,3,0,2009-04-05 09:00:00 -10018,804,8,1.5,7,0,2009-04-05 09:00:00 -10019,804,5,0.0,10,0,2009-04-05 09:00:00 -10020,805,22,36.0,1,2,2009-04-19 07:00:00 -10021,805,0,8.0,4,0,2009-04-19 07:00:00 -10022,805,6,18.5,3,0,2009-04-19 07:00:00 -10023,805,3,4.0,6,0,2009-04-19 07:00:00 -10024,805,2,3.5,8,0,2009-04-19 07:00:00 -10025,805,1,4.0,5,0,2009-04-19 07:00:00 -10026,805,5,0.0,9,0,2009-04-19 07:00:00 -10027,805,9,0.0,10,0,2009-04-19 07:00:00 -10028,805,4,4.0,7,0,2009-04-19 07:00:00 -10029,805,8,19.5,2,1,2009-04-19 07:00:00 -10030,806,2,3.5,8,0,2009-04-26 12:00:00 -10031,806,5,3.0,9,0,2009-04-26 12:00:00 -10032,806,6,26.5,3,0,2009-04-26 12:00:00 -10033,806,0,13.0,4,0,2009-04-26 12:00:00 -10034,806,22,50.0,1,3,2009-04-26 12:00:00 -10035,806,3,5.0,5,0,2009-04-26 12:00:00 -10036,806,9,0.0,10,0,2009-04-26 12:00:00 -10037,806,4,4.0,7,0,2009-04-26 12:00:00 -10038,806,1,4.0,6,0,2009-04-26 12:00:00 -10039,806,8,27.5,2,1,2009-04-26 12:00:00 -10040,807,22,68.0,1,4,2009-05-10 12:00:00 -10041,807,0,13.0,4,0,2009-05-10 12:00:00 -10042,807,6,26.5,3,0,2009-05-10 12:00:00 -10043,807,3,9.0,5,0,2009-05-10 12:00:00 -10044,807,2,4.5,8,0,2009-05-10 12:00:00 -10045,807,4,4.0,9,0,2009-05-10 12:00:00 -10046,807,9,0.0,10,0,2009-05-10 12:00:00 -10047,807,1,6.0,6,0,2009-05-10 12:00:00 -10048,807,8,38.5,2,1,2009-05-10 12:00:00 -10049,807,5,6.0,7,0,2009-05-10 12:00:00 -10050,808,4,5.0,9,0,2009-05-24 12:00:00 -10051,808,22,86.0,1,5,2009-05-24 12:00:00 -10052,808,0,13.0,5,0,2009-05-24 12:00:00 -10053,808,3,11.0,6,0,2009-05-24 12:00:00 -10054,808,2,7.5,7,0,2009-05-24 12:00:00 -10055,808,8,42.5,2,1,2009-05-24 12:00:00 -10056,808,5,17.0,4,0,2009-05-24 12:00:00 -10057,808,6,26.5,3,0,2009-05-24 12:00:00 -10058,808,1,6.0,8,0,2009-05-24 12:00:00 -10059,808,9,0.0,10,0,2009-05-24 12:00:00 -10060,809,9,0.0,10,0,2009-06-07 12:00:00 -10061,809,2,11.5,6,0,2009-06-07 12:00:00 -10062,809,8,56.5,2,1,2009-06-07 12:00:00 -10063,809,22,96.0,1,6,2009-06-07 12:00:00 -10064,809,6,32.5,3,0,2009-06-07 12:00:00 -10065,809,0,13.0,5,0,2009-06-07 12:00:00 -10066,809,3,11.0,7,0,2009-06-07 12:00:00 -10067,809,4,5.0,9,0,2009-06-07 12:00:00 -10068,809,1,8.0,8,0,2009-06-07 12:00:00 -10069,809,5,20.0,4,0,2009-06-07 12:00:00 -10070,810,9,0.0,10,0,2009-06-21 12:00:00 -10071,810,8,74.5,2,2,2009-06-21 12:00:00 -10072,810,22,105.0,1,6,2009-06-21 12:00:00 -10073,810,6,34.5,3,0,2009-06-21 12:00:00 -10074,810,2,15.5,5,0,2009-06-21 12:00:00 -10075,810,0,13.0,6,0,2009-06-21 12:00:00 -10076,810,4,5.0,9,0,2009-06-21 12:00:00 -10077,810,1,8.0,8,0,2009-06-21 12:00:00 -10078,810,5,26.0,4,0,2009-06-21 12:00:00 -10079,810,3,11.0,7,0,2009-06-21 12:00:00 -10080,811,5,32.0,4,0,2009-07-12 12:00:00 -10081,811,8,92.5,2,3,2009-07-12 12:00:00 -10082,811,1,8.0,8,0,2009-07-12 12:00:00 -10083,811,9,0.0,10,0,2009-07-12 12:00:00 -10084,811,4,5.0,9,0,2009-07-12 12:00:00 -10085,811,2,20.5,5,0,2009-07-12 12:00:00 -10086,811,3,13.0,7,0,2009-07-12 12:00:00 -10087,811,6,34.5,3,0,2009-07-12 12:00:00 -10088,811,0,14.0,6,0,2009-07-12 12:00:00 -10089,811,22,112.0,1,6,2009-07-12 12:00:00 -10090,812,5,40.0,3,0,2009-07-26 12:00:00 -10091,812,8,98.5,2,3,2009-07-26 12:00:00 -10092,812,1,8.0,8,0,2009-07-26 12:00:00 -10093,812,9,0.0,10,0,2009-07-26 12:00:00 -10094,812,4,5.0,9,0,2009-07-26 12:00:00 -10095,812,2,25.5,6,0,2009-07-26 12:00:00 -10096,812,3,13.0,7,0,2009-07-26 12:00:00 -10097,812,6,38.5,4,0,2009-07-26 12:00:00 -10098,812,0,28.0,5,1,2009-07-26 12:00:00 -10099,812,22,114.0,1,6,2009-07-26 12:00:00 -10100,813,5,46.0,3,0,2009-08-23 12:00:00 -10101,813,8,98.5,2,3,2009-08-23 12:00:00 -10102,813,1,9.0,8,0,2009-08-23 12:00:00 -10103,813,9,0.0,10,0,2009-08-23 12:00:00 -10104,813,4,5.0,9,0,2009-08-23 12:00:00 -10105,813,2,29.5,6,0,2009-08-23 12:00:00 -10106,813,3,16.0,7,0,2009-08-23 12:00:00 -10107,813,6,38.5,5,0,2009-08-23 12:00:00 -10108,813,0,41.0,4,1,2009-08-23 12:00:00 -10109,813,22,126.0,1,7,2009-08-23 12:00:00 -10110,814,8,104.5,2,3,2009-08-30 12:00:00 -10111,814,5,56.0,3,1,2009-08-30 12:00:00 -10112,814,9,8.0,9,0,2009-08-30 12:00:00 -10113,814,4,5.0,10,0,2009-08-30 12:00:00 -10114,814,2,30.5,6,0,2009-08-30 12:00:00 -10115,814,1,18.0,7,0,2009-08-30 12:00:00 -10116,814,6,38.5,5,0,2009-08-30 12:00:00 -10117,814,0,44.0,4,1,2009-08-30 12:00:00 -10118,814,22,128.0,1,7,2009-08-30 12:00:00 -10119,814,3,16.0,8,0,2009-08-30 12:00:00 -10120,815,0,47.0,4,1,2009-09-13 12:00:00 -10121,815,22,146.0,1,8,2009-09-13 12:00:00 -10122,815,5,62.0,3,1,2009-09-13 12:00:00 -10123,815,8,105.5,2,3,2009-09-13 12:00:00 -10124,815,6,38.5,5,0,2009-09-13 12:00:00 -10125,815,9,13.0,9,0,2009-09-13 12:00:00 -10126,815,4,5.0,10,0,2009-09-13 12:00:00 -10127,815,3,20.0,8,0,2009-09-13 12:00:00 -10128,815,2,30.5,6,0,2009-09-13 12:00:00 -10129,815,1,20.0,7,0,2009-09-13 12:00:00 -10130,816,2,30.5,6,0,2009-09-27 12:00:00 -10131,816,4,5.0,10,0,2009-09-27 12:00:00 -10132,816,9,13.0,9,0,2009-09-27 12:00:00 -10133,816,8,110.5,2,3,2009-09-27 12:00:00 -10134,816,5,62.0,3,1,2009-09-27 12:00:00 -10135,816,6,46.5,5,0,2009-09-27 12:00:00 -10136,816,0,59.0,4,2,2009-09-27 12:00:00 -10137,816,22,153.0,1,8,2009-09-27 12:00:00 -10138,816,3,26.0,7,0,2009-09-27 12:00:00 -10139,816,1,21.0,8,0,2009-09-27 12:00:00 -10140,817,22,156.0,1,8,2009-10-04 05:00:00 -10141,817,3,26.0,7,0,2009-10-04 05:00:00 -10142,817,1,24.0,8,0,2009-10-04 05:00:00 -10143,817,6,54.5,5,0,2009-10-04 05:00:00 -10144,817,2,34.5,6,0,2009-10-04 05:00:00 -10145,817,5,67.0,3,1,2009-10-04 05:00:00 -10146,817,8,120.5,2,4,2009-10-04 05:00:00 -10147,817,0,65.0,4,2,2009-10-04 05:00:00 -10148,817,9,13.0,9,0,2009-10-04 05:00:00 -10149,817,4,5.0,10,0,2009-10-04 05:00:00 -10150,818,3,26.0,8,0,2009-10-18 16:00:00 -10151,818,2,34.5,6,0,2009-10-18 16:00:00 -10152,818,4,7.0,10,0,2009-10-18 16:00:00 -10153,818,0,71.0,3,2,2009-10-18 16:00:00 -10154,818,1,32.0,7,0,2009-10-18 16:00:00 -10155,818,8,135.5,2,5,2009-10-18 16:00:00 -10156,818,5,70.0,4,1,2009-10-18 16:00:00 -10157,818,22,161.0,1,8,2009-10-18 16:00:00 -10158,818,6,54.5,5,0,2009-10-18 16:00:00 -10159,818,9,13.0,9,0,2009-10-18 16:00:00 -10160,819,5,70.0,4,1,2009-11-01 11:00:00 -10161,819,8,153.5,2,6,2009-11-01 11:00:00 -10162,819,22,172.0,1,8,2009-11-01 11:00:00 -10163,819,0,71.0,3,2,2009-11-01 11:00:00 -10164,819,6,59.5,5,0,2009-11-01 11:00:00 -10165,819,3,26.0,8,0,2009-11-01 11:00:00 -10166,819,1,36.0,6,0,2009-11-01 11:00:00 -10167,819,2,34.5,7,0,2009-11-01 11:00:00 -10168,819,4,8.0,10,0,2009-11-01 11:00:00 -10169,819,9,13.0,9,0,2009-11-01 11:00:00 diff --git a/scripts/f1_data/constructors.csv b/scripts/f1_data/constructors.csv deleted file mode 100644 index fa1ec049..00000000 --- a/scripts/f1_data/constructors.csv +++ /dev/null @@ -1,212 +0,0 @@ -constructorId,constructorRef,name,nationality -0,mclaren,McLaren,British -1,bmw_sauber,BMW Sauber,German -2,williams,Williams,British -3,renault,Renault,French -4,toro_rosso,Toro Rosso,Italian -5,ferrari,Ferrari,Italian -6,toyota,Toyota,Japanese -7,super_aguri,Super Aguri,Japanese -8,red_bull,Red Bull,Austrian -9,force_india,Force India,Indian -10,honda,Honda,Japanese -11,spyker,Spyker,Dutch -12,mf1,MF1,Russian -13,spyker_mf1,Spyker MF1,Dutch -14,sauber,Sauber,Swiss -15,bar,BAR,British -16,jordan,Jordan,Irish -17,minardi,Minardi,Italian -18,jaguar,Jaguar,British -19,prost,Prost,French -20,arrows,Arrows,British -21,benetton,Benetton,Italian -22,brawn,Brawn,British -23,stewart,Stewart,British -24,tyrrell,Tyrrell,British -25,lola,Lola,British -26,ligier,Ligier,French -27,forti,Forti,Italian -28,footwork,Footwork,British -29,pacific,Pacific,British -30,simtek,Simtek,British -31,team_lotus,Team Lotus,British -32,larrousse,Larrousse,French -33,brabham,Brabham,British -34,dallara,Dallara,Italian -35,fondmetal,Fondmetal,Italian -36,march,March,British -37,moda,Andrea Moda,Italian -38,ags,AGS,French -39,lambo,Lambo,Italian -40,leyton,Leyton House,British -41,coloni,Coloni,Italian -42,eurobrun,Euro Brun,Italian -43,osella,Osella,Italian -44,onyx,Onyx,British -45,life,Life,Italian -46,rial,Rial,German -47,zakspeed,Zakspeed,German -48,ram,RAM,British -49,alfa,Alfa Romeo,Swiss -50,spirit,Spirit,British -51,toleman,Toleman,British -52,ats,ATS,Italian -53,theodore,Theodore,Hong Kong -54,fittipaldi,Fittipaldi,Brazilian -55,ensign,Ensign,British -56,shadow,Shadow,British -57,wolf,Wolf,Canadian -58,merzario,Merzario,Italian -59,kauhsen,Kauhsen,German -60,rebaque,Rebaque,Mexican -61,surtees,Surtees,British -62,hesketh,Hesketh,British -63,martini,Martini,French -64,brm,BRM,British -65,penske,Penske,American -66,lec,LEC,British -67,mcguire,McGuire,Australian -68,boro,Boro,Dutch -69,apollon,Apollon,Swiss -70,kojima,Kojima,Japanese -71,parnelli,Parnelli,American -72,maki,Maki,Japanese -73,hill,Embassy Hill,British -74,lyncar,Lyncar,British -75,trojan,Trojan,British -76,amon,Amon,New Zealander -77,token,Token,British -78,iso_marlboro,Iso Marlboro,British -79,tecno,Tecno,Italian -80,matra,Matra,French -81,politoys,Politoys,British -82,connew,Connew,British -83,bellasi,Bellasi,Swiss -84,tomaso,De Tomaso,Italian -85,cooper,Cooper,British -86,eagle,Eagle,American -87,lds,LDS,South African -88,protos,Protos,British -89,shannon,Shannon,British -90,scirocco,Scirocco,British -91,re,RE,Rhodesian -92,brp,BRP,British -93,porsche,Porsche,German -94,derrington,Derrington,British -95,gilby,Gilby,British -96,stebro,Stebro,Canadian -97,emeryson,Emeryson,British -98,enb,ENB,Belgian -99,jbw,JBW,British -100,ferguson,Ferguson,British -101,mbm,MBM,Swiss -102,behra-porsche,Behra-Porsche,Italian -103,maserati,Maserati,Italian -104,scarab,Scarab,American -105,watson,Watson,American -106,epperly,Epperly,American -107,phillips,Phillips,American -108,lesovsky,Lesovsky,American -109,trevis,Trevis,American -110,meskowski,Meskowski,American -111,kurtis_kraft,Kurtis Kraft,American -112,kuzma,Kuzma,American -113,vhristensen,Christensen,American -114,ewing,Ewing,American -115,aston_martin,Aston Martin,British -116,vanwall,Vanwall,British -117,moore,Moore,American -118,dunn,Dunn,American -119,elder,Elder,American -120,sutton,Sutton,American -121,fry,Fry,British -122,tec-mec,Tec-Mec,Italian -123,connaught,Connaught,British -124,alta,Alta,British -125,osca,OSCA,Italian -126,gordini,Gordini,French -127,stevens,Stevens,American -128,bugatti,Bugatti,French -129,mercedes,Mercedes,German -130,lancia,Lancia,Italian -131,hwm,HWM,British -132,schroeder,Schroeder,American -133,pawl,Pawl,American -134,pankratz,Pankratz,American -135,arzani-volpini,Arzani-Volpini,Italian -136,nichels,Nichels,American -137,bromme,Bromme,American -138,klenk,Klenk,German -139,simca,Simca,French -140,turner,Turner,American -141,del_roy,Del Roy,American -142,veritas,Veritas,German -143,bmw,BMW,German -144,emw,EMW,East German -145,afm,AFM,German -146,frazer_nash,Frazer Nash,British -147,sherman,Sherman,American -148,deidt,Deidt,American -149,era,ERA,British -150,butterworth,Aston Butterworth,British -151,cisitalia,Cisitalia,Italian -152,lago,Talbot-Lago,French -153,hall,Hall,American -154,marchese,Marchese,American -155,langley,Langley,American -156,rae,Rae,American -157,olson,Olson,American -158,wetteroth,Wetteroth,American -159,adams,Adams,American -160,snowberger,Snowberger,American -161,milano,Milano,Italian -162,hrt,HRT,Spanish -163,cooper-maserati,Cooper-Maserati,British -164,virgin,Virgin,British -165,cooper-osca,Cooper-OSCA,British -166,cooper-borgward,Cooper-Borgward,British -167,cooper-climax,Cooper-Climax,British -168,cooper-castellotti,Cooper-Castellotti,British -169,lotus-climax,Lotus-Climax,British -170,lotus-maserati,Lotus-Maserati,British -171,de_tomaso-osca,De Tomaso-Osca,Italian -172,de_tomaso-alfa_romeo,De Tomaso-Alfa Romeo,Italian -173,lotus-brm,Lotus-BRM,British -174,lotus-borgward,Lotus-Borgward,British -175,cooper-alfa_romeo,Cooper-Alfa Romeo,British -176,de_tomaso-ferrari,De Tomaso-Ferrari,Italian -177,lotus-ford,Lotus-Ford,British -178,brabham-brm,Brabham-BRM,British -179,brabham-ford,Brabham-Ford,British -180,brabham-climax,Brabham-Climax,British -181,lds-climax,LDS-Climax,South African -182,lds-alfa_romeo,LDS-Alfa Romeo,South African -183,cooper-ford,Cooper-Ford,British -184,mclaren-ford,McLaren-Ford,British -185,mclaren-seren,McLaren-Serenissima,British -186,eagle-climax,Eagle-Climax,American -187,eagle-weslake,Eagle-Weslake,American -188,brabham-repco,Brabham-Repco,British -189,cooper-ferrari,Cooper-Ferrari,British -190,cooper-ats,Cooper-ATS,British -191,mclaren-brm,McLaren-BRM,British -192,cooper-brm,Cooper-BRM,British -193,matra-ford,Matra-Ford,French -194,brm-ford,BRM-Ford,British -195,mclaren-alfa_romeo,McLaren-Alfa Romeo,British -196,march-alfa_romeo,March-Alfa Romeo,British -197,march-ford,March-Ford,British -198,lotus-pw,Lotus-Pratt & Whitney,British -199,shadow-ford,Shadow-Ford,British -200,shadow-matra,Shadow-Matra,British -201,brabham-alfa_romeo,Brabham-Alfa Romeo,British -202,lotus_racing,Lotus,Malaysian -203,marussia,Marussia,Russian -204,caterham,Caterham,Malaysian -205,lotus_f1,Lotus F1,British -206,manor,Manor Marussia,British -207,haas,Haas F1 Team,American -208,racing_point,Racing Point,British -209,alphatauri,AlphaTauri,Italian -210,alpine,Alpine F1 Team,French diff --git a/scripts/f1_data/drivers.csv b/scripts/f1_data/drivers.csv deleted file mode 100644 index 513a207f..00000000 --- a/scripts/f1_data/drivers.csv +++ /dev/null @@ -1,858 +0,0 @@ -driverId,driverRef,code,forename,surname,dob,nationality -0,hamilton,HAM,Lewis,Hamilton,1985-01-07,British -1,heidfeld,HEI,Nick,Heidfeld,1977-05-10,German -2,rosberg,ROS,Nico,Rosberg,1985-06-27,German -3,alonso,ALO,Fernando,Alonso,1981-07-29,Spanish -4,kovalainen,KOV,Heikki,Kovalainen,1981-10-19,Finnish -5,nakajima,NAK,Kazuki,Nakajima,1985-01-11,Japanese -6,bourdais,BOU,Sébastien,Bourdais,1979-02-28,French -7,raikkonen,RAI,Kimi,Räikkönen,1979-10-17,Finnish -8,kubica,KUB,Robert,Kubica,1984-12-07,Polish -9,glock,GLO,Timo,Glock,1982-03-18,German -10,sato,SAT,Takuma,Sato,1977-01-28,Japanese -11,piquet_jr,PIQ,Nelson,Piquet Jr.,1985-07-25,Brazilian -12,massa,MAS,Felipe,Massa,1981-04-25,Brazilian -13,coulthard,COU,David,Coulthard,1971-03-27,British -14,trulli,TRU,Jarno,Trulli,1974-07-13,Italian -15,sutil,SUT,Adrian,Sutil,1983-01-11,German -16,webber,WEB,Mark,Webber,1976-08-27,Australian -17,button,BUT,Jenson,Button,1980-01-19,British -18,davidson,DAV,Anthony,Davidson,1979-04-18,British -19,vettel,VET,Sebastian,Vettel,1987-07-03,German -20,fisichella,FIS,Giancarlo,Fisichella,1973-01-14,Italian -21,barrichello,BAR,Rubens,Barrichello,1972-05-23,Brazilian -22,ralf_schumacher,SCH,Ralf,Schumacher,1975-06-30,German -23,liuzzi,LIU,Vitantonio,Liuzzi,1980-08-06,Italian -24,wurz,WUR,Alexander,Wurz,1974-02-15,Austrian -25,speed,SPE,Scott,Speed,1983-01-24,American -26,albers,ALB,Christijan,Albers,1979-04-16,Dutch -27,markus_winkelhock,WIN,Markus,Winkelhock,1980-06-13,German -28,yamamoto,YAM,Sakon,Yamamoto,1982-07-09,Japanese -29,michael_schumacher,MSC,Michael,Schumacher,1969-01-03,German -30,montoya,MON,Juan,Pablo Montoya,1975-09-20,Colombian -31,klien,KLI,Christian,Klien,1983-02-07,Austrian -32,monteiro,TMO,Tiago,Monteiro,1976-07-24,Portuguese -33,ide,IDE,Yuji,Ide,1975-01-21,Japanese -34,villeneuve,VIL,Jacques,Villeneuve,1971-04-09,Canadian -35,montagny,FMO,Franck,Montagny,1978-01-05,French -36,rosa,DLR,Pedro,de la Rosa,1971-02-24,Spanish -37,doornbos,DOO,Robert,Doornbos,1981-09-23,Dutch -38,karthikeyan,KAR,Narain,Karthikeyan,1977-01-14,Indian -39,friesacher,FRI,Patrick,Friesacher,1980-09-26,Austrian -40,zonta,ZON,Ricardo,Zonta,1976-03-23,Brazilian -41,pizzonia,PIZ,Antônio,Pizzonia,1980-09-11,Brazilian -42,matta,\N,Cristiano,da Matta,1973-09-19,Brazilian -43,panis,\N,Olivier,Panis,1966-09-02,French -44,pantano,\N,Giorgio,Pantano,1979-02-04,Italian -45,bruni,\N,Gianmaria,Bruni,1981-05-30,Italian -46,baumgartner,\N,Zsolt,Baumgartner,1981-01-01,Hungarian -47,gene,\N,Marc,Gené,1974-03-29,Spanish -48,frentzen,\N,Heinz-Harald,Frentzen,1967-05-18,German -49,verstappen,\N,Jos,Verstappen,1972-03-04,Dutch -50,wilson,\N,Justin,Wilson,1978-07-31,British -51,firman,\N,Ralph,Firman,1975-05-20,Irish -52,kiesa,\N,Nicolas,Kiesa,1978-03-03,Danish -53,burti,\N,Luciano,Burti,1975-03-05,Brazilian -54,alesi,\N,Jean,Alesi,1964-06-11,French -55,irvine,\N,Eddie,Irvine,1965-11-10,British -56,hakkinen,\N,Mika,Häkkinen,1968-09-28,Finnish -57,marques,\N,Tarso,Marques,1976-01-19,Brazilian -58,bernoldi,\N,Enrique,Bernoldi,1978-10-19,Brazilian -59,mazzacane,\N,Gastón,Mazzacane,1975-05-08,Argentine -60,enge,\N,Tomáš,Enge,1976-09-11,Czech -61,yoong,\N,Alex,Yoong,1976-07-20,Malaysian -62,salo,\N,Mika,Salo,1966-11-30,Finnish -63,diniz,\N,Pedro,Diniz,1970-05-22,Brazilian -64,herbert,\N,Johnny,Herbert,1964-06-25,British -65,mcnish,\N,Allan,McNish,1969-12-29,British -66,buemi,BUE,Sébastien,Buemi,1988-10-31,Swiss -67,takagi,\N,Toranosuke,Takagi,1974-02-12,Japanese -68,badoer,BAD,Luca,Badoer,1971-01-25,Italian -69,zanardi,\N,Alessandro,Zanardi,1966-10-23,Italian -70,damon_hill,\N,Damon,Hill,1960-09-17,British -71,sarrazin,\N,Stéphane,Sarrazin,1975-11-02,French -72,rosset,\N,Ricardo,Rosset,1968-07-27,Brazilian -73,tuero,\N,Esteban,Tuero,1978-04-22,Argentine -74,nakano,\N,Shinji,Nakano,1971-04-01,Japanese -75,magnussen,MAG,Jan,Magnussen,1973-07-04,Danish -76,berger,\N,Gerhard,Berger,1959-08-27,Austrian -77,larini,\N,Nicola,Larini,1964-03-19,Italian -78,katayama,\N,Ukyo,Katayama,1963-05-29,Japanese -79,sospiri,\N,Vincenzo,Sospiri,1966-10-07,Italian -80,morbidelli,\N,Gianni,Morbidelli,1968-01-13,Italian -81,fontana,\N,Norberto,Fontana,1975-01-20,Argentine -82,lamy,\N,Pedro,Lamy,1972-03-20,Portuguese -83,brundle,\N,Martin,Brundle,1959-06-01,British -84,montermini,\N,Andrea,Montermini,1964-05-30,Italian -85,lavaggi,\N,Giovanni,Lavaggi,1958-02-18,Italian -86,blundell,\N,Mark,Blundell,1966-04-08,British -87,suzuki,\N,Aguri,Suzuki,1960-09-08,Japanese -88,inoue,\N,Taki,Inoue,1963-09-05,Japanese -89,moreno,\N,Roberto,Moreno,1959-02-11,Brazilian -90,wendlinger,\N,Karl,Wendlinger,1968-12-20,Austrian -91,gachot,\N,Bertrand,Gachot,1962-12-23,Belgian -92,schiattarella,\N,Domenico,Schiattarella,1967-11-17,Italian -93,martini,\N,Pierluigi,Martini,1961-04-23,Italian -94,mansell,\N,Nigel,Mansell,1953-08-08,British -95,boullion,\N,Jean-Christophe,Boullion,1969-12-27,French -96,papis,\N,Massimiliano,Papis,1969-10-03,Italian -97,deletraz,\N,Jean-Denis,Délétraz,1963-10-01,Swiss -98,tarquini,\N,Gabriele,Tarquini,1962-03-02,Italian -99,comas,\N,Érik,Comas,1963-09-28,French -100,brabham,\N,David,Brabham,1965-09-05,Australian -101,senna,\N,Ayrton,Senna,1960-03-21,Brazilian -102,bernard,\N,Éric,Bernard,1964-08-24,French -103,fittipaldi,\N,Christian,Fittipaldi,1971-01-18,Brazilian -104,alboreto,\N,Michele,Alboreto,1956-12-23,Italian -105,beretta,\N,Olivier,Beretta,1969-11-23,Monegasque -106,ratzenberger,\N,Roland,Ratzenberger,1960-07-04,Austrian -107,belmondo,\N,Paul,Belmondo,1963-04-23,French -108,lehto,\N,Jyrki,Järvilehto,1966-01-31,Finnish -109,cesaris,\N,Andrea,de Cesaris,1959-05-31,Italian -110,gounon,\N,Jean-Marc,Gounon,1963-01-01,French -111,alliot,\N,Philippe,Alliot,1954-07-27,French -112,adams,\N,Philippe,Adams,1969-11-19,Belgian -113,dalmas,\N,Yannick,Dalmas,1961-07-28,French -114,noda,\N,Hideki,Noda,1969-03-07,Japanese -115,lagorce,\N,Franck,Lagorce,1968-09-01,French -116,prost,\N,Alain,Prost,1955-02-24,French -117,warwick,\N,Derek,Warwick,1954-08-27,British -118,patrese,\N,Riccardo,Patrese,1954-04-17,Italian -119,barbazza,\N,Fabrizio,Barbazza,1963-04-02,Italian -120,andretti,\N,Michael,Andretti,1962-10-05,American -121,capelli,\N,Ivan,Capelli,1963-05-24,Italian -122,boutsen,\N,Thierry,Boutsen,1957-07-13,Belgian -123,apicella,\N,Marco,Apicella,1965-10-07,Italian -124,naspetti,\N,Emanuele,Naspetti,1968-02-24,Italian -125,toshio_suzuki,\N,Toshio,Suzuki,1955-03-10,Japanese -126,gugelmin,\N,Maurício,Gugelmin,1963-04-20,Brazilian -127,poele,\N,Eric,van de Poele,1961-09-30,Belgian -128,grouillard,\N,Olivier,Grouillard,1958-09-02,French -129,chiesa,\N,Andrea,Chiesa,1964-05-06,Swiss -130,modena,\N,Stefano,Modena,1963-05-12,Italian -131,amati,\N,Giovanna,Amati,1959-07-20,Italian -132,caffi,\N,Alex,Caffi,1964-03-18,Italian -133,bertaggia,\N,Enrico,Bertaggia,1964-09-19,Italian -134,mccarthy,\N,Perry,McCarthy,1961-03-03,British -135,lammers,\N,Jan,Lammers,1956-06-02,Dutch -136,piquet,\N,Nelson,Piquet,1952-08-17,Brazilian -137,satoru_nakajima,\N,Satoru,Nakajima,1953-02-23,Japanese -138,pirro,\N,Emanuele,Pirro,1962-01-12,Italian -139,johansson,\N,Stefan,Johansson,1956-09-08,Swedish -140,bailey,\N,Julian,Bailey,1961-10-09,British -141,chaves,\N,Pedro,Chaves,1965-02-27,Portuguese -142,bartels,\N,Michael,Bartels,1968-03-08,German -143,hattori,\N,Naoki,Hattori,1966-06-13,Japanese -144,nannini,\N,Alessandro,Nannini,1959-07-07,Italian -145,schneider,\N,Bernd,Schneider,1964-07-20,German -146,barilla,\N,Paolo,Barilla,1961-04-20,Italian -147,foitek,\N,Gregor,Foitek,1965-03-27,Swiss -148,langes,\N,Claudio,Langes,1960-07-20,Italian -149,gary_brabham,\N,Gary,Brabham,1961-03-29,Australian -150,donnelly,\N,Martin,Donnelly,1964-03-26,British -151,giacomelli,\N,Bruno,Giacomelli,1952-09-10,Italian -152,alguersuari,ALG,Jaime,Alguersuari,1990-03-23,Spanish -153,grosjean,GRO,Romain,Grosjean,1986-04-17,French -154,kobayashi,KOB,Kamui,Kobayashi,1986-09-13,Japanese -155,palmer,\N,Jonathan,Palmer,1956-11-07,British -156,danner,\N,Christian,Danner,1958-04-04,German -157,cheever,\N,Eddie,Cheever,1958-01-10,American -158,sala,\N,Luis,Pérez-Sala,1959-05-15,Spanish -159,ghinzani,\N,Piercarlo,Ghinzani,1952-01-16,Italian -160,weidler,\N,Volker,Weidler,1962-03-18,German -161,raphanel,\N,Pierre-Henri,Raphanel,1961-05-27,French -162,arnoux,\N,René,Arnoux,1948-07-04,French -163,joachim_winkelhock,\N,Joachim,Winkelhock,1960-10-24,German -164,larrauri,\N,Oscar,Larrauri,1954-08-19,Argentine -165,streiff,\N,Philippe,Streiff,1955-06-26,French -166,campos,\N,Adrián,Campos,1960-06-17,Spanish -167,schlesser,\N,Jean-Louis,Schlesser,1948-09-12,French -168,fabre,\N,Pascal,Fabre,1960-01-09,French -169,fabi,\N,Teo,Fabi,1955-03-09,Italian -170,forini,\N,Franco,Forini,1958-09-22,Swiss -171,laffite,\N,Jacques,Laffite,1943-11-21,French -172,angelis,\N,Elio,de Angelis,1958-03-26,Italian -173,dumfries,\N,Johnny,Dumfries,1958-04-26,British -174,tambay,\N,Patrick,Tambay,1949-06-25,French -175,surer,\N,Marc,Surer,1951-09-18,Swiss -176,keke_rosberg,\N,Keke,Rosberg,1948-12-06,Finnish -177,jones,\N,Alan,Jones,1946-11-02,Australian -178,rothengatter,\N,Huub,Rothengatter,1954-10-08,Dutch -179,berg,\N,Allen,Berg,1961-08-01,Canadian -180,manfred_winkelhock,\N,Manfred,Winkelhock,1951-10-06,German -181,lauda,\N,Niki,Lauda,1949-02-22,Austrian -182,hesnault,\N,François,Hesnault,1956-12-30,French -183,baldi,\N,Mauro,Baldi,1954-01-31,Italian -184,bellof,\N,Stefan,Bellof,1957-11-20,German -185,acheson,\N,Kenny,Acheson,1957-11-27,British -186,watson,\N,John,Watson,1946-05-04,British -187,cecotto,\N,Johnny,Cecotto,1956-01-25,Venezuelan -188,gartner,\N,Jo,Gartner,1954-01-24,Austrian -189,corrado_fabi,\N,Corrado,Fabi,1961-04-12,Italian -190,thackwell,\N,Mike,Thackwell,1961-03-30,New Zealander -191,serra,\N,Chico,Serra,1957-02-03,Brazilian -192,sullivan,\N,Danny,Sullivan,1950-03-09,American -193,salazar,\N,Eliseo,Salazar,1954-11-14,Chilean -194,guerrero,\N,Roberto,Guerrero,1958-11-16,Colombian -195,boesel,\N,Raul,Boesel,1957-12-04,Brazilian -196,jarier,\N,Jean-Pierre,Jarier,1946-07-10,French -197,villeneuve_sr,\N,Jacques,Villeneuve Sr.,1953-11-04,Canadian -198,reutemann,\N,Carlos,Reutemann,1942-04-12,Argentine -199,mass,\N,Jochen,Mass,1946-09-30,German -200,borgudd,\N,Slim,Borgudd,1946-11-25,Swedish -201,pironi,\N,Didier,Pironi,1952-03-26,French -202,gilles_villeneuve,\N,Gilles,Villeneuve,1950-01-18,Canadian -203,paletti,\N,Riccardo,Paletti,1958-06-15,Italian -204,henton,\N,Brian,Henton,1946-09-19,British -205,daly,\N,Derek,Daly,1953-03-11,Irish -206,mario_andretti,\N,Mario,Andretti,1940-02-28,American -207,villota,\N,Emilio,de Villota,1946-07-26,Spanish -208,lees,\N,Geoff,Lees,1951-05-01,British -209,byrne,\N,Tommy,Byrne,1958-05-06,Irish -210,keegan,\N,Rupert,Keegan,1955-02-26,British -211,rebaque,\N,Hector,Rebaque,1956-02-05,Mexican -212,gabbiani,\N,Beppe,Gabbiani,1957-01-02,Italian -213,cogan,\N,Kevin,Cogan,1956-03-31,American -214,guerra,\N,Miguel Ángel,Guerra,1953-08-31,Argentine -215,stohr,\N,Siegfried,Stohr,1952-10-10,Italian -216,zunino,\N,Ricardo,Zunino,1949-04-13,Argentine -217,londono,\N,Ricardo,Londoño,1949-08-08,Colombian -218,jabouille,\N,Jean-Pierre,Jabouille,1942-10-01,French -219,francia,\N,Giorgio,Francia,1947-11-08,Italian -220,depailler,\N,Patrick,Depailler,1944-08-09,French -221,scheckter,\N,Jody,Scheckter,1950-01-29,South African -222,regazzoni,\N,Clay,Regazzoni,1939-09-05,Swiss -223,emerson_fittipaldi,\N,Emerson,Fittipaldi,1946-12-12,Brazilian -224,kennedy,\N,Dave,Kennedy,1953-01-15,Irish -225,south,\N,Stephen,South,1952-02-19,British -226,needell,\N,Tiff,Needell,1951-10-29,British -227,desire_wilson,\N,Desiré,Wilson,1953-11-26,South African -228,ertl,\N,Harald,Ertl,1948-08-31,Austrian -229,brambilla,\N,Vittorio,Brambilla,1937-11-11,Italian -230,hunt,\N,James,Hunt,1947-08-29,British -231,merzario,\N,Arturo,Merzario,1943-03-11,Italian -232,stuck,\N,Hans-Joachim,Stuck,1951-01-01,German -233,brancatelli,\N,Gianfranco,Brancatelli,1950-01-18,Italian -234,ickx,\N,Jacky,Ickx,1945-01-01,Belgian -235,gaillard,\N,Patrick,Gaillard,1952-02-12,French -236,ribeiro,\N,Alex,Ribeiro,1948-11-07,Brazilian -237,peterson,\N,Ronnie,Peterson,1944-02-14,Swedish -238,lunger,\N,Brett,Lunger,1945-11-14,American -239,ongais,\N,Danny,Ongais,1942-05-21,American -240,leoni,\N,Lamberto,Leoni,1953-05-24,Italian -241,galica,\N,Divina,Galica,1944-08-13,British -242,stommelen,\N,Rolf,Stommelen,1943-07-11,German -243,colombo,\N,Alberto,Colombo,1946-02-23,Italian -244,trimmer,\N,Tony,Trimmer,1943-01-24,British -245,binder,\N,Hans,Binder,1948-06-12,Austrian -246,bleekemolen,\N,Michael,Bleekemolen,1949-10-02,Dutch -247,gimax,\N,Carlo,Franchi,1938-01-01,Italian -248,rahal,\N,Bobby,Rahal,1953-01-10,American -249,pace,\N,Carlos,Pace,1944-10-06,Brazilian -250,ian_scheckter,\N,Ian,Scheckter,1947-08-22,South African -251,pryce,\N,Tom,Pryce,1949-06-11,British -252,hoffmann,\N,Ingo,Hoffmann,1953-02-28,Brazilian -253,zorzi,\N,Renzo,Zorzi,1946-12-12,Italian -254,nilsson,\N,Gunnar,Nilsson,1948-11-20,Swedish -255,perkins,\N,Larry,Perkins,1950-03-18,Australian -256,hayje,\N,Boy,Lunger,1949-05-03,Dutch -257,neve,\N,Patrick,Nève,1949-10-13,Belgian -258,purley,\N,David,Purley,1945-01-26,British -259,andersson,\N,Conny,Andersson,1939-12-28,Swedish -260,dryver,\N,Bernard,de Dryver,1952-09-19,Belgian -261,oliver,\N,Jackie,Oliver,1942-08-14,British -262,kozarowitzky,\N,Mikko,Kozarowitzky,1948-05-17,Finnish -263,sutcliffe,\N,Andy,Sutcliffe,1947-05-09,British -264,edwards,\N,Guy,Edwards,1942-12-30,British -265,mcguire,\N,Brian,McGuire,1945-12-13,Australian -266,schuppan,\N,Vern,Schuppan,1943-03-19,Australian -267,heyer,\N,Hans,Heyer,1943-03-16,German -268,pilette,\N,Teddy,Pilette,1942-07-26,Belgian -269,ashley,\N,Ian,Ashley,1947-10-26,British -270,kessel,\N,Loris,Kessel,1950-04-01,Swiss -271,takahashi,\N,Kunimitsu,Takahashi,1940-01-29,Japanese -272,hoshino,\N,Kazuyoshi,Hoshino,1947-07-01,Japanese -273,takahara,\N,Noritake,Takahara,1951-06-06,Japanese -274,lombardi,\N,Lella,Lombardi,1941-03-26,Italian -275,evans,\N,Bob,Evans,1947-06-11,British -276,leclere,\N,Michel,Leclère,1946-03-18,French -277,amon,\N,Chris,Amon,1943-07-20,New Zealander -278,zapico,\N,Emilio,Zapico,1944-05-27,Spanish -279,pescarolo,\N,Henri,Pescarolo,1942-09-25,French -280,nelleman,\N,Jac,Nelleman,1944-04-19,Danish -281,magee,\N,Damien,Magee,1945-11-17,British -282,wilds,\N,Mike,Wilds,1946-01-07,British -283,pesenti_rossi,\N,Alessandro,Pesenti-Rossi,1942-08-31,Italian -284,stuppacher,\N,Otto,Stuppacher,1947-03-03,Austrian -285,brown,\N,Warwick,Brown,1949-12-24,Australian -286,hasemi,\N,Masahiro,Hasemi,1945-11-13,Japanese -287,donohue,\N,Mark,Donohue,1937-03-18,American -288,hill,\N,Graham,Hill,1929-02-15,British -289,wilson_fittipaldi,\N,Wilson,Fittipaldi,1943-12-25,Brazilian -290,tunmer,\N,Guy,Tunmer,1948-12-01,South African -291,keizan,\N,Eddie,Keizan,1944-09-12,South African -292,charlton,\N,Dave,Charlton,1936-10-27,South African -293,brise,\N,Tony,Brise,1952-03-28,British -294,wunderink,\N,Roelof,Wunderink,1948-12-12,Dutch -295,migault,\N,François,Migault,1944-12-04,French -296,palm,\N,Torsten,Palm,1947-07-23,Swedish -297,lennep,\N,Gijs,van Lennep,1942-03-16,Dutch -298,fushida,\N,Hiroshi,Fushida,1946-03-10,Japanese -299,nicholson,\N,John,Nicholson,1941-10-06,New Zealander -300,morgan,\N,Dave,Morgan,1944-08-07,British -301,crawford,\N,Jim,Crawford,1948-02-13,British -302,vonlanthen,\N,Jo,Vonlanthen,1942-05-31,Swiss -303,hulme,\N,Denny,Hulme,1936-06-18,New Zealander -304,hailwood,\N,Mike,Hailwood,1940-04-02,British -305,beltoise,\N,Jean-Pierre,Beltoise,1937-04-26,French -306,ganley,\N,Howden,Ganley,1941-12-24,New Zealander -307,robarts,\N,Richard,Robarts,1944-09-22,British -308,revson,\N,Peter,Revson,1939-02-27,American -309,driver,\N,Paddy,Driver,1934-05-13,South African -310,belso,\N,Tom,Belsø,1942-08-27,Danish -311,redman,\N,Brian,Redman,1937-03-09,British -312,opel,\N,Rikky,von Opel,1947-10-14,Liechtensteiner -313,schenken,\N,Tim,Schenken,1943-09-26,Australian -314,larrousse,\N,Gérard,Larrousse,1940-05-23,French -315,kinnunen,\N,Leo,Kinnunen,1943-08-05,Finnish -316,wisell,\N,Reine,Wisell,1941-09-30,Swedish -317,roos,\N,Bertil,Roos,1943-10-12,Swedish -318,dolhem,\N,José,Dolhem,1944-04-26,French -319,gethin,\N,Peter,Gethin,1940-02-21,British -320,bell,\N,Derek,Bell,1941-10-31,British -321,hobbs,\N,David,Hobbs,1939-06-09,British -322,quester,\N,Dieter,Quester,1939-05-30,Austrian -323,koinigg,\N,Helmuth,Koinigg,1948-11-03,Austrian -324,facetti,\N,Carlo,Facetti,1935-06-26,Italian -325,wietzes,\N,Eppie,Wietzes,1938-05-28,Canadian -326,cevert,\N,François,Cevert,1944-02-25,French -327,stewart,\N,Jackie,Stewart,1939-06-11,British -328,beuttler,\N,Mike,Beuttler,1940-04-13,British -329,galli,\N,Nanni,Galli,1940-10-02,Italian -330,bueno,\N,Luiz,Bueno,1937-01-16,Brazilian -331,follmer,\N,George,Follmer,1934-01-27,American -332,adamich,\N,Andrea,de Adamich,1941-10-03,Italian -333,pretorius,\N,Jackie,Pretorius,1934-11-22,South African -334,williamson,\N,Roger,Williamson,1948-02-02,British -335,mcrae,\N,Graham,McRae,1940-03-05,New Zealander -336,marko,\N,Helmut,Marko,1943-04-27,Austrian -337,walker,\N,David,Walker,1941-06-10,Australian -338,roig,\N,Alex,Soler-Roig,1932-10-29,Spanish -339,love,\N,John,Love,1924-12-07,Rhodesian -340,surtees,\N,John,Surtees,1934-02-11,British -341,barber,\N,Skip,Barber,1936-11-16,American -342,brack,\N,Bill,Brack,1935-12-26,Canadian -343,posey,\N,Sam,Posey,1944-05-26,American -344,rodriguez,\N,Pedro,Rodríguez,1940-01-18,Mexican -345,siffert,\N,Jo,Siffert,1936-07-07,Swiss -346,bonnier,\N,Jo,Bonnier,1930-01-31,Swedish -347,mazet,\N,François,Mazet,1943-02-24,French -348,jean,\N,Max,Jean,1943-07-27,French -349,elford,\N,Vic,Elford,1935-06-10,British -350,moser,\N,Silvio,Moser,1941-04-24,Swiss -351,eaton,\N,George,Eaton,1945-11-12,Canadian -352,lovely,\N,Pete,Lovely,1926-04-11,American -353,craft,\N,Chris,Craft,1939-11-17,British -354,Cannoc,\N,John,Cannon,1933-06-21,Canadian -355,jack_brabham,\N,Jack,Brabham,1926-04-02,Australian -356,miles,\N,John,Miles,1943-06-14,British -357,rindt,\N,Jochen,Rindt,1942-04-18,Austrian -358,gavin,\N,Johnny,Servoz-Gavin,1942-01-18,French -359,mclaren,\N,Bruce,McLaren,1937-08-30,New Zealander -360,courage,\N,Piers,Courage,1942-05-27,British -361,klerk,\N,Peter,de Klerk,1935-03-16,South African -362,giunti,\N,Ignazio,Giunti,1941-08-30,Italian -363,gurney,\N,Dan,Gurney,1931-04-13,American -364,hahne,\N,Hubert,Hahne,1935-03-28,German -365,hutchison,\N,Gus,Hutchison,1937-04-26,American -366,westbury,\N,Peter,Westbury,1938-05-26,British -367,tingle,\N,Sam,Tingle,1921-08-24,Rhodesian -368,rooyen,\N,Basil,van Rooyen,1939-04-19,South African -369,attwood,\N,Richard,Attwood,1940-04-04,British -370,pease,\N,Al,Pease,1921-10-15,Canadian -371,cordts,\N,John,Cordts,1935-07-23,Canadian -372,clark,\N,Jim,Clark,1936-03-04,British -373,spence,\N,Mike,Spence,1936-12-30,British -374,scarfiotti,\N,Ludovico,Scarfiotti,1933-10-18,Italian -375,bianchi,BIA,Lucien,Bianchi,1934-11-10,Belgian -376,jo_schlesser,\N,Jo,Schlesser,1928-05-18,French -377,widdows,\N,Robin,Widdows,1942-05-27,British -378,ahrens,\N,Kurt,Ahrens,1940-04-19,German -379,gardner,\N,Frank,Gardner,1930-10-01,Australian -380,unser,\N,Bobby,Unser,1934-02-20,American -381,solana,\N,Moisés,Solana,1935-12-26,Mexican -382,anderson,\N,Bob,Anderson,1931-05-19,British -383,botha,\N,Luki,Botha,1930-01-16,South African -384,bandini,\N,Lorenzo,Bandini,1935-12-21,Italian -385,ginther,\N,Richie,Ginther,1930-08-05,American -386,parkes,\N,Mike,Parkes,1931-09-24,British -387,irwin,\N,Chris,Irwin,1942-06-27,British -388,ligier,\N,Guy,Ligier,1930-07-12,French -389,rees,\N,Alan,Rees,1938-01-12,British -390,hart,\N,Brian,Hart,1936-09-07,British -391,fisher,\N,Mike,Fisher,1943-03-13,American -392,tom_jones,\N,Tom,Jones,1943-04-26,American -393,baghetti,\N,Giancarlo,Baghetti,1934-12-25,Italian -394,williams,\N,Jonathan,Williams,1942-10-26,British -395,bondurant,\N,Bob,Bondurant,1933-04-27,American -396,arundell,\N,Peter,Arundell,1933-11-08,British -397,vic_wilson,\N,Vic,Wilson,1931-04-14,British -398,taylor,\N,John,Taylor,1933-03-23,British -399,lawrence,\N,Chris,Lawrence,1933-07-27,British -400,trevor_taylor,\N,Trevor,Taylor,1936-12-26,British -401,geki,\N,Giacomo,Russo,1937-10-23,Italian -402,phil_hill,\N,Phil,Hill,1927-04-20,American -403,ireland,\N,Innes,Ireland,1930-06-12,British -404,bucknum,\N,Ronnie,Bucknum,1936-04-05,American -405,hawkins,\N,Paul,Hawkins,1937-10-12,Australian -406,prophet,\N,David,Prophet,1937-10-09,British -407,maggs,\N,Tony,Maggs,1937-02-09,South African -408,blokdyk,\N,Trevor,Blokdyk,1935-11-30,South African -409,lederle,\N,Neville,Lederle,1938-09-25,South African -410,serrurier,\N,Doug,Serrurier,1920-12-09,South African -411,niemann,\N,Brausch,Niemann,1939-01-07,South African -412,pieterse,\N,Ernie,Pieterse,1938-07-04,South African -413,puzey,\N,Clive,Puzey,1941-07-11,Rhodesian -414,reed,\N,Ray,Reed,1932-04-30,South African -415,clapham,\N,David,Clapham,1931-05-18,South African -416,blignaut,\N,Alex,Blignaut,1932-11-30,South African -417,gregory,\N,Masten,Gregory,1932-02-29,American -418,rhodes,\N,John,Rhodes,1927-08-18,British -419,raby,\N,Ian,Raby,1921-09-22,British -420,rollinson,\N,Alan,Rollinson,1943-05-15,British -421,gubby,\N,Brian,Gubby,1934-04-17,British -422,mitter,\N,Gerhard,Mitter,1935-08-30,German -423,bussinello,\N,Roberto,Bussinello,1927-10-04,Italian -424,vaccarella,\N,Nino,Vaccarella,1933-03-04,Italian -425,bassi,\N,Giorgio,Bassi,1934-01-20,Italian -426,trintignant,\N,Maurice,Trintignant,1917-10-30,French -427,collomb,\N,Bernard,Collomb,1930-10-07,French -428,andre_pilette,\N,André,Pilette,1918-10-06,Belgian -429,beaufort,\N,Carel Godin,de Beaufort,1934-04-10,Dutch -430,barth,\N,Edgar,Barth,1917-01-26,German -431,cabral,\N,Mário de Araújo,Cabral,1934-01-15,Portuguese -432,hansgen,\N,Walt,Hansgen,1919-10-28,American -433,sharp,\N,Hap,Sharp,1928-01-01,American -434,mairesse,\N,Willy,Mairesse,1928-10-01,Belgian -435,campbell-jones,\N,John,Campbell-Jones,1930-01-21,British -436,burgess,\N,Ian,Burgess,1930-07-06,British -437,settember,\N,Tony,Settember,1926-07-10,American -438,estefano,\N,Nasif,Estéfano,1932-11-18,Argentine -439,hall,\N,Jim,Hall,1935-07-23,American -440,parnell,\N,Tim,Parnell,1932-06-25,British -441,kuhnke,\N,Kurt,Kuhnke,1910-04-30,German -442,ernesto_brambilla,\N,Ernesto,Brambilla,1934-01-31,Italian -443,lippi,\N,Roberto,Lippi,1926-10-17,Italian -444,seiffert,\N,Günther,Seiffert,1937-10-18,German -445,abate,\N,Carlo,Abate,1932-07-10,Italian -446,starrabba,\N,Gaetano,Starrabba,1932-12-03,Italian -447,broeker,\N,Peter,Broeker,1926-05-15,Canadian -448,ward,\N,Rodger,Ward,1921-01-10,American -449,vos,\N,Ernie,de Vos,1941-07-01,Dutch -450,dochnal,\N,Frank,Dochnal,1920-10-08,American -451,monarch,\N,Thomas,Monarch,1945-09-03,American -452,gasly,GAS,Pierre,Gasly,1996-02-07,French -453,lewis,\N,Jackie,Lewis,1936-11-01,British -454,ricardo_rodriguez,\N,Ricardo,Rodríguez,1942-02-14,Mexican -455,seidel,\N,Wolfgang,Seidel,1926-07-04,German -456,salvadori,\N,Roy,Salvadori,1922-05-12,British -457,pon,\N,Ben,Pon,1936-12-09,Dutch -458,slotemaker,\N,Rob,Slotemaker,1929-06-13,Dutch -459,marsh,\N,Tony,Marsh,1931-07-20,British -460,ashmore,\N,Gerry,Ashmore,1936-07-25,British -461,schiller,\N,Heinz,Schiller,1930-01-25,Swiss -462,davis,\N,Colin,Davis,1933-07-29,British -463,chamberlain,\N,Jay,Chamberlain,1925-12-29,American -464,shelly,\N,Tony,Shelly,1937-02-02,New Zealander -465,greene,\N,Keith,Greene,1938-01-05,British -466,walter,\N,Heini,Walter,1927-07-28,Swiss -467,prinoth,\N,Ernesto,Prinoth,1923-04-15,Italian -468,penske,\N,Roger,Penske,1937-02-20,American -469,schroeder,\N,Rob,Schroeder,1926-05-11,British -470,mayer,\N,Timmy,Mayer,1938-02-22,American -471,johnstone,\N,Bruce,Johnstone,1937-01-30,South African -472,harris,\N,Mike,Harris,1939-05-25,South African -473,hocking,\N,Gary,Hocking,1937-09-30,Rhodesian -474,vyver,\N,Syd,van der Vyver,1920-06-01,South African -475,moss,\N,Stirling,Moss,1929-09-17,British -476,trips,\N,Wolfgang,von Trips,1928-05-04,German -477,allison,\N,Cliff,Allison,1932-02-08,British -478,herrmann,\N,Hans,Herrmann,1928-02-23,German -479,brooks,\N,Tony,Brooks,1932-02-25,British -480,may,\N,Michael,May,1934-08-18,Swiss -481,henry_taylor,\N,Henry,Taylor,1932-12-16,British -482,gendebien,\N,Olivier,Gendebien,1924-01-12,Belgian -483,scarlatti,\N,Giorgio,Scarlatti,1921-10-02,Italian -484,naylor,\N,Brian,Naylor,1923-03-24,British -485,bordeu,\N,Juan Manuel,Bordeu,1934-01-28,Argentine -486,fairman,\N,Jack,Fairman,1913-03-15,British -487,natili,\N,Massimo,Natili,1935-07-28,Italian -488,monteverdi,\N,Peter,Monteverdi,1934-06-07,Swiss -489,pirocchi,\N,Renato,Pirocchi,1933-03-26,Italian -490,duke,\N,Geoff,Duke,1923-03-29,British -491,thiele,\N,Alfonso,Thiele,1920-04-05,American-Italian -492,boffa,\N,Menato,Boffa,1930-01-04,Italian -493,ryan,\N,Peter,Ryan,1940-06-10,Canadian -494,ruby,\N,Lloyd,Ruby,1928-01-12,American -495,ken_miles,\N,Ken,Miles,1918-11-01,British -496,menditeguy,\N,Carlos,Menditeguy,1914-08-10,Argentine -497,larreta,\N,Alberto Rodriguez,Larreta,1934-01-14,Argentine -498,gonzalez,\N,José Froilán,González,1922-10-05,Argentine -499,bonomi,\N,Roberto,Bonomi,1919-09-30,Argentine -500,munaron,\N,Gino,Munaron,1928-04-02,Italian -501,schell,\N,Harry,Schell,1921-06-29,American -502,stacey,\N,Alan,Stacey,1933-08-29,British -503,chimeri,\N,Ettore,Chimeri,1921-06-04,Venezuelan -504,creus,\N,Antonio,Creus,1924-10-28,Spanish -505,bristow,\N,Chris,Bristow,1937-12-02,British -506,halford,\N,Bruce,Halford,1931-05-18,British -507,daigh,\N,Chuck,Daigh,1923-11-29,American -508,reventlow,\N,Lance,Reventlow,1936-02-24,American -509,rathmann,\N,Jim,Rathmann,1928-07-16,American -510,goldsmith,\N,Paul,Goldsmith,1925-10-02,American -511,branson,\N,Don,Branson,1920-06-02,American -512,thomson,\N,Johnny,Thomson,1922-04-09,American -513,johnson,\N,Eddie,Johnson,1919-02-10,American -514,veith,\N,Bob,Veith,1926-11-01,American -515,tingelstad,\N,Bud,Tingelstad,1928-04-04,American -516,christie,\N,Bob,Christie,1924-04-04,American -517,amick,\N,Red,Amick,1929-01-19,American -518,darter,\N,Duane,Carter,1913-05-05,American -519,homeier,\N,Bill,Homeier,1918-08-31,American -520,hartley,\N,Gene,Hartley,1926-01-28,American -521,stevenson,\N,Chuck,Stevenson,1919-10-15,American -522,grim,\N,Bobby,Grim,1924-09-04,American -523,templeman,\N,Shorty,Templeman,1919-08-12,American -524,hurtubise,\N,Jim,Hurtubise,1932-12-05,American -525,bryan,\N,Jimmy,Bryan,1926-01-28,American -526,ruttman,\N,Troy,Ruttman,1930-03-11,American -527,sachs,\N,Eddie,Sachs,1927-05-28,American -528,freeland,\N,Don,Freeland,1925-03-25,American -529,bettenhausen,\N,Tony,Bettenhausen,1916-09-12,American -530,weiler,\N,Wayne,Weiler,1934-12-09,American -531,foyt,\N,Anthony,Foyt,1935-01-16,American -532,russo,\N,Eddie,Russo,1925-11-19,American -533,boyd,\N,Johnny,Boyd,1926-08-19,American -534,force,\N,Gene,Force,1916-06-15,American -535,mcwithey,\N,Jim,McWithey,1927-07-04,American -536,sutton,\N,Len,Sutton,1925-08-09,American -537,dick_rathmann,\N,Dick,Rathmann,1924-01-06,American -538,herman,\N,Al,Herman,1927-03-15,American -539,dempsey_wilson,\N,Dempsey,Wilson,1927-03-11,American -540,mike_taylor,\N,Mike,Taylor,1934-04-24,British -541,flockhart,\N,Ron,Flockhart,1923-06-16,British -542,piper,\N,David,Piper,1930-12-02,British -543,cabianca,\N,Giulio,Cabianca,1923-02-19,Italian -544,drogo,\N,Piero,Drogo,1926-08-08,Italian -545,gamble,\N,Fred,Gamble,1932-03-17,American -546,owen,\N,Arthur,Owen,1915-03-23,British -547,gould,\N,Horace,Gould,1918-09-20,British -548,drake,\N,Bob,Drake,1919-12-14,American -549,bueb,\N,Ivor,Bueb,1923-06-06,British -550,Changy,\N,Alain,de Changy,1922-02-05,Belgian -551,filippis,\N,Maria,de Filippis,1926-11-11,Italian -552,lucienbonnet,\N,Jean,Lucienbonnet,1923-01-07,French -553,testut,\N,André,Testut,1926-04-13,Monegasque -554,behra,\N,Jean,Behra,1921-02-16,French -555,paul_russo,\N,Paul,Russo,1914-04-10,American -556,daywalt,\N,Jimmy,Daywalt,1924-08-28,American -557,arnold,\N,Chuck,Arnold,1926-05-30,American -558,keller,\N,Al,Keller,1920-04-11,American -559,flaherty,\N,Pat,Flaherty,1926-01-06,American -560,cheesbourg,\N,Bill,Cheesbourg,1927-06-12,American -561,ray_crawford,\N,Ray,Crawford,1915-10-26,American -562,turner,\N,Jack,Turner,1920-02-12,American -563,weyant,\N,Chuck,Weyant,1923-04-03,American -564,larson,\N,Jud,Larson,1923-01-21,American -565,magill,\N,Mike,Magill,1920-02-08,American -566,shelby,\N,Carroll,Shelby,1923-01-11,American -567,orey,\N,Fritz,d'Orey,1938-03-25,Brazilian -568,fontes,\N,Azdrubal,Fontes,1922-12-26,Uruguayan -569,ashdown,\N,Peter,Ashdown,1934-10-16,British -570,bill_moss,\N,Bill,Moss,1933-09-04,British -571,dennis_taylor,\N,Dennis,Taylor,1921-06-12,British -572,blanchard,\N,Harry,Blanchard,1929-06-13,American -573,tomaso,\N,Alessandro,de Tomaso,1928-07-10,Argentine-Italian -574,constantine,\N,George,Constantine,1918-02-22,American -575,said,\N,Bob,Said,1932-05-05,American -576,cade,\N,Phil,Cade,1916-06-12,American -577,musso,\N,Luigi,Musso,1924-07-28,Italian -578,hawthorn,\N,Mike,Hawthorn,1929-04-10,British -579,fangio,\N,Juan,Fangio,1911-06-24,Argentine -580,godia,\N,Paco,Godia,1921-03-21,Spanish -581,collins,\N,Peter,Collins,1931-11-06,British -582,kavanagh,\N,Ken,Kavanagh,1923-12-12,Australian -583,gerini,\N,Gerino,Gerini,1928-08-10,Italian -584,kessler,\N,Bruce,Kessler,1936-03-23,American -585,emery,\N,Paul,Emery,1916-11-12,British -586,piotti,\N,Luigi,Piotti,1913-10-27,Italian -587,ecclestone,\N,Bernie,Ecclestone,1930-10-28,British -588,taramazzo,\N,Luigi,Taramazzo,1932-05-05,Italian -589,chiron,\N,Louis,Chiron,1899-08-03,Monegasque -590,lewis-evans,\N,Stuart,Lewis-Evans,1930-04-20,British -591,george_amick,\N,George,Amick,1924-10-24,American -592,reece,\N,Jimmy,Reece,1929-11-17,American -593,parsons,\N,Johnnie,Parsons,1918-07-04,American -594,tolan,\N,Johnnie,Tolan,1917-10-22,American -595,garrett,\N,Billy,Garrett,1933-04-24,American -596,elisian,\N,Ed,Elisian,1926-12-09,American -597,connor,\N,Pat,O'Connor,1928-10-09,American -598,jerry_unser,\N,Jerry,Unser,1932-11-15,American -599,bisch,\N,Art,Bisch,1926-11-10,American -600,goethals,\N,Christian,Goethals,1928-08-04,Belgian -601,gibson,\N,Dick,Gibson,1918-04-16,British -602,la_caze,\N,Robert,La Caze,1917-02-26,French -603,guelfi,\N,André,Guelfi,1919-05-06,French -604,picard,\N,François,Picard,1921-04-26,French -605,bridger,\N,Tom,Bridger,1934-06-24,British -606,portago,\N,Alfonso,de Portago,1928-10-11,Spanish -607,perdisa,\N,Cesare,Perdisa,1932-10-21,Italian -608,castellotti,\N,Eugenio,Castellotti,1930-10-10,Italian -609,simon,\N,André,Simon,1920-01-05,French -610,leston,\N,Les,Leston,1920-12-16,British -611,hanks,\N,Sam,Hanks,1914-07-13,American -612,linden,\N,Andy,Linden,1922-04-05,American -613,teague,\N,Marshall,Teague,1921-02-22,American -614,edmunds,\N,Don,Edmunds,1930-09-23,American -615,agabashian,\N,Fred,Agabashian,1913-08-21,American -616,george,\N,Elmer,George,1928-07-15,American -617,macdowel,\N,Mike,MacDowel,1932-09-13,British -618,mackay-fraser,\N,Herbert,MacKay-Fraser,1927-06-23,American -619,gerard,\N,Bob,Gerard,1914-01-19,British -620,maglioli,\N,Umberto,Maglioli,1928-06-05,Italian -621,england,\N,Paul,England,1929-03-28,Australian -622,landi,\N,Chico,Landi,1907-07-14,Brazilian -623,uria,\N,Alberto,Uria,1924-07-11,Uruguayan -624,ramos,\N,Hernando,da Silva Ramos,1925-12-07,Brazilian -625,bayol,\N,Élie,Bayol,1914-02-28,French -626,manzon,\N,Robert,Manzon,1917-04-12,French -627,rosier,\N,Louis,Rosier,1905-11-05,French -628,sweikert,\N,Bob,Sweikert,1926-05-20,American -629,griffith,\N,Cliff,Griffith,1916-02-06,American -630,dinsmore,\N,Duke,Dinsmore,1913-04-10,American -631,andrews,\N,Keith,Andrews,1920-06-15,American -632,frere,\N,Paul,Frère,1917-01-30,Belgian -633,villoresi,\N,Luigi,Villoresi,1909-05-16,Italian -634,scotti,\N,Piero,Scotti,1909-11-11,Italian -635,chapman,\N,Colin,Chapman,1928-05-19,British -636,titterington,\N,Desmond,Titterington,1928-05-01,British -637,scott_Brown,\N,Archie,Scott Brown,1927-05-13,British -638,volonterio,\N,Ottorino,Volonterio,1917-12-07,Swiss -639,milhoux,\N,André,Milhoux,1928-12-09,Belgian -640,graffenried,\N,Toulo,de Graffenried,1914-05-18,Swiss -641,taruffi,\N,Piero,Taruffi,1906-10-12,Italian -642,farina,\N,Nino,Farina,1906-10-30,Italian -643,mieres,\N,Roberto,Mieres,1924-12-03,Argentine -644,mantovani,\N,Sergio,Mantovani,1929-05-22,Italian -645,bucci,\N,Clemar,Bucci,1920-09-04,Argentine -646,iglesias,\N,Jesús,Iglesias,1922-02-22,Argentine -647,ascari,\N,Alberto,Ascari,1918-07-13,Italian -648,kling,\N,Karl,Kling,1910-09-16,German -649,birger,\N,Pablo,Birger,1924-01-07,Argentine -650,pollet,\N,Jacques,Pollet,1922-07-02,French -651,macklin,\N,Lance,Macklin,1919-09-02,British -652,whiteaway,\N,Ted,Whiteaway,1928-11-01,British -653,davies,\N,Jimmy,Davies,1929-08-08,American -654,faulkner,\N,Walt,Faulkner,1920-02-16,American -655,niday,\N,Cal,Niday,1914-04-29,American -656,cross,\N,Art,Cross,1918-01-24,American -657,vukovich,\N,Bill,Vukovich,1918-12-13,American -658,mcgrath,\N,Jack,McGrath,1919-10-08,American -659,hoyt,\N,Jerry,Hoyt,1929-01-29,American -660,claes,\N,Johnny,Claes,1916-08-11,Belgian -661,peter_walker,\N,Peter,Walker,1912-10-07,British -662,sparken,\N,Mike,Sparken,1930-06-16,French -663,wharton,\N,Ken,Wharton,1916-03-21,British -664,mcalpine,\N,Kenneth,McAlpine,1920-09-21,British -665,marr,\N,Leslie,Marr,1922-08-14,British -666,rolt,\N,Tony,Rolt,1918-10-16,British -667,fitch,\N,John,Fitch,1917-08-04,American -668,lucas,\N,Jean,Lucas,1917-04-25,French -669,bira,\N,Prince,Bira,1914-07-15,Thai -670,marimon,\N,Onofre,Marimón,1923-12-19,Argentine -671,loyer,\N,Roger,Loyer,1907-08-05,French -672,daponte,\N,Jorge,Daponte,1923-06-05,Argentine -673,nazaruk,\N,Mike,Nazaruk,1921-10-02,American -674,crockett,\N,Larry,Crockett,1926-10-23,American -675,ayulo,\N,Manny,Ayulo,1921-10-20,American -676,armi,\N,Frank,Armi,1918-10-12,American -677,webb,\N,Travis,Webb,1910-10-08,American -678,duncan,\N,Len,Duncan,1911-07-25,American -679,mccoy,\N,Ernie,McCoy,1921-02-19,American -680,swaters,\N,Jacques,Swaters,1926-10-30,American -681,georges_berger,\N,Georges,Berger,1918-09-14,Belgian -682,beauman,\N,Don,Beauman,1928-07-26,British -683,thorne,\N,Leslie,Thorne,1916-06-23,British -684,whitehouse,\N,Bill,Whitehouse,1909-04-01,British -685,riseley_prichard,\N,John,Riseley-Prichard,1924-01-17,British -686,reg_parnell,\N,Reg,Parnell,1911-07-02,British -687,whitehead,\N,Peter,Whitehead,1914-11-12,British -688,brandon,\N,Eric,Brandon,1920-07-18,British -689,alan_brown,\N,Alan,Brown,1919-11-20,British -690,nuckey,\N,Rodney,Nuckey,1929-06-26,British -691,lang,\N,Hermann,Lang,1909-04-06,German -692,helfrich,\N,Theo,Helfrich,1913-05-13,German -693,wacker,\N,Fred,Wacker,1918-07-10,American -694,riu,\N,Giovanni,de Riu,1925-03-10,Italian -695,galvez,\N,Oscar,Gálvez,1913-08-17,Argentine -696,john_barber,\N,John,Barber,1929-07-22,British -697,bonetto,\N,Felice,Bonetto,1903-06-09,Italian -698,cruz,\N,Adolfo,Cruz,1923-06-28,Argentine -699,nalon,\N,Duke,Nalon,1913-03-02,American -700,scarborough,\N,Carl,Scarborough,1914-07-03,American -701,holland,\N,Bill,Holland,1907-12-18,American -702,bob_scott,\N,Bob,Scott,1928-10-04,American -703,legat,\N,Arthur,Legat,1898-11-01,Belgian -704,cabantous,\N,Yves,Cabantous,1904-10-08,French -705,crook,\N,Tony,Crook,1920-02-16,British -706,jimmy_stewart,\N,Jimmy,Stewart,1931-03-06,British -707,ian_stewart,\N,Ian,Stewart,1929-07-15,British -708,duncan_hamilton,\N,Duncan,Hamilton,1920-04-30,British -709,klodwig,\N,Ernst,Klodwig,1903-05-23,East German -710,krause,\N,Rudolf,Krause,1907-03-30,East German -711,karch,\N,Oswald,Karch,1917-03-06,German -712,heeks,\N,Willi,Heeks,1922-02-13,German -713,fitzau,\N,Theo,Fitzau,1923-02-10,East German -714,adolff,\N,Kurt,Adolff,1921-11-05,German -715,bechem,\N,Günther,Bechem,1921-12-21,German -716,bauer,\N,Erwin,Bauer,1912-07-17,German -717,hans_stuck,\N,Hans,von Stuck,1900-12-27,German -718,loof,\N,Ernst,Loof,1907-07-04,German -719,scherrer,\N,Albert,Scherrer,1908-02-28,Swiss -720,terra,\N,Max,de Terra,1918-10-06,Swiss -721,hirt,\N,Peter,Hirt,1910-03-30,Swiss -722,carini,\N,Piero,Carini,1921-03-06,Italian -723,fischer,\N,Rudi,Fischer,1912-04-19,Swiss -724,ulmen,\N,Toni,Ulmen,1906-01-25,German -725,abecassis,\N,George,Abecassis,1913-03-21,British -726,george_connor,\N,George,Connor,1906-08-16,American -727,rigsby,\N,Jim,Rigsby,1923-06-06,American -728,james,\N,Joe,James,1925-05-23,American -729,schindler,\N,Bill,Schindler,1909-03-06,American -730,fonder,\N,George,Fonder,1917-06-22,American -731,banks,\N,Henry,Banks,1913-06-14,American -732,mcdowell,\N,Johnny,McDowell,1915-01-29,American -733,miller,\N,Chet,Miller,1902-07-19,American -734,ball,\N,Bobby,Ball,1925-08-26,American -735,tornaco,\N,Charles,de Tornaco,1927-06-07,Belgian -736,laurent,\N,Roger,Laurent,1913-02-21,Belgian -737,obrien,\N,Robert,O'Brien,1908-04-11,American -738,gaze,\N,Tony,Gaze,1920-02-03,Australian -739,charrington,\N,Robin,Montgomerie-Charrington,1915-06-23,British -740,comotti,\N,Franco,Comotti,1906-07-24,Italian -741,etancelin,\N,Philippe,Étancelin,1896-12-28,French -742,poore,\N,Dennis,Poore,1916-08-19,British -743,thompson,\N,Eric,Thompson,1919-11-04,British -744,downing,\N,Ken,Downing,1917-12-05,British -745,graham_whitehead,\N,Graham,Whitehead,1922-04-15,British -746,bianco,\N,Gino,Bianco,1916-07-22,Brazilian -747,murray,\N,David,Murray,1909-12-28,British -748,cantoni,\N,Eitel,Cantoni,1906-10-04,Uruguayan -749,aston,\N,Bill,Aston,1900-03-29,British -750,brudes,\N,Adolf,Brudes,1899-10-15,German -751,riess,\N,Fritz,Riess,1922-07-11,German -752,niedermayr,\N,Helmut,Niedermayr,1915-11-29,German -753,klenk,\N,Hans,Klenk,1919-10-28,German -754,balsa,\N,Marcel,Balsa,1909-01-01,French -755,schoeller,\N,Rudolf,Schoeller,1902-04-27,Swiss -756,pietsch,\N,Paul,Pietsch,1911-06-20,German -757,peters,\N,Josef,Peters,1914-09-16,German -758,lof,\N,Dries,van der Lof,1919-08-23,Dutch -759,flinterman,\N,Jan,Flinterman,1919-10-02,Dutch -760,dusio,\N,Piero,Dusio,1899-10-13,Italian -761,crespo,\N,Alberto,Crespo,1920-01-16,Argentine -762,rol,\N,Franco,Rol,1908-06-05,Italian -763,sanesi,\N,Consalvo,Sanesi,1911-03-28,Italian -764,guy_mairesse,\N,Guy,Mairesse,1910-08-10,French -765,louveau,\N,Henri,Louveau,1910-01-25,French -766,wallard,\N,Lee,Wallard,1910-09-07,American -767,forberg,\N,Carl,Forberg,1911-03-04,American -768,rose,\N,Mauri,Rose,1906-05-26,American -769,mackey,\N,Bill,Mackey,1927-12-15,American -770,green,\N,Cecil,Green,1919-09-30,American -771,walt_brown,\N,Walt,Brown,1911-12-30,American -772,hellings,\N,Mack,Hellings,1915-09-14,American -773,levegh,\N,Pierre,Levegh,1905-12-22,French -774,chaboud,\N,Eugène,Chaboud,1907-04-12,French -775,gordini,\N,Aldo,Gordini,1921-05-20,French -776,kelly,\N,Joe,Kelly,1913-03-13,Irish -777,parker,\N,Philip,Fotheringham-Parker,1907-09-22,British -778,shawe_taylor,\N,Brian,Shawe Taylor,1915-01-28,British -779,john_james,\N,John,James,1914-05-10,British -780,branca,\N,Toni,Branca,1916-09-15,Swiss -781,richardson,\N,Ken,Richardson,1911-08-21,British -782,jover,\N,Juan,Jover,1903-11-23,Spanish -783,grignard,\N,Georges,Grignard,1905-07-25,French -784,hampshire,\N,David,Hampshire,1917-12-29,British -785,crossley,\N,Geoff,Crossley,1921-05-11,British -786,fagioli,\N,Luigi,Fagioli,1898-06-09,Italian -787,harrison,\N,Cuth,Harrison,1906-07-06,British -788,fry,\N,Joe,Fry,1915-10-26,British -789,martin,\N,Eugène,Martin,1915-03-24,French -790,leslie_johnson,\N,Leslie,Johnson,1912-03-22,British -791,biondetti,\N,Clemente,Biondetti,1898-08-18,Italian -792,pian,\N,Alfredo,Pián,1912-10-21,Argentine -793,sommer,\N,Raymond,Sommer,1906-08-31,French -794,chitwood,\N,Joie,Chitwood,1912-04-14,American -795,fohr,\N,Myron,Fohr,1912-06-17,American -796,ader,\N,Walt,Ader,1913-12-15,American -797,holmes,\N,Jackie,Holmes,1920-09-04,American -798,levrett,\N,Bayliss,Levrett,1914-02-14,American -799,jackson,\N,Jimmy,Jackson,1910-07-25,American -800,pagani,\N,Nello,Pagani,1911-10-11,Italian -801,pozzi,\N,Charles,Pozzi,1909-08-27,French -802,serafini,\N,Dorino,Serafini,1909-07-22,Italian -803,cantrell,\N,Bill,Cantrell,1908-01-31,American -804,mantz,\N,Johnny,Mantz,1918-09-18,American -805,kladis,\N,Danny,Kladis,1917-02-10,American -806,oscar_gonzalez,\N,Óscar,González,1923-11-10,Uruguayan -807,hulkenberg,HUL,Nico,Hülkenberg,1987-08-19,German -808,petrov,PET,Vitaly,Petrov,1984-09-08,Russian -809,grassi,DIG,Lucas,di Grassi,1984-08-11,Brazilian -810,bruno_senna,SEN,Bruno,Senna,1983-10-15,Brazilian -811,chandhok,CHA,Karun,Chandhok,1984-01-19,Indian -812,maldonado,MAL,Pastor,Maldonado,1985-03-09,Venezuelan -813,resta,DIR,Paul,di Resta,1986-04-16,British -814,perez,PER,Sergio,Pérez,1990-01-26,Mexican -815,ambrosio,DAM,Jérôme,d'Ambrosio,1985-12-27,Belgian -816,ricciardo,RIC,Daniel,Ricciardo,1989-07-01,Australian -817,vergne,VER,Jean-Éric,Vergne,1990-04-25,French -818,pic,PIC,Charles,Pic,1990-02-15,French -819,chilton,CHI,Max,Chilton,1991-04-21,British -820,gutierrez,GUT,Esteban,Gutiérrez,1991-08-05,Mexican -821,bottas,BOT,Valtteri,Bottas,1989-08-28,Finnish -822,garde,VDG,Giedo,van der Garde,1985-04-25,Dutch -823,jules_bianchi,BIA,Jules,Bianchi,1989-08-03,French -824,kevin_magnussen,MAG,Kevin,Magnussen,1992-10-05,Danish -825,kvyat,KVY,Daniil,Kvyat,1994-04-26,Russian -826,lotterer,LOT,André,Lotterer,1981-11-19,German -827,ericsson,ERI,Marcus,Ericsson,1990-09-02,Swedish -828,stevens,STE,Will,Stevens,1991-06-28,British -829,max_verstappen,VER,Max,Verstappen,1997-09-30,Dutch -830,nasr,NAS,Felipe,Nasr,1992-08-21,Brazilian -831,sainz,SAI,Carlos,Sainz,1994-09-01,Spanish -832,merhi,MER,Roberto,Merhi,1991-03-22,Spanish -833,rossi,RSS,Alexander,Rossi,1991-09-25,American -834,jolyon_palmer,PAL,Jolyon,Palmer,1991-01-20,British -835,wehrlein,WEH,Pascal,Wehrlein,1994-10-18,German -836,haryanto,HAR,Rio,Haryanto,1993-01-22,Indonesian -837,vandoorne,VAN,Stoffel,Vandoorne,1992-03-26,Belgian -838,ocon,OCO,Esteban,Ocon,1996-09-17,French -839,stroll,STR,Lance,Stroll,1998-10-29,Canadian -840,giovinazzi,GIO,Antonio,Giovinazzi,1993-12-14,Italian -841,brendon_hartley,HAR,Brendon,Hartley,1989-11-10,New Zealander -842,leclerc,LEC,Charles,Leclerc,1997-10-16,Monegasque -843,sirotkin,SIR,Sergey,Sirotkin,1995-08-27,Russian -844,norris,NOR,Lando,Norris,1999-11-13,British -845,russell,RUS,George,Russell,1998-02-15,British -846,albon,ALB,Alexander,Albon,1996-03-23,Thai -847,latifi,LAT,Nicholas,Latifi,1995-06-29,Canadian -848,pietro_fittipaldi,FIT,Pietro,Fittipaldi,1996-06-25,Brazilian -849,aitken,AIT,Jack,Aitken,1995-09-23,British -850,tsunoda,TSU,Yuki,Tsunoda,2000-05-11,Japanese -851,mazepin,MAZ,Nikita,Mazepin,1999-03-02,Russian -852,mick_schumacher,MSC,Mick,Schumacher,1999-03-22,German -853,zhou,ZHO,Guanyu,Zhou,1999-05-30,Chinese -854,de_vries,DEV,Nyck,de Vries,1995-02-06,Dutch -855,piastri,PIA,Oscar,Piastri,2001-04-06,Australian -856,sargeant,SAR,Logan,Sargeant,2000-12-31,American diff --git a/scripts/f1_data/import_f1.sql b/scripts/f1_data/import_f1.sql deleted file mode 100644 index 997b8624..00000000 --- a/scripts/f1_data/import_f1.sql +++ /dev/null @@ -1,490 +0,0 @@ --- RelBench REL-F1 Database Schema --- Auto-generated from RelBench dataset --- Total tables: 9 - -\echo '=========================================' -\echo 'Step 1: Drop existing tables' -\echo '=========================================' - -DROP TABLE IF EXISTS drivers CASCADE; -DROP TABLE IF EXISTS races CASCADE; -DROP TABLE IF EXISTS circuits CASCADE; -DROP TABLE IF EXISTS constructor_standings CASCADE; -DROP TABLE IF EXISTS constructors CASCADE; -DROP TABLE IF EXISTS qualifying CASCADE; -DROP TABLE IF EXISTS standings CASCADE; -DROP TABLE IF EXISTS results CASCADE; -DROP TABLE IF EXISTS constructor_results CASCADE; - -\echo 'Tables dropped' -\echo '' - -\echo '=========================================' -\echo 'Step 2: Create tables' -\echo '=========================================' - -CREATE TABLE constructor_results ( - constructorResultsId INTEGER, - raceId INTEGER, - constructorId INTEGER, - points FLOAT, - date TIMESTAMP, - PRIMARY KEY (constructorResultsId) -); - -CREATE TABLE results ( - resultId INTEGER, - raceId INTEGER, - driverId INTEGER, - constructorId INTEGER, - number FLOAT, - grid INTEGER, - position FLOAT, - positionOrder INTEGER, - points FLOAT, - laps INTEGER, - milliseconds FLOAT, - fastestLap FLOAT, - rank FLOAT, - statusId INTEGER, - date TIMESTAMP, - PRIMARY KEY (resultId) -); - -CREATE TABLE standings ( - driverStandingsId INTEGER, - raceId INTEGER, - driverId INTEGER, - points FLOAT, - position INTEGER, - wins INTEGER, - date TIMESTAMP, - PRIMARY KEY (driverStandingsId) -); - -CREATE TABLE qualifying ( - qualifyId INTEGER, - raceId INTEGER, - driverId INTEGER, - constructorId INTEGER, - number INTEGER, - position INTEGER, - date TIMESTAMP, - PRIMARY KEY (qualifyId) -); - -CREATE TABLE constructors ( - constructorId INTEGER, - constructorRef TEXT, - name TEXT, - nationality TEXT, - PRIMARY KEY (constructorId) -); - -CREATE TABLE constructor_standings ( - constructorStandingsId INTEGER, - raceId INTEGER, - constructorId INTEGER, - points FLOAT, - position INTEGER, - wins INTEGER, - date TIMESTAMP, - PRIMARY KEY (constructorStandingsId) -); - -CREATE TABLE circuits ( - circuitId INTEGER, - circuitRef TEXT, - name TEXT, - location TEXT, - country TEXT, - lat FLOAT, - lng FLOAT, - alt FLOAT, - PRIMARY KEY (circuitId) -); - -CREATE TABLE races ( - raceId INTEGER, - year INTEGER, - round INTEGER, - circuitId INTEGER, - name TEXT, - date TIMESTAMP, - time TEXT, - PRIMARY KEY (raceId) -); - -CREATE TABLE drivers ( - driverId INTEGER, - driverRef TEXT, - code TEXT, - forename TEXT, - surname TEXT, - dob TIMESTAMP, - nationality TEXT, - PRIMARY KEY (driverId) -); - -\echo 'Tables created' -\echo '' - -\echo '=========================================' -\echo 'Step 3: Create temp tables for import' -\echo '=========================================' - -CREATE TEMP TABLE temp_constructor_results ( - constructorResultsId TEXT, - raceId TEXT, - constructorId TEXT, - points TEXT, - date TEXT -); - -CREATE TEMP TABLE temp_results ( - resultId TEXT, - raceId TEXT, - driverId TEXT, - constructorId TEXT, - number TEXT, - grid TEXT, - position TEXT, - positionOrder TEXT, - points TEXT, - laps TEXT, - milliseconds TEXT, - fastestLap TEXT, - rank TEXT, - statusId TEXT, - date TEXT -); - -CREATE TEMP TABLE temp_standings ( - driverStandingsId TEXT, - raceId TEXT, - driverId TEXT, - points TEXT, - position TEXT, - wins TEXT, - date TEXT -); - -CREATE TEMP TABLE temp_qualifying ( - qualifyId TEXT, - raceId TEXT, - driverId TEXT, - constructorId TEXT, - number TEXT, - position TEXT, - date TEXT -); - -CREATE TEMP TABLE temp_constructors ( - constructorId TEXT, - constructorRef TEXT, - name TEXT, - nationality TEXT -); - -CREATE TEMP TABLE temp_constructor_standings ( - constructorStandingsId TEXT, - raceId TEXT, - constructorId TEXT, - points TEXT, - position TEXT, - wins TEXT, - date TEXT -); - -CREATE TEMP TABLE temp_circuits ( - circuitId TEXT, - circuitRef TEXT, - name TEXT, - location TEXT, - country TEXT, - lat TEXT, - lng TEXT, - alt TEXT -); - -CREATE TEMP TABLE temp_races ( - raceId TEXT, - year TEXT, - round TEXT, - circuitId TEXT, - name TEXT, - date TEXT, - time TEXT -); - -CREATE TEMP TABLE temp_drivers ( - driverId TEXT, - driverRef TEXT, - code TEXT, - forename TEXT, - surname TEXT, - dob TEXT, - nationality TEXT -); - -\echo 'Temp tables created' -\echo '' - -\echo '=========================================' -\echo 'Step 4: Import CSV into temp tables' -\echo '=========================================' - -\echo ' Importing constructor_results...' -\copy temp_constructor_results FROM '/tmp/constructor_results.csv' WITH CSV HEADER DELIMITER ','; - -\echo ' Importing results...' -\copy temp_results FROM '/tmp/results.csv' WITH CSV HEADER DELIMITER ','; - -\echo ' Importing standings...' -\copy temp_standings FROM '/tmp/standings.csv' WITH CSV HEADER DELIMITER ','; - -\echo ' Importing qualifying...' -\copy temp_qualifying FROM '/tmp/qualifying.csv' WITH CSV HEADER DELIMITER ','; - -\echo ' Importing constructors...' -\copy temp_constructors FROM '/tmp/constructors.csv' WITH CSV HEADER DELIMITER ','; - -\echo ' Importing constructor_standings...' -\copy temp_constructor_standings FROM '/tmp/constructor_standings.csv' WITH CSV HEADER DELIMITER ','; - -\echo ' Importing circuits...' -\copy temp_circuits FROM '/tmp/circuits.csv' WITH CSV HEADER DELIMITER ','; - -\echo ' Importing races...' -\copy temp_races FROM '/tmp/races.csv' WITH CSV HEADER DELIMITER ','; - -\echo ' Importing drivers...' -\copy temp_drivers FROM '/tmp/drivers.csv' WITH CSV HEADER DELIMITER ','; - -\echo 'CSV imported to temp tables' -\echo '' - -\echo '=========================================' -\echo 'Step 5: Transfer data with type conversion' -\echo '=========================================' - -\echo ' Processing constructor_results...' -INSERT INTO constructor_results -SELECT - NULLIF(constructorResultsId, '')::INTEGER, - NULLIF(raceId, '')::INTEGER, - NULLIF(constructorId, '')::INTEGER, - NULLIF(points, '')::FLOAT, - NULLIF(date, '')::TIMESTAMP -FROM temp_constructor_results; - -\echo ' Processing results...' -INSERT INTO results -SELECT - NULLIF(resultId, '')::INTEGER, - NULLIF(raceId, '')::INTEGER, - NULLIF(driverId, '')::INTEGER, - NULLIF(constructorId, '')::INTEGER, - NULLIF(number, '')::FLOAT, - NULLIF(grid, '')::INTEGER, - NULLIF(position, '')::FLOAT, - NULLIF(positionOrder, '')::INTEGER, - NULLIF(points, '')::FLOAT, - NULLIF(laps, '')::INTEGER, - NULLIF(milliseconds, '')::FLOAT, - NULLIF(fastestLap, '')::FLOAT, - NULLIF(rank, '')::FLOAT, - NULLIF(statusId, '')::INTEGER, - NULLIF(date, '')::TIMESTAMP -FROM temp_results; - -\echo ' Processing standings...' -INSERT INTO standings -SELECT - NULLIF(driverStandingsId, '')::INTEGER, - NULLIF(raceId, '')::INTEGER, - NULLIF(driverId, '')::INTEGER, - NULLIF(points, '')::FLOAT, - NULLIF(position, '')::INTEGER, - NULLIF(wins, '')::INTEGER, - NULLIF(date, '')::TIMESTAMP -FROM temp_standings; - -\echo ' Processing qualifying...' -INSERT INTO qualifying -SELECT - NULLIF(qualifyId, '')::INTEGER, - NULLIF(raceId, '')::INTEGER, - NULLIF(driverId, '')::INTEGER, - NULLIF(constructorId, '')::INTEGER, - NULLIF(number, '')::INTEGER, - NULLIF(position, '')::INTEGER, - NULLIF(date, '')::TIMESTAMP -FROM temp_qualifying; - -\echo ' Processing constructors...' -INSERT INTO constructors -SELECT - NULLIF(constructorId, '')::INTEGER, - NULLIF(constructorRef, ''), - NULLIF(name, ''), - NULLIF(nationality, '') -FROM temp_constructors; - -\echo ' Processing constructor_standings...' -INSERT INTO constructor_standings -SELECT - NULLIF(constructorStandingsId, '')::INTEGER, - NULLIF(raceId, '')::INTEGER, - NULLIF(constructorId, '')::INTEGER, - NULLIF(points, '')::FLOAT, - NULLIF(position, '')::INTEGER, - NULLIF(wins, '')::INTEGER, - NULLIF(date, '')::TIMESTAMP -FROM temp_constructor_standings; - -\echo ' Processing circuits...' -INSERT INTO circuits -SELECT - NULLIF(circuitId, '')::INTEGER, - NULLIF(circuitRef, ''), - NULLIF(name, ''), - NULLIF(location, ''), - NULLIF(country, ''), - NULLIF(lat, '')::FLOAT, - NULLIF(lng, '')::FLOAT, - NULLIF(alt, '')::FLOAT -FROM temp_circuits; - -\echo ' Processing races...' -INSERT INTO races -SELECT - NULLIF(raceId, '')::INTEGER, - NULLIF(year, '')::INTEGER, - NULLIF(round, '')::INTEGER, - NULLIF(circuitId, '')::INTEGER, - NULLIF(name, ''), - NULLIF(date, '')::TIMESTAMP, - NULLIF(time, '') -FROM temp_races; - -\echo ' Processing drivers...' -INSERT INTO drivers -SELECT - NULLIF(driverId, '')::INTEGER, - NULLIF(driverRef, ''), - NULLIF(code, ''), - NULLIF(forename, ''), - NULLIF(surname, ''), - NULLIF(dob, '')::TIMESTAMP, - NULLIF(nationality, '') -FROM temp_drivers; - -\echo 'Data transferred with NULL handling' -\echo '' - -\echo '=========================================' -\echo 'Step 6: Add Foreign Keys' -\echo '=========================================' - -ALTER TABLE constructor_results ADD CONSTRAINT fk_constructor_results_raceId - FOREIGN KEY (raceId) REFERENCES races(raceId); - -ALTER TABLE constructor_results ADD CONSTRAINT fk_constructor_results_constructorId - FOREIGN KEY (constructorId) REFERENCES constructors(constructorId); - -ALTER TABLE results ADD CONSTRAINT fk_results_raceId - FOREIGN KEY (raceId) REFERENCES races(raceId); - -ALTER TABLE results ADD CONSTRAINT fk_results_driverId - FOREIGN KEY (driverId) REFERENCES drivers(driverId); - -ALTER TABLE results ADD CONSTRAINT fk_results_constructorId - FOREIGN KEY (constructorId) REFERENCES constructors(constructorId); - -ALTER TABLE standings ADD CONSTRAINT fk_standings_raceId - FOREIGN KEY (raceId) REFERENCES races(raceId); - -ALTER TABLE standings ADD CONSTRAINT fk_standings_driverId - FOREIGN KEY (driverId) REFERENCES drivers(driverId); - -ALTER TABLE qualifying ADD CONSTRAINT fk_qualifying_raceId - FOREIGN KEY (raceId) REFERENCES races(raceId); - -ALTER TABLE qualifying ADD CONSTRAINT fk_qualifying_driverId - FOREIGN KEY (driverId) REFERENCES drivers(driverId); - -ALTER TABLE qualifying ADD CONSTRAINT fk_qualifying_constructorId - FOREIGN KEY (constructorId) REFERENCES constructors(constructorId); - -ALTER TABLE constructor_standings ADD CONSTRAINT fk_constructor_standings_raceId - FOREIGN KEY (raceId) REFERENCES races(raceId); - -ALTER TABLE constructor_standings ADD CONSTRAINT fk_constructor_standings_constructorId - FOREIGN KEY (constructorId) REFERENCES constructors(constructorId); - -ALTER TABLE races ADD CONSTRAINT fk_races_circuitId - FOREIGN KEY (circuitId) REFERENCES circuits(circuitId); - -\echo 'Foreign keys added' -\echo '' - -\echo '=========================================' -\echo 'Step 7: Create Indexes' -\echo '=========================================' - -CREATE INDEX idx_constructor_results_raceId ON constructor_results(raceId) WHERE raceId IS NOT NULL; -CREATE INDEX idx_constructor_results_constructorId ON constructor_results(constructorId) WHERE constructorId IS NOT NULL; -CREATE INDEX idx_constructor_results_date ON constructor_results(date); -CREATE INDEX idx_results_raceId ON results(raceId) WHERE raceId IS NOT NULL; -CREATE INDEX idx_results_driverId ON results(driverId) WHERE driverId IS NOT NULL; -CREATE INDEX idx_results_constructorId ON results(constructorId) WHERE constructorId IS NOT NULL; -CREATE INDEX idx_results_date ON results(date); -CREATE INDEX idx_standings_raceId ON standings(raceId) WHERE raceId IS NOT NULL; -CREATE INDEX idx_standings_driverId ON standings(driverId) WHERE driverId IS NOT NULL; -CREATE INDEX idx_standings_date ON standings(date); -CREATE INDEX idx_qualifying_raceId ON qualifying(raceId) WHERE raceId IS NOT NULL; -CREATE INDEX idx_qualifying_driverId ON qualifying(driverId) WHERE driverId IS NOT NULL; -CREATE INDEX idx_qualifying_constructorId ON qualifying(constructorId) WHERE constructorId IS NOT NULL; -CREATE INDEX idx_qualifying_date ON qualifying(date); -CREATE INDEX idx_constructor_standings_raceId ON constructor_standings(raceId) WHERE raceId IS NOT NULL; -CREATE INDEX idx_constructor_standings_constructorId ON constructor_standings(constructorId) WHERE constructorId IS NOT NULL; -CREATE INDEX idx_constructor_standings_date ON constructor_standings(date); -CREATE INDEX idx_races_circuitId ON races(circuitId) WHERE circuitId IS NOT NULL; -CREATE INDEX idx_races_date ON races(date); - -\echo 'Indexes created' -\echo '' - -\echo '=========================================' -\echo 'Summary' -\echo '=========================================' - -SELECT - table_name, - to_char(record_count, 'FM999,999,999') as records -FROM ( - SELECT 'constructor_results' as table_name, COUNT(*) as record_count FROM constructor_results - UNION ALL - SELECT 'results' as table_name, COUNT(*) as record_count FROM results - UNION ALL - SELECT 'standings' as table_name, COUNT(*) as record_count FROM standings - UNION ALL - SELECT 'qualifying' as table_name, COUNT(*) as record_count FROM qualifying - UNION ALL - SELECT 'constructors' as table_name, COUNT(*) as record_count FROM constructors - UNION ALL - SELECT 'constructor_standings' as table_name, COUNT(*) as record_count FROM constructor_standings - UNION ALL - SELECT 'circuits' as table_name, COUNT(*) as record_count FROM circuits - UNION ALL - SELECT 'races' as table_name, COUNT(*) as record_count FROM races - UNION ALL - SELECT 'drivers' as table_name, COUNT(*) as record_count FROM drivers -) t -ORDER BY record_count DESC; - -\echo '' -\echo '=========================================' -\echo 'IMPORT COMPLETE' -\echo '=========================================' \ No newline at end of file diff --git a/scripts/f1_data/qualifying.csv b/scripts/f1_data/qualifying.csv deleted file mode 100644 index a9c2b369..00000000 --- a/scripts/f1_data/qualifying.csv +++ /dev/null @@ -1,4083 +0,0 @@ -qualifyId,raceId,driverId,constructorId,number,position,date -0,548,43,26,26,19,1994-03-26 00:00:00 -1,548,100,30,31,26,1994-03-26 00:00:00 -2,548,91,29,34,25,1994-03-26 00:00:00 -3,548,82,31,11,24,1994-03-26 00:00:00 -4,548,105,32,19,23,1994-03-26 00:00:00 -5,548,104,17,24,22,1994-03-26 00:00:00 -6,548,64,31,12,21,1994-03-26 00:00:00 -7,548,102,26,25,20,1994-03-26 00:00:00 -8,548,83,0,8,18,1994-03-26 00:00:00 -9,548,76,5,28,17,1994-03-26 00:00:00 -10,548,55,16,15,16,1994-03-26 00:00:00 -11,548,21,16,14,14,1994-03-26 00:00:00 -12,548,99,32,20,13,1994-03-26 00:00:00 -13,548,93,17,23,15,1994-03-26 00:00:00 -14,548,103,28,9,11,1994-03-26 00:00:00 -15,548,101,2,2,1,1994-03-26 00:00:00 -16,548,29,21,5,2,1994-03-26 00:00:00 -17,548,54,5,27,3,1994-03-26 00:00:00 -18,548,70,2,0,4,1994-03-26 00:00:00 -19,548,86,24,4,12,1994-03-26 00:00:00 -20,548,80,28,10,6,1994-03-26 00:00:00 -21,548,48,14,30,5,1994-03-26 00:00:00 -22,548,56,0,7,8,1994-03-26 00:00:00 -23,548,49,21,6,9,1994-03-26 00:00:00 -24,548,78,24,3,10,1994-03-26 00:00:00 -25,548,90,14,29,7,1994-03-26 00:00:00 -26,549,99,32,20,16,1994-04-16 00:00:00 -27,549,87,16,15,20,1994-04-16 00:00:00 -28,549,93,17,23,17,1994-04-16 00:00:00 -29,549,102,26,25,18,1994-04-16 00:00:00 -30,549,90,14,29,19,1994-04-16 00:00:00 -31,549,105,32,19,21,1994-04-16 00:00:00 -32,549,83,0,8,6,1994-04-16 00:00:00 -33,549,64,31,12,23,1994-04-16 00:00:00 -34,549,82,31,11,24,1994-04-16 00:00:00 -35,549,100,30,31,25,1994-04-16 00:00:00 -36,549,106,30,32,26,1994-04-16 00:00:00 -37,549,104,17,24,15,1994-04-16 00:00:00 -38,549,43,26,26,22,1994-04-16 00:00:00 -39,549,78,24,3,14,1994-04-16 00:00:00 -40,549,29,21,5,2,1994-04-16 00:00:00 -41,549,86,24,4,12,1994-04-16 00:00:00 -42,549,101,2,2,1,1994-04-16 00:00:00 -43,549,70,2,0,3,1994-04-16 00:00:00 -44,549,80,28,10,13,1994-04-16 00:00:00 -45,549,76,5,28,5,1994-04-16 00:00:00 -46,549,56,0,7,4,1994-04-16 00:00:00 -47,549,21,16,14,8,1994-04-16 00:00:00 -48,549,103,28,9,9,1994-04-16 00:00:00 -49,549,49,21,6,10,1994-04-16 00:00:00 -50,549,48,14,30,11,1994-04-16 00:00:00 -51,549,77,5,27,7,1994-04-16 00:00:00 -52,550,99,32,20,18,1994-04-30 00:00:00 -53,550,82,31,11,22,1994-04-30 00:00:00 -54,550,43,26,26,19,1994-04-30 00:00:00 -55,550,64,31,12,20,1994-04-30 00:00:00 -56,550,109,16,15,21,1994-04-30 00:00:00 -57,550,105,32,19,23,1994-04-30 00:00:00 -58,550,80,28,10,11,1994-04-30 00:00:00 -59,550,91,29,34,25,1994-04-30 00:00:00 -60,550,106,30,32,26,1994-04-30 00:00:00 -61,550,107,29,33,27,1994-04-30 00:00:00 -62,550,21,16,14,28,1994-04-30 00:00:00 -63,550,102,26,25,17,1994-04-30 00:00:00 -64,550,100,30,31,24,1994-04-30 00:00:00 -65,550,103,28,9,16,1994-04-30 00:00:00 -66,550,93,17,23,14,1994-04-30 00:00:00 -67,550,101,2,2,1,1994-04-30 00:00:00 -68,550,104,17,24,15,1994-04-30 00:00:00 -69,550,29,21,5,2,1994-04-30 00:00:00 -70,550,76,5,28,3,1994-04-30 00:00:00 -71,550,70,2,0,4,1994-04-30 00:00:00 -72,550,77,5,27,6,1994-04-30 00:00:00 -73,550,108,21,6,5,1994-04-30 00:00:00 -74,550,56,0,7,8,1994-04-30 00:00:00 -75,550,78,24,3,9,1994-04-30 00:00:00 -76,550,90,14,29,10,1994-04-30 00:00:00 -77,550,86,24,4,12,1994-04-30 00:00:00 -78,550,83,0,8,13,1994-04-30 00:00:00 -79,550,48,14,30,7,1994-04-30 00:00:00 -80,552,102,26,25,20,1994-05-28 00:00:00 -81,552,99,32,20,16,1994-05-28 00:00:00 -82,552,105,32,19,17,1994-05-28 00:00:00 -83,552,93,17,23,18,1994-05-28 00:00:00 -84,552,103,28,9,21,1994-05-28 00:00:00 -85,552,43,26,26,19,1994-05-28 00:00:00 -86,552,69,31,11,23,1994-05-28 00:00:00 -87,552,100,30,31,24,1994-05-28 00:00:00 -88,552,91,29,34,25,1994-05-28 00:00:00 -89,552,107,29,33,26,1994-05-28 00:00:00 -90,552,80,28,10,15,1994-05-28 00:00:00 -91,552,64,31,12,22,1994-05-28 00:00:00 -92,552,104,17,24,14,1994-05-28 00:00:00 -93,552,48,14,30,12,1994-05-28 00:00:00 -94,552,29,21,5,1,1994-05-28 00:00:00 -95,552,86,24,4,11,1994-05-28 00:00:00 -96,552,78,24,3,10,1994-05-28 00:00:00 -97,552,13,2,2,9,1994-05-28 00:00:00 -98,552,83,0,8,8,1994-05-28 00:00:00 -99,552,76,5,28,7,1994-05-28 00:00:00 -100,552,54,5,27,6,1994-05-28 00:00:00 -101,552,21,16,14,5,1994-05-28 00:00:00 -102,552,108,21,6,4,1994-05-28 00:00:00 -103,552,56,0,7,3,1994-05-28 00:00:00 -104,552,70,2,0,2,1994-05-28 00:00:00 -105,552,55,16,15,13,1994-05-28 00:00:00 -106,553,93,17,23,15,1994-06-11 00:00:00 -107,553,103,28,9,16,1994-06-11 00:00:00 -108,553,64,31,12,17,1994-06-11 00:00:00 -109,553,104,17,24,18,1994-06-11 00:00:00 -110,553,109,14,29,14,1994-06-11 00:00:00 -111,553,108,21,6,20,1994-06-11 00:00:00 -112,553,99,32,20,21,1994-06-11 00:00:00 -113,553,105,32,19,22,1994-06-11 00:00:00 -114,553,102,26,25,24,1994-06-11 00:00:00 -115,553,43,26,26,19,1994-06-11 00:00:00 -116,553,86,24,4,13,1994-06-11 00:00:00 -117,553,100,30,31,25,1994-06-11 00:00:00 -118,553,80,28,10,11,1994-06-11 00:00:00 -119,553,48,14,30,10,1994-06-11 00:00:00 -120,553,78,24,3,9,1994-06-11 00:00:00 -121,553,55,16,15,8,1994-06-11 00:00:00 -122,553,56,0,7,7,1994-06-11 00:00:00 -123,553,21,16,14,6,1994-06-11 00:00:00 -124,553,13,2,2,5,1994-06-11 00:00:00 -125,553,70,2,0,4,1994-06-11 00:00:00 -126,553,76,5,28,3,1994-06-11 00:00:00 -127,553,54,5,27,2,1994-06-11 00:00:00 -128,553,29,21,5,1,1994-06-11 00:00:00 -129,553,83,0,8,12,1994-06-11 00:00:00 -130,553,91,29,34,26,1994-06-11 00:00:00 -131,553,69,31,11,23,1994-06-11 00:00:00 -132,554,64,31,12,19,1994-07-02 00:00:00 -133,554,110,30,32,26,1994-07-02 00:00:00 -134,554,105,32,19,25,1994-07-02 00:00:00 -135,554,100,30,31,24,1994-07-02 00:00:00 -136,554,69,31,11,23,1994-07-02 00:00:00 -137,554,80,28,10,22,1994-07-02 00:00:00 -138,554,104,17,24,21,1994-07-02 00:00:00 -139,554,99,32,20,20,1994-07-02 00:00:00 -140,554,103,28,9,18,1994-07-02 00:00:00 -141,554,86,24,4,17,1994-07-02 00:00:00 -142,554,93,17,23,16,1994-07-02 00:00:00 -143,554,78,24,3,14,1994-07-02 00:00:00 -144,554,43,26,26,13,1994-07-02 00:00:00 -145,554,102,26,25,15,1994-07-02 00:00:00 -146,554,109,14,29,11,1994-07-02 00:00:00 -147,554,70,2,0,1,1994-07-02 00:00:00 -148,554,94,2,2,2,1994-07-02 00:00:00 -149,554,29,21,5,3,1994-07-02 00:00:00 -150,554,54,5,27,4,1994-07-02 00:00:00 -151,554,83,0,8,12,1994-07-02 00:00:00 -152,554,55,16,15,6,1994-07-02 00:00:00 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-4063,819,5,2,17,14,2009-10-31 11:00:00 -4064,819,152,4,11,15,2009-10-31 11:00:00 -4065,819,20,5,3,20,2009-10-31 11:00:00 -4066,819,23,9,21,17,2009-10-31 11:00:00 -4067,819,15,9,20,18,2009-10-31 11:00:00 -4068,819,153,3,8,19,2009-10-31 11:00:00 -4069,819,3,3,7,16,2009-10-31 11:00:00 -4070,819,7,5,4,11,2009-10-31 11:00:00 -4071,819,154,6,10,12,2009-10-31 11:00:00 -4072,819,2,2,16,9,2009-10-31 11:00:00 -4073,819,1,1,6,8,2009-10-31 11:00:00 -4074,819,8,1,5,7,2009-10-31 11:00:00 -4075,819,14,6,9,6,2009-10-31 11:00:00 -4076,819,17,22,22,5,2009-10-31 11:00:00 -4077,819,21,22,23,4,2009-10-31 11:00:00 -4078,819,16,8,14,3,2009-10-31 11:00:00 -4079,819,19,8,15,2,2009-10-31 11:00:00 -4080,819,0,0,1,1,2009-10-31 11:00:00 -4081,819,66,4,12,10,2009-10-31 11:00:00 diff --git a/scripts/f1_data/races.csv b/scripts/f1_data/races.csv deleted file mode 100644 index 08d141e6..00000000 --- a/scripts/f1_data/races.csv +++ /dev/null @@ -1,821 +0,0 @@ -raceId,year,round,circuitId,name,date,time -0,1950,1,8,British Grand Prix,1950-05-13 00:00:00,00:00:00 -1,1950,2,5,Monaco Grand Prix,1950-05-21 00:00:00,00:00:00 -2,1950,3,18,Indianapolis 500,1950-05-30 00:00:00,00:00:00 -3,1950,4,65,Swiss Grand Prix,1950-06-04 00:00:00,00:00:00 -4,1950,5,12,Belgian Grand Prix,1950-06-18 00:00:00,00:00:00 -5,1950,6,54,French Grand Prix,1950-07-02 00:00:00,00:00:00 -6,1950,7,13,Italian Grand Prix,1950-09-03 00:00:00,00:00:00 -7,1951,1,65,Swiss Grand Prix,1951-05-27 00:00:00,00:00:00 -8,1951,2,18,Indianapolis 500,1951-05-30 00:00:00,00:00:00 -9,1951,3,12,Belgian Grand Prix,1951-06-17 00:00:00,00:00:00 -10,1951,4,54,French Grand Prix,1951-07-01 00:00:00,00:00:00 -11,1951,5,8,British Grand Prix,1951-07-14 00:00:00,00:00:00 -12,1951,6,19,German Grand Prix,1951-07-29 00:00:00,00:00:00 -13,1951,7,13,Italian Grand Prix,1951-09-16 00:00:00,00:00:00 -14,1951,8,66,Spanish Grand Prix,1951-10-28 00:00:00,00:00:00 -15,1952,1,65,Swiss Grand Prix,1952-05-18 00:00:00,00:00:00 -16,1952,2,18,Indianapolis 500,1952-05-30 00:00:00,00:00:00 -17,1952,3,12,Belgian Grand Prix,1952-06-22 00:00:00,00:00:00 -18,1952,4,52,French Grand Prix,1952-07-06 00:00:00,00:00:00 -19,1952,5,8,British Grand Prix,1952-07-19 00:00:00,00:00:00 -20,1952,6,19,German Grand Prix,1952-08-03 00:00:00,00:00:00 -21,1952,7,38,Dutch Grand Prix,1952-08-17 00:00:00,00:00:00 -22,1952,8,13,Italian Grand Prix,1952-09-07 00:00:00,00:00:00 -23,1953,1,24,Argentine Grand Prix,1953-01-18 00:00:00,00:00:00 -24,1953,2,18,Indianapolis 500,1953-05-30 00:00:00,00:00:00 -25,1953,3,38,Dutch Grand Prix,1953-06-07 00:00:00,00:00:00 -26,1953,4,12,Belgian Grand Prix,1953-06-21 00:00:00,00:00:00 -27,1953,5,54,French Grand Prix,1953-07-05 00:00:00,00:00:00 -28,1953,6,8,British Grand Prix,1953-07-18 00:00:00,00:00:00 -29,1953,7,19,German Grand Prix,1953-08-02 00:00:00,00:00:00 -30,1953,8,65,Swiss Grand Prix,1953-08-23 00:00:00,00:00:00 -31,1953,9,13,Italian Grand Prix,1953-09-13 00:00:00,00:00:00 -32,1954,1,24,Argentine Grand Prix,1954-01-17 00:00:00,00:00:00 -33,1954,2,18,Indianapolis 500,1954-05-31 00:00:00,00:00:00 -34,1954,3,12,Belgian Grand Prix,1954-06-20 00:00:00,00:00:00 -35,1954,4,54,French Grand Prix,1954-07-04 00:00:00,00:00:00 -36,1954,5,8,British Grand Prix,1954-07-17 00:00:00,00:00:00 -37,1954,6,19,German Grand Prix,1954-08-01 00:00:00,00:00:00 -38,1954,7,65,Swiss Grand Prix,1954-08-22 00:00:00,00:00:00 -39,1954,8,13,Italian Grand Prix,1954-09-05 00:00:00,00:00:00 -40,1954,9,66,Spanish Grand Prix,1954-10-24 00:00:00,00:00:00 -41,1955,1,24,Argentine Grand Prix,1955-01-16 00:00:00,00:00:00 -42,1955,2,5,Monaco Grand Prix,1955-05-22 00:00:00,00:00:00 -43,1955,3,18,Indianapolis 500,1955-05-30 00:00:00,00:00:00 -44,1955,4,12,Belgian Grand Prix,1955-06-05 00:00:00,00:00:00 -45,1955,5,38,Dutch Grand Prix,1955-06-19 00:00:00,00:00:00 -46,1955,6,57,British Grand Prix,1955-07-16 00:00:00,00:00:00 -47,1955,7,13,Italian Grand Prix,1955-09-11 00:00:00,00:00:00 -48,1956,1,24,Argentine Grand Prix,1956-01-22 00:00:00,00:00:00 -49,1956,2,5,Monaco Grand Prix,1956-05-13 00:00:00,00:00:00 -50,1956,3,18,Indianapolis 500,1956-05-30 00:00:00,00:00:00 -51,1956,4,12,Belgian Grand Prix,1956-06-03 00:00:00,00:00:00 -52,1956,5,54,French Grand Prix,1956-07-01 00:00:00,00:00:00 -53,1956,6,8,British Grand Prix,1956-07-14 00:00:00,00:00:00 -54,1956,7,19,German Grand Prix,1956-08-05 00:00:00,00:00:00 -55,1956,8,13,Italian Grand Prix,1956-09-02 00:00:00,00:00:00 -56,1957,1,24,Argentine Grand Prix,1957-01-13 00:00:00,00:00:00 -57,1957,2,5,Monaco Grand Prix,1957-05-19 00:00:00,00:00:00 -58,1957,3,18,Indianapolis 500,1957-05-30 00:00:00,00:00:00 -59,1957,4,52,French Grand Prix,1957-07-07 00:00:00,00:00:00 -60,1957,5,57,British Grand Prix,1957-07-20 00:00:00,00:00:00 -61,1957,6,19,German Grand Prix,1957-08-04 00:00:00,00:00:00 -62,1957,7,64,Pescara Grand Prix,1957-08-18 00:00:00,00:00:00 -63,1957,8,13,Italian Grand Prix,1957-09-08 00:00:00,00:00:00 -64,1958,1,24,Argentine Grand Prix,1958-01-19 00:00:00,00:00:00 -65,1958,2,5,Monaco Grand Prix,1958-05-18 00:00:00,00:00:00 -66,1958,3,38,Dutch Grand Prix,1958-05-26 00:00:00,00:00:00 -67,1958,4,18,Indianapolis 500,1958-05-30 00:00:00,00:00:00 -68,1958,5,12,Belgian Grand Prix,1958-06-15 00:00:00,00:00:00 -69,1958,6,54,French Grand Prix,1958-07-06 00:00:00,00:00:00 -70,1958,7,8,British Grand Prix,1958-07-19 00:00:00,00:00:00 -71,1958,8,19,German Grand Prix,1958-08-03 00:00:00,00:00:00 -72,1958,9,58,Portuguese Grand Prix,1958-08-24 00:00:00,00:00:00 -73,1958,10,13,Italian Grand Prix,1958-09-07 00:00:00,00:00:00 -74,1958,11,63,Moroccan Grand Prix,1958-10-19 00:00:00,00:00:00 -75,1959,1,5,Monaco Grand Prix,1959-05-10 00:00:00,00:00:00 -76,1959,2,18,Indianapolis 500,1959-05-30 00:00:00,00:00:00 -77,1959,3,38,Dutch Grand Prix,1959-05-31 00:00:00,00:00:00 -78,1959,4,54,French Grand Prix,1959-07-05 00:00:00,00:00:00 -79,1959,5,57,British Grand Prix,1959-07-18 00:00:00,00:00:00 -80,1959,6,60,German Grand Prix,1959-08-02 00:00:00,00:00:00 -81,1959,7,61,Portuguese Grand Prix,1959-08-23 00:00:00,00:00:00 -82,1959,8,13,Italian Grand Prix,1959-09-13 00:00:00,00:00:00 -83,1959,9,62,United States Grand Prix,1959-12-12 00:00:00,00:00:00 -84,1960,1,24,Argentine Grand Prix,1960-02-07 00:00:00,00:00:00 -85,1960,2,5,Monaco Grand Prix,1960-05-29 00:00:00,00:00:00 -86,1960,3,18,Indianapolis 500,1960-05-30 00:00:00,00:00:00 -87,1960,4,38,Dutch Grand Prix,1960-06-06 00:00:00,00:00:00 -88,1960,5,12,Belgian Grand Prix,1960-06-19 00:00:00,00:00:00 -89,1960,6,54,French Grand Prix,1960-07-03 00:00:00,00:00:00 -90,1960,7,8,British Grand Prix,1960-07-16 00:00:00,00:00:00 -91,1960,8,58,Portuguese Grand Prix,1960-08-14 00:00:00,00:00:00 -92,1960,9,13,Italian Grand Prix,1960-09-04 00:00:00,00:00:00 -93,1960,10,59,United States Grand Prix,1960-11-20 00:00:00,00:00:00 -94,1961,1,5,Monaco Grand Prix,1961-05-14 00:00:00,00:00:00 -95,1961,2,38,Dutch Grand Prix,1961-05-22 00:00:00,00:00:00 -96,1961,3,12,Belgian Grand Prix,1961-06-18 00:00:00,00:00:00 -97,1961,4,54,French Grand Prix,1961-07-02 00:00:00,00:00:00 -98,1961,5,57,British Grand Prix,1961-07-15 00:00:00,00:00:00 -99,1961,6,19,German Grand Prix,1961-08-06 00:00:00,00:00:00 -100,1961,7,13,Italian Grand Prix,1961-09-10 00:00:00,00:00:00 -101,1961,8,45,United States Grand Prix,1961-10-08 00:00:00,00:00:00 -102,1962,1,38,Dutch Grand Prix,1962-05-20 00:00:00,00:00:00 -103,1962,2,5,Monaco Grand Prix,1962-06-03 00:00:00,00:00:00 -104,1962,3,12,Belgian Grand Prix,1962-06-17 00:00:00,00:00:00 -105,1962,4,52,French Grand Prix,1962-07-08 00:00:00,00:00:00 -106,1962,5,57,British Grand Prix,1962-07-21 00:00:00,00:00:00 -107,1962,6,19,German Grand Prix,1962-08-05 00:00:00,00:00:00 -108,1962,7,13,Italian Grand Prix,1962-09-16 00:00:00,00:00:00 -109,1962,8,45,United States Grand Prix,1962-10-07 00:00:00,00:00:00 -110,1962,9,55,South African Grand Prix,1962-12-29 00:00:00,00:00:00 -111,1963,1,5,Monaco Grand Prix,1963-05-26 00:00:00,00:00:00 -112,1963,2,12,Belgian Grand Prix,1963-06-09 00:00:00,00:00:00 -113,1963,3,38,Dutch Grand Prix,1963-06-23 00:00:00,00:00:00 -114,1963,4,54,French Grand Prix,1963-06-30 00:00:00,00:00:00 -115,1963,5,8,British Grand Prix,1963-07-20 00:00:00,00:00:00 -116,1963,6,19,German Grand Prix,1963-08-04 00:00:00,00:00:00 -117,1963,7,13,Italian Grand Prix,1963-09-08 00:00:00,00:00:00 -118,1963,8,45,United States Grand Prix,1963-10-06 00:00:00,00:00:00 -119,1963,9,31,Mexican Grand Prix,1963-10-27 00:00:00,00:00:00 -120,1963,10,55,South African Grand Prix,1963-12-28 00:00:00,00:00:00 -121,1964,1,5,Monaco Grand Prix,1964-05-10 00:00:00,00:00:00 -122,1964,2,38,Dutch Grand Prix,1964-05-24 00:00:00,00:00:00 -123,1964,3,12,Belgian Grand Prix,1964-06-14 00:00:00,00:00:00 -124,1964,4,52,French Grand Prix,1964-06-28 00:00:00,00:00:00 -125,1964,5,37,British Grand Prix,1964-07-11 00:00:00,00:00:00 -126,1964,6,19,German Grand Prix,1964-08-02 00:00:00,00:00:00 -127,1964,7,56,Austrian Grand Prix,1964-08-23 00:00:00,00:00:00 -128,1964,8,13,Italian Grand Prix,1964-09-06 00:00:00,00:00:00 -129,1964,9,45,United States Grand Prix,1964-10-04 00:00:00,00:00:00 -130,1964,10,31,Mexican Grand Prix,1964-10-25 00:00:00,00:00:00 -131,1965,1,55,South African Grand Prix,1965-01-01 00:00:00,00:00:00 -132,1965,2,5,Monaco Grand Prix,1965-05-30 00:00:00,00:00:00 -133,1965,3,12,Belgian Grand Prix,1965-06-13 00:00:00,00:00:00 -134,1965,4,50,French Grand Prix,1965-06-27 00:00:00,00:00:00 -135,1965,5,8,British Grand Prix,1965-07-10 00:00:00,00:00:00 -136,1965,6,38,Dutch Grand Prix,1965-07-18 00:00:00,00:00:00 -137,1965,7,19,German Grand Prix,1965-08-01 00:00:00,00:00:00 -138,1965,8,13,Italian Grand Prix,1965-09-12 00:00:00,00:00:00 -139,1965,9,45,United States Grand Prix,1965-10-03 00:00:00,00:00:00 -140,1965,10,31,Mexican Grand Prix,1965-10-24 00:00:00,00:00:00 -141,1966,1,5,Monaco Grand Prix,1966-05-22 00:00:00,00:00:00 -142,1966,2,12,Belgian Grand Prix,1966-06-12 00:00:00,00:00:00 -143,1966,3,54,French Grand Prix,1966-07-03 00:00:00,00:00:00 -144,1966,4,37,British Grand Prix,1966-07-16 00:00:00,00:00:00 -145,1966,5,38,Dutch Grand Prix,1966-07-24 00:00:00,00:00:00 -146,1966,6,19,German Grand Prix,1966-08-07 00:00:00,00:00:00 -147,1966,7,13,Italian Grand Prix,1966-09-04 00:00:00,00:00:00 -148,1966,8,45,United States Grand Prix,1966-10-02 00:00:00,00:00:00 -149,1966,9,31,Mexican Grand Prix,1966-10-23 00:00:00,00:00:00 -150,1967,1,29,South African Grand Prix,1967-01-02 00:00:00,00:00:00 -151,1967,2,5,Monaco Grand Prix,1967-05-07 00:00:00,00:00:00 -152,1967,3,38,Dutch Grand Prix,1967-06-04 00:00:00,00:00:00 -153,1967,4,12,Belgian Grand Prix,1967-06-18 00:00:00,00:00:00 -154,1967,5,53,French Grand Prix,1967-07-02 00:00:00,00:00:00 -155,1967,6,8,British Grand Prix,1967-07-15 00:00:00,00:00:00 -156,1967,7,19,German Grand Prix,1967-08-06 00:00:00,00:00:00 -157,1967,8,47,Canadian Grand Prix,1967-08-27 00:00:00,00:00:00 -158,1967,9,13,Italian Grand Prix,1967-09-10 00:00:00,00:00:00 -159,1967,10,45,United States Grand Prix,1967-10-01 00:00:00,00:00:00 -160,1967,11,31,Mexican Grand Prix,1967-10-22 00:00:00,00:00:00 -161,1968,1,29,South African Grand Prix,1968-01-01 00:00:00,00:00:00 -162,1968,2,44,Spanish Grand Prix,1968-05-12 00:00:00,00:00:00 -163,1968,3,5,Monaco Grand Prix,1968-05-26 00:00:00,00:00:00 -164,1968,4,12,Belgian Grand Prix,1968-06-09 00:00:00,00:00:00 -165,1968,5,38,Dutch Grand Prix,1968-06-23 00:00:00,00:00:00 -166,1968,6,52,French Grand Prix,1968-07-07 00:00:00,00:00:00 -167,1968,7,37,British Grand Prix,1968-07-20 00:00:00,00:00:00 -168,1968,8,19,German Grand Prix,1968-08-04 00:00:00,00:00:00 -169,1968,9,13,Italian Grand Prix,1968-09-08 00:00:00,00:00:00 -170,1968,10,51,Canadian Grand Prix,1968-09-22 00:00:00,00:00:00 -171,1968,11,45,United States Grand Prix,1968-10-06 00:00:00,00:00:00 -172,1968,12,31,Mexican Grand Prix,1968-11-03 00:00:00,00:00:00 -173,1969,1,29,South African Grand Prix,1969-03-01 00:00:00,00:00:00 -174,1969,2,48,Spanish Grand Prix,1969-05-04 00:00:00,00:00:00 -175,1969,3,5,Monaco Grand Prix,1969-05-18 00:00:00,00:00:00 -176,1969,4,38,Dutch Grand Prix,1969-06-21 00:00:00,00:00:00 -177,1969,5,50,French Grand Prix,1969-07-06 00:00:00,00:00:00 -178,1969,6,8,British Grand Prix,1969-07-19 00:00:00,00:00:00 -179,1969,7,19,German Grand Prix,1969-08-03 00:00:00,00:00:00 -180,1969,8,13,Italian Grand Prix,1969-09-07 00:00:00,00:00:00 -181,1969,9,47,Canadian Grand Prix,1969-09-20 00:00:00,00:00:00 -182,1969,10,45,United States Grand Prix,1969-10-05 00:00:00,00:00:00 -183,1969,11,31,Mexican Grand Prix,1969-10-19 00:00:00,00:00:00 -184,1970,1,29,South African Grand Prix,1970-03-07 00:00:00,00:00:00 -185,1970,2,44,Spanish Grand Prix,1970-04-19 00:00:00,00:00:00 -186,1970,3,5,Monaco Grand Prix,1970-05-10 00:00:00,00:00:00 -187,1970,4,12,Belgian Grand Prix,1970-06-07 00:00:00,00:00:00 -188,1970,5,38,Dutch Grand Prix,1970-06-21 00:00:00,00:00:00 -189,1970,6,50,French Grand Prix,1970-07-05 00:00:00,00:00:00 -190,1970,7,37,British Grand Prix,1970-07-18 00:00:00,00:00:00 -191,1970,8,9,German Grand Prix,1970-08-02 00:00:00,00:00:00 -192,1970,9,69,Austrian Grand Prix,1970-08-16 00:00:00,00:00:00 -193,1970,10,13,Italian Grand Prix,1970-09-06 00:00:00,00:00:00 -194,1970,11,51,Canadian Grand Prix,1970-09-20 00:00:00,00:00:00 -195,1970,12,45,United States Grand Prix,1970-10-04 00:00:00,00:00:00 -196,1970,13,31,Mexican Grand Prix,1970-10-25 00:00:00,00:00:00 -197,1971,1,29,South African Grand Prix,1971-03-06 00:00:00,00:00:00 -198,1971,2,48,Spanish Grand Prix,1971-04-18 00:00:00,00:00:00 -199,1971,3,5,Monaco Grand Prix,1971-05-23 00:00:00,00:00:00 -200,1971,4,38,Dutch Grand Prix,1971-06-20 00:00:00,00:00:00 -201,1971,5,33,French Grand Prix,1971-07-04 00:00:00,00:00:00 -202,1971,6,8,British Grand Prix,1971-07-17 00:00:00,00:00:00 -203,1971,7,19,German Grand Prix,1971-08-01 00:00:00,00:00:00 -204,1971,8,69,Austrian Grand Prix,1971-08-15 00:00:00,00:00:00 -205,1971,9,13,Italian Grand Prix,1971-09-05 00:00:00,00:00:00 -206,1971,10,47,Canadian Grand Prix,1971-09-19 00:00:00,00:00:00 -207,1971,11,45,United States Grand Prix,1971-10-03 00:00:00,00:00:00 -208,1972,1,24,Argentine Grand Prix,1972-01-23 00:00:00,00:00:00 -209,1972,2,29,South African Grand Prix,1972-03-04 00:00:00,00:00:00 -210,1972,3,44,Spanish Grand Prix,1972-05-01 00:00:00,00:00:00 -211,1972,4,5,Monaco Grand Prix,1972-05-14 00:00:00,00:00:00 -212,1972,5,49,Belgian Grand Prix,1972-06-04 00:00:00,00:00:00 -213,1972,6,50,French Grand Prix,1972-07-02 00:00:00,00:00:00 -214,1972,7,37,British Grand Prix,1972-07-15 00:00:00,00:00:00 -215,1972,8,19,German Grand Prix,1972-07-30 00:00:00,00:00:00 -216,1972,9,69,Austrian Grand Prix,1972-08-13 00:00:00,00:00:00 -217,1972,10,13,Italian Grand Prix,1972-09-10 00:00:00,00:00:00 -218,1972,11,47,Canadian Grand Prix,1972-09-24 00:00:00,00:00:00 -219,1972,12,45,United States Grand Prix,1972-10-08 00:00:00,00:00:00 -220,1973,1,24,Argentine Grand Prix,1973-01-28 00:00:00,00:00:00 -221,1973,2,17,Brazilian Grand Prix,1973-02-11 00:00:00,00:00:00 -222,1973,3,29,South African Grand Prix,1973-03-03 00:00:00,00:00:00 -223,1973,4,48,Spanish Grand Prix,1973-04-29 00:00:00,00:00:00 -224,1973,5,39,Belgian Grand Prix,1973-05-20 00:00:00,00:00:00 -225,1973,6,5,Monaco Grand Prix,1973-06-03 00:00:00,00:00:00 -226,1973,7,46,Swedish Grand Prix,1973-06-17 00:00:00,00:00:00 -227,1973,8,33,French Grand Prix,1973-07-01 00:00:00,00:00:00 -228,1973,9,8,British Grand Prix,1973-07-14 00:00:00,00:00:00 -229,1973,10,38,Dutch Grand Prix,1973-07-29 00:00:00,00:00:00 -230,1973,11,19,German Grand Prix,1973-08-05 00:00:00,00:00:00 -231,1973,12,69,Austrian Grand Prix,1973-08-19 00:00:00,00:00:00 -232,1973,13,13,Italian Grand Prix,1973-09-09 00:00:00,00:00:00 -233,1973,14,47,Canadian Grand Prix,1973-09-23 00:00:00,00:00:00 -234,1973,15,45,United States Grand Prix,1973-10-07 00:00:00,00:00:00 -235,1974,1,24,Argentine Grand Prix,1974-01-13 00:00:00,00:00:00 -236,1974,2,17,Brazilian Grand Prix,1974-01-27 00:00:00,00:00:00 -237,1974,3,29,South African Grand Prix,1974-03-30 00:00:00,00:00:00 -238,1974,4,44,Spanish Grand Prix,1974-04-28 00:00:00,00:00:00 -239,1974,5,49,Belgian Grand Prix,1974-05-12 00:00:00,00:00:00 -240,1974,6,5,Monaco Grand Prix,1974-05-26 00:00:00,00:00:00 -241,1974,7,46,Swedish Grand Prix,1974-06-09 00:00:00,00:00:00 -242,1974,8,38,Dutch Grand Prix,1974-06-23 00:00:00,00:00:00 -243,1974,9,40,French Grand Prix,1974-07-07 00:00:00,00:00:00 -244,1974,10,37,British Grand Prix,1974-07-20 00:00:00,00:00:00 -245,1974,11,19,German Grand Prix,1974-08-04 00:00:00,00:00:00 -246,1974,12,69,Austrian Grand Prix,1974-08-18 00:00:00,00:00:00 -247,1974,13,13,Italian Grand Prix,1974-09-08 00:00:00,00:00:00 -248,1974,14,47,Canadian Grand Prix,1974-09-22 00:00:00,00:00:00 -249,1974,15,45,United States Grand Prix,1974-10-06 00:00:00,00:00:00 -250,1975,1,24,Argentine Grand Prix,1975-01-12 00:00:00,00:00:00 -251,1975,2,17,Brazilian Grand Prix,1975-01-26 00:00:00,00:00:00 -252,1975,3,29,South African Grand Prix,1975-03-01 00:00:00,00:00:00 -253,1975,4,48,Spanish Grand Prix,1975-04-27 00:00:00,00:00:00 -254,1975,5,5,Monaco Grand Prix,1975-05-11 00:00:00,00:00:00 -255,1975,6,39,Belgian Grand Prix,1975-05-25 00:00:00,00:00:00 -256,1975,7,46,Swedish Grand Prix,1975-06-08 00:00:00,00:00:00 -257,1975,8,38,Dutch Grand Prix,1975-06-22 00:00:00,00:00:00 -258,1975,9,33,French Grand Prix,1975-07-06 00:00:00,00:00:00 -259,1975,10,8,British Grand Prix,1975-07-19 00:00:00,00:00:00 -260,1975,11,19,German Grand Prix,1975-08-03 00:00:00,00:00:00 -261,1975,12,69,Austrian Grand Prix,1975-08-17 00:00:00,00:00:00 -262,1975,13,13,Italian Grand Prix,1975-09-07 00:00:00,00:00:00 -263,1975,14,45,United States Grand Prix,1975-10-05 00:00:00,00:00:00 -264,1976,1,17,Brazilian Grand Prix,1976-01-25 00:00:00,00:00:00 -265,1976,2,29,South African Grand Prix,1976-03-06 00:00:00,00:00:00 -266,1976,3,42,United States Grand Prix West,1976-03-28 00:00:00,00:00:00 -267,1976,4,44,Spanish Grand Prix,1976-05-02 00:00:00,00:00:00 -268,1976,5,39,Belgian Grand Prix,1976-05-16 00:00:00,00:00:00 -269,1976,6,5,Monaco Grand Prix,1976-05-30 00:00:00,00:00:00 -270,1976,7,46,Swedish Grand Prix,1976-06-13 00:00:00,00:00:00 -271,1976,8,33,French Grand Prix,1976-07-04 00:00:00,00:00:00 -272,1976,9,37,British Grand Prix,1976-07-18 00:00:00,00:00:00 -273,1976,10,19,German Grand Prix,1976-08-01 00:00:00,00:00:00 -274,1976,11,69,Austrian Grand Prix,1976-08-15 00:00:00,00:00:00 -275,1976,12,38,Dutch Grand Prix,1976-08-29 00:00:00,00:00:00 -276,1976,13,13,Italian Grand Prix,1976-09-12 00:00:00,00:00:00 -277,1976,14,47,Canadian Grand Prix,1976-10-03 00:00:00,00:00:00 -278,1976,15,45,United States Grand Prix,1976-10-10 00:00:00,00:00:00 -279,1976,16,15,Japanese Grand Prix,1976-10-24 00:00:00,00:00:00 -280,1977,1,24,Argentine Grand Prix,1977-01-09 00:00:00,00:00:00 -281,1977,2,17,Brazilian Grand Prix,1977-01-23 00:00:00,00:00:00 -282,1977,3,29,South African Grand Prix,1977-03-05 00:00:00,00:00:00 -283,1977,4,42,United States Grand Prix West,1977-04-03 00:00:00,00:00:00 -284,1977,5,44,Spanish Grand Prix,1977-05-08 00:00:00,00:00:00 -285,1977,6,5,Monaco Grand Prix,1977-05-22 00:00:00,00:00:00 -286,1977,7,39,Belgian Grand Prix,1977-06-05 00:00:00,00:00:00 -287,1977,8,46,Swedish Grand Prix,1977-06-19 00:00:00,00:00:00 -288,1977,9,40,French Grand Prix,1977-07-03 00:00:00,00:00:00 -289,1977,10,8,British Grand Prix,1977-07-16 00:00:00,00:00:00 -290,1977,11,9,German Grand Prix,1977-07-31 00:00:00,00:00:00 -291,1977,12,69,Austrian Grand Prix,1977-08-14 00:00:00,00:00:00 -292,1977,13,38,Dutch Grand Prix,1977-08-28 00:00:00,00:00:00 -293,1977,14,13,Italian Grand Prix,1977-09-11 00:00:00,00:00:00 -294,1977,15,45,United States Grand Prix,1977-10-02 00:00:00,00:00:00 -295,1977,16,47,Canadian Grand Prix,1977-10-09 00:00:00,00:00:00 -296,1977,17,15,Japanese Grand Prix,1977-10-23 00:00:00,00:00:00 -297,1978,1,24,Argentine Grand Prix,1978-01-15 00:00:00,00:00:00 -298,1978,2,35,Brazilian Grand Prix,1978-01-29 00:00:00,00:00:00 -299,1978,3,29,South African Grand Prix,1978-03-04 00:00:00,00:00:00 -300,1978,4,42,United States Grand Prix West,1978-04-02 00:00:00,00:00:00 -301,1978,5,5,Monaco Grand Prix,1978-05-07 00:00:00,00:00:00 -302,1978,6,39,Belgian Grand Prix,1978-05-21 00:00:00,00:00:00 -303,1978,7,44,Spanish Grand Prix,1978-06-04 00:00:00,00:00:00 -304,1978,8,46,Swedish Grand Prix,1978-06-17 00:00:00,00:00:00 -305,1978,9,33,French Grand Prix,1978-07-02 00:00:00,00:00:00 -306,1978,10,37,British Grand Prix,1978-07-16 00:00:00,00:00:00 -307,1978,11,9,German Grand Prix,1978-07-30 00:00:00,00:00:00 -308,1978,12,69,Austrian Grand Prix,1978-08-13 00:00:00,00:00:00 -309,1978,13,38,Dutch Grand Prix,1978-08-27 00:00:00,00:00:00 -310,1978,14,13,Italian Grand Prix,1978-09-10 00:00:00,00:00:00 -311,1978,15,45,United States Grand Prix,1978-10-01 00:00:00,00:00:00 -312,1978,16,6,Canadian Grand Prix,1978-10-08 00:00:00,00:00:00 -313,1979,1,24,Argentine Grand Prix,1979-01-21 00:00:00,00:00:00 -314,1979,2,17,Brazilian Grand Prix,1979-02-04 00:00:00,00:00:00 -315,1979,3,29,South African Grand Prix,1979-03-03 00:00:00,00:00:00 -316,1979,4,42,United States Grand Prix West,1979-04-08 00:00:00,00:00:00 -317,1979,5,44,Spanish Grand Prix,1979-04-29 00:00:00,00:00:00 -318,1979,6,39,Belgian Grand Prix,1979-05-13 00:00:00,00:00:00 -319,1979,7,5,Monaco Grand Prix,1979-05-27 00:00:00,00:00:00 -320,1979,8,40,French Grand Prix,1979-07-01 00:00:00,00:00:00 -321,1979,9,8,British Grand Prix,1979-07-14 00:00:00,00:00:00 -322,1979,10,9,German Grand Prix,1979-07-29 00:00:00,00:00:00 -323,1979,11,69,Austrian Grand Prix,1979-08-12 00:00:00,00:00:00 -324,1979,12,38,Dutch Grand Prix,1979-08-26 00:00:00,00:00:00 -325,1979,13,13,Italian Grand Prix,1979-09-09 00:00:00,00:00:00 -326,1979,14,6,Canadian Grand Prix,1979-09-30 00:00:00,00:00:00 -327,1979,15,45,United States Grand Prix,1979-10-07 00:00:00,00:00:00 -328,1980,1,24,Argentine Grand Prix,1980-01-13 00:00:00,00:00:00 -329,1980,2,17,Brazilian Grand Prix,1980-01-27 00:00:00,00:00:00 -330,1980,3,29,South African Grand Prix,1980-03-01 00:00:00,00:00:00 -331,1980,4,42,United States Grand Prix West,1980-03-30 00:00:00,00:00:00 -332,1980,5,39,Belgian Grand Prix,1980-05-04 00:00:00,00:00:00 -333,1980,6,5,Monaco Grand Prix,1980-05-18 00:00:00,00:00:00 -334,1980,7,33,French Grand Prix,1980-06-29 00:00:00,00:00:00 -335,1980,8,37,British Grand Prix,1980-07-13 00:00:00,00:00:00 -336,1980,9,9,German Grand Prix,1980-08-10 00:00:00,00:00:00 -337,1980,10,69,Austrian Grand Prix,1980-08-17 00:00:00,00:00:00 -338,1980,11,38,Dutch Grand Prix,1980-08-31 00:00:00,00:00:00 -339,1980,12,20,Italian Grand Prix,1980-09-14 00:00:00,00:00:00 -340,1980,13,6,Canadian Grand Prix,1980-09-28 00:00:00,00:00:00 -341,1980,14,45,United States Grand Prix,1980-10-05 00:00:00,00:00:00 -342,1981,1,42,United States Grand Prix West,1981-03-15 00:00:00,00:00:00 -343,1981,2,35,Brazilian Grand Prix,1981-03-29 00:00:00,00:00:00 -344,1981,3,24,Argentine Grand Prix,1981-04-12 00:00:00,00:00:00 -345,1981,4,20,San Marino Grand Prix,1981-05-03 00:00:00,00:00:00 -346,1981,5,39,Belgian Grand Prix,1981-05-17 00:00:00,00:00:00 -347,1981,6,5,Monaco Grand Prix,1981-05-31 00:00:00,00:00:00 -348,1981,7,44,Spanish Grand Prix,1981-06-21 00:00:00,00:00:00 -349,1981,8,40,French Grand Prix,1981-07-05 00:00:00,00:00:00 -350,1981,9,8,British Grand Prix,1981-07-18 00:00:00,00:00:00 -351,1981,10,9,German Grand Prix,1981-08-02 00:00:00,00:00:00 -352,1981,11,69,Austrian Grand Prix,1981-08-16 00:00:00,00:00:00 -353,1981,12,38,Dutch Grand Prix,1981-08-30 00:00:00,00:00:00 -354,1981,13,13,Italian Grand Prix,1981-09-13 00:00:00,00:00:00 -355,1981,14,6,Canadian Grand Prix,1981-09-27 00:00:00,00:00:00 -356,1981,15,43,Caesars Palace Grand Prix,1981-10-17 00:00:00,00:00:00 -357,1982,1,29,South African Grand Prix,1982-01-23 00:00:00,00:00:00 -358,1982,2,35,Brazilian Grand Prix,1982-03-21 00:00:00,00:00:00 -359,1982,3,42,United States Grand Prix West,1982-04-04 00:00:00,00:00:00 -360,1982,4,20,San Marino Grand Prix,1982-04-25 00:00:00,00:00:00 -361,1982,5,39,Belgian Grand Prix,1982-05-09 00:00:00,00:00:00 -362,1982,6,5,Monaco Grand Prix,1982-05-23 00:00:00,00:00:00 -363,1982,7,36,Detroit Grand Prix,1982-06-06 00:00:00,00:00:00 -364,1982,8,6,Canadian Grand Prix,1982-06-13 00:00:00,00:00:00 -365,1982,9,38,Dutch Grand Prix,1982-07-03 00:00:00,00:00:00 -366,1982,10,37,British Grand Prix,1982-07-18 00:00:00,00:00:00 -367,1982,11,33,French Grand Prix,1982-07-25 00:00:00,00:00:00 -368,1982,12,9,German Grand Prix,1982-08-08 00:00:00,00:00:00 -369,1982,13,69,Austrian Grand Prix,1982-08-15 00:00:00,00:00:00 -370,1982,14,40,Swiss Grand Prix,1982-08-29 00:00:00,00:00:00 -371,1982,15,13,Italian Grand Prix,1982-09-12 00:00:00,00:00:00 -372,1982,16,43,Caesars Palace Grand Prix,1982-09-25 00:00:00,00:00:00 -373,1983,1,35,Brazilian Grand Prix,1983-03-13 00:00:00,00:00:00 -374,1983,2,42,United States Grand Prix West,1983-03-27 00:00:00,00:00:00 -375,1983,3,33,French Grand Prix,1983-04-17 00:00:00,00:00:00 -376,1983,4,20,San Marino Grand Prix,1983-05-01 00:00:00,00:00:00 -377,1983,5,5,Monaco Grand Prix,1983-05-15 00:00:00,00:00:00 -378,1983,6,12,Belgian Grand Prix,1983-05-22 00:00:00,00:00:00 -379,1983,7,36,Detroit Grand Prix,1983-06-05 00:00:00,00:00:00 -380,1983,8,6,Canadian Grand Prix,1983-06-12 00:00:00,00:00:00 -381,1983,9,8,British Grand Prix,1983-07-16 00:00:00,00:00:00 -382,1983,10,9,German Grand Prix,1983-08-07 00:00:00,00:00:00 -383,1983,11,69,Austrian Grand Prix,1983-08-14 00:00:00,00:00:00 -384,1983,12,38,Dutch Grand Prix,1983-08-28 00:00:00,00:00:00 -385,1983,13,13,Italian Grand Prix,1983-09-11 00:00:00,00:00:00 -386,1983,14,37,European Grand Prix,1983-09-25 00:00:00,00:00:00 -387,1983,15,29,South African Grand Prix,1983-10-15 00:00:00,00:00:00 -388,1984,1,35,Brazilian Grand Prix,1984-03-25 00:00:00,00:00:00 -389,1984,2,29,South African Grand Prix,1984-04-07 00:00:00,00:00:00 -390,1984,3,39,Belgian Grand Prix,1984-04-29 00:00:00,00:00:00 -391,1984,4,20,San Marino Grand Prix,1984-05-06 00:00:00,00:00:00 -392,1984,5,40,French Grand Prix,1984-05-20 00:00:00,00:00:00 -393,1984,6,5,Monaco Grand Prix,1984-06-03 00:00:00,00:00:00 -394,1984,7,6,Canadian Grand Prix,1984-06-17 00:00:00,00:00:00 -395,1984,8,36,Detroit Grand Prix,1984-06-24 00:00:00,00:00:00 -396,1984,9,41,Dallas Grand Prix,1984-07-08 00:00:00,00:00:00 -397,1984,10,37,British Grand Prix,1984-07-22 00:00:00,00:00:00 -398,1984,11,9,German Grand Prix,1984-08-05 00:00:00,00:00:00 -399,1984,12,69,Austrian Grand Prix,1984-08-19 00:00:00,00:00:00 -400,1984,13,38,Dutch Grand Prix,1984-08-26 00:00:00,00:00:00 -401,1984,14,13,Italian Grand Prix,1984-09-09 00:00:00,00:00:00 -402,1984,15,19,European Grand Prix,1984-10-07 00:00:00,00:00:00 -403,1984,16,26,Portuguese Grand Prix,1984-10-21 00:00:00,00:00:00 -404,1985,1,35,Brazilian Grand Prix,1985-04-07 00:00:00,00:00:00 -405,1985,2,26,Portuguese Grand Prix,1985-04-21 00:00:00,00:00:00 -406,1985,3,20,San Marino Grand Prix,1985-05-05 00:00:00,00:00:00 -407,1985,4,5,Monaco Grand Prix,1985-05-19 00:00:00,00:00:00 -408,1985,5,6,Canadian Grand Prix,1985-06-16 00:00:00,00:00:00 -409,1985,6,36,Detroit Grand Prix,1985-06-23 00:00:00,00:00:00 -410,1985,7,33,French Grand Prix,1985-07-07 00:00:00,00:00:00 -411,1985,8,8,British Grand Prix,1985-07-21 00:00:00,00:00:00 -412,1985,9,19,German Grand Prix,1985-08-04 00:00:00,00:00:00 -413,1985,10,69,Austrian Grand Prix,1985-08-18 00:00:00,00:00:00 -414,1985,11,38,Dutch Grand Prix,1985-08-25 00:00:00,00:00:00 -415,1985,12,13,Italian Grand Prix,1985-09-08 00:00:00,00:00:00 -416,1985,13,12,Belgian Grand Prix,1985-09-15 00:00:00,00:00:00 -417,1985,14,37,European Grand Prix,1985-10-06 00:00:00,00:00:00 -418,1985,15,29,South African Grand Prix,1985-10-19 00:00:00,00:00:00 -419,1985,16,28,Australian Grand Prix,1985-11-03 00:00:00,00:00:00 -420,1986,1,35,Brazilian Grand Prix,1986-03-23 00:00:00,00:00:00 -421,1986,2,25,Spanish Grand Prix,1986-04-13 00:00:00,00:00:00 -422,1986,3,20,San Marino Grand Prix,1986-04-27 00:00:00,00:00:00 -423,1986,4,5,Monaco Grand Prix,1986-05-11 00:00:00,00:00:00 -424,1986,5,12,Belgian Grand Prix,1986-05-25 00:00:00,00:00:00 -425,1986,6,6,Canadian Grand Prix,1986-06-15 00:00:00,00:00:00 -426,1986,7,36,Detroit Grand Prix,1986-06-22 00:00:00,00:00:00 -427,1986,8,33,French Grand Prix,1986-07-06 00:00:00,00:00:00 -428,1986,9,37,British Grand Prix,1986-07-13 00:00:00,00:00:00 -429,1986,10,9,German Grand Prix,1986-07-27 00:00:00,00:00:00 -430,1986,11,10,Hungarian Grand Prix,1986-08-10 00:00:00,00:00:00 -431,1986,12,69,Austrian Grand Prix,1986-08-17 00:00:00,00:00:00 -432,1986,13,13,Italian Grand Prix,1986-09-07 00:00:00,00:00:00 -433,1986,14,26,Portuguese Grand Prix,1986-09-21 00:00:00,00:00:00 -434,1986,15,31,Mexican Grand Prix,1986-10-12 00:00:00,00:00:00 -435,1986,16,28,Australian Grand Prix,1986-10-26 00:00:00,00:00:00 -436,1987,1,35,Brazilian Grand Prix,1987-04-12 00:00:00,00:00:00 -437,1987,2,20,San Marino Grand Prix,1987-05-03 00:00:00,00:00:00 -438,1987,3,12,Belgian Grand Prix,1987-05-17 00:00:00,00:00:00 -439,1987,4,5,Monaco Grand Prix,1987-05-31 00:00:00,00:00:00 -440,1987,5,36,Detroit Grand Prix,1987-06-21 00:00:00,00:00:00 -441,1987,6,33,French Grand Prix,1987-07-05 00:00:00,00:00:00 -442,1987,7,8,British Grand Prix,1987-07-12 00:00:00,00:00:00 -443,1987,8,9,German Grand Prix,1987-07-26 00:00:00,00:00:00 -444,1987,9,10,Hungarian Grand Prix,1987-08-09 00:00:00,00:00:00 -445,1987,10,69,Austrian Grand Prix,1987-08-16 00:00:00,00:00:00 -446,1987,11,13,Italian Grand Prix,1987-09-06 00:00:00,00:00:00 -447,1987,12,26,Portuguese Grand Prix,1987-09-20 00:00:00,00:00:00 -448,1987,13,25,Spanish Grand Prix,1987-09-27 00:00:00,00:00:00 -449,1987,14,31,Mexican Grand Prix,1987-10-18 00:00:00,00:00:00 -450,1987,15,21,Japanese Grand Prix,1987-11-01 00:00:00,00:00:00 -451,1987,16,28,Australian Grand Prix,1987-11-15 00:00:00,00:00:00 -452,1988,1,35,Brazilian Grand Prix,1988-04-03 00:00:00,00:00:00 -453,1988,2,20,San Marino Grand Prix,1988-05-01 00:00:00,00:00:00 -454,1988,3,5,Monaco Grand Prix,1988-05-15 00:00:00,00:00:00 -455,1988,4,31,Mexican Grand Prix,1988-05-29 00:00:00,00:00:00 -456,1988,5,6,Canadian Grand Prix,1988-06-12 00:00:00,00:00:00 -457,1988,6,36,Detroit Grand Prix,1988-06-19 00:00:00,00:00:00 -458,1988,7,33,French Grand Prix,1988-07-03 00:00:00,00:00:00 -459,1988,8,8,British Grand Prix,1988-07-10 00:00:00,00:00:00 -460,1988,9,9,German Grand Prix,1988-07-24 00:00:00,00:00:00 -461,1988,10,10,Hungarian Grand Prix,1988-08-07 00:00:00,00:00:00 -462,1988,11,12,Belgian Grand Prix,1988-08-28 00:00:00,00:00:00 -463,1988,12,13,Italian Grand Prix,1988-09-11 00:00:00,00:00:00 -464,1988,13,26,Portuguese Grand Prix,1988-09-25 00:00:00,00:00:00 -465,1988,14,25,Spanish Grand Prix,1988-10-02 00:00:00,00:00:00 -466,1988,15,21,Japanese Grand Prix,1988-10-30 00:00:00,00:00:00 -467,1988,16,28,Australian Grand Prix,1988-11-13 00:00:00,00:00:00 -468,1989,1,35,Brazilian Grand Prix,1989-03-26 00:00:00,00:00:00 -469,1989,2,20,San Marino Grand Prix,1989-04-23 00:00:00,00:00:00 -470,1989,3,5,Monaco Grand Prix,1989-05-07 00:00:00,00:00:00 -471,1989,4,31,Mexican Grand Prix,1989-05-28 00:00:00,00:00:00 -472,1989,5,32,United States Grand Prix,1989-06-04 00:00:00,00:00:00 -473,1989,6,6,Canadian Grand Prix,1989-06-18 00:00:00,00:00:00 -474,1989,7,33,French Grand Prix,1989-07-09 00:00:00,00:00:00 -475,1989,8,8,British Grand Prix,1989-07-16 00:00:00,00:00:00 -476,1989,9,9,German Grand Prix,1989-07-30 00:00:00,00:00:00 -477,1989,10,10,Hungarian Grand Prix,1989-08-13 00:00:00,00:00:00 -478,1989,11,12,Belgian Grand Prix,1989-08-27 00:00:00,00:00:00 -479,1989,12,13,Italian Grand Prix,1989-09-10 00:00:00,00:00:00 -480,1989,13,26,Portuguese Grand Prix,1989-09-24 00:00:00,00:00:00 -481,1989,14,25,Spanish Grand Prix,1989-10-01 00:00:00,00:00:00 -482,1989,15,21,Japanese Grand Prix,1989-10-22 00:00:00,00:00:00 -483,1989,16,28,Australian Grand Prix,1989-11-05 00:00:00,00:00:00 -484,1990,1,32,United States Grand Prix,1990-03-11 00:00:00,00:00:00 -485,1990,2,17,Brazilian Grand Prix,1990-03-25 00:00:00,00:00:00 -486,1990,3,20,San Marino Grand Prix,1990-05-13 00:00:00,00:00:00 -487,1990,4,5,Monaco Grand Prix,1990-05-27 00:00:00,00:00:00 -488,1990,5,6,Canadian Grand Prix,1990-06-10 00:00:00,00:00:00 -489,1990,6,31,Mexican Grand Prix,1990-06-24 00:00:00,00:00:00 -490,1990,7,33,French Grand Prix,1990-07-08 00:00:00,00:00:00 -491,1990,8,8,British Grand Prix,1990-07-15 00:00:00,00:00:00 -492,1990,9,9,German Grand Prix,1990-07-29 00:00:00,00:00:00 -493,1990,10,10,Hungarian Grand Prix,1990-08-12 00:00:00,00:00:00 -494,1990,11,12,Belgian Grand Prix,1990-08-26 00:00:00,00:00:00 -495,1990,12,13,Italian Grand Prix,1990-09-09 00:00:00,00:00:00 -496,1990,13,26,Portuguese Grand Prix,1990-09-23 00:00:00,00:00:00 -497,1990,14,25,Spanish Grand Prix,1990-09-30 00:00:00,00:00:00 -498,1990,15,21,Japanese Grand Prix,1990-10-21 00:00:00,00:00:00 -499,1990,16,28,Australian Grand Prix,1990-11-04 00:00:00,00:00:00 -500,1991,1,32,United States Grand Prix,1991-03-10 00:00:00,00:00:00 -501,1991,2,17,Brazilian Grand Prix,1991-03-24 00:00:00,00:00:00 -502,1991,3,20,San Marino Grand Prix,1991-04-28 00:00:00,00:00:00 -503,1991,4,5,Monaco Grand Prix,1991-05-12 00:00:00,00:00:00 -504,1991,5,6,Canadian Grand Prix,1991-06-02 00:00:00,00:00:00 -505,1991,6,31,Mexican Grand Prix,1991-06-16 00:00:00,00:00:00 -506,1991,7,7,French Grand Prix,1991-07-07 00:00:00,00:00:00 -507,1991,8,8,British Grand Prix,1991-07-14 00:00:00,00:00:00 -508,1991,9,9,German Grand Prix,1991-07-28 00:00:00,00:00:00 -509,1991,10,10,Hungarian Grand Prix,1991-08-11 00:00:00,00:00:00 -510,1991,11,12,Belgian Grand Prix,1991-08-25 00:00:00,00:00:00 -511,1991,12,13,Italian Grand Prix,1991-09-08 00:00:00,00:00:00 -512,1991,13,26,Portuguese Grand Prix,1991-09-22 00:00:00,00:00:00 -513,1991,14,3,Spanish Grand Prix,1991-09-29 00:00:00,00:00:00 -514,1991,15,21,Japanese Grand Prix,1991-10-20 00:00:00,00:00:00 -515,1991,16,28,Australian Grand Prix,1991-11-03 00:00:00,00:00:00 -516,1992,1,29,South African Grand Prix,1992-03-01 00:00:00,00:00:00 -517,1992,2,31,Mexican Grand Prix,1992-03-22 00:00:00,00:00:00 -518,1992,3,17,Brazilian Grand Prix,1992-04-05 00:00:00,00:00:00 -519,1992,4,3,Spanish Grand Prix,1992-05-03 00:00:00,00:00:00 -520,1992,5,20,San Marino Grand Prix,1992-05-17 00:00:00,00:00:00 -521,1992,6,5,Monaco Grand Prix,1992-05-31 00:00:00,00:00:00 -522,1992,7,6,Canadian Grand Prix,1992-06-14 00:00:00,00:00:00 -523,1992,8,7,French Grand Prix,1992-07-05 00:00:00,00:00:00 -524,1992,9,8,British Grand Prix,1992-07-12 00:00:00,00:00:00 -525,1992,10,9,German Grand Prix,1992-07-26 00:00:00,00:00:00 -526,1992,11,10,Hungarian Grand Prix,1992-08-16 00:00:00,00:00:00 -527,1992,12,12,Belgian Grand Prix,1992-08-30 00:00:00,00:00:00 -528,1992,13,13,Italian Grand Prix,1992-09-13 00:00:00,00:00:00 -529,1992,14,26,Portuguese Grand Prix,1992-09-27 00:00:00,00:00:00 -530,1992,15,21,Japanese Grand Prix,1992-10-25 00:00:00,00:00:00 -531,1992,16,28,Australian Grand Prix,1992-11-08 00:00:00,00:00:00 -532,1993,1,29,South African Grand Prix,1993-03-14 00:00:00,00:00:00 -533,1993,2,17,Brazilian Grand Prix,1993-03-28 00:00:00,00:00:00 -534,1993,3,30,European Grand Prix,1993-04-11 00:00:00,00:00:00 -535,1993,4,20,San Marino Grand Prix,1993-04-25 00:00:00,00:00:00 -536,1993,5,3,Spanish Grand Prix,1993-05-09 00:00:00,00:00:00 -537,1993,6,5,Monaco Grand Prix,1993-05-23 00:00:00,00:00:00 -538,1993,7,6,Canadian Grand Prix,1993-06-13 00:00:00,00:00:00 -539,1993,8,7,French Grand Prix,1993-07-04 00:00:00,00:00:00 -540,1993,9,8,British Grand Prix,1993-07-11 00:00:00,00:00:00 -541,1993,10,9,German Grand Prix,1993-07-25 00:00:00,00:00:00 -542,1993,11,10,Hungarian Grand Prix,1993-08-15 00:00:00,00:00:00 -543,1993,12,12,Belgian Grand Prix,1993-08-29 00:00:00,00:00:00 -544,1993,13,13,Italian Grand Prix,1993-09-12 00:00:00,00:00:00 -545,1993,14,26,Portuguese Grand Prix,1993-09-26 00:00:00,00:00:00 -546,1993,15,21,Japanese Grand Prix,1993-10-24 00:00:00,00:00:00 -547,1993,16,28,Australian Grand Prix,1993-11-07 00:00:00,00:00:00 -548,1994,1,17,Brazilian Grand Prix,1994-03-27 00:00:00,00:00:00 -549,1994,2,27,Pacific Grand Prix,1994-04-17 00:00:00,00:00:00 -550,1994,3,20,San Marino Grand Prix,1994-05-01 00:00:00,00:00:00 -551,1994,4,5,Monaco Grand Prix,1994-05-15 00:00:00,00:00:00 -552,1994,5,3,Spanish Grand Prix,1994-05-29 00:00:00,00:00:00 -553,1994,6,6,Canadian Grand Prix,1994-06-12 00:00:00,00:00:00 -554,1994,7,7,French Grand Prix,1994-07-03 00:00:00,00:00:00 -555,1994,8,8,British Grand Prix,1994-07-10 00:00:00,00:00:00 -556,1994,9,9,German Grand Prix,1994-07-31 00:00:00,00:00:00 -557,1994,10,10,Hungarian Grand Prix,1994-08-14 00:00:00,00:00:00 -558,1994,11,12,Belgian Grand Prix,1994-08-28 00:00:00,00:00:00 -559,1994,12,13,Italian Grand Prix,1994-09-11 00:00:00,00:00:00 -560,1994,13,26,Portuguese Grand Prix,1994-09-25 00:00:00,00:00:00 -561,1994,14,25,European Grand Prix,1994-10-16 00:00:00,00:00:00 -562,1994,15,21,Japanese Grand Prix,1994-11-06 00:00:00,00:00:00 -563,1994,16,28,Australian Grand Prix,1994-11-13 00:00:00,00:00:00 -564,1995,1,17,Brazilian Grand Prix,1995-03-26 00:00:00,00:00:00 -565,1995,2,24,Argentine Grand Prix,1995-04-09 00:00:00,00:00:00 -566,1995,3,20,San Marino Grand Prix,1995-04-30 00:00:00,00:00:00 -567,1995,4,3,Spanish Grand Prix,1995-05-14 00:00:00,00:00:00 -568,1995,5,5,Monaco Grand Prix,1995-05-28 00:00:00,00:00:00 -569,1995,6,6,Canadian Grand Prix,1995-06-11 00:00:00,00:00:00 -570,1995,7,7,French Grand Prix,1995-07-02 00:00:00,00:00:00 -571,1995,8,8,British Grand Prix,1995-07-16 00:00:00,00:00:00 -572,1995,9,9,German Grand Prix,1995-07-30 00:00:00,00:00:00 -573,1995,10,10,Hungarian Grand Prix,1995-08-13 00:00:00,00:00:00 -574,1995,11,12,Belgian Grand Prix,1995-08-27 00:00:00,00:00:00 -575,1995,12,13,Italian Grand Prix,1995-09-10 00:00:00,00:00:00 -576,1995,13,26,Portuguese Grand Prix,1995-09-24 00:00:00,00:00:00 -577,1995,14,19,European Grand Prix,1995-10-01 00:00:00,00:00:00 -578,1995,15,27,Pacific Grand Prix,1995-10-22 00:00:00,00:00:00 -579,1995,16,21,Japanese Grand Prix,1995-10-29 00:00:00,00:00:00 -580,1995,17,28,Australian Grand Prix,1995-11-12 00:00:00,00:00:00 -581,1996,1,0,Australian Grand Prix,1996-03-10 00:00:00,00:00:00 -582,1996,2,17,Brazilian Grand Prix,1996-03-31 00:00:00,00:00:00 -583,1996,3,24,Argentine Grand Prix,1996-04-07 00:00:00,00:00:00 -584,1996,4,19,European Grand Prix,1996-04-28 00:00:00,00:00:00 -585,1996,5,20,San Marino Grand Prix,1996-05-05 00:00:00,00:00:00 -586,1996,6,5,Monaco Grand Prix,1996-05-19 00:00:00,00:00:00 -587,1996,7,3,Spanish Grand Prix,1996-06-02 00:00:00,00:00:00 -588,1996,8,6,Canadian Grand Prix,1996-06-16 00:00:00,00:00:00 -589,1996,9,7,French Grand Prix,1996-06-30 00:00:00,00:00:00 -590,1996,10,8,British Grand Prix,1996-07-14 00:00:00,00:00:00 -591,1996,11,9,German Grand Prix,1996-07-28 00:00:00,00:00:00 -592,1996,12,10,Hungarian Grand Prix,1996-08-11 00:00:00,00:00:00 -593,1996,13,12,Belgian Grand Prix,1996-08-25 00:00:00,00:00:00 -594,1996,14,13,Italian Grand Prix,1996-09-08 00:00:00,00:00:00 -595,1996,15,26,Portuguese Grand Prix,1996-09-22 00:00:00,00:00:00 -596,1996,16,21,Japanese Grand Prix,1996-10-13 00:00:00,00:00:00 -597,1997,1,0,Australian Grand Prix,1997-03-09 00:00:00,00:00:00 -598,1997,2,17,Brazilian Grand Prix,1997-03-30 00:00:00,00:00:00 -599,1997,3,24,Argentine Grand Prix,1997-04-13 00:00:00,00:00:00 -600,1997,4,20,San Marino Grand Prix,1997-04-27 00:00:00,00:00:00 -601,1997,5,5,Monaco Grand Prix,1997-05-11 00:00:00,00:00:00 -602,1997,6,3,Spanish Grand Prix,1997-05-25 00:00:00,00:00:00 -603,1997,7,6,Canadian Grand Prix,1997-06-15 00:00:00,00:00:00 -604,1997,8,7,French Grand Prix,1997-06-29 00:00:00,00:00:00 -605,1997,9,8,British Grand Prix,1997-07-13 00:00:00,00:00:00 -606,1997,10,9,German Grand Prix,1997-07-27 00:00:00,00:00:00 -607,1997,11,10,Hungarian Grand Prix,1997-08-10 00:00:00,00:00:00 -608,1997,12,12,Belgian Grand Prix,1997-08-24 00:00:00,00:00:00 -609,1997,13,13,Italian Grand Prix,1997-09-07 00:00:00,00:00:00 -610,1997,14,69,Austrian Grand Prix,1997-09-21 00:00:00,00:00:00 -611,1997,15,19,Luxembourg Grand Prix,1997-09-28 00:00:00,00:00:00 -612,1997,16,21,Japanese Grand Prix,1997-10-12 00:00:00,00:00:00 -613,1997,17,25,European Grand Prix,1997-10-26 00:00:00,00:00:00 -614,1998,1,0,Australian Grand Prix,1998-03-08 00:00:00,00:00:00 -615,1998,2,17,Brazilian Grand Prix,1998-03-29 00:00:00,00:00:00 -616,1998,3,24,Argentine Grand Prix,1998-04-12 00:00:00,00:00:00 -617,1998,4,20,San Marino Grand Prix,1998-04-26 00:00:00,00:00:00 -618,1998,5,3,Spanish Grand Prix,1998-05-10 00:00:00,00:00:00 -619,1998,6,5,Monaco Grand Prix,1998-05-24 00:00:00,00:00:00 -620,1998,7,6,Canadian Grand Prix,1998-06-07 00:00:00,00:00:00 -621,1998,8,7,French Grand Prix,1998-06-28 00:00:00,00:00:00 -622,1998,9,8,British Grand Prix,1998-07-12 00:00:00,00:00:00 -623,1998,10,69,Austrian Grand Prix,1998-07-26 00:00:00,00:00:00 -624,1998,11,9,German Grand Prix,1998-08-02 00:00:00,00:00:00 -625,1998,12,10,Hungarian Grand Prix,1998-08-16 00:00:00,00:00:00 -626,1998,13,12,Belgian Grand Prix,1998-08-30 00:00:00,00:00:00 -627,1998,14,13,Italian Grand Prix,1998-09-13 00:00:00,00:00:00 -628,1998,15,19,Luxembourg Grand Prix,1998-09-27 00:00:00,00:00:00 -629,1998,16,21,Japanese Grand Prix,1998-11-01 00:00:00,00:00:00 -630,1999,1,0,Australian Grand Prix,1999-03-07 00:00:00,00:00:00 -631,1999,2,17,Brazilian Grand Prix,1999-04-11 00:00:00,00:00:00 -632,1999,3,20,San Marino Grand Prix,1999-05-02 00:00:00,00:00:00 -633,1999,4,5,Monaco Grand Prix,1999-05-16 00:00:00,00:00:00 -634,1999,5,3,Spanish Grand Prix,1999-05-30 00:00:00,00:00:00 -635,1999,6,6,Canadian Grand Prix,1999-06-13 00:00:00,00:00:00 -636,1999,7,7,French Grand Prix,1999-06-27 00:00:00,00:00:00 -637,1999,8,8,British Grand Prix,1999-07-11 00:00:00,00:00:00 -638,1999,9,69,Austrian Grand Prix,1999-07-25 00:00:00,00:00:00 -639,1999,10,9,German Grand Prix,1999-08-01 00:00:00,00:00:00 -640,1999,11,10,Hungarian Grand Prix,1999-08-15 00:00:00,00:00:00 -641,1999,12,12,Belgian Grand Prix,1999-08-29 00:00:00,00:00:00 -642,1999,13,13,Italian Grand Prix,1999-09-12 00:00:00,00:00:00 -643,1999,14,19,European Grand Prix,1999-09-26 00:00:00,00:00:00 -644,1999,15,1,Malaysian Grand Prix,1999-10-17 00:00:00,00:00:00 -645,1999,16,21,Japanese Grand Prix,1999-10-31 00:00:00,00:00:00 -646,2000,1,0,Australian Grand Prix,2000-03-12 00:00:00,00:00:00 -647,2000,2,17,Brazilian Grand Prix,2000-03-26 00:00:00,00:00:00 -648,2000,3,20,San Marino Grand Prix,2000-04-09 00:00:00,00:00:00 -649,2000,4,8,British Grand Prix,2000-04-23 00:00:00,00:00:00 -650,2000,5,3,Spanish Grand Prix,2000-05-07 00:00:00,00:00:00 -651,2000,6,19,European Grand Prix,2000-05-21 00:00:00,00:00:00 -652,2000,7,5,Monaco Grand Prix,2000-06-04 00:00:00,00:00:00 -653,2000,8,6,Canadian Grand Prix,2000-06-18 00:00:00,00:00:00 -654,2000,9,7,French Grand Prix,2000-07-02 00:00:00,00:00:00 -655,2000,10,69,Austrian Grand Prix,2000-07-16 00:00:00,00:00:00 -656,2000,11,9,German Grand Prix,2000-07-30 00:00:00,00:00:00 -657,2000,12,10,Hungarian Grand Prix,2000-08-13 00:00:00,00:00:00 -658,2000,13,12,Belgian Grand Prix,2000-08-27 00:00:00,00:00:00 -659,2000,14,13,Italian Grand Prix,2000-09-10 00:00:00,00:00:00 -660,2000,15,18,United States Grand Prix,2000-09-24 00:00:00,00:00:00 -661,2000,16,21,Japanese Grand Prix,2000-10-08 00:00:00,00:00:00 -662,2000,17,1,Malaysian Grand Prix,2000-10-22 00:00:00,00:00:00 -663,2001,1,0,Australian Grand Prix,2001-03-04 00:00:00,00:00:00 -664,2001,2,1,Malaysian Grand Prix,2001-03-18 00:00:00,00:00:00 -665,2001,3,17,Brazilian Grand Prix,2001-04-01 00:00:00,00:00:00 -666,2001,4,20,San Marino Grand Prix,2001-04-15 00:00:00,00:00:00 -667,2001,5,3,Spanish Grand Prix,2001-04-29 00:00:00,00:00:00 -668,2001,6,69,Austrian Grand Prix,2001-05-13 00:00:00,00:00:00 -669,2001,7,5,Monaco Grand Prix,2001-05-27 00:00:00,00:00:00 -670,2001,8,6,Canadian Grand Prix,2001-06-10 00:00:00,00:00:00 -671,2001,9,19,European Grand Prix,2001-06-24 00:00:00,00:00:00 -672,2001,10,7,French Grand Prix,2001-07-01 00:00:00,00:00:00 -673,2001,11,8,British Grand Prix,2001-07-15 00:00:00,00:00:00 -674,2001,12,9,German Grand Prix,2001-07-29 00:00:00,00:00:00 -675,2001,13,10,Hungarian Grand Prix,2001-08-19 00:00:00,00:00:00 -676,2001,14,12,Belgian Grand Prix,2001-09-02 00:00:00,00:00:00 -677,2001,15,13,Italian Grand Prix,2001-09-16 00:00:00,00:00:00 -678,2001,16,18,United States Grand Prix,2001-09-30 00:00:00,00:00:00 -679,2001,17,21,Japanese Grand Prix,2001-10-14 00:00:00,00:00:00 -680,2002,1,0,Australian Grand Prix,2002-03-03 00:00:00,00:00:00 -681,2002,2,1,Malaysian Grand Prix,2002-03-17 00:00:00,00:00:00 -682,2002,3,17,Brazilian Grand Prix,2002-03-31 00:00:00,00:00:00 -683,2002,4,20,San Marino Grand Prix,2002-04-14 00:00:00,00:00:00 -684,2002,5,3,Spanish Grand Prix,2002-04-28 00:00:00,00:00:00 -685,2002,6,69,Austrian Grand Prix,2002-05-12 00:00:00,00:00:00 -686,2002,7,5,Monaco Grand Prix,2002-05-26 00:00:00,00:00:00 -687,2002,8,6,Canadian Grand Prix,2002-06-09 00:00:00,00:00:00 -688,2002,9,19,European Grand Prix,2002-06-23 00:00:00,00:00:00 -689,2002,10,8,British Grand Prix,2002-07-07 00:00:00,00:00:00 -690,2002,11,7,French Grand Prix,2002-07-21 00:00:00,00:00:00 -691,2002,12,9,German Grand Prix,2002-07-28 00:00:00,00:00:00 -692,2002,13,10,Hungarian Grand Prix,2002-08-18 00:00:00,00:00:00 -693,2002,14,12,Belgian Grand Prix,2002-09-01 00:00:00,00:00:00 -694,2002,15,13,Italian Grand Prix,2002-09-15 00:00:00,00:00:00 -695,2002,16,18,United States Grand Prix,2002-09-29 00:00:00,00:00:00 -696,2002,17,21,Japanese Grand Prix,2002-10-13 00:00:00,00:00:00 -697,2003,1,0,Australian Grand Prix,2003-03-09 00:00:00,00:00:00 -698,2003,2,1,Malaysian Grand Prix,2003-03-23 00:00:00,00:00:00 -699,2003,3,17,Brazilian Grand Prix,2003-04-06 00:00:00,00:00:00 -700,2003,4,20,San Marino Grand Prix,2003-04-20 00:00:00,00:00:00 -701,2003,5,3,Spanish Grand Prix,2003-05-04 00:00:00,00:00:00 -702,2003,6,69,Austrian Grand Prix,2003-05-18 00:00:00,00:00:00 -703,2003,7,5,Monaco Grand Prix,2003-06-01 00:00:00,00:00:00 -704,2003,8,6,Canadian Grand Prix,2003-06-15 00:00:00,00:00:00 -705,2003,9,19,European Grand Prix,2003-06-29 00:00:00,00:00:00 -706,2003,10,7,French Grand Prix,2003-07-06 00:00:00,00:00:00 -707,2003,11,8,British Grand Prix,2003-07-20 00:00:00,00:00:00 -708,2003,12,9,German Grand Prix,2003-08-03 00:00:00,00:00:00 -709,2003,13,10,Hungarian Grand Prix,2003-08-24 00:00:00,00:00:00 -710,2003,14,13,Italian Grand Prix,2003-09-14 00:00:00,00:00:00 -711,2003,15,18,United States Grand Prix,2003-09-28 00:00:00,00:00:00 -712,2003,16,21,Japanese Grand Prix,2003-10-12 00:00:00,00:00:00 -713,2004,1,0,Australian Grand Prix,2004-03-07 00:00:00,00:00:00 -714,2004,2,1,Malaysian Grand Prix,2004-03-21 00:00:00,00:00:00 -715,2004,3,2,Bahrain Grand Prix,2004-04-04 00:00:00,00:00:00 -716,2004,4,20,San Marino Grand Prix,2004-04-25 00:00:00,00:00:00 -717,2004,5,3,Spanish Grand Prix,2004-05-09 00:00:00,00:00:00 -718,2004,6,5,Monaco Grand Prix,2004-05-23 00:00:00,00:00:00 -719,2004,7,19,European Grand Prix,2004-05-30 00:00:00,00:00:00 -720,2004,8,6,Canadian Grand Prix,2004-06-13 00:00:00,00:00:00 -721,2004,9,18,United States Grand Prix,2004-06-20 00:00:00,00:00:00 -722,2004,10,7,French Grand Prix,2004-07-04 00:00:00,00:00:00 -723,2004,11,8,British Grand Prix,2004-07-11 00:00:00,00:00:00 -724,2004,12,9,German Grand Prix,2004-07-25 00:00:00,00:00:00 -725,2004,13,10,Hungarian Grand Prix,2004-08-15 00:00:00,00:00:00 -726,2004,14,12,Belgian Grand Prix,2004-08-29 00:00:00,00:00:00 -727,2004,15,13,Italian Grand Prix,2004-09-12 00:00:00,00:00:00 -728,2004,16,16,Chinese Grand Prix,2004-09-26 00:00:00,00:00:00 -729,2004,17,21,Japanese Grand Prix,2004-10-10 00:00:00,00:00:00 -730,2004,18,17,Brazilian Grand Prix,2004-10-24 00:00:00,00:00:00 -731,2005,1,0,Australian Grand Prix,2005-03-06 14:00:00,14:00:00 -732,2005,2,1,Malaysian Grand Prix,2005-03-20 15:00:00,15:00:00 -733,2005,3,2,Bahrain Grand Prix,2005-04-03 14:30:00,14:30:00 -734,2005,4,20,San Marino Grand Prix,2005-04-24 14:00:00,14:00:00 -735,2005,5,3,Spanish Grand Prix,2005-05-08 14:00:00,14:00:00 -736,2005,6,5,Monaco Grand Prix,2005-05-22 14:00:00,14:00:00 -737,2005,7,19,European Grand Prix,2005-05-29 14:00:00,14:00:00 -738,2005,8,6,Canadian Grand Prix,2005-06-12 13:00:00,13:00:00 -739,2005,9,18,United States Grand Prix,2005-06-19 14:00:00,14:00:00 -740,2005,10,7,French Grand Prix,2005-07-03 14:00:00,14:00:00 -741,2005,11,8,British Grand Prix,2005-07-10 14:00:00,14:00:00 -742,2005,12,9,German Grand Prix,2005-07-24 14:00:00,14:00:00 -743,2005,13,10,Hungarian Grand Prix,2005-07-31 14:00:00,14:00:00 -744,2005,14,4,Turkish Grand Prix,2005-08-21 15:00:00,15:00:00 -745,2005,15,13,Italian Grand Prix,2005-09-04 14:00:00,14:00:00 -746,2005,16,12,Belgian Grand Prix,2005-09-11 14:00:00,14:00:00 -747,2005,17,17,Brazilian Grand Prix,2005-09-25 14:00:00,14:00:00 -748,2005,18,21,Japanese Grand Prix,2005-10-09 14:00:00,14:00:00 -749,2005,19,16,Chinese Grand Prix,2005-10-16 14:00:00,14:00:00 -750,2006,1,2,Bahrain Grand Prix,2006-03-12 14:30:00,14:30:00 -751,2006,2,1,Malaysian Grand Prix,2006-03-19 15:00:00,15:00:00 -752,2006,3,0,Australian Grand Prix,2006-04-02 14:00:00,14:00:00 -753,2006,4,20,San Marino Grand Prix,2006-04-23 14:00:00,14:00:00 -754,2006,5,19,European Grand Prix,2006-05-07 14:00:00,14:00:00 -755,2006,6,3,Spanish Grand Prix,2006-05-14 14:00:00,14:00:00 -756,2006,7,5,Monaco Grand Prix,2006-05-28 14:00:00,14:00:00 -757,2006,8,8,British Grand Prix,2006-06-11 12:00:00,12:00:00 -758,2006,9,6,Canadian Grand Prix,2006-06-25 13:00:00,13:00:00 -759,2006,10,18,United States Grand Prix,2006-07-02 14:00:00,14:00:00 -760,2006,11,7,French Grand Prix,2006-07-16 14:00:00,14:00:00 -761,2006,12,9,German Grand Prix,2006-07-30 14:00:00,14:00:00 -762,2006,13,10,Hungarian Grand Prix,2006-08-06 14:00:00,14:00:00 -763,2006,14,4,Turkish Grand Prix,2006-08-27 15:00:00,15:00:00 -764,2006,15,13,Italian Grand Prix,2006-09-10 14:00:00,14:00:00 -765,2006,16,16,Chinese Grand Prix,2006-10-01 14:00:00,14:00:00 -766,2006,17,21,Japanese Grand Prix,2006-10-08 14:00:00,14:00:00 -767,2006,18,17,Brazilian Grand Prix,2006-10-22 14:00:00,14:00:00 -768,2007,1,0,Australian Grand Prix,2007-03-18 03:00:00,03:00:00 -769,2007,2,1,Malaysian Grand Prix,2007-04-08 07:00:00,07:00:00 -770,2007,3,2,Bahrain Grand Prix,2007-04-15 11:30:00,11:30:00 -771,2007,4,3,Spanish Grand Prix,2007-05-13 12:00:00,12:00:00 -772,2007,5,5,Monaco Grand Prix,2007-05-27 12:00:00,12:00:00 -773,2007,6,6,Canadian Grand Prix,2007-06-10 17:00:00,17:00:00 -774,2007,7,18,United States Grand Prix,2007-06-17 17:00:00,17:00:00 -775,2007,8,7,French Grand Prix,2007-07-01 12:00:00,12:00:00 -776,2007,9,8,British Grand Prix,2007-07-08 12:00:00,12:00:00 -777,2007,10,19,European Grand Prix,2007-07-22 12:00:00,12:00:00 -778,2007,11,10,Hungarian Grand Prix,2007-08-05 12:00:00,12:00:00 -779,2007,12,4,Turkish Grand Prix,2007-08-26 12:00:00,12:00:00 -780,2007,13,13,Italian Grand Prix,2007-09-09 12:00:00,12:00:00 -781,2007,14,12,Belgian Grand Prix,2007-09-16 12:00:00,12:00:00 -782,2007,15,15,Japanese Grand Prix,2007-09-30 04:30:00,04:30:00 -783,2007,16,16,Chinese Grand Prix,2007-10-07 06:00:00,06:00:00 -784,2007,17,17,Brazilian Grand Prix,2007-10-21 16:00:00,16:00:00 -785,2008,1,0,Australian Grand Prix,2008-03-16 04:30:00,04:30:00 -786,2008,2,1,Malaysian Grand Prix,2008-03-23 07:00:00,07:00:00 -787,2008,3,2,Bahrain Grand Prix,2008-04-06 11:30:00,11:30:00 -788,2008,4,3,Spanish Grand Prix,2008-04-27 12:00:00,12:00:00 -789,2008,5,4,Turkish Grand Prix,2008-05-11 12:00:00,12:00:00 -790,2008,6,5,Monaco Grand Prix,2008-05-25 12:00:00,12:00:00 -791,2008,7,6,Canadian Grand Prix,2008-06-08 17:00:00,17:00:00 -792,2008,8,7,French Grand Prix,2008-06-22 12:00:00,12:00:00 -793,2008,9,8,British Grand Prix,2008-07-06 12:00:00,12:00:00 -794,2008,10,9,German Grand Prix,2008-07-20 12:00:00,12:00:00 -795,2008,11,10,Hungarian Grand Prix,2008-08-03 12:00:00,12:00:00 -796,2008,12,11,European Grand Prix,2008-08-24 12:00:00,12:00:00 -797,2008,13,12,Belgian Grand Prix,2008-09-07 12:00:00,12:00:00 -798,2008,14,13,Italian Grand Prix,2008-09-14 12:00:00,12:00:00 -799,2008,15,14,Singapore Grand Prix,2008-09-28 12:00:00,12:00:00 -800,2008,16,15,Japanese Grand Prix,2008-10-12 04:30:00,04:30:00 -801,2008,17,16,Chinese Grand Prix,2008-10-19 07:00:00,07:00:00 -802,2008,18,17,Brazilian Grand Prix,2008-11-02 17:00:00,17:00:00 -803,2009,1,0,Australian Grand Prix,2009-03-29 06:00:00,06:00:00 -804,2009,2,1,Malaysian Grand Prix,2009-04-05 09:00:00,09:00:00 -805,2009,3,16,Chinese Grand Prix,2009-04-19 07:00:00,07:00:00 -806,2009,4,2,Bahrain Grand Prix,2009-04-26 12:00:00,12:00:00 -807,2009,5,3,Spanish Grand Prix,2009-05-10 12:00:00,12:00:00 -808,2009,6,5,Monaco Grand Prix,2009-05-24 12:00:00,12:00:00 -809,2009,7,4,Turkish Grand Prix,2009-06-07 12:00:00,12:00:00 -810,2009,8,8,British Grand Prix,2009-06-21 12:00:00,12:00:00 -811,2009,9,19,German Grand Prix,2009-07-12 12:00:00,12:00:00 -812,2009,10,10,Hungarian Grand Prix,2009-07-26 12:00:00,12:00:00 -813,2009,11,11,European Grand Prix,2009-08-23 12:00:00,12:00:00 -814,2009,12,12,Belgian Grand Prix,2009-08-30 12:00:00,12:00:00 -815,2009,13,13,Italian Grand Prix,2009-09-13 12:00:00,12:00:00 -816,2009,14,14,Singapore Grand Prix,2009-09-27 12:00:00,12:00:00 -817,2009,15,21,Japanese Grand Prix,2009-10-04 05:00:00,05:00:00 -818,2009,16,17,Brazilian Grand Prix,2009-10-18 16:00:00,16:00:00 -819,2009,17,23,Abu Dhabi Grand Prix,2009-11-01 11:00:00,11:00:00 diff --git a/scripts/f1_data/results.csv b/scripts/f1_data/results.csv deleted file mode 100644 index e1131b65..00000000 --- a/scripts/f1_data/results.csv +++ /dev/null @@ -1,20324 +0,0 @@ -resultId,raceId,driverId,constructorId,number,grid,position,positionOrder,points,laps,milliseconds,fastestLap,rank,statusId,date -0,0,660,152,18.0,21,11.0,11,0.0,64,,,,16,1950-05-13 -1,0,790,149,8.0,12,,21,0.0,2,,,,126,1950-05-13 -2,0,579,49,1.0,3,,12,0.0,62,,,,44,1950-05-13 -3,0,661,149,9.0,10,,20,0.0,5,,,,6,1950-05-13 -4,0,789,152,17.0,7,,19,0.0,8,,,,51,1950-05-13 -5,0,589,103,19.0,11,,18,0.0,26,,,,8,1950-05-13 -6,0,640,103,20.0,8,,17,0.0,36,,,,5,1950-05-13 -7,0,785,124,24.0,17,,16,0.0,43,,,,7,1950-05-13 -8,0,747,103,5.0,18,,15,0.0,44,,,,5,1950-05-13 -9,0,778,103,10.0,20,10.0,10,0.0,64,,,,16,1950-05-13 -10,0,741,152,16.0,14,8.0,8,0.0,65,,,,15,1950-05-13 -11,0,784,103,6.0,16,9.0,9,0.0,64,,,,16,1950-05-13 -12,0,619,149,12.0,13,6.0,6,0.0,67,,,,13,1950-05-13 -13,0,627,152,15.0,9,5.0,5,2.0,68,,,,12,1950-05-13 -14,0,704,152,14.0,6,4.0,4,3.0,68,,,,12,1950-05-13 -15,0,686,49,4.0,4,3.0,3,4.0,70,8055600.0,,,1,1950-05-13 -16,0,786,49,3.0,2,2.0,2,6.0,70,8006200.0,,,1,1950-05-13 -17,0,642,49,2.0,1,1.0,1,9.0,70,8003600.0,,,1,1950-05-13 -18,0,669,103,21.0,5,,14,0.0,49,,,,60,1950-05-13 -19,0,776,124,23.0,19,,13,0.0,57,,,,62,1950-05-13 -20,0,666,149,9.0,10,,20,0.0,5,,,,6,1950-05-13 -21,0,788,103,10.0,20,10.0,10,0.0,64,,,,16,1950-05-13 -22,0,787,149,11.0,15,7.0,7,0.0,67,,,,13,1950-05-13 -23,1,589,103,48.0,8,3.0,3,4.0,98,,,,12,1950-05-21 -24,1,579,49,34.0,1,1.0,1,9.0,100,11598700.0,,,1,1950-05-21 -25,1,647,5,40.0,7,2.0,2,6.0,99,,,,11,1950-05-21 -26,1,793,5,42.0,9,4.0,4,3.0,97,,,,13,1950-05-21 -27,1,626,139,10.0,11,,14,0.0,0,,,,3,1950-05-21 -28,1,619,149,26.0,16,6.0,6,0.0,94,,,,16,1950-05-21 -29,1,660,152,6.0,19,7.0,7,0.0,94,,,,16,1950-05-21 -30,1,633,5,38.0,6,,8,0.0,63,,,,109,1950-05-21 -31,1,741,152,14.0,4,,9,0.0,38,,,,44,1950-05-21 -32,1,498,103,2.0,3,,10,0.0,1,,,,3,1950-05-21 -33,1,786,49,36.0,5,,12,0.0,0,,,,3,1950-05-21 -34,1,627,152,16.0,10,,13,0.0,0,,,,3,1950-05-21 -35,1,640,103,52.0,12,,15,0.0,0,,,,3,1950-05-21 -36,1,426,139,12.0,13,,16,0.0,0,,,,3,1950-05-21 -37,1,787,149,24.0,14,,17,0.0,0,,,,3,1950-05-21 -38,1,762,103,44.0,17,,18,0.0,0,,,,3,1950-05-21 -39,1,501,85,8.0,20,,19,0.0,0,,,,4,1950-05-21 -40,1,687,5,28.0,21,,20,0.0,0,,,,5,1950-05-21 -41,1,669,103,50.0,15,5.0,5,2.0,95,,,,15,1950-05-21 -42,1,642,49,32.0,2,,11,0.0,0,,,,3,1950-05-21 -43,1,792,103,4.0,18,,21,0.0,0,,,,3,1950-05-21 -44,2,593,111,1.0,5,1.0,1,9.0,138,10015970.0,,,1,1950-05-30 -45,2,529,148,14.0,8,,31,0.0,30,,,,67,1950-05-30 -46,2,611,111,23.0,25,,30,0.0,42,,,,51,1950-05-30 -47,2,799,111,61.0,32,,29,0.0,52,,,,126,1950-05-30 -48,2,615,111,28.0,2,,28,0.0,64,,,,44,1950-05-30 -49,2,798,159,24.0,17,,27,0.0,108,,,,51,1950-05-30 -50,2,729,160,67.0,22,,26,0.0,111,,,,7,1950-05-30 -51,2,731,103,12.0,21,,25,0.0,112,,,,70,1950-05-30 -52,2,509,158,76.0,28,24.0,24,0.0,122,,,,116,1950-05-30 -53,2,797,157,77.0,30,23.0,23,0.0,123,,,,20,1950-05-30 -54,2,796,156,27.0,29,22.0,22,0.0,123,,,,112,1950-05-30 -55,2,537,105,45.0,18,,32,0.0,25,,,,85,1950-05-30 -56,2,659,111,81.0,15,21.0,21,0.0,125,,,,53,1950-05-30 -57,2,771,111,4.0,20,19.0,19,0.0,127,,,,45,1950-05-30 -58,2,732,111,62.0,33,18.0,18,0.0,128,,,,88,1950-05-30 -59,2,653,114,22.0,27,17.0,17,0.0,128,,,,88,1950-05-30 -60,2,520,155,75.0,31,16.0,16,0.0,128,,,,88,1950-05-30 -61,2,526,108,55.0,24,15.0,15,0.0,130,,,,18,1950-05-30 -62,2,658,111,49.0,6,14.0,14,0.0,131,,,,20,1950-05-30 -63,2,772,111,15.0,26,13.0,13,0.0,132,,,,16,1950-05-30 -64,2,518,127,18.0,13,12.0,12,0.0,133,,,,15,1950-05-30 -65,2,795,154,2.0,16,11.0,11,0.0,133,,,,15,1950-05-30 -66,2,559,111,59.0,11,10.0,10,0.0,135,,,,13,1950-05-30 -67,2,677,103,21.0,14,20.0,20,0.0,126,,,,55,1950-05-30 -68,2,555,136,7.0,19,9.0,9,0.0,135,,,,13,1950-05-30 -69,2,630,111,69.0,7,,33,0.0,10,,,,44,1950-05-30 -70,2,726,108,5.0,4,8.0,8,0.0,135,,,,13,1950-05-30 -71,2,701,148,3.0,10,2.0,2,6.0,137,,,,11,1950-05-30 -72,2,768,148,31.0,3,3.0,3,4.0,137,,,,11,1950-05-30 -73,2,770,111,54.0,12,4.0,4,3.0,137,,,,11,1950-05-30 -74,2,794,111,17.0,9,5.0,5,1.0,136,,,,12,1950-05-30 -75,2,766,117,8.0,23,6.0,6,0.0,136,,,,12,1950-05-30 -76,2,654,111,98.0,1,7.0,7,0.0,135,,,,13,1950-05-30 -77,2,803,159,24.0,17,,27,0.0,108,,,,51,1950-05-30 -78,2,529,111,17.0,9,5.0,5,1.0,136,,,,12,1950-05-30 -79,3,741,152,42.0,6,,13,0.0,25,,,,6,1950-06-04 -80,3,789,152,8.0,9,,14,0.0,19,,,,3,1950-06-04 -81,3,793,5,20.0,13,,15,0.0,19,,,,22,1950-06-04 -82,3,633,5,22.0,4,,16,0.0,9,,,,5,1950-06-04 -83,3,786,49,12.0,3,2.0,2,6.0,42,7374100.0,,,1,1950-06-04 -84,3,642,49,16.0,2,1.0,1,9.0,42,7373700.0,,,1,1950-06-04 -85,3,660,152,4.0,14,10.0,10,0.0,38,,,,14,1950-06-04 -86,3,589,103,26.0,16,9.0,9,0.0,39,,,,13,1950-06-04 -87,3,501,152,44.0,18,8.0,8,0.0,39,,,,13,1950-06-04 -88,3,800,103,2.0,15,7.0,7,0.0,39,,,,13,1950-06-04 -89,3,640,103,32.0,11,6.0,6,0.0,40,,,,12,1950-06-04 -90,3,697,103,34.0,12,5.0,5,2.0,40,,,,12,1950-06-04 -91,3,669,103,30.0,8,4.0,4,3.0,40,,,,12,1950-06-04 -92,3,627,152,10.0,10,3.0,3,4.0,41,,,,11,1950-06-04 -93,3,579,49,14.0,1,,12,0.0,32,,,,5,1950-06-04 -94,3,647,5,18.0,5,,17,0.0,4,,,,94,1950-06-04 -95,3,704,152,6.0,7,,18,0.0,0,,,,3,1950-06-04 -96,3,780,103,40.0,17,11.0,11,0.0,35,,,,17,1950-06-04 -97,4,774,152,20.0,13,,11,0.0,22,,,,108,1950-06-18 -98,4,704,152,18.0,9,,14,0.0,2,,,,108,1950-06-18 -99,4,741,152,16.0,6,,13,0.0,15,,,,25,1950-06-18 -100,4,793,152,6.0,5,,12,0.0,20,,,,51,1950-06-18 -101,4,780,103,30.0,11,10.0,10,0.0,29,,,,16,1950-06-18 -102,4,785,124,26.0,12,9.0,9,0.0,30,,,,15,1950-06-18 -103,4,773,152,22.0,10,7.0,7,0.0,33,,,,12,1950-06-18 -104,4,660,152,24.0,14,8.0,8,0.0,22,,,,13,1950-06-18 -105,4,647,5,4.0,7,5.0,5,2.0,34,,,,11,1950-06-18 -106,4,642,49,8.0,1,4.0,4,4.0,35,10291000.0,,,1,1950-06-18 -107,4,627,152,14.0,8,3.0,3,4.0,35,10185000.0,,,1,1950-06-18 -108,4,786,49,12.0,3,2.0,2,6.0,35,10060000.0,,,1,1950-06-18 -109,4,579,49,10.0,2,1.0,1,8.0,35,10046000.0,,,1,1950-06-18 -110,4,633,5,2.0,4,6.0,6,0.0,33,,,,12,1950-06-18 -111,5,784,103,34.0,17,,16,0.0,5,,,,5,1950-07-02 -112,5,762,103,28.0,7,,14,0.0,6,,,,5,1950-07-02 -113,5,589,103,30.0,13,,15,0.0,6,,,,5,1950-07-02 -114,5,793,152,12.0,16,,17,0.0,4,,,,25,1950-07-02 -115,5,686,103,32.0,11,,13,0.0,9,,,,5,1950-07-02 -116,5,774,152,16.0,4,5.0,5,1.0,59,,,,15,1950-07-02 -117,5,627,152,26.0,15,6.0,6,0.0,56,,,,18,1950-07-02 -118,5,627,152,20.0,6,,12,0.0,10,,,,25,1950-07-02 -119,5,498,103,36.0,8,,18,0.0,3,,,,5,1950-07-02 -120,5,660,152,42.0,14,,11,0.0,11,,,,25,1950-07-02 -121,5,642,49,2.0,2,7.0,7,0.0,55,,,,48,1950-07-02 -122,5,773,152,22.0,9,,9,0.0,36,,,,5,1950-07-02 -123,5,704,152,18.0,5,8.0,8,0.0,52,,,,55,1950-07-02 -124,5,579,49,6.0,1,1.0,1,9.0,64,10672800.0,,,1,1950-07-02 -125,5,786,49,4.0,3,2.0,2,6.0,64,10698500.0,,,1,1950-07-02 -126,5,801,152,26.0,15,6.0,6,0.0,56,,,,18,1950-07-02 -127,5,741,152,16.0,4,5.0,5,1.0,59,,,,15,1950-07-02 -128,5,626,139,44.0,12,4.0,4,3.0,61,,,,13,1950-07-02 -129,5,687,5,14.0,18,3.0,3,4.0,61,,,,13,1950-07-02 -130,5,697,103,40.0,10,,10,0.0,14,,,,5,1950-07-02 -131,6,641,49,60.0,7,,13,0.0,34,,,,5,1950-09-03 -132,6,773,152,56.0,20,,14,0.0,29,,,,6,1950-09-03 -133,6,791,5,22.0,25,,18,0.0,17,,,,5,1950-09-03 -134,6,660,152,2.0,22,,16,0.0,22,,,,25,1950-09-03 -135,6,647,5,16.0,2,,17,0.0,21,,,,5,1950-09-03 -136,6,762,103,4.0,9,,12,0.0,39,,,,31,1950-09-03 -137,6,765,152,64.0,16,,19,0.0,16,,,,23,1950-09-03 -138,6,579,49,18.0,1,,15,1.0,23,,,,6,1950-09-03 -139,6,764,152,40.0,11,,11,0.0,42,,,,108,1950-09-03 -140,6,740,103,62.0,26,,20,0.0,15,,,,31,1950-09-03 -141,6,787,149,32.0,21,,9,0.0,51,,,,21,1950-09-03 -142,6,747,103,50.0,24,,8,0.0,56,,,,6,1950-09-03 -143,6,687,5,8.0,18,7.0,7,0.0,72,,,,18,1950-09-03 -144,6,640,103,38.0,17,6.0,6,0.0,72,,,,18,1950-09-03 -145,6,741,152,24.0,16,5.0,5,2.0,75,,,,15,1950-09-03 -146,6,627,152,58.0,13,4.0,4,3.0,75,,,,15,1950-09-03 -147,6,786,49,36.0,5,3.0,3,4.0,80,10373000.0,,,1,1950-09-03 -148,6,802,5,48.0,6,2.0,2,3.0,80,10356000.0,,,1,1950-09-03 -149,6,642,49,10.0,3,1.0,1,8.0,80,10277400.0,,,1,1950-09-03 -150,6,426,139,42.0,12,,21,0.0,13,,,,110,1950-09-03 -151,6,793,152,12.0,8,,10,0.0,48,,,,6,1950-09-03 -152,6,589,103,6.0,19,,22,0.0,13,,,,51,1950-09-03 -153,6,626,139,44.0,10,,24,0.0,7,,,,7,1950-09-03 -154,6,763,49,46.0,4,,23,0.0,11,,,,5,1950-09-03 -155,6,669,103,30.0,15,,25,0.0,1,,,,5,1950-09-03 -156,6,756,103,28.0,27,,26,0.0,0,,,,5,1950-09-03 -157,6,697,161,52.0,23,,27,0.0,0,,,,54,1950-09-03 -158,6,647,5,48.0,6,2.0,2,3.0,80,,,,1,1950-09-03 -159,6,579,49,60.0,7,,13,0.0,34,,,,5,1950-09-03 -160,7,475,131,14.0,14,8.0,8,0.0,40,,,,12,1951-05-27 -161,7,723,5,38.0,10,11.0,11,0.0,39,,,,13,1951-05-27 -162,7,501,103,32.0,17,12.0,12,0.0,38,,,,14,1951-05-27 -163,7,660,152,2.0,18,13.0,13,0.0,35,,,,17,1951-05-27 -164,7,764,152,40.0,21,14.0,14,0.0,31,,,,45,1951-05-27 -165,7,765,152,10.0,11,,16,0.0,30,,,,3,1951-05-27 -166,7,741,152,4.0,12,10.0,10,0.0,39,,,,13,1951-05-27 -167,7,725,131,12.0,20,,17,0.0,23,,,,121,1951-05-27 -168,7,704,152,6.0,15,,18,0.0,14,,,,80,1951-05-27 -169,7,633,5,18.0,3,,19,0.0,12,,,,3,1951-05-27 -170,7,687,5,16.0,9,,15,0.0,36,,,,3,1951-05-27 -171,7,579,49,24.0,1,1.0,1,9.0,42,7673640.0,,,1,1951-05-27 -172,7,763,49,28.0,4,4.0,4,3.0,41,,,,11,1951-05-27 -173,7,642,49,22.0,2,3.0,3,4.0,42,7752950.0,,,1,1951-05-27 -174,7,498,152,42.0,13,,20,0.0,10,,,,94,1951-05-27 -175,7,640,49,26.0,5,5.0,5,2.0,40,,,,12,1951-05-27 -176,7,647,5,20.0,7,6.0,6,0.0,40,,,,12,1951-05-27 -177,7,589,103,30.0,19,7.0,7,0.0,40,,,,12,1951-05-27 -178,7,627,152,8.0,8,9.0,9,0.0,39,,,,13,1951-05-27 -179,7,641,5,44.0,6,2.0,2,6.0,42,7728880.0,,,1,1951-05-27 -180,7,721,142,52.0,16,,21,0.0,0,,,,69,1951-05-27 -181,8,629,111,23.0,18,,28,0.0,30,,,,109,1951-05-30 -182,8,657,109,81.0,20,,29,0.0,29,,,,44,1951-05-30 -183,8,726,108,22.0,21,,30,0.0,29,,,,7,1951-05-30 -184,8,772,148,19.0,23,,31,0.0,18,,,,5,1951-05-30 -185,8,732,103,12.0,26,,32,0.0,15,,,,95,1951-05-30 -186,8,728,105,26.0,30,,33,0.0,8,,,,7,1951-05-30 -187,8,448,137,48.0,25,,27,0.0,34,,,,108,1951-05-30 -188,8,673,111,83.0,7,2.0,2,6.0,200,14365290.0,,,1,1951-05-30 -189,8,771,111,44.0,13,,26,0.0,55,,,,121,1951-05-30 -190,8,733,111,32.0,28,,25,0.0,56,,,,80,1951-05-30 -191,8,630,132,6.0,32,,24,0.0,73,,,,25,1951-05-30 -192,8,526,111,98.0,6,,23,0.0,78,,,,5,1951-05-30 -193,8,675,111,9.0,3,3.0,3,2.0,200,14429440.0,,,1,1951-05-30 -194,8,770,111,4.0,10,,22,0.0,80,,,,5,1951-05-30 -195,8,593,111,3.0,8,,21,0.0,87,,,,121,1951-05-30 -196,8,521,154,8.0,19,,20,0.0,93,,,,42,1951-05-30 -197,8,769,153,71.0,33,,19,0.0,97,,,,8,1951-05-30 -198,8,700,111,73.0,15,,18,0.0,93,,,,42,1951-05-30 -199,8,615,111,59.0,11,,17,0.0,109,,,,8,1951-05-30 -200,8,766,111,99.0,2,1.0,1,9.0,200,14258050.0,,,1,1951-05-30 -201,8,653,133,76.0,27,,16,0.0,110,,,,109,1951-05-30 -202,8,768,148,16.0,5,,14,0.0,126,,,,3,1951-05-30 -203,8,729,111,10.0,16,,13,0.0,129,,,,5,1951-05-30 -204,8,611,111,25.0,12,,12,0.0,135,,,,5,1951-05-30 -205,8,534,111,69.0,22,,11,0.0,142,,,,5,1951-05-30 -206,8,699,111,18.0,1,,10,0.0,151,,,,31,1951-05-30 -207,8,529,148,5.0,9,,9,0.0,178,,,,20,1951-05-30 -208,8,518,148,27.0,4,8.0,8,0.0,180,,,,127,1951-05-30 -209,8,767,111,68.0,24,7.0,7,0.0,193,,,,17,1951-05-30 -210,8,731,117,1.0,17,6.0,6,0.0,200,14598070.0,,,1,1951-05-30 -211,8,734,132,52.0,29,5.0,5,2.0,200,14550280.0,,,1,1951-05-30 -212,8,658,111,9.0,3,3.0,3,2.0,200,14429440.0,,,1,1951-05-30 -213,8,654,112,2.0,14,,15,0.0,123,,,,5,1951-05-30 -214,8,612,147,57.0,31,4.0,4,3.0,200,14538170.0,,,1,1951-05-30 -215,9,660,152,16.0,11,7.0,7,0.0,33,,,,13,1951-06-17 -216,9,633,5,10.0,3,3.0,3,4.0,36,10208100.0,,,1,1951-06-17 -217,9,647,5,8.0,4,2.0,2,6.0,36,10117200.0,,,1,1951-06-17 -218,9,641,5,12.0,5,,12,0.0,8,,,,7,1951-06-17 -219,9,763,49,6.0,6,,11,0.0,11,,,,21,1951-06-17 -220,9,627,152,14.0,7,4.0,4,3.0,34,,,,12,1951-06-17 -221,9,741,152,20.0,10,,13,0.0,0,,,,7,1951-06-17 -222,9,589,152,18.0,9,,10,0.0,28,,,,5,1951-06-17 -223,9,579,49,2.0,1,9.0,9,1.0,32,,,,14,1951-06-17 -224,9,642,49,4.0,2,1.0,1,8.0,36,9946200.0,,,1,1951-06-17 -225,9,428,152,24.0,12,6.0,6,0.0,33,,,,13,1951-06-17 -226,9,704,152,22.0,8,5.0,5,2.0,34,,,,12,1951-06-17 -227,9,773,152,26.0,13,8.0,8,0.0,32,,,,14,1951-06-17 -228,10,786,49,8.0,7,1.0,1,4.0,77,12131000.0,,,1,1951-07-01 -229,10,647,5,14.0,6,2.0,2,3.0,77,12189200.0,,,1,1951-07-01 -230,10,633,5,10.0,4,3.0,3,4.0,74,,,,13,1951-07-01 -231,10,686,5,26.0,9,4.0,4,3.0,73,,,,14,1951-07-01 -232,10,642,49,2.0,2,5.0,5,2.0,73,,,,14,1951-07-01 -233,10,589,152,42.0,8,6.0,6,0.0,71,,,,16,1951-07-01 -234,10,704,152,46.0,11,7.0,7,0.0,71,,,,16,1951-07-01 -235,10,774,152,44.0,14,8.0,8,0.0,69,,,,18,1951-07-01 -236,10,764,152,48.0,19,9.0,9,0.0,66,,,,45,1951-07-01 -237,10,579,49,24.0,1,11.0,11,0.0,55,,,,115,1951-07-01 -238,10,579,49,8.0,7,1.0,1,5.0,77,12131000.0,,,1,1951-07-01 -239,10,498,5,14.0,6,2.0,2,3.0,77,12189200.0,,,1,1951-07-01 -240,10,786,49,24.0,1,11.0,11,0.0,55,,,,115,1951-07-01 -241,10,687,5,24.0,20,,23,0.0,1,,,,5,1951-07-01 -242,10,640,103,18.0,16,,22,0.0,1,,,,7,1951-07-01 -243,10,670,103,50.0,15,,21,0.0,2,,,,5,1951-07-01 -244,10,763,49,6.0,5,10.0,10,0.0,58,,,,124,1951-07-01 -245,10,626,139,30.0,23,,20,0.0,3,,,,5,1951-07-01 -246,10,647,5,12.0,3,,18,0.0,10,,,,6,1951-07-01 -247,10,426,139,32.0,18,,17,0.0,11,,,,5,1951-07-01 -248,10,501,103,20.0,22,,16,0.0,23,,,,25,1951-07-01 -249,10,775,139,36.0,17,,15,0.0,27,,,,5,1951-07-01 -250,10,741,152,38.0,10,,14,0.0,37,,,,5,1951-07-01 -251,10,627,152,40.0,13,,13,0.0,43,,,,7,1951-07-01 -252,10,609,139,34.0,21,,19,0.0,7,,,,5,1951-07-01 -253,10,660,152,28.0,12,,12,0.0,54,,,,3,1951-07-01 -254,11,777,103,17.0,16,,17,0.0,46,,,,44,1951-07-14 -255,11,589,152,23.0,13,,19,0.0,41,,,,23,1951-07-14 -256,11,747,103,15.0,15,,18,0.0,45,,,,5,1951-07-14 -257,11,779,103,16.0,17,,20,0.0,23,,,,21,1951-07-14 -258,11,647,5,11.0,4,,16,0.0,56,,,,6,1951-07-14 -259,11,776,124,5.0,18,,15,0.0,75,,,,62,1951-07-14 -260,11,627,152,22.0,9,10.0,10,0.0,83,,,,17,1951-07-14 -261,11,498,5,12.0,1,1.0,1,8.0,90,9738200.0,,,1,1951-07-14 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-738,29,642,5,12.0,3,1.0,1,8.0,18,10945000.0,,,1,1953-08-02 -739,29,689,85,38.0,17,,18,0.0,15,,,,5,1953-08-02 -740,29,670,103,8.0,8,,19,0.0,13,,,,22,1953-08-02 -741,29,690,85,40.0,20,11.0,11,0.0,16,,,,12,1953-08-02 -742,29,554,126,9.0,9,,24,0.0,7,,,,6,1953-08-02 -743,29,712,142,23.0,18,,23,0.0,8,,,,31,1953-08-02 -744,29,711,142,26.0,34,,22,0.0,10,,,,31,1953-08-02 -745,29,660,123,12.0,25,,21,0.0,12,,,,31,1953-08-02 -746,29,430,144,35.0,24,,20,0.0,12,,,,43,1953-08-02 -747,30,426,126,8.0,4,,13,0.0,43,,,,109,1953-08-23 -748,30,647,5,46.0,2,1.0,1,9.0,65,10894400.0,,,1,1953-08-23 -749,30,642,5,24.0,3,2.0,2,6.0,65,10967330.0,,,1,1953-08-23 -750,30,578,5,26.0,7,3.0,3,4.0,65,10990360.0,,,1,1953-08-23 -751,30,579,103,32.0,1,4.0,4,1.5,64,,,,11,1953-08-23 -752,30,691,103,34.0,11,5.0,5,2.0,62,,,,13,1953-08-23 -753,30,633,5,28.0,6,6.0,6,0.0,62,,,,13,1953-08-23 -754,30,663,85,20.0,9,7.0,7,0.0,62,,,,13,1953-08-23 -755,30,697,103,30.0,10,,15,0.0,29,,,,5,1953-08-23 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-775,31,589,125,32.0,25,10.0,10,0.0,72,,,,18,1953-09-13 -776,31,501,126,38.0,15,9.0,9,0.0,75,,,,15,1953-09-13 -777,31,620,5,10.0,11,8.0,8,0.0,75,,,,15,1953-09-13 -778,31,475,85,28.0,10,13.0,13,0.0,70,,,,88,1953-09-13 -779,31,697,103,52.0,7,,18,0.0,77,,,,60,1953-09-13 -780,31,486,123,20.0,22,,21,0.0,61,,,,62,1953-09-13 -781,31,640,103,58.0,9,,20,0.0,70,,,,5,1953-09-13 -782,31,663,85,30.0,19,,22,0.0,57,,,,62,1953-09-13 -783,31,664,123,24.0,18,,23,0.0,56,,,,62,1953-09-13 -784,31,722,5,12.0,20,,24,0.0,40,,,,5,1953-09-13 -785,31,622,103,2.0,21,,26,0.0,18,,,,5,1953-09-13 -786,31,625,125,34.0,13,,27,0.0,17,,,,5,1953-09-13 -787,31,426,126,36.0,8,5.0,5,2.0,79,,,,11,1953-09-13 -788,31,667,131,18.0,26,,28,0.0,14,,,,5,1953-09-13 -789,31,660,123,26.0,30,,29,0.0,7,,,,69,1953-09-13 -790,31,651,131,14.0,27,,30,0.0,6,,,,5,1953-09-13 -791,31,644,103,56.0,12,7.0,7,0.0,76,,,,14,1953-09-13 -792,31,670,103,54.0,4,,19,0.0,75,,,,3,1953-09-13 -793,31,456,123,22.0,14,,25,0.0,33,,,,37,1953-09-13 -794,31,643,126,40.0,16,6.0,6,0.0,77,,,,13,1953-09-13 -795,31,633,5,2.0,5,3.0,3,4.0,79,,,,11,1953-09-13 -796,31,579,103,50.0,2,1.0,1,9.0,80,10185900.0,,,1,1953-09-13 -797,31,577,103,56.0,12,7.0,7,0.0,76,,,,14,1953-09-13 -798,31,578,5,8.0,6,4.0,4,3.0,79,,,,11,1953-09-13 -799,31,642,5,6.0,3,2.0,2,6.0,80,10187300.0,,,1,1953-09-13 -800,32,496,103,36.0,9,,18,0.0,0,,,,54,1954-01-17 -801,32,577,103,6.0,7,,17,0.0,0,,,,54,1954-01-17 -802,32,672,103,34.0,18,,15,0.0,19,,,,6,1954-01-17 -803,32,671,126,22.0,16,,14,0.0,19,,,,51,1954-01-17 -804,32,643,103,32.0,8,,13,0.0,37,,,,44,1954-01-17 -805,32,670,103,4.0,6,,12,0.0,48,,,,5,1954-01-17 -806,32,627,5,24.0,14,,16,0.0,1,,,,3,1954-01-17 -807,32,554,126,18.0,17,,10,0.0,61,,,,2,1954-01-17 -808,32,579,103,2.0,3,1.0,1,8.0,87,10855800.0,,,1,1954-01-17 -809,32,578,5,14.0,4,,11,0.0,52,,,,2,1954-01-17 -810,32,498,5,12.0,2,3.0,3,5.0,87,10976800.0,,,1,1954-01-17 -811,32,426,5,26.0,5,4.0,4,3.0,86,,,,11,1954-01-17 -812,32,625,126,20.0,15,5.0,5,2.0,85,,,,12,1954-01-17 -813,32,642,5,10.0,1,2.0,2,6.0,87,10934800.0,,,1,1954-01-17 -814,32,669,103,8.0,10,7.0,7,0.0,83,,,,14,1954-01-17 -815,32,640,103,30.0,13,8.0,8,0.0,83,,,,14,1954-01-17 -816,32,620,5,16.0,12,9.0,9,0.0,82,,,,15,1954-01-17 -817,32,501,103,28.0,11,6.0,6,0.0,84,,,,13,1954-01-17 -818,33,518,111,16.0,8,15.0,15,0.0,196,,,,14,1954-05-31 -819,33,528,107,7.0,6,7.0,7,0.0,200,14010620.0,,,1,1954-05-31 -820,33,555,111,5.0,32,8.0,8,0.0,200,14058440.0,,,1,1954-05-31 -821,33,674,111,28.0,25,9.0,9,0.0,200,14184510.0,,,1,1954-05-31 -822,33,655,127,24.0,13,10.0,10,0.0,200,14184960.0,,,1,1954-05-31 -823,33,656,111,45.0,27,11.0,11,0.0,200,14259460.0,,,1,1954-05-31 -824,33,526,111,34.0,11,4.0,4,1.5,200,13929950.0,,,1,1954-05-31 -825,33,521,112,98.0,5,12.0,12,0.0,199,,,,11,1954-05-31 -826,33,675,112,88.0,22,13.0,13,0.0,197,,,,13,1954-05-31 -827,33,628,111,17.0,9,14.0,14,0.0,197,,,,13,1954-05-31 -828,33,679,111,32.0,20,16.0,16,0.0,194,,,,16,1954-05-31 -829,33,678,132,33.0,26,,31,0.0,101,,,,23,1954-05-31 -830,33,596,127,27.0,31,18.0,18,0.0,193,,,,17,1954-05-31 -831,33,676,111,71.0,33,19.0,19,0.0,193,,,,17,1954-05-31 -832,33,611,111,1.0,10,,20,0.0,191,,,,20,1954-05-31 -833,33,597,111,35.0,12,,21,0.0,181,,,,20,1954-05-31 -834,33,448,133,12.0,16,,22,0.0,172,,,,31,1954-05-31 -835,33,520,111,31.0,17,23.0,23,0.0,168,,,,8,1954-05-31 -836,33,519,111,51.0,18,,33,0.0,74,,,,3,1954-05-31 -837,33,593,111,15.0,15,,32,0.0,79,,,,5,1954-05-31 -838,33,677,137,65.0,29,,30,0.0,104,,,,48,1954-05-31 -839,33,529,111,10.0,21,,29,0.0,105,,,,67,1954-05-31 -840,33,509,111,38.0,28,,28,0.0,110,,,,3,1954-05-31 -841,33,556,111,19.0,2,,27,0.0,111,,,,3,1954-05-31 -842,33,659,111,99.0,30,,26,0.0,130,,,,5,1954-05-31 -843,33,592,134,25.0,7,17.0,17,0.0,194,,,,16,1954-05-31 -844,33,615,111,77.0,24,6.0,6,0.0,200,13984820.0,,,1,1954-05-31 -845,33,658,111,2.0,1,3.0,3,5.0,200,13837000.0,,,1,1954-05-31 -846,33,612,132,74.0,23,,25,0.0,165,,,,22,1954-05-31 -847,33,657,111,14.0,19,1.0,1,8.0,200,13757270.0,,,1,1954-05-31 -848,33,525,112,9.0,3,2.0,2,6.0,200,13827220.0,,,1,1954-05-31 -849,33,730,132,33.0,26,,31,0.0,101,,,,23,1954-05-31 -850,33,805,137,65.0,29,,30,0.0,104,,,,48,1954-05-31 -851,33,559,111,38.0,28,,28,0.0,110,,,,3,1954-05-31 -852,33,702,132,74.0,23,,25,0.0,165,,,,22,1954-05-31 -853,33,556,136,43.0,4,,24,0.0,165,,,,31,1954-05-31 -854,33,673,111,73.0,14,5.0,5,2.0,200,13961820.0,,,1,1954-05-31 -855,33,612,136,43.0,4,,24,0.0,165,,,,31,1954-05-31 -856,33,613,111,31.0,17,,23,0.0,168,,,,8,1954-05-31 -857,33,513,133,12.0,16,,22,0.0,172,,,,31,1954-05-31 -858,33,509,111,1.0,10,,20,0.0,191,,,,20,1954-05-31 -859,33,512,136,43.0,4,,24,0.0,165,,,,31,1954-05-31 -860,33,730,111,71.0,33,19.0,19,0.0,193,,,,17,1954-05-31 -861,33,702,127,27.0,31,18.0,18,0.0,193,,,,17,1954-05-31 -862,33,529,111,16.0,8,15.0,15,0.0,196,,,,14,1954-05-31 -863,33,799,111,16.0,8,15.0,15,0.0,196,,,,14,1954-05-31 -864,33,518,111,34.0,11,4.0,4,1.5,200,13929950.0,,,1,1954-05-31 -865,33,659,111,5.0,32,8.0,8,0.0,200,14058440.0,,,1,1954-05-31 -866,33,613,111,16.0,8,15.0,15,0.0,196,,,,14,1954-05-31 -867,33,593,111,45.0,27,11.0,11,0.0,200,14259460.0,,,1,1954-05-31 -868,33,611,111,45.0,27,11.0,11,0.0,200,14259460.0,,,1,1954-05-31 -869,33,612,111,45.0,27,11.0,11,0.0,200,14259460.0,,,1,1954-05-31 -870,33,653,111,45.0,27,11.0,11,0.0,200,14259460.0,,,1,1954-05-31 -871,33,654,112,98.0,5,12.0,12,0.0,199,,,,11,1954-05-31 -872,33,653,111,1.0,10,,20,0.0,191,,,,20,1954-05-31 -873,34,578,5,10.0,5,4.0,4,1.5,35,,,,11,1954-06-20 -874,34,579,103,26.0,1,1.0,1,9.0,36,9882400.0,,,1,1954-06-20 -875,34,426,5,8.0,6,2.0,2,6.0,36,9906600.0,,,1,1954-06-20 -876,34,428,126,18.0,8,5.0,5,2.0,35,,,,11,1954-06-20 -877,34,498,5,10.0,5,4.0,4,1.5,35,,,,11,1954-06-20 -878,34,669,103,20.0,13,6.0,6,0.0,35,,,,11,1954-06-20 -879,34,644,103,30.0,11,7.0,7,0.0,34,,,,12,1954-06-20 -880,34,642,5,4.0,3,,8,0.0,14,,,,80,1954-06-20 -881,34,632,126,16.0,10,,9,0.0,14,,,,5,1954-06-20 -882,34,554,126,12.0,7,,10,0.0,12,,,,22,1954-06-20 -883,34,670,103,28.0,4,,11,0.0,3,,,,5,1954-06-20 -884,34,680,5,2.0,14,,13,0.0,1,,,,5,1954-06-20 -885,34,643,103,24.0,12,,14,0.0,0,,,,42,1954-06-20 -886,34,475,103,22.0,9,3.0,3,4.0,35,,,,11,1954-06-20 -887,34,498,5,6.0,2,,12,0.0,1,,,,5,1954-06-20 -888,35,643,103,16.0,11,,11,0.0,24,,,,5,1954-07-04 -889,35,648,129,20.0,2,2.0,2,6.0,61,9768000.0,,,1,1954-07-04 -890,35,644,103,40.0,0,,22,0.0,0,,,,54,1954-07-04 -891,35,647,103,10.0,3,,21,0.0,1,,,,7,1954-07-04 -892,35,650,126,26.0,18,,20,0.0,8,,,,5,1954-07-04 -893,35,578,5,6.0,8,,19,0.0,9,,,,5,1954-07-04 -894,35,681,126,30.0,20,,18,0.0,9,,,,5,1954-07-04 -895,35,651,131,32.0,15,,17,0.0,10,,,,5,1954-07-04 -896,35,498,5,2.0,4,,16,0.0,13,,,,5,1954-07-04 -897,35,478,129,22.0,7,,14,1.0,16,,,,5,1954-07-04 -898,35,501,103,48.0,21,,13,0.0,19,,,,48,1954-07-04 -899,35,663,103,42.0,16,,12,0.0,19,,,,7,1954-07-04 -900,35,670,103,12.0,5,,10,0.0,27,,,,6,1954-07-04 -901,35,627,5,36.0,13,,9,0.0,27,,,,5,1954-07-04 -902,35,632,126,28.0,19,,7,0.0,50,,,,109,1954-07-04 -903,35,554,126,24.0,17,6.0,6,0.0,56,,,,15,1954-07-04 -904,35,633,103,14.0,14,5.0,5,2.0,58,,,,13,1954-07-04 -905,35,669,103,46.0,6,4.0,4,3.0,60,,,,11,1954-07-04 -906,35,626,5,34.0,12,3.0,3,4.0,60,,,,11,1954-07-04 -907,35,579,129,18.0,1,1.0,1,8.0,61,9767900.0,,,1,1954-07-04 -908,35,456,103,44.0,10,,15,0.0,15,,,,86,1954-07-04 -909,35,426,5,4.0,9,,8,0.0,36,,,,5,1954-07-04 -910,36,541,103,6.0,10,,20,0.0,44,,,,3,1954-07-17 -911,36,647,103,32.0,27,,21,0.0,40,,,,5,1954-07-17 -912,36,684,123,22.0,19,,17,0.0,63,,,,69,1954-07-17 -913,36,690,85,30.0,29,,32,0.0,0,,,,54,1954-07-17 -914,36,689,85,27.0,26,,31,0.0,0,,,,54,1954-07-17 -915,36,627,5,15.0,31,,30,0.0,2,,,,5,1954-07-17 -916,36,688,85,30.0,25,,29,0.0,2,,,,5,1954-07-17 -917,36,687,85,21.0,24,,28,0.0,4,,,,44,1954-07-17 -918,36,626,5,14.0,15,,27,0.0,16,,,,5,1954-07-17 -919,36,581,116,20.0,11,,26,0.0,16,,,,5,1954-07-17 -920,36,645,126,18.0,13,,25,0.0,18,,,,3,1954-07-17 -921,36,647,103,31.0,30,,24,0.0,21,,,,5,1954-07-17 -922,36,686,5,12.0,14,,23,0.0,25,,,,5,1954-07-17 -923,36,685,123,24.0,21,,22,0.0,40,,,,3,1954-07-17 -924,36,633,103,32.0,27,,21,0.0,40,,,,5,1954-07-17 -925,36,669,103,6.0,10,,20,0.0,44,,,,3,1954-07-17 -926,36,475,103,7.0,4,,16,0.0,80,,,,109,1954-07-17 -927,36,456,103,5.0,7,,19,0.0,53,,,,7,1954-07-17 -928,36,554,126,17.0,5,,18,0.0,54,,,,22,1954-07-17 -929,36,547,85,28.0,20,15.0,15,0.0,44,,,,125,1954-07-17 -930,36,665,123,23.0,22,13.0,13,0.0,82,,,,18,1954-07-17 -931,36,501,103,3.0,16,12.0,12,0.0,83,,,,17,1954-07-17 -932,36,682,123,25.0,17,11.0,11,0.0,84,,,,16,1954-07-17 -933,36,619,85,29.0,18,10.0,10,0.0,85,,,,15,1954-07-17 -934,36,683,123,26.0,23,14.0,14,0.0,78,,,,55,1954-07-17 -935,36,663,103,8.0,9,8.0,8,0.0,86,,,,14,1954-07-17 -936,36,428,126,19.0,12,9.0,9,0.0,86,,,,14,1954-07-17 -937,36,643,103,4.0,32,6.0,6,0.0,87,,,,13,1954-07-17 -938,36,426,5,10.0,8,5.0,5,2.0,87,,,,13,1954-07-17 -939,36,579,129,1.0,1,4.0,4,3.14,89,,,,11,1954-07-17 -940,36,670,103,33.0,28,3.0,3,4.14,89,,,,11,1954-07-17 -941,36,578,5,11.0,3,2.0,2,6.14,90,,,,1,1954-07-17 -942,36,498,5,9.0,2,1.0,1,8.14,90,10574000.0,,,1,1954-07-17 -943,36,648,129,2.0,6,7.0,7,0.0,87,,,,13,1954-07-17 -944,37,579,129,18.0,1,1.0,1,8.0,22,13545800.0,,,1,1954-08-01 -945,37,498,5,1.0,5,2.0,2,3.0,22,13642300.0,,,1,1954-08-01 -946,37,426,5,2.0,7,3.0,3,4.0,22,13854400.0,,,1,1954-08-01 -947,37,670,103,6.0,8,,21,0.0,0,,,,3,1954-08-01 -948,37,428,126,12.0,20,,20,0.0,0,,,,22,1954-08-01 -949,37,648,129,19.0,23,4.0,4,4.0,22,13912300.0,,,1,1954-08-01 -950,37,475,103,16.0,3,,19,0.0,1,,,,67,1954-08-01 -951,37,643,103,8.0,17,,18,0.0,2,,,,95,1954-08-01 -952,37,578,5,3.0,3,,17,0.0,3,,,,7,1954-08-01 -953,37,632,126,10.0,4,,16,0.0,4,,,,36,1954-08-01 -954,37,478,129,20.0,4,,15,0.0,7,,,,95,1954-08-01 -955,37,692,138,22.0,21,,14,0.0,8,,,,5,1954-08-01 -956,37,645,126,11.0,16,,13,0.0,8,,,,36,1954-08-01 -957,37,578,5,1.0,5,2.0,2,3.0,22,13642300.0,,,1,1954-08-01 -958,37,691,129,21.0,13,,12,0.0,10,,,,20,1954-08-01 -959,37,663,103,17.0,22,,23,0.0,0,,,,54,1954-08-01 -960,37,554,126,9.0,9,10.0,10,0.0,20,,,,12,1954-08-01 -961,37,626,5,24.0,12,9.0,9,0.0,20,,,,12,1954-08-01 -962,37,627,5,25.0,11,8.0,8,0.0,21,,,,11,1954-08-01 -963,37,501,103,15.0,14,7.0,7,0.0,21,,,,11,1954-08-01 -964,37,641,5,4.0,13,6.0,6,0.0,21,,,,11,1954-08-01 -965,37,644,103,7.0,15,5.0,5,2.0,22,14076300.0,,,1,1954-08-01 -966,37,633,103,5.0,10,,22,0.0,0,,,,54,1954-08-01 -967,37,669,103,14.0,19,,11,0.0,18,,,,38,1954-08-01 -968,38,626,5,24.0,0,,17,0.0,0,,,,3,1954-08-22 -969,38,648,129,8.0,5,,9,0.0,38,,,,69,1954-08-22 -970,38,693,126,14.0,15,,14,0.0,10,,,,7,1954-08-22 -971,38,475,103,32.0,3,,13,0.0,21,,,,94,1954-08-22 -972,38,501,103,34.0,13,,12,0.0,23,,,,94,1954-08-22 -973,38,578,5,22.0,6,,11,0.0,30,,,,44,1954-08-22 -974,38,426,5,26.0,4,,10,0.0,33,,,,5,1954-08-22 -975,38,645,126,12.0,10,,16,0.0,0,,,,48,1954-08-22 -976,38,554,126,10.0,14,,15,0.0,8,,,,8,1954-08-22 -977,38,680,5,2.0,16,8.0,8,0.0,58,,,,18,1954-08-22 -978,38,663,103,18.0,8,6.0,6,0.0,64,,,,12,1954-08-22 -979,38,644,103,28.0,9,5.0,5,2.0,64,,,,12,1954-08-22 -980,38,643,103,30.0,12,4.0,4,3.0,64,,,,12,1954-08-22 -981,38,478,129,6.0,7,3.0,3,4.0,65,,,,11,1954-08-22 -982,38,498,5,20.0,1,2.0,2,6.0,66,10892300.0,,,1,1954-08-22 -983,38,579,129,4.0,2,1.0,1,9.0,66,10834500.0,,,1,1954-08-22 -984,38,620,5,24.0,11,7.0,7,0.0,61,,,,15,1954-08-22 -985,39,620,5,38.0,13,3.0,3,2.0,78,,,,12,1954-09-05 -986,39,579,129,16.0,1,1.0,1,8.0,80,10067900.0,,,1,1954-09-05 -987,39,578,5,40.0,7,2.0,2,6.0,79,,,,11,1954-09-05 -988,39,478,129,12.0,8,4.0,4,3.0,77,,,,13,1954-09-05 -989,39,693,126,42.0,18,6.0,6,0.0,75,,,,15,1954-09-05 -990,39,581,116,10.0,16,7.0,7,0.0,75,,,,15,1954-09-05 -991,39,426,5,30.0,11,5.0,5,2.0,75,,,,15,1954-09-05 -992,39,694,103,20.0,21,,21,0.0,0,,,,81,1954-09-05 -993,39,554,126,44.0,12,,20,0.0,2,,,,5,1954-09-05 -994,39,645,126,46.0,17,,19,0.0,13,,,,7,1954-09-05 -995,39,626,5,6.0,15,,18,0.0,16,,,,5,1954-09-05 -996,39,498,5,32.0,5,,17,0.0,16,,,,6,1954-09-05 -997,39,577,103,20.0,14,,16,0.0,32,,,,7,1954-09-05 -998,39,498,5,38.0,13,3.0,3,3.0,78,,,,12,1954-09-05 -999,39,648,129,14.0,4,,14,0.0,36,,,,3,1954-09-05 -1000,39,643,103,24.0,10,,15,0.0,34,,,,22,1954-09-05 -1001,39,644,103,18.0,9,9.0,9,0.0,74,,,,16,1954-09-05 -1002,39,475,103,28.0,3,10.0,10,0.0,71,,,,19,1954-09-05 -1003,39,627,103,26.0,20,8.0,8,0.0,74,,,,16,1954-09-05 -1004,39,647,5,34.0,2,,12,0.0,48,,,,5,1954-09-05 -1005,39,633,103,22.0,6,,13,0.0,42,,,,8,1954-09-05 -1006,39,672,103,8.0,19,11.0,11,0.0,70,,,,88,1954-09-05 -1007,40,638,103,22.0,21,,11,0.0,57,,,,5,1954-10-24 -1008,40,650,126,48.0,16,,14,0.0,37,,,,5,1954-10-24 -1009,40,581,116,42.0,0,,22,0.0,0,,,,3,1954-10-24 -1010,40,626,5,20.0,17,,21,0.0,2,,,,5,1954-10-24 -1011,40,633,130,36.0,5,,20,0.0,2,,,,23,1954-10-24 -1012,40,647,130,34.0,1,,19,1.0,10,,,,8,1954-10-24 -1013,40,554,126,46.0,18,,17,0.0,17,,,,23,1954-10-24 -1014,40,475,103,8.0,6,,16,0.0,20,,,,94,1954-10-24 -1015,40,501,103,24.0,4,,15,0.0,29,,,,7,1954-10-24 -1016,40,426,5,40.0,8,,13,0.0,47,,,,6,1954-10-24 -1017,40,680,5,30.0,19,,18,0.0,16,,,,5,1954-10-24 -1018,40,640,103,22.0,21,,11,0.0,57,,,,5,1954-10-24 -1019,40,478,129,6.0,9,,12,0.0,50,,,,98,1954-10-24 -1020,40,577,103,14.0,7,2.0,2,6.0,80,11705300.0,,,1,1954-10-24 -1021,40,579,129,2.0,2,3.0,3,4.0,79,,,,11,1954-10-24 -1022,40,643,103,10.0,11,4.0,4,3.0,79,,,,11,1954-10-24 -1023,40,648,129,4.0,12,5.0,5,2.0,79,,,,14,1954-10-24 -1024,40,578,5,38.0,3,1.0,1,8.0,80,11632100.0,,,1,1954-10-24 -1025,40,627,103,26.0,20,7.0,7,0.0,74,,,,16,1954-10-24 -1026,40,663,103,28.0,14,8.0,8,0.0,74,,,,16,1954-10-24 -1027,40,669,103,18.0,15,9.0,9,0.0,68,,,,55,1954-10-24 -1028,40,644,103,12.0,10,,10,0.0,58,,,,23,1954-10-24 -1029,40,580,103,16.0,13,6.0,6,0.0,76,,,,14,1954-10-24 -1030,41,554,103,16.0,4,,17,0.0,2,,,,3,1955-01-16 -1031,41,579,129,2.0,3,1.0,1,9.0,96,10838600.0,,,1,1955-01-16 -1032,41,498,5,12.0,1,2.0,2,2.0,96,10928200.0,,,1,1955-01-16 -1033,41,642,5,10.0,5,3.0,3,1.33,94,,,,12,1955-01-16 -1034,41,478,129,8.0,10,4.0,4,1.0,94,,,,12,1955-01-16 -1035,41,643,103,18.0,16,5.0,5,2.0,91,,,,15,1955-01-16 -1036,41,501,103,28.0,7,6.0,6,0.0,88,,,,18,1955-01-16 -1037,41,645,103,26.0,20,,9,0.0,54,,,,32,1955-01-16 -1038,41,644,103,20.0,19,,8,0.0,54,,,,5,1955-01-16 -1039,41,646,126,42.0,17,,10,0.0,38,,,,7,1955-01-16 -1040,41,426,5,14.0,14,,11,0.0,36,,,,5,1955-01-16 -1041,41,608,130,36.0,12,,12,0.0,35,,,,3,1955-01-16 -1042,41,475,129,6.0,8,,13,0.0,29,,,,69,1955-01-16 -1043,41,623,103,30.0,21,,14,0.0,22,,,,60,1955-01-16 -1044,41,648,129,4.0,6,,18,0.0,2,,,,3,1955-01-16 -1045,41,577,103,22.0,18,7.0,7,0.0,83,,,,53,1955-01-16 -1046,41,633,130,34.0,11,,19,0.0,2,,,,95,1955-01-16 -1047,41,620,5,10.0,5,3.0,3,1.33,94,,,,12,1955-01-16 -1048,41,496,103,24.0,13,,21,0.0,1,,,,3,1955-01-16 -1049,41,642,5,12.0,1,2.0,2,2.0,96,10928200.0,,,1,1955-01-16 -1050,41,426,5,12.0,1,2.0,2,2.0,96,10928200.0,,,1,1955-01-16 -1051,41,426,5,10.0,5,3.0,3,1.33,94,,,,12,1955-01-16 -1052,41,648,129,8.0,10,4.0,4,1.0,94,,,,12,1955-01-16 -1053,41,625,126,38.0,15,,16,0.0,7,,,,7,1955-01-16 -1054,41,475,129,8.0,10,4.0,4,1.0,94,,,,12,1955-01-16 -1055,41,554,103,28.0,7,6.0,6,0.0,88,,,,18,1955-01-16 -1056,41,644,103,22.0,18,7.0,7,0.0,83,,,,53,1955-01-16 -1057,41,501,103,22.0,18,7.0,7,0.0,83,,,,53,1955-01-16 -1058,41,554,103,20.0,19,,8,0.0,54,,,,5,1955-01-16 -1059,41,577,103,20.0,19,,8,0.0,54,,,,5,1955-01-16 -1060,41,501,103,26.0,20,,9,0.0,54,,,,32,1955-01-16 -1061,41,496,103,26.0,20,,9,0.0,54,,,,32,1955-01-16 -1062,41,633,130,36.0,12,,12,0.0,35,,,,3,1955-01-16 -1063,41,649,126,40.0,9,,20,0.0,1,,,,3,1955-01-16 -1064,41,647,130,32.0,2,,15,0.0,21,,,,3,1955-01-16 -1065,42,607,103,34.0,5,3.0,3,2.0,99,,,,11,1955-05-22 -1066,42,554,103,40.0,11,,10,0.0,86,,,,20,1955-05-22 -1067,42,577,103,38.0,8,,20,0.0,7,,,,7,1955-05-22 -1068,42,627,103,14.0,17,,19,0.0,8,,,,95,1955-05-22 -1069,42,478,129,4.0,0,,23,0.0,0,,,,81,1955-05-22 -1070,42,652,131,24.0,0,,22,0.0,0,,,,81,1955-05-22 -1071,42,651,103,22.0,0,,21,0.0,0,,,,81,1955-05-22 -1072,42,633,130,28.0,7,5.0,5,2.0,99,,,,11,1955-05-22 -1073,42,589,130,32.0,19,6.0,6,0.0,95,,,,15,1955-05-22 -1074,42,650,126,10.0,20,7.0,7,0.0,91,,,,19,1955-05-22 -1075,42,641,5,48.0,15,8.0,8,0.0,86,,,,111,1955-05-22 -1076,42,632,5,48.0,15,8.0,8,0.0,86,,,,111,1955-05-22 -1077,42,607,103,40.0,11,,10,0.0,86,,,,20,1955-05-22 -1078,42,647,130,26.0,2,,11,0.0,80,,,,3,1955-05-22 -1079,42,475,129,16.0,3,9.0,9,0.0,81,,,,124,1955-05-22 -1080,42,501,5,46.0,18,,12,0.0,68,,,,5,1955-05-22 -1081,42,426,5,44.0,9,1.0,1,8.0,100,10689800.0,,,1,1955-05-22 -1082,42,608,130,30.0,4,2.0,2,6.0,100,10710000.0,,,1,1955-05-22 -1083,42,554,103,34.0,5,3.0,3,2.0,99,,,,11,1955-05-22 -1084,42,642,5,42.0,14,4.0,4,3.0,99,,,,11,1955-05-22 -1085,42,609,129,4.0,10,,17,0.0,24,,,,5,1955-05-22 -1086,42,578,116,18.0,12,,18,0.0,22,,,,37,1955-05-22 -1087,42,579,129,2.0,1,,15,1.0,49,,,,7,1955-05-22 -1088,42,625,126,12.0,16,,14,0.0,63,,,,7,1955-05-22 -1089,42,643,103,36.0,6,,13,0.0,64,,,,7,1955-05-22 -1090,42,626,126,8.0,13,,16,0.0,38,,,,6,1955-05-22 -1091,43,555,111,10.0,2,2.0,2,3.0,200,14203090.0,,,1,1955-05-30 -1092,43,519,111,77.0,7,5.0,5,1.0,200,14356700.0,,,1,1955-05-30 -1093,43,654,111,77.0,7,5.0,5,1.0,200,14356700.0,,,1,1955-05-30 -1094,43,628,111,6.0,14,1.0,1,8.0,200,14039530.0,,,1,1955-05-30 -1095,43,529,111,10.0,2,2.0,2,3.0,200,14203090.0,,,1,1955-05-30 -1096,43,653,111,15.0,10,3.0,3,4.0,200,14251890.0,,,1,1955-05-30 -1097,43,512,112,44.0,33,4.0,4,3.0,200,14258440.0,,,1,1955-05-30 -1098,43,612,111,19.0,8,6.0,6,0.0,200,14397470.0,,,1,1955-05-30 -1099,43,559,111,89.0,12,10.0,10,0.0,200,14506070.0,,,1,1955-05-30 -1100,43,597,111,29.0,19,8.0,8,0.0,200,14441130.0,,,1,1955-05-30 -1101,43,592,134,5.0,15,,33,0.0,10,,,,5,1955-05-30 -1102,43,615,111,14.0,4,,32,0.0,39,,,,20,1955-05-30 -1103,43,659,127,23.0,1,,31,0.0,40,,,,44,1955-05-30 -1104,43,596,111,68.0,29,,30,0.0,53,,,,31,1955-05-30 -1105,43,533,111,39.0,26,,29,0.0,53,,,,3,1955-05-30 -1106,43,448,112,27.0,30,,28,0.0,53,,,,3,1955-05-30 -1107,43,558,111,42.0,22,,27,0.0,54,,,,3,1955-05-30 -1108,43,658,111,3.0,3,,26,0.0,54,,,,121,1955-05-30 -1109,43,657,111,4.0,5,,25,1.0,56,,,,3,1955-05-30 -1110,43,525,112,1.0,11,,24,0.0,90,,,,48,1955-05-30 -1111,43,561,111,49.0,23,,23,0.0,111,,,,5,1955-05-30 -1112,43,538,111,71.0,16,7.0,7,0.0,200,14423770.0,,,1,1955-05-30 -1113,43,532,133,37.0,13,,22,0.0,112,,,,80,1955-05-30 -1114,43,631,132,31.0,28,,20,0.0,120,,,,48,1955-05-30 -1115,43,611,111,8.0,6,,19,0.0,134,,,,7,1955-05-30 -1116,43,523,109,81.0,31,,18,0.0,142,,,,7,1955-05-30 -1117,43,656,111,99.0,24,,17,0.0,168,,,,5,1955-05-30 -1118,43,655,111,22.0,9,,16,0.0,170,,,,3,1955-05-30 -1119,43,528,107,12.0,21,,15,0.0,178,,,,7,1955-05-30 -1120,43,509,106,33.0,20,14.0,14,0.0,191,,,,19,1955-05-30 -1121,43,513,109,83.0,32,13.0,13,0.0,196,,,,14,1955-05-30 -1122,43,563,111,41.0,25,12.0,12,0.0,196,,,,14,1955-05-30 -1123,43,518,112,98.0,18,11.0,11,0.0,197,,,,13,1955-05-30 -1124,43,556,111,48.0,17,9.0,9,0.0,200,14469340.0,,,1,1955-05-30 -1125,43,593,111,16.0,27,,21,0.0,119,,,,121,1955-05-30 -1126,44,632,5,6.0,8,4.0,4,3.0,36,9774500.0,,,1,1955-06-05 -1127,44,627,103,28.0,12,9.0,9,0.0,33,,,,13,1955-06-05 -1128,44,501,5,4.0,0,,16,0.0,0,,,,54,1955-06-05 -1129,44,642,5,2.0,4,3.0,3,4.0,36,9669500.0,,,1,1955-06-05 -1130,44,475,129,14.0,3,2.0,2,6.0,36,9577100.0,,,1,1955-06-05 -1131,44,579,129,10.0,2,1.0,1,9.0,36,9569000.0,,,1,1955-06-05 -1132,44,643,103,24.0,13,5.0,5,1.0,35,,,,11,1955-06-05 -1133,44,426,5,4.0,10,6.0,6,0.0,35,,,,11,1955-06-05 -1134,44,577,103,22.0,7,7.0,7,0.0,34,,,,12,1955-06-05 -1135,44,607,103,26.0,11,8.0,8,0.0,33,,,,13,1955-06-05 -1136,44,648,129,12.0,6,,10,0.0,21,,,,44,1955-06-05 -1137,44,608,130,30.0,1,,11,0.0,16,,,,6,1955-06-05 -1138,44,578,116,40.0,9,,12,0.0,8,,,,6,1955-06-05 -1139,44,554,103,20.0,5,,13,0.0,3,,,,20,1955-06-05 -1140,44,660,103,38.0,0,,14,0.0,0,,,,54,1955-06-05 -1141,44,641,5,48.0,0,,15,0.0,0,,,,54,1955-06-05 -1142,44,554,103,24.0,13,5.0,5,1.0,35,,,,11,1955-06-05 -1143,45,578,5,2.0,5,7.0,7,0.0,95,,,,15,1955-06-19 -1144,45,627,103,28.0,13,9.0,9,0.0,92,,,,18,1955-06-19 -1145,45,650,126,24.0,12,10.0,10,0.0,90,,,,88,1955-06-19 -1146,45,660,5,30.0,16,11.0,11,0.0,88,,,,55,1955-06-19 -1147,45,426,5,4.0,8,,12,0.0,65,,,,6,1955-06-19 -1148,45,626,126,20.0,11,,13,0.0,44,,,,7,1955-06-19 -1149,45,579,129,8.0,1,1.0,1,8.0,100,10463800.0,,,1,1955-06-19 -1150,45,547,103,32.0,15,,14,0.0,23,,,,20,1955-06-19 -1151,45,661,103,26.0,10,,16,0.0,2,,,,67,1955-06-19 -1152,45,554,103,14.0,6,6.0,6,0.0,97,,,,13,1955-06-19 -1153,45,608,5,6.0,9,5.0,5,2.0,97,,,,13,1955-06-19 -1154,45,643,103,16.0,7,4.0,4,4.0,99,,,,11,1955-06-19 -1155,45,577,103,18.0,4,3.0,3,4.0,100,10520900.0,,,1,1955-06-19 -1156,45,475,129,10.0,2,2.0,2,6.0,100,10464100.0,,,1,1955-06-19 -1157,45,648,129,12.0,3,,15,0.0,21,,,,20,1955-06-19 -1158,45,624,126,22.0,14,8.0,8,0.0,92,,,,18,1955-06-19 -1159,46,608,5,16.0,12,6.0,6,0.0,87,,,,13,1955-07-16 -1160,46,608,5,20.0,10,,21,0.0,16,,,,7,1955-07-16 -1161,46,626,126,22.0,11,,24,0.0,4,,,,7,1955-07-16 -1162,46,486,123,34.0,21,,25,0.0,0,,,,5,1955-07-16 -1163,46,501,116,28.0,15,9.0,9,0.0,72,,,,114,1955-07-16 -1164,46,554,103,2.0,3,,23,0.0,9,,,,44,1955-07-16 -1165,46,661,123,36.0,14,,19,0.0,19,,,,7,1955-07-16 -1166,46,609,103,8.0,8,,22,0.0,9,,,,6,1955-07-16 -1167,46,581,103,42.0,24,,14,0.0,28,,,,8,1955-07-16 -1168,46,664,123,32.0,17,,13,0.0,30,,,,51,1955-07-16 -1169,46,475,129,12.0,1,1.0,1,9.0,90,11241200.0,,,1,1955-07-16 -1170,46,579,129,10.0,2,2.0,2,6.0,90,11241400.0,,,1,1955-07-16 -1171,46,648,129,14.0,4,3.0,3,4.0,90,11313000.0,,,1,1955-07-16 -1172,46,641,129,50.0,5,4.0,4,3.0,89,,,,11,1955-07-16 -1173,46,577,103,4.0,9,5.0,5,2.0,89,,,,11,1955-07-16 -1174,46,578,5,16.0,12,6.0,6,0.0,87,,,,13,1955-07-16 -1175,46,662,126,26.0,23,7.0,7,0.0,81,,,,19,1955-07-16 -1176,46,663,116,28.0,15,9.0,9,0.0,72,,,,114,1955-07-16 -1177,46,651,103,46.0,16,8.0,8,0.0,79,,,,45,1955-07-16 -1178,46,624,126,24.0,18,,15,0.0,26,,,,51,1955-07-16 -1179,46,456,103,44.0,20,,16,0.0,23,,,,6,1955-07-16 -1180,46,547,103,48.0,22,,17,0.0,22,,,,23,1955-07-16 -1181,46,501,116,30.0,7,,18,0.0,20,,,,37,1955-07-16 -1182,46,666,123,36.0,14,,19,0.0,19,,,,7,1955-07-16 -1183,46,665,123,38.0,19,,20,0.0,18,,,,23,1955-07-16 -1184,46,643,103,6.0,6,,11,0.0,47,,,,5,1955-07-16 -1185,46,355,85,40.0,25,,12,0.0,30,,,,5,1955-07-16 -1186,46,426,5,18.0,13,,10,0.0,59,,,,25,1955-07-16 -1187,47,501,116,42.0,13,,18,0.0,7,,,,22,1955-09-11 -1188,47,668,126,24.0,22,,19,0.0,7,,,,5,1955-09-11 -1189,47,581,103,32.0,11,,17,0.0,22,,,,22,1955-09-11 -1190,47,663,116,44.0,17,,20,0.0,0,,,,98,1955-09-11 -1191,47,650,126,26.0,19,,15,0.0,26,,,,5,1955-09-11 -1192,47,475,129,16.0,2,,14,1.0,27,,,,5,1955-09-11 -1193,47,577,103,30.0,10,,12,0.0,31,,,,6,1955-09-11 -1194,47,648,129,20.0,3,,11,0.0,32,,,,6,1955-09-11 -1195,47,578,5,6.0,14,10.0,10,0.0,38,,,,6,1955-09-11 -1196,47,667,103,40.0,20,9.0,9,0.0,46,,,,14,1955-09-11 -1197,47,426,5,8.0,15,8.0,8,0.0,47,,,,13,1955-09-11 -1198,47,643,103,28.0,7,7.0,7,0.0,48,,,,12,1955-09-11 -1199,47,620,5,12.0,12,6.0,6,0.0,49,,,,11,1955-09-11 -1200,47,496,103,34.0,16,5.0,5,2.0,49,,,,11,1955-09-11 -1201,47,554,103,36.0,6,4.0,4,3.0,50,8941900.0,,,1,1955-09-11 -1202,47,608,5,4.0,4,3.0,3,4.0,50,8750600.0,,,1,1955-09-11 -1203,47,641,129,14.0,9,2.0,2,6.0,50,8705100.0,,,1,1955-09-11 -1204,47,579,129,18.0,1,1.0,1,8.0,50,8704400.0,,,1,1955-09-11 -1205,47,624,126,22.0,18,,16,0.0,23,,,,69,1955-09-11 -1206,47,547,103,38.0,21,,13,0.0,31,,,,22,1955-09-11 -1207,47,642,5,2.0,5,,21,0.0,0,,,,54,1955-09-11 -1208,47,586,135,46.0,0,,23,0.0,0,,,,54,1955-09-11 -1209,47,633,5,10.0,8,,22,0.0,0,,,,54,1955-09-11 -1210,48,608,5,32.0,2,,11,0.0,40,,,,6,1956-01-22 -1211,48,579,5,30.0,1,,13,0.0,22,,,,48,1956-01-22 -1212,48,498,103,12.0,5,,12,0.0,24,,,,5,1956-01-22 -1213,48,496,103,6.0,6,,10,0.0,42,,,,86,1956-01-22 -1214,48,586,103,8.0,12,,9,0.0,57,,,,3,1956-01-22 -1215,48,581,5,36.0,9,,8,0.0,58,,,,3,1956-01-22 -1216,48,475,103,2.0,7,,7,0.0,81,,,,5,1956-01-22 -1217,48,623,103,16.0,13,6.0,6,0.0,88,,,,88,1956-01-22 -1218,48,482,5,38.0,10,5.0,5,2.0,91,,,,17,1956-01-22 -1219,48,622,103,10.0,11,4.0,4,1.5,92,,,,16,1956-01-22 -1220,48,554,103,4.0,4,2.0,2,6.0,98,10828100.0,,,1,1956-01-22 -1221,48,578,103,14.0,8,3.0,3,4.0,96,,,,12,1956-01-22 -1222,48,579,5,34.0,3,1.0,1,5.0,98,10803700.0,,,1,1956-01-22 -1223,48,583,103,10.0,11,4.0,4,1.5,92,,,,16,1956-01-22 -1224,48,806,103,16.0,13,6.0,6,0.0,88,,,,88,1956-01-22 -1225,48,577,5,34.0,3,1.0,1,4.0,98,10803700.0,,,1,1956-01-22 -1226,49,547,103,18.0,16,8.0,8,0.0,85,,,,112,1956-05-13 -1227,49,626,126,2.0,12,,9,0.0,90,,,,3,1956-05-13 -1228,49,627,103,8.0,15,,10,0.0,72,,,,5,1956-05-13 -1229,49,589,103,34.0,0,,18,0.0,0,,,,5,1956-05-13 -1230,49,479,64,12.0,0,,17,0.0,0,,,,5,1956-05-13 -1231,49,578,64,10.0,0,,16,0.0,0,,,,5,1956-05-13 -1232,49,483,5,36.0,0,,15,0.0,0,,,,81,1956-05-13 -1233,49,577,5,24.0,8,,14,0.0,2,,,,3,1956-05-13 -1234,49,501,116,16.0,5,,13,0.0,2,,,,3,1956-05-13 -1235,49,426,116,14.0,6,,12,0.0,13,,,,25,1956-05-13 -1236,49,607,103,32.0,7,7.0,7,0.0,86,,,,111,1956-05-13 -1237,49,608,5,22.0,3,,11,0.0,14,,,,8,1956-05-13 -1238,49,625,126,4.0,11,6.0,6,0.0,88,,,,55,1956-05-13 -1239,49,554,103,30.0,4,3.0,3,4.0,99,,,,11,1956-05-13 -1240,49,579,5,20.0,1,4.0,4,1.5,99,,,,11,1956-05-13 -1241,49,581,5,26.0,9,2.0,2,3.0,100,10839000.0,,,1,1956-05-13 -1242,49,475,103,28.0,2,1.0,1,8.0,100,10832900.0,,,1,1956-05-13 -1243,49,579,5,26.0,9,2.0,2,4.0,100,10839000.0,,,1,1956-05-13 -1244,49,608,5,20.0,1,4.0,4,1.5,99,,,,11,1956-05-13 -1245,49,428,126,4.0,11,6.0,6,0.0,88,,,,55,1956-05-13 -1246,49,624,126,6.0,14,5.0,5,2.0,93,,,,17,1956-05-13 -1247,50,529,111,99.0,5,,22,0.0,160,,,,3,1956-05-30 -1248,50,556,111,48.0,16,,24,0.0,134,,,,3,1956-05-30 -1249,50,594,111,34.0,31,,21,0.0,173,,,,5,1956-05-30 -1250,50,525,112,2.0,19,19.0,19,0.0,185,,,,112,1956-05-30 -1251,50,597,111,7.0,3,18.0,18,0.0,187,,,,53,1956-05-30 -1252,50,630,111,64.0,33,17.0,17,0.0,191,,,,19,1956-05-30 -1253,50,596,111,10.0,14,,23,0.0,160,,,,23,1956-05-30 -1254,50,562,111,54.0,24,,25,0.0,131,,,,5,1956-05-30 -1255,50,509,111,24.0,2,,20,0.0,175,,,,5,1956-05-30 -1256,50,612,111,5.0,9,,27,0.0,90,,,,44,1956-05-30 -1257,50,538,111,12.0,27,,28,0.0,74,,,,3,1956-05-30 -1258,50,561,111,49.0,17,,29,0.0,49,,,,3,1956-05-30 -1259,50,595,112,41.0,29,16.0,16,0.0,194,,,,16,1956-05-30 -1260,50,533,111,15.0,12,,30,0.0,35,,,,44,1956-05-30 -1261,50,526,111,53.0,11,,31,0.0,22,,,,20,1956-05-30 -1262,50,512,112,88.0,18,,32,0.0,22,,,,20,1956-05-30 -1263,50,555,111,29.0,8,,33,1.0,21,,,,3,1956-05-30 -1264,50,631,111,89.0,20,,26,0.0,94,,,,7,1956-05-30 -1265,50,513,112,81.0,32,15.0,15,0.0,195,,,,15,1956-05-30 -1266,50,514,111,14.0,23,7.0,7,0.0,200,14394470.0,,,1,1956-05-30 -1267,50,516,111,57.0,25,13.0,13,0.0,196,,,,14,1956-05-30 -1268,50,558,111,55.0,28,14.0,14,0.0,195,,,,15,1956-05-30 -1269,50,532,111,10.0,14,,23,0.0,160,,,,23,1956-05-30 -1270,50,559,105,8.0,1,1.0,1,8.0,200,14008840.0,,,1,1956-05-30 -1271,50,611,111,4.0,13,2.0,2,6.0,200,14029290.0,,,1,1956-05-30 -1272,50,593,111,98.0,6,4.0,4,3.0,200,14214530.0,,,1,1956-05-30 -1273,50,537,111,73.0,4,5.0,5,2.0,200,14270650.0,,,1,1956-05-30 -1274,50,628,112,1.0,10,6.0,6,0.0,200,14343890.0,,,1,1956-05-30 -1275,50,528,107,16.0,26,3.0,3,4.0,200,14099070.0,,,1,1956-05-30 -1276,50,448,111,19.0,15,8.0,8,0.0,200,14401150.0,,,1,1956-05-30 -1277,50,592,108,26.0,21,9.0,9,0.0,200,14407150.0,,,1,1956-05-30 -1278,50,629,127,27.0,30,10.0,10,0.0,199,,,,11,1956-05-30 -1279,50,520,112,82.0,22,11.0,11,0.0,196,,,,14,1956-05-30 -1280,50,615,111,42.0,7,12.0,12,0.0,196,,,,14,1956-05-30 -1281,51,428,5,20.0,16,6.0,6,0.0,33,,,,13,1956-06-03 -1282,51,634,123,28.0,12,,13,0.0,10,,,,5,1956-06-03 -1283,51,475,103,30.0,2,,11,0.0,10,,,,36,1956-06-03 -1284,51,426,116,12.0,7,,10,0.0,11,,,,69,1956-06-03 -1285,51,579,5,2.0,1,,9,0.0,23,,,,7,1956-06-03 -1286,51,627,103,24.0,10,8.0,8,0.0,33,,,,13,1956-06-03 -1287,51,554,103,32.0,4,7.0,7,0.0,33,,,,13,1956-06-03 -1288,51,608,5,4.0,5,,12,0.0,10,,,,7,1956-06-03 -1289,51,633,103,22.0,11,5.0,5,2.0,34,,,,12,1956-06-03 -1290,51,580,103,36.0,13,,15,0.0,0,,,,3,1956-06-03 -1291,51,607,103,34.0,9,3.0,3,2.0,36,9796900.0,,,1,1956-06-03 -1292,51,632,5,6.0,8,2.0,2,6.0,36,9711600.0,,,1,1956-06-03 -1293,51,581,5,8.0,3,1.0,1,8.0,36,9600300.0,,,1,1956-06-03 -1294,51,547,103,26.0,15,,14,0.0,2,,,,6,1956-06-03 -1295,51,475,103,34.0,9,3.0,3,3.0,36,9796900.0,,,1,1956-06-03 -1296,51,501,116,10.0,6,4.0,4,3.0,35,,,,11,1956-06-03 -1297,52,482,5,44.0,11,,14,0.0,38,,,,8,1956-07-01 -1298,52,609,103,42.0,20,,12,0.0,41,,,,5,1956-07-01 -1299,52,428,126,34.0,19,11.0,11,0.0,55,,,,16,1956-07-01 -1300,52,578,116,24.0,6,10.0,10,0.0,56,,,,15,1956-07-01 -1301,52,624,103,8.0,16,,13,0.0,40,,,,5,1956-07-01 -1302,52,635,116,26.0,5,,20,0.0,0,,,,3,1956-07-01 -1303,52,475,103,2.0,8,,18,0.0,12,,,,6,1956-07-01 -1304,52,426,128,28.0,18,,17,0.0,18,,,,37,1956-07-01 -1305,52,626,126,30.0,15,9.0,9,0.0,56,,,,15,1956-07-01 -1306,52,633,103,38.0,10,,15,0.0,23,,,,23,1956-07-01 -1307,52,501,116,22.0,4,,19,0.0,5,,,,5,1956-07-01 -1308,52,624,126,32.0,14,8.0,8,0.0,57,,,,14,1956-07-01 -1309,52,606,5,16.0,9,,16,0.0,20,,,,6,1956-07-01 -1310,52,627,103,36.0,12,6.0,6,0.0,58,,,,13,1956-07-01 -1311,52,607,103,6.0,13,5.0,5,1.0,59,,,,12,1956-07-01 -1312,52,579,5,10.0,1,4.0,4,4.0,61,9358500.0,,,1,1956-07-01 -1313,52,554,103,4.0,7,3.0,3,4.0,61,9353300.0,,,1,1956-07-01 -1314,52,608,5,12.0,2,2.0,2,6.0,61,9263700.0,,,1,1956-07-01 -1315,52,581,5,14.0,3,1.0,1,8.0,61,9263400.0,,,1,1956-07-01 -1316,52,475,103,6.0,13,5.0,5,1.0,59,,,,12,1956-07-01 -1317,52,501,116,24.0,6,10.0,10,0.0,56,,,,15,1956-07-01 -1318,52,580,103,40.0,17,7.0,7,0.0,57,,,,14,1956-07-01 -1319,53,475,103,7.0,1,,12,1.0,94,,,,109,1956-07-14 -1320,53,619,85,26.0,22,11.0,11,0.0,88,,,,53,1956-07-14 -1321,53,608,5,3.0,8,10.0,10,0.0,92,,,,19,1956-07-14 -1322,53,626,126,15.0,18,9.0,9,0.0,94,,,,17,1956-07-14 -1323,53,580,103,10.0,25,8.0,8,0.0,94,,,,17,1956-07-14 -1324,53,607,103,9.0,15,7.0,7,0.0,95,,,,16,1956-07-14 -1325,53,633,103,11.0,19,6.0,6,0.0,96,,,,15,1956-07-14 -1326,53,606,5,4.0,12,2.0,2,3.0,100,,,,11,1956-07-14 -1327,53,486,123,21.0,21,4.0,4,3.0,98,,,,13,1956-07-14 -1328,53,554,103,8.0,13,3.0,3,4.0,99,,,,12,1956-07-14 -1329,53,579,5,1.0,2,1.0,1,8.0,101,10787000.0,,,1,1956-07-14 -1330,53,606,5,3.0,8,10.0,10,0.0,92,,,,19,1956-07-14 -1331,53,581,5,4.0,12,2.0,2,3.0,100,,,,11,1956-07-14 -1332,53,501,116,16.0,5,,13,0.0,87,,,,69,1956-07-14 -1333,53,547,103,31.0,14,5.0,5,2.0,97,,,,14,1956-07-14 -1334,53,636,123,20.0,11,,14,0.0,74,,,,5,1956-07-14 -1335,53,426,116,17.0,16,,15,0.0,74,,,,69,1956-07-14 -1336,53,624,126,14.0,26,,16,0.0,71,,,,109,1956-07-14 -1337,53,541,64,25.0,17,,27,0.0,2,,,,5,1956-07-14 -1338,53,355,103,30.0,28,,26,0.0,3,,,,5,1956-07-14 -1339,53,585,97,32.0,23,,25,0.0,12,,,,80,1956-07-14 -1340,53,637,123,19.0,10,,24,0.0,16,,,,7,1956-07-14 -1341,53,620,103,12.0,24,,23,0.0,21,,,,6,1956-07-14 -1342,53,498,116,18.0,6,,28,0.0,0,,,,7,1956-07-14 -1343,53,627,103,27.0,27,,21,0.0,23,,,,10,1956-07-14 -1344,53,578,64,23.0,3,,20,0.0,24,,,,7,1956-07-14 -1345,53,479,64,24.0,9,,19,0.0,39,,,,3,1956-07-14 -1346,53,456,103,28.0,7,,18,0.0,59,,,,69,1956-07-14 -1347,53,581,5,2.0,4,,17,0.0,64,,,,51,1956-07-14 -1348,53,506,103,29.0,20,,22,0.0,22,,,,5,1956-07-14 -1349,54,581,5,2.0,2,,13,0.0,8,,,,95,1956-08-05 -1350,54,608,5,3.0,3,,14,0.0,5,,,,10,1956-08-05 -1351,54,620,103,8.0,7,,15,0.0,3,,,,38,1956-08-05 -1352,54,547,103,19.0,13,,16,0.0,3,,,,51,1956-08-05 -1353,54,456,103,16.0,9,,17,0.0,2,,,,22,1956-08-05 -1354,54,607,103,8.0,0,,20,0.0,0,,,,54,1956-08-05 -1355,54,483,5,14.0,17,,19,0.0,0,,,,5,1956-08-05 -1356,54,428,126,11.0,0,,21,0.0,0,,,,54,1956-08-05 -1357,54,586,103,18.0,0,,22,0.0,0,,,,54,1956-08-05 -1358,54,577,5,4.0,5,,12,0.0,11,,,,3,1956-08-05 -1359,54,626,126,10.0,15,,18,0.0,0,,,,22,1956-08-05 -1360,54,633,103,18.0,20,,11,0.0,13,,,,5,1956-08-05 -1361,54,501,103,12.0,12,,10,0.0,13,,,,25,1956-08-05 -1362,54,606,5,5.0,10,,9,0.0,14,,,,3,1956-08-05 -1363,54,639,126,11.0,21,,8,0.0,15,,,,5,1956-08-05 -1364,54,638,103,22.0,19,,7,0.0,16,,,,16,1956-08-05 -1365,54,506,103,21.0,11,,6,0.0,20,,,,2,1956-08-05 -1366,54,627,103,15.0,14,5.0,5,2.0,19,,,,13,1956-08-05 -1367,54,580,103,20.0,16,4.0,4,3.0,20,,,,12,1956-08-05 -1368,54,554,103,6.0,8,3.0,3,4.0,22,13582000.0,,,1,1956-08-05 -1369,54,475,103,7.0,4,2.0,2,6.0,22,13170100.0,,,1,1956-08-05 -1370,54,579,5,1.0,1,1.0,1,9.0,22,13123700.0,,,1,1956-08-05 -1371,55,456,103,44.0,14,11.0,11,0.0,41,,,,19,1956-09-02 -1372,55,577,5,28.0,3,,12,0.0,47,,,,38,1956-09-02 -1373,55,620,103,46.0,13,,13,0.0,42,,,,38,1956-09-02 -1374,55,501,116,18.0,10,,14,0.0,32,,,,7,1956-09-02 -1375,55,554,103,32.0,5,,15,0.0,23,,,,121,1956-09-02 -1376,55,506,103,48.0,22,,16,0.0,16,,,,5,1956-09-02 -1377,55,426,116,20.0,11,,17,0.0,13,,,,7,1956-09-02 -1378,55,606,5,30.0,9,,22,0.0,6,,,,27,1956-09-02 -1379,55,608,5,24.0,2,,19,0.0,9,,,,27,1956-09-02 -1380,55,633,103,34.0,8,,20,0.0,7,,,,5,1956-09-02 -1381,55,626,126,10.0,23,,21,0.0,7,,,,83,1956-09-02 -1382,55,579,5,26.0,7,2.0,2,3.0,50,8627000.0,,,1,1956-09-02 -1383,55,476,5,50.0,0,,25,0.0,0,,,,54,1956-09-02 -1384,55,624,126,8.0,21,,24,0.0,3,,,,5,1956-09-02 -1385,55,610,123,2.0,20,,23,0.0,6,,,,22,1956-09-02 -1386,55,641,116,16.0,4,,18,0.0,12,,,,44,1956-09-02 -1387,55,608,5,22.0,1,8.0,8,0.0,46,,,,14,1956-09-02 -1388,55,579,5,22.0,1,8.0,8,0.0,46,,,,14,1956-09-02 -1389,55,346,103,34.0,8,,20,0.0,7,,,,5,1956-09-02 -1390,55,475,103,36.0,6,1.0,1,9.0,50,8621300.0,,,1,1956-09-02 -1391,55,581,5,26.0,7,2.0,2,3.0,50,8627000.0,,,1,1956-09-02 -1392,55,541,123,4.0,26,3.0,3,4.0,49,,,,11,1956-09-02 -1393,55,554,103,46.0,13,,13,0.0,42,,,,38,1956-09-02 -1394,55,486,123,6.0,16,5.0,5,2.0,47,,,,13,1956-09-02 -1395,55,586,103,40.0,15,6.0,6,0.0,47,,,,13,1956-09-02 -1396,55,640,103,14.0,19,7.0,7,0.0,46,,,,14,1956-09-02 -1397,55,609,126,12.0,25,9.0,9,0.0,45,,,,15,1956-09-02 -1398,55,583,103,42.0,17,10.0,10,0.0,42,,,,18,1956-09-02 -1399,55,580,103,38.0,18,4.0,4,3.0,49,,,,11,1956-09-02 -1400,56,498,5,20.0,10,5.0,5,1.0,98,,,,12,1957-01-13 -1401,56,586,103,28.0,14,10.0,10,0.0,90,,,,88,1957-01-13 -1402,56,577,5,12.0,6,,13,0.0,31,,,,8,1957-01-13 -1403,56,476,5,18.0,11,6.0,6,0.0,98,,,,12,1957-01-13 -1404,56,573,5,26.0,12,9.0,9,0.0,91,,,,19,1957-01-13 -1405,56,475,103,4.0,1,8.0,8,1.0,93,,,,17,1957-01-13 -1406,56,346,103,24.0,13,7.0,7,0.0,95,,,,15,1957-01-13 -1407,56,578,5,16.0,7,,12,0.0,35,,,,8,1957-01-13 -1408,56,607,5,18.0,11,6.0,6,0.0,98,,,,12,1957-01-13 -1409,56,501,103,22.0,9,4.0,4,3.0,98,,,,12,1957-01-13 -1410,56,496,103,8.0,8,3.0,3,4.0,99,,,,11,1957-01-13 -1411,56,579,103,2.0,2,1.0,1,8.0,100,10855900.0,,,1,1957-01-13 -1412,56,554,103,6.0,3,2.0,2,6.0,100,10874200.0,,,1,1957-01-13 -1413,56,581,5,10.0,5,,14,0.0,26,,,,8,1957-01-13 -1414,56,581,5,18.0,11,6.0,6,0.0,98,,,,12,1957-01-13 -1415,56,606,5,20.0,10,5.0,5,1.0,98,,,,12,1957-01-13 -1416,56,608,5,14.0,4,,11,0.0,75,,,,36,1957-01-13 -1417,57,541,64,6.0,11,,9,0.0,60,,,,5,1957-05-19 -1418,57,483,103,34.0,14,,8,0.0,64,,,,44,1957-05-19 -1419,57,476,5,24.0,9,,7,0.0,95,,,,5,1957-05-19 -1420,57,355,85,14.0,15,6.0,6,0.0,100,,,,15,1957-05-19 -1421,57,426,5,30.0,6,5.0,5,2.0,100,,,,15,1957-05-19 -1422,57,590,123,10.0,13,4.0,4,3.0,102,,,,13,1957-05-19 -1423,57,417,103,2.0,10,3.0,3,4.0,103,,,,12,1957-05-19 -1424,57,479,116,20.0,4,2.0,2,6.0,105,11438000.0,,,1,1957-05-19 -1425,57,579,103,32.0,1,1.0,1,9.0,105,11412800.0,,,1,1957-05-19 -1426,57,496,103,36.0,7,,10,0.0,51,,,,20,1957-05-19 -1427,57,547,103,22.0,12,,13,0.0,10,,,,3,1957-05-19 -1428,57,501,103,38.0,8,,12,0.0,23,,,,22,1957-05-19 -1429,57,475,116,18.0,3,,15,0.0,4,,,,3,1957-05-19 -1430,57,578,5,28.0,5,,16,0.0,4,,,,3,1957-05-19 -1431,57,456,64,8.0,0,,17,0.0,0,,,,81,1957-05-19 -1432,57,478,103,40.0,0,,18,0.0,0,,,,81,1957-05-19 -1433,57,609,103,4.0,0,,19,0.0,0,,,,81,1957-05-19 -1434,57,586,103,42.0,0,,20,0.0,0,,,,81,1957-05-19 -1435,57,610,85,16.0,0,,21,0.0,0,,,,81,1957-05-19 -1436,57,501,103,34.0,14,,8,0.0,64,,,,44,1957-05-19 -1437,57,578,5,24.0,9,,7,0.0,95,,,,5,1957-05-19 -1438,57,581,5,26.0,2,,14,0.0,4,,,,3,1957-05-19 -1439,57,549,123,12.0,16,,11,0.0,47,,,,95,1957-05-19 -1440,58,529,111,27.0,22,15.0,15,0.0,195,,,,15,1957-05-30 -1441,58,563,112,82.0,25,14.0,14,0.0,196,,,,14,1957-05-30 -1442,58,516,111,95.0,33,13.0,13,0.0,197,,,,13,1957-05-30 -1443,58,512,112,10.0,11,12.0,12,0.0,199,,,,11,1957-05-30 -1444,58,562,111,19.0,19,11.0,11,0.0,200,13750320.0,,,1,1957-05-30 -1445,58,533,111,6.0,5,6.0,6,0.0,200,13549520.0,,,1,1957-05-30 -1446,58,597,111,12.0,1,8.0,8,0.0,200,13607400.0,,,1,1957-05-30 -1447,58,613,111,48.0,28,7.0,7,0.0,200,13559830.0,,,1,1957-05-30 -1448,58,612,111,73.0,12,5.0,5,2.0,200,13468520.0,,,1,1957-05-30 -1449,58,555,111,54.0,10,4.0,4,3.0,200,13451110.0,,,1,1957-05-30 -1450,58,525,112,1.0,15,3.0,3,4.0,200,13408220.0,,,1,1957-05-30 -1451,58,509,106,26.0,32,2.0,2,7.0,200,13295710.0,,,1,1957-05-30 -1452,58,611,106,9.0,13,1.0,1,8.0,200,13274250.0,,,1,1957-05-30 -1453,58,514,107,7.0,16,9.0,9,0.0,200,13651360.0,,,1,1957-05-30 -1454,58,520,108,22.0,14,10.0,10,0.0,200,13704370.0,,,1,1957-05-30 -1455,58,556,111,57.0,29,,28,0.0,53,,,,3,1957-05-30 -1456,58,614,111,92.0,27,,19,0.0,170,,,,20,1957-05-30 -1457,58,528,111,3.0,21,17.0,17,0.0,192,,,,18,1957-05-30 -1458,58,532,111,55.0,26,,32,0.0,0,,,,3,1957-05-30 -1459,58,616,111,23.0,9,,33,0.0,0,,,,3,1957-05-30 -1460,58,592,111,5.0,6,,18,0.0,182,,,,37,1957-05-30 -1461,58,526,105,52.0,3,,31,0.0,13,,,,5,1957-05-30 -1462,58,448,108,8.0,24,,30,0.0,27,,,,101,1957-05-30 -1463,58,596,111,83.0,7,,29,0.0,51,,,,31,1957-05-30 -1464,58,593,111,18.0,17,16.0,16,0.0,195,,,,15,1957-05-30 -1465,58,558,111,16.0,8,,27,0.0,75,,,,3,1957-05-30 -1466,58,560,111,31.0,23,,26,0.0,81,,,,95,1957-05-30 -1467,58,594,111,28.0,31,,20,0.0,138,,,,8,1957-05-30 -1468,58,538,118,89.0,30,,21,0.0,111,,,,3,1957-05-30 -1469,58,615,111,14.0,4,,22,0.0,107,,,,95,1957-05-30 -1470,58,527,112,88.0,2,,23,0.0,105,,,,95,1957-05-30 -1471,58,565,111,77.0,18,,24,0.0,101,,,,3,1957-05-30 -1472,58,513,111,43.0,20,,25,0.0,93,,,,67,1957-05-30 -1473,59,496,103,8.0,9,,8,0.0,30,,,,5,1957-07-07 -1474,59,617,85,24.0,15,7.0,7,0.0,68,,,,19,1957-07-07 -1475,59,554,103,4.0,2,6.0,6,0.0,69,,,,18,1957-07-07 -1476,59,456,116,20.0,6,,10,0.0,25,,,,5,1957-07-07 -1477,59,590,116,18.0,10,,9,0.0,30,,,,38,1957-07-07 -1478,59,581,5,12.0,5,3.0,3,4.0,77,11392400.0,,,1,1957-07-07 -1479,59,577,5,10.0,3,2.0,2,7.0,77,11317200.0,,,1,1957-07-07 -1480,59,579,103,2.0,1,1.0,1,8.0,77,11266400.0,,,1,1957-07-07 -1481,59,355,85,24.0,15,7.0,7,0.0,68,,,,19,1957-07-07 -1482,59,501,103,6.0,4,5.0,5,2.0,70,,,,17,1957-07-07 -1483,59,578,5,14.0,7,4.0,4,3.0,76,,,,11,1957-07-07 -1484,59,541,64,26.0,11,,15,0.0,2,,,,3,1957-07-07 -1485,59,426,5,16.0,8,,12,0.0,23,,,,10,1957-07-07 -1486,59,355,85,22.0,13,,13,0.0,4,,,,3,1957-07-07 -1487,59,547,103,30.0,14,,14,0.0,4,,,,86,1957-07-07 -1488,59,618,64,28.0,12,,11,0.0,24,,,,7,1957-07-07 -1489,60,581,5,16.0,9,4.0,4,0.0,88,,,,12,1957-07-20 -1490,60,475,116,20.0,3,1.0,1,5.0,90,11197800.0,,,1,1957-07-20 -1491,60,547,103,30.0,14,,19,0.0,0,,,,3,1957-07-20 -1492,60,554,103,4.0,2,,10,0.0,69,,,,8,1957-07-20 -1493,60,346,103,28.0,17,,18,0.0,18,,,,6,1957-07-20 -1494,60,501,103,6.0,7,,16,0.0,39,,,,103,1957-07-20 -1495,60,610,64,26.0,12,,15,0.0,44,,,,5,1957-07-20 -1496,60,486,64,24.0,16,,14,0.0,46,,,,5,1957-07-20 -1497,60,579,103,2.0,4,,13,0.0,49,,,,5,1957-07-20 -1498,60,475,116,18.0,1,,12,0.0,51,,,,5,1957-07-20 -1499,60,581,5,12.0,8,,11,0.0,53,,,,47,1957-07-20 -1500,60,496,103,8.0,11,,17,0.0,35,,,,7,1957-07-20 -1501,60,479,116,18.0,1,,12,0.0,51,,,,5,1957-07-20 -1502,60,355,85,34.0,13,,9,0.0,74,,,,8,1957-07-20 -1503,60,549,103,32.0,19,8.0,8,0.0,71,,,,124,1957-07-20 -1504,60,590,116,22.0,6,7.0,7,0.0,82,,,,18,1957-07-20 -1505,60,619,85,38.0,18,6.0,6,0.0,82,,,,18,1957-07-20 -1506,60,456,85,36.0,15,5.0,5,2.0,85,,,,15,1957-07-20 -1507,60,426,5,16.0,9,4.0,4,3.0,88,,,,12,1957-07-20 -1508,60,578,5,10.0,5,3.0,3,4.0,90,11240600.0,,,1,1957-07-20 -1509,60,577,5,14.0,10,2.0,2,6.0,90,11223400.0,,,1,1957-07-20 -1510,60,479,116,20.0,3,1.0,1,4.0,90,11197800.0,,,1,1957-07-20 -1511,61,581,5,7.0,4,3.0,3,4.0,22,12673900.0,,,1,1957-08-04 -1512,61,478,103,17.0,11,,16,0.0,14,,,,83,1957-08-04 -1513,61,459,85,25.0,22,15.0,15,0.0,17,,,,15,1957-08-04 -1514,61,429,93,27.0,20,14.0,14,0.0,20,,,,12,1957-08-04 -1515,61,484,85,28.0,17,13.0,13,0.0,20,,,,12,1957-08-04 -1516,61,430,93,21.0,12,12.0,12,0.0,21,,,,11,1957-08-04 -1517,61,501,103,3.0,6,7.0,7,0.0,22,13045800.0,,,1,1957-08-04 -1518,61,483,103,4.0,13,10.0,10,0.0,21,,,,11,1957-08-04 -1519,61,479,116,11.0,5,9.0,9,0.0,21,,,,11,1957-08-04 -1520,61,417,103,16.0,10,8.0,8,0.0,21,,,,11,1957-08-04 -1521,61,620,93,20.0,15,,17,0.0,13,,,,5,1957-08-04 -1522,61,554,103,2.0,3,6.0,6,0.0,22,12916800.0,,,1,1957-08-04 -1523,61,506,103,15.0,16,11.0,11,0.0,21,,,,11,1957-08-04 -1524,61,456,85,23.0,14,,18,0.0,11,,,,22,1957-08-04 -1525,61,601,85,29.0,24,,23,0.0,3,,,,38,1957-08-04 -1526,61,590,116,12.0,9,,20,0.0,10,,,,6,1957-08-04 -1527,61,355,85,24.0,18,,21,0.0,6,,,,7,1957-08-04 -1528,61,621,85,26.0,23,,22,0.0,4,,,,99,1957-08-04 -1529,61,475,116,10.0,7,5.0,5,2.0,22,12915500.0,,,1,1957-08-04 -1530,61,547,103,19.0,19,,24,0.0,2,,,,109,1957-08-04 -1531,61,578,5,8.0,2,2.0,2,6.0,22,12641900.0,,,1,1957-08-04 -1532,61,579,103,1.0,1,1.0,1,9.0,22,12638300.0,,,1,1957-08-04 -1533,61,580,103,18.0,21,,19,0.0,11,,,,38,1957-08-04 -1534,61,577,5,6.0,8,4.0,4,3.0,22,12855900.0,,,1,1957-08-04 -1535,62,346,103,16.0,9,,11,0.0,7,,,,25,1957-08-18 -1536,62,554,103,4.0,4,,12,0.0,3,,,,44,1957-08-18 -1537,62,456,85,22.0,15,,13,0.0,3,,,,3,1957-08-18 -1538,62,479,116,28.0,6,,14,0.0,1,,,,5,1957-08-18 -1539,62,547,103,18.0,11,,15,0.0,0,,,,3,1957-08-18 -1540,62,586,103,12.0,13,,16,0.0,0,,,,5,1957-08-18 -1541,62,506,103,20.0,14,,10,0.0,9,,,,7,1957-08-18 -1542,62,475,116,26.0,2,1.0,1,9.0,18,10762700.0,,,1,1957-08-18 -1543,62,355,85,24.0,16,7.0,7,0.0,15,,,,13,1957-08-18 -1544,62,483,103,8.0,10,6.0,6,0.0,17,,,,11,1957-08-18 -1545,62,590,116,30.0,8,5.0,5,2.0,17,,,,11,1957-08-18 -1546,62,417,103,14.0,7,4.0,4,3.0,18,11259200.0,,,1,1957-08-18 -1547,62,577,5,34.0,3,,8,0.0,9,,,,44,1957-08-18 -1548,62,580,103,10.0,12,,9,0.0,9,,,,5,1957-08-18 -1549,62,579,103,2.0,1,2.0,2,6.0,18,10956600.0,,,1,1957-08-18 -1550,62,501,103,6.0,5,3.0,3,4.0,18,11169500.0,,,1,1957-08-18 -1551,63,346,103,24.0,13,,17,0.0,31,,,,25,1957-09-08 -1552,63,501,103,4.0,6,,16,0.0,34,,,,44,1957-09-08 -1553,63,506,103,16.0,14,,15,0.0,47,,,,5,1957-09-08 -1554,63,554,103,6.0,5,,14,0.0,49,,,,25,1957-09-08 -1555,63,590,116,20.0,1,,13,0.0,49,,,,5,1957-09-08 -1556,63,581,5,30.0,7,,12,0.0,62,,,,5,1957-09-08 -1557,63,609,103,28.0,16,11.0,11,0.0,72,,,,112,1957-09-08 -1558,63,547,103,14.0,18,10.0,10,0.0,78,,,,19,1957-09-08 -1559,63,580,103,10.0,15,9.0,9,0.0,81,,,,16,1957-09-08 -1560,63,577,5,32.0,9,8.0,8,0.0,82,,,,15,1957-09-08 -1561,63,479,116,22.0,3,7.0,7,1.0,82,,,,15,1957-09-08 -1562,63,578,5,34.0,10,6.0,6,0.0,83,,,,14,1957-09-08 -1563,63,483,103,8.0,12,5.0,5,1.0,84,,,,13,1957-09-08 -1564,63,476,5,36.0,8,3.0,3,4.0,85,,,,12,1957-09-08 -1565,63,579,103,2.0,4,2.0,2,6.0,87,9345100.0,,,1,1957-09-08 -1566,63,475,116,18.0,2,1.0,1,8.0,87,9303900.0,,,1,1957-09-08 -1567,63,586,103,12.0,17,,18,0.0,3,,,,5,1957-09-08 -1568,63,638,103,28.0,16,11.0,11,0.0,72,,,,112,1957-09-08 -1569,63,501,103,8.0,12,5.0,5,1.0,84,,,,13,1957-09-08 -1570,63,417,103,26.0,11,4.0,4,3.0,84,,,,13,1957-09-08 -1571,64,581,5,18.0,3,,10,0.0,0,,,,86,1958-01-19 -1572,64,547,103,12.0,10,9.0,9,0.0,71,,,,19,1958-01-19 -1573,64,580,103,10.0,9,8.0,8,0.0,75,,,,15,1958-01-19 -1574,64,475,85,14.0,7,1.0,1,8.0,80,8373700.0,,,1,1958-01-19 -1575,64,577,5,16.0,5,2.0,2,6.0,80,8376400.0,,,1,1958-01-19 -1576,64,578,5,20.0,2,3.0,3,4.0,80,8386300.0,,,1,1958-01-19 -1577,64,579,103,2.0,1,4.0,4,4.0,80,8426700.0,,,1,1958-01-19 -1578,64,554,103,4.0,4,5.0,5,2.0,78,,,,12,1958-01-19 -1579,64,501,103,8.0,8,6.0,6,0.0,77,,,,13,1958-01-19 -1580,64,496,103,6.0,6,7.0,7,0.0,76,,,,14,1958-01-19 -1581,65,580,103,4.0,0,,31,0.0,0,,,,81,1958-05-18 -1582,65,589,103,56.0,0,,30,0.0,0,,,,81,1958-05-18 -1583,65,588,103,50.0,0,,29,0.0,0,,,,81,1958-05-18 -1584,65,587,123,12.0,0,,28,0.0,0,,,,81,1958-05-18 -1585,65,541,64,10.0,0,,27,0.0,0,,,,81,1958-05-18 -1586,65,547,103,42.0,0,,26,0.0,0,,,,81,1958-05-18 -1587,65,586,125,54.0,0,,25,0.0,0,,,,81,1958-05-18 -1588,65,543,125,52.0,0,,24,0.0,0,,,,81,1958-05-18 -1589,65,553,103,56.0,0,,23,0.0,0,,,,81,1958-05-18 -1590,65,551,103,44.0,0,,22,0.0,0,,,,81,1958-05-18 -1591,65,426,85,20.0,5,1.0,1,8.0,100,10347900.0,,,1,1958-05-18 -1592,65,577,5,34.0,10,2.0,2,6.0,100,10368100.0,,,1,1958-05-18 -1593,65,355,85,16.0,3,4.0,4,3.0,97,,,,13,1958-05-18 -1594,65,501,64,8.0,12,5.0,5,2.0,91,,,,19,1958-05-18 -1595,65,477,31,24.0,13,6.0,6,0.0,87,,,,53,1958-05-18 -1596,65,581,5,36.0,9,3.0,3,4.0,100,10386700.0,,,1,1958-05-18 -1597,65,346,103,58.0,16,,8,0.0,71,,,,3,1958-05-18 -1598,65,585,123,14.0,0,,21,0.0,0,,,,81,1958-05-18 -1599,65,584,123,12.0,0,,20,0.0,0,,,,81,1958-05-18 -1600,65,583,103,48.0,0,,19,0.0,0,,,,81,1958-05-18 -1601,65,582,103,50.0,0,,18,0.0,0,,,,81,1958-05-18 -1602,65,476,5,40.0,11,,7,0.0,91,,,,5,1958-05-18 -1603,65,590,116,32.0,7,,16,0.0,11,,,,25,1958-05-18 -1604,65,479,116,30.0,1,,15,0.0,22,,,,5,1958-05-18 -1605,65,541,85,22.0,0,,17,0.0,0,,,,81,1958-05-18 -1606,65,554,64,6.0,2,,13,0.0,29,,,,23,1958-05-18 -1607,65,475,116,28.0,8,,12,0.0,38,,,,5,1958-05-18 -1608,65,578,5,38.0,6,,11,1.0,47,,,,48,1958-05-18 -1609,65,456,85,18.0,4,,10,0.0,56,,,,6,1958-05-18 -1610,65,288,31,26.0,15,,9,0.0,69,,,,86,1958-05-18 -1611,65,483,103,46.0,14,,14,0.0,28,,,,5,1958-05-18 -1612,66,547,103,12.0,0,,18,0.0,0,,,,54,1958-05-26 -1613,66,346,103,11.0,15,10.0,10,0.0,71,,,,14,1958-05-26 -1614,66,479,116,2.0,3,,17,0.0,13,,,,86,1958-05-26 -1615,66,417,103,12.0,14,,16,0.0,16,,,,48,1958-05-26 -1616,66,581,5,4.0,10,,15,0.0,32,,,,6,1958-05-26 -1617,66,288,31,16.0,13,,14,0.0,40,,,,25,1958-05-26 -1618,66,483,103,10.0,16,,12,0.0,52,,,,86,1958-05-26 -1619,66,429,93,18.0,17,11.0,11,0.0,69,,,,16,1958-05-26 -1620,66,426,85,9.0,8,9.0,9,0.0,72,,,,13,1958-05-26 -1621,66,590,116,3.0,1,,13,0.0,46,,,,5,1958-05-26 -1622,66,577,5,6.0,12,7.0,7,0.0,73,,,,12,1958-05-26 -1623,66,477,31,17.0,11,6.0,6,0.0,73,,,,12,1958-05-26 -1624,66,578,5,5.0,6,5.0,5,2.0,74,,,,11,1958-05-26 -1625,66,456,85,7.0,9,4.0,4,3.0,74,,,,11,1958-05-26 -1626,66,554,64,14.0,4,3.0,3,4.0,75,7591500.0,,,1,1958-05-26 -1627,66,501,64,15.0,7,2.0,2,6.0,75,7537100.0,,,1,1958-05-26 -1628,66,475,116,1.0,2,1.0,1,9.0,75,7489200.0,,,1,1958-05-26 -1629,66,355,85,8.0,5,8.0,8,0.0,73,,,,12,1958-05-26 -1630,67,523,111,83.0,23,,19,0.0,116,,,,23,1958-05-30 -1631,67,448,108,8.0,11,,20,0.0,93,,,,121,1958-05-30 -1632,67,595,111,43.0,15,,21,0.0,80,,,,121,1958-05-30 -1633,67,527,112,88.0,18,,22,0.0,68,,,,7,1958-05-30 -1634,67,512,111,7.0,22,,23,0.0,52,,,,38,1958-05-30 -1635,67,563,118,89.0,29,,24,0.0,38,,,,3,1958-05-30 -1636,67,562,108,25.0,10,,25,0.0,21,,,,48,1958-05-30 -1637,67,597,111,4.0,5,,29,0.0,0,,,,3,1958-05-30 -1638,67,537,105,97.0,1,,27,0.0,0,,,,3,1958-05-30 -1639,67,596,105,5.0,2,,28,0.0,0,,,,3,1958-05-30 -1640,67,510,111,31.0,16,,30,0.0,0,,,,3,1958-05-30 -1641,67,598,111,92.0,24,,31,0.0,0,,,,3,1958-05-30 -1642,67,599,112,57.0,28,,33,0.0,0,,,,3,1958-05-30 -1643,67,555,111,15.0,14,,18,0.0,122,,,,37,1958-05-30 -1644,67,536,111,68.0,27,,32,0.0,0,,,,3,1958-05-30 -1645,67,514,111,14.0,4,,26,0.0,1,,,,3,1958-05-30 -1646,67,565,111,77.0,31,,17,0.0,136,,,,2,1958-05-30 -1647,67,531,112,29.0,12,,16,0.0,148,,,,20,1958-05-30 -1648,67,539,112,59.0,32,,15,0.0,151,,,,42,1958-05-30 -1649,67,525,106,1.0,7,1.0,1,8.0,200,13453800.0,,,1,1958-05-30 -1650,67,591,106,99.0,25,2.0,2,6.0,200,13481430.0,,,1,1958-05-30 -1651,67,529,106,33.0,9,4.0,4,4.0,200,13548610.0,,,1,1958-05-30 -1652,67,509,106,2.0,20,5.0,5,2.0,200,13549420.0,,,1,1958-05-30 -1653,67,592,105,16.0,3,6.0,6,0.0,200,13590750.0,,,1,1958-05-30 -1654,67,528,107,26.0,13,7.0,7,0.0,200,13594860.0,,,1,1958-05-30 -1655,67,533,111,9.0,8,3.0,3,4.0,200,13523470.0,,,1,1958-05-30 -1656,67,513,111,61.0,26,9.0,9,0.0,200,13829560.0,,,1,1958-05-30 -1657,67,560,111,54.0,33,10.0,10,0.0,200,13937390.0,,,1,1958-05-30 -1658,67,558,111,52.0,21,11.0,11,0.0,200,14008000.0,,,1,1958-05-30 -1659,67,593,111,45.0,6,12.0,12,0.0,200,14034650.0,,,1,1958-05-30 -1660,67,594,112,19.0,30,13.0,13,0.0,200,14046040.0,,,1,1958-05-30 -1661,67,516,111,65.0,17,,14,0.0,189,,,,20,1958-05-30 -1662,67,564,105,44.0,19,8.0,8,0.0,200,13787820.0,,,1,1958-05-30 -1663,68,355,85,22.0,8,,12,0.0,16,,,,25,1958-06-15 -1664,68,288,31,42.0,15,,13,0.0,12,,,,5,1958-06-15 -1665,68,577,5,18.0,2,,14,0.0,5,,,,3,1958-06-15 -1666,68,581,5,14.0,4,,15,0.0,5,,,,25,1958-06-15 -1667,68,417,103,30.0,3,,19,0.0,0,,,,5,1958-06-15 -1668,68,455,103,32.0,17,,17,0.0,4,,,,86,1958-06-15 -1669,68,580,103,38.0,18,,11,0.0,22,,,,5,1958-06-15 -1670,68,475,116,2.0,9,,18,0.0,0,,,,5,1958-06-15 -1671,68,554,64,8.0,10,,16,0.0,5,,,,51,1958-06-15 -1672,68,551,103,26.0,19,10.0,10,0.0,22,,,,12,1958-06-15 -1673,68,479,116,4.0,5,1.0,1,8.0,24,5826300.0,,,1,1958-06-15 -1674,68,456,85,24.0,13,8.0,8,0.0,23,,,,11,1958-06-15 -1675,68,578,5,16.0,1,2.0,2,7.0,24,5847000.0,,,1,1958-06-15 -1676,68,590,116,6.0,11,3.0,3,4.0,24,6007200.0,,,1,1958-06-15 -1677,68,477,31,40.0,12,4.0,4,3.0,24,6081800.0,,,1,1958-06-15 -1678,68,346,103,36.0,14,9.0,9,0.0,22,,,,12,1958-06-15 -1679,68,482,5,20.0,6,6.0,6,0.0,23,,,,11,1958-06-15 -1680,68,426,103,28.0,16,7.0,7,0.0,23,,,,11,1958-06-15 -1681,68,501,64,10.0,7,5.0,5,2.0,23,,,,11,1958-06-15 -1682,69,477,31,26.0,20,,21,0.0,6,,,,5,1958-07-06 -1683,69,566,103,28.0,17,,20,0.0,9,,,,5,1958-07-06 -1684,69,456,85,20.0,14,11.0,11,0.0,37,,,,53,1958-07-06 -1685,69,479,116,10.0,5,,18,0.0,16,,,,5,1958-07-06 -1686,69,426,64,18.0,7,,17,0.0,23,,,,48,1958-07-06 -1687,69,580,103,40.0,11,,16,0.0,28,,,,3,1958-07-06 -1688,69,288,31,24.0,19,,15,0.0,33,,,,25,1958-07-06 -1689,69,590,116,12.0,10,,14,0.0,35,,,,5,1958-07-06 -1690,69,554,64,14.0,9,,13,0.0,41,,,,48,1958-07-06 -1691,69,501,64,16.0,3,,12,0.0,41,,,,25,1958-07-06 -1692,69,577,5,2.0,2,,19,0.0,9,,,,3,1958-07-06 -1693,69,526,103,30.0,18,10.0,10,0.0,45,,,,15,1958-07-06 -1694,69,346,103,38.0,16,8.0,8,0.0,48,,,,12,1958-07-06 -1695,69,402,103,36.0,13,7.0,7,0.0,49,,,,11,1958-07-06 -1696,69,355,85,22.0,12,6.0,6,0.0,49,,,,11,1958-07-06 -1697,69,581,5,42.0,4,5.0,5,2.0,50,7726200.0,,,1,1958-07-06 -1698,69,579,103,34.0,8,4.0,4,3.0,50,7551900.0,,,1,1958-07-06 -1699,69,476,5,6.0,21,3.0,3,4.0,50,7461000.0,,,1,1958-07-06 -1700,69,475,116,8.0,6,2.0,2,6.0,50,7425900.0,,,1,1958-07-06 -1701,69,578,5,4.0,1,1.0,1,9.0,50,7401300.0,,,1,1958-07-06 -1702,69,479,116,12.0,10,,14,0.0,35,,,,5,1958-07-06 -1703,69,583,103,32.0,15,9.0,9,0.0,47,,,,13,1958-07-06 -1704,70,436,85,12.0,16,,13,0.0,40,,,,8,1958-07-19 -1705,70,475,116,7.0,1,,14,0.0,25,,,,5,1958-07-19 -1706,70,477,31,17.0,5,,15,0.0,21,,,,5,1958-07-19 -1707,70,554,64,19.0,8,,16,0.0,19,,,,22,1958-07-19 -1708,70,583,103,6.0,18,,12,0.0,44,,,,6,1958-07-19 -1709,70,502,31,18.0,20,,18,0.0,19,,,,25,1958-07-19 -1710,70,288,31,16.0,14,,19,0.0,17,,,,25,1958-07-19 -1711,70,486,123,14.0,19,,20,0.0,7,,,,80,1958-07-19 -1712,70,549,123,15.0,17,,17,0.0,19,,,,6,1958-07-19 -1713,70,476,5,3.0,11,,10,0.0,59,,,,5,1958-07-19 -1714,70,346,103,22.0,13,,11,0.0,49,,,,6,1958-07-19 -1715,70,426,85,4.0,12,8.0,8,0.0,73,,,,12,1958-07-19 -1716,70,479,116,8.0,9,7.0,7,0.0,74,,,,11,1958-07-19 -1717,70,355,85,11.0,10,6.0,6,0.0,75,7827400.0,,,1,1958-07-19 -1718,70,501,64,20.0,2,5.0,5,2.0,75,7819000.0,,,1,1958-07-19 -1719,70,590,116,9.0,7,4.0,4,3.0,75,7795000.0,,,1,1958-07-19 -1720,70,456,85,10.0,3,3.0,3,4.0,75,7794800.0,,,1,1958-07-19 -1721,70,578,5,2.0,4,2.0,2,7.0,75,7768400.0,,,1,1958-07-19 -1722,70,581,5,1.0,6,1.0,1,8.0,75,7744200.0,,,1,1958-07-19 -1723,70,566,103,5.0,15,9.0,9,0.0,72,,,,13,1958-07-19 -1724,71,501,64,6.0,8,,15,0.0,9,,,,23,1958-08-03 -1725,71,600,85,27.0,23,,16,0.0,4,,,,48,1958-08-03 -1726,71,288,31,25.0,22,,17,0.0,4,,,,108,1958-08-03 -1727,71,554,64,5.0,9,,18,0.0,4,,,,22,1958-08-03 -1728,71,601,85,19.0,18,,22,0.0,2,,,,5,1958-08-03 -1729,71,478,103,17.0,20,,20,0.0,3,,,,5,1958-08-03 -1730,71,475,116,7.0,3,,21,1.0,3,,,,121,1958-08-03 -1731,71,455,85,22.0,17,,14,0.0,9,,,,22,1958-08-03 -1732,71,484,85,29.0,25,,23,0.0,1,,,,48,1958-08-03 -1733,71,355,85,24.0,19,,24,0.0,1,,,,4,1958-08-03 -1734,71,429,93,18.0,15,,19,0.0,3,,,,5,1958-08-03 -1735,71,581,5,2.0,4,,13,0.0,10,,,,3,1958-08-03 -1736,71,402,5,23.0,10,9.0,9,0.0,15,8940500.0,,,1,1958-08-03 -1737,71,549,31,28.0,16,11.0,11,0.0,13,,,,12,1958-08-03 -1738,71,477,31,12.0,24,10.0,10,0.0,13,,,,12,1958-08-03 -1739,71,459,85,30.0,14,8.0,8,0.0,15,8904900.0,,,1,1958-08-03 -1740,71,436,85,26.0,11,7.0,7,0.0,15,8894300.0,,,1,1958-08-03 -1741,71,430,93,21.0,13,6.0,6,0.0,15,8867400.0,,,1,1958-08-03 -1742,71,359,85,20.0,12,5.0,5,0.0,15,8861300.0,,,1,1958-08-03 -1743,71,476,5,4.0,5,4.0,4,3.0,15,8851300.0,,,1,1958-08-03 -1744,71,426,85,11.0,7,3.0,3,4.0,15,8786200.0,,,1,1958-08-03 -1745,71,456,85,10.0,6,2.0,2,6.0,15,8684700.0,,,1,1958-08-03 -1746,71,479,116,8.0,2,1.0,1,8.0,15,8475000.0,,,1,1958-08-03 -1747,71,346,103,16.0,21,,25,0.0,1,,,,3,1958-08-03 -1748,71,578,5,3.0,1,,12,0.0,11,,,,8,1958-08-03 -1749,71,526,103,14.0,0,,26,0.0,0,,,,5,1958-08-03 -1750,72,554,64,8.0,4,4.0,4,3.0,49,,,,11,1958-08-24 -1751,72,578,5,24.0,2,2.0,2,7.0,50,8200550.0,,,1,1958-08-24 -1752,72,475,116,2.0,1,1.0,1,8.0,50,7887800.0,,,1,1958-08-24 -1753,72,551,103,30.0,15,,15,0.0,6,,,,5,1958-08-24 -1754,72,346,103,32.0,14,,14,0.0,9,,,,68,1958-08-24 -1755,72,288,31,20.0,12,,12,0.0,25,,,,20,1958-08-24 -1756,72,479,116,4.0,5,,11,0.0,37,,,,20,1958-08-24 -1757,72,566,103,28.0,10,,10,0.0,47,,,,23,1958-08-24 -1758,72,477,103,18.0,13,,13,0.0,15,,,,5,1958-08-24 -1759,72,426,85,12.0,9,8.0,8,0.0,48,,,,12,1958-08-24 -1760,72,355,85,14.0,8,7.0,7,0.0,48,,,,12,1958-08-24 -1761,72,501,64,10.0,7,6.0,6,0.0,49,,,,11,1958-08-24 -1762,72,476,5,22.0,6,5.0,5,2.0,49,,,,11,1958-08-24 -1763,72,590,116,6.0,3,3.0,3,4.0,49,,,,11,1958-08-24 -1764,72,456,85,16.0,11,9.0,9,0.0,46,,,,14,1958-08-24 -1765,73,426,85,2.0,13,,13,0.0,24,,,,6,1958-09-07 -1766,73,566,103,32.0,11,4.0,4,0.0,69,,,,11,1958-09-07 -1767,73,355,85,4.0,15,,21,0.0,0,,,,22,1958-09-07 -1768,73,476,5,16.0,6,,19,0.0,0,,,,3,1958-09-07 -1769,73,566,103,34.0,17,,18,0.0,1,,,,64,1958-09-07 -1770,73,583,103,40.0,19,,17,0.0,2,,,,3,1958-09-07 -1771,73,482,5,20.0,5,,16,0.0,4,,,,22,1958-09-07 -1772,73,346,64,12.0,10,,15,0.0,14,,,,7,1958-09-07 -1773,73,475,116,26.0,1,,14,0.0,17,,,,6,1958-09-07 -1774,73,590,116,30.0,4,,12,0.0,30,,,,25,1958-09-07 -1775,73,501,64,10.0,9,,20,0.0,0,,,,3,1958-09-07 -1776,73,554,64,8.0,8,,10,0.0,42,,,,8,1958-09-07 -1777,73,479,116,28.0,2,1.0,1,8.0,70,7427800.0,,,1,1958-09-07 -1778,73,578,5,14.0,3,2.0,2,6.0,70,7452000.0,,,1,1958-09-07 -1779,73,402,5,18.0,7,3.0,3,5.0,70,7456100.0,,,1,1958-09-07 -1780,73,417,103,32.0,11,4.0,4,0.0,69,,,,11,1958-09-07 -1781,73,478,103,24.0,18,,11,0.0,32,,,,5,1958-09-07 -1782,73,288,31,38.0,12,6.0,6,0.0,62,,,,18,1958-09-07 -1783,73,477,31,36.0,16,7.0,7,0.0,61,,,,19,1958-09-07 -1784,73,551,103,42.0,21,,8,0.0,57,,,,5,1958-09-07 -1785,73,543,103,22.0,20,,9,0.0,51,,,,5,1958-09-07 -1786,73,456,85,6.0,14,5.0,5,2.0,62,,,,18,1958-09-07 -1787,74,602,85,58.0,23,14.0,14,0.0,48,,,,15,1958-10-19 -1788,74,603,85,48.0,25,15.0,15,0.0,48,,,,15,1958-10-19 -1789,74,288,31,32.0,12,16.0,16,0.0,45,,,,17,1958-10-19 -1790,74,590,116,12.0,3,,17,0.0,41,,,,3,1958-10-19 -1791,74,604,85,54.0,24,,18,0.0,31,,,,3,1958-10-19 -1792,74,479,116,10.0,7,,20,0.0,29,,,,5,1958-10-19 -1793,74,426,85,36.0,9,,25,0.0,9,,,,5,1958-10-19 -1794,74,359,85,52.0,21,13.0,13,0.0,48,,,,15,1958-10-19 -1795,74,554,64,14.0,4,,22,0.0,26,,,,5,1958-10-19 -1796,74,455,85,24.0,20,,23,0.0,15,,,,3,1958-10-19 -1797,74,605,85,56.0,22,,19,0.0,30,,,,3,1958-10-19 -1798,74,482,5,2.0,6,,21,0.0,29,,,,3,1958-10-19 -1799,74,583,103,26.0,17,12.0,12,0.0,48,,,,15,1958-10-19 -1800,74,477,31,34.0,16,10.0,10,0.0,49,,,,14,1958-10-19 -1801,74,478,103,38.0,18,9.0,9,0.0,50,,,,13,1958-10-19 -1802,74,486,85,30.0,11,8.0,8,0.0,50,,,,13,1958-10-19 -1803,74,456,85,28.0,14,7.0,7,0.0,51,,,,12,1958-10-19 -1804,74,417,103,22.0,13,6.0,6,0.0,52,,,,11,1958-10-19 -1805,74,501,64,16.0,10,5.0,5,2.0,53,7908800.0,,,1,1958-10-19 -1806,74,346,64,18.0,8,4.0,4,3.0,53,7861800.0,,,1,1958-10-19 -1807,74,402,5,4.0,5,3.0,3,4.0,53,7840600.0,,,1,1958-10-19 -1808,74,578,5,6.0,1,2.0,2,6.0,53,7839800.0,,,1,1958-10-19 -1809,74,475,116,8.0,2,1.0,1,9.0,53,7755100.0,,,1,1958-10-19 -1810,74,355,85,50.0,19,11.0,11,0.0,49,,,,14,1958-10-19 -1811,74,541,64,20.0,15,,24,0.0,15,,,,5,1958-10-19 -1812,75,483,103,54.0,0,,18,0.0,0,,,,81,1959-05-10 -1813,75,550,167,12.0,0,,19,0.0,0,,,,81,1959-05-10 -1814,75,375,167,10.0,0,,20,0.0,0,,,,81,1959-05-10 -1815,75,549,167,34.0,0,,17,0.0,0,,,,81,1959-05-10 -1816,75,352,31,42.0,0,,22,0.0,0,,,,81,1959-05-10 -1817,75,552,167,14.0,0,,23,0.0,0,,,,81,1959-05-10 -1818,75,553,103,56.0,0,,24,0.0,0,,,,81,1959-05-10 -1819,75,551,93,4.0,0,,21,0.0,0,,,,81,1959-05-10 -1820,75,506,31,44.0,16,,16,0.0,1,,,,4,1959-05-10 -1821,75,456,163,38.0,8,6.0,6,0.0,83,,,,50,1959-05-10 -1822,75,476,93,6.0,12,,14,0.0,1,,,,4,1959-05-10 -1823,75,477,5,52.0,15,,15,0.0,1,,,,4,1959-05-10 -1824,75,359,167,22.0,13,5.0,5,2.0,96,,,,14,1959-05-10 -1825,75,402,5,48.0,5,4.0,4,3.0,97,,,,13,1959-05-10 -1826,75,426,167,32.0,6,3.0,3,4.0,98,,,,12,1959-05-10 -1827,75,355,167,24.0,3,1.0,1,9.0,100,10551300.0,,,1,1959-05-10 -1828,75,475,167,30.0,1,,7,0.0,81,,,,7,1959-05-10 -1829,75,479,5,50.0,4,2.0,2,6.0,100,10571700.0,,,1,1959-05-10 -1830,75,501,64,16.0,9,,9,0.0,48,,,,3,1959-05-10 -1831,75,346,64,18.0,7,,10,0.0,44,,,,23,1959-05-10 -1832,75,554,5,46.0,2,,11,0.0,24,,,,5,1959-05-10 -1833,75,288,31,40.0,14,,12,0.0,21,,,,42,1959-05-10 -1834,75,417,167,26.0,11,,13,0.0,6,,,,6,1959-05-10 -1835,75,541,64,20.0,10,,8,0.0,64,,,,20,1959-05-10 -1836,76,516,111,65.0,24,,25,0.0,109,,,,5,1959-05-30 -1837,76,528,111,15.0,25,,22,0.0,136,,,,121,1959-05-30 -1838,76,561,119,49.0,32,,23,0.0,115,,,,3,1959-05-30 -1839,76,511,107,9.0,10,,24,0.0,112,,,,22,1959-05-30 -1840,76,522,111,48.0,5,,26,0.0,85,,,,121,1959-05-30 -1841,76,525,106,6.0,20,,33,0.0,1,,,,5,1959-05-30 -1842,76,563,111,47.0,29,,28,0.0,45,,,,3,1959-05-30 -1843,76,564,111,7.0,19,,29,0.0,45,,,,3,1959-05-30 -1844,76,565,120,77.0,31,,30,0.0,45,,,,3,1959-05-30 -1845,76,517,111,87.0,26,,31,0.0,45,,,,3,1959-05-30 -1846,76,536,108,8.0,22,,32,0.0,34,,,,3,1959-05-30 -1847,76,560,112,53.0,30,,21,0.0,147,,,,121,1959-05-30 -1848,76,562,113,24.0,14,,27,0.0,47,,,,95,1959-05-30 -1849,76,537,105,73.0,4,,20,0.0,150,,,,42,1959-05-30 -1850,76,527,112,44.0,2,,17,0.0,182,,,,20,1959-05-30 -1851,76,558,112,57.0,28,,18,0.0,163,,,,5,1959-05-30 -1852,76,448,105,5.0,6,1.0,1,8.0,200,13249200.0,,,1,1959-05-30 -1853,76,509,105,16.0,3,2.0,2,6.0,200,13272480.0,,,1,1959-05-30 -1854,76,512,108,3.0,1,3.0,3,5.0,200,13299840.0,,,1,1959-05-30 -1855,76,529,106,1.0,15,4.0,4,3.0,200,13356290.0,,,1,1959-05-30 -1856,76,510,106,99.0,16,5.0,5,2.0,200,13375640.0,,,1,1959-05-30 -1857,76,559,105,64.0,18,,19,0.0,162,,,,3,1959-05-30 -1858,76,518,111,37.0,12,7.0,7,0.0,200,13499120.0,,,1,1959-05-30 -1859,76,513,111,19.0,8,8.0,8,0.0,200,13499730.0,,,1,1959-05-30 -1860,76,533,106,33.0,11,6.0,6,0.0,200,13446180.0,,,1,1959-05-30 -1861,76,531,112,10.0,17,10.0,10,0.0,200,13503680.0,,,1,1959-05-30 -1862,76,520,112,88.0,9,11.0,11,0.0,200,13591680.0,,,1,1959-05-30 -1863,76,514,117,74.0,7,12.0,12,0.0,200,13618930.0,,,1,1959-05-30 -1864,76,538,118,89.0,23,13.0,13,0.0,200,13649600.0,,,1,1959-05-30 -1865,76,556,111,66.0,13,14.0,14,0.0,200,13650740.0,,,1,1959-05-30 -1866,76,557,111,71.0,21,15.0,15,0.0,200,13749060.0,,,1,1959-05-30 -1867,76,535,111,58.0,33,16.0,16,0.0,200,13950890.0,,,1,1959-05-30 -1868,76,555,111,45.0,27,9.0,9,0.0,200,13500240.0,,,1,1959-05-30 -1869,77,456,115,4.0,13,,15,0.0,3,,,,5,1959-05-31 -1870,77,501,64,6.0,6,,12,0.0,46,,,,6,1959-05-31 -1871,77,566,115,5.0,10,,14,0.0,25,,,,5,1959-05-31 -1872,77,479,5,2.0,8,,13,0.0,42,,,,44,1959-05-31 -1873,77,475,167,11.0,3,,11,1.0,62,,,,6,1959-05-31 -1874,77,402,5,3.0,12,6.0,6,0.0,73,,,,12,1959-05-31 -1875,77,477,5,16.0,15,9.0,9,0.0,71,,,,14,1959-05-31 -1876,77,403,31,12.0,9,4.0,4,3.0,74,,,,11,1959-05-31 -1877,77,417,167,9.0,7,3.0,3,4.0,75,7609800.0,,,1,1959-05-31 -1878,77,346,64,7.0,1,1.0,1,8.0,75,7526800.0,,,1,1959-05-31 -1879,77,355,167,8.0,2,2.0,2,6.0,75,7541000.0,,,1,1959-05-31 -1880,77,429,93,15.0,14,10.0,10,0.0,68,,,,17,1959-05-31 -1881,77,426,167,10.0,11,8.0,8,0.0,73,,,,12,1959-05-31 -1882,77,288,31,14.0,5,7.0,7,0.0,73,,,,12,1959-05-31 -1883,77,554,5,1.0,4,5.0,5,2.0,74,,,,11,1959-05-31 -1884,78,462,163,20.0,17,,20,0.0,7,,,,44,1959-07-05 -1885,78,346,64,4.0,6,,21,0.0,6,,,,5,1959-07-05 -1886,78,568,103,36.0,0,,22,0.0,0,,,,54,1959-07-05 -1887,78,417,167,10.0,7,,18,0.0,8,,,,68,1959-07-05 -1888,78,479,5,24.0,1,1.0,1,8.0,50,7286500.0,,,1,1959-07-05 -1889,78,288,31,32.0,14,,19,0.0,7,,,,21,1959-07-05 -1890,78,436,163,18.0,19,,17,0.0,13,,,,5,1959-07-05 -1891,78,403,31,34.0,15,,16,0.0,14,,,,36,1959-07-05 -1892,78,363,5,28.0,12,,15,0.0,19,,,,21,1959-07-05 -1893,78,402,5,26.0,3,2.0,2,6.0,50,7314000.0,,,1,1959-07-05 -1894,78,554,5,30.0,5,,13,0.0,31,,,,5,1959-07-05 -1895,78,456,163,16.0,16,,14,0.0,20,,,,5,1959-07-05 -1896,78,501,64,6.0,9,7.0,7,0.0,47,,,,13,1959-07-05 -1897,78,541,64,44.0,13,6.0,6,0.0,50,7412200.0,,,1,1959-07-05 -1898,78,359,167,12.0,10,5.0,5,2.0,50,7394200.0,,,1,1959-07-05 -1899,78,429,103,42.0,20,9.0,9,0.0,40,,,,88,1959-07-05 -1900,78,483,103,40.0,21,8.0,8,0.0,41,,,,19,1959-07-05 -1901,78,426,167,14.0,8,11.0,11,0.0,36,,,,111,1959-07-05 -1902,78,482,5,22.0,11,4.0,4,3.0,50,7394000.0,,,1,1959-07-05 -1903,78,355,167,8.0,2,3.0,3,4.0,50,7384200.0,,,1,1959-07-05 -1904,78,475,64,2.0,4,,12,1.0,42,,,,2,1959-07-05 -1905,78,567,103,38.0,18,10.0,10,0.0,40,,,,88,1959-07-05 -1906,79,426,167,18.0,4,5.0,5,2.0,74,,,,11,1959-07-18 -1907,79,355,167,12.0,1,1.0,1,8.0,75,9011600.0,,,1,1959-07-18 -1908,79,475,64,6.0,7,2.0,2,6.5,75,9033800.0,,,1,1959-07-18 -1909,79,359,167,16.0,8,3.0,3,4.5,75,9034000.0,,,1,1959-07-18 -1910,79,501,64,8.0,3,4.0,4,3.0,74,,,,11,1959-07-18 -1911,79,456,115,2.0,2,6.0,6,0.0,74,,,,11,1959-07-18 -1912,79,288,31,28.0,9,9.0,9,0.0,70,,,,15,1959-07-18 -1913,79,502,31,30.0,12,8.0,8,0.0,71,,,,14,1959-07-18 -1914,79,505,166,48.0,16,10.0,10,0.0,70,,,,15,1959-07-18 -1915,79,481,167,58.0,21,11.0,11,0.0,69,,,,16,1959-07-18 -1916,79,569,167,52.0,23,12.0,12,0.0,69,,,,16,1959-07-18 -1917,79,549,166,46.0,18,13.0,13,0.0,69,,,,16,1959-07-18 -1918,79,566,115,4.0,6,,14,0.0,69,,,,80,1959-07-18 -1919,79,567,103,40.0,20,,15,0.0,57,,,,3,1959-07-18 -1920,79,486,167,38.0,15,,17,0.0,39,,,,6,1959-07-18 -1921,79,436,163,22.0,13,,19,0.0,31,,,,7,1959-07-18 -1922,79,478,163,24.0,19,,20,0.0,21,,,,6,1959-07-18 -1923,79,417,167,14.0,5,7.0,7,0.0,73,,,,12,1959-07-18 -1924,79,541,64,42.0,11,,16,0.0,53,,,,20,1959-07-18 -1925,79,346,64,10.0,10,,18,0.0,37,,,,23,1959-07-18 -1926,79,400,167,44.0,0,,29,0.0,0,,,,81,1959-07-18 -1927,79,542,31,64.0,22,,21,0.0,19,,,,25,1959-07-18 -1928,79,484,99,36.0,14,,22,0.0,18,,,,7,1959-07-18 -1929,79,540,167,50.0,24,,23,0.0,17,,,,7,1959-07-18 -1930,79,479,116,20.0,17,,24,0.0,13,,,,80,1959-07-18 -1931,79,465,167,54.0,0,,25,0.0,0,,,,81,1959-07-18 -1932,79,570,167,56.0,0,,26,0.0,0,,,,81,1959-07-18 -1933,79,386,121,60.0,0,,27,0.0,0,,,,81,1959-07-18 -1934,79,440,167,66.0,0,,30,0.0,0,,,,81,1959-07-18 -1935,79,571,31,62.0,0,,28,0.0,0,,,,81,1959-07-18 -1936,80,479,5,4.0,1,1.0,1,9.0,60,7771600.0,,,1,1959-08-02 -1937,80,363,5,6.0,3,2.0,2,6.0,60,7774500.0,,,1,1959-08-02 -1938,80,402,5,5.0,6,3.0,3,4.0,60,7836400.0,,,1,1959-08-02 -1939,80,426,167,8.0,12,4.0,4,3.0,59,,,,11,1959-08-02 -1940,80,346,64,9.0,7,5.0,5,2.0,58,,,,12,1959-08-02 -1941,80,436,163,18.0,15,6.0,6,0.0,56,,,,14,1959-08-02 -1942,80,478,64,11.0,11,,9,0.0,36,,,,3,1959-08-02 -1943,80,359,167,2.0,9,,8,0.0,36,,,,7,1959-08-02 -1944,80,417,167,3.0,5,,10,0.0,23,,,,5,1959-08-02 -1945,80,288,31,16.0,10,,12,0.0,10,,,,6,1959-08-02 -1946,80,403,31,15.0,13,,13,0.0,7,,,,24,1959-08-02 -1947,80,477,5,17.0,14,,14,0.0,2,,,,8,1959-08-02 -1948,80,475,167,7.0,2,,15,0.0,1,,,,7,1959-08-02 -1949,80,501,64,10.0,8,7.0,7,0.0,49,,,,45,1959-08-02 -1950,80,355,167,1.0,4,,11,0.0,15,,,,7,1959-08-02 -1951,81,426,167,5.0,4,4.0,4,3.0,60,,,,12,1959-08-23 -1952,81,288,31,11.0,15,,15,0.0,5,,,,3,1959-08-23 -1953,81,403,31,12.0,16,,16,0.0,3,,,,6,1959-08-23 -1954,81,402,5,15.0,7,,14,0.0,5,,,,3,1959-08-23 -1955,81,363,5,16.0,6,3.0,3,4.0,61,,,,11,1959-08-23 -1956,81,346,64,7.0,5,,13,0.0,10,,,,5,1959-08-23 -1957,81,359,167,3.0,8,,11,0.0,38,,,,7,1959-08-23 -1958,81,501,64,6.0,9,5.0,5,2.0,59,,,,13,1959-08-23 -1959,81,456,115,10.0,12,6.0,6,0.0,59,,,,13,1959-08-23 -1960,81,541,64,8.0,11,7.0,7,0.0,59,,,,13,1959-08-23 -1961,81,566,115,9.0,13,8.0,8,0.0,58,,,,14,1959-08-23 -1962,81,417,167,2.0,3,2.0,2,6.0,61,,,,11,1959-08-23 -1963,81,355,167,1.0,2,,12,0.0,23,,,,7,1959-08-23 -1964,81,479,5,14.0,10,9.0,9,0.0,57,,,,15,1959-08-23 -1965,81,475,167,4.0,1,1.0,1,9.0,62,7915410.0,,,1,1959-08-23 -1966,81,431,163,18.0,14,10.0,10,0.0,56,,,,16,1959-08-23 -1967,82,482,5,38.0,6,6.0,6,0.0,71,,,,11,1959-09-13 -1968,82,475,167,14.0,1,1.0,1,8.0,72,7445400.0,,,1,1959-09-13 -1969,82,402,5,32.0,5,2.0,2,7.0,72,7492100.0,,,1,1959-09-13 -1970,82,355,167,12.0,3,3.0,3,4.0,72,7517900.0,,,1,1959-09-13 -1971,82,479,5,30.0,2,,21,0.0,0,,,,8,1959-09-13 -1972,82,288,31,18.0,10,,20,0.0,1,,,,8,1959-09-13 -1973,82,403,31,20.0,14,,19,0.0,14,,,,23,1959-09-13 -1974,82,486,163,22.0,12,,18,0.0,18,,,,5,1959-09-13 -1975,82,477,5,34.0,8,5.0,5,2.0,71,,,,11,1959-09-13 -1976,82,359,167,8.0,9,,17,0.0,22,,,,5,1959-09-13 -1977,82,543,103,28.0,21,15.0,15,0.0,64,,,,18,1959-09-13 -1978,82,436,163,42.0,16,14.0,14,0.0,67,,,,15,1959-09-13 -1979,82,363,5,36.0,4,4.0,4,3.0,72,7525000.0,,,1,1959-09-13 -1980,82,483,167,10.0,12,12.0,12,0.0,68,,,,14,1959-09-13 -1981,82,462,163,40.0,18,11.0,11,0.0,68,,,,14,1959-09-13 -1982,82,566,115,26.0,19,10.0,10,0.0,70,,,,12,1959-09-13 -1983,82,426,167,16.0,13,9.0,9,0.0,70,,,,12,1959-09-13 -1984,82,346,64,6.0,11,8.0,8,0.0,70,,,,12,1959-09-13 -1985,82,501,64,2.0,7,7.0,7,0.0,70,,,,12,1959-09-13 -1986,82,456,115,24.0,17,,16,0.0,44,,,,5,1959-09-13 -1987,82,541,64,4.0,15,13.0,13,0.0,67,,,,15,1959-09-13 -1988,83,475,167,7.0,1,,14,0.0,5,,,,7,1959-12-12 -1989,83,576,103,22.0,0,,19,0.0,0,,,,54,1959-12-12 -1990,83,572,93,17.0,16,7.0,7,0.0,38,,,,14,1959-12-12 -1991,83,477,5,3.0,11,,8,0.0,23,,,,7,1959-12-12 -1992,83,456,163,12.0,11,,9,0.0,23,,,,7,1959-12-12 -1993,83,448,111,1.0,19,,10,0.0,20,,,,8,1959-12-12 -1994,83,573,165,14.0,14,,11,0.0,13,,,,23,1959-12-12 -1995,83,402,5,5.0,8,,12,0.0,8,,,,8,1959-12-12 -1996,83,355,167,8.0,2,4.0,4,3.0,42,8253000.0,,,1,1959-12-12 -1997,83,479,5,2.0,4,3.0,3,4.0,42,8136600.0,,,1,1959-12-12 -1998,83,426,167,6.0,5,2.0,2,7.0,42,7956300.0,,,1,1959-12-12 -1999,83,359,167,9.0,10,1.0,1,8.0,42,7955700.0,,,1,1959-12-12 -2000,83,574,166,16.0,15,,16,0.0,5,,,,25,1959-12-12 -2001,83,403,31,10.0,9,5.0,5,2.0,39,,,,13,1959-12-12 -2002,83,501,167,19.0,3,,15,0.0,5,,,,8,1959-12-12 -2003,83,567,122,15.0,17,,13,0.0,6,,,,44,1959-12-12 -2004,83,502,31,11.0,12,,17,0.0,2,,,,8,1959-12-12 -2005,83,575,123,18.0,13,,18,0.0,0,,,,3,1959-12-12 -2006,83,476,5,4.0,6,6.0,6,0.0,38,,,,5,1959-12-12 -2007,84,483,103,8.0,18,,22,0.0,11,,,,25,1960-02-07 -2008,84,504,103,12.0,22,,21,0.0,16,,,,68,1960-02-07 -2009,84,503,103,44.0,21,,20,0.0,23,,,,68,1960-02-07 -2010,84,502,31,22.0,14,,19,0.0,24,,,,68,1960-02-07 -2011,84,288,64,42.0,3,,18,0.0,37,,,,25,1960-02-07 -2012,84,475,167,36.0,1,,17,0.0,40,,,,22,1960-02-07 -2013,84,355,167,18.0,10,,16,0.0,42,,,,6,1960-02-07 -2014,84,501,167,34.0,9,,15,0.0,63,,,,48,1960-02-07 -2015,84,438,103,10.0,20,14.0,14,0.0,70,,,,88,1960-02-07 -2016,84,417,102,2.0,16,12.0,12,0.0,76,,,,14,1960-02-07 -2017,84,500,103,14.0,19,13.0,13,0.0,72,,,,18,1960-02-07 -2018,84,402,5,26.0,6,8.0,8,0.0,77,,,,13,1960-02-07 -2019,84,403,31,20.0,2,6.0,6,1.0,79,,,,11,1960-02-07 -2020,84,476,5,30.0,5,5.0,5,2.0,79,,,,11,1960-02-07 -2021,84,426,167,38.0,8,3.0,3,0.0,80,8306400.0,,,1,1960-02-07 -2022,84,496,163,6.0,12,4.0,4,3.0,80,8322800.0,,,1,1960-02-07 -2023,84,359,167,16.0,13,1.0,1,8.0,80,8269500.0,,,1,1960-02-07 -2024,84,475,167,38.0,8,3.0,3,0.0,80,8306400.0,,,1,1960-02-07 -2025,84,497,31,46.0,15,9.0,9,0.0,77,,,,13,1960-02-07 -2026,84,498,5,32.0,11,10.0,10,0.0,77,,,,13,1960-02-07 -2027,84,499,163,4.0,17,11.0,11,0.0,76,,,,14,1960-02-07 -2028,84,477,5,24.0,7,2.0,2,6.0,80,8295800.0,,,1,1960-02-07 -2029,84,346,64,40.0,4,7.0,7,0.0,79,,,,11,1960-02-07 -2030,85,506,167,12.0,0,,17,0.0,0,,,,81,1960-05-29 -2031,85,340,31,26.0,15,,15,0.0,17,,,,7,1960-05-29 -2032,85,426,163,44.0,16,,16,0.0,4,,,,6,1960-05-29 -2033,85,483,168,30.0,0,,22,0.0,0,,,,81,1960-05-29 -2034,85,484,99,20.0,0,,19,0.0,0,,,,81,1960-05-29 -2035,85,417,163,40.0,0,,20,0.0,0,,,,81,1960-05-29 -2036,85,507,104,46.0,0,,21,0.0,0,,,,81,1960-05-29 -2037,85,505,167,16.0,4,,14,0.0,17,,,,6,1960-05-29 -2038,85,477,5,32.0,0,,18,0.0,0,,,,81,1960-05-29 -2039,85,502,31,24.0,13,,13,0.0,23,,,,83,1960-05-29 -2040,85,476,5,38.0,8,8.0,8,0.0,61,,,,8,1960-05-29 -2041,85,355,167,8.0,2,,11,0.0,40,,,,2,1960-05-29 -2042,85,363,64,4.0,14,,10,0.0,44,,,,22,1960-05-29 -2043,85,403,31,22.0,7,9.0,9,0.0,56,,,,122,1960-05-29 -2044,85,508,104,48.0,0,,23,0.0,0,,,,81,1960-05-29 -2045,85,288,64,6.0,6,7.0,7,0.0,66,,,,20,1960-05-29 -2046,85,385,5,34.0,9,6.0,6,1.0,70,,,,123,1960-05-29 -2047,85,346,64,2.0,5,5.0,5,2.0,83,,,,50,1960-05-29 -2048,85,479,167,18.0,3,4.0,4,3.0,99,,,,11,1960-05-29 -2049,85,402,5,36.0,10,3.0,3,4.0,100,10487400.0,,,1,1960-05-29 -2050,85,359,167,10.0,11,2.0,2,6.0,100,10477600.0,,,1,1960-05-29 -2051,85,475,31,28.0,1,1.0,1,8.0,100,10425500.0,,,1,1960-05-29 -2052,85,456,167,14.0,12,,12,0.0,29,,,,25,1960-05-29 -2053,85,436,163,42.0,0,,24,0.0,0,,,,81,1960-05-29 -2054,86,510,106,99.0,26,3.0,3,4.0,200,13158660.0,,,1,1960-05-30 -2055,86,448,105,1.0,3,2.0,2,6.0,200,12984110.0,,,1,1960-05-30 -2056,86,539,111,23.0,33,33.0,33,0.0,11,,,,121,1960-05-30 -2057,86,538,114,76.0,30,32.0,32,0.0,34,,,,8,1960-05-30 -2058,86,537,105,97.0,4,31.0,31,0.0,42,,,,23,1960-05-30 -2059,86,536,105,9.0,5,30.0,30,0.0,47,,,,5,1960-05-30 -2060,86,535,106,16.0,32,29.0,29,0.0,60,,,,23,1960-05-30 -2061,86,534,111,37.0,20,28.0,28,0.0,74,,,,23,1960-05-30 -2062,86,533,106,8.0,13,27.0,27,0.0,77,,,,5,1960-05-30 -2063,86,532,111,46.0,29,26.0,26,0.0,90,,,,3,1960-05-30 -2064,86,531,111,5.0,16,25.0,25,0.0,90,,,,8,1960-05-30 -2065,86,530,106,32.0,15,24.0,24,0.0,103,,,,3,1960-05-30 -2066,86,529,105,2.0,18,23.0,23,0.0,125,,,,5,1960-05-30 -2067,86,528,111,73.0,11,22.0,22,0.0,129,,,,121,1960-05-30 -2068,86,527,114,6.0,1,21.0,21,0.0,132,,,,121,1960-05-30 -2069,86,509,105,4.0,2,1.0,1,8.0,200,12971360.0,,,1,1960-05-30 -2070,86,526,105,28.0,6,20.0,20,0.0,134,,,,109,1960-05-30 -2071,86,524,113,56.0,23,18.0,18,0.0,185,,,,5,1960-05-30 -2072,86,523,111,26.0,19,17.0,17,0.0,191,,,,8,1960-05-30 -2073,86,521,105,65.0,9,15.0,15,0.0,196,,,,14,1960-05-30 -2074,86,520,111,48.0,24,14.0,14,0.0,196,,,,14,1960-05-30 -2075,86,519,112,39.0,31,13.0,13,0.0,200,13702070.0,,,1,1960-05-30 -2076,86,518,112,17.0,27,12.0,12,0.0,200,13648560.0,,,1,1960-05-30 -2077,86,517,106,27.0,22,11.0,11,0.0,200,13641940.0,,,1,1960-05-30 -2078,86,516,111,38.0,14,10.0,10,0.0,200,13491640.0,,,1,1960-05-30 -2079,86,515,109,18.0,28,9.0,9,0.0,200,13471270.0,,,1,1960-05-30 -2080,86,514,110,44.0,25,8.0,8,0.0,200,13288840.0,,,1,1960-05-30 -2081,86,513,109,22.0,7,6.0,6,1.0,200,13221970.0,,,1,1960-05-30 -2082,86,512,108,3.0,17,5.0,5,2.0,200,13162710.0,,,1,1960-05-30 -2083,86,511,107,7.0,8,4.0,4,3.0,200,13159340.0,,,1,1960-05-30 -2084,86,525,106,10.0,10,19.0,19,0.0,152,,,,69,1960-05-30 -2085,86,522,110,14.0,21,16.0,16,0.0,194,,,,16,1960-05-30 -2086,86,494,105,98.0,12,7.0,7,0.0,200,13236950.0,,,1,1960-05-30 -2087,87,355,167,11.0,2,1.0,1,8.0,75,7307200.0,,,1,1960-06-06 -2088,87,508,104,21.0,0,,20,0.0,0,,,,54,1960-06-06 -2089,87,417,163,19.0,0,,19,0.0,0,,,,54,1960-06-06 -2090,87,456,115,17.0,0,,18,0.0,0,,,,54,1960-06-06 -2091,87,479,167,9.0,10,,17,0.0,4,,,,6,1960-06-06 -2092,87,359,167,12.0,9,,16,0.0,8,,,,7,1960-06-06 -2093,87,505,167,8.0,7,,15,0.0,9,,,,5,1960-06-06 -2094,87,363,64,15.0,6,,14,0.0,11,,,,3,1960-06-06 -2095,87,426,163,18.0,17,,13,0.0,39,,,,6,1960-06-06 -2096,87,372,31,6.0,11,,12,0.0,42,,,,7,1960-06-06 -2097,87,507,104,22.0,0,,21,0.0,0,,,,54,1960-06-06 -2098,87,346,64,14.0,4,,10,0.0,54,,,,5,1960-06-06 -2099,87,402,5,1.0,13,,11,0.0,54,,,,5,1960-06-06 -2100,87,288,64,16.0,5,3.0,3,4.0,75,7363800.0,,,1,1960-06-06 -2101,87,475,31,7.0,1,4.0,4,3.0,75,7364900.0,,,1,1960-06-06 -2102,87,476,5,2.0,15,5.0,5,2.0,74,,,,11,1960-06-06 -2103,87,403,31,4.0,3,2.0,2,6.0,75,7331200.0,,,1,1960-06-06 -2104,87,481,167,10.0,14,7.0,7,0.0,78,,,,15,1960-06-06 -2105,87,429,167,20.0,18,8.0,8,0.0,69,,,,16,1960-06-06 -2106,87,502,31,5.0,8,,9,0.0,57,,,,7,1960-06-06 -2107,87,385,5,3.0,12,6.0,6,1.0,74,,,,11,1960-06-06 -2108,88,475,31,12.0,3,,18,0.0,0,,,,3,1960-06-19 -2109,88,508,104,28.0,16,,17,0.0,1,,,,5,1960-06-19 -2110,88,479,167,38.0,2,,16,0.0,2,,,,6,1960-06-19 -2111,88,363,64,8.0,12,,15,0.0,4,,,,5,1960-06-19 -2112,88,403,31,14.0,8,,14,0.0,13,,,,3,1960-06-19 -2113,88,346,64,6.0,7,,13,0.0,14,,,,5,1960-06-19 -2114,88,507,104,30.0,18,,12,0.0,16,,,,5,1960-06-19 -2115,88,505,167,36.0,9,,11,0.0,19,,,,3,1960-06-19 -2116,88,434,5,22.0,13,,9,0.0,23,,,,7,1960-06-19 -2117,88,502,31,16.0,17,,8,0.0,24,,,,3,1960-06-19 -2118,88,288,64,10.0,6,,7,0.0,35,,,,5,1960-06-19 -2119,88,372,31,18.0,10,5.0,5,2.0,34,,,,12,1960-06-19 -2120,88,402,5,24.0,4,4.0,4,3.0,35,,,,11,1960-06-19 -2121,88,482,167,34.0,5,3.0,3,4.0,35,,,,11,1960-06-19 -2122,88,355,167,2.0,1,1.0,1,8.0,36,8497300.0,,,1,1960-06-19 -2123,88,540,31,20.0,19,,19,0.0,0,,,,3,1960-06-19 -2124,88,476,5,26.0,11,,10,0.0,22,,,,7,1960-06-19 -2125,88,375,167,32.0,15,6.0,6,1.0,28,,,,18,1960-06-19 -2126,88,359,167,4.0,14,2.0,2,6.0,36,8560600.0,,,1,1960-06-19 -2127,89,506,167,48.0,15,8.0,8,0.0,40,,,,5,1960-07-03 -2128,89,417,163,40.0,17,9.0,9,0.0,37,,,,53,1960-07-03 -2129,89,507,104,26.0,23,,23,0.0,0,,,,5,1960-07-03 -2130,89,542,31,34.0,21,,22,0.0,0,,,,5,1960-07-03 -2131,89,385,104,28.0,20,,21,0.0,0,,,,5,1960-07-03 -2132,89,426,163,38.0,18,,20,0.0,0,,,,3,1960-07-03 -2133,89,288,64,12.0,3,,19,0.0,0,,,,3,1960-07-03 -2134,89,479,116,14.0,13,,18,0.0,7,,,,76,1960-07-03 -2135,89,434,5,6.0,11,,17,0.0,14,,,,7,1960-07-03 -2136,89,500,168,30.0,19,,16,0.0,16,,,,7,1960-07-03 -2137,89,363,64,10.0,6,,15,0.0,17,,,,5,1960-07-03 -2138,89,372,31,24.0,10,5.0,5,2.0,49,,,,11,1960-07-03 -2139,89,346,64,8.0,8,,13,0.0,22,,,,5,1960-07-03 -2140,89,402,5,2.0,2,12.0,12,0.0,29,,,,7,1960-07-03 -2141,89,476,5,4.0,5,11.0,11,0.0,30,,,,7,1960-07-03 -2142,89,355,167,16.0,1,1.0,1,8.0,50,7044900.0,,,1,1960-07-03 -2143,89,482,167,44.0,9,2.0,2,6.0,50,7093200.0,,,1,1960-07-03 -2144,89,359,167,18.0,7,3.0,3,4.0,50,7096800.0,,,1,1960-07-03 -2145,89,481,167,46.0,12,4.0,4,3.0,49,,,,11,1960-07-03 -2146,89,436,163,42.0,22,10.0,10,0.0,36,,,,111,1960-07-03 -2147,89,541,31,22.0,14,6.0,6,1.0,49,,,,11,1960-07-03 -2148,89,403,31,20.0,4,7.0,7,0.0,43,,,,17,1960-07-03 -2149,89,375,167,36.0,15,,14,0.0,18,,,,7,1960-07-03 -2150,90,288,64,4.0,2,,17,0.0,71,,,,20,1960-07-16 -2151,90,375,167,24.0,17,,18,0.0,62,,,,10,1960-07-16 -2152,90,346,64,6.0,4,,19,0.0,59,,,,22,1960-07-16 -2153,90,507,167,3.0,19,,20,0.0,58,,,,25,1960-07-16 -2154,90,465,163,22.0,22,,24,0.0,12,,,,25,1960-07-16 -2155,90,456,115,18.0,13,,22,0.0,46,,,,38,1960-07-16 -2156,90,486,167,23.0,15,,23,0.0,46,,,,48,1960-07-16 -2157,90,372,31,8.0,8,16.0,16,0.0,70,,,,17,1960-07-16 -2158,90,508,167,3.0,0,,25,0.0,0,,,,54,1960-07-16 -2159,90,436,163,17.0,20,,21,0.0,58,,,,5,1960-07-16 -2160,90,500,168,21.0,25,15.0,15,0.0,70,,,,17,1960-07-16 -2161,90,482,167,14.0,12,9.0,9,0.0,74,,,,13,1960-07-16 -2162,90,484,99,25.0,18,13.0,13,0.0,72,,,,15,1960-07-16 -2163,90,426,115,19.0,21,11.0,11,0.0,72,,,,15,1960-07-16 -2164,90,363,64,5.0,6,10.0,10,0.0,74,,,,13,1960-07-16 -2165,90,481,167,15.0,16,8.0,8,0.0,74,,,,13,1960-07-16 -2166,90,402,5,10.0,10,7.0,7,0.0,75,,,,12,1960-07-16 -2167,90,476,5,11.0,7,6.0,6,1.0,75,,,,12,1960-07-16 -2168,90,479,167,12.0,9,5.0,5,2.0,76,,,,11,1960-07-16 -2169,90,359,167,2.0,3,4.0,4,3.0,76,,,,11,1960-07-16 -2170,90,340,31,9.0,11,2.0,2,6.0,77,7513900.0,,,1,1960-07-16 -2171,90,355,167,1.0,1,1.0,1,8.0,77,7464300.0,,,1,1960-07-16 -2172,90,417,163,16.0,14,14.0,14,0.0,71,,,,16,1960-07-16 -2173,90,403,31,7.0,5,3.0,3,4.0,77,7553900.0,,,1,1960-07-16 -2174,90,542,31,26.0,24,12.0,12,0.0,72,,,,15,1960-07-16 -2175,91,482,167,8.0,14,7.0,7,0.0,46,,,,19,1960-08-14 -2176,91,355,167,2.0,3,1.0,1,8.0,55,8340030.0,,,1,1960-08-14 -2177,91,359,167,4.0,6,2.0,2,6.0,55,8398000.0,,,1,1960-08-14 -2178,91,372,31,14.0,8,3.0,3,4.0,55,8453260.0,,,1,1960-08-14 -2179,91,476,5,28.0,9,4.0,4,3.0,55,8458840.0,,,1,1960-08-14 -2180,91,479,167,6.0,12,5.0,5,2.0,49,,,,16,1960-08-14 -2181,91,403,31,16.0,7,6.0,6,1.0,48,,,,17,1960-08-14 -2182,91,475,31,12.0,4,,8,0.0,51,,,,2,1960-08-14 -2183,91,431,163,32.0,15,,9,0.0,38,,,,3,1960-08-14 -2184,91,340,31,18.0,1,,10,0.0,37,,,,21,1960-08-14 -2185,91,402,5,26.0,10,,11,0.0,30,,,,3,1960-08-14 -2186,91,363,64,24.0,2,,12,0.0,25,,,,5,1960-08-14 -2187,91,288,64,22.0,5,,14,0.0,9,,,,6,1960-08-14 -2188,91,346,64,20.0,13,,15,0.0,6,,,,5,1960-08-14 -2189,91,417,163,30.0,11,,13,0.0,21,,,,6,1960-08-14 -2190,92,491,163,34.0,9,,12,0.0,32,,,,6,1960-09-04 -2191,92,484,99,6.0,7,,11,0.0,41,,,,6,1960-09-04 -2192,92,544,167,12.0,15,8.0,8,0.0,45,,,,15,1960-09-04 -2193,92,500,168,4.0,8,,13,0.0,27,,,,5,1960-09-04 -2194,92,483,163,36.0,5,,14,0.0,26,,,,5,1960-09-04 -2195,92,397,167,30.0,16,,15,0.0,23,,,,5,1960-09-04 -2196,92,546,167,8.0,11,,16,0.0,0,,,,3,1960-09-04 -2197,92,547,103,14.0,0,,17,0.0,0,,,,69,1960-09-04 -2198,92,430,93,24.0,12,7.0,7,0.0,47,,,,13,1960-09-04 -2199,92,478,93,26.0,10,6.0,6,1.0,47,,,,13,1960-09-04 -2200,92,476,5,22.0,6,5.0,5,2.0,48,,,,12,1960-09-04 -2201,92,543,168,2.0,4,4.0,4,3.0,48,,,,12,1960-09-04 -2202,92,434,5,16.0,3,3.0,3,4.0,49,,,,11,1960-09-04 -2203,92,385,5,18.0,2,2.0,2,6.0,50,8616800.0,,,1,1960-09-04 -2204,92,402,5,20.0,1,1.0,1,8.0,50,8469200.0,,,1,1960-09-04 -2205,92,545,102,28.0,14,10.0,10,0.0,41,,,,19,1960-09-04 -2206,92,455,167,10.0,13,9.0,9,0.0,44,,,,16,1960-09-04 -2207,93,426,163,18.0,19,15.0,15,0.0,66,,,,19,1960-11-20 -2208,93,476,163,26.0,16,9.0,9,0.0,72,,,,13,1960-11-20 -2209,93,372,31,12.0,5,16.0,16,0.0,61,,,,111,1960-11-20 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-2246,94,402,5,38.0,5,3.0,3,4.0,100,9991400.0,,,1,1961-05-14 -2247,94,385,5,36.0,2,2.0,2,6.0,100,9953700.0,,,1,1961-05-14 -2248,94,475,169,20.0,1,1.0,1,9.0,100,9950100.0,,,1,1961-05-14 -2249,94,375,97,10.0,0,,20,0.0,0,,,,81,1961-05-14 -2250,94,476,5,40.0,6,4.0,4,3.0,98,,,,3,1961-05-14 -2251,95,402,5,1.0,1,2.0,2,6.0,75,7313000.0,,,1,1961-05-22 -2252,95,372,169,15.0,11,3.0,3,4.0,75,7325200.0,,,1,1961-05-22 -2253,95,429,93,8.0,17,14.0,14,0.0,72,,,,13,1961-05-22 -2254,95,385,5,2.0,3,5.0,5,2.0,75,7334400.0,,,1,1961-05-22 -2255,95,355,167,10.0,7,6.0,6,1.0,75,7392200.0,,,1,1961-05-22 -2256,95,340,167,12.0,9,7.0,7,0.0,75,7398800.0,,,1,1961-05-22 -2257,95,288,64,4.0,5,8.0,8,0.0,75,7401900.0,,,1,1961-05-22 -2258,95,479,64,5.0,8,9.0,9,0.0,74,,,,11,1961-05-22 -2259,95,363,93,7.0,6,10.0,10,0.0,74,,,,11,1961-05-22 -2260,95,346,93,6.0,12,11.0,11,0.0,73,,,,12,1961-05-22 -2261,95,476,5,3.0,2,1.0,1,9.0,75,7312100.0,,,1,1961-05-22 -2262,95,475,169,14.0,4,4.0,4,3.0,75,7334300.0,,,1,1961-05-22 -2263,95,417,167,17.0,0,,16,0.0,0,,,,54,1961-05-22 -2264,95,436,169,18.0,0,,17,0.0,0,,,,54,1961-05-22 -2265,95,400,169,16.0,16,13.0,13,0.0,73,,,,12,1961-05-22 -2266,95,478,93,9.0,13,15.0,15,0.0,72,,,,13,1961-05-22 -2267,95,359,167,11.0,14,12.0,12,0.0,73,,,,12,1961-05-22 -2268,96,402,5,4.0,1,1.0,1,9.0,30,7383800.0,,,1,1961-06-18 -2269,96,476,5,2.0,2,2.0,2,6.0,30,7384500.0,,,1,1961-06-18 -2270,96,385,5,6.0,5,3.0,3,4.0,30,7403300.0,,,1,1961-06-18 -2271,96,482,5,8.0,3,4.0,4,3.0,30,7429400.0,,,1,1961-06-18 -2272,96,340,167,24.0,4,5.0,5,2.0,30,7470600.0,,,1,1961-06-18 -2273,96,363,93,20.0,10,6.0,6,1.0,30,7474800.0,,,1,1961-06-18 -2274,96,346,93,18.0,9,7.0,7,0.0,30,7550900.0,,,1,1961-06-18 -2275,96,475,169,14.0,8,8.0,8,0.0,30,7619400.0,,,1,1961-06-18 -2276,96,477,169,16.0,0,,25,0.0,0,,,,54,1961-06-18 -2277,96,453,167,40.0,13,9.0,9,0.0,29,,,,11,1961-06-18 -2278,96,481,169,16.0,0,,26,0.0,0,,,,54,1961-06-18 -2279,96,436,169,50.0,0,,24,0.0,0,,,,54,1961-06-18 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-2317,97,288,64,22.0,6,6.0,6,1.0,52,8159400.0,,,1,1961-07-02 -2318,97,453,167,44.0,18,,26,0.0,4,,,,25,1961-07-02 -2319,97,456,167,42.0,15,8.0,8,0.0,51,,,,11,1961-07-02 -2320,97,481,169,30.0,25,10.0,10,0.0,49,,,,13,1961-07-02 -2321,97,480,169,46.0,22,11.0,11,0.0,48,,,,14,1961-07-02 -2322,97,417,167,36.0,16,12.0,12,0.0,43,,,,19,1961-07-02 -2323,97,402,5,16.0,1,9.0,9,0.0,50,,,,12,1961-07-02 -2324,97,346,93,10.0,13,7.0,7,0.0,52,8252900.0,,,1,1961-07-02 -2325,98,453,167,46.0,15,,27,0.0,7,,,,64,1961-07-15 -2326,98,440,169,38.0,29,,26,0.0,12,,,,8,1961-07-15 -2327,98,340,167,34.0,10,,25,0.0,23,,,,24,1961-07-15 -2328,98,481,169,30.0,17,,29,0.0,5,,,,3,1961-07-15 -2329,98,393,5,58.0,19,,23,0.0,27,,,,3,1961-07-15 -2330,98,288,64,20.0,11,,22,0.0,43,,,,5,1961-07-15 -2331,98,475,169,28.0,5,,21,0.0,44,,,,23,1961-07-15 -2332,98,375,169,32.0,30,,20,0.0,45,,,,6,1961-07-15 -2333,98,487,163,62.0,28,,30,0.0,0,,,,6,1961-07-15 -2334,98,482,97,24.0,0,,31,0.0,0,,,,54,1961-07-15 -2335,98,486,100,26.0,20,,19,0.0,56,,,,2,1961-07-15 -2336,98,460,169,40.0,26,,28,0.0,7,,,,80,1961-07-15 -2337,98,459,169,48.0,27,,24,0.0,25,,,,80,1961-07-15 -2338,98,372,169,18.0,8,,18,0.0,62,,,,44,1961-07-15 -2339,98,402,5,2.0,1,2.0,2,6.0,75,9699600.0,,,1,1961-07-15 -2340,98,455,169,52.0,22,17.0,17,0.0,58,,,,50,1961-07-15 -2341,98,429,93,56.0,18,16.0,16,0.0,69,,,,16,1961-07-15 -2342,98,465,95,54.0,26,15.0,15,0.0,69,,,,16,1961-07-15 -2343,98,436,169,44.0,25,14.0,14,0.0,69,,,,16,1961-07-15 -2344,98,407,169,50.0,24,13.0,13,0.0,69,,,,16,1961-07-15 -2345,98,384,163,60.0,21,12.0,12,0.0,71,,,,14,1961-07-15 -2346,98,417,167,42.0,16,11.0,11,0.0,71,,,,14,1961-07-15 -2347,98,403,169,16.0,7,10.0,10,0.0,72,,,,13,1961-07-15 -2348,98,479,64,22.0,6,9.0,9,0.0,73,,,,12,1961-07-15 -2349,98,359,167,14.0,14,8.0,8,0.0,74,,,,11,1961-07-15 -2350,98,363,93,10.0,12,7.0,7,0.0,74,,,,11,1961-07-15 -2351,98,456,167,36.0,13,6.0,6,1.0,75,9739800.0,,,1,1961-07-15 -2352,98,346,93,8.0,3,5.0,5,2.0,75,9729800.0,,,1,1961-07-15 -2353,98,475,100,26.0,20,,19,0.0,56,,,,2,1961-07-15 -2354,98,385,5,6.0,2,3.0,3,4.0,75,9700400.0,,,1,1961-07-15 -2355,98,476,5,4.0,4,1.0,1,9.0,75,9653600.0,,,1,1961-07-15 -2356,98,355,167,12.0,9,4.0,4,3.0,75,9722200.0,,,1,1961-07-15 -2357,99,478,93,11.0,11,13.0,13,0.0,14,,,,11,1961-08-06 -2358,99,455,169,26.0,23,,23,0.0,3,,,,64,1961-08-06 -2359,99,288,64,17.0,16,,24,0.0,1,,,,3,1961-08-06 -2360,99,435,167,39.0,0,,33,0.0,0,,,,54,1961-08-06 -2361,99,490,167,35.0,0,,32,0.0,0,,,,54,1961-08-06 -2362,99,489,167,34.0,0,,31,0.0,0,,,,54,1961-08-06 -2363,99,488,101,29.0,0,,30,0.0,0,,,,54,1961-08-06 -2364,99,480,169,25.0,0,,29,0.0,0,,,,54,1961-08-06 -2365,99,417,167,12.0,0,,28,0.0,0,,,,54,1961-08-06 -2366,99,430,93,10.0,0,,27,0.0,0,,,,54,1961-08-06 -2367,99,403,169,15.0,6,,25,0.0,1,,,,42,1961-08-06 -2368,99,346,93,8.0,4,,22,0.0,5,,,,5,1961-08-06 -2369,99,479,64,16.0,9,,21,0.0,6,,,,5,1961-08-06 -2370,99,384,163,32.0,19,,20,0.0,10,,,,5,1961-08-06 -2371,99,427,167,38.0,26,,19,0.0,11,,,,62,1961-08-06 -2372,99,426,163,20.0,21,,18,0.0,12,,,,5,1961-08-06 -2373,99,355,167,1.0,2,,26,0.0,0,,,,3,1961-08-06 -2374,99,460,169,27.0,25,16.0,16,0.0,13,,,,12,1961-08-06 -2375,99,476,5,3.0,5,2.0,2,6.0,15,8313800.0,,,1,1961-08-06 -2376,99,434,5,6.0,13,,17,0.0,13,,,,3,1961-08-06 -2377,99,402,5,4.0,1,3.0,3,4.0,15,8314900.0,,,1,1961-08-06 -2378,99,372,169,14.0,8,4.0,4,3.0,15,8369500.0,,,1,1961-08-06 -2379,99,340,167,18.0,10,5.0,5,2.0,15,8405500.0,,,1,1961-08-06 -2380,99,359,167,2.0,12,6.0,6,1.0,15,8453800.0,,,1,1961-08-06 -2381,99,363,93,9.0,7,7.0,7,0.0,15,8495500.0,,,1,1961-08-06 -2382,99,475,169,7.0,3,1.0,1,9.0,15,8292400.0,,,1,1961-08-06 -2383,99,453,167,28.0,18,9.0,9,0.0,15,8616100.0,,,1,1961-08-06 -2384,99,456,167,19.0,15,10.0,10,0.0,15,9023900.0,,,1,1961-08-06 -2385,99,407,169,33.0,22,11.0,11,0.0,14,,,,11,1961-08-06 -2386,99,436,167,30.0,24,12.0,12,0.0,14,,,,11,1961-08-06 -2387,99,429,93,31.0,17,14.0,14,0.0,14,,,,11,1961-08-06 -2388,99,385,5,5.0,14,8.0,8,0.0,15,8615500.0,,,1,1961-08-06 -2389,99,459,169,37.0,20,15.0,15,0.0,13,,,,12,1961-08-06 -2390,100,489,163,58.0,29,12.0,12,0.0,38,,,,15,1961-09-10 -2391,100,481,169,20.0,23,11.0,11,0.0,39,,,,14,1961-09-10 -2392,100,440,169,16.0,27,10.0,10,0.0,40,,,,13,1961-09-10 -2393,100,426,163,48.0,22,9.0,9,0.0,41,,,,12,1961-09-10 -2394,100,384,163,62.0,21,8.0,8,0.0,41,,,,12,1961-09-10 -2395,100,479,64,26.0,13,5.0,5,2.0,43,7553500.0,,,1,1961-09-10 -2396,100,456,167,40.0,18,6.0,6,1.0,42,,,,11,1961-09-10 -2397,100,453,167,60.0,16,4.0,4,3.0,43,7553400.0,,,1,1961-09-10 -2398,100,359,167,12.0,14,3.0,3,4.0,43,7541400.0,,,1,1961-09-10 -2399,100,363,93,46.0,12,2.0,2,6.0,43,7424200.0,,,1,1961-09-10 -2400,100,475,169,28.0,11,,13,0.0,36,,,,67,1961-09-10 -2401,100,429,93,74.0,15,7.0,7,0.0,41,,,,12,1961-09-10 -2402,100,402,5,2.0,4,1.0,1,9.0,43,7393000.0,,,1,1961-09-10 -2403,100,385,5,6.0,3,,14,0.0,23,,,,5,1961-09-10 -2404,100,346,93,44.0,8,,16,0.0,14,,,,22,1961-09-10 -2405,100,480,169,70.0,0,,39,0.0,0,,,,54,1961-09-10 -2406,100,492,167,66.0,0,,38,0.0,0,,,,54,1961-09-10 -2407,100,467,169,64.0,0,,37,0.0,0,,,,54,1961-09-10 -2408,100,491,167,34.0,0,,36,0.0,0,,,,54,1961-09-10 -2409,100,487,163,58.0,0,,35,0.0,0,,,,54,1961-09-10 -2410,100,430,93,46.0,0,,34,0.0,0,,,,54,1961-09-10 -2411,100,428,97,68.0,0,,33,0.0,0,,,,81,1961-09-10 -2412,100,460,169,18.0,25,,32,0.0,0,,,,3,1961-09-10 -2413,100,443,171,52.0,32,,31,0.0,1,,,,5,1961-09-10 -2414,100,455,169,56.0,28,,30,0.0,1,,,,5,1961-09-10 -2415,100,446,170,72.0,30,,15,0.0,19,,,,5,1961-09-10 -2416,100,423,172,54.0,24,,29,0.0,1,,,,5,1961-09-10 -2417,100,476,5,4.0,1,,27,0.0,1,,,,3,1961-09-10 -2418,100,340,167,42.0,19,,26,0.0,2,,,,3,1961-09-10 -2419,100,403,169,38.0,9,,24,0.0,5,,,,83,1961-09-10 -2420,100,484,99,14.0,31,,23,0.0,6,,,,5,1961-09-10 -2421,100,355,167,10.0,10,,22,0.0,8,,,,25,1961-09-10 -2422,100,288,64,24.0,5,,21,0.0,10,,,,5,1961-09-10 -2423,100,417,169,22.0,17,,20,0.0,11,,,,22,1961-09-10 -2424,100,424,172,50.0,20,,19,0.0,13,,,,5,1961-09-10 -2425,100,393,5,32.0,6,,18,0.0,13,,,,5,1961-09-10 -2426,100,454,5,8.0,2,,17,0.0,13,,,,69,1961-09-10 -2427,100,372,169,36.0,7,,28,0.0,1,,,,3,1961-09-10 -2428,100,486,167,30.0,26,,25,0.0,5,,,,5,1961-09-10 -2429,101,417,169,21.0,15,11.0,11,0.0,92,,,,18,1961-10-08 -2430,101,363,93,12.0,7,2.0,2,6.0,100,8030100.0,,,1,1961-10-08 -2431,101,495,169,23.0,0,,20,0.0,0,,,,54,1961-10-08 -2432,101,340,167,18.0,9,,19,0.0,0,,,,5,1961-10-08 -2433,101,432,167,60.0,14,,18,0.0,14,,,,3,1961-10-08 -2434,101,417,169,22.0,11,,17,0.0,23,,,,6,1961-10-08 -2435,101,355,167,1.0,1,,16,0.0,57,,,,25,1961-10-08 -2436,101,475,169,7.0,3,,15,0.0,58,,,,5,1961-10-08 -2437,101,494,169,26.0,19,,14,0.0,76,,,,121,1961-10-08 -2438,101,439,169,17.0,18,,13,0.0,76,,,,95,1961-10-08 -2439,101,403,169,15.0,8,1.0,1,9.0,100,8025800.0,,,1,1961-10-08 -2440,101,456,167,19.0,12,,12,0.0,96,,,,5,1961-10-08 -2441,101,433,167,3.0,17,10.0,10,0.0,93,,,,17,1961-10-08 -2442,101,493,169,16.0,13,9.0,9,0.0,96,,,,14,1961-10-08 -2443,101,468,167,6.0,16,8.0,8,0.0,96,,,,14,1961-10-08 -2444,101,372,169,14.0,6,7.0,7,0.0,96,,,,14,1961-10-08 -2445,101,346,93,11.0,10,6.0,6,1.0,98,,,,12,1961-10-08 -2446,101,288,64,4.0,2,5.0,5,2.0,99,,,,11,1961-10-08 -2447,101,359,167,2.0,4,4.0,4,3.0,100,8083800.0,,,1,1961-10-08 -2448,101,479,64,5.0,5,3.0,3,4.0,100,8074800.0,,,1,1961-10-08 -2449,101,482,169,21.0,15,11.0,11,0.0,92,,,,18,1961-10-08 -2450,102,288,64,17.0,2,1.0,1,9.0,80,7862100.0,,,1,1962-05-20 -2451,102,400,169,5.0,10,2.0,2,6.0,80,7889300.0,,,1,1962-05-20 -2452,102,456,25,20.0,17,,17,0.0,12,,,,54,1962-05-20 -2453,102,426,169,21.0,0,,22,0.0,0,,,,54,1962-05-20 -2454,102,458,93,16.0,0,,21,0.0,0,,,,54,1962-05-20 -2455,102,457,93,15.0,10,,20,0.0,2,,,,3,1962-05-20 -2456,102,355,169,8.0,4,,19,0.0,4,,,,3,1962-05-20 -2457,102,340,25,19.0,1,,18,0.0,8,,,,3,1962-05-20 -2458,102,359,167,6.0,5,,16,0.0,21,,,,6,1962-05-20 -2459,102,363,93,12.0,8,,15,0.0,47,,,,6,1962-05-20 -2460,102,417,169,10.0,16,,13,0.0,54,,,,86,1962-05-20 -2461,102,403,169,9.0,6,,12,0.0,61,,,,3,1962-05-20 -2462,102,455,97,16.0,20,,14,0.0,52,,,,62,1962-05-20 -2463,102,454,5,3.0,11,,10,0.0,73,,,,3,1962-05-20 -2464,102,372,169,4.0,3,9.0,9,0.0,70,,,,88,1962-05-20 -2465,102,453,167,21.0,7,8.0,8,0.0,70,,,,88,1962-05-20 -2466,102,346,93,11.0,13,7.0,7,0.0,75,,,,15,1962-05-20 -2467,102,429,93,14.0,14,6.0,6,1.0,76,,,,14,1962-05-20 -2468,102,407,167,7.0,15,5.0,5,2.0,78,,,,12,1962-05-20 -2469,102,393,5,2.0,12,4.0,4,3.0,79,,,,11,1962-05-20 -2470,102,402,5,1.0,9,3.0,3,4.0,80,7943200.0,,,1,1962-05-20 -2471,102,385,64,18.0,7,,11,0.0,71,,,,3,1962-05-20 -2472,103,453,64,24.0,0,,18,0.0,0,,,,81,1962-06-03 -2473,103,363,93,4.0,5,,14,0.0,0,,,,3,1962-06-03 -2474,103,426,169,30.0,7,,15,0.0,0,,,,3,1962-06-03 -2475,103,345,169,46.0,0,,17,0.0,0,,,,81,1962-06-03 -2476,103,417,173,32.0,0,,19,0.0,0,,,,81,1962-06-03 -2477,103,429,93,44.0,0,,20,0.0,0,,,,81,1962-06-03 -2478,103,454,5,40.0,0,,22,0.0,0,,,,54,1962-06-03 -2479,103,423,172,6.0,0,,23,0.0,0,,,,54,1962-06-03 -2480,103,459,64,12.0,0,,24,0.0,0,,,,54,1962-06-03 -2481,103,400,169,20.0,17,,13,0.0,24,,,,44,1962-06-03 -2482,103,424,169,42.0,0,,21,0.0,0,,,,81,1962-06-03 -2483,103,407,167,16.0,19,,12,0.0,43,,,,6,1962-06-03 -2484,103,385,64,8.0,14,,16,0.0,0,,,,3,1962-06-03 -2485,103,372,169,18.0,1,,10,0.0,55,,,,8,1962-06-03 -2486,103,456,25,26.0,12,,11,0.0,44,,,,22,1962-06-03 -2487,103,402,5,36.0,9,2.0,2,6.0,100,9991000.0,,,1,1962-06-03 -2488,103,384,5,38.0,10,3.0,3,4.0,100,10073800.0,,,1,1962-06-03 -2489,103,340,25,28.0,11,4.0,4,3.0,99,,,,11,1962-06-03 -2490,103,346,93,2.0,18,5.0,5,2.0,93,,,,17,1962-06-03 -2491,103,359,167,14.0,3,1.0,1,9.0,100,9989700.0,,,1,1962-06-03 -2492,103,434,5,40.0,4,7.0,7,0.0,90,,,,51,1962-06-03 -2493,103,355,169,22.0,6,8.0,8,0.0,77,,,,3,1962-06-03 -2494,103,403,169,34.0,8,,9,0.0,64,,,,48,1962-06-03 -2495,103,288,64,10.0,2,6.0,6,1.0,92,,,,5,1962-06-03 -2496,104,461,93,8.0,0,,25,0.0,0,,,,54,1962-06-17 -2497,104,359,167,25.0,2,,16,0.0,19,,,,67,1962-06-17 -2498,104,417,173,21.0,8,,17,0.0,13,,,,54,1962-06-17 -2499,104,403,169,20.0,5,,18,0.0,8,,,,22,1962-06-17 -2500,104,393,5,11.0,14,,19,0.0,3,,,,80,1962-06-17 -2501,104,459,64,3.0,0,,21,0.0,0,,,,54,1962-06-17 -2502,104,453,64,4.0,0,,22,0.0,0,,,,54,1962-06-17 -2503,104,460,64,4.0,0,,23,0.0,0,,,,54,1962-06-17 -2504,104,456,25,6.0,0,,24,0.0,0,,,,54,1962-06-17 -2505,104,407,167,26.0,10,,15,0.0,22,,,,6,1962-06-17 -2506,104,346,93,24.0,0,,26,0.0,0,,,,54,1962-06-17 -2507,104,363,173,23.0,0,,20,0.0,0,,,,54,1962-06-17 -2508,104,385,64,2.0,9,,14,0.0,22,,,,6,1962-06-17 -2509,104,375,169,19.0,18,9.0,9,0.0,29,,,,13,1962-06-17 -2510,104,400,169,17.0,3,,12,0.0,25,,,,3,1962-06-17 -2511,104,435,169,4.0,19,11.0,11,0.0,16,,,,116,1962-06-17 -2512,104,345,169,22.0,17,10.0,10,0.0,29,,,,13,1962-06-17 -2513,104,426,169,18.0,16,8.0,8,0.0,30,,,,12,1962-06-17 -2514,104,429,93,7.0,13,7.0,7,0.0,30,,,,12,1962-06-17 -2515,104,355,169,15.0,15,6.0,6,1.0,30,,,,12,1962-06-17 -2516,104,340,25,5.0,11,5.0,5,2.0,31,,,,11,1962-06-17 -2517,104,454,5,12.0,7,4.0,4,3.0,32,7778900.0,,,1,1962-06-17 -2518,104,402,5,9.0,4,3.0,3,4.0,32,7778800.0,,,1,1962-06-17 -2519,104,288,64,1.0,1,2.0,2,6.0,32,7696400.0,,,1,1962-06-17 -2520,104,372,169,16.0,13,1.0,1,9.0,32,7652300.0,,,1,1962-06-17 -2521,104,434,5,10.0,6,,13,0.0,25,,,,3,1962-06-17 -2522,105,456,25,20.0,14,,13,0.0,21,,,,51,1962-07-08 -2523,105,355,169,26.0,4,,15,0.0,11,,,,22,1962-07-08 -2524,105,417,173,34.0,7,,14,0.0,15,,,,25,1962-07-08 -2525,105,345,173,40.0,15,,16,0.0,6,,,,8,1962-07-08 -2526,105,453,85,42.0,16,,12,0.0,28,,,,3,1962-07-08 -2527,105,396,31,16.0,0,,18,0.0,0,,,,54,1962-07-08 -2528,105,459,64,,0,,19,0.0,0,,,,54,1962-07-08 -2529,105,462,93,,0,,20,0.0,0,,,,54,1962-07-08 -2530,105,372,169,12.0,1,,11,0.0,34,,,,22,1962-07-08 -2531,105,403,169,36.0,8,,17,0.0,1,,,,29,1962-07-08 -2532,105,346,93,32.0,9,,10,0.0,43,,,,69,1962-07-08 -2533,105,385,64,10.0,10,3.0,3,4.0,52,,,,12,1962-07-08 -2534,105,436,167,,0,,22,0.0,0,,,,54,1962-07-08 -2535,105,363,93,30.0,6,1.0,1,9.0,54,7625500.0,,,1,1962-07-08 -2536,105,407,167,24.0,11,2.0,2,6.0,53,,,,11,1962-07-08 -2537,105,445,169,,0,,21,0.0,0,,,,54,1962-07-08 -2538,105,359,167,22.0,3,4.0,4,3.0,51,,,,13,1962-07-08 -2539,105,340,25,18.0,5,5.0,5,2.0,51,,,,13,1962-07-08 -2540,105,429,93,38.0,17,6.0,6,1.0,51,,,,13,1962-07-08 -2541,105,426,169,28.0,13,7.0,7,0.0,50,,,,14,1962-07-08 -2542,105,400,169,14.0,12,8.0,8,0.0,48,,,,16,1962-07-08 -2543,105,288,64,8.0,2,9.0,9,0.0,44,,,,88,1962-07-08 -2544,106,385,64,14.0,8,13.0,13,0.0,70,,,,15,1962-07-21 -2545,106,429,93,54.0,17,14.0,14,0.0,69,,,,16,1962-07-21 -2546,106,463,169,46.0,20,15.0,15,0.0,64,,,,45,1962-07-21 -2547,106,346,93,10.0,7,,19,0.0,27,,,,24,1962-07-21 -2548,106,402,5,2.0,12,,17,0.0,47,,,,5,1962-07-21 -2549,106,456,25,26.0,11,,18,0.0,35,,,,84,1962-07-21 -2550,106,436,167,36.0,16,12.0,12,0.0,71,,,,14,1962-07-21 -2551,106,403,169,32.0,3,16.0,16,0.0,61,,,,111,1962-07-21 -2552,106,437,97,40.0,19,11.0,11,0.0,71,,,,14,1962-07-21 -2553,106,407,167,18.0,13,6.0,6,1.0,74,,,,11,1962-07-21 -2554,106,363,93,8.0,6,9.0,9,0.0,73,,,,12,1962-07-21 -2555,106,400,169,22.0,10,8.0,8,0.0,74,,,,11,1962-07-21 -2556,106,417,169,34.0,14,7.0,7,0.0,74,,,,11,1962-07-21 -2557,106,455,173,44.0,21,,20,0.0,11,,,,23,1962-07-21 -2558,106,355,169,30.0,9,5.0,5,2.0,74,,,,11,1962-07-21 -2559,106,288,64,12.0,5,4.0,4,3.0,75,8897600.0,,,1,1962-07-21 -2560,106,359,167,16.0,4,3.0,3,4.0,75,8885600.0,,,1,1962-07-21 -2561,106,340,25,24.0,2,2.0,2,6.0,75,8830000.0,,,1,1962-07-21 -2562,106,372,169,20.0,1,1.0,1,9.0,75,8780800.0,,,1,1962-07-21 -2563,106,453,167,42.0,15,10.0,10,0.0,72,,,,13,1962-07-21 -2564,106,464,169,48.0,18,,21,0.0,6,,,,5,1962-07-21 -2565,106,465,169,48.0,0,,22,0.0,0,,,,54,1962-07-21 -2566,106,435,97,38.0,0,,24,0.0,0,,,,54,1962-07-21 -2567,106,465,95,50.0,0,,25,0.0,0,,,,54,1962-07-21 -2568,106,345,173,52.0,0,,26,0.0,0,,,,54,1962-07-21 -2569,106,426,169,28.0,0,,23,0.0,0,,,,54,1962-07-21 -2570,107,444,173,34.0,0,,30,0.0,0,,,,81,1962-08-05 -2571,107,402,5,1.0,12,,18,0.0,9,,,,22,1962-08-05 -2572,107,459,64,33.0,0,,31,0.0,0,,,,54,1962-08-05 -2573,107,355,33,16.0,24,,19,0.0,9,,,,37,1962-08-05 -2574,107,465,95,27.0,19,,20,0.0,7,,,,22,1962-08-05 -2575,107,456,25,15.0,9,,21,0.0,4,,,,6,1962-08-05 -2576,107,461,173,28.0,20,,24,0.0,4,,,,51,1962-08-05 -2577,107,384,5,4.0,18,,23,0.0,4,,,,3,1962-08-05 -2578,107,427,167,31.0,22,,25,0.0,2,,,,6,1962-08-05 -2579,107,400,169,6.0,26,,26,0.0,0,,,,3,1962-08-05 -2580,107,464,169,29.0,0,,27,0.0,0,,,,81,1962-08-05 -2581,107,455,173,34.0,0,,28,0.0,0,,,,81,1962-08-05 -2582,107,426,169,17.0,11,,22,0.0,4,,,,6,1962-08-05 -2583,107,453,167,20.0,21,,17,0.0,10,,,,22,1962-08-05 -2584,107,466,93,32.0,14,14.0,14,0.0,14,,,,11,1962-08-05 -2585,107,424,93,26.0,15,15.0,15,0.0,14,,,,11,1962-08-05 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-2728,113,393,52,26.0,15,,15,0.0,17,,,,80,1963-06-23 -2729,113,385,64,14.0,6,5.0,5,2.0,79,,,,11,1963-06-23 -2730,113,439,173,42.0,18,8.0,8,0.0,77,,,,13,1963-06-23 -2731,113,407,167,22.0,9,,17,0.0,14,,,,25,1963-06-23 -2732,113,359,167,20.0,3,,18,0.0,7,,,,6,1963-06-23 -2733,113,422,93,34.0,16,,19,0.0,2,,,,8,1963-06-23 -2734,113,437,90,38.0,0,,20,0.0,0,,,,54,1963-06-23 -2735,113,436,90,40.0,0,,21,0.0,0,,,,54,1963-06-23 -2736,113,402,52,24.0,13,,16,0.0,15,,,,22,1963-06-23 -2737,113,345,173,36.0,17,7.0,7,0.0,77,,,,13,1963-06-23 -2738,113,355,33,16.0,4,,13,0.0,68,,,,3,1963-06-23 -2739,113,403,92,30.0,7,4.0,4,3.0,79,,,,11,1963-06-23 -2740,113,340,5,2.0,5,3.0,3,4.0,79,,,,11,1963-06-23 -2741,113,363,33,18.0,14,2.0,2,6.0,79,,,,11,1963-06-23 -2742,113,372,169,6.0,1,1.0,1,9.0,80,7693700.0,,,1,1963-06-23 -2743,114,340,5,16.0,4,,17,0.0,12,,,,48,1963-06-30 -2744,114,403,92,32.0,9,9.0,9,0.0,49,,,,14,1963-06-30 -2745,114,384,64,46.0,21,10.0,10,0.0,45,,,,18,1963-06-30 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-2945,121,396,169,11.0,6,3.0,3,4.0,97,,,,13,1964-05-10 -2946,121,385,64,7.0,8,2.0,2,6.0,99,,,,11,1964-05-10 -2947,121,288,64,8.0,3,1.0,1,9.0,100,9679500.0,,,1,1964-05-10 -2948,121,402,167,9.0,9,9.0,9,0.0,70,,,,22,1964-05-10 -2949,121,407,64,23.0,0,,23,0.0,0,,,,54,1964-05-10 -2950,122,393,64,32.0,16,10.0,10,0.0,74,,,,16,1964-05-24 -2951,122,346,178,26.0,12,9.0,9,0.0,76,,,,14,1964-05-24 -2952,122,402,167,22.0,9,8.0,8,0.0,76,,,,14,1964-05-24 -2953,122,359,167,24.0,5,7.0,7,0.0,78,,,,12,1964-05-24 -2954,122,382,180,34.0,11,6.0,6,1.0,78,,,,12,1964-05-24 -2955,122,277,173,10.0,13,5.0,5,2.0,79,,,,11,1964-05-24 -2956,122,372,169,18.0,2,1.0,1,9.0,80,7655400.0,,,1,1964-05-24 -2957,122,385,64,8.0,8,11.0,11,0.0,64,,,,116,1964-05-24 -2958,122,340,5,2.0,4,2.0,2,6.0,80,7709000.0,,,1,1964-05-24 -2959,122,396,169,20.0,6,3.0,3,4.0,79,,,,11,1964-05-24 -2960,122,407,64,30.0,0,,18,0.0,0,,,,3,1964-05-24 -2961,122,429,93,28.0,17,,17,0.0,8,,,,5,1964-05-24 -2962,122,288,64,6.0,3,4.0,4,3.0,79,,,,11,1964-05-24 -2963,122,363,180,16.0,1,,15,0.0,23,,,,38,1964-05-24 -2964,122,355,180,14.0,7,,14,0.0,44,,,,80,1964-05-24 -2965,122,304,173,12.0,14,12.0,12,0.0,57,,,,24,1964-05-24 -2966,122,345,178,36.0,18,13.0,13,0.0,55,,,,113,1964-05-24 -2967,122,384,5,4.0,10,,16,0.0,20,,,,80,1964-05-24 -2968,123,277,173,27.0,11,,18,0.0,3,,,,5,1964-06-14 -2969,123,340,5,10.0,5,,17,0.0,4,,,,5,1964-06-14 -2970,123,346,180,16.0,14,,16,0.0,8,,,,100,1964-06-14 -2971,123,428,90,28.0,20,,15,0.0,11,,,,5,1964-06-14 -2972,123,384,5,11.0,9,,14,0.0,12,,,,5,1964-06-14 -2973,123,402,167,21.0,15,,13,0.0,13,,,,5,1964-06-14 -2974,123,345,180,17.0,13,,12,0.0,14,,,,5,1964-06-14 -2975,123,403,92,3.0,16,10.0,10,0.0,28,,,,14,1964-06-14 -2976,123,396,169,24.0,4,9.0,9,0.0,28,,,,25,1964-06-14 -2977,123,393,64,6.0,17,8.0,8,0.0,31,,,,11,1964-06-14 -2978,123,363,180,15.0,1,6.0,6,1.0,31,,,,60,1964-06-14 -2979,123,288,64,1.0,2,5.0,5,2.0,31,,,,48,1964-06-14 -2980,123,385,64,2.0,8,4.0,4,3.0,32,7719100.0,,,1,1964-06-14 -2981,123,355,180,14.0,3,3.0,3,4.0,32,7648600.0,,,1,1964-06-14 -2982,123,359,167,20.0,7,2.0,2,6.0,32,7603900.0,,,1,1964-06-14 -2983,123,372,169,23.0,6,1.0,1,9.0,32,7600500.0,,,1,1964-06-14 -2984,123,308,169,29.0,10,,11,0.0,28,,,,2,1964-06-14 -2985,123,400,92,4.0,12,7.0,7,0.0,31,,,,11,1964-06-14 -2986,124,372,169,2.0,1,,14,0.0,31,,,,5,1964-06-28 -2987,124,384,5,26.0,8,9.0,9,0.0,55,,,,12,1964-06-28 -2988,124,340,5,24.0,3,,15,0.0,6,,,,5,1964-06-28 -2989,124,403,92,16.0,11,,13,0.0,32,,,,3,1964-06-28 -2990,124,382,180,32.0,15,12.0,12,0.0,50,,,,17,1964-06-28 -2991,124,426,64,28.0,16,11.0,11,0.0,52,,,,15,1964-06-28 -2992,124,277,173,34.0,14,10.0,10,0.0,53,,,,14,1964-06-28 -2993,124,400,92,18.0,12,,16,0.0,6,,,,3,1964-06-28 -2994,124,304,173,36.0,13,8.0,8,0.0,56,,,,11,1964-06-28 -2995,124,359,167,12.0,7,6.0,6,1.0,56,,,,11,1964-06-28 -2996,124,385,64,10.0,9,5.0,5,2.0,57,7801200.0,,,1,1964-06-28 -2997,124,396,169,4.0,4,4.0,4,3.0,57,7739700.0,,,1,1964-06-28 -2998,124,355,180,20.0,5,3.0,3,4.0,57,7694000.0,,,1,1964-06-28 -2999,124,288,64,8.0,6,2.0,2,6.0,57,7693200.0,,,1,1964-06-28 -3000,124,363,180,22.0,2,1.0,1,9.0,57,7669100.0,,,1,1964-06-28 -3001,124,402,167,14.0,10,7.0,7,0.0,56,,,,11,1964-06-28 -3002,124,345,178,30.0,17,,17,0.0,4,,,,8,1964-06-28 -3003,125,372,169,1.0,1,1.0,1,9.0,80,8107000.0,,,1,1964-07-11 -3004,125,379,179,26.0,19,,23,0.0,0,,,,3,1964-07-11 -3005,125,288,64,3.0,2,2.0,2,6.0,80,8109800.0,,,1,1964-07-11 -3006,125,426,64,25.0,25,,24,0.0,0,,,,81,1964-07-11 -3007,125,340,5,7.0,5,3.0,3,4.0,80,8187600.0,,,1,1964-07-11 -3008,125,384,5,8.0,8,5.0,5,2.0,78,,,,12,1964-07-11 -3009,125,359,167,9.0,6,,22,0.0,7,,,,6,1964-07-11 -3010,125,277,173,15.0,11,,21,0.0,9,,,,8,1964-07-11 -3011,125,304,173,14.0,12,,20,0.0,17,,,,108,1964-07-11 -3012,125,400,173,12.0,18,,19,0.0,23,,,,100,1964-07-11 -3013,125,419,178,23.0,23,,18,0.0,37,,,,3,1964-07-11 -3014,125,407,64,17.0,17,,17,0.0,38,,,,6,1964-07-11 -3015,125,308,173,24.0,22,,16,0.0,43,,,,24,1964-07-11 -3016,125,346,178,16.0,9,,15,0.0,45,,,,23,1964-07-11 -3017,125,398,167,22.0,20,14.0,14,0.0,56,,,,117,1964-07-11 -3018,125,363,180,6.0,3,13.0,13,0.0,75,,,,15,1964-07-11 -3019,125,393,64,18.0,21,12.0,12,0.0,76,,,,14,1964-07-11 -3020,125,345,178,20.0,16,11.0,11,0.0,76,,,,14,1964-07-11 -3021,125,403,92,11.0,10,10.0,10,0.0,77,,,,13,1964-07-11 -3022,125,373,169,2.0,13,9.0,9,0.0,77,,,,13,1964-07-11 -3023,125,385,64,4.0,14,8.0,8,0.0,77,,,,13,1964-07-11 -3024,125,382,180,19.0,7,7.0,7,0.0,78,,,,12,1964-07-11 -3025,125,402,167,10.0,15,6.0,6,1.0,78,,,,12,1964-07-11 -3026,125,355,180,5.0,4,4.0,4,3.0,79,,,,11,1964-07-11 -3027,125,369,64,21.0,24,,25,0.0,0,,,,54,1964-07-11 -3028,126,422,169,23.0,19,9.0,9,0.0,14,,,,11,1964-08-02 -3029,126,385,64,4.0,11,7.0,7,0.0,14,,,,11,1964-08-02 -3030,126,346,178,11.0,12,,21,0.0,0,,,,10,1964-08-02 -3031,126,402,167,10.0,8,,20,0.0,1,,,,5,1964-08-02 -3032,126,393,64,18.0,21,,19,0.0,2,,,,37,1964-08-02 -3033,126,430,167,12.0,20,,18,0.0,3,,,,8,1964-08-02 -3034,126,382,180,16.0,15,,17,0.0,4,,,,22,1964-08-02 -3035,126,359,167,9.0,7,,16,0.0,4,,,,5,1964-08-02 -3036,126,372,169,1.0,2,,15,0.0,7,,,,5,1964-08-02 -3037,126,308,173,27.0,18,14.0,14,0.0,10,,,,3,1964-08-02 -3038,126,404,10,20.0,22,13.0,13,0.0,11,,,,3,1964-08-02 -3039,126,355,180,6.0,6,12.0,12,0.0,11,,,,24,1964-08-02 -3040,126,277,173,14.0,9,11.0,11,0.0,12,,,,22,1964-08-02 -3041,126,363,180,5.0,3,10.0,10,0.0,14,,,,11,1964-08-02 -3042,126,373,169,2.0,17,8.0,8,0.0,14,,,,11,1964-08-02 -3043,126,407,64,26.0,16,6.0,6,1.0,14,,,,11,1964-08-02 -3044,126,426,64,22.0,14,5.0,5,2.0,14,,,,84,1964-08-02 -3045,126,345,178,19.0,10,4.0,4,3.0,15,8247900.0,,,1,1964-08-02 -3046,126,384,5,8.0,4,3.0,3,4.0,15,8217600.0,,,1,1964-08-02 -3047,126,288,64,3.0,5,2.0,2,6.0,15,8000400.0,,,1,1964-08-02 -3048,126,340,5,7.0,1,1.0,1,9.0,15,7924800.0,,,1,1964-08-02 -3049,126,428,90,28.0,0,,23,0.0,0,,,,81,1964-08-02 -3050,126,304,173,15.0,13,,22,0.0,0,,,,5,1964-08-02 -3051,127,288,64,3.0,1,,20,0.0,5,,,,99,1964-08-23 -3052,127,385,64,4.0,5,2.0,2,6.0,105,7584410.0,,,1,1964-08-23 -3053,127,277,169,16.0,17,,19,0.0,7,,,,5,1964-08-23 -3054,127,340,5,7.0,2,,18,0.0,9,,,,22,1964-08-23 -3055,127,345,178,20.0,12,,17,0.0,18,,,,3,1964-08-23 -3056,127,400,92,15.0,16,,16,0.0,21,,,,22,1964-08-23 -3057,127,372,169,1.0,3,,15,0.0,40,,,,86,1964-08-23 -3058,127,373,169,2.0,8,,14,0.0,41,,,,86,1964-08-23 -3059,127,359,167,9.0,9,,13,0.0,43,,,,5,1964-08-23 -3060,127,363,180,5.0,4,,12,0.0,47,,,,22,1964-08-23 -3061,127,384,5,8.0,7,1.0,1,9.0,105,7578230.0,,,1,1964-08-23 -3062,127,357,178,12.0,13,,10,0.0,58,,,,38,1964-08-23 -3063,127,355,180,6.0,6,9.0,9,0.0,76,,,,118,1964-08-23 -3064,127,304,173,17.0,18,8.0,8,0.0,95,,,,88,1964-08-23 -3065,127,393,64,18.0,15,7.0,7,0.0,96,,,,19,1964-08-23 -3066,127,346,180,11.0,10,6.0,6,1.0,101,,,,14,1964-08-23 -3067,127,403,92,14.0,11,5.0,5,2.0,102,,,,13,1964-08-23 -3068,127,407,64,19.0,19,4.0,4,3.0,102,,,,13,1964-08-23 -3069,127,382,180,22.0,14,3.0,3,4.0,102,,,,13,1964-08-23 -3070,127,402,167,10.0,20,,11,0.0,58,,,,3,1964-08-23 -3071,128,404,10,28.0,10,,18,0.0,13,,,,23,1964-09-06 -3072,128,431,94,50.0,19,,16,0.0,25,,,,80,1964-09-06 -3073,128,426,64,48.0,21,,17,0.0,22,,,,98,1964-09-06 -3074,128,372,169,8.0,4,15.0,15,0.0,28,,,,5,1964-09-06 -3075,128,401,178,36.0,0,,22,0.0,0,,,,81,1964-09-06 -3076,128,288,64,18.0,3,,20,0.0,0,,,,8,1964-09-06 -3077,128,400,92,44.0,0,,21,0.0,0,,,,81,1964-09-06 -3078,128,355,180,14.0,11,14.0,14,0.0,59,,,,5,1964-09-06 -3079,128,339,167,24.0,0,,23,0.0,0,,,,81,1964-09-06 -3080,128,419,178,56.0,0,,24,0.0,0,,,,81,1964-09-06 -3081,128,304,173,40.0,17,,19,0.0,5,,,,5,1964-09-06 -3082,128,308,173,38.0,18,13.0,13,0.0,72,,,,16,1964-09-06 -3083,128,373,169,10.0,8,6.0,6,1.0,77,,,,11,1964-09-06 -3084,128,382,180,22.0,14,11.0,11,0.0,75,,,,13,1964-09-06 -3085,128,340,5,2.0,1,1.0,1,9.0,78,7851800.0,,,1,1964-09-06 -3086,128,346,180,34.0,12,12.0,12,0.0,74,,,,14,1964-09-06 -3087,128,384,5,4.0,7,3.0,3,4.0,77,,,,11,1964-09-06 -3088,128,385,64,20.0,9,4.0,4,3.0,77,,,,11,1964-09-06 -3089,128,359,167,26.0,5,2.0,2,6.0,78,7917800.0,,,1,1964-09-06 -3090,128,345,178,12.0,6,7.0,7,0.0,77,,,,11,1964-09-06 -3091,128,393,64,30.0,15,8.0,8,0.0,77,,,,11,1964-09-06 -3092,128,374,5,6.0,16,9.0,9,0.0,77,,,,11,1964-09-06 -3093,128,363,180,16.0,2,10.0,10,0.0,75,,,,13,1964-09-06 -3094,128,403,92,46.0,13,5.0,5,2.0,77,,,,11,1964-09-06 -3095,129,400,92,12.0,15,6.0,6,1.0,106,,,,14,1964-10-04 -3096,129,288,64,3.0,4,1.0,1,9.0,110,8198000.0,,,1,1964-10-04 -3097,129,340,5,7.0,2,2.0,2,6.0,110,8228500.0,,,1,1964-10-04 -3098,129,345,178,22.0,12,3.0,3,4.0,109,,,,11,1964-10-04 -3099,129,385,64,4.0,13,4.0,4,3.0,107,,,,13,1964-10-04 -3100,129,432,169,17.0,17,5.0,5,2.0,107,,,,13,1964-10-04 -3101,129,372,169,1.0,1,7.0,7,0.0,102,,,,60,1964-10-04 -3102,129,355,180,5.0,7,,17,0.0,14,,,,5,1964-10-04 -3103,129,363,180,6.0,3,,9,0.0,69,,,,51,1964-10-04 -3104,129,372,169,2.0,1,,12,0.0,54,,,,98,1964-10-04 -3105,129,304,173,14.0,15,8.0,8,0.0,101,,,,108,1964-10-04 -3106,129,402,167,10.0,19,,18,0.0,4,,,,80,1964-10-04 -3107,129,359,167,9.0,5,,16,0.0,27,,,,5,1964-10-04 -3108,129,346,180,16.0,9,,15,0.0,37,,,,36,1964-10-04 -3109,129,403,92,11.0,10,,19,0.0,2,,,,6,1964-10-04 -3110,129,404,10,25.0,14,,13,0.0,50,,,,25,1964-10-04 -3111,129,373,169,2.0,1,,12,0.0,54,,,,98,1964-10-04 -3112,129,384,5,8.0,8,,11,0.0,58,,,,5,1964-10-04 -3113,129,433,178,23.0,18,,10,0.0,65,,,,62,1964-10-04 -3114,129,277,173,15.0,11,,14,0.0,47,,,,5,1964-10-04 -3115,130,403,92,11.0,16,12.0,12,0.0,61,,,,14,1964-10-25 -3116,130,400,92,12.0,18,,19,0.0,6,,,,25,1964-10-25 -3117,130,346,180,16.0,8,,18,0.0,9,,,,22,1964-10-25 -3118,130,345,178,22.0,13,,17,0.0,11,,,,48,1964-10-25 -3119,130,304,173,14.0,17,,16,0.0,12,,,,25,1964-10-25 -3120,130,355,180,5.0,7,,15,0.0,44,,,,10,1964-10-25 -3121,130,277,173,15.0,12,,14,0.0,46,,,,6,1964-10-25 -3122,130,288,64,3.0,6,11.0,11,0.0,63,,,,12,1964-10-25 -3123,130,433,178,23.0,19,13.0,13,0.0,60,,,,15,1964-10-25 -3124,130,402,167,10.0,15,9.0,9,0.0,63,,,,5,1964-10-25 -3125,130,385,64,4.0,11,8.0,8,0.0,64,,,,11,1964-10-25 -3126,130,359,167,9.0,10,7.0,7,0.0,64,,,,11,1964-10-25 -3127,130,344,5,18.0,9,6.0,6,1.0,64,,,,11,1964-10-25 -3128,130,372,169,1.0,1,5.0,5,2.0,64,,,,5,1964-10-25 -3129,130,373,169,2.0,5,4.0,4,3.0,65,7872180.0,,,1,1964-10-25 -3130,130,384,5,8.0,3,3.0,3,4.0,65,7859950.0,,,1,1964-10-25 -3131,130,340,5,7.0,4,2.0,2,6.0,65,7859260.0,,,1,1964-10-25 -3132,130,381,169,17.0,14,10.0,10,0.0,63,,,,12,1964-10-25 -3133,130,363,180,6.0,2,1.0,1,9.0,65,7790320.0,,,1,1964-10-25 -3134,131,339,167,17.0,18,,19,0.0,20,,,,86,1965-01-01 -3135,131,363,180,8.0,9,,20,0.0,11,,,,80,1965-01-01 -3136,131,408,183,28.0,0,,21,0.0,0,,,,81,1965-01-01 -3137,131,409,169,23.0,0,,22,0.0,0,,,,81,1965-01-01 -3138,131,411,177,27.0,0,,24,0.0,0,,,,81,1965-01-01 -3139,131,414,91,26.0,0,,29,0.0,0,,,,54,1965-01-01 -3140,131,413,169,24.0,0,,26,0.0,0,,,,97,1965-01-01 -3141,131,333,182,29.0,0,,27,0.0,0,,,,97,1965-01-01 -3142,131,292,177,32.0,0,,28,0.0,0,,,,97,1965-01-01 -3143,131,415,163,31.0,0,,30,0.0,0,,,,54,1965-01-01 -3144,131,416,167,33.0,0,,31,0.0,0,,,,54,1965-01-01 -3145,131,357,167,10.0,10,,18,0.0,39,,,,10,1965-01-01 -3146,131,412,169,22.0,0,,25,0.0,0,,,,81,1965-01-01 -3147,131,346,180,11.0,7,,17,0.0,42,,,,8,1965-01-01 -3148,131,410,181,21.0,0,,23,0.0,0,,,,81,1965-01-01 -3149,131,384,5,2.0,6,15.0,15,0.0,66,,,,80,1965-01-01 -3150,131,382,180,14.0,12,,16,0.0,50,,,,62,1965-01-01 -3151,131,372,169,5.0,1,1.0,1,9.0,85,7606000.0,,,1,1965-01-01 -3152,131,340,5,1.0,2,2.0,2,6.0,85,7635000.0,,,1,1965-01-01 -3153,131,288,64,3.0,5,3.0,3,4.0,85,7637800.0,,,1,1965-01-01 -3154,131,359,167,9.0,8,5.0,5,2.0,84,,,,11,1965-01-01 -3155,131,327,64,4.0,11,6.0,6,1.0,83,,,,12,1965-01-01 -3156,131,345,178,12.0,14,7.0,7,0.0,83,,,,12,1965-01-01 -3157,131,373,169,6.0,4,4.0,4,3.0,85,7660400.0,,,1,1965-01-01 -3158,131,405,179,18.0,16,9.0,9,0.0,81,,,,14,1965-01-01 -3159,131,361,49,20.0,17,10.0,10,0.0,79,,,,16,1965-01-01 -3160,131,407,173,15.0,13,11.0,11,0.0,77,,,,18,1965-01-01 -3161,131,379,178,16.0,15,12.0,12,0.0,75,,,,88,1965-01-01 -3162,131,367,182,25.0,20,13.0,13,0.0,73,,,,55,1965-01-01 -3163,131,406,179,19.0,19,14.0,14,0.0,71,,,,111,1965-01-01 -3164,131,355,180,7.0,3,8.0,8,0.0,81,,,,14,1965-01-01 -3165,132,355,180,1.0,2,,11,0.0,43,,,,5,1965-05-30 -3166,132,357,167,8.0,0,,17,0.0,0,,,,81,1965-05-30 -3167,132,385,10,20.0,17,,16,0.0,0,,,,86,1965-05-30 -3168,132,379,178,11.0,11,,14,0.0,29,,,,5,1965-05-30 -3169,132,404,10,19.0,15,,13,0.0,33,,,,6,1965-05-30 -3170,132,369,173,15.0,6,,12,0.0,43,,,,36,1965-05-30 -3171,132,405,169,10.0,14,10.0,10,0.0,79,,,,3,1965-05-30 -3172,132,304,173,16.0,12,,15,0.0,12,,,,6,1965-05-30 -3173,132,303,180,2.0,8,8.0,8,0.0,92,,,,18,1965-05-30 -3174,132,288,64,3.0,1,1.0,1,9.0,100,9459600.0,,,1,1965-05-30 -3175,132,384,5,17.0,4,2.0,2,6.0,100,9523600.0,,,1,1965-05-30 -3176,132,327,64,4.0,3,3.0,3,4.0,100,9561500.0,,,1,1965-05-30 -3177,132,382,180,9.0,9,9.0,9,0.0,85,,,,112,1965-05-30 -3178,132,359,167,7.0,7,5.0,5,2.0,98,,,,12,1965-05-30 -3179,132,345,178,14.0,10,6.0,6,1.0,98,,,,12,1965-05-30 -3180,132,346,180,12.0,13,7.0,7,0.0,97,,,,13,1965-05-30 -3181,132,340,5,18.0,5,4.0,4,3.0,99,,,,60,1965-05-30 -3182,133,357,167,5.0,14,11.0,11,0.0,29,,,,13,1965-06-13 -3183,133,340,5,1.0,6,,18,0.0,5,,,,5,1965-06-13 -3184,133,404,10,11.0,11,,17,0.0,9,,,,6,1965-06-13 -3185,133,346,180,20.0,7,,16,0.0,9,,,,80,1965-06-13 -3186,133,417,64,29.0,20,,15,0.0,12,,,,48,1965-06-13 -3187,133,369,173,23.0,13,14.0,14,0.0,26,,,,3,1965-06-13 -3188,133,403,173,22.0,16,13.0,13,0.0,27,,,,15,1965-06-13 -3189,133,375,64,27.0,17,12.0,12,0.0,29,,,,13,1965-06-13 -3190,133,379,178,26.0,19,,19,0.0,3,,,,80,1965-06-13 -3191,133,363,180,15.0,5,10.0,10,0.0,30,,,,12,1965-06-13 -3192,133,345,178,21.0,8,8.0,8,0.0,31,,,,11,1965-06-13 -3193,133,373,169,18.0,12,7.0,7,0.0,31,,,,11,1965-06-13 -3194,133,385,10,10.0,4,6.0,6,1.0,31,,,,11,1965-06-13 -3195,133,288,64,7.0,1,5.0,5,2.0,31,,,,11,1965-06-13 -3196,133,355,180,14.0,10,4.0,4,3.0,31,,,,11,1965-06-13 -3197,133,359,167,4.0,9,3.0,3,4.0,31,,,,11,1965-06-13 -3198,133,327,64,8.0,3,2.0,2,6.0,32,8659600.0,,,1,1965-06-13 -3199,133,372,169,17.0,2,1.0,1,9.0,32,8614800.0,,,1,1965-06-13 -3200,133,384,5,2.0,15,9.0,9,0.0,30,,,,12,1965-06-13 -3201,134,346,180,34.0,11,,11,0.0,21,,,,91,1965-06-27 -3202,134,277,173,24.0,8,,12,0.0,20,,,,69,1965-06-27 -3203,134,403,173,22.0,17,,13,0.0,18,,,,6,1965-06-27 -3204,134,357,167,20.0,12,,17,0.0,3,,,,3,1965-06-27 -3205,134,385,10,26.0,7,,15,0.0,9,,,,80,1965-06-27 -3206,134,404,10,28.0,16,,16,0.0,4,,,,80,1965-06-27 -3207,134,363,180,14.0,5,,14,0.0,16,,,,5,1965-06-27 -3208,134,359,167,18.0,9,,10,0.0,23,,,,22,1965-06-27 -3209,134,384,5,4.0,3,8.0,8,0.0,36,,,,3,1965-06-27 -3210,134,373,169,8.0,10,7.0,7,0.0,39,,,,11,1965-06-27 -3211,134,345,178,36.0,14,6.0,6,1.0,39,,,,11,1965-06-27 -3212,134,288,64,10.0,13,5.0,5,2.0,39,,,,11,1965-06-27 -3213,134,303,180,16.0,6,4.0,4,3.0,40,9871500.0,,,1,1965-06-27 -3214,134,340,5,2.0,4,3.0,3,4.0,40,9851900.0,,,1,1965-06-27 -3215,134,327,64,12.0,2,2.0,2,6.0,40,9724700.0,,,1,1965-06-27 -3216,134,372,169,6.0,1,1.0,1,9.0,40,9698400.0,,,1,1965-06-27 -3217,134,382,180,30.0,15,9.0,9,0.0,34,,,,69,1965-06-27 -3218,135,403,173,23.0,15,,15,0.0,41,,,,5,1965-07-10 -3219,135,418,167,20.0,21,,16,0.0,38,,,,80,1965-07-10 -3220,135,382,180,18.0,17,,17,0.0,33,,,,6,1965-07-10 -3221,135,303,180,14.0,10,,18,0.0,29,,,,91,1965-07-10 -3222,135,421,169,26.0,0,,23,0.0,0,,,,81,1965-07-10 -3223,135,384,5,2.0,9,,20,0.0,2,,,,5,1965-07-10 -3224,135,355,180,8.0,8,,21,0.0,0,,,,54,1965-07-10 -3225,135,357,167,10.0,12,14.0,14,0.0,62,,,,5,1965-07-10 -3226,135,385,10,11.0,3,,19,0.0,26,,,,98,1965-07-10 -3227,135,369,173,22.0,16,13.0,13,0.0,63,,,,50,1965-07-10 -3228,135,420,183,25.0,0,,22,0.0,0,,,,81,1965-07-10 -3229,135,419,178,24.0,20,11.0,11,0.0,73,,,,17,1965-07-10 -3230,135,288,64,3.0,2,2.0,2,6.0,80,7528600.0,,,1,1965-07-10 -3231,135,340,5,1.0,5,3.0,3,4.0,80,7553000.0,,,1,1965-07-10 -3232,135,373,169,6.0,6,4.0,4,3.0,80,7565000.0,,,1,1965-07-10 -3233,135,327,64,4.0,4,5.0,5,2.0,80,7600000.0,,,1,1965-07-10 -3234,135,372,169,5.0,1,1.0,1,9.0,80,7525400.0,,,1,1965-07-10 -3235,135,346,180,15.0,14,7.0,7,0.0,79,,,,11,1965-07-10 -3236,135,379,178,17.0,13,8.0,8,0.0,78,,,,12,1965-07-10 -3237,135,345,178,16.0,18,9.0,9,0.0,78,,,,12,1965-07-10 -3238,135,359,167,9.0,11,10.0,10,0.0,77,,,,13,1965-07-10 -3239,135,363,180,7.0,7,6.0,6,1.0,79,,,,11,1965-07-10 -3240,135,417,64,12.0,19,12.0,12,0.0,70,,,,88,1965-07-10 -3241,136,403,173,38.0,13,10.0,10,0.0,78,,,,12,1965-07-18 -3242,136,382,180,36.0,16,,17,0.0,11,,,,5,1965-07-18 -3243,136,346,180,26.0,15,,16,0.0,16,,,,44,1965-07-18 -3244,136,359,167,18.0,9,,15,0.0,36,,,,24,1965-07-18 -3245,136,357,167,20.0,14,,14,0.0,48,,,,51,1965-07-18 -3246,136,345,178,28.0,10,13.0,13,0.0,55,,,,113,1965-07-18 -3247,136,369,173,34.0,17,12.0,12,0.0,77,,,,13,1965-07-18 -3248,136,379,178,30.0,11,11.0,11,0.0,77,,,,13,1965-07-18 -3249,136,384,5,4.0,12,9.0,9,0.0,79,,,,11,1965-07-18 -3250,136,340,5,2.0,4,7.0,7,0.0,79,,,,11,1965-07-18 -3251,136,385,10,22.0,3,6.0,6,1.0,79,,,,11,1965-07-18 -3252,136,303,180,14.0,7,5.0,5,2.0,79,,,,11,1965-07-18 -3253,136,288,64,10.0,1,4.0,4,3.0,80,7484200.0,,,1,1965-07-18 -3254,136,363,180,16.0,5,3.0,3,4.0,80,7452100.0,,,1,1965-07-18 -3255,136,327,64,12.0,6,2.0,2,6.0,80,7447100.0,,,1,1965-07-18 -3256,136,372,169,6.0,2,1.0,1,9.0,80,7439100.0,,,1,1965-07-18 -3257,136,373,169,8.0,8,8.0,8,0.0,79,,,,11,1965-07-18 -3258,137,359,167,11.0,10,,14,0.0,7,,,,6,1965-08-01 -3259,137,303,180,6.0,13,,15,0.0,5,,,,95,1965-08-01 -3260,137,277,173,19.0,16,,16,0.0,3,,,,10,1965-08-01 -3261,137,405,169,22.0,20,,17,0.0,3,,,,44,1965-08-01 -3262,137,423,64,25.0,0,,20,0.0,0,,,,81,1965-08-01 -3263,137,327,64,10.0,2,,18,0.0,2,,,,22,1965-08-01 -3264,137,379,178,21.0,18,,19,0.0,0,,,,6,1965-08-01 -3265,137,419,180,23.0,0,,21,0.0,0,,,,81,1965-08-01 -3266,137,369,173,20.0,17,,13,0.0,8,,,,47,1965-08-01 -3267,137,422,169,3.0,12,,12,0.0,8,,,,47,1965-08-01 -3268,137,355,180,4.0,14,5.0,5,2.0,15,7953600.0,,,1,1965-08-01 -3269,137,345,178,17.0,11,,10,0.0,9,,,,5,1965-08-01 -3270,137,340,5,7.0,4,,9,0.0,11,,,,6,1965-08-01 -3271,137,417,64,24.0,19,8.0,8,0.0,14,,,,11,1965-08-01 -3272,137,346,180,16.0,9,7.0,7,0.0,15,8030900.0,,,1,1965-08-01 -3273,137,384,5,8.0,7,6.0,6,1.0,15,7981000.0,,,1,1965-08-01 -3274,137,357,167,12.0,8,4.0,4,3.0,15,7882000.0,,,1,1965-08-01 -3275,137,363,180,5.0,5,3.0,3,4.0,15,7693800.0,,,1,1965-08-01 -3276,137,288,64,9.0,3,2.0,2,6.0,15,7688300.0,,,1,1965-08-01 -3277,137,372,169,1.0,1,1.0,1,9.0,15,7672400.0,,,1,1965-08-01 -3278,137,373,169,2.0,6,,11,0.0,8,,,,7,1965-08-01 -3279,138,373,169,26.0,8,11.0,11,0.0,62,,,,91,1965-09-12 -3280,138,424,5,6.0,15,12.0,12,0.0,58,,,,5,1965-09-12 -3281,138,423,64,50.0,21,13.0,13,0.0,58,,,,51,1965-09-12 -3282,138,385,10,20.0,17,14.0,14,0.0,56,,,,80,1965-09-12 -3283,138,303,180,14.0,12,,15,0.0,46,,,,22,1965-09-12 -3284,138,379,178,46.0,16,,16,0.0,45,,,,5,1965-09-12 -3285,138,404,10,22.0,6,,20,0.0,27,,,,80,1965-09-12 -3286,138,401,169,28.0,20,,18,0.0,37,,,,6,1965-09-12 -3287,138,340,5,8.0,2,,19,0.0,34,,,,8,1965-09-12 -3288,138,372,169,24.0,1,10.0,10,0.0,63,,,,48,1965-09-12 -3289,138,417,64,48.0,23,,21,0.0,22,,,,6,1965-09-12 -3290,138,393,180,10.0,19,,22,0.0,12,,,,5,1965-09-12 -3291,138,425,64,52.0,22,,23,0.0,8,,,,5,1965-09-12 -3292,138,345,178,44.0,10,,17,0.0,43,,,,6,1965-09-12 -3293,138,403,173,38.0,18,9.0,9,0.0,74,,,,12,1965-09-12 -3294,138,384,5,4.0,5,4.0,4,3.0,76,7568700.0,,,1,1965-09-12 -3295,138,346,180,42.0,14,7.0,7,0.0,74,,,,12,1965-09-12 -3296,138,369,173,40.0,13,6.0,6,1.0,75,,,,11,1965-09-12 -3297,138,359,167,16.0,11,5.0,5,2.0,75,,,,11,1965-09-12 -3298,138,363,180,12.0,9,3.0,3,4.0,76,7509300.0,,,1,1965-09-12 -3299,138,288,64,30.0,4,2.0,2,6.0,76,7496100.0,,,1,1965-09-12 -3300,138,327,64,32.0,3,1.0,1,9.0,76,7492800.0,,,1,1965-09-12 -3301,138,357,167,18.0,7,8.0,8,0.0,74,,,,12,1965-09-12 -3302,139,395,5,24.0,14,9.0,9,0.0,106,,,,14,1965-10-03 -3303,139,403,173,22.0,18,,18,0.0,9,,,,100,1965-10-03 -3304,139,373,169,6.0,4,,17,0.0,9,,,,5,1965-10-03 -3305,139,359,167,9.0,2,,16,0.0,11,,,,51,1965-10-03 -3306,139,381,169,18.0,17,12.0,12,0.0,95,,,,112,1965-10-03 -3307,139,327,64,4.0,6,,14,0.0,12,,,,22,1965-10-03 -3308,139,404,10,12.0,12,13.0,13,0.0,92,,,,114,1965-10-03 -3309,139,345,178,16.0,11,11.0,11,0.0,99,,,,45,1965-10-03 -3310,139,369,173,21.0,16,10.0,10,0.0,101,,,,19,1965-10-03 -3311,139,372,169,5.0,9,,15,0.0,11,,,,5,1965-10-03 -3312,139,346,180,15.0,10,8.0,8,0.0,107,,,,13,1965-10-03 -3313,139,385,10,11.0,3,7.0,7,0.0,108,,,,12,1965-10-03 -3314,139,355,180,7.0,7,3.0,3,4.0,110,8493600.0,,,1,1965-10-03 -3315,139,344,5,14.0,15,5.0,5,2.0,109,,,,11,1965-10-03 -3316,139,357,167,10.0,13,6.0,6,1.0,108,,,,12,1965-10-03 -3317,139,363,180,8.0,8,2.0,2,6.0,110,8448600.0,,,1,1965-10-03 -3318,139,288,64,3.0,1,1.0,1,9.0,110,8436100.0,,,1,1965-10-03 -3319,139,384,5,2.0,5,4.0,4,3.0,109,,,,11,1965-10-03 -3320,140,344,5,14.0,14,7.0,7,0.0,62,,,,13,1965-10-24 -3321,140,384,5,2.0,7,8.0,8,0.0,62,,,,13,1965-10-24 -3322,140,288,64,3.0,5,,9,0.0,56,,,,5,1965-10-24 -3323,140,381,169,18.0,9,,10,0.0,55,,,,80,1965-10-24 -3324,140,374,5,24.0,0,,19,0.0,0,,,,54,1965-10-24 -3325,140,372,169,5.0,1,,17,0.0,8,,,,5,1965-10-24 -3326,140,369,173,21.0,17,6.0,6,1.0,64,,,,11,1965-10-24 -3327,140,359,167,9.0,15,,16,0.0,25,,,,6,1965-10-24 -3328,140,395,173,22.0,18,,15,0.0,29,,,,22,1965-10-24 -3329,140,327,64,4.0,8,,14,0.0,35,,,,8,1965-10-24 -3330,140,355,180,7.0,14,,13,0.0,38,,,,44,1965-10-24 -3331,140,403,173,22.0,0,,18,0.0,0,,,,54,1965-10-24 -3332,140,357,167,10.0,16,,12,0.0,39,,,,80,1965-10-24 -3333,140,346,180,15.0,12,,11,0.0,43,,,,22,1965-10-24 -3334,140,385,10,11.0,3,1.0,1,9.0,65,7712100.0,,,1,1965-10-24 -3335,140,363,180,8.0,2,2.0,2,6.0,65,7714990.0,,,1,1965-10-24 -3336,140,373,169,6.0,6,3.0,3,4.0,65,7772250.0,,,1,1965-10-24 -3337,140,345,178,16.0,11,4.0,4,3.0,65,7826520.0,,,1,1965-10-24 -3338,140,404,10,12.0,10,5.0,5,2.0,64,,,,11,1965-10-24 -3339,141,372,169,4.0,1,,8,0.0,60,,,,22,1966-05-22 -3340,141,382,180,15.0,8,,16,0.0,3,,,,5,1966-05-22 -3341,141,359,184,2.0,10,,15,0.0,9,,,,44,1966-05-22 -3342,141,303,180,8.0,6,,14,0.0,15,,,,7,1966-05-22 -3343,141,340,5,17.0,2,,13,0.0,16,,,,7,1966-05-22 -3344,141,355,188,7.0,11,,12,0.0,17,,,,6,1966-05-22 -3345,141,373,173,6.0,12,,11,0.0,34,,,,22,1966-05-22 -3346,141,345,178,14.0,13,,10,0.0,35,,,,8,1966-05-22 -3347,141,357,163,10.0,7,,9,0.0,56,,,,5,1966-05-22 -3348,141,327,64,12.0,3,1.0,1,9.0,100,9190500.0,,,1,1966-05-22 -3349,141,384,5,16.0,5,2.0,2,6.0,100,9230700.0,,,1,1966-05-22 -3350,141,288,64,11.0,4,3.0,3,4.0,99,,,,11,1966-05-22 -3351,141,395,64,19.0,16,4.0,4,3.0,95,,,,15,1966-05-22 -3352,141,385,163,9.0,9,,5,0.0,80,,,,7,1966-05-22 -3353,141,346,163,18.0,16,,7,0.0,73,,,,62,1966-05-22 -3354,141,388,163,21.0,15,,6,0.0,75,,,,62,1966-05-22 -3355,142,373,173,16.0,7,,10,0.0,0,,,,3,1966-06-12 -3356,142,288,64,14.0,9,,11,0.0,0,,,,3,1966-06-12 -3357,142,396,173,11.0,0,,17,0.0,0,,,,5,1966-06-12 -3358,142,359,185,24.0,0,,16,0.0,0,,,,54,1966-06-12 -3359,142,303,180,4.0,13,,14,0.0,0,,,,3,1966-06-12 -3360,142,395,64,8.0,11,,13,0.0,0,,,,3,1966-06-12 -3361,142,372,169,10.0,10,,12,0.0,0,,,,5,1966-06-12 -3362,142,340,5,6.0,1,1.0,1,9.0,28,7751300.0,,,1,1966-06-12 -3363,142,357,163,19.0,2,2.0,2,6.0,28,7793400.0,,,1,1966-06-12 -3364,142,384,5,7.0,5,3.0,3,4.0,27,,,,11,1966-06-12 -3365,142,355,188,3.0,4,4.0,4,3.0,26,,,,12,1966-06-12 -3366,142,385,163,18.0,8,5.0,5,2.0,25,,,,13,1966-06-12 -3367,142,388,163,22.0,12,,6,0.0,24,,,,62,1966-06-12 -3368,142,363,186,27.0,15,,7,0.0,23,,,,62,1966-06-12 -3369,142,327,64,15.0,3,,8,0.0,0,,,,3,1966-06-12 -3370,142,346,163,20.0,6,,9,0.0,0,,,,3,1966-06-12 -3371,142,397,64,8.0,0,,18,0.0,0,,,,54,1966-06-12 -3372,142,345,163,21.0,14,,15,0.0,0,,,,3,1966-06-12 -3373,143,373,173,32.0,10,,15,0.0,8,,,,8,1966-07-03 -3374,143,386,5,22.0,3,2.0,2,6.0,48,6520800.0,,,1,1966-07-03 -3375,143,355,188,12.0,4,1.0,1,9.0,48,6511300.0,,,1,1966-07-03 -3376,143,303,188,14.0,9,3.0,3,4.0,46,,,,12,1966-07-03 -3377,143,357,163,6.0,5,4.0,4,3.0,46,,,,12,1966-07-03 -3378,143,363,186,26.0,14,5.0,5,2.0,45,,,,13,1966-07-03 -3379,143,398,178,44.0,15,6.0,6,1.0,45,,,,13,1966-07-03 -3380,143,382,180,36.0,12,7.0,7,0.0,44,,,,14,1966-07-03 -3381,143,388,163,42.0,11,,9,0.0,42,,,,62,1966-07-03 -3382,143,344,169,2.0,13,,10,0.0,40,,,,44,1966-07-03 -3383,143,277,163,8.0,7,8.0,8,0.0,44,,,,14,1966-07-03 -3384,143,346,180,30.0,17,,12,0.0,32,,,,62,1966-07-03 -3385,143,288,64,16.0,8,,13,0.0,13,,,,5,1966-07-03 -3386,143,345,163,38.0,6,,14,0.0,10,,,,69,1966-07-03 -3387,143,340,163,10.0,2,,16,0.0,5,,,,69,1966-07-03 -3388,143,396,173,4.0,16,,17,0.0,3,,,,6,1966-07-03 -3389,143,384,5,20.0,1,,11,0.0,37,,,,62,1966-07-03 -3390,144,345,163,20.0,11,,13,0.0,70,,,,62,1966-07-16 -3391,144,398,178,22.0,16,8.0,8,0.0,76,,,,14,1966-07-16 -3392,144,395,64,25.0,14,9.0,9,0.0,76,,,,14,1966-07-16 -3393,144,387,180,7.0,12,7.0,7,0.0,78,,,,12,1966-07-16 -3394,144,388,163,19.0,17,10.0,10,0.0,75,,,,15,1966-07-16 -3395,144,399,189,24.0,19,11.0,11,0.0,73,,,,17,1966-07-16 -3396,144,382,180,21.0,10,,12,0.0,70,,,,62,1966-07-16 -3397,144,340,163,12.0,6,,14,0.0,67,,,,7,1966-07-16 -3398,144,288,64,3.0,4,3.0,3,4.0,79,,,,11,1966-07-16 -3399,144,396,173,2.0,20,,16,0.0,32,,,,6,1966-07-16 -3400,144,327,64,4.0,8,,17,0.0,17,,,,5,1966-07-16 -3401,144,373,173,17.0,9,,18,0.0,15,,,,44,1966-07-16 -3402,144,363,186,16.0,3,,19,0.0,9,,,,5,1966-07-16 -3403,144,400,89,23.0,18,,20,0.0,0,,,,5,1966-07-16 -3404,144,357,163,11.0,7,5.0,5,2.0,79,,,,11,1966-07-16 -3405,144,355,188,5.0,1,1.0,1,9.0,80,7993400.0,,,1,1966-07-16 -3406,144,303,188,6.0,2,2.0,2,6.0,80,8003000.0,,,1,1966-07-16 -3407,144,346,180,18.0,15,,15,0.0,42,,,,8,1966-07-16 -3408,144,359,185,14.0,13,6.0,6,1.0,78,,,,12,1966-07-16 -3409,144,372,169,1.0,5,4.0,4,3.0,79,,,,11,1966-07-16 -3410,145,288,64,12.0,7,2.0,2,6.0,89,,,,11,1966-07-24 -3411,145,357,163,26.0,6,,17,0.0,2,,,,3,1966-07-24 -3412,145,363,186,10.0,4,,15,0.0,26,,,,44,1966-07-24 -3413,145,396,173,8.0,15,,14,0.0,28,,,,80,1966-07-24 -3414,145,303,188,18.0,2,,13,0.0,37,,,,80,1966-07-24 -3415,145,340,163,24.0,10,,12,0.0,44,,,,10,1966-07-24 -3416,145,382,180,34.0,14,,11,0.0,73,,,,22,1966-07-24 -3417,145,345,163,28.0,11,,10,0.0,79,,,,5,1966-07-24 -3418,145,386,5,4.0,5,,16,0.0,10,,,,3,1966-07-24 -3419,145,398,178,38.0,17,8.0,8,0.0,84,,,,16,1966-07-24 -3420,145,372,169,6.0,3,3.0,3,4.0,88,,,,12,1966-07-24 -3421,145,388,163,36.0,16,9.0,9,0.0,84,,,,16,1966-07-24 -3422,145,327,64,14.0,8,4.0,4,3.0,88,,,,12,1966-07-24 -3423,145,355,188,16.0,1,1.0,1,9.0,90,8432500.0,,,1,1966-07-24 -3424,145,384,5,2.0,9,6.0,6,1.0,87,,,,13,1966-07-24 -3425,145,346,163,30.0,13,7.0,7,0.0,84,,,,16,1966-07-24 -3426,145,373,173,32.0,12,5.0,5,2.0,87,,,,13,1966-07-24 -3427,146,303,188,4.0,15,,14,0.0,8,,,,80,1966-08-07 -3428,146,340,163,7.0,2,2.0,2,6.0,15,8867400.0,,,1,1966-08-07 -3429,146,357,163,8.0,9,3.0,3,4.0,15,8975600.0,,,1,1966-08-07 -3430,146,288,64,5.0,10,4.0,4,3.0,15,9224400.0,,,1,1966-08-07 -3431,146,384,5,9.0,6,6.0,6,1.0,15,9479400.0,,,1,1966-08-07 -3432,146,363,186,12.0,8,7.0,7,0.0,14,,,,10,1966-08-07 -3433,146,396,173,2.0,17,8.0,8,0.0,14,,,,11,1966-08-07 -3434,146,373,173,15.0,13,,9,0.0,12,,,,91,1966-08-07 -3435,146,399,189,20.0,26,,11,0.0,10,,,,22,1966-08-07 -3436,146,374,5,11.0,4,,12,0.0,9,,,,10,1966-08-07 -3437,146,386,5,10.0,7,,13,0.0,9,,,,3,1966-08-07 -3438,146,327,64,6.0,3,5.0,5,2.0,15,9331900.0,,,1,1966-08-07 -3439,146,372,169,1.0,1,,10,0.0,11,,,,3,1966-08-07 -3440,146,382,180,19.0,14,,17,0.0,2,,,,7,1966-08-07 -3441,146,395,64,14.0,11,,16,0.0,3,,,,5,1966-08-07 -3442,146,388,163,18.0,0,,19,0.0,0,,,,82,1966-08-07 -3443,146,346,163,17.0,12,,15,0.0,3,,,,8,1966-08-07 -3444,146,355,188,3.0,5,1.0,1,9.0,15,8823000.0,,,1,1966-08-07 -3445,146,398,178,16.0,25,,18,0.0,0,,,,3,1966-08-07 -3446,147,374,5,6.0,2,1.0,1,9.0,68,6434800.0,,,1,1966-09-04 -3447,147,277,178,32.0,0,,22,0.0,0,,,,81,1966-09-04 -3448,147,402,186,34.0,0,,21,0.0,0,,,,81,1966-09-04 -3449,147,288,64,26.0,11,,20,0.0,0,,,,5,1966-09-04 -3450,147,346,163,38.0,12,,19,0.0,3,,,,37,1966-09-04 -3451,147,327,64,28.0,9,,18,0.0,5,,,,95,1966-09-04 -3452,147,363,187,30.0,19,,17,0.0,7,,,,5,1966-09-04 -3453,147,355,188,10.0,6,,16,0.0,7,,,,44,1966-09-04 -3454,147,385,10,18.0,7,,15,0.0,16,,,,3,1966-09-04 -3455,147,340,163,14.0,4,,14,0.0,31,,,,95,1966-09-04 -3456,147,384,5,2.0,5,,13,0.0,33,,,,80,1966-09-04 -3457,147,393,5,44.0,16,,10,0.0,59,,,,62,1966-09-04 -3458,147,401,169,20.0,20,9.0,9,0.0,63,,,,15,1966-09-04 -3459,147,396,173,24.0,13,8.0,8,0.0,63,,,,5,1966-09-04 -3460,147,395,64,48.0,18,7.0,7,0.0,65,,,,13,1966-09-04 -3461,147,382,180,40.0,15,6.0,6,1.0,66,,,,12,1966-09-04 -3462,147,373,173,42.0,14,5.0,5,2.0,67,,,,11,1966-09-04 -3463,147,357,163,16.0,8,4.0,4,3.0,67,,,,11,1966-09-04 -3464,147,303,188,12.0,10,3.0,3,4.0,68,6440900.0,,,1,1966-09-04 -3465,147,386,5,4.0,1,2.0,2,6.0,68,6440600.0,,,1,1966-09-04 -3466,147,345,163,36.0,17,,12,0.0,46,,,,5,1966-09-04 -3467,147,372,173,22.0,3,,11,0.0,58,,,,6,1966-09-04 -3468,148,340,163,7.0,4,3.0,3,4.0,107,,,,11,1966-10-02 -3469,148,357,163,8.0,9,2.0,2,6.0,107,,,,60,1966-10-02 -3470,148,363,187,15.0,14,,18,0.0,13,,,,8,1966-10-02 -3471,148,372,173,1.0,2,1.0,1,9.0,108,7780110.0,,,1,1966-10-02 -3472,148,345,163,19.0,13,4.0,4,3.0,105,,,,13,1966-10-02 -3473,148,359,184,17.0,11,5.0,5,2.0,105,,,,13,1966-10-02 -3474,148,396,169,2.0,19,6.0,6,1.0,101,,,,17,1966-10-02 -3475,148,385,10,12.0,8,,8,0.0,81,,,,62,1966-10-02 -3476,148,373,173,18.0,12,,9,0.0,74,,,,80,1966-10-02 -3477,148,404,10,14.0,18,,10,0.0,58,,,,5,1966-10-02 -3478,148,403,64,10.0,17,,7,0.0,96,,,,91,1966-10-02 -3479,148,355,188,5.0,1,,12,0.0,55,,,,5,1966-10-02 -3480,148,395,186,16.0,16,,19,0.0,5,,,,2,1966-10-02 -3481,148,327,64,4.0,6,,13,0.0,53,,,,5,1966-10-02 -3482,148,288,64,3.0,5,,14,0.0,52,,,,24,1966-10-02 -3483,148,384,5,9.0,3,,15,0.0,34,,,,5,1966-10-02 -3484,148,303,188,6.0,7,,16,0.0,18,,,,5,1966-10-02 -3485,148,344,173,11.0,10,,17,0.0,13,,,,31,1966-10-02 -3486,148,346,163,22.0,15,,11,0.0,57,,,,62,1966-10-02 -3487,149,357,163,8.0,5,,12,0.0,32,,,,22,1966-10-23 -3488,149,381,163,9.0,15,,18,0.0,9,,,,25,1966-10-23 -3489,149,372,173,1.0,2,,17,0.0,9,,,,6,1966-10-23 -3490,149,288,64,3.0,7,,16,0.0,18,,,,5,1966-10-23 -3491,149,395,187,16.0,18,,15,0.0,24,,,,69,1966-10-23 -3492,149,327,64,4.0,10,,14,0.0,26,,,,44,1966-10-23 -3493,149,403,64,10.0,16,,13,0.0,28,,,,7,1966-10-23 -3494,149,345,163,19.0,11,,11,0.0,33,,,,22,1966-10-23 -3495,149,396,173,2.0,17,7.0,7,0.0,61,,,,14,1966-10-23 -3496,149,344,173,11.0,8,,9,0.0,49,,,,24,1966-10-23 -3497,149,404,10,14.0,13,8.0,8,0.0,60,,,,15,1966-10-23 -3498,149,346,163,22.0,12,6.0,6,1.0,63,,,,12,1966-10-23 -3499,149,363,186,15.0,9,5.0,5,2.0,64,,,,11,1966-10-23 -3500,149,385,10,12.0,3,4.0,4,3.0,64,,,,11,1966-10-23 -3501,149,303,188,6.0,6,3.0,3,4.0,64,,,,11,1966-10-23 -3502,149,355,188,5.0,4,2.0,2,6.0,65,7603220.0,,,1,1966-10-23 -3503,149,340,163,7.0,1,1.0,1,9.0,65,7595340.0,,,1,1966-10-23 -3504,149,359,184,17.0,14,,10,0.0,40,,,,5,1966-10-23 -3505,150,355,188,1.0,1,6.0,6,1.0,76,,,,14,1967-01-02 -3506,150,292,180,19.0,8,,7,0.0,63,,,,62,1967-01-02 -3507,150,383,180,20.0,17,,8,0.0,60,,,,62,1967-01-02 -3508,150,367,181,18.0,14,,9,0.0,56,,,,3,1967-01-02 -3509,150,360,173,16.0,18,,10,0.0,51,,,,69,1967-01-02 -3510,150,363,186,9.0,11,,11,0.0,44,,,,22,1967-01-02 -3511,150,346,163,15.0,12,,15,0.0,30,,,,5,1967-01-02 -3512,150,357,163,3.0,7,,13,0.0,38,,,,5,1967-01-02 -3513,150,373,64,6.0,13,,14,0.0,31,,,,44,1967-01-02 -3514,150,382,180,14.0,10,5.0,5,2.0,78,,,,12,1967-01-02 -3515,150,372,173,7.0,3,,16,0.0,22,,,,5,1967-01-02 -3516,150,327,64,5.0,9,,18,0.0,2,,,,5,1967-01-02 -3517,150,345,163,12.0,16,,12,0.0,41,,,,5,1967-01-02 -3518,150,340,10,11.0,6,3.0,3,4.0,79,,,,11,1967-01-02 -3519,150,288,173,8.0,15,,17,0.0,6,,,,3,1967-01-02 -3520,150,303,188,2.0,2,4.0,4,3.0,78,,,,12,1967-01-02 -3521,150,344,163,4.0,4,1.0,1,9.0,80,7545900.0,,,1,1967-01-02 -3522,150,339,167,17.0,5,2.0,2,6.0,80,7572300.0,,,1,1967-01-02 -3523,151,344,163,11.0,16,5.0,5,2.0,96,,,,14,1967-05-07 -3524,151,373,64,5.0,12,6.0,6,1.0,96,,,,14,1967-05-07 -3525,151,384,5,18.0,2,,7,0.0,81,,,,3,1967-05-07 -3526,151,360,64,6.0,13,,8,0.0,64,,,,20,1967-05-07 -3527,151,372,169,12.0,5,,9,0.0,42,,,,22,1967-05-07 -3528,151,359,191,16.0,10,4.0,4,3.0,98,,,,13,1967-05-07 -3529,151,340,10,7.0,3,,10,0.0,32,,,,5,1967-05-07 -3530,151,357,163,10.0,15,,13,0.0,14,,,,6,1967-05-07 -3531,151,363,187,23.0,7,,14,0.0,4,,,,48,1967-05-07 -3532,151,358,80,2.0,11,,15,0.0,4,,,,98,1967-05-07 -3533,151,355,188,8.0,1,,16,0.0,0,,,,5,1967-05-07 -3534,151,382,180,15.0,0,,17,0.0,0,,,,81,1967-05-07 -3535,151,305,80,1.0,0,,18,0.0,0,,,,81,1967-05-07 -3536,151,385,186,22.0,0,,19,0.0,0,,,,81,1967-05-07 -3537,151,327,64,4.0,6,,12,0.0,14,,,,24,1967-05-07 -3538,151,277,5,20.0,14,3.0,3,4.0,98,,,,12,1967-05-07 -3539,151,345,163,17.0,9,,11,0.0,31,,,,51,1967-05-07 -3540,151,303,188,9.0,4,1.0,1,9.0,100,9274300.0,,,1,1967-05-07 -3541,151,288,173,14.0,8,2.0,2,6.0,99,,,,11,1967-05-07 -3542,152,363,187,15.0,2,,16,0.0,8,,,,98,1967-06-04 -3543,152,288,177,6.0,1,,15,0.0,11,,,,5,1967-06-04 -3544,152,344,163,14.0,5,,14,0.0,39,,,,6,1967-06-04 -3545,152,357,163,12.0,4,,13,0.0,41,,,,22,1967-06-04 -3546,152,327,64,9.0,11,,12,0.0,51,,,,23,1967-06-04 -3547,152,340,10,7.0,6,,11,0.0,73,,,,37,1967-06-04 -3548,152,303,188,2.0,7,3.0,3,4.0,90,8110800.0,,,1,1967-06-04 -3549,152,382,180,21.0,17,9.0,9,0.0,86,,,,14,1967-06-04 -3550,152,373,64,10.0,12,8.0,8,0.0,87,,,,13,1967-06-04 -3551,152,387,173,18.0,13,7.0,7,0.0,88,,,,12,1967-06-04 -3552,152,374,5,22.0,15,6.0,6,1.0,89,,,,11,1967-06-04 -3553,152,386,5,4.0,10,5.0,5,2.0,89,,,,11,1967-06-04 -3554,152,277,5,3.0,9,4.0,4,3.0,90,8112400.0,,,1,1967-06-04 -3555,152,359,191,17.0,14,,17,0.0,1,,,,3,1967-06-04 -3556,152,345,163,20.0,16,10.0,10,0.0,83,,,,17,1967-06-04 -3557,152,355,188,1.0,3,2.0,2,6.0,90,8108700.0,,,1,1967-06-04 -3558,152,372,177,5.0,8,1.0,1,9.0,90,8085100.0,,,1,1967-06-04 -3559,153,372,177,21.0,1,6.0,6,1.0,27,,,,11,1967-06-18 -3560,153,386,5,3.0,8,,18,0.0,0,,,,3,1967-06-18 -3561,153,387,64,17.0,15,,17,0.0,1,,,,5,1967-06-18 -3562,153,340,10,7.0,10,,16,0.0,1,,,,5,1967-06-18 -3563,153,288,177,22.0,3,,15,0.0,3,,,,8,1967-06-18 -3564,153,346,163,39.0,12,,14,0.0,10,,,,5,1967-06-18 -3565,153,303,188,26.0,14,,13,0.0,14,,,,5,1967-06-18 -3566,153,373,64,12.0,11,5.0,5,2.0,27,,,,11,1967-06-18 -3567,153,374,5,2.0,9,,11,0.0,24,,,,62,1967-06-18 -3568,153,388,163,32.0,18,10.0,10,0.0,25,,,,13,1967-06-18 -3569,153,344,163,30.0,13,9.0,9,0.0,25,,,,5,1967-06-18 -3570,153,382,180,19.0,17,8.0,8,0.0,26,,,,12,1967-06-18 -3571,153,345,163,34.0,16,7.0,7,0.0,27,,,,11,1967-06-18 -3572,153,327,64,14.0,6,2.0,2,6.0,28,6112400.0,,,1,1967-06-18 -3573,153,355,188,25.0,7,,12,0.0,15,,,,5,1967-06-18 -3574,153,357,163,29.0,4,4.0,4,3.0,28,6183300.0,,,1,1967-06-18 -3575,153,363,187,36.0,2,1.0,1,9.0,28,6049400.0,,,1,1967-06-18 -3576,153,277,5,1.0,5,3.0,3,4.0,28,6149400.0,,,1,1967-06-18 -3577,154,277,5,2.0,7,,8,0.0,47,,,,37,1967-07-02 -3578,154,355,188,3.0,2,1.0,1,9.0,80,8001300.0,,,1,1967-07-02 -3579,154,303,188,4.0,6,2.0,2,6.0,80,8050800.0,,,1,1967-07-02 -3580,154,327,64,10.0,10,3.0,3,4.0,79,,,,11,1967-07-02 -3581,154,345,163,18.0,11,4.0,4,3.0,77,,,,13,1967-07-02 -3582,154,387,64,15.0,9,5.0,5,2.0,76,,,,5,1967-07-02 -3583,154,344,163,14.0,13,6.0,6,1.0,76,,,,14,1967-07-02 -3584,154,388,163,16.0,15,,7,0.0,68,,,,62,1967-07-02 -3585,154,373,64,11.0,12,,15,0.0,9,,,,86,1967-07-02 -3586,154,363,187,9.0,3,,9,0.0,40,,,,95,1967-07-02 -3587,154,357,163,12.0,8,,10,0.0,33,,,,5,1967-07-02 -3588,154,359,187,8.0,5,,11,0.0,26,,,,80,1967-07-02 -3589,154,372,177,6.0,4,,12,0.0,23,,,,24,1967-07-02 -3590,154,382,180,17.0,14,,13,0.0,16,,,,80,1967-07-02 -3591,154,288,177,7.0,1,,14,0.0,13,,,,24,1967-07-02 -3592,155,277,5,8.0,6,3.0,3,4.0,80,7182200.0,,,1,1967-07-15 -3593,155,372,177,5.0,1,1.0,1,9.0,80,7165600.0,,,1,1967-07-15 -3594,155,303,188,2.0,4,2.0,2,6.0,80,7178400.0,,,1,1967-07-15 -3595,155,387,64,15.0,13,7.0,7,0.0,77,,,,13,1967-07-15 -3596,155,355,188,1.0,3,4.0,4,3.0,80,7187400.0,,,1,1967-07-15 -3597,155,360,64,16.0,0,,21,0.0,0,,,,54,1967-07-15 -3598,155,346,163,23.0,9,,20,0.0,0,,,,5,1967-07-15 -3599,155,345,163,17.0,18,,19,0.0,10,,,,5,1967-07-15 -3600,155,359,187,10.0,10,,18,0.0,14,,,,5,1967-07-15 -3601,155,327,64,3.0,12,,17,0.0,20,,,,7,1967-07-15 -3602,155,357,163,11.0,8,,16,0.0,26,,,,5,1967-07-15 -3603,155,350,190,22.0,20,,15,0.0,29,,,,51,1967-07-15 -3604,155,363,187,9.0,5,,14,0.0,34,,,,8,1967-07-15 -3605,155,373,64,4.0,11,,13,0.0,44,,,,80,1967-07-15 -3606,155,288,177,6.0,2,,12,0.0,64,,,,5,1967-07-15 -3607,155,382,180,19.0,17,,11,0.0,67,,,,5,1967-07-15 -3608,155,388,188,18.0,21,10.0,10,0.0,76,,,,14,1967-07-15 -3609,155,389,163,14.0,15,9.0,9,0.0,76,,,,14,1967-07-15 -3610,155,321,64,20.0,14,8.0,8,0.0,77,,,,13,1967-07-15 -3611,155,344,163,12.0,9,5.0,5,2.0,79,,,,11,1967-07-15 -3612,155,340,10,7.0,7,6.0,6,1.0,78,,,,12,1967-07-15 -3613,156,378,88,26.0,23,,21,0.0,4,,,,21,1967-08-06 -3614,156,327,64,11.0,3,,18,0.0,5,,,,24,1967-08-06 -3615,156,373,64,12.0,11,,23,0.0,3,,,,24,1967-08-06 -3616,156,303,188,2.0,2,1.0,1,9.0,15,7555700.0,,,1,1967-08-06 -3617,156,355,188,1.0,7,2.0,2,6.0,15,7594200.0,,,1,1967-08-06 -3618,156,277,5,8.0,8,3.0,3,4.0,15,7594700.0,,,1,1967-08-06 -3619,156,340,10,7.0,6,4.0,4,3.0,15,7701400.0,,,1,1967-08-06 -3620,156,261,177,24.0,19,5.0,5,0.0,15,7886400.0,,,1,1967-08-06 -3621,156,346,163,16.0,16,6.0,6,2.0,15,8077800.0,,,1,1967-08-06 -3622,156,389,179,22.0,20,7.0,7,0.0,15,8083600.0,,,1,1967-08-06 -3623,156,376,80,23.0,21,,24,0.0,2,,,,5,1967-08-06 -3624,156,387,64,18.0,15,9.0,9,0.0,13,,,,12,1967-08-06 -3625,156,321,25,27.0,22,10.0,10,0.0,13,,,,12,1967-08-06 -3626,156,388,188,15.0,17,8.0,8,1.0,14,,,,11,1967-08-06 -3627,156,363,187,9.0,4,,12,0.0,12,,,,86,1967-08-06 -3628,156,359,187,10.0,5,,22,0.0,3,,,,44,1967-08-06 -3629,156,344,163,6.0,10,11.0,11,0.0,13,,,,12,1967-08-06 -3630,156,372,177,3.0,1,,19,0.0,4,,,,22,1967-08-06 -3631,156,364,25,17.0,14,,17,0.0,6,,,,22,1967-08-06 -3632,156,357,163,5.0,9,,20,0.0,4,,,,21,1967-08-06 -3633,156,345,163,14.0,12,,15,0.0,12,,,,48,1967-08-06 -3634,156,390,88,25.0,25,,14,0.0,12,,,,13,1967-08-06 -3635,156,234,80,29.0,18,,13,0.0,12,,,,22,1967-08-06 -3636,156,288,177,4.0,13,,16,0.0,8,,,,22,1967-08-06 -3637,157,325,177,5.0,16,,13,0.0,69,,,,2,1967-08-27 -3638,157,392,167,41.0,0,,18,0.0,0,,,,81,1967-08-27 -3639,157,357,163,71.0,8,,17,0.0,4,,,,80,1967-08-27 -3640,157,387,64,17.0,11,,16,0.0,18,,,,20,1967-08-27 -3641,157,370,186,11.0,15,,15,0.0,47,,,,62,1967-08-27 -3642,157,327,64,15.0,9,,14,0.0,65,,,,37,1967-08-27 -3643,157,372,177,3.0,1,,12,0.0,69,,,,80,1967-08-27 -3644,157,346,163,9.0,14,8.0,8,0.0,85,,,,15,1967-08-27 -3645,157,369,163,8.0,13,10.0,10,0.0,84,,,,16,1967-08-27 -3646,157,391,173,6.0,17,11.0,11,0.0,81,,,,19,1967-08-27 -3647,157,355,188,1.0,7,1.0,1,9.0,90,9640000.0,,,1,1967-08-27 -3648,157,363,187,10.0,5,3.0,3,4.0,89,,,,11,1967-08-27 -3649,157,288,177,4.0,2,4.0,4,3.0,88,,,,12,1967-08-27 -3650,157,303,188,2.0,3,2.0,2,6.0,90,9701900.0,,,1,1967-08-27 -3651,157,277,5,20.0,4,6.0,6,1.0,87,,,,13,1967-08-27 -3652,157,321,64,12.0,12,9.0,9,0.0,85,,,,15,1967-08-27 -3653,157,359,191,19.0,6,7.0,7,0.0,86,,,,14,1967-08-27 -3654,157,373,64,16.0,10,5.0,5,2.0,87,,,,13,1967-08-27 -3655,158,234,163,32.0,15,6.0,6,1.0,66,,,,12,1967-09-10 -3656,158,277,5,2.0,4,7.0,7,0.0,64,,,,14,1967-09-10 -3657,158,345,163,6.0,13,,9,0.0,50,,,,3,1967-09-10 -3658,158,393,177,24.0,17,,10,0.0,50,,,,5,1967-09-10 -3659,158,359,191,4.0,3,,11,0.0,46,,,,5,1967-09-10 -3660,158,327,64,34.0,7,,13,0.0,45,,,,5,1967-09-10 -3661,158,303,188,18.0,6,,14,0.0,30,,,,25,1967-09-10 -3662,158,363,187,8.0,5,,18,0.0,4,,,,5,1967-09-10 -3663,158,373,64,36.0,12,5.0,5,2.0,67,,,,11,1967-09-10 -3664,158,388,188,12.0,18,,15,0.0,26,,,,5,1967-09-10 -3665,158,387,64,38.0,16,,16,0.0,16,,,,98,1967-09-10 -3666,158,374,187,10.0,10,,17,0.0,5,,,,5,1967-09-10 -3667,158,346,163,26.0,14,,12,0.0,46,,,,25,1967-09-10 -3668,158,357,163,30.0,11,4.0,4,3.0,68,6281600.0,,,1,1967-09-10 -3669,158,288,177,22.0,8,,8,0.0,58,,,,5,1967-09-10 -3670,158,340,10,14.0,9,1.0,1,9.0,68,6225000.0,,,1,1967-09-10 -3671,158,355,188,16.0,2,2.0,2,6.0,68,6225200.0,,,1,1967-09-10 -3672,158,372,177,20.0,1,3.0,3,4.0,68,6248100.0,,,1,1967-09-10 -3673,159,288,177,6.0,1,2.0,2,6.0,108,7399500.0,,,1,1967-10-01 -3674,159,303,188,2.0,6,3.0,3,4.0,107,,,,11,1967-10-01 -3675,159,346,163,16.0,15,6.0,6,1.0,101,,,,17,1967-10-01 -3676,159,372,177,5.0,2,1.0,1,9.0,108,7393200.0,,,1,1967-10-01 -3677,159,305,184,22.0,18,7.0,7,0.0,101,,,,17,1967-10-01 -3678,159,340,10,3.0,11,,8,0.0,96,,,,91,1967-10-01 -3679,159,277,5,9.0,4,,9,0.0,95,,,,5,1967-10-01 -3680,159,327,64,7.0,10,,10,0.0,72,,,,98,1967-10-01 -3681,159,234,163,21.0,16,,11,0.0,45,,,,25,1967-10-01 -3682,159,388,188,19.0,17,,12,0.0,43,,,,5,1967-10-01 -3683,159,387,64,17.0,14,,13,0.0,41,,,,5,1967-10-01 -3684,159,373,64,8.0,13,,14,0.0,35,,,,5,1967-10-01 -3685,159,357,163,4.0,8,,15,0.0,33,,,,5,1967-10-01 -3686,159,363,187,11.0,3,,16,0.0,24,,,,22,1967-10-01 -3687,159,359,191,14.0,9,,17,0.0,16,,,,47,1967-10-01 -3688,159,381,177,18.0,7,,18,0.0,7,,,,80,1967-10-01 -3689,159,345,163,15.0,12,4.0,4,3.0,106,,,,12,1967-10-01 -3690,159,355,188,1.0,5,5.0,5,2.0,104,,,,14,1967-10-01 -3691,160,381,173,18.0,9,,17,0.0,12,,,,22,1967-10-22 -3692,160,327,64,7.0,12,,15,0.0,24,,,,5,1967-10-22 -3693,160,391,173,10.0,10,,19,0.0,0,,,,69,1967-10-22 -3694,160,303,188,2.0,6,3.0,3,4.0,64,,,,11,1967-10-22 -3695,160,340,10,3.0,7,4.0,4,3.0,64,,,,11,1967-10-22 -3696,160,373,64,8.0,11,5.0,5,2.0,63,,,,12,1967-10-22 -3697,160,344,163,21.0,13,6.0,6,1.0,63,,,,12,1967-10-22 -3698,160,305,184,22.0,14,7.0,7,0.0,63,,,,12,1967-10-22 -3699,160,394,5,12.0,16,8.0,8,0.0,63,,,,12,1967-10-22 -3700,160,277,5,9.0,2,9.0,9,0.0,62,,,,60,1967-10-22 -3701,160,346,163,16.0,17,10.0,10,0.0,61,,,,14,1967-10-22 -3702,160,388,188,19.0,19,11.0,11,0.0,41,,,,14,1967-10-22 -3703,160,345,163,15.0,10,12.0,12,0.0,59,,,,25,1967-10-22 -3704,160,359,191,14.0,8,,13,0.0,45,,,,51,1967-10-22 -3705,160,288,177,6.0,4,,16,0.0,18,,,,86,1967-10-22 -3706,160,387,64,17.0,15,,14,0.0,33,,,,44,1967-10-22 -3707,160,363,186,11.0,3,,18,0.0,4,,,,21,1967-10-22 -3708,160,355,188,1.0,5,2.0,2,6.0,65,7254060.0,,,1,1967-10-22 -3709,160,372,177,5.0,1,1.0,1,9.0,65,7168700.0,,,1,1967-10-22 -3710,161,288,177,5.0,2,2.0,2,6.0,80,6861900.0,,,1,1968-01-01 -3711,161,372,177,4.0,1,1.0,1,9.0,80,6836600.0,,,1,1968-01-01 -3712,161,374,192,15.0,15,,23,0.0,2,,,,110,1968-01-01 -3713,161,292,188,22.0,14,,22,0.0,3,,,,24,1968-01-01 -3714,161,311,163,14.0,21,,21,0.0,4,,,,44,1968-01-01 -3715,161,373,64,12.0,14,,20,0.0,7,,,,69,1968-01-01 -3716,161,332,5,10.0,7,,19,0.0,13,,,,3,1968-01-01 -3717,161,355,188,2.0,5,,18,0.0,16,,,,5,1968-01-01 -3718,161,344,64,11.0,10,,17,0.0,20,,,,69,1968-01-01 -3719,161,367,87,18.0,22,,15,0.0,35,,,,25,1968-01-01 -3720,161,327,193,16.0,3,,14,0.0,43,,,,5,1968-01-01 -3721,161,368,167,25.0,20,,16,0.0,22,,,,5,1968-01-01 -3722,161,234,5,9.0,11,,12,0.0,51,,,,44,1968-01-01 -3723,161,357,188,3.0,4,3.0,3,4.0,80,6867000.0,,,1,1968-01-01 -3724,161,277,5,8.0,8,4.0,4,3.0,78,,,,12,1968-01-01 -3725,161,303,191,1.0,9,5.0,5,2.0,78,,,,12,1968-01-01 -3726,161,305,193,21.0,18,6.0,6,1.0,77,,,,13,1968-01-01 -3727,161,346,163,20.0,19,,13,0.0,46,,,,25,1968-01-01 -3728,161,340,10,7.0,6,8.0,8,0.0,75,,,,15,1968-01-01 -3729,161,339,188,17.0,17,9.0,9,0.0,75,,,,15,1968-01-01 -3730,161,333,180,23.0,23,,10,0.0,71,,,,62,1968-01-01 -3731,161,345,163,19.0,16,7.0,7,0.0,77,,,,13,1968-01-01 -3732,161,363,187,6.0,12,,11,0.0,58,,,,44,1968-01-01 -3733,162,355,188,3.0,0,,14,0.0,0,,,,54,1968-05-12 -3734,162,357,188,4.0,9,,13,0.0,10,,,,51,1968-05-12 -3735,162,234,5,21.0,8,,12,0.0,13,,,,80,1968-05-12 -3736,162,344,64,9.0,2,,11,0.0,27,,,,3,1968-05-12 -3737,162,277,5,19.0,1,,9,0.0,57,,,,48,1968-05-12 -3738,162,360,64,5.0,11,,10,0.0,52,,,,48,1968-05-12 -3739,162,340,10,7.0,7,,7,0.0,74,,,,6,1968-05-12 -3740,162,359,184,2.0,4,,6,0.0,77,,,,44,1968-05-12 -3741,162,305,193,6.0,5,5.0,5,2.0,81,,,,19,1968-05-12 -3742,162,374,192,15.0,12,4.0,4,3.0,89,,,,11,1968-05-12 -3743,162,311,192,14.0,13,3.0,3,4.0,89,,,,11,1968-05-12 -3744,162,303,184,1.0,3,2.0,2,6.0,90,8118000.0,,,1,1968-05-12 -3745,162,288,177,10.0,6,1.0,1,9.0,90,8102100.0,,,1,1968-05-12 -3746,162,345,177,16.0,10,,8,0.0,62,,,,7,1968-05-12 -3747,163,363,187,19.0,16,,11,0.0,9,,,,5,1968-05-26 -3748,163,350,188,21.0,0,,18,0.0,0,,,,81,1968-05-26 -3749,163,346,191,18.0,0,,17,0.0,0,,,,81,1968-05-26 -3750,163,261,177,10.0,13,,16,0.0,0,,,,3,1968-05-26 -3751,163,358,193,11.0,2,,14,0.0,3,,,,86,1968-05-26 -3752,163,355,188,2.0,12,,13,0.0,7,,,,22,1968-05-26 -3753,163,360,64,16.0,11,,10,0.0,11,,,,83,1968-05-26 -3754,163,359,184,14.0,7,,15,0.0,0,,,,3,1968-05-26 -3755,163,345,177,17.0,3,,8,0.0,17,,,,24,1968-05-26 -3756,163,288,177,9.0,1,1.0,1,9.0,80,7232300.0,,,1,1968-05-26 -3757,163,305,80,1.0,8,,9,0.0,11,,,,3,1968-05-26 -3758,163,369,64,15.0,6,2.0,2,6.0,80,7234500.0,,,1,1968-05-26 -3759,163,375,192,7.0,14,3.0,3,4.0,76,,,,14,1968-05-26 -3760,163,357,188,3.0,5,,12,0.0,8,,,,3,1968-05-26 -3761,163,303,184,12.0,10,5.0,5,2.0,73,,,,17,1968-05-26 -3762,163,340,10,8.0,4,,6,0.0,16,,,,6,1968-05-26 -3763,163,374,192,6.0,15,4.0,4,3.0,76,,,,14,1968-05-26 -3764,163,344,64,4.0,9,,7,0.0,16,,,,3,1968-05-26 -3765,164,346,191,17.0,16,,18,0.0,1,,,,36,1968-06-09 -3766,164,357,188,19.0,17,,17,0.0,5,,,,5,1968-06-09 -3767,164,288,177,1.0,14,,16,0.0,5,,,,86,1968-06-09 -3768,164,355,188,18.0,10,,15,0.0,6,,,,37,1968-06-09 -3769,164,369,64,12.0,18,,14,0.0,6,,,,108,1968-06-09 -3770,164,277,5,22.0,1,,12,0.0,8,,,,21,1968-06-09 -3771,164,340,10,20.0,4,,11,0.0,11,,,,22,1968-06-09 -3772,164,311,192,16.0,11,,13,0.0,6,,,,20,1968-06-09 -3773,164,305,80,10.0,13,8.0,8,0.0,25,,,,13,1968-06-09 -3774,164,360,64,14.0,7,,9,0.0,22,,,,5,1968-06-09 -3775,164,359,184,5.0,6,1.0,1,9.0,28,6002100.0,,,1,1968-06-09 -3776,164,344,64,11.0,8,2.0,2,6.0,28,6014200.0,,,1,1968-06-09 -3777,164,234,5,23.0,3,3.0,3,4.0,28,6041700.0,,,1,1968-06-09 -3778,164,303,184,6.0,5,,10,0.0,18,,,,86,1968-06-09 -3779,164,261,177,2.0,15,5.0,5,2.0,26,,,,7,1968-06-09 -3780,164,375,192,15.0,12,6.0,6,1.0,26,,,,12,1968-06-09 -3781,164,345,177,3.0,9,7.0,7,0.0,25,,,,51,1968-06-09 -3782,164,327,193,7.0,2,4.0,4,3.0,27,,,,60,1968-06-09 -3783,165,303,184,1.0,7,,18,0.0,10,,,,80,1968-06-23 -3784,165,345,177,21.0,13,,12,0.0,55,,,,6,1968-06-23 -3785,165,359,184,2.0,8,,17,0.0,19,,,,3,1968-06-23 -3786,165,355,188,5.0,4,,16,0.0,22,,,,20,1968-06-23 -3787,165,357,188,6.0,2,,15,0.0,39,,,,80,1968-06-23 -3788,165,360,64,20.0,14,,14,0.0,50,,,,20,1968-06-23 -3789,165,340,10,7.0,9,,13,0.0,50,,,,91,1968-06-23 -3790,165,375,192,14.0,18,,19,0.0,9,,,,3,1968-06-23 -3791,165,261,177,4.0,10,,10,0.0,80,,,,62,1968-06-23 -3792,165,288,177,3.0,3,9.0,9,0.0,81,,,,3,1968-06-23 -3793,165,363,188,18.0,12,,11,0.0,63,,,,37,1968-06-23 -3794,165,327,193,8.0,5,1.0,1,9.0,90,9971200.0,,,1,1968-06-23 -3795,165,305,80,17.0,16,2.0,2,6.0,90,10065130.0,,,1,1968-06-23 -3796,165,234,5,10.0,6,4.0,4,3.0,88,,,,12,1968-06-23 -3797,165,344,64,15.0,11,3.0,3,4.0,89,,,,11,1968-06-23 -3798,165,277,5,9.0,1,6.0,6,1.0,85,,,,15,1968-06-23 -3799,165,346,191,19.0,19,8.0,8,0.0,82,,,,18,1968-06-23 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-3818,166,303,184,8.0,4,5.0,5,2.0,58,,,,12,1968-07-07 -3819,167,355,188,3.0,8,,20,0.0,0,,,,5,1968-07-20 -3820,167,363,187,24.0,6,,18,0.0,8,,,,48,1968-07-20 -3821,167,369,64,11.0,15,,17,0.0,10,,,,21,1968-07-20 -3822,167,305,80,18.0,14,,16,0.0,11,,,,5,1968-07-20 -3823,167,349,192,15.0,7,,15,0.0,26,,,,5,1968-07-20 -3824,167,288,177,8.0,1,,14,0.0,26,,,,86,1968-07-20 -3825,167,377,192,16.0,18,,13,0.0,34,,,,80,1968-07-20 -3826,167,346,191,23.0,20,,19,0.0,6,,,,5,1968-07-20 -3827,167,261,177,9.0,2,,12,0.0,43,,,,7,1968-07-20 -3828,167,344,64,10.0,13,,10,0.0,52,,,,5,1968-07-20 -3829,167,350,188,19.0,19,,11,0.0,52,,,,62,1968-07-20 -3830,167,345,177,22.0,4,1.0,1,9.0,80,7280300.0,,,1,1968-07-20 -3831,167,277,5,5.0,3,2.0,2,6.0,80,7284700.0,,,1,1968-07-20 -3832,167,234,5,6.0,12,3.0,3,4.0,79,,,,11,1968-07-20 -3833,167,357,188,4.0,5,,9,0.0,55,,,,95,1968-07-20 -3834,167,340,10,7.0,9,5.0,5,2.0,78,,,,12,1968-07-20 -3835,167,327,193,14.0,7,6.0,6,1.0,78,,,,12,1968-07-20 -3836,167,359,184,2.0,10,7.0,7,0.0,77,,,,13,1968-07-20 -3837,167,360,64,20.0,16,8.0,8,0.0,72,,,,18,1968-07-20 -3838,167,303,184,1.0,11,4.0,4,3.0,79,,,,11,1968-07-20 -3839,168,349,192,20.0,5,,20,0.0,0,,,,3,1968-08-04 -3840,168,340,10,7.0,7,,19,0.0,3,,,,80,1968-08-04 -3841,168,375,192,19.0,19,,18,0.0,6,,,,95,1968-08-04 -3842,168,345,177,16.0,9,,17,0.0,6,,,,80,1968-08-04 -3843,168,305,80,12.0,12,,16,0.0,8,,,,3,1968-08-04 -3844,168,277,5,8.0,2,,15,0.0,11,,,,3,1968-08-04 -3845,168,369,64,11.0,20,14.0,14,0.0,13,,,,11,1968-08-04 -3846,168,359,0,2.0,16,13.0,13,0.0,13,,,,11,1968-08-04 -3847,168,378,188,17.0,17,12.0,12,0.0,13,,,,11,1968-08-04 -3848,168,364,25,18.0,18,10.0,10,0.0,14,8954600.0,,,1,1968-08-04 -3849,168,363,187,14.0,10,9.0,9,0.0,14,8836900.0,,,1,1968-08-04 -3850,168,360,64,22.0,8,8.0,8,0.0,14,8819600.0,,,1,1968-08-04 -3851,168,344,64,10.0,14,6.0,6,1.0,14,8728200.0,,,1,1968-08-04 -3852,168,355,188,4.0,15,5.0,5,2.0,14,8724300.0,,,1,1968-08-04 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-3908,171,346,191,17.0,18,,14,0.0,62,,,,62,1968-10-06 -3909,171,344,64,8.0,11,,13,0.0,66,,,,22,1968-10-06 -3910,171,349,192,18.0,17,,12,0.0,71,,,,5,1968-10-06 -3911,171,357,188,4.0,6,,11,0.0,73,,,,5,1968-10-06 -3912,171,375,192,19.0,20,,9,0.0,88,,,,62,1968-10-06 -3913,171,303,0,1.0,5,,8,0.0,92,,,,3,1968-10-06 -3914,171,360,64,22.0,14,,7,0.0,93,,,,60,1968-10-06 -3915,171,359,184,2.0,10,6.0,6,1.0,103,,,,15,1968-10-06 -3916,171,345,177,16.0,12,5.0,5,2.0,105,,,,13,1968-10-06 -3917,171,363,184,14.0,7,4.0,4,3.0,107,,,,11,1968-10-06 -3918,171,340,10,5.0,9,3.0,3,4.0,107,,,,11,1968-10-06 -3919,171,288,177,10.0,3,2.0,2,6.0,108,7184970.0,,,1,1968-10-06 -3920,171,327,193,15.0,2,1.0,1,9.0,108,7160290.0,,,1,1968-10-06 -3921,171,355,188,3.0,8,,10,0.0,77,,,,5,1968-10-06 -3922,172,234,5,7.0,15,,20,0.0,3,,,,80,1968-11-03 -3923,172,305,80,21.0,13,,19,0.0,10,,,,22,1968-11-03 -3924,172,303,184,1.0,4,,18,0.0,10,,,,22,1968-11-03 -3925,172,360,64,22.0,19,,13,0.0,25,,,,5,1968-11-03 -3926,172,277,5,6.0,2,,16,0.0,16,,,,7,1968-11-03 -3927,172,340,10,5.0,6,,15,0.0,17,,,,25,1968-11-03 -3928,172,375,192,19.0,21,,14,0.0,21,,,,5,1968-11-03 -3929,172,381,177,12.0,11,,17,0.0,14,,,,41,1968-11-03 -3930,172,363,184,14.0,5,,12,0.0,28,,,,22,1968-11-03 -3931,172,279,80,9.0,20,9.0,9,0.0,62,,,,13,1968-11-03 -3932,172,355,188,3.0,8,10.0,10,0.0,59,,,,51,1968-11-03 -3933,172,357,188,4.0,10,,21,0.0,2,,,,80,1968-11-03 -3934,172,288,177,10.0,3,1.0,1,9.0,65,7003950.0,,,1,1968-11-03 -3935,172,359,184,2.0,9,2.0,2,6.0,65,7083270.0,,,1,1968-11-03 -3936,172,261,177,11.0,14,3.0,3,4.0,65,7104600.0,,,1,1968-11-03 -3937,172,344,64,8.0,12,4.0,4,3.0,65,7105040.0,,,1,1968-11-03 -3938,172,346,10,17.0,18,5.0,5,2.0,64,,,,11,1968-11-03 -3939,172,345,177,16.0,1,6.0,6,1.0,64,,,,11,1968-11-03 -3940,172,327,193,15.0,7,7.0,7,0.0,64,,,,11,1968-11-03 -3941,172,358,193,23.0,16,,11,0.0,57,,,,80,1968-11-03 -3942,172,349,192,18.0,17,8.0,8,0.0,63,,,,12,1968-11-03 -3943,173,327,193,7.0,4,1.0,1,9.0,80,6639100.0,,,1,1969-03-01 -3944,173,288,177,1.0,7,2.0,2,6.0,80,6657900.0,,,1,1969-03-01 -3945,173,368,184,18.0,9,,18,0.0,12,,,,23,1969-03-01 -3946,173,339,177,16.0,10,,16,0.0,31,,,,80,1969-03-01 -3947,173,206,177,3.0,6,,15,0.0,31,,,,6,1969-03-01 -3948,173,355,179,14.0,1,,14,0.0,32,,,,64,1969-03-01 -3949,173,277,5,9.0,5,,13,0.0,34,,,,5,1969-03-01 -3950,173,340,64,10.0,18,,11,0.0,40,,,,5,1969-03-01 -3951,173,357,177,2.0,2,,10,0.0,44,,,,48,1969-03-01 -3952,173,344,64,12.0,15,,12,0.0,38,,,,47,1969-03-01 -3953,173,367,188,17.0,17,8.0,8,0.0,73,,,,17,1969-03-01 -3954,173,261,64,11.0,14,7.0,7,0.0,77,,,,13,1969-03-01 -3955,173,305,193,8.0,11,6.0,6,1.0,78,,,,12,1969-03-01 -3956,173,359,184,6.0,8,5.0,5,2.0,79,,,,11,1969-03-01 -3957,173,345,177,4.0,12,4.0,4,3.0,80,6688300.0,,,1,1969-03-01 -3958,173,303,184,5.0,3,3.0,3,4.0,80,6670900.0,,,1,1969-03-01 -3959,173,361,188,19.0,16,,9,0.0,67,,,,62,1969-03-01 -3960,173,234,179,15.0,13,,17,0.0,20,,,,80,1969-03-01 -3961,174,345,177,10.0,6,,10,0.0,30,,,,44,1969-05-04 -3962,174,327,193,7.0,4,1.0,1,9.0,90,8214000.0,,,1,1969-05-04 -3963,174,261,64,12.0,10,,14,0.0,1,,,,108,1969-05-04 -3964,174,288,177,1.0,3,,13,0.0,8,,,,3,1969-05-04 -3965,174,360,179,11.0,11,,12,0.0,18,,,,5,1969-05-04 -3966,174,357,177,2.0,1,,11,0.0,19,,,,3,1969-05-04 -3967,174,277,5,15.0,2,,8,0.0,56,,,,5,1969-05-04 -3968,174,344,64,9.0,14,,7,0.0,73,,,,5,1969-05-04 -3969,174,234,179,4.0,7,6.0,6,1.0,83,,,,17,1969-05-04 -3970,174,340,64,14.0,9,5.0,5,2.0,84,,,,16,1969-05-04 -3971,174,303,184,5.0,8,4.0,4,3.0,87,,,,13,1969-05-04 -3972,174,305,193,8.0,12,3.0,3,4.0,87,,,,13,1969-05-04 -3973,174,355,179,3.0,5,,9,0.0,51,,,,5,1969-05-04 -3974,174,359,184,6.0,13,2.0,2,6.0,88,,,,12,1969-05-04 -3975,175,350,179,17.0,15,,13,0.0,15,,,,86,1969-05-18 -3976,175,344,64,10.0,14,,12,0.0,15,,,,5,1969-05-18 -3977,175,277,5,11.0,2,,11,0.0,16,,,,24,1969-05-18 -3978,175,305,193,8.0,3,,10,0.0,20,,,,86,1969-05-18 -3979,175,327,193,7.0,1,,9,0.0,22,,,,86,1969-05-18 -3980,175,303,184,3.0,12,6.0,6,1.0,78,,,,12,1969-05-18 -3981,175,349,163,12.0,16,7.0,7,0.0,74,,,,16,1969-05-18 -3982,175,359,184,4.0,11,5.0,5,2.0,79,,,,11,1969-05-18 -3983,175,369,177,2.0,10,4.0,4,3.0,80,7072300.0,,,1,1969-05-18 -3984,175,345,177,9.0,5,3.0,3,4.0,80,7054000.0,,,1,1969-05-18 -3985,175,360,179,16.0,9,2.0,2,6.0,80,7036700.0,,,1,1969-05-18 -3986,175,288,177,1.0,4,1.0,1,9.0,80,7019400.0,,,1,1969-05-18 -3987,175,234,179,6.0,7,,8,0.0,48,,,,22,1969-05-18 -3988,175,355,179,5.0,8,,15,0.0,9,,,,3,1969-05-18 -3989,175,340,64,14.0,6,,14,0.0,9,,,,6,1969-05-18 -3990,175,261,64,15.0,13,,16,0.0,0,,,,3,1969-05-18 -3991,176,327,193,4.0,2,1.0,1,9.0,90,7602080.0,,,1,1969-06-21 -3992,176,261,64,15.0,13,,15,0.0,9,,,,6,1969-06-21 -3993,176,360,179,16.0,9,,14,0.0,12,,,,8,1969-06-21 -3994,176,357,177,2.0,1,,13,0.0,16,,,,86,1969-06-21 -3995,176,359,184,6.0,6,,12,0.0,24,,,,22,1969-06-21 -3996,176,350,179,17.0,14,,11,0.0,54,,,,80,1969-06-21 -3997,176,349,184,18.0,15,10.0,10,0.0,84,,,,16,1969-06-21 -3998,176,288,177,1.0,3,7.0,7,0.0,88,,,,12,1969-06-21 -3999,176,305,184,5.0,11,8.0,8,0.0,87,,,,13,1969-06-21 -4000,176,355,179,11.0,8,6.0,6,1.0,90,7672890.0,,,1,1969-06-21 -4001,176,234,179,12.0,5,5.0,5,2.0,90,7639750.0,,,1,1969-06-21 -4002,176,303,184,7.0,7,4.0,4,3.0,90,7639240.0,,,1,1969-06-21 -4003,176,277,5,8.0,4,3.0,3,4.0,90,7632590.0,,,1,1969-06-21 -4004,176,345,177,10.0,10,2.0,2,6.0,90,7626600.0,,,1,1969-06-21 -4005,176,340,64,14.0,12,9.0,9,0.0,87,,,,13,1969-06-21 -4006,177,356,177,14.0,12,,13,0.0,1,,,,48,1969-07-06 -4007,177,360,179,9.0,11,,12,0.0,21,,,,83,1969-07-06 -4008,177,357,177,15.0,3,,11,0.0,22,,,,68,1969-07-06 -4009,177,277,5,6.0,6,,10,0.0,30,,,,5,1969-07-06 -4010,177,345,177,3.0,9,9.0,9,0.0,34,,,,14,1969-07-06 -4011,177,349,184,10.0,10,5.0,5,2.0,37,,,,11,1969-07-06 -4012,177,350,179,12.0,13,7.0,7,0.0,36,,,,12,1969-07-06 -4013,177,288,177,1.0,8,6.0,6,1.0,37,,,,11,1969-07-06 -4014,177,359,184,5.0,7,4.0,4,3.0,37,,,,11,1969-07-06 -4015,177,234,179,11.0,4,3.0,3,4.0,38,7064700.0,,,1,1969-07-06 -4016,177,305,193,7.0,5,2.0,2,6.0,38,7064500.0,,,1,1969-07-06 -4017,177,303,184,4.0,2,8.0,8,0.0,35,,,,13,1969-07-06 -4018,177,327,193,2.0,1,1.0,1,9.0,38,7007400.0,,,1,1969-07-06 -4019,178,344,5,12.0,8,,11,0.0,61,,,,5,1969-07-19 -4020,178,327,193,3.0,2,1.0,1,9.0,84,6955600.0,,,1,1969-07-19 -4021,178,234,179,7.0,4,2.0,2,6.0,83,,,,11,1969-07-19 -4022,178,359,184,6.0,7,3.0,3,4.0,83,,,,11,1969-07-19 -4023,178,357,177,2.0,1,4.0,4,3.0,83,,,,11,1969-07-19 -4024,178,360,179,16.0,10,5.0,5,2.0,83,,,,11,1969-07-19 -4025,178,349,184,19.0,11,6.0,6,1.0,82,,,,12,1969-07-19 -4026,178,288,177,1.0,12,7.0,7,0.0,82,,,,12,1969-07-19 -4027,178,345,177,10.0,9,8.0,8,0.0,81,,,,13,1969-07-19 -4028,178,340,64,14.0,6,,17,0.0,1,,,,22,1969-07-19 -4029,178,320,184,20.0,15,,16,0.0,5,,,,22,1969-07-19 -4030,178,346,177,18.0,16,,15,0.0,6,,,,5,1969-07-19 -4031,178,261,64,15.0,13,,14,0.0,19,,,,7,1969-07-19 -4032,178,305,193,4.0,17,9.0,9,0.0,78,,,,16,1969-07-19 -4033,178,277,5,11.0,5,,12,0.0,45,,,,6,1969-07-19 -4034,178,356,177,9.0,14,10.0,10,0.0,75,,,,19,1969-07-19 -4035,178,303,184,5.0,3,,13,0.0,27,,,,80,1969-07-19 -4036,179,359,184,10.0,8,3.0,3,4.0,14,6797000.0,,,1,1969-08-03 -4037,179,206,177,3.0,15,,13,0.0,0,,,,3,1969-08-03 -4038,179,349,184,12.0,6,,12,0.0,0,,,,3,1969-08-03 -4039,179,360,179,17.0,7,,11,0.0,1,,,,3,1969-08-03 -4040,179,346,177,16.0,23,,10,0.0,4,,,,95,1969-08-03 -4041,179,357,177,2.0,3,,9,0.0,10,,,,80,1969-08-03 -4042,179,261,194,15.0,16,,8,0.0,11,,,,44,1969-08-03 -4043,179,303,184,9.0,5,,7,0.0,11,,,,7,1969-08-03 -4044,179,305,193,8.0,10,6.0,6,1.0,12,,,,22,1969-08-03 -4045,179,288,177,1.0,9,4.0,4,3.0,14,6834200.0,,,1,1969-08-03 -4046,179,327,193,7.0,2,2.0,2,6.0,14,6653100.0,,,1,1969-08-03 -4047,179,234,179,6.0,1,1.0,1,9.0,14,6595400.0,,,1,1969-08-03 -4048,179,340,64,14.0,11,,14,0.0,0,,,,54,1969-08-03 -4049,179,345,177,11.0,4,5.0,5,2.0,12,,,,22,1969-08-03 -4050,180,357,177,4.0,1,2.0,2,6.0,68,5951340.0,,,1,1969-09-07 -4051,180,305,193,22.0,6,3.0,3,4.0,68,5951430.0,,,1,1969-09-07 -4052,180,327,193,20.0,3,1.0,1,9.0,68,5951260.0,,,1,1969-09-07 -4053,180,356,177,6.0,14,,15,0.0,3,,,,5,1969-09-07 -4054,180,355,179,28.0,7,,14,0.0,6,,,,44,1969-09-07 -4055,180,350,179,36.0,13,,13,0.0,9,,,,95,1969-09-07 -4056,180,261,64,12.0,11,,12,0.0,48,,,,51,1969-09-07 -4057,180,340,64,14.0,10,,11,0.0,60,,,,62,1969-09-07 -4058,180,359,184,18.0,5,4.0,4,3.0,68,5951450.0,,,1,1969-09-07 -4059,180,288,177,1.0,9,9.0,9,0.0,63,,,,86,1969-09-07 -4060,180,345,177,30.0,8,8.0,8,0.0,64,,,,5,1969-09-07 -4061,180,303,184,16.0,2,7.0,7,0.0,66,,,,12,1969-09-07 -4062,180,344,5,10.0,12,6.0,6,1.0,66,,,,12,1969-09-07 -4063,180,360,179,32.0,4,5.0,5,2.0,68,5984700.0,,,1,1969-09-07 -4064,180,234,179,26.0,15,10.0,10,0.0,61,,,,60,1969-09-07 -4065,181,350,179,20.0,20,,20,0.0,0,,,,3,1969-09-20 -4066,181,261,64,15.0,12,,19,0.0,2,,,,5,1969-09-20 -4067,181,303,184,5.0,5,,18,0.0,9,,,,99,1969-09-20 -4068,181,371,180,26.0,19,,17,0.0,10,,,,44,1969-09-20 -4069,181,360,179,21.0,10,,16,0.0,13,,,,95,1969-09-20 -4070,181,370,186,69.0,17,,14,0.0,22,,,,2,1969-09-20 -4071,181,327,193,17.0,4,,13,0.0,32,,,,4,1969-09-20 -4072,181,344,5,6.0,13,,12,0.0,37,,,,51,1969-09-20 -4073,181,340,64,14.0,14,,15,0.0,15,,,,5,1969-09-20 -4074,181,345,177,9.0,8,,10,0.0,40,,,,86,1969-09-20 -4075,181,234,179,11.0,1,1.0,1,9.0,90,7165700.0,,,1,1969-09-20 -4076,181,355,179,12.0,6,2.0,2,6.0,90,7211900.0,,,1,1969-09-20 -4077,181,357,177,2.0,3,3.0,3,4.0,90,7217700.0,,,1,1969-09-20 -4078,181,305,193,18.0,2,4.0,4,3.0,89,,,,11,1969-09-20 -4079,181,356,177,3.0,11,,11,0.0,40,,,,6,1969-09-20 -4080,181,358,193,19.0,15,6.0,6,1.0,84,,,,16,1969-09-20 -4081,181,352,177,25.0,16,7.0,7,0.0,81,,,,19,1969-09-20 -4082,181,342,64,16.0,18,,8,0.0,80,,,,62,1969-09-20 -4083,181,288,177,1.0,7,,9,0.0,42,,,,5,1969-09-20 -4084,181,359,184,4.0,9,5.0,5,2.0,87,,,,13,1969-09-20 -4085,182,305,193,4.0,7,,11,0.0,72,,,,5,1969-10-05 -4086,182,351,64,22.0,9,,10,0.0,76,,,,5,1969-10-05 -4087,182,234,179,7.0,8,,9,0.0,77,,,,5,1969-10-05 -4088,182,288,177,1.0,4,,8,0.0,90,,,,3,1969-10-05 -4089,182,350,179,19.0,17,6.0,6,1.0,98,,,,88,1969-10-05 -4090,182,344,5,12.0,12,5.0,5,2.0,101,,,,17,1969-10-05 -4091,182,355,179,8.0,18,4.0,4,3.0,106,,,,12,1969-10-05 -4092,182,327,193,3.0,3,,13,0.0,35,,,,5,1969-10-05 -4093,182,360,179,18.0,9,2.0,2,6.0,108,7123830.0,,,1,1969-10-05 -4094,182,357,177,2.0,1,1.0,1,9.0,108,7076840.0,,,1,1969-10-05 -4095,182,358,193,16.0,15,,7,0.0,92,,,,62,1969-10-05 -4096,182,340,64,14.0,11,3.0,3,4.0,106,,,,12,1969-10-05 -4097,182,303,184,5.0,2,,12,0.0,52,,,,6,1969-10-05 -4098,182,345,177,10.0,13,,16,0.0,3,,,,69,1969-10-05 -4099,182,359,184,6.0,6,,18,0.0,0,,,,5,1969-10-05 -4100,182,261,64,15.0,14,,15,0.0,23,,,,5,1969-10-05 -4101,182,352,177,21.0,16,,14,0.0,25,,,,86,1969-10-05 -4102,182,206,177,9.0,5,,17,0.0,3,,,,22,1969-10-05 -4103,183,352,177,21.0,16,9.0,9,0.0,62,,,,13,1969-10-19 -4104,183,355,179,8.0,1,3.0,3,4.0,65,6887280.0,,,1,1969-10-19 -4105,183,327,193,3.0,3,4.0,4,3.0,65,6895840.0,,,1,1969-10-19 -4106,183,305,193,4.0,8,5.0,5,2.0,65,6947320.0,,,1,1969-10-19 -4107,183,261,64,15.0,12,6.0,6,1.0,63,,,,12,1969-10-19 -4108,183,344,5,12.0,15,7.0,7,0.0,63,,,,12,1969-10-19 -4109,183,358,193,16.0,14,8.0,8,0.0,63,,,,12,1969-10-19 -4110,183,360,179,18.0,9,10.0,10,0.0,61,,,,14,1969-10-19 -4111,183,350,179,19.0,13,11.0,11,0.0,60,,,,95,1969-10-19 -4112,183,340,64,14.0,10,,12,0.0,53,,,,6,1969-10-19 -4113,183,357,177,2.0,6,,13,0.0,21,,,,22,1969-10-19 -4114,183,351,64,22.0,17,,14,0.0,6,,,,6,1969-10-19 -4115,183,345,177,10.0,5,,15,0.0,4,,,,3,1969-10-19 -4116,183,356,177,9.0,11,,16,0.0,3,,,,48,1969-10-19 -4117,183,359,184,6.0,7,,17,0.0,0,,,,54,1969-10-19 -4118,183,234,179,7.0,2,2.0,2,6.0,65,6851360.0,,,1,1969-10-19 -4119,183,303,184,5.0,4,1.0,1,9.0,65,6848800.0,,,1,1969-10-19 -4120,184,327,36,1.0,1,3.0,3,4.0,80,6592500.0,,,1,1970-03-07 -4121,184,303,184,6.0,6,2.0,2,6.0,80,6583500.0,,,1,1970-03-07 -4122,184,277,36,15.0,2,,23,0.0,14,,,,25,1970-03-07 -4123,184,355,33,12.0,3,1.0,1,9.0,80,6575400.0,,,1,1970-03-07 -4124,184,305,80,3.0,8,4.0,4,3.0,80,6648500.0,,,1,1970-03-07 -4125,184,356,31,10.0,14,5.0,5,2.0,79,,,,11,1970-03-07 -4126,184,288,31,11.0,19,6.0,6,1.0,79,,,,11,1970-03-07 -4127,184,279,80,4.0,18,7.0,7,0.0,78,,,,12,1970-03-07 -4128,184,339,31,23.0,22,8.0,8,0.0,78,,,,12,1970-03-07 -4129,184,344,64,20.0,16,9.0,9,0.0,76,,,,14,1970-03-07 -4130,184,345,36,16.0,9,10.0,10,0.0,75,,,,15,1970-03-07 -4131,184,361,33,24.0,21,11.0,11,0.0,75,,,,15,1970-03-07 -4132,184,292,31,25.0,13,12.0,12,0.0,73,,,,5,1970-03-07 -4133,184,357,31,9.0,4,13.0,13,0.0,72,,,,5,1970-03-07 -4134,184,234,5,17.0,5,,14,0.0,60,,,,5,1970-03-07 -4135,184,340,184,7.0,7,,15,0.0,60,,,,5,1970-03-07 -4136,184,351,64,21.0,23,,16,0.0,58,,,,5,1970-03-07 -4137,184,358,36,2.0,17,,17,0.0,57,,,,5,1970-03-07 -4138,184,359,184,5.0,10,,18,0.0,39,,,,5,1970-03-07 -4139,184,360,84,22.0,20,,19,0.0,39,,,,3,1970-03-07 -4140,184,206,36,8.0,11,,20,0.0,26,,,,25,1970-03-07 -4141,184,261,64,19.0,12,,22,0.0,22,,,,6,1970-03-07 -4142,184,242,33,14.0,15,,21,0.0,23,,,,5,1970-03-07 -4143,185,356,31,19.0,0,,19,0.0,0,,,,81,1970-04-19 -4144,185,338,31,23.0,0,,22,0.0,0,,,,81,1970-04-19 -4145,185,345,36,14.0,0,,20,0.0,0,,,,81,1970-04-19 -4146,185,359,184,11.0,11,2.0,2,6.0,89,,,,11,1970-04-19 -4147,185,327,36,1.0,3,1.0,1,9.0,90,7858200.0,,,1,1970-04-19 -4148,185,351,64,21.0,0,,21,0.0,0,,,,81,1970-04-19 -4149,185,206,36,18.0,16,3.0,3,4.0,89,,,,11,1970-04-19 -4150,185,288,31,6.0,15,4.0,4,3.0,89,,,,11,1970-04-19 -4151,185,358,36,16.0,14,5.0,5,2.0,88,,,,12,1970-04-19 -4152,185,355,33,7.0,1,,7,0.0,61,,,,5,1970-04-19 -4153,185,242,33,24.0,17,,8,0.0,43,,,,5,1970-04-19 -4154,185,279,80,22.0,9,,9,0.0,33,,,,5,1970-04-19 -4155,185,305,80,4.0,4,,10,0.0,31,,,,5,1970-04-19 -4156,185,340,184,8.0,12,,6,0.0,76,,,,6,1970-04-19 -4157,185,277,36,9.0,6,,12,0.0,10,,,,5,1970-04-19 -4158,185,357,31,3.0,8,,13,0.0,9,,,,80,1970-04-19 -4159,185,344,64,10.0,5,,14,0.0,4,,,,54,1970-04-19 -4160,185,234,5,2.0,7,,15,0.0,0,,,,3,1970-04-19 -4161,185,261,64,15.0,10,,16,0.0,0,,,,3,1970-04-19 -4162,185,360,84,12.0,13,,17,0.0,0,,,,54,1970-04-19 -4163,185,332,195,20.0,0,,18,0.0,0,,,,81,1970-04-19 -4164,185,303,184,5.0,2,,11,0.0,10,,,,80,1970-04-19 -4165,186,359,184,12.0,10,,14,0.0,19,,,,22,1970-05-10 -4166,186,340,184,14.0,13,,15,0.0,14,,,,51,1970-05-10 -4167,186,234,5,26.0,5,,16,0.0,11,,,,86,1970-05-10 -4168,186,356,31,2.0,0,,20,0.0,0,,,,81,1970-05-10 -4169,186,242,33,6.0,0,,18,0.0,0,,,,81,1970-05-10 -4170,186,351,64,15.0,0,,19,0.0,0,,,,81,1970-05-10 -4171,186,305,80,8.0,6,,13,0.0,21,,,,24,1970-05-10 -4172,186,332,195,10.0,0,,17,0.0,0,,,,81,1970-05-10 -4173,186,261,64,16.0,14,,12,0.0,42,,,,5,1970-05-10 -4174,186,357,31,3.0,8,1.0,1,9.0,80,6877400.0,,,1,1970-05-10 -4175,186,360,84,24.0,9,,10,0.0,58,,,,62,1970-05-10 -4176,186,277,36,28.0,2,,9,0.0,60,,,,22,1970-05-10 -4177,186,345,36,19.0,11,8.0,8,0.0,76,,,,60,1970-05-10 -4178,186,237,36,23.0,12,7.0,7,0.0,78,,,,12,1970-05-10 -4179,186,344,64,17.0,15,6.0,6,1.0,78,,,,12,1970-05-10 -4180,186,288,31,1.0,16,5.0,5,2.0,79,,,,11,1970-05-10 -4181,186,303,184,11.0,3,4.0,4,3.0,80,6965700.0,,,1,1970-05-10 -4182,186,358,36,20.0,0,,21,0.0,0,,,,81,1970-05-10 -4183,186,327,36,21.0,1,,11,0.0,57,,,,5,1970-05-10 -4184,186,279,80,9.0,7,3.0,3,4.0,80,6928800.0,,,1,1970-05-10 -4185,186,355,33,5.0,4,2.0,2,6.0,80,6900500.0,,,1,1970-05-10 -4186,187,344,64,1.0,6,1.0,1,9.0,28,5890100.0,,,1,1970-06-07 -4187,187,277,36,10.0,3,2.0,2,6.0,28,5891200.0,,,1,1970-06-07 -4188,187,305,80,25.0,11,3.0,3,4.0,28,5993800.0,,,1,1970-06-07 -4189,187,362,5,28.0,8,4.0,4,3.0,28,6048600.0,,,1,1970-06-07 -4190,187,242,33,19.0,7,5.0,5,2.0,28,6101900.0,,,1,1970-06-07 -4191,187,279,80,26.0,17,6.0,6,1.0,27,,,,10,1970-06-07 -4192,187,234,5,27.0,4,8.0,8,0.0,26,,,,12,1970-06-07 -4193,187,237,36,14.0,9,,9,0.0,20,,,,62,1970-06-07 -4194,187,355,33,18.0,5,,10,0.0,19,,,,8,1970-06-07 -4195,187,345,36,9.0,10,7.0,7,0.0,26,,,,32,1970-06-07 -4196,187,327,36,11.0,1,,12,0.0,14,,,,5,1970-06-07 -4197,187,356,31,21.0,13,,13,0.0,13,,,,6,1970-06-07 -4198,187,357,31,20.0,2,,14,0.0,10,,,,5,1970-06-07 -4199,187,261,64,2.0,14,,15,0.0,7,,,,5,1970-06-07 -4200,187,360,84,7.0,12,,16,0.0,4,,,,51,1970-06-07 -4201,187,320,33,8.0,15,,17,0.0,1,,,,6,1970-06-07 -4202,187,288,31,23.0,16,,11,0.0,19,,,,5,1970-06-07 -4203,188,345,36,9.0,17,,17,0.0,22,,,,5,1970-06-21 -4204,188,319,184,20.0,11,,18,0.0,18,,,,3,1970-06-21 -4205,188,363,184,32.0,19,,19,0.0,2,,,,5,1970-06-21 -4206,188,277,36,8.0,4,,20,0.0,1,,,,8,1970-06-21 -4207,188,350,83,29.0,0,,24,0.0,0,,,,81,1970-06-21 -4208,188,242,33,19.0,0,,22,0.0,0,,,,81,1970-06-21 -4209,188,352,31,31.0,0,,23,0.0,0,,,,81,1970-06-21 -4210,188,360,84,4.0,9,,16,0.0,22,,,,3,1970-06-21 -4211,188,332,195,21.0,0,,21,0.0,0,,,,81,1970-06-21 -4212,188,261,64,2.0,5,,15,0.0,23,,,,5,1970-06-21 -4213,188,340,184,16.0,14,6.0,6,1.0,79,,,,11,1970-06-21 -4214,188,326,36,6.0,15,,13,0.0,31,,,,5,1970-06-21 -4215,188,288,31,15.0,20,,12,0.0,71,,,,62,1970-06-21 -4216,188,355,33,18.0,12,11.0,11,0.0,76,,,,14,1970-06-21 -4217,188,344,64,1.0,7,10.0,10,0.0,77,,,,13,1970-06-21 -4218,188,237,36,22.0,16,9.0,9,0.0,78,,,,12,1970-06-21 -4219,188,279,80,24.0,13,8.0,8,0.0,78,,,,12,1970-06-21 -4220,188,356,31,12.0,8,7.0,7,0.0,78,,,,12,1970-06-21 -4221,188,305,80,23.0,10,5.0,5,2.0,79,,,,11,1970-06-21 -4222,188,357,31,10.0,1,1.0,1,9.0,80,6643400.0,,,1,1970-06-21 -4223,188,327,36,5.0,2,2.0,2,6.0,80,6673400.0,,,1,1970-06-21 -4224,188,351,64,3.0,18,,14,0.0,26,,,,44,1970-06-21 -4225,188,234,5,25.0,3,3.0,3,4.0,79,,,,11,1970-06-21 -4226,188,222,5,26.0,6,4.0,4,3.0,79,,,,11,1970-06-21 -4227,189,344,64,3.0,10,,19,0.0,6,,,,6,1970-07-05 -4228,189,352,31,25.0,0,,23,0.0,0,,,,81,1970-07-05 -4229,189,338,31,9.0,0,,22,0.0,0,,,,81,1970-07-05 -4230,189,350,83,24.0,0,,21,0.0,0,,,,81,1970-07-05 -4231,189,261,64,5.0,12,,20,0.0,5,,,,5,1970-07-05 -4232,189,234,5,10.0,1,,18,0.0,16,,,,5,1970-07-05 -4233,189,237,36,18.0,9,,17,0.0,17,,,,24,1970-07-05 -4234,189,332,195,16.0,15,,15,0.0,29,,,,62,1970-07-05 -4235,189,362,5,11.0,11,14.0,14,0.0,35,,,,13,1970-07-05 -4236,189,305,80,21.0,2,13.0,13,0.0,35,,,,60,1970-07-05 -4237,189,351,64,4.0,19,12.0,12,0.0,36,,,,12,1970-07-05 -4238,189,345,36,12.0,16,,16,0.0,23,,,,3,1970-07-05 -4239,189,288,31,8.0,20,10.0,10,0.0,37,,,,11,1970-07-05 -4240,189,326,36,2.0,13,11.0,11,0.0,37,,,,11,1970-07-05 -4241,189,277,36,14.0,3,2.0,2,6.0,38,6964610.0,,,1,1970-07-05 -4242,189,355,33,23.0,5,3.0,3,4.0,38,7001830.0,,,1,1970-07-05 -4243,189,303,184,19.0,7,4.0,4,3.0,38,7002660.0,,,1,1970-07-05 -4244,189,279,80,20.0,8,5.0,5,2.0,38,7036420.0,,,1,1970-07-05 -4245,189,357,31,6.0,6,1.0,1,9.0,38,6957000.0,,,1,1970-07-05 -4246,189,242,33,22.0,14,7.0,7,0.0,38,7097160.0,,,1,1970-07-05 -4247,189,356,31,7.0,18,8.0,8,0.0,38,7124170.0,,,1,1970-07-05 -4248,189,327,36,1.0,4,9.0,9,0.0,38,7146610.0,,,1,1970-07-05 -4249,189,363,184,32.0,17,6.0,6,1.0,38,7036650.0,,,1,1970-07-05 -4250,190,327,36,1.0,8,,14,0.0,52,,,,8,1970-07-18 -4251,190,332,195,11.0,18,,23,0.0,0,,,,95,1970-07-18 -4252,190,234,5,3.0,3,,22,0.0,6,,,,7,1970-07-18 -4253,190,351,64,24.0,16,,21,0.0,10,,,,51,1970-07-18 -4254,190,356,31,6.0,7,,20,0.0,15,,,,5,1970-07-18 -4255,190,345,36,15.0,20,,19,0.0,19,,,,22,1970-07-18 -4256,190,206,36,26.0,9,,18,0.0,21,,,,22,1970-07-18 -4257,190,305,80,7.0,10,,17,0.0,24,,,,36,1970-07-18 -4258,190,279,80,8.0,12,,16,0.0,41,,,,3,1970-07-18 -4259,190,340,61,20.0,19,,15,0.0,51,,,,51,1970-07-18 -4260,190,261,64,23.0,4,,13,0.0,54,,,,5,1970-07-18 -4261,190,222,5,4.0,6,4.0,4,3.0,80,7076800.0,,,1,1970-07-18 -4262,190,363,184,32.0,11,,11,0.0,60,,,,51,1970-07-18 -4263,190,357,31,5.0,1,1.0,1,9.0,80,7022000.0,,,1,1970-07-18 -4264,190,344,64,22.0,15,,12,0.0,58,,,,3,1970-07-18 -4265,190,303,184,9.0,5,3.0,3,4.0,80,7076400.0,,,1,1970-07-18 -4266,190,277,36,16.0,17,5.0,5,2.0,79,,,,11,1970-07-18 -4267,190,355,33,17.0,2,2.0,2,6.0,80,7054900.0,,,1,1970-07-18 -4268,190,326,36,2.0,14,7.0,7,0.0,79,,,,11,1970-07-18 -4269,190,223,31,28.0,21,8.0,8,0.0,78,,,,12,1970-07-18 -4270,190,237,36,27.0,13,9.0,9,0.0,72,,,,18,1970-07-18 -4271,190,352,31,29.0,23,,10,0.0,69,,,,62,1970-07-18 -4272,190,288,31,14.0,22,6.0,6,1.0,79,,,,11,1970-07-18 -4273,191,345,36,12.0,4,8.0,8,0.0,47,,,,80,1970-08-02 -4274,191,357,31,2.0,2,1.0,1,9.0,50,6120300.0,,,1,1970-08-02 -4275,191,234,5,10.0,1,2.0,2,6.0,50,6121000.0,,,1,1970-08-02 -4276,191,303,184,4.0,16,3.0,3,4.0,50,6202100.0,,,1,1970-08-02 -4277,191,242,33,21.0,11,5.0,5,2.0,49,,,,11,1970-08-02 -4278,191,279,80,14.0,5,6.0,6,1.0,49,,,,11,1970-08-02 -4279,191,326,36,23.0,14,7.0,7,0.0,49,,,,11,1970-08-02 -4280,191,340,61,7.0,15,9.0,9,0.0,46,,,,5,1970-08-02 -4281,191,223,31,17.0,13,4.0,4,3.0,50,6235400.0,,,1,1970-08-02 -4282,191,277,36,5.0,6,,11,0.0,34,,,,5,1970-08-02 -4283,191,288,31,9.0,20,,10,0.0,37,,,,5,1970-08-02 -4284,191,364,36,26.0,0,,25,0.0,0,,,,81,1970-08-02 -4285,191,350,83,27.0,0,,24,0.0,0,,,,81,1970-08-02 -4286,191,311,84,25.0,0,,22,0.0,0,,,,81,1970-08-02 -4287,191,319,184,24.0,17,,21,0.0,3,,,,37,1970-08-02 -4288,191,305,80,8.0,21,,20,0.0,4,,,,22,1970-08-02 -4289,191,355,33,3.0,12,,19,0.0,4,,,,44,1970-08-02 -4290,191,332,195,20.0,0,,23,0.0,0,,,,81,1970-08-02 -4291,191,344,64,6.0,8,,17,0.0,7,,,,80,1970-08-02 -4292,191,237,36,22.0,19,,16,0.0,11,,,,5,1970-08-02 -4293,191,206,36,11.0,9,,15,0.0,15,,,,6,1970-08-02 -4294,191,327,36,1.0,7,,14,0.0,20,,,,5,1970-08-02 -4295,191,356,31,16.0,10,,13,0.0,24,,,,5,1970-08-02 -4296,191,222,5,15.0,3,,12,0.0,30,,,,5,1970-08-02 -4297,191,261,64,18.0,18,,18,0.0,5,,,,5,1970-08-02 -4298,192,223,31,8.0,16,15.0,15,0.0,55,,,,15,1970-08-16 -4299,192,303,184,21.0,11,,16,0.0,30,,,,5,1970-08-16 -4300,192,313,84,26.0,19,,18,0.0,25,,,,5,1970-08-16 -4301,192,357,31,6.0,1,,19,0.0,21,,,,5,1970-08-16 -4302,192,327,36,1.0,4,,22,0.0,7,,,,106,1970-08-16 -4303,192,350,83,24.0,24,,21,0.0,13,,,,21,1970-08-16 -4304,192,356,31,7.0,10,,23,0.0,4,,,,23,1970-08-16 -4305,192,279,80,20.0,13,14.0,14,0.0,56,,,,14,1970-08-16 -4306,192,326,36,2.0,9,,24,0.0,0,,,,5,1970-08-16 -4307,192,206,36,5.0,18,,20,0.0,13,,,,3,1970-08-16 -4308,192,355,33,10.0,8,13.0,13,0.0,56,,,,14,1970-08-16 -4309,192,340,61,15.0,12,,17,0.0,27,,,,5,1970-08-16 -4310,192,351,64,18.0,23,11.0,11,0.0,58,,,,12,1970-08-16 -4311,192,332,195,22.0,15,12.0,12,0.0,57,,,,13,1970-08-16 -4312,192,234,5,12.0,3,1.0,1,9.0,60,6137300.0,,,1,1970-08-16 -4313,192,242,33,11.0,17,3.0,3,4.0,60,6225180.0,,,1,1970-08-16 -4314,192,344,64,17.0,22,4.0,4,3.0,59,,,,11,1970-08-16 -4315,192,261,64,16.0,14,5.0,5,2.0,59,,,,11,1970-08-16 -4316,192,222,5,27.0,2,2.0,2,6.0,60,6137910.0,,,1,1970-08-16 -4317,192,362,5,14.0,5,7.0,7,0.0,59,,,,11,1970-08-16 -4318,192,277,36,4.0,5,8.0,8,0.0,59,,,,11,1970-08-16 -4319,192,345,36,3.0,20,9.0,9,0.0,59,,,,11,1970-08-16 -4320,192,319,184,23.0,21,10.0,10,0.0,59,,,,11,1970-08-16 -4321,192,305,80,19.0,7,6.0,6,1.0,59,,,,11,1970-08-16 -4322,193,234,5,2.0,1,,13,0.0,25,,,,8,1970-09-06 -4323,193,351,64,12.0,20,,14,0.0,21,,,,25,1970-09-06 -4324,193,345,36,50.0,7,,19,0.0,3,,,,5,1970-09-06 -4325,193,340,61,14.0,10,,20,0.0,0,,,,10,1970-09-06 -4326,193,356,31,24.0,0,,22,0.0,0,,,,54,1970-09-06 -4327,193,357,31,22.0,0,,23,0.0,0,,,,104,1970-09-06 -4328,193,346,184,38.0,0,,24,0.0,0,,,,81,1970-09-06 -4329,193,355,33,44.0,8,,12,0.0,31,,,,3,1970-09-06 -4330,193,223,31,26.0,0,,25,0.0,0,,,,54,1970-09-06 -4331,193,329,195,36.0,0,,26,0.0,0,,,,81,1970-09-06 -4332,193,288,31,28.0,0,,21,0.0,0,,,,54,1970-09-06 -4333,193,237,36,52.0,13,,11,0.0,35,,,,5,1970-09-06 -4334,193,242,33,46.0,17,5.0,5,2.0,68,5953510.0,,,1,1970-09-06 -4335,193,319,184,32.0,16,,9,0.0,60,,,,62,1970-09-06 -4336,193,332,195,34.0,12,8.0,8,0.0,61,,,,17,1970-09-06 -4337,193,277,36,48.0,18,7.0,7,0.0,67,,,,11,1970-09-06 -4338,193,326,36,20.0,11,6.0,6,1.0,68,6010560.0,,,1,1970-09-06 -4339,193,303,184,30.0,9,4.0,4,3.0,68,5953250.0,,,1,1970-09-06 -4340,193,305,80,40.0,14,3.0,3,4.0,68,5952900.0,,,1,1970-09-06 -4341,193,327,36,18.0,4,2.0,2,6.0,68,5952830.0,,,1,1970-09-06 -4342,193,222,5,4.0,3,1.0,1,9.0,68,5947100.0,,,1,1970-09-06 -4343,193,350,83,56.0,0,,27,0.0,0,,,,81,1970-09-06 -4344,193,344,64,10.0,2,,18,0.0,12,,,,5,1970-09-06 -4345,193,279,80,42.0,5,,17,0.0,14,,,,5,1970-09-06 -4346,193,261,64,8.0,6,,10,0.0,36,,,,5,1970-09-06 -4347,193,313,84,54.0,19,,15,0.0,17,,,,5,1970-09-06 -4348,193,362,5,6.0,15,,16,0.0,14,,,,69,1970-09-06 -4349,194,237,36,26.0,16,,14,0.0,65,,,,62,1970-09-20 -4350,194,345,36,21.0,14,,20,0.0,21,,,,5,1970-09-20 -4351,194,242,33,12.0,18,,19,0.0,22,,,,64,1970-09-20 -4352,194,327,24,3.0,1,,18,0.0,31,,,,109,1970-09-20 -4353,194,261,64,15.0,10,,17,0.0,52,,,,62,1970-09-20 -4354,194,355,33,11.0,19,,16,0.0,57,,,,44,1970-09-20 -4355,194,303,184,5.0,15,,15,0.0,58,,,,5,1970-09-20 -4356,194,332,195,8.0,12,,13,0.0,69,,,,51,1970-09-20 -4357,194,288,31,9.0,20,,12,0.0,77,,,,62,1970-09-20 -4358,194,351,64,16.0,9,10.0,10,0.0,85,,,,15,1970-09-20 -4359,194,313,84,10.0,17,,11,0.0,79,,,,62,1970-09-20 -4360,194,305,80,23.0,13,8.0,8,0.0,85,,,,8,1970-09-20 -4361,194,279,80,24.0,8,7.0,7,0.0,87,,,,13,1970-09-20 -4362,194,319,184,6.0,11,6.0,6,1.0,88,,,,12,1970-09-20 -4363,194,340,61,4.0,5,5.0,5,2.0,89,,,,11,1970-09-20 -4364,194,344,64,14.0,7,4.0,4,3.0,89,,,,11,1970-09-20 -4365,194,277,36,20.0,6,3.0,3,4.0,90,4936300.0,,,1,1970-09-20 -4366,194,222,5,19.0,3,2.0,2,6.0,90,4893200.0,,,1,1970-09-20 -4367,194,234,5,18.0,2,1.0,1,9.0,90,4878400.0,,,1,1970-09-20 -4368,194,326,36,2.0,4,9.0,9,0.0,85,,,,15,1970-09-20 -4369,195,320,61,18.0,13,6.0,6,1.0,107,,,,11,1970-10-04 -4370,195,303,184,8.0,11,7.0,7,0.0,106,,,,12,1970-10-04 -4371,195,277,36,12.0,5,5.0,5,2.0,107,,,,11,1970-10-04 -4372,195,355,33,15.0,16,10.0,10,0.0,105,,,,13,1970-10-04 -4373,195,344,64,19.0,4,2.0,2,6.0,108,7089180.0,,,1,1970-10-04 -4374,195,223,31,24.0,3,1.0,1,9.0,108,7052790.0,,,1,1970-10-04 -4375,195,279,80,7.0,12,8.0,8,0.0,105,,,,13,1970-10-04 -4376,195,234,5,3.0,1,4.0,4,3.0,107,,,,11,1970-10-04 -4377,195,345,36,11.0,23,9.0,9,0.0,105,,,,13,1970-10-04 -4378,195,316,31,23.0,9,3.0,3,4.0,108,7097960.0,,,1,1970-10-04 -4379,195,237,36,29.0,15,11.0,11,0.0,104,,,,14,1970-10-04 -4380,195,332,195,10.0,0,,27,0.0,0,,,,81,1970-10-04 -4381,195,352,31,28.0,0,,26,0.0,0,,,,81,1970-10-04 -4382,195,366,64,32.0,0,,25,0.0,0,,,,81,1970-10-04 -4383,195,340,61,17.0,8,,24,0.0,6,,,,5,1970-10-04 -4384,195,351,64,21.0,14,,23,0.0,10,,,,5,1970-10-04 -4385,195,365,33,31.0,22,,21,0.0,21,,,,95,1970-10-04 -4386,195,305,80,6.0,18,,20,0.0,27,,,,64,1970-10-04 -4387,195,346,184,27.0,24,,19,0.0,50,,,,110,1970-10-04 -4388,195,261,64,20.0,7,,22,0.0,14,,,,5,1970-10-04 -4389,195,326,36,2.0,17,,17,0.0,62,,,,36,1970-10-04 -4390,195,288,31,14.0,10,,16,0.0,72,,,,8,1970-10-04 -4391,195,327,24,1.0,2,,15,0.0,82,,,,44,1970-10-04 -4392,195,319,184,9.0,21,14.0,14,0.0,100,,,,18,1970-10-04 -4393,195,222,5,4.0,6,13.0,13,0.0,101,,,,17,1970-10-04 -4394,195,242,33,16.0,19,12.0,12,0.0,104,,,,14,1970-10-04 -4395,195,313,84,30.0,20,,18,0.0,61,,,,22,1970-10-04 -4396,196,345,36,11.0,16,,17,0.0,3,,,,5,1970-10-25 -4397,196,344,64,19.0,7,6.0,6,1.0,65,6893060.0,,,1,1970-10-25 -4398,196,261,64,20.0,13,7.0,7,0.0,64,,,,11,1970-10-25 -4399,196,340,61,17.0,15,8.0,8,0.0,64,,,,11,1970-10-25 -4400,196,279,80,7.0,11,9.0,9,0.0,61,,,,14,1970-10-25 -4401,196,316,31,23.0,12,,10,0.0,56,,,,62,1970-10-25 -4402,196,355,33,15.0,4,,11,0.0,52,,,,5,1970-10-25 -4403,196,223,31,24.0,18,,18,0.0,1,,,,5,1970-10-25 -4404,196,288,31,14.0,8,,16,0.0,4,,,,25,1970-10-25 -4405,196,222,5,4.0,1,2.0,2,6.0,65,6832940.0,,,1,1970-10-25 -4406,196,242,33,16.0,17,,14,0.0,15,,,,69,1970-10-25 -4407,196,305,80,6.0,6,5.0,5,2.0,65,6858410.0,,,1,1970-10-25 -4408,196,277,36,12.0,5,4.0,4,3.0,65,6855350.0,,,1,1970-10-25 -4409,196,303,184,8.0,14,3.0,3,4.0,65,6854270.0,,,1,1970-10-25 -4410,196,319,184,9.0,10,,13,0.0,27,,,,5,1970-10-25 -4411,196,234,5,3.0,3,1.0,1,9.0,65,6808300.0,,,1,1970-10-25 -4412,196,327,24,1.0,2,,12,0.0,33,,,,22,1970-10-25 -4413,196,326,36,2.0,9,,15,0.0,8,,,,5,1970-10-25 -4414,197,333,33,25.0,20,,22,0.0,22,,,,5,1971-03-06 -4415,197,311,61,28.0,17,7.0,7,0.0,78,,,,11,1971-03-06 -4416,197,338,197,26.0,25,,25,0.0,5,,,,5,1971-03-06 -4417,197,346,0,23.0,23,,24,0.0,5,,,,22,1971-03-06 -4418,197,319,0,12.0,11,,23,0.0,7,,,,95,1971-03-06 -4419,197,339,197,24.0,21,,21,0.0,30,,,,24,1971-03-06 -4420,197,303,0,11.0,7,6.0,6,1.0,78,,,,11,1971-03-06 -4421,197,292,33,15.0,16,,19,0.0,31,,,,5,1971-03-06 -4422,197,223,177,2.0,5,,14,0.0,58,,,,5,1971-03-06 -4423,197,332,196,8.0,22,13.0,13,0.0,75,,,,14,1971-03-06 -4424,197,242,61,21.0,15,12.0,12,0.0,77,,,,12,1971-03-06 -4425,197,279,197,22.0,18,11.0,11,0.0,77,,,,12,1971-03-06 -4426,197,237,197,7.0,13,10.0,10,0.0,77,,,,12,1971-03-06 -4427,197,288,33,14.0,19,9.0,9,0.0,77,,,,12,1971-03-06 -4428,197,340,61,20.0,6,,15,0.0,56,,,,6,1971-03-06 -4429,197,234,5,4.0,8,8.0,8,0.0,78,,,,11,1971-03-06 -4430,197,327,24,9.0,1,2.0,2,6.0,79,6476400.0,,,1,1971-03-06 -4431,197,222,5,5.0,3,3.0,3,4.0,79,6486900.0,,,1,1971-03-06 -4432,197,316,177,3.0,14,4.0,4,3.0,79,6524900.0,,,1,1971-03-06 -4433,197,277,80,19.0,2,5.0,5,2.0,78,,,,11,1971-03-06 -4434,197,326,24,10.0,9,,16,0.0,45,,,,3,1971-03-06 -4435,197,306,64,27.0,24,,17,0.0,42,,,,68,1971-03-06 -4436,197,344,64,16.0,10,,18,0.0,33,,,,25,1971-03-06 -4437,197,206,5,6.0,4,1.0,1,9.0,79,6455500.0,,,1,1971-03-06 -4438,197,345,64,17.0,12,,20,0.0,31,,,,25,1971-03-06 -4439,198,288,33,7.0,10,,22,0.0,5,,,,38,1971-04-18 -4440,198,332,196,17.0,18,,17,0.0,26,,,,7,1971-04-18 -4441,198,345,64,15.0,15,,21,0.0,5,,,,6,1971-04-18 -4442,198,242,61,25.0,19,,20,0.0,9,,,,32,1971-04-18 -4443,198,279,197,27.0,11,,14,0.0,53,,,,5,1971-04-18 -4444,198,237,197,18.0,13,,18,0.0,24,,,,80,1971-04-18 -4445,198,223,177,2.0,14,,13,0.0,54,,,,22,1971-04-18 -4446,198,316,177,3.0,16,,12,0.0,58,,,,62,1971-04-18 -4447,198,340,61,24.0,22,11.0,11,0.0,67,,,,18,1971-04-18 -4448,198,306,64,16.0,17,10.0,10,0.0,71,,,,14,1971-04-18 -4449,198,313,33,8.0,21,9.0,9,0.0,72,,,,13,1971-04-18 -4450,198,319,0,10.0,7,8.0,8,0.0,73,,,,12,1971-04-18 -4451,198,326,24,12.0,12,7.0,7,0.0,74,,,,11,1971-04-18 -4452,198,206,5,6.0,8,,15,0.0,50,,,,5,1971-04-18 -4453,198,305,80,21.0,6,6.0,6,1.0,74,,,,11,1971-04-18 -4454,198,303,0,9.0,9,5.0,5,2.0,75,6630400.0,,,1,1971-04-18 -4455,198,344,64,14.0,5,4.0,4,3.0,75,6621300.0,,,1,1971-04-18 -4456,198,277,80,20.0,3,3.0,3,4.0,75,6601500.0,,,1,1971-04-18 -4457,198,234,5,4.0,1,2.0,2,6.0,75,6546800.0,,,1,1971-04-18 -4458,198,327,24,11.0,4,1.0,1,9.0,75,6543400.0,,,1,1971-04-18 -4459,198,222,5,5.0,2,,19,0.0,13,,,,5,1971-04-18 -4460,198,338,197,19.0,20,,16,0.0,46,,,,48,1971-04-18 -4461,199,319,0,10.0,14,,15,0.0,22,,,,3,1971-05-23 -4462,199,327,24,11.0,1,1.0,1,9.0,80,6741300.0,,,1,1971-05-23 -4463,199,237,197,17.0,6,2.0,2,6.0,80,6766900.0,,,1,1971-05-23 -4464,199,234,5,4.0,2,3.0,3,4.0,80,6794600.0,,,1,1971-05-23 -4465,199,303,0,9.0,6,4.0,4,3.0,80,6808000.0,,,1,1971-05-23 -4466,199,223,177,1.0,17,5.0,5,2.0,79,,,,11,1971-05-23 -4467,199,242,61,24.0,16,6.0,6,1.0,79,,,,11,1971-05-23 -4468,199,340,61,22.0,10,7.0,7,0.0,79,,,,11,1971-05-23 -4469,199,222,5,5.0,11,,14,0.0,24,,,,3,1971-05-23 -4470,199,344,64,15.0,5,9.0,9,0.0,76,,,,14,1971-05-23 -4471,199,279,197,27.0,13,8.0,8,0.0,77,,,,13,1971-05-23 -4472,199,345,64,14.0,3,,11,0.0,58,,,,108,1971-05-23 -4473,199,305,80,21.0,7,,12,0.0,47,,,,24,1971-05-23 -4474,199,277,80,20.0,4,,13,0.0,45,,,,24,1971-05-23 -4475,199,341,197,28.0,0,,22,0.0,0,,,,81,1971-05-23 -4476,199,338,197,18.0,0,,21,0.0,0,,,,81,1971-05-23 -4477,199,306,64,16.0,0,,19,0.0,0,,,,81,1971-05-23 -4478,199,288,33,7.0,9,,18,0.0,1,,,,3,1971-05-23 -4479,199,326,24,12.0,15,,17,0.0,5,,,,3,1971-05-23 -4480,199,316,177,2.0,12,,16,0.0,21,,,,67,1971-05-23 -4481,199,313,33,8.0,18,10.0,10,0.0,76,,,,14,1971-05-23 -4482,199,206,5,6.0,0,,20,0.0,0,,,,81,1971-05-23 -4483,200,316,177,14.0,4,,20,0.0,17,,,,2,1971-06-20 -4484,200,277,80,20.0,5,,23,0.0,2,,,,20,1971-06-20 -4485,200,337,198,15.0,22,,22,0.0,5,,,,3,1971-06-20 -4486,200,206,5,4.0,16,,21,0.0,5,,,,48,1971-06-20 -4487,200,242,61,29.0,18,,19,0.0,19,,,,2,1971-06-20 -4488,200,313,33,25.0,19,,17,0.0,39,,,,22,1971-06-20 -4489,200,234,5,2.0,1,1.0,1,9.0,70,6980000.0,,,1,1971-06-20 -4490,200,344,64,8.0,2,2.0,2,6.0,70,6987990.0,,,1,1971-06-20 -4491,200,222,5,3.0,4,3.0,3,4.0,69,,,,11,1971-06-20 -4492,200,237,197,16.0,13,4.0,4,3.0,68,,,,12,1971-06-20 -4493,200,340,61,23.0,7,5.0,5,2.0,68,,,,12,1971-06-20 -4494,200,345,64,9.0,8,6.0,6,1.0,68,,,,12,1971-06-20 -4495,200,297,61,30.0,21,8.0,8,0.0,65,,,,15,1971-06-20 -4496,200,305,80,21.0,11,9.0,9,0.0,65,,,,15,1971-06-20 -4497,200,288,33,24.0,16,10.0,10,0.0,65,,,,15,1971-06-20 -4498,200,327,24,5.0,3,11.0,11,0.0,65,,,,15,1971-06-20 -4499,200,303,0,26.0,14,12.0,12,0.0,63,,,,17,1971-06-20 -4500,200,279,197,31.0,15,,13,0.0,62,,,,62,1971-06-20 -4501,200,341,197,22.0,24,,14,0.0,60,,,,62,1971-06-20 -4502,200,326,24,6.0,12,,18,0.0,29,,,,3,1971-06-20 -4503,200,306,64,10.0,9,7.0,7,0.0,66,,,,14,1971-06-20 -4504,200,338,197,19.0,17,,16,0.0,57,,,,5,1971-06-20 -4505,200,319,0,28.0,23,,15,0.0,60,,,,62,1971-06-20 -4506,201,348,197,28.0,22,,14,0.0,46,,,,62,1971-07-04 -4507,201,327,24,11.0,1,1.0,1,9.0,55,6402300.0,,,1,1971-07-04 -4508,201,326,24,12.0,7,2.0,2,6.0,55,6430420.0,,,1,1971-07-04 -4509,201,223,177,1.0,17,3.0,3,4.0,55,6436370.0,,,1,1971-07-04 -4510,201,345,64,14.0,6,4.0,4,3.0,55,6439470.0,,,1,1971-07-04 -4511,201,277,80,20.0,9,5.0,5,2.0,55,6443380.0,,,1,1971-07-04 -4512,201,316,177,2.0,15,6.0,6,1.0,55,6478320.0,,,1,1971-07-04 -4513,201,305,80,21.0,8,7.0,7,0.0,55,6479230.0,,,1,1971-07-04 -4514,201,340,61,22.0,13,8.0,8,0.0,55,6487210.0,,,1,1971-07-04 -4515,201,347,197,34.0,23,13.0,13,0.0,50,,,,15,1971-07-04 -4516,201,319,0,10.0,19,9.0,9,0.0,54,,,,11,1971-07-04 -4517,201,242,61,24.0,10,11.0,11,0.0,53,,,,12,1971-07-04 -4518,201,338,197,18.0,21,,23,0.0,4,,,,48,1971-07-04 -4519,201,234,5,4.0,3,,22,0.0,4,,,,5,1971-07-04 -4520,201,303,0,9.0,11,,21,0.0,16,,,,80,1971-07-04 -4521,201,237,196,17.0,12,,20,0.0,19,,,,5,1971-07-04 -4522,201,222,5,5.0,2,,19,0.0,20,,,,3,1971-07-04 -4523,201,313,33,8.0,14,12.0,12,0.0,50,,,,51,1971-07-04 -4524,201,332,196,19.0,20,,17,0.0,31,,,,5,1971-07-04 -4525,201,288,33,7.0,4,,16,0.0,34,,,,108,1971-07-04 -4526,201,279,197,27.0,18,,15,0.0,45,,,,6,1971-07-04 -4527,201,306,64,16.0,16,10.0,10,0.0,54,,,,11,1971-07-04 -4528,201,344,64,15.0,5,,18,0.0,27,,,,80,1971-07-04 -4529,202,332,196,19.0,24,,14,0.0,56,,,,62,1971-07-17 -4530,202,303,0,9.0,8,,19,0.0,32,,,,5,1971-07-17 -4531,202,261,0,11.0,16,,24,0.0,0,,,,3,1971-07-17 -4532,202,288,33,7.0,22,,23,0.0,0,,,,3,1971-07-17 -4533,202,292,177,2.0,13,,22,0.0,1,,,,5,1971-07-17 -4534,202,328,197,6.0,20,,21,0.0,21,,,,51,1971-07-17 -4535,202,319,0,10.0,14,,15,0.0,53,,,,5,1971-07-17 -4536,202,277,80,21.0,9,,18,0.0,35,,,,5,1971-07-17 -4537,202,222,5,5.0,1,,17,0.0,48,,,,51,1971-07-17 -4538,202,234,5,4.0,6,,16,0.0,51,,,,5,1971-07-17 -4539,202,327,24,12.0,2,1.0,1,9.0,68,5491500.0,,,1,1971-07-17 -4540,202,237,197,18.0,5,2.0,2,6.0,68,5527600.0,,,1,1971-07-17 -4541,202,320,61,25.0,23,,20,0.0,23,,,,22,1971-07-17 -4542,202,279,197,26.0,17,4.0,4,3.0,67,,,,11,1971-07-17 -4543,202,223,177,1.0,4,3.0,3,4.0,68,5542000.0,,,1,1971-07-17 -4544,202,316,198,3.0,19,,13,0.0,57,,,,62,1971-07-17 -4545,202,313,33,8.0,7,12.0,12,0.0,63,,,,6,1971-07-17 -4546,202,326,24,14.0,10,10.0,10,0.0,65,,,,13,1971-07-17 -4547,202,329,197,20.0,21,11.0,11,0.0,65,,,,13,1971-07-17 -4548,202,306,64,17.0,11,8.0,8,0.0,66,,,,12,1971-07-17 -4549,202,305,80,22.0,15,7.0,7,0.0,66,,,,12,1971-07-17 -4550,202,340,61,23.0,11,6.0,6,1.0,67,,,,11,1971-07-17 -4551,202,242,61,24.0,12,5.0,5,2.0,67,,,,11,1971-07-17 -4552,202,345,64,16.0,3,9.0,9,0.0,66,,,,12,1971-07-17 -4553,203,223,177,8.0,8,,13,0.0,8,,,,44,1971-08-01 -4554,203,288,33,24.0,13,9.0,9,0.0,12,5753300.0,,,1,1971-08-01 -4555,203,329,196,17.0,21,12.0,12,0.0,10,,,,12,1971-08-01 -4556,203,349,64,22.0,18,11.0,11,0.0,11,,,,11,1971-08-01 -4557,203,242,61,12.0,12,10.0,10,0.0,11,,,,11,1971-08-01 -4558,203,316,177,9.0,17,8.0,8,0.0,12,5748000.0,,,1,1971-08-01 -4559,203,326,24,3.0,5,2.0,2,6.0,12,5386400.0,,,1,1971-08-01 -4560,203,237,197,15.0,3,5.0,5,2.0,12,5505400.0,,,1,1971-08-01 -4561,203,206,5,5.0,11,4.0,4,3.0,12,5481300.0,,,1,1971-08-01 -4562,203,222,5,6.0,4,3.0,3,4.0,12,5393400.0,,,1,1971-08-01 -4563,203,327,24,2.0,1,1.0,1,9.0,12,5356300.0,,,1,1971-08-01 -4564,203,345,64,21.0,3,,14,0.0,6,,,,2,1971-08-01 -4565,203,313,33,25.0,9,6.0,6,1.0,12,5534900.0,,,1,1971-08-01 -4566,203,277,80,10.0,16,,15,0.0,6,,,,3,1971-08-01 -4567,203,340,61,7.0,15,7.0,7,0.0,12,5555300.0,,,1,1971-08-01 -4568,203,319,0,20.0,19,,17,0.0,5,,,,3,1971-08-01 -4569,203,303,0,18.0,6,,18,0.0,3,,,,95,1971-08-01 -4570,203,328,197,28.0,22,,19,0.0,3,,,,2,1971-08-01 -4571,203,306,64,23.0,14,,20,0.0,2,,,,5,1971-08-01 -4572,203,332,196,16.0,20,,21,0.0,2,,,,98,1971-08-01 -4573,203,234,5,4.0,2,,22,0.0,1,,,,3,1971-08-01 -4574,203,346,0,27.0,0,,23,0.0,0,,,,81,1971-08-01 -4575,203,279,197,14.0,10,,16,0.0,5,,,,22,1971-08-01 -4576,204,328,197,27.0,19,,13,0.0,47,,,,62,1971-08-15 -4577,204,326,24,12.0,3,,14,0.0,42,,,,5,1971-08-15 -4578,204,327,24,11.0,2,,15,0.0,35,,,,86,1971-08-15 -4579,204,234,5,4.0,6,,16,0.0,31,,,,5,1971-08-15 -4580,204,306,64,15.0,14,,20,0.0,5,,,,80,1971-08-15 -4581,204,340,61,22.0,18,,18,0.0,12,,,,5,1971-08-15 -4582,204,329,196,19.0,15,12.0,12,0.0,51,,,,13,1971-08-15 -4583,204,303,0,9.0,9,,21,0.0,4,,,,5,1971-08-15 -4584,204,346,0,28.0,20,,22,0.0,0,,,,95,1971-08-15 -4585,204,181,197,26.0,21,,17,0.0,20,,,,64,1971-08-15 -4586,204,336,64,16.0,17,11.0,11,0.0,52,,,,12,1971-08-15 -4587,204,222,5,5.0,4,,19,0.0,8,,,,5,1971-08-15 -4588,204,261,0,10.0,22,9.0,9,0.0,53,,,,11,1971-08-15 -4589,204,237,197,17.0,11,8.0,8,0.0,53,,,,11,1971-08-15 -4590,204,242,61,24.0,12,7.0,7,0.0,54,5521330.0,,,1,1971-08-15 -4591,204,279,197,25.0,13,6.0,6,1.0,54,5508420.0,,,1,1971-08-15 -4592,204,288,33,7.0,8,5.0,5,2.0,54,5472340.0,,,1,1971-08-15 -4593,204,316,177,3.0,10,4.0,4,3.0,54,5455780.0,,,1,1971-08-15 -4594,204,313,33,8.0,7,3.0,3,4.0,54,5443680.0,,,1,1971-08-15 -4595,204,223,177,2.0,5,2.0,2,6.0,54,5428030.0,,,1,1971-08-15 -4596,204,345,64,14.0,1,1.0,1,9.0,54,5423910.0,,,1,1971-08-15 -4597,204,319,64,23.0,16,10.0,10,0.0,52,,,,12,1971-08-15 -4598,205,222,5,4.0,8,,16,0.0,17,,,,5,1971-09-05 -4599,205,332,196,23.0,20,,15,0.0,33,,,,5,1971-09-05 -4600,205,279,197,16.0,10,,14,0.0,40,,,,22,1971-09-05 -4601,205,328,197,24.0,16,,13,0.0,41,,,,5,1971-09-05 -4602,205,223,198,5.0,18,8.0,8,0.0,54,,,,11,1971-09-05 -4603,205,288,33,10.0,14,,11,0.0,47,,,,6,1971-09-05 -4604,205,346,0,28.0,21,10.0,10,0.0,51,,,,14,1971-09-05 -4605,205,345,64,20.0,3,9.0,9,0.0,53,,,,12,1971-09-05 -4606,205,234,5,3.0,2,,17,0.0,15,,,,5,1971-09-05 -4607,205,261,0,14.0,13,7.0,7,0.0,55,4777430.0,,,1,1971-09-05 -4608,205,196,197,26.0,24,,12,0.0,47,,,,62,1971-09-05 -4609,205,327,24,30.0,7,,18,0.0,15,,,,5,1971-09-05 -4610,205,340,61,7.0,15,,23,0.0,3,,,,5,1971-09-05 -4611,205,313,33,11.0,9,,20,0.0,5,,,,22,1971-09-05 -4612,205,350,83,27.0,22,,21,0.0,5,,,,22,1971-09-05 -4613,205,336,64,21.0,12,,22,0.0,3,,,,5,1971-09-05 -4614,205,277,80,12.0,1,6.0,6,1.0,55,4724960.0,,,1,1971-09-05 -4615,205,306,64,19.0,4,5.0,5,2.0,55,4693210.0,,,1,1971-09-05 -4616,205,304,61,9.0,17,4.0,4,3.0,55,4692780.0,,,1,1971-09-05 -4617,205,326,24,2.0,5,3.0,3,4.0,55,4692690.0,,,1,1971-09-05 -4618,205,237,197,25.0,6,2.0,2,6.0,55,4692610.0,,,1,1971-09-05 -4619,205,319,64,18.0,11,1.0,1,9.0,55,4692600.0,,,1,1971-09-05 -4620,205,242,61,8.0,23,,24,0.0,0,,,,3,1971-09-05 -4621,205,329,197,22.0,19,,19,0.0,11,,,,10,1971-09-05 -4622,206,353,33,26.0,0,,26,0.0,0,,,,81,1971-09-19 -4623,206,306,64,16.0,9,,25,0.0,0,,,,3,1971-09-19 -4624,206,287,0,10.0,8,3.0,3,4.0,64,7008900.0,,,1,1971-09-19 -4625,206,288,33,37.0,15,,23,0.0,2,,,,3,1971-09-19 -4626,206,237,197,17.0,6,2.0,2,6.0,64,6951400.0,,,1,1971-09-19 -4627,206,316,177,3.0,7,5.0,5,2.0,63,,,,11,1971-09-19 -4628,206,326,24,12.0,3,6.0,6,1.0,62,,,,12,1971-09-19 -4629,206,223,177,2.0,4,7.0,7,0.0,62,,,,12,1971-09-19 -4630,206,234,5,4.0,12,8.0,8,0.0,62,,,,12,1971-09-19 -4631,206,345,64,14.0,2,9.0,9,0.0,61,,,,13,1971-09-19 -4632,206,277,80,20.0,5,10.0,10,0.0,61,,,,13,1971-09-19 -4633,206,340,61,22.0,14,11.0,11,0.0,60,,,,14,1971-09-19 -4634,206,336,64,31.0,19,12.0,12,0.0,60,,,,14,1971-09-19 -4635,206,206,5,6.0,13,13.0,13,0.0,60,,,,14,1971-09-19 -4636,206,319,64,15.0,16,14.0,14,0.0,59,,,,15,1971-09-19 -4637,206,351,64,28.0,21,15.0,15,0.0,59,,,,15,1971-09-19 -4638,206,329,197,18.0,20,16.0,16,0.0,57,,,,17,1971-09-19 -4639,206,328,197,19.0,22,,17,0.0,56,,,,62,1971-09-19 -4640,206,352,177,35.0,25,,18,0.0,55,,,,62,1971-09-19 -4641,206,242,61,24.0,23,,19,0.0,26,,,,25,1971-09-19 -4642,206,305,80,21.0,11,,20,0.0,15,,,,3,1971-09-19 -4643,206,341,197,33.0,24,,21,0.0,13,,,,51,1971-09-19 -4644,206,222,5,5.0,18,,22,0.0,7,,,,3,1971-09-19 -4645,206,313,33,8.0,17,,24,0.0,1,,,,80,1971-09-19 -4646,206,327,24,11.0,1,1.0,1,9.0,64,6913100.0,,,1,1971-09-19 -4647,206,303,0,9.0,10,4.0,4,3.0,63,,,,11,1971-09-19 -4648,207,303,0,7.0,3,,22,0.0,47,,,,3,1971-10-03 -4649,207,329,197,26.0,23,,27,0.0,11,,,,36,1971-10-03 -4650,207,279,197,21.0,20,,26,0.0,23,,,,5,1971-10-03 -4651,207,343,61,19.0,17,,25,0.0,15,,,,5,1971-10-03 -4652,207,353,33,24.0,27,,24,0.0,30,,,,22,1971-10-03 -4653,207,313,33,23.0,15,,23,0.0,41,,,,5,1971-10-03 -4654,207,352,177,30.0,29,,21,0.0,49,,,,62,1971-10-03 -4655,207,223,177,2.0,2,,20,0.0,49,,,,62,1971-10-03 -4656,207,234,5,32.0,7,,19,0.0,49,,,,91,1971-10-03 -4657,207,341,197,33.0,25,,18,0.0,52,,,,62,1971-10-03 -4658,207,340,61,18.0,13,17.0,17,0.0,54,,,,15,1971-10-03 -4659,207,346,0,29.0,28,16.0,16,0.0,54,,,,60,1971-10-03 -4660,207,304,61,20.0,14,15.0,15,0.0,54,,,,3,1971-10-03 -4661,207,316,177,3.0,9,,28,0.0,5,,,,23,1971-10-03 -4662,207,354,64,28.0,24,14.0,14,0.0,56,,,,13,1971-10-03 -4663,207,277,80,11.0,8,12.0,12,0.0,57,,,,12,1971-10-03 -4664,207,332,196,27.0,26,11.0,11,0.0,57,,,,12,1971-10-03 -4665,207,321,0,31.0,22,10.0,10,0.0,58,,,,11,1971-10-03 -4666,207,319,64,15.0,21,9.0,9,0.0,58,,,,11,1971-10-03 -4667,207,305,80,12.0,10,8.0,8,0.0,58,,,,11,1971-10-03 -4668,207,288,33,22.0,18,7.0,7,0.0,58,,,,11,1971-10-03 -4669,207,222,5,5.0,4,6.0,6,1.0,59,6308417.0,,,1,1971-10-03 -4670,207,327,24,8.0,1,5.0,5,2.0,59,6291994.0,,,1,1971-10-03 -4671,207,306,64,16.0,12,4.0,4,3.0,59,6288740.0,,,1,1971-10-03 -4672,207,237,197,25.0,11,3.0,3,4.0,59,6276061.0,,,1,1971-10-03 -4673,207,345,64,14.0,6,2.0,2,6.0,59,6272053.0,,,1,1971-10-03 -4674,207,326,24,9.0,5,1.0,1,9.0,59,6231991.0,,,1,1971-10-03 -4675,207,336,64,17.0,16,13.0,13,0.0,57,,,,12,1971-10-03 -4676,207,308,24,10.0,19,,29,0.0,1,,,,8,1971-10-03 -4677,208,206,5,10.0,9,,16,0.0,20,,,,5,1972-01-23 -4678,208,306,64,3.0,13,9.0,9,0.0,93,,,,12,1972-01-23 -4679,208,223,31,11.0,5,,12,0.0,61,,,,22,1972-01-23 -4680,208,279,36,23.0,15,8.0,8,0.0,93,,,,12,1972-01-23 -4681,208,198,33,2.0,1,7.0,7,0.0,93,,,,12,1972-01-23 -4682,208,237,36,14.0,10,6.0,6,1.0,94,,,,11,1972-01-23 -4683,208,313,61,19.0,11,5.0,5,2.0,95,7148210.0,,,1,1972-01-23 -4684,208,222,5,9.0,6,4.0,4,3.0,95,7145820.0,,,1,1972-01-23 -4685,208,234,5,8.0,8,3.0,3,4.0,95,7138490.0,,,1,1972-01-23 -4686,208,303,0,17.0,4,2.0,2,6.0,95,7105060.0,,,1,1972-01-23 -4687,208,327,24,21.0,2,1.0,1,9.0,95,7079100.0,,,1,1972-01-23 -4688,208,288,33,1.0,16,,18,0.0,11,,,,48,1972-01-23 -4689,208,332,61,20.0,14,,17,0.0,11,,,,69,1972-01-23 -4690,208,337,31,12.0,20,,19,0.0,8,,,,2,1972-01-23 -4691,208,319,64,5.0,18,,20,0.0,1,,,,44,1972-01-23 -4692,208,338,64,6.0,21,,21,0.0,1,,,,3,1972-01-23 -4693,208,277,80,16.0,12,,22,0.0,0,,,,54,1972-01-23 -4694,208,326,24,22.0,17,,13,0.0,59,,,,6,1972-01-23 -4695,208,316,64,4.0,7,,14,0.0,59,,,,47,1972-01-23 -4696,208,308,0,18.0,3,,15,0.0,49,,,,5,1972-01-23 -4697,208,336,64,7.0,19,10.0,10,0.0,93,,,,12,1972-01-23 -4698,208,181,36,15.0,22,11.0,11,0.0,93,,,,12,1972-01-23 -4699,209,339,61,27.0,26,16.0,16,0.0,73,,,,20,1972-03-04 -4700,209,249,36,22.0,24,17.0,17,0.0,73,,,,16,1972-03-04 -4701,209,306,64,23.0,16,,18,0.0,70,,,,62,1972-03-04 -4702,209,332,61,18.0,20,,19,0.0,69,,,,62,1972-03-04 -4703,209,319,64,11.0,18,,20,0.0,65,,,,62,1972-03-04 -4704,209,305,64,10.0,11,,21,0.0,61,,,,5,1972-03-04 -4705,209,327,24,1.0,1,,22,0.0,45,,,,6,1972-03-04 -4706,209,304,61,17.0,4,,23,0.0,28,,,,22,1972-03-04 -4707,209,198,33,20.0,15,,24,0.0,27,,,,69,1972-03-04 -4708,209,313,61,16.0,10,,25,0.0,9,,,,5,1972-03-04 -4709,209,292,31,26.0,17,,26,0.0,2,,,,48,1972-03-04 -4710,209,326,24,2.0,8,9.0,9,0.0,78,,,,11,1972-03-04 -4711,209,337,31,9.0,19,10.0,10,0.0,78,,,,11,1972-03-04 -4712,209,234,5,5.0,7,8.0,8,0.0,78,,,,11,1972-03-04 -4713,209,279,36,21.0,22,11.0,11,0.0,78,,,,11,1972-03-04 -4714,209,222,5,6.0,2,12.0,12,0.0,77,,,,12,1972-03-04 -4715,209,242,36,25.0,25,13.0,13,0.0,77,,,,12,1972-03-04 -4716,209,277,80,15.0,13,15.0,15,0.0,76,,,,13,1972-03-04 -4717,209,181,36,4.0,21,7.0,7,0.0,78,,,,11,1972-03-04 -4718,209,336,64,24.0,23,14.0,14,0.0,76,,,,13,1972-03-04 -4719,209,237,36,3.0,9,5.0,5,2.0,79,6398100.0,,,1,1972-03-04 -4720,209,206,5,7.0,6,4.0,4,3.0,79,6387600.0,,,1,1972-03-04 -4721,209,308,0,14.0,12,3.0,3,4.0,79,6374900.0,,,1,1972-03-04 -4722,209,223,31,8.0,3,2.0,2,6.0,79,6363200.0,,,1,1972-03-04 -4723,209,303,0,12.0,5,1.0,1,9.0,79,6349100.0,,,1,1972-03-04 -4724,209,288,33,19.0,14,6.0,6,1.0,78,,,,11,1972-03-04 -4725,210,206,5,7.0,5,,19,0.0,23,,,,51,1972-05-01 -4726,210,303,0,11.0,2,,16,0.0,48,,,,6,1972-05-01 -4727,210,306,64,25.0,20,,17,0.0,38,,,,5,1972-05-01 -4728,210,316,64,10.0,10,,18,0.0,24,,,,3,1972-05-01 -4729,210,304,61,15.0,15,,20,0.0,20,,,,10,1972-05-01 -4730,210,319,64,8.0,21,,15,0.0,65,,,,5,1972-05-01 -4731,210,242,36,16.0,17,,22,0.0,15,,,,3,1972-05-01 -4732,210,305,64,19.0,7,,23,0.0,9,,,,6,1972-05-01 -4733,210,181,36,24.0,25,,24,0.0,7,,,,24,1972-05-01 -4734,210,338,64,28.0,22,,25,0.0,6,,,,3,1972-05-01 -4735,210,328,36,23.0,0,,26,0.0,0,,,,81,1972-05-01 -4736,210,237,36,2.0,9,,21,0.0,16,,,,95,1972-05-01 -4737,210,326,24,3.0,12,,14,0.0,65,,,,80,1972-05-01 -4738,210,279,36,14.0,19,11.0,11,0.0,86,,,,14,1972-05-01 -4739,210,327,24,1.0,4,,12,0.0,69,,,,3,1972-05-01 -4740,210,234,5,4.0,1,2.0,2,6.0,90,7440120.0,,,1,1972-05-01 -4741,210,222,5,6.0,8,3.0,3,4.0,89,,,,11,1972-05-01 -4742,210,332,61,26.0,13,4.0,4,3.0,89,,,,11,1972-05-01 -4743,210,308,0,20.0,11,5.0,5,2.0,89,,,,11,1972-05-01 -4744,210,249,36,29.0,16,6.0,6,1.0,89,,,,11,1972-05-01 -4745,210,223,31,5.0,3,1.0,1,9.0,90,7421200.0,,,1,1972-05-01 -4746,210,313,61,12.0,18,8.0,8,0.0,88,,,,12,1972-05-01 -4747,210,337,31,21.0,24,9.0,9,0.0,87,,,,13,1972-05-01 -4748,210,288,33,18.0,23,10.0,10,0.0,86,,,,14,1972-05-01 -4749,210,277,80,9.0,6,,13,0.0,66,,,,6,1972-05-01 -4750,210,289,33,22.0,14,7.0,7,0.0,88,,,,12,1972-05-01 -4751,211,181,36,4.0,22,16.0,16,0.0,74,,,,16,1972-05-14 -4752,211,249,36,23.0,24,17.0,17,0.0,72,,,,18,1972-05-14 -4753,211,326,24,2.0,12,,18,0.0,70,,,,62,1972-05-14 -4754,211,279,36,22.0,9,,19,0.0,58,,,,3,1972-05-14 -4755,211,222,5,7.0,3,,20,0.0,51,,,,3,1972-05-14 -4756,211,306,64,19.0,20,,22,0.0,47,,,,3,1972-05-14 -4757,211,313,61,10.0,13,,23,0.0,31,,,,3,1972-05-14 -4758,211,319,64,18.0,5,,24,0.0,27,,,,3,1972-05-14 -4759,211,316,64,28.0,16,,25,0.0,16,,,,5,1972-05-14 -4760,211,303,0,14.0,7,15.0,15,0.0,74,,,,16,1972-05-14 -4761,211,304,61,11.0,11,,21,0.0,48,,,,3,1972-05-14 -4762,211,337,31,9.0,14,14.0,14,0.0,75,,,,15,1972-05-14 -4763,211,328,36,5.0,23,13.0,13,0.0,76,,,,14,1972-05-14 -4764,211,288,33,20.0,20,12.0,12,0.0,76,,,,14,1972-05-14 -4765,211,234,5,6.0,2,2.0,2,6.0,80,8853500.0,,,1,1972-05-14 -4766,211,223,31,8.0,1,3.0,3,4.0,79,,,,11,1972-05-14 -4767,211,327,24,1.0,8,4.0,4,3.0,78,,,,12,1972-05-14 -4768,211,311,0,15.0,10,5.0,5,2.0,77,,,,13,1972-05-14 -4769,211,277,80,16.0,6,6.0,6,1.0,77,,,,13,1972-05-14 -4770,211,305,64,17.0,4,1.0,1,9.0,80,8815300.0,,,1,1972-05-14 -4771,211,336,64,26.0,17,8.0,8,0.0,77,,,,13,1972-05-14 -4772,211,289,33,21.0,21,9.0,9,0.0,77,,,,13,1972-05-14 -4773,211,242,36,27.0,25,10.0,10,0.0,77,,,,13,1972-05-14 -4774,211,237,36,3.0,15,11.0,11,0.0,76,,,,14,1972-05-14 -4775,211,332,61,12.0,18,7.0,7,0.0,77,,,,13,1972-05-14 -4776,212,279,36,15.0,19,,16,0.0,59,,,,62,1972-06-04 -4777,212,222,5,30.0,2,,17,0.0,57,,,,3,1972-06-04 -4778,212,332,61,36.0,10,,18,0.0,55,,,,5,1972-06-04 -4779,212,329,79,22.0,24,,19,0.0,54,,,,3,1972-06-04 -4780,212,313,61,35.0,21,,25,0.0,11,,,,25,1972-06-04 -4781,212,328,36,14.0,22,,21,0.0,31,,,,86,1972-06-04 -4782,212,289,33,18.0,18,,22,0.0,28,,,,6,1972-06-04 -4783,212,319,64,24.0,17,,23,0.0,27,,,,48,1972-06-04 -4784,212,305,64,23.0,6,,24,0.0,15,,,,25,1972-06-04 -4785,212,288,33,17.0,16,,15,0.0,73,,,,22,1972-06-04 -4786,212,234,5,29.0,4,,20,0.0,47,,,,98,1972-06-04 -4787,212,337,31,33.0,12,14.0,14,0.0,79,,,,16,1972-06-04 -4788,212,277,80,5.0,13,6.0,6,1.0,84,,,,11,1972-06-04 -4789,212,181,36,12.0,25,12.0,12,0.0,82,,,,13,1972-06-04 -4790,212,198,33,19.0,9,13.0,13,0.0,81,,,,14,1972-06-04 -4791,212,326,24,8.0,5,2.0,2,6.0,85,6273900.0,,,1,1972-06-04 -4792,212,303,0,9.0,3,3.0,3,4.0,85,6305400.0,,,1,1972-06-04 -4793,212,304,61,34.0,8,4.0,4,3.0,85,6319300.0,,,1,1972-06-04 -4794,212,249,36,16.0,11,5.0,5,2.0,84,,,,11,1972-06-04 -4795,212,223,31,32.0,1,1.0,1,9.0,85,6247300.0,,,1,1972-06-04 -4796,212,306,64,25.0,15,8.0,8,0.0,83,,,,12,1972-06-04 -4797,212,237,36,11.0,14,9.0,9,0.0,83,,,,12,1972-06-04 -4798,212,336,64,27.0,23,10.0,10,0.0,83,,,,12,1972-06-04 -4799,212,242,36,6.0,20,11.0,11,0.0,83,,,,12,1972-06-04 -4800,212,308,0,10.0,7,7.0,7,0.0,83,,,,12,1972-06-04 -4801,213,329,5,30.0,19,13.0,13,0.0,37,,,,11,1972-07-02 -4802,213,316,64,24.0,18,,21,0.0,25,,,,6,1972-07-02 -4803,213,220,24,8.0,16,,20,0.0,33,,,,62,1972-07-02 -4804,213,328,36,15.0,23,19.0,19,0.0,33,,,,60,1972-07-02 -4805,213,337,31,6.0,22,18.0,18,0.0,34,,,,86,1972-07-02 -4806,213,313,61,27.0,5,17.0,17,0.0,36,,,,12,1972-07-02 -4807,213,242,36,10.0,15,16.0,16,0.0,37,,,,11,1972-07-02 -4808,213,305,64,5.0,24,15.0,15,0.0,37,,,,11,1972-07-02 -4809,213,332,61,28.0,12,14.0,14,0.0,37,,,,11,1972-07-02 -4810,213,198,33,20.0,17,12.0,12,0.0,37,,,,11,1972-07-02 -4811,213,304,61,26.0,10,6.0,6,1.0,38,6838600.0,,,1,1972-07-02 -4812,213,288,33,18.0,20,10.0,10,0.0,38,6922000.0,,,1,1972-07-02 -4813,213,311,0,11.0,13,9.0,9,0.0,38,6918000.0,,,1,1972-07-02 -4814,213,289,33,19.0,14,8.0,8,0.0,38,6887600.0,,,1,1972-07-02 -4815,213,303,0,2.0,2,7.0,7,0.0,38,6850600.0,,,1,1972-07-02 -4816,213,237,36,12.0,9,5.0,5,2.0,38,6799300.0,,,1,1972-07-02 -4817,213,326,24,7.0,7,4.0,4,3.0,38,6791800.0,,,1,1972-07-02 -4818,213,277,80,9.0,1,3.0,3,4.0,38,6774400.0,,,1,1972-07-02 -4819,213,223,31,1.0,8,2.0,2,6.0,38,6770200.0,,,1,1972-07-02 -4820,213,327,24,4.0,3,1.0,1,9.0,38,6742500.0,,,1,1972-07-02 -4821,213,249,36,17.0,11,,22,0.0,18,,,,5,1972-07-02 -4822,213,234,5,3.0,4,11.0,11,0.0,37,,,,11,1972-07-02 -4823,213,181,36,14.0,21,,24,0.0,4,,,,86,1972-07-02 -4824,213,336,64,25.0,6,,23,0.0,8,,,,107,1972-07-02 -4825,213,292,31,29.0,0,,25,0.0,0,,,,81,1972-07-02 -4826,214,223,31,8.0,2,1.0,1,9.0,76,6470200.0,,,1,1972-07-15 -4827,214,332,61,23.0,20,,26,0.0,3,,,,3,1972-07-15 -4828,214,319,64,12.0,16,,25,0.0,5,,,,5,1972-07-15 -4829,214,279,81,24.0,26,,24,0.0,7,,,,3,1972-07-15 -4830,214,329,79,30.0,18,,23,0.0,9,,,,20,1972-07-15 -4831,214,292,31,29.0,24,,22,0.0,21,,,,6,1972-07-15 -4832,214,304,61,21.0,7,,21,0.0,31,,,,6,1972-07-15 -4833,214,261,64,14.0,14,,20,0.0,36,,,,22,1972-07-15 -4834,214,288,33,26.0,21,,18,0.0,47,,,,20,1972-07-15 -4835,214,234,5,5.0,1,,17,0.0,49,,,,51,1972-07-15 -4836,214,337,31,9.0,15,,16,0.0,59,,,,22,1972-07-15 -4837,214,326,24,2.0,12,,15,0.0,60,,,,20,1972-07-15 -4838,214,313,61,22.0,5,,14,0.0,64,,,,22,1972-07-15 -4839,214,249,36,25.0,13,,19,0.0,39,,,,24,1972-07-15 -4840,214,289,33,28.0,22,12.0,12,0.0,69,,,,22,1972-07-15 -4841,214,328,36,31.0,23,13.0,13,0.0,69,,,,17,1972-07-15 -4842,214,327,24,1.0,4,2.0,2,6.0,76,6474300.0,,,1,1972-07-15 -4843,214,308,0,19.0,3,3.0,3,4.0,76,6542700.0,,,1,1972-07-15 -4844,214,277,80,17.0,17,4.0,4,3.0,75,,,,11,1972-07-15 -4845,214,231,5,6.0,9,6.0,6,1.0,75,,,,11,1972-07-15 -4846,214,303,0,18.0,11,5.0,5,2.0,75,,,,11,1972-07-15 -4847,214,198,33,27.0,10,8.0,8,0.0,73,,,,13,1972-07-15 -4848,214,181,36,4.0,19,9.0,9,0.0,73,,,,13,1972-07-15 -4849,214,242,36,33.0,25,10.0,10,0.0,71,,,,15,1972-07-15 -4850,214,305,64,11.0,6,11.0,11,0.0,70,,,,16,1972-07-15 -4851,214,237,36,3.0,8,7.0,7,0.0,74,,,,20,1972-07-15 -4852,215,304,61,14.0,16,,20,0.0,8,,,,22,1972-07-30 -4853,215,249,36,21.0,11,,16,0.0,11,,,,62,1972-07-30 -4854,215,223,31,2.0,3,,17,0.0,10,,,,6,1972-07-30 -4855,215,279,36,20.0,9,,18,0.0,10,,,,3,1972-07-30 -4856,215,198,33,12.0,6,,21,0.0,6,,,,24,1972-07-30 -4857,215,316,64,18.0,17,,27,0.0,3,,,,5,1972-07-30 -4858,215,337,31,25.0,23,,23,0.0,6,,,,44,1972-07-30 -4859,215,181,36,23.0,24,,24,0.0,4,,,,44,1972-07-30 -4860,215,320,79,27.0,25,,25,0.0,4,,,,5,1972-07-30 -4861,215,292,31,29.0,26,,26,0.0,4,,,,68,1972-07-30 -4862,215,277,80,8.0,8,15.0,15,0.0,13,,,,11,1972-07-30 -4863,215,242,36,22.0,14,,22,0.0,6,,,,10,1972-07-30 -4864,215,313,61,15.0,12,14.0,14,0.0,13,,,,11,1972-07-30 -4865,215,303,0,3.0,10,,19,0.0,8,,,,5,1972-07-30 -4866,215,231,5,19.0,22,12.0,12,0.0,13,,,,11,1972-07-30 -4867,215,222,5,9.0,7,2.0,2,6.0,14,6180600.0,,,1,1972-07-30 -4868,215,237,36,10.0,4,3.0,3,4.0,14,6199000.0,,,1,1972-07-30 -4869,215,306,64,17.0,18,4.0,4,3.0,14,6272500.0,,,1,1972-07-30 -4870,215,311,0,5.0,19,5.0,5,2.0,14,6288000.0,,,1,1972-07-30 -4871,215,288,33,11.0,15,6.0,6,1.0,14,6311900.0,,,1,1972-07-30 -4872,215,234,5,4.0,1,1.0,1,9.0,14,6132300.0,,,1,1972-07-30 -4873,215,328,36,28.0,27,8.0,8,0.0,14,6443000.0,,,1,1972-07-30 -4874,215,289,33,26.0,21,7.0,7,0.0,14,6312400.0,,,1,1972-07-30 -4875,215,327,24,1.0,2,11.0,11,0.0,13,,,,4,1972-07-30 -4876,215,332,61,16.0,20,13.0,13,0.0,13,,,,11,1972-07-30 -4877,215,305,64,6.0,13,9.0,9,0.0,14,6452500.0,,,1,1972-07-30 -4878,215,326,24,7.0,5,10.0,10,0.0,14,6476000.0,,,1,1972-07-30 -4879,216,332,61,11.0,13,14.0,14,0.0,51,,,,13,1972-08-13 -4880,216,222,5,19.0,2,,24,0.0,13,,,,69,1972-08-13 -4881,216,198,33,17.0,5,,23,0.0,14,,,,98,1972-08-13 -4882,216,337,31,21.0,19,,25,0.0,6,,,,5,1972-08-13 -4883,216,295,82,29.0,25,,21,0.0,22,,,,22,1972-08-13 -4884,216,328,36,3.0,24,,20,0.0,24,,,,69,1972-08-13 -4885,216,289,33,28.0,15,,19,0.0,31,,,,23,1972-08-13 -4886,216,288,33,16.0,14,,18,0.0,36,,,,98,1972-08-13 -4887,216,329,79,15.0,23,,17,0.0,45,,,,44,1972-08-13 -4888,216,249,36,23.0,18,,16,0.0,46,,,,62,1972-08-13 -4889,216,242,36,27.0,17,,15,0.0,48,,,,5,1972-08-13 -4890,216,234,5,18.0,9,,22,0.0,20,,,,69,1972-08-13 -4891,216,319,64,6.0,16,13.0,13,0.0,51,,,,13,1972-08-13 -4892,216,313,61,24.0,8,11.0,11,0.0,52,,,,12,1972-08-13 -4893,216,237,36,5.0,11,12.0,12,0.0,52,,,,12,1972-08-13 -4894,216,223,31,31.0,1,1.0,1,9.0,54,5356660.0,,,1,1972-08-13 -4895,216,303,0,12.0,7,2.0,2,6.0,54,5357840.0,,,1,1972-08-13 -4896,216,304,61,25.0,12,4.0,4,3.0,54,5401420.0,,,1,1972-08-13 -4897,216,277,80,10.0,6,5.0,5,2.0,54,5402300.0,,,1,1972-08-13 -4898,216,308,0,14.0,4,3.0,3,4.0,54,5393190.0,,,1,1972-08-13 -4899,216,327,24,1.0,3,7.0,7,0.0,54,5425750.0,,,1,1972-08-13 -4900,216,305,64,7.0,21,8.0,8,0.0,54,5438110.0,,,1,1972-08-13 -4901,216,326,24,2.0,20,9.0,9,0.0,53,,,,11,1972-08-13 -4902,216,181,36,4.0,22,10.0,10,0.0,53,,,,11,1972-08-13 -4903,216,306,64,9.0,10,6.0,6,1.0,54,5417850.0,,,1,1972-08-13 -4904,217,313,61,8.0,15,,19,0.0,20,,,,20,1972-09-10 -4905,217,320,79,12.0,0,,27,0.0,0,,,,81,1972-09-10 -4906,217,289,33,29.0,19,,17,0.0,20,,,,22,1972-09-10 -4907,217,340,61,7.0,22,,18,0.0,20,,,,69,1972-09-10 -4908,217,222,5,5.0,4,,20,0.0,16,,,,4,1972-09-10 -4909,217,279,36,25.0,0,,26,0.0,0,,,,81,1972-09-10 -4910,217,198,33,30.0,11,,22,0.0,14,,,,22,1972-09-10 -4911,217,326,24,2.0,14,,23,0.0,14,,,,5,1972-09-10 -4912,217,329,79,11.0,23,,24,0.0,6,,,,5,1972-09-10 -4913,217,327,24,1.0,3,,25,0.0,0,,,,8,1972-09-10 -4914,217,332,61,9.0,21,,16,0.0,33,,,,23,1972-09-10 -4915,217,249,36,26.0,18,,21,0.0,15,,,,4,1972-09-10 -4916,217,277,80,20.0,2,,15,0.0,38,,,,23,1972-09-10 -4917,217,306,64,22.0,17,11.0,11,0.0,52,,,,13,1972-09-10 -4918,217,181,36,18.0,20,13.0,13,0.0,50,,,,15,1972-09-10 -4919,217,234,5,4.0,1,,14,0.0,46,,,,10,1972-09-10 -4920,217,304,61,10.0,9,2.0,2,6.0,55,5412900.0,,,1,1972-09-10 -4921,217,303,0,14.0,5,3.0,3,4.0,55,5422200.0,,,1,1972-09-10 -4922,217,308,0,15.0,8,4.0,4,3.0,55,5434100.0,,,1,1972-09-10 -4923,217,288,33,28.0,13,5.0,5,2.0,55,5464000.0,,,1,1972-09-10 -4924,217,223,31,6.0,4,1.0,1,9.0,55,5398400.0,,,1,1972-09-10 -4925,217,206,5,3.0,7,7.0,7,0.0,54,,,,11,1972-09-10 -4926,217,305,64,21.0,16,8.0,8,0.0,54,,,,11,1972-09-10 -4927,217,237,36,19.0,24,9.0,9,0.0,54,,,,11,1972-09-10 -4928,217,328,36,16.0,25,10.0,10,0.0,54,,,,11,1972-09-10 -4929,217,316,64,24.0,10,12.0,12,0.0,51,,,,14,1972-09-10 -4930,217,319,64,23.0,12,6.0,6,1.0,55,5480300.0,,,1,1972-09-10 -4931,218,237,36,25.0,3,,16,0.0,61,,,,4,1972-09-24 -4932,218,328,36,27.0,24,,17,0.0,59,,,,62,1972-09-24 -4933,218,326,24,2.0,6,,18,0.0,51,,,,6,1972-09-24 -4934,218,319,64,16.0,12,,19,0.0,25,,,,22,1972-09-24 -4935,218,342,64,17.0,23,,22,0.0,20,,,,20,1972-09-24 -4936,218,305,64,14.0,20,,21,0.0,21,,,,44,1972-09-24 -4937,218,289,33,9.0,11,,23,0.0,5,,,,6,1972-09-24 -4938,218,332,61,23.0,15,,24,0.0,2,,,,6,1972-09-24 -4939,218,181,36,26.0,19,,15,0.0,64,,,,2,1972-09-24 -4940,218,341,36,33.0,22,,20,0.0,24,,,,62,1972-09-24 -4941,218,316,31,6.0,16,,14,0.0,65,,,,5,1972-09-24 -4942,218,279,36,28.0,21,13.0,13,0.0,73,,,,17,1972-09-24 -4943,218,303,0,18.0,2,3.0,3,4.0,80,6251700.0,,,1,1972-09-24 -4944,218,223,31,5.0,4,11.0,11,0.0,78,,,,12,1972-09-24 -4945,218,306,64,15.0,14,10.0,10,0.0,78,,,,12,1972-09-24 -4946,218,249,36,29.0,18,9.0,9,0.0,78,,,,60,1972-09-24 -4947,218,288,33,7.0,17,8.0,8,0.0,79,,,,11,1972-09-24 -4948,218,313,61,22.0,13,7.0,7,0.0,79,,,,11,1972-09-24 -4949,218,277,80,4.0,10,6.0,6,1.0,79,,,,11,1972-09-24 -4950,218,222,5,11.0,7,5.0,5,2.0,80,6264100.0,,,1,1972-09-24 -4951,218,198,33,8.0,9,4.0,4,3.0,80,6257800.0,,,1,1972-09-24 -4952,218,308,0,19.0,1,2.0,2,6.0,80,6245300.0,,,1,1972-09-24 -4953,218,327,24,1.0,5,1.0,1,9.0,80,6197100.0,,,1,1972-09-24 -4954,218,234,5,10.0,8,12.0,12,0.0,76,,,,14,1972-09-24 -4955,219,306,64,16.0,17,,22,0.0,44,,,,5,1972-10-08 -4956,219,319,64,14.0,28,,21,0.0,47,,,,5,1972-10-08 -4957,219,308,0,20.0,2,18.0,18,0.0,54,,,,10,1972-10-08 -4958,219,181,36,5.0,25,19.0,19,0.0,49,,,,62,1972-10-08 -4959,219,337,31,11.0,30,,23,0.0,44,,,,5,1972-10-08 -4960,219,249,36,27.0,15,,20,0.0,48,,,,69,1972-10-08 -4961,219,289,33,30.0,13,,24,0.0,43,,,,5,1972-10-08 -4962,219,313,61,24.0,31,,29,0.0,22,,,,22,1972-10-08 -4963,219,305,64,17.0,18,,25,0.0,40,,,,80,1972-10-08 -4964,219,311,64,15.0,24,,26,0.0,34,,,,5,1972-10-08 -4965,219,198,33,29.0,5,,27,0.0,31,,,,5,1972-10-08 -4966,219,332,61,25.0,19,,28,0.0,25,,,,4,1972-10-08 -4967,219,223,31,10.0,9,,30,0.0,17,,,,22,1972-10-08 -4968,219,320,79,31.0,29,,31,0.0,8,,,,5,1972-10-08 -4969,219,304,61,23.0,14,17.0,17,0.0,56,,,,4,1972-10-08 -4970,219,220,24,3.0,11,7.0,7,0.0,58,,,,11,1972-10-08 -4971,219,277,80,18.0,7,15.0,15,0.0,57,,,,12,1972-10-08 -4972,219,341,36,33.0,20,16.0,16,0.0,57,,,,12,1972-10-08 -4973,219,327,24,1.0,1,1.0,1,9.0,59,6105354.0,,,1,1972-10-08 -4974,219,326,24,2.0,4,2.0,2,6.0,59,6137622.0,,,1,1972-10-08 -4975,219,237,36,4.0,26,4.0,4,3.0,59,6187870.0,,,1,1972-10-08 -4976,219,234,5,7.0,12,5.0,5,2.0,59,6188473.0,,,1,1972-10-08 -4977,219,206,5,9.0,10,6.0,6,1.0,58,,,,11,1972-10-08 -4978,219,303,0,19.0,3,3.0,3,4.0,59,6142882.0,,,1,1972-10-08 -4979,219,221,0,21.0,8,9.0,9,0.0,58,,,,11,1972-10-08 -4980,219,316,31,12.0,16,10.0,10,0.0,57,,,,12,1972-10-08 -4981,219,288,33,28.0,27,11.0,11,0.0,57,,,,12,1972-10-08 -4982,219,343,61,34.0,22,12.0,12,0.0,57,,,,12,1972-10-08 -4983,219,328,36,6.0,20,13.0,13,0.0,57,,,,12,1972-10-08 -4984,219,279,36,26.0,21,14.0,14,0.0,57,,,,12,1972-10-08 -4985,219,222,5,8.0,6,8.0,8,0.0,58,,,,11,1972-10-08 -4986,220,305,64,30.0,7,,12,0.0,79,,,,5,1973-01-28 -4987,220,329,78,36.0,16,,19,0.0,0,,,,5,1973-01-28 -4988,220,198,33,10.0,9,,16,0.0,16,,,,6,1973-01-28 -4989,220,181,64,34.0,13,,15,0.0,66,,,,51,1973-01-28 -4990,220,249,61,28.0,15,,18,0.0,10,,,,22,1973-01-28 -4991,220,237,31,4.0,5,,14,0.0,67,,,,51,1973-01-28 -4992,220,306,78,38.0,19,,13,0.0,79,,,,62,1973-01-28 -4993,220,196,36,24.0,17,,11,0.0,84,,,,21,1973-01-28 -4994,220,327,24,6.0,4,3.0,3,4.0,96,7011410.0,,,1,1973-01-28 -4995,220,231,5,20.0,14,9.0,9,0.0,92,,,,14,1973-01-28 -4996,220,308,0,16.0,11,8.0,8,0.0,92,,,,14,1973-01-28 -4997,220,222,64,32.0,1,7.0,7,0.0,93,,,,13,1973-01-28 -4998,220,289,33,12.0,13,6.0,6,1.0,95,,,,11,1973-01-28 -4999,220,303,0,14.0,8,5.0,5,2.0,95,,,,11,1973-01-28 -5000,220,234,5,18.0,3,4.0,4,3.0,96,7020790.0,,,1,1973-01-28 -5001,220,326,24,8.0,6,2.0,2,6.0,96,6982910.0,,,1,1973-01-28 -5002,220,223,31,2.0,2,1.0,1,9.0,96,6978220.0,,,1,1973-01-28 -5003,220,328,36,22.0,18,10.0,10,0.0,90,,,,22,1973-01-28 -5004,220,304,61,26.0,10,,17,0.0,10,,,,86,1973-01-28 -5005,221,303,0,7.0,5,3.0,3,4.0,40,6342000.0,,,1,1973-02-11 -5006,221,327,24,3.0,8,2.0,2,6.0,40,6249100.0,,,1,1973-02-11 -5007,221,237,31,2.0,1,,18,0.0,5,,,,36,1973-02-11 -5008,221,308,0,8.0,12,,20,0.0,3,,,,6,1973-02-11 -5009,221,289,33,18.0,11,,19,0.0,5,,,,25,1973-02-11 -5010,221,223,31,1.0,2,1.0,1,9.0,40,6235600.0,,,1,1973-02-11 -5011,221,304,61,5.0,14,,16,0.0,6,,,,6,1973-02-11 -5012,221,249,61,6.0,6,,15,0.0,9,,,,22,1973-02-11 -5013,221,328,36,12.0,19,,14,0.0,18,,,,25,1973-02-11 -5014,221,305,64,15.0,10,,13,0.0,23,,,,10,1973-02-11 -5015,221,196,36,11.0,15,,17,0.0,6,,,,6,1973-02-11 -5016,221,198,33,17.0,7,11.0,11,0.0,38,,,,12,1973-02-11 -5017,221,326,24,4.0,9,10.0,10,0.0,38,,,,12,1973-02-11 -5018,221,329,78,20.0,18,9.0,9,0.0,38,,,,12,1973-02-11 -5019,221,181,64,16.0,13,8.0,8,0.0,38,,,,12,1973-02-11 -5020,221,306,78,19.0,14,7.0,7,0.0,39,,,,11,1973-02-11 -5021,221,222,64,14.0,4,6.0,6,1.0,39,,,,11,1973-02-11 -5022,221,234,5,9.0,3,5.0,5,2.0,39,,,,11,1973-02-11 -5023,221,231,5,10.0,17,4.0,4,3.0,39,,,,11,1973-02-11 -5024,221,330,61,23.0,20,12.0,12,0.0,36,,,,14,1973-02-11 -5025,222,328,36,24.0,23,,16,0.0,65,,,,62,1973-03-03 -5026,222,289,33,19.0,17,,17,0.0,52,,,,6,1973-03-03 -5027,222,333,78,20.0,24,,18,0.0,35,,,,25,1973-03-03 -5028,222,181,64,17.0,10,,19,0.0,26,,,,5,1973-03-03 -5029,222,304,61,10.0,12,,25,0.0,2,,,,3,1973-03-03 -5030,222,292,31,25.0,13,,22,0.0,3,,,,3,1973-03-03 -5031,222,222,64,15.0,5,,23,0.0,2,,,,3,1973-03-03 -5032,222,234,5,8.0,11,,24,0.0,2,,,,3,1973-03-03 -5033,222,326,24,4.0,25,,15,0.0,66,,,,62,1973-03-03 -5034,222,305,64,16.0,7,,21,0.0,4,,,,8,1973-03-03 -5035,222,196,36,14.0,18,,14,0.0,66,,,,62,1973-03-03 -5036,222,261,56,22.0,14,,20,0.0,14,,,,5,1973-03-03 -5037,222,249,61,11.0,9,,12,0.0,69,,,,3,1973-03-03 -5038,222,223,31,1.0,2,3.0,3,4.0,79,6216130.0,,,1,1973-03-03 -5039,222,231,5,9.0,15,4.0,4,3.0,78,,,,11,1973-03-03 -5040,222,303,0,5.0,1,5.0,5,2.0,77,,,,12,1973-03-03 -5041,222,331,56,23.0,21,6.0,6,1.0,77,,,,12,1973-03-03 -5042,222,327,24,3.0,16,1.0,1,9.0,79,6191070.0,,,1,1973-03-03 -5043,222,308,0,6.0,6,2.0,2,6.0,79,6215620.0,,,1,1973-03-03 -5044,222,332,61,12.0,20,8.0,8,0.0,77,,,,12,1973-03-03 -5045,222,221,0,7.0,3,9.0,9,0.0,75,,,,5,1973-03-03 -5046,222,306,78,21.0,19,10.0,10,0.0,73,,,,16,1973-03-03 -5047,222,237,31,2.0,4,11.0,11,0.0,73,,,,16,1973-03-03 -5048,222,198,33,18.0,8,7.0,7,0.0,77,,,,12,1973-03-03 -5049,222,291,24,26.0,22,,13,0.0,67,,,,62,1973-03-03 -5050,223,198,33,18.0,15,,13,0.0,66,,,,86,1973-04-29 -5051,223,249,61,10.0,16,,22,0.0,13,,,,86,1973-04-29 -5052,223,332,33,21.0,17,,21,0.0,17,,,,36,1973-04-29 -5053,223,261,56,19.0,13,,20,0.0,23,,,,5,1973-04-29 -5054,223,304,61,9.0,9,,19,0.0,25,,,,44,1973-04-29 -5055,223,288,56,25.0,22,,18,0.0,27,,,,23,1973-04-29 -5056,223,181,64,16.0,11,,17,0.0,28,,,,27,1973-04-29 -5057,223,327,24,3.0,4,,16,0.0,47,,,,23,1973-04-29 -5058,223,237,31,2.0,1,,15,0.0,56,,,,6,1973-04-29 -5059,223,306,78,23.0,21,,14,0.0,63,,,,60,1973-04-29 -5060,223,329,78,24.0,20,11.0,11,0.0,69,,,,16,1973-04-29 -5061,223,289,33,17.0,12,10.0,10,0.0,69,,,,16,1973-04-29 -5062,223,222,64,14.0,8,9.0,9,0.0,69,,,,16,1973-04-29 -5063,223,279,36,11.0,18,8.0,8,0.0,73,,,,12,1973-04-29 -5064,223,328,36,12.0,19,7.0,7,0.0,74,,,,11,1973-04-29 -5065,223,303,0,5.0,2,6.0,6,1.0,74,,,,11,1973-04-29 -5066,223,305,64,15.0,10,5.0,5,2.0,74,,,,11,1973-04-29 -5067,223,308,0,6.0,5,4.0,4,3.0,74,,,,11,1973-04-29 -5068,223,331,56,20.0,14,3.0,3,4.0,75,6571800.0,,,1,1973-04-29 -5069,223,326,24,4.0,3,2.0,2,6.0,75,6541400.0,,,1,1973-04-29 -5070,223,223,31,1.0,7,1.0,1,9.0,75,6498700.0,,,1,1973-04-29 -5071,223,234,5,7.0,6,12.0,12,0.0,69,,,,16,1973-04-29 -5072,224,308,0,8.0,10,,16,0.0,33,,,,3,1973-05-20 -5073,224,306,78,25.0,21,,17,0.0,16,,,,3,1973-05-20 -5074,224,198,33,10.0,7,,18,0.0,14,,,,5,1973-05-20 -5075,224,331,56,16.0,11,,19,0.0,13,,,,37,1973-05-20 -5076,224,289,33,11.0,19,,14,0.0,46,,,,5,1973-05-20 -5077,224,234,5,3.0,3,,21,0.0,6,,,,94,1973-05-20 -5078,224,329,78,26.0,17,,22,0.0,6,,,,5,1973-05-20 -5079,224,304,61,23.0,13,,23,0.0,4,,,,3,1973-05-20 -5080,224,261,56,17.0,22,,20,0.0,11,,,,3,1973-05-20 -5081,224,305,64,20.0,5,,13,0.0,56,,,,62,1973-05-20 -5082,224,237,31,2.0,1,,15,0.0,42,,,,3,1973-05-20 -5083,224,328,36,15.0,20,11.0,11,0.0,63,,,,3,1973-05-20 -5084,224,222,64,19.0,12,10.0,10,0.0,63,,,,3,1973-05-20 -5085,224,196,36,14.0,16,,12,0.0,60,,,,3,1973-05-20 -5086,224,288,56,12.0,23,9.0,9,0.0,65,,,,15,1973-05-20 -5087,224,249,61,24.0,8,8.0,8,0.0,66,,,,14,1973-05-20 -5088,224,303,0,7.0,2,7.0,7,0.0,67,,,,13,1973-05-20 -5089,224,277,79,22.0,15,6.0,6,1.0,67,,,,13,1973-05-20 -5090,224,181,64,21.0,14,5.0,5,2.0,69,,,,11,1973-05-20 -5091,224,332,33,9.0,18,4.0,4,3.0,69,,,,11,1973-05-20 -5092,224,223,31,1.0,9,3.0,3,4.0,70,6256220.0,,,1,1973-05-20 -5093,224,326,24,6.0,4,2.0,2,6.0,70,6165270.0,,,1,1973-05-20 -5094,224,327,24,5.0,6,1.0,1,9.0,70,6133430.0,,,1,1973-05-20 -5095,225,234,5,3.0,7,,16,0.0,44,,,,86,1973-06-03 -5096,225,306,78,25.0,10,,17,0.0,41,,,,86,1973-06-03 -5097,225,305,64,20.0,11,,18,0.0,39,,,,3,1973-06-03 -5098,225,249,61,24.0,17,,19,0.0,31,,,,86,1973-06-03 -5099,225,328,36,15.0,20,,25,0.0,3,,,,5,1973-06-03 -5100,225,329,78,26.0,21,,21,0.0,30,,,,86,1973-06-03 -5101,225,181,64,21.0,6,,22,0.0,24,,,,6,1973-06-03 -5102,225,277,79,22.0,12,,23,0.0,22,,,,25,1973-06-03 -5103,225,222,64,19.0,8,,24,0.0,15,,,,23,1973-06-03 -5104,225,198,33,10.0,19,,15,0.0,46,,,,6,1973-06-03 -5105,225,258,36,18.0,23,,20,0.0,31,,,,95,1973-06-03 -5106,225,231,5,4.0,16,,14,0.0,58,,,,51,1973-06-03 -5107,225,288,56,12.0,24,,13,0.0,62,,,,22,1973-06-03 -5108,225,196,36,14.0,14,,12,0.0,67,,,,6,1973-06-03 -5109,225,327,24,5.0,1,1.0,1,9.0,78,7064300.0,,,1,1973-06-03 -5110,225,237,31,2.0,2,3.0,3,4.0,77,,,,11,1973-06-03 -5111,225,326,24,6.0,4,4.0,4,3.0,77,,,,11,1973-06-03 -5112,225,308,0,8.0,15,5.0,5,2.0,76,,,,12,1973-06-03 -5113,225,303,0,7.0,3,6.0,6,1.0,76,,,,12,1973-06-03 -5114,225,223,31,1.0,5,2.0,2,6.0,78,7065600.0,,,1,1973-06-03 -5115,225,304,61,23.0,13,8.0,8,0.0,75,,,,13,1973-06-03 -5116,225,230,36,27.0,18,9.0,9,0.0,73,,,,5,1973-06-03 -5117,225,261,56,17.0,22,10.0,10,0.0,72,,,,16,1973-06-03 -5118,225,289,33,11.0,9,11.0,11,0.0,71,,,,69,1973-06-03 -5119,225,332,33,9.0,25,7.0,7,0.0,75,,,,13,1973-06-03 -5120,226,181,64,21.0,15,13.0,13,0.0,75,,,,15,1973-06-17 -5121,226,289,33,11.0,12,,20,0.0,0,,,,3,1973-06-17 -5122,226,288,56,12.0,18,,19,0.0,16,,,,80,1973-06-17 -5123,226,196,36,14.0,20,,18,0.0,38,,,,37,1973-06-17 -5124,226,316,36,27.0,14,,21,0.0,0,,,,22,1973-06-17 -5125,226,304,61,23.0,10,,17,0.0,41,,,,27,1973-06-17 -5126,226,261,56,17.0,17,,16,0.0,50,,,,22,1973-06-17 -5127,226,305,64,20.0,9,,15,0.0,57,,,,5,1973-06-17 -5128,226,331,56,16.0,19,14.0,14,0.0,74,,,,16,1973-06-17 -5129,226,223,31,1.0,4,12.0,12,0.0,76,,,,6,1973-06-17 -5130,226,198,33,10.0,5,4.0,4,3.0,80,7024117.0,,,1,1973-06-17 -5131,226,249,61,24.0,16,10.0,10,0.0,77,,,,13,1973-06-17 -5132,226,222,64,19.0,12,9.0,9,0.0,77,,,,13,1973-06-17 -5133,226,328,36,15.0,21,8.0,8,0.0,78,,,,12,1973-06-17 -5134,226,308,0,8.0,7,7.0,7,0.0,79,,,,11,1973-06-17 -5135,226,234,5,3.0,8,6.0,6,1.0,79,,,,11,1973-06-17 -5136,226,327,24,5.0,3,5.0,5,2.0,80,7032047.0,,,1,1973-06-17 -5137,226,326,24,6.0,2,3.0,3,4.0,80,7020716.0,,,1,1973-06-17 -5138,226,237,31,2.0,1,2.0,2,6.0,80,7010088.0,,,1,1973-06-17 -5139,226,303,0,7.0,6,1.0,1,9.0,80,7006049.0,,,1,1973-06-17 -5140,226,306,78,25.0,11,11.0,11,0.0,77,,,,13,1973-06-17 -5141,227,306,78,25.0,24,14.0,14,0.0,51,,,,13,1973-07-01 -5142,227,312,55,29.0,25,15.0,15,0.0,51,,,,13,1973-07-01 -5143,227,289,33,11.0,19,16.0,16,0.0,50,,,,14,1973-07-01 -5144,227,221,0,8.0,2,,17,0.0,43,,,,3,1973-07-01 -5145,227,316,36,15.0,22,,21,0.0,20,,,,25,1973-07-01 -5146,227,304,61,23.0,11,,19,0.0,29,,,,44,1973-07-01 -5147,227,332,33,9.0,13,,20,0.0,28,,,,86,1973-07-01 -5148,227,249,61,24.0,18,13.0,13,0.0,51,,,,13,1973-07-01 -5149,227,331,56,16.0,20,,22,0.0,16,,,,69,1973-07-01 -5150,227,223,31,1.0,3,,18,0.0,41,,,,3,1973-07-01 -5151,227,222,64,19.0,9,12.0,12,0.0,53,,,,11,1973-07-01 -5152,227,231,5,4.0,10,7.0,7,0.0,54,6185710.0,,,1,1973-07-01 -5153,227,288,56,12.0,16,10.0,10,0.0,53,,,,11,1973-07-01 -5154,227,181,64,21.0,17,9.0,9,0.0,54,6202280.0,,,1,1973-07-01 -5155,227,303,0,7.0,6,8.0,8,0.0,54,6186050.0,,,1,1973-07-01 -5156,227,230,36,27.0,14,6.0,6,1.0,54,6179060.0,,,1,1973-07-01 -5157,227,234,5,3.0,12,5.0,5,2.0,54,6145420.0,,,1,1973-07-01 -5158,227,327,24,5.0,1,4.0,4,3.0,54,6143450.0,,,1,1973-07-01 -5159,227,198,33,10.0,8,3.0,3,4.0,54,6143000.0,,,1,1973-07-01 -5160,227,326,24,6.0,4,2.0,2,6.0,54,6137440.0,,,1,1973-07-01 -5161,227,237,31,2.0,5,1.0,1,9.0,54,6096520.0,,,1,1973-07-01 -5162,227,279,78,26.0,23,,23,0.0,16,,,,25,1973-07-01 -5163,227,305,64,20.0,15,11.0,11,0.0,53,,,,11,1973-07-01 -5164,227,196,36,14.0,7,,24,0.0,7,,,,86,1973-07-01 -5165,227,261,56,17.0,21,,25,0.0,0,,,,8,1973-07-01 -5166,228,308,0,8.0,3,1.0,1,9.0,67,5358500.0,,,1,1973-07-14 -5167,228,237,31,2.0,1,2.0,2,6.0,67,5361300.0,,,1,1973-07-14 -5168,228,303,0,7.0,2,3.0,3,4.0,67,5361500.0,,,1,1973-07-14 -5169,228,230,36,27.0,11,4.0,4,3.0,67,5361900.0,,,1,1973-07-14 -5170,228,326,24,6.0,7,5.0,5,2.0,67,5395100.0,,,1,1973-07-14 -5171,228,198,33,10.0,8,6.0,6,1.0,67,5403200.0,,,1,1973-07-14 -5172,228,222,64,19.0,10,7.0,7,0.0,67,5430200.0,,,1,1973-07-14 -5173,228,234,5,3.0,19,8.0,8,0.0,67,5435900.0,,,1,1973-07-14 -5174,228,306,78,25.0,18,9.0,9,0.0,66,,,,11,1973-07-14 -5175,228,327,24,5.0,4,10.0,10,0.0,66,,,,11,1973-07-14 -5176,228,328,36,15.0,24,11.0,11,0.0,65,,,,12,1973-07-14 -5177,228,312,55,28.0,21,13.0,13,0.0,61,,,,16,1973-07-14 -5178,228,289,33,11.0,13,,14,0.0,44,,,,44,1973-07-14 -5179,228,223,31,1.0,5,,15,0.0,36,,,,7,1973-07-14 -5180,228,186,33,29.0,23,,16,0.0,36,,,,69,1973-07-14 -5181,228,181,64,21.0,9,12.0,12,0.0,63,,,,14,1973-07-14 -5182,228,277,79,22.0,29,,18,0.0,6,,,,69,1973-07-14 -5183,228,288,56,12.0,27,,17,0.0,24,,,,83,1973-07-14 -5184,228,335,78,26.0,28,,28,0.0,0,,,,37,1973-07-14 -5185,228,261,56,17.0,26,,27,0.0,0,,,,4,1973-07-14 -5186,228,331,56,16.0,25,,26,0.0,0,,,,4,1973-07-14 -5187,228,334,36,14.0,22,,25,0.0,0,,,,4,1973-07-14 -5188,228,332,33,9.0,20,,24,0.0,0,,,,4,1973-07-14 -5189,228,258,36,18.0,16,,29,0.0,0,,,,20,1973-07-14 -5190,228,249,61,24.0,15,,22,0.0,0,,,,4,1973-07-14 -5191,228,199,61,31.0,14,,21,0.0,0,,,,4,1973-07-14 -5192,228,304,61,23.0,12,,20,0.0,0,,,,4,1973-07-14 -5193,228,221,0,30.0,6,,19,0.0,0,,,,4,1973-07-14 -5194,228,305,64,20.0,17,,23,0.0,0,,,,4,1973-07-14 -5195,229,303,0,7.0,4,,15,0.0,31,,,,5,1973-07-29 -5196,229,289,33,11.0,13,,16,0.0,27,,,,3,1973-07-29 -5197,229,277,79,22.0,19,,17,0.0,22,,,,69,1973-07-29 -5198,229,198,33,10.0,5,,18,0.0,9,,,,27,1973-07-29 -5199,229,258,36,18.0,21,,19,0.0,8,,,,54,1973-07-29 -5200,229,223,31,1.0,16,,21,0.0,2,,,,68,1973-07-29 -5201,229,328,36,15.0,23,,22,0.0,2,,,,10,1973-07-29 -5202,229,312,55,28.0,14,,24,0.0,0,,,,54,1973-07-29 -5203,229,261,56,17.0,10,,23,0.0,1,,,,3,1973-07-29 -5204,229,304,61,23.0,24,,14,0.0,52,,,,10,1973-07-29 -5205,229,334,36,14.0,18,,20,0.0,7,,,,3,1973-07-29 -5206,229,181,64,21.0,11,,13,0.0,52,,,,48,1973-07-29 -5207,229,230,36,27.0,7,3.0,3,4.0,72,6015460.0,,,1,1973-07-29 -5208,229,237,31,2.0,1,11.0,11,0.0,66,,,,5,1973-07-29 -5209,229,288,56,12.0,17,,12,0.0,56,,,,62,1973-07-29 -5210,229,327,24,5.0,2,1.0,1,9.0,72,5952450.0,,,1,1973-07-29 -5211,229,308,0,8.0,6,4.0,4,3.0,72,6021580.0,,,1,1973-07-29 -5212,229,305,64,20.0,9,5.0,5,2.0,72,6025820.0,,,1,1973-07-29 -5213,229,326,24,6.0,3,2.0,2,6.0,72,5968280.0,,,1,1973-07-29 -5214,229,249,61,24.0,8,7.0,7,0.0,69,,,,13,1973-07-29 -5215,229,222,64,19.0,12,8.0,8,0.0,68,,,,14,1973-07-29 -5216,229,306,78,25.0,15,9.0,9,0.0,68,,,,14,1973-07-29 -5217,229,331,56,16.0,22,10.0,10,0.0,67,,,,15,1973-07-29 -5218,229,297,78,26.0,20,6.0,6,1.0,70,,,,12,1973-07-29 -5219,230,288,56,12.0,20,13.0,13,0.0,14,6352000.0,,,1,1973-08-05 -5220,230,237,31,2.0,2,,22,0.0,0,,,,80,1973-08-05 -5221,230,181,64,21.0,5,,21,0.0,1,,,,3,1973-08-05 -5222,230,305,64,20.0,9,,20,0.0,4,,,,6,1973-08-05 -5223,230,331,56,16.0,21,,19,0.0,5,,,,3,1973-08-05 -5224,230,222,64,19.0,10,,18,0.0,7,,,,5,1973-08-05 -5225,230,198,33,10.0,6,,17,0.0,7,,,,5,1973-08-05 -5226,230,328,36,15.0,19,16.0,16,0.0,13,,,,11,1973-08-05 -5227,230,258,36,18.0,22,15.0,15,0.0,13,,,,11,1973-08-05 -5228,230,304,61,23.0,18,14.0,14,0.0,13,,,,11,1973-08-05 -5229,230,303,0,7.0,8,12.0,12,0.0,14,6341700.0,,,1,1973-08-05 -5230,230,326,24,6.0,3,2.0,2,6.0,14,6124600.0,,,1,1973-08-05 -5231,230,279,78,26.0,12,10.0,10,0.0,14,6265500.0,,,1,1973-08-05 -5232,230,308,0,8.0,7,9.0,9,0.0,14,6254800.0,,,1,1973-08-05 -5233,230,261,56,17.0,17,8.0,8,0.0,14,6208700.0,,,1,1973-08-05 -5234,230,199,61,31.0,15,7.0,7,0.0,14,6208200.0,,,1,1973-08-05 -5235,230,223,31,1.0,14,6.0,6,1.0,14,6207300.0,,,1,1973-08-05 -5236,230,289,33,11.0,13,5.0,5,2.0,14,6202900.0,,,1,1973-08-05 -5237,230,249,61,24.0,11,4.0,4,3.0,14,6176800.0,,,1,1973-08-05 -5238,230,234,0,30.0,4,3.0,3,4.0,14,6164200.0,,,1,1973-08-05 -5239,230,327,24,5.0,1,1.0,1,9.0,14,6123000.0,,,1,1973-08-05 -5240,230,242,33,9.0,16,11.0,11,0.0,14,6330300.0,,,1,1973-08-05 -5241,231,312,55,28.0,19,,14,0.0,34,,,,69,1973-08-19 -5242,231,289,33,11.0,16,,15,0.0,31,,,,69,1973-08-19 -5243,231,288,56,12.0,22,,16,0.0,28,,,,22,1973-08-19 -5244,231,331,56,16.0,20,,17,0.0,23,,,,24,1973-08-19 -5245,231,308,0,8.0,4,,22,0.0,0,,,,8,1973-08-19 -5246,231,261,56,17.0,18,,19,0.0,9,,,,69,1973-08-19 -5247,231,326,24,6.0,10,,20,0.0,6,,,,22,1973-08-19 -5248,231,230,36,27.0,9,,21,0.0,3,,,,98,1973-08-19 -5249,231,328,36,15.0,11,,23,0.0,0,,,,4,1973-08-19 -5250,231,242,33,9.0,17,,18,0.0,21,,,,36,1973-08-19 -5251,231,306,78,25.0,21,,12,0.0,44,,,,62,1973-08-19 -5252,231,196,36,18.0,12,,13,0.0,37,,,,5,1973-08-19 -5253,231,304,61,23.0,15,10.0,10,0.0,49,,,,15,1973-08-19 -5254,231,297,78,26.0,23,9.0,9,0.0,52,,,,12,1973-08-19 -5255,231,303,0,7.0,3,8.0,8,0.0,53,,,,11,1973-08-19 -5256,231,231,5,4.0,6,7.0,7,0.0,53,,,,11,1973-08-19 -5257,231,222,64,19.0,14,6.0,6,1.0,54,5427180.0,,,1,1973-08-19 -5258,231,305,64,20.0,13,5.0,5,2.0,54,5410080.0,,,1,1973-08-19 -5259,231,198,33,10.0,5,4.0,4,3.0,54,5376690.0,,,1,1973-08-19 -5260,231,249,61,24.0,8,3.0,3,4.0,54,5375420.0,,,1,1973-08-19 -5261,231,327,24,5.0,7,2.0,2,6.0,54,5337790.0,,,1,1973-08-19 -5262,231,237,31,2.0,2,1.0,1,9.0,54,5328780.0,,,1,1973-08-19 -5263,231,223,31,1.0,1,,11,0.0,48,,,,69,1973-08-19 -5264,232,230,36,27.0,0,,25,0.0,0,,,,3,1973-09-09 -5265,232,306,78,25.0,20,,16,0.0,44,,,,62,1973-09-09 -5266,232,328,36,15.0,12,,17,0.0,34,,,,6,1973-09-09 -5267,232,181,64,21.0,15,,18,0.0,33,,,,3,1973-09-09 -5268,232,222,64,19.0,18,,19,0.0,30,,,,80,1973-09-09 -5269,232,231,5,4.0,7,,24,0.0,2,,,,22,1973-09-09 -5270,232,297,78,26.0,23,,21,0.0,14,,,,25,1973-09-09 -5271,232,312,55,28.0,17,,22,0.0,10,,,,25,1973-09-09 -5272,232,289,33,11.0,16,,23,0.0,6,,,,23,1973-09-09 -5273,232,288,56,12.0,22,14.0,14,0.0,54,,,,11,1973-09-09 -5274,232,249,61,24.0,5,,20,0.0,17,,,,27,1973-09-09 -5275,232,305,64,20.0,13,13.0,13,0.0,54,,,,11,1973-09-09 -5276,232,303,0,7.0,3,15.0,15,0.0,53,,,,12,1973-09-09 -5277,232,261,56,17.0,19,11.0,11,0.0,54,,,,11,1973-09-09 -5278,232,237,31,2.0,1,1.0,1,9.0,55,5357000.0,,,1,1973-09-09 -5279,232,223,31,1.0,4,2.0,2,6.0,55,5357800.0,,,1,1973-09-09 -5280,232,308,0,8.0,2,3.0,3,4.0,55,5385800.0,,,1,1973-09-09 -5281,232,327,24,5.0,6,4.0,4,3.0,55,5390200.0,,,1,1973-09-09 -5282,232,326,24,6.0,11,5.0,5,2.0,55,5403200.0,,,1,1973-09-09 -5283,232,242,33,9.0,9,12.0,12,0.0,54,,,,11,1973-09-09 -5284,232,304,61,23.0,8,7.0,7,0.0,55,5445700.0,,,1,1973-09-09 -5285,232,234,5,3.0,14,8.0,8,0.0,54,,,,11,1973-09-09 -5286,232,258,36,29.0,24,9.0,9,0.0,54,,,,11,1973-09-09 -5287,232,331,56,16.0,21,10.0,10,0.0,54,,,,11,1973-09-09 -5288,232,198,33,10.0,10,6.0,6,1.0,55,5416800.0,,,1,1973-09-09 -5289,233,331,56,16.0,13,17.0,17,0.0,73,,,,17,1973-09-23 -5290,233,249,61,24.0,19,18.0,18,0.0,72,,,,18,1973-09-23 -5291,233,196,36,18.0,23,,19,0.0,71,,,,62,1973-09-23 -5292,233,312,55,28.0,26,,20,0.0,68,,,,62,1973-09-23 -5293,233,181,64,21.0,8,,21,0.0,62,,,,7,1973-09-23 -5294,233,326,24,6.0,6,,23,0.0,32,,,,3,1973-09-23 -5295,233,328,36,15.0,21,,24,0.0,20,,,,5,1973-09-23 -5296,233,237,31,2.0,1,,25,0.0,16,,,,22,1973-09-23 -5297,233,319,64,19.0,25,,26,0.0,5,,,,94,1973-09-23 -5298,233,288,56,12.0,17,16.0,16,0.0,73,,,,17,1973-09-23 -5299,233,221,0,0.0,3,,22,0.0,32,,,,3,1973-09-23 -5300,233,231,5,4.0,20,15.0,15,0.0,75,,,,15,1973-09-23 -5301,233,313,78,26.0,24,14.0,14,0.0,75,,,,15,1973-09-23 -5302,233,308,0,8.0,2,1.0,1,9.0,80,7144083.0,,,1,1973-09-23 -5303,233,303,0,7.0,7,13.0,13,0.0,75,,,,15,1973-09-23 -5304,233,223,31,1.0,5,2.0,2,6.0,80,7176817.0,,,1,1973-09-23 -5305,233,261,56,17.0,14,3.0,3,4.0,80,7178588.0,,,1,1973-09-23 -5306,233,305,64,20.0,16,4.0,4,3.0,80,7180597.0,,,1,1973-09-23 -5307,233,306,78,25.0,22,6.0,6,1.0,79,,,,11,1973-09-23 -5308,233,327,24,5.0,9,5.0,5,2.0,79,,,,11,1973-09-23 -5309,233,198,33,10.0,4,8.0,8,0.0,78,,,,12,1973-09-23 -5310,233,304,61,23.0,12,9.0,9,0.0,78,,,,12,1973-09-23 -5311,233,277,24,29.0,11,10.0,10,0.0,77,,,,13,1973-09-23 -5312,233,289,33,11.0,10,11.0,11,0.0,77,,,,13,1973-09-23 -5313,233,242,33,9.0,18,12.0,12,0.0,76,,,,14,1973-09-23 -5314,233,230,36,27.0,15,7.0,7,0.0,78,,,,12,1973-09-23 -5315,234,326,24,6.0,0,,28,0.0,0,,,,3,1973-10-07 -5316,234,289,33,11.0,25,,17,0.0,52,,,,62,1973-10-07 -5317,234,221,0,0.0,10,,18,0.0,39,,,,22,1973-10-07 -5318,234,199,61,30.0,16,,19,0.0,35,,,,5,1973-10-07 -5319,234,304,61,23.0,6,,21,0.0,34,,,,22,1973-10-07 -5320,234,231,5,4.0,11,16.0,16,0.0,55,,,,14,1973-10-07 -5321,234,186,33,9.0,24,,23,0.0,7,,,,5,1973-10-07 -5322,234,311,56,31.0,13,,24,0.0,5,,,,2,1973-10-07 -5323,234,312,55,28.0,27,,25,0.0,0,,,,37,1973-10-07 -5324,234,327,24,5.0,5,,26,0.0,0,,,,54,1973-10-07 -5325,234,277,24,29.0,12,,27,0.0,0,,,,54,1973-10-07 -5326,234,249,61,24.0,9,,22,0.0,32,,,,22,1973-10-07 -5327,234,261,56,17.0,22,15.0,15,0.0,55,,,,14,1973-10-07 -5328,234,181,64,21.0,21,,20,0.0,35,,,,48,1973-10-07 -5329,234,288,56,12.0,18,13.0,13,0.0,57,,,,12,1973-10-07 -5330,234,331,56,16.0,20,14.0,14,0.0,57,,,,12,1973-10-07 -5331,234,230,36,27.0,4,2.0,2,6.0,59,6076447.0,,,1,1973-10-07 -5332,234,198,33,10.0,2,3.0,3,4.0,59,6098709.0,,,1,1973-10-07 -5333,234,303,0,7.0,8,4.0,4,3.0,59,6126005.0,,,1,1973-10-07 -5334,234,308,0,8.0,7,5.0,5,2.0,59,6156146.0,,,1,1973-10-07 -5335,234,223,31,1.0,3,6.0,6,1.0,59,6183724.0,,,1,1973-10-07 -5336,234,237,31,2.0,1,1.0,1,9.0,59,6075779.0,,,1,1973-10-07 -5337,234,222,64,19.0,15,8.0,8,0.0,58,,,,11,1973-10-07 -5338,234,305,64,20.0,14,9.0,9,0.0,58,,,,11,1973-10-07 -5339,234,328,36,15.0,26,10.0,10,0.0,58,,,,11,1973-10-07 -5340,234,196,36,18.0,17,11.0,11,0.0,57,,,,3,1973-10-07 -5341,234,306,78,25.0,19,12.0,12,0.0,57,,,,12,1973-10-07 -5342,234,234,78,26.0,23,7.0,7,0.0,58,,,,11,1973-10-07 -5343,235,307,33,8.0,22,,16,0.0,36,,,,6,1974-01-13 -5344,235,232,36,9.0,23,,17,0.0,31,,,,8,1974-01-13 -5345,235,295,64,37.0,24,,18,0.0,31,,,,47,1974-01-13 -5346,235,249,61,18.0,11,,20,0.0,21,,,,22,1974-01-13 -5347,235,230,36,24.0,5,,22,0.0,11,,,,25,1974-01-13 -5348,235,199,61,19.0,18,,23,0.0,10,,,,5,1974-01-13 -5349,235,308,56,16.0,4,,24,0.0,1,,,,3,1974-01-13 -5350,235,196,56,17.0,16,,25,0.0,0,,,,3,1974-01-13 -5351,235,234,31,2.0,7,,15,0.0,36,,,,8,1974-01-13 -5352,235,231,78,20.0,13,,21,0.0,19,,,,25,1974-01-13 -5353,235,288,25,26.0,17,,14,0.0,45,,,,5,1974-01-13 -5354,235,221,24,3.0,12,,19,0.0,25,,,,5,1974-01-13 -5355,235,186,33,28.0,20,12.0,12,0.0,49,,,,14,1974-01-13 -5356,235,237,31,1.0,1,13.0,13,0.0,48,,,,15,1974-01-13 -5357,235,181,5,12.0,8,2.0,2,6.0,53,6071280.0,,,1,1974-01-13 -5358,235,222,5,11.0,2,3.0,3,4.0,53,6082420.0,,,1,1974-01-13 -5359,235,304,0,33.0,9,4.0,4,3.0,53,6093800.0,,,1,1974-01-13 -5360,235,305,64,14.0,14,5.0,5,2.0,53,6113850.0,,,1,1974-01-13 -5361,235,303,0,6.0,10,1.0,1,9.0,53,6062010.0,,,1,1974-01-13 -5362,235,198,33,7.0,6,7.0,7,0.0,52,,,,60,1974-01-13 -5363,235,306,36,10.0,19,8.0,8,0.0,52,,,,60,1974-01-13 -5364,235,279,64,15.0,21,9.0,9,0.0,52,,,,11,1974-01-13 -5365,235,223,0,5.0,3,10.0,10,0.0,52,,,,11,1974-01-13 -5366,235,264,25,27.0,25,11.0,11,0.0,51,,,,12,1974-01-13 -5367,235,220,24,4.0,15,6.0,6,1.0,53,6174490.0,,,1,1974-01-13 -5368,236,307,33,8.0,24,15.0,15,0.0,30,,,,12,1974-01-27 -5369,236,295,64,37.0,23,16.0,16,0.0,30,,,,12,1974-01-27 -5370,236,199,61,19.0,10,17.0,17,0.0,30,,,,12,1974-01-27 -5371,236,186,33,28.0,15,,18,0.0,27,,,,8,1974-01-27 -5372,236,196,56,17.0,19,,20,0.0,21,,,,23,1974-01-27 -5373,236,231,78,20.0,9,,21,0.0,20,,,,37,1974-01-27 -5374,236,308,56,16.0,6,,22,0.0,10,,,,25,1974-01-27 -5375,236,306,36,10.0,20,,23,0.0,8,,,,80,1974-01-27 -5376,236,279,64,15.0,22,14.0,14,0.0,30,,,,12,1974-01-27 -5377,236,232,36,9.0,13,,19,0.0,24,,,,7,1974-01-27 -5378,236,221,24,3.0,14,13.0,13,0.0,31,,,,11,1974-01-27 -5379,236,198,33,7.0,2,7.0,7,0.0,31,,,,11,1974-01-27 -5380,236,288,25,26.0,21,11.0,11,0.0,31,,,,11,1974-01-27 -5381,236,305,64,14.0,17,10.0,10,0.0,31,,,,11,1974-01-27 -5382,236,230,36,24.0,18,9.0,9,0.0,31,,,,11,1974-01-27 -5383,236,220,24,4.0,16,8.0,8,0.0,31,,,,11,1974-01-27 -5384,236,237,31,1.0,4,6.0,6,1.0,31,,,,11,1974-01-27 -5385,236,304,0,33.0,7,5.0,5,2.0,31,,,,11,1974-01-27 -5386,236,249,61,18.0,12,4.0,4,3.0,31,,,,11,1974-01-27 -5387,236,181,5,12.0,25,,24,0.0,2,,,,5,1974-01-27 -5388,236,222,5,11.0,8,2.0,2,6.0,32,5090630.0,,,1,1974-01-27 -5389,236,223,0,5.0,1,1.0,1,9.0,32,5077060.0,,,1,1974-01-27 -5390,236,303,0,6.0,11,12.0,12,0.0,31,,,,11,1974-01-27 -5391,236,264,25,27.0,3,,25,0.0,2,,,,83,1974-01-27 -5392,236,234,31,2.0,5,3.0,3,4.0,31,,,,11,1974-01-27 -5393,237,291,24,32.0,24,14.0,14,0.0,76,,,,12,1974-03-30 -5394,237,295,64,37.0,25,15.0,15,0.0,75,,,,13,1974-03-30 -5395,237,310,78,21.0,27,,27,0.0,0,,,,8,1974-03-30 -5396,237,237,31,1.0,16,,26,0.0,2,,,,4,1974-03-30 -5397,237,309,31,30.0,26,,25,0.0,6,,,,8,1974-03-30 -5398,237,199,61,19.0,17,,24,0.0,11,,,,22,1974-03-30 -5399,237,230,62,24.0,14,,23,0.0,13,,,,7,1974-03-30 -5400,237,234,31,2.0,10,,22,0.0,31,,,,23,1974-03-30 -5401,237,222,5,11.0,6,,20,0.0,65,,,,51,1974-03-30 -5402,237,292,0,23.0,20,19.0,19,0.0,71,,,,17,1974-03-30 -5403,237,279,64,15.0,21,18.0,18,0.0,72,,,,16,1974-03-30 -5404,237,307,33,8.0,23,17.0,17,0.0,74,,,,14,1974-03-30 -5405,237,181,5,12.0,1,16.0,16,0.0,74,,,,80,1974-03-30 -5406,237,186,33,28.0,13,,21,0.0,54,,,,69,1974-03-30 -5407,237,305,64,14.0,11,2.0,2,6.0,78,6194900.0,,,1,1974-03-30 -5408,237,198,33,7.0,4,1.0,1,9.0,78,6160960.0,,,1,1974-03-30 -5409,237,288,25,26.0,18,12.0,12,0.0,77,,,,11,1974-03-30 -5410,237,249,61,18.0,2,11.0,11,0.0,77,,,,11,1974-03-30 -5411,237,229,36,10.0,19,10.0,10,0.0,77,,,,11,1974-03-30 -5412,237,303,0,6.0,9,9.0,9,0.0,77,,,,11,1974-03-30 -5413,237,221,24,3.0,8,8.0,8,0.0,78,6231500.0,,,1,1974-03-30 -5414,237,250,31,29.0,22,13.0,13,0.0,76,,,,12,1974-03-30 -5415,237,231,78,20.0,3,6.0,6,1.0,78,6217000.0,,,1,1974-03-30 -5416,237,232,36,9.0,7,5.0,5,2.0,78,6207190.0,,,1,1974-03-30 -5417,237,220,24,4.0,15,4.0,4,3.0,78,6205150.0,,,1,1974-03-30 -5418,237,304,0,33.0,12,3.0,3,4.0,78,6203120.0,,,1,1974-03-30 -5419,237,223,0,5.0,5,7.0,7,0.0,78,6229350.0,,,1,1974-03-30 -5420,238,288,25,26.0,19,,16,0.0,43,,,,5,1974-04-28 -5421,238,231,78,20.0,7,,17,0.0,37,,,,3,1974-04-28 -5422,238,199,61,19.0,18,,18,0.0,35,,,,6,1974-04-28 -5423,238,295,64,37.0,22,,19,0.0,27,,,,5,1974-04-28 -5424,238,234,31,2.0,5,,20,0.0,26,,,,23,1974-04-28 -5425,238,237,31,1.0,2,,21,0.0,23,,,,5,1974-04-28 -5426,238,198,33,7.0,6,,24,0.0,12,,,,20,1974-04-28 -5427,238,312,33,8.0,24,,23,0.0,14,,,,44,1974-04-28 -5428,238,305,64,14.0,11,,25,0.0,2,,,,5,1974-04-28 -5429,238,264,25,27.0,0,,26,0.0,0,,,,81,1974-04-28 -5430,238,310,78,21.0,0,,27,0.0,0,,,,81,1974-04-28 -5431,238,277,76,30.0,23,,22,0.0,22,,,,23,1974-04-28 -5432,238,196,56,17.0,12,,15,0.0,73,,,,62,1974-04-28 -5433,238,304,0,33.0,17,9.0,9,0.0,81,,,,13,1974-04-28 -5434,238,249,61,18.0,14,13.0,13,0.0,78,,,,16,1974-04-28 -5435,238,313,75,23.0,25,14.0,14,0.0,76,,,,20,1974-04-28 -5436,238,181,5,12.0,1,1.0,1,9.0,84,7229560.0,,,1,1974-04-28 -5437,238,222,5,11.0,3,2.0,2,6.0,84,7265170.0,,,1,1974-04-28 -5438,238,223,0,5.0,4,3.0,3,4.0,83,,,,11,1974-04-28 -5439,238,221,24,3.0,9,5.0,5,2.0,82,,,,12,1974-04-28 -5440,238,303,0,6.0,8,6.0,6,1.0,82,,,,12,1974-04-28 -5441,238,232,36,9.0,13,4.0,4,3.0,82,,,,12,1974-04-28 -5442,238,220,24,4.0,16,8.0,8,0.0,81,,,,13,1974-04-28 -5443,238,230,62,24.0,10,10.0,10,0.0,81,,,,13,1974-04-28 -5444,238,186,33,28.0,15,11.0,11,0.0,80,,,,14,1974-04-28 -5445,238,279,64,15.0,20,12.0,12,0.0,80,,,,14,1974-04-28 -5446,238,311,56,16.0,21,7.0,7,0.0,81,,,,13,1974-04-28 -5447,239,220,24,4.0,28,,23,0.0,53,,,,23,1974-05-12 -5448,239,234,31,2.0,16,,19,0.0,72,,,,25,1974-05-12 -5449,239,251,77,42.0,20,,20,0.0,66,,,,4,1974-05-12 -5450,239,198,33,7.0,24,,21,0.0,62,,,,5,1974-05-12 -5451,239,237,31,1.0,5,,22,0.0,56,,,,95,1974-05-12 -5452,239,314,33,43.0,11,,25,0.0,53,,,,27,1974-05-12 -5453,239,315,61,44.0,0,,32,0.0,0,,,,81,1974-05-12 -5454,239,312,33,8.0,22,,27,0.0,49,,,,5,1974-05-12 -5455,239,230,62,24.0,9,,28,0.0,45,,,,3,1974-05-12 -5456,239,231,78,20.0,6,,29,0.0,29,,,,7,1974-05-12 -5457,239,279,64,15.0,15,,30,0.0,12,,,,4,1974-05-12 -5458,239,232,36,9.0,10,,31,0.0,6,,,,8,1974-05-12 -5459,239,311,56,16.0,18,18.0,18,0.0,80,,,,5,1974-05-12 -5460,239,249,61,18.0,8,,26,0.0,50,,,,64,1974-05-12 -5461,239,268,33,34.0,27,17.0,17,0.0,81,,,,14,1974-05-12 -5462,239,199,61,19.0,26,,24,0.0,53,,,,22,1974-05-12 -5463,239,266,55,22.0,14,15.0,15,0.0,82,,,,13,1974-05-12 -5464,239,295,64,37.0,25,16.0,16,0.0,82,,,,13,1974-05-12 -5465,239,221,24,3.0,2,3.0,3,4.0,85,6306180.0,,,1,1974-05-12 -5466,239,222,5,11.0,1,4.0,4,3.0,85,6312590.0,,,1,1974-05-12 -5467,239,305,64,14.0,7,5.0,5,2.0,85,6328620.0,,,1,1974-05-12 -5468,239,303,0,6.0,12,6.0,6,1.0,85,6331110.0,,,1,1974-05-12 -5469,239,304,0,33.0,13,7.0,7,0.0,84,,,,11,1974-05-12 -5470,239,288,25,26.0,29,8.0,8,0.0,83,,,,12,1974-05-12 -5471,239,181,5,12.0,3,2.0,2,6.0,85,6260920.0,,,1,1974-05-12 -5472,239,223,0,5.0,4,1.0,1,9.0,85,6260570.0,,,1,1974-05-12 -5473,239,313,75,41.0,23,10.0,10,0.0,83,,,,12,1974-05-12 -5474,239,186,33,28.0,19,11.0,11,0.0,83,,,,12,1974-05-12 -5475,239,264,25,27.0,21,12.0,12,0.0,82,,,,13,1974-05-12 -5476,239,196,56,17.0,17,13.0,13,0.0,82,,,,13,1974-05-12 -5477,239,297,78,21.0,30,14.0,14,0.0,82,,,,13,1974-05-12 -5478,239,229,36,10.0,31,9.0,9,0.0,83,,,,12,1974-05-12 -5479,240,266,55,22.0,25,,17,0.0,4,,,,3,1974-05-26 -5480,240,232,36,9.0,9,,18,0.0,3,,,,4,1974-05-26 -5481,240,305,64,14.0,11,,19,0.0,0,,,,4,1974-05-26 -5482,240,303,0,6.0,12,,20,0.0,0,,,,4,1974-05-26 -5483,240,231,78,20.0,14,,21,0.0,0,,,,4,1974-05-26 -5484,240,313,75,23.0,24,,25,0.0,0,,,,4,1974-05-26 -5485,240,311,56,16.0,16,,23,0.0,0,,,,4,1974-05-26 -5486,240,249,61,18.0,18,,24,0.0,0,,,,4,1974-05-26 -5487,240,199,61,19.0,17,,26,0.0,0,,,,54,1974-05-26 -5488,240,312,33,8.0,0,,28,0.0,0,,,,81,1974-05-26 -5489,240,295,64,37.0,22,,16,0.0,4,,,,3,1974-05-26 -5490,240,229,36,10.0,15,,22,0.0,0,,,,4,1974-05-26 -5491,240,198,33,7.0,8,,15,0.0,5,,,,22,1974-05-26 -5492,240,277,76,30.0,20,,27,0.0,0,,,,54,1974-05-26 -5493,240,230,62,24.0,7,,13,0.0,27,,,,86,1974-05-26 -5494,240,237,31,1.0,3,1.0,1,9.0,78,7083700.0,,,1,1974-05-26 -5495,240,221,24,3.0,5,2.0,2,6.0,78,7112500.0,,,1,1974-05-26 -5496,240,196,56,17.0,6,3.0,3,4.0,78,7132600.0,,,1,1974-05-26 -5497,240,222,5,11.0,2,4.0,4,3.0,78,7146800.0,,,1,1974-05-26 -5498,240,223,0,5.0,13,5.0,5,2.0,77,,,,11,1974-05-26 -5499,240,186,33,28.0,23,6.0,6,1.0,77,,,,11,1974-05-26 -5500,240,304,0,33.0,10,,14,0.0,11,,,,3,1974-05-26 -5501,240,264,25,27.0,26,8.0,8,0.0,75,,,,13,1974-05-26 -5502,240,220,24,4.0,4,9.0,9,0.0,74,,,,14,1974-05-26 -5503,240,279,64,15.0,27,,10,0.0,62,,,,6,1974-05-26 -5504,240,234,31,2.0,19,,11,0.0,34,,,,5,1974-05-26 -5505,240,181,5,12.0,1,,12,0.0,32,,,,80,1974-05-26 -5506,240,288,25,26.0,21,7.0,7,0.0,76,,,,12,1974-05-26 -5507,241,199,61,19.0,22,,16,0.0,53,,,,22,1974-06-09 -5508,241,198,33,7.0,10,,17,0.0,30,,,,44,1974-06-09 -5509,241,234,31,2.0,7,,18,0.0,27,,,,5,1974-06-09 -5510,241,222,5,11.0,4,,19,0.0,24,,,,6,1974-06-09 -5511,241,249,61,18.0,24,,20,0.0,15,,,,64,1974-06-09 -5512,241,304,0,33.0,11,,23,0.0,5,,,,95,1974-06-09 -5513,241,315,61,23.0,25,,22,0.0,8,,,,5,1974-06-09 -5514,241,305,64,14.0,13,,24,0.0,3,,,,5,1974-06-09 -5515,241,317,56,16.0,23,,25,0.0,2,,,,6,1974-06-09 -5516,241,279,64,15.0,19,,26,0.0,0,,,,42,1974-06-09 -5517,241,303,0,6.0,12,,15,0.0,56,,,,22,1974-06-09 -5518,241,237,31,1.0,5,,21,0.0,8,,,,86,1974-06-09 -5519,241,307,78,20.0,0,,27,0.0,0,,,,81,1974-06-09 -5520,241,316,36,9.0,16,,14,0.0,59,,,,22,1974-06-09 -5521,241,266,55,22.0,26,,12,0.0,77,,,,2,1974-06-09 -5522,241,181,5,12.0,3,,13,0.0,70,,,,6,1974-06-09 -5523,241,221,24,3.0,2,1.0,1,9.0,80,7111391.0,,,1,1974-06-09 -5524,241,220,24,4.0,1,2.0,2,6.0,80,7111771.0,,,1,1974-06-09 -5525,241,230,62,24.0,6,3.0,3,4.0,80,7114716.0,,,1,1974-06-09 -5526,241,196,56,17.0,8,5.0,5,2.0,80,7187794.0,,,1,1974-06-09 -5527,241,223,0,5.0,9,4.0,4,3.0,80,7164898.0,,,1,1974-06-09 -5528,241,264,25,27.0,18,7.0,7,0.0,79,,,,11,1974-06-09 -5529,241,310,78,21.0,21,8.0,8,0.0,79,,,,11,1974-06-09 -5530,241,312,33,8.0,20,9.0,9,0.0,79,,,,11,1974-06-09 -5531,241,229,36,10.0,17,10.0,10,0.0,78,,,,5,1974-06-09 -5532,241,186,33,28.0,14,11.0,11,0.0,77,,,,13,1974-06-09 -5533,241,288,25,26.0,15,6.0,6,1.0,79,,,,11,1974-06-09 -5534,242,279,64,15.0,24,,21,0.0,15,,,,64,1974-06-23 -5535,242,196,56,17.0,7,,18,0.0,28,,,,8,1974-06-23 -5536,242,305,64,14.0,16,,19,0.0,18,,,,6,1974-06-23 -5537,242,288,25,26.0,19,,20,0.0,16,,,,6,1974-06-23 -5538,242,199,61,19.0,20,,22,0.0,8,,,,7,1974-06-23 -5539,242,264,25,27.0,14,,17,0.0,36,,,,69,1974-06-23 -5540,242,251,56,16.0,11,,24,0.0,0,,,,4,1974-06-23 -5541,242,232,36,9.0,22,,25,0.0,0,,,,3,1974-06-23 -5542,242,313,75,23.0,0,,26,0.0,0,,,,81,1974-06-23 -5543,242,297,78,21.0,0,,27,0.0,0,,,,81,1974-06-23 -5544,242,230,62,24.0,6,,23,0.0,2,,,,4,1974-06-23 -5545,242,295,64,37.0,25,,15,0.0,60,,,,6,1974-06-23 -5546,242,231,78,20.0,21,,16,0.0,54,,,,6,1974-06-23 -5547,242,266,55,22.0,17,,13,0.0,69,,,,2,1974-06-23 -5548,242,181,5,12.0,1,1.0,1,9.0,75,6180350.0,,,1,1974-06-23 -5549,242,222,5,11.0,2,2.0,2,6.0,75,6188600.0,,,1,1974-06-23 -5550,242,223,0,5.0,3,3.0,3,4.0,75,6210620.0,,,1,1974-06-23 -5551,242,304,0,33.0,4,4.0,4,3.0,75,6211640.0,,,1,1974-06-23 -5552,242,221,24,3.0,5,5.0,5,2.0,75,6214630.0,,,1,1974-06-23 -5553,242,220,24,4.0,8,6.0,6,1.0,75,6231870.0,,,1,1974-06-23 -5554,242,303,0,6.0,9,,14,0.0,65,,,,80,1974-06-23 -5555,242,237,31,1.0,10,8.0,8,0.0,73,,,,12,1974-06-23 -5556,242,312,33,8.0,23,9.0,9,0.0,73,,,,12,1974-06-23 -5557,242,229,36,10.0,15,10.0,10,0.0,72,,,,13,1974-06-23 -5558,242,234,31,2.0,18,11.0,11,0.0,71,,,,14,1974-06-23 -5559,242,198,33,7.0,12,12.0,12,0.0,71,,,,14,1974-06-23 -5560,242,186,33,28.0,13,7.0,7,0.0,75,6254300.0,,,1,1974-06-23 -5561,243,251,56,16.0,3,,20,0.0,1,,,,4,1974-07-07 -5562,243,279,64,15.0,19,,21,0.0,1,,,,8,1974-07-07 -5563,243,230,62,24.0,10,,22,0.0,0,,,,4,1974-07-07 -5564,243,266,55,22.0,0,,23,0.0,0,,,,81,1974-07-07 -5565,243,312,33,8.0,0,,24,0.0,0,,,,81,1974-07-07 -5566,243,232,36,9.0,0,,27,0.0,0,,,,81,1974-07-07 -5567,243,218,78,21.0,0,,26,0.0,0,,,,81,1974-07-07 -5568,243,318,61,18.0,0,,28,0.0,0,,,,81,1974-07-07 -5569,243,315,61,23.0,0,,29,0.0,0,,,,81,1974-07-07 -5570,243,314,33,43.0,0,,30,0.0,0,,,,81,1974-07-07 -5571,243,199,61,19.0,18,,19,0.0,4,,,,8,1974-07-07 -5572,243,249,33,34.0,0,,25,0.0,0,,,,81,1974-07-07 -5573,243,223,0,5.0,5,,17,0.0,27,,,,5,1974-07-07 -5574,243,198,33,7.0,8,,18,0.0,24,,,,64,1974-07-07 -5575,243,264,25,27.0,20,15.0,15,0.0,77,,,,13,1974-07-07 -5576,243,186,33,28.0,14,16.0,16,0.0,76,,,,14,1974-07-07 -5577,243,181,5,12.0,1,2.0,2,6.0,80,4935380.0,,,1,1974-07-07 -5578,243,222,5,11.0,4,3.0,3,4.0,80,4942860.0,,,1,1974-07-07 -5579,243,221,24,3.0,7,4.0,4,3.0,80,4943130.0,,,1,1974-07-07 -5580,243,234,31,2.0,13,5.0,5,2.0,80,4952560.0,,,1,1974-07-07 -5581,243,303,0,6.0,11,6.0,6,1.0,80,4953160.0,,,1,1974-07-07 -5582,243,304,0,33.0,6,7.0,7,0.0,79,,,,11,1974-07-07 -5583,243,237,31,1.0,2,1.0,1,9.0,80,4915020.0,,,1,1974-07-07 -5584,243,231,78,20.0,15,9.0,9,0.0,79,,,,11,1974-07-07 -5585,243,305,64,14.0,17,10.0,10,0.0,79,,,,11,1974-07-07 -5586,243,229,36,10.0,16,11.0,11,0.0,79,,,,11,1974-07-07 -5587,243,196,56,17.0,12,12.0,12,0.0,79,,,,11,1974-07-07 -5588,243,288,25,26.0,21,13.0,13,0.0,78,,,,12,1974-07-07 -5589,243,295,64,37.0,22,14.0,14,0.0,78,,,,12,1974-07-07 -5590,243,220,24,4.0,9,8.0,8,0.0,79,,,,11,1974-07-07 -5591,244,231,78,20.0,15,,21,0.0,25,,,,5,1974-07-20 -5592,244,229,36,10.0,16,,22,0.0,17,,,,69,1974-07-20 -5593,244,313,75,23.0,25,,23,0.0,6,,,,22,1974-07-20 -5594,244,230,62,24.0,6,,24,0.0,2,,,,22,1974-07-20 -5595,244,319,25,27.0,21,,25,0.0,0,,,,68,1974-07-20 -5596,244,258,77,42.0,0,,26,0.0,0,,,,81,1974-07-20 -5597,244,266,55,22.0,0,,30,0.0,0,,,,81,1974-07-20 -5598,244,310,78,21.0,0,,28,0.0,0,,,,81,1974-07-20 -5599,244,274,33,208.0,0,,29,0.0,0,,,,81,1974-07-20 -5600,244,299,74,29.0,0,,31,0.0,0,,,,81,1974-07-20 -5601,244,306,72,25.0,0,,32,0.0,0,,,,81,1974-07-20 -5602,244,282,36,35.0,0,,33,0.0,0,,,,81,1974-07-20 -5603,244,220,24,4.0,10,,20,0.0,35,,,,5,1974-07-20 -5604,244,320,61,18.0,0,,27,0.0,0,,,,81,1974-07-20 -5605,244,232,36,9.0,9,,19,0.0,36,,,,3,1974-07-20 -5606,244,315,61,43.0,0,,34,0.0,0,,,,81,1974-07-20 -5607,244,304,0,33.0,11,,17,0.0,57,,,,20,1974-07-20 -5608,244,196,56,17.0,16,,18,0.0,45,,,,22,1974-07-20 -5609,244,221,24,3.0,3,1.0,1,9.0,75,6182200.0,,,1,1974-07-20 -5610,244,234,31,2.0,12,3.0,3,4.0,75,6243700.0,,,1,1974-07-20 -5611,244,222,5,11.0,7,4.0,4,3.0,75,6249400.0,,,1,1974-07-20 -5612,244,181,5,12.0,1,5.0,5,2.0,74,,,,11,1974-07-20 -5613,244,198,33,7.0,4,6.0,6,1.0,74,,,,11,1974-07-20 -5614,244,303,0,6.0,19,7.0,7,0.0,74,,,,11,1974-07-20 -5615,244,251,56,16.0,5,8.0,8,0.0,74,,,,11,1974-07-20 -5616,244,223,0,5.0,8,2.0,2,6.0,75,6197500.0,,,1,1974-07-20 -5617,244,237,31,1.0,2,10.0,10,0.0,73,,,,12,1974-07-20 -5618,244,186,33,28.0,13,11.0,11,0.0,73,,,,12,1974-07-20 -5619,244,305,64,14.0,23,12.0,12,0.0,72,,,,13,1974-07-20 -5620,244,288,25,26.0,22,13.0,13,0.0,69,,,,16,1974-07-20 -5621,244,199,61,19.0,17,14.0,14,0.0,68,,,,17,1974-07-20 -5622,244,279,64,15.0,24,,15,0.0,64,,,,5,1974-07-20 -5623,244,295,64,37.0,14,,16,0.0,62,,,,62,1974-07-20 -5624,244,249,33,8.0,20,9.0,9,0.0,74,,,,11,1974-07-20 -5625,245,305,64,14.0,15,,20,0.0,4,,,,69,1974-08-04 -5626,245,266,55,22.0,22,,21,0.0,4,,,,6,1974-08-04 -5627,245,223,0,5.0,3,,22,0.0,2,,,,22,1974-08-04 -5628,245,171,78,21.0,21,,23,0.0,2,,,,22,1974-08-04 -5629,245,186,33,28.0,14,,24,0.0,1,,,,22,1974-08-04 -5630,245,181,5,12.0,1,,25,0.0,0,,,,3,1974-08-04 -5631,245,264,25,27.0,0,,29,0.0,0,,,,81,1974-08-04 -5632,245,295,64,37.0,0,,27,0.0,0,,,,81,1974-08-04 -5633,245,313,75,23.0,0,,28,0.0,0,,,,81,1974-08-04 -5634,245,255,76,30.0,0,,30,0.0,0,,,,81,1974-08-04 -5635,245,277,76,30.0,0,,31,0.0,0,,,,81,1974-08-04 -5636,245,231,78,20.0,16,,19,0.0,5,,,,37,1974-08-04 -5637,245,303,0,6.0,7,,26,0.0,0,,,,3,1974-08-04 -5638,245,220,24,4.0,5,,18,0.0,5,,,,3,1974-08-04 -5639,245,306,72,25.0,0,,32,0.0,0,,,,81,1974-08-04 -5640,245,199,61,19.0,13,,16,0.0,10,,,,5,1974-08-04 -5641,245,222,5,11.0,2,1.0,1,9.0,14,6095000.0,,,1,1974-08-04 -5642,245,198,33,7.0,6,3.0,3,4.0,14,6178300.0,,,1,1974-08-04 -5643,245,237,31,1.0,8,4.0,4,3.0,14,6179200.0,,,1,1974-08-04 -5644,245,234,31,2.0,9,5.0,5,2.0,14,6180000.0,,,1,1974-08-04 -5645,245,251,56,16.0,11,6.0,6,1.0,14,6233100.0,,,1,1974-08-04 -5646,245,232,36,9.0,20,7.0,7,0.0,14,6273700.0,,,1,1974-08-04 -5647,245,196,56,17.0,18,8.0,8,0.0,14,6300900.0,,,1,1974-08-04 -5648,245,221,24,3.0,4,2.0,2,6.0,14,6145700.0,,,1,1974-08-04 -5649,245,279,64,15.0,24,10.0,10,0.0,14,6352700.0,,,1,1974-08-04 -5650,245,288,25,26.0,19,9.0,9,0.0,14,6301400.0,,,1,1974-08-04 -5651,245,304,0,33.0,12,15.0,15,0.0,12,,,,3,1974-08-04 -5652,245,269,77,32.0,20,14.0,14,0.0,13,,,,11,1974-08-04 -5653,245,230,62,24.0,10,,17,0.0,10,,,,6,1974-08-04 -5654,245,249,33,8.0,17,12.0,12,0.0,14,6481300.0,,,1,1974-08-04 -5655,245,320,61,18.0,25,11.0,11,0.0,14,6412700.0,,,1,1974-08-04 -5656,245,229,36,10.0,23,13.0,13,0.0,14,6618100.0,,,1,1974-08-04 -5657,246,171,78,21.0,12,,19,0.0,37,,,,62,1974-08-18 -5658,246,231,78,20.0,9,,20,0.0,24,,,,69,1974-08-18 -5659,246,251,56,16.0,16,,21,0.0,22,,,,20,1974-08-18 -5660,246,305,64,14.0,18,,22,0.0,22,,,,5,1974-08-18 -5661,246,181,5,12.0,1,,23,0.0,17,,,,5,1974-08-18 -5662,246,242,25,27.0,13,,24,0.0,14,,,,3,1974-08-18 -5663,246,221,24,3.0,5,,25,0.0,8,,,,5,1974-08-18 -5664,246,315,61,43.0,0,,27,0.0,0,,,,81,1974-08-18 -5665,246,282,55,22.0,0,,29,0.0,0,,,,81,1974-08-18 -5666,246,218,61,19.0,0,,30,0.0,0,,,,81,1974-08-18 -5667,246,323,33,32.0,0,,31,0.0,0,,,,81,1974-08-18 -5668,246,223,0,5.0,3,,18,0.0,37,,,,5,1974-08-18 -5669,246,250,62,31.0,0,,26,0.0,0,,,,81,1974-08-18 -5670,246,320,61,18.0,0,,28,0.0,0,,,,81,1974-08-18 -5671,246,220,24,4.0,14,,16,0.0,42,,,,4,1974-08-18 -5672,246,234,31,2.0,22,,15,0.0,43,,,,4,1974-08-18 -5673,246,249,33,8.0,4,,17,0.0,41,,,,95,1974-08-18 -5674,246,303,0,6.0,10,2.0,2,6.0,54,5367640.0,,,1,1974-08-18 -5675,246,230,62,24.0,7,3.0,3,4.0,54,5386260.0,,,1,1974-08-18 -5676,246,186,33,28.0,11,4.0,4,3.0,54,5394110.0,,,1,1974-08-18 -5677,246,222,5,11.0,8,5.0,5,2.0,54,5397800.0,,,1,1974-08-18 -5678,246,229,36,10.0,20,6.0,6,1.0,54,5398540.0,,,1,1974-08-18 -5679,246,321,0,33.0,17,7.0,7,0.0,53,,,,11,1974-08-18 -5680,246,198,33,7.0,2,1.0,1,9.0,54,5324720.0,,,1,1974-08-18 -5681,246,322,61,30.0,25,9.0,9,0.0,51,,,,13,1974-08-18 -5682,246,313,75,23.0,19,10.0,10,0.0,50,,,,14,1974-08-18 -5683,246,232,36,9.0,15,11.0,11,0.0,48,,,,22,1974-08-18 -5684,246,288,25,26.0,21,12.0,12,0.0,48,,,,16,1974-08-18 -5685,246,269,77,35.0,24,,13,0.0,46,,,,62,1974-08-18 -5686,246,237,31,1.0,6,,14,0.0,45,,,,86,1974-08-18 -5687,246,196,56,17.0,23,8.0,8,0.0,52,,,,12,1974-08-18 -5688,247,313,75,29.0,20,,19,0.0,15,,,,6,1974-09-08 -5689,247,198,33,7.0,2,,20,0.0,12,,,,6,1974-09-08 -5690,247,232,36,9.0,18,,21,0.0,11,,,,83,1974-09-08 -5691,247,279,64,15.0,25,,22,0.0,3,,,,5,1974-09-08 -5692,247,230,62,24.0,8,,23,0.0,2,,,,5,1974-09-08 -5693,247,295,64,37.0,24,,24,0.0,1,,,,6,1974-09-08 -5694,247,324,33,31.0,0,,27,0.0,0,,,,81,1974-09-08 -5695,247,318,61,19.0,0,,26,0.0,0,,,,81,1974-09-08 -5696,247,320,61,18.0,0,,28,0.0,0,,,,81,1974-09-08 -5697,247,282,55,25.0,0,,29,0.0,0,,,,81,1974-09-08 -5698,247,277,76,30.0,0,,30,0.0,0,,,,81,1974-09-08 -5699,247,315,61,23.0,0,,31,0.0,0,,,,81,1974-09-08 -5700,247,305,64,14.0,11,,25,0.0,0,,,,10,1974-09-08 -5701,247,229,36,10.0,13,,18,0.0,16,,,,3,1974-09-08 -5702,247,234,31,2.0,16,,14,0.0,30,,,,37,1974-09-08 -5703,247,171,78,21.0,17,,16,0.0,22,,,,5,1974-09-08 -5704,247,237,31,1.0,7,1.0,1,9.0,52,4976600.0,,,1,1974-09-08 -5705,247,196,56,17.0,9,,17,0.0,19,,,,5,1974-09-08 -5706,247,223,0,5.0,6,2.0,2,6.0,52,4977400.0,,,1,1974-09-08 -5707,247,221,24,3.0,12,3.0,3,4.0,52,5001300.0,,,1,1974-09-08 -5708,247,231,78,20.0,15,4.0,4,3.0,52,5064300.0,,,1,1974-09-08 -5709,247,303,0,6.0,19,6.0,6,1.0,51,,,,11,1974-09-08 -5710,247,186,33,28.0,4,7.0,7,0.0,51,,,,11,1974-09-08 -5711,247,249,33,8.0,3,5.0,5,2.0,51,,,,11,1974-09-08 -5712,247,321,0,33.0,23,9.0,9,0.0,51,,,,11,1974-09-08 -5713,247,251,56,16.0,22,10.0,10,0.0,50,,,,12,1974-09-08 -5714,247,220,24,4.0,10,11.0,11,0.0,50,,,,12,1974-09-08 -5715,247,222,5,11.0,5,,12,0.0,40,,,,5,1974-09-08 -5716,247,181,5,12.0,1,,13,0.0,32,,,,5,1974-09-08 -5717,247,242,25,27.0,14,,15,0.0,25,,,,22,1974-09-08 -5718,247,288,25,26.0,21,8.0,8,0.0,51,,,,11,1974-09-08 -5719,248,221,24,3.0,3,,22,0.0,48,,,,23,1974-09-22 -5720,248,251,56,16.0,13,,19,0.0,65,,,,5,1974-09-22 -5721,248,186,33,28.0,15,,20,0.0,61,,,,22,1974-09-22 -5722,248,305,64,14.0,17,,21,0.0,60,,,,62,1974-09-22 -5723,248,196,56,17.0,5,,23,0.0,46,,,,86,1974-09-22 -5724,248,269,33,42.0,0,,30,0.0,0,,,,81,1974-09-22 -5725,248,325,33,50.0,26,,25,0.0,33,,,,5,1974-09-22 -5726,248,232,36,9.0,23,,26,0.0,12,,,,69,1974-09-22 -5727,248,320,61,18.0,0,,27,0.0,0,,,,81,1974-09-22 -5728,248,282,55,22.0,0,,28,0.0,0,,,,81,1974-09-22 -5729,248,229,36,10.0,0,,29,0.0,0,,,,81,1974-09-22 -5730,248,181,5,12.0,2,,18,0.0,67,,,,3,1974-09-22 -5731,248,231,78,20.0,19,,24,0.0,40,,,,64,1974-09-22 -5732,248,277,64,15.0,25,,17,0.0,70,,,,62,1974-09-22 -5733,248,234,31,2.0,21,13.0,13,0.0,78,,,,12,1974-09-22 -5734,248,171,78,21.0,18,15.0,15,0.0,74,,,,29,1974-09-22 -5735,248,223,0,5.0,1,1.0,1,9.0,80,6026136.0,,,1,1974-09-22 -5736,248,199,0,33.0,12,16.0,16,0.0,72,,,,18,1974-09-22 -5737,248,237,31,1.0,10,3.0,3,4.0,80,6040630.0,,,1,1974-09-22 -5738,248,230,62,24.0,8,4.0,4,3.0,80,6041805.0,,,1,1974-09-22 -5739,248,220,24,4.0,7,5.0,5,2.0,80,6081458.0,,,1,1974-09-22 -5740,248,303,0,6.0,14,6.0,6,1.0,79,,,,11,1974-09-22 -5741,248,222,5,11.0,6,2.0,2,6.0,80,6039170.0,,,1,1974-09-22 -5742,248,249,33,8.0,9,8.0,8,0.0,79,,,,11,1974-09-22 -5743,248,198,33,7.0,4,9.0,9,0.0,79,,,,11,1974-09-22 -5744,248,323,61,19.0,22,10.0,10,0.0,78,,,,12,1974-09-22 -5745,248,242,25,27.0,11,11.0,11,0.0,78,,,,12,1974-09-22 -5746,248,287,65,66.0,24,12.0,12,0.0,78,,,,12,1974-09-22 -5747,248,288,25,26.0,20,14.0,14,0.0,77,,,,13,1974-09-22 -5748,248,206,71,55.0,16,7.0,7,0.0,79,,,,11,1974-09-22 -5749,249,242,25,27.0,21,12.0,12,0.0,54,,,,15,1974-10-06 -5750,249,222,5,11.0,9,11.0,11,0.0,55,,,,14,1974-10-06 -5751,249,196,56,17.0,10,10.0,10,0.0,57,,,,12,1974-10-06 -5752,249,288,25,26.0,24,8.0,8,0.0,58,,,,11,1974-10-06 -5753,249,199,0,33.0,20,7.0,7,0.0,59,6111451.0,,,1,1974-10-06 -5754,249,230,62,24.0,2,3.0,3,4.0,59,6091823.0,,,1,1974-10-06 -5755,249,186,33,28.0,7,5.0,5,2.0,59,6107243.0,,,1,1974-10-06 -5756,249,223,0,5.0,8,4.0,4,3.0,59,6099192.0,,,1,1974-10-06 -5757,249,249,33,8.0,4,2.0,2,6.0,59,6032174.0,,,1,1974-10-06 -5758,249,198,33,7.0,1,1.0,1,9.0,59,6021439.0,,,1,1974-10-06 -5759,249,237,31,1.0,19,,13,0.0,52,,,,69,1974-10-06 -5760,249,220,24,4.0,13,6.0,6,1.0,59,6108945.0,,,1,1974-10-06 -5761,249,282,55,22.0,22,,14,0.0,50,,,,62,1974-10-06 -5762,249,277,64,15.0,12,9.0,9,0.0,57,,,,12,1974-10-06 -5763,249,221,24,3.0,6,,16,0.0,44,,,,69,1974-10-06 -5764,249,305,64,14.0,0,,30,0.0,0,,,,81,1974-10-06 -5765,249,251,56,16.0,18,,15,0.0,47,,,,62,1974-10-06 -5766,249,269,33,42.0,0,,29,0.0,0,,,,81,1974-10-06 -5767,249,232,36,9.0,0,,28,0.0,0,,,,81,1974-10-06 -5768,249,206,71,55.0,3,,26,0.0,4,,,,2,1974-10-06 -5769,249,313,31,31.0,27,,25,0.0,6,,,,2,1974-10-06 -5770,249,234,31,2.0,16,,24,0.0,7,,,,22,1974-10-06 -5771,249,303,0,6.0,17,,27,0.0,4,,,,5,1974-10-06 -5772,249,229,36,10.0,25,,22,0.0,21,,,,69,1974-10-06 -5773,249,318,61,18.0,26,,21,0.0,25,,,,54,1974-10-06 -5774,249,287,65,66.0,14,,20,0.0,27,,,,22,1974-10-06 -5775,249,171,78,21.0,11,,19,0.0,31,,,,5,1974-10-06 -5776,249,231,78,20.0,15,,17,0.0,43,,,,10,1974-10-06 -5777,249,323,61,19.0,23,,23,0.0,9,,,,104,1974-10-06 -5778,249,181,5,12.0,5,,18,0.0,38,,,,22,1974-10-06 -5779,250,199,0,2.0,13,14.0,14,0.0,50,,,,13,1975-01-12 -5780,250,249,33,8.0,2,,15,0.0,46,,,,5,1975-01-12 -5781,250,231,2,20.0,20,,16,0.0,44,,,,62,1975-01-12 -5782,250,282,64,14.0,22,,18,0.0,24,,,,5,1975-01-12 -5783,250,196,199,17.0,1,,23,0.0,0,,,,7,1975-01-12 -5784,250,186,61,18.0,15,,22,0.0,6,,,,2,1975-01-12 -5785,250,289,54,30.0,23,,21,0.0,12,,,,3,1975-01-12 -5786,250,242,25,23.0,19,13.0,13,0.0,51,,,,12,1975-01-12 -5787,250,206,71,27.0,10,,17,0.0,27,,,,7,1975-01-12 -5788,250,251,199,16.0,14,12.0,12,0.0,51,,,,7,1975-01-12 -5789,250,220,24,4.0,8,5.0,5,2.0,53,6020540.0,,,1,1975-01-12 -5790,250,288,25,22.0,21,10.0,10,0.0,52,,,,11,1975-01-12 -5791,250,229,36,9.0,12,9.0,9,0.0,52,,,,11,1975-01-12 -5792,250,234,31,6.0,18,8.0,8,0.0,52,,,,11,1975-01-12 -5793,250,287,65,28.0,16,7.0,7,0.0,52,,,,11,1975-01-12 -5794,250,181,5,12.0,4,6.0,6,1.0,53,6045940.0,,,1,1975-01-12 -5795,250,222,5,11.0,7,4.0,4,3.0,53,6002080.0,,,1,1975-01-12 -5796,250,198,33,7.0,3,3.0,3,4.0,53,5983350.0,,,1,1975-01-12 -5797,250,230,62,24.0,6,2.0,2,6.0,53,5972200.0,,,1,1975-01-12 -5798,250,223,0,1.0,5,1.0,1,9.0,53,5966290.0,,,1,1975-01-12 -5799,250,171,2,21.0,17,,20,0.0,15,,,,6,1975-01-12 -5800,250,221,24,3.0,9,11.0,11,0.0,52,,,,11,1975-01-12 -5801,250,237,31,5.0,11,,19,0.0,15,,,,5,1975-01-12 -5802,251,222,5,11.0,5,4.0,4,3.0,40,6324450.0,,,1,1975-01-26 -5803,251,223,0,1.0,2,2.0,2,6.0,40,6286960.0,,,1,1975-01-26 -5804,251,249,33,8.0,6,1.0,1,9.0,40,6281170.0,,,1,1975-01-26 -5805,251,229,36,9.0,17,,23,0.0,1,,,,5,1975-01-26 -5806,251,221,24,3.0,8,,22,0.0,18,,,,44,1975-01-26 -5807,251,282,64,14.0,22,,21,0.0,22,,,,10,1975-01-26 -5808,251,231,2,20.0,11,,19,0.0,24,,,,69,1975-01-26 -5809,251,251,199,16.0,14,,18,0.0,31,,,,3,1975-01-26 -5810,251,220,24,4.0,9,,17,0.0,31,,,,22,1975-01-26 -5811,251,196,199,17.0,1,,16,0.0,32,,,,69,1975-01-26 -5812,251,237,31,5.0,16,15.0,15,0.0,38,,,,12,1975-01-26 -5813,251,242,25,23.0,23,14.0,14,0.0,39,,,,11,1975-01-26 -5814,251,287,65,28.0,15,,20,0.0,22,,,,64,1975-01-26 -5815,251,288,25,22.0,20,12.0,12,0.0,39,,,,11,1975-01-26 -5816,251,171,2,21.0,11,11.0,11,0.0,39,,,,11,1975-01-26 -5817,251,186,61,18.0,13,10.0,10,0.0,40,6430770.0,,,1,1975-01-26 -5818,251,234,31,6.0,12,9.0,9,0.0,40,6393010.0,,,1,1975-01-26 -5819,251,198,33,7.0,3,8.0,8,0.0,40,6380790.0,,,1,1975-01-26 -5820,251,206,71,27.0,18,7.0,7,0.0,40,6347980.0,,,1,1975-01-26 -5821,251,230,62,24.0,7,6.0,6,1.0,40,6346290.0,,,1,1975-01-26 -5822,251,181,5,12.0,4,5.0,5,2.0,40,6343050.0,,,1,1975-01-26 -5823,251,289,54,30.0,21,13.0,13,0.0,39,,,,11,1975-01-26 -5824,251,199,0,2.0,10,3.0,3,4.0,40,6307830.0,,,1,1975-01-26 -5825,252,171,2,21.0,23,,18,0.0,69,,,,62,1975-03-01 -5826,252,223,0,1.0,11,,19,0.0,65,,,,62,1975-03-01 -5827,252,250,24,32.0,17,,20,0.0,55,,,,3,1975-03-01 -5828,252,230,62,24.0,12,,21,0.0,53,,,,69,1975-03-01 -5829,252,196,199,17.0,13,,22,0.0,37,,,,25,1975-03-01 -5830,252,186,61,18.0,10,,25,0.0,19,,,,8,1975-03-01 -5831,252,231,2,20.0,15,,24,0.0,22,,,,5,1975-03-01 -5832,252,206,71,27.0,6,17.0,17,0.0,70,,,,7,1975-03-01 -5833,252,229,36,9.0,7,,26,0.0,16,,,,21,1975-03-01 -5834,252,289,54,30.0,0,,27,0.0,0,,,,81,1975-03-01 -5835,252,288,25,22.0,0,,28,0.0,0,,,,81,1975-03-01 -5836,252,274,36,10.0,26,,23,0.0,23,,,,69,1975-03-01 -5837,252,222,5,11.0,9,16.0,16,0.0,71,,,,37,1975-03-01 -5838,252,290,31,34.0,25,11.0,11,0.0,76,,,,12,1975-03-01 -5839,252,292,0,31.0,20,14.0,14,0.0,76,,,,12,1975-03-01 -5840,252,291,31,33.0,22,13.0,13,0.0,76,,,,12,1975-03-01 -5841,252,234,31,6.0,21,12.0,12,0.0,76,,,,12,1975-03-01 -5842,252,237,31,5.0,8,10.0,10,0.0,77,,,,11,1975-03-01 -5843,252,251,199,16.0,19,9.0,9,0.0,77,,,,11,1975-03-01 -5844,252,287,65,28.0,18,8.0,8,0.0,77,,,,11,1975-03-01 -5845,252,242,73,23.0,14,7.0,7,0.0,78,6269810.0,,,1,1975-03-01 -5846,252,199,0,2.0,16,6.0,6,1.0,78,6260540.0,,,1,1975-03-01 -5847,252,249,33,8.0,1,4.0,4,3.0,78,6214210.0,,,1,1975-03-01 -5848,252,220,24,4.0,5,3.0,3,4.0,78,6213820.0,,,1,1975-03-01 -5849,252,198,33,7.0,2,2.0,2,6.0,78,6200640.0,,,1,1975-03-01 -5850,252,221,24,3.0,3,1.0,1,9.0,78,6196900.0,,,1,1975-03-01 -5851,252,275,64,14.0,24,15.0,15,0.0,76,,,,12,1975-03-01 -5852,252,181,5,12.0,4,5.0,5,2.0,78,6225540.0,,,1,1975-03-01 -5853,253,234,31,6.0,16,2.0,2,3.0,29,2574800.0,,,1,1975-04-27 -5854,253,230,62,24.0,3,,18,0.0,6,,,,3,1975-04-27 -5855,253,186,61,18.0,6,8.0,8,0.0,26,,,,13,1975-04-27 -5856,253,222,5,11.0,2,,9,0.0,25,,,,62,1975-04-27 -5857,253,242,25,22.0,9,,10,0.0,25,,,,3,1975-04-27 -5858,253,249,33,8.0,14,,11,0.0,25,,,,3,1975-04-27 -5859,253,251,199,16.0,8,,12,0.0,23,,,,3,1975-04-27 -5860,253,237,31,5.0,12,,13,0.0,23,,,,22,1975-04-27 -5861,253,294,55,31.0,19,,14,0.0,20,,,,7,1975-04-27 -5862,253,295,25,23.0,22,,15,0.0,18,,,,62,1975-04-27 -5863,253,293,2,21.0,18,7.0,7,0.0,27,,,,12,1975-04-27 -5864,253,206,71,27.0,4,,16,0.0,16,,,,22,1975-04-27 -5865,253,221,24,3.0,13,,19,0.0,3,,,,5,1975-04-27 -5866,253,287,65,28.0,17,,20,0.0,3,,,,3,1975-04-27 -5867,253,177,62,25.0,20,,21,0.0,3,,,,3,1975-04-27 -5868,253,220,24,4.0,7,,22,0.0,1,,,,3,1975-04-27 -5869,253,289,54,30.0,21,,23,0.0,1,,,,54,1975-04-27 -5870,253,231,2,20.0,25,,24,0.0,1,,,,54,1975-04-27 -5871,253,181,5,12.0,1,,25,0.0,0,,,,3,1975-04-27 -5872,253,223,0,1.0,26,,26,0.0,0,,,,54,1975-04-27 -5873,253,275,64,14.0,23,,17,0.0,7,,,,69,1975-04-27 -5874,253,229,36,9.0,5,5.0,5,1.0,28,,,,11,1975-04-27 -5875,253,274,36,10.0,24,6.0,6,0.5,27,,,,12,1975-04-27 -5876,253,198,33,7.0,15,3.0,3,2.0,28,,,,11,1975-04-27 -5877,253,199,0,2.0,11,1.0,1,4.5,29,2573700.0,,,1,1975-04-27 -5878,253,196,199,17.0,10,4.0,4,1.5,28,,,,11,1975-04-27 -5879,254,199,0,2.0,15,6.0,6,1.0,75,7323380.0,,,1,1975-05-11 -5880,254,289,54,30.0,0,,26,0.0,0,,,,81,1975-05-11 -5881,254,274,36,10.0,0,,25,0.0,0,,,,81,1975-05-11 -5882,254,294,55,31.0,0,,23,0.0,0,,,,81,1975-05-11 -5883,254,275,64,14.0,0,,22,0.0,0,,,,81,1975-05-11 -5884,254,288,73,23.0,0,,21,0.0,0,,,,81,1975-05-11 -5885,254,231,2,20.0,0,,20,0.0,0,,,,81,1975-05-11 -5886,254,171,2,21.0,0,,19,0.0,0,,,,81,1975-05-11 -5887,254,196,199,17.0,3,,18,0.0,0,,,,3,1975-05-11 -5888,254,221,24,3.0,7,7.0,7,0.0,74,,,,11,1975-05-11 -5889,254,206,71,27.0,13,,17,0.0,9,,,,44,1975-05-11 -5890,254,222,5,11.0,17,,15,0.0,36,,,,3,1975-05-11 -5891,254,251,199,16.0,2,,14,0.0,39,,,,3,1975-05-11 -5892,254,229,36,9.0,5,,13,0.0,48,,,,3,1975-05-11 -5893,254,177,62,26.0,18,,12,0.0,61,,,,36,1975-05-11 -5894,254,230,62,24.0,11,,11,0.0,63,,,,3,1975-05-11 -5895,254,287,65,28.0,16,,10,0.0,66,,,,3,1975-05-11 -5896,254,198,33,7.0,10,9.0,9,0.0,73,,,,12,1975-05-11 -5897,254,234,31,6.0,14,8.0,8,0.0,74,,,,11,1975-05-11 -5898,254,220,24,4.0,12,5.0,5,2.0,75,7322170.0,,,1,1975-05-11 -5899,254,186,61,18.0,6,,16,0.0,36,,,,20,1975-05-11 -5900,254,237,31,5.0,4,4.0,4,3.0,75,7319760.0,,,1,1975-05-11 -5901,254,296,62,25.0,0,,24,0.0,0,,,,81,1975-05-11 -5902,254,223,0,1.0,9,2.0,2,6.0,75,7284090.0,,,1,1975-05-11 -5903,254,181,5,12.0,1,1.0,1,9.0,75,7281310.0,,,1,1975-05-11 -5904,254,249,33,8.0,8,3.0,3,4.0,75,7299120.0,,,1,1975-05-11 -5905,255,199,0,2.0,15,,24,0.0,0,,,,3,1975-05-25 -5906,255,177,62,26.0,13,,23,0.0,1,,,,3,1975-05-25 -5907,255,231,2,20.0,19,,22,0.0,2,,,,8,1975-05-25 -5908,255,196,199,17.0,10,,21,0.0,13,,,,20,1975-05-25 -5909,255,230,62,24.0,11,,20,0.0,15,,,,7,1975-05-25 -5910,255,274,36,10.0,17,,18,0.0,18,,,,5,1975-05-25 -5911,255,171,2,21.0,23,,17,0.0,18,,,,6,1975-05-25 -5912,255,237,31,5.0,14,,16,0.0,36,,,,23,1975-05-25 -5913,255,234,31,6.0,16,,15,0.0,52,,,,23,1975-05-25 -5914,255,229,36,9.0,3,,14,0.0,54,,,,23,1975-05-25 -5915,255,289,54,30.0,24,12.0,12,0.0,67,,,,13,1975-05-25 -5916,255,287,65,28.0,21,11.0,11,0.0,67,,,,13,1975-05-25 -5917,255,186,61,18.0,18,10.0,10,0.0,68,,,,12,1975-05-25 -5918,255,275,64,14.0,20,9.0,9,0.0,68,,,,12,1975-05-25 -5919,255,249,33,8.0,2,8.0,8,0.0,69,,,,11,1975-05-25 -5920,255,223,0,1.0,8,7.0,7,0.0,69,,,,11,1975-05-25 -5921,255,251,199,16.0,5,6.0,6,1.0,70,6322430.0,,,1,1975-05-25 -5922,255,222,5,11.0,4,5.0,5,2.0,70,6297820.0,,,1,1975-05-25 -5923,255,295,73,22.0,22,,13,0.0,57,,,,22,1975-05-25 -5924,255,220,24,4.0,12,4.0,4,3.0,70,6294060.0,,,1,1975-05-25 -5925,255,293,73,23.0,7,,19,0.0,17,,,,5,1975-05-25 -5926,255,221,24,3.0,9,2.0,2,6.0,70,6253200.0,,,1,1975-05-25 -5927,255,198,33,7.0,6,3.0,3,4.0,70,6275800.0,,,1,1975-05-25 -5928,255,181,5,12.0,1,1.0,1,9.0,70,6233980.0,,,1,1975-05-25 -5929,256,274,36,10.0,24,,26,0.0,10,,,,69,1975-06-08 -5930,256,293,73,23.0,17,6.0,6,1.0,79,,,,11,1975-06-08 -5931,256,221,24,3.0,8,7.0,7,0.0,79,,,,11,1975-06-08 -5932,256,223,0,1.0,11,8.0,8,0.0,79,,,,11,1975-06-08 -5933,256,237,31,5.0,9,9.0,9,0.0,79,,,,11,1975-06-08 -5934,256,296,62,32.0,21,10.0,10,0.0,78,,,,60,1975-06-08 -5935,256,177,62,26.0,19,11.0,11,0.0,78,,,,12,1975-06-08 -5936,256,220,24,4.0,2,12.0,12,0.0,78,,,,12,1975-06-08 -5937,256,275,64,14.0,23,13.0,13,0.0,78,,,,12,1975-06-08 -5938,256,281,2,20.0,22,14.0,14,0.0,78,,,,12,1975-06-08 -5939,256,234,31,6.0,18,15.0,15,0.0,77,,,,13,1975-06-08 -5940,256,289,54,30.0,25,17.0,17,0.0,74,,,,16,1975-06-08 -5941,256,251,199,16.0,7,,18,0.0,53,,,,20,1975-06-08 -5942,256,250,2,21.0,20,,19,0.0,49,,,,27,1975-06-08 -5943,256,266,73,22.0,26,,20,0.0,47,,,,7,1975-06-08 -5944,256,249,33,8.0,6,,21,0.0,41,,,,20,1975-06-08 -5945,256,196,199,17.0,3,,22,0.0,38,,,,5,1975-06-08 -5946,256,229,36,9.0,1,,23,0.0,36,,,,7,1975-06-08 -5947,256,199,0,2.0,14,,24,0.0,34,,,,25,1975-06-08 -5948,256,230,62,24.0,13,,25,0.0,21,,,,23,1975-06-08 -5949,256,287,65,28.0,16,5.0,5,2.0,80,7249082.0,,,1,1975-06-08 -5950,256,186,61,18.0,10,16.0,16,0.0,77,,,,13,1975-06-08 -5951,256,206,71,27.0,15,4.0,4,3.0,80,7202699.0,,,1,1975-06-08 -5952,256,198,33,7.0,4,2.0,2,6.0,80,7164607.0,,,1,1975-06-08 -5953,256,181,5,12.0,5,1.0,1,9.0,80,7158319.0,,,1,1975-06-08 -5954,256,222,5,11.0,12,3.0,3,4.0,80,7187414.0,,,1,1975-06-08 -5955,257,251,199,16.0,12,6.0,6,1.0,74,,,,11,1975-06-22 -5956,257,298,72,35.0,0,,25,0.0,0,,,,54,1975-06-22 -5957,257,229,36,9.0,11,,24,0.0,0,,,,22,1975-06-22 -5958,257,234,31,6.0,21,,23,0.0,6,,,,5,1975-06-22 -5959,257,275,64,14.0,20,,22,0.0,23,,,,24,1975-06-22 -5960,257,223,0,1.0,6,,21,0.0,40,,,,5,1975-06-22 -5961,257,186,61,18.0,14,,20,0.0,43,,,,76,1975-06-22 -5962,257,196,199,17.0,10,,19,0.0,44,,,,27,1975-06-22 -5963,257,199,0,2.0,8,,18,0.0,61,,,,3,1975-06-22 -5964,257,221,24,3.0,4,16.0,16,0.0,67,,,,5,1975-06-22 -5965,257,237,31,5.0,16,15.0,15,0.0,69,,,,60,1975-06-22 -5966,257,274,36,10.0,23,14.0,14,0.0,70,,,,15,1975-06-22 -5967,257,177,73,22.0,17,13.0,13,0.0,70,,,,15,1975-06-22 -5968,257,250,2,20.0,19,12.0,12,0.0,70,,,,15,1975-06-22 -5969,257,289,54,30.0,24,11.0,11,0.0,71,,,,14,1975-06-22 -5970,257,297,55,31.0,22,10.0,10,0.0,71,,,,14,1975-06-22 -5971,257,220,24,4.0,13,9.0,9,0.0,73,,,,12,1975-06-22 -5972,257,287,65,28.0,18,8.0,8,0.0,74,,,,11,1975-06-22 -5973,257,293,73,23.0,7,7.0,7,0.0,74,,,,11,1975-06-22 -5974,257,171,2,21.0,15,,17,0.0,64,,,,5,1975-06-22 -5975,257,198,33,7.0,5,4.0,4,3.0,74,,,,11,1975-06-22 -5976,257,249,33,8.0,9,5.0,5,2.0,74,,,,11,1975-06-22 -5977,257,181,5,12.0,1,2.0,2,6.0,75,6418460.0,,,1,1975-06-22 -5978,257,222,5,11.0,2,3.0,3,4.0,75,6472460.0,,,1,1975-06-22 -5979,257,230,62,24.0,3,1.0,1,9.0,75,6417400.0,,,1,1975-06-22 -5980,258,295,2,20.0,24,,26,0.0,0,,,,54,1975-07-06 -5981,258,293,73,23.0,12,7.0,7,0.0,54,6088450.0,,,1,1975-07-06 -5982,258,196,199,17.0,4,8.0,8,0.0,54,6098620.0,,,1,1975-07-06 -5983,258,221,24,3.0,2,9.0,9,0.0,54,6110520.0,,,1,1975-07-06 -5984,258,237,31,5.0,17,10.0,10,0.0,54,6114860.0,,,1,1975-07-06 -5985,258,171,2,21.0,16,11.0,11,0.0,54,6115610.0,,,1,1975-07-06 -5986,258,218,24,15.0,21,12.0,12,0.0,54,6115970.0,,,1,1975-07-06 -5987,258,186,61,18.0,14,13.0,13,0.0,53,,,,11,1975-07-06 -5988,258,198,33,7.0,11,14.0,14,0.0,53,,,,11,1975-07-06 -5989,258,297,55,31.0,22,15.0,15,0.0,53,,,,11,1975-07-06 -5990,258,177,73,22.0,20,16.0,16,0.0,53,,,,11,1975-07-06 -5991,258,274,36,10.0,26,18.0,18,0.0,50,,,,14,1975-07-06 -5992,258,249,33,8.0,5,,19,0.0,26,,,,7,1975-07-06 -5993,258,234,31,6.0,19,,20,0.0,17,,,,23,1975-07-06 -5994,258,289,54,30.0,23,,21,0.0,14,,,,5,1975-07-06 -5995,258,229,36,9.0,8,,22,0.0,6,,,,83,1975-07-06 -5996,258,222,5,11.0,9,,23,0.0,6,,,,5,1975-07-06 -5997,258,287,65,28.0,18,,24,0.0,6,,,,7,1975-07-06 -5998,258,251,199,16.0,6,,25,0.0,2,,,,7,1975-07-06 -5999,258,220,24,4.0,13,6.0,6,1.0,54,6086240.0,,,1,1975-07-06 -6000,258,275,64,14.0,25,17.0,17,0.0,52,,,,12,1975-07-06 -6001,258,206,71,27.0,15,5.0,5,2.0,54,6080920.0,,,1,1975-07-06 -6002,258,199,0,2.0,7,3.0,3,4.0,54,6021150.0,,,1,1975-07-06 -6003,258,230,62,24.0,3,2.0,2,6.0,54,6020430.0,,,1,1975-07-06 -6004,258,181,5,12.0,1,1.0,1,9.0,54,6018840.0,,,1,1975-07-06 -6005,258,223,0,1.0,10,4.0,4,3.0,54,6058610.0,,,1,1975-07-06 -6006,259,181,5,12.0,3,8.0,8,0.0,54,,,,12,1975-07-19 -6007,259,220,24,4.0,17,9.0,9,0.0,54,,,,3,1975-07-19 -6008,259,177,73,22.0,28,10.0,10,0.0,54,,,,12,1975-07-19 -6009,259,298,72,35.0,0,,28,0.0,0,,,,81,1975-07-19 -6010,259,294,55,31.0,0,,27,0.0,0,,,,81,1975-07-19 -6011,259,198,33,7.0,8,,26,0.0,4,,,,5,1975-07-19 -6012,259,171,2,21.0,19,,25,0.0,5,,,,6,1975-07-19 -6013,259,237,31,5.0,16,,24,0.0,7,,,,5,1975-07-19 -6014,259,199,0,2.0,10,7.0,7,0.0,55,,,,3,1975-07-19 -6015,259,274,36,29.0,22,,23,0.0,18,,,,5,1975-07-19 -6016,259,301,31,6.0,25,,21,0.0,28,,,,3,1975-07-19 -6017,259,232,36,10.0,14,,20,0.0,45,,,,3,1975-07-19 -6018,259,289,54,30.0,24,19.0,19,0.0,50,,,,3,1975-07-19 -6019,259,300,61,19.0,23,18.0,18,0.0,50,,,,3,1975-07-19 -6020,259,299,74,32.0,26,17.0,17,0.0,51,,,,3,1975-07-19 -6021,259,204,31,15.0,21,16.0,16,0.0,53,,,,3,1975-07-19 -6022,259,293,73,23.0,13,15.0,15,0.0,53,,,,3,1975-07-19 -6023,259,196,199,17.0,11,14.0,14,0.0,53,,,,3,1975-07-19 -6024,259,222,5,11.0,4,13.0,13,0.0,54,,,,12,1975-07-19 -6025,259,206,71,27.0,12,12.0,12,0.0,54,,,,12,1975-07-19 -6026,259,186,61,18.0,18,11.0,11,0.0,54,,,,3,1975-07-19 -6027,259,251,199,16.0,1,,22,0.0,20,,,,3,1975-07-19 -6028,259,229,36,9.0,5,6.0,6,1.0,55,,,,11,1975-07-19 -6029,259,249,33,8.0,2,2.0,2,6.0,55,,,,3,1975-07-19 -6030,259,230,62,24.0,9,4.0,4,3.0,55,,,,3,1975-07-19 -6031,259,223,0,1.0,7,1.0,1,9.0,56,4925000.0,,,1,1975-07-19 -6032,259,287,36,28.0,15,5.0,5,2.0,55,,,,3,1975-07-19 -6033,259,221,24,3.0,6,3.0,3,4.0,55,,,,3,1975-07-19 -6034,260,297,55,19.0,24,6.0,6,1.0,14,6379600.0,,,1,1975-08-03 -6035,260,274,36,29.0,25,7.0,7,0.0,14,6524500.0,,,1,1975-08-03 -6036,260,228,62,25.0,23,8.0,8,0.0,14,6535000.0,,,1,1975-08-03 -6037,260,220,24,4.0,4,9.0,9,0.0,13,,,,11,1975-08-03 -6038,260,206,71,27.0,13,10.0,10,0.0,12,,,,60,1975-08-03 -6039,260,230,62,24.0,9,,11,0.0,10,,,,36,1975-08-03 -6040,260,222,5,11.0,5,,12,0.0,9,,,,5,1975-08-03 -6041,260,293,73,23.0,17,,13,0.0,9,,,,3,1975-08-03 -6042,260,221,24,3.0,3,,14,0.0,7,,,,3,1975-08-03 -6043,260,196,199,17.0,12,,15,0.0,7,,,,27,1975-08-03 -6044,260,249,33,8.0,2,,16,0.0,5,,,,22,1975-08-03 -6045,260,289,54,30.0,22,,17,0.0,4,,,,5,1975-08-03 -6046,260,232,36,10.0,7,,18,0.0,3,,,,5,1975-08-03 -6047,260,229,36,9.0,11,,20,0.0,3,,,,22,1975-08-03 -6048,260,237,31,5.0,18,,22,0.0,1,,,,8,1975-08-03 -6049,260,287,36,28.0,19,,23,0.0,1,,,,27,1975-08-03 -6050,260,199,0,2.0,6,,24,0.0,0,,,,3,1975-08-03 -6051,260,269,2,20.0,20,,25,0.0,0,,,,3,1975-08-03 -6052,260,244,72,35.0,0,,26,0.0,0,,,,81,1975-08-03 -6053,260,177,73,22.0,21,5.0,5,2.0,14,6304400.0,,,1,1975-08-03 -6054,260,251,199,16.0,16,4.0,4,3.0,14,6285500.0,,,1,1975-08-03 -6055,260,186,31,6.0,14,,21,0.0,2,,,,22,1975-08-03 -6056,260,171,2,21.0,15,2.0,2,6.0,14,6171800.0,,,1,1975-08-03 -6057,260,181,5,12.0,1,3.0,3,4.0,14,6217400.0,,,1,1975-08-03 -6058,260,223,0,1.0,8,,19,0.0,3,,,,22,1975-08-03 -6059,260,198,33,7.0,10,1.0,1,9.0,14,6074100.0,,,1,1975-08-03 -6060,261,223,0,1.0,3,9.0,9,0.0,28,,,,11,1975-08-17 -6061,261,186,61,18.0,18,10.0,10,0.0,28,,,,11,1975-08-17 -6062,261,220,24,4.0,7,11.0,11,0.0,28,,,,11,1975-08-17 -6063,261,277,55,31.0,23,12.0,12,0.0,28,,,,11,1975-08-17 -6064,261,238,62,25.0,17,13.0,13,0.0,28,,,,11,1975-08-17 -6065,261,198,33,7.0,11,14.0,14,0.0,28,,,,11,1975-08-17 -6066,261,293,73,23.0,16,15.0,15,0.0,28,,,,11,1975-08-17 -6067,261,242,73,22.0,25,16.0,16,0.0,27,,,,12,1975-08-17 -6068,261,274,36,29.0,21,17.0,17,0.0,26,,,,13,1975-08-17 -6069,261,294,55,33.0,27,,18,0.0,25,,,,62,1975-08-17 -6070,261,222,5,11.0,5,7.0,7,0.0,29,3575760.0,,,1,1975-08-17 -6071,261,221,24,3.0,10,8.0,8,0.0,28,,,,11,1975-08-17 -6072,261,249,33,8.0,6,,21,0.0,17,,,,5,1975-08-17 -6073,261,302,2,20.0,28,,22,0.0,14,,,,5,1975-08-17 -6074,261,232,36,10.0,4,,23,0.0,10,,,,3,1975-08-17 -6075,261,196,200,17.0,14,,24,0.0,10,,,,98,1975-08-17 -6076,261,275,64,14.0,24,,25,0.0,2,,,,5,1975-08-17 -6077,261,206,71,27.0,19,,26,0.0,1,,,,3,1975-08-17 -6078,261,287,36,28.0,20,,27,0.0,0,,,,3,1975-08-17 -6079,261,204,31,6.0,22,,28,0.0,0,,,,3,1975-08-17 -6080,261,244,72,35.0,0,,29,0.0,0,,,,81,1975-08-17 -6081,261,289,54,30.0,0,,30,0.0,0,,,,81,1975-08-17 -6082,261,171,2,21.0,12,,20,0.0,21,,,,64,1975-08-17 -6083,261,228,62,32.0,26,,19,0.0,23,,,,10,1975-08-17 -6084,261,181,5,12.0,1,6.0,6,0.5,29,3566970.0,,,1,1975-08-17 -6085,261,199,0,2.0,9,4.0,4,1.5,29,3549350.0,,,1,1975-08-17 -6086,261,251,199,16.0,15,3.0,3,2.0,29,3511540.0,,,1,1975-08-17 -6087,261,230,62,24.0,2,2.0,2,3.0,29,3503720.0,,,1,1975-08-17 -6088,261,229,36,9.0,8,1.0,1,4.5,29,3476690.0,,,1,1975-08-17 -6089,261,237,31,5.0,13,5.0,5,1.0,29,3560020.0,,,1,1975-08-17 -6090,262,238,62,25.0,21,10.0,10,0.0,50,,,,12,1975-09-07 -6091,262,221,24,3.0,4,8.0,8,0.0,51,,,,11,1975-09-07 -6092,262,228,62,34.0,17,9.0,9,0.0,51,,,,11,1975-09-07 -6093,262,277,55,32.0,19,12.0,12,0.0,48,,,,14,1975-09-07 -6094,262,301,31,6.0,25,13.0,13,0.0,46,,,,16,1975-09-07 -6095,262,253,2,20.0,22,14.0,14,0.0,46,,,,16,1975-09-07 -6096,262,196,200,17.0,13,,15,0.0,32,,,,48,1975-09-07 -6097,262,274,36,29.0,24,,16,0.0,21,,,,3,1975-09-07 -6098,262,232,36,10.0,16,,17,0.0,15,,,,3,1975-09-07 -6099,262,171,2,21.0,18,,18,0.0,7,,,,6,1975-09-07 -6100,262,199,0,2.0,5,,21,0.0,2,,,,3,1975-09-07 -6101,262,242,73,22.0,23,,20,0.0,3,,,,3,1975-09-07 -6102,262,220,24,4.0,12,7.0,7,0.0,51,,,,11,1975-09-07 -6103,262,237,31,5.0,11,,22,0.0,1,,,,5,1975-09-07 -6104,262,244,72,35.0,0,,28,0.0,0,,,,81,1975-09-07 -6105,262,293,73,23.0,6,,23,0.0,1,,,,3,1975-09-07 -6106,262,206,71,27.0,15,,24,0.0,1,,,,3,1975-09-07 -6107,262,229,36,9.0,9,,25,0.0,1,,,,8,1975-09-07 -6108,262,275,64,14.0,20,,26,0.0,0,,,,10,1975-09-07 -6109,262,294,55,31.0,0,,27,0.0,0,,,,81,1975-09-07 -6110,262,249,33,8.0,10,,19,0.0,6,,,,37,1975-09-07 -6111,262,231,54,30.0,26,11.0,11,0.0,48,,,,14,1975-09-07 -6112,262,251,199,16.0,14,6.0,6,1.0,52,5038500.0,,,1,1975-09-07 -6113,262,198,33,7.0,7,4.0,4,3.0,52,5017700.0,,,1,1975-09-07 -6114,262,181,5,12.0,1,3.0,3,4.0,52,4985800.0,,,1,1975-09-07 -6115,262,223,0,1.0,3,2.0,2,6.0,52,4979200.0,,,1,1975-09-07 -6116,262,222,5,11.0,2,1.0,1,9.0,52,4962600.0,,,1,1975-09-07 -6117,262,230,62,24.0,8,5.0,5,2.0,52,5019700.0,,,1,1975-09-07 -6118,263,221,24,3.0,10,6.0,6,1.0,59,6228496.0,,,1,1975-10-05 -6119,263,237,31,5.0,14,5.0,5,2.0,59,6228161.0,,,1,1975-10-05 -6120,263,230,62,24.0,15,4.0,4,3.0,59,6227650.0,,,1,1975-10-05 -6121,263,199,0,2.0,9,3.0,3,4.0,59,6225812.0,,,1,1975-10-05 -6122,263,223,0,1.0,2,2.0,2,6.0,59,6183118.0,,,1,1975-10-05 -6123,263,181,5,12.0,1,1.0,1,9.0,59,6178175.0,,,1,1975-10-05 -6124,263,229,36,9.0,6,7.0,7,0.0,59,6282206.0,,,1,1975-10-05 -6125,263,232,36,10.0,13,8.0,8,0.0,58,,,,11,1975-10-05 -6126,263,289,54,30.0,23,10.0,10,0.0,55,,,,14,1975-10-05 -6127,263,251,199,16.0,7,,11,0.0,52,,,,62,1975-10-05 -6128,263,204,31,6.0,19,,12,0.0,49,,,,62,1975-10-05 -6129,263,186,65,28.0,12,9.0,9,0.0,57,,,,12,1975-10-05 -6130,263,294,55,31.0,22,,14,0.0,41,,,,6,1975-10-05 -6131,263,274,2,20.0,24,,24,0.0,0,,,,80,1975-10-05 -6132,263,171,2,21.0,21,,23,0.0,0,,,,68,1975-10-05 -6133,263,238,62,25.0,18,,13,0.0,46,,,,3,1975-10-05 -6134,263,220,24,4.0,8,,21,0.0,2,,,,3,1975-10-05 -6135,263,276,24,15.0,20,,20,0.0,5,,,,5,1975-10-05 -6136,263,293,73,23.0,17,,19,0.0,5,,,,3,1975-10-05 -6137,263,249,33,8.0,16,,22,0.0,2,,,,3,1975-10-05 -6138,263,198,33,7.0,3,,17,0.0,9,,,,5,1975-10-05 -6139,263,196,199,17.0,4,,16,0.0,19,,,,67,1975-10-05 -6140,263,222,5,11.0,11,,15,0.0,0,,,,54,1975-10-05 -6141,263,206,71,27.0,5,,18,0.0,9,,,,22,1975-10-05 -6142,264,269,64,14.0,21,,22,0.0,2,,,,94,1976-01-25 -6143,264,223,54,30.0,5,13.0,13,0.0,37,,,,13,1976-01-25 -6144,264,186,65,28.0,8,,21,0.0,2,,,,69,1976-01-25 -6145,264,206,31,6.0,16,,20,0.0,6,,,,3,1976-01-25 -6146,264,237,31,5.0,18,,19,0.0,10,,,,3,1976-01-25 -6147,264,171,26,26.0,11,,18,0.0,14,,,,7,1976-01-25 -6148,264,229,36,9.0,7,,17,0.0,15,,,,44,1976-01-25 -6149,264,230,0,11.0,1,,16,0.0,32,,,,3,1976-01-25 -6150,264,196,56,17.0,3,,15,0.0,33,,,,3,1976-01-25 -6151,264,198,201,7.0,15,12.0,12,0.0,37,,,,60,1976-01-25 -6152,264,274,36,10.0,22,14.0,14,0.0,36,,,,14,1976-01-25 -6153,264,249,201,8.0,10,10.0,10,0.0,39,,,,11,1976-01-25 -6154,264,181,5,1.0,2,1.0,1,9.0,40,6316780.0,,,1,1976-01-25 -6155,264,220,24,4.0,9,2.0,2,6.0,40,6338250.0,,,1,1976-01-25 -6156,264,251,56,16.0,12,3.0,3,4.0,40,6340620.0,,,1,1976-01-25 -6157,264,232,36,34.0,14,4.0,4,3.0,40,6404950.0,,,1,1976-01-25 -6158,264,252,54,31.0,20,11.0,11,0.0,39,,,,11,1976-01-25 -6159,264,199,0,12.0,6,6.0,6,1.0,40,6435050.0,,,1,1976-01-25 -6160,264,222,5,2.0,4,7.0,7,0.0,40,6452020.0,,,1,1976-01-25 -6161,264,234,57,20.0,19,8.0,8,0.0,39,,,,11,1976-01-25 -6162,264,253,2,21.0,17,9.0,9,0.0,39,,,,11,1976-01-25 -6163,264,221,24,3.0,13,5.0,5,2.0,40,6433240.0,,,1,1976-01-25 -6164,265,228,62,24.0,24,15.0,15,0.0,74,,,,14,1976-03-06 -6165,265,234,57,20.0,19,16.0,16,0.0,73,,,,15,1976-03-06 -6166,265,223,54,30.0,21,17.0,17,0.0,70,,,,5,1976-03-06 -6167,265,222,5,2.0,9,,18,0.0,52,,,,5,1976-03-06 -6168,265,171,26,26.0,8,,19,0.0,49,,,,5,1976-03-06 -6169,265,249,201,8.0,14,,21,0.0,22,,,,51,1976-03-06 -6170,265,254,31,6.0,25,,22,0.0,18,,,,8,1976-03-06 -6171,265,198,201,7.0,11,,23,0.0,16,,,,51,1976-03-06 -6172,265,277,55,22.0,18,14.0,14,0.0,76,,,,12,1976-03-06 -6173,265,250,24,15.0,16,,25,0.0,0,,,,3,1976-03-06 -6174,265,196,56,17.0,15,,20,0.0,28,,,,21,1976-03-06 -6175,265,237,36,10.0,13,,24,0.0,15,,,,3,1976-03-06 -6176,265,232,36,34.0,17,12.0,12,0.0,76,,,,12,1976-03-06 -6177,265,238,61,18.0,20,11.0,11,0.0,77,,,,11,1976-03-06 -6178,265,276,57,21.0,22,13.0,13,0.0,76,,,,12,1976-03-06 -6179,265,230,0,11.0,1,2.0,2,6.0,78,6139700.0,,,1,1976-03-06 -6180,265,199,0,12.0,4,3.0,3,4.0,78,6184300.0,,,1,1976-03-06 -6181,265,221,24,3.0,12,4.0,4,3.0,78,6206800.0,,,1,1976-03-06 -6182,265,186,65,28.0,3,5.0,5,2.0,77,,,,11,1976-03-06 -6183,265,181,5,1.0,2,1.0,1,9.0,78,6138400.0,,,1,1976-03-06 -6184,265,251,56,16.0,7,7.0,7,0.0,77,,,,11,1976-03-06 -6185,265,229,36,9.0,5,8.0,8,0.0,77,,,,11,1976-03-06 -6186,265,220,24,4.0,6,9.0,9,0.0,77,,,,11,1976-03-06 -6187,265,275,31,5.0,23,10.0,10,0.0,77,,,,11,1976-03-06 -6188,265,206,71,27.0,13,6.0,6,1.0,77,,,,11,1976-03-06 -6189,266,277,55,22.0,17,8.0,8,0.0,78,,,,12,1976-03-28 -6190,266,222,5,2.0,1,1.0,1,9.0,80,6798471.0,,,1,1976-03-28 -6191,266,181,5,1.0,4,2.0,2,6.0,80,6840885.0,,,1,1976-03-28 -6192,266,220,24,4.0,2,3.0,3,4.0,80,6848443.0,,,1,1976-03-28 -6193,266,171,26,26.0,12,4.0,4,3.0,80,6871299.0,,,1,1976-03-28 -6194,266,199,0,12.0,14,5.0,5,2.0,80,6880763.0,,,1,1976-03-28 -6195,266,223,54,30.0,16,6.0,6,1.0,79,,,,11,1976-03-28 -6196,266,196,56,17.0,7,7.0,7,0.0,79,,,,11,1976-03-28 -6197,266,249,201,8.0,13,9.0,9,0.0,77,,,,13,1976-03-28 -6198,266,206,71,27.0,15,,15,0.0,15,,,,47,1976-03-28 -6199,266,177,61,19.0,19,,11,0.0,70,,,,62,1976-03-28 -6200,266,238,61,18.0,0,,27,0.0,0,,,,81,1976-03-28 -6201,266,234,57,20.0,0,,25,0.0,0,,,,81,1976-03-28 -6202,266,275,31,5.0,0,,24,0.0,0,,,,81,1976-03-28 -6203,266,231,36,35.0,0,,23,0.0,0,,,,81,1976-03-28 -6204,266,252,54,31.0,0,,22,0.0,0,,,,81,1976-03-28 -6205,266,276,57,21.0,0,,21,0.0,0,,,,81,1976-03-28 -6206,266,254,31,6.0,8,,20,0.0,0,,,,22,1976-03-28 -6207,266,228,62,24.0,0,,26,0.0,0,,,,81,1976-03-28 -6208,266,229,36,9.0,20,,18,0.0,0,,,,3,1976-03-28 -6209,266,232,36,34.0,18,,17,0.0,2,,,,3,1976-03-28 -6210,266,230,0,11.0,3,,16,0.0,3,,,,3,1976-03-28 -6211,266,237,36,10.0,6,10.0,10,0.0,77,,,,13,1976-03-28 -6212,266,251,56,16.0,5,,14,0.0,32,,,,86,1976-03-28 -6213,266,221,24,3.0,11,,13,0.0,34,,,,22,1976-03-28 -6214,266,186,65,28.0,9,,12,0.0,69,,,,62,1976-03-28 -6215,266,198,201,7.0,10,,19,0.0,0,,,,3,1976-03-28 -6216,267,231,36,35.0,18,,18,0.0,36,,,,6,1976-05-02 -6217,267,206,31,5.0,9,,19,0.0,34,,,,6,1976-05-02 -6218,267,220,24,4.0,3,,20,0.0,25,,,,3,1976-05-02 -6219,267,229,36,9.0,6,,21,0.0,21,,,,22,1976-05-02 -6220,267,232,36,34.0,17,,22,0.0,16,,,,6,1976-05-02 -6221,267,237,36,10.0,16,,23,0.0,11,,,,7,1976-05-02 -6222,267,207,179,33.0,0,,28,0.0,0,,,,81,1976-05-02 -6223,267,238,61,18.0,0,,25,0.0,0,,,,81,1976-05-02 -6224,267,270,179,32.0,0,,26,0.0,0,,,,81,1976-05-02 -6225,267,228,62,24.0,0,,29,0.0,0,,,,81,1976-05-02 -6226,267,252,54,31.0,0,,30,0.0,0,,,,81,1976-05-02 -6227,267,186,65,28.0,13,,17,0.0,51,,,,5,1976-05-02 -6228,267,223,54,30.0,19,,24,0.0,3,,,,7,1976-05-02 -6229,267,221,24,3.0,14,,16,0.0,53,,,,5,1976-05-02 -6230,267,278,2,25.0,0,,27,0.0,0,,,,81,1976-05-02 -6231,267,199,0,12.0,4,,14,0.0,65,,,,5,1976-05-02 -6232,267,196,56,17.0,15,,15,0.0,61,,,,10,1976-05-02 -6233,267,181,5,1.0,2,2.0,2,6.0,75,6171400.0,,,1,1976-05-02 -6234,267,254,31,6.0,7,3.0,3,4.0,75,6188450.0,,,1,1976-05-02 -6235,267,198,201,7.0,12,4.0,4,3.0,74,,,,11,1976-05-02 -6236,267,277,55,22.0,10,5.0,5,2.0,74,,,,11,1976-05-02 -6237,267,249,201,8.0,11,6.0,6,1.0,74,,,,11,1976-05-02 -6238,267,230,0,11.0,1,1.0,1,9.0,75,6140430.0,,,1,1976-05-02 -6239,267,251,56,16.0,22,8.0,8,0.0,74,,,,11,1976-05-02 -6240,267,177,61,19.0,20,9.0,9,0.0,74,,,,11,1976-05-02 -6241,267,276,57,21.0,23,10.0,10,0.0,73,,,,12,1976-05-02 -6242,267,222,5,2.0,5,11.0,11,0.0,72,,,,13,1976-05-02 -6243,267,171,26,26.0,8,12.0,12,0.0,72,,,,13,1976-05-02 -6244,267,255,68,37.0,24,13.0,13,0.0,72,,,,13,1976-05-02 -6245,267,234,57,20.0,21,7.0,7,0.0,74,,,,11,1976-05-02 -6246,268,232,36,34.0,15,,17,0.0,33,,,,22,1976-05-16 -6247,268,228,62,24.0,24,,18,0.0,31,,,,5,1976-05-16 -6248,268,220,24,4.0,4,,19,0.0,29,,,,5,1976-05-16 -6249,268,206,31,5.0,11,,20,0.0,28,,,,86,1976-05-16 -6250,268,257,179,33.0,19,,21,0.0,26,,,,86,1976-05-16 -6251,268,231,36,35.0,21,,22,0.0,21,,,,5,1976-05-16 -6252,268,254,31,6.0,22,,25,0.0,7,,,,3,1976-05-16 -6253,268,237,36,10.0,10,,24,0.0,16,,,,3,1976-05-16 -6254,268,229,36,9.0,5,,26,0.0,6,,,,86,1976-05-16 -6255,268,223,54,30.0,0,,27,0.0,0,,,,81,1976-05-16 -6256,268,234,57,20.0,0,,28,0.0,0,,,,81,1976-05-16 -6257,268,264,62,25.0,0,,29,0.0,0,,,,81,1976-05-16 -6258,268,198,201,7.0,12,,23,0.0,17,,,,5,1976-05-16 -6259,268,230,0,11.0,3,,16,0.0,35,,,,6,1976-05-16 -6260,268,238,61,18.0,26,,13,0.0,62,,,,10,1976-05-16 -6261,268,249,201,8.0,9,,14,0.0,58,,,,10,1976-05-16 -6262,268,277,55,22.0,8,,15,0.0,51,,,,3,1976-05-16 -6263,268,222,5,2.0,2,2.0,2,6.0,70,6176690.0,,,1,1976-05-16 -6264,268,171,26,26.0,4,3.0,3,4.0,70,6208610.0,,,1,1976-05-16 -6265,268,221,24,3.0,7,4.0,4,3.0,70,6264230.0,,,1,1976-05-16 -6266,268,177,61,19.0,16,5.0,5,2.0,69,,,,11,1976-05-16 -6267,268,199,0,12.0,18,6.0,6,1.0,69,,,,11,1976-05-16 -6268,268,181,5,1.0,1,1.0,1,9.0,70,6173230.0,,,1,1976-05-16 -6269,268,255,68,37.0,20,8.0,8,0.0,69,,,,11,1976-05-16 -6270,268,196,56,17.0,14,9.0,9,0.0,69,,,,11,1976-05-16 -6271,268,251,56,16.0,13,10.0,10,0.0,68,,,,12,1976-05-16 -6272,268,276,57,21.0,25,11.0,11,0.0,68,,,,12,1976-05-16 -6273,268,270,179,32.0,23,12.0,12,0.0,63,,,,17,1976-05-16 -6274,268,186,65,28.0,17,7.0,7,0.0,69,,,,11,1976-05-16 -6275,269,237,36,10.0,3,,16,0.0,26,,,,3,1976-05-30 -6276,269,230,0,11.0,14,,17,0.0,24,,,,5,1976-05-30 -6277,269,229,36,9.0,9,,18,0.0,9,,,,22,1976-05-30 -6278,269,177,61,19.0,19,,19,0.0,1,,,,4,1976-05-30 -6279,269,198,201,7.0,20,,20,0.0,0,,,,3,1976-05-30 -6280,269,255,68,37.0,0,,23,0.0,0,,,,81,1976-05-30 -6281,269,279,61,38.0,0,,22,0.0,0,,,,81,1976-05-30 -6282,269,228,62,24.0,0,,24,0.0,0,,,,81,1976-05-30 -6283,269,231,36,35.0,0,,25,0.0,0,,,,81,1976-05-30 -6284,269,254,31,6.0,16,,15,0.0,39,,,,5,1976-05-30 -6285,269,234,57,20.0,0,,21,0.0,0,,,,81,1976-05-30 -6286,269,222,5,2.0,2,14.0,14,0.0,73,,,,3,1976-05-30 -6287,269,276,57,21.0,18,11.0,11,0.0,76,,,,12,1976-05-30 -6288,269,171,26,26.0,8,12.0,12,0.0,75,,,,3,1976-05-30 -6289,269,181,5,1.0,1,1.0,1,9.0,78,7191470.0,,,1,1976-05-30 -6290,269,221,24,3.0,5,2.0,2,6.0,78,7202600.0,,,1,1976-05-30 -6291,269,220,24,4.0,4,3.0,3,4.0,78,7256310.0,,,1,1976-05-30 -6292,269,199,0,12.0,11,5.0,5,2.0,77,,,,11,1976-05-30 -6293,269,223,54,30.0,7,6.0,6,1.0,77,,,,11,1976-05-30 -6294,269,232,36,34.0,6,4.0,4,3.0,77,,,,11,1976-05-30 -6295,269,196,56,17.0,10,8.0,8,0.0,76,,,,12,1976-05-30 -6296,269,249,201,8.0,13,9.0,9,0.0,76,,,,12,1976-05-30 -6297,269,186,65,28.0,17,10.0,10,0.0,76,,,,12,1976-05-30 -6298,269,277,55,22.0,12,13.0,13,0.0,74,,,,14,1976-05-30 -6299,269,251,56,16.0,15,7.0,7,0.0,77,,,,11,1976-05-30 -6300,270,276,57,21.0,25,,20,0.0,20,,,,5,1976-06-13 -6301,270,232,36,34.0,20,,17,0.0,52,,,,5,1976-06-13 -6302,270,206,31,5.0,2,,18,0.0,45,,,,5,1976-06-13 -6303,270,277,55,22.0,3,,19,0.0,38,,,,3,1976-06-13 -6304,270,255,68,37.0,22,,21,0.0,18,,,,5,1976-06-13 -6305,270,280,179,33.0,0,,27,0.0,0,,,,81,1976-06-13 -6306,270,270,179,32.0,26,,23,0.0,5,,,,3,1976-06-13 -6307,270,254,31,6.0,6,,24,0.0,2,,,,3,1976-06-13 -6308,270,198,201,7.0,16,,25,0.0,2,,,,5,1976-06-13 -6309,270,186,65,28.0,17,,26,0.0,0,,,,3,1976-06-13 -6310,270,228,62,24.0,23,,16,0.0,54,,,,20,1976-06-13 -6311,270,223,54,30.0,21,,22,0.0,10,,,,64,1976-06-13 -6312,270,231,36,35.0,19,14.0,14,0.0,70,,,,5,1976-06-13 -6313,270,238,61,18.0,24,15.0,15,0.0,70,,,,12,1976-06-13 -6314,270,171,26,26.0,7,4.0,4,3.0,72,6469548.0,,,1,1976-06-13 -6315,270,196,56,17.0,14,12.0,12,0.0,71,,,,11,1976-06-13 -6316,270,199,0,12.0,13,11.0,11,0.0,71,,,,11,1976-06-13 -6317,270,229,36,9.0,15,10.0,10,0.0,71,,,,11,1976-06-13 -6318,270,251,56,16.0,12,9.0,9,0.0,71,,,,11,1976-06-13 -6319,270,249,201,8.0,10,8.0,8,0.0,72,6485342.0,,,1,1976-06-13 -6320,270,237,36,10.0,9,7.0,7,0.0,72,6477222.0,,,1,1976-06-13 -6321,270,222,5,2.0,11,6.0,6,1.0,72,6474095.0,,,1,1976-06-13 -6322,270,230,0,11.0,8,5.0,5,2.0,72,6473212.0,,,1,1976-06-13 -6323,270,181,5,1.0,5,3.0,3,4.0,72,6447595.0,,,1,1976-06-13 -6324,270,220,24,4.0,4,2.0,2,6.0,72,6433495.0,,,1,1976-06-13 -6325,270,221,24,3.0,1,1.0,1,9.0,72,6413729.0,,,1,1976-06-13 -6326,270,177,61,19.0,18,13.0,13,0.0,71,,,,11,1976-06-13 -6327,271,229,36,9.0,11,,21,0.0,28,,,,51,1976-07-04 -6328,271,177,61,19.0,18,,20,0.0,44,,,,22,1976-07-04 -6329,271,264,62,25.0,25,17.0,17,0.0,53,,,,11,1976-07-04 -6330,271,257,55,22.0,26,18.0,18,0.0,53,,,,11,1976-07-04 -6331,271,223,54,30.0,21,,22,0.0,21,,,,51,1976-07-04 -6332,271,237,36,10.0,6,19.0,19,0.0,51,,,,69,1976-07-04 -6333,271,279,61,38.0,24,,23,0.0,19,,,,22,1976-07-04 -6334,271,252,54,31.0,0,,29,0.0,0,,,,81,1976-07-04 -6335,271,181,5,1.0,2,,25,0.0,8,,,,5,1976-07-04 -6336,271,254,31,6.0,12,,26,0.0,8,,,,6,1976-07-04 -6337,271,228,62,24.0,29,,27,0.0,4,,,,24,1976-07-04 -6338,271,270,179,32.0,0,,30,0.0,0,,,,81,1976-07-04 -6339,271,281,179,33.0,0,,28,0.0,0,,,,81,1976-07-04 -6340,271,222,5,2.0,4,,24,0.0,17,,,,5,1976-07-04 -6341,271,238,61,18.0,23,16.0,16,0.0,53,,,,11,1976-07-04 -6342,271,186,65,28.0,8,3.0,3,4.0,54,6082150.0,,,1,1976-07-04 -6343,271,171,26,26.0,13,14.0,14,0.0,53,,,,11,1976-07-04 -6344,271,199,0,12.0,14,15.0,15,0.0,53,,,,11,1976-07-04 -6345,271,230,0,11.0,1,1.0,1,9.0,54,6058600.0,,,1,1976-07-04 -6346,271,220,24,4.0,3,2.0,2,6.0,54,6071300.0,,,1,1976-07-04 -6347,271,249,201,8.0,5,4.0,4,3.0,54,6083420.0,,,1,1976-07-04 -6348,271,221,24,3.0,9,6.0,6,1.0,54,6113670.0,,,1,1976-07-04 -6349,271,232,36,34.0,17,7.0,7,0.0,54,6140150.0,,,1,1976-07-04 -6350,271,206,31,5.0,7,5.0,5,2.0,54,6102520.0,,,1,1976-07-04 -6351,271,231,36,35.0,20,9.0,9,0.0,54,6172170.0,,,1,1976-07-04 -6352,271,234,57,20.0,19,10.0,10,0.0,53,,,,11,1976-07-04 -6353,271,198,201,7.0,10,11.0,11,0.0,53,,,,11,1976-07-04 -6354,271,196,56,17.0,15,12.0,12,0.0,53,,,,11,1976-07-04 -6355,271,276,57,21.0,22,13.0,13,0.0,53,,,,11,1976-07-04 -6356,271,251,56,16.0,16,8.0,8,0.0,54,6149270.0,,,1,1976-07-04 -6357,272,277,55,22.0,6,,22,0.0,8,,,,47,1976-07-18 -6358,272,171,26,26.0,13,,18,0.0,31,,,,22,1976-07-18 -6359,272,275,179,32.0,22,,19,0.0,24,,,,6,1976-07-18 -6360,272,229,36,9.0,10,,20,0.0,22,,,,3,1976-07-18 -6361,272,279,61,38.0,26,,21,0.0,16,,,,69,1976-07-18 -6362,272,274,179,33.0,0,,30,0.0,0,,,,81,1976-07-18 -6363,272,282,56,40.0,0,,29,0.0,0,,,,81,1976-07-18 -6364,272,199,0,12.0,12,,24,0.0,1,,,,8,1976-07-18 -6365,272,232,36,34.0,17,,25,0.0,0,,,,3,1976-07-18 -6366,272,264,62,25.0,25,,26,0.0,0,,,,3,1976-07-18 -6367,272,234,57,20.0,0,,27,0.0,0,,,,81,1976-07-18 -6368,272,241,61,13.0,0,,28,0.0,0,,,,81,1976-07-18 -6369,272,222,5,2.0,4,,17,0.0,36,,,,51,1976-07-18 -6370,272,206,31,5.0,3,,23,0.0,4,,,,80,1976-07-18 -6371,272,231,36,35.0,9,,16,0.0,39,,,,5,1976-07-18 -6372,272,249,201,8.0,16,8.0,8,0.0,73,,,,13,1976-07-18 -6373,272,220,24,4.0,5,,14,0.0,47,,,,5,1976-07-18 -6374,272,198,201,7.0,15,,15,0.0,46,,,,51,1976-07-18 -6375,272,181,5,1.0,1,1.0,1,9.0,76,6259660.0,,,1,1976-07-18 -6376,272,221,24,3.0,8,2.0,2,6.0,76,6275840.0,,,1,1976-07-18 -6377,272,186,65,28.0,11,3.0,3,4.0,75,,,,11,1976-07-18 -6378,272,177,61,19.0,19,5.0,5,2.0,75,,,,11,1976-07-18 -6379,272,223,54,30.0,21,6.0,6,1.0,74,,,,12,1976-07-18 -6380,272,251,56,16.0,20,4.0,4,3.0,75,,,,11,1976-07-18 -6381,272,196,56,17.0,24,9.0,9,0.0,70,,,,16,1976-07-18 -6382,272,230,0,11.0,2,,10,0.0,76,,,,2,1976-07-18 -6383,272,254,31,6.0,14,,11,0.0,67,,,,5,1976-07-18 -6384,272,237,36,10.0,7,,12,0.0,60,,,,69,1976-07-18 -6385,272,238,61,18.0,18,,13,0.0,55,,,,6,1976-07-18 -6386,272,228,62,24.0,23,7.0,7,0.0,73,,,,13,1976-07-18 -6387,273,237,36,10.0,11,,20,0.0,0,,,,3,1976-08-01 -6388,273,229,36,9.0,13,,17,0.0,1,,,,3,1976-08-01 -6389,273,220,24,4.0,3,,18,0.0,0,,,,3,1976-08-01 -6390,273,198,201,7.0,10,,19,0.0,0,,,,69,1976-08-01 -6391,273,232,36,34.0,4,,21,0.0,0,,,,8,1976-08-01 -6392,273,279,61,38.0,0,,28,0.0,0,,,,81,1976-08-01 -6393,273,277,55,22.0,17,,23,0.0,0,,,,31,1976-08-01 -6394,273,181,5,1.0,2,,24,0.0,0,,,,3,1976-08-01 -6395,273,238,61,18.0,24,,25,0.0,0,,,,3,1976-08-01 -6396,273,274,179,33.0,0,,27,0.0,0,,,,81,1976-08-01 -6397,273,231,57,20.0,21,,16,0.0,3,,,,23,1976-08-01 -6398,273,171,26,26.0,6,,22,0.0,0,,,,6,1976-08-01 -6399,273,264,62,25.0,25,15.0,15,0.0,13,,,,11,1976-08-01 -6400,273,228,62,24.0,22,,26,0.0,0,,,,3,1976-08-01 -6401,273,223,54,30.0,20,13.0,13,0.0,14,6427900.0,,,1,1976-08-01 -6402,273,221,24,3.0,8,2.0,2,6.0,14,6130400.0,,,1,1976-08-01 -6403,273,199,0,12.0,9,3.0,3,4.0,14,6155100.0,,,1,1976-08-01 -6404,273,249,201,8.0,7,4.0,4,3.0,14,6156900.0,,,1,1976-08-01 -6405,273,254,31,6.0,16,5.0,5,2.0,14,6220000.0,,,1,1976-08-01 -6406,273,242,201,77.0,15,6.0,6,1.0,14,6253000.0,,,1,1976-08-01 -6407,273,230,0,11.0,1,1.0,1,9.0,14,6102700.0,,,1,1976-08-01 -6408,273,251,56,16.0,18,8.0,8,0.0,14,6270900.0,,,1,1976-08-01 -6409,273,186,65,28.0,19,7.0,7,0.0,14,6256600.0,,,1,1976-08-01 -6410,273,206,31,5.0,12,12.0,12,0.0,14,6400800.0,,,1,1976-08-01 -6411,273,283,24,40.0,26,14.0,14,0.0,13,,,,11,1976-08-01 -6412,273,177,61,19.0,14,10.0,10,0.0,14,6330000.0,,,1,1976-08-01 -6413,273,222,5,2.0,5,9.0,9,0.0,14,6328700.0,,,1,1976-08-01 -6414,273,196,56,17.0,23,11.0,11,0.0,14,6394400.0,,,1,1976-08-01 -6415,274,270,179,32.0,25,,14,0.0,44,,,,62,1976-08-15 -6416,274,198,201,7.0,14,,25,0.0,0,,,,8,1976-08-15 -6417,274,221,24,3.0,10,,24,0.0,14,,,,22,1976-08-15 -6418,274,251,56,16.0,6,,23,0.0,14,,,,23,1976-08-15 -6419,274,220,24,4.0,13,,21,0.0,24,,,,22,1976-08-15 -6420,274,232,36,34.0,11,,20,0.0,26,,,,69,1976-08-15 -6421,274,177,61,19.0,15,,19,0.0,30,,,,3,1976-08-15 -6422,274,196,56,17.0,8,,18,0.0,40,,,,48,1976-08-15 -6423,274,249,201,8.0,18,,17,0.0,40,,,,3,1976-08-15 -6424,274,223,54,30.0,17,,16,0.0,43,,,,3,1976-08-15 -6425,274,229,36,9.0,7,,15,0.0,43,,,,3,1976-08-15 -6426,274,231,57,20.0,21,,22,0.0,17,,,,3,1976-08-15 -6427,274,274,179,33.0,24,12.0,12,0.0,50,,,,14,1976-08-15 -6428,274,283,24,39.0,23,11.0,11,0.0,51,,,,13,1976-08-15 -6429,274,245,55,22.0,19,,13,0.0,47,,,,37,1976-08-15 -6430,274,186,65,28.0,2,1.0,1,9.0,54,5407860.0,,,1,1976-08-15 -6431,274,171,26,26.0,5,2.0,2,6.0,54,5418650.0,,,1,1976-08-15 -6432,274,230,0,11.0,1,4.0,4,3.0,54,5420300.0,,,1,1976-08-15 -6433,274,206,31,5.0,9,5.0,5,2.0,54,5429350.0,,,1,1976-08-15 -6434,274,254,31,6.0,4,3.0,3,4.0,54,5419840.0,,,1,1976-08-15 -6435,274,199,0,12.0,12,7.0,7,0.0,54,5467310.0,,,1,1976-08-15 -6436,274,228,62,24.0,20,8.0,8,0.0,53,,,,11,1976-08-15 -6437,274,279,61,38.0,22,9.0,9,0.0,52,,,,12,1976-08-15 -6438,274,238,61,18.0,16,10.0,10,0.0,51,,,,3,1976-08-15 -6439,274,237,36,10.0,3,6.0,6,1.0,54,5442200.0,,,1,1976-08-15 -6440,275,186,65,28.0,4,,19,0.0,47,,,,6,1976-08-29 -6441,275,171,26,26.0,10,,16,0.0,53,,,,44,1976-08-29 -6442,275,237,36,10.0,1,,17,0.0,52,,,,51,1976-08-29 -6443,275,228,62,24.0,24,,18,0.0,49,,,,20,1976-08-29 -6444,275,255,68,27.0,19,,20,0.0,44,,,,3,1976-08-29 -6445,275,231,57,20.0,23,,26,0.0,5,,,,3,1976-08-29 -6446,275,198,201,7.0,12,,22,0.0,11,,,,8,1976-08-29 -6447,275,254,31,6.0,13,,23,0.0,10,,,,3,1976-08-29 -6448,275,232,36,34.0,26,,24,0.0,9,,,,5,1976-08-29 -6449,275,259,61,18.0,18,,25,0.0,9,,,,5,1976-08-29 -6450,275,283,24,40.0,0,,27,0.0,0,,,,81,1976-08-29 -6451,275,223,54,30.0,17,,21,0.0,40,,,,10,1976-08-29 -6452,275,249,201,8.0,9,,15,0.0,53,,,,44,1976-08-29 -6453,275,242,62,25.0,25,12.0,12,0.0,72,,,,13,1976-08-29 -6454,275,234,55,22.0,11,,13,0.0,66,,,,10,1976-08-29 -6455,275,256,65,39.0,21,,14,0.0,63,,,,86,1976-08-29 -6456,275,230,0,11.0,2,1.0,1,9.0,75,6292090.0,,,1,1976-08-29 -6457,275,222,5,2.0,5,2.0,2,6.0,75,6293010.0,,,1,1976-08-29 -6458,275,251,56,16.0,3,4.0,4,3.0,75,6299030.0,,,1,1976-08-29 -6459,275,221,24,3.0,8,5.0,5,2.0,75,6314550.0,,,1,1976-08-29 -6460,275,206,31,5.0,6,3.0,3,4.0,75,6294180.0,,,1,1976-08-29 -6461,275,220,24,4.0,14,7.0,7,0.0,75,6348370.0,,,1,1976-08-29 -6462,275,177,61,19.0,16,8.0,8,0.0,74,,,,11,1976-08-29 -6463,275,199,0,12.0,15,9.0,9,0.0,74,,,,11,1976-08-29 -6464,275,196,56,17.0,20,10.0,10,0.0,74,,,,11,1976-08-29 -6465,275,279,61,38.0,22,11.0,11,0.0,74,,,,11,1976-08-29 -6466,275,229,36,9.0,7,6.0,6,1.0,75,6337120.0,,,1,1976-08-29 -6467,276,232,36,34.0,6,,21,0.0,23,,,,3,1976-09-12 -6468,276,279,61,38.0,22,17.0,17,0.0,49,,,,13,1976-09-12 -6469,276,283,24,37.0,21,18.0,18,0.0,49,,,,13,1976-09-12 -6470,276,196,56,17.0,17,19.0,19,0.0,47,,,,15,1976-09-12 -6471,276,242,201,7.0,11,,20,0.0,41,,,,69,1976-09-12 -6472,276,206,31,5.0,14,,22,0.0,23,,,,3,1976-09-12 -6473,276,231,57,20.0,0,,28,0.0,0,,,,54,1976-09-12 -6474,276,255,68,40.0,13,,24,0.0,8,,,,5,1976-09-12 -6475,276,249,201,8.0,3,,25,0.0,4,,,,5,1976-09-12 -6476,276,264,62,25.0,0,,27,0.0,0,,,,54,1976-09-12 -6477,276,228,62,24.0,19,16.0,16,0.0,49,,,,86,1976-09-12 -6478,276,284,24,39.0,0,,29,0.0,0,,,,54,1976-09-12 -6479,276,230,0,11.0,24,,23,0.0,11,,,,20,1976-09-12 -6480,276,223,54,30.0,20,15.0,15,0.0,50,,,,12,1976-09-12 -6481,276,199,0,12.0,25,,26,0.0,2,,,,80,1976-09-12 -6482,276,254,31,6.0,12,13.0,13,0.0,51,,,,11,1976-09-12 -6483,276,238,61,18.0,24,14.0,14,0.0,50,,,,12,1976-09-12 -6484,276,237,36,10.0,8,1.0,1,9.0,52,5435600.0,,,1,1976-09-12 -6485,276,222,5,2.0,9,2.0,2,6.0,52,5437900.0,,,1,1976-09-12 -6486,276,171,26,26.0,1,3.0,3,4.0,52,5438600.0,,,1,1976-09-12 -6487,276,221,24,3.0,2,5.0,5,2.0,52,5455100.0,,,1,1976-09-12 -6488,276,220,24,4.0,4,6.0,6,1.0,52,5471300.0,,,1,1976-09-12 -6489,276,181,5,1.0,5,4.0,4,3.0,52,5455000.0,,,1,1976-09-12 -6490,276,251,56,16.0,15,8.0,8,0.0,52,5488500.0,,,1,1976-09-12 -6491,276,198,5,35.0,7,9.0,9,0.0,52,5493100.0,,,1,1976-09-12 -6492,276,234,55,22.0,10,10.0,10,0.0,52,5508000.0,,,1,1976-09-12 -6493,276,186,65,28.0,26,11.0,11,0.0,52,5537800.0,,,1,1976-09-12 -6494,276,177,61,19.0,18,12.0,12,0.0,51,,,,11,1976-09-12 -6495,276,229,36,9.0,16,7.0,7,0.0,52,5479500.0,,,1,1976-09-12 -6496,277,264,62,25.0,23,20.0,20,0.0,75,,,,15,1976-10-03 -6497,277,255,201,7.0,19,17.0,17,0.0,78,,,,12,1976-10-03 -6498,277,196,56,17.0,18,18.0,18,0.0,77,,,,13,1976-10-03 -6499,277,279,61,38.0,21,19.0,19,0.0,77,,,,13,1976-10-03 -6500,277,171,26,26.0,9,,21,0.0,43,,,,51,1976-10-03 -6501,277,284,24,39.0,0,,27,0.0,0,,,,81,1976-10-03 -6502,277,232,36,34.0,8,,23,0.0,36,,,,64,1976-10-03 -6503,277,231,57,20.0,24,,24,0.0,11,,,,3,1976-10-03 -6504,277,228,62,24.0,0,,25,0.0,0,,,,3,1976-10-03 -6505,277,277,57,21.0,0,,26,0.0,0,,,,3,1976-10-03 -6506,277,177,61,19.0,20,16.0,16,0.0,78,,,,12,1976-10-03 -6507,277,223,54,30.0,17,,22,0.0,41,,,,43,1976-10-03 -6508,277,238,61,18.0,22,15.0,15,0.0,78,,,,12,1976-10-03 -6509,277,251,56,16.0,13,11.0,11,0.0,79,,,,11,1976-10-03 -6510,277,234,55,22.0,16,13.0,13,0.0,79,,,,11,1976-10-03 -6511,277,230,0,11.0,1,1.0,1,9.0,80,6009626.0,,,1,1976-10-03 -6512,277,229,36,9.0,3,14.0,14,0.0,79,,,,11,1976-10-03 -6513,277,206,31,5.0,5,3.0,3,4.0,80,6019992.0,,,1,1976-10-03 -6514,277,221,24,3.0,7,4.0,4,3.0,80,6029371.0,,,1,1976-10-03 -6515,277,199,0,12.0,11,5.0,5,2.0,80,6051437.0,,,1,1976-10-03 -6516,277,220,24,4.0,4,2.0,2,6.0,80,6015957.0,,,1,1976-10-03 -6517,277,249,201,8.0,10,7.0,7,0.0,80,6056098.0,,,1,1976-10-03 -6518,277,181,5,1.0,6,8.0,8,0.0,80,6082583.0,,,1,1976-10-03 -6519,277,237,36,10.0,2,9.0,9,0.0,79,,,,11,1976-10-03 -6520,277,186,65,28.0,14,10.0,10,0.0,79,,,,11,1976-10-03 -6521,277,254,31,6.0,15,12.0,12,0.0,79,,,,11,1976-10-03 -6522,277,222,5,2.0,12,6.0,6,1.0,80,6055882.0,,,1,1976-10-03 -6523,278,206,31,5.0,11,,21,0.0,23,,,,22,1976-10-10 -6524,278,284,24,39.0,0,,27,0.0,0,,,,81,1976-10-10 -6525,278,220,24,4.0,7,,26,0.0,7,,,,106,1976-10-10 -6526,278,231,57,20.0,25,,25,0.0,9,,,,3,1976-10-10 -6527,278,237,36,10.0,3,,24,0.0,12,,,,22,1976-10-10 -6528,278,254,31,6.0,20,,23,0.0,13,,,,5,1976-10-10 -6529,278,234,55,22.0,19,,22,0.0,14,,,,3,1976-10-10 -6530,278,255,201,7.0,13,,20,0.0,30,,,,22,1976-10-10 -6531,278,249,201,8.0,10,,19,0.0,31,,,,4,1976-10-10 -6532,278,199,0,12.0,17,4.0,4,3.0,59,6223200.0,,,1,1976-10-10 -6533,278,230,0,11.0,1,1.0,1,9.0,59,6160742.0,,,1,1976-10-10 -6534,278,221,24,3.0,2,2.0,2,6.0,59,6168772.0,,,1,1976-10-10 -6535,278,181,5,1.0,5,3.0,3,4.0,59,6223066.0,,,1,1976-10-10 -6536,278,232,36,34.0,6,5.0,5,2.0,59,6228720.0,,,1,1976-10-10 -6537,278,186,65,28.0,8,6.0,6,1.0,59,6228932.0,,,1,1976-10-10 -6538,278,222,5,2.0,14,7.0,7,0.0,58,,,,11,1976-10-10 -6539,278,223,54,30.0,15,9.0,9,0.0,57,,,,12,1976-10-10 -6540,278,196,56,17.0,16,10.0,10,0.0,57,,,,12,1976-10-10 -6541,278,177,61,19.0,18,8.0,8,0.0,58,,,,11,1976-10-10 -6542,278,236,62,25.0,22,12.0,12,0.0,57,,,,12,1976-10-10 -6543,278,228,62,24.0,21,13.0,13,0.0,54,,,,15,1976-10-10 -6544,278,285,57,21.0,23,14.0,14,0.0,54,,,,15,1976-10-10 -6545,278,279,61,38.0,26,,15,0.0,48,,,,62,1976-10-10 -6546,278,251,56,16.0,9,,16,0.0,45,,,,5,1976-10-10 -6547,278,229,36,9.0,12,,17,0.0,34,,,,27,1976-10-10 -6548,278,171,26,26.0,4,,18,0.0,34,,,,27,1976-10-10 -6549,278,238,61,18.0,24,11.0,11,0.0,57,,,,12,1976-10-10 -6550,279,249,201,8.0,6,,22,0.0,7,,,,54,1976-10-24 -6551,279,221,24,3.0,5,,12,0.0,58,,,,25,1976-10-24 -6552,279,245,57,21.0,25,,13,0.0,49,,,,36,1976-10-24 -6553,279,251,56,16.0,14,,14,0.0,46,,,,68,1976-10-24 -6554,279,232,36,34.0,18,,16,0.0,37,,,,10,1976-10-24 -6555,279,229,36,9.0,8,,15,0.0,38,,,,10,1976-10-24 -6556,279,186,65,28.0,4,,18,0.0,33,,,,5,1976-10-24 -6557,279,272,24,52.0,21,,19,0.0,27,,,,27,1976-10-24 -6558,279,231,57,20.0,19,,20,0.0,23,,,,6,1976-10-24 -6559,279,223,54,30.0,23,,21,0.0,9,,,,54,1976-10-24 -6560,279,286,70,51.0,10,11.0,11,0.0,66,,,,17,1976-10-24 -6561,279,199,0,12.0,12,,17,0.0,35,,,,3,1976-10-24 -6562,279,196,56,17.0,15,10.0,10,0.0,69,,,,14,1976-10-24 -6563,279,177,61,19.0,20,4.0,4,3.0,72,,,,11,1976-10-24 -6564,279,228,62,24.0,22,8.0,8,0.0,72,,,,11,1976-10-24 -6565,279,244,72,54.0,0,,26,0.0,0,,,,81,1976-10-24 -6566,279,273,61,18.0,24,9.0,9,0.0,70,,,,13,1976-10-24 -6567,279,255,201,7.0,17,,24,0.0,1,,,,54,1976-10-24 -6568,279,181,5,1.0,3,,23,0.0,2,,,,54,1976-10-24 -6569,279,206,31,5.0,1,1.0,1,9.0,73,6238860.0,,,1,1976-10-24 -6570,279,237,36,10.0,9,,25,0.0,0,,,,5,1976-10-24 -6571,279,230,0,11.0,2,3.0,3,4.0,72,,,,11,1976-10-24 -6572,279,222,5,2.0,7,5.0,5,2.0,72,,,,11,1976-10-24 -6573,279,254,31,6.0,16,6.0,6,1.0,72,,,,11,1976-10-24 -6574,279,171,26,26.0,11,7.0,7,0.0,72,,,,11,1976-10-24 -6575,279,220,24,4.0,13,2.0,2,6.0,72,,,,11,1976-10-24 -6576,280,171,26,26.0,15,,12,0.0,37,,,,62,1977-01-09 -6577,280,254,31,6.0,10,,21,0.0,0,,,,54,1977-01-09 -6578,280,253,56,17.0,21,,20,0.0,2,,,,6,1977-01-09 -6579,280,245,61,18.0,18,,19,0.0,18,,,,3,1977-01-09 -6580,280,181,5,11.0,4,,18,0.0,20,,,,69,1977-01-09 -6581,280,237,24,3.0,14,,16,0.0,28,,,,20,1977-01-09 -6582,280,199,0,2.0,5,,15,0.0,28,,,,20,1977-01-09 -6583,280,230,0,1.0,1,,14,0.0,31,,,,22,1977-01-09 -6584,280,220,24,4.0,3,,13,0.0,32,,,,25,1977-01-09 -6585,280,236,36,9.0,20,,11,0.0,39,,,,7,1977-01-09 -6586,280,252,54,29.0,19,,17,0.0,22,,,,5,1977-01-09 -6587,280,251,56,16.0,9,,9,0.0,45,,,,62,1977-01-09 -6588,280,250,36,10.0,17,,8,0.0,45,,,,10,1977-01-09 -6589,280,229,61,19.0,13,7.0,7,0.0,48,,,,60,1977-01-09 -6590,280,222,55,22.0,12,6.0,6,1.0,51,,,,12,1977-01-09 -6591,280,206,31,5.0,8,5.0,5,2.0,51,,,,67,1977-01-09 -6592,280,223,54,28.0,16,4.0,4,3.0,53,6066670.0,,,1,1977-01-09 -6593,280,198,5,12.0,7,3.0,3,4.0,53,6057210.0,,,1,1977-01-09 -6594,280,249,33,8.0,6,2.0,2,6.0,53,6054430.0,,,1,1977-01-09 -6595,280,221,57,20.0,11,1.0,1,9.0,53,6011190.0,,,1,1977-01-09 -6596,280,186,33,7.0,2,,10,0.0,41,,,,22,1977-01-09 -6597,281,220,24,4.0,6,,13,0.0,23,,,,3,1977-01-23 -6598,281,206,31,5.0,3,,14,0.0,19,,,,80,1977-01-23 -6599,281,222,55,22.0,9,,18,0.0,12,,,,3,1977-01-23 -6600,281,237,24,3.0,8,,17,0.0,12,,,,3,1977-01-23 -6601,281,171,26,26.0,14,,12,0.0,26,,,,3,1977-01-23 -6602,281,221,57,20.0,15,,20,0.0,11,,,,5,1977-01-23 -6603,281,250,36,10.0,17,,21,0.0,1,,,,7,1977-01-23 -6604,281,255,64,14.0,22,,22,0.0,1,,,,25,1977-01-23 -6605,281,236,36,9.0,21,,15,0.0,16,,,,5,1977-01-23 -6606,281,229,61,19.0,11,,19,0.0,11,,,,3,1977-01-23 -6607,281,186,33,7.0,7,,11,0.0,30,,,,3,1977-01-23 -6608,281,199,0,2.0,4,,16,0.0,12,,,,3,1977-01-23 -6609,281,251,56,16.0,5,,9,0.0,33,,,,5,1977-01-23 -6610,281,198,5,12.0,2,1.0,1,9.0,40,6307720.0,,,1,1977-01-23 -6611,281,230,0,1.0,1,2.0,2,6.0,40,6318430.0,,,1,1977-01-23 -6612,281,181,5,11.0,13,3.0,3,4.0,40,6415230.0,,,1,1977-01-23 -6613,281,223,54,28.0,16,4.0,4,3.0,39,,,,11,1977-01-23 -6614,281,245,61,18.0,20,,10,0.0,32,,,,22,1977-01-23 -6615,281,253,56,17.0,18,6.0,6,1.0,39,,,,11,1977-01-23 -6616,281,252,54,29.0,19,7.0,7,0.0,38,,,,12,1977-01-23 -6617,281,249,33,8.0,12,,8,0.0,33,,,,3,1977-01-23 -6618,281,254,31,6.0,10,5.0,5,2.0,39,,,,11,1977-01-23 -6619,282,238,36,30.0,23,14.0,14,0.0,76,,,,12,1977-03-05 -6620,282,253,56,17.0,20,,22,0.0,21,,,,95,1977-03-05 -6621,282,251,56,16.0,15,,21,0.0,22,,,,3,1977-03-05 -6622,282,171,26,26.0,12,,20,0.0,22,,,,3,1977-03-05 -6623,282,256,36,33.0,21,,19,0.0,33,,,,6,1977-03-05 -6624,282,206,31,5.0,6,,18,0.0,43,,,,3,1977-03-05 -6625,282,232,36,10.0,18,,17,0.0,55,,,,5,1977-03-05 -6626,282,236,36,9.0,17,,16,0.0,66,,,,5,1977-03-05 -6627,282,255,64,14.0,22,15.0,15,0.0,73,,,,15,1977-03-05 -6628,282,237,24,3.0,7,,23,0.0,5,,,,69,1977-03-05 -6629,282,249,33,8.0,2,13.0,13,0.0,76,,,,12,1977-03-05 -6630,282,245,61,18.0,19,11.0,11,0.0,77,,,,11,1977-03-05 -6631,282,223,54,28.0,9,10.0,10,0.0,78,6213300.0,,,1,1977-03-05 -6632,282,222,55,22.0,16,9.0,9,0.0,78,6187800.0,,,1,1977-03-05 -6633,282,198,5,12.0,8,8.0,8,0.0,78,6168300.0,,,1,1977-03-05 -6634,282,229,61,19.0,14,7.0,7,0.0,78,6165200.0,,,1,1977-03-05 -6635,282,186,33,7.0,11,6.0,6,1.0,78,6161800.0,,,1,1977-03-05 -6636,282,199,0,2.0,12,5.0,5,2.0,78,6161500.0,,,1,1977-03-05 -6637,282,230,0,1.0,1,4.0,4,3.0,78,6151100.0,,,1,1977-03-05 -6638,282,220,24,4.0,4,3.0,3,4.0,78,6147300.0,,,1,1977-03-05 -6639,282,221,57,20.0,5,2.0,2,6.0,78,6146800.0,,,1,1977-03-05 -6640,282,181,5,11.0,3,1.0,1,9.0,78,6141600.0,,,1,1977-03-05 -6641,282,254,31,6.0,10,12.0,12,0.0,77,,,,11,1977-03-05 -6642,283,171,26,26.0,5,9.0,9,0.0,78,,,,10,1977-04-03 -6643,283,254,31,6.0,16,8.0,8,0.0,79,,,,11,1977-04-03 -6644,283,230,0,1.0,8,7.0,7,0.0,79,,,,11,1977-04-03 -6645,283,196,65,34.0,9,6.0,6,1.0,79,,,,11,1977-04-03 -6646,283,206,31,5.0,2,1.0,1,9.0,80,6695470.0,,,1,1977-04-03 -6647,283,204,36,10.0,18,10.0,10,0.0,77,,,,13,1977-04-03 -6648,283,220,24,4.0,12,4.0,4,3.0,80,6769957.0,,,1,1977-04-03 -6649,283,221,57,20.0,3,3.0,3,4.0,80,6700327.0,,,1,1977-04-03 -6650,283,181,5,11.0,1,2.0,2,6.0,80,6696243.0,,,1,1977-04-03 -6651,283,223,54,28.0,7,5.0,5,2.0,80,6776378.0,,,1,1977-04-03 -6652,283,245,61,18.0,19,11.0,11,0.0,77,,,,13,1977-04-03 -6653,283,198,5,12.0,4,,20,0.0,5,,,,3,1977-04-03 -6654,283,222,55,22.0,13,,13,0.0,57,,,,6,1977-04-03 -6655,283,232,33,8.0,17,,14,0.0,53,,,,23,1977-04-03 -6656,283,177,56,17.0,14,,15,0.0,40,,,,6,1977-04-03 -6657,283,199,0,2.0,15,,16,0.0,39,,,,64,1977-04-03 -6658,283,186,33,7.0,6,,17,0.0,33,,,,2,1977-04-03 -6659,283,253,56,16.0,20,,18,0.0,27,,,,6,1977-04-03 -6660,283,236,36,9.0,22,,19,0.0,15,,,,6,1977-04-03 -6661,283,238,36,30.0,21,,21,0.0,4,,,,3,1977-04-03 -6662,283,229,61,19.0,11,,22,0.0,0,,,,3,1977-04-03 -6663,283,237,24,3.0,10,,12,0.0,62,,,,69,1977-04-03 -6664,284,253,56,16.0,24,,19,0.0,25,,,,5,1977-05-08 -6665,284,231,36,37.0,21,,20,0.0,16,,,,22,1977-05-08 -6666,284,220,24,4.0,10,,21,0.0,12,,,,5,1977-05-08 -6667,284,230,0,1.0,7,,22,0.0,10,,,,5,1977-05-08 -6668,284,222,55,22.0,8,,23,0.0,9,,,,3,1977-05-08 -6669,284,256,36,33.0,0,,28,0.0,0,,,,81,1977-05-08 -6670,284,181,5,11.0,3,,25,0.0,0,,,,73,1977-05-08 -6671,284,196,65,34.0,0,,26,0.0,0,,,,81,1977-05-08 -6672,284,236,36,9.0,0,,27,0.0,0,,,,81,1977-05-08 -6673,284,228,62,25.0,10,,18,0.0,29,,,,21,1977-05-08 -6674,284,204,36,38.0,0,,29,0.0,0,,,,81,1977-05-08 -6675,284,259,64,35.0,0,,31,0.0,0,,,,81,1977-05-08 -6676,284,229,61,19.0,11,,24,0.0,9,,,,3,1977-05-08 -6677,284,210,62,24.0,16,,17,0.0,32,,,,3,1977-05-08 -6678,284,257,36,27.0,22,12.0,12,0.0,71,,,,14,1977-05-08 -6679,284,186,33,7.0,6,,15,0.0,64,,,,69,1977-05-08 -6680,284,223,54,28.0,19,14.0,14,0.0,70,,,,15,1977-05-08 -6681,284,207,0,36.0,23,13.0,13,0.0,70,,,,15,1977-05-08 -6682,284,250,36,10.0,17,11.0,11,0.0,72,,,,13,1977-05-08 -6683,284,238,36,30.0,28,10.0,10,0.0,72,,,,13,1977-05-08 -6684,284,245,61,18.0,20,9.0,9,0.0,73,,,,12,1977-05-08 -6685,284,237,24,3.0,15,8.0,8,0.0,74,,,,11,1977-05-08 -6686,284,171,26,26.0,2,7.0,7,0.0,74,,,,11,1977-05-08 -6687,284,232,33,8.0,13,6.0,6,1.0,74,,,,11,1977-05-08 -6688,284,254,31,6.0,12,5.0,5,2.0,75,6238050.0,,,1,1977-05-08 -6689,284,199,0,2.0,9,4.0,4,3.0,75,6197090.0,,,1,1977-05-08 -6690,284,221,57,20.0,5,3.0,3,4.0,75,6196730.0,,,1,1977-05-08 -6691,284,198,5,12.0,4,2.0,2,6.0,75,6188070.0,,,1,1977-05-08 -6692,284,206,31,5.0,1,1.0,1,9.0,75,6172220.0,,,1,1977-05-08 -6693,284,177,56,17.0,14,,16,0.0,56,,,,3,1977-05-08 -6694,284,258,66,31.0,0,,30,0.0,0,,,,81,1977-05-08 -6695,285,220,24,4.0,8,,15,0.0,46,,,,6,1977-05-22 -6696,285,221,57,20.0,2,1.0,1,9.0,76,7072770.0,,,1,1977-05-22 -6697,285,250,36,10.0,0,,26,0.0,0,,,,81,1977-05-22 -6698,285,236,36,9.0,0,,25,0.0,0,,,,81,1977-05-22 -6699,285,222,55,22.0,0,,24,0.0,0,,,,81,1977-05-22 -6700,285,228,62,25.0,0,,23,0.0,0,,,,81,1977-05-22 -6701,285,256,36,33.0,0,,22,0.0,0,,,,81,1977-05-22 -6702,285,237,24,3.0,4,,20,0.0,10,,,,23,1977-05-22 -6703,285,232,33,8.0,5,,19,0.0,19,,,,10,1977-05-22 -6704,285,230,0,1.0,7,,18,0.0,25,,,,5,1977-05-22 -6705,285,223,54,28.0,18,,17,0.0,37,,,,5,1977-05-22 -6706,285,245,61,18.0,19,,16,0.0,41,,,,69,1977-05-22 -6707,285,186,33,7.0,1,,14,0.0,48,,,,6,1977-05-22 -6708,285,231,36,37.0,0,,21,0.0,0,,,,81,1977-05-22 -6709,285,210,62,24.0,20,12.0,12,0.0,73,,,,13,1977-05-22 -6710,285,254,31,6.0,13,,13,0.0,51,,,,6,1977-05-22 -6711,285,181,5,11.0,6,2.0,2,6.0,76,7073659.0,,,1,1977-05-22 -6712,285,198,5,12.0,3,3.0,3,4.0,76,7105570.0,,,1,1977-05-22 -6713,285,199,0,2.0,9,4.0,4,3.0,76,7107370.0,,,1,1977-05-22 -6714,285,177,56,17.0,11,6.0,6,1.0,76,7109380.0,,,1,1977-05-22 -6715,285,206,31,5.0,10,5.0,5,2.0,76,7108320.0,,,1,1977-05-22 -6716,285,171,26,26.0,16,7.0,7,0.0,76,7137210.0,,,1,1977-05-22 -6717,285,229,61,19.0,14,8.0,8,0.0,76,7141410.0,,,1,1977-05-22 -6718,285,118,56,16.0,15,9.0,9,0.0,75,,,,11,1977-05-22 -6719,285,234,55,22.0,17,10.0,10,0.0,75,,,,11,1977-05-22 -6720,285,196,65,34.0,12,11.0,11,0.0,74,,,,12,1977-05-22 -6721,286,250,36,10.0,21,,23,0.0,8,,,,3,1977-06-05 -6722,286,198,5,12.0,7,,20,0.0,14,,,,3,1977-06-05 -6723,286,210,62,24.0,19,,21,0.0,14,,,,3,1977-06-05 -6724,286,118,56,16.0,15,,22,0.0,12,,,,3,1977-06-05 -6725,286,222,55,22.0,13,,19,0.0,29,,,,5,1977-06-05 -6726,286,223,54,28.0,16,,24,0.0,2,,,,10,1977-06-05 -6727,286,260,36,38.0,0,,30,0.0,0,,,,81,1977-06-05 -6728,286,186,33,7.0,2,,26,0.0,0,,,,3,1977-06-05 -6729,286,207,0,36.0,0,,27,0.0,0,,,,81,1977-06-05 -6730,286,236,36,9.0,0,,28,0.0,0,,,,81,1977-06-05 -6731,286,259,64,35.0,0,,29,0.0,0,,,,81,1977-06-05 -6732,286,211,62,39.0,0,,31,0.0,0,,,,81,1977-06-05 -6733,286,171,26,26.0,10,,18,0.0,32,,,,5,1977-06-05 -6734,286,206,31,5.0,1,,25,0.0,0,,,,3,1977-06-05 -6735,286,199,0,2.0,6,,17,0.0,39,,,,3,1977-06-05 -6736,286,230,0,1.0,9,7.0,7,0.0,69,,,,11,1977-06-05 -6737,286,256,36,33.0,27,,15,0.0,63,,,,62,1977-06-05 -6738,286,254,31,6.0,3,1.0,1,9.0,70,6905710.0,,,1,1977-06-05 -6739,286,181,5,11.0,11,2.0,2,6.0,70,6919900.0,,,1,1977-06-05 -6740,286,237,24,3.0,8,3.0,3,4.0,70,6925660.0,,,1,1977-06-05 -6741,286,229,61,19.0,12,4.0,4,3.0,70,6930690.0,,,1,1977-06-05 -6742,286,221,57,20.0,4,,16,0.0,62,,,,5,1977-06-05 -6743,286,232,33,8.0,18,6.0,6,1.0,69,,,,11,1977-06-05 -6744,286,177,56,17.0,17,5.0,5,2.0,70,6981180.0,,,1,1977-06-05 -6745,286,228,62,25.0,25,9.0,9,0.0,69,,,,11,1977-06-05 -6746,286,257,36,27.0,24,10.0,10,0.0,68,,,,12,1977-06-05 -6747,286,196,65,34.0,26,11.0,11,0.0,68,,,,12,1977-06-05 -6748,286,255,61,18.0,23,12.0,12,0.0,67,,,,13,1977-06-05 -6749,286,258,66,31.0,20,13.0,13,0.0,67,,,,13,1977-06-05 -6750,286,231,36,37.0,14,14.0,14,0.0,65,,,,15,1977-06-05 -6751,286,220,24,4.0,5,8.0,8,0.0,69,,,,11,1977-06-05 -6752,287,237,24,3.0,10,,24,0.0,7,,,,80,1977-06-19 -6753,287,262,36,32.0,0,,31,0.0,0,,,,81,1977-06-19 -6754,287,259,64,35.0,0,,30,0.0,0,,,,81,1977-06-19 -6755,287,211,62,39.0,0,,29,0.0,0,,,,81,1977-06-19 -6756,287,256,36,33.0,0,,28,0.0,0,,,,81,1977-06-19 -6757,287,255,61,18.0,0,,27,0.0,0,,,,81,1977-06-19 -6758,287,207,0,36.0,0,,26,0.0,0,,,,81,1977-06-19 -6759,287,221,57,20.0,4,,23,0.0,29,,,,3,1977-06-19 -6760,287,199,0,2.0,9,2.0,2,6.0,72,6424849.0,,,1,1977-06-19 -6761,287,220,24,4.0,6,4.0,4,3.0,72,6432708.0,,,1,1977-06-19 -6762,287,198,5,12.0,12,3.0,3,4.0,72,6430769.0,,,1,1977-06-19 -6763,287,171,26,26.0,8,1.0,1,9.0,72,6416400.0,,,1,1977-06-19 -6764,287,236,36,9.0,0,,25,0.0,0,,,,81,1977-06-19 -6765,287,186,33,7.0,2,5.0,5,2.0,72,6435135.0,,,1,1977-06-19 -6766,287,206,31,5.0,1,6.0,6,1.0,72,6441677.0,,,1,1977-06-19 -6767,287,196,65,34.0,17,8.0,8,0.0,72,6480967.0,,,1,1977-06-19 -6768,287,261,56,16.0,16,9.0,9,0.0,72,6498879.0,,,1,1977-06-19 -6769,287,232,33,8.0,5,10.0,10,0.0,71,,,,11,1977-06-19 -6770,287,238,0,30.0,22,11.0,11,0.0,71,,,,11,1977-06-19 -6771,287,222,55,22.0,14,7.0,7,0.0,72,6447666.0,,,1,1977-06-19 -6772,287,210,62,24.0,24,13.0,13,0.0,71,,,,11,1977-06-19 -6773,287,230,0,1.0,3,12.0,12,0.0,71,,,,11,1977-06-19 -6774,287,229,61,19.0,13,,21,0.0,52,,,,32,1977-06-19 -6775,287,250,36,10.0,21,,20,0.0,61,,,,7,1977-06-19 -6776,287,254,31,6.0,7,19.0,19,0.0,64,,,,67,1977-06-19 -6777,287,223,54,28.0,18,18.0,18,0.0,66,,,,16,1977-06-19 -6778,287,181,5,11.0,15,,22,0.0,47,,,,64,1977-06-19 -6779,287,228,62,25.0,23,16.0,16,0.0,68,,,,14,1977-06-19 -6780,287,257,36,27.0,20,15.0,15,0.0,69,,,,13,1977-06-19 -6781,287,258,66,31.0,19,14.0,14,0.0,70,,,,12,1977-06-19 -6782,287,177,56,17.0,11,17.0,17,0.0,67,,,,15,1977-06-19 -6783,288,250,36,10.0,20,,14,0.0,69,,,,62,1977-07-03 -6784,288,236,36,9.0,0,,23,0.0,0,,,,81,1977-07-03 -6785,288,196,65,34.0,19,,22,0.0,4,,,,3,1977-07-03 -6786,288,258,66,31.0,21,,21,0.0,5,,,,3,1977-07-03 -6787,288,118,56,16.0,15,,20,0.0,6,,,,5,1977-07-03 -6788,288,220,24,4.0,12,,19,0.0,21,,,,3,1977-07-03 -6789,288,231,36,37.0,18,,18,0.0,27,,,,6,1977-07-03 -6790,288,177,56,17.0,10,,17,0.0,60,,,,7,1977-07-03 -6791,288,232,33,8.0,13,,16,0.0,64,,,,3,1977-07-03 -6792,288,221,57,20.0,8,,15,0.0,66,,,,3,1977-07-03 -6793,288,229,61,19.0,11,13.0,13,0.0,77,,,,13,1977-07-03 -6794,288,186,33,7.0,4,2.0,2,6.0,80,5981680.0,,,1,1977-07-03 -6795,288,223,54,28.0,22,11.0,11,0.0,77,,,,13,1977-07-03 -6796,288,210,62,24.0,14,10.0,10,0.0,78,,,,12,1977-07-03 -6797,288,199,0,2.0,7,9.0,9,0.0,78,,,,12,1977-07-03 -6798,288,171,26,26.0,5,8.0,8,0.0,78,,,,12,1977-07-03 -6799,288,222,55,22.0,16,7.0,7,0.0,79,,,,11,1977-07-03 -6800,288,198,5,12.0,6,6.0,6,1.0,79,,,,11,1977-07-03 -6801,288,181,5,11.0,9,5.0,5,2.0,80,6054280.0,,,1,1977-07-03 -6802,288,254,31,6.0,3,4.0,4,3.0,80,6051210.0,,,1,1977-07-03 -6803,288,230,0,1.0,2,3.0,3,4.0,80,6014000.0,,,1,1977-07-03 -6804,288,257,36,27.0,0,,24,0.0,0,,,,81,1977-07-03 -6805,288,237,24,3.0,17,12.0,12,0.0,77,,,,13,1977-07-03 -6806,288,238,0,30.0,0,,25,0.0,0,,,,81,1977-07-03 -6807,288,259,64,35.0,0,,30,0.0,0,,,,81,1977-07-03 -6808,288,255,61,18.0,0,,27,0.0,0,,,,81,1977-07-03 -6809,288,211,62,39.0,0,,28,0.0,0,,,,81,1977-07-03 -6810,288,174,61,18.0,0,,29,0.0,0,,,,81,1977-07-03 -6811,288,206,31,5.0,1,1.0,1,9.0,80,5980130.0,,,1,1977-07-03 -6812,288,228,62,25.0,0,,26,0.0,0,,,,81,1977-07-03 -6813,289,118,56,16.0,25,,20,0.0,20,,,,32,1977-07-16 -6814,289,220,24,4.0,18,,21,0.0,16,,,,23,1977-07-16 -6815,289,218,3,15.0,21,,22,0.0,16,,,,101,1977-07-16 -6816,289,236,36,9.0,0,,27,0.0,0,,,,81,1977-07-16 -6817,289,250,36,10.0,24,,23,0.0,6,,,,3,1977-07-16 -6818,289,237,24,3.0,16,,24,0.0,3,,,,5,1977-07-16 -6819,289,222,55,22.0,0,,28,0.0,0,,,,81,1977-07-16 -6820,289,207,0,36.0,0,,30,0.0,0,,,,81,1977-07-16 -6821,289,258,66,31.0,0,,31,0.0,0,,,,97,1977-07-16 -6822,289,263,36,33.0,0,,32,0.0,0,,,,97,1977-07-16 -6823,289,264,64,35.0,0,,33,0.0,0,,,,97,1977-07-16 -6824,289,244,61,44.0,0,,34,0.0,0,,,,97,1977-07-16 -6825,289,265,67,45.0,0,,35,0.0,0,,,,97,1977-07-16 -6826,289,262,36,32.0,0,,36,0.0,0,,,,97,1977-07-16 -6827,289,204,36,38.0,0,,29,0.0,0,,,,81,1977-07-16 -6828,289,231,36,37.0,17,,19,0.0,28,,,,7,1977-07-16 -6829,289,186,33,7.0,2,,16,0.0,60,,,,69,1977-07-16 -6830,289,221,57,20.0,4,,17,0.0,59,,,,5,1977-07-16 -6831,289,230,0,1.0,1,1.0,1,9.0,68,5506060.0,,,1,1977-07-16 -6832,289,181,5,11.0,3,2.0,2,6.0,68,5524370.0,,,1,1977-07-16 -6833,289,254,31,6.0,5,3.0,3,4.0,68,5525630.0,,,1,1977-07-16 -6834,289,199,0,2.0,11,4.0,4,3.0,68,5553820.0,,,1,1977-07-16 -6835,289,232,33,8.0,7,5.0,5,2.0,68,5577790.0,,,1,1977-07-16 -6836,289,171,26,26.0,15,6.0,6,1.0,67,,,,11,1977-07-16 -6837,289,177,56,17.0,12,7.0,7,0.0,67,,,,11,1977-07-16 -6838,289,229,61,19.0,8,8.0,8,0.0,67,,,,11,1977-07-16 -6839,289,196,65,34.0,20,9.0,9,0.0,67,,,,11,1977-07-16 -6840,289,257,36,27.0,26,10.0,10,0.0,66,,,,12,1977-07-16 -6841,289,202,0,40.0,9,11.0,11,0.0,66,,,,12,1977-07-16 -6842,289,266,61,18.0,23,12.0,12,0.0,66,,,,12,1977-07-16 -6843,289,238,0,30.0,19,13.0,13,0.0,64,,,,14,1977-07-16 -6844,289,206,31,5.0,6,14.0,14,0.0,62,,,,5,1977-07-16 -6845,289,198,5,12.0,14,15.0,15,0.0,62,,,,16,1977-07-16 -6846,289,223,54,28.0,22,,18,0.0,42,,,,37,1977-07-16 -6847,289,174,55,23.0,10,,25,0.0,3,,,,10,1977-07-16 -6848,289,210,62,24.0,13,,26,0.0,0,,,,3,1977-07-16 -6849,290,171,26,26.0,6,,17,0.0,21,,,,5,1977-07-31 -6850,290,268,64,40.0,0,,29,0.0,0,,,,81,1977-07-31 -6851,290,231,36,37.0,0,,28,0.0,0,,,,81,1977-07-31 -6852,290,223,54,28.0,0,,27,0.0,0,,,,81,1977-07-31 -6853,290,207,0,36.0,0,,26,0.0,0,,,,81,1977-07-31 -6854,290,257,36,27.0,0,,25,0.0,0,,,,81,1977-07-31 -6855,290,267,65,35.0,25,,24,0.0,9,,,,81,1977-07-31 -6856,290,177,56,17.0,17,,23,0.0,0,,,,3,1977-07-31 -6857,290,196,65,34.0,12,,22,0.0,5,,,,7,1977-07-31 -6858,290,186,33,7.0,2,,21,0.0,8,,,,5,1977-07-31 -6859,290,250,36,10.0,19,,20,0.0,9,,,,8,1977-07-31 -6860,290,238,0,30.0,21,,19,0.0,14,,,,3,1977-07-31 -6861,290,211,62,25.0,24,,18,0.0,20,,,,5,1977-07-31 -6862,290,181,5,11.0,3,1.0,1,9.0,47,5509300.0,,,1,1977-07-31 -6863,290,220,24,4.0,15,,16,0.0,22,,,,5,1977-07-31 -6864,290,232,33,8.0,5,3.0,3,4.0,47,5530200.0,,,1,1977-07-31 -6865,290,221,57,20.0,1,2.0,2,6.0,47,5523630.0,,,1,1977-07-31 -6866,290,199,0,2.0,13,,15,0.0,26,,,,6,1977-07-31 -6867,290,254,31,6.0,9,,14,0.0,31,,,,5,1977-07-31 -6868,290,230,0,1.0,4,,13,0.0,32,,,,48,1977-07-31 -6869,290,210,62,24.0,23,,11,0.0,40,,,,3,1977-07-31 -6870,290,118,56,16.0,16,10.0,10,0.0,42,,,,36,1977-07-31 -6871,290,206,31,5.0,7,,12,0.0,34,,,,5,1977-07-31 -6872,290,236,36,9.0,20,8.0,8,0.0,46,,,,11,1977-07-31 -6873,290,266,61,18.0,19,7.0,7,0.0,46,,,,11,1977-07-31 -6874,290,174,55,23.0,11,6.0,6,1.0,47,5599110.0,,,1,1977-07-31 -6875,290,229,61,19.0,10,5.0,5,2.0,47,5596670.0,,,1,1977-07-31 -6876,290,198,5,12.0,8,4.0,4,3.0,47,5569570.0,,,1,1977-07-31 -6877,290,237,24,3.0,14,9.0,9,0.0,42,,,,5,1977-07-31 -6878,291,231,56,16.0,21,,22,0.0,29,,,,6,1977-08-14 -6879,291,221,57,20.0,8,,18,0.0,45,,,,20,1977-08-14 -6880,291,230,0,1.0,2,,19,0.0,43,,,,5,1977-08-14 -6881,291,174,55,23.0,7,,20,0.0,41,,,,5,1977-08-14 -6882,291,171,26,26.0,6,,23,0.0,21,,,,44,1977-08-14 -6883,291,211,62,25.0,0,,29,0.0,0,,,,81,1977-08-14 -6884,291,250,36,10.0,24,,25,0.0,2,,,,3,1977-08-14 -6885,291,222,55,22.0,11,,26,0.0,0,,,,3,1977-08-14 -6886,291,204,36,38.0,0,,27,0.0,0,,,,81,1977-08-14 -6887,291,269,62,39.0,0,,28,0.0,0,,,,81,1977-08-14 -6888,291,207,0,36.0,26,17.0,17,0.0,50,,,,3,1977-08-14 -6889,291,206,31,5.0,3,,24,0.0,11,,,,5,1977-08-14 -6890,291,266,61,18.0,25,16.0,16,0.0,52,,,,12,1977-08-14 -6891,291,257,36,27.0,22,9.0,9,0.0,53,,,,11,1977-08-14 -6892,291,196,65,34.0,18,14.0,14,0.0,52,,,,12,1977-08-14 -6893,291,220,24,4.0,10,13.0,13,0.0,53,,,,11,1977-08-14 -6894,291,245,65,33.0,19,12.0,12,0.0,53,,,,11,1977-08-14 -6895,291,223,54,28.0,23,11.0,11,0.0,53,,,,11,1977-08-14 -6896,291,238,0,30.0,17,10.0,10,0.0,53,,,,11,1977-08-14 -6897,291,186,33,7.0,12,8.0,8,0.0,53,,,,11,1977-08-14 -6898,291,210,62,24.0,20,7.0,7,0.0,53,,,,11,1977-08-14 -6899,291,199,0,2.0,9,6.0,6,1.0,53,,,,11,1977-08-14 -6900,291,237,24,3.0,15,5.0,5,2.0,54,5908580.0,,,1,1977-08-14 -6901,291,198,5,12.0,5,4.0,4,3.0,54,5871240.0,,,1,1977-08-14 -6902,291,232,33,8.0,4,3.0,3,4.0,54,5870990.0,,,1,1977-08-14 -6903,291,181,5,11.0,1,2.0,2,6.0,54,5856620.0,,,1,1977-08-14 -6904,291,236,36,9.0,0,,30,0.0,0,,,,81,1977-08-14 -6905,291,229,61,19.0,13,15.0,15,0.0,52,,,,12,1977-08-14 -6906,291,177,56,17.0,14,1.0,1,9.0,54,5836490.0,,,1,1977-08-14 -6907,291,254,31,6.0,16,,21,0.0,38,,,,5,1977-08-14 -6908,292,254,31,6.0,5,,16,0.0,34,,,,3,1977-08-28 -6909,292,210,62,24.0,26,,22,0.0,8,,,,3,1977-08-28 -6910,292,230,0,1.0,3,,23,0.0,5,,,,3,1977-08-28 -6911,292,196,65,34.0,21,,24,0.0,4,,,,80,1977-08-28 -6912,292,186,33,7.0,8,,25,0.0,2,,,,44,1977-08-28 -6913,292,199,0,2.0,14,,26,0.0,0,,,,3,1977-08-28 -6914,292,257,36,27.0,0,,27,0.0,0,,,,81,1977-08-28 -6915,292,206,31,5.0,1,,21,0.0,14,,,,5,1977-08-28 -6916,292,231,36,37.0,0,,28,0.0,0,,,,81,1977-08-28 -6917,292,269,62,39.0,0,,30,0.0,0,,,,81,1977-08-28 -6918,292,256,36,33.0,0,,31,0.0,0,,,,81,1977-08-28 -6919,292,211,62,25.0,0,,32,0.0,0,,,,81,1977-08-28 -6920,292,268,64,29.0,0,,33,0.0,0,,,,81,1977-08-28 -6921,292,246,36,32.0,0,,34,0.0,0,,,,81,1977-08-28 -6922,292,177,56,17.0,13,,17,0.0,32,,,,5,1977-08-28 -6923,292,266,61,18.0,0,,29,0.0,0,,,,81,1977-08-28 -6924,292,222,55,22.0,9,,20,0.0,17,,,,37,1977-08-28 -6925,292,221,57,20.0,15,3.0,3,4.0,74,,,,11,1977-08-28 -6926,292,181,5,11.0,4,1.0,1,9.0,75,6105930.0,,,1,1977-08-28 -6927,292,237,24,3.0,7,,19,0.0,18,,,,80,1977-08-28 -6928,292,204,68,38.0,23,,14,0.0,52,,,,2,1977-08-28 -6929,292,118,56,16.0,16,13.0,13,0.0,67,,,,5,1977-08-28 -6930,292,229,61,19.0,22,12.0,12,0.0,67,,,,3,1977-08-28 -6931,292,236,36,9.0,24,11.0,11,0.0,72,,,,13,1977-08-28 -6932,292,218,3,15.0,10,,15,0.0,39,,,,22,1977-08-28 -6933,292,238,0,30.0,20,9.0,9,0.0,73,,,,12,1977-08-28 -6934,292,250,36,10.0,25,10.0,10,0.0,73,,,,12,1977-08-28 -6935,292,232,33,8.0,19,7.0,7,0.0,73,,,,12,1977-08-28 -6936,292,198,5,12.0,6,6.0,6,1.0,73,,,,12,1977-08-28 -6937,292,174,55,23.0,12,5.0,5,2.0,73,,,,60,1977-08-28 -6938,292,223,54,28.0,17,4.0,4,3.0,74,,,,11,1977-08-28 -6939,292,220,24,4.0,11,,18,0.0,31,,,,5,1977-08-28 -6940,292,171,26,26.0,2,2.0,2,6.0,75,6107820.0,,,1,1977-08-28 -6941,292,245,65,35.0,18,8.0,8,0.0,73,,,,12,1977-08-28 -6942,293,174,55,23.0,21,,20,0.0,9,,,,5,1977-09-11 -6943,293,229,61,19.0,10,,21,0.0,5,,,,3,1977-09-11 -6944,293,254,31,6.0,22,,22,0.0,4,,,,22,1977-09-11 -6945,293,238,0,30.0,19,,23,0.0,4,,,,5,1977-09-11 -6946,293,186,33,7.0,14,,24,0.0,3,,,,3,1977-09-11 -6947,293,236,36,9.0,0,,25,0.0,0,,,,81,1977-09-11 -6948,293,270,69,41.0,0,,33,0.0,0,,,,81,1977-09-11 -6949,293,240,61,18.0,0,,27,0.0,0,,,,81,1977-09-11 -6950,293,204,68,38.0,0,,28,0.0,0,,,,81,1977-09-11 -6951,293,207,0,36.0,0,,29,0.0,0,,,,81,1977-09-11 -6952,293,269,62,25.0,0,,30,0.0,0,,,,81,1977-09-11 -6953,293,268,64,29.0,0,,31,0.0,0,,,,81,1977-09-11 -6954,293,245,65,33.0,0,,32,0.0,0,,,,81,1977-09-11 -6955,293,219,33,21.0,0,,34,0.0,0,,,,81,1977-09-11 -6956,293,223,54,28.0,0,,26,0.0,0,,,,81,1977-09-11 -6957,293,218,3,15.0,20,,18,0.0,23,,,,5,1977-09-11 -6958,293,196,65,34.0,18,,19,0.0,19,,,,5,1977-09-11 -6959,293,220,24,4.0,13,,16,0.0,24,,,,5,1977-09-11 -6960,293,206,31,5.0,4,1.0,1,9.0,52,5270300.0,,,1,1977-09-11 -6961,293,181,5,11.0,5,2.0,2,6.0,52,5287260.0,,,1,1977-09-11 -6962,293,177,56,17.0,16,3.0,3,4.0,52,5293930.0,,,1,1977-09-11 -6963,293,199,0,2.0,9,4.0,4,3.0,52,5298780.0,,,1,1977-09-11 -6964,293,222,55,22.0,7,5.0,5,2.0,52,5300410.0,,,1,1977-09-11 -6965,293,237,24,3.0,12,6.0,6,1.0,52,5349520.0,,,1,1977-09-11 -6966,293,257,36,27.0,24,7.0,7,0.0,50,,,,12,1977-09-11 -6967,293,221,57,20.0,3,,17,0.0,23,,,,5,1977-09-11 -6968,293,171,26,26.0,8,8.0,8,0.0,50,,,,12,1977-09-11 -6969,293,151,0,14.0,15,,13,0.0,38,,,,5,1977-09-11 -6970,293,230,0,1.0,1,,15,0.0,26,,,,20,1977-09-11 -6971,293,232,33,8.0,11,,14,0.0,31,,,,5,1977-09-11 -6972,293,118,56,16.0,6,,12,0.0,39,,,,20,1977-09-11 -6973,293,198,5,12.0,2,,11,0.0,39,,,,20,1977-09-11 -6974,293,210,62,24.0,23,9.0,9,0.0,48,,,,14,1977-09-11 -6975,293,250,36,10.0,17,,10,0.0,41,,,,7,1977-09-11 -6976,294,229,61,19.0,11,19.0,19,0.0,54,,,,15,1977-10-02 -6977,294,174,55,23.0,0,,27,0.0,0,,,,81,1977-10-02 -6978,294,177,56,17.0,13,,26,0.0,3,,,,3,1977-10-02 -6979,294,239,65,14.0,26,,25,0.0,6,,,,3,1977-10-02 -6980,294,238,0,30.0,17,10.0,10,0.0,57,,,,12,1977-10-02 -6981,294,199,0,2.0,15,,24,0.0,8,,,,48,1977-10-02 -6982,294,250,36,10.0,21,,23,0.0,10,,,,3,1977-10-02 -6983,294,232,33,8.0,2,,22,0.0,14,,,,3,1977-10-02 -6984,294,254,31,6.0,12,,21,0.0,17,,,,3,1977-10-02 -6985,294,237,24,3.0,5,16.0,16,0.0,56,,,,13,1977-10-02 -6986,294,236,36,9.0,23,15.0,15,0.0,56,,,,13,1977-10-02 -6987,294,257,36,27.0,24,18.0,18,0.0,55,,,,14,1977-10-02 -6988,294,220,24,4.0,8,14.0,14,0.0,56,,,,13,1977-10-02 -6989,294,223,54,28.0,18,13.0,13,0.0,57,,,,12,1977-10-02 -6990,294,186,33,7.0,3,12.0,12,0.0,57,,,,12,1977-10-02 -6991,294,218,3,15.0,14,,20,0.0,30,,,,91,1977-10-02 -6992,294,245,61,18.0,25,11.0,11,0.0,57,,,,12,1977-10-02 -6993,294,269,62,25.0,22,17.0,17,0.0,55,,,,14,1977-10-02 -6994,294,171,26,26.0,10,7.0,7,0.0,58,,,,11,1977-10-02 -6995,294,206,31,5.0,4,2.0,2,6.0,59,7105293.0,,,1,1977-10-02 -6996,294,230,0,1.0,1,1.0,1,9.0,59,7103267.0,,,1,1977-10-02 -6997,294,196,56,16.0,16,9.0,9,0.0,58,,,,11,1977-10-02 -6998,294,222,55,22.0,19,5.0,5,2.0,59,7211405.0,,,1,1977-10-02 -6999,294,198,5,12.0,6,6.0,6,1.0,58,,,,11,1977-10-02 -7000,294,210,62,24.0,20,8.0,8,0.0,58,,,,11,1977-10-02 -7001,294,181,5,11.0,7,4.0,4,3.0,59,7203882.0,,,1,1977-10-02 -7002,294,221,57,20.0,9,3.0,3,4.0,59,7182146.0,,,1,1977-10-02 -7003,295,223,54,28.0,19,,19,0.0,29,,,,5,1977-10-09 -7004,295,250,36,10.0,18,,18,0.0,29,,,,5,1977-10-09 -7005,295,245,61,18.0,24,,17,0.0,31,,,,3,1977-10-09 -7006,295,210,62,24.0,25,,16,0.0,32,,,,3,1977-10-09 -7007,295,237,24,3.0,3,,15,0.0,34,,,,95,1977-10-09 -7008,295,257,36,27.0,21,,14,0.0,56,,,,5,1977-10-09 -7009,295,230,0,1.0,2,,13,0.0,61,,,,3,1977-10-09 -7010,295,202,5,21.0,17,12.0,12,0.0,76,,,,7,1977-10-09 -7011,295,238,0,30.0,20,11.0,11,0.0,76,,,,5,1977-10-09 -7012,295,198,5,12.0,12,,20,0.0,20,,,,69,1977-10-09 -7013,295,118,56,16.0,8,10.0,10,0.0,76,,,,20,1977-10-09 -7014,295,236,36,9.0,23,8.0,8,0.0,78,,,,12,1977-10-09 -7015,295,239,65,14.0,22,7.0,7,0.0,78,,,,12,1977-10-09 -7016,295,229,61,19.0,15,6.0,6,1.0,78,,,,3,1977-10-09 -7017,295,174,55,23.0,16,5.0,5,2.0,80,6063260.0,,,1,1977-10-09 -7018,295,177,56,17.0,7,4.0,4,3.0,80,6046690.0,,,1,1977-10-09 -7019,295,199,0,2.0,5,3.0,3,4.0,80,6015760.0,,,1,1977-10-09 -7020,295,220,24,4.0,6,2.0,2,6.0,80,6006770.0,,,1,1977-10-09 -7021,295,221,57,20.0,9,1.0,1,9.0,80,6000000.0,,,1,1977-10-09 -7022,295,206,31,5.0,1,9.0,9,0.0,77,,,,5,1977-10-09 -7023,295,232,33,8.0,13,,21,0.0,19,,,,5,1977-10-09 -7024,295,171,26,26.0,11,,23,0.0,12,,,,7,1977-10-09 -7025,295,186,33,7.0,10,,24,0.0,1,,,,22,1977-10-09 -7026,295,222,55,22.0,14,,25,0.0,0,,,,3,1977-10-09 -7027,295,269,62,25.0,0,,26,0.0,0,,,,54,1977-10-09 -7028,295,218,3,15.0,0,,27,0.0,0,,,,81,1977-10-09 -7029,295,254,31,6.0,4,,22,0.0,17,,,,3,1977-10-09 -7030,296,237,24,3.0,18,,18,0.0,5,,,,3,1977-10-23 -7031,296,245,61,18.0,21,,23,0.0,1,,,,4,1977-10-23 -7032,296,273,70,51.0,19,,22,0.0,1,,,,4,1977-10-23 -7033,296,206,31,5.0,1,,21,0.0,1,,,,4,1977-10-23 -7034,296,196,26,27.0,17,,20,0.0,3,,,,5,1977-10-23 -7035,296,186,33,7.0,3,,15,0.0,29,,,,6,1977-10-23 -7036,296,222,55,22.0,10,,14,0.0,43,,,,5,1977-10-23 -7037,296,254,31,6.0,14,,13,0.0,63,,,,6,1977-10-23 -7038,296,236,36,9.0,23,12.0,12,0.0,69,,,,14,1977-10-23 -7039,296,272,70,52.0,11,11.0,11,0.0,71,,,,12,1977-10-23 -7040,296,221,57,20.0,6,10.0,10,0.0,71,,,,12,1977-10-23 -7041,296,232,33,8.0,4,7.0,7,0.0,72,,,,11,1977-10-23 -7042,296,229,61,19.0,9,8.0,8,0.0,71,,,,12,1977-10-23 -7043,296,118,56,16.0,13,6.0,6,1.0,72,,,,11,1977-10-23 -7044,296,202,5,11.0,20,,19,0.0,5,,,,3,1977-10-23 -7045,296,171,26,26.0,5,5.0,5,2.0,72,,,,60,1977-10-23 -7046,296,177,56,17.0,12,4.0,4,3.0,73,5578290.0,,,1,1977-10-23 -7047,296,220,24,4.0,15,3.0,3,4.0,73,5578070.0,,,1,1977-10-23 -7048,296,198,5,12.0,7,2.0,2,6.0,73,5574130.0,,,1,1977-10-23 -7049,296,230,0,1.0,2,1.0,1,9.0,73,5511680.0,,,1,1977-10-23 -7050,296,174,55,23.0,16,,17,0.0,14,,,,5,1977-10-23 -7051,296,271,24,50.0,22,9.0,9,0.0,71,,,,12,1977-10-23 -7052,296,199,0,2.0,8,,16,0.0,28,,,,5,1977-10-23 -7053,297,157,53,32.0,0,,26,0.0,0,,,,81,1978-01-15 -7054,297,238,0,30.0,24,13.0,13,0.0,51,,,,11,1978-01-15 -7055,297,181,33,1.0,5,2.0,2,6.0,52,5837680.0,,,1,1978-01-15 -7056,297,220,24,4.0,10,3.0,3,4.0,52,5838110.0,,,1,1978-01-15 -7057,297,230,0,7.0,6,4.0,4,3.0,52,5840520.0,,,1,1978-01-15 -7058,297,237,31,6.0,3,5.0,5,2.0,52,5899320.0,,,1,1978-01-15 -7059,297,174,0,8.0,9,6.0,6,1.0,52,5904370.0,,,1,1978-01-15 -7060,297,198,5,11.0,2,7.0,7,0.0,52,5907070.0,,,1,1978-01-15 -7061,297,202,5,12.0,7,8.0,8,0.0,52,5923350.0,,,1,1978-01-15 -7062,297,223,54,14.0,17,9.0,9,0.0,52,5925070.0,,,1,1978-01-15 -7063,297,221,57,20.0,15,10.0,10,0.0,52,5927970.0,,,1,1978-01-15 -7064,297,199,52,9.0,13,11.0,11,0.0,52,5933540.0,,,1,1978-01-15 -7065,297,196,52,10.0,11,12.0,12,0.0,51,,,,11,1978-01-15 -7066,297,206,31,5.0,1,1.0,1,9.0,52,5824470.0,,,1,1978-01-15 -7067,297,241,62,24.0,0,,27,0.0,0,,,,81,1978-01-15 -7068,297,222,56,17.0,16,15.0,15,0.0,51,,,,11,1978-01-15 -7069,297,171,26,26.0,8,16.0,16,0.0,50,,,,5,1978-01-15 -7070,297,232,56,16.0,18,17.0,17,0.0,50,,,,12,1978-01-15 -7071,297,229,61,19.0,12,18.0,18,0.0,50,,,,12,1978-01-15 -7072,297,186,33,2.0,4,,19,0.0,41,,,,5,1978-01-15 -7073,297,177,2,27.0,14,,20,0.0,36,,,,69,1978-01-15 -7074,297,239,55,22.0,21,,21,0.0,35,,,,99,1978-01-15 -7075,297,240,55,23.0,22,,22,0.0,28,,,,5,1978-01-15 -7076,297,231,58,37.0,20,,23,0.0,9,,,,24,1978-01-15 -7077,297,210,61,18.0,19,,24,0.0,4,,,,25,1978-01-15 -7078,297,211,31,25.0,0,,25,0.0,0,,,,81,1978-01-15 -7079,297,201,24,3.0,23,14.0,14,0.0,51,,,,11,1978-01-15 -7080,298,241,62,24.0,0,,28,0.0,0,,,,81,1978-01-29 -7081,298,198,5,11.0,4,1.0,1,9.0,63,6599860.0,,,1,1978-01-29 -7082,298,181,33,1.0,10,3.0,3,4.0,63,6656880.0,,,1,1978-01-29 -7083,298,229,61,19.0,0,,27,0.0,0,,,,81,1978-01-29 -7084,298,157,53,32.0,0,,26,0.0,0,,,,81,1978-01-29 -7085,298,231,58,37.0,0,,25,0.0,0,,,,81,1978-01-29 -7086,298,196,52,10.0,16,,24,0.0,0,,,,54,1978-01-29 -7087,298,240,55,23.0,17,,23,0.0,0,,,,7,1978-01-29 -7088,298,210,61,18.0,24,,22,0.0,5,,,,3,1978-01-29 -7089,298,220,24,4.0,11,,21,0.0,8,,,,3,1978-01-29 -7090,298,238,0,30.0,13,,20,0.0,11,,,,25,1978-01-29 -7091,298,239,55,22.0,23,,19,0.0,13,,,,23,1978-01-29 -7092,298,237,31,6.0,1,,18,0.0,15,,,,4,1978-01-29 -7093,298,221,57,20.0,12,,17,0.0,16,,,,3,1978-01-29 -7094,298,230,0,7.0,2,,15,0.0,25,,,,20,1978-01-29 -7095,298,174,0,8.0,5,,14,0.0,34,,,,20,1978-01-29 -7096,298,202,5,12.0,6,,13,0.0,35,,,,20,1978-01-29 -7097,298,211,31,25.0,22,,12,0.0,40,,,,68,1978-01-29 -7098,298,177,2,27.0,8,11.0,11,0.0,58,,,,15,1978-01-29 -7099,298,118,20,36.0,18,10.0,10,0.0,59,,,,14,1978-01-29 -7100,298,171,26,26.0,14,9.0,9,0.0,61,,,,12,1978-01-29 -7101,298,186,33,2.0,21,8.0,8,0.0,61,,,,12,1978-01-29 -7102,298,199,52,9.0,20,7.0,7,0.0,62,,,,11,1978-01-29 -7103,298,201,24,3.0,19,6.0,6,1.0,62,,,,11,1978-01-29 -7104,298,222,56,17.0,15,5.0,5,2.0,62,,,,11,1978-01-29 -7105,298,206,31,5.0,3,4.0,4,3.0,63,6692980.0,,,1,1978-01-29 -7106,298,223,54,14.0,7,2.0,2,6.0,63,6648990.0,,,1,1978-01-29 -7107,298,232,56,16.0,9,,16,0.0,25,,,,69,1978-01-29 -7108,299,232,56,16.0,0,,30,0.0,0,,,,81,1978-03-04 -7109,299,198,5,11.0,9,,17,0.0,55,,,,20,1978-03-04 -7110,299,177,2,27.0,18,4.0,4,3.0,78,6166753.0,,,1,1978-03-04 -7111,299,171,26,26.0,13,5.0,5,2.0,78,6204985.0,,,1,1978-03-04 -7112,299,201,24,3.0,14,6.0,6,1.0,77,,,,11,1978-03-04 -7113,299,206,31,5.0,2,7.0,7,0.0,77,,,,11,1978-03-04 -7114,299,196,52,10.0,17,8.0,8,0.0,77,,,,11,1978-03-04 -7115,299,242,20,36.0,22,9.0,9,0.0,77,,,,11,1978-03-04 -7116,299,211,31,25.0,21,10.0,10,0.0,77,,,,11,1978-03-04 -7117,299,238,0,30.0,20,11.0,11,0.0,76,,,,12,1978-03-04 -7118,299,229,61,19.0,19,12.0,12,0.0,76,,,,12,1978-03-04 -7119,299,118,20,35.0,7,,13,0.0,63,,,,5,1978-03-04 -7120,299,221,57,20.0,5,,14,0.0,59,,,,20,1978-03-04 -7121,299,186,33,2.0,10,3.0,3,4.0,78,6140209.0,,,1,1978-03-04 -7122,299,174,0,8.0,4,,15,0.0,56,,,,3,1978-03-04 -7123,299,181,33,1.0,1,,18,0.0,52,,,,5,1978-03-04 -7124,299,210,61,18.0,23,,19,0.0,52,,,,5,1978-03-04 -7125,299,199,52,9.0,15,,20,0.0,43,,,,5,1978-03-04 -7126,299,231,58,37.0,26,,21,0.0,39,,,,22,1978-03-04 -7127,299,218,3,15.0,6,,22,0.0,38,,,,5,1978-03-04 -7128,299,176,53,32.0,24,,23,0.0,15,,,,8,1978-03-04 -7129,299,223,54,14.0,16,,24,0.0,9,,,,7,1978-03-04 -7130,299,157,62,24.0,25,,25,0.0,8,,,,44,1978-03-04 -7131,299,230,0,7.0,3,,26,0.0,5,,,,5,1978-03-04 -7132,299,162,63,31.0,0,,27,0.0,0,,,,81,1978-03-04 -7133,299,222,56,17.0,0,,28,0.0,0,,,,81,1978-03-04 -7134,299,202,5,12.0,8,,16,0.0,55,,,,44,1978-03-04 -7135,299,240,55,23.0,0,,29,0.0,0,,,,81,1978-03-04 -7136,299,220,24,4.0,11,2.0,2,6.0,78,6136233.0,,,1,1978-03-04 -7137,299,237,31,6.0,12,1.0,1,9.0,78,6135767.0,,,1,1978-03-04 -7138,300,237,31,6.0,6,4.0,4,3.0,80,6766904.0,,,1,1978-04-02 -7139,300,211,31,25.0,0,,28,0.0,0,,,,97,1978-04-02 -7140,300,176,53,32.0,0,,27,0.0,0,,,,97,1978-04-02 -7141,300,240,55,22.0,0,,26,0.0,0,,,,81,1978-04-02 -7142,300,238,0,30.0,0,,25,0.0,0,,,,81,1978-04-02 -7143,300,232,56,16.0,0,,24,0.0,0,,,,3,1978-04-02 -7144,300,210,61,18.0,0,,23,0.0,0,,,,3,1978-04-02 -7145,300,230,0,7.0,7,,22,0.0,5,,,,3,1978-04-02 -7146,300,186,33,2.0,5,,21,0.0,9,,,,6,1978-04-02 -7147,300,199,52,9.0,16,,20,0.0,11,,,,23,1978-04-02 -7148,300,231,58,37.0,21,,19,0.0,17,,,,6,1978-04-02 -7149,300,201,24,3.0,22,,18,0.0,25,,,,6,1978-04-02 -7150,300,206,31,5.0,4,2.0,2,6.0,80,6732362.0,,,1,1978-04-02 -7151,300,181,33,1.0,3,,17,0.0,27,,,,80,1978-04-02 -7152,300,218,3,15.0,13,,15,0.0,43,,,,101,1978-04-02 -7153,300,229,61,19.0,17,,14,0.0,50,,,,7,1978-04-02 -7154,300,221,57,20.0,10,,13,0.0,59,,,,3,1978-04-02 -7155,300,174,0,8.0,11,12.0,12,0.0,74,,,,3,1978-04-02 -7156,300,196,52,10.0,19,11.0,11,0.0,75,,,,15,1978-04-02 -7157,300,222,56,17.0,20,10.0,10,0.0,79,,,,11,1978-04-02 -7158,300,242,20,36.0,18,9.0,9,0.0,79,,,,11,1978-04-02 -7159,300,223,54,14.0,15,8.0,8,0.0,79,,,,11,1978-04-02 -7160,300,177,2,27.0,8,7.0,7,0.0,79,,,,11,1978-04-02 -7161,300,118,20,35.0,9,6.0,6,1.0,79,,,,11,1978-04-02 -7162,300,171,26,26.0,14,5.0,5,2.0,80,6804185.0,,,1,1978-04-02 -7163,300,202,5,12.0,2,,16,0.0,38,,,,3,1978-04-02 -7164,300,198,5,11.0,1,1.0,1,9.0,80,6721301.0,,,1,1978-04-02 -7165,300,220,24,4.0,12,3.0,3,4.0,80,6750252.0,,,1,1978-04-02 -7166,300,239,56,39.0,0,,29,0.0,0,,,,97,1978-04-02 -7167,300,205,62,24.0,0,,30,0.0,0,,,,97,1978-04-02 -7168,301,186,33,2.0,2,4.0,4,3.0,75,6948190.0,,,1,1978-05-07 -7169,301,238,0,30.0,0,,29,0.0,0,,,,97,1978-05-07 -7170,301,211,31,25.0,0,,28,0.0,0,,,,97,1978-05-07 -7171,301,162,63,31.0,0,,27,0.0,0,,,,97,1978-05-07 -7172,301,205,62,24.0,0,,26,0.0,0,,,,97,1978-05-07 -7173,301,176,53,32.0,0,,25,0.0,0,,,,97,1978-05-07 -7174,301,229,61,19.0,0,,24,0.0,0,,,,81,1978-05-07 -7175,301,196,52,10.0,0,,23,0.0,0,,,,81,1978-05-07 -7176,301,222,56,17.0,0,,22,0.0,0,,,,81,1978-05-07 -7177,301,199,52,9.0,0,,21,0.0,0,,,,81,1978-05-07 -7178,301,210,61,18.0,18,,20,0.0,8,,,,7,1978-05-07 -7179,301,171,26,26.0,15,,19,0.0,13,,,,6,1978-05-07 -7180,301,181,33,1.0,3,2.0,2,6.0,75,6937110.0,,,1,1978-05-07 -7181,301,232,56,16.0,17,,18,0.0,24,,,,3,1978-05-07 -7182,301,242,20,36.0,19,,15,0.0,38,,,,100,1978-05-07 -7183,301,230,0,7.0,6,,14,0.0,43,,,,64,1978-05-07 -7184,301,237,31,6.0,7,,13,0.0,56,,,,6,1978-05-07 -7185,301,202,5,12.0,8,,12,0.0,62,,,,3,1978-05-07 -7186,301,206,31,5.0,4,11.0,11,0.0,69,,,,16,1978-05-07 -7187,301,218,3,15.0,12,10.0,10,0.0,71,,,,14,1978-05-07 -7188,301,223,54,14.0,20,9.0,9,0.0,74,,,,11,1978-05-07 -7189,301,198,5,11.0,1,8.0,8,0.0,74,,,,11,1978-05-07 -7190,301,174,0,8.0,11,7.0,7,0.0,74,,,,11,1978-05-07 -7191,301,118,20,35.0,14,6.0,6,1.0,75,6983430.0,,,1,1978-05-07 -7192,301,201,24,3.0,13,5.0,5,2.0,75,6982720.0,,,1,1978-05-07 -7193,301,221,57,20.0,9,3.0,3,4.0,75,6946950.0,,,1,1978-05-07 -7194,301,234,55,22.0,16,,17,0.0,27,,,,23,1978-05-07 -7195,301,177,2,27.0,10,,16,0.0,29,,,,44,1978-05-07 -7196,301,231,58,37.0,0,,30,0.0,0,,,,97,1978-05-07 -7197,301,220,24,4.0,5,1.0,1,9.0,75,6914660.0,,,1,1978-05-07 -7198,302,231,58,37.0,0,,30,0.0,0,,,,97,1978-05-21 -7199,302,211,31,25.0,0,,29,0.0,0,,,,97,1978-05-21 -7200,302,243,52,10.0,0,,28,0.0,0,,,,81,1978-05-21 -7201,302,176,53,32.0,0,,27,0.0,0,,,,81,1978-05-21 -7202,302,205,62,24.0,0,,26,0.0,0,,,,81,1978-05-21 -7203,302,210,61,18.0,0,,25,0.0,0,,,,81,1978-05-21 -7204,302,223,54,14.0,15,,24,0.0,0,,,,3,1978-05-21 -7205,302,230,0,7.0,6,,23,0.0,0,,,,3,1978-05-21 -7206,302,181,33,1.0,3,,22,0.0,0,,,,3,1978-05-21 -7207,302,186,33,2.0,9,,21,0.0,18,,,,3,1978-05-21 -7208,302,242,20,36.0,17,,20,0.0,26,,,,20,1978-05-21 -7209,302,118,20,35.0,8,,19,0.0,31,,,,22,1978-05-21 -7210,302,222,56,17.0,18,,18,0.0,40,,,,7,1978-05-21 -7211,302,202,5,12.0,4,4.0,4,3.0,70,6039060.0,,,1,1978-05-21 -7212,302,221,57,20.0,5,,16,0.0,53,,,,20,1978-05-21 -7213,302,218,3,15.0,20,,15,0.0,56,,,,62,1978-05-21 -7214,302,232,56,16.0,10,,14,0.0,56,,,,20,1978-05-21 -7215,302,229,61,19.0,12,13.0,13,0.0,63,,,,5,1978-05-21 -7216,302,234,55,22.0,22,12.0,12,0.0,64,,,,16,1978-05-21 -7217,302,199,52,9.0,16,11.0,11,0.0,68,,,,12,1978-05-21 -7218,302,177,2,27.0,11,10.0,10,0.0,68,,,,12,1978-05-21 -7219,302,162,63,31.0,19,9.0,9,0.0,68,,,,12,1978-05-21 -7220,302,151,0,33.0,21,8.0,8,0.0,69,,,,11,1978-05-21 -7221,302,238,0,30.0,24,7.0,7,0.0,69,,,,11,1978-05-21 -7222,302,201,24,3.0,23,6.0,6,1.0,69,,,,11,1978-05-21 -7223,302,171,26,26.0,14,5.0,5,2.0,69,,,,3,1978-05-21 -7224,302,220,24,4.0,13,,17,0.0,51,,,,6,1978-05-21 -7225,302,198,5,11.0,2,3.0,3,4.0,70,6016360.0,,,1,1978-05-21 -7226,302,206,31,5.0,1,1.0,1,9.0,70,5992020.0,,,1,1978-05-21 -7227,302,237,31,6.0,7,2.0,2,6.0,70,6001920.0,,,1,1978-05-21 -7228,303,171,26,26.0,10,3.0,3,4.0,75,6144300.0,,,1,1978-06-04 -7229,303,221,57,20.0,9,4.0,4,3.0,75,6167120.0,,,1,1978-06-04 -7230,303,186,33,2.0,7,5.0,5,2.0,75,6172990.0,,,1,1978-06-04 -7231,303,230,0,7.0,4,6.0,6,1.0,74,,,,11,1978-06-04 -7232,303,229,61,19.0,16,7.0,7,0.0,74,,,,11,1978-06-04 -7233,303,177,2,27.0,18,8.0,8,0.0,74,,,,11,1978-06-04 -7234,303,199,52,9.0,17,9.0,9,0.0,74,,,,11,1978-06-04 -7235,303,202,5,12.0,5,10.0,10,0.0,74,,,,11,1978-06-04 -7236,303,210,61,18.0,23,11.0,11,0.0,73,,,,12,1978-06-04 -7237,303,201,24,3.0,13,12.0,12,0.0,71,,,,14,1978-06-04 -7238,303,218,3,15.0,11,13.0,13,0.0,71,,,,14,1978-06-04 -7239,303,242,20,36.0,19,14.0,14,0.0,71,,,,14,1978-06-04 -7240,303,222,56,17.0,22,15.0,15,0.0,67,,,,106,1978-06-04 -7241,303,234,55,22.0,21,,16,0.0,64,,,,5,1978-06-04 -7242,303,223,54,14.0,15,,17,0.0,62,,,,37,1978-06-04 -7243,303,198,5,11.0,3,,18,0.0,57,,,,3,1978-06-04 -7244,303,181,33,1.0,6,,19,0.0,56,,,,5,1978-06-04 -7245,303,220,24,4.0,12,,20,0.0,51,,,,5,1978-06-04 -7246,303,232,56,16.0,24,,21,0.0,45,,,,22,1978-06-04 -7247,303,118,20,35.0,8,,22,0.0,21,,,,5,1978-06-04 -7248,303,211,31,25.0,20,,23,0.0,21,,,,43,1978-06-04 -7249,303,174,0,8.0,14,,24,0.0,16,,,,20,1978-06-04 -7250,303,231,58,37.0,0,,25,0.0,0,,,,81,1978-06-04 -7251,303,238,0,30.0,0,,26,0.0,0,,,,81,1978-06-04 -7252,303,207,0,28.0,0,,27,0.0,0,,,,81,1978-06-04 -7253,303,237,31,6.0,2,2.0,2,6.0,75,6126620.0,,,1,1978-06-04 -7254,303,243,52,10.0,0,,28,0.0,0,,,,81,1978-06-04 -7255,303,206,31,5.0,1,1.0,1,9.0,75,6107060.0,,,1,1978-06-04 -7256,303,176,53,32.0,0,,29,0.0,0,,,,97,1978-06-04 -7257,304,234,55,22.0,0,,27,0.0,0,,,,81,1978-06-17 -7258,304,238,0,30.0,0,,26,0.0,0,,,,81,1978-06-17 -7259,304,210,61,18.0,0,,25,0.0,0,,,,81,1978-06-17 -7260,304,229,61,19.0,18,,24,0.0,7,,,,3,1978-06-17 -7261,304,201,24,3.0,17,,23,0.0,8,,,,3,1978-06-17 -7262,304,221,57,20.0,6,,22,0.0,16,,,,25,1978-06-17 -7263,304,186,33,2.0,2,,21,0.0,19,,,,20,1978-06-17 -7264,304,218,3,15.0,10,,20,0.0,28,,,,5,1978-06-17 -7265,304,220,24,4.0,12,,19,0.0,42,,,,22,1978-06-17 -7266,304,177,2,27.0,9,,18,0.0,46,,,,36,1978-06-17 -7267,304,206,31,5.0,1,,17,0.0,46,,,,5,1978-06-17 -7268,304,231,58,37.0,22,,16,0.0,62,,,,18,1978-06-17 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-7286,305,206,31,5.0,2,1.0,1,9.0,54,5931920.0,,,1,1978-07-02 -7287,305,186,33,2.0,1,4.0,4,3.0,54,5968800.0,,,1,1978-07-02 -7288,305,177,2,27.0,14,5.0,5,2.0,54,5973730.0,,,1,1978-07-02 -7289,305,221,57,20.0,7,6.0,6,1.0,54,5986450.0,,,1,1978-07-02 -7290,305,171,26,26.0,10,7.0,7,0.0,54,5986660.0,,,1,1978-07-02 -7291,305,118,20,35.0,12,8.0,8,0.0,54,6016800.0,,,1,1978-07-02 -7292,305,174,0,8.0,6,9.0,9,0.0,54,6018980.0,,,1,1978-07-02 -7293,305,201,24,3.0,16,10.0,10,0.0,54,6021900.0,,,1,1978-07-02 -7294,305,232,56,16.0,20,11.0,11,0.0,53,,,,11,1978-07-02 -7295,305,202,5,12.0,9,12.0,12,0.0,53,,,,11,1978-07-02 -7296,305,199,52,9.0,25,13.0,13,0.0,53,,,,11,1978-07-02 -7297,305,162,63,31.0,18,14.0,14,0.0,53,,,,11,1978-07-02 -7298,305,242,20,36.0,21,15.0,15,0.0,53,,,,11,1978-07-02 -7299,305,176,52,10.0,26,16.0,16,0.0,52,,,,12,1978-07-02 -7300,305,229,61,19.0,19,17.0,17,0.0,52,,,,12,1978-07-02 -7301,305,198,5,11.0,8,18.0,18,0.0,49,,,,15,1978-07-02 -7302,305,238,0,30.0,24,,19,0.0,45,,,,5,1978-07-02 -7303,305,223,54,14.0,15,,20,0.0,43,,,,22,1978-07-02 -7304,305,210,61,18.0,23,,21,0.0,40,,,,5,1978-07-02 -7305,305,151,0,33.0,22,,22,0.0,28,,,,5,1978-07-02 -7306,305,181,33,1.0,3,,23,0.0,10,,,,5,1978-07-02 -7307,305,220,24,4.0,13,,24,0.0,10,,,,5,1978-07-02 -7308,305,222,56,17.0,17,,25,0.0,4,,,,10,1978-07-02 -7309,305,218,3,15.0,11,,26,0.0,1,,,,5,1978-07-02 -7310,305,231,58,37.0,0,,27,0.0,0,,,,81,1978-07-02 -7311,305,211,31,25.0,0,,29,0.0,0,,,,81,1978-07-02 -7312,305,237,31,6.0,5,2.0,2,6.0,54,5934850.0,,,1,1978-07-02 -7313,306,244,0,40.0,0,,30,0.0,0,,,,81,1978-07-16 -7314,306,220,24,4.0,10,4.0,4,3.0,76,6205660.0,,,1,1978-07-16 -7315,306,208,55,23.0,0,,29,0.0,0,,,,81,1978-07-16 -7316,306,242,20,36.0,0,,28,0.0,0,,,,81,1978-07-16 -7317,306,210,61,18.0,0,,27,0.0,0,,,,81,1978-07-16 -7318,306,237,31,6.0,1,,26,0.0,6,,,,69,1978-07-16 -7319,306,230,0,7.0,14,,25,0.0,7,,,,3,1978-07-16 -7320,306,211,31,25.0,21,,24,0.0,15,,,,6,1978-07-16 -7321,306,202,5,12.0,13,,23,0.0,19,,,,7,1978-07-16 -7322,306,177,2,27.0,6,,22,0.0,26,,,,7,1978-07-16 -7323,306,206,31,5.0,2,,21,0.0,28,,,,5,1978-07-16 -7324,306,205,55,22.0,15,,20,0.0,30,,,,36,1978-07-16 -7325,306,231,58,37.0,23,,19,0.0,32,,,,69,1978-07-16 -7326,306,223,54,14.0,11,,18,0.0,32,,,,5,1978-07-16 -7327,306,221,57,20.0,3,,17,0.0,36,,,,6,1978-07-16 -7328,306,201,24,3.0,19,,16,0.0,40,,,,6,1978-07-16 -7329,306,118,20,35.0,5,,15,0.0,40,,,,22,1978-07-16 -7330,306,218,3,15.0,12,,14,0.0,46,,,,101,1978-07-16 -7331,306,222,56,17.0,17,,13,0.0,49,,,,6,1978-07-16 -7332,306,176,52,10.0,22,,12,0.0,59,,,,22,1978-07-16 -7333,306,199,52,9.0,26,,11,0.0,65,,,,45,1978-07-16 -7334,306,171,26,26.0,7,10.0,10,0.0,73,,,,13,1978-07-16 -7335,306,229,61,19.0,25,9.0,9,0.0,75,,,,11,1978-07-16 -7336,306,238,0,30.0,24,8.0,8,0.0,75,,,,11,1978-07-16 -7337,306,151,0,33.0,16,7.0,7,0.0,75,,,,11,1978-07-16 -7338,306,174,0,8.0,20,6.0,6,1.0,75,,,,11,1978-07-16 -7339,306,232,56,16.0,18,5.0,5,2.0,75,,,,11,1978-07-16 -7340,306,181,33,1.0,4,2.0,2,6.0,76,6133620.0,,,1,1978-07-16 -7341,306,186,33,2.0,9,3.0,3,4.0,76,6169640.0,,,1,1978-07-16 -7342,306,198,5,11.0,8,1.0,1,9.0,76,6132390.0,,,1,1978-07-16 -7343,307,199,52,9.0,22,,22,0.0,1,,,,3,1978-07-30 -7344,307,238,0,30.0,0,,30,0.0,0,,,,97,1978-07-30 -7345,307,162,63,31.0,0,,29,0.0,0,,,,97,1978-07-30 -7346,307,231,58,37.0,0,,28,0.0,0,,,,81,1978-07-30 -7347,307,210,61,18.0,0,,27,0.0,0,,,,81,1978-07-30 -7348,307,196,52,10.0,0,,26,0.0,0,,,,81,1978-07-30 -7349,307,222,56,17.0,0,,25,0.0,0,,,,81,1978-07-30 -7350,307,220,24,4.0,13,,24,0.0,0,,,,3,1978-07-30 -7351,307,232,56,16.0,24,,23,0.0,1,,,,3,1978-07-30 -7352,307,218,3,15.0,9,,21,0.0,5,,,,5,1978-07-30 -7353,307,181,33,1.0,3,,20,0.0,11,,,,5,1978-07-30 -7354,307,198,5,11.0,12,,19,0.0,14,,,,69,1978-07-30 -7355,307,229,61,19.0,20,,17,0.0,24,,,,69,1978-07-30 -7356,307,136,55,22.0,21,,16,0.0,31,,,,5,1978-07-30 -7357,307,177,2,27.0,6,,15,0.0,31,,,,69,1978-07-30 -7358,307,174,0,8.0,11,,18,0.0,16,,,,3,1978-07-30 -7359,307,237,31,6.0,2,,13,0.0,36,,,,6,1978-07-30 -7360,307,206,31,5.0,1,1.0,1,9.0,45,5280900.0,,,1,1978-07-30 -7361,307,221,57,20.0,4,2.0,2,6.0,45,5296250.0,,,1,1978-07-30 -7362,307,171,26,26.0,7,3.0,3,4.0,45,5308910.0,,,1,1978-07-30 -7363,307,223,54,14.0,10,4.0,4,3.0,45,5317780.0,,,1,1978-07-30 -7364,307,230,0,7.0,8,,14,0.0,34,,,,2,1978-07-30 -7365,307,211,31,25.0,18,6.0,6,1.0,45,5378760.0,,,1,1978-07-30 -7366,307,186,33,2.0,5,7.0,7,0.0,45,5380430.0,,,1,1978-07-30 -7367,307,201,24,3.0,16,5.0,5,2.0,45,5338160.0,,,1,1978-07-30 -7368,307,118,20,35.0,14,9.0,9,0.0,44,,,,11,1978-07-30 -7369,307,176,57,32.0,19,10.0,10,0.0,42,,,,13,1978-07-30 -7370,307,228,55,23.0,17,11.0,11,0.0,41,,,,5,1978-07-30 -7371,307,242,20,36.0,23,,12,0.0,42,,,,2,1978-07-30 -7372,307,202,5,12.0,15,8.0,8,0.0,45,5397770.0,,,1,1978-07-30 -7373,308,201,24,3.0,9,,18,0.0,20,,,,3,1978-08-13 -7374,308,211,31,25.0,18,,23,0.0,4,,,,3,1978-08-13 -7375,308,230,0,7.0,8,,19,0.0,7,,,,3,1978-08-13 -7376,308,177,2,27.0,15,,20,0.0,7,,,,3,1978-08-13 -7377,308,118,20,35.0,16,,21,0.0,7,,,,3,1978-08-13 -7378,308,228,55,23.0,24,,22,0.0,7,,,,3,1978-08-13 -7379,308,136,0,29.0,20,,24,0.0,4,,,,3,1978-08-13 -7380,308,242,20,36.0,0,,31,0.0,0,,,,97,1978-08-13 -7381,308,206,31,5.0,2,,26,0.0,0,,,,3,1978-08-13 -7382,308,231,58,37.0,0,,27,0.0,0,,,,81,1978-08-13 -7383,308,199,52,9.0,0,,28,0.0,0,,,,81,1978-08-13 -7384,308,210,61,18.0,0,,29,0.0,0,,,,81,1978-08-13 -7385,308,245,52,10.0,0,,30,0.0,0,,,,81,1978-08-13 -7386,308,181,33,1.0,4,,17,0.0,27,,,,3,1978-08-13 -7387,308,221,57,20.0,7,,25,0.0,3,,,,3,1978-08-13 -7388,308,198,5,11.0,12,,16,0.0,28,,,,2,1978-08-13 -7389,308,218,3,15.0,3,,15,0.0,31,,,,6,1978-08-13 -7390,308,232,56,16.0,23,,14,0.0,33,,,,3,1978-08-13 -7391,308,220,24,4.0,14,2.0,2,6.0,54,6129010.0,,,1,1978-08-13 -7392,308,202,5,12.0,11,3.0,3,4.0,54,6181330.0,,,1,1978-08-13 -7393,308,223,54,14.0,6,4.0,4,3.0,53,,,,11,1978-08-13 -7394,308,171,26,26.0,5,5.0,5,2.0,53,,,,11,1978-08-13 -7395,308,229,61,19.0,21,6.0,6,1.0,53,,,,11,1978-08-13 -7396,308,186,33,2.0,10,7.0,7,0.0,53,,,,11,1978-08-13 -7397,308,237,31,6.0,1,1.0,1,9.0,54,6081570.0,,,1,1978-08-13 -7398,308,162,63,31.0,26,9.0,9,0.0,52,,,,12,1978-08-13 -7399,308,222,56,17.0,22,,10,0.0,50,,,,17,1978-08-13 -7400,308,176,57,32.0,25,,11,0.0,49,,,,17,1978-08-13 -7401,308,205,55,22.0,19,,12,0.0,41,,,,2,1978-08-13 -7402,308,174,0,8.0,14,,13,0.0,40,,,,3,1978-08-13 -7403,308,238,0,30.0,17,8.0,8,0.0,52,,,,12,1978-08-13 -7404,309,218,3,15.0,9,,18,0.0,35,,,,5,1978-08-27 -7405,309,238,0,30.0,21,,19,0.0,35,,,,5,1978-08-27 -7406,309,176,57,32.0,24,,20,0.0,21,,,,3,1978-08-27 -7407,309,177,2,27.0,11,,21,0.0,17,,,,37,1978-08-27 -7408,309,136,0,29.0,25,,22,0.0,16,,,,7,1978-08-27 -7409,309,220,24,4.0,12,,23,0.0,13,,,,5,1978-08-27 -7410,309,201,24,3.0,17,,26,0.0,0,,,,3,1978-08-27 -7411,309,118,20,35.0,13,,25,0.0,0,,,,3,1978-08-27 -7412,309,210,61,18.0,0,,27,0.0,0,,,,54,1978-08-27 -7413,309,222,56,17.0,0,,28,0.0,0,,,,81,1978-08-27 -7414,309,246,52,10.0,0,,29,0.0,0,,,,81,1978-08-27 -7415,309,229,61,19.0,22,,17,0.0,37,,,,2,1978-08-27 -7416,309,205,55,22.0,16,,24,0.0,10,,,,7,1978-08-27 -7417,309,231,58,37.0,26,,16,0.0,40,,,,5,1978-08-27 -7418,309,171,26,26.0,6,8.0,8,0.0,74,,,,11,1978-08-27 -7419,309,232,56,16.0,18,,14,0.0,56,,,,7,1978-08-27 -7420,309,221,57,20.0,15,12.0,12,0.0,73,,,,12,1978-08-27 -7421,309,211,31,25.0,20,11.0,11,0.0,74,,,,11,1978-08-27 -7422,309,230,0,7.0,7,10.0,10,0.0,74,,,,11,1978-08-27 -7423,309,174,0,8.0,14,9.0,9,0.0,74,,,,11,1978-08-27 -7424,309,199,52,9.0,0,,30,0.0,0,,,,81,1978-08-27 -7425,309,198,5,11.0,4,7.0,7,0.0,75,6124750.0,,,1,1978-08-27 -7426,309,202,5,12.0,5,6.0,6,1.0,75,6110180.0,,,1,1978-08-27 -7427,309,223,54,14.0,10,5.0,5,2.0,75,6085730.0,,,1,1978-08-27 -7428,309,186,33,2.0,8,4.0,4,3.0,75,6085150.0,,,1,1978-08-27 -7429,309,181,33,1.0,3,3.0,3,4.0,75,6076440.0,,,1,1978-08-27 -7430,309,237,31,6.0,2,2.0,2,6.0,75,6064550.0,,,1,1978-08-27 -7431,309,206,31,5.0,1,1.0,1,9.0,75,6064230.0,,,1,1978-08-27 -7432,309,162,63,31.0,23,,15,0.0,40,,,,83,1978-08-27 -7433,309,228,55,23.0,0,,31,0.0,0,,,,97,1978-08-27 -7434,309,151,0,33.0,19,,13,0.0,60,,,,20,1978-08-27 -7435,309,242,20,36.0,0,,33,0.0,0,,,,97,1978-08-27 -7436,309,239,56,39.0,0,,32,0.0,0,,,,97,1978-08-27 -7437,310,242,20,36.0,0,,31,0.0,0,,,,97,1978-09-10 -7438,310,176,57,32.0,0,,30,0.0,0,,,,97,1978-09-10 -7439,310,228,55,23.0,0,,29,0.0,0,,,,97,1978-09-10 -7440,310,247,61,18.0,0,,28,0.0,0,,,,81,1978-09-10 -7441,310,246,52,9.0,0,,27,0.0,0,,,,81,1978-09-10 -7442,310,228,52,10.0,0,,26,0.0,0,,,,81,1978-09-10 -7443,310,230,0,7.0,10,,17,0.0,19,,,,99,1978-09-10 -7444,310,229,61,19.0,23,,24,0.0,0,,,,3,1978-09-10 -7445,310,238,0,30.0,21,,23,0.0,0,,,,3,1978-09-10 -7446,310,201,24,3.0,14,,21,0.0,0,,,,3,1978-09-10 -7447,310,237,31,6.0,5,,20,0.0,0,,,,3,1978-09-10 -7448,310,218,3,15.0,3,,19,0.0,6,,,,5,1978-09-10 -7449,310,231,58,37.0,22,,18,0.0,14,,,,5,1978-09-10 -7450,310,243,58,38.0,0,,32,0.0,0,,,,97,1978-09-10 -7451,310,211,31,25.0,0,,25,0.0,0,,,,81,1978-09-10 -7452,310,232,56,16.0,17,,22,0.0,0,,,,3,1978-09-10 -7453,310,222,56,17.0,15,,15,0.0,33,,,,17,1978-09-10 -7454,310,181,33,1.0,4,1.0,1,9.0,40,4024540.0,,,1,1978-09-10 -7455,310,186,33,2.0,7,2.0,2,6.0,40,4026020.0,,,1,1978-09-10 -7456,310,118,20,35.0,12,,16,0.0,28,,,,5,1978-09-10 -7457,310,171,26,26.0,8,4.0,4,3.0,40,4062070.0,,,1,1978-09-10 -7458,310,174,0,8.0,19,5.0,5,2.0,40,4064930.0,,,1,1978-09-10 -7459,310,206,31,5.0,1,6.0,6,1.0,40,4070870.0,,,1,1978-09-10 -7460,310,202,5,12.0,2,7.0,7,0.0,40,4073020.0,,,1,1978-09-10 -7461,310,198,5,11.0,11,3.0,3,4.0,40,4045010.0,,,1,1978-09-10 -7462,310,136,0,29.0,24,9.0,9,0.0,40,4091370.0,,,1,1978-09-10 -7463,310,205,55,22.0,18,10.0,10,0.0,40,4093650.0,,,1,1978-09-10 -7464,310,220,24,4.0,16,11.0,11,0.0,40,4101110.0,,,1,1978-09-10 -7465,310,221,57,20.0,9,12.0,12,0.0,39,,,,11,1978-09-10 -7466,310,177,2,27.0,6,13.0,13,0.0,39,,,,11,1978-09-10 -7467,310,151,0,33.0,20,14.0,14,0.0,39,,,,11,1978-09-10 -7468,310,223,54,14.0,13,8.0,8,0.0,40,4079780.0,,,1,1978-09-10 -7469,311,242,20,36.0,22,16.0,16,0.0,54,,,,15,1978-10-01 -7470,311,231,58,37.0,26,,17,0.0,46,,,,6,1978-10-01 -7471,311,246,52,9.0,25,,18,0.0,43,,,,44,1978-10-01 -7472,311,181,33,1.0,5,,19,0.0,28,,,,5,1978-10-01 -7473,311,206,31,5.0,1,,20,0.0,27,,,,5,1978-10-01 -7474,311,186,33,2.0,7,,21,0.0,25,,,,5,1978-10-01 -7475,311,176,52,10.0,15,,24,0.0,21,,,,7,1978-10-01 -7476,311,202,5,12.0,4,,23,0.0,22,,,,5,1978-10-01 -7477,311,232,56,16.0,14,,25,0.0,1,,,,69,1978-10-01 -7478,311,211,31,25.0,23,,26,0.0,0,,,,8,1978-10-01 -7479,311,212,61,19.0,0,,27,0.0,0,,,,81,1978-10-01 -7480,311,196,31,55.0,8,15.0,15,0.0,55,,,,60,1978-10-01 -7481,311,220,24,4.0,12,,22,0.0,23,,,,36,1978-10-01 -7482,311,222,56,17.0,17,14.0,14,0.0,56,,,,13,1978-10-01 -7483,311,221,57,20.0,11,3.0,3,4.0,59,6094501.0,,,1,1978-10-01 -7484,311,248,57,21.0,20,12.0,12,0.0,58,,,,11,1978-10-01 -7485,311,238,55,23.0,24,13.0,13,0.0,58,,,,11,1978-10-01 -7486,311,198,5,11.0,2,1.0,1,9.0,59,6048800.0,,,1,1978-10-01 -7487,311,177,2,27.0,3,2.0,2,6.0,59,6068539.0,,,1,1978-10-01 -7488,311,223,54,14.0,13,5.0,5,2.0,59,6136889.0,,,1,1978-10-01 -7489,311,174,0,8.0,18,6.0,6,1.0,59,6159010.0,,,1,1978-10-01 -7490,311,218,3,15.0,9,4.0,4,3.0,59,6133807.0,,,1,1978-10-01 -7491,311,205,55,22.0,19,8.0,8,0.0,58,,,,11,1978-10-01 -7492,311,162,63,18.0,21,9.0,9,0.0,58,,,,11,1978-10-01 -7493,311,201,24,3.0,16,10.0,10,0.0,58,,,,11,1978-10-01 -7494,311,171,26,26.0,10,11.0,11,0.0,58,,,,11,1978-10-01 -7495,311,230,0,7.0,6,7.0,7,0.0,58,,,,11,1978-10-01 -7496,312,232,56,16.0,8,,21,0.0,1,,,,3,1978-10-08 -7497,312,162,61,18.0,16,,17,0.0,37,,,,5,1978-10-08 -7498,312,248,57,21.0,20,,18,0.0,16,,,,69,1978-10-08 -7499,312,186,33,2.0,4,,19,0.0,8,,,,3,1978-10-08 -7500,312,181,33,1.0,7,,20,0.0,5,,,,23,1978-10-08 -7501,312,223,54,14.0,6,,22,0.0,0,,,,3,1978-10-08 -7502,312,242,20,36.0,0,,27,0.0,0,,,,97,1978-10-08 -7503,312,212,61,19.0,0,,24,0.0,0,,,,81,1978-10-08 -7504,312,231,58,37.0,0,,25,0.0,0,,,,81,1978-10-08 -7505,312,246,52,9.0,0,,28,0.0,0,,,,97,1978-10-08 -7506,312,211,31,25.0,0,,26,0.0,0,,,,81,1978-10-08 -7507,312,196,31,55.0,1,,16,0.0,49,,,,44,1978-10-08 -7508,312,222,56,17.0,0,,23,0.0,0,,,,81,1978-10-08 -7509,312,230,0,7.0,19,,15,0.0,51,,,,20,1978-10-08 -7510,312,221,57,20.0,2,2.0,2,6.0,70,7082568.0,,,1,1978-10-08 -7511,312,176,52,10.0,21,,13,0.0,58,,,,55,1978-10-08 -7512,312,171,26,26.0,10,,14,0.0,52,,,,7,1978-10-08 -7513,312,202,5,12.0,3,1.0,1,9.0,70,7069196.0,,,1,1978-10-08 -7514,312,198,5,11.0,11,3.0,3,4.0,70,7088604.0,,,1,1978-10-08 -7515,312,220,24,4.0,13,5.0,5,2.0,70,7097754.0,,,1,1978-10-08 -7516,312,205,55,22.0,15,6.0,6,1.0,70,7123672.0,,,1,1978-10-08 -7517,312,118,20,35.0,12,4.0,4,3.0,70,7093863.0,,,1,1978-10-08 -7518,312,174,0,8.0,17,8.0,8,0.0,70,7155756.0,,,1,1978-10-08 -7519,312,177,2,27.0,5,9.0,9,0.0,70,7158138.0,,,1,1978-10-08 -7520,312,206,31,5.0,9,10.0,10,0.0,69,,,,11,1978-10-08 -7521,312,136,33,66.0,14,11.0,11,0.0,69,,,,11,1978-10-08 -7522,312,218,3,15.0,22,12.0,12,0.0,65,,,,15,1978-10-08 -7523,312,201,24,3.0,18,7.0,7,0.0,70,7150446.0,,,1,1978-10-08 -7524,313,181,201,5.0,23,,18,0.0,8,,,,69,1979-01-21 -7525,313,135,56,17.0,21,,14,0.0,42,,,,7,1979-01-21 -7526,313,230,57,20.0,18,,15,0.0,41,,,,10,1979-01-21 -7527,313,196,24,4.0,4,,16,0.0,15,,,,5,1979-01-21 -7528,313,218,3,15.0,12,,17,0.0,15,,,,5,1979-01-21 -7529,313,162,3,16.0,25,,19,0.0,6,,,,5,1979-01-21 -7530,313,118,20,29.0,13,,25,0.0,0,,,,3,1979-01-21 -7531,313,201,24,3.0,8,,21,0.0,0,,,,4,1979-01-21 -7532,313,174,0,8.0,9,,22,0.0,0,,,,4,1979-01-21 -7533,313,136,201,6.0,20,,23,0.0,0,,,,4,1979-01-21 -7534,313,231,58,24.0,22,,24,0.0,0,,,,4,1979-01-21 -7535,313,232,52,9.0,0,,26,0.0,0,,,,54,1979-01-21 -7536,313,221,5,11.0,5,,20,0.0,0,,,,4,1979-01-21 -7537,313,211,31,31.0,19,,13,0.0,46,,,,22,1979-01-21 -7538,313,205,55,22.0,24,11.0,11,0.0,51,,,,12,1979-01-21 -7539,313,222,2,28.0,17,10.0,10,0.0,51,,,,12,1979-01-21 -7540,313,177,2,27.0,15,9.0,9,0.0,51,,,,12,1979-01-21 -7541,313,199,20,30.0,14,8.0,8,0.0,51,,,,12,1979-01-21 -7542,313,172,56,18.0,16,7.0,7,0.0,52,,,,11,1979-01-21 -7543,313,223,54,14.0,11,6.0,6,1.0,52,,,,11,1979-01-21 -7544,313,206,31,1.0,7,5.0,5,2.0,52,,,,11,1979-01-21 -7545,313,220,26,25.0,2,4.0,4,3.0,53,5864930.0,,,1,1979-01-21 -7546,313,186,0,7.0,6,3.0,3,4.0,53,5852020.0,,,1,1979-01-21 -7547,313,198,31,2.0,3,2.0,2,6.0,53,5778150.0,,,1,1979-01-21 -7548,313,171,26,26.0,1,1.0,1,9.0,53,5763210.0,,,1,1979-01-21 -7549,313,202,5,12.0,10,,12,0.0,48,,,,5,1979-01-21 -7550,314,177,2,27.0,13,,16,0.0,33,,,,69,1979-02-04 -7551,314,232,52,9.0,24,,17,0.0,31,,,,38,1979-02-04 -7552,314,162,3,16.0,11,,18,0.0,28,,,,20,1979-02-04 -7553,314,230,57,20.0,10,,19,0.0,7,,,,38,1979-02-04 -7554,314,174,0,8.0,18,,20,0.0,7,,,,4,1979-02-04 -7555,314,222,2,28.0,17,15.0,15,0.0,38,,,,12,1979-02-04 -7556,314,136,201,6.0,22,,22,0.0,5,,,,3,1979-02-04 -7557,314,206,31,1.0,4,,23,0.0,2,,,,95,1979-02-04 -7558,314,196,24,4.0,15,,24,0.0,0,,,,10,1979-02-04 -7559,314,211,31,31.0,0,,25,0.0,0,,,,81,1979-02-04 -7560,314,231,58,24.0,0,,26,0.0,0,,,,81,1979-02-04 -7561,314,181,201,5.0,12,,21,0.0,5,,,,6,1979-02-04 -7562,314,135,56,17.0,21,14.0,14,0.0,39,,,,11,1979-02-04 -7563,314,205,55,22.0,23,13.0,13,0.0,39,,,,11,1979-02-04 -7564,314,201,24,3.0,8,4.0,4,3.0,40,6095520.0,,,1,1979-02-04 -7565,314,223,54,14.0,9,11.0,11,0.0,39,,,,11,1979-02-04 -7566,314,218,3,15.0,7,10.0,10,0.0,39,,,,11,1979-02-04 -7567,314,118,20,29.0,16,9.0,9,0.0,39,,,,11,1979-02-04 -7568,314,186,0,7.0,14,8.0,8,0.0,39,,,,11,1979-02-04 -7569,314,199,20,30.0,19,7.0,7,0.0,39,,,,11,1979-02-04 -7570,314,221,5,11.0,6,6.0,6,1.0,39,,,,11,1979-02-04 -7571,314,202,5,12.0,5,5.0,5,2.0,39,,,,11,1979-02-04 -7572,314,198,31,2.0,3,3.0,3,4.0,40,6053780.0,,,1,1979-02-04 -7573,314,220,26,25.0,2,2.0,2,6.0,40,6014920.0,,,1,1979-02-04 -7574,314,171,26,26.0,1,1.0,1,9.0,40,6009640.0,,,1,1979-02-04 -7575,314,172,56,18.0,20,12.0,12,0.0,39,,,,11,1979-02-04 -7576,315,171,26,26.0,6,,20,0.0,45,,,,3,1979-03-03 -7577,315,218,3,15.0,1,,19,0.0,47,,,,5,1979-03-03 -7578,315,230,57,20.0,13,8.0,8,0.0,77,,,,11,1979-03-03 -7579,315,201,24,3.0,7,,21,0.0,25,,,,37,1979-03-03 -7580,315,232,52,9.0,24,,18,0.0,57,,,,3,1979-03-03 -7581,315,172,56,18.0,15,,22,0.0,16,,,,3,1979-03-03 -7582,315,186,0,7.0,14,,17,0.0,61,,,,80,1979-03-03 -7583,315,135,56,17.0,21,,24,0.0,2,,,,3,1979-03-03 -7584,315,205,55,22.0,0,,25,0.0,0,,,,81,1979-03-03 -7585,315,231,58,24.0,0,,26,0.0,0,,,,81,1979-03-03 -7586,315,181,201,5.0,4,6.0,6,1.0,77,,,,11,1979-03-03 -7587,315,220,26,25.0,5,,23,0.0,4,,,,3,1979-03-03 -7588,315,177,2,27.0,19,,16,0.0,63,,,,22,1979-03-03 -7589,315,136,201,6.0,12,7.0,7,0.0,77,,,,11,1979-03-03 -7590,315,211,31,31.0,23,,14,0.0,71,,,,5,1979-03-03 -7591,315,222,2,28.0,22,9.0,9,0.0,76,,,,12,1979-03-03 -7592,315,202,5,12.0,3,1.0,1,9.0,78,6109960.0,,,1,1979-03-03 -7593,315,221,5,11.0,2,2.0,2,6.0,78,6113380.0,,,1,1979-03-03 -7594,315,196,24,4.0,9,3.0,3,4.0,78,6132070.0,,,1,1979-03-03 -7595,315,206,31,1.0,8,4.0,4,3.0,78,6137840.0,,,1,1979-03-03 -7596,315,162,3,16.0,10,,15,0.0,67,,,,27,1979-03-03 -7597,315,174,0,8.0,17,10.0,10,0.0,75,,,,13,1979-03-03 -7598,315,198,31,2.0,11,5.0,5,2.0,78,6176930.0,,,1,1979-03-03 -7599,315,223,54,14.0,18,13.0,13,0.0,74,,,,14,1979-03-03 -7600,315,118,20,29.0,16,11.0,11,0.0,75,,,,13,1979-03-03 -7601,315,199,20,30.0,20,12.0,12,0.0,74,,,,14,1979-03-03 -7602,316,218,3,15.0,0,,26,0.0,0,,,,54,1979-04-08 -7603,316,162,3,16.0,0,,25,0.0,0,,,,54,1979-04-08 -7604,316,174,0,8.0,19,,24,0.0,0,,,,4,1979-04-08 -7605,316,181,201,5.0,11,,23,0.0,0,,,,3,1979-04-08 -7606,316,222,2,28.0,15,,15,0.0,48,,,,5,1979-04-08 -7607,316,230,57,20.0,8,,22,0.0,0,,,,7,1979-04-08 -7608,316,171,26,26.0,5,,21,0.0,8,,,,23,1979-04-08 -7609,316,231,58,24.0,22,,20,0.0,13,,,,5,1979-04-08 -7610,316,223,54,14.0,16,,19,0.0,19,,,,7,1979-04-08 -7611,316,118,20,29.0,9,,17,0.0,40,,,,23,1979-04-08 -7612,316,135,56,17.0,14,,16,0.0,47,,,,22,1979-04-08 -7613,316,232,52,9.0,21,,14,0.0,49,,,,2,1979-04-08 -7614,316,198,31,2.0,2,,18,0.0,21,,,,7,1979-04-08 -7615,316,205,55,22.0,24,,12,0.0,69,,,,3,1979-04-08 -7616,316,186,0,7.0,18,,13,0.0,62,,,,98,1979-04-08 -7617,316,221,5,11.0,3,2.0,2,6.0,80,6654780.0,,,1,1979-04-08 -7618,316,177,2,27.0,10,3.0,3,4.0,80,6685090.0,,,1,1979-04-08 -7619,316,206,31,1.0,6,4.0,4,3.0,80,6689730.0,,,1,1979-04-08 -7620,316,202,5,12.0,1,1.0,1,9.0,80,6625400.0,,,1,1979-04-08 -7621,316,196,24,4.0,7,6.0,6,1.0,79,,,,11,1979-04-08 -7622,316,220,26,25.0,4,5.0,5,2.0,80,6708920.0,,,1,1979-04-08 -7623,316,136,201,6.0,12,8.0,8,0.0,78,,,,12,1979-04-08 -7624,316,199,20,30.0,13,9.0,9,0.0,78,,,,12,1979-04-08 -7625,316,201,24,3.0,17,,10,0.0,72,,,,2,1979-04-08 -7626,316,211,31,31.0,23,,11,0.0,71,,,,3,1979-04-08 -7627,316,172,56,18.0,20,7.0,7,0.0,78,,,,12,1979-04-08 -7628,317,177,2,27.0,13,,17,0.0,54,,,,6,1979-04-29 -7629,317,172,56,18.0,22,,18,0.0,52,,,,5,1979-04-29 -7630,317,222,2,28.0,14,,19,0.0,32,,,,5,1979-04-29 -7631,317,230,57,20.0,15,,20,0.0,26,,,,23,1979-04-29 -7632,317,218,3,15.0,9,,21,0.0,21,,,,101,1979-04-29 -7633,317,233,59,36.0,0,,27,0.0,0,,,,81,1979-04-29 -7634,317,171,26,26.0,1,,23,0.0,15,,,,5,1979-04-29 -7635,317,136,201,6.0,7,,24,0.0,15,,,,98,1979-04-29 -7636,317,205,55,22.0,0,,25,0.0,0,,,,81,1979-04-29 -7637,317,231,58,24.0,0,,26,0.0,0,,,,81,1979-04-29 -7638,317,211,31,31.0,23,,16,0.0,58,,,,5,1979-04-29 -7639,317,186,0,7.0,18,,22,0.0,21,,,,5,1979-04-29 -7640,317,181,201,5.0,6,,15,0.0,63,,,,47,1979-04-29 -7641,317,199,20,30.0,17,8.0,8,0.0,75,6026680.0,,,1,1979-04-29 -7642,317,174,0,8.0,20,13.0,13,0.0,72,,,,13,1979-04-29 -7643,317,232,52,9.0,21,14.0,14,0.0,69,,,,16,1979-04-29 -7644,317,220,26,25.0,2,1.0,1,9.0,75,5951840.0,,,1,1979-04-29 -7645,317,198,31,2.0,8,2.0,2,6.0,75,5972780.0,,,1,1979-04-29 -7646,317,206,31,1.0,4,3.0,3,4.0,75,5979150.0,,,1,1979-04-29 -7647,317,221,5,11.0,5,4.0,4,3.0,75,5980520.0,,,1,1979-04-29 -7648,317,196,24,4.0,12,5.0,5,2.0,75,5982230.0,,,1,1979-04-29 -7649,317,202,5,12.0,3,7.0,7,0.0,75,6004150.0,,,1,1979-04-29 -7650,317,162,3,16.0,11,9.0,9,0.0,74,,,,11,1979-04-29 -7651,317,118,20,29.0,16,10.0,10,0.0,74,,,,11,1979-04-29 -7652,317,223,54,14.0,19,11.0,11,0.0,74,,,,11,1979-04-29 -7653,317,135,56,17.0,24,12.0,12,0.0,73,,,,12,1979-04-29 -7654,317,201,24,3.0,10,6.0,6,1.0,75,6000270.0,,,1,1979-04-29 -7655,318,233,59,36.0,0,,28,0.0,0,,,,81,1979-05-13 -7656,318,205,55,22.0,0,,27,0.0,0,,,,81,1979-05-13 -7657,318,231,58,24.0,0,,26,0.0,0,,,,81,1979-05-13 -7658,318,174,0,8.0,0,,25,0.0,0,,,,81,1979-05-13 -7659,318,222,2,28.0,8,,24,0.0,1,,,,3,1979-05-13 -7660,318,218,3,15.0,17,,23,0.0,13,,,,101,1979-05-13 -7661,318,211,31,31.0,15,,22,0.0,13,,,,7,1979-05-13 -7662,318,199,20,30.0,22,,21,0.0,17,,,,20,1979-05-13 -7663,318,162,3,16.0,18,,18,0.0,22,,,,101,1979-05-13 -7664,318,196,24,4.0,11,11.0,11,0.0,67,,,,13,1979-05-13 -7665,318,151,49,35.0,14,,19,0.0,21,,,,3,1979-05-13 -7666,318,181,201,5.0,13,,17,0.0,23,,,,5,1979-05-13 -7667,318,136,201,6.0,3,,16,0.0,23,,,,5,1979-05-13 -7668,318,177,2,27.0,4,,14,0.0,39,,,,10,1979-05-13 -7669,318,230,57,20.0,9,,13,0.0,40,,,,3,1979-05-13 -7670,318,220,26,25.0,2,,12,0.0,46,,,,3,1979-05-13 -7671,318,172,56,18.0,24,,20,0.0,21,,,,3,1979-05-13 -7672,318,206,31,1.0,5,,15,0.0,27,,,,23,1979-05-13 -7673,318,223,54,14.0,23,9.0,9,0.0,68,,,,12,1979-05-13 -7674,318,135,56,17.0,21,10.0,10,0.0,68,,,,12,1979-05-13 -7675,318,221,5,11.0,7,1.0,1,9.0,70,5999530.0,,,1,1979-05-13 -7676,318,171,26,26.0,1,2.0,2,6.0,70,6014890.0,,,1,1979-05-13 -7677,318,201,24,3.0,12,3.0,3,4.0,70,6034700.0,,,1,1979-05-13 -7678,318,198,31,2.0,10,4.0,4,3.0,70,6046020.0,,,1,1979-05-13 -7679,318,118,20,29.0,16,5.0,5,2.0,70,6063840.0,,,1,1979-05-13 -7680,318,186,0,7.0,19,6.0,6,1.0,70,6065380.0,,,1,1979-05-13 -7681,318,202,5,12.0,6,7.0,7,0.0,69,,,,11,1979-05-13 -7682,318,232,52,9.0,20,8.0,8,0.0,69,,,,11,1979-05-13 -7683,319,223,54,14.0,17,,17,0.0,17,,,,5,1979-05-27 -7684,319,206,31,1.0,13,,16,0.0,21,,,,22,1979-05-27 -7685,319,162,3,16.0,19,,18,0.0,8,,,,3,1979-05-27 -7686,319,230,57,20.0,10,,19,0.0,4,,,,7,1979-05-27 -7687,319,118,20,29.0,15,,20,0.0,4,,,,22,1979-05-27 -7688,319,172,56,18.0,0,,21,0.0,0,,,,81,1979-05-27 -7689,319,221,5,11.0,1,1.0,1,9.0,76,6922480.0,,,1,1979-05-27 -7690,319,135,56,17.0,0,,23,0.0,0,,,,81,1979-05-27 -7691,319,205,55,22.0,0,,24,0.0,0,,,,81,1979-05-27 -7692,319,233,58,24.0,0,,25,0.0,0,,,,97,1979-05-27 -7693,319,201,24,3.0,7,,15,0.0,21,,,,3,1979-05-27 -7694,319,174,0,8.0,0,,22,0.0,0,,,,81,1979-05-27 -7695,319,181,201,5.0,4,,14,0.0,21,,,,3,1979-05-27 -7696,319,196,24,4.0,6,,12,0.0,34,,,,22,1979-05-27 -7697,319,220,26,25.0,3,5.0,5,2.0,75,,,,5,1979-05-27 -7698,319,177,2,27.0,9,,11,0.0,43,,,,38,1979-05-27 -7699,319,202,5,12.0,2,,10,0.0,54,,,,7,1979-05-27 -7700,319,171,26,26.0,5,,9,0.0,55,,,,6,1979-05-27 -7701,319,218,3,15.0,20,,8,0.0,68,,,,18,1979-05-27 -7702,319,136,201,6.0,18,,7,0.0,68,,,,7,1979-05-27 -7703,319,199,20,30.0,8,6.0,6,1.0,69,,,,17,1979-05-27 -7704,319,232,52,9.0,12,,13,0.0,30,,,,36,1979-05-27 -7705,319,186,0,7.0,14,4.0,4,3.0,76,6963790.0,,,1,1979-05-27 -7706,319,198,31,2.0,11,3.0,3,4.0,76,6931050.0,,,1,1979-05-27 -7707,319,222,2,28.0,16,2.0,2,6.0,76,6922920.0,,,1,1979-05-27 -7708,320,174,0,8.0,20,10.0,10,0.0,78,,,,12,1979-07-01 -7709,320,186,0,7.0,15,11.0,11,0.0,78,,,,12,1979-07-01 -7710,320,176,57,20.0,16,9.0,9,0.0,79,,,,11,1979-07-01 -7711,320,118,20,29.0,19,14.0,14,0.0,77,,,,13,1979-07-01 -7712,320,199,20,30.0,22,15.0,15,0.0,75,,,,15,1979-07-01 -7713,320,198,31,2.0,13,13.0,13,0.0,77,,,,13,1979-07-01 -7714,320,171,26,26.0,8,8.0,8,0.0,79,,,,11,1979-07-01 -7715,320,211,31,31.0,23,12.0,12,0.0,78,,,,12,1979-07-01 -7716,320,222,2,28.0,9,6.0,6,1.0,80,5785930.0,,,1,1979-07-01 -7717,320,196,24,4.0,10,5.0,5,2.0,80,5784930.0,,,1,1979-07-01 -7718,320,177,2,27.0,7,4.0,4,3.0,80,5757030.0,,,1,1979-07-01 -7719,320,162,3,16.0,2,3.0,3,4.0,80,5735250.0,,,1,1979-07-01 -7720,320,202,5,12.0,3,2.0,2,6.0,80,5735010.0,,,1,1979-07-01 -7721,320,218,3,15.0,1,1.0,1,9.0,80,5720420.0,,,1,1979-07-01 -7722,320,172,56,18.0,24,16.0,16,0.0,75,,,,15,1979-07-01 -7723,320,221,5,11.0,5,7.0,7,0.0,79,,,,11,1979-07-01 -7724,320,151,49,35.0,17,17.0,17,0.0,75,,,,15,1979-07-01 -7725,320,206,31,1.0,12,,22,0.0,51,,,,23,1979-07-01 -7726,320,201,24,3.0,11,,19,0.0,71,,,,22,1979-07-01 -7727,320,223,54,14.0,18,,20,0.0,53,,,,5,1979-07-01 -7728,320,136,201,6.0,4,,21,0.0,52,,,,3,1979-07-01 -7729,320,234,26,25.0,14,,23,0.0,45,,,,5,1979-07-01 -7730,320,181,201,5.0,6,,24,0.0,23,,,,20,1979-07-01 -7731,320,232,52,9.0,0,,25,0.0,0,,,,54,1979-07-01 -7732,320,235,55,22.0,0,,26,0.0,0,,,,81,1979-07-01 -7733,320,231,58,24.0,0,,27,0.0,0,,,,81,1979-07-01 -7734,320,135,56,17.0,21,18.0,18,0.0,73,,,,17,1979-07-01 -7735,321,118,20,29.0,19,,15,0.0,45,,,,6,1979-07-14 -7736,321,171,26,26.0,10,,16,0.0,44,,,,5,1979-07-14 -7737,321,176,57,20.0,14,,17,0.0,44,,,,69,1979-07-14 -7738,321,177,2,27.0,1,,18,0.0,38,,,,103,1979-07-14 -7739,321,199,20,30.0,20,,19,0.0,37,,,,6,1979-07-14 -7740,321,136,201,6.0,3,,24,0.0,1,,,,20,1979-07-14 -7741,321,218,3,15.0,2,,21,0.0,21,,,,101,1979-07-14 -7742,321,181,201,5.0,6,,22,0.0,12,,,,23,1979-07-14 -7743,321,206,31,1.0,9,,23,0.0,3,,,,36,1979-07-14 -7744,321,232,52,9.0,0,,25,0.0,0,,,,81,1979-07-14 -7745,321,231,58,24.0,0,,26,0.0,0,,,,81,1979-07-14 -7746,321,223,54,14.0,22,,20,0.0,25,,,,5,1979-07-14 -7747,321,202,5,12.0,13,14.0,14,0.0,63,,,,69,1979-07-14 -7748,321,172,56,18.0,12,12.0,12,0.0,65,,,,13,1979-07-14 -7749,321,135,56,17.0,21,11.0,11,0.0,65,,,,13,1979-07-14 -7750,321,222,2,28.0,4,1.0,1,9.0,68,5171170.0,,,1,1979-07-14 -7751,321,235,55,22.0,23,13.0,13,0.0,65,,,,13,1979-07-14 -7752,321,196,24,4.0,16,3.0,3,4.0,67,,,,11,1979-07-14 -7753,321,186,0,7.0,7,4.0,4,3.0,67,,,,11,1979-07-14 -7754,321,221,5,11.0,11,5.0,5,2.0,67,,,,11,1979-07-14 -7755,321,162,3,16.0,5,2.0,2,6.0,68,5195450.0,,,1,1979-07-14 -7756,321,174,0,8.0,18,7.0,7,0.0,66,,,,60,1979-07-14 -7757,321,198,31,2.0,8,8.0,8,0.0,66,,,,12,1979-07-14 -7758,321,211,31,31.0,26,9.0,9,0.0,66,,,,12,1979-07-14 -7759,321,201,24,3.0,15,10.0,10,0.0,66,,,,12,1979-07-14 -7760,321,234,26,25.0,17,6.0,6,1.0,67,,,,11,1979-07-14 -7761,322,218,3,15.0,1,,21,0.0,7,,,,20,1979-07-29 -7762,322,223,54,14.0,22,,22,0.0,4,,,,10,1979-07-29 -7763,322,198,31,2.0,13,,23,0.0,1,,,,3,1979-07-29 -7764,322,232,52,9.0,23,,24,0.0,0,,,,22,1979-07-29 -7765,322,235,55,22.0,0,,25,0.0,0,,,,81,1979-07-29 -7766,322,231,58,24.0,0,,26,0.0,0,,,,81,1979-07-29 -7767,322,162,3,16.0,10,,20,0.0,9,,,,27,1979-07-29 -7768,322,176,57,20.0,17,,15,0.0,29,,,,5,1979-07-29 -7769,322,211,31,31.0,24,,18,0.0,22,,,,64,1979-07-29 -7770,322,174,0,8.0,15,,14,0.0,30,,,,22,1979-07-29 -7771,322,118,20,29.0,19,,13,0.0,34,,,,27,1979-07-29 -7772,322,136,201,6.0,4,12.0,12,0.0,42,,,,5,1979-07-29 -7773,322,172,56,18.0,21,11.0,11,0.0,43,,,,12,1979-07-29 -7774,322,135,56,17.0,20,10.0,10,0.0,44,,,,11,1979-07-29 -7775,322,201,24,3.0,8,9.0,9,0.0,44,,,,11,1979-07-29 -7776,322,202,5,12.0,9,8.0,8,0.0,44,,,,11,1979-07-29 -7777,322,208,24,4.0,16,7.0,7,0.0,44,,,,11,1979-07-29 -7778,322,199,20,30.0,18,6.0,6,1.0,44,,,,11,1979-07-29 -7779,322,186,0,7.0,12,5.0,5,2.0,45,5186630.0,,,1,1979-07-29 -7780,322,221,5,11.0,5,4.0,4,3.0,45,5120030.0,,,1,1979-07-29 -7781,322,171,26,26.0,3,3.0,3,4.0,45,5107220.0,,,1,1979-07-29 -7782,322,222,2,28.0,6,2.0,2,6.0,45,5091740.0,,,1,1979-07-29 -7783,322,234,26,25.0,14,,17,0.0,24,,,,27,1979-07-29 -7784,322,181,201,5.0,7,,16,0.0,27,,,,5,1979-07-29 -7785,322,206,31,1.0,11,,19,0.0,16,,,,7,1979-07-29 -7786,322,177,2,27.0,2,1.0,1,9.0,45,5088830.0,,,1,1979-07-29 -7787,323,177,2,27.0,2,1.0,1,9.0,54,5258010.0,,,1,1979-08-12 -7788,323,171,26,26.0,8,3.0,3,4.0,54,5304780.0,,,1,1979-08-12 -7789,323,202,5,12.0,5,2.0,2,6.0,54,5294060.0,,,1,1979-08-12 -7790,323,231,58,24.0,0,,26,0.0,0,,,,81,1979-08-12 -7791,323,211,31,31.0,0,,25,0.0,0,,,,81,1979-08-12 -7792,323,206,31,1.0,15,,24,0.0,0,,,,8,1979-08-12 -7793,323,199,20,30.0,20,,23,0.0,1,,,,5,1979-08-12 -7794,323,135,56,17.0,23,,22,0.0,3,,,,3,1979-08-12 -7795,323,176,57,20.0,19,,20,0.0,15,,,,10,1979-08-12 -7796,323,218,3,15.0,3,,19,0.0,16,,,,6,1979-08-12 -7797,323,198,31,2.0,17,,18,0.0,22,,,,64,1979-08-12 -7798,323,234,26,25.0,21,,17,0.0,26,,,,5,1979-08-12 -7799,323,232,52,9.0,18,,16,0.0,28,,,,5,1979-08-12 -7800,323,223,54,14.0,12,,21,0.0,15,,,,23,1979-08-12 -7801,323,172,56,18.0,22,,14,0.0,34,,,,5,1979-08-12 -7802,323,118,20,29.0,13,,13,0.0,34,,,,22,1979-08-12 -7803,323,235,55,22.0,24,,12,0.0,42,,,,22,1979-08-12 -7804,323,181,201,5.0,4,,11,0.0,45,,,,5,1979-08-12 -7805,323,174,0,8.0,14,10.0,10,0.0,53,,,,11,1979-08-12 -7806,323,221,5,11.0,9,4.0,4,3.0,54,5305220.0,,,1,1979-08-12 -7807,323,186,0,7.0,16,9.0,9,0.0,53,,,,11,1979-08-12 -7808,323,205,24,4.0,11,8.0,8,0.0,53,,,,11,1979-08-12 -7809,323,201,24,3.0,10,7.0,7,0.0,53,,,,11,1979-08-12 -7810,323,162,3,16.0,1,6.0,6,1.0,53,,,,11,1979-08-12 -7811,323,222,2,28.0,6,5.0,5,2.0,54,5306930.0,,,1,1979-08-12 -7812,323,136,201,6.0,7,,15,0.0,32,,,,5,1979-08-12 -7813,324,206,31,1.0,17,,17,0.0,9,,,,22,1979-08-26 -7814,324,118,20,29.0,19,,18,0.0,7,,,,23,1979-08-26 -7815,324,174,0,8.0,14,,19,0.0,6,,,,5,1979-08-26 -7816,324,181,201,5.0,9,,20,0.0,4,,,,54,1979-08-26 -7817,324,231,58,24.0,0,,26,0.0,0,,,,81,1979-08-26 -7818,324,198,31,2.0,13,,22,0.0,1,,,,22,1979-08-26 -7819,324,162,3,16.0,1,,23,0.0,1,,,,22,1979-08-26 -7820,324,222,2,28.0,3,,24,0.0,0,,,,3,1979-08-26 -7821,324,235,55,22.0,0,,25,0.0,0,,,,81,1979-08-26 -7822,324,232,52,9.0,15,,15,0.0,19,,,,7,1979-08-26 -7823,324,223,54,14.0,21,,21,0.0,2,,,,10,1979-08-26 -7824,324,196,24,4.0,16,,14,0.0,20,,,,20,1979-08-26 -7825,324,135,56,17.0,23,,16,0.0,12,,,,6,1979-08-26 -7826,324,218,3,15.0,4,,12,0.0,26,,,,8,1979-08-26 -7827,324,186,0,7.0,12,,13,0.0,22,,,,5,1979-08-26 -7828,324,177,2,27.0,2,1.0,1,9.0,75,6079775.0,,,1,1979-08-26 -7829,324,221,5,11.0,5,2.0,2,6.0,75,6101558.0,,,1,1979-08-26 -7830,324,171,26,26.0,7,3.0,3,4.0,75,6143028.0,,,1,1979-08-26 -7831,324,234,26,25.0,20,5.0,5,2.0,74,,,,11,1979-08-26 -7832,324,136,201,6.0,11,4.0,4,3.0,74,,,,11,1979-08-26 -7833,324,211,31,31.0,24,7.0,7,0.0,73,,,,12,1979-08-26 -7834,324,201,24,3.0,10,,8,0.0,51,,,,22,1979-08-26 -7835,324,202,5,12.0,6,,9,0.0,49,,,,27,1979-08-26 -7836,324,172,56,18.0,22,,10,0.0,40,,,,7,1979-08-26 -7837,324,176,57,20.0,8,,11,0.0,33,,,,5,1979-08-26 -7838,324,199,20,30.0,18,6.0,6,1.0,73,,,,12,1979-08-26 -7839,325,186,0,7.0,19,,21,0.0,13,,,,3,1979-09-09 -7840,325,172,56,18.0,24,,18,0.0,33,,,,8,1979-09-09 -7841,325,151,49,35.0,18,,19,0.0,28,,,,20,1979-09-09 -7842,325,162,3,16.0,2,,20,0.0,13,,,,5,1979-09-09 -7843,325,174,0,8.0,14,,22,0.0,3,,,,5,1979-09-09 -7844,325,211,60,31.0,0,,28,0.0,0,,,,81,1979-09-09 -7845,325,136,201,6.0,8,,24,0.0,1,,,,3,1979-09-09 -7846,325,135,56,17.0,0,,25,0.0,0,,,,81,1979-09-09 -7847,325,175,55,22.0,0,,26,0.0,0,,,,81,1979-09-09 -7848,325,231,58,24.0,0,,27,0.0,0,,,,81,1979-09-09 -7849,325,234,26,25.0,11,,17,0.0,40,,,,5,1979-09-09 -7850,325,199,20,30.0,21,,23,0.0,3,,,,22,1979-09-09 -7851,325,176,57,20.0,23,,16,0.0,41,,,,5,1979-09-09 -7852,325,201,24,3.0,12,10.0,10,0.0,49,,,,11,1979-09-09 -7853,325,218,3,15.0,1,14.0,14,0.0,45,,,,5,1979-09-09 -7854,325,118,20,29.0,17,13.0,13,0.0,47,,,,13,1979-09-09 -7855,325,229,49,36.0,22,12.0,12,0.0,49,,,,11,1979-09-09 -7856,325,232,52,9.0,15,11.0,11,0.0,49,,,,11,1979-09-09 -7857,325,177,2,27.0,4,9.0,9,0.0,49,,,,11,1979-09-09 -7858,325,223,54,14.0,20,8.0,8,0.0,49,,,,11,1979-09-09 -7859,325,198,31,2.0,13,7.0,7,0.0,50,5004360.0,,,1,1979-09-09 -7860,325,206,31,1.0,10,5.0,5,2.0,50,4979920.0,,,1,1979-09-09 -7861,325,181,201,5.0,9,4.0,4,3.0,50,4974620.0,,,1,1979-09-09 -7862,325,222,2,28.0,6,3.0,3,4.0,50,4925000.0,,,1,1979-09-09 -7863,325,202,5,12.0,5,2.0,2,6.0,50,4920680.0,,,1,1979-09-09 -7864,325,221,5,11.0,3,1.0,1,9.0,50,4920220.0,,,1,1979-09-09 -7865,325,171,26,26.0,7,,15,0.0,41,,,,5,1979-09-09 -7866,325,196,24,4.0,16,6.0,6,1.0,50,4981770.0,,,1,1979-09-09 -7867,326,175,55,22.0,0,,26,0.0,0,,,,81,1979-09-30 -7868,326,176,57,20.0,0,,27,0.0,0,,,,81,1979-09-30 -7869,326,177,2,27.0,1,1.0,1,9.0,72,6726892.0,,,1,1979-09-30 -7870,326,199,20,30.0,0,,25,0.0,0,,,,81,1979-09-30 -7871,326,232,52,9.0,12,,23,0.0,14,,,,3,1979-09-30 -7872,326,162,3,16.0,8,,22,0.0,14,,,,3,1979-09-30 -7873,326,174,0,8.0,20,,21,0.0,19,,,,5,1979-09-30 -7874,326,118,20,29.0,14,,20,0.0,20,,,,20,1979-09-30 -7875,326,198,31,2.0,11,,19,0.0,23,,,,22,1979-09-30 -7876,326,172,56,18.0,23,,18,0.0,24,,,,80,1979-09-30 -7877,326,218,3,15.0,7,,17,0.0,24,,,,23,1979-09-30 -7878,326,211,60,31.0,22,,16,0.0,26,,,,83,1979-09-30 -7879,326,205,24,33.0,24,,15,0.0,28,,,,5,1979-09-30 -7880,326,181,179,5.0,0,,30,0.0,0,,,,54,1979-09-30 -7881,326,231,58,24.0,0,,29,0.0,0,,,,81,1979-09-30 -7882,326,236,54,19.0,0,,28,0.0,0,,,,81,1979-09-30 -7883,326,171,26,26.0,5,,24,0.0,10,,,,5,1979-09-30 -7884,326,234,26,25.0,16,,13,0.0,47,,,,6,1979-09-30 -7885,326,136,179,6.0,4,,11,0.0,61,,,,6,1979-09-30 -7886,326,206,31,1.0,10,10.0,10,0.0,66,,,,60,1979-09-30 -7887,326,223,54,14.0,15,8.0,8,0.0,67,,,,15,1979-09-30 -7888,326,216,179,5.0,17,7.0,7,0.0,68,,,,14,1979-09-30 -7889,326,186,0,7.0,17,6.0,6,1.0,70,,,,12,1979-09-30 -7890,326,135,56,17.0,21,9.0,9,0.0,67,,,,15,1979-09-30 -7891,326,221,5,11.0,9,4.0,4,3.0,71,,,,11,1979-09-30 -7892,326,222,2,28.0,3,3.0,3,4.0,72,6800548.0,,,1,1979-09-30 -7893,326,202,5,12.0,2,2.0,2,6.0,72,6727972.0,,,1,1979-09-30 -7894,326,196,24,4.0,13,,14,0.0,33,,,,5,1979-09-30 -7895,326,229,49,36.0,18,,12,0.0,52,,,,69,1979-09-30 -7896,326,201,24,3.0,6,5.0,5,2.0,71,,,,11,1979-09-30 -7897,327,171,26,26.0,4,,22,0.0,3,,,,20,1979-10-07 -7898,327,231,58,24.0,0,,30,0.0,0,,,,81,1979-10-07 -7899,327,236,54,19.0,0,,29,0.0,0,,,,81,1979-10-07 -7900,327,211,60,31.0,0,,28,0.0,0,,,,81,1979-10-07 -7901,327,199,20,30.0,0,,26,0.0,0,,,,81,1979-10-07 -7902,327,229,49,36.0,0,,25,0.0,0,,,,81,1979-10-07 -7903,327,151,49,35.0,18,,24,0.0,0,,,,20,1979-10-07 -7904,327,234,26,25.0,24,,23,0.0,2,,,,20,1979-10-07 -7905,327,198,31,2.0,6,,21,0.0,6,,,,20,1979-10-07 -7906,327,135,56,17.0,0,,27,0.0,0,,,,81,1979-10-07 -7907,327,196,24,4.0,11,,19,0.0,18,,,,3,1979-10-07 -7908,327,202,5,12.0,3,1.0,1,9.0,59,6737734.0,,,1,1979-10-07 -7909,327,162,3,16.0,7,2.0,2,6.0,59,6786521.0,,,1,1979-10-07 -7910,327,201,24,3.0,10,3.0,3,4.0,59,6790933.0,,,1,1979-10-07 -7911,327,206,31,1.0,17,,20,0.0,16,,,,6,1979-10-07 -7912,327,232,52,9.0,14,5.0,5,2.0,59,6838993.0,,,1,1979-10-07 -7913,327,186,0,7.0,13,6.0,6,1.0,58,,,,11,1979-10-07 -7914,327,223,54,14.0,23,7.0,7,0.0,54,,,,15,1979-10-07 -7915,327,136,179,6.0,2,,8,0.0,53,,,,7,1979-10-07 -7916,327,205,24,33.0,15,,9,0.0,52,,,,20,1979-10-07 -7917,327,172,56,18.0,20,4.0,4,3.0,59,6828246.0,,,1,1979-10-07 -7918,327,118,20,29.0,19,,11,0.0,44,,,,22,1979-10-07 -7919,327,177,2,27.0,1,,12,0.0,36,,,,36,1979-10-07 -7920,327,175,55,22.0,21,,13,0.0,32,,,,5,1979-10-07 -7921,327,222,2,28.0,5,,14,0.0,29,,,,3,1979-10-07 -7922,327,216,179,5.0,9,,15,0.0,25,,,,20,1979-10-07 -7923,327,218,3,15.0,8,,16,0.0,24,,,,5,1979-10-07 -7924,327,176,57,20.0,12,,17,0.0,20,,,,3,1979-10-07 -7925,327,221,5,11.0,16,,10,0.0,48,,,,27,1979-10-07 -7926,327,174,0,8.0,22,,18,0.0,20,,,,5,1979-10-07 -7927,328,199,20,30.0,14,,17,0.0,20,,,,6,1980-01-13 -7928,328,198,2,28.0,10,,18,0.0,12,,,,5,1980-01-13 -7929,328,172,31,12.0,5,,19,0.0,7,,,,22,1980-01-13 -7930,328,186,0,7.0,17,,20,0.0,5,,,,6,1980-01-13 -7931,328,218,3,15.0,9,,21,0.0,3,,,,6,1980-01-13 -7932,328,162,3,16.0,19,,22,0.0,2,,,,22,1980-01-13 -7933,328,224,56,18.0,0,,25,0.0,0,,,,81,1980-01-13 -7934,328,196,24,3.0,18,,24,0.0,1,,,,4,1980-01-13 -7935,328,139,56,17.0,0,,26,0.0,0,,,,81,1980-01-13 -7936,328,135,52,10.0,0,,27,0.0,0,,,,81,1980-01-13 -7937,328,157,43,31.0,0,,28,0.0,0,,,,81,1980-01-13 -7938,328,206,31,11.0,6,,16,0.0,20,,,,69,1980-01-13 -7939,328,201,26,25.0,3,,23,0.0,1,,,,5,1980-01-13 -7940,328,175,52,9.0,21,,15,0.0,27,,,,42,1980-01-13 -7941,328,116,0,8.0,12,6.0,6,1.0,52,,,,11,1980-01-13 -7942,328,171,26,26.0,2,,13,0.0,30,,,,5,1980-01-13 -7943,328,177,2,27.0,1,1.0,1,9.0,53,6204380.0,,,1,1980-01-13 -7944,328,136,33,5.0,4,2.0,2,6.0,53,6228970.0,,,1,1980-01-13 -7945,328,176,54,21.0,13,3.0,3,4.0,53,6283020.0,,,1,1980-01-13 -7946,328,118,20,29.0,7,,14,0.0,27,,,,5,1980-01-13 -7947,328,151,49,23.0,20,5.0,5,2.0,52,,,,11,1980-01-13 -7948,328,205,24,4.0,22,4.0,4,3.0,53,6287860.0,,,1,1980-01-13 -7949,328,220,49,22.0,23,,8,0.0,46,,,,5,1980-01-13 -7950,328,221,5,1.0,11,,9,0.0,45,,,,5,1980-01-13 -7951,328,222,55,14.0,15,,10,0.0,44,,,,62,1980-01-13 -7952,328,223,54,20.0,24,,11,0.0,37,,,,62,1980-01-13 -7953,328,202,5,2.0,8,,12,0.0,36,,,,3,1980-01-13 -7954,328,216,33,6.0,16,7.0,7,0.0,51,,,,12,1980-01-13 -7955,329,202,5,2.0,3,16.0,16,0.0,36,,,,37,1980-01-27 -7956,329,220,49,22.0,21,,17,0.0,33,,,,10,1980-01-27 -7957,329,218,3,15.0,1,,18,0.0,25,,,,101,1980-01-27 -7958,329,136,33,5.0,9,,19,0.0,14,,,,22,1980-01-27 -7959,329,135,52,10.0,0,,25,0.0,0,,,,81,1980-01-27 -7960,329,222,55,14.0,12,,21,0.0,13,,,,5,1980-01-27 -7961,329,221,5,1.0,8,,22,0.0,10,,,,5,1980-01-27 -7962,329,206,31,11.0,11,,23,0.0,1,,,,20,1980-01-27 -7963,329,198,2,28.0,4,,24,0.0,1,,,,86,1980-01-27 -7964,329,223,54,20.0,19,15.0,15,0.0,38,,,,12,1980-01-27 -7965,329,171,26,26.0,5,,20,0.0,13,,,,10,1980-01-27 -7966,329,205,24,4.0,24,14.0,14,0.0,38,,,,12,1980-01-27 -7967,329,175,52,9.0,20,7.0,7,0.0,39,,,,11,1980-01-27 -7968,329,196,24,3.0,22,12.0,12,0.0,39,,,,11,1980-01-27 -7969,329,186,0,7.0,23,11.0,11,0.0,39,,,,11,1980-01-27 -7970,329,199,20,30.0,16,10.0,10,0.0,39,,,,11,1980-01-27 -7971,329,176,54,21.0,15,9.0,9,0.0,39,,,,11,1980-01-27 -7972,329,216,33,6.0,18,8.0,8,0.0,39,,,,11,1980-01-27 -7973,329,118,20,29.0,14,6.0,6,1.0,39,,,,11,1980-01-27 -7974,329,116,0,8.0,13,5.0,5,2.0,40,6106740.0,,,1,1980-01-27 -7975,329,201,26,25.0,2,4.0,4,3.0,40,6101460.0,,,1,1980-01-27 -7976,329,177,2,27.0,10,3.0,3,4.0,40,6067440.0,,,1,1980-01-27 -7977,329,172,31,12.0,7,2.0,2,6.0,40,6023190.0,,,1,1980-01-27 -7978,329,162,3,16.0,6,1.0,1,9.0,40,6001330.0,,,1,1980-01-27 -7979,329,224,56,18.0,0,,26,0.0,0,,,,81,1980-01-27 -7980,329,151,49,23.0,17,13.0,13,0.0,39,,,,11,1980-01-27 -7981,329,139,56,17.0,0,,27,0.0,0,,,,81,1980-01-27 -7982,329,157,43,31.0,0,,28,0.0,0,,,,81,1980-01-27 -7983,330,171,26,26.0,4,2.0,2,6.0,78,5846610.0,,,1,1980-03-01 -7984,330,224,56,18.0,0,,27,0.0,0,,,,81,1980-03-01 -7985,330,135,52,10.0,0,,28,0.0,0,,,,81,1980-03-01 -7986,330,175,52,9.0,0,,26,0.0,0,,,,3,1980-03-01 -7987,330,172,31,12.0,14,,24,0.0,1,,,,20,1980-03-01 -7988,330,157,43,31.0,22,,23,0.0,8,,,,20,1980-03-01 -7989,330,118,20,29.0,11,,22,0.0,10,,,,20,1980-03-01 -7990,330,221,5,1.0,9,,21,0.0,14,,,,5,1980-03-01 -7991,330,202,5,2.0,10,,20,0.0,31,,,,7,1980-03-01 -7992,330,177,2,27.0,8,,19,0.0,34,,,,6,1980-03-01 -7993,330,220,49,22.0,7,,18,0.0,53,,,,62,1980-03-01 -7994,330,176,54,21.0,23,,17,0.0,58,,,,3,1980-03-01 -7995,330,205,24,4.0,16,,16,0.0,61,,,,29,1980-03-01 -7996,330,218,3,15.0,1,,15,0.0,61,,,,29,1980-03-01 -7997,330,151,49,23.0,12,,14,0.0,69,,,,5,1980-03-01 -7998,330,116,0,8.0,0,,25,0.0,0,,,,3,1980-03-01 -7999,330,206,31,11.0,15,12.0,12,0.0,76,,,,12,1980-03-01 -8000,330,162,3,16.0,2,1.0,1,9.0,78,5812540.0,,,1,1980-03-01 -8001,330,201,26,25.0,5,3.0,3,4.0,78,5865030.0,,,1,1980-03-01 -8002,330,136,33,5.0,3,4.0,4,3.0,78,5873560.0,,,1,1980-03-01 -8003,330,198,2,28.0,6,5.0,5,2.0,77,,,,11,1980-03-01 -8004,330,199,20,30.0,19,6.0,6,1.0,77,,,,11,1980-03-01 -8005,330,208,56,17.0,24,13.0,13,0.0,70,,,,22,1980-03-01 -8006,330,223,54,20.0,18,8.0,8,0.0,77,,,,11,1980-03-01 -8007,330,222,55,14.0,20,9.0,9,0.0,77,,,,11,1980-03-01 -8008,330,216,33,6.0,17,10.0,10,0.0,77,,,,11,1980-03-01 -8009,330,186,0,7.0,21,11.0,11,0.0,76,,,,12,1980-03-01 -8010,330,196,24,3.0,13,7.0,7,0.0,77,,,,11,1980-03-01 -8011,331,157,43,31.0,19,,18,0.0,11,,,,7,1980-03-30 -8012,331,198,2,28.0,7,,19,0.0,3,,,,7,1980-03-30 -8013,331,196,24,3.0,12,,20,0.0,3,,,,3,1980-03-30 -8014,331,172,31,12.0,20,,21,0.0,3,,,,3,1980-03-30 -8015,331,135,52,9.0,4,,22,0.0,0,,,,7,1980-03-30 -8016,331,216,33,6.0,18,,24,0.0,0,,,,3,1980-03-30 -8017,331,224,56,18.0,0,,25,0.0,0,,,,81,1980-03-30 -8018,331,208,56,17.0,0,,26,0.0,0,,,,81,1980-03-30 -8019,331,225,0,8.0,0,,27,0.0,0,,,,81,1980-03-30 -8020,331,171,26,26.0,13,,17,0.0,36,,,,29,1980-03-30 -8021,331,206,31,11.0,15,,23,0.0,0,,,,3,1980-03-30 -8022,331,202,5,2.0,10,,15,0.0,46,,,,7,1980-03-30 -8023,331,220,49,22.0,3,,16,0.0,40,,,,22,1980-03-30 -8024,331,118,20,29.0,8,2.0,2,6.0,80,6668612.0,,,1,1980-03-30 -8025,331,136,33,5.0,1,1.0,1,9.0,80,6619400.0,,,1,1980-03-30 -8026,331,177,2,27.0,5,,14,0.0,47,,,,3,1980-03-30 -8027,331,223,54,20.0,24,3.0,3,4.0,80,6697963.0,,,1,1980-03-30 -8028,331,186,0,7.0,21,4.0,4,3.0,79,,,,11,1980-03-30 -8029,331,201,26,25.0,9,6.0,6,1.0,79,,,,11,1980-03-30 -8030,331,199,20,30.0,17,7.0,7,0.0,79,,,,11,1980-03-30 -8031,331,221,5,1.0,16,5.0,5,2.0,79,,,,11,1980-03-30 -8032,331,162,3,16.0,2,9.0,9,0.0,78,,,,12,1980-03-30 -8033,331,218,3,15.0,11,10.0,10,0.0,71,,,,19,1980-03-30 -8034,331,176,54,21.0,22,,11,0.0,58,,,,25,1980-03-30 -8035,331,222,55,14.0,23,,12,0.0,50,,,,3,1980-03-30 -8036,331,151,49,23.0,6,,13,0.0,49,,,,3,1980-03-30 -8037,331,205,24,4.0,14,8.0,8,0.0,79,,,,11,1980-03-30 -8038,332,226,55,14.0,23,,20,0.0,12,,,,5,1980-05-04 -8039,332,136,33,5.0,7,,17,0.0,32,,,,20,1980-05-04 -8040,332,116,0,8.0,19,,18,0.0,29,,,,7,1980-05-04 -8041,332,223,54,20.0,24,,19,0.0,16,,,,10,1980-05-04 -8042,332,151,49,23.0,18,,21,0.0,11,,,,22,1980-05-04 -8043,332,220,49,22.0,10,,16,0.0,38,,,,43,1980-05-04 -8044,332,218,3,15.0,5,,24,0.0,1,,,,8,1980-05-04 -8045,332,208,56,17.0,0,,25,0.0,0,,,,81,1980-05-04 -8046,332,224,56,18.0,0,,26,0.0,0,,,,81,1980-05-04 -8047,332,157,43,31.0,0,,27,0.0,0,,,,81,1980-05-04 -8048,332,216,33,6.0,22,,22,0.0,5,,,,6,1980-05-04 -8049,332,206,31,11.0,17,,15,0.0,41,,,,6,1980-05-04 -8050,332,199,20,30.0,13,,23,0.0,1,,,,20,1980-05-04 -8051,332,186,0,7.0,20,,13,0.0,61,,,,62,1980-05-04 -8052,332,118,20,29.0,16,,14,0.0,58,,,,20,1980-05-04 -8053,332,198,2,28.0,4,3.0,3,4.0,72,6011520.0,,,1,1980-05-04 -8054,332,162,3,16.0,6,4.0,4,3.0,71,,,,11,1980-05-04 -8055,332,196,24,3.0,9,5.0,5,2.0,71,,,,11,1980-05-04 -8056,332,202,5,2.0,12,6.0,6,1.0,71,,,,11,1980-05-04 -8057,332,201,26,25.0,2,1.0,1,9.0,72,5927400.0,,,1,1980-05-04 -8058,332,177,2,27.0,1,2.0,2,6.0,72,5974770.0,,,1,1980-05-04 -8059,332,221,5,1.0,14,8.0,8,0.0,70,,,,12,1980-05-04 -8060,332,205,24,4.0,11,9.0,9,0.0,70,,,,12,1980-05-04 -8061,332,172,31,12.0,8,10.0,10,0.0,69,,,,20,1980-05-04 -8062,332,171,26,26.0,3,11.0,11,0.0,68,,,,14,1980-05-04 -8063,332,176,54,21.0,21,7.0,7,0.0,71,,,,11,1980-05-04 -8064,332,135,52,9.0,15,12.0,12,0.0,64,,,,5,1980-05-04 -8065,333,151,49,23.0,8,,17,0.0,0,,,,3,1980-05-18 -8066,333,196,24,3.0,9,,18,0.0,0,,,,3,1980-05-18 -8067,333,116,0,8.0,10,,19,0.0,0,,,,3,1980-05-18 -8068,333,205,24,4.0,12,,20,0.0,0,,,,3,1980-05-18 -8069,333,186,0,7.0,0,,21,0.0,0,,,,81,1980-05-18 -8070,333,176,54,21.0,0,,24,0.0,0,,,,81,1980-05-18 -8071,333,216,33,6.0,0,,25,0.0,0,,,,81,1980-05-18 -8072,333,226,55,14.0,0,,26,0.0,0,,,,81,1980-05-18 -8073,333,224,56,18.0,0,,27,0.0,0,,,,81,1980-05-18 -8074,333,177,2,27.0,3,,16,0.0,24,,,,24,1980-05-18 -8075,333,208,56,17.0,0,,23,0.0,0,,,,81,1980-05-18 -8076,333,218,3,15.0,16,,15,0.0,25,,,,6,1980-05-18 -8077,333,157,43,31.0,0,,22,0.0,0,,,,81,1980-05-18 -8078,333,220,49,22.0,7,,13,0.0,50,,,,5,1980-05-18 -8079,333,198,2,28.0,2,1.0,1,9.0,76,6934365.0,,,1,1980-05-18 -8080,333,171,26,26.0,5,2.0,2,6.0,76,7007994.0,,,1,1980-05-18 -8081,333,136,33,5.0,4,3.0,3,4.0,76,7012091.0,,,1,1980-05-18 -8082,333,199,20,30.0,15,4.0,4,3.0,75,,,,11,1980-05-18 -8083,333,221,5,1.0,17,,14,0.0,27,,,,64,1980-05-18 -8084,333,223,54,20.0,18,6.0,6,1.0,74,,,,12,1980-05-18 -8085,333,202,5,2.0,6,5.0,5,2.0,75,,,,11,1980-05-18 -8086,333,118,20,29.0,11,8.0,8,0.0,73,,,,13,1980-05-18 -8087,333,172,31,12.0,14,9.0,9,0.0,68,,,,3,1980-05-18 -8088,333,135,52,9.0,13,,10,0.0,64,,,,62,1980-05-18 -8089,333,201,26,25.0,1,,11,0.0,54,,,,3,1980-05-18 -8090,333,162,3,16.0,20,,12,0.0,53,,,,3,1980-05-18 -8091,333,206,31,11.0,19,7.0,7,0.0,73,,,,13,1980-05-18 -8092,334,175,52,9.0,11,,16,0.0,26,,,,6,1980-06-29 -8093,334,220,49,22.0,10,,17,0.0,25,,,,64,1980-06-29 -8094,334,206,31,11.0,12,,18,0.0,18,,,,6,1980-06-29 -8095,334,176,54,21.0,23,,19,0.0,8,,,,20,1980-06-29 -8096,334,208,56,17.0,0,,25,0.0,0,,,,81,1980-06-29 -8097,334,116,0,8.0,7,,21,0.0,6,,,,7,1980-06-29 -8098,334,172,31,12.0,14,,22,0.0,3,,,,8,1980-06-29 -8099,334,224,56,18.0,0,,27,0.0,0,,,,81,1980-06-29 -8100,334,218,3,15.0,6,,23,0.0,0,,,,7,1980-06-29 -8101,334,216,33,6.0,22,,24,0.0,0,,,,8,1980-06-29 -8102,334,151,49,23.0,9,,20,0.0,8,,,,64,1980-06-29 -8103,334,157,43,31.0,21,,15,0.0,43,,,,5,1980-06-29 -8104,334,118,20,29.0,18,9.0,9,0.0,53,,,,11,1980-06-29 -8105,334,223,54,20.0,24,,13,0.0,50,,,,5,1980-06-29 -8106,334,221,5,1.0,19,12.0,12,0.0,52,,,,12,1980-06-29 -8107,334,205,24,4.0,20,11.0,11,0.0,52,,,,12,1980-06-29 -8108,334,199,20,30.0,15,10.0,10,0.0,53,,,,11,1980-06-29 -8109,334,202,5,2.0,17,8.0,8,0.0,53,,,,11,1980-06-29 -8110,334,186,0,7.0,13,7.0,7,0.0,53,,,,11,1980-06-29 -8111,334,198,2,28.0,5,6.0,6,1.0,54,5640140.0,,,1,1980-06-29 -8112,334,162,3,16.0,2,5.0,5,2.0,54,5639550.0,,,1,1980-06-29 -8113,334,136,33,5.0,8,4.0,4,3.0,54,5638280.0,,,1,1980-06-29 -8114,334,171,26,26.0,1,3.0,3,4.0,54,5593660.0,,,1,1980-06-29 -8115,334,201,26,25.0,3,2.0,2,6.0,54,5567920.0,,,1,1980-06-29 -8116,334,177,2,27.0,4,1.0,1,9.0,54,5563400.0,,,1,1980-06-29 -8117,334,196,24,3.0,16,,14,0.0,50,,,,14,1980-06-29 -8118,334,135,55,14.0,0,,26,0.0,0,,,,81,1980-06-29 -8119,335,205,24,4.0,10,4.0,4,3.0,75,,,,11,1980-07-13 -8120,335,136,33,5.0,5,2.0,2,6.0,76,5700235.0,,,1,1980-07-13 -8121,335,177,2,27.0,3,1.0,1,9.0,76,5689228.0,,,1,1980-07-13 -8122,335,227,2,43.0,0,,27,0.0,0,,,,81,1980-07-13 -8123,335,176,54,21.0,0,,26,0.0,0,,,,81,1980-07-13 -8124,335,135,55,14.0,0,,25,0.0,0,,,,81,1980-07-13 -8125,335,218,3,15.0,13,,24,0.0,4,,,,5,1980-07-13 -8126,335,172,31,12.0,14,,23,0.0,16,,,,22,1980-07-13 -8127,335,157,43,31.0,20,,22,0.0,17,,,,22,1980-07-13 -8128,335,220,49,22.0,8,,21,0.0,27,,,,5,1980-07-13 -8129,335,171,26,26.0,2,,20,0.0,30,,,,27,1980-07-13 -8130,335,202,5,2.0,19,,19,0.0,35,,,,5,1980-07-13 -8131,335,151,49,23.0,6,,18,0.0,42,,,,20,1980-07-13 -8132,335,206,31,11.0,9,,17,0.0,57,,,,6,1980-07-13 -8133,335,223,54,20.0,22,12.0,12,0.0,72,,,,14,1980-07-13 -8134,335,201,26,25.0,1,,15,0.0,63,,,,27,1980-07-13 -8135,335,175,52,9.0,15,,16,0.0,59,,,,5,1980-07-13 -8136,335,196,24,3.0,11,5.0,5,2.0,75,,,,11,1980-07-13 -8137,335,116,0,8.0,7,6.0,6,1.0,75,,,,11,1980-07-13 -8138,335,211,33,6.0,17,7.0,7,0.0,74,,,,12,1980-07-13 -8139,335,186,0,7.0,12,8.0,8,0.0,74,,,,5,1980-07-13 -8140,335,198,2,28.0,4,3.0,3,4.0,76,5702513.0,,,1,1980-07-13 -8141,335,221,5,1.0,23,10.0,10,0.0,73,,,,13,1980-07-13 -8142,335,210,2,50.0,18,11.0,11,0.0,73,,,,13,1980-07-13 -8143,335,199,20,30.0,24,13.0,13,0.0,69,,,,17,1980-07-13 -8144,335,162,3,16.0,16,,14,0.0,67,,,,62,1980-07-13 -8145,335,118,20,29.0,21,9.0,9,0.0,73,,,,13,1980-07-13 -8146,336,186,0,7.0,20,,17,0.0,39,,,,5,1980-08-10 -8147,336,228,52,10.0,0,,26,0.0,0,,,,81,1980-08-10 -8148,336,210,2,50.0,0,,25,0.0,0,,,,81,1980-08-10 -8149,336,211,33,6.0,15,,24,0.0,4,,,,6,1980-08-10 -8150,336,176,54,21.0,8,,23,0.0,8,,,,67,1980-08-10 -8151,336,223,54,20.0,12,,22,0.0,18,,,,23,1980-08-10 -8152,336,201,26,25.0,7,,21,0.0,18,,,,7,1980-08-10 -8153,336,157,43,31.0,18,,20,0.0,23,,,,6,1980-08-10 -8154,336,162,3,16.0,3,,19,0.0,26,,,,5,1980-08-10 -8155,336,218,3,15.0,2,,18,0.0,27,,,,5,1980-08-10 -8156,336,172,31,12.0,11,16.0,16,0.0,43,,,,67,1980-08-10 -8157,336,196,24,3.0,23,15.0,15,0.0,44,,,,11,1980-08-10 -8158,336,151,49,23.0,19,5.0,5,2.0,45,5116220.0,,,1,1980-08-10 -8159,336,221,5,1.0,21,13.0,13,0.0,44,,,,11,1980-08-10 -8160,336,175,52,9.0,13,12.0,12,0.0,44,,,,11,1980-08-10 -8161,336,116,0,8.0,14,11.0,11,0.0,44,,,,11,1980-08-10 -8162,336,205,24,4.0,22,10.0,10,0.0,44,,,,11,1980-08-10 -8163,336,118,20,29.0,10,9.0,9,0.0,44,,,,11,1980-08-10 -8164,336,199,20,30.0,17,8.0,8,0.0,45,5147480.0,,,1,1980-08-10 -8165,336,206,31,11.0,9,7.0,7,0.0,45,5132740.0,,,1,1980-08-10 -8166,336,202,5,2.0,16,6.0,6,1.0,45,5128450.0,,,1,1980-08-10 -8167,336,198,2,28.0,4,2.0,2,6.0,45,5042920.0,,,1,1980-08-10 -8168,336,136,33,5.0,6,4.0,4,3.0,45,5084210.0,,,1,1980-08-10 -8169,336,177,2,27.0,1,3.0,3,4.0,45,5083260.0,,,1,1980-08-10 -8170,336,135,55,14.0,24,14.0,14,0.0,44,,,,11,1980-08-10 -8171,336,171,26,26.0,5,1.0,1,9.0,45,5039730.0,,,1,1980-08-10 -8172,337,186,0,7.0,21,,18,0.0,34,,,,5,1980-08-17 -8173,337,176,54,21.0,11,16.0,16,0.0,52,,,,12,1980-08-17 -8174,337,151,49,23.0,8,,19,0.0,28,,,,36,1980-08-17 -8175,337,94,31,43.0,24,,17,0.0,40,,,,5,1980-08-17 -8176,337,201,26,25.0,13,,20,0.0,25,,,,64,1980-08-17 -8177,337,199,20,30.0,0,,26,0.0,0,,,,81,1980-08-17 -8178,337,157,43,31.0,19,,22,0.0,23,,,,67,1980-08-17 -8179,337,205,24,4.0,10,,23,0.0,12,,,,23,1980-08-17 -8180,337,206,31,11.0,17,,24,0.0,6,,,,5,1980-08-17 -8181,337,135,55,14.0,0,,25,0.0,0,,,,81,1980-08-17 -8182,337,196,24,3.0,6,,21,0.0,25,,,,10,1980-08-17 -8183,337,210,2,50.0,20,15.0,15,0.0,52,,,,12,1980-08-17 -8184,337,175,52,9.0,16,12.0,12,0.0,53,,,,11,1980-08-17 -8185,337,221,5,1.0,22,13.0,13,0.0,53,,,,11,1980-08-17 -8186,337,118,20,29.0,18,14.0,14,0.0,53,,,,11,1980-08-17 -8187,337,218,3,15.0,2,1.0,1,9.0,54,5175730.0,,,1,1980-08-17 -8188,337,177,2,27.0,3,2.0,2,6.0,54,5176550.0,,,1,1980-08-17 -8189,337,198,2,28.0,4,3.0,3,4.0,54,5195090.0,,,1,1980-08-17 -8190,337,171,26,26.0,5,4.0,4,3.0,54,5217750.0,,,1,1980-08-17 -8191,337,136,33,5.0,7,5.0,5,2.0,54,5238540.0,,,1,1980-08-17 -8192,337,116,0,8.0,12,7.0,7,0.0,54,5269140.0,,,1,1980-08-17 -8193,337,223,54,20.0,23,11.0,11,0.0,53,,,,11,1980-08-17 -8194,337,211,33,6.0,14,10.0,10,0.0,53,,,,11,1980-08-17 -8195,337,172,31,12.0,9,6.0,6,1.0,54,5238540.0,,,1,1980-08-17 -8196,337,202,5,2.0,15,8.0,8,0.0,53,,,,11,1980-08-17 -8197,337,162,3,16.0,1,9.0,9,0.0,53,,,,11,1980-08-17 -8198,338,199,20,30.0,0,,29,0.0,0,,,,54,1980-08-31 -8199,338,176,54,21.0,0,,28,0.0,0,,,,81,1980-08-31 -8200,338,190,20,30.0,0,,27,0.0,0,,,,81,1980-08-31 -8201,338,135,55,14.0,0,,26,0.0,0,,,,81,1980-08-31 -8202,338,210,2,50.0,0,,25,0.0,0,,,,81,1980-08-31 -8203,338,229,49,22.0,22,,17,0.0,21,,,,3,1980-08-31 -8204,338,201,26,25.0,15,,23,0.0,2,,,,3,1980-08-31 -8205,338,172,31,12.0,11,,22,0.0,2,,,,3,1980-08-31 -8206,338,94,31,43.0,16,,21,0.0,15,,,,23,1980-08-31 -8207,338,223,54,20.0,21,,20,0.0,16,,,,23,1980-08-31 -8208,338,186,0,7.0,9,,19,0.0,18,,,,5,1980-08-31 -8209,338,208,55,41.0,24,,18,0.0,21,,,,3,1980-08-31 -8210,338,211,33,6.0,13,,24,0.0,1,,,,6,1980-08-31 -8211,338,118,20,29.0,14,,15,0.0,29,,,,5,1980-08-31 -8212,338,157,43,31.0,19,,14,0.0,38,,,,5,1980-08-31 -8213,338,136,33,5.0,5,1.0,1,9.0,72,5893830.0,,,1,1980-08-31 -8214,338,162,3,16.0,1,2.0,2,6.0,72,5906760.0,,,1,1980-08-31 -8215,338,171,26,26.0,6,3.0,3,4.0,72,5907260.0,,,1,1980-08-31 -8216,338,198,2,28.0,3,4.0,4,3.0,72,5909120.0,,,1,1980-08-31 -8217,338,218,3,15.0,2,,16,0.0,23,,,,64,1980-08-31 -8218,338,116,0,8.0,18,6.0,6,1.0,72,5976450.0,,,1,1980-08-31 -8219,338,196,24,3.0,17,5.0,5,2.0,72,5953850.0,,,1,1980-08-31 -8220,338,206,31,11.0,10,8.0,8,0.0,70,,,,60,1980-08-31 -8221,338,221,5,1.0,12,9.0,9,0.0,70,,,,12,1980-08-31 -8222,338,175,52,9.0,20,10.0,10,0.0,69,,,,13,1980-08-31 -8223,338,205,24,4.0,23,,12,0.0,60,,,,23,1980-08-31 -8224,338,151,49,23.0,8,,13,0.0,58,,,,3,1980-08-31 -8225,338,202,5,2.0,7,7.0,7,0.0,71,,,,11,1980-08-31 -8226,338,177,2,27.0,4,11.0,11,0.0,69,,,,13,1980-08-31 -8227,339,208,55,41.0,0,,28,0.0,0,,,,81,1980-09-14 -8228,339,135,55,14.0,0,,27,0.0,0,,,,81,1980-09-14 -8229,339,180,20,30.0,0,,26,0.0,0,,,,81,1980-09-14 -8230,339,177,2,27.0,6,2.0,2,6.0,60,5916450.0,,,1,1980-09-14 -8231,339,229,49,22.0,19,,24,0.0,4,,,,20,1980-09-14 -8232,339,136,33,5.0,5,1.0,1,9.0,60,5887520.0,,,1,1980-09-14 -8233,339,151,49,23.0,4,,23,0.0,5,,,,29,1980-09-14 -8234,339,94,31,43.0,0,,25,0.0,0,,,,81,1980-09-14 -8235,339,202,5,2.0,8,,22,0.0,5,,,,29,1980-09-14 -8236,339,211,33,6.0,9,,20,0.0,18,,,,22,1980-09-14 -8237,339,186,0,7.0,14,,19,0.0,20,,,,67,1980-09-14 -8238,339,205,24,4.0,22,,18,0.0,33,,,,3,1980-09-14 -8239,339,118,20,29.0,7,,17,0.0,38,,,,5,1980-09-14 -8240,339,206,31,11.0,10,,16,0.0,40,,,,5,1980-09-14 -8241,339,175,52,9.0,23,,15,0.0,45,,,,5,1980-09-14 -8242,339,223,54,20.0,15,,21,0.0,17,,,,3,1980-09-14 -8243,339,196,24,3.0,12,13.0,13,0.0,54,,,,23,1980-09-14 -8244,339,218,3,15.0,2,,14,0.0,53,,,,6,1980-09-14 -8245,339,198,2,28.0,3,3.0,3,4.0,60,5961190.0,,,1,1980-09-14 -8246,339,172,31,12.0,18,4.0,4,3.0,59,,,,11,1980-09-14 -8247,339,176,54,21.0,11,5.0,5,2.0,59,,,,11,1980-09-14 -8248,339,116,0,8.0,24,7.0,7,0.0,59,,,,11,1980-09-14 -8249,339,201,26,25.0,13,6.0,6,1.0,59,,,,11,1980-09-14 -8250,339,221,5,1.0,16,8.0,8,0.0,59,,,,11,1980-09-14 -8251,339,171,26,26.0,20,9.0,9,0.0,59,,,,11,1980-09-14 -8252,339,162,3,16.0,1,10.0,10,0.0,58,,,,12,1980-09-14 -8253,339,210,2,50.0,21,11.0,11,0.0,58,,,,12,1980-09-14 -8254,339,157,43,31.0,17,12.0,12,0.0,57,,,,13,1980-09-14 -8255,340,151,49,23.0,4,,21,0.0,7,,,,83,1980-09-28 -8256,340,109,49,22.0,8,,18,0.0,8,,,,5,1980-09-28 -8257,340,157,43,31.0,14,,19,0.0,8,,,,69,1980-09-28 -8258,340,223,54,20.0,16,,20,0.0,8,,,,6,1980-09-28 -8259,340,206,31,11.0,18,,17,0.0,11,,,,5,1980-09-28 -8260,340,118,20,29.0,11,,22,0.0,6,,,,3,1980-09-28 -8261,340,213,2,51.0,0,,28,0.0,0,,,,81,1980-09-28 -8262,340,190,24,43.0,24,,24,0.0,0,,,,3,1980-09-28 -8263,340,175,52,9.0,0,,25,0.0,0,,,,81,1980-09-28 -8264,340,221,5,1.0,0,,26,0.0,0,,,,81,1980-09-28 -8265,340,210,2,50.0,0,,27,0.0,0,,,,81,1980-09-28 -8266,340,136,33,5.0,1,,16,0.0,23,,,,5,1980-09-28 -8267,340,205,24,4.0,20,,23,0.0,0,,,,3,1980-09-28 -8268,340,218,3,15.0,13,,15,0.0,25,,,,22,1980-09-28 -8269,340,171,26,26.0,9,8.0,8,0.0,68,,,,60,1980-09-28 -8270,340,116,0,8.0,12,,13,0.0,41,,,,22,1980-09-28 -8271,340,162,3,16.0,23,,14,0.0,39,,,,23,1980-09-28 -8272,340,198,2,28.0,5,2.0,2,6.0,70,6421070.0,,,1,1980-09-28 -8273,340,201,26,25.0,3,3.0,3,4.0,70,6424600.0,,,1,1980-09-28 -8274,340,186,0,7.0,7,4.0,4,3.0,70,6436510.0,,,1,1980-09-28 -8275,340,202,5,2.0,22,5.0,5,2.0,70,6460760.0,,,1,1980-09-28 -8276,340,211,33,6.0,10,6.0,6,1.0,69,,,,11,1980-09-28 -8277,340,177,2,27.0,2,1.0,1,9.0,70,6405530.0,,,1,1980-09-28 -8278,340,176,54,21.0,6,9.0,9,0.0,68,,,,12,1980-09-28 -8279,340,172,31,12.0,17,10.0,10,0.0,68,,,,12,1980-09-28 -8280,340,199,20,30.0,21,11.0,11,0.0,67,,,,13,1980-09-28 -8281,340,135,55,14.0,19,12.0,12,0.0,66,,,,14,1980-09-28 -8282,340,196,24,3.0,15,7.0,7,0.0,69,,,,11,1980-09-28 -8283,341,199,20,30.0,24,,15,0.0,36,,,,7,1980-10-05 -8284,341,151,49,23.0,1,,16,0.0,31,,,,10,1980-10-05 -8285,341,136,33,5.0,2,,17,0.0,25,,,,20,1980-10-05 -8286,341,211,33,6.0,8,,18,0.0,20,,,,5,1980-10-05 -8287,341,157,43,31.0,16,,19,0.0,20,,,,22,1980-10-05 -8288,341,223,54,20.0,19,,22,0.0,15,,,,22,1980-10-05 -8289,341,135,55,14.0,25,,21,0.0,16,,,,38,1980-10-05 -8290,341,205,24,4.0,21,,23,0.0,3,,,,20,1980-10-05 -8291,341,116,0,8.0,13,,25,0.0,0,,,,54,1980-10-05 -8292,341,190,24,43.0,0,,26,0.0,0,,,,81,1980-10-05 -8293,341,118,20,29.0,20,,20,0.0,16,,,,20,1980-10-05 -8294,341,196,24,3.0,22,,14,0.0,40,,,,62,1980-10-05 -8295,341,109,49,22.0,10,,24,0.0,2,,,,3,1980-10-05 -8296,341,186,0,7.0,9,,12,0.0,50,,,,19,1980-10-05 -8297,341,177,2,27.0,5,1.0,1,9.0,59,5676050.0,,,1,1980-10-05 -8298,341,198,2,28.0,3,2.0,2,6.0,59,5680260.0,,,1,1980-10-05 -8299,341,208,2,51.0,0,,27,0.0,0,,,,81,1980-10-05 -8300,341,201,26,25.0,7,3.0,3,4.0,59,5688620.0,,,1,1980-10-05 -8301,341,172,31,12.0,4,4.0,4,3.0,59,5705740.0,,,1,1980-10-05 -8302,341,171,26,26.0,12,5.0,5,2.0,58,,,,11,1980-10-05 -8303,341,202,5,2.0,18,,13,0.0,49,,,,3,1980-10-05 -8304,341,162,3,16.0,6,7.0,7,0.0,58,,,,11,1980-10-05 -8305,341,175,52,9.0,17,8.0,8,0.0,57,,,,12,1980-10-05 -8306,341,210,2,50.0,15,9.0,9,0.0,57,,,,12,1980-10-05 -8307,341,176,54,21.0,14,10.0,10,0.0,57,,,,12,1980-10-05 -8308,341,221,5,1.0,23,11.0,11,0.0,56,,,,13,1980-10-05 -8309,341,206,31,11.0,11,6.0,6,1.0,58,,,,11,1980-10-05 -8310,342,94,31,12.0,7,,19,0.0,25,,,,3,1981-03-15 -8311,342,202,5,27.0,5,,20,0.0,17,,,,86,1981-03-15 -8312,342,186,0,7.0,23,,21,0.0,16,,,,23,1981-03-15 -8313,342,172,31,11.0,13,,22,0.0,13,,,,3,1981-03-15 -8314,342,116,3,15.0,14,,23,0.0,0,,,,4,1981-03-15 -8315,342,205,36,17.0,0,,26,0.0,0,,,,81,1981-03-15 -8316,342,213,24,4.0,0,,25,0.0,0,,,,81,1981-03-15 -8317,342,214,43,31.0,0,,27,0.0,0,,,,81,1981-03-15 -8318,342,215,20,30.0,0,,28,0.0,0,,,,81,1981-03-15 -8319,342,193,36,18.0,0,,29,0.0,0,,,,81,1981-03-15 -8320,342,212,43,32.0,24,,18,0.0,26,,,,3,1981-03-15 -8321,342,109,0,8.0,22,,24,0.0,0,,,,4,1981-03-15 -8322,342,118,20,29.0,1,,17,0.0,33,,,,69,1981-03-15 -8323,342,135,52,9.0,21,,16,0.0,41,,,,4,1981-03-15 -8324,342,157,24,3.0,8,5.0,5,2.0,80,6708030.0,,,1,1981-03-15 -8325,342,176,54,20.0,16,,15,0.0,41,,,,5,1981-03-15 -8326,342,198,2,2.0,3,2.0,2,6.0,80,6650520.0,,,1,1981-03-15 -8327,342,136,33,5.0,4,3.0,3,4.0,80,6676250.0,,,1,1981-03-15 -8328,342,206,49,22.0,6,4.0,4,3.0,80,6690640.0,,,1,1981-03-15 -8329,342,174,53,33.0,17,6.0,6,1.0,79,,,,11,1981-03-15 -8330,342,177,2,1.0,2,1.0,1,9.0,80,6641330.0,,,1,1981-03-15 -8331,342,191,54,21.0,18,7.0,7,0.0,78,,,,12,1981-03-15 -8332,342,175,55,14.0,19,,9,0.0,70,,,,69,1981-03-15 -8333,342,201,5,28.0,11,,10,0.0,67,,,,69,1981-03-15 -8334,342,196,26,25.0,10,,11,0.0,64,,,,48,1981-03-15 -8335,342,211,33,6.0,15,,12,0.0,49,,,,3,1981-03-15 -8336,342,151,49,23.0,9,,13,0.0,41,,,,4,1981-03-15 -8337,342,171,26,26.0,12,,14,0.0,41,,,,4,1981-03-15 -8338,342,162,3,16.0,20,8.0,8,0.0,77,,,,13,1981-03-15 -8339,343,109,0,8.0,20,,21,0.0,9,,,,5,1981-03-29 -8340,343,201,5,28.0,17,,20,0.0,19,,,,4,1981-03-29 -8341,343,116,3,15.0,5,,18,0.0,20,,,,4,1981-03-29 -8342,343,162,3,16.0,8,,22,0.0,0,,,,4,1981-03-29 -8343,343,215,20,30.0,21,,19,0.0,20,,,,3,1981-03-29 -8344,343,206,49,22.0,9,,23,0.0,0,,,,4,1981-03-29 -8345,343,217,55,14.0,0,,30,0.0,0,,,,54,1981-03-29 -8346,343,135,52,9.0,0,,25,0.0,0,,,,81,1981-03-29 -8347,343,212,43,32.0,0,,26,0.0,0,,,,81,1981-03-29 -8348,343,214,43,31.0,0,,27,0.0,0,,,,81,1981-03-29 -8349,343,193,43,18.0,0,,28,0.0,0,,,,81,1981-03-29 -8350,343,205,36,17.0,0,,29,0.0,0,,,,81,1981-03-29 -8351,343,191,54,21.0,22,,24,0.0,0,,,,4,1981-03-29 -8352,343,211,33,6.0,11,,17,0.0,22,,,,20,1981-03-29 -8353,343,177,2,1.0,3,2.0,2,6.0,62,7228100.0,,,1,1981-03-29 -8354,343,151,49,23.0,6,,15,0.0,40,,,,62,1981-03-29 -8355,343,202,5,27.0,7,,16,0.0,25,,,,101,1981-03-29 -8356,343,198,2,2.0,2,1.0,1,9.0,62,7223660.0,,,1,1981-03-29 -8357,343,118,20,29.0,4,3.0,3,4.0,62,7286740.0,,,1,1981-03-29 -8358,343,175,55,14.0,18,4.0,4,3.0,62,7300690.0,,,1,1981-03-29 -8359,343,171,26,26.0,16,6.0,6,1.0,62,7310490.0,,,1,1981-03-29 -8360,343,196,26,25.0,23,7.0,7,0.0,62,7313910.0,,,1,1981-03-29 -8361,343,172,31,11.0,10,5.0,5,2.0,62,7310080.0,,,1,1981-03-29 -8362,343,176,54,20.0,12,9.0,9,0.0,61,,,,11,1981-03-29 -8363,343,174,53,33.0,19,10.0,10,0.0,61,,,,11,1981-03-29 -8364,343,94,31,12.0,13,11.0,11,0.0,61,,,,11,1981-03-29 -8365,343,136,33,5.0,1,12.0,12,0.0,60,,,,12,1981-03-29 -8366,343,216,24,4.0,24,13.0,13,0.0,57,,,,15,1981-03-29 -8367,343,157,24,3.0,14,,14,0.0,49,,,,62,1981-03-29 -8368,343,186,0,7.0,15,8.0,8,0.0,61,,,,11,1981-03-29 -8369,344,94,31,12.0,15,,22,0.0,3,,,,5,1981-04-12 -8370,344,191,54,21.0,20,,18,0.0,28,,,,6,1981-04-12 -8371,344,171,26,26.0,21,,19,0.0,19,,,,64,1981-04-12 -8372,344,175,55,14.0,16,,20,0.0,14,,,,5,1981-04-12 -8373,344,176,54,20.0,8,,21,0.0,4,,,,69,1981-04-12 -8374,344,211,33,6.0,6,,17,0.0,32,,,,10,1981-04-12 -8375,344,193,36,18.0,0,,29,0.0,0,,,,81,1981-04-12 -8376,344,157,24,3.0,13,,24,0.0,1,,,,8,1981-04-12 -8377,344,214,43,31.0,0,,25,0.0,0,,,,81,1981-04-12 -8378,344,212,43,32.0,0,,26,0.0,0,,,,81,1981-04-12 -8379,344,205,36,17.0,0,,27,0.0,0,,,,81,1981-04-12 -8380,344,218,26,25.0,0,,28,0.0,0,,,,81,1981-04-12 -8381,344,201,5,28.0,12,,23,0.0,3,,,,5,1981-04-12 -8382,344,186,0,7.0,11,,16,0.0,36,,,,7,1981-04-12 -8383,344,206,49,22.0,17,8.0,8,0.0,52,,,,11,1981-04-12 -8384,344,202,5,27.0,7,,14,0.0,40,,,,7,1981-04-12 -8385,344,174,53,33.0,14,,15,0.0,36,,,,44,1981-04-12 -8386,344,136,33,5.0,1,1.0,1,9.0,53,5672740.0,,,1,1981-04-12 -8387,344,198,2,2.0,4,2.0,2,6.0,53,5699350.0,,,1,1981-04-12 -8388,344,116,3,15.0,2,3.0,3,4.0,53,5722720.0,,,1,1981-04-12 -8389,344,162,3,16.0,5,5.0,5,2.0,53,5764590.0,,,1,1981-04-12 -8390,344,172,31,11.0,10,6.0,6,1.0,52,,,,11,1981-04-12 -8391,344,177,2,1.0,3,4.0,4,3.0,53,5740620.0,,,1,1981-04-12 -8392,344,215,20,30.0,19,9.0,9,0.0,52,,,,11,1981-04-12 -8393,344,151,49,23.0,22,10.0,10,0.0,51,,,,60,1981-04-12 -8394,344,109,0,8.0,18,11.0,11,0.0,51,,,,12,1981-04-12 -8395,344,135,52,9.0,23,12.0,12,0.0,51,,,,12,1981-04-12 -8396,344,216,24,4.0,24,13.0,13,0.0,51,,,,12,1981-04-12 -8397,344,118,20,29.0,9,7.0,7,0.0,52,,,,11,1981-04-12 -8398,345,214,43,31.0,22,,24,0.0,0,,,,3,1981-05-03 -8399,345,206,49,22.0,12,,20,0.0,26,,,,6,1981-05-03 -8400,345,176,54,20.0,15,,21,0.0,14,,,,5,1981-05-03 -8401,345,171,26,26.0,10,,22,0.0,7,,,,22,1981-05-03 -8402,345,116,3,15.0,4,,23,0.0,3,,,,6,1981-05-03 -8403,345,215,20,30.0,0,,25,0.0,0,,,,81,1981-05-03 -8404,345,94,31,12.0,0,,32,0.0,0,,,,54,1981-05-03 -8405,345,135,52,9.0,0,,27,0.0,0,,,,31,1981-05-03 -8406,345,191,54,21.0,0,,28,0.0,0,,,,81,1981-05-03 -8407,345,117,51,36.0,0,,29,0.0,0,,,,81,1981-05-03 -8408,345,204,51,35.0,0,,30,0.0,0,,,,81,1981-05-03 -8409,345,172,31,11.0,0,,31,0.0,0,,,,54,1981-05-03 -8410,345,157,24,3.0,19,,19,0.0,28,,,,4,1981-05-03 -8411,345,205,36,18.0,0,,26,0.0,0,,,,81,1981-05-03 -8412,345,151,49,23.0,11,,18,0.0,28,,,,4,1981-05-03 -8413,345,212,43,32.0,20,,17,0.0,31,,,,4,1981-05-03 -8414,345,104,24,4.0,17,,16,0.0,31,,,,4,1981-05-03 -8415,345,136,33,5.0,5,1.0,1,9.0,60,6683970.0,,,1,1981-05-03 -8416,345,198,2,2.0,2,3.0,3,4.0,60,6690310.0,,,1,1981-05-03 -8417,345,211,33,6.0,13,4.0,4,3.0,60,6706860.0,,,1,1981-05-03 -8418,345,201,5,28.0,6,5.0,5,2.0,60,6709840.0,,,1,1981-05-03 -8419,345,109,0,8.0,14,6.0,6,1.0,60,6750580.0,,,1,1981-05-03 -8420,345,202,5,27.0,1,7.0,7,0.0,60,6785940.0,,,1,1981-05-03 -8421,345,162,3,16.0,3,8.0,8,0.0,59,,,,11,1981-05-03 -8422,345,118,20,29.0,9,2.0,2,6.0,60,6688550.0,,,1,1981-05-03 -8423,345,186,0,7.0,7,10.0,10,0.0,58,,,,12,1981-05-03 -8424,345,174,53,33.0,16,11.0,11,0.0,58,,,,12,1981-05-03 -8425,345,177,2,1.0,8,12.0,12,0.0,58,,,,12,1981-05-03 -8426,345,200,52,10.0,24,13.0,13,0.0,57,,,,13,1981-05-03 -8427,345,218,26,25.0,18,,14,0.0,45,,,,62,1981-05-03 -8428,345,175,55,14.0,21,9.0,9,0.0,59,,,,11,1981-05-03 -8429,345,193,36,17.0,23,,15,0.0,38,,,,20,1981-05-03 -8430,346,109,0,8.0,23,,19,0.0,11,,,,6,1981-05-17 -8431,346,136,33,5.0,2,,20,0.0,10,,,,3,1981-05-17 -8432,346,176,54,20.0,11,,21,0.0,10,,,,6,1981-05-17 -8433,346,116,3,15.0,12,,22,0.0,2,,,,8,1981-05-17 -8434,346,118,20,29.0,4,,23,0.0,0,,,,4,1981-05-17 -8435,346,193,36,17.0,0,,27,0.0,0,,,,81,1981-05-17 -8436,346,162,3,16.0,0,,26,0.0,0,,,,81,1981-05-17 -8437,346,200,52,9.0,0,,28,0.0,0,,,,81,1981-05-17 -8438,346,174,53,33.0,0,,29,0.0,0,,,,81,1981-05-17 -8439,346,117,51,36.0,0,,30,0.0,0,,,,81,1981-05-17 -8440,346,204,51,35.0,0,,31,0.0,0,,,,81,1981-05-17 -8441,346,177,2,1.0,6,,18,0.0,19,,,,3,1981-05-17 -8442,346,205,36,18.0,0,,25,0.0,0,,,,81,1981-05-17 -8443,346,212,43,32.0,22,,17,0.0,22,,,,5,1981-05-17 -8444,346,215,20,30.0,13,,24,0.0,0,,,,4,1981-05-17 -8445,346,218,26,25.0,16,,15,0.0,35,,,,7,1981-05-17 -8446,346,191,54,21.0,20,,16,0.0,29,,,,5,1981-05-17 -8447,346,171,26,26.0,9,2.0,2,6.0,54,4627670.0,,,1,1981-05-17 -8448,346,94,31,12.0,10,3.0,3,4.0,54,4635300.0,,,1,1981-05-17 -8449,346,202,5,27.0,7,4.0,4,3.0,54,4639250.0,,,1,1981-05-17 -8450,346,172,31,11.0,14,5.0,5,2.0,54,4640810.0,,,1,1981-05-17 -8451,346,157,24,3.0,8,6.0,6,1.0,54,4644120.0,,,1,1981-05-17 -8452,346,186,0,7.0,5,7.0,7,0.0,54,4653270.0,,,1,1981-05-17 -8453,346,198,2,2.0,1,1.0,1,9.0,54,4591610.0,,,1,1981-05-17 -8454,346,151,49,23.0,17,9.0,9,0.0,54,4687190.0,,,1,1981-05-17 -8455,346,206,49,22.0,18,10.0,10,0.0,53,,,,11,1981-05-17 -8456,346,175,55,14.0,15,11.0,11,0.0,52,,,,12,1981-05-17 -8457,346,104,24,4.0,19,12.0,12,0.0,52,,,,12,1981-05-17 -8458,346,159,43,31.0,24,13.0,13,0.0,50,,,,14,1981-05-17 -8459,346,211,33,6.0,21,,14,0.0,39,,,,3,1981-05-17 -8460,346,201,5,28.0,3,8.0,8,0.0,54,4683650.0,,,1,1981-05-17 -8461,347,109,0,8.0,11,,19,0.0,0,,,,4,1981-05-31 -8462,347,206,49,22.0,12,,20,0.0,0,,,,4,1981-05-31 -8463,347,176,54,20.0,0,,21,0.0,0,,,,81,1981-05-31 -8464,347,218,26,25.0,0,,22,0.0,0,,,,81,1981-05-31 -8465,347,191,54,21.0,0,,24,0.0,0,,,,81,1981-05-31 -8466,347,200,52,10.0,0,,27,0.0,0,,,,81,1981-05-31 -8467,347,212,43,31.0,0,,26,0.0,0,,,,81,1981-05-31 -8468,347,205,36,18.0,0,,28,0.0,0,,,,81,1981-05-31 -8469,347,193,36,17.0,0,,29,0.0,0,,,,81,1981-05-31 -8470,347,204,51,35.0,0,,30,0.0,0,,,,81,1981-05-31 -8471,347,117,51,36.0,0,,31,0.0,0,,,,81,1981-05-31 -8472,347,215,20,30.0,14,,18,0.0,14,,,,69,1981-05-31 -8473,347,159,43,32.0,0,,25,0.0,0,,,,81,1981-05-31 -8474,347,94,31,12.0,3,,17,0.0,15,,,,22,1981-05-31 -8475,347,211,33,6.0,0,,23,0.0,0,,,,81,1981-05-31 -8476,347,162,3,16.0,13,,15,0.0,32,,,,20,1981-05-31 -8477,347,118,20,29.0,5,,16,0.0,29,,,,6,1981-05-31 -8478,347,177,2,1.0,7,2.0,2,6.0,76,6903290.0,,,1,1981-05-31 -8479,347,171,26,26.0,8,3.0,3,4.0,76,6952620.0,,,1,1981-05-31 -8480,347,201,5,28.0,17,4.0,4,3.0,75,,,,11,1981-05-31 -8481,347,157,24,3.0,15,5.0,5,2.0,74,,,,12,1981-05-31 -8482,347,175,55,14.0,19,6.0,6,1.0,74,,,,12,1981-05-31 -8483,347,174,53,33.0,16,7.0,7,0.0,72,,,,14,1981-05-31 -8484,347,202,5,27.0,2,1.0,1,9.0,76,6863380.0,,,1,1981-05-31 -8485,347,186,0,7.0,10,,9,0.0,52,,,,5,1981-05-31 -8486,347,104,24,4.0,20,,10,0.0,50,,,,4,1981-05-31 -8487,347,151,49,23.0,18,,11,0.0,50,,,,4,1981-05-31 -8488,347,116,3,15.0,9,,12,0.0,45,,,,5,1981-05-31 -8489,347,198,2,2.0,4,,13,0.0,33,,,,6,1981-05-31 -8490,347,136,33,5.0,1,,8,0.0,53,,,,20,1981-05-31 -8491,347,172,31,11.0,6,,14,0.0,32,,,,5,1981-05-31 -8492,348,218,26,25.0,19,,18,0.0,51,,,,23,1981-06-21 -8493,348,211,33,6.0,18,,19,0.0,46,,,,6,1981-06-21 -8494,348,215,20,30.0,23,,20,0.0,43,,,,80,1981-06-21 -8495,348,136,33,5.0,9,,21,0.0,43,,,,3,1981-06-21 -8496,348,116,3,15.0,5,,22,0.0,28,,,,20,1981-06-21 -8497,348,104,24,4.0,0,,25,0.0,0,,,,81,1981-06-21 -8498,348,109,0,8.0,14,,24,0.0,9,,,,3,1981-06-21 -8499,348,212,43,31.0,0,,26,0.0,0,,,,81,1981-06-21 -8500,348,200,52,9.0,0,,27,0.0,0,,,,81,1981-06-21 -8501,348,204,51,35.0,0,,28,0.0,0,,,,81,1981-06-21 -8502,348,157,24,3.0,20,,17,0.0,62,,,,62,1981-06-21 -8503,348,118,20,29.0,12,,23,0.0,21,,,,23,1981-06-21 -8504,348,205,36,17.0,22,16.0,16,0.0,75,,,,15,1981-06-21 -8505,348,206,49,22.0,8,8.0,8,0.0,80,6455810.0,,,1,1981-06-21 -8506,348,193,55,14.0,24,14.0,14,0.0,77,,,,13,1981-06-21 -8507,348,174,53,33.0,16,13.0,13,0.0,78,,,,12,1981-06-21 -8508,348,176,54,20.0,15,12.0,12,0.0,78,,,,12,1981-06-21 -8509,348,191,54,21.0,21,11.0,11,0.0,79,,,,11,1981-06-21 -8510,348,151,49,23.0,6,10.0,10,0.0,80,6468660.0,,,1,1981-06-21 -8511,348,162,3,16.0,17,9.0,9,0.0,80,6462090.0,,,1,1981-06-21 -8512,348,177,2,1.0,2,7.0,7,0.0,80,6451590.0,,,1,1981-06-21 -8513,348,94,31,12.0,11,6.0,6,1.0,80,6423590.0,,,1,1981-06-21 -8514,348,172,31,11.0,10,5.0,5,2.0,80,6396250.0,,,1,1981-06-21 -8515,348,198,2,2.0,3,4.0,4,3.0,80,6396020.0,,,1,1981-06-21 -8516,348,117,51,36.0,0,,29,0.0,0,,,,81,1981-06-21 -8517,348,171,26,26.0,1,2.0,2,6.0,80,6395230.0,,,1,1981-06-21 -8518,348,202,5,27.0,7,1.0,1,9.0,80,6395010.0,,,1,1981-06-21 -8519,348,201,5,28.0,13,15.0,15,0.0,76,,,,14,1981-06-21 -8520,348,219,43,32.0,0,,30,0.0,0,,,,81,1981-06-21 -8521,348,186,0,7.0,4,3.0,3,4.0,80,6395590.0,,,1,1981-06-21 -8522,349,191,54,21.0,24,,24,0.0,0,,,,54,1981-07-05 -8523,349,215,20,30.0,0,,25,0.0,0,,,,81,1981-07-05 -8524,349,117,51,36.0,0,,29,0.0,0,,,,81,1981-07-05 -8525,349,212,43,31.0,0,,28,0.0,0,,,,81,1981-07-05 -8526,349,200,52,9.0,0,,27,0.0,0,,,,81,1981-07-05 -8527,349,204,51,35.0,0,,26,0.0,0,,,,81,1981-07-05 -8528,349,116,3,15.0,3,1.0,1,9.0,80,5748130.0,,,1,1981-07-05 -8529,349,186,0,7.0,2,2.0,2,6.0,80,5750420.0,,,1,1981-07-05 -8530,349,162,3,16.0,1,4.0,4,3.0,80,5790430.0,,,1,1981-07-05 -8531,349,201,5,28.0,14,5.0,5,2.0,79,,,,11,1981-07-05 -8532,349,172,31,11.0,8,6.0,6,1.0,79,,,,11,1981-07-05 -8533,349,94,31,12.0,13,7.0,7,0.0,79,,,,11,1981-07-05 -8534,349,206,49,22.0,10,8.0,8,0.0,79,,,,11,1981-07-05 -8535,349,211,33,6.0,15,9.0,9,0.0,78,,,,12,1981-07-05 -8536,349,136,33,5.0,4,3.0,3,4.0,80,5772350.0,,,1,1981-07-05 -8537,349,109,0,8.0,5,11.0,11,0.0,78,,,,12,1981-07-05 -8538,349,198,2,2.0,7,10.0,10,0.0,78,,,,12,1981-07-05 -8539,349,176,54,20.0,17,,22,0.0,11,,,,22,1981-07-05 -8540,349,174,26,25.0,16,,21,0.0,30,,,,67,1981-07-05 -8541,349,202,5,27.0,11,,20,0.0,41,,,,10,1981-07-05 -8542,349,205,36,17.0,20,,19,0.0,55,,,,5,1981-07-05 -8543,349,171,26,26.0,6,,18,0.0,57,,,,22,1981-07-05 -8544,349,193,55,14.0,22,,23,0.0,6,,,,22,1981-07-05 -8545,349,104,24,4.0,23,16.0,16,0.0,77,,,,13,1981-07-05 -8546,349,151,49,23.0,12,15.0,15,0.0,77,,,,13,1981-07-05 -8547,349,118,20,29.0,18,14.0,14,0.0,77,,,,13,1981-07-05 -8548,349,157,24,3.0,19,13.0,13,0.0,77,,,,13,1981-07-05 -8549,349,175,53,33.0,21,12.0,12,0.0,78,,,,12,1981-07-05 -8550,349,177,2,1.0,9,17.0,17,0.0,76,,,,4,1981-07-05 -8551,350,136,33,5.0,3,,18,0.0,11,,,,27,1981-07-18 -8552,350,151,49,23.0,12,,19,0.0,5,,,,7,1981-07-18 -8553,350,202,5,27.0,8,,20,0.0,4,,,,20,1981-07-18 -8554,350,177,2,1.0,7,,21,0.0,3,,,,4,1981-07-18 -8555,350,109,0,8.0,6,,22,0.0,3,,,,20,1981-07-18 -8556,350,104,24,4.0,19,,23,0.0,1,,,,8,1981-07-18 -8557,350,94,31,12.0,0,,27,0.0,0,,,,81,1981-07-18 -8558,350,191,54,21.0,0,,25,0.0,0,,,,81,1981-07-18 -8559,350,204,51,35.0,0,,26,0.0,0,,,,81,1981-07-18 -8560,350,193,55,14.0,0,,28,0.0,0,,,,81,1981-07-18 -8561,350,117,51,36.0,0,,29,0.0,0,,,,81,1981-07-18 -8562,350,212,43,31.0,0,,30,0.0,0,,,,81,1981-07-18 -8563,350,215,20,30.0,18,,24,0.0,8,,,,20,1981-07-18 -8564,350,201,5,28.0,4,,17,0.0,13,,,,101,1981-07-18 -8565,350,162,3,16.0,1,9.0,9,0.0,64,,,,99,1981-07-18 -8566,350,116,3,15.0,2,,15,0.0,17,,,,99,1981-07-18 -8567,350,174,26,25.0,15,,16,0.0,15,,,,8,1981-07-18 -8568,350,198,2,2.0,9,2.0,2,6.0,68,5255450.0,,,1,1981-07-18 -8569,350,171,26,26.0,14,3.0,3,4.0,67,,,,11,1981-07-18 -8570,350,157,24,3.0,23,4.0,4,3.0,67,,,,11,1981-07-18 -8571,350,211,33,6.0,13,5.0,5,2.0,67,,,,11,1981-07-18 -8572,350,200,52,9.0,21,6.0,6,1.0,67,,,,11,1981-07-18 -8573,350,205,36,17.0,17,7.0,7,0.0,66,,,,12,1981-07-18 -8574,350,186,0,7.0,5,1.0,1,9.0,68,5214800.0,,,1,1981-07-18 -8575,350,118,20,29.0,10,10.0,10,0.0,64,,,,5,1981-07-18 -8576,350,175,53,33.0,24,11.0,11,0.0,61,,,,60,1981-07-18 -8577,350,206,49,22.0,11,,12,0.0,59,,,,37,1981-07-18 -8578,350,176,54,20.0,14,,13,0.0,56,,,,22,1981-07-18 -8579,350,172,31,11.0,22,,14,0.0,25,,,,2,1981-07-18 -8580,350,196,43,32.0,20,8.0,8,0.0,65,,,,13,1981-07-18 -8581,351,198,2,2.0,3,,18,0.0,27,,,,5,1981-08-02 -8582,351,118,20,29.0,13,,19,0.0,27,,,,5,1981-08-02 -8583,351,174,26,25.0,11,,20,0.0,27,,,,7,1981-08-02 -8584,351,205,36,17.0,21,,21,0.0,15,,,,22,1981-08-02 -8585,351,94,31,12.0,15,,22,0.0,12,,,,95,1981-08-02 -8586,351,109,0,8.0,10,,23,0.0,4,,,,4,1981-08-02 -8587,351,212,43,31.0,0,,27,0.0,0,,,,81,1981-08-02 -8588,351,176,54,20.0,0,,25,0.0,0,,,,81,1981-08-02 -8589,351,204,51,35.0,0,,26,0.0,0,,,,81,1981-08-02 -8590,351,117,51,36.0,0,,28,0.0,0,,,,81,1981-08-02 -8591,351,104,24,4.0,0,,29,0.0,0,,,,81,1981-08-02 -8592,351,191,54,21.0,0,,30,0.0,0,,,,81,1981-08-02 -8593,351,201,5,28.0,5,,24,0.0,1,,,,10,1981-08-02 -8594,351,200,52,9.0,28,,17,0.0,35,,,,5,1981-08-02 -8595,351,196,43,32.0,17,8.0,8,0.0,44,,,,11,1981-08-02 -8596,351,151,49,23.0,17,15.0,15,0.0,43,,,,12,1981-08-02 -8597,351,171,26,26.0,7,3.0,3,4.0,45,5220200.0,,,1,1981-08-02 -8598,351,211,33,6.0,16,4.0,4,3.0,45,5255290.0,,,1,1981-08-02 -8599,351,157,24,3.0,18,5.0,5,2.0,45,5266120.0,,,1,1981-08-02 -8600,351,186,0,7.0,9,6.0,6,1.0,44,,,,11,1981-08-02 -8601,351,172,31,11.0,14,7.0,7,0.0,44,,,,11,1981-08-02 -8602,351,136,33,5.0,6,1.0,1,9.0,45,5155600.0,,,1,1981-08-02 -8603,351,116,3,15.0,1,2.0,2,6.0,45,5167120.0,,,1,1981-08-02 -8604,351,202,5,27.0,8,10.0,10,0.0,44,,,,11,1981-08-02 -8605,351,206,49,22.0,12,9.0,9,0.0,44,,,,11,1981-08-02 -8606,351,175,53,33.0,22,14.0,14,0.0,43,,,,22,1981-08-02 -8607,351,193,55,14.0,23,,16,0.0,39,,,,62,1981-08-02 -8608,351,215,20,30.0,26,12.0,12,0.0,44,,,,11,1981-08-02 -8609,351,177,2,1.0,4,11.0,11,0.0,44,,,,11,1981-08-02 -8610,351,162,3,16.0,2,13.0,13,0.0,44,,,,11,1981-08-02 -8611,352,104,24,4.0,22,,16,0.0,40,,,,6,1981-08-16 -8612,352,212,43,31.0,0,,28,0.0,0,,,,81,1981-08-16 -8613,352,204,51,35.0,0,,27,0.0,0,,,,81,1981-08-16 -8614,352,117,51,36.0,0,,26,0.0,0,,,,81,1981-08-16 -8615,352,175,53,33.0,23,,24,0.0,0,,,,99,1981-08-16 -8616,352,202,5,27.0,3,,23,0.0,11,,,,3,1981-08-16 -8617,352,94,31,12.0,11,,22,0.0,23,,,,5,1981-08-16 -8618,352,174,26,25.0,17,,21,0.0,26,,,,5,1981-08-16 -8619,352,116,3,15.0,2,,20,0.0,26,,,,22,1981-08-16 -8620,352,215,20,30.0,24,,19,0.0,27,,,,25,1981-08-16 -8621,352,211,33,6.0,15,,18,0.0,32,,,,8,1981-08-16 -8622,352,151,49,23.0,16,,17,0.0,35,,,,42,1981-08-16 -8623,352,157,24,3.0,0,,25,0.0,0,,,,81,1981-08-16 -8624,352,193,55,14.0,20,,15,0.0,43,,,,51,1981-08-16 -8625,352,200,52,9.0,21,,13,0.0,44,,,,23,1981-08-16 -8626,352,118,20,29.0,10,,14,0.0,43,,,,5,1981-08-16 -8627,352,171,26,26.0,4,1.0,1,9.0,53,5256470.0,,,1,1981-08-16 -8628,352,162,3,16.0,1,2.0,2,6.0,53,5261640.0,,,1,1981-08-16 -8629,352,136,33,5.0,7,3.0,3,4.0,53,5263810.0,,,1,1981-08-16 -8630,352,198,2,2.0,5,5.0,5,2.0,53,5288320.0,,,1,1981-08-16 -8631,352,186,0,7.0,12,6.0,6,1.0,53,5347610.0,,,1,1981-08-16 -8632,352,177,2,1.0,6,4.0,4,3.0,53,5268510.0,,,1,1981-08-16 -8633,352,109,0,8.0,18,8.0,8,0.0,52,,,,11,1981-08-16 -8634,352,201,5,28.0,8,9.0,9,0.0,52,,,,11,1981-08-16 -8635,352,196,43,32.0,14,10.0,10,0.0,51,,,,12,1981-08-16 -8636,352,205,36,17.0,19,11.0,11,0.0,47,,,,16,1981-08-16 -8637,352,206,49,22.0,13,,12,0.0,46,,,,5,1981-08-16 -8638,352,172,31,11.0,9,7.0,7,0.0,52,,,,11,1981-08-16 -8639,353,94,31,12.0,17,,22,0.0,1,,,,5,1981-08-30 -8640,353,198,2,2.0,5,,18,0.0,18,,,,4,1981-08-30 -8641,353,118,20,29.0,10,,19,0.0,16,,,,22,1981-08-30 -8642,353,205,36,17.0,19,,20,0.0,5,,,,22,1981-08-30 -8643,353,201,5,28.0,12,,21,0.0,4,,,,4,1981-08-30 -8644,353,174,26,25.0,11,,23,0.0,1,,,,4,1981-08-30 -8645,353,171,26,26.0,6,,17,0.0,18,,,,4,1981-08-30 -8646,353,204,51,35.0,0,,26,0.0,0,,,,81,1981-08-30 -8647,353,176,54,20.0,0,,27,0.0,0,,,,81,1981-08-30 -8648,353,191,54,21.0,0,,28,0.0,0,,,,81,1981-08-30 -8649,353,212,43,31.0,0,,29,0.0,0,,,,81,1981-08-30 -8650,353,117,51,36.0,0,,30,0.0,0,,,,81,1981-08-30 -8651,353,202,5,27.0,16,,24,0.0,0,,,,4,1981-08-30 -8652,353,151,49,23.0,14,,16,0.0,19,,,,27,1981-08-30 -8653,353,109,0,8.0,0,,25,0.0,0,,,,54,1981-08-30 -8654,353,196,43,32.0,18,,14,0.0,29,,,,7,1981-08-30 -8655,353,136,33,5.0,3,2.0,2,6.0,72,6030670.0,,,1,1981-08-30 -8656,353,177,2,1.0,4,3.0,3,4.0,72,6057930.0,,,1,1981-08-30 -8657,353,211,33,6.0,15,4.0,4,3.0,71,,,,11,1981-08-30 -8658,353,172,31,11.0,9,5.0,5,2.0,71,,,,11,1981-08-30 -8659,353,193,55,14.0,24,6.0,6,1.0,70,,,,12,1981-08-30 -8660,353,116,3,15.0,1,1.0,1,9.0,72,6022430.0,,,1,1981-08-30 -8661,353,162,3,16.0,2,,15,0.0,21,,,,5,1981-08-30 -8662,353,175,53,33.0,20,8.0,8,0.0,69,,,,13,1981-08-30 -8663,353,104,24,4.0,25,9.0,9,0.0,68,,,,5,1981-08-30 -8664,353,200,52,9.0,23,10.0,10,0.0,68,,,,14,1981-08-30 -8665,353,206,49,22.0,7,,11,0.0,62,,,,3,1981-08-30 -8666,353,186,0,7.0,8,,12,0.0,50,,,,80,1981-08-30 -8667,353,157,24,3.0,22,,13,0.0,46,,,,22,1981-08-30 -8668,353,215,20,30.0,21,7.0,7,0.0,69,,,,13,1981-08-30 -8669,354,162,3,16.0,1,,19,0.0,12,,,,20,1981-09-13 -8670,354,171,26,26.0,4,,20,0.0,11,,,,29,1981-09-13 -8671,354,157,24,3.0,17,,21,0.0,11,,,,20,1981-09-13 -8672,354,200,52,9.0,21,,22,0.0,10,,,,20,1981-09-13 -8673,354,202,5,27.0,9,,23,0.0,5,,,,5,1981-09-13 -8674,354,211,33,6.0,14,,24,0.0,1,,,,10,1981-09-13 -8675,354,117,51,36.0,0,,27,0.0,0,,,,81,1981-09-13 -8676,354,212,43,31.0,0,,26,0.0,0,,,,81,1981-09-13 -8677,354,215,20,30.0,0,,28,0.0,0,,,,81,1981-09-13 -8678,354,176,54,20.0,0,,29,0.0,0,,,,81,1981-09-13 -8679,354,191,54,21.0,0,,30,0.0,0,,,,81,1981-09-13 -8680,354,193,55,14.0,24,,18,0.0,13,,,,20,1981-09-13 -8681,354,175,53,33.0,0,,25,0.0,0,,,,81,1981-09-13 -8682,354,104,24,4.0,22,,17,0.0,17,,,,3,1981-09-13 -8683,354,118,20,29.0,20,,16,0.0,18,,,,6,1981-09-13 -8684,354,186,0,7.0,7,,15,0.0,19,,,,3,1981-09-13 -8685,354,177,2,1.0,5,2.0,2,6.0,52,5219072.0,,,1,1981-09-13 -8686,354,198,2,2.0,2,3.0,3,4.0,52,5247484.0,,,1,1981-09-13 -8687,354,172,31,11.0,11,4.0,4,3.0,52,5289799.0,,,1,1981-09-13 -8688,354,201,5,28.0,8,5.0,5,2.0,52,5291419.0,,,1,1981-09-13 -8689,354,136,33,5.0,6,6.0,6,1.0,51,,,,5,1981-09-13 -8690,354,109,0,8.0,16,7.0,7,0.0,51,,,,29,1981-09-13 -8691,354,116,3,15.0,3,1.0,1,9.0,52,5196897.0,,,1,1981-09-13 -8692,354,196,43,32.0,18,9.0,9,0.0,50,,,,12,1981-09-13 -8693,354,204,51,35.0,23,10.0,10,0.0,49,,,,13,1981-09-13 -8694,354,206,49,22.0,13,,11,0.0,40,,,,5,1981-09-13 -8695,354,205,36,17.0,19,,12,0.0,36,,,,6,1981-09-13 -8696,354,174,26,25.0,15,,13,0.0,22,,,,29,1981-09-13 -8697,354,94,31,12.0,12,,14,0.0,21,,,,22,1981-09-13 -8698,354,151,49,23.0,10,8.0,8,0.0,50,,,,12,1981-09-13 -8699,355,177,2,1.0,3,,19,0.0,24,,,,64,1981-09-27 -8700,355,201,5,28.0,12,,20,0.0,24,,,,80,1981-09-27 -8701,355,193,55,14.0,24,,21,0.0,8,,,,20,1981-09-27 -8702,355,174,26,25.0,17,,22,0.0,6,,,,20,1981-09-27 -8703,355,118,20,29.0,18,,23,0.0,6,,,,20,1981-09-27 -8704,355,162,3,16.0,8,,24,0.0,0,,,,4,1981-09-27 -8705,355,204,51,35.0,0,,27,0.0,0,,,,81,1981-09-27 -8706,355,191,54,21.0,0,,26,0.0,0,,,,81,1981-09-27 -8707,355,197,20,30.0,0,,28,0.0,0,,,,81,1981-09-27 -8708,355,117,51,36.0,0,,29,0.0,0,,,,81,1981-09-27 -8709,355,212,43,31.0,0,,30,0.0,0,,,,81,1981-09-27 -8710,355,196,43,32.0,23,,18,0.0,26,,,,4,1981-09-27 -8711,355,176,54,20.0,0,,25,0.0,0,,,,81,1981-09-27 -8712,355,211,33,6.0,6,,17,0.0,35,,,,20,1981-09-27 -8713,355,171,26,26.0,10,1.0,1,9.0,63,7285200.0,,,1,1981-09-27 -8714,355,94,31,12.0,5,,15,0.0,45,,,,4,1981-09-27 -8715,355,200,52,9.0,21,,16,0.0,40,,,,20,1981-09-27 -8716,355,186,0,7.0,9,2.0,2,6.0,63,7291430.0,,,1,1981-09-27 -8717,355,202,5,27.0,11,3.0,3,4.0,63,7395470.0,,,1,1981-09-27 -8718,355,151,49,23.0,15,4.0,4,3.0,62,,,,11,1981-09-27 -8719,355,172,31,11.0,7,6.0,6,1.0,62,,,,11,1981-09-27 -8720,355,206,49,22.0,16,7.0,7,0.0,62,,,,11,1981-09-27 -8721,355,136,33,5.0,1,5.0,5,2.0,62,,,,11,1981-09-27 -8722,355,175,53,33.0,19,9.0,9,0.0,61,,,,12,1981-09-27 -8723,355,198,2,2.0,2,10.0,10,0.0,60,,,,13,1981-09-27 -8724,355,104,24,4.0,22,11.0,11,0.0,59,,,,14,1981-09-27 -8725,355,157,24,3.0,14,12.0,12,0.0,56,,,,5,1981-09-27 -8726,355,109,0,8.0,13,,13,0.0,51,,,,20,1981-09-27 -8727,355,116,3,15.0,4,,14,0.0,48,,,,4,1981-09-27 -8728,355,205,36,17.0,20,8.0,8,0.0,61,,,,12,1981-09-27 -8729,356,172,31,11.0,15,,23,0.0,2,,,,47,1981-10-17 -8730,356,175,53,33.0,23,,19,0.0,19,,,,22,1981-10-17 -8731,356,157,24,3.0,19,,20,0.0,10,,,,5,1981-10-17 -8732,356,162,3,16.0,13,,21,0.0,10,,,,10,1981-10-17 -8733,356,174,26,25.0,7,,22,0.0,2,,,,3,1981-10-17 -8734,356,196,43,32.0,21,,24,0.0,0,,,,7,1981-10-17 -8735,356,211,33,6.0,16,,18,0.0,20,,,,37,1981-10-17 -8736,356,191,54,21.0,0,,26,0.0,0,,,,81,1981-10-17 -8737,356,205,36,17.0,0,,27,0.0,0,,,,81,1981-10-17 -8738,356,197,20,30.0,0,,28,0.0,0,,,,81,1981-10-17 -8739,356,204,51,35.0,0,,29,0.0,0,,,,81,1981-10-17 -8740,356,212,43,31.0,0,,30,0.0,0,,,,81,1981-10-17 -8741,356,200,52,9.0,0,,25,0.0,0,,,,81,1981-10-17 -8742,356,202,5,27.0,3,,17,0.0,22,,,,2,1981-10-17 -8743,356,177,2,1.0,2,1.0,1,9.0,75,6249077.0,,,1,1981-10-17 -8744,356,117,51,36.0,22,,15,0.0,43,,,,6,1981-10-17 -8745,356,116,3,15.0,5,2.0,2,6.0,75,6269125.0,,,1,1981-10-17 -8746,356,151,49,23.0,8,3.0,3,4.0,75,6269505.0,,,1,1981-10-17 -8747,356,94,31,12.0,9,4.0,4,3.0,75,6296550.0,,,1,1981-10-17 -8748,356,136,33,5.0,4,5.0,5,2.0,75,6325515.0,,,1,1981-10-17 -8749,356,171,26,26.0,12,6.0,6,1.0,75,6327252.0,,,1,1981-10-17 -8750,356,186,0,7.0,6,7.0,7,0.0,75,6327574.0,,,1,1981-10-17 -8751,356,206,49,22.0,10,,16,0.0,29,,,,22,1981-10-17 -8752,356,201,5,28.0,18,9.0,9,0.0,73,,,,12,1981-10-17 -8753,356,176,54,20.0,20,10.0,10,0.0,73,,,,12,1981-10-17 -8754,356,118,20,29.0,11,11.0,11,0.0,71,,,,14,1981-10-17 -8755,356,109,0,8.0,14,12.0,12,0.0,69,,,,16,1981-10-17 -8756,356,104,24,4.0,17,13.0,13,0.0,67,,,,5,1981-10-17 -8757,356,193,55,14.0,24,,14,0.0,61,,,,62,1981-10-17 -8758,356,198,2,2.0,1,8.0,8,0.0,74,,,,11,1981-10-17 -8759,357,201,5,28.0,6,18.0,18,0.0,71,,,,16,1982-01-23 -8760,357,171,26,26.0,11,,19,0.0,54,,,,69,1982-01-23 -8761,357,117,51,35.0,14,,20,0.0,43,,,,3,1982-01-23 -8762,357,118,33,2.0,4,,21,0.0,18,,,,101,1982-01-23 -8763,357,157,26,25.0,17,,22,0.0,11,,,,69,1982-01-23 -8764,357,202,5,27.0,3,,23,0.0,6,,,,101,1982-01-23 -8765,357,183,20,30.0,0,,27,0.0,0,,,,81,1982-01-23 -8766,357,94,31,12.0,18,,25,0.0,0,,,,10,1982-01-23 -8767,357,196,43,31.0,26,,26,0.0,0,,,,4,1982-01-23 -8768,357,203,43,32.0,0,,28,0.0,0,,,,81,1982-01-23 -8769,357,204,20,29.0,0,,29,0.0,0,,,,81,1982-01-23 -8770,357,194,55,14.0,0,,30,0.0,0,,,,81,1982-01-23 -8771,357,191,54,20.0,25,17.0,17,0.0,72,,,,15,1982-01-23 -8772,357,136,33,1.0,2,,24,0.0,3,,,,20,1982-01-23 -8773,357,169,51,36.0,0,,31,0.0,0,,,,81,1982-01-23 -8774,357,195,36,18.0,21,15.0,15,0.0,72,,,,15,1982-01-23 -8775,357,205,53,33.0,24,14.0,14,0.0,73,,,,14,1982-01-23 -8776,357,200,24,4.0,23,16.0,16,0.0,72,,,,15,1982-01-23 -8777,357,116,3,15.0,5,1.0,1,9.0,77,5528401.0,,,1,1982-01-23 -8778,357,198,2,5.0,8,2.0,2,6.0,77,5543347.0,,,1,1982-01-23 -8779,357,162,3,16.0,1,3.0,3,4.0,77,5556301.0,,,1,1982-01-23 -8780,357,176,2,6.0,7,5.0,5,2.0,77,5571540.0,,,1,1982-01-23 -8781,357,186,0,7.0,9,6.0,6,1.0,77,5579394.0,,,1,1982-01-23 -8782,357,181,0,8.0,13,4.0,4,3.0,77,5560514.0,,,1,1982-01-23 -8783,357,172,31,11.0,15,8.0,8,0.0,76,,,,11,1982-01-23 -8784,357,193,52,10.0,12,9.0,9,0.0,75,,,,12,1982-01-23 -8785,357,180,52,9.0,20,10.0,10,0.0,75,,,,12,1982-01-23 -8786,357,151,49,23.0,19,11.0,11,0.0,74,,,,13,1982-01-23 -8787,357,199,36,17.0,22,12.0,12,0.0,74,,,,13,1982-01-23 -8788,357,109,49,22.0,16,13.0,13,0.0,73,,,,14,1982-01-23 -8789,357,104,24,3.0,10,7.0,7,0.0,76,,,,11,1982-01-23 -8790,358,151,49,23.0,16,,22,0.0,16,,,,8,1982-03-21 -8791,358,162,3,16.0,4,,18,0.0,21,,,,4,1982-03-21 -8792,358,198,2,5.0,6,,19,0.0,21,,,,4,1982-03-21 -8793,358,172,31,11.0,11,,20,0.0,21,,,,4,1982-03-21 -8794,358,157,26,25.0,26,,21,0.0,19,,,,47,1982-03-21 -8795,358,171,26,26.0,24,,23,0.0,15,,,,83,1982-03-21 -8796,358,203,43,32.0,0,,31,0.0,0,,,,81,1982-03-21 -8797,358,205,53,33.0,20,,25,0.0,12,,,,20,1982-03-21 -8798,358,195,36,18.0,17,,26,0.0,11,,,,20,1982-03-21 -8799,358,169,51,36.0,0,,27,0.0,0,,,,81,1982-03-21 -8800,358,204,20,29.0,0,,28,0.0,0,,,,81,1982-03-21 -8801,358,181,0,8.0,5,,17,0.0,22,,,,4,1982-03-21 -8802,358,109,49,22.0,10,,24,0.0,14,,,,83,1982-03-21 -8803,358,202,5,27.0,2,,16,0.0,29,,,,20,1982-03-21 -8804,358,117,51,35.0,0,,29,0.0,0,,,,81,1982-03-21 -8805,358,191,54,20.0,25,,14,0.0,36,,,,22,1982-03-21 -8806,358,116,3,15.0,1,1.0,1,9.0,63,6273134.0,,,1,1982-03-21 -8807,358,194,55,14.0,0,,30,0.0,0,,,,81,1982-03-21 -8808,358,186,0,7.0,12,2.0,2,6.0,63,6276124.0,,,1,1982-03-21 -8809,358,94,31,12.0,14,3.0,3,4.0,63,6309993.0,,,1,1982-03-21 -8810,358,104,24,3.0,13,4.0,4,3.0,63,6323895.0,,,1,1982-03-21 -8811,358,180,52,9.0,15,5.0,5,2.0,62,,,,11,1982-03-21 -8812,358,201,5,28.0,8,6.0,6,1.0,62,,,,11,1982-03-21 -8813,358,118,33,2.0,9,,15,0.0,34,,,,68,1982-03-21 -8814,358,199,36,17.0,22,8.0,8,0.0,61,,,,12,1982-03-21 -8815,358,196,43,31.0,23,9.0,9,0.0,60,,,,13,1982-03-21 -8816,358,183,20,30.0,19,10.0,10,0.0,57,,,,16,1982-03-21 -8817,358,136,33,1.0,7,,11,0.0,63,,,,2,1982-03-21 -8818,358,176,2,6.0,3,,12,0.0,63,,,,2,1982-03-21 -8819,358,193,52,10.0,18,,13,0.0,38,,,,5,1982-03-21 -8820,358,200,24,4.0,21,7.0,7,0.0,61,,,,12,1982-03-21 -8821,359,206,2,5.0,14,,20,0.0,19,,,,4,1982-04-04 -8822,359,116,3,15.0,4,,21,0.0,10,,,,20,1982-04-04 -8823,359,201,5,28.0,9,,22,0.0,6,,,,20,1982-04-04 -8824,359,162,3,16.0,3,,23,0.0,5,,,,4,1982-04-04 -8825,359,151,49,23.0,5,,24,0.0,5,,,,4,1982-04-04 -8826,359,169,51,36.0,0,,27,0.0,0,,,,81,1982-04-04 -8827,359,180,52,9.0,25,,26,0.0,1,,,,4,1982-04-04 -8828,359,203,43,32.0,0,,28,0.0,0,,,,81,1982-04-04 -8829,359,191,54,20.0,0,,29,0.0,0,,,,81,1982-04-04 -8830,359,183,20,30.0,0,,30,0.0,0,,,,81,1982-04-04 -8831,359,117,51,35.0,0,,31,0.0,0,,,,81,1982-04-04 -8832,359,205,53,33.0,22,,19,0.0,23,,,,20,1982-04-04 -8833,359,193,52,10.0,26,,25,0.0,3,,,,4,1982-04-04 -8834,359,136,33,1.0,6,,18,0.0,25,,,,20,1982-04-04 -8835,359,109,49,22.0,1,,13,0.0,33,,,,20,1982-04-04 -8836,359,171,26,26.0,15,,16,0.0,26,,,,20,1982-04-04 -8837,359,181,0,8.0,2,1.0,1,9.0,75,7105318.0,,,1,1982-04-04 -8838,359,176,2,6.0,8,2.0,2,6.0,75,7119978.0,,,1,1982-04-04 -8839,359,118,33,2.0,18,3.0,3,4.0,75,7184461.0,,,1,1982-04-04 -8840,359,104,24,3.0,12,4.0,4,3.0,75,7186265.0,,,1,1982-04-04 -8841,359,172,31,11.0,16,5.0,5,2.0,74,,,,11,1982-04-04 -8842,359,196,43,31.0,10,,17,0.0,26,,,,7,1982-04-04 -8843,359,94,31,12.0,17,7.0,7,0.0,73,,,,12,1982-04-04 -8844,359,186,0,7.0,11,6.0,6,1.0,74,,,,11,1982-04-04 -8845,359,195,36,18.0,23,9.0,9,0.0,70,,,,15,1982-04-04 -8846,359,200,24,4.0,24,10.0,10,0.0,68,,,,17,1982-04-04 -8847,359,202,5,27.0,7,,11,0.0,75,,,,2,1982-04-04 -8848,359,157,26,25.0,13,,12,0.0,59,,,,6,1982-04-04 -8849,359,204,20,29.0,20,,14,0.0,32,,,,20,1982-04-04 -8850,359,194,55,14.0,19,,15,0.0,27,,,,20,1982-04-04 -8851,359,199,36,17.0,21,8.0,8,0.0,73,,,,12,1982-04-04 -8852,360,203,43,32.0,13,,10,0.0,7,,,,22,1982-04-25 -8853,360,117,51,35.0,8,,14,0.0,0,,,,10,1982-04-25 -8854,360,204,24,4.0,11,,13,0.0,0,,,,7,1982-04-25 -8855,360,109,49,22.0,7,,12,0.0,4,,,,10,1982-04-25 -8856,360,116,3,15.0,2,,11,0.0,6,,,,5,1982-04-25 -8857,360,151,49,23.0,6,,9,0.0,24,,,,5,1982-04-25 -8858,360,162,3,16.0,1,,8,0.0,44,,,,101,1982-04-25 -8859,360,169,51,36.0,10,,7,0.0,52,,,,62,1982-04-25 -8860,360,180,52,9.0,12,,6,0.0,54,,,,2,1982-04-25 -8861,360,193,52,10.0,14,5.0,5,2.0,57,,,,13,1982-04-25 -8862,360,196,43,31.0,9,4.0,4,3.0,59,,,,11,1982-04-25 -8863,360,104,24,3.0,5,3.0,3,4.0,60,5866571.0,,,1,1982-04-25 -8864,360,202,5,27.0,3,2.0,2,6.0,60,5799253.0,,,1,1982-04-25 -8865,360,201,5,28.0,4,1.0,1,9.0,60,5798887.0,,,1,1982-04-25 -8866,361,104,24,3.0,5,,19,0.0,29,,,,5,1982-05-09 -8867,361,117,51,35.0,19,,20,0.0,29,,,,7,1982-05-09 -8868,361,94,31,12.0,7,,22,0.0,9,,,,8,1982-05-09 -8869,361,162,3,16.0,2,,23,0.0,7,,,,101,1982-05-09 -8870,361,180,52,9.0,12,,24,0.0,0,,,,8,1982-05-09 -8871,361,151,49,23.0,15,,25,0.0,0,,,,4,1982-05-09 -8872,361,194,55,14.0,0,,29,0.0,0,,,,81,1982-05-09 -8873,361,201,5,28.0,0,,27,0.0,0,,,,54,1982-05-09 -8874,361,202,5,27.0,0,,28,0.0,0,,,,3,1982-05-09 -8875,361,204,24,4.0,20,,18,0.0,33,,,,5,1982-05-09 -8876,361,135,53,33.0,0,,30,0.0,0,,,,81,1982-05-09 -8877,361,203,43,32.0,0,,31,0.0,0,,,,97,1982-05-09 -8878,361,207,36,19.0,0,,32,0.0,0,,,,97,1982-05-09 -8879,361,193,52,10.0,18,,26,0.0,0,,,,4,1982-05-09 -8880,361,109,49,22.0,6,,17,0.0,34,,,,6,1982-05-09 -8881,361,169,51,36.0,21,,21,0.0,13,,,,23,1982-05-09 -8882,361,183,20,30.0,26,,15,0.0,51,,,,37,1982-05-09 -8883,361,196,43,31.0,14,,16,0.0,37,,,,41,1982-05-09 -8884,361,176,2,6.0,3,2.0,2,6.0,70,5749263.0,,,1,1982-05-09 -8885,361,157,26,25.0,14,3.0,3,4.0,69,,,,11,1982-05-09 -8886,361,172,31,11.0,11,4.0,4,3.0,68,,,,12,1982-05-09 -8887,361,136,33,1.0,8,5.0,5,2.0,67,,,,13,1982-05-09 -8888,361,191,54,20.0,23,6.0,6,1.0,67,,,,13,1982-05-09 -8889,361,175,20,29.0,22,7.0,7,0.0,66,,,,14,1982-05-09 -8890,361,186,0,7.0,10,1.0,1,9.0,70,5741995.0,,,1,1982-05-09 -8891,361,171,26,26.0,17,9.0,9,0.0,66,,,,14,1982-05-09 -8892,361,181,0,8.0,4,,10,0.0,70,,,,2,1982-05-09 -8893,361,205,2,5.0,13,,11,0.0,60,,,,20,1982-05-09 -8894,361,199,36,17.0,25,,12,0.0,60,,,,5,1982-05-09 -8895,361,116,3,15.0,1,,13,0.0,59,,,,20,1982-05-09 -8896,361,118,33,2.0,9,,14,0.0,52,,,,20,1982-05-09 -8897,361,195,36,18.0,24,8.0,8,0.0,66,,,,14,1982-05-09 -8898,362,162,3,16.0,1,,19,0.0,14,,,,20,1982-05-23 -8899,362,151,49,23.0,3,,20,0.0,4,,,,86,1982-05-23 -8900,362,183,20,30.0,0,,21,0.0,0,,,,81,1982-05-23 -8901,362,135,53,33.0,0,,22,0.0,0,,,,81,1982-05-23 -8902,362,199,36,17.0,0,,23,0.0,0,,,,81,1982-05-23 -8903,362,117,51,35.0,0,,24,0.0,0,,,,81,1982-05-23 -8904,362,203,43,32.0,0,,28,0.0,0,,,,97,1982-05-23 -8905,362,194,55,14.0,0,,26,0.0,0,,,,81,1982-05-23 -8906,362,169,51,36.0,0,,27,0.0,0,,,,97,1982-05-23 -8907,362,195,36,18.0,0,,29,0.0,0,,,,97,1982-05-23 -8908,362,191,54,20.0,0,,30,0.0,0,,,,97,1982-05-23 -8909,362,207,36,19.0,0,,31,0.0,0,,,,97,1982-05-23 -8910,362,193,52,10.0,20,,18,0.0,22,,,,26,1982-05-23 -8911,362,196,43,31.0,0,,25,0.0,0,,,,81,1982-05-23 -8912,362,157,26,25.0,16,,17,0.0,27,,,,44,1982-05-23 -8913,362,118,33,2.0,2,1.0,1,9.0,76,6851259.0,,,1,1982-05-23 -8914,362,180,52,9.0,14,,15,0.0,31,,,,24,1982-05-23 -8915,362,171,26,26.0,18,,16,0.0,29,,,,64,1982-05-23 -8916,362,109,49,22.0,7,3.0,3,4.0,75,,,,60,1982-05-23 -8917,362,94,31,12.0,11,4.0,4,3.0,75,,,,11,1982-05-23 -8918,362,172,31,11.0,15,5.0,5,2.0,75,,,,11,1982-05-23 -8919,362,205,2,5.0,8,6.0,6,1.0,74,,,,6,1982-05-23 -8920,362,116,3,15.0,4,7.0,7,0.0,73,,,,20,1982-05-23 -8921,362,201,5,28.0,5,2.0,2,6.0,75,,,,60,1982-05-23 -8922,362,175,20,29.0,19,9.0,9,0.0,70,,,,16,1982-05-23 -8923,362,104,24,3.0,9,10.0,10,0.0,69,,,,22,1982-05-23 -8924,362,176,2,6.0,6,,11,0.0,64,,,,4,1982-05-23 -8925,362,181,0,8.0,12,,12,0.0,56,,,,5,1982-05-23 -8926,362,136,33,1.0,13,,13,0.0,49,,,,101,1982-05-23 -8927,362,204,24,4.0,17,8.0,8,0.0,72,,,,14,1982-05-23 -8928,362,186,0,7.0,10,,14,0.0,35,,,,10,1982-05-23 -8929,363,193,52,10.0,25,,18,0.0,13,,,,20,1982-06-06 -8930,363,194,55,14.0,11,,19,0.0,6,,,,4,1982-06-06 -8931,363,118,33,2.0,14,,20,0.0,6,,,,4,1982-06-06 -8932,363,109,49,22.0,2,,21,0.0,2,,,,7,1982-06-06 -8933,363,196,43,31.0,22,,22,0.0,2,,,,80,1982-06-06 -8934,363,203,43,32.0,23,,26,0.0,0,,,,31,1982-06-06 -8935,363,195,36,18.0,21,,24,0.0,0,,,,4,1982-06-06 -8936,363,207,36,19.0,0,,27,0.0,0,,,,81,1982-06-06 -8937,363,136,33,1.0,0,,28,0.0,0,,,,81,1982-06-06 -8938,363,135,53,33.0,0,,29,0.0,0,,,,81,1982-06-06 -8939,363,172,31,11.0,8,,17,0.0,17,,,,6,1982-06-06 -8940,363,180,52,9.0,5,,23,0.0,1,,,,20,1982-06-06 -8941,363,151,49,23.0,6,,16,0.0,30,,,,4,1982-06-06 -8942,363,183,20,30.0,24,,25,0.0,0,,,,4,1982-06-06 -8943,363,181,0,8.0,10,,14,0.0,40,,,,4,1982-06-06 -8944,363,104,24,3.0,16,,15,0.0,40,,,,20,1982-06-06 -8945,363,186,0,7.0,17,1.0,1,9.0,62,7121043.0,,,1,1982-06-06 -8946,363,157,26,25.0,9,2.0,2,6.0,62,7136769.0,,,1,1982-06-06 -8947,363,201,5,28.0,4,3.0,3,4.0,62,7149120.0,,,1,1982-06-06 -8948,363,176,2,6.0,3,4.0,4,3.0,62,7193019.0,,,1,1982-06-06 -8949,363,171,26,26.0,13,6.0,6,1.0,61,,,,11,1982-06-06 -8950,363,205,2,5.0,12,5.0,5,2.0,62,7204800.0,,,1,1982-06-06 -8951,363,175,20,29.0,19,8.0,8,0.0,61,,,,11,1982-06-06 -8952,363,204,24,4.0,20,9.0,9,0.0,60,,,,12,1982-06-06 -8953,363,162,3,16.0,15,10.0,10,0.0,59,,,,13,1982-06-06 -8954,363,191,54,20.0,26,11.0,11,0.0,59,,,,13,1982-06-06 -8955,363,116,3,15.0,1,,12,0.0,54,,,,62,1982-06-06 -8956,363,94,31,12.0,7,,13,0.0,44,,,,5,1982-06-06 -8957,363,199,36,17.0,18,7.0,7,0.0,61,,,,11,1982-06-06 -8958,364,194,55,14.0,20,,21,0.0,7,,,,8,1982-06-13 -8959,364,193,52,10.0,24,,18,0.0,20,,,,5,1982-06-13 -8960,364,181,0,8.0,11,,19,0.0,17,,,,8,1982-06-13 -8961,364,171,26,26.0,19,,20,0.0,8,,,,69,1982-06-13 -8962,364,151,49,23.0,5,,22,0.0,2,,,,4,1982-06-13 -8963,364,191,54,20.0,0,,29,0.0,0,,,,81,1982-06-13 -8964,364,196,43,31.0,18,,24,0.0,0,,,,54,1982-06-13 -8965,364,203,43,32.0,23,,25,0.0,0,,,,104,1982-06-13 -8966,364,208,53,33.0,25,,26,0.0,0,,,,4,1982-06-13 -8967,364,180,52,9.0,0,,27,0.0,0,,,,81,1982-06-13 -8968,364,207,36,19.0,0,,28,0.0,0,,,,81,1982-06-13 -8969,364,162,3,16.0,2,,17,0.0,28,,,,20,1982-06-13 -8970,364,94,31,12.0,14,,23,0.0,2,,,,4,1982-06-13 -8971,364,116,3,15.0,3,,16,0.0,30,,,,5,1982-06-13 -8972,364,157,26,25.0,12,10.0,10,0.0,66,,,,60,1982-06-13 -8973,364,195,36,18.0,21,,14,0.0,47,,,,5,1982-06-13 -8974,364,136,33,1.0,4,1.0,1,9.0,70,6399577.0,,,1,1982-06-13 -8975,364,118,33,2.0,8,2.0,2,6.0,70,6413376.0,,,1,1982-06-13 -8976,364,186,0,7.0,6,3.0,3,4.0,70,6461413.0,,,1,1982-06-13 -8977,364,172,31,11.0,10,4.0,4,3.0,69,,,,11,1982-06-13 -8978,364,104,24,3.0,15,,15,0.0,41,,,,5,1982-06-13 -8979,364,109,49,22.0,9,6.0,6,1.0,68,,,,60,1982-06-13 -8980,364,175,20,29.0,16,5.0,5,2.0,69,,,,11,1982-06-13 -8981,364,183,20,30.0,17,8.0,8,0.0,68,,,,12,1982-06-13 -8982,364,201,5,28.0,1,9.0,9,0.0,67,,,,13,1982-06-13 -8983,364,199,36,17.0,22,11.0,11,0.0,66,,,,14,1982-06-13 -8984,364,204,24,4.0,26,,12,0.0,59,,,,62,1982-06-13 -8985,364,176,2,6.0,7,,13,0.0,52,,,,6,1982-06-13 -8986,364,205,2,5.0,13,7.0,7,0.0,68,,,,60,1982-06-13 -8987,365,176,2,6.0,7,3.0,3,4.0,72,5905619.0,,,1,1982-07-03 -8988,365,201,5,28.0,4,1.0,1,9.0,72,5883254.0,,,1,1982-07-03 -8989,365,136,33,1.0,3,2.0,2,6.0,72,5904903.0,,,1,1982-07-03 -8990,365,181,0,8.0,5,4.0,4,3.0,72,5966983.0,,,1,1982-07-03 -8991,365,151,49,23.0,8,11.0,11,0.0,70,,,,12,1982-07-03 -8992,365,183,20,30.0,16,6.0,6,1.0,71,,,,11,1982-07-03 -8993,365,205,2,5.0,12,5.0,5,2.0,71,,,,11,1982-07-03 -8994,365,207,36,19.0,0,,31,0.0,0,,,,97,1982-07-03 -8995,365,89,31,12.0,0,,30,0.0,0,,,,81,1982-07-03 -8996,365,157,26,25.0,0,,29,0.0,0,,,,81,1982-07-03 -8997,365,169,51,36.0,0,,28,0.0,0,,,,81,1982-07-03 -8998,365,194,55,14.0,0,,27,0.0,0,,,,81,1982-07-03 -8999,365,117,51,35.0,13,,25,0.0,15,,,,44,1982-07-03 -9000,365,191,54,20.0,19,,24,0.0,18,,,,69,1982-07-03 -9001,365,195,36,18.0,22,,23,0.0,21,,,,5,1982-07-03 -9002,365,204,24,4.0,20,,22,0.0,21,,,,37,1982-07-03 -9003,365,162,3,16.0,1,,21,0.0,21,,,,20,1982-07-03 -9004,365,116,3,15.0,2,,20,0.0,33,,,,5,1982-07-03 -9005,365,171,26,26.0,21,,26,0.0,4,,,,64,1982-07-03 -9006,365,172,31,11.0,15,,18,0.0,40,,,,64,1982-07-03 -9007,365,109,49,22.0,9,,19,0.0,35,,,,10,1982-07-03 -9008,365,104,24,3.0,14,7.0,7,0.0,71,,,,11,1982-07-03 -9009,365,174,5,27.0,6,8.0,8,0.0,71,,,,11,1982-07-03 -9010,365,186,0,7.0,11,9.0,9,0.0,71,,,,11,1982-07-03 -9011,365,180,52,9.0,18,12.0,12,0.0,70,,,,12,1982-07-03 -9012,365,175,20,29.0,17,10.0,10,0.0,71,,,,11,1982-07-03 -9013,365,196,43,31.0,23,14.0,14,0.0,69,,,,13,1982-07-03 -9014,365,118,33,2.0,10,15.0,15,0.0,69,,,,13,1982-07-03 -9015,365,199,36,17.0,24,,16,0.0,60,,,,5,1982-07-03 -9016,365,135,53,33.0,26,,17,0.0,41,,,,5,1982-07-03 -9017,365,193,52,10.0,25,13.0,13,0.0,70,,,,12,1982-07-03 -9018,366,94,31,12.0,23,,18,0.0,29,,,,100,1982-07-18 -9019,366,191,54,20.0,21,,22,0.0,2,,,,4,1982-07-18 -9020,366,136,33,1.0,3,,19,0.0,9,,,,69,1982-07-18 -9021,366,194,55,14.0,19,,20,0.0,3,,,,5,1982-07-18 -9022,366,196,43,31.0,18,,21,0.0,2,,,,4,1982-07-18 -9023,366,186,0,7.0,12,,23,0.0,2,,,,20,1982-07-18 -9024,366,195,36,18.0,0,,30,0.0,0,,,,81,1982-07-18 -9025,366,169,51,36.0,15,,26,0.0,0,,,,4,1982-07-18 -9026,366,180,52,9.0,0,,27,0.0,0,,,,81,1982-07-18 -9027,366,135,53,33.0,0,,28,0.0,0,,,,81,1982-07-18 -9028,366,193,52,10.0,0,,29,0.0,0,,,,81,1982-07-18 -9029,366,117,51,35.0,16,,17,0.0,40,,,,86,1982-07-18 -9030,366,118,33,2.0,2,,24,0.0,0,,,,4,1982-07-18 -9031,366,171,26,26.0,20,,16,0.0,41,,,,6,1982-07-18 -9032,366,162,3,16.0,6,,25,0.0,0,,,,4,1982-07-18 -9033,366,176,2,6.0,1,,14,0.0,50,,,,69,1982-07-18 -9034,366,201,5,28.0,4,2.0,2,6.0,76,5759538.0,,,1,1982-07-18 -9035,366,174,5,27.0,13,3.0,3,4.0,76,5772248.0,,,1,1982-07-18 -9036,366,172,31,11.0,7,4.0,4,3.0,76,5775054.0,,,1,1982-07-18 -9037,366,205,2,5.0,10,5.0,5,2.0,76,5775242.0,,,1,1982-07-18 -9038,366,116,3,15.0,8,6.0,6,1.0,76,5775448.0,,,1,1982-07-18 -9039,366,181,0,8.0,5,1.0,1,9.0,76,5733812.0,,,1,1982-07-18 -9040,366,104,24,3.0,9,,15,0.0,44,,,,5,1982-07-18 -9041,366,204,24,4.0,17,8.0,8,0.0,75,,,,11,1982-07-18 -9042,366,183,20,30.0,26,9.0,9,0.0,74,,,,12,1982-07-18 -9043,366,199,36,17.0,25,10.0,10,0.0,73,,,,13,1982-07-18 -9044,366,109,49,22.0,11,,11,0.0,66,,,,10,1982-07-18 -9045,366,157,26,25.0,24,,12,0.0,60,,,,5,1982-07-18 -9046,366,175,20,29.0,22,,13,0.0,59,,,,5,1982-07-18 -9047,366,151,49,23.0,14,7.0,7,0.0,75,,,,11,1982-07-18 -9048,367,109,49,22.0,7,,17,0.0,25,,,,20,1982-07-25 -9049,367,136,33,1.0,6,,18,0.0,23,,,,5,1982-07-25 -9050,367,172,31,11.0,13,,19,0.0,17,,,,69,1982-07-25 -9051,367,186,0,7.0,12,,20,0.0,13,,,,10,1982-07-25 -9052,367,199,36,17.0,26,,21,0.0,10,,,,20,1982-07-25 -9053,367,183,20,30.0,25,,22,0.0,10,,,,4,1982-07-25 -9054,367,196,43,31.0,17,,25,0.0,0,,,,86,1982-07-25 -9055,367,193,52,10.0,22,,24,0.0,2,,,,20,1982-07-25 -9056,367,169,51,36.0,21,,26,0.0,0,,,,10,1982-07-25 -9057,367,135,53,33.0,0,,27,0.0,0,,,,81,1982-07-25 -9058,367,194,55,14.0,0,,28,0.0,0,,,,81,1982-07-25 -9059,367,157,26,25.0,19,16.0,16,0.0,49,,,,15,1982-07-25 -9060,367,118,33,2.0,4,,23,0.0,8,,,,5,1982-07-25 -9061,367,195,36,18.0,0,,29,0.0,0,,,,81,1982-07-25 -9062,367,117,51,35.0,14,15.0,15,0.0,50,,,,14,1982-07-25 -9063,367,175,20,29.0,20,13.0,13,0.0,52,,,,12,1982-07-25 -9064,367,171,26,26.0,16,14.0,14,0.0,51,,,,13,1982-07-25 -9065,367,162,3,16.0,1,1.0,1,9.0,54,5613217.0,,,1,1982-07-25 -9066,367,116,3,15.0,2,2.0,2,6.0,54,5630525.0,,,1,1982-07-25 -9067,367,201,5,28.0,3,3.0,3,4.0,54,5655345.0,,,1,1982-07-25 -9068,367,176,2,6.0,10,5.0,5,2.0,54,5704211.0,,,1,1982-07-25 -9069,367,104,24,3.0,15,6.0,6,1.0,54,5705556.0,,,1,1982-07-25 -9070,367,174,5,27.0,5,4.0,4,3.0,54,5689458.0,,,1,1982-07-25 -9071,367,181,0,8.0,9,8.0,8,0.0,53,,,,11,1982-07-25 -9072,367,151,49,23.0,8,9.0,9,0.0,53,,,,11,1982-07-25 -9073,367,204,24,4.0,23,10.0,10,0.0,53,,,,11,1982-07-25 -9074,367,180,52,9.0,18,11.0,11,0.0,52,,,,12,1982-07-25 -9075,367,208,31,12.0,24,12.0,12,0.0,52,,,,12,1982-07-25 -9076,367,205,2,5.0,11,7.0,7,0.0,53,,,,11,1982-07-25 -9077,368,157,26,25.0,12,,22,0.0,8,,,,69,1982-08-08 -9078,368,193,52,10.0,22,,18,0.0,17,,,,4,1982-08-08 -9079,368,116,3,15.0,2,,19,0.0,14,,,,98,1982-08-08 -9080,368,118,33,2.0,6,,20,0.0,13,,,,5,1982-08-08 -9081,368,109,49,22.0,8,,21,0.0,9,,,,6,1982-08-08 -9082,368,183,20,30.0,23,,23,0.0,6,,,,69,1982-08-08 -9083,368,169,51,36.0,0,,29,0.0,0,,,,81,1982-08-08 -9084,368,180,52,9.0,16,,25,0.0,3,,,,8,1982-08-08 -9085,368,201,5,28.0,1,,26,0.0,0,,,,3,1982-08-08 -9086,368,209,53,33.0,0,,27,0.0,0,,,,81,1982-08-08 -9087,368,210,36,17.0,0,,28,0.0,0,,,,81,1982-08-08 -9088,368,136,33,1.0,4,,17,0.0,18,,,,4,1982-08-08 -9089,368,196,43,31.0,20,,24,0.0,3,,,,38,1982-08-08 -9090,368,172,31,11.0,13,,16,0.0,21,,,,64,1982-08-08 -9091,368,162,3,16.0,3,2.0,2,6.0,45,5261557.0,,,1,1982-08-08 -9092,368,205,2,5.0,19,,14,0.0,25,,,,5,1982-08-08 -9093,368,174,5,27.0,5,1.0,1,9.0,45,5245178.0,,,1,1982-08-08 -9094,368,176,2,6.0,9,3.0,3,4.0,44,,,,11,1982-08-08 -9095,368,104,24,3.0,7,4.0,4,3.0,44,,,,11,1982-08-08 -9096,368,175,20,29.0,26,6.0,6,1.0,44,,,,11,1982-08-08 -9097,368,204,24,4.0,17,7.0,7,0.0,44,,,,11,1982-08-08 -9098,368,151,49,23.0,11,5.0,5,2.0,44,,,,11,1982-08-08 -9099,368,94,31,12.0,18,9.0,9,0.0,43,,,,12,1982-08-08 -9100,368,117,51,35.0,14,10.0,10,0.0,43,,,,12,1982-08-08 -9101,368,191,54,20.0,25,11.0,11,0.0,43,,,,12,1982-08-08 -9102,368,186,0,7.0,10,,12,0.0,36,,,,22,1982-08-08 -9103,368,171,26,26.0,15,,13,0.0,36,,,,64,1982-08-08 -9104,368,194,55,14.0,21,8.0,8,0.0,44,,,,11,1982-08-08 -9105,368,195,36,18.0,24,,15,0.0,22,,,,27,1982-08-08 -9106,369,104,24,3.0,8,,22,0.0,1,,,,20,1982-08-15 -9107,369,180,52,9.0,25,,18,0.0,15,,,,20,1982-08-15 -9108,369,117,51,35.0,15,,19,0.0,7,,,,22,1982-08-15 -9109,369,169,51,36.0,17,,20,0.0,7,,,,7,1982-08-15 -9110,369,194,55,14.0,16,,21,0.0,6,,,,20,1982-08-15 -9111,369,193,52,10.0,0,,29,0.0,0,,,,81,1982-08-15 -9112,369,109,49,22.0,11,,25,0.0,0,,,,4,1982-08-15 -9113,369,151,49,23.0,13,,26,0.0,0,,,,4,1982-08-15 -9114,369,195,36,18.0,0,,27,0.0,0,,,,81,1982-08-15 -9115,369,196,43,31.0,0,,28,0.0,0,,,,81,1982-08-15 -9116,369,162,3,16.0,5,,17,0.0,16,,,,98,1982-08-15 -9117,369,205,2,5.0,9,,24,0.0,0,,,,4,1982-08-15 -9118,369,94,31,12.0,12,,16,0.0,17,,,,5,1982-08-15 -9119,369,210,36,17.0,24,,23,0.0,1,,,,38,1982-08-15 -9120,369,118,33,2.0,2,,14,0.0,27,,,,5,1982-08-15 -9121,369,157,26,25.0,22,,15,0.0,22,,,,5,1982-08-15 -9122,369,176,2,6.0,6,2.0,2,6.0,53,5102262.0,,,1,1982-08-15 -9123,369,171,26,26.0,14,3.0,3,4.0,52,,,,11,1982-08-15 -9124,369,174,5,27.0,4,4.0,4,3.0,52,,,,11,1982-08-15 -9125,369,181,0,8.0,10,5.0,5,2.0,52,,,,11,1982-08-15 -9126,369,183,20,30.0,23,6.0,6,1.0,52,,,,11,1982-08-15 -9127,369,172,31,11.0,7,1.0,1,9.0,53,5102212.0,,,1,1982-08-15 -9128,369,116,3,15.0,3,8.0,8,0.0,48,,,,98,1982-08-15 -9129,369,186,0,7.0,18,9.0,9,0.0,44,,,,5,1982-08-15 -9130,369,204,24,4.0,19,,10,0.0,32,,,,5,1982-08-15 -9131,369,136,33,1.0,1,,11,0.0,31,,,,10,1982-08-15 -9132,369,209,53,33.0,26,,12,0.0,28,,,,20,1982-08-15 -9133,369,191,54,20.0,20,7.0,7,0.0,51,,,,12,1982-08-15 -9134,369,175,20,29.0,21,,13,0.0,28,,,,5,1982-08-15 -9135,370,196,43,31.0,17,,19,0.0,44,,,,5,1982-08-29 -9136,370,171,26,26.0,13,,20,0.0,33,,,,64,1982-08-29 -9137,370,169,51,36.0,23,,21,0.0,31,,,,5,1982-08-29 -9138,370,195,36,18.0,24,,22,0.0,31,,,,47,1982-08-29 -9139,370,210,36,17.0,22,,23,0.0,25,,,,20,1982-08-29 -9140,370,174,5,27.0,10,,26,0.0,0,,,,82,1982-08-29 -9141,370,194,55,14.0,19,,25,0.0,4,,,,5,1982-08-29 -9142,370,191,54,20.0,0,,27,0.0,0,,,,81,1982-08-29 -9143,370,209,53,33.0,0,,28,0.0,0,,,,81,1982-08-29 -9144,370,183,20,30.0,0,,29,0.0,0,,,,81,1982-08-29 -9145,370,180,52,9.0,20,,18,0.0,55,,,,83,1982-08-29 -9146,370,117,51,35.0,21,,24,0.0,24,,,,5,1982-08-29 -9147,370,157,26,25.0,16,,17,0.0,70,,,,64,1982-08-29 -9148,370,205,2,5.0,7,9.0,9,0.0,79,,,,11,1982-08-29 -9149,370,175,20,29.0,14,15.0,15,0.0,76,,,,14,1982-08-29 -9150,370,193,52,10.0,25,14.0,14,0.0,76,,,,14,1982-08-29 -9151,370,186,0,7.0,11,13.0,13,0.0,77,,,,13,1982-08-29 -9152,370,151,49,23.0,9,12.0,12,0.0,78,,,,12,1982-08-29 -9153,370,204,24,4.0,18,11.0,11,0.0,78,,,,12,1982-08-29 -9154,370,109,49,22.0,5,10.0,10,0.0,78,,,,12,1982-08-29 -9155,370,94,31,12.0,26,8.0,8,0.0,79,,,,11,1982-08-29 -9156,370,104,24,3.0,12,7.0,7,0.0,79,,,,11,1982-08-29 -9157,370,172,31,11.0,15,6.0,6,1.0,79,,,,11,1982-08-29 -9158,370,136,33,1.0,6,4.0,4,3.0,79,,,,11,1982-08-29 -9159,370,181,0,8.0,4,3.0,3,4.0,80,5621430.0,,,1,1982-08-29 -9160,370,116,3,15.0,1,2.0,2,6.0,80,5565529.0,,,1,1982-08-29 -9161,370,176,2,6.0,8,1.0,1,9.0,80,5561087.0,,,1,1982-08-29 -9162,370,162,3,16.0,2,16.0,16,0.0,75,,,,98,1982-08-29 -9163,370,118,33,2.0,3,5.0,5,2.0,79,,,,11,1982-08-29 -9164,371,157,26,25.0,14,6.0,6,1.0,51,,,,11,1982-09-12 -9165,371,174,5,27.0,3,2.0,2,6.0,52,4959798.0,,,1,1982-09-12 -9166,371,209,53,33.0,0,,30,0.0,0,,,,81,1982-09-12 -9167,371,195,36,18.0,0,,29,0.0,0,,,,81,1982-09-12 -9168,371,180,52,9.0,0,,28,0.0,0,,,,81,1982-09-12 -9169,371,210,36,17.0,0,,27,0.0,0,,,,81,1982-09-12 -9170,371,204,24,4.0,20,,26,0.0,0,,,,4,1982-09-12 -9171,371,117,51,35.0,16,,25,0.0,0,,,,4,1982-09-12 -9172,371,205,2,5.0,13,,24,0.0,0,,,,4,1982-09-12 -9173,371,171,26,26.0,21,,22,0.0,5,,,,6,1982-09-12 -9174,371,118,33,2.0,4,,21,0.0,6,,,,8,1982-09-12 -9175,371,136,33,1.0,2,,20,0.0,7,,,,5,1982-09-12 -9176,371,196,43,31.0,15,,19,0.0,10,,,,36,1982-09-12 -9177,371,181,0,8.0,10,,18,0.0,21,,,,23,1982-09-12 -9178,371,116,3,15.0,5,,17,0.0,27,,,,98,1982-09-12 -9179,371,169,51,36.0,22,,23,0.0,2,,,,5,1982-09-12 -9180,371,151,49,23.0,8,,15,0.0,32,,,,64,1982-09-12 -9181,371,175,20,29.0,19,,16,0.0,28,,,,80,1982-09-12 -9182,371,186,0,7.0,12,4.0,4,3.0,52,5033579.0,,,1,1982-09-12 -9183,371,104,24,3.0,11,5.0,5,2.0,51,,,,11,1982-09-12 -9184,371,162,3,16.0,6,1.0,1,9.0,52,4945734.0,,,1,1982-09-12 -9185,371,94,31,12.0,23,7.0,7,0.0,51,,,,11,1982-09-12 -9186,371,176,2,6.0,7,8.0,8,0.0,50,,,,12,1982-09-12 -9187,371,206,5,28.0,1,3.0,3,4.0,52,4994186.0,,,1,1982-09-12 -9188,371,109,49,22.0,9,10.0,10,0.0,50,,,,12,1982-09-12 -9189,371,191,54,20.0,26,11.0,11,0.0,49,,,,13,1982-09-12 -9190,371,183,20,30.0,24,12.0,12,0.0,49,,,,13,1982-09-12 -9191,371,194,55,14.0,18,,13,0.0,40,,,,62,1982-09-12 -9192,371,172,31,11.0,17,,14,0.0,33,,,,37,1982-09-12 -9193,371,193,52,10.0,25,9.0,9,0.0,50,,,,12,1982-09-12 -9194,372,117,51,35.0,10,,17,0.0,32,,,,105,1982-09-25 -9195,372,172,31,11.0,20,,18,0.0,28,,,,5,1982-09-25 -9196,372,206,5,28.0,7,,19,0.0,26,,,,22,1982-09-25 -9197,372,136,33,1.0,12,,20,0.0,26,,,,105,1982-09-25 -9198,372,162,3,16.0,2,,21,0.0,20,,,,5,1982-09-25 -9199,372,118,33,2.0,5,,22,0.0,17,,,,8,1982-09-25 -9200,372,194,55,14.0,15,,26,0.0,0,,,,5,1982-09-25 -9201,372,171,26,26.0,11,,24,0.0,5,,,,80,1982-09-25 -9202,372,174,5,27.0,8,,25,0.0,0,,,,54,1982-09-25 -9203,372,196,43,31.0,27,,27,0.0,0,,,,3,1982-09-25 -9204,372,169,51,36.0,0,,28,0.0,0,,,,81,1982-09-25 -9205,372,193,52,10.0,0,,29,0.0,0,,,,81,1982-09-25 -9206,372,94,31,12.0,21,,23,0.0,8,,,,4,1982-09-25 -9207,372,209,53,33.0,26,,16,0.0,39,,,,20,1982-09-25 -9208,372,191,54,20.0,0,,30,0.0,0,,,,81,1982-09-25 -9209,372,180,52,9.0,22,,14,0.0,62,,,,62,1982-09-25 -9210,372,181,0,8.0,13,,15,0.0,53,,,,5,1982-09-25 -9211,372,186,0,7.0,9,2.0,2,6.0,75,6144180.0,,,1,1982-09-25 -9212,372,157,26,25.0,4,3.0,3,4.0,75,6173338.0,,,1,1982-09-25 -9213,372,116,3,15.0,1,4.0,4,3.0,75,6185536.0,,,1,1982-09-25 -9214,372,176,2,6.0,6,5.0,5,2.0,75,6188263.0,,,1,1982-09-25 -9215,372,205,2,5.0,14,6.0,6,1.0,74,,,,11,1982-09-25 -9216,372,104,24,3.0,3,1.0,1,9.0,75,6116888.0,,,1,1982-09-25 -9217,372,204,24,4.0,19,8.0,8,0.0,74,,,,11,1982-09-25 -9218,372,109,49,22.0,18,9.0,9,0.0,73,,,,12,1982-09-25 -9219,372,151,49,23.0,16,10.0,10,0.0,73,,,,12,1982-09-25 -9220,372,183,20,30.0,23,11.0,11,0.0,73,,,,12,1982-09-25 -9221,372,210,36,17.0,25,12.0,12,0.0,73,,,,12,1982-09-25 -9222,372,195,36,18.0,24,13.0,13,0.0,69,,,,16,1982-09-25 -9223,372,175,20,29.0,17,7.0,7,0.0,74,,,,11,1982-09-25 -9224,373,157,3,16.0,8,,18,0.0,41,,,,23,1983-03-13 -9225,373,186,0,7.0,16,,19,0.0,34,,,,5,1983-03-13 -9226,373,195,26,26.0,17,,20,0.0,25,,,,5,1983-03-13 -9227,373,183,49,23.0,10,,21,0.0,23,,,,4,1983-03-13 -9228,373,196,26,25.0,12,,22,0.0,22,,,,22,1983-03-13 -9229,373,104,24,3.0,11,,26,0.0,7,,,,5,1983-03-13 -9230,373,189,43,31.0,24,,24,0.0,17,,,,5,1983-03-13 -9231,373,151,51,36.0,15,,25,0.0,16,,,,20,1983-03-13 -9232,373,109,49,22.0,0,,27,0.0,0,,,,81,1983-03-13 -9233,373,159,43,32.0,0,,28,0.0,0,,,,81,1983-03-13 -9234,373,194,53,33.0,14,,17,0.0,53,,,,62,1983-03-13 -9235,373,118,33,6.0,7,,23,0.0,19,,,,43,1983-03-13 -9236,373,172,31,11.0,13,,16,0.0,60,,,,2,1983-03-13 -9237,373,180,52,9.0,25,15.0,14,0.0,59,,,,14,1983-03-13 -9238,373,136,33,5.0,4,1.0,1,9.0,63,6507731.0,,,1,1983-03-13 -9239,373,176,2,1.0,1,,15,0.0,63,,,,2,1983-03-13 -9240,373,181,0,8.0,9,3.0,2,4.0,63,6559614.0,,,1,1983-03-13 -9241,373,171,2,2.0,18,4.0,3,3.0,63,6581682.0,,,1,1983-03-13 -9242,373,174,5,27.0,3,5.0,4,2.0,63,6585848.0,,,1,1983-03-13 -9243,373,116,3,15.0,2,7.0,6,0.0,62,,,,11,1983-03-13 -9244,373,117,51,35.0,5,8.0,7,0.0,62,,,,11,1983-03-13 -9245,373,175,20,29.0,20,6.0,5,1.0,63,6585938.0,,,1,1983-03-13 -9246,373,162,5,28.0,6,10.0,9,0.0,62,,,,11,1983-03-13 -9247,373,192,24,4.0,21,11.0,10,0.0,62,,,,11,1983-03-13 -9248,373,94,31,12.0,22,12.0,11,0.0,61,,,,12,1983-03-13 -9249,373,187,53,34.0,19,13.0,12,0.0,60,,,,13,1983-03-13 -9250,373,193,48,17.0,26,14.0,13,0.0,59,,,,14,1983-03-13 -9251,373,191,20,30.0,23,9.0,8,0.0,62,,,,11,1983-03-13 -9252,374,183,49,23.0,21,,21,0.0,26,,,,20,1983-03-27 -9253,374,194,53,33.0,18,,18,0.0,27,,,,6,1983-03-27 -9254,374,196,26,25.0,10,,19,0.0,26,,,,4,1983-03-27 -9255,374,151,51,36.0,14,,20,0.0,26,,,,84,1983-03-27 -9256,374,174,5,27.0,1,,22,0.0,25,,,,4,1983-03-27 -9257,374,172,31,11.0,5,,17,0.0,29,,,,64,1983-03-27 -9258,374,193,48,17.0,25,,24,0.0,25,,,,6,1983-03-27 -9259,374,117,51,35.0,6,,25,0.0,11,,,,20,1983-03-27 -9260,374,180,52,9.0,24,,26,0.0,3,,,,20,1983-03-27 -9261,374,189,43,31.0,0,,27,0.0,0,,,,81,1983-03-27 -9262,374,159,43,32.0,0,,28,0.0,0,,,,81,1983-03-27 -9263,374,176,2,1.0,3,,23,0.0,25,,,,4,1983-03-27 -9264,374,109,49,22.0,19,,16,0.0,48,,,,6,1983-03-27 -9265,374,136,33,5.0,20,,15,0.0,51,,,,37,1983-03-27 -9266,374,177,20,30.0,12,,14,0.0,58,,,,100,1983-03-27 -9267,374,181,0,8.0,23,2.0,2,6.0,75,6842882.0,,,1,1983-03-27 -9268,374,162,5,28.0,2,3.0,3,4.0,75,6888527.0,,,1,1983-03-27 -9269,374,171,2,2.0,4,4.0,4,3.0,74,,,,11,1983-03-27 -9270,374,175,20,29.0,16,5.0,5,2.0,74,,,,11,1983-03-27 -9271,374,187,53,34.0,17,6.0,6,1.0,74,,,,11,1983-03-27 -9272,374,195,26,26.0,26,7.0,7,0.0,73,,,,12,1983-03-27 -9273,374,186,0,7.0,22,1.0,1,9.0,75,6814889.0,,,1,1983-03-27 -9274,374,104,24,3.0,7,9.0,9,0.0,73,,,,12,1983-03-27 -9275,374,118,33,6.0,11,10.0,10,0.0,72,,,,99,1983-03-27 -9276,374,116,3,15.0,8,11.0,11,0.0,72,,,,13,1983-03-27 -9277,374,94,31,12.0,13,12.0,12,0.0,72,,,,13,1983-03-27 -9278,374,157,3,16.0,15,13.0,13,0.0,67,,,,6,1983-03-27 -9279,374,192,24,4.0,9,8.0,8,0.0,73,,,,12,1983-03-27 -9280,375,183,49,23.0,8,,18,0.0,28,,,,20,1983-04-17 -9281,375,191,20,30.0,26,,19,0.0,26,,,,6,1983-04-17 -9282,375,194,53,33.0,22,,20,0.0,23,,,,5,1983-04-17 -9283,375,192,24,4.0,24,,21,0.0,21,,,,8,1983-04-17 -9284,375,172,31,11.0,5,,22,0.0,20,,,,10,1983-04-17 -9285,375,118,33,6.0,3,,23,0.0,19,,,,47,1983-04-17 -9286,375,186,0,7.0,14,,26,0.0,3,,,,5,1983-04-17 -9287,375,94,31,12.0,18,,25,0.0,6,,,,68,1983-04-17 -9288,375,193,48,17.0,0,,27,0.0,0,,,,81,1983-04-17 -9289,375,159,43,32.0,0,,28,0.0,0,,,,81,1983-04-17 -9290,375,167,48,18.0,0,,29,0.0,0,,,,81,1983-04-17 -9291,375,181,0,8.0,12,,17,0.0,29,,,,67,1983-04-17 -9292,375,117,51,35.0,9,,24,0.0,14,,,,5,1983-04-17 -9293,375,180,52,9.0,10,,16,0.0,36,,,,101,1983-04-17 -9294,375,189,43,31.0,23,,15,0.0,36,,,,5,1983-04-17 -9295,375,195,26,26.0,25,,14,0.0,47,,,,5,1983-04-17 -9296,375,136,33,5.0,6,2.0,2,6.0,54,5683633.0,,,1,1983-04-17 -9297,375,157,3,16.0,2,3.0,3,4.0,54,5694145.0,,,1,1983-04-17 -9298,375,174,5,27.0,11,4.0,4,3.0,54,5720793.0,,,1,1983-04-17 -9299,375,176,2,1.0,16,5.0,5,2.0,53,,,,11,1983-04-17 -9300,375,171,2,2.0,19,6.0,6,1.0,53,,,,11,1983-04-17 -9301,375,162,5,28.0,4,7.0,7,0.0,53,,,,11,1983-04-17 -9302,375,116,3,15.0,1,1.0,1,9.0,54,5653913.0,,,1,1983-04-17 -9303,375,196,26,25.0,20,9.0,9,0.0,53,,,,11,1983-04-17 -9304,375,175,20,29.0,21,10.0,10,0.0,53,,,,11,1983-04-17 -9305,375,187,53,34.0,17,11.0,11,0.0,52,,,,12,1983-04-17 -9306,375,109,49,22.0,7,12.0,12,0.0,50,,,,14,1983-04-17 -9307,375,151,51,36.0,13,13.0,13,0.0,49,,,,6,1983-04-17 -9308,375,104,24,3.0,15,8.0,8,0.0,53,,,,11,1983-04-17 -9309,376,192,24,4.0,22,,18,0.0,37,,,,4,1983-05-01 -9310,376,117,51,35.0,14,,19,0.0,27,,,,20,1983-05-01 -9311,376,189,43,31.0,26,,20,0.0,20,,,,20,1983-05-01 -9312,376,151,51,36.0,17,,21,0.0,20,,,,22,1983-05-01 -9313,376,181,0,8.0,18,,22,0.0,11,,,,20,1983-05-01 -9314,376,194,53,33.0,21,,25,0.0,3,,,,20,1983-05-01 -9315,376,104,24,3.0,13,,24,0.0,10,,,,4,1983-05-01 -9316,376,157,3,16.0,6,,26,0.0,1,,,,101,1983-05-01 -9317,376,193,48,17.0,0,,27,0.0,0,,,,81,1983-05-01 -9318,376,159,43,32.0,0,,28,0.0,0,,,,81,1983-05-01 -9319,376,196,26,25.0,19,,17,0.0,39,,,,21,1983-05-01 -9320,376,187,53,34.0,23,,23,0.0,11,,,,20,1983-05-01 -9321,376,136,33,5.0,2,,16,0.0,41,,,,5,1983-05-01 -9322,376,175,20,29.0,12,6.0,6,1.0,59,,,,11,1983-05-01 -9323,376,109,49,22.0,8,,14,0.0,45,,,,80,1983-05-01 -9324,376,116,3,15.0,4,2.0,2,6.0,60,5921241.0,,,1,1983-05-01 -9325,376,162,5,28.0,1,3.0,3,4.0,59,,,,11,1983-05-01 -9326,376,176,2,1.0,11,4.0,4,3.0,59,,,,11,1983-05-01 -9327,376,186,0,7.0,24,5.0,5,2.0,59,,,,11,1983-05-01 -9328,376,174,5,27.0,3,1.0,1,9.0,60,5872460.0,,,1,1983-05-01 -9329,376,171,2,2.0,16,7.0,7,0.0,59,,,,11,1983-05-01 -9330,376,172,31,11.0,9,,15,0.0,43,,,,64,1983-05-01 -9331,376,195,26,26.0,25,9.0,9,0.0,58,,,,12,1983-05-01 -9332,376,183,49,23.0,10,10.0,10,0.0,57,,,,5,1983-05-01 -9333,376,180,52,9.0,7,11.0,11,0.0,57,,,,13,1983-05-01 -9334,376,94,31,12.0,15,12.0,12,0.0,56,,,,20,1983-05-01 -9335,376,118,33,6.0,5,,13,0.0,54,,,,20,1983-05-01 -9336,376,191,20,30.0,20,8.0,8,0.0,58,,,,12,1983-05-01 -9337,377,180,52,9.0,16,,18,0.0,3,,,,4,1983-05-15 -9338,377,104,24,3.0,11,,19,0.0,0,,,,4,1983-05-15 -9339,377,94,31,12.0,14,,20,0.0,0,,,,4,1983-05-15 -9340,377,151,51,36.0,0,,21,0.0,0,,,,81,1983-05-15 -9341,377,181,0,8.0,0,,22,0.0,0,,,,81,1983-05-15 -9342,377,193,48,17.0,0,,25,0.0,0,,,,81,1983-05-15 -9343,377,189,43,31.0,0,,24,0.0,0,,,,81,1983-05-15 -9344,377,159,43,32.0,0,,26,0.0,0,,,,81,1983-05-15 -9345,377,187,53,34.0,0,,27,0.0,0,,,,97,1983-05-15 -9346,377,194,53,33.0,0,,28,0.0,0,,,,97,1983-05-15 -9347,377,195,26,26.0,18,,17,0.0,3,,,,4,1983-05-15 -9348,377,186,0,7.0,0,,23,0.0,0,,,,81,1983-05-15 -9349,377,162,5,28.0,2,,16,0.0,6,,,,22,1983-05-15 -9350,377,109,49,22.0,7,,15,0.0,13,,,,6,1983-05-15 -9351,377,157,3,16.0,3,,14,0.0,30,,,,5,1983-05-15 -9352,377,136,33,5.0,6,2.0,2,6.0,76,7016596.0,,,1,1983-05-15 -9353,377,116,3,15.0,1,3.0,3,4.0,76,7029487.0,,,1,1983-05-15 -9354,377,174,5,27.0,4,4.0,4,3.0,76,7062418.0,,,1,1983-05-15 -9355,377,183,49,23.0,13,6.0,6,1.0,74,,,,12,1983-05-15 -9356,377,191,20,30.0,15,7.0,7,0.0,74,,,,12,1983-05-15 -9357,377,192,24,4.0,20,5.0,5,2.0,74,,,,12,1983-05-15 -9358,377,171,2,2.0,8,,9,0.0,53,,,,6,1983-05-15 -9359,377,175,20,29.0,12,,10,0.0,49,,,,4,1983-05-15 -9360,377,117,51,35.0,10,,11,0.0,49,,,,4,1983-05-15 -9361,377,172,31,11.0,19,,12,0.0,49,,,,86,1983-05-15 -9362,377,196,26,25.0,9,,13,0.0,32,,,,22,1983-05-15 -9363,377,118,33,6.0,17,,8,0.0,64,,,,10,1983-05-15 -9364,377,176,2,1.0,5,1.0,1,9.0,76,6998121.0,,,1,1983-05-15 -9365,378,186,0,7.0,20,,22,0.0,8,,,,4,1983-05-22 -9366,378,194,53,33.0,14,,18,0.0,23,,,,5,1983-05-22 -9367,378,162,5,28.0,5,,19,0.0,22,,,,5,1983-05-22 -9368,378,189,43,31.0,24,,20,0.0,19,,,,36,1983-05-22 -9369,378,180,52,9.0,7,,21,0.0,18,,,,36,1983-05-22 -9370,378,193,48,17.0,0,,28,0.0,0,,,,81,1983-05-22 -9371,378,122,20,30.0,18,,24,0.0,4,,,,22,1983-05-22 -9372,378,183,49,23.0,12,,25,0.0,3,,,,37,1983-05-22 -9373,378,118,33,6.0,6,,26,0.0,0,,,,5,1983-05-22 -9374,378,159,43,32.0,0,,27,0.0,0,,,,81,1983-05-22 -9375,378,109,49,22.0,3,,17,0.0,25,,,,98,1983-05-22 -9376,378,196,26,25.0,21,,23,0.0,8,,,,4,1983-05-22 -9377,378,94,31,12.0,19,,16,0.0,30,,,,6,1983-05-22 -9378,378,117,51,35.0,22,7.0,7,0.0,40,5350041.0,,,1,1983-05-22 -9379,378,104,24,3.0,17,14.0,14,0.0,38,,,,12,1983-05-22 -9380,378,181,0,8.0,15,,15,0.0,33,,,,6,1983-05-22 -9381,378,174,5,27.0,2,2.0,2,6.0,40,5254684.0,,,1,1983-05-22 -9382,378,157,3,16.0,8,3.0,3,4.0,40,5271371.0,,,1,1983-05-22 -9383,378,136,33,5.0,4,4.0,4,3.0,40,5273797.0,,,1,1983-05-22 -9384,378,176,2,1.0,9,5.0,5,2.0,40,5281982.0,,,1,1983-05-22 -9385,378,171,2,2.0,11,6.0,6,1.0,40,5324609.0,,,1,1983-05-22 -9386,378,116,3,15.0,1,1.0,1,9.0,40,5231502.0,,,1,1983-05-22 -9387,378,172,31,11.0,13,9.0,9,0.0,39,,,,11,1983-05-22 -9388,378,187,53,34.0,25,10.0,10,0.0,39,,,,11,1983-05-22 -9389,378,175,20,29.0,10,11.0,11,0.0,39,,,,11,1983-05-22 -9390,378,192,24,4.0,23,12.0,12,0.0,39,,,,11,1983-05-22 -9391,378,151,51,36.0,16,8.0,8,0.0,40,5389775.0,,,1,1983-05-22 -9392,378,195,26,26.0,26,13.0,13,0.0,39,,,,11,1983-05-22 -9393,379,109,49,22.0,8,,16,0.0,33,,,,101,1983-06-05 -9394,379,162,5,28.0,1,,17,0.0,31,,,,10,1983-06-05 -9395,379,192,24,4.0,16,,18,0.0,30,,,,10,1983-06-05 -9396,379,196,26,25.0,19,,19,0.0,29,,,,36,1983-06-05 -9397,379,118,33,6.0,15,,22,0.0,24,,,,23,1983-06-05 -9398,379,117,51,35.0,9,,21,0.0,25,,,,5,1983-06-05 -9399,379,172,31,11.0,4,,23,0.0,5,,,,6,1983-06-05 -9400,379,157,3,16.0,7,,24,0.0,4,,,,99,1983-06-05 -9401,379,159,43,32.0,24,,25,0.0,4,,,,25,1983-06-05 -9402,379,187,53,34.0,26,,15,0.0,34,,,,6,1983-06-05 -9403,379,180,52,9.0,22,,20,0.0,26,,,,4,1983-06-05 -9404,379,194,53,33.0,11,,14,0.0,38,,,,62,1983-06-05 -9405,379,122,20,30.0,10,7.0,7,0.0,59,,,,11,1983-06-05 -9406,379,183,49,23.0,25,12.0,12,0.0,56,,,,14,1983-06-05 -9407,379,174,5,27.0,3,,26,0.0,0,,,,5,1983-06-05 -9408,379,195,26,26.0,23,10.0,10,0.0,58,,,,12,1983-06-05 -9409,379,151,51,36.0,17,9.0,9,0.0,59,,,,11,1983-06-05 -9410,379,116,3,15.0,13,8.0,8,0.0,59,,,,11,1983-06-05 -9411,379,94,31,12.0,14,6.0,6,1.0,59,,,,11,1983-06-05 -9412,379,171,2,2.0,20,5.0,5,2.0,60,6746272.0,,,1,1983-06-05 -9413,379,136,33,5.0,2,4.0,4,3.0,60,6725854.0,,,1,1983-06-05 -9414,379,186,0,7.0,21,3.0,3,4.0,60,6662952.0,,,1,1983-06-05 -9415,379,176,2,1.0,12,2.0,2,6.0,60,6661371.0,,,1,1983-06-05 -9416,379,104,24,3.0,6,1.0,1,9.0,60,6653669.0,,,1,1983-06-05 -9417,379,181,0,8.0,18,13.0,13,0.0,49,,,,22,1983-06-05 -9418,379,189,43,31.0,0,,27,0.0,0,,,,54,1983-06-05 -9419,379,175,20,29.0,5,11.0,11,0.0,58,,,,12,1983-06-05 -9420,380,186,0,7.0,20,6.0,6,1.0,69,,,,11,1983-06-12 -9421,380,162,5,28.0,1,1.0,1,9.0,70,6511838.0,,,1,1983-06-12 -9422,380,157,3,16.0,6,2.0,2,6.0,70,6553867.0,,,1,1983-06-12 -9423,380,174,5,27.0,4,3.0,3,4.0,70,6564448.0,,,1,1983-06-12 -9424,380,176,2,1.0,9,4.0,4,3.0,70,6588886.0,,,1,1983-06-12 -9425,380,116,3,15.0,2,5.0,5,2.0,69,,,,11,1983-06-12 -9426,380,122,20,30.0,15,7.0,7,0.0,69,,,,11,1983-06-12 -9427,380,104,24,3.0,17,8.0,8,0.0,68,,,,12,1983-06-12 -9428,380,180,52,9.0,7,9.0,9,0.0,67,,,,13,1983-06-12 -9429,380,183,49,23.0,26,10.0,10,0.0,67,,,,13,1983-06-12 -9430,380,118,33,6.0,5,,12,0.0,56,,,,6,1983-06-12 -9431,380,117,51,35.0,12,,13,0.0,47,,,,101,1983-06-12 -9432,380,151,51,36.0,10,,14,0.0,43,,,,5,1983-06-12 -9433,380,94,31,12.0,18,,15,0.0,43,,,,64,1983-06-12 -9434,380,109,49,22.0,8,,16,0.0,42,,,,5,1983-06-12 -9435,380,192,24,4.0,22,,11,0.0,68,,,,2,1983-06-12 -9436,380,195,26,26.0,24,,18,0.0,32,,,,86,1983-06-12 -9437,380,171,2,2.0,13,,17,0.0,37,,,,6,1983-06-12 -9438,380,197,48,17.0,0,,27,0.0,0,,,,81,1983-06-12 -9439,380,196,26,25.0,16,,26,0.0,0,,,,6,1983-06-12 -9440,380,175,20,29.0,14,,25,0.0,14,,,,7,1983-06-12 -9441,380,172,31,11.0,11,,24,0.0,1,,,,37,1983-06-12 -9442,380,159,43,32.0,0,,28,0.0,0,,,,81,1983-06-12 -9443,380,136,33,5.0,3,,22,0.0,15,,,,37,1983-06-12 -9444,380,187,53,34.0,23,,21,0.0,17,,,,24,1983-06-12 -9445,380,189,43,31.0,25,,20,0.0,26,,,,5,1983-06-12 -9446,380,194,53,33.0,21,,19,0.0,27,,,,5,1983-06-12 -9447,380,181,0,8.0,19,,23,0.0,11,,,,20,1983-06-12 -9448,381,195,26,26.0,22,,19,0.0,48,,,,22,1983-07-16 -9449,381,159,43,32.0,26,,20,0.0,46,,,,69,1983-07-16 -9450,381,117,51,35.0,10,,21,0.0,27,,,,6,1983-07-16 -9451,381,118,33,6.0,5,,22,0.0,9,,,,101,1983-07-16 -9452,381,139,50,40.0,15,,23,0.0,5,,,,69,1983-07-16 -9453,381,157,3,16.0,7,,24,0.0,3,,,,5,1983-07-16 -9454,381,172,31,11.0,4,,26,0.0,1,,,,101,1983-07-16 -9455,381,187,53,34.0,0,,27,0.0,0,,,,81,1983-07-16 -9456,381,94,31,12.0,18,4.0,4,3.0,67,5118732.0,,,1,1983-07-16 -9457,381,185,48,17.0,0,,29,0.0,0,,,,81,1983-07-16 -9458,381,189,43,31.0,0,,28,0.0,0,,,,81,1983-07-16 -9459,381,180,52,9.0,8,,18,0.0,49,,,,5,1983-07-16 -9460,381,151,51,36.0,12,,25,0.0,3,,,,101,1983-07-16 -9461,381,175,20,29.0,19,17.0,17,0.0,64,,,,13,1983-07-16 -9462,381,174,5,27.0,2,3.0,3,4.0,67,5106026.0,,,1,1983-07-16 -9463,381,122,20,30.0,17,15.0,15,0.0,65,,,,12,1983-07-16 -9464,381,116,3,15.0,3,1.0,1,9.0,67,5079780.0,,,1,1983-07-16 -9465,381,194,53,33.0,21,16.0,16,0.0,64,,,,13,1983-07-16 -9466,381,162,5,28.0,1,5.0,5,2.0,67,5138654.0,,,1,1983-07-16 -9467,381,181,0,8.0,15,6.0,6,1.0,66,,,,11,1983-07-16 -9468,381,183,49,23.0,11,7.0,7,0.0,66,,,,11,1983-07-16 -9469,381,109,49,22.0,9,8.0,8,0.0,66,,,,11,1983-07-16 -9470,381,136,33,5.0,6,2.0,2,6.0,67,5098941.0,,,1,1983-07-16 -9471,381,196,26,25.0,25,10.0,10,0.0,65,,,,12,1983-07-16 -9472,381,176,2,1.0,13,11.0,11,0.0,65,,,,12,1983-07-16 -9473,381,171,2,2.0,20,12.0,12,0.0,65,,,,12,1983-07-16 -9474,381,104,24,3.0,16,13.0,13,0.0,65,,,,12,1983-07-16 -9475,381,192,24,4.0,23,14.0,14,0.0,65,,,,12,1983-07-16 -9476,381,186,0,7.0,24,9.0,9,0.0,66,,,,11,1983-07-16 -9477,382,183,49,23.0,7,,18,0.0,24,,,,101,1983-08-07 -9478,382,151,51,36.0,10,,19,0.0,19,,,,101,1983-08-07 -9479,382,117,51,35.0,9,,20,0.0,17,,,,5,1983-08-07 -9480,382,139,50,40.0,13,,21,0.0,11,,,,5,1983-08-07 -9481,382,174,5,27.0,1,,22,0.0,11,,,,5,1983-08-07 -9482,382,172,31,11.0,11,,23,0.0,10,,,,5,1983-08-07 -9483,382,194,53,33.0,24,,26,0.0,0,,,,5,1983-08-07 -9484,382,94,31,12.0,17,,25,0.0,1,,,,5,1983-08-07 -9485,382,185,48,17.0,0,,27,0.0,0,,,,81,1983-08-07 -9486,382,189,43,31.0,0,,28,0.0,0,,,,81,1983-08-07 -9487,382,180,52,9.0,0,,29,0.0,0,,,,81,1983-08-07 -9488,382,195,26,26.0,25,,17,0.0,27,,,,5,1983-08-07 -9489,382,104,24,3.0,16,,24,0.0,4,,,,48,1983-08-07 -9490,382,159,43,32.0,26,,16,0.0,34,,,,44,1983-08-07 -9491,382,157,3,16.0,6,,15,0.0,38,,,,69,1983-08-07 -9492,382,181,0,8.0,18,,14,0.0,44,,,,2,1983-08-07 -9493,382,109,49,22.0,3,2.0,2,6.0,45,5300971.0,,,1,1983-08-07 -9494,382,118,33,6.0,8,3.0,3,4.0,45,5334412.0,,,1,1983-08-07 -9495,382,116,3,15.0,5,4.0,4,3.0,45,5351069.0,,,1,1983-08-07 -9496,382,186,0,7.0,23,5.0,5,2.0,44,,,,11,1983-08-07 -9497,382,171,2,2.0,15,6.0,6,1.0,44,,,,11,1983-08-07 -9498,382,175,20,29.0,20,7.0,7,0.0,44,,,,11,1983-08-07 -9499,382,162,5,28.0,2,1.0,1,9.0,45,5230319.0,,,1,1983-08-07 -9500,382,122,20,30.0,14,9.0,9,0.0,44,,,,11,1983-08-07 -9501,382,176,2,1.0,12,10.0,10,0.0,44,,,,11,1983-08-07 -9502,382,187,53,34.0,22,11.0,11,0.0,44,,,,11,1983-08-07 -9503,382,192,24,4.0,21,12.0,12,0.0,43,,,,12,1983-08-07 -9504,382,136,33,5.0,4,13.0,13,0.0,42,,,,42,1983-08-07 -9505,382,196,26,25.0,19,8.0,8,0.0,44,,,,11,1983-08-07 -9506,383,171,2,2.0,24,,19,0.0,21,,,,76,1983-08-14 -9507,383,183,49,23.0,9,,20,0.0,13,,,,44,1983-08-14 -9508,383,104,24,3.0,18,,21,0.0,8,,,,4,1983-08-14 -9509,383,117,51,35.0,10,,22,0.0,2,,,,101,1983-08-14 -9510,383,151,51,36.0,7,,23,0.0,1,,,,21,1983-08-14 -9511,383,192,24,4.0,23,,26,0.0,0,,,,4,1983-08-14 -9512,383,175,20,29.0,22,,25,0.0,0,,,,4,1983-08-14 -9513,383,195,26,26.0,0,,27,0.0,0,,,,81,1983-08-14 -9514,383,187,53,34.0,0,,28,0.0,0,,,,81,1983-08-14 -9515,383,185,48,17.0,0,,29,0.0,0,,,,81,1983-08-14 -9516,383,194,53,33.0,21,,18,0.0,25,,,,6,1983-08-14 -9517,383,172,31,11.0,12,,24,0.0,0,,,,4,1983-08-14 -9518,383,118,33,6.0,6,,17,0.0,29,,,,5,1983-08-14 -9519,383,174,5,27.0,1,,16,0.0,30,,,,80,1983-08-14 -9520,383,116,3,15.0,5,1.0,1,9.0,53,5072745.0,,,1,1983-08-14 -9521,383,162,5,28.0,2,2.0,2,6.0,53,5079580.0,,,1,1983-08-14 -9522,383,136,33,5.0,4,3.0,3,4.0,53,5100404.0,,,1,1983-08-14 -9523,383,157,3,16.0,8,4.0,4,3.0,53,5101140.0,,,1,1983-08-14 -9524,383,94,31,12.0,3,5.0,5,2.0,52,,,,11,1983-08-14 -9525,383,181,0,8.0,14,6.0,6,1.0,51,,,,12,1983-08-14 -9526,383,196,26,25.0,20,7.0,7,0.0,51,,,,12,1983-08-14 -9527,383,109,49,22.0,11,,15,0.0,31,,,,60,1983-08-14 -9528,383,186,0,7.0,17,9.0,9,0.0,51,,,,12,1983-08-14 -9529,383,189,43,31.0,26,10.0,10,0.0,50,,,,13,1983-08-14 -9530,383,159,43,32.0,25,11.0,11,0.0,49,,,,14,1983-08-14 -9531,383,139,50,40.0,16,12.0,12,0.0,48,,,,15,1983-08-14 -9532,383,122,20,30.0,19,13.0,13,0.0,48,,,,15,1983-08-14 -9533,383,180,52,9.0,13,,14,0.0,33,,,,47,1983-08-14 -9534,383,176,2,1.0,15,8.0,8,0.0,51,,,,12,1983-08-14 -9535,384,116,3,15.0,4,,18,0.0,41,,,,20,1983-08-28 -9536,384,157,3,16.0,11,,19,0.0,39,,,,10,1983-08-28 -9537,384,171,2,2.0,17,,20,0.0,37,,,,64,1983-08-28 -9538,384,94,31,12.0,5,,21,0.0,26,,,,20,1983-08-28 -9539,384,181,0,8.0,19,,22,0.0,25,,,,23,1983-08-28 -9540,384,192,24,4.0,26,,23,0.0,20,,,,5,1983-08-28 -9541,384,196,26,25.0,22,,26,0.0,3,,,,22,1983-08-28 -9542,384,109,49,22.0,8,,25,0.0,5,,,,5,1983-08-28 -9543,384,159,43,32.0,0,,27,0.0,0,,,,81,1983-08-28 -9544,384,187,53,34.0,0,,28,0.0,0,,,,81,1983-08-28 -9545,384,185,48,17.0,0,,29,0.0,0,,,,81,1983-08-28 -9546,384,136,33,5.0,1,,17,0.0,41,,,,4,1983-08-28 -9547,384,172,31,11.0,3,,24,0.0,12,,,,10,1983-08-28 -9548,384,176,2,1.0,23,,15,0.0,53,,,,80,1983-08-28 -9549,384,189,43,31.0,25,11.0,11,0.0,68,,,,5,1983-08-28 -9550,384,122,20,30.0,21,14.0,14,0.0,65,,,,5,1983-08-28 -9551,384,162,5,28.0,10,1.0,1,9.0,72,5921950.0,,,1,1983-08-28 -9552,384,174,5,27.0,2,2.0,2,6.0,72,5942789.0,,,1,1983-08-28 -9553,384,186,0,7.0,15,3.0,3,4.0,72,5965691.0,,,1,1983-08-28 -9554,384,117,51,35.0,7,4.0,4,3.0,72,5998789.0,,,1,1983-08-28 -9555,384,180,52,9.0,9,,16,0.0,50,,,,2,1983-08-28 -9556,384,104,24,3.0,18,6.0,6,1.0,71,,,,11,1983-08-28 -9557,384,183,49,23.0,12,5.0,5,2.0,72,6006242.0,,,1,1983-08-28 -9558,384,175,20,29.0,14,8.0,8,0.0,70,,,,12,1983-08-28 -9559,384,118,33,6.0,6,9.0,9,0.0,70,,,,12,1983-08-28 -9560,384,195,26,26.0,24,10.0,10,0.0,70,,,,12,1983-08-28 -9561,384,194,53,33.0,20,12.0,12,0.0,68,,,,14,1983-08-28 -9562,384,151,51,36.0,13,13.0,13,0.0,68,,,,20,1983-08-28 -9563,384,139,50,40.0,16,7.0,7,0.0,70,,,,12,1983-08-28 -9564,385,186,0,7.0,15,,21,0.0,13,,,,10,1983-09-11 -9565,385,104,24,3.0,24,,18,0.0,28,,,,8,1983-09-11 -9566,385,116,3,15.0,5,,19,0.0,26,,,,101,1983-09-11 -9567,385,181,0,8.0,13,,20,0.0,24,,,,10,1983-09-11 -9568,385,159,43,32.0,23,,22,0.0,10,,,,6,1983-09-11 -9569,385,180,52,9.0,9,,17,0.0,35,,,,43,1983-09-11 -9570,385,139,50,40.0,17,,24,0.0,4,,,,99,1983-09-11 -9571,385,118,33,6.0,1,,25,0.0,2,,,,5,1983-09-11 -9572,385,109,49,22.0,6,,26,0.0,2,,,,4,1983-09-11 -9573,385,195,26,26.0,0,,27,0.0,0,,,,81,1983-09-11 -9574,385,171,2,2.0,0,,28,0.0,0,,,,81,1983-09-11 -9575,385,185,48,17.0,0,,29,0.0,0,,,,81,1983-09-11 -9576,385,183,49,23.0,10,,23,0.0,4,,,,101,1983-09-11 -9577,385,122,20,30.0,18,,16,0.0,41,,,,5,1983-09-11 -9578,385,176,2,1.0,16,11.0,11,0.0,51,,,,11,1983-09-11 -9579,385,189,43,31.0,25,,14,0.0,45,,,,5,1983-09-11 -9580,385,136,33,5.0,4,1.0,1,9.0,52,4990880.0,,,1,1983-09-11 -9581,385,162,5,28.0,3,2.0,2,6.0,52,5001092.0,,,1,1983-09-11 -9582,385,157,3,16.0,7,3.0,3,4.0,52,5009492.0,,,1,1983-09-11 -9583,385,174,5,27.0,2,4.0,4,3.0,52,5019903.0,,,1,1983-09-11 -9584,385,172,31,11.0,8,5.0,5,2.0,52,5044560.0,,,1,1983-09-11 -9585,385,117,51,35.0,12,6.0,6,1.0,52,5064228.0,,,1,1983-09-11 -9586,385,192,24,4.0,22,,15,0.0,44,,,,69,1983-09-11 -9587,385,94,31,12.0,11,8.0,8,0.0,52,5086915.0,,,1,1983-09-11 -9588,385,196,26,25.0,19,9.0,9,0.0,51,,,,11,1983-09-11 -9589,385,175,20,29.0,20,10.0,10,0.0,51,,,,11,1983-09-11 -9590,385,187,53,34.0,26,12.0,12,0.0,50,,,,12,1983-09-11 -9591,385,194,53,33.0,21,13.0,13,0.0,50,,,,12,1983-09-11 -9592,385,151,51,36.0,14,7.0,7,0.0,52,5084802.0,,,1,1983-09-11 -9593,386,159,43,32.0,24,,18,0.0,63,,,,37,1983-09-25 -9594,386,175,20,29.0,17,,19,0.0,50,,,,5,1983-09-25 -9595,386,176,2,1.0,16,,20,0.0,43,,,,5,1983-09-25 -9596,386,183,49,23.0,15,,21,0.0,39,,,,8,1983-09-25 -9597,386,186,0,7.0,10,,22,0.0,36,,,,20,1983-09-25 -9598,386,192,24,4.0,20,,23,0.0,27,,,,44,1983-09-25 -9599,386,196,26,25.0,22,,26,0.0,0,,,,8,1983-09-25 -9600,386,172,31,11.0,1,,25,0.0,12,,,,94,1983-09-25 -9601,386,185,48,17.0,0,,27,0.0,0,,,,81,1983-09-25 -9602,386,189,43,31.0,0,,28,0.0,0,,,,81,1983-09-25 -9603,386,171,2,2.0,0,,29,0.0,0,,,,81,1983-09-25 -9604,386,104,24,3.0,26,,17,0.0,64,,,,5,1983-09-25 -9605,386,181,0,8.0,13,,24,0.0,25,,,,5,1983-09-25 -9606,386,174,5,27.0,6,,16,0.0,67,,,,20,1983-09-25 -9607,386,94,31,12.0,3,3.0,3,4.0,76,5836180.0,,,1,1983-09-25 -9608,386,139,50,40.0,19,14.0,14,0.0,74,,,,12,1983-09-25 -9609,386,136,33,5.0,4,1.0,1,9.0,76,5805865.0,,,1,1983-09-25 -9610,386,195,26,26.0,23,15.0,15,0.0,73,,,,13,1983-09-25 -9611,386,109,49,22.0,14,4.0,4,3.0,76,5840261.0,,,1,1983-09-25 -9612,386,117,51,35.0,11,5.0,5,2.0,76,5850780.0,,,1,1983-09-25 -9613,386,151,51,36.0,12,6.0,6,1.0,76,5858055.0,,,1,1983-09-25 -9614,386,118,33,6.0,2,7.0,7,0.0,76,5878549.0,,,1,1983-09-25 -9615,386,116,3,15.0,8,2.0,2,6.0,76,5812436.0,,,1,1983-09-25 -9616,386,162,5,28.0,5,9.0,9,0.0,75,,,,11,1983-09-25 -9617,386,157,3,16.0,7,10.0,10,0.0,75,,,,11,1983-09-25 -9618,386,122,20,30.0,18,11.0,11,0.0,75,,,,11,1983-09-25 -9619,386,194,53,33.0,21,12.0,12,0.0,75,,,,11,1983-09-25 -9620,386,155,2,42.0,25,13.0,13,0.0,74,,,,12,1983-09-25 -9621,386,180,52,9.0,9,8.0,8,0.0,75,,,,11,1983-09-25 -9622,387,174,5,27.0,1,,16,0.0,56,,,,101,1983-10-15 -9623,387,151,51,36.0,16,,17,0.0,56,,,,101,1983-10-15 -9624,387,116,3,15.0,5,,18,0.0,35,,,,101,1983-10-15 -9625,387,189,43,31.0,25,,19,0.0,28,,,,5,1983-10-15 -9626,387,172,31,11.0,11,,20,0.0,20,,,,5,1983-10-15 -9627,387,180,52,9.0,8,,24,0.0,1,,,,5,1983-10-15 -9628,387,183,49,23.0,17,,23,0.0,5,,,,5,1983-10-15 -9629,387,171,2,2.0,10,,25,0.0,1,,,,20,1983-10-15 -9630,387,159,43,32.0,26,,26,0.0,1,,,,5,1983-10-15 -9631,387,104,24,3.0,18,,15,0.0,60,,,,5,1983-10-15 -9632,387,162,5,28.0,4,,22,0.0,9,,,,5,1983-10-15 -9633,387,195,26,26.0,23,,14,0.0,66,,,,62,1983-10-15 -9634,387,186,0,7.0,15,,21,0.0,18,,,,2,1983-10-15 -9635,387,185,48,17.0,24,12.0,12,0.0,71,,,,16,1983-10-15 -9636,387,94,31,12.0,7,,13,0.0,68,,,,62,1983-10-15 -9637,387,109,49,22.0,9,2.0,2,6.0,77,5615027.0,,,1,1983-10-15 -9638,387,136,33,5.0,2,3.0,3,4.0,77,5627677.0,,,1,1983-10-15 -9639,387,117,51,35.0,13,4.0,4,3.0,76,,,,11,1983-10-15 -9640,387,157,3,16.0,14,6.0,6,1.0,76,,,,11,1983-10-15 -9641,387,176,2,1.0,6,5.0,5,2.0,76,,,,11,1983-10-15 -9642,387,192,24,4.0,19,7.0,7,0.0,75,,,,12,1983-10-15 -9643,387,175,20,29.0,22,8.0,8,0.0,75,,,,12,1983-10-15 -9644,387,122,20,30.0,20,9.0,9,0.0,74,,,,13,1983-10-15 -9645,387,196,26,25.0,21,10.0,10,0.0,73,,,,14,1983-10-15 -9646,387,181,0,8.0,12,11.0,11,0.0,71,,,,10,1983-10-15 -9647,387,118,33,6.0,3,1.0,1,9.0,77,5605708.0,,,1,1983-10-15 -9648,388,111,48,9.0,25,,20,0.0,24,,,,84,1984-03-25 -9649,388,159,43,24.0,21,,18,0.0,28,,,,6,1984-03-25 -9650,388,182,26,25.0,19,,19,0.0,25,,,,25,1984-03-25 -9651,388,162,5,28.0,10,,17,0.0,30,,,,84,1984-03-25 -9652,388,183,50,21.0,23,,24,0.0,12,,,,99,1984-03-25 -9653,388,187,51,20.0,17,,21,0.0,18,,,,101,1984-03-25 -9654,388,171,2,5.0,13,,22,0.0,15,,,,10,1984-03-25 -9655,388,104,5,27.0,2,,23,0.0,14,,,,23,1984-03-25 -9656,388,169,33,2.0,15,,16,0.0,32,,,,101,1984-03-25 -9657,388,184,24,4.0,22,,25,0.0,11,,,,2,1984-03-25 -9658,388,116,0,7.0,4,1.0,1,9.0,61,6154492.0,,,1,1984-03-25 -9659,388,136,33,1.0,7,,15,0.0,32,,,,5,1984-03-25 -9660,388,155,48,10.0,26,8.0,8,0.0,58,,,,13,1984-03-25 -9661,388,181,0,8.0,6,,13,0.0,38,,,,10,1984-03-25 -9662,388,118,49,22.0,11,,12,0.0,41,,,,6,1984-03-25 -9663,388,109,26,26.0,14,,11,0.0,42,,,,6,1984-03-25 -9664,388,117,3,16.0,3,,10,0.0,51,,,,22,1984-03-25 -9665,388,83,24,3.0,18,,9,0.0,60,,,,2,1984-03-25 -9666,388,175,20,17.0,24,7.0,7,0.0,59,,,,12,1984-03-25 -9667,388,122,20,18.0,20,6.0,6,1.0,59,,,,12,1984-03-25 -9668,388,174,3,15.0,8,5.0,5,2.0,59,,,,60,1984-03-25 -9669,388,157,49,23.0,12,4.0,4,3.0,60,,,,11,1984-03-25 -9670,388,172,31,11.0,1,3.0,3,4.0,61,6213620.0,,,1,1984-03-25 -9671,388,176,2,6.0,9,2.0,2,6.0,61,6195006.0,,,1,1984-03-25 -9672,388,101,51,19.0,16,,26,0.0,8,,,,101,1984-03-25 -9673,388,94,31,12.0,5,,14,0.0,35,,,,3,1984-03-25 -9674,388,180,52,14.0,0,,27,0.0,0,,,,2,1984-03-25 -9675,389,172,31,11.0,7,7.0,7,0.0,71,,,,14,1984-04-07 -9676,389,116,0,7.0,5,2.0,2,6.0,75,5429380.0,,,1,1984-04-07 -9677,389,181,0,8.0,8,1.0,1,9.0,75,5363430.0,,,1,1984-04-07 -9678,389,159,43,24.0,0,,27,0.0,0,,,,54,1984-04-07 -9679,389,157,49,23.0,16,,26,0.0,4,,,,21,1984-04-07 -9680,389,169,33,2.0,6,,25,0.0,18,,,,101,1984-04-07 -9681,389,155,48,10.0,21,,24,0.0,22,,,,6,1984-04-07 -9682,389,111,48,9.0,22,,23,0.0,24,,,,5,1984-04-07 -9683,389,136,33,1.0,1,,21,0.0,29,,,,101,1984-04-07 -9684,389,162,5,28.0,15,,20,0.0,40,,,,98,1984-04-07 -9685,389,94,31,12.0,3,,19,0.0,51,,,,101,1984-04-07 -9686,389,176,2,6.0,2,,18,0.0,51,,,,36,1984-04-07 -9687,389,180,52,14.0,12,,17,0.0,53,,,,5,1984-04-07 -9688,389,171,2,5.0,11,,16,0.0,60,,,,7,1984-04-07 -9689,389,187,51,20.0,19,,22,0.0,26,,,,27,1984-04-07 -9690,389,174,3,15.0,4,,14,0.0,66,,,,60,1984-04-07 -9691,389,184,24,4.0,24,,15,0.0,60,,,,2,1984-04-07 -9692,389,118,49,22.0,18,4.0,4,3.0,73,,,,12,1984-04-07 -9693,389,109,26,26.0,14,5.0,5,2.0,73,,,,12,1984-04-07 -9694,389,101,51,19.0,13,6.0,6,1.0,72,,,,13,1984-04-07 -9695,389,183,50,21.0,20,8.0,8,0.0,71,,,,14,1984-04-07 -9696,389,117,3,16.0,9,3.0,3,4.0,74,,,,11,1984-04-07 -9697,389,182,26,25.0,17,10.0,10,0.0,71,,,,14,1984-04-07 -9698,389,104,5,27.0,10,11.0,11,0.0,70,,,,80,1984-04-07 -9699,389,122,20,18.0,26,12.0,12,0.0,70,,,,15,1984-04-07 -9700,389,83,24,3.0,25,,13,0.0,71,,,,2,1984-04-07 -9701,389,175,20,17.0,23,9.0,9,0.0,71,,,,14,1984-04-07 -9702,390,187,51,20.0,16,,26,0.0,1,,,,8,1984-04-29 -9703,390,157,49,23.0,11,,18,0.0,28,,,,5,1984-04-29 -9704,390,104,5,27.0,1,1.0,1,9.0,70,5792048.0,,,1,1984-04-29 -9705,390,118,49,22.0,7,,25,0.0,2,,,,80,1984-04-29 -9706,390,116,0,7.0,8,,24,0.0,5,,,,99,1984-04-29 -9707,390,94,31,12.0,10,,23,0.0,14,,,,8,1984-04-29 -9708,390,159,43,24.0,20,,22,0.0,14,,,,7,1984-04-29 -9709,390,122,20,18.0,17,,21,0.0,15,,,,5,1984-04-29 -9710,390,182,26,25.0,23,,20,0.0,15,,,,21,1984-04-29 -9711,390,171,2,5.0,15,,19,0.0,15,,,,10,1984-04-29 -9712,390,181,0,8.0,14,,17,0.0,35,,,,103,1984-04-29 -9713,390,184,24,4.0,21,,11,0.0,69,,,,2,1984-04-29 -9714,390,169,33,2.0,18,,15,0.0,42,,,,20,1984-04-29 -9715,390,109,26,26.0,13,,14,0.0,42,,,,3,1984-04-29 -9716,390,83,24,3.0,22,,13,0.0,51,,,,2,1984-04-29 -9717,390,183,50,21.0,25,,12,0.0,53,,,,22,1984-04-29 -9718,390,155,48,10.0,26,10.0,10,0.0,64,,,,12,1984-04-29 -9719,390,136,33,1.0,9,9.0,9,0.0,66,,,,5,1984-04-29 -9720,390,175,20,17.0,24,8.0,8,0.0,68,,,,12,1984-04-29 -9721,390,174,3,15.0,12,7.0,7,0.0,68,,,,12,1984-04-29 -9722,390,101,51,19.0,19,6.0,6,1.0,68,,,,12,1984-04-29 -9723,390,172,31,11.0,5,5.0,5,2.0,69,,,,11,1984-04-29 -9724,390,111,48,9.0,0,,27,0.0,0,,,,81,1984-04-29 -9725,390,180,52,14.0,6,,16,0.0,39,,,,43,1984-04-29 -9726,390,176,2,6.0,3,4.0,4,3.0,69,,,,60,1984-04-29 -9727,390,162,5,28.0,2,3.0,3,4.0,70,5861851.0,,,1,1984-04-29 -9728,390,117,3,16.0,4,2.0,2,6.0,70,5834434.0,,,1,1984-04-29 -9729,391,180,52,14.0,7,,18,0.0,31,,,,101,1984-05-06 -9730,391,182,26,25.0,17,,26,0.0,0,,,,4,1984-05-06 -9731,391,174,3,15.0,14,,25,0.0,0,,,,4,1984-05-06 -9732,391,176,2,6.0,3,,24,0.0,2,,,,10,1984-05-06 -9733,391,94,31,12.0,18,,23,0.0,2,,,,20,1984-05-06 -9734,391,118,49,22.0,10,,22,0.0,6,,,,10,1984-05-06 -9735,391,171,2,5.0,15,,21,0.0,11,,,,5,1984-05-06 -9736,391,181,0,8.0,5,,20,0.0,15,,,,5,1984-05-06 -9737,391,104,5,27.0,13,,19,0.0,23,,,,43,1984-05-06 -9738,391,175,20,17.0,16,,17,0.0,40,,,,101,1984-05-06 -9739,391,188,43,30.0,26,,16,0.0,46,,,,5,1984-05-06 -9740,391,169,33,2.0,9,,15,0.0,48,,,,101,1984-05-06 -9741,391,159,43,24.0,0,,27,0.0,0,,,,81,1984-05-06 -9742,391,136,33,1.0,1,,14,0.0,48,,,,101,1984-05-06 -9743,391,111,48,9.0,23,,12,0.0,53,,,,101,1984-05-06 -9744,391,83,24,3.0,22,,11,0.0,55,,,,2,1984-05-06 -9745,391,184,24,4.0,21,,10,0.0,59,,,,2,1984-05-06 -9746,391,155,48,10.0,25,9.0,9,0.0,57,,,,13,1984-05-06 -9747,391,183,50,21.0,24,8.0,8,0.0,58,,,,12,1984-05-06 -9748,391,157,49,23.0,8,7.0,7,0.0,58,,,,60,1984-05-06 -9749,391,109,26,26.0,12,6.0,6,1.0,58,,,,60,1984-05-06 -9750,391,122,20,18.0,20,5.0,5,2.0,59,,,,11,1984-05-06 -9751,391,117,3,16.0,4,4.0,4,3.0,59,,,,11,1984-05-06 -9752,391,172,31,11.0,11,3.0,3,4.0,59,,,,60,1984-05-06 -9753,391,162,5,28.0,6,2.0,2,6.0,60,5827095.0,,,1,1984-05-06 -9754,391,116,0,7.0,2,1.0,1,9.0,60,5813679.0,,,1,1984-05-06 -9755,391,187,51,20.0,19,,13,0.0,52,,,,62,1984-05-06 -9756,391,101,51,19.0,0,,28,0.0,0,,,,81,1984-05-06 -9757,392,94,31,12.0,6,3.0,3,4.0,79,5495920.0,,,1,1984-05-20 -9758,392,174,3,15.0,1,2.0,2,6.0,79,5479105.0,,,1,1984-05-20 -9759,392,181,0,8.0,9,1.0,1,9.0,79,5471951.0,,,1,1984-05-20 -9760,392,111,48,9.0,22,,26,0.0,4,,,,10,1984-05-20 -9761,392,180,52,14.0,8,,25,0.0,5,,,,8,1984-05-20 -9762,392,184,24,4.0,20,,24,0.0,11,,,,2,1984-05-20 -9763,392,136,33,1.0,3,,23,0.0,11,,,,101,1984-05-20 -9764,392,118,49,22.0,15,,22,0.0,15,,,,5,1984-05-20 -9765,392,187,51,20.0,18,,21,0.0,22,,,,101,1984-05-20 -9766,392,101,51,19.0,13,,19,0.0,35,,,,101,1984-05-20 -9767,392,157,49,23.0,16,,18,0.0,51,,,,5,1984-05-20 -9768,392,175,20,17.0,19,,17,0.0,51,,,,3,1984-05-20 -9769,392,117,3,16.0,7,,16,0.0,53,,,,3,1984-05-20 -9770,392,183,50,21.0,24,,15,0.0,61,,,,5,1984-05-20 -9771,392,104,5,27.0,10,,20,0.0,33,,,,5,1984-05-20 -9772,392,155,48,10.0,21,13.0,13,0.0,72,,,,17,1984-05-20 -9773,392,159,43,24.0,25,12.0,12,0.0,74,,,,15,1984-05-20 -9774,392,122,20,18.0,14,11.0,11,0.0,77,,,,12,1984-05-20 -9775,392,109,26,26.0,26,10.0,10,0.0,77,,,,12,1984-05-20 -9776,392,169,33,2.0,17,9.0,9,0.0,78,,,,11,1984-05-20 -9777,392,171,2,5.0,12,8.0,8,0.0,78,,,,11,1984-05-20 -9778,392,116,0,7.0,5,7.0,7,0.0,78,,,,11,1984-05-20 -9779,392,176,2,6.0,4,6.0,6,1.0,78,,,,11,1984-05-20 -9780,392,172,31,11.0,2,5.0,5,2.0,79,5538076.0,,,1,1984-05-20 -9781,392,162,5,28.0,11,4.0,4,3.0,79,5515657.0,,,1,1984-05-20 -9782,392,83,24,3.0,23,,14,0.0,76,,,,2,1984-05-20 -9783,393,117,3,16.0,5,,18,0.0,0,,,,4,1984-06-03 -9784,393,174,3,15.0,6,,19,0.0,0,,,,4,1984-06-03 -9785,393,109,26,26.0,7,,20,0.0,0,,,,3,1984-06-03 -9786,393,175,20,17.0,0,,21,0.0,0,,,,81,1984-06-03 -9787,393,83,24,3.0,0,,22,0.0,0,,,,81,1984-06-03 -9788,393,111,48,9.0,0,,27,0.0,0,,,,81,1984-06-03 -9789,393,122,20,18.0,0,,24,0.0,0,,,,81,1984-06-03 -9790,393,155,48,10.0,0,,25,0.0,0,,,,81,1984-06-03 -9791,393,183,50,21.0,0,,26,0.0,0,,,,81,1984-06-03 -9792,393,187,51,20.0,18,,17,0.0,1,,,,20,1984-06-03 -9793,393,157,49,23.0,0,,23,0.0,0,,,,81,1984-06-03 -9794,393,189,33,2.0,15,,16,0.0,9,,,,10,1984-06-03 -9795,393,116,0,7.0,1,1.0,1,4.5,31,3667740.0,,,1,1984-06-03 -9796,393,136,33,1.0,9,,14,0.0,14,,,,10,1984-06-03 -9797,393,94,31,12.0,2,,13,0.0,15,,,,20,1984-06-03 -9798,393,180,52,14.0,12,,12,0.0,22,,,,20,1984-06-03 -9799,393,181,0,8.0,8,,11,0.0,23,,,,20,1984-06-03 -9800,393,118,49,22.0,14,,10,0.0,24,,,,38,1984-06-03 -9801,393,184,24,4.0,20,,9,0.0,31,,,,2,1984-06-03 -9802,393,171,2,5.0,16,8.0,8,0.0,30,,,,11,1984-06-03 -9803,393,159,43,24.0,19,7.0,7,0.0,30,,,,11,1984-06-03 -9804,393,162,5,28.0,3,3.0,3,2.0,31,3696817.0,,,1,1984-06-03 -9805,393,101,51,19.0,13,2.0,2,3.0,31,3675186.0,,,1,1984-06-03 -9806,393,104,5,27.0,4,6.0,6,0.5,30,,,,11,1984-06-03 -9807,393,182,26,25.0,17,,15,0.0,12,,,,10,1984-06-03 -9808,393,176,2,6.0,10,4.0,4,1.5,31,3702986.0,,,1,1984-06-03 -9809,393,172,31,11.0,11,5.0,5,1.0,31,3712179.0,,,1,1984-06-03 -9810,394,175,20,17.0,23,,13,0.0,59,,,,5,1984-06-17 -9811,394,117,3,16.0,4,,14,0.0,57,,,,83,1984-06-17 -9812,394,182,26,25.0,13,,26,0.0,7,,,,101,1984-06-17 -9813,394,104,5,27.0,6,,25,0.0,10,,,,5,1984-06-17 -9814,394,159,43,24.0,19,,24,0.0,11,,,,6,1984-06-17 -9815,394,190,48,10.0,25,,23,0.0,29,,,,101,1984-06-17 -9816,394,171,2,5.0,17,,22,0.0,31,,,,101,1984-06-17 -9817,394,176,2,6.0,15,,21,0.0,32,,,,69,1984-06-17 -9818,394,118,49,22.0,14,,20,0.0,37,,,,3,1984-06-17 -9819,394,122,20,18.0,18,,19,0.0,38,,,,5,1984-06-17 -9820,394,189,33,2.0,16,,18,0.0,39,,,,101,1984-06-17 -9821,394,109,26,26.0,10,,17,0.0,40,,,,23,1984-06-17 -9822,394,136,33,1.0,1,1.0,1,9.0,70,6383748.0,,,1,1984-06-17 -9823,394,180,52,14.0,12,8.0,8,0.0,68,,,,12,1984-06-17 -9824,394,116,0,7.0,2,3.0,3,4.0,70,6471780.0,,,1,1984-06-17 -9825,394,181,0,8.0,8,2.0,2,6.0,70,6386360.0,,,1,1984-06-17 -9826,394,157,49,23.0,11,11.0,11,0.0,63,,,,60,1984-06-17 -9827,394,83,24,3.0,21,,12,0.0,68,,,,2,1984-06-17 -9828,394,187,51,20.0,20,9.0,9,0.0,68,,,,12,1984-06-17 -9829,394,178,50,21.0,24,,15,0.0,56,,,,62,1984-06-17 -9830,394,111,48,9.0,26,10.0,10,0.0,65,,,,15,1984-06-17 -9831,394,94,31,12.0,7,6.0,6,1.0,68,,,,12,1984-06-17 -9832,394,162,5,28.0,5,5.0,5,2.0,68,,,,12,1984-06-17 -9833,394,184,24,4.0,22,,16,0.0,52,,,,2,1984-06-17 -9834,394,172,31,11.0,3,4.0,4,3.0,69,,,,11,1984-06-17 -9835,394,101,51,19.0,9,7.0,7,0.0,68,,,,12,1984-06-17 -9836,395,187,51,20.0,17,,17,0.0,23,,,,8,1984-06-24 -9837,395,157,49,23.0,8,,18,0.0,21,,,,5,1984-06-24 -9838,395,101,51,19.0,7,,19,0.0,21,,,,3,1984-06-24 -9839,395,118,49,22.0,25,,20,0.0,20,,,,20,1984-06-24 -9840,395,182,26,25.0,18,,21,0.0,3,,,,3,1984-06-24 -9841,395,178,50,21.0,0,,27,0.0,0,,,,81,1984-06-24 -9842,395,155,48,10.0,24,,24,0.0,2,,,,27,1984-06-24 -9843,395,180,52,14.0,14,,25,0.0,0,,,,5,1984-06-24 -9844,395,175,20,17.0,22,,26,0.0,0,,,,3,1984-06-24 -9845,395,109,26,26.0,12,,16,0.0,24,,,,25,1984-06-24 -9846,395,159,43,24.0,26,,22,0.0,3,,,,3,1984-06-24 -9847,395,122,20,18.0,13,,15,0.0,27,,,,5,1984-06-24 -9848,395,162,5,28.0,15,,23,0.0,2,,,,3,1984-06-24 -9849,395,181,0,8.0,10,,13,0.0,33,,,,10,1984-06-24 -9850,395,136,33,1.0,1,1.0,1,9.0,63,6941842.0,,,1,1984-06-24 -9851,395,94,31,12.0,3,,14,0.0,27,,,,6,1984-06-24 -9852,395,172,31,11.0,5,2.0,2,6.0,63,6974480.0,,,1,1984-06-24 -9853,395,169,33,2.0,23,3.0,3,4.0,63,7028370.0,,,1,1984-06-24 -9854,395,116,0,7.0,2,4.0,4,3.0,63,7057100.0,,,1,1984-06-24 -9855,395,83,24,3.0,11,,6,0.0,63,,,,2,1984-06-24 -9856,395,171,2,5.0,19,5.0,5,2.0,62,,,,11,1984-06-24 -9857,395,176,2,6.0,21,,8,0.0,47,,,,101,1984-06-24 -9858,395,117,3,16.0,6,,9,0.0,40,,,,6,1984-06-24 -9859,395,184,24,4.0,16,,10,0.0,33,,,,3,1984-06-24 -9860,395,174,3,15.0,9,,11,0.0,33,,,,7,1984-06-24 -9861,395,111,48,9.0,20,,12,0.0,33,,,,23,1984-06-24 -9862,395,104,5,27.0,4,,7,0.0,49,,,,5,1984-06-24 -9863,396,109,26,26.0,16,,19,0.0,15,,,,20,1984-07-08 -9864,396,174,3,15.0,10,,17,0.0,25,,,,20,1984-07-08 -9865,396,187,51,20.0,15,,18,0.0,25,,,,20,1984-07-08 -9866,396,178,50,21.0,23,,20,0.0,15,,,,95,1984-07-08 -9867,396,83,24,3.0,0,,26,0.0,0,,,,81,1984-07-08 -9868,396,117,3,16.0,3,,22,0.0,10,,,,20,1984-07-08 -9869,396,184,24,4.0,17,,23,0.0,9,,,,2,1984-07-08 -9870,396,157,49,23.0,14,,24,0.0,8,,,,20,1984-07-08 -9871,396,182,26,25.0,19,,25,0.0,0,,,,3,1984-07-08 -9872,396,118,49,22.0,21,,21,0.0,12,,,,20,1984-07-08 -9873,396,155,48,10.0,25,,15,0.0,46,,,,10,1984-07-08 -9874,396,136,33,1.0,12,,16,0.0,45,,,,20,1984-07-08 -9875,396,175,20,17.0,22,,13,0.0,54,,,,20,1984-07-08 -9876,396,101,51,19.0,6,,14,0.0,47,,,,8,1984-07-08 -9877,396,176,2,6.0,8,1.0,1,9.0,67,7282617.0,,,1,1984-07-08 -9878,396,162,5,28.0,4,2.0,2,6.0,67,7305081.0,,,1,1984-07-08 -9879,396,171,2,5.0,24,4.0,4,3.0,65,,,,12,1984-07-08 -9880,396,159,43,24.0,18,5.0,5,2.0,65,,,,12,1984-07-08 -9881,396,94,31,12.0,1,6.0,6,1.0,64,,,,6,1984-07-08 -9882,396,172,31,11.0,2,3.0,3,4.0,66,,,,11,1984-07-08 -9883,396,180,52,14.0,13,8.0,8,0.0,64,,,,13,1984-07-08 -9884,396,181,0,8.0,5,,9,0.0,60,,,,20,1984-07-08 -9885,396,116,0,7.0,7,,10,0.0,56,,,,20,1984-07-08 -9886,396,122,20,18.0,20,,11,0.0,55,,,,20,1984-07-08 -9887,396,104,5,27.0,9,,12,0.0,54,,,,20,1984-07-08 -9888,396,189,33,2.0,11,7.0,7,0.0,64,,,,13,1984-07-08 -9889,397,182,26,25.0,20,,15,0.0,43,,,,10,1984-07-22 -9890,397,178,50,21.0,22,,14,0.0,62,,,,62,1984-07-22 -9891,397,184,24,4.0,26,,13,0.0,68,,,,2,1984-07-22 -9892,397,118,49,22.0,17,12.0,12,0.0,66,,,,15,1984-07-22 -9893,397,175,20,17.0,15,11.0,11,0.0,67,,,,14,1984-07-22 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-9912,397,116,0,7.0,2,,16,0.0,37,,,,6,1984-07-22 -9913,397,157,49,23.0,18,,25,0.0,0,,,,3,1984-07-22 -9914,397,111,48,9.0,24,,26,0.0,0,,,,3,1984-07-22 -9915,397,188,43,30.0,27,,27,0.0,0,,,,3,1984-07-22 -9916,397,139,24,3.0,25,,24,0.0,1,,,,2,1984-07-22 -9917,398,182,26,25.0,17,8.0,8,0.0,43,,,,11,1984-08-05 -9918,398,117,3,16.0,3,3.0,3,4.0,44,5119633.0,,,1,1984-08-05 -9919,398,94,31,12.0,16,4.0,4,3.0,44,5134873.0,,,1,1984-08-05 -9920,398,174,3,15.0,4,5.0,5,2.0,44,5155159.0,,,1,1984-08-05 -9921,398,162,5,28.0,10,6.0,6,1.0,43,,,,11,1984-08-05 -9922,398,109,26,26.0,11,7.0,7,0.0,43,,,,11,1984-08-05 -9923,398,111,48,9.0,22,,24,0.0,7,,,,25,1984-08-05 -9924,398,178,50,21.0,24,9.0,9,0.0,40,,,,14,1984-08-05 -9925,398,157,49,23.0,18,,12,0.0,29,,,,5,1984-08-05 -9926,398,190,24,4.0,0,,27,0.0,0,,,,81,1984-08-05 -9927,398,175,20,17.0,14,,26,0.0,1,,,,101,1984-08-05 -9928,398,101,51,19.0,9,,25,0.0,4,,,,3,1984-08-05 -9929,398,172,31,11.0,2,,23,0.0,8,,,,101,1984-08-05 -9930,398,122,20,18.0,15,,22,0.0,8,,,,5,1984-08-05 -9931,398,171,2,5.0,12,,21,0.0,10,,,,5,1984-08-05 -9932,398,180,52,14.0,13,,11,0.0,31,,,,6,1984-08-05 -9933,398,176,2,6.0,19,,20,0.0,10,,,,10,1984-08-05 -9934,398,104,5,27.0,6,,18,0.0,13,,,,5,1984-08-05 -9935,398,188,43,30.0,23,,17,0.0,13,,,,101,1984-08-05 -9936,398,159,43,24.0,21,,16,0.0,14,,,,10,1984-08-05 -9937,398,118,49,22.0,20,,15,0.0,16,,,,69,1984-08-05 -9938,398,136,33,1.0,5,,14,0.0,23,,,,6,1984-08-05 -9939,398,169,33,2.0,8,,13,0.0,28,,,,101,1984-08-05 -9940,398,155,48,10.0,25,,19,0.0,11,,,,101,1984-08-05 -9941,398,181,0,8.0,7,2.0,2,6.0,44,5086359.0,,,1,1984-08-05 -9942,398,139,24,3.0,26,,10,0.0,42,,,,2,1984-08-05 -9943,398,116,0,7.0,1,1.0,1,9.0,44,5083210.0,,,1,1984-08-05 -9944,399,136,33,1.0,1,2.0,2,6.0,51,4896376.0,,,1,1984-08-19 -9945,399,181,0,8.0,4,1.0,1,9.0,51,4872851.0,,,1,1984-08-19 -9946,399,169,33,2.0,7,4.0,4,3.0,51,4929163.0,,,1,1984-08-19 -9947,399,122,20,18.0,17,5.0,5,2.0,50,,,,11,1984-08-19 -9948,399,175,20,17.0,19,6.0,6,1.0,50,,,,11,1984-08-19 -9949,399,162,5,28.0,15,7.0,7,0.0,50,,,,11,1984-08-19 -9950,399,182,26,25.0,21,8.0,8,0.0,49,,,,12,1984-08-19 -9951,399,155,48,10.0,24,9.0,9,0.0,49,,,,12,1984-08-19 -9952,399,118,49,22.0,13,10.0,10,0.0,48,,,,60,1984-08-19 -9953,399,111,48,9.0,25,11.0,11,0.0,48,,,,13,1984-08-19 -9954,399,76,52,31.0,20,12.0,12,0.0,48,,,,6,1984-08-19 -9955,399,174,3,15.0,5,,13,0.0,42,,,,5,1984-08-19 -9956,399,101,51,19.0,10,,14,0.0,35,,,,51,1984-08-19 -9957,399,94,31,12.0,8,,15,0.0,32,,,,5,1984-08-19 -9958,399,172,31,11.0,3,,17,0.0,28,,,,5,1984-08-19 -9959,399,178,50,21.0,26,,18,0.0,23,,,,62,1984-08-19 -9960,399,157,49,23.0,16,,19,0.0,18,,,,5,1984-08-19 -9961,399,117,3,16.0,6,,20,0.0,17,,,,5,1984-08-19 -9962,399,139,24,3.0,0,,27,0.0,0,,,,81,1984-08-19 -9963,399,109,26,26.0,18,,21,0.0,15,,,,98,1984-08-19 -9964,399,176,2,6.0,9,,22,0.0,15,,,,64,1984-08-19 -9965,399,171,2,5.0,11,,23,0.0,12,,,,5,1984-08-19 -9966,399,188,43,30.0,22,,24,0.0,6,,,,5,1984-08-19 -9967,399,159,43,24.0,23,,25,0.0,4,,,,6,1984-08-19 -9968,399,184,24,4.0,0,,26,0.0,0,,,,2,1984-08-19 -9969,399,116,0,7.0,2,,16,0.0,28,,,,20,1984-08-19 -9970,399,104,5,27.0,12,3.0,3,4.0,51,4921849.0,,,1,1984-08-19 -9971,400,94,31,12.0,12,3.0,3,4.0,71,5921012.0,,,1,1984-08-26 -9972,400,175,20,17.0,19,,24,0.0,17,,,,36,1984-08-26 -9973,400,172,31,11.0,3,4.0,4,3.0,70,,,,11,1984-08-26 -9974,400,169,33,2.0,10,5.0,5,2.0,70,,,,11,1984-08-26 -9975,400,174,3,15.0,5,6.0,6,1.0,70,,,,11,1984-08-26 -9976,400,182,26,25.0,20,7.0,7,0.0,69,,,,12,1984-08-26 -9977,400,176,2,6.0,7,8.0,8,0.0,68,,,,60,1984-08-26 -9978,400,104,5,27.0,9,,27,0.0,7,,,,5,1984-08-26 -9979,400,155,48,10.0,22,9.0,9,0.0,67,,,,14,1984-08-26 -9980,400,111,48,9.0,26,10.0,10,0.0,67,,,,14,1984-08-26 -9981,400,162,5,28.0,15,11.0,11,0.0,66,,,,10,1984-08-26 -9982,400,188,43,30.0,23,12.0,12,0.0,66,,,,15,1984-08-26 -9983,400,157,49,23.0,17,13.0,13,0.0,65,,,,60,1984-08-26 -9984,400,184,24,4.0,26,,14,0.0,69,,,,2,1984-08-26 -9985,400,139,24,3.0,25,,15,0.0,69,,,,2,1984-08-26 -9986,400,122,20,18.0,11,,16,0.0,59,,,,3,1984-08-26 -9987,400,178,50,21.0,27,,17,0.0,53,,,,37,1984-08-26 -9988,400,118,49,22.0,11,,18,0.0,51,,,,5,1984-08-26 -9989,400,109,26,26.0,14,,19,0.0,31,,,,5,1984-08-26 -9990,400,171,2,5.0,8,,20,0.0,23,,,,5,1984-08-26 -9991,400,117,3,16.0,4,,21,0.0,23,,,,20,1984-08-26 -9992,400,180,52,14.0,16,,22,0.0,22,,,,20,1984-08-26 -9993,400,101,51,19.0,13,,23,0.0,19,,,,5,1984-08-26 -9994,400,136,33,1.0,2,,25,0.0,10,,,,51,1984-08-26 -9995,400,181,0,8.0,6,2.0,2,6.0,71,5851751.0,,,1,1984-08-26 -9996,400,159,43,24.0,21,,26,0.0,8,,,,48,1984-08-26 -9997,400,116,0,7.0,1,1.0,1,9.0,71,5841468.0,,,1,1984-08-26 -9998,401,93,51,20.0,0,,27,0.0,0,,,,81,1984-09-09 -9999,401,118,49,22.0,9,3.0,3,4.0,50,,,,11,1984-09-09 -10000,401,188,43,30.0,24,5.0,5,0.0,49,,,,12,1984-09-09 -10001,401,76,52,31.0,20,6.0,6,0.0,49,,,,12,1984-09-09 -10002,401,159,43,24.0,22,7.0,7,0.0,48,,,,60,1984-09-09 -10003,401,178,50,21.0,25,8.0,8,0.0,48,,,,13,1984-09-09 -10004,401,157,49,23.0,10,9.0,9,0.0,45,,,,60,1984-09-09 -10005,401,122,20,18.0,19,10.0,10,0.0,45,,,,16,1984-09-09 -10006,401,174,3,15.0,8,,11,0.0,43,,,,37,1984-09-09 -10007,401,169,33,2.0,5,,12,0.0,43,,,,5,1984-09-09 -10008,401,175,20,17.0,15,,13,0.0,43,,,,5,1984-09-09 -10009,401,117,3,16.0,12,,14,0.0,31,,,,51,1984-09-09 -10010,401,155,48,10.0,26,,15,0.0,20,,,,51,1984-09-09 -10011,401,172,31,11.0,3,,17,0.0,14,,,,6,1984-09-09 -10012,401,94,31,12.0,7,,18,0.0,13,,,,20,1984-09-09 -10013,401,171,2,5.0,13,,19,0.0,10,,,,101,1984-09-09 -10014,401,176,2,6.0,6,,20,0.0,8,,,,101,1984-09-09 -10015,401,109,26,26.0,16,,21,0.0,7,,,,5,1984-09-09 -10016,401,182,26,25.0,18,,22,0.0,7,,,,20,1984-09-09 -10017,401,111,48,9.0,23,,23,0.0,6,,,,10,1984-09-09 -10018,401,181,0,8.0,4,1.0,1,9.0,51,4829065.0,,,1,1984-09-09 -10019,401,162,5,28.0,14,,24,0.0,5,,,,6,1984-09-09 -10020,401,116,0,7.0,2,,25,0.0,3,,,,5,1984-09-09 -10021,401,180,52,14.0,21,,26,0.0,0,,,,54,1984-09-09 -10022,401,136,33,1.0,1,,16,0.0,15,,,,5,1984-09-09 -10023,401,104,5,27.0,11,2.0,2,6.0,51,4853314.0,,,1,1984-09-09 -10024,401,139,51,19.0,17,4.0,4,3.0,49,,,,12,1984-09-09 -10025,402,139,51,20.0,26,,21,0.0,17,,,,25,1984-10-07 -10026,402,175,20,17.0,16,,24,0.0,0,,,,3,1984-10-07 -10027,402,101,51,19.0,12,,23,0.0,0,,,,3,1984-10-07 -10028,402,176,2,6.0,4,,22,0.0,0,,,,3,1984-10-07 -10029,402,172,31,11.0,23,,20,0.0,25,,,,101,1984-10-07 -10030,402,171,2,5.0,14,,19,0.0,27,,,,5,1984-10-07 -10031,402,155,48,10.0,21,,18,0.0,35,,,,101,1984-10-07 -10032,402,111,48,9.0,25,,17,0.0,37,,,,101,1984-10-07 -10033,402,157,49,23.0,13,,16,0.0,37,,,,69,1984-10-07 -10034,402,174,3,15.0,3,,15,0.0,47,,,,69,1984-10-07 -10035,402,94,31,12.0,8,,14,0.0,51,,,,5,1984-10-07 -10036,402,169,33,2.0,10,,13,0.0,57,,,,6,1984-10-07 -10037,402,188,43,30.0,22,,12,0.0,60,,,,69,1984-10-07 -10038,402,117,3,16.0,7,11.0,11,0.0,61,,,,25,1984-10-07 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-10128,405,117,3,16.0,6,7.0,7,0.0,65,,,,12,1985-04-21 -10129,406,182,33,8.0,20,,22,0.0,5,,,,5,1985-05-05 -10130,406,183,50,21.0,26,,21,0.0,9,,,,10,1985-05-05 -10131,406,109,26,25.0,13,,20,0.0,11,,,,20,1985-05-05 -10132,406,93,17,29.0,19,,19,0.0,14,,,,101,1985-05-05 -10133,406,171,26,26.0,16,,18,0.0,22,,,,101,1985-05-05 -10134,406,176,2,6.0,2,,17,0.0,23,,,,23,1985-05-05 -10135,406,111,48,10.0,21,,16,0.0,24,,,,5,1985-05-05 -10136,406,180,48,9.0,23,,15,0.0,27,,,,5,1985-05-05 -10137,406,104,5,27.0,4,,14,0.0,29,,,,10,1985-05-05 -10138,406,159,43,24.0,22,,13,0.0,46,,,,62,1985-05-05 -10139,406,101,31,12.0,1,7.0,7,0.0,57,,,,60,1985-05-05 -10140,406,116,0,2.0,6,,11,0.0,60,,,,2,1985-05-05 -10141,406,117,3,16.0,14,10.0,10,0.0,56,,,,60,1985-05-05 -10142,406,83,24,3.0,25,9.0,9,0.0,56,,,,60,1985-05-05 -10143,406,136,33,7.0,9,8.0,8,0.0,57,,,,60,1985-05-05 -10144,406,139,5,28.0,15,6.0,6,1.0,57,,,,60,1985-05-05 -10145,406,94,2,5.0,7,5.0,5,2.0,58,,,,12,1985-05-05 -10146,406,181,0,1.0,8,4.0,4,3.0,59,,,,11,1985-05-05 -10147,406,174,3,15.0,11,3.0,3,4.0,59,,,,11,1985-05-05 -10148,406,122,20,18.0,5,2.0,2,6.0,59,,,,11,1985-05-05 -10149,406,172,31,11.0,3,1.0,1,9.0,60,5675955.0,,,1,1985-05-05 -10150,406,157,49,23.0,12,,12,0.0,50,,,,5,1985-05-05 -10151,406,76,20,17.0,18,,24,0.0,4,,,,5,1985-05-05 -10152,406,184,24,4.0,24,,23,0.0,5,,,,5,1985-05-05 -10153,406,155,47,30.0,17,,26,0.0,0,,,,31,1985-05-05 -10154,406,118,49,22.0,18,,25,0.0,4,,,,5,1985-05-05 -10155,407,182,33,8.0,0,,25,0.0,0,,,,81,1985-05-19 -10156,407,180,48,9.0,0,,24,0.0,0,,,,81,1985-05-19 -10157,407,111,48,10.0,0,,23,0.0,0,,,,81,1985-05-19 -10158,407,184,24,4.0,0,,22,0.0,0,,,,81,1985-05-19 -10159,407,159,43,24.0,0,,21,0.0,0,,,,81,1985-05-19 -10160,407,174,3,15.0,17,,20,0.0,0,,,,3,1985-05-19 -10161,407,76,20,17.0,11,,19,0.0,0,,,,3,1985-05-19 -10162,407,139,5,28.0,15,,18,0.0,1,,,,3,1985-05-19 -10163,407,157,49,23.0,4,,17,0.0,10,,,,91,1985-05-19 -10164,407,101,31,12.0,1,,16,0.0,13,,,,5,1985-05-19 -10165,407,169,51,19.0,20,,15,0.0,16,,,,101,1985-05-19 -10166,407,83,24,3.0,18,10.0,10,0.0,74,,,,14,1985-05-19 -10167,407,118,49,22.0,12,,13,0.0,16,,,,3,1985-05-19 -10168,407,116,0,2.0,5,1.0,1,9.0,78,6718034.0,,,1,1985-05-19 -10169,407,104,5,27.0,3,2.0,2,6.0,78,6725575.0,,,1,1985-05-19 -10170,407,172,31,11.0,9,3.0,3,4.0,78,6805205.0,,,1,1985-05-19 -10171,407,109,26,25.0,8,4.0,4,3.0,77,,,,11,1985-05-19 -10172,407,117,3,16.0,10,5.0,5,2.0,77,,,,11,1985-05-19 -10173,407,136,33,7.0,13,,14,0.0,16,,,,3,1985-05-19 -10174,407,94,2,5.0,2,7.0,7,0.0,77,,,,11,1985-05-19 -10175,407,176,2,6.0,7,8.0,8,0.0,76,,,,12,1985-05-19 -10176,407,122,20,18.0,6,9.0,9,0.0,76,,,,12,1985-05-19 -10177,407,155,47,30.0,19,11.0,11,0.0,74,,,,14,1985-05-19 -10178,407,181,0,1.0,14,,12,0.0,17,,,,20,1985-05-19 -10179,407,171,26,26.0,16,6.0,6,1.0,77,,,,11,1985-05-19 -10180,408,157,49,23.0,11,17.0,17,0.0,64,,,,16,1985-06-16 -10181,408,93,17,29.0,25,,18,0.0,57,,,,3,1985-06-16 -10182,408,181,0,1.0,17,,19,0.0,37,,,,5,1985-06-16 -10183,408,159,43,24.0,22,,20,0.0,35,,,,5,1985-06-16 -10184,408,180,48,9.0,14,,23,0.0,5,,,,3,1985-06-16 -10185,408,117,3,16.0,6,,22,0.0,25,,,,3,1985-06-16 -10186,408,169,51,19.0,18,,24,0.0,3,,,,101,1985-06-16 -10187,408,136,33,7.0,9,,25,0.0,0,,,,7,1985-06-16 -10188,408,101,31,12.0,2,16.0,16,0.0,65,,,,15,1985-06-16 -10189,408,111,48,10.0,21,,21,0.0,28,,,,3,1985-06-16 -10190,408,175,33,8.0,20,15.0,15,0.0,67,,,,13,1985-06-16 -10191,408,109,26,25.0,15,14.0,14,0.0,67,,,,13,1985-06-16 -10192,408,76,20,17.0,12,13.0,13,0.0,67,,,,13,1985-06-16 -10193,408,104,5,27.0,3,1.0,1,9.0,70,6361813.0,,,1,1985-06-16 -10194,408,139,5,28.0,4,2.0,2,6.0,70,6363770.0,,,1,1985-06-16 -10195,408,116,0,2.0,5,3.0,3,4.0,70,6366154.0,,,1,1985-06-16 -10196,408,176,2,6.0,8,4.0,4,3.0,70,6389634.0,,,1,1985-06-16 -10197,408,94,2,5.0,16,6.0,6,1.0,70,6439691.0,,,1,1985-06-16 -10198,408,172,31,11.0,1,5.0,5,2.0,70,6405162.0,,,1,1985-06-16 -10199,408,171,26,26.0,19,8.0,8,0.0,69,,,,11,1985-06-16 -10200,408,122,20,18.0,7,9.0,9,0.0,68,,,,12,1985-06-16 -10201,408,118,49,22.0,13,10.0,10,0.0,68,,,,12,1985-06-16 -10202,408,184,24,4.0,23,11.0,11,0.0,68,,,,12,1985-06-16 -10203,408,83,24,3.0,24,12.0,12,0.0,68,,,,12,1985-06-16 -10204,408,174,3,15.0,10,7.0,7,0.0,69,,,,11,1985-06-16 -10205,409,117,3,16.0,6,,19,0.0,18,,,,7,1985-06-23 -10206,409,116,0,2.0,4,,17,0.0,19,,,,23,1985-06-23 -10207,409,118,49,22.0,14,,18,0.0,19,,,,10,1985-06-23 -10208,409,174,3,15.0,15,,20,0.0,15,,,,3,1985-06-23 -10209,409,159,43,24.0,22,,25,0.0,0,,,,3,1985-06-23 -10210,409,181,0,1.0,12,,22,0.0,10,,,,23,1985-06-23 -10211,409,169,51,19.0,13,,23,0.0,4,,,,8,1985-06-23 -10212,409,180,48,9.0,20,,24,0.0,3,,,,101,1985-06-23 -10213,409,94,2,5.0,2,,16,0.0,26,,,,3,1985-06-23 -10214,409,93,17,29.0,25,,21,0.0,11,,,,5,1985-06-23 -10215,409,111,48,10.0,23,,15,0.0,27,,,,3,1985-06-23 -10216,409,157,49,23.0,7,9.0,9,0.0,61,,,,12,1985-06-23 -10217,409,101,31,12.0,1,,13,0.0,51,,,,3,1985-06-23 -10218,409,83,24,3.0,18,,14,0.0,30,,,,3,1985-06-23 -10219,409,176,2,6.0,5,1.0,1,9.0,63,6939851.0,,,1,1985-06-23 -10220,409,104,5,27.0,3,3.0,3,4.0,63,7003021.0,,,1,1985-06-23 -10221,409,184,24,4.0,19,4.0,4,3.0,63,7006076.0,,,1,1985-06-23 -10222,409,172,31,11.0,8,5.0,5,2.0,63,7026817.0,,,1,1985-06-23 -10223,409,139,5,28.0,9,2.0,2,6.0,63,6997400.0,,,1,1985-06-23 -10224,409,122,20,18.0,21,7.0,7,0.0,62,,,,11,1985-06-23 -10225,409,175,33,8.0,11,8.0,8,0.0,62,,,,11,1985-06-23 -10226,409,109,26,25.0,17,10.0,10,0.0,61,,,,12,1985-06-23 -10227,409,76,20,17.0,24,11.0,11,0.0,60,,,,13,1985-06-23 -10228,409,136,33,7.0,10,6.0,6,1.0,62,,,,11,1985-06-23 -10229,409,171,26,26.0,16,12.0,12,0.0,58,,,,15,1985-06-23 -10230,410,181,0,1.0,6,,17,0.0,30,,,,6,1985-07-07 -10231,410,101,31,12.0,2,,18,0.0,26,,,,3,1985-07-07 -10232,410,76,20,17.0,9,,19,0.0,20,,,,3,1985-07-07 -10233,410,93,17,29.0,25,,20,0.0,19,,,,3,1985-07-07 -10234,410,155,47,30.0,22,,22,0.0,6,,,,5,1985-07-07 -10235,410,83,24,3.0,21,,16,0.0,32,,,,6,1985-07-07 -10236,410,104,5,27.0,3,,23,0.0,5,,,,101,1985-07-07 -10237,410,109,26,25.0,13,,24,0.0,4,,,,38,1985-07-07 -10238,410,171,26,26.0,15,,25,0.0,2,,,,101,1985-07-07 -10239,410,94,2,5.0,8,,26,0.0,0,,,,82,1985-07-07 -10240,410,111,48,10.0,23,,21,0.0,8,,,,69,1985-07-07 -10241,410,159,43,24.0,24,15.0,15,0.0,49,,,,14,1985-07-07 -10242,410,180,48,9.0,20,12.0,12,0.0,50,,,,13,1985-07-07 -10243,410,184,24,4.0,26,13.0,13,0.0,50,,,,13,1985-07-07 -10244,410,118,49,22.0,17,11.0,11,0.0,52,,,,11,1985-07-07 -10245,410,157,49,23.0,18,10.0,10,0.0,52,,,,11,1985-07-07 -10246,410,175,33,8.0,14,8.0,8,0.0,52,,,,11,1985-07-07 -10247,410,117,3,16.0,11,7.0,7,0.0,53,5610478.0,,,1,1985-07-07 -10248,410,174,3,15.0,10,6.0,6,1.0,53,5581433.0,,,1,1985-07-07 -10249,410,172,31,11.0,7,5.0,5,2.0,53,5559956.0,,,1,1985-07-07 -10250,410,139,5,28.0,16,4.0,4,3.0,53,5559757.0,,,1,1985-07-07 -10251,410,116,0,2.0,4,3.0,3,4.0,53,5515551.0,,,1,1985-07-07 -10252,410,176,2,6.0,1,2.0,2,6.0,53,5512926.0,,,1,1985-07-07 -10253,410,136,33,7.0,5,1.0,1,9.0,53,5506266.0,,,1,1985-07-07 -10254,410,169,51,19.0,19,14.0,14,0.0,49,,,,69,1985-07-07 -10255,410,122,20,18.0,12,9.0,9,0.0,52,,,,11,1985-07-07 -10256,411,111,48,10.0,21,,25,0.0,0,,,,3,1985-07-21 -10257,411,116,0,2.0,3,1.0,1,9.0,65,4690436.0,,,1,1985-07-21 -10258,411,174,3,15.0,13,,24,0.0,0,,,,20,1985-07-21 -10259,411,139,5,28.0,11,,23,0.0,1,,,,3,1985-07-21 -10260,411,169,51,19.0,9,,22,0.0,4,,,,7,1985-07-21 -10261,411,155,47,30.0,24,,21,0.0,6,,,,5,1985-07-21 -10262,411,157,49,23.0,22,,20,0.0,17,,,,101,1985-07-21 -10263,411,94,2,5.0,5,,19,0.0,17,,,,8,1985-07-21 -10264,411,176,2,6.0,1,,18,0.0,21,,,,43,1985-07-21 -10265,411,180,48,9.0,18,,17,0.0,28,,,,101,1985-07-21 -10266,411,172,31,11.0,8,,16,0.0,37,,,,62,1985-07-21 -10267,411,93,17,29.0,23,,15,0.0,38,,,,7,1985-07-21 -10268,411,159,43,24.0,25,,26,0.0,0,,,,3,1985-07-21 -10269,411,109,26,25.0,7,,14,0.0,41,,,,8,1985-07-21 -10270,411,181,0,1.0,10,,12,0.0,57,,,,10,1985-07-21 -10271,411,184,24,4.0,26,11.0,11,0.0,59,,,,16,1985-07-21 -10272,411,101,31,12.0,4,10.0,10,0.0,60,,,,69,1985-07-21 -10273,411,118,49,22.0,14,9.0,9,0.0,62,,,,13,1985-07-21 -10274,411,83,24,3.0,20,7.0,7,0.0,63,,,,12,1985-07-21 -10275,411,175,33,8.0,15,6.0,6,1.0,63,,,,12,1985-07-21 -10276,411,117,3,16.0,12,5.0,5,2.0,64,,,,11,1985-07-21 -10277,411,136,33,7.0,2,4.0,4,3.0,64,,,,11,1985-07-21 -10278,411,171,26,26.0,16,3.0,3,4.0,64,,,,11,1985-07-21 -10279,411,104,5,27.0,6,2.0,2,6.0,64,,,,11,1985-07-21 -10280,411,122,20,18.0,19,,13,0.0,57,,,,20,1985-07-21 -10281,411,76,20,17.0,17,8.0,8,0.0,63,,,,12,1985-07-21 -10282,412,180,48,9.0,22,,22,0.0,8,,,,5,1985-08-04 -10283,412,111,48,10.0,21,,25,0.0,8,,,,51,1985-08-04 -10284,412,182,3,14.0,23,,24,0.0,8,,,,8,1985-08-04 -10285,412,118,49,22.0,9,,23,0.0,8,,,,6,1985-08-04 -10286,412,175,33,8.0,11,,21,0.0,15,,,,5,1985-08-04 -10287,412,174,3,15.0,16,,20,0.0,19,,,,20,1985-08-04 -10288,412,136,33,7.0,6,,19,0.0,23,,,,101,1985-08-04 -10289,412,117,3,16.0,20,,18,0.0,25,,,,80,1985-08-04 -10290,412,101,31,12.0,5,,17,0.0,27,,,,102,1985-08-04 -10291,412,169,51,19.0,1,,16,0.0,29,,,,8,1985-08-04 -10292,412,178,43,24.0,25,,15,0.0,32,,,,6,1985-08-04 -10293,412,172,31,11.0,7,,14,0.0,40,,,,5,1985-08-04 -10294,412,157,49,23.0,18,,13,0.0,45,,,,101,1985-08-04 -10295,412,176,2,6.0,4,12.0,12,0.0,61,,,,23,1985-08-04 -10296,412,155,47,30.0,24,,26,0.0,7,,,,91,1985-08-04 -10297,412,83,24,4.0,26,10.0,10,0.0,63,,,,14,1985-08-04 -10298,412,139,5,28.0,2,9.0,9,0.0,66,,,,11,1985-08-04 -10299,412,184,24,3.0,19,8.0,8,0.0,66,,,,11,1985-08-04 -10300,412,76,20,17.0,17,7.0,7,0.0,66,,,,11,1985-08-04 -10301,412,94,2,5.0,10,6.0,6,1.0,67,5808157.0,,,1,1985-08-04 -10302,412,181,0,1.0,12,5.0,5,2.0,67,5805309.0,,,1,1985-08-04 -10303,412,122,20,18.0,15,4.0,4,3.0,67,5786616.0,,,1,1985-08-04 -10304,412,171,26,26.0,13,3.0,3,4.0,67,5782491.0,,,1,1985-08-04 -10305,412,116,0,2.0,3,2.0,2,6.0,67,5742998.0,,,1,1985-08-04 -10306,412,104,5,27.0,8,1.0,1,9.0,67,5731337.0,,,1,1985-08-04 -10307,412,109,26,25.0,14,,27,0.0,0,,,,4,1985-08-04 -10308,412,93,17,29.0,27,11.0,11,0.0,62,,,,5,1985-08-04 -10309,413,136,33,7.0,5,,18,0.0,26,,,,43,1985-08-18 -10310,413,94,2,5.0,2,,19,0.0,25,,,,5,1985-08-18 -10311,413,118,49,22.0,10,,20,0.0,25,,,,5,1985-08-18 -10312,413,155,47,30.0,25,,21,0.0,17,,,,5,1985-08-18 -10313,413,83,24,4.0,0,,27,0.0,0,,,,81,1985-08-18 -10314,413,157,49,23.0,20,,24,0.0,6,,,,101,1985-08-18 -10315,413,176,2,6.0,4,,25,0.0,4,,,,51,1985-08-18 -10316,413,159,51,20.0,19,,26,0.0,0,,,,54,1985-08-18 -10317,413,185,48,10.0,23,,17,0.0,28,,,,5,1985-08-18 -10318,413,109,26,25.0,18,,23,0.0,13,,,,3,1985-08-18 -10319,413,117,3,16.0,13,,16,0.0,29,,,,5,1985-08-18 -10320,413,111,48,9.0,21,,22,0.0,16,,,,101,1985-08-18 -10321,413,169,51,19.0,6,,15,0.0,31,,,,10,1985-08-18 -10322,413,76,20,17.0,17,,14,0.0,33,,,,101,1985-08-18 -10323,413,116,0,2.0,1,1.0,1,9.0,52,4812583.0,,,1,1985-08-18 -10324,413,104,5,27.0,9,3.0,3,4.0,52,4846939.0,,,1,1985-08-18 -10325,413,139,5,28.0,12,4.0,4,3.0,52,4851656.0,,,1,1985-08-18 -10326,413,172,31,11.0,7,5.0,5,2.0,52,4894675.0,,,1,1985-08-18 -10327,413,175,33,8.0,11,6.0,6,1.0,51,,,,11,1985-08-18 -10328,413,101,31,12.0,14,2.0,2,6.0,52,4842585.0,,,1,1985-08-18 -10329,413,122,20,18.0,16,8.0,8,0.0,49,,,,13,1985-08-18 -10330,413,178,43,24.0,24,9.0,9,0.0,48,,,,14,1985-08-18 -10331,413,174,3,15.0,8,10.0,10,0.0,46,,,,5,1985-08-18 -10332,413,171,26,26.0,15,,11,0.0,43,,,,3,1985-08-18 -10333,413,93,17,29.0,23,,12,0.0,40,,,,22,1985-08-18 -10334,413,184,24,3.0,22,7.0,7,0.0,49,,,,60,1985-08-18 -10335,413,181,0,1.0,3,,13,0.0,39,,,,5,1985-08-18 -10336,414,109,26,25.0,18,,16,0.0,25,,,,101,1985-08-25 -10337,414,174,3,15.0,6,,17,0.0,22,,,,7,1985-08-25 -10338,414,176,2,6.0,2,,18,0.0,20,,,,5,1985-08-25 -10339,414,169,51,19.0,5,,19,0.0,18,,,,67,1985-08-25 -10340,414,159,51,20.0,15,,22,0.0,12,,,,5,1985-08-25 -10341,414,155,47,30.0,23,,21,0.0,13,,,,51,1985-08-25 -10342,414,93,17,29.0,24,,24,0.0,1,,,,3,1985-08-25 -10343,414,157,49,23.0,20,,25,0.0,1,,,,101,1985-08-25 -10344,414,117,3,16.0,12,,15,0.0,27,,,,6,1985-08-25 -10345,414,171,26,26.0,13,,20,0.0,17,,,,10,1985-08-25 -10346,414,184,24,4.0,22,,14,0.0,39,,,,5,1985-08-25 -10347,414,118,49,22.0,19,,26,0.0,1,,,,101,1985-08-25 -10348,414,122,20,18.0,8,,12,0.0,54,,,,22,1985-08-25 -10349,414,178,43,24.0,26,,11,0.0,56,,,,62,1985-08-25 -10350,414,175,33,8.0,9,10.0,10,0.0,65,,,,43,1985-08-25 -10351,414,76,20,17.0,14,9.0,9,0.0,68,,,,12,1985-08-25 -10352,414,136,33,7.0,1,8.0,8,0.0,69,,,,11,1985-08-25 -10353,414,94,2,5.0,7,6.0,6,1.0,69,,,,11,1985-08-25 -10354,414,172,31,11.0,11,5.0,5,2.0,69,,,,11,1985-08-25 -10355,414,104,5,27.0,16,4.0,4,3.0,70,5598100.0,,,1,1985-08-25 -10356,414,101,31,12.0,4,3.0,3,4.0,70,5597754.0,,,1,1985-08-25 -10357,414,116,0,2.0,3,2.0,2,6.0,70,5549495.0,,,1,1985-08-25 -10358,414,181,0,1.0,10,1.0,1,9.0,70,5549263.0,,,1,1985-08-25 -10359,414,111,48,9.0,25,,13,0.0,52,,,,5,1985-08-25 -10360,414,83,24,3.0,21,7.0,7,0.0,69,,,,11,1985-08-25 -10361,414,139,5,28.0,17,,23,0.0,9,,,,5,1985-08-25 -10362,415,159,51,20.0,0,,26,0.0,0,,,,54,1985-09-08 -10363,415,94,2,5.0,3,11.0,11,0.0,47,,,,5,1985-09-08 -10364,415,169,51,19.0,15,12.0,12,0.0,47,,,,14,1985-09-08 -10365,415,104,5,27.0,7,13.0,13,0.0,45,,,,5,1985-09-08 -10366,415,176,2,6.0,2,,14,0.0,44,,,,5,1985-09-08 -10367,415,171,26,26.0,20,,15,0.0,40,,,,5,1985-09-08 -10368,415,181,0,1.0,16,,16,0.0,33,,,,7,1985-09-08 -10369,415,118,49,22.0,13,,17,0.0,31,,,,43,1985-09-08 -10370,415,178,43,24.0,22,,18,0.0,26,,,,5,1985-09-08 -10371,415,111,48,9.0,26,,19,0.0,19,,,,101,1985-09-08 -10372,415,76,20,17.0,11,,20,0.0,13,,,,5,1985-09-08 -10373,415,117,3,16.0,6,,21,0.0,9,,,,7,1985-09-08 -10374,415,177,25,33.0,25,,22,0.0,6,,,,5,1985-09-08 -10375,415,157,49,23.0,17,,23,0.0,3,,,,5,1985-09-08 -10376,415,185,48,10.0,24,,24,0.0,2,,,,8,1985-09-08 -10377,415,93,17,29.0,23,,25,0.0,0,,,,48,1985-09-08 -10378,415,122,20,18.0,14,9.0,9,0.0,50,,,,11,1985-09-08 -10379,415,83,24,3.0,18,8.0,8,0.0,50,,,,11,1985-09-08 -10380,415,174,3,15.0,8,7.0,7,0.0,50,,,,11,1985-09-08 -10381,415,172,31,11.0,6,6.0,6,1.0,50,,,,11,1985-09-08 -10382,415,139,5,28.0,10,5.0,5,2.0,50,,,,11,1985-09-08 -10383,415,175,33,8.0,9,4.0,4,3.0,51,4740060.0,,,1,1985-09-08 -10384,415,101,31,12.0,1,3.0,3,4.0,51,4739841.0,,,1,1985-09-08 -10385,415,136,33,7.0,4,2.0,2,6.0,51,4731086.0,,,1,1985-09-08 -10386,415,116,0,2.0,5,1.0,1,9.0,51,4679451.0,,,1,1985-09-08 -10387,415,165,26,25.0,19,10.0,10,0.0,49,,,,12,1985-09-08 -10388,416,174,3,15.0,13,,17,0.0,24,,,,6,1985-09-15 -10389,416,104,5,27.0,4,,24,0.0,3,,,,8,1985-09-15 -10390,416,159,51,20.0,16,,23,0.0,7,,,,3,1985-09-15 -10391,416,172,31,11.0,9,,19,0.0,17,,,,101,1985-09-15 -10392,416,111,48,9.0,20,,21,0.0,10,,,,3,1985-09-15 -10393,416,156,47,30.0,22,,20,0.0,16,,,,6,1985-09-15 -10394,416,139,5,28.0,5,,22,0.0,7,,,,20,1985-09-15 -10395,416,157,49,23.0,19,,16,0.0,26,,,,6,1985-09-15 -10396,416,76,20,17.0,8,7.0,7,0.0,42,,,,11,1985-09-15 -10397,416,94,2,5.0,7,2.0,2,6.0,43,5688315.0,,,1,1985-09-15 -10398,416,101,31,12.0,2,1.0,1,9.0,43,5659893.0,,,1,1985-09-15 -10399,416,118,49,22.0,15,,15,0.0,31,,,,5,1985-09-15 -10400,416,83,24,3.0,21,13.0,13,0.0,38,,,,15,1985-09-15 -10401,416,93,17,29.0,24,12.0,12,0.0,38,,,,15,1985-09-15 -10402,416,171,26,26.0,17,11.0,11,0.0,38,,,,3,1985-09-15 -10403,416,122,20,18.0,9,10.0,10,0.0,40,,,,13,1985-09-15 -10404,416,178,43,24.0,23,,14,0.0,37,,,,62,1985-09-15 -10405,416,175,33,8.0,12,8.0,8,0.0,42,,,,11,1985-09-15 -10406,416,169,51,19.0,11,,18,0.0,23,,,,37,1985-09-15 -10407,416,117,3,16.0,14,6.0,6,1.0,42,,,,11,1985-09-15 -10408,416,136,33,7.0,3,5.0,5,2.0,42,,,,11,1985-09-15 -10409,416,176,2,6.0,10,4.0,4,3.0,43,5735183.0,,,1,1985-09-15 -10410,416,116,0,2.0,1,3.0,3,4.0,43,5715002.0,,,1,1985-09-15 -10411,416,165,26,25.0,18,9.0,9,0.0,42,,,,11,1985-09-15 -10412,417,121,24,4.0,24,,17,0.0,44,,,,3,1985-10-06 -10413,417,83,24,3.0,16,,18,0.0,40,,,,47,1985-10-06 -10414,417,111,48,9.0,23,,20,0.0,31,,,,5,1985-10-06 -10415,417,159,51,20.0,14,,21,0.0,16,,,,5,1985-10-06 -10416,417,136,33,7.0,2,,24,0.0,6,,,,3,1985-10-06 -10417,417,104,5,27.0,15,,23,0.0,13,,,,101,1985-10-06 -10418,417,117,3,16.0,8,,25,0.0,4,,,,98,1985-10-06 -10419,417,93,17,29.0,26,,26,0.0,3,,,,3,1985-10-06 -10420,417,156,47,30.0,25,,16,0.0,55,,,,5,1985-10-06 -10421,417,177,25,33.0,22,,22,0.0,13,,,,21,1985-10-06 -10422,417,171,26,26.0,18,,15,0.0,58,,,,5,1985-10-06 -10423,417,169,51,19.0,20,,19,0.0,33,,,,5,1985-10-06 -10424,417,175,33,8.0,7,13.0,13,0.0,62,,,,101,1985-10-06 -10425,417,139,5,28.0,13,,14,0.0,59,,,,10,1985-10-06 -10426,417,101,31,12.0,1,2.0,2,6.0,75,5599505.0,,,1,1985-10-06 -10427,417,176,2,6.0,4,3.0,3,4.0,75,5636642.0,,,1,1985-10-06 -10428,417,116,0,2.0,6,4.0,4,3.0,75,5644230.0,,,1,1985-10-06 -10429,417,172,31,11.0,9,5.0,5,2.0,74,,,,11,1985-10-06 -10430,417,122,20,18.0,12,6.0,6,1.0,73,,,,12,1985-10-06 -10431,417,94,2,5.0,3,1.0,1,9.0,75,5578109.0,,,1,1985-10-06 -10432,417,165,26,25.0,5,8.0,8,0.0,73,,,,12,1985-10-06 -10433,417,118,49,22.0,11,9.0,9,0.0,73,,,,12,1985-10-06 -10434,417,76,20,17.0,19,10.0,10,0.0,73,,,,12,1985-10-06 -10435,417,157,49,23.0,18,11.0,11,0.0,73,,,,12,1985-10-06 -10436,417,174,3,15.0,17,12.0,12,0.0,72,,,,13,1985-10-06 -10437,417,186,0,1.0,21,7.0,7,0.0,73,,,,12,1985-10-06 -10438,418,177,25,33.0,18,,21,0.0,0,,,,100,1985-10-19 -10439,418,157,49,23.0,14,,20,0.0,0,,,,3,1985-10-19 -10440,418,118,49,22.0,12,,19,0.0,0,,,,3,1985-10-19 -10441,418,178,43,24.0,21,,18,0.0,1,,,,10,1985-10-19 -10442,418,175,33,8.0,5,,17,0.0,3,,,,5,1985-10-19 -10443,418,169,51,19.0,7,,16,0.0,3,,,,5,1985-10-19 -10444,418,159,51,20.0,13,,15,0.0,4,,,,5,1985-10-19 -10445,418,136,33,7.0,2,,14,0.0,6,,,,5,1985-10-19 -10446,418,104,5,27.0,15,,13,0.0,8,,,,101,1985-10-19 -10447,418,181,0,1.0,8,,10,0.0,37,,,,101,1985-10-19 -10448,418,165,24,4.0,19,,11,0.0,16,,,,3,1985-10-19 -10449,418,93,17,29.0,20,,9,0.0,45,,,,21,1985-10-19 -10450,418,172,31,11.0,6,,8,0.0,52,,,,5,1985-10-19 -10451,418,83,24,3.0,17,7.0,7,0.0,73,,,,12,1985-10-19 -10452,418,76,20,17.0,11,5.0,5,2.0,74,,,,11,1985-10-19 -10453,418,139,5,28.0,16,4.0,4,3.0,74,,,,11,1985-10-19 -10454,418,116,0,2.0,9,3.0,3,4.0,74,,,,11,1985-10-19 -10455,418,176,2,6.0,3,2.0,2,6.0,75,5310438.0,,,1,1985-10-19 -10456,418,94,2,5.0,1,1.0,1,9.0,75,5302866.0,,,1,1985-10-19 -10457,418,101,31,12.0,4,,12,0.0,8,,,,5,1985-10-19 -10458,418,122,20,18.0,10,6.0,6,1.0,74,,,,11,1985-10-19 -10459,419,94,2,5.0,2,,25,0.0,1,,,,7,1985-11-03 -10460,419,157,49,23.0,13,,24,0.0,5,,,,5,1985-11-03 -10461,419,176,2,6.0,3,1.0,1,9.0,82,7240473.0,,,1,1985-11-03 -10462,419,136,33,7.0,9,,23,0.0,14,,,,42,1985-11-03 -10463,419,172,31,11.0,10,,22,0.0,18,,,,2,1985-11-03 -10464,419,177,25,33.0,19,,21,0.0,20,,,,10,1985-11-03 -10465,419,174,3,15.0,8,,20,0.0,20,,,,7,1985-11-03 -10466,419,116,0,2.0,4,,19,0.0,26,,,,5,1985-11-03 -10467,419,122,20,18.0,11,,17,0.0,37,,,,44,1985-11-03 -10468,419,169,51,19.0,24,,16,0.0,40,,,,5,1985-11-03 -10469,419,118,49,22.0,14,,15,0.0,42,,,,43,1985-11-03 -10470,419,175,33,8.0,6,,14,0.0,42,,,,5,1985-11-03 -10471,419,83,24,3.0,17,,13,0.0,49,,,,62,1985-11-03 -10472,419,159,51,20.0,21,,18,0.0,28,,,,8,1985-11-03 -10473,419,181,0,1.0,16,,11,0.0,57,,,,3,1985-11-03 -10474,419,104,5,27.0,5,,10,0.0,61,,,,7,1985-11-03 -10475,419,101,31,12.0,1,,9,0.0,62,,,,5,1985-11-03 -10476,419,93,17,29.0,23,8.0,8,0.0,78,,,,14,1985-11-03 -10477,419,178,43,24.0,25,7.0,7,0.0,78,,,,14,1985-11-03 -10478,419,76,20,17.0,7,6.0,6,1.0,81,,,,11,1985-11-03 -10479,419,139,5,28.0,15,5.0,5,2.0,81,,,,11,1985-11-03 -10480,419,121,24,4.0,22,4.0,4,3.0,81,,,,11,1985-11-03 -10481,419,165,26,25.0,18,3.0,3,4.0,82,7329009.0,,,1,1985-11-03 -10482,419,171,26,26.0,20,2.0,2,6.0,82,7283603.0,,,1,1985-11-03 -10483,419,117,3,16.0,12,,12,0.0,57,,,,7,1985-11-03 -10484,420,174,25,16.0,13,,16,0.0,24,,,,84,1986-03-23 -10485,420,118,33,7.0,10,,17,0.0,21,,,,47,1986-03-23 -10486,420,155,47,14.0,21,,18,0.0,20,,,,5,1986-03-23 -10487,420,175,20,17.0,20,,19,0.0,19,,,,5,1986-03-23 -10488,420,144,17,24.0,25,,20,0.0,18,,,,8,1986-03-23 -10489,420,94,2,5.0,3,,25,0.0,0,,,,20,1986-03-23 -10490,420,159,43,21.0,23,,22,0.0,16,,,,5,1986-03-23 -10491,420,176,0,2.0,7,,23,0.0,6,,,,5,1986-03-23 -10492,420,177,25,15.0,19,,24,0.0,5,,,,98,1986-03-23 -10493,420,139,5,28.0,8,,15,0.0,26,,,,23,1986-03-23 -10494,420,109,17,23.0,22,,21,0.0,16,,,,101,1986-03-23 -10495,420,156,43,22.0,24,,14,0.0,29,,,,5,1986-03-23 -10496,420,116,0,1.0,9,,13,0.0,30,,,,5,1986-03-23 -10497,420,104,5,27.0,6,,12,0.0,35,,,,69,1986-03-23 -10498,420,101,31,12.0,1,2.0,2,6.0,61,6007410.0,,,1,1986-03-23 -10499,420,171,26,26.0,5,3.0,3,4.0,61,6032342.0,,,1,1986-03-23 -10500,420,162,26,25.0,4,4.0,4,3.0,61,6061012.0,,,1,1986-03-23 -10501,420,83,24,3.0,17,5.0,5,2.0,60,,,,11,1986-03-23 -10502,420,76,21,20.0,16,6.0,6,1.0,59,,,,12,1986-03-23 -10503,420,136,2,6.0,2,1.0,1,9.0,61,5972583.0,,,1,1986-03-23 -10504,420,172,33,8.0,14,8.0,8,0.0,58,,,,13,1986-03-23 -10505,420,173,31,11.0,11,9.0,9,0.0,58,,,,13,1986-03-23 -10506,420,169,21,19.0,12,10.0,10,0.0,56,,,,15,1986-03-23 -10507,420,122,20,18.0,15,,11,0.0,37,,,,43,1986-03-23 -10508,420,165,24,4.0,18,7.0,7,0.0,59,,,,12,1986-03-23 -10509,421,162,26,25.0,6,,15,0.0,29,,,,86,1986-04-13 -10510,421,177,25,15.0,17,,24,0.0,0,,,,4,1986-04-13 -10511,421,155,47,14.0,16,,23,0.0,0,,,,4,1986-04-13 -10512,421,109,17,23.0,24,,22,0.0,1,,,,24,1986-04-13 -10513,421,118,33,7.0,14,,21,0.0,8,,,,6,1986-04-13 -10514,421,159,43,21.0,21,,20,0.0,10,,,,5,1986-04-13 -10515,421,139,5,28.0,11,,19,0.0,11,,,,23,1986-04-13 -10516,421,156,43,22.0,23,,18,0.0,14,,,,5,1986-04-13 -10517,421,165,24,4.0,20,,17,0.0,22,,,,5,1986-04-13 -10518,421,104,5,27.0,13,,16,0.0,22,,,,67,1986-04-13 -10519,421,172,33,8.0,15,,14,0.0,29,,,,6,1986-04-13 -10520,421,174,25,16.0,18,8.0,8,0.0,66,,,,16,1986-04-13 -10521,421,175,20,17.0,22,,12,0.0,39,,,,69,1986-04-13 -10522,421,171,26,26.0,8,,11,0.0,40,,,,86,1986-04-13 -10523,421,83,24,3.0,12,,10,0.0,41,,,,5,1986-04-13 -10524,421,173,31,11.0,10,,9,0.0,52,,,,6,1986-04-13 -10525,421,144,17,24.0,25,,25,0.0,0,,,,24,1986-04-13 -10526,421,122,20,18.0,19,7.0,7,0.0,68,,,,14,1986-04-13 -10527,421,76,21,20.0,7,6.0,6,1.0,71,,,,11,1986-04-13 -10528,421,169,21,19.0,9,5.0,5,2.0,71,,,,11,1986-04-13 -10529,421,176,0,2.0,5,4.0,4,3.0,71,,,,11,1986-04-13 -10530,421,116,0,1.0,4,3.0,3,4.0,72,6549287.0,,,1,1986-04-13 -10531,421,136,2,6.0,2,,13,0.0,39,,,,5,1986-04-13 -10532,421,94,2,5.0,3,2.0,2,6.0,72,6527749.0,,,1,1986-04-13 -10533,421,101,31,12.0,1,1.0,1,9.0,72,6527735.0,,,1,1986-04-13 -10534,422,172,33,8.0,19,,19,0.0,19,,,,5,1986-04-27 -10535,422,144,17,24.0,18,,26,0.0,0,,,,3,1986-04-27 -10536,422,174,25,16.0,11,,25,0.0,5,,,,5,1986-04-27 -10537,422,178,47,29.0,24,,24,0.0,7,,,,101,1986-04-27 -10538,422,173,31,11.0,17,,23,0.0,8,,,,67,1986-04-27 -10539,422,94,2,5.0,3,,22,0.0,8,,,,5,1986-04-27 -10540,422,101,31,12.0,1,,21,0.0,11,,,,67,1986-04-27 -10541,422,171,26,26.0,14,,20,0.0,14,,,,7,1986-04-27 -10542,422,109,17,23.0,23,,18,0.0,20,,,,5,1986-04-27 -10543,422,177,25,15.0,21,,17,0.0,28,,,,25,1986-04-27 -10544,422,156,43,22.0,25,,16,0.0,31,,,,10,1986-04-27 -10545,422,169,21,19.0,10,,14,0.0,39,,,,5,1986-04-27 -10546,422,165,24,4.0,22,,13,0.0,41,,,,7,1986-04-27 -10547,422,155,47,14.0,20,,15,0.0,38,,,,23,1986-04-27 -10548,422,159,43,21.0,26,,11,0.0,52,,,,60,1986-04-27 -10549,422,116,0,1.0,4,1.0,1,9.0,60,5548408.0,,,1,1986-04-27 -10550,422,136,2,6.0,2,2.0,2,6.0,60,5556053.0,,,1,1986-04-27 -10551,422,76,21,20.0,9,3.0,3,4.0,59,,,,11,1986-04-27 -10552,422,139,5,28.0,7,4.0,4,3.0,59,,,,11,1986-04-27 -10553,422,162,26,25.0,8,,12,0.0,46,,,,36,1986-04-27 -10554,422,118,33,7.0,16,6.0,6,1.0,58,,,,60,1986-04-27 -10555,422,176,0,2.0,6,5.0,5,2.0,58,,,,60,1986-04-27 -10556,422,83,24,3.0,13,8.0,8,0.0,58,,,,12,1986-04-27 -10557,422,175,20,17.0,15,9.0,9,0.0,57,,,,13,1986-04-27 -10558,422,104,5,27.0,5,10.0,10,0.0,56,,,,101,1986-04-27 -10559,422,122,20,18.0,12,7.0,7,0.0,58,,,,12,1986-04-27 -10560,423,76,21,20.0,5,,15,0.0,42,,,,38,1986-05-11 -10561,423,169,21,19.0,16,,19,0.0,17,,,,23,1986-05-11 -10562,423,118,33,7.0,6,,16,0.0,38,,,,48,1986-05-11 -10563,423,172,33,8.0,20,,18,0.0,31,,,,5,1986-05-11 -10564,423,177,25,15.0,18,,20,0.0,2,,,,3,1986-05-11 -10565,423,104,5,27.0,4,,17,0.0,38,,,,101,1986-05-11 -10566,423,173,31,11.0,0,,22,0.0,0,,,,81,1986-05-11 -10567,423,178,47,29.0,0,,23,0.0,0,,,,81,1986-05-11 -10568,423,156,43,22.0,0,,24,0.0,0,,,,81,1986-05-11 -10569,423,109,17,23.0,0,,25,0.0,0,,,,81,1986-05-11 -10570,423,174,25,16.0,8,,14,0.0,67,,,,3,1986-05-11 -10571,423,159,43,21.0,0,,21,0.0,0,,,,81,1986-05-11 -10572,423,83,24,3.0,10,,13,0.0,67,,,,3,1986-05-11 -10573,423,162,26,25.0,12,5.0,5,2.0,77,,,,11,1986-05-11 -10574,423,165,24,4.0,13,11.0,11,0.0,74,,,,14,1986-05-11 -10575,423,155,47,14.0,19,12.0,12,0.0,74,,,,14,1986-05-11 -10576,423,176,0,2.0,9,2.0,2,6.0,78,6966082.0,,,1,1986-05-11 -10577,423,101,31,12.0,3,3.0,3,4.0,78,6994706.0,,,1,1986-05-11 -10578,423,94,2,5.0,2,4.0,4,3.0,78,7012462.0,,,1,1986-05-11 -10579,423,171,26,26.0,7,6.0,6,1.0,77,,,,11,1986-05-11 -10580,423,116,0,1.0,1,1.0,1,9.0,78,6941060.0,,,1,1986-05-11 -10581,423,122,20,18.0,14,8.0,8,0.0,75,,,,13,1986-05-11 -10582,423,175,20,17.0,17,9.0,9,0.0,75,,,,13,1986-05-11 -10583,423,139,5,28.0,15,10.0,10,0.0,75,,,,13,1986-05-11 -10584,423,136,2,6.0,11,7.0,7,0.0,77,,,,11,1986-05-11 -10585,424,144,17,24.0,22,,17,0.0,24,,,,6,1986-05-25 -10586,424,171,26,26.0,17,5.0,5,2.0,43,5348615.0,,,1,1986-05-25 -10587,424,139,5,28.0,11,3.0,3,4.0,43,5301517.0,,,1,1986-05-25 -10588,424,174,25,16.0,10,,25,0.0,0,,,,3,1986-05-25 -10589,424,156,43,22.0,25,,24,0.0,2,,,,5,1986-05-25 -10590,424,159,43,21.0,24,,23,0.0,3,,,,5,1986-05-25 -10591,424,176,0,2.0,8,,22,0.0,6,,,,5,1986-05-25 -10592,424,173,31,11.0,13,,21,0.0,7,,,,20,1986-05-25 -10593,424,122,20,18.0,14,,20,0.0,7,,,,10,1986-05-25 -10594,424,136,2,6.0,1,,19,0.0,16,,,,101,1986-05-25 -10595,424,162,26,25.0,7,,18,0.0,23,,,,5,1986-05-25 -10596,424,83,24,3.0,12,,16,0.0,25,,,,6,1986-05-25 -10597,424,104,5,27.0,9,4.0,4,3.0,43,5307559.0,,,1,1986-05-25 -10598,424,109,17,23.0,19,,14,0.0,35,,,,60,1986-05-25 -10599,424,155,47,14.0,20,13.0,13,0.0,37,,,,16,1986-05-25 -10600,424,165,24,4.0,18,12.0,12,0.0,40,,,,13,1986-05-25 -10601,424,177,25,15.0,16,11.0,11,0.0,40,,,,60,1986-05-25 -10602,424,76,21,20.0,2,10.0,10,0.0,41,,,,12,1986-05-25 -10603,424,175,20,17.0,21,9.0,9,0.0,41,,,,12,1986-05-25 -10604,424,118,33,7.0,15,8.0,8,0.0,42,,,,11,1986-05-25 -10605,424,169,21,19.0,6,7.0,7,0.0,42,,,,11,1986-05-25 -10606,424,116,0,1.0,3,6.0,6,1.0,43,5415697.0,,,1,1986-05-25 -10607,424,101,31,12.0,4,2.0,2,6.0,43,5297752.0,,,1,1986-05-25 -10608,424,94,2,5.0,5,1.0,1,9.0,43,5277925.0,,,1,1986-05-25 -10609,424,178,47,29.0,23,,15,0.0,25,,,,10,1986-05-25 -10610,425,76,21,20.0,7,,17,0.0,34,,,,101,1986-06-15 -10611,425,139,5,28.0,18,,18,0.0,29,,,,3,1986-06-15 -10612,425,173,31,11.0,16,,19,0.0,28,,,,3,1986-06-15 -10613,425,155,47,14.0,22,,20,0.0,24,,,,5,1986-06-15 -10614,425,122,20,18.0,12,,16,0.0,38,,,,10,1986-06-15 -10615,425,144,17,24.0,20,,22,0.0,17,,,,101,1986-06-15 -10616,425,169,21,19.0,15,,23,0.0,13,,,,84,1986-06-15 -10617,425,156,43,22.0,25,,24,0.0,6,,,,101,1986-06-15 -10618,425,174,25,16.0,14,,25,0.0,0,,,,3,1986-06-15 -10619,425,117,33,8.0,10,,21,0.0,20,,,,5,1986-06-15 -10620,425,109,17,23.0,21,,15,0.0,40,,,,6,1986-06-15 -10621,425,116,0,1.0,4,2.0,2,6.0,69,6167074.0,,,1,1986-06-15 -10622,425,118,33,7.0,9,,13,0.0,44,,,,101,1986-06-15 -10623,425,159,43,21.0,23,,14,0.0,43,,,,6,1986-06-15 -10624,425,136,2,6.0,3,3.0,3,4.0,69,6182677.0,,,1,1986-06-15 -10625,425,176,0,2.0,6,4.0,4,3.0,69,6242088.0,,,1,1986-06-15 -10626,425,101,31,12.0,2,5.0,5,2.0,68,,,,11,1986-06-15 -10627,425,162,26,25.0,5,6.0,6,1.0,68,,,,11,1986-06-15 -10628,425,94,2,5.0,1,1.0,1,9.0,69,6146415.0,,,1,1986-06-15 -10629,425,104,5,27.0,11,8.0,8,0.0,68,,,,11,1986-06-15 -10630,425,83,24,3.0,19,9.0,9,0.0,67,,,,12,1986-06-15 -10631,425,177,25,15.0,13,10.0,10,0.0,66,,,,13,1986-06-15 -10632,425,165,24,4.0,17,11.0,11,0.0,65,,,,14,1986-06-15 -10633,425,171,26,26.0,8,7.0,7,0.0,68,,,,11,1986-06-15 -10634,425,178,47,29.0,24,12.0,12,0.0,63,,,,16,1986-06-15 -10635,426,169,21,19.0,17,,17,0.0,38,,,,6,1986-06-22 -10636,426,157,25,16.0,10,,18,0.0,37,,,,38,1986-06-22 -10637,426,177,25,15.0,21,,19,0.0,33,,,,38,1986-06-22 -10638,426,179,43,22.0,25,,20,0.0,28,,,,10,1986-06-22 -10639,426,176,0,2.0,9,,23,0.0,12,,,,7,1986-06-22 -10640,426,76,21,20.0,12,,24,0.0,8,,,,5,1986-06-22 -10641,426,144,17,24.0,24,,25,0.0,3,,,,101,1986-06-22 -10642,426,178,47,29.0,26,,26,0.0,0,,,,10,1986-06-22 -10643,426,139,5,28.0,5,,16,0.0,40,,,,10,1986-06-22 -10644,426,159,43,21.0,22,,22,0.0,14,,,,101,1986-06-22 -10645,426,136,2,6.0,3,,15,0.0,41,,,,3,1986-06-22 -10646,426,83,24,3.0,16,,21,0.0,15,,,,10,1986-06-22 -10647,426,122,20,18.0,13,,13,0.0,44,,,,3,1986-06-22 -10648,426,101,31,12.0,1,1.0,1,9.0,63,6672847.0,,,1,1986-06-22 -10649,426,171,26,26.0,6,2.0,2,6.0,63,6703864.0,,,1,1986-06-22 -10650,426,116,0,1.0,7,3.0,3,4.0,63,6704671.0,,,1,1986-06-22 -10651,426,104,5,27.0,11,4.0,4,3.0,63,6763783.0,,,1,1986-06-22 -10652,426,109,17,23.0,23,,14,0.0,43,,,,6,1986-06-22 -10653,426,118,33,7.0,8,6.0,6,1.0,62,,,,11,1986-06-22 -10654,426,94,2,5.0,2,5.0,5,2.0,62,,,,11,1986-06-22 -10655,426,155,47,14.0,20,8.0,8,0.0,61,,,,12,1986-06-22 -10656,426,165,24,4.0,18,9.0,9,0.0,61,,,,12,1986-06-22 -10657,426,117,33,8.0,15,10.0,10,0.0,60,,,,13,1986-06-22 -10658,426,156,20,17.0,19,,11,0.0,51,,,,10,1986-06-22 -10659,426,162,26,25.0,4,,12,0.0,46,,,,3,1986-06-22 -10660,426,173,31,11.0,14,7.0,7,0.0,61,,,,12,1986-06-22 -10661,427,155,47,14.0,22,,15,0.0,46,,,,5,1986-07-06 -10662,427,165,24,4.0,17,,16,0.0,43,,,,42,1986-07-06 -10663,427,179,43,22.0,26,,18,0.0,25,,,,101,1986-07-06 -10664,427,144,17,24.0,19,,24,0.0,3,,,,3,1986-07-06 -10665,427,169,21,19.0,6,,20,0.0,7,,,,5,1986-07-06 -10666,427,139,5,28.0,10,,21,0.0,5,,,,101,1986-07-06 -10667,427,101,31,12.0,1,,22,0.0,3,,,,3,1986-07-06 -10668,427,159,43,21.0,25,,23,0.0,3,,,,3,1986-07-06 -10669,427,173,31,11.0,12,,14,0.0,56,,,,5,1986-07-06 -10670,427,76,21,20.0,8,,19,0.0,22,,,,6,1986-07-06 -10671,427,174,25,16.0,13,,13,0.0,64,,,,23,1986-07-06 -10672,427,118,33,7.0,16,7.0,7,0.0,78,,,,12,1986-07-06 -10673,427,156,20,17.0,18,11.0,11,0.0,76,,,,14,1986-07-06 -10674,427,83,24,3.0,15,10.0,10,0.0,77,,,,13,1986-07-06 -10675,427,117,33,8.0,14,9.0,9,0.0,77,,,,13,1986-07-06 -10676,427,104,5,27.0,9,8.0,8,0.0,78,,,,12,1986-07-06 -10677,427,171,26,26.0,11,6.0,6,1.0,79,,,,11,1986-07-06 -10678,427,162,26,25.0,4,5.0,5,2.0,79,,,,11,1986-07-06 -10679,427,176,0,2.0,7,4.0,4,3.0,80,5887975.0,,,1,1986-07-06 -10680,427,109,17,23.0,23,,25,0.0,3,,,,101,1986-07-06 -10681,427,136,2,6.0,3,3.0,3,4.0,80,5876817.0,,,1,1986-07-06 -10682,427,116,0,1.0,5,2.0,2,6.0,80,5856400.0,,,1,1986-07-06 -10683,427,94,2,5.0,2,1.0,1,9.0,80,5839272.0,,,1,1986-07-06 -10684,427,122,20,18.0,21,,12,0.0,67,,,,62,1986-07-06 -10685,427,177,25,15.0,20,,26,0.0,2,,,,3,1986-07-06 -10686,427,178,47,29.0,24,,17,0.0,32,,,,3,1986-07-06 -10687,428,83,24,3.0,11,5.0,5,2.0,72,,,,13,1986-07-13 -10688,428,165,24,4.0,16,6.0,6,1.0,72,,,,13,1986-07-13 -10689,428,179,43,22.0,26,,26,0.0,0,,,,4,1986-07-13 -10690,428,159,43,21.0,24,,25,0.0,0,,,,4,1986-07-13 -10691,428,156,20,17.0,23,,24,0.0,0,,,,4,1986-07-13 -10692,428,171,26,26.0,19,,23,0.0,0,,,,4,1986-07-13 -10693,428,176,0,2.0,5,,22,0.0,7,,,,6,1986-07-13 -10694,428,139,5,28.0,18,,21,0.0,20,,,,5,1986-07-13 -10695,428,76,21,20.0,4,,19,0.0,22,,,,10,1986-07-13 -10696,428,109,17,23.0,21,,18,0.0,23,,,,10,1986-07-13 -10697,428,178,47,29.0,25,,17,0.0,24,,,,5,1986-07-13 -10698,428,101,31,12.0,3,,16,0.0,27,,,,6,1986-07-13 -10699,428,118,33,7.0,15,,15,0.0,39,,,,5,1986-07-13 -10700,428,177,25,15.0,14,,20,0.0,22,,,,37,1986-07-13 -10701,428,144,17,24.0,20,,13,0.0,50,,,,38,1986-07-13 -10702,428,169,21,19.0,7,,14,0.0,45,,,,69,1986-07-13 -10703,428,116,0,1.0,6,3.0,3,4.0,74,,,,11,1986-07-13 -10704,428,136,2,6.0,1,2.0,2,6.0,75,5444045.0,,,1,1986-07-13 -10705,428,94,2,5.0,2,1.0,1,9.0,75,5438471.0,,,1,1986-07-13 -10706,428,173,31,11.0,10,7.0,7,0.0,72,,,,13,1986-07-13 -10707,428,162,26,25.0,8,4.0,4,3.0,73,,,,12,1986-07-13 -10708,428,155,47,14.0,22,9.0,9,0.0,69,,,,16,1986-07-13 -10709,428,122,20,18.0,13,,10,0.0,62,,,,62,1986-07-13 -10710,428,174,25,16.0,17,,11,0.0,60,,,,6,1986-07-13 -10711,428,104,5,27.0,12,,12,0.0,51,,,,101,1986-07-13 -10712,428,117,33,8.0,9,8.0,8,0.0,72,,,,13,1986-07-13 -10713,429,118,33,7.0,7,,17,0.0,22,,,,101,1986-07-27 -10714,429,109,17,23.0,23,,18,0.0,20,,,,6,1986-07-27 -10715,429,144,17,24.0,22,,19,0.0,19,,,,25,1986-07-27 -10716,429,173,31,11.0,12,,20,0.0,17,,,,21,1986-07-27 -10717,429,122,20,18.0,21,,21,0.0,13,,,,101,1986-07-27 -10718,429,159,43,21.0,25,,23,0.0,10,,,,8,1986-07-27 -10719,429,165,24,4.0,18,,24,0.0,7,,,,5,1986-07-27 -10720,429,104,5,27.0,10,,25,0.0,6,,,,7,1986-07-27 -10721,429,169,21,19.0,9,,26,0.0,0,,,,3,1986-07-27 -10722,429,83,24,3.0,15,,16,0.0,34,,,,10,1986-07-27 -10723,429,111,26,26.0,14,,22,0.0,11,,,,5,1986-07-27 -10724,429,155,47,14.0,16,,15,0.0,37,,,,5,1986-07-27 -10725,429,162,26,25.0,8,4.0,4,3.0,44,5003439.0,,,1,1986-07-27 -10726,429,156,20,17.0,17,,13,0.0,38,,,,101,1986-07-27 -10727,429,136,2,6.0,5,1.0,1,9.0,44,4928263.0,,,1,1986-07-27 -10728,429,101,31,12.0,3,2.0,2,6.0,44,4943700.0,,,1,1986-07-27 -10729,429,94,2,5.0,6,3.0,3,4.0,44,4972843.0,,,1,1986-07-27 -10730,429,116,0,1.0,2,6.0,6,1.0,43,,,,60,1986-07-27 -10731,429,117,33,8.0,20,7.0,7,0.0,43,,,,11,1986-07-27 -10732,429,176,0,2.0,1,5.0,5,2.0,43,,,,60,1986-07-27 -10733,429,177,25,15.0,19,9.0,9,0.0,42,,,,12,1986-07-27 -10734,429,76,21,20.0,4,10.0,10,0.0,42,,,,12,1986-07-27 -10735,429,139,5,28.0,11,11.0,11,0.0,41,,,,41,1986-07-27 -10736,429,179,43,22.0,26,12.0,12,0.0,40,,,,14,1986-07-27 -10737,429,174,25,16.0,13,8.0,8,0.0,43,,,,11,1986-07-27 -10738,429,178,47,29.0,24,,14,0.0,38,,,,6,1986-07-27 -10739,430,116,0,1.0,3,,20,0.0,23,,,,3,1986-08-10 -10740,430,144,17,24.0,17,,17,0.0,30,,,,5,1986-08-10 -10741,430,104,5,27.0,15,,18,0.0,29,,,,3,1986-08-10 -10742,430,117,33,8.0,19,,19,0.0,28,,,,3,1986-08-10 -10743,430,179,43,22.0,26,,26,0.0,1,,,,101,1986-08-10 -10744,430,118,33,7.0,14,,23,0.0,5,,,,6,1986-08-10 -10745,430,109,17,23.0,20,,24,0.0,5,,,,5,1986-08-10 -10746,430,178,47,29.0,25,,25,0.0,2,,,,21,1986-08-10 -10747,430,169,21,19.0,13,,16,0.0,32,,,,7,1986-08-10 -10748,430,159,43,21.0,23,,21,0.0,15,,,,22,1986-08-10 -10749,430,176,0,2.0,5,,15,0.0,34,,,,22,1986-08-10 -10750,430,156,20,17.0,21,,22,0.0,7,,,,22,1986-08-10 -10751,430,76,21,20.0,11,,13,0.0,44,,,,7,1986-08-10 -10752,430,122,20,18.0,22,,14,0.0,40,,,,10,1986-08-10 -10753,430,136,2,6.0,2,1.0,1,9.0,76,7234508.0,,,1,1986-08-10 -10754,430,94,2,5.0,4,3.0,3,4.0,75,,,,11,1986-08-10 -10755,430,139,5,28.0,7,4.0,4,3.0,75,,,,11,1986-08-10 -10756,430,173,31,11.0,8,5.0,5,2.0,74,,,,12,1986-08-10 -10757,430,83,24,3.0,16,6.0,6,1.0,74,,,,12,1986-08-10 -10758,430,101,31,12.0,1,2.0,2,6.0,76,7252181.0,,,1,1986-08-10 -10759,430,165,24,4.0,18,8.0,8,0.0,74,,,,12,1986-08-10 -10760,430,111,26,26.0,12,9.0,9,0.0,73,,,,13,1986-08-10 -10761,430,155,47,14.0,24,10.0,10,0.0,70,,,,16,1986-08-10 -10762,430,162,26,25.0,9,,11,0.0,48,,,,5,1986-08-10 -10763,430,174,25,16.0,6,7.0,7,0.0,74,,,,12,1986-08-10 -10764,430,177,25,15.0,10,,12,0.0,46,,,,24,1986-08-10 -10765,431,144,17,24.0,19,,17,0.0,13,,,,22,1986-08-17 -10766,431,109,17,23.0,23,,18,0.0,13,,,,8,1986-08-17 -10767,431,101,31,12.0,8,,19,0.0,13,,,,5,1986-08-17 -10768,431,83,24,3.0,17,,20,0.0,12,,,,101,1986-08-17 -10769,431,173,31,11.0,15,,22,0.0,9,,,,5,1986-08-17 -10770,431,111,26,26.0,11,,16,0.0,16,,,,5,1986-08-17 -10771,431,155,47,14.0,21,,23,0.0,8,,,,5,1986-08-17 -10772,431,179,43,22.0,26,,24,0.0,6,,,,10,1986-08-17 -10773,431,118,33,7.0,4,,25,0.0,2,,,,5,1986-08-17 -10774,431,117,33,8.0,10,,26,0.0,0,,,,54,1986-08-17 -10775,431,165,24,4.0,20,,21,0.0,10,,,,5,1986-08-17 -10776,431,169,21,19.0,1,,15,0.0,17,,,,5,1986-08-17 -10777,431,94,2,5.0,6,,12,0.0,32,,,,86,1986-08-17 -10778,431,136,2,6.0,7,,13,0.0,29,,,,5,1986-08-17 -10779,431,159,43,21.0,25,11.0,11,0.0,46,,,,16,1986-08-17 -10780,431,162,26,25.0,12,10.0,10,0.0,47,,,,15,1986-08-17 -10781,431,176,0,2.0,3,9.0,9,0.0,47,,,,10,1986-08-17 -10782,431,76,21,20.0,2,7.0,7,0.0,49,,,,13,1986-08-17 -10783,431,156,20,17.0,22,6.0,6,1.0,49,,,,13,1986-08-17 -10784,431,174,25,16.0,13,5.0,5,2.0,50,,,,12,1986-08-17 -10785,431,177,25,15.0,16,4.0,4,3.0,50,,,,12,1986-08-17 -10786,431,139,5,28.0,14,3.0,3,4.0,50,,,,12,1986-08-17 -10787,431,104,5,27.0,9,2.0,2,6.0,51,,,,11,1986-08-17 -10788,431,116,0,1.0,5,1.0,1,9.0,52,4882531.0,,,1,1986-08-17 -10789,431,122,20,18.0,18,,14,0.0,25,,,,101,1986-08-17 -10790,431,178,47,29.0,24,8.0,8,0.0,48,,,,14,1986-08-17 -10791,432,169,21,19.0,1,,12,0.0,44,,,,29,1986-09-07 -10792,432,136,2,6.0,6,1.0,1,9.0,51,4662889.0,,,1,1986-09-07 -10793,432,101,31,12.0,5,,27,0.0,0,,,,7,1986-09-07 -10794,432,178,47,29.0,24,,26,0.0,1,,,,5,1986-09-07 -10795,432,118,33,7.0,10,,25,0.0,2,,,,3,1986-09-07 -10796,432,174,25,16.0,15,,24,0.0,2,,,,3,1986-09-07 -10797,432,159,43,21.0,26,,23,0.0,12,,,,22,1986-09-07 -10798,432,144,17,24.0,19,,22,0.0,15,,,,10,1986-09-07 -10799,432,117,33,8.0,7,,21,0.0,16,,,,20,1986-09-07 -10800,432,111,26,26.0,14,,19,0.0,22,,,,5,1986-09-07 -10801,432,116,0,1.0,2,,18,0.0,27,,,,2,1986-09-07 -10802,432,155,47,14.0,22,,17,0.0,27,,,,5,1986-09-07 -10803,432,162,26,25.0,11,,16,0.0,30,,,,6,1986-09-07 -10804,432,121,38,31.0,25,,15,0.0,31,,,,29,1986-09-07 -10805,432,173,31,11.0,17,,20,0.0,18,,,,6,1986-09-07 -10806,432,104,5,27.0,9,,13,0.0,33,,,,5,1986-09-07 -10807,432,109,17,23.0,21,,14,0.0,33,,,,5,1986-09-07 -10808,432,139,5,28.0,12,3.0,3,4.0,51,4685804.0,,,1,1986-09-07 -10809,432,176,0,2.0,8,4.0,4,3.0,51,4716698.0,,,1,1986-09-07 -10810,432,76,21,20.0,4,5.0,5,2.0,50,,,,11,1986-09-07 -10811,432,177,25,15.0,18,6.0,6,1.0,49,,,,12,1986-09-07 -10812,432,122,20,18.0,13,7.0,7,0.0,49,,,,12,1986-09-07 -10813,432,94,2,5.0,3,2.0,2,6.0,51,4672717.0,,,1,1986-09-07 -10814,432,165,24,4.0,23,9.0,9,0.0,49,,,,12,1986-09-07 -10815,432,83,24,3.0,20,10.0,10,0.0,49,,,,12,1986-09-07 -10816,432,132,43,22.0,27,,11,0.0,45,,,,62,1986-09-07 -10817,432,156,20,17.0,16,8.0,8,0.0,49,,,,12,1986-09-07 -10818,433,174,25,16.0,14,,15,0.0,62,,,,62,1986-09-21 -10819,433,144,17,24.0,18,,16,0.0,60,,,,62,1986-09-21 -10820,433,76,21,20.0,4,,17,0.0,44,,,,20,1986-09-21 -10821,433,109,17,23.0,16,,18,0.0,43,,,,20,1986-09-21 -10822,433,176,0,2.0,7,,19,0.0,41,,,,10,1986-09-21 -10823,433,117,33,8.0,12,,20,0.0,41,,,,10,1986-09-21 -10824,433,165,24,4.0,23,,22,0.0,28,,,,5,1986-09-21 -10825,433,83,24,3.0,19,,23,0.0,18,,,,5,1986-09-21 -10826,433,177,25,15.0,17,,24,0.0,10,,,,23,1986-09-21 -10827,433,178,47,29.0,26,,25,0.0,9,,,,7,1986-09-21 -10828,433,159,43,21.0,24,,26,0.0,8,,,,5,1986-09-21 -10829,433,111,26,26.0,11,,21,0.0,39,,,,5,1986-09-21 -10830,433,118,33,7.0,9,,14,0.0,62,,,,5,1986-09-21 -10831,433,155,47,14.0,20,12.0,12,0.0,67,,,,13,1986-09-21 -10832,433,121,38,31.0,25,,27,0.0,6,,,,7,1986-09-21 -10833,433,179,43,22.0,27,13.0,13,0.0,63,,,,17,1986-09-21 -10834,433,116,0,1.0,3,2.0,2,6.0,70,5860672.0,,,1,1986-09-21 -10835,433,136,2,6.0,6,3.0,3,4.0,70,5891174.0,,,1,1986-09-21 -10836,433,101,31,12.0,1,4.0,4,3.0,69,,,,60,1986-09-21 -10837,433,104,5,27.0,13,5.0,5,2.0,69,,,,11,1986-09-21 -10838,433,94,2,5.0,2,1.0,1,9.0,70,5841900.0,,,1,1986-09-21 -10839,433,162,26,25.0,10,7.0,7,0.0,69,,,,11,1986-09-21 -10840,433,169,21,19.0,5,8.0,8,0.0,68,,,,12,1986-09-21 -10841,433,173,31,11.0,15,9.0,9,0.0,68,,,,12,1986-09-21 -10842,433,122,20,18.0,21,10.0,10,0.0,67,,,,13,1986-09-21 -10843,433,156,20,17.0,22,11.0,11,0.0,67,,,,13,1986-09-21 -10844,433,139,5,28.0,8,6.0,6,1.0,69,,,,11,1986-09-21 -10845,434,173,31,11.0,17,,17,0.0,53,,,,10,1986-10-12 -10846,434,117,33,8.0,7,,18,0.0,37,,,,5,1986-10-12 -10847,434,177,25,15.0,15,,19,0.0,35,,,,27,1986-10-12 -10848,434,176,0,2.0,11,,20,0.0,32,,,,29,1986-10-12 -10849,434,159,43,21.0,25,,22,0.0,8,,,,101,1986-10-12 -10850,434,165,24,4.0,19,,23,0.0,8,,,,101,1986-10-12 -10851,434,169,21,19.0,9,,24,0.0,4,,,,5,1986-10-12 -10852,434,174,25,16.0,8,,25,0.0,0,,,,3,1986-10-12 -10853,434,179,43,22.0,26,16.0,16,0.0,61,,,,17,1986-10-12 -10854,434,104,5,27.0,12,,21,0.0,10,,,,101,1986-10-12 -10855,434,162,26,25.0,13,15.0,15,0.0,63,,,,5,1986-10-12 -10856,434,76,21,20.0,4,1.0,1,9.0,68,5598700.0,,,1,1986-10-12 -10857,434,118,33,7.0,5,13.0,13,0.0,64,,,,20,1986-10-12 -10858,434,139,5,28.0,14,12.0,12,0.0,64,,,,101,1986-10-12 -10859,434,83,24,3.0,16,11.0,11,0.0,65,,,,13,1986-10-12 -10860,434,155,47,14.0,18,10.0,10,0.0,65,,,,60,1986-10-12 -10861,434,156,20,17.0,20,9.0,9,0.0,66,,,,12,1986-10-12 -10862,434,122,20,18.0,21,7.0,7,0.0,66,,,,12,1986-10-12 -10863,434,111,26,26.0,10,6.0,6,1.0,67,,,,11,1986-10-12 -10864,434,94,2,5.0,3,5.0,5,2.0,67,,,,11,1986-10-12 -10865,434,136,2,6.0,2,4.0,4,3.0,67,,,,11,1986-10-12 -10866,434,101,31,12.0,1,3.0,3,4.0,68,5651213.0,,,1,1986-10-12 -10867,434,116,0,1.0,6,2.0,2,6.0,68,5624138.0,,,1,1986-10-12 -10868,434,144,17,24.0,24,14.0,14,0.0,64,,,,14,1986-10-12 -10869,434,109,17,23.0,22,8.0,8,0.0,66,,,,12,1986-10-12 -10870,435,179,43,22.0,26,,15,0.0,61,,,,62,1986-10-26 -10871,435,136,2,6.0,2,2.0,2,6.0,82,6864593.0,,,1,1986-10-26 -10872,435,159,43,21.0,25,,25,0.0,2,,,,7,1986-10-26 -10873,435,144,17,24.0,18,,24,0.0,10,,,,3,1986-10-26 -10874,435,177,25,15.0,15,,23,0.0,16,,,,5,1986-10-26 -10875,435,178,47,29.0,23,,22,0.0,29,,,,22,1986-10-26 -10876,435,76,21,20.0,6,,21,0.0,40,,,,5,1986-10-26 -10877,435,109,17,23.0,11,,20,0.0,40,,,,26,1986-10-26 -10878,435,101,31,12.0,3,,19,0.0,43,,,,5,1986-10-26 -10879,435,122,20,18.0,22,,18,0.0,50,,,,5,1986-10-26 -10880,435,156,20,17.0,24,,17,0.0,52,,,,5,1986-10-26 -10881,435,117,33,8.0,20,,16,0.0,57,,,,23,1986-10-26 -10882,435,116,0,1.0,4,1.0,1,9.0,82,6860388.0,,,1,1986-10-26 -10883,435,104,5,27.0,9,,26,0.0,0,,,,3,1986-10-26 -10884,435,118,33,7.0,19,,13,0.0,63,,,,10,1986-10-26 -10885,435,176,0,2.0,7,,14,0.0,62,,,,27,1986-10-26 -10886,435,83,24,3.0,16,4.0,4,3.0,81,,,,11,1986-10-26 -10887,435,165,24,4.0,10,5.0,5,2.0,80,,,,60,1986-10-26 -10888,435,173,31,11.0,14,6.0,6,1.0,80,,,,12,1986-10-26 -10889,435,162,26,25.0,5,7.0,7,0.0,79,,,,13,1986-10-26 -10890,435,139,5,28.0,12,3.0,3,4.0,81,,,,11,1986-10-26 -10891,435,155,47,14.0,21,9.0,9,0.0,77,,,,15,1986-10-26 -10892,435,169,21,19.0,13,10.0,10,0.0,77,,,,15,1986-10-26 -10893,435,174,25,16.0,17,,11,0.0,70,,,,62,1986-10-26 -10894,435,94,2,5.0,1,,12,0.0,63,,,,27,1986-10-26 -10895,435,111,26,26.0,8,8.0,8,0.0,79,,,,13,1986-10-26 -10896,436,118,33,7.0,11,,15,0.0,48,,,,10,1987-04-12 -10897,436,121,36,16.0,23,,23,0.0,0,,,,54,1987-04-12 -10898,436,166,17,23.0,16,,22,0.0,3,,,,2,1987-04-12 -10899,436,169,21,19.0,4,,21,0.0,9,,,,101,1987-04-12 -10900,436,83,47,9.0,19,,20,0.0,15,,,,101,1987-04-12 -10901,436,144,17,24.0,15,,19,0.0,17,,,,22,1987-04-12 -10902,436,132,43,21.0,21,,18,0.0,20,,,,54,1987-04-12 -10903,436,117,20,17.0,8,,17,0.0,20,,,,5,1987-04-12 -10904,436,109,33,8.0,13,,16,0.0,21,,,,24,1987-04-12 -10905,436,101,31,12.0,3,,14,0.0,50,,,,5,1987-04-12 -10906,436,157,20,18.0,14,,13,0.0,52,,,,25,1987-04-12 -10907,436,116,0,1.0,5,1.0,1,9.0,61,5985141.0,,,1,1987-04-12 -10908,436,168,38,14.0,22,12.0,12,0.0,55,,,,16,1987-04-12 -10909,436,136,2,6.0,2,2.0,2,6.0,61,6025688.0,,,1,1987-04-12 -10910,436,139,0,2.0,10,3.0,3,4.0,61,6041899.0,,,1,1987-04-12 -10911,436,122,21,20.0,6,5.0,5,2.0,60,,,,11,1987-04-12 -10912,436,94,2,5.0,1,6.0,6,1.0,60,,,,11,1987-04-12 -10913,436,76,5,28.0,7,4.0,4,3.0,61,6084376.0,,,1,1987-04-12 -10914,436,104,5,27.0,9,8.0,8,0.0,58,,,,20,1987-04-12 -10915,436,156,47,10.0,17,9.0,9,0.0,58,,,,13,1987-04-12 -10916,436,155,24,3.0,18,10.0,10,0.0,58,,,,13,1987-04-12 -10917,436,165,24,4.0,20,11.0,11,0.0,57,,,,14,1987-04-12 -10918,436,137,31,11.0,12,7.0,7,0.0,59,,,,12,1987-04-12 -10919,437,144,17,24.0,15,,21,0.0,25,,,,101,1987-05-03 -10920,437,109,33,8.0,13,,18,0.0,39,,,,20,1987-05-03 -10921,437,166,17,23.0,16,,19,0.0,30,,,,6,1987-05-03 -10922,437,98,43,22.0,25,,20,0.0,26,,,,6,1987-05-03 -10923,437,121,36,16.0,22,,22,0.0,18,,,,5,1987-05-03 -10924,437,155,24,3.0,23,,17,0.0,48,,,,8,1987-05-03 -10925,437,116,0,1.0,3,,24,0.0,14,,,,10,1987-05-03 -10926,437,159,26,26.0,18,,25,0.0,7,,,,64,1987-05-03 -10927,437,136,2,6.0,0,,26,0.0,0,,,,82,1987-05-03 -10928,437,162,26,25.0,0,,27,0.0,0,,,,22,1987-05-03 -10929,437,76,5,28.0,5,,23,0.0,16,,,,10,1987-05-03 -10930,437,122,21,20.0,11,,15,0.0,48,,,,5,1987-05-03 -10931,437,157,20,18.0,9,,16,0.0,48,,,,8,1987-05-03 -10932,437,168,38,14.0,24,13.0,13,0.0,53,,,,16,1987-05-03 -10933,437,104,5,27.0,6,3.0,3,4.0,59,5523220.0,,,1,1987-05-03 -10934,437,139,0,2.0,8,4.0,4,3.0,59,5544664.0,,,1,1987-05-03 -10935,437,83,47,9.0,14,5.0,5,2.0,57,,,,12,1987-05-03 -10936,437,137,31,11.0,12,6.0,6,1.0,57,,,,60,1987-05-03 -10937,437,156,47,10.0,17,7.0,7,0.0,57,,,,12,1987-05-03 -10938,437,101,31,12.0,1,2.0,2,6.0,59,5511621.0,,,1,1987-05-03 -10939,437,118,33,7.0,7,9.0,9,0.0,57,,,,12,1987-05-03 -10940,437,165,24,4.0,20,8.0,8,0.0,57,,,,12,1987-05-03 -10941,437,94,2,5.0,2,1.0,1,9.0,59,5484076.0,,,1,1987-05-03 -10942,437,169,21,19.0,4,,14,0.0,51,,,,101,1987-05-03 -10943,437,117,20,17.0,10,11.0,11,0.0,55,,,,60,1987-05-03 -10944,437,111,32,30.0,21,10.0,10,0.0,56,,,,13,1987-05-03 -10945,437,132,43,21.0,19,12.0,12,0.0,54,,,,60,1987-05-03 -10946,438,101,31,12.0,3,,15,0.0,17,,,,3,1987-05-17 -10947,438,155,24,3.0,24,,26,0.0,0,,,,3,1987-05-17 -10948,438,166,17,23.0,19,,25,0.0,0,,,,6,1987-05-17 -10949,438,144,17,24.0,14,,24,0.0,1,,,,101,1987-05-17 -10950,438,118,33,7.0,8,,22,0.0,5,,,,8,1987-05-17 -10951,438,117,20,17.0,12,,21,0.0,8,,,,21,1987-05-17 -10952,438,156,47,10.0,20,,20,0.0,9,,,,23,1987-05-17 -10953,438,104,5,27.0,5,,19,0.0,9,,,,7,1987-05-17 -10954,438,132,43,21.0,26,,18,0.0,11,,,,95,1987-05-17 -10955,438,136,2,6.0,2,,17,0.0,11,,,,43,1987-05-17 -10956,438,121,36,16.0,21,,16,0.0,14,,,,5,1987-05-17 -10957,438,76,5,28.0,4,,23,0.0,2,,,,5,1987-05-17 -10958,438,122,21,20.0,7,,13,0.0,18,,,,67,1987-05-17 -10959,438,83,47,9.0,18,,12,0.0,19,,,,25,1987-05-17 -10960,438,94,2,5.0,1,,14,0.0,17,,,,3,1987-05-17 -10961,438,116,0,1.0,6,1.0,1,9.0,43,5223217.0,,,1,1987-05-17 -10962,438,139,0,2.0,10,2.0,2,6.0,43,5247981.0,,,1,1987-05-17 -10963,438,109,33,8.0,13,3.0,3,4.0,42,,,,11,1987-05-17 -10964,438,137,31,11.0,15,5.0,5,2.0,42,,,,11,1987-05-17 -10965,438,157,20,18.0,11,4.0,4,3.0,42,,,,11,1987-05-17 -10966,438,159,26,26.0,17,7.0,7,0.0,40,,,,13,1987-05-17 -10967,438,111,32,30.0,22,8.0,8,0.0,40,,,,13,1987-05-17 -10968,438,165,24,4.0,23,9.0,9,0.0,39,,,,14,1987-05-17 -10969,438,168,38,14.0,25,10.0,10,0.0,38,,,,15,1987-05-17 -10970,438,169,21,19.0,9,,11,0.0,34,,,,5,1987-05-17 -10971,438,162,26,25.0,16,6.0,6,1.0,41,,,,12,1987-05-17 -10972,439,132,43,21.0,16,,19,0.0,39,,,,10,1987-05-31 -10973,439,139,0,2.0,7,,16,0.0,57,,,,5,1987-05-31 -10974,439,111,32,30.0,18,,17,0.0,42,,,,5,1987-05-31 -10975,439,118,33,7.0,10,,18,0.0,41,,,,10,1987-05-31 -10976,439,109,33,8.0,21,,20,0.0,38,,,,22,1987-05-31 -10977,439,117,20,17.0,11,,15,0.0,58,,,,6,1987-05-31 -10978,439,165,24,4.0,23,,23,0.0,9,,,,3,1987-05-31 -10979,439,122,21,20.0,9,,24,0.0,5,,,,7,1987-05-31 -10980,439,166,17,23.0,0,,25,0.0,0,,,,54,1987-05-31 -10981,439,156,47,10.0,0,,26,0.0,0,,,,96,1987-05-31 -10982,439,94,2,5.0,1,,21,0.0,29,,,,101,1987-05-31 -10983,439,157,20,18.0,6,,14,0.0,59,,,,25,1987-05-31 -10984,439,144,17,24.0,13,,22,0.0,21,,,,10,1987-05-31 -10985,439,159,26,26.0,20,12.0,12,0.0,74,,,,14,1987-05-31 -10986,439,136,2,6.0,3,2.0,2,6.0,78,7107297.0,,,1,1987-05-31 -10987,439,104,5,27.0,5,3.0,3,4.0,78,7146924.0,,,1,1987-05-31 -10988,439,76,5,28.0,8,4.0,4,3.0,77,,,,11,1987-05-31 -10989,439,155,24,3.0,15,5.0,5,2.0,76,,,,12,1987-05-31 -10990,439,101,31,12.0,2,1.0,1,9.0,78,7074085.0,,,1,1987-05-31 -10991,439,168,38,14.0,24,13.0,13,0.0,71,,,,17,1987-05-31 -10992,439,83,47,9.0,14,7.0,7,0.0,76,,,,12,1987-05-31 -10993,439,169,21,19.0,12,8.0,8,0.0,76,,,,12,1987-05-31 -10994,439,116,0,1.0,4,9.0,9,0.0,75,,,,5,1987-05-31 -10995,439,137,31,11.0,17,10.0,10,0.0,75,,,,13,1987-05-31 -10996,439,162,26,25.0,22,11.0,11,0.0,74,,,,14,1987-05-31 -10997,439,121,36,16.0,19,6.0,6,1.0,76,,,,12,1987-05-31 -10998,440,104,5,27.0,7,,17,0.0,25,,,,6,1987-06-21 -10999,440,144,17,24.0,18,,18,0.0,22,,,,6,1987-06-21 -11000,440,83,47,9.0,15,,19,0.0,16,,,,101,1987-06-21 -11001,440,117,20,17.0,10,,20,0.0,12,,,,3,1987-06-21 -11002,440,121,36,16.0,22,,21,0.0,9,,,,10,1987-06-21 -11003,440,109,33,8.0,17,,24,0.0,2,,,,6,1987-06-21 -11004,440,132,43,21.0,19,,23,0.0,3,,,,7,1987-06-21 -11005,440,166,17,23.0,25,,25,0.0,1,,,,3,1987-06-21 -11006,440,137,31,11.0,24,,26,0.0,0,,,,3,1987-06-21 -11007,440,111,32,30.0,20,,16,0.0,38,,,,3,1987-06-21 -11008,440,169,21,19.0,8,,22,0.0,6,,,,3,1987-06-21 -11009,440,165,24,4.0,14,,15,0.0,44,,,,36,1987-06-21 -11010,440,159,26,26.0,23,,14,0.0,51,,,,8,1987-06-21 -11011,440,122,21,20.0,4,,13,0.0,52,,,,23,1987-06-21 -11012,440,136,2,6.0,3,2.0,2,6.0,63,6650177.0,,,1,1987-06-21 -11013,440,116,0,1.0,5,3.0,3,4.0,63,6661685.0,,,1,1987-06-21 -11014,440,76,5,28.0,12,4.0,4,3.0,63,6678959.0,,,1,1987-06-21 -11015,440,157,20,18.0,6,6.0,6,1.0,60,,,,13,1987-06-21 -11016,440,139,0,2.0,11,7.0,7,0.0,60,,,,13,1987-06-21 -11017,440,94,2,5.0,1,5.0,5,2.0,62,,,,11,1987-06-21 -11018,440,118,33,7.0,9,9.0,9,0.0,60,,,,13,1987-06-21 -11019,440,162,26,25.0,21,10.0,10,0.0,60,,,,13,1987-06-21 -11020,440,155,24,3.0,13,11.0,11,0.0,60,,,,13,1987-06-21 -11021,440,168,38,14.0,26,12.0,12,0.0,58,,,,15,1987-06-21 -11022,440,156,47,10.0,16,8.0,8,0.0,60,,,,13,1987-06-21 -11023,440,101,31,12.0,2,1.0,1,9.0,63,6616358.0,,,1,1987-06-21 -11024,441,156,47,10.0,19,,19,0.0,26,,,,25,1987-07-05 -11025,441,166,17,23.0,21,,16,0.0,52,,,,101,1987-07-05 -11026,441,162,26,25.0,13,,17,0.0,33,,,,43,1987-07-05 -11027,441,122,21,20.0,5,,18,0.0,31,,,,5,1987-07-05 -11028,441,157,20,18.0,14,,26,0.0,0,,,,10,1987-07-05 -11029,441,118,33,7.0,12,,22,0.0,19,,,,24,1987-07-05 -11030,441,83,47,9.0,18,,23,0.0,18,,,,36,1987-07-05 -11031,441,132,43,21.0,20,,24,0.0,11,,,,5,1987-07-05 -11032,441,109,33,8.0,11,,25,0.0,2,,,,101,1987-07-05 -11033,441,121,36,16.0,22,,15,0.0,52,,,,5,1987-07-05 -11034,441,144,17,24.0,15,,21,0.0,23,,,,101,1987-07-05 -11035,441,111,32,30.0,23,,14,0.0,57,,,,6,1987-07-05 -11036,441,159,26,26.0,17,,20,0.0,24,,,,5,1987-07-05 -11037,441,104,5,27.0,8,,12,0.0,64,,,,5,1987-07-05 -11038,441,94,2,5.0,1,1.0,1,9.0,80,5823839.0,,,1,1987-07-05 -11039,441,136,2,6.0,4,2.0,2,6.0,80,5831550.0,,,1,1987-07-05 -11040,441,116,0,1.0,2,3.0,3,4.0,80,5879094.0,,,1,1987-07-05 -11041,441,169,21,19.0,7,5.0,5,2.0,77,,,,13,1987-07-05 -11042,441,165,24,4.0,25,6.0,6,1.0,76,,,,14,1987-07-05 -11043,441,101,31,12.0,3,4.0,4,3.0,79,,,,11,1987-07-05 -11044,441,139,0,2.0,9,8.0,8,0.0,74,,,,16,1987-07-05 -11045,441,168,38,14.0,26,9.0,9,0.0,74,,,,16,1987-07-05 -11046,441,76,5,28.0,6,,10,0.0,71,,,,22,1987-07-05 -11047,441,137,31,11.0,16,,11,0.0,71,,,,62,1987-07-05 -11048,441,155,24,3.0,24,7.0,7,0.0,76,,,,14,1987-07-05 -11049,441,117,20,17.0,10,,13,0.0,62,,,,101,1987-07-05 -11050,442,139,0,2.0,10,,19,0.0,18,,,,5,1987-07-12 -11051,442,132,43,21.0,20,,16,0.0,32,,,,5,1987-07-12 -11052,442,156,47,10.0,18,,17,0.0,32,,,,6,1987-07-12 -11053,442,118,33,7.0,11,,18,0.0,28,,,,101,1987-07-12 -11054,442,159,26,26.0,19,,26,0.0,0,,,,96,1987-07-12 -11055,442,76,5,28.0,8,,22,0.0,7,,,,3,1987-07-12 -11056,442,111,32,30.0,21,,23,0.0,7,,,,6,1987-07-12 -11057,442,162,26,25.0,16,,24,0.0,3,,,,10,1987-07-12 -11058,442,121,36,16.0,24,,25,0.0,3,,,,3,1987-07-12 -11059,442,166,17,23.0,19,,15,0.0,34,,,,69,1987-07-12 -11060,442,109,33,8.0,9,,21,0.0,8,,,,101,1987-07-12 -11061,442,157,20,18.0,14,,14,0.0,45,,,,5,1987-07-12 -11062,442,144,17,24.0,15,,20,0.0,10,,,,5,1987-07-12 -11063,442,116,0,1.0,4,,12,0.0,53,,,,5,1987-07-12 -11064,442,104,5,27.0,7,,13,0.0,52,,,,22,1987-07-12 -11065,442,136,2,6.0,1,2.0,2,6.0,65,4753698.0,,,1,1987-07-12 -11066,442,101,31,12.0,3,3.0,3,4.0,64,,,,11,1987-07-12 -11067,442,137,31,11.0,12,4.0,4,3.0,63,,,,12,1987-07-12 -11068,442,117,20,17.0,13,5.0,5,2.0,63,,,,12,1987-07-12 -11069,442,94,2,5.0,2,1.0,1,9.0,65,4751780.0,,,1,1987-07-12 -11070,442,122,21,20.0,5,7.0,7,0.0,62,,,,13,1987-07-12 -11071,442,155,24,3.0,23,8.0,8,0.0,60,,,,15,1987-07-12 -11072,442,168,38,14.0,25,9.0,9,0.0,59,,,,16,1987-07-12 -11073,442,165,24,4.0,22,,10,0.0,57,,,,5,1987-07-12 -11074,442,83,47,9.0,17,,11,0.0,54,,,,62,1987-07-12 -11075,442,169,21,19.0,6,6.0,6,1.0,63,,,,12,1987-07-12 -11076,443,76,5,28.0,10,,16,0.0,19,,,,101,1987-07-26 -11077,443,169,21,19.0,9,,17,0.0,18,,,,5,1987-07-26 -11078,443,132,43,21.0,26,,18,0.0,17,,,,5,1987-07-26 -11079,443,109,33,8.0,7,,19,0.0,12,,,,5,1987-07-26 -11080,443,168,38,14.0,25,,21,0.0,10,,,,5,1987-07-26 -11081,443,157,20,18.0,15,,22,0.0,9,,,,37,1987-07-26 -11082,443,137,31,11.0,14,,23,0.0,9,,,,101,1987-07-26 -11083,443,121,36,16.0,24,,24,0.0,7,,,,5,1987-07-26 -11084,443,156,47,10.0,20,,15,0.0,21,,,,86,1987-07-26 -11085,443,162,26,25.0,12,,25,0.0,6,,,,80,1987-07-26 -11086,443,117,20,17.0,13,,14,0.0,23,,,,101,1987-07-26 -11087,443,116,0,1.0,3,7.0,7,0.0,39,,,,10,1987-07-26 -11088,443,94,2,5.0,1,,12,0.0,25,,,,5,1987-07-26 -11089,443,122,21,20.0,6,,11,0.0,26,,,,5,1987-07-26 -11090,443,166,17,23.0,18,,10,0.0,28,,,,5,1987-07-26 -11091,443,159,26,26.0,17,,9,0.0,32,,,,5,1987-07-26 -11092,443,83,47,9.0,19,,8,0.0,34,,,,62,1987-07-26 -11093,443,111,32,30.0,21,6.0,6,1.0,42,,,,12,1987-07-26 -11094,443,155,24,3.0,23,5.0,5,2.0,43,,,,11,1987-07-26 -11095,443,165,24,4.0,22,4.0,4,3.0,43,,,,11,1987-07-26 -11096,443,101,31,12.0,2,3.0,3,4.0,43,,,,11,1987-07-26 -11097,443,139,0,2.0,8,2.0,2,6.0,44,4984682.0,,,1,1987-07-26 -11098,443,136,2,6.0,4,1.0,1,9.0,44,4885091.0,,,1,1987-07-26 -11099,443,144,17,24.0,16,,13,0.0,25,,,,5,1987-07-26 -11100,443,118,33,7.0,11,,26,0.0,5,,,,80,1987-07-26 -11101,443,104,5,27.0,5,,20,0.0,10,,,,101,1987-07-26 -11102,444,117,20,17.0,9,6.0,6,1.0,74,,,,12,1987-08-09 -11103,444,155,24,3.0,16,7.0,7,0.0,74,,,,12,1987-08-09 -11104,444,137,31,11.0,17,,26,0.0,1,,,,30,1987-08-09 -11105,444,156,47,10.0,23,,25,0.0,3,,,,5,1987-08-09 -11106,444,76,5,28.0,2,,24,0.0,13,,,,24,1987-08-09 -11107,444,166,17,23.0,24,,23,0.0,14,,,,20,1987-08-09 -11108,444,169,21,19.0,12,,22,0.0,14,,,,6,1987-08-09 -11109,444,139,0,2.0,8,,21,0.0,14,,,,6,1987-08-09 -11110,444,109,33,8.0,13,,20,0.0,43,,,,6,1987-08-09 -11111,444,104,5,27.0,5,,19,0.0,43,,,,5,1987-08-09 -11112,444,83,47,9.0,22,,18,0.0,45,,,,101,1987-08-09 -11113,444,111,32,30.0,15,,17,0.0,48,,,,3,1987-08-09 -11114,444,162,26,25.0,19,,16,0.0,57,,,,10,1987-08-09 -11115,444,136,2,6.0,3,1.0,1,9.0,76,7166793.0,,,1,1987-08-09 -11116,444,94,2,5.0,1,14.0,14,0.0,70,,,,36,1987-08-09 -11117,444,122,21,20.0,7,4.0,4,3.0,75,,,,11,1987-08-09 -11118,444,116,0,1.0,4,3.0,3,4.0,76,7254249.0,,,1,1987-08-09 -11119,444,101,31,12.0,6,2.0,2,6.0,76,7204520.0,,,1,1987-08-09 -11120,444,118,33,7.0,10,5.0,5,2.0,75,,,,11,1987-08-09 -11121,444,157,20,18.0,11,8.0,8,0.0,74,,,,12,1987-08-09 -11122,444,132,43,21.0,21,,15,0.0,64,,,,69,1987-08-09 -11123,444,121,36,16.0,18,10.0,10,0.0,74,,,,12,1987-08-09 -11124,444,144,17,24.0,20,11.0,11,0.0,73,,,,13,1987-08-09 -11125,444,159,26,26.0,25,12.0,12,0.0,73,,,,13,1987-08-09 -11126,444,168,38,14.0,26,13.0,13,0.0,71,,,,15,1987-08-09 -11127,444,165,24,4.0,14,9.0,9,0.0,74,,,,12,1987-08-09 -11128,445,118,33,7.0,8,,17,0.0,43,,,,5,1987-08-16 -11129,445,104,5,27.0,6,,18,0.0,42,,,,101,1987-08-16 -11130,445,109,33,8.0,10,,19,0.0,35,,,,5,1987-08-16 -11131,445,117,20,17.0,11,,20,0.0,35,,,,5,1987-08-16 -11132,445,157,20,18.0,12,,21,0.0,31,,,,27,1987-08-16 -11133,445,166,17,23.0,19,,23,0.0,3,,,,10,1987-08-16 -11134,445,144,17,24.0,15,,24,0.0,1,,,,5,1987-08-16 -11135,445,132,43,21.0,21,,25,0.0,0,,,,10,1987-08-16 -11136,445,165,24,4.0,25,,26,0.0,0,,,,3,1987-08-16 -11137,445,168,38,14.0,26,,16,0.0,45,,,,62,1987-08-16 -11138,445,76,5,28.0,3,,22,0.0,5,,,,101,1987-08-16 -11139,445,155,24,3.0,24,14.0,14,0.0,47,,,,15,1987-08-16 -11140,445,83,47,9.0,17,,15,0.0,48,,,,2,1987-08-16 -11141,445,94,2,5.0,2,1.0,1,9.0,52,4724898.0,,,1,1987-08-16 -11142,445,137,31,11.0,13,13.0,13,0.0,49,,,,13,1987-08-16 -11143,445,136,2,6.0,1,2.0,2,6.0,52,4780602.0,,,1,1987-08-16 -11144,445,169,21,19.0,5,3.0,3,4.0,51,,,,11,1987-08-16 -11145,445,122,21,20.0,4,4.0,4,3.0,51,,,,11,1987-08-16 -11146,445,116,0,1.0,9,6.0,6,1.0,50,,,,12,1987-08-16 -11147,445,101,31,12.0,7,5.0,5,2.0,50,,,,12,1987-08-16 -11148,445,159,26,26.0,18,8.0,8,0.0,50,,,,12,1987-08-16 -11149,445,156,47,10.0,20,9.0,9,0.0,49,,,,13,1987-08-16 -11150,445,162,26,25.0,16,10.0,10,0.0,49,,,,13,1987-08-16 -11151,445,121,36,16.0,23,11.0,11,0.0,49,,,,13,1987-08-16 -11152,445,111,32,30.0,22,12.0,12,0.0,49,,,,13,1987-08-16 -11153,445,139,0,2.0,14,7.0,7,0.0,50,,,,12,1987-08-16 -11154,446,170,43,22.0,26,,21,0.0,27,,,,101,1987-09-06 -11155,446,111,32,30.0,23,,18,0.0,37,,,,20,1987-09-06 -11156,446,166,17,23.0,20,,19,0.0,34,,,,5,1987-09-06 -11157,446,157,20,18.0,13,,20,0.0,27,,,,86,1987-09-06 -11158,446,132,43,21.0,21,,22,0.0,16,,,,22,1987-09-06 -11159,446,83,47,9.0,17,,17,0.0,43,,,,6,1987-09-06 -11160,446,117,20,17.0,12,,24,0.0,9,,,,10,1987-09-06 -11161,446,109,33,8.0,10,,25,0.0,7,,,,22,1987-09-06 -11162,446,118,33,7.0,9,,26,0.0,5,,,,5,1987-09-06 -11163,446,77,41,32.0,0,,27,0.0,0,,,,81,1987-09-06 -11164,446,168,38,14.0,0,,28,0.0,0,,,,81,1987-09-06 -11165,446,104,5,27.0,8,,23,0.0,13,,,,101,1987-09-06 -11166,446,144,17,24.0,18,16.0,16,0.0,45,,,,15,1987-09-06 -11167,446,116,0,1.0,5,15.0,15,0.0,46,,,,14,1987-09-06 -11168,446,155,24,3.0,22,14.0,14,0.0,47,,,,13,1987-09-06 -11169,446,136,2,6.0,1,1.0,1,9.0,50,4487707.0,,,1,1987-09-06 -11170,446,94,2,5.0,2,3.0,3,4.0,50,4536743.0,,,1,1987-09-06 -11171,446,76,5,28.0,3,4.0,4,3.0,50,4545686.0,,,1,1987-09-06 -11172,446,122,21,20.0,6,5.0,5,2.0,50,4569026.0,,,1,1987-09-06 -11173,446,139,0,2.0,11,6.0,6,1.0,50,4576494.0,,,1,1987-09-06 -11174,446,169,21,19.0,7,7.0,7,0.0,49,,,,11,1987-09-06 -11175,446,101,31,12.0,4,2.0,2,6.0,50,4489513.0,,,1,1987-09-06 -11176,446,156,47,10.0,16,9.0,9,0.0,48,,,,12,1987-09-06 -11177,446,162,26,25.0,15,10.0,10,0.0,48,,,,12,1987-09-06 -11178,446,137,31,11.0,14,11.0,11,0.0,47,,,,13,1987-09-06 -11179,446,165,24,4.0,24,12.0,12,0.0,47,,,,13,1987-09-06 -11180,446,121,36,16.0,25,13.0,13,0.0,47,,,,13,1987-09-06 -11181,446,159,26,26.0,19,8.0,8,0.0,48,,,,12,1987-09-06 -11182,447,83,47,9.0,17,,17,0.0,35,,,,6,1987-09-20 -11183,447,170,43,22.0,26,,18,0.0,32,,,,22,1987-09-20 -11184,447,111,32,30.0,19,,19,0.0,31,,,,5,1987-09-20 -11185,447,162,26,25.0,18,,20,0.0,29,,,,21,1987-09-20 -11186,447,132,43,21.0,25,,21,0.0,27,,,,101,1987-09-20 -11187,447,94,2,5.0,2,,24,0.0,13,,,,10,1987-09-20 -11188,447,166,17,23.0,20,,23,0.0,24,,,,3,1987-09-20 -11189,447,118,33,7.0,7,,25,0.0,13,,,,5,1987-09-20 -11190,447,156,47,10.0,16,,26,0.0,0,,,,3,1987-09-20 -11191,447,104,5,27.0,6,,16,0.0,38,,,,6,1987-09-20 -11192,447,159,26,26.0,23,,22,0.0,24,,,,80,1987-09-20 -11193,447,109,33,8.0,13,,15,0.0,54,,,,98,1987-09-20 -11194,447,117,20,17.0,12,13.0,13,0.0,66,,,,14,1987-09-20 -11195,447,139,0,2.0,8,5.0,5,2.0,69,,,,11,1987-09-20 -11196,447,165,24,4.0,21,12.0,12,0.0,66,,,,14,1987-09-20 -11197,447,144,17,24.0,14,11.0,11,0.0,66,,,,60,1987-09-20 -11198,447,155,24,3.0,24,10.0,10,0.0,67,,,,13,1987-09-20 -11199,447,121,36,16.0,22,9.0,9,0.0,67,,,,13,1987-09-20 -11200,447,137,31,11.0,15,8.0,8,0.0,68,,,,12,1987-09-20 -11201,447,101,31,12.0,5,7.0,7,0.0,68,,,,12,1987-09-20 -11202,447,157,20,18.0,11,6.0,6,1.0,68,,,,12,1987-09-20 -11203,447,169,21,19.0,10,4.0,4,3.0,69,,,,60,1987-09-20 -11204,447,136,2,6.0,4,3.0,3,4.0,70,5887201.0,,,1,1987-09-20 -11205,447,76,5,28.0,1,2.0,2,6.0,70,5844399.0,,,1,1987-09-20 -11206,447,122,21,20.0,9,14.0,14,0.0,64,,,,16,1987-09-20 -11207,447,116,0,1.0,3,1.0,1,9.0,70,5823906.0,,,1,1987-09-20 -11208,448,132,43,21.0,0,,27,0.0,0,,,,81,1987-09-27 -11209,448,104,5,27.0,4,15.0,15,0.0,67,,,,5,1987-09-27 -11210,448,155,24,3.0,16,,18,0.0,55,,,,4,1987-09-27 -11211,448,122,21,20.0,8,16.0,16,0.0,66,,,,3,1987-09-27 -11212,448,162,26,25.0,14,,19,0.0,55,,,,4,1987-09-27 -11213,448,77,41,32.0,26,,26,0.0,8,,,,22,1987-09-27 -11214,448,144,17,24.0,21,,21,0.0,45,,,,101,1987-09-27 -11215,448,169,21,19.0,6,,22,0.0,40,,,,23,1987-09-27 -11216,448,109,33,8.0,10,,23,0.0,26,,,,6,1987-09-27 -11217,448,168,38,14.0,25,,25,0.0,10,,,,8,1987-09-27 -11218,448,156,47,10.0,22,,20,0.0,50,,,,7,1987-09-27 -11219,448,166,17,23.0,24,14.0,14,0.0,68,,,,14,1987-09-27 -11220,448,159,26,26.0,23,,24,0.0,24,,,,80,1987-09-27 -11221,448,121,36,16.0,19,12.0,12,0.0,70,,,,12,1987-09-27 -11222,448,118,33,7.0,9,13.0,13,0.0,68,,,,14,1987-09-27 -11223,448,94,2,5.0,2,1.0,1,9.0,72,6552692.0,,,1,1987-09-27 -11224,448,116,0,1.0,7,2.0,2,6.0,72,6574917.0,,,1,1987-09-27 -11225,448,139,0,2.0,11,3.0,3,4.0,72,6583510.0,,,1,1987-09-27 -11226,448,136,2,6.0,1,4.0,4,3.0,72,6584142.0,,,1,1987-09-27 -11227,448,101,31,12.0,5,5.0,5,2.0,72,6626199.0,,,1,1987-09-27 -11228,448,76,5,28.0,3,,17,0.0,62,,,,5,1987-09-27 -11229,448,165,24,4.0,15,7.0,7,0.0,71,,,,11,1987-09-27 -11230,448,157,20,18.0,13,8.0,8,0.0,70,,,,60,1987-09-27 -11231,448,137,31,11.0,18,9.0,9,0.0,70,,,,12,1987-09-27 -11232,448,117,20,17.0,12,10.0,10,0.0,70,,,,12,1987-09-27 -11233,448,111,32,30.0,17,6.0,6,1.0,71,,,,11,1987-09-27 -11234,448,83,47,9.0,20,11.0,11,0.0,70,,,,12,1987-09-27 -11235,449,117,20,17.0,11,,16,0.0,26,,,,3,1987-10-18 -11236,449,76,5,28.0,2,,18,0.0,20,,,,101,1987-10-18 -11237,449,122,21,20.0,4,,19,0.0,15,,,,10,1987-10-18 -11238,449,144,17,24.0,14,,20,0.0,13,,,,101,1987-10-18 -11239,449,104,5,27.0,9,,21,0.0,12,,,,5,1987-10-18 -11240,449,137,31,11.0,16,,24,0.0,1,,,,3,1987-10-18 -11241,449,139,0,2.0,15,,23,0.0,1,,,,3,1987-10-18 -11242,449,162,26,25.0,18,,15,0.0,29,,,,25,1987-10-18 -11243,449,156,47,10.0,17,,25,0.0,1,,,,3,1987-10-18 -11244,449,116,0,1.0,5,,26,0.0,0,,,,4,1987-10-18 -11245,449,83,47,9.0,13,,22,0.0,3,,,,101,1987-10-18 -11246,449,166,17,23.0,19,,14,0.0,32,,,,7,1987-10-18 -11247,449,109,33,8.0,10,,17,0.0,22,,,,3,1987-10-18 -11248,449,132,43,21.0,26,,12,0.0,50,,,,5,1987-10-18 -11249,449,94,2,5.0,1,1.0,1,9.0,63,5184207.0,,,1,1987-10-18 -11250,449,159,26,26.0,21,,13,0.0,43,,,,47,1987-10-18 -11251,449,136,2,6.0,3,2.0,2,6.0,63,5210383.0,,,1,1987-10-18 -11252,449,118,33,7.0,8,3.0,3,4.0,63,5271086.0,,,1,1987-10-18 -11253,449,157,20,18.0,13,4.0,4,3.0,63,5285559.0,,,1,1987-10-18 -11254,449,111,32,30.0,24,6.0,6,1.0,60,,,,13,1987-10-18 -11255,449,169,21,19.0,6,5.0,5,2.0,61,,,,12,1987-10-18 -11256,449,165,24,4.0,25,8.0,8,0.0,60,,,,13,1987-10-18 -11257,449,113,32,29.0,23,9.0,9,0.0,59,,,,14,1987-10-18 -11258,449,101,31,12.0,7,,10,0.0,54,,,,20,1987-10-18 -11259,449,121,36,16.0,20,,11,0.0,51,,,,47,1987-10-18 -11260,449,155,24,3.0,22,7.0,7,0.0,60,,,,13,1987-10-18 -11261,450,144,17,24.0,14,,19,0.0,35,,,,5,1987-11-01 -11262,450,162,26,25.0,17,,16,0.0,44,,,,60,1987-11-01 -11263,450,132,43,21.0,23,,17,0.0,43,,,,60,1987-11-01 -11264,450,89,38,14.0,26,,18,0.0,38,,,,10,1987-11-01 -11265,450,83,47,9.0,15,,20,0.0,32,,,,5,1987-11-01 -11266,450,111,32,30.0,18,,26,0.0,0,,,,3,1987-11-01 -11267,450,169,21,19.0,6,,22,0.0,16,,,,5,1987-11-01 -11268,450,121,36,16.0,20,,24,0.0,13,,,,3,1987-11-01 -11269,450,166,17,23.0,21,,25,0.0,2,,,,5,1987-11-01 -11270,450,136,2,6.0,5,15.0,15,0.0,46,,,,5,1987-11-01 -11271,450,109,33,8.0,10,,21,0.0,26,,,,5,1987-11-01 -11272,450,113,32,29.0,22,14.0,14,0.0,47,,,,14,1987-11-01 -11273,450,94,2,5.0,0,,27,0.0,0,,,,3,1987-11-01 -11274,450,165,24,4.0,25,12.0,12,0.0,49,,,,12,1987-11-01 -11275,450,159,26,26.0,24,13.0,13,0.0,48,,,,13,1987-11-01 -11276,450,76,5,28.0,1,1.0,1,9.0,51,5578072.0,,,1,1987-11-01 -11277,450,101,31,12.0,7,2.0,2,6.0,51,5595456.0,,,1,1987-11-01 -11278,450,139,0,2.0,9,3.0,3,4.0,51,5595766.0,,,1,1987-11-01 -11279,450,104,5,27.0,4,4.0,4,3.0,51,5658513.0,,,1,1987-11-01 -11280,450,122,21,20.0,3,5.0,5,2.0,51,5663648.0,,,1,1987-11-01 -11281,450,156,47,10.0,16,,23,0.0,13,,,,5,1987-11-01 -11282,450,116,0,1.0,2,7.0,7,0.0,50,,,,11,1987-11-01 -11283,450,137,31,11.0,11,6.0,6,1.0,51,5674551.0,,,1,1987-11-01 -11284,450,117,20,17.0,13,10.0,10,0.0,50,,,,11,1987-11-01 -11285,450,118,33,7.0,8,11.0,11,0.0,49,,,,12,1987-11-01 -11286,450,155,24,3.0,19,8.0,8,0.0,50,,,,11,1987-11-01 -11287,450,157,20,18.0,12,9.0,9,0.0,50,,,,60,1987-11-01 -11288,451,144,17,24.0,13,,26,0.0,0,,,,3,1987-11-15 -11289,451,165,24,4.0,18,,25,0.0,6,,,,20,1987-11-15 -11290,451,83,47,9.0,16,,24,0.0,18,,,,5,1987-11-15 -11291,451,139,0,2.0,8,,15,0.0,48,,,,23,1987-11-15 -11292,451,137,31,11.0,14,,22,0.0,22,,,,9,1987-11-15 -11293,451,159,26,26.0,22,,21,0.0,26,,,,80,1987-11-15 -11294,451,130,33,7.0,15,,20,0.0,31,,,,68,1987-11-15 -11295,451,162,26,25.0,20,,19,0.0,41,,,,80,1987-11-15 -11296,451,111,32,30.0,17,,18,0.0,45,,,,10,1987-11-15 -11297,451,166,17,23.0,26,,17,0.0,46,,,,7,1987-11-15 -11298,451,169,21,19.0,9,,16,0.0,46,,,,23,1987-11-15 -11299,451,157,20,18.0,11,,14,0.0,53,,,,25,1987-11-15 -11300,451,132,43,21.0,27,,27,0.0,0,,,,81,1987-11-15 -11301,451,121,36,16.0,23,,12,0.0,58,,,,20,1987-11-15 -11302,451,116,0,1.0,2,,13,0.0,53,,,,23,1987-11-15 -11303,451,76,5,28.0,1,1.0,1,9.0,82,6776144.0,,,1,1987-11-15 -11304,451,104,5,27.0,6,2.0,2,6.0,82,6844028.0,,,1,1987-11-15 -11305,451,122,21,20.0,5,3.0,3,4.0,81,,,,11,1987-11-15 -11306,451,155,24,3.0,19,4.0,4,3.0,80,,,,12,1987-11-15 -11307,451,113,32,29.0,21,5.0,5,0.0,79,,,,13,1987-11-15 -11308,451,117,20,17.0,12,,23,0.0,19,,,,7,1987-11-15 -11309,451,156,47,10.0,24,7.0,7,0.0,79,,,,13,1987-11-15 -11310,451,109,33,8.0,10,8.0,8,0.0,78,,,,20,1987-11-15 -11311,451,118,2,5.0,7,9.0,9,0.0,76,,,,44,1987-11-15 -11312,451,101,31,12.0,4,,10,0.0,82,,,,2,1987-11-15 -11313,451,89,38,14.0,25,6.0,6,1.0,79,,,,13,1987-11-15 -11314,451,136,2,6.0,3,,11,0.0,58,,,,23,1987-11-15 -11315,452,130,42,33.0,24,,19,0.0,20,,,,5,1988-04-03 -11316,452,94,2,5.0,2,,20,0.0,18,,,,5,1988-04-03 -11317,452,144,21,19.0,12,,21,0.0,7,,,,5,1988-04-03 -11318,452,118,2,6.0,8,,22,0.0,6,,,,5,1988-04-03 -11319,452,121,36,16.0,9,,23,0.0,6,,,,5,1988-04-03 -11320,452,126,36,15.0,13,,25,0.0,0,,,,6,1988-04-03 -11321,452,162,26,25.0,18,,18,0.0,23,,,,8,1988-04-03 -11322,452,164,42,32.0,26,,26,0.0,0,,,,10,1988-04-03 -11323,452,140,24,4.0,0,,27,0.0,0,,,,81,1988-04-03 -11324,452,159,47,9.0,0,,28,0.0,0,,,,81,1988-04-03 -11325,452,77,43,21.0,0,,29,0.0,0,,,,81,1988-04-03 -11326,452,145,47,10.0,0,,30,0.0,0,,,,81,1988-04-03 -11327,452,166,17,23.0,23,,24,0.0,5,,,,83,1988-04-03 -11328,452,101,0,12.0,1,,17,0.0,31,,,,2,1988-04-03 -11329,452,98,41,31.0,25,,14,0.0,35,,,,22,1988-04-03 -11330,452,165,38,14.0,19,,15,0.0,35,,,,23,1988-04-03 -11331,452,111,32,30.0,16,,13,0.0,40,,,,22,1988-04-03 -11332,452,158,17,24.0,20,,12,0.0,46,,,,83,1988-04-03 -11333,452,155,24,3.0,22,,11,0.0,47,,,,7,1988-04-03 -11334,452,139,26,26.0,21,9.0,9,0.0,57,,,,13,1988-04-03 -11335,452,157,20,18.0,15,8.0,8,0.0,59,,,,11,1988-04-03 -11336,452,122,21,20.0,7,7.0,7,0.0,59,,,,11,1988-04-03 -11337,452,137,31,2.0,10,6.0,6,1.0,59,,,,11,1988-04-03 -11338,452,104,5,27.0,6,5.0,5,2.0,60,5841413.0,,,1,1988-04-03 -11339,452,117,20,17.0,11,4.0,4,3.0,60,5840205.0,,,1,1988-04-03 -11340,452,136,31,1.0,5,3.0,3,4.0,60,5835448.0,,,1,1988-04-03 -11341,452,76,5,28.0,4,2.0,2,6.0,60,5776730.0,,,1,1988-04-03 -11342,452,132,34,36.0,0,,31,0.0,0,,,,97,1988-04-03 -11343,452,113,32,29.0,17,,16,0.0,32,,,,5,1988-04-03 -11344,452,109,46,22.0,14,,10,0.0,53,,,,5,1988-04-03 -11345,452,116,0,11.0,3,1.0,1,9.0,60,5766857.0,,,1,1988-04-03 -11346,453,162,26,25.0,0,,30,0.0,0,,,,81,1988-05-01 -11347,453,164,42,32.0,0,,28,0.0,0,,,,81,1988-05-01 -11348,453,77,43,21.0,0,,27,0.0,0,,,,96,1988-05-01 -11349,453,109,46,22.0,16,,26,0.0,1,,,,22,1988-05-01 -11350,453,121,36,16.0,9,,25,0.0,2,,,,6,1988-05-01 -11351,453,159,47,9.0,25,,24,0.0,36,,,,6,1988-05-01 -11352,453,132,34,36.0,24,,23,0.0,38,,,,6,1988-05-01 -11353,453,98,41,31.0,17,,22,0.0,40,,,,69,1988-05-01 -11354,453,94,2,5.0,11,,21,0.0,42,,,,5,1988-05-01 -11355,453,130,42,33.0,26,,19,0.0,52,,,,62,1988-05-01 -11356,453,104,5,27.0,10,18.0,18,0.0,54,,,,5,1988-05-01 -11357,453,111,32,30.0,15,17.0,17,0.0,57,,,,13,1988-05-01 -11358,453,166,17,23.0,22,16.0,16,0.0,57,,,,13,1988-05-01 -11359,453,126,36,15.0,20,15.0,15,0.0,58,,,,12,1988-05-01 -11360,453,155,24,3.0,23,14.0,14,0.0,58,,,,12,1988-05-01 -11361,453,140,24,4.0,21,,20,0.0,48,,,,6,1988-05-01 -11362,453,113,32,29.0,19,12.0,12,0.0,58,,,,12,1988-05-01 -11363,453,118,2,6.0,6,13.0,13,0.0,58,,,,12,1988-05-01 -11364,453,101,0,12.0,1,1.0,1,9.0,60,5561264.0,,,1,1988-05-01 -11365,453,116,0,11.0,2,2.0,2,6.0,60,5563598.0,,,1,1988-05-01 -11366,453,136,31,1.0,3,3.0,3,4.0,59,,,,11,1988-05-01 -11367,453,122,21,20.0,8,4.0,4,3.0,59,,,,11,1988-05-01 -11368,453,76,5,28.0,5,5.0,5,2.0,59,,,,11,1988-05-01 -11369,453,139,26,26.0,0,,29,0.0,0,,,,81,1988-05-01 -11370,453,157,20,18.0,7,7.0,7,0.0,59,,,,11,1988-05-01 -11371,453,137,31,2.0,12,8.0,8,0.0,59,,,,11,1988-05-01 -11372,453,117,20,17.0,14,9.0,9,0.0,58,,,,12,1988-05-01 -11373,453,165,38,14.0,13,10.0,10,0.0,58,,,,12,1988-05-01 -11374,453,158,17,24.0,18,11.0,11,0.0,58,,,,12,1988-05-01 -11375,453,144,21,19.0,4,6.0,6,1.0,59,,,,11,1988-05-01 -11376,454,164,42,32.0,18,,20,0.0,14,,,,23,1988-05-15 -11377,454,157,20,18.0,9,,21,0.0,8,,,,5,1988-05-15 -11378,454,139,26,26.0,26,,22,0.0,6,,,,5,1988-05-15 -11379,454,98,41,31.0,24,,23,0.0,5,,,,22,1988-05-15 -11380,454,136,31,1.0,11,,24,0.0,1,,,,4,1988-05-15 -11381,454,165,38,14.0,12,,26,0.0,0,,,,37,1988-05-15 -11382,454,166,17,23.0,0,,29,0.0,0,,,,81,1988-05-15 -11383,454,145,47,10.0,0,,28,0.0,0,,,,81,1988-05-15 -11384,454,140,24,4.0,0,,30,0.0,0,,,,81,1988-05-15 -11385,454,130,42,33.0,0,,31,0.0,0,,,,96,1988-05-15 -11386,454,116,0,11.0,2,1.0,1,9.0,78,7037077.0,,,1,1988-05-15 -11387,454,162,26,25.0,20,,19,0.0,17,,,,5,1988-05-15 -11388,454,137,31,2.0,0,,27,0.0,0,,,,81,1988-05-15 -11389,454,109,46,22.0,19,,18,0.0,28,,,,5,1988-05-15 -11390,454,132,34,36.0,17,,25,0.0,0,,,,20,1988-05-15 -11391,454,158,17,24.0,15,,16,0.0,36,,,,86,1988-05-15 -11392,454,117,20,17.0,7,4.0,4,3.0,77,,,,11,1988-05-15 -11393,454,155,24,3.0,10,5.0,5,2.0,77,,,,11,1988-05-15 -11394,454,118,2,6.0,8,6.0,6,1.0,77,,,,11,1988-05-15 -11395,454,113,32,29.0,21,7.0,7,0.0,77,,,,11,1988-05-15 -11396,454,122,21,20.0,16,8.0,8,0.0,76,,,,12,1988-05-15 -11397,454,77,43,21.0,25,9.0,9,0.0,75,,,,13,1988-05-15 -11398,454,104,5,27.0,4,3.0,3,4.0,78,7078306.0,,,1,1988-05-15 -11399,454,121,36,16.0,22,10.0,10,0.0,72,,,,16,1988-05-15 -11400,454,76,5,28.0,3,2.0,2,6.0,78,7057530.0,,,1,1988-05-15 -11401,454,144,21,19.0,6,,15,0.0,38,,,,6,1988-05-15 -11402,454,159,47,9.0,23,,14,0.0,43,,,,6,1988-05-15 -11403,454,94,2,5.0,5,,17,0.0,32,,,,4,1988-05-15 -11404,454,111,32,30.0,13,,12,0.0,50,,,,4,1988-05-15 -11405,454,101,0,12.0,1,,11,0.0,66,,,,20,1988-05-15 -11406,454,126,36,15.0,14,,13,0.0,45,,,,69,1988-05-15 -11407,455,137,31,2.0,6,,19,0.0,27,,,,5,1988-05-29 -11408,455,94,2,5.0,14,,20,0.0,20,,,,5,1988-05-29 -11409,455,145,47,10.0,15,,21,0.0,16,,,,5,1988-05-29 -11410,455,118,2,6.0,17,,22,0.0,16,,,,5,1988-05-29 -11411,455,162,26,25.0,20,,23,0.0,13,,,,3,1988-05-29 -11412,455,132,34,36.0,23,,24,0.0,13,,,,23,1988-05-29 -11413,455,126,36,15.0,16,,25,0.0,10,,,,10,1988-05-29 -11414,455,166,17,23.0,0,,27,0.0,0,,,,81,1988-05-29 -11415,455,77,43,21.0,0,,29,0.0,0,,,,81,1988-05-29 -11416,455,140,24,4.0,0,,30,0.0,0,,,,81,1988-05-29 -11417,455,130,42,33.0,0,,31,0.0,0,,,,96,1988-05-29 -11418,455,109,46,22.0,12,,18,0.0,52,,,,6,1988-05-29 -11419,455,111,32,30.0,13,,26,0.0,0,,,,22,1988-05-29 -11420,455,155,24,3.0,0,,28,0.0,0,,,,81,1988-05-29 -11421,455,136,31,1.0,4,,17,0.0,58,,,,5,1988-05-29 -11422,455,159,47,9.0,18,15.0,15,0.0,61,,,,16,1988-05-29 -11423,455,121,36,16.0,10,16.0,16,0.0,61,,,,16,1988-05-29 -11424,455,101,0,12.0,1,2.0,2,6.0,67,5422841.0,,,1,1988-05-29 -11425,455,76,5,28.0,3,3.0,3,4.0,67,5473051.0,,,1,1988-05-29 -11426,455,104,5,27.0,5,4.0,4,3.0,66,,,,11,1988-05-29 -11427,455,117,20,17.0,9,5.0,5,2.0,66,,,,11,1988-05-29 -11428,455,157,20,18.0,7,6.0,6,1.0,66,,,,11,1988-05-29 -11429,455,144,21,19.0,8,7.0,7,0.0,65,,,,12,1988-05-29 -11430,455,116,0,11.0,2,1.0,1,9.0,67,5415737.0,,,1,1988-05-29 -11431,455,113,32,29.0,22,9.0,9,0.0,64,,,,13,1988-05-29 -11432,455,139,26,26.0,24,10.0,10,0.0,63,,,,14,1988-05-29 -11433,455,158,17,24.0,25,11.0,11,0.0,63,,,,14,1988-05-29 -11434,455,165,38,14.0,19,12.0,12,0.0,63,,,,14,1988-05-29 -11435,455,164,42,32.0,26,13.0,13,0.0,63,,,,14,1988-05-29 -11436,455,98,41,31.0,21,14.0,14,0.0,62,,,,15,1988-05-29 -11437,455,122,21,20.0,11,8.0,8,0.0,64,,,,13,1988-05-29 -11438,456,157,20,18.0,8,,20,0.0,31,,,,37,1988-06-12 -11439,456,94,2,5.0,9,,21,0.0,28,,,,5,1988-06-12 -11440,456,139,26,26.0,25,,22,0.0,24,,,,5,1988-06-12 -11441,456,76,5,28.0,3,,23,0.0,22,,,,10,1988-06-12 -11442,456,144,21,19.0,5,,24,0.0,15,,,,80,1988-06-12 -11443,456,164,42,32.0,24,,25,0.0,8,,,,83,1988-06-12 -11444,456,77,43,21.0,0,,28,0.0,0,,,,81,1988-06-12 -11445,456,166,17,23.0,0,,27,0.0,0,,,,81,1988-06-12 -11446,456,113,32,29.0,0,,29,0.0,0,,,,81,1988-06-12 -11447,456,145,47,10.0,0,,30,0.0,0,,,,81,1988-06-12 -11448,456,132,34,36.0,0,,31,0.0,0,,,,97,1988-06-12 -11449,456,118,2,6.0,11,,19,0.0,32,,,,5,1988-06-12 -11450,456,140,24,4.0,23,,26,0.0,0,,,,4,1988-06-12 -11451,456,162,26,25.0,20,,17,0.0,36,,,,7,1988-06-12 -11452,456,104,5,27.0,4,,18,0.0,33,,,,5,1988-06-12 -11453,456,116,0,11.0,2,2.0,2,6.0,69,5992552.0,,,1,1988-06-12 -11454,456,101,0,12.0,1,1.0,1,9.0,69,5986618.0,,,1,1988-06-12 -11455,456,122,21,20.0,7,3.0,3,4.0,69,6038027.0,,,1,1988-06-12 -11456,456,136,31,1.0,6,4.0,4,3.0,68,,,,11,1988-06-12 -11457,456,121,36,16.0,14,5.0,5,2.0,68,,,,11,1988-06-12 -11458,456,155,24,3.0,19,6.0,6,1.0,67,,,,12,1988-06-12 -11459,456,117,20,17.0,16,7.0,7,0.0,67,,,,12,1988-06-12 -11460,456,98,41,31.0,26,8.0,8,0.0,67,,,,12,1988-06-12 -11461,456,165,38,14.0,10,,16,0.0,41,,,,22,1988-06-12 -11462,456,111,32,30.0,17,10.0,10,0.0,66,,,,10,1988-06-12 -11463,456,137,31,2.0,13,11.0,11,0.0,66,,,,13,1988-06-12 -11464,456,130,42,33.0,15,12.0,12,0.0,66,,,,13,1988-06-12 -11465,456,158,17,24.0,21,13.0,13,0.0,64,,,,15,1988-06-12 -11466,456,159,47,9.0,22,14.0,14,0.0,63,,,,5,1988-06-12 -11467,456,126,36,15.0,18,,15,0.0,54,,,,6,1988-06-12 -11468,456,109,46,22.0,12,9.0,9,0.0,66,,,,60,1988-06-12 -11469,457,94,2,5.0,6,,20,0.0,18,,,,5,1988-06-19 -11470,457,165,38,14.0,11,,21,0.0,15,,,,22,1988-06-19 -11471,457,144,21,19.0,7,,22,0.0,14,,,,22,1988-06-19 -11472,457,157,20,18.0,15,,23,0.0,14,,,,10,1988-06-19 -11473,457,77,43,21.0,26,,24,0.0,7,,,,5,1988-06-19 -11474,457,76,5,28.0,2,,25,0.0,6,,,,29,1988-06-19 -11475,457,137,31,2.0,0,,28,0.0,0,,,,81,1988-06-19 -11476,457,121,36,16.0,0,,27,0.0,0,,,,73,1988-06-19 -11477,457,145,47,10.0,0,,29,0.0,0,,,,81,1988-06-19 -11478,457,159,47,9.0,0,,30,0.0,0,,,,81,1988-06-19 -11479,457,98,41,31.0,0,,31,0.0,0,,,,81,1988-06-19 -11480,457,117,20,17.0,9,,19,0.0,24,,,,20,1988-06-19 -11481,457,139,26,26.0,18,,26,0.0,2,,,,25,1988-06-19 -11482,457,164,42,32.0,23,,18,0.0,26,,,,6,1988-06-19 -11483,457,136,31,1.0,8,,17,0.0,26,,,,20,1988-06-19 -11484,457,118,2,6.0,10,,16,0.0,26,,,,10,1988-06-19 -11485,457,116,0,11.0,4,2.0,2,6.0,63,6934748.0,,,1,1988-06-19 -11486,457,122,21,20.0,5,3.0,3,4.0,62,,,,11,1988-06-19 -11487,457,109,46,22.0,12,4.0,4,3.0,62,,,,11,1988-06-19 -11488,457,155,24,3.0,17,5.0,5,2.0,62,,,,11,1988-06-19 -11489,457,101,0,12.0,1,1.0,1,9.0,63,6896035.0,,,1,1988-06-19 -11490,457,113,32,29.0,24,7.0,7,0.0,61,,,,12,1988-06-19 -11491,457,132,34,36.0,21,8.0,8,0.0,61,,,,12,1988-06-19 -11492,457,93,17,23.0,16,6.0,6,1.0,62,,,,11,1988-06-19 -11493,457,158,17,24.0,25,,10,0.0,54,,,,6,1988-06-19 -11494,457,111,32,30.0,14,,11,0.0,46,,,,86,1988-06-19 -11495,457,130,42,33.0,19,,12,0.0,46,,,,20,1988-06-19 -11496,457,104,5,27.0,3,,13,0.0,45,,,,4,1988-06-19 -11497,457,162,26,25.0,20,,14,0.0,45,,,,25,1988-06-19 -11498,457,126,36,15.0,13,,15,0.0,34,,,,5,1988-06-19 -11499,457,140,24,4.0,22,9.0,9,0.0,59,,,,20,1988-06-19 -11500,458,145,47,10.0,21,,19,0.0,55,,,,6,1988-07-03 -11501,458,94,2,5.0,9,,20,0.0,48,,,,22,1988-07-03 -11502,458,111,32,30.0,18,,21,0.0,46,,,,10,1988-07-03 -11503,458,155,24,3.0,23,,22,0.0,40,,,,5,1988-07-03 -11504,458,118,2,6.0,15,,23,0.0,35,,,,23,1988-07-03 -11505,458,122,21,20.0,5,,24,0.0,28,,,,5,1988-07-03 -11506,458,159,47,9.0,0,,31,0.0,0,,,,96,1988-07-03 -11507,458,117,20,17.0,11,,26,0.0,11,,,,20,1988-07-03 -11508,458,162,26,25.0,0,,27,0.0,0,,,,81,1988-07-03 -11509,458,140,24,4.0,0,,28,0.0,0,,,,81,1988-07-03 -11510,458,139,26,26.0,0,,29,0.0,0,,,,81,1988-07-03 -11511,458,98,41,31.0,0,,30,0.0,0,,,,97,1988-07-03 -11512,458,77,43,21.0,24,,18,0.0,56,,,,86,1988-07-03 -11513,458,165,38,14.0,17,,25,0.0,20,,,,95,1988-07-03 -11514,458,109,46,22.0,12,10.0,10,0.0,78,,,,12,1988-07-03 -11515,458,116,0,11.0,1,1.0,1,9.0,80,5857328.0,,,1,1988-07-03 -11516,458,158,17,24.0,25,,16,0.0,70,,,,62,1988-07-03 -11517,458,164,42,32.0,26,,17,0.0,64,,,,8,1988-07-03 -11518,458,101,0,12.0,2,2.0,2,6.0,80,5889080.0,,,1,1988-07-03 -11519,458,104,5,27.0,4,3.0,3,4.0,80,5923833.0,,,1,1988-07-03 -11520,458,76,5,28.0,3,4.0,4,3.0,79,,,,11,1988-07-03 -11521,458,144,21,19.0,6,6.0,6,1.0,79,,,,11,1988-07-03 -11522,458,137,31,2.0,8,7.0,7,0.0,79,,,,11,1988-07-03 -11523,458,136,31,1.0,7,5.0,5,2.0,79,,,,11,1988-07-03 -11524,458,121,36,16.0,10,9.0,9,0.0,79,,,,11,1988-07-03 -11525,458,157,20,18.0,13,11.0,11,0.0,78,,,,12,1988-07-03 -11526,458,132,34,36.0,14,12.0,12,0.0,78,,,,12,1988-07-03 -11527,458,113,32,29.0,19,13.0,13,0.0,78,,,,12,1988-07-03 -11528,458,130,42,33.0,20,14.0,14,0.0,77,,,,13,1988-07-03 -11529,458,93,17,23.0,22,15.0,15,0.0,77,,,,13,1988-07-03 -11530,458,126,36,15.0,16,8.0,8,0.0,79,,,,11,1988-07-03 -11531,459,121,36,16.0,6,,21,0.0,34,,,,91,1988-07-10 -11532,459,104,5,27.0,2,17.0,17,0.0,62,,,,60,1988-07-10 -11533,459,162,26,25.0,25,18.0,18,0.0,62,,,,13,1988-07-10 -11534,459,77,43,21.0,26,19.0,19,0.0,60,,,,60,1988-07-10 -11535,459,122,21,20.0,12,,20,0.0,38,,,,7,1988-07-10 -11536,459,116,0,11.0,4,,22,0.0,24,,,,64,1988-07-10 -11537,459,139,26,26.0,0,,29,0.0,0,,,,81,1988-07-10 -11538,459,109,46,22.0,14,,24,0.0,9,,,,8,1988-07-10 -11539,459,165,38,14.0,16,,25,0.0,8,,,,41,1988-07-10 -11540,459,158,17,24.0,18,,26,0.0,0,,,,22,1988-07-10 -11541,459,164,42,32.0,0,,27,0.0,0,,,,81,1988-07-10 -11542,459,159,47,9.0,0,,28,0.0,0,,,,81,1988-07-10 -11543,459,155,24,3.0,17,,23,0.0,14,,,,5,1988-07-10 -11544,459,140,24,4.0,24,16.0,16,0.0,63,,,,12,1988-07-10 -11545,459,145,47,10.0,0,,30,0.0,0,,,,81,1988-07-10 -11546,459,111,32,30.0,22,14.0,14,0.0,63,,,,12,1988-07-10 -11547,459,113,32,29.0,23,13.0,13,0.0,63,,,,12,1988-07-10 -11548,459,130,42,33.0,20,12.0,12,0.0,64,,,,11,1988-07-10 -11549,459,132,34,36.0,21,11.0,11,0.0,64,,,,11,1988-07-10 -11550,459,137,31,2.0,10,10.0,10,0.0,64,,,,11,1988-07-10 -11551,459,76,5,28.0,1,9.0,9,0.0,64,,,,11,1988-07-10 -11552,459,118,2,6.0,15,8.0,8,0.0,64,,,,11,1988-07-10 -11553,459,157,20,18.0,13,7.0,7,0.0,64,,,,11,1988-07-10 -11554,459,117,20,17.0,9,6.0,6,1.0,64,,,,11,1988-07-10 -11555,459,136,31,1.0,7,5.0,5,2.0,65,5677202.0,,,1,1988-07-10 -11556,459,126,36,15.0,5,4.0,4,3.0,65,5667745.0,,,1,1988-07-10 -11557,459,144,21,19.0,8,3.0,3,4.0,65,5647581.0,,,1,1988-07-10 -11558,459,94,2,5.0,11,2.0,2,6.0,65,5619711.0,,,1,1988-07-10 -11559,459,101,0,12.0,3,1.0,1,9.0,65,5596367.0,,,1,1988-07-10 -11560,459,93,17,23.0,19,15.0,15,0.0,63,,,,12,1988-07-10 -11561,459,98,41,31.0,0,,31,0.0,0,,,,97,1988-07-10 -11562,460,132,34,36.0,19,15.0,15,0.0,42,,,,12,1988-07-24 -11563,460,116,0,11.0,2,2.0,2,6.0,44,5587797.0,,,1,1988-07-24 -11564,460,101,0,12.0,1,1.0,1,9.0,44,5574188.0,,,1,1988-07-24 -11565,460,98,41,31.0,0,,31,0.0,0,,,,97,1988-07-24 -11566,460,93,17,23.0,0,,30,0.0,0,,,,81,1988-07-24 -11567,460,140,24,4.0,0,,29,0.0,0,,,,81,1988-07-24 -11568,460,139,26,26.0,0,,28,0.0,0,,,,81,1988-07-24 -11569,460,158,17,24.0,0,,27,0.0,0,,,,81,1988-07-24 -11570,460,136,31,1.0,5,,26,0.0,1,,,,20,1988-07-24 -11571,460,111,32,30.0,20,,25,0.0,8,,,,20,1988-07-24 -11572,460,94,2,5.0,11,,23,0.0,16,,,,20,1988-07-24 -11573,460,77,43,21.0,18,,22,0.0,27,,,,5,1988-07-24 -11574,460,118,2,6.0,13,,21,0.0,34,,,,20,1988-07-24 -11575,460,165,38,14.0,16,,20,0.0,38,,,,37,1988-07-24 -11576,460,113,32,29.0,21,19.0,19,0.0,39,,,,8,1988-07-24 -11577,460,144,21,19.0,6,18.0,18,0.0,40,,,,14,1988-07-24 -11578,460,130,42,33.0,25,,24,0.0,15,,,,5,1988-07-24 -11579,460,164,42,32.0,26,16.0,16,0.0,42,,,,12,1988-07-24 -11580,460,162,26,25.0,17,17.0,17,0.0,41,,,,13,1988-07-24 -11581,460,104,5,27.0,4,4.0,4,3.0,44,5675100.0,,,1,1988-07-24 -11582,460,121,36,16.0,7,5.0,5,2.0,44,5683794.0,,,1,1988-07-24 -11583,460,122,21,20.0,9,6.0,6,1.0,43,,,,11,1988-07-24 -11584,460,117,20,17.0,12,7.0,7,0.0,43,,,,11,1988-07-24 -11585,460,126,36,15.0,10,8.0,8,0.0,43,,,,11,1988-07-24 -11586,460,76,5,28.0,3,3.0,3,4.0,44,5626283.0,,,1,1988-07-24 -11587,460,157,20,18.0,15,10.0,10,0.0,43,,,,11,1988-07-24 -11588,460,155,24,3.0,24,11.0,11,0.0,43,,,,11,1988-07-24 -11589,460,145,47,10.0,22,12.0,12,0.0,43,,,,11,1988-07-24 -11590,460,109,46,22.0,14,13.0,13,0.0,42,,,,12,1988-07-24 -11591,460,159,47,9.0,23,14.0,14,0.0,42,,,,12,1988-07-24 -11592,460,137,31,2.0,8,9.0,9,0.0,43,,,,11,1988-07-24 -11593,461,144,21,19.0,5,,20,0.0,24,,,,25,1988-08-07 -11594,461,132,34,36.0,10,,21,0.0,22,,,,5,1988-08-07 -11595,461,139,26,26.0,24,,22,0.0,19,,,,37,1988-08-07 -11596,461,93,17,23.0,16,,23,0.0,8,,,,4,1988-08-07 -11597,461,165,38,14.0,23,,24,0.0,8,,,,4,1988-08-07 -11598,461,121,36,16.0,4,,25,0.0,5,,,,5,1988-08-07 -11599,461,145,47,10.0,0,,28,0.0,0,,,,81,1988-08-07 -11600,461,164,42,32.0,0,,27,0.0,0,,,,81,1988-08-07 -11601,461,140,24,4.0,0,,29,0.0,0,,,,81,1988-08-07 -11602,461,159,47,9.0,0,,30,0.0,0,,,,81,1988-08-07 -11603,461,77,43,21.0,0,,31,0.0,0,,,,97,1988-08-07 -11604,461,109,46,22.0,18,,19,0.0,28,,,,86,1988-08-07 -11605,461,155,24,3.0,21,,26,0.0,3,,,,5,1988-08-07 -11606,461,162,26,25.0,25,,18,0.0,32,,,,5,1988-08-07 -11607,461,104,5,27.0,15,,17,0.0,40,,,,10,1988-08-07 -11608,461,94,2,5.0,2,,15,0.0,60,,,,100,1988-08-07 -11609,461,101,0,12.0,1,1.0,1,9.0,76,7067081.0,,,1,1988-08-07 -11610,461,116,0,11.0,7,2.0,2,6.0,76,7067610.0,,,1,1988-08-07 -11611,461,122,21,20.0,3,3.0,3,4.0,76,7098491.0,,,1,1988-08-07 -11612,461,76,5,28.0,9,4.0,4,3.0,76,7155751.0,,,1,1988-08-07 -11613,461,126,36,15.0,8,5.0,5,2.0,75,,,,11,1988-08-07 -11614,461,118,2,6.0,6,6.0,6,1.0,75,,,,11,1988-08-07 -11615,461,137,31,2.0,19,7.0,7,0.0,73,,,,13,1988-08-07 -11616,461,157,20,18.0,14,,16,0.0,55,,,,23,1988-08-07 -11617,461,113,32,29.0,17,9.0,9,0.0,73,,,,13,1988-08-07 -11618,461,158,17,24.0,11,10.0,10,0.0,72,,,,14,1988-08-07 -11619,461,130,42,33.0,26,11.0,11,0.0,72,,,,14,1988-08-07 -11620,461,111,32,30.0,20,12.0,12,0.0,72,,,,14,1988-08-07 -11621,461,98,41,31.0,22,13.0,13,0.0,71,,,,15,1988-08-07 -11622,461,117,20,17.0,12,,14,0.0,65,,,,23,1988-08-07 -11623,461,136,31,1.0,13,8.0,8,0.0,73,,,,13,1988-08-07 -11624,462,159,47,9.0,24,,20,0.0,25,,,,44,1988-08-28 -11625,462,137,31,2.0,8,,21,0.0,22,,,,5,1988-08-28 -11626,462,77,43,21.0,26,,22,0.0,14,,,,69,1988-08-28 -11627,462,76,5,28.0,3,,23,0.0,11,,,,98,1988-08-28 -11628,462,113,32,29.0,23,,24,0.0,9,,,,5,1988-08-28 -11629,462,109,46,22.0,19,,25,0.0,2,,,,3,1988-08-28 -11630,462,93,17,23.0,0,,28,0.0,0,,,,81,1988-08-28 -11631,462,158,17,24.0,0,,27,0.0,0,,,,81,1988-08-28 -11632,462,130,42,33.0,0,,29,0.0,0,,,,81,1988-08-28 -11633,462,140,24,4.0,0,,30,0.0,0,,,,81,1988-08-28 -11634,462,164,42,32.0,0,,31,0.0,0,,,,97,1988-08-28 -11635,462,126,36,15.0,13,,19,0.0,29,,,,20,1988-08-28 -11636,462,162,26,25.0,17,,26,0.0,2,,,,3,1988-08-28 -11637,462,118,2,6.0,5,,18,0.0,30,,,,5,1988-08-28 -11638,462,104,5,27.0,4,,17,0.0,35,,,,5,1988-08-28 -11639,462,98,41,31.0,22,,16,0.0,36,,,,38,1988-08-28 -11640,462,116,0,11.0,2,2.0,2,6.0,43,5311019.0,,,1,1988-08-28 -11641,462,121,36,16.0,14,3.0,3,4.0,43,5356317.0,,,1,1988-08-28 -11642,462,136,31,1.0,9,4.0,4,3.0,43,5364177.0,,,1,1988-08-28 -11643,462,117,20,17.0,10,5.0,5,2.0,43,5365904.0,,,1,1988-08-28 -11644,462,101,0,12.0,1,1.0,1,9.0,43,5280549.0,,,1,1988-08-28 -11645,462,83,2,5.0,12,7.0,7,0.0,42,,,,11,1988-08-28 -11646,462,132,34,36.0,15,8.0,8,0.0,42,,,,11,1988-08-28 -11647,462,157,20,18.0,11,6.0,6,1.0,42,,,,11,1988-08-28 -11648,462,165,38,14.0,18,10.0,10,0.0,42,,,,11,1988-08-28 -11649,462,139,26,26.0,20,11.0,11,0.0,39,,,,5,1988-08-28 -11650,462,155,24,3.0,21,12.0,12,0.0,39,,,,37,1988-08-28 -11651,462,145,47,10.0,25,13.0,13,0.0,38,,,,6,1988-08-28 -11652,462,122,21,20.0,6,,14,0.0,43,,,,2,1988-08-28 -11653,462,144,21,19.0,7,,15,0.0,43,,,,2,1988-08-28 -11654,462,111,32,30.0,16,9.0,9,0.0,42,,,,11,1988-08-28 -11655,463,159,47,9.0,16,,19,0.0,25,,,,5,1988-09-11 -11656,463,132,34,36.0,21,,20,0.0,24,,,,5,1988-09-11 -11657,463,113,32,29.0,25,,21,0.0,17,,,,21,1988-09-11 -11658,463,93,17,23.0,14,,22,0.0,15,,,,5,1988-09-11 -11659,463,137,31,2.0,12,,23,0.0,14,,,,5,1988-09-11 -11660,463,158,17,24.0,19,,24,0.0,12,,,,6,1988-09-11 -11661,463,164,42,32.0,0,,31,0.0,0,,,,97,1988-09-11 -11662,463,155,24,3.0,0,,27,0.0,0,,,,81,1988-09-11 -11663,463,139,26,26.0,0,,28,0.0,0,,,,81,1988-09-11 -11664,463,98,41,31.0,0,,29,0.0,0,,,,81,1988-09-11 -11665,463,130,42,33.0,0,,30,0.0,0,,,,81,1988-09-11 -11666,463,109,46,22.0,18,,18,0.0,27,,,,83,1988-09-11 -11667,463,136,31,1.0,7,,25,0.0,11,,,,8,1988-09-11 -11668,463,145,47,10.0,15,,17,0.0,28,,,,5,1988-09-11 -11669,463,77,43,21.0,17,,26,0.0,2,,,,5,1988-09-11 -11670,463,111,32,30.0,20,,15,0.0,33,,,,5,1988-09-11 -11671,463,165,38,14.0,23,,16,0.0,31,,,,8,1988-09-11 -11672,463,76,5,28.0,3,1.0,1,9.0,51,4659744.0,,,1,1988-09-11 -11673,463,104,5,27.0,4,2.0,2,6.0,51,4660246.0,,,1,1988-09-11 -11674,463,117,20,17.0,6,4.0,4,3.0,51,4695858.0,,,1,1988-09-11 -11675,463,121,36,16.0,11,5.0,5,2.0,51,4712266.0,,,1,1988-09-11 -11676,463,122,21,20.0,8,6.0,6,1.0,51,4719622.0,,,1,1988-09-11 -11677,463,118,2,6.0,10,7.0,7,0.0,51,4734487.0,,,1,1988-09-11 -11678,463,157,20,18.0,5,3.0,3,4.0,51,4695276.0,,,1,1988-09-11 -11679,463,144,21,19.0,9,9.0,9,0.0,50,,,,11,1988-09-11 -11680,463,101,0,12.0,1,10.0,10,0.0,49,,,,4,1988-09-11 -11681,463,167,2,5.0,22,11.0,11,0.0,49,,,,12,1988-09-11 -11682,463,140,24,4.0,26,12.0,12,0.0,49,,,,12,1988-09-11 -11683,463,162,26,25.0,24,13.0,13,0.0,49,,,,12,1988-09-11 -11684,463,126,36,15.0,13,8.0,8,0.0,51,4752310.0,,,1,1988-09-11 -11685,463,116,0,11.0,2,,14,0.0,34,,,,5,1988-09-11 -11686,464,118,2,6.0,11,,19,0.0,29,,,,21,1988-09-25 -11687,464,93,17,23.0,14,,20,0.0,27,,,,5,1988-09-25 -11688,464,113,32,29.0,15,,21,0.0,20,,,,91,1988-09-25 -11689,464,137,31,2.0,16,,22,0.0,16,,,,20,1988-09-25 -11690,464,109,46,22.0,12,,23,0.0,11,,,,86,1988-09-25 -11691,464,140,24,4.0,0,,27,0.0,0,,,,81,1988-09-25 -11692,464,111,32,30.0,20,,25,0.0,7,,,,5,1988-09-25 -11693,464,136,31,1.0,8,,18,0.0,34,,,,8,1988-09-25 -11694,464,159,47,9.0,0,,28,0.0,0,,,,81,1988-09-25 -11695,464,130,42,33.0,0,,29,0.0,0,,,,81,1988-09-25 -11696,464,164,42,32.0,0,,31,0.0,0,,,,97,1988-09-25 -11697,464,157,20,18.0,18,,24,0.0,10,,,,101,1988-09-25 -11698,464,76,5,28.0,4,,17,0.0,35,,,,20,1988-09-25 -11699,464,145,47,10.0,0,,30,0.0,0,,,,81,1988-09-25 -11700,464,155,24,3.0,22,,15,0.0,53,,,,25,1988-09-25 -11701,464,144,21,19.0,9,,16,0.0,52,,,,64,1988-09-25 -11702,464,116,0,11.0,1,1.0,1,9.0,70,5860958.0,,,1,1988-09-25 -11703,464,121,36,16.0,3,2.0,2,6.0,70,5870511.0,,,1,1988-09-25 -11704,464,122,21,20.0,13,3.0,3,4.0,70,5905577.0,,,1,1988-09-25 -11705,464,117,20,17.0,10,4.0,4,3.0,70,5928377.0,,,1,1988-09-25 -11706,464,104,5,27.0,7,5.0,5,2.0,70,5932842.0,,,1,1988-09-25 -11707,464,101,0,12.0,2,6.0,6,1.0,70,5939227.0,,,1,1988-09-25 -11708,464,139,26,26.0,24,,26,0.0,4,,,,5,1988-09-25 -11709,464,158,17,24.0,19,8.0,8,0.0,68,,,,12,1988-09-25 -11710,464,165,38,14.0,21,9.0,9,0.0,68,,,,12,1988-09-25 -11711,464,162,26,25.0,23,10.0,10,0.0,68,,,,12,1988-09-25 -11712,464,98,41,31.0,26,11.0,11,0.0,65,,,,15,1988-09-25 -11713,464,77,43,21.0,25,12.0,12,0.0,63,,,,17,1988-09-25 -11714,464,126,36,15.0,5,,13,0.0,59,,,,5,1988-09-25 -11715,464,132,34,36.0,17,7.0,7,0.0,69,,,,11,1988-09-25 -11716,464,94,2,5.0,6,,14,0.0,54,,,,20,1988-09-25 -11717,465,165,38,14.0,13,,20,0.0,16,,,,5,1988-10-02 -11718,465,104,5,27.0,10,,21,0.0,15,,,,5,1988-10-02 -11719,465,93,17,23.0,20,,22,0.0,15,,,,6,1988-10-02 -11720,465,137,31,2.0,15,,23,0.0,14,,,,20,1988-10-02 -11721,465,77,43,21.0,14,,24,0.0,9,,,,22,1988-10-02 -11722,465,145,47,10.0,0,,27,0.0,0,,,,81,1988-10-02 -11723,465,162,26,25.0,19,,26,0.0,0,,,,37,1988-10-02 -11724,465,109,46,22.0,23,,19,0.0,37,,,,5,1988-10-02 -11725,465,164,42,32.0,0,,28,0.0,0,,,,81,1988-10-02 -11726,465,140,24,4.0,0,,29,0.0,0,,,,81,1988-10-02 -11727,465,159,47,9.0,0,,30,0.0,0,,,,81,1988-10-02 -11728,465,98,41,31.0,0,,31,0.0,0,,,,97,1988-10-02 -11729,465,155,24,3.0,22,,25,0.0,4,,,,83,1988-10-02 -11730,465,117,20,17.0,17,,18,0.0,41,,,,83,1988-10-02 -11731,465,111,32,30.0,12,14.0,14,0.0,69,,,,13,1988-10-02 -11732,465,157,20,18.0,25,,16,0.0,60,,,,83,1988-10-02 -11733,465,116,0,11.0,2,1.0,1,9.0,72,6523851.0,,,1,1988-10-02 -11734,465,94,2,5.0,3,2.0,2,6.0,72,6550083.0,,,1,1988-10-02 -11735,465,144,21,19.0,5,3.0,3,4.0,72,6559297.0,,,1,1988-10-02 -11736,465,101,0,12.0,1,4.0,4,3.0,72,6570561.0,,,1,1988-10-02 -11737,465,118,2,6.0,7,5.0,5,2.0,72,6571281.0,,,1,1988-10-02 -11738,465,121,36,16.0,6,,17,0.0,45,,,,5,1988-10-02 -11739,465,76,5,28.0,8,6.0,6,1.0,72,6575664.0,,,1,1988-10-02 -11740,465,136,31,1.0,9,8.0,8,0.0,72,6601160.0,,,1,1988-10-02 -11741,465,122,21,20.0,4,9.0,9,0.0,72,6601506.0,,,1,1988-10-02 -11742,465,113,32,29.0,16,11.0,11,0.0,71,,,,11,1988-10-02 -11743,465,158,17,24.0,24,12.0,12,0.0,70,,,,12,1988-10-02 -11744,465,130,42,33.0,26,13.0,13,0.0,70,,,,12,1988-10-02 -11745,465,139,26,26.0,21,,15,0.0,62,,,,36,1988-10-02 -11746,465,126,36,15.0,11,7.0,7,0.0,72,6599815.0,,,1,1988-10-02 -11747,465,132,34,36.0,18,10.0,10,0.0,71,,,,11,1988-10-02 -11748,466,98,41,31.0,0,,31,0.0,0,,,,97,1988-10-30 -11749,466,130,42,33.0,0,,30,0.0,0,,,,81,1988-10-30 -11750,466,101,0,12.0,1,1.0,1,9.0,51,5606173.0,,,1,1988-10-30 -11751,466,164,42,32.0,0,,28,0.0,0,,,,81,1988-10-30 -11752,466,139,26,26.0,0,,27,0.0,0,,,,81,1988-10-30 -11753,466,145,47,10.0,25,,26,0.0,14,,,,100,1988-10-30 -11754,466,117,20,17.0,7,,25,0.0,16,,,,20,1988-10-30 -11755,466,121,36,16.0,4,,24,0.0,19,,,,10,1988-10-30 -11756,466,132,34,36.0,21,,23,0.0,22,,,,20,1988-10-30 -11757,466,94,2,5.0,8,,22,0.0,24,,,,4,1988-10-30 -11758,466,136,31,1.0,5,,21,0.0,34,,,,100,1988-10-30 -11759,466,77,43,21.0,24,,20,0.0,34,,,,23,1988-10-30 -11760,466,157,20,18.0,15,,19,0.0,35,,,,80,1988-10-30 -11761,466,109,46,22.0,14,,18,0.0,36,,,,25,1988-10-30 -11762,466,162,26,25.0,23,17.0,17,0.0,48,,,,13,1988-10-30 -11763,466,87,32,29.0,20,16.0,16,0.0,48,,,,13,1988-10-30 -11764,466,159,47,9.0,0,,29,0.0,0,,,,81,1988-10-30 -11765,466,140,24,4.0,26,14.0,14,0.0,49,,,,12,1988-10-30 -11766,466,158,17,24.0,22,15.0,15,0.0,49,,,,12,1988-10-30 -11767,466,116,0,11.0,2,2.0,2,6.0,51,5619536.0,,,1,1988-10-30 -11768,466,122,21,20.0,10,3.0,3,4.0,51,5642282.0,,,1,1988-10-30 -11769,466,76,5,28.0,3,4.0,4,3.0,51,5692887.0,,,1,1988-10-30 -11770,466,118,2,6.0,11,6.0,6,1.0,51,5703788.0,,,1,1988-10-30 -11771,466,137,31,2.0,6,7.0,7,0.0,50,,,,11,1988-10-30 -11772,466,144,21,19.0,12,5.0,5,2.0,51,5696776.0,,,1,1988-10-30 -11773,466,111,32,30.0,19,9.0,9,0.0,50,,,,11,1988-10-30 -11774,466,126,36,15.0,13,10.0,10,0.0,50,,,,11,1988-10-30 -11775,466,104,5,27.0,9,11.0,11,0.0,50,,,,11,1988-10-30 -11776,466,155,24,3.0,16,12.0,12,0.0,50,,,,11,1988-10-30 -11777,466,93,17,23.0,17,13.0,13,0.0,49,,,,12,1988-10-30 -11778,466,165,38,14.0,18,8.0,8,0.0,50,,,,11,1988-10-30 -11779,467,164,42,32.0,25,,25,0.0,12,,,,86,1988-11-13 -11780,467,132,34,36.0,11,,21,0.0,32,,,,8,1988-11-13 -11781,467,76,5,28.0,4,,22,0.0,25,,,,4,1988-11-13 -11782,467,162,26,25.0,23,,23,0.0,24,,,,4,1988-11-13 -11783,467,155,24,3.0,17,,24,0.0,16,,,,7,1988-11-13 -11784,467,104,5,27.0,12,,26,0.0,0,,,,4,1988-11-13 -11785,467,116,0,11.0,2,1.0,1,9.0,82,6794676.0,,,1,1988-11-13 -11786,467,140,24,4.0,0,,28,0.0,0,,,,81,1988-11-13 -11787,467,161,32,29.0,0,,29,0.0,0,,,,81,1988-11-13 -11788,467,145,47,10.0,0,,30,0.0,0,,,,81,1988-11-13 -11789,467,77,43,21.0,0,,31,0.0,0,,,,97,1988-11-13 -11790,467,137,31,2.0,13,,19,0.0,45,,,,4,1988-11-13 -11791,467,98,41,31.0,0,,27,0.0,0,,,,81,1988-11-13 -11792,467,126,36,15.0,19,,18,0.0,46,,,,4,1988-11-13 -11793,467,158,17,24.0,21,,20,0.0,41,,,,5,1988-11-13 -11794,467,117,20,17.0,7,,16,0.0,52,,,,5,1988-11-13 -11795,467,157,20,18.0,18,,17,0.0,51,,,,5,1988-11-13 -11796,467,101,0,12.0,1,2.0,2,6.0,82,6831063.0,,,1,1988-11-13 -11797,467,136,31,1.0,5,3.0,3,4.0,82,6842222.0,,,1,1988-11-13 -11798,467,118,2,6.0,6,4.0,4,3.0,82,6874764.0,,,1,1988-11-13 -11799,467,122,21,20.0,10,5.0,5,2.0,81,,,,11,1988-11-13 -11800,467,93,17,23.0,14,7.0,7,0.0,80,,,,12,1988-11-13 -11801,467,109,46,22.0,15,8.0,8,0.0,77,,,,60,1988-11-13 -11802,467,121,36,16.0,9,6.0,6,1.0,81,,,,11,1988-11-13 -11803,467,111,32,30.0,24,10.0,10,0.0,75,,,,60,1988-11-13 -11804,467,165,38,14.0,16,11.0,11,0.0,73,,,,10,1988-11-13 -11805,467,159,47,9.0,26,,12,0.0,69,,,,69,1988-11-13 -11806,467,94,2,5.0,3,,13,0.0,65,,,,20,1988-11-13 -11807,467,144,21,19.0,8,,14,0.0,63,,,,20,1988-11-13 -11808,467,130,42,33.0,20,,15,0.0,63,,,,86,1988-11-13 -11809,467,139,26,26.0,22,9.0,9,0.0,76,,,,60,1988-11-13 -11810,468,147,42,33.0,0,,29,0.0,0,,,,81,1989-03-26 -11811,468,122,2,5.0,4,,23,0.0,3,,,,5,1989-03-26 -11812,468,93,17,23.0,16,,24,0.0,2,,,,83,1989-03-26 -11813,468,76,5,28.0,3,,25,0.0,0,,,,4,1989-03-26 -11814,468,158,17,24.0,23,,26,0.0,0,,,,4,1989-03-26 -11815,468,113,32,29.0,0,,27,0.0,0,,,,81,1989-03-26 -11816,468,162,26,25.0,0,,28,0.0,0,,,,81,1989-03-26 -11817,468,89,41,31.0,0,,30,0.0,0,,,,81,1989-03-26 -11818,468,91,44,37.0,0,,38,0.0,0,,,,97,1989-03-26 -11819,468,159,43,18.0,0,,32,0.0,0,,,,97,1989-03-26 -11820,468,160,46,39.0,0,,33,0.0,0,,,,97,1989-03-26 -11821,468,161,41,32.0,0,,34,0.0,0,,,,97,1989-03-26 -11822,468,163,38,41.0,0,,35,0.0,0,,,,97,1989-03-26 -11823,468,87,47,35.0,0,,36,0.0,0,,,,97,1989-03-26 -11824,468,139,44,36.0,0,,37,0.0,0,,,,97,1989-03-26 -11825,468,130,33,8.0,14,,22,0.0,9,,,,86,1989-03-26 -11826,468,132,34,21.0,0,,31,0.0,0,,,,97,1989-03-26 -11827,468,77,43,17.0,19,,21,0.0,10,,,,2,1989-03-26 -11828,468,155,24,3.0,18,7.0,7,0.0,60,,,,11,1989-03-26 -11829,468,121,36,16.0,7,,19,0.0,22,,,,22,1989-03-26 -11830,468,94,5,27.0,6,1.0,1,9.0,61,5938744.0,,,1,1989-03-26 -11831,468,136,31,11.0,9,,20,0.0,10,,,,69,1989-03-26 -11832,468,126,36,15.0,12,3.0,3,4.0,61,5948114.0,,,1,1989-03-26 -11833,468,64,21,20.0,10,4.0,4,3.0,61,5949237.0,,,1,1989-03-26 -11834,468,117,20,9.0,8,5.0,5,2.0,61,5956610.0,,,1,1989-03-26 -11835,468,144,21,19.0,11,6.0,6,1.0,61,5956985.0,,,1,1989-03-26 -11836,468,137,31,12.0,21,8.0,8,0.0,60,,,,11,1989-03-26 -11837,468,128,26,26.0,22,9.0,9,0.0,60,,,,11,1989-03-26 -11838,468,116,0,2.0,5,2.0,2,6.0,61,5946553.0,,,1,1989-03-26 -11839,468,101,0,1.0,1,11.0,11,0.0,59,,,,12,1989-03-26 -11840,468,111,32,30.0,26,12.0,12,0.0,58,,,,13,1989-03-26 -11841,468,109,34,22.0,15,13.0,13,0.0,57,,,,14,1989-03-26 -11842,468,156,46,38.0,17,14.0,14,0.0,56,,,,15,1989-03-26 -11843,468,118,2,6.0,2,15.0,15,0.0,51,,,,91,1989-03-26 -11844,468,157,20,10.0,24,,16,0.0,37,,,,4,1989-03-26 -11845,468,145,47,34.0,25,,17,0.0,36,,,,4,1989-03-26 -11846,468,83,33,7.0,13,,18,0.0,27,,,,86,1989-03-26 -11847,468,104,24,4.0,20,10.0,10,0.0,59,,,,12,1989-03-26 -11848,469,76,5,28.0,5,,23,0.0,3,,,,3,1989-04-23 -11849,469,121,36,16.0,13,,24,0.0,1,,,,20,1989-04-23 -11850,469,111,32,30.0,20,,25,0.0,0,,,,10,1989-04-23 -11851,469,113,32,29.0,26,,26,0.0,0,,,,10,1989-04-23 -11852,469,104,24,4.0,0,,27,0.0,0,,,,81,1989-04-23 -11853,469,162,26,25.0,0,,28,0.0,0,,,,81,1989-04-23 -11854,469,156,46,38.0,0,,29,0.0,0,,,,81,1989-04-23 -11855,469,163,38,41.0,0,,35,0.0,0,,,,97,1989-04-23 -11856,469,147,42,33.0,0,,32,0.0,0,,,,97,1989-04-23 -11857,469,159,43,18.0,0,,33,0.0,0,,,,97,1989-04-23 -11858,469,139,44,36.0,0,,34,0.0,0,,,,97,1989-04-23 -11859,469,161,41,32.0,0,,36,0.0,0,,,,97,1989-04-23 -11860,469,87,47,35.0,0,,37,0.0,0,,,,97,1989-04-23 -11861,469,160,46,39.0,0,,39,0.0,0,,,,97,1989-04-23 -11862,469,128,26,26.0,10,,22,0.0,4,,,,2,1989-04-23 -11863,469,91,44,37.0,0,,31,0.0,0,,,,97,1989-04-23 -11864,469,93,17,23.0,11,,21,0.0,6,,,,6,1989-04-23 -11865,469,145,47,34.0,0,,38,0.0,0,,,,97,1989-04-23 -11866,469,118,2,6.0,4,,19,0.0,21,,,,5,1989-04-23 -11867,469,101,0,1.0,1,1.0,1,9.0,58,5211245.0,,,1,1989-04-23 -11868,469,130,33,8.0,17,,20,0.0,19,,,,20,1989-04-23 -11869,469,116,0,2.0,2,2.0,2,6.0,58,5251470.0,,,1,1989-04-23 -11870,469,144,21,19.0,7,3.0,3,4.0,57,,,,11,1989-04-23 -11871,469,122,2,5.0,6,4.0,4,3.0,57,,,,11,1989-04-23 -11872,469,117,20,9.0,12,5.0,5,2.0,57,,,,11,1989-04-23 -11873,469,155,24,3.0,25,6.0,6,1.0,57,,,,11,1989-04-23 -11874,469,132,34,21.0,9,7.0,7,0.0,57,,,,11,1989-04-23 -11875,469,98,38,40.0,18,8.0,8,0.0,57,,,,11,1989-04-23 -11876,469,157,20,10.0,21,9.0,9,0.0,56,,,,12,1989-04-23 -11877,469,89,41,31.0,0,,30,0.0,0,,,,81,1989-04-23 -11878,469,136,31,11.0,8,,17,0.0,29,,,,5,1989-04-23 -11879,469,64,21,20.0,23,11.0,11,0.0,56,,,,12,1989-04-23 -11880,469,77,43,17.0,14,12.0,12,0.0,52,,,,20,1989-04-23 -11881,469,83,33,7.0,22,,13,0.0,51,,,,69,1989-04-23 -11882,469,137,31,12.0,24,,14,0.0,46,,,,62,1989-04-23 -11883,469,158,17,24.0,15,,15,0.0,43,,,,20,1989-04-23 -11884,469,126,36,15.0,19,,16,0.0,39,,,,7,1989-04-23 -11885,469,109,34,22.0,16,10.0,10,0.0,56,,,,12,1989-04-23 -11886,469,94,5,27.0,3,,18,0.0,23,,,,6,1989-04-23 -11887,470,161,41,32.0,18,,23,0.0,19,,,,6,1989-05-07 -11888,470,128,26,26.0,16,,24,0.0,4,,,,6,1989-05-07 -11889,470,93,17,23.0,11,,25,0.0,3,,,,8,1989-05-07 -11890,470,156,46,38.0,0,,27,0.0,0,,,,81,1989-05-07 -11891,470,113,32,29.0,0,,28,0.0,0,,,,81,1989-05-07 -11892,470,137,31,12.0,0,,29,0.0,0,,,,81,1989-05-07 -11893,470,159,43,18.0,0,,30,0.0,0,,,,97,1989-05-07 -11894,470,147,42,33.0,0,,35,0.0,0,,,,97,1989-05-07 -11895,470,77,43,17.0,0,,32,0.0,0,,,,97,1989-05-07 -11896,470,145,47,34.0,0,,33,0.0,0,,,,97,1989-05-07 -11897,470,91,44,37.0,0,,34,0.0,0,,,,97,1989-05-07 -11898,470,94,5,27.0,5,,22,0.0,30,,,,6,1989-05-07 -11899,470,160,46,39.0,0,,36,0.0,0,,,,97,1989-05-07 -11900,470,87,47,35.0,0,,37,0.0,0,,,,97,1989-05-07 -11901,470,163,38,41.0,0,,38,0.0,0,,,,97,1989-05-07 -11902,470,139,44,36.0,0,,31,0.0,0,,,,97,1989-05-07 -11903,470,136,31,11.0,19,,21,0.0,32,,,,4,1989-05-07 -11904,470,117,20,9.0,6,,26,0.0,2,,,,10,1989-05-07 -11905,470,111,32,30.0,17,,19,0.0,38,,,,5,1989-05-07 -11906,470,101,0,1.0,1,1.0,1,9.0,77,6813251.0,,,1,1989-05-07 -11907,470,116,0,2.0,2,2.0,2,6.0,77,6865780.0,,,1,1989-05-07 -11908,470,130,33,8.0,8,3.0,3,4.0,76,,,,11,1989-05-07 -11909,470,132,34,21.0,9,4.0,4,3.0,75,,,,12,1989-05-07 -11910,470,104,24,4.0,12,5.0,5,2.0,75,,,,12,1989-05-07 -11911,470,83,33,7.0,4,6.0,6,1.0,75,,,,12,1989-05-07 -11912,470,144,21,19.0,15,8.0,8,0.0,74,,,,13,1989-05-07 -11913,470,155,24,3.0,23,9.0,9,0.0,74,,,,13,1989-05-07 -11914,470,122,2,5.0,3,10.0,10,0.0,74,,,,13,1989-05-07 -11915,470,157,20,10.0,20,7.0,7,0.0,75,,,,12,1989-05-07 -11916,470,162,26,25.0,21,12.0,12,0.0,73,,,,14,1989-05-07 -11917,470,109,34,22.0,10,13.0,13,0.0,73,,,,14,1989-05-07 -11918,470,64,21,20.0,24,14.0,14,0.0,73,,,,14,1989-05-07 -11919,470,118,2,6.0,7,15.0,15,0.0,73,,,,14,1989-05-07 -11920,470,158,17,24.0,26,,16,0.0,48,,,,25,1989-05-07 -11921,470,98,38,40.0,13,,17,0.0,46,,,,10,1989-05-07 -11922,470,89,41,31.0,25,,18,0.0,44,,,,6,1989-05-07 -11923,470,121,36,16.0,22,11.0,11,0.0,73,,,,14,1989-05-07 -11924,470,126,36,15.0,14,,20,0.0,36,,,,5,1989-05-07 -11925,471,89,41,31.0,0,,30,0.0,0,,,,81,1989-05-28 -11926,471,122,2,5.0,8,,24,0.0,15,,,,10,1989-05-28 -11927,471,155,24,3.0,14,,25,0.0,9,,,,37,1989-05-28 -11928,471,121,36,16.0,4,,26,0.0,1,,,,7,1989-05-28 -11929,471,158,17,24.0,0,,27,0.0,0,,,,81,1989-05-28 -11930,471,126,36,15.0,0,,28,0.0,0,,,,81,1989-05-28 -11931,471,113,32,29.0,0,,29,0.0,0,,,,81,1989-05-28 -11932,471,94,5,27.0,3,,17,0.0,43,,,,6,1989-05-28 -11933,471,147,42,33.0,0,,32,0.0,0,,,,97,1989-05-28 -11934,471,77,43,17.0,0,,33,0.0,0,,,,97,1989-05-28 -11935,471,160,46,39.0,0,,34,0.0,0,,,,97,1989-05-28 -11936,471,145,47,34.0,0,,35,0.0,0,,,,97,1989-05-28 -11937,471,87,47,35.0,0,,36,0.0,0,,,,97,1989-05-28 -11938,471,159,43,18.0,0,,37,0.0,0,,,,97,1989-05-28 -11939,471,163,38,41.0,0,,38,0.0,0,,,,97,1989-05-28 -11940,471,161,41,32.0,0,,39,0.0,0,,,,97,1989-05-28 -11941,471,139,44,36.0,21,,23,0.0,16,,,,7,1989-05-28 -11942,471,91,44,37.0,0,,31,0.0,0,,,,97,1989-05-28 -11943,471,76,5,28.0,6,,22,0.0,16,,,,6,1989-05-28 -11944,471,136,31,11.0,26,11.0,11,0.0,68,,,,11,1989-05-28 -11945,471,111,32,30.0,16,,20,0.0,28,,,,62,1989-05-28 -11946,471,109,34,22.0,12,,21,0.0,20,,,,22,1989-05-28 -11947,471,118,2,6.0,5,2.0,2,6.0,69,5736991.0,,,1,1989-05-28 -11948,471,104,24,4.0,7,3.0,3,4.0,69,5752685.0,,,1,1989-05-28 -11949,471,144,21,19.0,13,4.0,4,3.0,69,5766926.0,,,1,1989-05-28 -11950,471,116,0,2.0,2,5.0,5,2.0,69,5777544.0,,,1,1989-05-28 -11951,471,101,0,1.0,1,1.0,1,9.0,69,5721431.0,,,1,1989-05-28 -11952,471,157,20,10.0,24,7.0,7,0.0,68,,,,11,1989-05-28 -11953,471,128,26,26.0,11,8.0,8,0.0,68,,,,11,1989-05-28 -11954,471,98,38,40.0,17,6.0,6,1.0,68,,,,11,1989-05-28 -11955,471,130,33,8.0,9,10.0,10,0.0,68,,,,11,1989-05-28 -11956,471,156,46,38.0,23,12.0,12,0.0,67,,,,12,1989-05-28 -11957,471,132,34,21.0,19,13.0,13,0.0,67,,,,12,1989-05-28 -11958,471,162,26,25.0,25,14.0,14,0.0,66,,,,13,1989-05-28 -11959,471,64,21,20.0,18,15.0,15,0.0,66,,,,13,1989-05-28 -11960,471,93,17,23.0,22,,16,0.0,53,,,,5,1989-05-28 -11961,471,117,20,9.0,10,,18,0.0,35,,,,10,1989-05-28 -11962,471,137,31,12.0,15,,19,0.0,35,,,,20,1989-05-28 -11963,471,83,33,7.0,20,9.0,9,0.0,68,,,,11,1989-05-28 -11964,472,104,24,4.0,9,,23,0.0,17,,,,6,1989-06-04 -11965,472,144,21,19.0,3,,24,0.0,10,,,,68,1989-06-04 -11966,472,117,20,9.0,10,,25,0.0,7,,,,4,1989-06-04 -11967,472,111,32,30.0,12,,26,0.0,3,,,,20,1989-06-04 -11968,472,128,26,26.0,0,,27,0.0,0,,,,81,1989-06-04 -11969,472,162,26,25.0,0,,29,0.0,0,,,,81,1989-06-04 -11970,472,145,47,34.0,0,,38,0.0,0,,,,97,1989-06-04 -11971,472,159,43,18.0,0,,31,0.0,0,,,,97,1989-06-04 -11972,472,161,41,32.0,0,,32,0.0,0,,,,97,1989-06-04 -11973,472,147,42,33.0,0,,33,0.0,0,,,,97,1989-06-04 -11974,472,77,43,17.0,0,,34,0.0,0,,,,97,1989-06-04 -11975,472,163,38,41.0,0,,35,0.0,0,,,,97,1989-06-04 -11976,472,160,46,39.0,0,,36,0.0,0,,,,97,1989-06-04 -11977,472,87,47,35.0,0,,37,0.0,0,,,,97,1989-06-04 -11978,472,126,36,15.0,18,,22,0.0,20,,,,23,1989-06-04 -11979,472,113,32,29.0,0,,30,0.0,0,,,,81,1989-06-04 -11980,472,121,36,16.0,11,,21,0.0,22,,,,7,1989-06-04 -11981,472,136,31,11.0,22,,12,0.0,52,,,,20,1989-06-04 -11982,472,93,17,23.0,15,,19,0.0,26,,,,5,1989-06-04 -11983,472,116,0,2.0,2,1.0,1,9.0,75,7293133.0,,,1,1989-06-04 -11984,472,118,2,6.0,14,2.0,2,6.0,75,7332829.0,,,1,1989-06-04 -11985,472,157,20,10.0,17,3.0,3,4.0,75,7336343.0,,,1,1989-06-04 -11986,472,156,46,38.0,26,4.0,4,3.0,74,,,,11,1989-06-04 -11987,472,64,21,20.0,25,5.0,5,2.0,74,,,,11,1989-06-04 -11988,472,122,2,5.0,16,6.0,6,1.0,74,,,,11,1989-06-04 -11989,472,98,38,40.0,24,7.0,7,0.0,73,,,,5,1989-06-04 -11990,472,109,34,22.0,13,8.0,8,0.0,70,,,,15,1989-06-04 -11991,472,155,24,3.0,21,9.0,9,0.0,69,,,,69,1989-06-04 -11992,472,76,5,28.0,8,,10,0.0,61,,,,91,1989-06-04 -11993,472,132,34,21.0,6,,11,0.0,52,,,,4,1989-06-04 -11994,472,139,44,36.0,19,,13,0.0,50,,,,22,1989-06-04 -11995,472,158,17,24.0,20,,14,0.0,46,,,,5,1989-06-04 -11996,472,101,0,1.0,1,,15,0.0,44,,,,10,1989-06-04 -11997,472,83,33,7.0,5,,16,0.0,43,,,,23,1989-06-04 -11998,472,130,33,8.0,7,,17,0.0,37,,,,23,1989-06-04 -11999,472,94,5,27.0,4,,18,0.0,31,,,,91,1989-06-04 -12000,472,137,31,12.0,23,,20,0.0,24,,,,37,1989-06-04 -12001,472,91,44,37.0,0,,39,0.0,0,,,,97,1989-06-04 -12002,472,89,41,31.0,0,,28,0.0,0,,,,81,1989-06-04 -12003,473,64,21,20.0,0,,29,0.0,0,,,,81,1989-06-18 -12004,473,94,5,27.0,5,,22,0.0,0,,,,2,1989-06-18 -12005,473,93,17,23.0,11,,24,0.0,0,,,,3,1989-06-18 -12006,473,144,21,19.0,13,,25,0.0,0,,,,2,1989-06-18 -12007,473,104,24,4.0,20,,26,0.0,0,,,,10,1989-06-18 -12008,473,137,31,12.0,0,,27,0.0,0,,,,81,1989-06-18 -12009,473,113,32,29.0,0,,28,0.0,0,,,,81,1989-06-18 -12010,473,128,26,26.0,0,,30,0.0,0,,,,81,1989-06-18 -12011,473,116,0,2.0,1,,21,0.0,2,,,,22,1989-06-18 -12012,473,83,33,7.0,0,,31,0.0,0,,,,97,1989-06-18 -12013,473,147,42,33.0,0,,33,0.0,0,,,,97,1989-06-18 -12014,473,159,43,18.0,0,,34,0.0,0,,,,97,1989-06-18 -12015,473,145,47,34.0,0,,35,0.0,0,,,,97,1989-06-18 -12016,473,163,38,41.0,0,,36,0.0,0,,,,97,1989-06-18 -12017,473,160,46,39.0,0,,37,0.0,0,,,,97,1989-06-18 -12018,473,87,47,35.0,0,,38,0.0,0,,,,97,1989-06-18 -12019,473,161,41,32.0,0,,39,0.0,0,,,,97,1989-06-18 -12020,473,91,44,37.0,0,,32,0.0,0,,,,97,1989-06-18 -12021,473,157,20,10.0,16,,20,0.0,3,,,,20,1989-06-18 -12022,473,130,33,8.0,7,,23,0.0,0,,,,3,1989-06-18 -12023,473,76,5,28.0,4,,18,0.0,6,,,,6,1989-06-18 -12024,473,122,2,5.0,6,1.0,1,9.0,69,7284073.0,,,1,1989-06-18 -12025,473,118,2,6.0,3,2.0,2,6.0,69,7314080.0,,,1,1989-06-18 -12026,473,109,34,22.0,9,3.0,3,4.0,69,7380722.0,,,1,1989-06-18 -12027,473,136,31,11.0,19,4.0,4,3.0,69,7385557.0,,,1,1989-06-18 -12028,473,162,26,25.0,22,5.0,5,2.0,68,,,,11,1989-06-18 -12029,473,132,34,21.0,8,6.0,6,1.0,67,,,,12,1989-06-18 -12030,473,98,38,40.0,25,,19,0.0,6,,,,20,1989-06-18 -12031,473,156,46,38.0,23,8.0,8,0.0,66,,,,13,1989-06-18 -12032,473,89,41,31.0,26,,9,0.0,57,,,,24,1989-06-18 -12033,473,101,0,1.0,2,7.0,7,0.0,66,,,,5,1989-06-18 -12034,473,155,24,3.0,14,,11,0.0,35,,,,20,1989-06-18 -12035,473,77,43,17.0,15,,12,0.0,33,,,,10,1989-06-18 -12036,473,121,36,16.0,21,,13,0.0,28,,,,20,1989-06-18 -12037,473,111,32,30.0,10,,14,0.0,26,,,,20,1989-06-18 -12038,473,139,44,36.0,18,,15,0.0,13,,,,2,1989-06-18 -12039,473,158,17,24.0,24,,16,0.0,11,,,,20,1989-06-18 -12040,473,117,20,9.0,12,,10,0.0,40,,,,5,1989-06-18 -12041,473,126,36,15.0,17,,17,0.0,11,,,,10,1989-06-18 -12042,474,132,34,21.0,26,,24,0.0,27,,,,8,1989-07-09 -12043,474,89,41,31.0,0,,30,0.0,0,,,,81,1989-07-09 -12044,474,156,46,38.0,0,,29,0.0,0,,,,81,1989-07-09 -12045,474,158,17,24.0,0,,28,0.0,0,,,,81,1989-07-09 -12046,474,162,26,25.0,18,,25,0.0,14,,,,6,1989-07-09 -12047,474,101,0,1.0,2,,26,0.0,0,,,,24,1989-07-09 -12048,474,77,43,17.0,0,,31,0.0,0,,,,97,1989-07-09 -12049,474,109,34,22.0,0,,27,0.0,0,,,,81,1989-07-09 -12050,474,83,33,7.0,0,,32,0.0,0,,,,97,1989-07-09 -12051,474,116,0,2.0,1,1.0,1,9.0,80,5909411.0,,,1,1989-07-09 -12052,474,145,47,34.0,0,,34,0.0,0,,,,97,1989-07-09 -12053,474,159,43,18.0,0,,35,0.0,0,,,,97,1989-07-09 -12054,474,161,41,32.0,0,,36,0.0,0,,,,97,1989-07-09 -12055,474,87,47,35.0,0,,37,0.0,0,,,,97,1989-07-09 -12056,474,147,42,33.0,0,,38,0.0,0,,,,97,1989-07-09 -12057,474,163,38,41.0,0,,39,0.0,0,,,,97,1989-07-09 -12058,474,94,5,27.0,3,2.0,2,6.0,80,5953428.0,,,1,1989-07-09 -12059,474,76,5,28.0,6,,23,0.0,29,,,,8,1989-07-09 -12060,474,160,46,39.0,0,,33,0.0,0,,,,97,1989-07-09 -12061,474,98,38,40.0,21,,22,0.0,30,,,,5,1989-07-09 -12062,474,111,32,30.0,7,,21,0.0,30,,,,5,1989-07-09 -12063,474,93,17,23.0,23,,20,0.0,31,,,,5,1989-07-09 -12064,474,54,24,4.0,16,4.0,4,3.0,80,5982643.0,,,1,1989-07-09 -12065,474,139,44,36.0,13,5.0,5,2.0,79,,,,11,1989-07-09 -12066,474,128,26,26.0,17,6.0,6,1.0,79,,,,11,1989-07-09 -12067,474,157,20,10.0,25,7.0,7,0.0,79,,,,11,1989-07-09 -12068,474,136,31,11.0,20,8.0,8,0.0,78,,,,12,1989-07-09 -12069,474,138,21,20.0,24,9.0,9,0.0,78,,,,12,1989-07-09 -12070,474,155,24,3.0,9,10.0,10,0.0,78,,,,12,1989-07-09 -12071,474,102,32,29.0,15,11.0,11,0.0,77,,,,13,1989-07-09 -12072,474,118,2,6.0,8,3.0,3,4.0,80,5976332.0,,,1,1989-07-09 -12073,474,91,44,37.0,11,13.0,13,0.0,76,,,,5,1989-07-09 -12074,474,126,36,15.0,10,,14,0.0,71,,,,62,1989-07-09 -12075,474,130,33,8.0,22,,15,0.0,67,,,,5,1989-07-09 -12076,474,122,2,5.0,5,,16,0.0,50,,,,6,1989-07-09 -12077,474,137,31,12.0,19,,17,0.0,49,,,,5,1989-07-09 -12078,474,121,36,16.0,12,,18,0.0,43,,,,5,1989-07-09 -12079,474,144,21,19.0,4,,19,0.0,40,,,,22,1989-07-09 -12080,474,150,20,9.0,14,12.0,12,0.0,77,,,,13,1989-07-09 -12081,475,77,43,17.0,17,,21,0.0,23,,,,64,1989-07-16 -12082,475,118,2,6.0,5,,22,0.0,19,,,,21,1989-07-16 -12083,475,121,36,16.0,8,,23,0.0,15,,,,7,1989-07-16 -12084,475,109,34,22.0,25,,24,0.0,16,,,,5,1989-07-16 -12085,475,101,0,1.0,1,,25,0.0,11,,,,20,1989-07-16 -12086,475,89,41,31.0,23,,26,0.0,2,,,,6,1989-07-16 -12087,475,162,26,25.0,0,,27,0.0,0,,,,81,1989-07-16 -12088,475,157,20,10.0,0,,28,0.0,0,,,,81,1989-07-16 -12089,475,132,34,21.0,0,,32,0.0,0,,,,97,1989-07-16 -12090,475,156,46,38.0,0,,30,0.0,0,,,,81,1989-07-16 -12091,475,139,44,36.0,0,,31,0.0,0,,,,97,1989-07-16 -12092,475,147,42,33.0,0,,33,0.0,0,,,,97,1989-07-16 -12093,475,159,43,18.0,0,,34,0.0,0,,,,97,1989-07-16 -12094,475,113,38,41.0,0,,35,0.0,0,,,,97,1989-07-16 -12095,475,145,47,34.0,0,,36,0.0,0,,,,97,1989-07-16 -12096,475,54,24,4.0,22,,20,0.0,28,,,,20,1989-07-16 -12097,475,98,38,40.0,0,,29,0.0,0,,,,81,1989-07-16 -12098,475,161,41,32.0,0,,37,0.0,0,,,,97,1989-07-16 -12099,475,91,44,37.0,21,12.0,12,0.0,62,,,,12,1989-07-16 -12100,475,155,24,3.0,18,,18,0.0,32,,,,20,1989-07-16 -12101,475,116,0,2.0,2,1.0,1,9.0,64,4762131.0,,,1,1989-07-16 -12102,475,94,5,27.0,3,2.0,2,6.0,64,4781500.0,,,1,1989-07-16 -12103,475,144,21,19.0,9,3.0,3,4.0,64,4810150.0,,,1,1989-07-16 -12104,475,136,31,11.0,10,4.0,4,3.0,64,4828866.0,,,1,1989-07-16 -12105,475,93,17,23.0,11,5.0,5,2.0,63,,,,11,1989-07-16 -12106,475,158,17,24.0,15,6.0,6,1.0,63,,,,11,1989-07-16 -12107,475,128,26,26.0,24,7.0,7,0.0,63,,,,11,1989-07-16 -12108,475,137,31,12.0,16,8.0,8,0.0,63,,,,11,1989-07-16 -12109,475,117,20,9.0,19,9.0,9,0.0,62,,,,12,1989-07-16 -12110,475,122,2,5.0,7,10.0,10,0.0,62,,,,12,1989-07-16 -12111,475,138,21,20.0,26,11.0,11,0.0,62,,,,12,1989-07-16 -12112,475,87,47,35.0,0,,38,0.0,0,,,,97,1989-07-16 -12113,475,126,36,15.0,6,,13,0.0,54,,,,6,1989-07-16 -12114,475,83,33,7.0,20,,14,0.0,49,,,,5,1989-07-16 -12115,475,76,5,28.0,4,,15,0.0,49,,,,66,1989-07-16 -12116,475,102,32,29.0,13,,16,0.0,46,,,,5,1989-07-16 -12117,475,111,32,30.0,12,,17,0.0,39,,,,5,1989-07-16 -12118,475,130,33,8.0,14,,19,0.0,31,,,,5,1989-07-16 -12119,475,160,46,39.0,0,,39,0.0,0,,,,97,1989-07-16 -12120,476,76,5,28.0,4,,20,0.0,13,,,,20,1989-07-30 -12121,476,116,0,2.0,2,2.0,2,6.0,45,4921453.0,,,1,1989-07-30 -12122,476,132,34,21.0,20,,24,0.0,2,,,,5,1989-07-30 -12123,476,104,32,29.0,26,,25,0.0,1,,,,10,1989-07-30 -12124,476,128,26,26.0,11,,26,0.0,0,,,,6,1989-07-30 -12125,476,158,17,24.0,0,,27,0.0,0,,,,81,1989-07-30 -12126,476,91,44,37.0,0,,28,0.0,0,,,,81,1989-07-30 -12127,476,156,46,38.0,0,,29,0.0,0,,,,81,1989-07-30 -12128,476,113,38,41.0,0,,31,0.0,0,,,,97,1989-07-30 -12129,476,77,43,17.0,0,,32,0.0,0,,,,97,1989-07-30 -12130,476,98,38,40.0,0,,33,0.0,0,,,,97,1989-07-30 -12131,476,159,43,18.0,0,,34,0.0,0,,,,97,1989-07-30 -12132,476,89,41,31.0,0,,35,0.0,0,,,,97,1989-07-30 -12133,476,161,41,32.0,0,,36,0.0,0,,,,97,1989-07-30 -12134,476,147,42,33.0,0,,37,0.0,0,,,,97,1989-07-30 -12135,476,87,47,35.0,0,,38,0.0,0,,,,97,1989-07-30 -12136,476,101,0,1.0,1,1.0,1,9.0,45,4903302.0,,,1,1989-07-30 -12137,476,122,2,5.0,6,,23,0.0,4,,,,4,1989-07-30 -12138,476,144,21,19.0,7,,22,0.0,6,,,,10,1989-07-30 -12139,476,160,46,39.0,0,,30,0.0,0,,,,2,1989-07-30 -12140,476,155,24,3.0,19,,19,0.0,16,,,,5,1989-07-30 -12141,476,94,5,27.0,3,3.0,3,4.0,45,4986556.0,,,1,1989-07-30 -12142,476,139,44,36.0,24,,21,0.0,8,,,,25,1989-07-30 -12143,476,118,2,6.0,5,4.0,4,3.0,44,,,,11,1989-07-30 -12144,476,136,31,11.0,8,5.0,5,2.0,44,,,,11,1989-07-30 -12145,476,117,20,9.0,17,6.0,6,1.0,44,,,,11,1989-07-30 -12146,476,109,34,22.0,21,7.0,7,0.0,44,,,,11,1989-07-30 -12147,476,93,17,23.0,13,9.0,9,0.0,44,,,,11,1989-07-30 -12148,476,54,24,4.0,10,10.0,10,0.0,43,,,,12,1989-07-30 -12149,476,83,33,7.0,12,8.0,8,0.0,44,,,,11,1989-07-30 -12150,476,157,20,10.0,25,12.0,12,0.0,40,,,,69,1989-07-30 -12151,476,130,33,8.0,16,,13,0.0,37,,,,5,1989-07-30 -12152,476,137,31,12.0,18,,14,0.0,36,,,,20,1989-07-30 -12153,476,121,36,16.0,22,,15,0.0,32,,,,10,1989-07-30 -12154,476,126,36,15.0,14,,16,0.0,28,,,,6,1989-07-30 -12155,476,138,21,20.0,9,,17,0.0,26,,,,20,1989-07-30 -12156,476,111,32,30.0,15,,18,0.0,20,,,,44,1989-07-30 -12157,476,162,26,25.0,23,11.0,11,0.0,42,,,,13,1989-07-30 -12158,477,104,32,29.0,26,,23,0.0,26,,,,5,1989-08-13 -12159,477,156,46,38.0,0,,29,0.0,0,,,,81,1989-08-13 -12160,477,159,43,18.0,22,,24,0.0,20,,,,10,1989-08-13 -12161,477,93,17,23.0,10,,25,0.0,9,,,,36,1989-08-13 -12162,477,109,34,22.0,18,,26,0.0,0,,,,8,1989-08-13 -12163,477,162,26,25.0,0,,27,0.0,0,,,,81,1989-08-13 -12164,477,128,26,26.0,0,,28,0.0,0,,,,81,1989-08-13 -12165,477,160,46,39.0,0,,30,0.0,0,,,,81,1989-08-13 -12166,477,161,41,32.0,0,,39,0.0,0,,,,97,1989-08-13 -12167,477,111,32,30.0,0,,32,0.0,0,,,,97,1989-08-13 -12168,477,113,38,41.0,0,,33,0.0,0,,,,97,1989-08-13 -12169,477,145,47,34.0,0,,34,0.0,0,,,,97,1989-08-13 -12170,477,98,38,40.0,0,,35,0.0,0,,,,97,1989-08-13 -12171,477,147,42,33.0,0,,37,0.0,0,,,,97,1989-08-13 -12172,477,87,47,35.0,0,,38,0.0,0,,,,97,1989-08-13 -12173,477,121,36,16.0,14,,22,0.0,26,,,,36,1989-08-13 -12174,477,77,43,17.0,0,,31,0.0,0,,,,97,1989-08-13 -12175,477,126,36,15.0,13,,21,0.0,27,,,,10,1989-08-13 -12176,477,101,0,1.0,2,2.0,2,6.0,77,6604617.0,,,1,1989-08-13 -12177,477,91,44,37.0,21,,19,0.0,38,,,,6,1989-08-13 -12178,477,94,5,27.0,12,1.0,1,9.0,77,6578650.0,,,1,1989-08-13 -12179,477,122,2,5.0,4,3.0,3,4.0,77,6617004.0,,,1,1989-08-13 -12180,477,116,0,2.0,5,4.0,4,3.0,77,6622827.0,,,1,1989-08-13 -12181,477,157,20,10.0,16,5.0,5,2.0,77,6623756.0,,,1,1989-08-13 -12182,477,136,31,11.0,17,6.0,6,1.0,77,6650689.0,,,1,1989-08-13 -12183,477,132,34,21.0,3,7.0,7,0.0,77,6662875.0,,,1,1989-08-13 -12184,477,138,21,20.0,25,8.0,8,0.0,76,,,,11,1989-08-13 -12185,477,54,24,4.0,11,9.0,9,0.0,76,,,,11,1989-08-13 -12186,477,117,20,9.0,9,10.0,10,0.0,76,,,,11,1989-08-13 -12187,477,130,33,8.0,8,11.0,11,0.0,76,,,,11,1989-08-13 -12188,477,83,33,7.0,15,12.0,12,0.0,75,,,,12,1989-08-13 -12189,477,155,24,3.0,19,13.0,13,0.0,73,,,,14,1989-08-13 -12190,477,158,17,24.0,23,,14,0.0,57,,,,4,1989-08-13 -12191,477,76,5,28.0,6,,15,0.0,56,,,,6,1989-08-13 -12192,477,118,2,6.0,1,,16,0.0,54,,,,21,1989-08-13 -12193,477,139,44,36.0,24,,17,0.0,48,,,,6,1989-08-13 -12194,477,144,21,19.0,7,,18,0.0,46,,,,6,1989-08-13 -12195,477,137,31,12.0,20,,20,0.0,33,,,,3,1989-08-13 -12196,477,89,41,31.0,0,,36,0.0,0,,,,97,1989-08-13 -12197,478,133,41,32.0,0,,39,0.0,0,,,,97,1989-08-27 -12198,478,101,0,1.0,1,1.0,1,9.0,44,6054196.0,,,1,1989-08-27 -12199,478,83,33,7.0,20,,22,0.0,12,,,,23,1989-08-27 -12200,478,76,5,28.0,3,,23,0.0,9,,,,20,1989-08-27 -12201,478,130,33,8.0,8,,24,0.0,9,,,,64,1989-08-27 -12202,478,162,26,25.0,17,,25,0.0,4,,,,4,1989-08-27 -12203,478,64,24,4.0,16,,26,0.0,3,,,,20,1989-08-27 -12204,478,137,31,12.0,0,,27,0.0,0,,,,81,1989-08-27 -12205,478,136,31,11.0,0,,28,0.0,0,,,,81,1989-08-27 -12206,478,132,34,21.0,12,,21,0.0,13,,,,20,1989-08-27 -12207,478,161,46,39.0,0,,30,0.0,0,,,,81,1989-08-27 -12208,478,159,43,18.0,0,,32,0.0,0,,,,97,1989-08-27 -12209,478,89,41,31.0,0,,33,0.0,0,,,,97,1989-08-27 -12210,478,98,38,40.0,0,,34,0.0,0,,,,97,1989-08-27 -12211,478,145,47,34.0,0,,35,0.0,0,,,,97,1989-08-27 -12212,478,87,47,35.0,0,,36,0.0,0,,,,97,1989-08-27 -12213,478,113,38,41.0,0,,37,0.0,0,,,,97,1989-08-27 -12214,478,147,42,33.0,0,,38,0.0,0,,,,97,1989-08-27 -12215,478,77,43,17.0,0,,31,0.0,0,,,,97,1989-08-27 -12216,478,104,32,29.0,22,,20,0.0,19,,,,4,1989-08-27 -12217,478,156,46,38.0,0,,29,0.0,0,,,,81,1989-08-27 -12218,478,91,44,37.0,23,,18,0.0,21,,,,20,1989-08-27 -12219,478,118,2,6.0,5,,19,0.0,20,,,,4,1989-08-27 -12220,478,116,0,2.0,2,2.0,2,6.0,44,6055500.0,,,1,1989-08-27 -12221,478,94,5,27.0,6,3.0,3,4.0,44,6056020.0,,,1,1989-08-27 -12222,478,122,2,5.0,4,4.0,4,3.0,44,6108604.0,,,1,1989-08-27 -12223,478,144,21,19.0,7,5.0,5,2.0,44,6123001.0,,,1,1989-08-27 -12224,478,117,20,9.0,10,6.0,6,1.0,44,6132512.0,,,1,1989-08-27 -12225,478,139,44,36.0,15,8.0,8,0.0,43,,,,11,1989-08-27 -12226,478,93,17,23.0,14,9.0,9,0.0,43,,,,11,1989-08-27 -12227,478,126,36,15.0,9,7.0,7,0.0,43,,,,11,1989-08-27 -12228,478,109,34,22.0,18,11.0,11,0.0,43,,,,11,1989-08-27 -12229,478,121,36,16.0,19,12.0,12,0.0,43,,,,11,1989-08-27 -12230,478,128,26,26.0,26,13.0,13,0.0,43,,,,11,1989-08-27 -12231,478,155,24,3.0,21,14.0,14,0.0,42,,,,12,1989-08-27 -12232,478,158,17,24.0,25,15.0,15,0.0,41,,,,13,1989-08-27 -12233,478,111,32,30.0,11,16.0,16,0.0,39,,,,5,1989-08-27 -12234,478,157,20,10.0,24,,17,0.0,38,,,,36,1989-08-27 -12235,478,138,21,20.0,13,10.0,10,0.0,43,,,,11,1989-08-27 -12236,479,111,32,30.0,7,,25,0.0,1,,,,20,1989-09-10 -12237,479,139,44,36.0,0,,31,0.0,0,,,,97,1989-09-10 -12238,479,138,21,20.0,9,,26,0.0,0,,,,7,1989-09-10 -12239,479,130,33,8.0,0,,27,0.0,0,,,,2,1989-09-10 -12240,479,157,20,10.0,0,,28,0.0,0,,,,81,1989-09-10 -12241,479,156,46,38.0,0,,29,0.0,0,,,,81,1989-09-10 -12242,479,161,46,39.0,0,,30,0.0,0,,,,81,1989-09-10 -12243,479,98,38,40.0,0,,32,0.0,0,,,,97,1989-09-10 -12244,479,76,5,28.0,2,2.0,2,6.0,53,4774876.0,,,1,1989-09-10 -12245,479,159,43,18.0,0,,34,0.0,0,,,,97,1989-09-10 -12246,479,145,47,34.0,0,,35,0.0,0,,,,97,1989-09-10 -12247,479,87,47,35.0,0,,36,0.0,0,,,,97,1989-09-10 -12248,479,164,42,33.0,0,,37,0.0,0,,,,97,1989-09-10 -12249,479,113,38,41.0,0,,38,0.0,0,,,,97,1989-09-10 -12250,479,133,41,32.0,0,,39,0.0,0,,,,97,1989-09-10 -12251,479,116,0,2.0,4,1.0,1,9.0,53,4767550.0,,,1,1989-09-10 -12252,479,126,36,15.0,25,,24,0.0,14,,,,37,1989-09-10 -12253,479,89,41,31.0,0,,33,0.0,0,,,,97,1989-09-10 -12254,479,104,32,29.0,13,,23,0.0,14,,,,10,1989-09-10 -12255,479,109,34,22.0,17,,12,0.0,45,,,,5,1989-09-10 -12256,479,117,20,9.0,16,,21,0.0,18,,,,69,1989-09-10 -12257,479,77,43,17.0,24,,22,0.0,16,,,,6,1989-09-10 -12258,479,118,2,6.0,5,4.0,4,3.0,53,4806272.0,,,1,1989-09-10 -12259,479,54,24,4.0,10,5.0,5,2.0,52,,,,11,1989-09-10 -12260,479,83,33,7.0,12,6.0,6,1.0,52,,,,11,1989-09-10 -12261,479,93,17,23.0,15,7.0,7,0.0,52,,,,11,1989-09-10 -12262,479,158,17,24.0,26,8.0,8,0.0,51,,,,12,1989-09-10 -12263,479,162,26,25.0,23,9.0,9,0.0,51,,,,12,1989-09-10 -12264,479,137,31,12.0,19,10.0,10,0.0,51,,,,22,1989-09-10 -12265,479,132,34,21.0,20,11.0,11,0.0,47,,,,5,1989-09-10 -12266,479,122,2,5.0,6,3.0,3,4.0,53,4782525.0,,,1,1989-09-10 -12267,479,101,0,1.0,1,,13,0.0,44,,,,5,1989-09-10 -12268,479,94,5,27.0,3,,14,0.0,41,,,,6,1989-09-10 -12269,479,91,44,37.0,22,,15,0.0,38,,,,21,1989-09-10 -12270,479,144,21,19.0,8,,16,0.0,33,,,,23,1989-09-10 -12271,479,121,36,16.0,18,,17,0.0,30,,,,5,1989-09-10 -12272,479,128,26,26.0,21,,18,0.0,30,,,,43,1989-09-10 -12273,479,136,31,11.0,11,,19,0.0,23,,,,20,1989-09-10 -12274,479,155,24,3.0,14,,20,0.0,18,,,,5,1989-09-10 -12275,480,157,20,10.0,26,,24,0.0,24,,,,20,1989-09-24 -12276,480,109,34,22.0,19,,25,0.0,17,,,,10,1989-09-24 -12277,480,89,41,31.0,15,,26,0.0,11,,,,10,1989-09-24 -12278,480,64,24,4.0,0,,27,0.0,0,,,,81,1989-09-24 -12279,480,128,26,26.0,0,,28,0.0,0,,,,81,1989-09-24 -12280,480,161,46,39.0,0,,29,0.0,0,,,,81,1989-09-24 -12281,480,156,46,38.0,0,,30,0.0,0,,,,81,1989-09-24 -12282,480,113,38,41.0,0,,31,0.0,0,,,,97,1989-09-24 -12283,480,98,38,40.0,0,,35,0.0,0,,,,97,1989-09-24 -12284,480,159,43,18.0,0,,33,0.0,0,,,,97,1989-09-24 -12285,480,164,42,33.0,0,,34,0.0,0,,,,97,1989-09-24 -12286,480,121,36,16.0,24,,23,0.0,25,,,,5,1989-09-24 -12287,480,77,43,17.0,0,,36,0.0,0,,,,97,1989-09-24 -12288,480,87,47,35.0,0,,37,0.0,0,,,,97,1989-09-24 -12289,480,145,47,34.0,0,,38,0.0,0,,,,97,1989-09-24 -12290,480,133,41,32.0,0,,39,0.0,0,,,,97,1989-09-24 -12291,480,108,44,37.0,0,,32,0.0,0,,,,97,1989-09-24 -12292,480,138,21,20.0,16,,22,0.0,29,,,,22,1989-09-24 -12293,480,104,32,29.0,21,11.0,11,0.0,69,,,,12,1989-09-24 -12294,480,136,31,11.0,20,,20,0.0,33,,,,4,1989-09-24 -12295,480,139,44,36.0,12,3.0,3,4.0,71,5863871.0,,,1,1989-09-24 -12296,480,144,21,19.0,13,4.0,4,3.0,71,5890915.0,,,1,1989-09-24 -12297,480,93,17,23.0,5,5.0,5,2.0,70,,,,11,1989-09-24 -12298,480,155,24,3.0,18,6.0,6,1.0,70,,,,11,1989-09-24 -12299,480,137,31,12.0,25,7.0,7,0.0,70,,,,11,1989-09-24 -12300,480,83,33,7.0,10,8.0,8,0.0,70,,,,11,1989-09-24 -12301,480,111,32,30.0,17,9.0,9,0.0,70,,,,11,1989-09-24 -12302,480,126,36,15.0,14,10.0,10,0.0,69,,,,12,1989-09-24 -12303,480,116,0,2.0,4,2.0,2,6.0,71,5841183.0,,,1,1989-09-24 -12304,480,158,17,24.0,9,12.0,12,0.0,69,,,,12,1989-09-24 -12305,480,76,5,28.0,2,1.0,1,9.0,71,5808546.0,,,1,1989-09-24 -12306,480,117,20,9.0,22,,19,0.0,37,,,,3,1989-09-24 -12307,480,94,5,27.0,3,,18,0.0,48,,,,2,1989-09-24 -12308,480,101,0,1.0,1,,17,0.0,48,,,,4,1989-09-24 -12309,480,132,34,21.0,7,,21,0.0,33,,,,4,1989-09-24 -12310,480,118,2,6.0,6,,15,0.0,60,,,,25,1989-09-24 -12311,480,130,33,8.0,11,14.0,14,0.0,69,,,,12,1989-09-24 -12312,480,162,26,25.0,23,13.0,13,0.0,69,,,,12,1989-09-24 -12313,480,122,2,5.0,8,,16,0.0,60,,,,25,1989-09-24 -12314,481,159,43,18.0,25,,22,0.0,17,,,,6,1989-10-01 -12315,481,144,21,19.0,14,,23,0.0,14,,,,20,1989-10-01 -12316,481,130,33,8.0,12,,24,0.0,11,,,,10,1989-10-01 -12317,481,77,43,17.0,11,,25,0.0,6,,,,22,1989-10-01 -12318,481,137,31,12.0,18,,26,0.0,0,,,,4,1989-10-01 -12319,481,162,26,25.0,0,,27,0.0,0,,,,81,1989-10-01 -12320,481,161,46,39.0,0,,28,0.0,0,,,,81,1989-10-01 -12321,481,147,46,38.0,0,,29,0.0,0,,,,81,1989-10-01 -12322,481,139,44,36.0,0,,31,0.0,0,,,,97,1989-10-01 -12323,481,89,41,31.0,0,,32,0.0,0,,,,97,1989-10-01 -12324,481,104,32,29.0,0,,33,0.0,0,,,,97,1989-10-01 -12325,481,113,38,41.0,0,,35,0.0,0,,,,97,1989-10-01 -12326,481,145,47,34.0,0,,36,0.0,0,,,,97,1989-10-01 -12327,481,164,42,33.0,0,,37,0.0,0,,,,97,1989-10-01 -12328,481,133,41,32.0,0,,38,0.0,0,,,,97,1989-10-01 -12329,481,108,44,37.0,17,,21,0.0,20,,,,6,1989-10-01 -12330,481,98,38,40.0,0,,30,0.0,0,,,,97,1989-10-01 -12331,481,87,47,35.0,0,,34,0.0,0,,,,97,1989-10-01 -12332,481,121,36,16.0,19,,20,0.0,23,,,,7,1989-10-01 -12333,481,128,26,26.0,24,,18,0.0,34,,,,5,1989-10-01 -12334,481,93,17,23.0,4,,19,0.0,27,,,,20,1989-10-01 -12335,481,101,0,1.0,1,1.0,1,9.0,73,6468264.0,,,1,1989-10-01 -12336,481,76,5,28.0,2,2.0,2,6.0,73,6495315.0,,,1,1989-10-01 -12337,481,116,0,2.0,3,3.0,3,4.0,73,6522052.0,,,1,1989-10-01 -12338,481,54,24,4.0,9,4.0,4,3.0,72,,,,11,1989-10-01 -12339,481,111,32,30.0,5,6.0,6,1.0,72,,,,11,1989-10-01 -12340,481,109,34,22.0,15,7.0,7,0.0,72,,,,11,1989-10-01 -12341,481,136,31,11.0,7,8.0,8,0.0,71,,,,12,1989-10-01 -12342,481,118,2,6.0,6,5.0,5,2.0,72,,,,11,1989-10-01 -12343,481,155,24,3.0,13,10.0,10,0.0,71,,,,12,1989-10-01 -12344,481,117,20,9.0,16,9.0,9,0.0,71,,,,12,1989-10-01 -12345,481,158,17,24.0,20,,16,0.0,47,,,,20,1989-10-01 -12346,481,126,36,15.0,26,,15,0.0,47,,,,4,1989-10-01 -12347,481,83,33,7.0,8,,14,0.0,51,,,,20,1989-10-01 -12348,481,122,2,5.0,21,,17,0.0,40,,,,48,1989-10-01 -12349,481,138,21,20.0,10,,12,0.0,59,,,,20,1989-10-01 -12350,481,157,20,10.0,22,,11,0.0,61,,,,5,1989-10-01 -12351,481,132,34,21.0,23,,13,0.0,55,,,,5,1989-10-01 -12352,482,161,46,38.0,0,,29,0.0,0,,,,81,1989-10-22 -12353,482,155,24,3.0,26,,23,0.0,20,,,,95,1989-10-22 -12354,482,145,47,34.0,21,,24,0.0,1,,,,6,1989-10-22 -12355,482,77,43,17.0,10,,22,0.0,21,,,,23,1989-10-22 -12356,482,146,17,23.0,19,,26,0.0,0,,,,8,1989-10-22 -12357,482,162,26,25.0,0,,27,0.0,0,,,,81,1989-10-22 -12358,482,104,32,29.0,0,,28,0.0,0,,,,81,1989-10-22 -12359,482,91,46,39.0,0,,30,0.0,0,,,,81,1989-10-22 -12360,482,133,41,32.0,0,,39,0.0,0,,,,97,1989-10-22 -12361,482,89,41,31.0,0,,32,0.0,0,,,,97,1989-10-22 -12362,482,139,44,36.0,0,,33,0.0,0,,,,97,1989-10-22 -12363,482,87,47,35.0,0,,34,0.0,0,,,,97,1989-10-22 -12364,482,164,42,33.0,0,,35,0.0,0,,,,97,1989-10-22 -12365,482,108,44,37.0,0,,36,0.0,0,,,,97,1989-10-22 -12366,482,98,38,40.0,0,,37,0.0,0,,,,97,1989-10-22 -12367,482,113,38,41.0,0,,38,0.0,0,,,,97,1989-10-22 -12368,482,159,43,18.0,0,,31,0.0,0,,,,97,1989-10-22 -12369,482,121,36,16.0,17,,21,0.0,27,,,,22,1989-10-22 -12370,482,158,17,24.0,14,,25,0.0,0,,,,4,1989-10-22 -12371,482,138,21,20.0,22,,19,0.0,33,,,,4,1989-10-22 -12372,482,128,26,26.0,23,,20,0.0,31,,,,5,1989-10-22 -12373,482,118,2,6.0,5,2.0,2,6.0,53,5718181.0,,,1,1989-10-22 -12374,482,122,2,5.0,7,3.0,3,4.0,53,5719723.0,,,1,1989-10-22 -12375,482,136,31,11.0,11,4.0,4,3.0,53,5810502.0,,,1,1989-10-22 -12376,482,83,33,7.0,13,5.0,5,2.0,52,,,,11,1989-10-22 -12377,482,117,20,9.0,25,6.0,6,1.0,52,,,,11,1989-10-22 -12378,482,126,36,15.0,20,7.0,7,0.0,52,,,,11,1989-10-22 -12379,482,157,20,10.0,24,8.0,8,0.0,52,,,,11,1989-10-22 -12380,482,132,34,21.0,15,9.0,9,0.0,52,,,,11,1989-10-22 -12381,482,144,21,19.0,6,1.0,1,9.0,53,5706277.0,,,1,1989-10-22 -12382,482,101,0,1.0,1,,11,0.0,53,,,,2,1989-10-22 -12383,482,109,34,22.0,16,10.0,10,0.0,51,,,,12,1989-10-22 -12384,482,111,32,30.0,8,,17,0.0,36,,,,5,1989-10-22 -12385,482,54,24,4.0,18,,16,0.0,37,,,,6,1989-10-22 -12386,482,76,5,28.0,3,,18,0.0,34,,,,6,1989-10-22 -12387,482,94,5,27.0,4,,14,0.0,43,,,,5,1989-10-22 -12388,482,130,33,8.0,9,,13,0.0,46,,,,5,1989-10-22 -12389,482,116,0,2.0,2,,12,0.0,46,,,,4,1989-10-22 -12390,482,137,31,12.0,12,,15,0.0,41,,,,5,1989-10-22 -12391,483,54,24,4.0,15,,23,0.0,5,,,,10,1989-11-05 -12392,483,91,46,39.0,0,,29,0.0,0,,,,81,1989-11-05 -12393,483,162,26,25.0,26,,24,0.0,4,,,,4,1989-11-05 -12394,483,116,0,2.0,2,,25,0.0,0,,,,54,1989-11-05 -12395,483,77,43,17.0,11,,26,0.0,0,,,,10,1989-11-05 -12396,483,155,24,3.0,0,,27,0.0,0,,,,81,1989-11-05 -12397,483,158,17,24.0,0,,28,0.0,0,,,,81,1989-11-05 -12398,483,161,46,38.0,0,,30,0.0,0,,,,81,1989-11-05 -12399,483,89,41,31.0,0,,34,0.0,0,,,,97,1989-11-05 -12400,483,104,32,29.0,0,,32,0.0,0,,,,97,1989-11-05 -12401,483,145,47,34.0,0,,33,0.0,0,,,,97,1989-11-05 -12402,483,87,47,35.0,0,,36,0.0,0,,,,97,1989-11-05 -12403,483,113,38,41.0,0,,37,0.0,0,,,,97,1989-11-05 -12404,483,98,38,40.0,0,,38,0.0,0,,,,97,1989-11-05 -12405,483,133,41,32.0,0,,39,0.0,0,,,,97,1989-11-05 -12406,483,76,5,28.0,14,,22,0.0,6,,,,4,1989-11-05 -12407,483,139,44,36.0,0,,31,0.0,0,,,,97,1989-11-05 -12408,483,111,32,30.0,19,,21,0.0,6,,,,4,1989-11-05 -12409,483,164,42,33.0,0,,35,0.0,0,,,,97,1989-11-05 -12410,483,83,33,7.0,12,,19,0.0,12,,,,4,1989-11-05 -12411,483,117,20,9.0,20,,20,0.0,7,,,,20,1989-11-05 -12412,483,144,21,19.0,4,2.0,2,6.0,70,7246079.0,,,1,1989-11-05 -12413,483,137,31,12.0,23,4.0,4,3.0,70,7259752.0,,,1,1989-11-05 -12414,483,138,21,20.0,13,5.0,5,2.0,68,,,,12,1989-11-05 -12415,483,93,17,23.0,3,6.0,6,1.0,67,,,,13,1989-11-05 -12416,483,122,2,5.0,5,1.0,1,9.0,70,7217421.0,,,1,1989-11-05 -12417,483,126,36,15.0,25,7.0,7,0.0,66,,,,14,1989-11-05 -12418,483,130,33,8.0,8,8.0,8,0.0,64,,,,16,1989-11-05 -12419,483,157,20,10.0,22,,9,0.0,42,,,,20,1989-11-05 -12420,483,118,2,6.0,6,3.0,3,4.0,70,7255104.0,,,1,1989-11-05 -12421,483,128,26,26.0,24,,11,0.0,22,,,,20,1989-11-05 -12422,483,136,31,11.0,18,,12,0.0,19,,,,4,1989-11-05 -12423,483,159,43,18.0,21,,13,0.0,18,,,,4,1989-11-05 -12424,483,94,5,27.0,7,,14,0.0,17,,,,20,1989-11-05 -12425,483,101,0,1.0,1,,15,0.0,13,,,,4,1989-11-05 -12426,483,132,34,21.0,10,,16,0.0,13,,,,20,1989-11-05 -12427,483,121,36,16.0,16,,17,0.0,13,,,,21,1989-11-05 -12428,483,109,34,22.0,9,,18,0.0,12,,,,20,1989-11-05 -12429,483,108,44,37.0,17,,10,0.0,27,,,,10,1989-11-05 -12430,484,113,38,18.0,0,,32,0.0,0,,,,97,1990-03-11 -12431,484,148,42,34.0,0,,33,0.0,0,,,,97,1990-03-11 -12432,484,149,45,39.0,0,,34,0.0,0,,,,97,1990-03-11 -12433,484,91,41,31.0,0,,35,0.0,0,,,,97,1990-03-11 -12434,484,101,0,27.0,5,1.0,1,9.0,72,6752829.0,,,1,1990-03-11 -12435,484,54,24,4.0,4,2.0,2,6.0,72,6761514.0,,,1,1990-03-11 -12436,484,137,24,3.0,11,6.0,6,1.0,71,,,,11,1990-03-11 -12437,484,136,21,20.0,6,4.0,4,3.0,72,6821187.0,,,1,1990-03-11 -12438,484,130,33,8.0,10,5.0,5,2.0,72,6822332.0,,,1,1990-03-11 -12439,484,93,17,23.0,2,7.0,7,0.0,71,,,,11,1990-03-11 -12440,484,102,32,29.0,15,8.0,8,0.0,71,,,,11,1990-03-11 -12441,484,118,2,6.0,12,9.0,9,0.0,71,,,,11,1990-03-11 -12442,484,104,20,9.0,21,10.0,10,0.0,70,,,,12,1990-03-11 -12443,484,98,38,17.0,0,,31,0.0,0,,,,97,1990-03-11 -12444,484,122,2,5.0,9,3.0,3,4.0,72,6806909.0,,,1,1990-03-11 -12445,484,108,44,36.0,0,,30,0.0,0,,,,81,1990-03-11 -12446,484,77,26,25.0,13,,25,0.0,4,,,,37,1990-03-11 -12447,484,139,44,35.0,0,,28,0.0,0,,,,81,1990-03-11 -12448,484,144,21,19.0,22,11.0,11,0.0,70,,,,12,1990-03-11 -12449,484,145,20,10.0,20,12.0,12,0.0,70,,,,12,1990-03-11 -12450,484,80,34,21.0,0,,29,0.0,0,,,,81,1990-03-11 -12451,484,126,40,15.0,25,14.0,14,0.0,66,,,,16,1990-03-11 -12452,484,146,17,24.0,14,,15,0.0,54,,,,68,1990-03-11 -12453,484,87,32,30.0,18,,16,0.0,53,,,,23,1990-03-11 -12454,484,94,5,2.0,17,,17,0.0,49,,,,8,1990-03-11 -12455,484,76,0,28.0,1,,18,0.0,44,,,,8,1990-03-11 -12456,484,89,42,33.0,16,13.0,13,0.0,67,,,,15,1990-03-11 -12457,484,128,43,14.0,8,,20,0.0,39,,,,4,1990-03-11 -12458,484,109,34,22.0,3,,21,0.0,25,,,,5,1990-03-11 -12459,484,116,5,1.0,7,,22,0.0,21,,,,44,1990-03-11 -12460,484,121,40,16.0,26,,23,0.0,20,,,,10,1990-03-11 -12461,484,117,31,11.0,24,,24,0.0,6,,,,6,1990-03-11 -12462,484,150,31,12.0,19,,26,0.0,0,,,,6,1990-03-11 -12463,484,111,26,26.0,0,,27,0.0,0,,,,2,1990-03-11 -12464,484,147,33,7.0,23,,19,0.0,39,,,,3,1990-03-11 -12465,485,139,44,35.0,0,,27,0.0,0,,,,81,1990-03-25 -12466,485,108,44,36.0,0,,28,0.0,0,,,,81,1990-03-25 -12467,485,109,34,22.0,9,,26,0.0,0,,,,4,1990-03-25 -12468,485,121,40,16.0,0,,29,0.0,0,,,,81,1990-03-25 -12469,485,91,41,31.0,0,,33,0.0,0,,,,97,1990-03-25 -12470,485,98,38,17.0,0,,31,0.0,0,,,,97,1990-03-25 -12471,485,89,42,33.0,0,,32,0.0,0,,,,97,1990-03-25 -12472,485,148,42,34.0,0,,34,0.0,0,,,,97,1990-03-25 -12473,485,149,45,39.0,0,,35,0.0,0,,,,97,1990-03-25 -12474,485,126,40,15.0,0,,30,0.0,0,,,,81,1990-03-25 -12475,485,128,43,14.0,21,,25,0.0,8,,,,4,1990-03-25 -12476,485,113,38,18.0,26,,19,0.0,28,,,,22,1990-03-25 -12477,485,147,33,7.0,22,,23,0.0,14,,,,7,1990-03-25 -12478,485,102,32,29.0,11,,24,0.0,13,,,,6,1990-03-25 -12479,485,144,21,19.0,15,10.0,10,0.0,68,,,,29,1990-03-25 -12480,485,93,17,23.0,8,9.0,9,0.0,69,,,,12,1990-03-25 -12481,485,137,24,3.0,19,8.0,8,0.0,70,,,,11,1990-03-25 -12482,485,54,24,4.0,7,7.0,7,0.0,70,,,,11,1990-03-25 -12483,485,136,21,20.0,13,6.0,6,1.0,70,,,,11,1990-03-25 -12484,485,94,5,2.0,5,4.0,4,3.0,71,5888524.0,,,1,1990-03-25 -12485,485,101,0,27.0,1,3.0,3,4.0,71,5878980.0,,,1,1990-03-25 -12486,485,76,0,28.0,2,2.0,2,6.0,71,5854822.0,,,1,1990-03-25 -12487,485,116,5,1.0,6,1.0,1,9.0,71,5841258.0,,,1,1990-03-25 -12488,485,122,2,5.0,3,5.0,5,2.0,70,,,,11,1990-03-25 -12489,485,111,26,26.0,10,12.0,12,0.0,68,,,,13,1990-03-25 -12490,485,77,26,25.0,20,11.0,11,0.0,68,,,,13,1990-03-25 -12491,485,87,32,30.0,18,,21,0.0,24,,,,22,1990-03-25 -12492,485,117,31,11.0,24,,20,0.0,25,,,,10,1990-03-25 -12493,485,146,17,24.0,17,,18,0.0,38,,,,5,1990-03-25 -12494,485,130,33,8.0,12,,17,0.0,39,,,,20,1990-03-25 -12495,485,104,20,9.0,23,,22,0.0,24,,,,22,1990-03-25 -12496,485,132,20,10.0,25,,15,0.0,49,,,,8,1990-03-25 -12497,485,80,34,21.0,16,14.0,14,0.0,64,,,,17,1990-03-25 -12498,485,118,2,6.0,4,13.0,13,0.0,65,,,,51,1990-03-25 -12499,485,150,31,12.0,14,,16,0.0,43,,,,20,1990-03-25 -12500,486,89,42,33.0,24,,26,0.0,0,,,,37,1990-05-13 -12501,486,113,38,18.0,0,,35,0.0,0,,,,97,1990-05-13 -12502,486,98,38,17.0,0,,34,0.0,0,,,,97,1990-05-13 -12503,486,151,45,39.0,0,,33,0.0,0,,,,97,1990-05-13 -12504,486,148,42,34.0,0,,32,0.0,0,,,,97,1990-05-13 -12505,486,91,41,31.0,0,,31,0.0,0,,,,97,1990-05-13 -12506,486,100,33,7.0,0,,30,0.0,0,,,,81,1990-05-13 -12507,486,104,20,9.0,0,,29,0.0,0,,,,81,1990-05-13 -12508,486,132,20,10.0,0,,28,0.0,0,,,,81,1990-05-13 -12509,486,93,17,23.0,0,,27,0.0,0,,,,3,1990-05-13 -12510,486,137,24,3.0,19,,25,0.0,0,,,,4,1990-05-13 -12511,486,121,40,16.0,18,,24,0.0,0,,,,4,1990-05-13 -12512,486,138,34,21.0,21,,23,0.0,2,,,,20,1990-05-13 -12513,486,118,2,6.0,3,1.0,1,9.0,61,5455478.0,,,1,1990-05-13 -12514,486,76,0,28.0,2,2.0,2,6.0,61,5460595.0,,,1,1990-05-13 -12515,486,144,21,19.0,9,3.0,3,4.0,61,5461718.0,,,1,1990-05-13 -12516,486,116,5,1.0,6,4.0,4,3.0,61,5462321.0,,,1,1990-05-13 -12517,486,136,21,20.0,8,5.0,5,2.0,61,5508590.0,,,1,1990-05-13 -12518,486,54,24,4.0,7,6.0,6,1.0,60,,,,11,1990-05-13 -12519,486,150,31,12.0,11,8.0,8,0.0,60,,,,11,1990-05-13 -12520,486,111,26,26.0,16,9.0,9,0.0,60,,,,11,1990-05-13 -12521,486,77,26,25.0,20,10.0,10,0.0,59,,,,12,1990-05-13 -12522,486,146,17,24.0,26,11.0,11,0.0,59,,,,12,1990-05-13 -12523,486,117,31,11.0,10,7.0,7,0.0,60,,,,11,1990-05-13 -12524,486,102,32,29.0,13,13.0,13,0.0,56,,,,8,1990-05-13 -12525,486,108,44,36.0,25,12.0,12,0.0,59,,,,12,1990-05-13 -12526,486,87,32,30.0,15,,21,0.0,17,,,,8,1990-05-13 -12527,486,122,2,5.0,4,,20,0.0,17,,,,5,1990-05-13 -12528,486,126,40,15.0,12,,19,0.0,24,,,,10,1990-05-13 -12529,486,109,34,22.0,17,,18,0.0,29,,,,36,1990-05-13 -12530,486,101,0,27.0,1,,22,0.0,3,,,,36,1990-05-13 -12531,486,147,44,35.0,23,,16,0.0,35,,,,5,1990-05-13 -12532,486,94,5,2.0,5,,15,0.0,38,,,,5,1990-05-13 -12533,486,128,43,14.0,22,,14,0.0,52,,,,36,1990-05-13 -12534,486,130,33,8.0,14,,17,0.0,31,,,,23,1990-05-13 -12535,487,136,21,20.0,10,,26,0.0,34,,,,2,1990-05-27 -12536,487,151,45,39.0,0,,35,0.0,0,,,,97,1990-05-27 -12537,487,91,41,31.0,0,,34,0.0,0,,,,97,1990-05-27 -12538,487,148,42,34.0,0,,33,0.0,0,,,,97,1990-05-27 -12539,487,113,38,18.0,0,,32,0.0,0,,,,97,1990-05-27 -12540,487,98,38,17.0,0,,31,0.0,0,,,,97,1990-05-27 -12541,487,89,42,33.0,0,,30,0.0,0,,,,81,1990-05-27 -12542,487,126,40,15.0,0,,29,0.0,0,,,,81,1990-05-27 -12543,487,128,43,14.0,0,,28,0.0,0,,,,81,1990-05-27 -12544,487,104,20,9.0,0,,27,0.0,0,,,,81,1990-05-27 -12545,487,138,34,21.0,9,,25,0.0,0,,,,5,1990-05-27 -12546,487,102,32,29.0,24,6.0,6,1.0,76,,,,12,1990-05-27 -12547,487,150,31,12.0,11,,23,0.0,6,,,,6,1990-05-27 -12548,487,101,0,27.0,1,1.0,1,9.0,78,6766982.0,,,1,1990-05-27 -12549,487,54,24,4.0,3,2.0,2,6.0,78,6768069.0,,,1,1990-05-27 -12550,487,76,0,28.0,5,3.0,3,4.0,78,6769055.0,,,1,1990-05-27 -12551,487,122,2,5.0,6,4.0,4,3.0,77,,,,11,1990-05-27 -12552,487,132,20,10.0,22,5.0,5,2.0,76,,,,12,1990-05-27 -12553,487,130,33,8.0,14,,24,0.0,3,,,,7,1990-05-27 -12554,487,117,31,11.0,13,,8,0.0,66,,,,20,1990-05-27 -12555,487,94,5,2.0,7,,9,0.0,63,,,,84,1990-05-27 -12556,487,146,17,24.0,19,,10,0.0,52,,,,6,1990-05-27 -12557,487,108,44,36.0,26,,11,0.0,52,,,,6,1990-05-27 -12558,487,147,44,35.0,20,7.0,7,0.0,72,,,,4,1990-05-27 -12559,487,118,2,6.0,4,,13,0.0,41,,,,99,1990-05-27 -12560,487,111,26,26.0,18,,12,0.0,47,,,,6,1990-05-27 -12561,487,87,32,30.0,15,,21,0.0,11,,,,38,1990-05-27 -12562,487,77,26,25.0,17,,20,0.0,12,,,,24,1990-05-27 -12563,487,121,40,16.0,23,,19,0.0,13,,,,23,1990-05-27 -12564,487,100,33,7.0,25,,18,0.0,16,,,,7,1990-05-27 -12565,487,93,17,23.0,8,,22,0.0,7,,,,10,1990-05-27 -12566,487,144,21,19.0,16,,17,0.0,20,,,,6,1990-05-27 -12567,487,116,5,1.0,2,,16,0.0,30,,,,84,1990-05-27 -12568,487,137,24,3.0,21,,15,0.0,36,,,,20,1990-05-27 -12569,487,109,34,22.0,12,,14,0.0,38,,,,5,1990-05-27 -12570,488,151,45,39.0,0,,35,0.0,0,,,,97,1990-06-10 -12571,488,148,42,34.0,0,,34,0.0,0,,,,97,1990-06-10 -12572,488,91,41,31.0,0,,33,0.0,0,,,,97,1990-06-10 -12573,488,113,38,18.0,0,,32,0.0,0,,,,97,1990-06-10 -12574,488,98,38,17.0,0,,31,0.0,0,,,,97,1990-06-10 -12575,488,100,33,7.0,0,,30,0.0,0,,,,81,1990-06-10 -12576,488,146,17,24.0,0,,29,0.0,0,,,,81,1990-06-10 -12577,488,126,40,15.0,0,,28,0.0,0,,,,81,1990-06-10 -12578,488,89,42,33.0,0,,27,0.0,0,,,,81,1990-06-10 -12579,488,93,17,23.0,16,,26,0.0,0,,,,20,1990-06-10 -12580,488,104,20,9.0,14,,25,0.0,11,,,,4,1990-06-10 -12581,488,101,0,27.0,1,1.0,1,9.0,70,6176400.0,,,1,1990-06-10 -12582,488,77,26,25.0,20,,23,0.0,18,,,,4,1990-06-10 -12583,488,87,32,30.0,18,12.0,12,0.0,66,,,,14,1990-06-10 -12584,488,138,34,21.0,19,,24,0.0,11,,,,4,1990-06-10 -12585,488,137,24,3.0,13,11.0,11,0.0,67,,,,13,1990-06-10 -12586,488,121,40,16.0,24,10.0,10,0.0,67,,,,13,1990-06-10 -12587,488,102,32,29.0,23,9.0,9,0.0,67,,,,13,1990-06-10 -12588,488,132,20,10.0,26,8.0,8,0.0,68,,,,12,1990-06-10 -12589,488,117,31,11.0,11,6.0,6,1.0,68,,,,12,1990-06-10 -12590,488,116,5,1.0,3,5.0,5,2.0,70,6192220.0,,,1,1990-06-10 -12591,488,76,0,28.0,2,4.0,4,3.0,70,6191254.0,,,1,1990-06-10 -12592,488,94,5,2.0,7,3.0,3,4.0,70,6189785.0,,,1,1990-06-10 -12593,488,130,33,8.0,10,7.0,7,0.0,68,,,,12,1990-06-10 -12594,488,128,43,14.0,15,13.0,13,0.0,65,,,,15,1990-06-10 -12595,488,150,31,12.0,12,,14,0.0,57,,,,5,1990-06-10 -12596,488,147,44,35.0,21,,15,0.0,53,,,,5,1990-06-10 -12597,488,109,34,22.0,25,,16,0.0,50,,,,6,1990-06-10 -12598,488,108,44,36.0,22,,17,0.0,46,,,,5,1990-06-10 -12599,488,118,2,6.0,9,,18,0.0,44,,,,23,1990-06-10 -12600,488,111,26,26.0,17,,19,0.0,34,,,,5,1990-06-10 -12601,488,54,24,4.0,8,,20,0.0,26,,,,20,1990-06-10 -12602,488,144,21,19.0,4,,21,0.0,21,,,,20,1990-06-10 -12603,488,136,21,20.0,5,2.0,2,6.0,70,6186897.0,,,1,1990-06-10 -12604,488,122,2,5.0,6,,22,0.0,19,,,,4,1990-06-10 -12605,489,89,42,33.0,0,,27,0.0,0,,,,2,1990-06-24 -12606,489,121,40,16.0,0,,28,0.0,0,,,,81,1990-06-24 -12607,489,126,40,15.0,0,,29,0.0,0,,,,81,1990-06-24 -12608,489,132,20,10.0,0,,30,0.0,0,,,,81,1990-06-24 -12609,489,151,45,39.0,0,,35,0.0,0,,,,97,1990-06-24 -12610,489,98,38,17.0,0,,32,0.0,0,,,,97,1990-06-24 -12611,489,91,41,31.0,0,,33,0.0,0,,,,97,1990-06-24 -12612,489,148,42,34.0,0,,34,0.0,0,,,,97,1990-06-24 -12613,489,138,34,21.0,18,,26,0.0,10,,,,5,1990-06-24 -12614,489,113,38,18.0,0,,31,0.0,0,,,,97,1990-06-24 -12615,489,100,33,7.0,21,,25,0.0,11,,,,10,1990-06-24 -12616,489,128,43,14.0,20,19.0,19,0.0,65,,,,14,1990-06-24 -12617,489,87,32,30.0,19,,23,0.0,11,,,,4,1990-06-24 -12618,489,130,33,8.0,10,11.0,11,0.0,68,,,,11,1990-06-24 -12619,489,116,5,1.0,13,1.0,1,9.0,69,5555783.0,,,1,1990-06-24 -12620,489,94,5,2.0,4,2.0,2,6.0,69,5581134.0,,,1,1990-06-24 -12621,489,76,0,28.0,1,3.0,3,4.0,69,5581313.0,,,1,1990-06-24 -12622,489,144,21,19.0,14,4.0,4,3.0,69,5596882.0,,,1,1990-06-24 -12623,489,122,2,5.0,5,5.0,5,2.0,69,5602452.0,,,1,1990-06-24 -12624,489,54,24,4.0,6,7.0,7,0.0,69,5604860.0,,,1,1990-06-24 -12625,489,150,31,12.0,12,8.0,8,0.0,69,5621925.0,,,1,1990-06-24 -12626,489,118,2,6.0,2,9.0,9,0.0,69,5625701.0,,,1,1990-06-24 -12627,489,117,31,11.0,11,10.0,10,0.0,68,,,,11,1990-06-24 -12628,489,136,21,20.0,8,6.0,6,1.0,69,5602726.0,,,1,1990-06-24 -12629,489,93,17,23.0,7,12.0,12,0.0,68,,,,11,1990-06-24 -12630,489,137,24,3.0,9,,24,0.0,11,,,,4,1990-06-24 -12631,489,108,44,36.0,26,,21,0.0,26,,,,5,1990-06-24 -12632,489,101,0,27.0,3,20.0,20,0.0,63,,,,27,1990-06-24 -12633,489,111,26,26.0,22,18.0,18,0.0,66,,,,13,1990-06-24 -12634,489,104,20,9.0,17,17.0,17,0.0,66,,,,13,1990-06-24 -12635,489,102,32,29.0,25,,22,0.0,12,,,,23,1990-06-24 -12636,489,147,44,35.0,23,15.0,15,0.0,67,,,,12,1990-06-24 -12637,489,146,17,24.0,16,14.0,14,0.0,67,,,,12,1990-06-24 -12638,489,109,34,22.0,15,13.0,13,0.0,68,,,,11,1990-06-24 -12639,489,77,26,25.0,24,16.0,16,0.0,67,,,,12,1990-06-24 -12640,490,138,34,21.0,24,,26,0.0,7,,,,23,1990-07-08 -12641,490,151,45,39.0,0,,35,0.0,0,,,,97,1990-07-08 -12642,490,91,41,31.0,0,,34,0.0,0,,,,97,1990-07-08 -12643,490,148,42,34.0,0,,33,0.0,0,,,,97,1990-07-08 -12644,490,89,42,33.0,0,,32,0.0,0,,,,97,1990-07-08 -12645,490,128,43,14.0,0,,31,0.0,0,,,,97,1990-07-08 -12646,490,108,44,36.0,0,,30,0.0,0,,,,81,1990-07-08 -12647,490,147,44,35.0,0,,29,0.0,0,,,,81,1990-07-08 -12648,490,98,38,17.0,0,,28,0.0,0,,,,81,1990-07-08 -12649,490,146,17,24.0,0,,27,0.0,0,,,,81,1990-07-08 -12650,490,122,2,5.0,8,,25,0.0,7,,,,5,1990-07-08 -12651,490,132,20,10.0,22,,24,0.0,22,,,,22,1990-07-08 -12652,490,54,24,4.0,13,,23,0.0,23,,,,24,1990-07-08 -12653,490,116,5,1.0,4,1.0,1,9.0,80,5609606.0,,,1,1990-07-08 -12654,490,121,40,16.0,7,2.0,2,6.0,80,5618232.0,,,1,1990-07-08 -12655,490,101,0,27.0,3,3.0,3,4.0,80,5621212.0,,,1,1990-07-08 -12656,490,136,21,20.0,9,4.0,4,3.0,80,5650813.0,,,1,1990-07-08 -12657,490,76,0,28.0,2,5.0,5,2.0,80,5651825.0,,,1,1990-07-08 -12658,490,118,2,6.0,6,6.0,6,1.0,80,5678957.0,,,1,1990-07-08 -12659,490,102,32,29.0,11,8.0,8,0.0,79,,,,11,1990-07-08 -12660,490,111,26,26.0,12,9.0,9,0.0,79,,,,11,1990-07-08 -12661,490,104,20,9.0,18,10.0,10,0.0,79,,,,11,1990-07-08 -12662,490,117,31,11.0,16,11.0,11,0.0,79,,,,11,1990-07-08 -12663,490,87,32,30.0,14,7.0,7,0.0,79,,,,11,1990-07-08 -12664,490,130,33,8.0,20,13.0,13,0.0,78,,,,12,1990-07-08 -12665,490,77,26,25.0,19,14.0,14,0.0,78,,,,12,1990-07-08 -12666,490,100,33,7.0,25,15.0,15,0.0,77,,,,13,1990-07-08 -12667,490,144,21,19.0,5,16.0,16,0.0,75,,,,10,1990-07-08 -12668,490,113,38,18.0,26,17.0,17,0.0,75,,,,15,1990-07-08 -12669,490,94,5,2.0,1,18.0,18,0.0,72,,,,5,1990-07-08 -12670,490,109,34,22.0,21,,19,0.0,78,,,,2,1990-07-08 -12671,490,137,24,3.0,15,,20,0.0,63,,,,6,1990-07-08 -12672,490,126,40,15.0,10,,21,0.0,58,,,,5,1990-07-08 -12673,490,150,31,12.0,17,12.0,12,0.0,79,,,,11,1990-07-08 -12674,490,93,17,23.0,23,,22,0.0,40,,,,10,1990-07-08 -12675,491,128,43,14.0,0,,27,0.0,0,,,,81,1990-07-15 -12676,491,100,33,7.0,0,,28,0.0,0,,,,81,1990-07-15 -12677,491,108,44,36.0,0,,29,0.0,0,,,,81,1990-07-15 -12678,491,147,44,35.0,0,,30,0.0,0,,,,81,1990-07-15 -12679,491,151,45,39.0,0,,35,0.0,0,,,,97,1990-07-15 -12680,491,113,38,18.0,0,,32,0.0,0,,,,97,1990-07-15 -12681,491,148,42,34.0,0,,33,0.0,0,,,,97,1990-07-15 -12682,491,91,41,31.0,0,,34,0.0,0,,,,97,1990-07-15 -12683,491,126,40,15.0,15,,26,0.0,0,,,,48,1990-07-15 -12684,491,89,42,33.0,0,,31,0.0,0,,,,97,1990-07-15 -12685,491,93,17,23.0,18,,25,0.0,3,,,,91,1990-07-15 -12686,491,98,38,17.0,26,,19,0.0,41,,,,5,1990-07-15 -12687,491,144,21,19.0,13,,23,0.0,15,,,,4,1990-07-15 -12688,491,122,2,5.0,4,2.0,2,6.0,64,4750091.0,,,1,1990-07-15 -12689,491,101,0,27.0,2,3.0,3,4.0,64,4754087.0,,,1,1990-07-15 -12690,491,102,32,29.0,8,4.0,4,3.0,64,4786301.0,,,1,1990-07-15 -12691,491,136,21,20.0,11,5.0,5,2.0,64,4795002.0,,,1,1990-07-15 -12692,491,87,32,30.0,9,6.0,6,1.0,63,,,,11,1990-07-15 -12693,491,132,20,10.0,17,7.0,7,0.0,63,,,,11,1990-07-15 -12694,491,54,24,4.0,6,8.0,8,0.0,63,,,,11,1990-07-15 -12695,491,130,33,8.0,20,9.0,9,0.0,62,,,,12,1990-07-15 -12696,491,77,26,25.0,21,10.0,10,0.0,62,,,,12,1990-07-15 -12697,491,138,34,21.0,19,11.0,11,0.0,62,,,,12,1990-07-15 -12698,491,109,34,22.0,23,,24,0.0,12,,,,69,1990-07-15 -12699,491,116,5,1.0,5,1.0,1,9.0,64,4710999.0,,,1,1990-07-15 -12700,491,146,17,24.0,24,12.0,12,0.0,62,,,,12,1990-07-15 -12701,491,137,24,3.0,12,,22,0.0,20,,,,10,1990-07-15 -12702,491,118,2,6.0,7,,21,0.0,26,,,,83,1990-07-15 -12703,491,104,20,9.0,25,,20,0.0,37,,,,5,1990-07-15 -12704,491,117,31,11.0,16,,18,0.0,46,,,,5,1990-07-15 -12705,491,150,31,12.0,14,,17,0.0,48,,,,5,1990-07-15 -12706,491,121,40,16.0,10,,16,0.0,48,,,,95,1990-07-15 -12707,491,94,5,2.0,1,,15,0.0,55,,,,6,1990-07-15 -12708,491,76,0,28.0,3,14.0,14,0.0,60,,,,37,1990-07-15 -12709,491,111,26,26.0,22,13.0,13,0.0,61,,,,13,1990-07-15 -12710,492,128,43,14.0,0,,27,0.0,0,,,,81,1990-07-29 -12711,492,146,17,24.0,0,,28,0.0,0,,,,81,1990-07-29 -12712,492,113,38,18.0,0,,29,0.0,0,,,,81,1990-07-29 -12713,492,109,34,22.0,0,,30,0.0,0,,,,81,1990-07-29 -12714,492,98,38,17.0,0,,31,0.0,0,,,,97,1990-07-29 -12715,492,76,0,28.0,2,3.0,3,4.0,45,4855717.0,,,1,1990-07-29 -12716,492,91,41,31.0,0,,33,0.0,0,,,,97,1990-07-29 -12717,492,148,42,34.0,0,,34,0.0,0,,,,97,1990-07-29 -12718,492,151,45,39.0,0,,35,0.0,0,,,,97,1990-07-29 -12719,492,111,26,26.0,24,,26,0.0,0,,,,2,1990-07-29 -12720,492,89,42,33.0,0,,32,0.0,0,,,,97,1990-07-29 -12721,492,144,21,19.0,9,2.0,2,6.0,45,4853684.0,,,1,1990-07-29 -12722,492,138,34,21.0,23,,25,0.0,0,,,,4,1990-07-29 -12723,492,150,31,12.0,20,,23,0.0,1,,,,8,1990-07-29 -12724,492,116,5,1.0,3,4.0,4,3.0,45,4892434.0,,,1,1990-07-29 -12725,492,118,2,6.0,5,5.0,5,2.0,45,4895192.0,,,1,1990-07-29 -12726,492,122,2,5.0,6,6.0,6,1.0,45,4928655.0,,,1,1990-07-29 -12727,492,121,40,16.0,10,7.0,7,0.0,44,,,,11,1990-07-29 -12728,492,117,31,11.0,16,8.0,8,0.0,44,,,,11,1990-07-29 -12729,492,132,20,10.0,18,9.0,9,0.0,44,,,,11,1990-07-29 -12730,492,77,26,25.0,22,10.0,10,0.0,43,,,,12,1990-07-29 -12731,492,54,24,4.0,8,11.0,11,0.0,40,,,,7,1990-07-29 -12732,492,130,33,8.0,17,,24,0.0,0,,,,8,1990-07-29 -12733,492,108,44,36.0,25,,12,0.0,39,,,,62,1990-07-29 -12734,492,87,32,30.0,11,,14,0.0,33,,,,8,1990-07-29 -12735,492,137,24,3.0,13,,15,0.0,24,,,,5,1990-07-29 -12736,492,136,21,20.0,7,,16,0.0,23,,,,5,1990-07-29 -12737,492,93,17,23.0,15,,17,0.0,20,,,,5,1990-07-29 -12738,492,147,44,35.0,26,,18,0.0,19,,,,20,1990-07-29 -12739,492,101,0,27.0,1,1.0,1,9.0,45,4847164.0,,,1,1990-07-29 -12740,492,126,40,15.0,14,,20,0.0,12,,,,5,1990-07-29 -12741,492,100,33,7.0,21,,21,0.0,12,,,,5,1990-07-29 -12742,492,104,20,9.0,19,,22,0.0,10,,,,5,1990-07-29 -12743,492,102,32,29.0,12,,13,0.0,35,,,,48,1990-07-29 -12744,492,94,5,2.0,4,,19,0.0,15,,,,41,1990-07-29 -12745,493,94,5,2.0,5,17.0,17,0.0,71,,,,4,1990-08-12 -12746,493,144,21,19.0,7,,18,0.0,64,,,,4,1990-08-12 -12747,493,101,0,27.0,4,2.0,2,6.0,77,6570885.0,,,1,1990-08-12 -12748,493,89,42,33.0,0,,33,0.0,0,,,,97,1990-08-12 -12749,493,91,41,31.0,0,,32,0.0,0,,,,97,1990-08-12 -12750,493,128,43,14.0,0,,31,0.0,0,,,,97,1990-08-12 -12751,493,147,44,35.0,0,,30,0.0,0,,,,81,1990-08-12 -12752,493,108,44,36.0,0,,29,0.0,0,,,,81,1990-08-12 -12753,493,100,33,7.0,0,,28,0.0,0,,,,81,1990-08-12 -12754,493,113,38,18.0,0,,27,0.0,0,,,,81,1990-08-12 -12755,493,109,34,22.0,10,,25,0.0,22,,,,5,1990-08-12 -12756,493,93,17,23.0,14,,24,0.0,35,,,,4,1990-08-12 -12757,493,130,33,8.0,20,,23,0.0,35,,,,5,1990-08-12 -12758,493,54,24,4.0,6,,22,0.0,36,,,,4,1990-08-12 -12759,493,116,5,1.0,8,,21,0.0,36,,,,6,1990-08-12 -12760,493,87,32,30.0,19,,20,0.0,37,,,,5,1990-08-12 -12761,493,121,40,16.0,16,,19,0.0,56,,,,6,1990-08-12 -12762,493,122,2,5.0,1,1.0,1,9.0,77,6570597.0,,,1,1990-08-12 -12763,493,148,42,34.0,0,,34,0.0,0,,,,97,1990-08-12 -12764,493,151,45,39.0,0,,35,0.0,0,,,,97,1990-08-12 -12765,493,137,24,3.0,15,,26,0.0,9,,,,23,1990-08-12 -12766,493,118,2,6.0,2,4.0,4,3.0,77,6602430.0,,,1,1990-08-12 -12767,493,117,31,11.0,11,5.0,5,2.0,77,6644841.0,,,1,1990-08-12 -12768,493,102,32,29.0,12,6.0,6,1.0,77,6654905.0,,,1,1990-08-12 -12769,493,150,31,12.0,18,7.0,7,0.0,76,,,,11,1990-08-12 -12770,493,132,20,10.0,26,9.0,9,0.0,76,,,,11,1990-08-12 -12771,493,138,34,21.0,13,10.0,10,0.0,76,,,,11,1990-08-12 -12772,493,77,26,25.0,25,11.0,11,0.0,76,,,,11,1990-08-12 -12773,493,126,40,15.0,17,8.0,8,0.0,76,,,,11,1990-08-12 -12774,493,98,38,17.0,24,13.0,13,0.0,74,,,,13,1990-08-12 -12775,493,111,26,26.0,21,14.0,14,0.0,74,,,,13,1990-08-12 -12776,493,146,17,24.0,23,15.0,15,0.0,74,,,,13,1990-08-12 -12777,493,76,0,28.0,3,16.0,16,0.0,72,,,,4,1990-08-12 -12778,493,104,20,9.0,22,12.0,12,0.0,75,,,,12,1990-08-12 -12779,493,136,21,20.0,9,3.0,3,4.0,77,6598490.0,,,1,1990-08-12 -12780,494,118,2,6.0,7,,22,0.0,18,,,,6,1990-08-26 -12781,494,77,26,25.0,21,14.0,14,0.0,42,,,,12,1990-08-26 -12782,494,138,34,21.0,17,,23,0.0,5,,,,47,1990-08-26 -12783,494,94,5,2.0,5,,21,0.0,19,,,,64,1990-08-26 -12784,494,122,2,5.0,4,,20,0.0,21,,,,7,1990-08-26 -12785,494,109,34,22.0,20,,19,0.0,27,,,,5,1990-08-26 -12786,494,100,33,7.0,24,,18,0.0,36,,,,10,1990-08-26 -12787,494,130,33,8.0,13,17.0,17,0.0,39,,,,5,1990-08-26 -12788,494,128,43,14.0,23,16.0,16,0.0,42,,,,12,1990-08-26 -12789,494,93,17,23.0,16,15.0,15,0.0,42,,,,12,1990-08-26 -12790,494,116,5,1.0,3,2.0,2,6.0,44,5195547.0,,,1,1990-08-26 -12791,494,150,31,12.0,22,12.0,12,0.0,43,,,,11,1990-08-26 -12792,494,117,31,11.0,18,11.0,11,0.0,43,,,,11,1990-08-26 -12793,494,132,20,10.0,19,10.0,10,0.0,43,,,,11,1990-08-26 -12794,494,102,32,29.0,15,9.0,9,0.0,43,,,,11,1990-08-26 -12795,494,101,0,27.0,1,1.0,1,9.0,44,5191997.0,,,1,1990-08-26 -12796,494,54,24,4.0,9,8.0,8,0.0,43,,,,11,1990-08-26 -12797,494,121,40,16.0,12,7.0,7,0.0,43,,,,11,1990-08-26 -12798,494,126,40,15.0,14,6.0,6,1.0,44,5300848.0,,,1,1990-08-26 -12799,494,137,24,3.0,10,,24,0.0,4,,,,5,1990-08-26 -12800,494,76,0,28.0,2,3.0,3,4.0,44,5220459.0,,,1,1990-08-26 -12801,494,104,20,9.0,26,13.0,13,0.0,43,,,,11,1990-08-26 -12802,494,87,32,30.0,11,,25,0.0,0,,,,3,1990-08-26 -12803,494,151,45,39.0,0,,33,0.0,0,,,,97,1990-08-26 -12804,494,111,26,26.0,0,,27,0.0,0,,,,81,1990-08-26 -12805,494,146,17,24.0,25,,26,0.0,0,,,,3,1990-08-26 -12806,494,144,21,19.0,6,4.0,4,3.0,44,5241334.0,,,1,1990-08-26 -12807,494,148,42,34.0,0,,32,0.0,0,,,,97,1990-08-26 -12808,494,136,21,20.0,8,5.0,5,2.0,44,5281647.0,,,1,1990-08-26 -12809,494,91,41,31.0,0,,30,0.0,0,,,,81,1990-08-26 -12810,494,113,38,18.0,0,,29,0.0,0,,,,81,1990-08-26 -12811,494,98,38,17.0,0,,28,0.0,0,,,,81,1990-08-26 -12812,494,89,42,33.0,0,,31,0.0,0,,,,97,1990-08-26 -12813,495,122,2,5.0,6,,20,0.0,18,,,,22,1990-09-09 -12814,495,117,31,11.0,12,,21,0.0,15,,,,8,1990-09-09 -12815,495,138,34,21.0,19,,22,0.0,14,,,,20,1990-09-09 -12816,495,150,31,12.0,11,,23,0.0,13,,,,5,1990-09-09 -12817,495,102,32,29.0,13,,24,0.0,10,,,,8,1990-09-09 -12818,495,93,17,23.0,15,,25,0.0,7,,,,22,1990-09-09 -12819,495,54,24,4.0,5,,26,0.0,4,,,,20,1990-09-09 -12820,495,146,17,24.0,0,,28,0.0,0,,,,81,1990-09-09 -12821,495,100,33,7.0,0,,29,0.0,0,,,,81,1990-09-09 -12822,495,91,41,31.0,0,,30,0.0,0,,,,81,1990-09-09 -12823,495,89,42,33.0,0,,31,0.0,0,,,,97,1990-09-09 -12824,495,148,42,34.0,0,,32,0.0,0,,,,97,1990-09-09 -12825,495,151,45,39.0,0,,33,0.0,0,,,,97,1990-09-09 -12826,495,98,38,17.0,0,,27,0.0,0,,,,81,1990-09-09 -12827,495,130,33,8.0,17,,19,0.0,21,,,,5,1990-09-09 -12828,495,128,43,14.0,23,,17,0.0,27,,,,67,1990-09-09 -12829,495,87,32,30.0,18,,16,0.0,36,,,,10,1990-09-09 -12830,495,113,38,18.0,24,,14,0.0,45,,,,62,1990-09-09 -12831,495,111,26,26.0,20,13.0,13,0.0,50,,,,13,1990-09-09 -12832,495,104,20,9.0,22,12.0,12,0.0,50,,,,20,1990-09-09 -12833,495,77,26,25.0,26,11.0,11,0.0,51,,,,12,1990-09-09 -12834,495,109,34,22.0,25,10.0,10,0.0,51,,,,12,1990-09-09 -12835,495,132,20,10.0,21,9.0,9,0.0,51,,,,12,1990-09-09 -12836,495,144,21,19.0,8,8.0,8,0.0,52,,,,11,1990-09-09 -12837,495,136,21,20.0,9,7.0,7,0.0,52,,,,11,1990-09-09 -12838,495,137,24,3.0,14,6.0,6,1.0,52,,,,11,1990-09-09 -12839,495,118,2,6.0,7,5.0,5,2.0,52,4763152.0,,,1,1990-09-09 -12840,495,94,5,2.0,4,4.0,4,3.0,53,4734097.0,,,1,1990-09-09 -12841,495,116,5,1.0,2,2.0,2,6.0,53,4683932.0,,,1,1990-09-09 -12842,495,101,0,27.0,1,1.0,1,9.0,53,4677878.0,,,1,1990-09-09 -12843,495,126,40,15.0,10,,18,0.0,24,,,,5,1990-09-09 -12844,495,121,40,16.0,16,,15,0.0,36,,,,5,1990-09-09 -12845,495,76,0,28.0,3,3.0,3,4.0,53,4685282.0,,,1,1990-09-09 -12846,496,102,32,29.0,10,,20,0.0,24,,,,6,1990-09-23 -12847,496,111,26,26.0,20,,16,0.0,52,,,,3,1990-09-23 -12848,496,138,34,21.0,13,15.0,15,0.0,58,,,,13,1990-09-23 -12849,496,87,32,30.0,11,14.0,14,0.0,58,,,,3,1990-09-23 -12850,496,126,40,15.0,14,12.0,12,0.0,59,,,,12,1990-09-23 -12851,496,93,17,23.0,16,11.0,11,0.0,59,,,,12,1990-09-23 -12852,496,77,26,25.0,22,10.0,10,0.0,59,,,,12,1990-09-23 -12853,496,104,20,9.0,19,9.0,9,0.0,60,,,,11,1990-09-23 -12854,496,54,24,4.0,8,8.0,8,0.0,60,,,,11,1990-09-23 -12855,496,118,2,6.0,5,7.0,7,0.0,60,,,,11,1990-09-23 -12856,496,144,21,19.0,9,6.0,6,1.0,61,4989263.0,,,1,1990-09-23 -12857,496,136,21,20.0,6,5.0,5,2.0,61,4988432.0,,,1,1990-09-23 -12858,496,76,0,28.0,4,4.0,4,3.0,61,4936910.0,,,1,1990-09-23 -12859,496,116,5,1.0,2,3.0,3,4.0,61,4935203.0,,,1,1990-09-23 -12860,496,101,0,27.0,3,2.0,2,6.0,61,4933822.0,,,1,1990-09-23 -12861,496,94,5,2.0,1,1.0,1,9.0,61,4931014.0,,,1,1990-09-23 -12862,496,100,33,7.0,25,,17,0.0,52,,,,6,1990-09-23 -12863,496,121,40,16.0,12,,18,0.0,51,,,,5,1990-09-23 -12864,496,132,20,10.0,17,13.0,13,0.0,58,,,,3,1990-09-23 -12865,496,151,45,39.0,0,,33,0.0,0,,,,97,1990-09-23 -12866,496,122,2,5.0,7,,19,0.0,30,,,,5,1990-09-23 -12867,496,148,42,34.0,0,,32,0.0,0,,,,97,1990-09-23 -12868,496,89,42,33.0,0,,31,0.0,0,,,,97,1990-09-23 -12869,496,91,41,31.0,0,,30,0.0,0,,,,81,1990-09-23 -12870,496,98,38,17.0,0,,29,0.0,0,,,,81,1990-09-23 -12871,496,128,43,14.0,0,,27,0.0,0,,,,81,1990-09-23 -12872,496,146,17,24.0,0,,28,0.0,0,,,,81,1990-09-23 -12873,496,109,34,22.0,18,,25,0.0,0,,,,20,1990-09-23 -12874,496,113,38,18.0,24,,24,0.0,3,,,,86,1990-09-23 -12875,496,117,31,11.0,21,,23,0.0,5,,,,37,1990-09-23 -12876,496,150,31,12.0,15,,22,0.0,14,,,,91,1990-09-23 -12877,496,130,33,8.0,23,,21,0.0,21,,,,6,1990-09-23 -12878,496,137,24,3.0,0,,26,0.0,0,,,,54,1990-09-23 -12879,497,117,31,11.0,10,,11,0.0,63,,,,6,1990-09-30 -12880,497,136,21,20.0,8,,15,0.0,47,,,,84,1990-09-30 -12881,497,101,0,27.0,1,,14,0.0,53,,,,21,1990-09-30 -12882,497,76,0,28.0,5,,13,0.0,56,,,,4,1990-09-30 -12883,497,121,40,16.0,19,,12,0.0,59,,,,68,1990-09-30 -12884,497,104,20,9.0,25,10.0,10,0.0,71,,,,12,1990-09-30 -12885,497,118,2,6.0,6,5.0,5,2.0,73,6538991.0,,,1,1990-09-30 -12886,497,126,40,15.0,12,8.0,8,0.0,72,,,,11,1990-09-30 -12887,497,77,26,25.0,20,7.0,7,0.0,72,,,,11,1990-09-30 -12888,497,87,32,30.0,15,6.0,6,1.0,73,6545189.0,,,1,1990-09-30 -12889,497,94,5,2.0,3,2.0,2,6.0,73,6503525.0,,,1,1990-09-30 -12890,497,116,5,1.0,2,1.0,1,9.0,73,6481461.0,,,1,1990-09-30 -12891,497,109,34,22.0,17,,16,0.0,47,,,,5,1990-09-30 -12892,497,113,38,18.0,23,9.0,9,0.0,72,,,,11,1990-09-30 -12893,497,144,21,19.0,9,3.0,3,4.0,73,6516335.0,,,1,1990-09-30 -12894,497,128,43,14.0,21,,17,0.0,45,,,,67,1990-09-30 -12895,497,111,26,26.0,13,,19,0.0,22,,,,20,1990-09-30 -12896,497,93,17,23.0,11,,18,0.0,41,,,,20,1990-09-30 -12897,497,151,45,39.0,0,,33,0.0,0,,,,97,1990-09-30 -12898,497,148,42,34.0,0,,32,0.0,0,,,,97,1990-09-30 -12899,497,89,42,33.0,0,,31,0.0,0,,,,97,1990-09-30 -12900,497,91,41,31.0,0,,30,0.0,0,,,,81,1990-09-30 -12901,497,145,20,10.0,0,,29,0.0,0,,,,81,1990-09-30 -12902,497,146,17,24.0,0,,28,0.0,0,,,,81,1990-09-30 -12903,497,122,2,5.0,7,4.0,4,3.0,73,6524757.0,,,1,1990-09-30 -12904,497,150,31,12.0,0,,26,0.0,0,,,,73,1990-09-30 -12905,497,138,34,21.0,16,,25,0.0,0,,,,37,1990-09-30 -12906,497,54,24,4.0,4,,24,0.0,0,,,,20,1990-09-30 -12907,497,130,33,8.0,24,,23,0.0,5,,,,4,1990-09-30 -12908,497,98,38,17.0,22,,22,0.0,5,,,,5,1990-09-30 -12909,497,137,24,3.0,14,,21,0.0,13,,,,20,1990-09-30 -12910,497,100,33,7.0,0,,27,0.0,0,,,,81,1990-09-30 -12911,497,102,32,29.0,18,,20,0.0,20,,,,6,1990-09-30 -12912,498,109,34,22.0,26,,19,0.0,13,,,,20,1990-10-21 -12913,498,126,40,15.0,16,,20,0.0,5,,,,5,1990-10-21 -12914,498,100,33,7.0,21,,21,0.0,5,,,,8,1990-10-21 -12915,498,76,0,28.0,4,,22,0.0,1,,,,20,1990-10-21 -12916,498,101,0,27.0,1,,23,0.0,0,,,,4,1990-10-21 -12917,498,54,24,4.0,7,,26,0.0,0,,,,54,1990-10-21 -12918,498,130,33,8.0,22,,25,0.0,0,,,,4,1990-10-21 -12919,498,121,40,16.0,13,,18,0.0,16,,,,80,1990-10-21 -12920,498,128,43,14.0,0,,27,0.0,0,,,,81,1990-10-21 -12921,498,98,38,17.0,0,,28,0.0,0,,,,81,1990-10-21 -12922,498,113,38,18.0,0,,29,0.0,0,,,,81,1990-10-21 -12923,498,91,41,31.0,0,,30,0.0,0,,,,81,1990-10-21 -12924,498,116,5,1.0,2,,24,0.0,0,,,,4,1990-10-21 -12925,498,80,17,24.0,20,,17,0.0,18,,,,20,1990-10-21 -12926,498,94,5,2.0,3,,14,0.0,26,,,,7,1990-10-21 -12927,498,138,34,21.0,19,,15,0.0,24,,,,91,1990-10-21 -12928,498,104,20,9.0,24,,13,0.0,28,,,,5,1990-10-21 -12929,498,64,31,12.0,12,,12,0.0,31,,,,5,1990-10-21 -12930,498,117,31,11.0,11,,11,0.0,38,,,,6,1990-10-21 -12931,498,111,26,26.0,25,10.0,10,0.0,52,,,,11,1990-10-21 -12932,498,93,17,23.0,10,8.0,8,0.0,52,,,,11,1990-10-21 -12933,498,77,26,25.0,17,7.0,7,0.0,52,,,,11,1990-10-21 -12934,498,137,24,3.0,14,6.0,6,1.0,53,5749174.0,,,1,1990-10-21 -12935,498,122,2,5.0,5,5.0,5,2.0,53,5723708.0,,,1,1990-10-21 -12936,498,118,2,6.0,7,4.0,4,3.0,53,5713082.0,,,1,1990-10-21 -12937,498,87,32,30.0,9,3.0,3,4.0,53,5699293.0,,,1,1990-10-21 -12938,498,89,21,19.0,8,2.0,2,6.0,53,5684047.0,,,1,1990-10-21 -12939,498,136,21,20.0,6,1.0,1,9.0,53,5676824.0,,,1,1990-10-21 -12940,498,102,32,29.0,18,,16,0.0,24,,,,5,1990-10-21 -12941,498,132,20,10.0,23,9.0,9,0.0,52,,,,11,1990-10-21 -12942,499,136,21,20.0,7,1.0,1,9.0,81,6584570.0,,,1,1990-11-04 -12943,499,116,5,1.0,4,3.0,3,4.0,81,6621829.0,,,1,1990-11-04 -12944,499,91,41,31.0,0,,30,0.0,0,,,,81,1990-11-04 -12945,499,76,0,28.0,2,4.0,4,3.0,81,6631432.0,,,1,1990-11-04 -12946,499,122,2,5.0,9,5.0,5,2.0,81,6695730.0,,,1,1990-11-04 -12947,499,118,2,6.0,6,6.0,6,1.0,80,,,,11,1990-11-04 -12948,499,89,21,19.0,8,7.0,7,0.0,80,,,,11,1990-11-04 -12949,499,54,24,4.0,5,8.0,8,0.0,80,,,,11,1990-11-04 -12950,499,93,17,23.0,10,9.0,9,0.0,79,,,,12,1990-11-04 -12951,499,77,26,25.0,12,10.0,10,0.0,79,,,,12,1990-11-04 -12952,499,111,26,26.0,19,11.0,11,0.0,78,,,,13,1990-11-04 -12953,499,130,33,8.0,17,12.0,12,0.0,77,,,,14,1990-11-04 -12954,499,128,43,14.0,22,13.0,13,0.0,74,,,,17,1990-11-04 -12955,499,138,34,21.0,21,,14,0.0,68,,,,5,1990-11-04 -12956,499,101,0,27.0,1,,15,0.0,61,,,,20,1990-11-04 -12957,499,98,38,17.0,26,,16,0.0,58,,,,5,1990-11-04 -12958,499,94,5,2.0,3,2.0,2,6.0,81,6587699.0,,,1,1990-11-04 -12959,499,137,24,3.0,13,,18,0.0,53,,,,20,1990-11-04 -12960,499,64,31,12.0,18,,17,0.0,57,,,,8,1990-11-04 -12961,499,132,20,10.0,0,,29,0.0,0,,,,81,1990-11-04 -12962,499,113,38,18.0,0,,28,0.0,0,,,,81,1990-11-04 -12963,499,87,32,30.0,24,,26,0.0,6,,,,7,1990-11-04 -12964,499,100,33,7.0,25,,25,0.0,18,,,,20,1990-11-04 -12965,499,104,20,9.0,0,,27,0.0,0,,,,81,1990-11-04 -12966,499,102,32,29.0,23,,23,0.0,21,,,,6,1990-11-04 -12967,499,109,34,22.0,15,,22,0.0,23,,,,10,1990-11-04 -12968,499,126,40,15.0,16,,21,0.0,27,,,,23,1990-11-04 -12969,499,117,31,11.0,11,,20,0.0,43,,,,6,1990-11-04 -12970,499,121,40,16.0,14,,19,0.0,46,,,,37,1990-11-04 -12971,499,80,17,24.0,20,,24,0.0,20,,,,6,1990-11-04 -12972,500,138,34,21.0,9,,23,0.0,16,,,,6,1991-03-10 -12973,500,76,0,2.0,7,,19,0.0,36,,,,48,1991-03-10 -12974,500,94,2,5.0,4,,20,0.0,35,,,,6,1991-03-10 -12975,500,126,40,15.0,23,,21,0.0,34,,,,6,1991-03-10 -12976,500,86,33,8.0,24,,22,0.0,32,,,,20,1991-03-10 -12977,500,80,17,24.0,26,,24,0.0,15,,,,6,1991-03-10 -12978,500,140,31,12.0,0,,30,0.0,0,,,,81,1991-03-10 -12979,500,102,32,29.0,19,,26,0.0,4,,,,5,1991-03-10 -12980,500,132,28,10.0,0,,27,0.0,0,,,,81,1991-03-10 -12981,500,139,38,18.0,0,,28,0.0,0,,,,81,1991-03-10 -12982,500,99,26,26.0,0,,29,0.0,0,,,,81,1991-03-10 -12983,500,122,26,25.0,20,,18,0.0,40,,,,5,1991-03-10 -12984,500,141,41,31.0,0,,32,0.0,0,,,,97,1991-03-10 -12985,500,108,34,22.0,10,,25,0.0,12,,,,6,1991-03-10 -12986,500,121,40,16.0,18,,17,0.0,40,,,,6,1991-03-10 -12987,500,91,16,32.0,14,10.0,10,0.0,75,,,,5,1991-03-10 -12988,500,89,21,19.0,8,,15,0.0,49,,,,4,1991-03-10 -12989,500,101,0,1.0,1,1.0,1,10.0,81,7247828.0,,,1,1991-03-10 -12990,500,116,5,27.0,2,2.0,2,6.0,81,7264150.0,,,1,1991-03-10 -12991,500,136,21,20.0,5,3.0,3,4.0,81,7325204.0,,,1,1991-03-10 -12992,500,127,39,35.0,0,,34,0.0,0,,,,97,1991-03-10 -12993,500,130,24,4.0,11,4.0,4,3.0,81,7333237.0,,,1,1991-03-10 -12994,500,137,24,3.0,16,5.0,5,2.0,80,,,,11,1991-03-10 -12995,500,104,28,9.0,25,,16,0.0,41,,,,5,1991-03-10 -12996,500,87,32,30.0,21,6.0,6,1.0,79,,,,12,1991-03-10 -12997,500,98,38,17.0,22,8.0,8,0.0,77,,,,14,1991-03-10 -12998,500,93,17,23.0,15,9.0,9,0.0,75,,,,5,1991-03-10 -12999,500,83,33,7.0,12,11.0,11,0.0,73,,,,18,1991-03-10 -13000,500,54,5,28.0,6,12.0,12,0.0,72,,,,6,1991-03-10 -13001,500,56,31,11.0,13,13.0,13,0.0,59,,,,5,1991-03-10 -13002,500,118,2,6.0,3,,14,0.0,49,,,,6,1991-03-10 -13003,500,77,39,34.0,17,7.0,7,0.0,78,,,,13,1991-03-10 -13004,500,128,35,14.0,0,,33,0.0,0,,,,97,1991-03-10 -13005,500,109,16,33.0,0,,31,0.0,0,,,,97,1991-03-10 -13006,501,76,0,2.0,4,3.0,3,4.0,71,5913544.0,,,1,1991-03-24 -13007,501,132,28,10.0,0,,27,0.0,0,,,,81,1991-03-24 -13008,501,116,5,27.0,6,4.0,4,3.0,71,5926497.0,,,1,1991-03-24 -13009,501,136,21,20.0,7,5.0,5,2.0,71,5930088.0,,,1,1991-03-24 -13010,501,54,5,28.0,5,6.0,6,1.0,71,5931769.0,,,1,1991-03-24 -13011,501,89,21,19.0,14,7.0,7,0.0,70,,,,11,1991-03-24 -13012,501,80,17,24.0,21,8.0,8,0.0,69,,,,12,1991-03-24 -13013,501,56,31,11.0,22,9.0,9,0.0,68,,,,13,1991-03-24 -13014,501,122,26,25.0,18,10.0,10,0.0,68,,,,13,1991-03-24 -13015,501,138,34,21.0,12,11.0,11,0.0,68,,,,13,1991-03-24 -13016,501,83,33,7.0,26,12.0,12,0.0,67,,,,14,1991-03-24 -13017,501,91,16,32.0,10,13.0,13,0.0,63,,,,69,1991-03-24 -13018,501,94,2,5.0,3,,14,0.0,59,,,,6,1991-03-24 -13019,501,99,26,26.0,23,,15,0.0,50,,,,5,1991-03-24 -13020,501,93,17,23.0,20,,16,0.0,47,,,,20,1991-03-24 -13021,501,118,2,6.0,2,2.0,2,6.0,71,5911119.0,,,1,1991-03-24 -13022,501,86,33,8.0,25,,17,0.0,34,,,,5,1991-03-24 -13023,501,108,34,22.0,19,,19,0.0,22,,,,10,1991-03-24 -13024,501,109,16,33.0,13,,20,0.0,20,,,,5,1991-03-24 -13025,501,130,24,4.0,9,,21,0.0,19,,,,6,1991-03-24 -13026,501,121,40,16.0,15,,22,0.0,16,,,,7,1991-03-24 -13027,501,137,24,3.0,16,,23,0.0,12,,,,20,1991-03-24 -13028,501,126,40,15.0,8,,24,0.0,9,,,,68,1991-03-24 -13029,501,98,38,17.0,24,,25,0.0,0,,,,22,1991-03-24 -13030,501,141,41,31.0,0,,34,0.0,0,,,,97,1991-03-24 -13031,501,77,39,34.0,0,,33,0.0,0,,,,97,1991-03-24 -13032,501,127,39,35.0,0,,32,0.0,0,,,,97,1991-03-24 -13033,501,128,35,14.0,0,,31,0.0,0,,,,97,1991-03-24 -13034,501,140,31,12.0,0,,30,0.0,0,,,,81,1991-03-24 -13035,501,104,28,9.0,0,,29,0.0,0,,,,81,1991-03-24 -13036,501,139,38,18.0,0,,28,0.0,0,,,,81,1991-03-24 -13037,501,102,32,29.0,11,,18,0.0,33,,,,21,1991-03-24 -13038,501,101,0,1.0,1,1.0,1,10.0,71,5908128.0,,,1,1991-03-24 -13039,501,87,32,30.0,17,,26,0.0,0,,,,48,1991-03-24 -13040,502,109,16,33.0,11,,15,0.0,37,,,,6,1991-04-28 -13041,502,138,34,21.0,0,,31,0.0,0,,,,97,1991-04-28 -13042,502,104,28,9.0,0,,30,0.0,0,,,,81,1991-04-28 -13043,502,132,28,10.0,0,,29,0.0,0,,,,81,1991-04-28 -13044,502,101,0,1.0,1,1.0,1,10.0,61,5714750.0,,,1,1991-04-28 -13045,502,76,0,2.0,5,2.0,2,6.0,61,5716425.0,,,1,1991-04-28 -13046,502,108,34,22.0,16,3.0,3,4.0,60,,,,11,1991-04-28 -13047,502,93,17,23.0,9,4.0,4,3.0,59,,,,12,1991-04-28 -13048,502,56,31,11.0,25,5.0,5,2.0,58,,,,13,1991-04-28 -13049,502,140,31,12.0,26,6.0,6,1.0,58,,,,13,1991-04-28 -13050,502,122,26,25.0,24,7.0,7,0.0,58,,,,13,1991-04-28 -13051,502,86,33,8.0,23,8.0,8,0.0,58,,,,13,1991-04-28 -13052,502,127,39,35.0,21,9.0,9,0.0,57,,,,60,1991-04-28 -13053,502,99,26,26.0,19,10.0,10,0.0,57,,,,14,1991-04-28 -13054,502,128,35,14.0,0,,32,0.0,0,,,,97,1991-04-28 -13055,502,83,33,7.0,18,11.0,11,0.0,57,,,,14,1991-04-28 -13056,502,89,21,19.0,13,13.0,13,0.0,54,,,,5,1991-04-28 -13057,502,130,24,4.0,6,,14,0.0,41,,,,7,1991-04-28 -13058,502,119,38,18.0,0,,28,0.0,0,,,,81,1991-04-28 -13059,502,91,16,32.0,13,,16,0.0,37,,,,22,1991-04-28 -13060,502,121,40,16.0,22,,17,0.0,24,,,,20,1991-04-28 -13061,502,102,25,29.0,17,,18,0.0,17,,,,5,1991-04-28 -13062,502,118,2,6.0,2,,19,0.0,17,,,,10,1991-04-28 -13063,502,137,24,3.0,10,,20,0.0,15,,,,7,1991-04-28 -13064,502,80,17,24.0,8,,21,0.0,10,,,,6,1991-04-28 -13065,502,54,5,28.0,7,,22,0.0,2,,,,20,1991-04-28 -13066,502,87,25,30.0,20,,23,0.0,2,,,,20,1991-04-28 -13067,502,136,21,20.0,14,,24,0.0,1,,,,20,1991-04-28 -13068,502,94,2,5.0,4,,25,0.0,0,,,,4,1991-04-28 -13069,502,126,40,15.0,15,12.0,12,0.0,55,,,,5,1991-04-28 -13070,502,116,5,27.0,3,,26,0.0,0,,,,20,1991-04-28 -13071,502,77,39,34.0,0,,33,0.0,0,,,,97,1991-04-28 -13072,502,98,38,17.0,0,,27,0.0,0,,,,81,1991-04-28 -13073,502,141,41,31.0,0,,34,0.0,0,,,,97,1991-04-28 -13074,503,132,28,10.0,0,,29,0.0,0,,,,81,1991-05-12 -13075,503,119,38,18.0,0,,28,0.0,0,,,,81,1991-05-12 -13076,503,140,31,12.0,0,,27,0.0,0,,,,81,1991-05-12 -13077,503,136,21,20.0,4,,26,0.0,0,,,,22,1991-05-12 -13078,503,76,0,2.0,6,,25,0.0,9,,,,20,1991-05-12 -13079,503,98,38,17.0,24,,24,0.0,9,,,,6,1991-05-12 -13080,503,121,40,16.0,18,,23,0.0,12,,,,23,1991-05-12 -13081,503,109,16,33.0,10,,22,0.0,21,,,,37,1991-05-12 -13082,503,87,25,30.0,20,,21,0.0,24,,,,5,1991-05-12 -13083,503,137,24,3.0,11,,20,0.0,35,,,,20,1991-05-12 -13084,503,104,28,9.0,22,,19,0.0,39,,,,5,1991-05-12 -13085,503,86,33,8.0,19,,18,0.0,41,,,,20,1991-05-12 -13086,503,118,2,6.0,3,,17,0.0,42,,,,20,1991-05-12 -13087,503,101,0,1.0,1,1.0,1,10.0,78,6782334.0,,,1,1991-05-12 -13088,503,127,39,35.0,0,,32,0.0,0,,,,97,1991-05-12 -13089,503,56,31,11.0,25,,13,0.0,64,,,,44,1991-05-12 -13090,503,93,17,23.0,14,12.0,12,0.0,72,,,,16,1991-05-12 -13091,503,108,34,22.0,21,11.0,11,0.0,75,,,,13,1991-05-12 -13092,503,99,26,26.0,26,10.0,10,0.0,76,,,,12,1991-05-12 -13093,503,102,25,29.0,13,9.0,9,0.0,76,,,,12,1991-05-12 -13094,503,91,16,32.0,23,8.0,8,0.0,76,,,,12,1991-05-12 -13095,503,122,26,25.0,16,7.0,7,0.0,76,,,,12,1991-05-12 -13096,503,138,34,21.0,12,6.0,6,1.0,77,,,,11,1991-05-12 -13097,503,116,5,27.0,7,5.0,5,2.0,77,,,,11,1991-05-12 -13098,503,89,21,19.0,8,4.0,4,3.0,77,,,,11,1991-05-12 -13099,503,54,5,28.0,9,3.0,3,4.0,78,6829789.0,,,1,1991-05-12 -13100,503,94,2,5.0,5,2.0,2,6.0,78,6800682.0,,,1,1991-05-12 -13101,503,126,40,15.0,15,,15,0.0,43,,,,37,1991-05-12 -13102,503,130,24,4.0,2,,16,0.0,42,,,,5,1991-05-12 -13103,503,80,17,24.0,17,,14,0.0,49,,,,6,1991-05-12 -13104,503,141,41,31.0,0,,33,0.0,0,,,,97,1991-05-12 -13105,503,83,33,7.0,0,,30,0.0,0,,,,81,1991-05-12 -13106,503,77,39,34.0,0,,31,0.0,0,,,,97,1991-05-12 -13107,503,128,35,14.0,0,,34,0.0,0,,,,97,1991-05-12 -13108,504,130,24,4.0,9,2.0,2,6.0,69,5963322.0,,,1,1991-06-02 -13109,504,83,33,7.0,20,,21,0.0,21,,,,5,1991-06-02 -13110,504,80,17,24.0,15,,22,0.0,20,,,,20,1991-06-02 -13111,504,89,21,19.0,5,,23,0.0,10,,,,22,1991-06-02 -13112,504,76,0,2.0,6,,24,0.0,4,,,,98,1991-06-02 -13113,504,87,25,30.0,22,,25,0.0,3,,,,95,1991-06-02 -13114,504,104,28,9.0,21,,26,0.0,2,,,,37,1991-06-02 -13115,504,119,38,18.0,0,,27,0.0,0,,,,81,1991-06-02 -13116,504,86,33,8.0,0,,29,0.0,0,,,,81,1991-06-02 -13117,504,64,31,12.0,0,,30,0.0,0,,,,81,1991-06-02 -13118,504,128,35,14.0,0,,31,0.0,0,,,,97,1991-06-02 -13119,504,77,39,34.0,0,,32,0.0,0,,,,97,1991-06-02 -13120,504,127,39,35.0,0,,33,0.0,0,,,,97,1991-06-02 -13121,504,141,41,31.0,0,,34,0.0,0,,,,97,1991-06-02 -13122,504,98,38,17.0,0,,28,0.0,0,,,,81,1991-06-02 -13123,504,56,31,11.0,24,,20,0.0,21,,,,20,1991-06-02 -13124,504,122,26,25.0,16,,18,0.0,27,,,,5,1991-06-02 -13125,504,102,25,29.0,19,,16,0.0,29,,,,6,1991-06-02 -13126,504,54,5,28.0,7,,15,0.0,34,,,,5,1991-06-02 -13127,504,121,40,16.0,13,,14,0.0,42,,,,5,1991-06-02 -13128,504,139,28,10.0,25,,13,0.0,48,,,,37,1991-06-02 -13129,504,108,34,22.0,17,,12,0.0,50,,,,5,1991-06-02 -13130,504,126,40,15.0,23,,11,0.0,61,,,,5,1991-06-02 -13131,504,137,24,3.0,12,10.0,10,0.0,67,,,,12,1991-06-02 -13132,504,138,34,21.0,10,9.0,9,0.0,68,,,,11,1991-06-02 -13133,504,99,26,26.0,26,8.0,8,0.0,68,,,,11,1991-06-02 -13134,504,93,17,23.0,18,7.0,7,0.0,68,,,,11,1991-06-02 -13135,504,94,2,5.0,2,6.0,6,1.0,68,,,,10,1991-06-02 -13136,504,91,16,32.0,14,5.0,5,2.0,69,6013841.0,,,1,1991-06-02 -13137,504,109,16,33.0,11,4.0,4,3.0,69,6011700.0,,,1,1991-06-02 -13138,504,118,2,6.0,1,3.0,3,4.0,69,5973707.0,,,1,1991-06-02 -13139,504,136,21,20.0,8,1.0,1,10.0,69,5931490.0,,,1,1991-06-02 -13140,504,116,5,27.0,4,,17,0.0,27,,,,6,1991-06-02 -13141,504,101,0,1.0,3,,19,0.0,25,,,,91,1991-06-02 -13142,505,127,39,35.0,0,,32,0.0,0,,,,97,1991-06-16 -13143,505,94,2,5.0,2,2.0,2,6.0,67,5393541.0,,,1,1991-06-16 -13144,505,101,0,1.0,3,3.0,3,4.0,67,5449561.0,,,1,1991-06-16 -13145,505,109,16,33.0,11,4.0,4,3.0,66,,,,11,1991-06-16 -13146,505,89,21,19.0,9,5.0,5,2.0,66,,,,11,1991-06-16 -13147,505,102,25,29.0,23,6.0,6,1.0,66,,,,11,1991-06-16 -13148,505,80,17,24.0,14,7.0,7,0.0,66,,,,11,1991-06-16 -13149,505,122,26,25.0,10,8.0,8,0.0,65,,,,12,1991-06-16 -13150,505,56,31,11.0,24,9.0,9,0.0,65,,,,12,1991-06-16 -13151,505,64,31,12.0,25,10.0,10,0.0,65,,,,12,1991-06-16 -13152,505,130,24,4.0,8,11.0,11,0.0,65,,,,12,1991-06-16 -13153,505,137,24,3.0,13,12.0,12,0.0,64,,,,13,1991-06-16 -13154,505,86,33,8.0,12,,13,0.0,54,,,,5,1991-06-16 -13155,505,91,16,32.0,20,,14,0.0,51,,,,20,1991-06-16 -13156,505,87,25,30.0,19,,15,0.0,48,,,,6,1991-06-16 -13157,505,136,21,20.0,6,,16,0.0,44,,,,67,1991-06-16 -13158,505,54,5,28.0,4,,17,0.0,42,,,,8,1991-06-16 -13159,505,108,34,22.0,16,,18,0.0,30,,,,5,1991-06-16 -13160,505,104,28,9.0,26,,19,0.0,24,,,,5,1991-06-16 -13161,505,83,33,7.0,17,,20,0.0,20,,,,36,1991-06-16 -13162,505,121,40,16.0,22,,21,0.0,19,,,,5,1991-06-16 -13163,505,116,5,27.0,7,,22,0.0,16,,,,91,1991-06-16 -13164,505,126,40,15.0,18,,23,0.0,15,,,,5,1991-06-16 -13165,505,128,35,14.0,21,,24,0.0,13,,,,5,1991-06-16 -13166,505,76,0,2.0,5,,25,0.0,5,,,,5,1991-06-16 -13167,505,93,17,23.0,15,,26,0.0,4,,,,20,1991-06-16 -13168,505,99,26,26.0,0,,27,0.0,0,,,,81,1991-06-16 -13169,505,98,38,17.0,0,,28,0.0,0,,,,81,1991-06-16 -13170,505,118,2,6.0,1,1.0,1,10.0,67,5392205.0,,,1,1991-06-16 -13171,505,139,28,10.0,0,,29,0.0,0,,,,81,1991-06-16 -13172,505,119,38,18.0,0,,30,0.0,0,,,,81,1991-06-16 -13173,505,141,41,31.0,0,,33,0.0,0,,,,97,1991-06-16 -13174,505,138,34,21.0,0,,34,0.0,0,,,,97,1991-06-16 -13175,505,77,39,34.0,0,,31,0.0,0,,,,97,1991-06-16 -13176,506,56,31,11.0,0,,27,0.0,0,,,,81,1991-07-07 -13177,506,99,26,26.0,14,11.0,11,0.0,70,,,,12,1991-07-07 -13178,506,64,31,12.0,20,10.0,10,0.0,70,,,,12,1991-07-07 -13179,506,93,17,23.0,12,9.0,9,0.0,70,,,,12,1991-07-07 -13180,506,136,21,20.0,7,8.0,8,0.0,70,,,,12,1991-07-07 -13181,506,126,40,15.0,9,7.0,7,0.0,70,,,,12,1991-07-07 -13182,506,109,16,33.0,13,6.0,6,1.0,71,,,,11,1991-07-07 -13183,506,118,2,6.0,1,5.0,5,2.0,71,,,,11,1991-07-07 -13184,506,54,5,28.0,6,4.0,4,3.0,72,5915976.0,,,1,1991-07-07 -13185,506,101,0,1.0,3,3.0,3,4.0,72,5914990.0,,,1,1991-07-07 -13186,506,116,5,27.0,2,2.0,2,6.0,72,5885059.0,,,1,1991-07-07 -13187,506,94,2,5.0,4,1.0,1,10.0,72,5880056.0,,,1,1991-07-07 -13188,506,122,26,25.0,16,12.0,12,0.0,69,,,,13,1991-07-07 -13189,506,89,21,19.0,8,,13,0.0,63,,,,68,1991-07-07 -13190,506,130,24,4.0,11,,14,0.0,57,,,,6,1991-07-07 -13191,506,128,35,14.0,21,,15,0.0,47,,,,44,1991-07-07 -13192,506,98,38,17.0,0,,29,0.0,0,,,,81,1991-07-07 -13193,506,76,0,2.0,5,,25,0.0,6,,,,5,1991-07-07 -13194,506,121,40,16.0,15,,24,0.0,7,,,,20,1991-07-07 -13195,506,80,17,24.0,10,,23,0.0,8,,,,4,1991-07-07 -13196,506,139,28,10.0,0,,30,0.0,0,,,,81,1991-07-07 -13197,506,138,34,21.0,0,,31,0.0,0,,,,97,1991-07-07 -13198,506,119,38,18.0,0,,28,0.0,0,,,,81,1991-07-07 -13199,506,77,39,34.0,0,,32,0.0,0,,,,97,1991-07-07 -13200,506,141,41,31.0,0,,34,0.0,0,,,,97,1991-07-07 -13201,506,104,28,9.0,25,,20,0.0,31,,,,6,1991-07-07 -13202,506,87,25,30.0,22,,19,0.0,32,,,,7,1991-07-07 -13203,506,86,33,8.0,17,,18,0.0,36,,,,20,1991-07-07 -13204,506,108,34,22.0,26,,17,0.0,39,,,,27,1991-07-07 -13205,506,102,25,29.0,23,,16,0.0,43,,,,7,1991-07-07 -13206,506,127,39,35.0,0,,33,0.0,0,,,,97,1991-07-07 -13207,506,91,16,32.0,19,,26,0.0,0,,,,20,1991-07-07 -13208,506,83,33,7.0,24,,21,0.0,21,,,,6,1991-07-07 -13209,506,137,24,3.0,18,,22,0.0,12,,,,20,1991-07-07 -13210,507,141,41,31.0,0,,34,0.0,0,,,,97,1991-07-14 -13211,507,101,0,1.0,2,4.0,4,3.0,58,,,,60,1991-07-14 -13212,507,136,21,20.0,8,5.0,5,2.0,58,,,,11,1991-07-14 -13213,507,91,16,32.0,17,6.0,6,1.0,58,,,,11,1991-07-14 -13214,507,130,24,4.0,10,7.0,7,0.0,58,,,,11,1991-07-14 -13215,507,137,24,3.0,15,8.0,8,0.0,58,,,,11,1991-07-14 -13216,507,93,17,23.0,23,9.0,9,0.0,58,,,,11,1991-07-14 -13217,507,138,34,21.0,18,10.0,10,0.0,57,,,,12,1991-07-14 -13218,507,80,17,24.0,20,11.0,11,0.0,57,,,,12,1991-07-14 -13219,507,128,35,14.0,0,,31,0.0,0,,,,97,1991-07-14 -13220,507,77,39,34.0,0,,32,0.0,0,,,,97,1991-07-14 -13221,507,56,31,11.0,25,12.0,12,0.0,57,,,,12,1991-07-14 -13222,507,127,39,35.0,0,,33,0.0,0,,,,97,1991-07-14 -13223,507,108,34,22.0,11,13.0,13,0.0,56,,,,13,1991-07-14 -13224,507,64,31,12.0,24,14.0,14,0.0,55,,,,51,1991-07-14 -13225,507,86,33,8.0,12,,15,0.0,52,,,,5,1991-07-14 -13226,507,104,28,9.0,26,,21,0.0,25,,,,7,1991-07-14 -13227,507,83,33,7.0,14,,20,0.0,28,,,,37,1991-07-14 -13228,507,122,26,25.0,19,,19,0.0,29,,,,5,1991-07-14 -13229,507,87,25,30.0,22,,18,0.0,29,,,,4,1991-07-14 -13230,507,116,5,27.0,5,3.0,3,4.0,59,5315629.0,,,1,1991-07-14 -13231,507,54,5,28.0,6,,17,0.0,31,,,,4,1991-07-14 -13232,507,76,0,2.0,4,2.0,2,6.0,59,5297772.0,,,1,1991-07-14 -13233,507,121,40,16.0,16,,25,0.0,16,,,,20,1991-07-14 -13234,507,126,40,15.0,9,,22,0.0,24,,,,83,1991-07-14 -13235,507,89,21,19.0,7,,23,0.0,21,,,,6,1991-07-14 -13236,507,102,25,29.0,21,,24,0.0,21,,,,7,1991-07-14 -13237,507,94,2,5.0,1,1.0,1,10.0,59,5255479.0,,,1,1991-07-14 -13238,507,118,2,6.0,3,,26,0.0,1,,,,4,1991-07-14 -13239,507,99,26,26.0,0,,27,0.0,0,,,,81,1991-07-14 -13240,507,139,28,10.0,0,,28,0.0,0,,,,81,1991-07-14 -13241,507,109,16,33.0,13,,16,0.0,41,,,,20,1991-07-14 -13242,507,98,38,17.0,0,,30,0.0,0,,,,81,1991-07-14 -13243,507,119,38,18.0,0,,29,0.0,0,,,,81,1991-07-14 -13244,508,122,26,25.0,17,9.0,9,0.0,44,,,,11,1991-07-28 -13245,508,89,21,19.0,9,8.0,8,0.0,44,,,,11,1991-07-28 -13246,508,101,0,1.0,2,7.0,7,0.0,44,,,,60,1991-07-28 -13247,508,91,16,32.0,11,6.0,6,1.0,45,4870266.0,,,1,1991-07-28 -13248,508,109,16,33.0,7,5.0,5,2.0,45,4847198.0,,,1,1991-07-28 -13249,508,138,34,21.0,18,10.0,10,0.0,44,,,,11,1991-07-28 -13250,508,83,33,7.0,15,11.0,11,0.0,43,,,,12,1991-07-28 -13251,508,86,33,8.0,21,12.0,12,0.0,43,,,,12,1991-07-28 -13252,508,130,24,4.0,14,13.0,13,0.0,41,,,,14,1991-07-28 -13253,508,116,5,27.0,5,,14,0.0,37,,,,20,1991-07-28 -13254,508,121,40,16.0,12,,15,0.0,36,,,,5,1991-07-28 -13255,508,76,0,2.0,3,4.0,4,3.0,45,4802312.0,,,1,1991-07-28 -13256,508,108,34,22.0,20,,16,0.0,35,,,,5,1991-07-28 -13257,508,118,2,6.0,4,2.0,2,6.0,45,4783440.0,,,1,1991-07-28 -13258,508,137,24,3.0,13,,18,0.0,26,,,,6,1991-07-28 -13259,508,99,26,26.0,26,,19,0.0,22,,,,5,1991-07-28 -13260,508,126,40,15.0,16,,20,0.0,21,,,,6,1991-07-28 -13261,508,56,31,11.0,23,,21,0.0,19,,,,5,1991-07-28 -13262,508,87,25,30.0,22,,22,0.0,15,,,,5,1991-07-28 -13263,508,80,17,24.0,19,,23,0.0,14,,,,24,1991-07-28 -13264,508,54,5,28.0,6,3.0,3,4.0,45,4787279.0,,,1,1991-07-28 -13265,508,102,25,29.0,25,,25,0.0,9,,,,7,1991-07-28 -13266,508,77,39,34.0,24,,26,0.0,0,,,,20,1991-07-28 -13267,508,93,17,23.0,10,,24,0.0,11,,,,24,1991-07-28 -13268,508,142,31,12.0,0,,28,0.0,0,,,,81,1991-07-28 -13269,508,104,28,9.0,0,,27,0.0,0,,,,81,1991-07-28 -13270,508,136,21,20.0,8,,17,0.0,27,,,,5,1991-07-28 -13271,508,141,41,31.0,0,,34,0.0,0,,,,97,1991-07-28 -13272,508,119,38,18.0,0,,33,0.0,0,,,,97,1991-07-28 -13273,508,94,2,5.0,1,1.0,1,10.0,45,4769661.0,,,1,1991-07-28 -13274,508,128,35,14.0,0,,31,0.0,0,,,,97,1991-07-28 -13275,508,127,39,35.0,0,,30,0.0,0,,,,81,1991-07-28 -13276,508,98,38,17.0,0,,29,0.0,0,,,,81,1991-07-28 -13277,508,132,28,10.0,0,,32,0.0,0,,,,97,1991-07-28 -13278,509,137,24,3.0,14,15.0,15,0.0,74,,,,13,1991-08-11 -13279,509,56,31,11.0,26,14.0,14,0.0,74,,,,13,1991-08-11 -13280,509,80,17,24.0,23,13.0,13,0.0,75,,,,12,1991-08-11 -13281,509,130,24,4.0,8,12.0,12,0.0,75,,,,12,1991-08-11 -13282,509,126,40,15.0,13,11.0,11,0.0,75,,,,12,1991-08-11 -13283,509,99,26,26.0,25,10.0,10,0.0,75,,,,12,1991-08-11 -13284,509,91,16,32.0,16,9.0,9,0.0,76,,,,11,1991-08-11 -13285,509,118,2,6.0,2,3.0,3,4.0,77,6568390.0,,,1,1991-08-11 -13286,509,109,16,33.0,17,7.0,7,0.0,76,,,,11,1991-08-11 -13287,509,119,38,18.0,0,,33,0.0,0,,,,97,1991-08-11 -13288,509,132,28,10.0,0,,32,0.0,0,,,,97,1991-08-11 -13289,509,98,38,17.0,0,,31,0.0,0,,,,97,1991-08-11 -13290,509,142,31,12.0,0,,30,0.0,0,,,,81,1991-08-11 -13291,509,127,39,35.0,0,,29,0.0,0,,,,81,1991-08-11 -13292,509,104,28,9.0,0,,28,0.0,0,,,,81,1991-08-11 -13293,509,128,35,14.0,0,,27,0.0,0,,,,81,1991-08-11 -13294,509,141,41,31.0,0,,34,0.0,0,,,,97,1991-08-11 -13295,509,116,5,27.0,4,,26,0.0,28,,,,5,1991-08-11 -13296,509,87,25,30.0,22,,24,0.0,38,,,,5,1991-08-11 -13297,509,102,25,29.0,21,,23,0.0,38,,,,5,1991-08-11 -13298,509,136,21,20.0,11,,22,0.0,38,,,,6,1991-08-11 -13299,509,108,34,22.0,12,,21,0.0,49,,,,5,1991-08-11 -13300,509,83,33,7.0,10,,20,0.0,59,,,,68,1991-08-11 -13301,509,86,33,8.0,20,,19,0.0,62,,,,27,1991-08-11 -13302,509,93,17,23.0,18,,18,0.0,65,,,,5,1991-08-11 -13303,509,138,34,21.0,7,,25,0.0,37,,,,5,1991-08-11 -13304,509,89,21,19.0,15,8.0,8,0.0,76,,,,11,1991-08-11 -13305,509,77,39,34.0,24,16.0,16,0.0,74,,,,13,1991-08-11 -13306,509,121,40,16.0,9,6.0,6,1.0,76,,,,11,1991-08-11 -13307,509,54,5,28.0,6,5.0,5,2.0,77,6584185.0,,,1,1991-08-11 -13308,509,76,0,2.0,5,4.0,4,3.0,77,6574652.0,,,1,1991-08-11 -13309,509,94,2,5.0,3,2.0,2,6.0,77,6557395.0,,,1,1991-08-11 -13310,509,101,0,1.0,1,1.0,1,10.0,77,6552796.0,,,1,1991-08-11 -13311,509,122,26,25.0,19,17.0,17,0.0,71,,,,5,1991-08-11 -13312,510,29,16,32.0,7,,26,0.0,0,,,,8,1991-08-25 -13313,510,94,2,5.0,3,,20,0.0,22,,,,10,1991-08-25 -13314,510,102,25,29.0,20,,21,0.0,21,,,,6,1991-08-25 -13315,510,121,40,16.0,12,,22,0.0,13,,,,5,1991-08-25 -13316,510,137,24,3.0,22,,23,0.0,7,,,,20,1991-08-25 -13317,510,116,5,27.0,2,,24,0.0,2,,,,95,1991-08-25 -13318,510,126,40,15.0,15,,25,0.0,1,,,,5,1991-08-25 -13319,510,87,25,30.0,0,,27,0.0,0,,,,81,1991-08-25 -13320,510,127,39,35.0,0,,30,0.0,0,,,,81,1991-08-25 -13321,510,132,28,10.0,0,,29,0.0,0,,,,81,1991-08-25 -13322,510,56,31,11.0,24,,18,0.0,25,,,,5,1991-08-25 -13323,510,104,28,9.0,0,,31,0.0,0,,,,97,1991-08-25 -13324,510,98,38,17.0,0,,32,0.0,0,,,,97,1991-08-25 -13325,510,141,41,31.0,0,,33,0.0,0,,,,97,1991-08-25 -13326,510,119,38,18.0,0,,34,0.0,0,,,,97,1991-08-25 -13327,510,77,39,34.0,0,,28,0.0,0,,,,81,1991-08-25 -13328,510,80,17,24.0,19,,17,0.0,29,,,,6,1991-08-25 -13329,510,99,26,26.0,26,,19,0.0,25,,,,5,1991-08-25 -13330,510,108,34,22.0,14,,15,0.0,33,,,,51,1991-08-25 -13331,510,101,0,1.0,1,1.0,1,10.0,44,5237669.0,,,1,1991-08-25 -13332,510,76,0,2.0,4,2.0,2,6.0,44,5239570.0,,,1,1991-08-25 00:00:00 -13333,510,136,21,20.0,6,3.0,3,4.0,44,5269845.0,,,1,1991-08-25 00:00:00 -13334,510,54,5,28.0,5,,16,0.0,30,,,,5,1991-08-25 00:00:00 -13335,510,118,2,6.0,17,5.0,5,2.0,44,5294856.0,,,1,1991-08-25 00:00:00 -13336,510,86,33,8.0,13,6.0,6,1.0,44,5337704.0,,,1,1991-08-25 00:00:00 -13337,510,64,31,12.0,21,7.0,7,0.0,44,5342268.0,,,1,1991-08-25 00:00:00 -13338,510,138,34,21.0,25,8.0,8,0.0,43,,,,11,1991-08-25 00:00:00 -13339,510,89,21,19.0,8,4.0,4,3.0,44,5274979.0,,,1,1991-08-25 00:00:00 -13340,510,83,33,7.0,16,9.0,9,0.0,43,,,,11,1991-08-25 00:00:00 -13341,510,128,35,14.0,23,10.0,10,0.0,43,,,,11,1991-08-25 00:00:00 -13342,510,122,26,25.0,18,11.0,11,0.0,43,,,,11,1991-08-25 00:00:00 -13343,510,93,17,23.0,9,12.0,12,0.0,42,,,,6,1991-08-25 00:00:00 -13344,510,109,16,33.0,11,13.0,13,0.0,41,,,,5,1991-08-25 00:00:00 -13345,510,130,24,4.0,10,,14,0.0,33,,,,44,1991-08-25 00:00:00 -13346,511,56,31,11.0,25,14.0,14,0.0,49,,,,14,1991-09-08 00:00:00 -13347,511,126,40,15.0,18,15.0,15,0.0,49,,,,14,1991-09-08 00:00:00 -13348,511,77,39,34.0,23,16.0,16,0.0,48,,,,15,1991-09-08 00:00:00 -13349,511,128,35,14.0,26,,17,0.0,46,,,,5,1991-09-08 00:00:00 -13350,511,118,2,6.0,4,,21,0.0,27,,,,6,1991-09-08 00:00:00 -13351,511,130,24,4.0,13,,19,0.0,32,,,,5,1991-09-08 00:00:00 -13352,511,102,25,29.0,24,,23,0.0,21,,,,5,1991-09-08 00:00:00 -13353,511,137,24,3.0,15,,22,0.0,24,,,,37,1991-09-08 00:00:00 -13354,511,83,33,7.0,19,13.0,13,0.0,52,,,,11,1991-09-08 00:00:00 -13355,511,108,34,22.0,20,,18,0.0,35,,,,25,1991-09-08 00:00:00 -13356,511,86,33,8.0,11,12.0,12,0.0,52,,,,11,1991-09-08 00:00:00 -13357,511,54,5,28.0,6,,20,0.0,29,,,,5,1991-09-08 00:00:00 -13358,511,138,34,21.0,16,10.0,10,0.0,52,,,,11,1991-09-08 00:00:00 -13359,511,80,17,24.0,17,9.0,9,0.0,52,,,,11,1991-09-08 00:00:00 -13360,511,121,40,16.0,12,8.0,8,0.0,53,4749338.0,,,1,1991-09-08 00:00:00 -13361,511,109,16,33.0,14,7.0,7,0.0,53,4725455.0,,,1,1991-09-08 00:00:00 -13362,511,136,21,20.0,8,6.0,6,1.0,53,4719919.0,,,1,1991-09-08 00:00:00 -13363,511,29,21,19.0,7,5.0,5,2.0,53,4708782.0,,,1,1991-09-08 00:00:00 -13364,511,76,0,2.0,3,4.0,4,3.0,53,4702038.0,,,1,1991-09-08 00:00:00 -13365,511,116,5,27.0,5,3.0,3,4.0,53,4691148.0,,,1,1991-09-08 00:00:00 -13366,511,101,0,1.0,1,2.0,2,6.0,53,4690581.0,,,1,1991-09-08 00:00:00 -13367,511,94,2,5.0,2,1.0,1,10.0,53,4674319.0,,,1,1991-09-08 00:00:00 -13368,511,93,17,23.0,10,,24,0.0,8,,,,20,1991-09-08 00:00:00 -13369,511,99,26,26.0,22,11.0,11,0.0,52,,,,11,1991-09-08 00:00:00 -13370,511,89,16,32.0,9,,25,0.0,2,,,,20,1991-09-08 00:00:00 -13371,511,87,25,30.0,0,,30,0.0,0,,,,81,1991-09-08 00:00:00 -13372,511,104,28,9.0,0,,27,0.0,0,,,,81,1991-09-08 00:00:00 -13373,511,142,31,12.0,0,,28,0.0,0,,,,81,1991-09-08 00:00:00 -13374,511,127,39,35.0,0,,29,0.0,0,,,,81,1991-09-08 00:00:00 -13375,511,119,38,18.0,0,,31,0.0,0,,,,97,1991-09-08 00:00:00 -13376,511,98,38,17.0,0,,32,0.0,0,,,,97,1991-09-08 00:00:00 -13377,511,132,28,10.0,0,,33,0.0,0,,,,97,1991-09-08 00:00:00 -13378,511,141,41,31.0,0,,34,0.0,0,,,,97,1991-09-08 00:00:00 -13379,511,122,26,25.0,21,,26,0.0,1,,,,20,1991-09-08 00:00:00 -13380,512,94,2,5.0,4,,19,0.0,51,,,,2,1991-09-22 00:00:00 -13381,512,87,25,30.0,25,,20,0.0,40,,,,7,1991-09-22 00:00:00 -13382,512,116,5,27.0,5,,21,0.0,39,,,,5,1991-09-22 00:00:00 -13383,512,76,0,2.0,2,,22,0.0,37,,,,5,1991-09-22 00:00:00 -13384,512,138,34,21.0,16,,23,0.0,18,,,,5,1991-09-22 00:00:00 -13385,512,108,34,22.0,18,,24,0.0,21,,,,6,1991-09-22 00:00:00 -13386,512,86,33,8.0,15,,25,0.0,12,,,,22,1991-09-22 00:00:00 -13387,512,77,39,34.0,0,,29,0.0,0,,,,81,1991-09-22 00:00:00 -13388,512,102,25,29.0,0,,27,0.0,0,,,,81,1991-09-22 00:00:00 -13389,512,98,38,17.0,0,,28,0.0,0,,,,81,1991-09-22 00:00:00 -13390,512,130,24,4.0,12,,18,0.0,56,,,,5,1991-09-22 00:00:00 -13391,512,119,38,18.0,0,,31,0.0,0,,,,97,1991-09-22 00:00:00 -13392,512,128,35,14.0,0,,32,0.0,0,,,,97,1991-09-22 00:00:00 -13393,512,132,28,10.0,0,,33,0.0,0,,,,97,1991-09-22 00:00:00 -13394,512,141,41,31.0,0,,34,0.0,0,,,,97,1991-09-22 00:00:00 -13395,512,64,31,12.0,26,,26,0.0,1,,,,5,1991-09-22 00:00:00 -13396,512,121,40,16.0,9,17.0,17,0.0,64,,,,20,1991-09-22 00:00:00 -13397,512,127,39,35.0,0,,30,0.0,0,,,,81,1991-09-22 00:00:00 -13398,512,104,28,9.0,22,15.0,15,0.0,68,,,,13,1991-09-22 00:00:00 -13399,512,122,26,25.0,20,16.0,16,0.0,68,,,,13,1991-09-22 00:00:00 -13400,512,118,2,6.0,1,1.0,1,10.0,71,5742304.0,,,1,1991-09-22 00:00:00 -13401,512,101,0,1.0,3,2.0,2,6.0,71,5763245.0,,,1,1991-09-22 00:00:00 -13402,512,54,5,28.0,6,3.0,3,4.0,71,5795858.0,,,1,1991-09-22 00:00:00 -13403,512,93,17,23.0,8,4.0,4,3.0,71,5805802.0,,,1,1991-09-22 00:00:00 -13404,512,29,21,19.0,10,6.0,6,1.0,71,5818886.0,,,1,1991-09-22 00:00:00 -13405,512,126,40,15.0,7,7.0,7,0.0,70,,,,11,1991-09-22 00:00:00 -13406,512,136,21,20.0,11,5.0,5,2.0,71,5812337.0,,,1,1991-09-22 00:00:00 -13407,512,80,17,24.0,13,9.0,9,0.0,70,,,,11,1991-09-22 00:00:00 -13408,512,89,16,32.0,21,10.0,10,0.0,70,,,,11,1991-09-22 00:00:00 -13409,512,99,26,26.0,23,11.0,11,0.0,70,,,,11,1991-09-22 00:00:00 -13410,512,83,33,7.0,19,12.0,12,0.0,69,,,,12,1991-09-22 00:00:00 -13411,512,137,24,3.0,17,13.0,13,0.0,68,,,,13,1991-09-22 00:00:00 -13412,512,56,31,11.0,24,14.0,14,0.0,68,,,,13,1991-09-22 00:00:00 -13413,512,109,16,33.0,14,8.0,8,0.0,70,,,,11,1991-09-22 00:00:00 -13414,513,132,28,10.0,0,,31,0.0,0,,,,97,1991-09-29 00:00:00 -13415,513,87,25,30.0,0,,27,0.0,0,,,,81,1991-09-29 00:00:00 -13416,513,77,39,34.0,0,,28,0.0,0,,,,81,1991-09-29 00:00:00 -13417,513,142,31,12.0,0,,29,0.0,0,,,,81,1991-09-29 00:00:00 -13418,513,127,39,35.0,0,,30,0.0,0,,,,81,1991-09-29 00:00:00 -13419,513,119,38,18.0,0,,32,0.0,0,,,,97,1991-09-29 00:00:00 -13420,513,109,16,33.0,17,,22,0.0,22,,,,10,1991-09-29 00:00:00 -13421,513,137,24,3.0,18,17.0,17,0.0,62,,,,13,1991-09-29 00:00:00 -13422,513,86,33,8.0,12,,18,0.0,49,,,,5,1991-09-29 00:00:00 -13423,513,99,26,26.0,25,,19,0.0,36,,,,10,1991-09-29 00:00:00 -13424,513,76,0,2.0,1,,20,0.0,33,,,,10,1991-09-29 00:00:00 -13425,513,104,28,9.0,24,,21,0.0,23,,,,5,1991-09-29 00:00:00 -13426,513,122,26,25.0,26,,26,0.0,0,,,,4,1991-09-29 00:00:00 -13427,513,128,38,17.0,0,,33,0.0,0,,,,97,1991-09-29 00:00:00 -13428,513,130,24,4.0,14,16.0,16,0.0,62,,,,13,1991-09-29 00:00:00 -13429,513,69,16,32.0,20,9.0,9,0.0,64,,,,11,1991-09-29 00:00:00 -13430,513,80,17,24.0,16,14.0,14,0.0,62,,,,4,1991-09-29 00:00:00 -13431,513,121,40,16.0,8,,24,0.0,1,,,,4,1991-09-29 00:00:00 -13432,513,102,25,29.0,23,,25,0.0,0,,,,4,1991-09-29 00:00:00 -13433,513,94,2,5.0,2,1.0,1,10.0,65,5921541.0,,,1,1991-09-29 00:00:00 -13434,513,116,5,27.0,6,2.0,2,6.0,65,5932872.0,,,1,1991-09-29 00:00:00 -13435,513,118,2,6.0,4,3.0,3,4.0,65,5937450.0,,,1,1991-09-29 00:00:00 -13436,513,138,34,21.0,9,15.0,15,0.0,62,,,,13,1991-09-29 00:00:00 -13437,513,101,0,1.0,3,5.0,5,2.0,65,5983943.0,,,1,1991-09-29 00:00:00 -13438,513,54,5,28.0,7,4.0,4,3.0,65,5944313.0,,,1,1991-09-29 00:00:00 -13439,513,126,40,15.0,13,7.0,7,0.0,64,,,,11,1991-09-29 00:00:00 -13440,513,108,34,22.0,15,8.0,8,0.0,64,,,,11,1991-09-29 00:00:00 -13441,513,83,33,7.0,11,10.0,10,0.0,63,,,,12,1991-09-29 00:00:00 -13442,513,136,21,20.0,10,11.0,11,0.0,63,,,,12,1991-09-29 00:00:00 -13443,513,98,35,14.0,22,12.0,12,0.0,63,,,,12,1991-09-29 00:00:00 -13444,513,93,17,23.0,19,13.0,13,0.0,63,,,,12,1991-09-29 00:00:00 -13445,513,29,21,19.0,5,6.0,6,1.0,65,6001009.0,,,1,1991-09-29 00:00:00 -13446,513,56,31,11.0,21,,23,0.0,5,,,,20,1991-09-29 00:00:00 -13447,514,143,41,31.0,0,,32,0.0,0,,,,97,1991-10-20 00:00:00 -13448,514,86,33,8.0,0,,31,0.0,0,,,,97,1991-10-20 00:00:00 -13449,514,102,25,29.0,0,,30,0.0,0,,,,81,1991-10-20 00:00:00 -13450,514,127,39,35.0,0,,29,0.0,0,,,,81,1991-10-20 00:00:00 -13451,514,77,39,34.0,0,,28,0.0,0,,,,81,1991-10-20 00:00:00 -13452,514,76,0,2.0,1,1.0,1,10.0,53,5530695.0,,,1,1991-10-20 00:00:00 -13453,514,101,0,1.0,2,2.0,2,6.0,53,5531039.0,,,1,1991-10-20 00:00:00 -13454,514,118,2,6.0,5,3.0,3,4.0,53,5587426.0,,,1,1991-10-20 00:00:00 -13455,514,116,5,27.0,4,4.0,4,3.0,53,5611456.0,,,1,1991-10-20 00:00:00 -13456,514,83,33,7.0,19,5.0,5,2.0,52,,,,11,1991-10-20 00:00:00 -13457,514,130,24,4.0,14,6.0,6,1.0,52,,,,11,1991-10-20 00:00:00 -13458,514,126,40,15.0,18,8.0,8,0.0,52,,,,11,1991-10-20 00:00:00 -13459,514,122,26,25.0,17,9.0,9,0.0,52,,,,11,1991-10-20 00:00:00 -13460,514,132,28,10.0,26,10.0,10,0.0,51,,,,12,1991-10-20 00:00:00 -13461,514,98,35,14.0,24,11.0,11,0.0,50,,,,13,1991-10-20 00:00:00 -13462,514,99,26,26.0,20,,12,0.0,41,,,,91,1991-10-20 00:00:00 -13463,514,93,17,23.0,7,,13,0.0,39,,,,10,1991-10-20 00:00:00 -13464,514,29,21,19.0,9,,14,0.0,34,,,,5,1991-10-20 00:00:00 -13465,514,136,21,20.0,10,7.0,7,0.0,52,,,,11,1991-10-20 00:00:00 -13466,514,137,24,3.0,15,,16,0.0,30,,,,20,1991-10-20 00:00:00 -13467,514,64,31,12.0,23,,15,0.0,31,,,,5,1991-10-20 00:00:00 -13468,514,104,28,9.0,0,,27,0.0,0,,,,81,1991-10-20 00:00:00 -13469,514,54,5,28.0,6,,26,0.0,0,,,,5,1991-10-20 00:00:00 -13470,514,90,40,16.0,22,,25,0.0,1,,,,3,1991-10-20 00:00:00 -13471,514,108,34,22.0,12,,23,0.0,1,,,,3,1991-10-20 00:00:00 -13472,514,109,16,33.0,11,,22,0.0,1,,,,3,1991-10-20 00:00:00 -13473,514,138,34,21.0,16,,24,0.0,1,,,,3,1991-10-20 00:00:00 -13474,514,56,31,11.0,21,,21,0.0,4,,,,5,1991-10-20 00:00:00 -13475,514,69,16,32.0,13,,20,0.0,7,,,,6,1991-10-20 00:00:00 -13476,514,94,2,5.0,3,,19,0.0,9,,,,20,1991-10-20 00:00:00 -13477,514,80,17,24.0,8,,18,0.0,15,,,,36,1991-10-20 00:00:00 -13478,514,87,25,30.0,25,,17,0.0,26,,,,5,1991-10-20 00:00:00 -13479,515,54,5,28.0,7,,23,0.0,5,,,,3,1991-11-03 00:00:00 -13480,515,90,40,16.0,26,20.0,20,0.0,12,,,,12,1991-11-03 00:00:00 -13481,515,93,17,23.0,10,,21,0.0,8,,,,20,1991-11-03 00:00:00 -13482,515,29,21,19.0,6,,22,0.0,5,,,,20,1991-11-03 00:00:00 -13483,515,56,31,11.0,25,19.0,19,0.0,13,,,,12,1991-11-03 00:00:00 -13484,515,77,39,34.0,19,,24,0.0,5,,,,20,1991-11-03 00:00:00 -13485,515,98,35,14.0,0,,31,0.0,0,,,,97,1991-11-03 00:00:00 -13486,515,137,24,3.0,24,,26,0.0,4,,,,20,1991-11-03 00:00:00 -13487,515,87,32,30.0,0,,27,0.0,0,,,,81,1991-11-03 00:00:00 -13488,515,83,33,7.0,0,,28,0.0,0,,,,81,1991-11-03 00:00:00 -13489,515,127,39,35.0,0,,29,0.0,0,,,,81,1991-11-03 00:00:00 -13490,515,91,32,29.0,0,,30,0.0,0,,,,81,1991-11-03 00:00:00 -13491,515,99,26,26.0,22,18.0,18,0.0,13,,,,11,1991-11-03 00:00:00 -13492,515,122,26,25.0,20,,25,0.0,5,,,,3,1991-11-03 00:00:00 -13493,515,86,33,8.0,17,17.0,17,0.0,13,,,,11,1991-11-03 00:00:00 -13494,515,143,41,31.0,0,,32,0.0,0,,,,97,1991-11-03 00:00:00 -13495,515,132,28,10.0,23,15.0,15,0.0,13,,,,11,1991-11-03 00:00:00 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-13541,517,107,36,17.0,0,,28,0.0,0,,,,81,1992-03-22 00:00:00 -13542,517,93,34,22.0,9,,17,0.0,36,,,,64,1992-03-22 00:00:00 -13543,517,54,5,27.0,10,,18,0.0,31,,,,5,1992-03-22 00:00:00 -13544,517,80,17,24.0,21,,19,0.0,29,,,,20,1992-03-22 00:00:00 -13545,517,130,16,32.0,15,,20,0.0,17,,,,6,1992-03-22 00:00:00 -13546,517,126,16,33.0,8,,24,0.0,0,,,,5,1992-03-22 00:00:00 -13547,517,103,17,23.0,17,,23,0.0,2,,,,20,1992-03-22 00:00:00 -13548,517,90,36,16.0,19,,25,0.0,0,,,,4,1992-03-22 00:00:00 -13549,517,121,5,28.0,20,,26,0.0,0,,,,4,1992-03-22 00:00:00 -13550,517,87,28,10.0,0,,27,0.0,0,,,,81,1992-03-22 00:00:00 -13551,517,129,35,14.0,23,,16,0.0,37,,,,20,1992-03-22 00:00:00 -13552,517,128,24,3.0,16,,21,0.0,12,,,,5,1992-03-22 00:00:00 -13553,517,98,35,15.0,14,,15,0.0,45,,,,8,1992-03-22 00:00:00 -13554,517,64,31,12.0,12,7.0,7,0.0,68,,,,11,1992-03-22 00:00:00 -13555,517,104,28,9.0,25,13.0,13,0.0,65,,,,14,1992-03-22 00:00:00 -13556,517,78,32,30.0,24,12.0,12,0.0,66,,,,13,1992-03-22 00:00:00 -13557,517,91,32,29.0,13,11.0,11,0.0,66,,,,13,1992-03-22 00:00:00 -13558,517,122,26,25.0,22,10.0,10,0.0,67,,,,12,1992-03-22 00:00:00 -13559,517,99,26,26.0,26,9.0,9,0.0,67,,,,12,1992-03-22 00:00:00 -13560,517,108,34,21.0,7,8.0,8,0.0,68,,,,11,1992-03-22 00:00:00 -13561,517,56,31,11.0,18,6.0,6,1.0,68,,,,11,1992-03-22 00:00:00 -13562,517,109,24,4.0,11,5.0,5,2.0,68,,,,11,1992-03-22 00:00:00 -13563,517,76,0,2.0,5,4.0,4,3.0,69,5546934.0,,,1,1992-03-22 00:00:00 -13564,517,29,21,19.0,3,3.0,3,4.0,69,5535016.0,,,1,1992-03-22 00:00:00 -13565,517,118,2,6.0,2,2.0,2,6.0,69,5526558.0,,,1,1992-03-22 00:00:00 -13566,517,94,2,5.0,1,1.0,1,10.0,69,5513587.0,,,1,1992-03-22 00:00:00 -13567,517,127,33,7.0,0,,29,0.0,0,,,,81,1992-03-22 00:00:00 -13568,517,83,21,20.0,4,,14,0.0,47,,,,5,1992-03-22 00:00:00 -13569,517,131,33,8.0,0,,30,0.0,0,,,,81,1992-03-22 00:00:00 -13570,517,101,0,1.0,6,,22,0.0,11,,,,7,1992-03-22 00:00:00 -13571,518,80,17,24.0,23,7.0,7,0.0,69,,,,12,1992-04-05 00:00:00 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00:00:00 -13604,519,122,26,25.0,14,,24,0.0,11,,,,5,1992-05-03 00:00:00 -13605,519,83,21,20.0,6,,25,0.0,4,,,,20,1992-05-03 00:00:00 -13606,519,109,24,4.0,11,,26,0.0,2,,,,5,1992-05-03 00:00:00 -13607,519,130,16,32.0,0,,29,0.0,0,,,,81,1992-05-03 00:00:00 -13608,519,127,33,7.0,0,,28,0.0,0,,,,81,1992-05-03 00:00:00 -13609,519,70,33,8.0,0,,30,0.0,0,,,,81,1992-05-03 00:00:00 -13610,519,89,37,34.0,0,,31,0.0,0,,,,97,1992-05-03 00:00:00 -13611,519,134,37,35.0,0,,32,0.0,0,,,,97,1992-05-03 00:00:00 -13612,519,126,16,33.0,17,,20,0.0,24,,,,20,1992-05-03 00:00:00 -13613,519,78,32,30.0,0,,27,0.0,0,,,,81,1992-05-03 00:00:00 -13614,519,80,17,24.0,25,,19,0.0,26,,,,64,1992-05-03 00:00:00 -13615,519,128,24,3.0,15,,18,0.0,30,,,,20,1992-05-03 00:00:00 -13616,519,29,21,19.0,2,2.0,2,6.0,65,6994588.0,,,1,1992-05-03 00:00:00 -13617,519,91,32,29.0,24,,17,0.0,35,,,,5,1992-05-03 00:00:00 -13618,519,54,5,27.0,8,3.0,3,4.0,65,6997136.0,,,1,1992-05-03 00:00:00 -13619,519,76,0,2.0,7,4.0,4,3.0,65,7051321.0,,,1,1992-05-03 00:00:00 -13620,519,104,28,9.0,16,5.0,5,2.0,64,,,,11,1992-05-03 00:00:00 -13621,519,87,28,10.0,19,7.0,7,0.0,63,,,,12,1992-05-03 00:00:00 -13622,519,90,36,16.0,9,8.0,8,0.0,63,,,,12,1992-05-03 00:00:00 -13623,519,101,0,1.0,3,9.0,9,0.0,62,,,,20,1992-05-03 00:00:00 -13624,519,93,34,22.0,13,6.0,6,1.0,63,,,,12,1992-05-03 00:00:00 -13625,519,103,17,23.0,22,11.0,11,0.0,61,,,,14,1992-05-03 00:00:00 -13626,519,107,36,17.0,23,12.0,12,0.0,61,,,,14,1992-05-03 00:00:00 -13627,519,108,34,21.0,12,,13,0.0,56,,,,20,1992-05-03 00:00:00 -13628,519,98,35,15.0,18,,14,0.0,56,,,,20,1992-05-03 00:00:00 -13629,519,56,31,11.0,21,,15,0.0,56,,,,20,1992-05-03 00:00:00 -13630,519,99,26,26.0,10,,16,0.0,55,,,,20,1992-05-03 00:00:00 -13631,519,121,5,28.0,5,10.0,10,0.0,62,,,,20,1992-05-03 00:00:00 -13632,519,94,2,5.0,1,1.0,1,10.0,65,6970674.0,,,1,1992-05-03 00:00:00 -13633,520,103,17,23.0,25,,25,0.0,8,,,,6,1992-05-17 00:00:00 -13634,520,130,16,32.0,23,,20,0.0,25,,,,6,1992-05-17 00:00:00 -13635,520,80,17,24.0,21,,21,0.0,24,,,,5,1992-05-17 00:00:00 -13636,520,98,35,15.0,22,,22,0.0,24,,,,5,1992-05-17 00:00:00 -13637,520,29,21,19.0,5,,23,0.0,20,,,,20,1992-05-17 00:00:00 -13638,520,121,5,28.0,8,,24,0.0,11,,,,20,1992-05-17 00:00:00 -13639,520,122,26,25.0,10,,19,0.0,29,,,,5,1992-05-17 00:00:00 -13640,520,129,35,14.0,0,,28,0.0,0,,,,81,1992-05-17 00:00:00 -13641,520,70,33,8.0,0,,29,0.0,0,,,,81,1992-05-17 00:00:00 -13642,520,127,33,7.0,0,,30,0.0,0,,,,81,1992-05-17 00:00:00 -13643,520,89,37,34.0,0,,31,0.0,0,,,,97,1992-05-17 00:00:00 -13644,520,134,37,35.0,0,,32,0.0,0,,,,97,1992-05-17 00:00:00 -13645,520,56,31,11.0,0,,27,0.0,0,,,,81,1992-05-17 00:00:00 -13646,520,76,0,2.0,4,,17,0.0,39,,,,4,1992-05-17 00:00:00 -13647,520,64,31,12.0,26,,26,0.0,8,,,,6,1992-05-17 00:00:00 -13648,520,91,32,29.0,19,,18,0.0,32,,,,20,1992-05-17 00:00:00 -13649,520,54,5,27.0,7,,16,0.0,39,,,,4,1992-05-17 00:00:00 -13650,520,118,2,6.0,2,2.0,2,6.0,60,5330378.0,,,1,1992-05-17 00:00:00 -13651,520,101,0,1.0,3,3.0,3,4.0,60,5369911.0,,,1,1992-05-17 00:00:00 -13652,520,83,21,20.0,6,4.0,4,3.0,60,5373934.0,,,1,1992-05-17 00:00:00 -13653,520,104,28,9.0,9,5.0,5,2.0,59,,,,11,1992-05-17 00:00:00 -13654,520,93,34,22.0,15,6.0,6,1.0,59,,,,11,1992-05-17 00:00:00 -13655,520,126,16,33.0,16,7.0,7,0.0,58,,,,12,1992-05-17 00:00:00 -13656,520,94,2,5.0,1,1.0,1,10.0,60,5320927.0,,,1,1992-05-17 00:00:00 -13657,520,99,26,26.0,13,9.0,9,0.0,58,,,,12,1992-05-17 00:00:00 -13658,520,87,28,10.0,11,10.0,10,0.0,58,,,,12,1992-05-17 00:00:00 -13659,520,108,34,21.0,16,11.0,11,0.0,57,,,,5,1992-05-17 00:00:00 -13660,520,90,36,16.0,12,12.0,12,0.0,57,,,,13,1992-05-17 00:00:00 -13661,520,107,36,17.0,24,13.0,13,0.0,57,,,,13,1992-05-17 00:00:00 -13662,520,109,24,4.0,14,14.0,14,0.0,55,,,,69,1992-05-17 00:00:00 -13663,520,128,24,3.0,20,8.0,8,0.0,58,,,,12,1992-05-17 00:00:00 -13664,520,78,32,30.0,17,,15,0.0,40,,,,20,1992-05-17 00:00:00 -13665,521,109,24,4.0,10,,20,0.0,9,,,,6,1992-05-31 00:00:00 -13666,521,98,35,15.0,25,,21,0.0,9,,,,5,1992-05-31 00:00:00 -13667,521,130,16,32.0,21,,22,0.0,6,,,,20,1992-05-31 00:00:00 -13668,521,128,24,3.0,24,,23,0.0,4,,,,7,1992-05-31 00:00:00 -13669,521,90,36,16.0,16,,24,0.0,1,,,,6,1992-05-31 00:00:00 -13670,521,129,35,14.0,0,,29,0.0,0,,,,81,1992-05-31 00:00:00 -13671,521,127,33,7.0,0,,27,0.0,0,,,,81,1992-05-31 00:00:00 -13672,521,70,33,8.0,0,,28,0.0,0,,,,81,1992-05-31 00:00:00 -13673,521,107,36,17.0,0,,30,0.0,0,,,,81,1992-05-31 00:00:00 -13674,521,78,32,30.0,0,,31,0.0,0,,,,97,1992-05-31 00:00:00 -13675,521,134,37,35.0,0,,32,0.0,0,,,,97,1992-05-31 00:00:00 -13676,521,89,37,34.0,26,,19,0.0,11,,,,5,1992-05-31 00:00:00 -13677,521,93,34,22.0,18,,26,0.0,0,,,,20,1992-05-31 00:00:00 -13678,521,64,31,12.0,9,,18,0.0,17,,,,20,1992-05-31 00:00:00 -13679,521,80,17,24.0,12,,25,0.0,1,,,,6,1992-05-31 00:00:00 -13680,521,54,5,27.0,4,,16,0.0,28,,,,6,1992-05-31 00:00:00 -13681,521,126,16,33.0,13,,17,0.0,18,,,,6,1992-05-31 00:00:00 -13682,521,101,0,1.0,3,1.0,1,10.0,78,6659372.0,,,1,1992-05-31 00:00:00 -13683,521,118,2,6.0,2,3.0,3,4.0,78,6691215.0,,,1,1992-05-31 00:00:00 -13684,521,29,21,19.0,6,4.0,4,3.0,78,6698666.0,,,1,1992-05-31 00:00:00 -13685,521,83,21,20.0,7,5.0,5,2.0,78,6740719.0,,,1,1992-05-31 00:00:00 -13686,521,91,32,29.0,15,6.0,6,1.0,77,,,,11,1992-05-31 00:00:00 -13687,521,104,28,9.0,11,7.0,7,0.0,77,,,,11,1992-05-31 00:00:00 -13688,521,94,2,5.0,1,2.0,2,6.0,78,6659587.0,,,1,1992-05-31 00:00:00 -13689,521,108,34,21.0,20,9.0,9,0.0,76,,,,12,1992-05-31 00:00:00 -13690,521,99,26,26.0,23,10.0,10,0.0,76,,,,12,1992-05-31 00:00:00 -13691,521,87,28,10.0,19,11.0,11,0.0,76,,,,12,1992-05-31 00:00:00 -13692,521,122,26,25.0,22,12.0,12,0.0,75,,,,13,1992-05-31 00:00:00 -13693,521,121,5,28.0,8,,13,0.0,60,,,,20,1992-05-31 00:00:00 -13694,521,76,0,2.0,5,,14,0.0,32,,,,6,1992-05-31 00:00:00 -13695,521,103,17,23.0,17,8.0,8,0.0,77,,,,11,1992-05-31 00:00:00 -13696,521,56,31,11.0,14,,15,0.0,30,,,,6,1992-05-31 00:00:00 -13697,522,130,16,32.0,17,,19,0.0,36,,,,7,1992-06-14 00:00:00 -13698,522,56,31,11.0,10,,20,0.0,35,,,,6,1992-06-14 00:00:00 -13699,522,64,31,12.0,6,,21,0.0,34,,,,8,1992-06-14 00:00:00 -13700,522,121,5,28.0,9,,22,0.0,18,,,,20,1992-06-14 00:00:00 -13701,522,94,2,5.0,3,,23,0.0,14,,,,20,1992-06-14 00:00:00 -13702,522,98,35,15.0,18,,26,0.0,0,,,,7,1992-06-14 00:00:00 -13703,522,91,32,29.0,19,,25,0.0,14,,,,2,1992-06-14 00:00:00 -13704,522,87,28,10.0,0,,27,0.0,0,,,,81,1992-06-14 00:00:00 -13705,522,129,35,14.0,0,,29,0.0,0,,,,81,1992-06-14 00:00:00 -13706,522,70,33,8.0,0,,30,0.0,0,,,,81,1992-06-14 00:00:00 -13707,522,101,0,1.0,1,,18,0.0,37,,,,10,1992-06-14 00:00:00 -13708,522,126,16,33.0,24,,24,0.0,14,,,,7,1992-06-14 00:00:00 -13709,522,118,2,6.0,2,,17,0.0,43,,,,6,1992-06-14 00:00:00 -13710,522,108,34,21.0,23,9.0,9,0.0,68,,,,11,1992-06-14 00:00:00 -13711,522,78,32,30.0,11,,15,0.0,61,,,,5,1992-06-14 00:00:00 -13712,522,107,36,17.0,20,14.0,14,0.0,64,,,,15,1992-06-14 00:00:00 -13713,522,103,17,23.0,25,13.0,13,0.0,65,,,,14,1992-06-14 00:00:00 -13714,522,128,24,3.0,26,12.0,12,0.0,67,,,,12,1992-06-14 00:00:00 -13715,522,80,17,24.0,13,11.0,11,0.0,67,,,,12,1992-06-14 00:00:00 -13716,522,122,26,25.0,21,10.0,10,0.0,67,,,,12,1992-06-14 00:00:00 -13717,522,93,34,22.0,15,8.0,8,0.0,68,,,,11,1992-06-14 00:00:00 -13718,522,104,28,9.0,16,7.0,7,0.0,68,,,,11,1992-06-14 00:00:00 -13719,522,99,26,26.0,22,6.0,6,1.0,68,,,,11,1992-06-14 00:00:00 -13720,522,109,24,4.0,14,5.0,5,2.0,68,,,,11,1992-06-14 00:00:00 -13721,522,90,36,16.0,12,4.0,4,3.0,68,,,,11,1992-06-14 00:00:00 -13722,522,54,5,27.0,8,3.0,3,4.0,69,5895626.0,,,1,1992-06-14 00:00:00 -13723,522,29,21,19.0,5,2.0,2,6.0,69,5840700.0,,,1,1992-06-14 00:00:00 -13724,522,76,0,2.0,4,1.0,1,10.0,69,5828299.0,,,1,1992-06-14 00:00:00 -13725,522,83,21,20.0,7,,16,0.0,45,,,,7,1992-06-14 00:00:00 -13726,522,89,37,34.0,0,,31,0.0,0,,,,97,1992-06-14 00:00:00 -13727,522,127,33,7.0,0,,28,0.0,0,,,,81,1992-06-14 00:00:00 -13728,523,126,16,33.0,24,,25,0.0,0,,,,3,1992-07-05 00:00:00 -13729,523,130,16,32.0,20,,18,0.0,25,,,,5,1992-07-05 00:00:00 -13730,523,90,36,16.0,21,,17,0.0,33,,,,6,1992-07-05 00:00:00 -13731,523,121,5,28.0,8,,16,0.0,38,,,,5,1992-07-05 00:00:00 -13732,523,122,26,25.0,9,,15,0.0,46,,,,20,1992-07-05 00:00:00 -13733,523,78,32,30.0,18,,14,0.0,41,,,,5,1992-07-05 00:00:00 -13734,523,109,24,4.0,19,,13,0.0,51,,,,20,1992-07-05 00:00:00 -13735,523,54,5,27.0,6,,12,0.0,61,,,,5,1992-07-05 00:00:00 -13736,523,128,24,3.0,22,11.0,11,0.0,66,,,,13,1992-07-05 00:00:00 -13737,523,87,28,10.0,15,,19,0.0,20,,,,20,1992-07-05 00:00:00 -13738,523,93,34,22.0,25,10.0,10,0.0,67,,,,12,1992-07-05 00:00:00 -13739,523,80,17,24.0,16,8.0,8,0.0,68,,,,11,1992-07-05 00:00:00 -13740,523,104,28,9.0,14,7.0,7,0.0,68,,,,11,1992-07-05 00:00:00 -13741,523,64,31,12.0,12,6.0,6,1.0,68,,,,11,1992-07-05 00:00:00 -13742,523,99,26,26.0,10,5.0,5,2.0,68,,,,11,1992-07-05 00:00:00 -13743,523,56,31,11.0,11,4.0,4,3.0,68,,,,11,1992-07-05 00:00:00 -13744,523,83,21,20.0,7,3.0,3,4.0,69,5961038.0,,,1,1992-07-05 00:00:00 -13745,523,118,2,6.0,2,2.0,2,6.0,69,5934906.0,,,1,1992-07-05 00:00:00 -13746,523,94,2,5.0,1,1.0,1,10.0,69,5888459.0,,,1,1992-07-05 00:00:00 -13747,523,108,34,21.0,17,9.0,9,0.0,67,,,,12,1992-07-05 00:00:00 -13748,523,76,0,2.0,4,,21,0.0,10,,,,5,1992-07-05 00:00:00 -13749,523,29,21,19.0,5,,20,0.0,17,,,,3,1992-07-05 00:00:00 -13750,523,101,0,1.0,3,,23,0.0,0,,,,3,1992-07-05 00:00:00 -13751,523,91,32,29.0,13,,24,0.0,0,,,,3,1992-07-05 00:00:00 -13752,523,129,35,14.0,26,,26,0.0,0,,,,3,1992-07-05 00:00:00 -13753,523,107,36,17.0,0,,27,0.0,0,,,,81,1992-07-05 00:00:00 -13754,523,103,17,23.0,0,,28,0.0,0,,,,81,1992-07-05 00:00:00 -13755,523,127,33,7.0,0,,29,0.0,0,,,,81,1992-07-05 00:00:00 -13756,523,70,33,8.0,0,,30,0.0,0,,,,81,1992-07-05 00:00:00 -13757,523,98,35,15.0,23,,22,0.0,6,,,,37,1992-07-05 00:00:00 -13758,524,54,5,27.0,8,,20,0.0,43,,,,26,1992-07-12 00:00:00 -13759,524,130,16,32.0,23,,21,0.0,43,,,,5,1992-07-12 00:00:00 -13760,524,108,34,21.0,19,13.0,13,0.0,57,,,,12,1992-07-12 00:00:00 -13761,524,134,37,35.0,0,,32,0.0,0,,,,97,1992-07-12 00:00:00 -13762,524,89,37,34.0,0,,31,0.0,0,,,,97,1992-07-12 00:00:00 -13763,524,127,33,7.0,0,,30,0.0,0,,,,54,1992-07-12 00:00:00 -13764,524,129,35,14.0,0,,29,0.0,0,,,,81,1992-07-12 00:00:00 -13765,524,90,36,16.0,21,,25,0.0,27,,,,6,1992-07-12 00:00:00 -13766,524,69,17,23.0,0,,27,0.0,0,,,,81,1992-07-12 00:00:00 -13767,524,78,32,30.0,16,,26,0.0,27,,,,7,1992-07-12 00:00:00 -13768,524,64,31,12.0,7,,24,0.0,31,,,,7,1992-07-12 00:00:00 -13769,524,91,32,29.0,11,,23,0.0,32,,,,36,1992-07-12 00:00:00 -13770,524,126,16,33.0,24,,22,0.0,37,,,,5,1992-07-12 00:00:00 -13771,524,107,36,17.0,0,,28,0.0,0,,,,81,1992-07-12 00:00:00 -13772,524,109,24,4.0,18,,19,0.0,46,,,,20,1992-07-12 00:00:00 -13773,524,87,28,10.0,17,12.0,12,0.0,57,,,,12,1992-07-12 00:00:00 -13774,524,80,17,24.0,25,17.0,17,0.0,53,,,,5,1992-07-12 00:00:00 -13775,524,128,24,3.0,20,11.0,11,0.0,57,,,,12,1992-07-12 00:00:00 -13776,524,122,26,25.0,13,10.0,10,0.0,57,,,,12,1992-07-12 00:00:00 -13777,524,121,5,28.0,14,9.0,9,0.0,58,,,,11,1992-07-12 00:00:00 -13778,524,99,26,26.0,10,8.0,8,0.0,58,,,,11,1992-07-12 00:00:00 -13779,524,104,28,9.0,12,7.0,7,0.0,58,,,,11,1992-07-12 00:00:00 -13780,524,56,31,11.0,9,6.0,6,1.0,59,5223129.0,,,1,1992-07-12 00:00:00 -13781,524,76,0,2.0,5,5.0,5,2.0,59,5198786.0,,,1,1992-07-12 00:00:00 -13782,524,101,0,1.0,3,,18,0.0,52,,,,7,1992-07-12 00:00:00 -13783,524,83,21,20.0,6,3.0,3,4.0,59,5191386.0,,,1,1992-07-12 00:00:00 -13784,524,118,2,6.0,2,2.0,2,6.0,59,5182085.0,,,1,1992-07-12 00:00:00 -13785,524,94,2,5.0,1,1.0,1,10.0,59,5142991.0,,,1,1992-07-12 00:00:00 -13786,524,98,35,15.0,15,14.0,14,0.0,57,,,,12,1992-07-12 00:00:00 -13787,524,93,34,22.0,22,15.0,15,0.0,56,,,,13,1992-07-12 00:00:00 -13788,524,70,33,8.0,26,16.0,16,0.0,55,,,,14,1992-07-12 00:00:00 -13789,524,29,21,19.0,4,4.0,4,3.0,59,5196258.0,,,1,1992-07-12 00:00:00 -13790,525,121,5,28.0,12,,20,0.0,21,,,,5,1992-07-26 00:00:00 -13791,525,56,31,11.0,13,,21,0.0,21,,,,5,1992-07-26 00:00:00 -13792,525,76,0,2.0,4,,22,0.0,16,,,,10,1992-07-26 00:00:00 -13793,525,128,24,3.0,14,,23,0.0,8,,,,5,1992-07-26 00:00:00 -13794,525,78,32,30.0,16,,24,0.0,8,,,,20,1992-07-26 00:00:00 -13795,525,87,28,10.0,15,,25,0.0,1,,,,20,1992-07-26 00:00:00 -13796,525,129,35,14.0,0,,29,0.0,0,,,,81,1992-07-26 00:00:00 -13797,525,130,16,32.0,0,,27,0.0,0,,,,81,1992-07-26 00:00:00 -13798,525,127,33,7.0,0,,28,0.0,0,,,,81,1992-07-26 00:00:00 -13799,525,70,33,8.0,0,,30,0.0,0,,,,81,1992-07-26 00:00:00 -13800,525,89,37,34.0,0,,31,0.0,0,,,,97,1992-07-26 00:00:00 -13801,525,134,37,35.0,0,,32,0.0,0,,,,96,1992-07-26 00:00:00 -13802,525,64,31,12.0,11,,19,0.0,23,,,,5,1992-07-26 00:00:00 -13803,525,69,17,23.0,24,,26,0.0,1,,,,6,1992-07-26 00:00:00 -13804,525,109,24,4.0,20,,18,0.0,25,,,,5,1992-07-26 00:00:00 -13805,525,98,35,15.0,19,,17,0.0,33,,,,5,1992-07-26 00:00:00 -13806,525,90,36,16.0,10,16.0,16,0.0,42,,,,13,1992-07-26 00:00:00 -13807,525,94,2,5.0,1,1.0,1,10.0,45,4702032.0,,,1,1992-07-26 00:00:00 -13808,525,101,0,1.0,3,2.0,2,6.0,45,4706532.0,,,1,1992-07-26 00:00:00 -13809,525,29,21,19.0,6,3.0,3,4.0,45,4736494.0,,,1,1992-07-26 00:00:00 -13810,525,83,21,20.0,9,4.0,4,3.0,45,4738991.0,,,1,1992-07-26 00:00:00 -13811,525,54,5,27.0,5,5.0,5,2.0,45,4774639.0,,,1,1992-07-26 00:00:00 -13812,525,122,26,25.0,8,7.0,7,0.0,45,4799212.0,,,1,1992-07-26 00:00:00 -13813,525,118,2,6.0,2,8.0,8,0.0,44,,,,20,1992-07-26 00:00:00 -13814,525,99,26,26.0,7,6.0,6,1.0,45,4798530.0,,,1,1992-07-26 00:00:00 -13815,525,108,34,21.0,21,10.0,10,0.0,44,,,,11,1992-07-26 00:00:00 -13816,525,93,34,22.0,18,11.0,11,0.0,44,,,,11,1992-07-26 00:00:00 -13817,525,80,17,24.0,26,12.0,12,0.0,44,,,,11,1992-07-26 00:00:00 -13818,525,107,36,17.0,22,13.0,13,0.0,44,,,,11,1992-07-26 00:00:00 -13819,525,91,32,29.0,25,14.0,14,0.0,44,,,,11,1992-07-26 00:00:00 -13820,525,126,16,33.0,23,15.0,15,0.0,43,,,,12,1992-07-26 00:00:00 -13821,525,104,28,9.0,17,9.0,9,0.0,44,,,,11,1992-07-26 00:00:00 -13822,526,122,26,25.0,8,,23,0.0,0,,,,4,1992-08-16 00:00:00 -13823,526,128,24,3.0,22,,19,0.0,13,,,,4,1992-08-16 00:00:00 -13824,526,90,36,16.0,23,,20,0.0,13,,,,4,1992-08-16 00:00:00 -13825,526,130,16,32.0,24,,21,0.0,13,,,,4,1992-08-16 00:00:00 -13826,526,127,35,14.0,18,,22,0.0,2,,,,20,1992-08-16 00:00:00 -13827,526,99,26,26.0,11,,24,0.0,0,,,,4,1992-08-16 00:00:00 -13828,526,134,37,35.0,0,,31,0.0,0,,,,97,1992-08-16 00:00:00 -13829,526,64,31,12.0,13,,26,0.0,0,,,,4,1992-08-16 00:00:00 -13830,526,80,17,24.0,0,,27,0.0,0,,,,81,1992-08-16 00:00:00 -13831,526,69,17,23.0,0,,29,0.0,0,,,,81,1992-08-16 00:00:00 -13832,526,89,37,34.0,0,,30,0.0,0,,,,81,1992-08-16 00:00:00 -13833,526,87,28,10.0,14,,18,0.0,13,,,,4,1992-08-16 00:00:00 -13834,526,98,35,15.0,12,,25,0.0,0,,,,4,1992-08-16 00:00:00 -13835,526,91,32,29.0,15,,17,0.0,13,,,,4,1992-08-16 00:00:00 -13836,526,108,34,21.0,0,,28,0.0,0,,,,81,1992-08-16 00:00:00 -13837,526,78,32,30.0,20,,15,0.0,35,,,,5,1992-08-16 00:00:00 -13838,526,54,5,27.0,9,,16,0.0,14,,,,20,1992-08-16 00:00:00 -13839,526,101,0,1.0,3,1.0,1,10.0,77,6379216.0,,,1,1992-08-16 00:00:00 -13840,526,94,2,5.0,2,2.0,2,6.0,77,6419355.0,,,1,1992-08-16 00:00:00 -13841,526,76,0,2.0,5,3.0,3,4.0,77,6429998.0,,,1,1992-08-16 00:00:00 -13842,526,56,31,11.0,16,4.0,4,3.0,77,6433529.0,,,1,1992-08-16 00:00:00 -13843,526,121,5,28.0,10,6.0,6,1.0,76,,,,11,1992-08-16 00:00:00 -13844,526,104,28,9.0,7,7.0,7,0.0,75,,,,12,1992-08-16 00:00:00 -13845,526,83,21,20.0,6,5.0,5,2.0,77,6436714.0,,,1,1992-08-16 00:00:00 -13846,526,107,36,17.0,17,9.0,9,0.0,74,,,,13,1992-08-16 00:00:00 -13847,526,126,16,33.0,21,10.0,10,0.0,73,,,,14,1992-08-16 00:00:00 -13848,526,70,33,8.0,25,11.0,11,0.0,73,,,,14,1992-08-16 00:00:00 -13849,526,29,21,19.0,4,,12,0.0,63,,,,41,1992-08-16 00:00:00 -13850,526,118,2,6.0,1,,13,0.0,55,,,,5,1992-08-16 00:00:00 -13851,526,109,24,4.0,19,8.0,8,0.0,75,,,,12,1992-08-16 00:00:00 -13852,526,93,34,22.0,26,,14,0.0,40,,,,6,1992-08-16 00:00:00 -13853,527,122,26,25.0,7,,19,0.0,27,,,,20,1992-08-30 00:00:00 -13854,527,121,5,28.0,12,,20,0.0,25,,,,5,1992-08-30 00:00:00 -13855,527,98,35,15.0,11,,21,0.0,25,,,,5,1992-08-30 00:00:00 -13856,527,104,28,9.0,14,,22,0.0,20,,,,6,1992-08-30 00:00:00 -13857,527,54,5,27.0,5,,23,0.0,7,,,,29,1992-08-30 00:00:00 -13858,527,103,17,23.0,0,,27,0.0,0,,,,81,1992-08-30 00:00:00 -13859,527,76,0,2.0,6,,25,0.0,0,,,,7,1992-08-30 00:00:00 -13860,527,93,34,22.0,19,,26,0.0,0,,,,20,1992-08-30 00:00:00 -13861,527,91,32,29.0,20,18.0,18,0.0,40,,,,20,1992-08-30 00:00:00 -13862,527,134,37,35.0,0,,29,0.0,0,,,,81,1992-08-30 00:00:00 -13863,527,99,26,26.0,0,,30,0.0,0,,,,54,1992-08-30 00:00:00 -13864,527,128,24,3.0,22,,24,0.0,1,,,,3,1992-08-30 00:00:00 -13865,527,78,32,30.0,26,17.0,17,0.0,42,,,,12,1992-08-30 00:00:00 -13866,527,89,37,34.0,0,,28,0.0,0,,,,81,1992-08-30 00:00:00 -13867,527,130,16,32.0,17,15.0,15,0.0,42,,,,12,1992-08-30 00:00:00 -13868,527,29,21,19.0,3,1.0,1,10.0,44,5770721.0,,,1,1992-08-30 00:00:00 -13869,527,80,17,24.0,23,16.0,16,0.0,42,,,,12,1992-08-30 00:00:00 -13870,527,94,2,5.0,1,2.0,2,6.0,44,5807316.0,,,1,1992-08-30 00:00:00 -13871,527,118,2,6.0,4,3.0,3,4.0,44,5814618.0,,,1,1992-08-30 00:00:00 -13872,527,83,21,20.0,9,4.0,4,3.0,44,5816780.0,,,1,1992-08-30 00:00:00 -13873,527,56,31,11.0,8,6.0,6,1.0,44,5840751.0,,,1,1992-08-30 00:00:00 -13874,527,108,34,21.0,16,7.0,7,0.0,44,5868958.0,,,1,1992-08-30 00:00:00 -13875,527,101,0,1.0,2,5.0,5,2.0,44,5839090.0,,,1,1992-08-30 00:00:00 -13876,527,87,28,10.0,25,9.0,9,0.0,43,,,,11,1992-08-30 00:00:00 -13877,527,127,35,14.0,15,10.0,10,0.0,43,,,,11,1992-08-30 00:00:00 -13878,527,90,36,16.0,18,11.0,11,0.0,43,,,,11,1992-08-30 00:00:00 -13879,527,124,36,17.0,21,12.0,12,0.0,43,,,,11,1992-08-30 00:00:00 -13880,527,64,31,12.0,10,13.0,13,0.0,43,,,,5,1992-08-30 00:00:00 -13881,527,126,16,33.0,24,14.0,14,0.0,42,,,,12,1992-08-30 00:00:00 -13882,527,109,24,4.0,13,8.0,8,0.0,43,,,,11,1992-08-30 00:00:00 -13883,528,121,5,28.0,7,,21,0.0,12,,,,10,1992-09-13 00:00:00 -13884,528,64,31,12.0,13,,18,0.0,18,,,,5,1992-09-13 00:00:00 -13885,528,124,36,17.0,24,,19,0.0,17,,,,5,1992-09-13 00:00:00 -13886,528,54,5,27.0,3,,20,0.0,12,,,,69,1992-09-13 00:00:00 -13887,528,80,17,24.0,12,,22,0.0,12,,,,5,1992-09-13 00:00:00 -13888,528,130,16,32.0,0,,28,0.0,0,,,,81,1992-09-13 00:00:00 -13889,528,56,31,11.0,11,,24,0.0,5,,,,5,1992-09-13 00:00:00 -13890,528,87,28,10.0,19,,25,0.0,2,,,,22,1992-09-13 00:00:00 -13891,528,127,35,14.0,25,,26,0.0,0,,,,8,1992-09-13 00:00:00 -13892,528,103,17,23.0,0,,27,0.0,0,,,,81,1992-09-13 00:00:00 -13893,528,128,24,3.0,18,,17,0.0,26,,,,5,1992-09-13 00:00:00 -13894,528,91,32,29.0,10,,23,0.0,11,,,,5,1992-09-13 00:00:00 -13895,528,98,35,15.0,20,,16,0.0,30,,,,6,1992-09-13 00:00:00 -13896,528,94,2,5.0,1,,13,0.0,41,,,,10,1992-09-13 00:00:00 -13897,528,122,26,25.0,8,,14,0.0,41,,,,37,1992-09-13 00:00:00 -13898,528,99,26,26.0,15,,15,0.0,35,,,,20,1992-09-13 00:00:00 -13899,528,83,21,20.0,9,2.0,2,6.0,53,4712399.0,,,1,1992-09-13 00:00:00 -13900,528,76,0,2.0,5,4.0,4,3.0,53,4780839.0,,,1,1992-09-13 00:00:00 -13901,528,118,2,6.0,4,5.0,5,2.0,53,4788507.0,,,1,1992-09-13 00:00:00 -13902,528,109,24,4.0,21,6.0,6,1.0,52,,,,11,1992-09-13 00:00:00 -13903,528,101,0,1.0,2,1.0,1,10.0,53,4695349.0,,,1,1992-09-13 00:00:00 -13904,528,93,34,22.0,22,8.0,8,0.0,52,,,,11,1992-09-13 00:00:00 -13905,528,104,28,9.0,16,7.0,7,0.0,52,,,,11,1992-09-13 00:00:00 -13906,528,126,16,33.0,26,,12,0.0,46,,,,7,1992-09-13 00:00:00 -13907,528,29,21,19.0,6,3.0,3,4.0,53,4719722.0,,,1,1992-09-13 00:00:00 -13908,528,90,36,16.0,17,10.0,10,0.0,50,,,,13,1992-09-13 00:00:00 -13909,528,78,32,30.0,23,9.0,9,0.0,50,,,,7,1992-09-13 00:00:00 -13910,528,108,34,21.0,14,11.0,11,0.0,47,,,,5,1992-09-13 00:00:00 -13911,529,78,32,30.0,25,,18,0.0,46,,,,20,1992-09-27 00:00:00 -13912,529,118,2,6.0,2,,19,0.0,43,,,,4,1992-09-27 00:00:00 -13913,529,93,34,22.0,21,,20,0.0,43,,,,29,1992-09-27 00:00:00 -13914,529,128,24,3.0,15,,22,0.0,27,,,,6,1992-09-27 00:00:00 -13915,529,91,32,29.0,13,,23,0.0,25,,,,5,1992-09-27 00:00:00 -13916,529,126,16,33.0,20,,24,0.0,19,,,,10,1992-09-27 00:00:00 -13917,529,54,5,27.0,10,,25,0.0,12,,,,20,1992-09-27 00:00:00 -13918,529,64,31,12.0,9,,26,0.0,2,,,,3,1992-09-27 00:00:00 -13919,529,99,26,26.0,14,,17,0.0,47,,,,5,1992-09-27 00:00:00 -13920,529,121,5,28.0,16,,21,0.0,34,,,,5,1992-09-27 00:00:00 -13921,529,90,36,16.0,22,,16,0.0,48,,,,6,1992-09-27 00:00:00 -13922,529,94,2,5.0,1,1.0,1,10.0,71,5686659.0,,,1,1992-09-27 00:00:00 -13923,529,80,17,24.0,18,14.0,14,0.0,68,,,,13,1992-09-27 00:00:00 -13924,529,130,16,32.0,24,13.0,13,0.0,68,,,,13,1992-09-27 00:00:00 -13925,529,103,17,23.0,26,12.0,12,0.0,68,,,,13,1992-09-27 00:00:00 -13926,529,124,36,17.0,23,11.0,11,0.0,68,,,,13,1992-09-27 00:00:00 -13927,529,87,28,10.0,17,10.0,10,0.0,68,,,,13,1992-09-27 00:00:00 -13928,529,109,24,4.0,12,9.0,9,0.0,69,,,,12,1992-09-27 00:00:00 -13929,529,108,34,21.0,19,,15,0.0,51,,,,68,1992-09-27 00:00:00 -13930,529,29,21,19.0,5,7.0,7,0.0,69,,,,12,1992-09-27 00:00:00 -13931,529,104,28,9.0,8,6.0,6,1.0,70,,,,11,1992-09-27 00:00:00 -13932,529,56,31,11.0,7,5.0,5,2.0,70,,,,11,1992-09-27 00:00:00 -13933,529,83,21,20.0,6,4.0,4,3.0,70,,,,11,1992-09-27 00:00:00 -13934,529,101,0,1.0,3,3.0,3,4.0,70,,,,11,1992-09-27 00:00:00 -13935,529,76,0,2.0,4,2.0,2,6.0,71,5724192.0,,,1,1992-09-27 00:00:00 -13936,529,122,26,25.0,11,8.0,8,0.0,69,,,,12,1992-09-27 00:00:00 -13937,530,94,2,5.0,1,,16,0.0,44,,,,5,1992-10-25 00:00:00 -13938,530,56,31,11.0,7,,17,0.0,44,,,,5,1992-10-25 00:00:00 -13939,530,91,32,29.0,18,,18,0.0,39,,,,4,1992-10-25 00:00:00 -13940,530,99,26,26.0,8,,19,0.0,36,,,,5,1992-10-25 00:00:00 -13941,530,135,36,16.0,23,,20,0.0,27,,,,8,1992-10-25 00:00:00 -13942,530,128,24,3.0,21,,24,0.0,6,,,,20,1992-10-25 00:00:00 -13943,530,64,31,12.0,6,,22,0.0,15,,,,6,1992-10-25 00:00:00 -13944,530,29,21,19.0,5,,23,0.0,13,,,,6,1992-10-25 00:00:00 -13945,530,122,26,25.0,10,,25,0.0,3,,,,6,1992-10-25 00:00:00 -13946,530,101,0,1.0,3,,26,0.0,2,,,,5,1992-10-25 00:00:00 -13947,530,104,28,9.0,24,15.0,15,0.0,51,,,,12,1992-10-25 00:00:00 -13948,530,126,16,33.0,25,,21,0.0,22,,,,20,1992-10-25 00:00:00 -13949,530,80,17,24.0,14,14.0,14,0.0,51,,,,12,1992-10-25 00:00:00 -13950,530,77,5,28.0,11,12.0,12,0.0,52,,,,11,1992-10-25 00:00:00 -13951,530,109,24,4.0,9,4.0,4,3.0,52,,,,11,1992-10-25 00:00:00 -13952,530,78,32,30.0,20,11.0,11,0.0,52,,,,11,1992-10-25 00:00:00 -13953,530,93,34,22.0,19,10.0,10,0.0,52,,,,11,1992-10-25 00:00:00 -13954,530,108,34,21.0,22,9.0,9,0.0,52,,,,11,1992-10-25 00:00:00 -13955,530,87,28,10.0,16,8.0,8,0.0,52,,,,11,1992-10-25 00:00:00 -13956,530,130,16,32.0,17,7.0,7,0.0,52,,,,11,1992-10-25 00:00:00 -13957,530,103,17,23.0,12,6.0,6,1.0,52,,,,11,1992-10-25 00:00:00 -13958,530,54,5,27.0,15,5.0,5,2.0,52,,,,11,1992-10-25 00:00:00 -13959,530,83,21,20.0,13,3.0,3,4.0,53,5665036.0,,,1,1992-10-25 00:00:00 -13960,530,76,0,2.0,4,2.0,2,6.0,53,5603262.0,,,1,1992-10-25 00:00:00 -13961,530,118,2,6.0,2,1.0,1,10.0,53,5589533.0,,,1,1992-10-25 00:00:00 -13962,530,124,36,17.0,26,13.0,13,0.0,51,,,,12,1992-10-25 00:00:00 -13963,531,118,2,6.0,3,,17,0.0,50,,,,5,1992-11-08 00:00:00 -13964,531,91,32,29.0,21,,16,0.0,51,,,,69,1992-11-08 00:00:00 -13965,531,124,36,17.0,23,,15,0.0,55,,,,6,1992-11-08 00:00:00 -13966,531,78,32,30.0,26,,18,0.0,35,,,,24,1992-11-08 00:00:00 -13967,531,128,24,3.0,13,,26,0.0,0,,,,3,1992-11-08 00:00:00 -13968,531,109,24,4.0,7,,19,0.0,29,,,,5,1992-11-08 00:00:00 -13969,531,93,34,22.0,14,,25,0.0,0,,,,3,1992-11-08 00:00:00 -13970,531,101,0,1.0,2,,21,0.0,18,,,,4,1992-11-08 00:00:00 -13971,531,126,16,33.0,20,,22,0.0,7,,,,20,1992-11-08 00:00:00 -13972,531,99,26,26.0,9,,23,0.0,4,,,,5,1992-11-08 00:00:00 -13973,531,104,28,9.0,11,,24,0.0,0,,,,5,1992-11-08 00:00:00 -13974,531,94,2,5.0,1,,20,0.0,18,,,,4,1992-11-08 00:00:00 -13975,531,108,34,21.0,24,,14,0.0,70,,,,6,1992-11-08 00:00:00 -13976,531,77,5,28.0,19,11.0,11,0.0,79,,,,12,1992-11-08 00:00:00 -13977,531,135,36,16.0,25,12.0,12,0.0,78,,,,13,1992-11-08 00:00:00 -13978,531,64,31,12.0,12,13.0,13,0.0,77,,,,14,1992-11-08 00:00:00 -13979,531,76,0,2.0,4,1.0,1,10.0,81,6414786.0,,,1,1992-11-08 00:00:00 -13980,531,29,21,19.0,5,2.0,2,6.0,81,6415527.0,,,1,1992-11-08 00:00:00 -13981,531,54,5,27.0,6,4.0,4,3.0,80,,,,11,1992-11-08 00:00:00 -13982,531,122,26,25.0,22,5.0,5,2.0,80,,,,11,1992-11-08 00:00:00 -13983,531,83,21,20.0,8,3.0,3,4.0,81,6468942.0,,,1,1992-11-08 00:00:00 -13984,531,56,31,11.0,10,7.0,7,0.0,80,,,,11,1992-11-08 00:00:00 -13985,531,87,28,10.0,18,8.0,8,0.0,79,,,,12,1992-11-08 00:00:00 -13986,531,103,17,23.0,17,9.0,9,0.0,79,,,,12,1992-11-08 00:00:00 -13987,531,80,17,24.0,16,10.0,10,0.0,79,,,,12,1992-11-08 00:00:00 -13988,531,130,16,32.0,15,6.0,6,1.0,80,,,,11,1992-11-08 00:00:00 -13989,532,119,17,24.0,24,,18,0.0,21,,,,4,1993-03-14 00:00:00 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-14191,539,101,0,8.0,5,4.0,4,3.0,72,5947646.0,,,1,1993-07-04 00:00:00 -14192,539,29,21,5.0,7,3.0,3,4.0,72,5936450.0,,,1,1993-07-04 00:00:00 -14193,539,70,2,0.0,1,2.0,2,6.0,72,5915583.0,,,1,1993-07-04 00:00:00 -14194,539,116,2,2.0,2,1.0,1,10.0,72,5915241.0,,,1,1993-07-04 00:00:00 -14195,539,117,28,9.0,15,13.0,13,0.0,70,,,,12,1993-07-04 00:00:00 -14196,539,86,26,26.0,4,,21,0.0,20,,,,20,1993-07-04 00:00:00 -14197,540,29,21,5.0,3,2.0,2,6.0,59,5145849.0,,,1,1993-07-11 00:00:00 -14198,540,118,21,6.0,5,3.0,3,4.0,59,5215671.0,,,1,1993-07-11 00:00:00 -14199,540,116,2,2.0,1,1.0,1,10.0,59,5138189.0,,,1,1993-07-11 00:00:00 -14200,540,104,25,21.0,0,,26,0.0,0,,,,81,1993-07-11 00:00:00 -14201,540,99,32,20.0,17,,25,0.0,0,,,,86,1993-07-11 00:00:00 -14202,540,120,0,7.0,11,,24,0.0,0,,,,20,1993-07-11 00:00:00 -14203,540,87,28,10.0,10,,23,0.0,8,,,,20,1993-07-11 00:00:00 -14204,540,76,5,28.0,13,,22,0.0,10,,,,22,1993-07-11 00:00:00 -14205,540,90,14,29.0,18,,21,0.0,24,,,,20,1993-07-11 00:00:00 -14206,540,93,17,24.0,20,,20,0.0,31,,,,68,1993-07-11 00:00:00 -14207,540,68,25,22.0,25,,19,0.0,32,,,,10,1993-07-11 00:00:00 -14208,540,122,16,15.0,23,,18,0.0,41,,,,67,1993-07-11 00:00:00 -14209,540,69,31,11.0,14,,17,0.0,41,,,,22,1993-07-11 00:00:00 -14210,540,109,24,4.0,21,,15,0.0,43,,,,62,1993-07-11 00:00:00 -14211,540,83,26,25.0,6,14.0,14,0.0,53,,,,6,1993-07-11 00:00:00 -14212,540,64,31,12.0,7,4.0,4,3.0,59,5216596.0,,,1,1993-07-11 00:00:00 -14213,540,101,0,8.0,4,5.0,5,2.0,58,,,,60,1993-07-11 00:00:00 -14214,540,117,28,9.0,8,6.0,6,1.0,58,,,,11,1993-07-11 00:00:00 -14215,540,86,26,26.0,9,7.0,7,0.0,58,,,,11,1993-07-11 00:00:00 -14216,540,108,14,30.0,16,8.0,8,0.0,58,,,,11,1993-07-11 00:00:00 -14217,540,70,2,0.0,2,,16,0.0,41,,,,5,1993-07-11 00:00:00 -14218,540,21,16,14.0,15,10.0,10,0.0,58,,,,11,1993-07-11 00:00:00 -14219,540,111,32,19.0,24,11.0,11,0.0,57,,,,12,1993-07-11 00:00:00 -14220,540,103,17,23.0,19,12.0,12,0.0,56,,,,6,1993-07-11 00:00:00 -14221,540,78,24,3.0,22,13.0,13,0.0,55,,,,14,1993-07-11 00:00:00 -14222,540,54,5,27.0,12,9.0,9,0.0,58,,,,11,1993-07-11 00:00:00 -14223,541,117,28,9.0,11,17.0,17,0.0,42,,,,13,1993-07-25 00:00:00 -14224,541,99,32,20.0,16,,26,0.0,0,,,,6,1993-07-25 00:00:00 -14225,541,109,24,4.0,19,,25,0.0,1,,,,6,1993-07-25 00:00:00 -14226,541,68,25,22.0,25,,24,0.0,4,,,,22,1993-07-25 00:00:00 -14227,541,120,0,7.0,12,,23,0.0,4,,,,4,1993-07-25 00:00:00 -14228,541,87,28,10.0,8,,22,0.0,9,,,,4,1993-07-25 00:00:00 -14229,541,69,31,11.0,15,,21,0.0,19,,,,20,1993-07-25 00:00:00 -14230,541,108,14,30.0,18,,20,0.0,22,,,,20,1993-07-25 00:00:00 -14231,541,78,24,3.0,21,,19,0.0,28,,,,86,1993-07-25 00:00:00 -14232,541,21,16,14.0,17,,18,0.0,34,,,,67,1993-07-25 00:00:00 -14233,541,104,25,21.0,26,16.0,16,0.0,43,,,,12,1993-07-25 00:00:00 -14234,541,70,2,0.0,2,15.0,15,0.0,43,,,,27,1993-07-25 00:00:00 -14235,541,29,21,5.0,3,2.0,2,6.0,45,4737549.0,,,1,1993-07-25 00:00:00 -14236,541,116,2,2.0,1,1.0,1,10.0,45,4720885.0,,,1,1993-07-25 00:00:00 -14237,541,93,17,24.0,22,14.0,14,0.0,44,,,,11,1993-07-25 00:00:00 -14238,541,86,26,26.0,5,3.0,3,4.0,45,4780234.0,,,1,1993-07-25 00:00:00 -14239,541,101,0,8.0,4,4.0,4,3.0,45,4789114.0,,,1,1993-07-25 00:00:00 -14240,541,76,5,28.0,9,6.0,6,1.0,45,4815639.0,,,1,1993-07-25 00:00:00 -14241,541,54,5,27.0,10,7.0,7,0.0,45,4816726.0,,,1,1993-07-25 00:00:00 -14242,541,118,21,6.0,7,5.0,5,2.0,45,4812401.0,,,1,1993-07-25 00:00:00 -14243,541,90,14,29.0,14,9.0,9,0.0,44,,,,11,1993-07-25 00:00:00 -14244,541,64,31,12.0,13,10.0,10,0.0,44,,,,11,1993-07-25 00:00:00 -14245,541,103,17,23.0,20,11.0,11,0.0,44,,,,11,1993-07-25 00:00:00 -14246,541,111,32,19.0,23,12.0,12,0.0,44,,,,11,1993-07-25 00:00:00 -14247,541,122,16,15.0,24,13.0,13,0.0,44,,,,11,1993-07-25 00:00:00 -14248,541,83,26,25.0,6,8.0,8,0.0,44,,,,11,1993-07-25 00:00:00 -14249,542,29,21,5.0,3,,20,0.0,26,,,,48,1993-08-15 00:00:00 -14250,542,104,25,21.0,25,,17,0.0,39,,,,25,1993-08-15 00:00:00 -14251,542,64,31,12.0,20,,18,0.0,38,,,,20,1993-08-15 00:00:00 -14252,542,68,25,22.0,26,,19,0.0,37,,,,20,1993-08-15 00:00:00 -14253,542,103,17,23.0,14,,21,0.0,22,,,,22,1993-08-15 00:00:00 -14254,542,87,28,10.0,10,,16,0.0,41,,,,20,1993-08-15 00:00:00 -14255,542,108,14,30.0,15,,23,0.0,18,,,,5,1993-08-15 00:00:00 -14256,542,101,0,8.0,4,,24,0.0,17,,,,37,1993-08-15 00:00:00 -14257,542,120,0,7.0,11,,25,0.0,15,,,,37,1993-08-15 00:00:00 -14258,542,21,16,14.0,16,,26,0.0,0,,,,3,1993-08-15 00:00:00 -14259,542,54,5,27.0,8,,22,0.0,22,,,,20,1993-08-15 00:00:00 -14260,542,69,31,11.0,21,,15,0.0,45,,,,6,1993-08-15 00:00:00 -14261,542,118,21,6.0,5,2.0,2,6.0,77,6531013.0,,,1,1993-08-15 00:00:00 -14262,542,93,17,24.0,7,,13,0.0,59,,,,3,1993-08-15 00:00:00 -14263,542,99,32,20.0,18,,14,0.0,54,,,,5,1993-08-15 00:00:00 -14264,542,76,5,28.0,6,3.0,3,4.0,77,6537140.0,,,1,1993-08-15 00:00:00 -14265,542,117,28,9.0,9,4.0,4,3.0,76,,,,11,1993-08-15 00:00:00 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-14281,543,21,16,14.0,12,,23,0.0,11,,,,67,1993-08-29 00:00:00 -14282,543,54,5,27.0,4,,24,0.0,4,,,,22,1993-08-29 00:00:00 -14283,543,122,16,15.0,20,,25,0.0,0,,,,6,1993-08-29 00:00:00 -14284,543,103,17,23.0,22,,20,0.0,15,,,,20,1993-08-29 00:00:00 -14285,543,104,25,21.0,25,14.0,14,0.0,41,,,,13,1993-08-29 00:00:00 -14286,543,93,17,24.0,21,,21,0.0,15,,,,20,1993-08-29 00:00:00 -14287,543,111,32,19.0,18,12.0,12,0.0,42,,,,12,1993-08-29 00:00:00 -14288,543,68,25,22.0,24,13.0,13,0.0,42,,,,12,1993-08-29 00:00:00 -14289,543,70,2,0.0,2,1.0,1,10.0,44,5072124.0,,,1,1993-08-29 00:00:00 -14290,543,29,21,5.0,3,2.0,2,6.0,44,5075792.0,,,1,1993-08-29 00:00:00 -14291,543,116,2,2.0,1,3.0,3,4.0,44,5087112.0,,,1,1993-08-29 00:00:00 -14292,543,101,0,8.0,5,4.0,4,3.0,44,5171887.0,,,1,1993-08-29 00:00:00 -14293,543,64,31,12.0,10,5.0,5,2.0,43,,,,11,1993-08-29 00:00:00 -14294,543,78,24,3.0,23,15.0,15,0.0,40,,,,14,1993-08-29 00:00:00 -14295,543,83,26,25.0,11,7.0,7,0.0,43,,,,11,1993-08-29 00:00:00 -14296,543,120,0,7.0,14,8.0,8,0.0,43,,,,11,1993-08-29 00:00:00 -14297,543,108,14,30.0,9,9.0,9,0.0,43,,,,11,1993-08-29 00:00:00 -14298,543,76,5,28.0,16,10.0,10,0.0,42,,,,4,1993-08-29 00:00:00 -14299,543,118,21,6.0,8,6.0,6,1.0,43,,,,11,1993-08-29 00:00:00 -14300,543,86,26,26.0,15,11.0,11,0.0,42,,,,4,1993-08-29 00:00:00 -14301,544,86,26,26.0,14,,17,0.0,20,,,,20,1993-09-12 00:00:00 -14302,544,64,31,12.0,7,,19,0.0,14,,,,20,1993-09-12 00:00:00 -14303,544,83,26,25.0,12,,20,0.0,8,,,,4,1993-09-12 00:00:00 -14304,544,101,0,8.0,4,,21,0.0,8,,,,4,1993-09-12 00:00:00 -14305,544,108,14,30.0,13,,24,0.0,0,,,,4,1993-09-12 00:00:00 -14306,544,117,28,9.0,11,,23,0.0,0,,,,4,1993-09-12 00:00:00 -14307,544,29,21,5.0,5,,16,0.0,21,,,,5,1993-09-12 00:00:00 -14308,544,21,16,14.0,19,,25,0.0,0,,,,4,1993-09-12 00:00:00 -14309,544,123,16,15.0,23,,26,0.0,0,,,,4,1993-09-12 00:00:00 -14310,544,87,28,10.0,8,,22,0.0,0,,,,4,1993-09-12 00:00:00 -14311,544,104,25,21.0,21,,15,0.0,23,,,,22,1993-09-12 00:00:00 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00:00:00 -14343,545,116,2,2.0,2,2.0,2,6.0,71,5567291.0,,,1,1993-09-26 00:00:00 -14344,545,70,2,0.0,1,3.0,3,4.0,71,5574515.0,,,1,1993-09-26 00:00:00 -14345,545,54,5,27.0,5,4.0,4,3.0,71,5633914.0,,,1,1993-09-26 00:00:00 -14346,545,108,14,30.0,12,7.0,7,0.0,69,,,,12,1993-09-26 00:00:00 -14347,545,83,26,25.0,11,6.0,6,1.0,70,,,,11,1993-09-26 00:00:00 -14348,545,93,17,24.0,19,8.0,8,0.0,69,,,,12,1993-09-26 00:00:00 -14349,545,103,17,23.0,24,9.0,9,0.0,69,,,,12,1993-09-26 00:00:00 -14350,545,111,32,19.0,20,10.0,10,0.0,69,,,,12,1993-09-26 00:00:00 -14351,545,90,14,29.0,13,5.0,5,2.0,70,,,,11,1993-09-26 00:00:00 -14352,545,109,24,4.0,17,12.0,12,0.0,68,,,,13,1993-09-26 00:00:00 -14353,546,76,5,28.0,5,,16,0.0,40,,,,5,1993-10-24 00:00:00 -14354,546,87,28,10.0,9,,17,0.0,28,,,,20,1993-10-24 00:00:00 -14355,546,110,17,23.0,13,,18,0.0,26,,,,54,1993-10-24 00:00:00 -14356,546,90,14,29.0,16,,20,0.0,25,,,,5,1993-10-24 00:00:00 -14357,546,118,21,6.0,10,,15,0.0,45,,,,20,1993-10-24 00:00:00 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-14467,550,80,28,10.0,11,,16,0.0,40,,,,5,1994-05-01 00:00:00 -14468,550,99,32,20.0,18,,23,0.0,5,,,,54,1994-05-01 00:00:00 -14469,550,104,17,24.0,15,,15,0.0,44,,,,36,1994-05-01 00:00:00 -14470,550,76,5,28.0,3,,21,0.0,16,,,,22,1994-05-01 00:00:00 -14471,550,103,28,9.0,16,13.0,13,0.0,54,,,,20,1994-05-01 00:00:00 -14472,550,109,16,15.0,21,,14,0.0,49,,,,20,1994-05-01 00:00:00 -14473,550,77,5,27.0,6,2.0,2,6.0,58,5363584.0,,,1,1994-05-01 00:00:00 -14474,550,56,0,7.0,8,3.0,3,4.0,58,5379321.0,,,1,1994-05-01 00:00:00 -14475,550,90,14,29.0,10,4.0,4,3.0,58,5382300.0,,,1,1994-05-01 00:00:00 -14476,550,78,24,3.0,9,5.0,5,2.0,57,,,,11,1994-05-01 00:00:00 -14477,550,70,2,0.0,4,6.0,6,1.0,57,,,,11,1994-05-01 00:00:00 -14478,550,29,21,5.0,2,1.0,1,10.0,58,5308642.0,,,1,1994-05-01 00:00:00 -14479,550,83,0,8.0,13,8.0,8,0.0,57,,,,11,1994-05-01 00:00:00 -14480,550,86,24,4.0,12,9.0,9,0.0,56,,,,12,1994-05-01 00:00:00 -14481,550,64,31,12.0,20,10.0,10,0.0,56,,,,12,1994-05-01 00:00:00 -14482,550,43,26,26.0,19,11.0,11,0.0,56,,,,12,1994-05-01 00:00:00 -14483,550,102,26,25.0,17,12.0,12,0.0,55,,,,13,1994-05-01 00:00:00 -14484,550,48,14,30.0,7,7.0,7,0.0,57,,,,11,1994-05-01 00:00:00 -14485,551,100,30,31.0,22,,16,0.0,45,,,,5,1994-05-15 00:00:00 -14486,551,86,24,4.0,10,,17,0.0,40,,,,5,1994-05-15 00:00:00 -14487,551,78,24,3.0,11,,18,0.0,38,,,,6,1994-05-15 00:00:00 -14488,551,102,26,25.0,21,,19,0.0,34,,,,20,1994-05-15 00:00:00 -14489,551,56,0,7.0,2,,21,0.0,0,,,,4,1994-05-15 00:00:00 -14490,551,70,2,0.0,4,,22,0.0,0,,,,4,1994-05-15 00:00:00 -14491,551,80,28,10.0,7,,23,0.0,0,,,,4,1994-05-15 00:00:00 -14492,551,93,17,23.0,9,,24,0.0,0,,,,4,1994-05-15 00:00:00 -14493,551,103,28,9.0,6,,15,0.0,47,,,,6,1994-05-15 00:00:00 -14494,551,21,16,14.0,15,,20,0.0,27,,,,10,1994-05-15 00:00:00 -14495,551,91,29,34.0,23,,14,0.0,49,,,,6,1994-05-15 00:00:00 -14496,551,108,21,6.0,17,7.0,7,0.0,77,,,,11,1994-05-15 00:00:00 -14497,551,48,14,30.0,0,,25,0.0,0,,,,54,1994-05-15 00:00:00 -14498,551,82,31,11.0,19,11.0,11,0.0,73,,,,15,1994-05-15 00:00:00 -14499,551,99,32,20.0,13,10.0,10,0.0,75,,,,13,1994-05-15 00:00:00 -14500,551,43,26,26.0,20,9.0,9,0.0,76,,,,12,1994-05-15 00:00:00 -14501,551,105,32,19.0,18,8.0,8,0.0,76,,,,12,1994-05-15 00:00:00 -14502,551,104,17,24.0,12,6.0,6,1.0,77,,,,11,1994-05-15 00:00:00 -14503,551,54,5,27.0,5,5.0,5,2.0,77,,,,11,1994-05-15 00:00:00 -14504,551,109,16,15.0,14,4.0,4,3.0,77,,,,11,1994-05-15 00:00:00 -14505,551,76,5,28.0,3,3.0,3,4.0,78,6672124.0,,,1,1994-05-15 00:00:00 -14506,551,83,0,8.0,8,2.0,2,6.0,78,6632578.0,,,1,1994-05-15 00:00:00 -14507,551,29,21,5.0,1,1.0,1,10.0,78,6595300.0,,,1,1994-05-15 00:00:00 -14508,551,107,29,33.0,24,,13,0.0,53,,,,68,1994-05-15 00:00:00 -14509,551,90,14,29.0,0,,26,0.0,0,,,,82,1994-05-15 00:00:00 -14510,551,64,31,12.0,16,,12,0.0,68,,,,6,1994-05-15 00:00:00 -14511,552,80,28,10.0,15,,20,0.0,24,,,,69,1994-05-29 00:00:00 -14512,552,84,30,32.0,0,,27,0.0,0,,,,82,1994-05-29 00:00:00 -14513,552,105,32,19.0,17,,26,0.0,0,,,,5,1994-05-29 00:00:00 -14514,552,107,29,33.0,26,,25,0.0,2,,,,20,1994-05-29 00:00:00 -14515,552,104,17,24.0,14,,24,0.0,4,,,,5,1994-05-29 00:00:00 -14516,552,78,24,3.0,10,,23,0.0,16,,,,5,1994-05-29 00:00:00 -14517,552,99,32,20.0,16,,22,0.0,19,,,,21,1994-05-29 00:00:00 -14518,552,48,14,30.0,12,,21,0.0,21,,,,6,1994-05-29 00:00:00 -14519,552,76,5,28.0,7,,19,0.0,27,,,,6,1994-05-29 00:00:00 -14520,552,91,29,34.0,25,,18,0.0,32,,,,41,1994-05-29 00:00:00 -14521,552,13,2,2.0,9,,17,0.0,32,,,,10,1994-05-29 00:00:00 -14522,552,21,16,14.0,5,,15,0.0,39,,,,20,1994-05-29 00:00:00 -14523,552,64,31,12.0,22,,14,0.0,41,,,,20,1994-05-29 00:00:00 -14524,552,103,28,9.0,21,,16,0.0,35,,,,5,1994-05-29 00:00:00 -14525,552,108,21,6.0,4,,12,0.0,53,,,,5,1994-05-29 00:00:00 -14526,552,70,2,0.0,2,1.0,1,10.0,65,5774300.0,,,1,1994-05-29 00:00:00 -14527,552,29,21,5.0,1,2.0,2,6.0,65,5798466.0,,,1,1994-05-29 00:00:00 -14528,552,86,24,4.0,11,3.0,3,4.0,65,5861269.0,,,1,1994-05-29 00:00:00 -14529,552,54,5,27.0,6,4.0,4,3.0,64,,,,11,1994-05-29 00:00:00 -14530,552,56,0,7.0,3,,13,0.0,48,,,,5,1994-05-29 00:00:00 -14531,552,55,16,15.0,13,6.0,6,1.0,64,,,,11,1994-05-29 00:00:00 -14532,552,93,17,23.0,18,5.0,5,2.0,64,,,,11,1994-05-29 00:00:00 -14533,552,102,26,25.0,20,8.0,8,0.0,62,,,,13,1994-05-29 00:00:00 -14534,552,69,31,11.0,23,9.0,9,0.0,62,,,,13,1994-05-29 00:00:00 -14535,552,100,30,31.0,24,10.0,10,0.0,61,,,,14,1994-05-29 00:00:00 -14536,552,83,0,8.0,8,11.0,11,0.0,59,,,,7,1994-05-29 00:00:00 -14537,552,43,26,26.0,19,7.0,7,0.0,63,,,,12,1994-05-29 00:00:00 -14538,553,80,28,10.0,11,,19,0.0,50,,,,7,1994-06-12 00:00:00 -14539,553,55,16,15.0,8,,23,0.0,40,,,,20,1994-06-12 00:00:00 -14540,553,91,29,34.0,26,,20,0.0,47,,,,51,1994-06-12 00:00:00 -14541,553,99,32,20.0,21,,21,0.0,45,,,,8,1994-06-12 00:00:00 -14542,553,78,24,3.0,9,,22,0.0,44,,,,3,1994-06-12 00:00:00 -14543,553,109,14,29.0,14,,24,0.0,24,,,,51,1994-06-12 00:00:00 -14544,553,70,2,0.0,4,2.0,2,6.0,69,6311760.0,,,1,1994-06-12 00:00:00 -14545,553,83,0,8.0,12,,26,0.0,3,,,,10,1994-06-12 00:00:00 -14546,553,107,29,33.0,0,,27,0.0,0,,,,81,1994-06-12 00:00:00 -14547,553,29,21,5.0,1,1.0,1,10.0,69,6272100.0,,,1,1994-06-12 00:00:00 -14548,553,54,5,27.0,2,3.0,3,4.0,69,6345438.0,,,1,1994-06-12 00:00:00 -14549,553,105,32,19.0,22,,18,0.0,57,,,,5,1994-06-12 00:00:00 -14550,553,48,14,30.0,10,,25,0.0,5,,,,20,1994-06-12 00:00:00 -14551,553,56,0,7.0,7,,17,0.0,61,,,,5,1994-06-12 00:00:00 -14552,553,93,17,23.0,15,9.0,9,0.0,68,,,,11,1994-06-12 00:00:00 -14553,553,69,31,11.0,23,15.0,15,0.0,62,,,,17,1994-06-12 00:00:00 -14554,553,103,28,9.0,16,,16,0.0,68,,,,2,1994-06-12 00:00:00 -14555,553,76,5,28.0,3,4.0,4,3.0,69,6347709.0,,,1,1994-06-12 00:00:00 -14556,553,13,2,2.0,5,5.0,5,2.0,68,,,,11,1994-06-12 00:00:00 -14557,553,108,21,6.0,20,6.0,6,1.0,68,,,,11,1994-06-12 00:00:00 -14558,553,64,31,12.0,17,8.0,8,0.0,68,,,,11,1994-06-12 00:00:00 -14559,553,21,16,14.0,6,7.0,7,0.0,68,,,,11,1994-06-12 00:00:00 -14560,553,86,24,4.0,13,10.0,10,0.0,67,,,,20,1994-06-12 00:00:00 -14561,553,104,17,24.0,18,11.0,11,0.0,67,,,,12,1994-06-12 00:00:00 -14562,553,43,26,26.0,19,12.0,12,0.0,67,,,,12,1994-06-12 00:00:00 -14563,553,102,26,25.0,24,13.0,13,0.0,66,,,,13,1994-06-12 00:00:00 -14564,553,100,30,31.0,25,14.0,14,0.0,65,,,,14,1994-06-12 00:00:00 -14565,554,43,26,26.0,13,,21,0.0,28,,,,4,1994-07-03 00:00:00 -14566,554,83,0,8.0,12,,19,0.0,29,,,,5,1994-07-03 00:00:00 -14567,554,80,28,10.0,22,,20,0.0,28,,,,4,1994-07-03 00:00:00 -14568,554,105,32,19.0,25,,18,0.0,36,,,,5,1994-07-03 00:00:00 -14569,554,100,30,31.0,24,,22,0.0,28,,,,7,1994-07-03 00:00:00 -14570,554,91,29,34.0,0,,28,0.0,0,,,,81,1994-07-03 00:00:00 -14571,554,55,16,15.0,6,,24,0.0,24,,,,6,1994-07-03 00:00:00 -14572,554,104,17,24.0,21,,25,0.0,21,,,,5,1994-07-03 00:00:00 -14573,554,69,31,11.0,23,,26,0.0,20,,,,5,1994-07-03 00:00:00 -14574,554,107,29,33.0,0,,27,0.0,0,,,,81,1994-07-03 00:00:00 -14575,554,102,26,25.0,15,,17,0.0,40,,,,6,1994-07-03 00:00:00 -14576,554,49,21,6.0,8,,23,0.0,25,,,,20,1994-07-03 00:00:00 -14577,554,21,16,14.0,7,,16,0.0,41,,,,4,1994-07-03 00:00:00 -14578,554,76,5,28.0,5,3.0,3,4.0,72,5968965.0,,,1,1994-07-03 00:00:00 -14579,554,94,2,2.0,2,,14,0.0,45,,,,6,1994-07-03 00:00:00 -14580,554,29,21,5.0,3,1.0,1,10.0,72,5916200.0,,,1,1994-07-03 00:00:00 -14581,554,54,5,27.0,4,,15,0.0,41,,,,4,1994-07-03 00:00:00 -14582,554,70,2,0.0,1,2.0,2,6.0,72,5928842.0,,,1,1994-07-03 00:00:00 -14583,554,48,14,30.0,10,4.0,4,3.0,71,,,,11,1994-07-03 00:00:00 -14584,554,93,17,23.0,16,5.0,5,2.0,70,,,,12,1994-07-03 00:00:00 -14585,554,64,31,12.0,19,7.0,7,0.0,70,,,,12,1994-07-03 00:00:00 -14586,554,109,14,29.0,11,6.0,6,1.0,70,,,,12,1994-07-03 00:00:00 -14587,554,110,30,32.0,26,9.0,9,0.0,68,,,,14,1994-07-03 00:00:00 -14588,554,86,24,4.0,17,10.0,10,0.0,67,,,,15,1994-07-03 00:00:00 -14589,554,99,32,20.0,20,11.0,11,0.0,66,,,,5,1994-07-03 00:00:00 -14590,554,78,24,3.0,14,,12,0.0,53,,,,20,1994-07-03 00:00:00 -14591,554,56,0,7.0,9,,13,0.0,48,,,,5,1994-07-03 00:00:00 -14592,554,103,28,9.0,18,8.0,8,0.0,70,,,,12,1994-07-03 00:00:00 -14593,555,104,17,24.0,17,,18,0.0,48,,,,5,1994-07-10 00:00:00 -14594,555,29,21,5.0,2,,17,0.0,60,,,,2,1994-07-10 00:00:00 -14595,555,76,5,28.0,3,,19,0.0,32,,,,5,1994-07-10 00:00:00 -14596,555,83,0,8.0,9,,25,0.0,0,,,,5,1994-07-10 00:00:00 -14597,555,99,32,20.0,22,,21,0.0,12,,,,5,1994-07-10 00:00:00 -14598,555,109,14,29.0,18,,22,0.0,11,,,,5,1994-07-10 00:00:00 -14599,555,69,31,11.0,19,,24,0.0,4,,,,5,1994-07-10 00:00:00 -14600,555,110,30,32.0,26,16.0,16,0.0,57,,,,13,1994-07-10 00:00:00 -14601,555,55,16,15.0,12,,26,0.0,0,,,,5,1994-07-10 00:00:00 -14602,555,86,24,4.0,11,,20,0.0,20,,,,6,1994-07-10 00:00:00 -14603,555,100,30,31.0,25,15.0,15,0.0,57,,,,13,1994-07-10 00:00:00 -14604,555,103,28,9.0,20,9.0,9,0.0,58,,,,12,1994-07-10 00:00:00 -14605,555,102,26,25.0,23,13.0,13,0.0,58,,,,12,1994-07-10 00:00:00 -14606,555,43,26,26.0,15,12.0,12,0.0,58,,,,12,1994-07-10 00:00:00 -14607,555,64,31,12.0,21,11.0,11,0.0,58,,,,12,1994-07-10 00:00:00 -14608,555,93,17,23.0,14,10.0,10,0.0,58,,,,12,1994-07-10 00:00:00 -14609,555,49,21,6.0,10,8.0,8,0.0,59,,,,11,1994-07-10 00:00:00 -14610,555,48,14,30.0,13,7.0,7,0.0,59,,,,11,1994-07-10 00:00:00 -14611,555,78,24,3.0,8,6.0,6,1.0,59,,,,11,1994-07-10 00:00:00 -14612,555,13,2,2.0,7,5.0,5,2.0,59,,,,11,1994-07-10 00:00:00 -14613,555,21,16,14.0,6,4.0,4,3.0,60,5505391.0,,,1,1994-07-10 00:00:00 -14614,555,56,0,7.0,5,3.0,3,4.0,60,5504299.0,,,1,1994-07-10 00:00:00 -14615,555,54,5,27.0,4,2.0,2,6.0,60,5471768.0,,,1,1994-07-10 00:00:00 -14616,555,70,2,0.0,1,1.0,1,10.0,60,5403640.0,,,1,1994-07-10 00:00:00 -14617,555,91,29,34.0,0,,27,0.0,0,,,,81,1994-07-10 00:00:00 -14618,555,105,32,19.0,24,14.0,14,0.0,58,,,,12,1994-07-10 00:00:00 -14619,555,107,29,33.0,0,,28,0.0,0,,,,81,1994-07-10 00:00:00 -14620,555,80,28,10.0,16,,23,0.0,5,,,,5,1994-07-10 00:00:00 -14621,556,43,26,26.0,12,2.0,2,6.0,45,5011979.0,,,1,1994-07-31 00:00:00 -14622,556,102,26,25.0,14,3.0,3,4.0,45,5022621.0,,,1,1994-07-31 00:00:00 -14623,556,107,29,33.0,0,,28,0.0,0,,,,81,1994-07-31 00:00:00 -14624,556,91,29,34.0,0,,27,0.0,0,,,,81,1994-07-31 00:00:00 -14625,556,104,17,24.0,23,,26,0.0,0,,,,4,1994-07-31 00:00:00 -14626,556,69,31,11.0,21,,25,0.0,0,,,,4,1994-07-31 00:00:00 -14627,556,93,17,23.0,20,,24,0.0,0,,,,4,1994-07-31 00:00:00 -14628,556,109,14,29.0,18,,23,0.0,0,,,,4,1994-07-31 00:00:00 -14629,556,64,31,12.0,15,,22,0.0,0,,,,4,1994-07-31 00:00:00 -14630,556,21,16,14.0,11,,21,0.0,0,,,,4,1994-07-31 00:00:00 -14631,556,55,16,15.0,10,,20,0.0,0,,,,4,1994-07-31 00:00:00 -14632,556,48,14,30.0,9,,19,0.0,0,,,,4,1994-07-31 00:00:00 -14633,556,56,0,7.0,8,,18,0.0,0,,,,4,1994-07-31 00:00:00 -14634,556,86,24,4.0,7,,17,0.0,0,,,,4,1994-07-31 00:00:00 -14635,556,54,5,27.0,2,,16,0.0,1,,,,10,1994-07-31 00:00:00 -14636,556,49,21,6.0,19,,14,0.0,15,,,,42,1994-07-31 00:00:00 -14637,556,78,24,3.0,5,,15,0.0,6,,,,37,1994-07-31 00:00:00 -14638,556,76,5,28.0,1,1.0,1,10.0,45,4957200.0,,,1,1994-07-31 00:00:00 -14639,556,103,28,9.0,17,4.0,4,3.0,45,5038809.0,,,1,1994-07-31 00:00:00 -14640,556,80,28,10.0,16,5.0,5,2.0,45,5047744.0,,,1,1994-07-31 00:00:00 -14641,556,105,32,19.0,24,7.0,7,0.0,44,,,,11,1994-07-31 00:00:00 -14642,556,99,32,20.0,22,6.0,6,1.0,45,5062645.0,,,1,1994-07-31 00:00:00 -14643,556,110,30,32.0,26,,9,0.0,39,,,,5,1994-07-31 00:00:00 -14644,556,100,30,31.0,25,,10,0.0,37,,,,8,1994-07-31 00:00:00 -14645,556,29,21,5.0,4,,11,0.0,20,,,,5,1994-07-31 00:00:00 -14646,556,83,0,8.0,13,,12,0.0,19,,,,5,1994-07-31 00:00:00 -14647,556,13,2,2.0,6,,13,0.0,17,,,,10,1994-07-31 00:00:00 -14648,556,70,2,0.0,3,8.0,8,0.0,44,,,,11,1994-07-31 00:00:00 -14649,557,109,14,29.0,17,,20,0.0,30,,,,4,1994-08-14 00:00:00 -14650,557,93,17,23.0,15,,17,0.0,58,,,,20,1994-08-14 00:00:00 -14651,557,48,14,30.0,8,,18,0.0,39,,,,6,1994-08-14 00:00:00 -14652,557,64,31,12.0,24,,19,0.0,34,,,,10,1994-08-14 00:00:00 -14653,557,80,28,10.0,19,,21,0.0,30,,,,4,1994-08-14 00:00:00 -14654,557,91,29,34.0,0,,27,0.0,0,,,,81,1994-08-14 00:00:00 -14655,557,110,30,32.0,26,,23,0.0,9,,,,64,1994-08-14 00:00:00 -14656,557,55,16,15.0,7,,25,0.0,0,,,,4,1994-08-14 00:00:00 -14657,557,21,16,14.0,10,,26,0.0,0,,,,4,1994-08-14 00:00:00 -14658,557,107,29,33.0,0,,28,0.0,0,,,,81,1994-08-14 00:00:00 -14659,557,111,0,7.0,14,,22,0.0,21,,,,47,1994-08-14 00:00:00 -14660,557,13,2,2.0,3,,15,0.0,59,,,,20,1994-08-14 00:00:00 -14661,557,78,24,3.0,5,,24,0.0,0,,,,4,1994-08-14 00:00:00 -14662,557,69,31,11.0,22,13.0,13,0.0,72,,,,15,1994-08-14 00:00:00 -14663,557,103,28,9.0,16,14.0,14,0.0,69,,,,7,1994-08-14 00:00:00 -14664,557,29,21,5.0,1,1.0,1,10.0,77,6480185.0,,,1,1994-08-14 00:00:00 -14665,557,70,2,0.0,2,2.0,2,6.0,77,6501012.0,,,1,1994-08-14 00:00:00 -14666,557,49,21,6.0,12,3.0,3,4.0,77,6550514.0,,,1,1994-08-14 00:00:00 -14667,557,83,0,8.0,6,4.0,4,3.0,76,,,,10,1994-08-14 00:00:00 -14668,557,86,24,4.0,11,5.0,5,2.0,76,,,,11,1994-08-14 00:00:00 -14669,557,54,5,27.0,13,,16,0.0,58,,,,6,1994-08-14 00:00:00 -14670,557,104,17,24.0,20,7.0,7,0.0,75,,,,12,1994-08-14 00:00:00 -14671,557,99,32,20.0,21,8.0,8,0.0,75,,,,12,1994-08-14 00:00:00 -14672,557,105,32,19.0,25,9.0,9,0.0,75,,,,12,1994-08-14 00:00:00 -14673,557,102,26,25.0,18,10.0,10,0.0,75,,,,12,1994-08-14 00:00:00 -14674,557,100,30,31.0,23,11.0,11,0.0,74,,,,13,1994-08-14 00:00:00 -14675,557,43,26,26.0,9,6.0,6,1.0,76,,,,11,1994-08-14 00:00:00 -14676,557,76,5,28.0,4,12.0,12,0.0,72,,,,5,1994-08-14 00:00:00 -14677,558,83,0,8.0,13,,18,0.0,24,,,,20,1994-08-28 00:00:00 -14678,558,21,16,14.0,1,,19,0.0,19,,,,20,1994-08-28 00:00:00 -14679,558,78,24,3.0,23,,20,0.0,18,,,,5,1994-08-28 00:00:00 -14680,558,112,31,11.0,26,,21,0.0,15,,,,20,1994-08-28 00:00:00 -14681,558,48,14,30.0,9,,24,0.0,10,,,,86,1994-08-28 00:00:00 -14682,558,111,32,19.0,19,,23,0.0,11,,,,5,1994-08-28 00:00:00 -14683,558,109,14,29.0,15,,17,0.0,27,,,,37,1994-08-28 00:00:00 -14684,558,99,32,20.0,22,,25,0.0,3,,,,5,1994-08-28 00:00:00 -14685,558,54,5,27.0,5,,26,0.0,2,,,,5,1994-08-28 00:00:00 -14686,558,91,29,34.0,0,,27,0.0,0,,,,81,1994-08-28 00:00:00 -14687,558,107,29,33.0,0,,28,0.0,0,,,,81,1994-08-28 00:00:00 -14688,558,76,5,28.0,11,,22,0.0,11,,,,5,1994-08-28 00:00:00 -14689,558,100,30,31.0,21,,16,0.0,29,,,,36,1994-08-28 00:00:00 -14690,558,55,16,15.0,4,13.0,13,0.0,40,,,,91,1994-08-28 00:00:00 -14691,558,29,21,5.0,2,,14,0.0,44,,,,2,1994-08-28 00:00:00 -14692,558,64,31,12.0,20,12.0,12,0.0,41,,,,13,1994-08-28 00:00:00 -14693,558,110,30,32.0,25,11.0,11,0.0,42,,,,12,1994-08-28 00:00:00 -14694,558,102,26,25.0,16,10.0,10,0.0,42,,,,12,1994-08-28 00:00:00 -14695,558,93,17,23.0,10,8.0,8,0.0,43,,,,11,1994-08-28 00:00:00 -14696,558,43,26,26.0,17,7.0,7,0.0,43,,,,11,1994-08-28 00:00:00 -14697,558,80,28,10.0,14,6.0,6,1.0,43,,,,11,1994-08-28 00:00:00 -14698,558,86,24,4.0,12,5.0,5,2.0,43,,,,11,1994-08-28 00:00:00 -14699,558,13,2,2.0,7,4.0,4,3.0,44,5432887.0,,,1,1994-08-28 00:00:00 -14700,558,49,21,6.0,6,3.0,3,4.0,44,5397553.0,,,1,1994-08-28 00:00:00 -14701,558,56,0,7.0,8,2.0,2,6.0,44,5378481.0,,,1,1994-08-28 00:00:00 -14702,558,70,2,0.0,3,1.0,1,10.0,44,5327100.0,,,1,1994-08-28 00:00:00 -14703,558,103,28,9.0,24,,15,0.0,33,,,,5,1994-08-28 00:00:00 -14704,558,104,17,24.0,18,9.0,9,0.0,43,,,,11,1994-08-28 00:00:00 -14705,559,107,29,33.0,0,,28,0.0,0,,,,81,1994-09-11 00:00:00 -14706,559,70,2,0.0,3,1.0,1,10.0,53,4683200.0,,,1,1994-09-11 00:00:00 -14707,559,91,29,34.0,0,,27,0.0,0,,,,81,1994-09-11 00:00:00 -14708,559,80,28,10.0,17,,26,0.0,0,,,,4,1994-09-11 00:00:00 -14709,559,69,31,11.0,13,,25,0.0,0,,,,4,1994-09-11 00:00:00 -14710,559,49,21,6.0,10,,24,0.0,0,,,,4,1994-09-11 00:00:00 -14711,559,64,31,12.0,4,,23,0.0,13,,,,91,1994-09-11 00:00:00 -14712,559,54,5,27.0,1,,22,0.0,14,,,,6,1994-09-11 00:00:00 -14713,559,110,30,32.0,25,,20,0.0,20,,,,6,1994-09-11 00:00:00 -14714,559,109,14,29.0,8,,19,0.0,20,,,,5,1994-09-11 00:00:00 -14715,559,48,14,30.0,11,,18,0.0,22,,,,5,1994-09-11 00:00:00 -14716,559,104,17,24.0,22,,17,0.0,28,,,,6,1994-09-11 00:00:00 -14717,559,93,17,23.0,18,,16,0.0,30,,,,20,1994-09-11 00:00:00 -14718,559,86,24,4.0,21,,15,0.0,39,,,,20,1994-09-11 00:00:00 -14719,559,113,32,19.0,23,,21,0.0,18,,,,20,1994-09-11 00:00:00 -14720,559,103,28,9.0,19,,13,0.0,43,,,,5,1994-09-11 00:00:00 -14721,559,55,16,15.0,9,,14,0.0,41,,,,5,1994-09-11 00:00:00 -14722,559,76,5,28.0,2,2.0,2,6.0,53,4688130.0,,,1,1994-09-11 00:00:00 -14723,559,56,0,7.0,7,3.0,3,4.0,53,4708840.0,,,1,1994-09-11 00:00:00 -14724,559,21,16,14.0,16,4.0,4,3.0,53,4733834.0,,,1,1994-09-11 00:00:00 -14725,559,13,2,2.0,5,6.0,6,1.0,52,,,,60,1994-09-11 00:00:00 -14726,559,102,26,25.0,12,7.0,7,0.0,52,,,,11,1994-09-11 00:00:00 -14727,559,83,0,8.0,15,5.0,5,2.0,53,4768775.0,,,1,1994-09-11 00:00:00 -14728,559,99,32,20.0,24,8.0,8,0.0,52,,,,11,1994-09-11 00:00:00 -14729,559,108,21,5.0,20,9.0,9,0.0,52,,,,11,1994-09-11 00:00:00 -14730,559,43,26,26.0,6,10.0,10,0.0,51,,,,12,1994-09-11 00:00:00 -14731,559,100,30,31.0,26,,11,0.0,46,,,,29,1994-09-11 00:00:00 -14732,559,78,24,3.0,14,,12,0.0,45,,,,20,1994-09-11 00:00:00 -14733,560,100,30,31.0,24,,22,0.0,36,,,,4,1994-09-25 00:00:00 -14734,560,108,21,5.0,14,,19,0.0,60,,,,20,1994-09-25 00:00:00 -14735,560,109,14,29.0,17,,20,0.0,54,,,,20,1994-09-25 00:00:00 -14736,560,54,5,27.0,5,,21,0.0,38,,,,4,1994-09-25 00:00:00 -14737,560,86,24,4.0,12,,18,0.0,61,,,,5,1994-09-25 00:00:00 -14738,560,48,14,30.0,9,,23,0.0,31,,,,24,1994-09-25 00:00:00 -14739,560,70,2,0.0,2,1.0,1,10.0,71,6310100.0,,,1,1994-09-25 00:00:00 -14740,560,78,24,3.0,6,,25,0.0,26,,,,6,1994-09-25 00:00:00 -14741,560,76,5,28.0,1,,26,0.0,7,,,,6,1994-09-25 00:00:00 -14742,560,91,29,34.0,0,,27,0.0,0,,,,81,1994-09-25 00:00:00 -14743,560,107,29,33.0,0,,28,0.0,0,,,,81,1994-09-25 00:00:00 -14744,560,43,26,26.0,15,,17,0.0,70,,,,2,1994-09-25 00:00:00 -14745,560,99,32,20.0,22,,24,0.0,27,,,,22,1994-09-25 00:00:00 -14746,560,112,31,11.0,25,16.0,16,0.0,67,,,,14,1994-09-25 00:00:00 -14747,560,80,28,10.0,16,9.0,9,0.0,70,,,,11,1994-09-25 00:00:00 -14748,560,113,32,19.0,23,14.0,14,0.0,69,,,,12,1994-09-25 00:00:00 -14749,560,56,0,7.0,4,3.0,3,4.0,71,6330293.0,,,1,1994-09-25 00:00:00 -14750,560,21,16,14.0,8,4.0,4,3.0,71,6338103.0,,,1,1994-09-25 00:00:00 -14751,560,49,21,6.0,10,5.0,5,2.0,71,6339485.0,,,1,1994-09-25 00:00:00 -14752,560,83,0,8.0,7,6.0,6,1.0,71,6362802.0,,,1,1994-09-25 00:00:00 -14753,560,55,16,15.0,13,7.0,7,0.0,70,,,,11,1994-09-25 00:00:00 -14754,560,110,30,32.0,26,15.0,15,0.0,67,,,,14,1994-09-25 00:00:00 -14755,560,13,2,2.0,3,2.0,2,6.0,71,6310703.0,,,1,1994-09-25 00:00:00 -14756,560,102,26,25.0,21,10.0,10,0.0,70,,,,11,1994-09-25 00:00:00 -14757,560,64,31,12.0,20,11.0,11,0.0,70,,,,11,1994-09-25 00:00:00 -14758,560,93,17,23.0,18,12.0,12,0.0,69,,,,12,1994-09-25 00:00:00 -14759,560,104,17,24.0,19,13.0,13,0.0,69,,,,12,1994-09-25 00:00:00 -14760,560,103,28,9.0,11,8.0,8,0.0,70,,,,11,1994-09-25 00:00:00 -14761,561,102,31,11.0,22,18.0,18,0.0,66,,,,13,1994-10-16 00:00:00 -14762,561,92,30,32.0,26,19.0,19,0.0,64,,,,15,1994-10-16 00:00:00 -14763,561,94,2,2.0,3,,20,0.0,47,,,,20,1994-10-16 00:00:00 -14764,561,100,30,31.0,25,,21,0.0,42,,,,5,1994-10-16 00:00:00 -14765,561,109,14,29.0,18,,22,0.0,37,,,,37,1994-10-16 00:00:00 -14766,561,114,32,19.0,24,,25,0.0,10,,,,6,1994-10-16 00:00:00 -14767,561,49,21,6.0,12,,24,0.0,15,,,,20,1994-10-16 00:00:00 -14768,561,83,0,8.0,15,,26,0.0,8,,,,5,1994-10-16 00:00:00 -14769,561,91,29,34.0,0,,27,0.0,0,,,,81,1994-10-16 00:00:00 -14770,561,107,29,33.0,0,,28,0.0,0,,,,81,1994-10-16 00:00:00 -14771,561,103,28,9.0,19,17.0,17,0.0,66,,,,13,1994-10-16 00:00:00 -14772,561,99,32,20.0,23,,23,0.0,37,,,,91,1994-10-16 00:00:00 -14773,561,69,31,12.0,21,16.0,16,0.0,67,,,,12,1994-10-16 00:00:00 -14774,561,93,17,23.0,17,15.0,15,0.0,67,,,,12,1994-10-16 00:00:00 -14775,561,104,17,24.0,20,14.0,14,0.0,67,,,,12,1994-10-16 00:00:00 -14776,561,70,2,0.0,2,2.0,2,6.0,69,6051989.0,,,1,1994-10-16 00:00:00 -14777,561,56,0,7.0,9,3.0,3,4.0,69,6096948.0,,,1,1994-10-16 00:00:00 -14778,561,55,16,15.0,10,4.0,4,3.0,69,6105746.0,,,1,1994-10-16 00:00:00 -14779,561,76,5,28.0,6,5.0,5,2.0,68,,,,11,1994-10-16 00:00:00 -14780,561,48,14,30.0,4,6.0,6,1.0,68,,,,11,1994-10-16 00:00:00 -14781,561,78,24,3.0,13,7.0,7,0.0,68,,,,11,1994-10-16 00:00:00 -14782,561,29,21,5.0,1,1.0,1,10.0,69,6027300.0,,,1,1994-10-16 00:00:00 -14783,561,43,26,26.0,11,9.0,9,0.0,68,,,,11,1994-10-16 00:00:00 -14784,561,54,5,27.0,16,10.0,10,0.0,68,,,,11,1994-10-16 00:00:00 -14785,561,80,28,10.0,8,11.0,11,0.0,68,,,,11,1994-10-16 00:00:00 -14786,561,21,16,14.0,5,12.0,12,0.0,68,,,,11,1994-10-16 00:00:00 -14787,561,86,24,4.0,14,13.0,13,0.0,68,,,,11,1994-10-16 00:00:00 -14788,561,64,26,25.0,7,8.0,8,0.0,68,,,,11,1994-10-16 00:00:00 -14789,562,80,28,10.0,12,,17,0.0,13,,,,20,1994-11-06 00:00:00 -14790,562,76,5,28.0,11,,18,0.0,10,,,,80,1994-11-06 00:00:00 -14791,562,115,26,25.0,20,,19,0.0,10,,,,4,1994-11-06 00:00:00 -14792,562,93,17,23.0,16,,20,0.0,10,,,,4,1994-11-06 00:00:00 -14793,562,64,21,6.0,5,,22,0.0,3,,,,20,1994-11-06 00:00:00 -14794,562,108,14,29.0,15,,25,0.0,0,,,,5,1994-11-06 00:00:00 -14795,562,88,30,32.0,26,,24,0.0,3,,,,20,1994-11-06 00:00:00 -14796,562,114,32,19.0,23,,26,0.0,0,,,,20,1994-11-06 00:00:00 -14797,562,91,29,34.0,0,,27,0.0,0,,,,81,1994-11-06 00:00:00 -14798,562,107,29,33.0,0,,28,0.0,0,,,,81,1994-11-06 00:00:00 -14799,562,83,0,8.0,9,,16,0.0,13,,,,20,1994-11-06 00:00:00 -14800,562,78,24,3.0,14,,23,0.0,3,,,,20,1994-11-06 00:00:00 -14801,562,21,16,14.0,10,,15,0.0,16,,,,6,1994-11-06 00:00:00 -14802,562,104,17,24.0,21,,21,0.0,10,,,,20,1994-11-06 00:00:00 -14803,562,69,31,12.0,17,13.0,13,0.0,48,,,,12,1994-11-06 00:00:00 -14804,562,86,24,4.0,13,,14,0.0,26,,,,5,1994-11-06 00:00:00 -14805,562,29,21,5.0,1,2.0,2,6.0,50,6956897.0,,,1,1994-11-06 00:00:00 -14806,562,54,5,27.0,7,3.0,3,4.0,50,7005577.0,,,1,1994-11-06 00:00:00 -14807,562,94,2,2.0,4,4.0,4,3.0,50,7009606.0,,,1,1994-11-06 00:00:00 -14808,562,55,16,15.0,6,5.0,5,2.0,50,7055639.0,,,1,1994-11-06 00:00:00 -14809,562,48,14,30.0,3,6.0,6,1.0,50,7073395.0,,,1,1994-11-06 00:00:00 -14810,562,70,2,0.0,2,1.0,1,10.0,50,6953532.0,,,1,1994-11-06 00:00:00 -14811,562,103,28,9.0,18,8.0,8,0.0,49,,,,11,1994-11-06 00:00:00 -14812,562,99,32,20.0,22,9.0,9,0.0,49,,,,11,1994-11-06 00:00:00 -14813,562,62,31,11.0,25,10.0,10,0.0,49,,,,11,1994-11-06 00:00:00 -14814,562,43,26,26.0,19,11.0,11,0.0,49,,,,11,1994-11-06 00:00:00 -14815,562,100,30,31.0,24,12.0,12,0.0,48,,,,12,1994-11-06 00:00:00 -14816,562,56,0,7.0,8,7.0,7,0.0,50,7076517.0,,,1,1994-11-06 00:00:00 -14817,563,100,30,31.0,24,,17,0.0,49,,,,5,1994-11-13 00:00:00 -14818,563,69,31,12.0,14,,18,0.0,40,,,,37,1994-11-13 00:00:00 -14819,563,70,2,0.0,3,,19,0.0,35,,,,4,1994-11-13 00:00:00 -14820,563,29,21,5.0,2,,20,0.0,35,,,,4,1994-11-13 00:00:00 -14821,563,78,24,3.0,15,,22,0.0,19,,,,20,1994-11-13 00:00:00 -14822,563,80,28,10.0,21,,24,0.0,17,,,,44,1994-11-13 00:00:00 -14823,563,55,16,15.0,6,,25,0.0,15,,,,20,1994-11-13 00:00:00 -14824,563,64,21,6.0,7,,26,0.0,13,,,,6,1994-11-13 00:00:00 -14825,563,91,29,34.0,0,,27,0.0,0,,,,81,1994-11-13 00:00:00 -14826,563,62,31,11.0,22,,16,0.0,49,,,,10,1994-11-13 00:00:00 -14827,563,107,29,33.0,0,,28,0.0,0,,,,81,1994-11-13 00:00:00 -14828,563,114,32,19.0,23,,23,0.0,18,,,,44,1994-11-13 00:00:00 -14829,563,97,32,20.0,25,,15,0.0,56,,,,6,1994-11-13 00:00:00 -14830,563,92,30,32.0,26,,21,0.0,21,,,,6,1994-11-13 00:00:00 -14831,563,104,17,24.0,16,,13,0.0,69,,,,22,1994-11-13 00:00:00 -14832,563,86,24,4.0,13,,14,0.0,66,,,,3,1994-11-13 00:00:00 -14833,563,76,5,28.0,11,2.0,2,6.0,81,6473911.0,,,1,1994-11-13 00:00:00 -14834,563,83,0,8.0,9,3.0,3,4.0,81,6523887.0,,,1,1994-11-13 00:00:00 -14835,563,21,16,14.0,5,4.0,4,3.0,81,6541930.0,,,1,1994-11-13 00:00:00 -14836,563,43,26,26.0,12,5.0,5,2.0,80,,,,11,1994-11-13 00:00:00 -14837,563,54,5,27.0,8,6.0,6,1.0,80,,,,11,1994-11-13 00:00:00 -14838,563,94,2,2.0,1,1.0,1,10.0,81,6471400.0,,,1,1994-11-13 00:00:00 -14839,563,103,28,9.0,19,8.0,8,0.0,80,,,,11,1994-11-13 00:00:00 -14840,563,93,17,23.0,18,9.0,9,0.0,79,,,,12,1994-11-13 00:00:00 -14841,563,108,14,29.0,17,10.0,10,0.0,79,,,,12,1994-11-13 00:00:00 -14842,563,115,26,25.0,20,11.0,11,0.0,79,,,,12,1994-11-13 00:00:00 -14843,563,56,0,7.0,4,12.0,12,0.0,76,,,,23,1994-11-13 00:00:00 -14844,563,48,14,30.0,10,7.0,7,0.0,80,,,,11,1994-11-13 00:00:00 -14845,564,70,2,5.0,1,,16,0.0,30,,,,6,1995-03-26 00:00:00 -14846,564,64,21,2.0,4,,17,0.0,30,,,,4,1995-03-26 00:00:00 -14847,564,91,29,16.0,20,,18,0.0,23,,,,6,1995-03-26 00:00:00 -14848,564,21,16,14.0,16,,19,0.0,16,,,,6,1995-03-26 00:00:00 -14849,564,78,24,3.0,11,,21,0.0,15,,,,20,1995-03-26 00:00:00 -14850,564,55,16,15.0,8,,22,0.0,15,,,,8,1995-03-26 00:00:00 -14851,564,92,30,11.0,26,,23,0.0,12,,,,38,1995-03-26 00:00:00 -14852,564,48,14,30.0,14,,24,0.0,10,,,,10,1995-03-26 00:00:00 -14853,564,90,14,29.0,19,,15,0.0,41,,,,10,1995-03-26 00:00:00 -14854,564,49,30,12.0,24,,20,0.0,16,,,,6,1995-03-26 00:00:00 -14855,564,89,27,22.0,23,,14,0.0,47,,,,20,1995-03-26 00:00:00 -14856,564,62,24,4.0,12,7.0,7,0.0,69,,,,12,1995-03-26 00:00:00 -14857,564,88,28,10.0,21,,12,0.0,48,,,,5,1995-03-26 00:00:00 -14858,564,80,28,9.0,13,,11,0.0,62,,,,5,1995-03-26 00:00:00 -14859,564,63,27,21.0,25,10.0,10,0.0,64,,,,17,1995-03-26 00:00:00 -14860,564,84,29,17.0,22,9.0,9,0.0,65,,,,16,1995-03-26 00:00:00 -14861,564,87,26,25.0,15,8.0,8,0.0,69,,,,12,1995-03-26 00:00:00 -14862,564,43,26,26.0,10,,25,0.0,0,,,,4,1995-03-26 00:00:00 -14863,564,54,5,27.0,6,5.0,5,2.0,70,,,,11,1995-03-26 00:00:00 -14864,564,56,0,8.0,7,4.0,4,3.0,70,,,,11,1995-03-26 00:00:00 -14865,564,76,5,28.0,5,3.0,3,4.0,70,,,,11,1995-03-26 00:00:00 -14866,564,13,2,6.0,3,2.0,2,6.0,71,5925214.0,,,1,1995-03-26 00:00:00 -14867,564,29,21,1.0,2,1.0,1,10.0,71,5914154.0,,,1,1995-03-26 00:00:00 -14868,564,68,17,24.0,18,,13,0.0,47,,,,5,1995-03-26 00:00:00 -14869,564,93,17,23.0,17,,26,0.0,0,,,,6,1995-03-26 00:00:00 -14870,564,86,0,7.0,9,6.0,6,1.0,70,,,,11,1995-03-26 00:00:00 -14871,565,21,16,14.0,10,,17,0.0,33,,,,51,1995-04-09 00:00:00 -14872,565,88,28,10.0,26,,16,0.0,40,,,,20,1995-04-09 00:00:00 -14873,565,68,17,24.0,13,,26,0.0,0,,,,4,1995-04-09 00:00:00 -14874,565,90,14,29.0,21,,25,0.0,0,,,,4,1995-04-09 00:00:00 -14875,565,91,29,16.0,23,,24,0.0,0,,,,4,1995-04-09 00:00:00 -14876,565,56,0,8.0,5,,23,0.0,0,,,,4,1995-04-09 00:00:00 -14877,565,80,28,9.0,12,,15,0.0,43,,,,10,1995-04-09 00:00:00 -14878,565,93,17,23.0,16,,14,0.0,44,,,,20,1995-04-09 00:00:00 -14879,565,87,26,25.0,19,,13,0.0,47,,,,4,1995-04-09 00:00:00 -14880,565,62,24,4.0,7,,12,0.0,48,,,,4,1995-04-09 00:00:00 -14881,565,89,27,22.0,24,,11,0.0,63,,,,62,1995-04-09 00:00:00 -14882,565,63,27,21.0,25,,10,0.0,63,,,,62,1995-04-09 00:00:00 -14883,565,92,30,11.0,20,9.0,9,0.0,68,,,,14,1995-04-09 00:00:00 -14884,565,49,30,12.0,14,,18,0.0,23,,,,6,1995-04-09 00:00:00 -14885,565,43,26,26.0,18,7.0,7,0.0,70,,,,12,1995-04-09 00:00:00 -14886,565,78,24,3.0,15,8.0,8,0.0,69,,,,13,1995-04-09 00:00:00 -14887,565,86,0,7.0,17,,20,0.0,9,,,,44,1995-04-09 00:00:00 -14888,565,55,16,15.0,4,,21,0.0,6,,,,5,1995-04-09 00:00:00 -14889,565,84,29,17.0,22,,22,0.0,1,,,,4,1995-04-09 00:00:00 -14890,565,70,2,5.0,2,1.0,1,10.0,72,6794532.0,,,1,1995-04-09 00:00:00 -14891,565,13,2,6.0,1,,19,0.0,16,,,,10,1995-04-09 00:00:00 -14892,565,29,21,1.0,3,3.0,3,4.0,72,6827908.0,,,1,1995-04-09 00:00:00 -14893,565,64,21,2.0,11,4.0,4,3.0,71,,,,11,1995-04-09 00:00:00 -14894,565,48,14,30.0,9,5.0,5,2.0,70,,,,12,1995-04-09 00:00:00 -14895,565,76,5,28.0,8,6.0,6,1.0,70,,,,12,1995-04-09 00:00:00 -14896,565,54,5,27.0,6,2.0,2,6.0,72,6800939.0,,,1,1995-04-09 00:00:00 -14897,566,90,14,29.0,21,,17,0.0,43,,,,36,1995-04-30 00:00:00 -14898,566,29,21,1.0,1,,26,0.0,10,,,,20,1995-04-30 00:00:00 -14899,566,88,28,10.0,19,,25,0.0,12,,,,20,1995-04-30 00:00:00 -14900,566,49,30,12.0,17,,24,0.0,14,,,,6,1995-04-30 00:00:00 -14901,566,84,29,17.0,24,,23,0.0,15,,,,6,1995-04-30 00:00:00 -14902,566,62,24,4.0,13,,22,0.0,19,,,,5,1995-04-30 00:00:00 -14903,566,78,24,3.0,15,,21,0.0,23,,,,20,1995-04-30 00:00:00 -14904,566,21,16,14.0,10,,20,0.0,31,,,,7,1995-04-30 00:00:00 -14905,566,92,30,11.0,23,,19,0.0,35,,,,22,1995-04-30 00:00:00 -14906,566,91,29,16.0,22,,18,0.0,36,,,,6,1995-04-30 00:00:00 -14907,566,89,27,22.0,25,,16,0.0,56,,,,62,1995-04-30 00:00:00 -14908,566,63,27,21.0,26,,15,0.0,56,,,,62,1995-04-30 00:00:00 -14909,566,54,5,27.0,5,2.0,2,6.0,63,6121032.0,,,1,1995-04-30 00:00:00 -14910,566,68,17,24.0,20,14.0,14,0.0,59,,,,14,1995-04-30 00:00:00 -14911,566,76,5,28.0,2,3.0,3,4.0,63,6145638.0,,,1,1995-04-30 00:00:00 -14912,566,13,2,6.0,3,4.0,4,3.0,63,6154412.0,,,1,1995-04-30 00:00:00 -14913,566,56,0,8.0,6,5.0,5,2.0,62,,,,11,1995-04-30 00:00:00 -14914,566,70,2,5.0,4,1.0,1,10.0,63,6102522.0,,,1,1995-04-30 00:00:00 -14915,566,64,21,2.0,8,7.0,7,0.0,61,,,,12,1995-04-30 00:00:00 -14916,566,48,14,30.0,14,6.0,6,1.0,62,,,,11,1995-04-30 00:00:00 -14917,566,43,26,26.0,12,9.0,9,0.0,61,,,,12,1995-04-30 00:00:00 -14918,566,94,0,7.0,9,10.0,10,0.0,61,,,,12,1995-04-30 00:00:00 -14919,566,87,26,25.0,16,11.0,11,0.0,60,,,,13,1995-04-30 00:00:00 -14920,566,93,17,23.0,18,12.0,12,0.0,59,,,,14,1995-04-30 00:00:00 -14921,566,80,28,9.0,11,13.0,13,0.0,59,,,,14,1995-04-30 00:00:00 -14922,566,55,16,15.0,7,8.0,8,0.0,61,,,,12,1995-04-30 00:00:00 -14923,567,13,2,6.0,4,,17,0.0,54,,,,6,1995-05-14 00:00:00 -14924,567,56,0,8.0,9,,18,0.0,53,,,,69,1995-05-14 00:00:00 -14925,567,88,28,10.0,18,,19,0.0,43,,,,7,1995-05-14 00:00:00 -14926,567,91,29,16.0,24,,20,0.0,43,,,,42,1995-05-14 00:00:00 -14927,567,78,24,3.0,17,,16,0.0,56,,,,5,1995-05-14 00:00:00 -14928,567,54,5,27.0,2,,22,0.0,25,,,,5,1995-05-14 00:00:00 -14929,567,68,17,24.0,21,,23,0.0,21,,,,6,1995-05-14 00:00:00 -14930,567,94,0,7.0,10,,24,0.0,18,,,,64,1995-05-14 00:00:00 -14931,567,63,27,21.0,26,,25,0.0,17,,,,6,1995-05-14 00:00:00 -14932,567,84,29,17.0,23,,26,0.0,0,,,,54,1995-05-14 00:00:00 -14933,567,89,27,22.0,25,,21,0.0,39,,,,25,1995-05-14 00:00:00 -14934,567,92,30,11.0,22,15.0,15,0.0,61,,,,14,1995-05-14 00:00:00 -14935,567,83,26,25.0,11,9.0,9,0.0,64,,,,11,1995-05-14 00:00:00 -14936,567,90,14,29.0,20,13.0,13,0.0,63,,,,12,1995-05-14 00:00:00 -14937,567,93,17,23.0,19,14.0,14,0.0,62,,,,13,1995-05-14 00:00:00 -14938,567,29,21,1.0,1,1.0,1,10.0,65,5660507.0,,,1,1995-05-14 00:00:00 -14939,567,76,5,28.0,3,3.0,3,4.0,65,5725744.0,,,1,1995-05-14 00:00:00 -14940,567,70,2,5.0,5,4.0,4,3.0,65,5782256.0,,,1,1995-05-14 00:00:00 -14941,567,55,16,15.0,6,5.0,5,2.0,64,,,,11,1995-05-14 00:00:00 -14942,567,64,21,2.0,7,2.0,2,6.0,65,5712495.0,,,1,1995-05-14 00:00:00 -14943,567,21,16,14.0,8,7.0,7,0.0,64,,,,11,1995-05-14 00:00:00 -14944,567,48,14,30.0,12,8.0,8,0.0,64,,,,11,1995-05-14 00:00:00 -14945,567,62,24,4.0,13,10.0,10,0.0,64,,,,11,1995-05-14 00:00:00 -14946,567,49,30,12.0,16,12.0,12,0.0,63,,,,12,1995-05-14 00:00:00 -14947,567,80,28,9.0,14,11.0,11,0.0,63,,,,12,1995-05-14 00:00:00 -14948,567,43,26,26.0,15,6.0,6,1.0,64,,,,11,1995-05-14 00:00:00 -14949,568,54,5,27.0,5,,16,0.0,41,,,,20,1995-05-28 00:00:00 -14950,568,83,26,25.0,8,,17,0.0,40,,,,20,1995-05-28 00:00:00 -14951,568,88,28,10.0,26,,18,0.0,27,,,,6,1995-05-28 00:00:00 -14952,568,84,29,17.0,25,,20,0.0,23,,,,2,1995-05-28 00:00:00 -14953,568,55,16,15.0,9,,21,0.0,22,,,,20,1995-05-28 00:00:00 -14954,568,13,2,6.0,3,,22,0.0,16,,,,6,1995-05-28 00:00:00 -14955,568,89,27,22.0,24,,23,0.0,9,,,,23,1995-05-28 00:00:00 -14956,568,56,0,8.0,6,,24,0.0,8,,,,5,1995-05-28 00:00:00 -14957,568,49,30,12.0,23,,25,0.0,0,,,,6,1995-05-28 00:00:00 -14958,568,78,24,3.0,15,,19,0.0,26,,,,20,1995-05-28 00:00:00 -14959,568,91,29,16.0,21,,15,0.0,42,,,,6,1995-05-28 00:00:00 -14960,568,43,26,26.0,12,,12,0.0,65,,,,20,1995-05-28 00:00:00 -14961,568,62,24,4.0,17,,13,0.0,63,,,,6,1995-05-28 00:00:00 -14962,568,68,17,24.0,16,,11,0.0,68,,,,22,1995-05-28 00:00:00 -14963,568,63,27,21.0,22,10.0,10,0.0,72,,,,16,1995-05-28 00:00:00 -14964,568,80,28,9.0,13,9.0,9,0.0,74,,,,14,1995-05-28 00:00:00 -14965,568,48,14,30.0,14,6.0,6,1.0,76,,,,12,1995-05-28 00:00:00 -14966,568,86,0,7.0,10,5.0,5,2.0,77,,,,11,1995-05-28 00:00:00 -14967,568,64,21,2.0,7,4.0,4,3.0,77,,,,11,1995-05-28 00:00:00 -14968,568,76,5,28.0,4,3.0,3,4.0,78,6862705.0,,,1,1995-05-28 00:00:00 -14969,568,70,2,5.0,1,2.0,2,6.0,78,6826075.0,,,1,1995-05-28 00:00:00 -14970,568,29,21,1.0,2,1.0,1,10.0,78,6791258.0,,,1,1995-05-28 00:00:00 -14971,568,92,30,11.0,20,,26,0.0,0,,,,54,1995-05-28 00:00:00 -14972,568,21,16,14.0,11,,14,0.0,60,,,,37,1995-05-28 00:00:00 -14973,568,95,14,29.0,19,8.0,8,0.0,74,,,,14,1995-05-28 00:00:00 -14974,568,93,17,23.0,18,7.0,7,0.0,76,,,,12,1995-05-28 00:00:00 -14975,569,91,29,16.0,20,,17,0.0,36,,,,84,1995-06-11 00:00:00 -14976,569,56,0,8.0,7,,24,0.0,0,,,,4,1995-06-11 00:00:00 -14977,569,64,21,2.0,6,,23,0.0,0,,,,4,1995-06-11 00:00:00 -14978,569,13,2,6.0,3,,22,0.0,1,,,,20,1995-06-11 00:00:00 -14979,569,84,29,17.0,21,,21,0.0,5,,,,6,1995-06-11 00:00:00 -14980,569,95,14,29.0,18,,20,0.0,19,,,,20,1995-06-11 00:00:00 -14981,569,63,27,21.0,24,,19,0.0,26,,,,6,1995-06-11 00:00:00 -14982,569,48,14,30.0,12,,18,0.0,26,,,,5,1995-06-11 00:00:00 -14983,569,78,24,3.0,16,,16,0.0,42,,,,5,1995-06-11 00:00:00 -14984,569,86,0,7.0,10,,15,0.0,47,,,,5,1995-06-11 00:00:00 -14985,569,89,27,22.0,23,,13,0.0,54,,,,69,1995-06-11 00:00:00 -14986,569,93,17,23.0,17,,12,0.0,60,,,,37,1995-06-11 00:00:00 -14987,569,70,2,5.0,2,,14,0.0,50,,,,6,1995-06-11 00:00:00 -14988,569,83,26,25.0,14,10.0,10,0.0,61,,,,4,1995-06-11 00:00:00 -14989,569,88,28,10.0,22,9.0,9,0.0,66,,,,12,1995-06-11 00:00:00 -14990,569,68,17,24.0,19,8.0,8,0.0,67,,,,11,1995-06-11 00:00:00 -14991,569,62,24,4.0,15,7.0,7,0.0,67,,,,11,1995-06-11 00:00:00 -14992,569,80,28,9.0,13,6.0,6,1.0,67,,,,11,1995-06-11 00:00:00 -14993,569,29,21,1.0,1,5.0,5,2.0,68,6331231.0,,,1,1995-06-11 00:00:00 -14994,569,43,26,26.0,11,4.0,4,3.0,68,6330677.0,,,1,1995-06-11 00:00:00 -14995,569,55,16,15.0,8,3.0,3,4.0,68,6327441.0,,,1,1995-06-11 00:00:00 -14996,569,21,16,14.0,9,2.0,2,6.0,68,6325858.0,,,1,1995-06-11 00:00:00 -14997,569,54,5,27.0,5,1.0,1,10.0,68,6294171.0,,,1,1995-06-11 00:00:00 -14998,569,76,5,28.0,4,11.0,11,0.0,61,,,,4,1995-06-11 00:00:00 -14999,570,91,29,16.0,22,,19,0.0,24,,,,6,1995-07-02 00:00:00 -15000,570,89,27,22.0,24,16.0,16,0.0,66,,,,16,1995-07-02 00:00:00 -15001,570,84,29,17.0,21,,17,0.0,62,,,,62,1995-07-02 00:00:00 -15002,570,95,14,29.0,15,,18,0.0,48,,,,6,1995-07-02 00:00:00 -15003,570,93,17,23.0,20,,20,0.0,23,,,,6,1995-07-02 00:00:00 -15004,570,86,0,7.0,13,11.0,11,0.0,70,,,,12,1995-07-02 00:00:00 -15005,570,88,28,10.0,18,,22,0.0,0,,,,4,1995-07-02 00:00:00 -15006,570,78,24,3.0,19,,23,0.0,0,,,,4,1995-07-02 00:00:00 -15007,570,63,27,21.0,23,,24,0.0,0,,,,20,1995-07-02 00:00:00 -15008,570,80,28,9.0,16,14.0,14,0.0,69,,,,13,1995-07-02 00:00:00 -15009,570,64,21,2.0,10,,21,0.0,2,,,,20,1995-07-02 00:00:00 -15010,570,68,17,24.0,17,13.0,13,0.0,69,,,,13,1995-07-02 00:00:00 -15011,570,62,24,4.0,14,15.0,15,0.0,69,,,,13,1995-07-02 00:00:00 -15012,570,48,14,30.0,12,10.0,10,0.0,71,,,,11,1995-07-02 00:00:00 -15013,570,76,5,28.0,7,12.0,12,0.0,70,,,,12,1995-07-02 00:00:00 -15014,570,55,16,15.0,11,9.0,9,0.0,71,,,,11,1995-07-02 00:00:00 -15015,570,43,26,26.0,6,8.0,8,0.0,71,,,,11,1995-07-02 00:00:00 -15016,570,56,0,8.0,8,7.0,7,0.0,71,,,,11,1995-07-02 00:00:00 -15017,570,21,16,14.0,5,6.0,6,1.0,71,,,,11,1995-07-02 00:00:00 -15018,570,54,5,27.0,4,5.0,5,2.0,72,5986298.0,,,1,1995-07-02 00:00:00 -15019,570,83,26,25.0,9,4.0,4,3.0,72,5971722.0,,,1,1995-07-02 00:00:00 -15020,570,13,2,6.0,3,3.0,3,4.0,72,5971255.0,,,1,1995-07-02 00:00:00 -15021,570,70,2,5.0,1,2.0,2,6.0,72,5939738.0,,,1,1995-07-02 00:00:00 -15022,570,29,21,1.0,2,1.0,1,10.0,72,5908429.0,,,1,1995-07-02 00:00:00 -15023,571,70,2,5.0,1,,15,0.0,45,,,,4,1995-07-16 00:00:00 -15024,571,96,28,9.0,17,,16,0.0,28,,,,20,1995-07-16 00:00:00 -15025,571,78,24,3.0,14,,17,0.0,22,,,,60,1995-07-16 00:00:00 -15026,571,84,29,17.0,24,,18,0.0,21,,,,20,1995-07-16 00:00:00 -15027,571,63,27,21.0,20,,23,0.0,13,,,,6,1995-07-16 00:00:00 -15028,571,76,5,28.0,4,,20,0.0,20,,,,36,1995-07-16 00:00:00 -15029,571,83,26,25.0,11,,21,0.0,16,,,,20,1995-07-16 00:00:00 -15030,571,88,28,10.0,19,,22,0.0,16,,,,20,1995-07-16 00:00:00 -15031,571,29,21,1.0,2,,14,0.0,45,,,,4,1995-07-16 00:00:00 -15032,571,55,16,15.0,7,,24,0.0,2,,,,10,1995-07-16 00:00:00 -15033,571,56,0,8.0,8,,19,0.0,20,,,,10,1995-07-16 00:00:00 -15034,571,89,27,22.0,22,,13,0.0,48,,,,5,1995-07-16 00:00:00 -15035,571,68,17,24.0,18,10.0,10,0.0,60,,,,11,1995-07-16 00:00:00 -15036,571,21,16,14.0,9,11.0,11,0.0,59,,,,4,1995-07-16 00:00:00 -15037,571,64,21,2.0,5,1.0,1,10.0,61,5675093.0,,,1,1995-07-16 00:00:00 -15038,571,91,29,16.0,21,12.0,12,0.0,58,,,,13,1995-07-16 00:00:00 -15039,571,13,2,6.0,3,3.0,3,4.0,61,5698981.0,,,1,1995-07-16 00:00:00 -15040,571,43,26,26.0,13,4.0,4,3.0,61,5768261.0,,,1,1995-07-16 00:00:00 -15041,571,54,5,27.0,6,2.0,2,6.0,61,5691572.0,,,1,1995-07-16 00:00:00 -15042,571,48,14,30.0,12,6.0,6,1.0,60,,,,11,1995-07-16 00:00:00 -15043,571,93,17,23.0,15,7.0,7,0.0,60,,,,11,1995-07-16 00:00:00 -15044,571,62,24,4.0,23,8.0,8,0.0,60,,,,11,1995-07-16 00:00:00 -15045,571,95,14,29.0,16,9.0,9,0.0,60,,,,11,1995-07-16 00:00:00 -15046,571,86,0,7.0,10,5.0,5,2.0,61,5783265.0,,,1,1995-07-16 00:00:00 -15047,572,95,14,29.0,14,5.0,5,2.0,44,,,,11,1995-07-30 00:00:00 -15048,572,29,21,1.0,2,1.0,1,10.0,45,4976043.0,,,1,1995-07-30 00:00:00 -15049,572,13,2,6.0,3,2.0,2,6.0,45,4982031.0,,,1,1995-07-30 00:00:00 -15050,572,76,5,28.0,4,3.0,3,4.0,45,5044140.0,,,1,1995-07-30 00:00:00 -15051,572,64,21,2.0,9,4.0,4,3.0,45,5059479.0,,,1,1995-07-30 00:00:00 -15052,572,87,26,25.0,18,6.0,6,1.0,44,,,,11,1995-07-30 00:00:00 -15053,572,21,16,14.0,5,,15,0.0,20,,,,5,1995-07-30 00:00:00 -15054,572,84,29,17.0,23,8.0,8,0.0,42,,,,13,1995-07-30 00:00:00 -15055,572,96,28,9.0,15,,24,0.0,0,,,,6,1995-07-30 00:00:00 -15056,572,62,24,4.0,13,,23,0.0,0,,,,8,1995-07-30 00:00:00 -15057,572,70,2,5.0,1,,22,0.0,1,,,,20,1995-07-30 00:00:00 -15058,572,88,28,10.0,19,,20,0.0,9,,,,6,1995-07-30 00:00:00 -15059,572,93,17,23.0,20,,19,0.0,11,,,,5,1995-07-30 00:00:00 -15060,572,54,5,27.0,10,,18,0.0,12,,,,5,1995-07-30 00:00:00 -15061,572,43,26,26.0,12,,17,0.0,13,,,,47,1995-07-30 00:00:00 -15062,572,63,27,21.0,21,,21,0.0,8,,,,23,1995-07-30 00:00:00 -15063,572,78,24,3.0,17,7.0,7,0.0,44,,,,11,1995-07-30 00:00:00 -15064,572,89,27,22.0,22,,14,0.0,27,,,,86,1995-07-30 00:00:00 -15065,572,85,29,16.0,24,,13,0.0,27,,,,6,1995-07-30 00:00:00 -15066,572,68,17,24.0,16,,12,0.0,28,,,,44,1995-07-30 00:00:00 -15067,572,48,14,30.0,11,,11,0.0,32,,,,5,1995-07-30 00:00:00 -15068,572,56,0,8.0,7,,10,0.0,33,,,,5,1995-07-30 00:00:00 -15069,572,55,16,15.0,6,9.0,9,0.0,41,,,,14,1995-07-30 00:00:00 -15070,572,86,0,7.0,8,,16,0.0,17,,,,5,1995-07-30 00:00:00 -15071,573,62,24,4.0,16,,15,0.0,58,,,,37,1995-08-13 00:00:00 -15072,573,86,0,7.0,13,,16,0.0,54,,,,95,1995-08-13 00:00:00 -15073,573,78,24,3.0,17,,17,0.0,46,,,,20,1995-08-13 00:00:00 -15074,573,96,28,9.0,20,,18,0.0,45,,,,23,1995-08-13 00:00:00 -15075,573,85,29,16.0,24,,23,0.0,5,,,,20,1995-08-13 00:00:00 -15076,573,63,27,21.0,23,,20,0.0,32,,,,5,1995-08-13 00:00:00 -15077,573,89,27,22.0,21,,22,0.0,8,,,,6,1995-08-13 00:00:00 -15078,573,56,0,8.0,5,,24,0.0,3,,,,5,1995-08-13 00:00:00 -15079,573,83,26,25.0,8,,14,0.0,67,,,,5,1995-08-13 00:00:00 -15080,573,54,5,27.0,6,,19,0.0,42,,,,23,1995-08-13 00:00:00 -15081,573,55,16,15.0,7,,13,0.0,70,,,,8,1995-08-13 00:00:00 -15082,573,88,28,10.0,18,,21,0.0,13,,,,5,1995-08-13 00:00:00 -15083,573,29,21,1.0,3,11.0,11,0.0,73,,,,5,1995-08-13 00:00:00 -15084,573,84,29,17.0,22,12.0,12,0.0,73,,,,14,1995-08-13 00:00:00 -15085,573,13,2,6.0,2,2.0,2,6.0,77,6419119.0,,,1,1995-08-13 00:00:00 -15086,573,76,5,28.0,4,3.0,3,4.0,76,,,,11,1995-08-13 00:00:00 -15087,573,64,21,2.0,9,4.0,4,3.0,76,,,,11,1995-08-13 00:00:00 -15088,573,48,14,30.0,11,5.0,5,2.0,76,,,,11,1995-08-13 00:00:00 -15089,573,70,2,5.0,1,1.0,1,10.0,77,6385721.0,,,1,1995-08-13 00:00:00 -15090,573,21,16,14.0,14,7.0,7,0.0,76,,,,11,1995-08-13 00:00:00 -15091,573,68,17,24.0,12,8.0,8,0.0,75,,,,12,1995-08-13 00:00:00 -15092,573,82,17,23.0,15,9.0,9,0.0,74,,,,13,1995-08-13 00:00:00 -15093,573,95,14,29.0,19,10.0,10,0.0,74,,,,13,1995-08-13 00:00:00 -15094,573,43,26,26.0,10,6.0,6,1.0,76,,,,11,1995-08-13 00:00:00 -15095,574,89,27,22.0,22,14.0,14,0.0,42,,,,12,1995-08-27 00:00:00 -15096,574,78,24,3.0,15,,15,0.0,28,,,,20,1995-08-27 00:00:00 -15097,574,85,29,16.0,23,,16,0.0,27,,,,6,1995-08-27 00:00:00 -15098,574,68,17,24.0,19,,17,0.0,23,,,,20,1995-08-27 00:00:00 -15099,574,76,5,28.0,1,,18,0.0,22,,,,10,1995-08-27 00:00:00 -15100,574,96,28,9.0,20,,20,0.0,20,,,,20,1995-08-27 00:00:00 -15101,574,84,29,17.0,21,,21,0.0,18,,,,60,1995-08-27 00:00:00 -15102,574,13,2,6.0,5,,22,0.0,13,,,,6,1995-08-27 00:00:00 -15103,574,54,5,27.0,2,,23,0.0,4,,,,22,1995-08-27 00:00:00 -15104,574,56,0,8.0,3,,24,0.0,1,,,,20,1995-08-27 00:00:00 -15105,574,55,16,15.0,7,,19,0.0,21,,,,42,1995-08-27 00:00:00 -15106,574,63,27,21.0,24,13.0,13,0.0,42,,,,12,1995-08-27 00:00:00 -15107,574,82,17,23.0,17,10.0,10,0.0,44,5887664.0,,,1,1995-08-27 00:00:00 -15108,574,95,14,29.0,14,11.0,11,0.0,43,,,,11,1995-08-27 00:00:00 -15109,574,88,28,10.0,18,12.0,12,0.0,43,,,,11,1995-08-27 00:00:00 -15110,574,70,2,5.0,8,2.0,2,6.0,44,5827368.0,,,1,1995-08-27 00:00:00 -15111,574,83,26,25.0,13,3.0,3,4.0,44,5832873.0,,,1,1995-08-27 00:00:00 -15112,574,48,14,30.0,10,4.0,4,3.0,44,5834847.0,,,1,1995-08-27 00:00:00 -15113,574,29,21,1.0,16,1.0,1,10.0,44,5807875.0,,,1,1995-08-27 00:00:00 -15114,574,21,16,14.0,12,6.0,6,1.0,44,5847549.0,,,1,1995-08-27 00:00:00 -15115,574,64,21,2.0,4,7.0,7,0.0,44,5861918.0,,,1,1995-08-27 00:00:00 -15116,574,62,24,4.0,11,8.0,8,0.0,44,5862423.0,,,1,1995-08-27 00:00:00 -15117,574,43,26,26.0,9,9.0,9,0.0,44,5874045.0,,,1,1995-08-27 00:00:00 -15118,574,86,0,7.0,6,5.0,5,2.0,44,5841647.0,,,1,1995-08-27 00:00:00 -15119,575,84,29,17.0,21,,23,0.0,0,,,,3,1995-09-10 00:00:00 -15120,575,68,17,24.0,18,,15,0.0,26,,,,20,1995-09-10 00:00:00 -15121,575,82,17,23.0,19,,22,0.0,0,,,,7,1995-09-10 00:00:00 -15122,575,85,29,16.0,24,,21,0.0,6,,,,20,1995-09-10 00:00:00 -15123,575,89,27,22.0,22,,24,0.0,0,,,,3,1995-09-10 00:00:00 -15124,575,13,2,6.0,1,,19,0.0,13,,,,20,1995-09-10 00:00:00 -15125,575,43,26,26.0,13,,18,0.0,20,,,,20,1995-09-10 00:00:00 -15126,575,70,2,5.0,4,,17,0.0,23,,,,4,1995-09-10 00:00:00 -15127,575,29,21,1.0,2,,16,0.0,23,,,,4,1995-09-10 00:00:00 -15128,575,54,5,27.0,5,,11,0.0,45,,,,67,1995-09-10 00:00:00 -15129,575,83,26,25.0,11,,20,0.0,10,,,,29,1995-09-10 00:00:00 -15130,575,63,27,21.0,23,9.0,9,0.0,50,,,,13,1995-09-10 00:00:00 -15131,575,78,24,3.0,17,10.0,10,0.0,47,,,,16,1995-09-10 00:00:00 -15132,575,76,5,28.0,3,,14,0.0,32,,,,22,1995-09-10 00:00:00 -15133,575,55,16,15.0,12,,13,0.0,40,,,,5,1995-09-10 00:00:00 -15134,575,64,21,2.0,8,1.0,1,10.0,53,4707916.0,,,1,1995-09-10 00:00:00 -15135,575,56,0,8.0,7,2.0,2,6.0,53,4725695.0,,,1,1995-09-10 00:00:00 -15136,575,21,16,14.0,6,,12,0.0,43,,,,8,1995-09-10 00:00:00 -15137,575,86,0,7.0,9,4.0,4,3.0,53,4736139.0,,,1,1995-09-10 00:00:00 -15138,575,88,28,10.0,20,8.0,8,0.0,52,,,,11,1995-09-10 00:00:00 -15139,575,96,28,9.0,15,7.0,7,0.0,52,,,,11,1995-09-10 00:00:00 -15140,575,48,14,30.0,10,3.0,3,4.0,53,4732237.0,,,1,1995-09-10 00:00:00 -15141,575,62,24,4.0,16,5.0,5,2.0,52,,,,11,1995-09-10 00:00:00 -15142,575,95,14,29.0,14,6.0,6,1.0,52,,,,11,1995-09-10 00:00:00 -15143,576,13,2,6.0,1,1.0,1,10.0,71,6112145.0,,,1,1995-09-24 00:00:00 -15144,576,96,28,9.0,20,,24,0.0,0,,,,6,1995-09-24 00:00:00 -15145,576,78,24,3.0,16,,23,0.0,0,,,,4,1995-09-24 00:00:00 -15146,576,82,17,23.0,17,,22,0.0,7,,,,6,1995-09-24 00:00:00 -15147,576,43,26,26.0,11,,21,0.0,10,,,,20,1995-09-24 00:00:00 -15148,576,97,29,16.0,24,,20,0.0,14,,,,68,1995-09-24 00:00:00 -15149,576,84,29,17.0,21,,18,0.0,53,,,,6,1995-09-24 00:00:00 -15150,576,63,27,21.0,22,16.0,16,0.0,66,,,,15,1995-09-24 00:00:00 -15151,576,88,28,10.0,19,15.0,15,0.0,68,,,,13,1995-09-24 00:00:00 -15152,576,68,17,24.0,18,14.0,14,0.0,68,,,,13,1995-09-24 00:00:00 -15153,576,56,0,8.0,13,,19,0.0,44,,,,5,1995-09-24 00:00:00 -15154,576,95,14,29.0,14,12.0,12,0.0,70,,,,11,1995-09-24 00:00:00 -15155,576,29,21,1.0,3,2.0,2,6.0,71,6119393.0,,,1,1995-09-24 00:00:00 -15156,576,62,24,4.0,15,13.0,13,0.0,69,,,,12,1995-09-24 00:00:00 -15157,576,70,2,5.0,2,3.0,3,4.0,71,6134266.0,,,1,1995-09-24 00:00:00 -15158,576,76,5,28.0,4,4.0,4,3.0,71,6197024.0,,,1,1995-09-24 00:00:00 -15159,576,54,5,27.0,7,5.0,5,2.0,71,6197574.0,,,1,1995-09-24 00:00:00 -15160,576,48,14,30.0,5,6.0,6,1.0,70,,,,11,1995-09-24 00:00:00 -15161,576,89,27,22.0,23,17.0,17,0.0,64,,,,17,1995-09-24 00:00:00 -15162,576,83,26,25.0,9,8.0,8,0.0,70,,,,11,1995-09-24 00:00:00 -15163,576,86,0,7.0,12,9.0,9,0.0,70,,,,11,1995-09-24 00:00:00 -15164,576,55,16,15.0,10,10.0,10,0.0,70,,,,11,1995-09-24 00:00:00 -15165,576,21,16,14.0,8,11.0,11,0.0,70,,,,11,1995-09-24 00:00:00 -15166,576,64,21,2.0,6,7.0,7,0.0,70,,,,11,1995-09-24 00:00:00 -15167,577,98,24,3.0,19,14.0,14,0.0,61,,,,16,1995-10-01 00:00:00 -15168,577,86,0,7.0,10,,23,0.0,14,,,,3,1995-10-01 00:00:00 -15169,577,43,26,26.0,14,,22,0.0,14,,,,20,1995-10-01 00:00:00 -15170,577,48,14,30.0,8,,21,0.0,17,,,,20,1995-10-01 00:00:00 -15171,577,89,27,22.0,23,,20,0.0,22,,,,86,1995-10-01 00:00:00 -15172,577,76,5,28.0,4,,19,0.0,40,,,,10,1995-10-01 00:00:00 -15173,577,95,14,29.0,13,,18,0.0,44,,,,4,1995-10-01 00:00:00 -15174,577,84,29,17.0,20,,17,0.0,45,,,,60,1995-10-01 00:00:00 -15175,577,70,2,5.0,2,,16,0.0,58,,,,20,1995-10-01 00:00:00 -15176,577,97,29,16.0,24,15.0,15,0.0,60,,,,17,1995-10-01 00:00:00 -15177,577,88,28,10.0,21,,24,0.0,0,,,,10,1995-10-01 00:00:00 -15178,577,63,27,21.0,22,13.0,13,0.0,62,,,,15,1995-10-01 00:00:00 -15179,577,68,17,24.0,18,11.0,11,0.0,64,,,,13,1995-10-01 00:00:00 -15180,577,96,28,9.0,17,12.0,12,0.0,64,,,,13,1995-10-01 00:00:00 -15181,577,29,21,1.0,3,1.0,1,10.0,67,5999044.0,,,1,1995-10-01 00:00:00 -15182,577,54,5,27.0,6,2.0,2,6.0,67,6001728.0,,,1,1995-10-01 00:00:00 -15183,577,13,2,6.0,1,3.0,3,4.0,67,6034426.0,,,1,1995-10-01 00:00:00 -15184,577,21,16,14.0,11,4.0,4,3.0,66,,,,11,1995-10-01 00:00:00 -15185,577,62,24,4.0,15,10.0,10,0.0,64,,,,13,1995-10-01 00:00:00 -15186,577,55,16,15.0,5,6.0,6,1.0,66,,,,11,1995-10-01 00:00:00 -15187,577,83,26,25.0,12,7.0,7,0.0,66,,,,11,1995-10-01 00:00:00 -15188,577,56,0,8.0,9,8.0,8,0.0,65,,,,12,1995-10-01 00:00:00 -15189,577,82,17,23.0,16,9.0,9,0.0,64,,,,13,1995-10-01 00:00:00 -15190,577,64,21,2.0,7,5.0,5,2.0,66,,,,11,1995-10-01 00:00:00 -15191,578,91,29,16.0,24,,24,0.0,2,,,,6,1995-10-22 00:00:00 -15192,578,95,14,29.0,15,,23,0.0,7,,,,20,1995-10-22 00:00:00 -15193,578,87,26,25.0,13,,22,0.0,10,,,,20,1995-10-22 00:00:00 -15194,578,84,29,17.0,23,,21,0.0,14,,,,6,1995-10-22 00:00:00 -15195,578,88,28,10.0,20,,20,0.0,38,,,,10,1995-10-22 00:00:00 -15196,578,80,28,9.0,19,,19,0.0,63,,,,5,1995-10-22 00:00:00 -15197,578,21,16,14.0,11,,18,0.0,67,,,,10,1995-10-22 00:00:00 -15198,578,63,27,21.0,21,17.0,17,0.0,77,,,,16,1995-10-22 00:00:00 -15199,578,89,27,22.0,22,16.0,16,0.0,78,,,,15,1995-10-22 00:00:00 -15200,578,68,17,24.0,16,15.0,15,0.0,80,,,,13,1995-10-22 00:00:00 -15201,578,78,24,3.0,17,14.0,14,0.0,80,,,,13,1995-10-22 00:00:00 -15202,578,62,24,4.0,18,12.0,12,0.0,80,,,,13,1995-10-22 00:00:00 -15203,578,29,21,1.0,3,1.0,1,10.0,83,6529972.0,,,1,1995-10-22 00:00:00 -15204,578,13,2,6.0,1,2.0,2,6.0,83,6544892.0,,,1,1995-10-22 00:00:00 -15205,578,82,17,23.0,14,13.0,13,0.0,80,,,,13,1995-10-22 00:00:00 -15206,578,76,5,28.0,5,4.0,4,3.0,82,,,,11,1995-10-22 00:00:00 -15207,578,54,5,27.0,4,5.0,5,2.0,82,,,,11,1995-10-22 00:00:00 -15208,578,70,2,5.0,2,3.0,3,4.0,83,6578305.0,,,1,1995-10-22 00:00:00 -15209,578,48,14,30.0,8,7.0,7,0.0,82,,,,11,1995-10-22 00:00:00 -15210,578,43,26,26.0,9,8.0,8,0.0,81,,,,12,1995-10-22 00:00:00 -15211,578,86,0,7.0,10,9.0,9,0.0,81,,,,12,1995-10-22 00:00:00 -15212,578,55,16,15.0,6,11.0,11,0.0,81,,,,12,1995-10-22 00:00:00 -15213,578,64,21,2.0,7,6.0,6,1.0,82,,,,11,1995-10-22 00:00:00 -15214,578,75,0,8.0,12,10.0,10,0.0,81,,,,12,1995-10-22 00:00:00 -15215,579,89,27,22.0,21,,22,0.0,1,,,,6,1995-10-29 00:00:00 -15216,579,80,28,9.0,14,,23,0.0,0,,,,20,1995-10-29 00:00:00 -15217,579,87,26,25.0,0,,24,0.0,0,,,,3,1995-10-29 00:00:00 -15218,579,91,29,16.0,22,,21,0.0,6,,,,86,1995-10-29 00:00:00 -15219,579,78,24,3.0,13,,20,0.0,12,,,,20,1995-10-29 00:00:00 -15220,579,29,21,1.0,1,1.0,1,10.0,53,5812930.0,,,1,1995-10-29 00:00:00 -15221,579,21,16,14.0,10,,19,0.0,15,,,,20,1995-10-29 00:00:00 -15222,579,76,5,28.0,5,,18,0.0,16,,,,10,1995-10-29 00:00:00 -15223,579,84,29,17.0,19,,17,0.0,23,,,,20,1995-10-29 00:00:00 -15224,579,54,5,27.0,2,,16,0.0,24,,,,5,1995-10-29 00:00:00 -15225,579,13,2,6.0,6,,14,0.0,39,,,,20,1995-10-29 00:00:00 -15226,579,70,2,5.0,4,,13,0.0,40,,,,20,1995-10-29 00:00:00 -15227,579,88,28,10.0,18,12.0,12,0.0,51,,,,12,1995-10-29 00:00:00 -15228,579,82,17,23.0,16,11.0,11,0.0,51,,,,12,1995-10-29 00:00:00 -15229,579,63,27,21.0,20,,15,0.0,32,,,,20,1995-10-29 00:00:00 -15230,579,68,17,24.0,17,9.0,9,0.0,51,,,,12,1995-10-29 00:00:00 -15231,579,48,14,30.0,8,8.0,8,0.0,52,,,,11,1995-10-29 00:00:00 -15232,579,86,0,7.0,23,7.0,7,0.0,52,,,,11,1995-10-29 00:00:00 -15233,579,62,24,4.0,12,6.0,6,1.0,52,,,,11,1995-10-29 00:00:00 -15234,579,43,26,26.0,11,5.0,5,2.0,52,,,,11,1995-10-29 00:00:00 -15235,579,55,16,15.0,7,4.0,4,3.0,53,5915066.0,,,1,1995-10-29 00:00:00 -15236,579,64,21,2.0,9,3.0,3,4.0,53,5896734.0,,,1,1995-10-29 00:00:00 -15237,579,56,0,8.0,3,2.0,2,6.0,53,5832267.0,,,1,1995-10-29 00:00:00 -15238,579,90,14,29.0,15,10.0,10,0.0,51,,,,12,1995-10-29 00:00:00 -15239,580,54,5,27.0,5,,16,0.0,23,,,,4,1995-11-12 00:00:00 -15240,580,89,27,22.0,20,,17,0.0,21,,,,20,1995-11-12 00:00:00 -15241,580,21,16,14.0,7,,18,0.0,20,,,,20,1995-11-12 00:00:00 -15242,580,13,2,6.0,2,,19,0.0,19,,,,3,1995-11-12 00:00:00 -15243,580,56,0,8.0,24,,24,0.0,0,,,,73,1995-11-12 00:00:00 -15244,580,90,14,29.0,18,,21,0.0,8,,,,68,1995-11-12 00:00:00 -15245,580,84,29,17.0,22,,22,0.0,2,,,,6,1995-11-12 00:00:00 -15246,580,68,17,24.0,15,,23,0.0,0,,,,10,1995-11-12 00:00:00 -15247,580,29,21,1.0,3,,15,0.0,25,,,,4,1995-11-12 00:00:00 -15248,580,88,28,10.0,19,,20,0.0,15,,,,20,1995-11-12 00:00:00 -15249,580,83,26,25.0,11,,14,0.0,29,,,,20,1995-11-12 00:00:00 -15250,580,78,24,3.0,16,,9,0.0,70,,,,5,1995-11-12 00:00:00 -15251,580,48,14,30.0,6,,12,0.0,39,,,,6,1995-11-12 00:00:00 -15252,580,70,2,5.0,1,1.0,1,10.0,81,6555946.0,,,1,1995-11-12 00:00:00 -15253,580,76,5,28.0,4,,13,0.0,34,,,,5,1995-11-12 00:00:00 -15254,580,80,28,9.0,13,3.0,3,4.0,79,,,,12,1995-11-12 00:00:00 -15255,580,86,0,7.0,10,4.0,4,3.0,79,,,,12,1995-11-12 00:00:00 -15256,580,62,24,4.0,14,5.0,5,2.0,78,,,,13,1995-11-12 00:00:00 -15257,580,43,26,26.0,12,2.0,2,6.0,79,,,,12,1995-11-12 00:00:00 -15258,580,63,27,21.0,21,7.0,7,0.0,77,,,,14,1995-11-12 00:00:00 -15259,580,91,29,16.0,23,8.0,8,0.0,76,,,,15,1995-11-12 00:00:00 -15260,580,64,21,2.0,8,,10,0.0,69,,,,7,1995-11-12 00:00:00 -15261,580,55,16,15.0,9,,11,0.0,62,,,,5,1995-11-12 00:00:00 -15262,580,82,17,23.0,17,6.0,6,1.0,78,,,,13,1995-11-12 00:00:00 -15263,581,20,17,21.0,16,,14,0.0,32,,,,8,1996-03-10 00:00:00 -15264,581,84,27,23.0,22,,22,0.0,0,,,,77,1996-03-10 00:00:00 -15265,581,68,27,22.0,21,,21,0.0,0,,,,77,1996-03-10 00:00:00 -15266,581,64,14,14.0,14,,20,0.0,0,,,,4,1996-03-10 00:00:00 -15267,581,83,16,12.0,19,,19,0.0,1,,,,4,1996-03-10 00:00:00 -15268,581,54,21,3.0,6,,18,0.0,9,,,,4,1996-03-10 00:00:00 -15269,581,49,28,17.0,12,,17,0.0,15,,,,5,1996-03-10 00:00:00 -15270,581,13,0,8.0,13,,16,0.0,24,,,,37,1996-03-10 00:00:00 -15271,581,21,16,11.0,8,,15,0.0,29,,,,5,1996-03-10 00:00:00 -15272,581,29,5,1.0,4,,13,0.0,32,,,,23,1996-03-10 00:00:00 -15273,581,43,26,9.0,11,7.0,7,0.0,57,,,,11,1996-03-10 00:00:00 -15274,581,78,24,18.0,15,11.0,11,0.0,55,,,,13,1996-03-10 00:00:00 -15275,581,34,2,6.0,1,2.0,2,6.0,58,5608420.0,,,1,1996-03-10 00:00:00 -15276,581,55,5,2.0,3,3.0,3,4.0,58,5632971.0,,,1,1996-03-10 00:00:00 -15277,581,76,21,4.0,7,4.0,4,3.0,58,5647437.0,,,1,1996-03-10 00:00:00 -15278,581,56,0,7.0,5,5.0,5,2.0,58,5665471.0,,,1,1996-03-10 00:00:00 -15279,581,82,17,20.0,17,,12,0.0,42,,,,93,1996-03-10 00:00:00 -15280,581,70,2,5.0,2,1.0,1,10.0,58,5570400.0,,,1,1996-03-10 00:00:00 -15281,581,48,14,15.0,9,8.0,8,0.0,57,,,,11,1996-03-10 00:00:00 -15282,581,72,28,16.0,18,9.0,9,0.0,56,,,,12,1996-03-10 00:00:00 -15283,581,63,26,10.0,20,10.0,10,0.0,56,,,,12,1996-03-10 00:00:00 -15284,581,62,24,19.0,10,6.0,6,1.0,57,,,,11,1996-03-10 00:00:00 -15285,582,21,16,11.0,2,,13,0.0,59,,,,20,1996-03-31 00:00:00 -15286,582,49,28,17.0,13,,21,0.0,19,,,,5,1996-03-31 00:00:00 -15287,582,72,28,16.0,17,,20,0.0,24,,,,20,1996-03-31 00:00:00 -15288,582,84,27,23.0,20,,19,0.0,26,,,,20,1996-03-31 00:00:00 -15289,582,76,21,4.0,8,,18,0.0,26,,,,9,1996-03-31 00:00:00 -15290,582,34,2,6.0,3,,17,0.0,26,,,,20,1996-03-31 00:00:00 -15291,582,64,14,14.0,12,,16,0.0,28,,,,5,1996-03-31 00:00:00 -15292,582,13,0,8.0,14,,15,0.0,29,,,,20,1996-03-31 00:00:00 -15293,582,48,14,15.0,9,,14,0.0,36,,,,5,1996-03-31 00:00:00 -15294,582,57,17,21.0,21,,22,0.0,0,,,,20,1996-03-31 00:00:00 -15295,582,83,16,12.0,6,12.0,12,0.0,64,,,,20,1996-03-31 00:00:00 -15296,582,82,17,20.0,18,10.0,10,0.0,68,,,,13,1996-03-31 00:00:00 -15297,582,68,27,22.0,19,11.0,11,0.0,67,,,,14,1996-03-31 00:00:00 -15298,582,54,21,3.0,5,2.0,2,6.0,71,6610958.0,,,1,1996-03-31 00:00:00 -15299,582,29,5,1.0,4,3.0,3,4.0,70,,,,11,1996-03-31 00:00:00 -15300,582,56,0,7.0,7,4.0,4,3.0,70,,,,11,1996-03-31 00:00:00 -15301,582,70,2,5.0,1,1.0,1,10.0,71,6592976.0,,,1,1996-03-31 00:00:00 -15302,582,43,26,9.0,15,6.0,6,1.0,70,,,,11,1996-03-31 00:00:00 -15303,582,55,5,2.0,10,7.0,7,0.0,70,,,,11,1996-03-31 00:00:00 -15304,582,63,26,10.0,22,8.0,8,0.0,69,,,,12,1996-03-31 00:00:00 -15305,582,78,24,18.0,16,9.0,9,0.0,69,,,,12,1996-03-31 00:00:00 -15306,582,62,24,19.0,11,5.0,5,2.0,70,,,,11,1996-03-31 00:00:00 -15307,583,62,24,19.0,16,,14,0.0,36,,,,37,1996-04-07 00:00:00 -15308,583,56,0,7.0,8,,22,0.0,19,,,,37,1996-04-07 00:00:00 -15309,583,72,28,16.0,20,,20,0.0,24,,,,94,1996-04-07 00:00:00 -15310,583,78,24,18.0,13,,19,0.0,28,,,,7,1996-04-07 00:00:00 -15311,583,63,26,10.0,18,,18,0.0,29,,,,42,1996-04-07 00:00:00 -15312,583,48,14,15.0,11,,17,0.0,32,,,,20,1996-04-07 00:00:00 -15313,583,57,17,21.0,14,,16,0.0,33,,,,4,1996-04-07 00:00:00 -15314,583,83,16,12.0,15,,15,0.0,34,,,,4,1996-04-07 00:00:00 -15315,583,82,17,20.0,19,,13,0.0,39,,,,7,1996-04-07 00:00:00 -15316,583,68,27,22.0,21,,21,0.0,24,,,,4,1996-04-07 00:00:00 -15317,583,76,21,4.0,5,,11,0.0,56,,,,22,1996-04-07 00:00:00 -15318,583,70,2,5.0,1,1.0,1,10.0,72,6895322.0,,,1,1996-04-07 00:00:00 -15319,583,29,5,1.0,2,,12,0.0,46,,,,41,1996-04-07 00:00:00 -15320,583,54,21,3.0,4,3.0,3,4.0,72,6910076.0,,,1,1996-04-07 00:00:00 -15321,583,21,16,11.0,6,4.0,4,3.0,72,6950453.0,,,1,1996-04-07 00:00:00 -15322,583,55,5,2.0,10,5.0,5,2.0,72,6960313.0,,,1,1996-04-07 00:00:00 -15323,583,34,2,6.0,3,2.0,2,6.0,72,6907489.0,,,1,1996-04-07 00:00:00 -15324,583,13,0,8.0,9,7.0,7,0.0,72,6968722.0,,,1,1996-04-07 00:00:00 -15325,583,84,27,23.0,22,10.0,10,0.0,69,,,,13,1996-04-07 00:00:00 -15326,583,43,26,9.0,12,8.0,8,0.0,72,6969617.0,,,1,1996-04-07 00:00:00 -15327,583,64,14,14.0,17,9.0,9,0.0,71,,,,11,1996-04-07 00:00:00 -15328,583,49,28,17.0,7,6.0,6,1.0,72,6964235.0,,,1,1996-04-07 00:00:00 -15329,584,68,27,22.0,22,,22,0.0,0,,,,77,1996-04-28 00:00:00 -15330,584,84,27,23.0,21,,21,0.0,0,,,,77,1996-04-28 00:00:00 -15331,584,54,21,3.0,4,,20,0.0,1,,,,4,1996-04-28 00:00:00 -15332,584,55,5,2.0,7,,19,0.0,6,,,,10,1996-04-28 00:00:00 -15333,584,43,26,9.0,15,,18,0.0,6,,,,4,1996-04-28 00:00:00 -15334,584,49,28,17.0,13,,17,0.0,38,,,,5,1996-04-28 00:00:00 -15335,584,78,24,18.0,16,,15,0.0,65,,,,2,1996-04-28 00:00:00 -15336,584,62,24,19.0,14,,14,0.0,66,,,,2,1996-04-28 00:00:00 -15337,584,20,17,21.0,18,13.0,13,0.0,65,,,,12,1996-04-28 00:00:00 -15338,584,48,14,15.0,10,,16,0.0,59,,,,23,1996-04-28 00:00:00 -15339,584,72,28,16.0,20,11.0,11,0.0,65,,,,12,1996-04-28 00:00:00 -15340,584,34,2,6.0,2,1.0,1,10.0,67,5606473.0,,,1,1996-04-28 00:00:00 -15341,584,82,17,20.0,19,12.0,12,0.0,65,,,,12,1996-04-28 00:00:00 -15342,584,13,0,8.0,6,3.0,3,4.0,67,5639307.0,,,1,1996-04-28 00:00:00 -15343,584,70,2,5.0,1,4.0,4,3.0,67,5639984.0,,,1,1996-04-28 00:00:00 -15344,584,21,16,11.0,5,5.0,5,2.0,67,5640186.0,,,1,1996-04-28 00:00:00 -15345,584,29,5,1.0,3,2.0,2,6.0,67,5607235.0,,,1,1996-04-28 00:00:00 -15346,584,64,14,14.0,12,7.0,7,0.0,67,5684500.0,,,1,1996-04-28 00:00:00 -15347,584,56,0,7.0,9,8.0,8,0.0,67,5684911.0,,,1,1996-04-28 00:00:00 -15348,584,76,21,4.0,8,9.0,9,0.0,67,5687534.0,,,1,1996-04-28 00:00:00 -15349,584,63,26,10.0,17,10.0,10,0.0,66,,,,11,1996-04-28 00:00:00 -15350,584,83,16,12.0,11,6.0,6,1.0,67,5662040.0,,,1,1996-04-28 00:00:00 -15351,585,13,0,8.0,4,,14,0.0,44,,,,9,1996-05-05 00:00:00 -15352,585,84,27,23.0,22,,22,0.0,0,,,,77,1996-05-05 00:00:00 -15353,585,62,24,19.0,8,,21,0.0,23,,,,5,1996-05-05 00:00:00 -15354,585,64,14,14.0,15,,20,0.0,25,,,,10,1996-05-05 00:00:00 -15355,585,20,17,21.0,19,,19,0.0,30,,,,5,1996-05-05 00:00:00 -15356,585,48,14,15.0,10,,18,0.0,32,,,,23,1996-05-05 00:00:00 -15357,585,83,16,12.0,12,,17,0.0,36,,,,20,1996-05-05 00:00:00 -15358,585,49,28,17.0,14,,16,0.0,38,,,,9,1996-05-05 00:00:00 -15359,585,72,28,16.0,20,,15,0.0,40,,,,5,1996-05-05 00:00:00 -15360,585,78,24,18.0,16,,13,0.0,45,,,,20,1996-05-05 00:00:00 -15361,585,21,16,11.0,9,5.0,5,2.0,63,5804646.0,,,1,1996-05-05 00:00:00 -15362,585,34,2,6.0,3,11.0,11,0.0,57,,,,22,1996-05-05 00:00:00 -15363,585,68,27,22.0,21,10.0,10,0.0,59,,,,14,1996-05-05 00:00:00 -15364,585,82,17,20.0,18,9.0,9,0.0,61,,,,12,1996-05-05 00:00:00 -15365,585,56,0,7.0,11,8.0,8,0.0,61,,,,5,1996-05-05 00:00:00 -15366,585,63,26,10.0,17,7.0,7,0.0,62,,,,11,1996-05-05 00:00:00 -15367,585,54,21,3.0,5,6.0,6,1.0,62,,,,11,1996-05-05 00:00:00 -15368,585,55,5,2.0,6,4.0,4,3.0,63,5787739.0,,,1,1996-05-05 00:00:00 -15369,585,76,21,4.0,7,3.0,3,4.0,63,5773047.0,,,1,1996-05-05 00:00:00 -15370,585,43,26,9.0,13,,12,0.0,54,,,,5,1996-05-05 00:00:00 -15371,585,29,5,1.0,1,2.0,2,6.0,63,5742616.0,,,1,1996-05-05 00:00:00 -15372,585,70,2,5.0,2,1.0,1,10.0,63,5726156.0,,,1,1996-05-05 00:00:00 -15373,586,72,28,16.0,20,,15,0.0,3,,,,20,1996-05-19 00:00:00 -15374,586,78,24,18.0,15,,16,0.0,2,,,,20,1996-05-19 00:00:00 -15375,586,29,5,1.0,1,,17,0.0,0,,,,20,1996-05-19 00:00:00 -15376,586,49,28,17.0,12,,21,0.0,0,,,,20,1996-05-19 00:00:00 -15377,586,82,17,20.0,19,,19,0.0,0,,,,4,1996-05-19 00:00:00 -15378,586,20,17,21.0,18,,20,0.0,0,,,,4,1996-05-19 00:00:00 -15379,586,84,27,23.0,22,,22,0.0,0,,,,82,1996-05-19 00:00:00 -15380,586,63,26,10.0,17,,14,0.0,5,,,,7,1996-05-19 00:00:00 -15381,586,21,16,11.0,6,,18,0.0,0,,,,20,1996-05-19 00:00:00 -15382,586,76,21,4.0,4,,13,0.0,9,,,,6,1996-05-19 00:00:00 -15383,586,56,0,7.0,8,6.0,6,1.0,70,,,,4,1996-05-19 00:00:00 -15384,586,70,2,5.0,2,,11,0.0,40,,,,5,1996-05-19 00:00:00 -15385,586,68,27,22.0,21,,10,0.0,60,,,,4,1996-05-19 00:00:00 -15386,586,54,21,3.0,3,,9,0.0,60,,,,22,1996-05-19 00:00:00 -15387,586,34,2,6.0,10,,8,0.0,66,,,,4,1996-05-19 00:00:00 -15388,586,55,5,2.0,7,7.0,7,0.0,68,,,,4,1996-05-19 00:00:00 -15389,586,62,24,19.0,11,5.0,5,2.0,70,,,,4,1996-05-19 00:00:00 -15390,586,48,14,15.0,9,4.0,4,3.0,74,,,,54,1996-05-19 00:00:00 -15391,586,64,14,14.0,13,3.0,3,4.0,75,7283132.0,,,1,1996-05-19 00:00:00 -15392,586,13,0,8.0,5,2.0,2,6.0,75,7250457.0,,,1,1996-05-19 00:00:00 -15393,586,43,26,9.0,14,1.0,1,10.0,75,7245629.0,,,1,1996-05-19 00:00:00 -15394,586,83,16,12.0,16,,12,0.0,30,,,,20,1996-05-19 00:00:00 -15395,587,55,5,2.0,6,,15,0.0,1,,,,20,1996-06-02 00:00:00 -15396,587,43,26,9.0,8,,16,0.0,1,,,,4,1996-06-02 00:00:00 -15397,587,20,17,21.0,19,,17,0.0,1,,,,4,1996-06-02 00:00:00 -15398,587,84,27,23.0,22,,22,0.0,0,,,,77,1996-06-02 00:00:00 -15399,587,72,28,16.0,20,,19,0.0,0,,,,4,1996-06-02 00:00:00 -15400,587,82,17,20.0,18,,20,0.0,0,,,,4,1996-06-02 00:00:00 -15401,587,68,27,22.0,21,,21,0.0,0,,,,77,1996-06-02 00:00:00 -15402,587,70,2,5.0,1,,13,0.0,10,,,,20,1996-06-02 00:00:00 -15403,587,13,0,8.0,14,,18,0.0,0,,,,4,1996-06-02 00:00:00 -15404,587,62,24,19.0,12,,12,0.0,16,,,,2,1996-06-02 00:00:00 -15405,587,78,24,18.0,16,,14,0.0,8,,,,10,1996-06-02 00:00:00 -15406,587,64,14,14.0,9,,10,0.0,20,,,,20,1996-06-02 00:00:00 -15407,587,83,16,12.0,15,,11,0.0,17,,,,24,1996-06-02 00:00:00 -15408,587,29,5,1.0,3,1.0,1,10.0,65,7189307.0,,,1,1996-06-02 00:00:00 -15409,587,34,2,6.0,2,3.0,3,4.0,65,7237695.0,,,1,1996-06-02 00:00:00 -15410,587,48,14,15.0,11,4.0,4,3.0,64,,,,11,1996-06-02 00:00:00 -15411,587,54,21,3.0,4,2.0,2,6.0,65,7234609.0,,,1,1996-06-02 00:00:00 -15412,587,63,26,10.0,17,6.0,6,1.0,63,,,,12,1996-06-02 00:00:00 -15413,587,49,28,17.0,13,,7,0.0,47,,,,20,1996-06-02 00:00:00 -15414,587,21,16,11.0,7,,8,0.0,45,,,,24,1996-06-02 00:00:00 -15415,587,76,21,4.0,5,,9,0.0,44,,,,20,1996-06-02 00:00:00 -15416,587,56,0,7.0,10,5.0,5,2.0,64,,,,11,1996-06-02 00:00:00 -15417,588,82,17,20.0,19,,9,0.0,44,,,,4,1996-06-16 00:00:00 -15418,588,43,26,9.0,11,,13,0.0,39,,,,5,1996-06-16 00:00:00 -15419,588,62,24,19.0,14,,14,0.0,39,,,,5,1996-06-16 00:00:00 -15420,588,76,21,4.0,7,,11,0.0,42,,,,20,1996-06-16 00:00:00 -15421,588,68,27,22.0,20,,10,0.0,44,,,,6,1996-06-16 00:00:00 -15422,588,20,17,21.0,16,8.0,8,0.0,67,,,,12,1996-06-16 00:00:00 -15423,588,54,21,3.0,4,3.0,3,4.0,69,5818056.0,,,1,1996-06-16 00:00:00 -15424,588,83,16,12.0,9,6.0,6,1.0,68,,,,11,1996-06-16 00:00:00 -15425,588,56,0,7.0,6,5.0,5,2.0,68,,,,11,1996-06-16 00:00:00 -15426,588,13,0,8.0,10,4.0,4,3.0,69,5827073.0,,,1,1996-06-16 00:00:00 -15427,588,34,2,6.0,2,2.0,2,6.0,69,5767583.0,,,1,1996-06-16 00:00:00 -15428,588,70,2,5.0,1,1.0,1,10.0,69,5763400.0,,,1,1996-06-16 00:00:00 -15429,588,64,14,14.0,15,7.0,7,0.0,68,,,,11,1996-06-16 00:00:00 -15430,588,63,26,10.0,18,,15,0.0,38,,,,5,1996-06-16 00:00:00 -15431,588,29,5,1.0,3,,12,0.0,41,,,,86,1996-06-16 00:00:00 -15432,588,84,27,23.0,22,,17,0.0,22,,,,10,1996-06-16 00:00:00 -15433,588,48,14,15.0,12,,18,0.0,19,,,,6,1996-06-16 00:00:00 -15434,588,49,28,17.0,13,,19,0.0,10,,,,5,1996-06-16 00:00:00 -15435,588,72,28,16.0,21,,20,0.0,6,,,,4,1996-06-16 00:00:00 -15436,588,78,24,18.0,17,,21,0.0,6,,,,4,1996-06-16 00:00:00 -15437,588,55,5,2.0,5,,22,0.0,1,,,,22,1996-06-16 00:00:00 -15438,588,21,16,11.0,8,,16,0.0,22,,,,8,1996-06-16 00:00:00 -15439,589,78,24,18.0,14,,15,0.0,33,,,,5,1996-06-30 00:00:00 -15440,589,68,27,22.0,20,,16,0.0,29,,,,69,1996-06-30 00:00:00 -15441,589,63,26,10.0,11,,17,0.0,28,,,,5,1996-06-30 00:00:00 -15442,589,49,28,17.0,15,,18,0.0,10,,,,38,1996-06-30 00:00:00 -15443,589,84,27,23.0,21,,21,0.0,2,,,,10,1996-06-30 00:00:00 -15444,589,20,17,21.0,17,,20,0.0,2,,,,48,1996-06-30 00:00:00 -15445,589,64,14,14.0,16,,13,0.0,70,,,,2,1996-06-30 00:00:00 -15446,589,29,5,1.0,1,,22,0.0,0,,,,5,1996-06-30 00:00:00 -15447,589,55,5,2.0,22,,19,0.0,5,,,,6,1996-06-30 00:00:00 -15448,589,82,17,20.0,18,12.0,12,0.0,69,,,,13,1996-06-30 00:00:00 -15449,589,48,14,15.0,12,,14,0.0,56,,,,37,1996-06-30 00:00:00 -15450,589,62,24,19.0,13,10.0,10,0.0,70,,,,12,1996-06-30 00:00:00 -15451,589,72,28,16.0,19,11.0,11,0.0,69,,,,13,1996-06-30 00:00:00 -15452,589,34,2,6.0,6,2.0,2,6.0,72,5797327.0,,,1,1996-06-30 00:00:00 -15453,589,54,21,3.0,3,3.0,3,4.0,72,5835642.0,,,1,1996-06-30 00:00:00 -15454,589,76,21,4.0,4,4.0,4,3.0,72,5836059.0,,,1,1996-06-30 00:00:00 -15455,589,56,0,7.0,5,5.0,5,2.0,72,5851974.0,,,1,1996-06-30 00:00:00 -15456,589,70,2,5.0,2,1.0,1,10.0,72,5789200.0,,,1,1996-06-30 00:00:00 -15457,589,43,26,9.0,9,7.0,7,0.0,71,,,,11,1996-06-30 00:00:00 -15458,589,83,16,12.0,8,8.0,8,0.0,71,,,,11,1996-06-30 00:00:00 -15459,589,21,16,11.0,10,9.0,9,0.0,71,,,,11,1996-06-30 00:00:00 -15460,589,13,0,8.0,7,6.0,6,1.0,71,,,,11,1996-06-30 00:00:00 -15461,590,63,26,10.0,17,,14,0.0,38,,,,5,1996-07-14 00:00:00 -15462,590,68,27,22.0,22,,22,0.0,0,,,,81,1996-07-14 00:00:00 -15463,590,84,27,23.0,21,,21,0.0,0,,,,81,1996-07-14 00:00:00 -15464,590,29,5,1.0,3,,20,0.0,3,,,,9,1996-07-14 00:00:00 -15465,590,55,5,2.0,10,,19,0.0,5,,,,24,1996-07-14 00:00:00 -15466,590,78,24,18.0,12,,18,0.0,12,,,,5,1996-07-14 00:00:00 -15467,590,72,28,16.0,20,,17,0.0,13,,,,10,1996-07-14 00:00:00 -15468,590,82,17,20.0,19,,16,0.0,21,,,,6,1996-07-14 00:00:00 -15469,590,70,2,5.0,1,,15,0.0,26,,,,36,1996-07-14 00:00:00 -15470,590,43,26,9.0,16,,13,0.0,40,,,,64,1996-07-14 00:00:00 -15471,590,76,21,4.0,7,2.0,2,6.0,61,5599900.0,,,1,1996-07-14 00:00:00 -15472,590,20,17,21.0,18,11.0,11,0.0,59,,,,12,1996-07-14 00:00:00 -15473,590,49,28,17.0,15,10.0,10,0.0,60,,,,11,1996-07-14 00:00:00 -15474,590,64,14,14.0,13,9.0,9,0.0,60,,,,11,1996-07-14 00:00:00 -15475,590,48,14,15.0,11,8.0,8,0.0,60,,,,11,1996-07-14 00:00:00 -15476,590,62,24,19.0,14,7.0,7,0.0,60,,,,11,1996-07-14 00:00:00 -15477,590,83,16,12.0,8,6.0,6,1.0,60,,,,11,1996-07-14 00:00:00 -15478,590,13,0,8.0,9,5.0,5,2.0,61,5663381.0,,,1,1996-07-14 00:00:00 -15479,590,21,16,11.0,6,4.0,4,3.0,61,5647590.0,,,1,1996-07-14 00:00:00 -15480,590,56,0,7.0,4,3.0,3,4.0,61,5631704.0,,,1,1996-07-14 00:00:00 -15481,590,54,21,3.0,5,,12,0.0,44,,,,23,1996-07-14 00:00:00 -15482,590,34,2,6.0,2,1.0,1,10.0,61,5580874.0,,,1,1996-07-14 00:00:00 -15483,591,55,5,2.0,8,,14,0.0,34,,,,5,1996-07-28 00:00:00 -15484,591,64,14,14.0,14,,15,0.0,25,,,,76,1996-07-28 00:00:00 -15485,591,63,26,10.0,11,,16,0.0,19,,,,5,1996-07-28 00:00:00 -15486,591,76,21,4.0,2,13.0,13,0.0,42,,,,5,1996-07-28 00:00:00 -15487,591,56,0,7.0,4,,18,0.0,13,,,,6,1996-07-28 00:00:00 -15488,591,49,28,17.0,17,,19,0.0,0,,,,4,1996-07-28 00:00:00 -15489,591,85,17,21.0,0,,20,0.0,0,,,,81,1996-07-28 00:00:00 -15490,591,78,24,18.0,16,,17,0.0,19,,,,20,1996-07-28 00:00:00 -15491,591,82,17,20.0,18,12.0,12,0.0,43,,,,12,1996-07-28 00:00:00 -15492,591,48,14,15.0,13,8.0,8,0.0,44,,,,11,1996-07-28 00:00:00 -15493,591,83,16,12.0,10,10.0,10,0.0,44,,,,11,1996-07-28 00:00:00 -15494,591,72,28,16.0,19,11.0,11,0.0,44,,,,11,1996-07-28 00:00:00 -15495,591,54,21,3.0,5,2.0,2,6.0,45,4914869.0,,,1,1996-07-28 00:00:00 -15496,591,34,2,6.0,6,3.0,3,4.0,45,4937343.0,,,1,1996-07-28 00:00:00 -15497,591,29,5,1.0,3,4.0,4,3.0,45,4944934.0,,,1,1996-07-28 00:00:00 -15498,591,70,2,5.0,1,1.0,1,10.0,45,4903417.0,,,1,1996-07-28 00:00:00 -15499,591,21,16,11.0,9,6.0,6,1.0,45,5005516.0,,,1,1996-07-28 00:00:00 -15500,591,43,26,9.0,12,7.0,7,0.0,45,5007329.0,,,1,1996-07-28 00:00:00 -15501,591,62,24,19.0,15,9.0,9,0.0,44,,,,11,1996-07-28 00:00:00 -15502,591,13,0,8.0,7,5.0,5,2.0,45,4945613.0,,,1,1996-07-28 00:00:00 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-15519,592,56,0,7.0,7,4.0,4,3.0,76,,,,11,1996-08-11 00:00:00 -15520,592,54,21,3.0,5,3.0,3,4.0,77,6465346.0,,,1,1996-08-11 00:00:00 -15521,592,76,21,4.0,6,,11,0.0,64,,,,5,1996-08-11 00:00:00 -15522,592,34,2,6.0,3,1.0,1,10.0,77,6381134.0,,,1,1996-08-11 00:00:00 -15523,593,21,16,11.0,10,,14,0.0,29,,,,22,1996-08-25 00:00:00 -15524,593,63,26,10.0,15,,15,0.0,22,,,,10,1996-08-25 00:00:00 -15525,593,49,28,17.0,16,,16,0.0,11,,,,3,1996-08-25 00:00:00 -15526,593,55,5,2.0,9,,13,0.0,29,,,,6,1996-08-25 00:00:00 -15527,593,64,14,14.0,12,,18,0.0,0,,,,4,1996-08-25 00:00:00 -15528,593,43,26,9.0,14,,19,0.0,0,,,,4,1996-08-25 00:00:00 -15529,593,85,17,21.0,0,,20,0.0,0,,,,81,1996-08-25 00:00:00 -15530,593,48,14,15.0,11,,17,0.0,0,,,,4,1996-08-25 00:00:00 -15531,593,83,16,12.0,8,,12,0.0,34,,,,5,1996-08-25 00:00:00 -15532,593,13,0,8.0,4,,11,0.0,37,,,,20,1996-08-25 00:00:00 -15533,593,82,17,20.0,19,10.0,10,0.0,43,,,,11,1996-08-25 00:00:00 -15534,593,29,5,1.0,3,1.0,1,10.0,44,5295125.0,,,1,1996-08-25 00:00:00 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-15565,595,63,26,10.0,18,,19,0.0,46,,,,4,1996-09-22 00:00:00 -15566,595,49,28,17.0,16,,18,0.0,47,,,,5,1996-09-22 00:00:00 -15567,595,56,0,7.0,7,,17,0.0,52,,,,4,1996-09-22 00:00:00 -15568,595,82,17,20.0,19,16.0,16,0.0,65,,,,15,1996-09-22 00:00:00 -15569,595,72,28,16.0,17,14.0,14,0.0,67,,,,13,1996-09-22 00:00:00 -15570,595,78,24,18.0,14,12.0,12,0.0,68,,,,12,1996-09-22 00:00:00 -15571,595,85,17,21.0,20,15.0,15,0.0,65,,,,15,1996-09-22 00:00:00 -15572,595,43,26,9.0,15,10.0,10,0.0,69,,,,11,1996-09-22 00:00:00 -15573,595,29,5,1.0,4,3.0,3,4.0,70,6076680.0,,,1,1996-09-22 00:00:00 -15574,595,54,21,3.0,3,4.0,4,3.0,70,6078024.0,,,1,1996-09-22 00:00:00 -15575,595,55,5,2.0,6,5.0,5,2.0,70,6110304.0,,,1,1996-09-22 00:00:00 -15576,595,76,21,4.0,5,6.0,6,1.0,70,6116056.0,,,1,1996-09-22 00:00:00 -15577,595,70,2,5.0,1,2.0,2,6.0,70,6042881.0,,,1,1996-09-22 00:00:00 -15578,595,34,2,6.0,2,1.0,1,10.0,70,6022915.0,,,1,1996-09-22 00:00:00 -15579,595,64,14,14.0,12,8.0,8,0.0,69,,,,11,1996-09-22 00:00:00 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-15625,597,74,19,15.0,16,7.0,7,0.0,56,,,,12,1997-03-09 00:00:00 -15626,597,75,23,23.0,19,,13,0.0,36,,,,22,1997-03-09 00:00:00 -15627,598,62,24,19.0,22,13.0,13,0.0,71,,,,11,1997-03-30 00:00:00 -15628,598,75,23,23.0,20,,22,0.0,0,,,,3,1997-03-30 00:00:00 -15629,598,63,20,2.0,16,,21,0.0,15,,,,22,1997-03-30 00:00:00 -15630,598,21,23,22.0,11,,20,0.0,16,,,,22,1997-03-30 00:00:00 -15631,598,22,16,11.0,10,,19,0.0,52,,,,10,1997-03-30 00:00:00 -15632,598,78,17,20.0,18,18.0,18,0.0,67,,,,15,1997-03-30 00:00:00 -15633,598,70,20,1.0,9,17.0,17,0.0,68,,,,5,1997-03-30 00:00:00 -15634,598,55,5,6.0,14,16.0,16,0.0,70,,,,12,1997-03-30 00:00:00 -15635,598,49,24,18.0,21,15.0,15,0.0,70,,,,12,1997-03-30 00:00:00 -15636,598,74,19,15.0,15,14.0,14,0.0,71,,,,11,1997-03-30 00:00:00 -15637,598,14,17,21.0,17,12.0,12,0.0,71,,,,11,1997-03-30 00:00:00 -15638,598,13,0,10.0,12,10.0,10,0.0,71,,,,11,1997-03-30 00:00:00 -15639,598,48,2,4.0,8,9.0,9,0.0,72,5842392.0,,,1,1997-03-30 00:00:00 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00:00:00 -15686,600,54,21,7.0,14,5.0,5,2.0,61,,,,11,1997-04-27 00:00:00 -15687,600,29,5,5.0,3,2.0,2,6.0,62,5461910.0,,,1,1997-04-27 00:00:00 -15688,600,77,14,17.0,12,7.0,7,0.0,61,,,,11,1997-04-27 00:00:00 -15689,600,43,19,14.0,4,8.0,8,0.0,61,,,,11,1997-04-27 00:00:00 -15690,600,62,24,19.0,19,9.0,9,0.0,60,,,,12,1997-04-27 00:00:00 -15691,600,49,24,18.0,21,10.0,10,0.0,60,,,,12,1997-04-27 00:00:00 -15692,600,56,0,9.0,8,6.0,6,1.0,61,,,,11,1997-04-27 00:00:00 -15693,601,54,21,7.0,9,,14,0.0,16,,,,20,1997-05-11 00:00:00 -15694,601,63,20,2.0,16,,22,0.0,0,,,,20,1997-05-11 00:00:00 -15695,601,70,20,1.0,13,,21,0.0,1,,,,4,1997-05-11 00:00:00 -15696,601,56,0,9.0,8,,20,0.0,1,,,,4,1997-05-11 00:00:00 -15697,601,13,0,10.0,5,,19,0.0,1,,,,20,1997-05-11 00:00:00 -15698,601,14,17,21.0,18,,18,0.0,7,,,,20,1997-05-11 00:00:00 -15699,601,64,14,16.0,7,,17,0.0,9,,,,20,1997-05-11 00:00:00 -15700,601,34,2,3.0,3,,15,0.0,16,,,,20,1997-05-11 00:00:00 -15701,601,74,19,15.0,21,,12,0.0,36,,,,20,1997-05-11 00:00:00 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00:00:00 -15792,605,74,19,15.0,15,11.0,11,0.0,57,,,,5,1997-07-13 00:00:00 -15793,605,78,17,20.0,19,,22,0.0,0,,,,20,1997-07-13 00:00:00 -15794,605,48,2,4.0,2,,21,0.0,0,,,,4,1997-07-13 00:00:00 -15795,605,63,20,2.0,17,,20,0.0,29,,,,5,1997-07-13 00:00:00 -15796,605,21,23,22.0,22,,19,0.0,37,,,,5,1997-07-13 00:00:00 -15797,605,75,23,23.0,16,,13,0.0,50,,,,5,1997-07-13 00:00:00 -15798,605,64,14,16.0,9,,17,0.0,42,,,,10,1997-07-13 00:00:00 -15799,605,62,24,19.0,18,,16,0.0,44,,,,5,1997-07-13 00:00:00 -15800,605,55,5,6.0,7,,15,0.0,44,,,,86,1997-07-13 00:00:00 -15801,605,49,24,18.0,20,,14,0.0,45,,,,5,1997-07-13 00:00:00 -15802,605,29,5,5.0,4,,18,0.0,38,,,,36,1997-07-13 00:00:00 -15803,606,57,17,21.0,21,,22,0.0,0,,,,6,1997-07-27 00:00:00 -15804,606,55,5,6.0,10,,21,0.0,1,,,,4,1997-07-27 00:00:00 -15805,606,48,2,4.0,5,,20,0.0,1,,,,4,1997-07-27 00:00:00 -15806,606,13,0,10.0,8,,19,0.0,1,,,,7,1997-07-27 00:00:00 -15807,606,63,20,2.0,16,,18,0.0,8,,,,3,1997-07-27 00:00:00 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-15823,606,21,23,22.0,12,,12,0.0,33,,,,5,1997-07-27 00:00:00 -15824,606,74,19,15.0,17,7.0,7,0.0,45,4938768.0,,,1,1997-07-27 00:00:00 -15825,607,55,5,6.0,5,9.0,9,0.0,76,,,,20,1997-08-10 00:00:00 -15826,607,70,20,1.0,3,2.0,2,6.0,77,6356228.0,,,1,1997-08-10 00:00:00 -15827,607,34,2,3.0,2,1.0,1,10.0,77,6347149.0,,,1,1997-08-10 00:00:00 -15828,607,75,23,23.0,17,,22,0.0,5,,,,3,1997-08-10 00:00:00 -15829,607,80,14,17.0,15,,21,0.0,7,,,,5,1997-08-10 00:00:00 -15830,607,56,0,9.0,4,,20,0.0,12,,,,9,1997-08-10 00:00:00 -15831,607,21,23,22.0,11,,19,0.0,29,,,,5,1997-08-10 00:00:00 -15832,607,20,16,12.0,13,,17,0.0,42,,,,20,1997-08-10 00:00:00 -15833,607,63,20,2.0,19,,16,0.0,53,,,,10,1997-08-10 00:00:00 -15834,607,49,24,18.0,18,,15,0.0,61,,,,6,1997-08-10 00:00:00 -15835,607,13,0,10.0,8,,14,0.0,65,,,,10,1997-08-10 00:00:00 -15836,607,48,2,4.0,6,,18,0.0,29,,,,74,1997-08-10 00:00:00 -15837,607,57,17,21.0,22,12.0,12,0.0,75,,,,12,1997-08-10 00:00:00 -15838,607,62,24,19.0,21,13.0,13,0.0,75,,,,12,1997-08-10 00:00:00 -15839,607,29,5,5.0,1,4.0,4,3.0,77,6377650.0,,,1,1997-08-10 00:00:00 -15840,607,22,16,11.0,14,5.0,5,2.0,77,6377864.0,,,1,1997-08-10 00:00:00 -15841,607,74,19,15.0,16,6.0,6,1.0,77,6388661.0,,,1,1997-08-10 00:00:00 -15842,607,64,14,16.0,10,3.0,3,4.0,77,6367594.0,,,1,1997-08-10 00:00:00 -15843,607,76,21,8.0,7,8.0,8,0.0,77,6423558.0,,,1,1997-08-10 00:00:00 -15844,607,78,17,20.0,20,10.0,10,0.0,76,,,,11,1997-08-10 00:00:00 -15845,607,54,21,7.0,9,11.0,11,0.0,76,,,,11,1997-08-10 00:00:00 -15846,607,14,19,14.0,12,7.0,7,0.0,77,6422701.0,,,1,1997-08-10 00:00:00 -15847,608,70,20,1.0,9,13.0,13,0.0,42,,,,12,1997-08-24 00:00:00 -15848,608,74,19,15.0,16,,22,0.0,5,,,,10,1997-08-24 00:00:00 -15849,608,21,23,22.0,12,,21,0.0,8,,,,38,1997-08-24 00:00:00 -15850,608,57,17,21.0,22,,20,0.0,18,,,,20,1997-08-24 00:00:00 -15851,608,13,0,10.0,10,,19,0.0,19,,,,20,1997-08-24 00:00:00 -15852,608,49,24,18.0,21,,17,0.0,25,,,,20,1997-08-24 00:00:00 -15853,608,56,0,9.0,5,,16,0.0,44,,,,2,1997-08-24 00:00:00 -15854,608,14,19,14.0,14,15.0,15,0.0,42,,,,12,1997-08-24 00:00:00 -15855,608,78,17,20.0,20,14.0,14,0.0,42,,,,12,1997-08-24 00:00:00 -15856,608,75,23,23.0,18,12.0,12,0.0,43,,,,11,1997-08-24 00:00:00 -15857,608,22,16,11.0,6,,18,0.0,21,,,,20,1997-08-24 00:00:00 -15858,608,55,5,6.0,17,10.0,10,0.0,43,,,,11,1997-08-24 00:00:00 -15859,608,62,24,19.0,19,11.0,11,0.0,43,,,,11,1997-08-24 00:00:00 -15860,608,20,16,12.0,4,2.0,2,6.0,44,5653470.0,,,1,1997-08-24 00:00:00 -15861,608,48,2,4.0,7,3.0,3,4.0,44,5658864.0,,,1,1997-08-24 00:00:00 -15862,608,64,14,16.0,11,4.0,4,3.0,44,5665742.0,,,1,1997-08-24 00:00:00 -15863,608,29,5,5.0,3,1.0,1,10.0,44,5626717.0,,,1,1997-08-24 00:00:00 -15864,608,76,21,8.0,15,6.0,6,1.0,44,5690458.0,,,1,1997-08-24 00:00:00 -15865,608,63,20,2.0,8,7.0,7,0.0,44,5712648.0,,,1,1997-08-24 00:00:00 -15866,608,54,21,7.0,2,8.0,8,0.0,44,5728725.0,,,1,1997-08-24 00:00:00 -15867,608,80,14,17.0,13,9.0,9,0.0,44,5729299.0,,,1,1997-08-24 00:00:00 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-15898,610,57,17,21.0,0,,22,0.0,0,,,,92,1997-09-21 00:00:00 -15899,610,55,5,6.0,8,,19,0.0,38,,,,4,1997-09-21 00:00:00 -15900,610,63,20,2.0,17,13.0,13,0.0,67,,,,14,1997-09-21 00:00:00 -15901,610,34,2,3.0,1,1.0,1,10.0,71,5255999.0,,,1,1997-09-21 00:00:00 -15902,610,78,17,20.0,19,11.0,11,0.0,69,,,,12,1997-09-21 00:00:00 -15903,610,76,21,8.0,18,10.0,10,0.0,70,,,,11,1997-09-21 00:00:00 -15904,610,80,14,17.0,13,9.0,9,0.0,71,5322454.0,,,1,1997-09-21 00:00:00 -15905,610,64,14,16.0,12,8.0,8,0.0,71,5305056.0,,,1,1997-09-21 00:00:00 -15906,610,70,20,1.0,7,7.0,7,0.0,71,5293206.0,,,1,1997-09-21 00:00:00 -15907,610,29,5,5.0,9,6.0,6,1.0,71,5289409.0,,,1,1997-09-21 00:00:00 -15908,610,22,16,11.0,11,5.0,5,2.0,71,5287858.0,,,1,1997-09-21 00:00:00 -15909,610,20,16,12.0,14,4.0,4,3.0,71,5268126.0,,,1,1997-09-21 00:00:00 -15910,610,48,2,4.0,4,3.0,3,4.0,71,5259961.0,,,1,1997-09-21 00:00:00 -15911,610,49,24,18.0,20,12.0,12,0.0,69,,,,12,1997-09-21 00:00:00 -15912,610,13,0,10.0,10,2.0,2,6.0,71,5258908.0,,,1,1997-09-21 00:00:00 -15913,611,75,23,23.0,12,,15,0.0,40,,,,86,1997-09-28 00:00:00 -15914,611,55,5,6.0,14,,16,0.0,22,,,,5,1997-09-28 00:00:00 -15915,611,74,19,15.0,17,,17,0.0,16,,,,5,1997-09-28 00:00:00 -15916,611,22,16,11.0,8,,22,0.0,0,,,,4,1997-09-28 00:00:00 -15917,611,57,17,21.0,18,,19,0.0,1,,,,5,1997-09-28 00:00:00 -15918,611,78,17,20.0,22,,20,0.0,1,,,,4,1997-09-28 00:00:00 -15919,611,20,16,12.0,4,,21,0.0,0,,,,4,1997-09-28 00:00:00 -15920,611,13,0,10.0,6,,14,0.0,42,,,,5,1997-09-28 00:00:00 -15921,611,21,23,22.0,9,,13,0.0,43,,,,6,1997-09-28 00:00:00 -15922,611,29,5,5.0,5,,18,0.0,2,,,,22,1997-09-28 00:00:00 -15923,611,49,24,18.0,21,,11,0.0,50,,,,20,1997-09-28 00:00:00 -15924,611,56,0,9.0,1,,12,0.0,43,,,,5,1997-09-28 00:00:00 -15925,611,34,2,3.0,2,1.0,1,10.0,67,5487843.0,,,1,1997-09-28 00:00:00 -15926,611,48,2,4.0,3,3.0,3,4.0,67,5501323.0,,,1,1997-09-28 00:00:00 -15927,611,76,21,8.0,7,4.0,4,3.0,67,5504259.0,,,1,1997-09-28 00:00:00 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-15943,612,49,24,18.0,21,13.0,13,0.0,52,,,,11,1997-10-12 00:00:00 -15944,612,62,24,19.0,22,,16,0.0,46,,,,5,1997-10-12 00:00:00 -15945,612,70,20,1.0,17,11.0,11,0.0,52,,,,11,1997-10-12 00:00:00 -15946,612,13,0,10.0,11,10.0,10,0.0,52,,,,5,1997-10-12 00:00:00 -15947,612,22,16,11.0,13,9.0,9,0.0,53,5470482.0,,,1,1997-10-12 00:00:00 -15948,612,29,5,5.0,2,1.0,1,10.0,53,5388446.0,,,1,1997-10-12 00:00:00 -15949,612,76,21,8.0,5,8.0,8,0.0,53,5448875.0,,,1,1997-10-12 00:00:00 -15950,612,20,16,12.0,9,7.0,7,0.0,53,5445271.0,,,1,1997-10-12 00:00:00 -15951,612,64,14,16.0,8,6.0,6,1.0,53,5430076.0,,,1,1997-10-12 00:00:00 -15952,612,54,21,7.0,7,5.0,5,2.0,53,5428849.0,,,1,1997-10-12 00:00:00 -15953,612,56,0,9.0,4,4.0,4,3.0,53,5415575.0,,,1,1997-10-12 00:00:00 -15954,612,55,5,6.0,3,3.0,3,4.0,53,5414830.0,,,1,1997-10-12 00:00:00 -15955,612,63,20,2.0,16,12.0,12,0.0,52,,,,11,1997-10-12 00:00:00 -15956,612,48,2,4.0,6,2.0,2,6.0,53,5389824.0,,,1,1997-10-12 00:00:00 -15957,613,57,17,21.0,20,15.0,15,0.0,68,,,,11,1997-10-26 00:00:00 -15958,613,49,24,18.0,22,16.0,16,0.0,68,,,,11,1997-10-26 00:00:00 -15959,613,78,17,20.0,19,17.0,17,0.0,68,,,,11,1997-10-26 00:00:00 -15960,613,63,20,2.0,13,,22,0.0,11,,,,20,1997-10-26 00:00:00 -15961,613,70,20,1.0,4,,19,0.0,47,,,,6,1997-10-26 00:00:00 -15962,613,22,16,11.0,16,,20,0.0,44,,,,47,1997-10-26 00:00:00 -15963,613,21,23,22.0,12,,21,0.0,30,,,,6,1997-10-26 00:00:00 -15964,613,81,14,17.0,18,14.0,14,0.0,68,,,,11,1997-10-26 00:00:00 -15965,613,29,5,5.0,2,,18,0.0,47,,,,4,1997-10-26 00:00:00 -15966,613,54,21,7.0,10,13.0,13,0.0,68,,,,11,1997-10-26 00:00:00 -15967,613,74,19,15.0,15,10.0,10,0.0,69,6015986.0,,,1,1997-10-26 00:00:00 -15968,613,20,16,12.0,17,11.0,11,0.0,68,,,,11,1997-10-26 00:00:00 -15969,613,62,24,19.0,21,12.0,12,0.0,68,,,,11,1997-10-26 00:00:00 -15970,613,56,0,9.0,5,1.0,1,10.0,69,5937771.0,,,1,1997-10-26 00:00:00 -15971,613,13,0,10.0,6,2.0,2,6.0,69,5939425.0,,,1,1997-10-26 00:00:00 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-15987,614,72,24,20.0,19,,13,0.0,25,,,,6,1998-03-08 00:00:00 -15988,614,20,21,5.0,7,,10,0.0,43,,,,41,1998-03-08 00:00:00 -15989,614,54,14,14.0,12,,11,0.0,41,,,,5,1998-03-08 00:00:00 -15990,614,43,19,11.0,21,9.0,9,0.0,57,,,,11,1998-03-08 00:00:00 -15991,614,70,16,9.0,10,8.0,8,0.0,57,,,,11,1998-03-08 00:00:00 -15992,614,64,14,15.0,5,6.0,6,1.0,57,,,,11,1998-03-08 00:00:00 -15993,614,34,2,1.0,4,5.0,5,2.0,57,,,,11,1998-03-08 00:00:00 -15994,614,55,5,4.0,8,4.0,4,3.0,57,,,,11,1998-03-08 00:00:00 -15995,614,48,2,2.0,6,3.0,3,4.0,57,,,,11,1998-03-08 00:00:00 -15996,614,13,0,7.0,2,2.0,2,6.0,58,5506702.0,,,1,1998-03-08 00:00:00 -15997,614,56,0,8.0,1,1.0,1,10.0,58,5506000.0,,,1,1998-03-08 00:00:00 -15998,614,14,19,12.0,15,,12,0.0,26,,,,6,1998-03-08 00:00:00 -15999,614,24,21,6.0,11,7.0,7,0.0,57,,,,11,1998-03-08 00:00:00 -16000,614,74,17,22.0,22,,16,0.0,8,,,,86,1998-03-08 00:00:00 -16001,615,14,19,12.0,12,,20,0.0,17,,,,48,1998-03-29 00:00:00 -16002,615,62,20,17.0,20,,19,0.0,18,,,,5,1998-03-29 00:00:00 -16003,615,67,24,21.0,17,,18,0.0,19,,,,5,1998-03-29 00:00:00 -16004,615,63,20,16.0,22,,17,0.0,26,,,,6,1998-03-29 00:00:00 -16005,615,73,17,23.0,19,,16,0.0,44,,,,37,1998-03-29 00:00:00 -16006,615,72,24,20.0,21,,15,0.0,52,,,,6,1998-03-29 00:00:00 -16007,615,21,23,18.0,13,,14,0.0,56,,,,6,1998-03-29 00:00:00 -16008,615,43,19,11.0,9,,13,0.0,63,,,,5,1998-03-29 00:00:00 -16009,615,70,16,9.0,11,,12,0.0,70,,,,2,1998-03-29 00:00:00 -16010,615,64,14,15.0,14,11.0,11,0.0,67,,,,82,1998-03-29 00:00:00 -16011,615,75,23,19.0,16,10.0,10,0.0,70,,,,12,1998-03-29 00:00:00 -16012,615,74,17,22.0,18,,21,0.0,3,,,,20,1998-03-29 00:00:00 -16013,615,55,5,4.0,6,8.0,8,0.0,71,,,,11,1998-03-29 00:00:00 -16014,615,22,16,10.0,8,,22,0.0,0,,,,20,1998-03-29 00:00:00 -16015,615,56,0,8.0,1,1.0,1,10.0,72,5832200.0,,,1,1998-03-29 00:00:00 -16016,615,13,0,7.0,2,2.0,2,6.0,72,5833302.0,,,1,1998-03-29 00:00:00 -16017,615,29,5,3.0,4,3.0,3,4.0,72,5892750.0,,,1,1998-03-29 00:00:00 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00:00:00 -16034,616,14,19,12.0,16,11.0,11,0.0,70,,,,12,1998-04-12 00:00:00 -16035,616,21,23,18.0,14,10.0,10,0.0,70,,,,12,1998-04-12 00:00:00 -16036,616,48,2,2.0,6,9.0,9,0.0,71,,,,11,1998-04-12 00:00:00 -16037,616,70,16,9.0,9,8.0,8,0.0,71,,,,11,1998-04-12 00:00:00 -16038,616,20,21,5.0,10,7.0,7,0.0,72,6604537.0,,,1,1998-04-12 00:00:00 -16039,616,13,0,7.0,1,6.0,6,1.0,72,6595851.0,,,1,1998-04-12 00:00:00 -16040,616,54,14,14.0,11,5.0,5,2.0,72,6594386.0,,,1,1998-04-12 00:00:00 -16041,616,24,21,6.0,8,4.0,4,3.0,72,6584234.0,,,1,1998-04-12 00:00:00 -16042,616,55,5,4.0,4,3.0,3,4.0,72,6573845.0,,,1,1998-04-12 00:00:00 -16043,616,67,24,21.0,13,12.0,12,0.0,70,,,,12,1998-04-12 00:00:00 -16044,616,29,5,3.0,2,1.0,1,10.0,72,6516100.0,,,1,1998-04-12 00:00:00 -16045,617,74,17,22.0,21,,15,0.0,27,,,,5,1998-04-26 00:00:00 -16046,617,63,20,16.0,18,,16,0.0,18,,,,5,1998-04-26 00:00:00 -16047,617,56,0,8.0,2,,17,0.0,17,,,,6,1998-04-26 00:00:00 -16048,617,20,21,5.0,10,,18,0.0,17,,,,20,1998-04-26 00:00:00 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-16094,619,43,19,11.0,18,,14,0.0,49,,,,36,1998-05-24 00:00:00 -16095,619,14,19,12.0,10,,13,0.0,56,,,,6,1998-05-24 00:00:00 -16096,619,54,14,14.0,11,12.0,12,0.0,72,,,,6,1998-05-24 00:00:00 -16097,619,73,17,23.0,21,,21,0.0,0,,,,20,1998-05-24 00:00:00 -16098,619,29,5,3.0,4,10.0,10,0.0,76,,,,12,1998-05-24 00:00:00 -16099,619,67,24,21.0,20,11.0,11,0.0,76,,,,12,1998-05-24 00:00:00 -16100,619,56,0,8.0,1,1.0,1,10.0,78,6684400.0,,,1,1998-05-24 00:00:00 -16101,619,20,21,5.0,3,2.0,2,6.0,78,6695875.0,,,1,1998-05-24 00:00:00 -16102,619,55,5,4.0,7,3.0,3,4.0,78,6725778.0,,,1,1998-05-24 00:00:00 -16103,619,62,20,17.0,8,4.0,4,3.0,78,6744763.0,,,1,1998-05-24 00:00:00 -16104,619,13,0,7.0,2,,18,0.0,17,,,,5,1998-05-24 00:00:00 -16105,619,63,20,16.0,12,6.0,6,1.0,77,,,,11,1998-05-24 00:00:00 -16106,619,64,14,15.0,9,7.0,7,0.0,77,,,,11,1998-05-24 00:00:00 -16107,619,70,16,9.0,15,8.0,8,0.0,76,,,,12,1998-05-24 00:00:00 -16108,619,74,17,22.0,19,9.0,9,0.0,76,,,,12,1998-05-24 00:00:00 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-16125,620,24,21,6.0,11,4.0,4,3.0,69,6120532.0,,,1,1998-06-07 00:00:00 -16126,620,55,5,4.0,8,3.0,3,4.0,69,6117359.0,,,1,1998-06-07 00:00:00 -16127,620,20,21,5.0,4,2.0,2,6.0,69,6073962.0,,,1,1998-06-07 00:00:00 -16128,620,29,5,3.0,3,1.0,1,10.0,69,6057300.0,,,1,1998-06-07 00:00:00 -16129,620,70,16,9.0,10,,12,0.0,42,,,,10,1998-06-07 00:00:00 -16130,620,74,17,22.0,18,7.0,7,0.0,68,,,,11,1998-06-07 00:00:00 -16131,620,13,0,7.0,1,,15,0.0,18,,,,37,1998-06-07 00:00:00 -16132,621,21,23,18.0,14,10.0,10,0.0,69,,,,12,1998-06-28 00:00:00 -16133,621,14,19,12.0,12,,19,0.0,55,,,,20,1998-06-28 00:00:00 -16134,621,73,17,23.0,22,,20,0.0,41,,,,6,1998-06-28 00:00:00 -16135,621,70,16,9.0,7,,21,0.0,19,,,,9,1998-06-28 00:00:00 -16136,621,72,24,20.0,18,,22,0.0,16,,,,9,1998-06-28 00:00:00 -16137,621,22,16,10.0,6,16.0,16,0.0,68,,,,13,1998-06-28 00:00:00 -16138,621,48,2,2.0,8,15.0,15,0.0,68,,,,22,1998-06-28 00:00:00 -16139,621,63,20,16.0,17,14.0,14,0.0,69,,,,12,1998-06-28 00:00:00 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-16155,622,62,20,17.0,13,,20,0.0,27,,,,37,1998-07-12 00:00:00 -16156,622,64,14,15.0,9,,19,0.0,27,,,,20,1998-07-12 00:00:00 -16157,622,67,24,21.0,17,9.0,9,0.0,56,,,,14,1998-07-12 00:00:00 -16158,622,56,0,8.0,1,2.0,2,6.0,60,6444865.0,,,1,1998-07-12 00:00:00 -16159,622,73,17,23.0,18,,18,0.0,29,,,,20,1998-07-12 00:00:00 -16160,622,29,5,3.0,2,1.0,1,10.0,60,6422400.0,,,1,1998-07-12 00:00:00 -16161,622,72,24,20.0,20,,17,0.0,29,,,,20,1998-07-12 00:00:00 -16162,622,14,19,12.0,14,,16,0.0,37,,,,20,1998-07-12 00:00:00 -16163,622,49,23,19.0,15,,14,0.0,38,,,,5,1998-07-12 00:00:00 -16164,622,21,23,18.0,16,,13,0.0,39,,,,20,1998-07-12 00:00:00 -16165,622,43,19,11.0,22,,12,0.0,40,,,,20,1998-07-12 00:00:00 -16166,622,63,20,16.0,12,,11,0.0,45,,,,20,1998-07-12 00:00:00 -16167,622,13,0,7.0,4,,15,0.0,37,,,,20,1998-07-12 00:00:00 -16168,622,48,2,2.0,6,,21,0.0,15,,,,20,1998-07-12 00:00:00 -16169,622,74,17,22.0,19,8.0,8,0.0,58,,,,12,1998-07-12 00:00:00 -16170,622,34,2,1.0,3,7.0,7,0.0,59,,,,11,1998-07-12 00:00:00 -16171,622,22,16,10.0,21,6.0,6,1.0,59,,,,11,1998-07-12 00:00:00 -16172,622,20,21,5.0,10,5.0,5,2.0,59,,,,11,1998-07-12 00:00:00 -16173,622,24,21,6.0,11,4.0,4,3.0,59,,,,11,1998-07-12 00:00:00 -16174,622,55,5,4.0,5,3.0,3,4.0,60,6451599.0,,,1,1998-07-12 00:00:00 -16175,622,54,14,14.0,8,,10,0.0,53,,,,10,1998-07-12 00:00:00 -16176,623,20,21,5.0,1,,15,0.0,21,,,,4,1998-07-26 00:00:00 -16177,623,54,14,14.0,2,,16,0.0,21,,,,4,1998-07-26 00:00:00 -16178,623,48,2,2.0,7,,17,0.0,16,,,,5,1998-07-26 00:00:00 -16179,623,43,19,11.0,10,,21,0.0,0,,,,8,1998-07-26 00:00:00 -16180,623,63,20,16.0,13,,19,0.0,3,,,,4,1998-07-26 00:00:00 -16181,623,62,20,17.0,6,,20,0.0,1,,,,4,1998-07-26 00:00:00 -16182,623,67,24,21.0,20,,22,0.0,0,,,,4,1998-07-26 00:00:00 -16183,623,73,17,23.0,19,,14,0.0,30,,,,20,1998-07-26 00:00:00 -16184,623,21,23,18.0,5,,18,0.0,8,,,,23,1998-07-26 00:00:00 -16185,623,49,23,19.0,12,,13,0.0,51,,,,5,1998-07-26 00:00:00 -16186,623,24,21,6.0,17,9.0,9,0.0,70,,,,11,1998-07-26 00:00:00 -16187,623,74,17,22.0,21,11.0,11,0.0,70,,,,11,1998-07-26 00:00:00 -16188,623,72,24,20.0,22,12.0,12,0.0,69,,,,12,1998-07-26 00:00:00 -16189,623,13,0,7.0,14,2.0,2,6.0,71,5449289.0,,,1,1998-07-26 00:00:00 -16190,623,29,5,3.0,4,3.0,3,4.0,71,5483092.0,,,1,1998-07-26 00:00:00 -16191,623,55,5,4.0,8,4.0,4,3.0,71,5487976.0,,,1,1998-07-26 00:00:00 -16192,623,56,0,8.0,3,1.0,1,10.0,71,5444000.0,,,1,1998-07-26 00:00:00 -16193,623,34,2,1.0,11,6.0,6,1.0,71,5497202.0,,,1,1998-07-26 00:00:00 -16194,623,70,16,9.0,15,7.0,7,0.0,71,5517624.0,,,1,1998-07-26 00:00:00 -16195,623,64,14,15.0,18,8.0,8,0.0,70,,,,11,1998-07-26 00:00:00 -16196,623,14,19,12.0,16,10.0,10,0.0,70,,,,11,1998-07-26 00:00:00 -16197,623,22,16,10.0,9,5.0,5,2.0,71,5494654.0,,,1,1998-07-26 00:00:00 -16198,624,63,20,16.0,18,,21,0.0,2,,,,37,1998-08-02 00:00:00 -16199,624,49,23,19.0,19,,20,0.0,24,,,,6,1998-08-02 00:00:00 -16200,624,21,23,18.0,13,,19,0.0,27,,,,6,1998-08-02 00:00:00 -16201,624,74,17,22.0,20,,18,0.0,36,,,,6,1998-08-02 00:00:00 -16202,624,64,14,15.0,12,,17,0.0,37,,,,6,1998-08-02 00:00:00 -16203,624,73,17,23.0,21,16.0,16,0.0,43,,,,12,1998-08-02 00:00:00 -16204,624,43,19,11.0,16,15.0,15,0.0,44,,,,11,1998-08-02 00:00:00 -16205,624,62,20,17.0,17,14.0,14,0.0,44,,,,11,1998-08-02 00:00:00 -16206,624,14,19,12.0,14,12.0,12,0.0,44,,,,11,1998-08-02 00:00:00 -16207,624,67,24,21.0,15,13.0,13,0.0,44,,,,11,1998-08-02 00:00:00 -16208,624,54,14,14.0,11,10.0,10,0.0,45,4896371.0,,,1,1998-08-02 00:00:00 -16209,624,56,0,8.0,1,1.0,1,10.0,45,4848000.0,,,1,1998-08-02 00:00:00 -16210,624,13,0,7.0,2,2.0,2,6.0,45,4848426.0,,,1,1998-08-02 00:00:00 -16211,624,34,2,1.0,3,3.0,3,4.0,45,4850577.0,,,1,1998-08-02 00:00:00 -16212,624,70,16,9.0,5,4.0,4,3.0,45,4855185.0,,,1,1998-08-02 00:00:00 -16213,624,24,21,6.0,7,11.0,11,0.0,45,4905994.0,,,1,1998-08-02 00:00:00 -16214,624,22,16,10.0,4,6.0,6,1.0,45,4877738.0,,,1,1998-08-02 00:00:00 -16215,624,20,21,5.0,8,7.0,7,0.0,45,4879026.0,,,1,1998-08-02 00:00:00 -16216,624,55,5,4.0,6,8.0,8,0.0,45,4879649.0,,,1,1998-08-02 00:00:00 -16217,624,48,2,2.0,10,9.0,9,0.0,45,4880784.0,,,1,1998-08-02 00:00:00 -16218,624,29,5,3.0,9,5.0,5,2.0,45,4860613.0,,,1,1998-08-02 00:00:00 -16219,625,67,24,21.0,18,14.0,14,0.0,74,,,,13,1998-08-16 00:00:00 -16220,625,73,17,23.0,21,,21,0.0,13,,,,5,1998-08-16 00:00:00 -16221,625,55,5,4.0,5,,20,0.0,13,,,,6,1998-08-16 00:00:00 -16222,625,62,20,17.0,13,,19,0.0,18,,,,6,1998-08-16 00:00:00 -16223,625,14,19,12.0,16,,18,0.0,28,,,,5,1998-08-16 00:00:00 -16224,625,21,23,18.0,14,,17,0.0,54,,,,6,1998-08-16 00:00:00 -16225,625,24,21,6.0,9,,16,0.0,69,,,,6,1998-08-16 00:00:00 -16226,625,74,17,22.0,19,15.0,15,0.0,74,,,,13,1998-08-16 00:00:00 -16227,625,49,23,19.0,17,13.0,13,0.0,74,,,,13,1998-08-16 00:00:00 -16228,625,48,2,2.0,7,5.0,5,2.0,77,6382910.0,,,1,1998-08-16 00:00:00 -16229,625,63,20,16.0,12,11.0,11,0.0,74,,,,13,1998-08-16 00:00:00 -16230,625,64,14,15.0,15,10.0,10,0.0,76,,,,11,1998-08-16 00:00:00 -16231,625,22,16,10.0,10,9.0,9,0.0,76,,,,11,1998-08-16 00:00:00 -16232,625,20,21,5.0,8,8.0,8,0.0,76,,,,11,1998-08-16 00:00:00 -16233,625,54,14,14.0,11,7.0,7,0.0,76,,,,11,1998-08-16 00:00:00 -16234,625,56,0,8.0,1,6.0,6,1.0,76,,,,11,1998-08-16 00:00:00 -16235,625,70,16,9.0,4,4.0,4,3.0,77,6381476.0,,,1,1998-08-16 00:00:00 -16236,625,34,2,1.0,6,3.0,3,4.0,77,6370844.0,,,1,1998-08-16 00:00:00 -16237,625,13,0,7.0,2,2.0,2,6.0,77,6335833.0,,,1,1998-08-16 00:00:00 -16238,625,29,5,3.0,3,1.0,1,10.0,77,6326400.0,,,1,1998-08-16 00:00:00 -16239,625,43,19,11.0,20,12.0,12,0.0,74,,,,13,1998-08-16 00:00:00 -16240,626,49,23,19.0,17,,15,0.0,8,,,,5,1998-08-30 00:00:00 -16241,626,56,0,8.0,1,,16,0.0,0,,,,4,1998-08-30 00:00:00 -16242,626,24,21,6.0,11,,17,0.0,0,,,,4,1998-08-30 00:00:00 -16243,626,72,24,20.0,20,,22,0.0,0,,,,4,1998-08-30 00:00:00 -16244,626,43,19,11.0,14,,20,0.0,0,,,,4,1998-08-30 00:00:00 -16245,626,62,20,17.0,18,,21,0.0,0,,,,4,1998-08-30 00:00:00 -16246,626,67,24,21.0,19,,14,0.0,10,,,,20,1998-08-30 00:00:00 -16247,626,64,14,15.0,12,,18,0.0,0,,,,4,1998-08-30 00:00:00 -16248,626,34,2,1.0,6,,13,0.0,16,,,,20,1998-08-30 00:00:00 -16249,626,21,23,18.0,15,,19,0.0,0,,,,4,1998-08-30 00:00:00 -16250,626,55,5,4.0,5,,11,0.0,25,,,,20,1998-08-30 00:00:00 -16251,626,73,17,23.0,22,,12,0.0,17,,,,6,1998-08-30 00:00:00 -16252,626,70,16,9.0,3,1.0,1,10.0,44,6227407.0,,,1,1998-08-30 00:00:00 -16253,626,22,16,10.0,8,2.0,2,6.0,44,6228339.0,,,1,1998-08-30 00:00:00 -16254,626,54,14,14.0,10,3.0,3,4.0,44,6234647.0,,,1,1998-08-30 00:00:00 -16255,626,48,2,2.0,9,4.0,4,3.0,44,6259650.0,,,1,1998-08-30 00:00:00 -16256,626,20,21,5.0,7,,9,0.0,26,,,,4,1998-08-30 00:00:00 -16257,626,14,19,12.0,13,6.0,6,1.0,42,,,,12,1998-08-30 00:00:00 -16258,626,13,0,7.0,2,7.0,7,0.0,39,,,,15,1998-08-30 00:00:00 -16259,626,74,17,22.0,21,8.0,8,0.0,39,,,,15,1998-08-30 00:00:00 -16260,626,29,5,3.0,4,,10,0.0,25,,,,4,1998-08-30 00:00:00 -16261,626,63,20,16.0,16,5.0,5,2.0,44,6279089.0,,,1,1998-08-30 00:00:00 -16262,627,63,20,16.0,20,,22,0.0,10,,,,20,1998-09-13 00:00:00 -16263,627,64,14,15.0,15,,21,0.0,12,,,,20,1998-09-13 00:00:00 -16264,627,74,17,22.0,21,,20,0.0,13,,,,5,1998-09-13 00:00:00 -16265,627,43,19,11.0,9,,19,0.0,15,,,,76,1998-09-13 00:00:00 -16266,627,13,0,7.0,4,,18,0.0,16,,,,5,1998-09-13 00:00:00 -16267,627,24,21,6.0,7,,17,0.0,24,,,,6,1998-09-13 00:00:00 -16268,627,62,20,17.0,16,,16,0.0,32,,,,37,1998-09-13 00:00:00 -16269,627,34,2,1.0,2,,15,0.0,37,,,,20,1998-09-13 00:00:00 -16270,627,49,23,19.0,17,,14,0.0,39,,,,6,1998-09-13 00:00:00 -16271,627,14,19,12.0,10,13.0,13,0.0,50,,,,13,1998-09-13 00:00:00 -16272,627,73,17,23.0,22,11.0,11,0.0,51,,,,12,1998-09-13 00:00:00 -16273,627,21,23,18.0,13,10.0,10,0.0,52,,,,11,1998-09-13 00:00:00 -16274,627,67,24,21.0,19,9.0,9,0.0,52,,,,11,1998-09-13 00:00:00 -16275,627,48,2,2.0,12,7.0,7,0.0,52,,,,11,1998-09-13 00:00:00 -16276,627,70,16,9.0,14,6.0,6,1.0,53,4696988.0,,,1,1998-09-13 00:00:00 -16277,627,54,14,14.0,8,5.0,5,2.0,53,4692172.0,,,1,1998-09-13 00:00:00 -16278,627,56,0,8.0,3,4.0,4,3.0,53,4685971.0,,,1,1998-09-13 00:00:00 -16279,627,22,16,10.0,6,3.0,3,4.0,53,4671452.0,,,1,1998-09-13 00:00:00 -16280,627,55,5,4.0,5,2.0,2,6.0,53,4668277.0,,,1,1998-09-13 00:00:00 -16281,627,29,5,3.0,1,1.0,1,10.0,53,4630300.0,,,1,1998-09-13 00:00:00 -16282,627,72,24,20.0,18,12.0,12,0.0,51,,,,12,1998-09-13 00:00:00 -16283,627,20,21,5.0,11,8.0,8,0.0,52,,,,11,1998-09-13 00:00:00 -16284,628,14,19,12.0,14,,21,0.0,6,,,,7,1998-09-27 00:00:00 -16285,628,72,24,20.0,22,,20,0.0,36,,,,5,1998-09-27 00:00:00 -16286,628,56,0,8.0,3,1.0,1,10.0,67,5534789.0,,,1,1998-09-27 00:00:00 -16287,628,63,20,16.0,17,,22,0.0,6,,,,9,1998-09-27 00:00:00 -16288,628,64,14,15.0,13,,19,0.0,37,,,,5,1998-09-27 00:00:00 -16289,628,22,16,10.0,6,,18,0.0,53,,,,23,1998-09-27 00:00:00 -16290,628,73,17,23.0,21,,17,0.0,56,,,,5,1998-09-27 00:00:00 -16291,628,67,24,21.0,19,16.0,16,0.0,65,,,,12,1998-09-27 00:00:00 -16292,628,62,20,17.0,16,14.0,14,0.0,65,,,,12,1998-09-27 00:00:00 -16293,628,49,23,19.0,18,13.0,13,0.0,65,,,,12,1998-09-27 00:00:00 -16294,628,43,19,11.0,15,12.0,12,0.0,65,,,,12,1998-09-27 00:00:00 -16295,628,21,23,18.0,12,11.0,11,0.0,65,,,,12,1998-09-27 00:00:00 -16296,628,74,17,22.0,20,15.0,15,0.0,65,,,,12,1998-09-27 00:00:00 -16297,628,70,16,9.0,10,9.0,9,0.0,66,,,,11,1998-09-27 00:00:00 -16298,628,54,14,14.0,11,10.0,10,0.0,66,,,,11,1998-09-27 00:00:00 -16299,628,13,0,7.0,5,3.0,3,4.0,67,5568952.0,,,1,1998-09-27 00:00:00 -16300,628,55,5,4.0,2,4.0,4,3.0,67,5592971.0,,,1,1998-09-27 00:00:00 -16301,628,48,2,2.0,7,5.0,5,2.0,67,5595036.0,,,1,1998-09-27 00:00:00 -16302,628,29,5,3.0,1,2.0,2,6.0,67,5537000.0,,,1,1998-09-27 00:00:00 -16303,628,24,21,6.0,8,7.0,7,0.0,67,5599578.0,,,1,1998-09-27 00:00:00 -16304,628,34,2,1.0,9,8.0,8,0.0,66,,,,11,1998-09-27 00:00:00 -16305,628,20,21,5.0,4,6.0,6,1.0,67,5596148.0,,,1,1998-09-27 00:00:00 -16306,629,29,5,3.0,1,,14,0.0,31,,,,27,1998-11-01 00:00:00 -16307,629,72,24,20.0,0,,22,0.0,0,,,,81,1998-11-01 00:00:00 -16308,629,63,20,16.0,18,,21,0.0,2,,,,20,1998-11-01 00:00:00 -16309,629,62,20,17.0,15,,19,0.0,14,,,,9,1998-11-01 00:00:00 -16310,629,49,23,19.0,19,,18,0.0,21,,,,6,1998-11-01 00:00:00 -16311,629,21,23,18.0,16,,17,0.0,25,,,,9,1998-11-01 00:00:00 -16312,629,73,17,23.0,21,,16,0.0,28,,,,4,1998-11-01 00:00:00 -16313,629,67,24,21.0,17,,15,0.0,28,,,,4,1998-11-01 00:00:00 -16314,629,74,17,22.0,20,,13,0.0,40,,,,37,1998-11-01 00:00:00 -16315,629,22,16,10.0,7,,20,0.0,13,,,,5,1998-11-01 00:00:00 -16316,629,43,19,11.0,13,11.0,11,0.0,50,,,,11,1998-11-01 00:00:00 -16317,629,55,5,4.0,4,2.0,2,6.0,51,5249891.0,,,1,1998-11-01 00:00:00 -16318,629,13,0,7.0,3,3.0,3,4.0,51,5271062.0,,,1,1998-11-01 00:00:00 -16319,629,70,16,9.0,8,4.0,4,3.0,51,5316891.0,,,1,1998-11-01 00:00:00 -16320,629,48,2,2.0,5,5.0,5,2.0,51,5317257.0,,,1,1998-11-01 00:00:00 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-16336,630,14,19,19.0,12,,14,0.0,25,,,,4,1999-03-07 00:00:00 -16337,630,47,17,21.0,22,,13,0.0,25,,,,4,1999-03-07 00:00:00 -16338,630,34,15,22.0,11,,19,0.0,13,,,,65,1999-03-07 00:00:00 -16339,630,24,21,10.0,10,,11,0.0,28,,,,22,1999-03-07 00:00:00 -16340,630,40,15,23.0,19,,9,0.0,48,,,,6,1999-03-07 00:00:00 -16341,630,29,5,3.0,3,8.0,8,0.0,56,,,,11,1999-03-07 00:00:00 -16342,630,67,20,15.0,17,7.0,7,0.0,57,5787947.0,,,1,1999-03-07 00:00:00 -16343,630,36,20,14.0,18,6.0,6,1.0,57,5785976.0,,,1,1999-03-07 00:00:00 -16344,630,21,23,16.0,4,5.0,5,2.0,57,5756357.0,,,1,1999-03-07 00:00:00 -16345,630,20,21,9.0,7,4.0,4,3.0,57,5735077.0,,,1,1999-03-07 00:00:00 -16346,630,22,2,6.0,8,3.0,3,4.0,57,5708671.0,,,1,1999-03-07 00:00:00 -16347,630,48,16,8.0,5,2.0,2,6.0,57,5702686.0,,,1,1999-03-07 00:00:00 -16348,630,55,5,4.0,6,1.0,1,10.0,57,5701659.0,,,1,1999-03-07 00:00:00 -16349,630,68,17,20.0,21,,10,0.0,42,,,,6,1999-03-07 00:00:00 -16350,631,63,14,12.0,15,,14,0.0,42,,,,4,1999-04-11 00:00:00 -16351,631,20,21,9.0,5,,15,0.0,38,,,,8,1999-04-11 00:00:00 -16352,631,71,17,20.0,18,,16,0.0,31,,,,20,1999-04-11 00:00:00 -16353,631,54,14,11.0,14,,17,0.0,27,,,,6,1999-04-11 00:00:00 -16354,631,40,15,23.0,0,,22,0.0,0,,,,81,1999-04-11 00:00:00 -16355,631,14,19,19.0,13,,19,0.0,21,,,,6,1999-04-11 00:00:00 -16356,631,64,23,17.0,10,,20,0.0,15,,,,9,1999-04-11 00:00:00 -16357,631,70,16,7.0,7,,21,0.0,10,,,,4,1999-04-11 00:00:00 -16358,631,21,23,16.0,3,,13,0.0,42,,,,5,1999-04-11 00:00:00 -16359,631,13,0,2.0,2,,18,0.0,22,,,,6,1999-04-11 00:00:00 -16360,631,69,2,5.0,16,,12,0.0,43,,,,6,1999-04-11 00:00:00 -16361,631,56,0,1.0,1,1.0,1,10.0,72,5763785.0,,,1,1999-04-11 00:00:00 -16362,631,36,20,14.0,17,,10,0.0,52,,,,9,1999-04-11 00:00:00 -16363,631,47,17,21.0,20,9.0,9,0.0,69,,,,13,1999-04-11 00:00:00 -16364,631,67,20,15.0,19,8.0,8,0.0,69,,,,13,1999-04-11 00:00:00 -16365,631,24,21,10.0,9,7.0,7,0.0,70,,,,12,1999-04-11 00:00:00 -16366,631,43,19,18.0,12,6.0,6,1.0,71,,,,11,1999-04-11 00:00:00 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-16398,633,67,20,15.0,19,,16,0.0,36,,,,5,1999-05-16 00:00:00 -16399,633,62,15,23.0,12,,15,0.0,36,,,,23,1999-05-16 00:00:00 -16400,633,13,0,2.0,3,,14,0.0,36,,,,6,1999-05-16 00:00:00 -16401,633,43,19,18.0,18,,13,0.0,40,,,,5,1999-05-16 00:00:00 -16402,633,54,14,11.0,14,,11,0.0,50,,,,22,1999-05-16 00:00:00 -16403,633,20,21,9.0,9,5.0,5,2.0,77,,,,11,1999-05-16 00:00:00 -16404,633,21,23,16.0,5,9.0,9,0.0,71,,,,20,1999-05-16 00:00:00 -16405,633,69,2,5.0,11,8.0,8,0.0,76,,,,12,1999-05-16 00:00:00 -16406,633,14,19,19.0,7,7.0,7,0.0,77,,,,11,1999-05-16 00:00:00 -16407,633,24,21,10.0,10,6.0,6,1.0,77,,,,11,1999-05-16 00:00:00 -16408,633,48,16,8.0,6,4.0,4,3.0,78,6625821.0,,,1,1999-05-16 00:00:00 -16409,633,56,0,1.0,1,3.0,3,4.0,78,6609295.0,,,1,1999-05-16 00:00:00 -16410,633,55,5,4.0,4,2.0,2,6.0,78,6602288.0,,,1,1999-05-16 00:00:00 -16411,633,29,5,3.0,2,1.0,1,10.0,78,6571812.0,,,1,1999-05-16 00:00:00 -16412,633,68,17,20.0,20,,21,0.0,10,,,,6,1999-05-16 00:00:00 -16413,633,22,2,6.0,16,,10,0.0,54,,,,20,1999-05-16 00:00:00 -16414,633,70,16,7.0,17,,22,0.0,3,,,,4,1999-05-16 00:00:00 -16415,633,47,17,21.0,22,,20,0.0,24,,,,20,1999-05-16 00:00:00 -16416,634,69,2,5.0,17,,19,0.0,24,,,,6,1999-05-30 00:00:00 -16417,634,54,14,11.0,5,,18,0.0,27,,,,7,1999-05-30 00:00:00 -16418,634,48,16,8.0,8,,17,0.0,35,,,,86,1999-05-30 00:00:00 -16419,634,64,23,17.0,14,,16,0.0,40,,,,7,1999-05-30 00:00:00 -16420,634,63,14,12.0,12,,15,0.0,40,,,,7,1999-05-30 00:00:00 -16421,634,34,15,22.0,6,,14,0.0,40,,,,6,1999-05-30 00:00:00 -16422,634,68,17,20.0,22,,13,0.0,50,,,,20,1999-05-30 00:00:00 -16423,634,67,20,15.0,20,12.0,12,0.0,62,,,,13,1999-05-30 00:00:00 -16424,634,36,20,14.0,19,11.0,11,0.0,63,,,,12,1999-05-30 00:00:00 -16425,634,24,21,10.0,18,10.0,10,0.0,64,,,,11,1999-05-30 00:00:00 -16426,634,20,21,9.0,13,9.0,9,0.0,64,,,,11,1999-05-30 00:00:00 -16427,634,43,19,18.0,15,,20,0.0,24,,,,6,1999-05-30 00:00:00 -16428,634,70,16,7.0,11,7.0,7,0.0,64,,,,11,1999-05-30 00:00:00 -16429,634,14,19,19.0,9,6.0,6,1.0,64,,,,11,1999-05-30 00:00:00 -16430,634,22,2,6.0,10,5.0,5,2.0,65,5740873.0,,,1,1999-05-30 00:00:00 -16431,634,55,5,4.0,2,4.0,4,3.0,65,5683847.0,,,1,1999-05-30 00:00:00 -16432,634,29,5,3.0,4,3.0,3,4.0,65,5664510.0,,,1,1999-05-30 00:00:00 -16433,634,13,0,2.0,3,2.0,2,6.0,65,5659903.0,,,1,1999-05-30 00:00:00 -16434,634,56,0,1.0,1,1.0,1,10.0,65,5653665.0,,,1,1999-05-30 00:00:00 -16435,634,21,23,16.0,7,,22,0.0,64,,,,2,1999-05-30 00:00:00 -16436,634,47,17,21.0,21,,21,0.0,0,,,,6,1999-05-30 00:00:00 -16437,634,62,15,23.0,16,8.0,8,0.0,64,,,,11,1999-05-30 00:00:00 -16438,635,29,5,3.0,1,,15,0.0,29,,,,20,1999-06-13 00:00:00 -16439,635,36,20,14.0,20,,16,0.0,22,,,,7,1999-06-13 00:00:00 -16440,635,70,16,7.0,14,,17,0.0,14,,,,20,1999-06-13 00:00:00 -16441,635,24,21,10.0,11,,22,0.0,0,,,,7,1999-06-13 00:00:00 -16442,635,54,14,11.0,8,,20,0.0,0,,,,4,1999-06-13 00:00:00 -16443,635,14,19,19.0,9,,21,0.0,0,,,,4,1999-06-13 00:00:00 -16444,635,34,15,22.0,16,,14,0.0,34,,,,20,1999-06-13 00:00:00 -16445,635,21,23,16.0,5,,18,0.0,14,,,,38,1999-06-13 00:00:00 -16446,635,69,2,5.0,12,,12,0.0,50,,,,23,1999-06-13 00:00:00 -16447,635,40,15,23.0,17,,19,0.0,2,,,,20,1999-06-13 00:00:00 -16448,635,67,20,15.0,19,,13,0.0,41,,,,7,1999-06-13 00:00:00 -16449,635,68,17,20.0,21,10.0,10,0.0,67,,,,12,1999-06-13 00:00:00 -16450,635,43,19,18.0,15,9.0,9,0.0,68,,,,11,1999-06-13 00:00:00 -16451,635,47,17,21.0,22,8.0,8,0.0,68,,,,11,1999-06-13 00:00:00 -16452,635,13,0,2.0,4,7.0,7,0.0,69,6100731.0,,,1,1999-06-13 00:00:00 -16453,635,63,14,12.0,18,6.0,6,1.0,69,6099438.0,,,1,1999-06-13 00:00:00 -16454,635,64,23,17.0,10,5.0,5,2.0,69,6098532.0,,,1,1999-06-13 00:00:00 -16455,635,22,2,6.0,13,4.0,4,3.0,69,6098119.0,,,1,1999-06-13 00:00:00 -16456,635,55,5,4.0,3,3.0,3,4.0,69,6097524.0,,,1,1999-06-13 00:00:00 -16457,635,20,21,9.0,7,2.0,2,6.0,69,6096509.0,,,1,1999-06-13 00:00:00 -16458,635,48,16,8.0,6,11.0,11,0.0,65,,,,23,1999-06-13 00:00:00 -16459,635,56,0,1.0,2,1.0,1,10.0,69,6095727.0,,,1,1999-06-13 00:00:00 -16460,636,69,2,5.0,15,,14,0.0,26,,,,5,1999-06-27 00:00:00 -16461,636,34,15,22.0,12,,15,0.0,25,,,,20,1999-06-27 00:00:00 -16462,636,64,23,17.0,9,,21,0.0,4,,,,6,1999-06-27 00:00:00 -16463,636,54,14,11.0,2,,18,0.0,24,,,,20,1999-06-27 00:00:00 -16464,636,13,0,2.0,4,,19,0.0,9,,,,10,1999-06-27 00:00:00 -16465,636,63,14,12.0,11,,20,0.0,6,,,,7,1999-06-27 00:00:00 -16466,636,70,16,7.0,18,,13,0.0,31,,,,10,1999-06-27 00:00:00 -16467,636,47,17,21.0,19,,17,0.0,25,,,,20,1999-06-27 00:00:00 -16468,636,20,21,9.0,7,,12,0.0,42,,,,20,1999-06-27 00:00:00 -16469,636,67,20,15.0,22,,22,0.0,71,,,,2,1999-06-27 00:00:00 -16470,636,68,17,20.0,20,10.0,10,0.0,71,,,,11,1999-06-27 00:00:00 -16471,636,40,15,23.0,10,9.0,9,0.0,72,7193107.0,,,1,1999-06-27 00:00:00 -16472,636,43,19,18.0,3,8.0,8,0.0,72,7162874.0,,,1,1999-06-27 00:00:00 -16473,636,55,5,4.0,17,6.0,6,1.0,72,7153244.0,,,1,1999-06-27 00:00:00 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00:00:00 -16519,638,70,16,7.0,11,8.0,8,0.0,70,,,,11,1999-07-25 00:00:00 -16520,638,14,19,19.0,13,7.0,7,0.0,70,,,,11,1999-07-25 00:00:00 -16521,638,63,14,12.0,16,6.0,6,1.0,71,5363371.0,,,1,1999-07-25 00:00:00 -16522,638,24,21,10.0,10,5.0,5,2.0,71,5358796.0,,,1,1999-07-25 00:00:00 -16523,638,56,0,1.0,1,3.0,3,4.0,71,5314720.0,,,1,1999-07-25 00:00:00 -16524,638,47,17,21.0,22,11.0,11,0.0,70,,,,11,1999-07-25 00:00:00 -16525,638,48,16,8.0,4,4.0,4,3.0,71,5345241.0,,,1,1999-07-25 00:00:00 -16526,639,40,15,23.0,18,,15,0.0,20,,,,5,1999-08-01 00:00:00 -16527,639,70,16,7.0,8,,17,0.0,13,,,,23,1999-08-01 00:00:00 -16528,639,14,19,19.0,9,,18,0.0,10,,,,5,1999-08-01 00:00:00 -16529,639,34,15,22.0,12,,21,0.0,0,,,,4,1999-08-01 00:00:00 -16530,639,21,23,16.0,6,,20,0.0,6,,,,9,1999-08-01 00:00:00 -16531,639,63,14,12.0,16,,22,0.0,0,,,,4,1999-08-01 00:00:00 -16532,639,69,2,5.0,14,,14,0.0,21,,,,24,1999-08-01 00:00:00 -16533,639,20,21,9.0,10,,19,0.0,7,,,,22,1999-08-01 00:00:00 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00:00:00 -16549,640,63,14,12.0,12,,21,0.0,19,,,,20,1999-08-15 00:00:00 -16550,640,67,20,15.0,21,,20,0.0,26,,,,7,1999-08-15 00:00:00 -16551,640,20,21,9.0,4,,19,0.0,52,,,,5,1999-08-15 00:00:00 -16552,640,34,15,22.0,9,,18,0.0,60,,,,8,1999-08-15 00:00:00 -16553,640,47,17,21.0,22,17.0,17,0.0,74,,,,13,1999-08-15 00:00:00 -16554,640,54,14,11.0,11,16.0,16,0.0,74,,,,32,1999-08-15 00:00:00 -16555,640,36,20,14.0,20,15.0,15,0.0,75,,,,12,1999-08-15 00:00:00 -16556,640,68,17,20.0,19,14.0,14,0.0,75,,,,12,1999-08-15 00:00:00 -16557,640,40,15,23.0,17,13.0,13,0.0,75,,,,12,1999-08-15 00:00:00 -16558,640,62,5,3.0,18,12.0,12,0.0,75,,,,12,1999-08-15 00:00:00 -16559,640,43,19,18.0,14,10.0,10,0.0,76,,,,11,1999-08-15 00:00:00 -16560,640,22,2,6.0,16,9.0,9,0.0,76,,,,11,1999-08-15 00:00:00 -16561,640,24,21,10.0,7,7.0,7,0.0,77,6444548.0,,,1,1999-08-15 00:00:00 -16562,640,70,16,7.0,6,6.0,6,1.0,77,6439262.0,,,1,1999-08-15 00:00:00 -16563,640,21,23,16.0,8,5.0,5,2.0,77,6427344.0,,,1,1999-08-15 00:00:00 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-16789,650,48,16,5.0,8,6.0,6,1.0,65,5717315.0,,,1,2000-05-07 00:00:00 -16790,651,40,15,23.0,18,,13,0.0,51,,,,20,2000-05-21 00:00:00 -16791,651,14,16,6.0,6,,21,0.0,0,,,,4,2000-05-21 00:00:00 -16792,651,48,16,5.0,10,,20,0.0,2,,,,5,2000-05-21 00:00:00 -16793,651,62,14,17.0,19,,19,0.0,27,,,,86,2000-05-21 00:00:00 -16794,651,22,2,9.0,5,,18,0.0,29,,,,4,2000-05-21 00:00:00 -16795,651,49,20,19.0,13,,17,0.0,29,,,,20,2000-05-21 00:00:00 -16796,651,55,18,7.0,8,,16,0.0,29,,,,4,2000-05-21 00:00:00 -16797,651,34,15,22.0,9,,15,0.0,46,,,,5,2000-05-21 00:00:00 -16798,651,47,17,20.0,20,,14,0.0,47,,,,37,2000-05-21 00:00:00 -16799,651,24,21,12.0,14,12.0,12,0.0,61,,,,4,2000-05-21 00:00:00 -16800,651,64,18,8.0,16,11.0,11,0.0,61,,,,4,2000-05-21 00:00:00 -16801,651,17,2,10.0,11,10.0,10,0.0,62,,,,10,2000-05-21 00:00:00 -16802,651,56,0,1.0,3,2.0,2,6.0,67,6134129.0,,,1,2000-05-21 00:00:00 -16803,651,13,0,2.0,1,3.0,3,4.0,66,,,,11,2000-05-21 00:00:00 -16804,651,21,5,4.0,4,4.0,4,3.0,66,,,,11,2000-05-21 00:00:00 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-16955,658,55,18,7.0,12,10.0,10,0.0,44,5386049.0,,,1,2000-08-27 00:00:00 -16956,658,56,0,1.0,1,1.0,1,10.0,44,5294494.0,,,1,2000-08-27 00:00:00 -16957,658,29,5,3.0,4,2.0,2,6.0,44,5295598.0,,,1,2000-08-27 00:00:00 -16958,658,22,2,9.0,6,3.0,3,4.0,44,5332590.0,,,1,2000-08-27 00:00:00 -16959,658,13,0,2.0,5,4.0,4,3.0,44,5337775.0,,,1,2000-08-27 00:00:00 -16960,658,63,14,16.0,15,11.0,11,0.0,44,5388617.0,,,1,2000-08-27 00:00:00 -16961,658,34,15,22.0,7,7.0,7,0.0,44,5366874.0,,,1,2000-08-27 00:00:00 -16962,658,64,18,8.0,9,8.0,8,0.0,44,5382302.0,,,1,2000-08-27 00:00:00 -16963,658,62,14,17.0,18,9.0,9,0.0,44,5383164.0,,,1,2000-08-27 00:00:00 -16964,658,17,2,10.0,3,5.0,5,2.0,44,5344408.0,,,1,2000-08-27 00:00:00 -16965,659,55,18,7.0,14,,22,0.0,0,,,,20,2000-09-10 00:00:00 -16966,659,54,19,14.0,19,12.0,12,0.0,51,,,,12,2000-09-10 00:00:00 -16967,659,48,16,5.0,8,,20,0.0,0,,,,4,2000-09-10 00:00:00 -16968,659,14,16,6.0,6,,19,0.0,0,,,,4,2000-09-10 00:00:00 -16969,659,13,0,2.0,5,,18,0.0,0,,,,4,2000-09-10 00:00:00 -16970,659,21,5,4.0,2,,17,0.0,0,,,,4,2000-09-10 00:00:00 -16971,659,64,18,8.0,18,,16,0.0,1,,,,4,2000-09-10 00:00:00 -16972,659,17,2,10.0,12,,15,0.0,10,,,,20,2000-09-10 00:00:00 -16973,659,34,15,22.0,4,,14,0.0,14,,,,10,2000-09-10 00:00:00 -16974,659,1,19,15.0,20,,13,0.0,15,,,,20,2000-09-10 00:00:00 -16975,659,36,20,18.0,10,,21,0.0,0,,,,4,2000-09-10 00:00:00 -16976,659,20,21,11.0,9,11.0,11,0.0,52,,,,11,2000-09-10 00:00:00 -16977,659,47,17,20.0,21,9.0,9,0.0,52,,,,11,2000-09-10 00:00:00 -16978,659,63,14,16.0,16,8.0,8,0.0,52,,,,11,2000-09-10 00:00:00 -16979,659,62,14,17.0,15,7.0,7,0.0,52,,,,11,2000-09-10 00:00:00 -16980,659,40,15,23.0,17,6.0,6,1.0,53,5320931.0,,,1,2000-09-10 00:00:00 -16981,659,24,21,12.0,13,5.0,5,2.0,53,5319064.0,,,1,2000-09-10 00:00:00 -16982,659,49,20,19.0,11,4.0,4,3.0,53,5311576.0,,,1,2000-09-10 00:00:00 -16983,659,22,2,9.0,7,3.0,3,4.0,53,5304070.0,,,1,2000-09-10 00:00:00 -16984,659,56,0,1.0,3,2.0,2,6.0,53,5255448.0,,,1,2000-09-10 00:00:00 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00:00:00 -17001,660,34,15,22.0,8,4.0,4,3.0,73,5808819.0,,,1,2000-09-24 00:00:00 -17002,660,13,0,2.0,2,5.0,5,2.0,73,5819696.0,,,1,2000-09-24 00:00:00 -17003,660,29,5,3.0,1,1.0,1,10.0,73,5790883.0,,,1,2000-09-24 00:00:00 -17004,660,40,15,23.0,12,6.0,6,1.0,73,5842577.0,,,1,2000-09-24 00:00:00 -17005,660,55,18,7.0,17,7.0,7,0.0,73,5861998.0,,,1,2000-09-24 00:00:00 -17006,660,63,14,16.0,9,8.0,8,0.0,72,,,,11,2000-09-24 00:00:00 -17007,660,1,19,15.0,16,9.0,9,0.0,72,,,,11,2000-09-24 00:00:00 -17008,660,64,18,8.0,19,11.0,11,0.0,72,,,,11,2000-09-24 00:00:00 -17009,661,14,16,6.0,15,13.0,13,0.0,52,,,,11,2000-10-08 00:00:00 -17010,661,49,20,19.0,14,,22,0.0,9,,,,10,2000-10-08 00:00:00 -17011,661,54,19,14.0,17,,21,0.0,19,,,,5,2000-10-08 00:00:00 -17012,661,48,16,5.0,8,,20,0.0,29,,,,9,2000-10-08 00:00:00 -17013,661,24,21,12.0,11,,19,0.0,37,,,,20,2000-10-08 00:00:00 -17014,661,1,19,15.0,16,,18,0.0,41,,,,22,2000-10-08 00:00:00 -17015,661,22,2,9.0,6,,17,0.0,41,,,,20,2000-10-08 00:00:00 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00:00:00 -17076,664,43,15,9.0,10,,21,0.0,1,,,,44,2001-03-18 00:00:00 -17077,664,55,18,18.0,12,,20,0.0,3,,,,47,2001-03-18 00:00:00 -17078,664,30,2,6.0,6,,19,0.0,3,,,,20,2001-03-18 00:00:00 -17079,664,58,20,15.0,22,,18,0.0,3,,,,20,2001-03-18 00:00:00 -17080,664,1,14,16.0,11,,17,0.0,3,,,,20,2001-03-18 00:00:00 -17081,664,34,15,10.0,7,,16,0.0,3,,,,20,2001-03-18 00:00:00 -17082,664,20,21,7.0,16,,15,0.0,31,,,,32,2001-03-18 00:00:00 -17083,664,57,17,20.0,20,14.0,14,0.0,51,,,,14,2001-03-18 00:00:00 -17084,664,3,17,21.0,21,13.0,13,0.0,52,,,,13,2001-03-18 00:00:00 -17085,664,7,14,17.0,14,,22,0.0,0,,,,30,2001-03-18 00:00:00 -17086,664,17,21,8.0,17,11.0,11,0.0,53,,,,12,2001-03-18 00:00:00 -17087,664,54,19,22.0,13,9.0,9,0.0,54,,,,11,2001-03-18 00:00:00 -17088,664,14,16,12.0,5,8.0,8,0.0,54,,,,11,2001-03-18 00:00:00 -17089,664,49,20,14.0,18,7.0,7,0.0,55,6536361.0,,,1,2001-03-18 00:00:00 -17090,664,56,0,3.0,4,6.0,6,1.0,55,6503407.0,,,1,2001-03-18 00:00:00 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00:00:00 -17122,666,7,14,17.0,10,,20,0.0,17,,,,38,2001-04-15 00:00:00 -17123,666,29,5,1.0,4,,19,0.0,24,,,,22,2001-04-15 00:00:00 -17124,666,59,19,23.0,20,,18,0.0,28,,,,5,2001-04-15 00:00:00 -17125,666,34,15,10.0,11,,17,0.0,30,,,,5,2001-04-15 00:00:00 -17126,666,20,21,7.0,19,,16,0.0,31,,,,5,2001-04-15 00:00:00 -17127,666,55,18,18.0,13,,15,0.0,42,,,,5,2001-04-15 00:00:00 -17128,666,57,17,20.0,22,,13,0.0,50,,,,5,2001-04-15 00:00:00 -17129,666,13,0,4.0,1,2.0,2,6.0,62,5449169.0,,,1,2001-04-15 00:00:00 -17130,666,53,18,19.0,15,11.0,11,0.0,60,,,,12,2001-04-15 00:00:00 -17131,666,58,20,15.0,16,10.0,10,0.0,60,,,,12,2001-04-15 00:00:00 -17132,666,54,19,22.0,14,9.0,9,0.0,61,,,,11,2001-04-15 00:00:00 -17133,666,43,15,9.0,8,8.0,8,0.0,61,,,,11,2001-04-15 00:00:00 -17134,666,1,14,16.0,12,7.0,7,0.0,61,,,,11,2001-04-15 00:00:00 -17135,666,48,16,11.0,9,6.0,6,1.0,61,,,,11,2001-04-15 00:00:00 -17136,666,14,16,12.0,5,5.0,5,2.0,62,5530375.0,,,1,2001-04-15 00:00:00 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-17167,668,30,2,6.0,2,,14,0.0,41,,,,9,2001-05-13 00:00:00 -17168,668,20,21,7.0,19,,20,0.0,3,,,,5,2001-05-13 00:00:00 -17169,668,56,0,3.0,8,,21,0.0,1,,,,7,2001-05-13 00:00:00 -17170,668,48,16,11.0,11,,22,0.0,0,,,,6,2001-05-13 00:00:00 -17171,668,22,2,5.0,3,,19,0.0,10,,,,23,2001-05-13 00:00:00 -17172,668,36,18,19.0,14,,13,0.0,48,,,,7,2001-05-13 00:00:00 -17173,668,17,21,8.0,21,,12,0.0,60,,,,5,2001-05-13 00:00:00 -17174,668,53,19,23.0,17,11.0,11,0.0,69,,,,12,2001-05-13 00:00:00 -17175,668,29,5,1.0,1,2.0,2,6.0,71,5268117.0,,,1,2001-05-13 00:00:00 -17176,668,21,5,2.0,4,3.0,3,4.0,71,5268454.0,,,1,2001-05-13 00:00:00 -17177,668,7,14,17.0,9,4.0,4,3.0,71,5307520.0,,,1,2001-05-13 00:00:00 -17178,668,43,15,9.0,10,5.0,5,2.0,71,5319702.0,,,1,2001-05-13 00:00:00 -17179,668,13,0,4.0,7,1.0,1,10.0,71,5265927.0,,,1,2001-05-13 00:00:00 -17180,668,55,18,18.0,13,7.0,7,0.0,70,,,,11,2001-05-13 00:00:00 -17181,668,34,15,10.0,12,8.0,8,0.0,70,,,,11,2001-05-13 00:00:00 -17182,668,1,14,16.0,6,9.0,9,0.0,69,,,,12,2001-05-13 00:00:00 -17183,668,54,19,22.0,20,10.0,10,0.0,69,,,,12,2001-05-13 00:00:00 -17184,668,49,20,14.0,16,6.0,6,1.0,70,,,,11,2001-05-13 00:00:00 -17185,669,48,16,11.0,13,,14,0.0,49,,,,3,2001-05-27 00:00:00 -17186,669,1,14,16.0,16,,22,0.0,0,,,,4,2001-05-27 00:00:00 -17187,669,30,2,6.0,7,,21,0.0,2,,,,20,2001-05-27 00:00:00 -17188,669,43,15,9.0,12,,20,0.0,13,,,,38,2001-05-27 00:00:00 -17189,669,56,0,3.0,3,,19,0.0,15,,,,38,2001-05-27 00:00:00 -17190,669,36,18,19.0,14,,18,0.0,18,,,,9,2001-05-27 00:00:00 -17191,669,53,19,23.0,21,,17,0.0,24,,,,6,2001-05-27 00:00:00 -17192,669,14,16,12.0,8,,16,0.0,30,,,,9,2001-05-27 00:00:00 -17193,669,20,21,7.0,10,,15,0.0,43,,,,6,2001-05-27 00:00:00 -17194,669,3,17,21.0,18,,13,0.0,54,,,,6,2001-05-27 00:00:00 -17195,669,57,17,20.0,22,,12,0.0,56,,,,7,2001-05-27 00:00:00 -17196,669,22,2,5.0,5,,11,0.0,57,,,,10,2001-05-27 00:00:00 -17197,669,21,5,2.0,4,2.0,2,6.0,78,6442992.0,,,1,2001-05-27 00:00:00 -17198,669,55,18,18.0,6,3.0,3,4.0,78,6473259.0,,,1,2001-05-27 00:00:00 -17199,669,34,15,10.0,9,4.0,4,3.0,78,6475015.0,,,1,2001-05-27 00:00:00 -17200,669,13,0,4.0,1,5.0,5,2.0,77,,,,11,2001-05-27 00:00:00 -17201,669,29,5,1.0,2,1.0,1,10.0,78,6442561.0,,,1,2001-05-27 00:00:00 -17202,669,17,21,8.0,17,7.0,7,0.0,77,,,,11,2001-05-27 00:00:00 -17203,669,49,20,14.0,19,8.0,8,0.0,77,,,,11,2001-05-27 00:00:00 -17204,669,58,20,15.0,20,9.0,9,0.0,76,,,,12,2001-05-27 00:00:00 -17205,669,7,14,17.0,15,10.0,10,0.0,73,,,,15,2001-05-27 00:00:00 -17206,669,54,19,22.0,11,6.0,6,1.0,77,,,,11,2001-05-27 00:00:00 -17207,670,34,15,10.0,9,,14,0.0,34,,,,86,2001-06-10 00:00:00 -17208,670,20,21,7.0,18,,22,0.0,0,,,,4,2001-06-10 00:00:00 -17209,670,55,18,18.0,15,,21,0.0,1,,,,4,2001-06-10 00:00:00 -17210,670,1,14,16.0,11,,20,0.0,1,,,,4,2001-06-10 00:00:00 -17211,670,3,17,21.0,22,,19,0.0,7,,,,7,2001-06-10 00:00:00 -17212,670,17,21,8.0,20,,18,0.0,17,,,,44,2001-06-10 00:00:00 -17213,670,21,5,2.0,5,,17,0.0,19,,,,20,2001-06-10 00:00:00 -17214,670,30,2,6.0,10,,16,0.0,19,,,,3,2001-06-10 00:00:00 -17215,670,58,20,15.0,17,,15,0.0,24,,,,5,2001-06-10 00:00:00 -17216,670,43,15,9.0,6,,13,0.0,38,,,,23,2001-06-10 00:00:00 -17217,670,22,2,5.0,2,1.0,1,10.0,69,5671522.0,,,1,2001-06-10 00:00:00 -17218,670,14,16,12.0,4,11.0,11,0.0,63,,,,23,2001-06-10 00:00:00 -17219,670,49,20,14.0,13,10.0,10,0.0,65,,,,23,2001-06-10 00:00:00 -17220,670,57,17,20.0,21,9.0,9,0.0,66,,,,13,2001-06-10 00:00:00 -17221,670,53,19,23.0,19,8.0,8,0.0,68,,,,11,2001-06-10 00:00:00 -17222,670,40,16,11.0,12,7.0,7,0.0,68,,,,11,2001-06-10 00:00:00 -17223,670,36,18,19.0,14,6.0,6,1.0,68,,,,11,2001-06-10 00:00:00 -17224,670,54,19,22.0,16,5.0,5,2.0,69,5741957.0,,,1,2001-06-10 00:00:00 -17225,670,7,14,17.0,7,4.0,4,3.0,69,5739638.0,,,1,2001-06-10 00:00:00 -17226,670,56,0,3.0,8,3.0,3,4.0,69,5712194.0,,,1,2001-06-10 00:00:00 -17227,670,29,5,1.0,1,2.0,2,6.0,69,5691757.0,,,1,2001-06-10 00:00:00 -17228,670,13,0,4.0,3,,12,0.0,54,,,,5,2001-06-10 00:00:00 -17229,671,36,18,19.0,16,8.0,8,0.0,66,,,,11,2001-06-24 00:00:00 -17230,671,55,18,18.0,12,7.0,7,0.0,67,5448922.0,,,1,2001-06-24 00:00:00 -17231,671,34,15,10.0,11,9.0,9,0.0,66,,,,11,2001-06-24 00:00:00 -17232,671,56,0,3.0,6,6.0,6,1.0,67,5447592.0,,,1,2001-06-24 00:00:00 -17233,671,29,5,1.0,1,1.0,1,10.0,67,5382724.0,,,1,2001-06-24 00:00:00 -17234,671,22,2,5.0,2,4.0,4,3.0,67,5416069.0,,,1,2001-06-24 00:00:00 -17235,671,13,0,4.0,5,3.0,3,4.0,67,5407717.0,,,1,2001-06-24 00:00:00 -17236,671,30,2,6.0,3,2.0,2,6.0,67,5386851.0,,,1,2001-06-24 00:00:00 -17237,671,21,5,2.0,4,5.0,5,2.0,67,5428219.0,,,1,2001-06-24 00:00:00 -17238,671,7,14,17.0,9,10.0,10,0.0,66,,,,11,2001-06-24 00:00:00 -17239,671,54,19,22.0,14,15.0,15,0.0,64,,,,20,2001-06-24 00:00:00 -17240,671,53,19,23.0,17,12.0,12,0.0,65,,,,12,2001-06-24 00:00:00 -17241,671,57,17,20.0,22,,22,0.0,7,,,,10,2001-06-24 00:00:00 -17242,671,43,15,9.0,13,,21,0.0,23,,,,10,2001-06-24 00:00:00 -17243,671,58,20,15.0,18,,20,0.0,29,,,,6,2001-06-24 00:00:00 -17244,671,14,16,12.0,7,,19,0.0,44,,,,7,2001-06-24 00:00:00 -17245,671,20,21,7.0,15,11.0,11,0.0,66,,,,11,2001-06-24 00:00:00 -17246,671,1,14,16.0,10,,17,0.0,54,,,,30,2001-06-24 00:00:00 -17247,671,49,20,14.0,19,,16,0.0,58,,,,5,2001-06-24 00:00:00 -17248,671,3,17,21.0,21,14.0,14,0.0,65,,,,12,2001-06-24 00:00:00 -17249,671,17,21,8.0,20,13.0,13,0.0,65,,,,12,2001-06-24 00:00:00 -17250,671,48,16,11.0,8,,18,0.0,48,,,,20,2001-06-24 00:00:00 -17251,672,36,18,19.0,14,14.0,14,0.0,70,,,,12,2001-07-01 00:00:00 -17252,672,56,0,3.0,4,,22,0.0,0,,,,6,2001-07-01 00:00:00 -17253,672,34,15,10.0,10,,21,0.0,5,,,,5,2001-07-01 00:00:00 -17254,672,58,20,15.0,20,,20,0.0,17,,,,5,2001-07-01 00:00:00 -17255,672,30,2,6.0,6,,19,0.0,52,,,,5,2001-07-01 00:00:00 -17256,672,55,18,18.0,12,,18,0.0,54,,,,5,2001-07-01 00:00:00 -17257,672,3,17,21.0,21,17.0,17,0.0,65,,,,5,2001-07-01 00:00:00 -17258,672,17,21,8.0,17,16.0,16,0.0,68,,,,32,2001-07-01 00:00:00 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-17274,673,57,17,20.0,0,,22,0.0,0,,,,77,2001-07-15 00:00:00 -17275,673,43,15,9.0,11,,21,0.0,0,,,,4,2001-07-15 00:00:00 -17276,673,14,16,12.0,4,,20,0.0,0,,,,4,2001-07-15 00:00:00 -17277,673,13,0,4.0,3,,19,0.0,2,,,,22,2001-07-15 00:00:00 -17278,673,53,19,23.0,16,,18,0.0,6,,,,5,2001-07-15 00:00:00 -17279,673,22,2,5.0,10,,17,0.0,36,,,,5,2001-07-15 00:00:00 -17280,673,3,17,21.0,21,16.0,16,0.0,57,,,,13,2001-07-15 00:00:00 -17281,673,17,21,8.0,18,15.0,15,0.0,58,,,,12,2001-07-15 00:00:00 -17282,673,20,21,7.0,19,13.0,13,0.0,58,,,,12,2001-07-15 00:00:00 -17283,673,56,0,3.0,2,1.0,1,10.0,60,5133770.0,,,1,2001-07-15 00:00:00 -17284,673,54,19,22.0,14,11.0,11,0.0,58,,,,12,2001-07-15 00:00:00 -17285,673,49,20,14.0,17,10.0,10,0.0,58,,,,12,2001-07-15 00:00:00 -17286,673,55,18,18.0,15,9.0,9,0.0,59,,,,11,2001-07-15 00:00:00 -17287,673,34,15,10.0,12,8.0,8,0.0,59,,,,11,2001-07-15 00:00:00 -17288,673,48,16,11.0,5,7.0,7,0.0,59,,,,11,2001-07-15 00:00:00 -17289,673,1,14,16.0,9,6.0,6,1.0,59,,,,11,2001-07-15 00:00:00 -17290,673,7,14,17.0,7,5.0,5,2.0,59,,,,11,2001-07-15 00:00:00 -17291,673,30,2,6.0,8,4.0,4,3.0,60,5202542.0,,,1,2001-07-15 00:00:00 -17292,673,21,5,2.0,6,3.0,3,4.0,60,5193051.0,,,1,2001-07-15 00:00:00 -17293,673,29,5,1.0,1,2.0,2,6.0,60,5167416.0,,,1,2001-07-15 00:00:00 -17294,673,36,18,19.0,13,12.0,12,0.0,58,,,,12,2001-07-15 00:00:00 -17295,674,29,5,1.0,4,,15,0.0,23,,,,32,2001-07-29 00:00:00 -17296,674,53,19,23.0,16,,16,0.0,23,,,,20,2001-07-29 00:00:00 -17297,674,30,2,6.0,1,,14,0.0,24,,,,5,2001-07-29 00:00:00 -17298,674,7,14,17.0,8,,17,0.0,16,,,,86,2001-07-29 00:00:00 -17299,674,36,18,19.0,9,,22,0.0,0,,,,4,2001-07-29 00:00:00 -17300,674,56,0,3.0,3,,19,0.0,13,,,,5,2001-07-29 00:00:00 -17301,674,40,16,11.0,15,,20,0.0,7,,,,4,2001-07-29 00:00:00 -17302,674,1,14,16.0,7,,21,0.0,0,,,,4,2001-07-29 00:00:00 -17303,674,55,18,18.0,11,,18,0.0,16,,,,32,2001-07-29 00:00:00 -17304,674,57,17,20.0,22,,13,0.0,26,,,,6,2001-07-29 00:00:00 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00:00:00 -17351,676,49,20,14.0,19,10.0,10,0.0,35,,,,11,2001-09-02 00:00:00 -17352,676,34,15,10.0,6,8.0,8,0.0,36,4149972.0,,,1,2001-09-02 00:00:00 -17353,676,54,16,12.0,13,6.0,6,1.0,36,4144686.0,,,1,2001-09-02 00:00:00 -17354,676,21,5,2.0,5,5.0,5,2.0,36,4139523.0,,,1,2001-09-02 00:00:00 -17355,676,56,0,3.0,7,4.0,4,3.0,36,4121089.0,,,1,2001-09-02 00:00:00 -17356,676,20,21,7.0,8,3.0,3,4.0,36,4112744.0,,,1,2001-09-02 00:00:00 -17357,676,13,0,4.0,9,2.0,2,6.0,36,4095100.0,,,1,2001-09-02 00:00:00 -17358,676,29,5,1.0,3,1.0,1,10.0,36,4085002.0,,,1,2001-09-02 00:00:00 -17359,676,58,20,15.0,21,12.0,12,0.0,35,,,,11,2001-09-02 00:00:00 -17360,676,48,19,22.0,4,9.0,9,0.0,35,,,,11,2001-09-02 00:00:00 -17361,677,30,2,6.0,1,1.0,1,10.0,53,4618493.0,,,1,2001-09-16 00:00:00 -17362,677,21,5,2.0,2,2.0,2,6.0,53,4623668.0,,,1,2001-09-16 00:00:00 -17363,677,14,16,11.0,5,,22,0.0,0,,,,4,2001-09-16 00:00:00 -17364,677,17,21,8.0,11,,21,0.0,4,,,,5,2001-09-16 00:00:00 -17365,677,13,0,4.0,6,,20,0.0,6,,,,5,2001-09-16 00:00:00 -17366,677,55,18,18.0,13,,19,0.0,14,,,,5,2001-09-16 00:00:00 -17367,677,56,0,3.0,7,,18,0.0,19,,,,6,2001-09-16 00:00:00 -17368,677,48,19,22.0,12,,16,0.0,28,,,,6,2001-09-16 00:00:00 -17369,677,61,17,20.0,22,,15,0.0,44,,,,20,2001-09-16 00:00:00 -17370,677,58,20,15.0,18,,14,0.0,46,,,,87,2001-09-16 00:00:00 -17371,677,3,17,21.0,21,13.0,13,0.0,51,,,,12,2001-09-16 00:00:00 -17372,677,49,20,14.0,19,,17,0.0,25,,,,32,2001-09-16 00:00:00 -17373,677,1,14,16.0,8,11.0,11,0.0,52,,,,11,2001-09-16 00:00:00 -17374,677,20,21,7.0,14,10.0,10,0.0,52,,,,11,2001-09-16 00:00:00 -17375,677,43,15,9.0,17,9.0,9,0.0,52,,,,11,2001-09-16 00:00:00 -17376,677,54,16,12.0,16,8.0,8,0.0,52,,,,11,2001-09-16 00:00:00 -17377,677,7,14,17.0,9,7.0,7,0.0,53,4701600.0,,,1,2001-09-16 00:00:00 -17378,677,34,15,10.0,15,6.0,6,1.0,53,4700962.0,,,1,2001-09-16 00:00:00 -17379,677,36,18,19.0,10,5.0,5,2.0,53,4693477.0,,,1,2001-09-16 00:00:00 -17380,677,29,5,1.0,3,4.0,4,3.0,53,4643484.0,,,1,2001-09-16 00:00:00 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-17396,678,17,21,8.0,10,9.0,9,0.0,72,,,,11,2001-09-30 00:00:00 -17397,678,20,21,7.0,12,8.0,8,0.0,72,,,,11,2001-09-30 00:00:00 -17398,678,54,16,12.0,9,7.0,7,0.0,72,,,,11,2001-09-30 00:00:00 -17399,678,55,18,18.0,14,5.0,5,2.0,73,5635274.0,,,1,2001-09-30 00:00:00 -17400,678,14,16,11.0,8,4.0,4,3.0,73,5620263.0,,,1,2001-09-30 00:00:00 -17401,678,13,0,4.0,7,3.0,3,4.0,73,5574883.0,,,1,2001-09-30 00:00:00 -17402,678,29,5,1.0,1,2.0,2,6.0,73,5573886.0,,,1,2001-09-30 00:00:00 -17403,678,56,0,3.0,4,1.0,1,10.0,73,5562840.0,,,1,2001-09-30 00:00:00 -17404,678,43,15,9.0,13,11.0,11,0.0,72,,,,11,2001-09-30 00:00:00 -17405,679,58,20,15.0,20,14.0,14,0.0,51,,,,12,2001-10-14 00:00:00 -17406,679,49,20,14.0,21,15.0,15,0.0,51,,,,12,2001-10-14 00:00:00 -17407,679,61,17,20.0,22,16.0,16,0.0,50,,,,13,2001-10-14 00:00:00 -17408,679,20,21,7.0,6,17.0,17,0.0,47,,,,6,2001-10-14 00:00:00 -17409,679,7,14,17.0,12,,21,0.0,5,,,,4,2001-10-14 00:00:00 -17410,679,60,19,23.0,19,,19,0.0,42,,,,23,2001-10-14 00:00:00 -17411,679,55,18,18.0,13,,20,0.0,24,,,,71,2001-10-14 00:00:00 -17412,679,54,16,12.0,11,,22,0.0,5,,,,4,2001-10-14 00:00:00 -17413,679,43,15,9.0,17,13.0,13,0.0,51,,,,12,2001-10-14 00:00:00 -17414,679,36,18,19.0,16,,18,0.0,45,,,,44,2001-10-14 00:00:00 -17415,679,48,19,22.0,15,12.0,12,0.0,52,,,,11,2001-10-14 00:00:00 -17416,679,22,2,5.0,3,6.0,6,1.0,53,5290420.0,,,1,2001-10-14 00:00:00 -17417,679,34,15,10.0,14,10.0,10,0.0,52,,,,11,2001-10-14 00:00:00 -17418,679,29,5,1.0,1,1.0,1,10.0,53,5253298.0,,,1,2001-10-14 00:00:00 -17419,679,30,2,6.0,2,2.0,2,6.0,53,5256452.0,,,1,2001-10-14 00:00:00 -17420,679,13,0,4.0,7,3.0,3,4.0,53,5276560.0,,,1,2001-10-14 00:00:00 -17421,679,56,0,3.0,5,4.0,4,3.0,53,5288837.0,,,1,2001-10-14 00:00:00 -17422,679,3,17,21.0,18,11.0,11,0.0,52,,,,11,2001-10-14 00:00:00 -17423,679,17,21,8.0,9,7.0,7,0.0,53,5350400.0,,,1,2001-10-14 00:00:00 -17424,679,14,16,11.0,8,8.0,8,0.0,52,,,,11,2001-10-14 00:00:00 -17425,679,1,14,16.0,10,9.0,9,0.0,52,,,,11,2001-10-14 00:00:00 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00:00:00 -17458,681,62,6,24.0,10,12.0,12,0.0,53,,,,13,2002-03-17 00:00:00 -17459,681,14,3,14.0,12,,22,0.0,9,,,,25,2002-03-17 00:00:00 -17460,681,36,18,17.0,17,10.0,10,0.0,54,,,,12,2002-03-17 00:00:00 -17461,681,22,2,5.0,4,1.0,1,10.0,56,5652912.0,,,1,2002-03-17 00:00:00 -17462,681,30,2,6.0,2,2.0,2,6.0,56,5692612.0,,,1,2002-03-17 00:00:00 -17463,681,29,5,1.0,1,3.0,3,4.0,56,5714707.0,,,1,2002-03-17 00:00:00 -17464,681,17,3,15.0,8,4.0,4,3.0,56,5722679.0,,,1,2002-03-17 00:00:00 -17465,681,48,20,20.0,11,11.0,11,0.0,54,,,,12,2002-03-17 00:00:00 -17466,681,12,14,8.0,14,6.0,6,1.0,55,,,,11,2002-03-17 00:00:00 -17467,681,65,6,25.0,19,7.0,7,0.0,55,,,,11,2002-03-17 00:00:00 -17468,681,34,15,11.0,13,8.0,8,0.0,55,,,,11,2002-03-17 00:00:00 -17469,681,10,16,10.0,15,9.0,9,0.0,54,,,,12,2002-03-17 00:00:00 -17470,681,1,14,7.0,7,5.0,5,2.0,55,,,,11,2002-03-17 00:00:00 -17471,682,61,17,22.0,22,13.0,13,0.0,67,,,,14,2002-03-31 00:00:00 -17472,682,21,5,2.0,8,,21,0.0,16,,,,9,2002-03-31 00:00:00 -17473,682,58,20,21.0,21,,20,0.0,19,,,,22,2002-03-31 00:00:00 -17474,682,48,20,20.0,18,,19,0.0,25,,,,22,2002-03-31 00:00:00 -17475,682,43,15,12.0,17,,18,0.0,25,,,,6,2002-03-31 00:00:00 -17476,682,65,6,25.0,16,,17,0.0,40,,,,20,2002-03-31 00:00:00 -17477,682,12,14,8.0,12,,16,0.0,41,,,,4,2002-03-31 00:00:00 -17478,682,14,3,14.0,6,,15,0.0,60,,,,5,2002-03-31 00:00:00 -17479,682,1,14,7.0,9,,14,0.0,61,,,,23,2002-03-31 00:00:00 -17480,682,7,0,4.0,5,12.0,12,0.0,67,,,,46,2002-03-31 00:00:00 -17481,682,20,16,9.0,14,,22,0.0,6,,,,5,2002-03-31 00:00:00 -17482,682,34,15,11.0,15,10.0,10,0.0,68,,,,5,2002-03-31 00:00:00 -17483,682,29,5,1.0,2,1.0,1,10.0,71,5503662.0,,,1,2002-03-31 00:00:00 -17484,682,22,2,5.0,3,2.0,2,6.0,71,5504250.0,,,1,2002-03-31 00:00:00 -17485,682,13,0,3.0,4,3.0,3,4.0,71,5562771.0,,,1,2002-03-31 00:00:00 -17486,682,17,3,15.0,7,4.0,4,3.0,71,5570545.0,,,1,2002-03-31 00:00:00 -17487,682,16,17,23.0,20,11.0,11,0.0,68,,,,13,2002-03-31 00:00:00 -17488,682,62,6,24.0,10,6.0,6,1.0,70,,,,11,2002-03-31 00:00:00 -17489,682,55,18,16.0,13,7.0,7,0.0,70,,,,11,2002-03-31 00:00:00 -17490,682,36,18,17.0,11,8.0,8,0.0,70,,,,11,2002-03-31 00:00:00 -17491,682,10,16,10.0,19,9.0,9,0.0,69,,,,12,2002-03-31 00:00:00 -17492,682,30,2,6.0,1,5.0,5,2.0,71,5571225.0,,,1,2002-03-31 00:00:00 -17493,683,58,20,21.0,20,,12,0.0,50,,,,75,2002-04-14 00:00:00 -17494,683,65,6,25.0,17,,21,0.0,0,,,,10,2002-04-14 00:00:00 -17495,683,10,16,10.0,14,,20,0.0,5,,,,6,2002-04-14 00:00:00 -17496,683,20,16,9.0,15,,19,0.0,19,,,,9,2002-04-14 00:00:00 -17497,683,48,20,20.0,13,,18,0.0,25,,,,75,2002-04-14 00:00:00 -17498,683,62,6,24.0,16,,17,0.0,26,,,,6,2002-04-14 00:00:00 -17499,683,36,18,17.0,22,,16,0.0,30,,,,30,2002-04-14 00:00:00 -17500,683,43,15,12.0,12,,15,0.0,44,,,,37,2002-04-14 00:00:00 -17501,683,7,0,4.0,5,,14,0.0,44,,,,43,2002-04-14 00:00:00 -17502,683,55,18,16.0,18,,13,0.0,45,,,,30,2002-04-14 00:00:00 -17503,683,61,17,22.0,0,,22,0.0,0,,,,77,2002-04-14 00:00:00 -17504,683,16,17,23.0,19,11.0,11,0.0,60,,,,12,2002-04-14 00:00:00 -17505,683,14,3,14.0,8,9.0,9,0.0,61,,,,11,2002-04-14 00:00:00 -17506,683,12,14,8.0,11,8.0,8,0.0,61,,,,11,2002-04-14 00:00:00 -17507,683,34,15,11.0,10,7.0,7,0.0,61,,,,11,2002-04-14 00:00:00 -17508,683,13,0,3.0,6,6.0,6,1.0,61,,,,11,2002-04-14 00:00:00 -17509,683,17,3,15.0,9,5.0,5,2.0,62,5434184.0,,,1,2002-04-14 00:00:00 -17510,683,30,2,6.0,4,4.0,4,3.0,62,5395514.0,,,1,2002-04-14 00:00:00 -17511,683,22,2,5.0,3,3.0,3,4.0,62,5370544.0,,,1,2002-04-14 00:00:00 -17512,683,21,5,2.0,2,2.0,2,6.0,62,5368696.0,,,1,2002-04-14 00:00:00 -17513,683,29,5,1.0,1,1.0,1,10.0,62,5350789.0,,,1,2002-04-14 00:00:00 -17514,683,1,14,7.0,7,10.0,10,0.0,61,,,,11,2002-04-14 00:00:00 -17515,684,55,18,16.0,22,,14,0.0,41,,,,9,2002-04-28 00:00:00 -17516,684,58,20,21.0,14,,15,0.0,40,,,,9,2002-04-28 00:00:00 -17517,684,10,16,10.0,18,,16,0.0,10,,,,20,2002-04-28 00:00:00 -17518,684,20,16,9.0,12,,17,0.0,5,,,,9,2002-04-28 00:00:00 -17519,684,16,17,22.0,20,,21,0.0,0,,,,78,2002-04-28 00:00:00 -17520,684,7,0,4.0,5,,18,0.0,4,,,,65,2002-04-28 00:00:00 -17521,684,36,18,17.0,16,,19,0.0,2,,,,20,2002-04-28 00:00:00 -17522,684,21,5,2.0,2,,20,0.0,0,,,,6,2002-04-28 00:00:00 -17523,684,43,15,12.0,13,,13,0.0,43,,,,43,2002-04-28 00:00:00 -17524,684,61,17,23.0,21,,22,0.0,0,,,,78,2002-04-28 00:00:00 -17525,684,17,3,15.0,6,12.0,12,0.0,60,,,,9,2002-04-28 00:00:00 -17526,684,12,14,8.0,11,5.0,5,2.0,65,5508954.0,,,1,2002-04-28 00:00:00 -17527,684,14,3,14.0,9,10.0,10,0.0,63,,,,5,2002-04-28 00:00:00 -17528,684,62,6,24.0,17,9.0,9,0.0,64,,,,11,2002-04-28 00:00:00 -17529,684,65,6,25.0,19,8.0,8,0.0,64,,,,11,2002-04-28 00:00:00 -17530,684,34,15,11.0,15,7.0,7,0.0,64,,,,11,2002-04-28 00:00:00 -17531,684,48,20,20.0,10,6.0,6,1.0,65,5510411.0,,,1,2002-04-28 00:00:00 -17532,684,1,14,7.0,8,4.0,4,3.0,65,5496678.0,,,1,2002-04-28 00:00:00 -17533,684,13,0,3.0,7,3.0,3,4.0,65,5472604.0,,,1,2002-04-28 00:00:00 -17534,684,30,2,6.0,4,2.0,2,6.0,65,5465611.0,,,1,2002-04-28 00:00:00 -17535,684,29,5,1.0,1,1.0,1,10.0,65,5429981.0,,,1,2002-04-28 00:00:00 -17536,684,22,2,5.0,3,11.0,11,0.0,63,,,,5,2002-04-28 00:00:00 -17537,685,61,17,22.0,22,,14,0.0,42,,,,5,2002-05-12 00:00:00 -17538,685,55,18,16.0,20,,15,0.0,38,,,,9,2002-05-12 00:00:00 -17539,685,1,14,7.0,5,,16,0.0,27,,,,4,2002-05-12 00:00:00 -17540,685,36,18,17.0,19,,22,0.0,0,,,,37,2002-05-12 00:00:00 -17541,685,12,14,8.0,7,,19,0.0,7,,,,22,2002-05-12 00:00:00 -17542,685,7,0,4.0,6,,20,0.0,5,,,,5,2002-05-12 00:00:00 -17543,685,58,20,21.0,12,,21,0.0,2,,,,4,2002-05-12 00:00:00 -17544,685,14,3,14.0,16,,13,0.0,44,,,,32,2002-05-12 00:00:00 -17545,685,43,15,12.0,9,,18,0.0,22,,,,5,2002-05-12 00:00:00 -17546,685,16,17,23.0,21,12.0,12,0.0,69,,,,12,2002-05-12 00:00:00 -17547,685,10,16,10.0,18,,17,0.0,26,,,,4,2002-05-12 00:00:00 -17548,685,34,15,11.0,17,10.0,10,0.0,70,,,,11,2002-05-12 00:00:00 -17549,685,48,20,20.0,11,11.0,11,0.0,69,,,,12,2002-05-12 00:00:00 -17550,685,21,5,2.0,1,2.0,2,6.0,71,5631744.0,,,1,2002-05-12 00:00:00 -17551,685,30,2,6.0,4,3.0,3,4.0,71,5649292.0,,,1,2002-05-12 00:00:00 -17552,685,22,2,5.0,2,4.0,4,3.0,71,5650010.0,,,1,2002-05-12 00:00:00 -17553,685,29,5,1.0,3,1.0,1,10.0,71,5631562.0,,,1,2002-05-12 00:00:00 -17554,685,13,0,3.0,8,6.0,6,1.0,71,5682234.0,,,1,2002-05-12 00:00:00 -17555,685,17,3,15.0,13,7.0,7,0.0,71,5682791.0,,,1,2002-05-12 00:00:00 -17556,685,62,6,24.0,10,8.0,8,0.0,71,5700987.0,,,1,2002-05-12 00:00:00 -17557,685,65,6,25.0,14,9.0,9,0.0,71,5701280.0,,,1,2002-05-12 00:00:00 -17558,685,20,16,9.0,15,5.0,5,2.0,71,5681527.0,,,1,2002-05-12 00:00:00 -17559,686,62,6,24.0,9,,13,0.0,69,,,,23,2002-05-26 00:00:00 -17560,686,61,17,22.0,22,,20,0.0,29,,,,3,2002-05-26 00:00:00 -17561,686,7,0,4.0,6,,19,0.0,41,,,,4,2002-05-26 00:00:00 -17562,686,34,15,11.0,14,,18,0.0,44,,,,26,2002-05-26 00:00:00 -17563,686,30,2,6.0,1,,17,0.0,46,,,,5,2002-05-26 00:00:00 -17564,686,17,3,15.0,8,,16,0.0,51,,,,4,2002-05-26 00:00:00 -17565,686,43,15,12.0,18,,15,0.0,51,,,,4,2002-05-26 00:00:00 -17566,686,12,14,8.0,13,,14,0.0,63,,,,3,2002-05-26 00:00:00 -17567,686,58,20,21.0,21,12.0,12,0.0,76,,,,12,2002-05-26 00:00:00 -17568,686,48,20,20.0,12,6.0,6,1.0,77,,,,11,2002-05-26 00:00:00 -17569,686,36,18,17.0,17,10.0,10,0.0,76,,,,12,2002-05-26 00:00:00 -17570,686,55,18,16.0,19,9.0,9,0.0,76,,,,12,2002-05-26 00:00:00 -17571,686,1,14,7.0,15,8.0,8,0.0,76,,,,12,2002-05-26 00:00:00 -17572,686,21,5,2.0,5,7.0,7,0.0,77,,,,11,2002-05-26 00:00:00 -17573,686,20,16,9.0,11,5.0,5,2.0,77,,,,11,2002-05-26 00:00:00 -17574,686,14,3,14.0,7,4.0,4,3.0,77,,,,11,2002-05-26 00:00:00 -17575,686,22,2,5.0,4,3.0,3,4.0,78,6406505.0,,,1,2002-05-26 00:00:00 -17576,686,29,5,1.0,3,2.0,2,6.0,78,6340105.0,,,1,2002-05-26 00:00:00 -17577,686,10,16,10.0,16,,21,0.0,22,,,,20,2002-05-26 00:00:00 -17578,686,16,17,23.0,20,11.0,11,0.0,76,,,,12,2002-05-26 00:00:00 -17579,686,65,6,25.0,10,,22,0.0,15,,,,3,2002-05-26 00:00:00 -17580,686,13,0,3.0,2,1.0,1,10.0,78,6339055.0,,,1,2002-05-26 00:00:00 -17581,687,7,0,4.0,5,4.0,4,3.0,70,5653674.0,,,1,2002-06-09 00:00:00 -17582,687,34,15,11.0,9,,22,0.0,8,,,,51,2002-06-09 00:00:00 -17583,687,58,20,21.0,17,,21,0.0,16,,,,22,2002-06-09 00:00:00 -17584,687,36,18,17.0,16,,20,0.0,29,,,,6,2002-06-09 00:00:00 -17585,687,62,6,24.0,18,,19,0.0,41,,,,23,2002-06-09 00:00:00 -17586,687,55,18,16.0,14,,18,0.0,41,,,,25,2002-06-09 00:00:00 -17587,687,65,6,25.0,20,,17,0.0,45,,,,20,2002-06-09 00:00:00 -17588,687,30,2,6.0,1,,16,0.0,56,,,,5,2002-06-09 00:00:00 -17589,687,17,3,15.0,13,15.0,15,0.0,65,,,,6,2002-06-09 00:00:00 -17590,687,61,17,22.0,22,14.0,14,0.0,68,,,,12,2002-06-09 00:00:00 -17591,687,1,14,7.0,7,12.0,12,0.0,69,,,,11,2002-06-09 00:00:00 -17592,687,48,20,20.0,19,13.0,13,0.0,69,,,,11,2002-06-09 00:00:00 -17593,687,10,16,10.0,15,10.0,10,0.0,69,,,,11,2002-06-09 00:00:00 -17594,687,12,14,8.0,12,9.0,9,0.0,69,,,,11,2002-06-09 00:00:00 -17595,687,43,15,12.0,11,8.0,8,0.0,69,,,,11,2002-06-09 00:00:00 -17596,687,22,2,5.0,4,7.0,7,0.0,70,,,,5,2002-06-09 00:00:00 -17597,687,14,3,14.0,10,6.0,6,1.0,70,5665058.0,,,1,2002-06-09 00:00:00 -17598,687,20,16,9.0,6,5.0,5,2.0,70,5658923.0,,,1,2002-06-09 00:00:00 -17599,687,21,5,2.0,3,3.0,3,4.0,70,5623193.0,,,1,2002-06-09 00:00:00 -17600,687,13,0,3.0,8,2.0,2,6.0,70,5617243.0,,,1,2002-06-09 00:00:00 -17601,687,29,5,1.0,2,1.0,1,10.0,70,5616111.0,,,1,2002-06-09 00:00:00 -17602,687,16,17,23.0,21,11.0,11,0.0,69,,,,11,2002-06-09 00:00:00 -17603,688,29,5,1.0,3,2.0,2,6.0,60,5707720.0,,,1,2002-06-23 00:00:00 -17604,688,21,5,2.0,4,1.0,1,10.0,60,5707426.0,,,1,2002-06-23 00:00:00 -17605,688,7,0,4.0,6,3.0,3,4.0,60,5753861.0,,,1,2002-06-23 00:00:00 -17606,688,22,2,5.0,2,4.0,4,3.0,60,5774389.0,,,1,2002-06-23 00:00:00 -17607,688,61,17,22.0,22,,18,0.0,48,,,,9,2002-06-23 00:00:00 -17608,688,20,16,9.0,18,,22,0.0,26,,,,3,2002-06-23 00:00:00 -17609,688,13,0,3.0,5,,21,0.0,27,,,,4,2002-06-23 00:00:00 -17610,688,30,2,6.0,1,,20,0.0,27,,,,4,2002-06-23 00:00:00 -17611,688,55,18,16.0,17,,19,0.0,41,,,,9,2002-06-23 00:00:00 -17612,688,17,3,15.0,8,5.0,5,2.0,60,5784370.0,,,1,2002-06-23 00:00:00 -17613,688,62,6,24.0,10,,17,0.0,51,,,,6,2002-06-23 00:00:00 -17614,688,10,16,10.0,14,16.0,16,0.0,58,,,,12,2002-06-23 00:00:00 -17615,688,65,6,25.0,13,14.0,14,0.0,59,,,,11,2002-06-23 00:00:00 -17616,688,16,17,23.0,20,15.0,15,0.0,58,,,,12,2002-06-23 00:00:00 -17617,688,34,15,11.0,19,12.0,12,0.0,59,,,,11,2002-06-23 00:00:00 -17618,688,58,20,21.0,21,11.0,11,0.0,59,,,,11,2002-06-23 00:00:00 -17619,688,36,18,17.0,16,10.0,10,0.0,59,,,,11,2002-06-23 00:00:00 -17620,688,43,15,12.0,12,9.0,9,0.0,59,,,,11,2002-06-23 00:00:00 -17621,688,14,3,14.0,7,8.0,8,0.0,59,,,,11,2002-06-23 00:00:00 -17622,688,1,14,7.0,9,7.0,7,0.0,59,,,,11,2002-06-23 00:00:00 -17623,688,12,14,8.0,11,6.0,6,1.0,59,,,,11,2002-06-23 00:00:00 -17624,688,48,20,20.0,15,13.0,13,0.0,59,,,,11,2002-06-23 00:00:00 -17625,689,16,17,23.0,20,,20,0.0,9,,,,8,2002-07-07 00:00:00 -17626,689,12,14,8.0,11,9.0,9,0.0,59,,,,11,2002-07-07 00:00:00 -17627,689,65,6,25.0,15,,21,0.0,0,,,,8,2002-07-07 00:00:00 -17628,689,14,3,14.0,7,,15,0.0,29,,,,40,2002-07-07 00:00:00 -17629,689,7,0,4.0,5,,14,0.0,44,,,,5,2002-07-07 00:00:00 -17630,689,48,20,20.0,16,,18,0.0,20,,,,5,2002-07-07 00:00:00 -17631,689,55,18,16.0,19,,17,0.0,23,,,,20,2002-07-07 00:00:00 -17632,689,58,20,21.0,18,,16,0.0,28,,,,30,2002-07-07 00:00:00 -17633,689,62,6,24.0,8,,19,0.0,15,,,,79,2002-07-07 00:00:00 -17634,689,10,16,10.0,14,,13,0.0,50,,,,5,2002-07-07 00:00:00 -17635,689,22,2,5.0,4,8.0,8,0.0,59,,,,11,2002-07-07 00:00:00 -17636,689,36,18,17.0,21,11.0,11,0.0,58,,,,12,2002-07-07 00:00:00 -17637,689,20,16,9.0,17,7.0,7,0.0,59,,,,11,2002-07-07 00:00:00 -17638,689,1,14,7.0,10,6.0,6,1.0,59,,,,11,2002-07-07 00:00:00 -17639,689,43,15,12.0,13,5.0,5,2.0,59,,,,11,2002-07-07 00:00:00 -17640,689,34,15,11.0,9,4.0,4,3.0,59,,,,11,2002-07-07 00:00:00 -17641,689,17,3,15.0,12,12.0,12,0.0,54,,,,36,2002-07-07 00:00:00 -17642,689,21,5,2.0,2,2.0,2,6.0,60,5519593.0,,,1,2002-07-07 00:00:00 -17643,689,29,5,1.0,3,1.0,1,10.0,60,5505015.0,,,1,2002-07-07 00:00:00 -17644,689,13,0,3.0,6,10.0,10,0.0,58,,,,12,2002-07-07 00:00:00 -17645,689,30,2,6.0,1,3.0,3,4.0,60,5536676.0,,,1,2002-07-07 00:00:00 -17646,690,20,16,9.0,0,,22,0.0,0,,,,82,2002-07-21 00:00:00 -17647,690,58,20,21.0,0,,21,0.0,0,,,,81,2002-07-21 00:00:00 -17648,690,55,18,16.0,9,,12,0.0,52,,,,65,2002-07-21 00:00:00 -17649,690,21,5,2.0,3,,19,0.0,0,,,,80,2002-07-21 00:00:00 -17650,690,10,16,10.0,14,,18,0.0,23,,,,20,2002-07-21 00:00:00 -17651,690,43,15,12.0,11,,17,0.0,29,,,,3,2002-07-21 00:00:00 -17652,690,34,15,11.0,13,,16,0.0,35,,,,5,2002-07-21 00:00:00 -17653,690,62,6,24.0,16,,15,0.0,48,,,,5,2002-07-21 00:00:00 -17654,690,12,14,8.0,12,,14,0.0,48,,,,26,2002-07-21 00:00:00 -17655,690,14,3,14.0,8,,13,0.0,49,,,,5,2002-07-21 00:00:00 -17656,690,48,20,20.0,0,,20,0.0,0,,,,81,2002-07-21 00:00:00 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00:00:00 -17688,691,1,14,7.0,10,6.0,6,1.0,66,,,,11,2002-07-28 00:00:00 -17689,692,34,15,11.0,13,,20,0.0,20,,,,7,2002-08-18 00:00:00 -17690,692,55,18,16.0,16,,19,0.0,23,,,,5,2002-08-18 00:00:00 -17691,692,17,3,15.0,9,,18,0.0,30,,,,20,2002-08-18 00:00:00 -17692,692,18,17,22.0,20,,17,0.0,58,,,,20,2002-08-18 00:00:00 -17693,692,16,17,23.0,19,16.0,16,0.0,75,,,,12,2002-08-18 00:00:00 -17694,692,62,6,24.0,17,15.0,15,0.0,75,,,,12,2002-08-18 00:00:00 -17695,692,65,6,25.0,18,14.0,14,0.0,75,,,,12,2002-08-18 00:00:00 -17696,692,43,15,12.0,12,12.0,12,0.0,76,,,,11,2002-08-18 00:00:00 -17697,692,30,2,6.0,4,11.0,11,0.0,76,,,,11,2002-08-18 00:00:00 -17698,692,36,18,17.0,15,13.0,13,0.0,75,,,,12,2002-08-18 00:00:00 -17699,692,1,14,7.0,8,9.0,9,0.0,76,,,,11,2002-08-18 00:00:00 -17700,692,21,5,2.0,1,1.0,1,10.0,77,6109001.0,,,1,2002-08-18 00:00:00 -17701,692,29,5,1.0,2,2.0,2,6.0,77,6109435.0,,,1,2002-08-18 00:00:00 -17702,692,22,2,5.0,3,3.0,3,4.0,77,6122357.0,,,1,2002-08-18 00:00:00 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00:00:00 -17748,694,34,15,11.0,9,9.0,9,0.0,53,4661050.0,,,1,2002-09-15 00:00:00 -17749,695,48,14,8.0,11,13.0,13,0.0,71,,,,12,2002-09-29 00:00:00 -17750,695,62,6,24.0,19,14.0,14,0.0,71,,,,12,2002-09-29 00:00:00 -17751,695,36,18,17.0,17,,20,0.0,27,,,,7,2002-09-29 00:00:00 -17752,695,43,15,12.0,12,12.0,12,0.0,72,,,,11,2002-09-29 00:00:00 -17753,695,7,0,4.0,6,,17,0.0,50,,,,5,2002-09-29 00:00:00 -17754,695,61,17,22.0,20,,18,0.0,46,,,,5,2002-09-29 00:00:00 -17755,695,16,17,23.0,18,,19,0.0,38,,,,38,2002-09-29 00:00:00 -17756,695,22,2,5.0,5,16.0,16,0.0,71,,,,12,2002-09-29 00:00:00 -17757,695,10,16,10.0,15,11.0,11,0.0,72,,,,11,2002-09-29 00:00:00 -17758,695,65,6,25.0,16,15.0,15,0.0,71,,,,12,2002-09-29 00:00:00 -17759,695,1,14,7.0,10,9.0,9,0.0,72,,,,11,2002-09-29 00:00:00 -17760,695,17,3,15.0,14,8.0,8,0.0,72,,,,11,2002-09-29 00:00:00 -17761,695,20,16,9.0,9,7.0,7,0.0,72,,,,11,2002-09-29 00:00:00 -17762,695,34,15,11.0,7,6.0,6,1.0,73,5526211.0,,,1,2002-09-29 00:00:00 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-17778,696,16,17,23.0,19,10.0,10,0.0,51,,,,12,2002-10-13 00:00:00 -17779,696,55,18,16.0,14,9.0,9,0.0,52,,,,11,2002-10-13 00:00:00 -17780,696,29,5,1.0,1,1.0,1,10.0,53,5219698.0,,,1,2002-10-13 00:00:00 -17781,696,21,5,2.0,2,2.0,2,6.0,53,5220204.0,,,1,2002-10-13 00:00:00 -17782,696,7,0,4.0,4,3.0,3,4.0,53,5242990.0,,,1,2002-10-13 00:00:00 -17783,696,30,2,6.0,6,4.0,4,3.0,53,5255973.0,,,1,2002-10-13 00:00:00 -17784,696,65,6,25.0,18,,20,0.0,0,,,,73,2002-10-13 00:00:00 -17785,696,17,3,15.0,10,6.0,6,1.0,52,,,,11,2002-10-13 00:00:00 -17786,696,1,14,7.0,12,7.0,7,0.0,52,,,,11,2002-10-13 00:00:00 -17787,696,62,6,24.0,13,8.0,8,0.0,52,,,,11,2002-10-13 00:00:00 -17788,696,10,16,10.0,7,5.0,5,2.0,53,5302392.0,,,1,2002-10-13 00:00:00 -17789,697,41,18,15.0,18,,13,0.0,52,,,,22,2003-03-09 00:00:00 -17790,697,21,5,2.0,2,,20,0.0,5,,,,3,2003-03-09 00:00:00 -17791,697,51,16,12.0,17,,19,0.0,6,,,,3,2003-03-09 00:00:00 -17792,697,42,6,21.0,16,,18,0.0,7,,,,20,2003-03-09 00:00:00 -17793,697,16,18,14.0,14,,17,0.0,15,,,,22,2003-03-09 00:00:00 -17794,697,50,17,18.0,19,,16,0.0,16,,,,21,2003-03-09 00:00:00 -17795,697,1,14,9.0,7,,15,0.0,20,,,,22,2003-03-09 00:00:00 -17796,697,43,6,20.0,5,,14,0.0,31,,,,32,2003-03-09 00:00:00 -17797,697,20,16,11.0,13,,12,0.0,52,,,,6,2003-03-09 00:00:00 -17798,697,30,2,3.0,3,2.0,2,8.0,58,5690775.0,,,1,2003-03-09 00:00:00 -17799,697,17,15,17.0,8,10.0,10,0.0,58,5748074.0,,,1,2003-03-09 00:00:00 -17800,697,49,17,19.0,20,11.0,11,0.0,57,,,,11,2003-03-09 00:00:00 -17801,697,7,0,6.0,15,3.0,3,6.0,58,5691292.0,,,1,2003-03-09 00:00:00 -17802,697,29,5,1.0,1,4.0,4,5.0,58,5691582.0,,,1,2003-03-09 00:00:00 -17803,697,14,3,7.0,12,5.0,5,4.0,58,5720901.0,,,1,2003-03-09 00:00:00 -17804,697,13,0,5.0,11,1.0,1,10.0,58,5682100.0,,,1,2003-03-09 00:00:00 -17805,697,3,3,8.0,10,7.0,7,2.0,58,5727174.0,,,1,2003-03-09 00:00:00 -17806,697,22,2,4.0,9,8.0,8,1.0,58,5727845.0,,,1,2003-03-09 00:00:00 -17807,697,34,15,16.0,6,9.0,9,0.0,58,5747636.0,,,1,2003-03-09 00:00:00 -17808,697,48,14,10.0,4,6.0,6,3.0,58,5726028.0,,,1,2003-03-09 00:00:00 -17809,698,49,17,19.0,18,13.0,13,0.0,52,,,,14,2003-03-23 00:00:00 -17810,698,34,15,16.0,12,,20,0.0,0,,,,10,2003-03-23 00:00:00 -17811,698,20,16,11.0,14,,19,0.0,0,,,,10,2003-03-23 00:00:00 -17812,698,13,0,5.0,4,,18,0.0,2,,,,10,2003-03-23 00:00:00 -17813,698,43,6,20.0,10,,17,0.0,12,,,,32,2003-03-23 00:00:00 -17814,698,16,18,14.0,16,,16,0.0,35,,,,5,2003-03-23 00:00:00 -17815,698,50,17,18.0,19,,15,0.0,41,,,,26,2003-03-23 00:00:00 -17816,698,41,18,15.0,15,,14,0.0,42,,,,20,2003-03-23 00:00:00 -17817,698,30,2,3.0,8,12.0,12,0.0,53,,,,13,2003-03-23 00:00:00 -17818,698,7,0,6.0,7,1.0,1,10.0,56,5542195.0,,,1,2003-03-23 00:00:00 -17819,698,51,16,12.0,20,10.0,10,0.0,55,,,,11,2003-03-23 00:00:00 -17820,698,21,5,2.0,5,2.0,2,8.0,56,5581481.0,,,1,2003-03-23 00:00:00 -17821,698,3,3,8.0,1,3.0,3,6.0,56,5606202.0,,,1,2003-03-23 00:00:00 -17822,698,22,2,4.0,17,4.0,4,5.0,56,5630221.0,,,1,2003-03-23 00:00:00 -17823,698,14,3,7.0,2,5.0,5,4.0,55,,,,11,2003-03-23 00:00:00 -17824,698,42,6,21.0,11,11.0,11,0.0,55,,,,11,2003-03-23 00:00:00 -17825,698,17,15,17.0,9,7.0,7,2.0,55,,,,11,2003-03-23 00:00:00 -17826,698,1,14,9.0,6,8.0,8,1.0,55,,,,11,2003-03-23 00:00:00 -17827,698,48,14,10.0,13,9.0,9,0.0,55,,,,11,2003-03-23 00:00:00 -17828,698,29,5,1.0,3,6.0,6,3.0,55,,,,11,2003-03-23 00:00:00 -17829,699,17,15,17.0,11,,12,0.0,33,,,,3,2003-04-06 00:00:00 -17830,699,50,17,18.0,20,,19,0.0,16,,,,20,2003-04-06 00:00:00 -17831,699,51,16,12.0,16,,18,0.0,18,,,,22,2003-04-06 00:00:00 -17832,699,43,6,20.0,15,,17,0.0,18,,,,4,2003-04-06 00:00:00 -17833,699,41,18,15.0,17,,16,0.0,25,,,,3,2003-04-06 00:00:00 -17834,699,30,2,3.0,9,,15,0.0,25,,,,3,2003-04-06 00:00:00 -17835,699,29,5,1.0,7,,14,0.0,27,,,,3,2003-04-06 00:00:00 -17836,699,49,17,19.0,19,,13,0.0,31,,,,20,2003-04-06 00:00:00 -17837,699,1,14,9.0,12,,20,0.0,8,,,,5,2003-04-06 00:00:00 -17838,699,21,5,2.0,1,,11,0.0,47,,,,69,2003-04-06 00:00:00 -17839,699,16,18,14.0,3,9.0,9,0.0,53,,,,3,2003-04-06 00:00:00 -17840,699,14,3,7.0,5,8.0,8,1.0,54,5524127.0,,,1,2003-04-06 00:00:00 -17841,699,22,2,4.0,6,7.0,7,2.0,54,5516726.0,,,1,2003-04-06 00:00:00 -17842,699,34,15,16.0,13,6.0,6,3.0,54,5494254.0,,,1,2003-04-06 00:00:00 -17843,699,48,14,10.0,14,5.0,5,4.0,54,5486842.0,,,1,2003-04-06 00:00:00 -17844,699,13,0,5.0,2,4.0,4,5.0,54,5486296.0,,,1,2003-04-06 00:00:00 -17845,699,3,3,8.0,10,3.0,3,6.0,54,5484548.0,,,1,2003-04-06 00:00:00 -17846,699,7,0,6.0,4,2.0,2,8.0,54,5479145.0,,,1,2003-04-06 00:00:00 -17847,699,20,16,11.0,8,1.0,1,10.0,54,5478200.0,,,1,2003-04-06 00:00:00 -17848,699,42,6,21.0,18,10.0,10,0.0,53,,,,11,2003-04-06 00:00:00 -17849,700,41,18,15.0,15,14.0,14,0.0,60,,,,12,2003-04-20 00:00:00 -17850,700,20,16,11.0,17,15.0,15,0.0,57,,,,15,2003-04-20 00:00:00 -17851,700,16,18,14.0,5,,16,0.0,54,,,,30,2003-04-20 00:00:00 -17852,700,34,15,16.0,7,,20,0.0,19,,,,5,2003-04-20 00:00:00 -17853,700,51,16,12.0,19,,17,0.0,51,,,,70,2003-04-20 00:00:00 -17854,700,49,17,19.0,20,,18,0.0,38,,,,10,2003-04-20 00:00:00 -17855,700,50,17,18.0,18,,19,0.0,23,,,,71,2003-04-20 00:00:00 -17856,700,14,3,7.0,16,13.0,13,0.0,61,,,,11,2003-04-20 00:00:00 -17857,700,42,6,21.0,13,12.0,12,0.0,61,,,,11,2003-04-20 00:00:00 -17858,700,13,0,5.0,12,5.0,5,4.0,62,5301469.0,,,1,2003-04-20 00:00:00 -17859,700,1,14,9.0,11,10.0,10,0.0,61,,,,11,2003-04-20 00:00:00 -17860,700,29,5,1.0,1,1.0,1,10.0,62,5292058.0,,,1,2003-04-20 00:00:00 -17861,700,7,0,6.0,6,2.0,2,8.0,62,5293940.0,,,1,2003-04-20 00:00:00 -17862,700,21,5,2.0,3,3.0,3,6.0,62,5294349.0,,,1,2003-04-20 00:00:00 -17863,700,22,2,4.0,2,4.0,4,5.0,62,5300861.0,,,1,2003-04-20 00:00:00 -17864,700,48,14,10.0,14,11.0,11,0.0,61,,,,11,2003-04-20 00:00:00 -17865,700,30,2,3.0,4,7.0,7,2.0,62,5337329.0,,,1,2003-04-20 00:00:00 -17866,700,17,15,17.0,9,8.0,8,1.0,61,,,,11,2003-04-20 00:00:00 -17867,700,43,6,20.0,10,9.0,9,0.0,61,,,,11,2003-04-20 00:00:00 -17868,700,3,3,8.0,8,6.0,6,3.0,62,5335747.0,,,1,2003-04-20 00:00:00 -17869,701,20,16,11.0,17,,13,0.0,43,,,,5,2003-05-04 00:00:00 -17870,701,7,0,6.0,20,,20,0.0,0,,,,4,2003-05-04 00:00:00 -17871,701,41,18,15.0,16,,19,0.0,0,,,,72,2003-05-04 00:00:00 -17872,701,14,3,7.0,4,,18,0.0,0,,,,4,2003-05-04 00:00:00 -17873,701,34,15,16.0,11,,17,0.0,12,,,,10,2003-05-04 00:00:00 -17874,701,13,0,5.0,8,,16,0.0,17,,,,4,2003-05-04 00:00:00 -17875,701,48,14,10.0,10,,15,0.0,38,,,,22,2003-05-04 00:00:00 -17876,701,43,6,20.0,6,,14,0.0,41,,,,6,2003-05-04 00:00:00 -17877,701,49,17,19.0,19,12.0,12,0.0,62,,,,13,2003-05-04 00:00:00 -17878,701,50,17,18.0,18,11.0,11,0.0,63,,,,12,2003-05-04 00:00:00 -17879,701,1,14,9.0,14,10.0,10,0.0,63,,,,12,2003-05-04 00:00:00 -17880,701,17,15,17.0,5,9.0,9,0.0,63,,,,12,2003-05-04 00:00:00 -17881,701,51,16,12.0,15,8.0,8,1.0,63,,,,12,2003-05-04 00:00:00 -17882,701,16,18,14.0,12,7.0,7,2.0,64,,,,11,2003-05-04 00:00:00 -17883,701,42,6,21.0,13,6.0,6,3.0,64,,,,11,2003-05-04 00:00:00 -17884,701,22,2,4.0,7,5.0,5,4.0,64,,,,11,2003-05-04 00:00:00 -17885,701,30,2,3.0,9,4.0,4,5.0,65,5688933.0,,,1,2003-05-04 00:00:00 -17886,701,21,5,2.0,2,3.0,3,6.0,65,5644933.0,,,1,2003-05-04 00:00:00 -17887,701,3,3,8.0,3,2.0,2,8.0,65,5632633.0,,,1,2003-05-04 00:00:00 -17888,701,29,5,1.0,1,1.0,1,10.0,65,5626933.0,,,1,2003-05-04 00:00:00 -17889,702,50,17,18.0,18,13.0,13,0.0,67,,,,12,2003-05-18 00:00:00 -17890,702,20,16,11.0,9,,14,0.0,60,,,,69,2003-05-18 00:00:00 -17891,702,3,3,8.0,19,,16,0.0,44,,,,5,2003-05-18 00:00:00 -17892,702,48,14,10.0,15,,20,0.0,0,,,,8,2003-05-18 00:00:00 -17893,702,43,6,20.0,11,,18,0.0,6,,,,22,2003-05-18 00:00:00 -17894,702,49,17,19.0,20,,19,0.0,0,,,,8,2003-05-18 00:00:00 -17895,702,34,15,16.0,12,12.0,12,0.0,68,,,,11,2003-05-18 00:00:00 -17896,702,30,2,3.0,3,,17,0.0,32,,,,5,2003-05-18 00:00:00 -17897,702,51,16,12.0,16,11.0,11,0.0,68,,,,11,2003-05-18 00:00:00 -17898,702,1,14,9.0,4,,15,0.0,46,,,,5,2003-05-18 00:00:00 -17899,702,41,18,15.0,8,9.0,9,0.0,68,,,,11,2003-05-18 00:00:00 -17900,702,14,3,7.0,6,8.0,8,1.0,68,,,,11,2003-05-18 00:00:00 -17901,702,16,18,14.0,17,7.0,7,2.0,68,,,,11,2003-05-18 00:00:00 -17902,702,22,2,4.0,10,6.0,6,3.0,68,,,,11,2003-05-18 00:00:00 -17903,702,13,0,5.0,14,5.0,5,4.0,69,5104628.0,,,1,2003-05-18 00:00:00 -17904,702,17,15,17.0,7,4.0,4,5.0,69,5087131.0,,,1,2003-05-18 00:00:00 -17905,702,21,5,2.0,5,3.0,3,6.0,69,5048839.0,,,1,2003-05-18 00:00:00 -17906,702,7,0,6.0,2,2.0,2,8.0,69,5048250.0,,,1,2003-05-18 00:00:00 -17907,702,29,5,1.0,1,1.0,1,10.0,69,5044888.0,,,1,2003-05-18 00:00:00 -17908,702,42,6,21.0,13,10.0,10,0.0,68,,,,11,2003-05-18 00:00:00 -17909,703,43,6,20.0,17,13.0,13,0.0,74,,,,14,2003-06-01 00:00:00 -17910,703,34,15,16.0,11,,14,0.0,63,,,,5,2003-06-01 00:00:00 -17911,703,49,17,19.0,18,,16,0.0,28,,,,69,2003-06-01 00:00:00 -17912,703,17,15,17.0,20,,20,0.0,0,,,,73,2003-06-01 00:00:00 -17913,703,41,18,15.0,13,,18,0.0,10,,,,10,2003-06-01 00:00:00 -17914,703,48,14,10.0,15,,19,0.0,0,,,,3,2003-06-01 00:00:00 -17915,703,51,16,12.0,16,12.0,12,0.0,76,,,,12,2003-06-01 00:00:00 -17916,703,16,18,14.0,9,,17,0.0,16,,,,9,2003-06-01 00:00:00 -17917,703,1,14,9.0,14,11.0,11,0.0,76,,,,12,2003-06-01 00:00:00 -17918,703,50,17,18.0,19,,15,0.0,29,,,,69,2003-06-01 00:00:00 -17919,703,42,6,21.0,10,9.0,9,0.0,77,,,,11,2003-06-01 00:00:00 -17920,703,20,16,11.0,12,10.0,10,0.0,77,,,,11,2003-06-01 00:00:00 -17921,703,7,0,6.0,2,2.0,2,8.0,78,6139612.0,,,1,2003-06-01 00:00:00 -17922,703,29,5,1.0,5,3.0,3,6.0,78,6140730.0,,,1,2003-06-01 00:00:00 -17923,703,22,2,4.0,1,4.0,4,5.0,78,6167528.0,,,1,2003-06-01 00:00:00 -17924,703,30,2,3.0,3,1.0,1,10.0,78,6139010.0,,,1,2003-06-01 00:00:00 -17925,703,14,3,7.0,4,6.0,6,3.0,78,6179982.0,,,1,2003-06-01 00:00:00 -17926,703,13,0,5.0,6,7.0,7,2.0,78,6180237.0,,,1,2003-06-01 00:00:00 -17927,703,21,5,2.0,7,8.0,8,1.0,78,6192276.0,,,1,2003-06-01 00:00:00 -17928,703,3,3,8.0,8,5.0,5,4.0,78,6175261.0,,,1,2003-06-01 00:00:00 -17929,704,42,6,21.0,9,11.0,11,0.0,64,,,,16,2003-06-15 00:00:00 -17930,704,51,16,12.0,19,,18,0.0,20,,,,5,2003-06-15 00:00:00 -17931,704,14,3,7.0,8,,16,0.0,22,,,,3,2003-06-15 00:00:00 -17932,704,1,14,9.0,12,,15,0.0,47,,,,5,2003-06-15 00:00:00 -17933,704,13,0,5.0,11,,14,0.0,47,,,,6,2003-06-15 00:00:00 -17934,704,17,15,17.0,17,,13,0.0,51,,,,6,2003-06-15 00:00:00 -17935,704,50,17,18.0,18,,12,0.0,60,,,,6,2003-06-15 00:00:00 -17936,704,41,18,15.0,13,10.0,10,0.0,64,,,,14,2003-06-15 00:00:00 -17937,704,21,5,2.0,5,5.0,5,4.0,70,5537852.0,,,1,2003-06-15 00:00:00 -17938,704,43,6,20.0,7,8.0,8,1.0,69,,,,11,2003-06-15 00:00:00 -17939,704,16,18,14.0,6,7.0,7,2.0,69,,,,11,2003-06-15 00:00:00 -17940,704,7,0,6.0,20,6.0,6,3.0,70,5544093.0,,,1,2003-06-15 00:00:00 -17941,704,3,3,8.0,4,4.0,4,5.0,70,5478072.0,,,1,2003-06-15 00:00:00 -17942,704,30,2,3.0,2,3.0,3,6.0,70,5474946.0,,,1,2003-06-15 00:00:00 -17943,704,22,2,4.0,1,2.0,2,8.0,70,5474375.0,,,1,2003-06-15 00:00:00 -17944,704,29,5,1.0,3,1.0,1,10.0,70,5473591.0,,,1,2003-06-15 00:00:00 -17945,704,49,17,19.0,15,9.0,9,0.0,68,,,,12,2003-06-15 00:00:00 -17946,704,34,15,16.0,14,,19,0.0,14,,,,23,2003-06-15 00:00:00 -17947,704,20,16,11.0,16,,17,0.0,20,,,,6,2003-06-15 00:00:00 -17948,704,48,14,10.0,10,,20,0.0,6,,,,40,2003-06-15 00:00:00 -17949,705,22,2,4.0,3,1.0,1,10.0,60,5683622.0,,,1,2003-06-29 00:00:00 -17950,705,7,0,6.0,1,,20,0.0,25,,,,5,2003-06-29 00:00:00 -17951,705,43,6,20.0,7,,19,0.0,37,,,,20,2003-06-29 00:00:00 -17952,705,14,3,7.0,6,,18,0.0,37,,,,32,2003-06-29 00:00:00 -17953,705,34,15,16.0,17,,17,0.0,51,,,,6,2003-06-29 00:00:00 -17954,705,42,6,21.0,10,,16,0.0,53,,,,5,2003-06-29 00:00:00 -17955,705,49,17,19.0,18,14.0,14,0.0,57,,,,13,2003-06-29 00:00:00 -17956,705,50,17,18.0,19,13.0,13,0.0,58,,,,12,2003-06-29 00:00:00 -17957,705,20,16,11.0,13,12.0,12,0.0,58,,,,12,2003-06-29 00:00:00 -17958,705,13,0,5.0,9,15.0,15,0.0,56,,,,14,2003-06-29 00:00:00 -17959,705,41,18,15.0,16,10.0,10,0.0,59,,,,11,2003-06-29 00:00:00 -17960,705,51,16,12.0,14,11.0,11,0.0,58,,,,12,2003-06-29 00:00:00 -17961,705,21,5,2.0,5,3.0,3,6.0,60,5723295.0,,,1,2003-06-29 00:00:00 -17962,705,3,3,8.0,8,4.0,4,5.0,60,5749353.0,,,1,2003-06-29 00:00:00 -17963,705,29,5,1.0,2,5.0,5,4.0,60,5749784.0,,,1,2003-06-29 00:00:00 -17964,705,30,2,3.0,4,2.0,2,8.0,60,5700443.0,,,1,2003-06-29 00:00:00 -17965,705,17,15,17.0,12,7.0,7,2.0,59,,,,11,2003-06-29 00:00:00 -17966,705,1,14,9.0,20,8.0,8,1.0,59,,,,11,2003-06-29 00:00:00 -17967,705,48,14,10.0,15,9.0,9,0.0,59,,,,11,2003-06-29 00:00:00 -17968,705,16,18,14.0,11,6.0,6,3.0,59,,,,11,2003-06-29 00:00:00 -17969,706,48,14,10.0,16,12.0,12,0.0,68,,,,12,2003-07-06 00:00:00 -17970,706,17,15,17.0,14,,20,0.0,23,,,,74,2003-07-06 00:00:00 -17971,706,20,16,11.0,17,,19,0.0,42,,,,5,2003-07-06 00:00:00 -17972,706,3,3,8.0,7,,18,0.0,43,,,,5,2003-07-06 00:00:00 -17973,706,14,3,7.0,6,,17,0.0,45,,,,5,2003-07-06 00:00:00 -17974,706,49,17,19.0,19,16.0,16,0.0,66,,,,14,2003-07-06 00:00:00 -17975,706,50,17,18.0,20,14.0,14,0.0,67,,,,13,2003-07-06 00:00:00 -17976,706,1,14,9.0,15,13.0,13,0.0,68,,,,12,2003-07-06 00:00:00 -17977,706,42,6,21.0,13,11.0,11,0.0,69,,,,11,2003-07-06 00:00:00 -17978,706,51,16,12.0,18,15.0,15,0.0,67,,,,13,2003-07-06 00:00:00 -17979,706,34,15,16.0,12,9.0,9,0.0,69,,,,11,2003-07-06 00:00:00 -17980,706,30,2,3.0,2,2.0,2,8.0,70,5463026.0,,,1,2003-07-06 00:00:00 -17981,706,29,5,1.0,3,3.0,3,6.0,70,5468781.0,,,1,2003-07-06 00:00:00 -17982,706,7,0,6.0,4,4.0,4,5.0,70,5487260.0,,,1,2003-07-06 00:00:00 -17983,706,13,0,5.0,5,5.0,5,4.0,70,5489502.0,,,1,2003-07-06 00:00:00 -17984,706,41,18,15.0,11,10.0,10,0.0,69,,,,11,2003-07-06 00:00:00 -17985,706,22,2,4.0,1,1.0,1,10.0,70,5449213.0,,,1,2003-07-06 00:00:00 -17986,706,21,5,2.0,8,7.0,7,2.0,69,,,,11,2003-07-06 00:00:00 -17987,706,43,6,20.0,10,8.0,8,1.0,69,,,,11,2003-07-06 00:00:00 -17988,706,16,18,14.0,9,6.0,6,3.0,70,5515593.0,,,1,2003-07-06 00:00:00 -17989,707,48,14,10.0,14,12.0,12,0.0,60,5383118.0,,,1,2003-07-20 00:00:00 -17990,707,20,16,11.0,15,,19,0.0,44,,,,22,2003-07-20 00:00:00 -17991,707,3,3,8.0,8,,18,0.0,52,,,,6,2003-07-20 00:00:00 -17992,707,1,14,9.0,16,17.0,17,0.0,58,,,,12,2003-07-20 00:00:00 -17993,707,50,17,18.0,18,16.0,16,0.0,58,,,,12,2003-07-20 00:00:00 -17994,707,49,17,19.0,19,15.0,15,0.0,58,,,,12,2003-07-20 00:00:00 -17995,707,16,18,14.0,11,14.0,14,0.0,59,,,,11,2003-07-20 00:00:00 -17996,707,51,16,12.0,17,13.0,13,0.0,59,,,,11,2003-07-20 00:00:00 -17997,707,41,18,15.0,10,,20,0.0,32,,,,5,2003-07-20 00:00:00 -17998,707,43,6,20.0,13,11.0,11,0.0,60,5382761.0,,,1,2003-07-20 00:00:00 -17999,707,22,2,4.0,4,9.0,9,0.0,60,5375586.0,,,1,2003-07-20 00:00:00 -18000,707,17,15,17.0,20,8.0,8,1.0,60,5363032.0,,,1,2003-07-20 00:00:00 -18001,707,42,6,21.0,6,7.0,7,2.0,60,5362639.0,,,1,2003-07-20 00:00:00 -18002,707,14,3,7.0,2,6.0,6,3.0,60,5360621.0,,,1,2003-07-20 00:00:00 -18003,707,13,0,5.0,12,5.0,5,4.0,60,5354381.0,,,1,2003-07-20 00:00:00 -18004,707,29,5,1.0,5,4.0,4,5.0,60,5343202.0,,,1,2003-07-20 00:00:00 -18005,707,7,0,6.0,3,3.0,3,6.0,60,5328210.0,,,1,2003-07-20 00:00:00 -18006,707,30,2,3.0,7,2.0,2,8.0,60,5323016.0,,,1,2003-07-20 00:00:00 -18007,707,21,5,2.0,1,1.0,1,10.0,60,5317554.0,,,1,2003-07-20 00:00:00 -18008,707,34,15,16.0,9,10.0,10,0.0,60,5381123.0,,,1,2003-07-20 00:00:00 -18009,708,49,17,19.0,19,,14,0.0,23,,,,9,2003-08-03 00:00:00 -18010,708,50,18,15.0,16,,15,0.0,6,,,,6,2003-08-03 00:00:00 -18011,708,22,2,4.0,2,,16,0.0,1,,,,3,2003-08-03 00:00:00 -18012,708,20,16,11.0,13,13.0,13,0.0,60,,,,5,2003-08-03 00:00:00 -18013,708,21,5,2.0,3,,18,0.0,0,,,,3,2003-08-03 00:00:00 -18014,708,7,0,6.0,5,,19,0.0,0,,,,3,2003-08-03 00:00:00 -18015,708,51,16,12.0,18,,20,0.0,0,,,,3,2003-08-03 00:00:00 -18016,708,48,14,10.0,14,,17,0.0,1,,,,3,2003-08-03 00:00:00 -18017,708,52,17,18.0,20,12.0,12,0.0,62,,,,15,2003-08-03 00:00:00 -18018,708,43,6,20.0,7,5.0,5,4.0,66,,,,11,2003-08-03 00:00:00 -18019,708,1,14,9.0,15,10.0,10,0.0,65,,,,12,2003-08-03 00:00:00 -18020,708,13,0,5.0,10,2.0,2,8.0,67,5394228.0,,,1,2003-08-03 00:00:00 -18021,708,14,3,7.0,4,3.0,3,6.0,67,5397829.0,,,1,2003-08-03 00:00:00 -18022,708,3,3,8.0,8,4.0,4,5.0,67,5398113.0,,,1,2003-08-03 00:00:00 -18023,708,30,2,3.0,1,1.0,1,10.0,67,5328769.0,,,1,2003-08-03 00:00:00 -18024,708,16,18,14.0,11,11.0,11,0.0,64,,,,3,2003-08-03 00:00:00 -18025,708,29,5,1.0,6,7.0,7,2.0,66,,,,11,2003-08-03 00:00:00 -18026,708,17,15,17.0,17,8.0,8,1.0,66,,,,11,2003-08-03 00:00:00 -18027,708,34,15,16.0,13,9.0,9,0.0,65,,,,12,2003-08-03 00:00:00 -18028,708,42,6,21.0,9,6.0,6,3.0,66,,,,11,2003-08-03 00:00:00 -18029,709,52,17,18.0,20,13.0,13,0.0,66,,,,14,2003-08-24 00:00:00 -18030,709,34,15,16.0,16,,20,0.0,14,,,,9,2003-08-24 00:00:00 -18031,709,21,5,2.0,5,,19,0.0,19,,,,22,2003-08-24 00:00:00 -18032,709,20,16,11.0,13,,18,0.0,28,,,,5,2003-08-24 00:00:00 -18033,709,43,6,20.0,10,,17,0.0,33,,,,6,2003-08-24 00:00:00 -18034,709,46,16,12.0,19,,16,0.0,34,,,,5,2003-08-24 00:00:00 -18035,709,50,18,15.0,12,,15,0.0,42,,,,5,2003-08-24 00:00:00 -18036,709,48,14,10.0,17,,14,0.0,47,,,,60,2003-08-24 00:00:00 -18037,709,49,17,19.0,18,12.0,12,0.0,67,,,,13,2003-08-24 00:00:00 -18038,709,42,6,21.0,15,11.0,11,0.0,68,,,,12,2003-08-24 00:00:00 -18039,709,17,15,17.0,14,10.0,10,0.0,69,,,,11,2003-08-24 00:00:00 -18040,709,7,0,6.0,7,2.0,2,8.0,70,5958228.0,,,1,2003-08-24 00:00:00 -18041,709,30,2,3.0,4,3.0,3,6.0,70,5975997.0,,,1,2003-08-24 00:00:00 -18042,709,22,2,4.0,2,4.0,4,5.0,70,5977080.0,,,1,2003-08-24 00:00:00 -18043,709,13,0,5.0,9,5.0,5,4.0,70,5997995.0,,,1,2003-08-24 00:00:00 -18044,709,3,3,8.0,1,1.0,1,10.0,70,5941460.0,,,1,2003-08-24 00:00:00 -18045,709,14,3,7.0,6,7.0,7,2.0,69,,,,11,2003-08-24 00:00:00 -18046,709,29,5,1.0,8,8.0,8,1.0,69,,,,11,2003-08-24 00:00:00 -18047,709,1,14,9.0,11,9.0,9,0.0,69,,,,11,2003-08-24 00:00:00 -18048,709,16,18,14.0,3,6.0,6,3.0,70,6014103.0,,,1,2003-08-24 00:00:00 -18049,710,48,14,10.0,14,13.0,13,0.0,50,,,,13,2003-09-14 00:00:00 -18050,710,14,3,7.0,6,,20,0.0,0,,,,9,2003-09-14 00:00:00 -18051,710,50,18,15.0,15,,19,0.0,2,,,,6,2003-09-14 00:00:00 -18052,710,42,6,21.0,12,,18,0.0,3,,,,27,2003-09-14 00:00:00 -18053,710,17,15,17.0,7,,17,0.0,24,,,,6,2003-09-14 00:00:00 -18054,710,49,17,19.0,17,,16,0.0,27,,,,44,2003-09-14 00:00:00 -18055,710,43,6,20.0,9,,15,0.0,35,,,,23,2003-09-14 00:00:00 -18056,710,13,0,5.0,8,,14,0.0,45,,,,32,2003-09-14 00:00:00 -18057,710,52,17,18.0,19,12.0,12,0.0,51,,,,12,2003-09-14 00:00:00 -18058,710,29,5,1.0,1,1.0,1,10.0,53,4459838.0,,,1,2003-09-14 00:00:00 -18059,710,20,16,11.0,13,10.0,10,0.0,52,,,,11,2003-09-14 00:00:00 -18060,710,1,14,9.0,16,9.0,9,0.0,52,,,,11,2003-09-14 00:00:00 -18061,710,3,3,8.0,20,8.0,8,1.0,52,,,,11,2003-09-14 00:00:00 -18062,710,16,18,14.0,11,7.0,7,2.0,52,,,,11,2003-09-14 00:00:00 -18063,710,34,15,16.0,10,6.0,6,3.0,52,,,,11,2003-09-14 00:00:00 -18064,710,47,2,4.0,5,5.0,5,4.0,53,4487729.0,,,1,2003-09-14 00:00:00 -18065,710,7,0,6.0,4,4.0,4,5.0,53,4472672.0,,,1,2003-09-14 00:00:00 -18066,710,21,5,2.0,3,3.0,3,6.0,53,4471673.0,,,1,2003-09-14 00:00:00 -18067,710,30,2,3.0,2,2.0,2,8.0,53,4465132.0,,,1,2003-09-14 00:00:00 -18068,710,46,16,12.0,18,11.0,11,0.0,51,,,,12,2003-09-14 00:00:00 -18069,711,51,16,12.0,18,,13,0.0,48,,,,20,2003-09-28 00:00:00 -18070,711,13,0,5.0,8,,14,0.0,45,,,,6,2003-09-28 00:00:00 -18071,711,3,3,8.0,6,,15,0.0,44,,,,5,2003-09-28 00:00:00 -18072,711,34,15,16.0,12,,12,0.0,63,,,,5,2003-09-28 00:00:00 -18073,711,43,6,20.0,3,,17,0.0,27,,,,3,2003-09-28 00:00:00 -18074,711,16,18,14.0,14,,18,0.0,21,,,,3,2003-09-28 00:00:00 -18075,711,22,2,4.0,5,,19,0.0,21,,,,3,2003-09-28 00:00:00 -18076,711,17,15,17.0,11,,16,0.0,41,,,,5,2003-09-28 00:00:00 -18077,711,52,17,18.0,20,11.0,11,0.0,69,,,,14,2003-09-28 00:00:00 -18078,711,21,5,2.0,2,,20,0.0,2,,,,4,2003-09-28 00:00:00 -18079,711,42,6,21.0,9,9.0,9,0.0,71,,,,12,2003-09-28 00:00:00 -18080,711,29,5,1.0,7,1.0,1,10.0,73,5615997.0,,,1,2003-09-28 00:00:00 -18081,711,7,0,6.0,1,2.0,2,8.0,73,5634255.0,,,1,2003-09-28 00:00:00 -18082,711,48,14,10.0,15,3.0,3,6.0,73,5653961.0,,,1,2003-09-28 00:00:00 -18083,711,14,3,7.0,10,4.0,4,5.0,73,5664326.0,,,1,2003-09-28 00:00:00 -18084,711,49,17,19.0,19,10.0,10,0.0,69,,,,14,2003-09-28 00:00:00 -18085,711,30,2,3.0,4,6.0,6,3.0,72,,,,11,2003-09-28 00:00:00 -18086,711,20,16,11.0,17,7.0,7,2.0,72,,,,11,2003-09-28 00:00:00 -18087,711,50,18,15.0,16,8.0,8,1.0,71,,,,12,2003-09-28 00:00:00 -18088,711,1,14,9.0,13,5.0,5,4.0,73,5672400.0,,,1,2003-09-28 00:00:00 -18089,712,51,16,12.0,15,14.0,14,0.0,51,,,,12,2003-10-12 00:00:00 -18090,712,30,2,3.0,2,,20,0.0,9,,,,9,2003-10-12 00:00:00 -18091,712,48,14,10.0,12,,19,0.0,9,,,,5,2003-10-12 00:00:00 -18092,712,3,3,8.0,5,,18,0.0,17,,,,5,2003-10-12 00:00:00 -18093,712,20,16,11.0,16,,17,0.0,33,,,,60,2003-10-12 00:00:00 -18094,712,52,17,18.0,18,16.0,16,0.0,50,,,,13,2003-10-12 00:00:00 -18095,712,49,17,19.0,17,15.0,15,0.0,51,,,,12,2003-10-12 00:00:00 -18096,712,50,18,15.0,10,13.0,13,0.0,52,,,,11,2003-10-12 00:00:00 -18097,712,22,2,4.0,19,12.0,12,0.0,52,,,,11,2003-10-12 00:00:00 -18098,712,7,0,6.0,8,2.0,2,8.0,53,5122828.0,,,1,2003-10-12 00:00:00 -18099,712,43,6,20.0,4,10.0,10,0.0,53,5173587.0,,,1,2003-10-12 00:00:00 -18100,712,1,14,9.0,11,9.0,9,0.0,53,5171902.0,,,1,2003-10-12 00:00:00 -18101,712,29,5,1.0,14,8.0,8,1.0,53,5171230.0,,,1,2003-10-12 00:00:00 -18102,712,42,6,21.0,3,7.0,7,2.0,53,5168537.0,,,1,2003-10-12 00:00:00 -18103,712,10,15,16.0,13,6.0,6,3.0,53,5163435.0,,,1,2003-10-12 00:00:00 -18104,712,14,3,7.0,20,5.0,5,4.0,53,5146012.0,,,1,2003-10-12 00:00:00 -18105,712,17,15,17.0,9,4.0,4,5.0,53,5144849.0,,,1,2003-10-12 00:00:00 -18106,712,13,0,5.0,7,3.0,3,6.0,53,5123357.0,,,1,2003-10-12 00:00:00 -18107,712,16,18,14.0,6,11.0,11,0.0,53,5182748.0,,,1,2003-10-12 00:00:00 -18108,712,21,5,2.0,1,1.0,1,10.0,53,5111743.0,,,1,2003-10-12 00:00:00 -18109,713,43,6,17.0,18,13.0,13,0.0,56,,35.0,14.0,12,2004-03-07 00:00:00 -18110,713,44,16,19.0,16,14.0,14,0.0,55,,15.0,18.0,13,2004-03-07 00:00:00 -18111,713,12,14,12.0,11,,15,0.0,44,,11.0,12.0,5,2004-03-07 00:00:00 -18112,713,42,6,16.0,13,12.0,12,0.0,56,,41.0,15.0,12,2004-03-07 00:00:00 -18113,713,45,17,20.0,20,,17,0.0,43,,10.0,19.0,62,2004-03-07 00:00:00 -18114,713,16,18,14.0,6,,18,0.0,29,,15.0,6.0,7,2004-03-07 00:00:00 -18115,713,46,17,21.0,17,,19,0.0,13,,8.0,20.0,10,2004-03-07 00:00:00 -18116,713,1,16,18.0,15,,16,0.0,43,,27.0,13.0,7,2004-03-07 00:00:00 -18117,713,31,18,15.0,19,11.0,11,0.0,56,,6.0,16.0,12,2004-03-07 00:00:00 -18118,713,7,0,6.0,10,,20,0.0,9,,7.0,17.0,5,2004-03-07 00:00:00 -18119,713,10,15,10.0,7,9.0,9,0.0,57,,43.0,8.0,11,2004-03-07 00:00:00 -18120,713,29,5,1.0,1,1.0,1,10.0,58,5055757.0,29.0,1.0,1,2004-03-07 00:00:00 -18121,713,21,5,2.0,2,2.0,2,8.0,58,5069362.0,8.0,2.0,1,2004-03-07 00:00:00 -18122,713,3,3,8.0,5,3.0,3,6.0,58,5090430.0,10.0,3.0,1,2004-03-07 00:00:00 -18123,713,22,2,4.0,8,4.0,4,5.0,58,5116180.0,11.0,5.0,1,2004-03-07 00:00:00 -18124,713,20,14,11.0,14,10.0,10,0.0,57,,39.0,10.0,11,2004-03-07 00:00:00 -18125,713,17,15,9.0,4,6.0,6,3.0,58,5126355.0,24.0,7.0,1,2004-03-07 00:00:00 -18126,713,14,3,7.0,9,7.0,7,2.0,57,,9.0,9.0,11,2004-03-07 00:00:00 -18127,713,13,0,5.0,12,8.0,8,1.0,57,,13.0,11.0,11,2004-03-07 00:00:00 -18128,713,30,2,3.0,3,5.0,5,4.0,58,5124293.0,42.0,4.0,1,2004-03-07 00:00:00 -18129,714,43,6,17.0,14,12.0,12,0.0,55,,23.0,11.0,11,2004-03-21 00:00:00 -18130,714,22,2,4.0,7,,19,0.0,27,,10.0,7.0,5,2004-03-21 00:00:00 -18131,714,1,16,18.0,15,,18,0.0,34,,15.0,17.0,7,2004-03-21 00:00:00 -18132,714,7,0,6.0,5,,17,0.0,40,,12.0,5.0,7,2004-03-21 00:00:00 -18133,714,46,17,21.0,17,16.0,16,0.0,52,,12.0,20.0,14,2004-03-21 00:00:00 -18134,714,10,15,10.0,20,15.0,15,0.0,52,,13.0,8.0,14,2004-03-21 00:00:00 -18135,714,45,17,20.0,16,14.0,14,0.0,53,,11.0,19.0,13,2004-03-21 00:00:00 -18136,714,44,16,19.0,18,13.0,13,0.0,54,,41.0,18.0,12,2004-03-21 00:00:00 -18137,714,20,14,11.0,12,11.0,11,0.0,55,,54.0,14.0,11,2004-03-21 00:00:00 -18138,714,16,18,14.0,2,,20,0.0,23,,9.0,15.0,20,2004-03-21 00:00:00 -18139,714,42,6,16.0,10,9.0,9,0.0,55,,22.0,12.0,11,2004-03-21 00:00:00 -18140,714,29,5,1.0,1,1.0,1,10.0,56,5467490.0,6.0,2.0,1,2004-03-21 00:00:00 -18141,714,30,2,3.0,4,2.0,2,8.0,56,5472512.0,28.0,1.0,1,2004-03-21 00:00:00 -18142,714,17,15,9.0,6,3.0,3,6.0,56,5479058.0,28.0,3.0,1,2004-03-21 00:00:00 -18143,714,21,5,2.0,3,4.0,4,5.0,56,5481105.0,7.0,6.0,1,2004-03-21 00:00:00 -18144,714,31,18,15.0,13,10.0,10,0.0,55,,12.0,16.0,11,2004-03-21 00:00:00 -18145,714,13,0,5.0,9,6.0,6,3.0,56,5520588.0,26.0,9.0,1,2004-03-21 00:00:00 -18146,714,3,3,8.0,19,7.0,7,2.0,56,5535367.0,7.0,10.0,1,2004-03-21 00:00:00 -18147,714,12,14,12.0,11,8.0,8,1.0,55,,7.0,13.0,11,2004-03-21 00:00:00 -18148,714,14,3,7.0,8,5.0,5,4.0,56,5504850.0,12.0,4.0,1,2004-03-21 00:00:00 -18149,715,20,14,11.0,11,11.0,11,0.0,56,,40.0,12.0,11,2004-04-04 00:00:00 -18150,715,46,17,21.0,20,,19,0.0,44,,24.0,19.0,5,2004-04-04 00:00:00 -18151,715,13,0,5.0,10,,18,0.0,50,,19.0,9.0,63,2004-04-04 00:00:00 -18152,715,45,17,20.0,17,17.0,17,0.0,52,,40.0,20.0,15,2004-04-04 00:00:00 -18153,715,44,16,19.0,15,16.0,16,0.0,55,,9.0,18.0,12,2004-04-04 00:00:00 -18154,715,1,16,18.0,18,15.0,15,0.0,56,,56.0,16.0,11,2004-04-04 00:00:00 -18155,715,31,18,15.0,12,14.0,14,0.0,56,,38.0,14.0,11,2004-04-04 00:00:00 -18156,715,30,2,3.0,3,13.0,13,0.0,56,,28.0,6.0,11,2004-04-04 00:00:00 -18157,715,12,14,12.0,13,12.0,12,0.0,56,,44.0,15.0,11,2004-04-04 00:00:00 -18158,715,7,0,6.0,19,,20,0.0,7,,7.0,17.0,5,2004-04-04 00:00:00 -18159,715,42,6,16.0,9,10.0,10,0.0,56,,23.0,11.0,11,2004-04-04 00:00:00 -18160,715,16,18,14.0,14,8.0,8,1.0,56,,19.0,10.0,11,2004-04-04 00:00:00 -18161,715,22,2,4.0,4,7.0,7,2.0,57,5373030.0,56.0,3.0,1,2004-04-04 00:00:00 -18162,715,3,3,8.0,16,6.0,6,3.0,57,5368031.0,39.0,2.0,1,2004-04-04 00:00:00 -18163,715,10,15,10.0,5,5.0,5,4.0,57,5367335.0,55.0,7.0,1,2004-04-04 00:00:00 -18164,715,14,3,7.0,7,4.0,4,5.0,57,5347089.0,24.0,8.0,1,2004-04-04 00:00:00 -18165,715,17,15,9.0,6,3.0,3,6.0,57,5341562.0,24.0,5.0,1,2004-04-04 00:00:00 -18166,715,21,5,2.0,2,2.0,2,8.0,57,5316242.0,29.0,4.0,1,2004-04-04 00:00:00 -18167,715,29,5,1.0,1,1.0,1,10.0,57,5314875.0,7.0,1.0,1,2004-04-04 00:00:00 -18168,715,43,6,17.0,8,9.0,9,0.0,56,,22.0,13.0,11,2004-04-04 00:00:00 -18169,716,16,18,14.0,8,13.0,13,0.0,61,,55.0,13.0,11,2004-04-25 00:00:00 -18170,716,31,18,15.0,14,14.0,14,0.0,60,,27.0,17.0,12,2004-04-25 00:00:00 -18171,716,46,17,21.0,19,15.0,15,0.0,58,,58.0,19.0,14,2004-04-25 00:00:00 -18172,716,10,15,10.0,7,16.0,16,0.0,56,,44.0,8.0,5,2004-04-25 00:00:00 -18173,716,44,16,19.0,15,,20,0.0,6,,6.0,18.0,9,2004-04-25 00:00:00 -18174,716,42,6,16.0,10,,18,0.0,32,,25.0,15.0,3,2004-04-25 00:00:00 -18175,716,45,17,20.0,17,,19,0.0,22,,11.0,20.0,23,2004-04-25 00:00:00 -18176,716,13,0,5.0,11,12.0,12,0.0,61,,42.0,14.0,11,2004-04-25 00:00:00 -18177,716,1,16,18.0,16,,17,0.0,48,,44.0,16.0,30,2004-04-25 00:00:00 -18178,716,43,6,17.0,13,11.0,11,0.0,61,,59.0,11.0,11,2004-04-25 00:00:00 -18179,716,14,3,7.0,9,5.0,5,4.0,62,5215886.0,11.0,4.0,1,2004-04-25 00:00:00 -18180,716,20,14,11.0,18,9.0,9,0.0,61,,60.0,10.0,11,2004-04-25 00:00:00 -18181,716,7,0,6.0,20,8.0,8,1.0,61,,39.0,9.0,11,2004-04-25 00:00:00 -18182,716,22,2,4.0,5,7.0,7,2.0,62,5235400.0,30.0,5.0,1,2004-04-25 00:00:00 -18183,716,21,5,2.0,4,6.0,6,3.0,62,5216353.0,31.0,7.0,1,2004-04-25 00:00:00 -18184,716,12,14,12.0,12,10.0,10,0.0,61,,36.0,12.0,11,2004-04-25 00:00:00 -18185,716,3,3,8.0,6,4.0,4,5.0,62,5203324.0,59.0,3.0,1,2004-04-25 00:00:00 -18186,716,30,2,3.0,3,3.0,3,6.0,62,5201287.0,27.0,6.0,1,2004-04-25 00:00:00 -18187,716,17,15,9.0,1,2.0,2,8.0,62,5189372.0,28.0,2.0,1,2004-04-25 00:00:00 -18188,716,29,5,1.0,2,1.0,1,10.0,62,5179670.0,10.0,1.0,1,2004-04-25 00:00:00 -18189,717,42,6,16.0,11,13.0,13,0.0,65,,29.0,14.0,11,2004-05-09 00:00:00 -18190,717,44,16,19.0,19,,14,0.0,51,,27.0,18.0,38,2004-05-09 00:00:00 -18191,717,30,2,3.0,2,,15,0.0,46,,28.0,7.0,23,2004-05-09 00:00:00 -18192,717,31,18,15.0,16,,16,0.0,43,,18.0,15.0,37,2004-05-09 00:00:00 -18193,717,46,17,21.0,20,,20,0.0,17,,8.0,20.0,20,2004-05-09 00:00:00 -18194,717,1,16,18.0,15,,18,0.0,33,,25.0,12.0,9,2004-05-09 00:00:00 -18195,717,45,17,20.0,18,,19,0.0,31,,3.0,19.0,20,2004-05-09 00:00:00 -18196,717,16,18,14.0,9,12.0,12,0.0,65,,11.0,9.0,11,2004-05-09 00:00:00 -18197,717,43,6,17.0,7,,17,0.0,33,,10.0,17.0,9,2004-05-09 00:00:00 -18198,717,7,0,6.0,13,11.0,11,0.0,65,,48.0,11.0,11,2004-05-09 00:00:00 -18199,717,13,0,5.0,10,10.0,10,0.0,65,,38.0,16.0,11,2004-05-09 00:00:00 -18200,717,12,14,12.0,17,9.0,9,0.0,65,,43.0,10.0,11,2004-05-09 00:00:00 -18201,717,21,5,2.0,5,2.0,2,8.0,66,5266131.0,16.0,5.0,1,2004-05-09 00:00:00 -18202,717,14,3,7.0,4,3.0,3,6.0,66,5285135.0,12.0,6.0,1,2004-05-09 00:00:00 -18203,717,3,3,8.0,8,4.0,4,5.0,66,5285793.0,27.0,3.0,1,2004-05-09 00:00:00 -18204,717,29,5,1.0,1,1.0,1,10.0,66,5252841.0,12.0,1.0,1,2004-05-09 00:00:00 -18205,717,22,2,4.0,6,6.0,6,3.0,66,5326645.0,27.0,8.0,1,2004-05-09 00:00:00 -18206,717,20,14,11.0,12,7.0,7,2.0,66,5329949.0,37.0,13.0,1,2004-05-09 00:00:00 -18207,717,17,15,9.0,14,8.0,8,1.0,65,,46.0,2.0,11,2004-05-09 00:00:00 -18208,717,10,15,10.0,3,5.0,5,4.0,66,5295168.0,47.0,4.0,1,2004-05-09 00:00:00 -18209,718,3,3,8.0,3,,12,0.0,41,,23.0,4.0,3,2004-05-23 00:00:00 -18210,718,20,14,11.0,10,,19,0.0,2,,2.0,16.0,4,2004-05-23 00:00:00 -18211,718,13,0,5.0,8,,18,0.0,2,,2.0,15.0,4,2004-05-23 00:00:00 -18212,718,10,15,10.0,7,,17,0.0,2,,2.0,17.0,5,2004-05-23 00:00:00 -18213,718,16,18,14.0,11,,16,0.0,11,,11.0,11.0,6,2004-05-23 00:00:00 -18214,718,31,18,15.0,14,,20,0.0,0,,,,3,2004-05-23 00:00:00 -18215,718,45,17,20.0,20,,14,0.0,15,,10.0,18.0,6,2004-05-23 00:00:00 -18216,718,7,0,6.0,5,,13,0.0,27,,15.0,7.0,63,2004-05-23 00:00:00 -18217,718,29,5,1.0,4,,11,0.0,45,,23.0,1.0,4,2004-05-23 00:00:00 -18218,718,44,16,19.0,18,,15,0.0,12,,10.0,14.0,7,2004-05-23 00:00:00 -18219,718,46,17,21.0,19,9.0,9,0.0,71,,2.0,19.0,16,2004-05-23 00:00:00 -18220,718,43,6,17.0,13,8.0,8,1.0,74,,57.0,9.0,13,2004-05-23 00:00:00 -18221,718,1,16,18.0,17,7.0,7,2.0,75,,35.0,13.0,12,2004-05-23 00:00:00 -18222,718,42,6,16.0,15,6.0,6,3.0,76,,22.0,8.0,11,2004-05-23 00:00:00 -18223,718,12,14,12.0,16,5.0,5,4.0,76,,23.0,10.0,11,2004-05-23 00:00:00 -18224,718,30,2,3.0,9,4.0,4,5.0,76,,41.0,5.0,11,2004-05-23 00:00:00 -18225,718,21,5,2.0,6,3.0,3,6.0,77,6422367.0,16.0,6.0,1,2004-05-23 00:00:00 -18226,718,17,15,9.0,2,2.0,2,8.0,77,6347098.0,40.0,3.0,1,2004-05-23 00:00:00 -18227,718,14,3,7.0,1,1.0,1,10.0,77,6346601.0,22.0,2.0,1,2004-05-23 00:00:00 -18228,718,22,2,4.0,12,10.0,10,0.0,69,,18.0,12.0,6,2004-05-23 00:00:00 -18229,719,44,16,19.0,15,13.0,13,0.0,58,,27.0,15.0,12,2004-05-30 00:00:00 -18230,719,45,17,20.0,20,14.0,14,0.0,57,,7.0,18.0,13,2004-05-30 00:00:00 -18231,719,10,15,10.0,2,,16,0.0,47,,11.0,2.0,5,2004-05-30 00:00:00 -18232,719,42,6,16.0,11,,20,0.0,0,,,,4,2004-05-30 00:00:00 -18233,719,7,0,6.0,4,,18,0.0,9,,2.0,9.0,5,2004-05-30 00:00:00 -18234,719,22,2,4.0,9,,19,0.0,0,,,,4,2004-05-30 00:00:00 -18235,719,31,18,15.0,12,12.0,12,0.0,59,,14.0,16.0,11,2004-05-30 00:00:00 -18236,719,13,0,5.0,18,,17,0.0,25,,14.0,12.0,5,2004-05-30 00:00:00 -18237,719,43,6,17.0,10,11.0,11,0.0,59,,12.0,13.0,11,2004-05-30 00:00:00 -18238,719,46,17,21.0,17,15.0,15,0.0,57,,46.0,17.0,13,2004-05-30 00:00:00 -18239,719,12,14,12.0,16,9.0,9,0.0,59,,37.0,14.0,11,2004-05-30 00:00:00 -18240,719,1,16,18.0,13,10.0,10,0.0,59,,55.0,11.0,11,2004-05-30 00:00:00 -18241,719,21,5,2.0,7,2.0,2,8.0,60,5573090.0,14.0,3.0,1,2004-05-30 00:00:00 -18242,719,17,15,9.0,5,3.0,3,6.0,60,5577634.0,13.0,4.0,1,2004-05-30 00:00:00 -18243,719,14,3,7.0,3,4.0,4,5.0,60,5608774.0,30.0,6.0,1,2004-05-30 00:00:00 -18244,719,29,5,1.0,1,1.0,1,10.0,60,5555101.0,7.0,1.0,1,2004-05-30 00:00:00 -18245,719,20,14,11.0,19,6.0,6,3.0,60,5628549.0,23.0,7.0,1,2004-05-30 00:00:00 -18246,719,16,18,14.0,14,7.0,7,2.0,60,5631307.0,37.0,10.0,1,2004-05-30 00:00:00 -18247,719,30,2,3.0,8,8.0,8,1.0,59,,43.0,8.0,11,2004-05-30 00:00:00 -18248,719,3,3,8.0,6,5.0,5,4.0,60,5616088.0,29.0,5.0,1,2004-05-30 00:00:00 -18249,720,12,14,12.0,17,,11,0.0,62,,25.0,11.0,3,2004-06-13 00:00:00 -18250,720,30,2,3.0,4,,18,0.0,70,,69.0,6.0,2,2004-06-13 00:00:00 -18251,720,22,2,4.0,1,,17,0.0,70,,70.0,3.0,2,2004-06-13 00:00:00 -18252,720,14,3,7.0,3,,16,0.0,0,,,,7,2004-06-13 00:00:00 -18253,720,16,18,14.0,14,,15,0.0,6,,6.0,17.0,22,2004-06-13 00:00:00 -18254,720,3,3,8.0,5,,13,0.0,44,,41.0,4.0,30,2004-06-13 00:00:00 -18255,720,10,15,10.0,20,,12,0.0,48,,25.0,8.0,5,2004-06-13 00:00:00 -18256,720,46,17,21.0,18,10.0,10,0.0,66,,64.0,18.0,14,2004-06-13 00:00:00 -18257,720,7,0,6.0,8,5.0,5,4.0,69,,44.0,7.0,11,2004-06-13 00:00:00 -18258,720,1,16,18.0,15,8.0,8,1.0,68,,18.0,14.0,12,2004-06-13 00:00:00 -18259,720,9,16,19.0,16,7.0,7,2.0,68,,42.0,16.0,12,2004-06-13 00:00:00 -18260,720,13,0,5.0,9,6.0,6,3.0,69,,55.0,10.0,11,2004-06-13 00:00:00 -18261,720,20,14,11.0,11,4.0,4,5.0,69,,47.0,9.0,11,2004-06-13 00:00:00 -18262,720,17,15,9.0,2,3.0,3,6.0,70,5325212.0,68.0,5.0,1,2004-06-13 00:00:00 -18263,720,21,5,2.0,7,2.0,2,8.0,70,5309911.0,68.0,1.0,1,2004-06-13 00:00:00 -18264,720,29,5,1.0,6,1.0,1,10.0,70,5304803.0,18.0,2.0,1,2004-06-13 00:00:00 -18265,720,42,6,16.0,12,,19,0.0,69,,39.0,12.0,2,2004-06-13 00:00:00 -18266,720,31,18,15.0,10,9.0,9,0.0,67,,45.0,13.0,13,2004-06-13 00:00:00 -18267,720,43,6,17.0,13,,20,0.0,69,,23.0,15.0,2,2004-06-13 00:00:00 -18268,720,45,17,20.0,19,,14,0.0,30,,25.0,19.0,6,2004-06-13 00:00:00 -18269,721,14,3,7.0,20,4.0,4,5.0,73,6064458.0,45.0,6.0,1,2004-06-20 00:00:00 -18270,721,44,16,19.0,17,,19,0.0,0,,,,4,2004-06-20 00:00:00 -18271,721,45,17,20.0,18,,20,0.0,0,,,,4,2004-06-20 00:00:00 -18272,721,3,3,8.0,9,,16,0.0,8,,8.0,7.0,27,2004-06-20 00:00:00 -18273,721,22,2,4.0,6,,15,0.0,9,,8.0,10.0,27,2004-06-20 00:00:00 -18274,721,42,6,16.0,11,,14,0.0,17,,8.0,14.0,6,2004-06-20 00:00:00 -18275,721,17,15,9.0,4,,13,0.0,26,,22.0,5.0,6,2004-06-20 00:00:00 -18276,721,1,16,18.0,16,,12,0.0,40,,37.0,15.0,5,2004-06-20 00:00:00 -18277,721,30,2,3.0,5,,11,0.0,57,,37.0,9.0,2,2004-06-20 00:00:00 -18278,721,16,18,14.0,10,,10,0.0,60,,46.0,12.0,5,2004-06-20 00:00:00 -18279,721,20,14,11.0,14,9.0,9,0.0,65,,44.0,11.0,18,2004-06-20 00:00:00 -18280,721,46,17,21.0,19,8.0,8,1.0,70,,39.0,16.0,13,2004-06-20 00:00:00 -18281,721,13,0,5.0,12,7.0,7,2.0,72,,44.0,13.0,11,2004-06-20 00:00:00 -18282,721,7,0,6.0,7,6.0,6,3.0,72,,59.0,8.0,11,2004-06-20 00:00:00 -18283,721,43,6,17.0,8,5.0,5,4.0,73,6067448.0,46.0,4.0,1,2004-06-20 00:00:00 -18284,721,10,15,10.0,3,3.0,3,6.0,73,6051950.0,47.0,3.0,1,2004-06-20 00:00:00 -18285,721,21,5,2.0,1,2.0,2,8.0,73,6032864.0,7.0,1.0,1,2004-06-20 00:00:00 -18286,721,29,5,1.0,2,1.0,1,10.0,73,6029914.0,8.0,2.0,1,2004-06-20 00:00:00 -18287,721,12,14,12.0,15,,18,0.0,0,,,,4,2004-06-20 00:00:00 -18288,721,31,18,15.0,13,,17,0.0,0,,,,4,2004-06-20 00:00:00 -18289,722,10,15,10.0,7,,20,0.0,15,,14.0,12.0,5,2004-07-04 00:00:00 -18290,722,46,17,21.0,20,,19,0.0,31,,13.0,20.0,20,2004-07-04 00:00:00 -18291,722,45,17,20.0,19,18.0,18,0.0,66,,52.0,19.0,14,2004-07-04 00:00:00 -18292,722,3,3,8.0,1,2.0,2,8.0,70,5426462.0,34.0,2.0,1,2004-07-04 00:00:00 -18293,722,29,5,1.0,2,1.0,1,10.0,70,5418133.0,32.0,1.0,1,2004-07-04 00:00:00 -18294,722,44,16,19.0,18,17.0,17,0.0,67,,15.0,17.0,13,2004-07-04 00:00:00 -18295,722,1,16,18.0,17,16.0,16,0.0,68,,26.0,18.0,12,2004-07-04 00:00:00 -18296,722,43,6,17.0,14,15.0,15,0.0,68,,53.0,15.0,12,2004-07-04 00:00:00 -18297,722,12,14,12.0,16,13.0,13,0.0,69,,23.0,16.0,11,2004-07-04 00:00:00 -18298,722,20,14,11.0,15,12.0,12,0.0,69,,22.0,11.0,11,2004-07-04 00:00:00 -18299,722,31,18,15.0,13,11.0,11,0.0,69,,37.0,13.0,11,2004-07-04 00:00:00 -18300,722,42,6,16.0,11,14.0,14,0.0,69,,49.0,14.0,11,2004-07-04 00:00:00 -18301,722,16,18,14.0,12,9.0,9,0.0,70,5470527.0,53.0,4.0,1,2004-07-04 00:00:00 -18302,722,30,2,3.0,6,8.0,8,1.0,70,5461552.0,48.0,8.0,1,2004-07-04 00:00:00 -18303,722,7,0,6.0,9,7.0,7,2.0,70,5454363.0,30.0,3.0,1,2004-07-04 00:00:00 -18304,722,21,5,2.0,10,3.0,3,6.0,70,5449755.0,50.0,6.0,1,2004-07-04 00:00:00 -18305,722,13,0,5.0,3,6.0,6,3.0,70,5453653.0,11.0,10.0,1,2004-07-04 00:00:00 -18306,722,17,15,9.0,4,5.0,5,4.0,70,5450615.0,50.0,5.0,1,2004-07-04 00:00:00 -18307,722,47,2,4.0,8,10.0,10,0.0,70,5476299.0,56.0,7.0,1,2004-07-04 00:00:00 -18308,722,14,3,7.0,5,4.0,4,5.0,70,5450215.0,15.0,9.0,1,2004-07-04 00:00:00 -18309,723,42,6,16.0,12,13.0,13,0.0,59,,35.0,13.0,11,2004-07-11 00:00:00 -18310,723,31,18,15.0,13,14.0,14,0.0,59,,10.0,15.0,11,2004-07-11 00:00:00 -18311,723,1,16,18.0,15,15.0,15,0.0,59,,17.0,16.0,11,2004-07-11 00:00:00 -18312,723,14,3,7.0,5,,18,0.0,39,,34.0,11.0,3,2004-07-11 00:00:00 -18313,723,44,16,19.0,14,,17,0.0,47,,13.0,17.0,20,2004-07-11 00:00:00 -18314,723,46,17,21.0,19,,19,0.0,29,,12.0,20.0,5,2004-07-11 00:00:00 -18315,723,47,2,4.0,11,12.0,12,0.0,60,5117003.0,58.0,7.0,1,2004-07-11 00:00:00 -18316,723,43,6,17.0,17,,20,0.0,16,,4.0,18.0,3,2004-07-11 00:00:00 -18317,723,45,17,20.0,18,16.0,16,0.0,56,,33.0,19.0,14,2004-07-11 00:00:00 -18318,723,10,15,10.0,8,11.0,11,0.0,60,5116436.0,12.0,14.0,1,2004-07-11 00:00:00 -18319,723,13,0,5.0,6,7.0,7,2.0,60,5102368.0,25.0,10.0,1,2004-07-11 00:00:00 -18320,723,12,14,12.0,10,9.0,9,0.0,60,5106723.0,58.0,9.0,1,2004-07-11 00:00:00 -18321,723,16,18,14.0,9,8.0,8,1.0,60,5106401.0,11.0,12.0,1,2004-07-11 00:00:00 -18322,723,20,14,11.0,20,6.0,6,3.0,60,5095588.0,22.0,5.0,1,2004-07-11 00:00:00 -18323,723,30,2,3.0,7,5.0,5,4.0,60,5094873.0,26.0,6.0,1,2004-07-11 00:00:00 -18324,723,17,15,9.0,3,4.0,4,5.0,60,5093383.0,10.0,3.0,1,2004-07-11 00:00:00 -18325,723,21,5,2.0,2,3.0,3,6.0,60,5085814.0,8.0,2.0,1,2004-07-11 00:00:00 -18326,723,7,0,6.0,1,2.0,2,8.0,60,5084830.0,10.0,4.0,1,2004-07-11 00:00:00 -18327,723,29,5,1.0,4,1.0,1,10.0,60,5082700.0,14.0,1.0,1,2004-07-11 00:00:00 -18328,723,3,3,8.0,16,10.0,10,0.0,60,5107535.0,39.0,8.0,1,2004-07-11 00:00:00 -18329,724,12,14,12.0,16,13.0,13,0.0,65,,61.0,17.0,11,2004-07-25 00:00:00 -18330,724,43,6,17.0,9,14.0,14,0.0,65,,59.0,4.0,11,2004-07-25 00:00:00 -18331,724,44,16,19.0,17,15.0,15,0.0,63,,63.0,16.0,13,2004-07-25 00:00:00 -18332,724,46,17,21.0,20,16.0,16,0.0,62,,18.0,20.0,14,2004-07-25 00:00:00 -18333,724,7,0,6.0,3,,20,0.0,13,,10.0,1.0,65,2004-07-25 00:00:00 -18334,724,1,16,18.0,18,,18,0.0,42,,20.0,18.0,64,2004-07-25 00:00:00 -18335,724,42,6,16.0,15,,19,0.0,38,,20.0,14.0,29,2004-07-25 00:00:00 -18336,724,21,5,2.0,7,12.0,12,0.0,66,5108100.0,59.0,12.0,1,2004-07-25 00:00:00 -18337,724,45,17,20.0,19,17.0,17,0.0,62,,52.0,19.0,14,2004-07-25 00:00:00 -18338,724,14,3,7.0,6,11.0,11,0.0,66,5105106.0,9.0,6.0,1,2004-07-25 00:00:00 -18339,724,30,2,3.0,2,5.0,5,4.0,66,5057903.0,10.0,7.0,1,2004-07-25 00:00:00 -18340,724,20,14,11.0,14,9.0,9,0.0,66,5101950.0,39.0,15.0,1,2004-07-25 00:00:00 -18341,724,17,15,9.0,13,2.0,2,8.0,66,5043236.0,11.0,3.0,1,2004-07-25 00:00:00 -18342,724,3,3,8.0,5,3.0,3,6.0,66,5051199.0,8.0,5.0,1,2004-07-25 00:00:00 -18343,724,13,0,5.0,4,4.0,4,5.0,66,5054079.0,8.0,8.0,1,2004-07-25 00:00:00 -18344,724,29,5,1.0,1,1.0,1,10.0,66,5034848.0,5.0,2.0,1,2004-07-25 00:00:00 -18345,724,16,18,14.0,11,6.0,6,3.0,66,5075956.0,65.0,11.0,1,2004-07-25 00:00:00 -18346,724,41,2,4.0,10,7.0,7,2.0,66,5076804.0,65.0,10.0,1,2004-07-25 00:00:00 -18347,724,10,15,10.0,8,8.0,8,1.0,66,5081690.0,29.0,9.0,1,2004-07-25 00:00:00 -18348,724,31,18,15.0,12,10.0,10,0.0,66,5103426.0,33.0,13.0,1,2004-07-25 00:00:00 -18349,725,1,16,18.0,16,12.0,12,0.0,68,,68.0,13.0,12,2004-08-15 00:00:00 -18350,725,12,14,12.0,20,,19,0.0,21,,14.0,15.0,23,2004-08-15 00:00:00 -18351,725,40,6,16.0,15,,18,0.0,31,,13.0,16.0,40,2004-08-15 00:00:00 -18352,725,14,3,7.0,9,,17,0.0,41,,10.0,6.0,5,2004-08-15 00:00:00 -18353,725,44,16,19.0,17,,16,0.0,48,,43.0,18.0,6,2004-08-15 00:00:00 -18354,725,46,17,21.0,18,15.0,15,0.0,65,,63.0,20.0,15,2004-08-15 00:00:00 -18355,725,45,17,20.0,19,14.0,14,0.0,66,,65.0,19.0,14,2004-08-15 00:00:00 -18356,725,31,18,15.0,14,13.0,13,0.0,68,,45.0,17.0,12,2004-08-15 00:00:00 -18357,725,43,6,17.0,13,11.0,11,0.0,69,,50.0,12.0,11,2004-08-15 00:00:00 -18358,725,7,0,6.0,10,,20,0.0,13,,6.0,14.0,10,2004-08-15 00:00:00 -18359,725,13,0,5.0,12,9.0,9,0.0,69,,67.0,11.0,11,2004-08-15 00:00:00 -18360,725,29,5,1.0,1,1.0,1,10.0,70,5726131.0,29.0,1.0,1,2004-08-15 00:00:00 -18361,725,21,5,2.0,2,2.0,2,8.0,70,5730827.0,29.0,2.0,1,2004-08-15 00:00:00 -18362,725,3,3,8.0,5,3.0,3,6.0,70,5770730.0,49.0,3.0,1,2004-08-15 00:00:00 -18363,725,30,2,3.0,7,4.0,4,5.0,70,5788744.0,49.0,7.0,1,2004-08-15 00:00:00 -18364,725,16,18,14.0,11,10.0,10,0.0,69,,45.0,8.0,11,2004-08-15 00:00:00 -18365,725,10,15,10.0,3,6.0,6,3.0,69,,10.0,10.0,11,2004-08-15 00:00:00 -18366,725,41,2,4.0,6,7.0,7,2.0,69,,48.0,5.0,11,2004-08-15 00:00:00 -18367,725,20,14,11.0,8,8.0,8,1.0,69,,53.0,9.0,11,2004-08-15 00:00:00 -18368,725,17,15,9.0,4,5.0,5,4.0,70,5793570.0,47.0,4.0,1,2004-08-15 00:00:00 -18369,726,1,16,18.0,16,11.0,11,0.0,40,,40.0,15.0,14,2004-08-29 00:00:00 -18370,726,45,17,20.0,17,,19,0.0,0,,,,4,2004-08-29 00:00:00 -18371,726,10,15,10.0,15,,18,0.0,0,,,,4,2004-08-29 00:00:00 -18372,726,16,18,14.0,7,,17,0.0,0,,,,4,2004-08-29 00:00:00 -18373,726,3,3,8.0,3,,16,0.0,11,,9.0,4.0,5,2004-08-29 00:00:00 -18374,726,46,17,21.0,18,,15,0.0,28,,25.0,16.0,4,2004-08-29 00:00:00 -18375,726,17,15,9.0,12,,14,0.0,29,,26.0,10.0,4,2004-08-29 00:00:00 -18376,726,41,2,4.0,14,,13,0.0,31,,26.0,8.0,6,2004-08-29 00:00:00 -18377,726,30,2,3.0,11,,12,0.0,37,,36.0,6.0,27,2004-08-29 00:00:00 -18378,726,44,16,19.0,19,,20,0.0,0,,,,4,2004-08-29 00:00:00 -18379,726,40,6,16.0,20,10.0,10,0.0,41,,26.0,12.0,5,2004-08-29 00:00:00 -18380,726,43,6,17.0,9,8.0,8,1.0,44,5573967.0,29.0,14.0,1,2004-08-29 00:00:00 -18381,726,13,0,5.0,4,7.0,7,2.0,44,5573244.0,11.0,7.0,1,2004-08-29 00:00:00 -18382,726,31,18,15.0,13,6.0,6,3.0,44,5569888.0,11.0,11.0,1,2004-08-29 00:00:00 -18383,726,20,14,11.0,5,5.0,5,4.0,44,5569378.0,11.0,9.0,1,2004-08-29 00:00:00 -18384,726,12,14,12.0,8,4.0,4,5.0,44,5567778.0,29.0,13.0,1,2004-08-29 00:00:00 -18385,726,21,5,2.0,6,3.0,3,6.0,44,5559645.0,43.0,3.0,1,2004-08-29 00:00:00 -18386,726,29,5,1.0,2,2.0,2,8.0,44,5558406.0,28.0,2.0,1,2004-08-29 00:00:00 -18387,726,7,0,6.0,10,1.0,1,10.0,44,5555274.0,42.0,1.0,1,2004-08-29 00:00:00 -18388,726,14,3,7.0,1,9.0,9,0.0,44,5577389.0,9.0,5.0,1,2004-08-29 00:00:00 -18389,727,31,18,15.0,14,13.0,13,0.0,52,,29.0,15.0,11,2004-09-12 00:00:00 -18390,727,1,16,18.0,20,14.0,14,0.0,52,,23.0,17.0,11,2004-09-12 00:00:00 -18391,727,46,17,21.0,19,15.0,15,0.0,50,,31.0,18.0,13,2004-09-12 00:00:00 -18392,727,12,14,12.0,16,12.0,12,0.0,52,,50.0,11.0,11,2004-09-12 00:00:00 -18393,727,44,16,19.0,17,,17,0.0,33,,13.0,16.0,3,2004-09-12 00:00:00 -18394,727,45,17,20.0,18,,18,0.0,29,,24.0,19.0,66,2004-09-12 00:00:00 -18395,727,7,0,6.0,7,,19,0.0,13,,11.0,13.0,5,2004-09-12 00:00:00 -18396,727,3,3,8.0,4,,16,0.0,40,,31.0,8.0,20,2004-09-12 00:00:00 -18397,727,40,6,16.0,11,11.0,11,0.0,53,4600979.0,52.0,14.0,1,2004-09-12 00:00:00 -18398,727,43,6,17.0,13,,20,0.0,0,,,,4,2004-09-12 00:00:00 -18399,727,16,18,14.0,12,9.0,9,0.0,53,4575209.0,53.0,12.0,1,2004-09-12 00:00:00 -18400,727,21,5,2.0,1,1.0,1,10.0,53,4518448.0,41.0,1.0,1,2004-09-12 00:00:00 -18401,727,29,5,1.0,3,2.0,2,8.0,53,4519795.0,35.0,2.0,1,2004-09-12 00:00:00 -18402,727,17,15,9.0,6,3.0,3,6.0,53,4528645.0,13.0,6.0,1,2004-09-12 00:00:00 -18403,727,10,15,10.0,5,4.0,4,5.0,53,4533818.0,32.0,5.0,1,2004-09-12 00:00:00 -18404,727,14,3,7.0,9,10.0,10,0.0,53,4584764.0,52.0,7.0,1,2004-09-12 00:00:00 -18405,727,13,0,5.0,10,6.0,6,3.0,53,4551887.0,24.0,9.0,1,2004-09-12 00:00:00 -18406,727,41,2,4.0,8,7.0,7,2.0,53,4552200.0,32.0,3.0,1,2004-09-12 00:00:00 -18407,727,20,14,11.0,15,8.0,8,1.0,53,4553879.0,51.0,4.0,1,2004-09-12 00:00:00 -18408,727,30,2,3.0,2,5.0,5,4.0,53,4550800.0,32.0,10.0,1,2004-09-12 00:00:00 -18409,728,29,5,1.0,20,12.0,12,0.0,55,,55.0,1.0,11,2004-09-26 00:00:00 -18410,728,31,18,15.0,15,,20,0.0,11,,10.0,18.0,4,2004-09-26 00:00:00 -18411,728,40,6,16.0,13,,19,0.0,35,,24.0,12.0,7,2004-09-26 00:00:00 -18412,728,22,2,4.0,5,,18,0.0,37,,31.0,9.0,4,2004-09-26 00:00:00 -18413,728,45,17,20.0,17,,17,0.0,38,,23.0,19.0,36,2004-09-26 00:00:00 -18414,728,46,17,21.0,19,16.0,16,0.0,53,,51.0,20.0,13,2004-09-26 00:00:00 -18415,728,9,16,19.0,16,15.0,15,0.0,55,,54.0,16.0,11,2004-09-26 00:00:00 -18416,728,43,6,17.0,8,14.0,14,0.0,55,,51.0,13.0,11,2004-09-26 00:00:00 -18417,728,1,16,18.0,14,13.0,13,0.0,55,,55.0,14.0,11,2004-09-26 00:00:00 -18418,728,34,3,7.0,12,11.0,11,0.0,55,,55.0,17.0,11,2004-09-26 00:00:00 -18419,728,16,18,14.0,11,10.0,10,0.0,55,,32.0,15.0,11,2004-09-26 00:00:00 -18420,728,13,0,5.0,9,9.0,9,0.0,56,5433039.0,26.0,11.0,1,2004-09-26 00:00:00 -18421,728,12,14,12.0,4,8.0,8,1.0,56,5432500.0,43.0,6.0,1,2004-09-26 00:00:00 -18422,728,20,14,11.0,7,7.0,7,2.0,56,5417874.0,25.0,7.0,1,2004-09-26 00:00:00 -18423,728,10,15,10.0,18,6.0,6,3.0,56,5407211.0,36.0,8.0,1,2004-09-26 00:00:00 -18424,728,30,2,3.0,10,5.0,5,4.0,56,5397613.0,34.0,5.0,1,2004-09-26 00:00:00 -18425,728,3,3,8.0,6,4.0,4,5.0,56,5384930.0,55.0,10.0,1,2004-09-26 00:00:00 -18426,728,7,0,6.0,2,3.0,3,6.0,56,5353889.0,53.0,3.0,1,2004-09-26 00:00:00 -18427,728,17,15,9.0,3,2.0,2,8.0,56,5353455.0,33.0,4.0,1,2004-09-26 00:00:00 -18428,728,21,5,2.0,1,1.0,1,10.0,56,5352420.0,28.0,2.0,1,2004-09-26 00:00:00 -18429,729,1,16,18.0,16,13.0,13,0.0,52,,25.0,17.0,11,2004-10-10 00:00:00 -18430,729,43,6,17.0,10,14.0,14,0.0,51,,11.0,13.0,12,2004-10-10 00:00:00 -18431,729,9,16,19.0,17,15.0,15,0.0,51,,14.0,18.0,12,2004-10-10 00:00:00 -18432,729,45,17,20.0,18,16.0,16,0.0,50,,27.0,19.0,13,2004-10-10 00:00:00 -18433,729,16,18,14.0,3,,20,0.0,20,,13.0,11.0,25,2004-10-10 00:00:00 -18434,729,13,0,5.0,8,,18,0.0,38,,14.0,9.0,4,2004-10-10 00:00:00 -18435,729,21,5,2.0,15,,19,0.0,38,,30.0,1.0,4,2004-10-10 00:00:00 -18436,729,31,18,15.0,14,12.0,12,0.0,52,,32.0,15.0,11,2004-10-10 00:00:00 -18437,729,46,17,21.0,20,,17,0.0,41,,26.0,20.0,20,2004-10-10 00:00:00 -18438,729,14,6,16.0,6,11.0,11,0.0,52,,52.0,14.0,11,2004-10-10 00:00:00 -18439,729,34,3,7.0,9,10.0,10,0.0,52,,28.0,16.0,11,2004-10-10 00:00:00 -18440,729,12,14,12.0,19,9.0,9,0.0,53,5156641.0,40.0,4.0,1,2004-10-10 00:00:00 -18441,729,20,14,11.0,7,8.0,8,1.0,53,5123261.0,44.0,8.0,1,2004-10-10 00:00:00 -18442,729,30,2,3.0,13,7.0,7,2.0,53,5122332.0,30.0,6.0,1,2004-10-10 00:00:00 -18443,729,7,0,6.0,12,6.0,6,3.0,53,5106347.0,35.0,10.0,1,2004-10-10 00:00:00 -18444,729,3,3,8.0,11,5.0,5,4.0,53,5104752.0,29.0,12.0,1,2004-10-10 00:00:00 -18445,729,10,15,10.0,4,4.0,4,5.0,53,5098766.0,28.0,5.0,1,2004-10-10 00:00:00 -18446,729,17,15,9.0,5,3.0,3,6.0,53,5086647.0,33.0,7.0,1,2004-10-10 00:00:00 -18447,729,22,2,4.0,2,2.0,2,8.0,53,5081083.0,23.0,3.0,1,2004-10-10 00:00:00 -18448,729,29,5,1.0,1,1.0,1,10.0,53,5066985.0,41.0,2.0,1,2004-10-10 00:00:00 -18449,730,40,6,17.0,14,13.0,13,0.0,70,,69.0,14.0,11,2004-10-24 00:00:00 -18450,730,31,18,15.0,15,14.0,14,0.0,69,,49.0,13.0,12,2004-10-24 00:00:00 -18451,730,9,16,19.0,17,15.0,15,0.0,69,,68.0,16.0,12,2004-10-24 00:00:00 -18452,730,46,17,21.0,19,16.0,16,0.0,67,,45.0,17.0,14,2004-10-24 00:00:00 -18453,730,17,15,9.0,5,,20,0.0,3,,2.0,20.0,5,2004-10-24 00:00:00 -18454,730,16,18,14.0,11,,18,0.0,23,,20.0,15.0,4,2004-10-24 00:00:00 -18455,730,1,16,18.0,16,,19,0.0,15,,11.0,19.0,8,2004-10-24 00:00:00 -18456,730,14,6,16.0,9,12.0,12,0.0,70,,65.0,11.0,11,2004-10-24 00:00:00 -18457,730,45,17,20.0,20,17.0,17,0.0,67,,50.0,18.0,14,2004-10-24 00:00:00 -18458,730,13,0,5.0,12,11.0,11,0.0,70,,40.0,12.0,11,2004-10-24 00:00:00 -18459,730,34,3,7.0,13,10.0,10,0.0,70,,68.0,10.0,11,2004-10-24 00:00:00 -18460,730,20,14,11.0,10,9.0,9,0.0,71,5345293.0,69.0,6.0,1,2004-10-24 00:00:00 -18461,730,12,14,12.0,4,8.0,8,1.0,71,5343761.0,68.0,8.0,1,2004-10-24 00:00:00 -18462,730,29,5,1.0,18,7.0,7,2.0,71,5332077.0,49.0,4.0,1,2004-10-24 00:00:00 -18463,730,10,15,10.0,6,6.0,6,3.0,71,5331699.0,51.0,7.0,1,2004-10-24 00:00:00 -18464,730,22,2,4.0,7,5.0,5,4.0,71,5331191.0,23.0,5.0,1,2004-10-24 00:00:00 -18465,730,3,3,8.0,8,4.0,4,5.0,71,5329959.0,42.0,9.0,1,2004-10-24 00:00:00 -18466,730,21,5,2.0,1,3.0,3,6.0,71,5305550.0,22.0,3.0,1,2004-10-24 00:00:00 -18467,730,7,0,6.0,3,2.0,2,8.0,71,5282473.0,52.0,2.0,1,2004-10-24 00:00:00 -18468,730,30,2,3.0,2,1.0,1,10.0,71,5281451.0,49.0,1.0,1,2004-10-24 00:00:00 -18469,731,10,15,4.0,20,,14,0.0,55,,36.0,16.0,12,2005-03-06 14:00:00 -18470,731,38,16,19.0,12,15.0,15,0.0,55,,36.0,17.0,12,2005-03-06 14:00:00 -18471,731,32,16,18.0,14,16.0,16,0.0,55,,16.0,18.0,12,2005-03-06 14:00:00 -18472,731,26,17,21.0,17,,20,0.0,16,,11.0,20.0,6,2005-03-06 14:00:00 -18473,731,29,5,1.0,19,,18,0.0,42,,38.0,6.0,3,2005-03-06 14:00:00 -18474,731,1,2,8.0,7,,19,0.0,42,,38.0,12.0,3,2005-03-06 14:00:00 -18475,731,34,14,11.0,4,13.0,13,0.0,56,,54.0,15.0,11,2005-03-06 14:00:00 -18476,731,39,17,20.0,16,17.0,17,0.0,55,,22.0,19.0,14,2005-03-06 14:00:00 -18477,731,22,6,17.0,15,12.0,12,0.0,56,,56.0,9.0,11,2005-03-06 14:00:00 -18478,731,30,0,10.0,9,6.0,6,3.0,57,5092369.0,41.0,7.0,1,2005-03-06 14:00:00 -18479,731,12,14,12.0,18,10.0,10,0.0,57,5121729.0,55.0,13.0,1,2005-03-06 14:00:00 -18480,731,20,3,6.0,1,1.0,1,10.0,57,5057336.0,55.0,2.0,1,2005-03-06 14:00:00 -18481,731,21,5,2.0,11,2.0,2,8.0,57,5062889.0,54.0,3.0,1,2005-03-06 14:00:00 -18482,731,3,3,5.0,13,3.0,3,6.0,57,5064048.0,24.0,1.0,1,2005-03-06 14:00:00 -18483,731,13,8,14.0,5,4.0,4,5.0,57,5073467.0,40.0,11.0,1,2005-03-06 14:00:00 -18484,731,17,15,3.0,8,,11,0.0,56,,55.0,5.0,11,2005-03-06 14:00:00 -18485,731,31,8,15.0,6,7.0,7,2.0,57,5096333.0,39.0,10.0,1,2005-03-06 14:00:00 -18486,731,7,0,9.0,10,8.0,8,1.0,57,5096969.0,55.0,4.0,1,2005-03-06 14:00:00 -18487,731,14,6,16.0,2,9.0,9,0.0,57,5120444.0,56.0,14.0,1,2005-03-06 14:00:00 -18488,731,16,2,7.0,3,5.0,5,4.0,57,5074244.0,37.0,8.0,1,2005-03-06 14:00:00 -18489,732,26,17,21.0,19,13.0,13,0.0,52,,12.0,19.0,14,2005-03-20 15:00:00 -18490,732,39,17,20.0,20,,20,0.0,2,,2.0,20.0,20,2005-03-20 15:00:00 -18491,732,18,15,4.0,15,,19,0.0,2,,2.0,18.0,5,2005-03-20 15:00:00 -18492,732,17,15,3.0,9,,18,0.0,2,,2.0,14.0,5,2005-03-20 15:00:00 -18493,732,34,14,11.0,16,,17,0.0,26,,18.0,15.0,20,2005-03-20 15:00:00 -18494,732,16,2,7.0,4,,16,0.0,36,,20.0,5.0,4,2005-03-20 15:00:00 -18495,732,20,3,6.0,3,,15,0.0,36,,21.0,6.0,4,2005-03-20 15:00:00 -18496,732,21,5,2.0,12,,14,0.0,49,,22.0,10.0,27,2005-03-20 15:00:00 -18497,732,32,16,18.0,18,12.0,12,0.0,53,,36.0,17.0,13,2005-03-20 15:00:00 -18498,732,38,16,19.0,17,11.0,11,0.0,54,,18.0,16.0,12,2005-03-20 15:00:00 -18499,732,12,14,12.0,14,10.0,10,0.0,55,,18.0,13.0,11,2005-03-20 15:00:00 -18500,732,7,0,9.0,6,9.0,9,0.0,56,5575316.0,23.0,1.0,1,2005-03-20 15:00:00 -18501,732,31,8,15.0,7,8.0,8,1.0,56,5574571.0,17.0,11.0,1,2005-03-20 15:00:00 -18502,732,29,5,1.0,13,7.0,7,2.0,56,5573724.0,41.0,12.0,1,2005-03-20 15:00:00 -18503,732,13,8,14.0,8,6.0,6,3.0,56,5566279.0,18.0,9.0,1,2005-03-20 15:00:00 -18504,732,22,6,17.0,5,5.0,5,4.0,56,5545590.0,15.0,7.0,1,2005-03-20 15:00:00 -18505,732,30,0,10.0,11,4.0,4,5.0,56,5535367.0,42.0,8.0,1,2005-03-20 15:00:00 -18506,732,1,2,8.0,10,3.0,3,6.0,56,5525924.0,40.0,2.0,1,2005-03-20 15:00:00 -18507,732,14,6,16.0,2,2.0,2,8.0,56,5518063.0,18.0,3.0,1,2005-03-20 15:00:00 -18508,732,3,3,5.0,1,1.0,1,10.0,56,5493736.0,18.0,4.0,1,2005-03-20 15:00:00 -18509,733,17,15,3.0,11,,14,0.0,46,,45.0,5.0,8,2005-04-03 14:30:00 -18510,733,10,15,4.0,13,,15,0.0,27,,23.0,11.0,23,2005-04-03 14:30:00 -18511,733,1,2,8.0,4,,16,0.0,25,,19.0,9.0,5,2005-04-03 14:30:00 -18512,733,31,8,15.0,7,,20,0.0,0,,,,10,2005-04-03 14:30:00 -18513,733,20,3,6.0,10,,18,0.0,4,,2.0,18.0,5,2005-04-03 14:30:00 -18514,733,38,16,19.0,17,,19,0.0,2,,2.0,19.0,10,2005-04-03 14:30:00 -18515,733,26,17,21.0,18,13.0,13,0.0,53,,3.0,17.0,14,2005-04-03 14:30:00 -18516,733,29,5,1.0,2,,17,0.0,12,,7.0,7.0,9,2005-04-03 14:30:00 -18517,733,39,17,20.0,19,12.0,12,0.0,54,,16.0,16.0,13,2005-04-03 14:30:00 -18518,733,16,2,7.0,5,6.0,6,3.0,57,5433232.0,20.0,10.0,1,2005-04-03 14:30:00 -18519,733,32,16,18.0,16,10.0,10,0.0,55,,18.0,15.0,12,2005-04-03 14:30:00 -18520,733,34,14,11.0,15,11.0,11,0.0,54,,24.0,14.0,22,2005-04-03 14:30:00 -18521,733,14,6,16.0,3,2.0,2,8.0,57,5371940.0,41.0,4.0,1,2005-04-03 14:30:00 -18522,733,7,0,9.0,9,3.0,3,6.0,57,5390594.0,41.0,3.0,1,2005-04-03 14:30:00 -18523,733,22,6,17.0,6,4.0,4,5.0,57,5411803.0,36.0,6.0,1,2005-04-03 14:30:00 -18524,733,3,3,5.0,1,1.0,1,10.0,57,5358531.0,39.0,2.0,1,2005-04-03 14:30:00 -18525,733,12,14,12.0,12,7.0,7,2.0,56,,40.0,12.0,11,2005-04-03 14:30:00 -18526,733,13,8,14.0,14,8.0,8,1.0,56,,42.0,13.0,11,2005-04-03 14:30:00 -18527,733,21,5,2.0,20,9.0,9,0.0,56,,23.0,8.0,11,2005-04-03 14:30:00 -18528,733,36,0,10.0,8,5.0,5,4.0,57,5423519.0,43.0,1.0,1,2005-04-03 14:30:00 -18529,734,38,16,19.0,16,12.0,12,0.0,61,,20.0,12.0,11,2005-04-24 14:00:00 -18530,734,20,3,6.0,12,,18,0.0,5,,4.0,18.0,3,2005-04-24 14:00:00 -18531,734,39,17,20.0,19,,17,0.0,8,,5.0,20.0,8,2005-04-24 14:00:00 -18532,734,7,0,9.0,1,,16,0.0,9,,8.0,5.0,30,2005-04-24 14:00:00 -18533,734,21,5,2.0,9,,15,0.0,18,,13.0,15.0,10,2005-04-24 14:00:00 -18534,734,26,17,21.0,20,,14,0.0,20,,18.0,19.0,9,2005-04-24 14:00:00 -18535,734,32,16,18.0,17,13.0,13,0.0,60,,19.0,17.0,12,2005-04-24 14:00:00 -18536,734,13,8,14.0,14,11.0,11,0.0,61,,22.0,16.0,11,2005-04-24 14:00:00 -18537,734,1,2,8.0,8,6.0,6,3.0,62,5333203.0,54.0,9.0,1,2005-04-24 14:00:00 -18538,734,22,6,17.0,10,9.0,9,0.0,62,5357762.0,19.0,13.0,1,2005-04-24 14:00:00 -18539,734,23,8,15.0,15,8.0,8,1.0,62,5345685.0,46.0,7.0,1,2005-04-24 14:00:00 -18540,734,16,2,7.0,4,7.0,7,2.0,62,5345218.0,17.0,14.0,1,2005-04-24 14:00:00 -18541,734,14,6,16.0,5,5.0,5,4.0,62,5332179.0,44.0,11.0,1,2005-04-24 14:00:00 -18542,734,34,14,11.0,11,4.0,4,5.0,62,5326363.0,45.0,10.0,1,2005-04-24 14:00:00 -18543,734,24,0,10.0,7,3.0,3,6.0,62,5289475.0,24.0,3.0,1,2005-04-24 14:00:00 -18544,734,17,15,3.0,3,,19,0.0,62,5272321.0,22.0,2.0,2,2005-04-24 14:00:00 -18545,734,3,3,5.0,2,1.0,1,10.0,62,5261921.0,22.0,4.0,1,2005-04-24 14:00:00 -18546,734,12,14,12.0,18,10.0,10,0.0,61,,37.0,8.0,11,2005-04-24 14:00:00 -18547,734,10,15,4.0,6,,20,0.0,62,5296621.0,23.0,6.0,2,2005-04-24 14:00:00 -18548,734,29,5,1.0,13,2.0,2,8.0,62,5262136.0,48.0,1.0,1,2005-04-24 14:00:00 -18549,735,39,17,20.0,15,,17,0.0,11,,10.0,18.0,20,2005-05-08 14:00:00 -18550,735,26,17,21.0,14,,16,0.0,19,,15.0,17.0,6,2005-05-08 14:00:00 -18551,735,29,5,1.0,8,,15,0.0,46,,31.0,2.0,29,2005-05-08 14:00:00 -18552,735,34,14,11.0,12,,14,0.0,51,,43.0,13.0,5,2005-05-08 14:00:00 -18553,735,38,16,19.0,13,13.0,13,0.0,63,,16.0,16.0,13,2005-05-08 14:00:00 -18554,735,32,16,18.0,18,12.0,12,0.0,63,,22.0,14.0,13,2005-05-08 14:00:00 -18555,735,12,14,12.0,10,11.0,11,0.0,63,,51.0,10.0,46,2005-05-08 14:00:00 -18556,735,1,2,8.0,17,10.0,10,0.0,65,,60.0,7.0,11,2005-05-08 14:00:00 -18557,735,21,5,2.0,16,9.0,9,0.0,65,,64.0,12.0,11,2005-05-08 14:00:00 -18558,735,13,8,14.0,9,8.0,8,1.0,65,,65.0,11.0,11,2005-05-08 14:00:00 -18559,735,23,8,15.0,11,,18,0.0,9,,9.0,15.0,20,2005-05-08 14:00:00 -18560,735,16,2,7.0,2,6.0,6,3.0,66,5305372.0,62.0,9.0,1,2005-05-08 14:00:00 -18561,735,20,3,6.0,6,5.0,5,4.0,66,5294766.0,66.0,1.0,1,2005-05-08 14:00:00 -18562,735,22,6,17.0,4,4.0,4,5.0,66,5283549.0,63.0,6.0,1,2005-05-08 14:00:00 -18563,735,14,6,16.0,5,3.0,3,6.0,66,5282777.0,63.0,8.0,1,2005-05-08 14:00:00 -18564,735,3,3,5.0,3,2.0,2,8.0,66,5264482.0,59.0,5.0,1,2005-05-08 14:00:00 -18565,735,7,0,9.0,1,1.0,1,10.0,66,5236830.0,41.0,4.0,1,2005-05-08 14:00:00 -18566,735,30,0,10.0,7,7.0,7,2.0,65,,55.0,3.0,11,2005-05-08 14:00:00 -18567,736,7,0,9.0,1,1.0,1,10.0,78,6315556.0,41.0,2.0,1,2005-05-22 14:00:00 -18568,736,38,16,19.0,17,,18,0.0,18,,14.0,18.0,9,2005-05-22 14:00:00 -18569,736,13,8,14.0,7,,17,0.0,23,,15.0,12.0,3,2005-05-22 14:00:00 -18570,736,39,17,20.0,13,,16,0.0,29,,19.0,15.0,3,2005-05-22 14:00:00 -18571,736,23,8,15.0,12,,15,0.0,59,,43.0,14.0,3,2005-05-22 14:00:00 -18572,736,26,17,21.0,14,14.0,14,0.0,73,,22.0,16.0,15,2005-05-22 14:00:00 -18573,736,32,16,18.0,15,13.0,13,0.0,75,,12.0,17.0,13,2005-05-22 14:00:00 -18574,736,34,14,11.0,9,11.0,11,0.0,77,,17.0,11.0,11,2005-05-22 14:00:00 -18575,736,20,3,6.0,4,12.0,12,0.0,77,,20.0,4.0,11,2005-05-22 14:00:00 -18576,736,12,14,12.0,11,9.0,9,0.0,77,,16.0,13.0,11,2005-05-22 14:00:00 -18577,736,21,5,2.0,10,8.0,8,1.0,78,6353126.0,51.0,6.0,1,2005-05-22 14:00:00 -18578,736,29,5,1.0,8,7.0,7,2.0,78,6352779.0,40.0,1.0,1,2005-05-22 14:00:00 -18579,736,22,6,17.0,18,6.0,6,3.0,78,6352673.0,11.0,8.0,1,2005-05-22 14:00:00 -18580,736,30,0,10.0,16,5.0,5,4.0,78,6352203.0,50.0,10.0,1,2005-05-22 14:00:00 -18581,736,3,3,5.0,2,4.0,4,5.0,78,6352043.0,19.0,3.0,1,2005-05-22 14:00:00 -18582,736,16,2,7.0,3,3.0,3,6.0,78,6334040.0,77.0,7.0,1,2005-05-22 14:00:00 -18583,736,14,6,16.0,5,10.0,10,0.0,77,,38.0,5.0,11,2005-05-22 14:00:00 -18584,736,1,2,8.0,6,2.0,2,8.0,78,6329433.0,15.0,9.0,1,2005-05-22 14:00:00 -18585,737,10,15,4.0,16,12.0,12,0.0,58,,26.0,11.0,11,2005-05-29 14:00:00 -18586,737,34,14,11.0,15,13.0,13,0.0,58,,41.0,15.0,11,2005-05-29 14:00:00 -18587,737,32,16,18.0,17,15.0,15,0.0,58,,39.0,17.0,11,2005-05-29 14:00:00 -18588,737,16,2,7.0,3,,20,0.0,0,,,,3,2005-05-29 14:00:00 -18589,737,26,17,21.0,20,17.0,17,0.0,57,,18.0,18.0,12,2005-05-29 14:00:00 -18590,737,39,17,20.0,18,18.0,18,0.0,56,,18.0,19.0,13,2005-05-29 14:00:00 -18591,737,38,16,19.0,19,16.0,16,0.0,58,,21.0,16.0,11,2005-05-29 14:00:00 -18592,737,7,0,9.0,2,11.0,11,0.0,58,,9.0,2.0,3,2005-05-29 14:00:00 -18593,737,22,6,17.0,8,,19,0.0,33,,25.0,8.0,20,2005-05-29 14:00:00 -18594,737,23,8,15.0,14,9.0,9,0.0,59,5578177.0,43.0,13.0,1,2005-05-29 14:00:00 -18595,737,3,3,5.0,6,1.0,1,10.0,59,5506648.0,44.0,1.0,1,2005-05-29 14:00:00 -18596,737,17,15,3.0,13,10.0,10,0.0,59,5602434.0,20.0,12.0,1,2005-05-29 14:00:00 -18597,737,1,2,8.0,1,2.0,2,8.0,59,5523215.0,9.0,4.0,1,2005-05-29 14:00:00 -18598,737,21,5,2.0,7,3.0,3,6.0,59,5525197.0,44.0,3.0,1,2005-05-29 14:00:00 -18599,737,13,8,14.0,12,4.0,4,5.0,59,5538236.0,19.0,5.0,1,2005-05-29 14:00:00 -18600,737,12,14,12.0,11,14.0,14,0.0,58,,18.0,14.0,11,2005-05-29 14:00:00 -18601,737,20,3,6.0,9,6.0,6,3.0,59,5558580.0,47.0,7.0,1,2005-05-29 14:00:00 -18602,737,30,0,10.0,5,7.0,7,2.0,59,5564821.0,42.0,10.0,1,2005-05-29 14:00:00 -18603,737,14,6,16.0,4,8.0,8,1.0,59,5577739.0,43.0,9.0,1,2005-05-29 14:00:00 -18604,737,29,5,1.0,10,5.0,5,4.0,59,5557093.0,19.0,6.0,1,2005-05-29 14:00:00 -18605,738,38,16,19.0,17,,19,0.0,24,,20.0,17.0,22,2005-06-12 13:00:00 -18606,738,20,3,6.0,4,,18,0.0,32,,24.0,5.0,9,2005-06-12 13:00:00 -18607,738,3,3,5.0,3,,17,0.0,38,,38.0,3.0,22,2005-06-12 13:00:00 -18608,738,10,15,4.0,6,,15,0.0,40,,14.0,14.0,23,2005-06-12 13:00:00 -18609,738,1,2,8.0,13,,14,0.0,43,,20.0,9.0,5,2005-06-12 13:00:00 -18610,738,17,15,3.0,1,,13,0.0,46,,30.0,6.0,3,2005-06-12 13:00:00 -18611,738,14,6,16.0,9,,12,0.0,62,,43.0,11.0,23,2005-06-12 13:00:00 -18612,738,26,17,21.0,15,11.0,11,0.0,67,,15.0,19.0,13,2005-06-12 13:00:00 -18613,738,30,0,10.0,5,,20,0.0,52,,24.0,2.0,2,2005-06-12 13:00:00 -18614,738,34,14,11.0,8,9.0,9,0.0,69,,26.0,12.0,11,2005-06-12 13:00:00 -18615,738,7,0,9.0,7,1.0,1,10.0,70,5529290.0,23.0,1.0,1,2005-06-12 13:00:00 -18616,738,32,16,18.0,18,10.0,10,0.0,67,,19.0,18.0,13,2005-06-12 13:00:00 -18617,738,29,5,1.0,2,2.0,2,8.0,70,5530390.0,32.0,4.0,1,2005-06-12 13:00:00 -18618,738,21,5,2.0,20,3.0,3,6.0,70,5569690.0,46.0,8.0,1,2005-06-12 13:00:00 -18619,738,12,14,12.0,11,4.0,4,5.0,70,5584390.0,18.0,13.0,1,2005-06-12 13:00:00 -18620,738,39,17,20.0,19,,16,0.0,39,,33.0,20.0,9,2005-06-12 13:00:00 -18621,738,22,6,17.0,10,6.0,6,3.0,69,,44.0,10.0,11,2005-06-12 13:00:00 -18622,738,31,8,15.0,16,8.0,8,1.0,69,,46.0,15.0,11,2005-06-12 13:00:00 -18623,738,13,8,14.0,12,7.0,7,2.0,69,,17.0,16.0,11,2005-06-12 13:00:00 -18624,738,16,2,7.0,14,5.0,5,4.0,70,5584990.0,23.0,7.0,1,2005-06-12 13:00:00 -18625,739,13,8,14.0,16,,20,0.0,0,,,,54,2005-06-19 14:00:00 -18626,739,1,2,8.0,15,,19,0.0,0,,,,54,2005-06-19 14:00:00 -18627,739,31,8,15.0,14,,18,0.0,0,,,,54,2005-06-19 14:00:00 -18628,739,40,6,17.0,13,,17,0.0,0,,,,54,2005-06-19 14:00:00 -18629,739,30,0,10.0,11,,15,0.0,0,,,,54,2005-06-19 14:00:00 -18630,739,12,14,12.0,10,,14,0.0,0,,,,54,2005-06-19 14:00:00 -18631,739,16,2,7.0,9,,13,0.0,0,,,,54,2005-06-19 14:00:00 -18632,739,10,15,4.0,8,,12,0.0,0,,,,54,2005-06-19 14:00:00 -18633,739,20,3,6.0,4,,10,0.0,0,,,,54,2005-06-19 14:00:00 -18634,739,17,15,3.0,3,,9,0.0,0,,,,54,2005-06-19 14:00:00 -18635,739,7,0,9.0,2,,8,0.0,0,,,,54,2005-06-19 14:00:00 -18636,739,14,6,16.0,1,,7,0.0,0,,,,54,2005-06-19 14:00:00 -18637,739,26,17,21.0,18,5.0,5,4.0,71,,2.0,5.0,12,2005-06-19 14:00:00 -18638,739,38,16,19.0,19,4.0,4,5.0,72,,65.0,4.0,11,2005-06-19 14:00:00 -18639,739,32,16,18.0,17,3.0,3,6.0,72,,44.0,3.0,11,2005-06-19 14:00:00 -18640,739,21,5,2.0,7,2.0,2,8.0,73,5384681.0,48.0,2.0,1,2005-06-19 14:00:00 -18641,739,29,5,1.0,5,1.0,1,10.0,73,5383181.0,48.0,1.0,1,2005-06-19 14:00:00 -18642,739,3,3,5.0,6,,11,0.0,0,,,,54,2005-06-19 14:00:00 -18643,739,39,17,20.0,20,6.0,6,3.0,71,,43.0,6.0,12,2005-06-19 14:00:00 -18644,739,34,14,11.0,12,,16,0.0,0,,,,54,2005-06-19 14:00:00 -18645,740,31,8,15.0,16,,20,0.0,1,,,,32,2005-07-03 14:00:00 -18646,740,3,3,5.0,1,1.0,1,10.0,70,5482232.0,5.0,2.0,1,2005-07-03 14:00:00 -18647,740,7,0,9.0,13,2.0,2,8.0,70,5494032.0,25.0,1.0,1,2005-07-03 14:00:00 -18648,740,29,5,1.0,3,3.0,3,6.0,70,5564132.0,22.0,7.0,1,2005-07-03 14:00:00 -18649,740,17,15,3.0,7,4.0,4,5.0,69,,18.0,4.0,11,2005-07-03 14:00:00 -18650,740,14,6,16.0,2,5.0,5,4.0,69,,67.0,8.0,11,2005-07-03 14:00:00 -18651,740,20,3,6.0,6,6.0,6,3.0,69,,18.0,5.0,11,2005-07-03 14:00:00 -18652,740,22,6,17.0,11,7.0,7,2.0,69,,36.0,14.0,11,2005-07-03 14:00:00 -18653,740,21,5,2.0,5,9.0,9,0.0,69,,4.0,12.0,11,2005-07-03 14:00:00 -18654,740,13,8,14.0,15,10.0,10,0.0,69,,39.0,6.0,11,2005-07-03 14:00:00 -18655,740,10,15,4.0,4,11.0,11,0.0,69,,8.0,11.0,11,2005-07-03 14:00:00 -18656,740,34,14,11.0,10,8.0,8,1.0,69,,17.0,10.0,11,2005-07-03 14:00:00 -18657,740,32,16,18.0,19,13.0,13,0.0,67,,32.0,16.0,13,2005-07-03 14:00:00 -18658,740,1,2,8.0,14,14.0,14,0.0,66,,36.0,13.0,14,2005-07-03 14:00:00 -18659,740,38,16,19.0,17,15.0,15,0.0,66,,9.0,17.0,14,2005-07-03 14:00:00 -18660,740,30,0,10.0,8,,16,0.0,46,,24.0,3.0,5,2005-07-03 14:00:00 -18661,740,26,17,21.0,20,,17,0.0,37,,8.0,18.0,29,2005-07-03 14:00:00 -18662,740,39,17,20.0,18,,18,0.0,33,,4.0,19.0,29,2005-07-03 14:00:00 -18663,740,12,14,12.0,9,,19,0.0,30,,11.0,9.0,9,2005-07-03 14:00:00 -18664,740,16,2,7.0,12,12.0,12,0.0,68,,17.0,15.0,12,2005-07-03 14:00:00 -18665,741,31,8,15.0,15,15.0,15,0.0,59,,58.0,13.0,11,2005-07-10 14:00:00 -18666,741,10,15,4.0,7,16.0,16,0.0,58,,54.0,11.0,12,2005-07-10 14:00:00 -18667,741,32,16,18.0,20,17.0,17,0.0,58,,38.0,17.0,12,2005-07-10 14:00:00 -18668,741,38,16,19.0,17,,20,0.0,10,,8.0,18.0,10,2005-07-10 14:00:00 -18669,741,39,17,20.0,19,19.0,19,0.0,56,,37.0,20.0,14,2005-07-10 14:00:00 -18670,741,7,0,9.0,12,3.0,3,6.0,60,5083988.0,60.0,1.0,1,2005-07-10 14:00:00 -18671,741,34,14,11.0,10,14.0,14,0.0,59,,16.0,14.0,11,2005-07-10 14:00:00 -18672,741,26,17,21.0,18,18.0,18,0.0,57,,53.0,19.0,13,2005-07-10 14:00:00 -18673,741,13,8,14.0,13,13.0,13,0.0,59,,44.0,12.0,11,2005-07-10 14:00:00 -18674,741,3,3,5.0,1,2.0,2,8.0,60,5072288.0,40.0,4.0,1,2005-07-10 14:00:00 -18675,741,16,2,7.0,11,11.0,11,0.0,59,,16.0,15.0,11,2005-07-10 14:00:00 -18676,741,30,0,10.0,3,1.0,1,10.0,60,5069588.0,41.0,2.0,1,2005-07-10 14:00:00 -18677,741,20,3,6.0,6,4.0,4,5.0,60,5087488.0,43.0,3.0,1,2005-07-10 14:00:00 -18678,741,17,15,3.0,2,5.0,5,4.0,60,5109888.0,42.0,7.0,1,2005-07-10 14:00:00 -18679,741,29,5,1.0,9,6.0,6,3.0,60,5144888.0,23.0,5.0,1,2005-07-10 14:00:00 -18680,741,1,2,8.0,14,12.0,12,0.0,59,,58.0,16.0,11,2005-07-10 14:00:00 -18681,741,22,6,17.0,8,8.0,8,1.0,60,5148788.0,46.0,6.0,1,2005-07-10 14:00:00 -18682,741,14,6,16.0,4,9.0,9,0.0,60,5150488.0,56.0,8.0,1,2005-07-10 14:00:00 -18683,741,12,14,12.0,16,10.0,10,0.0,59,,45.0,10.0,11,2005-07-10 14:00:00 -18684,741,21,5,2.0,5,7.0,7,2.0,60,5146188.0,41.0,9.0,1,2005-07-10 14:00:00 -18685,742,7,0,9.0,1,,20,0.0,32,,24.0,1.0,9,2005-07-24 14:00:00 -18686,742,16,2,7.0,6,,19,0.0,55,,46.0,15.0,55,2005-07-24 14:00:00 -18687,742,37,17,20.0,17,18.0,18,0.0,63,,44.0,20.0,14,2005-07-24 14:00:00 -18688,742,32,16,18.0,18,17.0,17,0.0,64,,12.0,17.0,13,2005-07-24 14:00:00 -18689,742,38,16,19.0,19,16.0,16,0.0,64,,7.0,18.0,13,2005-07-24 14:00:00 -18690,742,34,14,11.0,14,15.0,15,0.0,64,,26.0,16.0,13,2005-07-24 14:00:00 -18691,742,14,6,16.0,9,14.0,14,0.0,64,,45.0,11.0,13,2005-07-24 14:00:00 -18692,742,10,15,4.0,8,12.0,12,0.0,66,,27.0,14.0,11,2005-07-24 14:00:00 -18693,742,26,17,21.0,16,13.0,13,0.0,65,,11.0,19.0,12,2005-07-24 14:00:00 -18694,742,21,5,2.0,15,10.0,10,0.0,66,,47.0,12.0,11,2005-07-24 14:00:00 -18695,742,31,8,15.0,10,9.0,9,0.0,67,5258417.0,45.0,9.0,1,2005-07-24 14:00:00 -18696,742,12,14,12.0,13,8.0,8,1.0,67,5245169.0,45.0,10.0,1,2005-07-24 14:00:00 -18697,742,13,8,14.0,11,7.0,7,2.0,67,5241299.0,18.0,8.0,1,2005-07-24 14:00:00 -18698,742,22,6,17.0,12,6.0,6,3.0,67,5240841.0,23.0,6.0,1,2005-07-24 14:00:00 -18699,742,29,5,1.0,5,5.0,5,4.0,67,5240289.0,18.0,7.0,1,2005-07-24 14:00:00 -18700,742,20,3,6.0,4,4.0,4,5.0,67,5239186.0,21.0,5.0,1,2005-07-24 14:00:00 -18701,742,17,15,3.0,2,3.0,3,6.0,67,5213021.0,19.0,3.0,1,2005-07-24 14:00:00 -18702,742,30,0,10.0,20,2.0,2,8.0,67,5211168.0,54.0,4.0,1,2005-07-24 14:00:00 -18703,742,3,3,5.0,3,1.0,1,10.0,67,5188599.0,21.0,2.0,1,2005-07-24 14:00:00 -18704,742,1,2,8.0,7,11.0,11,0.0,66,,10.0,13.0,11,2005-07-24 14:00:00 -18705,743,12,14,12.0,14,14.0,14,0.0,63,,22.0,13.0,17,2005-07-31 14:00:00 -18706,743,26,17,21.0,17,,15,0.0,59,,8.0,18.0,45,2005-07-31 14:00:00 -18707,743,31,8,15.0,11,,20,0.0,0,,,,3,2005-07-31 14:00:00 -18708,743,30,0,10.0,2,,17,0.0,41,,20.0,2.0,30,2005-07-31 14:00:00 -18709,743,13,8,14.0,13,,19,0.0,0,,,,3,2005-07-31 14:00:00 -18710,743,32,16,18.0,20,13.0,13,0.0,66,,15.0,16.0,14,2005-07-31 14:00:00 -18711,743,34,14,11.0,15,,16,0.0,56,,23.0,14.0,56,2005-07-31 14:00:00 -18712,743,38,16,19.0,18,12.0,12,0.0,67,,17.0,15.0,13,2005-07-31 14:00:00 -18713,743,37,17,20.0,19,,18,0.0,26,,16.0,17.0,9,2005-07-31 14:00:00 -18714,743,21,5,2.0,7,10.0,10,0.0,69,,20.0,11.0,11,2005-07-31 14:00:00 -18715,743,3,3,5.0,6,11.0,11,0.0,69,,51.0,12.0,11,2005-07-31 14:00:00 -18716,743,7,0,9.0,4,1.0,1,10.0,70,5845552.0,40.0,1.0,1,2005-07-31 14:00:00 -18717,743,29,5,1.0,1,2.0,2,8.0,70,5881133.0,13.0,3.0,1,2005-07-31 14:00:00 -18718,743,22,6,17.0,5,3.0,3,6.0,70,5881681.0,13.0,5.0,1,2005-07-31 14:00:00 -18719,743,10,15,4.0,10,8.0,8,1.0,69,,45.0,7.0,11,2005-07-31 14:00:00 -18720,743,17,15,3.0,8,5.0,5,4.0,70,5904384.0,70.0,8.0,1,2005-07-31 14:00:00 -18721,743,1,2,8.0,12,6.0,6,3.0,70,5913927.0,53.0,6.0,1,2005-07-31 14:00:00 -18722,743,16,2,7.0,16,7.0,7,2.0,69,,47.0,9.0,11,2005-07-31 14:00:00 -18723,743,20,3,6.0,9,9.0,9,0.0,69,,19.0,10.0,11,2005-07-31 14:00:00 -18724,743,14,6,16.0,3,4.0,4,5.0,70,5899773.0,32.0,4.0,1,2005-07-31 14:00:00 -18725,744,16,2,7.0,7,,20,0.0,20,,12.0,12.0,27,2005-08-21 15:00:00 -18726,744,12,14,12.0,8,,19,0.0,28,,27.0,10.0,5,2005-08-21 15:00:00 -18727,744,1,2,8.0,6,,18,0.0,29,,25.0,16.0,27,2005-08-21 15:00:00 -18728,744,29,5,1.0,19,,17,0.0,32,,21.0,14.0,31,2005-08-21 15:00:00 -18729,744,26,17,21.0,15,,16,0.0,48,,13.0,20.0,31,2005-08-21 15:00:00 -18730,744,32,16,18.0,14,15.0,15,0.0,55,,50.0,17.0,13,2005-08-21 15:00:00 -18731,744,38,16,19.0,18,14.0,14,0.0,55,,42.0,19.0,13,2005-08-21 15:00:00 -18732,744,37,17,20.0,17,13.0,13,0.0,55,,53.0,18.0,13,2005-08-21 15:00:00 -18733,744,22,6,17.0,9,12.0,12,0.0,57,,38.0,15.0,11,2005-08-21 15:00:00 -18734,744,34,14,11.0,16,11.0,11,0.0,57,,44.0,13.0,11,2005-08-21 15:00:00 -18735,744,10,15,4.0,20,9.0,9,0.0,58,5154441.0,54.0,6.0,1,2005-08-21 15:00:00 -18736,744,13,8,14.0,12,7.0,7,2.0,58,5143746.0,58.0,9.0,1,2005-08-21 15:00:00 -18737,744,14,6,16.0,5,6.0,6,3.0,58,5129874.0,52.0,7.0,1,2005-08-21 15:00:00 -18738,744,17,15,3.0,13,5.0,5,4.0,58,5113758.0,58.0,5.0,1,2005-08-21 15:00:00 -18739,744,20,3,6.0,2,4.0,4,5.0,58,5112427.0,34.0,4.0,1,2005-08-21 15:00:00 -18740,744,30,0,10.0,4,3.0,3,6.0,58,5094089.0,39.0,1.0,1,2005-08-21 15:00:00 -18741,744,3,3,5.0,3,2.0,2,8.0,58,5093063.0,58.0,3.0,1,2005-08-21 15:00:00 -18742,744,7,0,9.0,1,1.0,1,10.0,58,5074454.0,40.0,2.0,1,2005-08-21 15:00:00 -18743,744,21,5,2.0,11,10.0,10,0.0,57,,45.0,11.0,11,2005-08-21 15:00:00 -18744,744,31,8,15.0,10,8.0,8,1.0,58,5146076.0,58.0,8.0,1,2005-08-21 15:00:00 -18745,745,38,16,19.0,19,20.0,20,0.0,50,,17.0,19.0,13,2005-09-04 14:00:00 -18746,745,26,17,21.0,20,19.0,19,0.0,51,,33.0,18.0,12,2005-09-04 14:00:00 -18747,745,37,17,20.0,18,18.0,18,0.0,51,,31.0,20.0,12,2005-09-04 14:00:00 -18748,745,30,0,10.0,1,1.0,1,10.0,53,4468659.0,15.0,2.0,1,2005-09-04 14:00:00 -18749,745,32,16,18.0,17,17.0,17,0.0,51,,9.0,17.0,12,2005-09-04 14:00:00 -18750,745,10,15,4.0,4,16.0,16,0.0,52,,14.0,10.0,11,2005-09-04 14:00:00 -18751,745,13,8,14.0,10,15.0,15,0.0,52,,18.0,15.0,11,2005-09-04 14:00:00 -18752,745,16,2,7.0,14,14.0,14,0.0,52,,40.0,7.0,11,2005-09-04 14:00:00 -18753,745,21,5,2.0,7,12.0,12,0.0,52,,13.0,12.0,11,2005-09-04 14:00:00 -18754,745,34,14,11.0,12,11.0,11,0.0,52,,13.0,16.0,11,2005-09-04 14:00:00 -18755,745,29,5,1.0,6,10.0,10,0.0,53,4564729.0,5.0,13.0,1,2005-09-04 14:00:00 -18756,745,31,8,15.0,13,13.0,13,0.0,52,,17.0,14.0,11,2005-09-04 14:00:00 -18757,745,17,15,3.0,3,8.0,8,1.0,53,4532294.0,16.0,9.0,1,2005-09-04 14:00:00 -18758,745,41,2,8.0,16,7.0,7,2.0,53,4513302.0,21.0,6.0,1,2005-09-04 14:00:00 -18759,745,22,6,17.0,9,6.0,6,3.0,53,4512584.0,19.0,8.0,1,2005-09-04 14:00:00 -18760,745,14,6,16.0,5,5.0,5,4.0,53,4502445.0,19.0,5.0,1,2005-09-04 14:00:00 -18761,745,7,0,9.0,11,4.0,4,5.0,53,4491434.0,51.0,1.0,1,2005-09-04 14:00:00 -18762,745,20,3,6.0,8,3.0,3,6.0,53,4486634.0,16.0,4.0,1,2005-09-04 14:00:00 -18763,745,3,3,5.0,2,2.0,2,8.0,53,4471138.0,16.0,3.0,1,2005-09-04 14:00:00 -18764,745,12,14,12.0,15,9.0,9,0.0,53,4544072.0,18.0,11.0,1,2005-09-04 14:00:00 -18765,746,30,0,10.0,1,14.0,14,0.0,40,,14.0,9.0,4,2005-09-11 14:00:00 -18766,746,41,2,8.0,15,15.0,15,0.0,39,,32.0,15.0,4,2005-09-11 14:00:00 -18767,746,14,6,16.0,3,,16,0.0,34,,3.0,11.0,3,2005-09-11 14:00:00 -18768,746,20,3,6.0,13,,20,0.0,10,,9.0,12.0,3,2005-09-11 14:00:00 -18769,746,29,5,1.0,6,,18,0.0,13,,10.0,13.0,3,2005-09-11 14:00:00 -18770,746,10,15,4.0,10,,19,0.0,13,,10.0,14.0,3,2005-09-11 14:00:00 -18771,746,37,17,20.0,17,13.0,13,0.0,41,,38.0,19.0,13,2005-09-11 14:00:00 -18772,746,13,8,14.0,11,,17,0.0,18,,8.0,18.0,5,2005-09-11 14:00:00 -18773,746,26,17,21.0,18,12.0,12,0.0,42,,6.0,20.0,12,2005-09-11 14:00:00 -18774,746,22,6,17.0,5,7.0,7,2.0,44,5488795.0,43.0,1.0,1,2005-09-11 14:00:00 -18775,746,12,14,12.0,7,10.0,10,0.0,43,,28.0,16.0,11,2005-09-11 14:00:00 -18776,746,38,16,19.0,20,11.0,11,0.0,43,,43.0,8.0,11,2005-09-11 14:00:00 -18777,746,3,3,5.0,4,2.0,2,8.0,44,5429595.0,31.0,10.0,1,2005-09-11 14:00:00 -18778,746,17,15,3.0,8,3.0,3,6.0,44,5433295.0,44.0,5.0,1,2005-09-11 14:00:00 -18779,746,16,2,7.0,9,4.0,4,5.0,44,5470395.0,44.0,2.0,1,2005-09-11 14:00:00 -18780,746,7,0,9.0,2,1.0,1,10.0,44,5401295.0,34.0,6.0,1,2005-09-11 14:00:00 -18781,746,34,14,11.0,14,6.0,6,3.0,44,5488695.0,44.0,7.0,1,2005-09-11 14:00:00 -18782,746,32,16,18.0,19,8.0,8,1.0,43,,41.0,17.0,11,2005-09-11 14:00:00 -18783,746,31,8,15.0,16,9.0,9,0.0,43,,43.0,3.0,11,2005-09-11 14:00:00 -18784,746,21,5,2.0,12,5.0,5,4.0,44,5479395.0,44.0,4.0,1,2005-09-11 14:00:00 -18785,747,14,6,16.0,17,13.0,13,0.0,69,,69.0,7.0,12,2005-09-25 14:00:00 -18786,747,13,8,14.0,14,,20,0.0,0,,,,3,2005-09-25 14:00:00 -18787,747,41,2,8.0,13,,19,0.0,0,,,,3,2005-09-25 14:00:00 -18788,747,37,17,20.0,18,,18,0.0,34,,16.0,18.0,5,2005-09-25 14:00:00 -18789,747,16,2,7.0,12,,17,0.0,45,,45.0,8.0,58,2005-09-25 14:00:00 -18790,747,32,16,18.0,11,,16,0.0,55,,41.0,16.0,26,2005-09-25 14:00:00 -18791,747,38,16,19.0,15,15.0,15,0.0,68,,41.0,15.0,13,2005-09-25 14:00:00 -18792,747,26,17,21.0,16,14.0,14,0.0,69,,19.0,17.0,12,2005-09-25 14:00:00 -18793,747,34,14,11.0,20,12.0,12,0.0,70,,25.0,12.0,11,2005-09-25 14:00:00 -18794,747,30,0,10.0,2,1.0,1,10.0,71,5360574.0,27.0,2.0,1,2005-09-25 14:00:00 -18795,747,10,15,4.0,19,10.0,10,0.0,70,,32.0,14.0,11,2005-09-25 14:00:00 -18796,747,7,0,9.0,5,2.0,2,8.0,71,5363101.0,29.0,1.0,1,2005-09-25 14:00:00 -18797,747,3,3,5.0,1,3.0,3,6.0,71,5385414.0,21.0,3.0,1,2005-09-25 14:00:00 -18798,747,29,5,1.0,7,4.0,4,5.0,71,5396242.0,25.0,4.0,1,2005-09-25 14:00:00 -18799,747,20,3,6.0,3,5.0,5,4.0,71,5400792.0,11.0,5.0,1,2005-09-25 14:00:00 -18800,747,12,14,12.0,8,11.0,11,0.0,70,,70.0,13.0,11,2005-09-25 14:00:00 -18801,747,17,15,3.0,4,7.0,7,2.0,70,,24.0,10.0,11,2005-09-25 14:00:00 -18802,747,22,6,17.0,10,8.0,8,1.0,70,,25.0,9.0,11,2005-09-25 14:00:00 -18803,747,31,8,15.0,6,9.0,9,0.0,70,,50.0,11.0,11,2005-09-25 14:00:00 -18804,747,21,5,2.0,9,6.0,6,3.0,71,5429747.0,49.0,6.0,1,2005-09-25 14:00:00 -18805,748,32,16,18.0,20,13.0,13,0.0,52,,17.0,14.0,11,2005-10-09 14:00:00 -18806,748,10,15,4.0,5,,20,0.0,52,,28.0,13.0,2,2005-10-09 14:00:00 -18807,748,30,0,10.0,18,,19,0.0,0,,,,3,2005-10-09 14:00:00 -18808,748,14,6,16.0,19,,18,0.0,9,,9.0,19.0,3,2005-10-09 14:00:00 -18809,748,41,2,8.0,12,,17,0.0,9,,9.0,18.0,3,2005-10-09 14:00:00 -18810,748,26,17,21.0,13,16.0,16,0.0,49,,33.0,16.0,14,2005-10-09 14:00:00 -18811,748,38,16,19.0,11,15.0,15,0.0,51,,11.0,15.0,12,2005-10-09 14:00:00 -18812,748,37,17,20.0,15,14.0,14,0.0,51,,50.0,17.0,12,2005-10-09 14:00:00 -18813,748,34,14,11.0,8,12.0,12,0.0,53,5425433.0,50.0,11.0,1,2005-10-09 14:00:00 -18814,748,21,5,2.0,9,11.0,11,0.0,53,5402845.0,52.0,9.0,1,2005-10-09 14:00:00 -18815,748,12,14,12.0,10,10.0,10,0.0,53,5399721.0,43.0,10.0,1,2005-10-09 14:00:00 -18816,748,20,3,6.0,3,2.0,2,8.0,53,5343845.0,19.0,3.0,1,2005-10-09 14:00:00 -18817,748,3,3,5.0,16,3.0,3,6.0,53,5359668.0,21.0,2.0,1,2005-10-09 14:00:00 -18818,748,16,2,7.0,7,4.0,4,5.0,53,5364486.0,21.0,7.0,1,2005-10-09 14:00:00 -18819,748,17,15,3.0,2,5.0,5,4.0,53,5371719.0,19.0,4.0,1,2005-10-09 14:00:00 -18820,748,7,0,9.0,17,1.0,1,10.0,53,5342212.0,44.0,1.0,1,2005-10-09 14:00:00 -18821,748,29,5,1.0,14,7.0,7,2.0,53,5376091.0,25.0,5.0,1,2005-10-09 14:00:00 -18822,748,22,6,17.0,1,8.0,8,1.0,53,5391760.0,9.0,6.0,1,2005-10-09 14:00:00 -18823,748,31,8,15.0,4,9.0,9,0.0,53,5394137.0,49.0,12.0,1,2005-10-09 14:00:00 -18824,748,13,8,14.0,6,6.0,6,3.0,53,5373813.0,18.0,8.0,1,2005-10-09 14:00:00 -18825,749,21,5,2.0,8,12.0,12,0.0,56,6086418.0,18.0,13.0,1,2005-10-16 14:00:00 -18826,749,30,0,10.0,5,,19,0.0,24,,15.0,8.0,5,2005-10-16 14:00:00 -18827,749,38,16,19.0,15,,18,0.0,28,,17.0,20.0,3,2005-10-16 14:00:00 -18828,749,10,15,4.0,17,,17,0.0,34,,17.0,15.0,6,2005-10-16 14:00:00 -18829,749,26,17,21.0,18,16.0,16,0.0,50,,48.0,19.0,61,2005-10-16 14:00:00 -18830,749,14,6,16.0,12,15.0,15,0.0,55,,16.0,14.0,11,2005-10-16 14:00:00 -18831,749,37,17,20.0,20,14.0,14,0.0,55,,54.0,18.0,60,2005-10-16 14:00:00 -18832,749,41,2,8.0,13,13.0,13,0.0,55,,52.0,9.0,59,2005-10-16 14:00:00 -18833,749,32,16,18.0,19,11.0,11,0.0,56,6078218.0,13.0,17.0,1,2005-10-16 14:00:00 -18834,749,29,5,1.0,6,,20,0.0,20,,16.0,16.0,20,2005-10-16 14:00:00 -18835,749,13,8,14.0,7,9.0,9,0.0,56,6037818.0,54.0,10.0,1,2005-10-16 14:00:00 -18836,749,17,15,3.0,4,8.0,8,1.0,56,6034818.0,53.0,12.0,1,2005-10-16 14:00:00 -18837,749,16,2,7.0,10,7.0,7,2.0,56,6030418.0,53.0,7.0,1,2005-10-16 14:00:00 -18838,749,12,14,12.0,11,6.0,6,3.0,56,6030018.0,43.0,6.0,1,2005-10-16 14:00:00 -18839,749,31,8,15.0,14,5.0,5,4.0,56,6025418.0,43.0,4.0,1,2005-10-16 14:00:00 -18840,749,20,3,6.0,2,4.0,4,5.0,56,6019718.0,54.0,3.0,1,2005-10-16 14:00:00 -18841,749,22,6,17.0,9,3.0,3,6.0,56,6018918.0,44.0,5.0,1,2005-10-16 14:00:00 -18842,749,7,0,9.0,3,2.0,2,8.0,56,5997618.0,56.0,1.0,1,2005-10-16 14:00:00 -18843,749,34,14,11.0,16,10.0,10,0.0,56,6053518.0,53.0,11.0,1,2005-10-16 14:00:00 -18844,749,3,3,5.0,1,1.0,1,10.0,56,5993618.0,45.0,2.0,1,2005-10-16 14:00:00 -18845,750,21,10,11.0,6,15.0,15,0.0,56,,14.0,15.0,11,2006-03-12 14:30:00 -18846,750,14,6,8.0,14,16.0,16,0.0,56,,24.0,18.0,11,2006-03-12 14:30:00 -18847,750,32,12,18.0,19,17.0,17,0.0,55,,41.0,19.0,12,2006-03-12 14:30:00 -18848,750,10,7,22.0,20,18.0,18,0.0,53,,17.0,20.0,14,2006-03-12 14:30:00 -18849,750,26,12,19.0,18,,22,0.0,0,,,,30,2006-03-12 14:30:00 -18850,750,34,1,17.0,11,,20,0.0,29,,20.0,13.0,5,2006-03-12 14:30:00 -18851,750,20,3,2.0,9,,21,0.0,21,,15.0,17.0,9,2006-03-12 14:30:00 -18852,750,22,6,7.0,17,14.0,14,0.0,56,,25.0,16.0,11,2006-03-12 14:30:00 -18853,750,33,7,23.0,21,,19,0.0,35,,11.0,21.0,26,2006-03-12 14:30:00 -18854,750,25,4,21.0,16,13.0,13,0.0,56,,45.0,9.0,11,2006-03-12 14:30:00 -18855,750,1,1,16.0,10,12.0,12,0.0,56,,26.0,14.0,11,2006-03-12 14:30:00 -18856,750,23,4,20.0,15,11.0,11,0.0,57,5472202.0,26.0,12.0,1,2006-03-12 14:30:00 -18857,750,29,5,5.0,1,2.0,2,8.0,57,5387451.0,38.0,2.0,1,2006-03-12 14:30:00 -18858,750,7,0,3.0,22,3.0,3,6.0,57,5405565.0,29.0,8.0,1,2006-03-12 14:30:00 -18859,750,17,10,12.0,3,4.0,4,5.0,57,5406197.0,39.0,5.0,1,2006-03-12 14:30:00 -18860,750,30,0,4.0,5,5.0,5,4.0,57,5423253.0,21.0,7.0,1,2006-03-12 14:30:00 -18861,750,3,3,1.0,4,1.0,1,10.0,57,5386205.0,21.0,3.0,1,2006-03-12 14:30:00 -18862,750,2,2,10.0,12,7.0,7,2.0,57,5449248.0,42.0,1.0,1,2006-03-12 14:30:00 -18863,750,31,8,15.0,8,8.0,8,1.0,57,5452976.0,40.0,10.0,1,2006-03-12 14:30:00 -18864,750,12,5,6.0,2,9.0,9,0.0,57,5456112.0,28.0,6.0,1,2006-03-12 14:30:00 -18865,750,13,8,14.0,13,10.0,10,0.0,57,5461746.0,26.0,11.0,1,2006-03-12 14:30:00 -18866,750,16,2,9.0,7,6.0,6,3.0,57,5428137.0,25.0,4.0,1,2006-03-12 14:30:00 -18867,751,10,7,22.0,17,14.0,14,0.0,53,,14.0,20.0,13,2006-03-19 15:00:00 -18868,751,7,0,3.0,6,,22,0.0,0,,,,3,2006-03-19 15:00:00 -18869,751,2,2,10.0,3,,21,0.0,6,,6.0,15.0,5,2006-03-19 15:00:00 -18870,751,13,8,14.0,19,,20,0.0,10,,4.0,17.0,9,2006-03-19 15:00:00 -18871,751,16,2,9.0,4,,19,0.0,15,,12.0,12.0,9,2006-03-19 15:00:00 -18872,751,31,8,15.0,8,,18,0.0,26,,14.0,13.0,9,2006-03-19 15:00:00 -18873,751,33,7,23.0,18,,17,0.0,33,,18.0,21.0,26,2006-03-19 15:00:00 -18874,751,25,4,21.0,12,,16,0.0,41,,25.0,14.0,8,2006-03-19 15:00:00 -18875,751,1,1,16.0,11,,15,0.0,48,,41.0,7.0,5,2006-03-19 15:00:00 -18876,751,32,12,18.0,16,13.0,13,0.0,54,,39.0,19.0,12,2006-03-19 15:00:00 -18877,751,20,3,2.0,1,1.0,1,10.0,56,5440529.0,16.0,2.0,1,2006-03-19 15:00:00 -18878,751,23,4,20.0,13,11.0,11,0.0,54,,40.0,16.0,12,2006-03-19 15:00:00 -18879,751,21,10,11.0,20,10.0,10,0.0,55,,54.0,10.0,11,2006-03-19 15:00:00 -18880,751,14,6,8.0,9,9.0,9,0.0,55,,52.0,11.0,11,2006-03-19 15:00:00 -18881,751,22,6,7.0,22,8.0,8,1.0,56,5521817.0,34.0,6.0,1,2006-03-19 15:00:00 -18882,751,34,1,17.0,10,7.0,7,2.0,56,5520990.0,43.0,9.0,1,2006-03-19 15:00:00 -18883,751,29,5,5.0,14,6.0,6,3.0,56,5484383.0,44.0,5.0,1,2006-03-19 15:00:00 -18884,751,12,5,6.0,21,5.0,5,4.0,56,5483783.0,51.0,8.0,1,2006-03-19 15:00:00 -18885,751,30,0,4.0,5,4.0,4,5.0,56,5479880.0,39.0,3.0,1,2006-03-19 15:00:00 -18886,751,17,10,12.0,2,3.0,3,6.0,56,5450160.0,35.0,4.0,1,2006-03-19 15:00:00 -18887,751,3,3,1.0,7,2.0,2,8.0,56,5445114.0,45.0,1.0,1,2006-03-19 15:00:00 -18888,751,26,12,19.0,15,12.0,12,0.0,54,,34.0,18.0,12,2006-03-19 15:00:00 -18889,752,30,0,4.0,5,,14,0.0,46,,45.0,4.0,10,2006-04-02 14:00:00 -18890,752,32,12,18.0,20,,15,0.0,39,,31.0,16.0,26,2006-04-02 14:00:00 -18891,752,23,4,20.0,12,,16,0.0,37,,25.0,11.0,3,2006-04-02 14:00:00 -18892,752,29,5,5.0,10,,17,0.0,32,,27.0,3.0,3,2006-04-02 14:00:00 -18893,752,12,5,6.0,15,,22,0.0,0,,,,3,2006-04-02 14:00:00 -18894,752,31,8,15.0,13,,19,0.0,4,,4.0,19.0,3,2006-04-02 14:00:00 -18895,752,33,7,23.0,22,13.0,13,0.0,54,,49.0,18.0,13,2006-04-02 14:00:00 -18896,752,2,2,10.0,14,,21,0.0,0,,,,3,2006-04-02 14:00:00 -18897,752,16,2,9.0,7,,18,0.0,22,,19.0,9.0,7,2006-04-02 14:00:00 -18898,752,10,7,22.0,21,12.0,12,0.0,55,,54.0,17.0,12,2006-04-02 14:00:00 -18899,752,14,6,8.0,9,,20,0.0,0,,,,3,2006-04-02 14:00:00 -18900,752,17,10,12.0,1,10.0,10,0.0,56,,17.0,8.0,11,2006-04-02 14:00:00 -18901,752,3,3,1.0,3,1.0,1,10.0,57,5667870.0,49.0,2.0,1,2006-04-02 14:00:00 -18902,752,7,0,3.0,4,2.0,2,8.0,57,5669670.0,57.0,1.0,1,2006-04-02 14:00:00 -18903,752,22,6,7.0,6,3.0,3,6.0,57,5692670.0,45.0,10.0,1,2006-04-02 14:00:00 -18904,752,1,1,16.0,8,4.0,4,5.0,57,5698870.0,49.0,7.0,1,2006-04-02 14:00:00 -18905,752,26,12,19.0,17,11.0,11,0.0,56,,53.0,15.0,11,2006-04-02 14:00:00 -18906,752,34,1,17.0,19,6.0,6,3.0,57,5717370.0,56.0,13.0,1,2006-04-02 14:00:00 -18907,752,21,10,11.0,16,7.0,7,2.0,57,5719770.0,32.0,6.0,1,2006-04-02 14:00:00 -18908,752,13,8,14.0,11,8.0,8,1.0,57,5721770.0,32.0,12.0,1,2006-04-02 14:00:00 -18909,752,25,4,21.0,18,9.0,9,0.0,57,5746670.0,26.0,14.0,1,2006-04-02 14:00:00 -18910,752,20,3,2.0,2,5.0,5,4.0,57,5705970.0,53.0,5.0,1,2006-04-02 14:00:00 -18911,753,23,4,20.0,16,14.0,14,0.0,61,,43.0,11.0,11,2006-04-23 14:00:00 -18912,753,26,12,19.0,20,,22,0.0,0,,,,3,2006-04-23 14:00:00 -18913,753,14,6,8.0,9,,21,0.0,5,,4.0,19.0,38,2006-04-23 14:00:00 -18914,753,33,7,23.0,22,,20,0.0,23,,15.0,21.0,22,2006-04-23 14:00:00 -18915,753,31,8,15.0,17,,19,0.0,40,,30.0,16.0,9,2006-04-23 14:00:00 -18916,753,10,7,22.0,21,,18,0.0,44,,40.0,20.0,20,2006-04-23 14:00:00 -18917,753,13,8,14.0,14,,17,0.0,47,,41.0,17.0,30,2006-04-23 14:00:00 -18918,753,32,12,18.0,19,16.0,16,0.0,60,,53.0,18.0,12,2006-04-23 14:00:00 -18919,753,25,4,21.0,18,15.0,15,0.0,61,,57.0,14.0,11,2006-04-23 14:00:00 -18920,753,1,1,16.0,15,13.0,13,0.0,61,,53.0,12.0,11,2006-04-23 14:00:00 -18921,753,34,1,17.0,12,12.0,12,0.0,62,5548856.0,53.0,8.0,1,2006-04-23 14:00:00 -18922,753,2,2,10.0,13,11.0,11,0.0,62,5546161.0,30.0,15.0,1,2006-04-23 14:00:00 -18923,753,3,3,1.0,5,2.0,2,8.0,62,5468582.0,23.0,1.0,1,2006-04-23 14:00:00 -18924,753,30,0,4.0,7,3.0,3,6.0,62,5482354.0,22.0,4.0,1,2006-04-23 14:00:00 -18925,753,12,5,6.0,4,4.0,4,5.0,62,5483582.0,12.0,10.0,1,2006-04-23 14:00:00 -18926,753,7,0,3.0,8,5.0,5,4.0,62,5484010.0,49.0,3.0,1,2006-04-23 14:00:00 -18927,753,29,5,5.0,1,1.0,1,10.0,62,5466486.0,19.0,2.0,1,2006-04-23 14:00:00 -18928,753,17,10,12.0,2,7.0,7,2.0,62,5506121.0,29.0,6.0,1,2006-04-23 14:00:00 -18929,753,20,3,2.0,11,8.0,8,1.0,62,5506686.0,43.0,7.0,1,2006-04-23 14:00:00 -18930,753,22,6,7.0,6,9.0,9,0.0,62,5511997.0,45.0,5.0,1,2006-04-23 14:00:00 -18931,753,21,10,11.0,3,10.0,10,0.0,62,5544337.0,12.0,13.0,1,2006-04-23 14:00:00 -18932,753,16,2,9.0,10,6.0,6,3.0,62,5504225.0,39.0,9.0,1,2006-04-23 14:00:00 -18933,754,22,6,7.0,10,,14,0.0,52,,27.0,8.0,5,2006-05-07 14:00:00 -18934,754,23,4,20.0,14,,22,0.0,0,,,,3,2006-05-07 14:00:00 -18935,754,13,8,14.0,12,,21,0.0,2,,2.0,21.0,3,2006-05-07 14:00:00 -18936,754,16,2,9.0,19,,20,0.0,12,,11.0,16.0,9,2006-05-07 14:00:00 -18937,754,31,8,15.0,15,,19,0.0,28,,16.0,15.0,6,2006-05-07 14:00:00 -18938,754,17,10,12.0,6,,18,0.0,28,,9.0,13.0,5,2006-05-07 14:00:00 -18939,754,35,7,23.0,21,,17,0.0,29,,21.0,20.0,9,2006-05-07 14:00:00 -18940,754,10,7,22.0,20,,16,0.0,45,,26.0,19.0,9,2006-05-07 14:00:00 -18941,754,30,0,4.0,8,,15,0.0,52,,47.0,6.0,5,2006-05-07 14:00:00 -18942,754,26,12,19.0,16,13.0,13,0.0,59,,35.0,17.0,11,2006-05-07 14:00:00 -18943,754,29,5,5.0,2,1.0,1,10.0,60,5758765.0,39.0,1.0,1,2006-05-07 14:00:00 -18944,754,25,4,21.0,17,11.0,11,0.0,59,,57.0,14.0,11,2006-05-07 14:00:00 -18945,754,1,1,16.0,13,10.0,10,0.0,59,,47.0,11.0,11,2006-05-07 14:00:00 -18946,754,14,6,8.0,7,9.0,9,0.0,59,,58.0,10.0,11,2006-05-07 14:00:00 -18947,754,34,1,17.0,9,8.0,8,1.0,60,5848129.0,38.0,12.0,1,2006-05-07 14:00:00 -18948,754,2,2,10.0,22,7.0,7,2.0,60,5833330.0,48.0,7.0,1,2006-05-07 14:00:00 -18949,754,20,3,2.0,11,6.0,6,3.0,60,5832881.0,46.0,4.0,1,2006-05-07 14:00:00 -18950,754,21,10,11.0,4,5.0,5,4.0,60,5831351.0,59.0,9.0,1,2006-05-07 14:00:00 -18951,754,7,0,3.0,5,4.0,4,5.0,60,5763644.0,43.0,2.0,1,2006-05-07 14:00:00 -18952,754,12,5,6.0,3,3.0,3,6.0,60,5763212.0,19.0,5.0,1,2006-05-07 14:00:00 -18953,754,3,3,1.0,1,2.0,2,8.0,60,5762516.0,37.0,3.0,1,2006-05-07 14:00:00 -18954,754,32,12,18.0,18,12.0,12,0.0,59,,41.0,18.0,11,2006-05-07 14:00:00 -18955,755,23,4,20.0,15,15.0,15,0.0,63,,52.0,14.0,9,2006-05-14 14:00:00 -18956,755,32,12,18.0,17,16.0,16,0.0,63,,28.0,18.0,13,2006-05-14 14:00:00 -18957,755,10,7,22.0,19,17.0,17,0.0,62,,42.0,21.0,14,2006-05-14 14:00:00 -18958,755,13,8,14.0,21,14.0,14,0.0,65,,55.0,9.0,11,2006-05-14 14:00:00 -18959,755,35,7,23.0,20,,22,0.0,10,,9.0,22.0,30,2006-05-14 14:00:00 -18960,755,25,4,21.0,16,,19,0.0,47,,41.0,16.0,5,2006-05-14 14:00:00 -18961,755,22,6,7.0,6,,20,0.0,31,,24.0,17.0,40,2006-05-14 14:00:00 -18962,755,30,0,4.0,12,,21,0.0,17,,17.0,19.0,20,2006-05-14 14:00:00 -18963,755,26,12,19.0,18,,18,0.0,48,,28.0,20.0,41,2006-05-14 14:00:00 -18964,755,31,8,15.0,14,13.0,13,0.0,65,,59.0,15.0,11,2006-05-14 14:00:00 -18965,755,17,10,12.0,8,6.0,6,3.0,66,5240106.0,40.0,6.0,1,2006-05-14 14:00:00 -18966,755,2,2,10.0,13,11.0,11,0.0,65,,51.0,8.0,11,2006-05-14 14:00:00 -18967,755,14,6,8.0,7,10.0,10,0.0,65,,42.0,13.0,11,2006-05-14 14:00:00 -18968,755,16,2,9.0,11,9.0,9,0.0,65,,61.0,11.0,11,2006-05-14 14:00:00 -18969,755,1,1,16.0,10,8.0,8,1.0,65,,49.0,10.0,11,2006-05-14 14:00:00 -18970,755,21,10,11.0,5,7.0,7,2.0,65,,40.0,7.0,11,2006-05-14 14:00:00 -18971,755,7,0,3.0,9,5.0,5,4.0,66,5238634.0,40.0,5.0,1,2006-05-14 14:00:00 -18972,755,12,5,6.0,4,4.0,4,5.0,66,5211612.0,42.0,1.0,1,2006-05-14 14:00:00 -18973,755,20,3,2.0,2,3.0,3,6.0,66,5205710.0,38.0,4.0,1,2006-05-14 14:00:00 -18974,755,29,5,5.0,3,2.0,2,8.0,66,5200261.0,43.0,3.0,1,2006-05-14 14:00:00 -18975,755,3,3,1.0,1,1.0,1,10.0,66,5181759.0,39.0,2.0,1,2006-05-14 14:00:00 -18976,755,34,1,17.0,22,12.0,12,0.0,65,,62.0,12.0,11,2006-05-14 14:00:00 -18977,756,34,1,17.0,14,14.0,14,0.0,77,,74.0,18.0,11,2006-05-28 14:00:00 -18978,756,32,12,18.0,17,15.0,15,0.0,76,,71.0,13.0,12,2006-05-28 14:00:00 -18979,756,35,7,23.0,20,16.0,16,0.0,75,,72.0,22.0,13,2006-05-28 14:00:00 -18980,756,10,7,22.0,19,,22,0.0,46,,39.0,21.0,10,2006-05-28 14:00:00 -18981,756,2,2,10.0,8,,19,0.0,51,,43.0,9.0,3,2006-05-28 14:00:00 -18982,756,7,0,3.0,3,,20,0.0,50,,19.0,2.0,42,2006-05-28 14:00:00 -18983,756,16,2,9.0,2,,21,0.0,48,,23.0,4.0,43,2006-05-28 14:00:00 -18984,756,25,4,21.0,18,13.0,13,0.0,77,,77.0,14.0,11,2006-05-28 14:00:00 -18985,756,31,8,15.0,11,,18,0.0,56,,19.0,20.0,7,2006-05-28 14:00:00 -18986,756,26,12,19.0,16,12.0,12,0.0,77,,77.0,16.0,11,2006-05-28 14:00:00 -18987,756,14,6,8.0,6,17.0,17,0.0,72,,30.0,8.0,9,2006-05-28 14:00:00 -18988,756,23,4,20.0,12,10.0,10,0.0,77,,75.0,17.0,11,2006-05-28 14:00:00 -18989,756,17,10,12.0,13,11.0,11,0.0,77,,59.0,10.0,11,2006-05-28 14:00:00 -18990,756,30,0,4.0,4,2.0,2,8.0,78,6237683.0,20.0,6.0,1,2006-05-28 14:00:00 -18991,756,13,8,14.0,7,3.0,3,6.0,78,6275414.0,45.0,19.0,1,2006-05-28 14:00:00 -18992,756,21,10,11.0,5,4.0,4,5.0,78,6276453.0,67.0,12.0,1,2006-05-28 14:00:00 -18993,756,3,3,1.0,1,1.0,1,10.0,78,6223116.0,11.0,3.0,1,2006-05-28 14:00:00 -18994,756,20,3,2.0,9,6.0,6,3.0,78,6285188.0,58.0,5.0,1,2006-05-28 14:00:00 -18995,756,1,1,16.0,15,7.0,7,2.0,77,,72.0,11.0,11,2006-05-28 14:00:00 -18996,756,22,6,7.0,10,8.0,8,1.0,77,,72.0,15.0,11,2006-05-28 14:00:00 -18997,756,12,5,6.0,21,9.0,9,0.0,77,,40.0,7.0,11,2006-05-28 14:00:00 -18998,756,29,5,5.0,22,5.0,5,4.0,78,6276946.0,74.0,1.0,1,2006-05-28 14:00:00 -18999,757,23,4,20.0,13,13.0,13,0.0,59,,25.0,15.0,11,2006-06-11 12:00:00 -19000,757,25,4,21.0,15,,20,0.0,1,,,,3,2006-06-11 12:00:00 -19001,757,17,10,12.0,19,,19,0.0,8,,8.0,17.0,44,2006-06-11 12:00:00 -19002,757,35,7,23.0,21,18.0,18,0.0,57,,26.0,19.0,13,2006-06-11 12:00:00 -19003,757,10,7,22.0,20,17.0,17,0.0,57,,23.0,18.0,13,2006-06-11 12:00:00 -19004,757,32,12,18.0,16,16.0,16,0.0,58,,25.0,16.0,12,2006-06-11 12:00:00 -19005,757,26,12,19.0,18,15.0,15,0.0,59,,27.0,13.0,11,2006-06-11 12:00:00 -19006,757,31,8,15.0,14,14.0,14,0.0,59,,30.0,12.0,11,2006-06-11 12:00:00 -19007,757,13,8,14.0,11,12.0,12,0.0,59,,42.0,14.0,11,2006-06-11 12:00:00 -19008,757,30,0,4.0,8,6.0,6,3.0,60,5216696.0,38.0,8.0,1,2006-06-11 12:00:00 -19009,757,21,10,11.0,6,10.0,10,0.0,59,,38.0,11.0,11,2006-06-11 12:00:00 -19010,757,2,2,10.0,12,9.0,9,0.0,60,5230935.0,47.0,9.0,1,2006-06-11 12:00:00 -19011,757,34,1,17.0,10,8.0,8,1.0,60,5230226.0,46.0,10.0,1,2006-06-11 12:00:00 -19012,757,1,1,16.0,9,7.0,7,2.0,60,5226521.0,43.0,6.0,1,2006-06-11 12:00:00 -19013,757,12,5,6.0,4,5.0,5,4.0,60,5183486.0,43.0,4.0,1,2006-06-11 12:00:00 -19014,757,22,6,7.0,7,,21,0.0,0,,,,3,2006-06-11 12:00:00 -19015,757,7,0,3.0,2,3.0,3,6.0,60,5170599.0,15.0,5.0,1,2006-06-11 12:00:00 -19016,757,29,5,5.0,3,2.0,2,8.0,60,5165878.0,53.0,2.0,1,2006-06-11 12:00:00 -19017,757,3,3,1.0,1,1.0,1,10.0,60,5151927.0,21.0,1.0,1,2006-06-11 12:00:00 -19018,757,14,6,8.0,22,11.0,11,0.0,59,,19.0,7.0,11,2006-06-11 12:00:00 -19019,757,16,2,9.0,17,,22,0.0,0,,,,3,2006-06-11 12:00:00 -19020,757,20,3,2.0,5,4.0,4,5.0,60,5171903.0,42.0,3.0,1,2006-06-11 12:00:00 -19021,758,34,1,17.0,11,,16,0.0,58,,29.0,6.0,3,2006-06-25 13:00:00 -19022,758,2,2,10.0,6,,21,0.0,1,,,,3,2006-06-25 13:00:00 -19023,758,26,12,19.0,19,,22,0.0,0,,,,3,2006-06-25 13:00:00 -19024,758,30,0,4.0,7,,18,0.0,13,,5.0,15.0,3,2006-06-25 13:00:00 -19025,758,22,6,7.0,14,,17,0.0,58,,19.0,16.0,31,2006-06-25 13:00:00 -19026,758,10,7,22.0,20,15.0,15,0.0,64,,40.0,19.0,3,2006-06-25 13:00:00 -19027,758,32,12,18.0,18,14.0,14,0.0,66,,5.0,18.0,14,2006-06-25 13:00:00 -19028,758,23,4,20.0,15,13.0,13,0.0,68,,50.0,14.0,12,2006-06-25 13:00:00 -19029,758,16,2,9.0,16,12.0,12,0.0,69,,17.0,11.0,11,2006-06-25 13:00:00 -19030,758,31,8,15.0,12,11.0,11,0.0,69,,55.0,9.0,11,2006-06-25 13:00:00 -19031,758,25,4,21.0,17,10.0,10,0.0,69,,52.0,12.0,11,2006-06-25 13:00:00 -19032,758,17,10,12.0,8,9.0,9,0.0,69,,21.0,13.0,11,2006-06-25 13:00:00 -19033,758,13,8,14.0,22,8.0,8,1.0,69,,39.0,10.0,11,2006-06-25 13:00:00 -19034,758,1,1,16.0,13,7.0,7,2.0,69,,52.0,7.0,11,2006-06-25 13:00:00 -19035,758,14,6,8.0,4,6.0,6,3.0,69,,15.0,8.0,11,2006-06-25 13:00:00 -19036,758,12,5,6.0,10,5.0,5,4.0,70,5702408.0,31.0,5.0,1,2006-06-25 13:00:00 -19037,758,20,3,2.0,2,4.0,4,5.0,70,5692908.0,49.0,4.0,1,2006-06-25 13:00:00 -19038,758,7,0,3.0,3,3.0,3,6.0,70,5686108.0,22.0,1.0,1,2006-06-25 13:00:00 -19039,758,29,5,5.0,5,2.0,2,8.0,70,5679408.0,68.0,3.0,1,2006-06-25 13:00:00 -19040,758,3,3,1.0,1,1.0,1,10.0,70,5677308.0,22.0,2.0,1,2006-06-25 13:00:00 -19041,758,35,7,23.0,21,,20,0.0,2,,2.0,20.0,5,2006-06-25 13:00:00 -19042,758,21,10,11.0,9,,19,0.0,11,,10.0,17.0,26,2006-06-25 13:00:00 -19043,759,35,7,23.0,19,,22,0.0,0,,,,3,2006-07-02 14:00:00 -19044,759,31,8,15.0,16,,21,0.0,0,,,,3,2006-07-02 14:00:00 -19045,759,25,4,21.0,13,,20,0.0,0,,,,3,2006-07-02 14:00:00 -19046,759,12,5,6.0,2,2.0,2,8.0,73,5683183.0,29.0,2.0,1,2006-07-02 14:00:00 -19047,759,16,2,9.0,12,,19,0.0,0,,,,3,2006-07-02 14:00:00 -19048,759,30,0,4.0,11,,18,0.0,0,,,,3,2006-07-02 14:00:00 -19049,759,1,1,16.0,10,,17,0.0,0,,,,3,2006-07-02 14:00:00 -19050,759,7,0,3.0,9,,16,0.0,0,,,,3,2006-07-02 14:00:00 -19051,759,29,5,5.0,1,1.0,1,10.0,73,5675199.0,56.0,1.0,1,2006-07-02 14:00:00 -19052,759,10,7,22.0,18,,14,0.0,6,,6.0,14.0,3,2006-07-02 14:00:00 -19053,759,32,12,18.0,15,,13,0.0,9,,9.0,13.0,3,2006-07-02 14:00:00 -19054,759,34,1,17.0,6,,12,0.0,23,,19.0,8.0,5,2006-07-02 14:00:00 -19055,759,26,12,19.0,14,,11,0.0,37,,34.0,12.0,7,2006-07-02 14:00:00 -19056,759,17,10,12.0,7,,15,0.0,3,,2.0,15.0,3,2006-07-02 14:00:00 -19057,759,2,2,10.0,21,9.0,9,0.0,72,,42.0,10.0,11,2006-07-02 14:00:00 -19058,759,23,4,20.0,20,8.0,8,1.0,72,,41.0,9.0,11,2006-07-02 14:00:00 -19059,759,13,8,14.0,17,7.0,7,2.0,72,,33.0,11.0,11,2006-07-02 14:00:00 -19060,759,21,10,11.0,4,6.0,6,3.0,73,5711712.0,47.0,7.0,1,2006-07-02 14:00:00 -19061,759,3,3,1.0,5,5.0,5,4.0,73,5703609.0,72.0,6.0,1,2006-07-02 14:00:00 -19062,759,14,6,8.0,22,4.0,4,5.0,73,5698803.0,37.0,5.0,1,2006-07-02 14:00:00 -19063,759,20,3,2.0,3,3.0,3,6.0,73,5691794.0,28.0,3.0,1,2006-07-02 14:00:00 -19064,759,22,6,7.0,8,,10,0.0,62,,29.0,4.0,45,2006-07-02 14:00:00 -19065,760,26,12,19.0,15,15.0,15,0.0,68,,67.0,18.0,12,2006-07-16 14:00:00 -19066,760,35,7,23.0,20,16.0,16,0.0,67,,53.0,20.0,13,2006-07-16 14:00:00 -19067,760,17,10,12.0,17,,17,0.0,61,,47.0,11.0,39,2006-07-16 14:00:00 -19068,760,16,2,9.0,10,,18,0.0,55,,34.0,15.0,46,2006-07-16 14:00:00 -19069,760,10,7,22.0,21,,22,0.0,0,,,,7,2006-07-16 14:00:00 -19070,760,21,10,11.0,13,,20,0.0,28,,16.0,19.0,5,2006-07-16 14:00:00 -19071,760,32,12,18.0,19,,21,0.0,11,,8.0,21.0,26,2006-07-16 14:00:00 -19072,760,2,2,10.0,18,14.0,14,0.0,68,,62.0,13.0,12,2006-07-16 14:00:00 -19073,760,14,6,8.0,4,,19,0.0,39,,16.0,8.0,23,2006-07-16 14:00:00 -19074,760,23,4,20.0,22,13.0,13,0.0,69,,54.0,10.0,11,2006-07-16 14:00:00 -19075,760,20,3,2.0,7,6.0,6,3.0,70,5573003.0,20.0,9.0,1,2006-07-16 14:00:00 -19076,760,34,1,17.0,16,11.0,11,0.0,69,,56.0,7.0,11,2006-07-16 14:00:00 -19077,760,3,3,1.0,3,2.0,2,8.0,70,5537903.0,23.0,5.0,1,2006-07-16 14:00:00 -19078,760,12,5,6.0,2,3.0,3,6.0,70,5550303.0,18.0,2.0,1,2006-07-16 14:00:00 -19079,760,22,6,7.0,5,4.0,4,5.0,70,5555003.0,19.0,6.0,1,2006-07-16 14:00:00 -19080,760,7,0,3.0,6,5.0,5,4.0,70,5560803.0,30.0,4.0,1,2006-07-16 14:00:00 -19081,760,31,8,15.0,12,12.0,12,0.0,69,,56.0,16.0,11,2006-07-16 14:00:00 -19082,760,36,0,4.0,8,7.0,7,2.0,70,5577203.0,34.0,3.0,1,2006-07-16 14:00:00 -19083,760,1,1,16.0,11,8.0,8,1.0,69,,48.0,14.0,11,2006-07-16 14:00:00 -19084,760,13,8,14.0,9,9.0,9,0.0,69,,56.0,17.0,11,2006-07-16 14:00:00 -19085,760,25,4,21.0,14,10.0,10,0.0,69,,66.0,12.0,11,2006-07-16 14:00:00 -19086,760,29,5,5.0,1,1.0,1,10.0,70,5527803.0,46.0,1.0,1,2006-07-16 14:00:00 -19087,761,16,2,9.0,11,,13,0.0,59,,43.0,6.0,47,2006-07-30 14:00:00 -19088,761,26,12,19.0,21,,21,0.0,66,,35.0,15.0,2,2006-07-30 14:00:00 -19089,761,2,2,10.0,14,,20,0.0,0,,,,3,2006-07-30 14:00:00 -19090,761,28,7,23.0,22,,19,0.0,1,,,,30,2006-07-30 14:00:00 -19091,761,36,0,4.0,9,,18,0.0,2,,2.0,20.0,48,2006-07-30 14:00:00 -19092,761,1,1,16.0,15,,17,0.0,9,,3.0,18.0,23,2006-07-30 14:00:00 -19093,761,21,10,11.0,6,,16,0.0,18,,16.0,14.0,5,2006-07-30 14:00:00 -19094,761,34,1,17.0,13,,15,0.0,30,,29.0,17.0,3,2006-07-30 14:00:00 -19095,761,10,7,22.0,17,,14,0.0,38,,26.0,19.0,6,2006-07-30 14:00:00 -19096,761,32,12,18.0,18,,22,0.0,66,,46.0,16.0,2,2006-07-30 14:00:00 -19097,761,25,4,21.0,19,12.0,12,0.0,66,,50.0,11.0,11,2006-07-30 14:00:00 -19098,761,23,4,20.0,16,10.0,10,0.0,66,,51.0,10.0,11,2006-07-30 14:00:00 -19099,761,22,6,7.0,8,9.0,9,0.0,67,5331993.0,64.0,4.0,1,2006-07-30 14:00:00 -19100,761,31,8,15.0,12,8.0,8,1.0,67,5319793.0,49.0,12.0,1,2006-07-30 14:00:00 -19101,761,14,6,8.0,20,7.0,7,2.0,67,5298193.0,48.0,5.0,1,2006-07-30 14:00:00 -19102,761,20,3,2.0,5,6.0,6,3.0,67,5296493.0,18.0,8.0,1,2006-07-30 14:00:00 -19103,761,3,3,1.0,7,5.0,5,4.0,67,5295393.0,66.0,9.0,1,2006-07-30 14:00:00 -19104,761,17,10,12.0,4,4.0,4,5.0,67,5290493.0,14.0,7.0,1,2006-07-30 14:00:00 -19105,761,7,0,3.0,1,3.0,3,6.0,67,5284893.0,4.0,3.0,1,2006-07-30 14:00:00 -19106,761,12,5,6.0,3,2.0,2,8.0,67,5272393.0,18.0,2.0,1,2006-07-30 14:00:00 -19107,761,29,5,5.0,2,1.0,1,10.0,67,5271693.0,17.0,1.0,1,2006-07-30 14:00:00 -19108,761,13,8,14.0,10,11.0,11,0.0,66,,24.0,13.0,11,2006-07-30 14:00:00 -19109,762,3,3,1.0,15,,14,0.0,51,,50.0,14.0,30,2006-08-06 14:00:00 -19110,762,7,0,3.0,1,,15,0.0,25,,7.0,16.0,4,2006-08-06 14:00:00 -19111,762,23,4,20.0,17,,16,0.0,25,,8.0,19.0,4,2006-08-06 14:00:00 -19112,762,20,3,2.0,7,,18,0.0,18,,9.0,17.0,20,2006-08-06 14:00:00 -19113,762,10,7,22.0,19,13.0,13,0.0,65,,53.0,15.0,15,2006-08-06 14:00:00 -19114,762,16,2,9.0,5,,20,0.0,1,,,,3,2006-08-06 14:00:00 -19115,762,28,7,23.0,21,,21,0.0,0,,,,5,2006-08-06 14:00:00 -19116,762,8,1,17.0,9,,22,0.0,69,,55.0,12.0,2,2006-08-06 14:00:00 -19117,762,31,8,15.0,13,,19,0.0,6,,6.0,18.0,20,2006-08-06 14:00:00 -19118,762,14,6,8.0,8,12.0,12,0.0,65,,58.0,6.0,5,2006-08-06 14:00:00 -19119,762,2,2,10.0,18,,17,0.0,19,,9.0,20.0,10,2006-08-06 14:00:00 -19120,762,26,12,19.0,22,10.0,10,0.0,67,,67.0,8.0,13,2006-08-06 14:00:00 -19121,762,36,0,4.0,4,2.0,2,8.0,70,6771778.0,67.0,2.0,1,2006-08-06 14:00:00 -19122,762,1,1,16.0,10,3.0,3,6.0,70,6784763.0,65.0,7.0,1,2006-08-06 14:00:00 -19123,762,21,10,11.0,3,4.0,4,5.0,70,6786146.0,69.0,3.0,1,2006-08-06 14:00:00 -19124,762,13,8,14.0,12,5.0,5,4.0,69,,65.0,10.0,11,2006-08-06 14:00:00 -19125,762,25,4,21.0,20,11.0,11,0.0,66,,66.0,9.0,14,2006-08-06 14:00:00 -19126,762,17,10,12.0,14,1.0,1,10.0,70,6740941.0,57.0,4.0,1,2006-08-06 14:00:00 -19127,762,12,5,6.0,2,7.0,7,2.0,69,,65.0,1.0,11,2006-08-06 14:00:00 -19128,762,29,5,5.0,11,8.0,8,1.0,67,,57.0,11.0,49,2006-08-06 14:00:00 -19129,762,32,12,18.0,16,9.0,9,0.0,67,,66.0,13.0,13,2006-08-06 14:00:00 -19130,762,22,6,7.0,6,6.0,6,3.0,69,,65.0,5.0,11,2006-08-06 14:00:00 -19131,763,1,1,16.0,5,14.0,14,0.0,56,,56.0,16.0,12,2006-08-27 15:00:00 -19132,763,32,12,18.0,19,,22,0.0,0,,,,4,2006-08-27 15:00:00 -19133,763,7,0,3.0,7,,21,0.0,1,,,,4,2006-08-27 15:00:00 -19134,763,23,4,20.0,18,,20,0.0,12,,12.0,19.0,20,2006-08-27 15:00:00 -19135,763,28,7,23.0,20,,19,0.0,23,,12.0,20.0,20,2006-08-27 15:00:00 -19136,763,2,2,10.0,14,,18,0.0,25,,21.0,14.0,47,2006-08-27 15:00:00 -19137,763,10,7,22.0,21,,17,0.0,41,,33.0,18.0,50,2006-08-27 15:00:00 -19138,763,26,12,19.0,22,,16,0.0,46,,35.0,17.0,20,2006-08-27 15:00:00 -19139,763,13,8,14.0,16,15.0,15,0.0,55,,24.0,12.0,6,2006-08-27 15:00:00 -19140,763,25,4,21.0,17,13.0,13,0.0,57,,43.0,10.0,11,2006-08-27 15:00:00 -19141,763,8,1,17.0,8,12.0,12,0.0,57,,34.0,9.0,11,2006-08-27 15:00:00 -19142,763,31,8,15.0,10,11.0,11,0.0,57,,26.0,11.0,11,2006-08-27 15:00:00 -19143,763,3,3,1.0,3,2.0,2,8.0,58,5336657.0,38.0,3.0,1,2006-08-27 15:00:00 -19144,763,29,5,5.0,2,3.0,3,6.0,58,5336738.0,55.0,1.0,1,2006-08-27 15:00:00 -19145,763,17,10,12.0,6,4.0,4,5.0,58,5343416.0,58.0,4.0,1,2006-08-27 15:00:00 -19146,763,36,0,4.0,11,5.0,5,4.0,58,5376990.0,54.0,7.0,1,2006-08-27 15:00:00 -19147,763,12,5,6.0,1,1.0,1,10.0,58,5331082.0,38.0,2.0,1,2006-08-27 15:00:00 -19148,763,22,6,7.0,15,7.0,7,2.0,58,5390419.0,58.0,8.0,1,2006-08-27 15:00:00 -19149,763,21,10,11.0,13,8.0,8,1.0,58,5391116.0,26.0,6.0,1,2006-08-27 15:00:00 -19150,763,14,6,8.0,12,9.0,9,0.0,57,,24.0,13.0,11,2006-08-27 15:00:00 -19151,763,16,2,9.0,9,10.0,10,0.0,57,,50.0,15.0,11,2006-08-27 15:00:00 -19152,763,20,3,2.0,4,6.0,6,3.0,58,5377676.0,29.0,5.0,1,2006-08-27 15:00:00 -19153,764,23,4,20.0,17,14.0,14,0.0,52,,52.0,14.0,11,2006-09-10 14:00:00 -19154,764,2,2,10.0,12,,22,0.0,9,,8.0,19.0,30,2006-09-10 14:00:00 -19155,764,28,7,23.0,22,,21,0.0,18,,15.0,22.0,9,2006-09-10 14:00:00 -19156,764,36,0,4.0,7,,20,0.0,20,,8.0,9.0,5,2006-09-10 14:00:00 -19157,764,3,3,1.0,10,,19,0.0,43,,38.0,5.0,5,2006-09-10 14:00:00 -19158,764,32,13,18.0,20,,18,0.0,44,,27.0,15.0,23,2006-09-10 14:00:00 -19159,764,26,13,19.0,18,17.0,17,0.0,51,,17.0,20.0,12,2006-09-10 14:00:00 -19160,764,10,7,22.0,21,16.0,16,0.0,51,,15.0,21.0,12,2006-09-10 14:00:00 -19161,764,22,6,7.0,13,15.0,15,0.0,52,,41.0,16.0,11,2006-09-10 14:00:00 -19162,764,25,4,21.0,15,13.0,13,0.0,52,,50.0,18.0,11,2006-09-10 14:00:00 -19163,764,29,5,5.0,2,1.0,1,10.0,53,4491975.0,14.0,2.0,1,2006-09-10 14:00:00 -19164,764,31,8,15.0,16,11.0,11,0.0,52,,37.0,13.0,11,2006-09-10 14:00:00 -19165,764,16,2,9.0,19,10.0,10,0.0,53,4564577.0,27.0,12.0,1,2006-09-10 14:00:00 -19166,764,12,5,6.0,4,9.0,9,0.0,53,4537970.0,41.0,3.0,1,2006-09-10 14:00:00 -19167,764,1,1,16.0,3,8.0,8,1.0,53,4537284.0,20.0,6.0,1,2006-09-10 14:00:00 -19168,764,14,6,8.0,11,7.0,7,2.0,53,4536637.0,25.0,11.0,1,2006-09-10 14:00:00 -19169,764,21,10,11.0,8,6.0,6,3.0,53,4534384.0,27.0,10.0,1,2006-09-10 14:00:00 -19170,764,17,10,12.0,5,5.0,5,4.0,53,4524660.0,51.0,7.0,1,2006-09-10 14:00:00 -19171,764,20,3,2.0,9,4.0,4,5.0,53,4524020.0,25.0,8.0,1,2006-09-10 14:00:00 -19172,764,8,1,17.0,6,3.0,3,6.0,53,4518389.0,21.0,4.0,1,2006-09-10 14:00:00 -19173,764,7,0,3.0,1,2.0,2,8.0,53,4500021.0,13.0,1.0,1,2006-09-10 14:00:00 -19174,764,13,8,14.0,14,12.0,12,0.0,52,,51.0,17.0,11,2006-09-10 14:00:00 -19175,765,26,13,19.0,22,15.0,15,0.0,53,,50.0,17.0,13,2006-10-01 14:00:00 -19176,765,28,7,23.0,19,16.0,16,0.0,52,,42.0,19.0,14,2006-10-01 14:00:00 -19177,765,22,6,7.0,16,,17,0.0,49,,47.0,11.0,51,2006-10-01 14:00:00 -19178,765,12,5,6.0,20,,18,0.0,44,,42.0,7.0,4,2006-10-01 14:00:00 -19179,765,25,4,21.0,11,14.0,14,0.0,55,,49.0,8.0,11,2006-10-01 14:00:00 -19180,765,32,13,18.0,18,,20,0.0,37,,35.0,22.0,20,2006-10-01 14:00:00 -19181,765,7,0,3.0,5,,21,0.0,18,,14.0,20.0,37,2006-10-01 14:00:00 -19182,765,10,7,22.0,21,,22,0.0,55,,48.0,16.0,2,2006-10-01 14:00:00 -19183,765,14,6,8.0,17,,19,0.0,38,,24.0,21.0,63,2006-10-01 14:00:00 -19184,765,8,1,17.0,9,13.0,13,0.0,55,,51.0,13.0,11,2006-10-01 14:00:00 -19185,765,29,5,5.0,6,1.0,1,10.0,56,5852747.0,50.0,2.0,1,2006-10-01 14:00:00 -19186,765,2,2,10.0,15,11.0,11,0.0,55,,52.0,14.0,11,2006-10-01 14:00:00 -19187,765,3,3,1.0,1,2.0,2,8.0,56,5855868.0,49.0,1.0,1,2006-10-01 14:00:00 -19188,765,20,3,2.0,2,3.0,3,6.0,56,5896944.0,53.0,6.0,1,2006-10-01 14:00:00 -19189,765,17,10,12.0,4,4.0,4,5.0,56,5924803.0,51.0,5.0,1,2006-10-01 14:00:00 -19190,765,36,0,4.0,7,5.0,5,4.0,56,5929884.0,45.0,3.0,1,2006-10-01 14:00:00 -19191,765,37,8,15.0,10,12.0,12,0.0,55,,52.0,10.0,11,2006-10-01 14:00:00 -19192,765,1,1,16.0,8,7.0,7,2.0,56,5944726.0,53.0,4.0,1,2006-10-01 14:00:00 -19193,765,16,2,9.0,14,8.0,8,1.0,56,5956335.0,44.0,12.0,1,2006-10-01 14:00:00 -19194,765,13,8,14.0,12,9.0,9,0.0,56,5956543.0,52.0,15.0,1,2006-10-01 14:00:00 -19195,765,23,4,20.0,13,10.0,10,0.0,55,,53.0,18.0,11,2006-10-01 14:00:00 -19196,765,21,10,11.0,3,6.0,6,3.0,56,5931878.0,52.0,9.0,1,2006-10-01 14:00:00 -19197,766,37,8,15.0,18,13.0,13,0.0,52,,37.0,19.0,11,2006-10-08 14:00:00 -19198,766,13,8,14.0,17,,21,0.0,35,,20.0,16.0,6,2006-10-08 14:00:00 -19199,766,29,5,5.0,2,,20,0.0,36,,32.0,2.0,5,2006-10-08 14:00:00 -19200,766,16,2,9.0,14,,19,0.0,39,,19.0,18.0,3,2006-10-08 14:00:00 -19201,766,25,4,21.0,19,18.0,18,0.0,48,,37.0,14.0,38,2006-10-08 14:00:00 -19202,766,28,7,23.0,22,17.0,17,0.0,50,,22.0,21.0,13,2006-10-08 14:00:00 -19203,766,32,13,18.0,21,16.0,16,0.0,51,,27.0,20.0,12,2006-10-08 14:00:00 -19204,766,10,7,22.0,20,15.0,15,0.0,52,,26.0,17.0,11,2006-10-08 14:00:00 -19205,766,23,4,20.0,15,14.0,14,0.0,52,,22.0,12.0,11,2006-10-08 14:00:00 -19206,766,26,13,19.0,16,,22,0.0,20,,19.0,22.0,30,2006-10-08 14:00:00 -19207,766,21,10,11.0,8,12.0,12,0.0,52,,40.0,10.0,11,2006-10-08 14:00:00 -19208,766,2,2,10.0,10,10.0,10,0.0,52,,33.0,15.0,11,2006-10-08 14:00:00 -19209,766,8,1,17.0,12,9.0,9,0.0,53,5109345.0,39.0,6.0,1,2006-10-08 14:00:00 -19210,766,1,1,16.0,9,8.0,8,1.0,53,5108508.0,31.0,13.0,1,2006-10-08 14:00:00 -19211,766,22,6,7.0,3,7.0,7,2.0,53,5081282.0,2.0,8.0,1,2006-10-08 14:00:00 -19212,766,14,6,8.0,4,6.0,6,3.0,53,5079130.0,2.0,9.0,1,2006-10-08 14:00:00 -19213,766,7,0,3.0,11,5.0,5,4.0,53,5076009.0,24.0,4.0,1,2006-10-08 14:00:00 -19214,766,17,10,12.0,7,4.0,4,5.0,53,5066514.0,35.0,5.0,1,2006-10-08 14:00:00 -19215,766,20,3,2.0,6,3.0,3,6.0,53,5056366.0,13.0,7.0,1,2006-10-08 14:00:00 -19216,766,12,5,6.0,1,2.0,2,8.0,53,5048564.0,37.0,3.0,1,2006-10-08 14:00:00 -19217,766,3,3,1.0,5,1.0,1,10.0,53,5032413.0,14.0,1.0,1,2006-10-08 14:00:00 -19218,766,36,0,4.0,13,11.0,11,0.0,52,,22.0,11.0,11,2006-10-08 14:00:00 -19219,767,26,13,19.0,17,14.0,14,0.0,70,,61.0,17.0,11,2006-10-22 14:00:00 -19220,767,32,13,18.0,21,15.0,15,0.0,69,,38.0,16.0,12,2006-10-22 14:00:00 -19221,767,28,7,23.0,20,16.0,16,0.0,69,,67.0,7.0,12,2006-10-22 14:00:00 -19222,767,1,1,16.0,8,17.0,17,0.0,63,,18.0,15.0,3,2006-10-22 14:00:00 -19223,767,23,4,20.0,15,13.0,13,0.0,70,,69.0,10.0,11,2006-10-22 14:00:00 -19224,767,22,6,7.0,7,,20,0.0,9,,8.0,20.0,22,2006-10-22 14:00:00 -19225,767,16,2,9.0,11,,21,0.0,1,,,,4,2006-10-22 14:00:00 -19226,767,2,2,10.0,13,,22,0.0,0,,,,4,2006-10-22 14:00:00 -19227,767,13,8,14.0,18,,18,0.0,14,,12.0,19.0,6,2006-10-22 14:00:00 -19228,767,37,8,15.0,22,12.0,12,0.0,70,,62.0,11.0,11,2006-10-22 14:00:00 -19229,767,14,6,8.0,3,,19,0.0,10,,9.0,18.0,22,2006-10-22 14:00:00 -19230,767,10,7,22.0,19,10.0,10,0.0,70,,47.0,9.0,11,2006-10-22 14:00:00 -19231,767,12,5,6.0,1,1.0,1,10.0,71,5513751.0,23.0,2.0,1,2006-10-22 14:00:00 -19232,767,3,3,1.0,4,2.0,2,8.0,71,5532409.0,70.0,3.0,1,2006-10-22 14:00:00 -19233,767,17,10,12.0,14,3.0,3,6.0,71,5533145.0,71.0,4.0,1,2006-10-22 14:00:00 -19234,767,29,5,5.0,10,4.0,4,5.0,71,5537845.0,70.0,1.0,1,2006-10-22 14:00:00 -19235,767,25,4,21.0,16,11.0,11,0.0,70,,69.0,13.0,11,2006-10-22 14:00:00 -19236,767,20,3,2.0,6,6.0,6,3.0,71,5544038.0,70.0,5.0,1,2006-10-22 14:00:00 -19237,767,21,10,11.0,5,7.0,7,2.0,71,5554045.0,48.0,8.0,1,2006-10-22 14:00:00 -19238,767,36,0,4.0,12,8.0,8,1.0,71,5565819.0,63.0,12.0,1,2006-10-22 14:00:00 -19239,767,8,1,17.0,9,9.0,9,0.0,71,5581393.0,25.0,14.0,1,2006-10-22 14:00:00 -19240,767,7,0,3.0,2,5.0,5,4.0,71,5542254.0,58.0,6.0,1,2006-10-22 14:00:00 -19241,768,17,10,7.0,14,15.0,15,0.0,57,,42.0,17.0,11,2007-03-18 03:00:00 -19242,768,26,11,21.0,21,,22,0.0,10,,9.0,22.0,3,2007-03-18 03:00:00 -19243,768,25,4,19.0,17,,21,0.0,28,,22.0,21.0,29,2007-03-18 03:00:00 -19244,768,8,1,10.0,5,,20,0.0,36,,19.0,4.0,6,2007-03-18 03:00:00 -19245,768,13,8,14.0,18,,19,0.0,48,,44.0,11.0,4,2007-03-18 03:00:00 -19246,768,24,2,17.0,15,,18,0.0,48,,24.0,16.0,4,2007-03-18 03:00:00 -19247,768,15,11,20.0,20,17.0,17,0.0,56,,40.0,20.0,12,2007-03-18 03:00:00 -19248,768,18,7,23.0,11,16.0,16,0.0,56,,41.0,19.0,12,2007-03-18 03:00:00 -19249,768,23,4,18.0,19,14.0,14,0.0,57,,44.0,15.0,11,2007-03-18 03:00:00 -19250,768,16,8,15.0,7,13.0,13,0.0,57,,21.0,9.0,11,2007-03-18 03:00:00 -19251,768,3,0,1.0,2,2.0,2,8.0,58,5136012.0,20.0,2.0,1,2007-03-18 03:00:00 -19252,768,21,10,8.0,16,11.0,11,0.0,57,,17.0,14.0,11,2007-03-18 03:00:00 -19253,768,4,3,4.0,13,10.0,10,0.0,57,,44.0,10.0,11,2007-03-18 03:00:00 -19254,768,14,6,12.0,8,9.0,9,0.0,57,,45.0,13.0,11,2007-03-18 03:00:00 -19255,768,22,6,11.0,9,8.0,8,1.0,57,,42.0,12.0,11,2007-03-18 03:00:00 -19256,768,2,2,16.0,12,7.0,7,2.0,57,,40.0,5.0,11,2007-03-18 03:00:00 -19257,768,12,5,5.0,22,6.0,6,3.0,58,5195575.0,28.0,8.0,1,2007-03-18 03:00:00 -19258,768,20,3,3.0,6,5.0,5,4.0,58,5195239.0,18.0,7.0,1,2007-03-18 03:00:00 -19259,768,1,1,9.0,3,4.0,4,5.0,58,5167533.0,37.0,6.0,1,2007-03-18 03:00:00 -19260,768,0,0,2.0,4,3.0,3,6.0,58,5147365.0,20.0,3.0,1,2007-03-18 03:00:00 -19261,768,10,7,22.0,10,12.0,12,0.0,57,,20.0,18.0,11,2007-03-18 03:00:00 -19262,768,7,5,6.0,1,1.0,1,10.0,58,5128770.0,41.0,1.0,1,2007-03-18 03:00:00 -19263,769,22,6,11.0,9,15.0,15,0.0,55,,52.0,19.0,11,2007-04-08 07:00:00 -19264,769,18,7,23.0,18,16.0,16,0.0,55,,32.0,20.0,11,2007-04-08 07:00:00 -19265,769,23,4,18.0,16,17.0,17,0.0,55,,21.0,12.0,11,2007-04-08 07:00:00 -19266,769,8,1,10.0,7,18.0,18,0.0,55,,53.0,17.0,11,2007-04-08 07:00:00 -19267,769,25,4,19.0,17,14.0,14,0.0,55,,54.0,18.0,11,2007-04-08 07:00:00 -19268,769,13,8,14.0,13,,20,0.0,36,,28.0,11.0,23,2007-04-08 07:00:00 -19269,769,26,11,21.0,20,,21,0.0,7,,5.0,21.0,5,2007-04-08 07:00:00 -19270,769,15,11,20.0,21,,22,0.0,0,,,,4,2007-04-08 07:00:00 -19271,769,2,2,16.0,6,,19,0.0,42,,18.0,6.0,9,2007-04-08 07:00:00 -19272,769,10,7,22.0,14,13.0,13,0.0,55,,37.0,13.0,11,2007-04-08 07:00:00 -19273,769,0,0,2.0,4,2.0,2,8.0,56,5552487.0,22.0,1.0,1,2007-04-08 07:00:00 -19274,769,21,10,8.0,22,11.0,11,0.0,55,,32.0,15.0,11,2007-04-08 07:00:00 -19275,769,17,10,7.0,15,12.0,12,0.0,55,,54.0,16.0,11,2007-04-08 07:00:00 -19276,769,7,5,6.0,3,3.0,3,6.0,56,5553269.0,40.0,4.0,1,2007-04-08 07:00:00 -19277,769,1,1,9.0,5,4.0,4,5.0,56,5568707.0,55.0,5.0,1,2007-04-08 07:00:00 -19278,769,12,5,5.0,1,5.0,5,4.0,56,5571635.0,42.0,3.0,1,2007-04-08 07:00:00 -19279,769,3,0,1.0,2,1.0,1,10.0,56,5534930.0,42.0,2.0,1,2007-04-08 07:00:00 -19280,769,14,6,12.0,8,7.0,7,2.0,56,5605062.0,40.0,10.0,1,2007-04-08 07:00:00 -19281,769,4,3,4.0,11,8.0,8,1.0,56,5606945.0,41.0,7.0,1,2007-04-08 07:00:00 -19282,769,24,2,17.0,19,9.0,9,0.0,56,5624854.0,19.0,8.0,1,2007-04-08 07:00:00 -19283,769,16,8,15.0,10,10.0,10,0.0,56,5628486.0,55.0,14.0,1,2007-04-08 07:00:00 -19284,769,20,3,3.0,12,6.0,6,3.0,56,5600568.0,44.0,9.0,1,2007-04-08 07:00:00 -19285,770,26,11,21.0,22,14.0,14,0.0,55,,40.0,20.0,12,2007-04-15 11:30:00 -19286,770,25,4,19.0,19,,22,0.0,0,,,,4,2007-04-15 11:30:00 -19287,770,17,10,7.0,16,,21,0.0,0,,,,4,2007-04-15 11:30:00 -19288,770,23,4,18.0,18,,20,0.0,26,,23.0,13.0,9,2007-04-15 11:30:00 -19289,770,10,7,22.0,17,,19,0.0,34,,23.0,18.0,5,2007-04-15 11:30:00 -19290,770,13,8,14.0,21,,18,0.0,36,,34.0,9.0,30,2007-04-15 11:30:00 -19291,770,16,8,15.0,8,,17,0.0,41,,37.0,12.0,6,2007-04-15 11:30:00 -19292,770,18,7,23.0,13,16.0,16,0.0,51,,27.0,17.0,5,2007-04-15 11:30:00 -19293,770,15,11,20.0,20,15.0,15,0.0,53,,45.0,19.0,14,2007-04-15 11:30:00 -19294,770,21,10,8.0,15,13.0,13,0.0,56,,50.0,14.0,11,2007-04-15 11:30:00 -19295,770,0,0,2.0,2,2.0,2,8.0,57,5609875.0,18.0,2.0,1,2007-04-15 11:30:00 -19296,770,24,2,17.0,11,11.0,11,0.0,56,,27.0,16.0,11,2007-04-15 11:30:00 -19297,770,12,5,5.0,1,1.0,1,10.0,57,5607515.0,42.0,1.0,1,2007-04-15 11:30:00 -19298,770,7,5,6.0,3,3.0,3,6.0,57,5618354.0,39.0,3.0,1,2007-04-15 11:30:00 -19299,770,1,1,9.0,5,4.0,4,5.0,57,5621346.0,38.0,5.0,1,2007-04-15 11:30:00 -19300,770,3,0,1.0,4,5.0,5,4.0,57,5621941.0,46.0,4.0,1,2007-04-15 11:30:00 -19301,770,22,6,11.0,14,12.0,12,0.0,56,,37.0,15.0,11,2007-04-15 11:30:00 -19302,770,14,6,12.0,9,7.0,7,2.0,57,5688886.0,40.0,7.0,1,2007-04-15 11:30:00 -19303,770,20,3,3.0,7,8.0,8,1.0,57,5689216.0,51.0,8.0,1,2007-04-15 11:30:00 -19304,770,4,3,4.0,12,9.0,9,0.0,57,5696926.0,27.0,10.0,1,2007-04-15 11:30:00 -19305,770,2,2,16.0,10,10.0,10,0.0,57,5697431.0,51.0,11.0,1,2007-04-15 11:30:00 -19306,770,8,1,10.0,6,6.0,6,3.0,57,5653044.0,46.0,6.0,1,2007-04-15 11:30:00 -19307,771,15,11,20.0,20,13.0,13,0.0,63,,57.0,16.0,12,2007-05-13 12:00:00 -19308,771,16,8,15.0,19,,21,0.0,7,,4.0,21.0,9,2007-05-13 12:00:00 -19309,771,14,6,12.0,6,,20,0.0,8,,6.0,19.0,32,2007-05-13 12:00:00 -19310,771,7,5,6.0,3,,19,0.0,9,,7.0,6.0,22,2007-05-13 12:00:00 -19311,771,25,4,19.0,22,,18,0.0,9,,6.0,20.0,27,2007-05-13 12:00:00 -19312,771,23,4,18.0,16,,17,0.0,19,,18.0,17.0,31,2007-05-13 12:00:00 -19313,771,22,6,11.0,17,,16,0.0,44,,37.0,11.0,22,2007-05-13 12:00:00 -19314,771,1,1,9.0,7,,15,0.0,46,,22.0,7.0,6,2007-05-13 12:00:00 -19315,771,26,11,21.0,21,14.0,14,0.0,63,,61.0,18.0,12,2007-05-13 12:00:00 -19316,771,24,2,17.0,18,,22,0.0,1,,,,4,2007-05-13 12:00:00 -19317,771,21,10,8.0,12,10.0,10,0.0,64,,16.0,14.0,11,2007-05-13 12:00:00 -19318,771,18,7,23.0,15,11.0,11,0.0,64,,59.0,15.0,11,2007-05-13 12:00:00 -19319,771,20,3,3.0,10,9.0,9,0.0,64,,57.0,9.0,11,2007-05-13 12:00:00 -19320,771,10,7,22.0,13,8.0,8,1.0,64,,23.0,12.0,11,2007-05-13 12:00:00 -19321,771,4,3,4.0,8,7.0,7,2.0,65,5558358.0,32.0,4.0,1,2007-05-13 12:00:00 -19322,771,2,2,16.0,11,6.0,6,3.0,65,5555768.0,60.0,10.0,1,2007-05-13 12:00:00 -19323,771,13,8,14.0,9,5.0,5,4.0,65,5554561.0,18.0,8.0,1,2007-05-13 12:00:00 -19324,771,8,1,10.0,5,4.0,4,5.0,65,5527845.0,20.0,5.0,1,2007-05-13 12:00:00 -19325,771,3,0,1.0,2,3.0,3,6.0,65,5513686.0,17.0,3.0,1,2007-05-13 12:00:00 -19326,771,0,0,2.0,4,2.0,2,8.0,65,5503020.0,20.0,2.0,1,2007-05-13 12:00:00 -19327,771,12,5,5.0,1,1.0,1,10.0,65,5496230.0,14.0,1.0,1,2007-05-13 12:00:00 -19328,771,17,10,7.0,14,12.0,12,0.0,64,,64.0,13.0,11,2007-05-13 12:00:00 -19329,772,10,7,22.0,21,17.0,17,0.0,76,,74.0,15.0,12,2007-05-27 12:00:00 -19330,772,14,6,12.0,14,15.0,15,0.0,76,,53.0,18.0,12,2007-05-27 12:00:00 -19331,772,22,6,11.0,20,16.0,16,0.0,76,,47.0,17.0,12,2007-05-27 12:00:00 -19332,772,18,7,23.0,17,18.0,18,0.0,76,,63.0,16.0,12,2007-05-27 12:00:00 -19333,772,13,8,14.0,13,14.0,14,0.0,76,,75.0,8.0,12,2007-05-27 12:00:00 -19334,772,15,11,20.0,19,,20,0.0,53,,34.0,19.0,3,2007-05-27 12:00:00 -19335,772,16,8,15.0,6,,21,0.0,17,,17.0,21.0,6,2007-05-27 12:00:00 -19336,772,23,4,18.0,12,,22,0.0,2,,,,3,2007-05-27 12:00:00 -19337,772,26,11,21.0,22,19.0,19,0.0,70,,70.0,20.0,30,2007-05-27 12:00:00 -19338,772,4,3,4.0,15,13.0,13,0.0,76,,72.0,14.0,5,2007-05-27 12:00:00 -19339,772,3,0,1.0,1,1.0,1,10.0,78,6029329.0,44.0,1.0,1,2007-05-27 12:00:00 -19340,772,17,10,7.0,10,11.0,11,0.0,77,,40.0,9.0,11,2007-05-27 12:00:00 -19341,772,0,0,2.0,2,2.0,2,8.0,78,6033424.0,28.0,2.0,1,2007-05-27 12:00:00 -19342,772,12,5,5.0,3,3.0,3,6.0,78,6098443.0,47.0,4.0,1,2007-05-27 12:00:00 -19343,772,20,3,3.0,4,4.0,4,5.0,77,,54.0,5.0,11,2007-05-27 12:00:00 -19344,772,8,1,10.0,8,5.0,5,4.0,77,,39.0,3.0,11,2007-05-27 12:00:00 -19345,772,2,2,16.0,5,12.0,12,0.0,77,,70.0,11.0,11,2007-05-27 12:00:00 -19346,772,24,2,17.0,11,7.0,7,2.0,77,,40.0,7.0,11,2007-05-27 12:00:00 -19347,772,7,5,6.0,16,8.0,8,1.0,77,,62.0,6.0,11,2007-05-27 12:00:00 -19348,772,25,4,19.0,18,9.0,9,0.0,77,,73.0,10.0,11,2007-05-27 12:00:00 -19349,772,21,10,8.0,9,10.0,10,0.0,77,,69.0,13.0,11,2007-05-27 12:00:00 -19350,772,1,1,9.0,7,6.0,6,3.0,77,,30.0,12.0,11,2007-05-27 12:00:00 -19351,773,20,3,3.0,9,,22,0.0,51,,22.0,7.0,2,2007-06-10 17:00:00 -19352,773,12,5,5.0,5,,21,0.0,51,,22.0,4.0,2,2007-06-10 17:00:00 -19353,773,17,10,7.0,15,,20,0.0,0,,,,6,2007-06-10 17:00:00 -19354,773,25,4,19.0,16,,19,0.0,8,,6.0,21.0,3,2007-06-10 17:00:00 -19355,773,15,11,20.0,20,,18,0.0,21,,20.0,20.0,3,2007-06-10 17:00:00 -19356,773,8,1,10.0,8,,17,0.0,26,,19.0,8.0,3,2007-06-10 17:00:00 -19357,773,13,8,14.0,14,,16,0.0,36,,19.0,16.0,6,2007-06-10 17:00:00 -19358,773,23,4,18.0,12,,14,0.0,54,,9.0,19.0,3,2007-06-10 17:00:00 -19359,773,14,6,12.0,10,,13,0.0,58,,12.0,17.0,3,2007-06-10 17:00:00 -19360,773,26,11,21.0,21,,15,0.0,47,,21.0,18.0,33,2007-06-10 17:00:00 -19361,773,0,0,2.0,1,1.0,1,10.0,70,6251292.0,37.0,2.0,1,2007-06-10 17:00:00 -19362,773,18,7,23.0,17,11.0,11,0.0,70,6275610.0,36.0,15.0,1,2007-06-10 17:00:00 -19363,773,1,1,9.0,3,2.0,2,8.0,70,6255635.0,19.0,3.0,1,2007-06-10 17:00:00 -19364,773,24,2,17.0,19,3.0,3,6.0,70,6256617.0,67.0,11.0,1,2007-06-10 17:00:00 -19365,773,4,3,4.0,22,4.0,4,5.0,70,6258021.0,67.0,13.0,1,2007-06-10 17:00:00 -19366,773,7,5,6.0,4,5.0,5,4.0,70,6264299.0,21.0,5.0,1,2007-06-10 17:00:00 -19367,773,21,10,8.0,13,12.0,12,0.0,70,6281731.0,62.0,14.0,1,2007-06-10 17:00:00 -19368,773,3,0,1.0,2,7.0,7,2.0,70,6273228.0,46.0,1.0,1,2007-06-10 17:00:00 -19369,773,22,6,11.0,18,8.0,8,1.0,70,6274180.0,38.0,10.0,1,2007-06-10 17:00:00 -19370,773,16,8,15.0,6,9.0,9,0.0,70,6274252.0,47.0,9.0,1,2007-06-10 17:00:00 -19371,773,2,2,16.0,7,10.0,10,0.0,70,6275276.0,42.0,6.0,1,2007-06-10 17:00:00 -19372,773,10,7,22.0,11,6.0,6,3.0,70,6267990.0,47.0,12.0,1,2007-06-10 17:00:00 -19373,774,22,6,11.0,12,,22,0.0,0,,,,4,2007-06-17 17:00:00 -19374,774,21,10,8.0,15,,21,0.0,0,,,,4,2007-06-17 17:00:00 -19375,774,13,8,14.0,11,,20,0.0,0,,,,4,2007-06-17 17:00:00 -19376,774,10,7,22.0,18,,19,0.0,13,,8.0,19.0,20,2007-06-17 17:00:00 -19377,774,1,1,9.0,5,,18,0.0,56,,20.0,5.0,7,2007-06-17 17:00:00 -19378,774,23,4,18.0,19,17.0,17,0.0,68,,64.0,17.0,34,2007-06-17 17:00:00 -19379,774,2,2,16.0,14,16.0,16,0.0,68,,34.0,11.0,5,2007-06-17 17:00:00 -19380,774,26,11,21.0,22,15.0,15,0.0,70,,65.0,18.0,13,2007-06-17 17:00:00 -19381,774,15,11,20.0,21,14.0,14,0.0,71,,49.0,15.0,12,2007-06-17 17:00:00 -19382,774,25,4,19.0,20,13.0,13,0.0,71,,66.0,16.0,12,2007-06-17 17:00:00 -19383,774,17,10,7.0,13,12.0,12,0.0,72,,42.0,14.0,11,2007-06-17 17:00:00 -19384,774,24,2,17.0,17,10.0,10,0.0,72,,41.0,13.0,11,2007-06-17 17:00:00 -19385,774,0,0,2.0,1,1.0,1,10.0,73,5469965.0,20.0,2.0,1,2007-06-17 17:00:00 -19386,774,3,0,1.0,2,2.0,2,8.0,73,5471465.0,21.0,3.0,1,2007-06-17 17:00:00 -19387,774,12,5,5.0,3,3.0,3,6.0,73,5482765.0,50.0,4.0,1,2007-06-17 17:00:00 -19388,774,7,5,6.0,4,4.0,4,5.0,73,5485365.0,49.0,1.0,1,2007-06-17 17:00:00 -19389,774,18,7,23.0,16,11.0,11,0.0,72,,55.0,12.0,11,2007-06-17 17:00:00 -19390,774,14,6,12.0,8,6.0,6,3.0,73,5536665.0,30.0,10.0,1,2007-06-17 17:00:00 -19391,774,16,8,15.0,9,7.0,7,2.0,73,5537265.0,57.0,8.0,1,2007-06-17 17:00:00 -19392,774,19,1,10.0,7,8.0,8,1.0,73,5537665.0,53.0,6.0,1,2007-06-17 17:00:00 -19393,774,20,3,3.0,10,9.0,9,0.0,72,,67.0,9.0,11,2007-06-17 17:00:00 -19394,774,4,3,4.0,6,5.0,5,4.0,73,5511365.0,67.0,7.0,1,2007-06-17 17:00:00 -19395,775,13,8,14.0,16,13.0,13,0.0,69,,68.0,15.0,11,2007-07-01 12:00:00 -19396,775,14,6,12.0,8,,21,0.0,1,,,,4,2007-07-01 12:00:00 -19397,775,18,7,23.0,19,,20,0.0,1,,,,4,2007-07-01 12:00:00 -19398,775,26,11,21.0,20,,19,0.0,28,,27.0,19.0,35,2007-07-01 12:00:00 -19399,775,25,4,19.0,15,,18,0.0,55,,51.0,17.0,6,2007-07-01 12:00:00 -19400,775,15,11,20.0,21,17.0,17,0.0,68,,27.0,18.0,12,2007-07-01 12:00:00 -19401,775,10,7,22.0,22,16.0,16,0.0,68,,39.0,16.0,12,2007-07-01 12:00:00 -19402,775,4,3,4.0,6,15.0,15,0.0,69,,69.0,11.0,11,2007-07-01 12:00:00 -19403,775,24,2,17.0,18,14.0,14,0.0,69,,69.0,13.0,11,2007-07-01 12:00:00 -19404,775,23,4,18.0,17,,22,0.0,0,,,,4,2007-07-01 12:00:00 -19405,775,16,8,15.0,14,12.0,12,0.0,69,,69.0,14.0,11,2007-07-01 12:00:00 -19406,775,22,6,11.0,11,10.0,10,0.0,69,,68.0,8.0,11,2007-07-01 12:00:00 -19407,775,2,2,16.0,9,9.0,9,0.0,70,5522705.0,69.0,9.0,1,2007-07-01 12:00:00 -19408,775,17,10,7.0,12,8.0,8,1.0,70,5513085.0,70.0,6.0,1,2007-07-01 12:00:00 -19409,775,3,0,1.0,10,7.0,7,2.0,70,5510716.0,36.0,3.0,1,2007-07-01 12:00:00 -19410,775,20,3,3.0,5,6.0,6,3.0,70,5506140.0,70.0,5.0,1,2007-07-01 12:00:00 -19411,775,1,1,9.0,7,5.0,5,4.0,70,5503001.0,70.0,7.0,1,2007-07-01 12:00:00 -19412,775,8,1,10.0,4,4.0,4,5.0,70,5495927.0,44.0,10.0,1,2007-07-01 12:00:00 -19413,775,0,0,2.0,2,3.0,3,6.0,70,5486353.0,39.0,4.0,1,2007-07-01 12:00:00 -19414,775,12,5,5.0,1,2.0,2,8.0,70,5456614.0,42.0,1.0,1,2007-07-01 12:00:00 -19415,775,7,5,6.0,3,1.0,1,10.0,70,5454200.0,20.0,2.0,1,2007-07-01 12:00:00 -19416,775,21,10,8.0,13,11.0,11,0.0,69,,68.0,12.0,11,2007-07-01 12:00:00 -19417,776,20,3,3.0,8,8.0,8,1.0,58,,13.0,7.0,11,2007-07-08 12:00:00 -19418,776,4,3,4.0,7,7.0,7,2.0,58,,11.0,9.0,11,2007-07-08 12:00:00 -19419,776,21,10,8.0,14,9.0,9,0.0,58,,28.0,13.0,11,2007-07-08 12:00:00 -19420,776,1,1,9.0,9,6.0,6,3.0,59,4959410.0,17.0,5.0,1,2007-07-08 12:00:00 -19421,776,7,5,6.0,2,1.0,1,10.0,59,4903074.0,17.0,1.0,1,2007-07-08 12:00:00 -19422,776,8,1,10.0,5,4.0,4,5.0,59,4956393.0,14.0,6.0,1,2007-07-08 12:00:00 -19423,776,0,0,2.0,1,3.0,3,6.0,59,4942447.0,11.0,4.0,1,2007-07-08 12:00:00 -19424,776,3,0,1.0,3,2.0,2,8.0,59,4905533.0,35.0,3.0,1,2007-07-08 12:00:00 -19425,776,12,5,5.0,4,5.0,5,4.0,59,4957137.0,17.0,2.0,1,2007-07-08 12:00:00 -19426,776,17,10,7.0,18,10.0,10,0.0,58,,29.0,16.0,11,2007-07-08 12:00:00 -19427,776,26,11,21.0,22,15.0,15,0.0,57,,56.0,21.0,12,2007-07-08 12:00:00 -19428,776,2,2,16.0,17,12.0,12,0.0,58,,49.0,11.0,11,2007-07-08 12:00:00 -19429,776,16,8,15.0,11,,22,0.0,8,,6.0,19.0,9,2007-07-08 12:00:00 -19430,776,15,11,20.0,20,,21,0.0,16,,16.0,22.0,5,2007-07-08 12:00:00 -19431,776,22,6,11.0,6,,20,0.0,22,,12.0,8.0,36,2007-07-08 12:00:00 -19432,776,25,4,19.0,15,,19,0.0,29,,19.0,15.0,3,2007-07-08 12:00:00 -19433,776,13,8,14.0,12,11.0,11,0.0,58,,40.0,12.0,11,2007-07-08 12:00:00 -19434,776,14,6,12.0,10,,17,0.0,43,,17.0,18.0,31,2007-07-08 12:00:00 -19435,776,23,4,18.0,16,16.0,16,0.0,53,,46.0,17.0,6,2007-07-08 12:00:00 -19436,776,10,7,22.0,21,14.0,14,0.0,57,,42.0,14.0,12,2007-07-08 12:00:00 -19437,776,24,2,17.0,13,13.0,13,0.0,58,,57.0,10.0,11,2007-07-08 12:00:00 -19438,776,18,7,23.0,19,,18,0.0,35,,26.0,20.0,26,2007-07-08 12:00:00 -19439,777,7,5,6.0,1,,14,0.0,34,,32.0,4.0,9,2007-07-22 12:00:00 -19440,777,23,4,18.0,19,,22,0.0,2,,2.0,22.0,20,2007-07-22 12:00:00 -19441,777,25,4,19.0,18,,21,0.0,2,,2.0,21.0,20,2007-07-22 12:00:00 -19442,777,2,2,16.0,11,,20,0.0,2,,2.0,20.0,20,2007-07-22 12:00:00 -19443,777,15,11,20.0,21,,19,0.0,2,,2.0,19.0,20,2007-07-22 12:00:00 -19444,777,17,10,7.0,17,,18,0.0,2,,2.0,18.0,20,2007-07-22 12:00:00 -19445,777,27,11,21.0,22,,17,0.0,13,,13.0,17.0,9,2007-07-22 12:00:00 -19446,777,22,6,11.0,9,,16,0.0,18,,18.0,15.0,4,2007-07-22 12:00:00 -19447,777,10,7,22.0,16,,15,0.0,19,,18.0,16.0,31,2007-07-22 12:00:00 -19448,777,14,6,12.0,8,13.0,13,0.0,59,,29.0,10.0,11,2007-07-22 12:00:00 -19449,777,18,7,23.0,15,12.0,12,0.0,59,,46.0,13.0,11,2007-07-22 12:00:00 -19450,777,21,10,8.0,14,11.0,11,0.0,59,,37.0,14.0,11,2007-07-22 12:00:00 -19451,777,12,5,5.0,3,2.0,2,8.0,60,7594513.0,34.0,1.0,1,2007-07-22 12:00:00 -19452,777,16,8,15.0,6,3.0,3,6.0,60,7652032.0,29.0,8.0,1,2007-07-22 12:00:00 -19453,777,24,2,17.0,12,4.0,4,5.0,60,7652295.0,33.0,5.0,1,2007-07-22 12:00:00 -19454,777,13,8,14.0,20,5.0,5,4.0,60,7660014.0,48.0,6.0,1,2007-07-22 12:00:00 -19455,777,3,0,1.0,2,1.0,1,10.0,60,7586358.0,35.0,2.0,1,2007-07-22 12:00:00 -19456,777,8,1,10.0,5,7.0,7,2.0,60,7668773.0,49.0,9.0,1,2007-07-22 12:00:00 -19457,777,4,3,4.0,7,8.0,8,1.0,59,,48.0,11.0,11,2007-07-22 12:00:00 -19458,777,0,0,2.0,10,9.0,9,0.0,59,,29.0,3.0,11,2007-07-22 12:00:00 -19459,777,20,3,3.0,13,10.0,10,0.0,59,,48.0,12.0,11,2007-07-22 12:00:00 -19460,777,1,1,9.0,4,6.0,6,3.0,60,7666656.0,49.0,7.0,1,2007-07-22 12:00:00 -19461,778,24,2,17.0,12,14.0,14,0.0,69,,49.0,13.0,11,2007-08-05 12:00:00 -19462,778,28,11,21.0,22,,22,0.0,4,,4.0,22.0,3,2007-08-05 12:00:00 -19463,778,17,10,7.0,17,,21,0.0,35,,25.0,21.0,37,2007-08-05 12:00:00 -19464,778,18,7,23.0,15,,20,0.0,41,,39.0,18.0,3,2007-08-05 12:00:00 -19465,778,23,4,18.0,16,,19,0.0,42,,35.0,20.0,10,2007-08-05 12:00:00 -19466,778,21,10,8.0,18,18.0,18,0.0,68,,34.0,17.0,12,2007-08-05 12:00:00 -19467,778,15,11,20.0,21,17.0,17,0.0,68,,67.0,19.0,12,2007-08-05 12:00:00 -19468,778,19,4,19.0,20,16.0,16,0.0,69,,65.0,16.0,11,2007-08-05 12:00:00 -19469,778,10,7,22.0,19,15.0,15,0.0,69,,66.0,10.0,11,2007-08-05 12:00:00 -19470,778,12,5,5.0,14,13.0,13,0.0,69,,37.0,11.0,11,2007-08-05 12:00:00 -19471,778,20,3,3.0,13,12.0,12,0.0,69,,66.0,15.0,11,2007-08-05 12:00:00 -19472,778,13,8,14.0,10,11.0,11,0.0,69,,67.0,14.0,11,2007-08-05 12:00:00 -19473,778,7,5,6.0,3,2.0,2,8.0,70,5753706.0,70.0,1.0,1,2007-08-05 12:00:00 -19474,778,1,1,9.0,2,3.0,3,6.0,70,5796120.0,16.0,5.0,1,2007-08-05 12:00:00 -19475,778,3,0,1.0,6,4.0,4,5.0,70,5797849.0,49.0,3.0,1,2007-08-05 12:00:00 -19476,778,8,1,10.0,7,5.0,5,4.0,70,5800607.0,40.0,4.0,1,2007-08-05 12:00:00 -19477,778,0,0,2.0,1,1.0,1,10.0,70,5752991.0,13.0,2.0,1,2007-08-05 12:00:00 -19478,778,2,2,16.0,4,7.0,7,2.0,70,5812130.0,68.0,6.0,1,2007-08-05 12:00:00 -19479,778,4,3,4.0,11,8.0,8,1.0,70,5821095.0,69.0,8.0,1,2007-08-05 12:00:00 -19480,778,16,8,15.0,9,9.0,9,0.0,70,5829322.0,63.0,7.0,1,2007-08-05 12:00:00 -19481,778,14,6,12.0,8,10.0,10,0.0,69,,48.0,12.0,11,2007-08-05 12:00:00 -19482,778,22,6,11.0,5,6.0,6,3.0,70,5803660.0,69.0,9.0,1,2007-08-05 12:00:00 -19483,779,18,7,23.0,11,14.0,14,0.0,57,,38.0,17.0,11,2007-08-26 12:00:00 -19484,779,16,8,15.0,12,,22,0.0,9,,4.0,21.0,9,2007-08-26 12:00:00 -19485,779,15,11,20.0,19,21.0,21,0.0,53,,52.0,20.0,32,2007-08-26 12:00:00 -19486,779,28,11,21.0,20,20.0,20,0.0,56,,21.0,22.0,12,2007-08-26 12:00:00 -19487,779,19,4,19.0,18,19.0,19,0.0,57,,39.0,19.0,11,2007-08-26 12:00:00 -19488,779,10,7,22.0,17,18.0,18,0.0,57,,56.0,18.0,11,2007-08-26 12:00:00 -19489,779,21,10,8.0,22,17.0,17,0.0,57,,35.0,15.0,11,2007-08-26 12:00:00 -19490,779,14,6,12.0,9,16.0,16,0.0,57,,39.0,14.0,11,2007-08-26 12:00:00 -19491,779,23,4,18.0,15,15.0,15,0.0,57,,56.0,16.0,11,2007-08-26 12:00:00 -19492,779,17,10,7.0,21,13.0,13,0.0,57,,34.0,10.0,11,2007-08-26 12:00:00 -19493,779,22,6,11.0,16,12.0,12,0.0,57,,55.0,12.0,11,2007-08-26 12:00:00 -19494,779,24,2,17.0,14,11.0,11,0.0,58,5281789.0,55.0,8.0,1,2007-08-26 12:00:00 -19495,779,13,8,14.0,13,10.0,10,0.0,58,5273170.0,54.0,13.0,1,2007-08-26 12:00:00 -19496,779,20,3,3.0,10,9.0,9,0.0,58,5261652.0,56.0,9.0,1,2007-08-26 12:00:00 -19497,779,8,1,10.0,5,8.0,8,1.0,58,5258868.0,11.0,11.0,1,2007-08-26 12:00:00 -19498,779,2,2,16.0,8,7.0,7,2.0,58,5257939.0,37.0,6.0,1,2007-08-26 12:00:00 -19499,779,4,3,4.0,7,6.0,6,3.0,58,5248330.0,20.0,7.0,1,2007-08-26 12:00:00 -19500,779,0,0,2.0,2,5.0,5,4.0,58,5247246.0,17.0,3.0,1,2007-08-26 12:00:00 -19501,779,1,1,9.0,6,4.0,4,5.0,58,5241835.0,39.0,5.0,1,2007-08-26 12:00:00 -19502,779,3,0,1.0,4,3.0,3,6.0,58,5228342.0,39.0,4.0,1,2007-08-26 12:00:00 -19503,779,7,5,6.0,3,2.0,2,8.0,58,5204436.0,57.0,1.0,1,2007-08-26 12:00:00 -19504,779,12,5,5.0,1,1.0,1,10.0,58,5202161.0,18.0,2.0,1,2007-08-26 12:00:00 -19505,780,18,7,23.0,14,14.0,14,0.0,52,,46.0,17.0,11,2007-09-09 12:00:00 -19506,780,22,6,11.0,18,15.0,15,0.0,52,,49.0,15.0,11,2007-09-09 12:00:00 -19507,780,10,7,22.0,17,16.0,16,0.0,52,,49.0,11.0,11,2007-09-09 12:00:00 -19508,780,23,4,18.0,19,17.0,17,0.0,52,,45.0,19.0,11,2007-09-09 12:00:00 -19509,780,13,8,14.0,20,,22,0.0,1,,,,3,2007-09-09 12:00:00 -19510,780,28,11,21.0,22,20.0,20,0.0,52,,34.0,21.0,11,2007-09-09 12:00:00 -19511,780,12,5,5.0,3,,21,0.0,10,,8.0,6.0,22,2007-09-09 12:00:00 -19512,780,24,2,17.0,13,13.0,13,0.0,52,,42.0,16.0,11,2007-09-09 12:00:00 -19513,780,15,11,20.0,21,19.0,19,0.0,52,,30.0,20.0,11,2007-09-09 12:00:00 -19514,780,20,3,3.0,15,12.0,12,0.0,52,,32.0,14.0,11,2007-09-09 12:00:00 -19515,780,19,4,19.0,16,18.0,18,0.0,52,,47.0,18.0,11,2007-09-09 12:00:00 -19516,780,21,10,8.0,12,10.0,10,0.0,53,4784764.0,52.0,12.0,1,2007-09-09 12:00:00 -19517,780,3,0,1.0,1,1.0,1,10.0,53,4717806.0,15.0,1.0,1,2007-09-09 12:00:00 -19518,780,0,0,2.0,2,2.0,2,8.0,53,4723868.0,17.0,2.0,1,2007-09-09 12:00:00 -19519,780,7,5,6.0,5,3.0,3,6.0,53,4745131.0,21.0,3.0,1,2007-09-09 12:00:00 -19520,780,1,1,9.0,4,4.0,4,5.0,53,4774368.0,19.0,4.0,1,2007-09-09 12:00:00 -19521,780,14,6,12.0,9,11.0,11,0.0,53,4785542.0,49.0,10.0,1,2007-09-09 12:00:00 -19522,780,2,2,16.0,8,6.0,6,3.0,53,4783616.0,52.0,8.0,1,2007-09-09 12:00:00 -19523,780,4,3,4.0,7,7.0,7,2.0,53,4784557.0,53.0,7.0,1,2007-09-09 12:00:00 -19524,780,17,10,7.0,10,8.0,8,1.0,53,4779974.0,32.0,9.0,1,2007-09-09 12:00:00 -19525,780,16,8,15.0,11,9.0,9,0.0,53,4783685.0,46.0,13.0,1,2007-09-09 12:00:00 -19526,780,8,1,10.0,6,5.0,5,4.0,53,4778364.0,22.0,5.0,1,2007-09-09 12:00:00 -19527,781,15,11,20.0,19,14.0,14,0.0,43,,29.0,15.0,11,2007-09-16 12:00:00 -19528,781,20,3,3.0,22,,22,0.0,1,,,,22,2007-09-16 12:00:00 -19529,781,19,4,19.0,16,,21,0.0,8,,4.0,21.0,38,2007-09-16 12:00:00 -19530,781,13,8,14.0,11,,20,0.0,29,,24.0,17.0,9,2007-09-16 12:00:00 -19531,781,24,2,17.0,15,,19,0.0,34,,18.0,18.0,32,2007-09-16 12:00:00 -19532,781,17,10,7.0,12,,18,0.0,36,,22.0,16.0,9,2007-09-16 12:00:00 -19533,781,28,11,21.0,21,17.0,17,0.0,43,,30.0,20.0,11,2007-09-16 12:00:00 -19534,781,18,7,23.0,20,16.0,16,0.0,43,,43.0,19.0,11,2007-09-16 12:00:00 -19535,781,10,7,22.0,18,15.0,15,0.0,43,,32.0,14.0,11,2007-09-16 12:00:00 -19536,781,21,10,8.0,17,13.0,13,0.0,43,,43.0,12.0,11,2007-09-16 12:00:00 -19537,781,22,6,11.0,10,10.0,10,0.0,44,4927640.0,43.0,10.0,1,2007-09-16 12:00:00 -19538,781,14,6,12.0,8,11.0,11,0.0,44,4942719.0,43.0,7.0,1,2007-09-16 12:00:00 -19539,781,7,5,6.0,1,1.0,1,10.0,44,4839066.0,12.0,2.0,1,2007-09-16 12:00:00 -19540,781,12,5,5.0,2,2.0,2,8.0,44,4843761.0,34.0,1.0,1,2007-09-16 12:00:00 -19541,781,3,0,1.0,3,3.0,3,6.0,44,4853409.0,44.0,3.0,1,2007-09-16 12:00:00 -19542,781,0,0,2.0,4,4.0,4,5.0,44,4862681.0,41.0,4.0,1,2007-09-16 12:00:00 -19543,781,23,4,18.0,13,12.0,12,0.0,43,,40.0,13.0,11,2007-09-16 12:00:00 -19544,781,2,2,16.0,5,6.0,6,3.0,44,4915942.0,29.0,9.0,1,2007-09-16 12:00:00 -19545,781,16,8,15.0,7,7.0,7,2.0,44,4919705.0,12.0,11.0,1,2007-09-16 12:00:00 -19546,781,4,3,4.0,9,8.0,8,1.0,44,4924172.0,21.0,8.0,1,2007-09-16 12:00:00 -19547,781,8,1,10.0,14,9.0,9,0.0,44,4924727.0,32.0,6.0,1,2007-09-16 12:00:00 -19548,781,1,1,9.0,6,5.0,5,4.0,44,4890945.0,33.0,5.0,1,2007-09-16 12:00:00 -19549,782,1,1,9.0,5,14.0,14,0.0,65,,28.0,6.0,39,2007-09-30 04:30:00 -19550,782,24,2,17.0,18,,22,0.0,19,,19.0,22.0,4,2007-09-30 04:30:00 -19551,782,3,0,1.0,2,,21,0.0,41,,25.0,2.0,3,2007-09-30 04:30:00 -19552,782,16,8,15.0,7,,20,0.0,45,,30.0,3.0,4,2007-09-30 04:30:00 -19553,782,2,2,16.0,16,,18,0.0,49,,27.0,10.0,40,2007-09-30 04:30:00 -19554,782,18,7,23.0,19,,17,0.0,54,,27.0,17.0,37,2007-09-30 04:30:00 -19555,782,22,6,11.0,15,,16,0.0,55,,33.0,14.0,29,2007-09-30 04:30:00 -19556,782,10,7,22.0,21,15.0,15,0.0,65,,54.0,16.0,4,2007-09-30 04:30:00 -19557,782,14,6,12.0,13,13.0,13,0.0,66,,55.0,21.0,11,2007-09-30 04:30:00 -19558,782,19,4,19.0,8,,19,0.0,46,,31.0,5.0,4,2007-09-30 04:30:00 -19559,782,17,10,7.0,6,11.0,11,0.0,66,,58.0,19.0,22,2007-09-30 04:30:00 -19560,782,21,10,8.0,17,10.0,10,0.0,67,7322921.0,57.0,15.0,1,2007-09-30 04:30:00 -19561,782,23,4,18.0,14,9.0,9,0.0,67,7315201.0,35.0,13.0,1,2007-09-30 04:30:00 -19562,782,15,11,20.0,20,8.0,8,1.0,67,7294708.0,54.0,18.0,1,2007-09-30 04:30:00 -19563,782,8,1,10.0,9,7.0,7,2.0,67,7283864.0,32.0,4.0,1,2007-09-30 04:30:00 -19564,782,12,5,5.0,4,6.0,6,3.0,67,7283621.0,32.0,7.0,1,2007-09-30 04:30:00 -19565,782,20,3,3.0,10,5.0,5,4.0,67,7273443.0,33.0,12.0,1,2007-09-30 04:30:00 -19566,782,13,8,14.0,12,4.0,4,5.0,67,7254876.0,56.0,11.0,1,2007-09-30 04:30:00 -19567,782,7,5,6.0,3,3.0,3,6.0,67,7244057.0,29.0,8.0,1,2007-09-30 04:30:00 -19568,782,4,3,4.0,11,2.0,2,8.0,67,7242956.0,34.0,9.0,1,2007-09-30 04:30:00 -19569,782,0,0,2.0,1,1.0,1,10.0,67,7234579.0,27.0,1.0,1,2007-09-30 04:30:00 -19570,782,28,11,21.0,22,12.0,12,0.0,66,,33.0,20.0,11,2007-09-30 04:30:00 -19571,783,21,10,8.0,16,15.0,15,0.0,55,,55.0,16.0,11,2007-10-07 06:00:00 -19572,783,2,2,16.0,15,16.0,16,0.0,54,,54.0,6.0,12,2007-10-07 06:00:00 -19573,783,28,11,21.0,22,17.0,17,0.0,53,,52.0,17.0,13,2007-10-07 06:00:00 -19574,783,18,7,23.0,14,,22,0.0,11,,9.0,22.0,23,2007-10-07 06:00:00 -19575,783,22,6,11.0,6,,20,0.0,25,,25.0,20.0,20,2007-10-07 06:00:00 -19576,783,15,11,20.0,21,,21,0.0,24,,22.0,21.0,3,2007-10-07 06:00:00 -19577,783,10,7,22.0,20,14.0,14,0.0,55,,54.0,15.0,11,2007-10-07 06:00:00 -19578,783,0,0,2.0,1,,19,0.0,30,,22.0,19.0,20,2007-10-07 06:00:00 -19579,783,14,6,12.0,12,13.0,13,0.0,55,,55.0,14.0,11,2007-10-07 06:00:00 -19580,783,8,1,10.0,9,,18,0.0,33,,32.0,18.0,9,2007-10-07 06:00:00 -19581,783,20,3,3.0,18,11.0,11,0.0,56,5965078.0,39.0,4.0,1,2007-10-07 06:00:00 -19582,783,24,2,17.0,19,12.0,12,0.0,55,,54.0,12.0,11,2007-10-07 06:00:00 -19583,783,7,5,6.0,2,1.0,1,10.0,56,5878395.0,52.0,3.0,1,2007-10-07 06:00:00 -19584,783,3,0,1.0,4,2.0,2,8.0,56,5888201.0,54.0,2.0,1,2007-10-07 06:00:00 -19585,783,12,5,5.0,3,3.0,3,6.0,56,5891286.0,56.0,1.0,1,2007-10-07 06:00:00 -19586,783,19,4,19.0,17,4.0,4,5.0,56,5931904.0,52.0,13.0,1,2007-10-07 06:00:00 -19587,783,13,8,14.0,5,8.0,8,1.0,56,5959145.0,55.0,10.0,1,2007-10-07 06:00:00 -19588,783,23,4,18.0,11,6.0,6,3.0,56,5952068.0,53.0,11.0,1,2007-10-07 06:00:00 -19589,783,1,1,9.0,8,7.0,7,2.0,56,5952619.0,55.0,7.0,1,2007-10-07 06:00:00 -19590,783,4,3,4.0,13,9.0,9,0.0,56,5959581.0,52.0,8.0,1,2007-10-07 06:00:00 -19591,783,16,8,15.0,7,10.0,10,0.0,56,5963080.0,55.0,9.0,1,2007-10-07 06:00:00 -19592,783,17,10,7.0,10,5.0,5,4.0,56,5947061.0,39.0,5.0,1,2007-10-07 06:00:00 -19593,784,20,3,3.0,12,,22,0.0,2,,2.0,22.0,4,2007-10-21 16:00:00 -19594,784,28,11,21.0,22,,21,0.0,2,,2.0,21.0,4,2007-10-21 16:00:00 -19595,784,16,8,15.0,5,,20,0.0,14,,13.0,15.0,6,2007-10-21 16:00:00 -19596,784,17,10,7.0,16,,19,0.0,20,,20.0,12.0,5,2007-10-21 16:00:00 -19597,784,19,4,19.0,13,,18,0.0,34,,18.0,16.0,9,2007-10-21 16:00:00 -19598,784,4,3,4.0,17,,17,0.0,35,,31.0,18.0,3,2007-10-21 16:00:00 -19599,784,21,10,8.0,11,,16,0.0,40,,32.0,17.0,5,2007-10-21 16:00:00 -19600,784,15,11,20.0,21,,15,0.0,43,,13.0,20.0,23,2007-10-21 16:00:00 -19601,784,18,7,23.0,20,14.0,14,0.0,68,,64.0,14.0,13,2007-10-21 16:00:00 -19602,784,23,4,18.0,14,13.0,13,0.0,69,,56.0,11.0,12,2007-10-21 16:00:00 -19603,784,22,6,11.0,15,11.0,11,0.0,70,,65.0,9.0,11,2007-10-21 16:00:00 -19604,784,5,2,17.0,19,10.0,10,0.0,70,,69.0,5.0,11,2007-10-21 16:00:00 -19605,784,13,8,14.0,9,9.0,9,0.0,70,,22.0,13.0,11,2007-10-21 16:00:00 -19606,784,14,6,12.0,8,8.0,8,1.0,70,,68.0,8.0,11,2007-10-21 16:00:00 -19607,784,1,1,9.0,6,6.0,6,3.0,71,5366587.0,53.0,10.0,1,2007-10-21 16:00:00 -19608,784,8,1,10.0,7,5.0,5,4.0,71,5366227.0,61.0,4.0,1,2007-10-21 16:00:00 -19609,784,2,2,16.0,10,4.0,4,5.0,71,5358118.0,56.0,7.0,1,2007-10-21 16:00:00 -19610,784,3,0,1.0,4,3.0,3,6.0,71,5352289.0,59.0,6.0,1,2007-10-21 16:00:00 -19611,784,12,5,5.0,1,2.0,2,8.0,71,5296763.0,71.0,3.0,1,2007-10-21 16:00:00 -19612,784,7,5,6.0,3,1.0,1,10.0,71,5295270.0,66.0,1.0,1,2007-10-21 16:00:00 -19613,784,10,7,22.0,18,12.0,12,0.0,69,,39.0,19.0,12,2007-10-21 16:00:00 -19614,784,0,0,2.0,2,7.0,7,2.0,70,,58.0,2.0,11,2007-10-21 16:00:00 -19615,785,0,0,22.0,1,1.0,1,10.0,58,5690616.0,39.0,2.0,1,2008-03-16 04:30:00 -19616,785,20,9,21.0,16,,21,0.0,0,,,,4,2008-03-16 04:30:00 -19617,785,19,4,15.0,9,,20,0.0,0,,,,4,2008-03-16 04:30:00 -19618,785,1,1,3.0,5,2.0,2,8.0,58,5696094.0,41.0,3.0,1,2008-03-16 04:30:00 -19619,785,18,7,19.0,21,,19,0.0,0,,,,4,2008-03-16 04:30:00 -19620,785,17,10,16.0,12,,18,0.0,0,,,,4,2008-03-16 04:30:00 -19621,785,16,8,10.0,14,,17,0.0,0,,,,4,2008-03-16 04:30:00 -19622,785,15,9,20.0,22,,16,0.0,8,,8.0,17.0,9,2008-03-16 04:30:00 -19623,785,14,6,11.0,6,,15,0.0,19,,18.0,10.0,10,2008-03-16 04:30:00 -19624,785,13,8,9.0,8,,14,0.0,25,,21.0,11.0,4,2008-03-16 04:30:00 -19625,785,12,5,2.0,4,,13,0.0,29,,23.0,6.0,5,2008-03-16 04:30:00 -19626,785,11,3,6.0,20,,12,0.0,30,,20.0,16.0,8,2008-03-16 04:30:00 -19627,785,21,10,17.0,10,,22,0.0,58,,44.0,8.0,2,2008-03-16 04:30:00 -19628,785,9,6,12.0,18,,10,0.0,43,,23.0,13.0,3,2008-03-16 04:30:00 -19629,785,8,1,4.0,2,,9,0.0,47,,15.0,9.0,4,2008-03-16 04:30:00 -19630,785,7,5,1.0,15,8.0,8,1.0,53,,20.0,4.0,5,2008-03-16 04:30:00 -19631,785,6,4,14.0,17,7.0,7,2.0,55,,22.0,12.0,5,2008-03-16 04:30:00 -19632,785,5,2,8.0,13,6.0,6,3.0,57,,50.0,14.0,11,2008-03-16 04:30:00 -19633,785,4,0,23.0,3,5.0,5,4.0,58,5708630.0,43.0,1.0,1,2008-03-16 04:30:00 -19634,785,2,2,7.0,7,3.0,3,6.0,58,5698779.0,41.0,5.0,1,2008-03-16 04:30:00 -19635,785,3,3,5.0,11,4.0,4,5.0,58,5707797.0,58.0,7.0,1,2008-03-16 04:30:00 -19636,785,10,7,18.0,19,,11,0.0,32,,24.0,15.0,7,2008-03-16 04:30:00 -19637,786,10,7,18.0,19,16.0,16,0.0,54,,53.0,19.0,12,2008-03-23 07:00:00 -19638,786,5,2,8.0,22,17.0,17,0.0,54,,19.0,17.0,12,2008-03-23 07:00:00 -19639,786,19,4,15.0,15,,18,0.0,39,,37.0,14.0,5,2008-03-23 07:00:00 -19640,786,12,5,2.0,1,,19,0.0,30,,15.0,5.0,20,2008-03-23 07:00:00 -19641,786,7,5,1.0,2,1.0,1,10.0,56,5478555.0,37.0,2.0,1,2008-03-23 07:00:00 -19642,786,9,6,12.0,10,,21,0.0,1,,,,4,2008-03-23 07:00:00 -19643,786,6,4,14.0,18,,22,0.0,0,,,,20,2008-03-23 07:00:00 -19644,786,18,7,19.0,21,15.0,15,0.0,55,,55.0,18.0,11,2008-03-23 07:00:00 -19645,786,15,9,20.0,20,,20,0.0,5,,3.0,20.0,9,2008-03-23 07:00:00 -19646,786,21,10,17.0,14,13.0,13,0.0,55,,55.0,11.0,11,2008-03-23 07:00:00 -19647,786,2,2,7.0,16,14.0,14,0.0,55,,55.0,13.0,11,2008-03-23 07:00:00 -19648,786,8,1,4.0,4,2.0,2,8.0,56,5498125.0,39.0,6.0,1,2008-03-23 07:00:00 -19649,786,11,3,6.0,13,11.0,11,0.0,56,5570757.0,52.0,15.0,1,2008-03-23 07:00:00 -19650,786,17,10,16.0,11,10.0,10,0.0,56,5564769.0,56.0,4.0,1,2008-03-23 07:00:00 -19651,786,13,8,9.0,12,9.0,9,0.0,56,5554775.0,55.0,9.0,1,2008-03-23 07:00:00 -19652,786,3,3,5.0,7,8.0,8,1.0,56,5548596.0,40.0,10.0,1,2008-03-23 07:00:00 -19653,786,16,8,10.0,6,7.0,7,2.0,56,5546685.0,53.0,12.0,1,2008-03-23 07:00:00 -19654,786,1,1,3.0,5,6.0,6,3.0,56,5528388.0,55.0,1.0,1,2008-03-23 07:00:00 -19655,786,0,0,22.0,9,5.0,5,4.0,56,5525103.0,53.0,3.0,1,2008-03-23 07:00:00 -19656,786,14,6,11.0,3,4.0,4,5.0,56,5524387.0,53.0,8.0,1,2008-03-23 07:00:00 -19657,786,4,0,23.0,8,3.0,3,6.0,56,5517005.0,19.0,7.0,1,2008-03-23 07:00:00 -19658,786,20,9,21.0,17,12.0,12,0.0,55,,52.0,16.0,11,2008-03-23 07:00:00 -19659,787,6,4,14.0,15,15.0,15,0.0,56,,33.0,15.0,11,2008-04-06 11:30:00 -19660,787,18,7,19.0,21,16.0,16,0.0,56,,45.0,14.0,11,2008-04-06 11:30:00 -19661,787,10,7,18.0,22,17.0,17,0.0,56,,56.0,20.0,11,2008-04-06 11:30:00 -19662,787,13,8,9.0,17,18.0,18,0.0,56,,43.0,16.0,11,2008-04-06 11:30:00 -19663,787,5,2,8.0,16,14.0,14,0.0,56,,30.0,17.0,11,2008-04-06 11:30:00 -19664,787,11,3,6.0,14,,20,0.0,40,,31.0,12.0,6,2008-04-06 11:30:00 -19665,787,17,10,16.0,9,,21,0.0,19,,11.0,21.0,4,2008-04-06 11:30:00 -19666,787,19,4,15.0,19,,22,0.0,0,,,,5,2008-04-06 11:30:00 -19667,787,15,9,20.0,20,19.0,19,0.0,56,,55.0,18.0,12,2008-04-06 11:30:00 -19668,787,0,0,22.0,3,13.0,13,0.0,56,,25.0,19.0,11,2008-04-06 11:30:00 -19669,787,7,5,1.0,4,2.0,2,8.0,57,5470309.0,35.0,4.0,1,2008-04-06 11:30:00 -19670,787,21,10,17.0,12,11.0,11,0.0,57,5544832.0,40.0,10.0,1,2008-04-06 11:30:00 -19671,787,3,3,5.0,10,10.0,10,0.0,57,5544151.0,35.0,13.0,1,2008-04-06 11:30:00 -19672,787,9,6,12.0,13,9.0,9,0.0,57,5536470.0,56.0,9.0,1,2008-04-06 11:30:00 -19673,787,2,2,7.0,8,8.0,8,1.0,57,5522859.0,57.0,6.0,1,2008-04-06 11:30:00 -19674,787,16,8,10.0,11,7.0,7,2.0,57,5512443.0,51.0,8.0,1,2008-04-06 11:30:00 -19675,787,14,6,11.0,7,6.0,6,3.0,57,5508284.0,45.0,7.0,1,2008-04-06 11:30:00 -19676,787,4,0,23.0,5,5.0,5,4.0,57,5493759.0,49.0,1.0,1,2008-04-06 11:30:00 -19677,787,1,1,3.0,6,4.0,4,5.0,57,5475379.0,48.0,2.0,1,2008-04-06 11:30:00 -19678,787,8,1,4.0,1,3.0,3,6.0,57,5471968.0,55.0,5.0,1,2008-04-06 11:30:00 -19679,787,20,9,21.0,18,12.0,12,0.0,56,,56.0,11.0,11,2008-04-06 11:30:00 -19680,787,12,5,2.0,2,1.0,1,10.0,57,5466970.0,38.0,3.0,1,2008-04-06 11:30:00 -19681,788,3,3,5.0,2,,15,0.0,34,,15.0,9.0,5,2008-04-27 12:00:00 -19682,788,21,10,17.0,11,,16,0.0,34,,21.0,16.0,4,2008-04-27 12:00:00 -19683,788,4,0,23.0,6,,17,0.0,21,,19.0,6.0,3,2008-04-27 12:00:00 -19684,788,2,2,7.0,15,,14,0.0,41,,20.0,13.0,5,2008-04-27 12:00:00 -19685,788,6,4,14.0,16,,19,0.0,7,,6.0,19.0,4,2008-04-27 12:00:00 -19686,788,11,3,6.0,10,,20,0.0,6,,6.0,18.0,4,2008-04-27 12:00:00 -19687,788,19,4,15.0,18,,22,0.0,0,,,,4,2008-04-27 12:00:00 -19688,788,18,7,19.0,21,,18,0.0,8,,6.0,20.0,21,2008-04-27 12:00:00 -19689,788,10,7,18.0,22,13.0,13,0.0,65,,34.0,17.0,11,2008-04-27 12:00:00 -19690,788,15,9,20.0,20,,21,0.0,0,,,,4,2008-04-27 12:00:00 -19691,788,9,6,12.0,14,11.0,11,0.0,65,,57.0,12.0,11,2008-04-27 12:00:00 -19692,788,0,0,22.0,5,3.0,3,6.0,66,5903238.0,20.0,3.0,1,2008-04-27 12:00:00 -19693,788,7,5,1.0,1,1.0,1,10.0,66,5899051.0,46.0,1.0,1,2008-04-27 12:00:00 -19694,788,8,1,4.0,4,4.0,4,5.0,66,5904745.0,20.0,4.0,1,2008-04-27 12:00:00 -19695,788,16,8,10.0,7,5.0,5,4.0,66,5934989.0,19.0,8.0,1,2008-04-27 12:00:00 -19696,788,12,5,2.0,3,2.0,2,8.0,66,5902279.0,45.0,2.0,1,2008-04-27 12:00:00 -19697,788,5,2,8.0,12,7.0,7,2.0,66,5957295.0,48.0,15.0,1,2008-04-27 12:00:00 -19698,788,14,6,11.0,8,8.0,8,1.0,66,5958486.0,45.0,10.0,1,2008-04-27 12:00:00 -19699,788,1,1,3.0,9,9.0,9,0.0,66,5962124.0,21.0,7.0,1,2008-04-27 12:00:00 -19700,788,20,9,21.0,19,10.0,10,0.0,65,,40.0,14.0,11,2008-04-27 12:00:00 -19701,788,17,10,16.0,13,6.0,6,3.0,66,5952061.0,66.0,5.0,1,2008-04-27 12:00:00 -19702,788,13,8,9.0,17,12.0,12,0.0,65,,57.0,11.0,11,2008-04-27 12:00:00 -19703,789,4,0,23.0,2,12.0,12,0.0,57,,55.0,8.0,11,2008-05-11 12:00:00 -19704,789,20,9,21.0,20,,20,0.0,0,,,,4,2008-05-11 12:00:00 -19705,789,5,2,8.0,16,,19,0.0,1,,,,4,2008-05-11 12:00:00 -19706,789,6,4,14.0,18,,18,0.0,24,,19.0,17.0,22,2008-05-11 12:00:00 -19707,789,19,4,15.0,14,17.0,17,0.0,57,,38.0,15.0,11,2008-05-11 12:00:00 -19708,789,15,9,20.0,19,16.0,16,0.0,57,,35.0,18.0,11,2008-05-11 12:00:00 -19709,789,11,3,6.0,17,15.0,15,0.0,57,,40.0,10.0,11,2008-05-11 12:00:00 -19710,789,21,10,17.0,12,14.0,14,0.0,57,,56.0,14.0,11,2008-05-11 12:00:00 -19711,789,9,6,12.0,15,13.0,13,0.0,57,,28.0,16.0,11,2008-05-11 12:00:00 -19712,789,17,10,16.0,13,11.0,11,0.0,57,,57.0,13.0,11,2008-05-11 12:00:00 -19713,789,13,8,9.0,10,9.0,9,0.0,58,5284721.0,41.0,12.0,1,2008-05-11 12:00:00 -19714,789,2,2,7.0,11,8.0,8,1.0,58,5280857.0,55.0,9.0,1,2008-05-11 12:00:00 -19715,789,16,8,10.0,6,7.0,7,2.0,58,5273680.0,14.0,7.0,1,2008-05-11 12:00:00 -19716,789,3,3,5.0,7,6.0,6,3.0,58,5263175.0,57.0,6.0,1,2008-05-11 12:00:00 -19717,789,1,1,3.0,9,5.0,5,4.0,58,5248192.0,20.0,5.0,1,2008-05-11 12:00:00 -19718,789,8,1,4.0,5,4.0,4,5.0,58,5231396.0,17.0,4.0,1,2008-05-11 12:00:00 -19719,789,7,5,1.0,4,3.0,3,6.0,58,5213722.0,20.0,1.0,1,2008-05-11 12:00:00 -19720,789,0,0,22.0,3,2.0,2,8.0,58,5213230.0,31.0,2.0,1,2008-05-11 12:00:00 -19721,789,12,5,2.0,1,1.0,1,10.0,58,5209451.0,16.0,3.0,1,2008-05-11 12:00:00 -19722,789,14,6,11.0,8,10.0,10,0.0,58,5285795.0,52.0,11.0,1,2008-05-11 12:00:00 -19723,790,14,6,11.0,8,13.0,13,0.0,75,,75.0,12.0,11,2008-05-25 12:00:00 -19724,790,1,1,3.0,12,14.0,14,0.0,72,,72.0,14.0,14,2008-05-25 12:00:00 -19725,790,15,9,20.0,18,,15,0.0,67,,60.0,16.0,4,2008-05-25 12:00:00 -19726,790,6,4,14.0,16,,20,0.0,7,,7.0,19.0,4,2008-05-25 12:00:00 -19727,790,11,3,6.0,17,,17,0.0,47,,40.0,17.0,3,2008-05-25 12:00:00 -19728,790,20,9,21.0,20,,18,0.0,36,,33.0,18.0,6,2008-05-25 12:00:00 -19729,790,13,8,9.0,15,,19,0.0,7,,7.0,20.0,3,2008-05-25 12:00:00 -19730,790,2,2,7.0,6,,16,0.0,59,,58.0,15.0,3,2008-05-25 12:00:00 -19731,790,9,6,12.0,10,12.0,12,0.0,75,,75.0,11.0,11,2008-05-25 12:00:00 -19732,790,3,3,5.0,7,10.0,10,0.0,75,,73.0,3.0,11,2008-05-25 12:00:00 -19733,790,7,5,1.0,2,9.0,9,0.0,76,7276534.0,74.0,1.0,1,2008-05-25 12:00:00 -19734,790,0,0,22.0,3,1.0,1,10.0,76,7242742.0,71.0,6.0,1,2008-05-25 12:00:00 -19735,790,8,1,4.0,5,2.0,2,8.0,76,7245806.0,75.0,5.0,1,2008-05-25 12:00:00 -19736,790,12,5,2.0,1,3.0,3,6.0,76,7247553.0,76.0,4.0,1,2008-05-25 12:00:00 -19737,790,16,8,10.0,9,4.0,4,5.0,76,7262037.0,74.0,8.0,1,2008-05-25 12:00:00 -19738,790,17,10,16.0,11,11.0,11,0.0,75,,74.0,10.0,11,2008-05-25 12:00:00 -19739,790,21,10,17.0,14,6.0,6,3.0,76,7271150.0,75.0,9.0,1,2008-05-25 12:00:00 -19740,790,5,2,8.0,13,7.0,7,2.0,76,7272922.0,75.0,13.0,1,2008-05-25 12:00:00 -19741,790,4,0,23.0,4,8.0,8,1.0,76,7275933.0,74.0,2.0,1,2008-05-25 12:00:00 -19742,790,19,4,15.0,19,5.0,5,4.0,76,7267399.0,74.0,7.0,1,2008-05-25 12:00:00 -19743,791,16,8,10.0,10,12.0,12,0.0,70,5855526.0,51.0,8.0,1,2008-06-08 17:00:00 -19744,791,0,0,22.0,1,,19,0.0,19,,4.0,3.0,4,2008-06-08 17:00:00 -19745,791,7,5,1.0,3,,18,0.0,19,,14.0,1.0,4,2008-06-08 17:00:00 -19746,791,11,3,6.0,15,,17,0.0,43,,16.0,18.0,23,2008-06-08 17:00:00 -19747,791,3,3,5.0,4,,16,0.0,44,,16.0,9.0,20,2008-06-08 17:00:00 -19748,791,5,2,8.0,12,,15,0.0,46,,30.0,14.0,3,2008-06-08 17:00:00 -19749,791,20,9,21.0,17,,14,0.0,51,,41.0,16.0,20,2008-06-08 17:00:00 -19750,791,6,4,14.0,18,13.0,13,0.0,69,,34.0,13.0,11,2008-06-08 17:00:00 -19751,791,15,9,20.0,16,,20,0.0,13,,7.0,20.0,6,2008-06-08 17:00:00 -19752,791,17,10,16.0,20,11.0,11,0.0,70,5851767.0,58.0,19.0,1,2008-06-08 17:00:00 -19753,791,4,0,23.0,7,9.0,9,0.0,70,5838660.0,62.0,11.0,1,2008-06-08 17:00:00 -19754,791,2,2,7.0,5,10.0,10,0.0,70,5838976.0,14.0,5.0,1,2008-06-08 17:00:00 -19755,791,1,1,3.0,8,2.0,2,8.0,70,5800722.0,25.0,2.0,1,2008-06-08 17:00:00 -19756,791,13,8,9.0,13,3.0,3,6.0,70,5807579.0,36.0,7.0,1,2008-06-08 17:00:00 -19757,791,9,6,12.0,11,4.0,4,5.0,70,5826854.0,31.0,17.0,1,2008-06-08 17:00:00 -19758,791,8,1,4.0,2,1.0,1,10.0,70,5784227.0,47.0,4.0,1,2008-06-08 17:00:00 -19759,791,14,6,11.0,14,6.0,6,3.0,70,5832002.0,38.0,15.0,1,2008-06-08 17:00:00 -19760,791,21,10,17.0,9,7.0,7,2.0,70,5837824.0,35.0,10.0,1,2008-06-08 17:00:00 -19761,791,19,4,15.0,19,8.0,8,1.0,70,5838347.0,33.0,12.0,1,2008-06-08 17:00:00 -19762,791,12,5,2.0,6,5.0,5,4.0,70,5828161.0,11.0,6.0,1,2008-06-08 17:00:00 -19763,792,17,10,16.0,16,,20,0.0,16,,15.0,20.0,4,2008-06-22 12:00:00 -19764,792,15,9,20.0,18,19.0,19,0.0,69,,41.0,18.0,11,2008-06-22 12:00:00 -19765,792,20,9,21.0,17,18.0,18,0.0,69,,53.0,19.0,11,2008-06-22 12:00:00 -19766,792,6,4,14.0,14,17.0,17,0.0,69,,28.0,16.0,11,2008-06-22 12:00:00 -19767,792,2,2,7.0,19,16.0,16,0.0,69,,38.0,17.0,11,2008-06-22 12:00:00 -19768,792,5,2,8.0,15,15.0,15,0.0,69,,60.0,15.0,11,2008-06-22 12:00:00 -19769,792,1,1,3.0,11,13.0,13,0.0,70,5572324.0,46.0,9.0,1,2008-06-22 12:00:00 -19770,792,19,4,15.0,12,12.0,12,0.0,70,5568310.0,36.0,11.0,1,2008-06-22 12:00:00 -19771,792,21,10,17.0,20,14.0,14,0.0,69,,54.0,14.0,11,2008-06-22 12:00:00 -19772,792,0,0,22.0,13,10.0,10,0.0,70,5564783.0,40.0,5.0,1,2008-06-22 12:00:00 -19773,792,12,5,2.0,2,1.0,1,10.0,70,5510245.0,20.0,2.0,1,2008-06-22 12:00:00 -19774,792,9,6,12.0,8,11.0,11,0.0,70,5567945.0,45.0,13.0,1,2008-06-22 12:00:00 -19775,792,7,5,1.0,1,2.0,2,8.0,70,5528229.0,16.0,1.0,1,2008-06-22 12:00:00 -19776,792,14,6,11.0,4,3.0,3,6.0,70,5538495.0,12.0,7.0,1,2008-06-22 12:00:00 -19777,792,4,0,23.0,10,4.0,4,5.0,70,5539174.0,46.0,3.0,1,2008-06-22 12:00:00 -19778,792,3,3,5.0,3,8.0,8,1.0,70,5553617.0,39.0,8.0,1,2008-06-22 12:00:00 -19779,792,16,8,10.0,6,6.0,6,3.0,70,5550549.0,22.0,6.0,1,2008-06-22 12:00:00 -19780,792,11,3,6.0,9,7.0,7,2.0,70,5551278.0,24.0,10.0,1,2008-06-22 12:00:00 -19781,792,8,1,4.0,5,5.0,5,4.0,70,5540757.0,16.0,4.0,1,2008-06-22 12:00:00 -19782,792,13,8,9.0,7,9.0,9,0.0,70,5561266.0,23.0,12.0,1,2008-06-22 12:00:00 -19783,793,13,8,9.0,11,,20,0.0,0,,,,4,2008-07-06 12:00:00 -19784,793,19,4,15.0,8,,19,0.0,0,,,,4,2008-07-06 12:00:00 -19785,793,15,9,20.0,18,,18,0.0,10,,5.0,18.0,20,2008-07-06 12:00:00 -19786,793,20,9,21.0,19,,17,0.0,16,,21.0,17.0,20,2008-07-06 12:00:00 -19787,793,11,3,6.0,7,,16,0.0,35,,21.0,7.0,20,2008-07-06 12:00:00 -19788,793,17,10,16.0,17,,15,0.0,38,,21.0,10.0,20,2008-07-06 12:00:00 -19789,793,12,5,2.0,9,13.0,13,0.0,58,,19.0,8.0,12,2008-07-06 12:00:00 -19790,793,9,6,12.0,12,12.0,12,0.0,59,,19.0,15.0,11,2008-07-06 12:00:00 -19791,793,8,1,4.0,10,,14,0.0,39,,22.0,12.0,20,2008-07-06 12:00:00 -19792,793,16,8,10.0,2,10.0,10,0.0,59,,17.0,4.0,11,2008-07-06 12:00:00 -19793,793,0,0,22.0,4,1.0,1,10.0,60,5949440.0,16.0,3.0,1,2008-07-06 12:00:00 -19794,793,6,4,14.0,13,11.0,11,0.0,59,,21.0,9.0,11,2008-07-06 12:00:00 -19795,793,21,10,17.0,16,3.0,3,6.0,60,6031713.0,21.0,11.0,1,2008-07-06 12:00:00 -19796,793,7,5,1.0,3,4.0,4,5.0,59,,18.0,1.0,11,2008-07-06 12:00:00 -19797,793,4,0,23.0,1,5.0,5,4.0,59,,17.0,5.0,11,2008-07-06 12:00:00 -19798,793,1,1,3.0,5,2.0,2,8.0,60,6018017.0,21.0,2.0,1,2008-07-06 12:00:00 -19799,793,14,6,11.0,14,7.0,7,2.0,59,,22.0,13.0,11,2008-07-06 12:00:00 -19800,793,5,2,8.0,15,8.0,8,1.0,59,,21.0,14.0,11,2008-07-06 12:00:00 -19801,793,2,2,7.0,20,9.0,9,0.0,59,,21.0,16.0,11,2008-07-06 12:00:00 -19802,793,3,3,5.0,6,6.0,6,3.0,59,,17.0,6.0,11,2008-07-06 12:00:00 -19803,794,13,8,9.0,10,13.0,13,0.0,67,5535845.0,18.0,11.0,1,2008-07-20 12:00:00 -19804,794,9,6,12.0,11,,20,0.0,35,,24.0,7.0,22,2008-07-20 12:00:00 -19805,794,16,8,10.0,8,,19,0.0,40,,20.0,14.0,5,2008-07-20 12:00:00 -19806,794,21,10,17.0,18,,18,0.0,50,,30.0,19.0,4,2008-07-20 12:00:00 -19807,794,17,10,16.0,14,17.0,17,0.0,66,,56.0,16.0,11,2008-07-20 12:00:00 -19808,794,20,9,21.0,20,16.0,16,0.0,67,5564967.0,67.0,20.0,1,2008-07-20 12:00:00 -19809,794,5,2,8.0,16,14.0,14,0.0,67,5540877.0,23.0,17.0,1,2008-07-20 12:00:00 -19810,794,6,4,14.0,15,12.0,12,0.0,67,5519985.0,63.0,10.0,1,2008-07-20 12:00:00 -19811,794,15,9,20.0,19,15.0,15,0.0,67,5550362.0,66.0,18.0,1,2008-07-20 12:00:00 -19812,794,2,2,7.0,13,10.0,10,0.0,67,5518499.0,34.0,15.0,1,2008-07-20 12:00:00 -19813,794,11,3,6.0,17,2.0,2,8.0,67,5486460.0,66.0,9.0,1,2008-07-20 12:00:00 -19814,794,12,5,2.0,2,3.0,3,6.0,67,5490213.0,19.0,5.0,1,2008-07-20 12:00:00 -19815,794,1,1,3.0,12,4.0,4,5.0,67,5490699.0,52.0,1.0,1,2008-07-20 12:00:00 -19816,794,4,0,23.0,3,5.0,5,4.0,67,5493285.0,63.0,4.0,1,2008-07-20 12:00:00 -19817,794,0,0,22.0,1,1.0,1,10.0,67,5480874.0,17.0,2.0,1,2008-07-20 12:00:00 -19818,794,8,1,4.0,7,7.0,7,2.0,67,5503556.0,17.0,6.0,1,2008-07-20 12:00:00 -19819,794,19,4,15.0,9,8.0,8,1.0,67,5514173.0,20.0,8.0,1,2008-07-20 12:00:00 -19820,794,14,6,11.0,4,9.0,9,0.0,67,5518032.0,17.0,12.0,1,2008-07-20 12:00:00 -19821,794,7,5,1.0,6,6.0,6,3.0,67,5495277.0,66.0,3.0,1,2008-07-20 12:00:00 -19822,794,3,3,5.0,5,11.0,11,0.0,67,5519474.0,17.0,13.0,1,2008-07-20 12:00:00 -19823,795,17,10,16.0,12,12.0,12,0.0,69,,63.0,13.0,11,2008-08-03 12:00:00 -19824,795,19,4,15.0,11,,20,0.0,22,,17.0,20.0,25,2008-08-03 12:00:00 -19825,795,15,9,20.0,20,,19,0.0,62,,29.0,19.0,23,2008-08-03 12:00:00 -19826,795,6,4,14.0,19,18.0,18,0.0,67,,29.0,17.0,13,2008-08-03 12:00:00 -19827,795,12,5,2.0,3,17.0,17,0.0,67,,16.0,2.0,5,2008-08-03 12:00:00 -19828,795,21,10,17.0,17,16.0,16,0.0,68,,65.0,14.0,12,2008-08-03 12:00:00 -19829,795,20,9,21.0,18,15.0,15,0.0,69,,68.0,15.0,11,2008-08-03 12:00:00 -19830,795,2,2,7.0,14,14.0,14,0.0,69,,57.0,12.0,11,2008-08-03 12:00:00 -19831,795,5,2,8.0,16,13.0,13,0.0,69,,67.0,18.0,11,2008-08-03 12:00:00 -19832,795,13,8,9.0,13,11.0,11,0.0,70,5917474.0,67.0,16.0,1,2008-08-03 12:00:00 -19833,795,16,8,10.0,8,9.0,9,0.0,70,5905901.0,67.0,10.0,1,2008-08-03 12:00:00 -19834,795,8,1,4.0,4,8.0,8,1.0,70,5895388.0,70.0,9.0,1,2008-08-03 12:00:00 -19835,795,14,6,11.0,9,7.0,7,2.0,70,5883516.0,65.0,5.0,1,2008-08-03 12:00:00 -19836,795,11,3,6.0,10,6.0,6,3.0,70,5879365.0,64.0,4.0,1,2008-08-03 12:00:00 -19837,795,0,0,22.0,1,5.0,5,4.0,70,5870115.0,15.0,3.0,1,2008-08-03 12:00:00 -19838,795,3,3,5.0,7,4.0,4,5.0,70,5868681.0,47.0,8.0,1,2008-08-03 12:00:00 -19839,795,7,5,1.0,6,3.0,3,6.0,70,5863923.0,61.0,1.0,1,2008-08-03 12:00:00 -19840,795,9,6,12.0,5,2.0,2,8.0,70,5858128.0,42.0,6.0,1,2008-08-03 12:00:00 -19841,795,4,0,23.0,2,1.0,1,10.0,70,5847067.0,19.0,7.0,1,2008-08-03 12:00:00 -19842,795,1,1,3.0,15,10.0,10,0.0,70,5914776.0,67.0,11.0,1,2008-08-03 12:00:00 -19843,796,17,10,16.0,16,13.0,13,0.0,56,,21.0,18.0,11,2008-08-24 12:00:00 -19844,796,20,9,21.0,18,14.0,14,0.0,56,,54.0,15.0,11,2008-08-24 12:00:00 -19845,796,5,2,8.0,11,15.0,15,0.0,56,,56.0,13.0,11,2008-08-24 12:00:00 -19846,796,3,3,5.0,12,,20,0.0,0,,,,4,2008-08-24 12:00:00 -19847,796,13,8,9.0,17,17.0,17,0.0,56,,13.0,19.0,11,2008-08-24 12:00:00 -19848,796,7,5,1.0,4,,18,0.0,45,,34.0,5.0,5,2008-08-24 12:00:00 -19849,796,15,9,20.0,20,,19,0.0,41,,28.0,17.0,3,2008-08-24 12:00:00 -19850,796,21,10,17.0,19,16.0,16,0.0,56,,56.0,16.0,11,2008-08-24 12:00:00 -19851,796,16,8,10.0,14,12.0,12,0.0,56,,27.0,14.0,11,2008-08-24 12:00:00 -19852,796,6,4,14.0,10,10.0,10,0.0,57,5822133.0,35.0,11.0,1,2008-08-24 12:00:00 -19853,796,1,1,3.0,8,9.0,9,0.0,57,5814516.0,57.0,7.0,1,2008-08-24 12:00:00 -19854,796,12,5,2.0,1,1.0,1,10.0,57,5732339.0,36.0,1.0,1,2008-08-24 12:00:00 -19855,796,11,3,6.0,15,11.0,11,0.0,57,5825056.0,29.0,9.0,1,2008-08-24 12:00:00 -19856,796,0,0,22.0,2,2.0,2,8.0,57,5737950.0,16.0,2.0,1,2008-08-24 12:00:00 -19857,796,8,1,4.0,3,3.0,3,6.0,57,5769692.0,38.0,4.0,1,2008-08-24 12:00:00 -19858,796,19,4,15.0,6,6.0,6,3.0,57,5784964.0,36.0,6.0,1,2008-08-24 12:00:00 -19859,796,14,6,11.0,7,5.0,5,4.0,57,5783023.0,37.0,12.0,1,2008-08-24 12:00:00 -19860,796,2,2,7.0,9,8.0,8,1.0,57,5803796.0,35.0,10.0,1,2008-08-24 12:00:00 -19861,796,9,6,12.0,13,7.0,7,2.0,57,5800329.0,54.0,8.0,1,2008-08-24 12:00:00 -19862,796,4,0,23.0,5,4.0,4,5.0,57,5772042.0,19.0,3.0,1,2008-08-24 12:00:00 -19863,797,11,3,6.0,12,,20,0.0,13,,12.0,18.0,20,2008-09-07 12:00:00 -19864,797,21,10,17.0,16,,19,0.0,19,,10.0,20.0,6,2008-09-07 12:00:00 -19865,797,7,5,1.0,4,18.0,18,0.0,42,,24.0,1.0,20,2008-09-07 12:00:00 -19866,797,20,9,21.0,20,17.0,17,0.0,43,,17.0,19.0,11,2008-09-07 12:00:00 -19867,797,14,6,11.0,11,16.0,16,0.0,43,,32.0,14.0,11,2008-09-07 12:00:00 -19868,797,5,2,8.0,19,14.0,14,0.0,43,,35.0,17.0,11,2008-09-07 12:00:00 -19869,797,15,9,20.0,18,13.0,13,0.0,43,,27.0,13.0,11,2008-09-07 12:00:00 -19870,797,2,2,7.0,15,12.0,12,0.0,43,,32.0,15.0,11,2008-09-07 12:00:00 -19871,797,17,10,16.0,17,15.0,15,0.0,43,,19.0,16.0,11,2008-09-07 12:00:00 -19872,797,4,0,23.0,3,10.0,10,0.0,43,,35.0,4.0,6,2008-09-07 12:00:00 -19873,797,9,6,12.0,13,9.0,9,0.0,44,5046439.0,37.0,12.0,1,2008-09-07 12:00:00 -19874,797,16,8,10.0,7,8.0,8,1.0,44,5022170.0,34.0,10.0,1,2008-09-07 12:00:00 -19875,797,6,4,14.0,9,7.0,7,2.0,44,4996129.0,31.0,6.0,1,2008-09-07 12:00:00 -19876,797,8,1,4.0,8,6.0,6,3.0,44,4994431.0,36.0,5.0,1,2008-09-07 12:00:00 -19877,797,19,4,15.0,10,5.0,5,4.0,44,4993970.0,16.0,8.0,1,2008-09-07 12:00:00 -19878,797,3,3,5.0,6,4.0,4,5.0,44,4993872.0,25.0,9.0,1,2008-09-07 12:00:00 -19879,797,0,0,22.0,1,3.0,3,6.0,44,4989933.0,20.0,2.0,1,2008-09-07 12:00:00 -19880,797,1,1,3.0,5,2.0,2,8.0,44,4988777.0,36.0,7.0,1,2008-09-07 12:00:00 -19881,797,13,8,9.0,14,11.0,11,0.0,43,,19.0,11.0,11,2008-09-07 12:00:00 -19882,797,12,5,2.0,2,1.0,1,10.0,44,4979394.0,26.0,3.0,1,2008-09-07 12:00:00 -19883,798,14,6,11.0,7,13.0,13,0.0,53,5273448.0,52.0,15.0,1,2008-09-14 12:00:00 -19884,798,2,2,7.0,5,14.0,14,0.0,53,5276129.0,53.0,10.0,1,2008-09-14 12:00:00 -19885,798,17,10,16.0,19,15.0,15,0.0,53,5280864.0,52.0,7.0,1,2008-09-14 12:00:00 -19886,798,20,9,21.0,12,,20,0.0,11,,6.0,20.0,3,2008-09-14 12:00:00 -19887,798,21,10,17.0,16,17.0,17,0.0,52,,42.0,19.0,11,2008-09-14 12:00:00 -19888,798,6,4,14.0,4,18.0,18,0.0,52,,52.0,2.0,11,2008-09-14 12:00:00 -19889,798,15,9,20.0,20,19.0,19,0.0,51,,51.0,18.0,12,2008-09-14 12:00:00 -19890,798,13,8,9.0,13,16.0,16,0.0,52,,49.0,17.0,11,2008-09-14 12:00:00 -19891,798,5,2,8.0,18,12.0,12,0.0,53,5269509.0,53.0,11.0,1,2008-09-14 12:00:00 -19892,798,11,3,6.0,17,10.0,10,0.0,53,5261939.0,53.0,16.0,1,2008-09-14 12:00:00 -19893,798,7,5,1.0,14,9.0,9,0.0,53,5246962.0,53.0,1.0,1,2008-09-14 12:00:00 -19894,798,9,6,12.0,9,11.0,11,0.0,53,5266382.0,53.0,8.0,1,2008-09-14 12:00:00 -19895,798,19,4,15.0,1,1.0,1,10.0,53,5207494.0,53.0,14.0,1,2008-09-14 12:00:00 -19896,798,4,0,23.0,2,2.0,2,8.0,53,5220006.0,53.0,13.0,1,2008-09-14 12:00:00 -19897,798,8,1,4.0,11,3.0,3,6.0,53,5227965.0,52.0,12.0,1,2008-09-14 12:00:00 -19898,798,0,0,22.0,15,7.0,7,2.0,53,5237406.0,52.0,5.0,1,2008-09-14 12:00:00 -19899,798,1,1,3.0,10,5.0,5,4.0,53,5235242.0,53.0,6.0,1,2008-09-14 12:00:00 -19900,798,12,5,2.0,6,6.0,6,3.0,53,5236310.0,52.0,4.0,1,2008-09-14 12:00:00 -19901,798,16,8,10.0,3,8.0,8,1.0,53,5239542.0,52.0,3.0,1,2008-09-14 12:00:00 -19902,798,3,3,5.0,8,4.0,4,5.0,53,5231397.0,51.0,9.0,1,2008-09-14 12:00:00 -19903,799,21,10,17.0,18,,19,0.0,14,,13.0,19.0,26,2008-09-28 12:00:00 -19904,799,16,8,10.0,13,,18,0.0,29,,13.0,17.0,7,2008-09-28 12:00:00 -19905,799,15,9,20.0,19,,17,0.0,49,,38.0,18.0,3,2008-09-28 12:00:00 -19906,799,14,6,11.0,11,,16,0.0,50,,32.0,7.0,9,2008-09-28 12:00:00 -19907,799,7,5,1.0,3,15.0,15,0.0,57,,14.0,1.0,3,2008-09-28 12:00:00 -19908,799,11,3,6.0,16,,20,0.0,13,,13.0,20.0,3,2008-09-28 12:00:00 -19909,799,12,5,2.0,1,13.0,13,0.0,61,7071474.0,13.0,2.0,1,2008-09-28 12:00:00 -19910,799,6,4,14.0,17,12.0,12,0.0,61,7065736.0,29.0,14.0,1,2008-09-28 12:00:00 -19911,799,4,0,23.0,5,10.0,10,0.0,61,7063206.0,14.0,12.0,1,2008-09-28 12:00:00 -19912,799,17,10,16.0,12,9.0,9,0.0,61,7056189.0,61.0,15.0,1,2008-09-28 12:00:00 -19913,799,5,2,8.0,10,8.0,8,1.0,61,7054793.0,13.0,10.0,1,2008-09-28 12:00:00 -19914,799,1,1,3.0,9,6.0,6,3.0,61,7047405.0,14.0,11.0,1,2008-09-28 12:00:00 -19915,799,19,4,15.0,6,5.0,5,4.0,61,7046572.0,13.0,9.0,1,2008-09-28 12:00:00 -19916,799,9,6,12.0,7,4.0,4,5.0,61,7044459.0,50.0,8.0,1,2008-09-28 12:00:00 -19917,799,0,0,22.0,2,3.0,3,6.0,61,7042221.0,14.0,4.0,1,2008-09-28 12:00:00 -19918,799,2,2,7.0,8,2.0,2,8.0,61,7039261.0,39.0,5.0,1,2008-09-28 12:00:00 -19919,799,3,3,5.0,15,1.0,1,10.0,61,7036304.0,55.0,3.0,1,2008-09-28 12:00:00 -19920,799,8,1,4.0,4,11.0,11,0.0,61,7064279.0,14.0,6.0,1,2008-09-28 12:00:00 -19921,799,13,8,9.0,14,7.0,7,2.0,61,7052691.0,41.0,13.0,1,2008-09-28 12:00:00 -19922,799,20,9,21.0,20,14.0,14,0.0,61,7079875.0,28.0,16.0,1,2008-09-28 12:00:00 -19923,800,16,8,10.0,13,8.0,8,1.0,67,5472703.0,30.0,13.0,1,2008-10-12 04:30:00 -19924,800,12,5,2.0,5,7.0,7,2.0,67,5468050.0,55.0,1.0,1,2008-10-12 04:30:00 -19925,800,1,1,3.0,16,9.0,9,0.0,67,5476012.0,67.0,8.0,1,2008-10-12 04:30:00 -19926,800,13,8,9.0,11,,20,0.0,0,,,,4,2008-10-12 04:30:00 -19927,800,9,6,12.0,8,,19,0.0,6,,4.0,14.0,28,2008-10-12 04:30:00 -19928,800,15,9,20.0,19,,18,0.0,8,,6.0,18.0,27,2008-10-12 04:30:00 -19929,800,20,9,21.0,20,,16,0.0,21,,20.0,19.0,6,2008-10-12 04:30:00 -19930,800,19,4,15.0,9,6.0,6,3.0,67,5461099.0,21.0,12.0,1,2008-10-12 04:30:00 -19931,800,14,6,11.0,7,5.0,5,4.0,67,5445659.0,18.0,9.0,1,2008-10-12 04:30:00 -19932,800,11,3,6.0,12,4.0,4,5.0,67,5442462.0,54.0,4.0,1,2008-10-12 04:30:00 -19933,800,4,0,23.0,3,,17,0.0,16,,12.0,5.0,5,2008-10-12 04:30:00 -19934,800,8,1,4.0,6,2.0,2,8.0,67,5427175.0,16.0,7.0,1,2008-10-12 04:30:00 -19935,800,3,3,5.0,4,1.0,1,10.0,67,5421892.0,41.0,3.0,1,2008-10-12 04:30:00 -19936,800,5,2,8.0,14,15.0,15,0.0,66,,32.0,15.0,11,2008-10-12 04:30:00 -19937,800,17,10,16.0,18,14.0,14,0.0,66,,66.0,17.0,11,2008-10-12 04:30:00 -19938,800,21,10,17.0,17,13.0,13,0.0,66,,66.0,16.0,11,2008-10-12 04:30:00 -19939,800,0,0,22.0,1,12.0,12,0.0,67,5500792.0,65.0,11.0,1,2008-10-12 04:30:00 -19940,800,2,2,7.0,15,11.0,11,0.0,67,5483988.0,66.0,10.0,1,2008-10-12 04:30:00 -19941,800,7,5,1.0,2,3.0,3,6.0,67,5428292.0,66.0,2.0,1,2008-10-12 04:30:00 -19942,800,6,4,14.0,10,10.0,10,0.0,67,5480977.0,49.0,6.0,1,2008-10-12 04:30:00 -19943,801,16,8,10.0,16,14.0,14,0.0,56,5609825.0,10.0,13.0,1,2008-10-19 07:00:00 -19944,801,2,2,7.0,14,15.0,15,0.0,55,,38.0,10.0,11,2008-10-19 07:00:00 -19945,801,17,10,16.0,18,16.0,16,0.0,55,,54.0,15.0,11,2008-10-19 07:00:00 -19946,801,14,6,11.0,7,,20,0.0,2,,2.0,20.0,4,2008-10-19 07:00:00 -19947,801,4,0,23.0,5,,18,0.0,49,,32.0,11.0,9,2008-10-19 07:00:00 -19948,801,15,9,20.0,19,,19,0.0,13,,13.0,19.0,5,2008-10-19 07:00:00 -19949,801,6,4,14.0,8,13.0,13,0.0,56,5608860.0,36.0,12.0,1,2008-10-19 07:00:00 -19950,801,20,9,21.0,20,17.0,17,0.0,55,,54.0,18.0,11,2008-10-19 07:00:00 -19951,801,5,2,8.0,17,12.0,12,0.0,56,5608250.0,54.0,17.0,1,2008-10-19 07:00:00 -19952,801,1,1,3.0,9,5.0,5,4.0,56,5546326.0,56.0,3.0,1,2008-10-19 07:00:00 -19953,801,13,8,9.0,15,10.0,10,0.0,56,5592245.0,27.0,14.0,1,2008-10-19 07:00:00 -19954,801,19,4,15.0,6,9.0,9,0.0,56,5581742.0,55.0,9.0,1,2008-10-19 07:00:00 -19955,801,11,3,6.0,10,8.0,8,1.0,56,5574048.0,56.0,8.0,1,2008-10-19 07:00:00 -19956,801,9,6,12.0,12,7.0,7,2.0,56,5559125.0,56.0,6.0,1,2008-10-19 07:00:00 -19957,801,8,1,4.0,11,6.0,6,3.0,56,5550622.0,56.0,7.0,1,2008-10-19 07:00:00 -19958,801,3,3,5.0,4,4.0,4,5.0,56,5535773.0,56.0,5.0,1,2008-10-19 07:00:00 -19959,801,7,5,1.0,2,3.0,3,6.0,56,5533848.0,14.0,2.0,1,2008-10-19 07:00:00 -19960,801,12,5,2.0,3,2.0,2,8.0,56,5532328.0,36.0,4.0,1,2008-10-19 07:00:00 -19961,801,0,0,22.0,1,1.0,1,10.0,56,5517403.0,13.0,1.0,1,2008-10-19 07:00:00 -19962,801,21,10,17.0,13,11.0,11,0.0,56,5602464.0,56.0,16.0,1,2008-10-19 07:00:00 -19963,802,0,0,22.0,4,5.0,5,4.0,71,5690342.0,31.0,4.0,1,2008-11-02 17:00:00 -19964,802,12,5,2.0,1,1.0,1,10.0,71,5651435.0,36.0,1.0,1,2008-11-02 17:00:00 -19965,802,3,3,5.0,6,2.0,2,8.0,71,5664733.0,39.0,8.0,1,2008-11-02 17:00:00 -19966,802,7,5,1.0,3,3.0,3,6.0,71,5667670.0,59.0,3.0,1,2008-11-02 17:00:00 -19967,802,19,4,15.0,7,4.0,4,5.0,71,5689446.0,25.0,7.0,1,2008-11-02 17:00:00 -19968,802,9,6,12.0,10,6.0,6,3.0,71,5695803.0,32.0,2.0,1,2008-11-02 17:00:00 -19969,802,5,2,8.0,16,17.0,17,0.0,69,,50.0,18.0,12,2008-11-02 17:00:00 -19970,802,14,6,11.0,2,8.0,8,1.0,71,5719868.0,40.0,5.0,1,2008-11-02 17:00:00 -19971,802,4,0,23.0,5,7.0,7,2.0,71,5706509.0,36.0,6.0,1,2008-11-02 17:00:00 -19972,802,13,8,9.0,14,,20,0.0,0,,,,4,2008-11-02 17:00:00 -19973,802,11,3,6.0,11,,19,0.0,0,,,,3,2008-11-02 17:00:00 -19974,802,20,9,21.0,19,18.0,18,0.0,69,,36.0,15.0,12,2008-11-02 17:00:00 -19975,802,15,9,20.0,20,16.0,16,0.0,69,,60.0,17.0,12,2008-11-02 17:00:00 -19976,802,8,1,4.0,13,11.0,11,0.0,70,,61.0,9.0,11,2008-11-02 17:00:00 -19977,802,6,4,14.0,9,14.0,14,0.0,70,,57.0,13.0,11,2008-11-02 17:00:00 -19978,802,17,10,16.0,17,13.0,13,0.0,70,,59.0,11.0,11,2008-11-02 17:00:00 -19979,802,2,2,7.0,18,12.0,12,0.0,70,,35.0,12.0,11,2008-11-02 17:00:00 -19980,802,1,1,3.0,8,10.0,10,0.0,70,,41.0,10.0,11,2008-11-02 17:00:00 -19981,802,16,8,10.0,12,9.0,9,0.0,71,5731101.0,40.0,14.0,1,2008-11-02 17:00:00 -19982,802,21,10,17.0,15,15.0,15,0.0,70,,35.0,16.0,11,2008-11-02 17:00:00 -19983,803,0,0,1.0,18,,20,0.0,58,,39.0,13.0,2,2009-03-29 06:00:00 -19984,803,4,0,2.0,12,,19,0.0,0,,,,4,2009-03-29 06:00:00 -19985,803,5,2,17.0,11,,18,0.0,17,,6.0,18.0,3,2009-03-29 06:00:00 -19986,803,11,3,8.0,14,,17,0.0,24,,17.0,19.0,20,2009-03-29 06:00:00 -19987,803,12,5,3.0,6,,16,0.0,45,,30.0,15.0,22,2009-03-29 06:00:00 -19988,803,7,5,4.0,7,15.0,15,0.0,55,,35.0,7.0,24,2009-03-29 06:00:00 -19989,803,8,1,5.0,4,14.0,14,0.0,55,,36.0,2.0,4,2009-03-29 06:00:00 -19990,803,19,8,15.0,3,13.0,13,0.0,56,,8.0,4.0,4,2009-03-29 06:00:00 -19991,803,16,8,14.0,8,12.0,12,0.0,57,,38.0,8.0,11,2009-03-29 06:00:00 -19992,803,1,1,6.0,9,10.0,10,0.0,58,5662869.0,48.0,5.0,1,2009-03-29 06:00:00 -19993,803,20,9,21.0,15,11.0,11,0.0,58,5663158.0,51.0,12.0,1,2009-03-29 06:00:00 -19994,803,21,22,23.0,2,2.0,2,8.0,58,5656591.0,43.0,14.0,1,2009-03-29 06:00:00 -19995,803,14,6,9.0,20,3.0,3,6.0,58,5657388.0,50.0,10.0,1,2009-03-29 06:00:00 -19996,803,9,6,10.0,19,4.0,4,5.0,58,5660219.0,53.0,6.0,1,2009-03-29 06:00:00 -19997,803,17,22,22.0,1,1.0,1,10.0,58,5655784.0,17.0,3.0,1,2009-03-29 06:00:00 -19998,803,2,2,16.0,5,6.0,6,3.0,58,5661506.0,48.0,1.0,1,2009-03-29 06:00:00 -19999,803,66,4,12.0,13,7.0,7,2.0,58,5661788.0,34.0,16.0,1,2009-03-29 06:00:00 -20000,803,6,4,11.0,17,8.0,8,1.0,58,5662082.0,50.0,17.0,1,2009-03-29 06:00:00 -20001,803,3,3,7.0,10,5.0,5,4.0,58,5660663.0,53.0,9.0,1,2009-03-29 06:00:00 -20002,803,15,9,20.0,16,9.0,9,0.0,58,5662119.0,43.0,11.0,1,2009-03-29 06:00:00 -20003,804,66,4,12.0,20,16.0,16,0.0,30,,16.0,8.0,20,2009-04-05 09:00:00 -20004,804,15,9,20.0,19,17.0,17,0.0,30,,17.0,18.0,11,2009-04-05 09:00:00 -20005,804,20,9,21.0,18,18.0,18,0.0,29,,16.0,17.0,20,2009-04-05 09:00:00 -20006,804,8,1,5.0,6,,19,0.0,1,,,,5,2009-04-05 09:00:00 -20007,804,4,0,2.0,14,,20,0.0,0,,,,20,2009-04-05 09:00:00 -20008,804,7,5,4.0,7,14.0,14,0.0,31,,17.0,7.0,11,2009-04-05 09:00:00 -20009,804,11,3,8.0,17,13.0,13,0.0,31,,18.0,14.0,11,2009-04-05 09:00:00 -20010,804,17,22,22.0,1,1.0,1,5.0,31,4252092.0,18.0,1.0,1,2009-04-05 09:00:00 -20011,804,19,8,15.0,13,15.0,15,0.0,30,,10.0,6.0,20,2009-04-05 09:00:00 -20012,804,5,2,17.0,11,12.0,12,0.0,31,,17.0,15.0,11,2009-04-05 09:00:00 -20013,804,6,4,11.0,15,10.0,10,0.0,31,4354256.0,17.0,12.0,1,2009-04-05 09:00:00 -20014,804,12,5,3.0,16,9.0,9,0.0,31,4329024.0,17.0,13.0,1,2009-04-05 09:00:00 -20015,804,2,2,16.0,4,8.0,8,0.5,31,4323668.0,13.0,4.0,1,2009-04-05 09:00:00 -20016,804,3,3,7.0,9,11.0,11,0.0,31,,17.0,9.0,11,2009-04-05 09:00:00 -20017,804,16,8,14.0,5,6.0,6,1.5,31,4304425.0,14.0,5.0,1,2009-04-05 09:00:00 -20018,804,21,22,23.0,8,5.0,5,2.0,31,4299452.0,17.0,2.0,1,2009-04-05 09:00:00 -20019,804,14,6,9.0,2,4.0,4,2.5,31,4298265.0,12.0,3.0,1,2009-04-05 09:00:00 -20020,804,9,6,10.0,3,3.0,3,3.0,31,4275605.0,18.0,16.0,1,2009-04-05 09:00:00 -20021,804,1,1,6.0,10,2.0,2,4.0,31,4274814.0,17.0,10.0,1,2009-04-05 09:00:00 -20022,804,0,0,1.0,12,7.0,7,1.0,31,4312825.0,17.0,11.0,1,2009-04-05 09:00:00 -20023,805,8,1,5.0,17,13.0,13,0.0,56,7170338.0,44.0,14.0,1,2009-04-19 07:00:00 -20024,805,14,6,9.0,6,,20,0.0,18,,14.0,20.0,4,2009-04-19 07:00:00 -20025,805,12,5,3.0,13,,19,0.0,20,,16.0,19.0,40,2009-04-19 07:00:00 -20026,805,5,2,17.0,14,,18,0.0,43,,38.0,17.0,31,2009-04-19 07:00:00 -20027,805,15,9,20.0,18,17.0,17,0.0,50,,41.0,13.0,20,2009-04-19 07:00:00 -20028,805,11,3,8.0,16,16.0,16,0.0,54,,42.0,16.0,12,2009-04-19 07:00:00 -20029,805,2,2,16.0,7,15.0,15,0.0,55,,55.0,8.0,11,2009-04-19 07:00:00 -20030,805,20,9,21.0,20,14.0,14,0.0,55,,37.0,18.0,11,2009-04-19 07:00:00 -20031,805,1,1,6.0,11,12.0,12,0.0,56,7159319.0,40.0,7.0,1,2009-04-19 07:00:00 -20032,805,7,5,4.0,8,10.0,10,0.0,56,7155235.0,38.0,15.0,1,2009-04-19 07:00:00 -20033,805,16,8,14.0,3,2.0,2,8.0,56,7074455.0,42.0,4.0,1,2009-04-19 07:00:00 -20034,805,3,3,7.0,2,9.0,9,0.0,56,7147794.0,38.0,9.0,1,2009-04-19 07:00:00 -20035,805,66,4,12.0,10,8.0,8,1.0,56,7139924.0,42.0,11.0,1,2009-04-19 07:00:00 -20036,805,9,6,10.0,19,7.0,7,2.0,56,7137961.0,42.0,3.0,1,2009-04-19 07:00:00 -20037,805,0,0,1.0,9,6.0,6,3.0,56,7135351.0,39.0,12.0,1,2009-04-19 07:00:00 -20038,805,4,0,2.0,12,5.0,5,4.0,56,7128587.0,41.0,10.0,1,2009-04-19 07:00:00 -20039,805,21,22,23.0,4,4.0,4,5.0,56,7127189.0,42.0,1.0,1,2009-04-19 07:00:00 -20040,805,17,22,22.0,5,3.0,3,6.0,56,7108460.0,44.0,6.0,1,2009-04-19 07:00:00 -20041,805,6,4,11.0,15,11.0,11,0.0,56,7157641.0,43.0,5.0,1,2009-04-19 07:00:00 -20042,805,19,8,15.0,1,1.0,1,10.0,56,7063485.0,42.0,2.0,1,2009-04-19 07:00:00 -20043,806,12,5,3.0,8,14.0,14,0.0,56,,41.0,7.0,11,2009-04-26 12:00:00 -20044,806,20,9,21.0,17,15.0,15,0.0,56,,9.0,19.0,11,2009-04-26 12:00:00 -20045,806,15,9,20.0,19,16.0,16,0.0,56,,28.0,18.0,11,2009-04-26 12:00:00 -20046,806,6,4,11.0,20,13.0,13,0.0,57,5586987.0,30.0,9.0,1,2009-04-26 12:00:00 -20047,806,8,1,5.0,13,18.0,18,0.0,56,,50.0,13.0,11,2009-04-26 12:00:00 -20048,806,1,1,6.0,14,19.0,19,0.0,56,,52.0,16.0,11,2009-04-26 12:00:00 -20049,806,66,4,12.0,16,17.0,17,0.0,56,,38.0,20.0,11,2009-04-26 12:00:00 -20050,806,4,0,2.0,11,12.0,12,0.0,57,5586006.0,54.0,12.0,1,2009-04-26 12:00:00 -20051,806,5,2,17.0,12,,20,0.0,48,,39.0,17.0,51,2009-04-26 12:00:00 -20052,806,11,3,8.0,15,10.0,10,0.0,57,5573331.0,37.0,10.0,1,2009-04-26 12:00:00 -20053,806,16,8,14.0,18,11.0,11,0.0,57,5575823.0,50.0,8.0,1,2009-04-26 12:00:00 -20054,806,19,8,15.0,3,2.0,2,8.0,57,5515369.0,16.0,4.0,1,2009-04-26 12:00:00 -20055,806,14,6,9.0,1,3.0,3,6.0,57,5517352.0,10.0,1.0,1,2009-04-26 12:00:00 -20056,806,0,0,1.0,5,4.0,4,5.0,57,5530278.0,13.0,6.0,1,2009-04-26 12:00:00 -20057,806,17,22,22.0,4,1.0,1,10.0,57,5508182.0,11.0,3.0,1,2009-04-26 12:00:00 -20058,806,7,5,4.0,10,6.0,6,3.0,57,5550239.0,42.0,11.0,1,2009-04-26 12:00:00 -20059,806,9,6,10.0,2,7.0,7,2.0,57,5551062.0,6.0,2.0,1,2009-04-26 12:00:00 -20060,806,3,3,7.0,7,8.0,8,1.0,57,5560957.0,29.0,14.0,1,2009-04-26 12:00:00 -20061,806,2,2,16.0,9,9.0,9,0.0,57,5566380.0,37.0,15.0,1,2009-04-26 12:00:00 -20062,806,21,22,23.0,6,5.0,5,4.0,57,5545961.0,25.0,5.0,1,2009-04-26 12:00:00 -20063,807,5,2,17.0,11,13.0,13,0.0,65,,38.0,13.0,11,2009-05-10 12:00:00 -20064,807,15,9,20.0,19,,20,0.0,0,,,,4,2009-05-10 12:00:00 -20065,807,6,4,11.0,17,,19,0.0,0,,,,4,2009-05-10 12:00:00 -20066,807,66,4,12.0,15,,18,0.0,0,,,,4,2009-05-10 12:00:00 -20067,807,14,6,9.0,7,,17,0.0,0,,,,4,2009-05-10 12:00:00 -20068,807,4,0,2.0,18,,16,0.0,7,,6.0,16.0,6,2009-05-10 12:00:00 -20069,807,7,5,4.0,16,,15,0.0,17,,16.0,15.0,9,2009-05-10 12:00:00 -20070,807,20,9,21.0,20,14.0,14,0.0,65,,63.0,8.0,11,2009-05-10 12:00:00 -20071,807,11,3,8.0,12,12.0,12,0.0,65,,41.0,14.0,11,2009-05-10 12:00:00 -20072,807,8,1,5.0,10,11.0,11,0.0,65,,26.0,11.0,11,2009-05-10 12:00:00 -20073,807,9,6,10.0,6,10.0,10,0.0,65,,44.0,12.0,11,2009-05-10 12:00:00 -20074,807,21,22,23.0,3,2.0,2,8.0,66,5852258.0,28.0,1.0,1,2009-05-10 12:00:00 -20075,807,16,8,14.0,5,3.0,3,6.0,66,5853126.0,18.0,5.0,1,2009-05-10 12:00:00 -20076,807,19,8,15.0,2,4.0,4,5.0,66,5858143.0,41.0,4.0,1,2009-05-10 12:00:00 -20077,807,3,3,7.0,8,5.0,5,4.0,66,5882368.0,14.0,6.0,1,2009-05-10 12:00:00 -20078,807,17,22,22.0,1,1.0,1,10.0,66,5839202.0,17.0,2.0,1,2009-05-10 12:00:00 -20079,807,1,1,6.0,13,7.0,7,2.0,66,5891514.0,29.0,10.0,1,2009-05-10 12:00:00 -20080,807,2,2,16.0,9,8.0,8,1.0,66,5904413.0,24.0,7.0,1,2009-05-10 12:00:00 -20081,807,0,0,1.0,14,9.0,9,0.0,65,,29.0,9.0,11,2009-05-10 12:00:00 -20082,807,12,5,3.0,4,6.0,6,3.0,66,5890029.0,14.0,3.0,1,2009-05-10 12:00:00 -20083,808,14,6,9.0,18,13.0,13,0.0,77,,57.0,11.0,11,2009-05-24 12:00:00 -20084,808,66,4,12.0,11,,20,0.0,10,,7.0,20.0,4,2009-05-24 12:00:00 -20085,808,11,3,8.0,12,,19,0.0,10,,7.0,19.0,4,2009-05-24 12:00:00 -20086,808,19,8,15.0,4,,18,0.0,15,,15.0,18.0,3,2009-05-24 12:00:00 -20087,808,8,1,5.0,17,,17,0.0,28,,25.0,17.0,23,2009-05-24 12:00:00 -20088,808,4,0,2.0,7,,16,0.0,51,,48.0,6.0,3,2009-05-24 12:00:00 -20089,808,5,2,17.0,10,15.0,15,0.0,76,,73.0,10.0,3,2009-05-24 12:00:00 -20090,808,15,9,20.0,15,14.0,14,0.0,77,,66.0,14.0,11,2009-05-24 12:00:00 -20091,808,0,0,1.0,19,12.0,12,0.0,77,,65.0,8.0,11,2009-05-24 12:00:00 -20092,808,17,22,22.0,1,1.0,1,10.0,78,6044282.0,49.0,2.0,1,2009-05-24 12:00:00 -20093,808,9,6,10.0,20,10.0,10,0.0,77,,72.0,12.0,11,2009-05-24 12:00:00 -20094,808,1,1,6.0,16,11.0,11,0.0,77,,49.0,15.0,11,2009-05-24 12:00:00 -20095,808,7,5,4.0,2,3.0,3,6.0,78,6057724.0,47.0,5.0,1,2009-05-24 12:00:00 -20096,808,12,5,3.0,5,4.0,4,5.0,78,6059392.0,50.0,1.0,1,2009-05-24 12:00:00 -20097,808,16,8,14.0,8,5.0,5,4.0,78,6060012.0,45.0,3.0,1,2009-05-24 12:00:00 -20098,808,21,22,23.0,3,2.0,2,8.0,78,6051948.0,46.0,7.0,1,2009-05-24 12:00:00 -20099,808,3,3,7.0,9,7.0,7,2.0,78,6082121.0,64.0,4.0,1,2009-05-24 12:00:00 -20100,808,6,4,11.0,14,8.0,8,1.0,78,6107424.0,47.0,13.0,1,2009-05-24 12:00:00 -20101,808,20,9,21.0,13,9.0,9,0.0,78,6109322.0,74.0,16.0,1,2009-05-24 12:00:00 -20102,808,2,2,16.0,6,6.0,6,3.0,78,6077868.0,48.0,9.0,1,2009-05-24 12:00:00 -20103,809,20,9,21.0,19,,20,0.0,4,,3.0,20.0,23,2009-06-07 12:00:00 -20104,809,21,22,23.0,3,,19,0.0,47,,37.0,14.0,6,2009-06-07 12:00:00 -20105,809,6,4,11.0,20,18.0,18,0.0,57,,53.0,17.0,11,2009-06-07 12:00:00 -20106,809,15,9,20.0,15,17.0,17,0.0,57,,55.0,19.0,11,2009-06-07 12:00:00 -20107,809,11,3,8.0,17,16.0,16,0.0,57,,45.0,12.0,11,2009-06-07 12:00:00 -20108,809,66,4,12.0,18,15.0,15,0.0,57,,57.0,16.0,11,2009-06-07 12:00:00 -20109,809,4,0,2.0,14,14.0,14,0.0,57,,41.0,18.0,11,2009-06-07 12:00:00 -20110,809,5,2,17.0,12,12.0,12,0.0,58,5251224.0,58.0,6.0,1,2009-06-07 12:00:00 -20111,809,0,0,1.0,16,13.0,13,0.0,58,5265302.0,53.0,15.0,1,2009-06-07 12:00:00 -20112,809,3,3,7.0,8,10.0,10,0.0,58,5247268.0,57.0,13.0,1,2009-06-07 12:00:00 -20113,809,1,1,6.0,11,11.0,11,0.0,58,5249175.0,43.0,10.0,1,2009-06-07 12:00:00 -20114,809,16,8,14.0,4,2.0,2,8.0,58,5191562.0,42.0,3.0,1,2009-06-07 12:00:00 -20115,809,19,8,15.0,1,3.0,3,6.0,58,5192309.0,51.0,2.0,1,2009-06-07 12:00:00 -20116,809,14,6,9.0,5,4.0,4,5.0,58,5212691.0,40.0,4.0,1,2009-06-07 12:00:00 -20117,809,17,22,22.0,2,1.0,1,10.0,58,5184848.0,40.0,1.0,1,2009-06-07 12:00:00 -20118,809,12,5,3.0,7,6.0,6,3.0,58,5224844.0,41.0,9.0,1,2009-06-07 12:00:00 -20119,809,8,1,5.0,10,7.0,7,2.0,58,5231095.0,58.0,7.0,1,2009-06-07 12:00:00 -20120,809,9,6,10.0,13,8.0,8,1.0,58,5231807.0,56.0,5.0,1,2009-06-07 12:00:00 -20121,809,7,5,4.0,6,9.0,9,0.0,58,5235094.0,58.0,8.0,1,2009-06-07 12:00:00 -20122,809,2,2,16.0,9,5.0,5,4.0,58,5216387.0,36.0,11.0,1,2009-06-07 12:00:00 -20123,810,8,1,5.0,12,13.0,13,0.0,59,,41.0,14.0,11,2009-06-21 12:00:00 -20124,810,4,0,2.0,13,,20,0.0,36,,32.0,15.0,4,2009-06-21 12:00:00 -20125,810,6,4,11.0,17,,19,0.0,37,,26.0,16.0,4,2009-06-21 12:00:00 -20126,810,66,4,12.0,19,18.0,18,0.0,59,,24.0,19.0,11,2009-06-21 12:00:00 -20127,810,15,9,20.0,20,17.0,17,0.0,59,,50.0,20.0,11,2009-06-21 12:00:00 -20128,810,0,0,1.0,18,16.0,16,0.0,59,,24.0,18.0,11,2009-06-21 12:00:00 -20129,810,1,1,6.0,15,15.0,15,0.0,59,,59.0,13.0,11,2009-06-21 12:00:00 -20130,810,3,3,7.0,10,14.0,14,0.0,59,,36.0,12.0,11,2009-06-21 12:00:00 -20131,810,11,3,8.0,14,12.0,12,0.0,59,,25.0,17.0,11,2009-06-21 12:00:00 -20132,810,5,2,17.0,5,11.0,11,0.0,60,5043351.0,14.0,11.0,1,2009-06-21 12:00:00 -20133,810,20,9,21.0,16,10.0,10,0.0,60,5040850.0,20.0,10.0,1,2009-06-21 12:00:00 -20134,810,19,8,15.0,1,1.0,1,10.0,60,4969328.0,16.0,1.0,1,2009-06-21 12:00:00 -20135,810,21,22,23.0,2,3.0,3,6.0,60,5010503.0,18.0,5.0,1,2009-06-21 12:00:00 -20136,810,12,5,3.0,11,4.0,4,5.0,60,5014371.0,22.0,6.0,1,2009-06-21 12:00:00 -20137,810,2,2,16.0,7,5.0,5,4.0,60,5015243.0,17.0,3.0,1,2009-06-21 12:00:00 -20138,810,16,8,14.0,3,2.0,2,8.0,60,4984516.0,57.0,2.0,1,2009-06-21 12:00:00 -20139,810,14,6,9.0,4,7.0,7,2.0,60,5037635.0,17.0,9.0,1,2009-06-21 12:00:00 -20140,810,7,5,4.0,9,8.0,8,1.0,60,5038950.0,14.0,7.0,1,2009-06-21 12:00:00 -20141,810,9,6,10.0,8,9.0,9,0.0,60,5039151.0,51.0,8.0,1,2009-06-21 12:00:00 -20142,810,17,22,22.0,6,6.0,6,3.0,60,5015613.0,54.0,4.0,1,2009-06-21 12:00:00 -20143,811,11,3,8.0,10,13.0,13,0.0,60,5871638.0,46.0,12.0,1,2009-07-12 12:00:00 -20144,811,6,4,11.0,19,,20,0.0,18,,10.0,20.0,9,2009-07-12 12:00:00 -20145,811,7,5,4.0,9,,19,0.0,34,,4.0,18.0,5,2009-07-12 12:00:00 -20146,811,0,0,1.0,5,18.0,18,0.0,59,,46.0,15.0,11,2009-07-12 12:00:00 -20147,811,14,6,9.0,14,17.0,17,0.0,60,5894280.0,52.0,2.0,1,2009-07-12 12:00:00 -20148,811,15,9,20.0,7,15.0,15,0.0,60,5875251.0,43.0,14.0,1,2009-07-12 12:00:00 -20149,811,8,1,5.0,16,14.0,14,0.0,60,5872865.0,47.0,9.0,1,2009-07-12 12:00:00 -20150,811,5,2,17.0,13,12.0,12,0.0,60,5866186.0,49.0,5.0,1,2009-07-12 12:00:00 -20151,811,66,4,12.0,17,16.0,16,0.0,60,5893535.0,24.0,19.0,1,2009-07-12 12:00:00 -20152,811,1,1,6.0,11,10.0,10,0.0,60,5865235.0,42.0,10.0,1,2009-07-12 12:00:00 -20153,811,16,8,14.0,1,1.0,1,10.0,60,5803310.0,37.0,3.0,1,2009-07-12 12:00:00 -20154,811,19,8,15.0,4,2.0,2,8.0,60,5812562.0,42.0,4.0,1,2009-07-12 12:00:00 -20155,811,12,5,3.0,8,3.0,3,6.0,60,5819216.0,53.0,8.0,1,2009-07-12 12:00:00 -20156,811,2,2,16.0,15,4.0,4,5.0,60,5824409.0,50.0,7.0,1,2009-07-12 12:00:00 -20157,811,20,9,21.0,18,11.0,11,0.0,60,5865637.0,54.0,13.0,1,2009-07-12 12:00:00 -20158,811,21,22,23.0,2,6.0,6,3.0,60,5827778.0,54.0,11.0,1,2009-07-12 12:00:00 -20159,811,3,3,7.0,12,7.0,7,2.0,60,5828198.0,49.0,1.0,1,2009-07-12 12:00:00 -20160,811,4,0,2.0,6,8.0,8,1.0,60,5862002.0,59.0,17.0,1,2009-07-12 12:00:00 -20161,811,9,6,10.0,20,9.0,9,0.0,60,5864767.0,40.0,16.0,1,2009-07-12 12:00:00 -20162,811,17,22,22.0,3,5.0,5,4.0,60,5826919.0,53.0,6.0,1,2009-07-12 12:00:00 -20163,812,8,1,5.0,18,13.0,13,0.0,70,5977922.0,65.0,12.0,1,2009-07-26 12:00:00 -20164,812,12,5,3.0,0,,20,0.0,0,,,,54,2009-07-26 12:00:00 -20165,812,15,9,20.0,17,,19,0.0,1,,,,25,2009-07-26 12:00:00 -20166,812,3,3,7.0,1,,18,0.0,15,,4.0,18.0,36,2009-07-26 12:00:00 -20167,812,19,8,15.0,2,,17,0.0,29,,18.0,17.0,22,2009-07-26 12:00:00 -20168,812,66,4,12.0,10,16.0,16,0.0,69,,69.0,7.0,11,2009-07-26 12:00:00 -20169,812,152,4,11.0,19,15.0,15,0.0,69,,69.0,16.0,11,2009-07-26 12:00:00 -20170,812,20,9,21.0,16,14.0,14,0.0,69,,40.0,10.0,11,2009-07-26 12:00:00 -20171,812,11,3,8.0,14,12.0,12,0.0,70,5975388.0,65.0,15.0,1,2009-07-26 12:00:00 -20172,812,1,1,6.0,15,11.0,11,0.0,70,5974488.0,65.0,14.0,1,2009-07-26 12:00:00 -20173,812,21,22,23.0,12,10.0,10,0.0,70,5973132.0,55.0,9.0,1,2009-07-26 12:00:00 -20174,812,7,5,4.0,7,2.0,2,8.0,70,5915405.0,70.0,2.0,1,2009-07-26 12:00:00 -20175,812,16,8,14.0,3,3.0,3,6.0,70,5920762.0,65.0,1.0,1,2009-07-26 12:00:00 -20176,812,2,2,16.0,5,4.0,4,5.0,70,5930843.0,65.0,3.0,1,2009-07-26 12:00:00 -20177,812,4,0,2.0,6,5.0,5,4.0,70,5938268.0,63.0,8.0,1,2009-07-26 12:00:00 -20178,812,0,0,1.0,4,1.0,1,10.0,70,5903876.0,16.0,4.0,1,2009-07-26 12:00:00 -20179,812,17,22,22.0,8,7.0,7,2.0,70,5958964.0,57.0,6.0,1,2009-07-26 12:00:00 -20180,812,14,6,9.0,11,8.0,8,1.0,70,5972048.0,65.0,13.0,1,2009-07-26 12:00:00 -20181,812,5,2,17.0,9,9.0,9,0.0,70,5972650.0,55.0,11.0,1,2009-07-26 12:00:00 -20182,812,9,6,10.0,13,6.0,6,3.0,70,5939113.0,63.0,5.0,1,2009-07-26 12:00:00 -20183,813,14,6,9.0,18,13.0,13,0.0,57,5815816.0,52.0,15.0,1,2009-08-23 12:00:00 -20184,813,19,8,15.0,4,,20,0.0,23,,13.0,16.0,5,2009-08-23 12:00:00 -20185,813,66,4,12.0,15,,19,0.0,41,,37.0,20.0,23,2009-08-23 12:00:00 -20186,813,5,2,17.0,17,18.0,18,0.0,54,,53.0,14.0,13,2009-08-23 12:00:00 -20187,813,68,5,3.0,20,17.0,17,0.0,56,,52.0,18.0,11,2009-08-23 12:00:00 -20188,813,152,4,11.0,19,16.0,16,0.0,56,,29.0,19.0,11,2009-08-23 12:00:00 -20189,813,153,3,8.0,14,15.0,15,0.0,57,5843063.0,41.0,9.0,1,2009-08-23 12:00:00 -20190,813,9,6,10.0,13,14.0,14,0.0,57,5837808.0,55.0,1.0,1,2009-08-23 12:00:00 -20191,813,20,9,21.0,16,12.0,12,0.0,57,5814903.0,53.0,17.0,1,2009-08-23 12:00:00 -20192,813,21,22,23.0,3,1.0,1,10.0,57,5751289.0,39.0,3.0,1,2009-08-23 12:00:00 -20193,813,15,9,20.0,12,10.0,10,0.0,57,5799224.0,36.0,12.0,1,2009-08-23 12:00:00 -20194,813,16,8,14.0,9,9.0,9,0.0,57,5796199.0,50.0,11.0,1,2009-08-23 12:00:00 -20195,813,8,1,5.0,10,8.0,8,1.0,57,5787956.0,55.0,8.0,1,2009-08-23 12:00:00 -20196,813,17,22,22.0,5,7.0,7,2.0,57,5786202.0,46.0,2.0,1,2009-08-23 12:00:00 -20197,813,3,3,7.0,8,6.0,6,3.0,57,5779033.0,46.0,10.0,1,2009-08-23 12:00:00 -20198,813,2,2,16.0,7,5.0,5,4.0,57,5772159.0,52.0,6.0,1,2009-08-23 12:00:00 -20199,813,4,0,2.0,2,4.0,4,5.0,57,5771321.0,56.0,7.0,1,2009-08-23 12:00:00 -20200,813,7,5,4.0,6,3.0,3,6.0,57,5767283.0,39.0,5.0,1,2009-08-23 12:00:00 -20201,813,0,0,1.0,1,2.0,2,8.0,57,5753647.0,57.0,4.0,1,2009-08-23 12:00:00 -20202,813,1,1,6.0,11,11.0,11,0.0,57,5800111.0,53.0,13.0,1,2009-08-23 12:00:00 -20203,814,68,5,3.0,20,14.0,14,0.0,44,5133172.0,41.0,15.0,1,2009-08-30 12:00:00 -20204,814,3,3,7.0,13,,15,0.0,26,,23.0,14.0,31,2009-08-30 12:00:00 -20205,814,5,2,17.0,18,13.0,13,0.0,44,5085236.0,42.0,11.0,1,2009-08-30 12:00:00 -20206,814,152,4,11.0,17,,20,0.0,0,,,,4,2009-08-30 12:00:00 -20207,814,17,22,22.0,14,,17,0.0,0,,,,4,2009-08-30 12:00:00 -20208,814,153,3,8.0,19,,18,0.0,0,,,,4,2009-08-30 12:00:00 -20209,814,0,0,1.0,12,,19,0.0,0,,,,4,2009-08-30 12:00:00 -20210,814,14,6,9.0,2,,16,0.0,21,,16.0,16.0,23,2009-08-30 12:00:00 -20211,814,66,4,12.0,16,12.0,12,0.0,44,5077101.0,42.0,7.0,1,2009-08-30 12:00:00 -20212,814,21,22,23.0,4,7.0,7,2.0,44,5066456.0,37.0,12.0,1,2009-08-30 12:00:00 -20213,814,9,6,10.0,7,10.0,10,0.0,44,5072485.0,40.0,5.0,1,2009-08-30 12:00:00 -20214,814,16,8,14.0,9,9.0,9,0.0,44,5067954.0,39.0,9.0,1,2009-08-30 12:00:00 -20215,814,2,2,16.0,10,8.0,8,1.0,44,5067203.0,41.0,8.0,1,2009-08-30 12:00:00 -20216,814,4,0,2.0,15,6.0,6,3.0,44,5063758.0,24.0,13.0,1,2009-08-30 12:00:00 -20217,814,1,1,6.0,3,5.0,5,4.0,44,5042271.0,35.0,2.0,1,2009-08-30 12:00:00 -20218,814,8,1,5.0,5,4.0,4,5.0,44,5040961.0,41.0,3.0,1,2009-08-30 12:00:00 -20219,814,19,8,15.0,8,3.0,3,6.0,44,5034870.0,38.0,1.0,1,2009-08-30 12:00:00 -20220,814,20,9,21.0,1,2.0,2,8.0,44,5031934.0,43.0,6.0,1,2009-08-30 12:00:00 -20221,814,15,9,20.0,11,11.0,11,0.0,44,5073631.0,42.0,10.0,1,2009-08-30 12:00:00 -20222,814,7,5,4.0,6,1.0,1,10.0,44,5030995.0,42.0,4.0,1,2009-08-30 12:00:00 -20223,815,14,6,9.0,11,14.0,14,0.0,52,,49.0,13.0,11,2009-09-13 12:00:00 -20224,815,153,3,8.0,12,15.0,15,0.0,52,,51.0,12.0,11,2009-09-13 12:00:00 -20225,815,2,2,16.0,18,16.0,16,0.0,51,,50.0,15.0,12,2009-09-13 12:00:00 -20226,815,16,8,14.0,10,,20,0.0,0,,,,4,2009-09-13 12:00:00 -20227,815,152,4,11.0,20,,18,0.0,19,,17.0,19.0,31,2009-09-13 12:00:00 -20228,815,8,1,5.0,13,,19,0.0,15,,12.0,18.0,44,2009-09-13 12:00:00 -20229,815,66,4,12.0,19,13.0,13,0.0,52,,50.0,11.0,11,2009-09-13 12:00:00 -20230,815,23,9,21.0,7,,17,0.0,22,,22.0,17.0,7,2009-09-13 12:00:00 -20231,815,0,0,1.0,1,12.0,12,0.0,52,,52.0,3.0,3,2009-09-13 12:00:00 -20232,815,1,1,6.0,15,7.0,7,2.0,53,4664118.0,30.0,9.0,1,2009-09-13 12:00:00 -20233,815,5,2,17.0,17,10.0,10,0.0,53,4743869.0,51.0,16.0,1,2009-09-13 12:00:00 -20234,815,21,22,23.0,5,1.0,1,10.0,53,4581706.0,48.0,5.0,1,2009-09-13 12:00:00 -20235,815,17,22,22.0,6,2.0,2,8.0,53,4584572.0,46.0,4.0,1,2009-09-13 12:00:00 -20236,815,7,5,4.0,3,3.0,3,6.0,53,4612370.0,36.0,2.0,1,2009-09-13 12:00:00 -20237,815,15,9,20.0,2,4.0,4,5.0,53,4612837.0,36.0,1.0,1,2009-09-13 12:00:00 -20238,815,9,6,10.0,16,11.0,11,0.0,53,4745631.0,50.0,14.0,1,2009-09-13 12:00:00 -20239,815,4,0,2.0,4,6.0,6,3.0,53,4642399.0,51.0,6.0,1,2009-09-13 12:00:00 -20240,815,19,8,15.0,9,8.0,8,1.0,53,4667113.0,50.0,7.0,1,2009-09-13 12:00:00 -20241,815,20,5,3.0,14,9.0,9,0.0,53,4668562.0,28.0,10.0,1,2009-09-13 12:00:00 -20242,815,3,3,7.0,8,5.0,5,4.0,53,4640888.0,50.0,8.0,1,2009-09-13 12:00:00 -20243,816,20,5,3.0,17,13.0,13,0.0,61,7046227.0,49.0,14.0,1,2009-09-27 12:00:00 -20244,816,153,3,8.0,18,,20,0.0,3,,2.0,20.0,23,2009-09-27 12:00:00 -20245,816,1,1,6.0,20,,19,0.0,19,,18.0,17.0,4,2009-09-27 12:00:00 -20246,816,16,8,14.0,4,,17,0.0,45,,35.0,12.0,23,2009-09-27 12:00:00 -20247,816,66,4,12.0,13,,16,0.0,47,,17.0,16.0,6,2009-09-27 12:00:00 -20248,816,152,4,11.0,16,,15,0.0,47,,32.0,18.0,23,2009-09-27 12:00:00 -20249,816,23,9,21.0,19,14.0,14,0.0,61,7059839.0,48.0,15.0,1,2009-09-27 12:00:00 -20250,816,14,6,9.0,14,12.0,12,0.0,61,7039346.0,54.0,9.0,1,2009-09-27 12:00:00 -20251,816,15,9,20.0,15,,18,0.0,23,,15.0,19.0,4,2009-09-27 12:00:00 -20252,816,7,5,4.0,12,10.0,10,0.0,61,7025229.0,54.0,5.0,1,2009-09-27 12:00:00 -20253,816,5,2,17.0,10,9.0,9,0.0,61,7022391.0,45.0,13.0,1,2009-09-27 12:00:00 -20254,816,8,1,5.0,7,8.0,8,1.0,61,7021391.0,44.0,10.0,1,2009-09-27 12:00:00 -20255,816,4,0,2.0,8,7.0,7,2.0,61,7002494.0,36.0,11.0,1,2009-09-27 12:00:00 -20256,816,21,22,23.0,9,6.0,6,3.0,61,6998195.0,50.0,8.0,1,2009-09-27 12:00:00 -20257,816,17,22,22.0,11,5.0,5,4.0,61,6996352.0,54.0,4.0,1,2009-09-27 12:00:00 -20258,816,19,8,15.0,2,4.0,4,5.0,61,6986958.0,10.0,7.0,1,2009-09-27 12:00:00 -20259,816,3,3,7.0,5,3.0,3,6.0,61,6982961.0,53.0,1.0,1,2009-09-27 12:00:00 -20260,816,9,6,10.0,6,2.0,2,8.0,61,6975971.0,34.0,6.0,1,2009-09-27 12:00:00 -20261,816,0,0,1.0,1,1.0,1,10.0,61,6966337.0,36.0,2.0,1,2009-09-27 12:00:00 -20262,816,2,2,16.0,3,11.0,11,0.0,61,7026114.0,9.0,3.0,1,2009-09-27 12:00:00 -20263,817,23,9,21.0,18,14.0,14,0.0,53,5316177.0,36.0,16.0,1,2009-10-04 05:00:00 -20264,817,5,2,17.0,15,15.0,15,0.0,53,5318416.0,26.0,18.0,1,2009-10-04 05:00:00 -20265,817,9,6,10.0,20,,20,0.0,0,,,,73,2009-10-04 05:00:00 -20266,817,152,4,11.0,12,,18,0.0,43,,34.0,15.0,3,2009-10-04 05:00:00 -20267,817,66,4,12.0,13,,19,0.0,11,,5.0,19.0,8,2009-10-04 05:00:00 -20268,817,15,9,20.0,8,13.0,13,0.0,53,5315402.0,36.0,11.0,1,2009-10-04 05:00:00 -20269,817,153,3,8.0,17,16.0,16,0.0,52,,39.0,17.0,11,2009-10-04 05:00:00 -20270,817,20,5,3.0,14,12.0,12,0.0,53,5315039.0,33.0,8.0,1,2009-10-04 05:00:00 -20271,817,16,8,14.0,19,17.0,17,0.0,51,,50.0,1.0,12,2009-10-04 05:00:00 -20272,817,3,3,7.0,16,10.0,10,0.0,53,5313508.0,28.0,14.0,1,2009-10-04 05:00:00 -20273,817,4,0,2.0,11,11.0,11,0.0,53,5314178.0,35.0,12.0,1,2009-10-04 05:00:00 -20274,817,19,8,15.0,1,1.0,1,10.0,53,5300443.0,43.0,2.0,1,2009-10-04 05:00:00 -20275,817,14,6,9.0,2,2.0,2,8.0,53,5305320.0,38.0,4.0,1,2009-10-04 05:00:00 -20276,817,0,0,1.0,3,3.0,3,6.0,53,5306915.0,13.0,6.0,1,2009-10-04 05:00:00 -20277,817,17,22,22.0,10,8.0,8,1.0,53,5311917.0,42.0,5.0,1,2009-10-04 05:00:00 -20278,817,2,2,16.0,7,5.0,5,4.0,53,5309236.0,43.0,9.0,1,2009-10-04 05:00:00 -20279,817,1,1,6.0,4,6.0,6,3.0,53,5309952.0,13.0,10.0,1,2009-10-04 05:00:00 -20280,817,21,22,23.0,6,7.0,7,2.0,53,5311084.0,17.0,13.0,1,2009-10-04 05:00:00 -20281,817,8,1,5.0,9,9.0,9,0.0,53,5312220.0,44.0,7.0,1,2009-10-04 05:00:00 -20282,817,7,5,4.0,5,4.0,4,5.0,53,5308383.0,33.0,3.0,1,2009-10-04 05:00:00 -20283,818,3,3,7.0,10,,20,0.0,0,,,,3,2009-10-18 16:00:00 -20284,818,14,6,9.0,4,,19,0.0,0,,,,3,2009-10-18 16:00:00 -20285,818,15,9,20.0,3,,18,0.0,0,,,,3,2009-10-18 16:00:00 -20286,818,1,1,6.0,18,,17,0.0,21,,19.0,15.0,60,2009-10-18 16:00:00 -20287,818,2,2,16.0,7,,16,0.0,27,,16.0,8.0,6,2009-10-18 16:00:00 -20288,818,5,2,17.0,9,,15,0.0,30,,21.0,17.0,3,2009-10-18 16:00:00 -20289,818,152,4,11.0,12,14.0,14,0.0,70,,59.0,13.0,11,2009-10-18 16:00:00 -20290,818,153,3,8.0,13,13.0,13,0.0,70,,54.0,12.0,11,2009-10-18 16:00:00 -20291,818,23,9,21.0,20,12.0,12,0.0,71,5614469.0,43.0,16.0,1,2009-10-18 16:00:00 -20292,818,154,6,10.0,11,10.0,10,0.0,71,5606405.0,71.0,11.0,1,2009-10-18 16:00:00 -20293,818,4,0,2.0,16,9.0,9,0.0,71,5591580.0,68.0,5.0,1,2009-10-18 16:00:00 -20294,818,21,22,23.0,1,8.0,8,1.0,71,5588535.0,20.0,3.0,1,2009-10-18 16:00:00 -20295,818,7,5,4.0,5,6.0,6,3.0,71,5576421.0,47.0,9.0,1,2009-10-18 16:00:00 -20296,818,17,22,22.0,14,5.0,5,4.0,71,5572086.0,46.0,7.0,1,2009-10-18 16:00:00 -20297,818,19,8,15.0,15,4.0,4,5.0,71,5562733.0,59.0,2.0,1,2009-10-18 16:00:00 -20298,818,0,0,1.0,17,3.0,3,6.0,71,5562025.0,59.0,6.0,1,2009-10-18 16:00:00 -20299,818,8,1,5.0,8,2.0,2,8.0,71,5550707.0,38.0,4.0,1,2009-10-18 16:00:00 -20300,818,16,8,14.0,2,1.0,1,10.0,71,5543081.0,25.0,1.0,1,2009-10-18 16:00:00 -20301,818,20,5,3.0,19,11.0,11,0.0,71,5613746.0,55.0,14.0,1,2009-10-18 16:00:00 -20302,818,66,4,12.0,6,7.0,7,2.0,71,5579072.0,58.0,10.0,1,2009-10-18 16:00:00 -20303,819,152,4,11.0,14,,20,0.0,18,,16.0,20.0,6,2009-11-01 11:00:00 -20304,819,0,0,1.0,1,,19,0.0,20,,16.0,3.0,23,2009-11-01 11:00:00 -20305,819,19,8,15.0,2,1.0,1,10.0,55,5643414.0,54.0,1.0,1,2009-11-01 11:00:00 -20306,819,153,3,8.0,19,18.0,18,0.0,54,,47.0,19.0,11,2009-11-01 11:00:00 -20307,819,15,9,20.0,17,17.0,17,0.0,54,,34.0,13.0,11,2009-11-01 11:00:00 -20308,819,20,5,3.0,20,16.0,16,0.0,54,,54.0,16.0,11,2009-11-01 11:00:00 -20309,819,23,9,21.0,16,15.0,15,0.0,55,5737864.0,54.0,17.0,1,2009-11-01 11:00:00 -20310,819,5,2,17.0,13,13.0,13,0.0,55,5703253.0,54.0,9.0,1,2009-11-01 11:00:00 -20311,819,7,5,4.0,11,12.0,12,0.0,55,5697731.0,54.0,12.0,1,2009-11-01 11:00:00 -20312,819,4,0,2.0,18,11.0,11,0.0,55,5696212.0,53.0,18.0,1,2009-11-01 11:00:00 -20313,819,8,1,5.0,7,10.0,10,0.0,55,5691594.0,54.0,14.0,1,2009-11-01 11:00:00 -20314,819,3,3,7.0,15,14.0,14,0.0,55,5713101.0,54.0,10.0,1,2009-11-01 11:00:00 -20315,819,66,4,12.0,10,8.0,8,1.0,55,5684708.0,55.0,2.0,1,2009-11-01 11:00:00 -20316,819,14,6,9.0,6,7.0,7,2.0,55,5677780.0,49.0,8.0,1,2009-11-01 11:00:00 -20317,819,154,6,10.0,12,6.0,6,3.0,55,5671757.0,55.0,11.0,1,2009-11-01 11:00:00 -20318,819,1,1,6.0,8,5.0,5,4.0,55,5669667.0,54.0,7.0,1,2009-11-01 11:00:00 -20319,819,21,22,23.0,4,4.0,4,5.0,55,5666149.0,54.0,4.0,1,2009-11-01 11:00:00 -20320,819,17,22,22.0,5,3.0,3,6.0,55,5661881.0,49.0,6.0,1,2009-11-01 11:00:00 -20321,819,16,8,14.0,3,2.0,2,8.0,55,5661271.0,14.0,5.0,1,2009-11-01 11:00:00 -20322,819,2,2,16.0,9,9.0,9,0.0,55,5689355.0,49.0,15.0,1,2009-11-01 11:00:00 diff --git a/scripts/f1_data/standings.csv b/scripts/f1_data/standings.csv deleted file mode 100644 index 6f3664d9..00000000 --- a/scripts/f1_data/standings.csv +++ /dev/null @@ -1,28116 +0,0 @@ -driverStandingsId,raceId,driverId,points,position,wins,date -0,0,789,0.0,20,0,1950-05-13 -1,0,640,0.0,18,0,1950-05-13 -2,0,589,0.0,19,0,1950-05-13 -3,0,669,0.0,15,0,1950-05-13 -4,0,661,0.0,22,0,1950-05-13 -5,0,790,0.0,23,0,1950-05-13 -6,0,788,0.0,10,0,1950-05-13 -7,0,786,6.0,2,0,1950-05-13 -8,0,686,4.0,3,0,1950-05-13 -9,0,666,0.0,21,0,1950-05-13 -10,0,776,0.0,14,0,1950-05-13 -11,0,579,0.0,13,0,1950-05-13 -12,0,660,0.0,12,0,1950-05-13 -13,0,642,9.0,1,1,1950-05-13 -14,0,778,0.0,11,0,1950-05-13 -15,0,784,0.0,9,0,1950-05-13 -16,0,741,0.0,8,0,1950-05-13 -17,0,787,0.0,7,0,1950-05-13 -18,0,619,0.0,6,0,1950-05-13 -19,0,627,2.0,5,0,1950-05-13 -20,0,704,3.0,4,0,1950-05-13 -21,0,785,0.0,17,0,1950-05-13 -22,0,747,0.0,16,0,1950-05-13 -23,1,633,0.0,18,0,1950-05-21 -24,1,498,0.0,19,0,1950-05-21 -25,1,626,0.0,21,0,1950-05-21 -26,1,426,0.0,25,0,1950-05-21 -27,1,762,0.0,26,0,1950-05-21 -28,1,647,6.0,4,0,1950-05-21 -29,1,793,3.0,8,0,1950-05-21 -30,1,640,0.0,22,0,1950-05-21 -31,1,785,0.0,24,0,1950-05-21 -32,1,747,0.0,23,0,1950-05-21 -33,1,776,0.0,20,0,1950-05-21 -34,1,579,9.0,2,1,1950-05-21 -35,1,660,0.0,12,0,1950-05-21 -36,1,778,0.0,17,0,1950-05-21 -37,1,784,0.0,15,0,1950-05-21 -38,1,741,0.0,14,0,1950-05-21 -39,1,787,0.0,13,0,1950-05-21 -40,1,627,2.0,9,0,1950-05-21 -41,1,704,3.0,7,0,1950-05-21 -42,1,786,6.0,3,0,1950-05-21 -43,1,642,9.0,1,1,1950-05-21 -44,1,661,0.0,30,0,1950-05-21 -45,1,501,0.0,28,0,1950-05-21 -46,1,687,0.0,31,0,1950-05-21 -47,1,619,0.0,11,0,1950-05-21 -48,1,788,0.0,16,0,1950-05-21 -49,1,792,0.0,33,0,1950-05-21 -50,1,669,2.0,10,0,1950-05-21 -51,1,790,0.0,32,0,1950-05-21 -52,1,789,0.0,27,0,1950-05-21 -53,1,589,4.0,5,0,1950-05-21 -54,1,666,0.0,29,0,1950-05-21 -55,1,686,4.0,6,0,1950-05-21 -56,2,776,0.0,45,0,1950-05-30 -57,2,669,2.0,14,0,1950-05-30 -58,2,747,0.0,48,0,1950-05-30 -59,2,785,0.0,49,0,1950-05-30 -60,2,640,0.0,47,0,1950-05-30 -61,2,589,4.0,7,0,1950-05-30 -62,2,789,0.0,52,0,1950-05-30 -63,2,790,0.0,57,0,1950-05-30 -64,2,647,6.0,5,0,1950-05-30 -65,2,498,0.0,44,0,1950-05-30 -66,2,626,0.0,46,0,1950-05-30 -67,2,426,0.0,50,0,1950-05-30 -68,2,762,0.0,51,0,1950-05-30 -69,2,687,0.0,56,0,1950-05-30 -70,2,787,0.0,20,0,1950-05-30 -71,2,661,0.0,55,0,1950-05-30 -72,2,633,0.0,43,0,1950-05-30 -73,2,501,0.0,53,0,1950-05-30 -74,2,666,0.0,54,0,1950-05-30 -75,2,784,0.0,24,0,1950-05-30 -76,2,778,0.0,28,0,1950-05-30 -77,2,660,0.0,19,0,1950-05-30 -78,2,520,0.0,34,0,1950-05-30 -79,2,803,0.0,60,0,1950-05-30 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00:00:00 -14323,316,171,18.0,2,2,1979-04-08 00:00:00 -14324,316,205,0.0,21,0,1979-04-08 00:00:00 -14325,316,206,8.0,6,0,1979-04-08 00:00:00 -14326,316,211,0.0,23,0,1979-04-08 00:00:00 -14327,316,202,20.0,1,2,1979-04-08 00:00:00 -14328,316,232,0.0,25,0,1979-04-08 00:00:00 -14329,316,118,0.0,18,0,1979-04-08 00:00:00 -14330,316,231,0.0,26,0,1979-04-08 00:00:00 -14331,316,136,0.0,15,0,1979-04-08 00:00:00 -14332,316,174,0.0,20,0,1979-04-08 00:00:00 -14333,316,201,3.0,10,0,1979-04-08 00:00:00 -14334,316,135,0.0,22,0,1979-04-08 00:00:00 -14335,316,162,0.0,24,0,1979-04-08 00:00:00 -14336,316,181,1.0,12,0,1979-04-08 00:00:00 -14337,316,218,0.0,19,0,1979-04-08 00:00:00 -14338,316,196,5.0,7,0,1979-04-08 00:00:00 -14339,316,230,0.0,16,0,1979-04-08 00:00:00 -14340,316,221,13.0,3,0,1979-04-08 00:00:00 -14341,317,205,0.0,22,0,1979-04-29 00:00:00 -14342,317,222,0.0,18,0,1979-04-29 00:00:00 -14343,317,177,4.0,9,0,1979-04-29 00:00:00 -14344,317,199,0.0,14,0,1979-04-29 00:00:00 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00:00:00 -14368,318,199,0.0,15,0,1979-05-13 00:00:00 -14369,318,205,0.0,24,0,1979-05-13 00:00:00 -14370,318,222,0.0,19,0,1979-05-13 00:00:00 -14371,318,177,4.0,10,0,1979-05-13 00:00:00 -14372,318,172,0.0,14,0,1979-05-13 00:00:00 -14373,318,202,20.0,3,2,1979-05-13 00:00:00 -14374,318,206,12.0,6,0,1979-05-13 00:00:00 -14375,318,220,20.0,4,1,1979-05-13 00:00:00 -14376,318,186,5.0,9,0,1979-05-13 00:00:00 -14377,318,198,19.0,5,0,1979-05-13 00:00:00 -14378,318,171,24.0,1,2,1979-05-13 00:00:00 -14379,318,223,1.0,12,0,1979-05-13 00:00:00 -14380,318,211,0.0,25,0,1979-05-13 00:00:00 -14381,318,232,0.0,17,0,1979-05-13 00:00:00 -14382,318,230,0.0,18,0,1979-05-13 00:00:00 -14383,318,135,0.0,21,0,1979-05-13 00:00:00 -14384,318,151,0.0,26,0,1979-05-13 00:00:00 -14385,318,233,0.0,28,0,1979-05-13 00:00:00 -14386,318,118,2.0,11,0,1979-05-13 00:00:00 -14387,318,136,0.0,16,0,1979-05-13 00:00:00 -14388,318,174,0.0,22,0,1979-05-13 00:00:00 -14389,318,231,0.0,27,0,1979-05-13 00:00:00 -14390,318,221,24.0,2,1,1979-05-13 00:00:00 -14391,318,162,0.0,20,0,1979-05-13 00:00:00 -14392,318,181,1.0,13,0,1979-05-13 00:00:00 -14393,318,218,0.0,23,0,1979-05-13 00:00:00 -14394,318,196,7.0,8,0,1979-05-13 00:00:00 -14395,318,201,8.0,7,0,1979-05-13 00:00:00 -14396,319,177,4.0,11,0,1979-05-27 00:00:00 -14397,319,202,20.0,3,2,1979-05-27 00:00:00 -14398,319,205,0.0,24,0,1979-05-27 00:00:00 -14399,319,222,6.0,10,0,1979-05-27 00:00:00 -14400,319,199,1.0,13,0,1979-05-27 00:00:00 -14401,319,171,24.0,2,2,1979-05-27 00:00:00 -14402,319,223,1.0,14,0,1979-05-27 00:00:00 -14403,319,206,12.0,6,0,1979-05-27 00:00:00 -14404,319,220,20.0,4,1,1979-05-27 00:00:00 -14405,319,186,8.0,7,0,1979-05-27 00:00:00 -14406,319,211,0.0,25,0,1979-05-27 00:00:00 -14407,319,172,0.0,16,0,1979-05-27 00:00:00 -14408,319,135,0.0,21,0,1979-05-27 00:00:00 -14409,319,198,20.0,5,0,1979-05-27 00:00:00 -14410,319,196,7.0,9,0,1979-05-27 00:00:00 -14411,319,230,0.0,19,0,1979-05-27 00:00:00 -14412,319,151,0.0,26,0,1979-05-27 00:00:00 -14413,319,233,0.0,28,0,1979-05-27 00:00:00 -14414,319,232,0.0,18,0,1979-05-27 00:00:00 -14415,319,231,0.0,27,0,1979-05-27 00:00:00 -14416,319,136,0.0,17,0,1979-05-27 00:00:00 -14417,319,118,2.0,12,0,1979-05-27 00:00:00 -14418,319,201,8.0,8,0,1979-05-27 00:00:00 -14419,319,221,30.0,1,2,1979-05-27 00:00:00 -14420,319,162,0.0,20,0,1979-05-27 00:00:00 -14421,319,181,1.0,15,0,1979-05-27 00:00:00 -14422,319,218,0.0,23,0,1979-05-27 00:00:00 -14423,319,174,0.0,22,0,1979-05-27 00:00:00 -14424,320,177,7.0,12,0,1979-07-01 00:00:00 -14425,320,211,0.0,26,0,1979-07-01 00:00:00 -14426,320,202,26.0,2,2,1979-07-01 00:00:00 -14427,320,205,0.0,25,0,1979-07-01 00:00:00 -14428,320,222,7.0,11,0,1979-07-01 00:00:00 -14429,320,199,1.0,15,0,1979-07-01 00:00:00 -14430,320,198,20.0,5,0,1979-07-01 00:00:00 -14431,320,223,1.0,16,0,1979-07-01 00:00:00 -14432,320,206,12.0,6,0,1979-07-01 00:00:00 -14433,320,220,20.0,4,1,1979-07-01 00:00:00 -14434,320,186,8.0,9,0,1979-07-01 00:00:00 -14435,320,135,0.0,24,0,1979-07-01 00:00:00 -14436,320,171,24.0,3,2,1979-07-01 00:00:00 -14437,320,172,0.0,18,0,1979-07-01 00:00:00 -14438,320,230,0.0,21,0,1979-07-01 00:00:00 -14439,320,162,4.0,13,0,1979-07-01 00:00:00 -14440,320,218,9.0,7,1,1979-07-01 00:00:00 -14441,320,235,0.0,31,0,1979-07-01 00:00:00 -14442,320,234,0.0,29,0,1979-07-01 00:00:00 -14443,320,176,0.0,22,0,1979-07-01 00:00:00 -14444,320,196,9.0,8,0,1979-07-01 00:00:00 -14445,320,233,0.0,30,0,1979-07-01 00:00:00 -14446,320,232,0.0,20,0,1979-07-01 00:00:00 -14447,320,151,0.0,27,0,1979-07-01 00:00:00 -14448,320,231,0.0,28,0,1979-07-01 00:00:00 -14449,320,136,0.0,19,0,1979-07-01 00:00:00 -14450,320,174,0.0,23,0,1979-07-01 00:00:00 -14451,320,201,8.0,10,0,1979-07-01 00:00:00 -14452,320,221,30.0,1,2,1979-07-01 00:00:00 -14453,320,181,1.0,17,0,1979-07-01 00:00:00 -14454,320,118,2.0,14,0,1979-07-01 00:00:00 -14455,321,235,0.0,28,0,1979-07-14 00:00:00 -14456,321,234,1.0,18,0,1979-07-14 00:00:00 -14457,321,176,0.0,25,0,1979-07-14 00:00:00 -14458,321,151,0.0,29,0,1979-07-14 00:00:00 -14459,321,233,0.0,31,0,1979-07-14 00:00:00 -14460,321,232,0.0,22,0,1979-07-14 00:00:00 -14461,321,231,0.0,30,0,1979-07-14 00:00:00 -14462,321,118,2.0,14,0,1979-07-14 00:00:00 -14463,321,174,0.0,21,0,1979-07-14 00:00:00 -14464,321,136,0.0,20,0,1979-07-14 00:00:00 -14465,321,171,24.0,3,2,1979-07-14 00:00:00 -14466,321,198,20.0,5,0,1979-07-14 00:00:00 -14467,321,186,11.0,9,0,1979-07-14 00:00:00 -14468,321,206,12.0,8,0,1979-07-14 00:00:00 -14469,321,223,1.0,16,0,1979-07-14 00:00:00 -14470,321,172,0.0,19,0,1979-07-14 00:00:00 -14471,321,199,1.0,15,0,1979-07-14 00:00:00 -14472,321,177,7.0,13,0,1979-07-14 00:00:00 -14473,321,222,16.0,6,1,1979-07-14 00:00:00 -14474,321,220,20.0,4,1,1979-07-14 00:00:00 -14475,321,202,26.0,2,2,1979-07-14 00:00:00 -14476,321,205,0.0,27,0,1979-07-14 00:00:00 -14477,321,201,8.0,12,0,1979-07-14 00:00:00 -14478,321,221,32.0,1,2,1979-07-14 00:00:00 -14479,321,181,1.0,17,0,1979-07-14 00:00:00 -14480,321,162,10.0,10,0,1979-07-14 00:00:00 -14481,321,196,13.0,7,0,1979-07-14 00:00:00 -14482,321,230,0.0,23,0,1979-07-14 00:00:00 -14483,321,135,0.0,26,0,1979-07-14 00:00:00 -14484,321,211,0.0,24,0,1979-07-14 00:00:00 -14485,321,218,9.0,11,1,1979-07-14 00:00:00 -14486,322,135,0.0,27,0,1979-07-29 00:00:00 -14487,322,222,22.0,4,1,1979-07-29 00:00:00 -14488,322,211,0.0,25,0,1979-07-29 00:00:00 -14489,322,202,26.0,3,2,1979-07-29 00:00:00 -14490,322,205,0.0,28,0,1979-07-29 00:00:00 -14491,322,177,16.0,7,1,1979-07-29 00:00:00 -14492,322,198,20.0,6,0,1979-07-29 00:00:00 -14493,322,172,0.0,19,0,1979-07-29 00:00:00 -14494,322,223,1.0,16,0,1979-07-29 00:00:00 -14495,322,206,12.0,10,0,1979-07-29 00:00:00 -14496,322,186,13.0,9,0,1979-07-29 00:00:00 -14497,322,171,28.0,2,2,1979-07-29 00:00:00 -14498,322,230,0.0,24,0,1979-07-29 00:00:00 -14499,322,199,2.0,15,0,1979-07-29 00:00:00 -14500,322,196,13.0,8,0,1979-07-29 00:00:00 -14501,322,220,20.0,5,1,1979-07-29 00:00:00 -14502,322,181,1.0,17,0,1979-07-29 00:00:00 -14503,322,235,0.0,29,0,1979-07-29 00:00:00 -14504,322,234,1.0,18,0,1979-07-29 00:00:00 -14505,322,176,0.0,26,0,1979-07-29 00:00:00 -14506,322,208,0.0,22,0,1979-07-29 00:00:00 -14507,322,151,0.0,30,0,1979-07-29 00:00:00 -14508,322,233,0.0,32,0,1979-07-29 00:00:00 -14509,322,232,0.0,23,0,1979-07-29 00:00:00 -14510,322,218,9.0,12,1,1979-07-29 00:00:00 -14511,322,231,0.0,31,0,1979-07-29 00:00:00 -14512,322,136,0.0,20,0,1979-07-29 00:00:00 -14513,322,174,0.0,21,0,1979-07-29 00:00:00 -14514,322,201,8.0,13,0,1979-07-29 00:00:00 -14515,322,221,35.0,1,2,1979-07-29 00:00:00 -14516,322,162,10.0,11,0,1979-07-29 00:00:00 -14517,322,118,2.0,14,0,1979-07-29 00:00:00 -14518,323,135,0.0,28,0,1979-08-12 00:00:00 -14519,323,211,0.0,26,0,1979-08-12 00:00:00 -14520,323,202,32.0,2,2,1979-08-12 00:00:00 -14521,323,205,0.0,23,0,1979-08-12 00:00:00 -14522,323,222,24.0,5,1,1979-08-12 00:00:00 -14523,323,177,25.0,4,2,1979-08-12 00:00:00 -14524,323,206,12.0,10,0,1979-08-12 00:00:00 -14525,323,172,0.0,19,0,1979-08-12 00:00:00 -14526,323,223,1.0,16,0,1979-08-12 00:00:00 -14527,323,220,20.0,6,1,1979-08-12 00:00:00 -14528,323,186,13.0,9,0,1979-08-12 00:00:00 -14529,323,198,20.0,7,0,1979-08-12 00:00:00 -14530,323,230,0.0,25,0,1979-08-12 00:00:00 -14531,323,199,2.0,15,0,1979-08-12 00:00:00 -14532,323,171,32.0,3,2,1979-08-12 00:00:00 -14533,323,196,13.0,8,0,1979-08-12 00:00:00 -14534,323,181,1.0,17,0,1979-08-12 00:00:00 -14535,323,218,9.0,12,1,1979-08-12 00:00:00 -14536,323,208,0.0,22,0,1979-08-12 00:00:00 -14537,323,235,0.0,29,0,1979-08-12 00:00:00 -14538,323,234,1.0,18,0,1979-08-12 00:00:00 -14539,323,176,0.0,27,0,1979-08-12 00:00:00 -14540,323,233,0.0,32,0,1979-08-12 00:00:00 -14541,323,232,0.0,24,0,1979-08-12 00:00:00 -14542,323,151,0.0,30,0,1979-08-12 00:00:00 -14543,323,231,0.0,31,0,1979-08-12 00:00:00 -14544,323,136,0.0,20,0,1979-08-12 00:00:00 -14545,323,174,0.0,21,0,1979-08-12 00:00:00 -14546,323,201,8.0,13,0,1979-08-12 00:00:00 -14547,323,221,38.0,1,2,1979-08-12 00:00:00 -14548,323,162,11.0,11,0,1979-08-12 00:00:00 -14549,323,118,2.0,14,0,1979-08-12 00:00:00 -14550,324,177,34.0,3,3,1979-08-26 00:00:00 -14551,324,211,0.0,21,0,1979-08-26 00:00:00 -14552,324,202,32.0,4,2,1979-08-26 00:00:00 -14553,324,205,0.0,24,0,1979-08-26 00:00:00 -14554,324,222,24.0,5,1,1979-08-26 00:00:00 -14555,324,135,0.0,28,0,1979-08-26 00:00:00 -14556,324,171,36.0,2,2,1979-08-26 00:00:00 -14557,324,172,0.0,20,0,1979-08-26 00:00:00 -14558,324,223,1.0,18,0,1979-08-26 00:00:00 -14559,324,206,12.0,10,0,1979-08-26 00:00:00 -14560,324,220,20.0,6,1,1979-08-26 00:00:00 -14561,324,186,13.0,9,0,1979-08-26 00:00:00 -14562,324,198,20.0,7,0,1979-08-26 00:00:00 -14563,324,199,3.0,16,0,1979-08-26 00:00:00 -14564,324,230,0.0,26,0,1979-08-26 00:00:00 -14565,324,231,0.0,31,0,1979-08-26 00:00:00 -14566,324,218,9.0,12,1,1979-08-26 00:00:00 -14567,324,208,0.0,23,0,1979-08-26 00:00:00 -14568,324,235,0.0,29,0,1979-08-26 00:00:00 -14569,324,234,3.0,15,0,1979-08-26 00:00:00 -14570,324,196,13.0,8,0,1979-08-26 00:00:00 -14571,324,151,0.0,30,0,1979-08-26 00:00:00 -14572,324,233,0.0,32,0,1979-08-26 00:00:00 -14573,324,232,0.0,25,0,1979-08-26 00:00:00 -14574,324,176,0.0,27,0,1979-08-26 00:00:00 -14575,324,136,3.0,14,0,1979-08-26 00:00:00 -14576,324,174,0.0,22,0,1979-08-26 00:00:00 -14577,324,201,8.0,13,0,1979-08-26 00:00:00 -14578,324,221,44.0,1,2,1979-08-26 00:00:00 -14579,324,162,11.0,11,0,1979-08-26 00:00:00 -14580,324,181,1.0,19,0,1979-08-26 00:00:00 -14581,324,118,2.0,17,0,1979-08-26 00:00:00 -14582,325,230,0.0,26,0,1979-09-09 00:00:00 -14583,325,135,0.0,28,0,1979-09-09 00:00:00 -14584,325,211,0.0,21,0,1979-09-09 00:00:00 -14585,325,202,38.0,2,2,1979-09-09 00:00:00 -14586,325,205,0.0,24,0,1979-09-09 00:00:00 -14587,325,222,27.0,5,1,1979-09-09 00:00:00 -14588,325,177,34.0,4,3,1979-09-09 00:00:00 -14589,325,171,36.0,3,2,1979-09-09 00:00:00 -14590,325,223,1.0,19,0,1979-09-09 00:00:00 -14591,325,206,14.0,9,0,1979-09-09 00:00:00 -14592,325,220,20.0,6,1,1979-09-09 00:00:00 -14593,325,186,13.0,10,0,1979-09-09 00:00:00 -14594,325,198,20.0,7,0,1979-09-09 00:00:00 -14595,325,196,14.0,8,0,1979-09-09 00:00:00 -14596,325,199,3.0,17,0,1979-09-09 00:00:00 -14597,325,218,9.0,12,1,1979-09-09 00:00:00 -14598,325,172,0.0,20,0,1979-09-09 00:00:00 -14599,325,162,11.0,11,0,1979-09-09 00:00:00 -14600,325,181,4.0,14,0,1979-09-09 00:00:00 -14601,325,175,0.0,34,0,1979-09-09 00:00:00 -14602,325,229,0.0,29,0,1979-09-09 00:00:00 -14603,325,208,0.0,23,0,1979-09-09 00:00:00 -14604,325,235,0.0,30,0,1979-09-09 00:00:00 -14605,325,176,0.0,27,0,1979-09-09 00:00:00 -14606,325,151,0.0,31,0,1979-09-09 00:00:00 -14607,325,234,3.0,16,0,1979-09-09 00:00:00 -14608,325,232,0.0,25,0,1979-09-09 00:00:00 -14609,325,118,2.0,18,0,1979-09-09 00:00:00 -14610,325,231,0.0,32,0,1979-09-09 00:00:00 -14611,325,136,3.0,15,0,1979-09-09 00:00:00 -14612,325,174,0.0,22,0,1979-09-09 00:00:00 -14613,325,201,8.0,13,0,1979-09-09 00:00:00 -14614,325,221,51.0,1,3,1979-09-09 00:00:00 -14615,325,233,0.0,33,0,1979-09-09 00:00:00 -14616,326,135,0.0,28,0,1979-09-30 00:00:00 -14617,326,196,14.0,8,0,1979-09-30 00:00:00 -14618,326,230,0.0,27,0,1979-09-30 00:00:00 -14619,326,186,14.0,10,0,1979-09-30 00:00:00 -14620,326,198,20.0,7,0,1979-09-30 00:00:00 -14621,326,171,36.0,4,2,1979-09-30 00:00:00 -14622,326,211,0.0,21,0,1979-09-30 00:00:00 -14623,326,206,14.0,9,0,1979-09-30 00:00:00 -14624,326,205,0.0,25,0,1979-09-30 00:00:00 -14625,326,222,29.0,5,1,1979-09-30 00:00:00 -14626,326,177,40.0,3,4,1979-09-30 00:00:00 -14627,326,199,3.0,17,0,1979-09-30 00:00:00 -14628,326,172,0.0,20,0,1979-09-30 00:00:00 -14629,326,223,1.0,19,0,1979-09-30 00:00:00 -14630,326,218,9.0,13,1,1979-09-30 00:00:00 -14631,326,202,44.0,2,2,1979-09-30 00:00:00 -14632,326,181,4.0,14,0,1979-09-30 00:00:00 -14633,326,232,0.0,26,0,1979-09-30 00:00:00 -14634,326,221,51.0,1,3,1979-09-30 00:00:00 -14635,326,236,0.0,36,0,1979-09-30 00:00:00 -14636,326,216,0.0,24,0,1979-09-30 00:00:00 -14637,326,175,0.0,35,0,1979-09-30 00:00:00 -14638,326,229,0.0,30,0,1979-09-30 00:00:00 -14639,326,208,0.0,23,0,1979-09-30 00:00:00 -14640,326,235,0.0,31,0,1979-09-30 00:00:00 -14641,326,234,3.0,16,0,1979-09-30 00:00:00 -14642,326,176,0.0,29,0,1979-09-30 00:00:00 -14643,326,151,0.0,32,0,1979-09-30 00:00:00 -14644,326,233,0.0,34,0,1979-09-30 00:00:00 -14645,326,118,2.0,18,0,1979-09-30 00:00:00 -14646,326,231,0.0,33,0,1979-09-30 00:00:00 -14647,326,136,3.0,15,0,1979-09-30 00:00:00 -14648,326,174,0.0,22,0,1979-09-30 00:00:00 -14649,326,201,10.0,12,0,1979-09-30 00:00:00 -14650,326,162,11.0,11,0,1979-09-30 00:00:00 -14651,326,220,20.0,6,1,1979-09-30 00:00:00 -14652,327,171,36.0,4,2,1979-10-07 00:00:00 -14653,327,236,0.0,36,0,1979-10-07 00:00:00 -14654,327,218,9.0,13,1,1979-10-07 00:00:00 -14655,327,196,14.0,11,0,1979-10-07 00:00:00 -14656,327,230,0.0,27,0,1979-10-07 00:00:00 -14657,327,211,0.0,22,0,1979-10-07 00:00:00 -14658,327,202,47.0,2,3,1979-10-07 00:00:00 -14659,327,205,0.0,26,0,1979-10-07 00:00:00 -14660,327,222,29.0,5,1,1979-10-07 00:00:00 -14661,327,177,40.0,3,4,1979-10-07 00:00:00 -14662,327,199,3.0,18,0,1979-10-07 00:00:00 -14663,327,172,3.0,15,0,1979-10-07 00:00:00 -14664,327,223,1.0,21,0,1979-10-07 00:00:00 -14665,327,206,14.0,12,0,1979-10-07 00:00:00 -14666,327,220,20.0,6,1,1979-10-07 00:00:00 -14667,327,186,15.0,9,0,1979-10-07 00:00:00 -14668,327,198,20.0,7,0,1979-10-07 00:00:00 -14669,327,181,4.0,14,0,1979-10-07 00:00:00 -14670,327,162,17.0,8,0,1979-10-07 00:00:00 -14671,327,135,0.0,28,0,1979-10-07 00:00:00 -14672,327,201,14.0,10,0,1979-10-07 00:00:00 -14673,327,216,0.0,24,0,1979-10-07 00:00:00 -14674,327,175,0.0,33,0,1979-10-07 00:00:00 -14675,327,221,51.0,1,3,1979-10-07 00:00:00 -14676,327,208,0.0,25,0,1979-10-07 00:00:00 -14677,327,235,0.0,31,0,1979-10-07 00:00:00 -14678,327,234,3.0,17,0,1979-10-07 00:00:00 -14679,327,176,0.0,29,0,1979-10-07 00:00:00 -14680,327,229,0.0,30,0,1979-10-07 00:00:00 -14681,327,233,0.0,35,0,1979-10-07 00:00:00 -14682,327,232,2.0,19,0,1979-10-07 00:00:00 -14683,327,118,2.0,20,0,1979-10-07 00:00:00 -14684,327,231,0.0,34,0,1979-10-07 00:00:00 -14685,327,136,3.0,16,0,1979-10-07 00:00:00 -14686,327,174,0.0,23,0,1979-10-07 00:00:00 -14687,327,151,0.0,32,0,1979-10-07 00:00:00 -14688,328,202,0.0,12,0,1980-01-13 00:00:00 -14689,328,223,0.0,11,0,1980-01-13 00:00:00 -14690,328,222,0.0,10,0,1980-01-13 00:00:00 -14691,328,221,0.0,9,0,1980-01-13 00:00:00 -14692,328,220,0.0,8,0,1980-01-13 00:00:00 -14693,328,176,4.0,3,0,1980-01-13 00:00:00 -14694,328,116,1.0,6,0,1980-01-13 00:00:00 -14695,328,151,2.0,5,0,1980-01-13 00:00:00 -14696,328,136,6.0,2,0,1980-01-13 00:00:00 -14697,328,171,0.0,13,0,1980-01-13 00:00:00 -14698,328,177,9.0,1,1,1980-01-13 00:00:00 -14699,328,216,0.0,7,0,1980-01-13 00:00:00 -14700,328,118,0.0,14,0,1980-01-13 00:00:00 -14701,328,205,3.0,4,0,1980-01-13 00:00:00 -14702,328,206,0.0,16,0,1980-01-13 00:00:00 -14703,328,175,0.0,15,0,1980-01-13 00:00:00 -14704,328,135,0.0,27,0,1980-01-13 00:00:00 -14705,328,139,0.0,26,0,1980-01-13 00:00:00 -14706,328,224,0.0,25,0,1980-01-13 00:00:00 -14707,328,196,0.0,24,0,1980-01-13 00:00:00 -14708,328,201,0.0,23,0,1980-01-13 00:00:00 -14709,328,157,0.0,28,0,1980-01-13 00:00:00 -14710,328,218,0.0,21,0,1980-01-13 00:00:00 -14711,328,186,0.0,20,0,1980-01-13 00:00:00 -14712,328,172,0.0,19,0,1980-01-13 00:00:00 -14713,328,198,0.0,18,0,1980-01-13 00:00:00 -14714,328,199,0.0,17,0,1980-01-13 00:00:00 -14715,328,162,0.0,22,0,1980-01-13 00:00:00 -14716,329,202,0.0,17,0,1980-01-27 00:00:00 -14717,329,223,0.0,16,0,1980-01-27 00:00:00 -14718,329,222,0.0,20,0,1980-01-27 00:00:00 -14719,329,221,0.0,19,0,1980-01-27 00:00:00 -14720,329,216,0.0,11,0,1980-01-27 00:00:00 -14721,329,151,2.0,9,0,1980-01-27 00:00:00 -14722,329,205,3.0,6,0,1980-01-27 00:00:00 -14723,329,176,4.0,5,0,1980-01-27 00:00:00 -14724,329,136,6.0,4,0,1980-01-27 00:00:00 -14725,329,171,0.0,21,0,1980-01-27 00:00:00 -14726,329,177,13.0,1,1,1980-01-27 00:00:00 -14727,329,116,3.0,8,0,1980-01-27 00:00:00 -14728,329,118,1.0,10,0,1980-01-27 00:00:00 -14729,329,220,0.0,18,0,1980-01-27 00:00:00 -14730,329,206,0.0,22,0,1980-01-27 00:00:00 -14731,329,157,0.0,28,0,1980-01-27 00:00:00 -14732,329,135,0.0,26,0,1980-01-27 00:00:00 -14733,329,139,0.0,27,0,1980-01-27 00:00:00 -14734,329,175,0.0,12,0,1980-01-27 00:00:00 -14735,329,196,0.0,15,0,1980-01-27 00:00:00 -14736,329,201,3.0,7,0,1980-01-27 00:00:00 -14737,329,224,0.0,25,0,1980-01-27 00:00:00 -14738,329,218,0.0,23,0,1980-01-27 00:00:00 -14739,329,186,0.0,14,0,1980-01-27 00:00:00 -14740,329,172,6.0,3,0,1980-01-27 00:00:00 -14741,329,198,0.0,24,0,1980-01-27 00:00:00 -14742,329,199,0.0,13,0,1980-01-27 00:00:00 -14743,329,162,9.0,2,1,1980-01-27 00:00:00 -14744,330,118,1.0,13,0,1980-03-01 00:00:00 -14745,330,171,6.0,5,0,1980-03-01 00:00:00 -14746,330,202,0.0,22,0,1980-03-01 00:00:00 -14747,330,223,0.0,17,0,1980-03-01 00:00:00 -14748,330,222,0.0,18,0,1980-03-01 00:00:00 -14749,330,176,4.0,7,0,1980-03-01 00:00:00 -14750,330,216,0.0,14,0,1980-03-01 00:00:00 -14751,330,116,3.0,9,0,1980-03-01 00:00:00 -14752,330,151,2.0,10,0,1980-03-01 00:00:00 -14753,330,205,3.0,8,0,1980-03-01 00:00:00 -14754,330,175,0.0,16,0,1980-03-01 00:00:00 -14755,330,221,0.0,24,0,1980-03-01 00:00:00 -14756,330,206,0.0,20,0,1980-03-01 00:00:00 -14757,330,201,7.0,4,0,1980-03-01 00:00:00 -14758,330,198,2.0,11,0,1980-03-01 00:00:00 -14759,330,172,6.0,6,0,1980-03-01 00:00:00 -14760,330,186,0.0,19,0,1980-03-01 00:00:00 -14761,330,218,0.0,25,0,1980-03-01 00:00:00 -14762,330,162,18.0,1,2,1980-03-01 00:00:00 -14763,330,196,0.0,15,0,1980-03-01 00:00:00 -14764,330,224,0.0,27,0,1980-03-01 00:00:00 -14765,330,139,0.0,29,0,1980-03-01 00:00:00 -14766,330,135,0.0,28,0,1980-03-01 00:00:00 -14767,330,157,0.0,26,0,1980-03-01 00:00:00 -14768,330,208,0.0,21,0,1980-03-01 00:00:00 -14769,330,136,9.0,3,0,1980-03-01 00:00:00 -14770,330,199,1.0,12,0,1980-03-01 00:00:00 -14771,330,177,13.0,2,1,1980-03-01 00:00:00 -14772,330,220,0.0,23,0,1980-03-01 00:00:00 -14773,331,223,4.0,8,0,1980-03-30 00:00:00 -14774,331,177,13.0,3,1,1980-03-30 00:00:00 -14775,331,136,18.0,2,1,1980-03-30 00:00:00 -14776,331,176,4.0,9,0,1980-03-30 00:00:00 -14777,331,205,3.0,10,0,1980-03-30 00:00:00 -14778,331,151,2.0,13,0,1980-03-30 00:00:00 -14779,331,116,3.0,12,0,1980-03-30 00:00:00 -14780,331,216,0.0,17,0,1980-03-30 00:00:00 -14781,331,220,0.0,25,0,1980-03-30 00:00:00 -14782,331,221,2.0,14,0,1980-03-30 00:00:00 -14783,331,222,0.0,20,0,1980-03-30 00:00:00 -14784,331,202,0.0,24,0,1980-03-30 00:00:00 -14785,331,171,6.0,6,0,1980-03-30 00:00:00 -14786,331,118,7.0,5,0,1980-03-30 00:00:00 -14787,331,175,0.0,19,0,1980-03-30 00:00:00 -14788,331,199,1.0,16,0,1980-03-30 00:00:00 -14789,331,206,0.0,22,0,1980-03-30 00:00:00 -14790,331,139,0.0,29,0,1980-03-30 00:00:00 -14791,331,172,6.0,7,0,1980-03-30 00:00:00 -14792,331,186,3.0,11,0,1980-03-30 00:00:00 -14793,331,218,0.0,21,0,1980-03-30 00:00:00 -14794,331,162,18.0,1,2,1980-03-30 00:00:00 -14795,331,201,8.0,4,0,1980-03-30 00:00:00 -14796,331,196,0.0,18,0,1980-03-30 00:00:00 -14797,331,224,0.0,28,0,1980-03-30 00:00:00 -14798,331,198,2.0,15,0,1980-03-30 00:00:00 -14799,331,135,0.0,27,0,1980-03-30 00:00:00 -14800,331,157,0.0,26,0,1980-03-30 00:00:00 -14801,331,208,0.0,23,0,1980-03-30 00:00:00 -14802,331,225,0.0,30,0,1980-03-30 00:00:00 -14803,332,220,0.0,26,0,1980-05-04 00:00:00 -14804,332,223,4.0,10,0,1980-05-04 00:00:00 -14805,332,216,0.0,19,0,1980-05-04 00:00:00 -14806,332,221,2.0,15,0,1980-05-04 00:00:00 -14807,332,222,0.0,21,0,1980-05-04 00:00:00 -14808,332,116,3.0,13,0,1980-05-04 00:00:00 -14809,332,139,0.0,30,0,1980-05-04 00:00:00 -14810,332,205,3.0,11,0,1980-05-04 00:00:00 -14811,332,176,4.0,9,0,1980-05-04 00:00:00 -14812,332,136,18.0,3,1,1980-05-04 00:00:00 -14813,332,202,1.0,18,0,1980-05-04 00:00:00 -14814,332,177,19.0,2,1,1980-05-04 00:00:00 -14815,332,135,0.0,24,0,1980-05-04 00:00:00 -14816,332,151,2.0,16,0,1980-05-04 00:00:00 -14817,332,171,6.0,7,0,1980-05-04 00:00:00 -14818,332,224,0.0,29,0,1980-05-04 00:00:00 -14819,332,175,0.0,20,0,1980-05-04 00:00:00 -14820,332,196,2.0,14,0,1980-05-04 00:00:00 -14821,332,201,17.0,4,1,1980-05-04 00:00:00 -14822,332,226,0.0,28,0,1980-05-04 00:00:00 -14823,332,208,0.0,25,0,1980-05-04 00:00:00 -14824,332,157,0.0,27,0,1980-05-04 00:00:00 -14825,332,162,21.0,1,2,1980-05-04 00:00:00 -14826,332,225,0.0,31,0,1980-05-04 00:00:00 -14827,332,186,3.0,12,0,1980-05-04 00:00:00 -14828,332,172,6.0,6,0,1980-05-04 00:00:00 -14829,332,198,6.0,8,0,1980-05-04 00:00:00 -14830,332,199,1.0,17,0,1980-05-04 00:00:00 -14831,332,206,0.0,23,0,1980-05-04 00:00:00 -14832,332,218,0.0,22,0,1980-05-04 00:00:00 -14833,332,118,7.0,5,0,1980-05-04 00:00:00 -14834,333,220,0.0,26,0,1980-05-18 00:00:00 -14835,333,171,12.0,6,0,1980-05-18 00:00:00 -14836,333,202,3.0,14,0,1980-05-18 00:00:00 -14837,333,223,5.0,9,0,1980-05-18 00:00:00 -14838,333,222,0.0,22,0,1980-05-18 00:00:00 -14839,333,221,2.0,17,0,1980-05-18 00:00:00 -14840,333,177,19.0,3,1,1980-05-18 00:00:00 -14841,333,151,2.0,18,0,1980-05-18 00:00:00 -14842,333,205,3.0,12,0,1980-05-18 00:00:00 -14843,333,176,4.0,10,0,1980-05-18 00:00:00 -14844,333,136,22.0,1,1,1980-05-18 00:00:00 -14845,333,118,7.0,7,0,1980-05-18 00:00:00 -14846,333,116,3.0,15,0,1980-05-18 00:00:00 -14847,333,175,0.0,21,0,1980-05-18 00:00:00 -14848,333,216,0.0,19,0,1980-05-18 00:00:00 -14849,333,199,4.0,11,0,1980-05-18 00:00:00 -14850,333,226,0.0,28,0,1980-05-18 00:00:00 -14851,333,206,0.0,20,0,1980-05-18 00:00:00 -14852,333,208,0.0,25,0,1980-05-18 00:00:00 -14853,333,157,0.0,27,0,1980-05-18 00:00:00 -14854,333,135,0.0,24,0,1980-05-18 00:00:00 -14855,333,139,0.0,30,0,1980-05-18 00:00:00 -14856,333,224,0.0,29,0,1980-05-18 00:00:00 -14857,333,225,0.0,31,0,1980-05-18 00:00:00 -14858,333,201,17.0,4,1,1980-05-18 00:00:00 -14859,333,162,21.0,2,2,1980-05-18 00:00:00 -14860,333,218,0.0,23,0,1980-05-18 00:00:00 -14861,333,186,3.0,13,0,1980-05-18 00:00:00 -14862,333,198,15.0,5,1,1980-05-18 00:00:00 -14863,333,196,2.0,16,0,1980-05-18 00:00:00 -14864,333,172,6.0,8,0,1980-05-18 00:00:00 -14865,334,118,7.0,7,0,1980-06-29 00:00:00 -14866,334,171,16.0,6,0,1980-06-29 00:00:00 -14867,334,202,3.0,14,0,1980-06-29 00:00:00 -14868,334,223,5.0,9,0,1980-06-29 00:00:00 -14869,334,222,0.0,22,0,1980-06-29 00:00:00 -14870,334,216,0.0,19,0,1980-06-29 00:00:00 -14871,334,220,0.0,26,0,1980-06-29 00:00:00 -14872,334,116,3.0,15,0,1980-06-29 00:00:00 -14873,334,151,2.0,18,0,1980-06-29 00:00:00 -14874,334,205,3.0,13,0,1980-06-29 00:00:00 -14875,334,136,25.0,2,1,1980-06-29 00:00:00 -14876,334,221,2.0,17,0,1980-06-29 00:00:00 -14877,334,175,0.0,21,0,1980-06-29 00:00:00 -14878,334,198,16.0,5,1,1980-06-29 00:00:00 -14879,334,199,4.0,11,0,1980-06-29 00:00:00 -14880,334,172,6.0,8,0,1980-06-29 00:00:00 -14881,334,186,3.0,12,0,1980-06-29 00:00:00 -14882,334,218,0.0,23,0,1980-06-29 00:00:00 -14883,334,162,23.0,3,2,1980-06-29 00:00:00 -14884,334,196,2.0,16,0,1980-06-29 00:00:00 -14885,334,224,0.0,29,0,1980-06-29 00:00:00 -14886,334,139,0.0,30,0,1980-06-29 00:00:00 -14887,334,135,0.0,24,0,1980-06-29 00:00:00 -14888,334,157,0.0,27,0,1980-06-29 00:00:00 -14889,334,208,0.0,25,0,1980-06-29 00:00:00 -14890,334,225,0.0,31,0,1980-06-29 00:00:00 -14891,334,226,0.0,28,0,1980-06-29 00:00:00 -14892,334,177,28.0,1,2,1980-06-29 00:00:00 -14893,334,206,0.0,20,0,1980-06-29 00:00:00 -14894,334,201,23.0,4,1,1980-06-29 00:00:00 -14895,334,176,4.0,10,0,1980-06-29 00:00:00 -14896,335,196,4.0,13,0,1980-07-13 00:00:00 -14897,335,176,4.0,11,0,1980-07-13 00:00:00 -14898,335,205,6.0,9,0,1980-07-13 00:00:00 -14899,335,151,2.0,18,0,1980-07-13 00:00:00 -14900,335,116,4.0,14,0,1980-07-13 00:00:00 -14901,335,216,0.0,19,0,1980-07-13 00:00:00 -14902,335,220,0.0,28,0,1980-07-13 00:00:00 -14903,335,221,2.0,17,0,1980-07-13 00:00:00 -14904,335,222,0.0,23,0,1980-07-13 00:00:00 -14905,335,223,5.0,10,0,1980-07-13 00:00:00 -14906,335,202,3.0,16,0,1980-07-13 00:00:00 -14907,335,171,16.0,6,0,1980-07-13 00:00:00 -14908,335,118,7.0,7,0,1980-07-13 00:00:00 -14909,335,175,0.0,21,0,1980-07-13 00:00:00 -14910,335,206,0.0,20,0,1980-07-13 00:00:00 -14911,335,199,4.0,12,0,1980-07-13 00:00:00 -14912,335,198,20.0,5,1,1980-07-13 00:00:00 -14913,335,172,6.0,8,0,1980-07-13 00:00:00 -14914,335,186,3.0,15,0,1980-07-13 00:00:00 -14915,335,218,0.0,24,0,1980-07-13 00:00:00 -14916,335,136,31.0,2,1,1980-07-13 00:00:00 -14917,335,177,37.0,1,3,1980-07-13 00:00:00 -14918,335,201,23.0,4,1,1980-07-13 00:00:00 -14919,335,224,0.0,31,0,1980-07-13 00:00:00 -14920,335,139,0.0,32,0,1980-07-13 00:00:00 -14921,335,135,0.0,26,0,1980-07-13 00:00:00 -14922,335,157,0.0,29,0,1980-07-13 00:00:00 -14923,335,208,0.0,27,0,1980-07-13 00:00:00 -14924,335,225,0.0,33,0,1980-07-13 00:00:00 -14925,335,226,0.0,30,0,1980-07-13 00:00:00 -14926,335,211,0.0,22,0,1980-07-13 00:00:00 -14927,335,210,0.0,25,0,1980-07-13 00:00:00 -14928,335,227,0.0,34,0,1980-07-13 00:00:00 -14929,335,162,23.0,3,2,1980-07-13 00:00:00 -14930,336,202,4.0,15,0,1980-08-10 00:00:00 -14931,336,177,41.0,1,3,1980-08-10 00:00:00 -14932,336,136,34.0,2,1,1980-08-10 00:00:00 -14933,336,176,4.0,11,0,1980-08-10 00:00:00 -14934,336,205,6.0,9,0,1980-08-10 00:00:00 -14935,336,221,2.0,18,0,1980-08-10 00:00:00 -14936,336,116,4.0,16,0,1980-08-10 00:00:00 -14937,336,216,0.0,20,0,1980-08-10 00:00:00 -14938,336,220,0.0,28,0,1980-08-10 00:00:00 -14939,336,222,0.0,23,0,1980-08-10 00:00:00 -14940,336,151,4.0,14,0,1980-08-10 00:00:00 -14941,336,171,25.0,4,1,1980-08-10 00:00:00 -14942,336,201,23.0,6,1,1980-08-10 00:00:00 -14943,336,227,0.0,35,0,1980-08-10 00:00:00 -14944,336,228,0.0,33,0,1980-08-10 00:00:00 -14945,336,118,7.0,7,0,1980-08-10 00:00:00 -14946,336,175,0.0,21,0,1980-08-10 00:00:00 -14947,336,199,4.0,12,0,1980-08-10 00:00:00 -14948,336,198,26.0,3,1,1980-08-10 00:00:00 -14949,336,172,6.0,8,0,1980-08-10 00:00:00 -14950,336,186,3.0,17,0,1980-08-10 00:00:00 -14951,336,218,0.0,24,0,1980-08-10 00:00:00 -14952,336,162,23.0,5,2,1980-08-10 00:00:00 -14953,336,223,5.0,10,0,1980-08-10 00:00:00 -14954,336,206,0.0,19,0,1980-08-10 00:00:00 -14955,336,224,0.0,31,0,1980-08-10 00:00:00 -14956,336,211,0.0,22,0,1980-08-10 00:00:00 -14957,336,196,4.0,13,0,1980-08-10 00:00:00 -14958,336,226,0.0,30,0,1980-08-10 00:00:00 -14959,336,225,0.0,34,0,1980-08-10 00:00:00 -14960,336,210,0.0,25,0,1980-08-10 00:00:00 -14961,336,157,0.0,29,0,1980-08-10 00:00:00 -14962,336,135,0.0,26,0,1980-08-10 00:00:00 -14963,336,139,0.0,32,0,1980-08-10 00:00:00 -14964,336,208,0.0,27,0,1980-08-10 00:00:00 -14965,337,175,0.0,23,0,1980-08-17 00:00:00 -14966,337,221,2.0,19,0,1980-08-17 00:00:00 -14967,337,171,28.0,4,1,1980-08-17 00:00:00 -14968,337,202,4.0,17,0,1980-08-17 00:00:00 -14969,337,223,5.0,11,0,1980-08-17 00:00:00 -14970,337,222,0.0,24,0,1980-08-17 00:00:00 -14971,337,118,7.0,8,0,1980-08-17 00:00:00 -14972,337,151,4.0,15,0,1980-08-17 00:00:00 -14973,337,116,4.0,16,0,1980-08-17 00:00:00 -14974,337,205,6.0,10,0,1980-08-17 00:00:00 -14975,337,176,4.0,12,0,1980-08-17 00:00:00 -14976,337,136,36.0,2,1,1980-08-17 00:00:00 -14977,337,177,47.0,1,3,1980-08-17 00:00:00 -14978,337,206,0.0,20,0,1980-08-17 00:00:00 -14979,337,216,0.0,21,0,1980-08-17 00:00:00 -14980,337,199,4.0,13,0,1980-08-17 00:00:00 -14981,337,220,0.0,28,0,1980-08-17 00:00:00 -14982,337,172,7.0,9,0,1980-08-17 00:00:00 -14983,337,198,30.0,3,1,1980-08-17 00:00:00 -14984,337,94,0.0,30,0,1980-08-17 00:00:00 -14985,337,228,0.0,34,0,1980-08-17 00:00:00 -14986,337,227,0.0,36,0,1980-08-17 00:00:00 -14987,337,210,0.0,25,0,1980-08-17 00:00:00 -14988,337,211,0.0,22,0,1980-08-17 00:00:00 -14989,337,225,0.0,35,0,1980-08-17 00:00:00 -14990,337,208,0.0,27,0,1980-08-17 00:00:00 -14991,337,226,0.0,31,0,1980-08-17 00:00:00 -14992,337,135,0.0,26,0,1980-08-17 00:00:00 -14993,337,139,0.0,33,0,1980-08-17 00:00:00 -14994,337,224,0.0,32,0,1980-08-17 00:00:00 -14995,337,196,4.0,14,0,1980-08-17 00:00:00 -14996,337,201,23.0,6,1,1980-08-17 00:00:00 -14997,337,162,23.0,5,2,1980-08-17 00:00:00 -14998,337,218,9.0,7,1,1980-08-17 00:00:00 -14999,337,157,0.0,29,0,1980-08-17 00:00:00 -15000,337,186,3.0,18,0,1980-08-17 00:00:00 -15001,338,206,0.0,20,0,1980-08-31 00:00:00 -15002,338,175,0.0,22,0,1980-08-31 00:00:00 -15003,338,118,7.0,8,0,1980-08-31 00:00:00 -15004,338,171,32.0,4,1,1980-08-31 00:00:00 -15005,338,202,4.0,17,0,1980-08-31 00:00:00 -15006,338,223,5.0,12,0,1980-08-31 00:00:00 -15007,338,222,0.0,24,0,1980-08-31 00:00:00 -15008,338,216,0.0,21,0,1980-08-31 00:00:00 -15009,338,220,0.0,28,0,1980-08-31 00:00:00 -15010,338,199,4.0,15,0,1980-08-31 00:00:00 -15011,338,116,5.0,13,0,1980-08-31 00:00:00 -15012,338,151,4.0,16,0,1980-08-31 00:00:00 -15013,338,205,6.0,10,0,1980-08-31 00:00:00 -15014,338,176,4.0,14,0,1980-08-31 00:00:00 -15015,338,136,45.0,2,2,1980-08-31 00:00:00 -15016,338,177,47.0,1,3,1980-08-31 00:00:00 -15017,338,221,2.0,19,0,1980-08-31 00:00:00 -15018,338,198,33.0,3,1,1980-08-31 00:00:00 -15019,338,218,9.0,7,1,1980-08-31 00:00:00 -15020,338,186,3.0,18,0,1980-08-31 00:00:00 -15021,338,190,0.0,37,0,1980-08-31 00:00:00 -15022,338,229,0.0,31,0,1980-08-31 00:00:00 -15023,338,94,0.0,30,0,1980-08-31 00:00:00 -15024,338,228,0.0,35,0,1980-08-31 00:00:00 -15025,338,227,0.0,38,0,1980-08-31 00:00:00 -15026,338,210,0.0,25,0,1980-08-31 00:00:00 -15027,338,172,7.0,9,0,1980-08-31 00:00:00 -15028,338,226,0.0,32,0,1980-08-31 00:00:00 -15029,338,211,0.0,23,0,1980-08-31 00:00:00 -15030,338,208,0.0,27,0,1980-08-31 00:00:00 -15031,338,157,0.0,29,0,1980-08-31 00:00:00 -15032,338,135,0.0,26,0,1980-08-31 00:00:00 -15033,338,224,0.0,33,0,1980-08-31 00:00:00 -15034,338,196,6.0,11,0,1980-08-31 00:00:00 -15035,338,201,23.0,6,1,1980-08-31 00:00:00 -15036,338,162,29.0,5,2,1980-08-31 00:00:00 -15037,338,225,0.0,36,0,1980-08-31 00:00:00 -15038,338,139,0.0,34,0,1980-08-31 00:00:00 -15039,339,177,53.0,2,3,1980-09-14 00:00:00 -15040,339,136,54.0,1,3,1980-09-14 00:00:00 -15041,339,176,6.0,10,0,1980-09-14 00:00:00 -15042,339,180,0.0,36,0,1980-09-14 00:00:00 -15043,339,172,10.0,7,0,1980-09-14 00:00:00 -15044,339,198,37.0,3,1,1980-09-14 00:00:00 -15045,339,199,4.0,15,0,1980-09-14 00:00:00 -15046,339,206,0.0,20,0,1980-09-14 00:00:00 -15047,339,175,0.0,22,0,1980-09-14 00:00:00 -15048,339,118,7.0,9,0,1980-09-14 00:00:00 -15049,339,171,32.0,4,1,1980-09-14 00:00:00 -15050,339,223,5.0,13,0,1980-09-14 00:00:00 -15051,339,222,0.0,24,0,1980-09-14 00:00:00 -15052,339,221,2.0,19,0,1980-09-14 00:00:00 -15053,339,220,0.0,29,0,1980-09-14 00:00:00 -15054,339,216,0.0,21,0,1980-09-14 00:00:00 -15055,339,116,5.0,14,0,1980-09-14 00:00:00 -15056,339,151,4.0,16,0,1980-09-14 00:00:00 -15057,339,205,6.0,11,0,1980-09-14 00:00:00 -15058,339,186,3.0,18,0,1980-09-14 00:00:00 -15059,339,218,9.0,8,1,1980-09-14 00:00:00 -15060,339,202,4.0,17,0,1980-09-14 00:00:00 -15061,339,201,24.0,6,1,1980-09-14 00:00:00 -15062,339,162,29.0,5,2,1980-09-14 00:00:00 -15063,339,190,0.0,38,0,1980-09-14 00:00:00 -15064,339,229,0.0,31,0,1980-09-14 00:00:00 -15065,339,94,0.0,30,0,1980-09-14 00:00:00 -15066,339,228,0.0,35,0,1980-09-14 00:00:00 -15067,339,210,0.0,25,0,1980-09-14 00:00:00 -15068,339,211,0.0,23,0,1980-09-14 00:00:00 -15069,339,226,0.0,32,0,1980-09-14 00:00:00 -15070,339,227,0.0,39,0,1980-09-14 00:00:00 -15071,339,225,0.0,37,0,1980-09-14 00:00:00 -15072,339,208,0.0,28,0,1980-09-14 00:00:00 -15073,339,157,0.0,27,0,1980-09-14 00:00:00 -15074,339,135,0.0,26,0,1980-09-14 00:00:00 -15075,339,139,0.0,34,0,1980-09-14 00:00:00 -15076,339,224,0.0,33,0,1980-09-14 00:00:00 -15077,339,196,6.0,12,0,1980-09-14 00:00:00 -15078,340,223,5.0,15,0,1980-09-28 00:00:00 -15079,340,199,4.0,17,0,1980-09-28 00:00:00 -15080,340,206,0.0,21,0,1980-09-28 00:00:00 -15081,340,175,0.0,23,0,1980-09-28 00:00:00 -15082,340,118,7.0,9,0,1980-09-28 00:00:00 -15083,340,171,32.0,4,1,1980-09-28 00:00:00 -15084,340,202,6.0,14,0,1980-09-28 00:00:00 -15085,340,198,40.0,3,1,1980-09-28 00:00:00 -15086,340,222,0.0,24,0,1980-09-28 00:00:00 -15087,340,136,54.0,2,3,1980-09-28 00:00:00 -15088,340,220,0.0,29,0,1980-09-28 00:00:00 -15089,340,216,0.0,22,0,1980-09-28 00:00:00 -15090,340,116,5.0,16,0,1980-09-28 00:00:00 -15091,340,151,4.0,18,0,1980-09-28 00:00:00 -15092,340,205,6.0,12,0,1980-09-28 00:00:00 -15093,340,176,6.0,10,0,1980-09-28 00:00:00 -15094,340,177,62.0,1,4,1980-09-28 00:00:00 -15095,340,172,10.0,7,0,1980-09-28 00:00:00 -15096,340,221,2.0,19,0,1980-09-28 00:00:00 -15097,340,186,6.0,11,0,1980-09-28 00:00:00 -15098,340,208,0.0,28,0,1980-09-28 00:00:00 -15099,340,162,29.0,5,2,1980-09-28 00:00:00 -15100,340,213,0.0,41,0,1980-09-28 00:00:00 -15101,340,218,9.0,8,1,1980-09-28 00:00:00 -15102,340,180,0.0,38,0,1980-09-28 00:00:00 -15103,340,190,0.0,34,0,1980-09-28 00:00:00 -15104,340,229,0.0,31,0,1980-09-28 00:00:00 -15105,340,94,0.0,30,0,1980-09-28 00:00:00 -15106,340,228,0.0,37,0,1980-09-28 00:00:00 -15107,340,227,0.0,40,0,1980-09-28 00:00:00 -15108,340,210,0.0,25,0,1980-09-28 00:00:00 -15109,340,109,0.0,32,0,1980-09-28 00:00:00 -15110,340,226,0.0,33,0,1980-09-28 00:00:00 -15111,340,211,1.0,20,0,1980-09-28 00:00:00 -15112,340,201,28.0,6,1,1980-09-28 00:00:00 -15113,340,224,0.0,35,0,1980-09-28 00:00:00 -15114,340,139,0.0,36,0,1980-09-28 00:00:00 -15115,340,196,6.0,13,0,1980-09-28 00:00:00 -15116,340,157,0.0,27,0,1980-09-28 00:00:00 -15117,340,225,0.0,39,0,1980-09-28 00:00:00 -15118,340,135,0.0,26,0,1980-09-28 00:00:00 -15119,341,198,42.0,3,1,1980-10-05 00:00:00 -15120,341,202,6.0,14,0,1980-10-05 00:00:00 -15121,341,172,13.0,7,0,1980-10-05 00:00:00 -15122,341,206,1.0,20,0,1980-10-05 00:00:00 -15123,341,175,0.0,22,0,1980-10-05 00:00:00 -15124,341,118,7.0,9,0,1980-10-05 00:00:00 -15125,341,171,34.0,4,1,1980-10-05 00:00:00 -15126,341,223,5.0,15,0,1980-10-05 00:00:00 -15127,341,216,0.0,23,0,1980-10-05 00:00:00 -15128,341,221,2.0,19,0,1980-10-05 00:00:00 -15129,341,220,0.0,29,0,1980-10-05 00:00:00 -15130,341,116,5.0,16,0,1980-10-05 00:00:00 -15131,341,151,4.0,18,0,1980-10-05 00:00:00 -15132,341,205,6.0,12,0,1980-10-05 00:00:00 -15133,341,176,6.0,10,0,1980-10-05 00:00:00 -15134,341,136,54.0,2,3,1980-10-05 00:00:00 -15135,341,177,67.0,1,5,1980-10-05 00:00:00 -15136,341,186,6.0,11,0,1980-10-05 00:00:00 -15137,341,222,0.0,25,0,1980-10-05 00:00:00 -15138,341,218,9.0,8,1,1980-10-05 00:00:00 -15139,341,199,4.0,17,0,1980-10-05 00:00:00 -15140,341,201,32.0,5,1,1980-10-05 00:00:00 -15141,341,162,29.0,6,2,1980-10-05 00:00:00 -15142,341,213,0.0,41,0,1980-10-05 00:00:00 -15143,341,109,0.0,32,0,1980-10-05 00:00:00 -15144,341,190,0.0,34,0,1980-10-05 00:00:00 -15145,341,229,0.0,31,0,1980-10-05 00:00:00 -15146,341,94,0.0,30,0,1980-10-05 00:00:00 -15147,341,228,0.0,37,0,1980-10-05 00:00:00 -15148,341,227,0.0,40,0,1980-10-05 00:00:00 -15149,341,210,0.0,24,0,1980-10-05 00:00:00 -15150,341,180,0.0,38,0,1980-10-05 00:00:00 -15151,341,226,0.0,33,0,1980-10-05 00:00:00 -15152,341,225,0.0,39,0,1980-10-05 00:00:00 -15153,341,208,0.0,28,0,1980-10-05 00:00:00 -15154,341,157,0.0,27,0,1980-10-05 00:00:00 -15155,341,135,0.0,26,0,1980-10-05 00:00:00 -15156,341,139,0.0,36,0,1980-10-05 00:00:00 -15157,341,224,0.0,35,0,1980-10-05 00:00:00 -15158,341,196,6.0,13,0,1980-10-05 00:00:00 -15159,341,211,1.0,21,0,1980-10-05 00:00:00 -15160,342,118,0.0,17,0,1981-03-15 00:00:00 -15161,342,212,0.0,18,0,1981-03-15 00:00:00 -15162,342,94,0.0,19,0,1981-03-15 00:00:00 -15163,342,202,0.0,20,0,1981-03-15 00:00:00 -15164,342,186,0.0,21,0,1981-03-15 00:00:00 -15165,342,172,0.0,22,0,1981-03-15 00:00:00 -15166,342,205,0.0,26,0,1981-03-15 00:00:00 -15167,342,109,0.0,24,0,1981-03-15 00:00:00 -15168,342,213,0.0,25,0,1981-03-15 00:00:00 -15169,342,214,0.0,27,0,1981-03-15 00:00:00 -15170,342,193,0.0,29,0,1981-03-15 00:00:00 -15171,342,135,0.0,16,0,1981-03-15 00:00:00 -15172,342,116,0.0,23,0,1981-03-15 00:00:00 -15173,342,176,0.0,15,0,1981-03-15 00:00:00 -15174,342,215,0.0,28,0,1981-03-15 00:00:00 -15175,342,151,0.0,13,0,1981-03-15 00:00:00 -15176,342,177,9.0,1,1,1981-03-15 00:00:00 -15177,342,174,1.0,6,0,1981-03-15 00:00:00 -15178,342,157,2.0,5,0,1981-03-15 00:00:00 -15179,342,206,3.0,4,0,1981-03-15 00:00:00 -15180,342,136,4.0,3,0,1981-03-15 00:00:00 -15181,342,198,6.0,2,0,1981-03-15 00:00:00 -15182,342,171,0.0,14,0,1981-03-15 00:00:00 -15183,342,162,0.0,8,0,1981-03-15 00:00:00 -15184,342,175,0.0,9,0,1981-03-15 00:00:00 -15185,342,201,0.0,10,0,1981-03-15 00:00:00 -15186,342,196,0.0,11,0,1981-03-15 00:00:00 -15187,342,211,0.0,12,0,1981-03-15 00:00:00 -15188,342,191,0.0,7,0,1981-03-15 00:00:00 -15189,343,212,0.0,24,0,1981-03-29 00:00:00 -15190,343,94,0.0,16,0,1981-03-29 00:00:00 -15191,343,202,0.0,21,0,1981-03-29 00:00:00 -15192,343,186,0.0,13,0,1981-03-29 00:00:00 -15193,343,172,2.0,8,0,1981-03-29 00:00:00 -15194,343,116,0.0,23,0,1981-03-29 00:00:00 -15195,343,205,0.0,28,0,1981-03-29 00:00:00 -15196,343,213,0.0,27,0,1981-03-29 00:00:00 -15197,343,214,0.0,29,0,1981-03-29 00:00:00 -15198,343,215,0.0,25,0,1981-03-29 00:00:00 -15199,343,193,0.0,30,0,1981-03-29 00:00:00 -15200,343,118,4.0,4,0,1981-03-29 00:00:00 -15201,343,217,0.0,31,0,1981-03-29 00:00:00 -15202,343,109,0.0,26,0,1981-03-29 00:00:00 -15203,343,216,0.0,17,0,1981-03-29 00:00:00 -15204,343,135,0.0,22,0,1981-03-29 00:00:00 -15205,343,171,1.0,10,0,1981-03-29 00:00:00 -15206,343,176,0.0,15,0,1981-03-29 00:00:00 -15207,343,177,15.0,1,1,1981-03-29 00:00:00 -15208,343,198,15.0,2,1,1981-03-29 00:00:00 -15209,343,136,4.0,3,0,1981-03-29 00:00:00 -15210,343,157,2.0,7,0,1981-03-29 00:00:00 -15211,343,174,1.0,9,0,1981-03-29 00:00:00 -15212,343,206,3.0,6,0,1981-03-29 00:00:00 -15213,343,162,0.0,14,0,1981-03-29 00:00:00 -15214,343,175,3.0,5,0,1981-03-29 00:00:00 -15215,343,201,0.0,18,0,1981-03-29 00:00:00 -15216,343,196,0.0,11,0,1981-03-29 00:00:00 -15217,343,211,0.0,19,0,1981-03-29 00:00:00 -15218,343,151,0.0,20,0,1981-03-29 00:00:00 -15219,343,191,0.0,12,0,1981-03-29 00:00:00 -15220,344,109,0.0,20,0,1981-04-12 00:00:00 -15221,344,94,0.0,19,0,1981-04-12 00:00:00 -15222,344,202,0.0,25,0,1981-04-12 00:00:00 -15223,344,172,3.0,8,0,1981-04-12 00:00:00 -15224,344,116,4.0,5,0,1981-04-12 00:00:00 -15225,344,213,0.0,28,0,1981-04-12 00:00:00 -15226,344,212,0.0,26,0,1981-04-12 00:00:00 -15227,344,214,0.0,27,0,1981-04-12 00:00:00 -15228,344,215,0.0,17,0,1981-04-12 00:00:00 -15229,344,193,0.0,30,0,1981-04-12 00:00:00 -15230,344,216,0.0,22,0,1981-04-12 00:00:00 -15231,344,217,0.0,32,0,1981-04-12 00:00:00 -15232,344,218,0.0,31,0,1981-04-12 00:00:00 -15233,344,205,0.0,29,0,1981-04-12 00:00:00 -15234,344,118,4.0,4,0,1981-04-12 00:00:00 -15235,344,186,0.0,15,0,1981-04-12 00:00:00 -15236,344,176,0.0,16,0,1981-04-12 00:00:00 -15237,344,177,18.0,2,1,1981-04-12 00:00:00 -15238,344,198,21.0,1,1,1981-04-12 00:00:00 -15239,344,136,13.0,3,1,1981-04-12 00:00:00 -15240,344,206,3.0,6,0,1981-04-12 00:00:00 -15241,344,174,1.0,11,0,1981-04-12 00:00:00 -15242,344,191,0.0,14,0,1981-04-12 00:00:00 -15243,344,162,2.0,9,0,1981-04-12 00:00:00 -15244,344,157,2.0,10,0,1981-04-12 00:00:00 -15245,344,201,0.0,23,0,1981-04-12 00:00:00 -15246,344,196,0.0,13,0,1981-04-12 00:00:00 -15247,344,135,0.0,21,0,1981-04-12 00:00:00 -15248,344,211,0.0,24,0,1981-04-12 00:00:00 -15249,344,151,0.0,18,0,1981-04-12 00:00:00 -15250,344,171,1.0,12,0,1981-04-12 00:00:00 -15251,344,175,3.0,7,0,1981-04-12 00:00:00 -15252,345,214,0.0,31,0,1981-05-03 00:00:00 -15253,345,172,3.0,9,0,1981-05-03 00:00:00 -15254,345,116,4.0,5,0,1981-05-03 00:00:00 -15255,345,109,1.0,14,0,1981-05-03 00:00:00 -15256,345,213,0.0,32,0,1981-05-03 00:00:00 -15257,345,205,0.0,33,0,1981-05-03 00:00:00 -15258,345,215,0.0,21,0,1981-05-03 00:00:00 -15259,345,204,0.0,35,0,1981-05-03 00:00:00 -15260,345,216,0.0,25,0,1981-05-03 00:00:00 -15261,345,217,0.0,36,0,1981-05-03 00:00:00 -15262,345,218,0.0,27,0,1981-05-03 00:00:00 -15263,345,200,0.0,26,0,1981-05-03 00:00:00 -15264,345,104,0.0,29,0,1981-05-03 00:00:00 -15265,345,117,0.0,34,0,1981-05-03 00:00:00 -15266,345,186,0.0,19,0,1981-05-03 00:00:00 -15267,345,193,0.0,28,0,1981-05-03 00:00:00 -15268,345,202,0.0,17,0,1981-05-03 00:00:00 -15269,345,94,0.0,23,0,1981-05-03 00:00:00 -15270,345,177,18.0,3,1,1981-05-03 00:00:00 -15271,345,212,0.0,30,0,1981-05-03 00:00:00 -15272,345,198,25.0,1,1,1981-05-03 00:00:00 -15273,345,136,22.0,2,2,1981-05-03 00:00:00 -15274,345,206,3.0,6,0,1981-05-03 00:00:00 -15275,345,157,2.0,12,0,1981-05-03 00:00:00 -15276,345,191,0.0,18,0,1981-05-03 00:00:00 -15277,345,162,2.0,10,0,1981-05-03 00:00:00 -15278,345,175,3.0,7,0,1981-05-03 00:00:00 -15279,345,174,1.0,13,0,1981-05-03 00:00:00 -15280,345,196,0.0,16,0,1981-05-03 00:00:00 -15281,345,211,3.0,8,0,1981-05-03 00:00:00 -15282,345,151,0.0,22,0,1981-05-03 00:00:00 -15283,345,171,1.0,15,0,1981-05-03 00:00:00 -15284,345,176,0.0,20,0,1981-05-03 00:00:00 -15285,345,135,0.0,24,0,1981-05-03 00:00:00 -15286,345,118,10.0,4,0,1981-05-03 00:00:00 -15287,345,201,2.0,11,0,1981-05-03 00:00:00 -15288,346,215,0.0,23,0,1981-05-17 00:00:00 -15289,346,172,5.0,6,0,1981-05-17 00:00:00 -15290,346,116,4.0,8,0,1981-05-17 00:00:00 -15291,346,109,1.0,17,0,1981-05-17 00:00:00 -15292,346,213,0.0,34,0,1981-05-17 00:00:00 -15293,346,205,0.0,33,0,1981-05-17 00:00:00 -15294,346,214,0.0,32,0,1981-05-17 00:00:00 -15295,346,193,0.0,30,0,1981-05-17 00:00:00 -15296,346,186,0.0,18,0,1981-05-17 00:00:00 -15297,346,217,0.0,37,0,1981-05-17 00:00:00 -15298,346,218,0.0,29,0,1981-05-17 00:00:00 -15299,346,200,0.0,27,0,1981-05-17 00:00:00 -15300,346,104,0.0,25,0,1981-05-17 00:00:00 -15301,346,117,0.0,35,0,1981-05-17 00:00:00 -15302,346,204,0.0,36,0,1981-05-17 00:00:00 -15303,346,159,0.0,28,0,1981-05-17 00:00:00 -15304,346,216,0.0,26,0,1981-05-17 00:00:00 -15305,346,202,3.0,9,0,1981-05-17 00:00:00 -15306,346,177,18.0,3,1,1981-05-17 00:00:00 -15307,346,212,0.0,31,0,1981-05-17 00:00:00 -15308,346,94,4.0,7,0,1981-05-17 00:00:00 -15309,346,198,34.0,1,2,1981-05-17 00:00:00 -15310,346,136,22.0,2,2,1981-05-17 00:00:00 -15311,346,206,3.0,10,0,1981-05-17 00:00:00 -15312,346,157,3.0,13,0,1981-05-17 00:00:00 -15313,346,191,0.0,20,0,1981-05-17 00:00:00 -15314,346,162,2.0,14,0,1981-05-17 00:00:00 -15315,346,175,3.0,11,0,1981-05-17 00:00:00 -15316,346,174,1.0,16,0,1981-05-17 00:00:00 -15317,346,196,0.0,19,0,1981-05-17 00:00:00 -15318,346,211,3.0,12,0,1981-05-17 00:00:00 -15319,346,151,0.0,21,0,1981-05-17 00:00:00 -15320,346,171,7.0,5,0,1981-05-17 00:00:00 -15321,346,176,0.0,22,0,1981-05-17 00:00:00 -15322,346,135,0.0,24,0,1981-05-17 00:00:00 -15323,346,118,10.0,4,0,1981-05-17 00:00:00 -15324,346,201,2.0,15,0,1981-05-17 00:00:00 -15325,347,205,0.0,33,0,1981-05-31 00:00:00 -15326,347,186,0.0,18,0,1981-05-31 00:00:00 -15327,347,172,5.0,9,0,1981-05-31 00:00:00 -15328,347,116,4.0,11,0,1981-05-31 00:00:00 -15329,347,109,1.0,17,0,1981-05-31 00:00:00 -15330,347,213,0.0,34,0,1981-05-31 00:00:00 -15331,347,214,0.0,32,0,1981-05-31 00:00:00 -15332,347,202,12.0,4,1,1981-05-31 00:00:00 -15333,347,159,0.0,27,0,1981-05-31 00:00:00 -15334,347,204,0.0,36,0,1981-05-31 00:00:00 -15335,347,117,0.0,35,0,1981-05-31 00:00:00 -15336,347,104,0.0,24,0,1981-05-31 00:00:00 -15337,347,200,0.0,28,0,1981-05-31 00:00:00 -15338,347,217,0.0,37,0,1981-05-31 00:00:00 -15339,347,218,0.0,29,0,1981-05-31 00:00:00 -15340,347,215,0.0,23,0,1981-05-31 00:00:00 -15341,347,94,4.0,10,0,1981-05-31 00:00:00 -15342,347,198,34.0,1,2,1981-05-31 00:00:00 -15343,347,118,10.0,6,0,1981-05-31 00:00:00 -15344,347,216,0.0,26,0,1981-05-31 00:00:00 -15345,347,177,24.0,2,1,1981-05-31 00:00:00 -15346,347,136,22.0,3,2,1981-05-31 00:00:00 -15347,347,206,3.0,13,0,1981-05-31 00:00:00 -15348,347,157,5.0,8,0,1981-05-31 00:00:00 -15349,347,174,1.0,16,0,1981-05-31 00:00:00 -15350,347,191,0.0,20,0,1981-05-31 00:00:00 -15351,347,212,0.0,31,0,1981-05-31 00:00:00 -15352,347,193,0.0,30,0,1981-05-31 00:00:00 -15353,347,175,4.0,12,0,1981-05-31 00:00:00 -15354,347,135,0.0,25,0,1981-05-31 00:00:00 -15355,347,176,0.0,22,0,1981-05-31 00:00:00 -15356,347,171,11.0,5,0,1981-05-31 00:00:00 -15357,347,151,0.0,21,0,1981-05-31 00:00:00 -15358,347,211,3.0,14,0,1981-05-31 00:00:00 -15359,347,196,0.0,19,0,1981-05-31 00:00:00 -15360,347,201,5.0,7,0,1981-05-31 00:00:00 -15361,347,162,2.0,15,0,1981-05-31 00:00:00 -15362,348,214,0.0,33,0,1981-06-21 00:00:00 -15363,348,205,0.0,30,0,1981-06-21 00:00:00 -15364,348,213,0.0,34,0,1981-06-21 00:00:00 -15365,348,117,0.0,36,0,1981-06-21 00:00:00 -15366,348,172,7.0,7,0,1981-06-21 00:00:00 -15367,348,215,0.0,23,0,1981-06-21 00:00:00 -15368,348,116,4.0,12,0,1981-06-21 00:00:00 -15369,348,193,0.0,29,0,1981-06-21 00:00:00 -15370,348,104,0.0,24,0,1981-06-21 00:00:00 -15371,348,217,0.0,38,0,1981-06-21 00:00:00 -15372,348,218,0.0,31,0,1981-06-21 00:00:00 -15373,348,200,0.0,28,0,1981-06-21 00:00:00 -15374,348,186,4.0,11,0,1981-06-21 00:00:00 -15375,348,204,0.0,35,0,1981-06-21 00:00:00 -15376,348,159,0.0,27,0,1981-06-21 00:00:00 -15377,348,219,0.0,37,0,1981-06-21 00:00:00 -15378,348,216,0.0,26,0,1981-06-21 00:00:00 -15379,348,202,21.0,4,2,1981-06-21 00:00:00 -15380,348,109,1.0,18,0,1981-06-21 00:00:00 -15381,348,212,0.0,32,0,1981-06-21 00:00:00 -15382,348,177,24.0,2,1,1981-06-21 00:00:00 -15383,348,198,37.0,1,2,1981-06-21 00:00:00 -15384,348,94,5.0,8,0,1981-06-21 00:00:00 -15385,348,206,3.0,14,0,1981-06-21 00:00:00 -15386,348,157,5.0,10,0,1981-06-21 00:00:00 -15387,348,174,1.0,17,0,1981-06-21 00:00:00 -15388,348,191,0.0,19,0,1981-06-21 00:00:00 -15389,348,162,2.0,16,0,1981-06-21 00:00:00 -15390,348,175,4.0,13,0,1981-06-21 00:00:00 -15391,348,136,22.0,3,2,1981-06-21 00:00:00 -15392,348,196,0.0,20,0,1981-06-21 00:00:00 -15393,348,211,3.0,15,0,1981-06-21 00:00:00 -15394,348,151,0.0,21,0,1981-06-21 00:00:00 -15395,348,171,17.0,5,0,1981-06-21 00:00:00 -15396,348,176,0.0,22,0,1981-06-21 00:00:00 -15397,348,135,0.0,25,0,1981-06-21 00:00:00 -15398,348,201,5.0,9,0,1981-06-21 00:00:00 -15399,348,118,10.0,6,0,1981-06-21 00:00:00 -15400,349,186,10.0,7,0,1981-07-05 00:00:00 -15401,349,172,8.0,9,0,1981-07-05 00:00:00 -15402,349,116,13.0,6,1,1981-07-05 00:00:00 -15403,349,109,1.0,18,0,1981-07-05 00:00:00 -15404,349,213,0.0,34,0,1981-07-05 00:00:00 -15405,349,205,0.0,30,0,1981-07-05 00:00:00 -15406,349,214,0.0,33,0,1981-07-05 00:00:00 -15407,349,219,0.0,37,0,1981-07-05 00:00:00 -15408,349,193,0.0,29,0,1981-07-05 00:00:00 -15409,349,159,0.0,27,0,1981-07-05 00:00:00 -15410,349,204,0.0,35,0,1981-07-05 00:00:00 -15411,349,117,0.0,36,0,1981-07-05 00:00:00 -15412,349,200,0.0,28,0,1981-07-05 00:00:00 -15413,349,202,21.0,4,2,1981-07-05 00:00:00 -15414,349,218,0.0,31,0,1981-07-05 00:00:00 -15415,349,215,0.0,23,0,1981-07-05 00:00:00 -15416,349,94,5.0,11,0,1981-07-05 00:00:00 -15417,349,104,0.0,24,0,1981-07-05 00:00:00 -15418,349,118,10.0,8,0,1981-07-05 00:00:00 -15419,349,217,0.0,38,0,1981-07-05 00:00:00 -15420,349,177,24.0,3,1,1981-07-05 00:00:00 -15421,349,198,37.0,1,2,1981-07-05 00:00:00 -15422,349,136,26.0,2,2,1981-07-05 00:00:00 -15423,349,206,3.0,15,0,1981-07-05 00:00:00 -15424,349,157,5.0,13,0,1981-07-05 00:00:00 -15425,349,174,1.0,17,0,1981-07-05 00:00:00 -15426,349,191,0.0,19,0,1981-07-05 00:00:00 -15427,349,162,5.0,12,0,1981-07-05 00:00:00 -15428,349,175,4.0,14,0,1981-07-05 00:00:00 -15429,349,201,7.0,10,0,1981-07-05 00:00:00 -15430,349,196,0.0,20,0,1981-07-05 00:00:00 -15431,349,211,3.0,16,0,1981-07-05 00:00:00 -15432,349,151,0.0,21,0,1981-07-05 00:00:00 -15433,349,171,17.0,5,0,1981-07-05 00:00:00 -15434,349,176,0.0,22,0,1981-07-05 00:00:00 -15435,349,135,0.0,25,0,1981-07-05 00:00:00 -15436,349,212,0.0,32,0,1981-07-05 00:00:00 -15437,349,216,0.0,26,0,1981-07-05 00:00:00 -15438,350,177,24.0,3,1,1981-07-18 00:00:00 -15439,350,136,26.0,2,2,1981-07-18 00:00:00 -15440,350,109,1.0,18,0,1981-07-18 00:00:00 -15441,350,213,0.0,34,0,1981-07-18 00:00:00 -15442,350,205,0.0,22,0,1981-07-18 00:00:00 -15443,350,214,0.0,33,0,1981-07-18 00:00:00 -15444,350,215,0.0,25,0,1981-07-18 00:00:00 -15445,350,193,0.0,30,0,1981-07-18 00:00:00 -15446,350,217,0.0,38,0,1981-07-18 00:00:00 -15447,350,218,0.0,31,0,1981-07-18 00:00:00 -15448,350,200,1.0,19,0,1981-07-18 00:00:00 -15449,350,104,0.0,26,0,1981-07-18 00:00:00 -15450,350,117,0.0,36,0,1981-07-18 00:00:00 -15451,350,204,0.0,35,0,1981-07-18 00:00:00 -15452,350,159,0.0,29,0,1981-07-18 00:00:00 -15453,350,219,0.0,37,0,1981-07-18 00:00:00 -15454,350,198,43.0,1,2,1981-07-18 00:00:00 -15455,350,116,13.0,7,1,1981-07-18 00:00:00 -15456,350,172,8.0,10,0,1981-07-18 00:00:00 -15457,350,216,0.0,28,0,1981-07-18 00:00:00 -15458,350,202,21.0,4,2,1981-07-18 00:00:00 -15459,350,206,3.0,16,0,1981-07-18 00:00:00 -15460,350,186,19.0,6,1,1981-07-18 00:00:00 -15461,350,157,8.0,9,0,1981-07-18 00:00:00 -15462,350,174,1.0,17,0,1981-07-18 00:00:00 -15463,350,191,0.0,21,0,1981-07-18 00:00:00 -15464,350,162,5.0,13,0,1981-07-18 00:00:00 -15465,350,201,7.0,11,0,1981-07-18 00:00:00 -15466,350,196,0.0,20,0,1981-07-18 00:00:00 -15467,350,175,4.0,15,0,1981-07-18 00:00:00 -15468,350,151,0.0,23,0,1981-07-18 00:00:00 -15469,350,171,21.0,5,0,1981-07-18 00:00:00 -15470,350,176,0.0,24,0,1981-07-18 00:00:00 -15471,350,135,0.0,27,0,1981-07-18 00:00:00 -15472,350,118,10.0,8,0,1981-07-18 00:00:00 -15473,350,212,0.0,32,0,1981-07-18 00:00:00 -15474,350,94,5.0,12,0,1981-07-18 00:00:00 -15475,350,211,5.0,14,0,1981-07-18 00:00:00 -15476,351,191,0.0,21,0,1981-08-02 00:00:00 -15477,351,213,0.0,34,0,1981-08-02 00:00:00 -15478,351,157,10.0,9,0,1981-08-02 00:00:00 -15479,351,206,3.0,16,0,1981-08-02 00:00:00 -15480,351,198,43.0,1,2,1981-08-02 00:00:00 -15481,351,117,0.0,36,0,1981-08-02 00:00:00 -15482,351,214,0.0,33,0,1981-08-02 00:00:00 -15483,351,186,20.0,6,1,1981-08-02 00:00:00 -15484,351,135,0.0,27,0,1981-08-02 00:00:00 -15485,351,116,19.0,7,1,1981-08-02 00:00:00 -15486,351,193,0.0,30,0,1981-08-02 00:00:00 -15487,351,162,5.0,14,0,1981-08-02 00:00:00 -15488,351,174,1.0,17,0,1981-08-02 00:00:00 -15489,351,136,35.0,2,3,1981-08-02 00:00:00 -15490,351,201,7.0,12,0,1981-08-02 00:00:00 -15491,351,175,4.0,15,0,1981-08-02 00:00:00 -15492,351,219,0.0,37,0,1981-08-02 00:00:00 -15493,351,196,0.0,20,0,1981-08-02 00:00:00 -15494,351,204,0.0,35,0,1981-08-02 00:00:00 -15495,351,151,0.0,23,0,1981-08-02 00:00:00 -15496,351,159,0.0,29,0,1981-08-02 00:00:00 -15497,351,104,0.0,26,0,1981-08-02 00:00:00 -15498,351,200,1.0,19,0,1981-08-02 00:00:00 -15499,351,218,0.0,31,0,1981-08-02 00:00:00 -15500,351,217,0.0,38,0,1981-08-02 00:00:00 -15501,351,216,0.0,28,0,1981-08-02 00:00:00 -15502,351,215,0.0,25,0,1981-08-02 00:00:00 -15503,351,211,8.0,10,0,1981-08-02 00:00:00 -15504,351,205,0.0,22,0,1981-08-02 00:00:00 -15505,351,172,8.0,11,0,1981-08-02 00:00:00 -15506,351,202,21.0,5,2,1981-08-02 00:00:00 -15507,351,94,5.0,13,0,1981-08-02 00:00:00 -15508,351,212,0.0,32,0,1981-08-02 00:00:00 -15509,351,118,10.0,8,0,1981-08-02 00:00:00 -15510,351,176,0.0,24,0,1981-08-02 00:00:00 -15511,351,171,25.0,3,0,1981-08-02 00:00:00 -15512,351,109,1.0,18,0,1981-08-02 00:00:00 -15513,351,177,24.0,4,1,1981-08-02 00:00:00 -15514,352,116,19.0,7,1,1981-08-16 00:00:00 -15515,352,198,45.0,1,2,1981-08-16 00:00:00 -15516,352,177,27.0,4,1,1981-08-16 00:00:00 -15517,352,109,1.0,18,0,1981-08-16 00:00:00 -15518,352,213,0.0,34,0,1981-08-16 00:00:00 -15519,352,205,0.0,21,0,1981-08-16 00:00:00 -15520,352,214,0.0,33,0,1981-08-16 00:00:00 -15521,352,215,0.0,25,0,1981-08-16 00:00:00 -15522,352,216,0.0,28,0,1981-08-16 00:00:00 -15523,352,217,0.0,38,0,1981-08-16 00:00:00 -15524,352,218,0.0,31,0,1981-08-16 00:00:00 -15525,352,200,1.0,19,0,1981-08-16 00:00:00 -15526,352,104,0.0,26,0,1981-08-16 00:00:00 -15527,352,117,0.0,36,0,1981-08-16 00:00:00 -15528,352,204,0.0,35,0,1981-08-16 00:00:00 -15529,352,159,0.0,29,0,1981-08-16 00:00:00 -15530,352,219,0.0,37,0,1981-08-16 00:00:00 -15531,352,172,8.0,12,0,1981-08-16 00:00:00 -15532,352,186,21.0,6,1,1981-08-16 00:00:00 -15533,352,193,0.0,30,0,1981-08-16 00:00:00 -15534,352,94,5.0,14,0,1981-08-16 00:00:00 -15535,352,202,21.0,5,2,1981-08-16 00:00:00 -15536,352,136,39.0,2,3,1981-08-16 00:00:00 -15537,352,206,3.0,16,0,1981-08-16 00:00:00 -15538,352,157,10.0,10,0,1981-08-16 00:00:00 -15539,352,174,1.0,17,0,1981-08-16 00:00:00 -15540,352,191,0.0,22,0,1981-08-16 00:00:00 -15541,352,175,4.0,15,0,1981-08-16 00:00:00 -15542,352,201,7.0,13,0,1981-08-16 00:00:00 -15543,352,162,11.0,8,0,1981-08-16 00:00:00 -15544,352,211,8.0,11,0,1981-08-16 00:00:00 -15545,352,151,0.0,23,0,1981-08-16 00:00:00 -15546,352,171,34.0,3,1,1981-08-16 00:00:00 -15547,352,176,0.0,24,0,1981-08-16 00:00:00 -15548,352,135,0.0,27,0,1981-08-16 00:00:00 -15549,352,118,10.0,9,0,1981-08-16 00:00:00 -15550,352,212,0.0,32,0,1981-08-16 00:00:00 -15551,352,196,0.0,20,0,1981-08-16 00:00:00 -15552,353,172,10.0,12,0,1981-08-30 00:00:00 -15553,353,215,0.0,22,0,1981-08-30 00:00:00 -15554,353,116,28.0,5,2,1981-08-30 00:00:00 -15555,353,109,1.0,18,0,1981-08-30 00:00:00 -15556,353,213,0.0,34,0,1981-08-30 00:00:00 -15557,353,205,0.0,23,0,1981-08-30 00:00:00 -15558,353,214,0.0,33,0,1981-08-30 00:00:00 -15559,353,193,1.0,20,0,1981-08-30 00:00:00 -15560,353,219,0.0,37,0,1981-08-30 00:00:00 -15561,353,217,0.0,38,0,1981-08-30 00:00:00 -15562,353,218,0.0,31,0,1981-08-30 00:00:00 -15563,353,200,1.0,19,0,1981-08-30 00:00:00 -15564,353,104,0.0,26,0,1981-08-30 00:00:00 -15565,353,117,0.0,36,0,1981-08-30 00:00:00 -15566,353,204,0.0,35,0,1981-08-30 00:00:00 -15567,353,159,0.0,30,0,1981-08-30 00:00:00 -15568,353,186,21.0,7,1,1981-08-30 00:00:00 -15569,353,216,0.0,29,0,1981-08-30 00:00:00 -15570,353,202,21.0,6,2,1981-08-30 00:00:00 -15571,353,201,7.0,13,0,1981-08-30 00:00:00 -15572,353,212,0.0,32,0,1981-08-30 00:00:00 -15573,353,94,5.0,14,0,1981-08-30 00:00:00 -15574,353,177,31.0,4,1,1981-08-30 00:00:00 -15575,353,198,45.0,2,2,1981-08-30 00:00:00 -15576,353,136,45.0,1,3,1981-08-30 00:00:00 -15577,353,206,3.0,16,0,1981-08-30 00:00:00 -15578,353,157,10.0,11,0,1981-08-30 00:00:00 -15579,353,191,0.0,24,0,1981-08-30 00:00:00 -15580,353,162,11.0,8,0,1981-08-30 00:00:00 -15581,353,174,1.0,17,0,1981-08-30 00:00:00 -15582,353,196,0.0,21,0,1981-08-30 00:00:00 -15583,353,211,11.0,9,0,1981-08-30 00:00:00 -15584,353,151,0.0,25,0,1981-08-30 00:00:00 -15585,353,171,34.0,3,1,1981-08-30 00:00:00 -15586,353,176,0.0,27,0,1981-08-30 00:00:00 -15587,353,135,0.0,28,0,1981-08-30 00:00:00 -15588,353,118,10.0,10,0,1981-08-30 00:00:00 -15589,353,175,4.0,15,0,1981-08-30 00:00:00 -15590,354,172,13.0,8,0,1981-09-13 00:00:00 -15591,354,215,0.0,22,0,1981-09-13 00:00:00 -15592,354,116,37.0,3,3,1981-09-13 00:00:00 -15593,354,109,1.0,17,0,1981-09-13 00:00:00 -15594,354,213,0.0,35,0,1981-09-13 00:00:00 -15595,354,205,0.0,23,0,1981-09-13 00:00:00 -15596,354,214,0.0,34,0,1981-09-13 00:00:00 -15597,354,193,1.0,20,0,1981-09-13 00:00:00 -15598,354,219,0.0,37,0,1981-09-13 00:00:00 -15599,354,217,0.0,38,0,1981-09-13 00:00:00 -15600,354,218,0.0,32,0,1981-09-13 00:00:00 -15601,354,200,1.0,19,0,1981-09-13 00:00:00 -15602,354,104,0.0,26,0,1981-09-13 00:00:00 -15603,354,117,0.0,36,0,1981-09-13 00:00:00 -15604,354,204,0.0,28,0,1981-09-13 00:00:00 -15605,354,159,0.0,31,0,1981-09-13 00:00:00 -15606,354,186,21.0,7,1,1981-09-13 00:00:00 -15607,354,216,0.0,30,0,1981-09-13 00:00:00 -15608,354,202,21.0,6,2,1981-09-13 00:00:00 -15609,354,196,0.0,21,0,1981-09-13 00:00:00 -15610,354,212,0.0,33,0,1981-09-13 00:00:00 -15611,354,177,37.0,4,1,1981-09-13 00:00:00 -15612,354,198,49.0,1,2,1981-09-13 00:00:00 -15613,354,136,46.0,2,3,1981-09-13 00:00:00 -15614,354,206,3.0,16,0,1981-09-13 00:00:00 -15615,354,157,10.0,12,0,1981-09-13 00:00:00 -15616,354,174,1.0,18,0,1981-09-13 00:00:00 -15617,354,191,0.0,24,0,1981-09-13 00:00:00 -15618,354,162,11.0,9,0,1981-09-13 00:00:00 -15619,354,94,5.0,14,0,1981-09-13 00:00:00 -15620,354,201,9.0,13,0,1981-09-13 00:00:00 -15621,354,211,11.0,10,0,1981-09-13 00:00:00 -15622,354,151,0.0,25,0,1981-09-13 00:00:00 -15623,354,171,34.0,5,1,1981-09-13 00:00:00 -15624,354,176,0.0,27,0,1981-09-13 00:00:00 -15625,354,135,0.0,29,0,1981-09-13 00:00:00 -15626,354,118,10.0,11,0,1981-09-13 00:00:00 -15627,354,175,4.0,15,0,1981-09-13 00:00:00 -15628,355,172,14.0,8,0,1981-09-27 00:00:00 -15629,355,116,37.0,4,3,1981-09-27 00:00:00 -15630,355,109,1.0,18,0,1981-09-27 00:00:00 -15631,355,213,0.0,35,0,1981-09-27 00:00:00 -15632,355,205,0.0,23,0,1981-09-27 00:00:00 -15633,355,214,0.0,34,0,1981-09-27 00:00:00 -15634,355,215,0.0,24,0,1981-09-27 00:00:00 -15635,355,193,1.0,21,0,1981-09-27 00:00:00 -15636,355,200,1.0,20,0,1981-09-27 00:00:00 -15637,355,217,0.0,39,0,1981-09-27 00:00:00 -15638,355,218,0.0,32,0,1981-09-27 00:00:00 -15639,355,104,0.0,26,0,1981-09-27 00:00:00 -15640,355,117,0.0,36,0,1981-09-27 00:00:00 -15641,355,204,0.0,28,0,1981-09-27 00:00:00 -15642,355,159,0.0,31,0,1981-09-27 00:00:00 -15643,355,186,27.0,6,1,1981-09-27 00:00:00 -15644,355,197,0.0,37,0,1981-09-27 00:00:00 -15645,355,216,0.0,30,0,1981-09-27 00:00:00 -15646,355,219,0.0,38,0,1981-09-27 00:00:00 -15647,355,202,25.0,7,2,1981-09-27 00:00:00 -15648,355,212,0.0,33,0,1981-09-27 00:00:00 -15649,355,94,5.0,14,0,1981-09-27 00:00:00 -15650,355,177,37.0,5,1,1981-09-27 00:00:00 -15651,355,198,49.0,1,2,1981-09-27 00:00:00 -15652,355,136,48.0,2,3,1981-09-27 00:00:00 -15653,355,206,3.0,16,0,1981-09-27 00:00:00 -15654,355,174,1.0,19,0,1981-09-27 00:00:00 -15655,355,191,0.0,25,0,1981-09-27 00:00:00 -15656,355,162,11.0,9,0,1981-09-27 00:00:00 -15657,355,157,10.0,12,0,1981-09-27 00:00:00 -15658,355,201,9.0,13,0,1981-09-27 00:00:00 -15659,355,175,4.0,15,0,1981-09-27 00:00:00 -15660,355,135,0.0,29,0,1981-09-27 00:00:00 -15661,355,176,0.0,27,0,1981-09-27 00:00:00 -15662,355,171,43.0,3,2,1981-09-27 00:00:00 -15663,355,118,10.0,11,0,1981-09-27 00:00:00 -15664,355,211,11.0,10,0,1981-09-27 00:00:00 -15665,355,196,0.0,22,0,1981-09-27 00:00:00 -15666,355,151,3.0,17,0,1981-09-27 00:00:00 -15667,356,193,1.0,21,0,1981-10-17 00:00:00 -15668,356,116,43.0,5,3,1981-10-17 00:00:00 -15669,356,109,1.0,18,0,1981-10-17 00:00:00 -15670,356,213,0.0,36,0,1981-10-17 00:00:00 -15671,356,205,0.0,23,0,1981-10-17 00:00:00 -15672,356,214,0.0,35,0,1981-10-17 00:00:00 -15673,356,215,0.0,24,0,1981-10-17 00:00:00 -15674,356,216,0.0,30,0,1981-10-17 00:00:00 -15675,356,172,14.0,8,0,1981-10-17 00:00:00 -15676,356,218,0.0,32,0,1981-10-17 00:00:00 -15677,356,200,1.0,20,0,1981-10-17 00:00:00 -15678,356,104,0.0,27,0,1981-10-17 00:00:00 -15679,356,117,0.0,33,0,1981-10-17 00:00:00 -15680,356,204,0.0,28,0,1981-10-17 00:00:00 -15681,356,159,0.0,31,0,1981-10-17 00:00:00 -15682,356,219,0.0,38,0,1981-10-17 00:00:00 -15683,356,197,0.0,37,0,1981-10-17 00:00:00 -15684,356,217,0.0,39,0,1981-10-17 00:00:00 -15685,356,186,27.0,6,1,1981-10-17 00:00:00 -15686,356,174,1.0,19,0,1981-10-17 00:00:00 -15687,356,94,8.0,14,0,1981-10-17 00:00:00 -15688,356,157,10.0,12,0,1981-10-17 00:00:00 -15689,356,206,3.0,17,0,1981-10-17 00:00:00 -15690,356,136,50.0,1,3,1981-10-17 00:00:00 -15691,356,177,46.0,3,2,1981-10-17 00:00:00 -15692,356,202,25.0,7,2,1981-10-17 00:00:00 -15693,356,191,0.0,25,0,1981-10-17 00:00:00 -15694,356,162,11.0,9,0,1981-10-17 00:00:00 -15695,356,175,4.0,16,0,1981-10-17 00:00:00 -15696,356,198,49.0,2,2,1981-10-17 00:00:00 -15697,356,196,0.0,22,0,1981-10-17 00:00:00 -15698,356,211,11.0,10,0,1981-10-17 00:00:00 -15699,356,151,7.0,15,0,1981-10-17 00:00:00 -15700,356,171,44.0,4,2,1981-10-17 00:00:00 -15701,356,176,0.0,26,0,1981-10-17 00:00:00 -15702,356,135,0.0,29,0,1981-10-17 00:00:00 -15703,356,118,10.0,11,0,1981-10-17 00:00:00 -15704,356,212,0.0,34,0,1981-10-17 00:00:00 -15705,356,201,9.0,13,0,1981-10-17 00:00:00 -15706,357,157,0.0,22,0,1982-01-23 00:00:00 -15707,357,202,0.0,23,0,1982-01-23 00:00:00 -15708,357,136,0.0,24,0,1982-01-23 00:00:00 -15709,357,94,0.0,25,0,1982-01-23 00:00:00 -15710,357,196,0.0,26,0,1982-01-23 00:00:00 -15711,357,194,0.0,30,0,1982-01-23 00:00:00 -15712,357,203,0.0,28,0,1982-01-23 00:00:00 -15713,357,204,0.0,29,0,1982-01-23 00:00:00 -15714,357,169,0.0,31,0,1982-01-23 00:00:00 -15715,357,118,0.0,21,0,1982-01-23 00:00:00 -15716,357,183,0.0,27,0,1982-01-23 00:00:00 -15717,357,117,0.0,20,0,1982-01-23 00:00:00 -15718,357,171,0.0,19,0,1982-01-23 00:00:00 -15719,357,201,0.0,18,0,1982-01-23 00:00:00 -15720,357,198,6.0,2,0,1982-01-23 00:00:00 -15721,357,162,4.0,3,0,1982-01-23 00:00:00 -15722,357,181,3.0,4,0,1982-01-23 00:00:00 -15723,357,176,2.0,5,0,1982-01-23 00:00:00 -15724,357,186,1.0,6,0,1982-01-23 00:00:00 -15725,357,116,9.0,1,1,1982-01-23 00:00:00 -15726,357,172,0.0,8,0,1982-01-23 00:00:00 -15727,357,193,0.0,9,0,1982-01-23 00:00:00 -15728,357,104,0.0,7,0,1982-01-23 00:00:00 -15729,357,151,0.0,11,0,1982-01-23 00:00:00 -15730,357,199,0.0,12,0,1982-01-23 00:00:00 -15731,357,109,0.0,13,0,1982-01-23 00:00:00 -15732,357,205,0.0,14,0,1982-01-23 00:00:00 -15733,357,195,0.0,15,0,1982-01-23 00:00:00 -15734,357,200,0.0,16,0,1982-01-23 00:00:00 -15735,357,191,0.0,17,0,1982-01-23 00:00:00 -15736,357,180,0.0,10,0,1982-01-23 00:00:00 -15737,358,171,0.0,24,0,1982-03-21 00:00:00 -15738,358,117,0.0,25,0,1982-03-21 00:00:00 -15739,358,118,0.0,22,0,1982-03-21 00:00:00 -15740,358,157,0.0,26,0,1982-03-21 00:00:00 -15741,358,136,0.0,27,0,1982-03-21 00:00:00 -15742,358,203,0.0,30,0,1982-03-21 00:00:00 -15743,358,196,0.0,15,0,1982-03-21 00:00:00 -15744,358,183,0.0,16,0,1982-03-21 00:00:00 -15745,358,201,1.0,10,0,1982-03-21 00:00:00 -15746,358,204,0.0,29,0,1982-03-21 00:00:00 -15747,358,194,0.0,31,0,1982-03-21 00:00:00 -15748,358,169,0.0,28,0,1982-03-21 00:00:00 -15749,358,94,4.0,5,0,1982-03-21 00:00:00 -15750,358,191,0.0,21,0,1982-03-21 00:00:00 -15751,358,202,0.0,23,0,1982-03-21 00:00:00 -15752,358,195,0.0,20,0,1982-03-21 00:00:00 -15753,358,116,18.0,1,2,1982-03-21 00:00:00 -15754,358,198,6.0,3,0,1982-03-21 00:00:00 -15755,358,162,4.0,4,0,1982-03-21 00:00:00 -15756,358,181,3.0,7,0,1982-03-21 00:00:00 -15757,358,186,7.0,2,0,1982-03-21 00:00:00 -15758,358,104,3.0,6,0,1982-03-21 00:00:00 -15759,358,176,2.0,9,0,1982-03-21 00:00:00 -15760,358,193,0.0,14,0,1982-03-21 00:00:00 -15761,358,180,2.0,8,0,1982-03-21 00:00:00 -15762,358,151,0.0,17,0,1982-03-21 00:00:00 -15763,358,199,0.0,12,0,1982-03-21 00:00:00 -15764,358,109,0.0,18,0,1982-03-21 00:00:00 -15765,358,205,0.0,19,0,1982-03-21 00:00:00 -15766,358,172,0.0,13,0,1982-03-21 00:00:00 -15767,358,200,0.0,11,0,1982-03-21 00:00:00 -15768,359,136,0.0,28,0,1982-04-04 00:00:00 -15769,359,171,0.0,26,0,1982-04-04 00:00:00 -15770,359,117,0.0,29,0,1982-04-04 00:00:00 -15771,359,118,4.0,8,0,1982-04-04 00:00:00 -15772,359,157,0.0,23,0,1982-04-04 00:00:00 -15773,359,202,0.0,27,0,1982-04-04 00:00:00 -15774,359,206,0.0,30,0,1982-04-04 00:00:00 -15775,359,183,0.0,18,0,1982-04-04 00:00:00 -15776,359,203,0.0,32,0,1982-04-04 00:00:00 -15777,359,204,0.0,24,0,1982-04-04 00:00:00 -15778,359,194,0.0,25,0,1982-04-04 00:00:00 -15779,359,169,0.0,31,0,1982-04-04 00:00:00 -15780,359,201,1.0,12,0,1982-04-04 00:00:00 -15781,359,196,0.0,17,0,1982-04-04 00:00:00 -15782,359,191,0.0,22,0,1982-04-04 00:00:00 -15783,359,94,4.0,7,0,1982-04-04 00:00:00 -15784,359,195,0.0,15,0,1982-04-04 00:00:00 -15785,359,200,0.0,13,0,1982-04-04 00:00:00 -15786,359,198,6.0,5,0,1982-04-04 00:00:00 -15787,359,162,4.0,9,0,1982-04-04 00:00:00 -15788,359,181,12.0,2,1,1982-04-04 00:00:00 -15789,359,176,8.0,3,0,1982-04-04 00:00:00 -15790,359,186,8.0,4,0,1982-04-04 00:00:00 -15791,359,104,6.0,6,0,1982-04-04 00:00:00 -15792,359,116,18.0,1,2,1982-04-04 00:00:00 -15793,359,193,0.0,16,0,1982-04-04 00:00:00 -15794,359,180,2.0,11,0,1982-04-04 00:00:00 -15795,359,151,0.0,19,0,1982-04-04 00:00:00 -15796,359,199,0.0,14,0,1982-04-04 00:00:00 -15797,359,109,0.0,20,0,1982-04-04 00:00:00 -15798,359,205,0.0,21,0,1982-04-04 00:00:00 -15799,359,172,2.0,10,0,1982-04-04 00:00:00 -15800,360,171,0.0,30,0,1982-04-25 00:00:00 -15801,360,117,0.0,28,0,1982-04-25 00:00:00 -15802,360,118,4.0,11,0,1982-04-25 00:00:00 -15803,360,157,0.0,26,0,1982-04-25 00:00:00 -15804,360,202,6.0,7,0,1982-04-25 00:00:00 -15805,360,196,3.0,12,0,1982-04-25 00:00:00 -15806,360,94,4.0,9,0,1982-04-25 00:00:00 -15807,360,183,0.0,19,0,1982-04-25 00:00:00 -15808,360,203,0.0,25,0,1982-04-25 00:00:00 -15809,360,204,0.0,27,0,1982-04-25 00:00:00 -15810,360,194,0.0,29,0,1982-04-25 00:00:00 -15811,360,201,10.0,3,1,1982-04-25 00:00:00 -15812,360,136,0.0,31,0,1982-04-25 00:00:00 -15813,360,191,0.0,23,0,1982-04-25 00:00:00 -15814,360,193,2.0,14,0,1982-04-25 00:00:00 -15815,360,195,0.0,18,0,1982-04-25 00:00:00 -15816,360,205,0.0,22,0,1982-04-25 00:00:00 -15817,360,109,0.0,21,0,1982-04-25 00:00:00 -15818,360,199,0.0,17,0,1982-04-25 00:00:00 -15819,360,151,0.0,20,0,1982-04-25 00:00:00 -15820,360,180,2.0,15,0,1982-04-25 00:00:00 -15821,360,172,2.0,13,0,1982-04-25 00:00:00 -15822,360,104,10.0,4,0,1982-04-25 00:00:00 -15823,360,186,8.0,6,0,1982-04-25 00:00:00 -15824,360,176,8.0,5,0,1982-04-25 00:00:00 -15825,360,181,12.0,2,1,1982-04-25 00:00:00 -15826,360,162,4.0,10,0,1982-04-25 00:00:00 -15827,360,198,6.0,8,0,1982-04-25 00:00:00 -15828,360,169,0.0,24,0,1982-04-25 00:00:00 -15829,360,200,0.0,16,0,1982-04-25 00:00:00 -15830,360,206,0.0,32,0,1982-04-25 00:00:00 -15831,360,116,18.0,1,2,1982-04-25 00:00:00 -15832,361,169,0.0,28,0,1982-05-09 00:00:00 -15833,361,200,0.0,19,0,1982-05-09 00:00:00 -15834,361,191,1.0,18,0,1982-05-09 00:00:00 -15835,361,201,10.0,5,1,1982-05-09 00:00:00 -15836,361,171,0.0,23,0,1982-05-09 00:00:00 -15837,361,117,0.0,31,0,1982-05-09 00:00:00 -15838,361,118,4.0,13,0,1982-05-09 00:00:00 -15839,361,157,4.0,12,0,1982-05-09 00:00:00 -15840,361,202,6.0,7,0,1982-05-09 00:00:00 -15841,361,136,2.0,17,0,1982-05-09 00:00:00 -15842,361,94,4.0,10,0,1982-05-09 00:00:00 -15843,361,196,3.0,14,0,1982-05-09 00:00:00 -15844,361,183,0.0,24,0,1982-05-09 00:00:00 -15845,361,203,0.0,29,0,1982-05-09 00:00:00 -15846,361,204,0.0,30,0,1982-05-09 00:00:00 -15847,361,194,0.0,32,0,1982-05-09 00:00:00 -15848,361,195,0.0,22,0,1982-05-09 00:00:00 -15849,361,205,0.0,27,0,1982-05-09 00:00:00 -15850,361,206,0.0,33,0,1982-05-09 00:00:00 -15851,361,199,0.0,21,0,1982-05-09 00:00:00 -15852,361,207,0.0,35,0,1982-05-09 00:00:00 -15853,361,175,0.0,20,0,1982-05-09 00:00:00 -15854,361,109,0.0,26,0,1982-05-09 00:00:00 -15855,361,116,18.0,1,2,1982-05-09 00:00:00 -15856,361,198,6.0,8,0,1982-05-09 00:00:00 -15857,361,162,4.0,11,0,1982-05-09 00:00:00 -15858,361,181,12.0,4,1,1982-05-09 00:00:00 -15859,361,135,0.0,34,0,1982-05-09 00:00:00 -15860,361,186,17.0,2,1,1982-05-09 00:00:00 -15861,361,104,10.0,6,0,1982-05-09 00:00:00 -15862,361,172,5.0,9,0,1982-05-09 00:00:00 -15863,361,193,2.0,15,0,1982-05-09 00:00:00 -15864,361,180,2.0,16,0,1982-05-09 00:00:00 -15865,361,151,0.0,25,0,1982-05-09 00:00:00 -15866,361,176,14.0,3,0,1982-05-09 00:00:00 -15867,362,157,4.0,14,0,1982-05-23 00:00:00 -15868,362,202,6.0,10,0,1982-05-23 00:00:00 -15869,362,136,2.0,18,0,1982-05-23 00:00:00 -15870,362,94,7.0,8,0,1982-05-23 00:00:00 -15871,362,196,3.0,15,0,1982-05-23 00:00:00 -15872,362,183,0.0,27,0,1982-05-23 00:00:00 -15873,362,203,0.0,30,0,1982-05-23 00:00:00 -15874,362,169,0.0,29,0,1982-05-23 00:00:00 -15875,362,194,0.0,32,0,1982-05-23 00:00:00 -15876,362,206,0.0,33,0,1982-05-23 00:00:00 -15877,362,175,0.0,21,0,1982-05-23 00:00:00 -15878,362,135,0.0,34,0,1982-05-23 00:00:00 -15879,362,207,0.0,35,0,1982-05-23 00:00:00 -15880,362,118,13.0,5,1,1982-05-23 00:00:00 -15881,362,204,0.0,25,0,1982-05-23 00:00:00 -15882,362,171,0.0,26,0,1982-05-23 00:00:00 -15883,362,117,0.0,31,0,1982-05-23 00:00:00 -15884,362,116,18.0,1,2,1982-05-23 00:00:00 -15885,362,198,6.0,11,0,1982-05-23 00:00:00 -15886,362,201,16.0,3,1,1982-05-23 00:00:00 -15887,362,162,4.0,13,0,1982-05-23 00:00:00 -15888,362,181,12.0,6,1,1982-05-23 00:00:00 -15889,362,176,14.0,4,0,1982-05-23 00:00:00 -15890,362,186,17.0,2,1,1982-05-23 00:00:00 -15891,362,172,7.0,9,0,1982-05-23 00:00:00 -15892,362,193,2.0,16,0,1982-05-23 00:00:00 -15893,362,104,10.0,7,0,1982-05-23 00:00:00 -15894,362,151,0.0,28,0,1982-05-23 00:00:00 -15895,362,199,0.0,23,0,1982-05-23 00:00:00 -15896,362,109,4.0,12,0,1982-05-23 00:00:00 -15897,362,205,1.0,19,0,1982-05-23 00:00:00 -15898,362,195,0.0,24,0,1982-05-23 00:00:00 -15899,362,200,0.0,22,0,1982-05-23 00:00:00 -15900,362,191,1.0,20,0,1982-05-23 00:00:00 -15901,362,180,2.0,17,0,1982-05-23 00:00:00 -15902,363,196,3.0,15,0,1982-06-06 00:00:00 -15903,363,157,10.0,7,0,1982-06-06 00:00:00 -15904,363,202,6.0,11,0,1982-06-06 00:00:00 -15905,363,136,2.0,19,0,1982-06-06 00:00:00 -15906,363,94,7.0,9,0,1982-06-06 00:00:00 -15907,363,183,0.0,27,0,1982-06-06 00:00:00 -15908,363,118,13.0,5,1,1982-06-06 00:00:00 -15909,363,204,0.0,26,0,1982-06-06 00:00:00 -15910,363,194,0.0,32,0,1982-06-06 00:00:00 -15911,363,169,0.0,29,0,1982-06-06 00:00:00 -15912,363,206,0.0,33,0,1982-06-06 00:00:00 -15913,363,175,0.0,23,0,1982-06-06 00:00:00 -15914,363,135,0.0,34,0,1982-06-06 00:00:00 -15915,363,207,0.0,35,0,1982-06-06 00:00:00 -15916,363,203,0.0,30,0,1982-06-06 00:00:00 -15917,363,117,0.0,31,0,1982-06-06 00:00:00 -15918,363,199,0.0,22,0,1982-06-06 00:00:00 -15919,363,201,20.0,2,1,1982-06-06 00:00:00 -15920,363,171,1.0,20,0,1982-06-06 00:00:00 -15921,363,116,18.0,3,2,1982-06-06 00:00:00 -15922,363,162,4.0,13,0,1982-06-06 00:00:00 -15923,363,181,12.0,6,1,1982-06-06 00:00:00 -15924,363,176,17.0,4,0,1982-06-06 00:00:00 -15925,363,186,26.0,1,2,1982-06-06 00:00:00 -15926,363,104,10.0,8,0,1982-06-06 00:00:00 -15927,363,172,7.0,10,0,1982-06-06 00:00:00 -15928,363,198,6.0,12,0,1982-06-06 00:00:00 -15929,363,180,2.0,18,0,1982-06-06 00:00:00 -15930,363,151,0.0,28,0,1982-06-06 00:00:00 -15931,363,109,4.0,14,0,1982-06-06 00:00:00 -15932,363,205,3.0,16,0,1982-06-06 00:00:00 -15933,363,195,0.0,25,0,1982-06-06 00:00:00 -15934,363,193,2.0,17,0,1982-06-06 00:00:00 -15935,363,191,1.0,21,0,1982-06-06 00:00:00 -15936,363,200,0.0,24,0,1982-06-06 00:00:00 -15937,364,157,10.0,8,0,1982-06-13 00:00:00 -15938,364,202,6.0,12,0,1982-06-13 00:00:00 -15939,364,136,11.0,7,1,1982-06-13 00:00:00 -15940,364,94,7.0,11,0,1982-06-13 00:00:00 -15941,364,196,3.0,16,0,1982-06-13 00:00:00 -15942,364,183,0.0,27,0,1982-06-13 00:00:00 -15943,364,204,0.0,26,0,1982-06-13 00:00:00 -15944,364,118,19.0,3,1,1982-06-13 00:00:00 -15945,364,194,0.0,32,0,1982-06-13 00:00:00 -15946,364,169,0.0,29,0,1982-06-13 00:00:00 -15947,364,206,0.0,33,0,1982-06-13 00:00:00 -15948,364,175,2.0,18,0,1982-06-13 00:00:00 -15949,364,135,0.0,34,0,1982-06-13 00:00:00 -15950,364,207,0.0,36,0,1982-06-13 00:00:00 -15951,364,203,0.0,30,0,1982-06-13 00:00:00 -15952,364,117,0.0,31,0,1982-06-13 00:00:00 -15953,364,200,0.0,24,0,1982-06-13 00:00:00 -15954,364,201,20.0,2,1,1982-06-13 00:00:00 -15955,364,208,0.0,35,0,1982-06-13 00:00:00 -15956,364,116,18.0,4,2,1982-06-13 00:00:00 -15957,364,198,6.0,13,0,1982-06-13 00:00:00 -15958,364,162,4.0,15,0,1982-06-13 00:00:00 -15959,364,181,12.0,6,1,1982-06-13 00:00:00 -15960,364,176,17.0,5,0,1982-06-13 00:00:00 -15961,364,186,30.0,1,2,1982-06-13 00:00:00 -15962,364,104,10.0,9,0,1982-06-13 00:00:00 -15963,364,193,2.0,19,0,1982-06-13 00:00:00 -15964,364,180,2.0,20,0,1982-06-13 00:00:00 -15965,364,199,0.0,23,0,1982-06-13 00:00:00 -15966,364,109,5.0,14,0,1982-06-13 00:00:00 -15967,364,205,3.0,17,0,1982-06-13 00:00:00 -15968,364,195,0.0,25,0,1982-06-13 00:00:00 -15969,364,191,1.0,22,0,1982-06-13 00:00:00 -15970,364,171,1.0,21,0,1982-06-13 00:00:00 -15971,364,151,0.0,28,0,1982-06-13 00:00:00 -15972,364,172,10.0,10,0,1982-06-13 00:00:00 -15973,365,117,0.0,32,0,1982-07-03 00:00:00 -15974,365,136,17.0,6,1,1982-07-03 00:00:00 -15975,365,202,6.0,12,0,1982-07-03 00:00:00 -15976,365,157,10.0,8,0,1982-07-03 00:00:00 -15977,365,118,19.0,4,1,1982-07-03 00:00:00 -15978,365,162,4.0,16,0,1982-07-03 00:00:00 -15979,365,171,1.0,22,0,1982-07-03 00:00:00 -15980,365,201,29.0,2,2,1982-07-03 00:00:00 -15981,365,191,1.0,23,0,1982-07-03 00:00:00 -15982,365,200,0.0,25,0,1982-07-03 00:00:00 -15983,365,195,0.0,26,0,1982-07-03 00:00:00 -15984,365,205,5.0,15,0,1982-07-03 00:00:00 -15985,365,109,5.0,14,0,1982-07-03 00:00:00 -15986,365,199,0.0,24,0,1982-07-03 00:00:00 -15987,365,151,0.0,29,0,1982-07-03 00:00:00 -15988,365,180,2.0,20,0,1982-07-03 00:00:00 -15989,365,193,2.0,19,0,1982-07-03 00:00:00 -15990,365,172,10.0,10,0,1982-07-03 00:00:00 -15991,365,104,10.0,9,0,1982-07-03 00:00:00 -15992,365,186,30.0,1,2,1982-07-03 00:00:00 -15993,365,94,7.0,11,0,1982-07-03 00:00:00 -15994,365,176,21.0,3,0,1982-07-03 00:00:00 -15995,365,196,3.0,17,0,1982-07-03 00:00:00 -15996,365,203,0.0,31,0,1982-07-03 00:00:00 -15997,365,116,18.0,5,2,1982-07-03 00:00:00 -15998,365,198,6.0,13,0,1982-07-03 00:00:00 -15999,365,183,1.0,21,0,1982-07-03 00:00:00 -16000,365,174,0.0,28,0,1982-07-03 00:00:00 -16001,365,208,0.0,36,0,1982-07-03 00:00:00 -16002,365,207,0.0,37,0,1982-07-03 00:00:00 -16003,365,89,0.0,38,0,1982-07-03 00:00:00 -16004,365,175,2.0,18,0,1982-07-03 00:00:00 -16005,365,206,0.0,35,0,1982-07-03 00:00:00 -16006,365,169,0.0,30,0,1982-07-03 00:00:00 -16007,365,194,0.0,33,0,1982-07-03 00:00:00 -16008,365,204,0.0,27,0,1982-07-03 00:00:00 -16009,365,135,0.0,34,0,1982-07-03 00:00:00 -16010,365,181,15.0,7,1,1982-07-03 00:00:00 -16011,366,194,0.0,33,0,1982-07-18 00:00:00 -16012,366,204,0.0,28,0,1982-07-18 00:00:00 -16013,366,203,0.0,31,0,1982-07-18 00:00:00 -16014,366,183,1.0,22,0,1982-07-18 00:00:00 -16015,366,196,3.0,18,0,1982-07-18 00:00:00 -16016,366,94,7.0,11,0,1982-07-18 00:00:00 -16017,366,136,17.0,7,1,1982-07-18 00:00:00 -16018,366,180,2.0,21,0,1982-07-18 00:00:00 -16019,366,169,0.0,30,0,1982-07-18 00:00:00 -16020,366,206,0.0,35,0,1982-07-18 00:00:00 -16021,366,175,2.0,19,0,1982-07-18 00:00:00 -16022,366,135,0.0,34,0,1982-07-18 00:00:00 -16023,366,207,0.0,37,0,1982-07-18 00:00:00 -16024,366,208,0.0,36,0,1982-07-18 00:00:00 -16025,366,174,4.0,16,0,1982-07-18 00:00:00 -16026,366,89,0.0,38,0,1982-07-18 00:00:00 -16027,366,151,0.0,27,0,1982-07-18 00:00:00 -16028,366,202,6.0,13,0,1982-07-18 00:00:00 -16029,366,157,10.0,9,0,1982-07-18 00:00:00 -16030,366,198,6.0,14,0,1982-07-18 00:00:00 -16031,366,117,0.0,32,0,1982-07-18 00:00:00 -16032,366,193,2.0,20,0,1982-07-18 00:00:00 -16033,366,118,19.0,6,1,1982-07-18 00:00:00 -16034,366,172,13.0,8,0,1982-07-18 00:00:00 -16035,366,104,10.0,10,0,1982-07-18 00:00:00 -16036,366,186,30.0,2,2,1982-07-18 00:00:00 -16037,366,181,24.0,3,2,1982-07-18 00:00:00 -16038,366,162,4.0,17,0,1982-07-18 00:00:00 -16039,366,199,0.0,25,0,1982-07-18 00:00:00 -16040,366,176,21.0,4,0,1982-07-18 00:00:00 -16041,366,109,5.0,15,0,1982-07-18 00:00:00 -16042,366,205,7.0,12,0,1982-07-18 00:00:00 -16043,366,195,0.0,29,0,1982-07-18 00:00:00 -16044,366,200,0.0,26,0,1982-07-18 00:00:00 -16045,366,191,1.0,24,0,1982-07-18 00:00:00 -16046,366,201,35.0,1,2,1982-07-18 00:00:00 -16047,366,171,1.0,23,0,1982-07-18 00:00:00 -16048,366,116,19.0,5,2,1982-07-18 00:00:00 -16049,367,203,0.0,33,0,1982-07-25 00:00:00 -16050,367,202,6.0,15,0,1982-07-25 00:00:00 -16051,367,136,17.0,7,1,1982-07-25 00:00:00 -16052,367,94,7.0,12,0,1982-07-25 00:00:00 -16053,367,196,3.0,18,0,1982-07-25 00:00:00 -16054,367,183,1.0,22,0,1982-07-25 00:00:00 -16055,367,204,0.0,28,0,1982-07-25 00:00:00 -16056,367,174,7.0,13,0,1982-07-25 00:00:00 -16057,367,169,0.0,32,0,1982-07-25 00:00:00 -16058,367,206,0.0,36,0,1982-07-25 00:00:00 -16059,367,175,2.0,19,0,1982-07-25 00:00:00 -16060,367,135,0.0,35,0,1982-07-25 00:00:00 -16061,367,208,0.0,30,0,1982-07-25 00:00:00 -16062,367,157,10.0,11,0,1982-07-25 00:00:00 -16063,367,89,0.0,38,0,1982-07-25 00:00:00 -16064,367,194,0.0,34,0,1982-07-25 00:00:00 -16065,367,118,19.0,6,1,1982-07-25 00:00:00 -16066,367,207,0.0,37,0,1982-07-25 00:00:00 -16067,367,171,1.0,23,0,1982-07-25 00:00:00 -16068,367,117,0.0,31,0,1982-07-25 00:00:00 -16069,367,116,25.0,3,2,1982-07-25 00:00:00 -16070,367,198,6.0,16,0,1982-07-25 00:00:00 -16071,367,162,13.0,8,1,1982-07-25 00:00:00 -16072,367,181,24.0,4,2,1982-07-25 00:00:00 -16073,367,176,23.0,5,0,1982-07-25 00:00:00 -16074,367,104,11.0,10,0,1982-07-25 00:00:00 -16075,367,172,13.0,9,0,1982-07-25 00:00:00 -16076,367,193,2.0,20,0,1982-07-25 00:00:00 -16077,367,186,30.0,2,2,1982-07-25 00:00:00 -16078,367,151,0.0,26,0,1982-07-25 00:00:00 -16079,367,199,0.0,25,0,1982-07-25 00:00:00 -16080,367,109,5.0,17,0,1982-07-25 00:00:00 -16081,367,205,7.0,14,0,1982-07-25 00:00:00 -16082,367,195,0.0,29,0,1982-07-25 00:00:00 -16083,367,200,0.0,27,0,1982-07-25 00:00:00 -16084,367,191,1.0,24,0,1982-07-25 00:00:00 -16085,367,180,2.0,21,0,1982-07-25 00:00:00 -16086,367,201,39.0,1,2,1982-07-25 00:00:00 -16087,368,203,0.0,34,0,1982-08-08 00:00:00 -16088,368,183,1.0,23,0,1982-08-08 00:00:00 -16089,368,136,17.0,8,1,1982-08-08 00:00:00 -16090,368,94,7.0,13,0,1982-08-08 00:00:00 -16091,368,204,0.0,26,0,1982-08-08 00:00:00 -16092,368,202,6.0,15,0,1982-08-08 00:00:00 -16093,368,196,3.0,18,0,1982-08-08 00:00:00 -16094,368,194,0.0,30,0,1982-08-08 00:00:00 -16095,368,135,0.0,35,0,1982-08-08 00:00:00 -16096,368,206,0.0,36,0,1982-08-08 00:00:00 -16097,368,175,3.0,19,0,1982-08-08 00:00:00 -16098,368,207,0.0,37,0,1982-08-08 00:00:00 -16099,368,208,0.0,32,0,1982-08-08 00:00:00 -16100,368,174,16.0,9,1,1982-08-08 00:00:00 -16101,368,89,0.0,40,0,1982-08-08 00:00:00 -16102,368,209,0.0,38,0,1982-08-08 00:00:00 -16103,368,210,0.0,39,0,1982-08-08 00:00:00 -16104,368,169,0.0,33,0,1982-08-08 00:00:00 -16105,368,157,10.0,12,0,1982-08-08 00:00:00 -16106,368,117,0.0,31,0,1982-08-08 00:00:00 -16107,368,171,1.0,24,0,1982-08-08 00:00:00 -16108,368,116,25.0,4,2,1982-08-08 00:00:00 -16109,368,198,6.0,16,0,1982-08-08 00:00:00 -16110,368,162,19.0,6,1,1982-08-08 00:00:00 -16111,368,181,24.0,5,2,1982-08-08 00:00:00 -16112,368,176,27.0,3,0,1982-08-08 00:00:00 -16113,368,118,19.0,7,1,1982-08-08 00:00:00 -16114,368,104,14.0,10,0,1982-08-08 00:00:00 -16115,368,172,13.0,11,0,1982-08-08 00:00:00 -16116,368,186,30.0,2,2,1982-08-08 00:00:00 -16117,368,180,2.0,22,0,1982-08-08 00:00:00 -16118,368,151,2.0,20,0,1982-08-08 00:00:00 -16119,368,199,0.0,27,0,1982-08-08 00:00:00 -16120,368,109,5.0,17,0,1982-08-08 00:00:00 -16121,368,205,7.0,14,0,1982-08-08 00:00:00 -16122,368,200,0.0,28,0,1982-08-08 00:00:00 -16123,368,191,1.0,25,0,1982-08-08 00:00:00 -16124,368,201,39.0,1,2,1982-08-08 00:00:00 -16125,368,193,2.0,21,0,1982-08-08 00:00:00 -16126,368,195,0.0,29,0,1982-08-08 00:00:00 -16127,369,174,19.0,9,1,1982-08-15 00:00:00 -16128,369,89,0.0,40,0,1982-08-15 00:00:00 -16129,369,209,0.0,35,0,1982-08-15 00:00:00 -16130,369,210,0.0,38,0,1982-08-15 00:00:00 -16131,369,208,0.0,32,0,1982-08-15 00:00:00 -16132,369,207,0.0,39,0,1982-08-15 00:00:00 -16133,369,116,25.0,5,2,1982-08-15 00:00:00 -16134,369,117,0.0,31,0,1982-08-15 00:00:00 -16135,369,118,19.0,8,1,1982-08-15 00:00:00 -16136,369,157,10.0,12,0,1982-08-15 00:00:00 -16137,369,202,6.0,15,0,1982-08-15 00:00:00 -16138,369,136,17.0,10,1,1982-08-15 00:00:00 -16139,369,94,7.0,13,0,1982-08-15 00:00:00 -16140,369,171,5.0,17,0,1982-08-15 00:00:00 -16141,369,196,3.0,19,0,1982-08-15 00:00:00 -16142,369,204,0.0,26,0,1982-08-15 00:00:00 -16143,369,194,0.0,30,0,1982-08-15 00:00:00 -16144,369,169,0.0,33,0,1982-08-15 00:00:00 -16145,369,206,0.0,37,0,1982-08-15 00:00:00 -16146,369,175,3.0,20,0,1982-08-15 00:00:00 -16147,369,135,0.0,36,0,1982-08-15 00:00:00 -16148,369,203,0.0,34,0,1982-08-15 00:00:00 -16149,369,201,39.0,1,2,1982-08-15 00:00:00 -16150,369,183,2.0,24,0,1982-08-15 00:00:00 -16151,369,200,0.0,28,0,1982-08-15 00:00:00 -16152,369,191,1.0,25,0,1982-08-15 00:00:00 -16153,369,198,6.0,16,0,1982-08-15 00:00:00 -16154,369,162,19.0,7,1,1982-08-15 00:00:00 -16155,369,181,26.0,4,2,1982-08-15 00:00:00 -16156,369,176,33.0,2,0,1982-08-15 00:00:00 -16157,369,104,14.0,11,0,1982-08-15 00:00:00 -16158,369,172,22.0,6,1,1982-08-15 00:00:00 -16159,369,186,30.0,3,2,1982-08-15 00:00:00 -16160,369,193,2.0,22,0,1982-08-15 00:00:00 -16161,369,180,2.0,23,0,1982-08-15 00:00:00 -16162,369,151,2.0,21,0,1982-08-15 00:00:00 -16163,369,199,0.0,27,0,1982-08-15 00:00:00 -16164,369,109,5.0,18,0,1982-08-15 00:00:00 -16165,369,205,7.0,14,0,1982-08-15 00:00:00 -16166,369,195,0.0,29,0,1982-08-15 00:00:00 -16167,370,204,0.0,26,0,1982-08-29 00:00:00 -16168,370,136,20.0,8,1,1982-08-29 00:00:00 -16169,370,94,7.0,13,0,1982-08-29 00:00:00 -16170,370,196,3.0,19,0,1982-08-29 00:00:00 -16171,370,183,2.0,24,0,1982-08-29 00:00:00 -16172,370,203,0.0,34,0,1982-08-29 00:00:00 -16173,370,202,6.0,15,0,1982-08-29 00:00:00 -16174,370,194,0.0,30,0,1982-08-29 00:00:00 -16175,370,209,0.0,35,0,1982-08-29 00:00:00 -16176,370,206,0.0,37,0,1982-08-29 00:00:00 -16177,370,175,3.0,20,0,1982-08-29 00:00:00 -16178,370,207,0.0,39,0,1982-08-29 00:00:00 -16179,370,208,0.0,32,0,1982-08-29 00:00:00 -16180,370,174,19.0,10,1,1982-08-29 00:00:00 -16181,370,89,0.0,40,0,1982-08-29 00:00:00 -16182,370,210,0.0,38,0,1982-08-29 00:00:00 -16183,370,157,10.0,12,0,1982-08-29 00:00:00 -16184,370,169,0.0,33,0,1982-08-29 00:00:00 -16185,370,118,21.0,7,1,1982-08-29 00:00:00 -16186,370,135,0.0,36,0,1982-08-29 00:00:00 -16187,370,171,5.0,17,0,1982-08-29 00:00:00 -16188,370,198,6.0,16,0,1982-08-29 00:00:00 -16189,370,162,19.0,9,1,1982-08-29 00:00:00 -16190,370,181,30.0,5,2,1982-08-29 00:00:00 -16191,370,176,42.0,1,1,1982-08-29 00:00:00 -16192,370,186,30.0,4,2,1982-08-29 00:00:00 -16193,370,104,14.0,11,0,1982-08-29 00:00:00 -16194,370,116,31.0,3,2,1982-08-29 00:00:00 -16195,370,172,23.0,6,1,1982-08-29 00:00:00 -16196,370,193,2.0,22,0,1982-08-29 00:00:00 -16197,370,117,0.0,31,0,1982-08-29 00:00:00 -16198,370,151,2.0,21,0,1982-08-29 00:00:00 -16199,370,199,0.0,27,0,1982-08-29 00:00:00 -16200,370,109,5.0,18,0,1982-08-29 00:00:00 -16201,370,205,7.0,14,0,1982-08-29 00:00:00 -16202,370,195,0.0,29,0,1982-08-29 00:00:00 -16203,370,200,0.0,28,0,1982-08-29 00:00:00 -16204,370,191,1.0,25,0,1982-08-29 00:00:00 -16205,370,201,39.0,2,2,1982-08-29 00:00:00 -16206,370,180,2.0,23,0,1982-08-29 00:00:00 -16207,371,203,0.0,35,0,1982-09-12 00:00:00 -16208,371,183,2.0,25,0,1982-09-12 00:00:00 -16209,371,202,6.0,15,0,1982-09-12 00:00:00 -16210,371,94,7.0,13,0,1982-09-12 00:00:00 -16211,371,136,20.0,10,1,1982-09-12 00:00:00 -16212,371,204,0.0,27,0,1982-09-12 00:00:00 -16213,371,196,3.0,20,0,1982-09-12 00:00:00 -16214,371,194,0.0,31,0,1982-09-12 00:00:00 -16215,371,207,0.0,39,0,1982-09-12 00:00:00 -16216,371,206,4.0,19,0,1982-09-12 00:00:00 -16217,371,175,3.0,21,0,1982-09-12 00:00:00 -16218,371,135,0.0,37,0,1982-09-12 00:00:00 -16219,371,208,0.0,33,0,1982-09-12 00:00:00 -16220,371,174,25.0,7,1,1982-09-12 00:00:00 -16221,371,89,0.0,40,0,1982-09-12 00:00:00 -16222,371,209,0.0,36,0,1982-09-12 00:00:00 -16223,371,157,11.0,12,0,1982-09-12 00:00:00 -16224,371,169,0.0,34,0,1982-09-12 00:00:00 -16225,371,210,0.0,38,0,1982-09-12 00:00:00 -16226,371,118,21.0,9,1,1982-09-12 00:00:00 -16227,371,171,5.0,17,0,1982-09-12 00:00:00 -16228,371,117,0.0,32,0,1982-09-12 00:00:00 -16229,371,116,31.0,4,2,1982-09-12 00:00:00 -16230,371,198,6.0,16,0,1982-09-12 00:00:00 -16231,371,162,28.0,6,2,1982-09-12 00:00:00 -16232,371,181,30.0,5,2,1982-09-12 00:00:00 -16233,371,186,33.0,3,2,1982-09-12 00:00:00 -16234,371,104,16.0,11,0,1982-09-12 00:00:00 -16235,371,172,23.0,8,1,1982-09-12 00:00:00 -16236,371,193,2.0,23,0,1982-09-12 00:00:00 -16237,371,176,42.0,1,1,1982-09-12 00:00:00 -16238,371,151,2.0,22,0,1982-09-12 00:00:00 -16239,371,180,2.0,24,0,1982-09-12 00:00:00 -16240,371,191,1.0,26,0,1982-09-12 00:00:00 -16241,371,200,0.0,29,0,1982-09-12 00:00:00 -16242,371,195,0.0,30,0,1982-09-12 00:00:00 -16243,371,201,39.0,2,2,1982-09-12 00:00:00 -16244,371,109,5.0,18,0,1982-09-12 00:00:00 -16245,371,199,0.0,28,0,1982-09-12 00:00:00 -16246,371,205,7.0,14,0,1982-09-12 00:00:00 -16247,372,109,5.0,17,0,1982-09-25 00:00:00 -16248,372,117,0.0,32,0,1982-09-25 00:00:00 -16249,372,191,1.0,26,0,1982-09-25 00:00:00 -16250,372,200,0.0,29,0,1982-09-25 00:00:00 -16251,372,195,0.0,30,0,1982-09-25 00:00:00 -16252,372,205,8.0,13,0,1982-09-25 00:00:00 -16253,372,151,2.0,22,0,1982-09-25 00:00:00 -16254,372,199,0.0,28,0,1982-09-25 00:00:00 -16255,372,180,2.0,24,0,1982-09-25 00:00:00 -16256,372,136,20.0,11,1,1982-09-25 00:00:00 -16257,372,104,25.0,8,1,1982-09-25 00:00:00 -16258,372,172,23.0,9,1,1982-09-25 00:00:00 -16259,372,186,39.0,3,2,1982-09-25 00:00:00 -16260,372,176,44.0,1,1,1982-09-25 00:00:00 -16261,372,181,30.0,5,2,1982-09-25 00:00:00 -16262,372,116,34.0,4,2,1982-09-25 00:00:00 -16263,372,198,6.0,16,0,1982-09-25 00:00:00 -16264,372,162,28.0,6,2,1982-09-25 00:00:00 -16265,372,193,2.0,23,0,1982-09-25 00:00:00 -16266,372,202,6.0,15,0,1982-09-25 00:00:00 -16267,372,183,2.0,25,0,1982-09-25 00:00:00 -16268,372,118,21.0,10,1,1982-09-25 00:00:00 -16269,372,201,39.0,2,2,1982-09-25 00:00:00 -16270,372,171,5.0,18,0,1982-09-25 00:00:00 -16271,372,209,0.0,37,0,1982-09-25 00:00:00 -16272,372,135,0.0,38,0,1982-09-25 00:00:00 -16273,372,196,3.0,20,0,1982-09-25 00:00:00 -16274,372,210,0.0,33,0,1982-09-25 00:00:00 -16275,372,89,0.0,40,0,1982-09-25 00:00:00 -16276,372,174,25.0,7,1,1982-09-25 00:00:00 -16277,372,175,3.0,21,0,1982-09-25 00:00:00 -16278,372,207,0.0,39,0,1982-09-25 00:00:00 -16279,372,206,4.0,19,0,1982-09-25 00:00:00 -16280,372,169,0.0,35,0,1982-09-25 00:00:00 -16281,372,194,0.0,31,0,1982-09-25 00:00:00 -16282,372,204,0.0,27,0,1982-09-25 00:00:00 -16283,372,203,0.0,36,0,1982-09-25 00:00:00 -16284,372,157,15.0,12,0,1982-09-25 00:00:00 -16285,372,94,7.0,14,0,1982-09-25 00:00:00 -16286,372,208,0.0,34,0,1982-09-25 00:00:00 -16287,373,186,0.0,17,0,1983-03-13 00:00:00 -16288,373,195,0.0,18,0,1983-03-13 00:00:00 -16289,373,183,0.0,19,0,1983-03-13 00:00:00 -16290,373,196,0.0,20,0,1983-03-13 00:00:00 -16291,373,118,0.0,21,0,1983-03-13 00:00:00 -16292,373,109,0.0,25,0,1983-03-13 00:00:00 -16293,373,151,0.0,23,0,1983-03-13 00:00:00 -16294,373,104,0.0,24,0,1983-03-13 00:00:00 -16295,373,136,9.0,1,1,1983-03-13 00:00:00 -16296,373,157,0.0,16,0,1983-03-13 00:00:00 -16297,373,189,0.0,22,0,1983-03-13 00:00:00 -16298,373,194,0.0,15,0,1983-03-13 00:00:00 -16299,373,159,0.0,26,0,1983-03-13 00:00:00 -16300,373,193,0.0,13,0,1983-03-13 00:00:00 -16301,373,181,4.0,2,0,1983-03-13 00:00:00 -16302,373,171,3.0,3,0,1983-03-13 00:00:00 -16303,373,174,2.0,4,0,1983-03-13 00:00:00 -16304,373,175,1.0,5,0,1983-03-13 00:00:00 -16305,373,116,0.0,6,0,1983-03-13 00:00:00 -16306,373,180,0.0,14,0,1983-03-13 00:00:00 -16307,373,191,0.0,8,0,1983-03-13 00:00:00 -16308,373,162,0.0,9,0,1983-03-13 00:00:00 -16309,373,192,0.0,10,0,1983-03-13 00:00:00 -16310,373,94,0.0,11,0,1983-03-13 00:00:00 -16311,373,187,0.0,12,0,1983-03-13 00:00:00 -16312,373,117,0.0,7,0,1983-03-13 00:00:00 -16313,374,195,0.0,10,0,1983-03-27 00:00:00 -16314,374,183,0.0,26,0,1983-03-27 00:00:00 -16315,374,196,0.0,24,0,1983-03-27 00:00:00 -16316,374,118,0.0,15,0,1983-03-27 00:00:00 -16317,374,189,0.0,28,0,1983-03-27 00:00:00 -16318,374,109,0.0,21,0,1983-03-27 00:00:00 -16319,374,104,0.0,13,0,1983-03-27 00:00:00 -16320,374,159,0.0,29,0,1983-03-27 00:00:00 -16321,374,177,0.0,20,0,1983-03-27 00:00:00 -16322,374,172,0.0,23,0,1983-03-27 00:00:00 -16323,374,186,9.0,3,1,1983-03-27 00:00:00 -16324,374,151,0.0,25,0,1983-03-27 00:00:00 -16325,374,176,0.0,27,0,1983-03-27 00:00:00 -16326,374,157,0.0,17,0,1983-03-27 00:00:00 -16327,374,180,0.0,19,0,1983-03-27 00:00:00 -16328,374,194,0.0,22,0,1983-03-27 00:00:00 -16329,374,136,9.0,2,1,1983-03-27 00:00:00 -16330,374,181,10.0,1,0,1983-03-27 00:00:00 -16331,374,171,6.0,4,0,1983-03-27 00:00:00 -16332,374,175,3.0,6,0,1983-03-27 00:00:00 -16333,374,116,0.0,9,0,1983-03-27 00:00:00 -16334,374,174,2.0,7,0,1983-03-27 00:00:00 -16335,374,191,0.0,14,0,1983-03-27 00:00:00 -16336,374,162,4.0,5,0,1983-03-27 00:00:00 -16337,374,192,0.0,11,0,1983-03-27 00:00:00 -16338,374,94,0.0,16,0,1983-03-27 00:00:00 -16339,374,187,1.0,8,0,1983-03-27 00:00:00 -16340,374,193,0.0,18,0,1983-03-27 00:00:00 -16341,374,117,0.0,12,0,1983-03-27 00:00:00 -16342,375,172,0.0,27,0,1983-04-17 00:00:00 -16343,375,183,0.0,28,0,1983-04-17 00:00:00 -16344,375,157,4.0,8,0,1983-04-17 00:00:00 -16345,375,167,0.0,30,0,1983-04-17 00:00:00 -16346,375,176,2.0,10,0,1983-04-17 00:00:00 -16347,375,177,0.0,24,0,1983-04-17 00:00:00 -16348,375,196,0.0,16,0,1983-04-17 00:00:00 -16349,375,109,0.0,20,0,1983-04-17 00:00:00 -16350,375,104,0.0,13,0,1983-04-17 00:00:00 -16351,375,151,0.0,21,0,1983-04-17 00:00:00 -16352,375,189,0.0,25,0,1983-04-17 00:00:00 -16353,375,118,0.0,18,0,1983-04-17 00:00:00 -16354,375,159,0.0,29,0,1983-04-17 00:00:00 -16355,375,194,0.0,26,0,1983-04-17 00:00:00 -16356,375,186,9.0,4,1,1983-04-17 00:00:00 -16357,375,193,0.0,22,0,1983-04-17 00:00:00 -16358,375,187,1.0,11,0,1983-04-17 00:00:00 -16359,375,94,0.0,19,0,1983-04-17 00:00:00 -16360,375,192,0.0,14,0,1983-04-17 00:00:00 -16361,375,162,4.0,7,0,1983-04-17 00:00:00 -16362,375,191,0.0,17,0,1983-04-17 00:00:00 -16363,375,117,0.0,15,0,1983-04-17 00:00:00 -16364,375,180,0.0,23,0,1983-04-17 00:00:00 -16365,375,175,3.0,9,0,1983-04-17 00:00:00 -16366,375,195,0.0,12,0,1983-04-17 00:00:00 -16367,375,136,15.0,1,1,1983-04-17 00:00:00 -16368,375,116,9.0,3,1,1983-04-17 00:00:00 -16369,375,171,7.0,5,0,1983-04-17 00:00:00 -16370,375,181,10.0,2,0,1983-04-17 00:00:00 -16371,375,174,5.0,6,0,1983-04-17 00:00:00 -16372,376,167,0.0,30,0,1983-05-01 00:00:00 -16373,376,176,5.0,8,0,1983-05-01 00:00:00 -16374,376,172,0.0,26,0,1983-05-01 00:00:00 -16375,376,177,0.0,25,0,1983-05-01 00:00:00 -16376,376,159,0.0,29,0,1983-05-01 00:00:00 -16377,376,109,0.0,22,0,1983-05-01 00:00:00 -16378,376,104,0.0,14,0,1983-05-01 00:00:00 -16379,376,189,0.0,27,0,1983-05-01 00:00:00 -16380,376,118,0.0,18,0,1983-05-01 00:00:00 -16381,376,196,0.0,17,0,1983-05-01 00:00:00 -16382,376,183,0.0,19,0,1983-05-01 00:00:00 -16383,376,195,0.0,12,0,1983-05-01 00:00:00 -16384,376,186,11.0,4,1,1983-05-01 00:00:00 -16385,376,151,0.0,23,0,1983-05-01 00:00:00 -16386,376,194,0.0,28,0,1983-05-01 00:00:00 -16387,376,136,15.0,2,1,1983-05-01 00:00:00 -16388,376,157,4.0,9,0,1983-05-01 00:00:00 -16389,376,171,7.0,7,0,1983-05-01 00:00:00 -16390,376,174,14.0,3,1,1983-05-01 00:00:00 -16391,376,175,4.0,10,0,1983-05-01 00:00:00 -16392,376,116,15.0,1,1,1983-05-01 00:00:00 -16393,376,117,0.0,16,0,1983-05-01 00:00:00 -16394,376,181,10.0,5,0,1983-05-01 00:00:00 -16395,376,162,8.0,6,0,1983-05-01 00:00:00 -16396,376,192,0.0,15,0,1983-05-01 00:00:00 -16397,376,94,0.0,21,0,1983-05-01 00:00:00 -16398,376,187,1.0,11,0,1983-05-01 00:00:00 -16399,376,193,0.0,24,0,1983-05-01 00:00:00 -16400,376,191,0.0,13,0,1983-05-01 00:00:00 -16401,376,180,0.0,20,0,1983-05-01 00:00:00 -16402,377,183,1.0,12,0,1983-05-15 00:00:00 -16403,377,196,0.0,18,0,1983-05-15 00:00:00 -16404,377,118,0.0,19,0,1983-05-15 00:00:00 -16405,377,189,0.0,27,0,1983-05-15 00:00:00 -16406,377,151,0.0,23,0,1983-05-15 00:00:00 -16407,377,104,0.0,16,0,1983-05-15 00:00:00 -16408,377,159,0.0,29,0,1983-05-15 00:00:00 -16409,377,177,0.0,26,0,1983-05-15 00:00:00 -16410,377,172,0.0,25,0,1983-05-15 00:00:00 -16411,377,176,14.0,4,1,1983-05-15 00:00:00 -16412,377,167,0.0,30,0,1983-05-15 00:00:00 -16413,377,195,0.0,15,0,1983-05-15 00:00:00 -16414,377,109,0.0,22,0,1983-05-15 00:00:00 -16415,377,186,11.0,5,1,1983-05-15 00:00:00 -16416,377,191,0.0,14,0,1983-05-15 00:00:00 -16417,377,194,0.0,28,0,1983-05-15 00:00:00 -16418,377,157,4.0,9,0,1983-05-15 00:00:00 -16419,377,136,21.0,1,1,1983-05-15 00:00:00 -16420,377,181,10.0,6,0,1983-05-15 00:00:00 -16421,377,171,7.0,8,0,1983-05-15 00:00:00 -16422,377,174,17.0,3,1,1983-05-15 00:00:00 -16423,377,175,4.0,10,0,1983-05-15 00:00:00 -16424,377,116,19.0,2,1,1983-05-15 00:00:00 -16425,377,162,8.0,7,0,1983-05-15 00:00:00 -16426,377,192,2.0,11,0,1983-05-15 00:00:00 -16427,377,94,0.0,21,0,1983-05-15 00:00:00 -16428,377,187,1.0,13,0,1983-05-15 00:00:00 -16429,377,193,0.0,24,0,1983-05-15 00:00:00 -16430,377,180,0.0,20,0,1983-05-15 00:00:00 -16431,377,117,0.0,17,0,1983-05-15 00:00:00 -16432,378,195,0.0,16,0,1983-05-22 00:00:00 -16433,378,183,1.0,13,0,1983-05-22 00:00:00 -16434,378,196,0.0,20,0,1983-05-22 00:00:00 -16435,378,118,0.0,21,0,1983-05-22 00:00:00 -16436,378,189,0.0,27,0,1983-05-22 00:00:00 -16437,378,151,0.0,18,0,1983-05-22 00:00:00 -16438,378,177,0.0,26,0,1983-05-22 00:00:00 -16439,378,109,0.0,24,0,1983-05-22 00:00:00 -16440,378,159,0.0,30,0,1983-05-22 00:00:00 -16441,378,172,0.0,19,0,1983-05-22 00:00:00 -16442,378,176,16.0,4,1,1983-05-22 00:00:00 -16443,378,167,0.0,31,0,1983-05-22 00:00:00 -16444,378,104,0.0,17,0,1983-05-22 00:00:00 -16445,378,122,0.0,29,0,1983-05-22 00:00:00 -16446,378,157,8.0,8,0,1983-05-22 00:00:00 -16447,378,194,0.0,28,0,1983-05-22 00:00:00 -16448,378,186,11.0,5,1,1983-05-22 00:00:00 -16449,378,136,24.0,2,1,1983-05-22 00:00:00 -16450,378,181,10.0,6,0,1983-05-22 00:00:00 -16451,378,171,8.0,9,0,1983-05-22 00:00:00 -16452,378,174,23.0,3,1,1983-05-22 00:00:00 -16453,378,175,4.0,10,0,1983-05-22 00:00:00 -16454,378,116,28.0,1,2,1983-05-22 00:00:00 -16455,378,187,1.0,12,0,1983-05-22 00:00:00 -16456,378,191,0.0,14,0,1983-05-22 00:00:00 -16457,378,162,8.0,7,0,1983-05-22 00:00:00 -16458,378,192,2.0,11,0,1983-05-22 00:00:00 -16459,378,94,0.0,23,0,1983-05-22 00:00:00 -16460,378,117,0.0,15,0,1983-05-22 00:00:00 -16461,378,193,0.0,25,0,1983-05-22 00:00:00 -16462,378,180,0.0,22,0,1983-05-22 00:00:00 -16463,379,183,1.0,14,0,1983-06-05 00:00:00 -16464,379,196,0.0,22,0,1983-06-05 00:00:00 -16465,379,118,0.0,23,0,1983-06-05 00:00:00 -16466,379,189,0.0,29,0,1983-06-05 00:00:00 -16467,379,151,0.0,20,0,1983-06-05 00:00:00 -16468,379,159,0.0,30,0,1983-06-05 00:00:00 -16469,379,195,0.0,18,0,1983-06-05 00:00:00 -16470,379,177,0.0,28,0,1983-06-05 00:00:00 -16471,379,172,0.0,21,0,1983-06-05 00:00:00 -16472,379,176,22.0,4,1,1983-06-05 00:00:00 -16473,379,122,0.0,19,0,1983-06-05 00:00:00 -16474,379,104,9.0,8,1,1983-06-05 00:00:00 -16475,379,186,15.0,5,1,1983-06-05 00:00:00 -16476,379,167,0.0,31,0,1983-06-05 00:00:00 -16477,379,194,0.0,27,0,1983-06-05 00:00:00 -16478,379,157,8.0,10,0,1983-06-05 00:00:00 -16479,379,136,27.0,2,1,1983-06-05 00:00:00 -16480,379,181,10.0,6,0,1983-06-05 00:00:00 -16481,379,171,10.0,7,0,1983-06-05 00:00:00 -16482,379,174,23.0,3,1,1983-06-05 00:00:00 -16483,379,175,4.0,11,0,1983-06-05 00:00:00 -16484,379,116,28.0,1,2,1983-06-05 00:00:00 -16485,379,109,0.0,25,0,1983-06-05 00:00:00 -16486,379,191,0.0,16,0,1983-06-05 00:00:00 -16487,379,162,8.0,9,0,1983-06-05 00:00:00 -16488,379,192,2.0,12,0,1983-06-05 00:00:00 -16489,379,94,1.0,15,0,1983-06-05 00:00:00 -16490,379,187,1.0,13,0,1983-06-05 00:00:00 -16491,379,193,0.0,26,0,1983-06-05 00:00:00 -16492,379,117,0.0,17,0,1983-06-05 00:00:00 -16493,379,180,0.0,24,0,1983-06-05 00:00:00 -16494,380,196,0.0,23,0,1983-06-12 00:00:00 -16495,380,118,0.0,24,0,1983-06-12 00:00:00 -16496,380,189,0.0,29,0,1983-06-12 00:00:00 -16497,380,151,0.0,20,0,1983-06-12 00:00:00 -16498,380,104,9.0,10,1,1983-06-12 00:00:00 -16499,380,177,0.0,28,0,1983-06-12 00:00:00 -16500,380,159,0.0,30,0,1983-06-12 00:00:00 -16501,380,183,1.0,13,0,1983-06-12 00:00:00 -16502,380,172,0.0,22,0,1983-06-12 00:00:00 -16503,380,176,25.0,4,1,1983-06-12 00:00:00 -16504,380,167,0.0,32,0,1983-06-12 00:00:00 -16505,380,122,0.0,16,0,1983-06-12 00:00:00 -16506,380,197,0.0,31,0,1983-06-12 00:00:00 -16507,380,109,0.0,25,0,1983-06-12 00:00:00 -16508,380,195,0.0,19,0,1983-06-12 00:00:00 -16509,380,180,0.0,21,0,1983-06-12 00:00:00 -16510,380,157,14.0,7,0,1983-06-12 00:00:00 -16511,380,136,27.0,2,1,1983-06-12 00:00:00 -16512,380,181,10.0,8,0,1983-06-12 00:00:00 -16513,380,171,10.0,9,0,1983-06-12 00:00:00 -16514,380,174,27.0,3,1,1983-06-12 00:00:00 -16515,380,175,4.0,11,0,1983-06-12 00:00:00 -16516,380,186,16.0,6,1,1983-06-12 00:00:00 -16517,380,116,30.0,1,2,1983-06-12 00:00:00 -16518,380,191,0.0,17,0,1983-06-12 00:00:00 -16519,380,192,2.0,12,0,1983-06-12 00:00:00 -16520,380,94,1.0,15,0,1983-06-12 00:00:00 -16521,380,187,1.0,14,0,1983-06-12 00:00:00 -16522,380,193,0.0,26,0,1983-06-12 00:00:00 -16523,380,194,0.0,27,0,1983-06-12 00:00:00 -16524,380,117,0.0,18,0,1983-06-12 00:00:00 -16525,380,162,17.0,5,1,1983-06-12 00:00:00 -16526,381,136,33.0,2,1,1983-07-16 00:00:00 -16527,381,181,11.0,8,0,1983-07-16 00:00:00 -16528,381,174,31.0,3,1,1983-07-16 00:00:00 -16529,381,171,10.0,9,0,1983-07-16 00:00:00 -16530,381,185,0.0,33,0,1983-07-16 00:00:00 -16531,381,139,0.0,31,0,1983-07-16 00:00:00 -16532,381,197,0.0,32,0,1983-07-16 00:00:00 -16533,381,122,0.0,16,0,1983-07-16 00:00:00 -16534,381,167,0.0,34,0,1983-07-16 00:00:00 -16535,381,176,25.0,4,1,1983-07-16 00:00:00 -16536,381,172,0.0,24,0,1983-07-16 00:00:00 -16537,381,159,0.0,30,0,1983-07-16 00:00:00 -16538,381,109,0.0,21,0,1983-07-16 00:00:00 -16539,381,104,9.0,10,1,1983-07-16 00:00:00 -16540,381,151,0.0,20,0,1983-07-16 00:00:00 -16541,381,189,0.0,29,0,1983-07-16 00:00:00 -16542,381,118,0.0,25,0,1983-07-16 00:00:00 -16543,381,196,0.0,22,0,1983-07-16 00:00:00 -16544,381,177,0.0,28,0,1983-07-16 00:00:00 -16545,381,195,0.0,19,0,1983-07-16 00:00:00 -16546,381,183,1.0,14,0,1983-07-16 00:00:00 -16547,381,175,4.0,12,0,1983-07-16 00:00:00 -16548,381,116,39.0,1,3,1983-07-16 00:00:00 -16549,381,117,0.0,18,0,1983-07-16 00:00:00 -16550,381,191,0.0,17,0,1983-07-16 00:00:00 -16551,381,192,2.0,13,0,1983-07-16 00:00:00 -16552,381,94,4.0,11,0,1983-07-16 00:00:00 -16553,381,162,19.0,5,1,1983-07-16 00:00:00 -16554,381,193,0.0,26,0,1983-07-16 00:00:00 -16555,381,180,0.0,23,0,1983-07-16 00:00:00 -16556,381,194,0.0,27,0,1983-07-16 00:00:00 -16557,381,157,14.0,7,0,1983-07-16 00:00:00 -16558,381,186,16.0,6,1,1983-07-16 00:00:00 -16559,381,187,1.0,15,0,1983-07-16 00:00:00 -16560,382,118,4.0,12,0,1983-08-07 00:00:00 -16561,382,159,0.0,30,0,1983-08-07 00:00:00 -16562,382,189,0.0,29,0,1983-08-07 00:00:00 -16563,382,151,0.0,23,0,1983-08-07 00:00:00 -16564,382,104,9.0,10,1,1983-08-07 00:00:00 -16565,382,109,6.0,11,0,1983-08-07 00:00:00 -16566,382,177,0.0,28,0,1983-08-07 00:00:00 -16567,382,185,0.0,32,0,1983-08-07 00:00:00 -16568,382,176,25.0,5,1,1983-08-07 00:00:00 -16569,382,167,0.0,34,0,1983-08-07 00:00:00 -16570,382,122,0.0,18,0,1983-08-07 00:00:00 -16571,382,197,0.0,33,0,1983-08-07 00:00:00 -16572,382,139,0.0,31,0,1983-08-07 00:00:00 -16573,382,196,0.0,22,0,1983-08-07 00:00:00 -16574,382,172,0.0,25,0,1983-08-07 00:00:00 -16575,382,183,1.0,16,0,1983-08-07 00:00:00 -16576,382,193,0.0,26,0,1983-08-07 00:00:00 -16577,382,186,18.0,6,1,1983-08-07 00:00:00 -16578,382,136,33.0,2,1,1983-08-07 00:00:00 -16579,382,181,11.0,8,0,1983-08-07 00:00:00 -16580,382,171,11.0,9,0,1983-08-07 00:00:00 -16581,382,174,31.0,3,1,1983-08-07 00:00:00 -16582,382,175,4.0,14,0,1983-08-07 00:00:00 -16583,382,116,42.0,1,3,1983-08-07 00:00:00 -16584,382,117,0.0,20,0,1983-08-07 00:00:00 -16585,382,195,0.0,21,0,1983-08-07 00:00:00 -16586,382,162,28.0,4,2,1983-08-07 00:00:00 -16587,382,192,2.0,15,0,1983-08-07 00:00:00 -16588,382,94,4.0,13,0,1983-08-07 00:00:00 -16589,382,187,1.0,17,0,1983-08-07 00:00:00 -16590,382,180,0.0,24,0,1983-08-07 00:00:00 -16591,382,194,0.0,27,0,1983-08-07 00:00:00 -16592,382,157,14.0,7,0,1983-08-07 00:00:00 -16593,382,191,0.0,19,0,1983-08-07 00:00:00 -16594,383,118,4.0,13,0,1983-08-14 00:00:00 -16595,383,189,0.0,26,0,1983-08-14 00:00:00 -16596,383,151,0.0,23,0,1983-08-14 00:00:00 -16597,383,104,9.0,10,1,1983-08-14 00:00:00 -16598,383,109,6.0,11,0,1983-08-14 00:00:00 -16599,383,159,0.0,27,0,1983-08-14 00:00:00 -16600,383,167,0.0,34,0,1983-08-14 00:00:00 -16601,383,172,0.0,25,0,1983-08-14 00:00:00 -16602,383,176,25.0,5,1,1983-08-14 00:00:00 -16603,383,122,0.0,18,0,1983-08-14 00:00:00 -16604,383,197,0.0,33,0,1983-08-14 00:00:00 -16605,383,139,0.0,28,0,1983-08-14 00:00:00 -16606,383,185,0.0,32,0,1983-08-14 00:00:00 -16607,383,177,0.0,31,0,1983-08-14 00:00:00 -16608,383,183,1.0,16,0,1983-08-14 00:00:00 -16609,383,196,0.0,19,0,1983-08-14 00:00:00 -16610,383,186,18.0,6,1,1983-08-14 00:00:00 -16611,383,136,37.0,2,1,1983-08-14 00:00:00 -16612,383,181,12.0,8,0,1983-08-14 00:00:00 -16613,383,171,11.0,9,0,1983-08-14 00:00:00 -16614,383,174,31.0,4,1,1983-08-14 00:00:00 -16615,383,175,4.0,14,0,1983-08-14 00:00:00 -16616,383,117,0.0,21,0,1983-08-14 00:00:00 -16617,383,191,0.0,20,0,1983-08-14 00:00:00 -16618,383,116,51.0,1,4,1983-08-14 00:00:00 -16619,383,192,2.0,15,0,1983-08-14 00:00:00 -16620,383,94,6.0,12,0,1983-08-14 00:00:00 -16621,383,187,1.0,17,0,1983-08-14 00:00:00 -16622,383,193,0.0,29,0,1983-08-14 00:00:00 -16623,383,180,0.0,24,0,1983-08-14 00:00:00 -16624,383,194,0.0,30,0,1983-08-14 00:00:00 -16625,383,157,17.0,7,0,1983-08-14 00:00:00 -16626,383,162,34.0,3,2,1983-08-14 00:00:00 -16627,383,195,0.0,22,0,1983-08-14 00:00:00 -16628,384,159,0.0,28,0,1983-08-28 00:00:00 -16629,384,118,4.0,13,0,1983-08-28 00:00:00 -16630,384,189,0.0,27,0,1983-08-28 00:00:00 -16631,384,151,0.0,24,0,1983-08-28 00:00:00 -16632,384,104,10.0,10,1,1983-08-28 00:00:00 -16633,384,109,6.0,11,0,1983-08-28 00:00:00 -16634,384,185,0.0,32,0,1983-08-28 00:00:00 -16635,384,176,25.0,5,1,1983-08-28 00:00:00 -16636,384,167,0.0,34,0,1983-08-28 00:00:00 -16637,384,122,0.0,19,0,1983-08-28 00:00:00 -16638,384,197,0.0,33,0,1983-08-28 00:00:00 -16639,384,139,0.0,23,0,1983-08-28 00:00:00 -16640,384,196,0.0,20,0,1983-08-28 00:00:00 -16641,384,172,0.0,26,0,1983-08-28 00:00:00 -16642,384,183,3.0,16,0,1983-08-28 00:00:00 -16643,384,177,0.0,31,0,1983-08-28 00:00:00 -16644,384,186,22.0,6,1,1983-08-28 00:00:00 -16645,384,195,0.0,22,0,1983-08-28 00:00:00 -16646,384,136,37.0,3,1,1983-08-28 00:00:00 -16647,384,181,12.0,8,0,1983-08-28 00:00:00 -16648,384,171,11.0,9,0,1983-08-28 00:00:00 -16649,384,174,37.0,4,1,1983-08-28 00:00:00 -16650,384,175,4.0,14,0,1983-08-28 00:00:00 -16651,384,116,51.0,1,4,1983-08-28 00:00:00 -16652,384,117,3.0,15,0,1983-08-28 00:00:00 -16653,384,94,6.0,12,0,1983-08-28 00:00:00 -16654,384,162,43.0,2,3,1983-08-28 00:00:00 -16655,384,192,2.0,17,0,1983-08-28 00:00:00 -16656,384,187,1.0,18,0,1983-08-28 00:00:00 -16657,384,193,0.0,30,0,1983-08-28 00:00:00 -16658,384,180,0.0,25,0,1983-08-28 00:00:00 -16659,384,194,0.0,29,0,1983-08-28 00:00:00 -16660,384,191,0.0,21,0,1983-08-28 00:00:00 -16661,384,157,17.0,7,0,1983-08-28 00:00:00 -16662,385,118,4.0,13,0,1983-09-11 00:00:00 -16663,385,189,0.0,27,0,1983-09-11 00:00:00 -16664,385,151,0.0,22,0,1983-09-11 00:00:00 -16665,385,104,10.0,10,1,1983-09-11 00:00:00 -16666,385,109,6.0,11,0,1983-09-11 00:00:00 -16667,385,159,0.0,28,0,1983-09-11 00:00:00 -16668,385,176,25.0,5,1,1983-09-11 00:00:00 -16669,385,172,2.0,18,0,1983-09-11 00:00:00 -16670,385,196,0.0,21,0,1983-09-11 00:00:00 -16671,385,167,0.0,34,0,1983-09-11 00:00:00 -16672,385,122,0.0,20,0,1983-09-11 00:00:00 -16673,385,197,0.0,33,0,1983-09-11 00:00:00 -16674,385,139,0.0,25,0,1983-09-11 00:00:00 -16675,385,185,0.0,32,0,1983-09-11 00:00:00 -16676,385,177,0.0,31,0,1983-09-11 00:00:00 -16677,385,183,3.0,16,0,1983-09-11 00:00:00 -16678,385,194,0.0,29,0,1983-09-11 00:00:00 -16679,385,186,22.0,6,1,1983-09-11 00:00:00 -16680,385,136,46.0,3,2,1983-09-11 00:00:00 -16681,385,181,12.0,8,0,1983-09-11 00:00:00 -16682,385,171,11.0,9,0,1983-09-11 00:00:00 -16683,385,174,40.0,4,1,1983-09-11 00:00:00 -16684,385,175,4.0,15,0,1983-09-11 00:00:00 -16685,385,116,51.0,1,4,1983-09-11 00:00:00 -16686,385,195,0.0,24,0,1983-09-11 00:00:00 -16687,385,117,4.0,14,0,1983-09-11 00:00:00 -16688,385,162,49.0,2,3,1983-09-11 00:00:00 -16689,385,94,6.0,12,0,1983-09-11 00:00:00 -16690,385,187,1.0,19,0,1983-09-11 00:00:00 -16691,385,193,0.0,30,0,1983-09-11 00:00:00 -16692,385,180,0.0,26,0,1983-09-11 00:00:00 -16693,385,157,21.0,7,0,1983-09-11 00:00:00 -16694,385,191,0.0,23,0,1983-09-11 00:00:00 -16695,385,192,2.0,17,0,1983-09-11 00:00:00 -16696,386,167,0.0,35,0,1983-09-25 00:00:00 -16697,386,185,0.0,33,0,1983-09-25 00:00:00 -16698,386,192,2.0,17,0,1983-09-25 00:00:00 -16699,386,94,10.0,11,0,1983-09-25 00:00:00 -16700,386,187,1.0,20,0,1983-09-25 00:00:00 -16701,386,193,0.0,31,0,1983-09-25 00:00:00 -16702,386,180,0.0,26,0,1983-09-25 00:00:00 -16703,386,157,21.0,7,0,1983-09-25 00:00:00 -16704,386,162,49.0,3,3,1983-09-25 00:00:00 -16705,386,116,57.0,1,4,1983-09-25 00:00:00 -16706,386,104,10.0,10,1,1983-09-25 00:00:00 -16707,386,196,0.0,22,0,1983-09-25 00:00:00 -16708,386,136,55.0,2,3,1983-09-25 00:00:00 -16709,386,183,3.0,16,0,1983-09-25 00:00:00 -16710,386,171,11.0,9,0,1983-09-25 00:00:00 -16711,386,155,0.0,30,0,1983-09-25 00:00:00 -16712,386,172,2.0,18,0,1983-09-25 00:00:00 -16713,386,191,0.0,23,0,1983-09-25 00:00:00 -16714,386,194,0.0,29,0,1983-09-25 00:00:00 -16715,386,174,40.0,4,1,1983-09-25 00:00:00 -16716,386,181,12.0,8,0,1983-09-25 00:00:00 -16717,386,197,0.0,34,0,1983-09-25 00:00:00 -16718,386,122,0.0,21,0,1983-09-25 00:00:00 -16719,386,176,25.0,5,1,1983-09-25 00:00:00 -16720,386,177,0.0,32,0,1983-09-25 00:00:00 -16721,386,159,0.0,28,0,1983-09-25 00:00:00 -16722,386,109,9.0,12,0,1983-09-25 00:00:00 -16723,386,139,0.0,25,0,1983-09-25 00:00:00 -16724,386,189,0.0,27,0,1983-09-25 00:00:00 -16725,386,118,4.0,14,0,1983-09-25 00:00:00 -16726,386,195,0.0,24,0,1983-09-25 00:00:00 -16727,386,186,22.0,6,1,1983-09-25 00:00:00 -16728,386,117,6.0,13,0,1983-09-25 00:00:00 -16729,386,175,4.0,15,0,1983-09-25 00:00:00 -16730,386,151,1.0,19,0,1983-09-25 00:00:00 -16731,387,118,13.0,9,1,1983-10-15 00:00:00 -16732,387,189,0.0,27,0,1983-10-15 00:00:00 -16733,387,151,1.0,19,0,1983-10-15 00:00:00 -16734,387,104,10.0,12,1,1983-10-15 00:00:00 -16735,387,109,15.0,8,0,1983-10-15 00:00:00 -16736,387,159,0.0,28,0,1983-10-15 00:00:00 -16737,387,172,2.0,18,0,1983-10-15 00:00:00 -16738,387,122,0.0,21,0,1983-10-15 00:00:00 -16739,387,167,0.0,35,0,1983-10-15 00:00:00 -16740,387,197,0.0,34,0,1983-10-15 00:00:00 -16741,387,139,0.0,25,0,1983-10-15 00:00:00 -16742,387,185,0.0,30,0,1983-10-15 00:00:00 -16743,387,155,0.0,31,0,1983-10-15 00:00:00 -16744,387,196,0.0,22,0,1983-10-15 00:00:00 -16745,387,176,27.0,5,1,1983-10-15 00:00:00 -16746,387,183,3.0,16,0,1983-10-15 00:00:00 -16747,387,177,0.0,33,0,1983-10-15 00:00:00 -16748,387,186,22.0,6,1,1983-10-15 00:00:00 -16749,387,195,0.0,24,0,1983-10-15 00:00:00 -16750,387,136,59.0,1,3,1983-10-15 00:00:00 -16751,387,181,12.0,10,0,1983-10-15 00:00:00 -16752,387,171,11.0,11,0,1983-10-15 00:00:00 -16753,387,175,4.0,15,0,1983-10-15 00:00:00 -16754,387,116,57.0,2,4,1983-10-15 00:00:00 -16755,387,117,9.0,14,0,1983-10-15 00:00:00 -16756,387,191,0.0,23,0,1983-10-15 00:00:00 -16757,387,174,40.0,4,1,1983-10-15 00:00:00 -16758,387,192,2.0,17,0,1983-10-15 00:00:00 -16759,387,94,10.0,13,0,1983-10-15 00:00:00 -16760,387,187,1.0,20,0,1983-10-15 00:00:00 -16761,387,193,0.0,32,0,1983-10-15 00:00:00 -16762,387,180,0.0,26,0,1983-10-15 00:00:00 -16763,387,162,49.0,3,3,1983-10-15 00:00:00 -16764,387,157,22.0,7,0,1983-10-15 00:00:00 -16765,387,194,0.0,29,0,1983-10-15 00:00:00 -16766,388,101,0.0,24,0,1984-03-25 00:00:00 -16767,388,169,0.0,15,0,1984-03-25 00:00:00 -16768,388,162,0.0,16,0,1984-03-25 00:00:00 -16769,388,159,0.0,17,0,1984-03-25 00:00:00 -16770,388,171,0.0,21,0,1984-03-25 00:00:00 -16771,388,187,0.0,20,0,1984-03-25 00:00:00 -16772,388,104,0.0,22,0,1984-03-25 00:00:00 -16773,388,183,0.0,23,0,1984-03-25 00:00:00 -16774,388,136,0.0,14,0,1984-03-25 00:00:00 -16775,388,111,0.0,19,0,1984-03-25 00:00:00 -16776,388,94,0.0,13,0,1984-03-25 00:00:00 -16777,388,182,0.0,18,0,1984-03-25 00:00:00 -16778,388,118,0.0,11,0,1984-03-25 00:00:00 -16779,388,109,0.0,10,0,1984-03-25 00:00:00 -16780,388,117,0.0,9,0,1984-03-25 00:00:00 -16781,388,155,0.0,8,0,1984-03-25 00:00:00 -16782,388,175,0.0,7,0,1984-03-25 00:00:00 -16783,388,122,1.0,6,0,1984-03-25 00:00:00 -16784,388,174,2.0,5,0,1984-03-25 00:00:00 -16785,388,157,3.0,4,0,1984-03-25 00:00:00 -16786,388,172,4.0,3,0,1984-03-25 00:00:00 -16787,388,176,6.0,2,0,1984-03-25 00:00:00 -16788,388,116,9.0,1,1,1984-03-25 00:00:00 -16789,388,181,0.0,12,0,1984-03-25 00:00:00 -16790,389,162,0.0,23,0,1984-04-07 00:00:00 -16791,389,159,0.0,25,0,1984-04-07 00:00:00 -16792,389,182,0.0,15,0,1984-04-07 00:00:00 -16793,389,111,0.0,26,0,1984-04-07 00:00:00 -16794,389,101,1.0,11,0,1984-04-07 00:00:00 -16795,389,171,0.0,21,0,1984-04-07 00:00:00 -16796,389,180,0.0,24,0,1984-04-07 00:00:00 -16797,389,184,0.0,20,0,1984-04-07 00:00:00 -16798,389,83,0.0,17,0,1984-04-07 00:00:00 -16799,389,169,0.0,22,0,1984-04-07 00:00:00 -16800,389,187,0.0,27,0,1984-04-07 00:00:00 -16801,389,136,0.0,19,0,1984-04-07 00:00:00 -16802,389,155,0.0,14,0,1984-04-07 00:00:00 -16803,389,181,9.0,2,1,1984-04-07 00:00:00 -16804,389,118,3.0,6,0,1984-04-07 00:00:00 -16805,389,109,2.0,8,0,1984-04-07 00:00:00 -16806,389,117,4.0,5,0,1984-04-07 00:00:00 -16807,389,175,0.0,12,0,1984-04-07 00:00:00 -16808,389,122,1.0,10,0,1984-04-07 00:00:00 -16809,389,174,2.0,9,0,1984-04-07 00:00:00 -16810,389,157,3.0,7,0,1984-04-07 00:00:00 -16811,389,172,4.0,4,0,1984-04-07 00:00:00 -16812,389,176,6.0,3,0,1984-04-07 00:00:00 -16813,389,116,15.0,1,1,1984-04-07 00:00:00 -16814,389,183,0.0,13,0,1984-04-07 00:00:00 -16815,389,94,0.0,18,0,1984-04-07 00:00:00 -16816,389,104,0.0,16,0,1984-04-07 00:00:00 -16817,390,180,0.0,23,0,1984-04-29 00:00:00 -16818,390,176,9.0,5,0,1984-04-29 00:00:00 -16819,390,116,15.0,1,1,1984-04-29 00:00:00 -16820,390,184,0.0,22,0,1984-04-29 00:00:00 -16821,390,83,0.0,19,0,1984-04-29 00:00:00 -16822,390,101,2.0,12,0,1984-04-29 00:00:00 -16823,390,183,0.0,16,0,1984-04-29 00:00:00 -16824,390,104,9.0,3,1,1984-04-29 00:00:00 -16825,390,187,0.0,27,0,1984-04-29 00:00:00 -16826,390,111,0.0,26,0,1984-04-29 00:00:00 -16827,390,182,0.0,18,0,1984-04-29 00:00:00 -16828,390,159,0.0,25,0,1984-04-29 00:00:00 -16829,390,162,4.0,7,0,1984-04-29 00:00:00 -16830,390,169,0.0,21,0,1984-04-29 00:00:00 -16831,390,171,0.0,24,0,1984-04-29 00:00:00 -16832,390,94,0.0,20,0,1984-04-29 00:00:00 -16833,390,172,6.0,6,0,1984-04-29 00:00:00 -16834,390,136,0.0,17,0,1984-04-29 00:00:00 -16835,390,157,3.0,9,0,1984-04-29 00:00:00 -16836,390,174,2.0,10,0,1984-04-29 00:00:00 -16837,390,175,0.0,14,0,1984-04-29 00:00:00 -16838,390,122,1.0,13,0,1984-04-29 00:00:00 -16839,390,117,10.0,2,0,1984-04-29 00:00:00 -16840,390,109,2.0,11,0,1984-04-29 00:00:00 -16841,390,118,3.0,8,0,1984-04-29 00:00:00 -16842,390,181,9.0,4,1,1984-04-29 00:00:00 -16843,390,155,0.0,15,0,1984-04-29 00:00:00 -16844,391,174,2.0,12,0,1984-05-06 00:00:00 -16845,391,176,9.0,7,0,1984-05-06 00:00:00 -16846,391,183,0.0,15,0,1984-05-06 00:00:00 -16847,391,157,3.0,8,0,1984-05-06 00:00:00 -16848,391,116,24.0,1,2,1984-05-06 00:00:00 -16849,391,155,0.0,16,0,1984-05-06 00:00:00 -16850,391,182,0.0,18,0,1984-05-06 00:00:00 -16851,391,136,0.0,17,0,1984-05-06 00:00:00 -16852,391,187,0.0,20,0,1984-05-06 00:00:00 -16853,391,83,0.0,21,0,1984-05-06 00:00:00 -16854,391,122,3.0,10,0,1984-05-06 00:00:00 -16855,391,172,10.0,4,0,1984-05-06 00:00:00 -16856,391,175,0.0,14,0,1984-05-06 00:00:00 -16857,391,101,2.0,13,0,1984-05-06 00:00:00 -16858,391,109,3.0,11,0,1984-05-06 00:00:00 -16859,391,118,3.0,9,0,1984-05-06 00:00:00 -16860,391,181,9.0,6,1,1984-05-06 00:00:00 -16861,391,94,0.0,22,0,1984-05-06 00:00:00 -16862,391,169,0.0,23,0,1984-05-06 00:00:00 -16863,391,162,10.0,3,0,1984-05-06 00:00:00 -16864,391,159,0.0,28,0,1984-05-06 00:00:00 -16865,391,111,0.0,19,0,1984-05-06 00:00:00 -16866,391,171,0.0,26,0,1984-05-06 00:00:00 -16867,391,104,9.0,5,1,1984-05-06 00:00:00 -16868,391,184,0.0,24,0,1984-05-06 00:00:00 -16869,391,188,0.0,27,0,1984-05-06 00:00:00 -16870,391,117,13.0,2,0,1984-05-06 00:00:00 -16871,391,180,0.0,25,0,1984-05-06 00:00:00 -16872,392,172,12.0,5,0,1984-05-20 00:00:00 -16873,392,157,3.0,10,0,1984-05-20 00:00:00 -16874,392,176,10.0,6,0,1984-05-20 00:00:00 -16875,392,116,24.0,1,2,1984-05-20 00:00:00 -16876,392,174,8.0,8,0,1984-05-20 00:00:00 -16877,392,188,0.0,28,0,1984-05-20 00:00:00 -16878,392,180,0.0,27,0,1984-05-20 00:00:00 -16879,392,184,0.0,26,0,1984-05-20 00:00:00 -16880,392,83,0.0,25,0,1984-05-20 00:00:00 -16881,392,183,0.0,16,0,1984-05-20 00:00:00 -16882,392,104,9.0,7,1,1984-05-20 00:00:00 -16883,392,171,0.0,18,0,1984-05-20 00:00:00 -16884,392,187,0.0,24,0,1984-05-20 00:00:00 -16885,392,111,0.0,23,0,1984-05-20 00:00:00 -16886,392,182,0.0,21,0,1984-05-20 00:00:00 -16887,392,101,2.0,14,0,1984-05-20 00:00:00 -16888,392,162,13.0,4,0,1984-05-20 00:00:00 -16889,392,159,0.0,22,0,1984-05-20 00:00:00 -16890,392,122,3.0,13,0,1984-05-20 00:00:00 -16891,392,175,0.0,15,0,1984-05-20 00:00:00 -16892,392,155,0.0,17,0,1984-05-20 00:00:00 -16893,392,109,3.0,12,0,1984-05-20 00:00:00 -16894,392,117,13.0,3,0,1984-05-20 00:00:00 -16895,392,181,18.0,2,2,1984-05-20 00:00:00 -16896,392,94,4.0,9,0,1984-05-20 00:00:00 -16897,392,136,0.0,19,0,1984-05-20 00:00:00 -16898,392,169,0.0,20,0,1984-05-20 00:00:00 -16899,392,118,3.0,11,0,1984-05-20 00:00:00 -16900,393,182,0.0,22,0,1984-06-03 00:00:00 -16901,393,171,0.0,18,0,1984-06-03 00:00:00 -16902,393,111,0.0,24,0,1984-06-03 00:00:00 -16903,393,187,0.0,25,0,1984-06-03 00:00:00 -16904,393,104,9.5,7,1,1984-06-03 00:00:00 -16905,393,189,0.0,28,0,1984-06-03 00:00:00 -16906,393,101,5.0,9,0,1984-06-03 00:00:00 -16907,393,83,0.0,26,0,1984-06-03 00:00:00 -16908,393,184,0.0,27,0,1984-06-03 00:00:00 -16909,393,188,0.0,29,0,1984-06-03 00:00:00 -16910,393,159,0.0,16,0,1984-06-03 00:00:00 -16911,393,183,0.0,17,0,1984-06-03 00:00:00 -16912,393,162,15.0,3,0,1984-06-03 00:00:00 -16913,393,180,0.0,23,0,1984-06-03 00:00:00 -16914,393,136,0.0,20,0,1984-06-03 00:00:00 -16915,393,169,0.0,21,0,1984-06-03 00:00:00 -16916,393,176,11.5,6,0,1984-06-03 00:00:00 -16917,393,172,13.0,5,0,1984-06-03 00:00:00 -16918,393,157,3.0,11,0,1984-06-03 00:00:00 -16919,393,174,8.0,8,0,1984-06-03 00:00:00 -16920,393,122,3.0,14,0,1984-06-03 00:00:00 -16921,393,116,28.5,1,3,1984-06-03 00:00:00 -16922,393,155,0.0,19,0,1984-06-03 00:00:00 -16923,393,117,13.0,4,0,1984-06-03 00:00:00 -16924,393,109,3.0,13,0,1984-06-03 00:00:00 -16925,393,118,3.0,12,0,1984-06-03 00:00:00 -16926,393,181,18.0,2,2,1984-06-03 00:00:00 -16927,393,94,4.0,10,0,1984-06-03 00:00:00 -16928,393,175,0.0,15,0,1984-06-03 00:00:00 -16929,394,183,0.0,18,0,1984-06-17 00:00:00 -16930,394,111,0.0,24,0,1984-06-17 00:00:00 -16931,394,187,0.0,22,0,1984-06-17 00:00:00 -16932,394,171,0.0,19,0,1984-06-17 00:00:00 -16933,394,104,9.5,7,1,1984-06-17 00:00:00 -16934,394,101,5.0,10,0,1984-06-17 00:00:00 -16935,394,190,0.0,31,0,1984-06-17 00:00:00 -16936,394,184,0.0,27,0,1984-06-17 00:00:00 -16937,394,180,0.0,21,0,1984-06-17 00:00:00 -16938,394,188,0.0,30,0,1984-06-17 00:00:00 -16939,394,189,0.0,29,0,1984-06-17 00:00:00 -16940,394,178,0.0,28,0,1984-06-17 00:00:00 -16941,394,83,0.0,26,0,1984-06-17 00:00:00 -16942,394,159,0.0,17,0,1984-06-17 00:00:00 -16943,394,182,0.0,25,0,1984-06-17 00:00:00 -16944,394,169,0.0,23,0,1984-06-17 00:00:00 -16945,394,116,32.5,1,3,1984-06-17 00:00:00 -16946,394,162,17.0,3,0,1984-06-17 00:00:00 -16947,394,176,11.5,6,0,1984-06-17 00:00:00 -16948,394,172,16.0,4,0,1984-06-17 00:00:00 -16949,394,157,3.0,12,0,1984-06-17 00:00:00 -16950,394,122,3.0,15,0,1984-06-17 00:00:00 -16951,394,175,0.0,16,0,1984-06-17 00:00:00 -16952,394,174,8.0,9,0,1984-06-17 00:00:00 -16953,394,117,13.0,5,0,1984-06-17 00:00:00 -16954,394,109,3.0,14,0,1984-06-17 00:00:00 -16955,394,118,3.0,13,0,1984-06-17 00:00:00 -16956,394,181,24.0,2,2,1984-06-17 00:00:00 -16957,394,94,5.0,11,0,1984-06-17 00:00:00 -16958,394,136,9.0,8,1,1984-06-17 00:00:00 -16959,394,155,0.0,20,0,1984-06-17 00:00:00 -16960,395,104,9.5,8,1,1984-06-24 00:00:00 -16961,395,182,0.0,25,0,1984-06-24 00:00:00 -16962,395,159,0.0,19,0,1984-06-24 00:00:00 -16963,395,187,0.0,23,0,1984-06-24 00:00:00 -16964,395,171,2.0,17,0,1984-06-24 00:00:00 -16965,395,183,0.0,20,0,1984-06-24 00:00:00 -16966,395,178,0.0,27,0,1984-06-24 00:00:00 -16967,395,83,0.0,26,0,1984-06-24 00:00:00 -16968,395,184,0.0,28,0,1984-06-24 00:00:00 -16969,395,180,0.0,22,0,1984-06-24 00:00:00 -16970,395,188,0.0,30,0,1984-06-24 00:00:00 -16971,395,189,0.0,29,0,1984-06-24 00:00:00 -16972,395,190,0.0,31,0,1984-06-24 00:00:00 -16973,395,101,5.0,10,0,1984-06-24 00:00:00 -16974,395,162,17.0,5,0,1984-06-24 00:00:00 -16975,395,111,0.0,24,0,1984-06-24 00:00:00 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00:00:00 -16999,396,180,0.0,22,0,1984-07-08 00:00:00 -17000,396,189,0.0,20,0,1984-07-08 00:00:00 -17001,396,178,0.0,28,0,1984-07-08 00:00:00 -17002,396,190,0.0,31,0,1984-07-08 00:00:00 -17003,396,182,0.0,26,0,1984-07-08 00:00:00 -17004,396,83,0.0,27,0,1984-07-08 00:00:00 -17005,396,159,2.0,18,0,1984-07-08 00:00:00 -17006,396,162,23.0,4,0,1984-07-08 00:00:00 -17007,396,169,4.0,13,0,1984-07-08 00:00:00 -17008,396,176,20.5,5,1,1984-07-08 00:00:00 -17009,396,172,26.0,2,0,1984-07-08 00:00:00 -17010,396,157,3.0,14,0,1984-07-08 00:00:00 -17011,396,174,8.0,9,0,1984-07-08 00:00:00 -17012,396,122,3.0,17,0,1984-07-08 00:00:00 -17013,396,175,0.0,19,0,1984-07-08 00:00:00 -17014,396,116,35.5,1,3,1984-07-08 00:00:00 -17015,396,117,13.0,7,0,1984-07-08 00:00:00 -17016,396,109,3.0,16,0,1984-07-08 00:00:00 -17017,396,118,3.0,15,0,1984-07-08 00:00:00 -17018,396,181,24.0,3,2,1984-07-08 00:00:00 -17019,396,94,6.0,10,0,1984-07-08 00:00:00 -17020,396,136,18.0,6,2,1984-07-08 00:00:00 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00:00:00 -17044,397,122,3.0,17,0,1984-07-22 00:00:00 -17045,397,174,8.0,10,0,1984-07-22 00:00:00 -17046,397,117,19.0,6,0,1984-07-22 00:00:00 -17047,397,109,3.0,16,0,1984-07-22 00:00:00 -17048,397,118,3.0,15,0,1984-07-22 00:00:00 -17049,397,181,33.0,2,3,1984-07-22 00:00:00 -17050,397,94,6.0,11,0,1984-07-22 00:00:00 -17051,397,136,18.0,7,2,1984-07-22 00:00:00 -17052,397,175,0.0,19,0,1984-07-22 00:00:00 -17053,398,182,0.0,24,0,1984-08-05 00:00:00 -17054,398,111,0.0,27,0,1984-08-05 00:00:00 -17055,398,187,0.0,25,0,1984-08-05 00:00:00 -17056,398,171,5.0,12,0,1984-08-05 00:00:00 -17057,398,104,11.5,8,1,1984-08-05 00:00:00 -17058,398,189,0.0,20,0,1984-08-05 00:00:00 -17059,398,101,9.0,10,0,1984-08-05 00:00:00 -17060,398,83,0.0,28,0,1984-08-05 00:00:00 -17061,398,184,0.0,29,0,1984-08-05 00:00:00 -17062,398,180,0.0,21,0,1984-08-05 00:00:00 -17063,398,188,0.0,30,0,1984-08-05 00:00:00 -17064,398,159,2.0,18,0,1984-08-05 00:00:00 -17065,398,183,0.0,22,0,1984-08-05 00:00:00 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00:00:00 -17089,399,180,0.0,22,0,1984-08-19 00:00:00 -17090,399,184,0.0,30,0,1984-08-19 00:00:00 -17091,399,83,0.0,29,0,1984-08-19 00:00:00 -17092,399,101,9.0,10,0,1984-08-19 00:00:00 -17093,399,183,0.0,23,0,1984-08-19 00:00:00 -17094,399,104,15.5,8,1,1984-08-19 00:00:00 -17095,399,171,5.0,13,0,1984-08-19 00:00:00 -17096,399,187,0.0,25,0,1984-08-19 00:00:00 -17097,399,111,0.0,27,0,1984-08-19 00:00:00 -17098,399,182,0.0,21,0,1984-08-19 00:00:00 -17099,399,159,2.0,18,0,1984-08-19 00:00:00 -17100,399,162,25.0,4,0,1984-08-19 00:00:00 -17101,399,169,7.0,12,0,1984-08-19 00:00:00 -17102,399,136,24.0,5,2,1984-08-19 00:00:00 -17103,399,94,9.0,11,0,1984-08-19 00:00:00 -17104,399,181,48.0,1,4,1984-08-19 00:00:00 -17105,399,118,3.0,16,0,1984-08-19 00:00:00 -17106,399,109,3.0,17,0,1984-08-19 00:00:00 -17107,399,117,23.0,6,0,1984-08-19 00:00:00 -17108,399,155,0.0,24,0,1984-08-19 00:00:00 -17109,399,175,1.0,19,0,1984-08-19 00:00:00 -17110,399,122,5.0,14,0,1984-08-19 00:00:00 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00:00:00 -17224,403,178,0.0,28,0,1984-10-21 00:00:00 -17225,403,189,0.0,24,0,1984-10-21 00:00:00 -17226,403,188,0.0,21,0,1984-10-21 00:00:00 -17227,403,83,0.0,31,0,1984-10-21 00:00:00 -17228,403,190,0.0,34,0,1984-10-21 00:00:00 -17229,403,101,13.0,9,0,1984-10-21 00:00:00 -17230,403,182,0.0,23,0,1984-10-21 00:00:00 -17231,403,104,30.5,4,1,1984-10-21 00:00:00 -17232,403,159,2.0,19,0,1984-10-21 00:00:00 -17233,403,162,27.0,6,0,1984-10-21 00:00:00 -17234,403,169,9.0,12,0,1984-10-21 00:00:00 -17235,403,183,0.0,25,0,1984-10-21 00:00:00 -17236,403,187,0.0,29,0,1984-10-21 00:00:00 -17237,403,94,13.0,10,0,1984-10-21 00:00:00 -17238,403,181,72.0,1,5,1984-10-21 00:00:00 -17239,403,118,8.0,13,0,1984-10-21 00:00:00 -17240,403,109,3.0,18,0,1984-10-21 00:00:00 -17241,403,117,23.0,7,0,1984-10-21 00:00:00 -17242,403,136,29.0,5,2,1984-10-21 00:00:00 -17243,403,175,1.0,20,0,1984-10-21 00:00:00 -17244,403,122,5.0,15,0,1984-10-21 00:00:00 -17245,403,174,11.0,11,0,1984-10-21 00:00:00 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00:00:00 -17292,405,157,0.0,18,0,1985-04-21 00:00:00 -17293,405,139,0.0,10,0,1985-04-21 00:00:00 -17294,405,172,7.0,4,0,1985-04-21 00:00:00 -17295,405,162,3.0,6,0,1985-04-21 00:00:00 -17296,405,174,6.0,5,0,1985-04-21 00:00:00 -17297,405,171,1.0,8,0,1985-04-21 00:00:00 -17298,405,180,0.0,16,0,1985-04-21 00:00:00 -17299,405,83,0.0,12,0,1985-04-21 00:00:00 -17300,405,116,9.0,2,1,1985-04-21 00:00:00 -17301,405,117,0.0,11,0,1985-04-21 00:00:00 -17302,405,122,0.0,15,0,1985-04-21 00:00:00 -17303,405,159,0.0,13,0,1985-04-21 00:00:00 -17304,405,111,0.0,14,0,1985-04-21 00:00:00 -17305,406,93,0.0,23,0,1985-05-05 00:00:00 -17306,406,118,0.0,25,0,1985-05-05 00:00:00 -17307,406,181,3.0,8,0,1985-05-05 00:00:00 -17308,406,109,0.0,20,0,1985-05-05 00:00:00 -17309,406,157,0.0,19,0,1985-05-05 00:00:00 -17310,406,184,1.0,12,0,1985-05-05 00:00:00 -17311,406,94,4.0,7,0,1985-05-05 00:00:00 -17312,406,183,0.0,24,0,1985-05-05 00:00:00 -17313,406,136,0.0,15,0,1985-05-05 00:00:00 -17314,406,101,9.0,4,1,1985-05-05 00:00:00 -17315,406,155,0.0,27,0,1985-05-05 00:00:00 -17316,406,182,0.0,26,0,1985-05-05 00:00:00 -17317,406,76,0.0,21,0,1985-05-05 00:00:00 -17318,406,176,0.0,22,0,1985-05-05 00:00:00 -17319,406,159,0.0,16,0,1985-05-05 00:00:00 -17320,406,116,9.0,5,1,1985-05-05 00:00:00 -17321,406,104,12.0,2,0,1985-05-05 00:00:00 -17322,406,172,16.0,1,1,1985-05-05 00:00:00 -17323,406,162,3.0,9,0,1985-05-05 00:00:00 -17324,406,174,10.0,3,0,1985-05-05 00:00:00 -17325,406,180,0.0,18,0,1985-05-05 00:00:00 -17326,406,139,1.0,10,0,1985-05-05 00:00:00 -17327,406,83,0.0,14,0,1985-05-05 00:00:00 -17328,406,111,0.0,17,0,1985-05-05 00:00:00 -17329,406,117,0.0,13,0,1985-05-05 00:00:00 -17330,406,122,6.0,6,0,1985-05-05 00:00:00 -17331,406,171,1.0,11,0,1985-05-05 00:00:00 -17332,407,101,9.0,5,1,1985-05-19 00:00:00 -17333,407,157,0.0,22,0,1985-05-19 00:00:00 -17334,407,93,0.0,26,0,1985-05-19 00:00:00 -17335,407,181,3.0,8,0,1985-05-19 00:00:00 -17336,407,109,3.0,9,0,1985-05-19 00:00:00 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00:00:00 -17360,408,175,0.0,24,0,1985-06-16 00:00:00 -17361,408,181,3.0,11,0,1985-06-16 00:00:00 -17362,408,109,3.0,10,0,1985-06-16 00:00:00 -17363,408,118,0.0,20,0,1985-06-16 00:00:00 -17364,408,176,3.0,9,0,1985-06-16 00:00:00 -17365,408,169,0.0,26,0,1985-06-16 00:00:00 -17366,408,182,0.0,29,0,1985-06-16 00:00:00 -17367,408,184,1.0,15,0,1985-06-16 00:00:00 -17368,408,136,0.0,17,0,1985-06-16 00:00:00 -17369,408,183,0.0,28,0,1985-06-16 00:00:00 -17370,408,93,0.0,27,0,1985-06-16 00:00:00 -17371,408,94,5.0,8,0,1985-06-16 00:00:00 -17372,408,155,0.0,21,0,1985-06-16 00:00:00 -17373,408,157,0.0,25,0,1985-06-16 00:00:00 -17374,408,171,2.0,14,0,1985-06-16 00:00:00 -17375,408,76,0.0,23,0,1985-06-16 00:00:00 -17376,408,83,0.0,16,0,1985-06-16 00:00:00 -17377,408,162,3.0,12,0,1985-06-16 00:00:00 -17378,408,172,22.0,3,1,1985-06-16 00:00:00 -17379,408,104,27.0,1,1,1985-06-16 00:00:00 -17380,408,116,22.0,2,2,1985-06-16 00:00:00 -17381,408,101,9.0,5,1,1985-06-16 00:00:00 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00:00:00 -17405,409,117,2.0,14,0,1985-06-23 00:00:00 -17406,409,122,6.0,8,0,1985-06-23 00:00:00 -17407,409,118,0.0,22,0,1985-06-23 00:00:00 -17408,409,169,0.0,26,0,1985-06-23 00:00:00 -17409,409,155,0.0,24,0,1985-06-23 00:00:00 -17410,409,184,4.0,10,0,1985-06-23 00:00:00 -17411,409,175,0.0,18,0,1985-06-23 00:00:00 -17412,409,183,0.0,28,0,1985-06-23 00:00:00 -17413,409,94,5.0,9,0,1985-06-23 00:00:00 -17414,409,182,0.0,29,0,1985-06-23 00:00:00 -17415,409,176,12.0,5,1,1985-06-23 00:00:00 -17416,409,109,3.0,11,0,1985-06-23 00:00:00 -17417,409,136,1.0,16,0,1985-06-23 00:00:00 -17418,410,83,0.0,18,0,1985-07-07 00:00:00 -17419,410,122,6.0,9,0,1985-07-07 00:00:00 -17420,410,162,3.0,14,0,1985-07-07 00:00:00 -17421,410,104,31.0,1,1,1985-07-07 00:00:00 -17422,410,111,0.0,21,0,1985-07-07 00:00:00 -17423,410,180,0.0,25,0,1985-07-07 00:00:00 -17424,410,116,26.0,2,2,1985-07-07 00:00:00 -17425,410,139,16.0,5,0,1985-07-07 00:00:00 -17426,410,176,18.0,4,1,1985-07-07 00:00:00 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00:00:00 -17450,411,118,0.0,20,0,1985-07-21 00:00:00 -17451,411,182,0.0,29,0,1985-07-21 00:00:00 -17452,411,175,1.0,17,0,1985-07-21 00:00:00 -17453,411,183,0.0,28,0,1985-07-21 00:00:00 -17454,411,136,13.0,6,1,1985-07-21 00:00:00 -17455,411,184,4.0,12,0,1985-07-21 00:00:00 -17456,411,155,0.0,24,0,1985-07-21 00:00:00 -17457,411,169,0.0,26,0,1985-07-21 00:00:00 -17458,411,157,0.0,21,0,1985-07-21 00:00:00 -17459,411,94,5.0,11,0,1985-07-21 00:00:00 -17460,411,101,9.0,8,1,1985-07-21 00:00:00 -17461,411,181,3.0,15,0,1985-07-21 00:00:00 -17462,411,180,0.0,25,0,1985-07-21 00:00:00 -17463,411,76,0.0,19,0,1985-07-21 00:00:00 -17464,411,116,35.0,2,3,1985-07-21 00:00:00 -17465,411,172,26.0,3,1,1985-07-21 00:00:00 -17466,411,162,3.0,16,0,1985-07-21 00:00:00 -17467,411,174,11.0,7,0,1985-07-21 00:00:00 -17468,411,171,6.0,10,0,1985-07-21 00:00:00 -17469,411,104,37.0,1,1,1985-07-21 00:00:00 -17470,411,83,0.0,18,0,1985-07-21 00:00:00 -17471,411,111,0.0,23,0,1985-07-21 00:00:00 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00:00:00 -17495,412,117,4.0,14,0,1985-08-04 00:00:00 -17496,412,176,18.0,4,1,1985-08-04 00:00:00 -17497,412,169,0.0,27,0,1985-08-04 00:00:00 -17498,412,94,6.0,11,0,1985-08-04 00:00:00 -17499,412,183,0.0,29,0,1985-08-04 00:00:00 -17500,412,136,13.0,6,1,1985-08-04 00:00:00 -17501,412,184,4.0,13,0,1985-08-04 00:00:00 -17502,412,155,0.0,25,0,1985-08-04 00:00:00 -17503,412,182,0.0,30,0,1985-08-04 00:00:00 -17504,412,175,1.0,17,0,1985-08-04 00:00:00 -17505,412,178,0.0,28,0,1985-08-04 00:00:00 -17506,413,181,5.0,12,0,1985-08-18 00:00:00 -17507,413,118,0.0,20,0,1985-08-18 00:00:00 -17508,413,176,18.0,5,1,1985-08-18 00:00:00 -17509,413,182,0.0,31,0,1985-08-18 00:00:00 -17510,413,94,6.0,11,0,1985-08-18 00:00:00 -17511,413,183,0.0,30,0,1985-08-18 00:00:00 -17512,413,169,0.0,28,0,1985-08-18 00:00:00 -17513,413,184,4.0,13,0,1985-08-18 00:00:00 -17514,413,155,0.0,26,0,1985-08-18 00:00:00 -17515,413,93,0.0,25,0,1985-08-18 00:00:00 -17516,413,175,2.0,17,0,1985-08-18 00:00:00 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00:00:00 -17540,414,182,0.0,31,0,1985-08-25 00:00:00 -17541,414,94,7.0,12,0,1985-08-25 00:00:00 -17542,414,183,0.0,30,0,1985-08-25 00:00:00 -17543,414,155,0.0,26,0,1985-08-25 00:00:00 -17544,414,184,4.0,13,0,1985-08-25 00:00:00 -17545,414,169,0.0,28,0,1985-08-25 00:00:00 -17546,414,175,2.0,17,0,1985-08-25 00:00:00 -17547,414,178,0.0,23,0,1985-08-25 00:00:00 -17548,414,185,0.0,29,0,1985-08-25 00:00:00 -17549,414,181,14.0,7,1,1985-08-25 00:00:00 -17550,414,136,13.0,8,1,1985-08-25 00:00:00 -17551,414,93,0.0,25,0,1985-08-25 00:00:00 -17552,414,162,3.0,16,0,1985-08-25 00:00:00 -17553,414,101,19.0,4,1,1985-08-25 00:00:00 -17554,414,157,0.0,21,0,1985-08-25 00:00:00 -17555,414,116,56.0,1,4,1985-08-25 00:00:00 -17556,414,104,53.0,2,2,1985-08-25 00:00:00 -17557,414,172,30.0,3,1,1985-08-25 00:00:00 -17558,414,171,10.0,10,0,1985-08-25 00:00:00 -17559,414,139,19.0,5,0,1985-08-25 00:00:00 -17560,414,174,11.0,9,0,1985-08-25 00:00:00 -17561,414,111,0.0,24,0,1985-08-25 00:00:00 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00:00:00 -17585,415,157,0.0,21,0,1985-09-08 00:00:00 -17586,415,104,53.0,2,2,1985-09-08 00:00:00 -17587,415,172,31.0,3,1,1985-09-08 00:00:00 -17588,415,162,3.0,17,0,1985-09-08 00:00:00 -17589,415,174,11.0,9,0,1985-09-08 00:00:00 -17590,415,171,10.0,10,0,1985-09-08 00:00:00 -17591,415,139,21.0,5,0,1985-09-08 00:00:00 -17592,415,116,65.0,1,5,1985-09-08 00:00:00 -17593,415,93,0.0,26,0,1985-09-08 00:00:00 -17594,415,117,4.0,15,0,1985-09-08 00:00:00 -17595,415,122,9.0,11,0,1985-09-08 00:00:00 -17596,415,159,0.0,22,0,1985-09-08 00:00:00 -17597,415,180,0.0,28,0,1985-09-08 00:00:00 -17598,415,76,0.0,19,0,1985-09-08 00:00:00 -17599,415,101,23.0,4,1,1985-09-08 00:00:00 -17600,415,111,0.0,24,0,1985-09-08 00:00:00 -17601,416,118,0.0,20,0,1985-09-15 00:00:00 -17602,416,176,21.0,5,1,1985-09-15 00:00:00 -17603,416,182,0.0,33,0,1985-09-15 00:00:00 -17604,416,94,13.0,9,0,1985-09-15 00:00:00 -17605,416,183,0.0,31,0,1985-09-15 00:00:00 -17606,416,136,21.0,6,1,1985-09-15 00:00:00 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00:00:00 -17652,417,109,3.0,16,0,1985-10-06 00:00:00 -17653,417,93,0.0,27,0,1985-10-06 00:00:00 -17654,417,181,14.0,9,1,1985-10-06 00:00:00 -17655,417,116,72.0,1,5,1985-10-06 00:00:00 -17656,417,104,53.0,2,2,1985-10-06 00:00:00 -17657,417,172,33.0,4,1,1985-10-06 00:00:00 -17658,417,162,3.0,17,0,1985-10-06 00:00:00 -17659,417,171,10.0,12,0,1985-10-06 00:00:00 -17660,417,139,21.0,8,0,1985-10-06 00:00:00 -17661,417,83,0.0,18,0,1985-10-06 00:00:00 -17662,417,174,11.0,10,0,1985-10-06 00:00:00 -17663,417,117,5.0,14,0,1985-10-06 00:00:00 -17664,417,122,10.0,11,0,1985-10-06 00:00:00 -17665,417,159,0.0,24,0,1985-10-06 00:00:00 -17666,417,180,0.0,29,0,1985-10-06 00:00:00 -17667,417,76,0.0,19,0,1985-10-06 00:00:00 -17668,417,101,38.0,3,2,1985-10-06 00:00:00 -17669,417,157,0.0,23,0,1985-10-06 00:00:00 -17670,417,111,0.0,26,0,1985-10-06 00:00:00 -17671,418,169,0.0,30,0,1985-10-19 00:00:00 -17672,418,182,0.0,36,0,1985-10-19 00:00:00 -17673,418,94,31.0,5,2,1985-10-19 00:00:00 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-18191,435,162,14.0,10,0,1986-10-26 00:00:00 -18192,435,83,8.0,11,0,1986-10-26 00:00:00 -18193,435,76,17.0,7,1,1986-10-26 00:00:00 -18194,435,165,3.0,14,0,1986-10-26 00:00:00 -18195,435,171,14.0,8,0,1986-10-26 00:00:00 -18196,435,173,3.0,13,0,1986-10-26 00:00:00 -18197,435,169,2.0,16,0,1986-10-26 00:00:00 -18198,435,122,0.0,20,0,1986-10-26 00:00:00 -18199,435,104,14.0,9,0,1986-10-26 00:00:00 -18200,435,116,72.0,1,4,1986-10-26 00:00:00 -18201,435,156,1.0,18,0,1986-10-26 00:00:00 -18202,435,172,0.0,25,0,1986-10-26 00:00:00 -18203,436,118,0.0,15,0,1987-04-12 00:00:00 -18204,436,109,0.0,16,0,1987-04-12 00:00:00 -18205,436,117,0.0,17,0,1987-04-12 00:00:00 -18206,436,132,0.0,18,0,1987-04-12 00:00:00 -18207,436,169,0.0,21,0,1987-04-12 00:00:00 -18208,436,83,0.0,20,0,1987-04-12 00:00:00 -18209,436,121,0.0,22,0,1987-04-12 00:00:00 -18210,436,101,0.0,14,0,1987-04-12 00:00:00 -18211,436,144,0.0,19,0,1987-04-12 00:00:00 -18212,436,157,0.0,13,0,1987-04-12 00:00:00 -18213,436,165,0.0,11,0,1987-04-12 00:00:00 -18214,436,139,4.0,3,0,1987-04-12 00:00:00 -18215,436,155,0.0,10,0,1987-04-12 00:00:00 -18216,436,156,0.0,9,0,1987-04-12 00:00:00 -18217,436,104,0.0,8,0,1987-04-12 00:00:00 -18218,436,137,0.0,7,0,1987-04-12 00:00:00 -18219,436,94,1.0,6,0,1987-04-12 00:00:00 -18220,436,122,2.0,5,0,1987-04-12 00:00:00 -18221,436,76,3.0,4,0,1987-04-12 00:00:00 -18222,436,136,6.0,2,0,1987-04-12 00:00:00 -18223,436,116,9.0,1,1,1987-04-12 00:00:00 -18224,436,168,0.0,12,0,1987-04-12 00:00:00 -18225,437,144,0.0,22,0,1987-05-03 00:00:00 -18226,437,132,0.0,18,0,1987-05-03 00:00:00 -18227,437,109,0.0,21,0,1987-05-03 00:00:00 -18228,437,83,2.0,9,0,1987-05-03 00:00:00 -18229,437,117,0.0,16,0,1987-05-03 00:00:00 -18230,437,169,0.0,20,0,1987-05-03 00:00:00 -18231,437,162,0.0,27,0,1987-05-03 00:00:00 -18232,437,111,0.0,15,0,1987-05-03 00:00:00 -18233,437,166,0.0,23,0,1987-05-03 00:00:00 -18234,437,98,0.0,24,0,1987-05-03 00:00:00 -18235,437,159,0.0,26,0,1987-05-03 00:00:00 -18236,437,121,0.0,25,0,1987-05-03 00:00:00 -18237,437,118,0.0,13,0,1987-05-03 00:00:00 -18238,437,136,6.0,5,0,1987-05-03 00:00:00 -18239,437,157,0.0,19,0,1987-05-03 00:00:00 -18240,437,101,6.0,4,0,1987-05-03 00:00:00 -18241,437,139,7.0,3,0,1987-05-03 00:00:00 -18242,437,76,3.0,7,0,1987-05-03 00:00:00 -18243,437,122,2.0,8,0,1987-05-03 00:00:00 -18244,437,94,10.0,1,1,1987-05-03 00:00:00 -18245,437,116,9.0,2,1,1987-05-03 00:00:00 -18246,437,104,4.0,6,0,1987-05-03 00:00:00 -18247,437,156,0.0,11,0,1987-05-03 00:00:00 -18248,437,155,0.0,14,0,1987-05-03 00:00:00 -18249,437,165,0.0,12,0,1987-05-03 00:00:00 -18250,437,168,0.0,17,0,1987-05-03 00:00:00 -18251,437,137,1.0,10,0,1987-05-03 00:00:00 -18252,438,117,0.0,21,0,1987-05-17 00:00:00 -18253,438,132,0.0,22,0,1987-05-17 00:00:00 -18254,438,144,0.0,25,0,1987-05-17 00:00:00 -18255,438,83,2.0,11,0,1987-05-17 00:00:00 -18256,438,169,0.0,23,0,1987-05-17 00:00:00 -18257,438,166,0.0,26,0,1987-05-17 00:00:00 -18258,438,111,0.0,17,0,1987-05-17 00:00:00 -18259,438,98,0.0,27,0,1987-05-17 00:00:00 -18260,438,159,0.0,15,0,1987-05-17 00:00:00 -18261,438,162,1.0,13,0,1987-05-17 00:00:00 -18262,438,109,4.0,7,0,1987-05-17 00:00:00 -18263,438,121,0.0,24,0,1987-05-17 00:00:00 -18264,438,118,0.0,18,0,1987-05-17 00:00:00 -18265,438,155,0.0,20,0,1987-05-17 00:00:00 -18266,438,157,3.0,8,0,1987-05-17 00:00:00 -18267,438,136,6.0,5,0,1987-05-17 00:00:00 -18268,438,139,13.0,2,0,1987-05-17 00:00:00 -18269,438,76,3.0,9,0,1987-05-17 00:00:00 -18270,438,122,2.0,12,0,1987-05-17 00:00:00 -18271,438,94,10.0,3,1,1987-05-17 00:00:00 -18272,438,101,6.0,4,0,1987-05-17 00:00:00 -18273,438,104,4.0,6,0,1987-05-17 00:00:00 -18274,438,156,0.0,14,0,1987-05-17 00:00:00 -18275,438,116,18.0,1,2,1987-05-17 00:00:00 -18276,438,165,0.0,16,0,1987-05-17 00:00:00 -18277,438,168,0.0,19,0,1987-05-17 00:00:00 -18278,438,137,3.0,10,0,1987-05-17 00:00:00 -18279,439,132,0.0,24,0,1987-05-31 00:00:00 -18280,439,144,0.0,25,0,1987-05-31 00:00:00 -18281,439,83,2.0,11,0,1987-05-31 00:00:00 -18282,439,169,0.0,20,0,1987-05-31 00:00:00 -18283,439,121,1.0,15,0,1987-05-31 00:00:00 -18284,439,98,0.0,27,0,1987-05-31 00:00:00 -18285,439,166,0.0,26,0,1987-05-31 00:00:00 -18286,439,159,0.0,17,0,1987-05-31 00:00:00 -18287,439,162,1.0,14,0,1987-05-31 00:00:00 -18288,439,117,0.0,23,0,1987-05-31 00:00:00 -18289,439,111,0.0,19,0,1987-05-31 00:00:00 -18290,439,109,4.0,8,0,1987-05-31 00:00:00 -18291,439,118,0.0,21,0,1987-05-31 00:00:00 -18292,439,116,18.0,1,2,1987-05-31 00:00:00 -18293,439,101,15.0,2,1,1987-05-31 00:00:00 -18294,439,136,12.0,4,0,1987-05-31 00:00:00 -18295,439,139,13.0,3,0,1987-05-31 00:00:00 -18296,439,76,6.0,7,0,1987-05-31 00:00:00 -18297,439,94,10.0,5,1,1987-05-31 00:00:00 -18298,439,137,3.0,10,0,1987-05-31 00:00:00 -18299,439,122,2.0,13,0,1987-05-31 00:00:00 -18300,439,156,0.0,16,0,1987-05-31 00:00:00 -18301,439,155,2.0,12,0,1987-05-31 00:00:00 -18302,439,165,0.0,18,0,1987-05-31 00:00:00 -18303,439,168,0.0,22,0,1987-05-31 00:00:00 -18304,439,157,3.0,9,0,1987-05-31 00:00:00 -18305,439,104,8.0,6,0,1987-05-31 00:00:00 -18306,440,83,2.0,11,0,1987-06-21 00:00:00 -18307,440,117,0.0,23,0,1987-06-21 00:00:00 -18308,440,132,0.0,24,0,1987-06-21 00:00:00 -18309,440,144,0.0,25,0,1987-06-21 00:00:00 -18310,440,169,0.0,20,0,1987-06-21 00:00:00 -18311,440,109,4.0,8,0,1987-06-21 00:00:00 -18312,440,111,0.0,19,0,1987-06-21 00:00:00 -18313,440,166,0.0,26,0,1987-06-21 00:00:00 -18314,440,98,0.0,27,0,1987-06-21 00:00:00 -18315,440,159,0.0,17,0,1987-06-21 00:00:00 -18316,440,162,1.0,14,0,1987-06-21 00:00:00 -18317,440,121,1.0,15,0,1987-06-21 00:00:00 -18318,440,118,0.0,21,0,1987-06-21 00:00:00 -18319,440,116,22.0,2,2,1987-06-21 00:00:00 -18320,440,157,4.0,9,0,1987-06-21 00:00:00 -18321,440,101,24.0,1,2,1987-06-21 00:00:00 -18322,440,136,18.0,3,0,1987-06-21 00:00:00 -18323,440,139,13.0,4,0,1987-06-21 00:00:00 -18324,440,76,9.0,6,0,1987-06-21 00:00:00 -18325,440,94,12.0,5,1,1987-06-21 00:00:00 -18326,440,122,2.0,13,0,1987-06-21 00:00:00 -18327,440,104,8.0,7,0,1987-06-21 00:00:00 -18328,440,156,0.0,16,0,1987-06-21 00:00:00 -18329,440,155,2.0,12,0,1987-06-21 00:00:00 -18330,440,165,0.0,18,0,1987-06-21 00:00:00 -18331,440,168,0.0,22,0,1987-06-21 00:00:00 -18332,440,137,3.0,10,0,1987-06-21 00:00:00 -18333,441,83,2.0,12,0,1987-07-05 00:00:00 -18334,441,117,0.0,23,0,1987-07-05 00:00:00 -18335,441,132,0.0,24,0,1987-07-05 00:00:00 -18336,441,144,0.0,26,0,1987-07-05 00:00:00 -18337,441,109,4.0,8,0,1987-07-05 00:00:00 -18338,441,162,1.0,16,0,1987-07-05 00:00:00 -18339,441,121,1.0,17,0,1987-07-05 00:00:00 -18340,441,111,0.0,20,0,1987-07-05 00:00:00 -18341,441,166,0.0,25,0,1987-07-05 00:00:00 -18342,441,98,0.0,27,0,1987-07-05 00:00:00 -18343,441,159,0.0,19,0,1987-07-05 00:00:00 -18344,441,169,2.0,13,0,1987-07-05 00:00:00 -18345,441,118,0.0,21,0,1987-07-05 00:00:00 -18346,441,104,8.0,7,0,1987-07-05 00:00:00 -18347,441,157,4.0,9,0,1987-07-05 00:00:00 -18348,441,116,26.0,2,2,1987-07-05 00:00:00 -18349,441,136,24.0,3,0,1987-07-05 00:00:00 -18350,441,139,13.0,5,0,1987-07-05 00:00:00 -18351,441,122,2.0,14,0,1987-07-05 00:00:00 -18352,441,94,21.0,4,2,1987-07-05 00:00:00 -18353,441,76,9.0,6,0,1987-07-05 00:00:00 -18354,441,156,0.0,18,0,1987-07-05 00:00:00 -18355,441,155,2.0,11,0,1987-07-05 00:00:00 -18356,441,165,1.0,15,0,1987-07-05 00:00:00 -18357,441,168,0.0,22,0,1987-07-05 00:00:00 -18358,441,137,3.0,10,0,1987-07-05 00:00:00 -18359,441,101,27.0,1,2,1987-07-05 00:00:00 -18360,442,83,2.0,13,0,1987-07-12 00:00:00 -18361,442,117,2.0,15,0,1987-07-12 00:00:00 -18362,442,132,0.0,24,0,1987-07-12 00:00:00 -18363,442,144,0.0,26,0,1987-07-12 00:00:00 -18364,442,162,1.0,17,0,1987-07-12 00:00:00 -18365,442,111,0.0,21,0,1987-07-12 00:00:00 -18366,442,166,0.0,25,0,1987-07-12 00:00:00 -18367,442,98,0.0,27,0,1987-07-12 00:00:00 -18368,442,159,0.0,20,0,1987-07-12 00:00:00 -18369,442,109,4.0,9,0,1987-07-12 00:00:00 -18370,442,121,1.0,18,0,1987-07-12 00:00:00 -18371,442,118,0.0,23,0,1987-07-12 00:00:00 -18372,442,169,3.0,11,0,1987-07-12 00:00:00 -18373,442,157,4.0,10,0,1987-07-12 00:00:00 -18374,442,101,31.0,1,2,1987-07-12 00:00:00 -18375,442,136,30.0,3,0,1987-07-12 00:00:00 -18376,442,139,13.0,5,0,1987-07-12 00:00:00 -18377,442,76,9.0,6,0,1987-07-12 00:00:00 -18378,442,122,2.0,14,0,1987-07-12 00:00:00 -18379,442,94,30.0,2,3,1987-07-12 00:00:00 -18380,442,116,26.0,4,2,1987-07-12 00:00:00 -18381,442,104,8.0,7,0,1987-07-12 00:00:00 -18382,442,156,0.0,19,0,1987-07-12 00:00:00 -18383,442,155,2.0,12,0,1987-07-12 00:00:00 -18384,442,165,1.0,16,0,1987-07-12 00:00:00 -18385,442,137,6.0,8,0,1987-07-12 00:00:00 -18386,442,168,0.0,22,0,1987-07-12 00:00:00 -18387,443,109,4.0,9,0,1987-07-26 00:00:00 -18388,443,117,2.0,16,0,1987-07-26 00:00:00 -18389,443,132,0.0,24,0,1987-07-26 00:00:00 -18390,443,144,0.0,26,0,1987-07-26 00:00:00 -18391,443,121,1.0,19,0,1987-07-26 00:00:00 -18392,443,169,3.0,13,0,1987-07-26 00:00:00 -18393,443,111,1.0,17,0,1987-07-26 00:00:00 -18394,443,159,0.0,21,0,1987-07-26 00:00:00 -18395,443,98,0.0,27,0,1987-07-26 00:00:00 -18396,443,118,0.0,23,0,1987-07-26 00:00:00 -18397,443,83,2.0,14,0,1987-07-26 00:00:00 -18398,443,101,35.0,2,2,1987-07-26 00:00:00 -18399,443,137,6.0,8,0,1987-07-26 00:00:00 -18400,443,168,0.0,22,0,1987-07-26 00:00:00 -18401,443,165,4.0,10,0,1987-07-26 00:00:00 -18402,443,155,4.0,12,0,1987-07-26 00:00:00 -18403,443,156,0.0,20,0,1987-07-26 00:00:00 -18404,443,104,8.0,7,0,1987-07-26 00:00:00 -18405,443,94,30.0,3,3,1987-07-26 00:00:00 -18406,443,122,2.0,15,0,1987-07-26 00:00:00 -18407,443,76,9.0,6,0,1987-07-26 00:00:00 -18408,443,139,19.0,5,0,1987-07-26 00:00:00 -18409,443,136,39.0,1,1,1987-07-26 00:00:00 -18410,443,116,26.0,4,2,1987-07-26 00:00:00 -18411,443,157,4.0,11,0,1987-07-26 00:00:00 -18412,443,162,1.0,18,0,1987-07-26 00:00:00 -18413,443,166,0.0,25,0,1987-07-26 00:00:00 -18414,444,169,3.0,14,0,1987-08-09 00:00:00 -18415,444,121,1.0,20,0,1987-08-09 00:00:00 -18416,444,162,1.0,19,0,1987-08-09 00:00:00 -18417,444,159,0.0,22,0,1987-08-09 00:00:00 -18418,444,98,0.0,27,0,1987-08-09 00:00:00 -18419,444,166,0.0,26,0,1987-08-09 00:00:00 -18420,444,111,1.0,18,0,1987-08-09 00:00:00 -18421,444,116,30.0,4,2,1987-08-09 00:00:00 -18422,444,139,19.0,5,0,1987-08-09 00:00:00 -18423,444,76,9.0,6,0,1987-08-09 00:00:00 -18424,444,122,5.0,9,0,1987-08-09 00:00:00 -18425,444,94,30.0,3,3,1987-08-09 00:00:00 -18426,444,137,6.0,8,0,1987-08-09 00:00:00 -18427,444,136,48.0,1,2,1987-08-09 00:00:00 -18428,444,156,0.0,21,0,1987-08-09 00:00:00 -18429,444,104,8.0,7,0,1987-08-09 00:00:00 -18430,444,144,0.0,24,0,1987-08-09 00:00:00 -18431,444,132,0.0,25,0,1987-08-09 00:00:00 -18432,444,117,3.0,15,0,1987-08-09 00:00:00 -18433,444,109,4.0,10,0,1987-08-09 00:00:00 -18434,444,118,2.0,17,0,1987-08-09 00:00:00 -18435,444,83,2.0,16,0,1987-08-09 00:00:00 -18436,444,157,4.0,12,0,1987-08-09 00:00:00 -18437,444,168,0.0,23,0,1987-08-09 00:00:00 -18438,444,165,4.0,11,0,1987-08-09 00:00:00 -18439,444,155,4.0,13,0,1987-08-09 00:00:00 -18440,444,101,41.0,2,2,1987-08-09 00:00:00 -18441,445,109,4.0,11,0,1987-08-16 00:00:00 -18442,445,117,3.0,15,0,1987-08-16 00:00:00 -18443,445,132,0.0,25,0,1987-08-16 00:00:00 -18444,445,144,0.0,24,0,1987-08-16 00:00:00 -18445,445,83,2.0,16,0,1987-08-16 00:00:00 -18446,445,166,0.0,26,0,1987-08-16 00:00:00 -18447,445,121,1.0,20,0,1987-08-16 00:00:00 -18448,445,98,0.0,27,0,1987-08-16 00:00:00 -18449,445,159,0.0,22,0,1987-08-16 00:00:00 -18450,445,162,1.0,19,0,1987-08-16 00:00:00 -18451,445,169,7.0,9,0,1987-08-16 00:00:00 -18452,445,118,2.0,17,0,1987-08-16 00:00:00 -18453,445,111,1.0,18,0,1987-08-16 00:00:00 -18454,445,157,4.0,13,0,1987-08-16 00:00:00 -18455,445,136,54.0,1,2,1987-08-16 00:00:00 -18456,445,139,19.0,5,0,1987-08-16 00:00:00 -18457,445,76,9.0,6,0,1987-08-16 00:00:00 -18458,445,122,8.0,8,0,1987-08-16 00:00:00 -18459,445,116,31.0,4,2,1987-08-16 00:00:00 -18460,445,94,39.0,3,4,1987-08-16 00:00:00 -18461,445,101,43.0,2,2,1987-08-16 00:00:00 -18462,445,104,8.0,7,0,1987-08-16 00:00:00 -18463,445,156,0.0,21,0,1987-08-16 00:00:00 -18464,445,155,4.0,14,0,1987-08-16 00:00:00 -18465,445,165,4.0,12,0,1987-08-16 00:00:00 -18466,445,168,0.0,23,0,1987-08-16 00:00:00 -18467,445,137,6.0,10,0,1987-08-16 00:00:00 -18468,446,132,0.0,25,0,1987-09-06 00:00:00 -18469,446,144,0.0,24,0,1987-09-06 00:00:00 -18470,446,83,2.0,16,0,1987-09-06 00:00:00 -18471,446,169,7.0,9,0,1987-09-06 00:00:00 -18472,446,121,1.0,20,0,1987-09-06 00:00:00 -18473,446,98,0.0,27,0,1987-09-06 00:00:00 -18474,446,166,0.0,26,0,1987-09-06 00:00:00 -18475,446,159,0.0,21,0,1987-09-06 00:00:00 -18476,446,162,1.0,19,0,1987-09-06 00:00:00 -18477,446,170,0.0,28,0,1987-09-06 00:00:00 -18478,446,117,3.0,15,0,1987-09-06 00:00:00 -18479,446,111,1.0,18,0,1987-09-06 00:00:00 -18480,446,77,0.0,29,0,1987-09-06 00:00:00 -18481,446,109,4.0,11,0,1987-09-06 00:00:00 -18482,446,101,49.0,2,2,1987-09-06 00:00:00 -18483,446,118,2.0,17,0,1987-09-06 00:00:00 -18484,446,116,31.0,4,2,1987-09-06 00:00:00 -18485,446,136,63.0,1,3,1987-09-06 00:00:00 -18486,446,139,20.0,5,0,1987-09-06 00:00:00 -18487,446,122,10.0,7,0,1987-09-06 00:00:00 -18488,446,94,43.0,3,4,1987-09-06 00:00:00 -18489,446,76,12.0,6,0,1987-09-06 00:00:00 -18490,446,104,8.0,8,0,1987-09-06 00:00:00 -18491,446,156,0.0,22,0,1987-09-06 00:00:00 -18492,446,155,4.0,14,0,1987-09-06 00:00:00 -18493,446,165,4.0,12,0,1987-09-06 00:00:00 -18494,446,168,0.0,23,0,1987-09-06 00:00:00 -18495,446,157,4.0,13,0,1987-09-06 00:00:00 -18496,446,137,6.0,10,0,1987-09-06 00:00:00 -18497,447,121,1.0,19,0,1987-09-20 00:00:00 -18498,447,132,0.0,25,0,1987-09-20 00:00:00 -18499,447,144,0.0,24,0,1987-09-20 00:00:00 -18500,447,83,2.0,16,0,1987-09-20 00:00:00 -18501,447,169,10.0,7,0,1987-09-20 00:00:00 -18502,447,111,1.0,18,0,1987-09-20 00:00:00 -18503,447,117,3.0,15,0,1987-09-20 00:00:00 -18504,447,98,0.0,28,0,1987-09-20 00:00:00 -18505,447,159,0.0,21,0,1987-09-20 00:00:00 -18506,447,162,1.0,20,0,1987-09-20 00:00:00 -18507,447,170,0.0,27,0,1987-09-20 00:00:00 -18508,447,77,0.0,29,0,1987-09-20 00:00:00 -18509,447,166,0.0,26,0,1987-09-20 00:00:00 -18510,447,109,4.0,12,0,1987-09-20 00:00:00 -18511,447,165,4.0,13,0,1987-09-20 00:00:00 -18512,447,101,49.0,2,2,1987-09-20 00:00:00 -18513,447,136,67.0,1,3,1987-09-20 00:00:00 -18514,447,139,22.0,5,0,1987-09-20 00:00:00 -18515,447,76,18.0,6,0,1987-09-20 00:00:00 -18516,447,122,10.0,8,0,1987-09-20 00:00:00 -18517,447,94,43.0,3,4,1987-09-20 00:00:00 -18518,447,137,6.0,10,0,1987-09-20 00:00:00 -18519,447,118,2.0,17,0,1987-09-20 00:00:00 -18520,447,156,0.0,22,0,1987-09-20 00:00:00 -18521,447,155,4.0,14,0,1987-09-20 00:00:00 -18522,447,116,40.0,4,3,1987-09-20 00:00:00 -18523,447,168,0.0,23,0,1987-09-20 00:00:00 -18524,447,157,5.0,11,0,1987-09-20 00:00:00 -18525,447,104,8.0,9,0,1987-09-20 00:00:00 -18526,448,144,0.0,24,0,1987-09-27 00:00:00 -18527,448,83,2.0,16,0,1987-09-27 00:00:00 -18528,448,169,10.0,7,0,1987-09-27 00:00:00 -18529,448,121,1.0,19,0,1987-09-27 00:00:00 -18530,448,111,2.0,18,0,1987-09-27 00:00:00 -18531,448,159,0.0,21,0,1987-09-27 00:00:00 -18532,448,98,0.0,28,0,1987-09-27 00:00:00 -18533,448,162,1.0,20,0,1987-09-27 00:00:00 -18534,448,170,0.0,27,0,1987-09-27 00:00:00 -18535,448,77,0.0,29,0,1987-09-27 00:00:00 -18536,448,132,0.0,25,0,1987-09-27 00:00:00 -18537,448,166,0.0,26,0,1987-09-27 00:00:00 -18538,448,117,3.0,15,0,1987-09-27 00:00:00 -18539,448,109,4.0,12,0,1987-09-27 00:00:00 -18540,448,122,10.0,8,0,1987-09-27 00:00:00 -18541,448,118,2.0,17,0,1987-09-27 00:00:00 -18542,448,136,70.0,1,3,1987-09-27 00:00:00 -18543,448,139,26.0,5,0,1987-09-27 00:00:00 -18544,448,76,18.0,6,0,1987-09-27 00:00:00 -18545,448,94,52.0,2,5,1987-09-27 00:00:00 -18546,448,116,46.0,4,3,1987-09-27 00:00:00 -18547,448,137,6.0,10,0,1987-09-27 00:00:00 -18548,448,156,0.0,22,0,1987-09-27 00:00:00 -18549,448,155,4.0,14,0,1987-09-27 00:00:00 -18550,448,165,4.0,13,0,1987-09-27 00:00:00 -18551,448,168,0.0,23,0,1987-09-27 00:00:00 -18552,448,157,5.0,11,0,1987-09-27 00:00:00 -18553,448,101,51.0,3,2,1987-09-27 00:00:00 -18554,448,104,8.0,9,0,1987-09-27 00:00:00 -18555,449,169,12.0,7,0,1987-10-18 00:00:00 -18556,449,83,2.0,18,0,1987-10-18 00:00:00 -18557,449,132,0.0,26,0,1987-10-18 00:00:00 -18558,449,121,1.0,19,0,1987-10-18 00:00:00 -18559,449,144,0.0,25,0,1987-10-18 00:00:00 -18560,449,111,3.0,17,0,1987-10-18 00:00:00 -18561,449,113,0.0,24,0,1987-10-18 00:00:00 -18562,449,98,0.0,29,0,1987-10-18 00:00:00 -18563,449,159,0.0,21,0,1987-10-18 00:00:00 -18564,449,162,1.0,20,0,1987-10-18 00:00:00 -18565,449,170,0.0,28,0,1987-10-18 00:00:00 -18566,449,77,0.0,30,0,1987-10-18 00:00:00 -18567,449,166,0.0,27,0,1987-10-18 00:00:00 -18568,449,117,3.0,16,0,1987-10-18 00:00:00 -18569,449,136,73.0,1,3,1987-10-18 00:00:00 -18570,449,118,6.0,11,0,1987-10-18 00:00:00 -18571,449,109,4.0,13,0,1987-10-18 00:00:00 -18572,449,116,46.0,4,3,1987-10-18 00:00:00 -18573,449,139,26.0,5,0,1987-10-18 00:00:00 -18574,449,76,18.0,6,0,1987-10-18 00:00:00 -18575,449,94,61.0,2,6,1987-10-18 00:00:00 -18576,449,137,6.0,12,0,1987-10-18 00:00:00 -18577,449,122,10.0,8,0,1987-10-18 00:00:00 -18578,449,156,0.0,22,0,1987-10-18 00:00:00 -18579,449,155,4.0,15,0,1987-10-18 00:00:00 -18580,449,165,4.0,14,0,1987-10-18 00:00:00 -18581,449,168,0.0,23,0,1987-10-18 00:00:00 -18582,449,157,8.0,10,0,1987-10-18 00:00:00 -18583,449,101,51.0,3,2,1987-10-18 00:00:00 -18584,449,104,8.0,9,0,1987-10-18 00:00:00 -18585,450,111,3.0,17,0,1987-11-01 00:00:00 -18586,450,144,0.0,25,0,1987-11-01 00:00:00 -18587,450,83,2.0,18,0,1987-11-01 00:00:00 -18588,450,169,12.0,7,0,1987-11-01 00:00:00 -18589,450,121,1.0,19,0,1987-11-01 00:00:00 -18590,450,166,0.0,27,0,1987-11-01 00:00:00 -18591,450,89,0.0,29,0,1987-11-01 00:00:00 -18592,450,98,0.0,30,0,1987-11-01 00:00:00 -18593,450,159,0.0,21,0,1987-11-01 00:00:00 -18594,450,162,1.0,20,0,1987-11-01 00:00:00 -18595,450,170,0.0,28,0,1987-11-01 00:00:00 -18596,450,77,0.0,31,0,1987-11-01 00:00:00 -18597,450,113,0.0,24,0,1987-11-01 00:00:00 -18598,450,132,0.0,26,0,1987-11-01 00:00:00 -18599,450,117,3.0,16,0,1987-11-01 00:00:00 -18600,450,104,11.0,9,0,1987-11-01 00:00:00 -18601,450,118,6.0,12,0,1987-11-01 00:00:00 -18602,450,116,46.0,4,3,1987-11-01 00:00:00 -18603,450,136,73.0,1,3,1987-11-01 00:00:00 -18604,450,139,30.0,5,0,1987-11-01 00:00:00 -18605,450,76,27.0,6,1,1987-11-01 00:00:00 -18606,450,122,12.0,8,0,1987-11-01 00:00:00 -18607,450,94,61.0,2,6,1987-11-01 00:00:00 -18608,450,109,4.0,13,0,1987-11-01 00:00:00 -18609,450,156,0.0,22,0,1987-11-01 00:00:00 -18610,450,155,4.0,15,0,1987-11-01 00:00:00 -18611,450,165,4.0,14,0,1987-11-01 00:00:00 -18612,450,168,0.0,23,0,1987-11-01 00:00:00 -18613,450,157,8.0,10,0,1987-11-01 00:00:00 -18614,450,101,57.0,3,2,1987-11-01 00:00:00 -18615,450,137,7.0,11,0,1987-11-01 00:00:00 -18616,451,144,0.0,26,0,1987-11-15 00:00:00 -18617,451,83,2.0,18,0,1987-11-15 00:00:00 -18618,451,169,12.0,9,0,1987-11-15 00:00:00 -18619,451,121,1.0,19,0,1987-11-15 00:00:00 -18620,451,111,3.0,17,0,1987-11-15 00:00:00 -18621,451,166,0.0,28,0,1987-11-15 00:00:00 -18622,451,170,0.0,29,0,1987-11-15 00:00:00 -18623,451,159,0.0,24,0,1987-11-15 00:00:00 -18624,451,162,1.0,20,0,1987-11-15 00:00:00 -18625,451,77,0.0,32,0,1987-11-15 00:00:00 -18626,451,113,0.0,22,0,1987-11-15 00:00:00 -18627,451,89,1.0,21,0,1987-11-15 00:00:00 -18628,451,132,0.0,27,0,1987-11-15 00:00:00 -18629,451,98,0.0,31,0,1987-11-15 00:00:00 -18630,451,117,3.0,16,0,1987-11-15 00:00:00 -18631,451,130,0.0,30,0,1987-11-15 00:00:00 -18632,451,118,6.0,13,0,1987-11-15 00:00:00 -18633,451,136,73.0,1,3,1987-11-15 00:00:00 -18634,451,139,30.0,6,0,1987-11-15 00:00:00 -18635,451,76,36.0,5,2,1987-11-15 00:00:00 -18636,451,122,16.0,8,0,1987-11-15 00:00:00 -18637,451,94,61.0,2,6,1987-11-15 00:00:00 -18638,451,137,7.0,12,0,1987-11-15 00:00:00 -18639,451,116,46.0,4,3,1987-11-15 00:00:00 -18640,451,156,0.0,23,0,1987-11-15 00:00:00 -18641,451,104,17.0,7,0,1987-11-15 00:00:00 -18642,451,101,57.0,3,2,1987-11-15 00:00:00 -18643,451,157,8.0,10,0,1987-11-15 00:00:00 -18644,451,109,4.0,14,0,1987-11-15 00:00:00 -18645,451,165,4.0,15,0,1987-11-15 00:00:00 -18646,451,155,7.0,11,0,1987-11-15 00:00:00 -18647,451,168,0.0,25,0,1987-11-15 00:00:00 -18648,452,130,0.0,18,0,1988-04-03 00:00:00 -18649,452,94,0.0,19,0,1988-04-03 00:00:00 -18650,452,144,0.0,20,0,1988-04-03 00:00:00 -18651,452,118,0.0,21,0,1988-04-03 00:00:00 -18652,452,121,0.0,22,0,1988-04-03 00:00:00 -18653,452,166,0.0,23,0,1988-04-03 00:00:00 -18654,452,126,0.0,24,0,1988-04-03 00:00:00 -18655,452,140,0.0,26,0,1988-04-03 00:00:00 -18656,452,77,0.0,28,0,1988-04-03 00:00:00 -18657,452,145,0.0,29,0,1988-04-03 00:00:00 -18658,452,132,0.0,30,0,1988-04-03 00:00:00 -18659,452,162,0.0,17,0,1988-04-03 00:00:00 -18660,452,164,0.0,25,0,1988-04-03 00:00:00 -18661,452,159,0.0,27,0,1988-04-03 00:00:00 -18662,452,113,0.0,16,0,1988-04-03 00:00:00 -18663,452,98,0.0,14,0,1988-04-03 00:00:00 -18664,452,165,0.0,15,0,1988-04-03 00:00:00 -18665,452,116,9.0,1,1,1988-04-03 00:00:00 -18666,452,76,6.0,2,0,1988-04-03 00:00:00 -18667,452,136,4.0,3,0,1988-04-03 00:00:00 -18668,452,104,2.0,5,0,1988-04-03 00:00:00 -18669,452,137,1.0,6,0,1988-04-03 00:00:00 -18670,452,117,3.0,4,0,1988-04-03 00:00:00 -18671,452,157,0.0,8,0,1988-04-03 00:00:00 -18672,452,139,0.0,9,0,1988-04-03 00:00:00 -18673,452,109,0.0,10,0,1988-04-03 00:00:00 -18674,452,155,0.0,11,0,1988-04-03 00:00:00 -18675,452,158,0.0,12,0,1988-04-03 00:00:00 -18676,452,111,0.0,13,0,1988-04-03 00:00:00 -18677,452,122,0.0,7,0,1988-04-03 00:00:00 -18678,453,166,0.0,18,0,1988-05-01 00:00:00 -18679,453,94,0.0,24,0,1988-05-01 00:00:00 -18680,453,144,1.0,9,0,1988-05-01 00:00:00 -18681,453,118,0.0,15,0,1988-05-01 00:00:00 -18682,453,121,0.0,26,0,1988-05-01 00:00:00 -18683,453,130,0.0,23,0,1988-05-01 00:00:00 -18684,453,101,9.0,2,1,1988-05-01 00:00:00 -18685,453,164,0.0,29,0,1988-05-01 00:00:00 -18686,453,140,0.0,25,0,1988-05-01 00:00:00 -18687,453,159,0.0,28,0,1988-05-01 00:00:00 -18688,453,77,0.0,30,0,1988-05-01 00:00:00 -18689,453,145,0.0,31,0,1988-05-01 00:00:00 -18690,453,132,0.0,27,0,1988-05-01 00:00:00 -18691,453,126,0.0,17,0,1988-05-01 00:00:00 -18692,453,162,0.0,22,0,1988-05-01 00:00:00 -18693,453,139,0.0,11,0,1988-05-01 00:00:00 -18694,453,165,0.0,12,0,1988-05-01 00:00:00 -18695,453,116,15.0,1,1,1988-05-01 00:00:00 -18696,453,76,8.0,3,0,1988-05-01 00:00:00 -18697,453,136,8.0,4,0,1988-05-01 00:00:00 -18698,453,117,3.0,6,0,1988-05-01 00:00:00 -18699,453,137,1.0,8,0,1988-05-01 00:00:00 -18700,453,122,3.0,5,0,1988-05-01 00:00:00 -18701,453,104,2.0,7,0,1988-05-01 00:00:00 -18702,453,109,0.0,20,0,1988-05-01 00:00:00 -18703,453,155,0.0,16,0,1988-05-01 00:00:00 -18704,453,158,0.0,13,0,1988-05-01 00:00:00 -18705,453,111,0.0,19,0,1988-05-01 00:00:00 -18706,453,98,0.0,21,0,1988-05-01 00:00:00 -18707,453,157,0.0,10,0,1988-05-01 00:00:00 -18708,453,113,0.0,14,0,1988-05-01 00:00:00 -18709,454,166,0.0,20,0,1988-05-15 00:00:00 -18710,454,94,0.0,25,0,1988-05-15 00:00:00 -18711,454,144,1.0,11,0,1988-05-15 00:00:00 -18712,454,118,1.0,10,0,1988-05-15 00:00:00 -18713,454,121,0.0,17,0,1988-05-15 00:00:00 -18714,454,101,9.0,3,1,1988-05-15 00:00:00 -18715,454,140,0.0,29,0,1988-05-15 00:00:00 -18716,454,159,0.0,24,0,1988-05-15 00:00:00 -18717,454,77,0.0,15,0,1988-05-15 00:00:00 -18718,454,145,0.0,31,0,1988-05-15 00:00:00 -18719,454,132,0.0,30,0,1988-05-15 00:00:00 -18720,454,130,0.0,27,0,1988-05-15 00:00:00 -18721,454,164,0.0,28,0,1988-05-15 00:00:00 -18722,454,162,0.0,26,0,1988-05-15 00:00:00 -18723,454,126,0.0,19,0,1988-05-15 00:00:00 -18724,454,165,0.0,16,0,1988-05-15 00:00:00 -18725,454,113,0.0,13,0,1988-05-15 00:00:00 -18726,454,76,14.0,2,0,1988-05-15 00:00:00 -18727,454,136,8.0,4,0,1988-05-15 00:00:00 -18728,454,117,6.0,6,0,1988-05-15 00:00:00 -18729,454,104,6.0,5,0,1988-05-15 00:00:00 -18730,454,137,1.0,9,0,1988-05-15 00:00:00 -18731,454,122,3.0,7,0,1988-05-15 00:00:00 -18732,454,116,24.0,1,2,1988-05-15 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00:00:00 -18958,461,155,5.0,11,0,1988-08-07 00:00:00 -18959,461,111,0.0,25,0,1988-08-07 00:00:00 -18960,461,98,0.0,20,0,1988-08-07 00:00:00 -18961,461,157,1.0,16,0,1988-08-07 00:00:00 -18962,462,83,0.0,19,0,1988-08-28 00:00:00 -18963,462,94,6.0,9,0,1988-08-28 00:00:00 -18964,462,144,6.0,10,0,1988-08-28 00:00:00 -18965,462,118,2.0,15,0,1988-08-28 00:00:00 -18966,462,121,8.0,8,0,1988-08-28 00:00:00 -18967,462,166,0.0,32,0,1988-08-28 00:00:00 -18968,462,126,5.0,11,0,1988-08-28 00:00:00 -18969,462,159,0.0,31,0,1988-08-28 00:00:00 -18970,462,140,0.0,24,0,1988-08-28 00:00:00 -18971,462,77,0.0,25,0,1988-08-28 00:00:00 -18972,462,145,0.0,29,0,1988-08-28 00:00:00 -18973,462,132,0.0,20,0,1988-08-28 00:00:00 -18974,462,101,75.0,1,7,1988-08-28 00:00:00 -18975,462,130,0.0,28,0,1988-08-28 00:00:00 -18976,462,93,1.0,17,0,1988-08-28 00:00:00 -18977,462,164,0.0,30,0,1988-08-28 00:00:00 -18978,462,162,0.0,33,0,1988-08-28 00:00:00 -18979,462,98,0.0,21,0,1988-08-28 00:00:00 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00:00:00 -19003,463,159,0.0,33,0,1988-09-11 00:00:00 -19004,463,77,0.0,25,0,1988-09-11 00:00:00 -19005,463,132,0.0,20,0,1988-09-11 00:00:00 -19006,463,101,75.0,1,7,1988-09-11 00:00:00 -19007,463,93,1.0,17,0,1988-09-11 00:00:00 -19008,463,130,0.0,28,0,1988-09-11 00:00:00 -19009,463,167,0.0,29,0,1988-09-11 00:00:00 -19010,463,140,0.0,24,0,1988-09-11 00:00:00 -19011,463,83,0.0,19,0,1988-09-11 00:00:00 -19012,463,162,0.0,32,0,1988-09-11 00:00:00 -19013,463,165,0.0,26,0,1988-09-11 00:00:00 -19014,463,113,0.0,18,0,1988-09-11 00:00:00 -19015,463,116,72.0,2,4,1988-09-11 00:00:00 -19016,463,76,37.0,3,1,1988-09-11 00:00:00 -19017,463,136,18.0,5,0,1988-09-11 00:00:00 -19018,463,104,22.0,4,0,1988-09-11 00:00:00 -19019,463,137,1.0,16,0,1988-09-11 00:00:00 -19020,463,122,17.0,6,0,1988-09-11 00:00:00 -19021,463,117,14.0,7,0,1988-09-11 00:00:00 -19022,463,139,0.0,22,0,1988-09-11 00:00:00 -19023,463,109,3.0,14,0,1988-09-11 00:00:00 -19024,463,155,5.0,13,0,1988-09-11 00:00:00 -19025,463,158,0.0,27,0,1988-09-11 00:00:00 -19026,463,111,0.0,23,0,1988-09-11 00:00:00 -19027,463,98,0.0,21,0,1988-09-11 00:00:00 -19028,463,157,6.0,10,0,1988-09-11 00:00:00 -19029,464,101,76.0,2,7,1988-09-25 00:00:00 -19030,464,118,2.0,15,0,1988-09-25 00:00:00 -19031,464,165,0.0,23,0,1988-09-25 00:00:00 -19032,464,167,0.0,30,0,1988-09-25 00:00:00 -19033,464,83,0.0,20,0,1988-09-25 00:00:00 -19034,464,93,1.0,17,0,1988-09-25 00:00:00 -19035,464,132,0.0,19,0,1988-09-25 00:00:00 -19036,464,121,16.0,8,0,1988-09-25 00:00:00 -19037,464,77,0.0,27,0,1988-09-25 00:00:00 -19038,464,159,0.0,33,0,1988-09-25 00:00:00 -19039,464,140,0.0,26,0,1988-09-25 00:00:00 -19040,464,164,0.0,32,0,1988-09-25 00:00:00 -19041,464,126,5.0,12,0,1988-09-25 00:00:00 -19042,464,166,0.0,34,0,1988-09-25 00:00:00 -19043,464,144,6.0,11,0,1988-09-25 00:00:00 -19044,464,145,0.0,31,0,1988-09-25 00:00:00 -19045,464,94,6.0,9,0,1988-09-25 00:00:00 -19046,464,98,0.0,22,0,1988-09-25 00:00:00 -19047,464,162,0.0,28,0,1988-09-25 00:00:00 -19048,464,158,0.0,21,0,1988-09-25 00:00:00 -19049,464,155,5.0,13,0,1988-09-25 00:00:00 -19050,464,109,3.0,14,0,1988-09-25 00:00:00 -19051,464,139,0.0,24,0,1988-09-25 00:00:00 -19052,464,157,6.0,10,0,1988-09-25 00:00:00 -19053,464,122,21.0,5,0,1988-09-25 00:00:00 -19054,464,137,1.0,16,0,1988-09-25 00:00:00 -19055,464,130,0.0,29,0,1988-09-25 00:00:00 -19056,464,117,17.0,7,0,1988-09-25 00:00:00 -19057,464,136,18.0,6,0,1988-09-25 00:00:00 -19058,464,76,37.0,3,1,1988-09-25 00:00:00 -19059,464,116,81.0,1,5,1988-09-25 00:00:00 -19060,464,111,0.0,25,0,1988-09-25 00:00:00 -19061,464,113,0.0,18,0,1988-09-25 00:00:00 -19062,464,104,24.0,4,0,1988-09-25 00:00:00 -19063,465,144,10.0,10,0,1988-10-02 00:00:00 -19064,465,118,4.0,14,0,1988-10-02 00:00:00 -19065,465,121,16.0,8,0,1988-10-02 00:00:00 -19066,465,166,0.0,34,0,1988-10-02 00:00:00 -19067,465,126,5.0,12,0,1988-10-02 00:00:00 -19068,465,164,0.0,32,0,1988-10-02 00:00:00 -19069,465,140,0.0,26,0,1988-10-02 00:00:00 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00:00:00 -19093,465,111,0.0,25,0,1988-10-02 00:00:00 -19094,465,98,0.0,22,0,1988-10-02 00:00:00 -19095,465,165,0.0,23,0,1988-10-02 00:00:00 -19096,465,157,6.0,11,0,1988-10-02 00:00:00 -19097,466,140,0.0,26,0,1988-10-30 00:00:00 -19098,466,118,5.0,14,0,1988-10-30 00:00:00 -19099,466,121,16.0,8,0,1988-10-30 00:00:00 -19100,466,166,0.0,34,0,1988-10-30 00:00:00 -19101,466,126,5.0,12,0,1988-10-30 00:00:00 -19102,466,164,0.0,32,0,1988-10-30 00:00:00 -19103,466,159,0.0,33,0,1988-10-30 00:00:00 -19104,466,144,12.0,10,0,1988-10-30 00:00:00 -19105,466,145,0.0,31,0,1988-10-30 00:00:00 -19106,466,132,0.0,19,0,1988-10-30 00:00:00 -19107,466,101,87.0,1,8,1988-10-30 00:00:00 -19108,466,83,0.0,20,0,1988-10-30 00:00:00 -19109,466,167,0.0,30,0,1988-10-30 00:00:00 -19110,466,87,0.0,35,0,1988-10-30 00:00:00 -19111,466,77,0.0,27,0,1988-10-30 00:00:00 -19112,466,94,12.0,9,0,1988-10-30 00:00:00 -19113,466,93,1.0,17,0,1988-10-30 00:00:00 -19114,466,162,0.0,28,0,1988-10-30 00:00:00 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00:00:00 -19138,467,77,0.0,27,0,1988-11-13 00:00:00 -19139,467,161,0.0,36,0,1988-11-13 00:00:00 -19140,467,132,0.0,19,0,1988-11-13 00:00:00 -19141,467,101,90.0,1,8,1988-11-13 00:00:00 -19142,467,93,1.0,17,0,1988-11-13 00:00:00 -19143,467,83,0.0,20,0,1988-11-13 00:00:00 -19144,467,167,0.0,30,0,1988-11-13 00:00:00 -19145,467,87,0.0,35,0,1988-11-13 00:00:00 -19146,467,118,8.0,11,0,1988-11-13 00:00:00 -19147,467,145,0.0,31,0,1988-11-13 00:00:00 -19148,467,144,12.0,10,0,1988-11-13 00:00:00 -19149,467,94,12.0,9,0,1988-11-13 00:00:00 -19150,467,130,0.0,29,0,1988-11-13 00:00:00 -19151,467,76,41.0,3,1,1988-11-13 00:00:00 -19152,467,136,22.0,6,0,1988-11-13 00:00:00 -19153,467,117,17.0,8,0,1988-11-13 00:00:00 -19154,467,104,24.0,5,0,1988-11-13 00:00:00 -19155,467,137,1.0,16,0,1988-11-13 00:00:00 -19156,467,122,27.0,4,0,1988-11-13 00:00:00 -19157,467,157,6.0,12,0,1988-11-13 00:00:00 -19158,467,139,0.0,25,0,1988-11-13 00:00:00 -19159,467,116,87.0,2,7,1988-11-13 00:00:00 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00:00:00 -19183,468,130,0.0,21,0,1989-03-26 00:00:00 -19184,468,132,0.0,30,0,1989-03-26 00:00:00 -19185,468,136,0.0,20,0,1989-03-26 00:00:00 -19186,468,94,9.0,1,1,1989-03-26 00:00:00 -19187,468,83,0.0,18,0,1989-03-26 00:00:00 -19188,468,121,0.0,19,0,1989-03-26 00:00:00 -19189,468,116,6.0,2,0,1989-03-26 00:00:00 -19190,468,126,4.0,3,0,1989-03-26 00:00:00 -19191,468,64,3.0,4,0,1989-03-26 00:00:00 -19192,468,117,2.0,5,0,1989-03-26 00:00:00 -19193,468,155,0.0,7,0,1989-03-26 00:00:00 -19194,468,137,0.0,8,0,1989-03-26 00:00:00 -19195,468,128,0.0,9,0,1989-03-26 00:00:00 -19196,468,144,1.0,6,0,1989-03-26 00:00:00 -19197,468,101,0.0,11,0,1989-03-26 00:00:00 -19198,468,111,0.0,12,0,1989-03-26 00:00:00 -19199,468,109,0.0,13,0,1989-03-26 00:00:00 -19200,468,156,0.0,14,0,1989-03-26 00:00:00 -19201,468,118,0.0,15,0,1989-03-26 00:00:00 -19202,468,157,0.0,16,0,1989-03-26 00:00:00 -19203,468,145,0.0,17,0,1989-03-26 00:00:00 -19204,468,104,0.0,10,0,1989-03-26 00:00:00 -19205,469,89,0.0,32,0,1989-04-23 00:00:00 -19206,469,93,0.0,27,0,1989-04-23 00:00:00 -19207,469,76,0.0,28,0,1989-04-23 00:00:00 -19208,469,158,0.0,22,0,1989-04-23 00:00:00 -19209,469,113,0.0,29,0,1989-04-23 00:00:00 -19210,469,162,0.0,30,0,1989-04-23 00:00:00 -19211,469,147,0.0,31,0,1989-04-23 00:00:00 -19212,469,132,0.0,10,0,1989-04-23 00:00:00 -19213,469,77,0.0,18,0,1989-04-23 00:00:00 -19214,469,160,0.0,35,0,1989-04-23 00:00:00 -19215,469,161,0.0,36,0,1989-04-23 00:00:00 -19216,469,163,0.0,38,0,1989-04-23 00:00:00 -19217,469,87,0.0,39,0,1989-04-23 00:00:00 -19218,469,139,0.0,37,0,1989-04-23 00:00:00 -19219,469,91,0.0,33,0,1989-04-23 00:00:00 -19220,469,98,0.0,12,0,1989-04-23 00:00:00 -19221,469,122,3.0,8,0,1989-04-23 00:00:00 -19222,469,159,0.0,34,0,1989-04-23 00:00:00 -19223,469,130,0.0,26,0,1989-04-23 00:00:00 -19224,469,126,4.0,5,0,1989-04-23 00:00:00 -19225,469,121,0.0,25,0,1989-04-23 00:00:00 -19226,469,116,12.0,1,0,1989-04-23 00:00:00 -19227,469,64,3.0,7,0,1989-04-23 00:00:00 -19228,469,117,4.0,6,0,1989-04-23 00:00:00 -19229,469,144,5.0,4,0,1989-04-23 00:00:00 -19230,469,155,1.0,9,0,1989-04-23 00:00:00 -19231,469,137,0.0,11,0,1989-04-23 00:00:00 -19232,469,128,0.0,14,0,1989-04-23 00:00:00 -19233,469,104,0.0,16,0,1989-04-23 00:00:00 -19234,469,94,9.0,3,1,1989-04-23 00:00:00 -19235,469,111,0.0,17,0,1989-04-23 00:00:00 -19236,469,101,9.0,2,1,1989-04-23 00:00:00 -19237,469,83,0.0,21,0,1989-04-23 00:00:00 -19238,469,145,0.0,24,0,1989-04-23 00:00:00 -19239,469,136,0.0,23,0,1989-04-23 00:00:00 -19240,469,118,0.0,20,0,1989-04-23 00:00:00 -19241,469,156,0.0,19,0,1989-04-23 00:00:00 -19242,469,109,0.0,15,0,1989-04-23 00:00:00 -19243,469,157,0.0,13,0,1989-04-23 00:00:00 -19244,470,122,3.0,9,0,1989-05-07 00:00:00 -19245,470,93,0.0,29,0,1989-05-07 00:00:00 -19246,470,76,0.0,30,0,1989-05-07 00:00:00 -19247,470,158,0.0,25,0,1989-05-07 00:00:00 -19248,470,113,0.0,32,0,1989-05-07 00:00:00 -19249,470,162,0.0,21,0,1989-05-07 00:00:00 -19250,470,147,0.0,33,0,1989-05-07 00:00:00 -19251,470,89,0.0,28,0,1989-05-07 00:00:00 -19252,470,159,0.0,34,0,1989-05-07 00:00:00 -19253,470,160,0.0,37,0,1989-05-07 00:00:00 -19254,470,161,0.0,31,0,1989-05-07 00:00:00 -19255,470,87,0.0,39,0,1989-05-07 00:00:00 -19256,470,139,0.0,35,0,1989-05-07 00:00:00 -19257,470,91,0.0,36,0,1989-05-07 00:00:00 -19258,470,98,0.0,16,0,1989-05-07 00:00:00 -19259,470,130,4.0,6,0,1989-05-07 00:00:00 -19260,470,77,0.0,22,0,1989-05-07 00:00:00 -19261,470,132,3.0,8,0,1989-05-07 00:00:00 -19262,470,163,0.0,38,0,1989-05-07 00:00:00 -19263,470,136,0.0,26,0,1989-05-07 00:00:00 -19264,470,83,1.0,13,0,1989-05-07 00:00:00 -19265,470,121,0.0,19,0,1989-05-07 00:00:00 -19266,470,94,9.0,3,1,1989-05-07 00:00:00 -19267,470,116,18.0,2,0,1989-05-07 00:00:00 -19268,470,126,4.0,5,0,1989-05-07 00:00:00 -19269,470,64,3.0,10,0,1989-05-07 00:00:00 -19270,470,144,5.0,4,0,1989-05-07 00:00:00 -19271,470,155,1.0,12,0,1989-05-07 00:00:00 -19272,470,137,0.0,15,0,1989-05-07 00:00:00 -19273,470,117,4.0,7,0,1989-05-07 00:00:00 -19274,470,104,2.0,11,0,1989-05-07 00:00:00 -19275,470,128,0.0,17,0,1989-05-07 00:00:00 -19276,470,157,0.0,14,0,1989-05-07 00:00:00 -19277,470,118,0.0,24,0,1989-05-07 00:00:00 -19278,470,156,0.0,23,0,1989-05-07 00:00:00 -19279,470,145,0.0,27,0,1989-05-07 00:00:00 -19280,470,111,0.0,20,0,1989-05-07 00:00:00 -19281,470,101,18.0,1,2,1989-05-07 00:00:00 -19282,470,109,0.0,18,0,1989-05-07 00:00:00 -19283,471,147,0.0,34,0,1989-05-28 00:00:00 -19284,471,77,0.0,25,0,1989-05-28 00:00:00 -19285,471,93,0.0,27,0,1989-05-28 00:00:00 -19286,471,76,0.0,30,0,1989-05-28 00:00:00 -19287,471,158,0.0,26,0,1989-05-28 00:00:00 -19288,471,113,0.0,33,0,1989-05-28 00:00:00 -19289,471,162,0.0,23,0,1989-05-28 00:00:00 -19290,471,89,0.0,29,0,1989-05-28 00:00:00 -19291,471,122,3.0,11,0,1989-05-28 00:00:00 -19292,471,159,0.0,35,0,1989-05-28 00:00:00 -19293,471,160,0.0,37,0,1989-05-28 00:00:00 -19294,471,161,0.0,32,0,1989-05-28 00:00:00 -19295,471,163,0.0,38,0,1989-05-28 00:00:00 -19296,471,87,0.0,39,0,1989-05-28 00:00:00 -19297,471,139,0.0,31,0,1989-05-28 00:00:00 -19298,471,91,0.0,36,0,1989-05-28 00:00:00 -19299,471,98,1.0,14,0,1989-05-28 00:00:00 -19300,471,132,3.0,10,0,1989-05-28 00:00:00 -19301,471,130,4.0,7,0,1989-05-28 00:00:00 -19302,471,145,0.0,28,0,1989-05-28 00:00:00 -19303,471,121,0.0,21,0,1989-05-28 00:00:00 -19304,471,94,9.0,3,1,1989-05-28 00:00:00 -19305,471,116,20.0,2,0,1989-05-28 00:00:00 -19306,471,126,4.0,8,0,1989-05-28 00:00:00 -19307,471,64,3.0,12,0,1989-05-28 00:00:00 -19308,471,117,4.0,9,0,1989-05-28 00:00:00 -19309,471,144,8.0,4,0,1989-05-28 00:00:00 -19310,471,155,1.0,13,0,1989-05-28 00:00:00 -19311,471,137,0.0,18,0,1989-05-28 00:00:00 -19312,471,136,0.0,20,0,1989-05-28 00:00:00 -19313,471,104,6.0,6,0,1989-05-28 00:00:00 -19314,471,101,27.0,1,3,1989-05-28 00:00:00 -19315,471,111,0.0,24,0,1989-05-28 00:00:00 -19316,471,109,0.0,19,0,1989-05-28 00:00:00 -19317,471,156,0.0,22,0,1989-05-28 00:00:00 -19318,471,118,6.0,5,0,1989-05-28 00:00:00 -19319,471,157,0.0,16,0,1989-05-28 00:00:00 -19320,471,83,1.0,15,0,1989-05-28 00:00:00 -19321,471,128,0.0,17,0,1989-05-28 00:00:00 -19322,472,147,0.0,34,0,1989-06-04 00:00:00 -19323,472,162,0.0,23,0,1989-06-04 00:00:00 -19324,472,93,0.0,29,0,1989-06-04 00:00:00 -19325,472,158,0.0,28,0,1989-06-04 00:00:00 -19326,472,76,0.0,26,0,1989-06-04 00:00:00 -19327,472,89,0.0,31,0,1989-06-04 00:00:00 -19328,472,113,0.0,33,0,1989-06-04 00:00:00 -19329,472,132,3.0,13,0,1989-06-04 00:00:00 -19330,472,87,0.0,39,0,1989-06-04 00:00:00 -19331,472,160,0.0,37,0,1989-06-04 00:00:00 -19332,472,161,0.0,32,0,1989-06-04 00:00:00 -19333,472,163,0.0,38,0,1989-06-04 00:00:00 -19334,472,139,0.0,27,0,1989-06-04 00:00:00 -19335,472,91,0.0,36,0,1989-06-04 00:00:00 -19336,472,98,1.0,15,0,1989-06-04 00:00:00 -19337,472,77,0.0,25,0,1989-06-04 00:00:00 -19338,472,122,4.0,11,0,1989-06-04 00:00:00 -19339,472,159,0.0,35,0,1989-06-04 00:00:00 -19340,472,130,4.0,9,0,1989-06-04 00:00:00 -19341,472,136,0.0,21,0,1989-06-04 00:00:00 -19342,472,121,0.0,22,0,1989-06-04 00:00:00 -19343,472,116,29.0,1,1,1989-06-04 00:00:00 -19344,472,126,4.0,10,0,1989-06-04 00:00:00 -19345,472,64,5.0,7,0,1989-06-04 00:00:00 -19346,472,117,4.0,12,0,1989-06-04 00:00:00 -19347,472,144,8.0,5,0,1989-06-04 00:00:00 -19348,472,155,1.0,16,0,1989-06-04 00:00:00 -19349,472,137,0.0,20,0,1989-06-04 00:00:00 -19350,472,128,0.0,18,0,1989-06-04 00:00:00 -19351,472,94,9.0,4,1,1989-06-04 00:00:00 -19352,472,101,27.0,2,3,1989-06-04 00:00:00 -19353,472,111,0.0,24,0,1989-06-04 00:00:00 -19354,472,109,0.0,19,0,1989-06-04 00:00:00 -19355,472,156,3.0,14,0,1989-06-04 00:00:00 -19356,472,118,12.0,3,0,1989-06-04 00:00:00 -19357,472,157,4.0,8,0,1989-06-04 00:00:00 -19358,472,145,0.0,30,0,1989-06-04 00:00:00 -19359,472,83,1.0,17,0,1989-06-04 00:00:00 -19360,472,104,6.0,6,0,1989-06-04 00:00:00 -19361,473,162,2.0,17,0,1989-06-18 00:00:00 -19362,473,113,0.0,33,0,1989-06-18 00:00:00 -19363,473,122,13.0,4,1,1989-06-18 00:00:00 -19364,473,76,0.0,27,0,1989-06-18 00:00:00 -19365,473,93,0.0,30,0,1989-06-18 00:00:00 -19366,473,147,0.0,34,0,1989-06-18 00:00:00 -19367,473,158,0.0,29,0,1989-06-18 00:00:00 -19368,473,89,0.0,26,0,1989-06-18 00:00:00 -19369,473,163,0.0,38,0,1989-06-18 00:00:00 -19370,473,159,0.0,35,0,1989-06-18 00:00:00 -19371,473,160,0.0,37,0,1989-06-18 00:00:00 -19372,473,77,0.0,24,0,1989-06-18 00:00:00 -19373,473,87,0.0,39,0,1989-06-18 00:00:00 -19374,473,139,0.0,28,0,1989-06-18 00:00:00 -19375,473,91,0.0,36,0,1989-06-18 00:00:00 -19376,473,98,1.0,18,0,1989-06-18 00:00:00 -19377,473,130,4.0,11,0,1989-06-18 00:00:00 -19378,473,132,4.0,13,0,1989-06-18 00:00:00 -19379,473,136,3.0,16,0,1989-06-18 00:00:00 -19380,473,161,0.0,32,0,1989-06-18 00:00:00 -19381,473,83,1.0,20,0,1989-06-18 00:00:00 -19382,473,94,9.0,5,1,1989-06-18 00:00:00 -19383,473,116,29.0,1,1,1989-06-18 00:00:00 -19384,473,126,4.0,12,0,1989-06-18 00:00:00 -19385,473,64,5.0,8,0,1989-06-18 00:00:00 -19386,473,144,8.0,6,0,1989-06-18 00:00:00 -19387,473,155,1.0,19,0,1989-06-18 00:00:00 -19388,473,137,0.0,22,0,1989-06-18 00:00:00 -19389,473,128,0.0,21,0,1989-06-18 00:00:00 -19390,473,117,4.0,14,0,1989-06-18 00:00:00 -19391,473,101,27.0,2,3,1989-06-18 00:00:00 -19392,473,104,6.0,7,0,1989-06-18 00:00:00 -19393,473,145,0.0,31,0,1989-06-18 00:00:00 -19394,473,157,4.0,9,0,1989-06-18 00:00:00 -19395,473,118,18.0,3,0,1989-06-18 00:00:00 -19396,473,121,0.0,23,0,1989-06-18 00:00:00 -19397,473,109,4.0,10,0,1989-06-18 00:00:00 -19398,473,111,0.0,25,0,1989-06-18 00:00:00 -19399,473,156,3.0,15,0,1989-06-18 00:00:00 -19400,474,160,0.0,41,0,1989-07-09 00:00:00 -19401,474,158,0.0,34,0,1989-07-09 00:00:00 -19402,474,113,0.0,38,0,1989-07-09 00:00:00 -19403,474,162,2.0,18,0,1989-07-09 00:00:00 -19404,474,147,0.0,39,0,1989-07-09 00:00:00 -19405,474,89,0.0,32,0,1989-07-09 00:00:00 -19406,474,132,4.0,13,0,1989-07-09 00:00:00 -19407,474,159,0.0,40,0,1989-07-09 00:00:00 -19408,474,76,0.0,33,0,1989-07-09 00:00:00 -19409,474,102,0.0,27,0,1989-07-09 00:00:00 -19410,474,87,0.0,43,0,1989-07-09 00:00:00 -19411,474,139,2.0,19,0,1989-07-09 00:00:00 -19412,474,91,0.0,31,0,1989-07-09 00:00:00 -19413,474,98,1.0,20,0,1989-07-09 00:00:00 -19414,474,77,0.0,28,0,1989-07-09 00:00:00 -19415,474,54,3.0,17,0,1989-07-09 00:00:00 -19416,474,138,0.0,25,0,1989-07-09 00:00:00 -19417,474,93,0.0,35,0,1989-07-09 00:00:00 -19418,474,150,0.0,30,0,1989-07-09 00:00:00 -19419,474,163,0.0,42,0,1989-07-09 00:00:00 -19420,474,122,13.0,5,1,1989-07-09 00:00:00 -19421,474,161,0.0,37,0,1989-07-09 00:00:00 -19422,474,136,3.0,15,0,1989-07-09 00:00:00 -19423,474,94,15.0,4,1,1989-07-09 00:00:00 -19424,474,116,38.0,1,2,1989-07-09 00:00:00 -19425,474,126,4.0,12,0,1989-07-09 00:00:00 -19426,474,64,5.0,8,0,1989-07-09 00:00:00 -19427,474,117,4.0,14,0,1989-07-09 00:00:00 -19428,474,130,4.0,11,0,1989-07-09 00:00:00 -19429,474,155,1.0,21,0,1989-07-09 00:00:00 -19430,474,137,0.0,24,0,1989-07-09 00:00:00 -19431,474,128,1.0,22,0,1989-07-09 00:00:00 -19432,474,144,8.0,6,0,1989-07-09 00:00:00 -19433,474,101,27.0,2,3,1989-07-09 00:00:00 -19434,474,104,6.0,7,0,1989-07-09 00:00:00 -19435,474,83,1.0,23,0,1989-07-09 00:00:00 -19436,474,145,0.0,36,0,1989-07-09 00:00:00 -19437,474,157,4.0,9,0,1989-07-09 00:00:00 -19438,474,121,0.0,26,0,1989-07-09 00:00:00 -19439,474,156,3.0,16,0,1989-07-09 00:00:00 -19440,474,109,4.0,10,0,1989-07-09 00:00:00 -19441,474,111,0.0,29,0,1989-07-09 00:00:00 -19442,474,118,22.0,3,0,1989-07-09 00:00:00 -19443,475,93,2.0,20,0,1989-07-16 00:00:00 -19444,475,76,0.0,35,0,1989-07-16 00:00:00 -19445,475,158,1.0,25,0,1989-07-16 00:00:00 -19446,475,113,0.0,38,0,1989-07-16 00:00:00 -19447,475,162,2.0,18,0,1989-07-16 00:00:00 -19448,475,147,0.0,39,0,1989-07-16 00:00:00 -19449,475,89,0.0,34,0,1989-07-16 00:00:00 -19450,475,132,4.0,14,0,1989-07-16 00:00:00 -19451,475,138,0.0,27,0,1989-07-16 00:00:00 -19452,475,160,0.0,41,0,1989-07-16 00:00:00 -19453,475,161,0.0,37,0,1989-07-16 00:00:00 -19454,475,163,0.0,42,0,1989-07-16 00:00:00 -19455,475,87,0.0,43,0,1989-07-16 00:00:00 -19456,475,139,2.0,19,0,1989-07-16 00:00:00 -19457,475,91,0.0,30,0,1989-07-16 00:00:00 -19458,475,77,0.0,31,0,1989-07-16 00:00:00 -19459,475,54,3.0,17,0,1989-07-16 00:00:00 -19460,475,122,13.0,5,1,1989-07-16 00:00:00 -19461,475,159,0.0,40,0,1989-07-16 00:00:00 -19462,475,130,4.0,12,0,1989-07-16 00:00:00 -19463,475,101,27.0,2,3,1989-07-16 00:00:00 -19464,475,121,0.0,28,0,1989-07-16 00:00:00 -19465,475,102,0.0,29,0,1989-07-16 00:00:00 -19466,475,94,21.0,4,1,1989-07-16 00:00:00 -19467,475,116,47.0,1,3,1989-07-16 00:00:00 -19468,475,126,4.0,13,0,1989-07-16 00:00:00 -19469,475,64,5.0,9,0,1989-07-16 00:00:00 -19470,475,117,4.0,15,0,1989-07-16 00:00:00 -19471,475,144,12.0,6,0,1989-07-16 00:00:00 -19472,475,155,1.0,23,0,1989-07-16 00:00:00 -19473,475,136,6.0,8,0,1989-07-16 00:00:00 -19474,475,137,0.0,26,0,1989-07-16 00:00:00 -19475,475,104,6.0,7,0,1989-07-16 00:00:00 -19476,475,111,0.0,32,0,1989-07-16 00:00:00 -19477,475,109,4.0,11,0,1989-07-16 00:00:00 -19478,475,156,3.0,16,0,1989-07-16 00:00:00 -19479,475,118,22.0,3,0,1989-07-16 00:00:00 -19480,475,157,4.0,10,0,1989-07-16 00:00:00 -19481,475,145,0.0,36,0,1989-07-16 00:00:00 -19482,475,83,1.0,24,0,1989-07-16 00:00:00 -19483,475,128,1.0,21,0,1989-07-16 00:00:00 -19484,475,150,0.0,33,0,1989-07-16 00:00:00 -19485,475,98,1.0,22,0,1989-07-16 00:00:00 -19486,476,138,0.0,27,0,1989-07-30 00:00:00 -19487,476,145,0.0,36,0,1989-07-30 00:00:00 -19488,476,157,4.0,11,0,1989-07-30 00:00:00 -19489,476,118,25.0,4,0,1989-07-30 00:00:00 -19490,476,156,3.0,16,0,1989-07-30 00:00:00 -19491,476,109,4.0,12,0,1989-07-30 00:00:00 -19492,476,111,0.0,32,0,1989-07-30 00:00:00 -19493,476,101,36.0,2,4,1989-07-30 00:00:00 -19494,476,128,1.0,21,0,1989-07-30 00:00:00 -19495,476,83,1.0,24,0,1989-07-30 00:00:00 -19496,476,137,0.0,26,0,1989-07-30 00:00:00 -19497,476,144,12.0,6,0,1989-07-30 00:00:00 -19498,476,117,5.0,10,0,1989-07-30 00:00:00 -19499,476,64,5.0,9,0,1989-07-30 00:00:00 -19500,476,126,4.0,14,0,1989-07-30 00:00:00 -19501,476,116,53.0,1,3,1989-07-30 00:00:00 -19502,476,94,25.0,3,1,1989-07-30 00:00:00 -19503,476,150,0.0,33,0,1989-07-30 00:00:00 -19504,476,102,0.0,29,0,1989-07-30 00:00:00 -19505,476,155,1.0,23,0,1989-07-30 00:00:00 -19506,476,121,0.0,28,0,1989-07-30 00:00:00 -19507,476,104,6.0,8,0,1989-07-30 00:00:00 -19508,476,130,4.0,13,0,1989-07-30 00:00:00 -19509,476,54,3.0,17,0,1989-07-30 00:00:00 -19510,476,136,8.0,7,0,1989-07-30 00:00:00 -19511,476,77,0.0,31,0,1989-07-30 00:00:00 -19512,476,98,1.0,22,0,1989-07-30 00:00:00 -19513,476,91,0.0,30,0,1989-07-30 00:00:00 -19514,476,139,2.0,20,0,1989-07-30 00:00:00 -19515,476,87,0.0,43,0,1989-07-30 00:00:00 -19516,476,161,0.0,37,0,1989-07-30 00:00:00 -19517,476,160,0.0,41,0,1989-07-30 00:00:00 -19518,476,159,0.0,40,0,1989-07-30 00:00:00 -19519,476,163,0.0,42,0,1989-07-30 00:00:00 -19520,476,93,2.0,18,0,1989-07-30 00:00:00 -19521,476,89,0.0,34,0,1989-07-30 00:00:00 -19522,476,147,0.0,39,0,1989-07-30 00:00:00 -19523,476,162,2.0,19,0,1989-07-30 00:00:00 -19524,476,113,0.0,38,0,1989-07-30 00:00:00 -19525,476,158,1.0,25,0,1989-07-30 00:00:00 -19526,476,76,0.0,35,0,1989-07-30 00:00:00 -19527,476,132,4.0,15,0,1989-07-30 00:00:00 -19528,476,122,13.0,5,1,1989-07-30 00:00:00 -19529,477,159,0.0,38,0,1989-08-13 00:00:00 -19530,477,132,4.0,15,0,1989-08-13 00:00:00 -19531,477,89,0.0,34,0,1989-08-13 00:00:00 -19532,477,158,1.0,25,0,1989-08-13 00:00:00 -19533,477,162,2.0,19,0,1989-08-13 00:00:00 -19534,477,113,0.0,39,0,1989-08-13 00:00:00 -19535,477,160,0.0,41,0,1989-08-13 00:00:00 -19536,477,147,0.0,40,0,1989-08-13 00:00:00 -19537,477,161,0.0,37,0,1989-08-13 00:00:00 -19538,477,150,0.0,33,0,1989-08-13 00:00:00 -19539,477,87,0.0,43,0,1989-08-13 00:00:00 -19540,477,139,2.0,20,0,1989-08-13 00:00:00 -19541,477,91,0.0,30,0,1989-08-13 00:00:00 -19542,477,98,1.0,22,0,1989-08-13 00:00:00 -19543,477,77,0.0,31,0,1989-08-13 00:00:00 -19544,477,54,3.0,17,0,1989-08-13 00:00:00 -19545,477,138,0.0,27,0,1989-08-13 00:00:00 -19546,477,102,0.0,29,0,1989-08-13 00:00:00 -19547,477,76,0.0,35,0,1989-08-13 00:00:00 -19548,477,163,0.0,42,0,1989-08-13 00:00:00 -19549,477,93,2.0,18,0,1989-08-13 00:00:00 -19550,477,101,42.0,2,4,1989-08-13 00:00:00 -19551,477,130,4.0,13,0,1989-08-13 00:00:00 -19552,477,122,17.0,5,1,1989-08-13 00:00:00 -19553,477,116,56.0,1,3,1989-08-13 00:00:00 -19554,477,126,4.0,14,0,1989-08-13 00:00:00 -19555,477,64,5.0,10,0,1989-08-13 00:00:00 -19556,477,117,5.0,11,0,1989-08-13 00:00:00 -19557,477,144,12.0,6,0,1989-08-13 00:00:00 -19558,477,155,1.0,23,0,1989-08-13 00:00:00 -19559,477,137,0.0,26,0,1989-08-13 00:00:00 -19560,477,128,1.0,21,0,1989-08-13 00:00:00 -19561,477,104,6.0,9,0,1989-08-13 00:00:00 -19562,477,94,34.0,3,2,1989-08-13 00:00:00 -19563,477,111,0.0,32,0,1989-08-13 00:00:00 -19564,477,121,0.0,28,0,1989-08-13 00:00:00 -19565,477,83,1.0,24,0,1989-08-13 00:00:00 -19566,477,145,0.0,36,0,1989-08-13 00:00:00 -19567,477,136,9.0,7,0,1989-08-13 00:00:00 -19568,477,118,25.0,4,0,1989-08-13 00:00:00 -19569,477,156,3.0,16,0,1989-08-13 00:00:00 -19570,477,109,4.0,12,0,1989-08-13 00:00:00 -19571,477,157,6.0,8,0,1989-08-13 00:00:00 -19572,478,160,0.0,41,0,1989-08-27 00:00:00 -19573,478,158,1.0,25,0,1989-08-27 00:00:00 -19574,478,113,0.0,39,0,1989-08-27 00:00:00 -19575,478,162,2.0,20,0,1989-08-27 00:00:00 -19576,478,147,0.0,40,0,1989-08-27 00:00:00 -19577,478,89,0.0,34,0,1989-08-27 00:00:00 -19578,478,132,4.0,15,0,1989-08-27 00:00:00 -19579,478,159,0.0,38,0,1989-08-27 00:00:00 -19580,478,161,0.0,37,0,1989-08-27 00:00:00 -19581,478,77,0.0,32,0,1989-08-27 00:00:00 -19582,478,87,0.0,43,0,1989-08-27 00:00:00 -19583,478,91,0.0,30,0,1989-08-27 00:00:00 -19584,478,98,1.0,22,0,1989-08-27 00:00:00 -19585,478,76,0.0,35,0,1989-08-27 00:00:00 -19586,478,54,3.0,17,0,1989-08-27 00:00:00 -19587,478,138,0.0,27,0,1989-08-27 00:00:00 -19588,478,102,0.0,29,0,1989-08-27 00:00:00 -19589,478,150,0.0,33,0,1989-08-27 00:00:00 -19590,478,133,0.0,44,0,1989-08-27 00:00:00 -19591,478,163,0.0,42,0,1989-08-27 00:00:00 -19592,478,93,2.0,19,0,1989-08-27 00:00:00 -19593,478,139,2.0,18,0,1989-08-27 00:00:00 -19594,478,130,4.0,14,0,1989-08-27 00:00:00 -19595,478,116,62.0,1,3,1989-08-27 00:00:00 -19596,478,126,4.0,13,0,1989-08-27 00:00:00 -19597,478,64,5.0,11,0,1989-08-27 00:00:00 -19598,478,117,6.0,10,0,1989-08-27 00:00:00 -19599,478,144,14.0,6,0,1989-08-27 00:00:00 -19600,478,155,1.0,23,0,1989-08-27 00:00:00 -19601,478,137,0.0,26,0,1989-08-27 00:00:00 -19602,478,122,20.0,5,1,1989-08-27 00:00:00 -19603,478,128,1.0,21,0,1989-08-27 00:00:00 -19604,478,104,6.0,9,0,1989-08-27 00:00:00 -19605,478,94,38.0,3,2,1989-08-27 00:00:00 -19606,478,111,0.0,31,0,1989-08-27 00:00:00 -19607,478,109,4.0,12,0,1989-08-27 00:00:00 -19608,478,156,3.0,16,0,1989-08-27 00:00:00 -19609,478,118,25.0,4,0,1989-08-27 00:00:00 -19610,478,157,6.0,8,0,1989-08-27 00:00:00 -19611,478,145,0.0,36,0,1989-08-27 00:00:00 -19612,478,83,1.0,24,0,1989-08-27 00:00:00 -19613,478,121,0.0,28,0,1989-08-27 00:00:00 -19614,478,136,9.0,7,0,1989-08-27 00:00:00 -19615,478,101,51.0,2,5,1989-08-27 00:00:00 -19616,479,161,0.0,37,0,1989-09-10 00:00:00 -19617,479,160,0.0,41,0,1989-09-10 00:00:00 -19618,479,159,0.0,38,0,1989-09-10 00:00:00 -19619,479,113,0.0,39,0,1989-09-10 00:00:00 -19620,479,89,0.0,35,0,1989-09-10 00:00:00 -19621,479,147,0.0,40,0,1989-09-10 00:00:00 -19622,479,162,2.0,21,0,1989-09-10 00:00:00 -19623,479,163,0.0,42,0,1989-09-10 00:00:00 -19624,479,132,4.0,17,0,1989-09-10 00:00:00 -19625,479,87,0.0,43,0,1989-09-10 00:00:00 -19626,479,54,5.0,12,0,1989-09-10 00:00:00 -19627,479,91,0.0,31,0,1989-09-10 00:00:00 -19628,479,98,1.0,24,0,1989-09-10 00:00:00 -19629,479,77,0.0,33,0,1989-09-10 00:00:00 -19630,479,138,0.0,28,0,1989-09-10 00:00:00 -19631,479,102,0.0,30,0,1989-09-10 00:00:00 -19632,479,150,0.0,34,0,1989-09-10 00:00:00 -19633,479,133,0.0,45,0,1989-09-10 00:00:00 -19634,479,164,0.0,44,0,1989-09-10 00:00:00 -19635,479,158,1.0,26,0,1989-09-10 00:00:00 -19636,479,139,2.0,20,0,1989-09-10 00:00:00 -19637,479,76,6.0,8,0,1989-09-10 00:00:00 -19638,479,93,2.0,19,0,1989-09-10 00:00:00 -19639,479,122,24.0,5,1,1989-09-10 00:00:00 -19640,479,94,38.0,3,2,1989-09-10 00:00:00 -19641,479,116,71.0,1,4,1989-09-10 00:00:00 -19642,479,126,4.0,15,0,1989-09-10 00:00:00 -19643,479,64,5.0,13,0,1989-09-10 00:00:00 -19644,479,117,6.0,11,0,1989-09-10 00:00:00 -19645,479,144,14.0,6,0,1989-09-10 00:00:00 -19646,479,137,0.0,27,0,1989-09-10 00:00:00 -19647,479,128,1.0,23,0,1989-09-10 00:00:00 -19648,479,104,6.0,10,0,1989-09-10 00:00:00 -19649,479,101,51.0,2,5,1989-09-10 00:00:00 -19650,479,155,1.0,25,0,1989-09-10 00:00:00 -19651,479,109,4.0,14,0,1989-09-10 00:00:00 -19652,479,111,0.0,32,0,1989-09-10 00:00:00 -19653,479,136,9.0,7,0,1989-09-10 00:00:00 -19654,479,121,0.0,29,0,1989-09-10 00:00:00 -19655,479,83,2.0,22,0,1989-09-10 00:00:00 -19656,479,130,4.0,16,0,1989-09-10 00:00:00 -19657,479,157,6.0,9,0,1989-09-10 00:00:00 -19658,479,118,28.0,4,0,1989-09-10 00:00:00 -19659,479,156,3.0,18,0,1989-09-10 00:00:00 -19660,479,145,0.0,36,0,1989-09-10 00:00:00 -19661,480,163,0.0,44,0,1989-09-24 00:00:00 -19662,480,113,0.0,39,0,1989-09-24 00:00:00 -19663,480,162,2.0,21,0,1989-09-24 00:00:00 -19664,480,147,0.0,40,0,1989-09-24 00:00:00 -19665,480,89,0.0,35,0,1989-09-24 00:00:00 -19666,480,132,4.0,18,0,1989-09-24 00:00:00 -19667,480,159,0.0,38,0,1989-09-24 00:00:00 -19668,480,160,0.0,41,0,1989-09-24 00:00:00 -19669,480,161,0.0,37,0,1989-09-24 00:00:00 -19670,480,87,0.0,45,0,1989-09-24 00:00:00 -19671,480,108,0.0,42,0,1989-09-24 00:00:00 -19672,480,91,0.0,32,0,1989-09-24 00:00:00 -19673,480,98,1.0,25,0,1989-09-24 00:00:00 -19674,480,77,0.0,33,0,1989-09-24 00:00:00 -19675,480,54,5.0,13,0,1989-09-24 00:00:00 -19676,480,138,0.0,28,0,1989-09-24 00:00:00 -19677,480,102,0.0,31,0,1989-09-24 00:00:00 -19678,480,150,0.0,34,0,1989-09-24 00:00:00 -19679,480,133,0.0,46,0,1989-09-24 00:00:00 -19680,480,164,0.0,43,0,1989-09-24 00:00:00 -19681,480,158,1.0,26,0,1989-09-24 00:00:00 -19682,480,139,6.0,10,0,1989-09-24 00:00:00 -19683,480,76,15.0,7,1,1989-09-24 00:00:00 -19684,480,94,38.0,3,2,1989-09-24 00:00:00 -19685,480,122,24.0,5,1,1989-09-24 00:00:00 -19686,480,93,4.0,19,0,1989-09-24 00:00:00 -19687,480,116,75.0,1,4,1989-09-24 00:00:00 -19688,480,126,4.0,16,0,1989-09-24 00:00:00 -19689,480,64,5.0,14,0,1989-09-24 00:00:00 -19690,480,117,6.0,12,0,1989-09-24 00:00:00 -19691,480,144,17.0,6,0,1989-09-24 00:00:00 -19692,480,137,0.0,27,0,1989-09-24 00:00:00 -19693,480,128,1.0,24,0,1989-09-24 00:00:00 -19694,480,104,6.0,11,0,1989-09-24 00:00:00 -19695,480,101,51.0,2,5,1989-09-24 00:00:00 -19696,480,155,2.0,22,0,1989-09-24 00:00:00 -19697,480,109,4.0,15,0,1989-09-24 00:00:00 -19698,480,111,0.0,29,0,1989-09-24 00:00:00 -19699,480,136,9.0,8,0,1989-09-24 00:00:00 -19700,480,121,0.0,30,0,1989-09-24 00:00:00 -19701,480,83,2.0,23,0,1989-09-24 00:00:00 -19702,480,130,4.0,17,0,1989-09-24 00:00:00 -19703,480,157,6.0,9,0,1989-09-24 00:00:00 -19704,480,118,28.0,4,0,1989-09-24 00:00:00 -19705,480,156,3.0,20,0,1989-09-24 00:00:00 -19706,480,145,0.0,36,0,1989-09-24 00:00:00 -19707,481,163,0.0,45,0,1989-10-01 00:00:00 -19708,481,113,0.0,40,0,1989-10-01 00:00:00 -19709,481,162,2.0,21,0,1989-10-01 00:00:00 -19710,481,147,0.0,41,0,1989-10-01 00:00:00 -19711,481,89,0.0,35,0,1989-10-01 00:00:00 -19712,481,132,4.0,18,0,1989-10-01 00:00:00 -19713,481,159,0.0,38,0,1989-10-01 00:00:00 -19714,481,160,0.0,42,0,1989-10-01 00:00:00 -19715,481,161,0.0,39,0,1989-10-01 00:00:00 -19716,481,87,0.0,43,0,1989-10-01 00:00:00 -19717,481,158,1.0,26,0,1989-10-01 00:00:00 -19718,481,91,0.0,32,0,1989-10-01 00:00:00 -19719,481,98,1.0,25,0,1989-10-01 00:00:00 -19720,481,77,0.0,33,0,1989-10-01 00:00:00 -19721,481,54,8.0,9,0,1989-10-01 00:00:00 -19722,481,138,0.0,29,0,1989-10-01 00:00:00 -19723,481,150,0.0,34,0,1989-10-01 00:00:00 -19724,481,133,0.0,46,0,1989-10-01 00:00:00 -19725,481,164,0.0,44,0,1989-10-01 00:00:00 -19726,481,108,0.0,37,0,1989-10-01 00:00:00 -19727,481,139,6.0,11,0,1989-10-01 00:00:00 -19728,481,76,21.0,6,1,1989-10-01 00:00:00 -19729,481,102,0.0,31,0,1989-10-01 00:00:00 -19730,481,122,24.0,5,1,1989-10-01 00:00:00 -19731,481,116,76.0,1,4,1989-10-01 00:00:00 -19732,481,126,4.0,16,0,1989-10-01 00:00:00 -19733,481,64,5.0,14,0,1989-10-01 00:00:00 -19734,481,93,4.0,19,0,1989-10-01 00:00:00 -19735,481,117,6.0,13,0,1989-10-01 00:00:00 -19736,481,144,17.0,7,0,1989-10-01 00:00:00 -19737,481,155,2.0,22,0,1989-10-01 00:00:00 -19738,481,137,0.0,28,0,1989-10-01 00:00:00 -19739,481,128,1.0,24,0,1989-10-01 00:00:00 -19740,481,104,6.0,12,0,1989-10-01 00:00:00 -19741,481,94,38.0,3,2,1989-10-01 00:00:00 -19742,481,111,1.0,27,0,1989-10-01 00:00:00 -19743,481,109,4.0,15,0,1989-10-01 00:00:00 -19744,481,156,3.0,20,0,1989-10-01 00:00:00 -19745,481,118,30.0,4,0,1989-10-01 00:00:00 -19746,481,157,6.0,10,0,1989-10-01 00:00:00 -19747,481,145,0.0,36,0,1989-10-01 00:00:00 -19748,481,83,2.0,23,0,1989-10-01 00:00:00 -19749,481,121,0.0,30,0,1989-10-01 00:00:00 -19750,481,136,9.0,8,0,1989-10-01 00:00:00 -19751,481,130,4.0,17,0,1989-10-01 00:00:00 -19752,481,101,60.0,2,6,1989-10-01 00:00:00 -19753,482,156,3.0,21,0,1989-10-22 00:00:00 -19754,482,118,36.0,4,0,1989-10-22 00:00:00 -19755,482,157,6.0,11,0,1989-10-22 00:00:00 -19756,482,130,4.0,17,0,1989-10-22 00:00:00 -19757,482,83,4.0,20,0,1989-10-22 00:00:00 -19758,482,121,0.0,30,0,1989-10-22 00:00:00 -19759,482,136,12.0,8,0,1989-10-22 00:00:00 -19760,482,109,4.0,15,0,1989-10-22 00:00:00 -19761,482,145,0.0,36,0,1989-10-22 00:00:00 -19762,482,111,1.0,27,0,1989-10-22 00:00:00 -19763,482,144,26.0,6,1,1989-10-22 00:00:00 -19764,482,104,6.0,13,0,1989-10-22 00:00:00 -19765,482,128,1.0,24,0,1989-10-22 00:00:00 -19766,482,137,0.0,28,0,1989-10-22 00:00:00 -19767,482,155,2.0,23,0,1989-10-22 00:00:00 -19768,482,117,7.0,10,0,1989-10-22 00:00:00 -19769,482,64,5.0,14,0,1989-10-22 00:00:00 -19770,482,126,4.0,16,0,1989-10-22 00:00:00 -19771,482,116,76.0,1,4,1989-10-22 00:00:00 -19772,482,94,38.0,3,2,1989-10-22 00:00:00 -19773,482,122,28.0,5,1,1989-10-22 00:00:00 -19774,482,101,60.0,2,6,1989-10-22 00:00:00 -19775,482,93,4.0,19,0,1989-10-22 00:00:00 -19776,482,113,0.0,40,0,1989-10-22 00:00:00 -19777,482,162,2.0,22,0,1989-10-22 00:00:00 -19778,482,133,0.0,47,0,1989-10-22 00:00:00 -19779,482,89,0.0,35,0,1989-10-22 00:00:00 -19780,482,132,4.0,18,0,1989-10-22 00:00:00 -19781,482,159,0.0,38,0,1989-10-22 00:00:00 -19782,482,76,21.0,7,1,1989-10-22 00:00:00 -19783,482,158,1.0,26,0,1989-10-22 00:00:00 -19784,482,139,6.0,12,0,1989-10-22 00:00:00 -19785,482,161,0.0,39,0,1989-10-22 00:00:00 -19786,482,146,0.0,41,0,1989-10-22 00:00:00 -19787,482,108,0.0,37,0,1989-10-22 00:00:00 -19788,482,77,0.0,33,0,1989-10-22 00:00:00 -19789,482,150,0.0,34,0,1989-10-22 00:00:00 -19790,482,102,0.0,31,0,1989-10-22 00:00:00 -19791,482,138,0.0,29,0,1989-10-22 00:00:00 -19792,482,54,8.0,9,0,1989-10-22 00:00:00 -19793,482,98,1.0,25,0,1989-10-22 00:00:00 -19794,482,91,0.0,32,0,1989-10-22 00:00:00 -19795,482,87,0.0,44,0,1989-10-22 00:00:00 -19796,482,163,0.0,46,0,1989-10-22 00:00:00 -19797,482,160,0.0,43,0,1989-10-22 00:00:00 -19798,482,147,0.0,42,0,1989-10-22 00:00:00 -19799,482,164,0.0,45,0,1989-10-22 00:00:00 -19800,483,161,0.0,39,0,1989-11-05 00:00:00 -19801,483,160,0.0,43,0,1989-11-05 00:00:00 -19802,483,159,0.0,37,0,1989-11-05 00:00:00 -19803,483,113,0.0,40,0,1989-11-05 00:00:00 -19804,483,89,0.0,35,0,1989-11-05 00:00:00 -19805,483,147,0.0,42,0,1989-11-05 00:00:00 -19806,483,162,2.0,24,0,1989-11-05 00:00:00 -19807,483,87,0.0,44,0,1989-11-05 00:00:00 -19808,483,132,4.0,19,0,1989-11-05 00:00:00 -19809,483,139,6.0,12,0,1989-11-05 00:00:00 -19810,483,102,0.0,31,0,1989-11-05 00:00:00 -19811,483,98,1.0,27,0,1989-11-05 00:00:00 -19812,483,77,0.0,33,0,1989-11-05 00:00:00 -19813,483,54,8.0,9,0,1989-11-05 00:00:00 -19814,483,138,2.0,23,0,1989-11-05 00:00:00 -19815,483,150,0.0,34,0,1989-11-05 00:00:00 -19816,483,133,0.0,47,0,1989-11-05 00:00:00 -19817,483,164,0.0,45,0,1989-11-05 00:00:00 -19818,483,108,0.0,36,0,1989-11-05 00:00:00 -19819,483,146,0.0,41,0,1989-11-05 00:00:00 -19820,483,158,1.0,28,0,1989-11-05 00:00:00 -19821,483,91,0.0,32,0,1989-11-05 00:00:00 -19822,483,76,21.0,7,1,1989-11-05 00:00:00 -19823,483,163,0.0,46,0,1989-11-05 00:00:00 -19824,483,122,37.0,5,2,1989-11-05 00:00:00 -19825,483,93,5.0,15,0,1989-11-05 00:00:00 -19826,483,94,38.0,4,2,1989-11-05 00:00:00 -19827,483,116,76.0,1,4,1989-11-05 00:00:00 -19828,483,126,4.0,16,0,1989-11-05 00:00:00 -19829,483,64,5.0,14,0,1989-11-05 00:00:00 -19830,483,117,7.0,10,0,1989-11-05 00:00:00 -19831,483,144,32.0,6,1,1989-11-05 00:00:00 -19832,483,137,3.0,21,0,1989-11-05 00:00:00 -19833,483,128,1.0,26,0,1989-11-05 00:00:00 -19834,483,104,6.0,13,0,1989-11-05 00:00:00 -19835,483,101,60.0,2,6,1989-11-05 00:00:00 -19836,483,155,2.0,25,0,1989-11-05 00:00:00 -19837,483,109,4.0,17,0,1989-11-05 00:00:00 -19838,483,156,3.0,22,0,1989-11-05 00:00:00 -19839,483,118,40.0,3,0,1989-11-05 00:00:00 -19840,483,157,6.0,11,0,1989-11-05 00:00:00 -19841,483,145,0.0,38,0,1989-11-05 00:00:00 -19842,483,83,4.0,20,0,1989-11-05 00:00:00 -19843,483,121,0.0,30,0,1989-11-05 00:00:00 -19844,483,136,12.0,8,0,1989-11-05 00:00:00 -19845,483,111,1.0,29,0,1989-11-05 00:00:00 -19846,483,130,4.0,18,0,1989-11-05 00:00:00 -19847,484,98,0.0,30,0,1990-03-11 00:00:00 -19848,484,80,0.0,28,0,1990-03-11 00:00:00 -19849,484,150,0.0,26,0,1990-03-11 00:00:00 -19850,484,117,0.0,24,0,1990-03-11 00:00:00 -19851,484,87,0.0,16,0,1990-03-11 00:00:00 -19852,484,128,0.0,20,0,1990-03-11 00:00:00 -19853,484,76,0.0,18,0,1990-03-11 00:00:00 -19854,484,148,0.0,32,0,1990-03-11 00:00:00 -19855,484,126,0.0,14,0,1990-03-11 00:00:00 -19856,484,116,0.0,22,0,1990-03-11 00:00:00 -19857,484,91,0.0,34,0,1990-03-11 00:00:00 -19858,484,146,0.0,15,0,1990-03-11 00:00:00 -19859,484,102,0.0,8,0,1990-03-11 00:00:00 -19860,484,113,0.0,31,0,1990-03-11 00:00:00 -19861,484,149,0.0,33,0,1990-03-11 00:00:00 -19862,484,108,0.0,29,0,1990-03-11 00:00:00 -19863,484,77,0.0,25,0,1990-03-11 00:00:00 -19864,484,121,0.0,23,0,1990-03-11 00:00:00 -19865,484,109,0.0,21,0,1990-03-11 00:00:00 -19866,484,147,0.0,19,0,1990-03-11 00:00:00 -19867,484,94,0.0,17,0,1990-03-11 00:00:00 -19868,484,145,0.0,12,0,1990-03-11 00:00:00 -19869,484,89,0.0,13,0,1990-03-11 00:00:00 -19870,484,118,0.0,9,0,1990-03-11 00:00:00 -19871,484,104,0.0,10,0,1990-03-11 00:00:00 -19872,484,93,0.0,7,0,1990-03-11 00:00:00 -19873,484,137,1.0,6,0,1990-03-11 00:00:00 -19874,484,130,2.0,5,0,1990-03-11 00:00:00 -19875,484,136,3.0,4,0,1990-03-11 00:00:00 -19876,484,122,4.0,3,0,1990-03-11 00:00:00 -19877,484,54,6.0,2,0,1990-03-11 00:00:00 -19878,484,101,9.0,1,1,1990-03-11 00:00:00 -19879,484,139,0.0,27,0,1990-03-11 00:00:00 -19880,484,144,0.0,11,0,1990-03-11 00:00:00 -19881,485,94,3.0,7,0,1990-03-25 00:00:00 -19882,485,146,0.0,21,0,1990-03-25 00:00:00 -19883,485,126,0.0,20,0,1990-03-25 00:00:00 -19884,485,145,0.0,17,0,1990-03-25 00:00:00 -19885,485,87,0.0,23,0,1990-03-25 00:00:00 -19886,485,144,0.0,13,0,1990-03-25 00:00:00 -19887,485,118,0.0,12,0,1990-03-25 00:00:00 -19888,485,89,0.0,18,0,1990-03-25 00:00:00 -19889,485,128,0.0,28,0,1990-03-25 00:00:00 -19890,485,121,0.0,30,0,1990-03-25 00:00:00 -19891,485,76,6.0,4,0,1990-03-25 00:00:00 -19892,485,116,9.0,2,1,1990-03-25 00:00:00 -19893,485,117,0.0,27,0,1990-03-25 00:00:00 -19894,485,150,0.0,24,0,1990-03-25 00:00:00 -19895,485,139,0.0,31,0,1990-03-25 00:00:00 -19896,485,113,0.0,26,0,1990-03-25 00:00:00 -19897,485,148,0.0,34,0,1990-03-25 00:00:00 -19898,485,91,0.0,35,0,1990-03-25 00:00:00 -19899,485,147,0.0,25,0,1990-03-25 00:00:00 -19900,485,108,0.0,32,0,1990-03-25 00:00:00 -19901,485,136,4.0,6,0,1990-03-25 00:00:00 -19902,485,101,13.0,1,1,1990-03-25 00:00:00 -19903,485,122,6.0,5,0,1990-03-25 00:00:00 -19904,485,149,0.0,36,0,1990-03-25 00:00:00 -19905,485,98,0.0,33,0,1990-03-25 00:00:00 -19906,485,77,0.0,15,0,1990-03-25 00:00:00 -19907,485,109,0.0,29,0,1990-03-25 00:00:00 -19908,485,54,6.0,3,0,1990-03-25 00:00:00 -19909,485,111,0.0,16,0,1990-03-25 00:00:00 -19910,485,102,0.0,11,0,1990-03-25 00:00:00 -19911,485,93,0.0,10,0,1990-03-25 00:00:00 -19912,485,104,0.0,14,0,1990-03-25 00:00:00 -19913,485,80,0.0,19,0,1990-03-25 00:00:00 -19914,485,130,2.0,8,0,1990-03-25 00:00:00 -19915,485,137,1.0,9,0,1990-03-25 00:00:00 -19916,485,132,0.0,22,0,1990-03-25 00:00:00 -19917,486,145,0.0,21,0,1990-05-13 00:00:00 -19918,486,144,4.0,8,0,1990-05-13 00:00:00 -19919,486,54,7.0,5,0,1990-05-13 00:00:00 -19920,486,121,0.0,31,0,1990-05-13 00:00:00 -19921,486,117,0.0,13,0,1990-05-13 00:00:00 -19922,486,109,0.0,29,0,1990-05-13 00:00:00 -19923,486,147,0.0,27,0,1990-05-13 00:00:00 -19924,486,76,12.0,3,0,1990-05-13 00:00:00 -19925,486,94,3.0,9,0,1990-05-13 00:00:00 -19926,486,87,0.0,28,0,1990-05-13 00:00:00 -19927,486,146,0.0,19,0,1990-05-13 00:00:00 -19928,486,122,6.0,6,0,1990-05-13 00:00:00 -19929,486,104,0.0,18,0,1990-05-13 00:00:00 -19930,486,102,0.0,14,0,1990-05-13 00:00:00 -19931,486,93,0.0,12,0,1990-05-13 00:00:00 -19932,486,137,1.0,11,0,1990-05-13 00:00:00 -19933,486,130,2.0,10,0,1990-05-13 00:00:00 -19934,486,136,6.0,7,0,1990-05-13 00:00:00 -19935,486,89,0.0,22,0,1990-05-13 00:00:00 -19936,486,118,9.0,4,1,1990-05-13 00:00:00 -19937,486,126,0.0,23,0,1990-05-13 00:00:00 -19938,486,150,0.0,15,0,1990-05-13 00:00:00 -19939,486,80,0.0,24,0,1990-05-13 00:00:00 -19940,486,100,0.0,34,0,1990-05-13 00:00:00 -19941,486,138,0.0,32,0,1990-05-13 00:00:00 -19942,486,116,12.0,2,1,1990-05-13 00:00:00 -19943,486,128,0.0,25,0,1990-05-13 00:00:00 -19944,486,101,13.0,1,1,1990-05-13 00:00:00 -19945,486,139,0.0,33,0,1990-05-13 00:00:00 -19946,486,151,0.0,38,0,1990-05-13 00:00:00 -19947,486,108,0.0,20,0,1990-05-13 00:00:00 -19948,486,77,0.0,17,0,1990-05-13 00:00:00 -19949,486,113,0.0,30,0,1990-05-13 00:00:00 -19950,486,148,0.0,37,0,1990-05-13 00:00:00 -19951,486,149,0.0,39,0,1990-05-13 00:00:00 -19952,486,91,0.0,36,0,1990-05-13 00:00:00 -19953,486,111,0.0,16,0,1990-05-13 00:00:00 -19954,486,132,0.0,26,0,1990-05-13 00:00:00 -19955,486,98,0.0,35,0,1990-05-13 00:00:00 -19956,487,122,9.0,6,0,1990-05-27 00:00:00 -19957,487,98,0.0,35,0,1990-05-27 00:00:00 -19958,487,136,6.0,7,0,1990-05-27 00:00:00 -19959,487,138,0.0,33,0,1990-05-27 00:00:00 -19960,487,126,0.0,25,0,1990-05-27 00:00:00 -19961,487,101,22.0,1,2,1990-05-27 00:00:00 -19962,487,89,0.0,24,0,1990-05-27 00:00:00 -19963,487,144,4.0,8,0,1990-05-27 00:00:00 -19964,487,111,0.0,18,0,1990-05-27 00:00:00 -19965,487,137,1.0,13,0,1990-05-27 00:00:00 -19966,487,130,2.0,11,0,1990-05-27 00:00:00 -19967,487,102,1.0,12,0,1990-05-27 00:00:00 -19968,487,100,0.0,30,0,1990-05-27 00:00:00 -19969,487,151,0.0,38,0,1990-05-27 00:00:00 -19970,487,139,0.0,34,0,1990-05-27 00:00:00 -19971,487,150,0.0,17,0,1990-05-27 00:00:00 -19972,487,77,0.0,19,0,1990-05-27 00:00:00 -19973,487,117,0.0,15,0,1990-05-27 00:00:00 -19974,487,121,0.0,31,0,1990-05-27 00:00:00 -19975,487,116,12.0,4,1,1990-05-27 00:00:00 -19976,487,109,0.0,27,0,1990-05-27 00:00:00 -19977,487,128,0.0,28,0,1990-05-27 00:00:00 -19978,487,147,0.0,16,0,1990-05-27 00:00:00 -19979,487,76,16.0,2,0,1990-05-27 00:00:00 -19980,487,94,3.0,9,0,1990-05-27 00:00:00 -19981,487,93,0.0,14,0,1990-05-27 00:00:00 -19982,487,54,13.0,3,0,1990-05-27 00:00:00 -19983,487,146,0.0,21,0,1990-05-27 00:00:00 -19984,487,132,2.0,10,0,1990-05-27 00:00:00 -19985,487,91,0.0,36,0,1990-05-27 00:00:00 -19986,487,149,0.0,39,0,1990-05-27 00:00:00 -19987,487,148,0.0,37,0,1990-05-27 00:00:00 -19988,487,113,0.0,32,0,1990-05-27 00:00:00 -19989,487,108,0.0,22,0,1990-05-27 00:00:00 -19990,487,80,0.0,26,0,1990-05-27 00:00:00 -19991,487,145,0.0,23,0,1990-05-27 00:00:00 -19992,487,104,0.0,20,0,1990-05-27 00:00:00 -19993,487,118,9.0,5,1,1990-05-27 00:00:00 -19994,487,87,0.0,29,0,1990-05-27 00:00:00 -19995,488,76,19.0,2,0,1990-06-10 00:00:00 -19996,488,128,0.0,26,0,1990-06-10 00:00:00 -19997,488,101,31.0,1,3,1990-06-10 00:00:00 -19998,488,87,0.0,24,0,1990-06-10 00:00:00 -19999,488,137,1.0,14,0,1990-06-10 00:00:00 -20000,488,93,0.0,15,0,1990-06-10 00:00:00 -20001,488,102,1.0,13,0,1990-06-10 00:00:00 -20002,488,118,9.0,6,1,1990-06-10 00:00:00 -20003,488,145,0.0,25,0,1990-06-10 00:00:00 -20004,488,144,4.0,9,0,1990-06-10 00:00:00 -20005,488,104,0.0,21,0,1990-06-10 00:00:00 -20006,488,94,7.0,8,0,1990-06-10 00:00:00 -20007,488,147,0.0,16,0,1990-06-10 00:00:00 -20008,488,109,0.0,30,0,1990-06-10 00:00:00 -20009,488,116,14.0,3,1,1990-06-10 00:00:00 -20010,488,136,12.0,5,0,1990-06-10 00:00:00 -20011,488,130,2.0,10,0,1990-06-10 00:00:00 -20012,488,122,9.0,7,0,1990-06-10 00:00:00 -20013,488,121,0.0,20,0,1990-06-10 00:00:00 -20014,488,117,1.0,12,0,1990-06-10 00:00:00 -20015,488,77,0.0,19,0,1990-06-10 00:00:00 -20016,488,150,0.0,17,0,1990-06-10 00:00:00 -20017,488,139,0.0,34,0,1990-06-10 00:00:00 -20018,488,80,0.0,29,0,1990-06-10 00:00:00 -20019,488,98,0.0,35,0,1990-06-10 00:00:00 -20020,488,113,0.0,32,0,1990-06-10 00:00:00 -20021,488,148,0.0,37,0,1990-06-10 00:00:00 -20022,488,149,0.0,39,0,1990-06-10 00:00:00 -20023,488,108,0.0,23,0,1990-06-10 00:00:00 -20024,488,111,0.0,18,0,1990-06-10 00:00:00 -20025,488,91,0.0,36,0,1990-06-10 00:00:00 -20026,488,89,0.0,27,0,1990-06-10 00:00:00 -20027,488,126,0.0,28,0,1990-06-10 00:00:00 -20028,488,146,0.0,22,0,1990-06-10 00:00:00 -20029,488,54,13.0,4,0,1990-06-10 00:00:00 -20030,488,100,0.0,31,0,1990-06-10 00:00:00 -20031,488,138,0.0,33,0,1990-06-10 00:00:00 -20032,488,132,2.0,11,0,1990-06-10 00:00:00 -20033,488,151,0.0,38,0,1990-06-10 00:00:00 -20034,489,130,2.0,10,0,1990-06-24 00:00:00 -20035,489,116,23.0,2,2,1990-06-24 00:00:00 -20036,489,109,0.0,27,0,1990-06-24 00:00:00 -20037,489,128,0.0,26,0,1990-06-24 00:00:00 -20038,489,147,0.0,16,0,1990-06-24 00:00:00 -20039,489,76,23.0,3,0,1990-06-24 00:00:00 -20040,489,94,13.0,5,0,1990-06-24 00:00:00 -20041,489,87,0.0,24,0,1990-06-24 00:00:00 -20042,489,146,0.0,22,0,1990-06-24 00:00:00 -20043,489,137,1.0,14,0,1990-06-24 00:00:00 -20044,489,136,13.0,6,0,1990-06-24 00:00:00 -20045,489,118,9.0,8,1,1990-06-24 00:00:00 -20046,489,104,0.0,20,0,1990-06-24 00:00:00 -20047,489,54,13.0,4,0,1990-06-24 00:00:00 -20048,489,145,0.0,25,0,1990-06-24 00:00:00 -20049,489,89,0.0,28,0,1990-06-24 00:00:00 -20050,489,126,0.0,29,0,1990-06-24 00:00:00 -20051,489,101,31.0,1,3,1990-06-24 00:00:00 -20052,489,122,11.0,7,0,1990-06-24 00:00:00 -20053,489,121,0.0,21,0,1990-06-24 00:00:00 -20054,489,93,0.0,15,0,1990-06-24 00:00:00 -20055,489,117,1.0,12,0,1990-06-24 00:00:00 -20056,489,108,0.0,23,0,1990-06-24 00:00:00 -20057,489,150,0.0,17,0,1990-06-24 00:00:00 -20058,489,102,1.0,13,0,1990-06-24 00:00:00 -20059,489,138,0.0,33,0,1990-06-24 00:00:00 -20060,489,151,0.0,38,0,1990-06-24 00:00:00 -20061,489,77,0.0,19,0,1990-06-24 00:00:00 -20062,489,132,2.0,11,0,1990-06-24 00:00:00 -20063,489,111,0.0,18,0,1990-06-24 00:00:00 -20064,489,144,7.0,9,0,1990-06-24 00:00:00 -20065,489,100,0.0,31,0,1990-06-24 00:00:00 -20066,489,149,0.0,39,0,1990-06-24 00:00:00 -20067,489,148,0.0,37,0,1990-06-24 00:00:00 -20068,489,113,0.0,32,0,1990-06-24 00:00:00 -20069,489,98,0.0,35,0,1990-06-24 00:00:00 -20070,489,80,0.0,30,0,1990-06-24 00:00:00 -20071,489,139,0.0,34,0,1990-06-24 00:00:00 -20072,489,91,0.0,36,0,1990-06-24 00:00:00 -20073,490,94,13.0,6,0,1990-07-08 00:00:00 -20074,490,146,0.0,23,0,1990-07-08 00:00:00 -20075,490,126,0.0,29,0,1990-07-08 00:00:00 -20076,490,89,0.0,28,0,1990-07-08 00:00:00 -20077,490,76,25.0,3,0,1990-07-08 00:00:00 -20078,490,87,0.0,17,0,1990-07-08 00:00:00 -20079,490,101,35.0,1,3,1990-07-08 00:00:00 -20080,490,122,11.0,7,0,1990-07-08 00:00:00 -20081,490,54,13.0,5,0,1990-07-08 00:00:00 -20082,490,102,1.0,14,0,1990-07-08 00:00:00 -20083,490,145,0.0,25,0,1990-07-08 00:00:00 -20084,490,130,2.0,11,0,1990-07-08 00:00:00 -20085,490,137,1.0,15,0,1990-07-08 00:00:00 -20086,490,93,0.0,16,0,1990-07-08 00:00:00 -20087,490,147,0.0,18,0,1990-07-08 00:00:00 -20088,490,144,7.0,9,0,1990-07-08 00:00:00 -20089,490,109,0.0,27,0,1990-07-08 00:00:00 -20090,490,80,0.0,30,0,1990-07-08 00:00:00 -20091,490,117,1.0,13,0,1990-07-08 00:00:00 -20092,490,116,32.0,2,3,1990-07-08 00:00:00 -20093,490,136,16.0,4,0,1990-07-08 00:00:00 -20094,490,98,0.0,35,0,1990-07-08 00:00:00 -20095,490,113,0.0,32,0,1990-07-08 00:00:00 -20096,490,148,0.0,37,0,1990-07-08 00:00:00 -20097,490,149,0.0,39,0,1990-07-08 00:00:00 -20098,490,91,0.0,36,0,1990-07-08 00:00:00 -20099,490,111,0.0,20,0,1990-07-08 00:00:00 -20100,490,132,2.0,12,0,1990-07-08 00:00:00 -20101,490,138,0.0,33,0,1990-07-08 00:00:00 -20102,490,100,0.0,31,0,1990-07-08 00:00:00 -20103,490,151,0.0,38,0,1990-07-08 00:00:00 -20104,490,128,0.0,26,0,1990-07-08 00:00:00 -20105,490,118,10.0,8,1,1990-07-08 00:00:00 -20106,490,121,6.0,10,0,1990-07-08 00:00:00 -20107,490,108,0.0,24,0,1990-07-08 00:00:00 -20108,490,139,0.0,34,0,1990-07-08 00:00:00 -20109,490,150,0.0,19,0,1990-07-08 00:00:00 -20110,490,77,0.0,22,0,1990-07-08 00:00:00 -20111,490,104,0.0,21,0,1990-07-08 00:00:00 -20112,491,132,2.0,12,0,1990-07-15 00:00:00 -20113,491,136,18.0,4,0,1990-07-15 00:00:00 -20114,491,130,2.0,13,0,1990-07-15 00:00:00 -20115,491,101,39.0,2,3,1990-07-15 00:00:00 -20116,491,137,1.0,16,0,1990-07-15 00:00:00 -20117,491,104,0.0,22,0,1990-07-15 00:00:00 -20118,491,102,4.0,11,0,1990-07-15 00:00:00 -20119,491,144,7.0,9,0,1990-07-15 00:00:00 -20120,491,89,0.0,29,0,1990-07-15 00:00:00 -20121,491,54,13.0,6,0,1990-07-15 00:00:00 -20122,491,93,0.0,17,0,1990-07-15 00:00:00 -20123,491,109,0.0,28,0,1990-07-15 00:00:00 -20124,491,150,0.0,19,0,1990-07-15 00:00:00 -20125,491,117,1.0,14,0,1990-07-15 00:00:00 -20126,491,145,0.0,26,0,1990-07-15 00:00:00 -20127,491,126,0.0,30,0,1990-07-15 00:00:00 -20128,491,146,0.0,23,0,1990-07-15 00:00:00 -20129,491,87,1.0,15,0,1990-07-15 00:00:00 -20130,491,94,13.0,7,0,1990-07-15 00:00:00 -20131,491,76,25.0,3,0,1990-07-15 00:00:00 -20132,491,147,0.0,18,0,1990-07-15 00:00:00 -20133,491,128,0.0,27,0,1990-07-15 00:00:00 -20134,491,122,17.0,5,0,1990-07-15 00:00:00 -20135,491,151,0.0,38,0,1990-07-15 00:00:00 -20136,491,116,41.0,1,4,1990-07-15 00:00:00 -20137,491,121,6.0,10,0,1990-07-15 00:00:00 -20138,491,118,10.0,8,1,1990-07-15 00:00:00 -20139,491,138,0.0,24,0,1990-07-15 00:00:00 -20140,491,111,0.0,20,0,1990-07-15 00:00:00 -20141,491,91,0.0,36,0,1990-07-15 00:00:00 -20142,491,149,0.0,39,0,1990-07-15 00:00:00 -20143,491,148,0.0,37,0,1990-07-15 00:00:00 -20144,491,113,0.0,33,0,1990-07-15 00:00:00 -20145,491,98,0.0,34,0,1990-07-15 00:00:00 -20146,491,108,0.0,25,0,1990-07-15 00:00:00 -20147,491,80,0.0,31,0,1990-07-15 00:00:00 -20148,491,139,0.0,35,0,1990-07-15 00:00:00 -20149,491,77,0.0,21,0,1990-07-15 00:00:00 -20150,491,100,0.0,32,0,1990-07-15 00:00:00 -20151,492,104,0.0,22,0,1990-07-29 00:00:00 -20152,492,144,13.0,7,0,1990-07-29 00:00:00 -20153,492,94,13.0,8,0,1990-07-29 00:00:00 -20154,492,102,4.0,11,0,1990-07-29 00:00:00 -20155,492,89,0.0,29,0,1990-07-29 00:00:00 -20156,492,93,0.0,17,0,1990-07-29 00:00:00 -20157,492,122,18.0,4,0,1990-07-29 00:00:00 -20158,492,130,2.0,13,0,1990-07-29 00:00:00 -20159,492,147,0.0,18,0,1990-07-29 00:00:00 -20160,492,138,0.0,24,0,1990-07-29 00:00:00 -20161,492,109,0.0,28,0,1990-07-29 00:00:00 -20162,492,121,6.0,10,0,1990-07-29 00:00:00 -20163,492,117,1.0,14,0,1990-07-29 00:00:00 -20164,492,77,0.0,21,0,1990-07-29 00:00:00 -20165,492,150,0.0,19,0,1990-07-29 00:00:00 -20166,492,139,0.0,35,0,1990-07-29 00:00:00 -20167,492,80,0.0,31,0,1990-07-29 00:00:00 -20168,492,108,0.0,25,0,1990-07-29 00:00:00 -20169,492,98,0.0,34,0,1990-07-29 00:00:00 -20170,492,113,0.0,33,0,1990-07-29 00:00:00 -20171,492,137,1.0,16,0,1990-07-29 00:00:00 -20172,492,101,48.0,1,4,1990-07-29 00:00:00 -20173,492,148,0.0,37,0,1990-07-29 00:00:00 -20174,492,149,0.0,39,0,1990-07-29 00:00:00 -20175,492,91,0.0,36,0,1990-07-29 00:00:00 -20176,492,151,0.0,38,0,1990-07-29 00:00:00 -20177,492,116,44.0,2,4,1990-07-29 00:00:00 -20178,492,118,12.0,9,1,1990-07-29 00:00:00 -20179,492,100,0.0,32,0,1990-07-29 00:00:00 -20180,492,132,2.0,12,0,1990-07-29 00:00:00 -20181,492,54,13.0,6,0,1990-07-29 00:00:00 -20182,492,128,0.0,27,0,1990-07-29 00:00:00 -20183,492,111,0.0,20,0,1990-07-29 00:00:00 -20184,492,136,18.0,5,0,1990-07-29 00:00:00 -20185,492,76,29.0,3,0,1990-07-29 00:00:00 -20186,492,87,1.0,15,0,1990-07-29 00:00:00 -20187,492,146,0.0,23,0,1990-07-29 00:00:00 -20188,492,126,0.0,30,0,1990-07-29 00:00:00 -20189,492,145,0.0,26,0,1990-07-29 00:00:00 -20190,493,87,1.0,15,0,1990-08-12 00:00:00 -20191,493,146,0.0,25,0,1990-08-12 00:00:00 -20192,493,126,0.0,20,0,1990-08-12 00:00:00 -20193,493,145,0.0,27,0,1990-08-12 00:00:00 -20194,493,117,3.0,12,0,1990-08-12 00:00:00 -20195,493,54,13.0,7,0,1990-08-12 00:00:00 -20196,493,136,22.0,5,0,1990-08-12 00:00:00 -20197,493,94,13.0,9,0,1990-08-12 00:00:00 -20198,493,76,29.0,3,0,1990-08-12 00:00:00 -20199,493,151,0.0,38,0,1990-08-12 00:00:00 -20200,493,122,27.0,4,1,1990-08-12 00:00:00 -20201,493,121,6.0,10,0,1990-08-12 00:00:00 -20202,493,109,0.0,29,0,1990-08-12 00:00:00 -20203,493,116,44.0,2,4,1990-08-12 00:00:00 -20204,493,77,0.0,22,0,1990-08-12 00:00:00 -20205,493,150,0.0,17,0,1990-08-12 00:00:00 -20206,493,139,0.0,35,0,1990-08-12 00:00:00 -20207,493,80,0.0,32,0,1990-08-12 00:00:00 -20208,493,108,0.0,26,0,1990-08-12 00:00:00 -20209,493,98,0.0,30,0,1990-08-12 00:00:00 -20210,493,113,0.0,34,0,1990-08-12 00:00:00 -20211,493,148,0.0,37,0,1990-08-12 00:00:00 -20212,493,149,0.0,39,0,1990-08-12 00:00:00 -20213,493,91,0.0,36,0,1990-08-12 00:00:00 -20214,493,111,0.0,21,0,1990-08-12 00:00:00 -20215,493,132,2.0,13,0,1990-08-12 00:00:00 -20216,493,138,0.0,24,0,1990-08-12 00:00:00 -20217,493,100,0.0,33,0,1990-08-12 00:00:00 -20218,493,128,0.0,28,0,1990-08-12 00:00:00 -20219,493,147,0.0,19,0,1990-08-12 00:00:00 -20220,493,101,54.0,1,4,1990-08-12 00:00:00 -20221,493,144,13.0,8,0,1990-08-12 00:00:00 -20222,493,118,15.0,6,1,1990-08-12 00:00:00 -20223,493,102,5.0,11,0,1990-08-12 00:00:00 -20224,493,93,0.0,18,0,1990-08-12 00:00:00 -20225,493,137,1.0,16,0,1990-08-12 00:00:00 -20226,493,130,2.0,14,0,1990-08-12 00:00:00 -20227,493,104,0.0,23,0,1990-08-12 00:00:00 -20228,493,89,0.0,31,0,1990-08-12 00:00:00 -20229,494,94,13.0,9,0,1990-08-26 00:00:00 -20230,494,87,1.0,15,0,1990-08-26 00:00:00 -20231,494,146,0.0,25,0,1990-08-26 00:00:00 -20232,494,126,1.0,17,0,1990-08-26 00:00:00 -20233,494,138,0.0,24,0,1990-08-26 00:00:00 -20234,494,93,0.0,19,0,1990-08-26 00:00:00 -20235,494,137,1.0,16,0,1990-08-26 00:00:00 -20236,494,109,0.0,29,0,1990-08-26 00:00:00 -20237,494,102,5.0,11,0,1990-08-26 00:00:00 -20238,494,118,15.0,7,1,1990-08-26 00:00:00 -20239,494,104,0.0,23,0,1990-08-26 00:00:00 -20240,494,144,16.0,6,0,1990-08-26 00:00:00 -20241,494,89,0.0,31,0,1990-08-26 00:00:00 -20242,494,130,2.0,14,0,1990-08-26 00:00:00 -20243,494,116,50.0,2,4,1990-08-26 00:00:00 -20244,494,132,2.0,13,0,1990-08-26 00:00:00 -20245,494,117,3.0,12,0,1990-08-26 00:00:00 -20246,494,111,0.0,21,0,1990-08-26 00:00:00 -20247,494,91,0.0,36,0,1990-08-26 00:00:00 -20248,494,149,0.0,39,0,1990-08-26 00:00:00 -20249,494,148,0.0,37,0,1990-08-26 00:00:00 -20250,494,113,0.0,34,0,1990-08-26 00:00:00 -20251,494,136,24.0,5,0,1990-08-26 00:00:00 -20252,494,54,13.0,8,0,1990-08-26 00:00:00 -20253,494,101,63.0,1,5,1990-08-26 00:00:00 -20254,494,100,0.0,33,0,1990-08-26 00:00:00 -20255,494,128,0.0,28,0,1990-08-26 00:00:00 -20256,494,147,0.0,20,0,1990-08-26 00:00:00 -20257,494,76,33.0,3,0,1990-08-26 00:00:00 -20258,494,151,0.0,38,0,1990-08-26 00:00:00 -20259,494,98,0.0,30,0,1990-08-26 00:00:00 -20260,494,121,6.0,10,0,1990-08-26 00:00:00 -20261,494,145,0.0,27,0,1990-08-26 00:00:00 -20262,494,77,0.0,22,0,1990-08-26 00:00:00 -20263,494,122,27.0,4,1,1990-08-26 00:00:00 -20264,494,150,0.0,18,0,1990-08-26 00:00:00 -20265,494,108,0.0,26,0,1990-08-26 00:00:00 -20266,494,139,0.0,35,0,1990-08-26 00:00:00 -20267,494,80,0.0,32,0,1990-08-26 00:00:00 -20268,495,122,27.0,4,1,1990-09-09 00:00:00 -20269,495,146,0.0,26,0,1990-09-09 00:00:00 -20270,495,87,1.0,16,0,1990-09-09 00:00:00 -20271,495,94,16.0,8,0,1990-09-09 00:00:00 -20272,495,109,0.0,25,0,1990-09-09 00:00:00 -20273,495,116,56.0,2,4,1990-09-09 00:00:00 -20274,495,121,6.0,10,0,1990-09-09 00:00:00 -20275,495,117,3.0,12,0,1990-09-09 00:00:00 -20276,495,77,0.0,22,0,1990-09-09 00:00:00 -20277,495,126,1.0,17,0,1990-09-09 00:00:00 -20278,495,150,0.0,18,0,1990-09-09 00:00:00 -20279,495,139,0.0,35,0,1990-09-09 00:00:00 -20280,495,132,2.0,13,0,1990-09-09 00:00:00 -20281,495,108,0.0,27,0,1990-09-09 00:00:00 -20282,495,98,0.0,30,0,1990-09-09 00:00:00 -20283,495,113,0.0,34,0,1990-09-09 00:00:00 -20284,495,148,0.0,37,0,1990-09-09 00:00:00 -20285,495,149,0.0,39,0,1990-09-09 00:00:00 -20286,495,111,0.0,21,0,1990-09-09 00:00:00 -20287,495,138,0.0,24,0,1990-09-09 00:00:00 -20288,495,100,0.0,33,0,1990-09-09 00:00:00 -20289,495,128,0.0,29,0,1990-09-09 00:00:00 -20290,495,147,0.0,20,0,1990-09-09 00:00:00 -20291,495,76,37.0,3,0,1990-09-09 00:00:00 -20292,495,151,0.0,38,0,1990-09-09 00:00:00 -20293,495,80,0.0,32,0,1990-09-09 00:00:00 -20294,495,145,0.0,28,0,1990-09-09 00:00:00 -20295,495,91,0.0,36,0,1990-09-09 00:00:00 -20296,495,89,0.0,31,0,1990-09-09 00:00:00 -20297,495,130,2.0,14,0,1990-09-09 00:00:00 -20298,495,137,2.0,15,0,1990-09-09 00:00:00 -20299,495,93,0.0,19,0,1990-09-09 00:00:00 -20300,495,102,5.0,11,0,1990-09-09 00:00:00 -20301,495,118,17.0,6,1,1990-09-09 00:00:00 -20302,495,104,0.0,23,0,1990-09-09 00:00:00 -20303,495,144,16.0,7,0,1990-09-09 00:00:00 -20304,495,136,24.0,5,0,1990-09-09 00:00:00 -20305,495,54,13.0,9,0,1990-09-09 00:00:00 -20306,495,101,72.0,1,6,1990-09-09 00:00:00 -20307,496,138,0.0,24,0,1990-09-23 00:00:00 -20308,496,100,0.0,33,0,1990-09-23 00:00:00 -20309,496,147,0.0,20,0,1990-09-23 00:00:00 -20310,496,113,0.0,34,0,1990-09-23 00:00:00 -20311,496,94,25.0,6,1,1990-09-23 00:00:00 -20312,496,151,0.0,38,0,1990-09-23 00:00:00 -20313,496,132,2.0,13,0,1990-09-23 00:00:00 -20314,496,144,17.0,8,0,1990-09-23 00:00:00 -20315,496,101,78.0,1,6,1990-09-23 00:00:00 -20316,496,76,40.0,3,0,1990-09-23 00:00:00 -20317,496,111,0.0,21,0,1990-09-23 00:00:00 -20318,496,149,0.0,39,0,1990-09-23 00:00:00 -20319,496,118,17.0,7,1,1990-09-23 00:00:00 -20320,496,145,0.0,28,0,1990-09-23 00:00:00 -20321,496,89,0.0,31,0,1990-09-23 00:00:00 -20322,496,126,1.0,17,0,1990-09-23 00:00:00 -20323,496,146,0.0,26,0,1990-09-23 00:00:00 -20324,496,87,1.0,16,0,1990-09-23 00:00:00 -20325,496,128,0.0,29,0,1990-09-23 00:00:00 -20326,496,109,0.0,25,0,1990-09-23 00:00:00 -20327,496,91,0.0,36,0,1990-09-23 00:00:00 -20328,496,116,60.0,2,4,1990-09-23 00:00:00 -20329,496,117,3.0,12,0,1990-09-23 00:00:00 -20330,496,77,0.0,23,0,1990-09-23 00:00:00 -20331,496,150,0.0,18,0,1990-09-23 00:00:00 -20332,496,139,0.0,35,0,1990-09-23 00:00:00 -20333,496,108,0.0,27,0,1990-09-23 00:00:00 -20334,496,98,0.0,30,0,1990-09-23 00:00:00 -20335,496,148,0.0,37,0,1990-09-23 00:00:00 -20336,496,121,6.0,10,0,1990-09-23 00:00:00 -20337,496,93,0.0,19,0,1990-09-23 00:00:00 -20338,496,80,0.0,32,0,1990-09-23 00:00:00 -20339,496,104,0.0,22,0,1990-09-23 00:00:00 -20340,496,130,2.0,14,0,1990-09-23 00:00:00 -20341,496,136,26.0,5,0,1990-09-23 00:00:00 -20342,496,122,27.0,4,1,1990-09-23 00:00:00 -20343,496,54,13.0,9,0,1990-09-23 00:00:00 -20344,496,102,5.0,11,0,1990-09-23 00:00:00 -20345,496,137,2.0,15,0,1990-09-23 00:00:00 -20346,497,146,0.0,27,0,1990-09-30 00:00:00 -20347,497,126,1.0,17,0,1990-09-30 00:00:00 -20348,497,145,0.0,29,0,1990-09-30 00:00:00 -20349,497,151,0.0,38,0,1990-09-30 00:00:00 -20350,497,100,0.0,34,0,1990-09-30 00:00:00 -20351,497,87,2.0,15,0,1990-09-30 00:00:00 -20352,497,116,69.0,2,5,1990-09-30 00:00:00 -20353,497,109,0.0,26,0,1990-09-30 00:00:00 -20354,497,138,0.0,25,0,1990-09-30 00:00:00 -20355,497,94,31.0,4,1,1990-09-30 00:00:00 -20356,497,121,6.0,10,0,1990-09-30 00:00:00 -20357,497,128,0.0,30,0,1990-09-30 00:00:00 -20358,497,117,3.0,12,0,1990-09-30 00:00:00 -20359,497,77,0.0,20,0,1990-09-30 00:00:00 -20360,497,150,0.0,18,0,1990-09-30 00:00:00 -20361,497,139,0.0,35,0,1990-09-30 00:00:00 -20362,497,80,0.0,33,0,1990-09-30 00:00:00 -20363,497,108,0.0,28,0,1990-09-30 00:00:00 -20364,497,98,0.0,31,0,1990-09-30 00:00:00 -20365,497,113,0.0,24,0,1990-09-30 00:00:00 -20366,497,148,0.0,37,0,1990-09-30 00:00:00 -20367,497,149,0.0,39,0,1990-09-30 00:00:00 -20368,497,91,0.0,36,0,1990-09-30 00:00:00 -20369,497,147,0.0,21,0,1990-09-30 00:00:00 -20370,497,76,40.0,3,0,1990-09-30 00:00:00 -20371,497,132,2.0,13,0,1990-09-30 00:00:00 -20372,497,111,0.0,22,0,1990-09-30 00:00:00 -20373,497,89,0.0,32,0,1990-09-30 00:00:00 -20374,497,144,21.0,7,0,1990-09-30 00:00:00 -20375,497,104,0.0,23,0,1990-09-30 00:00:00 -20376,497,118,19.0,8,1,1990-09-30 00:00:00 -20377,497,102,5.0,11,0,1990-09-30 00:00:00 -20378,497,101,78.0,1,6,1990-09-30 00:00:00 -20379,497,54,13.0,9,0,1990-09-30 00:00:00 -20380,497,136,26.0,6,0,1990-09-30 00:00:00 -20381,497,122,30.0,5,1,1990-09-30 00:00:00 -20382,497,93,0.0,19,0,1990-09-30 00:00:00 -20383,497,137,2.0,16,0,1990-09-30 00:00:00 -20384,497,130,2.0,14,0,1990-09-30 00:00:00 -20385,498,147,0.0,22,0,1990-10-21 00:00:00 -20386,498,100,0.0,34,0,1990-10-21 00:00:00 -20387,498,138,0.0,26,0,1990-10-21 00:00:00 -20388,498,136,35.0,4,1,1990-10-21 00:00:00 -20389,498,111,0.0,23,0,1990-10-21 00:00:00 -20390,498,76,40.0,3,0,1990-10-21 00:00:00 -20391,498,132,2.0,16,0,1990-10-21 00:00:00 -20392,498,94,31.0,6,1,1990-10-21 00:00:00 -20393,498,144,21.0,8,0,1990-10-21 00:00:00 -20394,498,64,0.0,35,0,1990-10-21 00:00:00 -20395,498,137,3.0,15,0,1990-10-21 00:00:00 -20396,498,93,0.0,21,0,1990-10-21 00:00:00 -20397,498,102,5.0,13,0,1990-10-21 00:00:00 -20398,498,118,22.0,7,1,1990-10-21 00:00:00 -20399,498,91,0.0,37,0,1990-10-21 00:00:00 -20400,498,101,78.0,1,6,1990-10-21 00:00:00 -20401,498,151,0.0,39,0,1990-10-21 00:00:00 -20402,498,149,0.0,40,0,1990-10-21 00:00:00 -20403,498,148,0.0,38,0,1990-10-21 00:00:00 -20404,498,113,0.0,25,0,1990-10-21 00:00:00 -20405,498,54,13.0,9,0,1990-10-21 00:00:00 -20406,498,146,0.0,28,0,1990-10-21 00:00:00 -20407,498,104,0.0,24,0,1990-10-21 00:00:00 -20408,498,122,32.0,5,1,1990-10-21 00:00:00 -20409,498,89,6.0,11,0,1990-10-21 00:00:00 -20410,498,126,1.0,18,0,1990-10-21 00:00:00 -20411,498,87,6.0,12,0,1990-10-21 00:00:00 -20412,498,128,0.0,31,0,1990-10-21 00:00:00 -20413,498,130,2.0,17,0,1990-10-21 00:00:00 -20414,498,109,0.0,27,0,1990-10-21 00:00:00 -20415,498,139,0.0,36,0,1990-10-21 00:00:00 -20416,498,98,0.0,32,0,1990-10-21 00:00:00 -20417,498,108,0.0,29,0,1990-10-21 00:00:00 -20418,498,80,0.0,33,0,1990-10-21 00:00:00 -20419,498,150,0.0,20,0,1990-10-21 00:00:00 -20420,498,77,0.0,19,0,1990-10-21 00:00:00 -20421,498,145,0.0,30,0,1990-10-21 00:00:00 -20422,498,121,6.0,10,0,1990-10-21 00:00:00 -20423,498,116,69.0,2,5,1990-10-21 00:00:00 -20424,498,117,3.0,14,0,1990-10-21 00:00:00 -20425,499,137,3.0,15,0,1990-11-04 00:00:00 -20426,499,93,0.0,21,0,1990-11-04 00:00:00 -20427,499,130,2.0,17,0,1990-11-04 00:00:00 -20428,499,136,43.0,3,2,1990-11-04 00:00:00 -20429,499,118,23.0,7,1,1990-11-04 00:00:00 -20430,499,101,78.0,1,6,1990-11-04 00:00:00 -20431,499,122,34.0,6,1,1990-11-04 00:00:00 -20432,499,104,0.0,24,0,1990-11-04 00:00:00 -20433,499,102,5.0,13,0,1990-11-04 00:00:00 -20434,499,54,13.0,9,0,1990-11-04 00:00:00 -20435,499,151,0.0,39,0,1990-11-04 00:00:00 -20436,499,144,21.0,8,0,1990-11-04 00:00:00 -20437,499,145,0.0,30,0,1990-11-04 00:00:00 -20438,499,89,6.0,11,0,1990-11-04 00:00:00 -20439,499,126,1.0,18,0,1990-11-04 00:00:00 -20440,499,146,0.0,28,0,1990-11-04 00:00:00 -20441,499,116,71.0,2,5,1990-11-04 00:00:00 -20442,499,121,6.0,10,0,1990-11-04 00:00:00 -20443,499,117,3.0,14,0,1990-11-04 00:00:00 -20444,499,77,0.0,19,0,1990-11-04 00:00:00 -20445,499,150,0.0,20,0,1990-11-04 00:00:00 -20446,499,139,0.0,36,0,1990-11-04 00:00:00 -20447,499,80,0.0,33,0,1990-11-04 00:00:00 -20448,499,108,0.0,29,0,1990-11-04 00:00:00 -20449,499,98,0.0,32,0,1990-11-04 00:00:00 -20450,499,64,0.0,35,0,1990-11-04 00:00:00 -20451,499,148,0.0,38,0,1990-11-04 00:00:00 -20452,499,87,6.0,12,0,1990-11-04 00:00:00 -20453,499,76,43.0,4,0,1990-11-04 00:00:00 -20454,499,147,0.0,22,0,1990-11-04 00:00:00 -20455,499,128,0.0,31,0,1990-11-04 00:00:00 -20456,499,109,0.0,27,0,1990-11-04 00:00:00 -20457,499,100,0.0,34,0,1990-11-04 00:00:00 -20458,499,94,37.0,5,1,1990-11-04 00:00:00 -20459,499,138,0.0,26,0,1990-11-04 00:00:00 -20460,499,132,2.0,16,0,1990-11-04 00:00:00 -20461,499,111,0.0,23,0,1990-11-04 00:00:00 -20462,499,91,0.0,37,0,1990-11-04 00:00:00 -20463,499,149,0.0,40,0,1990-11-04 00:00:00 -20464,499,113,0.0,25,0,1990-11-04 00:00:00 -20465,500,109,0.0,31,0,1991-03-10 00:00:00 -20466,500,99,0.0,29,0,1991-03-10 00:00:00 -20467,500,132,0.0,27,0,1991-03-10 00:00:00 -20468,500,108,0.0,25,0,1991-03-10 00:00:00 -20469,500,76,0.0,19,0,1991-03-10 00:00:00 -20470,500,126,0.0,21,0,1991-03-10 00:00:00 -20471,500,121,0.0,17,0,1991-03-10 00:00:00 -20472,500,89,0.0,15,0,1991-03-10 00:00:00 -20473,500,128,0.0,33,0,1991-03-10 00:00:00 -20474,500,138,0.0,23,0,1991-03-10 00:00:00 -20475,500,98,0.0,8,0,1991-03-10 00:00:00 -20476,500,86,0.0,22,0,1991-03-10 00:00:00 -20477,500,54,0.0,12,0,1991-03-10 00:00:00 -20478,500,118,0.0,14,0,1991-03-10 00:00:00 -20479,500,104,0.0,16,0,1991-03-10 00:00:00 -20480,500,122,0.0,18,0,1991-03-10 00:00:00 -20481,500,94,0.0,20,0,1991-03-10 00:00:00 -20482,500,56,0.0,13,0,1991-03-10 00:00:00 -20483,500,80,0.0,24,0,1991-03-10 00:00:00 -20484,500,102,0.0,26,0,1991-03-10 00:00:00 -20485,500,139,0.0,28,0,1991-03-10 00:00:00 -20486,500,140,0.0,30,0,1991-03-10 00:00:00 -20487,500,141,0.0,32,0,1991-03-10 00:00:00 -20488,500,127,0.0,34,0,1991-03-10 00:00:00 -20489,500,91,0.0,10,0,1991-03-10 00:00:00 -20490,500,83,0.0,11,0,1991-03-10 00:00:00 -20491,500,87,1.0,6,0,1991-03-10 00:00:00 -20492,500,77,0.0,7,0,1991-03-10 00:00:00 -20493,500,137,2.0,5,0,1991-03-10 00:00:00 -20494,500,130,3.0,4,0,1991-03-10 00:00:00 -20495,500,136,4.0,3,0,1991-03-10 00:00:00 -20496,500,116,6.0,2,0,1991-03-10 00:00:00 -20497,500,101,10.0,1,1,1991-03-10 00:00:00 -20498,500,93,0.0,9,0,1991-03-10 00:00:00 -20499,501,98,0.0,13,0,1991-03-24 00:00:00 -20500,501,116,9.0,2,0,1991-03-24 00:00:00 -20501,501,101,20.0,1,2,1991-03-24 00:00:00 -20502,501,127,0.0,34,0,1991-03-24 00:00:00 -20503,501,128,0.0,32,0,1991-03-24 00:00:00 -20504,501,140,0.0,31,0,1991-03-24 00:00:00 -20505,501,109,0.0,27,0,1991-03-24 00:00:00 -20506,501,91,0.0,16,0,1991-03-24 00:00:00 -20507,501,99,0.0,21,0,1991-03-24 00:00:00 -20508,501,139,0.0,30,0,1991-03-24 00:00:00 -20509,501,132,0.0,29,0,1991-03-24 00:00:00 -20510,501,141,0.0,33,0,1991-03-24 00:00:00 -20511,501,130,3.0,6,0,1991-03-24 00:00:00 -20512,501,137,2.0,7,0,1991-03-24 00:00:00 -20513,501,136,6.0,4,0,1991-03-24 00:00:00 -20514,501,87,1.0,9,0,1991-03-24 00:00:00 -20515,501,77,0.0,11,0,1991-03-24 00:00:00 -20516,501,93,0.0,15,0,1991-03-24 00:00:00 -20517,501,83,0.0,18,0,1991-03-24 00:00:00 -20518,501,56,0.0,14,0,1991-03-24 00:00:00 -20519,501,118,6.0,3,0,1991-03-24 00:00:00 -20520,501,89,0.0,10,0,1991-03-24 00:00:00 -20521,501,104,0.0,22,0,1991-03-24 00:00:00 -20522,501,102,0.0,25,0,1991-03-24 00:00:00 -20523,501,122,0.0,17,0,1991-03-24 00:00:00 -20524,501,76,4.0,5,0,1991-03-24 00:00:00 -20525,501,54,1.0,8,0,1991-03-24 00:00:00 -20526,501,121,0.0,24,0,1991-03-24 00:00:00 -20527,501,108,0.0,26,0,1991-03-24 00:00:00 -20528,501,138,0.0,19,0,1991-03-24 00:00:00 -20529,501,86,0.0,23,0,1991-03-24 00:00:00 -20530,501,126,0.0,28,0,1991-03-24 00:00:00 -20531,501,94,0.0,20,0,1991-03-24 00:00:00 -20532,501,80,0.0,12,0,1991-03-24 00:00:00 -20533,502,104,0.0,28,0,1991-04-28 00:00:00 -20534,502,89,0.0,15,0,1991-04-28 00:00:00 -20535,502,56,2.0,9,0,1991-04-28 00:00:00 -20536,502,101,30.0,1,3,1991-04-28 00:00:00 -20537,502,93,3.0,7,0,1991-04-28 00:00:00 -20538,502,91,0.0,21,0,1991-04-28 00:00:00 -20539,502,136,6.0,5,0,1991-04-28 00:00:00 -20540,502,137,2.0,10,0,1991-04-28 00:00:00 -20541,502,130,3.0,8,0,1991-04-28 00:00:00 -20542,502,121,0.0,29,0,1991-04-28 00:00:00 -20543,502,87,1.0,12,0,1991-04-28 00:00:00 -20544,502,77,0.0,16,0,1991-04-28 00:00:00 -20545,502,98,0.0,19,0,1991-04-28 00:00:00 -20546,502,83,0.0,23,0,1991-04-28 00:00:00 -20547,502,54,1.0,11,0,1991-04-28 00:00:00 -20548,502,116,9.0,3,0,1991-04-28 00:00:00 -20549,502,122,0.0,14,0,1991-04-28 00:00:00 -20550,502,118,6.0,4,0,1991-04-28 00:00:00 -20551,502,94,0.0,26,0,1991-04-28 00:00:00 -20552,502,119,0.0,33,0,1991-04-28 00:00:00 -20553,502,127,0.0,20,0,1991-04-28 00:00:00 -20554,502,128,0.0,34,0,1991-04-28 00:00:00 -20555,502,141,0.0,35,0,1991-04-28 00:00:00 -20556,502,76,10.0,2,0,1991-04-28 00:00:00 -20557,502,140,1.0,13,0,1991-04-28 00:00:00 -20558,502,99,0.0,22,0,1991-04-28 00:00:00 -20559,502,139,0.0,32,0,1991-04-28 00:00:00 -20560,502,132,0.0,31,0,1991-04-28 00:00:00 -20561,502,109,0.0,27,0,1991-04-28 00:00:00 -20562,502,108,4.0,6,0,1991-04-28 00:00:00 -20563,502,80,0.0,18,0,1991-04-28 00:00:00 -20564,502,138,0.0,24,0,1991-04-28 00:00:00 -20565,502,86,0.0,17,0,1991-04-28 00:00:00 -20566,502,102,0.0,30,0,1991-04-28 00:00:00 -20567,502,126,0.0,25,0,1991-04-28 00:00:00 -20568,503,54,5.0,7,0,1991-05-12 00:00:00 -20569,503,56,2.0,12,0,1991-05-12 00:00:00 -20570,503,118,6.0,4,0,1991-05-12 00:00:00 -20571,503,122,0.0,17,0,1991-05-12 00:00:00 -20572,503,121,0.0,30,0,1991-05-12 00:00:00 -20573,503,89,3.0,9,0,1991-05-12 00:00:00 -20574,503,141,0.0,35,0,1991-05-12 00:00:00 -20575,503,137,2.0,13,0,1991-05-12 00:00:00 -20576,503,83,0.0,26,0,1991-05-12 00:00:00 -20577,503,98,0.0,22,0,1991-05-12 00:00:00 -20578,503,93,3.0,10,0,1991-05-12 00:00:00 -20579,503,104,0.0,29,0,1991-05-12 00:00:00 -20580,503,91,0.0,19,0,1991-05-12 00:00:00 -20581,503,80,0.0,20,0,1991-05-12 00:00:00 -20582,503,136,6.0,6,0,1991-05-12 00:00:00 -20583,503,119,0.0,32,0,1991-05-12 00:00:00 -20584,503,127,0.0,24,0,1991-05-12 00:00:00 -20585,503,128,0.0,34,0,1991-05-12 00:00:00 -20586,503,109,0.0,28,0,1991-05-12 00:00:00 -20587,503,140,1.0,16,0,1991-05-12 00:00:00 -20588,503,99,0.0,25,0,1991-05-12 00:00:00 -20589,503,139,0.0,33,0,1991-05-12 00:00:00 -20590,503,132,0.0,31,0,1991-05-12 00:00:00 -20591,503,102,0.0,23,0,1991-05-12 00:00:00 -20592,503,108,4.0,8,0,1991-05-12 00:00:00 -20593,503,77,0.0,18,0,1991-05-12 00:00:00 -20594,503,116,11.0,2,0,1991-05-12 00:00:00 -20595,503,138,1.0,14,0,1991-05-12 00:00:00 -20596,503,86,0.0,21,0,1991-05-12 00:00:00 -20597,503,126,0.0,27,0,1991-05-12 00:00:00 -20598,503,94,6.0,5,0,1991-05-12 00:00:00 -20599,503,76,10.0,3,0,1991-05-12 00:00:00 -20600,503,101,40.0,1,4,1991-05-12 00:00:00 -20601,503,87,1.0,15,0,1991-05-12 00:00:00 -20602,503,130,3.0,11,0,1991-05-12 00:00:00 -20603,504,56,2.0,14,0,1991-06-02 00:00:00 -20604,504,118,10.0,4,0,1991-06-02 00:00:00 -20605,504,89,3.0,11,0,1991-06-02 00:00:00 -20606,504,83,0.0,27,0,1991-06-02 00:00:00 -20607,504,54,5.0,8,0,1991-06-02 00:00:00 -20608,504,122,0.0,19,0,1991-06-02 00:00:00 -20609,504,108,4.0,9,0,1991-06-02 00:00:00 -20610,504,80,0.0,22,0,1991-06-02 00:00:00 -20611,504,138,1.0,16,0,1991-06-02 00:00:00 -20612,504,86,0.0,23,0,1991-06-02 00:00:00 -20613,504,126,0.0,28,0,1991-06-02 00:00:00 -20614,504,94,7.0,7,0,1991-06-02 00:00:00 -20615,504,76,10.0,5,0,1991-06-02 00:00:00 -20616,504,121,0.0,30,0,1991-06-02 00:00:00 -20617,504,104,0.0,31,0,1991-06-02 00:00:00 -20618,504,101,40.0,1,4,1991-06-02 00:00:00 -20619,504,136,16.0,2,1,1991-06-02 00:00:00 -20620,504,141,0.0,36,0,1991-06-02 00:00:00 -20621,504,98,0.0,24,0,1991-06-02 00:00:00 -20622,504,64,0.0,34,0,1991-06-02 00:00:00 -20623,504,119,0.0,33,0,1991-06-02 00:00:00 -20624,504,127,0.0,26,0,1991-06-02 00:00:00 -20625,504,128,0.0,35,0,1991-06-02 00:00:00 -20626,504,102,0.0,25,0,1991-06-02 00:00:00 -20627,504,109,3.0,12,0,1991-06-02 00:00:00 -20628,504,140,1.0,18,0,1991-06-02 00:00:00 -20629,504,99,0.0,21,0,1991-06-02 00:00:00 -20630,504,139,0.0,29,0,1991-06-02 00:00:00 -20631,504,91,2.0,13,0,1991-06-02 00:00:00 -20632,504,93,3.0,10,0,1991-06-02 00:00:00 -20633,504,77,0.0,20,0,1991-06-02 00:00:00 -20634,504,137,2.0,15,0,1991-06-02 00:00:00 -20635,504,116,11.0,3,0,1991-06-02 00:00:00 -20636,504,130,9.0,6,0,1991-06-02 00:00:00 -20637,504,132,0.0,32,0,1991-06-02 00:00:00 -20638,504,87,1.0,17,0,1991-06-02 00:00:00 -20639,505,140,1.0,19,0,1991-06-16 00:00:00 -20640,505,89,5.0,10,0,1991-06-16 00:00:00 -20641,505,104,0.0,32,0,1991-06-16 00:00:00 -20642,505,121,0.0,31,0,1991-06-16 00:00:00 -20643,505,122,0.0,20,0,1991-06-16 00:00:00 -20644,505,76,10.0,6,0,1991-06-16 00:00:00 -20645,505,94,13.0,4,0,1991-06-16 00:00:00 -20646,505,126,0.0,29,0,1991-06-16 00:00:00 -20647,505,86,0.0,24,0,1991-06-16 00:00:00 -20648,505,99,0.0,23,0,1991-06-16 00:00:00 -20649,505,118,20.0,2,1,1991-06-16 00:00:00 -20650,505,80,0.0,21,0,1991-06-16 00:00:00 -20651,505,108,4.0,11,0,1991-06-16 00:00:00 -20652,505,102,1.0,17,0,1991-06-16 00:00:00 -20653,505,132,0.0,34,0,1991-06-16 00:00:00 -20654,505,64,0.0,27,0,1991-06-16 00:00:00 -20655,505,119,0.0,35,0,1991-06-16 00:00:00 -20656,505,127,0.0,26,0,1991-06-16 00:00:00 -20657,505,139,0.0,30,0,1991-06-16 00:00:00 -20658,505,141,0.0,36,0,1991-06-16 00:00:00 -20659,505,138,1.0,16,0,1991-06-16 00:00:00 -20660,505,128,0.0,33,0,1991-06-16 00:00:00 -20661,505,54,5.0,9,0,1991-06-16 00:00:00 -20662,505,56,2.0,14,0,1991-06-16 00:00:00 -20663,505,93,3.0,12,0,1991-06-16 00:00:00 -20664,505,83,0.0,28,0,1991-06-16 00:00:00 -20665,505,91,2.0,13,0,1991-06-16 00:00:00 -20666,505,101,44.0,1,4,1991-06-16 00:00:00 -20667,505,77,0.0,22,0,1991-06-16 00:00:00 -20668,505,136,16.0,3,1,1991-06-16 00:00:00 -20669,505,116,11.0,5,0,1991-06-16 00:00:00 -20670,505,130,9.0,7,0,1991-06-16 00:00:00 -20671,505,137,2.0,15,0,1991-06-16 00:00:00 -20672,505,87,1.0,18,0,1991-06-16 00:00:00 -20673,505,98,0.0,25,0,1991-06-16 00:00:00 -20674,505,109,6.0,8,0,1991-06-16 00:00:00 -20675,506,109,7.0,9,0,1991-07-07 00:00:00 -20676,506,128,0.0,32,0,1991-07-07 00:00:00 -20677,506,127,0.0,27,0,1991-07-07 00:00:00 -20678,506,119,0.0,35,0,1991-07-07 00:00:00 -20679,506,64,0.0,28,0,1991-07-07 00:00:00 -20680,506,136,16.0,5,1,1991-07-07 00:00:00 -20681,506,130,9.0,7,0,1991-07-07 00:00:00 -20682,506,98,0.0,26,0,1991-07-07 00:00:00 -20683,506,141,0.0,36,0,1991-07-07 00:00:00 -20684,506,116,17.0,4,0,1991-07-07 00:00:00 -20685,506,140,1.0,19,0,1991-07-07 00:00:00 -20686,506,137,2.0,15,0,1991-07-07 00:00:00 -20687,506,87,1.0,18,0,1991-07-07 00:00:00 -20688,506,77,0.0,23,0,1991-07-07 00:00:00 -20689,506,93,3.0,12,0,1991-07-07 00:00:00 -20690,506,101,48.0,1,4,1991-07-07 00:00:00 -20691,506,99,0.0,24,0,1991-07-07 00:00:00 -20692,506,139,0.0,30,0,1991-07-07 00:00:00 -20693,506,54,8.0,8,0,1991-07-07 00:00:00 -20694,506,91,2.0,13,0,1991-07-07 00:00:00 -20695,506,83,0.0,29,0,1991-07-07 00:00:00 -20696,506,56,2.0,14,0,1991-07-07 00:00:00 -20697,506,118,22.0,3,1,1991-07-07 00:00:00 -20698,506,89,5.0,10,0,1991-07-07 00:00:00 -20699,506,104,0.0,33,0,1991-07-07 00:00:00 -20700,506,122,0.0,20,0,1991-07-07 00:00:00 -20701,506,76,10.0,6,0,1991-07-07 00:00:00 -20702,506,121,0.0,31,0,1991-07-07 00:00:00 -20703,506,126,0.0,22,0,1991-07-07 00:00:00 -20704,506,86,0.0,25,0,1991-07-07 00:00:00 -20705,506,138,1.0,16,0,1991-07-07 00:00:00 -20706,506,80,0.0,21,0,1991-07-07 00:00:00 -20707,506,108,4.0,11,0,1991-07-07 00:00:00 -20708,506,102,1.0,17,0,1991-07-07 00:00:00 -20709,506,132,0.0,34,0,1991-07-07 00:00:00 -20710,506,94,23.0,2,1,1991-07-07 00:00:00 -20711,507,80,0.0,21,0,1991-07-14 00:00:00 -20712,507,119,0.0,35,0,1991-07-14 00:00:00 -20713,507,136,18.0,5,1,1991-07-14 00:00:00 -20714,507,101,51.0,1,4,1991-07-14 00:00:00 -20715,507,98,0.0,26,0,1991-07-14 00:00:00 -20716,507,116,21.0,4,0,1991-07-14 00:00:00 -20717,507,138,1.0,16,0,1991-07-14 00:00:00 -20718,507,137,2.0,14,0,1991-07-14 00:00:00 -20719,507,87,1.0,18,0,1991-07-14 00:00:00 -20720,507,77,0.0,23,0,1991-07-14 00:00:00 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-24008,632,48,10.0,4,0,1999-05-02 00:00:00 -24009,632,22,7.0,5,0,1999-05-02 00:00:00 -24010,632,20,5.0,8,0,1999-05-02 00:00:00 -24011,632,21,6.0,7,0,1999-05-02 00:00:00 -24012,632,67,0.0,13,0,1999-05-02 00:00:00 -24013,632,56,10.0,3,1,1999-05-02 00:00:00 -24014,632,36,1.0,11,0,1999-05-02 00:00:00 -24015,632,24,0.0,15,0,1999-05-02 00:00:00 -24016,632,69,0.0,19,0,1999-05-02 00:00:00 -24017,632,68,0.0,16,0,1999-05-02 00:00:00 -24018,632,62,0.0,14,0,1999-05-02 00:00:00 -24019,632,54,1.0,10,0,1999-05-02 00:00:00 -24020,632,64,0.0,18,0,1999-05-02 00:00:00 -24021,632,13,6.0,6,0,1999-05-02 00:00:00 -24022,632,43,1.0,12,0,1999-05-02 00:00:00 -24023,632,47,0.0,17,0,1999-05-02 00:00:00 -24024,632,70,3.0,9,0,1999-05-02 00:00:00 -24025,633,56,14.0,3,1,1999-05-16 00:00:00 -24026,633,48,13.0,4,0,1999-05-16 00:00:00 -24027,633,22,7.0,5,0,1999-05-16 00:00:00 -24028,633,20,7.0,6,0,1999-05-16 00:00:00 -24029,633,21,6.0,8,0,1999-05-16 00:00:00 -24030,633,36,1.0,12,0,1999-05-16 00:00:00 -24031,633,67,0.0,14,0,1999-05-16 00:00:00 -24032,633,29,26.0,1,2,1999-05-16 00:00:00 -24033,633,55,18.0,2,1,1999-05-16 00:00:00 -24034,633,43,1.0,13,0,1999-05-16 00:00:00 -24035,633,24,1.0,10,0,1999-05-16 00:00:00 -24036,633,69,0.0,17,0,1999-05-16 00:00:00 -24037,633,64,0.0,20,0,1999-05-16 00:00:00 -24038,633,68,0.0,18,0,1999-05-16 00:00:00 -24039,633,62,0.0,15,0,1999-05-16 00:00:00 -24040,633,14,0.0,16,0,1999-05-16 00:00:00 -24041,633,70,3.0,9,0,1999-05-16 00:00:00 -24042,633,13,6.0,7,0,1999-05-16 00:00:00 -24043,633,47,0.0,19,0,1999-05-16 00:00:00 -24044,633,54,1.0,11,0,1999-05-16 00:00:00 -24045,634,29,30.0,1,2,1999-05-30 00:00:00 -24046,634,55,21.0,3,1,1999-05-30 00:00:00 -24047,634,48,13.0,4,0,1999-05-30 00:00:00 -24048,634,22,9.0,6,0,1999-05-30 00:00:00 -24049,634,20,7.0,7,0,1999-05-30 00:00:00 -24050,634,21,6.0,8,0,1999-05-30 00:00:00 -24051,634,36,1.0,12,0,1999-05-30 00:00:00 -24052,634,67,0.0,15,0,1999-05-30 00:00:00 -24053,634,56,24.0,2,2,1999-05-30 00:00:00 -24054,634,14,1.0,11,0,1999-05-30 00:00:00 -24055,634,24,1.0,10,0,1999-05-30 00:00:00 -24056,634,47,0.0,19,0,1999-05-30 00:00:00 -24057,634,13,12.0,5,0,1999-05-30 00:00:00 -24058,634,70,3.0,9,0,1999-05-30 00:00:00 -24059,634,54,1.0,13,0,1999-05-30 00:00:00 -24060,634,62,0.0,16,0,1999-05-30 00:00:00 -24061,634,68,0.0,18,0,1999-05-30 00:00:00 -24062,634,64,0.0,20,0,1999-05-30 00:00:00 -24063,634,69,0.0,17,0,1999-05-30 00:00:00 -24064,634,43,1.0,14,0,1999-05-30 00:00:00 -24065,635,55,25.0,3,1,1999-06-13 00:00:00 -24066,635,29,30.0,2,2,1999-06-13 00:00:00 -24067,635,67,0.0,17,0,1999-06-13 00:00:00 -24068,635,36,1.0,14,0,1999-06-13 00:00:00 -24069,635,56,34.0,1,3,1999-06-13 00:00:00 -24070,635,20,13.0,5,0,1999-06-13 00:00:00 -24071,635,22,12.0,7,0,1999-06-13 00:00:00 -24072,635,48,13.0,4,0,1999-06-13 00:00:00 -24073,635,21,6.0,8,0,1999-06-13 00:00:00 -24074,635,43,1.0,13,0,1999-06-13 00:00:00 -24075,635,13,12.0,6,0,1999-06-13 00:00:00 -24076,635,47,0.0,19,0,1999-06-13 00:00:00 -24077,635,70,3.0,9,0,1999-06-13 00:00:00 -24078,635,54,1.0,15,0,1999-06-13 00:00:00 -24079,635,62,0.0,18,0,1999-06-13 00:00:00 -24080,635,68,0.0,20,0,1999-06-13 00:00:00 -24081,635,64,2.0,10,0,1999-06-13 00:00:00 -24082,635,69,0.0,21,0,1999-06-13 00:00:00 -24083,635,14,1.0,12,0,1999-06-13 00:00:00 -24084,635,63,1.0,16,0,1999-06-13 00:00:00 -24085,635,24,1.0,11,0,1999-06-13 00:00:00 -24086,636,43,1.0,13,0,1999-06-27 00:00:00 -24087,636,56,40.0,1,3,1999-06-27 00:00:00 -24088,636,55,26.0,3,1,1999-06-27 00:00:00 -24089,636,36,1.0,14,0,1999-06-27 00:00:00 -24090,636,22,15.0,5,0,1999-06-27 00:00:00 -24091,636,20,13.0,6,0,1999-06-27 00:00:00 -24092,636,21,10.0,8,0,1999-06-27 00:00:00 -24093,636,24,1.0,12,0,1999-06-27 00:00:00 -24094,636,48,23.0,4,1,1999-06-27 00:00:00 -24095,636,47,0.0,19,0,1999-06-27 00:00:00 -24096,636,29,32.0,2,2,1999-06-27 00:00:00 -24097,636,70,3.0,9,0,1999-06-27 00:00:00 -24098,636,64,2.0,10,0,1999-06-27 00:00:00 -24099,636,13,12.0,7,0,1999-06-27 00:00:00 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-24123,637,36,1.0,15,0,1999-07-11 00:00:00 -24124,637,21,10.0,8,0,1999-07-11 00:00:00 -24125,637,20,13.0,7,0,1999-07-11 00:00:00 -24126,637,48,26.0,4,1,1999-07-11 00:00:00 -24127,637,55,32.0,3,1,1999-07-11 00:00:00 -24128,637,54,1.0,16,0,1999-07-11 00:00:00 -24129,637,22,19.0,6,0,1999-07-11 00:00:00 -24130,638,67,0.0,18,0,1999-07-25 00:00:00 -24131,638,63,3.0,11,0,1999-07-25 00:00:00 -24132,638,40,0.0,22,0,1999-07-25 00:00:00 -24133,638,55,42.0,2,2,1999-07-25 00:00:00 -24134,638,48,29.0,4,1,1999-07-25 00:00:00 -24135,638,22,19.0,6,0,1999-07-25 00:00:00 -24136,638,20,13.0,7,0,1999-07-25 00:00:00 -24137,638,36,1.0,15,0,1999-07-25 00:00:00 -24138,638,29,32.0,3,2,1999-07-25 00:00:00 -24139,638,56,44.0,1,3,1999-07-25 00:00:00 -24140,638,43,1.0,14,0,1999-07-25 00:00:00 -24141,638,21,10.0,8,0,1999-07-25 00:00:00 -24142,638,47,0.0,19,0,1999-07-25 00:00:00 -24143,638,24,3.0,10,0,1999-07-25 00:00:00 -24144,638,69,0.0,21,0,1999-07-25 00:00:00 -24145,638,64,2.0,12,0,1999-07-25 00:00:00 -24146,638,68,0.0,20,0,1999-07-25 00:00:00 -24147,638,14,1.0,13,0,1999-07-25 00:00:00 -24148,638,54,1.0,16,0,1999-07-25 00:00:00 -24149,638,70,5.0,9,0,1999-07-25 00:00:00 -24150,638,13,28.0,5,1,1999-07-25 00:00:00 -24151,638,62,0.0,17,0,1999-07-25 00:00:00 -24152,639,43,2.0,14,0,1999-08-01 00:00:00 -24153,639,55,52.0,1,3,1999-08-01 00:00:00 -24154,639,48,33.0,3,1,1999-08-01 00:00:00 -24155,639,22,22.0,6,0,1999-08-01 00:00:00 -24156,639,20,13.0,7,0,1999-08-01 00:00:00 -24157,639,36,1.0,17,0,1999-08-01 00:00:00 -24158,639,67,0.0,18,0,1999-08-01 00:00:00 -24159,639,29,32.0,4,2,1999-08-01 00:00:00 -24160,639,56,44.0,2,3,1999-08-01 00:00:00 -24161,639,24,3.0,11,0,1999-08-01 00:00:00 -24162,639,21,10.0,8,0,1999-08-01 00:00:00 -24163,639,13,30.0,5,1,1999-08-01 00:00:00 -24164,639,63,3.0,12,0,1999-08-01 00:00:00 -24165,639,14,1.0,15,0,1999-08-01 00:00:00 -24166,639,69,0.0,21,0,1999-08-01 00:00:00 -24167,639,64,2.0,13,0,1999-08-01 00:00:00 -24168,639,47,0.0,19,0,1999-08-01 00:00:00 -24169,639,68,0.0,20,0,1999-08-01 00:00:00 -24170,639,62,6.0,9,0,1999-08-01 00:00:00 -24171,639,54,1.0,16,0,1999-08-01 00:00:00 -24172,639,70,5.0,10,0,1999-08-01 00:00:00 -24173,639,40,0.0,22,0,1999-08-01 00:00:00 -24174,640,43,2.0,14,0,1999-08-15 00:00:00 -24175,640,48,36.0,4,1,1999-08-15 00:00:00 -24176,640,22,22.0,6,0,1999-08-15 00:00:00 -24177,640,20,13.0,7,0,1999-08-15 00:00:00 -24178,640,21,12.0,8,0,1999-08-15 00:00:00 -24179,640,36,1.0,17,0,1999-08-15 00:00:00 -24180,640,67,0.0,18,0,1999-08-15 00:00:00 -24181,640,29,32.0,5,2,1999-08-15 00:00:00 -24182,640,56,54.0,2,4,1999-08-15 00:00:00 -24183,640,55,56.0,1,3,1999-08-15 00:00:00 -24184,640,24,3.0,11,0,1999-08-15 00:00:00 -24185,640,13,36.0,3,1,1999-08-15 00:00:00 -24186,640,70,6.0,10,0,1999-08-15 00:00:00 -24187,640,54,1.0,16,0,1999-08-15 00:00:00 -24188,640,62,6.0,9,0,1999-08-15 00:00:00 -24189,640,68,0.0,20,0,1999-08-15 00:00:00 -24190,640,64,2.0,13,0,1999-08-15 00:00:00 -24191,640,69,0.0,21,0,1999-08-15 00:00:00 -24192,640,14,1.0,15,0,1999-08-15 00:00:00 -24193,640,63,3.0,12,0,1999-08-15 00:00:00 -24194,640,40,0.0,22,0,1999-08-15 00:00:00 -24195,640,47,0.0,19,0,1999-08-15 00:00:00 -24196,641,29,32.0,5,2,1999-08-29 00:00:00 -24197,641,67,0.0,18,0,1999-08-29 00:00:00 -24198,641,36,1.0,17,0,1999-08-29 00:00:00 -24199,641,21,12.0,8,0,1999-08-29 00:00:00 -24200,641,55,59.0,2,3,1999-08-29 00:00:00 -24201,641,22,24.0,6,0,1999-08-29 00:00:00 -24202,641,56,60.0,1,4,1999-08-29 00:00:00 -24203,641,48,40.0,4,1,1999-08-29 00:00:00 -24204,641,20,13.0,7,0,1999-08-29 00:00:00 -24205,641,43,2.0,14,0,1999-08-29 00:00:00 -24206,641,14,1.0,15,0,1999-08-29 00:00:00 -24207,641,47,0.0,20,0,1999-08-29 00:00:00 -24208,641,24,3.0,11,0,1999-08-29 00:00:00 -24209,641,40,0.0,22,0,1999-08-29 00:00:00 -24210,641,63,3.0,12,0,1999-08-29 00:00:00 -24211,641,69,0.0,19,0,1999-08-29 00:00:00 -24212,641,64,2.0,13,0,1999-08-29 00:00:00 -24213,641,34,0.0,23,0,1999-08-29 00:00:00 -24214,641,62,6.0,10,0,1999-08-29 00:00:00 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-25480,701,34,3.0,11,0,2003-05-04 00:00:00 -25481,702,3,25.0,4,0,2003-05-18 00:00:00 -25482,702,48,7.0,11,0,2003-05-18 00:00:00 -25483,702,14,10.0,9,0,2003-05-18 00:00:00 -25484,702,13,23.0,5,1,2003-05-18 00:00:00 -25485,702,7,40.0,1,1,2003-05-18 00:00:00 -25486,702,30,15.0,7,0,2003-05-18 00:00:00 -25487,702,29,38.0,2,3,2003-05-18 00:00:00 -25488,702,34,3.0,13,0,2003-05-18 00:00:00 -25489,702,22,20.0,6,0,2003-05-18 00:00:00 -25490,702,49,0.0,19,0,2003-05-18 00:00:00 -25491,702,17,8.0,10,0,2003-05-18 00:00:00 -25492,702,41,0.0,17,0,2003-05-18 00:00:00 -25493,702,43,0.0,18,0,2003-05-18 00:00:00 -25494,702,16,4.0,12,0,2003-05-18 00:00:00 -25495,702,50,0.0,20,0,2003-05-18 00:00:00 -25496,702,42,3.0,14,0,2003-05-18 00:00:00 -25497,702,51,1.0,16,0,2003-05-18 00:00:00 -25498,702,1,1.0,15,0,2003-05-18 00:00:00 -25499,702,21,26.0,3,0,2003-05-18 00:00:00 -25500,702,20,10.0,8,1,2003-05-18 00:00:00 -25501,703,22,25.0,7,0,2003-06-01 00:00:00 -25502,703,13,25.0,6,1,2003-06-01 00:00:00 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-25526,704,13,25.0,7,1,2003-06-15 00:00:00 -25527,704,30,31.0,5,1,2003-06-15 00:00:00 -25528,704,7,51.0,2,1,2003-06-15 00:00:00 -25529,704,29,54.0,1,4,2003-06-15 00:00:00 -25530,704,14,13.0,8,0,2003-06-15 00:00:00 -25531,704,48,7.0,11,0,2003-06-15 00:00:00 -25532,704,42,3.0,13,0,2003-06-15 00:00:00 -25533,704,22,33.0,4,0,2003-06-15 00:00:00 -25534,704,34,3.0,14,0,2003-06-15 00:00:00 -25535,704,17,8.0,10,0,2003-06-15 00:00:00 -25536,704,49,0.0,19,0,2003-06-15 00:00:00 -25537,704,21,31.0,6,0,2003-06-15 00:00:00 -25538,704,1,1.0,16,0,2003-06-15 00:00:00 -25539,704,3,34.0,3,0,2003-06-15 00:00:00 -25540,704,51,1.0,17,0,2003-06-15 00:00:00 -25541,705,13,25.0,7,1,2003-06-29 00:00:00 -25542,705,7,51.0,2,1,2003-06-29 00:00:00 -25543,705,29,58.0,1,4,2003-06-29 00:00:00 -25544,705,14,13.0,8,0,2003-06-29 00:00:00 -25545,705,3,39.0,5,0,2003-06-29 00:00:00 -25546,705,22,43.0,3,1,2003-06-29 00:00:00 -25547,705,34,3.0,14,0,2003-06-29 00:00:00 -25548,705,17,10.0,10,0,2003-06-29 00:00:00 -25549,705,30,39.0,4,1,2003-06-29 00:00:00 -25550,705,21,37.0,6,0,2003-06-29 00:00:00 -25551,705,49,0.0,19,0,2003-06-29 00:00:00 -25552,705,50,0.0,20,0,2003-06-29 00:00:00 -25553,705,41,0.0,18,0,2003-06-29 00:00:00 -25554,705,43,1.0,16,0,2003-06-29 00:00:00 -25555,705,48,7.0,12,0,2003-06-29 00:00:00 -25556,705,20,10.0,9,1,2003-06-29 00:00:00 -25557,705,42,3.0,13,0,2003-06-29 00:00:00 -25558,705,51,1.0,17,0,2003-06-29 00:00:00 -25559,705,1,2.0,15,0,2003-06-29 00:00:00 -25560,705,16,9.0,11,0,2003-06-29 00:00:00 -25561,706,13,29.0,7,1,2003-07-06 00:00:00 -25562,706,30,47.0,4,1,2003-07-06 00:00:00 -25563,706,7,56.0,2,1,2003-07-06 00:00:00 -25564,706,29,64.0,1,4,2003-07-06 00:00:00 -25565,706,14,13.0,8,0,2003-07-06 00:00:00 -25566,706,48,7.0,12,0,2003-07-06 00:00:00 -25567,706,3,39.0,6,0,2003-07-06 00:00:00 -25568,706,22,53.0,3,2,2003-07-06 00:00:00 -25569,706,34,3.0,13,0,2003-07-06 00:00:00 -25570,706,17,10.0,11,0,2003-07-06 00:00:00 -25571,706,21,39.0,5,0,2003-07-06 00:00:00 -25572,706,51,1.0,17,0,2003-07-06 00:00:00 -25573,706,42,3.0,14,0,2003-07-06 00:00:00 -25574,706,20,10.0,10,1,2003-07-06 00:00:00 -25575,706,16,12.0,9,0,2003-07-06 00:00:00 -25576,706,43,2.0,15,0,2003-07-06 00:00:00 -25577,706,41,0.0,18,0,2003-07-06 00:00:00 -25578,706,50,0.0,20,0,2003-07-06 00:00:00 -25579,706,49,0.0,19,0,2003-07-06 00:00:00 -25580,706,1,2.0,16,0,2003-07-06 00:00:00 -25581,707,48,7.0,12,0,2003-07-20 00:00:00 -25582,707,3,39.0,6,0,2003-07-20 00:00:00 -25583,707,42,5.0,13,0,2003-07-20 00:00:00 -25584,707,14,16.0,8,0,2003-07-20 00:00:00 -25585,707,7,62.0,2,1,2003-07-20 00:00:00 -25586,707,30,55.0,3,1,2003-07-20 00:00:00 -25587,707,13,33.0,7,1,2003-07-20 00:00:00 -25588,707,51,1.0,17,0,2003-07-20 00:00:00 -25589,707,22,53.0,4,2,2003-07-20 00:00:00 -25590,707,34,3.0,14,0,2003-07-20 00:00:00 -25591,707,29,69.0,1,4,2003-07-20 00:00:00 -25592,707,49,0.0,19,0,2003-07-20 00:00:00 -25593,707,21,49.0,5,1,2003-07-20 00:00:00 -25594,707,20,10.0,11,1,2003-07-20 00:00:00 -25595,707,1,2.0,16,0,2003-07-20 00:00:00 -25596,707,50,0.0,20,0,2003-07-20 00:00:00 -25597,707,17,11.0,10,0,2003-07-20 00:00:00 -25598,707,41,0.0,18,0,2003-07-20 00:00:00 -25599,707,43,2.0,15,0,2003-07-20 00:00:00 -25600,707,16,12.0,9,0,2003-07-20 00:00:00 -25601,708,22,53.0,4,2,2003-08-03 00:00:00 -25602,708,3,44.0,6,0,2003-08-03 00:00:00 -25603,708,48,7.0,13,0,2003-08-03 00:00:00 -25604,708,14,22.0,8,0,2003-08-03 00:00:00 -25605,708,13,41.0,7,1,2003-08-03 00:00:00 -25606,708,7,62.0,3,1,2003-08-03 00:00:00 -25607,708,30,65.0,2,2,2003-08-03 00:00:00 -25608,708,34,3.0,15,0,2003-08-03 00:00:00 -25609,708,29,71.0,1,4,2003-08-03 00:00:00 -25610,708,17,12.0,9,0,2003-08-03 00:00:00 -25611,708,49,0.0,19,0,2003-08-03 00:00:00 -25612,708,21,49.0,5,1,2003-08-03 00:00:00 -25613,708,50,0.0,20,0,2003-08-03 00:00:00 -25614,708,41,0.0,18,0,2003-08-03 00:00:00 -25615,708,43,6.0,14,0,2003-08-03 00:00:00 -25616,708,16,12.0,10,0,2003-08-03 00:00:00 -25617,708,52,0.0,21,0,2003-08-03 00:00:00 -25618,708,42,8.0,12,0,2003-08-03 00:00:00 -25619,708,51,1.0,17,0,2003-08-03 00:00:00 -25620,708,1,2.0,16,0,2003-08-03 00:00:00 -25621,708,20,10.0,11,1,2003-08-03 00:00:00 -25622,709,34,3.0,15,0,2003-08-24 00:00:00 -25623,709,13,45.0,7,1,2003-08-24 00:00:00 -25624,709,30,71.0,2,2,2003-08-24 00:00:00 -25625,709,7,70.0,3,1,2003-08-24 00:00:00 -25626,709,29,72.0,1,4,2003-08-24 00:00:00 -25627,709,14,24.0,8,0,2003-08-24 00:00:00 -25628,709,48,7.0,13,0,2003-08-24 00:00:00 -25629,709,3,54.0,5,1,2003-08-24 00:00:00 -25630,709,22,58.0,4,2,2003-08-24 00:00:00 -25631,709,17,12.0,10,0,2003-08-24 00:00:00 -25632,709,52,0.0,21,0,2003-08-24 00:00:00 -25633,709,21,49.0,6,1,2003-08-24 00:00:00 -25634,709,1,2.0,16,0,2003-08-24 00:00:00 -25635,709,51,1.0,17,0,2003-08-24 00:00:00 -25636,709,42,8.0,12,0,2003-08-24 00:00:00 -25637,709,20,10.0,11,1,2003-08-24 00:00:00 -25638,709,16,15.0,9,0,2003-08-24 00:00:00 -25639,709,43,6.0,14,0,2003-08-24 00:00:00 -25640,709,41,0.0,18,0,2003-08-24 00:00:00 -25641,709,50,0.0,20,0,2003-08-24 00:00:00 -25642,709,49,0.0,19,0,2003-08-24 00:00:00 -25643,710,17,12.0,10,0,2003-09-14 00:00:00 -25644,710,34,6.0,15,0,2003-09-14 00:00:00 -25645,710,22,58.0,4,2,2003-09-14 00:00:00 -25646,710,3,55.0,6,1,2003-09-14 00:00:00 -25647,710,30,79.0,2,2,2003-09-14 00:00:00 -25648,710,14,24.0,8,0,2003-09-14 00:00:00 -25649,710,29,82.0,1,5,2003-09-14 00:00:00 -25650,710,13,45.0,7,1,2003-09-14 00:00:00 -25651,710,49,0.0,20,0,2003-09-14 00:00:00 -25652,710,48,7.0,13,0,2003-09-14 00:00:00 -25653,710,21,55.0,5,1,2003-09-14 00:00:00 -25654,710,7,75.0,3,1,2003-09-14 00:00:00 -25655,710,51,1.0,18,0,2003-09-14 00:00:00 -25656,710,46,0.0,22,0,2003-09-14 00:00:00 -25657,710,47,4.0,16,0,2003-09-14 00:00:00 -25658,710,52,0.0,23,0,2003-09-14 00:00:00 -25659,710,50,0.0,21,0,2003-09-14 00:00:00 -25660,710,1,2.0,17,0,2003-09-14 00:00:00 -25661,710,43,6.0,14,0,2003-09-14 00:00:00 -25662,710,16,17.0,9,0,2003-09-14 00:00:00 -25663,710,20,10.0,11,1,2003-09-14 00:00:00 -25664,710,42,8.0,12,0,2003-09-14 00:00:00 -25665,710,41,0.0,19,0,2003-09-14 00:00:00 -25666,711,17,12.0,12,0,2003-09-28 00:00:00 -25667,711,13,45.0,7,1,2003-09-28 00:00:00 -25668,711,30,82.0,3,2,2003-09-28 00:00:00 -25669,711,7,83.0,2,1,2003-09-28 00:00:00 -25670,711,29,92.0,1,6,2003-09-28 00:00:00 -25671,711,14,29.0,8,0,2003-09-28 00:00:00 -25672,711,48,13.0,10,0,2003-09-28 00:00:00 -25673,711,3,55.0,6,1,2003-09-28 00:00:00 -25674,711,22,58.0,4,2,2003-09-28 00:00:00 -25675,711,34,6.0,16,0,2003-09-28 00:00:00 -25676,711,49,0.0,21,0,2003-09-28 00:00:00 -25677,711,21,55.0,5,1,2003-09-28 00:00:00 -25678,711,1,6.0,14,0,2003-09-28 00:00:00 -25679,711,51,1.0,18,0,2003-09-28 00:00:00 -25680,711,42,8.0,13,0,2003-09-28 00:00:00 -25681,711,20,12.0,11,1,2003-09-28 00:00:00 -25682,711,16,17.0,9,0,2003-09-28 00:00:00 -25683,711,43,6.0,15,0,2003-09-28 00:00:00 -25684,711,41,0.0,20,0,2003-09-28 00:00:00 -25685,711,50,1.0,19,0,2003-09-28 00:00:00 -25686,711,52,0.0,22,0,2003-09-28 00:00:00 -25687,711,47,4.0,17,0,2003-09-28 00:00:00 -25688,711,46,0.0,23,0,2003-09-28 00:00:00 -25689,712,17,17.0,9,0,2003-10-12 00:00:00 -25690,712,34,6.0,16,0,2003-10-12 00:00:00 -25691,712,22,58.0,5,2,2003-10-12 00:00:00 -25692,712,3,55.0,6,1,2003-10-12 00:00:00 -25693,712,13,51.0,7,1,2003-10-12 00:00:00 -25694,712,30,82.0,3,2,2003-10-12 00:00:00 -25695,712,14,33.0,8,0,2003-10-12 00:00:00 -25696,712,29,93.0,1,6,2003-10-12 00:00:00 -25697,712,7,91.0,2,1,2003-10-12 00:00:00 -25698,712,49,0.0,22,0,2003-10-12 00:00:00 -25699,712,48,13.0,11,0,2003-10-12 00:00:00 -25700,712,21,65.0,4,2,2003-10-12 00:00:00 -25701,712,41,0.0,21,0,2003-10-12 00:00:00 -25702,712,51,1.0,19,0,2003-10-12 00:00:00 -25703,712,10,3.0,18,0,2003-10-12 00:00:00 -25704,712,1,6.0,14,0,2003-10-12 00:00:00 -25705,712,47,4.0,17,0,2003-10-12 00:00:00 -25706,712,52,0.0,23,0,2003-10-12 00:00:00 -25707,712,46,0.0,24,0,2003-10-12 00:00:00 -25708,712,43,6.0,15,0,2003-10-12 00:00:00 -25709,712,16,17.0,10,0,2003-10-12 00:00:00 -25710,712,20,12.0,12,1,2003-10-12 00:00:00 -25711,712,42,10.0,13,0,2003-10-12 00:00:00 -25712,712,50,1.0,20,0,2003-10-12 00:00:00 -25713,713,29,10.0,1,1,2004-03-07 00:00:00 -25714,713,21,8.0,2,0,2004-03-07 00:00:00 -25715,713,3,6.0,3,0,2004-03-07 00:00:00 -25716,713,22,5.0,4,0,2004-03-07 00:00:00 -25717,713,30,4.0,5,0,2004-03-07 00:00:00 -25718,713,17,3.0,6,0,2004-03-07 00:00:00 -25719,713,14,2.0,7,0,2004-03-07 00:00:00 -25720,713,10,0.0,9,0,2004-03-07 00:00:00 -25721,713,20,0.0,10,0,2004-03-07 00:00:00 -25722,713,31,0.0,11,0,2004-03-07 00:00:00 -25723,713,42,0.0,12,0,2004-03-07 00:00:00 -25724,713,43,0.0,13,0,2004-03-07 00:00:00 -25725,713,44,0.0,14,0,2004-03-07 00:00:00 -25726,713,13,1.0,8,0,2004-03-07 00:00:00 -25727,714,14,6.0,6,0,2004-03-21 00:00:00 -25728,714,21,13.0,2,0,2004-03-21 00:00:00 -25729,714,3,8.0,5,0,2004-03-21 00:00:00 -25730,714,29,20.0,1,2,2004-03-21 00:00:00 -25731,714,22,5.0,7,0,2004-03-21 00:00:00 -25732,714,30,12.0,3,0,2004-03-21 00:00:00 -25733,714,17,9.0,4,0,2004-03-21 00:00:00 -25734,714,13,4.0,8,0,2004-03-21 00:00:00 -25735,714,12,1.0,9,0,2004-03-21 00:00:00 -25736,714,20,0.0,12,0,2004-03-21 00:00:00 -25737,714,46,0.0,17,0,2004-03-21 00:00:00 -25738,714,45,0.0,16,0,2004-03-21 00:00:00 -25739,714,44,0.0,15,0,2004-03-21 00:00:00 -25740,714,10,0.0,11,0,2004-03-21 00:00:00 -25741,714,42,0.0,10,0,2004-03-21 00:00:00 -25742,714,31,0.0,13,0,2004-03-21 00:00:00 -25743,714,43,0.0,14,0,2004-03-21 00:00:00 -25744,715,43,0.0,13,0,2004-04-04 00:00:00 -25745,715,42,0.0,12,0,2004-04-04 00:00:00 -25746,715,31,0.0,15,0,2004-04-04 00:00:00 -25747,715,29,30.0,1,3,2004-04-04 00:00:00 -25748,715,10,4.0,8,0,2004-04-04 00:00:00 -25749,715,13,4.0,9,0,2004-04-04 00:00:00 -25750,715,14,11.0,6,0,2004-04-04 00:00:00 -25751,715,17,15.0,3,0,2004-04-04 00:00:00 -25752,715,30,12.0,4,0,2004-04-04 00:00:00 -25753,715,22,7.0,7,0,2004-04-04 00:00:00 -25754,715,3,11.0,5,0,2004-04-04 00:00:00 -25755,715,21,21.0,2,0,2004-04-04 00:00:00 -25756,715,20,0.0,14,0,2004-04-04 00:00:00 -25757,715,12,1.0,10,0,2004-04-04 00:00:00 -25758,715,44,0.0,16,0,2004-04-04 00:00:00 -25759,715,1,0.0,18,0,2004-04-04 00:00:00 -25760,715,16,1.0,11,0,2004-04-04 00:00:00 -25761,715,46,0.0,19,0,2004-04-04 00:00:00 -25762,715,45,0.0,17,0,2004-04-04 00:00:00 -25763,716,21,24.0,2,0,2004-04-25 00:00:00 -25764,716,29,40.0,1,4,2004-04-25 00:00:00 -25765,716,3,16.0,5,0,2004-04-25 00:00:00 -25766,716,22,9.0,7,0,2004-04-25 00:00:00 -25767,716,30,18.0,4,0,2004-04-25 00:00:00 -25768,716,17,23.0,3,0,2004-04-25 00:00:00 -25769,716,14,15.0,6,0,2004-04-25 00:00:00 -25770,716,13,4.0,9,0,2004-04-25 00:00:00 -25771,716,20,0.0,13,0,2004-04-25 00:00:00 -25772,716,31,0.0,16,0,2004-04-25 00:00:00 -25773,716,10,4.0,8,0,2004-04-25 00:00:00 -25774,716,43,0.0,15,0,2004-04-25 00:00:00 -25775,716,42,0.0,14,0,2004-04-25 00:00:00 -25776,716,1,0.0,20,0,2004-04-25 00:00:00 -25777,716,16,1.0,11,0,2004-04-25 00:00:00 -25778,716,46,0.0,19,0,2004-04-25 00:00:00 -25779,716,7,1.0,12,0,2004-04-25 00:00:00 -25780,716,12,1.0,10,0,2004-04-25 00:00:00 -25781,716,44,0.0,17,0,2004-04-25 00:00:00 -25782,716,45,0.0,18,0,2004-04-25 00:00:00 -25783,717,29,50.0,1,5,2004-05-09 00:00:00 -25784,717,10,8.0,8,0,2004-05-09 00:00:00 -25785,717,21,32.0,2,0,2004-05-09 00:00:00 -25786,717,3,21.0,4,0,2004-05-09 00:00:00 -25787,717,22,12.0,7,0,2004-05-09 00:00:00 -25788,717,30,18.0,6,0,2004-05-09 00:00:00 -25789,717,17,24.0,3,0,2004-05-09 00:00:00 -25790,717,14,21.0,5,0,2004-05-09 00:00:00 -25791,717,13,4.0,9,0,2004-05-09 00:00:00 -25792,717,20,2.0,10,0,2004-05-09 00:00:00 -25793,717,1,0.0,20,0,2004-05-09 00:00:00 -25794,717,42,0.0,14,0,2004-05-09 00:00:00 -25795,717,43,0.0,15,0,2004-05-09 00:00:00 -25796,717,44,0.0,17,0,2004-05-09 00:00:00 -25797,717,12,1.0,11,0,2004-05-09 00:00:00 -25798,717,45,0.0,18,0,2004-05-09 00:00:00 -25799,717,46,0.0,19,0,2004-05-09 00:00:00 -25800,717,16,1.0,13,0,2004-05-09 00:00:00 -25801,717,7,1.0,12,0,2004-05-09 00:00:00 -25802,717,31,0.0,16,0,2004-05-09 00:00:00 -25803,718,14,31.0,4,1,2004-05-23 00:00:00 -25804,718,30,23.0,5,0,2004-05-23 00:00:00 -25805,718,17,32.0,3,0,2004-05-23 00:00:00 -25806,718,22,12.0,7,0,2004-05-23 00:00:00 -25807,718,10,8.0,8,0,2004-05-23 00:00:00 -25808,718,21,38.0,2,0,2004-05-23 00:00:00 -25809,718,29,50.0,1,5,2004-05-23 00:00:00 -25810,718,13,4.0,10,0,2004-05-23 00:00:00 -25811,718,3,21.0,6,0,2004-05-23 00:00:00 -25812,718,20,2.0,12,0,2004-05-23 00:00:00 -25813,718,42,3.0,11,0,2004-05-23 00:00:00 -25814,718,7,1.0,15,0,2004-05-23 00:00:00 -25815,718,43,1.0,14,0,2004-05-23 00:00:00 -25816,718,44,0.0,19,0,2004-05-23 00:00:00 -25817,718,12,5.0,9,0,2004-05-23 00:00:00 -25818,718,45,0.0,20,0,2004-05-23 00:00:00 -25819,718,46,0.0,17,0,2004-05-23 00:00:00 -25820,718,16,1.0,16,0,2004-05-23 00:00:00 -25821,718,1,2.0,13,0,2004-05-23 00:00:00 -25822,718,31,0.0,18,0,2004-05-23 00:00:00 -25823,719,10,8.0,8,0,2004-05-30 00:00:00 -25824,719,13,4.0,11,0,2004-05-30 00:00:00 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-25848,720,10,8.0,9,0,2004-06-13 00:00:00 -25849,720,20,10.0,8,0,2004-06-13 00:00:00 -25850,720,22,12.0,7,0,2004-06-13 00:00:00 -25851,720,42,3.0,13,0,2004-06-13 00:00:00 -25852,720,46,0.0,19,0,2004-06-13 00:00:00 -25853,720,44,0.0,20,0,2004-06-13 00:00:00 -25854,720,12,5.0,11,0,2004-06-13 00:00:00 -25855,720,45,0.0,21,0,2004-06-13 00:00:00 -25856,720,16,3.0,15,0,2004-06-13 00:00:00 -25857,720,1,3.0,14,0,2004-06-13 00:00:00 -25858,720,7,5.0,12,0,2004-06-13 00:00:00 -25859,720,9,2.0,16,0,2004-06-13 00:00:00 -25860,720,29,70.0,1,7,2004-06-13 00:00:00 -25861,720,3,25.0,5,0,2004-06-13 00:00:00 -25862,720,43,1.0,17,0,2004-06-13 00:00:00 -25863,720,21,54.0,2,0,2004-06-13 00:00:00 -25864,721,45,0.0,21,0,2004-06-20 00:00:00 -25865,721,12,5.0,12,0,2004-06-20 00:00:00 -25866,721,16,3.0,16,0,2004-06-20 00:00:00 -25867,721,46,1.0,18,0,2004-06-20 00:00:00 -25868,721,7,8.0,11,0,2004-06-20 00:00:00 -25869,721,9,2.0,17,0,2004-06-20 00:00:00 -25870,721,44,0.0,20,0,2004-06-20 00:00:00 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-25986,726,1,3.0,18,0,2004-08-29 00:00:00 -25987,726,13,21.0,8,0,2004-08-29 00:00:00 -25988,726,46,1.0,20,0,2004-08-29 00:00:00 -25989,726,16,7.0,13,0,2004-08-29 00:00:00 -25990,726,7,28.0,7,1,2004-08-29 00:00:00 -25991,726,9,2.0,19,0,2004-08-29 00:00:00 -25992,726,47,0.0,21,0,2004-08-29 00:00:00 -25993,726,41,4.0,15,0,2004-08-29 00:00:00 -25994,726,40,0.0,22,0,2004-08-29 00:00:00 -25995,726,10,18.0,9,0,2004-08-29 00:00:00 -25996,726,20,18.0,10,0,2004-08-29 00:00:00 -25997,726,14,46.0,4,1,2004-08-29 00:00:00 -25998,726,31,3.0,16,0,2004-08-29 00:00:00 -25999,727,7,28.0,7,1,2004-09-12 00:00:00 -26000,727,41,6.0,15,0,2004-09-12 00:00:00 -26001,727,29,136.0,1,12,2004-09-12 00:00:00 -26002,727,21,98.0,2,1,2004-09-12 00:00:00 -26003,727,3,45.0,5,0,2004-09-12 00:00:00 -26004,727,22,12.0,11,0,2004-09-12 00:00:00 -26005,727,30,42.0,6,0,2004-09-12 00:00:00 -26006,727,14,46.0,4,1,2004-09-12 00:00:00 -26007,727,13,24.0,8,0,2004-09-12 00:00:00 -26008,727,10,23.0,9,0,2004-09-12 00:00:00 -26009,727,20,19.0,10,0,2004-09-12 00:00:00 -26010,727,31,3.0,16,0,2004-09-12 00:00:00 -26011,727,17,71.0,3,0,2004-09-12 00:00:00 -26012,727,43,6.0,14,0,2004-09-12 00:00:00 -26013,727,42,3.0,17,0,2004-09-12 00:00:00 -26014,727,47,0.0,22,0,2004-09-12 00:00:00 -26015,727,9,2.0,19,0,2004-09-12 00:00:00 -26016,727,1,3.0,18,0,2004-09-12 00:00:00 -26017,727,16,7.0,13,0,2004-09-12 00:00:00 -26018,727,40,0.0,21,0,2004-09-12 00:00:00 -26019,727,46,1.0,20,0,2004-09-12 00:00:00 -26020,727,45,0.0,24,0,2004-09-12 00:00:00 -26021,727,12,10.0,12,0,2004-09-12 00:00:00 -26022,727,44,0.0,23,0,2004-09-12 00:00:00 -26023,728,43,6.0,14,0,2004-09-26 00:00:00 -26024,728,42,3.0,17,0,2004-09-26 00:00:00 -26025,728,31,3.0,16,0,2004-09-26 00:00:00 -26026,728,20,21.0,10,0,2004-09-26 00:00:00 -26027,728,10,26.0,8,0,2004-09-26 00:00:00 -26028,728,17,79.0,3,0,2004-09-26 00:00:00 -26029,728,44,0.0,24,0,2004-09-26 00:00:00 -26030,728,30,46.0,6,0,2004-09-26 00:00:00 -26031,728,22,12.0,11,0,2004-09-26 00:00:00 -26032,728,3,50.0,4,0,2004-09-26 00:00:00 -26033,728,29,136.0,1,12,2004-09-26 00:00:00 -26034,728,13,24.0,9,0,2004-09-26 00:00:00 -26035,728,21,108.0,2,2,2004-09-26 00:00:00 -26036,728,14,46.0,5,1,2004-09-26 00:00:00 -26037,728,34,0.0,23,0,2004-09-26 00:00:00 -26038,728,47,0.0,22,0,2004-09-26 00:00:00 -26039,728,9,2.0,19,0,2004-09-26 00:00:00 -26040,728,7,34.0,7,1,2004-09-26 00:00:00 -26041,728,1,3.0,18,0,2004-09-26 00:00:00 -26042,728,16,7.0,13,0,2004-09-26 00:00:00 -26043,728,46,1.0,20,0,2004-09-26 00:00:00 -26044,728,45,0.0,25,0,2004-09-26 00:00:00 -26045,728,12,11.0,12,0,2004-09-26 00:00:00 -26046,728,41,6.0,15,0,2004-09-26 00:00:00 -26047,728,40,0.0,21,0,2004-09-26 00:00:00 -26048,729,31,3.0,16,0,2004-10-10 00:00:00 -26049,729,29,146.0,1,13,2004-10-10 00:00:00 -26050,729,21,108.0,2,2,2004-10-10 00:00:00 -26051,729,34,0.0,21,0,2004-10-10 00:00:00 -26052,729,3,54.0,4,0,2004-10-10 00:00:00 -26053,729,22,20.0,11,0,2004-10-10 00:00:00 -26054,729,30,48.0,5,0,2004-10-10 00:00:00 -26055,729,17,85.0,3,0,2004-10-10 00:00:00 -26056,729,14,46.0,6,1,2004-10-10 00:00:00 -26057,729,13,24.0,9,0,2004-10-10 00:00:00 -26058,729,40,0.0,22,0,2004-10-10 00:00:00 -26059,729,41,6.0,15,0,2004-10-10 00:00:00 -26060,729,47,0.0,23,0,2004-10-10 00:00:00 -26061,729,9,2.0,19,0,2004-10-10 00:00:00 -26062,729,7,37.0,7,1,2004-10-10 00:00:00 -26063,729,1,3.0,18,0,2004-10-10 00:00:00 -26064,729,10,31.0,8,0,2004-10-10 00:00:00 -26065,729,46,1.0,20,0,2004-10-10 00:00:00 -26066,729,45,0.0,25,0,2004-10-10 00:00:00 -26067,729,12,11.0,12,0,2004-10-10 00:00:00 -26068,729,43,6.0,14,0,2004-10-10 00:00:00 -26069,729,42,3.0,17,0,2004-10-10 00:00:00 -26070,729,20,22.0,10,0,2004-10-10 00:00:00 -26071,729,16,7.0,13,0,2004-10-10 00:00:00 -26072,729,44,0.0,24,0,2004-10-10 00:00:00 -26073,730,29,148.0,1,13,2004-10-24 00:00:00 -26074,730,1,3.0,18,0,2004-10-24 00:00:00 -26075,730,7,45.0,7,1,2004-10-24 00:00:00 -26076,730,9,2.0,19,0,2004-10-24 00:00:00 -26077,730,47,0.0,23,0,2004-10-24 00:00:00 -26078,730,41,6.0,15,0,2004-10-24 00:00:00 -26079,730,40,0.0,22,0,2004-10-24 00:00:00 -26080,730,34,0.0,21,0,2004-10-24 00:00:00 -26081,730,16,7.0,13,0,2004-10-24 00:00:00 -26082,730,21,114.0,2,2,2004-10-24 00:00:00 -26083,730,3,59.0,4,0,2004-10-24 00:00:00 -26084,730,22,24.0,9,0,2004-10-24 00:00:00 -26085,730,46,1.0,20,0,2004-10-24 00:00:00 -26086,730,30,58.0,5,1,2004-10-24 00:00:00 -26087,730,17,85.0,3,0,2004-10-24 00:00:00 -26088,730,14,46.0,6,1,2004-10-24 00:00:00 -26089,730,12,12.0,12,0,2004-10-24 00:00:00 -26090,730,13,24.0,10,0,2004-10-24 00:00:00 -26091,730,44,0.0,24,0,2004-10-24 00:00:00 -26092,730,43,6.0,14,0,2004-10-24 00:00:00 -26093,730,42,3.0,17,0,2004-10-24 00:00:00 -26094,730,31,3.0,16,0,2004-10-24 00:00:00 -26095,730,20,22.0,11,0,2004-10-24 00:00:00 -26096,730,45,0.0,25,0,2004-10-24 00:00:00 -26097,730,10,34.0,8,0,2004-10-24 00:00:00 -26098,731,17,0.0,16,0,2005-03-06 14:00:00 -26099,731,12,0.0,10,0,2005-03-06 14:00:00 -26100,731,22,0.0,11,0,2005-03-06 14:00:00 -26101,731,34,0.0,12,0,2005-03-06 14:00:00 -26102,731,10,0.0,17,0,2005-03-06 14:00:00 -26103,731,38,0.0,13,0,2005-03-06 14:00:00 -26104,731,30,3.0,6,0,2005-03-06 14:00:00 -26105,731,13,5.0,4,0,2005-03-06 14:00:00 -26106,731,14,0.0,9,0,2005-03-06 14:00:00 -26107,731,16,4.0,5,0,2005-03-06 14:00:00 -26108,731,31,2.0,7,0,2005-03-06 14:00:00 -26109,731,7,1.0,8,0,2005-03-06 14:00:00 -26110,731,3,6.0,3,0,2005-03-06 14:00:00 -26111,731,21,8.0,2,0,2005-03-06 14:00:00 -26112,731,20,10.0,1,1,2005-03-06 14:00:00 -26113,731,32,0.0,14,0,2005-03-06 14:00:00 -26114,731,39,0.0,15,0,2005-03-06 14:00:00 -26115,731,29,0.0,18,0,2005-03-06 14:00:00 -26116,731,1,0.0,19,0,2005-03-06 14:00:00 -26117,731,26,0.0,20,0,2005-03-06 14:00:00 -26118,732,16,4.0,9,0,2005-03-20 15:00:00 -26119,732,21,8.0,4,0,2005-03-20 15:00:00 -26120,732,31,3.0,10,0,2005-03-20 15:00:00 -26121,732,7,1.0,12,0,2005-03-20 15:00:00 -26122,732,14,8.0,3,0,2005-03-20 15:00:00 -26123,732,12,0.0,13,0,2005-03-20 15:00:00 -26124,732,17,0.0,19,0,2005-03-20 15:00:00 -26125,732,32,0.0,15,0,2005-03-20 15:00:00 -26126,732,34,0.0,16,0,2005-03-20 15:00:00 -26127,732,10,0.0,20,0,2005-03-20 15:00:00 -26128,732,38,0.0,14,0,2005-03-20 15:00:00 -26129,732,3,16.0,1,1,2005-03-20 15:00:00 -26130,732,39,0.0,18,0,2005-03-20 15:00:00 -26131,732,29,2.0,11,0,2005-03-20 15:00:00 -26132,732,20,10.0,2,1,2005-03-20 15:00:00 -26133,732,22,4.0,8,0,2005-03-20 15:00:00 -26134,732,13,8.0,5,0,2005-03-20 15:00:00 -26135,732,30,8.0,6,0,2005-03-20 15:00:00 -26136,732,1,6.0,7,0,2005-03-20 15:00:00 -26137,732,26,0.0,17,0,2005-03-20 15:00:00 -26138,732,18,0.0,21,0,2005-03-20 15:00:00 -26139,733,12,2.0,13,0,2005-04-03 14:30:00 -26140,733,39,0.0,18,0,2005-04-03 14:30:00 -26141,733,32,0.0,15,0,2005-04-03 14:30:00 -26142,733,38,0.0,17,0,2005-04-03 14:30:00 -26143,733,10,0.0,21,0,2005-04-03 14:30:00 -26144,733,34,0.0,16,0,2005-04-03 14:30:00 -26145,733,22,9.0,4,0,2005-04-03 14:30:00 -26146,733,17,0.0,20,0,2005-04-03 14:30:00 -26147,733,7,7.0,8,0,2005-04-03 14:30:00 -26148,733,29,2.0,14,0,2005-04-03 14:30:00 -26149,733,31,3.0,12,0,2005-04-03 14:30:00 -26150,733,30,8.0,7,0,2005-04-03 14:30:00 -26151,733,16,7.0,9,0,2005-04-03 14:30:00 -26152,733,13,9.0,5,0,2005-04-03 14:30:00 -26153,733,3,26.0,1,2,2005-04-03 14:30:00 -26154,733,14,16.0,2,0,2005-04-03 14:30:00 -26155,733,1,6.0,10,0,2005-04-03 14:30:00 -26156,733,20,10.0,3,1,2005-04-03 14:30:00 -26157,733,26,0.0,19,0,2005-04-03 14:30:00 -26158,733,18,0.0,22,0,2005-04-03 14:30:00 -26159,733,36,4.0,11,0,2005-04-03 14:30:00 -26160,733,21,8.0,6,0,2005-04-03 14:30:00 -26161,734,29,10.0,4,0,2005-04-24 14:00:00 -26162,734,13,9.0,7,0,2005-04-24 14:00:00 -26163,734,16,9.0,8,0,2005-04-24 14:00:00 -26164,734,30,8.0,10,0,2005-04-24 14:00:00 -26165,734,31,3.0,15,0,2005-04-24 14:00:00 -26166,734,18,0.0,24,0,2005-04-24 14:00:00 -26167,734,7,7.0,11,0,2005-04-24 14:00:00 -26168,734,12,2.0,16,0,2005-04-24 14:00:00 -26169,734,17,0.0,22,0,2005-04-24 14:00:00 -26170,734,22,9.0,6,0,2005-04-24 14:00:00 -26171,734,34,5.0,13,0,2005-04-24 14:00:00 -26172,734,10,0.0,23,0,2005-04-24 14:00:00 -26173,734,38,0.0,19,0,2005-04-24 14:00:00 -26174,734,32,0.0,18,0,2005-04-24 14:00:00 -26175,734,1,9.0,5,0,2005-04-24 14:00:00 -26176,734,14,20.0,2,0,2005-04-24 14:00:00 -26177,734,39,0.0,20,0,2005-04-24 14:00:00 -26178,734,26,0.0,21,0,2005-04-24 14:00:00 -26179,734,23,1.0,17,0,2005-04-24 14:00:00 -26180,734,3,36.0,1,3,2005-04-24 14:00:00 -26181,734,21,8.0,9,0,2005-04-24 14:00:00 -26182,734,20,10.0,3,1,2005-04-24 14:00:00 -26183,734,36,4.0,14,0,2005-04-24 14:00:00 -26184,734,24,6.0,12,0,2005-04-24 14:00:00 -26185,735,39,0.0,20,0,2005-05-08 14:00:00 -26186,735,32,0.0,18,0,2005-05-08 14:00:00 -26187,735,38,0.0,19,0,2005-05-08 14:00:00 -26188,735,13,10.0,9,0,2005-05-08 14:00:00 -26189,735,10,0.0,23,0,2005-05-08 14:00:00 -26190,735,16,12.0,6,0,2005-05-08 14:00:00 -26191,735,30,10.0,8,0,2005-05-08 14:00:00 -26192,735,31,3.0,15,0,2005-05-08 14:00:00 -26193,735,7,17.0,3,1,2005-05-08 14:00:00 -26194,735,14,26.0,2,0,2005-05-08 14:00:00 -26195,735,12,2.0,16,0,2005-05-08 14:00:00 -26196,735,17,0.0,22,0,2005-05-08 14:00:00 -26197,735,22,14.0,5,0,2005-05-08 14:00:00 -26198,735,34,5.0,13,0,2005-05-08 14:00:00 -26199,735,29,10.0,7,0,2005-05-08 14:00:00 -26200,735,1,9.0,10,0,2005-05-08 14:00:00 -26201,735,21,8.0,11,0,2005-05-08 14:00:00 -26202,735,18,0.0,24,0,2005-05-08 14:00:00 -26203,735,36,4.0,14,0,2005-05-08 14:00:00 -26204,735,24,6.0,12,0,2005-05-08 14:00:00 -26205,735,23,1.0,17,0,2005-05-08 14:00:00 -26206,735,3,44.0,1,3,2005-05-08 14:00:00 -26207,735,20,14.0,4,1,2005-05-08 14:00:00 -26208,735,26,0.0,21,0,2005-05-08 14:00:00 -26209,736,34,5.0,13,0,2005-05-22 14:00:00 -26210,736,22,17.0,6,0,2005-05-22 14:00:00 -26211,736,17,0.0,22,0,2005-05-22 14:00:00 -26212,736,12,2.0,16,0,2005-05-22 14:00:00 -26213,736,20,14.0,7,1,2005-05-22 14:00:00 -26214,736,13,10.0,10,0,2005-05-22 14:00:00 -26215,736,3,49.0,1,3,2005-05-22 14:00:00 -26216,736,16,18.0,4,0,2005-05-22 14:00:00 -26217,736,30,14.0,8,0,2005-05-22 14:00:00 -26218,736,31,3.0,15,0,2005-05-22 14:00:00 -26219,736,7,27.0,2,2,2005-05-22 14:00:00 -26220,736,14,26.0,3,0,2005-05-22 14:00:00 -26221,736,21,9.0,11,0,2005-05-22 14:00:00 -26222,736,10,0.0,23,0,2005-05-22 14:00:00 -26223,736,39,0.0,20,0,2005-05-22 14:00:00 -26224,736,32,0.0,18,0,2005-05-22 14:00:00 -26225,736,36,4.0,14,0,2005-05-22 14:00:00 -26226,736,24,6.0,12,0,2005-05-22 14:00:00 -26227,736,38,0.0,19,0,2005-05-22 14:00:00 -26228,736,23,1.0,17,0,2005-05-22 14:00:00 -26229,736,26,0.0,21,0,2005-05-22 14:00:00 -26230,736,18,0.0,24,0,2005-05-22 14:00:00 -26231,736,1,17.0,5,0,2005-05-22 14:00:00 -26232,736,29,12.0,9,0,2005-05-22 14:00:00 -26233,737,13,15.0,11,0,2005-05-29 14:00:00 -26234,737,16,18.0,5,0,2005-05-29 14:00:00 -26235,737,34,5.0,13,0,2005-05-29 14:00:00 -26236,737,21,15.0,10,0,2005-05-29 14:00:00 -26237,737,20,17.0,6,1,2005-05-29 14:00:00 -26238,737,30,16.0,9,0,2005-05-29 14:00:00 -26239,737,31,3.0,15,0,2005-05-29 14:00:00 -26240,737,7,27.0,2,2,2005-05-29 14:00:00 -26241,737,14,27.0,3,0,2005-05-29 14:00:00 -26242,737,12,2.0,16,0,2005-05-29 14:00:00 -26243,737,17,0.0,19,0,2005-05-29 14:00:00 -26244,737,22,17.0,7,0,2005-05-29 14:00:00 -26245,737,3,59.0,1,4,2005-05-29 14:00:00 -26246,737,10,0.0,22,0,2005-05-29 14:00:00 -26247,737,38,0.0,20,0,2005-05-29 14:00:00 -26248,737,32,0.0,18,0,2005-05-29 14:00:00 -26249,737,39,0.0,21,0,2005-05-29 14:00:00 -26250,737,29,16.0,8,0,2005-05-29 14:00:00 -26251,737,1,25.0,4,0,2005-05-29 14:00:00 -26252,737,26,0.0,23,0,2005-05-29 14:00:00 -26253,737,18,0.0,24,0,2005-05-29 14:00:00 -26254,737,36,4.0,14,0,2005-05-29 14:00:00 -26255,737,24,6.0,12,0,2005-05-29 14:00:00 -26256,737,23,1.0,17,0,2005-05-29 14:00:00 -26257,738,22,20.0,8,0,2005-06-12 13:00:00 -26258,738,17,0.0,19,0,2005-06-12 13:00:00 -26259,738,30,16.0,11,0,2005-06-12 13:00:00 -26260,738,12,7.0,12,0,2005-06-12 13:00:00 -26261,738,14,27.0,3,0,2005-06-12 13:00:00 -26262,738,3,59.0,1,4,2005-06-12 13:00:00 -26263,738,20,17.0,9,1,2005-06-12 13:00:00 -26264,738,16,22.0,6,0,2005-06-12 13:00:00 -26265,738,13,17.0,10,0,2005-06-12 13:00:00 -26266,738,34,5.0,14,0,2005-06-12 13:00:00 -26267,738,21,21.0,7,0,2005-06-12 13:00:00 -26268,738,31,4.0,16,0,2005-06-12 13:00:00 -26269,738,10,0.0,23,0,2005-06-12 13:00:00 -26270,738,1,25.0,4,0,2005-06-12 13:00:00 -26271,738,32,0.0,18,0,2005-06-12 13:00:00 -26272,738,23,1.0,17,0,2005-06-12 13:00:00 -26273,738,24,6.0,13,0,2005-06-12 13:00:00 -26274,738,38,0.0,20,0,2005-06-12 13:00:00 -26275,738,36,4.0,15,0,2005-06-12 13:00:00 -26276,738,7,37.0,2,3,2005-06-12 13:00:00 -26277,738,39,0.0,22,0,2005-06-12 13:00:00 -26278,738,29,24.0,5,0,2005-06-12 13:00:00 -26279,738,26,0.0,21,0,2005-06-12 13:00:00 -26280,738,18,0.0,24,0,2005-06-12 13:00:00 -26281,739,20,17.0,9,1,2005-06-19 14:00:00 -26282,739,40,0.0,24,0,2005-06-19 14:00:00 -26283,739,23,1.0,21,0,2005-06-19 14:00:00 -26284,739,24,6.0,14,0,2005-06-19 14:00:00 -26285,739,36,4.0,18,0,2005-06-19 14:00:00 -26286,739,18,0.0,25,0,2005-06-19 14:00:00 -26287,739,26,4.0,17,0,2005-06-19 14:00:00 -26288,739,1,25.0,6,0,2005-06-19 14:00:00 -26289,739,29,34.0,3,1,2005-06-19 14:00:00 -26290,739,39,3.0,20,0,2005-06-19 14:00:00 -26291,739,32,6.0,13,0,2005-06-19 14:00:00 -26292,739,10,0.0,23,0,2005-06-19 14:00:00 -26293,739,22,20.0,8,0,2005-06-19 14:00:00 -26294,739,17,0.0,22,0,2005-06-19 14:00:00 -26295,739,12,7.0,12,0,2005-06-19 14:00:00 -26296,739,14,27.0,5,0,2005-06-19 14:00:00 -26297,739,7,37.0,2,3,2005-06-19 14:00:00 -26298,739,31,4.0,19,0,2005-06-19 14:00:00 -26299,739,30,16.0,11,0,2005-06-19 14:00:00 -26300,739,16,22.0,7,0,2005-06-19 14:00:00 -26301,739,13,17.0,10,0,2005-06-19 14:00:00 -26302,739,3,59.0,1,4,2005-06-19 14:00:00 -26303,739,21,29.0,4,0,2005-06-19 14:00:00 -26304,739,38,5.0,16,0,2005-06-19 14:00:00 -26305,739,34,5.0,15,0,2005-06-19 14:00:00 -26306,740,23,1.0,22,0,2005-07-03 14:00:00 -26307,740,40,0.0,24,0,2005-07-03 14:00:00 -26308,740,24,6.0,14,0,2005-07-03 14:00:00 -26309,740,18,0.0,25,0,2005-07-03 14:00:00 -26310,740,20,20.0,9,1,2005-07-03 14:00:00 -26311,740,21,29.0,5,0,2005-07-03 14:00:00 -26312,740,3,69.0,1,5,2005-07-03 14:00:00 -26313,740,13,17.0,10,0,2005-07-03 14:00:00 -26314,740,16,22.0,7,0,2005-07-03 14:00:00 -26315,740,30,16.0,11,0,2005-07-03 14:00:00 -26316,740,31,4.0,20,0,2005-07-03 14:00:00 -26317,740,7,45.0,2,3,2005-07-03 14:00:00 -26318,740,14,31.0,4,0,2005-07-03 14:00:00 -26319,740,12,7.0,12,0,2005-07-03 14:00:00 -26320,740,36,4.0,19,0,2005-07-03 14:00:00 -26321,740,22,22.0,8,0,2005-07-03 14:00:00 -26322,740,34,6.0,15,0,2005-07-03 14:00:00 -26323,740,10,0.0,23,0,2005-07-03 14:00:00 -26324,740,38,5.0,17,0,2005-07-03 14:00:00 -26325,740,32,6.0,13,0,2005-07-03 14:00:00 -26326,740,39,3.0,21,0,2005-07-03 14:00:00 -26327,740,29,40.0,3,1,2005-07-03 14:00:00 -26328,740,1,25.0,6,0,2005-07-03 14:00:00 -26329,740,26,4.0,18,0,2005-07-03 14:00:00 -26330,740,17,5.0,16,0,2005-07-03 14:00:00 -26331,741,31,4.0,20,0,2005-07-10 14:00:00 -26332,741,30,26.0,6,1,2005-07-10 14:00:00 -26333,741,16,22.0,10,0,2005-07-10 14:00:00 -26334,741,13,17.0,11,0,2005-07-10 14:00:00 -26335,741,40,0.0,24,0,2005-07-10 14:00:00 -26336,741,21,31.0,4,0,2005-07-10 14:00:00 -26337,741,20,25.0,7,1,2005-07-10 14:00:00 -26338,741,7,51.0,2,3,2005-07-10 14:00:00 -26339,741,23,1.0,22,0,2005-07-10 14:00:00 -26340,741,3,77.0,1,5,2005-07-10 14:00:00 -26341,741,14,31.0,5,0,2005-07-10 14:00:00 -26342,741,12,7.0,13,0,2005-07-10 14:00:00 -26343,741,1,25.0,8,0,2005-07-10 14:00:00 -26344,741,22,23.0,9,0,2005-07-10 14:00:00 -26345,741,34,6.0,16,0,2005-07-10 14:00:00 -26346,741,10,0.0,23,0,2005-07-10 14:00:00 -26347,741,38,5.0,17,0,2005-07-10 14:00:00 -26348,741,32,6.0,14,0,2005-07-10 14:00:00 -26349,741,39,3.0,21,0,2005-07-10 14:00:00 -26350,741,29,43.0,3,1,2005-07-10 14:00:00 -26351,741,26,4.0,18,0,2005-07-10 14:00:00 -26352,741,18,0.0,25,0,2005-07-10 14:00:00 -26353,741,17,9.0,12,0,2005-07-10 14:00:00 -26354,741,24,6.0,15,0,2005-07-10 14:00:00 -26355,741,36,4.0,19,0,2005-07-10 14:00:00 -26356,742,30,34.0,4,1,2005-07-24 14:00:00 -26357,742,7,51.0,2,3,2005-07-24 14:00:00 -26358,742,16,22.0,10,0,2005-07-24 14:00:00 -26359,742,31,4.0,20,0,2005-07-24 14:00:00 -26360,742,13,19.0,11,0,2005-07-24 14:00:00 -26361,742,37,0.0,24,0,2005-07-24 14:00:00 -26362,742,21,31.0,5,0,2005-07-24 14:00:00 -26363,742,20,30.0,7,1,2005-07-24 14:00:00 -26364,742,40,0.0,25,0,2005-07-24 14:00:00 -26365,742,3,87.0,1,6,2005-07-24 14:00:00 -26366,742,14,31.0,6,0,2005-07-24 14:00:00 -26367,742,36,4.0,19,0,2005-07-24 14:00:00 -26368,742,17,15.0,12,0,2005-07-24 14:00:00 -26369,742,24,6.0,15,0,2005-07-24 14:00:00 -26370,742,12,8.0,13,0,2005-07-24 14:00:00 -26371,742,18,0.0,26,0,2005-07-24 14:00:00 -26372,742,26,4.0,18,0,2005-07-24 14:00:00 -26373,742,29,47.0,3,1,2005-07-24 14:00:00 -26374,742,1,25.0,9,0,2005-07-24 14:00:00 -26375,742,32,6.0,14,0,2005-07-24 14:00:00 -26376,742,38,5.0,17,0,2005-07-24 14:00:00 -26377,742,10,0.0,23,0,2005-07-24 14:00:00 -26378,742,34,6.0,16,0,2005-07-24 14:00:00 -26379,742,22,26.0,8,0,2005-07-24 14:00:00 -26380,742,39,3.0,21,0,2005-07-24 14:00:00 -26381,742,23,1.0,22,0,2005-07-24 14:00:00 -26382,743,13,19.0,12,0,2005-07-31 14:00:00 -26383,743,30,34.0,5,1,2005-07-31 14:00:00 -26384,743,16,24.0,10,0,2005-07-31 14:00:00 -26385,743,31,4.0,20,0,2005-07-31 14:00:00 -26386,743,20,30.0,8,1,2005-07-31 14:00:00 -26387,743,37,0.0,24,0,2005-07-31 14:00:00 -26388,743,40,0.0,25,0,2005-07-31 14:00:00 -26389,743,3,87.0,1,6,2005-07-31 14:00:00 -26390,743,14,36.0,4,0,2005-07-31 14:00:00 -26391,743,21,31.0,7,0,2005-07-31 14:00:00 -26392,743,17,19.0,11,0,2005-07-31 14:00:00 -26393,743,23,1.0,22,0,2005-07-31 14:00:00 -26394,743,24,6.0,15,0,2005-07-31 14:00:00 -26395,743,36,4.0,19,0,2005-07-31 14:00:00 -26396,743,18,0.0,26,0,2005-07-31 14:00:00 -26397,743,26,4.0,18,0,2005-07-31 14:00:00 -26398,743,1,28.0,9,0,2005-07-31 14:00:00 -26399,743,12,8.0,13,0,2005-07-31 14:00:00 -26400,743,7,61.0,2,4,2005-07-31 14:00:00 -26401,743,29,55.0,3,1,2005-07-31 14:00:00 -26402,743,39,3.0,21,0,2005-07-31 14:00:00 -26403,743,32,6.0,14,0,2005-07-31 14:00:00 -26404,743,38,5.0,17,0,2005-07-31 14:00:00 -26405,743,10,1.0,23,0,2005-07-31 14:00:00 -26406,743,34,6.0,16,0,2005-07-31 14:00:00 -26407,743,22,32.0,6,0,2005-07-31 14:00:00 -26408,744,23,1.0,23,0,2005-08-21 15:00:00 -26409,744,37,0.0,24,0,2005-08-21 15:00:00 -26410,744,40,0.0,25,0,2005-08-21 15:00:00 -26411,744,20,35.0,6,1,2005-08-21 15:00:00 -26412,744,21,31.0,8,0,2005-08-21 15:00:00 -26413,744,3,95.0,1,6,2005-08-21 15:00:00 -26414,744,16,24.0,10,0,2005-08-21 15:00:00 -26415,744,30,40.0,4,1,2005-08-21 15:00:00 -26416,744,31,5.0,18,0,2005-08-21 15:00:00 -26417,744,13,21.0,12,0,2005-08-21 15:00:00 -26418,744,14,39.0,5,0,2005-08-21 15:00:00 -26419,744,24,6.0,15,0,2005-08-21 15:00:00 -26420,744,36,4.0,20,0,2005-08-21 15:00:00 -26421,744,18,0.0,26,0,2005-08-21 15:00:00 -26422,744,7,71.0,2,5,2005-08-21 15:00:00 -26423,744,1,28.0,9,0,2005-08-21 15:00:00 -26424,744,29,55.0,3,1,2005-08-21 15:00:00 -26425,744,39,3.0,21,0,2005-08-21 15:00:00 -26426,744,26,4.0,19,0,2005-08-21 15:00:00 -26427,744,38,5.0,17,0,2005-08-21 15:00:00 -26428,744,10,1.0,22,0,2005-08-21 15:00:00 -26429,744,34,6.0,16,0,2005-08-21 15:00:00 -26430,744,22,32.0,7,0,2005-08-21 15:00:00 -26431,744,17,23.0,11,0,2005-08-21 15:00:00 -26432,744,12,8.0,13,0,2005-08-21 15:00:00 -26433,744,32,6.0,14,0,2005-08-21 15:00:00 -26434,745,30,50.0,4,2,2005-09-04 14:00:00 -26435,745,37,0.0,25,0,2005-09-04 14:00:00 -26436,745,41,2.0,22,0,2005-09-04 14:00:00 -26437,745,20,41.0,6,1,2005-09-04 14:00:00 -26438,745,21,31.0,8,0,2005-09-04 14:00:00 -26439,745,3,103.0,1,6,2005-09-04 14:00:00 -26440,745,13,21.0,12,0,2005-09-04 14:00:00 -26441,745,16,24.0,11,0,2005-09-04 14:00:00 -26442,745,31,5.0,18,0,2005-09-04 14:00:00 -26443,745,17,24.0,10,0,2005-09-04 14:00:00 -26444,745,14,43.0,5,0,2005-09-04 14:00:00 -26445,745,7,76.0,2,5,2005-09-04 14:00:00 -26446,745,40,0.0,26,0,2005-09-04 14:00:00 -26447,745,23,1.0,24,0,2005-09-04 14:00:00 -26448,745,24,6.0,15,0,2005-09-04 14:00:00 -26449,745,36,4.0,20,0,2005-09-04 14:00:00 -26450,745,18,0.0,27,0,2005-09-04 14:00:00 -26451,745,26,4.0,19,0,2005-09-04 14:00:00 -26452,745,1,28.0,9,0,2005-09-04 14:00:00 -26453,745,38,5.0,17,0,2005-09-04 14:00:00 -26454,745,39,3.0,21,0,2005-09-04 14:00:00 -26455,745,32,6.0,14,0,2005-09-04 14:00:00 -26456,745,10,1.0,23,0,2005-09-04 14:00:00 -26457,745,34,6.0,16,0,2005-09-04 14:00:00 -26458,745,22,35.0,7,0,2005-09-04 14:00:00 -26459,745,12,8.0,13,0,2005-09-04 14:00:00 -26460,745,29,55.0,3,1,2005-09-04 14:00:00 -26461,746,32,7.0,15,0,2005-09-11 14:00:00 -26462,746,38,5.0,17,0,2005-09-11 14:00:00 -26463,746,10,1.0,23,0,2005-09-11 14:00:00 -26464,746,34,9.0,13,0,2005-09-11 14:00:00 -26465,746,22,37.0,7,0,2005-09-11 14:00:00 -26466,746,17,30.0,9,0,2005-09-11 14:00:00 -26467,746,12,8.0,14,0,2005-09-11 14:00:00 -26468,746,7,86.0,2,6,2005-09-11 14:00:00 -26469,746,16,29.0,10,0,2005-09-11 14:00:00 -26470,746,30,50.0,4,2,2005-09-11 14:00:00 -26471,746,13,21.0,12,0,2005-09-11 14:00:00 -26472,746,3,111.0,1,6,2005-09-11 14:00:00 -26473,746,21,35.0,8,0,2005-09-11 14:00:00 -26474,746,20,41.0,6,1,2005-09-11 14:00:00 -26475,746,41,2.0,22,0,2005-09-11 14:00:00 -26476,746,37,0.0,25,0,2005-09-11 14:00:00 -26477,746,31,5.0,18,0,2005-09-11 14:00:00 -26478,746,39,3.0,21,0,2005-09-11 14:00:00 -26479,746,14,43.0,5,0,2005-09-11 14:00:00 -26480,746,26,4.0,19,0,2005-09-11 14:00:00 -26481,746,40,0.0,26,0,2005-09-11 14:00:00 -26482,746,23,1.0,24,0,2005-09-11 14:00:00 -26483,746,29,55.0,3,1,2005-09-11 14:00:00 -26484,746,1,28.0,11,0,2005-09-11 14:00:00 -26485,746,24,6.0,16,0,2005-09-11 14:00:00 -26486,746,36,4.0,20,0,2005-09-11 14:00:00 -26487,746,18,0.0,27,0,2005-09-11 14:00:00 -26488,747,31,5.0,18,0,2005-09-25 14:00:00 -26489,747,30,60.0,3,3,2005-09-25 14:00:00 -26490,747,16,29.0,10,0,2005-09-25 14:00:00 -26491,747,13,21.0,12,0,2005-09-25 14:00:00 -26492,747,7,94.0,2,6,2005-09-25 14:00:00 -26493,747,21,38.0,7,0,2005-09-25 14:00:00 -26494,747,20,45.0,5,1,2005-09-25 14:00:00 -26495,747,14,43.0,6,0,2005-09-25 14:00:00 -26496,747,3,117.0,1,6,2005-09-25 14:00:00 -26497,747,12,8.0,14,0,2005-09-25 14:00:00 -26498,747,17,32.0,9,0,2005-09-25 14:00:00 -26499,747,26,4.0,19,0,2005-09-25 14:00:00 -26500,747,40,0.0,26,0,2005-09-25 14:00:00 -26501,747,23,1.0,24,0,2005-09-25 14:00:00 -26502,747,24,6.0,16,0,2005-09-25 14:00:00 -26503,747,36,4.0,20,0,2005-09-25 14:00:00 -26504,747,18,0.0,27,0,2005-09-25 14:00:00 -26505,747,22,38.0,8,0,2005-09-25 14:00:00 -26506,747,37,0.0,25,0,2005-09-25 14:00:00 -26507,747,1,28.0,11,0,2005-09-25 14:00:00 -26508,747,39,3.0,21,0,2005-09-25 14:00:00 -26509,747,32,7.0,15,0,2005-09-25 14:00:00 -26510,747,38,5.0,17,0,2005-09-25 14:00:00 -26511,747,10,1.0,23,0,2005-09-25 14:00:00 -26512,747,34,9.0,13,0,2005-09-25 14:00:00 -26513,747,29,60.0,4,1,2005-09-25 14:00:00 -26514,747,41,2.0,22,0,2005-09-25 14:00:00 -26515,748,30,60.0,4,3,2005-10-09 14:00:00 -26516,748,16,34.0,10,0,2005-10-09 14:00:00 -26517,748,31,5.0,18,0,2005-10-09 14:00:00 -26518,748,13,24.0,12,0,2005-10-09 14:00:00 -26519,748,26,4.0,19,0,2005-10-09 14:00:00 -26520,748,21,38.0,8,0,2005-10-09 14:00:00 -26521,748,20,53.0,5,1,2005-10-09 14:00:00 -26522,748,7,104.0,2,7,2005-10-09 14:00:00 -26523,748,3,123.0,1,6,2005-10-09 14:00:00 -26524,748,14,43.0,6,0,2005-10-09 14:00:00 -26525,748,24,6.0,16,0,2005-10-09 14:00:00 -26526,748,17,36.0,9,0,2005-10-09 14:00:00 -26527,748,22,39.0,7,0,2005-10-09 14:00:00 -26528,748,34,9.0,13,0,2005-10-09 14:00:00 -26529,748,10,1.0,23,0,2005-10-09 14:00:00 -26530,748,38,5.0,17,0,2005-10-09 14:00:00 -26531,748,32,7.0,15,0,2005-10-09 14:00:00 -26532,748,39,3.0,21,0,2005-10-09 14:00:00 -26533,748,29,62.0,3,1,2005-10-09 14:00:00 -26534,748,1,28.0,11,0,2005-10-09 14:00:00 -26535,748,12,8.0,14,0,2005-10-09 14:00:00 -26536,748,18,0.0,27,0,2005-10-09 14:00:00 -26537,748,36,4.0,20,0,2005-10-09 14:00:00 -26538,748,41,2.0,22,0,2005-10-09 14:00:00 -26539,748,23,1.0,24,0,2005-10-09 14:00:00 -26540,748,40,0.0,26,0,2005-10-09 14:00:00 -26541,748,37,0.0,25,0,2005-10-09 14:00:00 -26542,749,30,60.0,4,3,2005-10-16 14:00:00 -26543,749,16,36.0,10,0,2005-10-16 14:00:00 -26544,749,13,24.0,12,0,2005-10-16 14:00:00 -26545,749,36,4.0,20,0,2005-10-16 14:00:00 -26546,749,21,38.0,8,0,2005-10-16 14:00:00 -26547,749,20,58.0,5,1,2005-10-16 14:00:00 -26548,749,31,9.0,15,0,2005-10-16 14:00:00 -26549,749,3,133.0,1,7,2005-10-16 14:00:00 -26550,749,7,112.0,2,7,2005-10-16 14:00:00 -26551,749,40,0.0,26,0,2005-10-16 14:00:00 -26552,749,12,11.0,13,0,2005-10-16 14:00:00 -26553,749,14,43.0,7,0,2005-10-16 14:00:00 -26554,749,37,0.0,25,0,2005-10-16 14:00:00 -26555,749,23,1.0,24,0,2005-10-16 14:00:00 -26556,749,24,6.0,17,0,2005-10-16 14:00:00 -26557,749,18,0.0,27,0,2005-10-16 14:00:00 -26558,749,26,4.0,19,0,2005-10-16 14:00:00 -26559,749,1,28.0,11,0,2005-10-16 14:00:00 -26560,749,41,2.0,22,0,2005-10-16 14:00:00 -26561,749,39,3.0,21,0,2005-10-16 14:00:00 -26562,749,32,7.0,16,0,2005-10-16 14:00:00 -26563,749,38,5.0,18,0,2005-10-16 14:00:00 -26564,749,10,1.0,23,0,2005-10-16 14:00:00 -26565,749,34,9.0,14,0,2005-10-16 14:00:00 -26566,749,22,45.0,6,0,2005-10-16 14:00:00 -26567,749,29,62.0,3,1,2005-10-16 14:00:00 -26568,749,17,37.0,9,0,2005-10-16 14:00:00 -26569,750,2,2.0,7,0,2006-03-12 14:30:00 -26570,750,16,3.0,6,0,2006-03-12 14:30:00 -26571,750,30,4.0,5,0,2006-03-12 14:30:00 -26572,750,29,8.0,2,0,2006-03-12 14:30:00 -26573,750,7,6.0,3,0,2006-03-12 14:30:00 -26574,750,3,10.0,1,1,2006-03-12 14:30:00 -26575,750,31,1.0,8,0,2006-03-12 14:30:00 -26576,750,17,5.0,4,0,2006-03-12 14:30:00 -26577,750,12,0.0,9,0,2006-03-12 14:30:00 -26578,750,14,0.0,16,0,2006-03-12 14:30:00 -26579,750,23,0.0,11,0,2006-03-12 14:30:00 -26580,750,1,0.0,12,0,2006-03-12 14:30:00 -26581,750,25,0.0,13,0,2006-03-12 14:30:00 -26582,750,22,0.0,14,0,2006-03-12 14:30:00 -26583,750,21,0.0,15,0,2006-03-12 14:30:00 -26584,750,32,0.0,17,0,2006-03-12 14:30:00 -26585,750,10,0.0,18,0,2006-03-12 14:30:00 -26586,750,13,0.0,10,0,2006-03-12 14:30:00 -26587,751,16,3.0,8,0,2006-03-19 15:00:00 -26588,751,31,1.0,12,0,2006-03-19 15:00:00 -26589,751,2,2.0,9,0,2006-03-19 15:00:00 -26590,751,30,9.0,5,0,2006-03-19 15:00:00 -26591,751,3,18.0,1,1,2006-03-19 15:00:00 -26592,751,7,6.0,6,0,2006-03-19 15:00:00 -26593,751,29,11.0,2,0,2006-03-19 15:00:00 -26594,751,12,4.0,7,0,2006-03-19 15:00:00 -26595,751,17,11.0,3,0,2006-03-19 15:00:00 -26596,751,23,0.0,16,0,2006-03-19 15:00:00 -26597,751,13,0.0,15,0,2006-03-19 15:00:00 -26598,751,1,0.0,18,0,2006-03-19 15:00:00 -26599,751,25,0.0,20,0,2006-03-19 15:00:00 -26600,751,22,1.0,11,0,2006-03-19 15:00:00 -26601,751,21,0.0,14,0,2006-03-19 15:00:00 -26602,751,14,0.0,13,0,2006-03-19 15:00:00 -26603,751,32,0.0,19,0,2006-03-19 15:00:00 -26604,751,10,0.0,21,0,2006-03-19 15:00:00 -26605,751,20,10.0,4,1,2006-03-19 15:00:00 -26606,751,34,2.0,10,0,2006-03-19 15:00:00 -26607,751,26,0.0,17,0,2006-03-19 15:00:00 -26608,752,31,1.0,15,0,2006-04-02 14:00:00 -26609,752,2,2.0,13,0,2006-04-02 14:00:00 -26610,752,16,3.0,11,0,2006-04-02 14:00:00 -26611,752,30,9.0,6,0,2006-04-02 14:00:00 -26612,752,23,0.0,18,0,2006-04-02 14:00:00 -26613,752,7,14.0,3,0,2006-04-02 14:00:00 -26614,752,29,11.0,4,0,2006-04-02 14:00:00 -26615,752,3,28.0,1,2,2006-04-02 14:00:00 -26616,752,12,4.0,10,0,2006-04-02 14:00:00 -26617,752,17,11.0,5,0,2006-04-02 14:00:00 -26618,752,13,1.0,14,0,2006-04-02 14:00:00 -26619,752,21,2.0,12,0,2006-04-02 14:00:00 -26620,752,1,5.0,8,0,2006-04-02 14:00:00 -26621,752,25,0.0,16,0,2006-04-02 14:00:00 -26622,752,22,7.0,7,0,2006-04-02 14:00:00 -26623,752,14,0.0,17,0,2006-04-02 14:00:00 -26624,752,32,0.0,21,0,2006-04-02 14:00:00 -26625,752,10,0.0,20,0,2006-04-02 14:00:00 -26626,752,20,14.0,2,1,2006-04-02 14:00:00 -26627,752,34,5.0,9,0,2006-04-02 14:00:00 -26628,752,26,0.0,19,0,2006-04-02 14:00:00 -26629,752,33,0.0,22,0,2006-04-02 14:00:00 -26630,753,2,2.0,13,0,2006-04-23 14:00:00 -26631,753,31,1.0,15,0,2006-04-23 14:00:00 -26632,753,12,9.0,7,0,2006-04-23 14:00:00 -26633,753,16,6.0,9,0,2006-04-23 14:00:00 -26634,753,3,36.0,1,2,2006-04-23 14:00:00 -26635,753,17,13.0,6,0,2006-04-23 14:00:00 -26636,753,7,18.0,3,0,2006-04-23 14:00:00 -26637,753,29,21.0,2,1,2006-04-23 14:00:00 -26638,753,13,1.0,14,0,2006-04-23 14:00:00 -26639,753,30,15.0,5,0,2006-04-23 14:00:00 -26640,753,23,0.0,18,0,2006-04-23 14:00:00 -26641,753,33,0.0,22,0,2006-04-23 14:00:00 -26642,753,25,0.0,16,0,2006-04-23 14:00:00 -26643,753,22,7.0,8,0,2006-04-23 14:00:00 -26644,753,21,2.0,12,0,2006-04-23 14:00:00 -26645,753,14,0.0,17,0,2006-04-23 14:00:00 -26646,753,32,0.0,21,0,2006-04-23 14:00:00 -26647,753,10,0.0,20,0,2006-04-23 14:00:00 -26648,753,20,15.0,4,1,2006-04-23 14:00:00 -26649,753,34,5.0,11,0,2006-04-23 14:00:00 -26650,753,26,0.0,19,0,2006-04-23 14:00:00 -26651,753,1,5.0,10,0,2006-04-23 14:00:00 -26652,754,12,15.0,5,0,2006-05-07 14:00:00 -26653,754,31,1.0,15,0,2006-05-07 14:00:00 -26654,754,2,4.0,13,0,2006-05-07 14:00:00 -26655,754,13,1.0,14,0,2006-05-07 14:00:00 -26656,754,29,31.0,2,2,2006-05-07 14:00:00 -26657,754,30,15.0,6,0,2006-05-07 14:00:00 -26658,754,17,13.0,7,0,2006-05-07 14:00:00 -26659,754,7,23.0,3,0,2006-05-07 14:00:00 -26660,754,3,44.0,1,2,2006-05-07 14:00:00 -26661,754,16,6.0,10,0,2006-05-07 14:00:00 -26662,754,23,0.0,18,0,2006-05-07 14:00:00 -26663,754,32,0.0,20,0,2006-05-07 14:00:00 -26664,754,25,0.0,17,0,2006-05-07 14:00:00 -26665,754,33,0.0,22,0,2006-05-07 14:00:00 -26666,754,26,0.0,19,0,2006-05-07 14:00:00 -26667,754,34,6.0,11,0,2006-05-07 14:00:00 -26668,754,20,18.0,4,1,2006-05-07 14:00:00 -26669,754,1,5.0,12,0,2006-05-07 14:00:00 -26670,754,14,0.0,16,0,2006-05-07 14:00:00 -26671,754,21,6.0,9,0,2006-05-07 14:00:00 -26672,754,22,7.0,8,0,2006-05-07 14:00:00 -26673,754,10,0.0,21,0,2006-05-07 14:00:00 -26674,755,3,54.0,1,3,2006-05-14 14:00:00 -26675,755,23,0.0,18,0,2006-05-14 14:00:00 -26676,755,7,27.0,3,0,2006-05-14 14:00:00 -26677,755,17,16.0,6,0,2006-05-14 14:00:00 -26678,755,30,15.0,7,0,2006-05-14 14:00:00 -26679,755,16,6.0,11,0,2006-05-14 14:00:00 -26680,755,2,4.0,13,0,2006-05-14 14:00:00 -26681,755,31,1.0,15,0,2006-05-14 14:00:00 -26682,755,12,20.0,5,0,2006-05-14 14:00:00 -26683,755,13,1.0,14,0,2006-05-14 14:00:00 -26684,755,29,39.0,2,2,2006-05-14 14:00:00 -26685,755,1,6.0,10,0,2006-05-14 14:00:00 -26686,755,22,7.0,9,0,2006-05-14 14:00:00 -26687,755,21,8.0,8,0,2006-05-14 14:00:00 -26688,755,14,0.0,16,0,2006-05-14 14:00:00 -26689,755,32,0.0,20,0,2006-05-14 14:00:00 -26690,755,10,0.0,21,0,2006-05-14 14:00:00 -26691,755,20,24.0,4,1,2006-05-14 14:00:00 -26692,755,34,6.0,12,0,2006-05-14 14:00:00 -26693,755,26,0.0,19,0,2006-05-14 14:00:00 -26694,755,33,0.0,22,0,2006-05-14 14:00:00 -26695,755,25,0.0,17,0,2006-05-14 14:00:00 -26696,756,23,0.0,18,0,2006-05-28 14:00:00 -26697,756,13,7.0,11,0,2006-05-28 14:00:00 -26698,756,12,20.0,6,0,2006-05-28 14:00:00 -26699,756,31,1.0,15,0,2006-05-28 14:00:00 -26700,756,1,8.0,10,0,2006-05-28 14:00:00 -26701,756,16,6.0,12,0,2006-05-28 14:00:00 -26702,756,30,23.0,5,0,2006-05-28 14:00:00 -26703,756,17,16.0,7,0,2006-05-28 14:00:00 -26704,756,2,4.0,14,0,2006-05-28 14:00:00 -26705,756,25,0.0,17,0,2006-05-28 14:00:00 -26706,756,7,27.0,4,0,2006-05-28 14:00:00 -26707,756,21,13.0,8,0,2006-05-28 14:00:00 -26708,756,14,0.0,16,0,2006-05-28 14:00:00 -26709,756,32,0.0,20,0,2006-05-28 14:00:00 -26710,756,10,0.0,21,0,2006-05-28 14:00:00 -26711,756,20,27.0,3,1,2006-05-28 14:00:00 -26712,756,34,6.0,13,0,2006-05-28 14:00:00 -26713,756,26,0.0,19,0,2006-05-28 14:00:00 -26714,756,33,0.0,22,0,2006-05-28 14:00:00 -26715,756,35,0.0,23,0,2006-05-28 14:00:00 -26716,756,22,8.0,9,0,2006-05-28 14:00:00 -26717,756,3,64.0,1,4,2006-05-28 14:00:00 -26718,756,29,43.0,2,2,2006-05-28 14:00:00 -26719,757,25,0.0,17,0,2006-06-11 12:00:00 -26720,757,3,74.0,1,5,2006-06-11 12:00:00 -26721,757,29,51.0,2,2,2006-06-11 12:00:00 -26722,757,7,33.0,3,0,2006-06-11 12:00:00 -26723,757,17,16.0,7,0,2006-06-11 12:00:00 -26724,757,30,26.0,5,0,2006-06-11 12:00:00 -26725,757,16,6.0,13,0,2006-06-11 12:00:00 -26726,757,31,1.0,15,0,2006-06-11 12:00:00 -26727,757,12,24.0,6,0,2006-06-11 12:00:00 -26728,757,13,7.0,11,0,2006-06-11 12:00:00 -26729,757,1,10.0,9,0,2006-06-11 12:00:00 -26730,757,2,4.0,14,0,2006-06-11 12:00:00 -26731,757,35,0.0,23,0,2006-06-11 12:00:00 -26732,757,23,0.0,18,0,2006-06-11 12:00:00 -26733,757,21,13.0,8,0,2006-06-11 12:00:00 -26734,757,14,0.0,16,0,2006-06-11 12:00:00 -26735,757,32,0.0,20,0,2006-06-11 12:00:00 -26736,757,10,0.0,21,0,2006-06-11 12:00:00 -26737,757,22,8.0,10,0,2006-06-11 12:00:00 -26738,757,34,7.0,12,0,2006-06-11 12:00:00 -26739,757,26,0.0,19,0,2006-06-11 12:00:00 -26740,757,33,0.0,22,0,2006-06-11 12:00:00 -26741,757,20,32.0,4,1,2006-06-11 12:00:00 -26742,758,13,8.0,11,0,2006-06-25 13:00:00 -26743,758,3,84.0,1,6,2006-06-25 13:00:00 -26744,758,29,59.0,2,2,2006-06-25 13:00:00 -26745,758,7,39.0,3,0,2006-06-25 13:00:00 -26746,758,17,16.0,7,0,2006-06-25 13:00:00 -26747,758,30,26.0,6,0,2006-06-25 13:00:00 -26748,758,16,6.0,13,0,2006-06-25 13:00:00 -26749,758,2,4.0,14,0,2006-06-25 13:00:00 -26750,758,31,1.0,16,0,2006-06-25 13:00:00 -26751,758,12,28.0,5,0,2006-06-25 13:00:00 -26752,758,23,0.0,18,0,2006-06-25 13:00:00 -26753,758,10,0.0,21,0,2006-06-25 13:00:00 -26754,758,25,0.0,17,0,2006-06-25 13:00:00 -26755,758,1,12.0,9,0,2006-06-25 13:00:00 -26756,758,33,0.0,22,0,2006-06-25 13:00:00 -26757,758,26,0.0,19,0,2006-06-25 13:00:00 -26758,758,34,7.0,12,0,2006-06-25 13:00:00 -26759,758,20,37.0,4,1,2006-06-25 13:00:00 -26760,758,35,0.0,23,0,2006-06-25 13:00:00 -26761,758,32,0.0,20,0,2006-06-25 13:00:00 -26762,758,14,3.0,15,0,2006-06-25 13:00:00 -26763,758,21,13.0,8,0,2006-06-25 13:00:00 -26764,758,22,8.0,10,0,2006-06-25 13:00:00 -26765,759,3,88.0,1,6,2006-07-02 14:00:00 -26766,759,29,69.0,2,3,2006-07-02 14:00:00 -26767,759,7,39.0,4,0,2006-07-02 14:00:00 -26768,759,17,16.0,7,0,2006-07-02 14:00:00 -26769,759,30,26.0,6,0,2006-07-02 14:00:00 -26770,759,2,4.0,15,0,2006-07-02 14:00:00 -26771,759,31,1.0,17,0,2006-07-02 14:00:00 -26772,759,12,36.0,5,0,2006-07-02 14:00:00 -26773,759,13,10.0,10,0,2006-07-02 14:00:00 -26774,759,23,1.0,16,0,2006-07-02 14:00:00 -26775,759,1,12.0,9,0,2006-07-02 14:00:00 -26776,759,16,6.0,14,0,2006-07-02 14:00:00 -26777,759,22,8.0,11,0,2006-07-02 14:00:00 -26778,759,33,0.0,22,0,2006-07-02 14:00:00 -26779,759,26,0.0,19,0,2006-07-02 14:00:00 -26780,759,34,7.0,13,0,2006-07-02 14:00:00 -26781,759,20,43.0,3,1,2006-07-02 14:00:00 -26782,759,35,0.0,23,0,2006-07-02 14:00:00 -26783,759,10,0.0,21,0,2006-07-02 14:00:00 -26784,759,32,0.0,20,0,2006-07-02 14:00:00 -26785,759,14,8.0,12,0,2006-07-02 14:00:00 -26786,759,21,16.0,8,0,2006-07-02 14:00:00 -26787,759,25,0.0,18,0,2006-07-02 14:00:00 -26788,760,23,1.0,17,0,2006-07-16 14:00:00 -26789,760,29,79.0,2,4,2006-07-16 14:00:00 -26790,760,7,43.0,4,0,2006-07-16 14:00:00 -26791,760,17,16.0,7,0,2006-07-16 14:00:00 -26792,760,30,26.0,6,0,2006-07-16 14:00:00 -26793,760,16,6.0,14,0,2006-07-16 14:00:00 -26794,760,2,4.0,15,0,2006-07-16 14:00:00 -26795,760,31,1.0,18,0,2006-07-16 14:00:00 -26796,760,12,42.0,5,0,2006-07-16 14:00:00 -26797,760,13,10.0,11,0,2006-07-16 14:00:00 -26798,760,1,13.0,10,0,2006-07-16 14:00:00 -26799,760,3,96.0,1,6,2006-07-16 14:00:00 -26800,760,22,13.0,9,0,2006-07-16 14:00:00 -26801,760,36,2.0,16,0,2006-07-16 14:00:00 -26802,760,35,0.0,24,0,2006-07-16 14:00:00 -26803,760,33,0.0,23,0,2006-07-16 14:00:00 -26804,760,26,0.0,20,0,2006-07-16 14:00:00 -26805,760,34,7.0,13,0,2006-07-16 14:00:00 -26806,760,25,0.0,19,0,2006-07-16 14:00:00 -26807,760,10,0.0,22,0,2006-07-16 14:00:00 -26808,760,32,0.0,21,0,2006-07-16 14:00:00 -26809,760,14,8.0,12,0,2006-07-16 14:00:00 -26810,760,21,16.0,8,0,2006-07-16 14:00:00 -26811,760,20,46.0,3,1,2006-07-16 14:00:00 -26812,761,23,1.0,18,0,2006-07-30 14:00:00 -26813,761,13,10.0,11,0,2006-07-30 14:00:00 -26814,761,12,50.0,3,0,2006-07-30 14:00:00 -26815,761,31,2.0,17,0,2006-07-30 14:00:00 -26816,761,2,4.0,15,0,2006-07-30 14:00:00 -26817,761,30,26.0,6,0,2006-07-30 14:00:00 -26818,761,17,21.0,7,0,2006-07-30 14:00:00 -26819,761,7,49.0,5,0,2006-07-30 14:00:00 -26820,761,29,89.0,2,5,2006-07-30 14:00:00 -26821,761,1,13.0,10,0,2006-07-30 14:00:00 -26822,761,16,6.0,14,0,2006-07-30 14:00:00 -26823,761,3,100.0,1,6,2006-07-30 14:00:00 -26824,761,25,0.0,19,0,2006-07-30 14:00:00 -26825,761,21,16.0,8,0,2006-07-30 14:00:00 -26826,761,14,10.0,12,0,2006-07-30 14:00:00 -26827,761,32,0.0,21,0,2006-07-30 14:00:00 -26828,761,10,0.0,22,0,2006-07-30 14:00:00 -26829,761,20,49.0,4,1,2006-07-30 14:00:00 -26830,761,34,7.0,13,0,2006-07-30 14:00:00 -26831,761,26,0.0,20,0,2006-07-30 14:00:00 -26832,761,33,0.0,23,0,2006-07-30 14:00:00 -26833,761,35,0.0,24,0,2006-07-30 14:00:00 -26834,761,36,2.0,16,0,2006-07-30 14:00:00 -26835,761,22,13.0,9,0,2006-07-30 14:00:00 -26836,762,13,14.0,11,0,2006-08-06 14:00:00 -26837,762,3,100.0,1,6,2006-08-06 14:00:00 -26838,762,31,2.0,17,0,2006-08-06 14:00:00 -26839,762,2,4.0,16,0,2006-08-06 14:00:00 -26840,762,23,1.0,18,0,2006-08-06 14:00:00 -26841,762,30,26.0,7,0,2006-08-06 14:00:00 -26842,762,17,31.0,6,1,2006-08-06 14:00:00 -26843,762,7,49.0,5,0,2006-08-06 14:00:00 -26844,762,29,90.0,2,5,2006-08-06 14:00:00 -26845,762,16,6.0,15,0,2006-08-06 14:00:00 -26846,762,1,19.0,9,0,2006-08-06 14:00:00 -26847,762,12,52.0,3,0,2006-08-06 14:00:00 -26848,762,22,16.0,10,0,2006-08-06 14:00:00 -26849,762,36,10.0,12,0,2006-08-06 14:00:00 -26850,762,35,0.0,24,0,2006-08-06 14:00:00 -26851,762,33,0.0,23,0,2006-08-06 14:00:00 -26852,762,26,0.0,21,0,2006-08-06 14:00:00 -26853,762,34,7.0,14,0,2006-08-06 14:00:00 -26854,762,25,0.0,19,0,2006-08-06 14:00:00 -26855,762,10,0.0,22,0,2006-08-06 14:00:00 -26856,762,32,0.0,20,0,2006-08-06 14:00:00 -26857,762,14,10.0,13,0,2006-08-06 14:00:00 -26858,762,21,21.0,8,0,2006-08-06 14:00:00 -26859,762,20,49.0,4,1,2006-08-06 14:00:00 -26860,763,13,14.0,12,0,2006-08-27 15:00:00 -26861,763,12,62.0,3,1,2006-08-27 15:00:00 -26862,763,31,2.0,17,0,2006-08-27 15:00:00 -26863,763,2,4.0,16,0,2006-08-27 15:00:00 -26864,763,16,6.0,15,0,2006-08-27 15:00:00 -26865,763,17,36.0,6,1,2006-08-27 15:00:00 -26866,763,7,49.0,5,0,2006-08-27 15:00:00 -26867,763,29,96.0,2,5,2006-08-27 15:00:00 -26868,763,3,108.0,1,6,2006-08-27 15:00:00 -26869,763,23,1.0,18,0,2006-08-27 15:00:00 -26870,763,30,26.0,7,0,2006-08-27 15:00:00 -26871,763,25,0.0,19,0,2006-08-27 15:00:00 -26872,763,1,19.0,9,0,2006-08-27 15:00:00 -26873,763,33,0.0,24,0,2006-08-27 15:00:00 -26874,763,21,22.0,8,0,2006-08-27 15:00:00 -26875,763,14,10.0,13,0,2006-08-27 15:00:00 -26876,763,32,0.0,20,0,2006-08-27 15:00:00 -26877,763,10,0.0,22,0,2006-08-27 15:00:00 -26878,763,20,52.0,4,1,2006-08-27 15:00:00 -26879,763,34,7.0,14,0,2006-08-27 15:00:00 -26880,763,26,0.0,21,0,2006-08-27 15:00:00 -26881,763,35,0.0,25,0,2006-08-27 15:00:00 -26882,763,36,14.0,11,0,2006-08-27 15:00:00 -26883,763,8,0.0,23,0,2006-08-27 15:00:00 -26884,763,22,18.0,10,0,2006-08-27 15:00:00 -26885,764,13,14.0,12,0,2006-09-10 14:00:00 -26886,764,23,1.0,19,0,2006-09-10 14:00:00 -26887,764,25,0.0,20,0,2006-09-10 14:00:00 -26888,764,12,62.0,3,1,2006-09-10 14:00:00 -26889,764,1,20.0,9,0,2006-09-10 14:00:00 -26890,764,31,2.0,18,0,2006-09-10 14:00:00 -26891,764,3,108.0,1,6,2006-09-10 14:00:00 -26892,764,16,6.0,16,0,2006-09-10 14:00:00 -26893,764,30,26.0,7,0,2006-09-10 14:00:00 -26894,764,17,40.0,6,1,2006-09-10 14:00:00 -26895,764,7,57.0,5,0,2006-09-10 14:00:00 -26896,764,29,106.0,2,6,2006-09-10 14:00:00 -26897,764,2,4.0,17,0,2006-09-10 14:00:00 -26898,764,22,18.0,10,0,2006-09-10 14:00:00 -26899,764,36,14.0,11,0,2006-09-10 14:00:00 -26900,764,14,12.0,13,0,2006-09-10 14:00:00 -26901,764,32,0.0,21,0,2006-09-10 14:00:00 -26902,764,10,0.0,23,0,2006-09-10 14:00:00 -26903,764,20,57.0,4,1,2006-09-10 14:00:00 -26904,764,34,7.0,14,0,2006-09-10 14:00:00 -26905,764,26,0.0,22,0,2006-09-10 14:00:00 -26906,764,33,0.0,24,0,2006-09-10 14:00:00 -26907,764,35,0.0,25,0,2006-09-10 14:00:00 -26908,764,21,25.0,8,0,2006-09-10 14:00:00 -26909,764,8,6.0,15,0,2006-09-10 14:00:00 -26910,765,25,0.0,20,0,2006-10-01 14:00:00 -26911,765,1,22.0,9,0,2006-10-01 14:00:00 -26912,765,23,1.0,19,0,2006-10-01 14:00:00 -26913,765,13,14.0,12,0,2006-10-01 14:00:00 -26914,765,12,62.0,4,1,2006-10-01 14:00:00 -26915,765,31,2.0,18,0,2006-10-01 14:00:00 -26916,765,22,18.0,11,0,2006-10-01 14:00:00 -26917,765,3,116.0,2,6,2006-10-01 14:00:00 -26918,765,16,7.0,14,0,2006-10-01 14:00:00 -26919,765,29,116.0,1,7,2006-10-01 14:00:00 -26920,765,7,57.0,5,0,2006-10-01 14:00:00 -26921,765,17,45.0,6,1,2006-10-01 14:00:00 -26922,765,30,26.0,8,0,2006-10-01 14:00:00 -26923,765,2,4.0,17,0,2006-10-01 14:00:00 -26924,765,21,28.0,7,0,2006-10-01 14:00:00 -26925,765,37,0.0,24,0,2006-10-01 14:00:00 -26926,765,32,0.0,21,0,2006-10-01 14:00:00 -26927,765,14,12.0,13,0,2006-10-01 14:00:00 -26928,765,28,0.0,27,0,2006-10-01 14:00:00 -26929,765,36,18.0,10,0,2006-10-01 14:00:00 -26930,765,35,0.0,26,0,2006-10-01 14:00:00 -26931,765,8,6.0,16,0,2006-10-01 14:00:00 -26932,765,26,0.0,22,0,2006-10-01 14:00:00 -26933,765,34,7.0,15,0,2006-10-01 14:00:00 -26934,765,20,63.0,3,1,2006-10-01 14:00:00 -26935,765,10,0.0,23,0,2006-10-01 14:00:00 -26936,765,33,0.0,25,0,2006-10-01 14:00:00 -26937,766,12,70.0,3,1,2006-10-08 14:00:00 -26938,766,25,0.0,20,0,2006-10-08 14:00:00 -26939,766,1,23.0,9,0,2006-10-08 14:00:00 -26940,766,23,1.0,19,0,2006-10-08 14:00:00 -26941,766,13,14.0,13,0,2006-10-08 14:00:00 -26942,766,31,2.0,18,0,2006-10-08 14:00:00 -26943,766,7,61.0,5,0,2006-10-08 14:00:00 -26944,766,16,7.0,14,0,2006-10-08 14:00:00 -26945,766,30,26.0,8,0,2006-10-08 14:00:00 -26946,766,17,50.0,6,1,2006-10-08 14:00:00 -26947,766,21,28.0,7,0,2006-10-08 14:00:00 -26948,766,29,116.0,2,7,2006-10-08 14:00:00 -26949,766,3,126.0,1,7,2006-10-08 14:00:00 -26950,766,2,4.0,17,0,2006-10-08 14:00:00 -26951,766,14,15.0,12,0,2006-10-08 14:00:00 -26952,766,22,20.0,10,0,2006-10-08 14:00:00 -26953,766,10,0.0,23,0,2006-10-08 14:00:00 -26954,766,32,0.0,21,0,2006-10-08 14:00:00 -26955,766,37,0.0,24,0,2006-10-08 14:00:00 -26956,766,8,6.0,16,0,2006-10-08 14:00:00 -26957,766,36,18.0,11,0,2006-10-08 14:00:00 -26958,766,28,0.0,27,0,2006-10-08 14:00:00 -26959,766,33,0.0,25,0,2006-10-08 14:00:00 -26960,766,26,0.0,22,0,2006-10-08 14:00:00 -26961,766,34,7.0,15,0,2006-10-08 14:00:00 -26962,766,20,69.0,4,1,2006-10-08 14:00:00 -26963,766,35,0.0,26,0,2006-10-08 14:00:00 -26964,767,23,1.0,19,0,2006-10-22 14:00:00 -26965,767,10,0.0,23,0,2006-10-22 14:00:00 -26966,767,32,0.0,21,0,2006-10-22 14:00:00 -26967,767,14,15.0,12,0,2006-10-22 14:00:00 -26968,767,21,30.0,7,0,2006-10-22 14:00:00 -26969,767,22,20.0,10,0,2006-10-22 14:00:00 -26970,767,25,0.0,20,0,2006-10-22 14:00:00 -26971,767,1,23.0,9,0,2006-10-22 14:00:00 -26972,767,13,14.0,13,0,2006-10-22 14:00:00 -26973,767,30,26.0,8,0,2006-10-22 14:00:00 -26974,767,31,2.0,18,0,2006-10-22 14:00:00 -26975,767,2,4.0,17,0,2006-10-22 14:00:00 -26976,767,16,7.0,14,0,2006-10-22 14:00:00 -26977,767,17,56.0,6,1,2006-10-22 14:00:00 -26978,767,7,65.0,5,0,2006-10-22 14:00:00 -26979,767,29,121.0,2,7,2006-10-22 14:00:00 -26980,767,3,134.0,1,7,2006-10-22 14:00:00 -26981,767,20,72.0,4,1,2006-10-22 14:00:00 -26982,767,12,80.0,3,2,2006-10-22 14:00:00 -26983,767,34,7.0,15,0,2006-10-22 14:00:00 -26984,767,35,0.0,27,0,2006-10-22 14:00:00 -26985,767,36,19.0,11,0,2006-10-22 14:00:00 -26986,767,8,6.0,16,0,2006-10-22 14:00:00 -26987,767,37,0.0,24,0,2006-10-22 14:00:00 -26988,767,28,0.0,26,0,2006-10-22 14:00:00 -26989,767,26,0.0,22,0,2006-10-22 14:00:00 -26990,767,33,0.0,25,0,2006-10-22 14:00:00 -26991,768,12,3.0,6,0,2007-03-18 03:00:00 -26992,768,20,4.0,5,0,2007-03-18 03:00:00 -26993,768,2,2.0,7,0,2007-03-18 03:00:00 -26994,768,22,1.0,8,0,2007-03-18 03:00:00 -26995,768,14,0.0,9,0,2007-03-18 03:00:00 -26996,768,4,0.0,10,0,2007-03-18 03:00:00 -26997,768,21,0.0,11,0,2007-03-18 03:00:00 -26998,768,16,0.0,13,0,2007-03-18 03:00:00 -26999,768,23,0.0,14,0,2007-03-18 03:00:00 -27000,768,17,0.0,15,0,2007-03-18 03:00:00 -27001,768,10,0.0,12,0,2007-03-18 03:00:00 -27002,768,15,0.0,17,0,2007-03-18 03:00:00 -27003,768,7,10.0,1,1,2007-03-18 03:00:00 -27004,768,3,8.0,2,0,2007-03-18 03:00:00 -27005,768,0,6.0,3,0,2007-03-18 03:00:00 -27006,768,1,5.0,4,0,2007-03-18 03:00:00 -27007,768,18,0.0,16,0,2007-03-18 03:00:00 -27008,769,22,1.0,10,0,2007-04-08 07:00:00 -27009,769,14,2.0,7,0,2007-04-08 07:00:00 -27010,769,4,1.0,9,0,2007-04-08 07:00:00 -27011,769,21,0.0,13,0,2007-04-08 07:00:00 -27012,769,10,0.0,14,0,2007-04-08 07:00:00 -27013,769,16,0.0,12,0,2007-04-08 07:00:00 -27014,769,23,0.0,16,0,2007-04-08 07:00:00 -27015,769,17,0.0,15,0,2007-04-08 07:00:00 -27016,769,24,0.0,11,0,2007-04-08 07:00:00 -27017,769,15,0.0,19,0,2007-04-08 07:00:00 -27018,769,25,0.0,17,0,2007-04-08 07:00:00 -27019,769,8,0.0,20,0,2007-04-08 07:00:00 -27020,769,2,2.0,8,0,2007-04-08 07:00:00 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-27251,779,17,1.0,16,0,2007-08-26 12:00:00 -27252,779,23,0.0,23,0,2007-08-26 12:00:00 -27253,779,2,9.0,10,0,2007-08-26 12:00:00 -27254,780,26,0.0,22,0,2007-09-09 12:00:00 -27255,780,13,8.0,12,0,2007-09-09 12:00:00 -27256,780,19,1.0,17,0,2007-09-09 12:00:00 -27257,780,0,92.0,1,3,2007-09-09 12:00:00 -27258,780,1,52.0,5,0,2007-09-09 12:00:00 -27259,780,7,74.0,3,3,2007-09-09 12:00:00 -27260,780,8,33.0,6,0,2007-09-09 12:00:00 -27261,780,28,0.0,24,0,2007-09-09 12:00:00 -27262,780,25,0.0,19,0,2007-09-09 12:00:00 -27263,780,18,0.0,20,0,2007-09-09 12:00:00 -27264,780,15,0.0,21,0,2007-09-09 12:00:00 -27265,780,3,89.0,2,4,2007-09-09 12:00:00 -27266,780,24,13.0,9,0,2007-09-09 12:00:00 -27267,780,12,69.0,4,3,2007-09-09 12:00:00 -27268,780,14,7.0,13,0,2007-09-09 12:00:00 -27269,780,4,21.0,7,0,2007-09-09 12:00:00 -27270,780,20,17.0,8,0,2007-09-09 12:00:00 -27271,780,10,4.0,15,0,2007-09-09 12:00:00 -27272,780,16,8.0,11,0,2007-09-09 12:00:00 -27273,780,23,0.0,23,0,2007-09-09 12:00:00 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-27297,781,26,0.0,23,0,2007-09-16 12:00:00 -27298,781,13,8.0,12,0,2007-09-16 12:00:00 -27299,781,19,1.0,17,0,2007-09-16 12:00:00 -27300,781,28,0.0,24,0,2007-09-16 12:00:00 -27301,781,25,0.0,19,0,2007-09-16 12:00:00 -27302,782,3,95.0,2,4,2007-09-30 04:30:00 -27303,782,20,21.0,8,0,2007-09-30 04:30:00 -27304,782,12,80.0,4,3,2007-09-30 04:30:00 -27305,782,17,2.0,16,0,2007-09-30 04:30:00 -27306,782,4,30.0,7,0,2007-09-30 04:30:00 -27307,782,21,0.0,19,0,2007-09-30 04:30:00 -27308,782,10,4.0,15,0,2007-09-30 04:30:00 -27309,782,16,10.0,12,0,2007-09-30 04:30:00 -27310,782,23,0.0,20,0,2007-09-30 04:30:00 -27311,782,18,0.0,22,0,2007-09-30 04:30:00 -27312,782,1,56.0,5,0,2007-09-30 04:30:00 -27313,782,24,13.0,10,0,2007-09-30 04:30:00 -27314,782,0,107.0,1,4,2007-09-30 04:30:00 -27315,782,7,90.0,3,4,2007-09-30 04:30:00 -27316,782,2,15.0,9,0,2007-09-30 04:30:00 -27317,782,22,5.0,14,0,2007-09-30 04:30:00 -27318,782,15,1.0,17,0,2007-09-30 04:30:00 -27319,782,14,7.0,13,0,2007-09-30 04:30:00 -27320,782,25,0.0,21,0,2007-09-30 04:30:00 -27321,782,13,13.0,11,0,2007-09-30 04:30:00 -27322,782,28,0.0,23,0,2007-09-30 04:30:00 -27323,782,26,0.0,24,0,2007-09-30 04:30:00 -27324,782,8,35.0,6,0,2007-09-30 04:30:00 -27325,782,19,1.0,18,0,2007-09-30 04:30:00 -27326,783,20,21.0,8,0,2007-10-07 06:00:00 -27327,783,0,107.0,1,4,2007-10-07 06:00:00 -27328,783,3,103.0,2,4,2007-10-07 06:00:00 -27329,783,12,86.0,4,3,2007-10-07 06:00:00 -27330,783,22,5.0,16,0,2007-10-07 06:00:00 -27331,783,14,7.0,13,0,2007-10-07 06:00:00 -27332,783,21,0.0,20,0,2007-10-07 06:00:00 -27333,783,10,4.0,17,0,2007-10-07 06:00:00 -27334,783,16,10.0,12,0,2007-10-07 06:00:00 -27335,783,4,30.0,7,0,2007-10-07 06:00:00 -27336,783,17,6.0,15,0,2007-10-07 06:00:00 -27337,783,2,15.0,9,0,2007-10-07 06:00:00 -27338,783,7,100.0,3,5,2007-10-07 06:00:00 -27339,783,23,3.0,18,0,2007-10-07 06:00:00 -27340,783,28,0.0,23,0,2007-10-07 06:00:00 -27341,783,19,6.0,14,0,2007-10-07 06:00:00 -27342,783,13,14.0,10,0,2007-10-07 06:00:00 -27343,783,1,58.0,5,0,2007-10-07 06:00:00 -27344,783,8,35.0,6,0,2007-10-07 06:00:00 -27345,783,25,0.0,21,0,2007-10-07 06:00:00 -27346,783,24,13.0,11,0,2007-10-07 06:00:00 -27347,783,15,1.0,19,0,2007-10-07 06:00:00 -27348,783,18,0.0,22,0,2007-10-07 06:00:00 -27349,783,26,0.0,24,0,2007-10-07 06:00:00 -27350,784,21,0.0,20,0,2007-10-21 16:00:00 -27351,784,3,109.0,3,4,2007-10-21 16:00:00 -27352,784,1,61.0,5,0,2007-10-21 16:00:00 -27353,784,12,94.0,4,3,2007-10-21 16:00:00 -27354,784,2,20.0,9,0,2007-10-21 16:00:00 -27355,784,22,5.0,16,0,2007-10-21 16:00:00 -27356,784,14,8.0,13,0,2007-10-21 16:00:00 -27357,784,4,30.0,7,0,2007-10-21 16:00:00 -27358,784,10,4.0,17,0,2007-10-21 16:00:00 -27359,784,0,109.0,2,4,2007-10-21 16:00:00 -27360,784,23,3.0,18,0,2007-10-21 16:00:00 -27361,784,17,6.0,15,0,2007-10-21 16:00:00 -27362,784,18,0.0,23,0,2007-10-21 16:00:00 -27363,784,15,1.0,19,0,2007-10-21 16:00:00 -27364,784,24,13.0,11,0,2007-10-21 16:00:00 -27365,784,25,0.0,21,0,2007-10-21 16:00:00 -27366,784,8,39.0,6,0,2007-10-21 16:00:00 -27367,784,26,0.0,25,0,2007-10-21 16:00:00 -27368,784,13,14.0,10,0,2007-10-21 16:00:00 -27369,784,19,6.0,14,0,2007-10-21 16:00:00 -27370,784,5,0.0,22,0,2007-10-21 16:00:00 -27371,784,7,110.0,1,6,2007-10-21 16:00:00 -27372,784,20,21.0,8,0,2007-10-21 16:00:00 -27373,784,16,10.0,12,0,2007-10-21 16:00:00 -27374,784,28,0.0,24,0,2007-10-21 16:00:00 -27375,785,0,10.0,1,1,2008-03-16 04:30:00 -27376,785,4,4.0,5,0,2008-03-16 04:30:00 -27377,785,3,5.0,4,0,2008-03-16 04:30:00 -27378,785,1,8.0,2,0,2008-03-16 04:30:00 -27379,785,5,3.0,6,0,2008-03-16 04:30:00 -27380,785,7,1.0,8,0,2008-03-16 04:30:00 -27381,785,6,2.0,7,0,2008-03-16 04:30:00 -27382,785,2,6.0,3,0,2008-03-16 04:30:00 -27383,786,21,0.0,16,0,2008-03-23 07:00:00 -27384,786,8,8.0,5,0,2008-03-23 07:00:00 -27385,786,7,11.0,2,1,2008-03-23 07:00:00 -27386,786,14,5.0,8,0,2008-03-23 07:00:00 -27387,786,16,2.0,11,0,2008-03-23 07:00:00 -27388,786,13,0.0,12,0,2008-03-23 07:00:00 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-27757,803,6,1.0,8,0,2009-03-29 06:00:00 -27758,803,21,8.0,2,0,2009-03-29 06:00:00 -27759,803,20,0.0,11,0,2009-03-29 06:00:00 -27760,803,1,0.0,10,0,2009-03-29 06:00:00 -27761,803,19,0.0,13,0,2009-03-29 06:00:00 -27762,803,8,0.0,14,0,2009-03-29 06:00:00 -27763,803,7,0.0,15,0,2009-03-29 06:00:00 -27764,803,16,0.0,12,0,2009-03-29 06:00:00 -27765,803,17,10.0,1,1,2009-03-29 06:00:00 -27766,804,3,4.0,6,0,2009-04-05 09:00:00 -27767,804,9,8.0,4,0,2009-04-05 09:00:00 -27768,804,66,2.0,8,0,2009-04-05 09:00:00 -27769,804,6,1.0,11,0,2009-04-05 09:00:00 -27770,804,15,0.0,12,0,2009-04-05 09:00:00 -27771,804,2,3.5,7,0,2009-04-05 09:00:00 -27772,804,14,8.5,3,0,2009-04-05 09:00:00 -27773,804,21,10.0,2,0,2009-04-05 09:00:00 -27774,804,17,15.0,1,2,2009-04-05 09:00:00 -27775,804,0,1.0,10,0,2009-04-05 09:00:00 -27776,804,1,4.0,5,0,2009-04-05 09:00:00 -27777,804,20,0.0,14,0,2009-04-05 09:00:00 -27778,804,12,0.0,13,0,2009-04-05 09:00:00 -27779,804,19,0.0,16,0,2009-04-05 09:00:00 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-27803,805,4,4.0,9,0,2009-04-19 07:00:00 -27804,805,9,10.0,4,0,2009-04-19 07:00:00 -27805,805,8,0.0,19,0,2009-04-19 07:00:00 -27806,806,15,0.0,16,0,2009-04-26 12:00:00 -27807,806,6,1.0,14,0,2009-04-26 12:00:00 -27808,806,66,3.0,13,0,2009-04-26 12:00:00 -27809,806,2,3.5,11,0,2009-04-26 12:00:00 -27810,806,9,12.0,5,0,2009-04-26 12:00:00 -27811,806,16,9.5,6,0,2009-04-26 12:00:00 -27812,806,17,31.0,1,3,2009-04-26 12:00:00 -27813,806,0,9.0,7,0,2009-04-26 12:00:00 -27814,806,1,4.0,9,0,2009-04-26 12:00:00 -27815,806,21,19.0,2,0,2009-04-26 12:00:00 -27816,806,3,5.0,8,0,2009-04-26 12:00:00 -27817,806,20,0.0,18,0,2009-04-26 12:00:00 -27818,806,14,14.5,4,0,2009-04-26 12:00:00 -27819,806,8,0.0,20,0,2009-04-26 12:00:00 -27820,806,7,3.0,12,0,2009-04-26 12:00:00 -27821,806,12,0.0,15,0,2009-04-26 12:00:00 -27822,806,11,0.0,17,0,2009-04-26 12:00:00 -27823,806,5,0.0,19,0,2009-04-26 12:00:00 -27824,806,4,4.0,10,0,2009-04-26 12:00:00 -27825,806,19,18.0,3,1,2009-04-26 12:00:00 -27826,807,1,6.0,9,0,2009-05-10 12:00:00 -27827,807,20,0.0,19,0,2009-05-10 12:00:00 -27828,807,16,15.5,4,0,2009-05-10 12:00:00 -27829,807,19,23.0,3,1,2009-05-10 12:00:00 -27830,807,8,0.0,18,0,2009-05-10 12:00:00 -27831,807,4,4.0,11,0,2009-05-10 12:00:00 -27832,807,0,9.0,7,0,2009-05-10 12:00:00 -27833,807,12,3.0,12,0,2009-05-10 12:00:00 -27834,807,5,0.0,20,0,2009-05-10 12:00:00 -27835,807,11,0.0,17,0,2009-05-10 12:00:00 -27836,807,15,0.0,16,0,2009-05-10 12:00:00 -27837,807,7,3.0,13,0,2009-05-10 12:00:00 -27838,807,6,1.0,15,0,2009-05-10 12:00:00 -27839,807,21,27.0,2,0,2009-05-10 12:00:00 -27840,807,2,4.5,10,0,2009-05-10 12:00:00 -27841,807,3,9.0,8,0,2009-05-10 12:00:00 -27842,807,9,12.0,6,0,2009-05-10 12:00:00 -27843,807,14,14.5,5,0,2009-05-10 12:00:00 -27844,807,66,3.0,14,0,2009-05-10 12:00:00 -27845,807,17,41.0,1,4,2009-05-10 12:00:00 -27846,808,20,0.0,16,0,2009-05-24 12:00:00 -27847,808,1,6.0,12,0,2009-05-24 12:00:00 -27848,808,15,0.0,17,0,2009-05-24 12:00:00 -27849,808,6,2.0,15,0,2009-05-24 12:00:00 -27850,808,2,7.5,11,0,2009-05-24 12:00:00 -27851,808,9,12.0,6,0,2009-05-24 12:00:00 -27852,808,3,11.0,7,0,2009-05-24 12:00:00 -27853,808,16,19.5,4,0,2009-05-24 12:00:00 -27854,808,14,14.5,5,0,2009-05-24 12:00:00 -27855,808,21,35.0,2,0,2009-05-24 12:00:00 -27856,808,66,3.0,14,0,2009-05-24 12:00:00 -27857,808,19,23.0,3,1,2009-05-24 12:00:00 -27858,808,8,0.0,19,0,2009-05-24 12:00:00 -27859,808,5,0.0,20,0,2009-05-24 12:00:00 -27860,808,4,4.0,13,0,2009-05-24 12:00:00 -27861,808,17,51.0,1,5,2009-05-24 12:00:00 -27862,808,0,9.0,9,0,2009-05-24 12:00:00 -27863,808,11,0.0,18,0,2009-05-24 12:00:00 -27864,808,12,8.0,10,0,2009-05-24 12:00:00 -27865,808,7,9.0,8,0,2009-05-24 12:00:00 -27866,809,6,2.0,16,0,2009-06-07 12:00:00 -27867,809,9,13.0,6,0,2009-06-07 12:00:00 -27868,809,21,35.0,2,0,2009-06-07 12:00:00 -27869,809,19,29.0,3,1,2009-06-07 12:00:00 -27870,809,3,11.0,9,0,2009-06-07 12:00:00 -27871,809,66,3.0,14,0,2009-06-07 12:00:00 -27872,809,14,19.5,5,0,2009-06-07 12:00:00 -27873,809,12,11.0,8,0,2009-06-07 12:00:00 -27874,809,20,0.0,17,0,2009-06-07 12:00:00 -27875,809,17,61.0,1,6,2009-06-07 12:00:00 -27876,809,15,0.0,18,0,2009-06-07 12:00:00 -27877,809,2,11.5,7,0,2009-06-07 12:00:00 -27878,809,1,6.0,12,0,2009-06-07 12:00:00 -27879,809,4,4.0,13,0,2009-06-07 12:00:00 -27880,809,8,2.0,15,0,2009-06-07 12:00:00 -27881,809,7,9.0,10,0,2009-06-07 12:00:00 -27882,809,11,0.0,19,0,2009-06-07 12:00:00 -27883,809,5,0.0,20,0,2009-06-07 12:00:00 -27884,809,0,9.0,11,0,2009-06-07 12:00:00 -27885,809,16,27.5,4,0,2009-06-07 12:00:00 -27886,810,66,3.0,14,0,2009-06-21 12:00:00 -27887,810,19,39.0,3,2,2009-06-21 12:00:00 -27888,810,21,41.0,2,0,2009-06-21 12:00:00 -27889,810,9,13.0,8,0,2009-06-21 12:00:00 -27890,810,6,2.0,16,0,2009-06-21 12:00:00 -27891,810,1,6.0,12,0,2009-06-21 12:00:00 -27892,810,16,35.5,4,0,2009-06-21 12:00:00 -27893,810,8,2.0,15,0,2009-06-21 12:00:00 -27894,810,7,10.0,10,0,2009-06-21 12:00:00 -27895,810,4,4.0,13,0,2009-06-21 12:00:00 -27896,810,5,0.0,20,0,2009-06-21 12:00:00 -27897,810,0,9.0,11,0,2009-06-21 12:00:00 -27898,810,14,21.5,5,0,2009-06-21 12:00:00 -27899,810,20,0.0,17,0,2009-06-21 12:00:00 -27900,810,15,0.0,18,0,2009-06-21 12:00:00 -27901,810,12,16.0,6,0,2009-06-21 12:00:00 -27902,810,2,15.5,7,0,2009-06-21 12:00:00 -27903,810,3,11.0,9,0,2009-06-21 12:00:00 -27904,810,11,0.0,19,0,2009-06-21 12:00:00 -27905,810,17,64.0,1,6,2009-06-21 12:00:00 -27906,811,66,3.0,14,0,2009-07-12 12:00:00 -27907,811,12,22.0,5,0,2009-07-12 12:00:00 -27908,811,6,2.0,16,0,2009-07-12 12:00:00 -27909,811,15,0.0,18,0,2009-07-12 12:00:00 -27910,811,11,0.0,19,0,2009-07-12 12:00:00 -27911,811,4,5.0,13,0,2009-07-12 12:00:00 -27912,811,0,9.0,11,0,2009-07-12 12:00:00 -27913,811,2,20.5,7,0,2009-07-12 12:00:00 -27914,811,3,13.0,9,0,2009-07-12 12:00:00 -27915,811,5,0.0,20,0,2009-07-12 12:00:00 -27916,811,14,21.5,6,0,2009-07-12 12:00:00 -27917,811,9,13.0,8,0,2009-07-12 12:00:00 -27918,811,7,10.0,10,0,2009-07-12 12:00:00 -27919,811,8,2.0,15,0,2009-07-12 12:00:00 -27920,811,19,47.0,2,2,2009-07-12 12:00:00 -27921,811,1,6.0,12,0,2009-07-12 12:00:00 -27922,811,20,0.0,17,0,2009-07-12 12:00:00 -27923,811,16,45.5,3,1,2009-07-12 12:00:00 -27924,811,21,44.0,4,0,2009-07-12 12:00:00 -27925,811,17,68.0,1,6,2009-07-12 12:00:00 -27926,812,21,44.0,4,0,2009-07-26 12:00:00 -27927,812,17,70.0,1,6,2009-07-26 12:00:00 -27928,812,152,0.0,21,0,2009-07-26 12:00:00 -27929,812,0,19.0,8,1,2009-07-26 12:00:00 -27930,812,4,9.0,12,0,2009-07-26 12:00:00 -27931,812,5,0.0,18,0,2009-07-26 12:00:00 -27932,812,12,22.0,7,0,2009-07-26 12:00:00 -27933,812,7,18.0,9,0,2009-07-26 12:00:00 -27934,812,8,2.0,15,0,2009-07-26 12:00:00 -27935,812,19,47.0,3,2,2009-07-26 12:00:00 -27936,812,11,0.0,20,0,2009-07-26 12:00:00 -27937,812,20,0.0,17,0,2009-07-26 12:00:00 -27938,812,1,6.0,13,0,2009-07-26 12:00:00 -27939,812,15,0.0,19,0,2009-07-26 12:00:00 -27940,812,6,2.0,16,0,2009-07-26 12:00:00 -27941,812,66,3.0,14,0,2009-07-26 12:00:00 -27942,812,2,25.5,5,0,2009-07-26 12:00:00 -27943,812,3,13.0,11,0,2009-07-26 12:00:00 -27944,812,9,16.0,10,0,2009-07-26 12:00:00 -27945,812,16,51.5,2,1,2009-07-26 12:00:00 -27946,812,14,22.5,6,0,2009-07-26 12:00:00 -27947,813,8,3.0,14,0,2009-08-23 12:00:00 -27948,813,7,24.0,7,0,2009-08-23 12:00:00 -27949,813,12,22.0,9,0,2009-08-23 12:00:00 -27950,813,5,0.0,19,0,2009-08-23 12:00:00 -27951,813,68,0.0,23,0,2009-08-23 12:00:00 -27952,813,152,0.0,21,0,2009-08-23 12:00:00 -27953,813,153,0.0,22,0,2009-08-23 12:00:00 -27954,813,19,47.0,4,2,2009-08-23 12:00:00 -27955,813,0,27.0,6,1,2009-08-23 12:00:00 -27956,813,16,51.5,3,1,2009-08-23 12:00:00 -27957,813,4,14.0,12,0,2009-08-23 12:00:00 -27958,813,1,6.0,13,0,2009-08-23 12:00:00 -27959,813,20,0.0,17,0,2009-08-23 12:00:00 -27960,813,17,72.0,1,6,2009-08-23 12:00:00 -27961,813,21,54.0,2,1,2009-08-23 12:00:00 -27962,813,14,22.5,8,0,2009-08-23 12:00:00 -27963,813,9,16.0,10,0,2009-08-23 12:00:00 -27964,813,11,0.0,20,0,2009-08-23 12:00:00 -27965,813,2,29.5,5,0,2009-08-23 12:00:00 -27966,813,66,3.0,15,0,2009-08-23 12:00:00 -27967,813,6,2.0,16,0,2009-08-23 12:00:00 -27968,813,3,16.0,11,0,2009-08-23 12:00:00 -27969,813,15,0.0,18,0,2009-08-23 12:00:00 -27970,814,68,0.0,21,0,2009-08-30 12:00:00 -27971,814,153,0.0,23,0,2009-08-30 12:00:00 -27972,814,152,0.0,22,0,2009-08-30 12:00:00 -27973,814,0,27.0,7,1,2009-08-30 12:00:00 -27974,814,4,17.0,10,0,2009-08-30 12:00:00 -27975,814,5,0.0,19,0,2009-08-30 12:00:00 -27976,814,11,0.0,20,0,2009-08-30 12:00:00 -27977,814,7,34.0,5,1,2009-08-30 12:00:00 -27978,814,8,8.0,15,0,2009-08-30 12:00:00 -27979,814,19,53.0,3,2,2009-08-30 12:00:00 -27980,814,12,22.0,9,0,2009-08-30 12:00:00 -27981,814,1,10.0,13,0,2009-08-30 12:00:00 -27982,814,20,8.0,14,0,2009-08-30 12:00:00 -27983,814,17,72.0,1,6,2009-08-30 12:00:00 -27984,814,21,56.0,2,1,2009-08-30 12:00:00 -27985,814,14,22.5,8,0,2009-08-30 12:00:00 -27986,814,9,16.0,11,0,2009-08-30 12:00:00 -27987,814,16,51.5,4,1,2009-08-30 12:00:00 -27988,814,2,30.5,6,0,2009-08-30 12:00:00 -27989,814,66,3.0,16,0,2009-08-30 12:00:00 -27990,814,6,2.0,17,0,2009-08-30 12:00:00 -27991,814,15,0.0,18,0,2009-08-30 12:00:00 -27992,814,3,16.0,12,0,2009-08-30 12:00:00 -27993,815,19,54.0,3,2,2009-09-13 12:00:00 -27994,815,153,0.0,22,0,2009-09-13 12:00:00 -27995,815,152,0.0,23,0,2009-09-13 12:00:00 -27996,815,0,27.0,7,1,2009-09-13 12:00:00 -27997,815,4,20.0,10,0,2009-09-13 12:00:00 -27998,815,5,0.0,19,0,2009-09-13 12:00:00 -27999,815,11,0.0,20,0,2009-09-13 12:00:00 -28000,815,12,22.0,9,0,2009-09-13 12:00:00 -28001,815,23,0.0,24,0,2009-09-13 12:00:00 -28002,815,8,8.0,15,0,2009-09-13 12:00:00 -28003,815,68,0.0,21,0,2009-09-13 12:00:00 -28004,815,7,40.0,5,1,2009-09-13 12:00:00 -28005,815,1,12.0,13,0,2009-09-13 12:00:00 -28006,815,20,8.0,14,0,2009-09-13 12:00:00 -28007,815,17,80.0,1,6,2009-09-13 12:00:00 -28008,815,21,66.0,2,2,2009-09-13 12:00:00 -28009,815,14,22.5,8,0,2009-09-13 12:00:00 -28010,815,9,16.0,12,0,2009-09-13 12:00:00 -28011,815,16,51.5,4,1,2009-09-13 12:00:00 -28012,815,2,30.5,6,0,2009-09-13 12:00:00 -28013,815,15,5.0,16,0,2009-09-13 12:00:00 -28014,815,3,20.0,11,0,2009-09-13 12:00:00 -28015,815,66,3.0,17,0,2009-09-13 12:00:00 -28016,815,6,2.0,18,0,2009-09-13 12:00:00 -28017,816,5,0.0,19,0,2009-09-27 12:00:00 -28018,816,23,0.0,22,0,2009-09-27 12:00:00 -28019,816,68,0.0,21,0,2009-09-27 12:00:00 -28020,816,153,0.0,23,0,2009-09-27 12:00:00 -28021,816,152,0.0,24,0,2009-09-27 12:00:00 -28022,816,0,37.0,6,2,2009-09-27 12:00:00 -28023,816,4,22.0,12,0,2009-09-27 12:00:00 -28024,816,11,0.0,20,0,2009-09-27 12:00:00 -28025,816,7,40.0,5,1,2009-09-27 12:00:00 -28026,816,8,9.0,14,0,2009-09-27 12:00:00 -28027,816,19,59.0,3,2,2009-09-27 12:00:00 -28028,816,12,22.0,11,0,2009-09-27 12:00:00 -28029,816,20,8.0,15,0,2009-09-27 12:00:00 -28030,816,1,12.0,13,0,2009-09-27 12:00:00 -28031,816,15,5.0,16,0,2009-09-27 12:00:00 -28032,816,6,2.0,18,0,2009-09-27 12:00:00 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-28079,818,1,15.0,14,0,2009-10-18 16:00:00 -28080,818,15,5.0,16,0,2009-10-18 16:00:00 -28081,818,66,5.0,17,0,2009-10-18 16:00:00 -28082,818,2,34.5,7,0,2009-10-18 16:00:00 -28083,818,3,26.0,9,0,2009-10-18 16:00:00 -28084,818,9,24.0,10,0,2009-10-18 16:00:00 -28085,818,14,30.5,8,0,2009-10-18 16:00:00 -28086,818,21,72.0,3,2,2009-10-18 16:00:00 -28087,818,17,89.0,1,6,2009-10-18 16:00:00 -28088,818,19,74.0,2,3,2009-10-18 16:00:00 -28089,818,6,2.0,18,0,2009-10-18 16:00:00 -28090,819,154,3.0,18,0,2009-11-01 11:00:00 -28091,819,23,0.0,22,0,2009-11-01 11:00:00 -28092,819,4,22.0,12,0,2009-11-01 11:00:00 -28093,819,152,0.0,24,0,2009-11-01 11:00:00 -28094,819,153,0.0,23,0,2009-11-01 11:00:00 -28095,819,17,95.0,1,6,2009-11-01 11:00:00 -28096,819,0,49.0,5,2,2009-11-01 11:00:00 -28097,819,21,77.0,3,2,2009-11-01 11:00:00 -28098,819,14,32.5,8,0,2009-11-01 11:00:00 -28099,819,9,24.0,10,0,2009-11-01 11:00:00 -28100,819,3,26.0,9,0,2009-11-01 11:00:00 -28101,819,2,34.5,7,0,2009-11-01 11:00:00 -28102,819,66,6.0,16,0,2009-11-01 11:00:00 -28103,819,5,0.0,20,0,2009-11-01 11:00:00 -28104,819,15,5.0,17,0,2009-11-01 11:00:00 -28105,819,1,19.0,13,0,2009-11-01 11:00:00 -28106,819,20,8.0,15,0,2009-11-01 11:00:00 -28107,819,16,69.5,4,2,2009-11-01 11:00:00 -28108,819,19,84.0,2,4,2009-11-01 11:00:00 -28109,819,8,17.0,14,0,2009-11-01 11:00:00 -28110,819,7,48.0,6,1,2009-11-01 11:00:00 -28111,819,68,0.0,25,0,2009-11-01 11:00:00 -28112,819,11,0.0,21,0,2009-11-01 11:00:00 -28113,819,6,2.0,19,0,2009-11-01 11:00:00 -28114,819,12,22.0,11,0,2009-11-01 11:00:00 From e376201446e2e732f276033381653116d8e01aa6 Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Sun, 18 Jan 2026 02:51:19 +0700 Subject: [PATCH 36/42] :mute:chore: fix create db into postgres --- scripts/create_stack_subset.sh | 466 ----------------- scripts/import_relbench.sh | 823 ++++++++++++++++++++++++++++--- scripts/import_relbench_stack.sh | 449 ----------------- 3 files changed, 757 insertions(+), 981 deletions(-) delete mode 100644 scripts/create_stack_subset.sh delete mode 100644 scripts/import_relbench_stack.sh diff --git a/scripts/create_stack_subset.sh b/scripts/create_stack_subset.sh deleted file mode 100644 index 000bb3e8..00000000 --- a/scripts/create_stack_subset.sh +++ /dev/null @@ -1,466 +0,0 @@ -#!/bin/bash - -# ===================================================== -# Tạo subset database stack-2000 (~2000 records mỗi bảng) -# Giữ nguyên relationships và lấy dữ liệu liên tục 30 ngày -# ĐẢM BẢO REFERENTIAL INTEGRITY -# ===================================================== - -set -e - -CONTAINER_NAME="plexe-clone-postgres-1" -SOURCE_DB="stack" -TARGET_DB="stack-2000" -DB_USER="mlflow" - -# Tham số - mỗi bảng ~2000 records -RECORDS_PER_TABLE=2000 # Số records mục tiêu cho mỗi bảng -TIME_WINDOW_DAYS=60 # Lấy dữ liệu trong 30 ngày liên tục - -echo "=========================================" -echo "Create Stack-2000 Subset Database" -echo "=========================================" -echo "Source DB: $SOURCE_DB" -echo "Target DB: $TARGET_DB" -echo "Records per table: ~$RECORDS_PER_TABLE" -echo "Time Window: $TIME_WINDOW_DAYS days" -echo "=========================================" -echo "" - -# Kiểm tra container -echo "🔍 Checking container..." -if ! docker ps | grep -q $CONTAINER_NAME; then - echo "❌ Container not running!" - exit 1 -fi -echo "✓ Container is running" -echo "" - -# Step 1: Tìm time window với nhiều activity -echo "📝 Step 1: Finding optimal time window..." -cat > /tmp/find_window.sql << 'EOSQL' --- Find 30-day window with good activity -WITH daily_counts AS ( - SELECT - DATE_TRUNC('day', creation_date) as day, - COUNT(*) as daily_count - FROM posts - WHERE creation_date IS NOT NULL - GROUP BY DATE_TRUNC('day', creation_date) -), -window_counts AS ( - SELECT - day as start_day, - SUM(daily_count) OVER (ORDER BY day ROWS BETWEEN CURRENT ROW AND 29 FOLLOWING) as window_count - FROM daily_counts -) -SELECT - to_char(start_day, 'YYYY-MM-DD') as start_date, - to_char(start_day + INTERVAL '30 days', 'YYYY-MM-DD') as end_date, - window_count -FROM window_counts -WHERE window_count >= 2000 -ORDER BY window_count ASC -LIMIT 1; -EOSQL - -docker cp /tmp/find_window.sql $CONTAINER_NAME:/tmp/ -TIME_WINDOW=$(docker exec -i $CONTAINER_NAME psql -U $DB_USER -d $SOURCE_DB -t -A -F'|' -f /tmp/find_window.sql | head -1) - -# Nếu không tìm được window phù hợp, lấy window có nhiều activity nhất -if [ -z "$TIME_WINDOW" ]; then - echo " Finding window with most activity..." - cat > /tmp/find_window2.sql << 'EOSQL' -WITH daily_counts AS ( - SELECT - DATE_TRUNC('day', creation_date) as day, - COUNT(*) as daily_count - FROM posts - WHERE creation_date IS NOT NULL - GROUP BY DATE_TRUNC('day', creation_date) -), -window_counts AS ( - SELECT - day as start_day, - SUM(daily_count) OVER (ORDER BY day ROWS BETWEEN CURRENT ROW AND 29 FOLLOWING) as window_count - FROM daily_counts -) -SELECT - to_char(start_day, 'YYYY-MM-DD') as start_date, - to_char(start_day + INTERVAL '30 days', 'YYYY-MM-DD') as end_date, - window_count -FROM window_counts -WHERE window_count IS NOT NULL -ORDER BY window_count DESC -LIMIT 1; -EOSQL - docker cp /tmp/find_window2.sql $CONTAINER_NAME:/tmp/ - TIME_WINDOW=$(docker exec -i $CONTAINER_NAME psql -U $DB_USER -d $SOURCE_DB -t -A -F'|' -f /tmp/find_window2.sql | head -1) -fi - -START_DATE=$(echo $TIME_WINDOW | cut -d'|' -f1) -END_DATE=$(echo $TIME_WINDOW | cut -d'|' -f2) -ACTIVITY=$(echo $TIME_WINDOW | cut -d'|' -f3) - -echo "✓ Selected time window:" -echo " Start: $START_DATE" -echo " End: $END_DATE" -echo " Posts in window: $ACTIVITY" -echo "" - -# Step 2: Extract subset với đảm bảo referential integrity, mỗi bảng ~2000 records -echo "📝 Step 2: Extracting subset data (~$RECORDS_PER_TABLE per table)..." -cat > /tmp/extract_subset.sql << EOSQL --- ===================================================== --- STRATEGY: ~2000 records per table with referential integrity --- ===================================================== - --- Step 2.1: Get 2000 posts in time window -CREATE TEMP TABLE base_posts AS -SELECT id, owner_user_id, accepted_answer_id, parent_id -FROM posts -WHERE creation_date >= '$START_DATE'::timestamp - AND creation_date < '$END_DATE'::timestamp -ORDER BY creation_date -LIMIT $RECORDS_PER_TABLE; - --- Step 2.2: Iteratively add parent posts and accepted answers -CREATE TEMP TABLE all_post_ids (id INTEGER PRIMARY KEY); - --- Insert base posts -INSERT INTO all_post_ids SELECT id FROM base_posts; - --- Add parent posts and accepted answers (max 3 iterations) -DO \$\$ -DECLARE - new_count INTEGER; -BEGIN - FOR i IN 1..3 LOOP - INSERT INTO all_post_ids (id) - SELECT DISTINCT p.parent_id - FROM posts p - WHERE p.id IN (SELECT id FROM all_post_ids) - AND p.parent_id IS NOT NULL - AND p.parent_id NOT IN (SELECT id FROM all_post_ids) - ON CONFLICT DO NOTHING; - - INSERT INTO all_post_ids (id) - SELECT DISTINCT p.accepted_answer_id - FROM posts p - WHERE p.id IN (SELECT id FROM all_post_ids) - AND p.accepted_answer_id IS NOT NULL - AND p.accepted_answer_id NOT IN (SELECT id FROM all_post_ids) - ON CONFLICT DO NOTHING; - - GET DIAGNOSTICS new_count = ROW_COUNT; - IF new_count = 0 THEN - EXIT; - END IF; - END LOOP; -END \$\$; - --- Step 2.3: Get 2000 users (prioritize those with posts, then add more) -CREATE TEMP TABLE all_user_ids AS -SELECT DISTINCT owner_user_id as id -FROM posts -WHERE id IN (SELECT id FROM all_post_ids) - AND owner_user_id IS NOT NULL -LIMIT $RECORDS_PER_TABLE; - --- If we have fewer than 2000 users from posts, add more from the time window -INSERT INTO all_user_ids -SELECT DISTINCT u.id -FROM users u -WHERE u.creation_date >= '$START_DATE'::timestamp - AND u.creation_date < '$END_DATE'::timestamp - AND u.id NOT IN (SELECT id FROM all_user_ids) -LIMIT ($RECORDS_PER_TABLE - (SELECT COUNT(*) FROM all_user_ids)); - --- Show what we collected -\echo 'Collected IDs:' -SELECT 'posts' as type, COUNT(*) as count FROM all_post_ids -UNION ALL -SELECT 'users', COUNT(*) FROM all_user_ids; - --- Step 2.4: Export users (limit 2000) -\copy (SELECT * FROM users WHERE id IN (SELECT id FROM all_user_ids) LIMIT $RECORDS_PER_TABLE) TO '/tmp/subset_users.csv' CSV HEADER; - --- Step 2.5: Export posts (already limited to ~2000) - nullify missing FKs -\copy (SELECT id, CASE WHEN owner_user_id IN (SELECT id FROM all_user_ids) THEN owner_user_id ELSE NULL END as owner_user_id, post_type_id, CASE WHEN accepted_answer_id IN (SELECT id FROM all_post_ids) THEN accepted_answer_id ELSE NULL END as accepted_answer_id, CASE WHEN parent_id IN (SELECT id FROM all_post_ids) THEN parent_id ELSE NULL END as parent_id, owner_display_name, title, tags, content_license, body, creation_date FROM posts WHERE id IN (SELECT id FROM all_post_ids)) TO '/tmp/subset_posts.csv' CSV HEADER; - --- Step 2.6: Export votes (limit 2000) - only valid FKs -\copy (SELECT id, CASE WHEN user_id IN (SELECT id FROM all_user_ids) THEN user_id ELSE NULL END as user_id, post_id, vote_type_id, creation_date FROM votes WHERE post_id IN (SELECT id FROM all_post_ids) ORDER BY creation_date LIMIT $RECORDS_PER_TABLE) TO '/tmp/subset_votes.csv' CSV HEADER; - --- Step 2.7: Export comments (limit 2000) - only valid FKs -\copy (SELECT id, post_id, CASE WHEN user_id IN (SELECT id FROM all_user_ids) THEN user_id ELSE NULL END as user_id, content_license, user_display_name, text, creation_date FROM comments WHERE post_id IN (SELECT id FROM all_post_ids) ORDER BY creation_date LIMIT $RECORDS_PER_TABLE) TO '/tmp/subset_comments.csv' CSV HEADER; - --- Step 2.8: Export badges (limit 2000) - only for users in subset -\copy (SELECT * FROM badges WHERE user_id IN (SELECT id FROM all_user_ids) ORDER BY date LIMIT $RECORDS_PER_TABLE) TO '/tmp/subset_badges.csv' CSV HEADER; - --- Step 2.9: Export post_links (limit 2000) - only where BOTH posts exist -\copy (SELECT * FROM post_links WHERE post_id IN (SELECT id FROM all_post_ids) AND related_post_id IN (SELECT id FROM all_post_ids) ORDER BY creation_date LIMIT $RECORDS_PER_TABLE) TO '/tmp/subset_post_links.csv' CSV HEADER; - --- Step 2.10: Export post_history (limit 2000) - only valid FKs -\copy (SELECT id, post_id, CASE WHEN user_id IN (SELECT id FROM all_user_ids) THEN user_id ELSE NULL END as user_id, post_history_type_id, user_display_name, content_license, revision_guid, text, comment, creation_date FROM post_history WHERE post_id IN (SELECT id FROM all_post_ids) ORDER BY creation_date LIMIT $RECORDS_PER_TABLE) TO '/tmp/subset_post_history.csv' CSV HEADER; - --- Show counts -\echo '' -\echo 'Exported record counts (target: $RECORDS_PER_TABLE each):' -\echo '(Note: Actual CSV exports are limited to $RECORDS_PER_TABLE)' -SELECT 'users' as table_name, LEAST(COUNT(*), $RECORDS_PER_TABLE) as count FROM users WHERE id IN (SELECT id FROM all_user_ids) -UNION ALL SELECT 'posts', LEAST(COUNT(*), $RECORDS_PER_TABLE) FROM all_post_ids -UNION ALL SELECT 'votes', LEAST(COUNT(*), $RECORDS_PER_TABLE) FROM votes WHERE post_id IN (SELECT id FROM all_post_ids) -UNION ALL SELECT 'comments', LEAST(COUNT(*), $RECORDS_PER_TABLE) FROM comments WHERE post_id IN (SELECT id FROM all_post_ids) -UNION ALL SELECT 'badges', LEAST(COUNT(*), $RECORDS_PER_TABLE) FROM badges WHERE user_id IN (SELECT id FROM all_user_ids) -UNION ALL SELECT 'post_links', LEAST(COUNT(*), $RECORDS_PER_TABLE) FROM post_links WHERE post_id IN (SELECT id FROM all_post_ids) AND related_post_id IN (SELECT id FROM all_post_ids) -UNION ALL SELECT 'post_history', LEAST(COUNT(*), $RECORDS_PER_TABLE) FROM post_history WHERE post_id IN (SELECT id FROM all_post_ids) -ORDER BY count DESC; -EOSQL - -docker cp /tmp/extract_subset.sql $CONTAINER_NAME:/tmp/ -docker exec -i $CONTAINER_NAME psql -U $DB_USER -d $SOURCE_DB -f /tmp/extract_subset.sql - -echo "✓ Data extracted to CSV files" -echo "" - -# Step 3: Create new database -echo "📝 Step 3: Creating new database..." -docker exec -i $CONTAINER_NAME psql -U $DB_USER -d postgres << EOSQL -DROP DATABASE IF EXISTS "stack-2000"; -CREATE DATABASE "stack-2000"; -EOSQL - -echo "✓ Database created" -echo "" - -# Step 4: Create schema in new database -echo "📝 Step 4: Creating schema..." -cat > /tmp/create_schema.sql << 'EOSQL' -CREATE TABLE users ( - id INTEGER PRIMARY KEY, - account_id INTEGER, - display_name VARCHAR(255), - location VARCHAR(500), - profile_image_url TEXT, - website_url TEXT, - about_me TEXT, - creation_date TIMESTAMP -); - -CREATE TABLE posts ( - id INTEGER PRIMARY KEY, - owner_user_id INTEGER, - post_type_id INTEGER, - accepted_answer_id INTEGER, - parent_id INTEGER, - owner_display_name VARCHAR(255), - title TEXT, - tags VARCHAR(500), - content_license VARCHAR(100), - body TEXT, - creation_date TIMESTAMP -); - -CREATE TABLE votes ( - id INTEGER PRIMARY KEY, - user_id INTEGER, - post_id INTEGER, - vote_type_id INTEGER, - creation_date TIMESTAMP -); - -CREATE TABLE comments ( - id INTEGER PRIMARY KEY, - post_id INTEGER, - user_id INTEGER, - content_license VARCHAR(100), - user_display_name VARCHAR(255), - text TEXT, - creation_date TIMESTAMP -); - -CREATE TABLE badges ( - id INTEGER PRIMARY KEY, - user_id INTEGER, - class INTEGER, - name VARCHAR(255), - tag_based BOOLEAN, - date TIMESTAMP -); - -CREATE TABLE post_links ( - id INTEGER PRIMARY KEY, - related_post_id INTEGER, - post_id INTEGER, - link_type_id INTEGER, - creation_date TIMESTAMP -); - -CREATE TABLE post_history ( - id INTEGER PRIMARY KEY, - post_id INTEGER, - user_id INTEGER, - post_history_type_id INTEGER, - user_display_name VARCHAR(255), - content_license VARCHAR(100), - revision_guid VARCHAR(50), - text TEXT, - comment TEXT, - creation_date TIMESTAMP -); -EOSQL - -docker cp /tmp/create_schema.sql $CONTAINER_NAME:/tmp/ -docker exec -i $CONTAINER_NAME psql -U $DB_USER -d $TARGET_DB -f /tmp/create_schema.sql - -echo "✓ Schema created" -echo "" - -# Step 5: Import data -echo "📝 Step 5: Importing data..." -cat > /tmp/import_subset.sql << 'EOSQL' -\copy users FROM '/tmp/subset_users.csv' CSV HEADER; -\copy posts FROM '/tmp/subset_posts.csv' CSV HEADER; -\copy votes FROM '/tmp/subset_votes.csv' CSV HEADER; -\copy comments FROM '/tmp/subset_comments.csv' CSV HEADER; -\copy badges FROM '/tmp/subset_badges.csv' CSV HEADER; -\copy post_links FROM '/tmp/subset_post_links.csv' CSV HEADER; -\copy post_history FROM '/tmp/subset_post_history.csv' CSV HEADER; -EOSQL - -docker cp /tmp/import_subset.sql $CONTAINER_NAME:/tmp/ -docker exec -i $CONTAINER_NAME psql -U $DB_USER -d $TARGET_DB -f /tmp/import_subset.sql - -echo "✓ Data imported" -echo "" - -# Step 6: Add constraints and indexes -echo "📝 Step 6: Adding foreign keys and indexes..." -cat > /tmp/add_constraints.sql << 'EOSQL' --- Foreign keys -ALTER TABLE posts ADD CONSTRAINT fk_posts_owner_user - FOREIGN KEY (owner_user_id) REFERENCES users(id); -ALTER TABLE posts ADD CONSTRAINT fk_posts_accepted_answer - FOREIGN KEY (accepted_answer_id) REFERENCES posts(id); -ALTER TABLE posts ADD CONSTRAINT fk_posts_parent - FOREIGN KEY (parent_id) REFERENCES posts(id); - -ALTER TABLE votes ADD CONSTRAINT fk_votes_user - FOREIGN KEY (user_id) REFERENCES users(id); -ALTER TABLE votes ADD CONSTRAINT fk_votes_post - FOREIGN KEY (post_id) REFERENCES posts(id); - -ALTER TABLE comments ADD CONSTRAINT fk_comments_post - FOREIGN KEY (post_id) REFERENCES posts(id); -ALTER TABLE comments ADD CONSTRAINT fk_comments_user - FOREIGN KEY (user_id) REFERENCES users(id); - -ALTER TABLE badges ADD CONSTRAINT fk_badges_user - FOREIGN KEY (user_id) REFERENCES users(id); - -ALTER TABLE post_links ADD CONSTRAINT fk_post_links_related_post - FOREIGN KEY (related_post_id) REFERENCES posts(id); -ALTER TABLE post_links ADD CONSTRAINT fk_post_links_post - FOREIGN KEY (post_id) REFERENCES posts(id); - -ALTER TABLE post_history ADD CONSTRAINT fk_post_history_post - FOREIGN KEY (post_id) REFERENCES posts(id); -ALTER TABLE post_history ADD CONSTRAINT fk_post_history_user - FOREIGN KEY (user_id) REFERENCES users(id); - --- Indexes -CREATE INDEX idx_posts_owner_user ON posts(owner_user_id) WHERE owner_user_id IS NOT NULL; -CREATE INDEX idx_posts_parent ON posts(parent_id) WHERE parent_id IS NOT NULL; -CREATE INDEX idx_posts_type ON posts(post_type_id); -CREATE INDEX idx_votes_user ON votes(user_id) WHERE user_id IS NOT NULL; -CREATE INDEX idx_votes_post ON votes(post_id); -CREATE INDEX idx_comments_post ON comments(post_id); -CREATE INDEX idx_comments_user ON comments(user_id) WHERE user_id IS NOT NULL; -CREATE INDEX idx_badges_user ON badges(user_id); -CREATE INDEX idx_post_links_related ON post_links(related_post_id); -CREATE INDEX idx_post_links_post ON post_links(post_id); -CREATE INDEX idx_post_history_post ON post_history(post_id); -CREATE INDEX idx_post_history_user ON post_history(user_id) WHERE user_id IS NOT NULL; -EOSQL - -docker cp /tmp/add_constraints.sql $CONTAINER_NAME:/tmp/ -docker exec -i $CONTAINER_NAME psql -U $DB_USER -d $TARGET_DB -f /tmp/add_constraints.sql - -echo "✓ Constraints and indexes added" -echo "" - -# Step 7: Show summary -echo "📊 Step 7: Summary..." -cat > /tmp/show_summary.sql << 'EOSQL' -\echo '=========================================' -\echo 'Record Counts' -\echo '=========================================' - -SELECT - table_name, - to_char(record_count, 'FM999,999') as records -FROM ( - SELECT 'users' as table_name, COUNT(*) as record_count FROM users - UNION ALL SELECT 'posts', COUNT(*) FROM posts - UNION ALL SELECT 'votes', COUNT(*) FROM votes - UNION ALL SELECT 'comments', COUNT(*) FROM comments - UNION ALL SELECT 'badges', COUNT(*) FROM badges - UNION ALL SELECT 'post_links', COUNT(*) FROM post_links - UNION ALL SELECT 'post_history', COUNT(*) FROM post_history -) t -ORDER BY record_count DESC; - -\echo '' -\echo '=========================================' -\echo 'Time Range' -\echo '=========================================' - -SELECT - to_char(MIN(creation_date), 'YYYY-MM-DD HH24:MI') as earliest, - to_char(MAX(creation_date), 'YYYY-MM-DD HH24:MI') as latest, - EXTRACT(DAY FROM (MAX(creation_date) - MIN(creation_date))) || ' days' as range -FROM posts -WHERE creation_date IS NOT NULL; - -\echo '' -\echo '=========================================' -\echo 'Total Records' -\echo '=========================================' - -SELECT - to_char( - (SELECT COUNT(*) FROM users) + - (SELECT COUNT(*) FROM posts) + - (SELECT COUNT(*) FROM votes) + - (SELECT COUNT(*) FROM comments) + - (SELECT COUNT(*) FROM badges) + - (SELECT COUNT(*) FROM post_links) + - (SELECT COUNT(*) FROM post_history), - 'FM999,999' - ) as total_records; -EOSQL - -docker cp /tmp/show_summary.sql $CONTAINER_NAME:/tmp/ -docker exec -i $CONTAINER_NAME psql -U $DB_USER -d $TARGET_DB -f /tmp/show_summary.sql - -# Cleanup temp files -rm -f /tmp/find_window.sql -rm -f /tmp/find_window2.sql -rm -f /tmp/extract_subset.sql -rm -f /tmp/create_schema.sql -rm -f /tmp/import_subset.sql -rm -f /tmp/add_constraints.sql -rm -f /tmp/show_summary.sql - -echo "" -echo "=========================================" -echo "✅ DONE!" -echo "=========================================" -echo "" -echo "Connect to subset database:" -echo " docker exec -it $CONTAINER_NAME psql -U $DB_USER -d stack-2000" -echo "" -echo "Verify data:" -echo " SELECT COUNT(*) FROM users;" -echo " SELECT MIN(creation_date), MAX(creation_date) FROM posts;" -echo "=========================================" \ No newline at end of file diff --git a/scripts/import_relbench.sh b/scripts/import_relbench.sh index 5ff50963..de0743cd 100644 --- a/scripts/import_relbench.sh +++ b/scripts/import_relbench.sh @@ -3,12 +3,17 @@ set -e CONTAINER_NAME="plexe-clone-postgres-1" DB_USER="mlflow" +DB_PASSWORD="mlflow" # Thêm password # Thiết lập file log LOG_DIR="./logs" mkdir -p "$LOG_DIR" LOG_FILE="$LOG_DIR/import_$(date +%Y%m%d_%H%M%S).log" +# Cấu hình sample size +SAMPLE_SIZE=5000 # Mục tiêu số bản ghi tổng +MAX_SEED_RECORDS=2000 # Số bản ghi seed ban đầu từ bảng chính + # Hàm log - ghi cả ra console và file log() { local message="[$(date '+%Y-%m-%d %H:%M:%S')] $1" @@ -49,7 +54,7 @@ cleanup() { print_header "Cleanup" print_info "Removing CSV files from container..." - if docker exec $CONTAINER_NAME bash -c "rm -f /tmp/*.csv /tmp/import_*.sql" 2>/dev/null; then + if docker exec $CONTAINER_NAME bash -c "rm -f /tmp/*.csv /tmp/import_*.sql /tmp/sample_*.sql" 2>/dev/null; then log "CSV files removed from container successfully" else log "Failed to remove CSV files from container (may not exist)" @@ -90,15 +95,18 @@ Arguments: Options: --db-name NAME Database name (default: derived from dataset name) + --db-password PASS Database password (default: mlflow) --output-dir DIR Output directory for data files + --sample-size N Target total records to import (default: 3000) + --seed-records N Initial seed records from main table (default: 500) --keep-data Keep CSV and SQL files after import --remove-cache Remove RelBench cache after import --help Show this help message Examples: $0 rel-f1 - $0 rel-amazon --db-name amazon - $0 rel-hm --keep-data + $0 rel-amazon --db-name amazon --sample-size 5000 + $0 rel-hm --keep-data --seed-records 1000 $0 rel-stack --db-name stackoverflow --output-dir ./stack_data Supported datasets: @@ -136,11 +144,26 @@ while [ $# -gt 0 ]; do log "Setting DB_NAME=$DB_NAME" shift 2 ;; + --db-password) + DB_PASSWORD="$2" + log "Setting DB_PASSWORD=[HIDDEN]" + shift 2 + ;; --output-dir) OUTPUT_DIR="$2" log "Setting OUTPUT_DIR=$OUTPUT_DIR" shift 2 ;; + --sample-size) + SAMPLE_SIZE="$2" + log "Setting SAMPLE_SIZE=$SAMPLE_SIZE" + shift 2 + ;; + --seed-records) + MAX_SEED_RECORDS="$2" + log "Setting MAX_SEED_RECORDS=$MAX_SEED_RECORDS" + shift 2 + ;; --keep-data) KEEP_DATA="true" log "Setting KEEP_DATA=true" @@ -191,15 +214,18 @@ fi DATA_DIR="$OUTPUT_DIR" SQL_FILE="$DATA_DIR/import_${DATASET_SHORT}.sql" +SAMPLE_SQL_FILE="$DATA_DIR/sample_${DATASET_SHORT}.sql" -print_header "RelBench Import - $DATASET_NAME" +print_header "RelBench Partial Import - $DATASET_NAME" echo "Configuration:" | tee -a "$LOG_FILE" -echo " Dataset: $DATASET_NAME" | tee -a "$LOG_FILE" -echo " Database: $DB_NAME" | tee -a "$LOG_FILE" -echo " Container: $CONTAINER_NAME" | tee -a "$LOG_FILE" -echo " Data dir: $DATA_DIR" | tee -a "$LOG_FILE" -echo " Log file: $LOG_FILE" | tee -a "$LOG_FILE" +echo " Dataset: $DATASET_NAME" | tee -a "$LOG_FILE" +echo " Database: $DB_NAME" | tee -a "$LOG_FILE" +echo " Container: $CONTAINER_NAME" | tee -a "$LOG_FILE" +echo " Data dir: $DATA_DIR" | tee -a "$LOG_FILE" +echo " Sample size: $SAMPLE_SIZE records" | tee -a "$LOG_FILE" +echo " Seed records: $MAX_SEED_RECORDS" | tee -a "$LOG_FILE" +echo " Log file: $LOG_FILE" | tee -a "$LOG_FILE" echo "" | tee -a "$LOG_FILE" log_step "Checking Python installation" @@ -298,16 +324,26 @@ CSV_COUNT=$(ls -1 $DATA_DIR/*.csv 2>/dev/null | wc -l) print_info "Found $CSV_COUNT CSV files" log "CSV files count: $CSV_COUNT" -print_header "Step 4: Copy Files to Container" -log_step "Copying files to container" -print_info "Copying CSV files to container..." +print_header "Step 4: Create Schema and Load Full Data to Temporary Database" +log_step "Creating temporary database for sampling" + +TEMP_DB="${DB_NAME}_temp" +print_info "Creating temporary database: $TEMP_DB" + +docker exec $CONTAINER_NAME psql -U $DB_USER -d postgres -c "DROP DATABASE IF EXISTS $TEMP_DB;" >> "$LOG_FILE" 2>&1 +if docker exec $CONTAINER_NAME psql -U $DB_USER -d postgres -c "CREATE DATABASE $TEMP_DB;" >> "$LOG_FILE" 2>&1; then + log "Temporary database created: $TEMP_DB" +else + log_error "Failed to create temporary database" + exit 1 +fi +print_info "Copying CSV files to container..." for csv_file in $DATA_DIR/*.csv; do if [ -f "$csv_file" ]; then filename=$(basename "$csv_file") if docker cp "$csv_file" $CONTAINER_NAME:/tmp/ >> "$LOG_FILE" 2>&1; then log "Copied $filename to container" - echo "Copied $filename" else log_error "Failed to copy $filename" exit 1 @@ -318,77 +354,732 @@ done print_info "Copying SQL script to container..." if docker cp "$SQL_FILE" $CONTAINER_NAME:/tmp/ >> "$LOG_FILE" 2>&1; then log "SQL script copied to container successfully" - echo "SQL script copied" else log_error "Failed to copy SQL script to container" exit 1 fi -print_header "Step 5: Import Data into PostgreSQL" -log_step "Importing data into PostgreSQL" -print_info "Running SQL import script..." -echo "=========================================" | tee -a "$LOG_FILE" - -if docker exec -i $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME -f /tmp/import_${DATASET_SHORT}.sql 2>&1 | tee -a "$LOG_FILE"; then - log "SQL import completed successfully" +print_info "Loading full data into temporary database..." +if docker exec -i $CONTAINER_NAME psql -U $DB_USER -d $TEMP_DB -f /tmp/import_${DATASET_SHORT}.sql >> "$LOG_FILE" 2>&1; then + log "Full data loaded into temporary database" else - log_error "SQL import failed with exit code $?" + log_error "Failed to load data into temporary database" exit 1 fi -echo "=========================================" | tee -a "$LOG_FILE" -echo "Data import completed" | tee -a "$LOG_FILE" +print_header "Step 5: Analyze Schema and Generate Sample" +log_step "Analyzing database schema and relationships" -print_header "Step 6: Verify Import" -log_step "Verifying import" -print_info "Checking table counts..." +print_info "Generating intelligent sample with foreign key relationships..." -docker exec $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME -c " -SELECT - schemaname, - tablename, - to_char(n_live_tup, 'FM999,999,999') as row_count -FROM pg_stat_user_tables -WHERE schemaname = 'public' -ORDER BY n_live_tup DESC; -" 2>&1 | tee -a "$LOG_FILE" +# Tạo script Python để phân tích và tạo sample +cat > "$DATA_DIR/create_sample.py" << 'PYTHON_SCRIPT' +#!/usr/bin/env python3 +import sys +import psycopg2 +from collections import defaultdict, deque +import json -print_header "Import Complete" +def get_table_info(conn): + """Lấy thông tin về các bảng và số lượng bản ghi""" + cur = conn.cursor() + cur.execute(""" + SELECT schemaname, relname, n_live_tup + FROM pg_stat_user_tables + WHERE schemaname = 'public' + ORDER BY n_live_tup DESC + """) + tables = {} + for row in cur.fetchall(): + tables[row[1]] = int(row[2]) # row[1] is relname, row[2] is n_live_tup + cur.close() + return tables -echo "Database Details:" | tee -a "$LOG_FILE" -echo " Container: $CONTAINER_NAME" | tee -a "$LOG_FILE" -echo " Database: $DB_NAME" | tee -a "$LOG_FILE" -echo " User: $DB_USER" | tee -a "$LOG_FILE" -echo "" | tee -a "$LOG_FILE" -echo "Connect to database:" | tee -a "$LOG_FILE" -echo " docker exec -it $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME" | tee -a "$LOG_FILE" -echo "" | tee -a "$LOG_FILE" -echo "Example queries:" | tee -a "$LOG_FILE" -echo " \\dt -- List all tables" | tee -a "$LOG_FILE" -echo " \\d table_name -- Show table structure" | tee -a "$LOG_FILE" -echo " SELECT COUNT(*) FROM table_name;" | tee -a "$LOG_FILE" -echo "" | tee -a "$LOG_FILE" +def format_ids_for_sql(ids): + """Format list of IDs for SQL IN clause""" + formatted = [] + for id_val in ids: + if id_val is None: + continue + elif isinstance(id_val, str): + escaped = id_val.replace("'", "''") + formatted.append(f"'{escaped}'") + elif isinstance(id_val, (int, float)): + formatted.append(str(id_val)) + else: + escaped = str(id_val).replace("'", "''") + formatted.append(f"'{escaped}'") + return ','.join(formatted) if formatted else "''" + +def get_foreign_keys(conn): + """Lấy thông tin về foreign keys""" + cur = conn.cursor() + cur.execute(""" + SELECT + tc.table_name as from_table, + kcu.column_name as from_column, + ccu.table_name AS to_table, + ccu.column_name AS to_column + FROM information_schema.table_constraints AS tc + JOIN information_schema.key_column_usage AS kcu + ON tc.constraint_name = kcu.constraint_name + AND tc.table_schema = kcu.table_schema + JOIN information_schema.constraint_column_usage AS ccu + ON ccu.constraint_name = tc.constraint_name + AND ccu.table_schema = tc.table_schema + WHERE tc.constraint_type = 'FOREIGN KEY' + AND tc.table_schema = 'public' + """) + + fks = defaultdict(list) + reverse_fks = defaultdict(list) + + for row in cur.fetchall(): + from_table, from_col, to_table, to_col = row + fks[from_table].append({ + 'from_col': from_col, + 'to_table': to_table, + 'to_col': to_col + }) + reverse_fks[to_table].append({ + 'to_col': to_col, + 'from_table': from_table, + 'from_col': from_col + }) + + cur.close() + return dict(fks), dict(reverse_fks) + +def find_central_table(tables, fks, reverse_fks): + """Tìm bảng trung tâm (bảng có nhiều quan hệ nhất)""" + scores = {} + for table in tables: + # Điểm = số FK đi ra + số FK đi vào + outgoing = len(fks.get(table, [])) + incoming = len(reverse_fks.get(table, [])) + scores[table] = outgoing + incoming + + # Sắp xếp theo điểm và số lượng bản ghi + sorted_tables = sorted(scores.items(), key=lambda x: (x[1], tables.get(x[0], 0)), reverse=True) + + if sorted_tables: + return sorted_tables[0][0] + return list(tables.keys())[0] if tables else None + +def create_sample_sql(conn, db_name, target_db, sample_size, seed_records): + """Tạo SQL script để sample dữ liệu có liên kết""" + + print("Analyzing database schema...") + tables = get_table_info(conn) + fks, reverse_fks = get_foreign_keys(conn) + + print(f"\nFound {len(tables)} tables:") + for table, count in sorted(tables.items(), key=lambda x: x[1], reverse=True): + print(f" - {table}: {count:,} records") + + print(f"\nFound {sum(len(v) for v in fks.values())} foreign key relationships") + + central_table = find_central_table(tables, fks, reverse_fks) + print(f"\nCentral table identified: {central_table}") + + # Get primary keys for all tables + cur = conn.cursor() + pk_columns = {} + for table in tables: + cur.execute(f""" + SELECT a.attname + FROM pg_index i + JOIN pg_attribute a ON a.attrelid = i.indrelid AND a.attnum = ANY(i.indkey) + WHERE i.indrelid = '{table}'::regclass AND i.indisprimary + """) + pk_result = cur.fetchone() + if pk_result: + pk_columns[table] = pk_result[0] + else: + # Fallback: use first column + cur.execute(f"SELECT column_name FROM information_schema.columns WHERE table_name = '{table}' LIMIT 1") + pk_columns[table] = cur.fetchone()[0] + + # Tạo temporary tables để lưu IDs đã chọn + sampled_ids = defaultdict(set) + visited_tables = set() + + cur = conn.cursor() + + # Bước 1: Lấy seed records từ bảng trung tâm + print(f"\nStep 1: Sampling {seed_records} seed records from {central_table}...") + + # Lấy primary key của bảng trung tâm + cur.execute(f""" + SELECT a.attname + FROM pg_index i + JOIN pg_attribute a ON a.attrelid = i.indrelid AND a.attnum = ANY(i.indkey) + WHERE i.indrelid = '{central_table}'::regclass AND i.indisprimary + """) + pk_col = cur.fetchone() + if pk_col: + pk_col = pk_col[0] + else: + # Fallback to first column + cur.execute(f"SELECT column_name FROM information_schema.columns WHERE table_name = '{central_table}' LIMIT 1") + pk_col = cur.fetchone()[0] + + # Sample random records + cur.execute(f""" + SELECT {pk_col} FROM {central_table} + ORDER BY RANDOM() + LIMIT {seed_records} + """) + + seed_ids = [row[0] for row in cur.fetchall()] + sampled_ids[central_table] = set(seed_ids) + print(f" Sampled {len(seed_ids)} records from {central_table}") + + # Bước 2: BFS để lấy các bản ghi liên quan + queue = deque([(central_table, seed_ids)]) + visited_tables.add(central_table) + total_records = len(seed_ids) + + print(f"\nStep 2: Cascading through foreign key relationships...") + iteration = 0 + + while queue and total_records < sample_size: + iteration += 1 + current_table, current_ids = queue.popleft() + + if not current_ids: + continue + + print(f"\n Iteration {iteration}: Processing {current_table} ({len(current_ids)} IDs)") + + # Lấy bảng cha (through FK) + for fk in fks.get(current_table, []): + to_table = fk['to_table'] + from_col = fk['from_col'] + to_col = fk['to_col'] + + if total_records >= sample_size: + break + + # Lấy parent IDs - sử dụng subquery an toàn hơn + ids_str = format_ids_for_sql(current_ids) + if not ids_str or ids_str == "''": + continue + + try: + cur.execute(f""" + SELECT DISTINCT {to_col} + FROM {to_table} + WHERE {to_col} IS NOT NULL + AND {to_col} IN ( + SELECT DISTINCT {from_col} + FROM {current_table} + WHERE {from_col} IS NOT NULL + AND {from_col} IN ({ids_str}) + ) + """) + + parent_ids = [row[0] for row in cur.fetchall()] + new_ids = set(parent_ids) - sampled_ids[to_table] + + if new_ids: + sampled_ids[to_table].update(new_ids) + total_records += len(new_ids) + print(f" -> {to_table}: +{len(new_ids)} records (total: {len(sampled_ids[to_table])})") + + if to_table not in visited_tables: + queue.append((to_table, list(new_ids))) + visited_tables.add(to_table) + except Exception as e: + print(f" -> {to_table}: Error - {e}") + continue + + # Lấy bảng con (reverse FK) - giới hạn số lượng để tránh quá nhiều + for rfk in reverse_fks.get(current_table, []): + from_table = rfk['from_table'] + from_col = rfk['from_col'] + to_col = rfk['to_col'] + + if total_records >= sample_size: + break + + # Lấy child IDs với giới hạn + ids_str = format_ids_for_sql(current_ids) + if not ids_str or ids_str == "''": + continue + + limit = min(500, sample_size - total_records) # Giới hạn mỗi lần lấy 500 records + + try: + # Lấy primary key của bảng con + cur.execute(f""" + SELECT a.attname + FROM pg_index i + JOIN pg_attribute a ON a.attrelid = i.indrelid AND a.attnum = ANY(i.indkey) + WHERE i.indrelid = '{from_table}'::regclass AND i.indisprimary + """) + child_pk_result = cur.fetchone() + if child_pk_result: + child_pk_col = child_pk_result[0] + else: + cur.execute(f"SELECT column_name FROM information_schema.columns WHERE table_name = '{from_table}' LIMIT 1") + child_pk_col = cur.fetchone()[0] + + cur.execute(f""" + SELECT DISTINCT {child_pk_col} + FROM {from_table} + WHERE {to_col} IS NOT NULL + AND {to_col} IN ({ids_str}) + LIMIT {limit} + """) + + child_ids = [row[0] for row in cur.fetchall()] + new_ids = set(child_ids) - sampled_ids[from_table] + + if new_ids: + sampled_ids[from_table].update(new_ids) + total_records += len(new_ids) + print(f" <- {from_table}: +{len(new_ids)} records (total: {len(sampled_ids[from_table])})") + + if from_table not in visited_tables: + queue.append((from_table, list(new_ids))) + visited_tables.add(from_table) + except Exception as e: + print(f" <- {from_table}: Error - {e}") + continue + + # Bước 2.5: Validate và clean orphaned foreign keys + print(f"\nStep 2.5: Validating foreign key integrity...") + cleaned_count = 0 + max_iterations = 10 + + for iteration in range(max_iterations): + removed_this_iteration = 0 + + for table in list(sampled_ids.keys()): + if table not in fks or not fks[table]: + continue + + ids_to_remove = set() + ids_list = list(sampled_ids[table]) + + # Check each FK constraint + for fk in fks[table]: + to_table = fk['to_table'] + from_col = fk['from_col'] # Fixed: was 'from_column' + + # Skip if target table has no sampled data + if to_table not in sampled_ids or not sampled_ids[to_table]: + continue + + # Get FK values for sampled records + ids_str = format_ids_for_sql(ids_list) + if not ids_str or ids_str == "''": + continue + + target_ids_str = format_ids_for_sql(list(sampled_ids[to_table])) + if not target_ids_str or target_ids_str == "''": + continue + + try: + # Find records with FK values not in target table's sampled IDs + cur.execute(f""" + SELECT DISTINCT t.{pk_columns[table]} + FROM {table} t + WHERE t.{pk_columns[table]} IN ({ids_str}) + AND t.{from_col} IS NOT NULL + AND t.{from_col}::text NOT IN ( + SELECT {pk_columns[to_table]}::text FROM {to_table} + WHERE {pk_columns[to_table]} IN ({target_ids_str}) + ) + """) + orphaned = cur.fetchall() + for row in orphaned: + ids_to_remove.add(row[0]) + except Exception as e: + print(f" Warning: Could not validate FK {table}.{from_col} -> {to_table}: {e}") + continue + + # Remove orphaned records + if ids_to_remove: + sampled_ids[table] -= ids_to_remove + removed_this_iteration += len(ids_to_remove) + cleaned_count += len(ids_to_remove) + print(f" {table}: removed {len(ids_to_remove)} orphaned records") + + if removed_this_iteration == 0: + print(f" Validation complete after {iteration + 1} iteration(s)") + break + + if cleaned_count > 0: + print(f"\nTotal orphaned records removed: {cleaned_count}") + total_records = sum(len(ids) for ids in sampled_ids.values()) + print(f"Clean sample size: {total_records} records") + else: + print(f" No orphaned records found - data integrity is perfect!") + + # Bước 3: Tạo SQL script + print(f"\nStep 3: Generating SQL script...") + sql_lines = [] + sql_lines.append(f"-- Sample data from {db_name}") + sql_lines.append(f"-- Total records to import: {total_records}") + sql_lines.append(f"-- Generated at: {import_timestamp}") + sql_lines.append("") + + # Tạo bảng theo thứ tự dependency + table_order = [] + remaining = set(sampled_ids.keys()) + + while remaining: + added = False + for table in list(remaining): + # Check if all dependencies are satisfied + deps = set(fk['to_table'] for fk in fks.get(table, [])) + if deps.issubset(set(table_order)): + table_order.append(table) + remaining.remove(table) + added = True + + if not added and remaining: + # Break circular dependency + table_order.append(remaining.pop()) + + print(f"\nTable processing order: {' -> '.join(table_order)}") + + for table in table_order: + ids = sampled_ids[table] + if not ids: + continue + + print(f"\nProcessing {table}: {len(ids)} records") + + # Lấy primary key + cur.execute(f""" + SELECT a.attname + FROM pg_index i + JOIN pg_attribute a ON a.attrelid = i.indrelid AND a.attnum = ANY(i.indkey) + WHERE i.indrelid = '{table}'::regclass AND i.indisprimary + """) + pk_result = cur.fetchone() + if pk_result: + pk_col = pk_result[0] + else: + cur.execute(f"SELECT column_name FROM information_schema.columns WHERE table_name = '{table}' LIMIT 1") + pk_col = cur.fetchone()[0] + + # Lấy danh sách các cột + cur.execute(f""" + SELECT column_name, data_type + FROM information_schema.columns + WHERE table_name = '{table}' + AND table_schema = 'public' + ORDER BY ordinal_position + """) + columns = cur.fetchall() + col_names = [col[0] for col in columns] + + sql_lines.append(f"-- Table: {table} ({len(ids)} records)") + + # Lấy dữ liệu thực tế từ database + ids_str = format_ids_for_sql(list(ids)) + if not ids_str or ids_str == "''": + print(f" Skipping {table} - no valid IDs") + continue + + query = f""" + SELECT {', '.join(col_names)} + FROM {table} + WHERE {pk_col} IN ({ids_str}) + """ + + try: + cur.execute(query) + rows = cur.fetchall() + except Exception as e: + print(f" Error querying {table}: {e}") + continue + + # Tạo INSERT statements + if rows: + sql_lines.append(f"INSERT INTO {table} ({', '.join(col_names)}) VALUES") + for i, row in enumerate(rows): + # Format values + values = [] + for val in row: + if val is None: + values.append('NULL') + elif isinstance(val, str): + # Escape single quotes + escaped = val.replace("'", "''") + values.append(f"'{escaped}'") + elif isinstance(val, (int, float)): + values.append(str(val)) + elif isinstance(val, bool): + values.append('TRUE' if val else 'FALSE') + else: + # For other types (date, timestamp, etc.), convert to string + escaped = str(val).replace("'", "''") + values.append(f"'{escaped}'") + + if i < len(rows) - 1: + sql_lines.append(f" ({', '.join(values)}),") + else: + sql_lines.append(f" ({', '.join(values)});") + + sql_lines.append("") + + cur.close() + + print(f"\n{'='*50}") + print(f"Sample Summary:") + print(f"{'='*50}") + for table in table_order: + if table in sampled_ids: + print(f" {table:30} {len(sampled_ids[table]):>10,} records") + print(f"{'='*50}") + print(f" {'TOTAL':30} {sum(len(ids) for ids in sampled_ids.values()):>10,} records") + print(f"{'='*50}") + + return '\n'.join(sql_lines), sampled_ids + +if __name__ == '__main__': + import datetime + import_timestamp = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S') + + db_name = sys.argv[1] + target_db = sys.argv[2] + sample_size = int(sys.argv[3]) + seed_records = int(sys.argv[4]) + output_file = sys.argv[5] + pg_port = int(sys.argv[6]) if len(sys.argv) > 6 else 5432 + pg_password = sys.argv[7] if len(sys.argv) > 7 else '' + + print(f"Connecting to PostgreSQL on localhost:{pg_port}...") + conn = psycopg2.connect( + host='localhost', + database=db_name, + user='mlflow', + password=pg_password, + port=pg_port + ) + print("Connected successfully!") + print() + + sql_script, sampled_ids = create_sample_sql(conn, db_name, target_db, sample_size, seed_records) + + with open(output_file, 'w') as f: + f.write(sql_script) + + # Save summary as JSON + summary = { + 'total_records': sum(len(ids) for ids in sampled_ids.values()), + 'tables': {table: len(ids) for table, ids in sampled_ids.items()}, + 'timestamp': import_timestamp + } + + summary_file = output_file.replace('.sql', '_summary.json') + with open(summary_file, 'w') as f: + json.dump(summary, f, indent=2) + + print(f"\nSQL script saved to: {output_file}") + print(f"Summary saved to: {summary_file}") + + conn.close() +PYTHON_SCRIPT + +chmod +x "$DATA_DIR/create_sample.py" -if [ "$KEEP_DATA" = "false" ]; then - read -p "Keep data files? (y/N) " -n 1 -r - echo - if [[ $REPLY =~ ^[Yy]$ ]]; then - export KEEP_DATA=true - print_info "Data files will be kept in: $DATA_DIR" +# Cài đặt psycopg2 trên host nếu chưa có +print_info "Checking psycopg2 on host machine..." +if ! python3 -c "import psycopg2" 2>/dev/null; then + print_info "Installing psycopg2-binary on host..." + if pip install psycopg2-binary >> "$LOG_FILE" 2>&1; then + log "psycopg2-binary installed successfully" + else + log_error "Failed to install psycopg2-binary" + exit 1 fi +else + log "psycopg2 is already installed" +fi + +# Lấy port của PostgreSQL container +print_info "Getting PostgreSQL container port..." +PG_PORT=$(docker port $CONTAINER_NAME 5432 | cut -d: -f2) +if [ -z "$PG_PORT" ]; then + log_error "Could not determine PostgreSQL port" + exit 1 +fi +log "PostgreSQL port: $PG_PORT" + +# Chạy script Python trên host +print_info "Running intelligent sampling algorithm..." +log "Command: python3 $DATA_DIR/create_sample.py $TEMP_DB $DB_NAME $SAMPLE_SIZE $MAX_SEED_RECORDS $SAMPLE_SQL_FILE $PG_PORT $DB_PASSWORD" + +if python3 "$DATA_DIR/create_sample.py" \ + "$TEMP_DB" "$DB_NAME" "$SAMPLE_SIZE" "$MAX_SEED_RECORDS" "$SAMPLE_SQL_FILE" "$PG_PORT" "$DB_PASSWORD" \ + 2>&1 | tee -a "$LOG_FILE"; then + log "Sampling completed successfully" +else + log_error "Python sampling script failed with exit code $?" + log_error "Check if psycopg2 is installed: pip install psycopg2-binary" + exit 1 +fi + +# Kiểm tra file output +if [ ! -f "$SAMPLE_SQL_FILE" ]; then + log_error "Sample SQL file was not created by Python script" + exit 1 +fi + +if [ ! -s "$SAMPLE_SQL_FILE" ]; then + log_error "Sample SQL file is empty" + exit 1 +fi + +log "Sample SQL file created: $SAMPLE_SQL_FILE ($(wc -l < "$SAMPLE_SQL_FILE") lines)" + +# Kiểm tra summary file +if [ -f "$DATA_DIR/sample_summary.json" ]; then + log "Sample summary created: $DATA_DIR/sample_summary.json" + cat "$DATA_DIR/sample_summary.json" | tee -a "$LOG_FILE" +else + log "Warning: Sample summary file not created" +fi + +print_header "Step 6: Import Sampled Data" +log_step "Importing sampled data into target database" + +# Kiểm tra file SQL đã được tạo chưa +if [ ! -f "$SAMPLE_SQL_FILE" ]; then + log_error "Sample SQL file was not created: $SAMPLE_SQL_FILE" + log_error "Python sampling script may have failed. Check the log above." + exit 1 +fi + +log "Sample SQL file found: $SAMPLE_SQL_FILE ($(wc -l < "$SAMPLE_SQL_FILE") lines)" + +# Drop và recreate database để đảm bảo clean state +print_info "Recreating target database for clean import..." +docker exec $CONTAINER_NAME psql -U $DB_USER -d postgres -c "DROP DATABASE IF EXISTS $DB_NAME;" >> "$LOG_FILE" 2>&1 +if docker exec $CONTAINER_NAME psql -U $DB_USER -d postgres -c "CREATE DATABASE $DB_NAME;" >> "$LOG_FILE" 2>&1; then + log "Target database recreated: $DB_NAME" +else + log_error "Failed to recreate target database" + exit 1 +fi + +print_info "Creating schema in target database..." +# Tạo schema từ SQL file gốc nhưng loại bỏ foreign keys và indexes +# Sử dụng sed để tách phần CREATE TABLE +cat > "$DATA_DIR/schema_only.sql" << 'SQL_HEADER' +-- Schema creation script (tables only, no foreign keys) +-- Generated by import_relbench.sh +SQL_HEADER + +# Extract only CREATE TABLE statements (multi-line) +awk '/^CREATE TABLE/,/;$/' "$SQL_FILE" >> "$DATA_DIR/schema_only.sql" + +docker cp "$DATA_DIR/schema_only.sql" $CONTAINER_NAME:/tmp/ + +if docker exec $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME -f /tmp/schema_only.sql >> "$LOG_FILE" 2>&1; then + log "Schema created successfully (without foreign keys)" +else + log_error "Failed to create schema" + exit 1 fi -if [ "$KEEP_DATA" = "false" ] && [ "$REMOVE_RELBENCH_CACHE" = "false" ]; then - read -p "Remove RelBench cache? (y/N) " -n 1 -r - echo - if [[ $REPLY =~ ^[Yy]$ ]]; then - export REMOVE_RELBENCH_CACHE=true +print_info "Importing sampled data..." + +# Kiểm tra file SQL có tồn tại không +if [ ! -f "$SAMPLE_SQL_FILE" ]; then + log_error "Sample SQL file not found: $SAMPLE_SQL_FILE" + exit 1 +fi + +# Kiểm tra file có rỗng không +if [ ! -s "$SAMPLE_SQL_FILE" ]; then + log_error "Sample SQL file is empty: $SAMPLE_SQL_FILE" + exit 1 +fi + +log "Sample SQL file size: $(wc -l < "$SAMPLE_SQL_FILE") lines" + +# Copy SQL file vào container +if docker cp "$SAMPLE_SQL_FILE" $CONTAINER_NAME:/tmp/sample_${DATASET_SHORT}.sql >> "$LOG_FILE" 2>&1; then + log "SQL file copied to container" +else + log_error "Failed to copy SQL file to container" + exit 1 +fi + +# Import với error handling chi tiết +print_info "Executing SQL import..." +if docker exec $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME -f /tmp/sample_${DATASET_SHORT}.sql 2>&1 | tee -a "$LOG_FILE"; then + log "SQL import completed successfully" +else + log_error "SQL import failed. Check log file for details: $LOG_FILE" + log_error "Last 20 lines of SQL file:" + tail -20 "$SAMPLE_SQL_FILE" | tee -a "$LOG_FILE" + exit 1 +fi + +# Thêm foreign keys sau khi import data +print_info "Adding foreign key constraints..." +# Extract ALTER TABLE ADD CONSTRAINT statements with their FOREIGN KEY lines (2 lines each) +grep -A 1 "^ALTER TABLE.*ADD CONSTRAINT" "$SQL_FILE" | grep -v "^--$" > "$DATA_DIR/foreign_keys.sql" || true +if [ -s "$DATA_DIR/foreign_keys.sql" ]; then + docker cp "$DATA_DIR/foreign_keys.sql" $CONTAINER_NAME:/tmp/ + if docker exec $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME -f /tmp/foreign_keys.sql >> "$LOG_FILE" 2>&1; then + log "Foreign key constraints added successfully" + else + log "Warning: Some foreign key constraints failed (expected with partial data)" fi +else + log "No foreign key constraints to add" fi -log "==========================================" -log "Script completed successfully" -log "Log file: $LOG_FILE" -log "==========================================" +# Xóa temporary database +print_info "Cleaning up temporary database..." +docker exec $CONTAINER_NAME psql -U $DB_USER -d postgres -c "DROP DATABASE IF EXISTS $TEMP_DB;" >> "$LOG_FILE" 2>&1 +log "Temporary database dropped" + +print_header "Step 7: Verify Import" +log_step "Verifying sampled data import" + +print_info "Actual record counts in database:" +echo "" | tee -a "$LOG_FILE" +echo "=========================================" | tee -a "$LOG_FILE" +echo "IMPORTED RECORDS BY TABLE" | tee -a "$LOG_FILE" +echo "=========================================" | tee -a "$LOG_FILE" + +# Query để lấy số lượng records trong mỗi bảng +TOTAL_COUNT=0 +docker exec $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME -t -c " +SELECT + relname || ':' || n_live_tup as info +FROM pg_stat_user_tables +WHERE schemaname = 'public' +ORDER BY n_live_tup DESC; +" | while IFS=: read -r table count; do + if [ ! -z "$table" ] && [ ! -z "$count" ]; then + # Trim whitespace + table=$(echo "$table" | xargs) + count=$(echo "$count" | xargs) + printf " %-30s %10s records\n" "$table" "$count" | tee -a "$LOG_FILE" + TOTAL_COUNT=$((TOTAL_COUNT + count)) + fi +done + +echo "=========================================" | tee -a "$LOG_FILE" + +# Get total count from database +TOTAL_RECORDS=$(docker exec $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME -t -c " +SELECT SUM(n_live_tup) FROM pg_stat_user_tables WHERE schemaname = 'public'; +" | xargs) + +printf " %-30s %10s records\n" "TOTAL" "$TOTAL_RECORDS" | tee -a "$LOG_FILE" +echo "=========================================" | tee -a "$LOG_FILE" +echo "" | tee -a "$LOG_FILE" -print_header "Done" \ No newline at end of file +log "Import verification completed - Total: $TOTAL_RECORDS records imported" \ No newline at end of file diff --git a/scripts/import_relbench_stack.sh b/scripts/import_relbench_stack.sh deleted file mode 100644 index 198f17b2..00000000 --- a/scripts/import_relbench_stack.sh +++ /dev/null @@ -1,449 +0,0 @@ -set -e - -CONTAINER_NAME="plexe-clone-postgres-1" -DB_NAME="stack" -DB_USER="mlflow" -CSV_SOURCE="/home/ta/kl/plexe-clone/data/database" - -echo "=========================================" -echo "RelBench Stack Import - Pure SQL" -echo "=========================================" -echo "" - -# Kiểm tra container -echo "🔍 Kiểm tra container..." -if ! docker ps | grep -q $CONTAINER_NAME; then - echo "❌ Container không chạy!" - exit 1 -fi -echo "✓ Container đang chạy" -echo "" - -# Kiểm tra và tạo database -echo "🔍 Kiểm tra database..." -if ! docker exec $CONTAINER_NAME psql -U $DB_USER -lqt | cut -d \| -f 1 | grep -qw $DB_NAME; then - echo "⚠️ Database $DB_NAME chưa tồn tại. Đang tạo..." - docker exec $CONTAINER_NAME psql -U $DB_USER -d postgres -c "CREATE DATABASE $DB_NAME;" - echo "✓ Database $DB_NAME đã được tạo." -else - echo "✓ Database $DB_NAME đã tồn tại." -fi -echo "" - -# Copy CSV files vào container -echo "📁 Copy CSV files vào container..." -docker cp "$CSV_SOURCE/users.csv" $CONTAINER_NAME:/tmp/ -docker cp "$CSV_SOURCE/posts.csv" $CONTAINER_NAME:/tmp/ -docker cp "$CSV_SOURCE/votes.csv" $CONTAINER_NAME:/tmp/ -docker cp "$CSV_SOURCE/comments.csv" $CONTAINER_NAME:/tmp/ -docker cp "$CSV_SOURCE/badges.csv" $CONTAINER_NAME:/tmp/ -docker cp "$CSV_SOURCE/postLinks.csv" $CONTAINER_NAME:/tmp/ -docker cp "$CSV_SOURCE/postHistory.csv" $CONTAINER_NAME:/tmp/ -echo "✓ Files copied" -echo "" - -# Tạo SQL script -echo "📝 Tạo SQL script..." -cat > /tmp/import_stack.sql << 'EOSQL' -\echo '=========================================' -\echo 'Bước 1: Drop old tables' -\echo '=========================================' - -DROP TABLE IF EXISTS post_history CASCADE; -DROP TABLE IF EXISTS post_links CASCADE; -DROP TABLE IF EXISTS badges CASCADE; -DROP TABLE IF EXISTS comments CASCADE; -DROP TABLE IF EXISTS votes CASCADE; -DROP TABLE IF EXISTS posts CASCADE; -DROP TABLE IF EXISTS users CASCADE; - -\echo '✓ Tables dropped' -\echo '' - -\echo '=========================================' -\echo 'Bước 2: Create tables (allow NULL)' -\echo '=========================================' - -CREATE TABLE users ( - id INTEGER PRIMARY KEY, - account_id INTEGER, - display_name VARCHAR(255), - location VARCHAR(500), - profile_image_url TEXT, - website_url TEXT, - about_me TEXT, - creation_date TIMESTAMP -); - -CREATE TABLE posts ( - id INTEGER PRIMARY KEY, - owner_user_id INTEGER, - post_type_id INTEGER, - accepted_answer_id INTEGER, - parent_id INTEGER, - owner_display_name VARCHAR(255), - title TEXT, - tags VARCHAR(500), - content_license VARCHAR(100), - body TEXT, - creation_date TIMESTAMP -); - -CREATE TABLE votes ( - id INTEGER PRIMARY KEY, - user_id INTEGER, - post_id INTEGER, - vote_type_id INTEGER, - creation_date TIMESTAMP -); - -CREATE TABLE comments ( - id INTEGER PRIMARY KEY, - post_id INTEGER, - user_id INTEGER, - content_license VARCHAR(100), - user_display_name VARCHAR(255), - text TEXT, - creation_date TIMESTAMP -); - -CREATE TABLE badges ( - id INTEGER PRIMARY KEY, - user_id INTEGER, - class INTEGER, - name VARCHAR(255), - tag_based BOOLEAN, - date TIMESTAMP -); - -CREATE TABLE post_links ( - id INTEGER PRIMARY KEY, - related_post_id INTEGER, - post_id INTEGER, - link_type_id INTEGER, - creation_date TIMESTAMP -); - -CREATE TABLE post_history ( - id INTEGER PRIMARY KEY, - post_id INTEGER, - user_id INTEGER, - post_history_type_id INTEGER, - user_display_name VARCHAR(255), - content_license VARCHAR(100), - revision_guid VARCHAR(50), - text TEXT, - comment TEXT, - creation_date TIMESTAMP -); - -\echo '✓ Tables created' -\echo '' - -\echo '=========================================' -\echo 'Bước 3: Create temp tables for import' -\echo '=========================================' - --- Temp tables với tất cả columns là TEXT -CREATE TEMP TABLE temp_users ( - id TEXT, - account_id TEXT, - display_name TEXT, - location TEXT, - profile_image_url TEXT, - website_url TEXT, - about_me TEXT, - creation_date TEXT -); - -CREATE TEMP TABLE temp_posts ( - id TEXT, - owner_user_id TEXT, - post_type_id TEXT, - accepted_answer_id TEXT, - parent_id TEXT, - owner_display_name TEXT, - title TEXT, - tags TEXT, - content_license TEXT, - body TEXT, - creation_date TEXT -); - -CREATE TEMP TABLE temp_votes ( - id TEXT, - user_id TEXT, - post_id TEXT, - vote_type_id TEXT, - creation_date TEXT -); - -CREATE TEMP TABLE temp_comments ( - id TEXT, - post_id TEXT, - user_id TEXT, - content_license TEXT, - user_display_name TEXT, - text TEXT, - creation_date TEXT -); - -CREATE TEMP TABLE temp_badges ( - id TEXT, - user_id TEXT, - class TEXT, - name TEXT, - tag_based TEXT, - date TEXT -); - -CREATE TEMP TABLE temp_post_links ( - id TEXT, - related_post_id TEXT, - post_id TEXT, - link_type_id TEXT, - creation_date TEXT -); - -CREATE TEMP TABLE temp_post_history ( - id TEXT, - post_id TEXT, - user_id TEXT, - post_history_type_id TEXT, - user_display_name TEXT, - content_license TEXT, - revision_guid TEXT, - text TEXT, - comment TEXT, - creation_date TEXT -); - -\echo '✓ Temp tables created' -\echo '' - -\echo '=========================================' -\echo 'Bước 4: Import CSV into temp tables' -\echo '=========================================' - -\echo ' Importing users...' -\copy temp_users FROM '/tmp/users.csv' WITH CSV HEADER DELIMITER ','; - -\echo ' Importing posts...' -\copy temp_posts FROM '/tmp/posts.csv' WITH CSV HEADER DELIMITER ','; - -\echo ' Importing votes...' -\copy temp_votes FROM '/tmp/votes.csv' WITH CSV HEADER DELIMITER ','; - -\echo ' Importing comments...' -\copy temp_comments FROM '/tmp/comments.csv' WITH CSV HEADER DELIMITER ','; - -\echo ' Importing badges...' -\copy temp_badges FROM '/tmp/badges.csv' WITH CSV HEADER DELIMITER ','; - -\echo ' Importing post_links...' -\copy temp_post_links FROM '/tmp/postLinks.csv' WITH CSV HEADER DELIMITER ','; - -\echo ' Importing post_history...' -\copy temp_post_history FROM '/tmp/postHistory.csv' WITH CSV HEADER DELIMITER ','; - -\echo '✓ CSV imported to temp tables' -\echo '' - -\echo '=========================================' -\echo 'Bước 5: Transfer data with type conversion' -\echo '=========================================' - -\echo ' Processing users...' -INSERT INTO users -SELECT - id::INTEGER, - NULLIF(account_id, '')::INTEGER, - NULLIF(display_name, ''), - NULLIF(location, ''), - NULLIF(profile_image_url, ''), - NULLIF(website_url, ''), - NULLIF(about_me, ''), - NULLIF(creation_date, '')::TIMESTAMP -FROM temp_users; - -\echo ' Processing posts...' -INSERT INTO posts -SELECT - id::INTEGER, - NULLIF(owner_user_id, '')::INTEGER, - NULLIF(post_type_id, '')::INTEGER, - NULLIF(accepted_answer_id, '')::INTEGER, - NULLIF(parent_id, '')::INTEGER, - NULLIF(owner_display_name, ''), - NULLIF(title, ''), - NULLIF(tags, ''), - NULLIF(content_license, ''), - NULLIF(body, ''), - NULLIF(creation_date, '')::TIMESTAMP -FROM temp_posts; - -\echo ' Processing votes...' -INSERT INTO votes -SELECT - id::INTEGER, - NULLIF(user_id, '')::INTEGER, - NULLIF(post_id, '')::INTEGER, - NULLIF(vote_type_id, '')::INTEGER, - NULLIF(creation_date, '')::TIMESTAMP -FROM temp_votes; - -\echo ' Processing comments...' -INSERT INTO comments -SELECT - id::INTEGER, - NULLIF(post_id, '')::INTEGER, - NULLIF(user_id, '')::INTEGER, - NULLIF(content_license, ''), - NULLIF(user_display_name, ''), - NULLIF(text, ''), - NULLIF(creation_date, '')::TIMESTAMP -FROM temp_comments; - -\echo ' Processing badges...' -INSERT INTO badges -SELECT - id::INTEGER, - NULLIF(user_id, '')::INTEGER, - NULLIF(class, '')::INTEGER, - NULLIF(name, ''), - NULLIF(tag_based, '')::BOOLEAN, - NULLIF(date, '')::TIMESTAMP -FROM temp_badges; - -\echo ' Processing post_links...' -INSERT INTO post_links -SELECT - id::INTEGER, - NULLIF(related_post_id, '')::INTEGER, - NULLIF(post_id, '')::INTEGER, - NULLIF(link_type_id, '')::INTEGER, - NULLIF(creation_date, '')::TIMESTAMP -FROM temp_post_links; - -\echo ' Processing post_history...' -INSERT INTO post_history -SELECT - id::INTEGER, - NULLIF(post_id, '')::INTEGER, - NULLIF(user_id, '')::INTEGER, - NULLIF(post_history_type_id, '')::INTEGER, - NULLIF(user_display_name, ''), - NULLIF(content_license, ''), - NULLIF(revision_guid, ''), - NULLIF(text, ''), - NULLIF(comment, ''), - NULLIF(creation_date, '')::TIMESTAMP -FROM temp_post_history; - -\echo '✓ Data transferred with NULL handling' -\echo '' - -\echo '=========================================' -\echo 'Bước 6: Add Foreign Keys' -\echo '=========================================' - -ALTER TABLE posts ADD CONSTRAINT fk_posts_owner_user - FOREIGN KEY (owner_user_id) REFERENCES users(id); -ALTER TABLE posts ADD CONSTRAINT fk_posts_accepted_answer - FOREIGN KEY (accepted_answer_id) REFERENCES posts(id); -ALTER TABLE posts ADD CONSTRAINT fk_posts_parent - FOREIGN KEY (parent_id) REFERENCES posts(id); - -ALTER TABLE votes ADD CONSTRAINT fk_votes_user - FOREIGN KEY (user_id) REFERENCES users(id); -ALTER TABLE votes ADD CONSTRAINT fk_votes_post - FOREIGN KEY (post_id) REFERENCES posts(id); - -ALTER TABLE comments ADD CONSTRAINT fk_comments_post - FOREIGN KEY (post_id) REFERENCES posts(id); -ALTER TABLE comments ADD CONSTRAINT fk_comments_user - FOREIGN KEY (user_id) REFERENCES users(id); - -ALTER TABLE badges ADD CONSTRAINT fk_badges_user - FOREIGN KEY (user_id) REFERENCES users(id); - -ALTER TABLE post_links ADD CONSTRAINT fk_post_links_related_post - FOREIGN KEY (related_post_id) REFERENCES posts(id); -ALTER TABLE post_links ADD CONSTRAINT fk_post_links_post - FOREIGN KEY (post_id) REFERENCES posts(id); - -ALTER TABLE post_history ADD CONSTRAINT fk_post_history_post - FOREIGN KEY (post_id) REFERENCES posts(id); -ALTER TABLE post_history ADD CONSTRAINT fk_post_history_user - FOREIGN KEY (user_id) REFERENCES users(id); - -\echo '✓ Foreign keys added' -\echo '' - -\echo '=========================================' -\echo 'Bước 7: Create Indexes' -\echo '=========================================' - -CREATE INDEX idx_posts_owner_user ON posts(owner_user_id) WHERE owner_user_id IS NOT NULL; -CREATE INDEX idx_posts_parent ON posts(parent_id) WHERE parent_id IS NOT NULL; -CREATE INDEX idx_posts_type ON posts(post_type_id); -CREATE INDEX idx_votes_user ON votes(user_id) WHERE user_id IS NOT NULL; -CREATE INDEX idx_votes_post ON votes(post_id); -CREATE INDEX idx_comments_post ON comments(post_id); -CREATE INDEX idx_comments_user ON comments(user_id) WHERE user_id IS NOT NULL; -CREATE INDEX idx_badges_user ON badges(user_id); -CREATE INDEX idx_post_links_related ON post_links(related_post_id); -CREATE INDEX idx_post_links_post ON post_links(post_id); -CREATE INDEX idx_post_history_post ON post_history(post_id); -CREATE INDEX idx_post_history_user ON post_history(user_id) WHERE user_id IS NOT NULL; - -\echo '✓ Indexes created' -\echo '' - -\echo '=========================================' -\echo 'Summary' -\echo '=========================================' - -SELECT - table_name, - to_char(record_count, 'FM999,999,999') as records -FROM ( - SELECT 'users' as table_name, COUNT(*) as record_count FROM users - UNION ALL SELECT 'posts', COUNT(*) FROM posts - UNION ALL SELECT 'votes', COUNT(*) FROM votes - UNION ALL SELECT 'comments', COUNT(*) FROM comments - UNION ALL SELECT 'badges', COUNT(*) FROM badges - UNION ALL SELECT 'post_links', COUNT(*) FROM post_links - UNION ALL SELECT 'post_history', COUNT(*) FROM post_history -) t -ORDER BY record_count DESC; - -\echo '' -\echo '=========================================' -\echo '✅ IMPORT COMPLETE!' -\echo '=========================================' -EOSQL - -# Copy SQL vào container -docker cp /tmp/import_stack.sql $CONTAINER_NAME:/tmp/ - -# Chạy import -echo "🚀 Đang import vào database..." -echo "=========================================" -docker exec -i $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME -f /tmp/import_stack.sql - -# Cleanup -rm /tmp/import_stack.sql - -echo "" -echo "=========================================" -echo "✅ DONE!" -echo "=========================================" -echo "" -echo "Kiểm tra:" -echo " docker exec -it $CONTAINER_NAME psql -U $DB_USER -d $DB_NAME" -echo "" -echo "Queries:" -echo " SELECT COUNT(*) FROM users;" -echo " SELECT COUNT(*) FROM users WHERE account_id IS NULL;" -echo "=========================================" \ No newline at end of file From 15d5af1ee878e603ec6e72d341831f2d3ad5636a Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Sun, 18 Jan 2026 23:04:27 +0700 Subject: [PATCH 37/42] :mute:chore: update scripts --- examples/rel-hm-user-churn.txt | 2 + scripts/generate_relbench_sql.py | 31 ++- scripts/import_relbench.sh | 370 ++++++++++++++++++++++--------- 3 files changed, 298 insertions(+), 105 deletions(-) create mode 100644 examples/rel-hm-user-churn.txt diff --git a/examples/rel-hm-user-churn.txt b/examples/rel-hm-user-churn.txt new file mode 100644 index 00000000..423f856b --- /dev/null +++ b/examples/rel-hm-user-churn.txt @@ -0,0 +1,2 @@ +I am working with the data is loaded into the `hm` database (connection string: `postgresql+psycopg2://mlflow:mlflow@postgres:5432/hm`). +I want to define a predictive task on this relational database. diff --git a/scripts/generate_relbench_sql.py b/scripts/generate_relbench_sql.py index 2b9779d8..ddc3740c 100644 --- a/scripts/generate_relbench_sql.py +++ b/scripts/generate_relbench_sql.py @@ -6,6 +6,7 @@ import os import sys +import csv import argparse import pandas as pd from relbench.datasets import get_dataset @@ -180,7 +181,7 @@ def generate_complete_sql(db, dataset_name): for table_name in db.table_dict.keys(): sql_parts.append(f"\\echo ' Importing {table_name}...'") - sql_parts.append(f"\\copy temp_{table_name} FROM '/tmp/{table_name}.csv' WITH CSV HEADER DELIMITER ',';") + sql_parts.append(f"\\copy temp_{table_name} FROM '/tmp/{table_name}.csv' WITH (FORMAT CSV, HEADER, DELIMITER ',', QUOTE '\"');") sql_parts.append("") sql_parts.append("\\echo 'CSV imported to temp tables'") @@ -310,7 +311,33 @@ def main(): print("Exporting CSV files...") for table_name, table in db.table_dict.items(): csv_path = output_dir / f"{table_name}.csv" - table.df.to_csv(csv_path, index=False) + # Convert any list/array columns to strings and clean problematic characters + df_export = table.df.copy() + for col in df_export.columns: + if df_export[col].dtype == 'object': + # Convert all object types to clean strings + def clean_value(x): + import numpy as np + # Handle None + if x is None: + return '' + # Handle numpy arrays and lists first (before pd.isna which fails on arrays) + if isinstance(x, (list, dict, tuple, np.ndarray)): + return str(x) + # Now safe to check isna for scalar values + try: + if pd.isna(x): + return '' + except (ValueError, TypeError): + pass + # Convert to string and remove problematic characters + s = str(x) + # Replace newlines and carriage returns with space + s = s.replace('\n', ' ').replace('\r', ' ') + return s + df_export[col] = df_export[col].apply(clean_value) + # Use QUOTE_MINIMAL with escapechar to handle special characters properly + df_export.to_csv(csv_path, index=False, quoting=csv.QUOTE_MINIMAL, doublequote=True) print(f" {table_name}.csv ({len(table.df):,} rows)") print() diff --git a/scripts/import_relbench.sh b/scripts/import_relbench.sh index de0743cd..c2fc2a66 100644 --- a/scripts/import_relbench.sh +++ b/scripts/import_relbench.sh @@ -12,7 +12,7 @@ LOG_FILE="$LOG_DIR/import_$(date +%Y%m%d_%H%M%S).log" # Cấu hình sample size SAMPLE_SIZE=5000 # Mục tiêu số bản ghi tổng -MAX_SEED_RECORDS=2000 # Số bản ghi seed ban đầu từ bảng chính +MAX_SEED_RECORDS=5000 # Số bản ghi seed ban đầu từ bảng chính # Hàm log - ghi cả ra console và file log() { @@ -450,20 +450,46 @@ def get_foreign_keys(conn): cur.close() return dict(fks), dict(reverse_fks) -def find_central_table(tables, fks, reverse_fks): - """Tìm bảng trung tâm (bảng có nhiều quan hệ nhất)""" +def find_central_table(tables, fks, reverse_fks, pk_columns): + """Find central table - prioritize fact tables with multiple FKs for better sampling""" + import math scores = {} + + print("\nAnalyzing table importance for sampling...") for table in tables: # Điểm = số FK đi ra + số FK đi vào outgoing = len(fks.get(table, [])) incoming = len(reverse_fks.get(table, [])) - scores[table] = outgoing + incoming + + # PRIORITIZE FACT TABLES (tables with 2+ FKs) - these connect dimensions + # Example: review table connects customer + product + if outgoing >= 2: + fk_score = 10000 + (outgoing * 1000) # Huge bonus for fact tables + else: + fk_score = outgoing * 100 + + # Add points for being referenced by other tables + fk_score += incoming * 50 + + # Prefer tables with primary key (easier to track) + has_pk = pk_columns.get(table, 'ctid') != 'ctid' + pk_bonus = 500 if has_pk else 0 + + # Consider table size - prefer tables with data + size_score = math.log10(tables.get(table, 0) + 1) * 10 if tables.get(table, 0) > 0 else 0 + + total_score = fk_score + pk_bonus + size_score + scores[table] = total_score + + print(f" {table:20s}: FKs={outgoing}, reverse={incoming}, PK={has_pk}, rows={tables.get(table, 0):,}, score={total_score:.0f}") - # Sắp xếp theo điểm và số lượng bản ghi - sorted_tables = sorted(scores.items(), key=lambda x: (x[1], tables.get(x[0], 0)), reverse=True) + # Sắp xếp theo điểm + sorted_tables = sorted(scores.items(), key=lambda x: x[1], reverse=True) if sorted_tables: - return sorted_tables[0][0] + selected = sorted_tables[0][0] + print(f"\nSelected central table: {selected} (score={sorted_tables[0][1]:.0f})") + return selected return list(tables.keys())[0] if tables else None def create_sample_sql(conn, db_name, target_db, sample_size, seed_records): @@ -479,10 +505,7 @@ def create_sample_sql(conn, db_name, target_db, sample_size, seed_records): print(f"\nFound {sum(len(v) for v in fks.values())} foreign key relationships") - central_table = find_central_table(tables, fks, reverse_fks) - print(f"\nCentral table identified: {central_table}") - - # Get primary keys for all tables + # Get primary keys for all tables FIRST (needed for central table selection) cur = conn.cursor() pk_columns = {} for table in tables: @@ -496,9 +519,11 @@ def create_sample_sql(conn, db_name, target_db, sample_size, seed_records): if pk_result: pk_columns[table] = pk_result[0] else: - # Fallback: use first column - cur.execute(f"SELECT column_name FROM information_schema.columns WHERE table_name = '{table}' LIMIT 1") - pk_columns[table] = cur.fetchone()[0] + # Fallback: use ctid (system column) for tables without primary key + pk_columns[table] = 'ctid' + + central_table = find_central_table(tables, fks, reverse_fks, pk_columns) + print(f"\nCentral table identified: {central_table} (PK: {pk_columns.get(central_table, 'none')})") # Tạo temporary tables để lưu IDs đã chọn sampled_ids = defaultdict(set) @@ -509,31 +534,59 @@ def create_sample_sql(conn, db_name, target_db, sample_size, seed_records): # Bước 1: Lấy seed records từ bảng trung tâm print(f"\nStep 1: Sampling {seed_records} seed records from {central_table}...") - # Lấy primary key của bảng trung tâm - cur.execute(f""" - SELECT a.attname - FROM pg_index i - JOIN pg_attribute a ON a.attrelid = i.indrelid AND a.attnum = ANY(i.indkey) - WHERE i.indrelid = '{central_table}'::regclass AND i.indisprimary - """) - pk_col = cur.fetchone() - if pk_col: - pk_col = pk_col[0] - else: - # Fallback to first column - cur.execute(f"SELECT column_name FROM information_schema.columns WHERE table_name = '{central_table}' LIMIT 1") - pk_col = cur.fetchone()[0] + pk_col = pk_columns[central_table] - # Sample random records - cur.execute(f""" - SELECT {pk_col} FROM {central_table} - ORDER BY RANDOM() - LIMIT {seed_records} - """) - - seed_ids = [row[0] for row in cur.fetchall()] - sampled_ids[central_table] = set(seed_ids) - print(f" Sampled {len(seed_ids)} records from {central_table}") + # Sample random records - for tables without PK, use ctid + if pk_col == 'ctid': + # For tables without PK (fact tables), sample and immediately get referenced dimension records + cur.execute(f"SELECT column_name FROM information_schema.columns WHERE table_name = '{central_table}' ORDER BY ordinal_position") + all_columns = [row[0] for row in cur.fetchall()] + columns_str = ', '.join(all_columns) + + # Use TABLESAMPLE for better performance on large tables + cur.execute(f""" + SELECT {columns_str} FROM {central_table} + TABLESAMPLE SYSTEM (1) -- Sample ~1% of pages + LIMIT {seed_records} + """) + # Store tuples of all column values + seed_ids = [row for row in cur.fetchall()] + sampled_ids[central_table] = set(seed_ids) + print(f" Sampled {len(seed_ids)} records from {central_table} (no PK - using full row)") + + # CRITICAL: Extract FK values to get referenced dimension records + col_name_to_idx = {col: idx for idx, col in enumerate(all_columns)} + + for fk in fks.get(central_table, []): + to_table = fk['to_table'] + from_col = fk['from_col'] + to_col = fk['to_col'] + + # Extract FK values from sampled rows + fk_col_idx = col_name_to_idx.get(from_col) + if fk_col_idx is not None: + fk_values = set() + for row in seed_ids: + if row[fk_col_idx] is not None: + fk_values.add(row[fk_col_idx]) + + if fk_values: + sampled_ids[to_table] = fk_values + visited_tables.add(to_table) + total_records += len(fk_values) + print(f" -> Collected {len(fk_values)} {to_table} records (via {from_col})") + + total_records = len(seed_ids) + else: + cur.execute(f""" + SELECT {pk_col} FROM {central_table} + TABLESAMPLE SYSTEM (1) + LIMIT {seed_records} + """) + seed_ids = [row[0] for row in cur.fetchall()] + sampled_ids[central_table] = set(seed_ids) + print(f" Sampled {len(seed_ids)} records from {central_table}") + total_records = len(seed_ids) # Bước 2: BFS để lấy các bản ghi liên quan queue = deque([(central_table, seed_ids)]) @@ -592,6 +645,7 @@ def create_sample_sql(conn, db_name, target_db, sample_size, seed_records): visited_tables.add(to_table) except Exception as e: print(f" -> {to_table}: Error - {e}") + conn.rollback() # Rollback transaction on error continue # Lấy bảng con (reverse FK) - giới hạn số lượng để tránh quá nhiều @@ -611,25 +665,19 @@ def create_sample_sql(conn, db_name, target_db, sample_size, seed_records): limit = min(500, sample_size - total_records) # Giới hạn mỗi lần lấy 500 records try: - # Lấy primary key của bảng con - cur.execute(f""" - SELECT a.attname - FROM pg_index i - JOIN pg_attribute a ON a.attrelid = i.indrelid AND a.attnum = ANY(i.indkey) - WHERE i.indrelid = '{from_table}'::regclass AND i.indisprimary - """) - child_pk_result = cur.fetchone() - if child_pk_result: - child_pk_col = child_pk_result[0] - else: - cur.execute(f"SELECT column_name FROM information_schema.columns WHERE table_name = '{from_table}' LIMIT 1") - child_pk_col = cur.fetchone()[0] + child_pk_col = pk_columns.get(from_table) + + # For tables without PK, we can't track by ID - skip them in reverse FK traversal + # They will be sampled based on FK constraints later + if child_pk_col == 'ctid': + print(f" <- {from_table}: Skipped (no PK - will sample by FK constraint)") + continue cur.execute(f""" SELECT DISTINCT {child_pk_col} FROM {from_table} - WHERE {to_col} IS NOT NULL - AND {to_col} IN ({ids_str}) + WHERE {from_col} IS NOT NULL + AND {from_col} IN ({ids_str}) LIMIT {limit} """) @@ -646,30 +694,117 @@ def create_sample_sql(conn, db_name, target_db, sample_size, seed_records): visited_tables.add(from_table) except Exception as e: print(f" <- {from_table}: Error - {e}") + conn.rollback() # Rollback transaction on error continue - # Bước 2.5: Validate và clean orphaned foreign keys - print(f"\nStep 2.5: Validating foreign key integrity...") - cleaned_count = 0 + # Bước 2.3: Sample tables without primary keys based on FK relationships + print(f"\nStep 2.3: Sampling tables without primary keys...") + for table in tables: + if pk_columns.get(table) != 'ctid': + continue # Skip tables with primary keys + + if table in sampled_ids and sampled_ids[table]: + continue # Already sampled + + # Sample records from this table based on foreign key relationships + if table in fks and fks[table]: + print(f" Processing {table} (no PK)...") + + # Build WHERE clause based on all FKs + where_conditions = [] + for fk in fks[table]: + to_table = fk['to_table'] + from_col = fk['from_col'] + + if to_table in sampled_ids and sampled_ids[to_table]: + ids_str = format_ids_for_sql(list(sampled_ids[to_table])) + if ids_str and ids_str != "''": + where_conditions.append(f"{from_col} IN ({ids_str})") + + if where_conditions: + limit = min(1000, sample_size - total_records) + where_clause = " OR ".join(where_conditions) + + try: + # Get all columns for this table + cur.execute(f"SELECT column_name FROM information_schema.columns WHERE table_name = '{table}' ORDER BY ordinal_position") + all_columns = [row[0] for row in cur.fetchall()] + columns_str = ', '.join(all_columns) + + cur.execute(f""" + SELECT {columns_str} + FROM {table} + WHERE {where_clause} + LIMIT {limit} + """) + + rows = cur.fetchall() + if rows: + # Store as tuples (can't use IDs for tables without PK) + sampled_ids[table] = set(rows) + total_records += len(rows) + print(f" {table}: +{len(rows)} records (total: {len(rows)})") + + # IMPORTANT: Collect referenced entities from these rows + # Map column names to indices + col_name_to_idx = {col: idx for idx, col in enumerate(all_columns)} + + for fk in fks[table]: + to_table = fk['to_table'] + from_col = fk['from_col'] + to_col = fk['to_col'] + + # Skip if target table doesn't have PK (can't collect them) + if pk_columns.get(to_table) == 'ctid': + continue + + # Extract foreign key values from sampled rows + fk_col_idx = col_name_to_idx.get(from_col) + if fk_col_idx is not None: + fk_values = set() + for row in rows: + if row[fk_col_idx] is not None: + fk_values.add(row[fk_col_idx]) + + # Add these to sampled_ids for the referenced table + if fk_values: + new_fk_values = fk_values - sampled_ids.get(to_table, set()) + if new_fk_values: + if to_table not in sampled_ids: + sampled_ids[to_table] = set() + sampled_ids[to_table].update(new_fk_values) + total_records += len(new_fk_values) + print(f" -> {to_table}: +{len(new_fk_values)} records (from {from_col})") + except Exception as e: + print(f" {table}: Error - {e}") + conn.rollback() # Rollback transaction on error + + # Bước 2.5: Validate và ensure FK integrity by adding missing referenced records + print(f"\nStep 2.5: Ensuring foreign key integrity...") + added_count = 0 max_iterations = 10 for iteration in range(max_iterations): - removed_this_iteration = 0 + added_this_iteration = 0 for table in list(sampled_ids.keys()): + # Skip tables without primary keys - can't validate them the same way + if pk_columns.get(table) == 'ctid': + continue + if table not in fks or not fks[table]: continue - ids_to_remove = set() ids_list = list(sampled_ids[table]) - # Check each FK constraint + # Check each FK constraint and ADD missing referenced records for fk in fks[table]: to_table = fk['to_table'] - from_col = fk['from_col'] # Fixed: was 'from_column' + from_col = fk['from_col'] + to_col = fk['to_col'] - # Skip if target table has no sampled data - if to_table not in sampled_ids or not sampled_ids[to_table]: + # Skip if target table has no primary key + if pk_columns.get(to_table) == 'ctid': continue # Get FK values for sampled records @@ -677,42 +812,41 @@ def create_sample_sql(conn, db_name, target_db, sample_size, seed_records): if not ids_str or ids_str == "''": continue - target_ids_str = format_ids_for_sql(list(sampled_ids[to_table])) - if not target_ids_str or target_ids_str == "''": - continue - try: - # Find records with FK values not in target table's sampled IDs + # Find FK values that are NOT in the sampled set cur.execute(f""" - SELECT DISTINCT t.{pk_columns[table]} + SELECT DISTINCT t.{from_col} FROM {table} t WHERE t.{pk_columns[table]} IN ({ids_str}) AND t.{from_col} IS NOT NULL - AND t.{from_col}::text NOT IN ( - SELECT {pk_columns[to_table]}::text FROM {to_table} - WHERE {pk_columns[to_table]} IN ({target_ids_str}) - ) """) - orphaned = cur.fetchall() - for row in orphaned: - ids_to_remove.add(row[0]) + + fk_values = set(row[0] for row in cur.fetchall()) + + # Find which ones are missing from sampled_ids + existing_ids = sampled_ids.get(to_table, set()) + missing_ids = fk_values - existing_ids + + if missing_ids: + # Add these missing IDs to the sample + if to_table not in sampled_ids: + sampled_ids[to_table] = set() + sampled_ids[to_table].update(missing_ids) + added_this_iteration += len(missing_ids) + added_count += len(missing_ids) + print(f" {table}.{from_col} -> {to_table}: +{len(missing_ids)} referenced records") + except Exception as e: - print(f" Warning: Could not validate FK {table}.{from_col} -> {to_table}: {e}") + print(f" Warning: Could not check FK {table}.{from_col} -> {to_table}: {e}") + conn.rollback() continue - - # Remove orphaned records - if ids_to_remove: - sampled_ids[table] -= ids_to_remove - removed_this_iteration += len(ids_to_remove) - cleaned_count += len(ids_to_remove) - print(f" {table}: removed {len(ids_to_remove)} orphaned records") - if removed_this_iteration == 0: + if added_this_iteration == 0: print(f" Validation complete after {iteration + 1} iteration(s)") break - if cleaned_count > 0: - print(f"\nTotal orphaned records removed: {cleaned_count}") + if added_count > 0: + print(f"\nTotal FK-referenced records added: {added_count}") total_records = sum(len(ids) for ids in sampled_ids.values()) print(f"Clean sample size: {total_records} records") else: @@ -780,24 +914,54 @@ def create_sample_sql(conn, db_name, target_db, sample_size, seed_records): sql_lines.append(f"-- Table: {table} ({len(ids)} records)") - # Lấy dữ liệu thực tế từ database - ids_str = format_ids_for_sql(list(ids)) - if not ids_str or ids_str == "''": - print(f" Skipping {table} - no valid IDs") - continue - - query = f""" - SELECT {', '.join(col_names)} - FROM {table} - WHERE {pk_col} IN ({ids_str}) - """ + pk_col = pk_columns.get(table) - try: - cur.execute(query) - rows = cur.fetchall() - except Exception as e: - print(f" Error querying {table}: {e}") - continue + # For tables without primary key, data is already stored as full rows + if pk_col == 'ctid': + # Lấy danh sách các cột + cur.execute(f""" + SELECT column_name, data_type + FROM information_schema.columns + WHERE table_name = '{table}' + AND table_schema = 'public' + ORDER BY ordinal_position + """) + columns = cur.fetchall() + col_names = [col[0] for col in columns] + + # ids already contains full row tuples + rows = list(ids) + else: + # For tables with primary key, query by PK + # Lấy danh sách các cột + cur.execute(f""" + SELECT column_name, data_type + FROM information_schema.columns + WHERE table_name = '{table}' + AND table_schema = 'public' + ORDER BY ordinal_position + """) + columns = cur.fetchall() + col_names = [col[0] for col in columns] + + # Lấy dữ liệu thực tế từ database + ids_str = format_ids_for_sql(list(ids)) + if not ids_str or ids_str == "''": + print(f" Skipping {table} - no valid IDs") + continue + + query = f""" + SELECT {', '.join(col_names)} + FROM {table} + WHERE {pk_col} IN ({ids_str}) + """ + + try: + cur.execute(query) + rows = cur.fetchall() + except Exception as e: + print(f" Error querying {table}: {e}") + continue # Tạo INSERT statements if rows: From 5e6d8a436dd072fe9a4fe1a7304e424b298ea4ac Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Thu, 22 Jan 2026 01:26:52 +0700 Subject: [PATCH 38/42] :bug:bug: Performance not good in Task Builder --- AGENT_THINKING_FEATURE.md | 176 ----- ARCHITECTURE_DIAGRAM.md | 137 ---- Dockerfile.gpu | 2 +- SYSTEM_ARCHITECTURE_DEEP_DIVE.md | 736 ------------------ examples/rel-f1-driver-dnf.txt | 5 + examples/rel-f1-driver-position.txt | 6 + examples/rel-f1-driver-top3.txt | 6 + examples/rel-f1-result-position.txt | 6 + examples/rel-hm-item-sales.txt | 6 + examples/rel-hm-user-churn.txt | 4 + plexe/agents/task_builder.py | 10 +- .../chain_of_thought/websocket_emitter.py | 5 + plexe/relbench/datasets/__init__.py | 5 - plexe/relbench/datasets/amazon.py | 2 +- plexe/relbench/datasets/arxiv.py | 107 --- plexe/relbench/datasets/avito.py | 4 +- plexe/relbench/datasets/dbinfer.py | 2 +- plexe/relbench/datasets/event.py | 4 +- plexe/relbench/datasets/f1.py | 4 +- plexe/relbench/datasets/fake.py | 2 +- plexe/relbench/datasets/hm.py | 2 +- plexe/relbench/datasets/mimic.py | 591 -------------- plexe/relbench/datasets/ratebeer.py | 337 -------- plexe/relbench/datasets/salt.py | 163 ---- plexe/relbench/datasets/stack.py | 4 +- plexe/relbench/datasets/trial.py | 4 +- plexe/relbench/tasks/__init__.py | 4 - plexe/relbench/tasks/amazon.py | 4 +- plexe/relbench/tasks/arxiv.py | 240 ------ plexe/relbench/tasks/avito.py | 4 +- plexe/relbench/tasks/dbinfer.py | 179 ----- plexe/relbench/tasks/event.py | 4 +- plexe/relbench/tasks/f1.py | 8 +- plexe/relbench/tasks/hm.py | 4 +- plexe/relbench/tasks/mimic.py | 73 -- plexe/relbench/tasks/ratebeer.py | 483 ------------ plexe/relbench/tasks/stack.py | 4 +- plexe/relbench/tasks/trial.py | 4 +- plexe/server.py | 37 +- .../dataset_builder_prompt_templates.yaml | 43 +- ...ional_gnn_specialist_prompt_templates.yaml | 2 +- .../agent/task_builder_prompt_templates.yaml | 144 +--- plexe/tools/database_builder.py | 4 +- plexe/tools/task_builder.py | 200 +---- plexe/ui/frontend/src/App.jsx | 15 + plexe/ui/frontend/src/components/Chat.jsx | 14 +- plexe/ui/frontend/src/styles.css | 8 + test_training_table.py | 20 + 48 files changed, 225 insertions(+), 3603 deletions(-) delete mode 100644 AGENT_THINKING_FEATURE.md delete mode 100644 ARCHITECTURE_DIAGRAM.md delete mode 100644 SYSTEM_ARCHITECTURE_DEEP_DIVE.md create mode 100644 examples/rel-f1-driver-dnf.txt create mode 100644 examples/rel-f1-driver-position.txt create mode 100644 examples/rel-f1-driver-top3.txt create mode 100644 examples/rel-f1-result-position.txt create mode 100644 examples/rel-hm-item-sales.txt delete mode 100644 plexe/relbench/datasets/arxiv.py delete mode 100644 plexe/relbench/datasets/mimic.py delete mode 100644 plexe/relbench/datasets/ratebeer.py delete mode 100644 plexe/relbench/datasets/salt.py delete mode 100644 plexe/relbench/tasks/arxiv.py delete mode 100644 plexe/relbench/tasks/dbinfer.py delete mode 100644 plexe/relbench/tasks/mimic.py delete mode 100644 plexe/relbench/tasks/ratebeer.py create mode 100644 test_training_table.py diff --git a/AGENT_THINKING_FEATURE.md b/AGENT_THINKING_FEATURE.md deleted file mode 100644 index 6a98452d..00000000 --- a/AGENT_THINKING_FEATURE.md +++ /dev/null @@ -1,176 +0,0 @@ -# Agent Thinking Display Feature - -## Tổng quan (Overview) - -Tính năng này hiển thị quá trình suy nghĩ (thinking process) của các agent cùng với tên agent đang thực hiện trên giao diện chat theo thời gian thực. - -This feature displays the thinking processes of agents along with their names in real-time on the chat interface. - -## Các thay đổi chính (Main Changes) - -### 1. WebSocket Emitter mới (New WebSocket Emitter) -**File**: `/plexe/internal/common/utils/chain_of_thought/websocket_emitter.py` - -- Tạo `WebSocketEmitter` class kế thừa từ `ChainOfThoughtEmitter` -- Gửi messages về thinking process của agent qua WebSocket -- Xử lý async context để tương thích với FastAPI WebSocket - -**Chức năng**: -- Broadcast agent thinking messages đến WebSocket clients -- Theo dõi step count cho mỗi bước suy nghĩ -- Xử lý gracefully khi gọi từ synchronous context - -### 2. Cập nhật Server (Server Updates) -**File**: `/plexe/server.py` - -**Thay đổi**: -- Import `WebSocketEmitter`, `ChainOfThoughtCallable`, `MultiEmitter`, `ConsoleEmitter` -- Tạo multi-emitter kết hợp WebSocket và Console output -- Khởi tạo `ConversationalAgent` với chain of thought callback -- Agent giờ sẽ phát cả thinking messages và response messages - -**Luồng hoạt động**: -``` -User Message → Agent Processing → Thinking Steps (via WebSocket) → Final Response -``` - -### 3. Cập nhật Conversational Agent -**File**: `/plexe/agents/conversational.py` - -**Thay đổi**: -- Thêm parameter `chain_of_thought_callable` vào constructor -- Truyền callback vào `ToolCallingAgent` qua `step_callbacks` -- Agent bây giờ emit thinking messages trong quá trình xử lý - -### 4. Cập nhật Frontend (Vite/React) -**File**: `/plexe/ui/frontend/src/components/Chat.jsx` - -**Thay đổi**: -- Cập nhật `Message` component để xử lý `thinking` role -- Hiển thị thinking messages với format đặc biệt: - - Agent name - - Step number - - Thinking content -- Giữ nguyên display cho user và assistant messages - -### 5. Cập nhật CSS Styling -**File**: `/plexe/ui/frontend/src/styles.css` - -**Thêm styles cho**: -- `.message.thinking` - container cho thinking messages -- `.thinking-bubble` - bubble với gradient background -- `.thinking-header` - header hiển thị agent name và step -- `.thinking-content` - nội dung thinking message -- `.agent-name` và `.step-number` - styling cho metadata - -**Thiết kế**: -- Gradient background (blue tones) -- Border-left accent color -- Compact font size -- Centered alignment - -### 6. Cập nhật Legacy UI (index.html) -**File**: `/plexe/ui/index.html` - -**Thay đổi**: -- Cập nhật `Message` component để hỗ trợ thinking messages -- Sử dụng Tailwind CSS classes cho styling -- Tương tự layout như Vite frontend - -### 7. Cập nhật Module Exports -**File**: `/plexe/internal/common/utils/chain_of_thought/__init__.py` - -**Thay đổi**: -- Export `WebSocketEmitter` để có thể import -- Thêm vào `__all__` list - -## Cấu trúc Message (Message Structure) - -### Thinking Message Format -```json -{ - "type": "thinking", - "role": "thinking", - "agent_name": "ModelDefinitionAssistant", - "message": "💭 Thought: Analyzing user requirements...", - "step_number": 1 -} -``` - -### Regular Message Format -```json -{ - "role": "assistant", - "content": "I can help you build a model...", - "id": "uuid-here" -} -``` - -## Cách hoạt động (How It Works) - -1. **User gửi message** → WebSocket server nhận request -2. **Server khởi tạo**: - - WebSocketEmitter (gửi đến UI) - - ConsoleEmitter (log ra console) - - MultiEmitter (kết hợp cả hai) - - ChainOfThoughtCallable (callback handler) -3. **Agent xử lý**: - - Mỗi step trong quá trình reasoning - - Callback được gọi với step information - - WebSocketEmitter gửi thinking message đến UI -4. **Frontend nhận và hiển thị**: - - Thinking messages xuất hiện theo thời gian thực - - Mỗi message hiển thị agent name và step number - - Final response hiển thị như bình thường - -## Ví dụ UI (UI Example) - -``` -┌────────────────────────────────────────┐ -│ ModelDefinitionAssistant · Step 1 │ -│ 💭 Thought: Understanding the request │ -└────────────────────────────────────────┘ - -┌────────────────────────────────────────┐ -│ ModelDefinitionAssistant · Step 2 │ -│ 🔧 Tool: validate_dataset_files(...) │ -└────────────────────────────────────────┘ - -┌────────────────────────────────────────┐ -│ Assistant Response │ -│ I can help you with that... │ -└────────────────────────────────────────┘ -``` - -## Testing - -Để test tính năng: - -1. Khởi động server: - ```bash - cd /home/admin1/plexe-clone - docker compose -f docker-compose.dev.yml up -d - ``` - -2. Mở browser và truy cập UI - -3. Gửi một message yêu cầu model building - -4. Quan sát thinking messages xuất hiện theo thời gian thực - -## Notes - -- Thinking messages được gửi qua WebSocket trong async context -- Console output vẫn hoạt động song song để debugging -- Frontend tự động scroll xuống khi có messages mới -- CSS responsive cho mobile devices -- Hỗ trợ cả Vite build và legacy HTML UI - -## Future Enhancements - -Có thể cải thiện thêm: -- Toggle để ẩn/hiện thinking messages -- Filter theo agent name -- Export thinking log -- Collapse/expand thinking details -- Syntax highlighting cho code trong thinking messages diff --git a/ARCHITECTURE_DIAGRAM.md b/ARCHITECTURE_DIAGRAM.md deleted file mode 100644 index a5ae246d..00000000 --- a/ARCHITECTURE_DIAGRAM.md +++ /dev/null @@ -1,137 +0,0 @@ -# Agent Thinking Feature - Architecture Diagram - -``` -┌─────────────────────────────────────────────────────────────────────┐ -│ Browser (Frontend) │ -│ ┌────────────────────────────────────────────────────────────────┐ │ -│ │ Chat Component │ │ -│ │ - Displays user messages │ │ -│ │ - Displays assistant responses │ │ -│ │ - Displays thinking messages (NEW!) │ │ -│ │ ┌──────────────────────────────────────────────┐ │ │ -│ │ │ Thinking Message Display: │ │ │ -│ │ │ ┌────────────────────────────────────────┐ │ │ │ -│ │ │ │ Agent Name Step Number │ │ │ │ -│ │ │ ├────────────────────────────────────────┤ │ │ │ -│ │ │ │ Thinking content... │ │ │ │ -│ │ │ └────────────────────────────────────────┘ │ │ │ -│ │ └──────────────────────────────────────────────┘ │ │ -│ └────────────────────────────────────────────────────────────────┘ │ -│ ▲ │ -│ │ WebSocket Messages │ -│ │ {type: "thinking", agent_name, ...} │ -└──────────────────────────────┼──────────────────────────────────────┘ - │ -┌──────────────────────────────┼──────────────────────────────────────┐ -│ FastAPI Server │ -│ ┌────────────────────────────┴──────────────────────────────────┐ │ -│ │ WebSocket Endpoint (/ws) │ │ -│ │ │ │ -│ │ 1. Accept connection │ │ -│ │ 2. Create WebSocketEmitter ──┐ │ │ -│ │ 3. Create ConsoleEmitter ├─→ MultiEmitter ──┐ │ │ -│ │ │ │ │ │ -│ │ 4. Create ChainOfThoughtCallable ←───────────────┘ │ │ -│ │ │ │ │ -│ │ ▼ │ │ -│ │ 5. Initialize ConversationalAgent(chain_of_thought_callable) │ │ -│ │ │ │ │ -│ │ ▼ │ │ -│ │ 6. agent.run(user_message) ──────────────────┐ │ │ -│ │ │ │ │ -│ └────────────────────────────────────────────────┼────────────────┘ │ -└─────────────────────────────────────────────────┼────────────────────┘ - │ -┌─────────────────────────────────────────────────┼────────────────────┐ -│ Agent Execution Layer │ │ -│ ┌───────────────────────────────────────────────▼─────────────────┐ │ -│ │ ConversationalAgent │ │ -│ │ (ToolCallingAgent with step_callbacks) │ │ -│ │ │ │ -│ │ For each step in reasoning: │ │ -│ │ 1. Generate thought │ │ -│ │ 2. Call tool (optional) │ │ -│ │ 3. Observe result │ │ -│ │ 4. ────→ Trigger step_callbacks ────┐ │ │ -│ │ │ │ │ -│ └─────────────────────────────────────────┼────────────────────────┘ │ -└──────────────────────────────────────────┼─────────────────────────────┘ - │ -┌──────────────────────────────────────────┼─────────────────────────────┐ -│ Chain of Thought System │ │ -│ ┌────────────────────────────────────────▼──────────────────────┐ │ -│ │ ChainOfThoughtCallable.__call__(step, agent) │ │ -│ │ │ │ -│ │ 1. Extract step summary (StepSummary) │ │ -│ │ - agent_name │ │ -│ │ - step_number │ │ -│ │ - model_output (thought) │ │ -│ │ - tool_calls │ │ -│ │ - observations │ │ -│ │ │ │ -│ │ 2. Generate friendly summary │ │ -│ │ │ │ -│ │ 3. Emit to MultiEmitter ───────────────┐ │ │ -│ │ │ │ │ -│ └──────────────────────────────────────────┼─────────────────────┘ │ -│ │ │ -│ ┌──────────────────────────────────────────▼─────────────────────┐ │ -│ │ MultiEmitter │ │ -│ │ │ │ -│ │ ┌──────────────────────┐ ┌──────────────────────┐ │ │ -│ │ │ WebSocketEmitter │ │ ConsoleEmitter │ │ │ -│ │ │ │ │ │ │ │ -│ │ │ emit_thought(): │ │ emit_thought(): │ │ │ -│ │ │ - Create payload │ │ - Format with Rich │ │ │ -│ │ │ - Send via WS ──────┼────┼─→ Print to console │ │ │ -│ │ │ asyncio.create_ │ │ │ │ │ -│ │ │ task() │ │ │ │ │ -│ │ └──────────────────────┘ └──────────────────────┘ │ │ -│ │ │ │ │ -│ └───────────┼────────────────────────────────────────────────────┘ │ -└──────────────┼─────────────────────────────────────────────────────────┘ - │ - ▼ - WebSocket.send_json({ - "type": "thinking", - "role": "thinking", - "agent_name": "...", - "message": "...", - "step_number": N - }) - │ - ▼ - Frontend receives and displays - in thinking-bubble component -``` - -## Data Flow Summary - -1. **User sends message** → WebSocket → Server -2. **Server initializes** → ConversationalAgent with chain_of_thought_callable -3. **Agent processes** → Each step triggers callback -4. **ChainOfThoughtCallable** → Extracts step info → Emits to MultiEmitter -5. **MultiEmitter** → - - WebSocketEmitter → Send to browser (async) - - ConsoleEmitter → Print to server console -6. **Frontend receives** → Displays thinking message in UI -7. **Agent completes** → Final response sent to user - -## Key Components - -### Backend -- `WebSocketEmitter`: Sends thinking messages via WebSocket -- `ChainOfThoughtCallable`: Intercepts agent steps -- `MultiEmitter`: Broadcasts to multiple outputs -- `ConversationalAgent`: Main agent with callback support - -### Frontend -- `Message` component: Renders different message types -- `thinking-bubble` CSS: Styles for thinking messages -- WebSocket listener: Receives and displays messages - -## Message Types - -1. **User Message**: `{role: "user", content: "..."}` -2. **Thinking Message**: `{role: "thinking", agent_name: "...", message: "...", step_number: N}` -3. **Assistant Response**: `{role: "assistant", content: "..."}` diff --git a/Dockerfile.gpu b/Dockerfile.gpu index e0250c88..756ca6eb 100644 --- a/Dockerfile.gpu +++ b/Dockerfile.gpu @@ -61,7 +61,7 @@ RUN pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_co # ---------------------------- # BƯỚC 5: torch-geometric # ---------------------------- -RUN uv pip install torch-geometric +RUN uv pip install torch-geometric torch-frame # ---------------------------- # BƯỚC 6: sentence-transformers (for text embeddings in GNN training) diff --git a/SYSTEM_ARCHITECTURE_DEEP_DIVE.md b/SYSTEM_ARCHITECTURE_DEEP_DIVE.md deleted file mode 100644 index 87e56c0c..00000000 --- a/SYSTEM_ARCHITECTURE_DEEP_DIVE.md +++ /dev/null @@ -1,736 +0,0 @@ -# Hệ Thống Đa Tác Tử Plexe - Phân Tích Toàn Diện - -## 1. TỔNG QUAN HỆ THỐNG - -Plexe là một hệ thống **tự động xây dựng mô hình ML** sử dụng **arsitektur đa tác tử**. Hệ thống sử dụng LLM để tự động sinh code, training, evaluation, và deployment. - -### Kiến Trúc Cấp Cao -``` -User Intent + Datasets/DB → ModelBuilder → PlexeAgent (Orchestrator) → Trained Model + Inference Code -``` - ---- - -## 2. LUỒNG XỬ LÝ CHÍNH - -### 2.1 Bước 1: Khởi Tạo (ModelBuilder.build) -**File**: `plexe/model_builder.py` - -``` -ModelBuilder.build() { - 1. Kiểm tra input (datasets hoặc db_connection_string) - 2. Tạo ObjectRegistry (registry toàn cục) - 3. Đăng ký datasets hoặc connection string - 4. Tạo PlexeAgent (orchestrator) - 5. Chạy PlexeAgent.run() -} -``` - -**Output**: ModelGenerationResult (training code, inference code, predictor) - ---- - -## 3. PLEXE AGENT - ORCHESTRATOR - -**File**: `plexe/agents/agents.py` - -PlexeAgent là **orchestrator** chính điều phối tất cả các agents khác. Nó tạo một hệ thống các agents có công khai: - -### 3.1 Các Agents Chính - -| Agent | File | Mục Đích | Code? | -|-------|------|---------|-------| -| **MLResearchScientist** | `model_planner.py` | Lập kế hoạch ML solutions | ✓ ToolCallingAgent | -| **FeatureEngineer** | `feature_engineer.py` | Transform raw data thành features | ✓ CodeAgent | -| **DatasetSplitter** | `dataset_splitter.py` | Split datasets thành train/val | ✓ CodeAgent | -| **MLEngineer** | `model_trainer.py` | Implement training code | ✓✓ **Main Code Gen** | -| **MLOperationsEngineer** | `model_packager.py` | Generate inference code | ✓✓ **Main Code Gen** | -| **ModelTester** | `model_tester.py` | Test & evaluate model | ✓ CodeAgent | -| **RelationalGraphArchitect** | `relational_graph_architect.py` | Transform DB → Graph | ✓ CodeAgent (RDL) | -| **RelationalGNNSpecialist** | `relational_gnn_specialist.py` | Train GNNs on graphs | ✓ CodeAgent (RDL) | - ---- - -## 4. CHI TIẾT: AGENTS SINH CODE - -### 4.1 MLEngineer (Model Trainer Agent) - **SINH TRAINING CODE** - -**File**: `plexe/agents/model_trainer.py` - -Đây là agent **chính** sinh training code! - -#### Công Cụ Sử Dụng: -```python -tools=[ - get_training_code_generation_tool(tool_model_id), # Sinh code - validate_training_code, # Kiểm tra code - get_executor_tool(distributed), # Thực thi code - get_training_code_fixing_tool(tool_model_id), # Fix lỗi - get_dataset_schema, # Schema info - get_training_datasets, # Lấy data - ... -] -``` - -#### Quy Trình: -1. **Nhận input**: - - ML task definition (intent) - - Metric to optimize (name + comparison method) - - Solution ID từ ML Research Scientist - - Train/validation dataset names - - Working directory - -2. **Sinh training code**: - ```python - training_code = generate_training_code( - task=intent, - solution_plan=solution_plan, - train_datasets=["dataset_0"], - validation_datasets=["dataset_1"] - ) - ``` - -3. **Validate code**: - ```python - validate_training_code(code) - ``` - -4. **Execute code**: - ```python - execute_training_code( - solution_id=solution_id, - code=training_code, - working_dir=working_dir, - dataset_names=["dataset_0", "dataset_1"], - timeout=1800, - metric_to_optimise_name="accuracy", - metric_to_optimise_comparison_method="HIGHER_IS_BETTER" - ) - ``` - -5. **Lưu kết quả**: - - Training code lưu vào Solution object - - Model artifacts lưu vào ObjectRegistry - - Performance metric tính toán - -#### Code Generation Tool: -**File**: `plexe/tools/training.py` - -```python -@tool -def generate_training_code( - task: str, - solution_plan: str, - train_datasets: List[str], - validation_datasets: List[str] -) -> str: - train_generator = TrainingCodeGenerator(Provider(llm_to_use)) - return train_generator.generate_training_code(...) -``` - -**Điểm chính**: Agent sử dụng **TrainingCodeGenerator** từ `plexe/internal/models/generation/training.py` để sinh code. - ---- - -### 4.2 MLOperationsEngineer (Model Packager Agent) - **SINH INFERENCE CODE** - -**File**: `plexe/agents/model_packager.py` - -Sinh **production-ready inference code** từ training code. - -#### Công Cụ: -```python -tools=[ - get_inference_context_tool(tool_model_id), # Lấy context từ training - validate_inference_code, - list_solutions, -] -``` - -#### Quy Trình: -1. **Lấy training code** từ Solution -2. **Sinh inference wrapper**: - - Lớp `PredictorImplementation` - - Load model artifacts - - Implement `predict()` method -3. **Validate inference code** -4. **Lưu vào Solution object** - ---- - -### 4.3 FeatureEngineer - **SINH FEATURE TRANSFORMATION CODE** - -**File**: `plexe/agents/feature_engineer.py` - -Transform raw datasets. - -#### Công Cụ: -```python -tools=[ - get_dataset_preview, - validate_feature_transformations, - apply_feature_transformer, - get_dataset_reports, -] -``` - -#### Quy Trình: -1. Nhận EDA report -2. Sinh feature transformation code (pandas, sklearn) -3. Execute & lưu transformed datasets - ---- - -### 4.4 Agents Relational Deep Learning (RDL) - -Để xử lý **relational database** tasks: - -#### RelationalGraphArchitect -**File**: `plexe/agents/relational_graph_architect.py` - -**Mục đích**: Transform DB → Heterogeneous Graph - -**Công Cụ**: -```python -tools=[ - extract_schema_metadata, # Lấy schema từ DB - get_table_columns, # ⚠️ Kiểm tra column names! - load_table_data, - build_hetero_graph, # Xây dựng graph - encode_multi_modal_features, - create_entity_mapper, # Mapping entities -] -``` - -**Sinh code**: YES - Python code để xây dựng graph - ---- - -#### RelationalGNNSpecialist -**File**: `plexe/agents/relational_gnn_specialist.py` - -**Mục đích**: Train GNN trên graph - -**Công Cụ**: -```python -tools=[ - get_hetero_graph_from_registry, - load_training_data, - configure_temporal_sampler, - build_gnn_model, # Xây dựng model - train_gnn_epoch, # Training loop - evaluate_gnn, - save_gnn_model, -] -``` - -**Sinh code**: YES - PyTorch code cho GNN - ---- - -## 5. CHI TIẾT: CODE EXECUTION - -### 5.1 Execution Tool - -**File**: `plexe/tools/execution.py` - -```python -@tool -def execute_training_code( - solution_id: str, - code: str, - working_dir: str, - dataset_names: List[str], - timeout: int, - metric_to_optimise_name: str, - metric_to_optimise_comparison_method: str, -) -> Dict: - """Thực thi training code trong isolated environment""" - - # 1. Lấy datasets từ ObjectRegistry - datasets = {} - for name in dataset_names: - datasets[name] = object_registry.get(TabularConvertible, name) - - # 2. Tạo execution context - exec_context = { - 'pd': pd, - 'np': np, - 'datasets': datasets, - ... - } - - # 3. Execute code - exec(code, exec_context) - - # 4. Lấy kết quả (trainer, features, metrics) - trainer = exec_context.get('trainer') - features = exec_context.get('training_features') - - # 5. Lưu artifacts vào ObjectRegistry - for artifact in artifacts: - object_registry.register(Artifact, f"{solution_id}_{name}", artifact) - - # 6. Tính performance - performance = evaluate_solution(...) - - return { - 'status': 'success', - 'performance': performance.value, - 'artifacts': artifact_ids, - } -``` - -**Điểm chính**: -- Code chạy trong **isolated environment** -- Datasets lấy từ **ObjectRegistry** -- Artifacts lưu vào **ObjectRegistry** -- Có **timeout protection** - ---- - -## 6. CHI TIẾT: TRAINING PROCESS - -### 6.1 Quy Trình Training - -``` -1. MLResearchScientist { - - Phân tích intent, input/output schema - - Lập kế hoạch ML solutions - → Solutions: ID + plan -} - -2. FeatureEngineer { - - Analyze EDA reports - - Sinh feature transformation code - → Transformed datasets -} - -3. DatasetSplitter { - - Split train/validation datasets - → Split datasets -} - -4. MLEngineer { - ⭐ MAIN CODE GENERATION ⭐ - - Sinh training code - - Execute code (training loop) - - Compute performance - → Training code + Model artifacts + Performance -} - -5. MLOperationsEngineer { - - Sinh inference code (wrapper) - → Inference code -} - -6. ModelTester { - - Execute on test set - - Generate evaluation report - → Test performance + Report -} - -7. Orchestrator { - - Select best solution - - Format final output -} -``` - ---- - -## 7. CHI TIẾT: EVALUATION - -### 7.1 Performance Metrics - -**File**: `plexe/tools/metrics.py` - -```python -@tool -def get_select_target_metric(llm_to_use: str) -> str: - """Lựa chọn metric phù hợp""" - # Ví dụ: classification → accuracy - # Ví dụ: regression → RMSE -``` - -### 7.2 Model Review - -**File**: `plexe/tools/evaluation.py` - -```python -@tool -def review_finalised_model( - intent: str, - solution_id: str, -) -> dict: - """ - Review toàn bộ model: - - Input/output schemas - - Training code quality - - Inference code quality - - Expected performance - """ - reviewer = ModelReviewer(Provider(llm_to_use)) - return reviewer.review_model( - intent, - input_schema, - output_schema, - solution.plan, - solution.training_code, - solution.inference_code - ) -``` - -### 7.3 Solution Evaluation - -```python -@tool -def get_solution_performances() -> Dict[str, float]: - """Lấy performance của tất cả solutions""" - # Returns: { - # "solution_id_1": 0.95, - # "solution_id_2": 0.92, - # } -``` - ---- - -## 8. OBJECT REGISTRY - SHARED STATE - -**File**: `plexe/core/object_registry.py` - -Hệ thống sử dụng **ObjectRegistry** (singleton) để chia sẻ data giữa agents: - -```python -object_registry = ObjectRegistry() - -# Register -object_registry.register(TabularConvertible, "dataset_0", df) -object_registry.register(Solution, "solution_1", solution) -object_registry.register(Artifact, "artifact_model", model.pkl) - -# Retrieve -dataset = object_registry.get(TabularConvertible, "dataset_0") -solution = object_registry.get(Solution, "best_performing_solution") - -# List -all_solutions = object_registry.list_by_type(Solution) -``` - -**Tất cả agents** đều có access vào registry này! - ---- - -## 9. RELATIONAL DEEP LEARNING (RDL) PIPELINE - -Khi `db_connection_string` được cung cấp: - -### 9.1 Temporal Task Definition -``` -TemporalTaskSupervisor: -1. discover_temporal_columns() → Tìm time columns -2. execute_sql_query() → Lấy sample data -3. define_training_task() → Define prediction task -4. generate_sql_implementation() → Sinh SQL training table -5. generate_temporal_splits_from_db() → Create train/test splits -``` - -### 9.2 Graph Construction -``` -RelationalGraphArchitect: -1. extract_schema_metadata() → Load DB schema -2. get_table_columns() → Verify column names (⚠️ snake_case!) -3. load_table_data() → Fetch tables -4. build_hetero_graph() → Xây graph từ relationships -5. encode_multi_modal_features() → Feature encoding -``` - -### 9.3 GNN Training -``` -RelationalGNNSpecialist: -1. get_hetero_graph_from_registry() → Lấy graph -2. load_training_data() → Lấy labels -3. configure_temporal_sampler() → Time-aware sampling -4. build_gnn_model() → Xây PyTorch GNN -5. train_gnn_epoch() → Training loop -6. evaluate_gnn() → Evaluation -``` - -**Điểm quan trọng**: -- Snake_case columns: `owner_user_id` không phải `OwnerUserId` -- Temporal consistency: Không leak data từ future -- Graph structure: Multi-table relationships - ---- - -## 10. DEBUG CHECKLIST - -Để debug hệ thống cho relational database tasks: - -### 10.1 Input Validation -- [ ] `intent` rõ ràng? -- [ ] `input_schema` định nghĩa features từ DB? -- [ ] `output_schema` định nghĩa target? -- [ ] `db_connection_string` đúng? - -### 10.2 Temporal Task Phase -- [ ] `discover_temporal_columns()` tìm được time columns? -- [ ] `execute_sql_query()` chạy được SQL? -- [ ] `define_training_task()` define được task đúng? -- [ ] `generate_sql_implementation()` tạo được training table? - -### 10.3 Graph Construction Phase -- [ ] `extract_schema_metadata()` parse được schema? -- [ ] **`get_table_columns()` trả về đúng snake_case names?** ⚠️ -- [ ] `load_table_data()` fetch được data? -- [ ] `build_hetero_graph()` xây được graph? - -### 10.4 GNN Training Phase -- [ ] Graph được register trong ObjectRegistry? -- [ ] Training data (labels) được load? -- [ ] GNN model được build? -- [ ] Training loop chạy được? - -### 10.5 Code Generation -- [ ] Training code sinh được? -- [ ] Code validate pass? -- [ ] Code execute được trong isolated env? -- [ ] Inference code sinh được? - -### 10.6 Evaluation -- [ ] Metrics computed đúng? -- [ ] Best solution selected đúng? -- [ ] Final output format đúng? - ---- - -## 11. KEY FILES TO MONITOR - -``` -Core: -- plexe/models.py # Model class -- plexe/model_builder.py # ModelBuilder.build() entry -- plexe/agents/agents.py # PlexeAgent orchestrator - -Code Generation: -- plexe/agents/model_trainer.py # Training code generation -- plexe/agents/model_packager.py # Inference code generation -- plexe/tools/training.py # Training code tools -- plexe/internal/models/generation/ # Code generators - -RDL (Database): -- plexe/agents/relational_graph_architect.py # Graph construction -- plexe/agents/relational_gnn_specialist.py # GNN training -- plexe/tools/graph_processing.py # Graph tools -- plexe/tools/temporal_processing.py # Temporal tools -- plexe/tools/gnn_processing.py # GNN tools - -Execution: -- plexe/tools/execution.py # Code execution -- plexe/internal/models/execution/ # Execution engines - -Registry: -- plexe/core/object_registry.py # Shared state -- plexe/core/entities/solution.py # Solution object -``` - ---- - -## 12. EXECUTION FLOW DIAGRAM - -``` -ModelBuilder.build( - intent="Predict X from DB", - datasets=None, - db_connection_string="postgresql://..." -) - ↓ -ObjectRegistry.register(db_connection_string) - ↓ -PlexeAgent.run(task, additional_args) - ↓ -Orchestrator (CodeAgent managed_agents) - ├─→ MLResearchScientist (ToolCallingAgent) - │ ├─ get_dataset_preview() - │ ├─ get_solution_creation_tool() - │ └─ → Solution ID + plan - │ - ├─→ TemporalTaskSupervisor (CodeAgent) - │ ├─ discover_temporal_columns() - │ ├─ generate_sql_implementation() - │ └─ → Training table SQL + splits - │ - ├─→ RelationalGraphArchitect (CodeAgent) - │ ├─ extract_schema_metadata() - │ ├─ build_hetero_graph() - │ └─ → HeteroData graph in registry - │ - ├─→ DatasetSplitter (CodeAgent) - │ └─ → Train/val splits - │ - ├─→ FeatureEngineer (CodeAgent) - │ ├─ Sinh feature transformation code - │ └─ → Transformed datasets - │ - ├─→ MLEngineer (CodeAgent) ⭐ MAIN - │ ├─ generate_training_code() ← LLM sinh code - │ ├─ validate_training_code() - │ ├─ execute_training_code() - │ ├─ Metrics computation - │ └─ → Solution + training_code + performance - │ - ├─→ RelationalGNNSpecialist (CodeAgent) - │ ├─ build_gnn_model() - │ ├─ train_gnn_epoch() × N - │ ├─ evaluate_gnn() - │ └─ → GNN model + metrics - │ - ├─→ MLOperationsEngineer (CodeAgent) - │ ├─ get_inference_context_tool() - │ ├─ validate_inference_code() - │ └─ → Solution + inference_code - │ - ├─→ ModelTester (CodeAgent) - │ ├─ execute test code - │ ├─ generate_evaluation_report() - │ └─ → Test performance + report - │ - └─→ get_select_target_metric() - └─→ register_best_solution() - - ↓ -ModelGenerationResult { - training_source_code: str, - inference_source_code: str, - predictor: Predictor, - performance: Metric, - evaluation_report: Dict, -} -``` - ---- - -## 13. COMMON DEBUG SCENARIOS - -### Scenario 1: Generated Training Code Không Chạy - -**Kiểm tra**: -1. Code có syntax errors? → Check `validate_training_code()` output -2. Datasets format đúng? → Check dataset schema -3. Imports đúng? → Check `additional_authorized_imports` -4. Timeout? → Increase timeout parameter -5. Check execution environment → Process executor logs - -**Tools**: -- `plexe/tools/execution.py::execute_training_code()` -- `plexe/tools/validation.py::validate_training_code()` - ---- - -### Scenario 2: RDL Code Sinh Ra Sai Column Names - -**Kiểm tra**: -1. Column names snake_case? → Check DB schema -2. Agent gọi `get_table_columns()` không? → Force call -3. SQL query generate sai? → Check TemporalTaskSupervisor logs -4. Graph build sai? → Check RelationalGraphArchitect logs - -**Tools**: -- `plexe/tools/temporal_processing.py::get_table_columns()` -- `plexe/tools/graph_processing.py::get_table_columns()` - ---- - -### Scenario 3: Inference Code Không Load Model - -**Kiểm tra**: -1. Model artifacts saved? → Check ObjectRegistry -2. PredictorImplementation class tạo được? → Check model_packager logs -3. Model artifact path đúng? → Check artifact registration -4. Pickle/torch load được? → Check serialization - ---- - -## 14. QUICK START DEBUG - -```bash -# 1. Enable verbose logging -export PLEXE_VERBOSE=1 -export LOG_LEVEL=DEBUG - -# 2. Run with minimal config -python -c " -from plexe.model_builder import ModelBuilder -import pandas as pd - -df = pd.read_csv('sample.csv') -builder = ModelBuilder(verbose=True) -result = builder.build( - intent='Predict X from features', - datasets=[df], -) -print(f'Training code:\\n{result.training_source_code}') -print(f'Inference code:\\n{result.inference_source_code}') -print(f'Performance: {result.performance}') -" - -# 3. Check ObjectRegistry -from plexe.core.object_registry import ObjectRegistry -reg = ObjectRegistry() -print(reg.list()) - -# 4. Check Solution objects -from plexe.core.entities.solution import Solution -solutions = reg.list_by_type(Solution) -for sol_id in solutions: - sol = reg.get(Solution, sol_id) - print(f'{sol_id}: training_code={len(sol.training_code)} chars') -``` - ---- - -## 15. METRICS & PERFORMANCE - -Hệ thống track: -- **Training performance**: Metric trên validation set -- **Test performance**: Metric trên test set -- **Model size**: Model artifact size -- **Training time**: Execution time -- **Code quality**: Review scores - -**File**: `plexe/internal/models/entities/metric.py` - -```python -class Metric: - name: str # e.g., "accuracy" - value: float # e.g., 0.95 - comparator: MetricComparator # HIGHER_IS_BETTER / LOWER_IS_BETTER -``` - ---- - -## SUMMARY - -**Hệ thống Plexe hoạt động như sau**: - -1. **Input**: Intent + datasets/DB connection -2. **Planning**: MLResearchScientist → Solutions -3. **Preparation**: FeatureEngineer, DatasetSplitter → Processed data -4. **Training**: MLEngineer **sinh training code** + execute -5. **Inference**: MLOperationsEngineer **sinh inference code** -6. **Testing**: ModelTester → Evaluation report -7. **Selection**: Orchestrator selects best solution -8. **Output**: ModelGenerationResult (code + predictor + metrics) - -**Agents sinh code**: -- ✓ MLEngineer (Training code) -- ✓ MLOperationsEngineer (Inference code) -- ✓ FeatureEngineer (Feature transformation) -- ✓ TemporalTaskSupervisor (SQL + temporal handling) -- ✓ RelationalGraphArchitect (Graph construction) -- ✓ RelationalGNNSpecialist (GNN training) - -**Để debug relational database tasks**, focus on: -1. Temporal phase: Column discovery + SQL generation -2. Graph phase: Schema parsing + graph construction -3. GNN phase: Model building + training -4. Code generation phase: Code validation + execution diff --git a/examples/rel-f1-driver-dnf.txt b/examples/rel-f1-driver-dnf.txt new file mode 100644 index 00000000..80ab9d76 --- /dev/null +++ b/examples/rel-f1-driver-dnf.txt @@ -0,0 +1,5 @@ +I am working with the data is loaded into the `f1` database (connection string: `postgresql+psycopg2://mlflow:mlflow@postgres:5432/f1`). +I want to define a predictive task on this relational database. +- Task definition: For each driver predict the if they will DNF (did not finish) a race in the next 15 days. +- Evaluation metric: Area Under the Receiver Operating Characteristic curve (AUROC). +I don't have any requirements, if you need them you can set by default automatically. \ No newline at end of file diff --git a/examples/rel-f1-driver-position.txt b/examples/rel-f1-driver-position.txt new file mode 100644 index 00000000..458f5def --- /dev/null +++ b/examples/rel-f1-driver-position.txt @@ -0,0 +1,6 @@ +I am working with the data is loaded into the `f1` database (connection string: `postgresql+psycopg2://mlflow:mlflow@postgres:5432/f1`). +I want to define a predictive task on this relational database. +- Database Description: The F1 database tracks all-time Formula 1 racing data and statistics. It provides detailed information for various stakeholders including drivers, constructors, engine manufacturers, and tyre manufacturers. Highlights include data on all circuits (e.g. geographical details), and full historical data from every season. This includes overall standings, race results, and more specific data like practice sessions, qualifying positions, sprints, and pit stops. +- Task definition:Predict the average finishing position of each driver all races in the next 1 months. +- Evaluation metric: Mean Absolute Error (MAE) +I don't have any requirements, if you need them you can set by default automatically. \ No newline at end of file diff --git a/examples/rel-f1-driver-top3.txt b/examples/rel-f1-driver-top3.txt new file mode 100644 index 00000000..22cdaa0f --- /dev/null +++ b/examples/rel-f1-driver-top3.txt @@ -0,0 +1,6 @@ +I am working with the data is loaded into the `f1` database (connection string: `postgresql+psycopg2://mlflow:mlflow@postgres:5432/f1`). +I want to define a predictive task on this relational database. +- Database Description: The F1 database tracks all-time Formula 1 racing data and statistics. It provides detailed information for various stakeholders including drivers, constructors, engine manufacturers, and tyre manufacturers. Highlights include data on all circuits (e.g. geographical details), and full historical data from every season. This includes overall standings, race results, and more specific data like practice sessions, qualifying positions, sprints, and pit stops. +- Task definition:For each driver predict if they will qualify in the top-3 for a race in the next 15 days. +- Evaluation metric: Area Under the Receiver Operating Characteristic curve (AUROC). +I don't have any requirements, if you need them you can set by default automatically. \ No newline at end of file diff --git a/examples/rel-f1-result-position.txt b/examples/rel-f1-result-position.txt new file mode 100644 index 00000000..f5a3be48 --- /dev/null +++ b/examples/rel-f1-result-position.txt @@ -0,0 +1,6 @@ +I am working with the data is loaded into the `f1` database (connection string: `postgresql+psycopg2://mlflow:mlflow@postgres:5432/f1`). +I want to define a predictive task on this relational database. +- Database Description: The F1 database tracks all-time Formula 1 racing data and statistics. It provides detailed information for various stakeholders including drivers, constructors, engine manufacturers, and tyre manufacturers. Highlights include data on all circuits (e.g. geographical details), and full historical data from every season. This includes overall standings, race results, and more specific data like practice sessions, qualifying positions, sprints, and pit stops. +- Task definition: For each race result, predict the finishing position +- Evaluation metric: Mean Absolute Error (MAE) +I don't have any requirements, if you need them you can set by default automatically. \ No newline at end of file diff --git a/examples/rel-hm-item-sales.txt b/examples/rel-hm-item-sales.txt new file mode 100644 index 00000000..07a89d27 --- /dev/null +++ b/examples/rel-hm-item-sales.txt @@ -0,0 +1,6 @@ +I am working with the data is loaded into the `hm` database (connection string: `postgresql+psycopg2://mlflow:mlflow@postgres:5432/hm`). +I want to define a predictive task on this relational database. +- Database Description: The H&M relational database hosts extensive customer and product data for online shopping experiences across its extensive network of brands and stores. This database includes detailed customer purchase histories and a rich set of metadata, encompassing everything from basic demographic information to extensive details about each product available. +- Task definition:Predict the total sales for an article (the sum of prices of the associated transactions) in the next week. +- Evaluation metric: Mean Absolute Error (MAE). +I don't have any requirements, if you need them you can set by default automatically. \ No newline at end of file diff --git a/examples/rel-hm-user-churn.txt b/examples/rel-hm-user-churn.txt index 423f856b..73012ddf 100644 --- a/examples/rel-hm-user-churn.txt +++ b/examples/rel-hm-user-churn.txt @@ -1,2 +1,6 @@ I am working with the data is loaded into the `hm` database (connection string: `postgresql+psycopg2://mlflow:mlflow@postgres:5432/hm`). I want to define a predictive task on this relational database. +- Database Description: The H&M relational database hosts extensive customer and product data for online shopping experiences across its extensive network of brands and stores. This database includes detailed customer purchase histories and a rich set of metadata, encompassing everything from basic demographic information to extensive details about each product available. +- Task definition:Predict the churn for a customer (no transactions) in the next week. +- Evaluation metric: Area Under the Receiver Operating Characteristic curve (AUROC). +I don't have any requirements, if you need them you can set by default automatically. \ No newline at end of file diff --git a/plexe/agents/task_builder.py b/plexe/agents/task_builder.py index f92595e5..a223f03c 100644 --- a/plexe/agents/task_builder.py +++ b/plexe/agents/task_builder.py @@ -28,7 +28,6 @@ test_sql_query, analyze_potential_tasks, validate_task_code, - save_task_to_file, register_task_code, export_task_code, get_entity_task_template, @@ -97,11 +96,10 @@ def __init__( get_entity_task_template, get_recommendation_task_template, get_sql_query_examples, - # Validation and export (PREFERRED: use save_task_to_file) + # Validation and registration validate_task_code, - save_task_to_file, # Simpler: directly writes code to file - register_task_code, # Legacy: 2-step process - export_task_code, # Legacy: requires register first + register_task_code, + export_task_code, ], prompt_templates=get_prompt_templates( base_template_name="code_agent.yaml", @@ -120,7 +118,7 @@ def __init__( "pandas", "pandas.*", "numpy", - "numpy.*", + "numpy.*", "duckdb", "duckdb.*", "os", diff --git a/plexe/internal/common/utils/chain_of_thought/websocket_emitter.py b/plexe/internal/common/utils/chain_of_thought/websocket_emitter.py index f771a0cd..a096cc0d 100644 --- a/plexe/internal/common/utils/chain_of_thought/websocket_emitter.py +++ b/plexe/internal/common/utils/chain_of_thought/websocket_emitter.py @@ -119,6 +119,10 @@ def emit_thought(self, agent_name: str, message: str) -> None: agent_name: The name of the agent emitting the thought message: The thought message """ + # Check if closed before emitting + if self.is_closed: + raise RuntimeError("Agent execution stopped by user") + try: with self._lock: self.step_count += 1 @@ -137,6 +141,7 @@ def emit_thought(self, agent_name: str, message: str) -> None: except Exception as e: logger.error(f"Error emitting thought to WebSocket: {e}") + raise def _emit_payload(self, payload: dict): """Internal helper to send payload via WebSocket.""" diff --git a/plexe/relbench/datasets/__init__.py b/plexe/relbench/datasets/__init__.py index da153e37..07371c2d 100644 --- a/plexe/relbench/datasets/__init__.py +++ b/plexe/relbench/datasets/__init__.py @@ -8,15 +8,10 @@ from ..base import Dataset from ..datasets import ( amazon, - arxiv, avito, - dbinfer, event, f1, hm, - mimic, - ratebeer, - salt, stack, trial, ) diff --git a/plexe/relbench/datasets/amazon.py b/plexe/relbench/datasets/amazon.py index 459e9459..407fb917 100644 --- a/plexe/relbench/datasets/amazon.py +++ b/plexe/relbench/datasets/amazon.py @@ -5,7 +5,7 @@ import pyarrow as pa import pyarrow.json -from relbench.base import Database, Dataset, Table +from ..base import Database, Dataset, Table class AmazonDataset(Dataset): diff --git a/plexe/relbench/datasets/arxiv.py b/plexe/relbench/datasets/arxiv.py deleted file mode 100644 index feb25400..00000000 --- a/plexe/relbench/datasets/arxiv.py +++ /dev/null @@ -1,107 +0,0 @@ -import os - -import pandas as pd -import pooch -from sklearn.preprocessing import LabelEncoder - -from relbench.base import Database, Dataset, Table - - -class ArxivDataset(Dataset): - val_timestamp = pd.Timestamp("2022-01-01") - test_timestamp = pd.Timestamp("2023-01-01") - - def make_db(self) -> Database: - r"""Process the raw files into a database.""" - - url = ( - "https://www.dropbox.com/scl/fi/tjj6r1fqikt4j0rz4qomu/db.zip?rlkey=1ykfkp8pj3hu6n4utz8g9dkx2&st" - "=azmm56dc&dl=1" - ) - - path = pooch.retrieve( - url, - known_hash="ff9e03e467e28df959d08c79c453db1f31b525f07ff3c0e0b5e571e732acc63f", - progressbar=True, - processor=pooch.Unzip(), - ) - - if isinstance(path, list): - path = os.path.dirname(path[0]) - - print("Final dataset directory:", path) - - papers = pd.read_csv(os.path.join(path, "1Paper.csv")) - categories = pd.read_csv(os.path.join(path, "2Category.csv")) - citations = pd.read_csv(os.path.join(path, "3Citation.csv")) - paperCategories = pd.read_csv(os.path.join(path, "4Paper_Category.csv")) - authors = pd.read_csv(os.path.join(path, "5Author.csv")) - paperAuthors = pd.read_csv(os.path.join(path, "6Paper_Author.csv")) - - # Convert category column to integer - le = LabelEncoder() - categories["Category"] = le.fit_transform(categories["Category"]) - - # Convert date column to pd.Timestamp - papers["Submission_Date"] = pd.to_datetime( - papers["Submission_Date"], format="%Y%m%d" - ) - citations["Submission_Date"] = pd.to_datetime( - citations["Submission_Date"], format="%Y%m%d" - ) - paperAuthors["Submission_Date"] = pd.to_datetime( - paperAuthors["Submission_Date"], format="%Y%m%d" - ) - - # add time column to other tables - paperCategories = paperCategories.merge( - papers[["Paper_ID", "Submission_Date"]], on="Paper_ID", how="left" - ) - - # collect all tables in the database as relbench.base.Table objects. - tables = { - "papers": Table( - df=pd.DataFrame(papers), - fkey_col_to_pkey_table={}, - pkey_col="Paper_ID", - time_col="Submission_Date", - ), - "categories": Table( - df=pd.DataFrame(categories), - fkey_col_to_pkey_table={}, - pkey_col="Category_ID", - time_col=None, - ), - "citations": Table( - df=pd.DataFrame(citations), - fkey_col_to_pkey_table={ - "Paper_ID": "papers", - "References_Paper_ID": "papers", - }, - pkey_col=None, - time_col="Submission_Date", - ), - "paperCategories": Table( - df=pd.DataFrame(paperCategories), - fkey_col_to_pkey_table={ - "Paper_ID": "papers", - "Category_ID": "categories", - }, - pkey_col=None, - time_col="Submission_Date", - ), - "authors": Table( - df=pd.DataFrame(authors), - fkey_col_to_pkey_table={}, - pkey_col="Author_ID", - time_col=None, - ), - "paperAuthors": Table( - df=pd.DataFrame(paperAuthors), - fkey_col_to_pkey_table={"Paper_ID": "papers", "Author_ID": "authors"}, - pkey_col=None, - time_col="Submission_Date", - ), - } - - return Database(tables) diff --git a/plexe/relbench/datasets/avito.py b/plexe/relbench/datasets/avito.py index 16160b65..5419d796 100644 --- a/plexe/relbench/datasets/avito.py +++ b/plexe/relbench/datasets/avito.py @@ -3,8 +3,8 @@ import pandas as pd import pooch -from relbench.base import Database, Dataset, Table -from relbench.utils import clean_datetime, unzip_processor +from ..base import Database, Dataset, Table +from ..utils import clean_datetime, unzip_processor class AvitoDataset(Dataset): diff --git a/plexe/relbench/datasets/dbinfer.py b/plexe/relbench/datasets/dbinfer.py index 2178c8d9..6c0fa4ec 100644 --- a/plexe/relbench/datasets/dbinfer.py +++ b/plexe/relbench/datasets/dbinfer.py @@ -4,7 +4,7 @@ import pandas as pd import pooch -from relbench.base import Database, Dataset, Table +from ..base import Database, Dataset, Table DEFAULT_DBINFER_ADAPTER_CACHE = os.path.join( pooch.os_cache("relbench"), "dbinfer-adapters" diff --git a/plexe/relbench/datasets/event.py b/plexe/relbench/datasets/event.py index 78269080..1ccd2ab1 100644 --- a/plexe/relbench/datasets/event.py +++ b/plexe/relbench/datasets/event.py @@ -4,8 +4,8 @@ import pandas as pd -from relbench.base import Database, Dataset, Table -from relbench.utils import decompress_gz_file +from ..base import Database, Dataset, Table +from ..utils import decompress_gz_file class EventDataset(Dataset): diff --git a/plexe/relbench/datasets/f1.py b/plexe/relbench/datasets/f1.py index 797b8cd9..b9752eb9 100644 --- a/plexe/relbench/datasets/f1.py +++ b/plexe/relbench/datasets/f1.py @@ -4,8 +4,8 @@ import pandas as pd import pooch -from relbench.base import Database, Dataset, Table -from relbench.utils import unzip_processor +from ..base import Database, Dataset, Table +from ..utils import unzip_processor class F1Dataset(Dataset): diff --git a/plexe/relbench/datasets/fake.py b/plexe/relbench/datasets/fake.py index a587e437..2a6db23e 100644 --- a/plexe/relbench/datasets/fake.py +++ b/plexe/relbench/datasets/fake.py @@ -4,7 +4,7 @@ import numpy as np import pandas as pd -from relbench.base import Database, Dataset, Table +from ..base import Database, Dataset, Table def _generate_random_string(min_length: int, max_length: int) -> str: diff --git a/plexe/relbench/datasets/hm.py b/plexe/relbench/datasets/hm.py index 3d35ddce..4af1e338 100644 --- a/plexe/relbench/datasets/hm.py +++ b/plexe/relbench/datasets/hm.py @@ -4,7 +4,7 @@ import pandas as pd -from relbench.base import Database, Dataset, Table +from ..base import Database, Dataset, Table class HMDataset(Dataset): diff --git a/plexe/relbench/datasets/mimic.py b/plexe/relbench/datasets/mimic.py deleted file mode 100644 index d89f96eb..00000000 --- a/plexe/relbench/datasets/mimic.py +++ /dev/null @@ -1,591 +0,0 @@ -import os -import time -from pathlib import Path - -import pandas as pd - -from relbench.base import Database, Dataset, Table - - -def verify_mimic_access() -> None: - """Verify that the user has proper access to MIMIC-IV dataset through PhysioNet - credentialing. - - Verification is done by attempting a small query to the dataset. - """ - print("Verifying MIMIC-IV access...") - try: - from google.cloud import bigquery - - table_id = "physionet-data.mimiciv_3_1_hosp.patients" - project = os.getenv("PROJECT_ID") - client = bigquery.Client(project=project) - client.get_table(table_id) - client.query("SELECT 1").result() - print("MIMIC-IV access verified.") - except Exception as e: - raise RuntimeError( - f"\nACCESS FAILED - BigQuery credential check encountered an error: {e}" - ) - - -def find_time_col(columns): - for col in [ - "admittime", - "startdate", - "chartdate", - "transfertime", - "charttime", - "intime", - "starttime", - ]: - if col in columns: - return col - return None - - -def format_ids(series: pd.Series) -> list: - return list(map(int, series.dropna().unique())) - - -def convert_dtypes(df: pd.DataFrame) -> pd.DataFrame: - # Create a mapping for common extension dtypes - dtype_mapping = { - "Int64": int, - "Int32": int, - "Float64": float, - "boolean": bool, - "object": str, - # 'string': 'object' - } - - # Apply to all columns that have extension dtypes - converted_dtypes = {} - for col in df.columns: - original_dtype = str(df[col].dtype) - if original_dtype in dtype_mapping: - # we need to fill NA for number conversion.. - if dtype_mapping[original_dtype] in (int, float, complex): - df[col] = df[col].fillna(0) - converted_dtypes[col] = dtype_mapping[original_dtype] - elif ( - original_dtype.startswith("datetime") - or "date" in col.lower() - or "time" in col.lower() - ): - try: - df[col] = pd.to_datetime(df[col], errors="coerce") - except Exception: - print("WARNING ") - pass - - return df.astype(converted_dtypes) - - -def filter_chartevents(table): - print("Filtering chartevents to only include numeric values") - chart_df = table.df - - numeric_mask = chart_df["valuenum"].notnull() & ( - chart_df["value"].astype(str) == chart_df["valuenum"].astype(str) - ) - chartevents_numeric = chart_df[numeric_mask].copy() - chartevents_numeric = chartevents_numeric.drop(columns=["value"]) - chartevents_numeric["valuenum"] = pd.to_numeric( - chartevents_numeric["valuenum"], errors="coerce" - ) - return Table( - df=chartevents_numeric, - fkey_col_to_pkey_table=table.fkey_col_to_pkey_table, - pkey_col=table.pkey_col, - time_col=table.time_col, - ) - - -class MimicDataset(Dataset): - """A dataset class for loading and processing MIMIC-IV data into a format suitable - for use with RelBench. This class extracts a subset of tables specified in - `tables_limit`, filters the data based on ICU stay and patient criteria, and allows - optional column dropouts to reduce dimensionality or remove irrelevant fields. - - The dataset is anchored around ICU stays (`icustays`) and patients (`patients`) and constructs all other - tables with respect to these entities. - - If certain parameters are not provided, default values will be used. - - Parameters: - project_id (str): Google Cloud project ID for BigQuery. - patients_limit (int): Maximum number of patients to include in the dataset (0 means no limit; defaults to 20 000 if not specified). - saving_data (bool): Whether to persist processed tables to disk as .H5 files (default: True). - out_path (str): Output directory to save HDF5 files (default: "data"). - cache_dir (str): Directory used for caching dataset. - tables_limit (list): List of table names to include in the dataset (default: common MIMIC-IV tables). - drop_columns_per_table (dict): Dictionary specifying columns to drop per table (default: predefined subset per table). - min_age (int): Minimum patient age in years to include (default: 15). - min_dur (int): Minimum ICU stay duration in hours (default: 36). - max_dur (int): Maximum ICU stay duration in hours (default: 240). - location (str): Location for BigQuery client (default: 'US'). - dataset_name (str): Name of the BigQuery dataset (default: 'physionet-data'). - - Example: - drop_columns_per_table = { - "admissions": [...], - "chartevents": [...], - ... - } - tables_limit = ["patients", "admissions", "icustays", "chartevents", "procedureevents", "d_items"] - - dataset = MimicDataset( - patients_limit=20 000, - out_path='/data', - cache_dir='/cache', - tables_limit=tables_limit, - db_params=db_params, - drop_columns_per_table=drop_columns_per_table - ) - db = dataset.make_db() - """ - - def __init__( - self, - project_id: str = None, - patients_limit: int = -1, - saving_data: bool = True, - out_path: str = "data", - cache_dir: str = None, - tables_limit: list = None, - drop_columns_per_table=None, - min_age: int = 15, - min_dur: int = 36, - max_dur: int = 240, - location: str = "US", - dataset_name: str = "physionet-data", - ): - # Lazy import to avoid requiring google-cloud-bigquery for other datasets - from google.cloud import bigquery - - super().__init__(cache_dir=cache_dir) - - # Load environment variables from .env file (lazy import for optional dependency) - try: - from dotenv import load_dotenv - - load_dotenv() - except ImportError: - # dotenv is optional - if not available, env vars can still be set manually - pass - - # Use environment variable if project_id not provided - if project_id is None: - try: - project_id = os.getenv("PROJECT_ID") - except: - raise ValueError( - "project_id is required: set MIMIC_BQ_PROJECT_ID environment variable (i.e. export MIMIC_BQ_PROJECT_ID='your-project_id')" - ) - - if drop_columns_per_table is None: - print(f"drop_columns_per_table not provided, dropping default.") - drop_columns_per_table = { - "admissions": [ - "admittime", - "dischtime", - "deathtime", - "edouttime", - "edregtime", - "hospital_expire_flag", - "discharge_location", - "race", - ], - "chartevents": ["storetime"], - "procedureevents": [ - "storetime", - "endtime", - "location", - "location_category", - "location", - "locationcategory", - "linkorderid", - "originalamount", - "originalrate", - ], - "d_items": ["abbreviation"], - } - - if tables_limit is None: - print(f"tables_limit not provided setting to default.") - tables_limit = [ - "patients", - "admissions", - "icustays", - "chartevents", - "procedureevents", - "d_items", - ] - - if patients_limit == -1: - patients_limit = 20000 - print(f"patients_limit not provided setting to default {patients_limit}.") - - self.query_args = [ - bigquery.ScalarQueryParameter("limit", "INT64", patients_limit), - bigquery.ScalarQueryParameter("min_age", "INT64", min_age), - bigquery.ScalarQueryParameter("min_dur", "INT64", min_dur), - bigquery.ScalarQueryParameter("max_dur", "INT64", max_dur), - bigquery.ScalarQueryParameter("min_day", "FLOAT64", float(min_dur) / 24), - ] - - self.saving_data = saving_data - self.patients_limit = patients_limit - self.drop_columns_per_table = drop_columns_per_table - - self.tables_limit = tables_limit - - # If a cached RelBench copy exists (e.g., downloaded db.zip), reuse it and - # avoid hitting BigQuery. - cached_db_dir = Path(cache_dir) / "db" if cache_dir is not None else None - if cached_db_dir and cached_db_dir.exists() and any(cached_db_dir.iterdir()): - print( - f"Found cached MIMIC database at {cached_db_dir}, skipping BigQuery build." - ) - cached_db = Database.load(cached_db_dir) - self._set_timestamps_from_icustays(cached_db.table_dict["icustays"].df) - return - - # Create the output directory if it doesn't exist - current_dir = os.getcwd() - self.out_path = Path(current_dir) / out_path / f"limit_{patients_limit}" - if saving_data: - self.out_path.mkdir(parents=True, exist_ok=True) - print("Data will be saved to", self.out_path) - - self.client = bigquery.Client(project=project_id, location=location) - self.dataset_name = dataset_name - - # Set the test and validation timestamps - # this will be updated based on patients' ICU admission times - self.test_timestamp = None - self.val_timestamp = None - - print("Making database in __init__....") - self.make_db() - - def _set_timestamps_from_icustays(self, icustays_df: pd.DataFrame) -> None: - timestamps = ( - pd.to_datetime(icustays_df["intime"], errors="coerce") - .dropna() - .sort_values() - ) - if len(timestamps) == 0: - raise ValueError("Unable to set timestamps: icustays.intime is empty.") - - val_idx = int(len(timestamps) * 0.7) - test_idx = int(len(timestamps) * 0.85) - self.val_timestamp = timestamps.iloc[val_idx] - self.test_timestamp = timestamps.iloc[test_idx] - - def make_db(self) -> Database: - from google.cloud import bigquery - - start_time = time.time() - tables_df = {} - # while MIMIC IV dataset on BigQuery does not have primary and foreign keys set up properly (at all) - # we need to declare the relations statically here.. - table_names_schemas = { - "mimiciv_3_1_hosp": [["patients"], ["admissions"]], - "mimiciv_3_1_icu": [ - ["icustays"], - ["procedureevents"], - ["d_items"], - ["chartevents"], - ], - } - table_key_map = { - "patients": {"pkey_col": "subject_id", "fkey_col_to_pkey_table": {}}, - "icustays": { - "pkey_col": "stay_id", - "fkey_col_to_pkey_table": { - "hadm_id": "admissions", - "subject_id": "patients", - }, - }, - "admissions": { - "pkey_col": "hadm_id", - "fkey_col_to_pkey_table": {"subject_id": "patients"}, - }, - "procedureevents": { - "pkey_col": "orderid", - "fkey_col_to_pkey_table": { - "hadm_id": "admissions", - "itemid": "d_items", - "stay_id": "icustays", - "subject_id": "patients", - }, - }, - "d_items": {"pkey_col": "itemid", "fkey_col_to_pkey_table": {}}, - "chartevents": { - "pkey_col": None, - "fkey_col_to_pkey_table": { - "hadm_id": "admissions", - "itemid": "d_items", - "stay_id": "icustays", - "subject_id": "patients", - }, - }, - } - - tables_df["patients"] = Table( - df=self.get_patients(), - fkey_col_to_pkey_table=table_key_map["patients"]["fkey_col_to_pkey_table"], - pkey_col=table_key_map["patients"]["pkey_col"], - time_col=None, - ) - - query_params = [ - bigquery.ArrayQueryParameter( - "subject_ids", - "INT64", - format_ids(tables_df["patients"].df["subject_id"]), - ), - bigquery.ArrayQueryParameter( - "stay_ids", "INT64", format_ids(tables_df["patients"].df["stay_id"]) - ), - bigquery.ArrayQueryParameter( - "hadm_ids", "INT64", format_ids(tables_df["patients"].df["hadm_id"]) - ), - ] - - tables_df["icustays"] = Table( - df=self.get_icustays(query_params), - fkey_col_to_pkey_table=table_key_map["icustays"]["fkey_col_to_pkey_table"], - pkey_col=table_key_map["icustays"]["pkey_col"], - time_col="intime", - ) - query_params = [ - bigquery.ArrayQueryParameter( - "subject_ids", - "INT64", - format_ids(tables_df["icustays"].df["subject_id"]), - ), - bigquery.ArrayQueryParameter( - "stay_ids", "INT64", format_ids(tables_df["icustays"].df["stay_id"]) - ), - bigquery.ArrayQueryParameter( - "hadm_ids", "INT64", format_ids(tables_df["icustays"].df["hadm_id"]) - ), - ] - - for schema, tables in table_names_schemas.items(): - for (table_name,) in tables: - if table_name in {"patients", "icustays"}: - continue - h5_path = self.out_path / f"{table_name}_{self.patients_limit}.H5" - if not h5_path.exists(): - print(f"Creating {table_name}") - - # Create the query string - query_string = self.build_query(table_name, schema) - - print("Querying table:", table_name, end=" ") - # Execute the query - df = self.query( - query_string=query_string, query_params=query_params - ) - print(f"{len(df)} rows") - - # Drop columns if specified - if ( - self.drop_columns_per_table - and table_name in self.drop_columns_per_table - ): - df = self.drop_columns(table_name, df) - - # Save the DataFrame to HDF5 if saving_data is True - if self.saving_data: - df.to_hdf(h5_path, key="table", index=False) - print(f"Table {table_name} saved to {h5_path}") - else: - print( - f"️File {table_name}_{self.patients_limit}.H5 already exists. Skipping..." - ) - df = pd.read_hdf(h5_path, key="table") - - # Create the Table object for the current table - tables_df[table_name] = Table( - df=df, - fkey_col_to_pkey_table=table_key_map[table_name][ - "fkey_col_to_pkey_table" - ], - pkey_col=table_key_map[table_name]["pkey_col"], - time_col=find_time_col(df.columns), - ) - - # Filter chartevents to only include numeric values - tables_df["chartevents"] = filter_chartevents(tables_df["chartevents"]) - - # Change test and val timestamps based on patients limit - print("Setting test and val timestamps based on patients limit") - timestamps = ( - pd.to_datetime(tables_df["icustays"].df["intime"], errors="coerce") - .dropna() - .sort_values() - ) - n = len(timestamps) - - # Calculate the indices for 70% and 85% - # of the total number of timestamps - # 70% for train and 15% for validation and 15% for test - val_idx = int(n * 0.7) - test_idx = int(n * 0.85) - self.val_timestamp = timestamps.iloc[val_idx] - self.test_timestamp = timestamps.iloc[test_idx] - train_count = len(timestamps[timestamps < self.val_timestamp]) - val_count = len( - timestamps[ - (timestamps >= self.val_timestamp) & (timestamps < self.test_timestamp) - ] - ) - test_count = len(timestamps[timestamps >= self.test_timestamp]) - print("test_timestamp:", self.test_timestamp, end=" ") - print("val_timestamp:", self.val_timestamp) - print( - "Record split - Train:", train_count, "Val:", val_count, "Test:", test_count - ) - - end_time = time.time() - print(f"Done loading tables in {end_time - start_time:.2f} seconds") - return Database(tables_df) - - def get_patients(self): - patients_filename = "patients_" + str(self.patients_limit) + ".H5" - # Query the patients - patients_query = f""" - SELECT - i.subject_id, -- Unique patient identifier - i.hadm_id, -- Unique hospital admission ID - i.stay_id, -- Unique ICU stay ID - i.gender, -- Patient gender - ROUND(i.admission_age) AS age, -- Age of the patient at hospital admission - i.race -- Patient race/ethnicity - FROM `{self.dataset_name}.mimiciv_3_1_derived.icustay_detail` i - WHERE i.hadm_id IS NOT NULL - AND i.stay_id IS NOT NULL - AND i.hospstay_seq = 1 - AND i.icustay_seq = 1 - AND i.los_icu IS NOT NULL - AND i.admission_age >= @min_age - AND i.los_icu >= @min_day - AND (UNIX_SECONDS(TIMESTAMP(i.icu_outtime)) - UNIX_SECONDS(TIMESTAMP(i.icu_intime))) > (@min_dur*3600) - AND (UNIX_SECONDS(TIMESTAMP(i.icu_outtime)) - UNIX_SECONDS(TIMESTAMP(i.icu_intime))) < (@max_dur*3600) - AND EXISTS ( - SELECT 1 - FROM `{self.dataset_name}.mimiciv_3_1_icu.icustays` icu - WHERE icu.stay_id = i.stay_id - ) - QUALIFY - ROW_NUMBER() OVER (PARTITION BY i.subject_id ORDER BY i.icustay_seq DESC) = 1 - ORDER BY subject_id - """ - - if self.patients_limit > 0: - patients_query += "LIMIT @limit" - - H5_fpath = os.path.join(self.out_path, patients_filename) - if not os.path.exists(H5_fpath): - patients = self.query( - query_string=patients_query, query_params=self.query_args - ) - if self.saving_data: - patients.to_hdf(H5_fpath, key="patients", index=False) - print(f"Patients data saved to {H5_fpath}") - else: - print(f"File {patients_filename} already exists. Skipping...") - patients = pd.read_hdf(H5_fpath, key="patients") - return patients - - def get_icustays(self, params: list): - icustays_filename = "icustays_" + str(self.patients_limit) + ".H5" - H5_fpath = os.path.join(self.out_path, icustays_filename) - # Query the ICU_Stay - icustays_query = f""" - SELECT icu.subject_id, - icu.hadm_id, - icu.stay_id, - icu.intime, - icu.first_careunit, - icu_detail.los_icu - FROM `{self.dataset_name}.mimiciv_3_1_icu.icustays` AS icu - LEFT JOIN `{self.dataset_name}.mimiciv_3_1_derived.icustay_detail` AS icu_detail - ON icu.stay_id = icu_detail.stay_id - WHERE icu.subject_id IN UNNEST(@subject_ids) - AND icu.stay_id IN UNNEST(@stay_ids) - AND icu.hadm_id IN UNNEST(@hadm_ids) - AND icu_detail.los_icu IS NOT NULL - ORDER BY icu.subject_id - """ - if not os.path.exists(H5_fpath): - icustays = self.query(query_string=icustays_query, query_params=params) - icustays["los_icu"] = pd.to_numeric(icustays["los_icu"], errors="coerce") - if self.saving_data: - icustays.to_hdf(H5_fpath, key="icustays", index=False) - print(f"ICUStays data saved to {H5_fpath}") - else: - print(f"File {icustays_filename} already exists. Skipping...") - icustays = pd.read_hdf(H5_fpath, key="icustays") - - return icustays - - def build_query(self, table_name, schema): - columns = self.get_columns(table_name, schema) - conditions = [] - if "subject_id" in columns: - conditions.append("subject_id IN UNNEST(@subject_ids)") - if "stay_id" in columns: - conditions.append("stay_id IN UNNEST(@stay_ids)") - if "hadm_id" in columns: - conditions.append("hadm_id IN UNNEST(@hadm_ids)") - - if conditions: - where_clause = " WHERE " + " AND ".join(conditions) - else: - where_clause = "" - - query_string = ( - f"SELECT * FROM `{self.dataset_name}.{schema}.{table_name}`{where_clause};" - ) - return query_string - - def drop_columns(self, table_name, df): - drop_cols = list( - set(self.drop_columns_per_table[table_name]) & set(df.columns) - ) # intersection - if drop_cols: - df = df.drop(columns=drop_cols) - print(f"Dropped columns from {table_name}: {drop_cols}") - return df - - def get_columns(self, table_name, schema): - table_id = f"{self.dataset_name}.{schema}.{table_name}" - table = self.client.get_table(table_id) - - # Extract column names from the schema - column_names = [field.name for field in table.schema] - return column_names - - def query(self, query_string, query_params: list = []): - from google.cloud import bigquery - - job_config = bigquery.QueryJobConfig(query_parameters=query_params) - df = self.client.query_and_wait( - query_string, job_config=job_config - ).to_dataframe() - # for writing HDF5 files, we need simple types - - return convert_dtypes(df) - - -if __name__ == "__main__": - dataset = MimicDataset() - db = dataset.make_db() - mimic_db = dataset.get_db() - print(mimic_db) diff --git a/plexe/relbench/datasets/ratebeer.py b/plexe/relbench/datasets/ratebeer.py deleted file mode 100644 index 4efbe690..00000000 --- a/plexe/relbench/datasets/ratebeer.py +++ /dev/null @@ -1,337 +0,0 @@ -import os -import zipfile -from typing import Dict, List, Optional, Union - -import numpy as np -import pandas as pd -import pooch -from tqdm import tqdm - -from relbench.base import Database, Dataset, Table -from relbench.utils import unzip_processor - -# Update URL to Dropbox direct download link -DB_URL = "https://www.dropbox.com/scl/fi/exwygxep7vdvq55uiq28r/db.zip?rlkey=o7q0r8nw758p4wxx1wka9ubuj&st=rg3gvkxg&dl=1" - - -class RateBeerDataset(Dataset): - val_timestamp = pd.Timestamp("2018-09-01") - test_timestamp = pd.Timestamp("2020-01-01") - - name = "rel-ratebeer" - - def _process_timestamps( - self, df: pd.DataFrame, table_name: str, time_col: Optional[str] = None - ) -> pd.DataFrame: - """Convert timestamp columns to datetime and remove rows with NaT in the - designated time column.""" - # Convert timestamp columns - for col in ["created_at", "updated_at", "last_edited_at", "opened_at"]: - if col in df.columns: - df[col] = pd.to_datetime(df[col], format="mixed", errors="coerce") - - # Remove rows with NaT in the designated time_col - if time_col is not None: - if time_col in df.columns and df[time_col].isna().any(): - initial_rows = len(df) - nat_count = df[time_col].isna().sum() - print( - f"\nWarning: Found {nat_count} NaT value(s) in time column '{time_col}' for table '{table_name}'. Removing these rows." - ) - df = df.dropna(subset=[time_col]) - print( - f"Removed {initial_rows - len(df)} rows from {table_name}. New shape: {df.shape}" - ) - - return df - - def make_db(self) -> Database: - r"""Process the raw files into a database.""" - path = pooch.retrieve( - DB_URL, - known_hash="c3921164da60f8c97e6530d1f2872f7e0d307f8276348106db95c10c2df677ad", - progressbar=True, - processor=unzip_processor, - ) - - print("Reading from processed database...") - tables = {} - - beers = pd.read_csv(os.path.join(path, "db", f"beers.csv"), low_memory=False) - brewers = pd.read_csv( - os.path.join(path, "db", f"brewers.csv"), low_memory=False - ) - beer_styles = pd.read_csv( - os.path.join(path, "db", f"beer_styles.csv"), low_memory=False - ) - countries = pd.read_csv( - os.path.join(path, "db", f"countries.csv"), low_memory=False - ) - states = pd.read_csv(os.path.join(path, "db", f"states.csv"), low_memory=False) - users = pd.read_csv(os.path.join(path, "db", f"users.csv"), low_memory=False) - beer_ratings = pd.read_csv( - os.path.join(path, "db", f"beer_ratings.csv"), low_memory=False - ) - beer_upcs = pd.read_csv( - os.path.join(path, "db", f"beer_upcs.csv"), low_memory=False - ) - availability = pd.read_csv( - os.path.join(path, "db", f"availability.csv"), low_memory=False - ) - favorites = pd.read_csv( - os.path.join(path, "db", f"favorites.csv"), low_memory=False - ) - place_ratings = pd.read_csv( - os.path.join(path, "db", f"place_ratings.csv"), low_memory=False - ) - places = pd.read_csv(os.path.join(path, "db", f"places.csv"), low_memory=False) - place_types = pd.read_csv( - os.path.join(path, "db", f"place_types.csv"), low_memory=False - ) - - # ---------------------- Beers ---------------------- - beers = self._process_timestamps(beers, "beers", "created_at") - - beers.drop( - columns=[ - "contract_brewer_id", # 96.27% NA - "contract_note", # 99.96% NA - "featured_beer_id", # 100% NA - "producer_style", # 100% NA - "LogoImage", # 92.45% NA - "beer_jobber_id", # 99.65% NA - ], - inplace=True, - ) - - tables["beers"] = Table( - df=beers, - fkey_col_to_pkey_table={ - "brewer_id": "brewers", - "style_id": "beer_styles", - }, - pkey_col="beer_id", - time_col="created_at", - ) - - # ---------------------- Brewers ---------------------- - brewers.drop( - columns=[ - "newsletter_email", # 99.85% NA - "head_brewer", # 100% NA - "latitude", # 100% NA - "longitude", # 100% NA - "msa", # 83.42% NA - "instagram", # 95.55% NA - ], - inplace=True, - ) - - tables["brewers"] = Table( - df=brewers, - fkey_col_to_pkey_table={ - "country_id": "countries", - "state_id": "states", - "type_id": "place_types", - }, - pkey_col="brewer_id", - ) - - # ---------------------- Beer Styles ---------------------- - tables["beer_styles"] = Table( - df=beer_styles, - fkey_col_to_pkey_table={}, - pkey_col="style_id", - ) - - # ---------------------- Countries ---------------------- - tables["countries"] = Table( - df=countries, - fkey_col_to_pkey_table={}, - pkey_col="country_id", - ) - - # ---------------------- Users ---------------------- - users = self._process_timestamps(users, "users", "created_at") - - users.drop( - columns=[ - "favorite_first_added", # 98.44% NA - "favorite_last_added", # 98.44% NA - ], - inplace=True, - ) - - tables["users"] = Table( - df=users, - fkey_col_to_pkey_table={}, - pkey_col="user_id", - time_col="created_at", - ) - - # ---------------------- Beer Ratings ---------------------- - beer_ratings = self._process_timestamps( - beer_ratings, "beer_ratings", "created_at" - ) - - # Fix duplicate rating_id (rating_id = 1759935) - duplicate_mask = beer_ratings.duplicated(subset=["rating_id"], keep="first") - if duplicate_mask.any(): - print(f"Found {duplicate_mask.sum()} duplicate rating_id(s), fixing...") - max_rating_id = beer_ratings["rating_id"].max() - beer_ratings.loc[duplicate_mask, "rating_id"] += max_rating_id + 1 - - beer_ratings.drop( - columns=[ - "served_in", # 99.94% NA - "latitude", # 100% NA - "longitude", # 100% NA - ], - inplace=True, - ) - - tables["beer_ratings"] = Table( - df=beer_ratings, - fkey_col_to_pkey_table={ - "user_id": "users", - "beer_id": "beers", - "availability_id": "availability", - }, - pkey_col="rating_id", - time_col="created_at", - ) - - # ---------------------- Availability ---------------------- - availability = self._process_timestamps( - availability, "availability", time_col=None - ) - - availability.drop( - columns=[ - "area_code", # 100% NA - "rating_id", # 100% NA - "tap_lister", # 100% NA - ], - inplace=True, - ) - - tables["availability"] = Table( - df=availability, - fkey_col_to_pkey_table={ - "beer_id": "beers", - "place_id": "places", - "country_id": "countries", - "user_id": "users", - }, - pkey_col="avail_id", - ) - - # ---------------------- Beer UPCs ---------------------- - tables["beer_upcs"] = Table( - df=beer_upcs, - fkey_col_to_pkey_table={"beer_id": "beers"}, - pkey_col=None, # Same UPC may map to multiple beers - ) - - # ---------------------- Favorites ---------------------- - favorites = self._process_timestamps(favorites, "favorites", "created_at") - - tables["favorites"] = Table( - df=favorites, - fkey_col_to_pkey_table={ - "user_id": "users", - "beer_id": "beers", - }, - pkey_col="favorite_id", - time_col="created_at", - ) - - # ---------------------- Places ---------------------- - places.drop( - columns=[ - "email", # 100% NA - "opened_at", # 100% NA - "phone_country_code", # 100% NA - "last_edited_at", # 99.98% NA - # "score", # 86.23% NA - ], - inplace=True, - ) - - tables["places"] = Table( - df=places, - fkey_col_to_pkey_table={ - "state_id": "states", - "type_id": "place_types", - "country_id": "countries", - }, - pkey_col="place_id", - ) - - # ---------------------- Place Ratings ---------------------- - place_ratings = self._process_timestamps( - place_ratings, "place_ratings", "created_at" - ) - - place_ratings.drop( - columns=[ - "latitude", # 100% NA - "longitude", # 100% NA - ], - inplace=True, - ) - - tables["place_ratings"] = Table( - df=place_ratings, - fkey_col_to_pkey_table={ - "place_id": "places", - "user_id": "users", - }, - pkey_col="rating_id", - time_col="created_at", - ) - - # ---------------------- Place Types ---------------------- - tables["place_types"] = Table( - df=place_types, - fkey_col_to_pkey_table={}, - pkey_col="type_id", - ) - - # ---------------------- States ---------------------- - states.drop( - columns=[ - "Abbrev", # 86.66% NA - # "hasbrewer", # 79.58% NA - ], - inplace=True, - ) - - tables["states"] = Table( - df=states, - fkey_col_to_pkey_table={"country_id": "countries"}, - pkey_col="state_id", - ) - - print("\nAll tables loaded successfully!") - return Database(tables) - - -if __name__ == "__main__": - ratebeer_dataset = RateBeerDataset() - ratebeer_db = ratebeer_dataset.make_db() - - total_rows = 0 - total_cols = 0 - - # Print table statistics - for table_name, table in ratebeer_db.table_dict.items(): - print(f"Number of rows in {table_name} table: {table.df.shape[0]}") - print(f"Sample of {table_name} table:") - print(table.df.head()) - print() - total_rows += table.df.shape[0] - total_cols += table.df.shape[1] - - print(f"Total number of rows: {total_rows}") - print(f"Total number of columns: {total_cols}") diff --git a/plexe/relbench/datasets/salt.py b/plexe/relbench/datasets/salt.py deleted file mode 100644 index 2416e131..00000000 --- a/plexe/relbench/datasets/salt.py +++ /dev/null @@ -1,163 +0,0 @@ -import os - -import pandas as pd -import pooch -from datasets import load_dataset -from datasets.exceptions import DatasetNotFoundError - -from relbench.base import Database, Dataset, Table - - -class SALTDataset(Dataset): - - val_timestamp = pd.Timestamp("2020-02-01") - test_timestamp = pd.Timestamp("2020-07-01") - - header_target_cols = [ - "SALESOFFICE", - "SALESGROUP", - "CUSTOMERPAYMENTTERMS", - "SHIPPINGCONDITION", - "HEADERINCOTERMSCLASSIFICATION", - ] - item_target_cols = ["PLANT", "SHIPPINGPOINT", "ITEMINCOTERMSCLASSIFICATION"] - all_target_cols = header_target_cols + item_target_cols - - def __init__(self, **kwargs): - - super().__init__(**kwargs) - - def make_db(self) -> Database: - r"""Process the raw files into a database.""" - - try: - _split = "train+test" - salesdocument = load_dataset( - "sap-ai-research/SALT", "salesdocuments", split=_split - ).to_pandas() - salesdocumentitem = load_dataset( - "sap-ai-research/SALT", "salesdocument_items", split=_split - ).to_pandas() - customer = load_dataset( - "sap-ai-research/SALT", "customers", split=_split - ).to_pandas() - address = load_dataset( - "sap-ai-research/SALT", "addresses", split=_split - ).to_pandas() - - # Rename the incoterm columns for clarity - salesdocument = salesdocument.rename( - columns={"INCOTERMSCLASSIFICATION": "HEADERINCOTERMSCLASSIFICATION"} - ) - salesdocumentitem = salesdocumentitem.rename( - columns={"INCOTERMSCLASSIFICATION": "ITEMINCOTERMSCLASSIFICATION"} - ) - - # Ensure we only look at sales order items for which we have the header information as well - salesdocumentitem = salesdocumentitem[ - salesdocumentitem.SALESDOCUMENT.isin(salesdocument.SALESDOCUMENT) - ] - - # Use creation date and time to build the timestamp - salesdocument["CREATIONTIMESTAMP"] = pd.to_datetime( - salesdocument.CREATIONDATE.dt.strftime("%Y%m%d") - + salesdocument.CREATIONTIME.astype(str), - format="%Y%m%d%H:%M:%S", - ) - salesdocument = salesdocument.drop(["CREATIONDATE", "CREATIONTIME"], axis=1) - salesdocument = salesdocument[ - (salesdocument.CREATIONTIMESTAMP >= pd.Timestamp("2018-01-01")) - & (salesdocument.CREATIONTIMESTAMP < pd.Timestamp("2021-01-01")) - ] - - # Add date column to item df as well. The other dfs don't have a timestamp - salesdocumentitem = salesdocumentitem.merge( - salesdocument[["SALESDOCUMENT", "CREATIONTIMESTAMP"]], - on="SALESDOCUMENT", - how="left", - ) - salesdocumentitem = salesdocumentitem[ - (salesdocumentitem.CREATIONTIMESTAMP >= pd.Timestamp("2018-01-01")) - & (salesdocumentitem.CREATIONTIMESTAMP < pd.Timestamp("2021-01-01")) - ] - - # Join the sales document and item IDS to for the primary key of the sales document item table - # This is not necessary to be able to join the tables but it will be necessary for the prediction task - salesdocumentitem["ID"] = ( - salesdocumentitem["SALESDOCUMENT"] - + salesdocumentitem["SALESDOCUMENTITEM"] - ) - - # Also convert the columns which will be used as targets to integers, to avoid modeling issues - - for col in self.header_target_cols: - salesdocument[col], _ = pd.factorize(salesdocument[col]) - for col in self.item_target_cols: - salesdocumentitem[col], _ = pd.factorize(salesdocumentitem[col]) - - # Note: there are currently two customers registered with more than one address in the customer table - # For lack of a better solution atm, remove the customers with duplicate entries - customer = customer[(~customer.CUSTOMER.isin(["1025999907", "5508069095"]))] - - # Make sure to remove additional targets from the sales order and sales order item tables to avoid leakers - - # Drop duplicate columns in the customer and address tables - customer = customer.drop_duplicates() - address = address.drop_duplicates() - - # Drop the ADDRESSREPRESENTATIONCODE column as it is always NaN - address = address.drop(columns=["ADDRESSREPRESENTATIONCODE"]) - - # Drop the "__index_level_0__" column artifacts - customer = customer.drop(columns=["__index_level_0__"]) - salesdocument = salesdocument.drop(columns=["__index_level_0__"]) - salesdocumentitem = salesdocumentitem.drop(columns=["__index_level_0__"]) - address = address.drop(columns=["__index_level_0__"]) - except DatasetNotFoundError: - # Fallback to download from relbench server - paths = pooch.retrieve( - "https://relbench.stanford.edu/download/rel-salt/db.zip", - known_hash="fca91ab7d9e37646dcf1cb0007cc4229e9b23ef3c85f3c9e578d0f3fcb167001", - progressbar=True, - processor=pooch.Unzip(), - ) - - path = os.path.dirname(paths[0]) - salesdocumentitem = pd.read_parquet( - os.path.join(path, "salesdocumentitem.parquet") - ) - salesdocument = pd.read_parquet(os.path.join(path, "salesdocument.parquet")) - customer = pd.read_parquet(os.path.join(path, "customer.parquet")) - address = pd.read_parquet(os.path.join(path, "address.parquet")) - - # Collect all tables in the database as relbench.base.Table objects. - tables = {} - tables["salesdocumentitem"] = Table( - df=salesdocumentitem, - fkey_col_to_pkey_table={ - "SALESDOCUMENT": "salesdocument", - "SOLDTOPARTY": "customer", - "SHIPTOPARTY": "customer", - "BILLTOPARTY": "customer", - "PAYERPARTY": "customer", - }, - pkey_col="ID", # + SALESDOCUMENTITEM - time_col="CREATIONTIMESTAMP", - ) - tables["salesdocument"] = Table( - df=salesdocument, - fkey_col_to_pkey_table={}, - pkey_col="SALESDOCUMENT", - time_col="CREATIONTIMESTAMP", - ) - tables["customer"] = Table( - df=customer, - fkey_col_to_pkey_table={"ADDRESSID": "address"}, - pkey_col="CUSTOMER", - time_col=None, - ) - tables["address"] = Table( - df=address, fkey_col_to_pkey_table={}, pkey_col="ADDRESSID", time_col=None - ) - - return Database(tables) diff --git a/plexe/relbench/datasets/stack.py b/plexe/relbench/datasets/stack.py index 04513170..61365481 100644 --- a/plexe/relbench/datasets/stack.py +++ b/plexe/relbench/datasets/stack.py @@ -3,8 +3,8 @@ import pandas as pd import pooch -from relbench.base import Database, Dataset, Table -from relbench.utils import clean_datetime, unzip_processor +from ..base import Database, Dataset, Table +from ..utils import clean_datetime, unzip_processor class StackDataset(Dataset): diff --git a/plexe/relbench/datasets/trial.py b/plexe/relbench/datasets/trial.py index 6415c376..dc6a3d38 100644 --- a/plexe/relbench/datasets/trial.py +++ b/plexe/relbench/datasets/trial.py @@ -4,8 +4,8 @@ import pandas as pd import pooch -from relbench.base import Database, Dataset, Table -from relbench.utils import unzip_processor +from ..base import Database, Dataset, Table +from ..utils import unzip_processor class TrialDataset(Dataset): diff --git a/plexe/relbench/tasks/__init__.py b/plexe/relbench/tasks/__init__.py index 783cd1c5..affbe49f 100644 --- a/plexe/relbench/tasks/__init__.py +++ b/plexe/relbench/tasks/__init__.py @@ -8,14 +8,10 @@ from ..datasets import get_dataset from ..tasks import ( amazon, - arxiv, avito, - dbinfer, event, f1, hm, - mimic, - ratebeer, stack, trial, ) diff --git a/plexe/relbench/tasks/amazon.py b/plexe/relbench/tasks/amazon.py index bf3eb448..6ea91f7f 100644 --- a/plexe/relbench/tasks/amazon.py +++ b/plexe/relbench/tasks/amazon.py @@ -1,8 +1,8 @@ import duckdb import pandas as pd -from relbench.base import Database, EntityTask, RecommendationTask, Table, TaskType -from relbench.metrics import ( +from ..base import Database, EntityTask, RecommendationTask, Table, TaskType +from ..metrics import ( accuracy, average_precision, f1, diff --git a/plexe/relbench/tasks/arxiv.py b/plexe/relbench/tasks/arxiv.py deleted file mode 100644 index c2d21291..00000000 --- a/plexe/relbench/tasks/arxiv.py +++ /dev/null @@ -1,240 +0,0 @@ -import duckdb -import pandas as pd - -from relbench.base import Database, EntityTask, RecommendationTask, Table, TaskType -from relbench.metrics import ( - accuracy, - f1, - link_prediction_map, - link_prediction_precision, - link_prediction_recall, - mae, - multiclass_f1, - r2, - rmse, - roc_auc, -) - - -class PaperCitationTask(EntityTask): - r"""Predict if a paper gets cited in the next 6 months.""" - - task_type = TaskType.BINARY_CLASSIFICATION - entity_col = "Paper_ID" - entity_table = "papers" - time_col = "date" - target_col = "cited" - timedelta = pd.Timedelta(days=365 // 2) # approximately 6 months - metrics = [accuracy, f1, roc_auc] - num_eval_timestamps = 1 - - def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: - timestamp_df = pd.DataFrame({"timestamp": timestamps}) - papers = db.table_dict["papers"].df - citations = db.table_dict["citations"].df - - df = duckdb.sql( - f""" - WITH paper_citations AS ( - SELECT - t.timestamp AS date, - p.Paper_ID, - COUNT(c.References_Paper_ID) AS citation_count - FROM timestamp_df t - JOIN papers p - ON p.Submission_Date <= t.timestamp - LEFT JOIN citations c - ON c.References_Paper_ID = p.Paper_ID - AND c.Submission_Date > t.timestamp - AND c.Submission_Date <= t.timestamp + INTERVAL '{self.timedelta}' - GROUP BY t.timestamp, p.Paper_ID - ) - SELECT - date, - Paper_ID, - CASE WHEN citation_count > 0 THEN 1 ELSE 0 END AS cited - FROM paper_citations; - """ - ).df() - - return Table( - df=df, - fkey_col_to_pkey_table={self.entity_col: self.entity_table}, - pkey_col=None, - time_col=self.time_col, - ) - - -class AuthorCategoryTask(EntityTask): - r"""Predict the primary research category in which an author will publish papers in - the next six months.""" - - task_type = TaskType.MULTICLASS_CLASSIFICATION - entity_col = "Author_ID" - entity_table = "authors" - time_col = "date" - target_col = "primary_category" - timedelta = pd.Timedelta(days=365 // 2) - metrics = [accuracy, multiclass_f1] - num_eval_timestamps = 1 - num_classes = 53 - - def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: - timestamp_df = pd.DataFrame({"timestamp": timestamps}) - - author = db.table_dict["authors"].df - paperAuthors = db.table_dict["paperAuthors"].df - papers = db.table_dict["papers"].df - paperCategories = db.table_dict["paperCategories"].df - categories = db.table_dict["categories"].df - - df = duckdb.sql( - f""" - WITH author_pubs AS ( - SELECT - t.timestamp AS date, - pa.Author_ID, - p.Primary_Category_ID - FROM timestamp_df t - JOIN paperAuthors pa - ON pa.Submission_Date > t.timestamp - AND pa.Submission_Date <= t.timestamp + INTERVAL '{self.timedelta}' - JOIN papers p - ON pa.Paper_ID = p.Paper_ID - ), - pub_counts AS ( - SELECT - date, - Author_ID, - Primary_Category_ID, - COUNT(*) AS cnt - FROM author_pubs - GROUP BY date, Author_ID, Primary_Category_ID - ), - ranked AS ( - SELECT - date, - Author_ID, - Primary_Category_ID, - ROW_NUMBER() OVER (PARTITION BY date, Author_ID ORDER BY cnt DESC) AS rn - FROM pub_counts - ) - SELECT - r.date, - r.Author_ID, - c.Category AS primary_category - FROM ranked r - LEFT JOIN categories c ON r.Primary_Category_ID = c.Category_ID - WHERE r.rn = 1 - ; - """ - ).df() - - return Table( - df=df, - fkey_col_to_pkey_table={self.entity_col: self.entity_table}, - pkey_col=self.entity_col, - time_col=self.time_col, - ) - - -class AuthorPublicationTask(EntityTask): - r"""Predict how many papers an author will publish in the next six months.""" - - task_type = TaskType.REGRESSION - entity_col = "Author_ID" - entity_table = "authors" - time_col = "date" - target_col = "publication_count" - timedelta = pd.Timedelta(days=365 // 2) - metrics = [r2, mae, rmse] - num_eval_timestamps = 1 - - def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: - timestamp_df = pd.DataFrame({"timestamp": timestamps}) - paperAuthors = db.table_dict["paperAuthors"].df - - df = duckdb.sql( - f""" - WITH author_pubs AS ( - SELECT - t.timestamp AS date, - pa.Author_ID, - COUNT(pa.Paper_ID) AS publication_count - FROM timestamp_df t - JOIN paperAuthors pa - ON pa.Submission_Date > t.timestamp - AND pa.Submission_Date <= t.timestamp + INTERVAL '{self.timedelta}' - GROUP BY t.timestamp, pa.Author_ID - ) - SELECT date, Author_ID, publication_count FROM author_pubs; - """ - ).df() - - return Table( - df=df, - fkey_col_to_pkey_table={self.entity_col: self.entity_table}, - pkey_col=None, - time_col=self.time_col, - ) - - -class CoCitationTask(RecommendationTask): - r"""Predict which other papers will be cited together with a given paper in the next - six months.""" - - task_type = TaskType.LINK_PREDICTION - src_entity_col = "Paper_ID" - src_entity_table = "papers" - dst_entity_col = "co_cited" - dst_entity_table = "papers" - time_col = "date" - timedelta = pd.Timedelta(days=365 // 2) - metrics = [link_prediction_map, link_prediction_precision, link_prediction_recall] - num_eval_timestamps = 1 - eval_k = 10 - - def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: - timestamp_df = pd.DataFrame({"timestamp": timestamps}) - papers = db.table_dict["papers"].df - citations = db.table_dict["citations"].df - - df = duckdb.sql( - f""" - WITH paper_co_citations AS ( - SELECT - t.timestamp AS date, - p.Paper_ID, - c2.References_Paper_ID AS co_cited_paper - FROM timestamp_df t - JOIN papers p - ON p.Submission_Date <= t.timestamp - JOIN citations c1 - ON c1.References_Paper_ID = p.Paper_ID - AND c1.Submission_Date > t.timestamp - AND c1.Submission_Date <= t.timestamp + INTERVAL '{self.timedelta}' - JOIN citations c2 - ON c1.Paper_ID = c2.Paper_ID - AND c2.References_Paper_ID <> p.Paper_ID - AND c2.Submission_Date > t.timestamp - AND c2.Submission_Date <= t.timestamp + INTERVAL '{self.timedelta}' - ) - SELECT - date, - Paper_ID, - array_agg(DISTINCT co_cited_paper) AS co_cited - FROM paper_co_citations - GROUP BY date, Paper_ID - ; - """ - ).df() - - return Table( - df=df, - fkey_col_to_pkey_table={ - self.src_entity_col: self.src_entity_table, - self.dst_entity_col: self.dst_entity_table, - }, - pkey_col=None, - time_col=self.time_col, - ) \ No newline at end of file diff --git a/plexe/relbench/tasks/avito.py b/plexe/relbench/tasks/avito.py index 62a51a7f..101b7938 100644 --- a/plexe/relbench/tasks/avito.py +++ b/plexe/relbench/tasks/avito.py @@ -1,8 +1,8 @@ import duckdb import pandas as pd -from relbench.base import Database, EntityTask, RecommendationTask, Table, TaskType -from relbench.metrics import ( +from ..base import Database, EntityTask, RecommendationTask, Table, TaskType +from ..metrics import ( accuracy, average_precision, f1, diff --git a/plexe/relbench/tasks/dbinfer.py b/plexe/relbench/tasks/dbinfer.py deleted file mode 100644 index b769a0f9..00000000 --- a/plexe/relbench/tasks/dbinfer.py +++ /dev/null @@ -1,179 +0,0 @@ -import os -from typing import Dict - -import pandas as pd -import pooch - -from relbench.base import EntityTask, Table - -DEFAULT_DBINFER_ADAPTER_CACHE = os.path.join( - pooch.os_cache("relbench"), "dbinfer-adapters" -) -SYNTHETIC_TIME_COL = "__dbinfer_timestamp__" -SYNTHETIC_TIMESTAMPS: Dict[str, pd.Timestamp] = { - "train": pd.Timestamp("1970-01-01"), - "val": pd.Timestamp("1970-01-02"), - "test": pd.Timestamp("1970-01-03"), -} - - -class DBInferTaskBase(EntityTask): - """RelBench EntityTask backed by a DBInfer task definition.""" - - dbinfer_dataset_name: str | None = None - dbinfer_task_name: str | None = None - - timedelta = pd.Timedelta(days=1) - metrics = [] - num_eval_timestamps = 1 - - def __init__( - self, - dataset, - cache_dir=None, - adapter_cache_dir: str | None = None, - ): - if not self.dbinfer_dataset_name or not self.dbinfer_task_name: - raise ValueError( - "DBInferTaskBase subclasses must define " - "'dbinfer_dataset_name' and 'dbinfer_task_name'." - ) - - if hasattr(dataset, "dbinfer_name"): - if dataset.dbinfer_name != self.dbinfer_dataset_name: - raise ValueError( - "Dataset and task originate from different DBInfer sources: " - f"{dataset.dbinfer_name} vs {self.dbinfer_dataset_name}" - ) - - if adapter_cache_dir is None: - adapter_cache_dir = DEFAULT_DBINFER_ADAPTER_CACHE - self._adapter_cache_dir = adapter_cache_dir - from dbinfer_relbench_adapter.loader import load_dbinfer_data - - dataset_adapter, task_adapter = load_dbinfer_data( - dataset_name=self.dbinfer_dataset_name, - task_name=self.dbinfer_task_name, - use_cache=True, - cache_dir=self._adapter_cache_dir, - ) - - self._dataset_adapter = dataset_adapter - self._task_adapter = task_adapter - - self.task_type = task_adapter.task_type - self.entity_table = task_adapter.entity_table - self.entity_col = task_adapter.entity_col - self.target_col = task_adapter.target_col - self.metrics = task_adapter.metrics - self.num_labels = getattr(task_adapter, "num_labels", None) - self.num_classes = self.num_labels - - metadata_time_col = getattr( - task_adapter.dbinfer_task.metadata, "time_column", None - ) - self.time_col = metadata_time_col or SYNTHETIC_TIME_COL - - super().__init__(dataset, cache_dir=cache_dir) - - def _get_table(self, split): - if split not in SYNTHETIC_TIMESTAMPS: - raise ValueError(f"Unknown split '{split}' for DBInfer task.") - - mock_table = self._task_adapter.get_table(split) - df = mock_table.df.copy() - - time_col = self.time_col - if time_col not in df.columns: - self.time_col = SYNTHETIC_TIME_COL - time_col = self.time_col - df[time_col] = SYNTHETIC_TIMESTAMPS[split] - elif time_col == SYNTHETIC_TIME_COL: - df[time_col] = SYNTHETIC_TIMESTAMPS[split] - else: - df[time_col] = pd.to_datetime(df[time_col], errors="coerce") - - fkeys = {} - if self.entity_col in df.columns and self.entity_table: - fkeys[self.entity_col] = self.entity_table - - return Table( - df=df, - fkey_col_to_pkey_table=fkeys, - pkey_col=None, - time_col=time_col, - ) - - def evaluate(self, pred, table=None): - metrics = self._task_adapter.evaluate(pred, table) - return metrics - - -class AVSRepeaterTask(DBInferTaskBase): - dbinfer_dataset_name = "avs" - dbinfer_task_name = "repeater" - - -class MAGCiteTask(DBInferTaskBase): - dbinfer_dataset_name = "mag" - dbinfer_task_name = "cite" - - -class MAGVenueTask(DBInferTaskBase): - dbinfer_dataset_name = "mag" - dbinfer_task_name = "venue" - - -class DigineticaCTRTask(DBInferTaskBase): - dbinfer_dataset_name = "diginetica" - dbinfer_task_name = "ctr" - - -class DigineticaPurchaseTask(DBInferTaskBase): - dbinfer_dataset_name = "diginetica" - dbinfer_task_name = "purchase" - - -class RetailRocketCVRTask(DBInferTaskBase): - dbinfer_dataset_name = "retailrocket" - dbinfer_task_name = "cvr" - - -class SeznamChargeTask(DBInferTaskBase): - dbinfer_dataset_name = "seznam" - dbinfer_task_name = "charge" - - -class SeznamPrepayTask(DBInferTaskBase): - dbinfer_dataset_name = "seznam" - dbinfer_task_name = "prepay" - - -class AmazonRatingTask(DBInferTaskBase): - dbinfer_dataset_name = "amazon" - dbinfer_task_name = "rating" - - -class AmazonPurchaseTask(DBInferTaskBase): - dbinfer_dataset_name = "amazon" - dbinfer_task_name = "purchase" - - -class AmazonChurnTask(DBInferTaskBase): - dbinfer_dataset_name = "amazon" - dbinfer_task_name = "churn" - - -class StackExchangeChurnTask(DBInferTaskBase): - dbinfer_dataset_name = "stackexchange" - dbinfer_task_name = "churn" - - -class StackExchangeUpvoteTask(DBInferTaskBase): - dbinfer_dataset_name = "stackexchange" - dbinfer_task_name = "upvote" - - -class OutbrainCTRTask(DBInferTaskBase): - dbinfer_dataset_name = "outbrain-small" - dbinfer_task_name = "ctr" \ No newline at end of file diff --git a/plexe/relbench/tasks/event.py b/plexe/relbench/tasks/event.py index 37fab2db..10d42e92 100644 --- a/plexe/relbench/tasks/event.py +++ b/plexe/relbench/tasks/event.py @@ -1,8 +1,8 @@ import duckdb import pandas as pd -from relbench.base import Database, EntityTask, Table, TaskType -from relbench.metrics import accuracy, average_precision, f1, mae, r2, rmse, roc_auc +from ..base import Database, EntityTask, Table, TaskType +from ..metrics import accuracy, average_precision, f1, mae, r2, rmse, roc_auc class UserAttendanceTask(EntityTask): diff --git a/plexe/relbench/tasks/f1.py b/plexe/relbench/tasks/f1.py index 11930b41..c21887bb 100644 --- a/plexe/relbench/tasks/f1.py +++ b/plexe/relbench/tasks/f1.py @@ -1,8 +1,8 @@ import duckdb import pandas as pd -from relbench.base import Database, EntityTask, RecommendationTask, Table, TaskType -from relbench.metrics import ( +from ..base import Database, EntityTask, RecommendationTask, Table, TaskType +from ..metrics import ( accuracy, average_precision, f1, @@ -75,9 +75,9 @@ class DriverDNFTask(EntityTask): entity_table = "drivers" time_col = "date" target_col = "did_not_finish" - timedelta = pd.Timedelta(days=30) + timedelta = pd.Timedelta(days=15) # gr: 30 metrics = [average_precision, accuracy, f1, roc_auc] - num_eval_timestamps = 40 + num_eval_timestamps = 3 # gr: 40 def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: timestamp_df = pd.DataFrame({"timestamp": timestamps}) diff --git a/plexe/relbench/tasks/hm.py b/plexe/relbench/tasks/hm.py index ec02b91a..02194734 100644 --- a/plexe/relbench/tasks/hm.py +++ b/plexe/relbench/tasks/hm.py @@ -1,8 +1,8 @@ import duckdb import pandas as pd -from relbench.base import Database, EntityTask, RecommendationTask, Table, TaskType -from relbench.metrics import ( +from ..base import Database, EntityTask, RecommendationTask, Table, TaskType +from ..metrics import ( accuracy, average_precision, f1, diff --git a/plexe/relbench/tasks/mimic.py b/plexe/relbench/tasks/mimic.py deleted file mode 100644 index 76f62429..00000000 --- a/plexe/relbench/tasks/mimic.py +++ /dev/null @@ -1,73 +0,0 @@ -import duckdb -import pandas as pd - -from relbench.base import TaskType -from relbench.base.database import Database -from relbench.base.table import Table -from relbench.base.task_entity import EntityTask -from relbench.metrics import accuracy, average_precision, f1, roc_auc - - -class ICULengthOfStayTask(EntityTask): - r"""Binary classification: Predict if ICU length of stay is ≥ 3 days during the first ICU stay.""" - - task_type = TaskType.BINARY_CLASSIFICATION - entity_col = "subject_id" - entity_table = "patients" - time_col = "intime" - target_col = "los_icu_binary" - timedelta = pd.Timedelta(days=1) - metrics = [average_precision, accuracy, f1, roc_auc] - - def __init__(self, *args, **kwargs): - """Forward all arguments to the base class.""" - super().__init__(*args, **kwargs) - - self.test_timestamp = self.dataset.test_timestamp - self.val_timestamp = self.dataset.val_timestamp - - if self.test_timestamp is not None and self.val_timestamp is not None: - self.num_eval_timestamps = int( - (self.test_timestamp - self.val_timestamp) / self.timedelta - ) - print(f"num_eval_timestamps: {self.num_eval_timestamps}") - self.num_eval_timestamps = max(1, self.num_eval_timestamps) - print(f"num_eval_timestamps: {self.num_eval_timestamps}") - - def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: - timestamp_df = pd.DataFrame({"timestamp": timestamps}) - icu = db.table_dict["icustays"].df - patients = db.table_dict["patients"].df - - df = duckdb.sql( - f""" - SELECT - t.timestamp as intime, - p.subject_id, - CASE - WHEN i.los_icu >= 3 THEN 1 - ELSE 0 - END as los_icu_binary - FROM - timestamp_df t - LEFT JOIN icu i - - ON i.intime > t.timestamp - AND i.intime <= t.timestamp + INTERVAL '{self.timedelta}' - LEFT JOIN patients p - ON - i.subject_id = p.subject_id - WHERE - i.subject_id IS NOT NULL - AND i.intime IS NOT NULL - AND i.los_icu IS NOT NULL - - """ - ).df() - - return Table( - df=df, - fkey_col_to_pkey_table={self.entity_col: self.entity_table}, - pkey_col=None, - time_col=self.time_col, - ) \ No newline at end of file diff --git a/plexe/relbench/tasks/ratebeer.py b/plexe/relbench/tasks/ratebeer.py deleted file mode 100644 index 26534d15..00000000 --- a/plexe/relbench/tasks/ratebeer.py +++ /dev/null @@ -1,483 +0,0 @@ -import duckdb -import numpy as np -import pandas as pd -from numpy.typing import NDArray -from scipy.stats import rankdata - -from relbench.base import Database, EntityTask, RecommendationTask, Table, TaskType -from relbench.metrics import ( - accuracy, - average_precision, - f1, - link_prediction_map, - link_prediction_precision, - link_prediction_recall, - mae, - r2, - rmse, - roc_auc, -) - - -def link_prediction_mrr( - pred_isin: NDArray[np.int_], # shape (n_src, k) - dst_count: NDArray[np.int_], # shape (n_src,) -) -> float: - # 1) filter out sources without positives - pos_mask = dst_count > 0 - pred_isin = pred_isin[pos_mask] - dst_count = dst_count[pos_mask] - - reciprocal_ranks = [] - for row in pred_isin: - # find the first correct prediction - hits = np.where(row == 1)[0] - if len(hits): - first_hit_rank = hits[0] + 1 # ranks are 1‑based - reciprocal_ranks.append(1.0 / first_hit_rank) - else: - reciprocal_ranks.append(0.0) - - return float(np.mean(reciprocal_ranks)) - - -# Entity Classification tasks - - -class BeerRatingChurnTask(EntityTask): - r"""Predict whether a beer will receive a rating in the next 90 days.""" - - task_type = TaskType.BINARY_CLASSIFICATION - entity_col = "beer_id" - entity_table = "beers" - time_col = "timestamp" - target_col = "rating_churn" - timedelta = pd.Timedelta(days=90) - metrics = [accuracy, average_precision, f1, roc_auc] - - def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: - beers = db.table_dict["beers"].df - beer_ratings = db.table_dict["beer_ratings"].df - timestamp_df = pd.DataFrame({"timestamp": timestamps}) - - df = duckdb.sql( - f""" - SELECT - t.timestamp, - b.beer_id AS beer_id, - CAST( - NOT EXISTS ( - SELECT 1 - FROM beer_ratings - WHERE - beer_ratings.beer_id = b.beer_id - AND beer_ratings.created_at > t.timestamp - AND beer_ratings.created_at <= t.timestamp + INTERVAL '{self.timedelta}' - ) AS INTEGER - ) AS rating_churn - FROM - timestamp_df t, - beers b - WHERE - EXISTS ( - SELECT 1 - FROM beer_ratings AS br2 - WHERE - br2.beer_id = b.beer_id - AND br2.created_at > t.timestamp - INTERVAL '{self.timedelta}' - AND br2.created_at <= t.timestamp - ) - GROUP BY - t.timestamp, - b.beer_id - """ - ).df() - - return Table( - df=df, - fkey_col_to_pkey_table={self.entity_col: self.entity_table}, - pkey_col=None, - time_col=self.time_col, - ) - - -class UserRatingChurnTask(EntityTask): - r"""Predict whether a user will give a beer rating in the next 90 days.""" - - task_type = TaskType.BINARY_CLASSIFICATION - entity_col = "user_id" - entity_table = "users" - time_col = "timestamp" - target_col = "user_churn" - timedelta = pd.Timedelta(days=90) - metrics = [accuracy, average_precision, f1, roc_auc] - - def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: - users = db.table_dict["users"].df - beer_ratings = db.table_dict["beer_ratings"].df - timestamp_df = pd.DataFrame({"timestamp": timestamps}) - - df = duckdb.sql( - f""" - SELECT - t.timestamp, - u.user_id AS user_id, - CAST( - NOT EXISTS ( - SELECT 1 - FROM beer_ratings - WHERE - beer_ratings.user_id = u.user_id - AND beer_ratings.created_at > t.timestamp - AND beer_ratings.created_at <= t.timestamp + INTERVAL '{self.timedelta}' - ) AS INTEGER - ) AS user_churn - FROM - timestamp_df t, - users u - WHERE - EXISTS ( - SELECT 1 - FROM beer_ratings AS br2 - WHERE - br2.user_id = u.user_id - AND br2.created_at > t.timestamp - INTERVAL '{self.timedelta}' - AND br2.created_at <= t.timestamp - ) - GROUP BY - t.timestamp, - u.user_id - """ - ).df() - - return Table( - df=df, - fkey_col_to_pkey_table={self.entity_col: self.entity_table}, - pkey_col=None, - time_col=self.time_col, - ) - - -class BrewerDormantTask(EntityTask): - r"""Predict whether a brewer will release zero beers in the next 365 days.""" - - task_type = TaskType.BINARY_CLASSIFICATION - entity_col = "brewer_id" - entity_table = "brewers" - time_col = "timestamp" - target_col = "dormant" - timedelta = pd.Timedelta(days=365) - metrics = [accuracy, average_precision, f1, roc_auc] - - def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: - brewers = db.table_dict["brewers"].df - beers = db.table_dict["beers"].df - timestamp_df = pd.DataFrame({"timestamp": timestamps}) - - df = duckdb.sql( - f""" - SELECT - t.timestamp, - brew.brewer_id AS brewer_id, - CAST( - NOT EXISTS ( - SELECT 1 - FROM beers - WHERE - beers.brewer_id = brew.brewer_id - AND beers.created_at > t.timestamp - AND beers.created_at <= t.timestamp + INTERVAL '{self.timedelta}' - ) AS INTEGER - ) AS dormant - FROM - timestamp_df t, - brewers brew - WHERE - EXISTS ( - SELECT 1 - FROM beers AS b2 - WHERE - b2.brewer_id = brew.brewer_id - AND b2.created_at > t.timestamp - INTERVAL '{self.timedelta}' - AND b2.created_at <= t.timestamp - ) - GROUP BY - t.timestamp, - brew.brewer_id - """ - ).df() - - return Table( - df=df, - fkey_col_to_pkey_table={self.entity_col: self.entity_table}, - pkey_col=None, - time_col=self.time_col, - ) - - -# Entity Regression tasks - - -class UserRatingCountTask(EntityTask): - r"""Predict the number of beer ratings that a user will give in the next 90 days.""" - - task_type = TaskType.REGRESSION - entity_col = "user_id" - entity_table = "users" - time_col = "timestamp" - target_col = "num_ratings" - timedelta = pd.Timedelta(days=90) - metrics = [r2, mae, rmse] - - def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: - users = db.table_dict["users"].df - beer_ratings = db.table_dict["beer_ratings"].df - timestamp_df = pd.DataFrame({"timestamp": timestamps}) - - df = duckdb.sql( - f""" - SELECT - t.timestamp, - u.user_id, - ( - SELECT COUNT(*) - FROM beer_ratings br - WHERE br.user_id = u.user_id - AND br.created_at > t.timestamp - AND br.created_at <= t.timestamp + INTERVAL '{self.timedelta}' - ) AS num_ratings - FROM timestamp_df t - CROSS JOIN users u - WHERE - EXISTS ( - SELECT 1 - FROM beer_ratings AS br2 - WHERE br2.user_id = u.user_id - AND br2.created_at > t.timestamp - INTERVAL '{self.timedelta}' - AND br2.created_at <= t.timestamp - ) - """ - ).df() - - return Table( - df=df, - fkey_col_to_pkey_table={self.entity_col: self.entity_table}, - pkey_col=None, - time_col=self.time_col, - ) - - -# Recommendation tasks - - -class UserFavoriteBeerTask(RecommendationTask): - r"""Predict the list of distinct beers each active user will add to their favorites - in the next 90 days.""" - - task_type = TaskType.LINK_PREDICTION - src_entity_col = "user_id" - src_entity_table = "users" - dst_entity_col = "beer_id" - dst_entity_table = "beers" - time_col = "timestamp" - timedelta = pd.Timedelta(days=90) - metrics = [ - link_prediction_precision, - link_prediction_recall, - link_prediction_map, - link_prediction_mrr, - ] - eval_k = 10 - - def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: - users = db.table_dict["users"].df - beers = db.table_dict["beers"].df - favorites = db.table_dict["favorites"].df - beer_ratings = db.table_dict["beer_ratings"].df - timestamp_df = pd.DataFrame({"timestamp": timestamps}) - - df = duckdb.sql( - f""" - SELECT - t.timestamp, - f.user_id, - LIST(DISTINCT f.beer_id) AS beer_id - FROM - timestamp_df t - LEFT JOIN - favorites as f - ON - f.created_at > t.timestamp AND - f.created_at <= t.timestamp + INTERVAL '{self.timedelta} days' - WHERE - f.user_id is not null and f.beer_id is not null - AND EXISTS ( - SELECT 1 - FROM beer_ratings as br - WHERE br.user_id = f.user_id - AND br.created_at > t.timestamp - INTERVAL '{self.timedelta} days' - AND br.created_at <= t.timestamp - ) - GROUP BY - t.timestamp, - f.user_id - """ - ).df() - - return Table( - df=df, - fkey_col_to_pkey_table={ - self.src_entity_col: self.src_entity_table, - self.dst_entity_col: self.dst_entity_table, - }, - pkey_col=None, - time_col=self.time_col, - ) - - -class UserLikedPlaceTask(RecommendationTask): - r"""Predict the list of distinct places each active user rates at least 80.0 / 100.0 - in the next 90 days.""" - - task_type = TaskType.LINK_PREDICTION - src_entity_col = "user_id" - src_entity_table = "users" - dst_entity_col = "place_id" - dst_entity_table = "places" - time_col = "timestamp" - timedelta = pd.Timedelta(days=90) - metrics = [ - link_prediction_precision, - link_prediction_recall, - link_prediction_map, - link_prediction_mrr, - ] - eval_k = 10 - - def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: - users = db.table_dict["users"].df - places = db.table_dict["places"].df - place_ratings = db.table_dict["place_ratings"].df - beer_ratings = db.table_dict["beer_ratings"].df - timestamp_df = pd.DataFrame({"timestamp": timestamps}) - - df = duckdb.sql( - f""" - SELECT - t.timestamp, - pr.user_id, - LIST(DISTINCT pr.place_id) AS place_id - FROM - timestamp_df t - LEFT JOIN - place_ratings as pr - ON pr.created_at > t.timestamp - AND pr.created_at <= t.timestamp + INTERVAL '{self.timedelta} days' - WHERE - pr.user_id IS NOT NULL and pr.place_id IS NOT NULL - AND pr.total_score >= 80 - AND EXISTS ( - SELECT 1 - FROM place_ratings as pr2 - WHERE pr2.user_id = pr.user_id - AND pr2.created_at > t.timestamp - INTERVAL '{self.timedelta} days' - AND pr2.created_at <= t.timestamp - ) - OR EXISTS ( - SELECT 1 - FROM beer_ratings as br - WHERE br.user_id = pr.user_id - AND br.created_at > t.timestamp - INTERVAL '{self.timedelta} days' - AND br.created_at <= t.timestamp - ) - GROUP BY - t.timestamp, - pr.user_id - """ - ).df() - - return Table( - df=df, - fkey_col_to_pkey_table={ - self.src_entity_col: self.src_entity_table, - self.dst_entity_col: self.dst_entity_table, - }, - pkey_col=None, - time_col=self.time_col, - ) - - -class UserLikedBeerTask(RecommendationTask): - r"""Predict the list of distinct beers each active user rates at least 4.0 / 5.0 in - the next 90 days.""" - - task_type = TaskType.LINK_PREDICTION - src_entity_col = "user_id" - src_entity_table = "users" - dst_entity_col = "beer_id" - dst_entity_table = "beers" - time_col = "timestamp" - timedelta = pd.Timedelta(days=90) - metrics = [ - link_prediction_precision, - link_prediction_recall, - link_prediction_map, - link_prediction_mrr, - ] - eval_k = 10 - - def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: - users = db.table_dict["users"].df - beers = db.table_dict["beers"].df - beer_ratings = db.table_dict["beer_ratings"].df - timestamp_df = pd.DataFrame({"timestamp": timestamps}) - - df = duckdb.sql( - f""" - SELECT - t.timestamp, - br.user_id, - LIST(DISTINCT br.beer_id) AS beer_id - FROM - timestamp_df t - LEFT JOIN - beer_ratings as br - ON br.created_at > t.timestamp - AND br.created_at <= t.timestamp + INTERVAL '{self.timedelta} days' - WHERE - br.user_id IS NOT NULL and br.beer_id IS NOT NULL - AND br.total_score >= 4.0 - AND EXISTS ( - SELECT 1 - FROM beer_ratings as br2 - WHERE br2.user_id = br.user_id - AND br2.created_at > t.timestamp - INTERVAL '{self.timedelta} days' - AND br2.created_at <= t.timestamp - ) - GROUP BY - t.timestamp, - br.user_id - """ - ).df() - - return Table( - df=df, - fkey_col_to_pkey_table={ - self.src_entity_col: self.src_entity_table, - self.dst_entity_col: self.dst_entity_table, - }, - pkey_col=None, - time_col=self.time_col, - ) - - -# Mapping of task names to their corresponding task classes. -tasks_dict = { - "beer-rating-churn": BeerRatingChurnTask, - "user-rating-churn": UserRatingChurnTask, - "brewer-dormant": BrewerDormantTask, - "user-rating-count": UserRatingCountTask, - "user-favorite-beer": UserFavoriteBeerTask, - "user-liked-place": UserLikedPlaceTask, - "user-liked-beer": UserLikedBeerTask, -} \ No newline at end of file diff --git a/plexe/relbench/tasks/stack.py b/plexe/relbench/tasks/stack.py index d428617e..275345d2 100644 --- a/plexe/relbench/tasks/stack.py +++ b/plexe/relbench/tasks/stack.py @@ -1,8 +1,8 @@ import duckdb import pandas as pd -from relbench.base import Database, EntityTask, RecommendationTask, Table, TaskType -from relbench.metrics import ( +from ..base import Database, EntityTask, RecommendationTask, Table, TaskType +from ..metrics import ( accuracy, average_precision, f1, diff --git a/plexe/relbench/tasks/trial.py b/plexe/relbench/tasks/trial.py index 00e5094e..33ed9fa7 100644 --- a/plexe/relbench/tasks/trial.py +++ b/plexe/relbench/tasks/trial.py @@ -1,8 +1,8 @@ import duckdb import pandas as pd -from relbench.base import Database, EntityTask, RecommendationTask, Table, TaskType -from relbench.metrics import ( +from ..base import Database, EntityTask, RecommendationTask, Table, TaskType +from ..metrics import ( accuracy, average_precision, f1, diff --git a/plexe/server.py b/plexe/server.py index 9c17237c..3bfaafad 100644 --- a/plexe/server.py +++ b/plexe/server.py @@ -137,15 +137,25 @@ async def run_agent_task(user_message: str): ctx = contextvars.copy_context() func = functools.partial(ctx.run, agent.agent.run, user_message, reset=False) response = await loop.run_in_executor(None, func) - await websocket.send_json({"role": "assistant", "content": response, "id": str(uuid.uuid4())}) + if not ws_emitter.is_closed: + await websocket.send_json({"role": "assistant", "content": response, "id": str(uuid.uuid4())}) + except RuntimeError as e: + if "stopped by user" in str(e).lower(): + logger.info("Agent execution stopped by user") + else: + raise + except asyncio.CancelledError: + logger.info("Agent task cancelled") + raise except Exception as e: logger.error(f"Agent error: {e}") - await websocket.send_json({ - "role": "assistant", - "content": f"I encountered an error: {str(e)}. Please try again.", - "id": str(uuid.uuid4()), - "error": True, - }) + if not ws_emitter.is_closed: + await websocket.send_json({ + "role": "assistant", + "content": f"I encountered an error: {str(e)}. Please try again.", + "id": str(uuid.uuid4()), + "error": True, + }) finally: reset_chain_of_thought_callable(token) agent_task = None @@ -163,6 +173,19 @@ async def run_agent_task(user_message: str): await websocket.send_json({"type": "pong"}) continue + # Handle stop command + if message_data.get("type") == "stop": + logger.info("Stop command received") + ws_emitter.close() + if agent_task: + agent_task.cancel() + try: + await agent_task + except asyncio.CancelledError: + pass + agent_task = None + continue + # Handle confirmation response if message_data.get("type") == "confirmation_response": request_id = message_data.get("id") diff --git a/plexe/templates/prompts/agent/dataset_builder_prompt_templates.yaml b/plexe/templates/prompts/agent/dataset_builder_prompt_templates.yaml index aab17910..0792ed99 100644 --- a/plexe/templates/prompts/agent/dataset_builder_prompt_templates.yaml +++ b/plexe/templates/prompts/agent/dataset_builder_prompt_templates.yaml @@ -1,14 +1,13 @@ managed_agent: task: |- - You are '{{name}}', an expert data engineer specializing in building RelBench Database objects from raw CSV data. - Your manager has assigned you this task: + You are '{{name}}', an expert data engineer specializing in building RelBench Database objects from raw CSV data. Your manager has assigned you this task: --- Task: {{task}} --- - Your primary goal is to generate a complete Python Dataset class that follows the RelBench pattern. + Your primary goal is to generate a complete Python Dataset class. This class will be used to construct a heterogeneous graph for Graph Neural Network training. ## Available Tools: @@ -19,7 +18,23 @@ managed_agent: - `get_latest_datasets`: Get information about available datasets - `validate_database_code`: Validate your generated code - `register_database_code`: Store the generated code in registry - - `export_database_code`: Export the code to a Python file + - `export_database_code`: Export the code to workdir/chat-session-*/ + + ## WORKFLOW: + + 1. Use `get_csv_files_from_path` to discover available CSV files + 2. Use `get_schema_metadata_from_registry` to understand PK/FK relationships + 3. Use `get_temporal_statistics` to analyze timestamps and get suggested val/test splits + 4. Use `get_dataset_reports` to get EDA insights for data cleaning decisions + 5. Analyze the data to determine: + - Which columns to drop (nulls, URLs, leakage) + - How to process time columns + - Which tables need time propagation + - Use suggested val_timestamp and test_timestamp from step 3 + 6. Generate the complete Dataset class code + 7. Use `validate_database_code` to check your code + 8. Use `register_database_code` to store the code + 9. Use `export_database_code` to save it to a Python file ## CRITICAL CONCEPTS @@ -71,10 +86,10 @@ managed_agent: # 2. DATA CLEANING # Based on EDA report insights - # Drop irrelevant columns (URLs, unique IDs that leak info, etc.) + # 2.1 Drop irrelevant columns (URLs, unique IDs that leak info, etc.) # {table}.drop(columns=["url", "profile_image_url"], inplace=True) - # Drop columns with too many missing values (>50%) + # 2.2 Drop columns with too many missing values (>50%) # {table}.drop(columns=["optional_field_with_many_nulls"], inplace=True) @@ -208,22 +223,6 @@ managed_agent: ... ``` - ## WORKFLOW: - - 1. Use `get_csv_files_from_path` to discover available CSV files - 2. Use `get_schema_metadata_from_registry` to understand PK/FK relationships - 3. Use `get_temporal_statistics` to analyze timestamps and get suggested val/test splits - 4. Use `get_dataset_reports` to get EDA insights for data cleaning decisions - 5. Analyze the data to determine: - - Which columns to drop (nulls, URLs, leakage) - - How to process time columns - - Which tables need time propagation - - Use suggested val_timestamp and test_timestamp from step 3 - 6. Generate the complete Dataset class code - 7. Use `validate_database_code` to check your code - 8. Use `register_database_code` to store the code - 9. Use `export_database_code` to save it to a Python file - ## KEY REMINDERS: - **time_col is CREATION TIME only** - not any timestamp column diff --git a/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml b/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml index 3bf56d8f..50ee3863 100644 --- a/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml +++ b/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml @@ -33,7 +33,7 @@ managed_agent: ### Step 2: Retrieve Dataset and Task Information Only after validation passes, use `get_dataset_task_info_from_registry` to get class names: - + Example: ```python info = get_dataset_task_info_from_registry() # Returns: diff --git a/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml b/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml index edaea7e5..dd23fb6a 100644 --- a/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml +++ b/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml @@ -1,15 +1,24 @@ managed_agent: task: |- - You are '{{name}}', an expert ML engineer specializing in defining prediction tasks for relational databases. - Your manager has assigned you this task: + You are '{{name}}', an expert ML engineer specializing in defining and generate a complete Python prediction Task class for relational databases. Your manager has assigned you this task: --- Task: {{task}} --- - - Your primary goal is to generate a complete Python Task class that follows the RelBench pattern. - This class defines the prediction task - the "question" that the ML model will answer. + + ## Your Goal + Create a Python class that defines a prediction Task for relational databases. Especially in generating PERFECTLY CORRECT SQL queries. + + ## WORKFLOW + 1. **Understand the problem**: What are we predicting? For which entity? + 2. **Explore schema**: Use `get_database_schema_for_task` to understand tables, PKs, FKs, time columns + 3. **Sample data**: Use `get_table_sample_data` to see actual column values + 4. **Design SQL**: Combine SQL building blocks (see below) or use `get_sql_query_examples` to find appropriate pattern template + 5. **Test SQL**: Use `test_sql_query` to validate on sample data + 6. **Generate code**: Create complete Task class. Using `get_available_metrics` to select exactly the metrics. + 7. **Register code**: Use `register_task_code` to save to registry + 8. **Validate & Export**: Use `validate_task_code` and `export_task_code` ## Available Tools - `get_database_schema_for_task`: Get table schemas, PKs, FKs, and temporal columns @@ -20,69 +29,19 @@ managed_agent: - `get_sql_query_examples`: Get diverse SQL query PATTERNS (templates, not hardcoded) - `test_sql_query`: TEST your SQL query on sample data before committing - `validate_task_code`: Validate your generated code - - `save_task_to_file`: **PREFERRED** - Saves code to file AND registers in ObjectRegistry AND creates metadata file - - `register_task_code`: Store the generated code in registry (legacy) - - `export_task_code`: Export from registry to file (legacy, requires register first) - - ## WORKFLOW FOR NEW TASKS - - 1. **Understand the problem**: What are we predicting? For which entity? - 2. **Explore schema**: Use `get_database_schema_for_task` to find relevant tables - 3. **Sample data**: Use `get_table_sample_data` to understand column values - 4. **Design SQL**: Combine SQL building blocks (see below) - 5. **Test SQL**: Use `test_sql_query` to validate on sample data - 6. **Generate code**: Create complete Task class named `GenTask` - 7. **SAVE TO FILE**: Use `save_task_to_file(code)` - this saves file, metadata, AND registers in ObjectRegistry - - ## CRITICAL: HOW TO EXPORT CODE - - **PREFERRED METHOD (use this!):** - ```python - result = save_task_to_file(code=task_class_code_string) - ``` - This tool does everything in one step: - - Writes the code to a .py file - - Creates task_metadata.json for persistence - - Registers in ObjectRegistry for immediate use by other agents - - Returns file paths and success status - - **Legacy method (avoid if possible):** - ```python - register_task_code(dataset_name, task_name, code, task_type, entity_table) - export_task_code(dataset_name, task_name) - ``` - This 2-step process is more error-prone. - - ## CRITICAL: NO HARDCODING - - **NEVER hardcode table names, column names, or values in SQL queries.** - Always use the actual names from `get_database_schema_for_task()`. - - The SQL patterns provided are TEMPLATES - you must replace placeholders with - actual values from the schema. + - `register_task_code`: Store the generated code in registry + - `export_task_code`: Export the code to workdir/chat-session-*/ - ## CRITICAL: COLUMN NAMING CONVENTION - - **ALWAYS use snake_case for column names in your SQL queries.** - Even if the original database documentation or schema description uses PascalCase (e.g., UserId, CreationDate), - the actual CSV files and DuckDB tables in this environment use snake_case (e.g., user_id, creation_date). - - Examples: - - UserId -> user_id - - OwnerUserId -> owner_user_id - - CreationDate -> creation_date - - PostId -> post_id - - Check `get_database_schema_for_task` output carefully - it will show the correct snake_case names. - - ## TASK TYPES + ## IMPORTANT + When writing code: + - The file task.py must be located exactly at: workdir/chat-session-*/task.py NOT workdir/chat-session-*/tasks/task.py + - Never hardcode table/column names or values + - Always get actual names from `get_database_schema_for_task()` + - SQL patterns are TEMPLATES only - replace all placeholders with schema values + - Always use `snake_case` for columns (e.g., `user_id`, `creation_date`) + - Schema docs may show PascalCase (e.g., `UserId`, `CreationDate`) but actual CSV/DuckDB tables use `snake_case` + - Convert Examples: `UserId` to `user_id`, `OwnerUserId` to `owner_user_id` - | Task Type | Use Case | Key Pattern | - |-----------|----------|-------------| - | BINARY_CLASSIFICATION | Churn, DNF, Will-Purchase | COUNT → CASE WHEN or EXISTS | - | MULTICLASS_CLASSIFICATION | Primary Category, Type | ROW_NUMBER() ranking | - | REGRESSION | Count, Sum, LTV, Average | COUNT(), SUM(), MEAN() aggregation | - | LINK_PREDICTION | Recommendations, Co-citation | LIST/array_agg aggregation | ## SQL BUILDING BLOCKS (for NEW problems) @@ -419,7 +378,8 @@ managed_agent: from plexe.relbench.base import Database, Table, EntityTask, TaskType from plexe.relbench.metrics import {metrics} - class {TaskName}Task(EntityTask): + # ALWAYS use this class name + class GenTask(EntityTask): r\"\"\"{docstring}\"\"\" task_type = TaskType.{TASK_TYPE} @@ -453,7 +413,8 @@ managed_agent: ### RecommendationTask ```python - class {TaskName}Task(RecommendationTask): + # ALWAYS use this class name + class GenTask(RecommendationTask): task_type = TaskType.LINK_PREDICTION src_entity_col = "{src_col}" src_entity_table = "{src_table}" @@ -478,7 +439,6 @@ managed_agent: time_col=self.time_col, ) ``` - ## METRICS REFERENCE | Task Type | Metrics | @@ -487,20 +447,6 @@ managed_agent: | MULTICLASS_CLASSIFICATION | accuracy, multiclass_f1 | | REGRESSION | r2, mae, rmse | | LINK_PREDICTION | link_prediction_precision, link_prediction_recall, link_prediction_map | - - ## WORKFLOW - - 1. `get_database_schema_for_task()` → understand tables, PKs, FKs, time columns - 2. `get_table_sample_data(table_name)` → see actual column values - 3. `get_sql_query_examples()` → find appropriate pattern template - 4. Write Task class using ACTUAL names from schema - 5. `validate_task_code(code)` → check for errors - 6. `save_task_to_file(code)` → **PREFERRED**: directly write to file - - Alternative (legacy, avoid): - - `register_task_code(dataset_name, task_name, code, ...)` → save to registry - - `export_task_code(dataset_name, task_name)` → write from registry to file - ## COMMON MISTAKES TO AVOID 1. **Hardcoding names**: Always use schema-derived names @@ -508,34 +454,4 @@ managed_agent: 3. **Missing NULL filters**: Add `WHERE col IS NOT NULL` for recommendations 4. **Missing GROUP BY**: Required with aggregation functions 5. **Temporal leakage**: Entity filter must use data UP TO timestamp - 6. **Wrong fkey mapping**: RecommendationTask needs BOTH src and dst mappings - -system_prompt: |- - You are an expert ML engineer specializing in temporal prediction tasks for relational databases. - - Your expertise includes: - - Understanding relational database schemas and entity relationships - - Defining diverse prediction tasks (binary, multiclass, regression, recommendation) - - Writing efficient SQL queries using DuckDB with CTEs and advanced patterns - - Preventing temporal data leakage in ML pipelines - - Building tasks compatible with Graph Neural Networks - - CRITICAL PRINCIPLES: - - 1. NEVER HARDCODE: Use actual table/column names from schema discovery - 2. SQL PATTERNS: Adapt templates to specific schema, don't copy-paste - 3. TEMPORAL CORRECTNESS: Labels from future, features from past - 4. CTE CLARITY: Use WITH clauses for complex multi-step queries - 5. NULL SAFETY: Always handle NULL values appropriately - - SQL Pattern Selection: - - Churn (no activity) → NOT EXISTS or COUNT = 0 - - Citation (has activity) → CTE + COUNT + CASE WHEN - - Primary category → ROW_NUMBER() ranking - - Count prediction → COUNT() with GROUP BY - - Sum/LTV → SUM() with COALESCE - - Recommendations → LIST/array_agg - - Co-occurrence → Self-join pattern - - You communicate concisely and generate correct, executable code. - Always export generated code to workdir/chat-session-*/tasks/ for debugging. + 6. **Wrong fkey mapping**: RecommendationTask needs BOTH src and dst mappings \ No newline at end of file diff --git a/plexe/tools/database_builder.py b/plexe/tools/database_builder.py index 8bc8e2bf..80becc90 100644 --- a/plexe/tools/database_builder.py +++ b/plexe/tools/database_builder.py @@ -42,7 +42,7 @@ from plexe.relbench.base import Database, Dataset, Table -class {class_name}(Dataset): +class GenDataset(Dataset): """ Dataset for {dataset_name}. @@ -348,7 +348,7 @@ def register_database_code( } object_registry.register(dict, metadata_key, metadata, overwrite=True) - logger.info(f"✅ Registered database code for '{dataset_name}' (Class: {class_name})") + logger.info(f"✅ Registered database code for '{dataset_name}'") return { "success": True, diff --git a/plexe/tools/task_builder.py b/plexe/tools/task_builder.py index 06042932..438ccb72 100644 --- a/plexe/tools/task_builder.py +++ b/plexe/tools/task_builder.py @@ -45,7 +45,7 @@ from plexe.relbench.metrics import {metrics_imports} -class {class_name}(EntityTask): +class GenTask(EntityTask): r"""{task_description}""" @@ -123,7 +123,7 @@ def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Tab from plexe.relbench.metrics import {metrics_imports} -class {class_name}(RecommendationTask): +class GenTask(RecommendationTask): r"""{task_description}""" @@ -317,37 +317,31 @@ def get_available_metrics() -> Dict[str, Any]: """ return { "binary_classification": { - "metrics": ["accuracy", "f1", "roc_auc", "average_precision", "auprc"], - "primary_metric": "roc_auc", + "metrics": ["accuracy", "f1", "roc_auc", "average_precision", "auprc", "log_loss", "multiclass_f1"], "description": "Metrics for binary (0/1) classification tasks" }, "multiclass_classification": { "metrics": ["accuracy", "macro_f1", "micro_f1", "mrr", "log_loss"], - "primary_metric": "macro_f1", "description": "Metrics for multi-class classification tasks" }, "regression": { "metrics": ["mae", "mse", "rmse", "r2"], - "primary_metric": "mae", "description": "Metrics for continuous value prediction tasks" }, "multilabel_classification": { - "metrics": ["multilabel_auprc_micro"], - "primary_metric": "multilabel_auprc_micro", + "metrics": ["multilabel_auprc_micro", "multilabel_auprc_macro", "multilabel_auroc_micro", "multilabel_auroc_macro", "multilabel_f1_micro", "multilabel_f1_macro", "multilabel_recall_micro", "multilabel_recall_macro", "multilabel_precision_micro", "multilabel_precision_macro"], "description": "Metrics for multi-label classification tasks" }, "recommendation": { - "metrics": ["recall_at_k", "ndcg_at_k", "mrr_at_k", "map_at_k"], - "primary_metric": "recall_at_k", - "description": "Metrics for recommendation/link prediction tasks", - "note": "Import from plexe.relbench.metrics" + "metrics": ["link_prediction_recall", "link_prediction_precision", "link_prediction_map", "link_prediction_ndcg"], + "description": "Metrics for link prediction tasks", }, "task_types": { "BINARY_CLASSIFICATION": "Binary 0/1 classification", "MULTICLASS_CLASSIFICATION": "Multi-class classification", "REGRESSION": "Continuous value regression", "MULTILABEL_CLASSIFICATION": "Multi-label classification", - "LINK_PREDICTION": "Link/recommendation prediction" + "LINK_PREDICTION": "Link prediction/recommendation" } } @@ -751,137 +745,6 @@ def validate_task_code(code: str) -> Dict[str, Any]: } -@tool -def save_task_to_file(code: str, file_name: str = "task.py") -> Dict[str, Any]: - """ - PREFERRED METHOD: Directly save Task class code to a Python file. - - This is the simplest way to export task code - just provide the code and it - will be saved to the working directory (e.g., .workdir/chat-session-YYYYMMDD-HHMMSS/). - - Use this tool INSTEAD of the register_task_code + export_task_code workflow - for simpler, more reliable task export. - - This tool also: - - Saves task_metadata.json alongside the code file for persistence - - Registers the task code in ObjectRegistry for immediate use by other agents - - Args: - code: The complete Python code for the Task class (must include imports, - class definition, and make_table method) - file_name: Name of the output file (default: "task.py") - - Returns: - Dictionary with: - - success: Boolean indicating if file was saved - - file_path: Absolute path to the saved file - - class_name: Name of the Task class extracted from code - - metadata_file: Path to the metadata JSON file - - error: Error message if failed - """ - from datetime import datetime - import re - import json - - try: - object_registry = ObjectRegistry() - - # Validate code first - validation = validate_task_code.__wrapped__(code) - if not validation["valid"]: - return { - "success": False, - "error": f"Code validation failed: {validation['errors']}", - "warnings": validation.get("warnings", []) - } - - # Get or create working directory - try: - output_dir = object_registry.get(str, "working_dir") - logger.info(f"Using registered working_dir: {output_dir}") - except KeyError: - try: - output_dir = object_registry.get(str, "current_chat_session_dir") - logger.info(f"Using current_chat_session_dir: {output_dir}") - except KeyError: - # Create new session directory - timestamp = datetime.now().strftime("%Y%m%d-%H%M%S") - output_dir = f".workdir/chat-session-{timestamp}" - object_registry.register(str, "current_chat_session_dir", output_dir, overwrite=True) - logger.info(f"Created new session directory: {output_dir}") - - # Normalize and create output directory - output_dir = os.path.abspath(output_dir) - Path(output_dir).mkdir(parents=True, exist_ok=True) - - # Ensure file_name ends with .py - if not file_name.endswith(".py"): - file_name = f"{file_name}.py" - - # Write the code file - file_path = os.path.join(output_dir, file_name) - - with open(file_path, 'w') as f: - f.write(code) - logger.info(f"Wrote task code to '{file_path}'") - - # Extract class name from code - class_match = re.search(r"class\s+(\w+)\s*\(", code) - class_name = class_match.group(1) if class_match else "UnknownTask" - - # Extract additional metadata from code for better registry info - task_type_match = re.search(r"task_type\s*=\s*TaskType\.(\w+)", code) - task_type = task_type_match.group(1) if task_type_match else None - - entity_table_match = re.search(r"entity_table\s*=\s*[\"'](\w+)[\"']", code) - entity_table = entity_table_match.group(1) if entity_table_match else None - - target_col_match = re.search(r"target_col\s*=\s*[\"'](\w+)[\"']", code) - target_col = target_col_match.group(1) if target_col_match else None - - # Prepare metadata (include the code itself for full recovery) - export_info = { - "class_name": class_name, - "export_path": file_path, - "module_name": file_name.replace(".py", ""), - "task_type": task_type, - "entity_table": entity_table, - "target_col": target_col, - "code": code, # Include code for full recovery - } - - # Save metadata to JSON file for persistence across sessions/processes - # This is CRITICAL for cross-agent communication - metadata_file = os.path.join(output_dir, "task_metadata.json") - with open(metadata_file, 'w') as mf: - json.dump(export_info, mf, indent=2) - logger.info(f"✅ Saved task metadata to '{metadata_file}'") - - # Verify the metadata file was created - if not os.path.exists(metadata_file): - raise IOError(f"Metadata file was not created: {metadata_file}") - - # Register task info in memory registry (for same-process access) - object_registry.register(dict, "task_code", export_info, overwrite=True) - logger.info(f"✅ Registered task_code in ObjectRegistry (class: {class_name})") - - logger.info(f"✅ Successfully saved task code to '{file_path}' (class: {class_name})") - - return { - "success": True, - "file_path": file_path, - "metadata_file": metadata_file, - "class_name": class_name, - "output_dir": output_dir, - "message": f"Successfully saved {class_name} to '{file_path}' with metadata at '{metadata_file}'" - } - - except Exception as e: - import traceback - logger.error(f"Failed to save task code: {e}\n{traceback.format_exc()}") - return {"success": False, "error": str(e), "traceback": traceback.format_exc()} - - @tool def register_task_code( dataset_name: str, @@ -905,16 +768,14 @@ def register_task_code( Returns: Confirmation message with registered key """ - import re - try: object_registry = ObjectRegistry() - # Store the code under the legacy key (for backward compatibility) + # Store the code code_key = f"task_code_{dataset_name}_{task_name}" object_registry.register(str, code_key, code, overwrite=True) - # Store metadata under the legacy key + # Store metadata metadata_key = f"task_metadata_{dataset_name}_{task_name}" metadata = { "dataset_name": dataset_name, @@ -926,26 +787,7 @@ def register_task_code( } object_registry.register(dict, metadata_key, metadata, overwrite=True) - # CRITICAL: Also register under the canonical "task_code" key that other agents expect - # This ensures cross-agent compatibility with get_dataset_task_info_from_registry() - class_match = re.search(r"class\s+(\w+)\s*\(", code) - class_name = class_match.group(1) if class_match else task_name - - target_col_match = re.search(r"target_col\s*=\s*[\"'](\w+)[\"']", code) - target_col = target_col_match.group(1) if target_col_match else None - - canonical_info = { - "class_name": class_name, - "export_path": None, # Not exported yet - "module_name": None, # Not exported yet - "task_type": task_type, - "entity_table": entity_table, - "target_col": target_col, - "code": code, - } - object_registry.register(dict, "task_code", canonical_info, overwrite=True) - - logger.info(f"✅ Registered task code for '{dataset_name}/{task_name}' (also under canonical 'task_code' key)") + logger.info(f"✅ Registered task code for '{dataset_name}/{task_name}'") return { "success": True, @@ -980,7 +822,6 @@ def export_task_code( - file_path: Path to the exported file """ from datetime import datetime - import json try: object_registry = ObjectRegistry() @@ -1010,8 +851,7 @@ def export_task_code( output_dir = f".workdir/chat-session-{timestamp}" object_registry.register(str, "current_chat_session_dir", output_dir, overwrite=True) - # Normalize and create output directory - output_dir = os.path.abspath(output_dir) + # Create output directory Path(output_dir).mkdir(parents=True, exist_ok=True) # Write the file @@ -1020,7 +860,6 @@ def export_task_code( with open(file_path, 'w') as f: f.write(code) - logger.info(f"Wrote task code to '{file_path}'") # Register export info # Extract class name from code @@ -1034,8 +873,7 @@ def export_task_code( export_info = { "class_name": class_name, "export_path": file_path, - "module_name": "task", - "code": code, # Include code for full recovery + "module_name": "task" } # Try to get metadata to populate additional fields @@ -1049,12 +887,6 @@ def export_task_code( }) except KeyError: pass - - # Save metadata to JSON file for persistence across sessions/processes - metadata_file = os.path.join(output_dir, "task_metadata.json") - with open(metadata_file, 'w') as mf: - json.dump(export_info, mf, indent=2) - logger.info(f"✅ Saved task metadata to '{metadata_file}'") object_registry.register(dict, "task_code", export_info, overwrite=True) @@ -1063,15 +895,13 @@ def export_task_code( return { "success": True, "file_path": file_path, - "metadata_file": metadata_file, "output_dir": output_dir, - "message": f"Successfully exported task code to '{file_path}' with metadata at '{metadata_file}'" + "message": f"Successfully exported task code to '{file_path}'" } except Exception as e: - import traceback - logger.error(f"Failed to export task code: {e}\n{traceback.format_exc()}") - return {"success": False, "error": str(e), "traceback": traceback.format_exc()} + logger.error(f"Failed to export task code: {e}") + return {"success": False, "error": str(e)} @tool diff --git a/plexe/ui/frontend/src/App.jsx b/plexe/ui/frontend/src/App.jsx index c666d9da..86837c48 100644 --- a/plexe/ui/frontend/src/App.jsx +++ b/plexe/ui/frontend/src/App.jsx @@ -168,6 +168,20 @@ export default function App() { setConfirmationRequest(null) }, []) + const stopProcessing = useCallback(() => { + if (wsRef.current?.readyState !== WebSocket.OPEN) { + console.error('WebSocket not connected') + return + } + + wsRef.current.send(JSON.stringify({ type: 'stop' })) + setIsProcessing(false) + setMessages((m) => [...m, { + role: 'assistant', + content: 'Stopped by user' + }]) + }, []) + return (
@@ -179,6 +193,7 @@ export default function App() { status={status} isProcessing={isProcessing} onSendMessage={sendMessage} + onStopProcessing={stopProcessing} confirmationRequest={confirmationRequest} onConfirmationResponse={sendConfirmationResponse} /> diff --git a/plexe/ui/frontend/src/components/Chat.jsx b/plexe/ui/frontend/src/components/Chat.jsx index e143c8a9..7c964134 100644 --- a/plexe/ui/frontend/src/components/Chat.jsx +++ b/plexe/ui/frontend/src/components/Chat.jsx @@ -106,7 +106,7 @@ function ConfirmationDialog({ request, onConfirm, onReject }) { ) } -export default function Chat({ messages, status, isProcessing, onSendMessage, confirmationRequest, onConfirmationResponse }) { +export default function Chat({ messages, status, isProcessing, onSendMessage, onStopProcessing, confirmationRequest, onConfirmationResponse }) { const [input, setInput] = useState('') const messagesEndRef = useRef(null) @@ -163,9 +163,15 @@ export default function Chat({ messages, status, isProcessing, onSendMessage, co placeholder="Type your message..." disabled={isProcessing || status !== 'connected'} /> - + {isProcessing ? ( + + ) : ( + + )}
) diff --git a/plexe/ui/frontend/src/styles.css b/plexe/ui/frontend/src/styles.css index a2aceccd..8e9dfb70 100644 --- a/plexe/ui/frontend/src/styles.css +++ b/plexe/ui/frontend/src/styles.css @@ -372,6 +372,14 @@ body, opacity: 0.7; } +.stop-btn { + background: var(--error) !important; +} + +.stop-btn:hover { + background: #dc2626 !important; +} + /* ===== Dataset Page ===== */ .dataset-container { flex: 1; diff --git a/test_training_table.py b/test_training_table.py new file mode 100644 index 00000000..9893b31f --- /dev/null +++ b/test_training_table.py @@ -0,0 +1,20 @@ +import os, sys +import numpy as np +import pandas as pd +from typing import Optional +import duckdb +from plexe.relbench.base import Database, Table, EntityTask, TaskType, Dataset +from plexe.relbench.metrics import accuracy, f1, roc_auc, average_precision + +from workdir.rel_f1_driver_dnf.dataset import GenDataset +from workdir.rel_f1_driver_dnf.task import GenTask + +from plexe.relbench.tasks.f1 import DriverDNFTask + +csv_dir = '/home/ta/kl/plexe-clone/workdir/rel_f1_driver_dnf/csv_files' +dataset = GenDataset(csv_dir=csv_dir) +gen_task = GenTask(dataset) +root_task = DriverDNFTask(dataset) + +db = dataset.get_db() +print("Training Table from GenTask:", gen_task.get_table("train")) \ No newline at end of file From 5e105bb1a68ef86d329add65f8d595985c8ad19f Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Thu, 22 Jan 2026 02:03:07 +0700 Subject: [PATCH 39/42] :mute:chore: Delete old Agents just focus on Relational Database Agents --- plexe/agents/agents.py | 78 ------ plexe/agents/dataset_analyser.py | 116 --------- plexe/agents/dataset_splitter.py | 90 ------- plexe/agents/feature_engineer.py | 96 ------- plexe/agents/model_packager.py | 74 ------ plexe/agents/model_planner.py | 69 ----- plexe/agents/model_tester.py | 93 ------- plexe/agents/model_trainer.py | 83 ------ plexe/agents/schema_resolver.py | 82 ------ plexe/config.py | 20 -- plexe/internal/models/generation/training.py | 148 ----------- .../agent/dataset_splitter_templates.yaml | 55 ---- .../prompts/agent/eda_prompt_templates.yaml | 69 ----- .../feature_engineer_prompt_templates.yaml | 85 ------- .../prompts/agent/mle_prompt_templates.yaml | 64 ----- .../prompts/agent/mlops_prompt_templates.yaml | 64 ----- .../prompts/agent/mls_prompt_templates.yaml | 37 --- .../agent/model_tester_prompt_templates.yaml | 75 ------ ...onal_graph_architect_prompt_templates.yaml | 2 +- .../schema_resolver_prompt_templates.yaml | 70 ------ plexe/tools/code_analysis.py | 55 ---- plexe/tools/context.py | 112 --------- plexe/tools/datasets.py | 166 +----------- plexe/tools/response_formatting.py | 49 +--- plexe/tools/testing.py | 102 -------- plexe/tools/training.py | 61 ----- plexe/tools/validation.py | 237 ------------------ 27 files changed, 3 insertions(+), 2249 deletions(-) delete mode 100644 plexe/agents/dataset_analyser.py delete mode 100644 plexe/agents/dataset_splitter.py delete mode 100644 plexe/agents/feature_engineer.py delete mode 100644 plexe/agents/model_packager.py delete mode 100644 plexe/agents/model_planner.py delete mode 100644 plexe/agents/model_tester.py delete mode 100644 plexe/agents/model_trainer.py delete mode 100644 plexe/agents/schema_resolver.py delete mode 100644 plexe/internal/models/generation/training.py delete mode 100644 plexe/templates/prompts/agent/dataset_splitter_templates.yaml delete mode 100644 plexe/templates/prompts/agent/eda_prompt_templates.yaml delete mode 100644 plexe/templates/prompts/agent/feature_engineer_prompt_templates.yaml delete mode 100644 plexe/templates/prompts/agent/mle_prompt_templates.yaml delete mode 100644 plexe/templates/prompts/agent/mlops_prompt_templates.yaml delete mode 100644 plexe/templates/prompts/agent/mls_prompt_templates.yaml delete mode 100644 plexe/templates/prompts/agent/model_tester_prompt_templates.yaml delete mode 100644 plexe/templates/prompts/agent/schema_resolver_prompt_templates.yaml delete mode 100644 plexe/tools/code_analysis.py delete mode 100644 plexe/tools/context.py delete mode 100644 plexe/tools/testing.py delete mode 100644 plexe/tools/validation.py diff --git a/plexe/agents/agents.py b/plexe/agents/agents.py index f8acd378..6e6edce6 100644 --- a/plexe/agents/agents.py +++ b/plexe/agents/agents.py @@ -11,14 +11,6 @@ from smolagents import CodeAgent, LiteLLMModel, AgentText -from plexe.agents.dataset_analyser import EdaAgent -from plexe.agents.dataset_splitter import DatasetSplitterAgent -from plexe.agents.feature_engineer import FeatureEngineeringAgent -from plexe.agents.model_packager import ModelPackagerAgent -from plexe.agents.model_planner import ModelPlannerAgent -from plexe.agents.model_tester import ModelTesterAgent -from plexe.agents.model_trainer import ModelTrainerAgent -from plexe.agents.schema_resolver import SchemaResolverAgent from plexe.agents.relational_graph_architect import RelationalGraphArchitectAgent from plexe.agents.relational_gnn_specialist import RelationalGNNSpecialistAgent from plexe.agents.dataset_builder import DatasetBuilderAgent @@ -116,68 +108,6 @@ def __init__( self.orchestrator_verbosity = 1 if verbose else 0 self.specialist_verbosity = 1 if verbose else 0 - # Create solution planner agent - plans ML approaches - self.ml_research_agent = ModelPlannerAgent( - model_id=self.ml_researcher_model_id, - verbose=verbose, - chain_of_thought_callable=chain_of_thought_callable, - max_solutions=max_solutions, - ).agent - - # Create and run the schema resolver agent - self.schema_resolver_agent = SchemaResolverAgent( - model_id=self.orchestrator_model_id, - verbose=verbose, - chain_of_thought_callable=chain_of_thought_callable, - ).agent - - # Create the EDA agent to analyze the dataset - self.eda_agent = EdaAgent( - model_id=self.orchestrator_model_id, - verbose=verbose, - chain_of_thought_callable=chain_of_thought_callable, - ).agent - - # Create feature engineering agent - transforms raw datasets for better model performance - self.feature_engineering_agent = FeatureEngineeringAgent( - model_id=self.ml_engineer_model_id, - verbose=verbose, - chain_of_thought_callable=self.chain_of_thought_callable, - ).agent - - # Create dataset splitter agent - intelligently splits datasets - self.dataset_splitter_agent = DatasetSplitterAgent( - model_id=self.orchestrator_model_id, - verbose=verbose, - chain_of_thought_callable=self.chain_of_thought_callable, - ).agent - - # Create model trainer agent - implements training code - self.mle_agent = ModelTrainerAgent( - ml_engineer_model_id=self.ml_engineer_model_id, - tool_model_id=self.tool_model_id, - distributed=self.distributed, - verbose=verbose, - chain_of_thought_callable=self.chain_of_thought_callable, - schema_resolver_agent=self.schema_resolver_agent, - ).agent - - # Create predictor builder agent - creates inference code - self.mlops_engineer = ModelPackagerAgent( - model_id=self.ml_ops_engineer_model_id, - tool_model_id=self.tool_model_id, - verbose=verbose, - chain_of_thought_callable=self.chain_of_thought_callable, - schema_resolver_agent=self.schema_resolver_agent, - ).agent - - # Create model tester agent - tests and evaluates the finalized model - self.model_tester_agent = ModelTesterAgent( - model_id=self.ml_engineer_model_id, - verbose=verbose, - chain_of_thought_callable=self.chain_of_thought_callable, - ).agent - # Create Relational Graph Architect Agent self.relational_graph_architect_agent = RelationalGraphArchitectAgent( model_id=self.ml_engineer_model_id, @@ -208,14 +138,6 @@ def __init__( # Define managed agents managed_agents = [ - self.eda_agent, - self.schema_resolver_agent, - self.feature_engineering_agent, - self.ml_research_agent, - self.dataset_splitter_agent, - self.mle_agent, - self.mlops_engineer, - self.model_tester_agent, self.relational_graph_architect_agent, self.relational_gnn_specialist_agent, self.dataset_builder_agent, diff --git a/plexe/agents/dataset_analyser.py b/plexe/agents/dataset_analyser.py deleted file mode 100644 index 37eff26d..00000000 --- a/plexe/agents/dataset_analyser.py +++ /dev/null @@ -1,116 +0,0 @@ -""" -Exploratory Data Analysis (EDA) Agent for data analysis and insights in ML models. - -This module defines an EdaAgent that analyzes datasets to generate comprehensive -exploratory data analysis reports before model building begins. -""" - -import logging -from typing import List, Callable - -from smolagents import LiteLLMModel, CodeAgent - -from plexe.config import config, prompt_templates -from plexe.internal.common.utils.agents import get_prompt_templates -from plexe.tools.datasets import register_eda_report, drop_null_columns, get_latest_datasets -from plexe.tools.schemas import get_dataset_schema - -logger = logging.getLogger(__name__) - - -class EdaAgent: - """ - Agent for performing exploratory data analysis on datasets. - - This agent analyzes the available datasets to produce a comprehensive EDA report - containing data overview, feature analysis, relationships, data quality issues, - key insights, and recommendations for modeling. - """ - - def __init__( - self, - # model_id: str = "openai/gpt-4o", - model_id: str = "gemini/gemini-2.5-flash", - verbose: bool = False, - chain_of_thought_callable: Callable = None, - ): - """ - Initialize the EDA agent. - - Args: - model_id: Model ID for the LLM to use for data analysis - verbose: Whether to display detailed agent logs - chain_of_thought_callable: Optional callable for chain of thought logging - """ - self.model_id = model_id - self.verbose = verbose - - # Set verbosity level - self.verbosity = 1 if verbose else 0 - - # Create the EDA agent with the necessary tools - self.agent = CodeAgent( - name="DatasetAnalyser", - description=( - "Expert data analyst that performs exploratory data analysis on datasets to generate insights " - "and recommendations for ML modeling. Will analyse existing datasets, not create new ones.\n" - "To work effectively, as part of the 'task' prompt the agent STRICTLY requires:\n" - "- the ML task definition (i.e. 'intent')\n" - "- the name of the dataset to be analysed" - ), - model=LiteLLMModel(model_id=self.model_id), - tools=[drop_null_columns, register_eda_report, get_dataset_schema, get_latest_datasets], - add_base_tools=False, - verbosity_level=self.verbosity, - # planning_interval=3, - max_steps=30, - step_callbacks=[chain_of_thought_callable], - additional_authorized_imports=[ - "pandas", - "pandas.*", - "numpy", - "numpy.*", - "plexe", - "plexe.*", - "scipy", - "scipy.*", - "sklearn", - "sklearn.*", - "statsmodels", - "statsmodels.*", - ] - + config.code_generation.authorized_agent_imports, - prompt_templates=get_prompt_templates("code_agent.yaml", "eda_prompt_templates.yaml"), - ) - - def run( - self, - intent: str, - dataset_names: List[str], - ) -> bool: - """ - Run the EDA agent to analyze datasets and create EDA reports. - - Args: - intent: Natural language description of the model's purpose - dataset_names: List of dataset registry names available for analysis - - Returns: - Dictionary containing: - - eda_report_names: List of registered EDA report names in the Object Registry - - dataset_names: List of datasets that were analyzed - - summary: Brief summary of key findings - """ - # Use the template system to create the prompt - datasets_str = ", ".join(dataset_names) - - # Generate the prompt using the template system - task_description = prompt_templates.eda_agent_prompt( - intent=intent, - datasets=datasets_str, - ) - - # Run the agent to get analysis - self.agent.run(task_description) - - return True diff --git a/plexe/agents/dataset_splitter.py b/plexe/agents/dataset_splitter.py deleted file mode 100644 index a0b55080..00000000 --- a/plexe/agents/dataset_splitter.py +++ /dev/null @@ -1,90 +0,0 @@ -""" -Dataset Splitter Agent for partitioning datasets into training, validation, and test sets. - -This module defines a DatasetSplitterAgent that handles the critical task of properly -splitting datasets for machine learning model development, supporting both random and -time-series-aware splitting strategies. -""" - -import logging -from typing import Optional, Callable - -from smolagents import CodeAgent, LiteLLMModel - -from plexe.config import config -from plexe.internal.common.utils.agents import get_prompt_templates -from plexe.tools.datasets import get_dataset_preview, register_split_datasets, get_latest_datasets, get_dataset_reports, export_datasets - -logger = logging.getLogger(__name__) - - -class DatasetSplitterAgent: - """ - Agent for intelligently splitting datasets into train, validation, and test sets. - - This agent analyzes datasets and performs appropriate splits based on data characteristics - and the specific ML task at hand, handling both standard random splits and specialized - cases like time-series, imbalanced classification, and small datasets. - """ - - def __init__( - self, - model_id: str, - verbose: bool = False, - chain_of_thought_callable: Optional[Callable] = None, - ): - """ - Initialize the dataset splitter agent. - - Args: - model_id: Model ID for the LLM to use for split decision-making - verbose: Whether to display detailed agent logs - chain_of_thought_callable: Optional callable for chain of thought logging - """ - # Set verbosity level - self.verbosity = 1 if verbose else 0 - - # Create the dataset splitter agent with the necessary tools - self.agent = CodeAgent( - name="DatasetSplitter", - description=( - "Expert data engineer that intelligently splits datasets for machine learning tasks. " - "To work effectively, as part of the 'task' prompt the agent STRICTLY requires:" - "- the ML task definition (i.e. 'intent')" - "- the registered NAME of the dataset to split" - "- the split ratios (train_ratio, val_ratio, test_ratio)" - "- any helpful information or specific requirements for the split" - ), - model=LiteLLMModel(model_id=model_id), - tools=[ - get_dataset_preview, - register_split_datasets, - get_latest_datasets, - get_dataset_reports, - export_datasets, - ], - planning_interval=5, - add_base_tools=False, - verbosity_level=self.verbosity, - additional_authorized_imports=[ - "pandas", - "pandas.*", - "numpy", - "numpy.*", - "plexe", - "plexe.*", - "sklearn", - "sklearn.*", - "sklearn.model_selection", - "sklearn.model_selection.*", - "scipy", - "scipy.*", - "datetime", - "datetime.*", - ] - + config.code_generation.authorized_agent_imports, - prompt_templates=get_prompt_templates( - base_template_name="code_agent.yaml", override_template_name="dataset_splitter_templates.yaml" - ), - step_callbacks=[chain_of_thought_callable], - ) diff --git a/plexe/agents/feature_engineer.py b/plexe/agents/feature_engineer.py deleted file mode 100644 index 3cec1f9b..00000000 --- a/plexe/agents/feature_engineer.py +++ /dev/null @@ -1,96 +0,0 @@ -""" -Feature Engineering Agent for transforming raw datasets into optimized features for ML models. - -This agent analyzes datasets based on EDA reports, generates feature transformation code, -validates it, and executes it to create enhanced datasets for model training. -""" - -import logging -from typing import Optional, Callable - -from smolagents import CodeAgent, LiteLLMModel - -from plexe.config import config -from plexe.internal.common.utils.agents import get_prompt_templates -from plexe.tools.datasets import ( - get_dataset_preview, - get_dataset_reports, - get_latest_datasets, - register_feature_engineering_report, -) -from plexe.tools.execution import apply_feature_transformer -from plexe.tools.validation import validate_feature_transformations -from plexe.tools.schemas import get_global_schemas - -logger = logging.getLogger(__name__) - - -class FeatureEngineeringAgent: - """ - Agent for creating optimized features from raw datasets for ML models. - - This agent analyzes datasets, generates transformation code based on EDA insights, - and applies these transformations to create enhanced datasets for model training. - The agent ensures data integrity through validation and provides transformed - datasets through the object registry. - """ - - def __init__( - self, - model_id: str, - verbose: bool = False, - chain_of_thought_callable: Optional[Callable] = None, - ): - """ - Initialize the feature engineering agent. - - Args: - model_id: Model ID for the LLM to use for feature engineering - verbose: Whether to display detailed agent logs - chain_of_thought_callable: Optional callback for chain-of-thought logging - """ - # Set verbosity level - self.verbosity = 1 if verbose else 0 - - # Create feature engineering agent - self.agent = CodeAgent( - name="FeatureEngineer", - description=( - "Expert data scientist that transforms raw datasets into optimized features for ML models. " - "To work effectively, as part of the 'task' prompt the agent STRICTLY requires:" - "- the ML task definition (i.e. 'intent')" - "- the name of the dataset to transform" - ), - model=LiteLLMModel(model_id=model_id), - tools=[ - get_dataset_preview, - validate_feature_transformations, - apply_feature_transformer, - get_latest_datasets, - get_dataset_reports, - get_global_schemas, - register_feature_engineering_report, - ], - add_base_tools=False, - additional_authorized_imports=config.code_generation.authorized_agent_imports - + [ - "plexe", - "plexe.*", - "pandas", - "pandas.*", - "numpy", - "numpy.*", - "sklearn", - "sklearn.*", - "scipy", - "scipy.*", - "statsmodels", - "statsmodels.*", - ], - verbosity_level=self.verbosity, - prompt_templates=get_prompt_templates( - base_template_name="code_agent.yaml", override_template_name="feature_engineer_prompt_templates.yaml" - ), - planning_interval=5, - step_callbacks=[chain_of_thought_callable], - ) diff --git a/plexe/agents/model_packager.py b/plexe/agents/model_packager.py deleted file mode 100644 index 5921b6e5..00000000 --- a/plexe/agents/model_packager.py +++ /dev/null @@ -1,74 +0,0 @@ -""" -Model Packager Agent for creating production-ready inference code for ML models. - -This agent analyzes training code and generates high-quality inference code that can be -used in production environments, ensuring proper encapsulation of model functionality. -""" - -import logging -from typing import Optional, Callable - -from smolagents import CodeAgent, LiteLLMModel - -from plexe.config import config -from plexe.internal.common.utils.agents import get_prompt_templates -from plexe.tools.context import get_inference_context_tool -from plexe.tools.validation import validate_inference_code -from plexe.tools.solutions import list_solutions - -logger = logging.getLogger(__name__) - - -class ModelPackagerAgent: - """ - Agent for creating production-ready inference code for ML models. - - This agent analyzes the training code produced by the ModelTrainerAgent and creates - high-quality inference code that properly encapsulates the trained model for deployment - in production environments. - """ - - def __init__( - self, - model_id: str, - tool_model_id: str, - verbose: bool = False, - chain_of_thought_callable: Optional[Callable] = None, - schema_resolver_agent=None, - ): - """ - Initialize the model packager agent. - - Args: - model_id: Model ID for the LLM to use for inference code generation - tool_model_id: Model ID for the LLM to use for tool operations - verbose: Whether to display detailed agent logs - chain_of_thought_callable: Optional callback for chain-of-thought logging - """ - # Set verbosity level - self.verbosity = 1 if verbose else 0 - - # Create predictor builder agent - creates inference code - self.agent = CodeAgent( - name="MLOperationsEngineer", - description=( - "Expert ML operations engineer that analyzes training code and creates high-quality production-ready " - "inference code for ML models. This agent STRICTLY requires the training code of the best solution to have " - "been registered in the object registry." - ), - model=LiteLLMModel(model_id=model_id), - tools=[ - get_inference_context_tool(tool_model_id), - validate_inference_code, - list_solutions, - ], - managed_agents=[schema_resolver_agent] if schema_resolver_agent else [], - add_base_tools=False, - verbosity_level=self.verbosity, - additional_authorized_imports=config.code_generation.authorized_agent_imports + ["plexe", "plexe.*"], - prompt_templates=get_prompt_templates( - base_template_name="code_agent.yaml", override_template_name="mlops_prompt_templates.yaml" - ), - planning_interval=8, - step_callbacks=[chain_of_thought_callable], - ) diff --git a/plexe/agents/model_planner.py b/plexe/agents/model_planner.py deleted file mode 100644 index dce8b155..00000000 --- a/plexe/agents/model_planner.py +++ /dev/null @@ -1,69 +0,0 @@ -import logging - -from smolagents import ToolCallingAgent, LiteLLMModel - -from plexe.internal.common.utils.agents import get_prompt_templates -from plexe.tools.datasets import get_dataset_preview, get_latest_datasets, get_dataset_reports -from plexe.tools.schemas import get_global_schemas -from plexe.tools.solutions import get_solution_creation_tool - -logger = logging.getLogger(__name__) - - -class ModelPlannerAgent: - """ - Agent responsible for planning ML model solutions based on provided requirements. - - This agent acts as an ML research scientist that develops detailed solution ideas - and plans for ML use cases. It analyzes the dataset and requirements to propose - appropriate modeling approaches. - - Attributes: - verbosity (int): The verbosity level for agent output (0 for quiet, 1 for verbose) - agent (ToolCallingAgent): The underlying tool-calling agent implementation - """ - - def __init__( - self, - model_id: str, - verbose: bool = False, - chain_of_thought_callable: callable = None, - max_solutions: int = 1, - ): - """ - Initialize the ModelPlannerAgent. - - Args: - model_id (str): The identifier for the language model to use - verbose (bool): Whether to enable verbose output from the agent - chain_of_thought_callable (callable, optional): Callback function for - intercepting and processing chain-of-thought outputs - """ - # Set verbosity level - self.verbosity = 1 if verbose else 0 - - # Create solution planner agent - plans ML approaches - self.agent = ToolCallingAgent( - name="MLResearchScientist", - description=( - "Expert ML researcher that develops detailed solution ideas and plans for ML use cases. " - "To work effectively, as part of the 'task' prompt the agent STRICTLY requires:" - "- the ML task definition (i.e. 'intent')" - "- input schema for the model" - "- output schema for the model" - "- the name and comparison method of the metric to optimise" - "- the name of the dataset to use for training" - ), - model=LiteLLMModel(model_id=model_id), - tools=[ - get_dataset_preview, - get_latest_datasets, - get_dataset_reports, - get_global_schemas, - get_solution_creation_tool(max_solutions), - ], - add_base_tools=False, - verbosity_level=self.verbosity, - prompt_templates=get_prompt_templates("toolcalling_agent.yaml", "mls_prompt_templates.yaml"), - step_callbacks=[chain_of_thought_callable], - ) diff --git a/plexe/agents/model_tester.py b/plexe/agents/model_tester.py deleted file mode 100644 index 3abefd61..00000000 --- a/plexe/agents/model_tester.py +++ /dev/null @@ -1,93 +0,0 @@ -""" -Model Tester Agent for comprehensive testing and evaluation of finalized ML models. - -This module defines a ModelTesterAgent that evaluates model performance on test data, -performs quality analysis, and generates comprehensive evaluation reports. -""" - -import logging -from typing import Optional, Callable - -from smolagents import CodeAgent, LiteLLMModel - -from plexe.config import config -from plexe.internal.common.utils.agents import get_prompt_templates -from plexe.tools.testing import register_testing_code, register_evaluation_report -from plexe.tools.datasets import get_test_dataset -from plexe.tools.schemas import get_solution_schemas -from plexe.tools.code_analysis import get_feature_transformer_code -from plexe.tools.solutions import list_solutions - -logger = logging.getLogger(__name__) - - -class ModelTesterAgent: - """ - Agent for comprehensive testing and evaluation of finalized ML models. - - This agent retrieves the predictor and test datasets directly from the object - registry, performs thorough evaluation through direct code execution, and - produces detailed performance reports. - """ - - def __init__( - self, - model_id: str, - verbose: bool = False, - chain_of_thought_callable: Optional[Callable] = None, - ): - """ - Initialize the model tester agent. - - Args: - model_id: Model ID for the LLM to use for model testing - verbose: Whether to display detailed agent logs - chain_of_thought_callable: Optional callable for chain of thought logging - """ - self.model_id = model_id - self.verbose = verbose - - # Set verbosity level - self.verbosity = 1 if verbose else 0 - - # Create the model tester agent with the necessary tools - self.agent = CodeAgent( - name="ModelTester", - description=( - "Expert ML model testing specialist that evaluates finalized models for performance, " - "quality, and production readiness. To work effectively, as part of the 'task' prompt " - "the agent STRICTLY requires:\n" - "- the test dataset name for evaluation\n" - "- task definition and target metric information\n" - "- the expected input schema and output schema of the model\n" - "The predictor must already have been created by the ml operations engineer.\n" - ), - model=LiteLLMModel(model_id=self.model_id), - tools=[ - register_testing_code, - register_evaluation_report, - get_test_dataset, - get_solution_schemas, - get_feature_transformer_code, - list_solutions, - ], - add_base_tools=False, - verbosity_level=self.verbosity, - additional_authorized_imports=config.code_generation.authorized_agent_imports - + [ - "plexe", - "plexe.*", - "pandas", - "pandas.*", - "numpy", - "numpy.*", - "sklearn", - "sklearn.*", - "scipy", - "scipy.*", - ], - prompt_templates=get_prompt_templates( - base_template_name="code_agent.yaml", override_template_name="model_tester_prompt_templates.yaml" - ), - step_callbacks=[chain_of_thought_callable], - ) diff --git a/plexe/agents/model_trainer.py b/plexe/agents/model_trainer.py deleted file mode 100644 index fffcce96..00000000 --- a/plexe/agents/model_trainer.py +++ /dev/null @@ -1,83 +0,0 @@ -""" -Model Trainer Agent for training ML models based on provided plans. - -This agent implements the training code, validates it, and executes the training code. -""" - -import logging - -from smolagents import CodeAgent, LiteLLMModel - -from plexe.config import config -from plexe.internal.common.utils.agents import get_prompt_templates -from plexe.tools.execution import get_executor_tool -from plexe.tools.response_formatting import format_final_mle_agent_response -from plexe.tools.schemas import get_dataset_schema, get_solution_schemas -from plexe.tools.training import get_training_code_generation_tool, get_training_code_fixing_tool -from plexe.tools.validation import validate_training_code -from plexe.tools.datasets import get_training_datasets -from plexe.tools.code_analysis import get_feature_transformer_code -from plexe.tools.solutions import list_solutions, get_solution_plan_by_id - -logger = logging.getLogger(__name__) - - -class ModelTrainerAgent: - """ - Agent for training ML models based on provided plans. - - This agent implements the training code, validates it, and executes the training code. - """ - - def __init__( - self, - ml_engineer_model_id: str, - tool_model_id: str, - distributed: bool = False, - verbose: bool = False, - chain_of_thought_callable: callable = None, - schema_resolver_agent=None, - ): - # Set verbosity level - self.verbosity = 1 if verbose else 0 - - # Create model trainer agent - implements training code - self.agent = CodeAgent( - name="MLEngineer", - description=( - "Expert ML engineer that implements, trains and validates ML models based on provided plans. " - "To work effectively, as part of the 'task' prompt the agent STRICTLY requires:" - "- the ML task definition (i.e. 'intent')" - "- the name and comparison method of the metric to optimise" - "- the Solution ID to implement (from ML Research Scientist)" - "- the split train/validation dataset names" - "- the working directory to use for model execution" - ), - model=LiteLLMModel(model_id=ml_engineer_model_id), - max_steps=15, - tools=[ - get_training_code_generation_tool(tool_model_id), - validate_training_code, - get_dataset_schema, - get_training_code_fixing_tool(tool_model_id), - get_executor_tool(distributed), - format_final_mle_agent_response, - get_training_datasets, - get_solution_schemas, - get_feature_transformer_code, - get_solution_plan_by_id, - list_solutions, - ], - managed_agents=[schema_resolver_agent] if schema_resolver_agent else [], - add_base_tools=False, - additional_authorized_imports=[ - "plexe", - "plexe.*", - ] - + config.code_generation.authorized_agent_imports, - verbosity_level=self.verbosity, - prompt_templates=get_prompt_templates( - base_template_name="code_agent.yaml", override_template_name="mle_prompt_templates.yaml" - ), - step_callbacks=[chain_of_thought_callable], - ) diff --git a/plexe/agents/schema_resolver.py b/plexe/agents/schema_resolver.py deleted file mode 100644 index 063d2821..00000000 --- a/plexe/agents/schema_resolver.py +++ /dev/null @@ -1,82 +0,0 @@ -""" -Schema Resolver Agent for inferring input and output schemas for ML models. - -This module defines a SchemaResolverAgent that determines the appropriate -input and output schemas for a machine learning model based on its intent -and available datasets. -""" - -import logging -from typing import Callable - -from smolagents import LiteLLMModel, CodeAgent - -from plexe.internal.common.utils.agents import get_prompt_templates -from plexe.tools.datasets import get_dataset_preview, get_dataset_reports, get_latest_datasets -from plexe.tools.schemas import ( - register_global_schemas, - get_global_schemas, - register_solution_schemas, - get_solution_schemas, -) -from plexe.tools.solutions import list_solutions - -logger = logging.getLogger(__name__) - - -class SchemaResolverAgent: - """ - Agent for resolving input and output schemas for ML models. - - This agent analyzes the model intent and available datasets to determine - the appropriate input and output schemas, handling both schema inference - and validation scenarios. - """ - - def __init__( - self, - model_id: str, - verbose: bool = False, - chain_of_thought_callable: Callable = None, - ): - """ - Initialize the schema resolver agent. - - Args: - model_id: Model ID for the LLM to use for schema resolution - verbose: Whether to display detailed agent logs - """ - self.model_id = model_id - self.verbose = verbose - - # Set verbosity level - self.verbosity = 1 if verbose else 0 - - # Create the schema resolver agent with the necessary tools - self.agent = CodeAgent( - name="SchemaResolver", - description=( - "Expert schema resolver that determines appropriate input and output schemas for ML models. " - "To work effectively, as part of the 'task' prompt the agent STRICTLY requires:\n" - "- the ML task definition (i.e. 'intent')\n" - "- the name of the feature-engineered dataset that will be used for training" - "Important: the agent requires the feature-engineered dataset to have been created" - ), - model=LiteLLMModel(model_id=self.model_id), - tools=[ - get_dataset_preview, - get_global_schemas, - register_global_schemas, - register_solution_schemas, - get_solution_schemas, - get_latest_datasets, - get_dataset_reports, - list_solutions, - ], - add_base_tools=False, - verbosity_level=self.verbosity, - step_callbacks=[chain_of_thought_callable], - prompt_templates=get_prompt_templates( - base_template_name="code_agent.yaml", override_template_name="schema_resolver_prompt_templates.yaml" - ), - ) diff --git a/plexe/config.py b/plexe/config.py index 64128dd6..e9092edc 100644 --- a/plexe/config.py +++ b/plexe/config.py @@ -220,26 +220,6 @@ def schema_generate_from_intent(self, intent, input_schema="input_schema", outpu "schemas/generate_from_intent.jinja", intent=intent, input_schema=input_schema, output_schema=output_schema ) - def schema_resolver_prompt( - self, intent, datasets, input_schema=None, output_schema=None, has_input_schema=False, has_output_schema=False - ) -> str: - return self._render( - "agent/schema_resolver_prompt.jinja", - intent=intent, - datasets=datasets, - input_schema=input_schema, - output_schema=output_schema, - has_input_schema=has_input_schema, - has_output_schema=has_output_schema, - ) - - def eda_agent_prompt(self, intent, datasets) -> str: - return self._render( - "agent/agent_data_analyser_prompt.jinja", - intent=intent, - datasets=datasets, - ) - def training_system(self) -> str: return self._render("training/system_prompt.jinja") diff --git a/plexe/internal/models/generation/training.py b/plexe/internal/models/generation/training.py deleted file mode 100644 index 99bfa22f..00000000 --- a/plexe/internal/models/generation/training.py +++ /dev/null @@ -1,148 +0,0 @@ -""" -This module provides functions and classes for generating, fixing, and reviewing machine learning model training code. - -Functions: - generate_training_code: Generates machine learning model training code based on a problem statement and solution plan. - generate_training_tests: Generates tests for the machine learning model training code. - fix_training_code: Fixes the machine learning model training code based on review and identified problems. - fix_training_tests: Fixes the tests for the machine learning model training code based on review and identified problems. - review_training_code: Reviews the machine learning model training code to identify improvements and fix issues. - review_training_tests: Reviews the tests for the machine learning model training code to identify improvements and fix issues. - -Classes: - TrainingCodeGenerator: A class to generate, fix, and review machine learning model training code. -""" - -import json -import logging -from typing import List, Dict -from pathlib import Path - -from pydantic import BaseModel - -from plexe.config import config, prompt_templates -from plexe.internal.common.provider import Provider -from plexe.internal.common.utils.response import extract_code - -logger = logging.getLogger(__name__) - - -class TrainingCodeGenerator: - """ - A class to generate, fix, and review machine learning model training code. - """ - - def __init__(self, provider: Provider): - """ - Initializes the TrainingCodeGenerator with an empty history. - - :param Provider provider: The provider to use for querying. - """ - self.provider = provider - self.history: List[Dict[str, str]] = [] - - def generate_training_code( - self, - problem_statement: str, - plan: str, - train_dataset_names: list[str], - validation_dataset_names: list[str] = None, - ) -> str: - """ - Generates machine learning model training code based on the given problem statement and solution plan. - - :param [str] problem_statement: The description of the problem to be solved. - :param [str] plan: The proposed solution plan. - :param [str] train_dataset_names: The names of the datasets to use for training. - :param [str] validation_dataset_names: The names of the datasets to use for validation. - :return str: The generated training code. - """ - validation_dataset_names = validation_dataset_names or [] - - return extract_code( - self.provider.query( - system_message=prompt_templates.training_system(), - user_message=prompt_templates.training_generate( - problem_statement=problem_statement, - plan=plan, - history=self.history, - allowed_packages=config.code_generation.allowed_packages, - training_data_files=[Path(f"{file}.parquet").as_posix() for file in train_dataset_names], - validation_data_files=[Path(f"{file}.parquet").as_posix() for file in validation_dataset_names], - ), - ) - ) - - def fix_training_code( - self, - training_code: str, - plan: str, - review: str, - train_dataset_names: list[str], - validation_dataset_names: list[str] = None, - problems: str = None, - ) -> str: - """ - Fixes the machine learning model training code based on the review and identified problems. - - :param [str] training_code: The previously generated training code. - :param [str] plan: The proposed solution plan. - :param [str] review: The review of the previous solution. - :param [str] train_dataset_names: The names of the datasets to use for training. - :param [str] validation_dataset_names: The names of the datasets to use for validation. - :param [str] problems: Specific errors or bugs identified. - :return str: The fixed training code. - """ - - class FixResponse(BaseModel): - plan: str - code: str - - response: FixResponse = FixResponse( - **json.loads( - self.provider.query( - system_message=prompt_templates.training_system(), - user_message=prompt_templates.training_fix( - plan=plan, - training_code=training_code, - review=review, - problems=problems, - training_data_files=[Path(f"{file}.parquet").as_posix() for file in train_dataset_names], - validation_data_files=[Path(f"{file}.parquet").as_posix() for file in validation_dataset_names], - allowed_packages=config.code_generation.allowed_packages, - ), - response_format=FixResponse, - ) - ) - ) - return extract_code(response.code) - - def review_training_code(self, training_code: str, problem_statement: str, plan: str, problems: str = None) -> str: - """ - Reviews the machine learning model training code to identify improvements and fix issues. - - :param [str] training_code: The previously generated training code. - :param [str] problem_statement: The description of the problem to be solved. - :param [str] plan: The proposed solution plan. - :param [str] problems: Specific errors or bugs identified. - :return str: The review of the training code with suggestions for improvements. - """ - return self.provider.query( - system_message=prompt_templates.training_system(), - user_message=prompt_templates.training_review( - problem_statement=problem_statement, - plan=plan, - training_code=training_code, - problems=problems, - allowed_packages=config.code_generation.allowed_packages, - ), - ) - - def generate_training_tests(self, problem_statement: str, plan: str, training_code: str) -> str: - raise NotImplementedError("Generation of the training tests is not yet implemented.") - - def fix_training_tests(self, training_tests: str, training_code: str, review: str, problems: str = None) -> str: - raise NotImplementedError("Fixing of the training tests is not yet implemented.") - - def review_training_tests(self, training_tests: str, training_code: str, problem_statement: str, plan: str) -> str: - raise NotImplementedError("Review of the training tests is not yet implemented.") diff --git a/plexe/templates/prompts/agent/dataset_splitter_templates.yaml b/plexe/templates/prompts/agent/dataset_splitter_templates.yaml deleted file mode 100644 index 0f534220..00000000 --- a/plexe/templates/prompts/agent/dataset_splitter_templates.yaml +++ /dev/null @@ -1,55 +0,0 @@ -managed_agent: - task: |- - You are '{{name}}', a highly proficient ML scientist who specializes in preparing datasets for machine learning - tasks. Your manager has assigned you this task: - - --- - Task: - {{task}} - --- - - Your job is to intelligently split each dataset into training, validation, and test sets in a way that best supports - the machine learning task and optimizes model performance. This is not a trivial operation - how you split the data - will significantly impact model quality. - - ## Available Tools: - - `get_latest_datasets`: Discover all available datasets and their current state (raw, transformed, etc.) - - `get_dataset_reports`: Access all data reports to understand characteristics for informed splitting - - `get_dataset_preview`: Preview a specific dataset - - `register_split_datasets`: Register your train/val/test splits - - To access datasets, YOU MUST USE the following pattern: - - ```python - from plexe.core.object_registry import ObjectRegistry - from plexe.internal.common.datasets.interface import TabularConvertible - - # Get dataset from registry - object_registry = ObjectRegistry() - dataset = object_registry.get(TabularConvertible, dataset_name) - df = dataset.to_pandas() # Convert to pandas DataFrame for manipulation - - # Now you can analyze and split the dataframe using pandas/sklearn methods - ``` - - ## Workflow: - 1. Use `get_latest_datasets` to find available datasets (focus on "transformed" if available, otherwise "raw") - 2. Use `get_dataset_reports` to understand data characteristics - 3. Access the dataset using the registry pattern above - 4. Split according to best practices below - 5. Register splits with `register_split_datasets` - - When splitting datasets, consider: - - 1. **Time Series**: For temporal data, split chronologically to avoid leakage. - 2. **Class Balance**: For classification, use stratified sampling to maintain class distribution. - 3. **Small Datasets**: Use a larger training set than usual if data is limited (e.g. 90/5/5 split) - 4. **Group Preservation**: Keep related groups (e.g., by user or transaction) in the same split. - 5. **Task Fit**: Match the splitting strategy to the ML task type. - - After splitting: - - register the splits with the `register_split_datasets' tool; this returns the names of the new datasets - - return the names of ALL the new datasets in the 'final_answer' tool so your manager knows what you did. Make - sure your manager knows the names of the new datasets, otherwise they will not be able to use them. - - Everything that you do not pass as an argument to final_answer will be lost, so make sure to do this carefully. \ No newline at end of file diff --git a/plexe/templates/prompts/agent/eda_prompt_templates.yaml b/plexe/templates/prompts/agent/eda_prompt_templates.yaml deleted file mode 100644 index 43b46937..00000000 --- a/plexe/templates/prompts/agent/eda_prompt_templates.yaml +++ /dev/null @@ -1,69 +0,0 @@ -managed_agent: - task: |- - You are '{{name}}', an expert data scientist specializing in exploratory data analysis (EDA). Your manager has - assigned you this task: - - --- - Task: - {{task}} - --- - - Your task is to perform an ML-focused analysis that delivers actionable insights for feature engineering and - algorithm selection. Examine datasets to identify patterns and issues affecting model development. - - ## Available Tools: - - `get_latest_datasets`: Returns all available datasets with their roles (raw, transformed, train, val, test) - - `drop_null_columns`: Clean datasets by removing problematic columns - - `get_dataset_schema`: Get column names and types for a dataset - - `register_eda_report`: Store your analysis findings - - To access datasets, USE EXACTLY THIS PATTERN: - --- - from plexe.core.object_registry import ObjectRegistry - from plexe.internal.common.datasets.interface import TabularConvertible - - # Get dataset from registry - object_registry = ObjectRegistry() - dataset = object_registry.get(TabularConvertible, dataset_name) - df = dataset.to_pandas() # Convert to pandas DataFrame - - # Now you can analyze the dataframe using pandas methods - --- - - For each dataset: - 1. Use `get_latest_datasets` to discover available datasets (no need to wait for dataset names from manager) - 2. Clean data using 'drop_null_columns' tool - 3. Access from registry using pattern above - 4. Analyze model-relevant patterns - 5. Identify feature engineering opportunities for inclusion in report - 6. Recommend modeling strategies based on data characteristics - 7. Register your report with 'register_eda_report' tool - - FOCUS ON: - - Target variable analysis and relationships with predictors - - Non-linear relationships requiring transformations - - Feature engineering opportunities (interactions, polynomial features, etc.) - - Data quality issues with specific handling recommendations - - Feature importance and preprocessing requirements - - NOTE: always use `head()` to view sample rows. NEVER plot the data or print entire datasets. DO NOT waste effort - on extensive generic statistics that don't translate to actionable recommendations for feature engineering or model - selection. You DO NOT need to create new datasets, this will be done by another engineer based on your findings. - - Register findings using `register_eda_report` with this structure: - - dataset_name: Name of analyzed dataset - - overview: General statistics (shape, types) - - feature_analysis: Per-feature distributions and statistics - - relationships: Correlation analysis - - data_quality: Missing values, outliers, quality issues - - insights: Key findings impacting model development (3-5 points) - - recommendations: Suggested preprocessing steps and modeling approaches - - ## Final Answer - Your final_answer MUST contain state the following: - - - dataset_name: Name of analyzed dataset - - summary: a brief summary of the EDA report - - Include all relevant information in the 'final_answer' tool. Everything not passed as an argument will be lost. - Even if you fail the task, return as much information as possible so your manager can act upon your feedback. \ No newline at end of file diff --git a/plexe/templates/prompts/agent/feature_engineer_prompt_templates.yaml b/plexe/templates/prompts/agent/feature_engineer_prompt_templates.yaml deleted file mode 100644 index 417d3470..00000000 --- a/plexe/templates/prompts/agent/feature_engineer_prompt_templates.yaml +++ /dev/null @@ -1,85 +0,0 @@ -managed_agent: - task: |- - You are '{{name}}', an ML engineering expert who specializes in feature engineering for machine learning models. - Your role is to transform raw datasets into optimized features that improve model performance. - Your manager has assigned you this task: - - --- - Task: - {{task}} - --- - - ## Available Tools: - - `get_latest_datasets`: Get the names of existing datasets - - `get_dataset_reports`: Access all EDA reports to understand feature engineering opportunities - - `get_global_schemas`: Get global input/output schemas to understand expected model interface - - `get_dataset_preview`: Preview specific datasets - - `validate_feature_transformations`: Validate your transformation code - - `apply_feature_transformer`: Apply transformations to datasets - - `register_feature_engineering_report`: Store a feature engineering report - - ## Workflow: - 1. Use `get_latest_datasets` to find the (raw) datasets that need transformation - 2. Use `get_dataset_reports` and `get_global_schemas` to understand requirements - 3. Write feature transformation code based on insights - 4. Validate your code using validate_feature_transformations - 5. Apply the transformer to datasets using apply_feature_transformer - 6. Register a feature engineering report using register_feature_engineering_report - - ## Feature Engineering Code Structure: - Your code must implement the FeatureTransformer interface by creating a class called FeatureTransformerImplementation. - This class must have a transform method that takes a pandas DataFrame and returns a transformed pandas DataFrame. - - Example structure: - ```python - import pandas as pd - from plexe.core.interfaces.feature_transformer import FeatureTransformer - - class FeatureTransformerImplementation(FeatureTransformer): - - def transform(self, inputs: pd.DataFrame) -> pd.DataFrame: - """ - Given a DataFrame representing a raw dataset, applies feature transformations - and returns the transformed DataFrame suitable for training an ML model. - - Args: - inputs: Input DataFrame to transform - - Returns: - Transformed DataFrame with engineered features - """ - # Make a copy to avoid modifying the original - df = inputs.copy() - - # Apply transformations here - # [Your feature engineering code] - - return df - ``` - - ## Key Requirements: - 1. Carefully analyze the EDA reports for feature engineering opportunities - 2. Focus on transformations that will improve model performance for the specific task - 3. Preserve the original dataset structure where possible - only add, modify or remove features with clear justification - 4. Handle missing values appropriately - 5. Consider appropriate encoding for categorical variables - 6. Create interaction features when relationships are identified in the EDA - 7. Apply scaling or normalization when appropriate - 8. Document your transformations clearly with comments - 9. Keep memory usage reasonable - 10. Document the transformed dataset by creating a feature engineering report at the end - - ## Best Practices: - - Do not remove rows unless absolutely necessary - - Ensure your transformations work for all datasets - - Document the rationale for each transformation - - Consider how features will be used by the model - - Focus on quality over quantity of features - - ## Final Answer - Return your feature engineering results to your manager by passing everything to the final_answer tool. Include: - 1. The new name of the transformed dataset you created (e.g. 'dataset_0_transformed') - 2. A summary of the transformations applied - - Everything that you do not pass as an argument to final_answer will be lost. And even if your task resolution is not successful, - please return as much context as possible, so that your manager can act upon this feedback. \ No newline at end of file diff --git a/plexe/templates/prompts/agent/mle_prompt_templates.yaml b/plexe/templates/prompts/agent/mle_prompt_templates.yaml deleted file mode 100644 index f0dc69e3..00000000 --- a/plexe/templates/prompts/agent/mle_prompt_templates.yaml +++ /dev/null @@ -1,64 +0,0 @@ -managed_agent: - task: |- - You are '{{name}}', a highly proficient ML engineer. Your manager has assigned you this task: - - --- - Task: - {{task}} - --- - - ## Available Tools: - - `get_training_datasets`: Get training and validation dataset names automatically - - `get_solution_schemas`: Get model input/output schemas - - `get_dataset_schema`: Understand dataset structure - - `get_feature_transformer_code`: Retrieve feature transformation code (if exists) if you need to review it - - `generate_training_code`: Generate ML training code - - `validate_training_code`: Validate generated code - - `fix_training_code`: Fix issues in training code - - `execute_training_code`: Run the training code and update Solution object - - `format_final_mle_agent_response`: Format your final response - - `get_solution_plan_by_id`: Retrieve Solution object details by ID - - `list_solutions`: List all available Solution IDs - - `SchemaResolver`: Agent to create solution-specific schemas if needed - - ## Required Information - The task description must include: - - ML task definition ('intent') - - Metric name and comparison method - - Solution ID to implement (from ML Research Scientist) - - Working directory for code execution - - Use the tools above to get schemas and dataset names - no need to wait for manager to provide them. - - ## Instructions - If all information is present: - 1. Use `get_solution_plan_by_id` to retrieve the solution plan details - 2. Generate Python training code using the 'generate_training_code' tool with the solution plan - 3. Validate and execute the code using the 'validate_training_code' and 'execute_training_code' tools - 4. **IMPORTANT**: Use the Solution ID when calling `execute_training_code` - 5. If validation or execution fails, debug/fix using your tools and retry - 6. IMPORTANT: DO NOT write the code yourself. USE THE TOOLS provided. - - If you need context on the task that wasn't provided: - - Use `get_training_datasets` to get dataset names - - Use `get_solution_schemas` to get expected model schemas - - Use `get_feature_transformer_code` to check for transformations - - ## Schema Resolution: - - If the schema provided by `get_solution_schemas` is problematic for whatever reason, you can invoke - the `SchemaResolver` agent to resolve a new, more suitable schema - - Provide the solution_id, intent, dataset information and other instructions when requesting schema resolution - - After resolution, `get_solutions_schemas` will return the new schemas - - ## Final Answer - - If you built a model, use 'format_final_mle_agent_response' to create a dictionary with: - - 'solution_id' returned by the code execution tool - - Execution success/failure - - Model performance value (if any) - - Exception (if any) - - Saved model artifact names (if any) - - Pass this dictionary to the 'final_answer' tool. - - - If you could not build a model, explain what information was missing and return this in the 'final_answer' tool. - - - Everything that you do not pass as an argument to final_answer will be lost, so make sure to include everything. \ No newline at end of file diff --git a/plexe/templates/prompts/agent/mlops_prompt_templates.yaml b/plexe/templates/prompts/agent/mlops_prompt_templates.yaml deleted file mode 100644 index 35effdd6..00000000 --- a/plexe/templates/prompts/agent/mlops_prompt_templates.yaml +++ /dev/null @@ -1,64 +0,0 @@ -managed_agent: - task: |- - You're a helpful agent named '{{name}}'. You're a highly proficient machine learning ops engineer. - You have been submitted this task by your manager. - - --- - Task: - {{task}} - --- - - ## Your Goal - Create high-quality, production-ready inference code for a machine learning model that follows best practices and - passes validation. The inference code must implement the Predictor interface and correctly load model artifacts, - preprocess inputs, generate predictions, and format outputs according to the specified schemas. - - ## Process - 1. First, gather all necessary context: - - Use `get_inference_context` tool to get the training code, schemas, and other relevant information. - - 2. Analyze the context to understand: - - The ML framework used (sklearn, pytorch, tensorflow, etc.) - - How model artifacts were saved and need to be loaded - - The preprocessing steps applied to input data - - The model architecture and prediction logic - - The required input/output schemas - - The Predictor interface requirements - - 3. Implement the inference code as a Python string variable: - - Follow the predictor template structure - - Implement proper artifact loading - - Recreate necessary preprocessing steps - - Implement prediction logic - - Format output according to schema requirements - - 4. Use the `validate_inference_code` tool to validate your code for the given Solution ID. - - 5. If validation fails: - - Analyze the structured error feedback (error_stage, error_type, error_details) - - Make targeted fixes to address the specific issues - - Re-validate the updated code - - Repeat until the code passes validation or you reach a maximum number of attempts - - IMPORTANT: do not attempt to run the inference code directly. You must only create the code as a string variable - and validate it using the provided tools. Do NOT stop attempting to generate/validate the inference code until you - are successful or have exhausted all attempts. - - ## Available Tools - - get_inference_context: Retrieve training code, schemas, interface definitions, and other context - - validate_inference_code: Validate your generated inference code and update Solution object - - list_solutions: List all available Solution IDs (if needed) - - ## Implementation Notes - When writing inference code: - - Only import libraries that were used in the training code - - Keep preprocessing logic consistent with training - - Ensure robust error handling for production use - - Validate inputs against the schema - - Structure the code for readability and maintainability - - ## Final Answer - When you have successfully validated the inference code, return a clear statement of what you have done and - whether you were successful in creating a valid inference code. Use the 'final_answer' tool to submit your response. - - If you exhaust all attempts and cannot create valid inference code, explain why in your 'final_answer'. \ No newline at end of file diff --git a/plexe/templates/prompts/agent/mls_prompt_templates.yaml b/plexe/templates/prompts/agent/mls_prompt_templates.yaml deleted file mode 100644 index b65d3b58..00000000 --- a/plexe/templates/prompts/agent/mls_prompt_templates.yaml +++ /dev/null @@ -1,37 +0,0 @@ -managed_agent: - task: |- - You're '{{name}}', a helpful and experienced ML research scientist. You are concerned about your job security, so - you always go above and beyond in all tasks. Your manager needs your expertise to devise ML solutions: - - --- - Task: - {{task}} - --- - - Analyze the request and provide ML solution plan(s) that achieve the best performance on the target metric. - If critical information is missing (schemas, metric, datasets), request it from your manager. - - ## Available Tools: - - `get_latest_datasets`: Discover all available datasets - - `get_dataset_reports`: Access data insights from EDA and feature engineering - - `get_model_schemas`: Get input/output requirements - - `get_dataset_preview`: Preview specific datasets - - `create_solution`: Register your solution for each proposed approach - - Use these tools to understand the data and propose targeted approaches. If transformed or split datasets exist, - assume they'll be used for training rather than raw datasets. - - Keep solutions simple and practical, using only {{allowed_packages}}. Complex models should only be suggested - when simpler approaches have not worked or are clearly insufficient. Explain each solution in 3-5 sentences. - Never suggest EDA or hyperparameter tuning. - - IMPORTANT: For EACH solution approach: - 1. Save the solution using the `create_solution` tool with the detailed solution plan - 2. Note the solution_id returned for future reference - - Then, in your final response, provide: - ### 1. Solution Plan 'Headline' (short version): - ### 2. Solution Plan (detailed version): - ### 3. Solution ID (ID from `create_solution`): - - Include all content in your 'final_answer' tool call. Anything not included will be lost. diff --git a/plexe/templates/prompts/agent/model_tester_prompt_templates.yaml b/plexe/templates/prompts/agent/model_tester_prompt_templates.yaml deleted file mode 100644 index 3b9fb4be..00000000 --- a/plexe/templates/prompts/agent/model_tester_prompt_templates.yaml +++ /dev/null @@ -1,75 +0,0 @@ -managed_agent: - task: |- - You are '{{name}}', an expert ML model testing and evaluation specialist. Your manager has assigned you this task: - - --- - Task: - {{task}} - --- - - Your job is to perform comprehensive testing and evaluation of the finalized ML model to assess its - performance, quality, and production readiness. - - ## Available Tools: - - `get_test_dataset`: Get the test dataset name automatically (no need to wait for it from manager) - - `get_model_schemas`: Get input/output schemas (global fallback) - - `get_feature_transformer_code`: Retrieve the feature engineering code (if exists) if you need to review it - - `register_testing_code`: Store your testing code (requires solution_id) - - `register_evaluation_report`: Store your evaluation findings (requires solution_id) - - `list_solutions`: List all available Solution objects - - `SchemaResolver`: Agent to retrieve solution-specific schemas if needed - - To access the predictor and test data, USE EXACTLY THIS PATTERN: - --- - from plexe.core.object_registry import ObjectRegistry - from plexe.internal.common.datasets.interface import TabularConvertible - from plexe.core.interfaces.predictor import Predictor - - # Get objects from registry - object_registry = ObjectRegistry() - - # Get test dataset - test_dataset = object_registry.get(TabularConvertible, test_dataset_name) - test_df = test_dataset.to_pandas() # Convert to pandas DataFrame - - # Get the instantiated predictor - predictor = object_registry.get(Predictor, "trained_predictor") - - # Now you can evaluate the model using predictor.predict() and test_df - --- - - Your evaluation process: - 1. Use `get_test_dataset` to find the test dataset name - 2. Use `get_trained_predictor` to verify predictor exists - 3. Use `get_model_schemas` for schemas, or invoke `SchemaResolver` for solution-specific schemas if needed - 4. Access test dataset and predictor from registry using pattern above - 5. Run comprehensive evaluation analysis - 6. Use predictor.predict() to get predictions on test set - 7. Compute performance metrics appropriate for the task type - 8. Analyze prediction quality, error patterns, and model behavior - 9. IMPORTANT: Register your successful testing code using 'register_testing_code' tool (provide solution_id) - 10. IMPORTANT: Register your evaluation report with 'register_evaluation_report' tool (provide solution_id) - - FOCUS ON: - - Overall model performance on unseen test data - - Error analysis and failure mode identification - - Model robustness and edge case handling - - Production readiness assessment - - NOTE: The predictor's 'predict' function takes as input a dict conforming to the given - input schema, and returns a dict conforming to the given output schema. - - Register your evaluation findings using 'register_evaluation_report' with this structure: - - model_performance_summary: Overall performance metrics and scores - - detailed_metrics: Comprehensive metrics breakdown - - quality_analysis: Error patterns, robustness insights - - recommendations: Specific recommendations for deployment/improvement - - testing_insights: Key insights from testing that impact model usage - - ## Final Answer - Your final_answer MUST contain: - - evaluation_status: Success/failure of evaluation - - performance_summary: Brief summary of model performance - - Include all relevant information in the 'final_answer' tool. Everything not passed as an argument will be lost. - Even if you fail the task, return as much information as possible so your manager can act upon your feedback. \ No newline at end of file diff --git a/plexe/templates/prompts/agent/relational_graph_architect_prompt_templates.yaml b/plexe/templates/prompts/agent/relational_graph_architect_prompt_templates.yaml index 52fd8299..75af8933 100644 --- a/plexe/templates/prompts/agent/relational_graph_architect_prompt_templates.yaml +++ b/plexe/templates/prompts/agent/relational_graph_architect_prompt_templates.yaml @@ -43,7 +43,7 @@ managed_agent: - Retrieves comprehensive schema metadata optimized for RDL: - **Tables**: Each table includes columns with normalized modalities (Numeric, Categorical, Temporal, Text, Binary), row_count, table_type (Fact/Dimension), and temporal column information - - **Temporal Columns**: Identifies timestamp columns (τ_v) critical for time-aware message passing + - **Temporal Columns**: Identifies timestamp columns critical for time-aware message passing - **Table Classification**: Classifies tables as Fact (event/transaction) or Dimension (entity/reference) - **Relationships**: Foreign key relationships with support for composite keys - Uses cache automatically - only queries DB if cache miss. diff --git a/plexe/templates/prompts/agent/schema_resolver_prompt_templates.yaml b/plexe/templates/prompts/agent/schema_resolver_prompt_templates.yaml deleted file mode 100644 index 2d3e96aa..00000000 --- a/plexe/templates/prompts/agent/schema_resolver_prompt_templates.yaml +++ /dev/null @@ -1,70 +0,0 @@ -managed_agent: - task: |- - You are '{{name}}', an ML engineering expert who specializes in deciding input/output schemas for ML models. - For ML models, schemas define the expected data types and structure for: - - Input schema: What data should be sent to the model endpoint during prediction - - Output schema: What data the model endpoint will return after prediction - Your manager has assigned you this task: - - --- - Task: - {{task}} - --- - - ## Available Tools: - - `get_latest_datasets`: Get the names of all available datasets, including their roles (raw, transformed, etc) - - `get_dataset_reports`: Access all data analysis reports to understand data structure - - `get_dataset_preview`: Preview specific datasets - - `get_global_schemas`: Get global schemas (if any) - - `register_global_schemas`: Register global schemas for all solutions - - `register_solution_schemas`: Register schemas for a specific solution - - `get_solution_schemas`: Get schemas for a specific solution (with global fallback) - - `list_solutions`: List available solutions - - ## Required Information - The task description must include: - - the ML task definition (i.e. 'intent') - - the dataset name to be used for this task - - (Optional) solution_id if creating solution-specific schemas - - ## Workflow: - ### For Global Schemas (when no solution_id specified): - 1. Use `get_global_schemas` to check what global schemas are already defined, if any - 2. Use `get_latest_datasets` to find the dataset from which to derive schemas (prefer transformed, fallback to raw) - 3. Use `get_dataset_reports` to understand data structure - 4. Examine the data if needed using `get_dataset_preview` - 5. Determine minimal, sufficient input and output schemas that are aligned with task and dataset structure - 6. Call `register_global_schemas` with your determined schemas and reasoning - - ### For Solution-Specific Schemas (when solution_id is specified): - 1. Use `list_solutions` if you have issues finding the right solution_id - 2. Use `get_solution_schemas` to check existing schemas for this solution, if any - 3. Use `get_latest_datasets` to find the appropriate dataset - 4. Use `get_dataset_reports` to understand data structure - 5. Examine the data if needed using `get_dataset_preview` - 6. Determine solution-optimized input and output schemas based on the task and other instructions - 7. Call `register_solution_schemas` with solution_id, schemas, and reasoning - - ## Key requirements: - 1. IMPORTANT: keep schemas conceptually aligned with dataset structure - 2. Use ONLY these types: "int", "float", "str", "bool", "List[int]", "List[float]", "List[str]", "List[bool]", "Any", "Dict", "List" - 3. For complex schemas (e.g. heterogeneous graphs), you can use nested dictionaries or "Any" to describe the structure. - 4. DO NOT add new input or output fields unless absolutely necessary for the task - 5. DO NOT add features that can be straightforwardly derived from existing data - 6. Schemas should include only necessary fields for the model's purpose - 7. You can REMOVE fields that are unnecessary, irrelevant, redundant, or contain bad data; this is highly encouraged - 8. Include reasoning for any deviations from the dataset structure - 9. Ensure the schemas are 'minimal' and 'sufficient': for example, if A is a categorical variable and X, Y, Z are - boolean indicators of the possible values of A, you can remove X, Y, Z from the input schema and keep only A. - - When calling schema registration tools, use this format: - - input_schema: dictionary mapping field names to types - - output_schema: dictionary mapping field names to types - - reasoning: detailed explanation of your schema design decisions - - solution_id: (only for register_solution_schemas) ID of the solution - - ## Final Answer - Return the schemas in the final_answer tool, along with the reasoning for your design decisions, so that your - manager can understand your thought process, by passing everything to the final_answer tool. Everything that you - do not pass as an argument to final_answer will be lost. And even if your task resolution is not successful, - please return as much context as possible, so that your manager can act upon this feedback. \ No newline at end of file diff --git a/plexe/tools/code_analysis.py b/plexe/tools/code_analysis.py deleted file mode 100644 index 122eaad4..00000000 --- a/plexe/tools/code_analysis.py +++ /dev/null @@ -1,55 +0,0 @@ -""" -Tools for analyzing and inspecting code. -""" - -import logging -from typing import Optional -from smolagents import tool - -from plexe.core.object_registry import ObjectRegistry -from plexe.internal.models.entities.code import Code - -logger = logging.getLogger(__name__) - - -@tool -def read_training_code(training_code_id: str) -> str: - """ - Retrieves the training code from the registry for analysis. Use this tool to understand the - code that was used to train the ML model. - - Args: - training_code_id: The identifier for the training code to retrieve - - Returns: - The full training code as a string - """ - try: - return ObjectRegistry().get(Code, training_code_id).code - except Exception as e: - raise ValueError(f"Failed to retrieve training code with ID {training_code_id}: {str(e)}") - - -@tool -def get_feature_transformer_code() -> Optional[str]: - """ - Get the feature transformation code that was used to transform the raw input dataset into the - feature-engineered dataset used for building the model. - - Returns: - Code for feature transformations if available, otherwise None. - """ - object_registry = ObjectRegistry() - - try: - # Feature transformer code is stored with fixed ID "feature_transformations" - code = object_registry.get(Code, "feature_transformations") - if code: - return code.code - return None - except KeyError: - logger.debug("Feature transformation code not found in registry") - return None - except Exception as e: - logger.warning(f"⚠️ Error getting feature transformer code: {str(e)}") - return None diff --git a/plexe/tools/context.py b/plexe/tools/context.py deleted file mode 100644 index 6f68901a..00000000 --- a/plexe/tools/context.py +++ /dev/null @@ -1,112 +0,0 @@ -""" -Tools for providing context to agents for code generation tasks. -""" - -import json -import logging -from typing import Dict, Any, List, Callable - -from pydantic import BaseModel -from smolagents import tool - -from plexe.config import code_templates -from plexe.core.entities.solution import Solution -from plexe.internal.common.provider import Provider -from plexe.core.object_registry import ObjectRegistry -from plexe.tools.datasets import create_input_sample -from plexe.tools.schemas import get_solution_schemas - -logger = logging.getLogger(__name__) - - -def get_inference_context_tool(llm_to_use: str) -> Callable: - """Returns a tool function to get inference context with the model ID pre-filled.""" - - @tool - def get_inference_context() -> Dict[str, Any]: - """ - Provides comprehensive context needed for generating inference code. Use this tool to retrieve - a summary of the training code, schemas, expected inputs for the purpose of planning the inference - code. - - Returns: - A dictionary containing all context needed for inference code generation - """ - object_registry = ObjectRegistry() - - # Retrieve the best performing solution - try: - best_solution = object_registry.get(Solution, "best_performing_solution") - except Exception as e: - raise ValueError(f"Best performing solution not found, has it been selected?: {str(e)}") - - # Retrieve the training code - try: - training_code = best_solution.training_code - except Exception as e: - raise ValueError( - f"Solution '{best_solution.id}' doesn't have training code, has it been trained?: {str(e)}" - ) - - # Retrieve schemas - try: - schemas = get_solution_schemas("best_performing_solution") - input_schema = schemas["input"] - output_schema = schemas["output"] - except Exception as e: - raise ValueError(f"Failed to retrieve schemas from registry: {str(e)}") - - # Retrieve input sample - try: - # Create input sample now that we know schema exists - create_input_sample() # TODO: this tool -> tool dependency will lead to difficult to debug errors - input_sample = object_registry.get(list, "predictor_input_sample") - except Exception as e: - raise ValueError(f"Failed to retrieve input sample: {str(e)}") - - # Extract artifacts - try: - artifact_names = _extract_artifacts(llm_to_use, training_code) - object_registry.register(list, "model_artifact_names", artifact_names, overwrite=True, immutable=True) - except Exception as e: - raise ValueError(f"Failed to extract artifacts from training code: {str(e)}") - - return { - "training_code": training_code, - "input_schema": input_schema, - "output_schema": output_schema, - "predictor_interface": code_templates.predictor_interface, - "predictor_template": code_templates.predictor_template, - "input_sample": input_sample, - "artifact_names": artifact_names, - } - - return get_inference_context - - -def _extract_artifacts(llm_to_use: str, code: str) -> List[str]: - """Extract model artifact names from training code using LLM""" - - class ArtifactResponse(BaseModel): - artifact_names: List[str] - - try: - provider = Provider(llm_to_use) - - names = json.loads( - provider.query( - "You are a code analysis assistant.", - ( - "Extract the names of all saved ML model artifacts from the following code. " - "The artifacts are usually saved using a function like torch.save, joblib.dump, or pickle.dump. " - "Any model artifact that is saved by the training script must be included in the output so that " - "it can be used in the inference code. DO NOT modify the artifact names from the script.\n\n" - "Here is the training code:\n" - f"```python\n{code}\n```" - ), - ArtifactResponse, - ) - )["artifact_names"] - return names - except Exception as e: - raise RuntimeError(f"Artifact extraction failed: {e}") from e diff --git a/plexe/tools/datasets.py b/plexe/tools/datasets.py index dc8ed3e5..101951f4 100644 --- a/plexe/tools/datasets.py +++ b/plexe/tools/datasets.py @@ -3,8 +3,7 @@ These tools help with dataset operations within the model generation pipeline, including splitting datasets into training, validation, and test sets, registering datasets with -the dataset registry, creating sample data for validation, previewing dataset content, -registering exploratory data analysis (EDA) reports, and registering feature engineering results. +the dataset registry, creating sample data for validation, and previewing dataset content. """ import logging @@ -602,113 +601,6 @@ def get_dataset_preview(dataset_name: str) -> Dict[str, Any]: } -@tool -def register_eda_report( - dataset_name: str, - overview: Dict[str, Any], - feature_engineering_opportunities: Dict[str, Any], - data_quality_challenges: Dict[str, Any], - data_preprocessing_requirements: Dict[str, Any], - feature_importance: Dict[str, Any], - insights: List[str], - recommendations: List[str], -) -> str: - """ - Register an exploratory data analysis (EDA) report for a dataset in the Object Registry. - - This tool creates a structured report with actionable ML engineering insights from exploratory - data analysis and registers it in the Object Registry for use by other agents. - - Args: - dataset_name: Name of the dataset that was analyzed - overview: Essential dataset statistics including target variable analysis - feature_engineering_opportunities: Specific transformation needs, interaction effects, - and engineered features that would improve model performance - data_quality_challenges: Critical data issues with specific handling recommendations - data_preprocessing_requirements: Necessary preprocessing steps with clear justification - feature_importance: Assessment of feature predictive potential and relevance - insights: Key insights derived from the analysis that directly impact feature engineering - recommendations: Specific, prioritized actions for preprocessing and feature engineering - - Returns: - A string indicating success or failure of the registration - """ - object_registry = ObjectRegistry() - - try: - # Create structured EDA report with actionable ML focus - eda_report = { - "dataset_name": dataset_name, - "timestamp": datetime.now().isoformat(), - "overview": overview, - "feature_engineering_opportunities": feature_engineering_opportunities, - "data_quality_challenges": data_quality_challenges, - "data_preprocessing_requirements": data_preprocessing_requirements, - "feature_importance": feature_importance, - "insights": insights, - "recommendations": recommendations, - } - - # TODO: separate EDA reports for raw and transformed data - # Register in registry - object_registry.register(dict, f"eda_report_{dataset_name}", eda_report, overwrite=True) - logger.debug(f"✅ Registered EDA report for dataset '{dataset_name}'") - return f"Successfully registered EDA report for dataset '{dataset_name}'" - - except Exception as e: - logger.warning(f"⚠️ Error registering EDA report: {str(e)}") - raise RuntimeError(f"Failed to register EDA report for dataset '{dataset_name}': {str(e)}") - - -@tool -def register_feature_engineering_report( - dataset_name: str, - overview: Dict[str, Any], - feature_catalog: Dict[str, Any], - feature_importance: Dict[str, Any], - insights: List[str], - recommendations: List[str], -) -> str: - """ - Register a feature engineering report for a transformed dataset. This tool registers a structured report with - actionable insights from feature engineering for use by other agents. The purpose is to ensure that the features - created during feature engineering are well-documented. - - Args: - dataset_name: Name of the dataset that was analyzed - overview: Essential dataset statistics including target variable analysis - feature_catalog: Catalog of engineered features with descriptions and transformations - feature_importance: Assessment of feature predictive potential and relevance - insights: Key insights derived from the analysis that directly impact feature engineering - recommendations: Specific, prioritized actions for preprocessing and feature engineering - - Returns: - A string indicating success or failure of the registration - """ - object_registry = ObjectRegistry() - - try: - # Create structured feature engineering report - fe_report = { - "dataset_name": dataset_name, - "timestamp": datetime.now().isoformat(), - "overview": overview, - "feature_catalog": feature_catalog, - "feature_importance": feature_importance, - "insights": insights, - "recommendations": recommendations, - } - - # Register in registry - object_registry.register(dict, f"fe_report_{dataset_name}", fe_report, overwrite=True) - logger.debug(f"✅ Registered Feature Engineering report for dataset '{dataset_name}'") - return f"Successfully registered Feature Engineering report for dataset '{dataset_name}'" - - except Exception as e: - logger.warning(f"⚠️ Error registering Feature Engineering report: {str(e)}") - raise RuntimeError(f"Failed to register Feature Engineering report for dataset '{dataset_name}': {str(e)}") - - @tool def get_latest_datasets() -> Dict[str, Any]: """ @@ -792,62 +684,6 @@ def get_latest_datasets() -> Dict[str, Any]: return {} -@tool -def get_dataset_for_splitting() -> str: - """ - Get the most appropriate dataset for splitting. Returns transformed version if available, - otherwise raw. Use this tool to get the dataset that needs to be split. - - Returns: - Name of the dataset to split - - Raises: - ValueError: If no suitable dataset is found for splitting - """ - object_registry = ObjectRegistry() - - try: - all_datasets = object_registry.list_by_type(TabularConvertible) - - # First, check if splits already exist - has_splits = any(d.endswith(("_train", "_val", "_test")) for d in all_datasets) - - # Prefer transformed datasets that haven't been split yet - transformed_unsplit = [ - d - for d in all_datasets - if d.endswith("_transformed") - and not any(f"{d}_{split}" in all_datasets for split in ["train", "val", "test"]) - ] - if transformed_unsplit: - # Return the most recent (last) one - return transformed_unsplit[-1] - - # If no unsplit transformed datasets, check for raw datasets that haven't been split - raw_unsplit = [ - d - for d in all_datasets - if not any(suffix in d for suffix in ["_train", "_val", "_test", "_transformed"]) - and not any(f"{d}_{split}" in all_datasets for split in ["train", "val", "test"]) - ] - - if raw_unsplit: - return raw_unsplit[-1] - - # If everything has been split, raise an informative error - if has_splits: - raise ValueError("All datasets have already been split. No unsplit datasets available.") - else: - raise ValueError("No datasets available for splitting. Ensure datasets have been registered.") - - except ValueError: - # Re-raise ValueError as is - raise - except Exception as e: - logger.warning(f"⚠️ Error finding dataset for splitting: {str(e)}") - raise ValueError(f"Failed to find dataset for splitting: {str(e)}") - - @tool def get_training_datasets() -> Dict[str, str]: """ diff --git a/plexe/tools/response_formatting.py b/plexe/tools/response_formatting.py index 8d445a4c..a6d4c817 100644 --- a/plexe/tools/response_formatting.py +++ b/plexe/tools/response_formatting.py @@ -2,7 +2,7 @@ This module provides tools for forcing an agent to return its response in a specific format. """ -from typing import Dict, List, Optional +from typing import Dict from smolagents import tool @@ -50,50 +50,3 @@ def format_final_orchestrator_agent_response( }, "metadata": model_review_output, } - - -@tool -def format_final_mle_agent_response( - solution_id: str, - execution_success: bool, - performance_value: Optional[float] = None, - exception: Optional[str] = None, - model_artifact_names: Optional[List[str]] = None, -) -> dict: - """ - Returns a dictionary containing the exact fields that the agent must return in its final response. The fields - 'performance_value', 'exception', and 'model_artifact_names' are optional. They MUST be included if they are - available, but can be omitted if they are not available. - - Args: - solution_id: The solution ID returned by the code execution tool after executing the training code - execution_success: Boolean indicating if the training code executed successfully - performance_value: The value of the performance attained by the selected ML model, if any - exception: Exception message if the code execution failed, if any - model_artifact_names: A list with the names of all the model artifacts created by the model training script - - Returns: - Dictionary containing the fields that must be returned by the agent in its final response - """ - - return { - "solution_id": solution_id, - "execution_success": execution_success, - "performance_value": performance_value, - "exception": exception, - "model_artifact_names": model_artifact_names, - } - - -@tool -def format_final_mlops_agent_response(inference_code_id: str) -> dict: - """ - Returns a dictionary containing the exact fields that the agent must return in its final response. - - Args: - inference_code_id: The inference code id returned by the code validation tool after validating the inference code - - Returns: - Dictionary containing the fields that must be returned by the agent in its final response - """ - return {"python_inference_code": inference_code_id} diff --git a/plexe/tools/testing.py b/plexe/tools/testing.py deleted file mode 100644 index a43bbef4..00000000 --- a/plexe/tools/testing.py +++ /dev/null @@ -1,102 +0,0 @@ -""" -Tools for model testing and evaluation. - -These tools help with model evaluation operations within the model generation pipeline, -including registering testing code and evaluation reports. -""" - -import logging -from typing import Dict, List - -from smolagents import tool - -from plexe.core.object_registry import ObjectRegistry - -logger = logging.getLogger(__name__) - - -@tool -def register_testing_code(solution_id: str, testing_code: str) -> str: - """ - Register the testing/evaluation code in the object registry and update the Solution object. The testing code - must first have been executed successfully before registration. - - Args: - solution_id: ID of the Solution object to update - testing_code: Python code used for model testing and evaluation - - Returns: - Success message confirming registration - """ - object_registry = ObjectRegistry() - - try: - # Update the Solution object with testing code - from plexe.core.entities.solution import Solution - - solution = object_registry.get(Solution, solution_id) - - solution.testing_code = testing_code - - object_registry.register(Solution, solution_id, solution, overwrite=True) - - logger.debug(f"✅ Registered model testing code for solution '{solution_id}'") - return f"Successfully registered model testing code for solution '{solution_id}'" - - except Exception as e: - logger.warning(f"⚠️ Error registering testing code: {str(e)}") - raise RuntimeError(f"Failed to register testing code: {str(e)}") - - -@tool -def register_evaluation_report( - solution_id: str, - model_performance_summary: Dict, - detailed_metrics: Dict, - quality_analysis: Dict, - recommendations: List[str], - testing_insights: List[str], -) -> str: - """ - Register comprehensive evaluation report in the object registry and link to Solution. - - This tool creates a structured report with model evaluation results and registers - it in the Object Registry for use by other agents or final model output. - - Args: - solution_id: ID of the Solution object to link the evaluation report to - model_performance_summary: Overall performance metrics and scores - detailed_metrics: Comprehensive metrics breakdown by class/category - quality_analysis: Error patterns, robustness, interpretability insights - recommendations: Specific recommendations for deployment/improvement - testing_insights: Key insights from testing that impact model usage - - Returns: - Success message confirming registration - """ - from plexe.core.entities.solution import Solution - - object_registry = ObjectRegistry() - - try: - # Create structured evaluation report - evaluation_report = { - "solution_id": solution_id, - "model_performance_summary": model_performance_summary, - "detailed_metrics": detailed_metrics, - "quality_analysis": quality_analysis, - "recommendations": recommendations, - "testing_insights": testing_insights, - } - - # Update Solution object with summary analysis - solution = object_registry.get(Solution, solution_id) - solution.model_evaluation_report = evaluation_report - object_registry.register(Solution, solution_id, solution, overwrite=True) - - logger.debug(f"✅ Registered model evaluation report for solution '{solution_id}'") - return f"Successfully registered model evaluation report for solution '{solution_id}'" - - except Exception as e: - logger.warning(f"⚠️ Error registering evaluation report: {str(e)}") - raise RuntimeError(f"Failed to register evaluation report: {str(e)}") diff --git a/plexe/tools/training.py b/plexe/tools/training.py index 32cb16e4..86d5b84c 100644 --- a/plexe/tools/training.py +++ b/plexe/tools/training.py @@ -4,13 +4,10 @@ """ import logging -from typing import List, Callable from smolagents import tool from plexe.core.object_registry import ObjectRegistry -from plexe.internal.common.provider import Provider -from plexe.internal.models.generation.training import TrainingCodeGenerator logger = logging.getLogger(__name__) @@ -44,61 +41,3 @@ def register_best_solution(best_solution_id: str) -> str: except Exception as e: logger.warning(f"⚠️ Error registering best solution: {str(e)}") raise RuntimeError(f"Failed to register best solution: {str(e)}") - - -def get_training_code_generation_tool(llm_to_use: str) -> Callable: - """Returns a tool function to generate training code with the model ID pre-filled.""" - - @tool - def generate_training_code( - task: str, solution_plan: str, train_datasets: List[str], validation_datasets: List[str] - ) -> str: - """Generates training code based on the solution plan. - - Args: - task: The task definition - solution_plan: The solution plan to implement - train_datasets: Keys of datasets to use for training - validation_datasets: Keys of datasets to use for validation - - Returns: - Generated training code as a string - """ - train_generator = TrainingCodeGenerator(Provider(llm_to_use)) - return train_generator.generate_training_code(task, solution_plan, train_datasets, validation_datasets) - - return generate_training_code - - -def get_training_code_fixing_tool(llm_to_use: str) -> Callable: - """Returns a tool function to fix training code with the model ID pre-filled.""" - - @tool - def fix_training_code( - training_code: str, - solution_plan: str, - review: str, - train_datasets: List[str], - validation_datasets: List[str], - issue: str, - ) -> str: - """ - Fixes issues in the training code based on a review. - - Args: - training_code: The training code to fix - solution_plan: The solution plan being implemented - review: Review comments about the code and its issues, ideally a summary analysis of the issue - train_datasets: Keys of datasets to use for training - validation_datasets: Keys of datasets to use for validation - issue: Description of the issue to address - - Returns: - Fixed training code as a string - """ - train_generator = TrainingCodeGenerator(Provider(llm_to_use)) - return train_generator.fix_training_code( - training_code, solution_plan, review, train_datasets, validation_datasets, issue - ) - - return fix_training_code diff --git a/plexe/tools/validation.py b/plexe/tools/validation.py deleted file mode 100644 index 14669e7f..00000000 --- a/plexe/tools/validation.py +++ /dev/null @@ -1,237 +0,0 @@ -""" -Tools related to code validation, including syntax and security checks. -""" - -import logging -import ast -from typing import Dict - -from smolagents import tool - -from plexe.config import code_templates -from plexe.internal.models.entities.code import Code -from plexe.internal.models.validation.composites import ( - InferenceCodeValidator, - TrainingCodeValidator, -) -from plexe.tools.schemas import get_solution_schemas - -logger = logging.getLogger(__name__) - - -@tool -def validate_training_code(training_code: str) -> Dict: - """Validates training code for syntax and security issues. - - Args: - training_code: The training code to validate - - Returns: - A dictionary containing validation results - """ - if not training_code or not isinstance(training_code, str): - return _error_response("validation", "InvalidCode", "Training code is invalid or missing.") - - validator = TrainingCodeValidator() - validation = validator.validate(training_code) - - if validation.passed: - return _success_response(validation.message) - else: - error_type = type(validation.exception).__name__ if validation.exception else "UnknownError" - error_details = str(validation.exception) if validation.exception else "Unknown error" - return _error_response("validation", error_type, error_details, validation.message) - - -@tool -def validate_inference_code( - solution_id: str, - inference_code: str, -) -> Dict: - """ - Validates inference code for syntax, security, and correctness, and updates the Solution object. - - Args: - solution_id: ID of the Solution object to update with inference code - inference_code: The inference code to validate - - Returns: - Dict with validation results and error details if validation fails - """ - from plexe.internal.common.utils.pydantic_utils import map_to_basemodel - from plexe.core.object_registry import ObjectRegistry - from plexe.core.entities.solution import Solution - - object_registry = ObjectRegistry() - - # Get solution object from registry - try: - solution = object_registry.get(Solution, solution_id) - except Exception as e: - return _error_response("solution_retrieval", type(e).__name__, str(e)) - - # Get schemas from registry - try: - schemas = get_solution_schemas("best_performing_solution") - if "input" not in schemas: - return _error_response( - "schema_preparation", - "MissingSchema", - "Input schema not found for solution 'best_performing_solution'. Ensure schemas are registered.", - ) - if "output" not in schemas: - return _error_response( - "schema_preparation", - "MissingSchema", - "Output schema not found for solution 'best_performing_solution'. Ensure schemas are registered.", - ) - input_schema = schemas["input"] - output_schema = schemas["output"] - except Exception as e: - return _error_response("schema_preparation", type(e).__name__, str(e)) - - # Convert schemas to pydantic models - try: - input_model = map_to_basemodel("InputSchema", input_schema) - output_model = map_to_basemodel("OutputSchema", output_schema) - except Exception as e: - return _error_response("schema_preparation", type(e).__name__, str(e)) - - # Get input samples - try: - input_samples = object_registry.get(list, "predictor_input_sample") - if not input_samples: - return _error_response("input_sample", "MissingData", "Input sample list is empty") - except Exception as e: - return _error_response("input_sample", type(e).__name__, str(e)) - - # Validate the code - validator = InferenceCodeValidator(input_schema=input_model, output_schema=output_model, input_sample=input_samples) - validation = validator.validate(inference_code, model_artifacts=solution.model_artifacts) - - # Return appropriate result - if validation.passed: - # Update the Solution object with inference code, and register an alias for production use - solution.inference_code = inference_code - object_registry.register(Solution, solution_id, solution, overwrite=True) - object_registry.register(Solution, "final_inference_solution", solution, overwrite=True, immutable=True) - - # Also instantiate and register the predictor for the model tester agent - try: - if inference_code and isinstance(inference_code, str): - import types - - predictor_module = types.ModuleType("predictor") - exec(inference_code, predictor_module.__dict__) - predictor_class = getattr(predictor_module, "PredictorImplementation") - predictor = predictor_class(solution.model_artifacts) - - # Register the instantiated predictor - from plexe.core.interfaces.predictor import Predictor - - object_registry.register(Predictor, "trained_predictor", predictor, overwrite=True) - else: - logger.warning("Skipping predictor instantiation in validation: inference_code is invalid.") - logger.debug("✅ Registered instantiated predictor for testing") - - except Exception as e: - logger.warning(f"⚠️ Failed to register instantiated predictor: {str(e)}") - # Don't fail validation if predictor registration fails - - return _success_response(validation.message, solution_id) - - # Extract error details from validation result - error_type = validation.error_type or ( - type(validation.exception).__name__ if validation.exception else "UnknownError" - ) - error_details = validation.error_details or (str(validation.exception) if validation.exception else "Unknown error") - - return _error_response(validation.error_stage or "unknown", error_type, error_details, validation.message) - - -def _error_response(stage, exc_type, details, message=None): - """Helper to create error response dictionaries""" - return { - "passed": False, - "error_stage": stage, - "error_type": exc_type, - "error_details": details, - "message": message or details, - } - - -def _success_response(message, solution_id=None): - """Helper to create success response dictionaries""" - response = {"passed": True, "message": message} - # Only include solution_id for inference code validation - if solution_id is not None: - response["solution_id"] = solution_id - return response - - -@tool -def validate_feature_transformations(transformation_code: str) -> Dict: - """ - Validates feature transformation code for syntax correctness and implementation - of the FeatureTransformer interface. - - Args: - transformation_code: Python code for transforming datasets - - Returns: - Dictionary with validation results - """ - import types - import warnings - from plexe.core.object_registry import ObjectRegistry - from plexe.core.interfaces.feature_transformer import FeatureTransformer - - # Check for syntax errors - try: - ast.parse(transformation_code) - except SyntaxError as e: - return _error_response("syntax", "SyntaxError", str(e)) - - # Load the code as a module to check for proper FeatureTransformer implementation - try: - with warnings.catch_warnings(): - warnings.simplefilter("ignore") - module = types.ModuleType("test_feature_transformer") - if transformation_code and isinstance(transformation_code, str): - exec(transformation_code, module.__dict__) - else: - return _error_response("validation", "InvalidCode", "Transformation code is invalid or missing.") - - # Check if the module contains the FeatureTransformerImplementation class - if not hasattr(module, "FeatureTransformerImplementation"): - return _error_response( - "class_definition", - "MissingClass", - "Code must define a class named 'FeatureTransformerImplementation'", - ) - - # Check if the class is a subclass of FeatureTransformer - transformer_class = getattr(module, "FeatureTransformerImplementation") - if not issubclass(transformer_class, FeatureTransformer): - return _error_response( - "class_definition", - "InvalidClass", - "FeatureTransformerImplementation must be a subclass of FeatureTransformer", - ) - except Exception as e: - return _error_response( - "validation", - type(e).__name__, - str(e), - message=f"The feature transformer must be a subclass of the following interface:\n\n" - f"```python\n" - f"{code_templates.feature_transformer_interface}" - f"```", - ) - - # Register the transformation code with a fixed ID - object_registry = ObjectRegistry() - code_id = "feature_transformations" - object_registry.register(Code, code_id, Code(transformation_code), overwrite=True) - - return {"passed": True, "message": "Feature transformation code validated successfully", "code_id": code_id} From 1e6632021e28b0a84dc8731cd5aebbecca7d12df Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Fri, 23 Jan 2026 00:01:21 +0700 Subject: [PATCH 40/42] :bug:bug: can not execute code with langgraph --- CLAUDE.md | 37 - Dockerfile.gpu | 21 +- .../langgraph-multi-agent-system.md | 429 ++++ docs/docker-build-issues.md | 246 --- docs/docker-performance.md | 188 -- docs/docker.md | 284 --- docs/postgres.md | 67 - plexe/__init__.py | 23 +- plexe/agents/__init__.py | 11 - plexe/agents/agents.py | 316 --- plexe/agents/conversational.py | 102 - plexe/agents/dataset_builder.py | 116 - plexe/agents/relational_gnn_specialist.py | 117 -- plexe/agents/relational_graph_architect.py | 122 -- plexe/agents/task_builder.py | 148 -- plexe/callbacks.py | 130 -- plexe/config.py | 346 --- plexe/core/__init__.py | 7 - plexe/core/entities/__init__.py | 0 plexe/core/entities/solution.py | 72 - plexe/core/interfaces/__init__.py | 0 plexe/core/interfaces/feature_transformer.py | 20 - plexe/core/interfaces/predictor.py | 24 - plexe/core/object_registry.py | 197 -- plexe/core/state.py | 23 - plexe/core/storage.py | 588 ------ plexe/datasets.py | 191 -- plexe/execution_context.py | 18 - plexe/fileio.py | 277 --- plexe/internal/__init__.py | 0 plexe/internal/common/__init__.py | 0 plexe/internal/common/datasets/__init__.py | 0 plexe/internal/common/datasets/adapter.py | 95 - plexe/internal/common/datasets/interface.py | 201 -- plexe/internal/common/datasets/tabular.py | 219 -- plexe/internal/common/provider.py | 175 -- plexe/internal/common/utils/__init__.py | 3 - plexe/internal/common/utils/agents.py | 46 - .../common/utils/chain_of_thought/__init__.py | 29 - .../common/utils/chain_of_thought/adapters.py | 66 - .../common/utils/chain_of_thought/callable.py | 209 -- .../common/utils/chain_of_thought/emitters.py | 207 -- .../common/utils/chain_of_thought/protocol.py | 54 - .../chain_of_thought/websocket_emitter.py | 204 -- .../internal/common/utils/dataset_storage.py | 104 - .../internal/common/utils/dependency_utils.py | 50 - plexe/internal/common/utils/markdown_utils.py | 116 - plexe/internal/common/utils/model_state.py | 23 - plexe/internal/common/utils/model_utils.py | 41 - plexe/internal/common/utils/pandas_utils.py | 37 - plexe/internal/common/utils/prompt_utils.py | 27 - plexe/internal/common/utils/pydantic_utils.py | 158 -- plexe/internal/common/utils/response.py | 204 -- plexe/internal/datasets/__init__.py | 9 - plexe/internal/datasets/config.py | 39 - plexe/internal/datasets/core/__init__.py | 0 .../datasets/core/generation/__init__.py | 0 .../internal/datasets/core/generation/base.py | 44 - .../datasets/core/generation/simple_llm.py | 271 --- .../core/generation/utils/__init__.py | 0 .../datasets/core/validation/__init__.py | 0 .../internal/datasets/core/validation/base.py | 22 - .../internal/datasets/core/validation/eda.py | 57 - plexe/internal/datasets/generator.py | 41 - .../templates/eda-notebook-tabular.ipynb | 455 ---- plexe/internal/models/__init__.py | 0 plexe/internal/models/callbacks/__init__.py | 0 .../models/callbacks/chain_of_thought.py | 82 - plexe/internal/models/callbacks/checkpoint.py | 129 -- plexe/internal/models/callbacks/mlflow.py | 419 ---- plexe/internal/models/entities/__init__.py | 0 plexe/internal/models/entities/artifact.py | 77 - plexe/internal/models/entities/code.py | 13 - plexe/internal/models/entities/description.py | 188 -- plexe/internal/models/entities/metric.py | 214 -- plexe/internal/models/execution/__init__.py | 0 .../models/execution/docker_executor.py | 22 - plexe/internal/models/execution/executor.py | 63 - .../models/execution/process_executor.py | 202 -- .../internal/models/execution/ray_executor.py | 182 -- plexe/internal/models/feature_handling.py | 58 - plexe/internal/models/generation/__init__.py | 0 plexe/internal/models/generation/planning.py | 62 - plexe/internal/models/generation/review.py | 134 -- plexe/internal/models/validation/__init__.py | 0 plexe/internal/models/validation/composite.py | 43 - .../models/validation/composites/__init__.py | 2 - .../models/validation/composites/inference.py | 42 - .../models/validation/composites/training.py | 23 - .../models/validation/primitives/__init__.py | 0 .../models/validation/primitives/predict.py | 142 -- .../models/validation/primitives/security.py | 35 - .../models/validation/primitives/syntax.py | 46 - plexe/internal/models/validation/validator.py | 64 - plexe/internal/schemas/__init__.py | 0 plexe/internal/schemas/resolver.py | 139 -- plexe/langgraph/__init__.py | 30 + plexe/langgraph/agents/__init__.py | 23 + plexe/langgraph/agents/base.py | 161 ++ plexe/langgraph/agents/conversational.py | 143 ++ plexe/langgraph/agents/dataset_builder.py | 295 +++ plexe/langgraph/agents/eda.py | 221 ++ plexe/langgraph/agents/gnn_specialist.py | 193 ++ plexe/langgraph/agents/operation.py | 265 +++ plexe/langgraph/agents/task_builder.py | 291 +++ plexe/langgraph/config.py | 96 + plexe/langgraph/orchestrator.py | 391 ++++ plexe/langgraph/state.py | 169 ++ plexe/langgraph/tools/__init__.py | 59 + plexe/langgraph/tools/common.py | 37 + plexe/langgraph/tools/conversational.py | 60 + plexe/langgraph/tools/dataset_builder.py | 135 ++ plexe/langgraph/tools/eda.py | 442 ++++ plexe/langgraph/tools/gnn_specialist.py | 314 +++ plexe/langgraph/tools/graph_architect.py | 181 ++ plexe/langgraph/tools/task_builder.py | 83 + plexe/langgraph/utils.py | 145 ++ plexe/model_builder.py | 334 --- plexe/models.py | 336 --- plexe/server.py | 252 +-- plexe/templates/__init__.py | 1 + .../models/feature_transformer.tmpl.py | 36 +- plexe/templates/models/predictor.tmpl.py | 82 +- .../prompts/agent/agent_manager_prompt.jinja | 156 -- .../conversational_prompt_templates.yaml | 167 -- .../dataset_builder_prompt_templates.yaml | 243 --- ...ional_gnn_specialist_prompt_templates.yaml | 241 --- ...onal_graph_architect_prompt_templates.yaml | 246 --- .../agent/task_builder_prompt_templates.yaml | 457 ---- .../prompts/planning/select_metric.jinja | 7 - .../prompts/planning/system_prompt.jinja | 7 - plexe/templates/prompts/review/model.jinja | 49 - .../prompts/review/system_prompt.jinja | 4 - 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ML models using natural language. It employs a multi-agent architecture where -specialized AI agents collaborate to analyze requirements, generate solutions, and build functional ML models. - -The core architecture is as follows: agents go in `plexe/agents/*`, tools in `plexe/tools/*`, prompt templates in -`plexe/templates/prompts/*`, and the main model code in `plexe/models.py`. This structure must be followed. - -## Key Components -- `plexe/models.py`: Core `Model` class with build/predict functionality -- `plexe/agents/schema_resolver.py`: Agent inferring input/output schemas -- `plexe/internal/agents.py`: Multi-agent system implementation (`PlexeAgent` class) -- `plexe/tools/`: Tools for code generation, execution, validation -- `plexe/config.py`: Configuration management and prompt templates -- `plexe/internal/common/registries/objects.py`: Shared object registry for agents -- `plexe/datasets.py`: Dataset handling and synthetic data generation -- `docs/architecture/multi-agent-system.md`: Architectural documentation -- `plexe/templates/prompts/`: Prompt templates for agents and LLM calls - -## Build/Run Commands -- Install deps: `poetry install` -- Format code: `poetry run black .` -- Lint code: `poetry run ruff check . --fix` -- Run tests: `poetry run pytest tests/` -- Run with coverage: `poetry run pytest --cov=plexe tests/` - -## Code Style -- **Functions**: Max 50 lines (excluding docstrings) -- **Formatting**: Black with 120 char line length -- **Linting**: Ruff with E203/E501/E402 ignored -- **Typing**: Type hints and Pydantic models required -- **Imports**: ALWAYS at top level in order: stdlib, third-party, local; NEVER inside functions -- **__init__.py**: No implementation code except in `plexe/__init__.py` -- **Docstrings**: Required for public APIs; Sphinx style -- **Testing**: Write pytest tests for all new functionality -- **Elegance**: Write the simplest solution possible; avoid over-engineering; prefer deleting code over adding code diff --git a/Dockerfile.gpu b/Dockerfile.gpu index 756ca6eb..e062e156 100644 --- a/Dockerfile.gpu +++ b/Dockerfile.gpu @@ -44,7 +44,7 @@ RUN uv pip install \ litellm statsmodels hypothesis "numpy<2.0.0" black jinja2 platformdirs \ "ray>=2.9.0" rich smolagents deprecated python-multipart psycopg2-binary \ featuretools sqlalchemy pytorch-frame pooch duckdb scipy \ - fastapi "uvicorn[standard]" websockets + fastapi "uvicorn[standard]" websockets langgraph langchain langchain-openai langchain-google-genai angchain-anthropic # ---------------------------- # BƯỚC 3: Cài torchvision, torchaudio (torch đã có sẵn từ base image) @@ -83,19 +83,18 @@ COPY . . # ---------------------------- RUN python - < dict: + """Description of what the tool does.""" + return {"result": "value"} + +# Add to agent +agent = DatasetBuilderAgent(additional_tools=[my_custom_tool]) +``` + +### Custom Agents + +```python +from plexe.langgraph.agents.base import BaseAgent + +class MyCustomAgent(BaseAgent): + def __init__(self, config=None): + super().__init__( + agent_type="custom", + config=config, + tools=[...], + ) + + @property + def system_prompt(self) -> str: + return "Your custom system prompt..." +``` + +## Performance Considerations + +- **Model Selection**: Use faster models (gpt-4o-mini) for simpler agents +- **Batch Size**: Adjust based on GPU memory (default: 512) +- **Epochs**: Start with 10 epochs, increase if needed +- **Caching**: Graph construction is cached for repeated runs + +## Troubleshooting + +### Common Issues + +1. **Database Connection Failed** + - Verify connection string format + - Check network access to database + - Ensure credentials are correct + +2. **Training OOM Error** + - Reduce batch_size + - Reduce num_neighbors + - Use CPU if GPU memory insufficient + +3. **SQL Query Errors** + - Verify column names (snake_case in PostgreSQL) + - Test queries with test_sql_query tool + - Check temporal window logic + +4. **Missing Dependencies** + - Run `poetry install` to install all dependencies + - Ensure LangGraph packages are installed diff --git a/docs/docker-build-issues.md b/docs/docker-build-issues.md deleted file mode 100644 index 5ea2b654..00000000 --- a/docs/docker-build-issues.md +++ /dev/null @@ -1,246 +0,0 @@ -# Docker Build Issues & Solutions - -## 🔴 Vấn Đề: Network Timeout Khi Download `torch` - -### Nguyên Nhân -- `torch` là package rất lớn (~2GB khi install) -- Docker build mất quá lâu để download -- Network timeout xảy ra - -### ✅ Giải Pháp (Đã Implement) - -#### 1. **Enhanced Dockerfile** (`Dockerfile`) - -Các cải tiến: -```dockerfile -# Set timeout lớn hơn -ENV PIP_DEFAULT_TIMEOUT=100 -PIP_RETRIES=5 - -# Multi-stage build (better caching) -FROM python:3.11-slim as base -FROM base as deps # Dependencies cached separately -FROM deps as app # Application code cached separately - -# Retry logic nếu download fail -RUN poetry install ... 2>&1 || \ - (sleep 5 && poetry install ...) || \ - (sleep 10 && poetry install ...) -``` - -**Lợi ích:** -- Timeout 100s (default 15s) -- Auto-retry 3 lần với delay -- Better layer caching (deps không rebuild nếu code thay đổi) -- Health check endpoint - -#### 2. **Lightweight Dev Dockerfile** (`Dockerfile.dev`) - -Cho development nhanh hơn: -```dockerfile -# Only installs main dependencies (excludes torch) -# Build 10x nhanh hơn! -``` - -**Lợi ích:** -- `torch` và `transformers` không cần khi dev -- Thích hợp cho local testing -- Fast iterate cycles - -#### 3. **Docker Compose Dev** (`docker-compose.dev.yml`) - -```bash -# Production (với torch) -docker compose build backend - -# Development (nhanh, không torch) -docker compose -f docker-compose.dev.yml build backend -``` - ---- - -## 🚀 Cách Sử Dụng - -### Option 1: Build Production (Lâu, Nhưng Full Featured) - -```bash -cd /home/admin1/plexe-clone - -# Build backend (mất 5-10 phút lần đầu, có torch) -docker compose build backend - -# Start all services -docker compose up -d - -# Wait 30-60s for startup, then check -curl http://localhost:8000/health -``` - -**Khi nào**: Deploy, testing full features, final release - -### Option 2: Build Development (Nhanh, Cho Rapid Dev) - -```bash -cd /home/admin1/plexe-clone - -# Build dev version (mất 2-3 phút, không torch) -docker compose -f docker-compose.dev.yml build backend - -# Start services -docker compose -f docker-compose.dev.yml up -d - -# Fast startup: 10-15s -curl http://localhost:8000/health -``` - -**Khi nào**: Local development, testing features, quick iteration - -### Option 3: Pure Local Dev (Không Docker) - -```bash -# Backend (local) -cd /home/admin1/plexe-clone -python -m uvicorn plexe.server:app --reload - -# Frontend (separate terminal) -cd plexe/ui/frontend -npm run dev - -# Services (Docker) -docker compose up postgres mlflow pgadmin -``` - -**Khi nào**: Hot-reload development, no docker overhead - ---- - -## 🛠️ If Build Still Fails - -### Increase Docker Build Timeout - -```bash -# Build with higher timeout (timeout in seconds) -DOCKER_BUILDKIT_PROGRESS=plain \ -docker compose build --progress=plain backend - -# Or manually increase Docker timeout -# Edit ~/.docker/config.json and add: -# { -# "http": { -# "maxConnIdleSeconds": 120 -# } -# } -``` - -### Use Different PyPI Mirror (China/Asia) - -If you're in a region with slow PyPI access: - -```bash -# Create .docker/pip.conf -mkdir -p /home/admin1/.docker -cat > /home/admin1/.docker/pip.conf << EOF -[global] -index-url = https://mirrors.aliyun.com/pypi/simple/ -timeout = 120 -EOF - -# Then rebuild -docker compose build --progress=plain backend -``` - -### Prebuild and Cache Locally - -Build once and reuse: - -```bash -# Build and tag -docker compose build backend -docker tag plexe-clone-backend:latest plexe:prod - -# Later, just use the cached image -docker run plexe:prod -``` - ---- - -## 📊 Build Time Comparison - -| Scenario | Time | Size | Notes | -|----------|------|------|-------| -| **Production (`Dockerfile`)** | 5-10m (1st), 20s (cached) | ~3.5GB | Full torch, all deps | -| **Dev (`Dockerfile.dev`)** | 2-3m (1st), 10s (cached) | ~1.5GB | No torch, faster | -| **Pure Local** | 0s (docker) | 0MB docker | Full python env needed | - ---- - -## ✨ Features in Updated Dockerfile - -✅ **Environment variables** for pip timeout & retries -✅ **System dependencies** (git, curl for tools) -✅ **Multi-stage build** (better caching) -✅ **Retry logic** (auto-retry 3x on timeout) -✅ **Health check** (Docker monitors service health) -✅ **Auto-reload** (dev mode with `--reload`) -✅ **Better logging** (PYTHONUNBUFFERED) - ---- - -## 🔍 Debugging Build Issues - -### View detailed build logs -```bash -DOCKER_BUILDKIT_PROGRESS=plain docker compose build backend -``` - -### Check which layer is slow -```bash -docker build --progress=plain -f Dockerfile . -``` - -### Inspect build cache -```bash -docker system df # See space usage -docker builder prune # Clear build cache if needed -``` - -### Test network manually -```bash -docker run --rm python:3.11-slim \ - python -c "import urllib.request; urllib.request.urlopen('https://files.pythonhosted.org')" -``` - ---- - -## 📚 Next Steps - -1. **Try Option 2 (Dev)** — Fast, good for testing -2. **If that works**, try Option 1 (Production) when network is stable -3. **If build still fails**, check your internet connection -4. **For Asia**, use the PyPI mirror tweak above - ---- - -## ❓ FAQ - -**Q: Which should I use?** -- Dev: `docker-compose.dev.yml` (fast iterations) -- Prod: `docker-compose.yml` (full features) -- Local: Manual python setup (hot reload, no docker overhead) - -**Q: How long does torch installation take?** -- First time: 3-5 minutes (download + compile) -- Cached: Instant (layer reuse) - -**Q: Can I skip torch?** -- Yes! Use `Dockerfile.dev` or remove from `pyproject.toml` -- But some ML features might not work - -**Q: Docker build fails on my network?** -- Use PyPI mirror (see above) -- Build on a machine with better internet -- Increase timeout: `PIP_DEFAULT_TIMEOUT=200` - ---- - -**Summary**: Updated Dockerfile with retry logic + dev variant = robust, fast builds ✨ diff --git a/docs/docker-performance.md b/docs/docker-performance.md deleted file mode 100644 index 20cc69d4..00000000 --- a/docs/docker-performance.md +++ /dev/null @@ -1,188 +0,0 @@ -# Docker Performance & Connection Fix - -## 📋 Vấn Đề Ban Đầu - -Khi chạy `docker compose up -d`: -1. **Frontend** (nginx) khởi động nhanh → Ready ở port 3000 ✅ -2. **Backend** (FastAPI) khởi động chậm → Mất 2-5 phút (`pip install`) -3. **Frontend kết nối trước khi backend sẵn sàng** → `Status: Disconnected` ❌ - -## ✅ Giải Pháp Được Thực Hiện - -### 1. **Dockerfile cho Backend** (`Dockerfile`) - -Thay vì `pip install` mỗi lần, backend giờ: -- Build image một lần (install deps) -- Chạy nhanh trong 2-3 giây (từ cache) - -**Lợi ích:** -- Khởi động nhanh hơn 10x -- Không phải re-download packages -- Dễ deploy (image ready-to-go) - -```dockerfile -FROM python:3.11-slim -WORKDIR /app -COPY pyproject.toml poetry.lock* ./ -RUN pip install --no-cache-dir poetry && \ - poetry config virtualenvs.create false && \ - poetry install --no-interaction --no-ansi -COPY . . -RUN pip install --no-cache-dir -e . -EXPOSE 8000 -CMD ["python", "-m", "uvicorn", "plexe.server:app", "--host", "0.0.0.0", "--port", "8000"] -``` - -### 2. **Health Check** (docker-compose.yml) - -Thêm health check để Docker chờ backend sẵn sàng trước khi cho frontend kết nối: - -```yaml -backend: - healthcheck: - test: ["CMD", "curl", "-f", "http://localhost:8000/health"] - interval: 10s - timeout: 5s - retries: 5 - start_period: 30s -``` - -Docker sẽ chỉ xem backend là "ready" khi `/health` endpoint trả `200 OK`. - -### 3. **nginx WebSocket Proxy** (nginx.conf) - -Frontend (port 3000) giờ proxy `/ws` tới backend (port 8000): - -```nginx -location /ws { - proxy_pass http://backend:8000; - proxy_http_version 1.1; - proxy_set_header Upgrade $http_upgrade; - proxy_set_header Connection "upgrade"; - # ... (headers để chuyển tiếp connection) -} -``` - -**Lợi ích:** -- Frontend & backend có thể ở ports khác nhau -- nginx tự động forward WebSocket -- CORS không cần config - -### 4. **.dockerignore** (repo root) - -Exclude files không cần khi build backend image: -- `__pycache__`, `*.pyc` -- `node_modules/`, `dist/` -- `.git`, `.vscode` -- `mlruns/`, test files - -**Lợi ích:** -- Build context nhỏ hơn -- Build nhanh hơn - -## 🚀 Cách Chạy (Sau Fix) - -### Lần Đầu (Build Image) - -```bash -cd /home/admin1/plexe-clone - -# Build backend image (mất 3-5 phút, một lần duy nhất) -docker compose build backend - -# Hoặc: build tất cả -docker compose build - -# Start all services -docker compose up -d -``` - -### Lần Sau (Nhanh) - -```bash -# Nếu code không thay đổi, image được cache -docker compose up -d -# → Khởi động trong 5-10 giây! -``` - -### Khi Code Thay Đổi - -```bash -# Rebuild backend (nếu pyproject.toml thay đổi) -docker compose build backend -docker compose up -d - -# Hoặc one-liner -docker compose up -d --build backend -``` - -## 📊 So Sánh Before/After - -| Tiêu Chí | Before | After | -|----------|--------|-------| -| **Lần đầu** | 5-7 phút | 3-5 phút | -| **Lần sau** | 5-7 phút | 10 giây | -| **Status: Connected** | ❌ Thường bị disconnect | ✅ Nhanh connect | -| **Development** | Reload slow | Reload fast | - -## 🔧 Tech Details - -### Dockerfile Layers (Cached) - -``` -Layer 1: FROM python:3.11-slim (cached) -Layer 2: COPY pyproject.toml (cached) -Layer 3: pip install poetry (cached) -Layer 4: poetry install (cached) ← 90% thời gian -Layer 5: COPY . . (rebuild nếu code thay đổi) -Layer 6: pip install -e . (rebuild) -Layer 7: EXPOSE 8000 (cached) -Layer 8: CMD (cached) -``` - -Khi bạn chỉ thay code Python (Layer 5), Layers 1-4 được reuse từ cache. - -### Health Check Flow - -``` -docker compose up - ↓ -[1s] Frontend container started - ↓ -[3-5s] Backend container started - ↓ -[Start period 30s] Wait for /health endpoint - ↓ -[Every 10s] Check /health - ↓ -[Healthy] ✅ Status = healthy - ↓ -Frontend connects to /ws ✅ -``` - -## 📝 Files Thay Đổi - -1. **`Dockerfile`** (new) — Backend image -2. **`.dockerignore`** (new) — Exclude files -3. **`docker-compose.yml`** — Updated backend service -4. **`plexe/ui/frontend/nginx.conf`** — Added WebSocket proxy - -## ⚠️ Lưu Ý - -- **Lần đầu build**: Mất 3-5 phút (poetry install từ scratch) -- **Lần sau**: 10 giây (cache layers) -- **Nếu `poetry.lock` thay đổi**: Rebuild layer 4 (pip install) -- **Nếu `pyproject.toml` thay đổi**: Rebuild từ layer 2 - -## 🎯 Kết Quả - -Bây giờ khi bạn chạy `docker compose up -d`: -1. ✅ Frontend khởi động nhanh (3-5s) -2. ✅ Backend khởi động nhanh từ cache (3-5s) -3. ✅ Health check chờ backend sẵn sàng -4. ✅ nginx proxy `/ws` tới backend -5. ✅ Frontend kết nối tới `/ws` → **Status: Connected** 🎉 - ---- - -**Tóm tắt**: Dockerfile + health check + nginx proxy = nhanh + reliable ✨ diff --git a/docs/docker.md b/docs/docker.md deleted file mode 100644 index 426e985f..00000000 --- a/docs/docker.md +++ /dev/null @@ -1,284 +0,0 @@ -# Docker Integration Guide - -This project includes complete Docker support for development and production deployment. - -## Services - -The `docker-compose.yml` orchestrates: - -| Service | Image/Build | Port | Purpose | -|---------|------------|------|---------| -| **frontend** | Custom (Vite + nginx) | 3000 | React UI for Plexe Assistant | -| **backend** | Python 3.11 | 8000 | FastAPI server + WebSocket | -| **postgres** | postgres:15 | 5432 | Database (MLflow backend) | -| **mlflow** | Python 3.11 | 5000 | Experiment tracking server | -| **pgadmin** | pgadmin4:7 | 8080 | Database management UI | - -## Quick Start - -### Prerequisites - -- Docker & Docker Compose installed -- Node.js 18+ (for local frontend dev; not needed if using Docker) - -### Option 1: Full Stack with Docker (Recommended for Development) - -```bash -# 1. Copy and edit environment variables -cp .env.example .env -# Edit .env if you want to change credentials - -# 2. Start all services -docker compose up -d - -# 3. Watch logs (optional) -docker compose logs -f frontend -docker compose logs -f backend - -# 4. Access services -# Frontend: http://localhost:3000 -# Backend API: http://localhost:8000 -# MLflow UI: http://localhost:5000 -# pgAdmin: http://localhost:8080 (admin@example.com / admin) -# Postgres: localhost:5432 (mlflow / mlflow) - -# 5. Stop services -docker compose down -``` - -### Option 2: Local Frontend Dev + Docker Backend - -Useful if you want hot-reload for React without rebuilding Docker image: - -```bash -# 1. Start backend services only -docker compose up -d postgres mlflow pgadmin - -# 2. In a separate terminal, run frontend dev server -cd plexe/ui/frontend -npm install -npm run dev -# Opens http://localhost:5173 - -# 3. The frontend dev server will connect to backend at http://localhost:8000 -# (because the React code uses relative URLs and defaults to current host) -``` - -### Option 3: Build & Run Frontend Image Separately - -For testing the Dockerfile locally: - -```bash -cd plexe/ui/frontend - -# Build the image -docker build -t plexe-frontend:latest . - -# Run the container -docker run -p 3000:80 plexe-frontend:latest - -# Open http://localhost:3000 -``` - -## Environment Variables - -Key variables in `.env.example` (copy to `.env` to customize): - -```env -# Database credentials -POSTGRES_USER=mlflow -POSTGRES_PASSWORD=mlflow -POSTGRES_DB=mlflow_db - -# MLflow backend store URI -MLFLOW_BACKEND_STORE_URI=postgresql+psycopg2://mlflow:mlflow@postgres:5432/mlflow_db - -# MLflow tracking URI (where server is running) -MLFLOW_TRACKING_URI=http://mlflow:5000 - -# Frontend API URL (for backend communication) -REACT_APP_API_URL=http://localhost:8000 - -# pgAdmin credentials -PGADMIN_EMAIL=admin@example.com -PGADMIN_PASSWORD=admin -``` - -## Architecture - -``` -┌─────────────┐ -│ Browser │ -└──────┬──────┘ - │ HTTP/WebSocket - ▼ -┌──────────────────────────┐ -│ Frontend (nginx) │ :3000 -│ Serves React SPA │ -└──────────────────────────┘ - │ API calls & WS - ▼ -┌──────────────────────────┐ -│ Backend (FastAPI) │ :8000 -│ /ws for chat │ -│ / serves dist/index.html│ -└──────────────────────────┘ - │ - ┌────┴─────┐ - ▼ ▼ -┌──────────┐ ┌────────────┐ -│Postgres │ │ MLflow │ -│ :5432 │ │ :5000 │ -└──────────┘ └────────────┘ -``` - -In Docker Compose, services communicate via: -- Service name (within containers): `postgres`, `mlflow`, `frontend`, `backend` -- Localhost + port (from host): `localhost:5432`, `localhost:5000`, etc. - -## Frontend Docker Details - -### Dockerfile Structure - -The `Dockerfile` uses a **multi-stage build**: - -1. **Build stage** (Node): Installs npm deps and runs `npm run build` → outputs `dist/` -2. **Serve stage** (nginx): Copies `dist/` and serves with nginx on port 80 - -### nginx Configuration - -- `nginx.conf` routes all requests to `index.html` (SPA routing) -- Assets in `/assets/` are cached long-term -- `/health` endpoint for container health checks - -### Building the Frontend Image - -When you run `docker compose up frontend`, Docker: -1. Reads `plexe/ui/frontend/Dockerfile` -2. Installs Node deps -3. Runs `npm run build` -4. Copies the built `dist/` folder into nginx container -5. Exposes port 80 (mapped to 3000 on host) - -No rebuilds needed unless source code changes (Docker uses cache). - -## Backend Docker Details - -The backend runs: -- Python 3.11-slim image -- Installs the repo as editable package (`pip install -e .`) -- Runs `uvicorn plexe.server:app --reload` - -Volume mapping (`- .:/app`) allows live code reloads during development. - -## Common Tasks - -### View service logs - -```bash -# All services -docker compose logs -f - -# Specific service -docker compose logs -f frontend -docker compose logs -f backend -docker compose logs -f postgres - -# Last 50 lines of a service -docker compose logs -n 50 frontend -``` - -### Access a container shell - -```bash -# Frontend (nginx) -docker compose exec frontend sh - -# Backend (Python) -docker compose exec backend bash - -# Database (psql) -docker compose exec postgres psql -U mlflow -d mlflow_db -``` - -### Rebuild a service (if Dockerfile changed) - -```bash -# Rebuild frontend -docker compose build frontend - -# Or rebuild and restart -docker compose up -d --build frontend -``` - -### Clean up volumes and containers - -```bash -# Stop and remove containers, networks (keeps volumes by default) -docker compose down - -# Also remove volumes (⚠️ deletes data) -docker compose down -v -``` - -## Troubleshooting - -### Frontend won't connect to backend - -- Check that backend is running: `docker compose ps` should show backend as `Up` -- Check backend logs: `docker compose logs -f backend` -- Verify WebSocket URL in React code matches backend port (default `:8000`) -- If using dev server, ensure CORS is enabled or use a proxy - -### Port already in use - -If port 3000 or 8000 is already in use: -```bash -# Change in docker-compose.yml or .env -# Edit ports: -# - "3001:80" # frontend on 3001 instead of 3000 -# - "8001:8000" # backend on 8001 -``` - -### Database connection errors - -- Verify `POSTGRES_USER`, `POSTGRES_PASSWORD`, `POSTGRES_DB` match in all services -- Check postgres is running: `docker compose logs postgres` -- Ensure MLflow can reach postgres: `docker compose exec mlflow psql -h postgres -U mlflow -d mlflow_db` - -### React build fails in Docker - -- Check `npm run build` works locally: `cd plexe/ui/frontend && npm run build` -- Verify `package.json` has all required scripts -- Check Node version in Dockerfile (currently 18-alpine) - -## Production Deployment - -For production: - -1. **Build images with specific versions** (don't use `latest`) - ```bash - docker compose build --tag plexe:v1.0.0 - ``` - -2. **Use a Kubernetes or Swarm orchestrator** for scaling - -3. **Use environment-specific `.env` files**: - ```bash - docker compose --env-file .env.prod up -d - ``` - -4. **Use a reverse proxy** (nginx/traefik) in front of the services - -5. **Enable HTTPS/TLS** for WebSocket (WSS) - -6. **Mount volumes for persistence**: - - Database: `postgres_data` volume (already configured) - - MLflow artifacts: `mlruns` directory (already configured) - -## Next Steps - -- Customize `nginx.conf` for your needs -- Add authentication/authorization layers -- Set up CI/CD to build and push Docker images -- Deploy to cloud (AWS, GCP, Azure, DigitalOcean, etc.) diff --git a/docs/postgres.md b/docs/postgres.md deleted file mode 100644 index ca34f677..00000000 --- a/docs/postgres.md +++ /dev/null @@ -1,67 +0,0 @@ -## Running PostgreSQL (and MLflow) with Docker - -This project uses MLflow and optionally can use PostgreSQL as a backing store. The repository includes a ready-to-run `docker-compose.yml` that starts: - -- PostgreSQL 15 -- MLflow server (configured to use Postgres for the backend store) -- pgAdmin (optional UI for managing the database) - -Files added: - -- `docker-compose.yml` — launches the services -- `.env.example` — example environment variables (copy to `.env` and edit) - -Quick start - -1. Copy the example env file and edit if you want different credentials: - -```bash -cp .env.example .env -# edit .env if necessary -``` - -2. Start the stack: - -```bash -docker compose up -d -``` - -3. Confirm services are running: - -```bash -docker compose ps -``` - -4. MLflow UI will be available at http://localhost:5000 - -5. pgAdmin will be available at http://localhost:8080 (use credentials from `.env`). - -How MLflow is configured - -The compose uses an environment variable `MLFLOW_BACKEND_STORE_URI` pointing to Postgres: - -``` -postgresql+psycopg2://:@postgres:5432/ -``` - -MLflow stores metadata (experiments, runs) in Postgres and artifacts under the `./mlruns` folder mounted from the host. - -Pointing Plexe to the MLflow server - -The repo contains an MLflow callback at `plexe/internal/models/callbacks/mlflow.py` that sets the MLflow tracking URI via `mlflow.set_tracking_uri(...)` when the callback is initialized. You can either: - -- Set the environment variable `MLFLOW_TRACKING_URI` before running your code, e.g. `export MLFLOW_TRACKING_URI=http://localhost:5000`. -- Or in Python set `mlflow.set_tracking_uri('http://localhost:5000')` before creating the `MLFlowCallback`. - -Example — run a script with MLflow tracking enabled: - -```bash -export MLFLOW_TRACKING_URI=http://localhost:5000 -python examples/test_saved_model.py -``` - -Notes & tips - -- The compose installs `psycopg2-binary` inside the `mlflow` container at startup for convenience. For production, build a small image with pinned deps. -- If you already have Postgres running locally, you can point `MLFLOW_BACKEND_STORE_URI` to it and remove the `postgres` service. -- To persist the DB data, `postgres_data` volume is created by compose. diff --git a/plexe/__init__.py b/plexe/__init__.py index 8817bfdb..3451de05 100644 --- a/plexe/__init__.py +++ b/plexe/__init__.py @@ -1,14 +1,11 @@ -from .models import Model as Model -from .model_builder import ModelBuilder as ModelBuilder -from .datasets import DatasetGenerator as DatasetGenerator -from .fileio import ( - load_model as load_model, - save_model as save_model, - save_checkpoint as save_checkpoint, - load_checkpoint as load_checkpoint, - list_checkpoints as list_checkpoints, - clear_checkpoints as clear_checkpoints, +from .langgraph import ( + PlexeOrchestrator, + AgentConfig, + PipelineState, + ConversationalAgent, + EDAAgent, + DatasetBuilderAgent, + TaskBuilderAgent, + RelationalGNNSpecialistAgent, + OperationAgent, ) -from .callbacks import Callback as Callback -from .callbacks import MLFlowCallback as MLFlowCallback -from .callbacks import ModelCheckpointCallback as ModelCheckpointCallback diff --git a/plexe/agents/__init__.py b/plexe/agents/__init__.py deleted file mode 100644 index 9e9a0b48..00000000 --- a/plexe/agents/__init__.py +++ /dev/null @@ -1,11 +0,0 @@ -""" -Agents for the Plexe ML platform. - -This package contains agent implementations for various tasks in the Plexe platform. -""" - -# ruff: noqa: F401 -from .relational_graph_architect import RelationalGraphArchitectAgent -from .relational_gnn_specialist import RelationalGNNSpecialistAgent -from .dataset_builder import DatasetBuilderAgent -from .task_builder import TaskBuilderAgent diff --git a/plexe/agents/agents.py b/plexe/agents/agents.py deleted file mode 100644 index 6e6edce6..00000000 --- a/plexe/agents/agents.py +++ /dev/null @@ -1,316 +0,0 @@ -""" -This module defines a multi-agent ML engineering system for building machine learning models. -""" - -import os -import json -import logging -import types -from dataclasses import dataclass, field -from typing import List, Dict, Optional, Callable - -from smolagents import CodeAgent, LiteLLMModel, AgentText - -from plexe.agents.relational_graph_architect import RelationalGraphArchitectAgent -from plexe.agents.relational_gnn_specialist import RelationalGNNSpecialistAgent -from plexe.agents.dataset_builder import DatasetBuilderAgent -from plexe.agents.task_builder import TaskBuilderAgent -from plexe.config import config -from plexe.core.object_registry import ObjectRegistry -from plexe.internal.models.entities.artifact import Artifact -from plexe.internal.models.entities.code import Code -from plexe.internal.models.entities.metric import Metric -from plexe.internal.models.entities.metric import MetricComparator, ComparisonMethod -from plexe.core.entities.solution import Solution -from plexe.core.interfaces.predictor import Predictor -from plexe.tools.datasets import get_latest_datasets -from plexe.tools.evaluation import get_review_finalised_model, get_solution_performances -from plexe.tools.metrics import get_select_target_metric -from plexe.tools.response_formatting import ( - format_final_orchestrator_agent_response, -) -from plexe.tools.training import register_best_solution -from plexe.tools.interaction import ask_user_confirmation, save_to_workdir - -logger = logging.getLogger(__name__) - - -@dataclass -class ModelGenerationResult: - training_source_code: str - inference_source_code: str - feature_transformer_source_code: str - dataset_split_code: str - predictor: Predictor - model_artifacts: List[Artifact] - performance: Metric # Validation performance - test_performance: Metric = None # Test set performance - testing_source_code: str = None # Testing code from model tester agent - evaluation_report: Dict = None # Evaluation report from model tester agent - metadata: Dict[str, str] = field(default_factory=dict) # Model metadata - - -class PlexeAgent: - """ - Multi-agent ML engineering system for building machine learning models. - - This class creates and manages a system of specialized agents that work together - to analyze data, plan solutions, train models, and generate inference code. - """ - - def __init__( - self, - orchestrator_model_id: str = None, - ml_researcher_model_id: str = None, - ml_engineer_model_id: str = None, - ml_ops_engineer_model_id: str = None, - tool_model_id: str = None, - verbose: bool = False, - max_steps: int = 50, - distributed: bool = False, - chain_of_thought_callable: Optional[Callable] = None, - max_solutions: int = 1, - ): - """ - Initialize the multi-agent ML engineering system. - - Args: - orchestrator_model_id: Model ID for the orchestrator agent - ml_researcher_model_id: Model ID for the ML researcher agent - ml_engineer_model_id: Model ID for the ML engineer agent - ml_ops_engineer_model_id: Model ID for the ML ops engineer agent - tool_model_id: Model ID for the model used inside tool calls - verbose: Whether to display detailed agent logs - max_steps: Maximum number of steps for the orchestrator agent - distributed: Whether to run the agents in a distributed environment - chain_of_thought_callable: Optional callable for chain of thought logging - max_solutions: Maximum number of solutions to generate - """ - self.orchestrator_model_id = orchestrator_model_id or os.environ.get( - "PLEXE_ORCHESTRATOR_MODEL", "gemini/gemini-2.5-flash" - ) - self.ml_researcher_model_id = ml_researcher_model_id or os.environ.get( - "PLEXE_ML_RESEARCHER_MODEL", "gemini/gemini-2.5-flash" - ) - self.ml_engineer_model_id = ml_engineer_model_id or os.environ.get( - "PLEXE_ML_ENGINEER_MODEL", "gemini/gemini-2.5-flash" - ) - self.ml_ops_engineer_model_id = ml_ops_engineer_model_id or os.environ.get( - "PLEXE_ML_OPS_ENGINEER_MODEL", "gemini/gemini-2.5-flash" - ) - self.tool_model_id = tool_model_id or os.environ.get("PLEXE_TOOL_MODEL", "gemini/gemini-2.5-flash") - self.verbose = verbose - self.max_steps = max_steps - self.distributed = distributed - self.chain_of_thought_callable = chain_of_thought_callable - - # Set verbosity levels - self.orchestrator_verbosity = 1 if verbose else 0 - self.specialist_verbosity = 1 if verbose else 0 - - # Create Relational Graph Architect Agent - self.relational_graph_architect_agent = RelationalGraphArchitectAgent( - model_id=self.ml_engineer_model_id, - verbose=verbose, - chain_of_thought_callable=self.chain_of_thought_callable, - ).agent - - # Create Relational GNN Specialist Agent - self.relational_gnn_specialist_agent = RelationalGNNSpecialistAgent( - model_id=self.ml_engineer_model_id, - verbose=verbose, - chain_of_thought_callable=self.chain_of_thought_callable, - ).agent - - # Create Dataset Builder Agent - builds RelBench Database from CSV files - self.dataset_builder_agent = DatasetBuilderAgent( - model_id=self.ml_engineer_model_id, - verbose=verbose, - chain_of_thought_callable=self.chain_of_thought_callable, - ).agent - - # Create Task Builder Agent - builds RelBench Tasks - self.task_builder_agent = TaskBuilderAgent( - model_id=self.ml_engineer_model_id, - verbose=verbose, - chain_of_thought_callable=self.chain_of_thought_callable, - ).agent - - # Define managed agents - managed_agents = [ - self.relational_graph_architect_agent, - self.relational_gnn_specialist_agent, - self.dataset_builder_agent, - self.task_builder_agent, - ] - - # Create orchestrator agent - coordinates the workflow - self.manager_agent = CodeAgent( - name="Orchestrator", - model=LiteLLMModel(model_id=self.orchestrator_model_id), - tools=[ - get_select_target_metric(self.tool_model_id), - get_review_finalised_model(self.tool_model_id), - get_latest_datasets, - get_solution_performances, - register_best_solution, - format_final_orchestrator_agent_response, - ask_user_confirmation, - save_to_workdir, - ], - managed_agents=managed_agents, - add_base_tools=False, - verbosity_level=self.orchestrator_verbosity, - additional_authorized_imports=config.code_generation.authorized_agent_imports, - max_steps=self.max_steps, - planning_interval=7, - step_callbacks=[self.chain_of_thought_callable], - ) - - def run(self, task, additional_args: dict) -> ModelGenerationResult: - """ - Run the orchestrator agent to generate a machine learning model. - - Returns: - ModelGenerationResult: The result of the model generation process. - """ - object_registry = ObjectRegistry() - result = self.manager_agent.run(task=task, additional_args=additional_args) - - print(f"Registry contents:\n\n" f"{json.dumps(sorted(object_registry.list()), indent=4)}" f"\n\n") - - try: - # Only log the full result when in verbose mode - if logger.isEnabledFor(logging.DEBUG): - logger.debug("Agent result: %s", result) - - if isinstance(result, AgentText): - try: - result = json.loads(str(result)) - except json.JSONDecodeError as e: - logger.error(f"Failed to parse agent result as JSON: {e}. Raw result: {str(result)}") - # Return a partial result indicating failure to prevent crash - result = { - "status": "failed", - "error": f"Agent returned invalid JSON: {str(e)}", - "raw_output": str(result), - "metadata": {}, - "performance": {"name": "unknown", "value": 0.0}, - } - - # Extract data from the agent result - try: - best_solution = object_registry.get(Solution, "best_performing_solution") - training_code = best_solution.training_code - inference_code = best_solution.inference_code - except KeyError: - logger.warning("No best solution found in registry. Returning partial result.") - return ModelGenerationResult( - training_source_code="", - inference_source_code="", - feature_transformer_source_code="", - dataset_split_code="", - predictor=None, - model_artifacts=[], - performance=Metric(name="unknown", value=0.0, comparator=MetricComparator(ComparisonMethod.HIGHER_IS_BETTER)), - metadata={"status": "failed", "reason": "No solution found"}, - ) - - # Extract performance metrics - if "performance" in result and isinstance(result["performance"], dict): - metrics = result["performance"] - else: - metrics = {} - - metric_name = metrics.get("name", "unknown") - metric_value = metrics.get("value", 0.0) - comparison_str = metrics.get("comparison_method", "") - comparison_method_map = { - "HIGHER_IS_BETTER": ComparisonMethod.HIGHER_IS_BETTER, - "LOWER_IS_BETTER": ComparisonMethod.LOWER_IS_BETTER, - "TARGET_IS_BETTER": ComparisonMethod.TARGET_IS_BETTER, - } - comparison_method = ComparisonMethod.HIGHER_IS_BETTER # Default to higher is better - for key, method in comparison_method_map.items(): - if key in comparison_str: - comparison_method = method - - comparator = MetricComparator(comparison_method) - performance = Metric( - name=metric_name, - value=metric_value, - comparator=comparator, - ) - - # Model metadata - metadata = result.get("metadata", {"model_type": "unknown", "framework": "unknown"}) - - # Compile the inference code into a module - inference_module: types.ModuleType = types.ModuleType("predictor") - predictor = None - - if inference_code and isinstance(inference_code, str): - try: - exec(inference_code, inference_module.__dict__) - # Instantiate the predictor class from the loaded module - if hasattr(inference_module, "PredictorImplementation"): - predictor_class = getattr(inference_module, "PredictorImplementation") - predictor = predictor_class(best_solution.model_artifacts) - else: - logger.warning("PredictorImplementation class not found in inference code.") - except Exception as e: - logger.error(f"Failed to compile or instantiate predictor: {e}") - else: - logger.warning("No valid inference code found. Predictor will be None.") - - # Get feature transformer code if available - feature_transformer_code = None - try: - feature_code = object_registry.get(Code, "feature_transformations") - if feature_code: - feature_transformer_code = feature_code.code - except KeyError: - # No feature transformations code found, that's ok - pass - - # Get dataset split code if available - dataset_split_code = None - try: - dataset_split_code = object_registry.get(Code, "dataset_splitting_code") - if dataset_split_code: - dataset_split_code = dataset_split_code.code - except KeyError: - # No dataset split code found, that's ok - pass - - # Get testing code if available - testing_code = None - try: - testing_code = best_solution.testing_code - except Exception: - # No testing code found, that's ok - pass - - # Get evaluation report if available - evaluation_report = None - try: - evaluation_report = best_solution.model_evaluation_report - except Exception: - # No evaluation report found, that's ok - pass - - return ModelGenerationResult( - training_source_code=training_code, - inference_source_code=inference_code, - feature_transformer_source_code=feature_transformer_code, - dataset_split_code=dataset_split_code, - predictor=predictor, - model_artifacts=best_solution.model_artifacts, - performance=performance, - test_performance=performance, # Using the same performance for now - testing_source_code=testing_code, - evaluation_report=evaluation_report, - metadata=metadata, - ) - except Exception as e: - raise RuntimeError(f"❌ Failed to process agent result: {str(e)}") from e diff --git a/plexe/agents/conversational.py b/plexe/agents/conversational.py deleted file mode 100644 index 78b800d6..00000000 --- a/plexe/agents/conversational.py +++ /dev/null @@ -1,102 +0,0 @@ -""" -Conversational Agent for guiding users through ML model definition and initiation. - -This module defines a ConversationalAgent that helps users define their ML requirements -through natural conversation, validates their inputs, and initiates model building -when all necessary information has been gathered. -""" - -import logging -import os -from typing import Optional, Callable - -from smolagents import ToolCallingAgent, LiteLLMModel - -from plexe.internal.common.utils.agents import get_prompt_templates -from plexe.tools.datasets import get_dataset_preview -from plexe.tools.conversation import ( - validate_dataset_files, - initiate_model_build, - validate_db_connection, -) - -logger = logging.getLogger(__name__) - - -class ConversationalAgent: - """ - Agent for conversational model definition and build initiation. - - This agent guides users through defining their ML requirements via natural - conversation, helps clarify the problem, validates dataset availability, - and initiates the model building process when all requirements are met. - """ - - def __init__( - self, - model_id: str | None = None, - verbose: bool = False, - chain_of_thought_callable: Optional[Callable] = None, - ): - """ - Initialize the conversational agent. - - Args: - model_id: Model ID for the LLM to use for conversation - verbose: Whether to display detailed agent logs - chain_of_thought_callable: Optional callable for chain of thought logging - """ - # Choose model id with this precedence: - # 1. explicit `model_id` argument - # 2. env var `PLEXE_CONVERSATIONAL_MODEL` - # 3. automatic selection based on available API keys - # - GEMINI -> gemini/gemini-2.5-flash - # - OPENAI -> gemini/gemini-2.5-flash - # - ANTHROPIC -> anthropic/claude-sonnet-4-20250514 - # 4. fallback to anthropic default - env_model = os.environ.get("PLEXE_CONVERSATIONAL_MODEL") - - if model_id: - self.model_id = model_id - elif env_model: - self.model_id = env_model - else: - # Auto-detect from available API keys - if os.environ.get("GEMINI_API_KEY"): - self.model_id = "gemini/gemini-2.5-flash" - elif os.environ.get("OPENAI_API_KEY"): - self.model_id = "gemini/gemini-2.5-flash" - elif os.environ.get("ANTHROPIC_API_KEY"): - self.model_id = "anthropic/claude-sonnet-4-20250514" - else: - self.model_id = "anthropic/claude-sonnet-4-20250514" - self.verbose = verbose - - # Set verbosity level - self.verbosity = 1 if verbose else 0 - - # Create the conversational agent with necessary tools - self.agent = ToolCallingAgent( - name="ModelDefinitionAssistant", - description=( - "Expert ML and DL consultant that helps users define their machine learning and deep learning requirements " - "through conversational guidance. Specializes in clarifying problem definitions, " - "understanding data requirements, and initiating model builds when ready. " - "Maintains a friendly, helpful conversation while ensuring all technical " - "requirements are properly defined before proceeding with model creation." - ), - model=LiteLLMModel(model_id=self.model_id), - tools=[ - get_dataset_preview, - validate_dataset_files, - validate_db_connection, - initiate_model_build, - ], - add_base_tools=False, - verbosity_level=self.verbosity, - step_callbacks=[chain_of_thought_callable] if chain_of_thought_callable else None, - prompt_templates=get_prompt_templates( - base_template_name="toolcalling_agent.yaml", - override_template_name="conversational_prompt_templates.yaml", - ), - ) diff --git a/plexe/agents/dataset_builder.py b/plexe/agents/dataset_builder.py deleted file mode 100644 index d02a9d76..00000000 --- a/plexe/agents/dataset_builder.py +++ /dev/null @@ -1,116 +0,0 @@ -""" -Dataset Builder Agent for constructing RelBench Database objects from raw CSV files. - -This agent builds a plexe.relbench.base.Database by: -1. Reading CSV files from a specified directory -2. Using EDA reports to determine data processing steps -3. Processing time columns (merging date/time, propagating timestamps) -4. Defining schema with primary keys, foreign keys, and time columns -5. Returning a complete Database object -""" - -import logging -from typing import Optional, Callable - -from smolagents import CodeAgent, LiteLLMModel - -from plexe.config import config -from plexe.internal.common.utils.agents import get_prompt_templates -from plexe.tools.datasets import get_dataset_reports, get_latest_datasets -from plexe.tools.database_builder import ( - get_csv_files_from_path, - get_schema_metadata_from_registry, - register_database_code, - export_database_code, - validate_database_code, - get_temporal_statistics, -) - -logger = logging.getLogger(__name__) - - -class DatasetBuilderAgent: - """ - Agent for building RelBench Database objects from raw CSV data. - - This agent analyzes CSV files, applies data processing based on EDA reports, - handles temporal data properly, and constructs a Database with correct - schema definitions (primary keys, foreign keys, time columns). - """ - - def __init__( - self, - model_id: str | None = None, - verbose: bool = False, - chain_of_thought_callable: Optional[Callable] = None, - ): - """ - Initialize the Dataset Builder Agent. - - Args: - model_id: Model ID for the LLM - verbose: Whether to display detailed agent logs - chain_of_thought_callable: Optional callback for chain-of-thought logging - """ - self.model_id = model_id or "gemini/gemini-2.5-flash" - self.verbosity = 1 if verbose else 0 - - self.agent = CodeAgent( - name="DatasetBuilder", - description=( - "Expert in building RelBench Database objects from raw CSV files. " - "Reads CSV files, applies data cleaning based on EDA reports, " - "processes temporal columns (merging date/time, propagating timestamps from parent to child tables), " - "defines schema with primary keys, foreign keys, and time columns, " - "and generates a complete Python Dataset class that can be registered and exported." - ), - model=LiteLLMModel(model_id=self.model_id), - tools=[ - # Data discovery - get_csv_files_from_path, - get_schema_metadata_from_registry, - get_dataset_reports, - get_latest_datasets, - # Temporal analysis - get_temporal_statistics, - # Database building - register_database_code, - export_database_code, - validate_database_code, - ], - prompt_templates=get_prompt_templates( - base_template_name="code_agent.yaml", - override_template_name="dataset_builder_prompt_templates.yaml", - ), - verbosity_level=self.verbosity, - add_base_tools=False, - additional_authorized_imports=config.code_generation.authorized_agent_imports - + [ - "plexe", - "plexe.*", - "pandas", - "pandas.*", - "numpy", - "numpy.*", - "os", - "os.*", - "pathlib", - "pathlib.*", - "plexe.relbench", - "plexe.relbench.*", - ], - step_callbacks=[chain_of_thought_callable], - max_steps=30, - ) - - def run(self, task_description: str) -> str: - """ - Run the agent to build a Database from CSV files. - - Args: - task_description: Description of the database building task - - Returns: - Result of the database building process - """ - return self.agent.run(task_description) diff --git a/plexe/agents/relational_gnn_specialist.py b/plexe/agents/relational_gnn_specialist.py deleted file mode 100644 index 66fbbfc7..00000000 --- a/plexe/agents/relational_gnn_specialist.py +++ /dev/null @@ -1,117 +0,0 @@ -""" -Relational GNN Specialist Agent. - -This agent is responsible for generating and executing GNN training scripts -that use the plexe.relbench.modeling modules for training on relational data. - -The agent takes the Dataset and Task classes generated by DatasetBuilder -and TaskBuilder agents, and creates a complete training pipeline. -""" - -import logging -from typing import Optional, Callable, Any - -from smolagents import CodeAgent, LiteLLMModel - -from plexe.config import config -from plexe.internal.common.utils.agents import get_prompt_templates -from plexe.tools.gnn_training_script_generator import ( - get_training_script_template, - generate_training_script, - execute_training_script, - get_dataset_task_info_from_registry, - validate_training_prerequisites, -) - -logger = logging.getLogger(__name__) - - -class RelationalGNNSpecialistAgent: - """ - Agent for training GNNs on Relational Entity Graphs using the RelBench framework. - - This agent generates training scripts that: - 1. Load custom Dataset and Task classes from previous agents - 2. Build heterogeneous graphs using make_pkey_fkey_graph - 3. Use HeteroEncoder, HeteroTemporalEncoder, HeteroGraphSAGE for modeling - 4. Train with temporal sampling to prevent data leakage - 5. Evaluate and save the best model - """ - - def __init__( - self, - model_id: str | None = None, - verbose: bool = False, - chain_of_thought_callable: Optional[Callable] = None, - ): - """ - Initialize the Relational GNN Specialist Agent. - - Args: - model_id: Model ID for the LLM - verbose: Whether to display detailed agent logs - chain_of_thought_callable: Optional callback for chain-of-thought logging - """ - self.model_id = model_id or "gpt-4o" - self.verbosity = 1 if verbose else 0 - - self.agent = CodeAgent( - name="RelationalGNNSpecialist", - description=( - "Expert in Graph Neural Networks for Relational Deep Learning. " - "Generates and executes training scripts using plexe.relbench.modeling modules " - "(make_pkey_fkey_graph, HeteroEncoder, HeteroTemporalEncoder, HeteroGraphSAGE). " - "Works with Dataset and Task classes from DatasetBuilder and TaskBuilder agents." - ), - model=LiteLLMModel(model_id=self.model_id), - tools=[ - # Information retrieval - get_dataset_task_info_from_registry, - get_training_script_template, - # Validation - validate_training_prerequisites, - generate_training_script, - # Execution - execute_training_script, - ], - prompt_templates=get_prompt_templates( - base_template_name="code_agent.yaml", - override_template_name="relational_gnn_specialist_prompt_templates.yaml", - ), - verbosity_level=self.verbosity, - add_base_tools=False, - additional_authorized_imports=config.code_generation.authorized_agent_imports - + [ - "plexe", - "plexe.*", - "pandas", - "pandas.*", - "numpy", - "numpy.*", - "torch", - "torch.*", - "torch_geometric", - "torch_geometric.*", - "torch_frame", - "torch_frame.*", - "plexe.relbench", - "plexe.relbench.*", - ], - step_callbacks=[chain_of_thought_callable], - ) - - def run(self, task_description: str) -> Any: - """ - Run the agent to generate and execute GNN training. - - Args: - task_description: Description of the training task including: - - Path to dataset module (or will retrieve from registry) - - Path to task module (or will retrieve from registry) - - Training configuration (epochs, batch_size, etc.) - - Task type (regression, classification) - - Returns: - Result of the training process - """ - return self.agent.run(task_description) diff --git a/plexe/agents/relational_graph_architect.py b/plexe/agents/relational_graph_architect.py deleted file mode 100644 index 85527fe8..00000000 --- a/plexe/agents/relational_graph_architect.py +++ /dev/null @@ -1,122 +0,0 @@ -""" -Relational Graph Architect Agent. -""" - -import logging -from typing import Optional, Callable, Any - -from smolagents import CodeAgent, LiteLLMModel - -from plexe.config import config -from plexe.internal.common.utils.agents import get_prompt_templates -from plexe.tools.datasets import register_data_source_path -from plexe.tools.graph_processing import ( - extract_schema_metadata, - load_table_data, - get_cached_schema, - build_hetero_graph, - get_graph_from_registry, - encode_multi_modal_features, - # EntityMapper tools - create_entity_mapper, - register_entities, - get_entity_index, - convert_edge_ids_to_indices, - interpret_prediction, - get_mapper_summary, - # Schema verification tool - critical for correct column names - get_table_columns, - # Export tables to CSV - export_tables_to_csv, - # Deprecated but kept for compatibility - create_id_mapping, -) - -logger = logging.getLogger(__name__) - - -class RelationalGraphArchitectAgent: - """ - Agent for transforming relational databases into heterogeneous graphs. - """ - - def __init__( - self, - model_id: str | None = None, - verbose: bool = False, - chain_of_thought_callable: Optional[Callable] = None, - ): - """ - Initialize the Relational Graph Architect Agent. - - Args: - model_id: Model ID for the LLM - verbose: Whether to display detailed agent logs - chain_of_thought_callable: Optional callback for chain-of-thought logging - """ - self.model_id = model_id or "gpt-4o" - self.verbosity = 1 if verbose else 0 - - self.agent = CodeAgent( - name="RelationalGraphArchitect", - description=( - "Expert in Graph Representation Learning and Heterogeneous Graph Construction. " - "Transforms multi-table relational databases into Heterogeneous Graphs for GNNs. " - "Can connect to databases, export tables to CSV, analyze schema relationships (PK/FK), and determine temporal splits. " - "IMPORTANT: The database columns use snake_case naming convention (e.g., owner_user_id instead of OwnerUserId). " - "Always check the actual column names from the schema before generating SQL." - ), - model=LiteLLMModel(model_id=self.model_id), - tools=[ - # Schema analysis & data loading - extract_schema_metadata, - get_cached_schema, - load_table_data, - register_data_source_path, - # Export tables to CSV for DatasetBuilder - export_tables_to_csv, - # Column name verification - USE BEFORE WRITING SQL! - get_table_columns, - # EntityMapper tools (for ID mapping and prediction interpretation) - create_entity_mapper, - register_entities, - convert_edge_ids_to_indices, - interpret_prediction, - get_mapper_summary, - # Graph construction - build_hetero_graph, - get_graph_from_registry, - encode_multi_modal_features, - ], - prompt_templates=get_prompt_templates( - base_template_name="code_agent.yaml", - override_template_name="relational_graph_architect_prompt_templates.yaml", - ), - # verbose=verbose, # Removed verbose argument - verbosity_level=self.verbosity, - add_base_tools=False, - additional_authorized_imports=config.code_generation.authorized_agent_imports - + [ - "plexe", - "plexe.*", - "pandas", - "pandas.*", - "numpy", - "numpy.*", - "torch", - "torch.*", - "torch_geometric", - "torch_geometric.*", - "sqlalchemy", - "sqlalchemy.*", - "psycopg2", - "psycopg2.*", - ], - step_callbacks=[chain_of_thought_callable], - ) - - def run(self, db_connection: Any) -> Any: - """ - Run the agent to build the graph. - """ - return self.agent.run(f"Build a heterogeneous graph from the database connection: {db_connection}") diff --git a/plexe/agents/task_builder.py b/plexe/agents/task_builder.py deleted file mode 100644 index a223f03c..00000000 --- a/plexe/agents/task_builder.py +++ /dev/null @@ -1,148 +0,0 @@ -""" -Task Builder Agent for constructing RelBench Task objects from Database/Dataset. - -This agent builds EntityTask or RecommendationTask by: -1. Analyzing the database schema to understand available tables and relationships -2. Identifying entity tables and potential prediction targets -3. Defining the prediction task (classification, regression, or recommendation) -4. Generating SQL queries to compute labels from historical data -5. Returning a complete Task class that can be used for training - -The Task is the "question" that we want the AI model to answer, while -the Dataset is the "raw material" used to answer that question. -""" - -import logging -from typing import Optional, Callable - -from smolagents import CodeAgent, LiteLLMModel - -from plexe.config import config -from plexe.internal.common.utils.agents import get_prompt_templates -from plexe.tools.datasets import get_dataset_reports, get_latest_datasets -from plexe.tools.task_builder import ( - get_database_schema_for_task, - get_dataset_info, - get_available_metrics, - get_table_sample_data, - test_sql_query, - analyze_potential_tasks, - validate_task_code, - register_task_code, - export_task_code, - get_entity_task_template, - get_recommendation_task_template, - get_sql_query_examples, -) - -logger = logging.getLogger(__name__) - - -class TaskBuilderAgent: - """ - Agent for building RelBench Task objects from Database/Dataset. - - This agent analyzes the database schema, understands entity relationships, - and constructs prediction tasks (EntityTask or RecommendationTask) with - proper SQL queries to compute labels from historical data. - - Tasks define what prediction we want to make: - - EntityTask: Classification or regression over a single entity - (e.g., predict if a user will churn, predict driver DNF) - - RecommendationTask: Link prediction between entities - (e.g., predict which products a user will buy) - """ - - def __init__( - self, - model_id: str | None = None, - verbose: bool = False, - chain_of_thought_callable: Optional[Callable] = None, - ): - """ - Initialize the Task Builder Agent. - - Args: - model_id: Model ID for the LLM - verbose: Whether to display detailed agent logs - chain_of_thought_callable: Optional callback for chain-of-thought logging - """ - self.model_id = model_id or "gemini/gemini-2.5-flash" - self.verbosity = 1 if verbose else 0 - - self.agent = CodeAgent( - name="TaskBuilder", - description=( - "Expert in building RelBench Task objects (EntityTask or RecommendationTask) " - "from a Database/Dataset. Analyzes database schema to understand entity relationships, " - "defines prediction tasks based on user requirements, generates efficient SQL queries " - "using DuckDB to compute labels from historical data, and produces complete Python " - "Task classes that can be registered and used for GNN training." - ), - model=LiteLLMModel(model_id=self.model_id), - tools=[ - # Schema and data discovery - get_database_schema_for_task, - get_dataset_info, - get_table_sample_data, - get_dataset_reports, - get_latest_datasets, - # Task analysis - analyze_potential_tasks, - get_available_metrics, - # SQL query testing - test_sql_query, - # Code generation support - get_entity_task_template, - get_recommendation_task_template, - get_sql_query_examples, - # Validation and registration - validate_task_code, - register_task_code, - export_task_code, - ], - prompt_templates=get_prompt_templates( - base_template_name="code_agent.yaml", - override_template_name="task_builder_prompt_templates.yaml", - ), - verbosity_level=self.verbosity, - add_base_tools=False, - additional_authorized_imports=config.code_generation.authorized_agent_imports - + [ - "plexe", - "plexe.*", - "plexe.relbench", - "plexe.relbench.*", - "plexe.relbench.base", - "plexe.relbench.metrics", - "pandas", - "pandas.*", - "numpy", - "numpy.*", - "duckdb", - "duckdb.*", - "os", - "os.*", - "pathlib", - "pathlib.*", - ], - step_callbacks=[chain_of_thought_callable], - max_steps=30, - ) - - def run(self, task_description: str) -> str: - """ - Run the agent to build a Task from the Database. - - Args: - task_description: Description of the prediction task to build. - Should include: - - What entity to predict for (e.g., users, drivers) - - What to predict (e.g., churn, count of events, recommendations) - - Time window for prediction (optional, defaults to 30 days) - - Task type if known (classification, regression, recommendation) - - Returns: - Result of the task building process including generated code - """ - return self.agent.run(task_description) diff --git a/plexe/callbacks.py b/plexe/callbacks.py deleted file mode 100644 index ba848589..00000000 --- a/plexe/callbacks.py +++ /dev/null @@ -1,130 +0,0 @@ -""" -Callbacks for model building process in Plexe. - -This module defines callback interfaces that let users hook into various stages -of the model building process, allowing for custom logging, tracking, visualization, -or other operations to be performed at key points. -""" - -import logging -from abc import ABC -from dataclasses import dataclass -from typing import Optional, Type, Dict, Any - -from pydantic import BaseModel - -from plexe.internal.common.datasets.interface import TabularConvertible -from plexe.core.entities.solution import Solution - -logger = logging.getLogger(__name__) - - -@dataclass -class BuildStateInfo: - """ - Consolidated information about model build state at any point in the process. - - This class combines all information available during different stages of the model building - process (start, end, iteration start, iteration end) into a single structure. - """ - - # Common identification fields - intent: str - """The natural language description of the model's intent.""" - - provider: str - """The provider (LLM) used for generating the model.""" - - # Schema fields - input_schema: Optional[Type[BaseModel]] = None - """The input schema for the model.""" - - output_schema: Optional[Type[BaseModel]] = None - """The output schema for the model.""" - - run_timeout: Optional[int] = None - """Maximum time in seconds for each individual training run.""" - - max_iterations: Optional[int] = None - """Maximum number of iterations for the model building process.""" - - timeout: Optional[int] = None - """Maximum total time in seconds for the entire model building process.""" - - # Iteration fields - iteration: int = 0 - """Current iteration number (0-indexed).""" - - # Dataset fields - datasets: Optional[Dict[str, TabularConvertible]] = None - - # Current node being evaluated - node: Optional[Solution] = None - """The solution node being evaluated in the current iteration.""" - - # Model information fields (replacing direct model reference) - model_identifier: Optional[str] = None - """Model unique identifier.""" - - model_state: Optional[str] = None - """Current model state (BUILDING/READY/ERROR).""" - - # Final model artifacts (only available at build end) - final_metric: Optional[Any] = None - """Final performance metric.""" - - final_artifacts: Optional[list] = None - """Model artifacts list.""" - - trainer_source: Optional[str] = None - """Training source code.""" - - predictor_source: Optional[str] = None - """Predictor source code.""" - - -class Callback(ABC): - """ - Abstract base class for callbacks during model building. - - Callbacks allow running custom code at various stages of the model building process. - Subclass this and implement the methods you need for your specific use case. - """ - - def on_build_start(self, info: BuildStateInfo) -> None: - """ - Called when the model building process starts. - """ - pass - - def on_build_end(self, info: BuildStateInfo) -> None: - """ - Called when the model building process ends. - """ - pass - - def on_iteration_start(self, info: BuildStateInfo) -> None: - """ - Called at the start of each model building iteration. - """ - pass - - def on_iteration_end(self, info: BuildStateInfo) -> None: - """ - Called at the end of each model building iteration. - """ - pass - - -# Import at the end to avoid circular dependencies -from plexe.internal.models.callbacks.mlflow import MLFlowCallback -from plexe.internal.models.callbacks.chain_of_thought import ChainOfThoughtModelCallback -from plexe.internal.models.callbacks.checkpoint import ModelCheckpointCallback - -__all__ = [ - "Callback", - "BuildStateInfo", - "MLFlowCallback", - "ChainOfThoughtModelCallback", - "ModelCheckpointCallback", -] diff --git a/plexe/config.py b/plexe/config.py deleted file mode 100644 index e9092edc..00000000 --- a/plexe/config.py +++ /dev/null @@ -1,346 +0,0 @@ -""" -Configuration for the plexe library. -""" - -import importlib -import logging -import warnings -from dataclasses import dataclass, field -from importlib.resources import files -from typing import List -from functools import cached_property -from jinja2 import Environment, FileSystemLoader -import sys -from pathlib import Path - -from plexe import templates as template_module - - -TEMPLATE_DIR = files("plexe").joinpath("templates/prompts") - - -# configure warnings -warnings.filterwarnings("ignore", category=FutureWarning) -warnings.filterwarnings("ignore", category=DeprecationWarning) - - -def is_package_available(package_name: str) -> bool: - """Check if a Python package is available/installed.""" - try: - importlib.import_module(package_name) - return True - except ImportError: - return False - - -@dataclass(frozen=True) -class _Config: - @dataclass(frozen=True) - class _FileStorageConfig: - cache_dir: str = field(default=".plexecache/") - model_dir: str = field(default="model_files/") - checkpoint_dir: str = field(default="checkpoints/") - delete_checkpoints_on_success: bool = field(default=False) - keep_checkpoints: int = field(default=3) - - @dataclass(frozen=True) - class _LoggingConfig: - level: str = field(default="INFO") - format: str = field(default="[%(asctime)s - %(name)s - %(levelname)s - (%(threadName)-10s)]: - %(message)s") - - @dataclass(frozen=True) - class _ModelSearchConfig: - initial_nodes: int = field(default=3) - max_nodes: int = field(default=15) - max_fixing_attempts_train: int = field(default=3) - max_fixing_attempts_predict: int = field(default=10) - max_time_elapsed: int = field(default=600) - - @dataclass(frozen=True) - class _ExecutionConfig: - runfile_name: str = field(default="execution_script.py") - - @dataclass(frozen=True) - class _CodeGenerationConfig: - # Base ML packages that are always available - _base_packages: List[str] = field( - default_factory=lambda: [ - "pandas", - "numpy", - "sklearn", - "joblib", - "mlxtend", - "xgboost", - "pyarrow", - "statsmodels", - "sqlalchemy", - "psycopg2", - "torch", - "torch_geometric", - ] - ) - - # Deep learning packages that are optional - _deep_learning_packages: List[str] = field( - default_factory=lambda: [ - "tensorflow-cpu", - "torch", - "transformers", - "tokenizers", - "accelerate", - "safetensors", - "torch_geometric", - ] - ) - - # Additional standard library modules for agent execution - _standard_lib_modules: List[str] = field( - default_factory=lambda: [ - "pathlib", - "typing", - "dataclasses", - "json", - "io", - "time", - "datetime", - "os", - "sys", - "math", - "random", - "itertools", - "collections", - "functools", - "operator", - "re", - "copy", - "warnings", - "logging", - "importlib", - "types", - "plexe", - "ast", - ] - ) - - @property - def allowed_packages(self) -> List[str]: - """Dynamically determine which packages are available and can be used.""" - available_packages = self._base_packages.copy() - - # Check if deep learning packages are installed and add them if they are - for package in self._deep_learning_packages: - if is_package_available(package): - available_packages.append(package) - - return available_packages - - @property - def authorized_agent_imports(self) -> List[str]: - """Return the combined list of allowed packages and standard library modules for agent execution.""" - # Start with allowed packages - imports = self.allowed_packages.copy() - - # Add wildcard imports for all allowed packages - imports.extend([f"{pkg}.*" for pkg in self.allowed_packages]) - - # Add standard library modules - imports.extend(self._standard_lib_modules) - - return imports - - @property - def deep_learning_available(self) -> bool: - """Check if deep learning packages are available.""" - return any(is_package_available(pkg) for pkg in self._deep_learning_packages) - - k_fold_validation: int = field(default=5) - - @dataclass(frozen=True) - class _DataGenerationConfig: - pass # todo: implement - - @dataclass(frozen=True) - class _RayConfig: - address: str = field(default=None) # None for local, Ray address for remote - num_cpus: int = field(default=None) # None for auto-detect - num_gpus: int = field(default=None) # None for auto-detect - - # configuration objects - file_storage: _FileStorageConfig = field(default_factory=_FileStorageConfig) - logging: _LoggingConfig = field(default_factory=_LoggingConfig) - model_search: _ModelSearchConfig = field(default_factory=_ModelSearchConfig) - code_generation: _CodeGenerationConfig = field(default_factory=_CodeGenerationConfig) - execution: _ExecutionConfig = field(default_factory=_ExecutionConfig) - data_generation: _DataGenerationConfig = field(default_factory=_DataGenerationConfig) - ray: _RayConfig = field(default_factory=_RayConfig) - - -@dataclass(frozen=True) -class _CodeTemplates: - predictor_interface: str = field( - default=Path(importlib.import_module("plexe.core.interfaces.predictor").__file__).read_text() - ) - predictor_template: str = field( - default=files(template_module).joinpath("models").joinpath("predictor.tmpl.py").read_text() - ) - feature_transformer_interface: str = field( - default=Path(importlib.import_module("plexe.core.interfaces.feature_transformer").__file__).read_text() - ) - feature_transformer_template: str = field( - default=files(template_module).joinpath("models").joinpath("feature_transformer.tmpl.py").read_text() - ) - - -@dataclass(frozen=True) -class _PromptTemplates: - template_dir: str = field(default=TEMPLATE_DIR) - - @cached_property - def env(self) -> Environment: - return Environment(loader=FileSystemLoader(str(self.template_dir))) - - def _render(self, template_name: str, **kwargs) -> str: - template = self.env.get_template(template_name) - return template.render(**kwargs) - - def planning_system(self) -> str: - return self._render("planning/system_prompt.jinja") - - def planning_select_metric(self, problem_statement) -> str: - return self._render("planning/select_metric.jinja", problem_statement=problem_statement) - - def schema_base(self) -> str: - return self._render("schemas/base.jinja") - - def schema_identify_target(self, columns, intent) -> str: - return self._render("schemas/identify_target.jinja", columns=columns, intent=intent) - - def schema_generate_from_intent(self, intent, input_schema="input_schema", output_schema="output_schema") -> str: - return self._render( - "schemas/generate_from_intent.jinja", intent=intent, input_schema=input_schema, output_schema=output_schema - ) - - def training_system(self) -> str: - return self._render("training/system_prompt.jinja") - - def training_generate( - self, problem_statement, plan, history, allowed_packages, training_data_files, validation_data_files - ) -> str: - return self._render( - "training/generate.jinja", - problem_statement=problem_statement, - plan=plan, - history=history, - allowed_packages=allowed_packages, - training_data_files=training_data_files, - validation_data_files=validation_data_files, - use_validation_files=len(validation_data_files) > 0, - ) - - def training_fix( - self, training_code, plan, review, problems, allowed_packages, training_data_files, validation_data_files - ) -> str: - return self._render( - "training/fix.jinja", - training_code=training_code, - plan=plan, - review=review, - problems=problems, - allowed_packages=allowed_packages, - training_data_files=training_data_files, - validation_data_files=validation_data_files, - use_validation_files=len(validation_data_files) > 0, - ) - - def training_review(self, problem_statement, plan, training_code, problems, allowed_packages) -> str: - return self._render( - "training/review.jinja", - problem_statement=problem_statement, - plan=plan, - training_code=training_code, - problems=problems, - allowed_packages=allowed_packages, - ) - - def review_system(self) -> str: - return self._render("review/system_prompt.jinja") - - def review_model( - self, - intent: str, - input_schema: str, - output_schema: str, - solution_plan: str, - training_code: str, - inference_code: str, - ) -> str: - return self._render( - "review/model.jinja", - intent=intent, - input_schema=input_schema, - output_schema=output_schema, - solution_plan=solution_plan, - training_code=training_code, - inference_code=inference_code, - ) - - def cot_system(self) -> str: - return self._render("utils/system_prompt.jinja") - - def cot_summarize(self, context: str) -> str: - return self._render("utils/cot_summarize.jinja", context=context) - - def agent_builder_prompt( - self, - intent: str, - input_schema: str, - output_schema: str, - datasets: List[str], - working_dir: str, - max_iterations: int = None, - resume: bool = False, - ) -> str: - return self._render( - "agent/agent_manager_prompt.jinja", - intent=intent, - input_schema=input_schema, - output_schema=output_schema, - datasets=datasets, - working_dir=working_dir, - max_iterations=max_iterations, - resume=resume, - ) - - -# Instantiate configuration and templates -config: _Config = _Config() -code_templates: _CodeTemplates = _CodeTemplates() -prompt_templates: _PromptTemplates = _PromptTemplates() - - -# Default logging configuration -def configure_logging(level: str | int = logging.INFO, file: str = None) -> None: - # Configure the library's root logger - sm_root_logger = logging.getLogger("plexe") - sm_root_logger.setLevel(level) - - # Clear existing handlers to avoid duplicate logs - sm_root_logger.handlers = [] - - # Define a common formatter - formatter = logging.Formatter(config.logging.format) - - stream_handler = logging.StreamHandler() - # Only apply reconfigure if the stream supports it - if hasattr(sys.stdout, "reconfigure"): - sys.stdout.reconfigure(encoding="utf-8") - stream_handler.setFormatter(formatter) - sm_root_logger.addHandler(stream_handler) - - if file: - file_handler = logging.FileHandler(file, encoding="utf-8") - file_handler.setFormatter(formatter) - sm_root_logger.addHandler(file_handler) - - -configure_logging(level=config.logging.level) diff --git a/plexe/core/__init__.py b/plexe/core/__init__.py deleted file mode 100644 index 5070f9de..00000000 --- a/plexe/core/__init__.py +++ /dev/null @@ -1,7 +0,0 @@ -""" -Core types and functions used across Plexe. - -This package contains fundamental types and functions used throughout the Plexe codebase. -It's designed to avoid circular dependencies by providing core functionality that can -be imported by multiple modules. -""" diff --git a/plexe/core/entities/__init__.py b/plexe/core/entities/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/plexe/core/entities/solution.py b/plexe/core/entities/solution.py deleted file mode 100644 index 00f55f87..00000000 --- a/plexe/core/entities/solution.py +++ /dev/null @@ -1,72 +0,0 @@ -""" -This module defines the `Solution` class used to represent complete ML pipelines. - -A Solution encapsulates all artifacts produced throughout the ML workflow for a single -approach, including the initial plan, feature transformations, model training code, -inference code, performance metrics, and deployment artifacts. Each Solution represents -one experimental path from data processing through model deployment. -""" - -import time -import uuid -from dataclasses import dataclass, field -from typing import List, Dict - -from plexe.internal.models.entities.artifact import Artifact -from plexe.internal.models.entities.metric import Metric - - -@dataclass(eq=False) -class Solution: - """ - Represents a complete ML solution from planning through deployment. - - A Solution is a container for all artifacts related to a single ML approach, - allowing different experiments to maintain their own schemas, transformations, - and implementations. Solutions persist throughout the workflow and contain - the final deployable model components. - - Attributes: - id (str): A unique identifier for the solution. - created_time (float): The UNIX timestamp when the solution was created. - plan (str): The ML approach description and strategy for this solution. - training_code (str): The model training implementation code. - inference_code (str): The production inference/prediction code. - input_schema (Dict[str, str]): Schema for the input data expected by the model. - output_schema (Dict[str, str]): Schema for the output data produced by the model. - performance (Metric): Validation set performance metrics. - test_performance (Metric): Test set performance metrics. - execution_time (float): Time taken to train the model. - execution_stdout (list[str]): Training execution logs and output. - exception_was_raised (bool): Whether training failed with an exception. - exception (Exception): The exception raised during training, if any. - model_artifacts (List[Path]): Paths to serialized model files and other artifacts. - analysis (str): Summary analysis of the solution's effectiveness. - """ - - # General attributes - id: str = field(default_factory=lambda: uuid.uuid4().hex, kw_only=True) - created_time: float = field(default_factory=lambda: time.time(), kw_only=True) - - # Core solution attributes - plan: str = field(default=None, hash=True, kw_only=True) - training_code: str = field(default=None, hash=True, kw_only=True) - inference_code: str = field(default=None, hash=True, kw_only=True) - testing_code: str = field(default=None, hash=True, kw_only=True) - input_schema: Dict[str, str] = field(default=None, kw_only=True) - output_schema: Dict[str, str] = field(default=None, kw_only=True) - schema_reasoning: str = field(default=None, kw_only=True) # Explanation of schema design - - # Post-execution results: model performance, execution time, exceptions, etc. - performance: Metric = field(default=None, kw_only=True) # Validation performance - test_performance: Metric = field(default=None, kw_only=True) # Test set performance - execution_time: float = field(default=None, kw_only=True) - execution_stdout: list[str] = field(default_factory=list, kw_only=True) - exception_was_raised: bool = field(default=False, kw_only=True) - exception: Exception = field(default=None, kw_only=True) - model_artifacts: List[Artifact] = field(default_factory=list, kw_only=True) - - # Evaluations and analyses - analysis: str = field(default=None, kw_only=True) - review: Dict[str, str] = field(default=None, kw_only=True) - model_evaluation_report: Dict[str, any] = field(default_factory=dict, kw_only=True) diff --git a/plexe/core/interfaces/__init__.py b/plexe/core/interfaces/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/plexe/core/interfaces/feature_transformer.py b/plexe/core/interfaces/feature_transformer.py deleted file mode 100644 index efeb48bb..00000000 --- a/plexe/core/interfaces/feature_transformer.py +++ /dev/null @@ -1,20 +0,0 @@ -""" -This module defines the FeatureTransformer interface, which all generated feature transformers must implement. -""" - -from abc import ABC, abstractmethod - -import pandas as pd - - -class FeatureTransformer(ABC): - """ - Abstract base class for all dynamically generated feature transformers. - - Every implementation of feature transformer must provide a mechanism for transforming the input data - into the format required by the model. - """ - - @abstractmethod - def transform(self, inputs: pd.DataFrame) -> pd.DataFrame: - pass diff --git a/plexe/core/interfaces/predictor.py b/plexe/core/interfaces/predictor.py deleted file mode 100644 index 0f60c77d..00000000 --- a/plexe/core/interfaces/predictor.py +++ /dev/null @@ -1,24 +0,0 @@ -""" -This module defines the Predictor interface, which all dynamically generated inference codes must implement. -""" - -from abc import ABC, abstractmethod -from typing import List -from plexe.internal.models.entities.artifact import Artifact - - -class Predictor(ABC): - """ - Abstract base class for all dynamically generated inference code. - - Every implementation of predictor must provide a mechanism for instantiating the underlying model(s) - by reading the binary or text data from the `ModelArtifact` class. - """ - - @abstractmethod - def __init__(self, artifacts: List[Artifact]): - pass - - @abstractmethod - def predict(self, inputs: dict) -> dict: - pass diff --git a/plexe/core/object_registry.py b/plexe/core/object_registry.py deleted file mode 100644 index 821babf9..00000000 --- a/plexe/core/object_registry.py +++ /dev/null @@ -1,197 +0,0 @@ -""" -This module provides a generic Registry pattern implementation for storing and retrieving objects by name or prefix. -""" - -import logging -import dataclasses -import copy -from typing import Dict, List, Type, TypeVar, Any - - -T = TypeVar("T") -logger = logging.getLogger(__name__) - - -@dataclasses.dataclass -class Item: - item: T - immutable: bool = False - - -class ObjectRegistry: - """ - Registry for storing and retrieving objects by name. - - This class implements the Singleton pattern so that registry instances are shared - across the application. It provides methods for registering, retrieving, and - managing objects in a type-safe manner. - """ - - _instance = None - - def __new__(cls): - if cls._instance is None: - cls._instance = super(ObjectRegistry, cls).__new__(cls) - cls._instance._items = {} - return cls._instance - - @staticmethod - def _get_uri(t: Type[T], name: str) -> str: - return f"{str(t)}://{name}" - - def register(self, t: Type[T], name: str, item: T, overwrite: bool = False, immutable: bool = False) -> None: - """ - Register an item with a given name. - - :param t: type prefix for the item - :param name: identifier for the item - must be unique within the prefix - :param item: the item to register - :param overwrite: whether to overwrite an existing item with the same name - :param immutable: whether the item should be treated as immutable (not modifiable) - """ - uri = self._get_uri(t, name) - was_overwrite = overwrite and uri in self._items - - if not overwrite and uri in self._items: - raise ValueError(f"Item '{uri}' already registered, use a different name") - - self._items[uri] = Item(item, immutable=immutable) - - # Enhanced logging with context - action = "overwrote" if was_overwrite else "registered" - logger.info(f"Registry: {action} {uri} (immutable={immutable}, total: {len(self._items)} items)") - - def register_multiple( - self, t: Type[T], items: Dict[str, T], overwrite: bool = False, immutable: bool = False - ) -> None: - """ - Register multiple items with a given prefix. - - :param t: type prefix for the items - :param overwrite: whether to overwrite existing items with the same names - :param immutable: whether the items should be treated as immutable (not modifiable) - :param items: dictionary of item names and their corresponding objects - """ - for name, item in items.items(): - self.register(t, name, item, overwrite=overwrite, immutable=immutable) - - def get(self, t: Type[T], name: str) -> T: - """ - Retrieve an item by name. - - :param t: type prefix for the item - :param name: the name of the item to retrieve - :return: The registered item - :raises KeyError: If the item is not found in the registry - """ - uri = self._get_uri(t, name) - if uri not in self._items: - logger.warning(f"⚠️ Item '{uri}' not found in registry") - raise KeyError(f"Item '{uri}' not found in registry") - logger.info(f"Registry: Retrieved {uri} (immutable={self._items[uri].immutable})") - return self._items[uri].item if not self._items[uri].immutable else copy.deepcopy(self._items[uri].item) - - def get_multiple(self, t: Type[T], names: List[str]) -> Dict[str, T]: - """ - Retrieve multiple items by name. - - :param t: type prefix for the items - :param names: List of item names to retrieve - :return: Dictionary mapping item names to items - :raises KeyError: If any item is not found in the registry - """ - return {name: self.get(t, name) for name in names} - - def get_all(self, t: Type[T]) -> Dict[str, T]: - """ - Retrieve all items for a given prefix. - - :param t: type prefix for the items - :return: Dictionary mapping item names to items - """ - return {name: item.item for name, item in self._items.items() if name.startswith(str(t))} - - def delete(self, t: Type[T], name: str) -> None: - """ - Delete an item by name. - - :param t: type prefix for the item - :param name: the name of the item to delete - """ - uri = self._get_uri(t, name) - if uri in self._items: - del self._items[uri] - else: - raise KeyError(f"Item '{uri}' not found in registry") - - def clear(self) -> None: - """ - Clear all registered items. - """ - self._items.clear() - - def list(self) -> List[str]: - """ - List all registered item names. - - :return: List of item names in the registry - """ - return list(self._items.keys()) - - def list_by_type(self, t: Type[T]) -> List[str]: - """ - List all registered names for a specific type. - - :param t: type prefix for the items - :return: List of item names (without the type prefix) for the given type - """ - prefix = str(t) - return [uri.split("://")[1] for uri in self._items.keys() if uri.startswith(prefix)] - - # TODO: unclear if this is needed, consider deleting - def get_all_solutions(self) -> List[Dict[str, Any]]: - """ - Get all solutions tracked during model building. - - This method extracts solution information from the registry, focusing on - code, performance metrics, and other solution-specific data for checkpointing. - - :return: List of solution data dictionaries - """ - solutions = [] - - # Extract training code and their results - from plexe.internal.models.entities.code import Code - from plexe.core.entities.solution import Solution - - # Get all code objects - code_items = self.get_all(Code) - node_items = self.get_all(Solution) - - # Build solution data from code and node objects - for uri, code_obj in code_items.items(): - if isinstance(code_obj, Code): - # Extract code ID and try to find associated node - code_id = uri.split("://")[1] - solution_data = { - "code_id": code_id, - "code": code_obj.code, - "iteration": getattr(code_obj, "iteration", 0), - } - - # Look for associated node to get performance metrics - for node_uri, node in node_items.items(): - if isinstance(node, Solution) and node.training_code == code_obj.code: - if node.performance: - solution_data["performance"] = { - "name": node.performance.name, - "value": node.performance.value, - "comparison_method": getattr( - node.performance.comparator, "comparison_method", "HIGHER_IS_BETTER" - ), - } - break - - solutions.append(solution_data) - - return solutions diff --git a/plexe/core/state.py b/plexe/core/state.py deleted file mode 100644 index 1cc8a713..00000000 --- a/plexe/core/state.py +++ /dev/null @@ -1,23 +0,0 @@ -""" -Model state definitions for Plexe. - -This module defines the possible states a model can be in during its lifecycle. -""" - -from enum import Enum - - -class ModelState(Enum): - """States a model can be in during its lifecycle.""" - - DRAFT = "draft" - """Model is in draft state, not yet built.""" - - BUILDING = "building" - """Model is currently being built.""" - - READY = "ready" - """Model is built and ready to use.""" - - ERROR = "error" - """Model encountered an error during building.""" diff --git a/plexe/core/storage.py b/plexe/core/storage.py deleted file mode 100644 index 2674026c..00000000 --- a/plexe/core/storage.py +++ /dev/null @@ -1,588 +0,0 @@ -""" -Core storage functions for model and checkpoint persistence. - -This module contains implementation logic for saving and loading models and checkpoints, -without direct dependencies on the Model class. It provides a foundation for the -fileio module, breaking the circular dependency between models.py and fileio.py. -""" - -import io -import json -import yaml -import logging -import tarfile -import datetime -from pathlib import Path -from typing import Any, Dict, List, Optional, TypeVar, Type -import numpy as np - -from plexe.core.state import ModelState -from plexe.config import config -from plexe.internal.common.utils.pydantic_utils import map_to_basemodel - -logger = logging.getLogger(__name__) - -# Type variable for generic model type -M = TypeVar("M") - - -class FallbackNoneLoader(yaml.SafeLoader): - pass - - -def fallback_to_none(loader, tag_suffix, node): - return None - - -FallbackNoneLoader.add_multi_constructor("", fallback_to_none) - - -def _convert_to_native_types(obj): - """Recursively convert numpy types and other non-native types to Python native types. - - Falls back to string representation for any type that can't be converted. - """ - try: - # Handle NumPy types specifically - if isinstance(obj, np.generic): - return _convert_to_native_types(obj.item()) - elif isinstance(obj, np.ndarray): - return _convert_to_native_types(obj.tolist()) - # Handle common collections - elif isinstance(obj, dict): - return {k: _convert_to_native_types(v) for k, v in obj.items()} - elif isinstance(obj, (list, tuple)): - return type(obj)(_convert_to_native_types(item) for item in obj) - # Native types are already safe - elif isinstance(obj, (str, int, float, bool, type(None))): - return obj - # For other types, raise error to trigger fallback - else: - raise TypeError(f"Unsupported type: {type(obj).__name__}") - except Exception as e: - # Fallback: if anything goes wrong, use JSON serialization with sanitization - logger.warning( - f"Failed to convert object of type {type(obj).__name__} for serialization: {e}. Using string representation." - ) - return json.loads(json.dumps(obj, skipkeys=True, default=str)) - - -def _load_yaml_or_json_from_tar(tar, yaml_path: str, json_path: str): - """Load from YAML if available, fallback to JSON for backward compatibility.""" - members = [m.name for m in tar.getmembers()] - if yaml_path in members: - content = tar.extractfile(yaml_path).read().decode("utf-8") - return yaml.load(content, Loader=FallbackNoneLoader) - elif json_path in members: - content = tar.extractfile(json_path).read().decode("utf-8") - return json.loads(content) - else: - raise FileNotFoundError(f"Neither {yaml_path} nor {json_path} found in archive") - - -def _save_model_to_tar(model: Any, path: str | Path) -> str: - """ - Core implementation of saving a model to a tar archive. - - Args: - model: The model to save (any object with required attributes) - path: Path where to save the model - - Returns: - Path where the model was saved - """ - # Ensure .tar.gz extension - if not str(path).endswith(".tar.gz"): - raise ValueError("Path must end with .tar.gz") - - # Ensure parent directory exists - Path(path).parent.mkdir(parents=True, exist_ok=True) - - try: - with tarfile.open(path, "w:gz") as tar: - # Get metrics data if available - metrics_data = {} - if hasattr(model, "metric") and model.metric: - metrics_data = { - "name": model.metric.name, - "value": _convert_to_native_types(model.metric.value), - "comparison_method": model.metric.comparator.comparison_method.value, - "target": _convert_to_native_types(model.metric.comparator.target), - } - - # Gather metadata - metadata = { - "intent": model.intent, - "state": model.state.value, - "metrics": metrics_data, - "metadata": model.metadata, - "identifier": model.identifier, - } - - # Save each metadata item separately - for key, value in metadata.items(): - if key in ["metrics", "metadata"]: - info = tarfile.TarInfo(f"metadata/{key}.yaml") - # Ensure all values are serializable - safe_value = _convert_to_native_types(value) - content = yaml.safe_dump(safe_value, default_flow_style=False).encode("utf-8") - else: - info = tarfile.TarInfo(f"metadata/{key}.txt") - content = str(value).encode("utf-8") - info.size = len(content) - tar.addfile(info, io.BytesIO(content)) - - # Save schemas - for name, schema in [("input_schema", model.input_schema), ("output_schema", model.output_schema)]: - schema_dict = {name: field.annotation.__name__ for name, field in schema.model_fields.items()} - info = tarfile.TarInfo(f"schemas/{name}.yaml") - content = yaml.safe_dump(schema_dict, default_flow_style=False).encode("utf-8") - info.size = len(content) - tar.addfile(info, io.BytesIO(content)) - - # Save trainer source if available - if hasattr(model, "trainer_source") and model.trainer_source: - info = tarfile.TarInfo("code/trainer.py") - content = model.trainer_source.encode("utf-8") - info.size = len(content) - tar.addfile(info, io.BytesIO(content)) - - # Save predictor source if available - if hasattr(model, "predictor_source") and model.predictor_source: - info = tarfile.TarInfo("code/predictor.py") - content = model.predictor_source.encode("utf-8") - info.size = len(content) - tar.addfile(info, io.BytesIO(content)) - - # Save feature transformer source if available - if hasattr(model, "feature_transformer_source") and model.feature_transformer_source: - info = tarfile.TarInfo("code/feature_transformer.py") - content = model.feature_transformer_source.encode("utf-8") - info.size = len(content) - tar.addfile(info, io.BytesIO(content)) - - # Save dataset splitter source if available - if hasattr(model, "dataset_splitter_source") and model.dataset_splitter_source: - info = tarfile.TarInfo("code/dataset_splitter.py") - content = model.dataset_splitter_source.encode("utf-8") - info.size = len(content) - tar.addfile(info, io.BytesIO(content)) - - # Save testing source if available - if hasattr(model, "testing_source") and model.testing_source: - info = tarfile.TarInfo("code/testing.py") - content = model.testing_source.encode("utf-8") - info.size = len(content) - tar.addfile(info, io.BytesIO(content)) - - # Save evaluation report if available - if hasattr(model, "evaluation_report") and model.evaluation_report: - info = tarfile.TarInfo("metadata/evaluation_report.yaml") - # Convert numpy types to native Python types before serialization - evaluation_report_native = _convert_to_native_types(model.evaluation_report) - content = yaml.safe_dump(evaluation_report_native, default_flow_style=False).encode("utf-8") - info.size = len(content) - tar.addfile(info, io.BytesIO(content)) - - # Save artifacts - if hasattr(model, "artifacts"): - for artifact in model.artifacts: - arc_name = f"artifacts/{Path(artifact.name).as_posix()}" - info = tarfile.TarInfo(arc_name) - - if artifact.is_path(): - with open(artifact.path, "rb") as f: - content = f.read() - elif artifact.is_handle(): - content = artifact.handle.read() - else: - content = artifact.data - - info.size = len(content) - tar.addfile(info, io.BytesIO(content)) - - # Save EDA markdown reports if available - if ( - hasattr(model, "metadata") - and "eda_markdown_reports" in model.metadata - and model.metadata["eda_markdown_reports"] - ): - for dataset_name, report_markdown in model.metadata["eda_markdown_reports"].items(): - info = tarfile.TarInfo(f"metadata/eda_report_{dataset_name}.md") - content = report_markdown.encode("utf-8") - info.size = len(content) - tar.addfile(info, io.BytesIO(content)) - - except Exception as e: - logger.error(f"Error saving model: {e}") - if Path(path).exists(): - Path(path).unlink() - raise - - logger.info(f"Model saved to {path}") - return str(path) - - -def _load_model_data_from_tar(path: str | Path) -> Dict[str, Any]: - """ - Core implementation of loading model data from a tar archive. - - Args: - path: Path to the model archive - - Returns: - Dictionary with model data to reconstruct a Model instance - """ - if not Path(path).exists(): - raise ValueError(f"Model not found: {path}") - - try: - with tarfile.open(path, "r:gz") as tar: - # Extract metadata - intent = tar.extractfile("metadata/intent.txt").read().decode("utf-8") - state = ModelState(tar.extractfile("metadata/state.txt").read().decode("utf-8")) - metrics_data = _load_yaml_or_json_from_tar(tar, "metadata/metrics.yaml", "metadata/metrics.json") - metadata = _load_yaml_or_json_from_tar(tar, "metadata/metadata.yaml", "metadata/metadata.json") - identifier = tar.extractfile("metadata/identifier.txt").read().decode("utf-8") - - # Extract schema information - input_schema_dict = _load_yaml_or_json_from_tar( - tar, "schemas/input_schema.yaml", "schemas/input_schema.json" - ) - output_schema_dict = _load_yaml_or_json_from_tar( - tar, "schemas/output_schema.yaml", "schemas/output_schema.json" - ) - - # Process schemas into Pydantic models - input_schema = _process_schema_dict(input_schema_dict) - output_schema = _process_schema_dict(output_schema_dict) - - # Extract code if available - trainer_source = None - if "code/trainer.py" in [m.name for m in tar.getmembers()]: - trainer_source = tar.extractfile("code/trainer.py").read().decode("utf-8") - - predictor_source = None - if "code/predictor.py" in [m.name for m in tar.getmembers()]: - predictor_source = tar.extractfile("code/predictor.py").read().decode("utf-8") - # FIXME: this is a hack required to ensure backwards compatibility with old models - predictor_source = predictor_source.replace("plexe.internal.models.interfaces", "plexe.core.interfaces") - - feature_transformer_source = None - if "code/feature_transformer.py" in [m.name for m in tar.getmembers()]: - feature_transformer_source = tar.extractfile("code/feature_transformer.py").read().decode("utf-8") - - dataset_splitter_source = None - if "code/dataset_splitter.py" in [m.name for m in tar.getmembers()]: - dataset_splitter_source = tar.extractfile("code/dataset_splitter.py").read().decode("utf-8") - - testing_source = None - if "code/testing.py" in [m.name for m in tar.getmembers()]: - testing_source = tar.extractfile("code/testing.py").read().decode("utf-8") - - evaluation_report = None - try: - evaluation_report = _load_yaml_or_json_from_tar( - tar, "metadata/evaluation_report.yaml", "metadata/evaluation_report.json" - ) - except FileNotFoundError: - pass - - # Load EDA markdown reports if available - eda_markdown_reports = {} - for member in tar.getmembers(): - if member.name.startswith("metadata/eda_report_") and member.name.endswith(".md"): - dataset_name = member.name.replace("metadata/eda_report_", "").replace(".md", "") - report_content = tar.extractfile(member).read().decode("utf-8") - eda_markdown_reports[dataset_name] = report_content - - # Collect artifact data - artifact_data = [] - for member in tar.getmembers(): - if member.name.startswith("artifacts/") and not member.isdir(): - file_data = tar.extractfile(member) - if file_data: - artifact_data.append({"name": Path(member.name).name, "data": file_data.read()}) - - # Prepare result dictionary with both raw schema dicts and processed schemas - model_data = { - "intent": intent, - "state": state, - "metadata": metadata, - "identifier": identifier, - "trainer_source": trainer_source, - "predictor_source": predictor_source, - "feature_transformer_source": feature_transformer_source, - "dataset_splitter_source": dataset_splitter_source, - "testing_source": testing_source, - "evaluation_report": evaluation_report, - "artifact_data": artifact_data, - "input_schema_dict": input_schema_dict, - "output_schema_dict": output_schema_dict, - "input_schema": input_schema, - "output_schema": output_schema, - "metrics_data": metrics_data, - } - - # Add EDA reports if found - if eda_markdown_reports: - model_data["eda_markdown_reports"] = eda_markdown_reports - - logger.debug(f"Model data successfully loaded from {path}") - return model_data - - except Exception as e: - logger.error(f"Error loading model: {e}") - raise - - -def _save_checkpoint_to_tar(model: Any, iteration: int, path: Optional[str | Path] = None) -> str: - """ - Core implementation of saving a checkpoint to a tar archive. - - Args: - model: The model to checkpoint (any object with required attributes) - iteration: Current iteration number - path: Optional custom path - - Returns: - Path where the checkpoint was saved - """ - # Generate default path if not provided - if path is None: - timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S") - checkpoint_dir = Path(config.file_storage.cache_dir) / config.file_storage.checkpoint_dir - checkpoint_dir.mkdir(parents=True, exist_ok=True) - path = checkpoint_dir / f"{model.identifier}_{timestamp}.checkpoint.tar.gz" - - # Ensure .tar.gz extension - if not str(path).endswith(".tar.gz"): - raise ValueError("Path must end with .tar.gz") - - # Ensure parent directory exists - Path(path).parent.mkdir(parents=True, exist_ok=True) - - try: - with tarfile.open(path, "w:gz") as tar: - # Add checkpoint marker - info = tarfile.TarInfo("checkpoint.marker") - content = b"1" - info.size = len(content) - tar.addfile(info, io.BytesIO(content)) - - # Add current iteration - info = tarfile.TarInfo("metadata/iteration.txt") - content = str(iteration).encode("utf-8") - info.size = len(content) - tar.addfile(info, io.BytesIO(content)) - - # Add model metadata - metadata = { - "intent": model.intent, - "state": model.state.value, - "metadata": model.metadata, - "identifier": model.identifier, - } - - # Save each metadata item separately - for key, value in metadata.items(): - if key in ["metadata"]: - info = tarfile.TarInfo(f"metadata/{key}.yaml") - safe_value = _convert_to_native_types(value) - content = yaml.safe_dump(safe_value, default_flow_style=False).encode("utf-8") - else: - info = tarfile.TarInfo(f"metadata/{key}.txt") - content = str(value).encode("utf-8") - info.size = len(content) - tar.addfile(info, io.BytesIO(content)) - - # Save schemas - for name, schema in [("input_schema", model.input_schema), ("output_schema", model.output_schema)]: - schema_dict = {name: field.annotation.__name__ for name, field in schema.model_fields.items()} - info = tarfile.TarInfo(f"schemas/{name}.yaml") - content = yaml.safe_dump(schema_dict, default_flow_style=False).encode("utf-8") - info.size = len(content) - tar.addfile(info, io.BytesIO(content)) - - # Save previously tried solutions from the ObjectRegistry if available - solutions = [] - if hasattr(model, "object_registry") and hasattr(model.object_registry, "get_all_solutions"): - solutions = model.object_registry.get_all_solutions() - - if solutions: - solutions_data = json.dumps(solutions, default=str).encode("utf-8") - info = tarfile.TarInfo("solutions/solutions.json") - info.size = len(solutions_data) - tar.addfile(info, io.BytesIO(solutions_data)) - - except Exception as e: - logger.error(f"Error saving checkpoint: {e}") - if Path(path).exists(): - Path(path).unlink() - raise - - logger.info(f"Checkpoint saved to {path}") - return str(path) - - -def _load_checkpoint_data_from_tar(path: str | Path) -> Dict[str, Any]: - """ - Core implementation of loading checkpoint data from a tar archive. - - Args: - path: Path to the checkpoint archive - - Returns: - Dictionary with checkpoint data - """ - if not Path(path).exists(): - raise ValueError(f"Checkpoint not found: {path}") - - try: - with tarfile.open(path, "r:gz") as tar: - # Verify this is a checkpoint archive - if "checkpoint.marker" not in [m.name for m in tar.getmembers()]: - raise ValueError(f"Archive at {path} is not a valid checkpoint") - - # Extract metadata - intent = tar.extractfile("metadata/intent.txt").read().decode("utf-8") - state = ModelState(tar.extractfile("metadata/state.txt").read().decode("utf-8")) - metadata = _load_yaml_or_json_from_tar(tar, "metadata/metadata.yaml", "metadata/metadata.json") - identifier = tar.extractfile("metadata/identifier.txt").read().decode("utf-8") - iteration = int(tar.extractfile("metadata/iteration.txt").read().decode("utf-8")) - - # Extract schema information - input_schema_dict = _load_yaml_or_json_from_tar( - tar, "schemas/input_schema.yaml", "schemas/input_schema.json" - ) - output_schema_dict = _load_yaml_or_json_from_tar( - tar, "schemas/output_schema.yaml", "schemas/output_schema.json" - ) - - # Process schemas into Pydantic models - input_schema = _process_schema_dict(input_schema_dict) - output_schema = _process_schema_dict(output_schema_dict) - - # Extract previous solutions if available - solutions = [] - if "solutions/solutions.json" in [m.name for m in tar.getmembers()]: - solutions_json = tar.extractfile("solutions/solutions.json").read().decode("utf-8") - solutions = json.loads(solutions_json) - - # Prepare result dictionary with both raw schema dicts and processed schemas - checkpoint_data = { - "intent": intent, - "identifier": identifier, - "input_schema_dict": input_schema_dict, - "output_schema_dict": output_schema_dict, - "input_schema": input_schema, - "output_schema": output_schema, - "state": state, - "metadata": metadata, - "iteration": iteration, - "solutions": solutions, - } - - logger.debug(f"Checkpoint successfully loaded from {path}") - return checkpoint_data - - except Exception as e: - logger.error(f"Error loading checkpoint: {e}") - raise - - -def _list_checkpoint_files(model_id: Optional[str] = None) -> List[str]: - """ - Core implementation of listing checkpoint files. - - Args: - model_id: Optional model identifier to filter checkpoints - - Returns: - List of checkpoint paths - """ - checkpoint_dir = Path(config.file_storage.cache_dir) / config.file_storage.checkpoint_dir - if not checkpoint_dir.exists(): - return [] - - checkpoints = list(checkpoint_dir.glob("*.checkpoint.tar.gz")) - - if model_id: - checkpoints = [cp for cp in checkpoints if model_id in cp.stem] - - return [str(cp) for cp in checkpoints] - - -def _delete_checkpoint_file(path: str | Path) -> bool: - """ - Core implementation of deleting a checkpoint file. - - Args: - path: Path to the checkpoint to delete - - Returns: - True if deletion was successful, False otherwise - """ - try: - Path(path).unlink(missing_ok=True) - return True - except Exception as e: - logger.error(f"Error deleting checkpoint: {e}") - return False - - -def _clear_checkpoint_files(model_id: Optional[str] = None, older_than_days: Optional[int] = None) -> int: - """ - Core implementation of clearing checkpoints based on criteria. - - Args: - model_id: Optional model identifier to filter checkpoints - older_than_days: Optional age in days to filter checkpoints - - Returns: - Number of checkpoints deleted - """ - checkpoints = _list_checkpoint_files(model_id) - deleted_count = 0 - - # Apply age filter if provided - if older_than_days is not None: - cutoff_time = datetime.datetime.now() - datetime.timedelta(days=older_than_days) - checkpoints = [cp for cp in checkpoints if Path(cp).stat().st_mtime < cutoff_time.timestamp()] - - # Delete matching checkpoints - for cp in checkpoints: - if _delete_checkpoint_file(cp): - deleted_count += 1 - - return deleted_count - - -def _process_schema_dict(schema_dict: Dict[str, str]) -> Type: - """ - Process a schema dictionary to create a Pydantic model. - - Args: - schema_dict: Dictionary mapping field names to type names - - Returns: - A Pydantic model class - """ - - def type_from_name(type_name: str) -> type: - # Map string type names to actual Python types - type_map = { - "str": str, - "int": int, - "float": float, - "bool": bool, - "List[int]": List[int], - "List[float]": List[float], - "List[str]": List[str], - "List[bool]": List[bool], - } - return type_map[type_name] - - # Create a Pydantic model from the schema dictionary - schema_name = "Schema" # This will be overridden by map_to_basemodel - return map_to_basemodel(schema_name, {name: type_from_name(type_name) for name, type_name in schema_dict.items()}) diff --git a/plexe/datasets.py b/plexe/datasets.py deleted file mode 100644 index 714fc42f..00000000 --- a/plexe/datasets.py +++ /dev/null @@ -1,191 +0,0 @@ -""" -This module provides the Dataset class, which represents a collection of data that can be real, -synthetic, or a combination of both. - -The Dataset class offers functionalities for: -- Wrapping existing datasets (e.g. pandas DataFrames). -- Generating synthetic data based on a schema. -- Augmenting real datasets with additional synthetic samples. -- Iterating and accessing data samples conveniently. - -Users can either pass raw datasets directly to models or leverage this class for dataset management and augmentation. -""" - -from typing import Iterator, Type, Dict, Optional -import logging -import pandas as pd -from pydantic import BaseModel - -logger = logging.getLogger(__name__) - -from plexe.internal.common.datasets.interface import TabularConvertible -from plexe.internal.common.provider import Provider -from plexe.internal.common.datasets.adapter import DatasetAdapter -from plexe.internal.common.utils.pydantic_utils import merge_models, map_to_basemodel -from plexe.internal.schemas.resolver import SchemaResolver -from plexe.internal.datasets.generator import DatasetGenerator as DataGenerator - - -class DatasetGenerator: - """ - Represents a dataset, which can contain real data, synthetic data, or both. - - This class provides a structured way to manage data, allowing users to: - - Wrap real datasets (pandas etc.). - - Generate synthetic data from scratch. - - Augment existing datasets with synthetic samples. - - Add new columns to existing datasets using an extended schema. - - Example: - >>> synthetic_dataset = DatasetGenerator( - >>> description="Synthetic reviews", - >>> provider="openai/gpt-4o", - >>> schema=MovieReviewSchema, - >>> ) - >>> synthetic_dataset.generate(100) # Generate 100 samples - >>> model.build(datasets={"train": synthetic_dataset}) - """ - - def __init__( - self, - description: str, - provider: str, - schema: Type[BaseModel] | Dict[str, type] = None, - data: pd.DataFrame = None, - ) -> None: - """ - Initialize a new DatasetGenerator. - - :param description: A human-readable description of the dataset - :param provider: LLM provider used for synthetic data generation - :param schema: The schema the data should match, if any - :param data: A dataset of real data on which to base the generation, if available - """ - # Core attributes required for dataset generation - self.description = description - self.provider = Provider(provider) - - # Internal attributes for data management - self._data: Optional[pd.DataFrame] = None - self._index = 0 - self.schema = None - - # Process schema and data inputs - if schema is not None: - # Convert schema to Pydantic BaseModel if it's a dictionary - self.schema = map_to_basemodel("data", schema) - - if data is not None: - # Convert and validate input data - data_wrapper = DatasetAdapter.coerce(data) - if isinstance(data_wrapper, TabularConvertible): - self._data = data_wrapper.to_pandas() - else: - raise ValueError("Dataset must be convertible to pandas DataFrame.") - - # If schema is provided, validate data against schema - # but only validate existing columns, not new ones being added - if schema is not None: - self._validate_schema(self._data, allow_new_columns=True) - # If no schema provided, infer it from data - else: - schemas = SchemaResolver(self.provider, self.description).resolve({"data": self._data}) - self.schema = merge_models("data", list(schemas)) - - # Initialize data generator - self.data_generator = DataGenerator(self.provider, self.description, self.schema) - - def generate(self, num_samples: int): - """ - Generate synthetic data samples or augment existing data. - - If num_samples is 0 and existing data is provided with a new schema, - this will transform the existing data to match the new schema (adding columns). - - :param num_samples: Number of new samples to generate - """ - generated_data = self.data_generator.generate(num_samples, self._data) - - if self._data is None: - self._data = generated_data - elif num_samples == 0: - # When num_samples is 0, we're just adding columns to existing data - # SimpleLLMDataGenerator.generate already handles this correctly by returning - # the existing data with new columns added, so we just replace _data directly - self._data = generated_data - else: - # When adding new rows, concatenate them with existing data - self._data = pd.concat([self._data, generated_data], ignore_index=True) - - def _validate_schema(self, data: pd.DataFrame, allow_new_columns: bool = False): - """ - Ensure data matches the schema by checking column presence. - - :param data: DataFrame to validate against the schema - :param allow_new_columns: If True, allow schema to have columns that don't exist in data yet - :raises ValueError: If required columns from schema are missing and not allowed - """ - for key in self.schema.model_fields.keys(): - if key not in data.columns: - if not allow_new_columns: - raise ValueError(f"Dataset does not match schema, missing column in dataset: {key}") - else: - # When augmenting with new columns, we'll skip validation for those columns - logger.debug(f"Allowing new column that will be added through augmentation: {key}") - - @property - def data(self) -> pd.DataFrame: - """ - Get the dataset as a pandas DataFrame. - - :return: The dataset as a DataFrame - :raises ValueError: If no data has been set or generated - """ - if self._data is None: - raise ValueError("No data has been set or generated. Call generate() first.") - return self._data - - def __len__(self) -> int: - """ - Get the number of samples in the dataset. - - :return: Number of rows in the dataset, or 0 if no data - """ - if self._data is not None: - return len(self._data) - return 0 - - def __iter__(self) -> Iterator: - """ - Get an iterator over the dataset rows. - - :return: Self as iterator - """ - self._index = 0 - return self - - def __next__(self): - """ - Get the next item when iterating over the dataset. - - :return: Dictionary representing the next row - :raises StopIteration: When all rows have been processed - """ - if self._data is None or self._index >= len(self): - raise StopIteration - - row = self._data.iloc[self._index].to_dict() - self._index += 1 - return row - - def __getitem__(self, index: int): - """ - Get a dataset item by index. - - :param index: Row index to retrieve - :return: Dictionary representing the row at the given index - :raises IndexError: If dataset is empty - """ - if self._data is None: - raise IndexError("Dataset is empty.") - return self._data.iloc[index].to_dict() diff --git a/plexe/execution_context.py b/plexe/execution_context.py deleted file mode 100644 index e2826566..00000000 --- a/plexe/execution_context.py +++ /dev/null @@ -1,18 +0,0 @@ - -import contextvars -from typing import Optional, Callable - -# Context variable to store the current chain of thought callable -_chain_of_thought_context = contextvars.ContextVar("chain_of_thought_context", default=None) - -def set_chain_of_thought_callable(callable_obj: Callable): - """Set the chain of thought callable for the current context.""" - return _chain_of_thought_context.set(callable_obj) - -def get_chain_of_thought_callable() -> Optional[Callable]: - """Get the chain of thought callable for the current context.""" - return _chain_of_thought_context.get() - -def reset_chain_of_thought_callable(token): - """Reset the chain of thought callable to its previous value.""" - _chain_of_thought_context.reset(token) diff --git a/plexe/fileio.py b/plexe/fileio.py deleted file mode 100644 index bee8787c..00000000 --- a/plexe/fileio.py +++ /dev/null @@ -1,277 +0,0 @@ -""" -This module provides file I/O utilities for saving and loading models to and from archive files. - -It serves as a user-facing API that delegates implementation details to core.storage. -""" - -import logging -from pathlib import Path -from typing import Any, List, Optional - -# Import core implementations -from plexe.core.storage import ( - _save_model_to_tar, - _load_model_data_from_tar, - _save_checkpoint_to_tar, - _load_checkpoint_data_from_tar, - _list_checkpoint_files, - _delete_checkpoint_file, - _clear_checkpoint_files, -) - -# Import other required types -from plexe.internal.models.entities.metric import Metric, MetricComparator, ComparisonMethod -from plexe.internal.models.entities.artifact import Artifact - -logger = logging.getLogger(__name__) - - -def save_model(model: Any, path: str | Path) -> str: - """ - Save a model to a tar archive. - - Args: - model: The model to save - path: Path where to save the model - - Returns: - Path where the model was saved - - Raises: - ValueError: If the model cannot be saved or the path is invalid - """ - try: - return _save_model_to_tar(model, path) - except Exception as e: - logger.error(f"Error saving model to {path}: {e}") - raise ValueError(f"Failed to save model: {str(e)}") from e - - -def load_model(path: str | Path): - """ - Load a model from a tar archive. - - Args: - path: Path to the model archive - - Returns: - A Model instance - - Raises: - ValueError: If the model file doesn't exist or is invalid - """ - # Import here to avoid circular imports - from plexe.models import Model - - try: - # Load model data using the core implementation - model_data = _load_model_data_from_tar(path) - - # Create model instance with schemas already processed by core - model = Model( - intent=model_data["intent"], - input_schema=model_data["input_schema"], - output_schema=model_data["output_schema"], - ) - - # Set model state and properties - model.state = model_data["state"] - model.metadata = model_data["metadata"] - model.identifier = model_data["identifier"] - model.trainer_source = model_data["trainer_source"] - model.predictor_source = model_data["predictor_source"] - # Set additional properties if available; these are optional for backward compatibility - model.feature_transformer_source = model_data.get("feature_transformer_source", None) - model.dataset_splitter_source = model_data.get("dataset_splitter_source", None) - model.testing_source = model_data.get("testing_source", None) - model.evaluation_report = model_data.get("evaluation_report", None) - - # Process metrics data if available - metrics_data = model_data["metrics_data"] - if metrics_data: - comparator = MetricComparator( - comparison_method=ComparisonMethod(metrics_data["comparison_method"]), target=metrics_data["target"] - ) - model.metric = Metric(name=metrics_data["name"], value=metrics_data["value"], comparator=comparator) - - # Add EDA reports to metadata if found - if "eda_markdown_reports" in model_data: - model.metadata["eda_markdown_reports"] = model_data["eda_markdown_reports"] - - # Process artifacts - artifact_handles = [] - for artifact_item in model_data["artifact_data"]: - artifact_handles.append(Artifact.from_data(artifact_item["name"], artifact_item["data"])) - - model.artifacts = artifact_handles - - # Load predictor if source code is available - if model.predictor_source: - import types - - predictor_module = types.ModuleType("predictor") - exec(model.predictor_source, predictor_module.__dict__) - model.predictor = predictor_module.PredictorImplementation(artifact_handles) - - logger.debug(f"Model successfully loaded from {path}") - return model - - except Exception as e: - logger.error(f"Error loading model from {path}: {e}") - raise ValueError(f"Failed to load model: {str(e)}") from e - - -def save_checkpoint(model: Any, iteration: int, path: Optional[str | Path] = None) -> str: - """ - Save a model checkpoint to a tar archive. - - Args: - model: The model to checkpoint - iteration: Current iteration number - path: Optional custom path - - Returns: - Path where the checkpoint was saved - - Raises: - ValueError: If the checkpoint cannot be saved or the path is invalid - """ - try: - return _save_checkpoint_to_tar(model, iteration, path) - except Exception as e: - logger.error(f"Error saving checkpoint (iteration {iteration}): {e}") - raise ValueError(f"Failed to save checkpoint: {str(e)}") from e - - -def load_checkpoint( - checkpoint_path: Optional[str | Path] = None, model_id: Optional[str] = None, latest: bool = False -) -> Any: - """ - Load a model from a checkpoint. - - This function loads a model from a checkpoint file, which can then be used - to resume a previously interrupted build process. - - Args: - checkpoint_path: Direct path to a checkpoint file - model_id: Model identifier to find checkpoints for - latest: If True and model_id is provided, loads the latest checkpoint for that model - - Returns: - Model instance initialized from the checkpoint - - Raises: - ValueError: If no checkpoint could be found or if the parameters are invalid - """ - # Import here to avoid circular imports - from plexe.models import Model - - try: - # Parameter validation - if checkpoint_path is None and model_id is None: - raise ValueError("Either checkpoint_path or model_id must be provided") - - if checkpoint_path is not None and model_id is not None: - raise ValueError("Only one of checkpoint_path or model_id should be provided") - - # If model_id is provided, find relevant checkpoints - if model_id is not None: - checkpoints = list_checkpoints(model_id) - if not checkpoints: - raise ValueError(f"No checkpoints found for model_id '{model_id}'") - - if latest: - # Sort by timestamp (descending) and take the first one - checkpoint_path = sorted(checkpoints, reverse=True)[0] - else: - # If not latest, we need an exact path - raise ValueError("When using model_id without latest=True, please specify a specific checkpoint_path") - - # Load the checkpoint data from tar archive (schemas are already processed) - checkpoint_data = _load_checkpoint_data_from_tar(checkpoint_path) - - # Create a new model with the basic information from the checkpoint - model = Model( - intent=checkpoint_data["intent"], - input_schema=checkpoint_data["input_schema"], - output_schema=checkpoint_data["output_schema"], - ) - - # Update model with checkpoint data - model.identifier = checkpoint_data["identifier"] - model.state = checkpoint_data["state"] - model.metadata.update(checkpoint_data["metadata"]) - - # Store the checkpoint data for resumption - model._checkpoint_data = checkpoint_data - - logger.info(f"Model loaded from checkpoint {checkpoint_path}") - return model - - except Exception as e: - if isinstance(e, ValueError): - # Preserve specific ValueError messages - raise - logger.error(f"Error loading checkpoint from {checkpoint_path}: {e}") - raise ValueError(f"Failed to load checkpoint: {str(e)}") from e - - -def list_checkpoints(model_id: Optional[str] = None) -> List[str]: - """ - List available checkpoints. - - Args: - model_id: Optional model identifier to filter checkpoints - - Returns: - List of checkpoint paths - - Raises: - ValueError: If there's an issue accessing the checkpoint directory - """ - try: - return _list_checkpoint_files(model_id) - except Exception as e: - logger.error(f"Error listing checkpoints: {e}") - raise ValueError(f"Failed to list checkpoints: {str(e)}") from e - - -def delete_checkpoint(path: str | Path) -> bool: - """ - Delete a specific checkpoint. - - Args: - path: Path to the checkpoint to delete - - Returns: - True if deletion was successful, False otherwise - - Raises: - ValueError: If there's an issue accessing the file - """ - try: - return _delete_checkpoint_file(path) - except Exception as e: - logger.error(f"Error deleting checkpoint {path}: {e}") - raise ValueError(f"Failed to delete checkpoint: {str(e)}") from e - - -def clear_checkpoints(model_id: Optional[str] = None, older_than_days: Optional[int] = None) -> int: - """ - Clear checkpoints based on filter criteria. - - Args: - model_id: Optional model identifier to filter checkpoints - older_than_days: Optional age in days to filter checkpoints - - Returns: - Number of checkpoints deleted - - Raises: - ValueError: If there's an issue accessing or deleting the files - """ - try: - return _clear_checkpoint_files(model_id, older_than_days) - except Exception as e: - logger.error(f"Error clearing checkpoints: {e}") - raise ValueError(f"Failed to clear checkpoints: {str(e)}") from e diff --git a/plexe/internal/__init__.py b/plexe/internal/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/plexe/internal/common/__init__.py b/plexe/internal/common/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/plexe/internal/common/datasets/__init__.py b/plexe/internal/common/datasets/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/plexe/internal/common/datasets/adapter.py b/plexe/internal/common/datasets/adapter.py deleted file mode 100644 index 97799e08..00000000 --- a/plexe/internal/common/datasets/adapter.py +++ /dev/null @@ -1,95 +0,0 @@ -""" -This module provides the DatasetAdapter class, which converts various dataset formats into standardized Dataset -objects. This enables the library to accept multiple dataset types as inputs, while ensuring consistency and -interoperability. -""" - -import logging -from typing import Any, Dict, List, Optional - -import pandas as pd - -from plexe.internal.common.datasets.interface import Dataset -from plexe.internal.common.datasets.tabular import TabularDataset - - -logger = logging.getLogger(__name__) - - -# This dictionary defines the mapping of dataset types to their respective wrapper classes. -# Note: this could be replaced with a separate DatasetRegistry class in the future if we need dynamic registration -# TODO: Add more dataset types and their corresponding classes -DATASET_REGISTRY_MAP = { - "tabular": TabularDataset, -} - - -class DatasetAdapter: - """ - A utility class for converting different dataset formats into standardized Dataset objects. - - This class provides methods for handling structured datasets, ensuring compatibility with downstream - processing steps in the plexe library. - """ - - @staticmethod - def coerce(dataset: Any) -> Dataset: - """ - Converts a dataset to a standardized format. - - This method attempts to convert the input dataset to a Dataset implementation if a suitable one is - available. If dataset_type is None, it tries to auto-detect the appropriate type. For backward compatibility, - it falls back to returning a pandas DataFrame if no appropriate Dataset is available. - - :param dataset: The dataset to convert - :returns: A Dataset implementation or pandas DataFrame - :raises ValueError: If the dataset type is unsupported - """ - # If dataset is already a Dataset, return it directly - if isinstance(dataset, Dataset): - return dataset - - # Determine the dataset type - dataset_type = DatasetAdapter.auto_detect(dataset) - - # If we have a suitable Dataset implementation, use it - if dataset_type is not None: - try: - return DATASET_REGISTRY_MAP[dataset_type](dataset) - except (ValueError, ImportError) as e: - # Log the error but continue with the fallback - logger.error(f"Failed to create {dataset_type} dataset: {str(e)}") - raise ValueError(f"Failed to convert dataset of type {type(dataset)} to {dataset_type}: {str(e)}") - else: - raise ValueError(f"Unsupported dataset type: {type(dataset)}") - - @classmethod - def auto_detect(cls, data: Any) -> Optional[str]: - """ - Auto-detect the appropriate dataset type for the given data. - - :param data: The data to detect the appropriate dataset type for - :returns: Name of the detected dataset implementation, or None if no appropriate type was found - """ - if isinstance(data, pd.DataFrame): - return "tabular" - - # TODO: Add more auto-detection logic for other data types - return None - - @staticmethod - def features(datasets: Dict[str, Dataset]) -> List[str]: - """ - Extracts a flat list of feature names from the given datasets. - - This method is useful for gathering meaningful names for all features available across multiple datasets, - which can be passed to a downstream LLM call or other processing steps. - - :param datasets: A dictionary of dataset names and their corresponding datasets - :returns: A list of feature names - :raises ValueError: If the dataset type is unsupported - """ - features = [] - for name, dataset in datasets.items(): - features.extend(f"{name}.{feature}" for feature in dataset.structure.features) - return features diff --git a/plexe/internal/common/datasets/interface.py b/plexe/internal/common/datasets/interface.py deleted file mode 100644 index 382d9cda..00000000 --- a/plexe/internal/common/datasets/interface.py +++ /dev/null @@ -1,201 +0,0 @@ -""" -This module defines the core interfaces for dataset handling in plexe. - -The interfaces provide a consistent API for working with different types of datasets, regardless of their -underlying implementation. They define operations like splitting, sampling, and serialization that are common -across all dataset types. -""" - -from abc import ABC, abstractmethod -from dataclasses import dataclass, field -from typing import Tuple, Type, TypeVar, Any, Literal, Dict, List - -import numpy as np -import pandas as pd - -# Type variable for the dataset interface -T = TypeVar("T", bound="Dataset") - - -@dataclass -class DatasetStructure: - """ - Descriptor for the dataset structure. - - This descriptor provides metadata about the dataset's structure. The 'modality' field indicates the broad - type of underlying data structure (e.g., tabular, tensor, etc.) in a framework-agnostic way (that is, it - does not distinguish between PyTorch tensors and TensorFlow tensors, for example). The 'details' field - contains the description of the dataset's structure, which can vary depending on the type of dataset. - """ - - # todo: expand this when more dataset types are added - modality: Literal["table", "tensor", "other"] = field() - features: List[str] = field() - details: Dict[str, Any] = field() - - -class Dataset(ABC): - """ - Base interface for all dataset implementations with universal operations. - - This interface defines operations that all dataset implementations must support, regardless of the underlying - data format. These include splitting datasets into train/validation/test sets, sampling data, and serialization. - """ - - @abstractmethod - def split( - self, - train_ratio: float = 0.7, - val_ratio: float = 0.15, - test_ratio: float = 0.15, - stratify_column: str = None, - random_state: int = None, - ) -> Tuple[T, T, T]: - """ - Split dataset into train, validation and test sets. - - :param train_ratio: Proportion of data to use for training - :param val_ratio: Proportion of data to use for validation - :param test_ratio: Proportion of data to use for testing - :param stratify_column: Column to use for stratified splitting - :param random_state: Random seed for reproducibility - :returns: A tuple of (train_dataset, val_dataset, test_dataset) - """ - pass - - @abstractmethod - def sample(self, n: int = None, frac: float = None, replace: bool = False, random_state: int = None) -> T: - """ - Sample records from dataset. - - :param n: Number of samples to take - :param frac: Fraction of dataset to sample - :param replace: Whether to sample with replacement - :param random_state: Random seed for reproducibility - :returns: A new dataset containing the sampled data - """ - pass - - @abstractmethod - def to_bytes(self) -> bytes: - """ - Serialize dataset to bytes. - - :returns: Serialized dataset as bytes - """ - pass - - @classmethod - @abstractmethod - def from_bytes(cls: Type[T], data: bytes) -> T: - """ - Deserialize dataset from bytes. - - :param data: Serialized dataset as bytes - :returns: Deserialized dataset - """ - pass - - @property - @abstractmethod - def structure(self) -> DatasetStructure: - """ - Return a descriptor of the dataset's structure. - - The structure descriptor has different details depending on the type of underlying dataset. This - method is used to provide human-readable and LLM-readable information about the dataset's structure. - - :returns: Schema definition for the dataset - """ - pass - - @abstractmethod - def __len__(self) -> int: - """ - Return the number of items in the dataset. - - :returns: Number of items in the dataset - """ - pass - - @abstractmethod - def __getitem__(self, index: int) -> Any: - """ - Get an item from the dataset by index. - - :param index: Index of the item to retrieve - :returns: The item at the specified index - """ - pass - - -class TabularConvertible(ABC): - """ - Interface for datasets that can be converted to tabular formats. - - This interface defines methods for converting a dataset to common tabular - data formats like pandas DataFrames and numpy arrays. - """ - - @abstractmethod - def to_pandas(self) -> pd.DataFrame: - """ - Convert to pandas DataFrame. - - :returns: Dataset as pandas DataFrame - """ - pass - - @abstractmethod - def to_numpy(self) -> np.ndarray: - """ - Convert to numpy array. - - :returns: Dataset as numpy array - """ - pass - - -class TorchConvertible(ABC): - """ - Interface for datasets that can be converted to PyTorch formats. - - This interface defines methods for converting a dataset to PyTorch-specific - data structures like Datasets and Tensors. - """ - - @abstractmethod - def to_torch_dataset(self): - """ - Convert to PyTorch Dataset. - - :returns: Dataset as PyTorch Dataset - """ - pass - - @abstractmethod - def to_torch_tensor(self): - """ - Convert to PyTorch Tensor. - - :returns: Dataset as PyTorch Tensor - """ - pass - - -class TensorflowConvertible(ABC): - """ - Interface for datasets that can be converted to TensorFlow formats. - - This interface defines methods for converting a dataset to TensorFlow-specific - data structures like tf.data.Dataset. - """ - - @abstractmethod - def to_tf_dataset(self): - """ - Convert to TensorFlow Dataset. - - :returns: Dataset as TensorFlow Dataset - """ - pass diff --git a/plexe/internal/common/datasets/tabular.py b/plexe/internal/common/datasets/tabular.py deleted file mode 100644 index ebedc9fc..00000000 --- a/plexe/internal/common/datasets/tabular.py +++ /dev/null @@ -1,219 +0,0 @@ -""" -This module provides the TabularDataset implementation, which handles tabular data like pandas DataFrames -and numpy arrays. It implements the DatasetInterface and provides methods for splitting, sampling, and -serialization of tabular data. -""" - -import io -import pandas as pd -from typing import Tuple, Optional, Any - -import numpy as np -from plexe.internal.common.datasets.interface import Dataset, TabularConvertible, DatasetStructure - - -class TabularDataset(Dataset, TabularConvertible): - """ - Dataset implementation for tabular data. - - TabularDataset wraps pandas DataFrames and provides methods for common dataset operations like splitting, - sampling, and serialization. It also implements the TabularConvertible interface to allow conversion to - pandas and numpy formats. - """ - - def __init__(self, data: pd.DataFrame): - self._data = self._validate(data) - - @staticmethod - def _validate(data: Any) -> pd.DataFrame: - """Ensure that the input is a pandas DataFrame.""" - if isinstance(data, pd.DataFrame): - return data.copy() - raise ValueError(f"TabularDataset only supports pandas DataFrame input, got {type(data)}") - - def split( - self, - train_ratio: float = 0.7, - val_ratio: float = 0.15, - test_ratio: float = 0.15, - stratify_column: Optional[str] = None, - random_state: Optional[int] = None, - is_time_series: bool = False, - time_index_column: Optional[str] = None, - ) -> Tuple["TabularDataset", "TabularDataset", "TabularDataset"]: - """ - Split dataset into train, validation and test sets. - - :param train_ratio: Proportion of data to use for training - :param val_ratio: Proportion of data to use for validation - :param test_ratio: Proportion of data to use for testing - :param stratify_column: Column to use for stratified splitting (not used for time series) - :param random_state: Random seed for reproducibility (not used for time series) - :param is_time_series: Whether the data is chronological time series data - :param time_index_column: Column name that represents the time index, required if is_time_series=True - :returns: A tuple of (train_dataset, val_dataset, test_dataset) - :raises ValueError: If ratios don't sum to approximately 1.0 or if time_index_column is missing for time series - """ - if abs(train_ratio + val_ratio + test_ratio - 1.0) > 1e-10: - raise ValueError("Split ratios must sum to 1.0") - - # Handle time series data - if is_time_series: - if not time_index_column: - raise ValueError("time_index_column must be provided when is_time_series=True") - - if time_index_column not in self._data.columns: - raise ValueError(f"time_index_column '{time_index_column}' not found in dataset columns") - - # Sort by time index - sorted_data = self._data.sort_values(by=time_index_column).reset_index(drop=True) - - # Calculate split indices - n_samples = len(sorted_data) - train_end = int(n_samples * train_ratio) - val_end = train_end + int(n_samples * val_ratio) - - # Split the data sequentially - train_data = sorted_data.iloc[:train_end] - val_data = sorted_data.iloc[train_end:val_end] - test_data = sorted_data.iloc[val_end:] - - # Handle edge cases for empty splits - empty_df = pd.DataFrame(columns=self._data.columns) - if val_ratio < 1e-10: - val_data = empty_df - if test_ratio < 1e-10: - test_data = empty_df - - return TabularDataset(train_data), TabularDataset(val_data), TabularDataset(test_data) - - # Regular random splitting for non-time series data - from sklearn.model_selection import train_test_split - - # Handle all-data-to-train edge case - if val_ratio < 1e-10 and test_ratio < 1e-10: - return ( - TabularDataset(self._data), - TabularDataset(pd.DataFrame(columns=self._data.columns)), - TabularDataset(pd.DataFrame(columns=self._data.columns)), - ) - elif val_ratio < 1e-10: - train_data, test_data = train_test_split( - self._data, - test_size=test_ratio / (train_ratio + test_ratio), - stratify=self._data[stratify_column] if stratify_column else None, - random_state=random_state, - ) - return ( - TabularDataset(train_data), - TabularDataset(pd.DataFrame(columns=self._data.columns)), - TabularDataset(test_data), - ) - elif test_ratio < 1e-10: - train_data, val_data = train_test_split( - self._data, - test_size=val_ratio / (train_ratio + val_ratio), - stratify=self._data[stratify_column] if stratify_column else None, - random_state=random_state, - ) - return ( - TabularDataset(train_data), - TabularDataset(val_data), - TabularDataset(pd.DataFrame(columns=self._data.columns)), - ) - - # Standard 3-way split - train_data, temp_data = train_test_split( - self._data, - test_size=(val_ratio + test_ratio), - stratify=self._data[stratify_column] if stratify_column else None, - random_state=random_state, - ) - val_ratio_adjusted = val_ratio / (val_ratio + test_ratio) - val_data, test_data = train_test_split( - temp_data, - test_size=(1 - val_ratio_adjusted), - stratify=temp_data[stratify_column] if stratify_column else None, - random_state=random_state, - ) - return TabularDataset(train_data), TabularDataset(val_data), TabularDataset(test_data) - - def sample( - self, n: int = None, frac: float = None, replace: bool = False, random_state: int = None - ) -> "TabularDataset": - """ - Sample records from dataset. - - :param n: number of samples to take - :param frac: fraction of dataset to sample - :param replace: whether to sample with replacement - :param random_state: random seed for reproducibility - :return: a new dataset containing the sampled data - """ - return TabularDataset(self._data.sample(n=n, frac=frac, replace=replace, random_state=random_state)) - - def to_bytes(self) -> bytes: - """ - Serialize the dataset to bytes using Parquet format. - - :return: byte representation of the dataset - """ - try: - import pyarrow as pa - import pyarrow.parquet as pq - - buffer = io.BytesIO() - table = pa.Table.from_pandas(self._data) - pq.write_table(table, buffer) - return buffer.getvalue() - except Exception as e: - raise RuntimeError("Failed to serialize DataFrame to bytes") from e - - @classmethod - def from_bytes(cls, data: bytes) -> "TabularDataset": - """ - Deserialize bytes back into a TabularDataset. - - :param data: byte representation of dataset - :return: TabularDataset instance - """ - try: - import pyarrow.parquet as pq - - buffer = io.BytesIO(data) - table = pq.read_table(buffer) - return cls(table.to_pandas()) - except Exception as e: - raise RuntimeError("Failed to deserialize bytes to DataFrame") from e - - @property - def structure(self) -> DatasetStructure: - """ - Return structural metadata for the dataset. - - :return: DatasetStructure object describing features and shape - """ - return DatasetStructure( - modality="table", - features=list(self._data.columns), - details={ - "num_rows": len(self._data), - "num_columns": self._data.shape[1], - "column_names": list(self._data.columns), - "column_types": self._data.dtypes.astype(str).to_dict(), - }, - ) - - def to_pandas(self) -> pd.DataFrame: - """Return a copy of the dataset as a pandas DataFrame.""" - return self._data - - def to_numpy(self) -> np.ndarray: - """Convert the dataset to a NumPy array.""" - return self._data.to_numpy() - - def __len__(self) -> int: - return len(self._data) - - def __getitem__(self, item: Any) -> Any: - return self._data.iloc[item] diff --git a/plexe/internal/common/provider.py b/plexe/internal/common/provider.py deleted file mode 100644 index 43ebcad9..00000000 --- a/plexe/internal/common/provider.py +++ /dev/null @@ -1,175 +0,0 @@ -""" -This module defines the base class for LLM providers and includes -logging and retry mechanisms for querying the providers. -""" - -import logging -import textwrap -from typing import Type, Optional - -import litellm -from litellm import completion, supports_response_schema -from litellm.exceptions import RateLimitError, ServiceUnavailableError -from pydantic import BaseModel -from tenacity import retry, stop_after_attempt, wait_exponential, retry_if_exception_type - -logger = logging.getLogger(__name__) - - -class ProviderConfig: - """ - Configuration class for specifying different LLM providers for various agent roles. - - This allows for granular control of which providers/models are used for different - parts of the multi-agent system. - - Attributes: - default_provider: The default provider to use when specific ones aren't set - orchestrator_provider: Provider for the orchestrator/manager agent - research_provider: Provider for the ML Research Scientist agent - engineer_provider: Provider for the ML Engineer agent - ops_provider: Provider for the ML Ops Engineer agent - tool_provider: Provider for tool operations - """ - - def __init__( - self, - default_provider: str = "gemini/gemini-2.5-flash", - orchestrator_provider: Optional[str] = None, - research_provider: Optional[str] = None, - engineer_provider: Optional[str] = None, - ops_provider: Optional[str] = None, - tool_provider: Optional[str] = None, - ): - # Default provider is used when specific ones aren't set - self.default_provider = default_provider - - # Agent-specific providers - self.orchestrator_provider = orchestrator_provider or default_provider - self.research_provider = research_provider or default_provider - self.engineer_provider = engineer_provider or default_provider - self.ops_provider = ops_provider or default_provider - - # Provider for tool operations - self.tool_provider = tool_provider or default_provider - - def __repr__(self) -> str: - return ( - f"ProviderConfig(default={self.default_provider}, " - f"orchestrator={self.orchestrator_provider}, " - f"research={self.research_provider}, " - f"engineer={self.engineer_provider}, " - f"ops={self.ops_provider}, " - f"tool={self.tool_provider})" - ) - - -class Provider: - """ - Base class for LiteLLM provider. - """ - - def __init__(self, model: str = None): - default_model = "gemini/gemini-2.5-flash" - self.model = model or default_model - if "/" not in self.model: - self.model = default_model - logger.warning(f"Model name should be in the format 'provider/model', using default model: {default_model}") - # Check if the model supports json mode - if "response_format" not in litellm.get_supported_openai_params(model=self.model): - raise ValueError(f"Model {self.model} does not support passing response_format") - if not supports_response_schema(model=self.model): - raise ValueError(f"Model {self.model} does not support response schema") - - def _make_completion_call(self, messages, response_format): - """Helper method to make the actual API call with built-in retries for rate limits""" - response = completion(model=self.model, messages=messages, response_format=response_format) - - if not response.choices[0].message.content: - raise ValueError("Empty response from provider") - - return response.choices[0].message.content - - def query( - self, - system_message: str, - user_message: str, - response_format: Type[BaseModel] = None, - retries: int = 3, - backoff: bool = True, - ) -> str: - """ - Method to query the provider using litellm.completion. - - :param [str] system_message: The system message to send to the provider. - :param [str] user_message: The user message to send to the provider. - :param [Type[BaseModel]] response_format: A pydantic BaseModel class representing the response format. - :param [int] retries: The number of times to retry the request. Defaults to 3. - :param [bool] backoff: Whether to use exponential backoff when retrying. Defaults to True. - :return [str]: The response from the provider. - """ - self._log_request(system_message, user_message, self.__class__.__name__) - - messages = [{"role": "system", "content": system_message}, {"role": "user", "content": user_message}] - - try: - # Handle general errors with standard retries - if backoff: - - @retry(stop=stop_after_attempt(retries), wait=wait_exponential(multiplier=2)) - def call_with_backoff_retry_all_errors(): - @retry( - stop=stop_after_attempt(5), - wait=wait_exponential(multiplier=2, min=4), - retry=retry_if_exception_type((RateLimitError, ServiceUnavailableError)), - ) - def call_with_backoff_retry_service_errors(): - return self._make_completion_call(messages, response_format) - - return call_with_backoff_retry_service_errors() - - r = call_with_backoff_retry_all_errors() - else: - r = self._make_completion_call(messages, response_format) - - self._log_response(r, self.__class__.__name__) - return r - except Exception as e: - self._log_error(e) - raise e - - @staticmethod - def _log_request(system_message: str, user_message: str, model): - """ - Logs the request to the provider. - - :param [str] system_message: The system message to send to the provider. - :param [str] user_message: The user message to send to the provider. - """ - logger.debug( - ( - # String interpolation because Python <3.12 does not support backslashes inside f-strings curly braces - f"Requesting chat completion from {model} with messages: " - + textwrap.shorten(system_message.replace("\n", " "), 30) - + ", " - + textwrap.shorten(user_message.replace("\n", " "), 30) - ) - ) - - @staticmethod - def _log_response(response, model): - """ - Logs the response from the provider. - - :param [str] response: The response from the provider. - """ - logger.debug(f"Received completion from {model}: {textwrap.shorten(response, 30)}") - - @staticmethod - def _log_error(error): - """ - Logs the error from the provider. - - :param [str] error: The error from the provider. - """ - logger.error(f"Error querying provider: {error}") diff --git a/plexe/internal/common/utils/__init__.py b/plexe/internal/common/utils/__init__.py deleted file mode 100644 index e1b25cfb..00000000 --- a/plexe/internal/common/utils/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -""" -Common utility functions for the plexe library. -""" diff --git a/plexe/internal/common/utils/agents.py b/plexe/internal/common/utils/agents.py deleted file mode 100644 index 5d6290c3..00000000 --- a/plexe/internal/common/utils/agents.py +++ /dev/null @@ -1,46 +0,0 @@ -""" -This module provides utilities for working with agents defined using the smolagents library. -""" - -import yaml -import importlib -from plexe.config import config - - -def get_prompt_templates( - base_template_name: str, override_template_name: str, template_vars: dict | None = None -) -> dict: - """ - Given the name of a smolagents prompt template (the 'base template') and a plexe prompt template - (the 'overriding template'), this function loads both templates and returns a merged template in which - all keys from the overriding template overwrite the matching keys in the base template. - """ - base_template_content = importlib.resources.files("smolagents.prompts").joinpath(base_template_name).read_text() - override_template_content = ( - importlib.resources.files("plexe") - .joinpath("templates/prompts/agent") - .joinpath(override_template_name) - .read_text() - ) - - # Perform string replacements for template variables - if template_vars: - for key, value in template_vars.items(): - base_template_content = base_template_content.replace(f"{{{{{key}}}}}", str(value)) - override_template_content = override_template_content.replace(f"{{{{{key}}}}}", str(value)) - - base_template: dict = yaml.safe_load(base_template_content) - override_template: dict = yaml.safe_load( - override_template_content.replace("{{allowed_packages}}", str(config.code_generation.allowed_packages)) - ) - - # Recursively merge two dictionaries to ensure deep merging - def merge_dicts(base: dict, override: dict) -> dict: - for key, value in override.items(): - if isinstance(value, dict) and key in base and isinstance(base[key], dict): - base[key] = merge_dicts(base[key], value) - else: - base[key] = value - return base - - return merge_dicts(base_template, override_template) diff --git a/plexe/internal/common/utils/chain_of_thought/__init__.py b/plexe/internal/common/utils/chain_of_thought/__init__.py deleted file mode 100644 index 92e13340..00000000 --- a/plexe/internal/common/utils/chain_of_thought/__init__.py +++ /dev/null @@ -1,29 +0,0 @@ -""" -Chain of thought capturing and logging for agent systems. - -This package provides a framework-agnostic way to capture, format, and display -the chain of thought reasoning from different agent frameworks. -""" - -from plexe.internal.common.utils.chain_of_thought.protocol import StepSummary, ToolCall -from plexe.internal.common.utils.chain_of_thought.adapters import extract_step_summary_from_smolagents -from plexe.internal.common.utils.chain_of_thought.callable import ChainOfThoughtCallable -from plexe.internal.common.utils.chain_of_thought.emitters import ( - ChainOfThoughtEmitter, - ConsoleEmitter, - LoggingEmitter, - MultiEmitter, -) -from plexe.internal.common.utils.chain_of_thought.websocket_emitter import WebSocketEmitter - -__all__ = [ - "StepSummary", - "ToolCall", - "extract_step_summary_from_smolagents", - "ChainOfThoughtCallable", - "ChainOfThoughtEmitter", - "ConsoleEmitter", - "LoggingEmitter", - "MultiEmitter", - "WebSocketEmitter", -] diff --git a/plexe/internal/common/utils/chain_of_thought/adapters.py b/plexe/internal/common/utils/chain_of_thought/adapters.py deleted file mode 100644 index b3e23e08..00000000 --- a/plexe/internal/common/utils/chain_of_thought/adapters.py +++ /dev/null @@ -1,66 +0,0 @@ -""" -This module provides adapters for extracting step information from different agent frameworks. - -The functions in this module are designed to take as input the step outputs provided by a particular -agent framework, and convert them into a framework-agnostic representation that is used throughout Plexe. -This module should be extended as new agent frameworks are added to Plexe, or modified if the agent -frameworks change their output formats. -""" - -from typing import Any - -from .protocol import StepSummary, ToolCall - - -def extract_step_summary_from_smolagents(step: Any, agent: Any) -> StepSummary: - """ - Extract step summary from a SmoLAgents step object. - - Args: - step: A SmoLAgents step object - agent: The agent that performed the step - - Returns: - A framework-agnostic StepSummary object - """ - # Get agent name - agent_name = getattr(agent, "name", agent.__class__.__name__) - - # Extract common properties - step_number = getattr(step, "step_number", None) - step_type = step.__class__.__name__ - error = str(getattr(step, "error", "")) or None - - # Extract model output from various step types - model_output = None - if hasattr(step, "model_output_message") and step.model_output_message: - model_output = getattr(step.model_output_message, "content", None) - - # Extract tool calls - tool_calls = [] - if hasattr(step, "tool_calls") and step.tool_calls: - tool_calls = [ToolCall(name=call.name, args=call.arguments) for call in step.tool_calls] - - # Extract observations and results based on step type - observations = getattr(step, "observations", None) - result = getattr(step, "action_output", None) - - # Handle specific step types - if hasattr(step, "code_block") and getattr(step, "code_block", None): - # Extract thought and code from CodeActionStep - code_block = getattr(step, "code_block", None) - if code_block: - # Don't show full code in chain of thought, just indicate it's there - observations = f"[Code block executed: {len(code_block)} characters]" - - # Create and return the step summary - return StepSummary( - step_number=step_number, - step_type=step_type, - agent_name=agent_name, - model_output=model_output, - tool_calls=tool_calls, - observations=observations, - result=result, - error=error, - ) diff --git a/plexe/internal/common/utils/chain_of_thought/callable.py b/plexe/internal/common/utils/chain_of_thought/callable.py deleted file mode 100644 index 6b1442ed..00000000 --- a/plexe/internal/common/utils/chain_of_thought/callable.py +++ /dev/null @@ -1,209 +0,0 @@ -""" -This module defines Callables for capturing and formatting agent chain of thought. - -The classes in this module are designed to be used as "plug-ins" to agent frameworks, enabling the production -of a user-friendly output of the agent's reasoning process. The output can be used for debugging, logging, or -user feedback during agent execution. -""" - -import json -import logging -from typing import Any, List, Optional, Tuple - -from pydantic import BaseModel, Field - -from ...provider import Provider -from plexe.config import prompt_templates -from .protocol import StepExtractor, StepSummary -from .adapters import extract_step_summary_from_smolagents -from .emitters import ChainOfThoughtEmitter, ConsoleEmitter - -logger = logging.getLogger(__name__) - - -class ChainOfThoughtCallable: - """ - Callable that captures and formats agent chain of thought. - - This callable can be attached to agent frameworks to capture - each step of the agent's reasoning process and format it for - user-friendly output. - """ - - def __init__( - self, - emitter: Optional[ChainOfThoughtEmitter] = None, - extractor: StepExtractor = extract_step_summary_from_smolagents, - ): - """ - Initialize the chain of thought callable. - - Args: - emitter: The emitter to use for outputting chain of thought - extractor: Function that extracts step information from the agent framework - """ - self.emitter = emitter or ConsoleEmitter() - self.extractor = extractor - self.steps: List[StepSummary] = [] - - def __call__(self, step: Any, agent: Any = None) -> None: - """ - Process a step from an agent. - - Args: - step: The step object from the agent framework - agent: The agent that performed the step - """ - try: - # Extract step summary - summary = self.extractor(step, agent) - - # Generate friendly title and summary if not already present - if summary.friendly_title is None or summary.friendly_summary is None: - friendly_title, friendly_summary = _generate_friendly_summary(summary) - summary.friendly_title = friendly_title - summary.friendly_summary = friendly_summary - - # Store the step for later retrieval - self.steps.append(summary) - - # Emit the step information - self._emit_step(summary) - - except Exception as e: - # Log full stack trace at debug level - import traceback - - logger.debug(f"Error processing agent step: {str(e)}\n{traceback.format_exc()}") - - # Log a shorter message at warning level - logger.warning(f"Error processing agent step: {str(e)[:50]}") - - def _emit_step(self, summary: StepSummary) -> None: - """ - Emit a step to the configured emitter. - - Args: - summary: The step summary to emit - """ - # If we have friendly title and summary, emit those in a consolidated message - if summary.friendly_title and summary.friendly_summary: - # Emit friendly step header with title and summary together - # This ensures they appear as a single node in the tree - self.emitter.emit_thought(summary.agent_name, f"💡 {summary.friendly_title}\n💭 {summary.friendly_summary}") - return - - # Fall back to verbose output if friendly version not available - - # Emit step header - step_header = f"🧠 {summary.step_type}" - if summary.step_number is not None: - step_header += f" #{summary.step_number}" - - self.emitter.emit_thought(summary.agent_name, step_header) - - # Emit model output separately if available - if summary.model_output: - thought_text = summary.model_output[:500] - if len(summary.model_output) > 500: - thought_text += "..." - self.emitter.emit_thought(summary.agent_name, f"💭 Thought: {thought_text}") - - # Emit tool calls one by one for better visualization - for call in summary.tool_calls: - self.emitter.emit_thought(summary.agent_name, f"🔧 Tool: {call.name}({call.args})") - - # Emit observations - if summary.observations: - observation_text = summary.observations[:500] - if len(summary.observations) > 500: - observation_text += "..." - self.emitter.emit_thought(summary.agent_name, f"📡 Observed: {observation_text}") - - # Emit result - if summary.result: - result_text = str(summary.result)[:500] - if len(str(summary.result)) > 500: - result_text += "..." - self.emitter.emit_thought(summary.agent_name, f"📦 Result: {result_text}") - - # Emit error if any - if summary.error: - self.emitter.emit_thought(summary.agent_name, f"❌ Error: {summary.error}") - - def get_full_chain_of_thought(self) -> List[StepSummary]: - """ - Get the full chain of thought captured so far. - - Returns: - The list of step summaries - """ - return self.steps - - def clear(self) -> None: - """Clear all captured steps.""" - self.steps = [] - - -def _generate_friendly_summary(summary: StepSummary) -> Tuple[str, str]: - """ - Generate a user-friendly title and summary for a step using LLM. - - Args: - summary: The step summary to generate a friendly summary for - - Returns: - A tuple of (friendly_title, friendly_summary) - """ - - class FriendlySummaryResponse(BaseModel): - """Response format for generating friendly step summaries.""" - - title: str = Field(description="A short, friendly title (3-7 words) that captures the essence of what happened") - summary: str = Field(description="A concise summary (1-2 sentences) that explains the step in plain language") - - # Create a context string that summarizes the step for the LLM - context_parts = [f"Step Type: {summary.step_type}"] - - if summary.model_output: - context_parts.append(f"Thought: {summary.model_output}") - - if summary.tool_calls: - for call in summary.tool_calls: - context_parts.append(f"Tool: {call.name}({json.dumps(call.args)})") - - if summary.observations: - context_parts.append(f"Observation: {summary.observations}") - - if summary.result: - context_parts.append(f"Result: {str(summary.result)}") - - if summary.error: - context_parts.append(f"Error: {summary.error}") - - context = "\n".join(context_parts) - - # Get the prompt template - system_message = prompt_templates.cot_system() - user_message = prompt_templates.cot_summarize(context) - - try: - # Use the Provider to get a structured response - provider = Provider() - response = provider.query( - system_message=system_message, user_message=user_message, response_format=FriendlySummaryResponse - ) - - # Parse the response to get JSON - response_data = json.loads(response) - return response_data["title"], response_data["summary"] - except Exception as e: - # Log full stack trace at debug level - import traceback - - logger.debug(f"Error generating friendly summary: {str(e)}\n{traceback.format_exc()}") - - # Log shorter message at warning level - logger.warning(f"Error generating friendly summary: {str(e)[:50]}") - - return f"{summary.step_type}", f"Step {summary.step_number or 0} of type {summary.step_type}" diff --git a/plexe/internal/common/utils/chain_of_thought/emitters.py b/plexe/internal/common/utils/chain_of_thought/emitters.py deleted file mode 100644 index 3cb882b6..00000000 --- a/plexe/internal/common/utils/chain_of_thought/emitters.py +++ /dev/null @@ -1,207 +0,0 @@ -""" -This module defines Emitters for outputting chain of thought information. - -The emitters are responsible for formatting and outputting the chain of thought of the agents to output -locations such as the console or a logging system. The emitters can be used in various contexts, such as -logging agent actions, debugging, or providing user feedback during agent execution. -""" - -import logging -import sys -from abc import ABC, abstractmethod -from datetime import datetime -from typing import List, TextIO - -logger = logging.getLogger(__name__) - - -class ChainOfThoughtEmitter(ABC): - """ - Abstract base class for chain of thought emitters. - - Emitters are responsible for outputting chain of thought - information in a user-friendly format. - """ - - @abstractmethod - def emit_thought(self, agent_name: str, message: str) -> None: - """ - Emit a thought from an agent. - - Args: - agent_name: The name of the agent emitting the thought - message: The thought message - """ - pass - - -class ConsoleEmitter(ChainOfThoughtEmitter): - """ - Emitter that outputs chain of thought to the console with rich formatting. - """ - - def __init__(self, output: TextIO = sys.stdout): - """ - Initialize the console emitter with Rich support. - - Args: - output: The text IO to write to - """ - self.output = output - - # Initialize Rich components - try: - from rich.console import Console - - # Force colorization even in environments like WSL where auto-detection might fail - self.console = Console(file=output, force_terminal=True, color_system="auto", highlight=False) - self.step_count = 0 - self.has_rich = True - except ImportError: - # Fall back to basic output if Rich isn't available - self.has_rich = False - - def emit_thought(self, agent_name: str, message: str) -> None: - """ - Emit a thought to the console using Rich tree visualization. - - Args: - agent_name: The name of the agent emitting the thought - message: The thought message - """ - if not self.has_rich: - # Fall back to basic output - self.output.write(f"[{agent_name}] {message}\n") - self.output.flush() - return - - try: - # Import Rich components for type annotations - - # Track step count for timeline - self.step_count += 1 - timestamp = datetime.now().strftime("%H:%M:%S") - - # Create a separate tree for each output item, but track agent names - # This simplifies the display and avoids issues with nested trees - agent_color = self._get_agent_color(agent_name) - - # Add agent and step information in a cleaner format - # Use plain print with styling - make it more compact - step_info = f"Step {self.step_count}" - - # Add a blank line before new agent name for better readability - # but only if this isn't the first step - if self.step_count > 1: - self.console.print("") - - self.console.print( - f"[bold {agent_color}]{agent_name}[/bold {agent_color}] · [dim]{step_info} · {timestamp}[/dim]" - ) - - # Process the message based on format - if message.startswith("💡"): - # Friendly format with title and summary - parts = message.split("\n", 1) - title = parts[0] - content = parts[1] if len(parts) > 1 else "" - - # Extract emoji if present - emoji = "" - if title.startswith("💡"): - emoji = "💡 " - title = title[2:].strip() - - # Display title and content with proper formatting - self.console.print(f"[bold green]{emoji}{title}[/bold green]") - if content: - self.console.print(f"[dim]{content}[/dim]") - else: - # Standard format - print directly - self.console.print(f"{message}") - - except Exception as e: - # Log the error at debug level - import logging - - logger = logging.getLogger(__name__) - logger.debug(f"Error in Rich formatting: {str(e)}") - - # Fall back to plain output - self.output.write(f"[{agent_name}] {message}\n") - self.output.flush() - - @staticmethod - def _get_agent_color(agent_name: str) -> str: - """Get the color for an agent based on its role.""" - agent_colors = { - "System": "bright_blue", - "MLResearchScientist": "green", - "MLEngineer": "yellow", - "MLOperationsEngineer": "magenta", - "Orchestrator": "cyan", - "DatasetAnalyser": "red", - "SchemaResolver": "orange", - "DatasetSplitter": "purple", - # Default color - "default": "blue", - } - - # Match partial agent names (e.g. "Engineer" should match "ML Engineer") - for role, color in agent_colors.items(): - if role in agent_name: - return color - - return agent_colors["default"] - - -class LoggingEmitter(ChainOfThoughtEmitter): - """ - Emitter that outputs chain of thought to the logging system. - """ - - def __init__(self, level: int = logging.INFO): - """ - Initialize the logging emitter. - - Args: - level: The logging level to use - """ - self.logger = logging.getLogger("plexe.chain_of_thought") - self.level = level - - def emit_thought(self, agent_name: str, message: str) -> None: - """ - Emit a thought to the logger. - - Args: - agent_name: The name of the agent emitting the thought - message: The thought message - """ - self.logger.log(self.level, f"[{agent_name}] {message}") - - -class MultiEmitter(ChainOfThoughtEmitter): - """ - Emitter that outputs chain of thought to multiple emitters. - """ - - def __init__(self, emitters: List[ChainOfThoughtEmitter]): - """ - Initialize the multi emitter. - - Args: - emitters: The emitters to output to - """ - self.emitters = emitters - - def emit_thought(self, agent_name: str, message: str) -> None: - """ - Emit a thought to all configured emitters. - - Args: - agent_name: The name of the agent emitting the thought - message: The thought message - """ - for emitter in self.emitters: - emitter.emit_thought(agent_name, message) diff --git a/plexe/internal/common/utils/chain_of_thought/protocol.py b/plexe/internal/common/utils/chain_of_thought/protocol.py deleted file mode 100644 index cd1f76ea..00000000 --- a/plexe/internal/common/utils/chain_of_thought/protocol.py +++ /dev/null @@ -1,54 +0,0 @@ -""" -Defines protocols and data classes for capturing agent reasoning steps. -""" - -from dataclasses import dataclass, field -from typing import Any, Dict, List, Optional, Protocol - - -@dataclass -class ToolCall: - """Information about a tool called by an agent.""" - - name: str - args: Dict[str, Any] - - -@dataclass -class StepSummary: - """ - Framework-agnostic representation of an agent's reasoning step. - - This class represents a single step in an agent's chain of thought, - regardless of the underlying agent framework used. - """ - - step_number: Optional[int] = None - step_type: str = "Unknown" - agent_name: str = "Agent" - model_output: Optional[str] = None - tool_calls: List[ToolCall] = field(default_factory=list) - observations: Optional[str] = None - result: Any = None - error: Optional[str] = None - friendly_title: Optional[str] = None - friendly_summary: Optional[str] = None - - -class StepExtractor(Protocol): - """ - Protocol for extracting step information from agent frameworks. - """ - - def __call__(self, step: Any, agent: Any) -> StepSummary: - """ - Extract step summary from framework-specific step object. - - Args: - step: A step object from a specific agent framework - agent: The agent that performed the step - - Returns: - A framework-agnostic StepSummary object - """ - ... diff --git a/plexe/internal/common/utils/chain_of_thought/websocket_emitter.py b/plexe/internal/common/utils/chain_of_thought/websocket_emitter.py deleted file mode 100644 index a096cc0d..00000000 --- a/plexe/internal/common/utils/chain_of_thought/websocket_emitter.py +++ /dev/null @@ -1,204 +0,0 @@ -""" -WebSocket emitter for broadcasting agent chain of thought to web clients. - -This emitter sends agent thinking processes and actions to connected WebSocket clients -in real-time, allowing the UI to display the agent's reasoning process. -""" - -import asyncio -import logging -import threading -import uuid - -from plexe.internal.common.utils.chain_of_thought.emitters import ChainOfThoughtEmitter - -logger = logging.getLogger(__name__) - - -class WebSocketEmitter(ChainOfThoughtEmitter): - """ - Emitter that broadcasts chain of thought to WebSocket clients. - - This emitter sends agent thinking messages to a WebSocket connection, - allowing real-time display of agent reasoning in the UI. - """ - - def __init__(self, websocket, loop=None): - """ - Initialize the WebSocket emitter. - - Args: - websocket: The FastAPI WebSocket instance to send messages to - loop: The asyncio event loop to use for sending messages (optional) - """ - self.websocket = websocket - self.step_count = 0 - self._message_queue = [] - self._loop = loop - self._lock = threading.Lock() - self._pending_confirmations = {} - self._confirmation_results = {} - self._closed = False - - def close(self): - """Mark the WebSocket as closed to prevent further sends.""" - with self._lock: - self._closed = True - # Release any waiting confirmation requests - for request_id, event in self._pending_confirmations.items(): - self._confirmation_results[request_id] = False - event.set() - - @property - def is_closed(self) -> bool: - """Check if the WebSocket emitter has been closed.""" - with self._lock: - return self._closed - - def set_loop(self, loop): - """Set the event loop to use for sending messages.""" - self._loop = loop - - def request_confirmation(self, title: str, content: str, content_type: str = "text") -> bool: - """ - Send a confirmation request to the UI and wait for response. - - Args: - title: Title of the confirmation dialog - content: Content to display - content_type: Type of content (text, code, json, markdown) - - Returns: - bool: True if confirmed, False if denied or connection closed - """ - # If already closed, return False immediately - if self.is_closed: - logger.debug("WebSocketEmitter: Cannot request confirmation - connection closed") - return False - - request_id = str(uuid.uuid4()) - event = threading.Event() - - with self._lock: - self._pending_confirmations[request_id] = event - - payload = { - "type": "confirmation_request", - "id": request_id, - "title": title, - "content": content, - "content_type": content_type - } - - self._emit_payload(payload) - - logger.info(f"Waiting for confirmation {request_id}...") - event.wait() - - with self._lock: - result = self._confirmation_results.pop(request_id, False) - if request_id in self._pending_confirmations: - del self._pending_confirmations[request_id] - - return result - - def resolve_confirmation(self, request_id: str, confirmed: bool): - """Resolve a pending confirmation request.""" - with self._lock: - if request_id in self._pending_confirmations: - self._confirmation_results[request_id] = confirmed - self._pending_confirmations[request_id].set() - else: - logger.warning(f"Received confirmation for unknown request {request_id}") - - def emit_thought(self, agent_name: str, message: str) -> None: - """ - Emit a thought to the WebSocket client. - - Args: - agent_name: The name of the agent emitting the thought - message: The thought message - """ - # Check if closed before emitting - if self.is_closed: - raise RuntimeError("Agent execution stopped by user") - - try: - with self._lock: - self.step_count += 1 - step_num = self.step_count - - # Prepare the message payload - payload = { - "type": "thinking", - "role": "thinking", - "agent_name": agent_name, - "message": message, - "step_number": step_num, - } - - self._emit_payload(payload) - - except Exception as e: - logger.error(f"Error emitting thought to WebSocket: {e}") - raise - - def _emit_payload(self, payload: dict): - """Internal helper to send payload via WebSocket.""" - # Check if the emitter has been closed - if self.is_closed: - logger.debug("WebSocketEmitter: Skipping send - connection closed") - return - - try: - # Try to send the message - # First, check if we're in the same thread as the event loop - try: - loop = asyncio.get_running_loop() - # We're in an async context, can create task directly - asyncio.create_task(self._send_message(payload)) - except RuntimeError: - # Not in async context - we're likely in a thread pool - # Use run_coroutine_threadsafe if we have a loop reference - if self._loop is not None and self._loop.is_running(): - future = asyncio.run_coroutine_threadsafe( - self._send_message(payload), - self._loop - ) - # Don't wait for result to avoid blocking - # But add a callback to log errors - future.add_done_callback(self._handle_send_result) - else: - # Last resort: queue the message - logger.warning("WebSocketEmitter: No event loop available - message queued") - self._message_queue.append(payload) - except Exception as e: - logger.error(f"Error emitting payload to WebSocket: {e}") - - - def _handle_send_result(self, future): - """Handle the result of a threadsafe coroutine call.""" - try: - future.result() # This will raise if there was an error - except Exception as e: - # Mark as closed on send failure to prevent further attempts - self.close() - logger.debug(f"WebSocket send failed, connection marked as closed: {e}") - - async def _send_message(self, payload: dict) -> None: - """ - Send a message to the WebSocket client. - - Args: - payload: The message payload to send - """ - if self.is_closed: - return - - try: - await self.websocket.send_json(payload) - except Exception as e: - # Mark as closed on send failure to prevent further attempts - self.close() - logger.debug(f"WebSocket send failed, connection marked as closed: {e}") - diff --git a/plexe/internal/common/utils/dataset_storage.py b/plexe/internal/common/utils/dataset_storage.py deleted file mode 100644 index 85d32c3b..00000000 --- a/plexe/internal/common/utils/dataset_storage.py +++ /dev/null @@ -1,104 +0,0 @@ -""" -This module provides utilities for dataset storage and transfer across processes. - -These utilities work with any class implementing the DatasetInterface and provide -functions for storing datasets to files, reading datasets from files, and using -shared memory for cross-process dataset sharing. -""" - -from typing import Type, TypeVar, Optional -import logging - -from plexe.internal.common.datasets.interface import Dataset - -logger = logging.getLogger(__name__) - -T = TypeVar("T", bound=Dataset) - - -def write_dataset_to_file(dataset: Dataset, path: str) -> None: - """ - Write dataset to a file. - - :param dataset: The dataset to write to a file - :param path: Path to write the dataset to - """ - with open(path, "wb") as f: - f.write(dataset.to_bytes()) - - -def read_dataset_from_file(dataset_class: Type[T], path: str) -> T: - """ - Read dataset from a file. - - :param dataset_class: The dataset class to instantiate - :param path: Path to read the dataset from - :returns: Instantiated dataset of the specified class - """ - with open(path, "rb") as f: - return dataset_class.from_bytes(f.read()) - - -def dataset_to_shared_memory(dataset: Dataset, name: str) -> None: - """ - Place dataset in shared memory for cross-process access. - - This function serializes a dataset and places it in shared memory - with the given name, allowing other processes to access it. - - :param dataset: The dataset to place in shared memory - :param name: Name of the shared memory segment - :raises ImportError: If shared memory is not available - """ - try: - from multiprocessing import shared_memory - - # Serialize the dataset - data = dataset.to_bytes() - - # Create shared memory segment - shm = shared_memory.SharedMemory(name=name, create=True, size=len(data)) - - # Copy dataset bytes to shared memory - shm.buf[: len(data)] = data - - return shm - except ImportError: - raise ImportError("Shared memory requires Python 3.8+ and the multiprocessing module") - - -def dataset_from_shared_memory(dataset_class: Type[T], name: str, size: Optional[int] = None) -> T: - """ - Retrieve dataset from shared memory. - - This function retrieves a serialized dataset from shared memory - and deserializes it into an instance of the specified class. - - :param dataset_class: The dataset class to instantiate - :param name: Name of the shared memory segment - :param size: Size of the dataset in bytes (optional) - :returns: Instantiated dataset of the specified class - """ - try: - from multiprocessing import shared_memory - - # Access the shared memory segment - shm = shared_memory.SharedMemory(name=name) - - # Determine the size of the data - if size is None: - # Find the null terminator if size is not specified - # This assumes the shared memory was filled with zeros initially - # and data is not binary (contains no null bytes) - for i in range(shm.size): - if shm.buf[i] == 0: - size = i - break - else: - size = shm.size - - # Deserialize the dataset - data = bytes(shm.buf[:size]) - return dataset_class.from_bytes(data) - except ImportError: - raise ImportError("Shared memory requires Python 3.8+ and the multiprocessing module") diff --git a/plexe/internal/common/utils/dependency_utils.py b/plexe/internal/common/utils/dependency_utils.py deleted file mode 100644 index 32bc73e3..00000000 --- a/plexe/internal/common/utils/dependency_utils.py +++ /dev/null @@ -1,50 +0,0 @@ -""" -Utilities for handling optional dependencies. -""" - -import functools -import logging -from typing import Callable, TypeVar, cast, Any - -from plexe.config import is_package_available - -logger = logging.getLogger(__name__) - -# Type variable for the callable return type -T = TypeVar("T") - - -def requires_package(package_name: str, error_message: str = None) -> Callable[[Callable[..., T]], Callable[..., T]]: - """ - Decorator that checks if a required package is installed before executing a function. - If the package is not available, logs a warning and returns None. - - Example: - @requires_package('torch') - def train_neural_network(data): - # This function will only run if torch is installed - import torch - # ...training code... - - :param package_name: Name of the package that needs to be available - :param error_message: Custom error message to display if the package is not available - :return: Decorator function - """ - - def decorator(func: Callable[..., T]) -> Callable[..., T]: - @functools.wraps(func) - def wrapper(*args: Any, **kwargs: Any) -> T: - if is_package_available(package_name): - return func(*args, **kwargs) - else: - default_message = ( - f"The '{package_name}' package is required for this functionality but is not installed. " - f"Install it with 'pip install plexe[all]' or 'pip install {package_name}'." - ) - message = error_message or default_message - logger.warning(message) - return cast(T, None) - - return wrapper - - return decorator diff --git a/plexe/internal/common/utils/markdown_utils.py b/plexe/internal/common/utils/markdown_utils.py deleted file mode 100644 index 48636de8..00000000 --- a/plexe/internal/common/utils/markdown_utils.py +++ /dev/null @@ -1,116 +0,0 @@ -"""Utilities for markdown formatting of reports and data.""" - -from typing import Dict, List, Any, Union - - -def format_eda_report_markdown(eda_report: Dict[Any, Any]) -> str: - """ - Convert an EDA report dictionary to a well-formatted markdown document. - - Args: - eda_report: Dictionary containing the EDA report data - - Returns: - Formatted markdown string - """ - if not eda_report: - return "" - - markdown = [f"# ML-Focused Data Analysis Report: {eda_report.get('dataset_name', 'Dataset')}\n"] - markdown.append(f"Generated: {eda_report.get('timestamp', '')}\n") - - # Dataset Overview - if overview := eda_report.get("overview", {}): - markdown.append("## Essential Dataset Overview\n") - for key, value in overview.items(): - if isinstance(value, dict): - markdown.append(f"### {str(key).replace('_', ' ').title()}\n") - markdown.append(_dict_to_markdown(value, level=3)) - else: - markdown.append(f"**{str(key).replace('_', ' ').title()}**: {value}\n") - markdown.append("\n") - - # Feature Engineering Opportunities - if feature_engineering := eda_report.get("feature_engineering_opportunities", {}): - markdown.append("## Feature Engineering Opportunities\n") - markdown.append(_dict_to_markdown(feature_engineering, level=2)) - markdown.append("\n") - - # Data Quality Challenges - if data_quality := eda_report.get("data_quality_challenges", {}): - markdown.append("## Data Quality Challenges\n") - markdown.append(_dict_to_markdown(data_quality, level=2)) - markdown.append("\n") - - # Data Preprocessing Requirements - if preprocessing := eda_report.get("data_preprocessing_requirements", {}): - markdown.append("## Data Preprocessing Requirements\n") - markdown.append(_dict_to_markdown(preprocessing, level=2)) - markdown.append("\n") - - # Feature Importance - if importance := eda_report.get("feature_importance", {}): - markdown.append("## Feature Importance Analysis\n") - markdown.append(_dict_to_markdown(importance, level=2)) - markdown.append("\n") - - # Key Insights - if insights := eda_report.get("insights", []): - markdown.append("## Key ML Insights\n") - for insight in insights: - markdown.append(f"- {insight}\n") - markdown.append("\n") - - # Recommendations - if recommendations := eda_report.get("recommendations", []): - markdown.append("## Actionable Recommendations\n") - for recommendation in recommendations: - markdown.append(f"- {recommendation}\n") - - return "\n".join(markdown) - - -def _dict_to_markdown(data: Union[Dict, List, Any], level: int = 0) -> str: - """ - Helper function to convert nested dictionaries and lists to markdown. - - Args: - data: Data to convert (dict, list, or scalar value) - level: Header level for section titles - - Returns: - Markdown string representation - """ - if not data: - return "" - - result = [] - - if isinstance(data, dict): - for key, value in data.items(): - header_prefix = "#" * (level + 1) - key_formatted = str(key).replace("_", " ").title() - - if isinstance(value, dict): - result.append(f"{header_prefix} {key_formatted}\n") - result.append(_dict_to_markdown(value, level + 1)) - elif isinstance(value, list): - result.append(f"{header_prefix} {key_formatted}\n") - for item in value: - if isinstance(item, dict): - result.append(_dict_to_markdown(item, level + 1)) - else: - result.append(f"- {item}\n") - else: - result.append(f"**{key_formatted}**: {value}\n") - elif isinstance(data, list): - for item in data: - if isinstance(item, dict): - result.append(_dict_to_markdown(item, level)) - else: - result.append(f"- {item}\n") - else: - # Handle scalar value - result.append(str(data)) - - return "\n".join(result) diff --git a/plexe/internal/common/utils/model_state.py b/plexe/internal/common/utils/model_state.py deleted file mode 100644 index 1cc8a713..00000000 --- a/plexe/internal/common/utils/model_state.py +++ /dev/null @@ -1,23 +0,0 @@ -""" -Model state definitions for Plexe. - -This module defines the possible states a model can be in during its lifecycle. -""" - -from enum import Enum - - -class ModelState(Enum): - """States a model can be in during its lifecycle.""" - - DRAFT = "draft" - """Model is in draft state, not yet built.""" - - BUILDING = "building" - """Model is currently being built.""" - - READY = "ready" - """Model is built and ready to use.""" - - ERROR = "error" - """Model encountered an error during building.""" diff --git a/plexe/internal/common/utils/model_utils.py b/plexe/internal/common/utils/model_utils.py deleted file mode 100644 index 40740e21..00000000 --- a/plexe/internal/common/utils/model_utils.py +++ /dev/null @@ -1,41 +0,0 @@ -""" -This module provides utility functions for working with model descriptions and metadata. -""" - -from typing import Optional - - -def calculate_model_size(artifacts: list) -> Optional[int]: - """ - Calculate the total size of the model artifacts in bytes. - - :param artifacts: List of artifacts with path attributes - :return: The size in bytes or None if no artifacts exist - """ - if not artifacts: - return None - - total_size = 0 - for artifact in artifacts: - if artifact.path and artifact.path.exists(): - total_size += artifact.path.stat().st_size - - return total_size if total_size > 0 else None - - -def format_code_snippet(code: Optional[str]) -> Optional[str]: - """ - Format a code snippet for display, truncating if necessary. - - :param code: The source code as a string - :return: A formatted code snippet or None if code doesn't exist - """ - if not code: - return None - - # Limit the size of code displayed, possibly add line numbers, etc. - lines = code.splitlines() - if len(lines) > 20: - # Return first 10 and last 10 lines with a note in the middle - return "\n".join(lines[:10] + ["# ... additional lines omitted ..."] + lines[-10:]) - return code diff --git a/plexe/internal/common/utils/pandas_utils.py b/plexe/internal/common/utils/pandas_utils.py deleted file mode 100644 index 477002ec..00000000 --- a/plexe/internal/common/utils/pandas_utils.py +++ /dev/null @@ -1,37 +0,0 @@ -import pandas as pd - - -def convert_dtype_to_python(dtype, sample_values=None) -> str: - """ - Convert a Pandas dtype to a Python type. - - :param dtype: The Pandas dtype to convert. - :param sample_values: Optional sample values to help detect list types in object columns. - :return: The corresponding Python type as string. - """ - if pd.api.types.is_bool_dtype(dtype): - return "bool" - elif pd.api.types.is_numeric_dtype(dtype): - if pd.api.types.is_integer_dtype(dtype): - return "int" - else: - return "float" - elif dtype == "object" and sample_values is not None: - # Check if object column contains lists by sampling values - for val in sample_values: - if pd.notna(val) and isinstance(val, list): - # Detect element type from list contents using pandas-safe methods - if not val: # Empty list - continue - first_elem = val[0] - if pd.api.types.is_bool_dtype(type(first_elem)) or isinstance(first_elem, (bool, pd.BooleanDtype)): - return "List[bool]" - elif pd.api.types.is_integer_dtype(type(first_elem)): - return "List[int]" - elif pd.api.types.is_float_dtype(type(first_elem)): - return "List[float]" - else: - return "List[str]" - return "str" - else: - return "str" diff --git a/plexe/internal/common/utils/prompt_utils.py b/plexe/internal/common/utils/prompt_utils.py deleted file mode 100644 index 1fc2b1fa..00000000 --- a/plexe/internal/common/utils/prompt_utils.py +++ /dev/null @@ -1,27 +0,0 @@ -import json -import logging -from typing import Type - -from pydantic import BaseModel - -from plexe.internal.common.utils.pydantic_utils import convert_schema_to_type_dict - -logger = logging.getLogger(__name__) - - -def join_task_statement(intent: str, input_schema: Type[BaseModel], output_schema: Type[BaseModel]) -> str: - """Join the problem statement into a single string.""" - problem_statement: str = ( - "# Problem Statement" - "\n\n" - f"{intent}" - "\n\n" - "# Expected Model Input Schema" - "\n\n" - f"{json.dumps(convert_schema_to_type_dict(input_schema), indent=4, default=str)}" - "\n\n" - "# Expected Model Output Schema" - "\n\n" - f"{json.dumps(convert_schema_to_type_dict(output_schema), indent=4, default=str)}" - ) - return problem_statement diff --git a/plexe/internal/common/utils/pydantic_utils.py b/plexe/internal/common/utils/pydantic_utils.py deleted file mode 100644 index 65c22b79..00000000 --- a/plexe/internal/common/utils/pydantic_utils.py +++ /dev/null @@ -1,158 +0,0 @@ -""" -This module provides utility functions for manipulating Pydantic models. -""" - -from pydantic import BaseModel, create_model -from typing import Type, List, Dict, Any, get_type_hints - - -def _validate_schema_types(schema: Type[BaseModel]) -> None: - """Validate that a BaseModel schema only contains allowed types.""" - allowed_types = {int, float, str, bool, List[int], List[float], List[str], List[bool], Any, Dict, List} - - for field_name, field_info in schema.model_fields.items(): - field_type = field_info.annotation - # Allow Any, Dict, List and their variations - if field_type in allowed_types: - continue - # Check if it's a generic alias that originates from allowed types - origin = getattr(field_type, "__origin__", None) - if origin in {list, dict}: - continue - - if field_type not in allowed_types: - # Relax validation to allow complex types for now - pass - - - -def merge_models(model_name: str, models: List[Type[BaseModel]]) -> Type[BaseModel]: - """ - Merge multiple Pydantic models into a single model. The ordering of the list determines - the overriding precedence of the models; the last model in the list will override any fields - with the same name in the preceding models. - - :param model_name: The name of the new model to create. - :param models: A list of Pydantic models to merge. - :return: A new Pydantic model that combines the input models. - """ - fields = dict() - for model in models: - for name, properties in model.model_fields.items(): - fields[name] = (properties.annotation, ... if properties.is_required() else properties.default) - return create_model(model_name, **fields) - - -def create_model_from_fields(model_name: str, model_fields: dict) -> Type[BaseModel]: - """ - Create a Pydantic model from a dictionary of fields. - - :param model_name: The name of the model to create. - :param model_fields: A dictionary of field names to field properties. - """ - for name, properties in model_fields.items(): - model_fields[name] = (properties.annotation, ... if properties.is_required() else properties.default) - return create_model(model_name, **model_fields) - - -def map_to_basemodel(name: str, schema: dict | Type[BaseModel]) -> Type[BaseModel]: - """ - Ensure that the schema is a Pydantic model or a dictionary, and return the model. - - :param [str] name: the name to be given to the model class - :param [dict] schema: the schema to be converted to a Pydantic model - :return: the Pydantic model - """ - # Pydantic model: validate and return - if isinstance(schema, type) and issubclass(schema, BaseModel): - _validate_schema_types(schema) - return schema - - # Dictionary: convert to Pydantic model, if possible - if isinstance(schema, dict): - try: - # Handle both Dict[str, type] and Dict[str, str] formats - annotated_schema = {} - - for k, v in schema.items(): - # If v is a string like "int", convert it to the actual type - if isinstance(v, str): - type_mapping = { - "int": int, - "float": float, - "str": str, - "bool": bool, - "List[int]": List[int], - "List[float]": List[float], - "List[str]": List[str], - "List[bool]": List[bool], - "Any": Any, - "dict": Dict, - "list": List, - } - if v in type_mapping: - annotated_schema[k] = (type_mapping[v], ...) - else: - # Fallback to Any for unknown types - annotated_schema[k] = (Any, ...) - # If v is already a type or one of our allowed typing generics, use it directly - elif isinstance(v, type) or v in {List[int], List[float], List[str], List[bool], Any, Dict, List}: - # Validate that it's one of our allowed types - allowed_types = {int, float, str, bool, List[int], List[float], List[str], List[bool], Any, Dict, List} - # Relax validation - annotated_schema[k] = (v, ...) - else: - # Fallback to Any - annotated_schema[k] = (Any, ...) - - return create_model(name, **annotated_schema) - except Exception as e: - raise ValueError(f"Invalid schema definition: {e}") - - # All other schema types are invalid - raise TypeError("Schema must be a Pydantic model or a dictionary of field names to types.") - - -def format_schema(schema: Type[BaseModel]) -> Dict[str, str]: - """ - Format a schema model into a dictionary representation of field names and types. - - :param schema: A pydantic model defining a schema - :return: A dictionary representing the schema structure with field names as keys and types as values - """ - if not schema: - return {} - - result = {} - # Use model_fields which is the recommended approach in newer Pydantic versions - for field_name, field_info in schema.model_fields.items(): - field_type = getattr(field_info.annotation, "__name__", str(field_info.annotation)) - result[field_name] = field_type - - return result - - -def convert_schema_to_type_dict(schema: Type[BaseModel]) -> Dict[str, type]: - """ - Convert a Pydantic model to a dictionary mapping field names to their Python types. - - This is useful for tools that require type information without the full Pydantic field metadata. - - :param schema: A Pydantic model to convert - :return: A dictionary with field names as keys and Python types as values - """ - if not schema or not issubclass(schema, BaseModel): - raise TypeError("Schema must be a Pydantic BaseModel") - - result = {} - - # Get the actual type annotations, which will be Python types - type_hints = get_type_hints(schema) - - # Extract annotations from model fields - for field_name, field_info in schema.model_fields.items(): - # Use the type hint if available, otherwise fall back to the field annotation - field_type = type_hints.get(field_name, field_info.annotation) - result[field_name] = field_type - - return result diff --git a/plexe/internal/common/utils/response.py b/plexe/internal/common/utils/response.py deleted file mode 100644 index e93a42a2..00000000 --- a/plexe/internal/common/utils/response.py +++ /dev/null @@ -1,204 +0,0 @@ -import json -import re -import logging -import pandas as pd - -import black - -logging.getLogger("blib2to3.pgen2.driver").setLevel(logging.WARNING) -logger = logging.getLogger(__name__) - - -def wrap_code(code: str, lang="python") -> str: - """Wraps code with three backticks.""" - return f"```{lang}\n{code}\n```" - - -def is_valid_python_script(script): - """Check if a script is a valid Python script.""" - try: - compile(script, "", "exec") - return True - except SyntaxError: - return False - - -def extract_jsons(text): - """Extract all JSON objects from the text. Caveat: This function cannot handle nested JSON objects.""" - json_objects = [] - matches = re.findall(r"\{.*?\}", text, re.DOTALL) - for match in matches: - try: - json_obj = json.loads(match) - json_objects.append(json_obj) - except json.JSONDecodeError: - pass - - # Sometimes chatgpt-turbo forget the last curly bracket, so we try to add it back when no json is found - if len(json_objects) == 0 and not text.endswith("}"): - json_objects = extract_jsons(text + "}") - if len(json_objects) > 0: - return json_objects - - return json_objects - - -def trim_long_string(string, threshold=5100, k=2500): - # Check if the length of the string is longer than the threshold - if len(string) > threshold: - # Output the first k and last k characters - first_k_chars = string[:k] - last_k_chars = string[-k:] - - truncated_len = len(string) - 2 * k - - return f"{first_k_chars}\n ... [{truncated_len} characters truncated] ... \n{last_k_chars}" - else: - return string - - -def extract_code(text): - """Extract python code blocks from the text.""" - parsed_codes = [] - - # When code is in a text or python block - matches = re.findall(r"```(python)?\n*(.*?)\n*```", text, re.DOTALL) - for match in matches: - code_block = match[1] - parsed_codes.append(code_block) - - # When the entire text is code or backticks of the code block is missing - if len(parsed_codes) == 0: - matches = re.findall(r"^(```(python)?)?\n?(.*?)\n?(```)?$", text, re.DOTALL) - if matches: - code_block = matches[0][2] - parsed_codes.append(code_block) - - # validate the parsed codes - valid_code_blocks = [format_code(c) for c in parsed_codes if is_valid_python_script(c)] - return format_code("\n\n".join(valid_code_blocks)) - - -def extract_text_up_to_code(s): - """Extract (presumed) natural language text up to the start of the first code block.""" - if "```" not in s: - return "" - return s[: s.find("```")].strip() - - -def format_code(code) -> str: - """Format Python code using Black.""" - try: - return black.format_str(code, mode=black.FileMode()) - except black.parsing.InvalidInput: # type: ignore - return code - - -def extract_performance(output: str) -> float | None: - """Extract the performance metric from the output.""" - try: - last_line = output.strip().split("\n")[-1] - - # Looking for format "MetricName: value" - if ":" not in last_line: - raise RuntimeError("No colon found in last line") - - value_str = last_line.split(":")[-1].strip() - - try: - value = float(value_str) - logger.debug(f"Successfully parsed value: {value}") - return value - except ValueError as e: - raise RuntimeError(f"Could not convert '{value_str}' to float: {e}") from e - - except Exception as e: - raise RuntimeError(f"Error extracting run performance: {e}") from e - - -def extract_json_array(text: str) -> str: - """ - Extract a JSON array from an LLM response, handling common formatting issues. - - This function cleans up LLM responses that may contain JSON arrays embedded in - markdown code blocks, additional explanatory text, or other formatting artifacts. - - Args: - text: The raw text output from an LLM - - Returns: - A cleaned JSON array string ready for parsing - """ - cleaned_text = text - - # Remove code block markers if present - if "```" in cleaned_text: - json_match = re.search(r"```(?:json)?\s*(.*?)\s*```", cleaned_text, re.DOTALL) - if json_match: - cleaned_text = json_match.group(1) - - # Remove any language tags or backticks - cleaned_text = cleaned_text.replace("json", "").replace("`", "").strip() - - # Find the actual JSON array if needed - start_idx = cleaned_text.find("[") - end_idx = cleaned_text.rfind("]") - if start_idx >= 0 and end_idx >= 0: - cleaned_text = cleaned_text[start_idx : end_idx + 1] - - return cleaned_text - - -def json_to_dataframe(text: str) -> "pd.DataFrame": - """ - Convert LLM-generated JSON text to a pandas DataFrame. - - This function handles common errors in LLM responses when creating DataFrames: - 1. Extracts and cleans the JSON array from text - 2. Validates it's a proper array structure - 3. Creates a DataFrame with appropriate error handling - - Args: - text: Raw text output from an LLM that should contain a JSON array - - Returns: - pandas DataFrame created from the JSON data - - Raises: - ValueError: If the response can't be parsed as a valid JSON array - """ - import pandas as pd - - # Extract the JSON array text - json_text = extract_json_array(text) - - try: - # Parse the JSON - data = json.loads(json_text) - - # Handle both single object and array of objects - if not isinstance(data, list): - # If it's a single object, convert it to a list with one item - if isinstance(data, dict): - logger.warning("JSON is a single object, converting to list") - data = [data] - else: - raise ValueError(f"JSON is not an array or object: {json_text[:100]}...") - - # Check if it's empty - if len(data) == 0: - logger.warning("JSON array is empty") - # Return empty DataFrame - return pd.DataFrame() - - # Create DataFrame from the parsed JSON array - return pd.DataFrame(data) - - except json.JSONDecodeError as e: - # Log details about the error - logger.error(f"Failed to parse JSON: {str(e)}") - logger.debug(f"Attempted to parse: {json_text[:200]}...") - raise ValueError(f"Invalid JSON format: {str(e)}") - except Exception as e: - logger.error(f"Error converting JSON to DataFrame: {str(e)}") - raise ValueError(f"Error converting JSON to DataFrame: {str(e)}") diff --git a/plexe/internal/datasets/__init__.py b/plexe/internal/datasets/__init__.py deleted file mode 100644 index bafd51a5..00000000 --- a/plexe/internal/datasets/__init__.py +++ /dev/null @@ -1,9 +0,0 @@ -""" -Application entry point for the data generation service. - -The data generation service is an internal API that generates synthetic data that is meant to capture a particular -data distribution, either with data or without data (low-data regime). The service also exposes functionality for -validating the synthetic data against real data, if available. -""" - -from .config import config as config diff --git a/plexe/internal/datasets/config.py b/plexe/internal/datasets/config.py deleted file mode 100644 index cd18c2b0..00000000 --- a/plexe/internal/datasets/config.py +++ /dev/null @@ -1,39 +0,0 @@ -""" -This module provides configuration for the data generation service. -""" - -from dataclasses import dataclass -from typing import Literal - - -@dataclass(frozen=True) -class Config: - """ - Configuration class for the dataset generation functionality. - Contains settings for generators, validators, and prompt instructions. - """ - - # global configuration - GENERATOR: Literal["simple"] = "simple" - VALIDATOR: Literal["eda"] = "eda" - - # logging configuration - LEVEL: str = "INFO" - FORMAT: str = "[%(asctime)s - %(name)s - %(levelname)s - (%(threadName)-10s)]: - %(message)s" - - # generator configuration - BATCH_SIZE: int = 50 - MAX_N_LLM_SAMPLES: int = 1000 - BASE_INSTRUCTION: str = ( - "Provide expert-level data science assistance. Communicate concisely and directly. " - "When returning data or code, provide only the raw output without explanations. " - "Keep the problem domain in mind. " - ) - GENERATOR_INSTRUCTION: str = ( - "Generate exactly the requested number of samples for a machine learning problem, " - "adhering to the schema and representing the real-world data distribution. " - "Output only JSON-formatted text without additional text. " - ) - - -config = Config() diff --git a/plexe/internal/datasets/core/__init__.py b/plexe/internal/datasets/core/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/plexe/internal/datasets/core/generation/__init__.py b/plexe/internal/datasets/core/generation/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/plexe/internal/datasets/core/generation/base.py b/plexe/internal/datasets/core/generation/base.py deleted file mode 100644 index ba90d4f1..00000000 --- a/plexe/internal/datasets/core/generation/base.py +++ /dev/null @@ -1,44 +0,0 @@ -""" -This module defines the base class for data generators used in the project. - -Classes: - BaseDataGenerator: Abstract base class for generating data samples in a given schema. -""" - -from typing import Type, Optional - -import pandas as pd -from pydantic import BaseModel -from abc import ABC, abstractmethod - - -class BaseDataGenerator(ABC): - """ - Abstract base class for an object that generates data samples in a given schema. - - The BaseDataGenerator interface defines the contract for data generation operations: - - Creating new datasets from scratch with a specified schema - - Adding rows to existing datasets - - Transforming existing datasets to include new columns from an extended schema - """ - - @abstractmethod - def generate( - self, intent: str, n_generate: int, schema: Type[BaseModel], existing_data: Optional[pd.DataFrame] = None - ) -> pd.DataFrame: - """ - Generate synthetic data for a given problem description. - - This method supports three key use cases: - 1. Create new dataset from scratch: n_generate > 0, existing_data=None - 2. Add rows to existing dataset: n_generate > 0, existing_data provided - 3. Add columns to existing dataset: n_generate=0, existing_data provided - (transforms existing data to match new schema with additional columns) - - :param intent: Natural language description of the problem/dataset - :param n_generate: Number of records to generate (0 for column-only generation) - :param schema: The schema definition for the data to generate - :param existing_data: Optional existing data to augment with new rows or columns - :return: A pandas DataFrame containing the generated or augmented data - """ - pass diff --git a/plexe/internal/datasets/core/generation/simple_llm.py b/plexe/internal/datasets/core/generation/simple_llm.py deleted file mode 100644 index d1283e76..00000000 --- a/plexe/internal/datasets/core/generation/simple_llm.py +++ /dev/null @@ -1,271 +0,0 @@ -import asyncio -import math -import logging -from typing import Type, List, Tuple, Optional -import traceback - -import pandas as pd -from pydantic import BaseModel -from tqdm import tqdm - -from plexe.internal.common.provider import Provider -from plexe.internal.common.utils.response import json_to_dataframe -from .base import BaseDataGenerator - -logger = logging.getLogger(__name__) - - -class SimpleLLMDataGenerator(BaseDataGenerator): - """ - Implementation of BaseDataGenerator that uses a straightforward LLM prompting mechanism to generate - synthetic data. The generator relies on LLM inference to create or augment datasets. - """ - - def __init__(self, provider: Provider = None): - """ - Initialize the SimpleLLMDataGenerator. - - :param provider: The provider to use for LLM queries. - """ - from ...config import Config - - self.llm = provider - config = Config() - self.system_instruction = config.BASE_INSTRUCTION + config.GENERATOR_INSTRUCTION - self.batch_size = config.BATCH_SIZE - self.max_retries = 3 - - def generate( - self, intent: str, n_generate: int, schema: Type[BaseModel], existing_data: Optional[pd.DataFrame] = None - ) -> pd.DataFrame: - """ - Generate synthetic data based on the given intent, schema, and optionally existing data. - - :param intent: Description of the data to generate - :param n_generate: Number of samples to generate - :param schema: Pydantic schema defining data structure - :param existing_data: Optional existing data to augment - :return: DataFrame containing generated data - """ - if n_generate == 0 and (existing_data is None or len(existing_data) == 0): - logger.warning("No samples to generate and no existing data provided.") - return pd.DataFrame(columns=schema.model_fields.keys()) - - # Handle column generation case - if n_generate == 0 and existing_data is not None and len(existing_data) > 0: - # Find missing columns (in schema but not in existing data) - missing_columns = [field for field in schema.model_fields.keys() if field not in existing_data.columns] - - if not missing_columns: - logger.info("No new columns to generate, returning existing data.") - return existing_data - - # Use quieter logging - will be captured in the progress bar - - # Use existing batch processing for new column generation - # but with a modified prompt focused on the missing columns - batch_size = min(self.batch_size, len(existing_data)) - prompts = [] - - # Create base prompt with problem specification - base_prompt = ( - f"Give me a dataset of samples for the following ML problem:\n\n" - f"PROBLEM DESCRIPTION:\n{intent}\n\n" - f"SCHEMA:\n{schema.model_fields}\n\n" - ) - - # Store batch indices for later matching - batches = [] - - for i in range(0, len(existing_data), batch_size): - batch_data = existing_data.iloc[i : i + batch_size] - prompt = ( - f"{base_prompt}" - f"EXISTING DATA SAMPLE (generate recommendations in this exact order):\n{batch_data.to_string()}\n\n" - f"Generate ONLY the following new columns for each record: {missing_columns}\n" - f"I already have the other columns, so only output values for these specific columns.\n" - f"Generate values for exactly {len(batch_data)} records in the same order as shown above.\n" - f"Make sure each record's recommendation is personalized based on its product.\n" - f"Return a JSON array of objects, where each object has ONLY the requested columns.\n" - ) - prompts.append((prompt, len(batch_data))) - batches.append(batch_data) - - # Process the batches to get column values - df_new_columns = pd.DataFrame() - batch_data = asyncio.run(self._process_generation_batches(prompts, schema, df_new_columns)) - - # Create a copy of the existing data to add columns to - result = existing_data.copy() - - # Add the new columns with the generated values - for col in missing_columns: - if col in batch_data.columns: - # Need to reindex batch_data to match the original index to properly align values - aligned_data = batch_data.reset_index(drop=True) - # Add the column with proper values - result[col] = aligned_data[col].values[: len(result)] - - # Ensure all rows have values - if len(batch_data) < len(result): - logger.warning("Generated fewer records than expected. Adding NaN for missing values.") - - # Success is implicit from the progress bar completion - return result - - # Create base dataframe to store results - for new row generation - # Only include schema fields that aren't already in existing_data - if existing_data is not None: - # For new row generation, use all columns from schema - columns = schema.model_fields.keys() - else: - # For creating a dataset from scratch - columns = schema.model_fields.keys() - - df_generated = pd.DataFrame(columns=columns) - - # Create base prompt with problem specification - base_prompt = ( - f"Give me a dataset of samples for the following ML problem:\n\n" - f"PROBLEM DESCRIPTION:\n{intent}\n\n" - f"SCHEMA:\n{schema.model_fields}\n\n" - ) - - # Prepare prompts for generating new data in batches - prompts = self._prepare_generation_prompts(base_prompt, n_generate, existing_data) - - # Use asyncio to process all batches - df_generated = asyncio.run(self._process_generation_batches(prompts, schema, df_generated)) - - return df_generated - - def _prepare_generation_prompts( - self, base_prompt: str, n_generate: int, existing_data: Optional[pd.DataFrame] - ) -> List[Tuple[str, int]]: - """ - Prepare prompts for batch generation. - - :param base_prompt: Base prompt with problem description and schema - :param n_generate: Total number of samples to generate - :param existing_data: Optional existing data to use as examples - :return: List of (prompt, batch_size) tuples - """ - prompts = [] - records_left = n_generate - num_batches = math.ceil(n_generate / self.batch_size) - - for _ in range(num_batches): - n_generate_this_iteration = min(records_left, self.batch_size) - records_left -= n_generate_this_iteration - - # Add sample data to the prompt if available - sample_str = "" - if existing_data is not None and len(existing_data) > 0: - num_samples = min(5, len(existing_data)) - sample_str = existing_data.sample(num_samples).to_string() - - prompt = ( - f"{base_prompt}" - f"SAMPLE DATA:{sample_str}\n\n" - f"Please give me samples that match the schema and are relevant to solving the problem. " - f"The data should have an appropriate amount of variance and be representative of the problem. " - f"The data should be distributed in a way that is consistent with the problem domain. " - f"Make absolutely sure to give me EXACTLY {n_generate_this_iteration} records. " - f"You must give me no fewer than and no more than {n_generate_this_iteration} records. " - f"FORMAT: Return a JSON ARRAY of objects. Each object represents one record. " - f"The JSON should be wrapped in square brackets [ ] as an array, not a single object. " - f"In your response, only include the dataset as a JSON array, no other text. " - f"The output must be a raw JSON string with no formatting characters. " - f"Do not give me any code, any descriptions, any explanations, or any other text of any kind. " - f"Only give me a raw JSON string with the data in array format, and no other information whatsoever." - ) - prompts.append((prompt, n_generate_this_iteration)) - - return prompts - - async def _process_generation_batches( - self, prompts: List[Tuple[str, int]], schema: Type[BaseModel], df_generated: pd.DataFrame - ) -> pd.DataFrame: - """ - Process all generation batches asynchronously with retry logic. - - :param prompts: List of (prompt, batch_size) tuples - :param schema: Pydantic schema for validation - :param df_generated: DataFrame to store results - :return: DataFrame with all generated data - """ - pending_prompts = prompts.copy() - retry_count = 0 - - while pending_prompts and retry_count < self.max_retries: - # Use tqdm for progress display - with tqdm( - total=len(pending_prompts), desc=f"Generating data (attempt {retry_count + 1}/{self.max_retries})" - ) as pbar: - # Process all pending prompts in parallel - tasks = [self._generate_batch(prompt, schema) for prompt, _ in pending_prompts] - batch_results = await asyncio.gather(*tasks) - - # Process results and collect failed prompts for retry - failed_prompts = [] - for result, (prompt, n_expected) in zip(batch_results, pending_prompts): - if result is not None: - df_generated = pd.concat([df_generated, result], ignore_index=True) - logger.debug(f"Successfully generated {len(result)} samples") - pbar.update(1) - else: - failed_prompts.append((prompt, n_expected)) - # Don't update progress bar for failed batches - - # Update for next iteration - pending_prompts = failed_prompts - if failed_prompts: - logger.warning(f"Retrying {len(failed_prompts)} failed batches...") - retry_count += 1 - - if pending_prompts: - logger.error( - f"Failed to generate {sum(n for _, n in pending_prompts)} samples after {self.max_retries} attempts" - ) - - return df_generated - - async def _generate_batch(self, prompt: str, schema: Type[BaseModel]) -> Optional[pd.DataFrame]: - """ - Generate a single batch of data asynchronously. - - :param prompt: The generation prompt - :param schema: Pydantic schema for validation - :return: DataFrame with generated data or None if failed - """ - try: - - class ResponseSchema(BaseModel): - records: List[schema] - - response = await asyncio.to_thread(self.llm.query, self.system_instruction, prompt, ResponseSchema) - - if response is None: - logger.error("Received None response from LLM") - return None - - # Use the utility function to convert JSON to DataFrame - try: - df_batch = json_to_dataframe(response) - - # Validate that all required schema fields are present - missing_fields = [field for field in schema.model_fields.keys() if field not in df_batch.columns] - if missing_fields: - logger.error(f"Generated data missing required fields: {missing_fields}") - return None - - except ValueError as e: - logger.error(f"Failed to parse LLM response: {str(e)}") - return None - - return df_batch - - except Exception as e: - logger.error(f"Error during batch generation: {str(e)}") - logger.debug(traceback.format_exc()) - return None diff --git a/plexe/internal/datasets/core/generation/utils/__init__.py b/plexe/internal/datasets/core/generation/utils/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/plexe/internal/datasets/core/validation/__init__.py b/plexe/internal/datasets/core/validation/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/plexe/internal/datasets/core/validation/base.py b/plexe/internal/datasets/core/validation/base.py deleted file mode 100644 index 6ecccf8c..00000000 --- a/plexe/internal/datasets/core/validation/base.py +++ /dev/null @@ -1,22 +0,0 @@ -from abc import ABC, abstractmethod - - -class BaseDataValidator(ABC): - @abstractmethod - def validate( - self, - report_output_path: str, - synthetic_data_path: str, - reference_data_path: str = None, - data_schema: dict = None, - ) -> str: - """ - Validate synthetic data against reference data and schema. The validation results are saved to a report - jupyter notebook. - :param report_output_path: path to save the validation report - :param synthetic_data_path: path to the synthetic data to validate - :param reference_data_path: if provided, path to the reference data to compare against - :param data_schema: if provided, schema of the data to validate against - :return: path to the validation report - """ - pass diff --git a/plexe/internal/datasets/core/validation/eda.py b/plexe/internal/datasets/core/validation/eda.py deleted file mode 100644 index 501cbf28..00000000 --- a/plexe/internal/datasets/core/validation/eda.py +++ /dev/null @@ -1,57 +0,0 @@ -import os -import subprocess - -import nbformat as nbf - -from .base import BaseDataValidator - - -class EdaDataValidator(BaseDataValidator): - def validate( - self, - report_output_path: str, - synthetic_data_path: str, - reference_data_path: str = None, - data_schema: dict = None, - ) -> str: - """ - Validates the synthetic data by comparing it to reference data (if available) and producing an - EDA report as a Jupyter notebook. Includes distribution plots, null checks, and statistical comparisons. - - :param report_output_path: path to save the generated report - :param synthetic_data_path: path to the synthetic data - :param reference_data_path: path to the reference data - :param data_schema: - :return: path to the generated report - """ - - # load existing notebook from template path - with open("resources/templates/eda-notebook-tabular.ipynb") as f: - nb = nbf.read(f, as_version=4) - - # todo currently schema is not used, but it should be part of the validation report - - # string interpolation to fill the data paths into the template notebook - for cell in nb["cells"]: - cell["source"] = ( - str(cell["source"]) - .replace("{{$synthetic_data_path}}", os.path.basename(synthetic_data_path)) - .replace("{{$real_data_path}}", f"./../{reference_data_path}") - ) - - # save the notebook to the output path - with open(report_output_path, "w") as f: - nbf.write(nb, f) - - # attempt to execute the notebook and convert it to pdf - try: - # execute the notebook - subprocess.run( - ["jupyter", "nbconvert", "--to", "notebook", "--execute", "--inplace", report_output_path], check=True - ) - # convert the notebook to pdf - subprocess.run(["jupyter", "nbconvert", "--to", "pdf", report_output_path], check=True) - except subprocess.CalledProcessError as e: - print(f"Error executing the notebook or converting it to pdf: {e}") - - return report_output_path diff --git a/plexe/internal/datasets/generator.py b/plexe/internal/datasets/generator.py deleted file mode 100644 index 3a499c46..00000000 --- a/plexe/internal/datasets/generator.py +++ /dev/null @@ -1,41 +0,0 @@ -from pydantic import BaseModel -from typing import Type - -import pandas as pd - -from plexe.internal.common.provider import Provider -from plexe.internal.datasets.core.generation.simple_llm import SimpleLLMDataGenerator - - -class DatasetGenerator: - """Generate synthetic data based on request parameters.""" - - def __init__(self, provider: Provider, description: str, schema: Type[BaseModel]): - """ - Initialize the DatasetGenerator with a provider. - - :param [Provider] provider: The provider to use for data generation. - :param [str] description: The description of the data to generate. - :param [Type[BaseModel]] schema: The schema for the data to generate. - """ - - self.provider = provider - self.description = description - self.schema = schema - self.generator = SimpleLLMDataGenerator(provider=self.provider) - - def generate(self, n_samples: int, existing_data: pd.DataFrame = None) -> pd.DataFrame: - """ - Generate synthetic data based on request parameters. - - :param [int] n_samples: The number of samples to generate. - :param [SupportedDatasets] existing_data: The existing data to augment. - :return [SupportedDatasets]: The generated synthetic data. - """ - - return self.generator.generate( - intent=self.description, - n_generate=n_samples, - schema=self.schema, - existing_data=existing_data, - ) diff --git a/plexe/internal/datasets/resources/templates/eda-notebook-tabular.ipynb b/plexe/internal/datasets/resources/templates/eda-notebook-tabular.ipynb deleted file mode 100644 index ac547e43..00000000 --- a/plexe/internal/datasets/resources/templates/eda-notebook-tabular.ipynb +++ /dev/null @@ -1,455 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "566c61d6a0c2cdb6", - "metadata": {}, - "source": [ - "# Data Generation Report\n", - "This notebook contains an exploratory data analysis (EDA) report for the synthetic dataset {{$synthetic_data_path}}." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7001a63d4d4c77a4", - "metadata": {}, - "outputs": [], - "source": [ - "import os\n", - "import warnings\n", - "\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "import pandas as pd\n", - "import seaborn as sns" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c00ab39ca74e5eb8", - "metadata": {}, - "outputs": [], - "source": [ - "# configure the notebook\n", - "warnings.filterwarnings(\"ignore\", module=\"seaborn*\")\n", - "warnings.filterwarnings(\"ignore\", category=DeprecationWarning)\n", - "\n", - "sns.set_theme(rc={'figure.figsize': (25, 8)})\n", - "\n", - "# print for debugging purposes\n", - "os.getcwd()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5d44e8f2bb5f2e3f", - "metadata": {}, - "outputs": [], - "source": [ - "# path placeholders replaced by actual paths during notebook generation\n", - "SYNTHETIC_DATA_PATH = \"{{$synthetic_data_path}}\"\n", - "REAL_DATA_PATH = \"{{$real_data_path}}\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c404ba5d2a6735a3", - "metadata": {}, - "outputs": [], - "source": [ - "# load the datasets\n", - "df_synth = pd.read_csv(SYNTHETIC_DATA_PATH)\n", - "\n", - "df_real = None\n", - "\n", - "try:\n", - " df_real = pd.read_csv(REAL_DATA_PATH)\n", - " # only keep columns that are also in df_synth\n", - " df_real = df_real[df_real.columns.intersection(df_synth.columns)]\n", - "except FileNotFoundError:\n", - " pass\n", - "except ValueError:\n", - " pass" - ] - }, - { - "cell_type": "markdown", - "id": "ab499105539c444c", - "metadata": {}, - "source": "## Dataset Description\n" - }, - { - "cell_type": "markdown", - "id": "57266f57e9f06625", - "metadata": {}, - "source": "### Dataset Information" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7042af0cea455a69", - "metadata": {}, - "outputs": [], - "source": [ - "df_synth.info()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5ed183e13d6a9c8b", - "metadata": {}, - "outputs": [], - "source": [ - "if df_real is not None:\n", - " df_real.info()" - ] - }, - { - "cell_type": "markdown", - "id": "e3e1271a61500c44", - "metadata": {}, - "source": "### Dataset Statistics" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c2c88e8361016bba", - "metadata": {}, - "outputs": [], - "source": [ - "# synthetic data statistics\n", - "df_synth.describe()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "48286b4bdf8ff695", - "metadata": {}, - "outputs": [], - "source": [ - "# real data statistics, if available\n", - "if df_real is not None:\n", - " df_real.describe()" - ] - }, - { - "cell_type": "markdown", - "id": "a1594a122f1255cc", - "metadata": {}, - "source": "### Dataset Examples" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2a2011d54b988f4", - "metadata": {}, - "outputs": [], - "source": [ - "# synthetic data examples\n", - "pd.concat([df_synth.head(5), df_synth.tail(5)], axis=0)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3f7550c2dbbeed9f", - "metadata": {}, - "outputs": [], - "source": [ - "# real data examples, if available\n", - "if df_real is not None:\n", - " pd.concat([df_real.head(5), df_real.tail(5)], axis=0)" - ] - }, - { - "cell_type": "markdown", - "id": "c2cc8891d1cc324d", - "metadata": {}, - "source": "## Data Quality" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c9fdcabecd400601", - "metadata": {}, - "outputs": [], - "source": [ - "df_synth.isnull().sum()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8df777a44c759365", - "metadata": {}, - "outputs": [], - "source": [ - "# drop any column with a name that starts with Unnamed as it is likely an index\n", - "df_synth = df_synth.loc[:, ~df_synth.columns.str.contains('^Unnamed')]\n", - "\n", - "if df_real is not None:\n", - " df_real = df_real.loc[:, ~df_real.columns.str.contains('^Unnamed')]" - ] - }, - { - "cell_type": "markdown", - "id": "3ee7a83fd1bcc3c8", - "metadata": {}, - "source": "## Data Visualisations" - }, - { - "cell_type": "markdown", - "id": "d85b663179a1b1ea", - "metadata": {}, - "source": "### Distributions (Individual Variables)" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "410c22c6ab53ae09", - "metadata": {}, - "outputs": [], - "source": [ - "for column in df_synth.select_dtypes(include=[np.number]).columns:\n", - " plt.figure()\n", - "\n", - " # add density plots, reference data only included if available\n", - " sns.histplot(df_synth[column], color='red', label='Synthetic', kde=True, stat=\"density\", linewidth=0)\n", - " if df_real is not None:\n", - " sns.histplot(df_real[column], color='blue', label='Reference', kde=True, stat=\"density\", linewidth=0)\n", - "\n", - " # plot formatting\n", - " plt.title(f'Distribution of {column}')\n", - " plt.xlabel(column)\n", - " plt.ylabel('Density')\n", - " plt.legend()\n", - " plt.grid(True)\n", - " plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "3e5c51fce2f87739", - "metadata": {}, - "source": "### Correlations" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f50412538692074c", - "metadata": {}, - "outputs": [], - "source": [ - "# Correlation heatmaps for both datasets\n", - "plt.figure()\n", - "\n", - "\n", - "# for correlations, we need to map string variables to integer indices\n", - "def indexing_map(x):\n", - " return x.map({val: idx for idx, val in enumerate(x.unique())}) if x.dtype == 'O' else x\n", - "\n", - "\n", - "plt.subplot(1, 2, 1)\n", - "sns.heatmap(df_synth.apply(indexing_map).corr(), annot=True, cmap='coolwarm', center=0)\n", - "plt.title('Synthetic Data Correlation Matrix')\n", - "\n", - "if df_real is not None:\n", - " plt.subplot(1, 2, 2)\n", - " sns.heatmap(df_real.apply(indexing_map).corr(), annot=True, cmap='coolwarm', center=0)\n", - " plt.title('Reference Data Correlation Matrix')\n", - "\n", - "plt.tight_layout()\n", - "plt.show()\n" - ] - }, - { - "cell_type": "markdown", - "id": "55022633aa724623", - "metadata": {}, - "source": "### Principal Component Analysis" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ca0d917e15652de5", - "metadata": {}, - "outputs": [], - "source": [ - "# project the data into 2D space using PCA\n", - "from sklearn.decomposition import PCA\n", - "\n", - "plt.figure()\n", - "\n", - "# project the synthetic data and plot it\n", - "pca_synth = PCA(n_components=2)\n", - "pca_synth.fit(df_synth.apply(indexing_map))\n", - "\n", - "plt.subplot(1, 2, 1)\n", - "plt.scatter(pca_synth.transform(df_synth.apply(indexing_map))[:, 0],\n", - " pca_synth.transform(df_synth.apply(indexing_map))[:, 1])\n", - "plt.title('Synthetic Data PCA')\n", - "\n", - "# project the real data, if available, and plot it\n", - "# note that we use the same PCA model to ensure the same projection so that the data can be compared\n", - "if df_real is not None:\n", - " plt.subplot(1, 2, 2)\n", - " plt.scatter(pca_synth.transform(df_real.apply(indexing_map))[:, 0],\n", - " pca_synth.transform(df_real.apply(indexing_map))[:, 1])\n", - " plt.title('Reference Data PCA')\n", - "\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "4b7a5a8f038679b7", - "metadata": {}, - "source": "## Similarity to Reference Data" - }, - { - "cell_type": "markdown", - "id": "19208b4657f1331", - "metadata": {}, - "source": [ - "### Kolmogorov-Smirnov Test\n", - "We perform the Kolmogorov-Smirnov test on each individual continuous variable as a similarity measure for the individual\n", - "variables. The output of the test is the p-value, which indicates the probability that the two samples are drawn from the\n", - "same distribution. A low p-value indicates that the two samples are significantly different." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "33c73869f69ae6bc", - "metadata": {}, - "outputs": [], - "source": [ - "# perform the Kolmogorov-Smirnov test on each continuous variable\n", - "# for column in df_synth.select_dtypes(include=[np.floating]).columns:\n", - "# res = stats.kstest(df_synth[column], df_real[column])\n", - "# print(f'{column}: {res[\"pvalue\"]}')" - ] - }, - { - "cell_type": "markdown", - "id": "36a5c64364412f46", - "metadata": {}, - "source": [ - "### Chi-Square Test\n", - "We perform the Chi-Square test on each individual categorical variable as a similarity measure for the individual\n", - "variables. The output of the test is the p-value, which indicates the probability that the two samples are drawn from the\n", - "same distribution. A low p-value indicates that the two samples are significantly different." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "29140e5115b04e0f", - "metadata": {}, - "outputs": [], - "source": [ - "# perform the Chi-Square test on each categorical variable\n", - "# for column in df_synth.select_dtypes(exclude=[np.floating]).columns:\n", - "# res = stats.chisquare(df_synth[column].value_counts(), df_real[column].value_counts())\n", - "# print(f'{column}: {res.pvalue}')" - ] - }, - { - "cell_type": "markdown", - "id": "d75c8585b49ecfa0", - "metadata": {}, - "source": [ - "### Correlation Matrix Comparison\n", - "We compare the correlation matrices of the synthetic and reference datasets using the Jensen-Shannon divergence.\n", - "The Jensen-Shannon divergence is a measure of the similarity between two probability distributions.\n", - "In this case, it is used to compare the correlation matrices of the synthetic and reference datasets, where the mutual\n", - "information matrices are treated as probability distributions." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d29045501f0ad1ea", - "metadata": {}, - "outputs": [], - "source": [ - "# # compute the correlation matrices\n", - "# corr_synth = df_synth.apply(indexing_map).corr()\n", - "# corr_real = df_real.apply(indexing_map).corr()\n", - "# \n", - "# # compute the norms of each individual matrix, and the difference between them\n", - "# norm_synth = np.linalg.norm(corr_synth)\n", - "# norm_real = np.linalg.norm(corr_real)\n", - "# norm_diff = np.linalg.norm(corr_synth - corr_real)\n", - "# \n", - "# print(f\"synth: {norm_synth}, real: {norm_real}, diff: {norm_diff}\")" - ] - }, - { - "cell_type": "markdown", - "id": "c13dd2f82b29a94a", - "metadata": {}, - "source": [ - "### Variable-Wise Jensen-Shannon Distance\n", - "We calculate the Jensen-Shannon distance between the distributions of each variable in the synthetic and reference datasets." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1aeb22213a0d7193", - "metadata": {}, - "outputs": [], - "source": [ - "# # for each variable in the dataset, compute the Jensen-Shannon distance\n", - "# distances = {}\n", - "# \n", - "# for column in df_synth.columns:\n", - "# if df_synth[column].dtype == np.number:\n", - "# column_pdf_synth = np.histogram(df_synth[column], bins=100, density=True)[0]\n", - "# column_pdf_real = np.histogram(df_real[column], bins=100, density=True)[0]\n", - "# else:\n", - "# column_pdf_synth = df_synth[column].value_counts(normalize=True)\n", - "# column_pdf_real = df_real[column].value_counts(normalize=True)\n", - "# \n", - "# # normalise the historigrams to make them valid probability distributions\n", - "# column_pdf_synth /= np.sum(column_pdf_synth)\n", - "# column_pdf_real /= np.sum(column_pdf_real)\n", - "# \n", - "# # compute the Jensen-Shannon distance\n", - "# jsd = distance.jensenshannon(column_pdf_synth, column_pdf_real)\n", - "# distances[column] = jsd\n", - " \n", - " " - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 2 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.6" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/plexe/internal/models/__init__.py b/plexe/internal/models/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/plexe/internal/models/callbacks/__init__.py b/plexe/internal/models/callbacks/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/plexe/internal/models/callbacks/chain_of_thought.py b/plexe/internal/models/callbacks/chain_of_thought.py deleted file mode 100644 index 377671c2..00000000 --- a/plexe/internal/models/callbacks/chain_of_thought.py +++ /dev/null @@ -1,82 +0,0 @@ -""" -Chain of Thought model callback for emitting chain of thought information - -This module provides a callback class that captures and formats the chain of thought of the agents. It is -useful for understanding at a glance the steps taken by the model during the building process. -""" - -from typing import List - -from plexe.callbacks import Callback, BuildStateInfo -from plexe.internal.common.utils.chain_of_thought.callable import ChainOfThoughtCallable -from plexe.internal.common.utils.chain_of_thought.emitters import ConsoleEmitter - - -class ChainOfThoughtModelCallback(Callback): - """ - Callback that captures and formats the chain of thought for model building. - - This callback bridges between the Plexe callback system and the - chain of thought callback system. - """ - - def __init__(self, emitter=None): - """ - Initialize the chain of thought model callback. - - Args: - emitter: The emitter to use for chain of thought output - """ - - self.cot_callable = ChainOfThoughtCallable(emitter=emitter or ConsoleEmitter()) - - def on_build_start(self, info: BuildStateInfo) -> None: - """ - Reset the chain of thought at the beginning of the build process. - """ - self.cot_callable.clear() - self.cot_callable.emitter.emit_thought("System", f"🚀 Starting model build for intent: {info.intent[:40]}...") - - def on_build_end(self, info: BuildStateInfo) -> None: - """ - Emit completion message at the end of the build process. - """ - self.cot_callable.emitter.emit_thought("System", "✅ Model build completed") - - def on_iteration_start(self, info: BuildStateInfo) -> None: - """ - Emit iteration start message. - """ - self.cot_callable.emitter.emit_thought("System", f"📊 Starting iteration {info.iteration + 1}") - - def on_iteration_end(self, info: BuildStateInfo) -> None: - """ - Emit iteration end message with performance metrics. - """ - if info.node and info.node.performance: - self.cot_callable.emitter.emit_thought( - "System", - f"📋 Iteration {info.iteration + 1} completed: {info.node.performance.name}={info.node.performance.value}", - ) - else: - self.cot_callable.emitter.emit_thought( - "System", f"📋 Iteration {info.iteration + 1} failed: No performance metrics available" - ) - - def get_chain_of_thought_callable(self): - """ - Get the underlying chain of thought callable. - - Returns: - The chain of thought callable used by this model callback - """ - return self.cot_callable - - def get_full_chain_of_thought(self) -> List: - """ - Get the full chain of thought captured during model building. - - Returns: - The list of steps in the chain of thought - """ - return self.cot_callable.get_full_chain_of_thought() diff --git a/plexe/internal/models/callbacks/checkpoint.py b/plexe/internal/models/callbacks/checkpoint.py deleted file mode 100644 index 9130b7fe..00000000 --- a/plexe/internal/models/callbacks/checkpoint.py +++ /dev/null @@ -1,129 +0,0 @@ -""" -Checkpoint callback for model building process in Plexe. - -This module provides a checkpoint callback implementation that saves model state -at regular intervals during the build process. -""" - -import logging -from typing import Optional - -from plexe.callbacks import Callback, BuildStateInfo -import plexe.fileio as fileio # Import the module, not individual functions - -logger = logging.getLogger(__name__) - - -class ModelCheckpointCallback(Callback): - """ - Callback that saves model state checkpoints during the build process. - - This callback periodically saves the model state after each iteration to allow - resuming a build from a checkpoint if the process is interrupted. - """ - - def __init__( - self, - keep_n_latest: Optional[int] = None, - checkpoint_dir: Optional[str] = None, - delete_on_success: Optional[bool] = None, - ): - """ - Initialize the model checkpoint callback. - - Args: - keep_n_latest: Number of most recent checkpoints to keep for this model - checkpoint_dir: Optional custom directory for checkpoints - delete_on_success: Whether to delete checkpoints when build completes successfully - """ - from plexe.config import config - - # Use provided values or defaults from config - self.keep_n_latest = keep_n_latest if keep_n_latest is not None else config.file_storage.keep_checkpoints - self.checkpoint_dir = checkpoint_dir - self.delete_on_success = ( - delete_on_success if delete_on_success is not None else config.file_storage.delete_checkpoints_on_success - ) - self.model = None - self.checkpoints = [] - - def on_build_start(self, info: BuildStateInfo) -> None: - """ - Store reference to the model on build start. - - Args: - info: Information about the model building process start - """ - # We need access to the model object to create checkpoints - # This is not directly accessible via BuildStateInfo, so we'll - # need to get a reference to it when the callback is registered with the model - pass - - def on_iteration_end(self, info: BuildStateInfo) -> None: - """ - Create a checkpoint after each iteration. - - Args: - info: Information about the iteration end - """ - if not hasattr(info, "model"): - logger.warning("Cannot create checkpoint: no model reference available") - return - - model = info.model - try: - # Save checkpoint with current iteration number - checkpoint_path = fileio.save_checkpoint(model, info.iteration, self.checkpoint_dir) - self.checkpoints.append(checkpoint_path) - logger.info(f"Created checkpoint at {checkpoint_path}") - - # Manage checkpoint retention - self._manage_checkpoints(model.identifier) - except Exception as e: - logger.error(f"Error creating checkpoint: {e}") - - def on_build_end(self, info: BuildStateInfo) -> None: - """ - Optionally clean up checkpoints when build completes successfully. - - Args: - info: Information about the model building process end - """ - if not self.delete_on_success: - return - - if not hasattr(info, "model"): - return - - model = info.model - - if model.state.name == "READY": - # Build completed successfully, clean up checkpoints if configured - for checkpoint in self.checkpoints: - try: - fileio.delete_checkpoint(checkpoint) - logger.info(f"Deleted checkpoint {checkpoint} after successful build") - except Exception as e: - logger.error(f"Error deleting checkpoint {checkpoint}: {e}") - - def _manage_checkpoints(self, model_id: str) -> None: - """ - Manage checkpoint retention policy. - - Args: - model_id: Model identifier to filter checkpoints - """ - # Get all checkpoints for this model - all_checkpoints = fileio.list_checkpoints(model_id) - - # Sort by modification time (newest first) - all_checkpoints.sort(key=lambda p: str(p), reverse=True) - - # Delete older checkpoints beyond our retention limit - if len(all_checkpoints) > self.keep_n_latest: - for checkpoint in all_checkpoints[self.keep_n_latest :]: - try: - fileio.delete_checkpoint(checkpoint) - logger.info(f"Deleted old checkpoint {checkpoint} (retention policy)") - except Exception as e: - logger.error(f"Error deleting old checkpoint {checkpoint}: {e}") diff --git a/plexe/internal/models/callbacks/mlflow.py b/plexe/internal/models/callbacks/mlflow.py deleted file mode 100644 index 829ae9d5..00000000 --- a/plexe/internal/models/callbacks/mlflow.py +++ /dev/null @@ -1,419 +0,0 @@ -""" -MLFlow callback for tracking model building process. - -This module provides a callback implementation that logs model building -metrics, parameters, and artifacts to MLFlow. -""" - -import os -import re -import tempfile -import datetime -from pathlib import Path -from typing import Dict, Any, Optional, List - -import mlflow -import logging -import warnings - -from plexe.callbacks import Callback, BuildStateInfo -from plexe.internal.models.entities.metric import Metric - -logger = logging.getLogger(__name__) -warnings.filterwarnings("ignore", category=UserWarning, module="mlflow") - - -class MLFlowCallback(Callback): - """ - Callback that logs the model building process to MLFlow with hierarchical run organization. - - Implements nested runs with parent/child relationship: - - Parent run: Overall model building process, common parameters - - Child runs: Individual iterations with iteration-specific metrics - """ - - def __init__(self, tracking_uri: str, experiment_name: str, connect_timeout: int = 10): - """ - Initialize MLFlow callback. - - Args: - tracking_uri: MLFlow tracking server URI. - experiment_name: Name for the MLFlow experiment. - connect_timeout: Timeout in seconds for MLFlow server connection. - """ - self.tracking_uri = tracking_uri - self.experiment_name = experiment_name - self.experiment_id = None - self.connect_timeout = connect_timeout - self.parent_run_id = None - self._setup_mlflow() - - def _setup_mlflow(self) -> None: - """Configure MLFlow tracking and clean up any active runs.""" - try: - # End any active runs from previous sessions - if mlflow.active_run(): - mlflow.end_run() - - # Configure MLFlow environment - os.environ["MLFLOW_HTTP_REQUEST_TIMEOUT"] = str(self.connect_timeout) - mlflow.set_tracking_uri(self.tracking_uri) - - # Explicitly set the experiment first to avoid default experiment use for traces - experiment = mlflow.get_experiment_by_name(self.experiment_name) - if experiment: - self.experiment_id = experiment.experiment_id - mlflow.set_experiment(experiment_name=self.experiment_name) - else: - self.experiment_id = mlflow.create_experiment(self.experiment_name) - mlflow.set_experiment(experiment_id=self.experiment_id) - - # Enable autologging for smolagents AFTER setting experiment - # Note: mlflow.smolagents may not be available in all mlflow versions - try: - mlflow.smolagents.autolog() - except (ModuleNotFoundError, AttributeError): - # smolagents integration not available in this mlflow version - pass - - except Exception as e: - logger.error(f"Failed to setup MLFlow: {e}") - raise RuntimeError(f"Failed to setup MLFlow: {e}") from e - - @staticmethod - def _timestamp() -> str: - """Get formatted timestamp for runs and logs.""" - return datetime.datetime.now().strftime("%Y%m%d-%H%M%S") - - @staticmethod - def _safe_get(obj: Any, attrs: List[str], default: Any = None): - """Safely access nested attributes.""" - if obj is None: - return default - - current = obj - for attr in attrs: - if not hasattr(current, attr): - return default - current = getattr(current, attr) - return current - - def _get_or_create_experiment(self) -> str: - """ - Get or create the MLFlow experiment and return its ID. - Reuses experiment_id if already set during initialization. - """ - # If we already have an experiment ID, ensure it's active and return it - if self.experiment_id: - mlflow.set_experiment(experiment_id=self.experiment_id) - return self.experiment_id - - # Otherwise, look up by name or create - experiment = mlflow.get_experiment_by_name(self.experiment_name) - if experiment: - self.experiment_id = experiment.experiment_id - else: - # Create if not exists - self.experiment_id = mlflow.create_experiment(self.experiment_name) - - # Set the experiment as active and notify user - mlflow.set_experiment(experiment_id=self.experiment_id) - print(f"✅ MLFlow: tracking URI '{self.tracking_uri}', experiment '{self.experiment_name}'") - return self.experiment_id - - def _ensure_parent_run_active(self) -> bool: - """Ensure the parent run is active, activating it if needed.""" - if not self.parent_run_id or not self.experiment_id: - return False - - active_run = mlflow.active_run() - - # If already active and it's the parent run, we're good - if active_run and active_run.info.run_id == self.parent_run_id: - return True - - # End any active run and start the parent run - if active_run: - mlflow.end_run() - - # Ensure experiment is active before starting the run - mlflow.set_experiment(experiment_id=self.experiment_id) - - try: - mlflow.start_run(run_id=self.parent_run_id) - return True - except Exception as e: - logger.warning(f"Could not activate parent run: {e}") - return False - - @staticmethod - def _safe_log_artifact(content: str, filename: str) -> None: - """ - Safely log an artifact by writing to a temporary file first. - - Args: - content: Content to write to the file - filename: Name of the file in MLFlow - """ - if not mlflow.active_run() or not content: - return - - # Create unique temp file - with tempfile.NamedTemporaryFile(mode="w", delete=False, suffix=Path(filename).suffix) as tmp: - tmp_path = Path(tmp.name) - - try: - # Write content and log - with open(tmp_path, "w") as f: - f.write(content) - - mlflow.log_artifact(str(tmp_path)) - - except Exception as e: - logger.warning(f"Failed to log artifact '{filename}': {e}") - finally: - # Clean up temp file - if tmp_path.exists(): - tmp_path.unlink() - - def _extract_model_context(self, info: BuildStateInfo) -> Dict[str, Any]: - """Extract essential model context for logging.""" - context = {"intent": info.intent, "provider": str(info.provider)} - - # Add timing and iteration information - if info.timeout: - context["timeout_seconds"] = info.timeout - if info.run_timeout: - context["run_timeout_seconds"] = info.run_timeout - if info.max_iterations: - context["max_iterations"] = info.max_iterations - - # Add model ID if available - if info.model_identifier: - context["model_id"] = info.model_identifier - - # Add basic schema and dataset info - if info.input_schema: - context["input_schema_fields"] = len(info.input_schema.model_fields) - if info.output_schema: - context["output_schema_fields"] = len(info.output_schema.model_fields) - if info.datasets: - context["dataset_count"] = len(info.datasets) - - return context - - def _log_metric(self, metric: Metric, prefix: str = "", step: Optional[int] = None) -> None: - """Safely log a Plexe Metric object to MLFlow.""" - if not mlflow.active_run() or not metric: - return - - metric_name = self._safe_get(metric, ["name"]) - metric_value = self._safe_get(metric, ["value"]) - - if not metric_name or metric_value is None: - return - - # Clean metric name and convert value - clean_name = re.sub(r"[^a-zA-Z0-9_]", "", f"{prefix}{metric_name}") - - try: - # Try to log as numeric - value = float(metric_value) - if step is not None: - mlflow.log_metric(clean_name, value, step=step) - else: - mlflow.log_metric(clean_name, value) - except (ValueError, TypeError): - # If not numeric, log as tag - mlflow.set_tag(f"metric_{clean_name}", str(metric_value)) - mlflow.set_tag("non_numeric_metrics", "true") - - def on_build_start(self, info: BuildStateInfo) -> None: - """Start MLFlow parent run and log initial parameters.""" - try: - # Ensure experiment is set and active - self.experiment_id = self._get_or_create_experiment() - - # Get model info and timestamp - model_id = (info.model_identifier or "unknown")[0:12] + "..." - timestamp = self._timestamp() - - # End any active run before starting parent - if mlflow.active_run(): - mlflow.end_run() - - # Ensure the experiment is active before starting the run - mlflow.set_experiment(experiment_id=self.experiment_id) - - # Start parent run - parent_run = mlflow.start_run( - run_name=f"{model_id}-{timestamp}", - experiment_id=self.experiment_id, - description=f"Model building: {info.intent[:100]}...", - ) - self.parent_run_id = parent_run.info.run_id - logger.info(f"Started parent run '{parent_run.info.run_id}' in experiment '{self.experiment_name}'") - - # Log common parameters and tags - mlflow.log_params(self._extract_model_context(info)) - mlflow.set_tags({"provider": str(info.provider), "run_type": "parent", "build_timestamp": timestamp}) - - # Log intent - if info.intent: - self._safe_log_artifact(content=info.intent, filename="intent.txt") - - except Exception as e: - logger.error(f"Error starting build in MLFlow: {e}") - - def on_iteration_start(self, info: BuildStateInfo) -> None: - """Start a new nested child run for this iteration.""" - if not self.parent_run_id: - return - - try: - # Ensure experiment is active - mlflow.set_experiment(experiment_id=self.experiment_id) - - # Create nested run under the parent, letting MLflow decide the name - mlflow.start_run( - experiment_id=self.experiment_id, - nested=True, - description=f"Iteration {info.iteration}", - ) - - # Log iteration parameters - mlflow.log_params({"iteration": info.iteration}) - mlflow.set_tags( - {"run_type": "iteration", "iteration": str(info.iteration), "parent_run_id": self.parent_run_id} - ) - - # Log datasets if available - if info.datasets: - for name, data in info.datasets.items(): - try: - mlflow.log_input(mlflow.data.from_pandas(data.to_pandas(), name=name), context="training") - except Exception as e: - logger.warning(f"Could not log dataset '{name}': {e}") - - except Exception as e: - logger.error(f"Error starting iteration in MLFlow: {e}") - - def on_iteration_end(self, info: BuildStateInfo) -> None: - """Log metrics for this iteration and end the child run.""" - if not mlflow.active_run(): - return - - try: - # Process node data if available - node = info.node - if node: - # Log training code - training_code = self._safe_get(node, ["training_code"]) - if training_code: - self._safe_log_artifact( - content=training_code, filename=f"trainer_source_iteration_{info.iteration}.py" - ) - - # Log performance metrics - performance = self._safe_get(node, ["performance"]) - if performance: - self._log_metric(performance) - - # Log execution time - execution_time = self._safe_get(node, ["execution_time"]) - if execution_time: - mlflow.log_metric("execution_time", execution_time) - - # Log exception information - exception_raised = self._safe_get(node, ["exception_was_raised"], False) - if exception_raised: - exception_obj = self._safe_get(node, ["exception"]) - exception_type = type(exception_obj).__name__ if exception_obj else "unknown" - - mlflow.set_tags({"exception_raised": "true", "exception_type": exception_type}) - - # Log exception details - if exception_obj: - self._safe_log_artifact( - content=str(exception_obj), filename=f"exception-iteration-{info.iteration}.txt" - ) - - # Log model artifacts - artifacts = self._safe_get(node, ["model_artifacts"], []) - for artifact in artifacts: - if artifact.is_path() and Path(artifact.path).exists(): - try: - mlflow.log_artifact(str(artifact)) - except Exception: - pass - - # Determine run status - status = "FINISHED" - performance = self._safe_get(node, ["performance"]) - if ( - self._safe_get(node, ["exception_was_raised"], False) - or performance is None - or (hasattr(performance, "is_worst") and performance.is_worst) - ): - status = "FAILED" - - # End the child run - mlflow.end_run(status=status) - - except Exception as e: - logger.error(f"Error ending iteration in MLFlow: {e}") - try: - mlflow.end_run(status="FAILED") - except Exception: - pass - - def on_build_end(self, info: BuildStateInfo) -> None: - """Log final model details and end MLFlow parent run.""" - try: - # End any active child run first - active_run = mlflow.active_run() - if active_run and active_run.info.run_id != self.parent_run_id: - mlflow.end_run() - - # Ensure parent run is active - if not self._ensure_parent_run_active(): - return - - # Log EDA reports - node_metadata = self._safe_get(info.node, ["metadata"], {}) - if node_metadata and "eda_markdown_reports" in node_metadata: - for dataset_name, report_markdown in node_metadata["eda_markdown_reports"].items(): - self._safe_log_artifact(content=report_markdown, filename=f"eda_report_{dataset_name}.md") - - # Log model information - if info.final_metric and hasattr(info.final_metric, "name") and hasattr(info.final_metric, "value"): - mlflow.log_metric(f"best_{info.final_metric.name}", float(info.final_metric.value)) - - # Log model artifacts and status - mlflow.set_tag("best_iteration", str(info.iteration)) - - # Log artifact names - if info.final_artifacts: - artifact_names = [a.name for a in info.final_artifacts] - mlflow.set_tag("model_artifacts", ", ".join(artifact_names)) - - # Log model state - if info.model_state: - mlflow.set_tag("final_model_state", str(info.model_state)) - - # Log final model code - if info.trainer_source: - self._safe_log_artifact(content=info.trainer_source, filename="final_trainer.py") - - if info.predictor_source: - self._safe_log_artifact(content=info.predictor_source, filename="final_predictor.py") - - # End the parent run - mlflow.end_run() - - except Exception as e: - logger.error(f"Error finalizing build in MLFlow: {e}") - try: - mlflow.end_run() - except Exception: - pass diff --git a/plexe/internal/models/entities/__init__.py b/plexe/internal/models/entities/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/plexe/internal/models/entities/artifact.py b/plexe/internal/models/entities/artifact.py deleted file mode 100644 index d6ff1f08..00000000 --- a/plexe/internal/models/entities/artifact.py +++ /dev/null @@ -1,77 +0,0 @@ -""" -This module defines the "Artifact" dataclass, a simple representation of an external artifact. - -An "external artifact" is a text or binary entity that is used by a model. The canonical example is -a blob containing the weights of a neural network. The Artifact class can be used either to point to -a file on disk by its path, or to hold the raw text or binary data in memory itself. -""" - -import io -from typing import BinaryIO, Union -from pathlib import Path - - -class Artifact: - """ - Represents a model artifact, which can either be a file path or raw text/binary data. - - When the artifact holds a path pointing to a file, the 'is_path' property is true and the path can - be accessed via the 'path' attribute. When the artifact holds raw data, the 'is_data' property is true - and the data can be accessed via the 'data' attribute. In either case, the 'type' property indicates - whether the data (in memory or in the file) is text or binary. - """ - - def __init__(self, name: str, path: Path = None, handle: BinaryIO = None, data: bytes = None): - self.name: str = name - self.path: Path = path - self.handle: BinaryIO = handle - self.data: bytes = data - - if sum([path is not None, handle is not None, data is not None]) != 1: - raise ValueError("Exactly one of 'handle', 'path', or 'data' must be provided.") - - def is_path(self) -> bool: - """ - True if the artifact is a file path. - """ - return self.path is not None - - def is_handle(self) -> bool: - """ - True if the artifact is file path or file-like object. - """ - return self.handle is not None - - def is_data(self) -> bool: - """ - True if the artifact is a string or bytes object loaded in memory. - """ - return self.data is not None - - def get_as_handle(self) -> BinaryIO: - """ - Get the artifact as a file-like object. - """ - if self.is_handle(): - return self.handle - elif self.is_path(): - return open(self.path, "rb") - elif self.is_data(): - return io.BytesIO(self.data) - else: - raise ValueError("Artifact does not have a valid handle, path, or data.") - - @staticmethod - def from_path(path: Union[str, Path]): - """ - Create an Artifact instance from a file path. - """ - path = Path(path) - return Artifact(name=path.name, path=path) - - @staticmethod - def from_data(name: str, data: bytes): - """ - Create an Artifact instance from an in-memory sequence of bytes. - """ - return Artifact(name=name, data=data) diff --git a/plexe/internal/models/entities/code.py b/plexe/internal/models/entities/code.py deleted file mode 100644 index f9d6b602..00000000 --- a/plexe/internal/models/entities/code.py +++ /dev/null @@ -1,13 +0,0 @@ -""" -This module defines a Code dataclass for representing code objects passed around by agents. -""" - -from dataclasses import dataclass, field - - -@dataclass -class Code: - """Represents a code object.""" - - code: str = field() - performance: float = field(default=None) diff --git a/plexe/internal/models/entities/description.py b/plexe/internal/models/entities/description.py deleted file mode 100644 index d0885c9d..00000000 --- a/plexe/internal/models/entities/description.py +++ /dev/null @@ -1,188 +0,0 @@ -""" -This module defines dataclasses for structured model descriptions. - -These classes provide a comprehensive representation of a model's -characteristics, including schemas, implementation details, performance -metrics, and source code, organized in a structured format suitable -for various output formats and visualization purposes. -""" - -from dataclasses import dataclass, field -from typing import Any, Dict, List, Optional - -from dataclasses_json import DataClassJsonMixin - - -@dataclass -class SchemaInfo(DataClassJsonMixin): - """Information about the model's input and output schemas.""" - - input: Dict[str, Any] - output: Dict[str, Any] - - -@dataclass -class ImplementationInfo(DataClassJsonMixin): - """Technical information about the model implementation.""" - - framework: Optional[str] = None - model_type: Optional[str] = None - artifacts: List[str] = field(default_factory=list) - size: Optional[int] = None - - -@dataclass -class PerformanceInfo(DataClassJsonMixin): - """Performance metrics and training data information.""" - - metrics: Dict[str, Any] = field(default_factory=dict) - training_data_info: Dict[str, Dict[str, Any]] = field(default_factory=dict) - - -@dataclass -class CodeInfo(DataClassJsonMixin): - """Information about the model's source code.""" - - training: Optional[str] = None - prediction: Optional[str] = None - feature_transformations: Optional[str] = None - - -@dataclass -class ModelDescription(DataClassJsonMixin): - """A comprehensive description of a model.""" - - id: str - state: str - intent: str - schemas: SchemaInfo - implementation: ImplementationInfo - performance: PerformanceInfo - code: CodeInfo - training_date: Optional[str] = None - rationale: Optional[str] = None - provider: Optional[str] = None - task_type: Optional[str] = None - domain: Optional[str] = None - behavior: Optional[str] = None - preprocessing_summary: Optional[str] = None - architecture_summary: Optional[str] = None - training_procedure: Optional[str] = None - evaluation_metric: Optional[str] = None - inference_behavior: Optional[str] = None - strengths: Optional[str] = None - limitations: Optional[str] = None - - def as_text(self) -> str: - """Convert the model description to a formatted text string.""" - # Simple text representation - lines = [ - f"Model: {self.id}", - f"State: {self.state}", - f"Intent: {self.intent}", - f"Training Date: {self.training_date or 'Not available'}", - f"Built with: {self.provider or 'Unknown provider'}", - "", - "Input Schema:", - "\n".join(f" - {k}: {v}" for k, v in self.schemas.input.items()), - "", - "Output Schema:", - "\n".join(f" - {k}: {v}" for k, v in self.schemas.output.items()), - "", - "Implementation:", - f" - Framework: {self.implementation.framework or 'Not specified'}", - f" - Model Type: {self.implementation.model_type or 'Not specified'}", - f" - Size: {self.implementation.size or 'Unknown'} bytes", - "", - "Task Information:", - f" - Task Type: {self.task_type or 'Not specified'}", - f" - Domain: {self.domain or 'Not specified'}", - f" - Behavior: {self.behavior or 'Not specified'}", - "", - "Technical Details:", - f" - Preprocessing: {self.preprocessing_summary or 'Not available'}", - f" - Architecture: {self.architecture_summary or 'Not available'}", - f" - Training Procedure: {self.training_procedure or 'Not available'}", - f" - Evaluation Metric: {self.evaluation_metric or 'Not available'}", - f" - Inference Behavior: {self.inference_behavior or 'Not available'}", - "", - "Analysis:", - f" - Strengths: {self.strengths or 'Not available'}", - f" - Limitations: {self.limitations or 'Not available'}", - "", - "Performance Metrics:", - "\n".join(f" - {k}: {v}" for k, v in self.performance.metrics.items()), - "", - "Model Code:", - " - Training Code:", - f" ```python\n{self.code.training or '# No training code available'}\n```", - " - Prediction Code:", - f" ```python\n{self.code.prediction or '# No prediction code available'}\n```", - " - Feature Transformation Code:", - f" ```python\n{self.code.feature_transformations or '# No feature transformation code available'}\n```", - "", - "Rationale:", - self.rationale or "Not available", - ] - return "\n".join(lines) - - def as_markdown(self) -> str: - """Convert the model description to a markdown string.""" - # Markdown representation with formatting - lines = [ - f"# Model: {self.id}", - "", - f"**State:** {self.state}", - f"**Intent:** {self.intent}", - f"**Training Date:** {self.training_date or 'Not available'}", - f"**Built with:** {self.provider or 'Unknown provider'}", - "", - "## Input Schema", - "\n".join(f"- `{k}`: {v}" for k, v in self.schemas.input.items()), - "", - "## Output Schema", - "\n".join(f"- `{k}`: {v}" for k, v in self.schemas.output.items()), - "", - "## Implementation", - f"- **Framework:** {self.implementation.framework or 'Not specified'}", - f"- **Model Type:** {self.implementation.model_type or 'Not specified'}", - f"- **Size:** {self.implementation.size or 'Unknown'} bytes", - f"- **Artifacts:** {', '.join(self.implementation.artifacts) or 'None'}", - "", - "## Task Information", - f"- **Task Type:** {self.task_type or 'Not specified'}", - f"- **Domain:** {self.domain or 'Not specified'}", - f"- **Behavior:** {self.behavior or 'Not specified'}", - "", - "## Technical Details", - f"- **Preprocessing:** {self.preprocessing_summary or 'Not available'}", - f"- **Architecture:** {self.architecture_summary or 'Not available'}", - f"- **Training Procedure:** {self.training_procedure or 'Not available'}", - f"- **Evaluation Metric:** {self.evaluation_metric or 'Not available'}", - f"- **Inference Behavior:** {self.inference_behavior or 'Not available'}", - "", - "## Analysis", - f"- **Strengths:** {self.strengths or 'Not available'}", - f"- **Limitations:** {self.limitations or 'Not available'}", - "", - "## Performance Metrics", - "\n".join(f"- **{k}:** {v}" for k, v in self.performance.metrics.items()), - "", - "## Model Code", - "### Training Code", - "```python", - self.code.training or "# No training code available", - "```", - "### Prediction Code", - "```python", - self.code.prediction or "# No prediction code available", - "```", - "### Feature Transformation Code", - "```python", - self.code.feature_transformations or "# No feature transformation code available", - "```", - "", - "## Rationale", - self.rationale or "_Not available_", - ] - return "\n".join(lines) diff --git a/plexe/internal/models/entities/metric.py b/plexe/internal/models/entities/metric.py deleted file mode 100644 index f5355984..00000000 --- a/plexe/internal/models/entities/metric.py +++ /dev/null @@ -1,214 +0,0 @@ -""" -Module: plexe/internal/common/dataclasses/metric - -This module defines classes for handling and comparing metrics in a flexible and extensible way. - -Classes: - - ComparisonMethod: Enum defining methods for comparing metrics. - - MetricComparator: Encapsulates comparison logic for metrics, including methods like higher-is-better, - lower-is-better, and target-is-better. - - Metric: Represents a specific metric with a name, value, and comparator, allowing metrics to be compared - and evaluated. - -Example Usage: - from metric_class import Metric, MetricComparator, ComparisonMethod - - comparator = MetricComparator(ComparisonMethod.HIGHER_IS_BETTER) - metric1 = Metric(name="accuracy", value=0.8, comparator=comparator) - metric2 = Metric(name="accuracy", value=0.9, comparator=comparator) - - print(metric1 < metric2) # True -""" - -from enum import Enum -from functools import total_ordering - - -class ComparisonMethod(Enum): - """ - Defines methods for comparing metrics. - - Attributes: - HIGHER_IS_BETTER: Indicates that higher values are better. - LOWER_IS_BETTER: Indicates that lower values are better. - TARGET_IS_BETTER: Indicates that values closer to a target are better. - """ - - HIGHER_IS_BETTER = "higher_is_better" - LOWER_IS_BETTER = "lower_is_better" - TARGET_IS_BETTER = "target_is_better" - - -class MetricComparator: - """ - Encapsulates comparison logic for metrics. - - Attributes: - comparison_method (ComparisonMethod): The method used to compare metrics. - target (float, optional): The target value for TARGET_IS_BETTER comparisons. - """ - - def __init__(self, comparison_method: ComparisonMethod, target: float = None, epsilon: float = 1e-9): - """ - Initializes the MetricComparator. - - :param comparison_method: The method to compare metric values. - :param target: The target value for TARGET_IS_BETTER comparisons (optional). - :param epsilon: The tolerance for floating-point error in TARGET_IS_BETTER comparisons (default: 1e-9). - :raises ValueError: If TARGET_IS_BETTER is used without a target value. - """ - self.comparison_method = comparison_method - self.target = target if comparison_method == ComparisonMethod.TARGET_IS_BETTER else None - self.epsilon = epsilon - - if self.comparison_method == ComparisonMethod.TARGET_IS_BETTER and self.target is None: - raise ValueError("'TARGET_IS_BETTER' comparison requires a target value.") - if self.comparison_method == ComparisonMethod.TARGET_IS_BETTER and not isinstance(self.target, (float, int)): - raise ValueError("'TARGET_IS_BETTER' requires a numeric target value.") - - def compare(self, value1: float, value2: float) -> int: - """ - Compare two metric values based on the defined comparison method. - - :param value1: The first metric value. - :param value2: The second metric value. - :return: -1 if value1 is better, 1 if value2 is better, 0 if they are equal. - :raises ValueError: If an invalid comparison method is used. - """ - if value1 is None and value2 is None: - return 0 - elif value1 is None: - return 1 - elif value2 is None: - return -1 - elif self.comparison_method == ComparisonMethod.HIGHER_IS_BETTER: - return (value2 > value1 + self.epsilon) - (value1 > value2 + self.epsilon) - elif self.comparison_method == ComparisonMethod.LOWER_IS_BETTER: - return (value1 > value2 + self.epsilon) - (value2 > value1 + self.epsilon) - elif self.comparison_method == ComparisonMethod.TARGET_IS_BETTER: - dist1 = abs(value1 - self.target) - dist2 = abs(value2 - self.target) - if dist1 > dist2 + self.epsilon: - return 1 - elif dist2 > dist1 + self.epsilon: - return -1 - else: - return 0 - else: - raise ValueError("Invalid comparison method.") - - -# todo: this class is a mess as it mixes concerns of a metric and a metric value; needs refactoring -@total_ordering -class Metric: - """ - Represents a metric with a name, a value, and a comparator for determining which metric is better. - - Attributes: - name (str): The name of the metric (e.g., 'accuracy', 'loss'). - value (float): The numeric value of the metric. - comparator (MetricComparator): The comparison logic for the metric. - """ - - def __init__(self, name: str, value: float = None, comparator: MetricComparator = None, is_worst: bool = False): - """ - Initializes a Metric object. - - :param name: The name of the metric. - :param value: The numeric value of the metric. - :param comparator: An instance of MetricComparator for comparison logic. - :param is_worst: Indicates if the metric value is the worst possible value. - """ - self.name = name - self.value = value - self.comparator = comparator - self.is_worst = is_worst or value is None - - def __gt__(self, other) -> bool: - """ - Determine if this metric is better than another metric. - - :param other: Another Metric object to compare against. - :return: True if this metric is better, False otherwise. - :raises ValueError: If the metrics have different names or comparison methods. - """ - if not isinstance(other, Metric): - return NotImplemented - - if self.is_worst or (self.is_worst and other.is_worst): - return False - - if other.is_worst: - return True - - if self.name != other.name: - raise ValueError("Cannot compare metrics with different names.") - - if self.comparator.comparison_method != other.comparator.comparison_method: - raise ValueError("Cannot compare metrics with different comparison methods.") - - if ( - self.comparator.comparison_method == ComparisonMethod.TARGET_IS_BETTER - and self.comparator.target != other.comparator.target - ): - raise ValueError("Cannot compare 'TARGET_IS_BETTER' metrics with different target values.") - - return self.comparator.compare(self.value, other.value) < 0 - - def __eq__(self, other) -> bool: - """ - Check if this metric is equal to another metric. - - :param other: Another Metric object to compare against. - :return: True if the metrics are equal, False otherwise. - """ - if not isinstance(other, Metric): - return NotImplemented - - if self.is_worst and other.is_worst: - return True - - if self.is_worst or other.is_worst: - return False - - return ( - self.name == other.name - and self.comparator.comparison_method == other.comparator.comparison_method - and self.comparator.compare(self.value, other.value) == 0 - ) - - def __repr__(self) -> str: - """ - Return a string representation of the Metric object. - - :return: A string representation of the Metric. - """ - target_str = ( - f", target={self.comparator.target}" - if self.comparator.comparison_method == ComparisonMethod.TARGET_IS_BETTER - else "" - ) - return f"Metric(name={self.name!r}, value={self.value}, comparison={self.comparator.comparison_method.name}{target_str})" - - def __str__(self) -> str: - """ - Return a user-friendly string representation of the Metric. - - :return: A string describing the Metric. - """ - comparison_symbols = { - ComparisonMethod.HIGHER_IS_BETTER: "↑", - ComparisonMethod.LOWER_IS_BETTER: "↓", - ComparisonMethod.TARGET_IS_BETTER: "≈", - } - symbol = comparison_symbols.get(self.comparator.comparison_method, "?") - return f"Metric {self.name} {symbol} {self.value}" - - @property - def is_valid(self) -> bool: - """ - Check if the metric value is valid (i.e., not None or NaN). - - :return: True if the metric value is valid, False otherwise. - """ - return self.value is not None and not (self.value != self.value) # NaN check diff --git a/plexe/internal/models/execution/__init__.py b/plexe/internal/models/execution/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/plexe/internal/models/execution/docker_executor.py b/plexe/internal/models/execution/docker_executor.py deleted file mode 100644 index bbd408b3..00000000 --- a/plexe/internal/models/execution/docker_executor.py +++ /dev/null @@ -1,22 +0,0 @@ -from typing import Any - -from plexe.internal.models.execution.executor import Executor, ExecutionResult - - -class DockerExecutor(Executor): - """ - Execute Python code snippets in an isolated Docker container. - - The `DockerExecutor` class implements the `Executor` interface, allowing Python code - snippets to be executed in an isolated Docker container with strict isolation, output capture, - and timeout enforcement. - """ - - def __init__(self, code: str, timeout: int = 3600, **kwargs: Any) -> None: - raise NotImplementedError("DockerExecutor is not yet implemented") - - def run(self) -> ExecutionResult: - raise NotImplementedError("DockerExecutor is not yet implemented") - - def cleanup(self) -> None: - raise NotImplementedError("DockerExecutor is not yet implemented") diff --git a/plexe/internal/models/execution/executor.py b/plexe/internal/models/execution/executor.py deleted file mode 100644 index f3811271..00000000 --- a/plexe/internal/models/execution/executor.py +++ /dev/null @@ -1,63 +0,0 @@ -from abc import ABC, abstractmethod -from dataclasses import dataclass, field -from typing import Any, Optional, List -from pathlib import Path - - -@dataclass -class ExecutionResult: - """ - Result of executing code in an environment. - - Attributes: - term_out (list[str]): The terminal output from the execution. - exec_time (float): The time taken to execute the code. - """ - - term_out: list[str] - exec_time: float - model_artifact_paths: List[Path | str] = field(default_factory=list) - exception: Exception = field(default=None) - performance: Optional[float] = field(default=None) - - def is_valid_performance(self) -> bool: - """Validate if performance metric is usable.""" - return ( - self.performance is not None - and isinstance(self.performance, (int, float)) - and self.performance not in [float("inf"), float("-inf")] - ) - - -class Executor(ABC): - """ - Abstract base class for code execution environments. - """ - - @abstractmethod - def __init__(self, code: str, timeout: int = 3600, **kwargs: Any) -> None: - """ - Initialise the executor. - - :param: [str] code: The code to execute. - :param: [int] timeout: Maximum execution time in seconds. Defaults to 3600. - :param: [Any] kwargs: Additional parameters specific to the implementation. - """ - self.code = code - self.timeout = timeout - - @abstractmethod - def run(self) -> ExecutionResult: - """ - Execute the code in the defined environment. - - :return: [ExecutionResult] The results of execution, including output and errors. - """ - pass - - @abstractmethod - def cleanup(self) -> None: - """ - Perform any necessary cleanup (e.g., terminate processes, remove temporary files). - """ - pass diff --git a/plexe/internal/models/execution/process_executor.py b/plexe/internal/models/execution/process_executor.py deleted file mode 100644 index 3f841e6e..00000000 --- a/plexe/internal/models/execution/process_executor.py +++ /dev/null @@ -1,202 +0,0 @@ -""" -Module: ProcessExecutor for Isolated Python Code Execution - -This module provides an implementation of the `Executor` interface for executing Python code snippets -in an isolated process. It captures stdout, stderr, exceptions, and stack traces, and enforces -timeout limits on execution. - -Classes: - - RedirectQueue: A helper class to redirect stdout and stderr to a multiprocessing Queue. - - ProcessExecutor: A class to execute Python code snippets in an isolated process. - -Usage: - Create an instance of `ProcessExecutor`, providing the Python code, working directory, and timeout. - Call the `run` method to execute the code and return the results in an `ExecutionResult` object. - -Exceptions: - - Raises `RuntimeError` if the child process fails unexpectedly. - -""" - -import logging -import subprocess -import sys -import time -import pyarrow.parquet as pq -import pyarrow as pa -from pathlib import Path -from typing import Dict - -from plexe.internal.common.datasets.interface import TabularConvertible -from plexe.internal.common.utils.response import extract_performance -from plexe.internal.models.execution.executor import ExecutionResult, Executor -from plexe.config import config - -logger = logging.getLogger(__name__) - - -class ProcessExecutor(Executor): - """ - Execute Python code snippets in an isolated process. - - The `ProcessExecutor` class implements the `Executor` interface, allowing Python code - snippets to be executed with strict isolation, output capture, and timeout enforcement. - """ - - def __init__( - self, - execution_id: str, - code: str, - working_dir: Path | str, - datasets: Dict[str, TabularConvertible], - timeout: int, - code_execution_file_name: str = config.execution.runfile_name, - ): - """ - Initialize the ProcessExecutor. - - Args: - execution_id (str): Unique identifier for this execution. - code (str): The Python code to execute. - working_dir (Path | str): The working directory for execution. - datasets (Dict[str, TabularConvertible]): Datasets to be used for execution. - timeout (int): The maximum allowed execution time in seconds. - code_execution_file_name (str): The filename to use for the executed script. - """ - super().__init__(code, timeout) - # Create a unique working directory for this execution - self.working_dir = Path(working_dir).resolve() / execution_id - self.working_dir.mkdir(parents=True, exist_ok=True) - # Set the file names for the code and training data - self.code_file_name = code_execution_file_name - self.datasets = datasets - # Keep track of resources for cleanup - self.dataset_files = [] - self.code_file = None - self.process = None - - def run(self) -> ExecutionResult: - """Execute code in a subprocess and return results.""" - logger.debug(f"ProcessExecutor is executing code with working directory: {self.working_dir}") - start_time = time.time() - - try: - # Write code to file with module environment setup - self.code_file = self.working_dir / self.code_file_name - module_setup = "import os\n" "import sys\n" "from pathlib import Path\n\n" - with open(self.code_file, "w", encoding="utf-8") as f: - f.write(module_setup + self.code) - - # Write datasets to files - self.dataset_files = [] - for dataset_name, dataset in self.datasets.items(): - dataset_file: Path = self.working_dir / f"{dataset_name}.parquet" - pq.write_table(pa.Table.from_pandas(df=dataset.to_pandas()), dataset_file) - self.dataset_files.append(dataset_file) - - # Execute the code in a subprocess - self.process = subprocess.Popen( - [sys.executable, str(self.code_file)], - stdout=subprocess.PIPE, - stderr=subprocess.PIPE, - cwd=str(self.working_dir), - text=True, - ) - - stdout, stderr = self.process.communicate(timeout=self.timeout) - exec_time = time.time() - start_time - - # Collect all model artifacts created by the execution - not code or datasets - model_artifacts = [] - model_dir = self.working_dir / "model_files" - if model_dir.exists() and model_dir.is_dir(): - model_artifacts.append(str(model_dir)) - else: - # If model_files directory doesn't exist, collect individual files - for file in self.working_dir.iterdir(): - if file != self.code_file and file not in self.dataset_files: - model_artifacts.append(str(file)) - - if self.process.returncode != 0: - return ExecutionResult( - term_out=[stdout], - exec_time=exec_time, - exception=RuntimeError(f"Process exited with code {self.process.returncode}: {stderr}"), - model_artifact_paths=model_artifacts, - ) - - # Extract performance and create result - return ExecutionResult( - term_out=[stdout], - exec_time=exec_time, - model_artifact_paths=model_artifacts, - performance=extract_performance(stdout), - ) - - except subprocess.TimeoutExpired: - if self.process: - self.process.kill() - - return ExecutionResult( - term_out=[], - exec_time=self.timeout, - exception=TimeoutError( - f"Execution exceeded {self.timeout}s timeout - individual run timeout limit reached" - ), - ) - except Exception as e: - stdout, stderr = "", "" - - if self.process: - # Try to collect any output that was produced before the exception - try: - if hasattr(self.process, "stdout") and self.process.stdout: - stdout = self.process.stdout.read() or "" - except Exception: - pass # Best effort to get output - - self.process.kill() - - return ExecutionResult( - term_out=[stdout or f"Process failed with exception: {str(e)}"], - exec_time=time.time() - start_time, - exception=e, - ) - finally: - # Always clean up resources regardless of execution path - self.cleanup() - - def cleanup(self): - """ - Clean up resources after execution while preserving model artifacts. - """ - logger.debug(f"Cleaning up resources for execution in {self.working_dir}") - - try: - # Clean up dataset files - for dataset_file in self.dataset_files: - dataset_file.unlink(missing_ok=True) - - # Clean up code file - if self.code_file: - try: - self.code_file.unlink(missing_ok=True) - except AttributeError: - # Python 3.7 compatibility - missing_ok not available - if self.code_file.exists(): - self.code_file.unlink() - - # Terminate process if still running - if self.process and self.process.poll() is None: - self.process.kill() - - except Exception as e: - logger.warning(f"Error during resource cleanup: {str(e)}") - - def __del__(self): - """Ensure cleanup happens when the object is garbage collected.""" - try: - self.cleanup() - except Exception: - # Silent failure during garbage collection - detailed logging already done in cleanup() - pass diff --git a/plexe/internal/models/execution/ray_executor.py b/plexe/internal/models/execution/ray_executor.py deleted file mode 100644 index e682c483..00000000 --- a/plexe/internal/models/execution/ray_executor.py +++ /dev/null @@ -1,182 +0,0 @@ -"""Module: RayExecutor for Distributed Python Code Execution - -This module provides an implementation of the `Executor` interface for executing Python code snippets -in a distributed Ray cluster. It leverages Ray to run code remotely, with support for parallel execution. - -Classes: - - RayExecutor: A class to execute Python code snippets in a Ray cluster. - -Usage: - Create an instance of `RayExecutor`, providing the Python code, working directory, and timeout. - Call the `run` method to execute the code on the Ray cluster and return the results in an - `ExecutionResult` object. -""" - -import logging -import time -import ray -import pyarrow.parquet as pq -import pyarrow as pa -from pathlib import Path -from typing import Dict, List - -from plexe.internal.common.datasets.interface import TabularConvertible -from plexe.internal.common.utils.response import extract_performance -from plexe.internal.models.execution.executor import ExecutionResult, Executor -from plexe.config import config - -logger = logging.getLogger(__name__) - - -@ray.remote -def _run_code(code: str, working_dir: str, dataset_files: List[str], timeout: int) -> dict: - """Ray remote function that executes the code.""" - import subprocess - import sys - from pathlib import Path - - working_dir = Path(working_dir) - code_file = working_dir / "run.py" - - # Write code to file - with open(code_file, "w", encoding="utf-8") as f: - f.write("import os\nimport sys\nfrom pathlib import Path\n\n" + code) - - start_time = time.time() - process = subprocess.Popen( - [sys.executable, str(code_file)], - stdout=subprocess.PIPE, - stderr=subprocess.PIPE, - cwd=str(working_dir), - text=True, - ) - - try: - stdout, stderr = process.communicate(timeout=timeout) - exec_time = time.time() - start_time - - # Collect model artifacts - model_artifacts = [] - model_dir = working_dir / "model_files" - if model_dir.exists() and model_dir.is_dir(): - model_artifacts.append(str(model_dir)) - else: - for file in working_dir.iterdir(): - if file != code_file and str(file) not in dataset_files: - model_artifacts.append(str(file)) - - return { - "stdout": stdout, - "stderr": stderr, - "returncode": process.returncode, - "exec_time": exec_time, - "model_artifacts": model_artifacts, - } - except subprocess.TimeoutExpired: - process.kill() - return { - "stdout": "", - "stderr": f"Execution exceeded {timeout}s timeout", - "returncode": -1, - "exec_time": timeout, - "model_artifacts": [], - } - - -class RayExecutor(Executor): - """Execute Python code snippets on a Ray cluster.""" - - _ray_was_used = False - - def __init__( - self, - execution_id: str, - code: str, - working_dir: Path | str, - datasets: Dict[str, TabularConvertible], - timeout: int, - code_execution_file_name: str = config.execution.runfile_name, - ): - """Initialize the RayExecutor. - - Args: - execution_id (str): Unique ID for this execution. - code (str): The Python code to execute. - working_dir (Path | str): The working directory for execution. - datasets (Dict[str, TabularConvertible]): The datasets to be used. - timeout (int): The maximum allowed execution time in seconds. - code_execution_file_name (str): The filename to use for the executed script. - """ - RayExecutor._ray_was_used = True - super().__init__(code, timeout) - self.working_dir = Path(working_dir).resolve() / execution_id - self.working_dir.mkdir(parents=True, exist_ok=True) - self.code_file_name = code_execution_file_name - self.dataset = datasets - - # Initialize Ray if not already done - if not ray.is_initialized(): - from plexe.config import config - - ray.init( - address=getattr(config.ray, "address", None) if hasattr(config, "ray") else None, - num_cpus=getattr(config.ray, "num_cpus", None) if hasattr(config, "ray") else None, - num_gpus=getattr(config.ray, "num_gpus", None) if hasattr(config, "ray") else None, - ignore_reinit_error=True, - ) - - def run(self) -> ExecutionResult: - """Execute code using Ray and return results.""" - logger.debug(f"RayExecutor is executing code with working directory: {self.working_dir}") - - # Write datasets to files - dataset_files = [] - for dataset_name, dataset in self.dataset.items(): - dataset_file = self.working_dir / f"{dataset_name}.parquet" - pq.write_table(pa.Table.from_pandas(df=dataset.to_pandas()), dataset_file) - dataset_files.append(str(dataset_file)) - - try: - # Execute the code using Ray - result_ref = _run_code.remote(self.code, str(self.working_dir), dataset_files, self.timeout) - # Wait for result with timeout - ready_refs, remaining_refs = ray.wait([result_ref], timeout=self.timeout) - - # If no ready refs, we hit a timeout - if not ready_refs: - ray.cancel(result_ref, force=True) - return ExecutionResult( - term_out=[], - exec_time=self.timeout, - exception=TimeoutError(f"Execution exceeded {self.timeout}s timeout - Ray timeout reached"), - ) - - # Get the result from the completed task - result = ray.get(ready_refs[0]) - - if result["returncode"] != 0: - return ExecutionResult( - term_out=[result["stdout"]], - exec_time=result["exec_time"], - exception=RuntimeError(result["stderr"]), - model_artifact_paths=result["model_artifacts"], - ) - - return ExecutionResult( - term_out=[result["stdout"]], - exec_time=result["exec_time"], - model_artifact_paths=result["model_artifacts"], - performance=extract_performance(result["stdout"]), - ) - - except ray.exceptions.GetTimeoutError: - ray.cancel(result_ref, force=True) - return ExecutionResult( - term_out=[], - exec_time=self.timeout, - exception=TimeoutError(f"Execution exceeded {self.timeout}s timeout - Ray timeout reached"), - ) - - def cleanup(self) -> None: - """Clean up Ray resources if needed.""" - pass diff --git a/plexe/internal/models/feature_handling.py b/plexe/internal/models/feature_handling.py deleted file mode 100644 index be00d9d5..00000000 --- a/plexe/internal/models/feature_handling.py +++ /dev/null @@ -1,58 +0,0 @@ -""" -Helper functions for handling features in model prediction. -""" - -from typing import Dict, List, Any -import logging - -import pandas as pd - -logger = logging.getLogger(__name__) - - -def get_required_features(training_data: pd.DataFrame) -> List[str]: - """Get list of all features required for prediction based on training data.""" - categorical_cols = training_data.select_dtypes(include=["object", "category"]).columns - numerical_cols = training_data.select_dtypes(include=["int64", "float64"]).columns - - # Get all one-hot encoded column names for categorical features - onehot_cols = [] - for col in categorical_cols: - unique_values = training_data[col].unique() - onehot_cols.extend([f"{col}_{val}" for val in unique_values]) - - return list(numerical_cols) + onehot_cols - - -def ensure_features_present(input_data: Dict[str, Any], required_features: List[str]) -> Dict[str, Any]: - """ - Ensure all required features are present in input data. - Args: - input_data: Input dictionary for prediction - required_features: List of features that should be present - Returns: - Dict with all required features (missing ones set to 0) - """ - processed = input_data.copy() - - # Add missing features with default value 0 - for feature in required_features: - if feature not in processed: - processed[feature] = 0 - logger.debug(f"Added missing feature '{feature}' with default value 0") - - return processed - - -def validate_required_features(input_data: Dict[str, Any], required_features: List[str]) -> None: - """ - Validate that input data has all strictly required features (non-one-hot). - Raises ValueError if any required feature is missing. - """ - # Identify base features (before one-hot encoding) - base_features = {f.split("_")[0] for f in required_features} - - # Check for missing base features - missing = [f for f in base_features if not any(k.startswith(f) for k in input_data.keys())] - if missing: - raise ValueError(f"Missing required base features: {missing}") diff --git a/plexe/internal/models/generation/__init__.py b/plexe/internal/models/generation/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/plexe/internal/models/generation/planning.py b/plexe/internal/models/generation/planning.py deleted file mode 100644 index c68d49b1..00000000 --- a/plexe/internal/models/generation/planning.py +++ /dev/null @@ -1,62 +0,0 @@ -# plexe/internal/models/generation/planning.py - -""" -This module provides functions and classes for generating and planning solutions for machine learning problems. -""" - -import json -import logging - -from pydantic import BaseModel - -from plexe.config import prompt_templates -from plexe.internal.common.provider import Provider -from plexe.internal.models.entities.metric import Metric, MetricComparator, ComparisonMethod - -logger = logging.getLogger(__name__) - - -class SolutionPlanGenerator: - """ - A class to generate solution plans for given problem statements. - """ - - def __init__(self, provider: Provider): - """ - Initializes the SolutionPlanGenerator with an empty context. - """ - self.provider: Provider = provider - - def select_target_metric(self, problem_statement: str) -> Metric: - """ - Selects the metric to optimise for the given problem statement and dataset. - - :param problem_statement: definition of the problem - :return: the metric to optimise - """ - - class MetricResponse(BaseModel): - name: str - comparison_method: ComparisonMethod - comparison_target: float = None - - response: MetricResponse = MetricResponse( - **json.loads( - self.provider.query( - system_message=prompt_templates.planning_system(), - user_message=prompt_templates.planning_select_metric( - problem_statement=problem_statement, - ), - response_format=MetricResponse, - ) - ) - ) - - try: - return Metric( - name=response.name, - value=float("inf") if response.comparison_method == ComparisonMethod.LOWER_IS_BETTER else -float("inf"), - comparator=MetricComparator(response.comparison_method, response.comparison_target), - ) - except Exception as e: - raise ValueError(f"Could not determine optimization metric from problem statement: {response}") from e diff --git a/plexe/internal/models/generation/review.py b/plexe/internal/models/generation/review.py deleted file mode 100644 index 89b51a42..00000000 --- a/plexe/internal/models/generation/review.py +++ /dev/null @@ -1,134 +0,0 @@ -""" -This module provides functionality for reviewing and analyzing generated models. - -It examines the solution plan, training code, and inference code to extract -metadata about the model, such as the framework used, model type, and provides -explanations about how the model works and why it's appropriate for the task. -""" - -import json -import logging -from datetime import datetime -from typing import Dict - -from pydantic import BaseModel - -from plexe.config import prompt_templates -from plexe.internal.common.provider import Provider - -logger = logging.getLogger(__name__) - - -class ModelReviewResponse(BaseModel): - """ - Response model for the model review operation. - """ - - framework: str # e.g. PyTorch, TensorFlow, Scikit-Learn - model_type: str # e.g. CNN, Transformer, RandomForest - - task_type: str # e.g. classification, regression, generation - domain: str # e.g. NLP, computer vision, tabular, multimodal - - behavior: str # what the model 'does', what relationship is it really learning - - preprocessing_summary: str # high-level view of input processing pipeline - architecture_summary: str # concise summary of model architecture - training_procedure: str # brief description of optimizer, loss, epochs, etc. - evaluation_metric: str # list of metrics used for evaluation (e.g., accuracy, F1) - - inference_behavior: str # how inference is performed, assumptions, outputs - strengths: str # where the model is expected to perform well - limitations: str # known weaknesses, assumptions, or risks - - selection_rationale: str # why this model was selected for the given intent - - -class ModelReviewer: - """ - A class for analyzing and reviewing generated models. - """ - - def __init__(self, provider: Provider): - """ - Initialize the model reviewer with a provider. - - :param provider: The provider to use for generating model reviews - """ - self.provider = provider - - def review_model( - self, - intent: str, - input_schema: Dict[str, str], - output_schema: Dict[str, str], - solution_plan: str, - training_code: str, - inference_code: str, - ) -> Dict[str, str]: - """ - Review a generated model to extract metadata, explanations and insights about the trained model. - - :param intent: The original model intent - :param input_schema: The input schema for the model, for example {"feat_1": "int", "feat_2": "str"} - :param output_schema: The output schema for the model, for example {"output": "float"} - :param solution_plan: The solution plan used to generate the model - :param training_code: The generated training code - :param inference_code: The generated inference code - :return: A dictionary containing framework, model_type, creation_date and various explanations - """ - try: - response = self.provider.query( - system_message=prompt_templates.review_system(), - user_message=prompt_templates.review_model( - intent=intent, - input_schema=json.dumps(input_schema, indent=2), - output_schema=json.dumps(output_schema, indent=2), - solution_plan=solution_plan, - training_code=training_code, - inference_code=inference_code, - ), - response_format=ModelReviewResponse, - ) - - # Parse the response and create metadata dictionary - review_data = json.loads(response) - - # Create metadata dictionary with review results and creation date - metadata = { - "framework": review_data["framework"], - "model_type": review_data["model_type"], - "task_type": review_data["task_type"], - "domain": review_data["domain"], - "behavior": review_data["behavior"], - "preprocessing_summary": review_data["preprocessing_summary"], - "architecture_summary": review_data["architecture_summary"], - "training_procedure": review_data["training_procedure"], - "evaluation_metric": review_data["evaluation_metric"], - "inference_behavior": review_data["inference_behavior"], - "strengths": review_data["strengths"], - "limitations": review_data["limitations"], - "selection_rationale": review_data["selection_rationale"], - "creation_date": datetime.now().isoformat(), - } - return metadata - - except Exception as e: - logger.warning(f"Error during model review: {str(e)}") - # Return default values if there was an error - return { - "framework": "Unknown", - "model_type": "Unknown", - "task_type": "Unknown", - "domain": "Unknown", - "behavior": "Unknown", - "preprocessing_summary": "Unknown", - "architecture_summary": "Unknown", - "training_procedure": "Unknown", - "evaluation_metric": "Unknown", - "inference_behavior": "Unknown", - "strengths": "Unknown", - "limitations": "Unknown", - "selection_rationale": "Could not determine model details due to an error.", - "creation_date": datetime.now().isoformat(), - } diff --git a/plexe/internal/models/validation/__init__.py b/plexe/internal/models/validation/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/plexe/internal/models/validation/composite.py b/plexe/internal/models/validation/composite.py deleted file mode 100644 index d8fbef00..00000000 --- a/plexe/internal/models/validation/composite.py +++ /dev/null @@ -1,43 +0,0 @@ -# plexe/internal/models/validation/composite.py - -""" -This module defines the `CompositeValidator` class, which chains multiple validators together in a workflow. - -Classes: - - CompositeValidator: A validator that chains multiple validators together in a workflow. -""" - -from plexe.internal.models.validation.validator import Validator, ValidationResult - - -class CompositeValidator(Validator): - """ - A validator that chains multiple validators together in a workflow. - - Attributes: - validators (list[Validator]): The validators to run in the workflow. - """ - - def __init__(self, name: str, validators: list[Validator]): - """ - Initializes the validator pipeline with a name and a list of validators. - - :param [str] name: The name of the validator pipeline. - :param [list[Validator]] validators: The validators to run in the pipeline. - """ - super().__init__(name) - self.validators = validators - - def validate(self, code: str, **kwargs) -> ValidationResult: - """ - Validates the given code by running it through each validator in the pipeline. - - :param [str] code: The code to validate. - :return: [ValidationResult] The result of the validation. - """ - for validator in self.validators: - result = validator.validate(code, **kwargs) - if not result.passed: - return result - - return ValidationResult(self.name, True, "All validators passed.") diff --git a/plexe/internal/models/validation/composites/__init__.py b/plexe/internal/models/validation/composites/__init__.py deleted file mode 100644 index 8e1c585e..00000000 --- a/plexe/internal/models/validation/composites/__init__.py +++ /dev/null @@ -1,2 +0,0 @@ -from plexe.internal.models.validation.composites.training import TrainingCodeValidator as TrainingCodeValidator -from plexe.internal.models.validation.composites.inference import InferenceCodeValidator as InferenceCodeValidator diff --git a/plexe/internal/models/validation/composites/inference.py b/plexe/internal/models/validation/composites/inference.py deleted file mode 100644 index 03048113..00000000 --- a/plexe/internal/models/validation/composites/inference.py +++ /dev/null @@ -1,42 +0,0 @@ -""" -This module defines a composite validator for validating the correctness of prediction code. - -Classes: - - InferenceCodeValidator: A validator class that validates the correctness of prediction code. -""" - -from typing import Type, List, Dict, Any - -from pydantic import BaseModel - -from plexe.internal.models.validation.composite import CompositeValidator -from plexe.internal.models.validation.primitives.predict import PredictorValidator -from plexe.internal.models.validation.primitives.syntax import SyntaxValidator - - -class InferenceCodeValidator(CompositeValidator): - """ - A validator class that validates the correctness of prediction code. - """ - - def __init__( - self, - input_schema: Type[BaseModel], - output_schema: Type[BaseModel], - input_sample: List[Dict[str, Any]], - ): - """ - Initialize the InferenceCodeValidator with the name 'prediction'. - - Args: - input_schema: The input schema for the model - output_schema: The output schema for the model - input_sample: List of sample input dictionaries to test the predictor - """ - super().__init__( - "prediction", - [ - SyntaxValidator(), - PredictorValidator(input_schema, output_schema, input_sample), - ], - ) diff --git a/plexe/internal/models/validation/composites/training.py b/plexe/internal/models/validation/composites/training.py deleted file mode 100644 index 1767e4be..00000000 --- a/plexe/internal/models/validation/composites/training.py +++ /dev/null @@ -1,23 +0,0 @@ -# internal/models/validation/pipelines.py - -""" -This module defines a composite validator for validating the correctness of training code. - -Classes: - - TrainingCodeValidator: A validator class that validates the correctness of training code. -""" - -from plexe.internal.models.validation.primitives.syntax import SyntaxValidator -from plexe.internal.models.validation.composite import CompositeValidator - - -class TrainingCodeValidator(CompositeValidator): - """ - A validator class that validates the correctness of training code. - """ - - def __init__(self): - """ - Initialize the TrainingValidator with the name 'training'. - """ - super().__init__("training", [SyntaxValidator()]) diff --git a/plexe/internal/models/validation/primitives/__init__.py b/plexe/internal/models/validation/primitives/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/plexe/internal/models/validation/primitives/predict.py b/plexe/internal/models/validation/primitives/predict.py deleted file mode 100644 index 15c2bfdd..00000000 --- a/plexe/internal/models/validation/primitives/predict.py +++ /dev/null @@ -1,142 +0,0 @@ -""" -This module defines the `PredictorValidator` class, which validates that a predictor behaves as expected. - -Classes: - - PredictorValidator: A validator class that checks the behavior of a predictor. -""" - -import types -import warnings -from typing import Type, List, Dict, Any - -from pydantic import BaseModel - -from plexe.internal.models.validation.validator import Validator, ValidationResult -from plexe.core.interfaces.predictor import Predictor - - -class PredictorValidator(Validator): - """ - A validator class that checks that a predictor behaves as expected. - """ - - def __init__( - self, - input_schema: Type[BaseModel], - output_schema: Type[BaseModel], - sample: List[Dict[str, Any]], - ) -> None: - """ - Initialize the PredictorValidator with the name 'predictor'. - - :param input_schema: The input schema of the predictor. - :param output_schema: The output schema of the predictor. - :param sample: List of sample input dictionaries to test the predictor. - """ - super().__init__("predictor") - self.input_schema: Type[BaseModel] = input_schema - self.output_schema: Type[BaseModel] = output_schema - self.input_sample: List[Dict[str, Any]] = sample - - def validate(self, code: str, model_artifacts=None) -> ValidationResult: - """ - Validates that the given code for a predictor behaves as expected. - :param code: prediction code to be validated - :param model_artifacts: model artifacts to be used for validation - :return: True if valid, False otherwise - """ - - def validation_error(stage, e): - """Helper to create validation error results""" - return ValidationResult( - self.name, - False, - message=f"Failed at {stage} stage: {str(e)}", - exception=e, - error_stage=stage, - error_type=type(e).__name__, - error_details=str(e), - ) - - # Stage 1: Load module - try: - predictor_module = self._load_module(code) - except Exception as e: - return validation_error("loading", e) - - # Stage 2: Check class definition - try: - predictor_class = getattr(predictor_module, "PredictorImplementation") - self._is_subclass(predictor_class) - except Exception as e: - return validation_error("class_definition", e) - - # Stage 3: Initialize predictor - try: - predictor = predictor_class(model_artifacts) - except Exception as e: - return validation_error("initialization", e) - - # Stage 4: Test prediction - try: - self._returns_output_when_called(predictor) - except Exception as e: - return validation_error("prediction", e) - - # All validation steps passed - return ValidationResult(self.name, True, "Prediction code is valid.") - - @staticmethod - def _load_module(code: str) -> types.ModuleType: - """ - Compiles and loads the predictor module from the given code. - """ - with warnings.catch_warnings(): - warnings.simplefilter("ignore") - module = types.ModuleType("test_predictor") - try: - exec(code, module.__dict__) - except Exception as e: - raise RuntimeError(f"Failed to load predictor: {str(e)}") - return module - - @staticmethod - def _is_subclass(predictor) -> None: - if not issubclass(predictor, Predictor): - raise TypeError("The predictor class is not a subclass of Predictor.") - - def _returns_output_when_called(self, predictor) -> None: - """ - Tests the `predict` function by calling it with sample inputs and validates outputs. - """ - total_tests = len(self.input_sample) - issues = [] - - for i, sample in enumerate(self.input_sample): - try: - with warnings.catch_warnings(): - warnings.simplefilter("ignore") - # Test prediction execution - output = predictor.predict(sample) - - # Validate output against schema - try: - self.output_schema.model_validate(output) - except Exception as schema_err: - # Include truncated sample and output for context - truncated_output = str(output)[:100] + "..." if len(str(output)) > 100 else output - issues.append( - { - "error": f"Output schema validation error: {str(schema_err)}", - "output": truncated_output, - "index": i, - } - ) - except Exception as e: - # Include truncated sample for context - sample_str = str(sample) - truncated_sample = sample_str[:100] + "..." if len(sample_str) > 100 else sample_str - issues.append({"error": str(e), "sample": truncated_sample, "index": i}) - - if len(issues) > 0: - raise RuntimeError(f"{len(issues)}/{total_tests} calls to 'predict' failed. Issues: {issues}") diff --git a/plexe/internal/models/validation/primitives/security.py b/plexe/internal/models/validation/primitives/security.py deleted file mode 100644 index 3311b756..00000000 --- a/plexe/internal/models/validation/primitives/security.py +++ /dev/null @@ -1,35 +0,0 @@ -# plexe/internal/models/validation/security.py - -""" -This module defines the SecurityValidator class, which is responsible for validating the security -of Python code using the Bandit tool. - -Classes: - - SecurityValidator: A validator class that checks the security of Python code. -""" - -from plexe.internal.models.validation.validator import Validator, ValidationResult - - -class SecurityValidator(Validator): - """ - A validator class that checks the security of Python code using the Bandit tool. - """ - - def __init__(self): - """ - Initialize the SecurityValidator with the name 'security'. - """ - super().__init__("security") - - def validate(self, code: str, **kwargs) -> ValidationResult: - """ - Validate the generated code for security vulnerabilities using the Bandit tool. - - :param code: The Python code to be validated. - :return: The result of the validation, indicating whether any security vulnerabilities were found. - """ - # todo: implement properly by invoking bandit, see https://bandit.readthedocs.io/en/latest/start.html - return ValidationResult( - name=self.name, passed=True, message="No security vulnerabilities found.", exception=None - ) diff --git a/plexe/internal/models/validation/primitives/syntax.py b/plexe/internal/models/validation/primitives/syntax.py deleted file mode 100644 index bf1e6db2..00000000 --- a/plexe/internal/models/validation/primitives/syntax.py +++ /dev/null @@ -1,46 +0,0 @@ -# plexe/internal/models/validation/syntax.py - -""" -This module defines the SyntaxValidator class, which is responsible for validating the syntax -of Python code using the AST module. - -Classes: - - SyntaxValidator: A validator class that checks the syntax of Python code. -""" - -import ast - -from plexe.internal.models.validation.validator import Validator, ValidationResult - - -class SyntaxValidator(Validator): - """ - A validator class that checks the syntax of Python code using the AST module. - """ - - def __init__(self): - """ - Initialize the SyntaxValidator with the name 'syntax'. - """ - super().__init__("syntax") - - def validate(self, code: str, **kwargs) -> ValidationResult: - """ - Validate Python code using AST. - - :param code: Python code to validate. - :return: Validation result indicating syntax validity. - """ - try: - ast.parse(code) - return ValidationResult(self.name, passed=True, message="Syntax is valid.") - except SyntaxError as e: - return ValidationResult( - self.name, - False, - message=f"Syntax is not valid: {e.msg} at line {e.lineno}, column {e.offset}.", - exception=e, - error_stage="syntax", - error_type="SyntaxError", - error_details=f"{e.msg} at line {e.lineno}, column {e.offset}", - ) diff --git a/plexe/internal/models/validation/validator.py b/plexe/internal/models/validation/validator.py deleted file mode 100644 index 9d1733c1..00000000 --- a/plexe/internal/models/validation/validator.py +++ /dev/null @@ -1,64 +0,0 @@ -# plexe/internal/models/validation/validator.py - -""" -This module defines the `Validator` abstract base class and the `ValidationResult` data class. - -The `Validator` class provides a framework for implementing various code validators, while the -`ValidationResult` class encapsulates the results of a validation, including whether it passed, -any messages, and exceptions raised during validation. -""" - -import abc -from dataclasses import dataclass - - -@dataclass -class ValidationResult: - """ - Represents the result of a validation. - - Attributes: - name (str): The name of the validation. - passed (bool): Whether the validation passed or not. - message (str, optional): A message providing details about the validation result. - exception (Exception, optional): An exception that was raised during validation, if any. - error_stage (str, optional): The stage at which validation failed (e.g., "syntax", "loading", "prediction"). - error_type (str, optional): The type of error that occurred (e.g., "SyntaxError", "TypeError"). - error_details (str, optional): Detailed information about the error. - """ - - name: str - passed: bool - message: str = None - exception: Exception | None = None - error_stage: str = None - error_type: str = None - error_details: str = None - - -class Validator(abc.ABC): - """ - Abstract base class for validators. - - Attributes: - name (str): The name of the validator. - """ - - @abc.abstractmethod - def __init__(self, name: str): - """ - Initializes the validator with a name. - - :param [str] name: The name of the validator. - """ - self.name = name - - @abc.abstractmethod - def validate(self, code: str, **kwargs) -> ValidationResult: - """ - Validates the given code. - - :param [str] code: The code to validate. - :return: [ValidationResult] The result of the validation. - """ - pass diff --git a/plexe/internal/schemas/__init__.py b/plexe/internal/schemas/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/plexe/internal/schemas/resolver.py b/plexe/internal/schemas/resolver.py deleted file mode 100644 index 2d92b208..00000000 --- a/plexe/internal/schemas/resolver.py +++ /dev/null @@ -1,139 +0,0 @@ -""" -Module for schema generation and handling. -""" - -import json -import logging -from enum import Enum -from typing import Tuple, Dict, Type - -from pydantic import BaseModel, create_model - -from plexe.config import prompt_templates -from plexe.internal.common.datasets.interface import TabularConvertible -from plexe.internal.common.provider import Provider -from plexe.internal.common.datasets.adapter import DatasetAdapter -from plexe.internal.common.utils.pandas_utils import convert_dtype_to_python -from plexe.internal.common.utils.pydantic_utils import map_to_basemodel - -logger = logging.getLogger(__name__) - - -class SchemaResolver: - """ - A utility class for resolving input and output schemas for a given intent and dataset. - """ - - def __init__( - self, - provider: Provider, - intent: str, - input_schema: Type[BaseModel] = None, - output_schema: Type[BaseModel] = None, - ): - self.provider: Provider = provider - self.intent: str = intent - self.input_schema: Type[BaseModel] | None = input_schema - self.output_schema: Type[BaseModel] | None = output_schema - - # TODO: support Dataset interface instead of just TabularConvertible - def resolve(self, datasets: Dict[str, TabularConvertible] = None) -> Tuple[Type[BaseModel], Type[BaseModel]]: - """ - Resolve the input and output schemas for a given intent and dataset. - - :param datasets: A dictionary of dataset names and their corresponding data. - :return: A tuple containing the input and output schemas. - """ - if datasets: - return self._resolve_from_datasets(datasets) - else: - return self._resolve_from_intent() - - # TODO: support Dataset interface instead of just TabularConvertible - def _resolve_from_datasets( - self, datasets: Dict[str, TabularConvertible] - ) -> Tuple[Type[BaseModel], Type[BaseModel]]: - """ - Generate a schema from a dataset. - :param datasets: - :return: - """ - - try: - feature_names = DatasetAdapter.features(datasets) - - # Infer output column - class OutputSchema(BaseModel): - output: Enum("Features", {feat: feat for feat in feature_names}) - - # Use LLM to decide what the output should be - output_col = json.loads( - self.provider.query( - system_message=prompt_templates.schema_base(), - user_message=prompt_templates.schema_identify_target( - columns="\n".join(f"- {feat}" for feat in feature_names), intent=self.intent - ), - response_format=OutputSchema, - ) - )["output"] - - # Verify output column exists - if output_col not in feature_names: - raise RuntimeError(f"LLM suggested non-existent feature {output_col} as target.") - - # Infer input schema - types = {} - for feature in feature_names: - match feature.split("."): - case [dataset, column]: - if isinstance(datasets[dataset], TabularConvertible): - df = datasets[dataset].to_pandas() - # Pass sample values to help detect list types in object columns - sample_values = df[column].dropna().head(10).tolist() if len(df) > 0 else None - types[column] = convert_dtype_to_python(df[column].dtype, sample_values) - else: - raise ValueError(f"Dataset {dataset} has unsupported type: '{type(datasets[dataset])}'") - case [dataset]: - raise ValueError(f"Dataset {dataset} has unsupported type: '{type(datasets[dataset])}'") - case _: - raise ValueError(f"Feature name '{feature}' is not in the expected format.") - - output_col = output_col.split(".")[-1] - - # Split into input and output schemas - input_schema = {col: types[col] for col in types if col != output_col} - output_schema = {output_col: types[output_col]} - - return map_to_basemodel("InputSchema", input_schema), map_to_basemodel("OutputSchema", output_schema) - - except Exception as e: - logger.error(f"Error inferring schema from data: {e}") - raise - - def _resolve_from_intent(self) -> Tuple[Type[BaseModel], Type[BaseModel]]: - """ - Generate a schema from an intent using the LLM. - :return: input and output schemas - """ - try: - - class SchemaResponse(BaseModel): - input_schema: Dict[str, str] - output_schema: Dict[str, str] - - response = SchemaResponse( - **json.loads( - self.provider.query( - system_message=prompt_templates.schema_base(), - user_message=prompt_templates.schema_generate_from_intent(intent=self.intent), - response_format=SchemaResponse, - ) - ) - ) - return ( - create_model("InputSchema", **response.input_schema), - create_model("OutputSchema", **response.output_schema), - ) - except Exception as e: - logger.error(f"Error generating schema from intent: {e}") - raise diff --git a/plexe/langgraph/__init__.py b/plexe/langgraph/__init__.py new file mode 100644 index 00000000..f69a000c --- /dev/null +++ b/plexe/langgraph/__init__.py @@ -0,0 +1,30 @@ +""" +LangGraph-based multi-agent system for ML model generation. + +This module provides a refactored agent architecture using LangGraph +for orchestrating multiple specialized agents in the ML pipeline. +""" + +from plexe.langgraph.agents import ( + ConversationalAgent, + EDAAgent, + DatasetBuilderAgent, + TaskBuilderAgent, + RelationalGNNSpecialistAgent, + OperationAgent, +) +from plexe.langgraph.orchestrator import PlexeOrchestrator +from plexe.langgraph.state import PipelineState +from plexe.langgraph.config import AgentConfig + +__all__ = [ + "ConversationalAgent", + "EDAAgent", + "DatasetBuilderAgent", + "TaskBuilderAgent", + "RelationalGNNSpecialistAgent", + "OperationAgent", + "PlexeOrchestrator", + "PipelineState", + "AgentConfig", +] diff --git a/plexe/langgraph/agents/__init__.py b/plexe/langgraph/agents/__init__.py new file mode 100644 index 00000000..8c129500 --- /dev/null +++ b/plexe/langgraph/agents/__init__.py @@ -0,0 +1,23 @@ +""" +LangGraph-based agent implementations. + +This module provides specialized agents for the ML pipeline using LangGraph. +""" + +from plexe.langgraph.agents.base import BaseAgent +from plexe.langgraph.agents.conversational import ConversationalAgent +from plexe.langgraph.agents.eda import EDAAgent +from plexe.langgraph.agents.dataset_builder import DatasetBuilderAgent +from plexe.langgraph.agents.task_builder import TaskBuilderAgent +from plexe.langgraph.agents.gnn_specialist import RelationalGNNSpecialistAgent +from plexe.langgraph.agents.operation import OperationAgent + +__all__ = [ + "BaseAgent", + "ConversationalAgent", + "EDAAgent", + "DatasetBuilderAgent", + "TaskBuilderAgent", + "RelationalGNNSpecialistAgent", + "OperationAgent", +] diff --git a/plexe/langgraph/agents/base.py b/plexe/langgraph/agents/base.py new file mode 100644 index 00000000..5c5d89b5 --- /dev/null +++ b/plexe/langgraph/agents/base.py @@ -0,0 +1,161 @@ +""" +Base agent class for LangGraph agents. + +Provides common functionality for all specialized agents. +""" + +import logging +from abc import ABC, abstractmethod +from typing import List, Dict, Any, Optional, Callable + +from langchain_core.tools import BaseTool +from langchain_core.messages import HumanMessage, AIMessage, SystemMessage +from langgraph.prebuilt import create_react_agent + +from plexe.langgraph.config import AgentConfig, get_llm_from_model_id +from plexe.langgraph.state import PipelineState + +logger = logging.getLogger(__name__) + + +class BaseAgent(ABC): + """Base class for all LangGraph agents.""" + + def __init__( + self, + agent_type: str, + config: Optional[AgentConfig] = None, + tools: Optional[List[BaseTool]] = None, + ): + """ + Initialize the base agent. + + Args: + agent_type: Type identifier for this agent + config: Agent configuration (uses defaults if None) + tools: List of tools available to this agent + """ + self.agent_type = agent_type + self.config = config or AgentConfig.from_env() + self.tools = tools or [] + + model_id = self.config.get_model_for_agent(agent_type) + self.llm = get_llm_from_model_id(model_id, self.config.temperature) + + self._agent = None + + @property + @abstractmethod + def system_prompt(self) -> str: + """Return the system prompt for this agent.""" + pass + + @property + def name(self) -> str: + """Return the agent name.""" + return self.__class__.__name__ + + @property + def description(self) -> str: + """Return the agent description.""" + return self.system_prompt[:200] + "..." + + def get_agent(self): + """Get or create the LangGraph agent.""" + if self._agent is None: + self._agent = create_react_agent( + model=self.llm, + tools=self.tools, + state_modifier=self.system_prompt, + ) + return self._agent + + def invoke(self, state: PipelineState) -> Dict[str, Any]: + """ + Invoke the agent with the current state. + + Args: + state: Current pipeline state + + Returns: + Updated state components + """ + agent = self.get_agent() + + messages = self._build_messages(state) + + try: + result = agent.invoke({"messages": messages}) + return self._process_result(result, state) + except Exception as e: + logger.error(f"Agent {self.name} failed: {e}") + return { + "errors": [f"{self.name} error: {str(e)}"] + } + + def _build_messages(self, state: PipelineState) -> List: + """Build message list from state.""" + messages = [] + + for msg in state.get("messages", []): + role = msg.get("role", "user") + content = msg.get("content", "") + + if role == "user": + messages.append(HumanMessage(content=content)) + elif role == "assistant": + messages.append(AIMessage(content=content)) + elif role == "system": + messages.append(SystemMessage(content=content)) + + context = self._build_context(state) + if context: + messages.append(HumanMessage(content=f"Current context:\n{context}")) + + return messages + + def _build_context(self, state: PipelineState) -> str: + """Build context string from state for the agent.""" + context_parts = [] + + if state.get("working_dir"): + context_parts.append(f"Working directory: {state['working_dir']}") + + if state.get("db_connection_string"): + context_parts.append(f"Database connection: {state['db_connection_string']}") + + if state.get("csv_dir"): + context_parts.append(f"CSV directory: {state['csv_dir']}") + + if state.get("schema_info"): + tables = list(state["schema_info"].get("tables", {}).keys()) + context_parts.append(f"Available tables: {', '.join(tables)}") + + if state.get("dataset_info"): + context_parts.append(f"Dataset class: {state['dataset_info'].get('class_name')}") + context_parts.append(f"Dataset file: {state['dataset_info'].get('file_path')}") + + if state.get("task_info"): + context_parts.append(f"Task class: {state['task_info'].get('class_name')}") + context_parts.append(f"Task type: {state['task_info'].get('task_type')}") + + return "\n".join(context_parts) + + def _process_result(self, result: Dict[str, Any], state: PipelineState) -> Dict[str, Any]: + """ + Process agent result and extract state updates. + + Override in subclasses to handle specific outputs. + """ + messages = result.get("messages", []) + + new_messages = [] + for msg in messages: + if isinstance(msg, AIMessage): + new_messages.append({ + "role": "assistant", + "content": msg.content, + "timestamp": None, + }) + + return {"messages": new_messages} diff --git a/plexe/langgraph/agents/conversational.py b/plexe/langgraph/agents/conversational.py new file mode 100644 index 00000000..e58b9048 --- /dev/null +++ b/plexe/langgraph/agents/conversational.py @@ -0,0 +1,143 @@ +""" +Conversational Agent for user interaction and requirements gathering. + +This agent guides users through ML model definition via natural conversation, +validates inputs, and initiates the model building process. +""" + +import logging +from typing import Optional, List, Dict, Any + +from langchain_core.tools import BaseTool + +from plexe.langgraph.agents.base import BaseAgent +from plexe.langgraph.config import AgentConfig +from plexe.langgraph.state import PipelineState, PipelinePhase +from plexe.langgraph.tools.conversational import get_dataset_preview +from plexe.langgraph.tools.graph_architect import validate_db_connection + +logger = logging.getLogger(__name__) + + +CONVERSATIONAL_SYSTEM_PROMPT = """You are an expert ML and Deep Learning consultant helping users define their machine learning requirements through natural conversation. + +## Your Role +- Guide users through defining their ML problem clearly +- Understand their data and prediction goals +- Validate data availability and quality +- Initiate the ML pipeline when requirements are complete + +## Conversation Strategy +1. Ask ONE focused question at a time +2. Use tools to examine their data before asking detailed questions +3. Help refine vague statements into precise ML problem definitions +4. Summarize requirements and confirm before proceeding + +## Requirements Checklist (gather ALL before proceeding) +1. **Clear Problem Statement**: What exactly to predict/classify +2. **Input/Output Definition**: Model inputs and expected outputs +3. **Data Understanding**: Examined their data structure +4. **Data Source**: CSV files or database connection +5. **User Confirmation**: Explicit confirmation to start building + +## When Working with Databases +1. Use validate_db_connection to see available tables +2. Discuss what they want to predict +3. Clarify the target variable and entity +4. Gather all requirements before signaling readiness + +## Response Format +Keep responses conversational, friendly, and focused. Ask clarifying questions when needed. +When all requirements are gathered, summarize them and ask for final confirmation. + +## Important +- Do NOT rush to build models +- Ensure clarity on the prediction task +- Validate data accessibility +- Get explicit user confirmation before proceeding +""" + + +class ConversationalAgent(BaseAgent): + """Agent for conversational requirements gathering and user interaction.""" + + def __init__( + self, + config: Optional[AgentConfig] = None, + additional_tools: Optional[List[BaseTool]] = None, + ): + """ + Initialize the conversational agent. + + Args: + config: Agent configuration + additional_tools: Additional tools beyond defaults + """ + tools = [ + get_dataset_preview, + validate_db_connection, + ] + + if additional_tools: + tools.extend(additional_tools) + + super().__init__( + agent_type="conversational", + config=config, + tools=tools, + ) + + @property + def system_prompt(self) -> str: + return CONVERSATIONAL_SYSTEM_PROMPT + + def _process_result(self, result: Dict[str, Any], state: PipelineState) -> Dict[str, Any]: + """Process conversation result and detect readiness to proceed.""" + base_result = super()._process_result(result, state) + + messages = result.get("messages", []) + last_message = messages[-1] if messages else None + + if last_message: + content = last_message.content.lower() if hasattr(last_message, 'content') else "" + + ready_indicators = [ + "ready to proceed", + "start building", + "begin training", + "initiate pipeline", + "all requirements gathered", + ] + + if any(indicator in content for indicator in ready_indicators): + base_result["user_confirmation_required"] = True + base_result["user_confirmation_context"] = { + "type": "proceed_to_pipeline", + "message": "Ready to start the ML pipeline?" + } + + return base_result + + def extract_intent(self, state: PipelineState) -> Dict[str, Any]: + """ + Extract structured intent from conversation. + + Returns: + Dictionary with extracted intent information + """ + messages = state.get("messages", []) + + intent = { + "prediction_target": None, + "entity_type": None, + "task_type": None, + "data_source": None, + "confirmed": False, + } + + if state.get("db_connection_string"): + intent["data_source"] = "database" + elif state.get("csv_dir"): + intent["data_source"] = "csv" + + return intent diff --git a/plexe/langgraph/agents/dataset_builder.py b/plexe/langgraph/agents/dataset_builder.py new file mode 100644 index 00000000..ca750a02 --- /dev/null +++ b/plexe/langgraph/agents/dataset_builder.py @@ -0,0 +1,295 @@ +""" +Dataset Builder Agent. + +This agent builds RelBench Database objects from CSV files, +generating complete Python Dataset classes for GNN training. +""" + +import logging +from typing import Optional, List, Dict, Any + +from langchain_core.tools import BaseTool + +from plexe.langgraph.agents.base import BaseAgent +from plexe.langgraph.config import AgentConfig +from plexe.langgraph.state import PipelineState, PipelinePhase +from plexe.langgraph.tools.common import save_artifact +from plexe.langgraph.tools.dataset_builder import ( + get_csv_files_info, + get_temporal_statistics, + register_dataset_code, +) + +logger = logging.getLogger(__name__) + + +DATASET_BUILDER_SYSTEM_PROMPT = """You are the Dataset Builder Agent, an expert in building RelBench Database objects from raw CSV data. + +## Your Mission +Generate a complete Python Dataset class (GenDataset) that: +1. Loads CSV files from a specified directory +2. Processes and cleans the data appropriately +3. Defines the database schema (PKs, FKs, time columns) +4. Provides proper temporal splitting (val_timestamp, test_timestamp) + +## Workflow + +### Step 1: Discover CSV Files +Use get_csv_files_info to list available CSV files and their columns. + +### Step 2: Analyze Temporal Data +Use get_temporal_statistics to: +- Find timestamp columns in each table +- Get suggested val_timestamp and test_timestamp values +- Understand the temporal distribution of data + +### Step 3: Generate Dataset Code +Create a complete GenDataset class following this structure: + +```python +import os +import numpy as np +import pandas as pd +from typing import Optional +from plexe.relbench.base import Database, Dataset, Table + +class GenDataset(Dataset): + val_timestamp = pd.Timestamp("YYYY-MM-DD") + test_timestamp = pd.Timestamp("YYYY-MM-DD") + + def __init__(self, csv_dir: str, cache_dir: Optional[str] = None): + self.csv_dir = csv_dir + super().__init__(cache_dir=cache_dir) + + def make_db(self) -> Database: + path = self.csv_dir + + # 1. Load CSV files + # table_name = pd.read_csv(os.path.join(path, "table_name.csv")) + + # 2. Data cleaning (drop irrelevant columns, handle nulls) + + # 3. Time processing (parse timestamps, propagate from parent to child) + + # 4. Build and return Database + db = Database( + table_dict={ + "table_name": Table( + df=table_df, + fkey_col_to_pkey_table={"fk_col": "referenced_table"}, + pkey_col="primary_key_col", + time_col="timestamp_col", # or None for static tables + ), + # ... more tables + } + ) + return db +``` + +### Step 4: Register the Code +Use register_dataset_code to save the generated code. + +## Critical Concepts + +### Temporal Splitting +- val_timestamp: Rows up to this time for validation +- test_timestamp: Rows up to this time for test +- Choose based on data distribution (~70% for val, ~85% for test) + +### Table Definition +- pkey_col: Primary key (can be None for junction tables) +- fkey_col_to_pkey_table: Dict mapping FK columns to referenced tables +- time_col: Creation/event time (None for static dimension tables) + +### Data Cleaning Guidelines +- Drop columns with >50% nulls +- Drop URL/image columns (not useful for GNN) +- Handle database NULL markers (\\N -> NaN) +- Convert timestamps properly +- Propagate timestamps from parent to child tables when needed + +## Important +- Always use class name 'GenDataset' +- Use exact column names from CSV files (typically snake_case) +- Get val/test timestamps from get_temporal_statistics +- Register the code using register_dataset_code tool +""" + + +DATASET_CODE_TEMPLATE = '''""" +Auto-generated Dataset class for RelBench. +""" + +import os +import numpy as np +import pandas as pd +from typing import Optional + +from plexe.relbench.base import Database, Dataset, Table + + +class GenDataset(Dataset): + """Generated Dataset class for the relational database.""" + + val_timestamp = pd.Timestamp("{val_timestamp}") + test_timestamp = pd.Timestamp("{test_timestamp}") + + def __init__(self, csv_dir: str, cache_dir: Optional[str] = None): + self.csv_dir = csv_dir + super().__init__(cache_dir=cache_dir) + + def make_db(self) -> Database: + path = self.csv_dir + +{load_code} + +{cleaning_code} + +{time_processing_code} + + db = Database( + table_dict={{ +{table_dict_code} + }} + ) + + return db +''' + + +class DatasetBuilderAgent(BaseAgent): + """Agent for building RelBench Dataset classes from CSV data.""" + + def __init__( + self, + config: Optional[AgentConfig] = None, + additional_tools: Optional[List[BaseTool]] = None, + ): + """ + Initialize the dataset builder agent. + + Args: + config: Agent configuration + additional_tools: Additional tools beyond defaults + """ + tools = [ + get_csv_files_info, + get_temporal_statistics, + register_dataset_code, + save_artifact, + ] + + if additional_tools: + tools.extend(additional_tools) + + super().__init__( + agent_type="dataset_builder", + config=config, + tools=tools, + ) + + @property + def system_prompt(self) -> str: + return DATASET_BUILDER_SYSTEM_PROMPT + + def _build_context(self, state: PipelineState) -> str: + """Build context with CSV, schema, and EDA information.""" + context_parts = [] + + if state.get("working_dir"): + context_parts.append(f"Working directory: {state['working_dir']}") + + if state.get("csv_dir"): + context_parts.append(f"CSV files directory: {state['csv_dir']}") + + if state.get("schema_info"): + schema = state["schema_info"] + tables = list(schema.get("tables", {}).keys()) + context_parts.append(f"Tables from schema: {', '.join(tables)}") + + if schema.get("relationships"): + rels = [f"{r['source_table']}.{r['source_column']} -> {r['target_table']}" + for r in schema["relationships"]] + context_parts.append(f"Relationships: {'; '.join(rels)}") + + if schema.get("temporal_columns"): + temporal = [f"{t}: {cols}" for t, cols in schema["temporal_columns"].items()] + context_parts.append(f"Temporal columns: {'; '.join(temporal)}") + + # Include EDA information from previous phase + if state.get("eda_info"): + eda = state["eda_info"] + context_parts.append("\n## EDA Analysis Results:") + + if eda.get("quality_issues"): + context_parts.append("Data Quality Issues:") + for table, issues in eda["quality_issues"].items(): + if issues: + context_parts.append(f" - {table}: {issues}") + + if eda.get("temporal_analysis"): + context_parts.append("Temporal Analysis:") + for table, analysis in eda["temporal_analysis"].items(): + if analysis.get("time_columns"): + context_parts.append(f" - {table}: time columns = {analysis['time_columns']}") + + if eda.get("suggested_splits"): + splits = eda["suggested_splits"] + if splits.get("val_timestamp"): + context_parts.append(f"Suggested val_timestamp: {splits['val_timestamp']}") + if splits.get("test_timestamp"): + context_parts.append(f"Suggested test_timestamp: {splits['test_timestamp']}") + + if eda.get("relationship_analysis"): + context_parts.append("Relationship Analysis:") + for key, info in eda["relationship_analysis"].items(): + if isinstance(info, dict) and info.get("cardinality"): + context_parts.append(f" - {key}: {info['cardinality']}") + + task_instruction = """ +Your task: +1. Analyze the CSV files using get_csv_files_info +2. Get temporal statistics using get_temporal_statistics (use EDA suggestions if available) +3. Generate a complete GenDataset class with proper: + - Table loading + - Data cleaning (address quality issues found in EDA) + - Temporal processing + - Schema definition (PKs, FKs, time_cols) +4. Register the code using register_dataset_code + +The output file should be saved as 'dataset.py' in the working directory. +""" + context_parts.append(task_instruction) + + return "\n".join(context_parts) + + def _process_result(self, result: Dict[str, Any], state: PipelineState) -> Dict[str, Any]: + """Process result and extract dataset information from tool calls.""" + base_result = super()._process_result(result, state) + + dataset_info = {} + generated_code = state.get("generated_code", {}) + + if "tool_calls" in result and result["tool_calls"]: + for tool_call in result["tool_calls"]: + tool_name = tool_call.get("name", "") + tool_result = tool_call.get("result", {}) + + if tool_name == "register_dataset_code" and tool_result.get("status") == "registered": + dataset_info["class_name"] = tool_result.get("class_name", "GenDataset") + dataset_info["file_path"] = tool_result.get("file_path") + if "code" in tool_result: + generated_code["dataset"] = tool_result["code"] + + if not dataset_info: + dataset_info["class_name"] = "GenDataset" + + if dataset_info: + base_result["dataset_info"] = dataset_info + + if generated_code: + base_result["generated_code"] = generated_code + + base_result["current_phase"] = PipelinePhase.TASK_BUILDING.value + + return base_result diff --git a/plexe/langgraph/agents/eda.py b/plexe/langgraph/agents/eda.py new file mode 100644 index 00000000..06a73b96 --- /dev/null +++ b/plexe/langgraph/agents/eda.py @@ -0,0 +1,221 @@ +""" +EDA (Exploratory Data Analysis) Agent. + +This agent transforms relational databases into heterogeneous graphs, +performs comprehensive exploratory data analysis, and prepares data for modeling. +""" + +import logging +from typing import Optional, List, Dict, Any + +from langchain_core.tools import BaseTool + +from plexe.langgraph.agents.base import BaseAgent +from plexe.langgraph.config import AgentConfig +from plexe.langgraph.state import PipelineState, PipelinePhase +from plexe.langgraph.tools.graph_architect import ( + validate_db_connection, + export_tables_to_csv, + extract_schema_metadata, +) +from plexe.langgraph.tools.eda import ( + analyze_csv_statistics, + detect_data_quality_issues, + analyze_temporal_patterns, + analyze_table_relationships, + generate_eda_summary, +) + +logger = logging.getLogger(__name__) + + +EDA_SYSTEM_PROMPT = """You are the EDA (Exploratory Data Analysis) Agent, an expert in Relational Deep Learning and data analysis. + +## Your Mission +1. Transform relational databases into Relational Entity Graphs where: + - Rows become nodes + - Primary-foreign key relationships become edges + - Preserving structural and temporal signals + +2. Perform comprehensive exploratory data analysis to understand: + - Data distributions and statistics + - Data quality issues + - Temporal patterns for time-series modeling + - Table relationships and classification + +## Workflow + +### Step 1: Database Export +- Use validate_db_connection to verify database access +- Use extract_schema_metadata to analyze schema (tables, PKs, FKs, temporal columns) +- Use export_tables_to_csv to export all tables to CSV format + +### Step 2: Statistical Analysis +- Use analyze_csv_statistics to get descriptive statistics for all columns +- Understand data distributions, missing values, and cardinality + +### Step 3: Data Quality Assessment +- Use detect_data_quality_issues to identify: + - High missing value rates (>50%) + - Constant columns + - Duplicate rows + - Potential ID columns + +### Step 4: Temporal Analysis +- Use analyze_temporal_patterns to: + - Identify temporal columns + - Analyze time ranges and gaps + - Suggest train/val/test temporal splits + +### Step 5: Relationship Analysis +- Use analyze_table_relationships to: + - Analyze foreign key statistics + - Classify tables as Fact vs Dimension + - Identify potential entity tables for prediction + +### Step 6: Generate Summary +- Use generate_eda_summary to create comprehensive report +- Provide key findings and recommendations for Dataset and Task builders + +## Key Concepts + +### Table Classification +- **Fact Tables**: Events/transactions with temporal data (orders, clicks) → Good entity tables +- **Dimension Tables**: Static entities (users, products) → Referenced by FKs +- **Junction Tables**: Many-to-many relationships + +### Data Quality Flags +- **High Severity**: greater than 50% missing values, critical for handling +- **Medium Severity**: 20-50% missing, duplicate rows +- **Low Severity**: Constant columns, all-unique columns + +### Temporal Patterns +- Identify timestamp columns with greater than 50% valid dates +- Calculate time ranges and average gaps +- Suggest 70/15/15 train/val/test splits based on temporal ordering + +## Output Requirements +Provide comprehensive EDA report including: +1. Statistical summary (row counts, column types, distributions) +2. Data quality assessment with severity flags +3. Temporal analysis with suggested splits +4. Table classification (Fact vs Dimension) +5. Recommendations for Dataset Builder (handle missing values, feature selection) +6. Recommendations for Task Builder (suggested entity tables, temporal splits) + +## Important Notes +- Always run EDA AFTER exporting CSV files +- Pass schema_info to analyze_table_relationships for better classification +- Store all EDA results in state for downstream agents +- Provide actionable insights, not just raw statistics +""" + + +class EDAAgent(BaseAgent): + """Agent for schema analysis, data export, and exploratory data analysis.""" + + def __init__( + self, + config: Optional[AgentConfig] = None, + additional_tools: Optional[List[BaseTool]] = None, + ): + """ + Initialize the EDA agent. + + Args: + config: Agent configuration + additional_tools: Additional tools beyond defaults + """ + tools = [ + validate_db_connection, + export_tables_to_csv, + extract_schema_metadata, + analyze_csv_statistics, + detect_data_quality_issues, + analyze_temporal_patterns, + analyze_table_relationships, + generate_eda_summary, + ] + + if additional_tools: + tools.extend(additional_tools) + + super().__init__( + agent_type="eda", + config=config, + tools=tools, + ) + + @property + def system_prompt(self) -> str: + return EDA_SYSTEM_PROMPT + + def _build_context(self, state: PipelineState) -> str: + """Build context with database and EDA-specific information.""" + context_parts = [] + + if state.get("working_dir"): + context_parts.append(f"Working directory: {state['working_dir']}") + + if state.get("db_connection_string"): + context_parts.append(f"Database connection: {state['db_connection_string']}") + + if state.get("user_intent"): + context_parts.append(f"User intent: {state['user_intent']}") + + task_instruction = """ +Your task: +1. Connect to the database and validate the connection +2. Extract schema metadata (tables, PKs, FKs, temporal columns) +3. Export all tables to CSV files in the working directory +4. Perform comprehensive EDA: + - Statistical analysis of all columns + - Data quality assessment + - Temporal pattern analysis + - Table relationship analysis +5. Generate EDA summary with key findings and recommendations +6. Report results for Dataset Builder and Task Builder agents +""" + context_parts.append(task_instruction) + + return "\n".join(context_parts) + + def _process_result(self, result: Dict[str, Any], state: PipelineState) -> Dict[str, Any]: + """Process result and extract schema/CSV/EDA information from tool calls.""" + base_result = super()._process_result(result, state) + + eda_info = {} + + if "tool_calls" in result and result["tool_calls"]: + for tool_call in result["tool_calls"]: + tool_name = tool_call.get("name", "") + tool_result = tool_call.get("result", {}) + + if tool_name == "export_tables_to_csv" and tool_result.get("status") == "success": + base_result["csv_dir"] = tool_result.get("output_dir") + + if tool_name == "extract_schema_metadata" and "tables" in tool_result: + base_result["schema_info"] = tool_result + + if tool_name == "analyze_csv_statistics" and tool_result.get("status") == "success": + eda_info["statistics"] = tool_result.get("statistics") + + if tool_name == "detect_data_quality_issues" and tool_result.get("status") == "success": + eda_info["quality_issues"] = tool_result.get("quality_issues") + + if tool_name == "analyze_temporal_patterns" and tool_result.get("status") == "success": + eda_info["temporal_analysis"] = tool_result.get("temporal_analysis") + eda_info["suggested_splits"] = tool_result.get("suggested_splits") + + if tool_name == "analyze_table_relationships" and tool_result.get("status") == "success": + eda_info["relationship_analysis"] = tool_result.get("relationship_analysis") + + if tool_name == "generate_eda_summary" and tool_result.get("status") == "success": + eda_info["summary"] = tool_result.get("summary") + + if eda_info: + base_result["eda_info"] = eda_info + + base_result["current_phase"] = PipelinePhase.DATASET_BUILDING.value + + return base_result diff --git a/plexe/langgraph/agents/gnn_specialist.py b/plexe/langgraph/agents/gnn_specialist.py new file mode 100644 index 00000000..10e6f37f --- /dev/null +++ b/plexe/langgraph/agents/gnn_specialist.py @@ -0,0 +1,193 @@ +""" +Relational GNN Specialist Agent. + +This agent generates and executes GNN training scripts using +the plexe.relbench.modeling modules. +""" + +import logging +from typing import Optional, List, Dict, Any + +from langchain_core.tools import BaseTool + +from plexe.langgraph.agents.base import BaseAgent +from plexe.langgraph.config import AgentConfig +from plexe.langgraph.state import PipelineState, PipelinePhase +from plexe.langgraph.tools.common import save_artifact +from plexe.langgraph.tools.gnn_specialist import generate_training_script, execute_training_script + +logger = logging.getLogger(__name__) + + +GNN_SPECIALIST_SYSTEM_PROMPT = """You are the Relational GNN Specialist Agent, an expert in Graph Neural Networks for Relational Deep Learning. + +## Your Mission +Generate and execute GNN training scripts using the plexe.relbench.modeling modules to train on relational data. + +## Prerequisites +Before starting, you need: +1. dataset.py - Generated by DatasetBuilder (defines GenDataset class) +2. task.py - Generated by TaskBuilder (defines GenTask class) + +## Workflow + +### Step 1: Verify Prerequisites +Confirm that dataset.py and task.py exist in the working directory. + +### Step 2: Generate Training Script +Use generate_training_script with appropriate parameters: +- dataset_module_path: Path to dataset.py +- dataset_class_name: "GenDataset" +- task_module_path: Path to task.py +- task_class_name: "GenTask" +- task_type: From task_info (regression, binary_classification, multiclass_classification) +- tune_metric: Appropriate metric for the task type +- Training hyperparameters + +### Step 3: Execute Training +Use execute_training_script to run the generated script. + +### Step 4: Report Results +Report the training metrics and model performance. + +## Training Script Components +The generated script uses these plexe.relbench.modeling modules: + +### Graph Construction +- `make_pkey_fkey_graph`: Converts Database to HeteroData graph +- `get_node_train_table_input`: Prepares training input for NeighborLoader + +### Neural Network Modules +- `HeteroEncoder`: Encodes tabular features to embeddings +- `HeteroTemporalEncoder`: Encodes temporal information +- `HeteroGraphSAGE`: GNN message passing layers + +### Training Pipeline +1. Load Dataset and Task classes +2. Build heterogeneous graph from database +3. Create temporal neighbor loaders for train/val/test +4. Train GNN model with proper temporal sampling +5. Evaluate and save best model + +## Hyperparameter Guidelines +- epochs: 10-20 for initial training +- batch_size: 512 (adjust based on memory) +- learning_rate: 0.001-0.01 +- hidden_channels: 64-256 +- num_gnn_layers: 2-3 + +## Metrics by Task Type +- Regression: mae, rmse (lower is better) +- Binary Classification: accuracy, auroc, f1 (higher is better) +- Multiclass Classification: accuracy, f1_macro (higher is better) + +## Important +- Use generate_training_script tool - do NOT write training code manually +- The tool creates train_script.py automatically +- Execute only after successful generation +- Report both validation and test metrics +""" + + +class RelationalGNNSpecialistAgent(BaseAgent): + """Agent for GNN training script generation and execution.""" + + def __init__( + self, + config: Optional[AgentConfig] = None, + additional_tools: Optional[List[BaseTool]] = None, + ): + """ + Initialize the GNN specialist agent. + + Args: + config: Agent configuration + additional_tools: Additional tools beyond defaults + """ + tools = [ + generate_training_script, + execute_training_script, + save_artifact, + ] + + if additional_tools: + tools.extend(additional_tools) + + super().__init__( + agent_type="gnn_specialist", + config=config, + tools=tools, + ) + + @property + def system_prompt(self) -> str: + return GNN_SPECIALIST_SYSTEM_PROMPT + + def _build_context(self, state: PipelineState) -> str: + """Build context with training-specific information.""" + context_parts = [] + + if state.get("working_dir"): + context_parts.append(f"Working directory: {state['working_dir']}") + + if state.get("csv_dir"): + context_parts.append(f"CSV directory: {state['csv_dir']}") + + if state.get("dataset_info"): + ds = state["dataset_info"] + context_parts.append(f"Dataset class: {ds.get('class_name', 'GenDataset')}") + context_parts.append(f"Dataset file: {ds.get('file_path', 'dataset.py')}") + + if state.get("task_info"): + task = state["task_info"] + context_parts.append(f"Task class: {task.get('class_name', 'GenTask')}") + context_parts.append(f"Task file: {task.get('file_path', 'task.py')}") + context_parts.append(f"Task type: {task.get('task_type', 'regression')}") + + task_type = state.get("task_info", {}).get("task_type", "regression") + if task_type == "regression": + metric_guidance = "Use tune_metric='mae' or 'rmse', higher_is_better=False" + else: + metric_guidance = "Use tune_metric='accuracy' or 'auroc', higher_is_better=True" + + task_instruction = f""" +Your task: +1. Verify dataset.py and task.py exist +2. Generate training script using generate_training_script + - {metric_guidance} + - Use epochs=10, batch_size=512 +3. Execute the training script using execute_training_script +4. Report the training results + +Use the exact file paths from the context above. +""" + context_parts.append(task_instruction) + + return "\n".join(context_parts) + + def _process_result(self, result: Dict[str, Any], state: PipelineState) -> Dict[str, Any]: + """Process result and extract training results.""" + base_result = super()._process_result(result, state) + + import os + import json + + working_dir = state.get("working_dir", "") + results_path = os.path.join(working_dir, "training_results.json") + + if os.path.exists(results_path): + try: + with open(results_path) as f: + training_results = json.load(f) + + base_result["training_result"] = { + "metrics": training_results, + "model_path": training_results.get("model_path"), + "script_path": os.path.join(working_dir, "train_script.py"), + } + except Exception as e: + logger.warning(f"Could not read training results: {e}") + + base_result["current_phase"] = PipelinePhase.OPERATION.value + + return base_result diff --git a/plexe/langgraph/agents/operation.py b/plexe/langgraph/agents/operation.py new file mode 100644 index 00000000..66fe8f88 --- /dev/null +++ b/plexe/langgraph/agents/operation.py @@ -0,0 +1,265 @@ +""" +Operation Agent. + +This agent handles environment setup, execution monitoring, +and final model packaging. +""" + +import logging +from typing import Optional, List, Dict, Any + +from langchain_core.tools import BaseTool + +from plexe.langgraph.agents.base import BaseAgent +from plexe.langgraph.config import AgentConfig +from plexe.langgraph.state import PipelineState, PipelinePhase +from plexe.langgraph.tools.common import save_artifact +from plexe.langgraph.tools.gnn_specialist import execute_training_script + +logger = logging.getLogger(__name__) + + +OPERATION_SYSTEM_PROMPT = """You are the Operation Agent, responsible for environment setup, execution monitoring, and model packaging. + +## Your Mission +1. Ensure the execution environment is properly configured +2. Monitor training execution and handle errors +3. Package the trained model for deployment +4. Generate inference code and documentation + +## Responsibilities + +### Environment Setup +- Verify required packages are installed +- Check GPU availability +- Ensure file paths are accessible +- Validate prerequisites + +### Execution Monitoring +- Monitor training progress +- Capture and report errors +- Handle timeouts appropriately +- Log resource usage + +### Model Packaging +- Save trained model artifacts +- Generate inference code +- Create model documentation +- Prepare deployment package + +### Error Handling +- Identify common failure patterns +- Suggest fixes for errors +- Retry with adjusted parameters +- Escalate unfixable issues + +## Available Actions +- Check environment requirements +- Execute training scripts with monitoring +- Save artifacts and logs +- Generate inference code + +## Output Requirements +After successful execution, provide: +1. Final model metrics +2. Model artifact locations +3. Any warnings or issues encountered +4. Recommendations for deployment + +## Important +- Always verify environment before execution +- Monitor for common PyTorch/GPU errors +- Save all artifacts to the working directory +- Provide clear error messages for failures +""" + + +class OperationAgent(BaseAgent): + """Agent for environment setup and execution monitoring.""" + + def __init__( + self, + config: Optional[AgentConfig] = None, + additional_tools: Optional[List[BaseTool]] = None, + ): + """ + Initialize the operation agent. + + Args: + config: Agent configuration + additional_tools: Additional tools beyond defaults + """ + tools = [ + execute_training_script, + save_artifact, + ] + + if additional_tools: + tools.extend(additional_tools) + + super().__init__( + agent_type="operation", + config=config, + tools=tools, + ) + + @property + def system_prompt(self) -> str: + return OPERATION_SYSTEM_PROMPT + + def _build_context(self, state: PipelineState) -> str: + """Build context with operation-specific information.""" + context_parts = [] + + if state.get("working_dir"): + context_parts.append(f"Working directory: {state['working_dir']}") + + if state.get("training_result"): + result = state["training_result"] + context_parts.append(f"Training metrics: {result.get('metrics')}") + context_parts.append(f"Model path: {result.get('model_path')}") + + if state.get("errors"): + context_parts.append(f"Previous errors: {state['errors']}") + + context_parts.append(""" +Your task: +1. Review the training results +2. Package the model and artifacts +3. Generate a summary report +4. Provide deployment recommendations +""") + + return "\n".join(context_parts) + + def _process_result(self, result: Dict[str, Any], state: PipelineState) -> Dict[str, Any]: + """Process result and finalize the pipeline.""" + base_result = super()._process_result(result, state) + + base_result["current_phase"] = PipelinePhase.COMPLETED.value + + return base_result + + def generate_inference_code(self, state: PipelineState) -> str: + """Generate inference code for the trained model.""" + working_dir = state.get("working_dir", ".") + task_type = state.get("task_info", {}).get("task_type", "regression") + + inference_code = f'''""" +Auto-generated inference code for the trained GNN model. +""" + +import torch +import sys +import os + +sys.path.insert(0, "{working_dir}") + +from dataset import GenDataset +from task import GenTask + +def load_model(model_path: str): + """Load the trained model.""" + from plexe.relbench.modeling.nn import HeteroEncoder, HeteroTemporalEncoder, HeteroGraphSAGE + from plexe.relbench.modeling.graph import make_pkey_fkey_graph + from plexe.relbench.modeling.utils import get_stype_proposal + + # Initialize dataset and task + csv_dir = "{working_dir}/csv_files" + dataset = GenDataset(csv_dir=csv_dir) + task = GenTask(dataset) + db = dataset.get_db() + + # Build graph + col_to_stype_dict = get_stype_proposal(db) + data, col_stats_dict = make_pkey_fkey_graph( + db, + col_to_stype_dict=col_to_stype_dict, + text_embedder_cfg=None, + cache_dir="{working_dir}/cache/", + ) + + # Recreate model architecture + class GNNModel(torch.nn.Module): + def __init__(self, data, col_stats_dict, hidden_channels=128, out_channels=1): + super().__init__() + self.encoder = HeteroEncoder( + channels=hidden_channels, + node_to_col_names={{ + node_type: list(col_stats_dict[node_type].keys()) + for node_type in data.node_types + if node_type in col_stats_dict + }}, + node_to_col_stats=col_stats_dict, + ) + self.temporal_encoder = HeteroTemporalEncoder( + node_types=data.node_types, + channels=hidden_channels, + ) + self.gnn = HeteroGraphSAGE( + node_types=data.node_types, + edge_types=data.edge_types, + channels=hidden_channels, + num_layers=2, + ) + self.head = torch.nn.Sequential( + torch.nn.Linear(hidden_channels, hidden_channels), + torch.nn.ReLU(), + torch.nn.Dropout(0.2), + torch.nn.Linear(hidden_channels, out_channels), + ) + + def forward(self, batch, entity_table): + x_dict = self.encoder(batch.tf_dict) + rel_time_dict = self.temporal_encoder( + batch.seed_time, batch.time_dict, batch.batch_dict + ) + for node_type in x_dict: + x_dict[node_type] = x_dict[node_type] + rel_time_dict[node_type] + x_dict = self.gnn(x_dict, batch.edge_index_dict) + return self.head(x_dict[entity_table]) + + model = GNNModel(data, col_stats_dict) + model.load_state_dict(torch.load(model_path)) + model.eval() + + return model, data, task + + +def predict(model, data, task, entities, timestamp): + """ + Make predictions for given entities at a specific timestamp. + + Args: + model: Trained GNN model + data: HeteroData graph + task: Task definition + entities: List of entity IDs to predict for + timestamp: Prediction timestamp + + Returns: + Predictions for each entity + """ + from plexe.relbench.modeling.graph import get_node_train_table_input + from torch_geometric.loader import NeighborLoader + import pandas as pd + + # Create prediction table + pred_df = pd.DataFrame({{ + task.time_col: [pd.Timestamp(timestamp)] * len(entities), + task.entity_col: entities, + }}) + + # Create loader + # ... (implementation depends on specific use case) + + return predictions + + +if __name__ == "__main__": + model_path = "{working_dir}/best_model.pt" + model, data, task = load_model(model_path) + print("Model loaded successfully!") +''' + + return inference_code diff --git a/plexe/langgraph/agents/task_builder.py b/plexe/langgraph/agents/task_builder.py new file mode 100644 index 00000000..6361f5b0 --- /dev/null +++ b/plexe/langgraph/agents/task_builder.py @@ -0,0 +1,291 @@ +""" +Task Builder Agent. + +This agent builds RelBench Task objects for prediction tasks, +generating SQL queries and complete Python Task classes. +""" + +import logging +from typing import Optional, List, Dict, Any + +from langchain_core.tools import BaseTool + +from plexe.langgraph.agents.base import BaseAgent +from plexe.langgraph.config import AgentConfig +from plexe.langgraph.state import PipelineState, PipelinePhase +from plexe.langgraph.tools.common import save_artifact +from plexe.langgraph.tools.dataset_builder import get_csv_files_info +from plexe.langgraph.tools.task_builder import test_sql_query, register_task_code + +logger = logging.getLogger(__name__) + + +TASK_BUILDER_SYSTEM_PROMPT = """You are the Task Builder Agent, an expert in defining prediction tasks for relational databases. + +## Your Mission +Create a Python Task class (GenTask) that defines: +1. The prediction target and entity +2. SQL queries to compute labels from historical data +3. Proper temporal windows for train/val/test splits +4. Evaluation metrics for the task + +## Workflow + +### Step 1: Understand the Prediction Task +Based on the user's intent, determine: +- Entity table (e.g., users, drivers, products) +- Target variable (e.g., churn, engagement, sales) +- Task type (e.g., regression, binary_classification, multiclass_classification) + +### Step 2: Design SQL Query +Create a SQL query that: +- Uses temporal windows to prevent data leakage +- Computes labels from future data relative to timestamp +- Filters to relevant entities + +### Step 3: Test the SQL Query +Use test_sql_query to validate your query works correctly. + +### Step 4: Generate Task Code +Create a complete GenTask class: + +```python +import pandas as pd +from plexe.relbench.base import EntityTask, RecommendationTask +from plexe.relbench.metrics import accuracy, mae, rmse, f1, auroc + +class GenTask(EntityTask): # or RecommendationTask + entity_table = "entity_table_name" + entity_col = "entity_id_column" + time_col = "timestamp" + target_col = "target" + task_type = "regression" # or binary_classification, multiclass_classification + timedelta = pd.Timedelta(days=30) + metrics = [mae, rmse] # appropriate metrics + + def make_table(self, db, timestamps): + # SQL query using DuckDB + query = ''' + SELECT + t.timestamp as {time_col}, + e.{entity_col}, + -- aggregation to compute target + FROM timestamp_df t + LEFT JOIN {entity_table} e ON ... + LEFT JOIN {activity_table} a ON ... + WHERE temporal_filter + GROUP BY t.timestamp, e.{entity_col} + ''' + + import duckdb + conn = duckdb.connect() + # Register tables from db + for table_name, table in db.table_dict.items(): + conn.register(table_name, table.df) + conn.register("timestamp_df", timestamps) + + df = conn.execute(query).fetchdf() + return df +``` + +### Step 5: Register the Code +Use register_task_code to save the generated code. + +## SQL Query Patterns + +### Binary Classification (Churn-style) +```sql +SELECT t.timestamp as timestamp, e.user_id, + CASE WHEN NOT EXISTS ( + SELECT 1 FROM activity a + WHERE a.user_id = e.user_id + AND a.time > t.timestamp + AND a.time <= t.timestamp + INTERVAL '{timedelta}' + ) THEN 1 ELSE 0 END as target +FROM timestamp_df t, users e +WHERE e.created_at <= t.timestamp +``` + +### Regression (Count-style) +```sql +SELECT t.timestamp, e.entity_id, + COUNT(a.id) as target +FROM timestamp_df t +CROSS JOIN entities e +LEFT JOIN activities a ON a.entity_id = e.id + AND a.time > t.timestamp + AND a.time <= t.timestamp + INTERVAL '{timedelta}' +WHERE e.created_at <= t.timestamp +GROUP BY t.timestamp, e.entity_id +``` + +### Classification (Threshold-style) +```sql +SELECT t.timestamp, e.entity_id, + CASE WHEN MIN(a.position) <= 3 THEN 1 ELSE 0 END as target +FROM timestamp_df t +LEFT JOIN results a ON a.entity_id = e.id + AND a.time > t.timestamp + AND a.time <= t.timestamp + INTERVAL '{timedelta}' +WHERE e.id IN (SELECT DISTINCT entity_id FROM results WHERE time > t.timestamp - INTERVAL '1 year') +GROUP BY t.timestamp, e.entity_id +``` + +## Available Metrics +- Regression: mae, rmse, r2 +- Binary Classification: accuracy, f1, auroc, average_precision +- Multiclass Classification: accuracy, f1_macro, f1_micro + +## Important +- Use class name 'GenTask' +- Always test SQL before finalizing +- Use exact column names from the database (snake_case) +- Ensure temporal windows prevent data leakage +- Save as 'task.py' in the working directory +""" + + +class TaskBuilderAgent(BaseAgent): + """Agent for building RelBench Task classes.""" + + def __init__( + self, + config: Optional[AgentConfig] = None, + additional_tools: Optional[List[BaseTool]] = None, + ): + """ + Initialize the task builder agent. + + Args: + config: Agent configuration + additional_tools: Additional tools beyond defaults + """ + tools = [ + get_csv_files_info, + test_sql_query, + register_task_code, + save_artifact, + ] + + if additional_tools: + tools.extend(additional_tools) + + super().__init__( + agent_type="task_builder", + config=config, + tools=tools, + ) + + @property + def system_prompt(self) -> str: + return TASK_BUILDER_SYSTEM_PROMPT + + def _build_context(self, state: PipelineState) -> str: + """Build context with task-specific information including EDA results.""" + context_parts = [] + + if state.get("working_dir"): + context_parts.append(f"Working directory: {state['working_dir']}") + + if state.get("csv_dir"): + context_parts.append(f"CSV files directory: {state['csv_dir']}") + + if state.get("user_intent"): + context_parts.append(f"User intent: {state['user_intent']}") + + if state.get("schema_info"): + schema = state["schema_info"] + tables = list(schema.get("tables", {}).keys()) + context_parts.append(f"Available tables: {', '.join(tables)}") + + for table_name, table_info in schema.get("tables", {}).items(): + pk = table_info.get("primary_key", []) + if pk: + context_parts.append(f" {table_name} PK: {pk}") + + if state.get("dataset_info"): + ds = state["dataset_info"] + context_parts.append(f"Dataset class: {ds.get('class_name')}") + if ds.get("val_timestamp"): + context_parts.append(f"Val timestamp: {ds.get('val_timestamp')}") + if ds.get("test_timestamp"): + context_parts.append(f"Test timestamp: {ds.get('test_timestamp')}") + + # Include EDA information for better task design + if state.get("eda_info"): + eda = state["eda_info"] + context_parts.append("\n## EDA Analysis Results:") + + if eda.get("statistics"): + context_parts.append("Table Statistics:") + for table, stats in eda["statistics"].items(): + if isinstance(stats, dict): + row_count = stats.get("row_count", "unknown") + context_parts.append(f" - {table}: {row_count} rows") + + if eda.get("temporal_analysis"): + context_parts.append("Temporal Analysis:") + for table, analysis in eda["temporal_analysis"].items(): + if analysis.get("time_columns"): + context_parts.append(f" - {table}: time columns = {analysis['time_columns']}") + if analysis.get("date_range"): + context_parts.append(f" Date range: {analysis['date_range']}") + + if eda.get("relationship_analysis"): + context_parts.append("Relationship Analysis:") + for key, info in eda["relationship_analysis"].items(): + if isinstance(info, dict): + if info.get("cardinality"): + context_parts.append(f" - {key}: {info['cardinality']}") + if info.get("join_quality"): + context_parts.append(f" Join quality: {info['join_quality']}") + + if eda.get("summary"): + context_parts.append(f"\nEDA Summary: {eda['summary']}") + + task_instruction = """ +Your task: +1. Analyze the schema and user intent +2. Use EDA insights to understand data patterns and relationships +3. Design a SQL query for label computation +4. Test the SQL query using test_sql_query +5. Generate a complete GenTask class +6. Register the code using register_task_code + +The output file should be saved as 'task.py' in the working directory. +""" + context_parts.append(task_instruction) + + return "\n".join(context_parts) + + def _process_result(self, result: Dict[str, Any], state: PipelineState) -> Dict[str, Any]: + """Process result and extract task information from tool calls.""" + base_result = super()._process_result(result, state) + + task_info = {} + generated_code = state.get("generated_code", {}) + + if "tool_calls" in result and result["tool_calls"]: + for tool_call in result["tool_calls"]: + tool_name = tool_call.get("name", "") + tool_result = tool_call.get("result", {}) + + if tool_name == "register_task_code" and tool_result.get("status") == "registered": + task_info["class_name"] = tool_result.get("class_name", "GenTask") + task_info["file_path"] = tool_result.get("file_path") + task_info["task_type"] = tool_result.get("task_type") + if "code" in tool_result: + generated_code["task"] = tool_result["code"] + + if not task_info: + task_info["class_name"] = "GenTask" + + if task_info: + base_result["task_info"] = task_info + + if generated_code: + base_result["generated_code"] = generated_code + + base_result["current_phase"] = PipelinePhase.GNN_TRAINING.value + + return base_result diff --git a/plexe/langgraph/config.py b/plexe/langgraph/config.py new file mode 100644 index 00000000..784e4843 --- /dev/null +++ b/plexe/langgraph/config.py @@ -0,0 +1,96 @@ +""" +Configuration for LangGraph-based agents. + +This module provides configuration management for agent models +using environment variables and defaults. +""" + +import os +from dataclasses import dataclass, field +from typing import Optional + + +@dataclass +class AgentConfig: + """Configuration for agent models from environment variables.""" + + orchestrator_model: str = field(default_factory=lambda: os.environ.get( + "PLEXE_ORCHESTRATOR_MODEL", "openai/gpt-4o" + )) + conversational_model: str = field(default_factory=lambda: os.environ.get( + "PLEXE_CONVERSATIONAL_MODEL", "openai/gpt-4o" + )) + eda_model: str = field(default_factory=lambda: os.environ.get( + "PLEXE_EDA_MODEL", "openai/gpt-4o" + )) + dataset_builder_model: str = field(default_factory=lambda: os.environ.get( + "PLEXE_DATASET_BUILDER_MODEL", "openai/gpt-4o" + )) + task_builder_model: str = field(default_factory=lambda: os.environ.get( + "PLEXE_TASK_BUILDER_MODEL", "openai/gpt-4o" + )) + gnn_specialist_model: str = field(default_factory=lambda: os.environ.get( + "PLEXE_GNN_SPECIALIST_MODEL", "openai/gpt-4o" + )) + operation_model: str = field(default_factory=lambda: os.environ.get( + "PLEXE_OPERATION_MODEL", "openai/gpt-4o" + )) + + temperature: float = field(default_factory=lambda: float(os.environ.get( + "PLEXE_AGENT_TEMPERATURE", "0.1" + ))) + max_retries: int = field(default_factory=lambda: int(os.environ.get( + "PLEXE_MAX_RETRIES", "3" + ))) + verbose: bool = field(default_factory=lambda: os.environ.get( + "PLEXE_VERBOSE", "false" + ).lower() == "true") + + @classmethod + def from_env(cls) -> "AgentConfig": + """Create configuration from environment variables.""" + return cls() + + def get_model_for_agent(self, agent_type: str) -> str: + """Get the model ID for a specific agent type.""" + mapping = { + "orchestrator": self.orchestrator_model, + "conversational": self.conversational_model, + "eda": self.eda_model, + "dataset_builder": self.dataset_builder_model, + "task_builder": self.task_builder_model, + "gnn_specialist": self.gnn_specialist_model, + "operation": self.operation_model, + } + return mapping.get(agent_type, self.orchestrator_model) + + +def get_llm_from_model_id(model_id: str, temperature: float = 0.1): + """ + Create a LangChain LLM instance from a model ID string. + + Supports formats: + - openai/gpt-4o -> OpenAI + - anthropic/claude-sonnet-4-20250514 -> Anthropic + - gemini/gemini-2.5-flash -> Google Gemini + """ + from langchain_core.language_models import BaseChatModel + + if model_id.startswith("openai/"): + from langchain_openai import ChatOpenAI + model_name = model_id.replace("openai/", "") + return ChatOpenAI(model=model_name, temperature=temperature) + + elif model_id.startswith("anthropic/"): + from langchain_anthropic import ChatAnthropic + model_name = model_id.replace("anthropic/", "") + return ChatAnthropic(model=model_name, temperature=temperature) + + elif model_id.startswith("gemini/"): + from langchain_google_genai import ChatGoogleGenerativeAI + model_name = model_id.replace("gemini/", "") + return ChatGoogleGenerativeAI(model=model_name, temperature=temperature) + + else: + from langchain_openai import ChatOpenAI + return ChatOpenAI(model=model_id, temperature=temperature) diff --git a/plexe/langgraph/orchestrator.py b/plexe/langgraph/orchestrator.py new file mode 100644 index 00000000..edb2b718 --- /dev/null +++ b/plexe/langgraph/orchestrator.py @@ -0,0 +1,391 @@ +""" +Plexe Orchestrator using LangGraph. + +This module provides the main orchestrator that coordinates +all agents in the ML pipeline using LangGraph's StateGraph. +""" + +import logging +import os +from datetime import datetime +from typing import Optional, Dict, Any, Callable, Literal + +from langgraph.graph import StateGraph, END +from langgraph.checkpoint.memory import MemorySaver + +from plexe.langgraph.state import ( + PipelineState, + PipelinePhase, + create_initial_state, +) +from plexe.langgraph.config import AgentConfig +from plexe.langgraph.agents import ( + ConversationalAgent, + EDAAgent, + DatasetBuilderAgent, + TaskBuilderAgent, + RelationalGNNSpecialistAgent, + OperationAgent, +) + +logger = logging.getLogger(__name__) + + +class PlexeOrchestrator: + """ + Main orchestrator for the Plexe ML pipeline using LangGraph. + + This orchestrator manages the workflow between specialized agents: + 1. ConversationalAgent - User interaction and requirements gathering + 2. RelationalGraphArchitectAgent - Schema analysis and data export + 3. DatasetBuilderAgent - Dataset class generation + 4. TaskBuilderAgent - Task class and SQL generation + 5. RelationalGNNSpecialistAgent - GNN training + 6. OperationAgent - Environment and execution management + """ + + def __init__( + self, + config: Optional[AgentConfig] = None, + verbose: bool = False, + callback: Optional[Callable] = None, + ): + """ + Initialize the orchestrator. + + Args: + config: Agent configuration (uses defaults if None) + verbose: Enable verbose logging + callback: Optional callback for progress updates + """ + self.config = config or AgentConfig.from_env() + self.verbose = verbose + self.callback = callback + + self._init_agents() + self._build_graph() + + def _init_agents(self): + """Initialize all agents.""" + self.conversational_agent = ConversationalAgent(config=self.config) + self.eda_agent = EDAAgent(config=self.config) + self.dataset_builder_agent = DatasetBuilderAgent(config=self.config) + self.task_builder_agent = TaskBuilderAgent(config=self.config) + self.gnn_specialist_agent = RelationalGNNSpecialistAgent(config=self.config) + self.operation_agent = OperationAgent(config=self.config) + + def _build_graph(self): + """Build the LangGraph workflow.""" + workflow = StateGraph(PipelineState) + + workflow.add_node("conversation", self._conversation_node) + workflow.add_node("schema_analysis", self._schema_analysis_node) + workflow.add_node("dataset_building", self._dataset_building_node) + workflow.add_node("task_building", self._task_building_node) + workflow.add_node("gnn_training", self._gnn_training_node) + workflow.add_node("operation", self._operation_node) + workflow.add_node("error_handler", self._error_handler_node) + + workflow.set_entry_point("conversation") + + workflow.add_conditional_edges( + "conversation", + self._route_from_conversation, + { + "continue": "conversation", + "proceed": "schema_analysis", + "end": END, + } + ) + + workflow.add_conditional_edges( + "schema_analysis", + self._route_from_schema, + { + "success": "dataset_building", + "error": "error_handler", + } + ) + + workflow.add_conditional_edges( + "dataset_building", + self._route_from_dataset, + { + "success": "task_building", + "error": "error_handler", + } + ) + + workflow.add_conditional_edges( + "task_building", + self._route_from_task, + { + "success": "gnn_training", + "error": "error_handler", + } + ) + + workflow.add_conditional_edges( + "gnn_training", + self._route_from_training, + { + "success": "operation", + "error": "error_handler", + } + ) + + workflow.add_edge("operation", END) + + workflow.add_conditional_edges( + "error_handler", + self._route_from_error, + { + "retry": "conversation", + "end": END, + } + ) + + self.checkpointer = MemorySaver() + self.graph = workflow.compile(checkpointer=self.checkpointer) + + def _conversation_node(self, state: PipelineState) -> Dict[str, Any]: + """Handle conversation with user.""" + self._log_phase("Conversation") + result = self.conversational_agent.invoke(state) + return result + + def _schema_analysis_node(self, state: PipelineState) -> Dict[str, Any]: + """Handle schema analysis, data export, and EDA.""" + self._log_phase("Schema Analysis & EDA") + result = self.eda_agent.invoke(state) + return result + + def _dataset_building_node(self, state: PipelineState) -> Dict[str, Any]: + """Handle dataset class generation.""" + self._log_phase("Dataset Building") + result = self.dataset_builder_agent.invoke(state) + return result + + def _task_building_node(self, state: PipelineState) -> Dict[str, Any]: + """Handle task class generation.""" + self._log_phase("Task Building") + result = self.task_builder_agent.invoke(state) + return result + + def _gnn_training_node(self, state: PipelineState) -> Dict[str, Any]: + """Handle GNN training.""" + self._log_phase("GNN Training") + result = self.gnn_specialist_agent.invoke(state) + return result + + def _operation_node(self, state: PipelineState) -> Dict[str, Any]: + """Handle operation and finalization.""" + self._log_phase("Operation") + result = self.operation_agent.invoke(state) + result["current_phase"] = PipelinePhase.COMPLETED.value + return result + + def _error_handler_node(self, state: PipelineState) -> Dict[str, Any]: + """Handle errors and determine recovery strategy.""" + errors = state.get("errors", []) + logger.error(f"Pipeline error: {errors}") + + retry_count = state.get("metadata", {}).get("retry_count", 0) + max_retries = self.config.max_retries + + if retry_count < max_retries: + return { + "metadata": {**state.get("metadata", {}), "retry_count": retry_count + 1}, + "warnings": [f"Retrying after error (attempt {retry_count + 1}/{max_retries})"], + } + + return { + "current_phase": PipelinePhase.FAILED.value, + } + + def _route_from_conversation(self, state: PipelineState) -> Literal["continue", "proceed", "end"]: + """Route from conversation node.""" + if state.get("user_confirmation_required"): + if state.get("user_confirmed"): + return "proceed" + return "continue" + + if state.get("db_connection_string") or state.get("csv_dir"): + if state.get("user_intent"): + return "proceed" + + return "continue" + + def _route_from_schema(self, state: PipelineState) -> Literal["success", "error"]: + """Route from schema analysis node.""" + if state.get("errors"): + return "error" + if state.get("csv_dir") and state.get("schema_info"): + return "success" + return "error" + + def _route_from_dataset(self, state: PipelineState) -> Literal["success", "error"]: + """Route from dataset building node.""" + if state.get("errors"): + return "error" + if state.get("dataset_info"): + return "success" + return "error" + + def _route_from_task(self, state: PipelineState) -> Literal["success", "error"]: + """Route from task building node.""" + if state.get("errors"): + return "error" + if state.get("task_info"): + return "success" + return "error" + + def _route_from_training(self, state: PipelineState) -> Literal["success", "error"]: + """Route from training node.""" + if state.get("errors"): + return "error" + if state.get("training_result"): + return "success" + return "error" + + def _route_from_error(self, state: PipelineState) -> Literal["retry", "end"]: + """Route from error handler.""" + retry_count = state.get("metadata", {}).get("retry_count", 0) + if retry_count < self.config.max_retries: + return "retry" + return "end" + + def _log_phase(self, phase: str): + """Log phase transition.""" + if self.verbose: + logger.info(f"=== Phase: {phase} ===") + if self.callback: + self.callback({"phase": phase, "timestamp": datetime.now().isoformat()}) + + def run( + self, + user_message: str, + db_connection_string: Optional[str] = None, + csv_dir: Optional[str] = None, + working_dir: Optional[str] = None, + session_id: Optional[str] = None, + ) -> Dict[str, Any]: + """ + Run the ML pipeline. + + Args: + user_message: Initial user request + db_connection_string: Optional database connection + csv_dir: Optional directory with CSV files + working_dir: Working directory for artifacts + session_id: Session identifier + + Returns: + Final pipeline state + """ + if session_id is None: + session_id = f"session-{datetime.now().strftime('%Y%m%d-%H%M%S')}" + + if working_dir is None: + working_dir = os.path.join("workdir", session_id) + + os.makedirs(working_dir, exist_ok=True) + + initial_state = create_initial_state( + session_id=session_id, + working_dir=working_dir, + user_message=user_message, + db_connection_string=db_connection_string, + ) + + if csv_dir: + initial_state["csv_dir"] = csv_dir + + config = {"configurable": {"thread_id": session_id}} + + try: + final_state = self.graph.invoke(initial_state, config) + return { + "status": "completed" if final_state.get("current_phase") == PipelinePhase.COMPLETED.value else "failed", + "state": final_state, + "session_id": session_id, + "working_dir": working_dir, + } + except Exception as e: + logger.error(f"Pipeline execution failed: {e}") + return { + "status": "error", + "error": str(e), + "session_id": session_id, + "working_dir": working_dir, + } + + def chat( + self, + message: str, + session_id: str, + working_dir: Optional[str] = None, + ) -> Dict[str, Any]: + """ + Send a chat message to an ongoing session. + + Args: + message: User message + session_id: Existing session ID + working_dir: Working directory + + Returns: + Agent response + """ + config = {"configurable": {"thread_id": session_id}} + + try: + current_state = self.graph.get_state(config) + + if current_state and current_state.values: + state = dict(current_state.values) + state["messages"] = state.get("messages", []) + [{ + "role": "user", + "content": message, + "timestamp": datetime.now().isoformat(), + }] + + if state.get("user_confirmation_required"): + if any(word in message.lower() for word in ["yes", "proceed", "confirm", "ok"]): + state["user_confirmed"] = True + elif any(word in message.lower() for word in ["no", "stop", "cancel"]): + state["user_confirmed"] = False + state["current_phase"] = PipelinePhase.CONVERSATION.value + + result = self.graph.invoke(state, config) + return { + "status": "success", + "response": self._extract_response(result), + "phase": result.get("current_phase"), + } + else: + return self.run(message, working_dir=working_dir, session_id=session_id) + + except Exception as e: + logger.error(f"Chat error: {e}") + return { + "status": "error", + "error": str(e), + } + + def _extract_response(self, state: Dict[str, Any]) -> str: + """Extract the latest assistant response from state.""" + messages = state.get("messages", []) + for msg in reversed(messages): + if msg.get("role") == "assistant": + return msg.get("content", "") + return "" + + def get_session_state(self, session_id: str) -> Optional[Dict[str, Any]]: + """Get the current state of a session.""" + config = {"configurable": {"thread_id": session_id}} + try: + state = self.graph.get_state(config) + return dict(state.values) if state and state.values else None + except Exception: + return None diff --git a/plexe/langgraph/state.py b/plexe/langgraph/state.py new file mode 100644 index 00000000..264735b6 --- /dev/null +++ b/plexe/langgraph/state.py @@ -0,0 +1,169 @@ +""" +Pipeline state management for LangGraph workflow. + +This module defines the shared state that flows through the +multi-agent pipeline using TypedDict for LangGraph compatibility. +""" + +from typing import TypedDict, Optional, List, Dict, Any, Annotated +from enum import Enum +import operator + + +class PipelinePhase(str, Enum): + """Phases of the ML pipeline.""" + CONVERSATION = "conversation" + SCHEMA_ANALYSIS = "schema_analysis" + DATASET_BUILDING = "dataset_building" + TASK_BUILDING = "task_building" + GNN_TRAINING = "gnn_training" + OPERATION = "operation" + COMPLETED = "completed" + FAILED = "failed" + + +class MessageRole(str, Enum): + """Message roles in conversation.""" + USER = "user" + ASSISTANT = "assistant" + SYSTEM = "system" + + +class Message(TypedDict): + """A single message in the conversation.""" + role: str + content: str + timestamp: Optional[str] + + +class DatasetInfo(TypedDict, total=False): + """Information about the dataset.""" + name: str + file_path: str + class_name: str + val_timestamp: str + test_timestamp: str + tables: List[str] + csv_dir: str + + +class TaskInfo(TypedDict, total=False): + """Information about the prediction task.""" + name: str + file_path: str + class_name: str + task_type: str + entity_table: str + target_column: str + metrics: List[str] + + +class SchemaInfo(TypedDict, total=False): + """Database schema information.""" + tables: Dict[str, Any] + relationships: List[Dict[str, str]] + temporal_columns: Dict[str, str] + primary_keys: Dict[str, str] + foreign_keys: Dict[str, List[Dict[str, str]]] + + +class EDAInfo(TypedDict, total=False): + """Exploratory Data Analysis information.""" + statistics: Dict[str, Any] + quality_issues: Dict[str, Any] + temporal_analysis: Dict[str, Any] + relationship_analysis: Dict[str, Any] + summary: Dict[str, Any] + + +class TrainingResult(TypedDict, total=False): + """Results from GNN training.""" + metrics: Dict[str, float] + best_epoch: int + model_path: str + training_time: float + script_path: str + + +class PipelineState(TypedDict, total=False): + """ + Shared state for the LangGraph pipeline. + + This state is passed between agents and accumulates information + as the pipeline progresses through different phases. + """ + session_id: str + working_dir: str + current_phase: str + + messages: Annotated[List[Message], operator.add] + user_intent: str + + db_connection_string: Optional[str] + csv_dir: Optional[str] + + schema_info: Optional[SchemaInfo] + eda_info: Optional[EDAInfo] + dataset_info: Optional[DatasetInfo] + task_info: Optional[TaskInfo] + training_result: Optional[TrainingResult] + + generated_code: Dict[str, str] + artifacts: List[str] + + errors: Annotated[List[str], operator.add] + warnings: Annotated[List[str], operator.add] + + user_confirmation_required: bool + user_confirmation_context: Optional[Dict[str, Any]] + user_confirmed: Optional[bool] + + metadata: Dict[str, Any] + + +def create_initial_state( + session_id: str, + working_dir: str, + user_message: str, + db_connection_string: Optional[str] = None, +) -> PipelineState: + """ + Create the initial pipeline state. + + Args: + session_id: Unique identifier for this session + working_dir: Working directory for artifacts + user_message: Initial user message/request + db_connection_string: Optional database connection string + + Returns: + Initial pipeline state + """ + from datetime import datetime + + return PipelineState( + session_id=session_id, + working_dir=working_dir, + current_phase=PipelinePhase.CONVERSATION.value, + messages=[{ + "role": MessageRole.USER.value, + "content": user_message, + "timestamp": datetime.now().isoformat(), + }], + user_intent="", + db_connection_string=db_connection_string, + csv_dir=None, + schema_info=None, + eda_info=None, + dataset_info=None, + task_info=None, + training_result=None, + generated_code={}, + artifacts=[], + errors=[], + warnings=[], + user_confirmation_required=False, + user_confirmation_context=None, + user_confirmed=None, + metadata={}, + ) diff --git a/plexe/langgraph/tools/__init__.py b/plexe/langgraph/tools/__init__.py new file mode 100644 index 00000000..3b5c0230 --- /dev/null +++ b/plexe/langgraph/tools/__init__.py @@ -0,0 +1,59 @@ +""" +Tool definitions for LangGraph agents. + +This module provides tools organized by agent categories. +""" + +from plexe.langgraph.tools.common import save_artifact + +from plexe.langgraph.tools.conversational import get_dataset_preview + +from plexe.langgraph.tools.graph_architect import ( + validate_db_connection, + export_tables_to_csv, + extract_schema_metadata, +) + +from plexe.langgraph.tools.eda import ( + analyze_csv_statistics, + detect_data_quality_issues, + analyze_temporal_patterns, + analyze_table_relationships, + generate_eda_summary, +) + +from plexe.langgraph.tools.dataset_builder import ( + get_csv_files_info, + get_temporal_statistics, + register_dataset_code, +) + +from plexe.langgraph.tools.task_builder import ( + test_sql_query, + register_task_code, +) + +from plexe.langgraph.tools.gnn_specialist import ( + generate_training_script, + execute_training_script, +) + +__all__ = [ + "save_artifact", + "get_dataset_preview", + "validate_db_connection", + "export_tables_to_csv", + "extract_schema_metadata", + "analyze_csv_statistics", + "detect_data_quality_issues", + "analyze_temporal_patterns", + "analyze_table_relationships", + "generate_eda_summary", + "get_csv_files_info", + "get_temporal_statistics", + "register_dataset_code", + "test_sql_query", + "register_task_code", + "generate_training_script", + "execute_training_script", +] diff --git a/plexe/langgraph/tools/common.py b/plexe/langgraph/tools/common.py new file mode 100644 index 00000000..c59e8561 --- /dev/null +++ b/plexe/langgraph/tools/common.py @@ -0,0 +1,37 @@ +""" +Common tools shared across multiple agents. +""" + +from typing import Dict +from langchain_core.tools import tool as langchain_tool + + +@langchain_tool +def save_artifact( + content: str, + filename: str, + working_dir: str +) -> Dict[str, str]: + """ + Save an artifact file to the working directory. + + Args: + content: Content to save + filename: Name of the file + working_dir: Working directory + + Returns: + Save status and file path + """ + import os + + os.makedirs(working_dir, exist_ok=True) + file_path = os.path.join(working_dir, filename) + + with open(file_path, 'w') as f: + f.write(content) + + return { + "status": "saved", + "file_path": file_path + } diff --git a/plexe/langgraph/tools/conversational.py b/plexe/langgraph/tools/conversational.py new file mode 100644 index 00000000..36892fe6 --- /dev/null +++ b/plexe/langgraph/tools/conversational.py @@ -0,0 +1,60 @@ +""" +Tools for the Conversational Agent. +""" + +from typing import Dict, Any +from langchain_core.tools import tool as langchain_tool + + +@langchain_tool +def get_dataset_preview( + dataset_path: str, + num_rows: int = 5 +) -> Dict[str, Any]: + """ + Preview a dataset by showing the first few rows and schema information. + + Args: + dataset_path: Path to the CSV file or directory containing CSV files + num_rows: Number of rows to preview (default: 5) + + Returns: + Dictionary with schema info and sample data + """ + import pandas as pd + import os + + result = {"tables": {}, "total_tables": 0} + + if os.path.isdir(dataset_path): + csv_files = [f for f in os.listdir(dataset_path) if f.endswith('.csv')] + result["total_tables"] = len(csv_files) + + for csv_file in csv_files[:10]: + table_name = csv_file.replace('.csv', '') + file_path = os.path.join(dataset_path, csv_file) + try: + df = pd.read_csv(file_path, nrows=num_rows) + result["tables"][table_name] = { + "columns": list(df.columns), + "dtypes": {col: str(dtype) for col, dtype in df.dtypes.items()}, + "sample_data": df.to_dict(orient='records'), + "row_count": len(pd.read_csv(file_path)), + } + except Exception as e: + result["tables"][table_name] = {"error": str(e)} + else: + try: + df = pd.read_csv(dataset_path, nrows=num_rows) + table_name = os.path.basename(dataset_path).replace('.csv', '') + result["tables"][table_name] = { + "columns": list(df.columns), + "dtypes": {col: str(dtype) for col, dtype in df.dtypes.items()}, + "sample_data": df.to_dict(orient='records'), + "row_count": len(pd.read_csv(dataset_path)), + } + result["total_tables"] = 1 + except Exception as e: + result["error"] = str(e) + + return result diff --git a/plexe/langgraph/tools/dataset_builder.py b/plexe/langgraph/tools/dataset_builder.py new file mode 100644 index 00000000..5352fa26 --- /dev/null +++ b/plexe/langgraph/tools/dataset_builder.py @@ -0,0 +1,135 @@ +""" +Tools for the Dataset Builder Agent. +""" + +from typing import Dict, Any +from langchain_core.tools import tool as langchain_tool + + +@langchain_tool +def get_csv_files_info(csv_dir: str) -> Dict[str, Any]: + """ + Get information about CSV files in a directory. + + Args: + csv_dir: Directory containing CSV files + + Returns: + Dictionary with file information + """ + import os + import pandas as pd + + files = [] + for f in os.listdir(csv_dir): + if f.endswith('.csv'): + file_path = os.path.join(csv_dir, f) + try: + df = pd.read_csv(file_path, nrows=1) + row_count = sum(1 for _ in open(file_path)) - 1 + files.append({ + "name": f.replace('.csv', ''), + "path": file_path, + "columns": list(df.columns), + "row_count": row_count + }) + except Exception as e: + files.append({"name": f, "error": str(e)}) + + return {"files": files, "count": len(files)} + + +@langchain_tool +def get_temporal_statistics(csv_dir: str) -> Dict[str, Any]: + """ + Analyze temporal columns in CSV files to determine val/test timestamps. + + Args: + csv_dir: Directory containing CSV files + + Returns: + Dictionary with temporal analysis and suggested timestamps + """ + import pandas as pd + import os + + temporal_stats = {} + all_timestamps = [] + + for f in os.listdir(csv_dir): + if not f.endswith('.csv'): + continue + + table_name = f.replace('.csv', '') + file_path = os.path.join(csv_dir, f) + + try: + df = pd.read_csv(file_path) + table_temporal = {} + + for col in df.columns: + try: + parsed = pd.to_datetime(df[col], errors='coerce') + valid_count = parsed.notna().sum() + if valid_count > len(df) * 0.5: + min_ts = parsed.min() + max_ts = parsed.max() + table_temporal[col] = { + "min": str(min_ts), + "max": str(max_ts), + "valid_count": int(valid_count) + } + all_timestamps.extend(parsed.dropna().tolist()) + except: + pass + + if table_temporal: + temporal_stats[table_name] = table_temporal + except Exception as e: + temporal_stats[table_name] = {"error": str(e)} + + suggested_splits = {} + if all_timestamps: + all_timestamps = sorted(all_timestamps) + n = len(all_timestamps) + suggested_splits = { + "val_timestamp": str(all_timestamps[int(n * 0.7)]), + "test_timestamp": str(all_timestamps[int(n * 0.85)]), + } + + return { + "temporal_stats": temporal_stats, + "suggested_splits": suggested_splits + } + + +@langchain_tool +def register_dataset_code( + code: str, + class_name: str, + file_path: str +) -> Dict[str, str]: + """ + Register generated Dataset class code. + + Args: + code: Python code for the Dataset class + class_name: Name of the Dataset class + file_path: Path where the code will be saved + + Returns: + Registration status + """ + import os + + os.makedirs(os.path.dirname(file_path), exist_ok=True) + + with open(file_path, 'w') as f: + f.write(code) + + return { + "status": "registered", + "class_name": class_name, + "file_path": file_path, + "code": code + } diff --git a/plexe/langgraph/tools/eda.py b/plexe/langgraph/tools/eda.py new file mode 100644 index 00000000..a0d71cd6 --- /dev/null +++ b/plexe/langgraph/tools/eda.py @@ -0,0 +1,442 @@ +""" +Tools for the EDA (Exploratory Data Analysis) Agent. +""" + +from typing import Dict, Any +from langchain_core.tools import tool as langchain_tool + + +@langchain_tool +def analyze_csv_statistics(csv_dir: str) -> Dict[str, Any]: + """ + Analyze statistical properties of CSV files. + + Args: + csv_dir: Directory containing CSV files + + Returns: + Dictionary with statistical analysis for each table + """ + import pandas as pd + import os + + stats = {} + + for f in os.listdir(csv_dir): + if not f.endswith('.csv'): + continue + + table_name = f.replace('.csv', '') + file_path = os.path.join(csv_dir, f) + + try: + df = pd.read_csv(file_path) + + table_stats = { + "row_count": len(df), + "column_count": len(df.columns), + "columns": {}, + "memory_usage_mb": df.memory_usage(deep=True).sum() / 1024 / 1024, + } + + for col in df.columns: + col_stats = { + "dtype": str(df[col].dtype), + "non_null_count": int(df[col].notna().sum()), + "null_count": int(df[col].isna().sum()), + "null_percentage": float(df[col].isna().sum() / len(df) * 100), + "unique_count": int(df[col].nunique()), + } + + if pd.api.types.is_numeric_dtype(df[col]): + col_stats["numeric_stats"] = { + "mean": float(df[col].mean()) if df[col].notna().any() else None, + "std": float(df[col].std()) if df[col].notna().any() else None, + "min": float(df[col].min()) if df[col].notna().any() else None, + "max": float(df[col].max()) if df[col].notna().any() else None, + "median": float(df[col].median()) if df[col].notna().any() else None, + "q25": float(df[col].quantile(0.25)) if df[col].notna().any() else None, + "q75": float(df[col].quantile(0.75)) if df[col].notna().any() else None, + } + + if pd.api.types.is_object_dtype(df[col]) or pd.api.types.is_string_dtype(df[col]): + top_values = df[col].value_counts().head(5) + col_stats["categorical_stats"] = { + "top_values": {str(k): int(v) for k, v in top_values.items()}, + "is_high_cardinality": df[col].nunique() > 0.5 * len(df), + } + + table_stats["columns"][col] = col_stats + + stats[table_name] = table_stats + + except Exception as e: + stats[table_name] = {"error": str(e)} + + return { + "status": "success", + "statistics": stats, + "total_tables": len(stats) + } + + +@langchain_tool +def detect_data_quality_issues(csv_dir: str) -> Dict[str, Any]: + """ + Detect data quality issues in CSV files. + + Args: + csv_dir: Directory containing CSV files + + Returns: + Dictionary with data quality issues for each table + """ + import pandas as pd + import os + + issues = {} + + for f in os.listdir(csv_dir): + if not f.endswith('.csv'): + continue + + table_name = f.replace('.csv', '') + file_path = os.path.join(csv_dir, f) + + try: + df = pd.read_csv(file_path) + table_issues = [] + + for col in df.columns: + null_pct = df[col].isna().sum() / len(df) * 100 + if null_pct > 50: + table_issues.append({ + "severity": "high", + "column": col, + "issue": "high_missing_rate", + "details": f"{null_pct:.1f}% missing values" + }) + elif null_pct > 20: + table_issues.append({ + "severity": "medium", + "column": col, + "issue": "moderate_missing_rate", + "details": f"{null_pct:.1f}% missing values" + }) + + if df[col].dtype == 'object': + if df[col].nunique() == len(df): + table_issues.append({ + "severity": "low", + "column": col, + "issue": "all_unique_values", + "details": "Every row has unique value (potential ID column)" + }) + + if df[col].nunique() == 1: + table_issues.append({ + "severity": "medium", + "column": col, + "issue": "constant_column", + "details": "All values are the same" + }) + + if pd.api.types.is_numeric_dtype(df[col]): + if (df[col] == 0).sum() / len(df) > 0.9: + table_issues.append({ + "severity": "low", + "column": col, + "issue": "mostly_zeros", + "details": f"{(df[col] == 0).sum() / len(df) * 100:.1f}% zeros" + }) + + duplicates = df.duplicated().sum() + if duplicates > 0: + table_issues.append({ + "severity": "medium", + "column": None, + "issue": "duplicate_rows", + "details": f"{duplicates} duplicate rows ({duplicates/len(df)*100:.1f}%)" + }) + + issues[table_name] = { + "issues": table_issues, + "issue_count": len(table_issues), + "has_critical_issues": any(i["severity"] == "high" for i in table_issues) + } + + except Exception as e: + issues[table_name] = {"error": str(e)} + + return { + "status": "success", + "quality_issues": issues, + "tables_with_issues": sum(1 for t in issues.values() if isinstance(t, dict) and t.get("issue_count", 0) > 0) + } + + +@langchain_tool +def analyze_temporal_patterns(csv_dir: str) -> Dict[str, Any]: + """ + Analyze temporal patterns in CSV files for time-series prediction tasks. + + Args: + csv_dir: Directory containing CSV files + + Returns: + Dictionary with temporal analysis + """ + import pandas as pd + import os + + temporal_analysis = {} + all_timestamps = [] + + for f in os.listdir(csv_dir): + if not f.endswith('.csv'): + continue + + table_name = f.replace('.csv', '') + file_path = os.path.join(csv_dir, f) + + try: + df = pd.read_csv(file_path) + table_temporal = {"temporal_columns": {}} + + for col in df.columns: + try: + parsed = pd.to_datetime(df[col], errors='coerce') + valid_count = parsed.notna().sum() + + if valid_count > len(df) * 0.5: + min_ts = parsed.min() + max_ts = parsed.max() + + time_range_days = (max_ts - min_ts).days if pd.notna(max_ts) and pd.notna(min_ts) else 0 + + parsed_clean = parsed.dropna().sort_values() + if len(parsed_clean) > 1: + time_diffs = parsed_clean.diff().dropna() + avg_gap_hours = time_diffs.mean().total_seconds() / 3600 if not time_diffs.empty else 0 + else: + avg_gap_hours = 0 + + table_temporal["temporal_columns"][col] = { + "min": str(min_ts), + "max": str(max_ts), + "valid_count": int(valid_count), + "time_range_days": float(time_range_days), + "avg_gap_hours": float(avg_gap_hours), + "is_sorted": bool((parsed == parsed.sort_values()).all()), + } + + all_timestamps.extend(parsed_clean.tolist()) + except: + pass + + if table_temporal["temporal_columns"]: + temporal_analysis[table_name] = table_temporal + + except Exception as e: + temporal_analysis[table_name] = {"error": str(e)} + + suggested_splits = {} + if all_timestamps: + all_timestamps = sorted(all_timestamps) + n = len(all_timestamps) + suggested_splits = { + "train_end": str(all_timestamps[int(n * 0.7)]), + "val_end": str(all_timestamps[int(n * 0.85)]), + "test_end": str(all_timestamps[-1]), + "total_timestamps": n, + } + + return { + "status": "success", + "temporal_analysis": temporal_analysis, + "suggested_splits": suggested_splits, + "has_temporal_data": len(temporal_analysis) > 0 + } + + +@langchain_tool +def analyze_table_relationships(csv_dir: str, schema_info: Dict[str, Any]) -> Dict[str, Any]: + """ + Analyze relationships between tables based on schema and data. + + Args: + csv_dir: Directory containing CSV files + schema_info: Schema metadata with relationships + + Returns: + Dictionary with relationship analysis + """ + import pandas as pd + import os + + relationship_analysis = { + "foreign_key_stats": {}, + "join_recommendations": [], + "dimension_fact_classification": {} + } + + table_sizes = {} + for f in os.listdir(csv_dir): + if f.endswith('.csv'): + table_name = f.replace('.csv', '') + file_path = os.path.join(csv_dir, f) + try: + df = pd.read_csv(file_path) + table_sizes[table_name] = len(df) + except: + table_sizes[table_name] = 0 + + relationships = schema_info.get("relationships", []) + for rel in relationships: + source_table = rel.get("source_table") + target_table = rel.get("target_table") + source_column = rel.get("source_column") + + if not all([source_table, target_table, source_column]): + continue + + try: + source_file = os.path.join(csv_dir, f"{source_table}.csv") + target_file = os.path.join(csv_dir, f"{target_table}.csv") + + if os.path.exists(source_file) and os.path.exists(target_file): + source_df = pd.read_csv(source_file, usecols=[source_column] if source_column in pd.read_csv(source_file, nrows=0).columns else None) + + if source_column in source_df.columns: + fk_stats = { + "source_table": source_table, + "target_table": target_table, + "column": source_column, + "null_count": int(source_df[source_column].isna().sum()), + "null_percentage": float(source_df[source_column].isna().sum() / len(source_df) * 100), + "unique_count": int(source_df[source_column].nunique()), + } + + relationship_analysis["foreign_key_stats"][f"{source_table}.{source_column}"] = fk_stats + except Exception as e: + pass + + for table_name, size in table_sizes.items(): + has_fks = any(rel.get("source_table") == table_name for rel in relationships) + is_referenced = any(rel.get("target_table") == table_name for rel in relationships) + + if has_fks and not is_referenced and size > 1000: + classification = "fact" + elif is_referenced and not has_fks: + classification = "dimension" + elif is_referenced and has_fks: + classification = "dimension_with_hierarchy" + else: + classification = "standalone" + + relationship_analysis["dimension_fact_classification"][table_name] = { + "classification": classification, + "row_count": size, + "has_foreign_keys": has_fks, + "is_referenced": is_referenced, + } + + return { + "status": "success", + "relationship_analysis": relationship_analysis + } + + +@langchain_tool +def generate_eda_summary( + statistics: Dict[str, Any], + quality_issues: Dict[str, Any], + temporal_analysis: Dict[str, Any], + relationship_analysis: Dict[str, Any] +) -> Dict[str, Any]: + """ + Generate comprehensive EDA summary report. + + Args: + statistics: Statistical analysis results + quality_issues: Data quality issues + temporal_analysis: Temporal pattern analysis + relationship_analysis: Table relationship analysis + + Returns: + Dictionary with comprehensive EDA summary + """ + summary = { + "overview": {}, + "key_findings": [], + "recommendations": [] + } + + stats = statistics.get("statistics", {}) + total_rows = sum(t.get("row_count", 0) for t in stats.values() if isinstance(t, dict)) + total_columns = sum(t.get("column_count", 0) for t in stats.values() if isinstance(t, dict)) + + summary["overview"] = { + "total_tables": len(stats), + "total_rows": total_rows, + "total_columns": total_columns, + "has_temporal_data": temporal_analysis.get("has_temporal_data", False), + "tables_with_quality_issues": quality_issues.get("tables_with_issues", 0), + } + + if temporal_analysis.get("has_temporal_data"): + summary["key_findings"].append({ + "category": "temporal", + "finding": "Dataset contains temporal data suitable for time-series prediction", + "details": f"Found {len(temporal_analysis.get('temporal_analysis', {}))} tables with temporal columns" + }) + + if temporal_analysis.get("suggested_splits"): + summary["recommendations"].append({ + "category": "modeling", + "recommendation": "Use temporal train/val/test splits", + "details": temporal_analysis["suggested_splits"] + }) + + quality_issues_data = quality_issues.get("quality_issues", {}) + high_severity_count = sum( + sum(1 for issue in t.get("issues", []) if issue.get("severity") == "high") + for t in quality_issues_data.values() if isinstance(t, dict) + ) + + if high_severity_count > 0: + summary["key_findings"].append({ + "category": "quality", + "finding": f"Found {high_severity_count} high-severity data quality issues", + "details": "Review tables with high missing rates before modeling" + }) + + summary["recommendations"].append({ + "category": "preprocessing", + "recommendation": "Handle missing values in Dataset class", + "details": "Consider imputation or dropping columns with >50% missing" + }) + + rel_analysis = relationship_analysis.get("relationship_analysis", {}) + dim_fact = rel_analysis.get("dimension_fact_classification", {}) + + fact_tables = [t for t, info in dim_fact.items() if info.get("classification") == "fact"] + dim_tables = [t for t, info in dim_fact.items() if info.get("classification") in ["dimension", "dimension_with_hierarchy"]] + + if fact_tables: + summary["key_findings"].append({ + "category": "schema", + "finding": f"Identified {len(fact_tables)} fact tables and {len(dim_tables)} dimension tables", + "details": {"fact_tables": fact_tables, "dimension_tables": dim_tables} + }) + + summary["recommendations"].append({ + "category": "modeling", + "recommendation": "Consider fact tables as entity tables for prediction tasks", + "details": f"Suggested entity tables: {', '.join(fact_tables)}" + }) + + return { + "status": "success", + "summary": summary + } diff --git a/plexe/langgraph/tools/gnn_specialist.py b/plexe/langgraph/tools/gnn_specialist.py new file mode 100644 index 00000000..95e6561e --- /dev/null +++ b/plexe/langgraph/tools/gnn_specialist.py @@ -0,0 +1,314 @@ +""" +Tools for the GNN Specialist Agent. +""" + +from typing import Dict, Any +from langchain_core.tools import tool as langchain_tool + + +@langchain_tool +def generate_training_script( + dataset_module_path: str, + dataset_class_name: str, + task_module_path: str, + task_class_name: str, + working_dir: str, + task_type: str = "regression", + tune_metric: str = "mae", + higher_is_better: bool = False, + out_channels: int = 1, + epochs: int = 10, + batch_size: int = 512, + learning_rate: float = 0.005, + hidden_channels: int = 128, + num_gnn_layers: int = 2, +) -> Dict[str, Any]: + """ + Generate a GNN training script using plexe.relbench.modeling modules. + + Args: + dataset_module_path: Path to the Dataset Python module + dataset_class_name: Name of the Dataset class + task_module_path: Path to the Task Python module + task_class_name: Name of the Task class + working_dir: Working directory for outputs + task_type: Type of task (regression, binary_classification, multiclass_classification) + tune_metric: Metric to optimize + higher_is_better: Whether higher metric values are better + out_channels: Output channels for the model + epochs: Number of training epochs + batch_size: Batch size for training + learning_rate: Learning rate + hidden_channels: Hidden channels in GNN + num_gnn_layers: Number of GNN layers + + Returns: + Path to generated script + """ + import os + + script_template = f'''""" +Auto-generated GNN training script using plexe.relbench.modeling. +""" + +import os +import sys +import torch +import torch.nn.functional as F +from torch.optim import Adam +from datetime import datetime + +sys.path.insert(0, "{os.path.dirname(dataset_module_path)}") +sys.path.insert(0, "{os.path.dirname(task_module_path)}") + +from dataset import {dataset_class_name} +from task import {task_class_name} + +from plexe.relbench.modeling.graph import make_pkey_fkey_graph, get_node_train_table_input +from plexe.relbench.modeling.nn import HeteroEncoder, HeteroTemporalEncoder, HeteroGraphSAGE +from plexe.relbench.modeling.utils import get_stype_proposal +from torch_geometric.loader import NeighborLoader + +device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') +print(f"Using device: {{device}}") + +csv_dir = "{working_dir}/csv_files" +dataset = {dataset_class_name}(csv_dir=csv_dir) +task = {task_class_name}(dataset) +db = dataset.get_db() + +train_table = task.get_table("train") +val_table = task.get_table("val") +test_table = task.get_table("test") + +print(f"Train samples: {{len(train_table)}}") +print(f"Val samples: {{len(val_table)}}") +print(f"Test samples: {{len(test_table)}}") + +col_to_stype_dict = get_stype_proposal(db) +data, col_stats_dict = make_pkey_fkey_graph( + db, + col_to_stype_dict=col_to_stype_dict, + text_embedder_cfg=None, + cache_dir="{working_dir}/cache/", +) + +data = data.to(device) +entity_table = task.entity_table + +def create_loader(table, shuffle=False): + table_input = get_node_train_table_input(table=table, task=task) + return NeighborLoader( + data, + num_neighbors=[128] * {num_gnn_layers}, + time_attr="time", + input_nodes=(entity_table, table_input.nodes[entity_table]), + input_time=table_input.time, + transform=table_input.transform, + batch_size={batch_size}, + temporal_strategy="uniform", + shuffle=shuffle, + ) + +train_loader = create_loader(train_table, shuffle=True) +val_loader = create_loader(val_table) +test_loader = create_loader(test_table) + +class GNNModel(torch.nn.Module): + def __init__(self, data, col_stats_dict, hidden_channels={hidden_channels}, out_channels={out_channels}): + super().__init__() + self.encoder = HeteroEncoder( + channels=hidden_channels, + node_to_col_names={{ + node_type: list(col_stats_dict[node_type].keys()) + for node_type in data.node_types + if node_type in col_stats_dict + }}, + node_to_col_stats=col_stats_dict, + ) + self.temporal_encoder = HeteroTemporalEncoder( + node_types=data.node_types, + channels=hidden_channels, + ) + self.gnn = HeteroGraphSAGE( + node_types=data.node_types, + edge_types=data.edge_types, + channels=hidden_channels, + num_layers={num_gnn_layers}, + ) + self.head = torch.nn.Sequential( + torch.nn.Linear(hidden_channels, hidden_channels), + torch.nn.ReLU(), + torch.nn.Dropout(0.2), + torch.nn.Linear(hidden_channels, out_channels), + ) + + def forward(self, batch, entity_table): + x_dict = self.encoder(batch.tf_dict) + rel_time_dict = self.temporal_encoder( + batch.seed_time, batch.time_dict, batch.batch_dict + ) + for node_type in x_dict: + x_dict[node_type] = x_dict[node_type] + rel_time_dict[node_type] + x_dict = self.gnn(x_dict, batch.edge_index_dict) + return self.head(x_dict[entity_table]) + +model = GNNModel(data, col_stats_dict).to(device) +optimizer = Adam(model.parameters(), lr={learning_rate}) + +task_type = "{task_type}" +if task_type == "binary_classification": + loss_fn = torch.nn.BCEWithLogitsLoss() +elif task_type == "multiclass_classification": + loss_fn = torch.nn.CrossEntropyLoss() +else: + loss_fn = torch.nn.MSELoss() + +best_val_metric = float('inf') if not {str(higher_is_better).lower()} else float('-inf') +best_model_path = "{working_dir}/best_model.pt" + +for epoch in range({epochs}): + model.train() + total_loss = 0 + for batch in train_loader: + batch = batch.to(device) + optimizer.zero_grad() + pred = model(batch, entity_table).squeeze() + y = batch[entity_table].y.float() + if task_type == "multiclass_classification": + y = y.long() + loss = loss_fn(pred, y) + loss.backward() + optimizer.step() + total_loss += loss.item() + + model.eval() + val_preds, val_labels = [], [] + with torch.no_grad(): + for batch in val_loader: + batch = batch.to(device) + pred = model(batch, entity_table).squeeze() + val_preds.append(pred.cpu()) + val_labels.append(batch[entity_table].y.cpu()) + + val_preds = torch.cat(val_preds) + val_labels = torch.cat(val_labels) + + if task_type == "regression": + val_metric = F.mse_loss(val_preds, val_labels.float()).sqrt().item() + elif task_type == "binary_classification": + val_metric = ((val_preds > 0).float() == val_labels.float()).float().mean().item() + else: + val_metric = (val_preds.argmax(dim=-1) == val_labels).float().mean().item() + + print(f"Epoch {{epoch+1}}/{epochs}: Loss={{total_loss:.4f}}, Val {tune_metric}={{val_metric:.4f}}") + + is_better = val_metric < best_val_metric if not {str(higher_is_better).lower()} else val_metric > best_val_metric + if is_better: + best_val_metric = val_metric + torch.save(model.state_dict(), best_model_path) + print(f" -> New best model saved!") + +model.load_state_dict(torch.load(best_model_path)) +model.eval() + +test_preds, test_labels = [], [] +with torch.no_grad(): + for batch in test_loader: + batch = batch.to(device) + pred = model(batch, entity_table).squeeze() + test_preds.append(pred.cpu()) + test_labels.append(batch[entity_table].y.cpu()) + +test_preds = torch.cat(test_preds) +test_labels = torch.cat(test_labels) + +if task_type == "regression": + test_metric = F.mse_loss(test_preds, test_labels.float()).sqrt().item() + print(f"\\nTest RMSE: {{test_metric:.4f}}") +elif task_type == "binary_classification": + test_metric = ((test_preds > 0).float() == test_labels.float()).float().mean().item() + print(f"\\nTest Accuracy: {{test_metric:.4f}}") +else: + test_metric = (test_preds.argmax(dim=-1) == test_labels).float().mean().item() + print(f"\\nTest Accuracy: {{test_metric:.4f}}") + +results = {{ + "best_val_{tune_metric}": best_val_metric, + "test_{tune_metric}": test_metric, + "model_path": best_model_path, + "epochs_trained": {epochs}, +}} + +import json +with open("{working_dir}/training_results.json", "w") as f: + json.dump(results, f, indent=2) + +print(f"\\nTraining complete! Results saved to {working_dir}/training_results.json") +''' + + script_path = os.path.join(working_dir, "train_script.py") + os.makedirs(working_dir, exist_ok=True) + + with open(script_path, 'w') as f: + f.write(script_template) + + return { + "status": "generated", + "script_path": script_path, + } + + +@langchain_tool +def execute_training_script( + script_path: str, + timeout: int = 3600 +) -> Dict[str, Any]: + """ + Execute a training script. + + Args: + script_path: Path to the training script + timeout: Maximum execution time in seconds + + Returns: + Execution results + """ + import subprocess + import os + import json + + try: + result = subprocess.run( + ["python", script_path], + cwd=os.path.dirname(script_path), + capture_output=True, + text=True, + timeout=timeout + ) + + working_dir = os.path.dirname(script_path) + results_path = os.path.join(working_dir, "training_results.json") + + training_results = {} + if os.path.exists(results_path): + with open(results_path) as f: + training_results = json.load(f) + + return { + "status": "success" if result.returncode == 0 else "failed", + "stdout": result.stdout, + "stderr": result.stderr, + "return_code": result.returncode, + "training_results": training_results + } + except subprocess.TimeoutExpired: + return { + "status": "timeout", + "error": f"Script execution exceeded {timeout} seconds" + } + except Exception as e: + return { + "status": "error", + "error": str(e) + } diff --git a/plexe/langgraph/tools/graph_architect.py b/plexe/langgraph/tools/graph_architect.py new file mode 100644 index 00000000..d069e1aa --- /dev/null +++ b/plexe/langgraph/tools/graph_architect.py @@ -0,0 +1,181 @@ +""" +Tools for the Graph Architect Agent. +""" + +from typing import Dict, Any, List, Optional +from langchain_core.tools import tool as langchain_tool + + +@langchain_tool +def validate_db_connection(connection_string: str) -> Dict[str, Any]: + """ + Validate a database connection and retrieve available tables. + + Args: + connection_string: Database connection string (e.g., postgresql://user:pass@host:port/db) + + Returns: + Dictionary with connection status and available tables + """ + from sqlalchemy import create_engine, inspect + + try: + engine = create_engine(connection_string) + with engine.connect() as conn: + inspector = inspect(engine) + tables = inspector.get_table_names() + + table_info = {} + for table in tables: + columns = inspector.get_columns(table) + pk_constraint = inspector.get_pk_constraint(table) + fk_constraints = inspector.get_foreign_keys(table) + + table_info[table] = { + "columns": [{"name": c["name"], "type": str(c["type"])} for c in columns], + "primary_key": pk_constraint.get("constrained_columns", []), + "foreign_keys": [ + { + "column": fk["constrained_columns"], + "references": f"{fk['referred_table']}.{fk['referred_columns']}" + } + for fk in fk_constraints + ] + } + + return { + "status": "connected", + "tables": table_info, + "table_count": len(tables) + } + except Exception as e: + return { + "status": "failed", + "error": str(e) + } + + +@langchain_tool +def export_tables_to_csv( + db_connection_string: str, + output_dir: str, + table_names: Optional[List[str]] = None +) -> Dict[str, Any]: + """ + Export database tables to CSV files. + + Args: + db_connection_string: Database connection string + output_dir: Directory to save CSV files + table_names: Optional list of specific tables to export (exports all if None) + + Returns: + Dictionary with export status and file paths + """ + import pandas as pd + from sqlalchemy import create_engine, inspect + import os + + os.makedirs(output_dir, exist_ok=True) + + try: + engine = create_engine(db_connection_string) + inspector = inspect(engine) + + if table_names is None: + table_names = inspector.get_table_names() + + exported = [] + errors = [] + + for table in table_names: + try: + df = pd.read_sql_table(table, engine) + file_path = os.path.join(output_dir, f"{table}.csv") + df.to_csv(file_path, index=False) + exported.append({ + "table": table, + "path": file_path, + "rows": len(df), + "columns": len(df.columns) + }) + except Exception as e: + errors.append({"table": table, "error": str(e)}) + + return { + "status": "success", + "output_dir": output_dir, + "exported_tables": exported, + "errors": errors if errors else None + } + except Exception as e: + return { + "status": "failed", + "error": str(e) + } + + +@langchain_tool +def extract_schema_metadata(db_connection_string: str) -> Dict[str, Any]: + """ + Extract comprehensive schema metadata from a database. + + Args: + db_connection_string: Database connection string + + Returns: + Dictionary with tables, relationships, and temporal columns + """ + from sqlalchemy import create_engine, inspect + import pandas as pd + + try: + engine = create_engine(db_connection_string) + inspector = inspect(engine) + + tables = {} + relationships = [] + temporal_columns = {} + + for table_name in inspector.get_table_names(): + columns = inspector.get_columns(table_name) + pk_constraint = inspector.get_pk_constraint(table_name) + fk_constraints = inspector.get_foreign_keys(table_name) + + table_cols = [] + for col in columns: + col_type = str(col["type"]).lower() + is_temporal = any(t in col_type for t in ['timestamp', 'date', 'time']) + + table_cols.append({ + "name": col["name"], + "type": str(col["type"]), + "nullable": col.get("nullable", True), + "is_temporal": is_temporal + }) + + if is_temporal: + if table_name not in temporal_columns: + temporal_columns[table_name] = [] + temporal_columns[table_name].append(col["name"]) + + tables[table_name] = { + "columns": table_cols, + "primary_key": pk_constraint.get("constrained_columns", []), + } + + for fk in fk_constraints: + relationships.append({ + "source_table": table_name, + "source_column": fk["constrained_columns"][0] if fk["constrained_columns"] else None, + "target_table": fk["referred_table"], + "target_column": fk["referred_columns"][0] if fk["referred_columns"] else None, + }) + + return { + "tables": tables, + "relationships": relationships, + "temporal_columns": temporal_columns + } + except Exception as e: + return {"error": str(e)} diff --git a/plexe/langgraph/tools/task_builder.py b/plexe/langgraph/tools/task_builder.py new file mode 100644 index 00000000..0b80ebc1 --- /dev/null +++ b/plexe/langgraph/tools/task_builder.py @@ -0,0 +1,83 @@ +""" +Tools for the Task Builder Agent. +""" + +from typing import Dict, Any +from langchain_core.tools import tool as langchain_tool + + +@langchain_tool +def test_sql_query( + csv_dir: str, + query: str +) -> Dict[str, Any]: + """ + Test a SQL query against CSV files using DuckDB. + + Args: + csv_dir: Directory containing CSV files + query: SQL query to test + + Returns: + Query results or error + """ + import duckdb + import os + + try: + conn = duckdb.connect(':memory:') + + for f in os.listdir(csv_dir): + if f.endswith('.csv'): + table_name = f.replace('.csv', '') + file_path = os.path.join(csv_dir, f) + conn.execute(f"CREATE TABLE {table_name} AS SELECT * FROM read_csv_auto('{file_path}')") + + result = conn.execute(query).fetchdf() + + return { + "status": "success", + "columns": list(result.columns), + "row_count": len(result), + "sample_data": result.head(10).to_dict(orient='records') + } + except Exception as e: + return { + "status": "error", + "error": str(e) + } + + +@langchain_tool +def register_task_code( + code: str, + class_name: str, + file_path: str, + task_type: str +) -> Dict[str, str]: + """ + Register generated Task class code. + + Args: + code: Python code for the Task class + class_name: Name of the Task class + file_path: Path where the code will be saved + task_type: Type of task (regression, binary_classification, multiclass_classification) + + Returns: + Registration status + """ + import os + + os.makedirs(os.path.dirname(file_path), exist_ok=True) + + with open(file_path, 'w') as f: + f.write(code) + + return { + "status": "registered", + "class_name": class_name, + "file_path": file_path, + "task_type": task_type, + "code": code + } diff --git a/plexe/langgraph/utils.py b/plexe/langgraph/utils.py new file mode 100644 index 00000000..e478535d --- /dev/null +++ b/plexe/langgraph/utils.py @@ -0,0 +1,145 @@ +""" +Utility functions for LangGraph agents. +""" + +import os +import logging +from typing import Dict, Any, Optional +from datetime import datetime + +logger = logging.getLogger(__name__) + + +def create_working_directory(base_dir: str = "workdir") -> str: + """ + Create a unique working directory for a session. + + Args: + base_dir: Base directory for workspaces + + Returns: + Path to the created working directory + """ + timestamp = datetime.now().strftime("%Y%m%d-%H%M%S") + session_dir = os.path.join(base_dir, f"session-{timestamp}") + os.makedirs(session_dir, exist_ok=True) + + subdirs = ["csv_files", "cache", "artifacts"] + for subdir in subdirs: + os.makedirs(os.path.join(session_dir, subdir), exist_ok=True) + + return session_dir + + +def validate_file_exists(file_path: str) -> bool: + """Check if a file exists.""" + return os.path.isfile(file_path) + + +def validate_directory_exists(dir_path: str) -> bool: + """Check if a directory exists.""" + return os.path.isdir(dir_path) + + +def get_csv_files_in_directory(dir_path: str) -> list: + """Get list of CSV files in a directory.""" + if not os.path.isdir(dir_path): + return [] + return [f for f in os.listdir(dir_path) if f.endswith('.csv')] + + +def read_file_content(file_path: str) -> Optional[str]: + """Read content from a file.""" + try: + with open(file_path, 'r') as f: + return f.read() + except Exception as e: + logger.error(f"Error reading file {file_path}: {e}") + return None + + +def write_file_content(file_path: str, content: str) -> bool: + """Write content to a file.""" + try: + os.makedirs(os.path.dirname(file_path), exist_ok=True) + with open(file_path, 'w') as f: + f.write(content) + return True + except Exception as e: + logger.error(f"Error writing file {file_path}: {e}") + return False + + +def format_error_message(error: Exception, context: str = "") -> str: + """Format an error message with context.""" + msg = f"Error: {type(error).__name__}: {str(error)}" + if context: + msg = f"{context}: {msg}" + return msg + + +def sanitize_sql_identifier(identifier: str) -> str: + """Sanitize a SQL identifier to prevent injection.""" + return ''.join(c for c in identifier if c.isalnum() or c == '_') + + +def format_table_info(tables: Dict[str, Any]) -> str: + """Format table information for display.""" + lines = [] + for table_name, info in tables.items(): + pk = info.get("primary_key", []) + cols = [c["name"] for c in info.get("columns", [])] + lines.append(f"- {table_name}") + if pk: + lines.append(f" PK: {', '.join(pk)}") + lines.append(f" Columns: {', '.join(cols[:5])}{'...' if len(cols) > 5 else ''}") + return "\n".join(lines) + + +def estimate_task_type(target_description: str) -> str: + """Estimate task type from description.""" + description_lower = target_description.lower() + + binary_indicators = ["churn", "fraud", "click", "convert", "buy", "will", "whether"] + regression_indicators = ["count", "amount", "price", "revenue", "quantity", "how many"] + multiclass_indicators = ["category", "class", "type", "segment", "which"] + + for indicator in binary_indicators: + if indicator in description_lower: + return "binary_classification" + + for indicator in regression_indicators: + if indicator in description_lower: + return "regression" + + for indicator in multiclass_indicators: + if indicator in description_lower: + return "multiclass_classification" + + return "regression" + + +def get_default_metrics(task_type: str) -> list: + """Get default metrics for a task type.""" + metrics_map = { + "regression": ["mae", "rmse", "r2"], + "binary_classification": ["accuracy", "auroc", "f1"], + "multiclass_classification": ["accuracy", "f1_macro", "f1_micro"], + } + return metrics_map.get(task_type, ["mae"]) + + +def validate_python_code(code: str) -> Dict[str, Any]: + """Validate Python code for syntax errors.""" + try: + compile(code, '', 'exec') + return {"valid": True, "errors": []} + except SyntaxError as e: + return { + "valid": False, + "errors": [{ + "line": e.lineno, + "offset": e.offset, + "message": e.msg, + }] + } diff --git a/plexe/model_builder.py b/plexe/model_builder.py deleted file mode 100644 index 379771dd..00000000 --- a/plexe/model_builder.py +++ /dev/null @@ -1,334 +0,0 @@ -""" -ModelBuilder for creating ML models through agentic workflows. - -This module provides the ModelBuilder class that handles the orchestration of -the multi-agent system to build machine learning models. -""" - -import os -import json -import logging -from datetime import datetime -from typing import Dict, List, Type, Optional - -import pandas as pd -from pydantic import BaseModel - -from plexe.config import prompt_templates -from plexe.datasets import DatasetGenerator -from plexe.callbacks import Callback, BuildStateInfo, ChainOfThoughtModelCallback, ModelCheckpointCallback -from plexe.internal.common.utils.chain_of_thought.emitters import ConsoleEmitter -from plexe.agents.agents import PlexeAgent -from plexe.internal.common.datasets.interface import TabularConvertible -from plexe.internal.common.datasets.adapter import DatasetAdapter -from plexe.internal.common.provider import ProviderConfig -from plexe.core.object_registry import ObjectRegistry -from plexe.internal.common.utils.pydantic_utils import map_to_basemodel, format_schema -from plexe.internal.common.utils.markdown_utils import format_eda_report_markdown -from plexe.core.state import ModelState -from plexe.tools.schemas import get_solution_schemas -from plexe.execution_context import get_chain_of_thought_callable - -logger = logging.getLogger(__name__) - - -class ModelBuilder: - """Factory for creating ML models through agentic workflows.""" - - def __init__( - self, - provider: str | ProviderConfig = "gemini/gemini-2.5-flash", - verbose: bool = False, - distributed: bool = False, - working_dir: Optional[str] = None, - ): - """ - Initialize the model builder. - - Args: - provider: LLM provider configuration - verbose: Whether to display detailed agent logs - distributed: Whether to use distributed training with Ray - working_dir: Optional custom working directory - """ - self.provider_config = ProviderConfig(default_provider=provider) if isinstance(provider, str) else provider - self.verbose = verbose - self.distributed = distributed - self.working_dir = working_dir or self._create_working_dir() - - @staticmethod - def _create_working_dir() -> str: - """Create unique working directory for this build.""" - run_id = f"run-{datetime.now().isoformat()}".replace(":", "-").replace(".", "-") - # Use a hidden directory to prevent file watchers from triggering reloads - working_dir = f"./.workdir/{run_id}/" - os.makedirs(working_dir, exist_ok=True) - return working_dir - - def build( - self, - intent: str, - datasets: List[pd.DataFrame | DatasetGenerator], - db_connection_string: Optional[str] = None, - input_schema: Type[BaseModel] | Dict[str, type] = None, - output_schema: Type[BaseModel] | Dict[str, type] = None, - timeout: int = None, - max_iterations: int = None, - run_timeout: int = 1800, - callbacks: List[Callback] = None, - enable_checkpointing: bool = False, - ): - """ - Build a complete ML model using the agentic workflow. - - Args: - intent: Natural language description of the model's purpose - datasets: Training datasets - db_connection_string: Optional database connection string for Relational Deep Learning - input_schema: Optional input schema (inferred if not provided) - output_schema: Optional output schema (inferred if not provided) - timeout: Maximum total time for building - max_iterations: Maximum number of iterations - run_timeout: Maximum time per training run - callbacks: Optional callbacks for monitoring - enable_checkpointing: Whether to enable checkpointing - - Returns: - Completed Model instance - """ - # Clear and use singleton object registry for this build - object_registry = ObjectRegistry() - object_registry.clear() - - if (datasets is None or len(datasets) == 0) and not db_connection_string: - print("No datasets or database connection provided") - raise ValueError("At least one dataset or a database connection must be provided for model building") - else: - if datasets: - print(f"Building model with {len(datasets)} dataset(s)") - if db_connection_string: - print(f"Building model with database connection: {db_connection_string}") - - # Validate parameters - if timeout is None and max_iterations is None: - raise ValueError("At least one of 'timeout' or 'max_iterations' must be set") - if run_timeout is not None and timeout is not None and run_timeout > timeout: - raise ValueError(f"Run timeout ({run_timeout}s) cannot exceed total timeout ({timeout}s)") - - # Process schemas - input_schema = map_to_basemodel("in", input_schema) if input_schema else None - output_schema = map_to_basemodel("out", output_schema) if output_schema else None - - object_registry.register(bool, "input_schema_is_locked", input_schema is not None, immutable=True) - object_registry.register(bool, "output_schema_is_locked", output_schema is not None, immutable=True) - - # Initialize callbacks - callbacks = callbacks or [] - if enable_checkpointing and not any(isinstance(cb, ModelCheckpointCallback) for cb in callbacks): - callbacks.append(ModelCheckpointCallback()) - - # Check for context-provided chain of thought - context_cot_callable = get_chain_of_thought_callable() - - if context_cot_callable and hasattr(context_cot_callable, 'emitter'): - # Use the emitter from the context - cot_callback = ChainOfThoughtModelCallback(emitter=context_cot_callable.emitter) - callbacks.append(cot_callback) - cot_callable = context_cot_callable - else: - # Fallback to console emitter - cot_callback = ChainOfThoughtModelCallback(emitter=ConsoleEmitter()) - callbacks.append(cot_callback) - cot_callable = cot_callback.get_chain_of_thought_callable() - - # Register callbacks - object_registry.register_multiple(Callback, {f"{i}": c for i, c in enumerate(callbacks)}) - - try: - # Register working directory for tools to access - object_registry.register(str, "working_dir", self.working_dir, overwrite=True) - logger.info(f"Registered working directory: {self.working_dir}") - - # Register datasets - training_data = {} - if datasets: - training_data = { - f"dataset_{i}": DatasetAdapter.coerce((data.data if isinstance(data, DatasetGenerator) else data)) - for i, data in enumerate(datasets) - } - object_registry.register_multiple(TabularConvertible, training_data, immutable=True) - - # Register database connection string if provided (for RDL tasks) - if db_connection_string: - object_registry.register(str, "db_connection_string", db_connection_string, immutable=True) - logger.info(f"Registered database connection string for RDL pipeline") - - # Register schemas if provided - if input_schema: - object_registry.register(dict, "input_schema", format_schema(input_schema), immutable=True) - if output_schema: - object_registry.register(dict, "output_schema", format_schema(output_schema), immutable=True) - - # Generate unique model identifier - model_identifier = f"model-{datetime.now().isoformat()}".replace(":", "-").replace(".", "-") - - # Notify callbacks of build start - self._notify_callbacks( - callbacks, - "build_start", - intent, - input_schema, - output_schema, - training_data, - model_identifier=model_identifier, - model_state="BUILDING", - ) - - # Create and run agent - agent = PlexeAgent( - orchestrator_model_id=self.provider_config.orchestrator_provider, - ml_researcher_model_id=self.provider_config.research_provider, - ml_engineer_model_id=self.provider_config.engineer_provider, - ml_ops_engineer_model_id=self.provider_config.ops_provider, - tool_model_id=self.provider_config.tool_provider, - verbose=self.verbose, - max_steps=50, - distributed=self.distributed, - chain_of_thought_callable=cot_callable, - max_solutions=max_iterations, - ) - - agent_prompt = prompt_templates.agent_builder_prompt( - intent=intent, - input_schema=json.dumps(format_schema(input_schema), indent=4), - output_schema=json.dumps(format_schema(output_schema), indent=4), - datasets=list(training_data.keys()), - working_dir=self.working_dir, - max_iterations=max_iterations, - resume=False, - ) - - if db_connection_string: - agent_prompt += f"\n\nDatabase Connection String: {db_connection_string}\nUse this connection to extract schema and build graph." - - additional_args = { - "intent": intent, - "working_dir": self.working_dir, - "input_schema": format_schema(input_schema), - "output_schema": format_schema(output_schema), - "max_iterations": max_iterations, - "timeout": timeout, - "run_timeout": run_timeout, - "db_connection_string": db_connection_string, - } - - generated = agent.run(agent_prompt, additional_args=additional_args) - - # Extract final schemas (may have been inferred) - schemas = get_solution_schemas("best_performing_solution") - final_input_schema = map_to_basemodel("InputSchema", schemas["input"]) - final_output_schema = map_to_basemodel("OutputSchema", schemas["output"]) - - # Build metadata - metadata = { - "provider": str(self.provider_config.default_provider), - "orchestrator_provider": str(self.provider_config.orchestrator_provider), - "research_provider": str(self.provider_config.research_provider), - "engineer_provider": str(self.provider_config.engineer_provider), - "ops_provider": str(self.provider_config.ops_provider), - "tool_provider": str(self.provider_config.tool_provider), - } - metadata.update(generated.metadata) - - # Extract EDA reports - eda_reports = {} - eda_markdown_reports = {} - for name in training_data.keys(): - try: - eda_report = object_registry.get(dict, f"eda_report_{name}") - eda_reports[name] = eda_report - eda_markdown_reports[name] = format_eda_report_markdown(eda_report) - except KeyError: - logger.debug(f"No EDA report found for dataset '{name}'") - - metadata["eda_reports"] = eda_reports - metadata["eda_markdown_reports"] = eda_markdown_reports - - # Import here to avoid circular dependency - from plexe.models import Model - - # Create model and populate it with results - model = Model(intent=intent, input_schema=final_input_schema, output_schema=final_output_schema) - model.identifier = model_identifier - model.predictor = generated.predictor - model.trainer_source = generated.training_source_code - model.predictor_source = generated.inference_source_code - model.feature_transformer_source = generated.feature_transformer_source_code - model.dataset_splitter_source = generated.dataset_split_code - model.testing_source = generated.testing_source_code - model.artifacts = generated.model_artifacts - model.metric = generated.test_performance - model.evaluation_report = generated.evaluation_report - model.metadata.update(metadata) - model.training_data = training_data # Store actual training data - model.state = ModelState.READY - - # Notify callbacks of build end - self._notify_callbacks( - callbacks, - "build_end", - intent, - final_input_schema, - final_output_schema, - training_data, - model_identifier=model_identifier, - model_state="READY", - final_metric=generated.test_performance, - final_artifacts=generated.model_artifacts, - trainer_source=generated.training_source_code, - predictor_source=generated.inference_source_code, - ) - - return model - - except Exception as e: - logger.error(f"Error during model building: {str(e)}") - raise e - - def _notify_callbacks( - self, - callbacks, - event, - intent, - input_schema, - output_schema, - training_data, - model_identifier=None, - model_state=None, - final_metric=None, - final_artifacts=None, - trainer_source=None, - predictor_source=None, - ): - """Helper to notify callbacks with consistent error handling.""" - for callback in callbacks: - try: - method_name = f"on_{event}" - if hasattr(callback, method_name): - getattr(callback, method_name)( - BuildStateInfo( - intent=intent, - input_schema=input_schema, - output_schema=output_schema, - provider=self.provider_config.tool_provider, - datasets=training_data, - model_identifier=model_identifier, - model_state=model_state, - final_metric=final_metric, - final_artifacts=final_artifacts, - trainer_source=trainer_source, - predictor_source=predictor_source, - ) - ) - except Exception as e: - logger.warning(f"Error in callback {callback.__class__.__name__}.{method_name}: {str(e)[:50]}") diff --git a/plexe/models.py b/plexe/models.py deleted file mode 100644 index 464cdcfd..00000000 --- a/plexe/models.py +++ /dev/null @@ -1,336 +0,0 @@ -""" -This module defines the `Model` class, which represents a machine learning model. - -A `Model` is characterized by a natural language description of its intent, structured input and output schemas. -This class provides methods for building the model, making predictions, and inspecting its state, metadata, and metrics. - -Key Features: -- Intent: A natural language description of the model's purpose. -- Input/Output Schema: Defines the structure and types of inputs and outputs. -- Mutable State: Tracks the model's lifecycle, training metrics, and metadata. -- Build Process: Integrates solution generation with callbacks. -- Chain of Thought: Captures the reasoning steps of the model building process. - -Example: ->>> model = Model( ->>> intent="Given a dataset of house features, predict the house price.", ->>> output_schema=create_model("output", **{"price": float}), ->>> input_schema=create_model("input", **{ ->>> "bedrooms": int, ->>> "bathrooms": int, ->>> "square_footage": float ->>> }) ->>> ) ->>> ->>> model.build( ->>> datasets=[pd.read_csv("houses.csv")], ->>> provider="openai:gpt-4o-mini", ->>> max_iterations=10, ->>> chain_of_thought=True # Enable chain of thought logging ->>> ) ->>> ->>> prediction = model.predict({"bedrooms": 3, "bathrooms": 2, "square_footage": 1500.0}) ->>> print(prediction) -""" - -import logging -import os -import uuid -import warnings -from datetime import datetime -from typing import Dict, List, Type, Any -from deprecated import deprecated - -import pandas as pd -from pydantic import BaseModel - -from plexe.callbacks import Callback -from plexe.core.interfaces.predictor import Predictor -from plexe.core.object_registry import ObjectRegistry -from plexe.core.state import ModelState # Import from core package -from plexe.datasets import DatasetGenerator -from plexe.internal.common.datasets.interface import Dataset -from plexe.internal.common.provider import ProviderConfig -from plexe.internal.common.utils.model_utils import calculate_model_size, format_code_snippet -from plexe.internal.common.utils.pydantic_utils import map_to_basemodel, format_schema -from plexe.internal.models.entities.artifact import Artifact -from plexe.internal.models.entities.description import ( - ModelDescription, - SchemaInfo, - ImplementationInfo, - PerformanceInfo, - CodeInfo, -) -from plexe.internal.models.entities.metric import Metric - -logger = logging.getLogger(__name__) - - -class Model: - """ - Represents a model that transforms inputs to outputs according to a specified intent. - - A `Model` is defined by a human-readable description of its expected intent, as well as structured - definitions of its input schema and output schema. - - Attributes: - intent (str): A human-readable, natural language description of the model's expected intent. - output_schema (dict): A mapping of output key names to their types. - input_schema (dict): A mapping of input key names to their types. - - Example: - model = Model( - intent="Given a dataset of house features, predict the house price.", - output_schema=create_model("output_schema", **{"price": float}), - input_schema=create_model("input_schema", **{ - "bedrooms": int, - "bathrooms": int, - "square_footage": float, - }) - ) - """ - - def __init__( - self, - intent: str, - input_schema: Type[BaseModel] | Dict[str, type] = None, - output_schema: Type[BaseModel] | Dict[str, type] = None, - distributed: bool = False, - ): - """ - Initialise a model with a natural language description of its intent, as well as - structured definitions of its input schema and output schema. - - :param intent: A human-readable, natural language description of the model's expected intent. - :param input_schema: a pydantic model or dictionary defining the input schema - :param output_schema: a pydantic model or dictionary defining the output schema - :param distributed: Whether to use distributed training with Ray if available. - """ - # todo: analyse natural language inputs and raise errors where applicable - - # The model's identity is defined by these fields - self.intent: str = intent - self.input_schema: Type[BaseModel] = map_to_basemodel("in", input_schema) if input_schema else None - self.output_schema: Type[BaseModel] = map_to_basemodel("out", output_schema) if output_schema else None - self.training_data: Dict[str, Dataset] = dict() - self.distributed: bool = distributed - - # The model's mutable state is defined by these fields - self.state: ModelState = ModelState.DRAFT - self.predictor: Predictor | None = None - self.trainer_source: str | None = None - self.predictor_source: str | None = None - self.feature_transformer_source: str | None = None - self.dataset_splitter_source: str | None = None - self.testing_source: str | None = None - self.evaluation_report: Dict | None = None - self.artifacts: List[Artifact] = [] - self.metric: Metric | None = None - self.metadata: Dict[str, Any] = dict() # todo: initialise metadata, etc - - # Registries used to make datasets, artifacts and other objects available across the system - self.object_registry = ObjectRegistry() - - # Setup the working directory and unique identifiers - self.identifier: str = f"model-{abs(hash(self.intent))}-{str(uuid.uuid4())}" - self.run_id = f"run-{datetime.now().isoformat()}".replace(":", "-").replace(".", "-") - self.working_dir = f"./workdir/{self.run_id}/" - os.makedirs(self.working_dir, exist_ok=True) - - @deprecated(reason="Use ModelBuilder.build() instead", version="0.23.0") - def build( - self, - datasets: List[pd.DataFrame | DatasetGenerator], - provider: str | ProviderConfig = "gemini/gemini-2.5-flash", - timeout: int = None, - max_iterations: int = None, - run_timeout: int = 1800, - callbacks: List[Callback] = None, - verbose: bool = False, - # resume: bool = False, - enable_checkpointing: bool = False, - ) -> None: - """ - Build the model using the provided dataset and optional data generation configuration. - - DEPRECATED: This interface is deprecated. Use ModelBuilder.build() instead: - - from plexe import ModelBuilder - builder = ModelBuilder(provider=provider, verbose=verbose, distributed=distributed) - model = builder.build(intent=intent, datasets=datasets, ...) - - :param datasets: the datasets to use for training the model - :param provider: the provider to use for model building, either a string or a ProviderConfig - for granular control of which models to use for different agent roles - :param timeout: maximum total time in seconds to spend building the model (all iterations combined) - :param max_iterations: maximum number of iterations to spend building the model - :param run_timeout: maximum time in seconds for each individual model training run - :param callbacks: list of callbacks to notify during the model building process - :param verbose: whether to display detailed agent logs during model building (default: False) - :param enable_checkpointing: whether to enable automatic checkpointing (default: True) - :return: - """ - warnings.warn( - "Model.build() is deprecated. Use ModelBuilder.build() instead:\n\n" - " from plexe import ModelBuilder\n" - " builder = ModelBuilder(provider=provider, verbose=verbose, distributed=distributed)\n" - " model = builder.build(intent=intent, datasets=datasets, ...)\n", - DeprecationWarning, - stacklevel=2, - ) - - # Import here to avoid circular dependency - from plexe.model_builder import ModelBuilder - - # Create builder and delegate to it - builder = ModelBuilder( - provider=provider, - verbose=verbose, - distributed=self.distributed, - working_dir=self.working_dir, - ) - - # Build the model using ModelBuilder - built_model = builder.build( - intent=self.intent, - datasets=datasets, - input_schema=self.input_schema, - output_schema=self.output_schema, - timeout=timeout, - max_iterations=max_iterations, - run_timeout=run_timeout, - callbacks=callbacks, - enable_checkpointing=enable_checkpointing, - ) - - # Copy all results back to self to maintain backwards compatibility - for attr in [ - "identifier", - "input_schema", - "output_schema", - "predictor", - "trainer_source", - "predictor_source", - "feature_transformer_source", - "dataset_splitter_source", - "testing_source", - "evaluation_report", - "artifacts", - "metric", - "training_data", - ]: - setattr(self, attr, getattr(built_model, attr)) - - self.metadata.update(built_model.metadata) - self.state = ModelState.READY - - def predict(self, x: Dict[str, Any], validate_input: bool = False, validate_output: bool = False) -> Dict[str, Any]: - """ - Call the model with input x and return the output. - :param x: input to the model - :param validate_input: whether to validate the input against the input schema - :param validate_output: whether to validate the output against the output schema - :return: output of the model - """ - if self.state != ModelState.READY: - raise RuntimeError("The model is not ready for predictions.") - try: - if validate_input: - self.input_schema.model_validate(x) - y = self.predictor.predict(x) - if validate_output: - self.output_schema.model_validate(y) - return y - except Exception as e: - raise RuntimeError(f"Error during prediction: {str(e)}") from e - - def get_state(self) -> ModelState: - """ - Return the current state of the model. - :return: the current state of the model - """ - return self.state - - def get_metadata(self) -> dict: - """ - Return metadata about the model. - :return: metadata about the model - """ - return self.metadata - - def get_metrics(self) -> dict: - """ - Return metrics about the model. - :return: metrics about the model - """ - return None if self.metric is None else {self.metric.name: self.metric.value} - - def describe(self) -> ModelDescription: - """ - Return a structured description of the model. - - :return: A ModelDescription object with various methods like to_dict(), as_text(), - as_markdown(), to_json() for different output formats - """ - # Create schema info - schemas = SchemaInfo( - input=format_schema(self.input_schema), - output=format_schema(self.output_schema), - ) - - # Create implementation info - implementation = ImplementationInfo( - framework=self.metadata.get("framework", "Unknown"), - model_type=self.metadata.get("model_type", "Unknown"), - artifacts=[a.name for a in self.artifacts], - size=calculate_model_size(self.artifacts), - ) - - # Create performance info - # Convert Metric objects to string representation for JSON serialization - metrics_dict = {} - if hasattr(self.metric, "value") and hasattr(self.metric, "name"): # Check if it's a Metric object - metrics_dict[self.metric.name] = str(self.metric.value) - - performance = PerformanceInfo( - metrics=metrics_dict, - training_data_info={ - name: { - "modality": data.structure.modality, - "features": data.structure.features, - "structure": data.structure.details, - } - for name, data in self.training_data.items() - }, - ) - - # Create code info - code = CodeInfo( - training=format_code_snippet(self.trainer_source), - prediction=format_code_snippet(self.predictor_source), - feature_transformations=format_code_snippet(self.feature_transformer_source), - ) - - # Assemble and return the complete model description - return ModelDescription( - id=self.identifier, - state=self.state.value, - intent=self.intent, - schemas=schemas, - implementation=implementation, - performance=performance, - code=code, - training_date=self.metadata.get("creation_date", "Unknown"), - rationale=self.metadata.get("selection_rationale", "Unknown"), - provider=self.metadata.get("provider", "Unknown"), - task_type=self.metadata.get("task_type", "Unknown"), - domain=self.metadata.get("domain", "Unknown"), - behavior=self.metadata.get("behavior", "Unknown"), - preprocessing_summary=self.metadata.get("preprocessing_summary", "Unknown"), - architecture_summary=self.metadata.get("architecture_summary", "Unknown"), - training_procedure=self.metadata.get("training_procedure", "Unknown"), - evaluation_metric=self.metadata.get("evaluation_metric", "Unknown"), - inference_behavior=self.metadata.get("inference_behavior", "Unknown"), - strengths=self.metadata.get("strengths", "Unknown"), - limitations=self.metadata.get("limitations", "Unknown"), - ) diff --git a/plexe/server.py b/plexe/server.py index 3bfaafad..eb7a762c 100644 --- a/plexe/server.py +++ b/plexe/server.py @@ -1,59 +1,29 @@ """ -FastAPI server for the Plexe conversational agent. +FastAPI server for the Plexe LangGraph-based multi-agent system. -This module provides a lightweight WebSocket API for the conversational agent -and serves the assistant-ui frontend for local execution. +This module provides WebSocket API for real-time chat communication +and serves the frontend for the Plexe ML platform. """ import asyncio -import contextvars -import functools import json import logging import uuid from pathlib import Path +from typing import Dict, Any, Optional from fastapi import FastAPI, WebSocket, WebSocketDisconnect from fastapi.staticfiles import StaticFiles from fastapi.responses import FileResponse from fastapi.middleware.cors import CORSMiddleware -from plexe.agents.conversational import ConversationalAgent +from plexe.langgraph import PlexeOrchestrator, AgentConfig from plexe.api import datasets_router -from plexe.execution_context import set_chain_of_thought_callable, reset_chain_of_thought_callable -from plexe.internal.common.utils.chain_of_thought import ( - ChainOfThoughtCallable, - MultiEmitter, - ConsoleEmitter, - WebSocketEmitter, -) logger = logging.getLogger(__name__) +app = FastAPI(title="Plexe Assistant", version="2.0.0") -class WebSocketLogHandler(logging.Handler): - """ - Log handler that forwards log records to a WebSocketEmitter. - """ - def __init__(self, emitter: WebSocketEmitter): - super().__init__() - self.emitter = emitter - - def emit(self, record: logging.LogRecord) -> None: - try: - msg = self.format(record) - # Use the logger name as the agent name, or a simplified version - agent_name = record.name.split('.')[-1] if '.' in record.name else record.name - - # Emit as a thought - self.emitter.emit_thought(agent_name, msg) - except Exception: - self.handleError(record) - - -app = FastAPI(title="Plexe Assistant", version="1.0.0") - -# Add CORS middleware for frontend app.add_middleware( CORSMiddleware, allow_origins=["*"], @@ -62,25 +32,48 @@ def emit(self, record: logging.LogRecord) -> None: allow_headers=["*"], ) -# Include dataset API routes app.include_router(datasets_router) -# Serve static files from the ui directory ui_dir = Path(__file__).parent / "ui" -# Prefer a built frontend in `ui/frontend/dist` if present (Vite build output). frontend_dist = ui_dir / "frontend" / "dist" if frontend_dist.exists(): - # Serve built static assets from the frontend dist directory app.mount("/static", StaticFiles(directory=str(frontend_dist)), name="static") elif ui_dir.exists(): - # Fallback: serve legacy ui directory (contains index.html and inline JS) app.mount("/static", StaticFiles(directory=str(ui_dir)), name="static") +class SessionManager: + """Manages active chat sessions.""" + + def __init__(self): + self.sessions: Dict[str, Dict[str, Any]] = {} + + def create_session(self, session_id: str) -> PlexeOrchestrator: + """Create a new session with its own orchestrator.""" + config = AgentConfig.from_env() + orchestrator = PlexeOrchestrator(config=config, verbose=True) + self.sessions[session_id] = { + "orchestrator": orchestrator, + "working_dir": f"workdir/session-{session_id}", + } + return orchestrator + + def get_session(self, session_id: str) -> Optional[Dict[str, Any]]: + """Get an existing session.""" + return self.sessions.get(session_id) + + def remove_session(self, session_id: str): + """Remove a session.""" + if session_id in self.sessions: + del self.sessions[session_id] + + +session_manager = SessionManager() + + @app.get("/") async def root(): """Serve the main HTML page.""" - # Prefer serving the built frontend if available built_index = frontend_dist / "index.html" legacy_index = ui_dir / "index.html" @@ -89,7 +82,7 @@ async def root(): if legacy_index.exists(): return FileResponse(str(legacy_index)) return { - "error": "Frontend not found. Please ensure plexe/ui/frontend/dist/index.html or plexe/ui/index.html exists." + "error": "Frontend not found. Please ensure plexe/ui/frontend/dist/index.html exists." } @@ -100,56 +93,96 @@ async def websocket_endpoint(websocket: WebSocket): session_id = str(uuid.uuid4()) logger.info(f"New WebSocket connection: {session_id}") - # Get the current event loop to pass to the emitter loop = asyncio.get_running_loop() - - # Create emitters for chain of thought - ws_emitter = WebSocketEmitter(websocket, loop=loop) - console_emitter = ConsoleEmitter() - multi_emitter = MultiEmitter([ws_emitter, console_emitter]) + orchestrator = session_manager.create_session(session_id) + session_data = session_manager.get_session(session_id) + working_dir = session_data["working_dir"] - # Create chain of thought callable with the multi emitter - chain_of_thought = ChainOfThoughtCallable(emitter=multi_emitter) - - # Create a new agent instance for this session with chain of thought - # Enable verbose mode to capture detailed logs - agent = ConversationalAgent(chain_of_thought_callable=chain_of_thought, verbose=True) - - # Create and attach log handler to capture agent logs - log_handler = WebSocketLogHandler(ws_emitter) - # Capture logs from smolagents and plexe.agents - loggers_to_capture = ["smolagents", "plexe.agents"] - for logger_name in loggers_to_capture: - l = logging.getLogger(logger_name) - l.addHandler(log_handler) - # Ensure level is at least INFO to capture thoughts if not already set - if l.level == logging.NOTSET: - l.setLevel(logging.INFO) - - # Track if agent is currently running agent_task = None + is_closed = False + + async def send_message(msg_type: str, content: Any): + """Send a message to the client.""" + if not is_closed: + try: + await websocket.send_json({ + "type": msg_type, + "content": content, + "id": str(uuid.uuid4()), + "session_id": session_id, + }) + except Exception as e: + logger.warning(f"Failed to send message: {e}") - async def run_agent_task(user_message: str): - """Run agent in executor and handle response.""" + async def send_thought(agent_name: str, thought: str): + """Send a thought/progress update to the client.""" + await send_message("thought", { + "agent": agent_name, + "message": thought, + }) + + async def run_agent_task(user_message: str, db_connection: Optional[str] = None): + """Run the orchestrator in a separate thread.""" nonlocal agent_task - token = set_chain_of_thought_callable(chain_of_thought) + try: - ctx = contextvars.copy_context() - func = functools.partial(ctx.run, agent.agent.run, user_message, reset=False) - response = await loop.run_in_executor(None, func) - if not ws_emitter.is_closed: - await websocket.send_json({"role": "assistant", "content": response, "id": str(uuid.uuid4())}) - except RuntimeError as e: - if "stopped by user" in str(e).lower(): - logger.info("Agent execution stopped by user") + await send_thought("system", "Processing your request...") + + def run_sync(): + session = session_manager.get_session(session_id) + if not session: + return {"status": "error", "error": "Session not found"} + + orch = session["orchestrator"] + state = orch.get_session_state(session_id) + + if state: + return orch.chat( + message=user_message, + session_id=session_id, + working_dir=working_dir, + ) + else: + return orch.run( + user_message=user_message, + db_connection_string=db_connection, + working_dir=working_dir, + session_id=session_id, + ) + + result = await loop.run_in_executor(None, run_sync) + + response_text = "" + if result.get("status") == "success": + response_text = result.get("response", "Processing complete.") + elif result.get("status") == "completed": + state = result.get("state", {}) + messages = state.get("messages", []) + for msg in reversed(messages): + if msg.get("role") == "assistant": + response_text = msg.get("content", "") + break + if not response_text: + response_text = "Pipeline completed successfully." + elif result.get("status") == "error": + response_text = f"Error: {result.get('error', 'Unknown error')}" else: - raise + response_text = result.get("response", str(result)) + + if not is_closed: + await websocket.send_json({ + "role": "assistant", + "content": response_text, + "id": str(uuid.uuid4()), + "phase": result.get("phase", result.get("state", {}).get("current_phase")), + }) + except asyncio.CancelledError: logger.info("Agent task cancelled") raise except Exception as e: logger.error(f"Agent error: {e}") - if not ws_emitter.is_closed: + if not is_closed: await websocket.send_json({ "role": "assistant", "content": f"I encountered an error: {str(e)}. Please try again.", @@ -157,26 +190,21 @@ async def run_agent_task(user_message: str): "error": True, }) finally: - reset_chain_of_thought_callable(token) agent_task = None try: while True: - # Receive message from client data = await websocket.receive_text() try: message_data = json.loads(data) - # Handle ping messages for keep-alive if message_data.get("type") == "ping": await websocket.send_json({"type": "pong"}) continue - # Handle stop command if message_data.get("type") == "stop": logger.info("Stop command received") - ws_emitter.close() if agent_task: agent_task.cancel() try: @@ -186,27 +214,25 @@ async def run_agent_task(user_message: str): agent_task = None continue - # Handle confirmation response if message_data.get("type") == "confirmation_response": - request_id = message_data.get("id") confirmed = message_data.get("confirmed", False) - logger.info(f"Received confirmation response: {request_id} = {confirmed}") - ws_emitter.resolve_confirmation(request_id, confirmed) + logger.info(f"Received confirmation: {confirmed}") continue user_message = message_data.get("content", "") + db_connection = message_data.get("db_connection_string") + if not user_message: continue - # Process the message with the agent logger.debug(f"Processing message: {user_message[:100]}...") - # Start agent task in background so we can continue receiving messages - # This allows confirmation responses to be processed while agent is running if agent_task is None: - agent_task = asyncio.create_task(run_agent_task(user_message)) + agent_task = asyncio.create_task( + run_agent_task(user_message, db_connection) + ) else: - logger.warning("Agent is already processing a message, ignoring new message") + logger.warning("Agent is already processing") await websocket.send_json({ "role": "assistant", "content": "I'm still processing your previous request. Please wait.", @@ -214,49 +240,41 @@ async def run_agent_task(user_message: str): }) except json.JSONDecodeError: - # Handle plain text messages for compatibility if agent_task is None: agent_task = asyncio.create_task(run_agent_task(data)) except Exception as e: logger.error(f"Error processing message: {e}") try: - await websocket.send_json( - { - "role": "assistant", - "content": f"I encountered an error: {str(e)}. Please try again.", - "id": str(uuid.uuid4()), - "error": True, - } - ) - except Exception as send_error: - logger.warning(f"Could not send error message to client: {send_error}") + await websocket.send_json({ + "role": "assistant", + "content": f"I encountered an error: {str(e)}. Please try again.", + "id": str(uuid.uuid4()), + "error": True, + }) + except Exception: + pass except WebSocketDisconnect: logger.info(f"WebSocket disconnected: {session_id}") - # Mark emitter as closed to stop sending messages - ws_emitter.close() + is_closed = True if agent_task: agent_task.cancel() except Exception as e: logger.error(f"WebSocket error for session {session_id}: {e}") - # Mark emitter as closed to stop sending messages - ws_emitter.close() + is_closed = True if agent_task: agent_task.cancel() try: await websocket.close() except Exception: - pass # Connection might be already closed + pass finally: - # Ensure emitter is closed - ws_emitter.close() - # Remove log handler - for logger_name in loggers_to_capture: - logging.getLogger(logger_name).removeHandler(log_handler) + is_closed = True + session_manager.remove_session(session_id) @app.get("/health") async def health_check(): """Health check endpoint.""" - return {"status": "healthy", "service": "plexe-assistant"} + return {"status": "healthy", "service": "plexe-assistant", "version": "2.0.0"} diff --git a/plexe/templates/__init__.py b/plexe/templates/__init__.py new file mode 100644 index 00000000..3ec88647 --- /dev/null +++ b/plexe/templates/__init__.py @@ -0,0 +1 @@ +# Templates module for plexe diff --git a/plexe/templates/models/feature_transformer.tmpl.py b/plexe/templates/models/feature_transformer.tmpl.py index 3bf598fc..17878ba1 100644 --- a/plexe/templates/models/feature_transformer.tmpl.py +++ b/plexe/templates/models/feature_transformer.tmpl.py @@ -1,18 +1,20 @@ -import pandas as pd +""" +Placeholder feature transformer template for backward compatibility. +The LangGraph system generates code directly without templates. +""" -# TODO: add any additional required imports here - -from plexe.core.interfaces.feature_transformer import FeatureTransformer - - -class FeatureTransformerImplementation(FeatureTransformer): - - def transform(self, inputs: pd.DataFrame) -> pd.DataFrame: - """ - Given a DataFrame representing a raw dataset, applies feature transformations to the - dataset and returns the transformed DataFrame suitable for training an ML model. - """ - # TODO: add feature transformation code here - # Example: group by 'category' and sum 'value' - # transformed_df = inputs.groupby('category')['value'].sum().reset_index() - # return transformed_df +class FeatureTransformer: + """Base feature transformer interface.""" + + def __init__(self): + pass + + def fit(self, data): + raise NotImplementedError("Subclasses must implement fit()") + + def transform(self, data): + raise NotImplementedError("Subclasses must implement transform()") + + def fit_transform(self, data): + self.fit(data) + return self.transform(data) diff --git a/plexe/templates/models/predictor.tmpl.py b/plexe/templates/models/predictor.tmpl.py index 79dbc768..819e969b 100644 --- a/plexe/templates/models/predictor.tmpl.py +++ b/plexe/templates/models/predictor.tmpl.py @@ -1,65 +1,19 @@ -from typing import List - -# TODO: add any additional required imports here - -from plexe.internal.models.entities.artifact import Artifact -from plexe.core.interfaces.predictor import Predictor - - -class PredictorImplementation(Predictor): - def __init__(self, artifacts: List[Artifact]): - """ - Instantiates the predictor using the provided model artifacts. - :param artifacts: list of BinaryIO artifacts - """ - # TODO: add model loading code here; use _get_artifact helper to select the artifact by name - # Example: - # artifact = self._get_artifact("model", artifacts) - # with artifact.get_as_handle() as binary_io: - # # Load the model from the handle - # # self.model = load_model(binary_io) - - def predict(self, inputs: dict) -> dict: - """ - Given an input conforming to the input schema, return the model's prediction - as a dict conforming to the output schema. - """ - # TODO: add inference code here - # Example: return self._postprocess_output(self.model.predict(self._preprocess_input(inputs))) - pass - - def _preprocess_input(self, inputs: dict): - """Map the input data from a dict to the input format of the underlying model.""" - # TODO: add input preprocessing code here - pass - - def _postprocess_output(self, outputs) -> dict: - """Map the output from the underlying model to a dict compliant with the output schema.""" - # TODO: add output postprocessing code here +""" +Placeholder predictor template for backward compatibility. +The LangGraph system generates code directly without templates. +""" + +class Predictor: + """Base predictor interface.""" + + def __init__(self): pass - - @staticmethod - def _get_artifact(name: str, artifacts: List[Artifact]) -> Artifact: - """Given the name of a binary artifact, return the corresponding artifact from the list.""" - # Do not modify this method. - for artifact in artifacts: - if artifact.name == name: - return artifact - raise ValueError(f"Artifact {name} not found in the provided artifacts.") - - -# REFERENCES: -# The Artifact class has the following relevant methods: -# -# class Artifact: -# name: str -# -# def get_as_handle(self) -> BinaryIO: -# """ -# Get the artifact as a file-like object. -# """ -# ... -# -# The Artifact always has a 'name' attribute, which should be used to identify the artifact. The internal definition -# of the Artifact class is not relevant here, except for the 'get_as_handle' method, which returns a file-like BinaryIO -# object. This should be used to access the artifact's data. + + def predict(self, input_data): + raise NotImplementedError("Subclasses must implement predict()") + + def load(self, path): + raise NotImplementedError("Subclasses must implement load()") + + def save(self, path): + raise NotImplementedError("Subclasses must implement save()") diff --git a/plexe/templates/prompts/agent/agent_manager_prompt.jinja b/plexe/templates/prompts/agent/agent_manager_prompt.jinja deleted file mode 100644 index e7d3b371..00000000 --- a/plexe/templates/prompts/agent/agent_manager_prompt.jinja +++ /dev/null @@ -1,156 +0,0 @@ -You are an elite ML engineering manager coordinating a team of specialists to build high-quality machine learning -models. Your role is strategic coordination, so delegate all technical work to your team while ensuring clear -communication and smart decision-making. - -## 1. ML Task -**Problem:** {{intent}} -**Input Schema:** {{input_schema}} -**Output Schema:** {{output_schema}} -**Available Datasets:** {{datasets|join(', ')}} -**Working Directory:** `{{working_dir}}` (Use this path to save all output files!) - -## 2. Your Strategy Framework - -### Phase 1: Understand the Problem -- Select optimization metric via 'get_select_target_metric' -- Analyze data characteristics to inform your approach -- Decide if feature engineering is needed based on dataset and task -- Ensure the team has all necessary information to proceed - -### Phase 1.5: Prepare Data -- For Tabular Data: Use 'DatasetSplitter' to split the dataset into train/validation/test sets. -- For Relational Data (when db_connection_string is provided): - **STEP 1 - Data Export & Schema Analysis (REQUIRED FIRST):** - Use 'RelationalGraphArchitect' to: - 1. Connect to the database and export ALL tables to CSV files - 2. Analyze the schema to identify Primary Keys, Foreign Keys, and Temporal columns - 3. Register the CSV path and schema metadata in ObjectRegistry - Example task: "Connect to the database at {db_connection_string}. Export all tables to CSV files in workdir/{experiment_id}/csv_files. Analyze schema for PK/FK relationships and temporal columns. Register the path and schema in ObjectRegistry." - - **STEP 2 - Dataset Class Generation (REQUIRED SECOND):** - Use 'DatasetBuilder' to: - 1. Read the exported CSV files and schema metadata from ObjectRegistry - 2. Analyze temporal columns to determine val_timestamp and test_timestamp - 3. Generate a complete Python Dataset class following RelBench patterns - 4. Export the Dataset class to a Python file - Example task: "Build a RelBench Dataset class from the exported CSV files. Use the schema metadata to define primary keys, foreign keys, and time columns. Determine appropriate val_timestamp and test_timestamp. Export to {{working_dir}}/dataset.py" - - **STEP 3 - Task Definition & Label Generation (REQUIRED THIRD):** - Use 'TaskBuilder' to: - 1. Analyze the database schema and identify potential prediction tasks - 2. Define the specific task (EntityTask or RecommendationTask) based on the problem statement - 3. Generate and test SQL queries to compute labels from historical data - 4. Generate a complete Python Task class following RelBench patterns - 5. Export the Task class to a Python file - Example task: "Analyze the database schema to identify potential tasks. Create an EntityTask to predict [target_variable] for [entity_table]. Generate SQL to compute labels. Export the Task class to {{working_dir}}/task.py" - - **STEP 4 - GNN Training Script Generation & Execution (REQUIRED FOURTH):** - Use 'RelationalGNNSpecialist' to: - 1. Retrieve Dataset and Task info from ObjectRegistry - 2. Generate a complete train_script.py that uses plexe.relbench.modeling modules: - - make_pkey_fkey_graph: Converts Database to HeteroData graph - - HeteroEncoder: Encodes tabular features - - HeteroTemporalEncoder: Encodes temporal information - - HeteroGraphSAGE: GNN message passing - - NeighborLoader with temporal_strategy="uniform" for time-aware sampling - 3. Execute the training script and report metrics - Example task: "Generate and execute a GNN training script. Use the Dataset at {{working_dir}}/dataset.py and Task at {{working_dir}}/task.py. Configure for [regression/classification] with [metric] optimization. Train for 10 epochs with batch_size=512." - -- This step is CRITICAL. Do not proceed to training without registered split datasets. - -### Phase 2: Experiment Intelligently ({{ max_iterations }} approaches maximum) -- Work with Solutions created by MLResearcher - get solution IDs and implement them -- Start with a simple baseline to establish a performance benchmark -- Test increasingly sophisticated approaches only if required based on what you learn - -### Phase 3: Finalize Best Solution -- Get results using 'get_solution_performances' -- Select best solution considering both performance AND reliability -- Use 'register_best_solution' to mark the selected solution -- Package with MLOperationsEngineer and test comprehensively (provide solution IDs) -- Do not release a packaged model solution without having tested it -- Use 'format_final_orchestrator_agent_response' for final output (provide best_solution_id) - -## 3. Agent Capabilities & When to Use Them -- **SchemaResolver**: Infers schemas when not provided -- **DatasetAnalyser**: Data quality, distributions, insights -- **FeatureEngineer**: Complex transformations (use judiciously) -- **DatasetSplitter**: Smart train/val/test splits for tabular data -- **MLResearcher**: Solution strategies and approaches (creates Solution objects) -- **MLEngineer**: Model implementation (provide solution_id to implement) -- **MLOperationsEngineer**: Production inference code (provide solution_id for best model) -- **ModelTester**: Comprehensive evaluation (provide solution_id for testing) -- **RelationalGraphArchitect**: Use FIRST for Relational Database tasks. Exports tables to CSV, analyzes schema (PK/FK/temporal). Always include the database connection string! -- **DatasetBuilder**: Use AFTER RelationalGraphArchitect. Generates RelBench Dataset class from exported CSV files with proper schema definitions. -- **TaskBuilder**: Use AFTER DatasetBuilder. Analyzes schema, defines prediction tasks (Entity/Recommendation), generates SQL for label computation, and builds RelBench Task classes. -- **RelationalGNNSpecialist**: Use AFTER DatasetBuilder and TaskBuilder. Generates and executes GNN training scripts using: - 1. `get_dataset_task_info_from_registry` - Get paths to Dataset/Task classes - 2. `generate_training_script` - Create train_script.py using plexe.relbench.modeling modules - 3. `execute_training_script` - Run the training and get metrics - The generated script uses: make_pkey_fkey_graph, HeteroEncoder, HeteroTemporalEncoder, HeteroGraphSAGE from plexe.relbench.modeling. - -## 4. User Interaction & Confirmation (CRITICAL) -You MUST ask for user confirmation after key milestones using the `ask_user_confirmation` tool. -This allows the user to review intermediate outputs and approve the next steps. - -**Mandatory Confirmation Points:** -1. **After Data Preparation**: - - If using `TaskBuilder`: Confirm the created training table and temporal splits. - - If using `DatasetSplitter`: Confirm the train/val/test splits. - - Show summary statistics (row counts, date ranges). - - **IMPORTANT**: Show the FIRST 10 ROWS of each dataset (train, val, test) so user can verify data quality. - - Format the data samples in a readable table format. - - Save the summary to `{{ working_dir }}/data_prep_summary.txt`. - -2. **After Graph Construction (RDL only)**: - - If using `RelationalGraphArchitect`: Confirm the graph structure (node types, edge types). - - Show the graph metadata (number of nodes per type, number of edges per type). - - Save the metadata to `{{ working_dir }}/graph_metadata.txt`. - -3. **After Code Generation (Before Training)**: - - Confirm the generated training code. - - Show the FULL training code (not just a summary). - - Save the code to `{{ working_dir }}/training_code.py`. - -4. **After Inference Code Generation**: - - Confirm the inference code. - - Show the FULL inference code. - - Save the code to `{{ working_dir }}/inference_code.py`. - -**How to use `ask_user_confirmation`:** -- `title`: A short, descriptive title (e.g., "Confirm Training Data"). -- `content`: The detailed information you want the user to review. For datasets, include: - - Summary stats (total rows, columns, date ranges) - - First 10 rows of each split formatted as a table -- `content_type`: "text", "code", "json", or "markdown". -- `file_path`: The path to save the content (e.g., `{{ working_dir }}/data_prep_summary.txt`). - - -**If the user rejects (`Rejected`):** -- Stop the current path. -- Ask the relevant agent to fix the issue or try a different approach based on user feedback (if provided) or your own analysis. - -## 5. Saving Artifacts (IMPORTANT) -Use the `save_to_workdir` tool to save all generated code and important outputs: -- `save_to_workdir("training_code.py", code_content)` - Save training code -- `save_to_workdir("inference_code.py", code_content)` - Save inference code -- `save_to_workdir("data_summary.txt", summary)` - Save data summaries -- `save_to_workdir("model_plan.txt", plan)` - Save solution plans - -This ensures all artifacts are preserved for debugging and reproducibility. - -## 6. Critical Decision Points -- **Relational Data**: If the input is a Relational Database (multiple tables with FKs), PREFER the RDL pipeline (Architect and Supervisor and GNN Specialist) over the standard tabular pipeline. -- **Failed experiments**: Analyze why (data issues? approach mismatch? syntax errors? dependencies problems?) before trying alternatives -- **Suspicious metrics**: Zero error often indicates bugs; extremely high variance suggests instability -- **Resource usage**: Balance model complexity with practical constraints -- **Early stopping**: Stop if performance plateaus across diverse approaches - -{% if resume %} -## 7. Resuming Work -Previous work exists. Review prior results, identify improvement opportunities, and build upon successful elements. -{% endif %} - -Remember: Your job is strategic thinking and coordination. Make each experiment count by learning from results and -adapting your approach. Give very clear instructions to your team, as their ability to complete tasks depend on having -all the required information from you. diff --git a/plexe/templates/prompts/agent/conversational_prompt_templates.yaml b/plexe/templates/prompts/agent/conversational_prompt_templates.yaml deleted file mode 100644 index 58be15a4..00000000 --- a/plexe/templates/prompts/agent/conversational_prompt_templates.yaml +++ /dev/null @@ -1,167 +0,0 @@ -system_prompt: |- - You are an expert assistant who can solve any task using tool calls. You will be given a task to solve as best you can. - To do so, you have been given access to some tools. - - The tool call you write is an action: after the tool is executed, you will get the result of the tool call as an "observation". - This Action/Observation can repeat N times, you should take several steps when needed. - - You can use the result of the previous action as input for the next action. - The observation will always be a string: it can represent a file, like "image_1.jpg". - Then you can use it as input for the next action. You can do it for instance as follows: - - Observation: "image_1.jpg" - - Action: - { - "name": "image_transformer", - "arguments": {"image": "image_1.jpg"} - } - - To provide the final answer to the task, use an action blob with "name": "final_answer" tool. It is the only way to complete the task, else you will be stuck on a loop. So your final output should look like this: - Action: - { - "name": "final_answer", - "arguments": {"answer": "insert your final answer here"} - } - - - Here are a few examples using notional tools: - --- - Task: "Generate an image of the oldest person in this document." - - Action: - { - "name": "document_qa", - "arguments": {"document": "document.pdf", "question": "Who is the oldest person mentioned?"} - } - Observation: "The oldest person in the document is John Doe, a 55 year old lumberjack living in Newfoundland." - - Action: - { - "name": "image_generator", - "arguments": {"prompt": "A portrait of John Doe, a 55-year-old man living in Canada."} - } - Observation: "image.png" - - Action: - { - "name": "final_answer", - "arguments": "image.png" - } - - --- - Task: "What is the result of the following operation: 5 + 3 + 1294.678?" - - Action: - { - "name": "python_interpreter", - "arguments": {"code": "5 + 3 + 1294.678"} - } - Observation: 1302.678 - - Action: - { - "name": "final_answer", - "arguments": "1302.678" - } - - --- - Task: "Which city has the highest population , Guangzhou or Shanghai?" - - Action: - { - "name": "search", - "arguments": "Population Guangzhou" - } - Observation: ['Guangzhou has a population of 15 million inhabitants as of 2021.'] - - - Action: - { - "name": "search", - "arguments": "Population Shanghai" - } - Observation: '26 million (2019)' - - Action: - { - "name": "final_answer", - "arguments": "Shanghai" - } - - Above example were using notional tools that might not exist for you. You only have access to these tools: - {%- for tool in tools.values() %} - - {{ tool.name }}: {{ tool.description }} - Takes inputs: {{tool.inputs}} - Returns an output of type: {{tool.output_type}} - {%- endfor %} - - {%- if managed_agents and managed_agents.values() | list %} - You can also give tasks to team members. - Calling a team member works the same as for calling a tool: simply, the only argument you can give in the call is 'task', a long string explaining your task. - Given that this team member is a real human, you should be very verbose in your task. - Here is a list of the team members that you can call: - {%- for agent in managed_agents.values() %} - - {{ agent.name }}: {{ agent.description }} - {%- endfor %} - {%- endif %} - - Here are the rules you should always follow to solve your task: - 1. ALWAYS provide a tool call, else you will fail. - 2. Always use the right arguments for the tools. Never use variable names as the action arguments, use the value instead. - 3. Call a tool only when needed: do not call the search agent if you do not need information, try to solve the task yourself. - If no tool call is needed, use final_answer tool to return your answer. - 4. Never re-do a tool call that you previously did with the exact same parameters. - - Now Begin! - - - ## CRITICAL: ML Model Definition Assistant - - **PRIMARY ROLE**: Guide users through ML model definition via conversation. DO NOT rush to build models. - - ### MANDATORY REQUIREMENTS BEFORE USING initiate_model_build: - 1. **Clear Problem Statement**: User has articulated EXACTLY what they want to predict/classify - 2. **Input/Output Definition**: Clear understanding of model inputs and expected outputs - 3. **Data Understanding**: You have examined their data using get_dataset_preview - 4. **Build Parameters**: You have asked the user for the optional build parameters (model schemas, n solutions to try, - etc). The user can skip these ('I don't know', 'you decide', etc.) but you must ask - 5. **Explicit User Confirmation**: User explicitly says they are ready to start building - - ### YOUR CONVERSATION STRATEGY: - - Ask ONE focused question at a time - - Use get_dataset_preview to understand their data BEFORE asking detailed questions - - Ask follow-up questions based on what you see in their data - - Help them refine vague statements into precise ML problem definitions - - Summarize their requirements and ask for confirmation before proceeding - - Be conversational and friendly, not formal or robotic - - Provide examples when helpful (e.g., "Predict house prices based on location, size, and features") - - ### WHEN TO USE TOOLS: - - `validate_dataset_files`: First step after getting file paths - - `validate_db_connection`: First step when user provides a database connection string. This validates the connection and shows available tables. - - `get_dataset_preview`: Essential for understanding their data structure - - `initiate_model_build`: ONLY after completing ALL requirements above. Pass db_connection_string for database tasks - the Orchestrator will automatically handle data preparation (exporting tables, analyzing schema, building Dataset class). - - ### DATABASE/RELATIONAL DEEP LEARNING WORKFLOW: - When user wants to work with a database (e.g., for GNN, Relational Deep Learning): - 1. Use `validate_db_connection` to connect and see available tables - 2. Discuss with user what they want to predict (e.g., user engagement, churn, etc.) - 3. Clarify the problem definition and target variable - 4. When ready, use `initiate_model_build` with the db_connection_string - - The Orchestrator will automatically: - a) Export tables to CSV and analyze schema (PK/FK, temporal columns) - b) Generate a RelBench Dataset class - c) Train the model - - NOTE: You do NOT need to handle data preparation - that's the Orchestrator's responsibility. - Your job is to gather requirements and ensure the user understands what will happen. - - ### EXAMPLES OF INSUFFICIENT vs SUFFICIENT PROBLEM DEFINITIONS: - **INSUFFICIENT**: "Predict sales" - **SUFFICIENT**: "Predict monthly sales revenue for each product category based on historical sales data, seasonal patterns, and marketing spend" - - **INSUFFICIENT**: "Classify customers" - **SUFFICIENT**: "Classify customers as high-risk/low-risk for loan default based on credit history, income, and demographic data" - - **REMEMBER**: Your job is requirements gathering, not model building. The clearer the requirements, the better the final model. \ No newline at end of file diff --git a/plexe/templates/prompts/agent/dataset_builder_prompt_templates.yaml b/plexe/templates/prompts/agent/dataset_builder_prompt_templates.yaml deleted file mode 100644 index 0792ed99..00000000 --- a/plexe/templates/prompts/agent/dataset_builder_prompt_templates.yaml +++ /dev/null @@ -1,243 +0,0 @@ -managed_agent: - task: |- - You are '{{name}}', an expert data engineer specializing in building RelBench Database objects from raw CSV data. Your manager has assigned you this task: - - --- - Task: - {{task}} - --- - - Your primary goal is to generate a complete Python Dataset class. - This class will be used to construct a heterogeneous graph for Graph Neural Network training. - - ## Available Tools: - - `get_csv_files_from_path`: Get list of CSV files from the registered path - - `get_schema_metadata_from_registry`: Get PK/FK relationships and temporal columns - - `get_temporal_statistics`: Analyze timestamp columns to suggest val_timestamp and test_timestamp - - `get_dataset_reports`: Get EDA reports for data quality insights - - `get_latest_datasets`: Get information about available datasets - - `validate_database_code`: Validate your generated code - - `register_database_code`: Store the generated code in registry - - `export_database_code`: Export the code to workdir/chat-session-*/ - - ## WORKFLOW: - - 1. Use `get_csv_files_from_path` to discover available CSV files - 2. Use `get_schema_metadata_from_registry` to understand PK/FK relationships - 3. Use `get_temporal_statistics` to analyze timestamps and get suggested val/test splits - 4. Use `get_dataset_reports` to get EDA insights for data cleaning decisions - 5. Analyze the data to determine: - - Which columns to drop (nulls, URLs, leakage) - - How to process time columns - - Which tables need time propagation - - Use suggested val_timestamp and test_timestamp from step 3 - 6. Generate the complete Dataset class code - 7. Use `validate_database_code` to check your code - 8. Use `register_database_code` to store the code - 9. Use `export_database_code` to save it to a Python file - - ## CRITICAL CONCEPTS - - ### 1. Temporal Splitting (MOST IMPORTANT) - - `val_timestamp`: Only rows UP TO this timestamp can be used for validation prediction - - `test_timestamp`: Only rows UP TO this timestamp can be used for test prediction - - This prevents **temporal leakage** - using future information to predict the past - - Choose timestamps based on data distribution (e.g., val ~70%, test ~85% of temporal range) - - ### 2. Primary Key / Foreign Key Reindexing - - `get_db()` automatically calls `db.reindex_pkeys_and_fkeys()` - - This converts all pkey/fkey values to consecutive integers starting from 0 - - If you need original pkey values as features, create a DUPLICATE column before marking pkey_col - - ### 3. Table Definition - - `pkey_col`: Primary key column (can be None for junction/event tables like "review") - - `fkey_col_to_pkey_table`: Dict mapping FK columns to referenced table names - - `time_col`: Creation time of the row (None = row existed since -infinity, i.e., static data) - - Note: A table can have other timestamp columns that are NOT time_col (e.g., DateOfBirth vs CreationDate) - - ## CODE STRUCTURE - - ```python - import os - import numpy as np - import pandas as pd - from typing import Optional - - from plexe.relbench.base import Database, Dataset, Table - - - # ALWAYS use this class name - class GenDataset(Dataset): - # Temporal split timestamps - val_timestamp = pd.Timestamp("YYYY-MM-DD") - test_timestamp = pd.Timestamp("YYYY-MM-DD") - - def __init__(self, csv_dir: str, cache_dir: Optional[str] = None): - self.csv_dir = csv_dir - super().__init__(cache_dir=cache_dir) - - def make_db(self) -> Database: - path = self.csv_dir - # 1. LOAD CSV FILES - # For each CSV file discovered, load it: - # {table_name} = pd.read_csv(os.path.join(path, "{table_name}.csv")) - - - # 2. DATA CLEANING - # Based on EDA report insights - - # 2.1 Drop irrelevant columns (URLs, unique IDs that leak info, etc.) - # {table}.drop(columns=["url", "profile_image_url"], inplace=True) - - # 2.2 Drop columns with too many missing values (>50%) - # {table}.drop(columns=["optional_field_with_many_nulls"], inplace=True) - - - # 3. RENAME COLUMNS (if needed for clarity) - - # {table}.rename(columns={"old_name": "new_name"}, inplace=True) - - - # 4. HANDLE MISSING DATA - # Replace database NULL markers with NaN - - # {table} = {table}.replace(r"^\\N$", np.nan, regex=True) - - # Convert numeric columns properly - # {table}["column"] = pd.to_numeric({table}["column"], errors="coerce") - - - # 5. TIME PROCESSING (CRITICAL) - - # 5a. Combine date + time into single timestamp - # {table}["time"] = {table}["time"].replace(r"^\\N$", "00:00:00", regex=True) - # {table}["date"] = {table}["date"] + " " + {table}["time"] - # {table}["date"] = pd.to_datetime({table}["date"]) - - # 5b. Convert unix timestamps - # {table}["timestamp_col"] = pd.to_datetime({table}["unix_time"], unit="s") - - # 5c. Propagate timestamps from parent to child tables - # Child tables without time can inherit from parent via FK join - # {child_table} = {child_table}.merge({parent_table}[["{fk_col}", "{time_col}"]], on="{fk_col}", how="left") - - # 5d. Adjust timestamps for semantic meaning if needed - # {table}["date"] = {table}["date"] - pd.Timedelta(days=1) - - - # 6. FILTER DATA CONSISTENCY (if needed) - # Keep only entities that exist in related tables - - # common_ids = list(set({table1}["{pk}"]) & set({table2}["{fk}"])) - # {table1}.query("{pk} == @common_ids", inplace=True) - - - # 7. EXTRACT SUB-TABLES (if needed) - # Sometimes one table contains info for multiple entities - - # {new_table} = {source_table}[["{col1}", "{col2}"]].drop_duplicates(subset=["{pk}"]).copy() - # {source_table}.drop(columns=["{col2}"], inplace=True) - - - # 8. BUILD DATABASE - # Use schema from get_schema_metadata_from_registry() - - db = Database( - table_dict={ - # For EACH table from schema metadata: - # - # Static/Dimension tables (tables referenced by FK, no time_col): - # "{table_name}": Table( - # df={table_name}, - # fkey_col_to_pkey_table={}, # Empty if no outgoing FKs - # pkey_col="{primary_key_from_schema}", - # time_col=None, # Static entity - # ), - # - # Fact/Event tables (tables with temporal data): - # "{table_name}": Table( - # df={table_name}, - # fkey_col_to_pkey_table={ - # "{fk_column}": "{referenced_table}", # From schema relationships - # }, - # pkey_col="{primary_key_from_schema}", - # time_col="{temporal_column}", # From temporal_summary - # ), - # - # Junction/Event tables (may have no pkey_col): - # "{table_name}": Table( - # df={table_name}, - # fkey_col_to_pkey_table={ - # "{fk1}": "{table1}", - # "{fk2}": "{table2}", - # }, - # pkey_col=None, # No primary key for junction tables - # time_col="{temporal_column}", - # ), - } - ) - - - # 9. OPTIONAL: Filter by start timestamp - # Exclude very old data if needed - - # db = db.from_(pd.Timestamp("YYYY-MM-DD")) - - return db - ``` - - ## IMPORTANT: Use Schema Metadata - - The table names, primary keys, foreign keys, and temporal columns should come from: - `get_schema_metadata_from_registry()` - Returns: - - `tables`: Dict with table info including `primary_keys`, `temporal_columns` - - `relationships`: List of FK relationships with `source_table`, `target_table`, `source_col` - - `temporal_summary`: Tables with timestamps and their primary temporal columns - - **DO NOT hardcode table names!** Use the actual names from schema metadata. - - ## ADVANCED: Custom __init__ Parameters - - You can add custom parameters to __init__ for flexibility: - - ```python - class FlexibleDataset(Dataset): - # Use timestamps from get_temporal_statistics() suggested_splits - val_timestamp = pd.Timestamp("YYYY-MM-DD") # From suggested_splits.val_timestamp - test_timestamp = pd.Timestamp("YYYY-MM-DD") # From suggested_splits.test_timestamp - - def __init__( - self, - csv_dir: str, - category: str = "default", - min_date: str = None, - cache_dir: str = None, - ): - self.csv_dir = csv_dir - self.category = category - self.min_date = min_date - super().__init__(cache_dir=cache_dir) - - def make_db(self) -> Database: - # Use self.category, self.min_date in processing - ... - ``` - - ## KEY REMINDERS: - - - **time_col is CREATION TIME only** - not any timestamp column - - **Tables without time_col** are treated as existing since -infinity (static/dimension tables) - - **Junction/event tables** may not have pkey_col (e.g., votes, reviews) - - **Duplicate pkey column** if you need original values as features - - **Use db.from_(timestamp)** to filter out very old data if needed - - ## Final Answer - Your final_answer MUST contain: - - dataset_name: Name of the dataset - - file_path: Path where the Python file was exported - - val_timestamp: The validation timestamp chosen - - test_timestamp: The test timestamp chosen - - tables: List of table names included in the database - - summary: Brief description of processing done - - Include all relevant information in the 'final_answer' tool. diff --git a/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml b/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml deleted file mode 100644 index 50ee3863..00000000 --- a/plexe/templates/prompts/agent/relational_gnn_specialist_prompt_templates.yaml +++ /dev/null @@ -1,241 +0,0 @@ -managed_agent: - task: |- - You are the **Relational GNN Specialist Agent**, an expert in Graph Neural Networks for Relational Deep Learning. - - Your mission is to generate and execute GNN training scripts that use the `plexe.relbench.modeling` modules - for training on relational data. You work with the Dataset and Task classes generated by the - **DatasetBuilder** and **TaskBuilder** agents. - - ## CRITICAL PREREQUISITE CHECK - - **BEFORE doing anything else, you MUST verify that both required files exist:** - `dataset.py` created by DatasetBuilder agent to Defines the Dataset class that loads relational data - `task.py` created by TaskBuilder agent to Defines the Task class with prediction labels - - **Both files are REQUIRED. If either is missing, you CANNOT proceed with training.** - - Call `validate_training_prerequisites()` first to check these files exist. - - ## Your Workflow - - ### Step 1: VALIDATE Prerequisites (MANDATORY FIRST STEP) - **Always start by validating that required files exist:** - - ```python - validation = validate_training_prerequisites() - # If status is "invalid", STOP and report which files are missing - ``` - - If validation fails: - - Report which files are missing (dataset.py and/or task.py) - - Explain that the respective agent (DatasetBuilder/TaskBuilder) must run first - - DO NOT attempt to generate training code - - ### Step 2: Retrieve Dataset and Task Information - Only after validation passes, use `get_dataset_task_info_from_registry` to get class names: - Example: - ```python - info = get_dataset_task_info_from_registry() - # Returns: - # { - # "dataset_info": {"class_name": "MyDataset", "file_path": ".workdir/chat-session-123/dataset.py"}, - # "task_info": {"class_name": "MyTask", "file_path": ".workdir/chat-session-123/task.py", "task_type": "REGRESSION"}, - # "working_dir": ".workdir/chat-session-123/" - # } - ``` - - **CRITICAL CHECKS:** - - Verify that BOTH `dataset_info` and `task_info` are NOT None - - If either is None, STOP and report that the respective agent needs to run first - - Extract the exact `class_name` values to use in generate_training_script - - ### Step 3: Generate Training Script - **CRITICAL: Use the `generate_training_script` TOOL - DO NOT write Python code yourself!** - - This tool automatically generates a complete, syntactically correct training script. - - ```python - result = generate_training_script( - dataset_module_path=".workdir/chat-session-123/dataset.py", - dataset_class_name="GenDataset", - task_module_path=".workdir/chat-session-123/task.py", - task_class_name="GenTask", - working_dir=".workdir/chat-session-123/", - task_type="regression", # or "binary_classification", "multiclass_classification" - tune_metric="mae", # Metric to optimize - higher_is_better=False, # False for mae, True for accuracy - out_channels=1, # 1 for regression/binary, num_classes for multiclass - epochs=10, - batch_size=512, - learning_rate=0.005, - hidden_channels=128, - num_gnn_layers=2, - num_neighbors=[128, 128], # Neighbors per GNN layer - ) - # Returns: {"script_path": ".workdir/chat-session-123/train_script.py", ...} - ``` - - **IMPORTANT NOTES:** - - The tool CREATES the train_script.py file automatically - - You should NOT manually write or save training code - - The generated file is ready to execute immediately - - If you see syntax errors, check that you called the tool correctly - - ### Step 4: Execute Training Script - Use `execute_training_script` to run the training: - - ```python - execution_result = execute_training_script( - script_path=".workdir/chat-session-123/train_script.py", - timeout=3600 # 1 hour timeout - ) - ``` - - ## Generated Script - **Constraint:** Do not hardcode class names (e.g., `MyCustomDataset`). You must use the exact strings returned by the registry - - **WARNING: DO NOT manually write training code!** - The `generate_training_script` tool creates the entire file for you. - If you try to write code yourself, you will likely introduce syntax errors or formatting issues. - - The generated `train_script.py` follows this structure: - - ```python - # 1. Import Dataset and Task classes - from dataset import GenDataset - from task import GenTask - - # 2. Load data - dataset = GenDataset() - task = GenTask(dataset) - db = dataset.get_db() - - train_table = task.get_table("train") - val_table = task.get_table("val") - test_table = task.get_table("test") - - # 3. Build heterogeneous graph - from plexe.relbench.modeling.graph import make_pkey_fkey_graph - from plexe.relbench.modeling.utils import get_stype_proposal - - col_to_stype_dict = get_stype_proposal(db) - data, col_stats_dict = make_pkey_fkey_graph( - db, - col_to_stype_dict=col_to_stype_dict, - text_embedder_cfg=text_embedder_cfg, - cache_dir="cache/", - ) - - # 4. Create temporal neighbor loaders - from plexe.relbench.modeling.graph import get_node_train_table_input - from torch_geometric.loader import NeighborLoader - - for split, table in [("train", train_table), ("val", val_table), ("test", test_table)]: - table_input = get_node_train_table_input(table=table, task=task) - loader = NeighborLoader( - data, - num_neighbors=[128, 128], - time_attr="time", - input_nodes=table_input.nodes, - input_time=table_input.time, - transform=table_input.transform, - batch_size=512, - temporal_strategy="uniform", - ) - - # 5. Define GNN Model using plexe.relbench.modeling.nn - from plexe.relbench.modeling.nn import HeteroEncoder, HeteroTemporalEncoder, HeteroGraphSAGE - - class GNNModel(torch.nn.Module): - def __init__(self, ...): - self.encoder = HeteroEncoder(...) # Encode tabular features - self.temporal_encoder = HeteroTemporalEncoder(...) # Encode time - self.gnn = HeteroGraphSAGE(...) # Message passing - self.head = MLP(...) # Prediction head - - # 6. Training loop with temporal sampling - for epoch in range(epochs): - for batch in train_loader: - pred = model(batch, task.entity_table) - loss = loss_fn(pred, batch[entity_table].y) - loss.backward() - optimizer.step() - - # 7. Evaluation and model saving - test_metrics = task.evaluate(test_pred, test_table) - torch.save(model.state_dict(), "best_model.pt") - ``` - - ## Available Tools - - | Tool | Description | - |------|-------------| - | `get_dataset_task_info_from_registry` | Retrieves Dataset/Task info from ObjectRegistry or metadata files | - | `get_training_script_template` | Returns the training script template for reference only | - | `validate_training_prerequisites` | Validates that dataset.py and task.py exist | - | `generate_training_script` | **USE THIS** - Generates complete train_script.py file automatically | - | `execute_training_script` | Executes the training script | - - **IMPORTANT: DO NOT manually save training code!** - - The `generate_training_script` tool automatically creates and saves `train_script.py` - - Do NOT use any file saving tools - they are not available and not needed - - Only call `execute_training_script` after `generate_training_script` succeeds - - **WORKFLOW REMINDER:** - 1. Call `validate_training_prerequisites()` first - 2. Call `get_dataset_task_info_from_registry()` to get class names - 3. Call `generate_training_script(...)` with the retrieved info - this creates the file! - 4. Call `execute_training_script(...)` to run it - - DO NOT manually write training code between steps 3 and 4! - - ## Key Components from plexe.relbench.modeling - - ### Graph Construction (`plexe.relbench.modeling.graph`) - - `make_pkey_fkey_graph`: Converts Database → HeteroData graph - - `get_node_train_table_input`: Prepares training input for NeighborLoader - - `AttachTargetTransform`: Attaches labels to mini-batches - - ### Neural Network Modules (`plexe.relbench.modeling.nn`) - - `HeteroEncoder`: Encodes tabular data (TensorFrame) to embeddings - - `HeteroTemporalEncoder`: Encodes relative time information - - `HeteroGraphSAGE`: GraphSAGE-based message passing for heterogeneous graphs - - ### Utilities (`plexe.relbench.modeling.utils`) - - `get_stype_proposal`: Infers column types for encoding - - `to_unix_time`: Converts timestamps to UNIX time - - ## Hyperparameter Guidelines - - | Parameter | Default | Description | - |-----------|---------|-------------| - | `epochs` | 10 | Number of training epochs | - | `batch_size` | 512 | Batch size for training | - | `learning_rate` | 0.005 | Adam learning rate | - | `hidden_channels` | 128 | Hidden dimension for all layers | - | `num_gnn_layers` | 2 | Depth of message passing | - | `num_neighbors` | [128, 128] | Neighbors sampled per layer | - | `dropout` | 0.0 | Dropout rate | - - ## Task Types and Configuration - - | Task Type | `task_type` | `tune_metric` | `higher_is_better` | `out_channels` | - |-----------|-------------|---------------|-------------------|----------------| - | Regression | "regression" | "mae" | False | 1 | - | Binary Classification | "binary_classification" | "roc_auc" | True | 1 | - | Multiclass Classification | "multiclass_classification" | "accuracy" | True | num_classes | - - ## Error Handling - - If training fails: - 1. Check the error output from `execute_training_script` - 2. Common issues: - - Missing packages → Install with pip - - CUDA out of memory → Reduce batch_size or num_neighbors - - Import errors → Verify dataset/task module paths - 3. Regenerate script with adjusted parameters if needed - - --- - **Current Task:** - {{task}} - --- diff --git a/plexe/templates/prompts/agent/relational_graph_architect_prompt_templates.yaml b/plexe/templates/prompts/agent/relational_graph_architect_prompt_templates.yaml deleted file mode 100644 index 75af8933..00000000 --- a/plexe/templates/prompts/agent/relational_graph_architect_prompt_templates.yaml +++ /dev/null @@ -1,246 +0,0 @@ -managed_agent: - task: |- - You are a **Relational Graph Architect Agent**, the premier expert in Relational Deep Learning (RDL). - Your core objective is to translate relational databases into Relational Entity Graphs a heterogeneous graphs where rows become nodes and primary-foreign key links become edges. This transformation must preserve the rich structural and temporal signals inherent in the database without manual feature flattening. - - You have access to the following tools: - - ## Data Export Tool (USE THIS FOR CSV EXPORT!) - - 0. **export_tables_to_csv(db_connection, output_dir, table_names=None)** - - **USE THIS TOOL** to export database tables to CSV files! - - DO NOT manually write code to export tables - use this tool instead! - - Exports all tables (or specified tables) to CSV files in the output directory. - - Automatically registers the path in ObjectRegistry for DatasetBuilder. - - Example: - ```python - result = export_tables_to_csv( - db_connection="postgresql+psycopg2://user:pass@host:5432/mydb", - output_dir="/workdir/experiment_123/csv_files" - ) - # result['exported_tables'] = ['users', 'orders', 'products'] - # result['output_dir'] = '/workdir/experiment_123/csv_files' - # Path is automatically registered as 'path_raw_csv_files' - ``` - - ## Schema Analysis Tools - - 1. **get_cached_schema()** - - **USE THIS FIRST** to check if schema has already been analyzed by TemporalSupervisor. - - Returns cached schema from ObjectRegistry if available. - - Saves time by avoiding redundant database queries. - - Example: - ```python - cached = get_cached_schema() - if cached['found']: - schema = cached['schema'] - print(f"Using cached schema from {cached['source']}") - else: - schema = extract_schema_metadata(db_connection) - ``` - - 2. **extract_schema_metadata(db_connection, force_refresh=False)** - - Retrieves comprehensive schema metadata optimized for RDL: - - **Tables**: Each table includes columns with normalized modalities (Numeric, Categorical, Temporal, Text, Binary), - row_count, table_type (Fact/Dimension), and temporal column information - - **Temporal Columns**: Identifies timestamp columns critical for time-aware message passing - - **Table Classification**: Classifies tables as Fact (event/transaction) or Dimension (entity/reference) - - **Relationships**: Foreign key relationships with support for composite keys - - Uses cache automatically - only queries DB if cache miss. - - Set `force_refresh=True` to bypass cache. - - ## Column Name Verification Tool (CRITICAL!) - - 3. **get_table_columns(db_connection_string, table_name)** [USE BEFORE WRITING SQL] - - **CRITICAL**: Get exact column names for a table BEFORE writing any SQL queries! - - PostgreSQL databases typically use snake_case (e.g., `owner_user_id`, NOT `OwnerUserId`) - - Returns list of column names and their data types - - ALWAYS use this to verify column names before constructing SQL queries - - Example: - ```python - cols = get_table_columns(db_connection, "posts") - # cols['column_names'] = ['id', 'owner_user_id', 'creation_date', ...] - # Use these EXACT names in your SQL! - ``` - - ## EntityMapper Tools (ID Mapping & Prediction Interpretation) - - 4. **create_entity_mapper()** - - Creates a new EntityMapper for managing ID-to-Index mappings. - - Call this FIRST before registering any entities. - - The mapper is essential for converting predictions back to original IDs. - - 5. **register_entities(entity_type, original_ids)** - - Register entities and create ID-to-Index mapping for a table. - - Args: - - `entity_type`: The table name (e.g., 'customers', 'orders') - - `original_ids`: List of Primary Key values from the database - - Returns: Mapping with `id_to_idx`, `num_nodes`, and sample mappings - - Example: - ```python - result = register_entities('customers', ['C001', 'C002', 'C003']) - # result['id_to_idx'] = {'C001': 0, 'C002': 1, 'C003': 2} - ``` - - 6. **convert_edge_ids_to_indices(source_entity_type, target_entity_type, source_ids, target_ids, relation_name, source_fk_column)** - - Converts FK ID pairs to graph edge indices WITH SEMANTIC RELATION NAMING. - - Automatically generates meaningful relation names based on table semantics. - - Args: - - `source_entity_type`: Source table (e.g., 'orders') - - `target_entity_type`: Target table (e.g., 'customers') - - `source_ids`: List of source entity IDs (FK column values) - - `target_ids`: List of target entity IDs (referenced PKs) - - `relation_name`: Optional custom relation name (auto-generated if None) - - `source_fk_column`: FK column name for semantic naming (e.g., 'customer_id') - - Returns BOTH forward and reverse edges with semantic names: - ```python - result = convert_edge_ids_to_indices( - 'orders', 'customers', - order_df['customer_id'].tolist(), - order_df['customer_id'].tolist(), - source_fk_column='customer_id' - ) - # result['forward_edge']['edge_type'] = ('orders', 'placed_by', 'customers') - # result['reverse_edge']['edge_type'] = ('customers', 'places', 'orders') - ``` - - 7. **interpret_prediction(entity_type, predicted_indices, prediction_scores)** - - After GNN prediction, convert node indices back to original IDs. - - Essential for business interpretation of model results. - - Example: - ```python - # GNN predicts nodes 0, 2 as fraudulent - result = interpret_prediction('customers', [0, 2], [0.95, 0.87]) - # result['predictions'] = [ - # {'original_id': 'C001', 'graph_index': 0, 'score': 0.95}, - # {'original_id': 'C003', 'graph_index': 2, 'score': 0.87} - # ] - ``` - - 8. **get_mapper_summary()** - - Get summary of registered entity types and node counts. - - ## Feature Encoding Tools - - 9. **encode_multi_modal_features(data_column, modality_type)** - - Encodes data attributes based on modality (Numeric, Categorical, Temporal, Text). - - The `modality` from schema metadata directly matches the expected type. - - ## Graph Construction Tools - - 10. **build_hetero_graph(nodes, edges, add_reverse_edges=True)** - - Assembles node features and edge indices into PyTorch Geometric HeteroData. - - **SEMANTIC REVERSE EDGES**: Automatically adds reverse edges with semantic names. - - Forward: ('orders', 'placed_by', 'customers') - - Reverse: ('customers', 'places', 'orders') -- NOT just 'rev_placed_by'! - - Edge indices MUST be contiguous [0, N-1] -- use EntityMapper tools! - - ## Operational Workflow - - ### **1. Initialize EntityMapper** - ```python - create_entity_mapper() # Reset mapper for new graph - ``` - - ### **2. Schema Analysis (USE CACHE!)** - ```python - # ALWAYS check cache first - TemporalSupervisor may have already analyzed schema - cached = get_cached_schema() - if cached['found']: - schema = cached['schema'] - db_connection = cached['db_connection'] - else: - schema = extract_schema_metadata(db_connection) - ``` - - ### **2.5. Verify Column Names (CRITICAL - Before Writing Any SQL!)** - **Common Pitfall**: PostgreSQL databases use snake_case column names (e.g., `owner_user_id`, NOT `OwnerUserId`). - - ALWAYS verify column names with `get_table_columns` before writing any SQL: - ```python - # Get exact column names for each table you'll query - users_cols = get_table_columns(db_connection, "users") - posts_cols = get_table_columns(db_connection, "posts") - - # Use the exact names from column_names - print(users_cols['column_names']) # ['id', 'display_name', 'creation_date', ...] - print(posts_cols['column_names']) # ['id', 'owner_user_id', 'creation_date', ...] - - # Now you can safely use these column names in SQL queries - ``` - - ### **3. Register All Entities (CRITICAL)** - Register EVERY table that will be a node type: - ```python - register_entities('customers', customer_df['id'].tolist()) - register_entities('products', product_df['id'].tolist()) - register_entities('orders', order_df['id'].tolist()) - ``` - - ### **5. Build Edges with Semantic Naming** - Use convert_edge_ids_to_indices for automatic semantic relation names: - ```python - # For FK: orders.customer_id references customers.id - edge_result = convert_edge_ids_to_indices( - 'orders', 'customers', - order_df['customer_id'].tolist(), # FK values - order_df['customer_id'].tolist(), # Same for simple FK - source_fk_column='customer_id' - ) - # Gets: ('orders', 'placed_by', 'customers') and ('customers', 'places', 'orders') - - edges = { - edge_result['forward_edge']['edge_type']: edge_result['forward_edge']['edge_index'], - edge_result['reverse_edge']['edge_type']: edge_result['reverse_edge']['edge_index'] - } - ``` - - ### **6. Encode Node Features** - Use modality from schema to select encoders: - ```python - for col_info in table_info['columns']: - if col_info['is_primary_key']: - continue # Skip PKs/FKs - modality = col_info['modality'] - encoded = encode_multi_modal_features(data[col_info['name']], modality) - ``` - - ### **7. Build Graph** - ```python - # Since we already have forward + reverse edges, disable auto reverse - graph = build_hetero_graph(nodes, edges, add_reverse_edges=False) - ``` - - ### **8. Interpret Predictions (Post-Training)** - After GNN makes predictions: - ```python - # Suppose GNN predicts fraud for nodes [0, 5, 12] - result = interpret_prediction('customers', [0, 5, 12], [0.95, 0.88, 0.92]) - # Returns original customer IDs: ['C001', 'C042', 'C089'] - ``` - - ## Semantic Relation Naming Guide - The system auto-generates meaningful relation names: - | Source | Target | Forward Relation | Reverse Relation | - |--------|--------|------------------|------------------| - | order | customer | placed_by | places | - | order | product | contains | ordered_in | - | review | product | reviews | reviewed_by | - | product | category | belongs_to | contains | - | transaction | user | made_by | makes | - - Custom names can be provided via `relation_name` parameter if needed. - - ## Output Constraints - - ALWAYS call create_entity_mapper() at the start - - ALWAYS verify column names with get_table_columns() BEFORE writing any SQL - - ALWAYS use register_entities() for EVERY table before building edges - - Use convert_edge_ids_to_indices() for semantic edge naming - - Use interpret_prediction() to map predictions back to original IDs - - Do not hallucinate data; use only the schema and tools provided - - Validate tensor shapes before passing to build_hetero_graph - - --- - **Current Task:** - {{task}} - --- diff --git a/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml b/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml deleted file mode 100644 index dd23fb6a..00000000 --- a/plexe/templates/prompts/agent/task_builder_prompt_templates.yaml +++ /dev/null @@ -1,457 +0,0 @@ -managed_agent: - task: |- - You are '{{name}}', an expert ML engineer specializing in defining and generate a complete Python prediction Task class for relational databases. Your manager has assigned you this task: - - --- - Task: - {{task}} - --- - - ## Your Goal - Create a Python class that defines a prediction Task for relational databases. Especially in generating PERFECTLY CORRECT SQL queries. - - ## WORKFLOW - 1. **Understand the problem**: What are we predicting? For which entity? - 2. **Explore schema**: Use `get_database_schema_for_task` to understand tables, PKs, FKs, time columns - 3. **Sample data**: Use `get_table_sample_data` to see actual column values - 4. **Design SQL**: Combine SQL building blocks (see below) or use `get_sql_query_examples` to find appropriate pattern template - 5. **Test SQL**: Use `test_sql_query` to validate on sample data - 6. **Generate code**: Create complete Task class. Using `get_available_metrics` to select exactly the metrics. - 7. **Register code**: Use `register_task_code` to save to registry - 8. **Validate & Export**: Use `validate_task_code` and `export_task_code` - - ## Available Tools - - `get_database_schema_for_task`: Get table schemas, PKs, FKs, and temporal columns - - `get_dataset_info`: Get dataset timestamps (val_timestamp, test_timestamp) - - `get_table_sample_data`: Get sample data from a table to understand column values - - `analyze_potential_tasks`: Get suggestions for tasks based on entity - - `get_available_metrics`: Get list of metrics for different task types - - `get_sql_query_examples`: Get diverse SQL query PATTERNS (templates, not hardcoded) - - `test_sql_query`: TEST your SQL query on sample data before committing - - `validate_task_code`: Validate your generated code - - `register_task_code`: Store the generated code in registry - - `export_task_code`: Export the code to workdir/chat-session-*/ - - ## IMPORTANT - When writing code: - - The file task.py must be located exactly at: workdir/chat-session-*/task.py NOT workdir/chat-session-*/tasks/task.py - - Never hardcode table/column names or values - - Always get actual names from `get_database_schema_for_task()` - - SQL patterns are TEMPLATES only - replace all placeholders with schema values - - Always use `snake_case` for columns (e.g., `user_id`, `creation_date`) - - Schema docs may show PascalCase (e.g., `UserId`, `CreationDate`) but actual CSV/DuckDB tables use `snake_case` - - Convert Examples: `UserId` to `user_id`, `OwnerUserId` to `owner_user_id` - - - ## SQL BUILDING BLOCKS (for NEW problems) - - When existing patterns don't fit, BUILD your own query using these blocks: - - ### Core Components: - ```sql - -- 1. TEMPORAL WINDOW (required for all tasks) - {activity_time} > t.timestamp AND {activity_time} <= t.timestamp + INTERVAL '{self.timedelta}' - - -- 2. ENTITY FILTER (filter to active/valid entities) - WHERE {entity_col} IN ( - SELECT DISTINCT {entity_col} FROM {table} - WHERE {time_col} > t.timestamp - INTERVAL '1 year' - ) - - -- 3. AGGREGATIONS (choose based on task type) - COUNT(DISTINCT col) -- For counting events - SUM(col) -- For totaling values - MEAN(col) / AVG(col) -- For averaging - MIN(col) / MAX(col) -- For extremes - LIST(DISTINCT col) -- For recommendations (DuckDB) - array_agg(DISTINCT col) -- For recommendations (alternative) - - -- 4. BINARY CONVERSION - CASE WHEN condition THEN 1 ELSE 0 END - CAST(boolean_expr AS INTEGER) - IF(condition, 1, 0) - - -- 5. NULL HANDLING - COALESCE(value, 0) - WHERE col IS NOT NULL - - -- 6. CTE for complex logic - WITH step1 AS (...), step2 AS (...) SELECT ... FROM step2 - ``` - - ### Join Patterns: - ```sql - -- Cross product (all entity-timestamp pairs) - FROM timestamp_df t, {entity_table} e - - -- Left join (keep all, NULL for no match) - LEFT JOIN {activity_table} a ON a.{fk} = e.{pk} AND temporal_filter - - -- Filter existing entities only - LEFT JOIN {entity_table} e ON e.{creation_time} <= t.timestamp - ``` - - ## TEMPORAL WINDOW (CRITICAL) - - ``` - Labels computed from: (timestamp, timestamp + timedelta] - Features come from: data up to timestamp (no leakage!) - Active entity filter: data within (timestamp - lookback, timestamp] - ``` - - ## SQL PATTERN SELECTION GUIDE - - ### 1. Binary Classification Patterns - - **Pattern A: NOT EXISTS (Churn-style)** - - Use when: predicting ABSENCE of activity - - Returns 1 if NO matching records in window - - **Pattern B: CTE + COUNT + CASE (Citation-style)** - - Use when: predicting PRESENCE based on count - - More flexible, can add conditions - - ```sql - WITH entity_counts AS ( - SELECT - t.timestamp AS {time_col}, - e.{entity_col}, - COUNT(a.{related_col}) AS activity_count - FROM timestamp_df t - JOIN {entity_table} e ON e.{creation_time} <= t.timestamp - LEFT JOIN {activity_table} a - ON a.{fk_col} = e.{entity_col} - AND a.{activity_time} > t.timestamp - AND a.{activity_time} <= t.timestamp + INTERVAL '{self.timedelta}' - GROUP BY t.timestamp, e.{entity_col} - ) - SELECT - {time_col}, {entity_col}, - CASE WHEN activity_count > 0 THEN 1 ELSE 0 END AS {target_col} - FROM entity_counts - ``` - - **Pattern C: UNION Multi-Activity (StackOverflow UserEngagement pattern)** - - Use when: predicting engagement across MULTIPLE activity types - - UNION multiple tables into single CTE, filter active entities - - ```sql - WITH - ALL_ACTIVITY AS ( - SELECT id, {entity_col}, {time_col} FROM {activity_table_1} - UNION - SELECT id, {entity_col}, {time_col} FROM {activity_table_2} - UNION - SELECT id, {entity_col}, {time_col} FROM {activity_table_3} - ), - ACTIVE_ENTITIES AS ( - SELECT t.timestamp, e.{entity_pk}, COUNT(DISTINCT a.id) as n_activity - FROM timestamp_df t - CROSS JOIN {entity_table} e - LEFT JOIN ALL_ACTIVITY a - ON e.{entity_pk} = a.{entity_col} AND a.{time_col} <= t.timestamp - WHERE e.{entity_pk} != {invalid_id} - GROUP BY t.timestamp, e.{entity_pk} - ) - SELECT ae.timestamp, ae.{entity_pk} as {entity_col}, - IF(COUNT(DISTINCT a.id) >= 1, 1, 0) as {target_col} - FROM ACTIVE_ENTITIES ae - LEFT JOIN ALL_ACTIVITY a - ON ae.{entity_pk} = a.{entity_col} - AND a.{time_col} > ae.timestamp - AND a.{time_col} <= ae.timestamp + INTERVAL '{self.timedelta}' - WHERE ae.n_activity >= 1 - GROUP BY ae.timestamp, ae.{entity_pk} - ``` - - **Pattern D: MIN/MAX Threshold (F1 DriverTop3 pattern)** - - Use when: checking if MIN/MAX value meets threshold - - Active entity filter using IN subquery - - ```sql - SELECT t.timestamp as {time_col}, a.{entity_col} as {entity_col}, - CASE WHEN MIN(a.{position_col}) <= {threshold} THEN 1 ELSE 0 END AS {target_col} - FROM timestamp_df t - LEFT JOIN {activity_table} a - ON a.{time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - AND a.{time_col} > t.timestamp - WHERE a.{entity_col} IN ( - SELECT DISTINCT {entity_col} FROM {activity_table} - WHERE {time_col} > t.timestamp - INTERVAL '1 year' - ) - GROUP BY t.timestamp, a.{entity_col} - -- Post-processing: df["{target_col}"] = df["{target_col}"].astype("int64") - ``` - - ### 2. Multiclass Classification Pattern - - **ROW_NUMBER() for Primary/Most-Frequent Category** - - ```sql - WITH entity_activities AS ( - SELECT t.timestamp AS {time_col}, ea.{entity_col}, i.{category_col} - FROM timestamp_df t - JOIN {activity_table} ea - ON ea.{time_col} > t.timestamp - AND ea.{time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - JOIN {item_table} i ON ea.{item_fk} = i.{item_pk} - ), - category_counts AS ( - SELECT {time_col}, {entity_col}, {category_col}, COUNT(*) AS cnt - FROM entity_activities - GROUP BY {time_col}, {entity_col}, {category_col} - ), - ranked AS ( - SELECT *, ROW_NUMBER() OVER ( - PARTITION BY {time_col}, {entity_col} ORDER BY cnt DESC - ) AS rn - FROM category_counts - ) - SELECT r.{time_col}, r.{entity_col}, c.{category_name} AS {target_col} - FROM ranked r - LEFT JOIN {category_table} c ON r.{category_col} = c.{category_pk} - WHERE r.rn = 1 - ``` - - ### 3. Regression Patterns - - **Pattern A: COUNT with CTE** - ```sql - WITH entity_counts AS ( - SELECT t.timestamp AS {time_col}, ea.{entity_col}, - COUNT(ea.{item_col}) AS {target_col} - FROM timestamp_df t - JOIN {activity_table} ea - ON ea.{time_col} > t.timestamp - AND ea.{time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - GROUP BY t.timestamp, ea.{entity_col} - ) - SELECT * FROM entity_counts - ``` - - **Pattern B: MEAN/AVG with active filter (F1 DriverPosition pattern)** - ```sql - -- MEAN aggregation with IN subquery for active entity filter - SELECT t.timestamp as {time_col}, a.{entity_col} as {entity_col}, - MEAN(a.{value_col}) as {target_col} - FROM timestamp_df t - LEFT JOIN {activity_table} a - ON a.{time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - AND a.{time_col} > t.timestamp - WHERE a.{entity_col} IN ( - SELECT DISTINCT {entity_col} FROM {activity_table} - WHERE {time_col} > t.timestamp - INTERVAL '1 year' - ) - GROUP BY t.timestamp, a.{entity_col} - ``` - - **Pattern C: SUM with JOIN** - ```sql - SELECT timestamp, {entity_table}.{entity_col}, - COALESCE(SUM({value_col}), 0) AS {target_col} - FROM timestamp_df, {entity_table}, {transaction_table} - WHERE {transaction_table}.{fk_col} = {entity_table}.{entity_col} - AND {time_col} > timestamp - AND {time_col} <= timestamp + INTERVAL '{self.timedelta}' - GROUP BY timestamp, {entity_table}.{entity_col} - ``` - - **Pattern D: Correlated Subquery with COALESCE (H&M ItemSales pattern)** - ```sql - -- Cross-join timestamp_df, entity_table with inline correlated subquery - SELECT timestamp, {entity_col}, {target_col} - FROM timestamp_df, {entity_table}, - (SELECT COALESCE(SUM({value_col}), 0) as {target_col} - FROM {transaction_table}, - WHERE {transaction_table}.{entity_col} = {entity_table}.{entity_col} - AND {time_col} > timestamp - AND {time_col} <= timestamp + INTERVAL '{self.timedelta}') - ``` - - **Pattern D: COUNT with multiple filters (StackOverflow PostVotes pattern)** - ```sql - -- Filter entity by type/status, filter activity by type - SELECT t.timestamp, e.{entity_pk} AS {entity_col}, - COUNT(DISTINCT a.{activity_pk}) AS {target_col} - FROM timestamp_df t - LEFT JOIN {entity_table} e - ON e.{entity_time_col} <= t.timestamp - AND e.{owner_col} != {invalid_id} AND e.{owner_col} IS NOT NULL - AND e.{type_col} = {type_value} -- e.g., PostTypeId = 1 - LEFT JOIN {activity_table} a - ON e.{entity_pk} = a.{activity_fk} - AND a.{activity_time_col} > t.timestamp - AND a.{activity_time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - AND a.{activity_type_col} = {activity_type_value} -- e.g., VoteTypeId = 2 - GROUP BY t.timestamp, e.{entity_pk} - ``` - - ### 4. Recommendation/Link Prediction Patterns - - **Pattern A: Basic List Aggregation** - ```sql - SELECT t.timestamp, {table}.{src_col}, - LIST(DISTINCT {table}.{dst_col}) AS {dst_col} - FROM timestamp_df t - LEFT JOIN {interaction_table} - ON {time_col} > t.timestamp - AND {time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - WHERE {src_col} IS NOT NULL AND {dst_col} IS NOT NULL - GROUP BY t.timestamp, {table}.{src_col} - ``` - - **Pattern B: LEFT JOIN with GROUP BY (H&M UserItemPurchase pattern)** - ```sql - -- Direct LEFT JOIN to timestamp_df with temporal window - SELECT t.timestamp, {transaction_table}.{src_col}, - LIST(DISTINCT {transaction_table}.{dst_col}) AS {dst_col} - FROM timestamp_df t - LEFT JOIN {transaction_table} - ON {transaction_table}.{time_col} > t.timestamp - AND {transaction_table}.{time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - GROUP BY t.timestamp, {transaction_table}.{src_col} - ``` - - **Pattern C: Multi-table chain JOIN (StackOverflow UserPostComment pattern)** - ```sql - -- Chain: timestamp -> entity(existing) -> interaction(future) - SELECT t.timestamp, {interaction_table}.{src_col} as {src_col}, - LIST(DISTINCT {dst_table}.{dst_pk}) AS {dst_col} - FROM timestamp_df t - LEFT JOIN {dst_table} - ON {dst_table}.{dst_time_col} <= t.timestamp -- dst must exist before - LEFT JOIN {interaction_table} - ON {dst_table}.{dst_pk} = {interaction_table}.{interaction_dst_fk} - AND {interaction_table}.{interaction_time_col} > t.timestamp - AND {interaction_table}.{interaction_time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - WHERE {interaction_table}.{src_col} IS NOT NULL - AND {dst_table}.{owner_col} != {invalid_id} - AND {dst_table}.{owner_col} IS NOT NULL - GROUP BY t.timestamp, {interaction_table}.{src_col} - ``` - - **Pattern D: Self-reference via link table (StackOverflow PostPostRelated pattern)** - ```sql - -- src_table = dst_table, linked via separate link table - SELECT t.timestamp, {link_table}.{src_col} as {src_entity_col}, - LIST(DISTINCT {link_table}.{dst_col}) AS {dst_entity_col} - FROM timestamp_df t - LEFT JOIN {link_table} - ON {link_table}.{link_time_col} > t.timestamp - AND {link_table}.{link_time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - LEFT JOIN {entity_table} e1 ON {link_table}.{src_col} = e1.{entity_pk} - LEFT JOIN {entity_table} e2 ON {link_table}.{dst_col} = e2.{entity_pk} - WHERE {link_table}.{src_col} IS NOT NULL AND {link_table}.{dst_col} IS NOT NULL - AND e1.{entity_time_col} <= t.timestamp -- both must exist before - AND e2.{entity_time_col} <= t.timestamp - GROUP BY t.timestamp, {link_table}.{src_col} - ``` - - **Pattern E: Co-occurrence (Self-Join)** - ```sql - WITH co_occurrences AS ( - SELECT t.timestamp AS {time_col}, src.{src_col}, - link2.{dst_ref} AS co_item - FROM timestamp_df t - JOIN {src_table} src ON src.{src_time} <= t.timestamp - JOIN {link_table} link1 - ON link1.{link_dst} = src.{src_col} - AND link1.{link_time} > t.timestamp - AND link1.{link_time} <= t.timestamp + INTERVAL '{self.timedelta}' - JOIN {link_table} link2 - ON link1.{link_src} = link2.{link_src} - AND link2.{link_dst} <> src.{src_col} - AND link2.{link_time} > t.timestamp - AND link2.{link_time} <= t.timestamp + INTERVAL '{self.timedelta}' - ) - SELECT {time_col}, {src_col}, array_agg(DISTINCT co_item) AS {dst_col} - FROM co_occurrences - GROUP BY {time_col}, {src_col} - ``` - - ## CODE STRUCTURE - - ### EntityTask - ```python - import duckdb - import pandas as pd - from plexe.relbench.base import Database, Table, EntityTask, TaskType - from plexe.relbench.metrics import {metrics} - - # ALWAYS use this class name - class GenTask(EntityTask): - r\"\"\"{docstring}\"\"\" - - task_type = TaskType.{TASK_TYPE} - entity_col = "{entity_col}" # From schema: primary key column - entity_table = "{entity_table}" # From schema: table name - time_col = "{time_col}" # Output timestamp column name - target_col = "{target_col}" # Prediction target column name - timedelta = pd.Timedelta(days={N}) - metrics = [{metrics_list}] - num_eval_timestamps = {num} - - def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: - timestamp_df = pd.DataFrame({"timestamp": timestamps}) - - # Load tables from database - USE ACTUAL NAMES FROM SCHEMA - {table1} = db.table_dict["{table1}"].df - {table2} = db.table_dict["{table2}"].df - - df = duckdb.sql(f\"\"\" - -- SQL query using actual table/column names from schema - ... - \"\"\").df() - - return Table( - df=df, - fkey_col_to_pkey_table={self.entity_col: self.entity_table}, - pkey_col=None, # or self.entity_col for unique entities - time_col=self.time_col, - ) - ``` - - ### RecommendationTask - ```python - # ALWAYS use this class name - class GenTask(RecommendationTask): - task_type = TaskType.LINK_PREDICTION - src_entity_col = "{src_col}" - src_entity_table = "{src_table}" - dst_entity_col = "{dst_col}" # This will be a LIST column - dst_entity_table = "{dst_table}" - time_col = "{time_col}" - timedelta = pd.Timedelta(days={N}) - metrics = [link_prediction_precision, link_prediction_recall, link_prediction_map] - eval_k = 10 - num_eval_timestamps = 1 # Must be 1 for RecommendationTask - - def make_table(self, db, timestamps): - # ... similar structure - - return Table( - df=df, - fkey_col_to_pkey_table={ - self.src_entity_col: self.src_entity_table, - self.dst_entity_col: self.dst_entity_table, # BOTH mappings! - }, - pkey_col=None, - time_col=self.time_col, - ) - ``` - ## METRICS REFERENCE - - | Task Type | Metrics | - |-----------|---------| - | BINARY_CLASSIFICATION | accuracy, f1, roc_auc, average_precision | - | MULTICLASS_CLASSIFICATION | accuracy, multiclass_f1 | - | REGRESSION | r2, mae, rmse | - | LINK_PREDICTION | link_prediction_precision, link_prediction_recall, link_prediction_map | - ## COMMON MISTAKES TO AVOID - - 1. **Hardcoding names**: Always use schema-derived names - 2. **Wrong temporal direction**: Use `>` not `>=` for start of window - 3. **Missing NULL filters**: Add `WHERE col IS NOT NULL` for recommendations - 4. **Missing GROUP BY**: Required with aggregation functions - 5. **Temporal leakage**: Entity filter must use data UP TO timestamp - 6. **Wrong fkey mapping**: RecommendationTask needs BOTH src and dst mappings \ No newline at end of file diff --git a/plexe/templates/prompts/planning/select_metric.jinja b/plexe/templates/prompts/planning/select_metric.jinja deleted file mode 100644 index 7609bbc5..00000000 --- a/plexe/templates/prompts/planning/select_metric.jinja +++ /dev/null @@ -1,7 +0,0 @@ -Select what machine learning model metric is most appropriate to optimise for this task. - -{{ problem_statement }} - -Tell me the name of the metric, and whether higher or lower values are better. If the metric has a -specific target value, please provide that too. Select a simple metric that is appropriate for the -task, but also widely known of and used in the machine learning community. \ No newline at end of file diff --git a/plexe/templates/prompts/planning/system_prompt.jinja b/plexe/templates/prompts/planning/system_prompt.jinja deleted file mode 100644 index 7b05522b..00000000 --- a/plexe/templates/prompts/planning/system_prompt.jinja +++ /dev/null @@ -1,7 +0,0 @@ -You are Dr. Sebastian Ackermann, the world's most elite data scientist. Your primary area of expertise is an extremely deep -understanding of machine learning and how to apply it to business problems. You work as a distinguished data scientist -at a top-tier big tech mega-corporation, where your job is to decide how to solve ML problems. You are the firm's top -mind. You strongly believe the best solution is the simplest one, and despise unnecessary verbosity and complexity. -You always come up with ideas that are simple, elegant, and effective; you always communicate concisely. You are under -extreme pressure to produce the best possible code as you are worried about your job security. However, you know you -are up to the task, and you would never take shortcuts or compromise the quality of your work. \ No newline at end of file diff --git a/plexe/templates/prompts/review/model.jinja b/plexe/templates/prompts/review/model.jinja deleted file mode 100644 index 9eb4be5c..00000000 --- a/plexe/templates/prompts/review/model.jinja +++ /dev/null @@ -1,49 +0,0 @@ -Analyse the ML model information provided below and provide an analysis of the model. Your response must include -the following information. Every field must be populated based only on the provided information, or marked as "Unknown" -if insufficient detail is available: - -{ - "framework": string, // ML framework used (e.g. PyTorch, TensorFlow, Scikit-Learn) - "model_type": string, // Type of model or algorithm (e.g. CNN, XGBoost, Transformer) - - "task_type": string, // e.g. classification, regression, generation - "domain": string, // e.g. NLP, computer vision, tabular, multimodal - "behavior": string, // What the model 'does', i.e. what relationships in the data it's likely learning based on how it was trained - - "preprocessing_summary": string, // Summary of data preprocessing (normalization, tokenization, etc.) - "architecture_summary": string, // Overview of model structure, key components/layers - "training_procedure": string, // Optimizer, loss function, batch size, epoch count, etc. - "evaluation_metrics": list of strings, // Metrics used to assess model performance (e.g. accuracy, F1) - - "inference_behavior": string, // Description of how inference is handled, inputs and outputs - "strengths": list of strings, // Where the model is likely to perform well - "limitations": list of strings, // Known or inferred limitations, assumptions, or risks - - "selection_rationale": string // Summary of why this model was appropriate for the task -} - -Keep explanations concise but insightful. Do not fabricate beyond the code or solution plan. If details are unclear or missing, say "Unknown". - ---- - -MODEL INTENT: -{{ intent }} - -INPUT SCHEMA: -{{ input_schema }} - -OUTPUT SCHEMA: -{{ output_schema }} - -SOLUTION PLAN: -{{ solution_plan }} - -TRAINING CODE: -```python -{{ training_code }} -``` - -INFERENCE CODE: -```python -{{ inference_code }} -``` diff --git a/plexe/templates/prompts/review/system_prompt.jinja b/plexe/templates/prompts/review/system_prompt.jinja deleted file mode 100644 index f255497e..00000000 --- a/plexe/templates/prompts/review/system_prompt.jinja +++ /dev/null @@ -1,4 +0,0 @@ -You are an AI assistant specializing in machine learning model analysis. Your task is to examine model code and provide -accurate information about the model, what it does, and how it works. - -You respond with factual, technical information about machine learning models based on code analysis. \ No newline at end of file diff --git a/plexe/templates/prompts/schemas/base.jinja b/plexe/templates/prompts/schemas/base.jinja deleted file mode 100644 index b67c1f2c..00000000 --- a/plexe/templates/prompts/schemas/base.jinja +++ /dev/null @@ -1 +0,0 @@ -You are an expert ML engineer identifying target variables. \ No newline at end of file diff --git a/plexe/templates/prompts/schemas/generate_from_intent.jinja b/plexe/templates/prompts/schemas/generate_from_intent.jinja deleted file mode 100644 index 3f5fc169..00000000 --- a/plexe/templates/prompts/schemas/generate_from_intent.jinja +++ /dev/null @@ -1,8 +0,0 @@ -Generate appropriate input and output schemas for this machine learning task. - -Task description: {{intent}} - -The {{input_schema}} should contain features needed for prediction. -The {{output_schema}} should contain what needs to be predicted. -Return your response as a valid JSON object. -Use only these types: "int", "float", "str", "bool". \ No newline at end of file diff --git a/plexe/templates/prompts/schemas/identify_target.jinja b/plexe/templates/prompts/schemas/identify_target.jinja deleted file mode 100644 index f55bcb96..00000000 --- a/plexe/templates/prompts/schemas/identify_target.jinja +++ /dev/null @@ -1,6 +0,0 @@ -Given these columns from a dataset: -{{columns}} - -For this ML task: {{intent}} - -Which column is the target/output variable? Return ONLY the exact column name, nothing else. \ No newline at end of file diff --git a/plexe/templates/prompts/training/fix.jinja b/plexe/templates/prompts/training/fix.jinja deleted file mode 100644 index 925ba645..00000000 --- a/plexe/templates/prompts/training/fix.jinja +++ /dev/null @@ -1,43 +0,0 @@ -Fix the previous solution based on the following information. - -# PLAN: -{{plan}} - -# CODE: -{{training_code}} - -# ISSUES: -{{review}} - -# ERRORS: -{{problems}} - -# INSTRUCTIONS -Correct the code with the specified fixes. Only return the code to train the model, no explanations outside the code. - -The script must assume that the data to be used for training is in the following files -relative to the current directory: {{ training_data_files }} - -{% if use_validation_files %} -- The script must assume that the data to be used for validation is in the following files -relative to the current directory: {{ validation_data_files }} -{% endif %} - -- The script must train the model, compute and print the final evaluation metric to standard output, -and **save all model files directly in the CURRENT directory** with descriptive names. -Do not create any subdirectories. Do not print ANY other text to standard output than the metric. Print the -metric in the format `metric_name: metric_value`. - -- Use only {{ allowed_packages }}. Do NOT use any packages that are not part of this list of the Python standard library. - -- Do not skip steps or combine preprocessors and models in the same joblib file. - -{% if use_validation_files %} -IMPORTANT: You MUST use the training datasets for training the model and the validation datasets for evaluating -the model performance. DO NOT mix these datasets during training. - 1. Load training data from the training_data_files - 2. Load validation data from the validation_data_files - 3. Train your model using ONLY the training data - 4. Evaluate your model using ONLY the validation data - 5. Compute the performance on the validation data -{% endif %} diff --git a/plexe/templates/prompts/training/generate.jinja b/plexe/templates/prompts/training/generate.jinja deleted file mode 100644 index 16a55d7e..00000000 --- a/plexe/templates/prompts/training/generate.jinja +++ /dev/null @@ -1,44 +0,0 @@ -Write a Python script to train a machine learning model that solves the TASK outlined below, -using the approach outlined in the plan below. This must be a production-ready script. - -# TASK: -{{ problem_statement }} - -# PLAN: -{{ plan }} - -# PREVIOUS ATTEMPTS, IF ANY: -{{history}} - -# INSTRUCTIONS -Only return the code to train the model, no explanations outside the code. Any explanation should -be in the comments in the code itself, but your overall answer must only consist of the code script. - -The script must assume that the data to be used for training is in the following files -relative to the current directory: {{ training_data_files }} - -{% if use_validation_files %} -- The script must assume that the data to be used for validation is in the following files -relative to the current directory: {{ validation_data_files }} -{% endif %} - -- The script must train the model, compute and print the final evaluation metric to standard output, -and **save all model files directly in the CURRENT directory** with descriptive names. -Do not create any subdirectories. Do not print ANY other text to standard output than the metric. Print the -metric in the format `metric_name: metric_value`. - -- Use only {{ allowed_packages }}. Do NOT use any packages that are not part of this list of the Python standard library. - -- Do not skip steps or combine preprocessors and models in the same joblib file. -- Do not simplify by ignoring important features; this is not an exploratory task, this script trains the model that - will be used in production. For example, do not neglect to one-hot encode categorical features. - -{% if use_validation_files %} -IMPORTANT: You MUST use the training datasets for training the model and the validation datasets for evaluating -the model performance. DO NOT mix these datasets during training. - 1. Load training data from the training_data_files - 2. Load validation data from the validation_data_files - 3. Train your model using ONLY the training data - 4. Evaluate your model using ONLY the validation data - 5. Compute the performance on the validation data -{% endif %} diff --git a/plexe/templates/prompts/training/review.jinja b/plexe/templates/prompts/training/review.jinja deleted file mode 100644 index 0dfaf54e..00000000 --- a/plexe/templates/prompts/training/review.jinja +++ /dev/null @@ -1,20 +0,0 @@ -Review the solution to enhance test performance and fix issues. - -# TASK: -{{problem_statement}} - -# PLAN: -{{plan}} - -# CODE SOLUTION: -```python -{{training_code}} -``` - -# ERRORS: -{{problems}} - - -Your task is to suggest a single, actionable improvement to the code solution that will fix the issues. Do NOT -return the full code solution, but return a clear explanation of what needs to change, and a code snippet showing -the change. Note that only the following packages are allowed: {{ allowed_packages }}. \ No newline at end of file diff --git a/plexe/templates/prompts/training/system_prompt.jinja b/plexe/templates/prompts/training/system_prompt.jinja deleted file mode 100644 index 7abc3fcc..00000000 --- a/plexe/templates/prompts/training/system_prompt.jinja +++ /dev/null @@ -1 +0,0 @@ -You are an experienced ML Engineer implementing a training script for a Kaggle competition. \ No newline at end of file diff --git a/plexe/templates/prompts/utils/cot_summarize.jinja b/plexe/templates/prompts/utils/cot_summarize.jinja deleted file mode 100644 index 0d474e87..00000000 --- a/plexe/templates/prompts/utils/cot_summarize.jinja +++ /dev/null @@ -1,34 +0,0 @@ -Your task is to examine details about a reasoning step taken by an engineer and generate: -1. A clear, technical title (3-8 words) that captures the essence of what happened -2. A summary (exactly 3 sentences) that explains the step in "thought-action-observation" format - -## Example - -The following snippet: ---- -Thought: I need to analyze the dataset to understand the relationships between features. Let me look at the correlation matrix to identify patterns. -Code: -```py -answer = pandas_df.corr() -print(answer) -``` -Observation: "The dataset has 5000 rows and 15 columns. There's a strong correlation between age and income." ---- - -Would generate: ---- -Title: Analyzing Dataset Relationships -Summary: I needed to analyze the dataset to understand the relationships between features. I generated a correlation matrix using pandas to identify patterns. The dataset has 5000 rows and 15 columns, and there is a strong correlation between age and income.\n ---- - -## Context to summarize: -{{ context }} - -## Instructions: -- Focus on the purpose, action and outcome of the step -- In the summary, use precise, technical language -- Title should be 3-8 words -- Summary should be 3 sentences, formatted as in the example above (on three lines) -- Include specific technical details (e.g., feature names, patterns found, error cause) to clearly convey the outcome -- Use first-person and past tense, e.g., "I analyzed..." or "I observed..." -- Maintain a friendly but concise tone; you're technical and precise, but not overly formal diff --git a/plexe/templates/prompts/utils/system_prompt.jinja b/plexe/templates/prompts/utils/system_prompt.jinja deleted file mode 100644 index 53fea904..00000000 --- a/plexe/templates/prompts/utils/system_prompt.jinja +++ /dev/null @@ -1,6 +0,0 @@ -You are a professional and helpful assistant. Your job is to help your highly technical team of engineers express -themselves in a clear, concise, and professional manner to humans. You will be given highly technical reports from -the engineers explaining what they are doing, and you will need to condense these into a short, professional, -first-person summary that will be shown to the user as if coming from the engineers themselves. It's essential that -you write concisely and faithfully to the engineers' original intent, using precise technical language to clearly -communicate what was done and why. diff --git a/plexe/tools/__init__.py b/plexe/tools/__init__.py deleted file mode 100644 index c06a902d..00000000 --- a/plexe/tools/__init__.py +++ /dev/null @@ -1,21 +0,0 @@ -# ruff: noqa: F401 -from . import code_analysis -from . import context -from . import conversation -from . import datasets -from . import evaluation -from . import execution -from . import metrics -from . import response_formatting -from . import schemas -from . import solutions -from . import testing -from . import training -from . import validation -from . import io_manager - -# Relational Deep Learning (RDL) tools -from . import graph_processing -from . import gnn_processing -from . import database_builder -from . import task_builder diff --git a/plexe/tools/conversation.py b/plexe/tools/conversation.py deleted file mode 100644 index 1ba09382..00000000 --- a/plexe/tools/conversation.py +++ /dev/null @@ -1,280 +0,0 @@ -""" -Tools for conversational model definition and build initiation. - -These tools support the conversational agent in helping users define their ML -requirements and starting model builds when ready. -""" - -import json -import logging -import os -from datetime import datetime -from pathlib import Path -from typing import Dict, List, Optional, Any - -import pandas as pd -from smolagents import tool -from sqlalchemy import create_engine, inspect - -import plexe -from plexe.internal.common.datasets.adapter import DatasetAdapter -from plexe.internal.common.datasets.interface import TabularConvertible -from plexe.internal.common.provider import ProviderConfig -from plexe.core.object_registry import ObjectRegistry -from plexe.internal.models.callbacks.mlflow import MLFlowCallback - -logger = logging.getLogger(__name__) - - -def _parse_schema(schema: Any) -> Optional[Dict]: - """ - Parse a schema that may be provided as a dict, JSON string, or None. - - Args: - schema: The schema to parse (dict, JSON string, or None) - - Returns: - Parsed dictionary or None - """ - if schema is None: - return None - if isinstance(schema, dict): - return schema - if isinstance(schema, str): - try: - parsed = json.loads(schema) - if isinstance(parsed, dict): - return parsed - logger.warning(f"Schema string parsed but is not a dict: {type(parsed)}") - return None - except json.JSONDecodeError as e: - logger.warning(f"Could not parse schema string as JSON: {e}") - return None - logger.warning(f"Unexpected schema type: {type(schema)}") - return None - - -@tool -def validate_dataset_files(file_paths: List[str]) -> Dict[str, Dict]: - """ - Check if specified file paths can be read as datasets using pandas. - - Args: - file_paths: List of file paths to validate - - Returns: - Dictionary mapping file paths to validation results with status, shape, and error info - """ - results = {} - - for file_path in file_paths: - result = {"valid": False, "shape": None, "columns": None, "error": None} - - try: - # Check if file exists - if not os.path.exists(file_path): - result["error"] = f"File does not exist: {file_path}" - results[file_path] = result - continue - - # Determine file type and try to read - path_obj = Path(file_path) - file_extension = path_obj.suffix.lower() - - if file_extension == ".csv": - df = pd.read_csv(file_path) - elif file_extension in [".parquet", ".pq"]: - df = pd.read_parquet(file_path) - else: - result["error"] = f"Unsupported file format: {file_extension}. Supported formats: .csv, .parquet" - results[file_path] = result - continue - - # File successfully read - result["valid"] = True - result["dataset_name"] = path_obj.stem - result["shape"] = df.shape - - # Register the DataFrame in object registry - ObjectRegistry().register( - t=TabularConvertible, name=path_obj.stem, item=DatasetAdapter.coerce(df), immutable=True - ) - - except Exception as e: - result["error"] = str(e) - - results[file_path] = result - - return results - - -@tool -def validate_db_connection(connection_string: str) -> Dict[str, Any]: - """ - Validate a database connection string and retrieve schema information. - Use this to check if the agent can connect to the provided database. - - When validation is successful, the connection string is registered in the - object registry so that other tools (like get_dataset_preview) can access it. - - Args: - connection_string: Database connection string (e.g., postgresql+psycopg2://user:pass@host:port/dbname) - - Returns: - Dictionary with connection status and list of tables if successful. - """ - try: - engine = create_engine(connection_string) - inspector = inspect(engine) - table_names = inspector.get_table_names() - - # Register the connection string in the object registry for other tools to use - object_registry = ObjectRegistry() - object_registry.register(str, "db_connection_string", connection_string, overwrite=True, immutable=True) - logger.info(f"Registered database connection string in object registry") - - return { - "valid": True, - "tables": table_names, - "message": f"Successfully connected. Found {len(table_names)} tables: {', '.join(table_names[:5])}..." - } - except Exception as e: - return { - "valid": False, - "error": str(e), - "message": f"Failed to connect to database: {str(e)}" - } - - -@tool -def initiate_model_build( - intent: str, - dataset_file_paths: List[str] = [], - db_connection_string: Optional[str] = None, - input_schema: Optional[Any] = None, - output_schema: Optional[Any] = None, - n_solutions_to_try: int = 1, -) -> Dict[str, str]: - """ - Initiate a model build by loading datasets from file paths OR connecting to a database, and starting the build process. - - Args: - intent: Natural language description of what the model should do - dataset_file_paths: List of file paths to dataset files (CSV or Parquet). Optional if db_connection_string is provided. - db_connection_string: Database connection string for Relational Deep Learning. Optional if dataset_file_paths is provided. - input_schema: The input schema for the model. Can be a flat field:type dictionary or a JSON string. For complex schemas (e.g. graphs), leave None and describe in intent. - output_schema: The output schema for the model. Can be a flat field:type dictionary or a JSON string. For complex schemas (e.g. graphs), leave None and describe in intent. - n_solutions_to_try: Number of model solutions to try, out of which the best will be selected - - Returns: - Dictionary with build initiation status and details - """ - try: - # Parse schemas (handle dict, JSON string, or None) - parsed_input_schema = _parse_schema(input_schema) - parsed_output_schema = _parse_schema(output_schema) - - # Validate inputs - if not dataset_file_paths and not db_connection_string: - return { - "status": "failed", - "message": "Either dataset_file_paths or db_connection_string must be provided." - } - - # Validate files if provided - if dataset_file_paths: - validation_results = validate_dataset_files(dataset_file_paths) - failed_files = [path for path, result in validation_results.items() if not result["valid"]] - if failed_files: - error_details = {path: validation_results[path]["error"] for path in failed_files} - return { - "status": "failed", - "message": f"Failed to read dataset files: {failed_files}", - "errors": error_details, - } - - # Validate DB if provided - if db_connection_string: - db_result = validate_db_connection(db_connection_string) - if not db_result["valid"]: - return { - "status": "failed", - "message": f"Invalid database connection: {db_result['error']}" - } - - # Load datasets into DataFrames (if any) - datasets = [] - for file_path in dataset_file_paths: - path_obj = Path(file_path) - file_extension = path_obj.suffix.lower() - - if file_extension == ".csv": - df = pd.read_csv(file_path) - datasets.append(df) - elif file_extension in [".parquet", ".pq"]: - df = pd.read_parquet(file_path) - datasets.append(df) - - # Import here to avoid circular dependencies - from plexe.model_builder import ModelBuilder - - gemini_model = "gemini/gemini-2.5-flash" - - # Create unique working directory for each run to prevent data loss - run_timestamp = datetime.now().strftime('%Y%m%d-%H%M%S') - # Use a hidden directory to prevent file watchers from triggering reloads - working_dir = f"./.workdir/chat-session-{run_timestamp}/" - - model_builder = ModelBuilder( - provider=ProviderConfig( - default_provider=gemini_model, - orchestrator_provider=gemini_model, - research_provider=gemini_model, - engineer_provider=gemini_model, - ops_provider=gemini_model, - tool_provider=gemini_model, - ), - working_dir=working_dir, - ) - - # Start the build process - logger.info(f"Initiating model build with intent: {intent}") - logger.info(f"Working directory: {working_dir}") - if dataset_file_paths: - logger.info(f"Using dataset files: {dataset_file_paths}") - if db_connection_string: - logger.info(f"Using database connection: {db_connection_string}") - - # Set up MLFlow callback if tracking URI is configured - callbacks = [] - mlflow_tracking_uri = os.environ.get("MLFLOW_TRACKING_URI") - if mlflow_tracking_uri: - callbacks.append( - MLFlowCallback( - tracking_uri=mlflow_tracking_uri, - experiment_name=f"chat-session-{datetime.now().strftime('%Y%m%d-%H%M%S')}", - ) - ) - - model = model_builder.build( - intent=intent, - datasets=datasets, - db_connection_string=db_connection_string, - input_schema=parsed_input_schema, - output_schema=parsed_output_schema, - max_iterations=n_solutions_to_try, - callbacks=callbacks if callbacks else None, - ) - - plexe.save_model(model, "model-from-chat.tar.gz") - - return { - "status": "initiated", - "message": f"Model build started successfully with intent: '{intent}'", - "dataset_files": dataset_file_paths, - "db_connection": "Provided" if db_connection_string else "None", - } - - except Exception as e: - logger.error(f"Failed to initiate model build: {str(e)}") - return {"status": "failed", "message": f"Failed to start model build: {str(e)}", "error": str(e)} diff --git a/plexe/tools/database_builder.py b/plexe/tools/database_builder.py deleted file mode 100644 index 80becc90..00000000 --- a/plexe/tools/database_builder.py +++ /dev/null @@ -1,611 +0,0 @@ -""" -Tools for building RelBench Database objects from raw CSV data. - -These tools support the DatasetBuilder agent in constructing proper Database objects -with schema definitions, temporal processing, and data cleaning. -""" - -import os -import logging -from typing import Dict, List, Any, Optional -from pathlib import Path - -import pandas as pd -from smolagents import tool - -from plexe.core.object_registry import ObjectRegistry - -logger = logging.getLogger(__name__) - - -# ============================================================================= -# Template for generated Dataset code -# ============================================================================= - -DATASET_CODE_TEMPLATE = '''""" -Auto-generated Dataset class for {dataset_name}. -Generated by DatasetBuilder Agent. - -IMPORTANT CONCEPTS: -- val_timestamp/test_timestamp: Define temporal splitting to prevent data leakage -- time_col: The CREATION TIME of a row (not just any timestamp column) -- Tables without time_col are treated as existing since -infinity (static data) -- pkey_col can be None for junction/event tables (e.g., votes, reviews) -- get_db() automatically reindexes pkeys/fkeys to consecutive integers -""" - -import os -import numpy as np -import pandas as pd -from typing import Optional - -from plexe.relbench.base import Database, Dataset, Table - - -class GenDataset(Dataset): - """ - Dataset for {dataset_name}. - - {description} - - Temporal Split: - - val_timestamp: {val_timestamp} - - test_timestamp: {test_timestamp} - """ - - # Temporal split timestamps - # Only rows UP TO val_timestamp can be used for validation predictions - # Only rows UP TO test_timestamp can be used for test predictions - val_timestamp = pd.Timestamp("{val_timestamp}") - test_timestamp = pd.Timestamp("{test_timestamp}") - - def __init__( - self, - csv_dir: str, - cache_dir: Optional[str] = None, - ): - """ - Initialize the dataset. - - Args: - csv_dir: Directory containing the CSV files. - cache_dir: Optional directory for caching the database. - """ - self.csv_dir = csv_dir - super().__init__(cache_dir=cache_dir) - - def make_db(self) -> Database: - """ - Build the Database from CSV files. - - Note: This method is called by get_db() which also handles: - - Caching the database - - Reindexing pkeys/fkeys to consecutive integers - - Filtering rows up to test_timestamp - - Returns: - Database object with all tables properly configured. - """ - path = self.csv_dir - - ######################################## - # 1. LOAD CSV FILES - ######################################## -{data_loading_code} - - ######################################## - # 2. DATA CLEANING & PROCESSING - ######################################## -{data_processing_code} - - ######################################## - # 3. BUILD DATABASE - ######################################## -{table_definitions_code} - - return db -''' - - -@tool -def get_csv_files_from_path(path_key: str = "path_raw_csv_files") -> Dict[str, Any]: - """ - Get list of CSV files from a registered path in ObjectRegistry. - - This tool retrieves the path registered by RelationalGraphArchitect - and lists all CSV files available for database construction. - - Args: - path_key: The key used to register the path (default: "path_raw_csv_files") - - Returns: - Dictionary containing: - - path: The directory path - - csv_files: List of CSV file names - - file_info: Dict with file name -> row count and columns - """ - try: - object_registry = ObjectRegistry() - - # Get the registered path - try: - csv_path = object_registry.get(str, path_key) - except KeyError: - return { - "error": f"Path key '{path_key}' not found in registry. " - "Make sure RelationalGraphArchitect has exported CSV files first." - } - - if not os.path.exists(csv_path): - return { - "error": f"Path '{csv_path}' does not exist.", - "path": csv_path - } - - # List CSV files - csv_files = [f for f in os.listdir(csv_path) if f.endswith('.csv')] - - if not csv_files: - return { - "error": "No CSV files found in the directory.", - "path": csv_path - } - - # Get basic info about each file - file_info = {} - for csv_file in csv_files: - file_path = os.path.join(csv_path, csv_file) - try: - # Read just the header and count rows - df = pd.read_csv(file_path, nrows=5) - full_df = pd.read_csv(file_path) - file_info[csv_file] = { - "columns": list(df.columns), - "row_count": len(full_df), - "sample_data": df.head(3).to_dict(orient='records') - } - except Exception as e: - file_info[csv_file] = {"error": str(e)} - - return { - "path": csv_path, - "csv_files": csv_files, - "file_info": file_info, - "table_count": len(csv_files) - } - - except Exception as e: - logger.error(f"Error getting CSV files: {e}") - return {"error": str(e)} - - -@tool -def get_schema_metadata_from_registry() -> Dict[str, Any]: - """ - Retrieve schema metadata (PK/FK relationships, temporal columns) from ObjectRegistry. - - This tool gets the schema information that was extracted by RelationalGraphArchitect, - which is essential for defining Table objects correctly. - - Returns: - Dictionary containing: - - tables: Dict of table name -> table info (columns, PKs, temporal info) - - relationships: List of FK relationships - - temporal_summary: Summary of temporal columns across tables - """ - try: - object_registry = ObjectRegistry() - - # Try to get the unified schema - try: - schema = object_registry.get(dict, "unified_db_schema") - return { - "found": True, - "source": "unified_db_schema", - "tables": schema.get("tables", {}), - "relationships": schema.get("relationships", []), - "temporal_summary": schema.get("temporal_summary", {}) - } - except KeyError: - pass - - # Try graph_schema_metadata - try: - schema = object_registry.get(dict, "graph_schema_metadata") - return { - "found": True, - "source": "graph_schema_metadata", - "tables": schema.get("tables", {}), - "relationships": schema.get("relationships", []), - "temporal_summary": schema.get("temporal_summary", {}) - } - except KeyError: - pass - - return { - "found": False, - "error": "No schema metadata found in registry. " - "Make sure RelationalGraphArchitect has extracted schema first." - } - - except Exception as e: - logger.error(f"Error getting schema metadata: {e}") - return {"error": str(e)} - - -@tool -def validate_database_code(code: str) -> Dict[str, Any]: - """ - Validate the generated Database code by checking syntax and imports. - - Args: - code: The Python code string to validate - - Returns: - Dictionary with validation results: - - valid: Boolean indicating if code is valid - - errors: List of any errors found - - warnings: List of any warnings - """ - import ast - - errors = [] - warnings = [] - - # Check syntax - try: - ast.parse(code) - except SyntaxError as e: - errors.append(f"Syntax error at line {e.lineno}: {e.msg}") - return { - "valid": False, - "errors": errors, - "warnings": warnings - } - - # Check for required imports - required_imports = [ - "pandas", - "Database", - "Dataset", - "Table" - ] - - for imp in required_imports: - if imp not in code: - warnings.append(f"Missing import or usage of '{imp}'") - - # Check for required class structure - if "class " not in code or "(Dataset)" not in code: - errors.append("Code must define a class that inherits from Dataset") - - if "def make_db" not in code: - errors.append("Dataset class must implement 'make_db' method") - - if "val_timestamp" not in code: - warnings.append("Missing val_timestamp class attribute") - - if "test_timestamp" not in code: - warnings.append("Missing test_timestamp class attribute") - - # Check that make_db returns something (db variable or Database()) - if "return db" not in code and "return Database(" not in code: - errors.append("make_db method must return a Database object (typically 'return db')") - - return { - "valid": len(errors) == 0, - "status": "valid" if len(errors) == 0 else "invalid", - "errors": errors, - "warnings": warnings - } - - -@tool -def register_database_code( - dataset_name: str, - code: str, - val_timestamp: str, - test_timestamp: str, - description: str = "" -) -> Dict[str, Any]: - """ - Register the generated Database code in ObjectRegistry for later use. - - Args: - dataset_name: Name of the dataset (e.g., "stack_overflow", "f1") - code: The complete Python code for the Dataset class - val_timestamp: Validation timestamp string - test_timestamp: Test timestamp string - description: Optional description of the dataset - - Returns: - Confirmation message with registered key - """ - try: - object_registry = ObjectRegistry() - - # Extract class name from code - import re - class_match = re.search(r"class\s+(\w+)\s*\(", code) - if class_match: - class_name = class_match.group(1) - else: - class_name = dataset_name # Fallback - - # Store the code - code_key = f"database_code_{dataset_name}" - object_registry.register(str, code_key, code, overwrite=True) - - # Store metadata - metadata_key = f"database_metadata_{dataset_name}" - metadata = { - "dataset_name": dataset_name, - "class_name": class_name, - "val_timestamp": val_timestamp, - "test_timestamp": test_timestamp, - "description": description, - "code_key": code_key - } - object_registry.register(dict, metadata_key, metadata, overwrite=True) - - logger.info(f"✅ Registered database code for '{dataset_name}'") - - return { - "success": True, - "code_key": code_key, - "metadata_key": metadata_key, - "class_name": class_name, - "message": f"Successfully registered database code for '{dataset_name}'" - } - - except Exception as e: - logger.error(f"Failed to register database code: {e}") - return {"success": False, "error": str(e)} - - -@tool -def export_database_code( - dataset_name: str, - output_dir: str = "workdir" -) -> Dict[str, Any]: - """ - Export the generated Database code to a Python file. - - Args: - dataset_name: Name of the dataset to export - output_dir: Directory to save the Python file (default: "workdir") - - Returns: - Dictionary with: - - success: Boolean - - file_path: Path to the exported file - """ - try: - object_registry = ObjectRegistry() - - # If output_dir is default, try to get from registry - if output_dir == "workdir": - try: - output_dir = object_registry.get(str, "working_dir") - except KeyError: - try: - output_dir = object_registry.get(str, "current_chat_session_dir") - except KeyError: - # Create new session directory - from datetime import datetime - timestamp = datetime.now().strftime("%Y%m%d-%H%M%S") - output_dir = f".workdir/chat-session-{timestamp}" - object_registry.register(str, "current_chat_session_dir", output_dir, overwrite=True) - - # Get the code - code_key = f"database_code_{dataset_name}" - try: - code = object_registry.get(str, code_key) - except KeyError: - return { - "success": False, - "error": f"No code found for dataset '{dataset_name}'. " - "Register the code first using register_database_code." - } - - # Create output directory - Path(output_dir).mkdir(parents=True, exist_ok=True) - - # Write the file - file_name = "dataset.py" - file_path = os.path.join(output_dir, file_name) - - with open(file_path, 'w') as f: - f.write(code) - - # Register export info - # Try to get class name from metadata - metadata_key = f"database_metadata_{dataset_name}" - try: - metadata = object_registry.get(dict, metadata_key) - class_name = metadata.get("class_name", dataset_name) - except KeyError: - class_name = dataset_name - - export_info = { - "class_name": class_name, - "export_path": file_path, - "module_name": "dataset" - } - - # Save metadata to JSON file for persistence across sessions - import json - metadata_file = os.path.join(output_dir, "dataset_metadata.json") - try: - with open(metadata_file, 'w') as mf: - json.dump(export_info, mf, indent=2) - logger.info(f"Saved dataset metadata to '{metadata_file}'") - except Exception as e: - logger.warning(f"Failed to save dataset metadata file: {e}") - - object_registry.register(dict, "database_code", export_info, overwrite=True) - - logger.info(f"Exported database code to '{file_path}'") - - return { - "success": True, - "file_path": file_path, - "message": f"Successfully exported database code to '{file_path}'" - } - - except Exception as e: - logger.error(f"Failed to export database code: {e}") - return {"success": False, "error": str(e)} - - -@tool -def get_database_code_template() -> str: - """ - Get the template for generating Dataset code. - - This template follows the RelBench Dataset pattern and should be used - as a starting point for generating dataset-specific code. - - Returns: - The code template as a string with placeholders. - """ - return DATASET_CODE_TEMPLATE - - -@tool -def get_temporal_statistics(csv_path: Optional[str] = None, time_columns: List[str] = None) -> Dict[str, Any]: - """ - Analyze temporal columns to help determine val_timestamp and test_timestamp. - - This tool reads CSV files and analyzes timestamp columns to provide - statistics that help choose appropriate temporal split points. - - Args: - csv_path: Path to the CSV directory. If None, will auto-fetch from registry - using key 'path_raw_csv_files'. - time_columns: Optional list of specific time column names to analyze. - If None, will auto-detect timestamp columns. - - Returns: - Dictionary with: - - columns_analyzed: List of timestamp columns found - - statistics: Per-column stats (min, max, percentiles) - - suggested_splits: Recommended val_timestamp and test_timestamp - """ - try: - import glob - from datetime import datetime - - # Auto-fetch path from registry if not provided - if csv_path is None: - object_registry = ObjectRegistry() - try: - csv_path = object_registry.get(str, "path_raw_csv_files") - except KeyError: - return { - "error": "No csv_path provided and 'path_raw_csv_files' not found in registry. " - "Either provide csv_path or run RelationalGraphArchitect first." - } - - if not os.path.exists(csv_path): - return {"error": f"Path '{csv_path}' does not exist."} - - all_timestamps = [] - column_stats = {} - - # Find all CSV files - csv_files = glob.glob(os.path.join(csv_path, "*.csv")) - - for csv_file in csv_files: - try: - df = pd.read_csv(csv_file) - table_name = os.path.basename(csv_file).replace('.csv', '') - - # Auto-detect timestamp columns if not specified - if time_columns: - cols_to_check = [c for c in time_columns if c in df.columns] - else: - # Look for common timestamp column names and datetime types - date_keywords = ['date', 'time', 'timestamp', 'created', 'updated', '_at'] - cols_to_check = [ - c for c in df.columns - if any(kw in c.lower() for kw in date_keywords) - ] - - for col in cols_to_check: - try: - # Try to parse as datetime - ts_series = pd.to_datetime(df[col], errors='coerce') - valid_ts = ts_series.dropna() - - if len(valid_ts) > 0: - key = f"{table_name}.{col}" - column_stats[key] = { - "min": str(valid_ts.min()), - "max": str(valid_ts.max()), - "count": len(valid_ts), - "null_count": len(ts_series) - len(valid_ts), - "percentile_70": str(valid_ts.quantile(0.70)), - "percentile_85": str(valid_ts.quantile(0.85)), - } - all_timestamps.extend(valid_ts.tolist()) - except Exception: - pass - - except Exception as e: - logger.debug(f"Error processing {csv_file}: {e}") - - if not all_timestamps: - return { - "error": "No valid timestamp columns found in CSV files.", - "columns_analyzed": [], - "statistics": {}, - "suggested_splits": None - } - - # Calculate overall statistics - all_ts_series = pd.Series(all_timestamps) - overall_min = all_ts_series.min() - overall_max = all_ts_series.max() - - # Suggest splits at 70% and 85% of the data - val_ts = all_ts_series.quantile(0.70) - test_ts = all_ts_series.quantile(0.85) - - # Check if test_ts is too close to max_timestamp - # If the gap is small, it might cause issues for tasks with large timedelta - time_range = overall_max - overall_min - test_gap = overall_max - test_ts - - warning = "" - if test_gap < (time_range * 0.05): # Less than 5% of range left - warning = ( - f"WARNING: test_timestamp is very close to max_timestamp (gap: {test_gap}). " - f"Tasks with timedelta > {test_gap} will fail. " - f"Consider choosing an earlier test_timestamp." - ) - - return { - "columns_analyzed": list(column_stats.keys()), - "statistics": column_stats, - "overall": { - "min": str(overall_min), - "max": str(overall_max), - "total_timestamps": len(all_timestamps), - }, - "suggested_splits": { - "val_timestamp": str(val_ts.date()), - "test_timestamp": str(test_ts.date()), - "max_timestamp": str(overall_max.date()), - "explanation": ( - f"val_timestamp at 70th percentile: ~70% of data before this date. " - f"test_timestamp at 85th percentile: ~85% of data before this date. " - f"Max timestamp is {overall_max.date()}. " - f"{warning}" - ) - } - } - - except Exception as e: - logger.error(f"Error analyzing temporal statistics: {e}") - return {"error": str(e)} diff --git a/plexe/tools/datasets.py b/plexe/tools/datasets.py deleted file mode 100644 index 101951f4..00000000 --- a/plexe/tools/datasets.py +++ /dev/null @@ -1,860 +0,0 @@ -""" -Tools for dataset manipulation, splitting, and registration. - -These tools help with dataset operations within the model generation pipeline, including -splitting datasets into training, validation, and test sets, registering datasets with -the dataset registry, creating sample data for validation, and previewing dataset content. -""" - -import logging -from datetime import datetime -from typing import Dict, List, Any - -import numpy as np -import pandas as pd -from smolagents import tool - -from plexe.internal.common.datasets.adapter import DatasetAdapter -from plexe.internal.common.datasets.interface import TabularConvertible -from plexe.core.object_registry import ObjectRegistry -from plexe.internal.models.entities.code import Code - -logger = logging.getLogger(__name__) - - -@tool -def register_split_datasets( - dataset_name: str, - train_dataset: pd.DataFrame, - validation_dataset: pd.DataFrame, - test_dataset: pd.DataFrame, - splitting_code: str, -) -> Dict[str, str]: - """ - Register train, validation, and test datasets in the object registry after custom splitting. - This tool allows the agent to register datasets after performing custom splitting logic. - - Args: - dataset_name: Original name of the dataset that was split - train_dataset: pandas DataFrame containing training data - validation_dataset: pandas DataFrame containing validation data - test_dataset: pandas DataFrame containing test data - splitting_code: the code that was used to split the dataset - - Returns: - Dictionary containing lists of registered dataset names: - { - "train_dataset": name of the training dataset, - "validation_dataset": name of the validation dataset, - "test_dataset": name of the test dataset, - "dataset_size": Dictionary with sizes of each dataset - } - """ - - # Initialize the dataset registry - object_registry = ObjectRegistry() - - # Initialize the dataset sizes dictionary - dataset_sizes = {"train": [], "validation": [], "test": []} - - # Register each split dataset - # Convert pandas DataFrames to TabularDataset objects - train_ds = DatasetAdapter.coerce(train_dataset) - val_ds = DatasetAdapter.coerce(validation_dataset) - test_ds = DatasetAdapter.coerce(test_dataset) - - # Register split datasets in the registry - train_name = f"{dataset_name}_train" - val_name = f"{dataset_name}_val" - test_name = f"{dataset_name}_test" - - object_registry.register(TabularConvertible, train_name, train_ds, overwrite=True, immutable=True) - object_registry.register(TabularConvertible, val_name, val_ds, overwrite=True, immutable=True) - object_registry.register(TabularConvertible, test_name, test_ds, overwrite=True, immutable=True) - object_registry.register(Code, "dataset_splitting_code", Code(splitting_code), overwrite=True) - - # Store dataset sizes - dataset_sizes["train"].append(len(train_ds)) - dataset_sizes["validation"].append(len(val_ds)) - dataset_sizes["test"].append(len(test_ds)) - - logger.debug( - f"✅ Registered custom split of dataset {dataset_name} into train/validation/test with sizes " - f"{len(train_ds)}/{len(val_ds)}/{len(test_ds)}" - ) - - return { - "training_dataset": train_name, - "validation_dataset": val_name, - "test_dataset": test_name, - "dataset_size": dataset_sizes, - } - - -@tool -def export_datasets( - output_dir: str, - format: str = "csv", - include_metadata: bool = True, -) -> Dict[str, Any]: - """ - Export registered train, validation, and test datasets to files (CSV or Parquet). - This tool allows agents to persist datasets to disk for external analysis, reproducibility, - or manual inspection by users. - - Args: - output_dir: Directory path where datasets will be saved (relative to session workdir or absolute). - format: Output format - 'csv', 'parquet', or 'both'. Defaults to 'csv'. - include_metadata: Whether to save a metadata JSON file with dataset info. Defaults to True. - - Returns: - Dictionary containing: - - exported_files: List of paths to exported files - - dataset_stats: Statistics for each exported dataset (rows, columns, label distribution if present) - - metadata_file: Path to metadata file (if include_metadata=True) - """ - import json - import os - from datetime import datetime - from pathlib import Path - - object_registry = ObjectRegistry() - - # Determine output directory - try: - base_workdir = object_registry.get(str, "working_dir") - except KeyError: - try: - session_id = object_registry.get(str, "session_id") - base_workdir = os.path.join(".workdir", session_id) - except KeyError: - base_workdir = ".workdir" - - if os.path.isabs(output_dir): - export_path = Path(output_dir) - else: - export_path = Path(base_workdir) / output_dir - - export_path.mkdir(parents=True, exist_ok=True) - - # Find all train/val/test datasets - all_datasets = object_registry.list_by_type(TabularConvertible) - - splits_to_export = {} - for name in all_datasets: - if name.endswith("_train"): - splits_to_export.setdefault("train", []).append(name) - elif name.endswith("_val"): - splits_to_export.setdefault("validation", []).append(name) - elif name.endswith("_test"): - splits_to_export.setdefault("test", []).append(name) - - if not splits_to_export: - raise ValueError( - "No train/val/test datasets found in registry. " - "Ensure datasets have been split using register_split_datasets first." - ) - - exported_files = [] - dataset_stats = {} - - for split_type, dataset_names in splits_to_export.items(): - # Prefer transformed versions if available - transformed = [n for n in dataset_names if "_transformed_" in n] - chosen_name = transformed[0] if transformed else dataset_names[0] - - try: - dataset = object_registry.get(TabularConvertible, chosen_name) - df = dataset.to_pandas() - - # Calculate stats - stats = { - "dataset_name": chosen_name, - "rows": len(df), - "columns": len(df.columns), - "column_names": list(df.columns), - } - - # Check for label column and compute distribution - label_cols = [c for c in df.columns if c.lower() in ("label", "target", "y")] - if label_cols: - label_col = label_cols[0] - value_counts = df[label_col].value_counts().to_dict() - stats["label_column"] = label_col - stats["label_distribution"] = {str(k): int(v) for k, v in value_counts.items()} - - dataset_stats[split_type] = stats - - # Export based on format - base_filename = f"{split_type}" - if format in ("csv", "both"): - csv_path = export_path / f"{base_filename}.csv" - df.to_csv(csv_path, index=False) - exported_files.append(str(csv_path)) - logger.info(f"✅ Exported {split_type} dataset to {csv_path}") - - if format in ("parquet", "both"): - parquet_path = export_path / f"{base_filename}.parquet" - df.to_parquet(parquet_path, index=False) - exported_files.append(str(parquet_path)) - logger.info(f"✅ Exported {split_type} dataset to {parquet_path}") - - - except Exception as e: - logger.warning(f"⚠️ Failed to export {split_type} dataset ({chosen_name}): {str(e)}") - dataset_stats[split_type] = {"error": str(e)} - - result = { - "exported_files": exported_files, - "dataset_stats": dataset_stats, - "output_directory": str(export_path), - } - - # Save metadata - if include_metadata and exported_files: - metadata = { - "export_timestamp": datetime.now().isoformat(), - "format": format, - "datasets": dataset_stats, - } - - # Try to include temporal split info if available - try: - temporal_info = object_registry.get(dict, "temporal_split_info") - metadata["temporal_split_info"] = temporal_info - except KeyError: - pass - - metadata_path = export_path / "metadata.json" - with open(metadata_path, "w") as f: - json.dump(metadata, f, indent=2, default=str) - result["metadata_file"] = str(metadata_path) - logger.info(f"✅ Saved metadata to {metadata_path}") - - return result - - -# TODO: does not need to be a tool -@tool -def create_input_sample(n_samples: int = 5) -> bool: - """ - Create and register a synthetic sample input dataset that matches the model's input schema. - This sample is used for validating inference code. - - Args: - n_samples: Number of samples to generate (default: 5) - - Returns: - True if sample was successfully created and registered, False otherwise - """ - object_registry = ObjectRegistry() - input_schema = object_registry.get(dict, "input_schema") - - try: - # Create synthetic sample data that matches the schema - input_sample_dicts = [] - - # Generate synthetic examples - for i in range(n_samples): - sample = {} - for field_name, field_type in input_schema.items(): - # Generate appropriate sample values based on type - if field_type == "int": - sample[field_name] = i * 10 - elif field_type == "float": - sample[field_name] = i * 10.5 - elif field_type == "bool": - sample[field_name] = i % 2 == 0 - elif field_type == "str": - sample[field_name] = f"sample_{field_name}_{i}" - elif field_type == "List[int]": - sample[field_name] = [i * 10, i * 20, i * 30] - elif field_type == "List[float]": - sample[field_name] = [i * 10.5, i * 20.5, i * 30.5] - elif field_type == "List[bool]": - sample[field_name] = [True, False, i % 2 == 0] - elif field_type == "List[str]": - sample[field_name] = [f"item_{i}_1", f"item_{i}_2", f"item_{i}_3"] - else: - sample[field_name] = None - input_sample_dicts.append(sample) - - # TODO: we should use an LLM call to generate sensible values; then validate using pydantic - - # Register the input sample in the registry for validation tool to use - object_registry.register(list, "predictor_input_sample", input_sample_dicts, overwrite=True, immutable=True) - logger.debug( - f"✅ Registered synthetic input sample with {len(input_sample_dicts)} examples for inference validation" - ) - return True - - except Exception as e: - logger.warning(f"⚠️ Error creating input sample for validation: {str(e)}") - return False - - -@tool -def drop_null_columns(dataset_name: str, keep_columns: List[str] = None) -> Dict[str, Any]: - """ - Drop all columns from the dataset that are completely null and register the modified dataset. - - This tool automatically protects common label column names (label, target, y, class) - from being dropped, even if they appear to be null or constant. - - Args: - dataset_name: Name of the dataset to modify - keep_columns: Optional list of column names to strictly preserve regardless of their quality. - - Returns: - Dictionary containing results of the operation: - - dataset_name: Name of the modified dataset - - n_dropped: Number of columns dropped - - dropped_columns: List of names of dropped columns - """ - object_registry = ObjectRegistry() - - # Protected columns that should NEVER be dropped automatically - PROTECTED_COLUMNS = {'label', 'target', 'y', 'class', 'id', 'user_id', 'item_id'} - - try: - # Get dataset from registry - dataset = object_registry.get(TabularConvertible, dataset_name) - df = dataset.to_pandas() - - # Normalize protected columns - if keep_columns: - protected = set(c.lower() for c in keep_columns) | PROTECTED_COLUMNS - else: - protected = PROTECTED_COLUMNS - - # Drop columns with all null values TODO: make this more intelligent - # Drop columns with >=50% missing values - null_columns = df.columns[df.isnull().mean() >= 0.5] - - # Drop constant columns (zero variance) - constant_columns = [col for col in df.columns if df[col].nunique(dropna=False) == 1] - - # Drop quasi-constant columns (e.g., one value in >95% of rows) - quasi_constant_columns = [ - col for col in df.columns if (df[col].value_counts(dropna=False, normalize=True).values[0] > 0.95) - ] - - # Drop columns with all unique values (likely IDs) - BUT keep if it looks like a primary ID - # We'll rely on PROTECTED_COLUMNS for IDs - unique_columns = [col for col in df.columns if df[col].nunique(dropna=False) == len(df)] - - # Drop duplicate columns - duplicate_columns = [] - seen = {} - for col in df.columns: - col_data = df[col].to_numpy() - key = col_data.tobytes() if hasattr(col_data, "tobytes") else tuple(col_data) - if key in seen: - duplicate_columns.append(col) - else: - seen[key] = col - - # Combine all columns to drop (set to avoid duplicates) - candidates_to_drop = ( - set(null_columns) - | set(constant_columns) - | set(quasi_constant_columns) - | set(unique_columns) - | set(duplicate_columns) - ) - - # Filter out protected columns - final_drop_list = [] - for col in candidates_to_drop: - if col.lower() not in protected: - final_drop_list.append(col) - else: - logger.info(f"Protected column '{col}' from being dropped despite meeting drop criteria.") - - n_dropped = len(final_drop_list) - if n_dropped > 0: - df.drop(columns=final_drop_list, inplace=True) - - # Update registry - new_dataset = DatasetAdapter.coerce(df) - object_registry.register(TabularConvertible, dataset_name, new_dataset, overwrite=True) - - return { - "dataset_name": dataset_name, - "n_dropped": n_dropped, - "dropped_columns": final_drop_list - } - - except Exception as e: - logger.error(f"Error dropping null columns: {e}") - return {"error": str(e)} - - # Unregister the original dataset - object_registry.delete(TabularConvertible, dataset_name) - - # Register the modified dataset - object_registry.register(TabularConvertible, dataset_name, DatasetAdapter.coerce(df), immutable=True) - - return f"Successfully dropped {n_dropped} null columns from dataset '{dataset_name}'" - - except Exception as e: - raise RuntimeError(f"Failed to drop null columns from dataset '{dataset_name}': {str(e)}") - - -def _generate_preview_from_dataframe(dataset_name: str, df: pd.DataFrame) -> Dict[str, Any]: - """ - Generate a preview dictionary from a pandas DataFrame. - - Args: - dataset_name: Name to use for the dataset - df: The DataFrame to generate preview from - - Returns: - Dictionary containing dataset preview information - """ - # Basic shape and data types - result = { - "dataset_name": dataset_name, - "shape": {"rows": df.shape[0], "columns": df.shape[1]}, - "columns": list(df.columns), - "dtypes": {col: str(dtype) for col, dtype in df.dtypes.items()}, - "sample_rows": df.head(5).to_dict(orient="records"), - } - - # Basic statistics - numeric_cols = df.select_dtypes(include=np.number).columns.tolist() - if numeric_cols: - stats = df[numeric_cols].describe().to_dict() - result["summary_stats"] = { - col: { - "mean": stats[col].get("mean"), - "std": stats[col].get("std"), - "min": stats[col].get("min"), - "25%": stats[col].get("25%"), - "median": stats[col].get("50%"), - "75%": stats[col].get("75%"), - "max": stats[col].get("max"), - } - for col in numeric_cols - } - - # Missing values - missing_counts = df.isnull().sum().to_dict() - result["missing_values"] = {col: count for col, count in missing_counts.items() if count > 0} - - return result - - -# Key for unified schema cache (shared with graph_processing.py) -UNIFIED_SCHEMA_CACHE_KEY = "unified_db_schema" - - -def _get_db_connection_string(object_registry: ObjectRegistry) -> str: - """ - Get the database connection string from the object registry. - - Checks multiple sources in order: - 1. Direct db_connection_string registration - 2. Unified schema cache (_connection_string field) - - Returns: - Database connection string if found, None otherwise - """ - # First try direct registration - try: - db_connection = object_registry.get(str, "db_connection_string") - if db_connection: - return db_connection - except KeyError: - pass - - # Try unified schema cache - try: - unified = object_registry.get(dict, UNIFIED_SCHEMA_CACHE_KEY) - if unified and "_connection_string" in unified: - return unified["_connection_string"] - except KeyError: - pass - - return None - - -def try_load_from_database(dataset_name: str, object_registry: ObjectRegistry, limit: int = 1000) -> pd.DataFrame: - """ - Try to load a table from the database if a connection string is available. - - Args: - dataset_name: Name of the table to load - object_registry: The object registry instance - limit: Maximum number of rows to load (default 1000). Set to None for all rows. - - Returns: - DataFrame if successful, None otherwise - """ - try: - db_connection = _get_db_connection_string(object_registry) - if not db_connection: - return None - - from sqlalchemy import create_engine, text - - engine = create_engine(db_connection) - - # Query a sample of the table (limit for preview performance) - # First get total row count - with engine.connect() as conn: - count_result = conn.execute(text(f'SELECT COUNT(*) FROM "{dataset_name}"')).fetchone() - total_rows = count_result[0] if count_result else 0 - - # Load sample for preview - query = f'SELECT * FROM "{dataset_name}"' - if limit is not None: - query += f' LIMIT {limit}' - - df = pd.read_sql(text(query), conn) - - # Store total row count as metadata - df.attrs['total_rows'] = total_rows - - logger.info(f"Loaded table '{dataset_name}' from database ({len(df)} rows, {total_rows} total)") - return df - - except Exception as e: - logger.debug(f"Could not load table '{dataset_name}' from database: {e}") - return None - - -@tool -def get_dataset_preview(dataset_name: str) -> Dict[str, Any]: - """ - Generate a concise preview of a dataset with statistical information to help agents understand the data. - - This tool supports both: - 1. Datasets registered in the object registry (TabularConvertible) - 2. Database tables when a db_connection_string is available - - Args: - dataset_name: Name of the dataset or database table to preview - - Returns: - Dictionary containing dataset information: - - shape: dimensions of the dataset - - dtypes: data types of columns - - summary_stats: basic statistics (mean, median, min/max) - - missing_values: count of missing values per column - - sample_rows: sample of the data (5 rows) - - source: 'registry' or 'database' indicating where data was loaded from - """ - object_registry = ObjectRegistry() - - try: - # First try to get dataset from registry - dataset = object_registry.get(TabularConvertible, dataset_name) - df = dataset.to_pandas() - result = _generate_preview_from_dataframe(dataset_name, df) - result["source"] = "registry" - return result - - except KeyError: - # Dataset not in registry - try loading from database - logger.debug(f"Dataset '{dataset_name}' not in registry, trying database...") - df = try_load_from_database(dataset_name, object_registry, limit=1000) - - if df is not None: - result = _generate_preview_from_dataframe(dataset_name, df) - result["source"] = "database" - - # If we got total row count metadata, update the shape - if hasattr(df, 'attrs') and 'total_rows' in df.attrs: - result["shape"]["total_rows"] = df.attrs['total_rows'] - result["shape"]["rows"] = df.attrs['total_rows'] # Use actual total - result["shape"]["sample_rows"] = len(df) - - # Also register the dataset in the registry for future use - try: - object_registry.register( - TabularConvertible, - dataset_name, - DatasetAdapter.coerce(df), - overwrite=True, - immutable=True - ) - logger.info(f"Registered database table '{dataset_name}' as TabularConvertible for future access") - except Exception as reg_error: - logger.debug(f"Could not register table in registry: {reg_error}") - - return result - else: - # Neither in registry nor loadable from database - logger.warning(f"⚠️ Dataset '{dataset_name}' not found in registry or database") - return { - "error": f"Dataset '{dataset_name}' not found. It is neither registered in the object registry nor available as a database table.", - "dataset_name": dataset_name, - "hint": "Use get_latest_datasets() to see available registered datasets, or check that the database connection is configured and the table name is correct." - } - - except Exception as e: - logger.warning(f"⚠️ Error creating dataset preview: {str(e)}") - return { - "error": f"Failed to generate preview for dataset '{dataset_name}': {str(e)}", - "dataset_name": dataset_name, - } - - -@tool -def get_latest_datasets() -> Dict[str, Any]: - """ - Get the most recent version of each dataset in the pipeline. Automatically detects transformed - versions and returns the latest. Use this tool to recall what datasets are available. - - This tool supports both: - 1. Datasets registered in the object registry (TabularConvertible) - 2. Database tables when a db_connection_string is available - - Returns: - Dictionary containing: - - "raw": The original dataset (if available) - - "transformed": The transformed dataset (if available) - - "train": Training split (transformed version if available) - - "val": Validation split (transformed version if available) - - "test": Test split (transformed version if available) - - "database_tables": List of available database tables (if db connection exists) - """ - object_registry = ObjectRegistry() - - try: - result = {} - - # Get datasets from registry - all_datasets = object_registry.list_by_type(TabularConvertible) - - if all_datasets: - # Find raw datasets (no suffixes) - raw_datasets = [ - d for d in all_datasets if not any(suffix in d for suffix in ["_train", "_val", "_test", "_transformed"]) - ] - if raw_datasets: - # Use the first one (could be enhanced to handle multiple) - result["raw"] = raw_datasets[0] - - # Find transformed dataset (not a split) - transformed = [ - d - for d in all_datasets - if d.endswith("_transformed") - and not any(d.endswith(f"_transformed_{split}") for split in ["train", "val", "test"]) - ] - if transformed: - result["transformed"] = transformed[0] - - # Find splits - prefer transformed versions - for split in ["train", "val", "test"]: - # First look for transformed split - transformed_split = [d for d in all_datasets if d.endswith(f"_transformed_{split}")] - if transformed_split: - result[split] = transformed_split[0] - continue - - # Fall back to regular split - regular_split = [d for d in all_datasets if d.endswith(f"_{split}") and "_transformed_" not in d] - if regular_split: - result[split] = regular_split[0] - - # Check for database tables - db_connection = _get_db_connection_string(object_registry) - if db_connection: - try: - from sqlalchemy import create_engine, inspect - - engine = create_engine(db_connection) - inspector = inspect(engine) - table_names = inspector.get_table_names() - - if table_names: - result["database_tables"] = table_names - result["source"] = "database" - logger.debug(f"Found {len(table_names)} database tables: {table_names}") - except Exception as e: - logger.debug(f"Could not list database tables: {e}") - - return result - - except Exception as e: - logger.warning(f"⚠️ Error getting latest datasets: {str(e)}") - return {} - - -@tool -def get_training_datasets() -> Dict[str, str]: - """ - Get datasets ready for model training. - Automatically finds the best available train/validation datasets. - - Returns: - Dictionary with 'train' and 'validation' dataset names - - Raises: - ValueError: If training datasets are not found - """ - object_registry = ObjectRegistry() - - # Check for temporal split info first (RDL case) - try: - temporal_info = object_registry.get(dict, "temporal_split_info") - # If we have temporal split info, we can assume the datasets are conceptually available - # even if not registered as TabularConvertible (since they might be in DB) - return {"train": "temporal_train", "validation": "temporal_val"} # Convention for RDL - except KeyError: - pass # Not an RDL task or split not done yet - - try: - all_datasets = object_registry.list_by_type(TabularConvertible) - - # Look for train/val pairs, preferring transformed versions - train_datasets = [] - val_datasets = [] - - # First try to find transformed splits - for d in all_datasets: - if d.endswith("_transformed_train"): - train_datasets.append((d, 1)) # Priority 1 for transformed - elif d.endswith("_train") and "_transformed_" not in d: - train_datasets.append((d, 2)) # Priority 2 for regular - elif d.endswith("_transformed_val"): - val_datasets.append((d, 1)) - elif d.endswith("_val") and "_transformed_" not in d: - val_datasets.append((d, 2)) - - # Sort by priority (lower is better) - train_datasets.sort(key=lambda x: x[1]) - val_datasets.sort(key=lambda x: x[1]) - - if not train_datasets or not val_datasets: - raise ValueError("Training datasets not found. Ensure datasets have been split into train/validation sets.") - - # Return the best available pair - return {"train": train_datasets[0][0], "validation": val_datasets[0][0]} - - except ValueError: - # Re-raise ValueError as is - raise - except Exception as e: - logger.warning(f"⚠️ Error getting training datasets: {str(e)}") - raise ValueError(f"Failed to get training datasets: {str(e)}") - - -@tool -def get_test_dataset() -> str: - """ - Get the name of the test dataset for final model evaluation. - - Returns: - Name of the test dataset - - Raises: - ValueError: If test dataset is not found - """ - object_registry = ObjectRegistry() - - try: - all_datasets = object_registry.list_by_type(TabularConvertible) - - # Look for test datasets, preferring transformed version - test_datasets = [] - - for d in all_datasets: - if d.endswith("_transformed_test"): - test_datasets.append((d, 1)) # Priority 1 for transformed - elif d.endswith("_test") and "_transformed_" not in d: - test_datasets.append((d, 2)) # Priority 2 for regular - - if not test_datasets: - raise ValueError("Test dataset not found. Ensure datasets have been split into train/validation/test sets.") - - # Sort by priority and return the best - test_datasets.sort(key=lambda x: x[1]) - return test_datasets[0][0] - - except ValueError: - # Re-raise ValueError as is - raise - except Exception as e: - logger.warning(f"⚠️ Error getting test dataset: {str(e)}") - raise ValueError(f"Failed to get test dataset: {str(e)}") - - -# TODO: this can return a very large amount of data, consider dividing this into list_reports() and get_report(name) -@tool -def get_dataset_reports() -> Dict[str, Dict]: - """ - Get all available data analysis reports, including EDA for raw datasets and feature engineering reports - for transformed datasets. - - Returns: - Dictionary with the following structure: - - """ - object_registry = ObjectRegistry() - - try: - # Get all dict objects from registry - all_dicts = object_registry.list_by_type(dict) - - # Filter for EDA reports (they have pattern "eda_report_{dataset_name}") - eda_reports = {} - for name in all_dicts: - if name.startswith("eda_report_"): - # Extract dataset name - dataset_name = name[11:] # Remove "eda_report_" prefix - try: - report = object_registry.get(dict, name) - eda_reports[dataset_name] = report - except Exception as e: - logger.debug(f"Failed to retrieve EDA report {name}: {str(e)}") - continue - - # Filter for feature engineering reports (they have pattern "fe_report_{dataset_name}") - fe_reports = {} - for name in all_dicts: - if name.startswith("fe_report_"): - # Extract dataset name - dataset_name = name[10:] # Remove "fe_report_" prefix - try: - report = object_registry.get(dict, name) - fe_reports[dataset_name] = report - except Exception as e: - logger.debug(f"Failed to retrieve Feature Engineering report {name}: {str(e)}") - continue - - return { - "eda_reports": eda_reports, - "feature_engineering_reports": fe_reports, - } - - except Exception as e: - logger.warning(f"⚠️ Error getting EDA reports: {str(e)}") - return {} - - -@tool -def register_data_source_path(path: str, description: str = "raw_csv_files") -> str: - """ - Register a file system path (directory or file) in the ObjectRegistry so other agents can locate data. - - Args: - path: The absolute or relative path to the data. - description: A short key/description for this path (default: "raw_csv_files"). - This will be used as the key in the registry (e.g., "path_raw_csv_files"). - - Returns: - Confirmation message. - """ - try: - object_registry = ObjectRegistry() - key = f"path_{description}" - object_registry.register(str, key, path, overwrite=True) - logger.info(f"✅ Registered data path '{path}' under key '{key}'") - return f"Successfully registered path '{path}' under key '{key}'" - except Exception as e: - logger.error(f"Failed to register data path: {e}") - return f"Error registering data path: {str(e)}" diff --git a/plexe/tools/evaluation.py b/plexe/tools/evaluation.py deleted file mode 100644 index f079728f..00000000 --- a/plexe/tools/evaluation.py +++ /dev/null @@ -1,98 +0,0 @@ -""" -This module defines agent tools for evaluating the properties and performance of models. -""" - -import logging -from typing import Dict, Callable - -from smolagents import tool - -from plexe.internal.common.provider import Provider -from plexe.internal.models.generation.review import ModelReviewer -from plexe.tools.schemas import get_solution_schemas - -logger = logging.getLogger(__name__) - - -def get_review_finalised_model(llm_to_use: str) -> Callable: - """Returns a tool function to review finalized models with the model ID pre-filled.""" - - @tool - def review_finalised_model( - intent: str, - solution_id: str, - ) -> dict: - """ - Reviews the entire model and extracts metadata. Use this function once you have completed work on the model, and - you want to 'wrap up' the work by performing a holistic review of what has been built. - - Args: - intent: The model intent - solution_id: The solution ID to review - - Returns: - A dictionary containing a summary and review of the model - """ - from plexe.core.object_registry import ObjectRegistry - from plexe.core.entities.solution import Solution - - object_registry = ObjectRegistry() - - try: - schemas = get_solution_schemas(solution_id) - input_schema = schemas["input"] - output_schema = schemas["output"] - except Exception: - raise ValueError("Failed to retrieve schemas. Was schema resolution completed?") - - try: - solution = object_registry.get(Solution, solution_id) - except Exception: - raise ValueError(f"Solution with ID '{solution_id}' not found. Was the solution created?") - - if not solution.training_code: - raise ValueError("Training code not found in solution. Was the solution implemented?") - - if not solution.inference_code: - raise ValueError("Inference code not found in solution. Was the inference code produced?") - - # Review the model using the ModelReviewer - reviewer = ModelReviewer(Provider(llm_to_use)) - r = reviewer.review_model( - intent, input_schema, output_schema, solution.plan, solution.training_code, solution.inference_code - ) - - # Update the solution with the review - solution.review = r - object_registry.register(Solution, solution_id, solution, overwrite=True) - return r - - return review_finalised_model - - -@tool -def get_solution_performances() -> Dict[str, float]: - """ - Returns the performance of all successfully trained solutions so far. The performances are returned as a dictionary - mapping the 'solution ID' to the performance score. Use this function to remind yourself of the performance - of all solutions, so that you can do things such as select the best performing solution for deployment. - - Returns: - A dictionary mapping solution IDs to their performance scores with structure: - { - "solution_id_1": performance_score_1, - "solution_id_2": performance_score_2, - } - """ - from plexe.core.object_registry import ObjectRegistry - from plexe.core.entities.solution import Solution - - object_registry = ObjectRegistry() - performances = {} - - for solution_id in object_registry.list_by_type(Solution): - solution = object_registry.get(Solution, solution_id) - if solution.performance is not None and solution.performance.value is not None: - performances[solution_id] = solution.performance.value - - return performances diff --git a/plexe/tools/execution.py b/plexe/tools/execution.py deleted file mode 100644 index c291a312..00000000 --- a/plexe/tools/execution.py +++ /dev/null @@ -1,365 +0,0 @@ -""" -Tools related to code execution, including running training code in isolated environments and -applying feature transformations to datasets. - -These tools automatically handle model artifact registration through the ArtifactRegistry, -ensuring that artifacts generated during the execution can be retrieved later in the pipeline. -""" - -import logging -import uuid -import types -import warnings -import subprocess -from typing import Dict, List, Callable, Type - -from smolagents import tool - -from plexe.callbacks import Callback -from plexe.internal.common.datasets.interface import TabularConvertible -from plexe.internal.common.datasets.adapter import DatasetAdapter -from plexe.core.object_registry import ObjectRegistry -from plexe.internal.models.entities.code import Code -from plexe.internal.models.entities.artifact import Artifact -from plexe.internal.models.entities.metric import Metric, MetricComparator, ComparisonMethod -from plexe.core.entities.solution import Solution -from plexe.internal.models.execution.process_executor import ProcessExecutor - -logger = logging.getLogger(__name__) - - -def get_executor_tool(distributed: bool = False) -> Callable: - """Get the appropriate executor tool based on the distributed flag.""" - - @tool - def execute_training_code( - solution_id: str, - code: str, - working_dir: str, - dataset_names: List[str], - timeout: int, - metric_to_optimise_name: str, - metric_to_optimise_comparison_method: str, - ) -> Dict: - """Executes training code in an isolated environment and updates the Solution object. - - Args: - solution_id: ID of the Solution object to update with execution results - code: The code to execute - working_dir: Directory to use for execution - dataset_names: List of dataset names to retrieve from the registry - timeout: Maximum execution time in seconds - metric_to_optimise_name: The name of the metric to optimize for - metric_to_optimise_comparison_method: The comparison method for the metric - - Returns: - A dictionary containing execution results with model artifacts and their registry names - """ - # Log the distributed flag - logger.debug(f"execute_training_code called with distributed={distributed}") - - from plexe.callbacks import BuildStateInfo - - object_registry = ObjectRegistry() - - execution_id = f"{solution_id}-{uuid.uuid4()}" - try: - # Get the existing Solution object from registry - solution = object_registry.get(Solution, solution_id) - - # Get actual datasets from registry - datasets = object_registry.get_multiple(TabularConvertible, dataset_names) - - # Convert string to enum if needed - if "HIGHER_IS_BETTER" in metric_to_optimise_comparison_method: - comparison_method = ComparisonMethod.HIGHER_IS_BETTER - elif "LOWER_IS_BETTER" in metric_to_optimise_comparison_method: - comparison_method = ComparisonMethod.LOWER_IS_BETTER - elif "TARGET_IS_BETTER" in metric_to_optimise_comparison_method: - comparison_method = ComparisonMethod.TARGET_IS_BETTER - else: - comparison_method = ComparisonMethod.HIGHER_IS_BETTER - - # Update the solution with training code and get callbacks - solution.training_code = code - # Create state info once for all callbacks - state_info = BuildStateInfo( - intent="Unknown", # Will be filled by agent context - provider="Unknown", # Will be filled by agent context - input_schema=None, # Will be filled by agent context - output_schema=None, # Will be filled by agent context - datasets=datasets, - iteration=0, # Default value, no longer used for MLFlow run naming - node=solution, - ) - - # Notify all callbacks about execution start - _notify_callbacks(object_registry.get_all(Callback), "start", state_info) - - # Import here to avoid circular imports - from plexe.config import config - - # Get the appropriate executor class via the factory - executor_class = _get_executor_class(distributed=distributed) - - # Create an instance of the executor - logger.debug(f"Creating {executor_class.__name__} for execution ID: {execution_id}") - executor = executor_class( - execution_id=execution_id, - code=code, - working_dir=working_dir, - datasets=datasets, - timeout=timeout, - code_execution_file_name=config.execution.runfile_name, - ) - - # Execute and collect results - ProcessExecutor.run() handles cleanup internally - logger.debug(f"Executing solution {solution} using executor {executor}") - result = executor.run() - logger.debug(f"Execution result: {result}") - solution.execution_time = result.exec_time - solution.execution_stdout = result.term_out - solution.exception_was_raised = result.exception is not None - solution.exception = result.exception or None - solution.model_artifacts = [Artifact.from_path(p) for p in result.model_artifact_paths] - - # Handle the performance metric properly using the consolidated validation logic - performance_value = None - is_worst = True - - if result.is_valid_performance(): - performance_value = result.performance - is_worst = False - - # Create a metric object with proper handling of None or invalid values - solution.performance = Metric( - name=metric_to_optimise_name, - value=performance_value, - comparator=MetricComparator(comparison_method=comparison_method), - is_worst=is_worst, - ) - - # Notify callbacks about the execution end with the same state_info - # The solution reference in state_info automatically reflects the updates to solution - _notify_callbacks(object_registry.get_all(Callback), "end", state_info) - - # Check if the execution failed in any way - if solution.exception is not None: - raise RuntimeError(f"Execution failed with exception: {solution.exception}") - if not result.is_valid_performance(): - raise RuntimeError(f"Execution failed due to not producing a valid performance: {result.performance}") - - # Register artifacts and update solution in registry - object_registry.register_multiple(Artifact, {a.name: a for a in solution.model_artifacts}) - - # Update the solution in the registry with all execution results - object_registry.register(Solution, solution_id, solution, overwrite=True) - - # Return results - return { - "success": not solution.exception_was_raised, - "performance": ( - { - "name": solution.performance.name if solution.performance else None, - "value": solution.performance.value if solution.performance else None, - "comparison_method": ( - str(solution.performance.comparator.comparison_method) if solution.performance else None - ), - } - if solution.performance - else None - ), - "exception": str(solution.exception) if solution.exception else None, - "model_artifact_names": [a.name for a in solution.model_artifacts], - "solution_id": solution_id, - } - except Exception as e: - # Log full stack trace at debug level - import traceback - - logger.debug(f"Error executing training code: {str(e)}\n{traceback.format_exc()}") - - return { - "success": False, - "performance": None, - "exception": str(e), - "model_artifact_names": [], - } - - return execute_training_code - - -def _get_executor_class(distributed: bool = False) -> Type: - """Get the appropriate executor class based on the distributed flag. - - Args: - distributed: Whether to use distributed execution if available - - Returns: - Executor class (not instance) appropriate for the environment - """ - # Log the distributed flag - logger.debug(f"get_executor_class using distributed={distributed}") - if distributed: - try: - # Try to import Ray executor - from plexe.internal.models.execution.ray_executor import RayExecutor - - logger.debug("Using Ray for distributed execution") - return RayExecutor - except ImportError: - # Fall back to process executor if Ray is not available - logger.warning("Ray not available, falling back to ProcessExecutor") - return ProcessExecutor - - # Default to ProcessExecutor for non-distributed execution - logger.debug("Using ProcessExecutor (non-distributed)") - return ProcessExecutor - - -def _notify_callbacks(callbacks: Dict, event_type: str, build_state_info) -> None: - """Helper function to notify callbacks with consistent error handling. - - Args: - callbacks: Dictionary of callbacks from the registry - event_type: The event type - either "start" or "end" - build_state_info: The state info to pass to callbacks - """ - method_name = f"on_iteration_{event_type}" - - for callback in callbacks.values(): - try: - getattr(callback, method_name)(build_state_info) - except Exception as e: - # Log full stack trace at debug level - import traceback - - logger.debug( - f"Error in callback {callback.__class__.__name__}.{method_name}: {e}\n{traceback.format_exc()}" - ) - # Log a shorter message at warning level - logger.warning(f"Error in callback {callback.__class__.__name__}.{method_name}: {str(e)[:50]}") - - -@tool -def apply_feature_transformer(dataset_name: str) -> Dict: - """ - Applies a feature transformer to datasets and registers the transformed datasets. The name of the - new transformed dataset is returned in the response. - - Args: - dataset_name: Name of datasets to transform - - Returns: - Dictionary with results of transformation: - - success: Boolean indicating success or failure - - original_dataset_name: Name of the original dataset - - new_dataset_name: Name of the transformed dataset - """ - object_registry = ObjectRegistry() - - try: - # Get feature transformer code from registry - code_obj = object_registry.get(Code, "feature_transformations") - transformer_code = code_obj.code - - # Load code as module - module = types.ModuleType("feature_transformer_module") - with warnings.catch_warnings(): - warnings.simplefilter("ignore") - if transformer_code and isinstance(transformer_code, str): - exec(transformer_code, module.__dict__) - else: - raise ValueError("Feature transformer code is invalid or missing.") - - # Instantiate transformer - transformer = module.FeatureTransformerImplementation() - - # Get dataset - dataset = object_registry.get(TabularConvertible, dataset_name) - df = dataset.to_pandas() - - # Apply transformation - transformed_df = transformer.transform(df) - - # Register transformed dataset - transformed_name = f"{dataset_name}_transformed" - transformed_ds = DatasetAdapter.coerce(transformed_df) - object_registry.register(TabularConvertible, transformed_name, transformed_ds, overwrite=True, immutable=True) - - logger.debug(f"✅ Applied feature transformer to {dataset_name} → {transformed_name}") - - return {"success": True, "original_dataset_name": dataset_name, "new_dataset_name": transformed_name} - except Exception as e: - import traceback - - logger.debug(f"Error applying feature transformer: {str(e)}\n{traceback.format_exc()}") - return {"success": False, "error": str(e), "transformed_datasets": []} - - -@tool -def get_model_artifacts() -> List[str]: - """ - Get all registered model artifact names. - - Returns: - List of artifact names (e.g., ["model.pkl", "scaler.pkl", ...]) - """ - object_registry = ObjectRegistry() - - try: - # Get all artifact names from registry - artifact_names = object_registry.list_by_type(Artifact) - return artifact_names - except Exception as e: - logger.warning(f"⚠️ Error getting model artifacts: {str(e)}") - return [] - - -from plexe.tools.io_manager import write_file - - -@tool -def execute_code(code: str, timeout: int = 60) -> dict: - """ - Executes a string of Python code in a subprocess. - - Args: - code: The Python code to execute. - timeout: The timeout in seconds for the execution. - - Returns: - A dictionary containing the stdout, stderr, and return code. - """ - # a temporary file to store the code - code_file = write_file("code.py", code) - try: - process = subprocess.run( - ["python", code_file], - capture_output=True, - text=True, - timeout=timeout, - check=False, - ) - logger.debug(f"✅ Code executed with return code {process.returncode}") - return { - "stdout": process.stdout, - "stderr": process.stderr, - "returncode": process.returncode, - } - except subprocess.TimeoutExpired as e: - logger.error(f"🔥 Code execution timed out: {e}") - return { - "stdout": e.stdout, - "stderr": e.stderr, - "returncode": -1, - "error": "TimeoutExpired", - } - except Exception as e: - logger.error(f"🔥 Error executing code: {e}") - return { - "stdout": "", - "stderr": str(e), - "returncode": -1, - "error": type(e).__name__, - } diff --git a/plexe/tools/gnn_processing.py b/plexe/tools/gnn_processing.py deleted file mode 100644 index f08032c4..00000000 --- a/plexe/tools/gnn_processing.py +++ /dev/null @@ -1,1566 +0,0 @@ -""" -Tools for GNN training and processing for the Relational GNN Specialist Agent. - -This module provides robust tools for: -1. Time-aware neighbor sampling (critical for RDL) -2. Heterogeneous GNN model construction -3. Training with proper backpropagation and seed node masking -""" - -import logging -from typing import Dict, List, Any, Optional, Tuple, Union -from smolagents import tool -import torch -import torch.nn as nn -import torch.nn.functional as F -import numpy as np -import pandas as pd - -# PyTorch Geometric imports -from torch_geometric.data import HeteroData -from torch_geometric.loader import NeighborLoader, LinkNeighborLoader -from torch_geometric.nn import ( - SAGEConv, GATConv, GCNConv, Linear, - HeteroConv, to_hetero -) -from torch_geometric.typing import EdgeType, NodeType - -# ObjectRegistry for data sharing between agents -from plexe.core.object_registry import ObjectRegistry -from plexe.internal.common.datasets.interface import TabularConvertible -from plexe.internal.common.datasets.adapter import DatasetAdapter -import os - -logger = logging.getLogger(__name__) - - -# ============================================================================= -# Helper: Parse Time Window String -# ============================================================================= -def _parse_time_window(time_window: str) -> int: - """ - Parse time window string to seconds. - - Supports formats: '30d' (days), '24h' (hours), '60m' (minutes), '3600s' (seconds) - - Args: - time_window: Time window string (e.g., '30d', '24h') - - Returns: - Time window in seconds - """ - if time_window is None: - return None - - time_window = time_window.strip().lower() - - multipliers = { - 's': 1, - 'm': 60, - 'h': 3600, - 'd': 86400, - 'w': 604800, # week - } - - for suffix, mult in multipliers.items(): - if time_window.endswith(suffix): - try: - value = float(time_window[:-1]) - return int(value * mult) - except ValueError: - raise ValueError(f"Invalid time window format: {time_window}") - - # Try parsing as raw seconds - try: - return int(float(time_window)) - except ValueError: - raise ValueError(f"Invalid time window format: {time_window}. Use formats like '30d', '24h', '60m'") - - -# ============================================================================= -# Tool 0: Get Graph from Registry (Bridge between agents) -# ============================================================================= - -@tool -def get_hetero_graph_from_registry() -> Dict[str, Any]: - """ - Retrieves the HeteroData graph built by RelationalGraphArchitect from ObjectRegistry. - - This is the FIRST tool to call in RelationalGNNSpecialist workflow. - It bridges the gap between GraphArchitect (which builds the graph) and - GNNSpecialist (which trains on it). - - Returns: - Dictionary containing: - - 'graph': The HeteroData object ready for training - - 'metadata': Graph structure info (node types, edge types, counts) - - 'temporal_info': Temporal split information if available - - 'entity_mapper': EntityMapper state for prediction interpretation - - Example: - >>> result = get_hetero_graph_from_registry() - >>> graph = result['graph'] - >>> print(f"Graph has {len(graph.node_types)} node types") - """ - try: - object_registry = ObjectRegistry() - - # Get the HeteroData graph - try: - graph = object_registry.get(HeteroData, "hetero_graph") - except KeyError: - return { - "error": "No HeteroData graph found in registry.", - "hint": "Run RelationalGraphArchitect's build_hetero_graph first.", - "available_keys": [] - } - - # Get metadata - metadata = { - "node_types": graph.node_types, - "edge_types": [str(et) for et in graph.edge_types], - "num_nodes": {}, - "num_edges": {}, - "has_features": {}, - "has_timestamps": {} - } - - for nt in graph.node_types: - if hasattr(graph[nt], 'num_nodes'): - metadata["num_nodes"][nt] = graph[nt].num_nodes - if hasattr(graph[nt], 'x') and graph[nt].x is not None: - metadata["has_features"][nt] = graph[nt].x.shape - if hasattr(graph[nt], 't') and graph[nt].t is not None: - metadata["has_timestamps"][nt] = True - - for et in graph.edge_types: - if hasattr(graph[et], 'edge_index'): - metadata["num_edges"][str(et)] = graph[et].edge_index.shape[1] - - # Get EntityMapper state - entity_mapper = None - try: - entity_mapper = object_registry.get(dict, "entity_mapper_state") - except KeyError: - pass - - # Get temporal split info if available - temporal_info = None - try: - temporal_info = object_registry.get(dict, "temporal_split_info") - except KeyError: - pass - - return { - "graph": graph, - "metadata": metadata, - "entity_mapper": entity_mapper, - "temporal_info": temporal_info, - "status": "Graph retrieved successfully from registry" - } - - except Exception as e: - import traceback - return { - "error": f"Failed to get graph from registry: {str(e)}", - "traceback": traceback.format_exc() - } - - -# ============================================================================= -# Tool 0.5: Load Training Data (Labels) -# ============================================================================= - -@tool -def load_training_data( - entity_type: str, - label_column: str = "label", - timestamp_column: str = "seed_time", - feature_columns: Optional[List[str]] = None, - entity_id_column: Optional[str] = None, - data_dir: Optional[str] = None -) -> Dict[str, Any]: - """ - Loads training/validation/test labels generated by TemporalSupervisor. - - This tool bridges the gap between the Temporal Task Supervisor (which creates - training tables with labels) and the GNN Specialist (which needs these labels - mapped to graph nodes). - - It performs: - 1. Retrieval of 'temporal_train', 'temporal_val', 'temporal_test' from ObjectRegistry - 2. If not in registry, attempts to load from disk (data_dir or .plexecache) - 3. Mapping of Entity IDs (from DB) to Graph Indices (using EntityMapper) - 4. Conversion to PyTorch tensors - 5. (Optional) Loading of point-in-time correct features for seed nodes - - Args: - entity_type: The node type in the graph corresponding to the training entities. - (e.g., 'customers', 'users') - label_column: Name of the label column in the training table. Default 'label'. - timestamp_column: Name of the timestamp column. Default 'seed_time'. - feature_columns: Optional list of feature columns to load from the training table. - These features are computed at seed_time and should override - graph features for the seed nodes to prevent leakage. - entity_id_column: Optional name of the entity ID column in the training table. - If not provided, tries to auto-detect. - data_dir: Optional directory path to load CSV/Parquet files from if not found in registry. - - Returns: - Dictionary containing: - - 'train_data': Dict with 'node_indices', 'labels', 'seed_times', 'features' tensors - - 'val_data': Dict with 'node_indices', 'labels', 'seed_times', 'features' tensors - - 'test_data': Dict with 'node_indices', 'labels', 'seed_times', 'features' tensors - - 'num_classes': Number of unique classes (for classification) - - 'stats': Sample counts - """ - try: - object_registry = ObjectRegistry() - - # 1. Get EntityMapper state - try: - entity_mapper_state = object_registry.get(dict, "entity_mapper_state") - # Extract mapping for the specific entity type - # Structure: mappings[entity_type]['id_to_idx'] - if entity_type not in entity_mapper_state.get("mappings", {}): - return { - "error": f"Entity type '{entity_type}' not found in EntityMapper.", - "available_types": list(entity_mapper_state.get("mappings", {}).keys()) - } - - id_to_idx = entity_mapper_state["mappings"][entity_type]["id_to_idx"] - - except KeyError: - return { - "error": "EntityMapper state not found in registry. Run RelationalGraphArchitect first." - } - - # Helper to process a dataset - def process_dataset(dataset_key: str) -> Optional[Dict[str, torch.Tensor]]: - try: - # Get dataset wrapper - dataset_obj = None - try: - dataset_obj = object_registry.get(TabularConvertible, dataset_key) - except KeyError: - # Try loading from disk if data_dir is provided or fallback to default - search_dirs = [] - if data_dir: - search_dirs.append(data_dir) - - # Also check .plexecache/ or current directory - search_dirs.append(".plexecache") - search_dirs.append(".") - - found = False - for d in search_dirs: - if not os.path.exists(d): - continue - - # Try csv and parquet - for ext in [".csv", ".parquet"]: - fpath = os.path.join(d, f"{dataset_key}{ext}") - if os.path.exists(fpath): - logger.info(f"Found {dataset_key} at {fpath}. Loading and registering.") - try: - if ext == ".csv": - df = pd.read_csv(fpath) - # Ensure timestamp column is datetime - if timestamp_column in df.columns: - df[timestamp_column] = pd.to_datetime(df[timestamp_column]) - else: - df = pd.read_parquet(fpath) - - dataset_obj = DatasetAdapter.coerce(df) - object_registry.register(TabularConvertible, dataset_key, dataset_obj, overwrite=True) - found = True - break - except Exception as e: - logger.error(f"Failed to load {fpath}: {e}") - if found: - break - - if not found: - logger.warning(f"Dataset {dataset_key} not found in registry or disk.") - return None - - # Convert to pandas DataFrame - df = dataset_obj.to_pandas() - - if df.empty: - return None - - # Check columns - if label_column not in df.columns: - logger.warning(f"Label column '{label_column}' not found in {dataset_key}") - return None - - # Map IDs to Indices - # We assume the dataframe has an ID column. - # We try to find it: 'entity_id', 'id', or matching the entity_type - id_col = None - - # 1. Try provided entity_id_column - if entity_id_column and entity_id_column in df.columns: - id_col = entity_id_column - - # 2. Try standard names - if not id_col: - possible_names = [entity_type + "_id", "entity_id", "id", "user_id", "customer_id"] - for col in df.columns: - if col.lower() in possible_names: - id_col = col - break - - # 3. Try case-insensitive match for provided entity_id_column - if not id_col and entity_id_column: - for col in df.columns: - if col.lower() == entity_id_column.lower(): - id_col = col - break - - - - # 4. Fallback: check if any column values overlap with mapper keys - if not id_col: - # Get a sample of keys from mapper to check types - sample_keys = list(id_to_idx.keys())[:5] - sample_key_type = type(sample_keys[0]) if sample_keys else None - - for col in df.columns: - if col == label_column or col == timestamp_column: - continue - - sample_val = df[col].iloc[0] - - # Direct match - if sample_val in id_to_idx: - id_col = col - break - - # Type conversion match (str <-> int) - try: - if isinstance(sample_val, (int, float)) and str(int(sample_val)) in id_to_idx: - id_col = col - break - if isinstance(sample_val, str) and sample_val.isdigit() and int(sample_val) in id_to_idx: - id_col = col - break - except: - pass - - if not id_col: - logger.warning(f"Could not identify ID column in {dataset_key}") - return None - - # Perform mapping - # Filter out IDs that don't exist in the graph (shouldn't happen if graph is up to date) - # Ensure type consistency for mapping - mapping_keys = set(id_to_idx.keys()) - - # Check if we need to convert column type to match keys - sample_val = df[id_col].iloc[0] - sample_key = next(iter(mapping_keys)) - - if type(sample_val) != type(sample_key): - try: - if isinstance(sample_key, str): - df[id_col] = df[id_col].astype(str) - # Handle float-string conversion (e.g. "1.0" -> "1") - if isinstance(sample_val, float): - df[id_col] = df[id_col].apply(lambda x: str(int(float(x)))) - elif isinstance(sample_key, int): - df[id_col] = df[id_col].astype(int) - except Exception as e: - logger.warning(f"Type mismatch between ID column {id_col} ({type(sample_val)}) and mapper keys ({type(sample_key)}). Conversion failed: {e}") - - valid_mask = df[id_col].isin(mapping_keys) - if (~valid_mask).any(): - logger.warning(f"Dropping { (~valid_mask).sum() } samples with unknown IDs in {dataset_key}") - df = df[valid_mask].copy() - - if df.empty: - return None - - # Map to indices - node_indices = df[id_col].map(id_to_idx).values.astype(np.int64) - - # Get labels - labels = df[label_column].values - # Convert to appropriate type (float for regression/binary, long for multiclass) - # We'll infer: if float, keep float. If int/string/bool, convert to long/float - if labels.dtype == np.float64 or labels.dtype == np.float32: - labels_tensor = torch.tensor(labels, dtype=torch.float) - else: - # Try converting to numeric - try: - labels_tensor = torch.tensor(labels.astype(float), dtype=torch.float) - # If all integers, convert to long - if torch.all(labels_tensor == labels_tensor.long()): - labels_tensor = labels_tensor.long() - except: - # Categorical strings? - # For now, assume numeric labels - logger.warning(f"Non-numeric labels in {dataset_key}. Converting to codes.") - labels_tensor = torch.tensor(pd.Categorical(labels).codes, dtype=torch.long) - - # Get timestamps if available - seed_times = None - if timestamp_column in df.columns: - # Convert to unix timestamp if needed - times = df[timestamp_column] - if pd.api.types.is_datetime64_any_dtype(times): - seed_times = torch.tensor(times.astype(np.int64) // 10**9, dtype=torch.long) - else: - # Assume already timestamp or convertable - try: - seed_times = torch.tensor(pd.to_datetime(times).astype(np.int64) // 10**9, dtype=torch.long) - except: - pass - - # Get features if requested - features_tensor = None - if feature_columns: - missing_cols = [c for c in feature_columns if c not in df.columns] - if missing_cols: - logger.warning(f"Missing feature columns in {dataset_key}: {missing_cols}") - else: - # Extract features - feat_data = df[feature_columns].values - # Convert to float tensor - try: - features_tensor = torch.tensor(feat_data.astype(float), dtype=torch.float) - except Exception as e: - logger.warning(f"Could not convert features to tensor in {dataset_key}: {e}") - - result = { - "node_indices": torch.tensor(node_indices, dtype=torch.long), - "labels": labels_tensor, - "seed_times": seed_times - } - - if features_tensor is not None: - result["features"] = features_tensor - - return result - - except KeyError: - return None - except Exception as e: - logger.warning(f"Error processing {dataset_key}: {e}") - return None - - # Process all splits - train_data = process_dataset("temporal_train") - val_data = process_dataset("temporal_val") - test_data = process_dataset("temporal_test") - - if not train_data: - return { - "error": "Could not load training data. Ensure TemporalSupervisor has run create_temporal_dataset." - } - - # Calculate num_classes - num_classes = 1 - if train_data["labels"].dtype == torch.long: - num_classes = int(train_data["labels"].max().item()) + 1 - - return { - "train_data": train_data, - "val_data": val_data, - "test_data": test_data, - "num_classes": num_classes, - "stats": { - "train_samples": len(train_data["node_indices"]), - "val_samples": len(val_data["node_indices"]) if val_data else 0, - "test_samples": len(test_data["node_indices"]) if test_data else 0 - }, - "status": "Training data loaded and mapped successfully" - } - - except Exception as e: - import traceback - return { - "error": f"Failed to load training data: {str(e)}", - "traceback": traceback.format_exc() - } - - -# ============================================================================= -# Tool 1: Configure Temporal Sampler -# ============================================================================= - -@tool -def configure_temporal_sampler( - hetero_data: Any, - num_neighbors: List[int], - input_nodes: Union[Tuple[str, Any], Dict[str, Any]], - seed_times: Optional[Any] = None, - time_attr: str = "t", - time_window: Optional[str] = None, - batch_size: int = 128, - shuffle: bool = True, - temporal_strategy: str = "last", - task_type: str = "node" -) -> Any: - """ - Creates a Time-Consistent Neighbor Sampler for RDL training. - - CRITICAL for RDL: Ensures temporal causality - when predicting for a seed node - at time t, the sampler ONLY retrieves neighbors with timestamps t_neighbor <= t. - This prevents data leakage from the future. - - The tool returns a PyTorch Geometric DataLoader that yields mini-batches - with proper temporal constraints. - - Args: - hetero_data: The HeteroData object from build_hetero_graph. - Must have time attribute (data[node_type].t) for temporal sampling. - - num_neighbors: List of integers specifying neighbors per layer. - Example: [15, 10] means sample 15 1-hop neighbors, 10 2-hop neighbors. - Deeper layers need fewer neighbors (exponential explosion). - - input_nodes: Either: - 1. Tuple of (node_type, node_indices) specifying seed nodes. - 2. Dictionary returned by load_training_data (containing 'node_indices', 'seed_times', 'labels'). - - seed_times: Optional tensor of timestamps for seed nodes. - If input_nodes is a dict, this is extracted automatically. - Used to enforce t_neighbor <= t_seed for each sample. - - time_attr: Name of the time attribute in HeteroData. Default 't'. - This attribute must exist in data[node_type].t - - time_window: Optional time window for neighbor filtering. - Format: '30d' (days), '24h' (hours), '60m' (minutes). - If set, only neighbors within this window are sampled. - - batch_size: Number of seed nodes per batch. Default 128. - - shuffle: Whether to shuffle seed nodes. Default True for training. - - temporal_strategy: Strategy for temporal sampling. Options: - - 'last': Use latest timestamp for each node (default) - - 'uniform': Uniform sampling within time window - - task_type: 'node' for node classification/regression, - 'link' for link prediction. - - Returns: - A configured DataLoader (NeighborLoader or LinkNeighborLoader) ready for training. - - Example: - >>> # Using data from load_training_data - >>> train_data = load_training_data('customers')['train_data'] - >>> loader = configure_temporal_sampler( - ... hetero_data=data, - ... num_neighbors=[15, 10], - ... input_nodes=train_data, # Pass the dict directly - ... time_attr='t', - ... batch_size=256 - ... ) - """ - try: - # Validate hetero_data - if not isinstance(hetero_data, HeteroData): - return { - "error": "hetero_data must be a PyTorch Geometric HeteroData object", - "received_type": type(hetero_data).__name__ - } - - # Parse time window - time_window_seconds = None - if time_window: - time_window_seconds = _parse_time_window(time_window) - - # Handle input_nodes - node_type = None - node_indices = None - labels = None - features = None - - if isinstance(input_nodes, dict): - # It's likely from load_training_data - # We need to know the node_type. It's not in the dict explicitly, - # but usually the caller knows. - # Wait, load_training_data takes entity_type but returns a dict without it. - # We need the user to pass node_type in the tuple if they use the dict? - # Or we assume input_nodes is (node_type, dict)? - # Let's support input_nodes being the dict, but we need node_type. - # Actually, the user should pass (node_type, dict) or we infer it? - # Let's assume the user passes (node_type, dict) OR we check if input_nodes has 'node_indices'. - # But we still need node_type. - - # Let's change the signature/docstring to require (node_type, dict) or just handle dict if we can't infer. - # But wait, the previous signature was (node_type, indices). - # If the user passes a dict, they must have extracted it. - # Let's assume the user passes the dict as the second element of the tuple? - # No, let's support input_nodes as a tuple (node_type, dict). - pass - - # Let's normalize input_nodes - if isinstance(input_nodes, tuple): - node_type = input_nodes[0] - data_obj = input_nodes[1] - - if isinstance(data_obj, dict) and "node_indices" in data_obj: - # It's the dict from load_training_data - node_indices = data_obj["node_indices"] - if "seed_times" in data_obj: - seed_times = data_obj["seed_times"] - if "labels" in data_obj: - labels = data_obj["labels"] - if "features" in data_obj: - features = data_obj["features"] - else: - # It's just indices - node_indices = data_obj - elif isinstance(input_nodes, dict) and "node_indices" in input_nodes: - return { - "error": "input_nodes must be a tuple (node_type, data) when passing a dictionary. Example: ('customers', train_data)" - } - else: - return { - "error": "input_nodes must be a tuple of (node_type, node_indices) or (node_type, data_dict)" - } - - # Check if node type exists - if node_type not in hetero_data.node_types: - return { - "error": f"Node type '{node_type}' not found in HeteroData", - "available_types": hetero_data.node_types - } - - # Check for time attribute - has_time_attr = hasattr(hetero_data[node_type], time_attr) - - # Attach labels to the graph temporarily? - # No, NeighborLoader doesn't attach labels to the graph. - # But we need labels in the batch. - # If we pass input_nodes as (node_type, indices), the loader yields batches. - # The batch will contain the sampled subgraph. - # But where are the labels? - # Usually, we attach labels to the graph: data['customer'].y = ... - # But here we have multiple labels per node (different times). - # So we cannot attach to the graph globally. - - # We need a custom transform or we need to pass labels to the loader? - # PyG NeighborLoader doesn't natively support passing labels for the seeds in the constructor easily - # unless we use a custom Dataset. - - # WORKAROUND: We will attach the labels to the returned batch using a transform or wrapper. - # Or, we can rely on the fact that the loader returns nodes in the order of input_nodes (if shuffle=False). - # But shuffle=True is needed for training. - - # Better approach: - # We can create a "fake" node type or use LinkNeighborLoader? - # Or we can use the `input_data` argument of NeighborLoader (available in newer PyG). - - # Let's assume we can't easily change PyG version. - # We will use a wrapper class around the loader that attaches the labels. - - class LabeledLoader: - def __init__(self, loader, labels, seed_times=None, features=None): - self.loader = loader - self.labels = labels - self.seed_times = seed_times - self.features = features - - def __iter__(self): - for batch in self.loader: - # We need to find which samples are in this batch. - # NeighborLoader with input_nodes=(type, indices) returns a batch - # where batch[node_type].input_id contains the original indices of the seed nodes. - # We can use this to fetch the corresponding labels. - - if hasattr(batch[node_type], 'input_id'): - input_ids = batch[node_type].input_id - # input_ids are indices into the ORIGINAL input_nodes tensor. - # So we can index into self.labels - - if self.labels is not None: - batch_labels = self.labels[input_ids] - # Attach to batch - # We attach it to the target node type - batch[node_type].y = batch_labels - batch.y = batch_labels # Convenience - - if self.seed_times is not None: - batch_seed_times = self.seed_times[input_ids] - batch[node_type].seed_time = batch_seed_times - batch.seed_time = batch_seed_times - - if self.features is not None: - batch_features = self.features[input_ids] - batch[node_type].seed_features = batch_features - - yield batch - - def __len__(self): - return len(self.loader) - - if task_type == "node": - # Node-level task: Use NeighborLoader - - # Prepare kwargs - kwargs = { - "data": hetero_data, - "num_neighbors": num_neighbors, - "input_nodes": (node_type, node_indices), - "batch_size": batch_size, - "shuffle": shuffle, - } - - if has_time_attr: - kwargs["time_attr"] = time_attr - - # If seed_times are provided, we try to pass them as input_time (PyG 2.3+) - # We'll try to pass it, if it fails, we catch it. - # Actually, let's check if we can use input_nodes=(node_type, torch.stack([indices, times], dim=1))? - # No, that's not standard. - - # For now, we will rely on the LabeledLoader to attach seed_times to the batch, - # BUT the sampling itself might not be time-aware per-sample if NeighborLoader doesn't support it. - # However, if we pass `input_time` to NeighborLoader, it works. - if seed_times is not None: - kwargs["input_time"] = seed_times - - try: - loader = NeighborLoader(**kwargs) - except TypeError: - # Fallback: input_time might not be supported in this PyG version - # Remove it and warn - if "input_time" in kwargs: - del kwargs["input_time"] - logger.warning("This PyG version might not support 'input_time' in NeighborLoader. Temporal sampling might be approximate.") - loader = NeighborLoader(**kwargs) - - # Wrap with LabeledLoader if we have labels or seed_times - if labels is not None or seed_times is not None or features is not None: - loader = LabeledLoader(loader, labels, seed_times, features) - - loader_info = { - "loader_type": "NeighborLoader (Labeled)", - "task_type": "node", - "seed_node_type": node_type, - "num_seed_nodes": len(node_indices), - "num_neighbors_per_layer": num_neighbors, - "batch_size": batch_size, - "temporal_enabled": has_time_attr, - "has_labels": labels is not None, - "has_seed_times": seed_times is not None, - "has_seed_features": features is not None - } - - elif task_type == "link": - # Link prediction: Use LinkNeighborLoader - loader = LinkNeighborLoader( - data=hetero_data, - num_neighbors=num_neighbors, - edge_label_index=node_indices, # For link pred, this is edge indices - batch_size=batch_size, - shuffle=shuffle, - time_attr=time_attr if has_time_attr else None, - ) - - loader_info = { - "loader_type": "LinkNeighborLoader", - "task_type": "link", - "num_neighbors_per_layer": num_neighbors, - "batch_size": batch_size, - "temporal_enabled": has_time_attr, - } - else: - return {"error": f"Unknown task_type: {task_type}. Use 'node' or 'link'."} - - # Return both the loader and info - return { - "loader": loader, - "info": loader_info, - "status": "Temporal sampler configured successfully" - } - - except Exception as e: - import traceback - return { - "error": f"Failed to configure sampler: {str(e)}", - "traceback": traceback.format_exc() - } - - -# ============================================================================= -# Tool 2: Build Heterogeneous GNN Model -# ============================================================================= - -class HeteroGNNModel(nn.Module): - """ - Heterogeneous GNN Model that handles multiple node/edge types. - - Uses HeteroConv to apply different message passing operations - for each edge type, as required by relational databases. - """ - - def __init__( - self, - metadata: Tuple[List[NodeType], List[EdgeType]], - in_channels_dict: Dict[str, int], - hidden_channels: int, - out_channels: int, - num_layers: int, - conv_type: str = "sage", - dropout: float = 0.2, - target_node_type: Optional[str] = None, - task_type: str = "classification" - ): - super().__init__() - - self.num_layers = num_layers - self.dropout = dropout - self.target_node_type = target_node_type - self.task_type = task_type - self.hidden_channels = hidden_channels - self.out_channels = out_channels - - node_types, edge_types = metadata - - # 1. Input Projection Layers (different input dims per node type) - self.input_projections = nn.ModuleDict() - for node_type in node_types: - in_dim = in_channels_dict.get(node_type, hidden_channels) - self.input_projections[node_type] = Linear(in_dim, hidden_channels) - - # 2. HeteroConv Layers (one per GNN layer) - self.convs = nn.ModuleList() - for i in range(num_layers): - conv_dict = {} - for edge_type in edge_types: - src_type, rel, dst_type = edge_type - - if conv_type.lower() == "sage": - conv_dict[edge_type] = SAGEConv( - in_channels=hidden_channels, - out_channels=hidden_channels, - aggr='mean' - ) - elif conv_type.lower() == "gat": - conv_dict[edge_type] = GATConv( - in_channels=hidden_channels, - out_channels=hidden_channels // 4, # Multi-head - heads=4, - concat=True, - dropout=dropout - ) - elif conv_type.lower() == "gcn": - conv_dict[edge_type] = GCNConv( - in_channels=hidden_channels, - out_channels=hidden_channels - ) - else: - # Default to SAGE - conv_dict[edge_type] = SAGEConv(hidden_channels, hidden_channels) - - self.convs.append(HeteroConv(conv_dict, aggr='sum')) - - # 3. Task Head (MLP for final prediction) - if target_node_type: - self.task_head = nn.Sequential( - Linear(hidden_channels, hidden_channels), - nn.ReLU(), - nn.Dropout(dropout), - Linear(hidden_channels, out_channels) - ) - else: - self.task_head = None - - def forward( - self, - x_dict: Dict[str, torch.Tensor], - edge_index_dict: Dict[EdgeType, torch.Tensor], - batch_size: Optional[int] = None - ) -> Union[Dict[str, torch.Tensor], torch.Tensor]: - """ - Forward pass through the heterogeneous GNN. - - Args: - x_dict: Dictionary mapping node types to feature tensors. - edge_index_dict: Dictionary mapping edge types to edge indices. - batch_size: If provided, only return predictions for first batch_size nodes - (the seed nodes in mini-batch training). - - Returns: - If target_node_type is set: Tensor of predictions for target nodes. - Otherwise: Dictionary of embeddings for all node types. - """ - # 1. Project inputs to hidden dimension - h_dict = {} - for node_type, x in x_dict.items(): - if node_type in self.input_projections: - h_dict[node_type] = self.input_projections[node_type](x) - else: - # Fallback: zero embedding if no projection - h_dict[node_type] = torch.zeros( - x.size(0), self.hidden_channels, device=x.device - ) - - # 2. Message Passing Layers - for i, conv in enumerate(self.convs): - h_dict = conv(h_dict, edge_index_dict) - - # Apply activation and dropout (except last layer before head) - if i < self.num_layers - 1: - h_dict = {key: F.relu(h) for key, h in h_dict.items()} - h_dict = {key: F.dropout(h, p=self.dropout, training=self.training) - for key, h in h_dict.items()} - - # 3. Task Head (if target node type specified) - if self.target_node_type and self.task_head: - h = h_dict[self.target_node_type] - - # For mini-batch training: only predict for seed nodes - if batch_size is not None: - h = h[:batch_size] - - out = self.task_head(h) - return out - - return h_dict - - def get_embeddings( - self, - x_dict: Dict[str, torch.Tensor], - edge_index_dict: Dict[EdgeType, torch.Tensor] - ) -> Dict[str, torch.Tensor]: - """Get node embeddings without task head (for downstream tasks).""" - # Project inputs - h_dict = {} - for node_type, x in x_dict.items(): - if node_type in self.input_projections: - h_dict[node_type] = self.input_projections[node_type](x) - else: - h_dict[node_type] = torch.zeros( - x.size(0), self.hidden_channels, device=x.device - ) - - # Message passing - for conv in self.convs: - h_dict = conv(h_dict, edge_index_dict) - h_dict = {key: F.relu(h) for key, h in h_dict.items()} - - return h_dict - - -@tool -def build_gnn_model( - hetero_data: Any, - hidden_channels: int = 64, - out_channels: int = 2, - num_layers: int = 2, - architecture_type: str = "sage", - target_node_type: Optional[str] = None, - task_type: str = "classification", - dropout: float = 0.2 -) -> Dict[str, Any]: - """ - Constructs a Heterogeneous GNN model adapted to the database schema. - - Uses HeteroConv to automatically handle multiple node/edge types. - Each edge type gets its own message passing weights, capturing - the semantics of different relationships in the relational database. - - Supported architectures: - - 'sage': GraphSAGE (recommended for large graphs, uses sampling) - - 'gat': Graph Attention Network (learns edge importance) - - 'gcn': Graph Convolutional Network (simple, effective baseline) - - Args: - hetero_data: The HeteroData object containing the graph structure. - Used to extract metadata (node types, edge types, feature dims). - - hidden_channels: Dimension of hidden layers. Default 64. - Larger values = more expressive but slower/more memory. - - out_channels: Output dimension. For classification, this is num_classes. - For regression, typically 1. - - num_layers: Number of GNN message passing layers. Default 2. - More layers = larger receptive field but risk of over-smoothing. - - architecture_type: GNN architecture. Options: 'sage', 'gat', 'gcn'. - - target_node_type: The node type for which to make predictions. - Example: 'customers' for customer churn prediction. - If None, returns embeddings for all node types. - - task_type: 'classification' (uses softmax) or 'regression' (raw output). - - dropout: Dropout rate for regularization. Default 0.2. - - Returns: - Dictionary containing: - - 'model': The PyTorch nn.Module (HeteroGNNModel) - - 'metadata': Graph metadata used for construction - - 'config': Model configuration for reproducibility - - Example: - >>> result = build_gnn_model( - ... hetero_data=data, - ... hidden_channels=128, - ... out_channels=2, # Binary classification - ... num_layers=3, - ... architecture_type='sage', - ... target_node_type='customers' - ... ) - >>> model = result['model'] - >>> model.to(device) - """ - try: - # Validate input - if not isinstance(hetero_data, HeteroData): - return { - "error": "hetero_data must be a PyTorch Geometric HeteroData object", - "received_type": type(hetero_data).__name__ - } - - # Extract metadata - metadata = hetero_data.metadata() - node_types, edge_types = metadata - - # Get input feature dimensions per node type - in_channels_dict = {} - for node_type in node_types: - if hasattr(hetero_data[node_type], 'x') and hetero_data[node_type].x is not None: - in_channels_dict[node_type] = hetero_data[node_type].x.size(1) - else: - # No features: use hidden_channels as default (will be learned) - in_channels_dict[node_type] = hidden_channels - - # Validate target node type - if target_node_type and target_node_type not in node_types: - return { - "error": f"target_node_type '{target_node_type}' not found in graph", - "available_types": node_types - } - - # Build model - model = HeteroGNNModel( - metadata=metadata, - in_channels_dict=in_channels_dict, - hidden_channels=hidden_channels, - out_channels=out_channels, - num_layers=num_layers, - conv_type=architecture_type, - dropout=dropout, - target_node_type=target_node_type, - task_type=task_type - ) - - # Count parameters - total_params = sum(p.numel() for p in model.parameters()) - trainable_params = sum(p.numel() for p in model.parameters() if p.requires_grad) - - config = { - "architecture": architecture_type, - "hidden_channels": hidden_channels, - "out_channels": out_channels, - "num_layers": num_layers, - "dropout": dropout, - "target_node_type": target_node_type, - "task_type": task_type, - "node_types": node_types, - "edge_types": [str(et) for et in edge_types], - "in_channels_dict": in_channels_dict, - "total_parameters": total_params, - "trainable_parameters": trainable_params - } - - return { - "model": model, - "metadata": metadata, - "config": config, - "status": f"HeteroGNN model built with {trainable_params:,} trainable parameters" - } - - except Exception as e: - import traceback - return { - "error": f"Failed to build model: {str(e)}", - "traceback": traceback.format_exc() - } - - -# ============================================================================= -# Tool 3: Train GNN Epoch -# ============================================================================= - -@tool -def train_gnn_epoch( - model: Any, - loader: Any, - optimizer_name: str = "adam", - learning_rate: float = 0.001, - loss_function: str = "cross_entropy", - target_node_type: str = "", - device: str = "auto" -) -> Dict[str, Any]: - """ - Executes one complete training epoch with proper backpropagation. - - CRITICAL for RDL mini-batch training: - - Only computes loss on SEED NODES (first batch_size nodes in each batch) - - Handles heterogeneous batches where each node type has different features - - Supports temporal batches from configure_temporal_sampler - - Args: - model: The HeteroGNN model from build_gnn_model. - Must be a PyTorch nn.Module. - - loader: DataLoader from configure_temporal_sampler. - Can be dict with 'loader' key or direct DataLoader. - - optimizer_name: Optimizer to use. Options: 'adam', 'adamw', 'sgd'. - Default 'adam'. - - learning_rate: Learning rate. Default 0.001. - - loss_function: Loss function. Options: - - 'cross_entropy': For classification (default) - - 'bce': Binary Cross Entropy (for binary classification) - - 'mse': Mean Squared Error (for regression) - - 'mae': Mean Absolute Error (for regression) - - target_node_type: The node type being predicted. Required for - extracting labels from batch. - - device: Device for training. 'auto' (default), 'cuda', 'cpu', 'mps'. - - Returns: - Dictionary containing: - - 'loss': Average loss over epoch - - 'num_batches': Number of batches processed - - 'total_samples': Total number of seed nodes trained - - 'metrics': Additional metrics (accuracy for classification) - - Example: - >>> for epoch in range(100): - ... result = train_gnn_epoch( - ... model=model, - ... loader=train_loader, - ... optimizer_name='adam', - ... learning_rate=0.001, - ... loss_function='cross_entropy', - ... target_node_type='customers' - ... ) - ... print(f"Epoch {epoch}: Loss = {result['loss']:.4f}") - """ - try: - # Validate model - if not isinstance(model, nn.Module): - # Check if it's wrapped in a dict from build_gnn_model - if isinstance(model, dict) and 'model' in model: - model = model['model'] - else: - return {"error": "model must be a PyTorch nn.Module"} - - # Extract loader if wrapped in dict from configure_temporal_sampler - if isinstance(loader, dict): - if 'loader' in loader: - loader = loader['loader'] - else: - return {"error": "loader dict must contain 'loader' key"} - - # Determine device - if device == "auto": - if torch.cuda.is_available(): - device = "cuda" - elif hasattr(torch.backends, 'mps') and torch.backends.mps.is_available(): - device = "mps" - else: - device = "cpu" - - device = torch.device(device) - model = model.to(device) - model.train() - - # Setup optimizer - optimizer_map = { - 'adam': lambda: torch.optim.Adam(model.parameters(), lr=learning_rate), - 'adamw': lambda: torch.optim.AdamW(model.parameters(), lr=learning_rate), - 'sgd': lambda: torch.optim.SGD(model.parameters(), lr=learning_rate, momentum=0.9), - } - - if optimizer_name.lower() not in optimizer_map: - return {"error": f"Unknown optimizer: {optimizer_name}. Use: adam, adamw, sgd"} - - optimizer = optimizer_map[optimizer_name.lower()]() - - # Setup loss function - loss_fn_map = { - 'cross_entropy': nn.CrossEntropyLoss(), - 'bce': nn.BCEWithLogitsLoss(), - 'mse': nn.MSELoss(), - 'mae': nn.L1Loss(), - } - - if loss_function.lower() not in loss_fn_map: - return {"error": f"Unknown loss: {loss_function}. Use: cross_entropy, bce, mse, mae"} - - loss_fn = loss_fn_map[loss_function.lower()] - - # Training loop - total_loss = 0.0 - total_samples = 0 - total_correct = 0 - num_batches = 0 - - for batch in loader: - batch = batch.to(device) - optimizer.zero_grad() - - # Get batch size (number of seed nodes) - # In NeighborLoader, the first batch_size nodes are the seeds - if hasattr(batch, 'batch_size'): - batch_size = batch.batch_size - else: - # Fallback: assume all nodes are seeds - batch_size = None - - # Overwrite features for seed nodes if available (Temporal Feature Filtering) - if target_node_type and hasattr(batch[target_node_type], 'seed_features'): - seed_features = batch[target_node_type].seed_features - # Ensure dimensions match - if seed_features.size(1) == batch[target_node_type].x.size(1): - # Overwrite the first batch_size rows (seed nodes) - # seed_features corresponds to the seed nodes in this batch - current_batch_size = seed_features.size(0) - batch[target_node_type].x[:current_batch_size] = seed_features.to(device) - - # Forward pass - # The model should handle x_dict and edge_index_dict - if hasattr(batch, 'x_dict') and hasattr(batch, 'edge_index_dict'): - out = model(batch.x_dict, batch.edge_index_dict, batch_size=batch_size) - else: - # Single node type case - out = model(batch.x, batch.edge_index) - - # Get labels for target node type - if target_node_type: - if hasattr(batch[target_node_type], 'y'): - y = batch[target_node_type].y - elif hasattr(batch, 'y'): - y = batch.y - else: - return {"error": f"No labels found for target_node_type '{target_node_type}'"} - - # Only use labels for seed nodes (first batch_size) - if batch_size is not None: - y = y[:batch_size] - else: - if hasattr(batch, 'y'): - y = batch.y - if batch_size is not None: - y = y[:batch_size] - else: - return {"error": "No labels found in batch. Set target_node_type."} - - # Compute loss - if loss_function.lower() == 'bce': - # BCE expects float targets - loss = loss_fn(out.view(-1), y.float()) - elif loss_function.lower() in ['mse', 'mae']: - # Regression - loss = loss_fn(out.view(-1), y.float()) - else: - # Classification with CrossEntropy - loss = loss_fn(out, y.long()) - - # Backward pass - loss.backward() - optimizer.step() - - # Accumulate metrics - total_loss += loss.item() * (batch_size if batch_size else len(y)) - total_samples += batch_size if batch_size else len(y) - num_batches += 1 - - # Accuracy for classification - if loss_function.lower() == 'cross_entropy': - pred = out.argmax(dim=-1) - total_correct += (pred == y).sum().item() - - # Compute averages - avg_loss = total_loss / total_samples if total_samples > 0 else 0.0 - - metrics = {} - if loss_function.lower() == 'cross_entropy': - metrics['accuracy'] = total_correct / total_samples if total_samples > 0 else 0.0 - - return { - "loss": avg_loss, - "num_batches": num_batches, - "total_samples": total_samples, - "metrics": metrics, - "device": str(device), - "status": "Epoch completed successfully" - } - - except Exception as e: - import traceback - return { - "error": f"Training failed: {str(e)}", - "traceback": traceback.format_exc() - } - - -@tool -def evaluate_gnn( - model: Any, - loader: Any, - loss_function: str = "cross_entropy", - target_node_type: str = "", - device: str = "auto" -) -> Dict[str, Any]: - """ - Evaluates the GNN model on a validation/test set. - - Similar to train_gnn_epoch but without gradient computation. - Computes comprehensive metrics: Loss, Accuracy, ROC-AUC, F1. - - Args: - model: The trained HeteroGNN model. - loader: DataLoader for evaluation data. - loss_function: Loss function used during training. - target_node_type: The node type being predicted. - device: Device for evaluation. - - Returns: - Dictionary with loss and metrics (accuracy, roc_auc, f1 for classification). - """ - try: - from sklearn.metrics import roc_auc_score, f1_score, accuracy_score - - # Extract model/loader from dicts - if isinstance(model, dict) and 'model' in model: - model = model['model'] - if isinstance(loader, dict) and 'loader' in loader: - loader = loader['loader'] - - # Device setup - if device == "auto": - if torch.cuda.is_available(): - device = "cuda" - elif hasattr(torch.backends, 'mps') and torch.backends.mps.is_available(): - device = "mps" - else: - device = "cpu" - - device = torch.device(device) - model = model.to(device) - model.eval() - - # Loss function - loss_fn_map = { - 'cross_entropy': nn.CrossEntropyLoss(), - 'bce': nn.BCEWithLogitsLoss(), - 'mse': nn.MSELoss(), - 'mae': nn.L1Loss(), - } - loss_fn = loss_fn_map.get(loss_function.lower(), nn.CrossEntropyLoss()) - - all_preds = [] - all_labels = [] - all_probs = [] - total_loss = 0.0 - total_samples = 0 - - with torch.no_grad(): - for batch in loader: - batch = batch.to(device) - - batch_size = getattr(batch, 'batch_size', None) - - # Overwrite features for seed nodes if available (Temporal Feature Filtering) - # We need target_node_type for this. If not provided, we can't easily guess. - # But evaluate_gnn takes target_node_type. - if target_node_type and hasattr(batch[target_node_type], 'seed_features'): - seed_features = batch[target_node_type].seed_features - if seed_features.size(1) == batch[target_node_type].x.size(1): - current_batch_size = seed_features.size(0) - batch[target_node_type].x[:current_batch_size] = seed_features.to(device) - - # Forward pass - if hasattr(batch, 'x_dict') and hasattr(batch, 'edge_index_dict'): - out = model(batch.x_dict, batch.edge_index_dict, batch_size=batch_size) - else: - out = model(batch.x, batch.edge_index) - - # Get labels - if target_node_type and hasattr(batch[target_node_type], 'y'): - y = batch[target_node_type].y - else: - y = batch.y - - if batch_size is not None: - y = y[:batch_size] - - # Compute loss - if loss_function.lower() in ['mse', 'mae']: - loss = loss_fn(out.view(-1), y.float()) - elif loss_function.lower() == 'bce': - loss = loss_fn(out.view(-1), y.float()) - else: - loss = loss_fn(out, y.long()) - - total_loss += loss.item() * len(y) - total_samples += len(y) - - # Collect predictions - if loss_function.lower() == 'cross_entropy': - probs = F.softmax(out, dim=-1) - preds = out.argmax(dim=-1) - all_probs.extend(probs[:, 1].cpu().numpy() if probs.size(1) == 2 else probs.cpu().numpy()) - else: - preds = out.view(-1) - all_probs.extend(torch.sigmoid(out).view(-1).cpu().numpy()) - - all_preds.extend(preds.cpu().numpy()) - all_labels.extend(y.cpu().numpy()) - - # Compute metrics - avg_loss = total_loss / total_samples if total_samples > 0 else 0.0 - - metrics = {"loss": avg_loss} - - if loss_function.lower() in ['cross_entropy', 'bce']: - all_preds = np.array(all_preds) - all_labels = np.array(all_labels) - all_probs = np.array(all_probs) - - metrics['accuracy'] = accuracy_score(all_labels, all_preds) - metrics['f1'] = f1_score(all_labels, all_preds, average='weighted') - - try: - if len(np.unique(all_labels)) == 2: - metrics['roc_auc'] = roc_auc_score(all_labels, all_probs) - except ValueError: - pass # ROC-AUC not computable - - return { - "metrics": metrics, - "total_samples": total_samples, - "status": "Evaluation completed" - } - - except Exception as e: - import traceback - return { - "error": f"Evaluation failed: {str(e)}", - "traceback": traceback.format_exc() - } - - -@tool -def save_gnn_model( - model: Any, - save_path: str, - config: Optional[Dict[str, Any]] = None -) -> Dict[str, Any]: - """ - Saves the trained GNN model to disk. - - Saves both model weights and configuration for reproducibility. - - Args: - model: The trained model (or dict with 'model' key). - save_path: Path to save the model (e.g., 'models/fraud_detector.pt'). - config: Optional configuration dict to save alongside model. - - Returns: - Dictionary with save status and path. - """ - try: - import os - - # Extract model from dict if needed - if isinstance(model, dict): - config = config or model.get('config', {}) - model = model.get('model', model) - - # Ensure directory exists - os.makedirs(os.path.dirname(save_path) if os.path.dirname(save_path) else '.', exist_ok=True) - - # Save model state and config - checkpoint = { - 'model_state_dict': model.state_dict(), - 'config': config or {} - } - - torch.save(checkpoint, save_path) - - return { - "status": "Model saved successfully", - "path": save_path, - "model_size_mb": os.path.getsize(save_path) / (1024 * 1024) - } - - except Exception as e: - return {"error": f"Failed to save model: {str(e)}"} - - -@tool -def load_gnn_model( - load_path: str, - hetero_data: Optional[Any] = None -) -> Dict[str, Any]: - """ - Loads a saved GNN model from disk. - - Args: - load_path: Path to the saved model file. - hetero_data: HeteroData object to reconstruct model architecture. - Required if loading for the first time. - - Returns: - Dictionary with loaded model and config. - """ - try: - checkpoint = torch.load(load_path, map_location='cpu') - config = checkpoint.get('config', {}) - - if hetero_data is not None: - # Rebuild model from config - result = build_gnn_model( - hetero_data=hetero_data, - hidden_channels=config.get('hidden_channels', 64), - out_channels=config.get('out_channels', 2), - num_layers=config.get('num_layers', 2), - architecture_type=config.get('architecture', 'sage'), - target_node_type=config.get('target_node_type'), - task_type=config.get('task_type', 'classification'), - dropout=config.get('dropout', 0.2) - ) - - if 'error' in result: - return result - - model = result['model'] - model.load_state_dict(checkpoint['model_state_dict']) - - return { - "model": model, - "config": config, - "status": "Model loaded successfully" - } - else: - return { - "state_dict": checkpoint['model_state_dict'], - "config": config, - "status": "State dict loaded. Provide hetero_data to reconstruct full model." - } - - except Exception as e: - import traceback - return { - "error": f"Failed to load model: {str(e)}", - "traceback": traceback.format_exc() - } diff --git a/plexe/tools/gnn_training_script_generator.py b/plexe/tools/gnn_training_script_generator.py deleted file mode 100644 index 547cf579..00000000 --- a/plexe/tools/gnn_training_script_generator.py +++ /dev/null @@ -1,1214 +0,0 @@ -""" -Tools for generating GNN training scripts for the Relational GNN Specialist Agent. - -This module provides tools to generate complete, executable training scripts -that use the relbench.modeling modules for training GNN models on relational data. -""" - -import os -import logging -from typing import Dict, List, Any, Optional -from pathlib import Path - -from smolagents import tool - -from plexe.core.object_registry import ObjectRegistry - -logger = logging.getLogger(__name__) - - -# ============================================================================= -# Training Script Template -# ============================================================================= - -TRAINING_SCRIPT_TEMPLATE = '''""" -Auto-generated GNN Training Script. -Generated by RelationalGNNSpecialist Agent. - -This script trains a Graph Neural Network model using the RelBench framework. -It uses temporal sampling to ensure no data leakage from future to past. -""" - -import os -import sys - -# Add project root to Python path to enable plexe imports -# First, check if we're in a Docker environment (/app) -if os.path.exists("/app/plexe"): - if "/app" not in sys.path: - sys.path.insert(0, "/app") -else: - # Local development: go up from .workdir/chat-session-xxx/ to project root - script_dir = os.path.dirname(os.path.abspath(__file__)) - project_root = os.path.dirname(os.path.dirname(script_dir)) # Go up two levels - if project_root not in sys.path and os.path.exists(os.path.join(project_root, "plexe")): - sys.path.insert(0, project_root) - -import math -import copy -import numpy as np -from tqdm import tqdm -from typing import Any, Dict, List, Optional - -import torch -import torch.nn as nn -from torch import Tensor -from torch.nn import Embedding, ModuleDict -from torch_geometric.data import HeteroData -from torch_geometric.nn import MLP -from torch_geometric.typing import NodeType -from torch_geometric.loader import NeighborLoader -from torch_geometric.seed import seed_everything -from torch_frame.data.stats import StatType - -# Import custom Dataset and Task -{dataset_import} -{task_import} - -# Import RelBench modeling utilities (from plexe's built-in relbench) -from plexe.relbench.modeling.graph import make_pkey_fkey_graph, get_node_train_table_input -from plexe.relbench.modeling.utils import get_stype_proposal -from plexe.relbench.modeling.nn import HeteroEncoder, HeteroGraphSAGE, HeteroTemporalEncoder - -# Set random seed for reproducibility -seed_everything({random_seed}) - -# Device configuration -device = torch.device("cuda" if torch.cuda.is_available() else "cpu") -print(f"Using device: {{device}}") - -# Configuration -WORKING_DIR = "{working_dir}" -CACHE_DIR = os.path.join(WORKING_DIR, "cache") -MODEL_SAVE_PATH = os.path.join(WORKING_DIR, "best_model.pt") - -# Training hyperparameters -EPOCHS = {epochs} -BATCH_SIZE = {batch_size} -LEARNING_RATE = {learning_rate} -HIDDEN_CHANNELS = {hidden_channels} -NUM_GNN_LAYERS = {num_gnn_layers} -NUM_NEIGHBORS = {num_neighbors} # Neighbors per layer -DROPOUT = {dropout} - -# Task configuration -TUNE_METRIC = "{tune_metric}" -HIGHER_IS_BETTER = {higher_is_better} - - -# ============================================================================= -# Text Embedder (for text columns) -# ============================================================================= - -{text_embedder_code} - - -# ============================================================================= -# GNN Model Definition -# ============================================================================= - -class GNNModel(torch.nn.Module): - """ - Heterogeneous GNN model for relational data. - - Components: - - HeteroEncoder: Encodes tabular features from each table into vectors - - HeteroTemporalEncoder: Encodes relative time information - - HeteroGraphSAGE: Message passing between tables via foreign key relations - - MLP: Final prediction head - """ - - def __init__( - self, - data: HeteroData, - col_stats_dict: Dict[str, Dict[str, Dict[StatType, Any]]], - num_layers: int, - channels: int, - out_channels: int, - aggr: str = "mean", - norm: str = "batch_norm", - shallow_list: List[NodeType] = [], - id_awareness: bool = False, - ): - super().__init__() - - # Tabular feature encoder - self.encoder = HeteroEncoder( - channels=channels, - node_to_col_names_dict={{ - node_type: data[node_type].tf.col_names_dict - for node_type in data.node_types - }}, - node_to_col_stats=col_stats_dict, - ) - - # Temporal encoder for time-aware representations - self.temporal_encoder = HeteroTemporalEncoder( - node_types=[ - node_type for node_type in data.node_types if "time" in data[node_type] - ], - channels=channels, - ) - - # Graph Neural Network (message passing) - self.gnn = HeteroGraphSAGE( - node_types=data.node_types, - edge_types=data.edge_types, - channels=channels, - aggr=aggr, - num_layers=num_layers, - ) - - # Prediction head - self.head = MLP( - channels, - out_channels=out_channels, - norm=norm, - num_layers=1, - ) - - # Optional: Shallow embeddings for specific node types - self.embedding_dict = ModuleDict({{ - node: Embedding(data.num_nodes_dict[node], channels) - for node in shallow_list - }}) - - # Optional: ID awareness embedding - self.id_awareness_emb = None - if id_awareness: - self.id_awareness_emb = torch.nn.Embedding(1, channels) - - self.reset_parameters() - - def reset_parameters(self): - self.encoder.reset_parameters() - self.temporal_encoder.reset_parameters() - self.gnn.reset_parameters() - self.head.reset_parameters() - for embedding in self.embedding_dict.values(): - torch.nn.init.normal_(embedding.weight, std=0.1) - if self.id_awareness_emb is not None: - self.id_awareness_emb.reset_parameters() - - def forward( - self, - batch: HeteroData, - entity_table: NodeType, - ) -> Tensor: - seed_time = batch[entity_table].seed_time - - # Encode tabular features - x_dict = self.encoder(batch.tf_dict) - - # Add temporal encoding - rel_time_dict = self.temporal_encoder( - seed_time, batch.time_dict, batch.batch_dict - ) - for node_type, rel_time in rel_time_dict.items(): - x_dict[node_type] = x_dict[node_type] + rel_time - - # Add shallow embeddings if configured - for node_type, embedding in self.embedding_dict.items(): - x_dict[node_type] = x_dict[node_type] + embedding(batch[node_type].n_id) - - # Message passing through GNN - x_dict = self.gnn( - x_dict, - batch.edge_index_dict, - batch.num_sampled_nodes_dict, - batch.num_sampled_edges_dict, - ) - - # Return predictions for seed nodes only - return self.head(x_dict[entity_table][:seed_time.size(0)]) - - -# ============================================================================= -# Main Training Logic -# ============================================================================= - -def main(): - print("=" * 60) - print("GNN Training Script for Relational Data") - print("=" * 60) - - # ------------------------------------------------------------------------- - # Step 1: Load Dataset and Task - # ------------------------------------------------------------------------- - print("\\n[Step 1] Loading Dataset and Task...") - - # Try to find csv_dir in the same directory as the script - csv_dir = os.path.join(WORKING_DIR, "csv_files") - if not os.path.exists(csv_dir): - # Fallback to looking for csv files in the working dir itself - csv_dir = WORKING_DIR - - try: - dataset = {dataset_class}(csv_dir=csv_dir) - except TypeError: - # Fallback if dataset doesn't accept csv_dir (e.g. standard RelBench datasets) - dataset = {dataset_class}() - - task = {task_class}(dataset) - db = dataset.get_db() - - print(f" Dataset: {{dataset.__class__.__name__}}") - print(f" Task: {{task.__class__.__name__}}") - print(f" Entity table: {{task.entity_table}}") - print(f" Task type: {{task.task_type}}") - - # ------------------------------------------------------------------------- - # Step 2: Create Train/Val/Test Tables - # ------------------------------------------------------------------------- - print("\\n[Step 2] Creating temporal train/val/test tables...") - - train_table = task.get_table("train") - val_table = task.get_table("val") - test_table = task.get_table("test") - - print(f" Train samples: {{len(train_table.df)}}") - print(f" Val samples: {{len(val_table.df)}}") - print(f" Test samples: {{len(test_table.df)}}") - - # ------------------------------------------------------------------------- - # Step 3: Build Heterogeneous Graph - # ------------------------------------------------------------------------- - print("\\n[Step 3] Building heterogeneous graph from database...") - - # Infer column types - col_to_stype_dict = get_stype_proposal(db) - - # Configure text embedder - {text_embedder_config} - - # Build graph - os.makedirs(CACHE_DIR, exist_ok=True) - data, col_stats_dict = make_pkey_fkey_graph( - db, - col_to_stype_dict=col_to_stype_dict, - text_embedder_cfg=text_embedder_cfg, - cache_dir=CACHE_DIR, - ) - # Clean up text embedder to free GPU memory - del text_embedder_cfg - import gc - gc.collect() - if torch.cuda.is_available(): - torch.cuda.empty_cache() - print(f" Node types: {{data.node_types}}") - print(f" Edge types: {{len(data.edge_types)}}") - for node_type in data.node_types: - print(f" - {{node_type}}: {{data[node_type].num_nodes}} nodes") - - # ------------------------------------------------------------------------- - # Step 4: Create Data Loaders with Temporal Sampling - # ------------------------------------------------------------------------- - print("\\n[Step 4] Creating temporal neighbor loaders...") - - loader_dict = {{}} - - for split, table in [ - ("train", train_table), - ("val", val_table), - ("test", test_table), - ]: - table_input = get_node_train_table_input( - table=table, - task=task, - ) - entity_table = table_input.nodes[0] - - loader_dict[split] = NeighborLoader( - data, - num_neighbors=NUM_NEIGHBORS, - time_attr="time", - input_nodes=table_input.nodes, - input_time=table_input.time, - transform=table_input.transform, - batch_size=BATCH_SIZE, - temporal_strategy="uniform", - shuffle=(split == "train"), - num_workers=0, - persistent_workers=False, - ) - print(f" {{split}}: {{len(loader_dict[split])}} batches") - - # ------------------------------------------------------------------------- - # Step 5: Initialize Model - # ------------------------------------------------------------------------- - print("\\n[Step 5] Initializing GNN model...") - - model = GNNModel( - data=data, - col_stats_dict=col_stats_dict, - num_layers=NUM_GNN_LAYERS, - channels=HIDDEN_CHANNELS, - out_channels={out_channels}, - aggr="sum", - norm="batch_norm", - ).to(device) - - total_params = sum(p.numel() for p in model.parameters()) - print(f" Total parameters: {{total_params:,}}") - - # ------------------------------------------------------------------------- - # Step 6: Setup Loss and Optimizer - # ------------------------------------------------------------------------- - print("\\n[Step 6] Setting up loss function and optimizer...") - - {loss_function_code} - optimizer = torch.optim.Adam(model.parameters(), lr=LEARNING_RATE) - - print(f" Loss function: {{loss_fn.__class__.__name__}}") - print(f" Optimizer: Adam (lr={{LEARNING_RATE}})") - - # ------------------------------------------------------------------------- - # Step 7: Training Loop - # ------------------------------------------------------------------------- - print("\\n[Step 7] Starting training...") - print("-" * 60) - - def train_epoch() -> float: - model.train() - loss_accum = 0 - count_accum = 0 - - for batch in tqdm(loader_dict["train"], desc="Training"): - batch = batch.to(device) - optimizer.zero_grad() - - pred = model(batch, task.entity_table) - pred = pred.view(-1) if pred.size(1) == 1 else pred - - loss = loss_fn(pred.float(), batch[entity_table].y.float()) - loss.backward() - optimizer.step() - - loss_accum += loss.detach().item() * pred.size(0) - count_accum += pred.size(0) - - return loss_accum / count_accum - - @torch.no_grad() - def evaluate(loader: NeighborLoader) -> np.ndarray: - model.eval() - pred_list = [] - - for batch in loader: - batch = batch.to(device) - pred = model(batch, task.entity_table) - pred = pred.view(-1) if pred.size(1) == 1 else pred - pred_list.append(pred.detach().cpu()) - - return torch.cat(pred_list, dim=0).numpy() - - # Training loop - best_state_dict = None - best_val_metric = -math.inf if HIGHER_IS_BETTER else math.inf - - for epoch in range(1, EPOCHS + 1): - train_loss = train_epoch() - val_pred = evaluate(loader_dict["val"]) - val_metrics = task.evaluate(val_pred, val_table) - - print(f"Epoch {{epoch:02d}} | Train Loss: {{train_loss:.4f}} | Val Metrics: {{val_metrics}}") - - # Check for improvement - current_metric = val_metrics[TUNE_METRIC] - improved = ( - (HIGHER_IS_BETTER and current_metric > best_val_metric) or - (not HIGHER_IS_BETTER and current_metric < best_val_metric) - ) - - if improved: - best_val_metric = current_metric - best_state_dict = copy.deepcopy(model.state_dict()) - print(f" -> New best {{TUNE_METRIC}}: {{best_val_metric:.4f}}") - - # ------------------------------------------------------------------------- - # Step 8: Final Evaluation - # ------------------------------------------------------------------------- - print("\\n[Step 8] Final evaluation with best model...") - print("-" * 60) - - # Load best model - model.load_state_dict(best_state_dict) - - # Evaluate on validation - val_pred = evaluate(loader_dict["val"]) - val_metrics = task.evaluate(val_pred, val_table) - print(f"Best Validation Metrics: {{val_metrics}}") - - # Evaluate on test - test_pred = evaluate(loader_dict["test"]) - test_metrics = task.evaluate(test_pred) - print(f"Test Metrics: {{test_metrics}}") - - # ------------------------------------------------------------------------- - # Step 9: Save Model - # ------------------------------------------------------------------------- - print(f"\\n[Step 9] Saving model to {{MODEL_SAVE_PATH}}...") - - torch.save({{ - "model_state_dict": best_state_dict, - "model_config": {{ - "num_layers": NUM_GNN_LAYERS, - "channels": HIDDEN_CHANNELS, - "out_channels": {out_channels}, - }}, - "val_metrics": val_metrics, - "test_metrics": test_metrics, - }}, MODEL_SAVE_PATH) - - print("\\n" + "=" * 60) - print("Training Complete!") - print(f"Best {{TUNE_METRIC}}: {{best_val_metric:.4f}}") - print("=" * 60) - - return test_metrics - - -if __name__ == "__main__": - main() -''' - - -# ============================================================================= -# Text Embedder Code Templates -# ============================================================================= - -GLOVE_TEXT_EMBEDDER = ''' -from typing import List, Optional -from torch import Tensor - -# Try to import sentence_transformers, fall back to simple embedder if not available -_SENTENCE_TRANSFORMERS_AVAILABLE = False -try: - from sentence_transformers import SentenceTransformer - _SENTENCE_TRANSFORMERS_AVAILABLE = True -except ImportError: - print("WARNING: sentence_transformers not installed. Using fallback text embedder.") - print("For better text embeddings, install: pip install sentence-transformers") - - -class GloveTextEmbedding: - """GloVe-based text embedder using sentence-transformers with fallback.""" - - def __init__(self, device: Optional[torch.device] = None): - self.device = device - if _SENTENCE_TRANSFORMERS_AVAILABLE: - self.model = SentenceTransformer( - "sentence-transformers/average_word_embeddings_glove.6B.300d", - device=device, - ) - self.embedding_dim = 300 - else: - self.model = None - self.embedding_dim = 64 # Fallback dimension - print("Using random embeddings as fallback (not recommended for production)") - - def __call__(self, sentences: List[str]) -> Tensor: - if self.model is not None: - # Use sentence-transformers - return torch.from_numpy(self.model.encode(sentences)).float() - else: - # Fallback: simple hash-based embeddings (deterministic but basic) - embeddings = [] - for sentence in sentences: - # Create a deterministic embedding based on string hash - torch.manual_seed(hash(sentence) % (2**32)) - emb = torch.randn(self.embedding_dim) - embeddings.append(emb) - return torch.stack(embeddings).float() -''' - -GLOVE_TEXT_EMBEDDER_CONFIG = ''' - from torch_frame.config.text_embedder import TextEmbedderConfig - text_embedder_cfg = TextEmbedderConfig( - text_embedder=GloveTextEmbedding(device=device), - batch_size=256 - ) -''' - -# ============================================================================= -# Loss Function Templates -# ============================================================================= - -LOSS_FUNCTION_TEMPLATES = { - "regression": "loss_fn = torch.nn.L1Loss() # MAE for regression", - "mse_regression": "loss_fn = torch.nn.MSELoss() # MSE for regression", - "binary_classification": "loss_fn = torch.nn.BCEWithLogitsLoss() # Binary classification", - "multiclass_classification": "loss_fn = torch.nn.CrossEntropyLoss() # Multiclass classification", -} - - -# ============================================================================= -# Tool: Get Training Script Template -# ============================================================================= - -@tool -def get_training_script_template() -> str: - """ - Returns the GNN training script template for reference. - - Use this to understand the structure of the training script before - generating a customized version with generate_training_script. - - Returns: - The training script template string - """ - return TRAINING_SCRIPT_TEMPLATE - - -# ============================================================================= -# Tool: Generate Training Script -# ============================================================================= - -@tool -def generate_training_script( - dataset_module_path: str, - dataset_class_name: str, - task_module_path: str, - task_class_name: str, - working_dir: str, - task_type: str = "regression", - tune_metric: str = "mae", - higher_is_better: bool = False, - out_channels: int = 1, - epochs: int = 10, - batch_size: int = 512, - learning_rate: float = 0.005, - hidden_channels: int = 128, - num_gnn_layers: int = 2, - num_neighbors: Optional[List[int]] = None, - dropout: float = 0.0, - use_text_embedder: bool = True, - random_seed: int = 42, -) -> Dict[str, Any]: - """ - Generates a complete GNN training script using plexe.relbench.modeling modules. - - This tool creates a Python script that: - 1. Loads the custom Dataset and Task classes - 2. Builds a heterogeneous graph using make_pkey_fkey_graph - 3. Creates temporal neighbor loaders for train/val/test - 4. Defines and trains a HeteroGNN model - 5. Evaluates and saves the best model - - Args: - dataset_module_path: Path to the dataset module (e.g., "workdir/dataset.py") - dataset_class_name: Name of the Dataset class (e.g., "MyCustomDataset") - task_module_path: Path to the task module (e.g., "workdir/task.py") - task_class_name: Name of the Task class (e.g., "UserLTVTask") - working_dir: Directory to save outputs (model checkpoints, cache, etc.) - task_type: Type of task - "regression", "binary_classification", "multiclass_classification" - tune_metric: Metric to optimize (e.g., "mae", "accuracy", "roc_auc") - higher_is_better: Whether higher metric values are better - out_channels: Number of output channels (1 for regression/binary, num_classes for multiclass) - epochs: Number of training epochs - batch_size: Batch size for training - learning_rate: Learning rate for Adam optimizer - hidden_channels: Hidden dimension for GNN layers - num_gnn_layers: Number of GNN layers (message passing depth) - num_neighbors: List of neighbors per layer (default: [128, 128]) - dropout: Dropout rate - use_text_embedder: Whether to use GloVe text embedder for text columns - random_seed: Random seed for reproducibility - - Returns: - Dictionary containing: - - 'script_content': The generated Python script - - 'script_path': Path where the script was saved - - 'config': Configuration used for generation - """ - try: - # Default num_neighbors - if num_neighbors is None: - num_neighbors = [128] * num_gnn_layers - - # Ensure working_dir exists - os.makedirs(working_dir, exist_ok=True) - - # Generate import statements - dataset_module = os.path.splitext(os.path.basename(dataset_module_path))[0] - task_module = os.path.splitext(os.path.basename(task_module_path))[0] - - # Add the working directory to the import path in the script - dataset_import = f""" -# Add working directory to path for imports -sys.path.insert(0, "{os.path.dirname(os.path.abspath(dataset_module_path))}") -from {dataset_module} import {dataset_class_name} -""" - - task_import = f"""from {task_module} import {task_class_name} -""" - - # Select loss function based on task type - if task_type == "regression": - loss_function_code = LOSS_FUNCTION_TEMPLATES["regression"] - elif task_type == "mse_regression": - loss_function_code = LOSS_FUNCTION_TEMPLATES["mse_regression"] - elif task_type == "binary_classification": - loss_function_code = LOSS_FUNCTION_TEMPLATES["binary_classification"] - elif task_type == "multiclass_classification": - loss_function_code = LOSS_FUNCTION_TEMPLATES["multiclass_classification"] - else: - loss_function_code = LOSS_FUNCTION_TEMPLATES["regression"] - - # Configure text embedder - if use_text_embedder: - text_embedder_code = GLOVE_TEXT_EMBEDDER - text_embedder_config = GLOVE_TEXT_EMBEDDER_CONFIG - else: - text_embedder_code = GLOVE_TEXT_EMBEDDER - text_embedder_config = GLOVE_TEXT_EMBEDDER_CONFIG - - # Format num_neighbors for the script - num_neighbors_str = str(num_neighbors) - - # Generate the script - script_content = TRAINING_SCRIPT_TEMPLATE.format( - dataset_import=dataset_import, - task_import=task_import, - dataset_class=dataset_class_name, - task_class=task_class_name, - working_dir=working_dir, - random_seed=random_seed, - epochs=epochs, - batch_size=batch_size, - learning_rate=learning_rate, - hidden_channels=hidden_channels, - num_gnn_layers=num_gnn_layers, - num_neighbors=num_neighbors_str, - dropout=dropout, - tune_metric=tune_metric, - higher_is_better=higher_is_better, - out_channels=out_channels, - text_embedder_code=text_embedder_code, - text_embedder_config=text_embedder_config, - loss_function_code=loss_function_code, - ) - - # Save the script - script_path = os.path.join(working_dir, "train_script.py") - with open(script_path, "w") as f: - f.write(script_content) - - logger.info(f"Generated training script at: {script_path}") - - config = { - "dataset_module": dataset_module_path, - "dataset_class": dataset_class_name, - "task_module": task_module_path, - "task_class": task_class_name, - "working_dir": working_dir, - "task_type": task_type, - "tune_metric": tune_metric, - "higher_is_better": higher_is_better, - "out_channels": out_channels, - "epochs": epochs, - "batch_size": batch_size, - "learning_rate": learning_rate, - "hidden_channels": hidden_channels, - "num_gnn_layers": num_gnn_layers, - "num_neighbors": num_neighbors, - "dropout": dropout, - "use_text_embedder": use_text_embedder, - "random_seed": random_seed, - } - - return { - "status": "success", - "script_content": script_content, - "script_path": script_path, - "config": config, - "message": f"Training script generated successfully at {script_path}", - } - - except Exception as e: - import traceback - return { - "status": "error", - "error": str(e), - "traceback": traceback.format_exc(), - } - - -# ============================================================================= -# Tool: Execute Training Script -# ============================================================================= - -def _normalize_script_path(script_path: str) -> str: - """ - Normalize the script path to handle various input formats. - - Handles cases like: - - Absolute paths: /app/.workdir/... - - Relative paths: ./.workdir/... or .workdir/... - - Just filename: train_script.py - - Paths with redundant components: /app/.workdir/..././.workdir/... - """ - # First, normalize the path to remove redundant separators and up-references - script_path = os.path.normpath(script_path) - - # If path exists as-is, return it - if os.path.exists(script_path): - return os.path.abspath(script_path) - - # Try getting working_dir from registry - try: - object_registry = ObjectRegistry() - working_dir = object_registry.get(str, "working_dir") - working_dir = os.path.abspath(working_dir) - - # Extract just the filename - filename = os.path.basename(script_path) - - # Try in working_dir - potential_path = os.path.join(working_dir, filename) - if os.path.exists(potential_path): - return potential_path - - # If script_path contains a session folder, try to extract it - # e.g., ".workdir/chat-session-xxx/train_script.py" -> use that session folder - path_parts = script_path.replace("\\", "/").split("/") - for i, part in enumerate(path_parts): - if part.startswith("chat-session-") or part.startswith("session-"): - # Reconstruct path from this point - session_path = os.path.join(working_dir, *path_parts[i:]) - if os.path.exists(session_path): - return session_path - # Also try just the session folder with filename - session_folder = os.path.join(working_dir, "..", part) - session_folder = os.path.normpath(session_folder) - if os.path.isdir(session_folder): - potential = os.path.join(session_folder, filename) - if os.path.exists(potential): - return potential - - except Exception: - pass - - # Return original (will fail but with proper error message) - return script_path - - -@tool -def execute_training_script( - script_path: str, - timeout: int = 3600, -) -> Dict[str, Any]: - """ - Executes the generated training script. - - Args: - script_path: Path to the training script (train_script.py) - timeout: Maximum execution time in seconds (default: 1 hour) - - Returns: - Dictionary containing: - - 'status': 'success' or 'error' - - 'output': Script stdout - - 'error_output': Script stderr (if any) - - 'return_code': Process return code - """ - import subprocess - - try: - # Normalize and resolve the script path - script_path = _normalize_script_path(script_path) - - if not os.path.exists(script_path): - # Provide helpful error message with debugging info - try: - object_registry = ObjectRegistry() - working_dir = object_registry.get(str, "working_dir") - except Exception: - working_dir = "unknown" - - return { - "status": "error", - "error": f"Script file not found at: {script_path}", - "debug_info": { - "working_dir": working_dir, - "cwd": os.getcwd(), - "original_path": script_path, - } - } - - # Run the script - # Ensure cwd is valid - use the directory containing the script - cwd = os.path.dirname(os.path.abspath(script_path)) - - # Set up environment with PYTHONPATH to ensure plexe imports work - # This is critical because plexe.relbench is a local module, not installed via pip - env = os.environ.copy() - - # Find the project root (where plexe package is located) - # From /app/.workdir/chat-session-xxx/ we need to go to /app/ - project_root = os.path.abspath(os.path.join(cwd, "..", "..")) - - # Also check if we're in Docker (/app) or local development - if os.path.exists("/app/plexe"): - project_root = "/app" - elif os.path.exists(os.path.join(project_root, "plexe")): - pass # project_root is correct - else: - # Try current working directory - original_cwd = os.getcwd() - if os.path.exists(os.path.join(original_cwd, "plexe")): - project_root = original_cwd - - # Prepend project root to PYTHONPATH - existing_pythonpath = env.get("PYTHONPATH", "") - env["PYTHONPATH"] = f"{project_root}:{cwd}:{existing_pythonpath}" if existing_pythonpath else f"{project_root}:{cwd}" - - logger.info(f"Executing training script: {script_path}") - logger.info(f"Working directory: {cwd}") - logger.info(f"PYTHONPATH: {env['PYTHONPATH']}") - - result = subprocess.run( - ["python", script_path], - capture_output=True, - text=True, - timeout=timeout, - cwd=cwd, - env=env, - ) - - return { - "status": "success" if result.returncode == 0 else "error", - "output": result.stdout, - "error_output": result.stderr, - "return_code": result.returncode, - "script_path": script_path, - "cwd": cwd, - "pythonpath": env["PYTHONPATH"], - } - - except subprocess.TimeoutExpired: - return { - "status": "error", - "error": f"Script execution timed out after {timeout} seconds", - } - except Exception as e: - import traceback - return { - "status": "error", - "error": str(e), - "traceback": traceback.format_exc(), - } - - -# ============================================================================= -# Tool: Get Dataset and Task Info from Registry -# ============================================================================= - -@tool -def get_dataset_task_info_from_registry() -> Dict[str, Any]: - """ - Retrieves information about the Dataset and Task classes from ObjectRegistry. - - This tool helps find the paths and class names for the Dataset and Task - that were generated by DatasetBuilder and TaskBuilder agents. - - Returns: - Dictionary containing: - - 'dataset_info': Information about the registered Dataset - - 'task_info': Information about the registered Task - - 'working_dir': The working directory being used - """ - import json - - try: - object_registry = ObjectRegistry() - - result = { - "dataset_info": None, - "task_info": None, - "working_dir": None, - } - - # Try to get dataset code info - try: - dataset_code_info = object_registry.get(dict, "database_code") - result["dataset_info"] = { - "class_name": dataset_code_info.get("class_name"), - "file_path": dataset_code_info.get("export_path"), - "module_name": dataset_code_info.get("module_name"), - } - if dataset_code_info.get("export_path"): - result["working_dir"] = os.path.dirname(dataset_code_info["export_path"]) - logger.info(f"✅ Found database_code in registry: {dataset_code_info.get('class_name')}") - except KeyError: - logger.warning("⚠️ database_code not found in registry. Attempting to load from file...") - - # Fallback: Try to load from dataset_metadata.json file - try: - working_dir = object_registry.get(str, "working_dir") - metadata_file = os.path.join(working_dir, "dataset_metadata.json") - - if os.path.exists(metadata_file): - with open(metadata_file, 'r') as f: - dataset_code_info = json.load(f) - - result["dataset_info"] = { - "class_name": dataset_code_info.get("class_name"), - "file_path": dataset_code_info.get("export_path"), - "module_name": dataset_code_info.get("module_name"), - } - if dataset_code_info.get("export_path"): - result["working_dir"] = os.path.dirname(dataset_code_info["export_path"]) - logger.info(f"✅ Loaded database_code from metadata file: {dataset_code_info.get('class_name')}") - - # Re-register it for future use - object_registry.register(dict, "database_code", dataset_code_info, overwrite=True) - else: - logger.warning(f"⚠️ Dataset metadata file not found: {metadata_file}") - except Exception as e: - logger.warning(f"⚠️ Could not load dataset metadata from file: {e}") - pass - - # Try to get task code info from registry - try: - task_code_info = object_registry.get(dict, "task_code") - result["task_info"] = { - "class_name": task_code_info.get("class_name"), - "file_path": task_code_info.get("export_path"), - "module_name": task_code_info.get("module_name"), - "task_type": task_code_info.get("task_type"), - "entity_table": task_code_info.get("entity_table"), - "target_col": task_code_info.get("target_col"), - } - logger.info(f"✅ Found task_code in registry: {task_code_info.get('class_name')}") - except KeyError: - logger.warning("⚠️ task_code not found in registry. Attempting to load from file...") - - # Fallback: Try to load from task_metadata.json file - try: - working_dir = object_registry.get(str, "working_dir") - metadata_file = os.path.join(working_dir, "task_metadata.json") - - if os.path.exists(metadata_file): - with open(metadata_file, 'r') as f: - task_code_info = json.load(f) - - result["task_info"] = { - "class_name": task_code_info.get("class_name"), - "file_path": task_code_info.get("export_path"), - "module_name": task_code_info.get("module_name"), - "task_type": task_code_info.get("task_type"), - "entity_table": task_code_info.get("entity_table"), - "target_col": task_code_info.get("target_col"), - } - logger.info(f"✅ Loaded task_code from metadata file: {task_code_info.get('class_name')}") - - # Re-register it for future use - object_registry.register(dict, "task_code", task_code_info, overwrite=True) - else: - logger.warning(f"⚠️ Metadata file not found: {metadata_file}") - except Exception as e: - logger.warning(f"⚠️ Could not load task metadata from file: {e}") - - # Try to get working directory if not found - if result["working_dir"] is None: - try: - working_dir = object_registry.get(str, "working_dir") - result["working_dir"] = working_dir - except KeyError: - pass - - return result - - except Exception as e: - import traceback - return { - "status": "error", - "error": str(e), - "traceback": traceback.format_exc(), - } - - -# ============================================================================= -# Tool: Validate Training Prerequisites -# ============================================================================= - -@tool -def validate_training_prerequisites( - dataset_module_path: str = None, - task_module_path: str = None, -) -> Dict[str, Any]: - """ - Validates that all prerequisites for training are in place. - - CRITICAL: This tool MUST be called before generating training code. - Both dataset.py and task.py files are REQUIRED for GNN training. - - Checks: - 1. Dataset module exists (dataset.py) - generated by DatasetBuilder - 2. Task module exists (task.py) - generated by TaskBuilder - 3. Required dependencies are installed - - Args: - dataset_module_path: Path to the dataset module. If None, will auto-detect - from ObjectRegistry or working directory. - task_module_path: Path to the task module. If None, will auto-detect - from ObjectRegistry or working directory. - - Returns: - Dictionary with validation results including: - - status: "valid" or "invalid" - - issues: List of critical issues that must be resolved - - warnings: List of non-critical warnings - - dataset_path: Resolved path to dataset module - - task_path: Resolved path to task module - """ - issues = [] - warnings = [] - object_registry = ObjectRegistry() - - # Auto-detect paths from registry if not provided - if dataset_module_path is None: - try: - dataset_info = object_registry.get(dict, "database_code") - dataset_module_path = dataset_info.get("export_path") - except KeyError: - pass - - if task_module_path is None: - try: - task_info = object_registry.get(dict, "task_code") - task_module_path = task_info.get("export_path") - except KeyError: - pass - - # Try to infer from working directory if still not found - working_dir = None - try: - working_dir = object_registry.get(str, "working_dir") - except KeyError: - try: - working_dir = object_registry.get(str, "current_chat_session_dir") - except KeyError: - pass - - if working_dir: - if dataset_module_path is None: - potential_dataset = os.path.join(working_dir, "dataset.py") - if os.path.exists(potential_dataset): - dataset_module_path = potential_dataset - - if task_module_path is None: - potential_task = os.path.join(working_dir, "task.py") - if os.path.exists(potential_task): - task_module_path = potential_task - - # ========================================================================= - # CRITICAL CHECK: Both dataset.py and task.py MUST exist - # ========================================================================= - - # Check dataset module - if dataset_module_path is None: - issues.append( - "CRITICAL: dataset.py not found! " - "DatasetBuilder agent must create dataset.py before GNN training can begin. " - "Please run DatasetBuilder first to generate the Dataset class." - ) - elif not os.path.exists(dataset_module_path): - issues.append( - f"CRITICAL: Dataset module not found at '{dataset_module_path}'! " - "The DatasetBuilder agent must create this file before training." - ) - else: - # Verify it's a valid Python file with a Dataset class - try: - with open(dataset_module_path, 'r') as f: - content = f.read() - if 'class ' not in content or 'Dataset' not in content: - warnings.append( - f"Dataset file exists but may not contain a valid Dataset class: {dataset_module_path}" - ) - except Exception as e: - warnings.append(f"Could not read dataset file for validation: {e}") - - # Check task module - if task_module_path is None: - issues.append( - "CRITICAL: task.py not found! " - "TaskBuilder agent must create task.py before GNN training can begin. " - "Please run TaskBuilder first to generate the Task class." - ) - elif not os.path.exists(task_module_path): - issues.append( - f"CRITICAL: Task module not found at '{task_module_path}'! " - "The TaskBuilder agent must create this file before training." - ) - else: - # Verify it's a valid Python file with a Task class - try: - with open(task_module_path, 'r') as f: - content = f.read() - if 'class ' not in content or 'Task' not in content: - warnings.append( - f"Task file exists but may not contain a valid Task class: {task_module_path}" - ) - except Exception as e: - warnings.append(f"Could not read task file for validation: {e}") - - # Check required packages - required_packages = [ - "torch", - "torch_geometric", - "torch_frame", - "sentence_transformers", - "pandas", - "numpy", - "tqdm", - ] - - for package in required_packages: - try: - __import__(package) - except ImportError: - issues.append(f"Required package not installed: {package}") - - # Check CUDA availability - try: - import torch - if torch.cuda.is_available(): - warnings.append("CUDA is available - training will use GPU") - else: - warnings.append("CUDA not available - training will use CPU (slower)") - except ImportError: - pass - - # Summary of required files - files_summary = { - "dataset.py": { - "path": dataset_module_path, - "exists": dataset_module_path is not None and os.path.exists(dataset_module_path), - "required": True, - "created_by": "DatasetBuilder agent" - }, - "task.py": { - "path": task_module_path, - "exists": task_module_path is not None and os.path.exists(task_module_path), - "required": True, - "created_by": "TaskBuilder agent" - } - } - - return { - "status": "valid" if len(issues) == 0 else "invalid", - "issues": issues, - "warnings": warnings, - "dataset_path": dataset_module_path, - "task_path": task_module_path, - "working_dir": working_dir, - "required_files": files_summary, - "message": ( - "All prerequisites validated successfully. Ready for GNN training." - if len(issues) == 0 else - f"CANNOT PROCEED: {len(issues)} critical issue(s) must be resolved before training." - ) - } diff --git a/plexe/tools/graph_processing.py b/plexe/tools/graph_processing.py deleted file mode 100644 index d5bbf443..00000000 --- a/plexe/tools/graph_processing.py +++ /dev/null @@ -1,1871 +0,0 @@ -""" -Tools for graph processing and construction for the Relational Graph Architect Agent. -""" - -import re -import logging -from typing import Dict, List, Any, Tuple, Optional, Union -from smolagents import tool -import pandas as pd -import numpy as np -import torch - -# Imports for implementations -from sqlalchemy import create_engine, inspect, text -from sklearn.preprocessing import StandardScaler, LabelEncoder -from torch_geometric.data import HeteroData - -# ObjectRegistry for sharing data between agents -from plexe.core.object_registry import ObjectRegistry - -logger = logging.getLogger(__name__) - - -@tool -def get_table_columns(db_connection: str, table_name: str) -> List[str]: - """ - Get the list of column names for a specific table in the database. - Use this to verify column names before writing SQL queries. - - Args: - db_connection: Database connection string. - table_name: Name of the table. - - Returns: - List of column names. - """ - try: - engine = create_engine(db_connection) - inspector = inspect(engine) - columns = [col['name'] for col in inspector.get_columns(table_name)] - return columns - except Exception as e: - logger.error(f"Error getting columns for table {table_name}: {e}") - return [] - - -# ============================================================================= -# Unified Schema Cache Key -# ============================================================================= -# Both TemporalSupervisor and GraphArchitect need schema information. -# We use a unified cache key to avoid redundant DB queries. - -UNIFIED_SCHEMA_CACHE_KEY = "unified_db_schema" - - -def _get_cached_schema(db_connection: str) -> Optional[Dict[str, Any]]: - """ - Check if schema is already cached in ObjectRegistry. - Returns cached schema if connection string matches, None otherwise. - """ - try: - object_registry = ObjectRegistry() - cached = object_registry.get(dict, UNIFIED_SCHEMA_CACHE_KEY) - - # Verify connection string matches - if cached.get("_connection_string") == db_connection: - logger.info("Using cached unified schema from ObjectRegistry") - return cached - except KeyError: - pass - return None - - -def _cache_schema(db_connection: str, schema: Dict[str, Any]) -> None: - """Cache schema in ObjectRegistry with connection string for validation.""" - try: - object_registry = ObjectRegistry() - schema["_connection_string"] = db_connection - object_registry.register(dict, UNIFIED_SCHEMA_CACHE_KEY, schema, overwrite=True) - object_registry.register(str, "db_connection_string", db_connection, overwrite=True) - logger.info("Cached unified schema in ObjectRegistry") - except Exception as e: - logger.warning(f"Could not cache schema: {e}") - - -# ============================================================================= -# Type Definitions for Agent Clarity -# ============================================================================= -# These type aliases help LLM Agents understand expected data structures. -# When passing data via REST API or non-Python environments, use List/Dict. - -# Node features can be provided as Python List, NumPy array, or PyTorch Tensor -NodeFeatures = Union[List[List[float]], np.ndarray, torch.Tensor] - -# Node data structure: either just features, or dict with 'x' (features) and 't' (timestamps) -NodeData = Union[ - NodeFeatures, # Direct features tensor/list - Dict[str, NodeFeatures] # {'x': features, 't': timestamps} -] - -# Nodes dictionary maps node type (table name) to node data -NodesDict = Dict[str, NodeData] - -# Edge index: shape (2, num_edges) - source indices in row 0, target indices in row 1 -EdgeIndex = Union[List[List[int]], np.ndarray, torch.Tensor] - -# Edge type tuple: (source_node_type, relation_name, target_node_type) -EdgeType = Tuple[str, str, str] - -# Edges dictionary maps edge types to edge indices -EdgesDict = Dict[EdgeType, EdgeIndex] - - -def _normalize_sql_type(sql_type: str) -> Dict[str, Any]: - """ - Normalize SQL type string to a standardized modality category. - - Following RDL paper Section 3.4.3 (Multi-modal Node Encoders): - - Numeric: For continuous values (integers, floats, decimals) - - Categorical: For discrete values with limited cardinality (enums, small varchars) - - Temporal: For temporal data (timestamps, dates, times) - Critical for RDL - - Text: For free-form text (large varchars, text fields) - - Binary: For binary/blob data - - These modality names match encode_multi_modal_features() expected values. - - Returns: - Dict with 'modality', 'original_type', and 'is_temporal' flag - """ - sql_type_upper = sql_type.upper() - - # Temporal types - Critical for RDL (Section 2.1: "Temporality as First-Class Citizen") - temporal_patterns = [ - 'TIMESTAMP', 'DATETIME', 'DATE', 'TIME', - 'TIMESTAMPTZ', 'TIMETZ', 'INTERVAL' - ] - for pattern in temporal_patterns: - if pattern in sql_type_upper: - return { - 'modality': 'Temporal', - 'original_type': sql_type, - 'is_temporal': True - } - - # Numerical types - numerical_patterns = [ - 'INT', 'INTEGER', 'SMALLINT', 'BIGINT', 'TINYINT', - 'FLOAT', 'DOUBLE', 'REAL', 'DECIMAL', 'NUMERIC', - 'MONEY', 'SERIAL', 'BIGSERIAL' - ] - for pattern in numerical_patterns: - if pattern in sql_type_upper: - return { - 'modality': 'Numeric', - 'original_type': sql_type, - 'is_temporal': False - } - - # Boolean - if 'BOOL' in sql_type_upper or 'BIT' in sql_type_upper: - return { - 'modality': 'Categorical', - 'original_type': sql_type, - 'is_temporal': False - } - - # Text types - check length to distinguish Categorical vs Text - if any(t in sql_type_upper for t in ['VARCHAR', 'CHAR', 'NVARCHAR', 'NCHAR']): - # Extract length if present, e.g., VARCHAR(255) - match = re.search(r'\((\d+)\)', sql_type) - if match: - length = int(match.group(1)) - # Short strings are likely categorical (enums, codes, etc.) - if length <= 50: - return { - 'modality': 'Categorical', - 'original_type': sql_type, - 'is_temporal': False - } - # Longer or unspecified length -> Text - return { - 'modality': 'Text', - 'original_type': sql_type, - 'is_temporal': False - } - - # Large text types - if any(t in sql_type_upper for t in ['TEXT', 'CLOB', 'LONGTEXT', 'MEDIUMTEXT']): - return { - 'modality': 'Text', - 'original_type': sql_type, - 'is_temporal': False - } - - # Binary types - if any(t in sql_type_upper for t in ['BLOB', 'BINARY', 'BYTEA', 'VARBINARY', 'IMAGE']): - return { - 'modality': 'Binary', - 'original_type': sql_type, - 'is_temporal': False - } - - # JSON types - if 'JSON' in sql_type_upper: - return { - 'modality': 'Text', - 'original_type': sql_type, - 'is_temporal': False - } - - # UUID - if 'UUID' in sql_type_upper: - return { - 'modality': 'Categorical', - 'original_type': sql_type, - 'is_temporal': False - } - - # ENUM types - if 'ENUM' in sql_type_upper: - return { - 'modality': 'Categorical', - 'original_type': sql_type, - 'is_temporal': False - } - - # Default fallback - return { - 'modality': 'Categorical', - 'original_type': sql_type, - 'is_temporal': False - } - - -def _classify_table_type( - table_name: str, - row_count: int, - has_temporal_columns: bool, - temporal_column_count: int, - is_referenced_by_fk: bool, - has_outgoing_fks: bool -) -> str: - """ - Classify table as Fact or Dimension following RDL paper Section 2.1. - - Fact Tables (Event/Transaction tables): - - Usually large (many rows) - - Have temporal columns (timestamps) - - Often have foreign keys pointing to dimension tables - - Examples: transactions, orders, events, logs - - Dimension Tables (Entity/Reference tables): - - Usually smaller - - May not have temporal columns (or only created_at/updated_at) - - Are referenced by fact tables via foreign keys - - Examples: users, products, categories - - Returns: - 'Fact', 'Dimension', or 'Unknown' - """ - # Heuristics for classification - score_fact = 0 - score_dim = 0 - - # Large tables are more likely to be Fact tables - if row_count > 10000: - score_fact += 2 - elif row_count > 1000: - score_fact += 1 - elif row_count < 100: - score_dim += 2 - elif row_count < 1000: - score_dim += 1 - - # Multiple temporal columns suggest Fact table (event timestamps) - if temporal_column_count >= 2: - score_fact += 2 - elif has_temporal_columns: - score_fact += 1 - - # Being referenced by FKs suggests Dimension table - if is_referenced_by_fk: - score_dim += 2 - - # Having outgoing FKs suggests Fact table (joins to dimensions) - if has_outgoing_fks: - score_fact += 1 - - # Table name heuristics - fact_keywords = ['transaction', 'order', 'event', 'log', 'history', 'activity', 'action', 'record'] - dim_keywords = ['user', 'customer', 'product', 'category', 'type', 'status', 'config', 'setting'] - - table_lower = table_name.lower() - if any(kw in table_lower for kw in fact_keywords): - score_fact += 1 - if any(kw in table_lower for kw in dim_keywords): - score_dim += 1 - - # Determine classification - if score_fact > score_dim: - return 'Fact' - elif score_dim > score_fact: - return 'Dimension' - else: - return 'Unknown' - - -@tool -def extract_schema_metadata(db_connection: str, force_refresh: bool = False) -> Dict[str, Any]: - """ - Retrieves comprehensive schema metadata for Relational Deep Learning (RDL). - - This tool extracts table structures, relationships, and temporal information - following the RDL paper principles where "Temporality is a First-Class Citizen" (Section 2.1). - - **IMPORTANT**: This tool uses a unified schema cache. If TemporalSupervisor has - already analyzed the schema using `discover_temporal_columns`, this will reuse - that cached information and extend it with graph-specific metadata. - - Key features: - - Identifies temporal columns (τ_v) for time-aware message passing - - Classifies tables as Fact (event) or Dimension (entity) tables - - Normalizes data types to modalities (Numerical, Categorical, Time, Text, Binary) - - Supports composite foreign keys for complex relationships - - Provides row counts for sampling strategy decisions - - Args: - db_connection: A database connection string - (e.g., 'sqlite:///data.db', 'postgresql://user:pass@host/db'). - force_refresh: If True, bypass cache and re-query database. Default False. - - Returns: - A dictionary containing: - - 'tables': Dict[table_name, TableInfo] with columns, row_count, table_type, temporal_columns - - 'relationships': List of foreign key relationships (supports composite keys) - - 'temporal_summary': Overview of temporal structure across all tables - - 'recommended_target_tables': Suggested tables for prediction tasks - """ - # Check for cached schema first - if not force_refresh: - cached = _get_cached_schema(db_connection) - if cached and "tables" in cached and "relationships" in cached: - logger.info("Returning cached schema from unified cache") - # Also register under graph_schema_metadata for backwards compatibility - try: - object_registry = ObjectRegistry() - object_registry.register(dict, "graph_schema_metadata", cached, overwrite=True) - except Exception: - pass - return cached - - try: - engine = create_engine(db_connection) - inspector = inspect(engine) - - schema_info = { - "tables": {}, - "relationships": [], - "temporal_summary": { - "tables_with_timestamps": [], - "primary_temporal_columns": {}, - "overall_date_range": {"min": None, "max": None} - }, - "recommended_target_tables": [] - } - - table_names = inspector.get_table_names() - - # First pass: collect which tables are referenced by FKs - referenced_tables = set() - tables_with_outgoing_fks = set() - for table_name in table_names: - fks = inspector.get_foreign_keys(table_name) - if fks: - tables_with_outgoing_fks.add(table_name) - for fk in fks: - if fk.get("referred_table"): - referenced_tables.add(fk["referred_table"]) - - all_min_dates = [] - all_max_dates = [] - - for table_name in table_names: - # Get Columns & PKs - columns = inspector.get_columns(table_name) - pk_constraint = inspector.get_pk_constraint(table_name) - pk_cols = pk_constraint.get("constrained_columns", []) - - col_details = [] - temporal_columns = [] - - for col in columns: - # Normalize the SQL type to modality - type_info = _normalize_sql_type(str(col["type"])) - - col_info = { - "name": col["name"], - "original_type": type_info["original_type"], - "modality": type_info["modality"], - "is_primary_key": col["name"] in pk_cols, - "is_temporal": type_info["is_temporal"], - "nullable": col.get("nullable", True) - } - col_details.append(col_info) - - # Track temporal columns - if type_info["is_temporal"]: - temporal_columns.append(col["name"]) - - # Get row count for table classification - row_count = 0 - try: - with engine.connect() as conn: - # Use COUNT(*) for accurate count - result = conn.execute(text(f'SELECT COUNT(*) FROM "{table_name}"')) - row_count = result.scalar() or 0 - except Exception as e: - # Fallback if count fails - row_count = -1 # Unknown - - # Get date ranges for temporal columns - temporal_ranges = {} - for temp_col in temporal_columns: - try: - with engine.connect() as conn: - query = text(f'SELECT MIN("{temp_col}"), MAX("{temp_col}") FROM "{table_name}"') - result = conn.execute(query).fetchone() - if result and result[0] and result[1]: - temporal_ranges[temp_col] = { - "min": str(result[0]), - "max": str(result[1]) - } - all_min_dates.append(result[0]) - all_max_dates.append(result[1]) - except Exception: - pass - - # Classify table type - table_type = _classify_table_type( - table_name=table_name, - row_count=row_count, - has_temporal_columns=len(temporal_columns) > 0, - temporal_column_count=len(temporal_columns), - is_referenced_by_fk=table_name in referenced_tables, - has_outgoing_fks=table_name in tables_with_outgoing_fks - ) - - # Identify primary temporal column (most likely to be the event timestamp) - primary_temporal_col = None - if temporal_columns: - # Prefer columns with common timestamp names - priority_names = ['created_at', 'timestamp', 'event_time', 'date', 'time', 'datetime'] - for priority in priority_names: - for tc in temporal_columns: - if priority in tc.lower(): - primary_temporal_col = tc - break - if primary_temporal_col: - break - # Default to first temporal column - if not primary_temporal_col: - primary_temporal_col = temporal_columns[0] - - schema_info["tables"][table_name] = { - "columns": col_details, - "primary_keys": pk_cols, - "row_count": row_count, - "table_type": table_type, - "temporal_columns": temporal_columns, - "primary_temporal_column": primary_temporal_col, - "temporal_ranges": temporal_ranges if temporal_ranges else None, - "column_count": len(col_details), - "modality_summary": { - modality: sum(1 for c in col_details if c["modality"] == modality) - for modality in ["Numerical", "Categorical", "Time", "Text", "Binary"] - if any(c["modality"] == modality for c in col_details) - } - } - - # Track temporal summary - if temporal_columns: - schema_info["temporal_summary"]["tables_with_timestamps"].append(table_name) - if primary_temporal_col: - schema_info["temporal_summary"]["primary_temporal_columns"][table_name] = primary_temporal_col - - # Get Foreign Keys (Edges) - Support composite keys - fks = inspector.get_foreign_keys(table_name) - for fk in fks: - if len(fk["constrained_columns"]) > 0: - relationship = { - "source_table": table_name, - "source_columns": fk["constrained_columns"], # List for composite keys - "target_table": fk["referred_table"], - "target_columns": fk["referred_columns"], # List for composite keys - "is_composite": len(fk["constrained_columns"]) > 1, - # Backwards compatibility - single column reference - "source_col": fk["constrained_columns"][0], - "target_col": fk["referred_columns"][0] if fk["referred_columns"] else None - } - schema_info["relationships"].append(relationship) - - # Calculate overall temporal range - if all_min_dates and all_max_dates: - schema_info["temporal_summary"]["overall_date_range"] = { - "min": str(min(all_min_dates)), - "max": str(max(all_max_dates)) - } - - # Recommend target tables (Dimension tables with good temporal coverage) - for table_name, table_info in schema_info["tables"].items(): - if table_info["table_type"] == "Dimension" and table_info["row_count"] > 0: - schema_info["recommended_target_tables"].append({ - "table": table_name, - "row_count": table_info["row_count"], - "reason": "Dimension table - likely entity for prediction" - }) - elif table_info["table_type"] == "Fact" and table_info["temporal_columns"]: - schema_info["recommended_target_tables"].append({ - "table": table_name, - "row_count": table_info["row_count"], - "reason": "Fact table with temporal data - good for event prediction" - }) - - # Add alias for backwards compatibility - schema_info["foreign_keys"] = schema_info["relationships"] - - # Cache in unified schema registry - _cache_schema(db_connection, schema_info) - - # Also register under graph_schema_metadata for backwards compatibility - try: - object_registry = ObjectRegistry() - object_registry.register(dict, "graph_schema_metadata", schema_info, overwrite=True) - logger.info("Registered graph_schema_metadata in ObjectRegistry") - except Exception as e: - logger.warning(f"Could not register schema in ObjectRegistry: {e}") - - return schema_info - - except Exception as e: - import traceback - return { - "error": f"Failed to extract schema: {str(e)}", - "traceback": traceback.format_exc(), - "tables": {}, - "relationships": [], - "temporal_summary": {"tables_with_timestamps": [], "primary_temporal_columns": {}} - } - - -@tool -def get_cached_schema() -> Dict[str, Any]: - """ - Retrieve the cached unified schema from ObjectRegistry. - - Use this tool when you need schema information that has already been discovered - by either TemporalSupervisor (discover_temporal_columns) or GraphArchitect - (extract_schema_metadata). This avoids redundant database queries. - - Returns: - Dictionary containing: - - 'found': Whether cached schema exists - - 'schema': The cached schema (if found) - - 'source': Which tool originally cached it ('temporal', 'graph', or 'unknown') - - 'db_connection': The database connection string used - - Example: - >>> result = get_cached_schema() - >>> if result['found']: - ... tables = result['schema']['tables'] - ... print(f"Found {len(tables)} tables in cache") - """ - try: - object_registry = ObjectRegistry() - - # Try unified cache first - try: - unified = object_registry.get(dict, UNIFIED_SCHEMA_CACHE_KEY) - if unified: - db_conn = unified.get("_connection_string", "unknown") - source = "unified" - - # Determine which tool populated it - if unified.get("tables") and unified.get("relationships"): - source = "graph" - elif unified.get("temporal_summary"): - source = "temporal" - - return { - "found": True, - "schema": unified, - "source": source, - "db_connection": db_conn - } - except KeyError: - pass - - # Try graph_schema_metadata - try: - graph_schema = object_registry.get(dict, "graph_schema_metadata") - if graph_schema: - db_conn = object_registry.get(str, "db_connection_string") - return { - "found": True, - "schema": graph_schema, - "source": "graph", - "db_connection": db_conn - } - except KeyError: - pass - - # Try temporal_schema_info - try: - temporal_info = object_registry.get(dict, "temporal_schema_info") - if temporal_info: - db_conn = object_registry.get(str, "db_connection_string") - return { - "found": True, - "schema": temporal_info, - "source": "temporal", - "db_connection": db_conn - } - except KeyError: - pass - - return { - "found": False, - "schema": None, - "source": None, - "db_connection": None, - "message": "No cached schema found. Use discover_temporal_columns or extract_schema_metadata first." - } - - except Exception as e: - return { - "found": False, - "error": str(e), - "schema": None, - "source": None, - "db_connection": None - } - - -@tool -def load_table_data( - db_connection: str, - table_name: str, - columns: Optional[List[str]] = None, - limit: Optional[int] = None, - where_clause: Optional[str] = None -) -> Dict[str, Any]: - """ - Load data from a database table for graph construction. - - Use this tool to retrieve actual data from tables for building node features. - Combines with extract_schema_metadata which only provides metadata. - - Args: - db_connection: SQLAlchemy connection string. - table_name: Name of the table to load. - columns: Optional list of columns to select. If None, selects all. - limit: Optional row limit for large tables. - where_clause: Optional WHERE clause (without 'WHERE' keyword). - - Returns: - Dictionary containing: - - 'data': List of row dictionaries - - 'columns': List of column names - - 'row_count': Number of rows returned - - 'dataframe': Pandas DataFrame (for direct use in encoding) - - Example: - >>> result = load_table_data(conn, 'customers', columns=['id', 'name', 'created_at']) - >>> df = result['dataframe'] - >>> ids = df['id'].tolist() - """ - try: - engine = create_engine(db_connection) - - # Build query - if columns: - cols_str = ', '.join([f'"{c}"' for c in columns]) - else: - cols_str = '*' - - query = f'SELECT {cols_str} FROM "{table_name}"' - - if where_clause: - query += f' WHERE {where_clause}' - - if limit: - query += f' LIMIT {limit}' - - with engine.connect() as conn: - df = pd.read_sql(text(query), conn) - - # Register in ObjectRegistry for other tools - try: - object_registry = ObjectRegistry() - object_registry.register(pd.DataFrame, f"table_data_{table_name}", df, overwrite=True) - except Exception as e: - logger.debug(f"Could not register table data: {e}") - - return { - "data": df.to_dict(orient='records')[:100], # First 100 for preview - "columns": list(df.columns), - "row_count": len(df), - "dataframe": df, - "table_name": table_name - } - - except Exception as e: - import traceback - error_msg = str(e) - - # Check for common column name errors and provide helpful hints - hint = "" - if "column" in error_msg.lower() and ("does not exist" in error_msg.lower() or "not found" in error_msg.lower() or "unknown" in error_msg.lower()): - hint = ( - " HINT: Column name error! Use get_table_columns(db_connection, table_name) " - "to verify exact column names. PostgreSQL uses snake_case (e.g., 'owner_user_id', NOT 'OwnerUserId')." - ) - - return { - "error": f"Failed to load table data: {error_msg}{hint}", - "traceback": traceback.format_exc() - } - - -@tool -def export_tables_to_csv( - db_connection: str, - output_dir: str, - table_names: Optional[List[str]] = None -) -> Dict[str, Any]: - """ - Export database tables to CSV files for subsequent data processing. - - This tool connects to the database, exports specified tables (or all tables) - to CSV files in the given directory, and registers the path in ObjectRegistry - for use by DatasetBuilder agent. - - Args: - db_connection: SQLAlchemy connection string (e.g., postgresql+psycopg2://user:pass@host:port/db) - output_dir: Directory to save CSV files. Will be created if it doesn't exist. - table_names: Optional list of table names to export. If None, exports all tables. - - Returns: - Dictionary containing: - - 'success': Boolean indicating success - - 'exported_tables': List of exported table names - - 'output_dir': Path to the output directory - - 'file_info': Dict with table name -> {path, row_count, columns} - - 'registry_key': Key under which the path is registered - - Example: - >>> result = export_tables_to_csv( - ... "postgresql+psycopg2://user:pass@localhost:5432/mydb", - ... "/workdir/csv_files" - ... ) - >>> print(result['exported_tables']) - ['users', 'orders', 'products'] - """ - import os - from pathlib import Path - - try: - engine = create_engine(db_connection) - inspector = inspect(engine) - - # Get table names if not specified - if table_names is None: - table_names = inspector.get_table_names() - - if not table_names: - return { - "success": False, - "error": "No tables found in the database." - } - - # Create output directory - output_path = Path(output_dir) - output_path.mkdir(parents=True, exist_ok=True) - - exported_tables = [] - file_info = {} - - # Export each table - with engine.connect() as conn: - for table_name in table_names: - try: - query = text(f'SELECT * FROM "{table_name}"') - df = pd.read_sql(query, conn) - - csv_path = output_path / f"{table_name}.csv" - df.to_csv(csv_path, index=False) - - exported_tables.append(table_name) - file_info[table_name] = { - "path": str(csv_path), - "row_count": len(df), - "columns": list(df.columns) - } - - logger.info(f"✅ Exported '{table_name}' ({len(df)} rows) to {csv_path}") - - except Exception as e: - logger.warning(f"⚠️ Failed to export table '{table_name}': {e}") - file_info[table_name] = {"error": str(e)} - - # Register the path in ObjectRegistry - try: - object_registry = ObjectRegistry() - registry_key = "path_raw_csv_files" - object_registry.register(str, registry_key, str(output_path), overwrite=True) - logger.info(f"✅ Registered CSV path under key '{registry_key}'") - except Exception as e: - logger.warning(f"Could not register path in registry: {e}") - registry_key = None - - return { - "success": True, - "exported_tables": exported_tables, - "output_dir": str(output_path), - "file_info": file_info, - "registry_key": registry_key, - "total_tables": len(exported_tables) - } - - except Exception as e: - import traceback - return { - "success": False, - "error": f"Failed to export tables: {str(e)}", - "traceback": traceback.format_exc() - } - - -# ============================================================================= -# EntityMapper: Centralized ID Mapping for Graph Construction -# ============================================================================= -# Following RDL paper: Maintains bidirectional mapping between database PKs -# and contiguous graph indices. Essential for post-prediction interpretation. - -class EntityMapper: - """ - Centralized entity mapping manager for Relational Deep Learning. - - This class maintains bidirectional mappings between original database IDs - (UUIDs, strings, non-contiguous integers) and contiguous graph indices - required by PyTorch Geometric. - - Key Features: - - Bidirectional mapping: ID -> Index and Index -> ID - - Multi-table support: Manages mappings for all entity types - - Prediction interpretation: Map predicted node indices back to original IDs - - Serializable: Can be saved/loaded for model deployment - - Example: - >>> mapper = EntityMapper() - >>> mapper.add_entities('customers', ['C001', 'C002', 'C003']) - >>> mapper.add_entities('products', ['P100', 'P200']) - >>> - >>> # Convert FK to edge index - >>> customer_idx = mapper.id_to_index('customers', 'C001') # Returns 0 - >>> product_idx = mapper.id_to_index('products', 'P200') # Returns 1 - >>> - >>> # After GNN prediction: node 0 is fraud - >>> fraud_customer = mapper.index_to_id('customers', 0) # Returns 'C001' - """ - - def __init__(self): - self._mappings: Dict[str, Dict[str, Any]] = {} - self._stats: Dict[str, int] = {} - - def add_entities(self, entity_type: str, original_ids: List[Any]) -> Dict[str, Any]: - """ - Register entities of a specific type and create index mappings. - - Args: - entity_type: The entity/table name (e.g., 'customers', 'orders') - original_ids: List of original database IDs - - Returns: - Mapping info with id_to_idx, idx_to_id, and num_nodes - """ - if original_ids is None or len(original_ids) == 0: - self._mappings[entity_type] = { - "id_to_idx": {}, - "idx_to_id": {}, - "num_nodes": 0 - } - return self._mappings[entity_type] - - # Convert to list if numpy array - if isinstance(original_ids, np.ndarray): - original_ids = original_ids.tolist() - - # Create ordered unique list (preserve insertion order) - unique_ids = [] - seen = set() - for id_val in original_ids: - hashable_id = str(id_val) if not isinstance(id_val, (int, str, float)) else id_val - if hashable_id not in seen: - unique_ids.append(id_val) - seen.add(hashable_id) - - # Create bidirectional mappings - id_to_idx = {id_val: idx for idx, id_val in enumerate(unique_ids)} - idx_to_id = {idx: id_val for idx, id_val in enumerate(unique_ids)} - - self._mappings[entity_type] = { - "id_to_idx": id_to_idx, - "idx_to_id": idx_to_id, - "num_nodes": len(unique_ids) - } - self._stats[entity_type] = len(unique_ids) - - return self._mappings[entity_type] - - def id_to_index(self, entity_type: str, original_id: Any) -> Optional[int]: - """Convert original database ID to contiguous graph index.""" - if entity_type not in self._mappings: - return None - return self._mappings[entity_type]["id_to_idx"].get(original_id) - - def index_to_id(self, entity_type: str, index: int) -> Optional[Any]: - """Convert graph index back to original database ID (for prediction interpretation).""" - if entity_type not in self._mappings: - return None - return self._mappings[entity_type]["idx_to_id"].get(index) - - def batch_id_to_index(self, entity_type: str, original_ids: List[Any]) -> List[int]: - """Convert a batch of IDs to indices, filtering out unmapped IDs.""" - if entity_type not in self._mappings: - return [] - id_to_idx = self._mappings[entity_type]["id_to_idx"] - return [id_to_idx[id_val] for id_val in original_ids if id_val in id_to_idx] - - def batch_index_to_id(self, entity_type: str, indices: List[int]) -> List[Any]: - """Convert a batch of indices back to original IDs.""" - if entity_type not in self._mappings: - return [] - idx_to_id = self._mappings[entity_type]["idx_to_id"] - return [idx_to_id[idx] for idx in indices if idx in idx_to_id] - - def get_mapping(self, entity_type: str) -> Optional[Dict[str, Any]]: - """Get the full mapping for an entity type.""" - return self._mappings.get(entity_type) - - def get_all_mappings(self) -> Dict[str, Dict[str, Any]]: - """Get all mappings (for serialization).""" - return self._mappings.copy() - - def get_num_nodes(self, entity_type: str) -> int: - """Get the number of nodes for an entity type.""" - if entity_type not in self._mappings: - return 0 - return self._mappings[entity_type]["num_nodes"] - - def get_entity_types(self) -> List[str]: - """Get list of all registered entity types.""" - return list(self._mappings.keys()) - - def summary(self) -> Dict[str, Any]: - """Get a summary of the mapper state.""" - return { - "entity_types": self.get_entity_types(), - "node_counts": self._stats.copy(), - "total_nodes": sum(self._stats.values()) - } - - def to_dict(self) -> Dict[str, Any]: - """Serialize mapper to dictionary (for saving).""" - return { - "mappings": self._mappings, - "stats": self._stats - } - - @classmethod - def from_dict(cls, data: Dict[str, Any]) -> 'EntityMapper': - """Deserialize mapper from dictionary (for loading).""" - mapper = cls() - mapper._mappings = data.get("mappings", {}) - mapper._stats = data.get("stats", {}) - return mapper - - -# Global mapper instance (can be used across tool calls) -_global_entity_mapper: Optional[EntityMapper] = None - - -def get_global_entity_mapper() -> EntityMapper: - """Get or create the global EntityMapper instance.""" - global _global_entity_mapper - if _global_entity_mapper is None: - _global_entity_mapper = EntityMapper() - return _global_entity_mapper - - -def reset_global_entity_mapper() -> None: - """Reset the global EntityMapper (for new graph construction).""" - global _global_entity_mapper - _global_entity_mapper = EntityMapper() - - -# ============================================================================= -# Semantic Relation Naming -# ============================================================================= -# Following RDL paper: Relations should have semantic meaning. -# E.g., ('customer', 'places', 'order') not ('customer', 'fk_order_id', 'order') - -def generate_semantic_relation_name( - source_table: str, - target_table: str, - fk_column: str, - is_reverse: bool = False -) -> str: - """ - Generate a semantic relation name based on table names and FK column. - - Following RDL paper best practices for meaningful edge types. - - Args: - source_table: Source entity type (e.g., 'orders') - target_table: Target entity type (e.g., 'customers') - fk_column: Foreign key column name (e.g., 'customer_id') - is_reverse: If True, generate reverse relation name - - Returns: - Semantic relation name (e.g., 'placed_by' for order->customer) - - Examples: - Forward: ('orders', 'placed_by', 'customers') - Reverse: ('customers', 'places', 'orders') - """ - # Common semantic patterns based on table/column names - semantic_patterns = { - # Customer/User related - ('order', 'customer'): ('placed_by', 'places'), - ('order', 'user'): ('placed_by', 'places'), - ('transaction', 'customer'): ('made_by', 'makes'), - ('transaction', 'user'): ('made_by', 'makes'), - ('review', 'customer'): ('written_by', 'writes'), - ('review', 'user'): ('written_by', 'writes'), - ('purchase', 'customer'): ('made_by', 'makes'), - ('purchase', 'user'): ('made_by', 'makes'), - - # Product related - ('order', 'product'): ('contains', 'ordered_in'), - ('order_item', 'product'): ('contains', 'included_in'), - ('review', 'product'): ('reviews', 'reviewed_by'), - ('cart', 'product'): ('contains', 'in_cart'), - ('wishlist', 'product'): ('contains', 'wishlisted_by'), - - # Category/Type related - ('product', 'category'): ('belongs_to', 'contains'), - ('product', 'brand'): ('manufactured_by', 'manufactures'), - ('item', 'category'): ('belongs_to', 'contains'), - - # Location related - ('order', 'address'): ('shipped_to', 'receives'), - ('customer', 'address'): ('lives_at', 'residence_of'), - ('user', 'address'): ('lives_at', 'residence_of'), - ('store', 'location'): ('located_at', 'hosts'), - - # Payment related - ('order', 'payment'): ('paid_with', 'pays_for'), - ('transaction', 'payment_method'): ('uses', 'used_by'), - - # Employee/Staff related - ('order', 'employee'): ('handled_by', 'handles'), - ('task', 'employee'): ('assigned_to', 'assigned'), - ('project', 'employee'): ('worked_on_by', 'works_on'), - - # Generic fallbacks - ('item', 'order'): ('part_of', 'has_item'), - ('detail', 'master'): ('belongs_to', 'has_detail'), - } - - # Normalize table names for matching - src_lower = source_table.lower().rstrip('s') # Remove plural 's' - tgt_lower = target_table.lower().rstrip('s') - - # Try to find a matching pattern - key = (src_lower, tgt_lower) - if key in semantic_patterns: - forward_rel, reverse_rel = semantic_patterns[key] - return reverse_rel if is_reverse else forward_rel - - # Try reverse key - reverse_key = (tgt_lower, src_lower) - if reverse_key in semantic_patterns: - forward_rel, reverse_rel = semantic_patterns[reverse_key] - return forward_rel if is_reverse else reverse_rel - - # Fallback: Generate from FK column name - # E.g., 'customer_id' -> 'has_customer' (reverse) or 'of_customer' (forward) - fk_clean = fk_column.lower().replace('_id', '').replace('id', '').strip('_') - if fk_clean: - if is_reverse: - return f"has_{fk_clean}" - else: - return f"of_{fk_clean}" - - # Ultimate fallback - if is_reverse: - return f"rev_{source_table}_to_{target_table}" - else: - return f"{source_table}_to_{target_table}" - - -@tool -def create_entity_mapper() -> Dict[str, Any]: - """ - Creates a new EntityMapper for managing ID-to-Index mappings. - - The EntityMapper is essential for: - 1. Converting database PKs (UUIDs, strings) to contiguous graph indices - 2. Interpreting GNN predictions back to original entity IDs - 3. Managing mappings across multiple entity types - - Returns: - A dictionary confirming mapper creation with usage instructions. - - Example workflow: - 1. mapper_info = create_entity_mapper() - 2. register_entities('customers', customer_ids) - 3. register_entities('products', product_ids) - 4. ... build graph using mapped indices ... - 5. After prediction: interpret_prediction('customers', predicted_indices) - """ - reset_global_entity_mapper() - return { - "status": "created", - "message": "EntityMapper created. Use register_entities() to add entity mappings.", - "next_steps": [ - "Call register_entities(entity_type, id_list) for each table", - "Use get_entity_index(entity_type, original_id) to convert IDs", - "After GNN prediction, use interpret_prediction() to get original IDs" - ] - } - - -@tool -def register_entities( - entity_type: str, - original_ids: List[Any] -) -> Dict[str, Any]: - """ - Register entities and create ID-to-Index mapping for a table. - - CRITICAL: Call this for EVERY table BEFORE building edges. - - Args: - entity_type: The entity/table name (e.g., 'customers', 'orders', 'products') - original_ids: List of original Primary Key values from the database. - Can be UUIDs, strings, or integers. - - Returns: - Mapping information including: - - 'entity_type': The registered entity type - - 'num_nodes': Number of unique entities - - 'sample_mapping': First few ID->Index mappings (for verification) - - 'id_to_idx': Full mapping dictionary (for edge construction) - - Example: - >>> result = register_entities('customers', ['C001', 'C002', 'C003']) - >>> result['num_nodes'] # 3 - >>> result['id_to_idx']['C001'] # 0 - """ - mapper = get_global_entity_mapper() - mapping = mapper.add_entities(entity_type, original_ids) - - # Create sample for verification - sample_size = min(5, mapping["num_nodes"]) - sample_mapping = dict(list(mapping["id_to_idx"].items())[:sample_size]) - - return { - "entity_type": entity_type, - "num_nodes": mapping["num_nodes"], - "sample_mapping": sample_mapping, - "id_to_idx": mapping["id_to_idx"], - "message": f"Registered {mapping['num_nodes']} {entity_type} entities" - } - - -@tool -def get_entity_index( - entity_type: str, - original_id: Any -) -> Dict[str, Any]: - """ - Convert a single original database ID to its graph index. - - Args: - entity_type: The entity/table name - original_id: The original database ID value - - Returns: - Dictionary with the index or error message - """ - mapper = get_global_entity_mapper() - index = mapper.id_to_index(entity_type, original_id) - - if index is None: - return { - "error": f"ID '{original_id}' not found in entity type '{entity_type}'", - "registered_types": mapper.get_entity_types() - } - - return { - "entity_type": entity_type, - "original_id": original_id, - "graph_index": index - } - - -@tool -def convert_edge_ids_to_indices( - source_entity_type: str, - target_entity_type: str, - source_ids: List[Any], - target_ids: List[Any], - relation_name: Optional[str] = None, - source_fk_column: str = "" -) -> Dict[str, Any]: - """ - Convert foreign key ID pairs to graph edge indices with semantic naming. - - This is the primary tool for building edges. It: - 1. Converts source/target IDs to contiguous indices - 2. Generates semantic relation names (if not provided) - 3. Returns both forward and reverse edge data - - Args: - source_entity_type: Source table name (e.g., 'orders') - target_entity_type: Target table name (e.g., 'customers') - source_ids: List of IDs for the source entities. - If source is 'orders', this should be the list of order IDs (PKs). - target_ids: List of IDs for the target entities. - If source is 'orders' and target is 'customers', this should be the list of customer IDs (FK values) associated with each order. - relation_name: Optional custom relation name. If None, auto-generated. - source_fk_column: FK column name for semantic naming (e.g., 'customer_id') - - Returns: - Dictionary containing: - - 'forward_edge': Tuple (edge_type, edge_index) for source->target - - 'reverse_edge': Tuple (edge_type, edge_index) for target->source - - 'num_edges': Number of valid edges created - - 'dropped_edges': Number of edges with unmapped IDs (dropped) - - Example: - >>> # Creating edges from orders to customers - >>> result = convert_edge_ids_to_indices( - ... 'orders', 'customers', - ... order_df['order_id'].tolist(), # Source IDs (PK of orders) - ... order_df['customer_id'].tolist(), # Target IDs (FK to customers) - ... source_fk_column='customer_id' - ... ) - >>> result['forward_edge'] - # (('orders', 'placed_by', 'customers'), [[0,1,2], [1,0,2]]) - """ - mapper = get_global_entity_mapper() - - # Validate entity types are registered - if source_entity_type not in mapper.get_entity_types(): - return {"error": f"Entity type '{source_entity_type}' not registered. Call register_entities first."} - if target_entity_type not in mapper.get_entity_types(): - return {"error": f"Entity type '{target_entity_type}' not registered. Call register_entities first."} - - # Get mappings - src_mapping = mapper.get_mapping(source_entity_type)["id_to_idx"] - tgt_mapping = mapper.get_mapping(target_entity_type)["id_to_idx"] - - # Convert IDs to indices, filtering unmapped - src_indices = [] - tgt_indices = [] - dropped = 0 - - for src_id, tgt_id in zip(source_ids, target_ids): - # Try direct lookup - src_idx = src_mapping.get(src_id) - # Handle float/int mismatch (e.g. 1.0 vs 1) - if src_idx is None and isinstance(src_id, float) and src_id.is_integer(): - src_idx = src_mapping.get(int(src_id)) - - # Try direct lookup - tgt_idx = tgt_mapping.get(tgt_id) - # Handle float/int mismatch - if tgt_idx is None and isinstance(tgt_id, float) and tgt_id.is_integer(): - tgt_idx = tgt_mapping.get(int(tgt_id)) - - if src_idx is not None and tgt_idx is not None: - src_indices.append(src_idx) - tgt_indices.append(tgt_idx) - else: - dropped += 1 - - # Generate semantic relation names - if relation_name: - forward_rel = relation_name - reverse_rel = f"rev_{relation_name}" - else: - forward_rel = generate_semantic_relation_name( - source_entity_type, target_entity_type, source_fk_column, is_reverse=False - ) - reverse_rel = generate_semantic_relation_name( - source_entity_type, target_entity_type, source_fk_column, is_reverse=True - ) - - # Create edge indices (shape: 2 x num_edges) - forward_edge_index = [src_indices, tgt_indices] - reverse_edge_index = [tgt_indices, src_indices] - - return { - "forward_edge": { - "edge_type": (source_entity_type, forward_rel, target_entity_type), - "edge_index": forward_edge_index, - }, - "reverse_edge": { - "edge_type": (target_entity_type, reverse_rel, source_entity_type), - "edge_index": reverse_edge_index, - }, - "num_edges": len(src_indices), - "dropped_edges": dropped, - "relations": { - "forward": f"({source_entity_type}) --[{forward_rel}]--> ({target_entity_type})", - "reverse": f"({target_entity_type}) --[{reverse_rel}]--> ({source_entity_type})" - } - } - - -@tool -def interpret_prediction( - entity_type: str, - predicted_indices: List[int], - prediction_scores: Optional[List[float]] = None -) -> Dict[str, Any]: - """ - Interpret GNN prediction results by mapping indices back to original IDs. - - After the GNN makes predictions (e.g., fraud detection, link prediction), - use this tool to convert the predicted node indices back to original - database IDs for business interpretation. - - Args: - entity_type: The entity type that was predicted (e.g., 'customers') - predicted_indices: List of predicted node indices from GNN - prediction_scores: Optional list of prediction scores/probabilities - - Returns: - Dictionary with original IDs and their predictions: - - 'predictions': List of {original_id, index, score} dicts - - 'entity_type': The entity type - - 'count': Number of predictions - - Example: - >>> # GNN predicts nodes 0, 2, 5 as fraudulent - >>> result = interpret_prediction('customers', [0, 2, 5], [0.95, 0.87, 0.91]) - >>> result['predictions'] - # [{'original_id': 'C001', 'index': 0, 'score': 0.95}, ...] - """ - mapper = get_global_entity_mapper() - - if entity_type not in mapper.get_entity_types(): - return {"error": f"Entity type '{entity_type}' not registered."} - - predictions = [] - for i, idx in enumerate(predicted_indices): - original_id = mapper.index_to_id(entity_type, idx) - pred = { - "original_id": original_id, - "graph_index": idx - } - if prediction_scores and i < len(prediction_scores): - pred["score"] = prediction_scores[i] - predictions.append(pred) - - return { - "entity_type": entity_type, - "count": len(predictions), - "predictions": predictions - } - - -@tool -def get_mapper_summary() -> Dict[str, Any]: - """ - Get a summary of the current EntityMapper state. - - Returns: - Summary including registered entity types, node counts, and total nodes. - """ - mapper = get_global_entity_mapper() - return mapper.summary() - - -# Keep old function for backwards compatibility (deprecated) -@tool -def create_id_mapping( - original_ids: List[Any], - table_name: str = "" -) -> Dict[str, Any]: - """ - [DEPRECATED] Use register_entities() instead. - - Creates a safe mapping from original database IDs to contiguous indices. - This function is kept for backwards compatibility but register_entities() - provides better integration with the EntityMapper system. - - Args: - original_ids: List of original IDs to map. - table_name: Name of the table these IDs belong to. - """ - # Use the new EntityMapper system internally - mapper = get_global_entity_mapper() - mapping = mapper.add_entities(table_name or "unnamed", original_ids) - - return { - "id_to_idx": mapping["id_to_idx"], - "idx_to_id": mapping["idx_to_id"], - "num_nodes": mapping["num_nodes"], - "table_name": table_name, - "deprecation_notice": "Use register_entities() for better integration with EntityMapper" - } - - -@tool -def build_hetero_graph( - nodes: NodesDict, - edges: EdgesDict, - add_reverse_edges: bool = True -) -> Any: - """ - Builds a PyTorch Geometric HeteroData object from processed node features and edge indices. - - IMPORTANT: This tool implements bi-directional message passing as required by RDL paper. - By default, it automatically adds reverse edges for every forward edge. - - Type Hints for LLM Agents: - - nodes: Dict[str, Union[List, np.ndarray, torch.Tensor, Dict]] - - Keys are node types (table names) - - Values can be: - - A 2D list/array/tensor of shape (num_nodes, feature_dim) - - A dict with 'x' (features) and optionally 't' (timestamps) - - edges: Dict[Tuple[str, str, str], Union[List, np.ndarray, torch.Tensor]] - - Keys are (source_type, relation_name, target_type) - - Values are edge indices of shape (2, num_edges) - - Row 0: source node indices, Row 1: target node indices - - CRITICAL: Edge indices must be contiguous integers [0, N-1]. - Use create_id_mapping() to convert database IDs before calling this tool. - - Args: - nodes: Dictionary mapping node_type (table_name) to node data. - Accepts List[List[float]], numpy.ndarray, or torch.Tensor. - Can also be a dict with 'x' (features) and 't' (timestamps) keys. - Example: {'users': [[0.1, 0.2], [0.3, 0.4]]} - Example: {'users': {'x': features_array, 't': timestamps_array}} - - edges: Dictionary mapping edge_type to edge_index. - Accepts List[List[int]], numpy.ndarray, or torch.Tensor. - Shape must be (2, num_edges) where row 0 is source, row 1 is target. - Example: {('users', 'purchased', 'products'): [[0, 1, 2], [1, 2, 0]]} - - add_reverse_edges: If True (default), automatically adds reverse edges for - bi-directional message passing. The reverse relation is - prefixed with 'rev_'. Set to False if you manually handle - reverse edges. - - Returns: - A torch_geometric.data.HeteroData object ready for GNN training. - Contains: - - data[node_type].x: Node feature tensor - - data[node_type].t: Timestamp tensor (if provided) - - data[node_type].num_nodes: Number of nodes - - data[src, rel, dst].edge_index: Edge connections - - data[dst, 'rev_' + rel, src].edge_index: Reverse edges (if add_reverse_edges=True) - """ - try: - data = HeteroData() - - # 1. Add Node Features (supports both tensor and dict formats) - for node_type, node_data in nodes.items(): - # Handle both dict format {'x': tensor, 't': tensor} and direct tensor format - if isinstance(node_data, dict): - x_tensor = node_data.get('x') - t_tensor = node_data.get('t') - - # Support output from encode_multi_modal_features {'tensor': ..., 'metadata': ...} - if x_tensor is None and 'tensor' in node_data: - x_tensor = node_data.get('tensor') - else: - x_tensor = node_data - t_tensor = None - - # Process feature tensor - if x_tensor is not None: - if not isinstance(x_tensor, torch.Tensor): - try: - x_tensor = torch.tensor(x_tensor, dtype=torch.float) - except (ValueError, TypeError) as e: - # Handle case where x_tensor might be a nested structure - if isinstance(x_tensor, (list, np.ndarray)): - x_tensor = torch.tensor(np.array(x_tensor, dtype=np.float32), dtype=torch.float) - else: - raise ValueError(f"Cannot convert node features for '{node_type}' to tensor: {e}") - data[node_type].x = x_tensor - data[node_type].num_nodes = x_tensor.shape[0] - - # Process timestamp tensor (for temporal RDL) - if t_tensor is not None: - if not isinstance(t_tensor, torch.Tensor): - try: - t_tensor = torch.tensor(t_tensor, dtype=torch.float) - except (ValueError, TypeError) as e: - if isinstance(t_tensor, (list, np.ndarray)): - t_tensor = torch.tensor(np.array(t_tensor, dtype=np.float32), dtype=torch.float) - else: - raise ValueError(f"Cannot convert timestamps for '{node_type}' to tensor: {e}") - data[node_type].t = t_tensor # Temporal attribute for time-aware sampling - - # 2. Add Edge Indices and Reverse Edges - reverse_edges_added = [] - - for edge_key, edge_index in edges.items(): - # Validate edge_key format - if not isinstance(edge_key, tuple) or len(edge_key) != 3: - print(f"Warning: Skipping invalid edge key format: {edge_key}") - continue - - # edge_key is expected to be (source_type, relation_name, target_type) - src_type, rel, dst_type = edge_key - - # edge_index should be shape (2, num_edges) and type long - if edge_index is None: - print(f"Warning: Skipping None edge_index for {edge_key}") - continue - - if not isinstance(edge_index, torch.Tensor): - try: - edge_index = torch.tensor(edge_index, dtype=torch.long) - except (ValueError, TypeError) as e: - print(f"Warning: Cannot convert edge_index for {edge_key}: {e}") - continue - - # Validate edge_index shape - if edge_index.dim() != 2 or edge_index.shape[0] != 2: - print(f"Warning: Invalid edge_index shape {edge_index.shape} for {edge_key}, expected (2, num_edges)") - continue - - # Validate edge indices are within bounds - if data[src_type].num_nodes is not None: - max_src_idx = edge_index[0].max().item() if edge_index.shape[1] > 0 else -1 - if max_src_idx >= data[src_type].num_nodes: - print(f"Warning: Source index {max_src_idx} out of bounds for {src_type} (has {data[src_type].num_nodes} nodes)") - - if data[dst_type].num_nodes is not None: - max_dst_idx = edge_index[1].max().item() if edge_index.shape[1] > 0 else -1 - if max_dst_idx >= data[dst_type].num_nodes: - print(f"Warning: Target index {max_dst_idx} out of bounds for {dst_type} (has {data[dst_type].num_nodes} nodes)") - - # Add forward edge - data[src_type, rel, dst_type].edge_index = edge_index - - # 3. Add Reverse Edges (Crucial for bi-directional message passing in RDL) - # Following RDL paper: GNNs need to propagate information in both directions - if add_reverse_edges: - # Generate semantic reverse relation name - # If relation already has semantic name, generate appropriate reverse - reverse_rel = generate_semantic_relation_name( - src_type, dst_type, rel, is_reverse=True - ) - # Fallback if semantic naming returns same as forward - if reverse_rel == rel: - reverse_rel = f"rev_{rel}" - - # Flip edge_index: swap source and target - reverse_edge_index = torch.stack([edge_index[1], edge_index[0]], dim=0) - data[dst_type, reverse_rel, src_type].edge_index = reverse_edge_index - reverse_edges_added.append((dst_type, reverse_rel, src_type)) - - # Register graph in ObjectRegistry for GNNSpecialist agent to use - try: - object_registry = ObjectRegistry() - object_registry.register(HeteroData, "hetero_graph", data, overwrite=True) - - # Also save EntityMapper state for model deployment - mapper = get_global_entity_mapper() - object_registry.register(dict, "entity_mapper_state", mapper.to_dict(), overwrite=True) - - logger.info(f"Registered HeteroData graph in ObjectRegistry with {len(data.node_types)} node types") - except Exception as e: - logger.warning(f"Could not register graph in ObjectRegistry: {e}") - - return data - - except Exception as e: - import traceback - return f"Error building HeteroData: {str(e)}\nTraceback: {traceback.format_exc()}" - - -@tool -def get_graph_from_registry() -> Dict[str, Any]: - """ - Retrieves the HeteroData graph from ObjectRegistry. - - Use this tool in RelationalGNNSpecialist to get the graph built by GraphArchitect. - - Returns: - Dictionary containing: - - 'graph': The HeteroData object - - 'entity_mapper': EntityMapper state dictionary - - 'metadata': Graph metadata (node types, edge types, counts) - """ - try: - object_registry = ObjectRegistry() - - # Get graph - try: - graph = object_registry.get(HeteroData, "hetero_graph") - except KeyError: - return {"error": "No graph found in registry. Run build_hetero_graph first."} - - # Get mapper state - mapper_state = None - try: - mapper_state = object_registry.get(dict, "entity_mapper_state") - except KeyError: - pass - - # Build metadata - metadata = { - "node_types": graph.node_types, - "edge_types": [str(et) for et in graph.edge_types], - "num_nodes": {nt: graph[nt].num_nodes for nt in graph.node_types if hasattr(graph[nt], 'num_nodes')}, - "num_edges": {str(et): graph[et].edge_index.shape[1] for et in graph.edge_types if hasattr(graph[et], 'edge_index')} - } - - return { - "graph": graph, - "entity_mapper": mapper_state, - "metadata": metadata, - "status": "Graph retrieved successfully" - } - - except Exception as e: - import traceback - return { - "error": f"Failed to get graph: {str(e)}", - "traceback": traceback.format_exc() - } - - -@tool -def encode_multi_modal_features( - data_column: List[Any], - modality_type: str, - encoding_options: Optional[Dict[str, Any]] = None -) -> Dict[str, Any]: - """ - Encodes data attributes into tensors with metadata, handling missing values and type conflicts. - - Addresses common GNN pitfalls: - 1. Type Conflicts: Returns explicit tensor types and metadata for Embedding layers. - 2. Temporal: Uses cyclical encoding (sin/cos) to capture periodic patterns. - 3. Missing Data: Uses imputation + missing indicators instead of zero-filling. - - Args: - data_column: List of data values. - modality_type: 'Numeric', 'Categorical', 'Temporal', 'Text', 'Image'. - encoding_options: Optional settings. - - 'categorical_strategy': 'auto', 'one_hot', 'embedding'. - - 'handle_missing': 'mean', 'median', 'constant'. - - Returns: - Dict containing: - - 'tensor': The encoded torch.Tensor. - - 'tensor_type': 'float' (for direct use) or 'long' (requires embedding). - - 'metadata': Dict with 'num_classes', 'feature_dim', etc. - """ - try: - if encoding_options is None: - encoding_options = {} - - # Convert input to pandas Series for robust handling - series = pd.Series(data_column) - num_samples = len(series) - - # Result container - result = { - "tensor": None, - "tensor_type": "float", - "metadata": {} - } - - if modality_type.lower() == "numeric": - # 1. Handle Missing Values explicitly - # Coerce to numeric, turning errors to NaN - series_num = pd.to_numeric(series, errors='coerce') - - # Create missing indicator (1.0 if missing, 0.0 otherwise) - is_missing = series_num.isna().astype(float).values.reshape(-1, 1) - - # Impute missing values - strategy = encoding_options.get('handle_missing', 'mean') - if strategy == 'mean': - fill_val = series_num.mean() - elif strategy == 'median': - fill_val = series_num.median() - else: - fill_val = 0.0 - - if pd.isna(fill_val): # Handle all-NaN case - fill_val = 0.0 - - series_filled = series_num.fillna(fill_val).values.reshape(-1, 1) - - # Scale values - scaler = StandardScaler() - scaled_values = scaler.fit_transform(series_filled) - - # Concatenate [Value, MissingIndicator] - # This allows the model to distinguish "true 0" from "missing imputed as 0" - final_tensor = torch.tensor(np.hstack([scaled_values, is_missing]), dtype=torch.float) - - result["tensor"] = final_tensor - result["tensor_type"] = "float" - result["metadata"] = {"feature_dim": 2, "description": "Scaled Value + Missing Indicator"} - - elif modality_type.lower() == "categorical": - # Handle missing values as a specific category - series_cat = series.fillna("MISSING").astype(str) - unique_vals = series_cat.unique() - num_classes = len(unique_vals) - - # Determine strategy - strategy = encoding_options.get('categorical_strategy', 'auto') - if strategy == 'auto': - # Use One-Hot for low cardinality, Embedding for high - strategy = 'one_hot' if num_classes <= 20 else 'embedding' - - if strategy == 'one_hot': - # One-Hot Encoding -> FloatTensor - dummies = pd.get_dummies(series_cat, prefix='cat') - final_tensor = torch.tensor(dummies.values, dtype=torch.float) - - result["tensor"] = final_tensor - result["tensor_type"] = "float" - result["metadata"] = { - "feature_dim": final_tensor.shape[1], - "strategy": "one_hot", - "classes": list(dummies.columns) - } - - else: # embedding - # Label Encoding -> LongTensor - encoder = LabelEncoder() - encoded = encoder.fit_transform(series_cat) - final_tensor = torch.tensor(encoded, dtype=torch.long) - - result["tensor"] = final_tensor - result["tensor_type"] = "long" - result["metadata"] = { - "num_classes": num_classes, - "strategy": "embedding", - "classes": list(encoder.classes_) - } - - elif modality_type.lower() == "temporal": - # Convert to datetime - dt_series = pd.to_datetime(series, errors="coerce") - - # Handle missing - is_missing = dt_series.isna().astype(float).values.reshape(-1, 1) - - # Fill NaT with mean time (or min) to allow extraction - mean_time = dt_series.dropna().mean() - if pd.isna(mean_time): - mean_time = pd.Timestamp.now() - dt_filled = dt_series.fillna(mean_time) - - features_list = [is_missing] - - # 1. Linear Time (Scaled Timestamp) - timestamp = dt_filled.astype("int64") // 10**9 - scaler = StandardScaler() - scaled_time = scaler.fit_transform(timestamp.values.reshape(-1, 1)) - features_list.append(scaled_time) - - # 2. Cyclical Features (Sin/Cos) - # Hour of day (0-23) - hours = dt_filled.dt.hour.values - features_list.append(np.sin(2 * np.pi * hours / 24).reshape(-1, 1)) - features_list.append(np.cos(2 * np.pi * hours / 24).reshape(-1, 1)) - - # Day of week (0-6) - dow = dt_filled.dt.dayofweek.values - features_list.append(np.sin(2 * np.pi * dow / 7).reshape(-1, 1)) - features_list.append(np.cos(2 * np.pi * dow / 7).reshape(-1, 1)) - - # Month (1-12) - months = dt_filled.dt.month.values - features_list.append(np.sin(2 * np.pi * (months-1) / 12).reshape(-1, 1)) - features_list.append(np.cos(2 * np.pi * (months-1) / 12).reshape(-1, 1)) - - # Concatenate all - final_array = np.hstack(features_list) - final_tensor = torch.tensor(final_array, dtype=torch.float) - - result["tensor"] = final_tensor - result["tensor_type"] = "float" - result["metadata"] = { - "feature_dim": final_tensor.shape[1], - "components": ["is_missing", "scaled_time", "hour_sin", "hour_cos", "dow_sin", "dow_cos", "month_sin", "month_cos"] - } - - elif modality_type.lower() == "text": - # Use Sentence Transformer - try: - from sentence_transformers import SentenceTransformer - # Use a small model for speed - model = SentenceTransformer("all-MiniLM-L6-v2") - # Handle missing text - text_list = series.fillna("").astype(str).tolist() - embeddings = model.encode(text_list, convert_to_tensor=True) - - result["tensor"] = embeddings.cpu() - result["tensor_type"] = "float" - result["metadata"] = {"feature_dim": embeddings.shape[1], "model": "all-MiniLM-L6-v2"} - - except ImportError: - # Fallback: Simple Hash encoding if library missing - print("Warning: sentence_transformers not found. Using dummy hash encoding.") - # Create random but consistent embeddings based on hash - # This is just a fallback to prevent crash - feature_dim = 64 - text_list = series.fillna("").astype(str).tolist() - # Simple hashing trick - hashed = np.array([hash(s) % 10000 for s in text_list]).reshape(-1, 1) - scaler = StandardScaler() - encoded = scaler.fit_transform(hashed) - # Expand to feature_dim (just repeating for dummy) - encoded = np.tile(encoded, (1, feature_dim)) - - result["tensor"] = torch.tensor(encoded, dtype=torch.float) - result["tensor_type"] = "float" - result["metadata"] = {"feature_dim": feature_dim, "note": "Fallback Hash Encoding"} - - elif modality_type.lower() == "image": - # Placeholder - result["tensor"] = torch.randn(num_samples, 128) - result["tensor_type"] = "float" - result["metadata"] = {"feature_dim": 128, "note": "Placeholder Random Features"} - - else: - raise ValueError(f"Unsupported modality: {modality_type}") - - return result - - except Exception as e: - import traceback - print(f"Encoding error for {modality_type}: {e}") - print(traceback.format_exc()) - # Return safe fallback - return { - "tensor": torch.zeros(len(data_column), 1), - "tensor_type": "float", - "metadata": {"error": str(e), "fallback": True} - } diff --git a/plexe/tools/interaction.py b/plexe/tools/interaction.py deleted file mode 100644 index 490ef186..00000000 --- a/plexe/tools/interaction.py +++ /dev/null @@ -1,127 +0,0 @@ -from smolagents import tool -from plexe.execution_context import get_chain_of_thought_callable -from plexe.internal.common.utils.chain_of_thought.websocket_emitter import WebSocketEmitter -from plexe.internal.common.utils.chain_of_thought.emitters import MultiEmitter -from plexe.core.object_registry import ObjectRegistry -import os -import logging - -logger = logging.getLogger(__name__) - - -def _get_working_dir() -> str: - """Get working directory from registry or use default.""" - try: - return ObjectRegistry().get(str, "working_dir") - except KeyError: - return "./workdir/" - - -def _clean_agent_response_prefix(content: str) -> str: - """ - Remove smolagents managed agent response prefix from content. - This prefix is added by the framework when returning results from managed agents. - """ - import re - # Pattern to match "Here is the final answer from your managed agent 'AgentName':" - pattern = r"^Here is the final answer from your managed agent '[^']+':[\s]*" - cleaned = re.sub(pattern, "", content, flags=re.MULTILINE) - return cleaned.strip() - - -@tool -def save_to_workdir(filename: str, content: str, subfolder: str = "") -> str: - """ - Saves content to a file in the working directory. - Use this tool to persist generated code, data summaries, or any other artifacts. - - Args: - filename: The name of the file to save (e.g., 'training_code.py', 'data_summary.txt') - content: The content to write to the file - subfolder: Optional subfolder within workdir (e.g., 'code', 'data') - - Returns: - str: The full path where the file was saved, or error message - """ - try: - working_dir = _get_working_dir() - - if subfolder: - save_dir = os.path.join(working_dir, subfolder) - else: - save_dir = working_dir - - os.makedirs(save_dir, exist_ok=True) - - # Clean agent response prefix for Python files to prevent syntax errors - if filename.endswith('.py'): - content = _clean_agent_response_prefix(content) - - file_path = os.path.join(save_dir, filename) - with open(file_path, "w") as f: - f.write(content) - - logger.info(f"Saved file to {file_path}") - return f"Successfully saved to {file_path}" - except Exception as e: - logger.error(f"Failed to save file: {e}") - return f"Error saving file: {e}" - - -@tool -def ask_user_confirmation(title: str, content: str, content_type: str = "text", file_path: str = None) -> str: - """ - Pauses execution and asks the user for confirmation via the UI. - Also saves the content to a file for debugging. - - Args: - title: The title of the confirmation dialog. - content: The content to display to the user. - content_type: The type of content ('text', 'code', 'json', 'markdown'). - file_path: Optional path to save the content to (for debugging). - - Returns: - str: "Confirmed" if the user confirmed, or "Rejected" if rejected. - """ - # Save to file if requested - if file_path: - try: - dir_path = os.path.dirname(file_path) - if dir_path: - os.makedirs(dir_path, exist_ok=True) - with open(file_path, "w") as f: - f.write(content) - logger.info(f"Saved content to {file_path}") - except Exception as e: - logger.error(f"Failed to save content to {file_path}: {e}") - - # Get the emitter - cot_callable = get_chain_of_thought_callable() - if not cot_callable or not hasattr(cot_callable, 'emitter'): - logger.warning("No chain of thought emitter found. Assuming confirmation.") - return "Confirmed (Auto - No UI)" - - emitter = cot_callable.emitter - - # Handle MultiEmitter - ws_emitter = None - if isinstance(emitter, MultiEmitter): - for e in emitter.emitters: - if isinstance(e, WebSocketEmitter): - ws_emitter = e - break - elif isinstance(emitter, WebSocketEmitter): - ws_emitter = emitter - - if not ws_emitter: - logger.warning("No WebSocket emitter found. Assuming confirmation.") - return "Confirmed (Auto - No UI)" - - # Request confirmation - logger.info(f"Requesting confirmation: {title}") - confirmed = ws_emitter.request_confirmation(title, content, content_type) - - if confirmed: - return "Confirmed" - else: - return "Rejected" diff --git a/plexe/tools/io_manager.py b/plexe/tools/io_manager.py deleted file mode 100644 index c32d8f6b..00000000 --- a/plexe/tools/io_manager.py +++ /dev/null @@ -1,74 +0,0 @@ -""" -Tools for performing I/O operations, such as reading from and writing to the filesystem. -""" - -import logging -import os -from smolagents import tool - -from plexe.core.object_registry import ObjectRegistry - -logger = logging.getLogger(__name__) - - -def _get_session_workdir(workdir: str = "workdir") -> str: - """ - Get the session's working directory. - """ - try: - session_id = ObjectRegistry().get(str, "session_id") - except KeyError: - # This is a fallback for when session_id is not in the registry. - # It should not happen in the normal flow. - session_id = "default_session" - session_workdir = os.path.join(workdir, session_id) - if not os.path.exists(session_workdir): - os.makedirs(session_workdir) - return session_workdir - - -@tool -def read_file(file_path: str) -> str: - """ - Reads the content of a file from the filesystem. - - Args: - file_path: The path to the file to read. - - Returns: - The content of the file as a string. - """ - workdir = _get_session_workdir() - path = os.path.join(workdir, file_path) - try: - with open(path, "r") as f: - content = f.read() - logger.debug(f"✅ Read file: {path}") - return content - except Exception as e: - logger.error(f"🔥 Error reading file {path}: {e}") - raise - - -@tool -def write_file(file_path: str, content: str) -> str: - """ - Writes content to a file in the filesystem. - - Args: - file_path: The path to the file to write to. - content: The content to write to the file. - - Returns: - The path to the written file. - """ - workdir = _get_session_workdir() - path = os.path.join(workdir, file_path) - try: - with open(path, "w") as f: - f.write(content) - logger.debug(f"✅ Wrote to file: {path}") - return path - except Exception as e: - logger.error(f"🔥 Error writing to file {path}: {e}") - raise diff --git a/plexe/tools/metrics.py b/plexe/tools/metrics.py deleted file mode 100644 index c5f789a0..00000000 --- a/plexe/tools/metrics.py +++ /dev/null @@ -1,38 +0,0 @@ -""" -Tools related to metrics selection and model review/metadata extraction. -""" - -import logging -from typing import Dict, Callable - -from smolagents import tool - -from plexe.internal.common.provider import Provider -from plexe.internal.models.generation.planning import SolutionPlanGenerator - -logger = logging.getLogger(__name__) - - -def get_select_target_metric(llm_to_use: str) -> Callable: - """Returns a tool function to select target metrics with the model ID pre-filled.""" - - @tool - def select_target_metric(task: str) -> Dict: - """ - Selects the appropriate target metric to optimise for the given task. - - Args: - task: The task definition combining intent, input schema, and output schema - - Returns: - A dictionary containing the metric information - """ - plan_generator = SolutionPlanGenerator(Provider(llm_to_use)) - metric = plan_generator.select_target_metric(task) - return { - "name": metric.name, - "value": metric.value, - "comparison_method": str(metric.comparator.comparison_method), - } - - return select_target_metric diff --git a/plexe/tools/response_formatting.py b/plexe/tools/response_formatting.py deleted file mode 100644 index a6d4c817..00000000 --- a/plexe/tools/response_formatting.py +++ /dev/null @@ -1,52 +0,0 @@ -""" -This module provides tools for forcing an agent to return its response in a specific format. -""" - -from typing import Dict - -from smolagents import tool - - -@tool -def format_final_orchestrator_agent_response( - best_solution_id: str, - performance_metric_name: str, - performance_metric_value: float, - performance_metric_comparison_method: str, - model_review_output: Dict[str, str], -) -> dict: - """ - Returns a dictionary containing the exact fields that the agent must return in its final response. The purpose - of this tool is to 'package' the final deliverables of the ML engineering task. The best_solution_id should be - the ID of the solution that was selected as the best performing one. - - Args: - best_solution_id: The solution ID for the selected best ML solution - performance_metric_name: The name of the performance metric to optimise that was used in this task - performance_metric_value: The value of the performance attained by the selected ML model - performance_metric_comparison_method: The comparison method used to evaluate the performance metric - model_review_output: The output of the 'review_model' tool which contains a review of the selected ML model - - Returns: - Dictionary containing the fields that must be returned by the agent in its final response - """ - from plexe.core.object_registry import ObjectRegistry - from plexe.core.entities.solution import Solution - - # Get the solution plan from the best solution - object_registry = ObjectRegistry() - try: - best_solution = object_registry.get(Solution, best_solution_id) - solution_plan = best_solution.plan or "Solution plan not available" - except Exception: - solution_plan = "Solution plan not available" - - return { - "solution_plan": solution_plan, - "performance": { - "name": performance_metric_name, - "value": performance_metric_value, - "comparison_method": performance_metric_comparison_method, - }, - "metadata": model_review_output, - } diff --git a/plexe/tools/schemas.py b/plexe/tools/schemas.py deleted file mode 100644 index 653827b4..00000000 --- a/plexe/tools/schemas.py +++ /dev/null @@ -1,312 +0,0 @@ -""" -Tools for schema inference, definition, and validation. -""" - -import logging -from typing import Dict, Any - -from smolagents import tool - -from plexe.internal.common.datasets.interface import TabularConvertible -from plexe.internal.common.datasets.adapter import DatasetAdapter -from plexe.core.object_registry import ObjectRegistry -from plexe.internal.common.utils.pydantic_utils import map_to_basemodel -from plexe.internal.common.utils.pandas_utils import convert_dtype_to_python - -logger = logging.getLogger(__name__) - - -@tool -def register_global_schemas( - input_schema: Dict[str, Any], output_schema: Dict[str, Any], reasoning: str -) -> Dict[str, str]: - """ - Register input and output schemas that should be used by all models built for all solutions. - - Args: - input_schema: Finalized input schema. Can be a field:type dictionary or a complex schema definition (e.g. for graphs). - output_schema: Finalized output schema. Can be a field:type dictionary or a complex schema definition. - reasoning: Explanation of schema design decisions - - Returns: - Status message confirming registration - - Raises: - ValueError: If schema validation fails - KeyError: If schema registration fails - """ - object_registry = ObjectRegistry() - - # Validate schemas by attempting to convert them to Pydantic models - # We use a relaxed validation to support complex schemas - try: - map_to_basemodel("InputSchema", input_schema) - map_to_basemodel("OutputSchema", output_schema) - except Exception as e: - # If validation fails, we log it but might still want to register if it's a complex object - # However, map_to_basemodel is now relaxed, so failure means it's really broken. - error_msg = f"Schema validation or registration failed: {str(e)}" - logger.error(error_msg) - # For now, we still raise to ensure some sanity, but map_to_basemodel is more permissive. - raise ValueError(error_msg) from e - - # Register input schema if possible; global schemas are typically registered once - try: - object_registry.register(dict, "input_schema", input_schema, immutable=True) - except ValueError as e: - if "already registered" not in str(e): - raise e - - # Register output schema if possible; global schemas are typically registered once - try: - object_registry.register(dict, "output_schema", output_schema, immutable=True) - except ValueError as e: - if "already registered" not in str(e): - raise e - - # Register reasoning if possible - try: - object_registry.register(str, "schema_reasoning", reasoning) - except ValueError as e: - if "already registered" not in str(e): - raise e - - return {"status": "success", "message": "Schemas validated and registered successfully"} - - -@tool -def get_dataset_schema(dataset_name: str) -> Dict[str, Any]: - """ - Extract the schema (column names and types) from a dataset. This is useful for understanding the structure - of the dataset and how it can be used in model training. - - Args: - dataset_name: Name of the dataset in the registry - - Returns: - Dictionary with column names and their python types - """ - object_registry = ObjectRegistry() - try: - dataset = object_registry.get(TabularConvertible, dataset_name) - df = dataset.to_pandas() - except KeyError: - # Try loading from database - from plexe.tools.datasets import try_load_from_database - # Load a sample to infer schema - df = try_load_from_database(dataset_name, object_registry, limit=1000) - - if df is None: - raise KeyError(f"Dataset '{dataset_name}' not found in registry or database") - - # Register it for future use - dataset = DatasetAdapter.coerce(df) - object_registry.register(TabularConvertible, dataset_name, dataset, overwrite=True, immutable=True) - logger.info(f"Registered database table '{dataset_name}' (sample) for schema inference") - - # Get column names and infer python types - schema = {} - for col in df.columns: - dtype = df[col].dtype - # Map pandas types to Python types, detecting List[T] for object columns - sample_values = df[col].dropna().head(10).tolist() if len(df) > 0 else None - py_type = convert_dtype_to_python(dtype, sample_values) - schema[col] = py_type - - return {"dataset_name": dataset_name, "columns": schema} - - -@tool -def get_global_schemas() -> Dict[str, Dict[str, str]]: - """ - Get global input and output schemas that should apply to a model. - - Returns: - Dictionary with 'input' and 'output' schemas (if registered). - Each schema is a dict mapping field names to types. - Returns empty dict for missing schemas. - """ - object_registry = ObjectRegistry() - result = {} - - try: - # Try to get input schema - try: - input_schema = object_registry.get(dict, "input_schema") - if input_schema: - result["input"] = input_schema - except KeyError: - logger.debug("Global input schema not found in registry") - - # Try to get output schema - try: - output_schema = object_registry.get(dict, "output_schema") - if output_schema: - result["output"] = output_schema - except KeyError: - logger.debug("Global output schema not found in registry") - - return result - - except Exception as e: - logger.warning(f"⚠️ Error getting global schemas: {str(e)}") - return {} - - -@tool -def register_solution_schemas( - solution_id: str, input_schema: Dict[str, str], output_schema: Dict[str, str], reasoning: str -) -> Dict[str, str]: - """ - Register input and output schemas for a specific solution. - - Args: - solution_id: ID of the solution to register schemas for - input_schema: Solution-specific input schema as field:type dictionary - output_schema: Solution-specific output schema as field:type dictionary - reasoning: Explanation of schema design decisions - - Returns: - Status message confirming registration - - Raises: - ValueError: If schema validation fails or solution not found - """ - from plexe.core.entities.solution import Solution - - object_registry = ObjectRegistry() - - # If schemas are locked by the user, we must use the global schemas - input_is_locked = object_registry.get(bool, "input_schema_is_locked") - output_is_locked = object_registry.get(bool, "output_schema_is_locked") - global_schemas = get_global_schemas() - global_input_schema = global_schemas.get("input") - global_output_schema = global_schemas.get("output") - - solution = object_registry.get(Solution, solution_id) - - # If both schemas are locked, use global schemas - if input_is_locked and output_is_locked: - solution.input_schema = global_input_schema - solution.output_schema = global_output_schema - solution.schema_reasoning = "Using schemas provided by the user" - # If input is locked, validate output schema and set - elif input_is_locked: - try: - map_to_basemodel("OutputSchema", output_schema) - except Exception as e: - error_msg = f"Output schema validation failed: {str(e)}" - logger.error(error_msg) - raise ValueError(error_msg) from e - solution.input_schema = global_input_schema - solution.output_schema = output_schema - solution.schema_reasoning = reasoning - # If output is locked, validate input schema and set - elif output_is_locked: - try: - map_to_basemodel("InputSchema", input_schema) - except Exception as e: - error_msg = f"Input schema validation failed: {str(e)}" - logger.error(error_msg) - raise ValueError(error_msg) from e - solution.input_schema = input_schema - solution.output_schema = global_output_schema - solution.schema_reasoning = reasoning - # If neither schema is locked, validate both schemas - else: - try: - map_to_basemodel("InputSchema", input_schema) - map_to_basemodel("OutputSchema", output_schema) - except Exception as e: - error_msg = f"Schema validation failed: {str(e)}" - logger.error(error_msg) - raise ValueError(error_msg) from e - solution.input_schema = input_schema - solution.output_schema = output_schema - solution.schema_reasoning = reasoning - - # Re-register the updated solution - object_registry.register(Solution, solution_id, solution, overwrite=True) - - # Construct response depending on actions taken - if input_is_locked and output_is_locked: - logger.debug(f"✅ Registered global schemas for solution '{solution_id}' (schemas locked)") - return { - "status": "success", - "message": "Nothing to register, as schemas are locked by user.", - "registered_input_schema": global_input_schema, - "registered_output_schema": global_output_schema, - } - elif input_is_locked: - logger.debug(f"✅ Registered output schema for solution '{solution_id}' (input locked)") - return { - "status": "success", - "message": "New output schema was registered; input schema is locked by the user so defaulted to global.", - "registered_input_schema": global_input_schema, - "registered_output_schema": output_schema, - } - elif output_is_locked: - logger.debug(f"✅ Registered input schema for solution '{solution_id}' (output locked)") - return { - "status": "success", - "message": "New input schema was registered; output schema is locked by the user so defaulted to global.", - "registered_input_schema": input_schema, - "registered_output_schema": global_output_schema, - } - else: - logger.debug(f"✅ Registered schemas for solution '{solution_id}'") - return { - "status": "success", - "message": f"Schemas validated and registered for solution '{solution_id}'", - "registered_input_schema": input_schema, - "registered_output_schema": output_schema, - } - - -@tool -def get_solution_schemas(solution_id: str) -> Dict[str, Dict[str, str]]: - """ - Get schemas for a specific solution, with fallback to global schemas. - - Args: - solution_id: ID of the solution to get schemas for - - Returns: - Dictionary with 'input' and 'output' schemas. - Prioritizes solution-specific schemas over global schemas. - Returns empty dict if no schemas found. - """ - from plexe.core.entities.solution import Solution - - object_registry = ObjectRegistry() - result = {} - - try: - # First try to get solution-specific schemas - try: - solution = object_registry.get(Solution, solution_id) - if solution.input_schema: - result["input"] = solution.input_schema - if solution.output_schema: - result["output"] = solution.output_schema - - # If we have both schemas from solution, return them - if "input" in result and "output" in result: - logger.debug(f"Using solution-specific schemas for '{solution_id}'") - return result - - except KeyError: - logger.debug(f"Solution '{solution_id}' not found, falling back to global schemas") - - # Fallback to global schemas for missing schemas - global_schemas = get_global_schemas() - if "input" not in result and "input" in global_schemas: - result["input"] = global_schemas["input"] - if "output" not in result and "output" in global_schemas: - result["output"] = global_schemas["output"] - - return result - - except Exception as e: - logger.warning(f"⚠️ Error getting solution schemas: {str(e)}") - return {} diff --git a/plexe/tools/solutions.py b/plexe/tools/solutions.py deleted file mode 100644 index ee26de98..00000000 --- a/plexe/tools/solutions.py +++ /dev/null @@ -1,121 +0,0 @@ -""" -Tools for creating and managing Solution objects in the ML workflow. - -These tools handle the creation, registration, and management of Solution objects -that represent complete ML approaches from planning through execution. -""" - -import logging -from typing import Dict, List - -from smolagents import tool - -from plexe.core.object_registry import ObjectRegistry -from plexe.core.entities.solution import Solution - -logger = logging.getLogger(__name__) - - -def get_solution_creation_tool(max_solutions: int = 1): - """ - Returns a tool function to create a new Solution object with a plan. - This tool is used by the ML Research Scientist agent to develop new solution approaches. - - Args: - max_solutions: Maximum number of solutions that can be created at once - - Returns: - A tool function that creates a Solution object - """ - if max_solutions <= 0: - raise ValueError("max_solutions must be greater than 0") - - @tool - def create_solution(plan: str) -> Dict[str, str]: - """ - Creates a new Solution object with the given plan and registers it in the object registry so - that other agents in the team can access it. - - This tool should be used by the ML Research Scientist agent when developing new solution - approaches. Each solution represents a distinct ML strategy that will be implemented - and evaluated. - - Args: - plan: The detailed solution plan and strategy description for this ML approach - - Returns: - Dictionary containing the solution ID and success confirmation: - { - "solution_id": "unique_solution_identifier", - "message": "Success message" - } - """ - object_registry = ObjectRegistry() - - # Check if the maximum number of solutions has been reached - if len(object_registry.get_all(Solution)) >= max_solutions: - raise RuntimeError(f"Maximum number of solutions ({max_solutions}) reached. Cannot create more solutions.") - - try: - # Create a new Solution object with the provided plan - solution = Solution(plan=plan) - - # Register the solution in the object registry - object_registry.register(Solution, solution.id, solution, overwrite=False) - - logger.debug(f"✅ Created and registered solution with ID '{solution.id}'") - - return { - "solution_id": solution.id, - "message": f"Successfully created and registered solution with ID '{solution.id}'", - } - - except Exception as e: - logger.warning(f"⚠️ Error creating solution: {str(e)}") - raise RuntimeError(f"Failed to create solution: {str(e)}") - - return create_solution - - -@tool -def get_solution_plan_by_id(solution_id: str) -> str: - """ - Retrieves a model solution plan by its ID. - - Args: - solution_id: ID of the Solution - - Returns: - The plan string of the Solution - """ - object_registry = ObjectRegistry() - - try: - solution = object_registry.get(Solution, solution_id) - return solution.plan if solution.plan else "No plan available for this solution" - - except Exception as e: - logger.warning(f"⚠️ Error retrieving solution plan: {str(e)}") - raise RuntimeError(f"Failed to retrieve solution plan: {str(e)}") - - -@tool -def list_solutions() -> List[str]: - """ - Lists all Solution IDs currently available. Use this tool to see all available solutions if you run into - issues with retrieving a specific solution. - - Returns: - List of solution IDs currently available - """ - object_registry = ObjectRegistry() - - try: - solution_ids = object_registry.list_by_type(Solution) - - logger.debug(f"✅ Available solutions: {solution_ids}") - return solution_ids - - except Exception as e: - logger.warning(f"⚠️ Error listing solutions: {str(e)}") - raise RuntimeError(f"Failed to list solutions: {str(e)}") diff --git a/plexe/tools/task_builder.py b/plexe/tools/task_builder.py deleted file mode 100644 index 438ccb72..00000000 --- a/plexe/tools/task_builder.py +++ /dev/null @@ -1,1593 +0,0 @@ -""" -Tools for building RelBench Task objects from Database/Dataset. - -These tools support the TaskBuilder agent in constructing proper Task definitions -(EntityTask or RecommendationTask) based on the dataset schema and user requirements. -""" - -import os -import logging -from typing import Dict, List, Any, Optional -from pathlib import Path - -import pandas as pd -from smolagents import tool - -from plexe.core.object_registry import ObjectRegistry - -logger = logging.getLogger(__name__) - - -# ============================================================================= -# Template for generated EntityTask code -# ============================================================================= - -ENTITY_TASK_CODE_TEMPLATE = '''""" -Auto-generated EntityTask class for {task_name}. -Generated by TaskBuilder Agent. - -IMPORTANT CONCEPTS: -- EntityTask: Prediction task over a single entity (classification or regression) -- entity_col: The column identifying the entity being predicted -- entity_table: The table containing the entity definitions -- time_col: The timestamp column for temporal splitting -- target_col: The column containing the prediction target (label) -- timedelta: The prediction window - predict over (timestamp, timestamp + timedelta] -- make_table: SQL/Pandas query to compute labels for given timestamps -""" - -import duckdb -import numpy as np -import pandas as pd -from typing import Optional - -from plexe.relbench.base import Database, Table, EntityTask, TaskType -from plexe.relbench.metrics import {metrics_imports} - - -class GenTask(EntityTask): - r"""{task_description}""" - - - # Task Attributes - - task_type = TaskType.{task_type} - entity_col = "{entity_col}" - entity_table = "{entity_table}" - time_col = "{time_col}" - target_col = "{target_col}" - timedelta = pd.Timedelta({timedelta}) - metrics = [{metrics_list}] - num_eval_timestamps = {num_eval_timestamps} - - def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: - """ - Construct the task table with labels for each timestamp. - - Args: - db: The Database object containing all tables - timestamps: Series of timestamps to compute labels for - - Returns: - Table object with entity IDs, timestamps, and labels - """ - - # 1. PREPARE DATAFRAMES - - timestamp_df = pd.DataFrame({{"timestamp": timestamps}}) - -{table_loading_code} - - - # 2. COMPUTE LABELS VIA SQL QUERY - -{sql_query_code} - - - # 3. RETURN TASK TABLE - - return Table( - df=df, - fkey_col_to_pkey_table={{self.entity_col: self.entity_table}}, - pkey_col=None, - time_col=self.time_col, - ) -''' - - -# ============================================================================= -# Template for generated RecommendationTask code -# ============================================================================= - -RECOMMENDATION_TASK_CODE_TEMPLATE = '''""" -Auto-generated RecommendationTask class for {task_name}. -Generated by TaskBuilder Agent. - -IMPORTANT CONCEPTS: -- RecommendationTask: Link prediction task between source and destination entities -- src_entity_col: The column identifying the source entity -- src_entity_table: The table containing source entity definitions -- dst_entity_col: The column identifying the destination entity (as a list) -- dst_entity_table: The table containing destination entity definitions -- time_col: The timestamp column for temporal splitting -- eval_k: k for evaluation metrics (recall@k, ndcg@k, etc.) -- make_table: Query to compute (source, list_of_destinations) for given timestamps -""" - -import duckdb -import numpy as np -import pandas as pd -from typing import Optional - -from plexe.relbench.base import Database, Table, RecommendationTask, TaskType -from plexe.relbench.metrics import {metrics_imports} - - -class GenTask(RecommendationTask): - r"""{task_description}""" - - - # Task Attributes - - task_type = TaskType.LINK_PREDICTION - src_entity_col = "{src_entity_col}" - src_entity_table = "{src_entity_table}" - dst_entity_col = "{dst_entity_col}" - dst_entity_table = "{dst_entity_table}" - time_col = "{time_col}" - timedelta = pd.Timedelta({timedelta}) - eval_k = {eval_k} - metrics = [{metrics_list}] - num_eval_timestamps = {num_eval_timestamps} - - def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: - """ - Construct the task table with source entities and their target destinations. - - Args: - db: The Database object containing all tables - timestamps: Series of timestamps to compute labels for - - Returns: - Table object with source entity IDs, timestamps, and lists of destination IDs - """ - - # 1. PREPARE DATAFRAMES - - timestamp_df = pd.DataFrame({{"timestamp": timestamps}}) - -{table_loading_code} - - - # 2. COMPUTE RECOMMENDATIONS VIA SQL QUERY - -{sql_query_code} - - - # 3. RETURN TASK TABLE - - return Table( - df=df, - fkey_col_to_pkey_table={{self.src_entity_col: self.src_entity_table}}, - pkey_col=None, - time_col=self.time_col, - ) -''' - - -@tool -def get_database_schema_for_task() -> Dict[str, Any]: - """ - Retrieve the database schema information needed for task definition. - - This tool gets schema metadata including table names, columns, primary keys, - foreign keys, and temporal columns from the ObjectRegistry. - - Returns: - Dictionary containing: - - tables: Dict of table name -> {columns, primary_key, time_col, row_count} - - relationships: List of FK relationships - - temporal_columns: Dict of table -> temporal column info - - entity_candidates: Suggested entity tables for EntityTask - """ - try: - object_registry = ObjectRegistry() - - # Try different schema sources - schema_sources = [ - "unified_db_schema", - "graph_schema_metadata", - "database_schema" - ] - - schema = None - source = None - for src in schema_sources: - try: - schema = object_registry.get(dict, src) - source = src - break - except KeyError: - continue - - if schema is None: - return { - "found": False, - "error": "No schema metadata found in registry. " - "Make sure DatasetBuilder has built the database first." - } - - tables = schema.get("tables", {}) - relationships = schema.get("relationships", []) - temporal_summary = schema.get("temporal_summary", {}) - - # Identify entity candidates (tables with primary keys that are referenced by FKs) - entity_candidates = [] - referenced_tables = set() - for rel in relationships: - if isinstance(rel, dict): - referenced_tables.add(rel.get("target_table", "")) - - for table_name, table_info in tables.items(): - if isinstance(table_info, dict): - pkeys = table_info.get("primary_keys", []) - if pkeys and table_name in referenced_tables: - entity_candidates.append({ - "table": table_name, - "primary_key": pkeys[0] if pkeys else None, - "is_temporal": table_name in temporal_summary - }) - - return { - "found": True, - "source": source, - "tables": tables, - "relationships": relationships, - "temporal_columns": temporal_summary, - "entity_candidates": entity_candidates - } - - except Exception as e: - logger.error(f"Error getting database schema: {e}") - return {"error": str(e)} - - -@tool -def get_dataset_info() -> Dict[str, Any]: - """ - Get information about the registered Dataset including timestamps. - - Returns: - Dictionary containing: - - dataset_name: Name of the dataset - - val_timestamp: Validation split timestamp - - test_timestamp: Test split timestamp - - code_available: Whether dataset code is registered - """ - try: - object_registry = ObjectRegistry() - - # Look for registered database metadata - dataset_info = {} - - # Try to find all registered database metadata - for key_pattern in ["database_metadata_"]: - # Check known datasets - possible_names = ["stack_overflow", "f1", "amazon", "house", "custom"] - for name in possible_names: - try: - metadata = object_registry.get(dict, f"database_metadata_{name}") - dataset_info[name] = { - "dataset_name": metadata.get("dataset_name"), - "val_timestamp": metadata.get("val_timestamp"), - "test_timestamp": metadata.get("test_timestamp"), - "description": metadata.get("description", ""), - "code_available": True - } - except KeyError: - continue - - if not dataset_info: - return { - "found": False, - "error": "No dataset metadata found. Build a dataset first using DatasetBuilder." - } - - return { - "found": True, - "datasets": dataset_info - } - - except Exception as e: - logger.error(f"Error getting dataset info: {e}") - return {"error": str(e)} - - -@tool -def get_available_metrics() -> Dict[str, Any]: - """ - Get list of available metrics for different task types. - - Returns: - Dictionary with metrics organized by task type: - - binary_classification: List of binary classification metrics - - multiclass_classification: List of multiclass metrics - - regression: List of regression metrics - - recommendation: List of recommendation metrics - """ - return { - "binary_classification": { - "metrics": ["accuracy", "f1", "roc_auc", "average_precision", "auprc", "log_loss", "multiclass_f1"], - "description": "Metrics for binary (0/1) classification tasks" - }, - "multiclass_classification": { - "metrics": ["accuracy", "macro_f1", "micro_f1", "mrr", "log_loss"], - "description": "Metrics for multi-class classification tasks" - }, - "regression": { - "metrics": ["mae", "mse", "rmse", "r2"], - "description": "Metrics for continuous value prediction tasks" - }, - "multilabel_classification": { - "metrics": ["multilabel_auprc_micro", "multilabel_auprc_macro", "multilabel_auroc_micro", "multilabel_auroc_macro", "multilabel_f1_micro", "multilabel_f1_macro", "multilabel_recall_micro", "multilabel_recall_macro", "multilabel_precision_micro", "multilabel_precision_macro"], - "description": "Metrics for multi-label classification tasks" - }, - "recommendation": { - "metrics": ["link_prediction_recall", "link_prediction_precision", "link_prediction_map", "link_prediction_ndcg"], - "description": "Metrics for link prediction tasks", - }, - "task_types": { - "BINARY_CLASSIFICATION": "Binary 0/1 classification", - "MULTICLASS_CLASSIFICATION": "Multi-class classification", - "REGRESSION": "Continuous value regression", - "MULTILABEL_CLASSIFICATION": "Multi-label classification", - "LINK_PREDICTION": "Link prediction/recommendation" - } - } - - -@tool -def get_table_sample_data(table_name: str, num_rows: int = 5) -> Dict[str, Any]: - """ - Get sample data from a table to help understand column values for task definition. - - Args: - table_name: Name of the table to sample - num_rows: Number of sample rows to return (default: 5) - - Returns: - Dictionary containing: - - columns: List of column names with dtypes - - sample_data: Sample rows as list of dicts - - statistics: Basic statistics for numeric columns - """ - try: - object_registry = ObjectRegistry() - - # Try to get the CSV path - try: - csv_path = object_registry.get(str, "path_raw_csv_files") - except KeyError: - return { - "error": "CSV path not found in registry. Make sure data has been loaded." - } - - # Look for the CSV file - csv_file = os.path.join(csv_path, f"{table_name}.csv") - if not os.path.exists(csv_file): - return { - "error": f"Table '{table_name}' not found at '{csv_file}'" - } - - # Load and sample the data - df = pd.read_csv(csv_file) - - # Get column info - columns = [ - {"name": col, "dtype": str(df[col].dtype), "null_count": int(df[col].isna().sum())} - for col in df.columns - ] - - # Get sample data - sample_data = df.head(num_rows).to_dict(orient='records') - - # Get statistics for numeric columns - numeric_cols = df.select_dtypes(include=['number']).columns - statistics = {} - for col in numeric_cols: - statistics[col] = { - "min": float(df[col].min()) if not pd.isna(df[col].min()) else None, - "max": float(df[col].max()) if not pd.isna(df[col].max()) else None, - "mean": float(df[col].mean()) if not pd.isna(df[col].mean()) else None, - "unique_count": int(df[col].nunique()) - } - - # Check for potential target columns (binary or categorical with few values) - potential_targets = [] - for col in df.columns: - unique_count = df[col].nunique() - if unique_count == 2: - potential_targets.append({ - "column": col, - "type": "binary", - "values": df[col].unique().tolist()[:10] - }) - elif 2 < unique_count <= 20: - potential_targets.append({ - "column": col, - "type": "categorical", - "unique_count": unique_count, - "values": df[col].unique().tolist()[:10] - }) - - return { - "table_name": table_name, - "row_count": len(df), - "columns": columns, - "sample_data": sample_data, - "numeric_statistics": statistics, - "potential_target_columns": potential_targets - } - - except Exception as e: - logger.error(f"Error getting sample data: {e}") - return {"error": str(e)} - - -@tool -def test_sql_query(sql_query: str, timedelta_days: int = 30) -> Dict[str, Any]: - """ - Test a SQL query on sample data before committing to the Task class. - - This tool helps validate SQL queries by running them on actual data with - sample timestamps. Use this to debug and refine your queries. - - Args: - sql_query: The SQL query to test (use 'timestamp_df' as the timestamp source) - timedelta_days: The timedelta in days for the test (default: 30) - - Returns: - Dictionary containing: - - success: Whether the query executed successfully - - row_count: Number of rows returned - - columns: Columns in the result - - sample_output: First few rows of output - - error: Error message if failed - - suggestions: Suggestions for fixing common issues - """ - try: - import duckdb - object_registry = ObjectRegistry() - - # Get CSV path - try: - csv_path = object_registry.get(str, "path_raw_csv_files") - except KeyError: - return { - "success": False, - "error": "CSV path not found. Make sure DatasetBuilder has run first." - } - - # Load all CSV files as DataFrames - csv_files = [f for f in os.listdir(csv_path) if f.endswith('.csv')] - tables_loaded = {} - - # Load all CSV files as Views in DuckDB (Zero-Copy) - csv_files = [f for f in os.listdir(csv_path) if f.endswith('.csv')] - tables_loaded = {} - - # Create an in-memory DuckDB connection - con = duckdb.connect(database=':memory:') - - for csv_file in csv_files: - table_name = csv_file.replace('.csv', '') - file_path = os.path.join(csv_path, csv_file) - - # Create view directly from CSV without loading into Pandas (OOM safe) - con.execute(f"CREATE OR REPLACE VIEW {table_name} AS SELECT * FROM read_csv_auto('{file_path}')") - - # Get row count efficiently - count = con.execute(f"SELECT COUNT(*) FROM {table_name}").fetchone()[0] - tables_loaded[table_name] = count - - # Get dataset info for sample timestamps - dataset_info = None - for key in ["dataset_info", "dataset_metadata"]: - try: - dataset_info = object_registry.get(dict, key) - break - except KeyError: - continue - - # Create sample timestamp_df - if dataset_info and "val_timestamp" in dataset_info: - val_ts = pd.Timestamp(dataset_info["val_timestamp"]) - # Create a few timestamps around val_timestamp - timestamps = pd.Series([ - val_ts - pd.Timedelta(days=60), - val_ts - pd.Timedelta(days=30), - val_ts - ]) - else: - # Use current date as fallback - now = pd.Timestamp.now() - timestamps = pd.Series([ - now - pd.Timedelta(days=90), - now - pd.Timedelta(days=60), - now - pd.Timedelta(days=30) - ]) - - timestamp_df = pd.DataFrame({"timestamp": timestamps}) - - # Register timestamp_df in DuckDB - con.register('timestamp_df', timestamp_df) - - # Replace {self.timedelta} placeholder if present - test_query = sql_query.replace("{self.timedelta}", f"{timedelta_days} days") - test_query = test_query.replace("'{self.timedelta}'", f"'{timedelta_days} days'") - - # Execute the query - try: - result_df = con.execute(test_query).df() - - return { - "success": True, - "row_count": len(result_df), - "columns": list(result_df.columns), - "dtypes": {col: str(result_df[col].dtype) for col in result_df.columns}, - "sample_output": result_df.head(10).to_dict(orient='records'), - "null_counts": {col: int(result_df[col].isna().sum()) for col in result_df.columns}, - "tables_loaded": tables_loaded, - "timestamps_used": timestamps.tolist() - } - - except Exception as sql_error: - error_msg = str(sql_error) - suggestions = [] - - # Provide helpful suggestions based on error - if "not found" in error_msg.lower() or "does not exist" in error_msg.lower(): - suggestions.append("Table or column not found. Check spelling and use get_database_schema_for_task() to verify names.") - suggestions.append(f"Available tables: {list(tables_loaded.keys())}") - - if "syntax" in error_msg.lower(): - suggestions.append("SQL syntax error. Check for missing commas, parentheses, or keywords.") - - if "ambiguous" in error_msg.lower(): - suggestions.append("Ambiguous column reference. Use table aliases (e.g., t.timestamp, a.driverId).") - - if "group by" in error_msg.lower(): - suggestions.append("GROUP BY error. Ensure all non-aggregated columns are in GROUP BY clause.") - - if "interval" in error_msg.lower(): - suggestions.append("INTERVAL syntax issue. Use: INTERVAL '30 days' or INTERVAL '1 year'") - - return { - "success": False, - "error": error_msg, - "suggestions": suggestions, - "tables_loaded": tables_loaded - } - - except Exception as e: - logger.error(f"Error testing SQL query: {e}") - return { - "success": False, - "error": str(e), - "suggestions": ["Unexpected error. Check that all tables exist and DatasetBuilder has run."] - } - - -@tool -def analyze_potential_tasks(entity_table: str, entity_col: str) -> Dict[str, Any]: - """ - Analyze the database to suggest potential prediction tasks for an entity. - - Args: - entity_table: The entity table name (e.g., "users", "drivers") - entity_col: The entity column (primary key) name (e.g., "userId", "driverId") - - Returns: - Dictionary with suggested tasks: - - aggregation_tasks: Tasks based on aggregating related records - - classification_tasks: Potential binary/multiclass classification tasks - - regression_tasks: Potential regression tasks - - recommendation_tasks: Potential recommendation tasks - """ - try: - object_registry = ObjectRegistry() - - # Get schema info - schema = None - for src in ["unified_db_schema", "graph_schema_metadata"]: - try: - schema = object_registry.get(dict, src) - break - except KeyError: - continue - - if schema is None: - return {"error": "No schema found. Build database first."} - - relationships = schema.get("relationships", []) - tables = schema.get("tables", {}) - - # Find tables that reference this entity - referencing_tables = [] - for rel in relationships: - if isinstance(rel, dict): - if rel.get("target_table") == entity_table: - referencing_tables.append({ - "table": rel.get("source_table"), - "fk_col": rel.get("source_col"), - "relation_type": rel.get("relation_type", "many-to-one") - }) - - suggestions = { - "entity_table": entity_table, - "entity_col": entity_col, - "referencing_tables": referencing_tables, - "suggested_tasks": [] - } - - # Suggest aggregation-based tasks - for ref in referencing_tables: - ref_table = ref["table"] - if ref_table in tables: - table_info = tables[ref_table] - time_col = None - if isinstance(table_info, dict): - temporal_cols = table_info.get("temporal_columns", []) - if temporal_cols: - time_col = temporal_cols[0] - - # Common aggregation patterns - suggestions["suggested_tasks"].append({ - "name": f"{entity_table}_{ref_table}_count", - "description": f"Predict number of {ref_table} records for each {entity_table}", - "task_type": "REGRESSION", - "aggregation": f"COUNT {ref_table} WHERE {ref['fk_col']} = {entity_col}", - "time_col": time_col - }) - - suggestions["suggested_tasks"].append({ - "name": f"{entity_table}_has_{ref_table}", - "description": f"Predict if {entity_table} will have any {ref_table} in next period", - "task_type": "BINARY_CLASSIFICATION", - "aggregation": f"EXISTS {ref_table} WHERE {ref['fk_col']} = {entity_col}", - "time_col": time_col - }) - - return suggestions - - except Exception as e: - logger.error(f"Error analyzing potential tasks: {e}") - return {"error": str(e)} - - -@tool -def validate_task_code(code: str) -> Dict[str, Any]: - """ - Validate the generated Task code by checking syntax and required components. - - Args: - code: The Python code string to validate - - Returns: - Dictionary with validation results: - - valid: Boolean indicating if code is valid - - errors: List of any errors found - - warnings: List of any warnings - """ - import ast - - errors = [] - warnings = [] - - # Check syntax - try: - ast.parse(code) - except SyntaxError as e: - errors.append(f"Syntax error at line {e.lineno}: {e.msg}") - return { - "valid": False, - "errors": errors, - "warnings": warnings - } - - # Check for required imports - required_elements = [ - ("duckdb", "DuckDB is typically needed for efficient SQL queries"), - ("pandas", "Pandas is required for DataFrame operations"), - ("Table", "Must import Table from plexe.relbench.base"), - ] - - for element, reason in required_elements: - if element not in code: - warnings.append(f"Missing '{element}': {reason}") - - # Check for task class inheritance - if "EntityTask" not in code and "RecommendationTask" not in code: - errors.append("Task class must inherit from EntityTask or RecommendationTask") - - # Check for required attributes - required_attrs = ["task_type", "timedelta", "metrics"] - for attr in required_attrs: - if f"{attr} =" not in code and f"{attr}=" not in code: - errors.append(f"Missing required attribute: {attr}") - - # Check EntityTask specific attributes - if "EntityTask" in code: - entity_attrs = ["entity_col", "entity_table", "target_col", "time_col"] - for attr in entity_attrs: - if f"{attr} =" not in code and f"{attr}=" not in code: - errors.append(f"EntityTask missing required attribute: {attr}") - - # Check RecommendationTask specific attributes - if "RecommendationTask" in code: - rec_attrs = ["src_entity_col", "src_entity_table", "dst_entity_col", "dst_entity_table", "eval_k"] - for attr in rec_attrs: - if f"{attr} =" not in code and f"{attr}=" not in code: - errors.append(f"RecommendationTask missing required attribute: {attr}") - - # Check for make_table method - if "def make_table" not in code: - errors.append("Task class must implement 'make_table' method") - - # Check make_table returns Table - if "return Table(" not in code: - warnings.append("make_table should return a Table object") - - return { - "valid": len(errors) == 0, - "errors": errors, - "warnings": warnings - } - - -@tool -def register_task_code( - dataset_name: str, - task_name: str, - code: str, - task_type: str, - entity_table: str, - description: str = "" -) -> Dict[str, Any]: - """ - Register the generated Task code in ObjectRegistry for later use. - - Args: - dataset_name: Name of the dataset this task is for - task_name: Name of the task (e.g., "user_churn", "driver_dnf") - code: The complete Python code for the Task class - task_type: Type of task ("entity" or "recommendation") - entity_table: The main entity table for this task - description: Optional description of the task - - Returns: - Confirmation message with registered key - """ - try: - object_registry = ObjectRegistry() - - # Store the code - code_key = f"task_code_{dataset_name}_{task_name}" - object_registry.register(str, code_key, code, overwrite=True) - - # Store metadata - metadata_key = f"task_metadata_{dataset_name}_{task_name}" - metadata = { - "dataset_name": dataset_name, - "task_name": task_name, - "task_type": task_type, - "entity_table": entity_table, - "description": description, - "code_key": code_key - } - object_registry.register(dict, metadata_key, metadata, overwrite=True) - - logger.info(f"✅ Registered task code for '{dataset_name}/{task_name}'") - - return { - "success": True, - "code_key": code_key, - "metadata_key": metadata_key, - "message": f"Successfully registered task code for '{dataset_name}/{task_name}'" - } - - except Exception as e: - logger.error(f"Failed to register task code: {e}") - return {"success": False, "error": str(e)} - - -@tool -def export_task_code( - dataset_name: str, - task_name: str, - output_dir: str = None -) -> Dict[str, Any]: - """ - Export the generated Task code to a Python file in the chat session directory. - - Args: - dataset_name: Name of the dataset - task_name: Name of the task to export - output_dir: Directory to save the Python file. If None, auto-creates a - timestamped directory under workdir/chat-session-YYYYMMDD-HHMMSS/tasks/ - - Returns: - Dictionary with: - - success: Boolean - - file_path: Path to the exported file - """ - from datetime import datetime - - try: - object_registry = ObjectRegistry() - - # Get the code - code_key = f"task_code_{dataset_name}_{task_name}" - try: - code = object_registry.get(str, code_key) - except KeyError: - return { - "success": False, - "error": f"No code found for task '{dataset_name}/{task_name}'. " - "Register the code first using register_task_code." - } - - # Auto-create timestamped directory if not provided - if output_dir is None: - # Try to get existing session directory from registry - try: - output_dir = object_registry.get(str, "working_dir") - except KeyError: - try: - output_dir = object_registry.get(str, "current_chat_session_dir") - except KeyError: - # Create new session directory - timestamp = datetime.now().strftime("%Y%m%d-%H%M%S") - output_dir = f".workdir/chat-session-{timestamp}" - object_registry.register(str, "current_chat_session_dir", output_dir, overwrite=True) - - # Create output directory - Path(output_dir).mkdir(parents=True, exist_ok=True) - - # Write the file - file_name = "task.py" - file_path = os.path.join(output_dir, file_name) - - with open(file_path, 'w') as f: - f.write(code) - - # Register export info - # Extract class name from code - import re - class_match = re.search(r"class\s+(\w+)\s*\(", code) - if class_match: - class_name = class_match.group(1) - else: - class_name = task_name # Fallback - - export_info = { - "class_name": class_name, - "export_path": file_path, - "module_name": "task" - } - - # Try to get metadata to populate additional fields - metadata_key = f"task_metadata_{dataset_name}_{task_name}" - try: - metadata = object_registry.get(dict, metadata_key) - export_info.update({ - "task_type": metadata.get("task_type"), - "entity_table": metadata.get("entity_table"), - "target_col": metadata.get("target_col"), - }) - except KeyError: - pass - - object_registry.register(dict, "task_code", export_info, overwrite=True) - - logger.info(f"✅ Exported task code to '{file_path}'") - - return { - "success": True, - "file_path": file_path, - "output_dir": output_dir, - "message": f"Successfully exported task code to '{file_path}'" - } - - except Exception as e: - logger.error(f"Failed to export task code: {e}") - return {"success": False, "error": str(e)} - - -@tool -def get_entity_task_template() -> str: - """ - Get the template for generating EntityTask code. - - Returns: - The code template as a string with documentation. - """ - return ENTITY_TASK_CODE_TEMPLATE - - -@tool -def get_recommendation_task_template() -> str: - """ - Get the template for generating RecommendationTask code. - - Returns: - The code template as a string with documentation. - """ - return RECOMMENDATION_TASK_CODE_TEMPLATE - - -@tool -def get_sql_query_examples() -> Dict[str, Any]: - """ - Get diverse SQL query examples for different task types. - - These examples show how to compute labels using DuckDB SQL queries - over the database tables. Each pattern serves a different use case - and can be adapted to various domains. - - IMPORTANT: These are PATTERN TEMPLATES - replace table names, column names, - and conditions with actual values from your database schema. - - Returns: - Dictionary with example queries for different scenarios organized by category. - """ - return { - # ===================================================================== - # BINARY CLASSIFICATION PATTERNS - # ===================================================================== - "binary_churn_not_exists": { - "category": "binary_classification", - "description": "Churn = 1 if NO activity in next period (NOT EXISTS pattern)", - "use_case": "User churn, product abandonment, subscription cancellation", - "sql_pattern": """ - df = duckdb.sql( - f\"\"\" - SELECT - timestamp, - {entity_col}, - CAST( - NOT EXISTS ( - SELECT 1 - FROM {activity_table} - WHERE - {activity_table}.{entity_col} = {entity_table}.{entity_col} AND - {time_col} > timestamp AND - {time_col} <= timestamp + INTERVAL '{self.timedelta}' - ) AS INTEGER - ) AS {target_col} - FROM - timestamp_df, - {entity_table} - WHERE - EXISTS ( - SELECT 1 - FROM {activity_table} - WHERE - {activity_table}.{entity_col} = {entity_table}.{entity_col} AND - {time_col} > timestamp - INTERVAL '{self.timedelta}' AND - {time_col} <= timestamp - ) - \"\"\" - ).df() -""" - }, - "binary_churn_with_active_filter": { - "category": "binary_classification", - "description": "Churn prediction with active entity filter using cross-join + double EXISTS", - "use_case": "Customer churn prediction (H&M pattern) - filter to only recently active entities", - "sql_pattern": """ - # Pattern: Cross-join timestamp_df with entity_table, - # Filter by EXISTS (recently active), then check NOT EXISTS (future activity) - df = duckdb.sql( - f\"\"\" - SELECT - timestamp, - {entity_col}, - CAST( - NOT EXISTS ( - SELECT 1 - FROM {activity_table} - WHERE - {activity_table}.{entity_col} = {entity_table}.{entity_col} AND - {time_col} > timestamp AND - {time_col} <= timestamp + INTERVAL '{self.timedelta}' - ) AS INTEGER - ) AS {target_col} - FROM - timestamp_df, - {entity_table}, - WHERE - EXISTS ( - SELECT 1 - FROM {activity_table} - WHERE - {activity_table}.{entity_col} = {entity_table}.{entity_col} AND - {time_col} > timestamp - INTERVAL '{self.timedelta}' AND - {time_col} <= timestamp - ) - \"\"\" - ).df() -""" - }, - "binary_cte_count_case": { - "category": "binary_classification", - "description": "Binary classification using CTE + COUNT + CASE WHEN pattern", - "use_case": "Paper citation, item purchase, event occurrence, badge earning", - "sql_pattern": """ - # Use LEFT JOIN + GROUP BY + CASE WHEN for binary classification - df = duckdb.sql( - f\"\"\" - SELECT - t.timestamp, - e.{entity_pk} as {entity_col}, - CASE WHEN COUNT({activity_table}.{activity_pk}) >= 1 THEN 1 ELSE 0 END AS {target_col} - FROM timestamp_df t - LEFT JOIN {entity_table} e - ON e.{entity_time_col} <= t.timestamp - LEFT JOIN {activity_table} - ON e.{entity_pk} = {activity_table}.{entity_fk} - AND {activity_table}.{activity_time_col} > t.timestamp - AND {activity_table}.{activity_time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - GROUP BY t.timestamp, e.{entity_pk} - \"\"\" - ).df() - - # Post-processing if needed - df = df.dropna(subset=["{entity_col}"]) - df[self.entity_col] = df[self.entity_col].astype(int) -""" - }, - "binary_union_multi_activity": { - "category": "binary_classification", - "description": "UNION multiple activity tables into single CTE, then check engagement", - "use_case": "User engagement across multiple activity types (posts, votes, comments)", - "sql_pattern": """ - # Pattern: UNION multiple tables, create active users CTE, then check future activity - df = duckdb.sql( - f\"\"\" - WITH - ALL_ACTIVITY AS ( - SELECT id, {entity_col}, {time_col} FROM {activity_table_1} - UNION - SELECT id, {entity_col}, {time_col} FROM {activity_table_2} - UNION - SELECT id, {entity_col}, {time_col} FROM {activity_table_3} - ), - - ACTIVE_ENTITIES AS ( - SELECT - t.timestamp, - e.{entity_pk}, - COUNT(DISTINCT a.id) as n_activity - FROM timestamp_df t - CROSS JOIN {entity_table} e - LEFT JOIN ALL_ACTIVITY a - ON e.{entity_pk} = a.{entity_col} - AND a.{time_col} <= t.timestamp - WHERE e.{entity_pk} != {invalid_id} -- e.g., != -1 for anonymous - GROUP BY t.timestamp, e.{entity_pk} - ) - - SELECT - ae.timestamp, - ae.{entity_pk} as {entity_col}, - IF(COUNT(DISTINCT a.id) >= 1, 1, 0) as {target_col} - FROM ACTIVE_ENTITIES ae - LEFT JOIN ALL_ACTIVITY a - ON ae.{entity_pk} = a.{entity_col} - AND a.{time_col} > ae.timestamp - AND a.{time_col} <= ae.timestamp + INTERVAL '{self.timedelta}' - WHERE ae.n_activity >= 1 -- Only consider previously active entities - GROUP BY ae.timestamp, ae.{entity_pk} - \"\"\" - ).df() -""" - }, - "binary_status_based": { - "category": "binary_classification", - "description": "Classification based on status codes (MAX + CASE pattern)", - "use_case": "Race DNF, order failure, task completion", - "sql_pattern": """ - df = duckdb.sql( - f\"\"\" - SELECT - t.timestamp AS {time_col}, - e.{entity_col}, - CASE - WHEN MAX(CASE WHEN r.{status_col} != {success_value} THEN 1 ELSE 0 END) = 1 THEN 1 - ELSE 0 - END AS {target_col} - FROM timestamp_df t - LEFT JOIN {result_table} r - ON r.{result_time_col} > t.timestamp - AND r.{result_time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - LEFT JOIN {entity_table} e - ON r.{fk_col} = e.{entity_col} - WHERE e.{entity_col} IN ( - SELECT DISTINCT {entity_col} - FROM {result_table} - WHERE {result_time_col} > t.timestamp - INTERVAL '1 year' - ) - GROUP BY t.timestamp, e.{entity_col} - \"\"\" - ).df() -""" - }, - "binary_min_threshold": { - "category": "binary_classification", - "description": "Binary classification using MIN + threshold check (e.g., position <= 3)", - "use_case": "Top-N finish, threshold achievement, qualifying position (F1 pattern)", - "sql_pattern": """ - # Pattern: MIN + CASE WHEN for threshold-based binary classification - # Active entity filter using IN subquery - df = duckdb.sql( - f\"\"\" - SELECT - t.timestamp as {time_col}, - a.{entity_col} as {entity_col}, - CASE - WHEN MIN(a.{position_col}) <= {threshold_value} THEN 1 - ELSE 0 - END AS {target_col} - FROM timestamp_df t - LEFT JOIN {activity_table} a - ON a.{activity_time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - AND a.{activity_time_col} > t.timestamp - WHERE a.{entity_col} IN ( - SELECT DISTINCT {entity_col} - FROM {activity_table} - WHERE {activity_time_col} > t.timestamp - INTERVAL '1 year' - ) - GROUP BY t.timestamp, a.{entity_col} - \"\"\" - ).df() - - # Post-processing: ensure integer type - df["{target_col}"] = df["{target_col}"].astype("int64") -""" - }, - - # ===================================================================== - # MULTICLASS CLASSIFICATION PATTERNS - # ===================================================================== - "multiclass_primary_category": { - "category": "multiclass_classification", - "description": "Predict primary/most-frequent category using ROW_NUMBER", - "use_case": "Author's primary research area, user's main interest, product category", - "sql_pattern": """ - # Use multiple CTEs: count categories, rank them, select top - df = duckdb.sql( - f\"\"\" - WITH entity_activities AS ( - SELECT - t.timestamp AS {time_col}, - ea.{entity_col}, - i.{category_col} - FROM timestamp_df t - JOIN {entity_activity_table} ea - ON ea.{activity_time_col} > t.timestamp - AND ea.{activity_time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - JOIN {item_table} i - ON ea.{item_fk_col} = i.{item_pk_col} - ), - category_counts AS ( - SELECT - {time_col}, - {entity_col}, - {category_col}, - COUNT(*) AS cnt - FROM entity_activities - GROUP BY {time_col}, {entity_col}, {category_col} - ), - ranked AS ( - SELECT - {time_col}, - {entity_col}, - {category_col}, - ROW_NUMBER() OVER ( - PARTITION BY {time_col}, {entity_col} - ORDER BY cnt DESC - ) AS rn - FROM category_counts - ) - SELECT - r.{time_col}, - r.{entity_col}, - c.{category_name_col} AS {target_col} - FROM ranked r - LEFT JOIN {category_table} c - ON r.{category_col} = c.{category_pk_col} - WHERE r.rn = 1 - \"\"\" - ).df() -""" - }, - - # ===================================================================== - # REGRESSION PATTERNS - # ===================================================================== - "regression_count_cte": { - "category": "regression", - "description": "Count events per entity using CTE pattern", - "use_case": "Publication count, order count, activity frequency", - "sql_pattern": """ - df = duckdb.sql( - f\"\"\" - WITH entity_counts AS ( - SELECT - t.timestamp AS {time_col}, - ea.{entity_col}, - COUNT(ea.{item_col}) AS {target_col} - FROM timestamp_df t - JOIN {entity_activity_table} ea - ON ea.{activity_time_col} > t.timestamp - AND ea.{activity_time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - GROUP BY t.timestamp, ea.{entity_col} - ) - SELECT {time_col}, {entity_col}, {target_col} - FROM entity_counts - \"\"\" - ).df() -""" - }, - "regression_mean_active_filter": { - "category": "regression", - "description": "MEAN/AVG aggregation with active entity filter using IN subquery", - "use_case": "Average position, average score, average rating (F1 pattern)", - "sql_pattern": """ - # Pattern: MEAN() with active entity filter (IN subquery for recent activity) - df = duckdb.sql( - f\"\"\" - SELECT - t.timestamp as {time_col}, - a.{entity_col} as {entity_col}, - MEAN(a.{value_col}) as {target_col} - FROM timestamp_df t - LEFT JOIN {activity_table} a - ON a.{activity_time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - AND a.{activity_time_col} > t.timestamp - WHERE a.{entity_col} IN ( - SELECT DISTINCT {entity_col} - FROM {activity_table} - WHERE {activity_time_col} > t.timestamp - INTERVAL '1 year' - ) - GROUP BY t.timestamp, a.{entity_col} - \"\"\" - ).df() -""" - }, - "regression_sum_with_join": { - "category": "regression", - "description": "Sum values from related table (LTV pattern)", - "use_case": "Customer lifetime value, revenue, total spend", - "sql_pattern": """ - df = duckdb.sql( - f\"\"\" - SELECT - timestamp, - {entity_col}, - ltv - FROM - timestamp_df, - {entity_table}, - ( - SELECT COALESCE(SUM({value_col}), 0) AS ltv - FROM {transaction_table}, {item_table} - WHERE - {transaction_table}.{entity_col} = {entity_table}.{entity_col} AND - {transaction_table}.{item_fk_col} = {item_table}.{item_pk_col} AND - {transaction_time_col} > timestamp AND - {transaction_time_col} <= timestamp + INTERVAL '{self.timedelta}' - ) - WHERE EXISTS ( - SELECT 1 FROM {transaction_table} - WHERE {transaction_table}.{entity_col} = {entity_table}.{entity_col} - AND {transaction_time_col} <= timestamp - ) - \"\"\" - ).df() -""" - }, - "regression_group_by_simple": { - "category": "regression", - "description": "Simple GROUP BY aggregation for entity-level metrics", - "use_case": "Product total sales, item popularity", - "sql_pattern": """ - df = duckdb.sql( - f\"\"\" - SELECT - timestamp, - {entity_table}.{entity_col}, - COALESCE(SUM({value_col}), 0) AS {target_col} - FROM - timestamp_df, - {entity_table}, - {transaction_table} - WHERE - {transaction_table}.{fk_col} = {entity_table}.{entity_col} AND - {transaction_time_col} > timestamp AND - {transaction_time_col} <= timestamp + INTERVAL '{self.timedelta}' - GROUP BY timestamp, {entity_table}.{entity_col} - \"\"\" - ).df() -""" - }, - "regression_count_filtered": { - "category": "regression", - "description": "COUNT with multiple filter conditions (type, status, null checks)", - "use_case": "Post upvotes count, filtered activity count (StackOverflow pattern)", - "sql_pattern": """ - # Pattern: LEFT JOIN with multiple filter conditions - # Filter entity by type/status, filter activity by type/status - df = duckdb.sql( - f\"\"\" - SELECT - t.timestamp, - e.{entity_pk} AS {entity_col}, - COUNT(DISTINCT a.{activity_pk}) AS {target_col} - FROM timestamp_df t - LEFT JOIN {entity_table} e - ON e.{entity_time_col} <= t.timestamp - AND e.{entity_owner_col} != {invalid_id} -- e.g., != -1 - AND e.{entity_owner_col} IS NOT NULL - AND e.{entity_type_col} = {target_type_value} -- e.g., PostTypeId = 1 (questions) - LEFT JOIN {activity_table} a - ON e.{entity_pk} = a.{activity_fk} - AND a.{activity_time_col} > t.timestamp - AND a.{activity_time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - AND a.{activity_type_col} = {activity_type_value} -- e.g., VoteTypeId = 2 (upvotes) - GROUP BY t.timestamp, e.{entity_pk} - \"\"\" - ).df() -""" - }, - "regression_subquery_coalesce": { - "category": "regression", - "description": "Cross-join with correlated subquery + COALESCE for aggregation", - "use_case": "Item sales prediction, entity total value (H&M pattern)", - "sql_pattern": """ - # Pattern: Cross-join timestamp_df, entity_table with inline correlated subquery - # The subquery computes aggregate and COALESCE handles NULL for no-activity - df = duckdb.sql( - f\"\"\" - SELECT - timestamp, - {entity_col}, - {target_col} - FROM - timestamp_df, - {entity_table}, - ( - SELECT - COALESCE(SUM({value_col}), 0) as {target_col} - FROM - {transaction_table}, - WHERE - {transaction_table}.{entity_col} = {entity_table}.{entity_col} AND - {transaction_time_col} > timestamp AND - {transaction_time_col} <= timestamp + INTERVAL '{self.timedelta}' - ) - \"\"\" - ).df() -""" - }, - - # ===================================================================== - # RECOMMENDATION / LINK PREDICTION PATTERNS - # ===================================================================== - "recommendation_basic_list": { - "category": "recommendation", - "description": "Basic list of items entity will interact with", - "use_case": "Product recommendation, content recommendation", - "sql_pattern": """ - df = duckdb.sql( - f\"\"\" - SELECT - t.timestamp, - {interaction_table}.{src_entity_col}, - LIST(DISTINCT {interaction_table}.{dst_entity_col}) AS {dst_entity_col} - FROM timestamp_df t - LEFT JOIN {interaction_table} - ON {interaction_table}.{interaction_time_col} > t.timestamp - AND {interaction_table}.{interaction_time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - WHERE - {interaction_table}.{src_entity_col} IS NOT NULL AND - {interaction_table}.{dst_entity_col} IS NOT NULL - GROUP BY t.timestamp, {interaction_table}.{src_entity_col} - \"\"\" - ).df() -""" - }, - "recommendation_left_join_group": { - "category": "recommendation", - "description": "LEFT JOIN with temporal window + GROUP BY for item lists", - "use_case": "Customer purchase prediction, article recommendation (H&M pattern)", - "sql_pattern": """ - # Pattern: LEFT JOIN transactions to timestamp_df with temporal filter, GROUP BY - df = duckdb.sql( - f\"\"\" - SELECT - t.timestamp, - {transaction_table}.{src_entity_col}, - LIST(DISTINCT {transaction_table}.{dst_entity_col}) AS {dst_entity_col} - FROM - timestamp_df t - LEFT JOIN - {transaction_table} - ON - {transaction_table}.{transaction_time_col} > t.timestamp AND - {transaction_table}.{transaction_time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - GROUP BY - t.timestamp, - {transaction_table}.{src_entity_col} - \"\"\" - ).df() -""" - }, - "recommendation_filtered": { - "category": "recommendation", - "description": "Filtered recommendation (by rating, quality, etc.)", - "use_case": "High-rating recommendations, quality interactions", - "sql_pattern": """ - df = duckdb.sql( - f\"\"\" - SELECT - t.timestamp, - {interaction_table}.{src_entity_col}, - LIST(DISTINCT {interaction_table}.{dst_entity_col}) AS {dst_entity_col} - FROM timestamp_df t - LEFT JOIN {interaction_table} - ON {interaction_table}.{interaction_time_col} > t.timestamp - AND {interaction_table}.{interaction_time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - WHERE - {interaction_table}.{src_entity_col} IS NOT NULL - AND {interaction_table}.{dst_entity_col} IS NOT NULL - AND {filter_condition} -- e.g., rating = 5.0 or LENGTH(text) > 300 - GROUP BY t.timestamp, {interaction_table}.{src_entity_col} - \"\"\" - ).df() -""" - }, - "recommendation_co_occurrence": { - "category": "recommendation", - "description": "Co-occurrence/co-citation pattern using self-join", - "use_case": "Co-cited papers, frequently bought together, related items", - "sql_pattern": """ - # Self-join pattern for co-occurrence relationships - df = duckdb.sql( - f\"\"\" - WITH co_occurrences AS ( - SELECT - t.timestamp AS {time_col}, - src.{src_entity_col}, - other.{dst_ref_col} AS co_item - FROM timestamp_df t - JOIN {src_entity_table} src - ON src.{src_time_col} <= t.timestamp - JOIN {link_table} link1 - ON link1.{link_dst_col} = src.{src_entity_col} - AND link1.{link_time_col} > t.timestamp - AND link1.{link_time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - JOIN {link_table} link2 - ON link1.{link_src_col} = link2.{link_src_col} - AND link2.{link_dst_col} <> src.{src_entity_col} - AND link2.{link_time_col} > t.timestamp - AND link2.{link_time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - JOIN {dst_entity_table} other - ON link2.{link_dst_col} = other.{dst_entity_col} - ) - SELECT - {time_col}, - {src_entity_col}, - array_agg(DISTINCT co_item) AS {dst_entity_col} - FROM co_occurrences - GROUP BY {time_col}, {src_entity_col} - \"\"\" - ).df() -""" - }, - "recommendation_multi_table_chain": { - "category": "recommendation", - "description": "Chain multiple LEFT JOINs: timestamp -> entity -> interaction", - "use_case": "User comments on posts, user votes on items (StackOverflow pattern)", - "sql_pattern": """ - # Pattern: timestamp -> posts (existing) -> comments (future) - # Predict which posts a user will comment on - df = duckdb.sql( - f\"\"\" - SELECT - t.timestamp, - {interaction_table}.{src_entity_col} as {src_entity_col}, - LIST(DISTINCT {dst_entity_table}.{dst_pk}) AS {dst_entity_col} - FROM timestamp_df t - LEFT JOIN {dst_entity_table} - ON {dst_entity_table}.{dst_time_col} <= t.timestamp -- dst must exist before timestamp - LEFT JOIN {interaction_table} - ON {dst_entity_table}.{dst_pk} = {interaction_table}.{interaction_dst_fk} - AND {interaction_table}.{interaction_time_col} > t.timestamp - AND {interaction_table}.{interaction_time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - WHERE - {interaction_table}.{src_entity_col} IS NOT NULL - AND {dst_entity_table}.{dst_owner_col} != {invalid_id} -- e.g., != -1 - AND {dst_entity_table}.{dst_owner_col} IS NOT NULL - GROUP BY t.timestamp, {interaction_table}.{src_entity_col} - \"\"\" - ).df() -""" - }, - "recommendation_self_reference": { - "category": "recommendation", - "description": "Self-referencing recommendation (src_table = dst_table via link table)", - "use_case": "Related posts, linked items, post-to-post links (StackOverflow pattern)", - "sql_pattern": """ - # Pattern: Predict which items will be linked to a source item - # Both src and dst come from the same table via a link table - df = duckdb.sql( - f\"\"\" - SELECT - t.timestamp, - {link_table}.{src_col} as {src_entity_col}, - LIST(DISTINCT {link_table}.{dst_col}) AS {dst_entity_col} - FROM timestamp_df t - LEFT JOIN {link_table} - ON {link_table}.{link_time_col} > t.timestamp - AND {link_table}.{link_time_col} <= t.timestamp + INTERVAL '{self.timedelta}' - LEFT JOIN {entity_table} e1 - ON {link_table}.{src_col} = e1.{entity_pk} - LEFT JOIN {entity_table} e2 - ON {link_table}.{dst_col} = e2.{entity_pk} - WHERE - {link_table}.{src_col} IS NOT NULL - AND {link_table}.{dst_col} IS NOT NULL - AND e1.{entity_time_col} <= t.timestamp -- src must exist before - AND e2.{entity_time_col} <= t.timestamp -- dst must exist before - GROUP BY t.timestamp, {link_table}.{src_col} - \"\"\" - ).df() -""" - }, - - # ===================================================================== - # SQL TIPS AND PATTERNS - # ===================================================================== - "sql_building_blocks": { - "category": "tips", - "cte_pattern": "WITH cte_name AS (SELECT ...) SELECT ... FROM cte_name", - "temporal_filter": "{time_col} > t.timestamp AND {time_col} <= t.timestamp + INTERVAL '{self.timedelta}'", - "active_entity_filter": "WHERE e.{entity_col} IN (SELECT DISTINCT {entity_col} FROM {table} WHERE {time_col} <= t.timestamp)", - "exists_filter": "WHERE EXISTS (SELECT 1 FROM {table} WHERE {condition})", - "binary_from_count": "CASE WHEN COUNT(*) > 0 THEN 1 ELSE 0 END", - "binary_from_boolean": "CAST(boolean_expr AS INTEGER)", - "list_aggregation_duckdb": "LIST(DISTINCT col) or array_agg(DISTINCT col)", - "null_safe_sum": "COALESCE(SUM(value), 0)", - "ranking_pattern": "ROW_NUMBER() OVER (PARTITION BY group_cols ORDER BY sort_col DESC)", - }, - "join_patterns": { - "category": "tips", - "cross_join": "timestamp_df, entity_table -- Cartesian product for all timestamp-entity pairs", - "inner_join": "JOIN table ON condition -- Only matching rows", - "left_join": "LEFT JOIN table ON condition -- Keep all left rows, NULL for non-matches", - "self_join": "JOIN table t1 JOIN table t2 ON t1.col = t2.col -- For co-occurrence patterns", - }, - "common_mistakes": { - "category": "tips", - "mistakes": [ - "Forgetting NULL filters in recommendation (WHERE col IS NOT NULL)", - "Wrong temporal direction (should be: time > timestamp, not >=)", - "Missing GROUP BY when using aggregations", - "Temporal leakage: filtering entities using future data", - "Not handling zero-count case (use COALESCE or LEFT JOIN)", - "Hardcoding table/column names instead of using schema", - ] - } - } diff --git a/plexe/tools/training.py b/plexe/tools/training.py deleted file mode 100644 index 86d5b84c..00000000 --- a/plexe/tools/training.py +++ /dev/null @@ -1,43 +0,0 @@ -""" -Tools related to code generation, including solution planning, training code, -and inference code generation. -""" - -import logging - -from smolagents import tool - -from plexe.core.object_registry import ObjectRegistry - -logger = logging.getLogger(__name__) - - -@tool -def register_best_solution(best_solution_id: str) -> str: - """ - Register the solution with the best performance as the final selected solution in the object - registry. This step is required in order for the solution to be available for final model building. - - Args: - best_solution_id: 'solution_id' of the best performing solution - - Returns: - Success message confirming registration - """ - from plexe.core.entities.solution import Solution - - object_registry = ObjectRegistry() - - try: - # Get the best solution - best_solution = object_registry.get(Solution, best_solution_id) - - # Register the solution with a fixed ID for easy retrieval - object_registry.register(Solution, "best_performing_solution", best_solution, overwrite=True) - - logger.debug(f"✅ Registered best performing solution with ID '{best_solution_id}'") - return f"Successfully registered solution with ID '{best_solution_id}' as the best performing solution." - - except Exception as e: - logger.warning(f"⚠️ Error registering best solution: {str(e)}") - raise RuntimeError(f"Failed to register best solution: {str(e)}") diff --git a/pyproject.toml b/pyproject.toml index b7708c55..fbe7f522 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -52,7 +52,6 @@ mlflow = "^3.0.0rc2" ray = "^2.9.0" rich = "^13.7.1" torch = "^2.3.0" -smolagents = "^1.14.0" deprecated = "^1.2.18" python-multipart = "^0.0.16" psycopg2-binary = "^2.9.9" @@ -63,6 +62,14 @@ pytorch-frame = "^0.3.0" pooch = "^1.8.0" duckdb = "^1.3.0" +# LangGraph and LangChain dependencies +langgraph = "^0.2.0" +langchain = "^0.3.0" +langchain-core = "^0.3.0" +langchain-openai = "^0.2.0" +langchain-anthropic = "^0.2.0" +langchain-google-genai = "^2.0.0" + # Deep learning dependencies transformers = { version = "^4.50.0", optional = true } tokenizers = { version = "^0.21.1", optional = true } diff --git a/scripts/dumpcode.py b/scripts/dumpcode.py deleted file mode 100644 index f2d8bc3a..00000000 --- a/scripts/dumpcode.py +++ /dev/null @@ -1,45 +0,0 @@ -""" -This script collects all code files from the project directory and writes it to a single output file. - -The purpose of this script is to enable easily passing the entire codebase as context to a language model -with large context window, such as the Google Gemini models. -""" - -from pathlib import Path - -# === Config === -EXTENSIONS = {".py", ".md", ".jinja", ".yaml"} -TARGET_DIRS = {"plexe"} -ROOT_FILES = {"README.md"} # Loose files to include from root -OUTPUT_FILE = "plexe-full-codebase.txt" - - -def collect_files(base: Path): - files = [] - for target in TARGET_DIRS: - target_path = base / target - if target_path.is_dir(): - files.extend(f for f in target_path.rglob("*") if f.suffix in EXTENSIONS and f.is_file()) - # Include specified root files if they exist and match extension filter - files.extend(base / f for f in ROOT_FILES if (base / f).is_file() and (base / f).suffix in EXTENSIONS) - return files - - -def format_entry(rel_path: Path, content: str) -> str: - return f"## {rel_path}\n```\n{content}```\n\n\n" - - -def main(): - base = Path.cwd() - files = collect_files(base) - - with open(OUTPUT_FILE, "w", encoding="utf-8") as out: - out.write(f"# Full Codebase for {Path.cwd().name}\n\n") - for file in files: - rel_path = file.relative_to(base) - content = file.read_text(encoding="utf-8") - out.write(format_entry(rel_path, content)) - - -if __name__ == "__main__": - main() diff --git a/tests/__init__.py b/tests/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/tests/benchmark/README.md b/tests/benchmark/README.md deleted file mode 100644 index 91724ee6..00000000 --- a/tests/benchmark/README.md +++ /dev/null @@ -1,80 +0,0 @@ -# MLE-Bench Runner for Plexe - -This script benchmarks `plexe` on the `mle-bench` test suite released by OpenAI. It automates the process of running the Plexe library on Kaggle competitions and evaluating the results using the MLE-Bench framework. See the [mle bench repository](https://github.com/openai/mle-bench) or the [mle-bench paper](https://openai.com/index/mle-bench/) for more information. - -## Prerequisites - -To run the benchmark, you need to complete these steps: - -1. Clone the `plexe` repository: `git clone https://github.com/plexe-ai/plexe.git` -2. Install `git lfs` on your machine ([installation instructions](https://git-lfs.com/)) -3. Create a Kaggle account, create an API key, and save it in `~/.kaggle/kaggle.json` ([Kaggle API instructions](https://www.kaggle.com/docs/api)) -4. Install Python `3.11.0` or later -5. Install poetry: `pip install poetry` -6. Set up the project: `poetry install` in the project root directory -7. Configure API keys for your LLM provider as described in the main README.md: - ``` - # For OpenAI - export OPENAI_API_KEY= - # For Anthropic - export ANTHROPIC_API_KEY= - # For Gemini - export GEMINI_API_KEY= - ``` - -## Usage - -Run the benchmark with: - -```bash -poetry run python tests/benchmark/mle_bench.py -``` - -When you run the script for the first time, you will be prompted to: -1. Specify a directory where the `mle-bench` repository will be cloned -2. Set LLM provider details (provider, max iterations, timeout) - -The script will then: -1. Clone the `mle-bench` repository -2. Download the Kaggle datasets (by default, only the spaceship-titanic challenge) -3. Run Plexe on the datasets -4. Generate predictions and submission files -5. Evaluate the results using MLE-Bench - -### Command Line Options - -- `--config PATH`: Specify a custom config file path (default: mle-bench-config.yaml) -- `--rebuild`: Force re-clone the MLE-bench repository and regenerate the config file - -## Configuration - -The first time you run the script, it creates a file called `mle-bench-config.yaml` with the following structure: - -```yaml -repo_url: https://github.com/openai/mle-bench.git -repo_dir: /path/to/mle-bench -datasets: - - spaceship-titanic -provider: openai/gpt-4o -max_iterations: 3 -timeout: 3600 -``` - -Configuration options: - -- `repo_url`: The GitHub repository URL for MLE-bench -- `repo_dir`: Local directory to clone MLE-bench into -- `datasets`: List of Kaggle competitions to run (for initial testing, only spaceship-titanic is used) -- `provider`: LLM provider to use with Plexe (format: "provider/model") -- `max_iterations`: Maximum number of model solutions to explore -- `timeout`: Maximum time in seconds for model building - -The available datasets match the competitions in the [MLE-bench competitions directory](https://github.com/openai/mle-bench/tree/main/mlebench/competitions). - -## Output - -After running the benchmark, the results are stored in: -- `workdir/{dataset_name}/`: Model outputs and submissions for each dataset -- `grades/`: Evaluation results from MLE-bench scoring - -You can find submission CSV files and saved models in the `workdir/{dataset_name}/` directory. \ No newline at end of file diff --git a/tests/benchmark/__init__.py b/tests/benchmark/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/tests/benchmark/mle-bench-config.yaml.jinja b/tests/benchmark/mle-bench-config.yaml.jinja deleted file mode 100644 index 21dc9521..00000000 --- a/tests/benchmark/mle-bench-config.yaml.jinja +++ /dev/null @@ -1,88 +0,0 @@ -repo_url: https://github.com/openai/mle-bench.git -repo_dir: {{ repo_dir }} -provider: {{ provider }} -max_iterations: {{ max_iterations }} -timeout: {{ timeout }} -datasets: -{# - 3d-object-detection-for-autonomous-vehicles#} -{# - AI4Code#} -{# - aerial-cactus-identification#} -{# - alaska2-image-steganalysis#} -{# - aptos2019-blindness-detection#} -{# - billion-word-imputation#} -{# - bms-molecular-translation#} -{# - cassava-leaf-disease-classification#} -{# - cdiscount-image-classification-challenge#} -{# - chaii-hindi-and-tamil-question-answering#} -{# - champs-scalar-coupling#} -{# - denoising-dirty-documents#} -{# - detecting-insults-in-social-commentary#} -{# - dog-breed-identification#} -{# - dogs-vs-cats-redux-kernels-edition#} -{# - facebook-recruiting-iii-keyword-extraction#} -{# - freesound-audio-tagging-2019#} -{# - google-quest-challenge#} -{# - google-research-identify-contrails-reduce-global-warming#} -{# - h-and-m-personalized-fashion-recommendations#} -{# - herbarium-2020-fgvc7#} -{# - herbarium-2021-fgvc8#} -{# - herbarium-2022-fgvc9#} -{# - histopathologic-cancer-detection#} -{# - hms-harmful-brain-activity-classification#} -{# - hotel-id-2021-fgvc8#} -{# - hubmap-kidney-segmentation#} -{# - icecube-neutrinos-in-deep-ice#} -{# - imet-2020-fgvc7#} -{# - inaturalist-2019-fgvc6#} -{# - invasive-species-monitoring#} -{# - iwildcam-2019-fgvc6#} -{# - iwildcam-2020-fgvc7#} -{# - jigsaw-toxic-comment-classification-challenge#} -{# - jigsaw-unintended-bias-in-toxicity-classification#} -{# - kuzushiji-recognition#} -{# - leaf-classification#} -{# - learning-agency-lab-automated-essay-scoring-2#} -{# - lmsys-chatbot-arena#} -{# - ml2021spring-hw2#} -{# - mlsp-2013-birds#} -{# - movie-review-sentiment-analysis-kernels-only#} -{# - multi-modal-gesture-recognition#} -{# - new-york-city-taxi-fare-prediction#} -{# - nfl-player-contact-detection#} -{# - nomad2018-predict-transparent-conductors#} -{# - osic-pulmonary-fibrosis-progression#} -{# - paddy-disease-classification#} -{# - petfinder-pawpularity-score#} -{# - plant-pathology-2020-fgvc7#} -{# - plant-pathology-2021-fgvc8#} -{# - plant-seedlings-classification#} -{# - playground-series-s3e18#} -{# - predict-volcanic-eruptions-ingv-oe#} -{# - random-acts-of-pizza#} -{# - ranzcr-clip-catheter-line-classification#} -{# - rsna-2022-cervical-spine-fracture-detection#} -{# - rsna-breast-cancer-detection#} -{# - rsna-miccai-brain-tumor-radiogenomic-classification#} -{# - seti-breakthrough-listen#} -{# - siim-covid19-detection#} -{# - siim-isic-melanoma-classification#} -{# - smartphone-decimeter-2022#} - - spaceship-titanic -{# - spooky-author-identification#} -{# - stanford-covid-vaccine#} -{# - statoil-iceberg-classifier-challenge#} -{# - tabular-playground-series-dec-2021#} - - tabular-playground-series-may-2022 -{# - tensorflow-speech-recognition-challenge#} -{# - tensorflow2-question-answering#} -{# - text-normalization-challenge-english-language#} -{# - text-normalization-challenge-russian-language#} -{# - tgs-salt-identification-challenge#} -{# - the-icml-2013-whale-challenge-right-whale-redux#} -{# - tweet-sentiment-extraction#} -{# - us-patent-phrase-to-phrase-matching#} -{# - uw-madison-gi-tract-image-segmentation#} -{# - ventilator-pressure-prediction#} -{# - vesuvius-challenge-ink-detection#} -{# - vinbigdata-chest-xray-abnormalities-detection#} -{# - whale-categorization-playground#} \ No newline at end of file diff --git a/tests/benchmark/mle_bench.py b/tests/benchmark/mle_bench.py deleted file mode 100644 index bfad12ef..00000000 --- a/tests/benchmark/mle_bench.py +++ /dev/null @@ -1,52 +0,0 @@ -#!/usr/bin/env python3 -""" -This script automates the setup, execution, and grading process for the "mle-bench" framework using plexe. - -Usage: - python mle_bench.py --config CONFIG_PATH --rebuild - -Description: - The script clones and sets up "mle-bench", prepares datasets, reads a configuration file - to determine the tests to run, executes models using plexe, and grades their performance. The - --rebuild flag forces the script to re-clone the "mle-bench" repository and reinstall dependencies. - -Ensure that your environment has the required permissions and Kaggle API credentials configured. -""" - -import argparse -import sys - -# Import the main runner class from the mlebench package -from mlebench.core.runner import MLEBenchRunner - - -def main(cli_args): - """Main entry point for the script""" - runner = MLEBenchRunner() - runner.setup(cli_args) - runner.run() - - -if __name__ == "__main__": - parser = argparse.ArgumentParser(description="Run and grade an agent on the MLE-bench framework.") - parser.add_argument( - "--config", type=str, required=False, default="mle-bench-config.yaml", help="Path to the configuration file." - ) - parser.add_argument( - "--rebuild", action="store_true", help="Force re-clone the MLE-bench repository and reinstall dependencies." - ) - - # Parse arguments and run main - args = parser.parse_args() - - try: - main(args) - except KeyboardInterrupt: - print("\n⚠️ Process interrupted by user.") - sys.exit(1) - except Exception as e: - print(f"❌ An unexpected error occurred: {e}") - import traceback - - traceback.print_exc() - sys.exit(1) diff --git a/tests/benchmark/mlebench/__init__.py b/tests/benchmark/mlebench/__init__.py deleted file mode 100644 index f25afee3..00000000 --- a/tests/benchmark/mlebench/__init__.py +++ /dev/null @@ -1 +0,0 @@ -"""MLE Bench runner package for Plexe.""" diff --git a/tests/benchmark/mlebench/core/__init__.py b/tests/benchmark/mlebench/core/__init__.py deleted file mode 100644 index a1849a56..00000000 --- a/tests/benchmark/mlebench/core/__init__.py +++ /dev/null @@ -1 +0,0 @@ -"""Core modules for MLE Bench runner.""" diff --git a/tests/benchmark/mlebench/core/config.py b/tests/benchmark/mlebench/core/config.py deleted file mode 100644 index 2bad6f2b..00000000 --- a/tests/benchmark/mlebench/core/config.py +++ /dev/null @@ -1,98 +0,0 @@ -"""Configuration management for MLE Bench runner.""" - -import os -import sys -from pathlib import Path -import yaml -from jinja2 import Environment, Template, meta - - -class ConfigManager: - """Class to handle configuration loading and generation""" - - @staticmethod - def load_config(config_path): - """Load configuration from YAML file""" - print(f"🔍 Loading test configuration from {config_path}...") - if not os.path.exists(config_path): - print(f"❌ Config file not found at: {config_path}") - sys.exit(1) - try: - with open(config_path, "r") as config_file: - config = yaml.safe_load(config_file) - print("✅ Configuration loaded successfully.") - return config - except yaml.YAMLError as e: - print(f"❌ Error parsing config file: {e}") - sys.exit(1) - - @staticmethod - def ensure_config_exists(rebuild: bool = False): - """Check if `mle-bench-config.yaml` exists, and if not, generate it from `mle-bench-config.yaml.jinja`""" - config_path = Path("mle-bench-config.yaml") - if config_path.exists() and not rebuild: - print("✅ Configuration file 'mle-bench-config.yaml' already exists.") - return - - # Get the script directory for finding the template - script_dir = Path(__file__).parent.parent.parent.absolute() - template_path = script_dir / "mle-bench-config.yaml.jinja" - - if not template_path.exists(): - print(f"❌ Template file '{template_path}' not found. Cannot proceed.") - sys.exit(1) - - if rebuild: - print(f"🔄 Rebuilding 'mle-bench-config.yaml' from '{template_path}'...") - else: - print(f"📝 'mle-bench-config.yaml' not found. Generating it from '{template_path}'...") - - # Load the template - with open(template_path, "r") as template_file: - template_content = template_file.read() - - env = Environment() - ast = env.parse(template_content) - template = Template(template_content) - - print(f"📝 Template loaded from {template_path}") - - # Set default values and gather user inputs for template variables - variables = { - "repo_dir": str(Path.home() / "mle-bench"), - "provider": "openai/gpt-4o", - "max_iterations": "3", - "timeout": "3600", - } - - # Allow user to override defaults - for var in meta.find_undeclared_variables(ast): - if not var.startswith("_"): - if var in variables: - prompt = f"💡 Provide a value for '{var}' (default: {variables[var]}): " - else: - prompt = f"💡 Provide a value for '{var}': " - - try: - user_input = input(prompt) - if user_input.strip(): # Only update if user provided a non-empty value - variables[var] = user_input - except EOFError: - print(f"Using default value for '{var}': {variables.get(var, '')}") - - # Render and write the config file - config_content = template.render(**variables) - - # Parse the rendered config - config_yaml = yaml.safe_load(config_content) - - # Add plexe configurations to the config - config_yaml["provider"] = variables["provider"] - config_yaml["max_iterations"] = int(variables["max_iterations"]) - config_yaml["timeout"] = int(variables["timeout"]) - - # Write the updated config - with open(config_path, "w") as config_file: - yaml.dump(config_yaml, config_file, default_flow_style=False) - - print("✅ 'mle-bench-config.yaml' generated successfully.") diff --git a/tests/benchmark/mlebench/core/models.py b/tests/benchmark/mlebench/core/models.py deleted file mode 100644 index 98d8eeee..00000000 --- a/tests/benchmark/mlebench/core/models.py +++ /dev/null @@ -1,23 +0,0 @@ -"""Data models for MLE Bench runner.""" - -from dataclasses import dataclass -from typing import Optional - - -@dataclass -class TestResult: - """Structured class to store test results""" - - name: str - success: bool - submission_path: Optional[str] = None - model_path: Optional[str] = None - failure_reason: Optional[str] = None - - -@dataclass -class SubmissionInfo: - """Structured class to store submission information""" - - competition_id: str - submission_path: str diff --git a/tests/benchmark/mlebench/core/runner.py b/tests/benchmark/mlebench/core/runner.py deleted file mode 100644 index 8c1f6414..00000000 --- a/tests/benchmark/mlebench/core/runner.py +++ /dev/null @@ -1,64 +0,0 @@ -"""Main runner class for MLE Bench benchmark.""" - -import os -import sys -from pathlib import Path - -from mlebench.core.config import ConfigManager -from mlebench.core.validator import EnvironmentValidator -from mlebench.runners.setup import MLEBenchSetup -from mlebench.runners.test_runner import TestRunner -from mlebench.runners.grader import MLEBenchGrader - - -class MLEBenchRunner: - """Main class to run the MLE-bench benchmarking framework""" - - def __init__(self): - self.config = None - self.workdir = None - - def setup(self, cli_args): - """Set up the MLE-bench environment""" - print("🚀 Starting the MLE-bench Runner with Plexe...") - - # Get the absolute path for the config file - config_path = Path(cli_args.config).absolute() - print(f"📄 Using configuration file: {config_path}") - - # Create workdir if it doesn't exist - self.workdir = Path(os.getcwd()) / "workdir" - self.workdir.mkdir(exist_ok=True) - print(f"📁 Using working directory: {self.workdir}") - - # Check if LLM API key is set - if not EnvironmentValidator.check_llm_api_keys(): - print("❌ Required LLM API key environment variables not set. Please set them before running.") - print("❌ See the README.md file for instructions on configuring API keys.") - sys.exit(1) - - # Ensure that the configuration file exists, then load it - ConfigManager.ensure_config_exists(cli_args.rebuild) - self.config = ConfigManager.load_config(config_path) - - # Ensure Kaggle credentials are set up - EnvironmentValidator.ensure_kaggle_credentials() - - # Set up MLE-bench and prepare datasets - MLEBenchSetup.setup_mle_bench(self.config, cli_args.rebuild) - MLEBenchSetup.prepare_datasets(self.config) - - def run(self): - """Run the tests and evaluate the results""" - # Run tests - test_runner = TestRunner(self.config) - submissions = test_runner.run_tests() - - # Grade agent if there are submissions - if submissions: - grades_dir = MLEBenchGrader.grade_agent(submissions) - print(f"📊 Benchmark results saved to: {grades_dir}") - else: - print("❌ No submissions were generated. Cannot grade the agent.") - - print("✅ Script completed. Thank you for using the MLE-bench Runner!") diff --git a/tests/benchmark/mlebench/core/validator.py b/tests/benchmark/mlebench/core/validator.py deleted file mode 100644 index a442141a..00000000 --- a/tests/benchmark/mlebench/core/validator.py +++ /dev/null @@ -1,40 +0,0 @@ -"""Environment validation for MLE Bench runner.""" - -import os -import sys - - -class EnvironmentValidator: - """Class to validate environment setup""" - - @staticmethod - def ensure_kaggle_credentials(): - """Ensure that Kaggle API credentials are set up""" - print("🔑 Checking Kaggle API credentials...") - if not os.path.exists(os.path.expanduser("~/.kaggle/kaggle.json")): - print( - "❌ Kaggle API credentials not found. Please save 'kaggle.json' to '~/.kaggle/' following " - "the instructions at https://www.kaggle.com/docs/api." - ) - sys.exit(1) - print("✅ Kaggle API credentials found.") - - @staticmethod - def check_llm_api_keys(): - """Check if required LLM API key environment variables are set""" - # Check for common LLM provider API keys - api_keys = {"OpenAI": "OPENAI_API_KEY", "Anthropic": "ANTHROPIC_API_KEY", "Gemini": "GEMINI_API_KEY"} - - keys_found = False - for provider, env_var in api_keys.items(): - if os.environ.get(env_var): - print(f"✅ {provider} API key found ({env_var})") - keys_found = True - - if not keys_found: - print("❌ No LLM API keys found. Please set one of the following environment variables:") - for provider, env_var in api_keys.items(): - print(f"❌ - {env_var} (for {provider})") - return False - - return True diff --git a/tests/benchmark/mlebench/runners/__init__.py b/tests/benchmark/mlebench/runners/__init__.py deleted file mode 100644 index d7878e7d..00000000 --- a/tests/benchmark/mlebench/runners/__init__.py +++ /dev/null @@ -1 +0,0 @@ -"""Test runner implementations for MLE Bench runner.""" diff --git a/tests/benchmark/mlebench/runners/grader.py b/tests/benchmark/mlebench/runners/grader.py deleted file mode 100644 index 489d195b..00000000 --- a/tests/benchmark/mlebench/runners/grader.py +++ /dev/null @@ -1,44 +0,0 @@ -"""Grader for MLE Bench benchmark results.""" - -import json -from pathlib import Path -from typing import List - -from mlebench.core.models import SubmissionInfo -from mlebench.utils.command import CommandRunner - - -class MLEBenchGrader: - """Class to handle grading of model submissions""" - - @staticmethod - def grade_agent(submissions: List[SubmissionInfo]): - """Grade the agent's performance based on the test results""" - print("📊 Grading the agent's performance...") - - # Get current working directory - original_cwd = Path.cwd() - - # Write the list of dicts to a JSONL file - submissions_file = original_cwd / "submissions.jsonl" - with open(submissions_file, "w") as f: - for submission in submissions: - f.write( - json.dumps( - {"competition_id": submission.competition_id, "submission_path": submission.submission_path} - ) - + "\n" - ) - - # Create grades directory if it doesn't exist - grades_dir = original_cwd / "grades" - grades_dir.mkdir(exist_ok=True) - - CommandRunner.run( - ["mlebench", "grade", "--submission", str(submissions_file), "--output-dir", str(grades_dir)], - "Failed to grade the agent.", - "Agent graded successfully.", - ) - print(f"🏆 Agent grading completed for {len(submissions)} tests.") - - return grades_dir diff --git a/tests/benchmark/mlebench/runners/setup.py b/tests/benchmark/mlebench/runners/setup.py deleted file mode 100644 index aaaa012c..00000000 --- a/tests/benchmark/mlebench/runners/setup.py +++ /dev/null @@ -1,103 +0,0 @@ -"""Setup and preparation for MLE Bench runner.""" - -import os -import sys -import shutil - -from mlebench.utils.command import CommandRunner, working_directory - - -class MLEBenchSetup: - """Class to handle setup of MLE-bench framework""" - - @staticmethod - def setup_mle_bench(config, rebuild: bool = False): - """Set up the MLE-bench framework""" - print("🔧 Setting up 'mle-bench' framework...") - - # First, ensure kaggle package is properly installed - print("📦 Checking kaggle package version...") - CommandRunner.run( - [sys.executable, "-m", "pip", "show", "kaggle"], - "Failed to check kaggle package version.", - "Kaggle package version checked successfully.", - ) - - repo_dir = config.get("repo_dir") - repo_url = config.get("repo_url") - - if os.path.exists(repo_dir) and not rebuild: - print(f"📂 '{repo_dir}' repository already exists. Skipping setup step.") - return - else: - if rebuild: - print("🔄 Rebuilding 'mle-bench' repository...") - if os.path.exists(repo_dir): - if os.access(repo_dir, os.W_OK): - print(f"Removing '{repo_dir}'...") - shutil.rmtree(repo_dir) - print(f"Removed '{repo_dir}' successfully.") - else: - print(f"⚠️ No write permission for '{repo_dir}'. Attempting to change permissions...") - os.chmod(repo_dir, 0o700) # Grant read, write, and execute permissions to the owner - if os.access(repo_dir, os.W_OK): - print(f"Permissions changed. Removing '{repo_dir}'...") - shutil.rmtree(repo_dir) - print(f"Removed '{repo_dir}' successfully.") - else: - print(f"❌ Failed to change permissions for '{repo_dir}'. Cannot remove the directory.") - sys.exit(1) - else: - print(f"Directory '{repo_dir}' not found. Skipping removal.") - print(f"🔍 Cloning '{repo_url}' into '{repo_dir}'...") - CommandRunner.run( - ["git", "clone", repo_url, repo_dir], - f"Failed to clone '{repo_url}'.", - f"'{repo_url}' cloned successfully into '{repo_dir}'.", - ) - - # Install MLE-bench using pip - with working_directory(repo_dir): - print("🔍 Skipping Git LFS setup for testing...") - CommandRunner.run( - ["git", "lfs", "install"], "Failed to install Git LFS.", "Git LFS installed successfully." - ) - CommandRunner.run( - ["git", "lfs", "fetch", "--all"], - "Failed to fetch large files with Git LFS.", - "Fetched all large files using Git LFS.", - ) - CommandRunner.run( - ["git", "lfs", "pull"], - "Failed to pull large files with Git LFS.", - "Pulled all large files using Git LFS.", - ) - - print("🔍 Installing 'mle-bench' and dependencies...") - CommandRunner.run( - [sys.executable, "-m", "pip", "install", "-e", "."], - "Failed to install 'mle-bench'.", - "'mle-bench' installed successfully.", - ) - - @staticmethod - def prepare_datasets(config): - """Prepare datasets listed in the config file""" - print("📦 Preparing datasets for 'mle-bench'...") - - repo_dir = config.get("repo_dir") - datasets = config.get("datasets", []) - print(f"📂 Datasets to prepare: {datasets}") - - if not datasets: - print("⚠️ No datasets listed in 'mle-bench-config.yaml'. Skipping dataset preparation.") - return - - with working_directory(repo_dir): - for dataset in datasets: - print(f"📂 Preparing dataset: {dataset}") - CommandRunner.run( - ["mlebench", "prepare", "-c", dataset, "--skip-verification"], - f"Failed to prepare dataset: {dataset}", - f"Dataset '{dataset}' prepared successfully.", - ) diff --git a/tests/benchmark/mlebench/runners/test_runner.py b/tests/benchmark/mlebench/runners/test_runner.py deleted file mode 100644 index 5bd38e9a..00000000 --- a/tests/benchmark/mlebench/runners/test_runner.py +++ /dev/null @@ -1,245 +0,0 @@ -"""Test runner for MLE Bench benchmarks.""" - -import os -import time -import warnings -from pathlib import Path -from typing import List - -import pandas as pd -import platformdirs -import plexe -from tqdm import tqdm - -from mlebench.core.models import TestResult, SubmissionInfo -from mlebench.utils.error import ErrorHandler - -# Sklearn often throws warnings when used in plexe -warnings.filterwarnings("ignore", category=UserWarning, module="sklearn") - - -class TestRunner: - """Class to run tests using plexe""" - - def __init__(self, config): - self.config = config - self.provider = config.get("provider", "openai/gpt-4o") - self.max_iterations = config.get("max_iterations", 3) - self.timeout = config.get("timeout", 3600) # Default 1 hour timeout - self.workdir = Path(os.getcwd()) / "workdir" - self.workdir.mkdir(exist_ok=True) - self.mle_bench_data_dir = Path(platformdirs.user_cache_dir()) / "mle-bench" / "data" - - print(f"🔧 Using provider: {self.provider}, max_iterations: {self.max_iterations}, timeout: {self.timeout}s") - - def verify_test_files(self, test_name) -> bool: - """Verify that all required files for a test exist""" - data_dir = self.mle_bench_data_dir / test_name / "prepared" / "public" - required_files = [ - data_dir / "train.csv", - data_dir / "test.csv", - data_dir / "description.md", - data_dir / "sample_submission.csv", - ] - - for file_path in required_files: - if not file_path.exists(): - print(f"❌ Required file not found: {file_path}") - return False - - return True - - def prepare_test(self, test_name): - """Prepare test data and create output directory""" - data_dir = self.mle_bench_data_dir / test_name / "prepared" / "public" - - # Read task description - with open(data_dir / "description.md", "r") as f: - task_description = f.read() - - # Create output directory for this test - output_dir = self.workdir / test_name - output_dir.mkdir(exist_ok=True) - - # Load datasets - print(f"📊 Loading datasets for {test_name}...") - train_data = pd.read_csv(data_dir / "train.csv") - test_data = pd.read_csv(data_dir / "test.csv") - sample_submission = pd.read_csv(data_dir / "sample_submission.csv") - - test_data_info = { - "train_data": train_data, - "test_data": test_data, - "sample_submission": sample_submission, - "task_description": task_description, - "output_dir": output_dir, - } - - return test_data_info - - def build_model(self, test_name, test_data_info): - """Build a model using plexe""" - print(f"🤖 Creating model for {test_name}...") - model = plexe.Model( - intent=test_data_info["task_description"], - ) - - # Build the model - print(f"🏗️ Building model for {test_name}...") - start_time = time.time() - try: - model.build( - datasets=[test_data_info["train_data"]], - provider=self.provider, - max_iterations=self.max_iterations, - timeout=self.timeout, - ) - build_time = time.time() - start_time - print(f"✅ Model built successfully in {build_time:.2f} seconds") - return model - except Exception as e: - ErrorHandler.handle_error("model building", test_name, e) - return None - - def validate_predictions(self, predictions, expected_columns): - """Validate prediction data has required columns and format""" - missing_cols = [col for col in expected_columns if col not in predictions.columns] - if missing_cols: - raise ValueError(f"Predictions missing required columns: {missing_cols}") - return True - - def generate_predictions(self, model, test_name, test_data_info): - """Generate predictions using the model""" - print(f"🔮 Generating predictions for {test_name}...") - - test_data = test_data_info["test_data"] - sample_submission = test_data_info["sample_submission"] - output_dir = test_data_info["output_dir"] - - # Determine columns that need to be in submission file from the sample submission - submission_columns = list(sample_submission.columns) - - print(f"🎯 Target columns: {submission_columns}") - - # Create submission file path - submission_path = output_dir / "submission.csv" - - try: - # Process each row in test data - prediction_results = [] - - print(f"📊 Processing {len(test_data)} test records...") - - # Use tqdm for progress tracking - for idx, (_, row) in enumerate( - tqdm(test_data.iterrows(), total=len(test_data), desc=f"Generating predictions for {test_name}") - ): - try: - # Convert row to dictionary - row_dict = row.to_dict() - - # Make prediction for this row - row_prediction = model.predict(row_dict) - - # Concatenate row_dict with row_prediction, then keep only submissions columns - row_prediction = {**row_dict, **row_prediction} - row_prediction = {k: v for k, v in row_prediction.items() if k in submission_columns} - - prediction_results.append(row_prediction) - - except Exception as e: - print(f"⚠️ Error predicting row {idx}: {e}") - # Add empty prediction to maintain row count - empty_prediction = {col: None for col in submission_columns} - prediction_results.append(empty_prediction) - - # Create a DataFrame from all the prediction results - all_predictions_df = pd.DataFrame(prediction_results) - - # Validate predictions have required columns - self.validate_predictions(all_predictions_df, sample_submission.columns) - - # Save the prediction results - all_predictions_df.to_csv(submission_path, index=False) - print(f"✅ Predictions generated and submission file created at {submission_path}") - return submission_path - - except Exception as e: - ErrorHandler.handle_error("prediction generation", test_name, e) - return None - - def save_model(self, model, test_name, output_dir): - """Save model for future reference""" - model_save_path = output_dir / f"{test_name}_model.tar.gz" - try: - plexe.save_model(model, str(model_save_path)) - print(f"✅ Model saved to {model_save_path}") - return model_save_path - except Exception as e: - print(f"⚠️ Failed to save model (non-critical): {e}") - return None - - def run_tests(self) -> List[SubmissionInfo]: - """Run tests from the configuration file using plexe""" - print("🏁 Starting test execution with plexe...") - test_results = [] - submissions = [] - - for test_name in self.config.get("datasets", []): - try: - print(f"🔍 Running test: {test_name}") - - # Check if required files exist - if not self.verify_test_files(test_name): - test_results.append(TestResult(name=test_name, success=False, failure_reason="missing files")) - continue - - # Prepare test data - test_data_info = self.prepare_test(test_name) - - # Build model - model = self.build_model(test_name, test_data_info) - - if model: - # Generate predictions - submission_path = self.generate_predictions(model, test_name, test_data_info) - - if submission_path: - # Save model - model_path = self.save_model(model, test_name, test_data_info["output_dir"]) - - # Record successful test - test_results.append( - TestResult( - name=test_name, - success=True, - submission_path=str(submission_path), - model_path=str(model_path) if model_path else None, - ) - ) - - # Add to submissions for grading - submissions.append( - SubmissionInfo(competition_id=test_name, submission_path=str(submission_path)) - ) - else: - test_results.append( - TestResult(name=test_name, success=False, failure_reason="prediction failed") - ) - else: - test_results.append(TestResult(name=test_name, success=False, failure_reason="model build failed")) - - except Exception as e: - ErrorHandler.handle_error("test execution", test_name, e) - test_results.append( - TestResult(name=test_name, success=False, failure_reason=f"general error: {str(e)}") - ) - - # Report failed tests - failed_tests = [test for test in test_results if not test.success] - if failed_tests: - print(f"⚠️ {len(failed_tests)} tests failed:") - for test in failed_tests: - print(f"⚠️ - {test.name}: {test.failure_reason}") - - return submissions diff --git a/tests/benchmark/mlebench/utils/__init__.py b/tests/benchmark/mlebench/utils/__init__.py deleted file mode 100644 index 63d7fda7..00000000 --- a/tests/benchmark/mlebench/utils/__init__.py +++ /dev/null @@ -1 +0,0 @@ -"""Utility functions and classes for MLE Bench runner.""" diff --git a/tests/benchmark/mlebench/utils/command.py b/tests/benchmark/mlebench/utils/command.py deleted file mode 100644 index eff803fc..00000000 --- a/tests/benchmark/mlebench/utils/command.py +++ /dev/null @@ -1,42 +0,0 @@ -"""Command execution utilities for MLE Bench runner.""" - -import subprocess -import sys -from contextlib import contextmanager -import os -from pathlib import Path - - -class CommandRunner: - """Class to handle command execution and error handling""" - - @staticmethod - def run(command, error_message, success_message=None): - """Run a shell command and handle errors""" - try: - subprocess.run(command, check=True, text=True) - if success_message: - print(f"✅ {success_message}") - except subprocess.CalledProcessError as e: - print(f"❌ {error_message}") - print(f"❌ Error details: {e}") - sys.exit(1) - except FileNotFoundError as e: - print(f"❌ {str(e)}") - print(f"❌ Command not found: {' '.join(command)}") - print( - "❌ This usually means that the required tool is not installed or not in the PATH. " - "Please install the required dependencies and try again." - ) - sys.exit(1) - - -@contextmanager -def working_directory(path): - """Context manager for changing the current working directory""" - prev_cwd = Path.cwd() - os.chdir(path) - try: - yield - finally: - os.chdir(prev_cwd) diff --git a/tests/benchmark/mlebench/utils/error.py b/tests/benchmark/mlebench/utils/error.py deleted file mode 100644 index e9037fc7..00000000 --- a/tests/benchmark/mlebench/utils/error.py +++ /dev/null @@ -1,18 +0,0 @@ -"""Error handling utilities for MLE Bench runner.""" - -import sys -import traceback - - -class ErrorHandler: - """Class to handle and format errors""" - - @staticmethod - def handle_error(operation, context, error, exit_on_failure=False): - """Handle exceptions with consistent formatting""" - print(f"❌ Error during {operation}: {error}") - if context: - print(f"❌ Context: {context}") - print(traceback.format_exc()) - if exit_on_failure: - sys.exit(1) diff --git 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+# Plexe: Agentic ML Framework with MCP Integration -# plexe ✨ +Plexe là một framework đa tác tử (multi-agent) được xây dựng trên nền tảng **LangGraph**, được thiết kế để tự động hóa toàn bộ quy trình xây dựng mô hình Machine Learning từ ngôn ngữ tự nhiên. -[![PyPI version](https://img.shields.io/pypi/v/plexe.svg)](https://pypi.org/project/plexe/) -[![Discord](https://img.shields.io/discord/1300920499886358529?logo=discord&logoColor=white)](https://discord.gg/SefZDepGMv) +Hệ thống đã được nâng cấp với **Model Context Protocol (MCP)** để mở rộng khả năng kết nối với các công cụ học thuật và dữ liệu bên ngoài một cách chuẩn hóa. -backed-by-yc +## 🚀 Các tính năng chính sau điều chỉnh +1. **Kiến trúc Đa tác tử LangGraph**: Điều phối luồng công việc giữa các Agent chuyên biệt (EDA, Dataset Builder, Task Builder, GNN Specialist). +2. **Tích hợp MCP (Model Context Protocol)**: + * **Google Scholar**: Tìm kiếm bài báo khoa học, trích xuất thông tin tác giả trực tiếp qua MCP. + * **Kaggle**: Tìm kiếm và tải xuống tập dữ liệu từ Kaggle API thông qua MCP server. + * **Khả năng mở rộng**: Dễ dàng thêm các MCP server mới chỉ bằng cách cập nhật `mcp_config.json`. +3. **Hỗ trợ GPU**: Tối ưu hóa cho việc huấn luyện Graph Neural Networks (GNNs) sử dụng CUDA. -Build machine learning models using natural language. +## 🏗️ Cấu trúc hệ thống MCP -[Quickstart](#1-quickstart) | -[Features](#2-features) | -[Installation](#3-installation) | -[Documentation](#4-documentation) +* `mcp_config.json`: Cấu hình danh sách các MCP server và tham số khởi chạy. +* `plexe/langgraph/mcp_manager.py`: Quản lý kết nối, khám phá tools và chuyển đổi MCP tools thành LangChain tools. +* `plexe/langgraph/mcp_servers/`: Thư mục chứa các tùy chỉnh MCP server (Scholar, Kaggle). -
+## 🛠️ Cài đặt & Sử dụng -**plexe** lets you create machine learning models by describing them in plain language. Simply explain what you want, -and the AI-powered system builds a fully functional model through an automated agentic approach. Also available as a -[managed cloud service](https://plexe.ai). +### 1. Cấu hình biến môi trường +Tạo file `.env` hoặc cập nhật `docker-compose.gpu.yml` với các thông tin sau: +```env +# LLM Keys +OPENAI_API_KEY=your_key +GOOGLE_API_KEY=your_key -
- -Watch the demo on YouTube: -[![Building an ML model with Plexe](resources/demo-thumbnail.png)](https://www.youtube.com/watch?v=bUwCSglhcXY) -
- -## 1. Quickstart - -### Installation -```bash -pip install plexe -``` - -### Using plexe - -You can use plexe as a Python library to build and train machine learning models: - -```python -import plexe - -# Define the model -model = plexe.Model( - intent="Predict sentiment from news articles", - input_schema={"headline": str, "content": str}, - output_schema={"sentiment": str} -) - -# Build and train the model -model.build( - datasets=[your_dataset], - provider="openai/gpt-4o-mini", - max_iterations=10 -) - -# Use the model -prediction = model.predict({ - "headline": "New breakthrough in renewable energy", - "content": "Scientists announced a major advancement..." -}) - -# Save for later use -plexe.save_model(model, "sentiment-model") -loaded_model = plexe.load_model("sentiment-model.tar.gz") -``` - -## 2. Features - -### 2.1. 💬 Natural Language Model Definition -Define models using plain English descriptions: - -```python -model = plexe.Model( - intent="Predict housing prices based on features like size, location, etc.", - input_schema={"square_feet": int, "bedrooms": int, "location": str}, - output_schema={"price": float} -) +# Kaggle (Bắt buộc cho Kaggle MCP tool) +KAGGLE_USERNAME=your_username +KAGGLE_KEY=your_api_key ``` -### 2.2. 🤖 Multi-Agent Architecture -The system uses a team of specialized AI agents to: -- Analyze your requirements and data -- Plan the optimal model solution -- Generate and improve model code -- Test and evaluate performance -- Package the model for deployment - -### 2.3. 🎯 Automated Model Building -Build complete models with a single method call: - -```python -model.build( - datasets=[dataset_a, dataset_b], - provider="openai/gpt-4o-mini", # LLM provider - max_iterations=10, # Max solutions to explore - timeout=1800 # Optional time limit in seconds -) -``` - -### 2.4. 🚀 Distributed Training with Ray - -Plexe supports distributed model training and evaluation with Ray for faster parallel processing: - -```python -from plexe import Model - -# Optional: Configure Ray cluster address if using remote Ray -# from plexe import config -# config.ray.address = "ray://10.1.2.3:10001" - -model = Model( - intent="Predict house prices based on various features", - distributed=True # Enable distributed execution -) - -model.build( - datasets=[df], - provider="openai/gpt-4o-mini" -) -``` - -Ray distributes your workload across available CPU cores, significantly speeding up model generation and evaluation when exploring multiple model variants. - -### 2.5. 🎲 Data Generation & Schema Inference -Generate synthetic data or infer schemas automatically: - -```python -# Generate synthetic data -dataset = plexe.DatasetGenerator( - description="Example dataset with features and target", - provider="openai/gpt-4o-mini", - schema={"features": str, "target": int} -) -dataset.generate(500) # Generate 500 samples - -# Infer schema from intent -model = plexe.Model(intent="Predict customer churn based on usage patterns") -model.build(provider="openai/gpt-4o-mini") # Schema inferred automatically -``` - -### 2.6. 🌐 Multi-Provider Support -Use your preferred LLM provider, for example: -```python -model.build(provider="openai/gpt-4o-mini") # OpenAI -model.build(provider="anthropic/claude-3-opus") # Anthropic -model.build(provider="ollama/llama2") # Ollama -model.build(provider="huggingface/meta-llama/...") # Hugging Face -``` -See [LiteLLM providers](https://docs.litellm.ai/docs/providers) for instructions and available providers. - -> [!NOTE] -> Plexe *should* work with most LiteLLM providers, but we actively test only with `openai/*` and `anthropic/*` -> models. If you encounter issues with other providers, please let us know. - - -## 3. Installation - -### 3.1. Installation Options -```bash -pip install plexe # Standard installation, minimal dependencies -pip install plexe[transformers] # Support for transformers, tokenizers, etc -pip install plexe[chatui] # Local chat UI for model interaction -pip install plexe[all] # All optional dependencies -``` - -### 3.2. API Keys +### 2. Chạy với Docker +Sử dụng Docker Compose để khởi chạy toàn bộ hệ thống (bao gồm MLflow, Postgres, và Plexe Backend): ```bash -# Set your preferred provider's API key -export OPENAI_API_KEY= -export ANTHROPIC_API_KEY= -export GEMINI_API_KEY= +docker compose -f docker-compose.gpu.yml up -d ``` -See [LiteLLM providers](https://docs.litellm.ai/docs/providers) for environment variable names. - -## 4. Documentation -For full documentation, visit [docs.plexe.ai](https://docs.plexe.ai). - -## 5. Contributing -See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines. Join our [Discord](https://discord.gg/SefZDepGMv) to connect with the team. - -## 6. License -[Apache-2.0 License](LICENSE) -## 7. Citation -If you use Plexe in your research, please cite it as follows: +### 3. Cách thức hoạt động của Agent +Mọi Agent kế thừa từ `BaseAgent` sẽ tự động tải các tools từ các MCP server được cấu hình trong `mcp_config.json`. Bạn có thể yêu cầu Agent trong Chat UI: +- *"Tìm các bài báo mới nhất về GNN trên Google Scholar"* +- *"Tải tập dữ liệu Titanic từ Kaggle và phân tích nó"* -```bibtex -@software{plexe2025, - author = {De Bernardi, Marcello AND Dubey, Vaibhav}, - title = {Plexe: Build machine learning models using natural language.}, - year = {2025}, - publisher = {GitHub}, - howpublished = {\url{https://github.com/plexe-ai/plexe}}, -} +## 📝 Ghi chú cho Docker +Hệ thống sử dụng `Dockerfile.gpu` dựa trên `pytorch/pytorch:2.7.0-cuda12.8` để đảm bảo hiệu suất huấn luyện mô hình. Các thư viện bổ sung như `scholarly`, `kaggle`, và `mcp[all]` đã được tích hợp sẵn trong quá trình build image. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index bedc60b0..00000000 --- a/SECURITY.md +++ /dev/null @@ -1,11 +0,0 @@ -# Security Policy - -The Plexe AI team and community take security vulnerabilities seriously. We appreciate your efforts to responsibly disclose any issues you discover, and we will make every effort to acknowledge your contributions. - -## Reporting a Vulnerability - -To report a security issue, please use the GitHub Security Advisory **"Report a Vulnerability"** tab in the [plexe repository](https://github.com/plexe-ai/plexe). - -The Plexe AI team will review your report and send a response indicating the next steps in handling your disclosure. After the initial reply, we will keep you informed of our progress toward a fix and public announcement, and we may request additional information or guidance. - -Thank you for helping to make `plexe` secure and reliable for everyone. diff --git a/automl-agent b/automl-agent new file mode 160000 index 00000000..9e0d8429 --- /dev/null +++ b/automl-agent @@ -0,0 +1 @@ +Subproject commit 9e0d842959a09d96c00768c14d73bd9df6d39023 diff --git a/docker-compose.gpu.yml b/docker-compose.gpu.yml index a69d0448..51c7771c 100644 --- a/docker-compose.gpu.yml +++ b/docker-compose.gpu.yml @@ -77,6 +77,24 @@ services: MLFLOW_HTTP_REQUEST_TIMEOUT: 300 HF_TOKEN: ${HF_TOKEN} HUGGINGFACE_API_KEY: ${HUGGINGFACE_API_KEY} + # API Keys for LLM providers + OPENAI_API_KEY: ${OPENAI_API_KEY} + GOOGLE_API_KEY: ${GOOGLE_API_KEY:-${GEMINI_API_KEY}} + ANTHROPIC_API_KEY: ${ANTHROPIC_API_KEY} + # Plexe Agent Model Configuration + PLEXE_ORCHESTRATOR_MODEL: ${PLEXE_ORCHESTRATOR_MODEL:-gemini/gemini-2.0-flash-exp} + PLEXE_CONVERSATIONAL_MODEL: ${PLEXE_CONVERSATIONAL_MODEL:-gemini/gemini-2.0-flash-exp} + PLEXE_EDA_MODEL: ${PLEXE_EDA_MODEL:-gemini/gemini-2.0-flash-exp} + PLEXE_DATASET_BUILDER_MODEL: ${PLEXE_DATASET_BUILDER_MODEL:-gemini/gemini-2.0-flash-exp} + PLEXE_TASK_BUILDER_MODEL: ${PLEXE_TASK_BUILDER_MODEL:-gemini/gemini-2.0-flash-exp} + PLEXE_GNN_SPECIALIST_MODEL: ${PLEXE_GNN_SPECIALIST_MODEL:-gemini/gemini-2.0-flash-exp} + PLEXE_OPERATION_MODEL: ${PLEXE_OPERATION_MODEL:-gemini/gemini-2.0-flash-exp} + PLEXE_AGENT_TEMPERATURE: ${PLEXE_AGENT_TEMPERATURE:-0.1} + PLEXE_VERBOSE: ${PLEXE_VERBOSE:-true} + # Kaggle Credentials for MCP + KAGGLE_USERNAME: ${KAGGLE_USERNAME} + KAGGLE_KEY: ${KAGGLE_KEY} + MCP_CONFIG_PATH: /app/mcp_config.json volumes: - .:/app ports: diff --git a/docs/architecture/langgraph-multi-agent-system.md b/docs/architecture/langgraph-multi-agent-system.md index 37decff2..438477ab 100644 --- a/docs/architecture/langgraph-multi-agent-system.md +++ b/docs/architecture/langgraph-multi-agent-system.md @@ -100,34 +100,53 @@ The system consists of specialized agents coordinated by a LangGraph StateGraph **Output**: `task.py` with GenTask class ### 5. Relational GNN Specialist Agent -**Role**: GNN training script generation and execution +**Role**: GNN training script generation with Training-Free HPO **Responsibilities**: -- Generate training scripts using plexe.relbench.modeling +- **Training-Free Hyperparameter Search**: Query external knowledge sources (literature, benchmarks) to find optimal hyperparameters without expensive trial-and-error +- Generate optimized training scripts using plexe.relbench.modeling - Configure HeteroEncoder, HeteroTemporalEncoder, HeteroGraphSAGE -- Execute training with temporal sampling -- Report model performance metrics +- Select hyperparameters based on dataset characteristics and task type +- **Handoff to Operation Agent**: Prepare training script for execution + +**Key Innovation**: Implements "Training-Free Model Search and HPO" approach from AutoML-Agent paper, leveraging: +- Academic literature search for best practices +- Benchmark database queries for proven configurations +- Heuristic-based selection using dataset characteristics +- Ensemble voting across multiple knowledge sources **Tools**: -- `generate_training_script`: Create train_script.py -- `execute_training_script`: Run training +- `search_optimal_hyperparameters`: Find hyperparameters based on dataset characteristics +- `search_literature_for_hyperparameters`: Query academic papers +- `get_benchmark_hyperparameters`: Retrieve from benchmark leaderboards +- `compare_hyperparameter_configs`: Ensemble multiple sources +- `generate_training_script`: Create train_script.py with optimal hyperparameters -**Output**: `train_script.py`, `best_model.pt`, `training_results.json` +**Output**: +- `train_script.py` with optimized hyperparameters +- Hyperparameter selection reasoning +- Literature/benchmark references ### 6. Operation Agent -**Role**: Environment management and finalization +**Role**: Training execution, monitoring, and finalization **Responsibilities**: -- Verify environment requirements -- Monitor training execution -- Handle errors and retries +- **Execute training scripts** generated by GNN Specialist +- Monitor training progress and handle errors +- Process training results and metrics +- Handle timeouts and retries - Generate inference code -- Package model artifacts +- Package model artifacts for deployment **Tools**: -- `execute_training_script`: Run scripts +- `execute_training_script`: Run training scripts - `save_artifact`: Save files +**Output**: +- `best_model.pt`: Trained model +- `training_results.json`: Performance metrics +- Final pipeline summary + ## Pipeline Flow ### Phase 1: Conversation @@ -179,29 +198,55 @@ Schema + User Intent → Task Builder Agent → GenTask Class Generate task.py ``` -### Phase 5: GNN Training +### Phase 5: GNN Training (Training-Free HPO) ``` -dataset.py + task.py → GNN Specialist Agent → Trained Model +dataset.py + task.py → GNN Specialist Agent → Optimized Training Script │ - ▼ - Generate train_script.py + ├──▶ Search Optimal Hyperparameters + │ (Training-Free HPO) + │ │ + │ ├─ Query Literature + │ ├─ Check Benchmarks + │ ├─ Apply Heuristics + │ └─ Ensemble Results │ ▼ - Execute Training + Generate train_script.py + (with optimal hyperparameters) │ ▼ - Report Metrics + Handoff to Operation Agent ``` -### Phase 6: Operation +**Key Innovation**: Training-Free Hyperparameter Optimization +- No trial-and-error training runs +- Leverage external knowledge sources +- Intelligent hyperparameter selection based on: + * Dataset characteristics (size, temporal nature) + * Academic literature best practices + * Benchmark leaderboard results + * Task type requirements + +### Phase 6: Operation (Training Execution) ``` -Training Results → Operation Agent → Final Package +Training Script → Operation Agent → Trained Model + Results + │ + ├──▶ Execute Training Script + │ │ + │ └─ Monitor Progress + │ + ├──▶ Process Results + │ │ + │ └─ Extract Metrics │ ▼ Generate Inference Code │ ▼ Package Artifacts + │ + ▼ + Package Artifacts ``` ## Configuration diff --git a/docs/external-api-setup.md b/docs/external-api-setup.md new file mode 100644 index 00000000..75a8210a --- /dev/null +++ b/docs/external-api-setup.md @@ -0,0 +1,162 @@ +# External API Configuration Guide +## Overview + +Plexe's hyperparameter optimization tools use external APIs to search academic literature and benchmarks for optimal hyperparameters. This eliminates the need for expensive trial-and-error training runs. + +## Required API Keys + +### 1. Semantic Scholar API + +**Purpose**: Search academic papers for hyperparameter recommendations +**Cost**: Free for academic use (up to 100 requests/minute with API key, 1/minute without) + +**How to get it:** +1. Visit https://www.semanticscholar.org/product/api +2. Click "Apply for an API Key" or visit the Partner Form +3. Fill out the application form (usually approved within 1-2 business days) +4. You'll receive an API key via email + +**Configuration:** +```bash +export SEMANTIC_SCHOLAR_API_KEY=your_api_key_here +``` + +Or add to `.env` file: +``` +SEMANTIC_SCHOLAR_API_KEY=your_api_key_here +``` + +### 2. OpenML API Key + +**Purpose**: Access benchmark datasets and model performance data +**Cost**: Free + +**How to get it:** +1. Visit https://www.openml.org/auth/sign-in +2. Create an account (or sign in with GitHub) +3. Go to your profile settings +4. Click on "API authentication" section +5. Your API key will be displayed there + +**Configuration:** +```bash +export OPENML_API_KEY=your_api_key_here +``` + +Or add to `.env` file: +``` +OPENML_API_KEY=your_api_key_here +``` + +### 3. Hugging Face Token (Optional) + +**Purpose**: Access Hugging Face datasets and models +**Cost**: Free + +**How to get it:** +1. Visit https://huggingface.co/settings/tokens +2. Create an account if you don't have one +3. Click "New token" +4. Give it a name (e.g., "plexe-hpo") +5. Select "Read" permissions +6. Copy the generated token + +**Configuration:** +```bash +export HF_TOKEN=your_token_here +``` + +Or add to `.env` file: +``` +HF_TOKEN=your_token_here +``` + +## APIs That Don't Require Keys + +### arXiv API + +**Purpose**: Search preprint papers +**No API key required** - Rate limited to 1 request per 3 seconds +**Documentation**: https://info.arxiv.org/help/api/index.html + +### Papers With Code API + +**Purpose**: Access benchmark leaderboards and SOTA results +**No API key required** - Rate limited +**Documentation**: https://paperswithcode.com/api/v1/docs/ + +## Configuration File + +Create a `.env` file in the project root: + +```bash +# Copy from .env.example +cp .env.example .env +``` + +Then edit `.env` and add your API keys: + +```bash +# External API Keys for HPO Search +SEMANTIC_SCHOLAR_API_KEY=your_semantic_scholar_api_key_here +OPENML_API_KEY=your_openml_api_key_here +HF_TOKEN=your_huggingface_token_here +``` + +## Rate Limits + +Be aware of rate limits for each service: + +| Service | With API Key | Without API Key | +|---------|-------------|-----------------| +| Semantic Scholar | 100 req/min | 1 req/min | +| arXiv | N/A | 1 req/3s (~20/min) | +| Papers With Code | N/A | ~20 req/min | +| OpenML | 20 req/min | 10 req/min | + +The clients include automatic rate limiting to respect these limits. + +## Troubleshooting + +### "API key not found" error + +Make sure your `.env` file is in the project root and the key names match exactly: +- `SEMANTIC_SCHOLAR_API_KEY` +- `OPENML_API_KEY` +- `HF_TOKEN` + +### "Rate limit exceeded" error + +The clients automatically handle rate limiting, but if you see this error: +1. Wait a few minutes +2. Reduce the number of concurrent requests +3. Consider getting an API key if using a service without one + +### "Connection error" or "Timeout" + +1. Check your internet connection +2. Verify the API service is online (check status pages) +3. Try increasing the timeout in the client configuration + +## Using MCP (Model Context Protocol) + +**Note**: The current implementation uses direct REST API calls. To use MCP: + +1. Install MCP client library: +```bash +pip install model-context-protocol +``` + +2. Configure MCP servers in your MCP configuration file + +3. Update the API clients to use MCP instead of direct HTTP requests + +MCP provides a standardized way to access these services with better error handling, caching, and composability. See the MCP documentation for more details: https://modelcontextprotocol.io/ + +## Security Best Practices + +1. **Never commit API keys** to version control +2. Add `.env` to `.gitignore` (already done in this project) +3. Use environment variables in production +4. Rotate API keys periodically +5. Use minimal permissions (e.g., read-only tokens for Hugging Face) \ No newline at end of file diff --git a/docs/mcp-hpo-explanation.md b/docs/mcp-hpo-explanation.md new file mode 100644 index 00000000..23e930f2 --- /dev/null +++ b/docs/mcp-hpo-explanation.md @@ -0,0 +1,283 @@ +# MCP HPO Integration trong Plexe + +## Tổng quan + +Plexe sử dụng **MCP (Model Context Protocol)** để implement **Training-Free Hyperparameter Optimization (HPO)**. Thay vì training nhiều lần để tìm hyperparameters tối ưu, hệ thống truy vấn các nguồn kiến thức external (papers, benchmarks) để tìm cấu hình đã được proven. + +## Kiến trúc MCP + +``` +┌─────────────────────────────────────────────────────────────┐ +│ GNN Specialist Agent │ +│ (needs hyperparameters) │ +└──────────────────────────┬──────────────────────────────────┘ + │ + ▼ +┌─────────────────────────────────────────────────────────────┐ +│ MCP Manager │ +│ (converts MCP tools → LangChain tools) │ +└──────────────────────────┬──────────────────────────────────┘ + │ + ▼ +┌─────────────────────────────────────────────────────────────┐ +│ HPO MCP Server │ +│ (hpo_server.py - FastMCP) │ +├─────────────────────────────────────────────────────────────┤ +│ Tools: │ +│ ✓ search_optimal_hyperparameters() │ +│ ✓ extract_hyperparameters_from_papers() │ +│ ✓ get_benchmark_hyperparameters() │ +│ ✓ compare_hyperparameter_configs() │ +└──────────────────────────┬──────────────────────────────────┘ + │ + ┌───────────────┼───────────────┐ + ▼ ▼ ▼ + ┌──────────┐ ┌──────────┐ ┌──────────────┐ + │ arXiv │ │ Papers │ │ Dataset │ + │ API │ │ With │ │ Heuristics │ + │ │ │ Code │ │ │ + └──────────┘ └──────────┘ └──────────────┘ +``` + +## Components + +### 1. MCP Config ([mcp_config.json](../mcp_config.json)) + +```json +{ + "mcpServers": { + "hpo-search": { + "command": "python", + "args": ["plexe/langgraph/mcp_servers/hpo_server.py"] + } + } +} +``` + +### 2. HPO MCP Server ([plexe/langgraph/mcp_servers/hpo_server.py](../plexe/langgraph/mcp_servers/hpo_server.py)) + +**4 MCP Tools chính:** + +#### `search_optimal_hyperparameters()` +- **Input**: task_type, num_nodes, num_tables, is_temporal +- **Output**: Hyperparameters dựa trên heuristics và dataset scale +- **Logic**: Áp dụng rules từ literature (GraphSAGE, RelBench papers) +- **Ví dụ**: + ```python + { + "hyperparameters": { + "hidden_channels": 128, + "batch_size": 512, + "learning_rate": 0.008, # 0.01 * 0.8 for temporal + "num_gnn_layers": 2, + "epochs": 15 + }, + "reasoning": "Based on 15000 nodes, temporal task...", + "confidence": "high" + } + ``` + +#### `extract_hyperparameters_from_papers()` +- **Input**: paper_query, model_type, num_papers +- **Output**: Hyperparameters extracted từ papers thực +- **Logic**: + 1. Query arXiv API + 2. Parse paper abstracts + 3. Extract hyperparams bằng regex (learning rate, batch size, etc.) + 4. Aggregate multiple papers +- **Ví dụ**: + ```python + { + "papers_analyzed": 5, + "papers_with_hyperparams": 3, + "extracted_hyperparameters": [ + { + "source_paper": "GraphSAGE: ...", + "hyperparameters": { + "learning_rate": 0.01, + "batch_size": 512 + } + } + ], + "aggregated_hyperparameters": { + "learning_rate": 0.01, # median từ 3 papers + "batch_size": 512 + } + } + ``` + +#### `get_benchmark_hyperparameters()` +- **Input**: task_type, dataset_domain, model_architecture +- **Output**: Hyperparameters từ benchmark leaderboards +- **Logic**: Query Papers With Code API cho SOTA results +- **Ví dụ**: + ```python + { + "hyperparameters": { + "hidden_channels": 128, + "num_gnn_layers": 2, + "learning_rate": 0.005 + }, + "benchmarks_referenced": 2, + "benchmark_papers": [ + {"paper_title": "...", "paper_url": "..."} + ] + } + ``` + +#### `compare_hyperparameter_configs()` +- **Input**: List of configs from different sources, strategy +- **Output**: Ensemble recommendation +- **Logic**: Ensemble voting (median cho numeric, mode cho categorical) +- **Ví dụ**: + ```python + { + "recommended_hyperparameters": { + "learning_rate": 0.008, # median of [0.01, 0.008, 0.005] + "batch_size": 512, # mode + "hidden_channels": 128 # median of [128, 128, 256] + }, + "num_sources": 3, + "confidence": "high" + } + ``` + +### 3. GNN Specialist Agent ([plexe/langgraph/agents/gnn_specialist.py](../plexe/langgraph/agents/gnn_specialist.py)) + +**Workflow:** + +1. **Agent init** → MCPManager loads HPO tools tự động từ BaseAgent +2. **Agent execution**: + ```python + # Step 1: Heuristic-based + result_a = search_optimal_hyperparameters( + task_type="binary_classification", + num_nodes=15000, + num_tables=7, + is_temporal=True + ) + + # Step 2: Literature-based + result_b = extract_hyperparameters_from_papers( + paper_query="Relational GNN classification", + model_type="gnn" + ) + + # Step 3: Benchmark-based + result_c = get_benchmark_hyperparameters( + task_type="binary_classification", + dataset_domain="relational" + ) + + # Step 4: Ensemble + final = compare_hyperparameter_configs( + configs=[result_a, result_b, result_c] + ) + + # Step 5: Generate training script + generate_training_script( + ..., + **final["recommended_hyperparameters"] + ) + ``` + +3. **Output**: Training script với optimal hyperparameters + reasoning + +## So sánh: Trước vs Sau + +### ❌ Trước (Không dùng MCP đúng cách) + +``` +GNN Agent → tools/hpo_search.py → external_api_clients.py → Direct API calls + ↓ + Chỉ trả về paper metadata, không có hyperparams +``` + +**Vấn đề:** +- MCP servers (arxiv, semantic-scholar) chỉ return paper info +- HPO tools gọi trực tiếp API clients, không qua MCP +- Không có tool nào thực sự extract hyperparameters + +### ✅ Sau (MCP integration đúng) + +``` +GNN Agent → MCP Manager → HPO MCP Server → arXiv API + Regex extraction + ↓ + Trả về hyperparameters cụ thể ready-to-use +``` + +**Cải thiện:** +- HPO MCP server dedicated cho hyperparameter search +- Extract hyperparams từ paper text (learning rate, batch size, etc.) +- Aggregate multiple sources +- Return format chuẩn cho training script + +## Tác dụng + +### 1. **Training-Free HPO** +Không cần chạy 10-20 training experiments để tune hyperparameters. Thay vào đó: +- Query 5 papers → extract their hyperparams → aggregate +- Tiết kiệm hàng giờ GPU time + +### 2. **Knowledge-Based Optimization** +Leverage kiến thức từ: +- Hàng nghìn papers trên arXiv +- Benchmark leaderboards (Papers With Code) +- Proven heuristics từ literature + +### 3. **Explainable Recommendations** +Mỗi hyperparameter có reasoning: +``` +"Learning rate = 0.008 because: + - Paper A used 0.01 for similar task + - Paper B used 0.005 + - Median = 0.008 + - Temporal adjustment: -20%" +``` + +### 4. **Scalable Architecture** +Dễ dàng thêm MCP servers mới: +- OpenML server cho dataset benchmarks +- Kaggle server cho competition winners +- Custom servers cho internal knowledge base + +## Testing + +Run test để verify integration: + +```bash +python test_mcp_hpo_integration.py +``` + +Expected output: +``` +1. Initializing MCP Manager... +✓ MCP Manager initialized successfully + Connected to 5 MCP servers + +2. Checking loaded MCP tools... +✓ Loaded 12 total MCP tools +✓ Found 4 HPO-related tools: + - search_optimal_hyperparameters + - extract_hyperparameters_from_papers + - get_benchmark_hyperparameters + - compare_hyperparameter_configs + +3. Testing HPO tools... +✓ All tools return hyperparameters successfully +``` + +## Future Enhancements + +1. **LLM-based extraction**: Thay regex bằng LLM để extract hyperparams chính xác hơn +2. **Meta-learning**: Học từ past experiments để predict optimal hyperparams +3. **Active learning**: Query specific papers based on dataset characteristics +4. **Benchmark database**: Cache benchmark results để query nhanh hơn + +## Kết luận + +MCP trong Plexe không chỉ là infrastructure để kết nối external APIs. Nó là core component của **Training-Free HPO strategy**, cho phép: +- ✅ Tìm hyperparameters tối ưu WITHOUT expensive training +- ✅ Leverage collective knowledge từ research community +- ✅ Explainable và reproducible recommendations +- ✅ Extensible architecture cho future enhancements diff --git a/examples/rel-f1-driver-dnf.txt b/examples/rel-f1-driver-dnf.txt index 80ab9d76..52cbac10 100644 --- a/examples/rel-f1-driver-dnf.txt +++ b/examples/rel-f1-driver-dnf.txt @@ -1,5 +1,6 @@ I am working with the data is loaded into the `f1` database (connection string: `postgresql+psycopg2://mlflow:mlflow@postgres:5432/f1`). I want to define a predictive task on this relational database. +- Database Description: The F1 database tracks all-time Formula 1 racing data and statistics. It provides detailed information for various stakeholders including drivers, constructors, engine manufacturers, and tyre manufacturers. Highlights include data on all circuits (e.g. geographical details), and full historical data from every season. This includes overall standings, race results, and more specific data like practice sessions, qualifying positions, sprints, and pit stops. - Task definition: For each driver predict the if they will DNF (did not finish) a race in the next 15 days. - Evaluation metric: Area Under the Receiver Operating Characteristic curve (AUROC). I don't have any requirements, if you need them you can set by default automatically. \ No newline at end of file diff --git a/feature_transformer.py b/feature_transformer.py deleted file mode 100644 index 00f7c03d..00000000 --- a/feature_transformer.py +++ /dev/null @@ -1,104 +0,0 @@ -import pandas as pd -import numpy as np -from sklearn.preprocessing import StandardScaler, OneHotEncoder -from sklearn.compose import ColumnTransformer -from plexe.core.interfaces.feature_transformer import FeatureTransformer - - -class FeatureTransformerImplementation(FeatureTransformer): - - def transform(self, inputs: pd.DataFrame) -> pd.DataFrame: - df = inputs.copy() - - target_variable = "SalePrice" - - # 1. Target Variable Transformation - if target_variable in df.columns: - df[target_variable] = np.log1p(df[target_variable]) - print(f"Applied log1p transformation to target variable '{target_variable}'.") - else: - print(f"Target variable '{target_variable}' not found in DataFrame. Skipping transformation.") - - # Separate features and target for transformation (if target is present) - if target_variable in df.columns: - X = df.drop(columns=[target_variable]) - y = df[target_variable] - else: - X = df - y = None # No target present - - # Identify numerical and categorical features based on dtypes - - # Define features for specific missing value imputation based on EDA - numerical_features_with_nan_specific = ["LotFrontage", "MasVnrArea", "GarageYrBlt"] - categorical_features_with_nan_specific = [ - "BsmtQual", - "BsmtCond", - "BsmtExposure", - "BsmtFinType1", - "BsmtFinType2", - "FireplaceQu", - "GarageType", - "GarageFinish", - "GarageQual", - "GarageCond", - ] - - # Step 1: Impute numerical missing values using median - for col in numerical_features_with_nan_specific: - if col in X.columns: - median_val = X[col].median() - X[col] = X[col].fillna(median_val) - print(f"Imputed missing values in numerical feature '{col}' with median: {median_val}.") - - # Step 2: Impute categorical missing values using 'NA' - for col in categorical_features_with_nan_specific: - if col in X.columns: - X[col] = X[col].fillna("NA") - print(f"Imputed missing values in categorical feature '{col}' with 'NA'.") - - # Re-identify numerical and categorical features after imputation - # This is important in case dtypes changed or columns were entirely removed/added (not in this case) - final_numerical_features = X.select_dtypes(include=np.number).columns.tolist() - final_categorical_features = X.select_dtypes(include="object").columns.tolist() - - # Define the ColumnTransformer for scaling numerical features and encoding categorical features - # StandardScaler for numerical features - # OneHotEncoder for categorical features (handle_unknown='ignore' for robustness) - preprocessor = ColumnTransformer( - transformers=[ - ("num_scaler", StandardScaler(), final_numerical_features), - ( - "cat_encoder", - OneHotEncoder(handle_unknown="ignore", sparse_output=False), - final_categorical_features, - ), - ], - remainder="drop", # Drop any columns not explicitly transformed - ) - - # Fit and transform the features - X_transformed_array = preprocessor.fit_transform(X) - - # Get feature names after one-hot encoding - # This requires fitting the one-hot encoder and then getting names - # Extract the one-hot encoder from the column transformer - ohe = preprocessor.named_transformers_["cat_encoder"] - feature_names_ohe = ohe.get_feature_names_out(final_categorical_features) - - # Combine all feature names - transformed_feature_names = final_numerical_features + list(feature_names_ohe) - - # Create a new DataFrame from the transformed array - X_transformed = pd.DataFrame(X_transformed_array, columns=transformed_feature_names, index=X.index) - print("Features scaled and encoded.") - - # Recombine with target variable if it was present - if y is not None: - transformed_df = pd.concat([X_transformed, y], axis=1) - print("Transformed features recombined with transformed target variable.") - else: - transformed_df = X_transformed - print("Transformed features returned without target variable.") - - return transformed_df diff --git a/feature_transformer_code.py b/feature_transformer_code.py deleted file mode 100644 index 00f7c03d..00000000 --- a/feature_transformer_code.py +++ /dev/null @@ -1,104 +0,0 @@ -import pandas as pd -import numpy as np -from sklearn.preprocessing import StandardScaler, OneHotEncoder -from sklearn.compose import ColumnTransformer -from plexe.core.interfaces.feature_transformer import FeatureTransformer - - -class FeatureTransformerImplementation(FeatureTransformer): - - def transform(self, inputs: pd.DataFrame) -> pd.DataFrame: - df = inputs.copy() - - target_variable = "SalePrice" - - # 1. Target Variable Transformation - if target_variable in df.columns: - df[target_variable] = np.log1p(df[target_variable]) - print(f"Applied log1p transformation to target variable '{target_variable}'.") - else: - print(f"Target variable '{target_variable}' not found in DataFrame. Skipping transformation.") - - # Separate features and target for transformation (if target is present) - if target_variable in df.columns: - X = df.drop(columns=[target_variable]) - y = df[target_variable] - else: - X = df - y = None # No target present - - # Identify numerical and categorical features based on dtypes - - # Define features for specific missing value imputation based on EDA - numerical_features_with_nan_specific = ["LotFrontage", "MasVnrArea", "GarageYrBlt"] - categorical_features_with_nan_specific = [ - "BsmtQual", - "BsmtCond", - "BsmtExposure", - "BsmtFinType1", - "BsmtFinType2", - "FireplaceQu", - "GarageType", - "GarageFinish", - "GarageQual", - "GarageCond", - ] - - # Step 1: Impute numerical missing values using median - for col in numerical_features_with_nan_specific: - if col in X.columns: - median_val = X[col].median() - X[col] = X[col].fillna(median_val) - print(f"Imputed missing values in numerical feature '{col}' with median: {median_val}.") - - # Step 2: Impute categorical missing values using 'NA' - for col in categorical_features_with_nan_specific: - if col in X.columns: - X[col] = X[col].fillna("NA") - print(f"Imputed missing values in categorical feature '{col}' with 'NA'.") - - # Re-identify numerical and categorical features after imputation - # This is important in case dtypes changed or columns were entirely removed/added (not in this case) - final_numerical_features = X.select_dtypes(include=np.number).columns.tolist() - final_categorical_features = X.select_dtypes(include="object").columns.tolist() - - # Define the ColumnTransformer for scaling numerical features and encoding categorical features - # StandardScaler for numerical features - # OneHotEncoder for categorical features (handle_unknown='ignore' for robustness) - preprocessor = ColumnTransformer( - transformers=[ - ("num_scaler", StandardScaler(), final_numerical_features), - ( - "cat_encoder", - OneHotEncoder(handle_unknown="ignore", sparse_output=False), - final_categorical_features, - ), - ], - remainder="drop", # Drop any columns not explicitly transformed - ) - - # Fit and transform the features - X_transformed_array = preprocessor.fit_transform(X) - - # Get feature names after one-hot encoding - # This requires fitting the one-hot encoder and then getting names - # Extract the one-hot encoder from the column transformer - ohe = preprocessor.named_transformers_["cat_encoder"] - feature_names_ohe = ohe.get_feature_names_out(final_categorical_features) - - # Combine all feature names - transformed_feature_names = final_numerical_features + list(feature_names_ohe) - - # Create a new DataFrame from the transformed array - X_transformed = pd.DataFrame(X_transformed_array, columns=transformed_feature_names, index=X.index) - print("Features scaled and encoded.") - - # Recombine with target variable if it was present - if y is not None: - transformed_df = pd.concat([X_transformed, y], axis=1) - print("Transformed features recombined with transformed target variable.") - else: - transformed_df = X_transformed - print("Transformed features returned without target variable.") - - return transformed_df diff --git a/mcp_config.json b/mcp_config.json new file mode 100644 index 00000000..99de27ee --- /dev/null +++ b/mcp_config.json @@ -0,0 +1,41 @@ +{ + "mcpServers": { + "hpo-search": { + "command": "python", + "args": [ + "plexe/langgraph/mcp_servers/hpo_server.py" + ] + }, + "google-scholar": { + "command": "python", + "args": [ + "plexe/langgraph/mcp_servers/scholar_server.py" + ] + }, + "kaggle": { + "command": "python", + "args": [ + "plexe/langgraph/mcp_servers/kaggle_server.py" + ], + "env": { + "KAGGLE_USERNAME": "${KAGGLE_USERNAME}", + "KAGGLE_KEY": "${KAGGLE_KEY}" + } + }, + "semantic-scholar": { + "command": "python", + "args": [ + "plexe/langgraph/mcp_servers/semantic_scholar_server.py" + ], + "env": { + "SEMANTIC_SCHOLAR_API_KEY": "${SEMANTIC_SCHOLAR_API_KEY}" + } + }, + "arxiv": { + "command": "python", + "args": [ + "plexe/langgraph/mcp_servers/arxiv_server.py" + ] + } + } +} \ No newline at end of file diff --git a/paper/AutoML_Agent.pdf b/paper/AutoML_Agent.pdf new file mode 100644 index 0000000000000000000000000000000000000000..cab7769c7a69c26d785522f0c3bd81c705fb9b5a GIT binary patch literal 1841386 zcmc$H1z40#_dd2_pdtn$tSE>I%XT23bO?w7qJol3ND52aEp}qPc8gfps92a_i;4jz zHnzSPzcbHs7M55)R(Sva>-(-(wr1|<%$alUGjryQo~yO35u3?Z)jR%m-7i%(gT;vQ zAE|0;$}o18Nc{r+q<#!8yg7(r?BW+8iDmHU7XzXtkrn~c(5OfTpMJ;HFIeIn6)0gC zd&Ejyq9WlB@>VQEK!5I@6b)}#L4)B@!3=YARY_zZ>52m%%eu6PlZHgaFbrJbTQPnN z_n6QaKWQI^XH;ZTRAey2Q3C(%!*Giuf5$QG6Z|5BdqSHr5LDeG{Yo0>UIxhQA~@G}27>-I3$E zjL<+cT~EF<%Q@Og5)x{k93yc{c5x3#4hs+m>h?8PHBB^0jEIf^jbS+C={fUYY3b}MVbS`r%&6BvM591SkRJ@Nu6gZ; z-PD+L6dr0$|3UR=EJKWM$~_tlNA3+qm1m`95h$6`PwOTbC3{-)3g)34BVw&!EvkH4 z!FZH^N zq?%jSO5;_gk2J#ndbmOZVG4!@g_7}-c@o7&uSTMcjq@KV36Lr;Tlwh_5X*G3D;Et; z19;cMp}KdioT_`**`oa2ijx5`)?B)OqpUKsZ|x_QnCXJc;~TLAMl7*Ai)F%NnQ%Ew 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a/tests/integration/README.md +++ /dev/null @@ -1,65 +0,0 @@ -# Plexe Integration Tests - - -## 1. Overview -This directory contains integration tests validating the end-to-end functionality of Plexe across various ML tasks. - - -## 2. Test Suite -### 2.1 Classification -- **Binary Classification** (`test_binary_classification.py`): Heart disease prediction; tests model lifecycle. -- **Multiclass Classification** (`test_multiclass_classification.py`): Sentiment analysis; tests synthetic data generation. - -### 2.2 Regression & Forecasting -- **Regression** (`test_regression.py`): House price prediction; tests schema specification and inference. -- **Time Series Forecasting** (`test_time_series.py`): Sales prediction; tests multi-feature temporal forecasting. - -### 2.3 Other ML Tasks -- **Recommendation** (`test_recommendation.py`): Product recommendations; tests list-based output and cross-selling. -- **Customer Churn** (`test_customer_churn.py`): Churn prediction; tests probability outputs and schema validation. -- **Schema Validation** (`test_schema_validation.py`): Validates complex schemas using Pydantic. - - -## 3. Execution -### 3.1 Prerequisites -- Plexe installed with development dependencies. -- `OPENAI_API_KEY` set as an environment variable. - -### 3.2 Running Tests - -#### 3.2.1 Single Test -```bash -poetry run pytest tests/integration/test_.py -v -``` -Example: -```bash -poetry run pytest tests/integration/test_binary_classification.py -v -``` - -#### 3.2.2 All Tests -```bash -poetry run pytest tests/integration/ -v -``` - -#### 3.2.3 Filtering Tests -```bash -poetry run pytest -k -v -``` -Example: -```bash -poetry run pytest tests/integration/test_binary_classification.py::test_heart_disease_classification -v -``` - -### 3.3 Optimization Tips -- Run tests individually to reduce execution time. -- Set `max_iterations` to 2-3 and timeouts to ~10 minutes. -- Use small synthetic datasets (~30-60 samples). - - -## 4. Adding New Tests -- Scope tests to a single model type or feature. -- Ensure runtime-generated synthetic data. -- Validate model training, inference, saving/loading. -- Confirm schema compliance and expected outputs. -- Use `openai/gpt-4o` for all tests. - diff --git a/tests/integration/__init__.py b/tests/integration/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/tests/integration/test_binary_classification.py b/tests/integration/test_binary_classification.py deleted file mode 100644 index a0cfd216..00000000 --- a/tests/integration/test_binary_classification.py +++ /dev/null @@ -1,128 +0,0 @@ -"""Integration test for binary classification models using plexe. - -This test covers: -1. Creating a binary classification model for heart disease prediction -2. Building the model with synthetic data -3. Making predictions with the model -4. Saving and loading the model -""" - -import os -import pytest -from pathlib import Path -from pydantic import create_model -import plexe -from tests.utils.utils import generate_heart_data, verify_prediction, cleanup_files, verify_model_description - - -@pytest.fixture -def heart_data(): - """Generate synthetic heart disease data for testing.""" - return generate_heart_data(n_samples=30) - - -@pytest.fixture -def heart_input_schema(): - """Define the input schema for heart disease prediction.""" - return create_model( - "HeartDiseaseInput", - **{ - "age": int, - "gender": int, - "cp": int, - "trtbps": int, - "chol": int, - "fbs": int, - "restecg": int, - "thalachh": int, - "exng": int, - "oldpeak": float, - "slp": int, - "caa": int, - "thall": int, - }, - ) - - -@pytest.fixture -def heart_output_schema(): - """Define the output schema for heart disease prediction.""" - return create_model("HeartDiseaseOutput", **{"output": int}) - - -@pytest.fixture -def model_dir(tmpdir): - """Create and manage a temporary directory for model files.""" - model_path = Path(tmpdir) / "models" - model_path.mkdir(exist_ok=True) - return model_path - - -@pytest.fixture(autouse=True) -def run_around_tests(model_dir): - """Set up and tear down for each test.""" - cleanup_files(model_dir) - os.environ["MODEL_PATH"] = str(model_dir) - yield - # Teardown - cleanup_files(model_dir) - - -def test_heart_disease_classification(heart_data, heart_input_schema, heart_output_schema): - """Test binary classification for heart disease prediction.""" - # Create a model for heart disease prediction - model = plexe.Model( - intent="Predict whether a patient is likely to have heart disease based on their medical features", - input_schema=heart_input_schema, - output_schema=heart_output_schema, - ) - - # Build the model with minimal data and iterations for faster testing - model.build( - datasets=[heart_data], - provider="openai/gpt-4o", - max_iterations=3, # Minimum iterations for reliable model generation - timeout=300, # 5 minute timeout - run_timeout=150, - ) - - # Test a sample prediction - test_input = { - "age": 61, - "gender": 1, - "cp": 3, - "trtbps": 145, - "chol": 233, - "fbs": 1, - "restecg": 0, - "thalachh": 150, - "exng": 0, - "oldpeak": 2.3, - "slp": 0, - "caa": 0, - "thall": 1, - } - # Try prediction with a dictionary directly - prediction = model.predict(test_input) - - # Verify the prediction - verify_prediction(prediction, heart_output_schema) - assert prediction["output"] in [0, 1], "Binary classification output should be 0 or 1" - - # Verify model description - description = model.describe() - verify_model_description(description) - - # Test model saving - model_path = plexe.save_model(model, "heart_disease_model.tar.gz") - assert Path(model_path).exists(), f"Model file {model_path} not created" - - # Test model loading - loaded_model = plexe.load_model(model_path) - # Use dictionary for prediction with the loaded model - loaded_prediction = loaded_model.predict(test_input) - - # Verify the loaded model's prediction - verify_prediction(loaded_prediction, heart_output_schema) - assert loaded_prediction["output"] in [0, 1], "Binary classification output should be 0 or 1" - assert loaded_prediction == prediction, "Loaded model prediction should match original model prediction" diff --git a/tests/integration/test_customer_churn.py b/tests/integration/test_customer_churn.py deleted file mode 100644 index 39d03e5e..00000000 --- a/tests/integration/test_customer_churn.py +++ /dev/null @@ -1,155 +0,0 @@ -"""Integration test for customer churn prediction models using plexe. - -This test covers: -1. Creating a model for predicting customer churn -2. Building the model with synthetic data -3. Making predictions with the model -4. Validating predictions with probability output -5. Using schema inference -""" - -import os -from pathlib import Path - -import pytest -from pydantic import create_model, Field - -import plexe -from tests.utils.utils import generate_customer_churn_data, verify_prediction, cleanup_files, verify_model_description - - -@pytest.fixture -def churn_data(): - """Generate synthetic customer churn data for testing.""" - return generate_customer_churn_data(n_samples=30) - - -@pytest.fixture -def churn_input_schema(): - """Define the input schema for churn prediction with field validations.""" - return create_model( - "ChurnInput", - **{ - "tenure": (int, Field(ge=0, description="Number of months the customer has been with the company")), - "monthly_charges": (float, Field(ge=0, description="Monthly charges in dollars")), - "total_charges": (float, Field(ge=0, description="Total charges in dollars")), - "contract_type": (int, Field(ge=0, le=2, description="0=month-to-month, 1=one year, 2=two year")), - "payment_method": ( - int, - Field(ge=0, le=3, description="0=electronic check, 1=mailed check, 2=bank transfer, 3=credit card"), - ), - "tech_support": (int, Field(ge=0, le=1, description="0=no, 1=yes")), - "online_backup": (int, Field(ge=0, le=1, description="0=no, 1=yes")), - "online_security": (int, Field(ge=0, le=1, description="0=no, 1=yes")), - }, - ) - - -@pytest.fixture -def churn_output_schema(): - """Define the output schema for churn prediction with probability.""" - return create_model( - "ChurnOutput", - **{ - "churn_probability": (float, Field(ge=0, le=1, description="Probability of customer churning (0-1)")), - "churn": (int, Field(ge=0, le=1, description="Binary churn prediction (0=no, 1=yes)")), - }, - ) - - -@pytest.fixture -def model_dir(tmpdir): - """Create and manage a temporary directory for model files.""" - model_path = Path(tmpdir) / "models" - model_path.mkdir(exist_ok=True) - return model_path - - -@pytest.fixture(autouse=True) -def run_around_tests(model_dir): - """Set up and tear down for each test.""" - cleanup_files(model_dir) - os.environ["MODEL_PATH"] = str(model_dir) - yield - # Teardown - cleanup_files(model_dir) - - -def test_customer_churn_prediction(churn_data, churn_input_schema, churn_output_schema): - """Test customer churn prediction with probability output.""" - # Create a model for churn prediction - model = plexe.Model( - intent=""" - Predict the probability that a customer will churn (leave the company) based on their - service usage and contract details. Return both the probability of churning (0-1) and - a binary prediction (0=will not churn, 1=will churn) using a threshold of 0.5. - """, - input_schema=churn_input_schema, - output_schema=churn_output_schema, - ) - - # Build the model with minimal iterations for faster testing - model.build( - datasets=[churn_data], - provider="openai/gpt-4o", - max_iterations=4, # Minimum iterations for reliable model generation - timeout=300, # 5 minute timeout - run_timeout=150, - ) - - # Test sample predictions - test_inputs = [ - # High risk customer (month-to-month contract, high monthly charge, low tenure) - { - "tenure": 3, - "monthly_charges": 120.00, - "total_charges": 360.00, - "contract_type": 0, - "payment_method": 0, - "tech_support": 0, - "online_backup": 0, - "online_security": 0, - }, - # Low risk customer (two-year contract, moderate monthly charge, high tenure) - { - "tenure": 60, - "monthly_charges": 90.00, - "total_charges": 5400.00, - "contract_type": 2, - "payment_method": 3, - "tech_support": 1, - "online_backup": 1, - "online_security": 1, - }, - ] - - for test_input in test_inputs: - prediction = model.predict(test_input) - - # Verify the prediction structure - verify_prediction(prediction, churn_output_schema) - - # Verify probability constraints - assert 0 <= prediction["churn_probability"] <= 1, "Churn probability should be between 0 and 1" - - # Verify binary prediction - assert prediction["churn"] in [0, 1], "Binary churn prediction should be 0 or 1" - - # Verify consistency between probability and binary prediction - if prediction["churn_probability"] > 0.5: - assert prediction["churn"] == 1, "Binary prediction should be 1 if probability > 0.5" - else: - assert prediction["churn"] == 0, "Binary prediction should be 0 if probability <= 0.5" - - # Verify model description - description = model.describe() - verify_model_description(description) - - # Test model saving and loading - model_path = plexe.save_model(model, "churn_model.tar.gz") - loaded_model = plexe.load_model(model_path) - - # Verify loaded model predictions - for test_input in test_inputs: - loaded_prediction = loaded_model.predict(test_input) - verify_prediction(loaded_prediction, churn_output_schema) diff --git a/tests/integration/test_model_description.py b/tests/integration/test_model_description.py deleted file mode 100644 index 42816f19..00000000 --- a/tests/integration/test_model_description.py +++ /dev/null @@ -1,215 +0,0 @@ -"""Integration test for model description functionality in plexe. - -This test covers: -1. Creating a simple model for iris flower classification -2. Building the model with synthetic data -3. Generating model descriptions in different formats (dict, json, text, markdown) -4. Verifying the content of the model descriptions -""" - -import json -import os -import pytest -from pathlib import Path -from pydantic import create_model - -import pandas as pd -import numpy as np -import plexe -from tests.utils.utils import cleanup_files - - -@pytest.fixture -def iris_data(): - """Generate synthetic iris data for testing.""" - # Create a simple dataset similar to the iris dataset - np.random.seed(42) - n_samples = 30 - - data = { - "sepal_length": np.random.uniform(4.5, 7.5, n_samples), - "sepal_width": np.random.uniform(2.0, 4.5, n_samples), - "petal_length": np.random.uniform(1.0, 6.5, n_samples), - "petal_width": np.random.uniform(0.1, 2.5, n_samples), - "species": ["setosa"] * n_samples, - } - - # Generate target based on petal length and width - # Simplistic rule: if petal_length > 3.0, it's likely virginica or versicolor - - for i in range(n_samples): - if data["petal_length"][i] < 2.0: - data["species"][i] = "setosa" - elif data["petal_length"][i] < 5.0: - data["species"][i] = "versicolor" - else: - data["species"][i] = "virginica" - - return pd.DataFrame(data) - - -@pytest.fixture -def iris_input_schema(): - """Define the input schema for iris classification.""" - return create_model( - "IrisInput", - **{ - "sepal_length": float, - "sepal_width": float, - "petal_length": float, - "petal_width": float, - }, - ) - - -@pytest.fixture -def iris_output_schema(): - """Define the output schema for iris classification.""" - return create_model("IrisOutput", **{"species": str}) - - -@pytest.fixture -def model_dir(tmpdir): - """Create and manage a temporary directory for model files.""" - model_path = Path(tmpdir) / "models" - model_path.mkdir(exist_ok=True) - return model_path - - -@pytest.fixture(autouse=True) -def run_around_tests(model_dir): - """Set up and tear down for each test.""" - cleanup_files(model_dir) - os.environ["MODEL_PATH"] = str(model_dir) - yield - # Teardown - cleanup_files(model_dir) - - -def verify_description_format(description, format_type): - """Verify that a description has the expected format and content.""" - if format_type == "dict": - assert isinstance(description, dict) - assert "id" in description - assert "intent" in description - assert "schemas" in description - assert "implementation" in description - assert "performance" in description - assert "code" in description - elif format_type == "json": - assert isinstance(description, str) - # Try to parse the JSON string - try: - json_dict = json.loads(description) - assert isinstance(json_dict, dict) - assert "id" in json_dict - assert "intent" in json_dict - except json.JSONDecodeError: - pytest.fail("Description is not valid JSON") - elif format_type == "text": - assert isinstance(description, str) - assert "Model:" in description - assert "Intent:" in description - assert "Input Schema:" in description - assert "Output Schema:" in description - elif format_type == "markdown": - assert isinstance(description, str) - assert "# Model:" in description - assert "**Intent:**" in description - assert "## Input Schema" in description - assert "## Output Schema" in description - - -def test_model_description(iris_data, iris_input_schema, iris_output_schema): - """Test model description generation in various formats and content verification.""" - - # Create a model for iris species classification - model = plexe.Model( - intent="Classify iris flowers into species based on their sepal and petal measurements", - input_schema=iris_input_schema, - output_schema=iris_output_schema, - ) - - # Build the model with minimal iterations for faster testing - model.build( - datasets=[iris_data], - provider="openai/gpt-4o", - max_iterations=2, # Minimum iterations for quick testing - timeout=180, # 3 minute timeout - run_timeout=150, - ) - - # Test that the model is in the ready state - assert model.state.value == "ready", "Model should be in ready state after building" - - # PART 1: Test description object and its format methods - - # Get the model description object - desc = model.describe() - - # Test the object has the expected attributes and methods - assert hasattr(desc, "id") - assert hasattr(desc, "intent") - assert hasattr(desc, "schemas") - assert hasattr(desc, "to_dict") - assert hasattr(desc, "to_json") - assert hasattr(desc, "as_text") - assert hasattr(desc, "as_markdown") - - # Test dictionary format - dict_desc = desc.to_dict() - verify_description_format(dict_desc, "dict") - - # Test JSON format - json_desc = desc.to_json() - verify_description_format(json_desc, "json") - - # Test text format - text_desc = desc.as_text() - verify_description_format(text_desc, "text") - - # Test markdown format - md_desc = desc.as_markdown() - verify_description_format(md_desc, "markdown") - - # Ensure output is always visible, even when tests pass - print("\n\n=== MODEL DESCRIPTION IN JSON FORMAT ===\n") - print(json_desc) - - print("\n\n=== MODEL DESCRIPTION IN TEXT FORMAT ===\n") - print(text_desc) - - print("\n\n=== MODEL DESCRIPTION IN MARKDOWN FORMAT ===\n") - print(md_desc) - - # PART 2: Verify description content details - - # Verify basic content - assert "id" in dict_desc - assert dict_desc["intent"] == "Classify iris flowers into species based on their sepal and petal measurements" - - # Verify schema information - assert "schemas" in dict_desc - assert "input" in dict_desc["schemas"] - assert "output" in dict_desc["schemas"] - - # Verify input schema has the expected fields - input_schema = dict_desc["schemas"]["input"] - for field in ["sepal_length", "sepal_width", "petal_length", "petal_width"]: - assert field in input_schema - - # Verify output schema has species field - output_schema = dict_desc["schemas"]["output"] - assert any(field.lower() == "species" for field in output_schema.keys()) - - # Verify implementation info - assert "implementation" in dict_desc - assert "artifacts" in dict_desc["implementation"] - - # Verify code sections - assert "code" in dict_desc - assert "prediction" in dict_desc["code"] - - # Verify performance metrics - assert "performance" in dict_desc - assert "metrics" in dict_desc["performance"] diff --git a/tests/integration/test_multiclass_classification.py b/tests/integration/test_multiclass_classification.py deleted file mode 100644 index 3f458f59..00000000 --- a/tests/integration/test_multiclass_classification.py +++ /dev/null @@ -1,92 +0,0 @@ -"""Integration test for multiclass classification models using plexe. - -This test covers: -1. Creating a multiclass classification model for sentiment analysis -2. Building the model with synthetic data -3. Making predictions with the model -4. Testing dataset generation capabilities -""" - -import os -import pytest -from pathlib import Path -from pydantic import create_model -import plexe -from tests.utils.utils import verify_prediction, cleanup_files, verify_model_description, generate_sentiment_data - - -@pytest.fixture -def sentiment_data(): - """Generate synthetic sentiment data for testing.""" - return generate_sentiment_data(n_samples=30) - - -@pytest.fixture -def sentiment_input_schema(): - """Define the input schema for sentiment analysis.""" - return create_model("SentimentInput", **{"text": str}) - - -@pytest.fixture -def sentiment_output_schema(): - """Define the output schema for sentiment analysis.""" - return create_model("SentimentOutput", **{"sentiment": str}) - - -@pytest.fixture -def model_dir(tmpdir): - """Create and manage a temporary directory for model files.""" - model_path = Path(tmpdir) / "models" - model_path.mkdir(exist_ok=True) - return model_path - - -@pytest.fixture(autouse=True) -def run_around_tests(model_dir): - """Set up and tear down for each test.""" - cleanup_files(model_dir) - os.environ["MODEL_PATH"] = str(model_dir) - yield - # Teardown - cleanup_files(model_dir) - - -def test_multiclass_classification(sentiment_data, sentiment_input_schema, sentiment_output_schema): - """Test multiclass classification for sentiment analysis.""" - # Create a model for sentiment analysis - model = plexe.Model( - intent="Classify text sentiment into positive, negative, or neutral categories", - input_schema=sentiment_input_schema, - output_schema=sentiment_output_schema, - ) - - # Build the model with minimal data and iterations for faster testing - model.build( - datasets=[sentiment_data], - provider="openai/gpt-4o", - max_iterations=3, # Minimum iterations for reliable model generation - timeout=300, # 5 minute timeout - run_timeout=150, - ) - - # Test sample predictions - test_inputs = [ - {"text": "This product exceeded my expectations! The quality is amazing."}, - {"text": "Very disappointed with this purchase. Would not recommend."}, - {"text": "The product is okay, nothing special but works as expected."}, - ] - - for test_input in test_inputs: - prediction = model.predict(test_input) - - # Verify the prediction - verify_prediction(prediction, sentiment_output_schema) - assert prediction["sentiment"] in [ - "positive", - "negative", - "neutral", - ], f"Prediction should be one of ['positive', 'negative', 'neutral'], got {prediction['sentiment']}" - - # Verify model description - description = model.describe() - verify_model_description(description) diff --git a/tests/integration/test_ray_integration.py b/tests/integration/test_ray_integration.py deleted file mode 100644 index d8f98336..00000000 --- a/tests/integration/test_ray_integration.py +++ /dev/null @@ -1,77 +0,0 @@ -""" -Integration test for Ray-based distributed training. -""" - -import pytest -import pandas as pd -import numpy as np -from plexe.models import Model - - -@pytest.fixture -def sample_dataset(): - """Create a simple synthetic dataset for testing.""" - # Create a sample regression dataset - np.random.seed(42) - n_samples = 1000 - X = np.random.randn(n_samples, 5) - y = 2 + 3 * X[:, 0] + 0.5 * X[:, 1] - X[:, 2] + np.random.randn(n_samples) * 0.1 - - # Create a DataFrame with feature and target columns - df = pd.DataFrame(data=np.column_stack([X, y]), columns=[f"feature_{i}" for i in range(5)] + ["target"]) - return df - - -def test_model_with_ray(sample_dataset): - """Test building a model with Ray-based distributed execution.""" - # Skip this test if no API key is available - import os - - if not os.environ.get("OPENAI_API_KEY"): - pytest.skip("OpenAI API key not available") - - # Ray is already initialized in the RayExecutor when needed - - # Create a model with distributed=True - model = Model(intent="Predict the target variable given 5 numerical features", distributed=True) - - # Set a short timeout for testing - model.build( - datasets=[sample_dataset], - provider="gemini/gemini-2.5-flash", - timeout=300, # 5 minutes max - run_timeout=60, # 1 minute per run - ) - - # Test a prediction - input_data = {f"feature_{i}": 0.5 for i in range(5)} - prediction = model.predict(input_data) - - # Verify that prediction has expected structure - assert prediction is not None - assert "target" in prediction - - # Verify that Ray was used in training - assert model.distributed - - # Verify model built successfully - assert model.metric is not None - - # Get executor classes - from plexe.tools.execution import _get_executor_class - from plexe.internal.models.execution.ray_executor import RayExecutor - - # Verify model has the distributed flag set - assert model.distributed, "Model should have distributed=True" - - # Verify the factory would select RayExecutor when distributed=True - executor_class = _get_executor_class(distributed=True) - assert executor_class == RayExecutor, "Factory should return RayExecutor when distributed=True" - - # The logs show Ray is being used, but the flag might not be set when checked - # Let's just print the status for diagnostics but not fail the test on it - print(f"Ray executor was used: {RayExecutor._ray_was_used}") - - # Instead, verify our factory returns the right executor when asked - # The logs confirm Ray is actually used - assert _get_executor_class(distributed=True) == RayExecutor diff --git a/tests/integration/test_recommendation.py b/tests/integration/test_recommendation.py deleted file mode 100644 index 6400695f..00000000 --- a/tests/integration/test_recommendation.py +++ /dev/null @@ -1,115 +0,0 @@ -"""Integration test for recommendation models using plexe. - -This test covers: -1. Creating a recommendation model for product cross-selling -2. Building the model with synthetic data -3. Making predictions with the model -4. Validating the returned recommendations -""" - -import os -import pytest -from pathlib import Path -from pydantic import create_model -import plexe -from tests.utils.utils import ( - generate_product_recommendation_data, - verify_prediction, - cleanup_files, - verify_model_description, -) - - -@pytest.fixture -def product_data(): - """Generate synthetic product recommendation data for testing.""" - return generate_product_recommendation_data(n_samples=60) # Gives ~20 orders with ~3 items each - - -@pytest.fixture -def recommendation_input_schema(): - """Define the input schema for product recommendation.""" - return create_model("ProductInput", **{"style": str}) - - -@pytest.fixture -def recommendation_output_schema(): - """Define the output schema for product recommendation.""" - return create_model("ProductOutput", **{"recommended_styles": list}) - - -@pytest.fixture -def model_dir(tmpdir): - """Create and manage a temporary directory for model files.""" - model_path = Path(tmpdir) / "models" - model_path.mkdir(exist_ok=True) - return model_path - - -@pytest.fixture(autouse=True) -def run_around_tests(model_dir): - """Set up and tear down for each test.""" - cleanup_files(model_dir) - os.environ["MODEL_PATH"] = str(model_dir) - yield - # Teardown - cleanup_files(model_dir) - - -def test_product_recommendation(product_data, recommendation_input_schema, recommendation_output_schema): - """Test recommendation model for suggesting related products.""" - # Create a model for product recommendations - model = plexe.Model( - intent=""" - Given a product style code, recommend up to 3 other product styles that are frequently - purchased together with it based on transaction history. Use the order_id to identify - products purchased in the same transaction. - """, - input_schema=recommendation_input_schema, - output_schema=recommendation_output_schema, - ) - - # Build the model with minimal iterations for faster testing - model.build( - datasets=[product_data], - provider="openai/gpt-4o", - max_iterations=3, # Minimum iterations for reliable model generation - timeout=300, # 5 minute timeout - run_timeout=150, - ) - - # Get a sample style to test with (first style in the dataset) - test_style = product_data["style"].iloc[0] - - # Test a sample prediction - test_input = {"style": test_style} - prediction = model.predict(test_input) - - # Verify the prediction - verify_prediction(prediction, recommendation_output_schema) - - # Check that the recommendations are a list - assert isinstance(prediction["recommended_styles"], list), "Recommendations should be a list" - - # Check that we have at most 3 recommendations - assert len(prediction["recommended_styles"]) <= 3, "Should have at most 3 recommendations" - - # Check that the recommended items are not the input item - for style in prediction["recommended_styles"]: - assert style != test_style, "Recommendations should not include the input item" - - # Verify model description - description = model.describe() - verify_model_description(description) - - # Test model saving - model_path = plexe.save_model(model, "recommendation_model.tar.gz") - assert Path(model_path).exists(), f"Model file {model_path} not created" - - # Test model loading - loaded_model = plexe.load_model(model_path) - loaded_prediction = loaded_model.predict(test_input) - - # Verify the loaded model's prediction - verify_prediction(loaded_prediction, recommendation_output_schema) - assert isinstance(loaded_prediction["recommended_styles"], list), "Recommendations should be a list" diff --git a/tests/integration/test_regression.py b/tests/integration/test_regression.py deleted file mode 100644 index 6d7b6c9a..00000000 --- a/tests/integration/test_regression.py +++ /dev/null @@ -1,115 +0,0 @@ -"""Integration test for regression models using plexe. - -This test covers: -1. Creating a regression model for house price prediction -2. Building the model with synthetic data -3. Making predictions with the model -4. Testing schema inference -""" - -import os -import pytest -from pathlib import Path -from pydantic import create_model -import plexe -from tests.utils.utils import generate_house_prices_data, verify_prediction, cleanup_files, verify_model_description - - -@pytest.fixture -def house_data(): - """Generate synthetic house price data for testing.""" - return generate_house_prices_data(n_samples=30) - - -@pytest.fixture -def house_input_schema(): - """Define the input schema for house price prediction.""" - return create_model( - "HousePriceInput", - **{ - "area": int, - "bedrooms": int, - "bathrooms": int, - "stories": int, - "garage": int, - "garden": int, - "fenced": int, - "age": int, - }, - ) - - -@pytest.fixture -def house_output_schema(): - """Define the output schema for house price prediction.""" - return create_model("HousePriceOutput", **{"price": float}) - - -@pytest.fixture -def model_dir(tmpdir): - """Create and manage a temporary directory for model files.""" - model_path = Path(tmpdir) / "models" - model_path.mkdir(exist_ok=True) - return model_path - - -@pytest.fixture(autouse=True) -def run_around_tests(model_dir): - """Set up and tear down for each test.""" - cleanup_files(model_dir) - os.environ["MODEL_PATH"] = str(model_dir) - yield - # Teardown - cleanup_files(model_dir) - - -def test_house_price_regression(house_data, house_input_schema, house_output_schema): - """Test regression for house price prediction.""" - # Create a model for house price prediction - model = plexe.Model( - intent="Predict the price of a house based on its features", - input_schema=house_input_schema, - output_schema=house_output_schema, - ) - - # Build the model with minimal data and iterations for faster testing - model.build( - datasets=[house_data], - provider="openai/gpt-4o", - max_iterations=3, # Minimum iterations for reliable model generation - timeout=300, # 5 minute timeout - run_timeout=150, - ) - - # Test a sample prediction - test_input = { - "area": 2500, - "bedrooms": 4, - "bathrooms": 2, - "stories": 2, - "garage": 1, - "garden": 1, - "fenced": 1, - "age": 5, - } - prediction = model.predict(test_input) - - # Verify the prediction - verify_prediction(prediction, house_output_schema) - assert isinstance(prediction["price"], (int, float)), "House price should be numeric" - assert prediction["price"] > 0, "House price should be positive" - - # Verify model description - description = model.describe() - verify_model_description(description) - - # Test model saving and loading - model_path = plexe.save_model(model, "house_price_model.tar.gz") - loaded_model = plexe.load_model(model_path) - loaded_prediction = loaded_model.predict(test_input) - - # Verify the loaded model's prediction - verify_prediction(loaded_prediction, house_output_schema) - assert isinstance(loaded_prediction["price"], (int, float)), "House price should be numeric" - assert loaded_prediction["price"] > 0, "House price should be positive" - assert loaded_prediction == prediction, "Loaded model prediction should match original model prediction" diff --git a/tests/integration/test_schema_validation.py b/tests/integration/test_schema_validation.py deleted file mode 100644 index 99e49107..00000000 --- a/tests/integration/test_schema_validation.py +++ /dev/null @@ -1,174 +0,0 @@ -"""Integration test for schema validation in plexe. - -This test covers: -1. Creating models with fields that have validation requirements -2. Testing that invalid inputs fail properly -3. Testing that valid inputs pass properly -""" - -import os -import pytest -from pathlib import Path -from pydantic import create_model, Field -import plexe -from tests.utils.utils import generate_house_prices_data, verify_prediction, cleanup_files - - -@pytest.fixture -def house_data(): - """Generate synthetic house price data for testing.""" - return generate_house_prices_data(n_samples=30) - - -@pytest.fixture -def house_data_copy(house_data): - """Create a copy of the house data to avoid mutation issues.""" - return house_data.copy() - - -@pytest.fixture -def validated_input_schema(): - """Define the input schema for house price prediction with validation.""" - return create_model( - "ValidatedHouseInput", - **{ - "area": (int, Field(description="Square feet (500-10000)")), - "bedrooms": (int, Field(description="Number of bedrooms (1-10)")), - "bathrooms": (int, Field(description="Number of bathrooms (1-7)")), - "stories": (int, Field(description="Number of stories (1-4)")), - "garage": (int, Field(description="Garage capacity in cars (0-3)")), - "garden": (int, Field(description="Has garden (0=no, 1=yes)")), - "fenced": (int, Field(description="Has fenced yard (0=no, 1=yes)")), - "age": (int, Field(description="Age of house in years (0-100)")), - }, - ) - - -@pytest.fixture -def validated_output_schema(): - """Define the output schema for house price prediction with validation.""" - return create_model( - "ValidatedHouseOutput", - **{"price": (float, Field(ge=50, le=5000, description="House price in thousands of dollars (50-5000)"))}, - ) - - -@pytest.fixture -def model_dir(tmpdir): - """Create and manage a temporary directory for model files.""" - model_path = Path(tmpdir) / "models" - model_path.mkdir(exist_ok=True) - return model_path - - -@pytest.fixture(autouse=True) -def run_around_tests(model_dir): - """Set up and tear down for each test.""" - cleanup_files(model_dir) - os.environ["MODEL_PATH"] = str(model_dir) - yield - # Teardown - cleanup_files(model_dir) - - -def test_input_validation(house_data_copy, validated_input_schema, validated_output_schema): - """Test validation of input schema.""" - # Create a model with validated input schema - model = plexe.Model( - intent="Predict the price of a house based on its features, with input validation", - input_schema=validated_input_schema, - output_schema=validated_output_schema, - ) - - # Build the model - model.build( - datasets=[house_data_copy], - provider="openai/gpt-4o", - max_iterations=3, # Minimum iterations for reliable model generation - timeout=300, # 5 minute timeout - run_timeout=150, - ) - - # Valid input should work - valid_input = { - "area": 2500, - "bedrooms": 4, - "bathrooms": 2, - "stories": 2, - "garage": 1, - "garden": 1, - "fenced": 1, - "age": 5, - } - prediction = model.predict(valid_input) - verify_prediction(prediction, validated_output_schema) - - # Invalid inputs should raise validation errors - invalid_inputs = [ - { - "area": 300, - "stories": 2, - "garage": 1, - "garden": 1, - "fenced": 1, - "age": 5, - }, # Missing features - { - "area": "not-a-number", - "bedrooms": None, - "bathrooms": "two", - "stories": False, - "garage": 1, - "garden": 1, - "fenced": 1, - "age": 5, - }, # Invalid types - ] - - for invalid_input in invalid_inputs: - with pytest.raises(Exception): - # This should raise a validation error when the model validates the input - # against the schema before prediction - model.predict(invalid_input, validate_input=True) - - -def test_output_validation(house_data_copy, validated_input_schema): - """Test validation of output schema.""" - # Create an output schema with strict range validation - strict_output_schema = create_model( - "StrictHouseOutput", - **{"price": (float, Field(ge=500, le=600, description="House price in thousands of dollars (500-600)"))}, - ) - - # Create a model with standard input but strictly bounded output - model = plexe.Model( - intent="Predict the price of a house based on its features, ensuring predictions are between 500-600k", - input_schema=validated_input_schema, - output_schema=strict_output_schema, - ) - - # Build the model - model.build( - datasets=[house_data_copy], - provider="openai/gpt-4o", - max_iterations=3, # Minimum iterations for reliable model generation - timeout=300, - run_timeout=150, - ) - - # Test a sample prediction - test_input = { - "area": 2500, - "bedrooms": 4, - "bathrooms": 2, - "stories": 2, - "garage": 1, - "garden": 1, - "fenced": 1, - "age": 5, - } - - prediction = model.predict(test_input) - - # Verify the prediction meets the strict output schema - verify_prediction(prediction, strict_output_schema) diff --git a/tests/integration/test_time_series.py b/tests/integration/test_time_series.py deleted file mode 100644 index b793d381..00000000 --- a/tests/integration/test_time_series.py +++ /dev/null @@ -1,120 +0,0 @@ -"""Integration test for time series forecasting models using plexe. - -This test covers: -1. Creating a time series forecasting model for sales prediction -2. Building the model with synthetic time series data -3. Making predictions with the model for future time periods -""" - -import os -import pytest -from pathlib import Path -from pydantic import create_model -import plexe -from tests.utils.utils import generate_time_series_data, verify_prediction, cleanup_files, verify_model_description - - -@pytest.fixture -def sales_data(): - """Generate synthetic time series data for testing.""" - return generate_time_series_data(n_samples=60) - - -@pytest.fixture -def sales_data_copy(sales_data): - """Create a copy of the sales data to avoid mutation issues.""" - return sales_data.copy() - - -@pytest.fixture -def sales_input_schema(): - """Define the input schema for sales forecasting.""" - return create_model( - "SalesInput", - **{ - "date": str, - "promo": int, - "holiday": int, - "day_of_week": int, - }, - ) - - -@pytest.fixture -def sales_output_schema(): - """Define the output schema for sales forecasting.""" - return create_model("SalesOutput", **{"sales": float}) - - -@pytest.fixture -def model_dir(tmpdir): - """Create and manage a temporary directory for model files.""" - model_path = Path(tmpdir) / "models" - model_path.mkdir(exist_ok=True) - return model_path - - -@pytest.fixture(autouse=True) -def run_around_tests(model_dir): - """Set up and tear down for each test.""" - cleanup_files(model_dir) - os.environ["MODEL_PATH"] = str(model_dir) - yield - # Teardown - cleanup_files(model_dir) - - -def test_time_series_forecasting(sales_data_copy, sales_input_schema, sales_output_schema): - """Test time series forecasting for sales prediction.""" - # Ensure date is in string format for the model input - sales_data_copy["date"] = sales_data_copy["date"].dt.strftime("%Y-%m-%d") - - # Create a model for sales forecasting - model = plexe.Model( - intent="Predict daily sales based on the date, promotions, holidays, and day of the week", - input_schema=sales_input_schema, - output_schema=sales_output_schema, - ) - - # Build the model - model.build( - datasets=[sales_data_copy], - provider="openai/gpt-4o", - max_iterations=4, # Minimum iterations for reliable model generation - timeout=400, # 5 minute timeout - run_timeout=150, - ) - - # Test prediction for a future date - future_date = "2023-03-01" # A date after the training data - test_input = { - "date": future_date, - "promo": 1, - "holiday": 0, - "day_of_week": 2, # Wednesday - } - prediction = model.predict(test_input) - - # Verify the prediction - verify_prediction(prediction, sales_output_schema) - assert isinstance(prediction["sales"], (int, float)), "Sales should be numeric" - assert prediction["sales"] > 0, "Sales should be positive" - - # Test another date with different features - future_date_2 = "2023-03-04" # Saturday - test_input_2 = { - "date": future_date_2, - "promo": 0, - "holiday": 1, - "day_of_week": 5, # Saturday - } - prediction_2 = model.predict(test_input_2) - - # Verify the prediction - verify_prediction(prediction_2, sales_output_schema) - assert isinstance(prediction_2["sales"], (int, float)), "Sales should be numeric" - assert prediction_2["sales"] > 0, "Sales should be positive" - - # Verify model description - description = model.describe() - verify_model_description(description) diff --git a/tests/unit/__init__.py b/tests/unit/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/tests/unit/internal/__init__.py b/tests/unit/internal/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/tests/unit/internal/common/datasets/__init__.py b/tests/unit/internal/common/datasets/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/tests/unit/internal/common/datasets/test_adapter.py b/tests/unit/internal/common/datasets/test_adapter.py deleted file mode 100644 index 777d58ec..00000000 --- a/tests/unit/internal/common/datasets/test_adapter.py +++ /dev/null @@ -1,118 +0,0 @@ -""" -Tests for the DatasetAdapter class. - -This module verifies: -1. Conversion of different data formats to appropriate dataset types -2. Auto-detection of dataset types -3. Feature extraction functionality -4. Error handling for unsupported dataset types -""" - -import pytest -import pandas as pd - -from plexe.internal.common.datasets.adapter import DatasetAdapter -from plexe.internal.common.datasets.interface import Dataset, DatasetStructure -from plexe.internal.common.datasets.tabular import TabularDataset - - -class MockDataset(Dataset): - """Mock dataset implementation for testing.""" - - def __init__(self, features=None): - self._features = features or ["feature1", "feature2"] - - def split(self, train_ratio=0.7, val_ratio=0.15, test_ratio=0.15, stratify_column=None, random_state=None): - return self, self, self - - def sample(self, n=None, frac=None, replace=False, random_state=None): - return self - - def to_bytes(self): - return b"mock_dataset" - - @classmethod - def from_bytes(cls, data): - return cls() - - @property - def structure(self): - return DatasetStructure(modality="other", features=self._features, details={"mock": True}) - - def __len__(self): - return 10 - - def __getitem__(self, idx): - return {"item": idx} - - -def test_adapter_coerce_pandas(): - """Test that DatasetAdapter.coerce handles pandas DataFrames.""" - # Create test data - df = pd.DataFrame({"feature1": [1, 2, 3], "feature2": ["a", "b", "c"], "target": [0, 1, 0]}) - - # Coerce to dataset - result = DatasetAdapter.coerce(df) - - # Check that the result is a TabularDataset - assert isinstance(result, TabularDataset) - assert len(result) == 3 - - # Check that the data was preserved - pd.testing.assert_frame_equal(result.to_pandas(), df) - - -def test_adapter_coerce_dataset(): - """Test that DatasetAdapter.coerce passes through Dataset instances.""" - # Create test data - df = pd.DataFrame({"feature1": [1, 2, 3], "feature2": ["a", "b", "c"], "target": [0, 1, 0]}) - - # Create TabularDataset - dataset = TabularDataset(df) - - # Coerce the dataset - result = DatasetAdapter.coerce(dataset) - - # Check that the result is the same TabularDataset - assert result is dataset - - -def test_adapter_auto_detect(): - """Test the auto_detect functionality.""" - # Test with pandas DataFrame - df = pd.DataFrame({"a": [1, 2, 3]}) - assert DatasetAdapter.auto_detect(df) == "tabular" - - # Test with unsupported type - assert DatasetAdapter.auto_detect("not a dataset") is None - - -def test_adapter_coerce_unsupported(): - """Test error handling for unsupported dataset types.""" - # Try to coerce an unsupported type - with pytest.raises(ValueError): - DatasetAdapter.coerce("not a dataset") - - -def test_adapter_features(): - """Test the features extraction functionality.""" - # Create test datasets - df1 = pd.DataFrame({"feature1": [1, 2, 3], "feature2": ["a", "b", "c"]}) - - df2 = pd.DataFrame({"feature3": [4, 5, 6], "feature4": ["d", "e", "f"]}) - - dataset1 = TabularDataset(df1) - dataset2 = TabularDataset(df2) - - # Create dataset dictionary - datasets = {"dataset1": dataset1, "dataset2": dataset2} - - # Extract features - features = DatasetAdapter.features(datasets) - - # Check that features were correctly extracted - assert len(features) == 4 - assert "dataset1.feature1" in features - assert "dataset1.feature2" in features - assert "dataset2.feature3" in features - assert "dataset2.feature4" in features diff --git a/tests/unit/internal/common/datasets/test_interface.py b/tests/unit/internal/common/datasets/test_interface.py deleted file mode 100644 index 9e6d239f..00000000 --- a/tests/unit/internal/common/datasets/test_interface.py +++ /dev/null @@ -1,136 +0,0 @@ -""" -Tests for the dataset interface. - -This module verifies: -1. Creation and usage of DatasetStructure -2. Basic attributes and operations of DatasetStructure -3. Abstract methods in Dataset must be implemented by subclasses -4. Error handling when trying to instantiate Dataset directly -""" - -import pytest -from plexe.internal.common.datasets.interface import Dataset, DatasetStructure - - -def test_dataset_structure_creation(): - """Test creation of a DatasetStructure with valid parameters.""" - # Create a simple structure - structure = DatasetStructure( - modality="table", features=["feature1", "feature2", "target"], details={"num_rows": 10, "num_columns": 3} - ) - - # Check attributes - assert structure.modality == "table" - assert structure.features == ["feature1", "feature2", "target"] - assert structure.details["num_rows"] == 10 - assert structure.details["num_columns"] == 3 - - -def test_dataset_structure_tensor_modality(): - """Test creation of a DatasetStructure with tensor modality.""" - # Create a tensor structure - structure = DatasetStructure( - modality="tensor", features=["pixel_values"], details={"shape": [32, 32, 3], "dtype": "float32"} - ) - - # Check attributes - assert structure.modality == "tensor" - assert structure.features == ["pixel_values"] - assert structure.details["shape"] == [32, 32, 3] - assert structure.details["dtype"] == "float32" - - -def test_dataset_structure_other_modality(): - """Test creation of a DatasetStructure with 'other' modality.""" - # Create a structure with 'other' modality - structure = DatasetStructure( - modality="other", features=["custom_data"], details={"type": "custom", "format": "specialized"} - ) - - # Check attributes - assert structure.modality == "other" - assert structure.features == ["custom_data"] - assert structure.details["type"] == "custom" - assert structure.details["format"] == "specialized" - - -# Note: Python doesn't enforce Literal type annotations at runtime, -# so we're not testing invalid modality values since they would pass -# in a regular Python environment. In a strictly typed environment -# or with runtime type checking, this would raise an error. - - -class MinimalDataset(Dataset): - """Minimal implementation of Dataset for testing.""" - - def split(self, train_ratio=0.7, val_ratio=0.15, test_ratio=0.15, stratify_column=None, random_state=None): - return self, self, self - - def sample(self, n=None, frac=None, replace=False, random_state=None): - return self - - def to_bytes(self): - return b"minimal_dataset" - - @classmethod - def from_bytes(cls, data): - return cls() - - @property - def structure(self): - return DatasetStructure(modality="other", features=["dummy"], details={}) - - def __len__(self): - return 0 - - def __getitem__(self, index): - return None - - -class IncompleteDataset(Dataset): - """Dataset implementation missing required methods.""" - - def split(self, train_ratio=0.7, val_ratio=0.15, test_ratio=0.15, stratify_column=None, random_state=None): - return self, self, self - - # Missing other required methods - - -def test_dataset_instantiation(): - """Test that Dataset can't be instantiated directly.""" - with pytest.raises(TypeError): - Dataset() # Should raise TypeError: Can't instantiate abstract class - - -def test_minimal_dataset(): - """Test that a minimal implementation of Dataset can be instantiated.""" - dataset = MinimalDataset() - assert isinstance(dataset, Dataset) - - # Test basic functionality - train, val, test = dataset.split() - assert isinstance(train, MinimalDataset) - assert isinstance(val, MinimalDataset) - assert isinstance(test, MinimalDataset) - - sample = dataset.sample(n=5) - assert isinstance(sample, MinimalDataset) - - data_bytes = dataset.to_bytes() - assert data_bytes == b"minimal_dataset" - - restored = MinimalDataset.from_bytes(data_bytes) - assert isinstance(restored, MinimalDataset) - - assert len(dataset) == 0 - assert dataset[0] is None - - structure = dataset.structure - assert structure.modality == "other" - assert structure.features == ["dummy"] - - -def test_incomplete_dataset(): - """Test that a Dataset implementation missing required methods raises errors.""" - with pytest.raises(TypeError): - IncompleteDataset() # Should raise TypeError for missing abstract methods diff --git a/tests/unit/internal/common/datasets/test_tabular.py b/tests/unit/internal/common/datasets/test_tabular.py deleted file mode 100644 index cb19b567..00000000 --- a/tests/unit/internal/common/datasets/test_tabular.py +++ /dev/null @@ -1,338 +0,0 @@ -""" -Tests for the TabularDataset implementation. - -This module verifies: -1. Creation of TabularDatasets from pandas DataFrames -2. Dataset splitting into train/val/test sets -3. Dataset sampling functionality -4. Serialization and deserialization -5. Dataset structure metadata -6. Conversion to pandas and numpy formats -7. Basic operations like __len__ and __getitem__ -""" - -import pytest -import pandas as pd -import numpy as np - -from plexe.internal.common.datasets.tabular import TabularDataset -from plexe.internal.common.datasets.interface import DatasetStructure -from plexe.internal.common.utils.dataset_storage import write_dataset_to_file, read_dataset_from_file - - -def test_tabular_dataset_creation(): - """Test that TabularDataset can be created from pandas DataFrame.""" - # Create test data - df = pd.DataFrame({"feature1": [1, 2, 3, 4, 5], "feature2": ["a", "b", "c", "d", "e"], "target": [0, 1, 0, 1, 0]}) - - # Create TabularDataset - dataset = TabularDataset(df) - - # Check that the dataset was created correctly - assert len(dataset) == 5 - assert isinstance(dataset.to_pandas(), pd.DataFrame) - assert isinstance(dataset.to_numpy(), np.ndarray) - pd.testing.assert_frame_equal(dataset.to_pandas(), df) - - -def test_tabular_dataset_validation(): - """Test validation of input data types.""" - # Valid input - df = pd.DataFrame({"a": [1, 2, 3]}) - TabularDataset(df) # Should work - - # Invalid input - with pytest.raises(ValueError): - TabularDataset("not a dataframe") - - with pytest.raises(ValueError): - TabularDataset([1, 2, 3]) - - -def test_tabular_dataset_split_standard(): - """Test standard train/val/test split with default ratios.""" - # Create test data - df = pd.DataFrame( - {"feature1": range(100), "feature2": [f"val_{i}" for i in range(100)], "target": [i % 2 for i in range(100)]} - ) - - # Create TabularDataset - dataset = TabularDataset(df) - - # Split dataset with default ratios (0.7, 0.15, 0.15) - train, val, test = dataset.split() - - # Check that each split is a TabularDataset - assert isinstance(train, TabularDataset) - assert isinstance(val, TabularDataset) - assert isinstance(test, TabularDataset) - - # Check split sizes - assert len(train) == 70 - assert len(val) == 15 - assert len(test) == 15 - - # Check total size - assert len(train) + len(val) + len(test) == 100 - - -def test_tabular_dataset_split_custom_ratios(): - """Test train/val/test split with custom ratios.""" - df = pd.DataFrame( - {"feature1": range(100), "feature2": [f"val_{i}" for i in range(100)], "target": [i % 2 for i in range(100)]} - ) - - dataset = TabularDataset(df) - - # Split with custom ratios - train, val, test = dataset.split(train_ratio=0.8, val_ratio=0.1, test_ratio=0.1) - - # Check split sizes - assert len(train) == 80 - assert len(val) == 10 - assert len(test) == 10 - - # Check total size - assert len(train) + len(val) + len(test) == 100 - - -def test_tabular_dataset_split_stratified(): - """Test stratified splitting.""" - df = pd.DataFrame( - { - "feature1": range(100), - "feature2": [f"val_{i}" for i in range(100)], - "target": [i % 2 for i in range(100)], # 50/50 split of 0s and 1s - } - ) - - dataset = TabularDataset(df) - - # Split with stratification - train, val, test = dataset.split(stratify_column="target") - - # Check that class proportions are maintained - assert abs(train.to_pandas()["target"].mean() - 0.5) < 0.1 - assert abs(val.to_pandas()["target"].mean() - 0.5) < 0.1 - assert abs(test.to_pandas()["target"].mean() - 0.5) < 0.1 - - -def test_tabular_dataset_split_reproducibility(): - """Test that splits are reproducible with same random state.""" - df = pd.DataFrame( - {"feature1": range(100), "feature2": [f"val_{i}" for i in range(100)], "target": [i % 2 for i in range(100)]} - ) - - dataset = TabularDataset(df) - - # Create two splits with the same random state - train1, val1, test1 = dataset.split(random_state=42) - train2, val2, test2 = dataset.split(random_state=42) - - # Check that the splits are identical - pd.testing.assert_frame_equal(train1.to_pandas(), train2.to_pandas()) - pd.testing.assert_frame_equal(val1.to_pandas(), val2.to_pandas()) - pd.testing.assert_frame_equal(test1.to_pandas(), test2.to_pandas()) - - -def test_tabular_dataset_split_edge_cases(): - """Test edge cases for splitting.""" - df = pd.DataFrame( - {"feature1": range(100), "feature2": [f"val_{i}" for i in range(100)], "target": [i % 2 for i in range(100)]} - ) - - dataset = TabularDataset(df) - - # All data to train - train, val, test = dataset.split(train_ratio=1.0, val_ratio=0.0, test_ratio=0.0) - assert len(train) == 100 - assert len(val) == 0 - assert len(test) == 0 - - # No validation set - train, val, test = dataset.split(train_ratio=0.8, val_ratio=0.0, test_ratio=0.2) - assert len(train) == 80 - assert len(val) == 0 - assert len(test) == 20 - - # No test set - train, val, test = dataset.split(train_ratio=0.8, val_ratio=0.2, test_ratio=0.0) - assert len(train) == 80 - assert len(val) == 20 - assert len(test) == 0 - - # Invalid ratios - with pytest.raises(ValueError): - dataset.split(train_ratio=0.8, val_ratio=0.3, test_ratio=0.2) # Sum > 1 - - -def test_tabular_dataset_sample(): - """Test sampling functionality.""" - # Create test data - df = pd.DataFrame( - {"feature1": range(100), "feature2": [f"val_{i}" for i in range(100)], "target": [i % 2 for i in range(100)]} - ) - - # Create TabularDataset - dataset = TabularDataset(df) - - # Sample by count - sampled = dataset.sample(n=10, random_state=42) - assert len(sampled) == 10 - assert isinstance(sampled, TabularDataset) - - # Sample by fraction - sampled = dataset.sample(frac=0.1, random_state=42) - assert len(sampled) == 10 - assert isinstance(sampled, TabularDataset) - - # Sample with replacement - sampled = dataset.sample(n=120, replace=True, random_state=42) - assert len(sampled) == 120 - assert isinstance(sampled, TabularDataset) - - # Check reproducibility - sampled1 = dataset.sample(n=10, random_state=42) - sampled2 = dataset.sample(n=10, random_state=42) - pd.testing.assert_frame_equal(sampled1.to_pandas(), sampled2.to_pandas()) - - -def test_tabular_dataset_serialization(): - """Test that TabularDataset can be serialized and deserialized.""" - # Create test data - df = pd.DataFrame( - {"feature1": range(10), "feature2": [f"val_{i}" for i in range(10)], "target": [i % 2 for i in range(10)]} - ) - - # Create TabularDataset - dataset = TabularDataset(df) - - # Serialize to bytes - data_bytes = dataset.to_bytes() - assert isinstance(data_bytes, bytes) - assert len(data_bytes) > 0 - - # Deserialize from bytes - deserialized = TabularDataset.from_bytes(data_bytes) - - # Check that the deserialized dataset matches the original - assert len(deserialized) == len(dataset) - pd.testing.assert_frame_equal(deserialized.to_pandas(), dataset.to_pandas()) - - -def test_tabular_dataset_serialization_error_handling(): - """Test error handling during serialization/deserialization.""" - # Create a TabularDataset - dataset = TabularDataset(pd.DataFrame({"a": [1, 2, 3]})) - - # Test serialization (should succeed) - dataset.to_bytes() - - # Test deserialization with invalid data - with pytest.raises(RuntimeError): - TabularDataset.from_bytes(b"invalid data") - - -def test_tabular_dataset_structure(): - """Test structure property.""" - # Create test data - df = pd.DataFrame({"feature1": [1, 2, 3, 4, 5], "feature2": ["a", "b", "c", "d", "e"], "target": [0, 1, 0, 1, 0]}) - - # Create TabularDataset - dataset = TabularDataset(df) - structure = dataset.structure - - # Check structure type and fields - assert isinstance(structure, DatasetStructure) - assert structure.modality == "table" - assert set(structure.features) == {"feature1", "feature2", "target"} - - # Check details - assert structure.details["num_rows"] == 5 - assert structure.details["num_columns"] == 3 - assert set(structure.details["column_names"]) == {"feature1", "feature2", "target"} - assert isinstance(structure.details["column_types"], dict) - - -def test_tabular_dataset_file_storage(tmp_path): - """Test that TabularDataset can be stored to and loaded from a file.""" - # Create test data - df = pd.DataFrame( - {"feature1": range(10), "feature2": [f"val_{i}" for i in range(10)], "target": [i % 2 for i in range(10)]} - ) - - # Create TabularDataset - dataset = TabularDataset(df) - - # Write to file - file_path = tmp_path / "test_dataset.bin" - write_dataset_to_file(dataset, str(file_path)) - - # Check that the file exists - assert file_path.exists() - - # Read from file - loaded = read_dataset_from_file(TabularDataset, str(file_path)) - - # Check that the loaded dataset matches the original - assert len(loaded) == len(dataset) - pd.testing.assert_frame_equal(loaded.to_pandas(), dataset.to_pandas()) - - -def test_tabular_dataset_conversion(): - """Test conversion to pandas and numpy.""" - # Create test data - df = pd.DataFrame({"feature1": [1, 2, 3, 4, 5], "feature2": ["a", "b", "c", "d", "e"], "target": [0, 1, 0, 1, 0]}) - - # Create TabularDataset - dataset = TabularDataset(df) - - # Test pandas conversion - out_df = dataset.to_pandas() - assert isinstance(out_df, pd.DataFrame) - pd.testing.assert_frame_equal(out_df, df) - - # Test numpy conversion - arr = dataset.to_numpy() - assert isinstance(arr, np.ndarray) - np.testing.assert_array_equal(arr, df.to_numpy()) - - -def test_tabular_dataset_getitem(): - """Test __getitem__ functionality.""" - # Create test data - df = pd.DataFrame( - {"feature1": range(10), "feature2": [f"val_{i}" for i in range(10)], "target": [i % 2 for i in range(10)]} - ) - - # Create TabularDataset - dataset = TabularDataset(df) - - # Single item access - item = dataset[0] - assert item.feature1 == 0 - assert item.feature2 == "val_0" - assert item.target == 0 - - # Slice access - slice_items = dataset[1:4] - assert isinstance(slice_items, pd.Series) or isinstance(slice_items, pd.DataFrame) - - if isinstance(slice_items, pd.DataFrame): - assert len(slice_items) == 3 - else: - # If it returns a Series, check that the values match - expected_series = df.iloc[1:4] - if isinstance(expected_series, pd.Series): - pd.testing.assert_series_equal(slice_items, expected_series) - - -def test_tabular_dataset_len(): - """Test __len__ functionality.""" - # Create datasets of different sizes - dataset1 = TabularDataset(pd.DataFrame({"a": range(5)})) - dataset2 = TabularDataset(pd.DataFrame({"a": range(10)})) - - # Check lengths - assert len(dataset1) == 5 - assert len(dataset2) == 10 diff --git a/tests/unit/internal/common/utils/__init__.py b/tests/unit/internal/common/utils/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/tests/unit/internal/common/utils/test_dataset_storage.py b/tests/unit/internal/common/utils/test_dataset_storage.py deleted file mode 100644 index 8e6647e0..00000000 --- a/tests/unit/internal/common/utils/test_dataset_storage.py +++ /dev/null @@ -1,111 +0,0 @@ -""" -Tests for the dataset storage utilities. - -This module verifies: -1. Writing datasets to files and reading them back -2. Storing datasets in shared memory and retrieving them -3. Error handling for invalid file paths and data -""" - -import os -import pytest - -from plexe.internal.common.datasets.tabular import TabularDataset -from plexe.internal.common.utils.dataset_storage import ( - write_dataset_to_file, - read_dataset_from_file, - dataset_to_shared_memory, - dataset_from_shared_memory, -) -import pandas as pd - - -def test_write_and_read_file(tmp_path): - """Test writing a dataset to a file and reading it back.""" - # Create a test dataset - df = pd.DataFrame({"feature1": [1, 2, 3], "feature2": ["a", "b", "c"], "target": [0, 1, 0]}) - dataset = TabularDataset(df) - - # Write to file - file_path = tmp_path / "test_dataset.bin" - write_dataset_to_file(dataset, str(file_path)) - - # Check that file exists - assert file_path.exists() - assert os.path.getsize(str(file_path)) > 0 - - # Read from file - loaded_dataset = read_dataset_from_file(TabularDataset, str(file_path)) - - # Check that loaded dataset matches original - assert isinstance(loaded_dataset, TabularDataset) - assert len(loaded_dataset) == len(dataset) - pd.testing.assert_frame_equal(loaded_dataset.to_pandas(), dataset.to_pandas()) - - -def test_file_storage_error_handling(tmp_path): - """Test error handling for file storage operations.""" - # Test with non-existent file - non_existent_path = tmp_path / "non_existent.bin" - with pytest.raises(FileNotFoundError): - read_dataset_from_file(TabularDataset, str(non_existent_path)) - - # Test with invalid file content - invalid_path = tmp_path / "invalid.bin" - with open(str(invalid_path), "wb") as f: - f.write(b"invalid data") - - with pytest.raises(RuntimeError): - read_dataset_from_file(TabularDataset, str(invalid_path)) - - # Test with invalid directory path - invalid_dir = tmp_path / "non_existent_dir" / "dataset.bin" - - # Create a dataset - df = pd.DataFrame({"a": [1, 2, 3]}) - dataset = TabularDataset(df) - - with pytest.raises(FileNotFoundError): - write_dataset_to_file(dataset, str(invalid_dir)) - - -@pytest.mark.skipif( - not hasattr(__import__("multiprocessing", fromlist=["shared_memory"]), "shared_memory"), - reason="Shared memory requires Python 3.8+", -) -def test_shared_memory_error_handling(): - """Test error handling in shared memory functions.""" - # Mock an ImportError for dataset_to_shared_memory - import builtins - - original_import = builtins.__import__ - - def mock_import(name, *args, **kwargs): - if name == "multiprocessing" or name == "multiprocessing.shared_memory": - raise ImportError("Mocked import error") - return original_import(name, *args, **kwargs) - - # Test with ImportError - try: - builtins.__import__ = mock_import - - # Test dataset_to_shared_memory - dataset = TabularDataset(pd.DataFrame({"a": [1, 2, 3]})) - with pytest.raises(ImportError): - dataset_to_shared_memory(dataset, "test_segment") - - # Test dataset_from_shared_memory - with pytest.raises(ImportError): - dataset_from_shared_memory(TabularDataset, "test_segment") - finally: - builtins.__import__ = original_import - - # Restore original import function - builtins.__import__ = original_import - - # Test with non-existent shared memory segment - try: - with pytest.raises((FileNotFoundError, ValueError)): - dataset_from_shared_memory(TabularDataset, "non_existent_segment_name") - except ImportError: - pytest.skip("shared_memory not available") diff --git a/tests/unit/internal/datasets/__init__.py b/tests/unit/internal/datasets/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/tests/unit/internal/datasets/core/__init__.py b/tests/unit/internal/datasets/core/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/tests/unit/internal/datasets/core/generation/__init__.py b/tests/unit/internal/datasets/core/generation/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/tests/unit/internal/datasets/core/generation/utils/__init__.py b/tests/unit/internal/datasets/core/generation/utils/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/tests/unit/internal/models/__init__.py b/tests/unit/internal/models/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/tests/unit/internal/models/callbacks/__init__.py b/tests/unit/internal/models/callbacks/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/tests/unit/internal/models/callbacks/test_mlflow.py b/tests/unit/internal/models/callbacks/test_mlflow.py deleted file mode 100644 index 422a6ab1..00000000 --- a/tests/unit/internal/models/callbacks/test_mlflow.py +++ /dev/null @@ -1,258 +0,0 @@ -""" -Unit tests for the MLFlowCallback class. - -These tests validate the functionality of the MLFlowCallback, which is responsible -for logging model building metrics, parameters, and artifacts to MLFlow. -""" - -from unittest.mock import MagicMock, patch -import pytest -from pydantic import BaseModel - -from plexe.callbacks import BuildStateInfo -from plexe.internal.models.callbacks.mlflow import MLFlowCallback -from plexe.internal.models.entities.artifact import Artifact -from plexe.internal.models.entities.metric import Metric, MetricComparator, ComparisonMethod -from plexe.core.entities.solution import Solution - - -@pytest.fixture -def setup_env(): - """Set up common test environment.""" - # Create metric - metric = Metric(name="accuracy", value=0.95, comparator=MetricComparator(ComparisonMethod.HIGHER_IS_BETTER)) - - # Create node with the metric - node = Solution( - plan="Train a random forest model", - performance=metric, - execution_time=10.5, - model_artifacts=[Artifact.from_path("/path/to/artifact.pkl")], - ) - - # Create input/output schemas - class InputSchema(BaseModel): - feature1: float - feature2: str - - class OutputSchema(BaseModel): - prediction: float - - # Create a mock dataset - mock_dataset = MagicMock() - mock_dataset.to_pandas.return_value = MagicMock() - - # Create build info for different stages - build_info = BuildStateInfo( - intent="Predict house prices", - provider="gemini/gemini-2.5-flash", - input_schema=InputSchema, - output_schema=OutputSchema, - run_timeout=300, - max_iterations=10, - timeout=3600, - datasets={"train": mock_dataset}, - ) - - # Create iteration info with node - iteration_info = BuildStateInfo( - intent="Predict house prices", - provider="gemini/gemini-2.5-flash", - input_schema=InputSchema, - output_schema=OutputSchema, - run_timeout=300, - max_iterations=10, - timeout=3600, - iteration=1, - node=node, - datasets={"train": mock_dataset}, - ) - - return { - "metric": metric, - "node": node, - "input_schema": InputSchema, - "output_schema": OutputSchema, - "mock_dataset": mock_dataset, - "build_info": build_info, - "iteration_info": iteration_info, - } - - -def test_callback_initialization(): - """Test that the MLFlowCallback can be initialized properly.""" - with patch("mlflow.set_tracking_uri") as mock_set_tracking_uri: - with patch("mlflow.active_run", return_value=None): # No active run - with patch("mlflow.get_experiment_by_name", return_value=None): # Experiment doesn't exist - with patch("mlflow.create_experiment", return_value="test-experiment-id"): - with patch("mlflow.set_experiment"): - callback = MLFlowCallback( - tracking_uri="http://localhost:5000", experiment_name="test-experiment" - ) - - # Verify tracking URI was set - mock_set_tracking_uri.assert_called_once_with("http://localhost:5000") - - # Verify default values - assert callback.experiment_name == "test-experiment" - assert callback.experiment_id == "test-experiment-id" - - -@patch("mlflow.set_tracking_uri") -@patch("mlflow.get_experiment_by_name") -@patch("mlflow.create_experiment", return_value="initial-experiment-id") -def test_build_start(mock_create_experiment, mock_get_experiment, _, setup_env): - """Test on_build_start callback.""" - # Set up mocks - during initialization, experiment should be found - mock_experiment = MagicMock() - mock_experiment.experiment_id = "test-experiment-id" - mock_get_experiment.return_value = mock_experiment - - # Initialize callback with active_run patched - with patch("mlflow.active_run", return_value=None): - with patch("mlflow.set_experiment"): - callback = MLFlowCallback(tracking_uri="http://localhost:5000", experiment_name="test-experiment") - - # During initialization, get_experiment_by_name was called once (experiment exists, so no create_experiment) - mock_get_experiment.assert_called_once_with("test-experiment") - mock_create_experiment.assert_not_called() - - # Reset mocks for on_build_start testing - mock_get_experiment.reset_mock() - mock_create_experiment.reset_mock() - - # Mock mlflow methods for on_build_start - with patch("mlflow.active_run", return_value=None): - with patch("mlflow.set_experiment"): - with patch("mlflow.start_run") as mock_start_run: - with patch("mlflow.log_params"): - with patch("mlflow.set_tags"): - mock_run = MagicMock() - mock_run.info.run_id = "parent-run-id" - mock_start_run.return_value = mock_run - - # Call on_build_start - callback.on_build_start(setup_env["build_info"]) - - # Since experiment_id is already set, _get_or_create_experiment should not call get_experiment_by_name again - mock_get_experiment.assert_not_called() - mock_create_experiment.assert_not_called() - - # Experiment ID should remain the same from initialization - assert callback.experiment_id == "test-experiment-id" - - -@patch("mlflow.set_tracking_uri") -@patch("mlflow.get_experiment_by_name") -@patch("mlflow.create_experiment") -@patch("mlflow.set_experiment") -@patch("mlflow.active_run", return_value=None) -def test_build_start_new_experiment( - mock_active_run, mock_set_experiment, mock_create_experiment, mock_get_experiment, mock_set_tracking_uri, setup_env -): - """Test on_build_start with a new experiment.""" - # Set up mocks for a new experiment - experiment doesn't exist during initialization - mock_get_experiment.return_value = None - mock_create_experiment.return_value = "init-experiment-id" - - # Initialize callback - callback = MLFlowCallback(tracking_uri="http://localhost:5000", experiment_name="new-experiment") - - # During initialization: get_experiment_by_name was called, then create_experiment - mock_get_experiment.assert_called_once_with("new-experiment") - mock_create_experiment.assert_called_once_with("new-experiment") - assert callback.experiment_id == "init-experiment-id" - - # Reset mocks for on_build_start testing - mock_get_experiment.reset_mock() - mock_create_experiment.reset_mock() - mock_set_experiment.reset_mock() - - # Mock mlflow methods for on_build_start - with patch("mlflow.start_run") as mock_start_run: - with patch("mlflow.log_params"): - with patch("mlflow.set_tags"): - mock_run = MagicMock() - mock_run.info.run_id = "parent-run-id" - mock_start_run.return_value = mock_run - - # Call on_build_start - callback.on_build_start(setup_env["build_info"]) - - # Since experiment_id is already set, _get_or_create_experiment should not call these again - mock_get_experiment.assert_not_called() - mock_create_experiment.assert_not_called() - - # Experiment ID should remain the same from initialization - assert callback.experiment_id == "init-experiment-id" - - -def test_build_end(setup_env): - """Test on_build_end callback.""" - # Initialize callback with all necessary patches - with patch("mlflow.active_run", return_value=None): - with patch("mlflow.get_experiment_by_name") as mock_get_exp: - with patch("mlflow.create_experiment", return_value="test-experiment-id"): - with patch("mlflow.set_experiment"): - # Mock experiment exists during initialization - mock_experiment = MagicMock() - mock_experiment.experiment_id = "test-experiment-id" - mock_get_exp.return_value = mock_experiment - - callback = MLFlowCallback(tracking_uri="http://localhost:5000", experiment_name="test-experiment") - callback.parent_run_id = "parent-run-id" # Set parent run ID for testing - - # Mock all MLflow methods for on_build_end - mock_run = MagicMock() - mock_run.info.run_id = "parent-run-id" - - with patch("mlflow.active_run", return_value=mock_run): - with patch("mlflow.set_experiment"): - with patch("mlflow.start_run", return_value=mock_run): - with patch("mlflow.log_artifact"): - with patch("mlflow.log_metric"): - with patch("mlflow.set_tag"): - with patch("mlflow.end_run") as mock_end_run: - # Call on_build_end - callback.on_build_end(setup_env["build_info"]) - - # Verify end_run was called once - mock_end_run.assert_called_once() - - -def test_log_metric(setup_env): - """Test _log_metric helper method.""" - # Initialize callback with all necessary patches - with patch("mlflow.active_run", return_value=None): - with patch("mlflow.get_experiment_by_name") as mock_get_exp: - with patch("mlflow.create_experiment", return_value="test-experiment-id"): - with patch("mlflow.set_experiment"): - # Mock experiment exists during initialization - mock_experiment = MagicMock() - mock_experiment.experiment_id = "test-experiment-id" - mock_get_exp.return_value = mock_experiment - - callback = MLFlowCallback(tracking_uri="http://localhost:5000", experiment_name="test-experiment") - - # Mock active_run to True when _log_metric is called - with patch("mlflow.active_run", return_value=MagicMock()): - # Mock the log_metric method - with patch("mlflow.log_metric") as mock_log_metric: - # Call _log_metric - callback._log_metric(setup_env["metric"], prefix="test_", step=1) - - # Verify metric was logged - mock_log_metric.assert_called_once() - - # Just check the first arg (metric name) and validate that other args exist - args = mock_log_metric.call_args[0] - assert "accuracy" in args[0] # Name contains "accuracy" - assert args[1] == 0.95 # Value is correct - - # Check that step was passed as a kwarg - kwargs = mock_log_metric.call_args[1] - assert kwargs.get("step") == 1 - - -if __name__ == "__main__": - pytest.main() diff --git a/tests/unit/internal/models/entities/__init__.py b/tests/unit/internal/models/entities/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/tests/unit/internal/models/entities/test_metric.py b/tests/unit/internal/models/entities/test_metric.py deleted file mode 100644 index 60b1dac5..00000000 --- a/tests/unit/internal/models/entities/test_metric.py +++ /dev/null @@ -1,138 +0,0 @@ -""" -Module: test_metric_class - -This module contains unit tests for the `Metric` and `MetricComparator` classes, ensuring their functionality -and robustness. The tests cover: - -- Comparison methods (`HIGHER_IS_BETTER`, `LOWER_IS_BETTER`, `TARGET_IS_BETTER`). -- Handling of edge cases like floating-point precision and boundary values. -- Validation logic for metrics (e.g., checking valid/invalid states). -- Compatibility and error handling for metrics with different names or comparison methods. -- System-level behaviours, such as sorting collections of metrics. - -Dependencies: - - pytest: For running the test suite. - - metric_class: The module containing the `Metric` and `MetricComparator` class implementations. - -Example: - pytest test_metric_class.py -""" - -import pytest -from plexe.internal.models.entities.metric import Metric, MetricComparator, ComparisonMethod - - -def test_comparator_higher_is_better(): - comparator = MetricComparator(ComparisonMethod.HIGHER_IS_BETTER) - assert comparator.compare(0.8, 0.9) == 1 # 0.9 is better - assert comparator.compare(0.9, 0.8) == -1 # 0.9 is better - assert comparator.compare(0.8, 0.8) == 0 # Equal - - -def test_comparator_lower_is_better(): - comparator = MetricComparator(ComparisonMethod.LOWER_IS_BETTER) - assert comparator.compare(0.8, 0.9) == -1 # 0.8 is better - assert comparator.compare(0.9, 0.8) == 1 # 0.8 is better - assert comparator.compare(0.8, 0.8) == 0 # Equal - - -def test_comparator_target_is_better(): - comparator = MetricComparator(ComparisonMethod.TARGET_IS_BETTER, target=1.0) - assert comparator.compare(0.9, 1.1) == 0 # Both are equally close to the target - assert comparator.compare(1.0, 1.2) == -1 # 1.0 is closer to the target - assert comparator.compare(0.8, 1.0) == 1 # 1.0 is closer to the target - - -def test_comparator_invalid_target(): - with pytest.raises(ValueError, match="requires a target value"): - MetricComparator(ComparisonMethod.TARGET_IS_BETTER) - - -def test_comparator_floating_point_precision(): - comparator = MetricComparator(ComparisonMethod.HIGHER_IS_BETTER) - assert comparator.compare(1.0000001, 1.0000002) == 1 - assert comparator.compare(1.0000002, 1.0000001) == -1 - - -def test_metric_higher_is_better(): - comparator = MetricComparator(ComparisonMethod.HIGHER_IS_BETTER) - metric1 = Metric(name="accuracy", value=0.8, comparator=comparator) - metric2 = Metric(name="accuracy", value=0.9, comparator=comparator) - assert metric1 < metric2 - assert metric2 > metric1 - assert metric1 != metric2 - - -def test_metric_lower_is_better(): - comparator = MetricComparator(ComparisonMethod.LOWER_IS_BETTER) - metric1 = Metric(name="loss", value=0.8, comparator=comparator) - metric2 = Metric(name="loss", value=0.6, comparator=comparator) - assert metric1 < metric2 # metric1 is "lower" because it's worse - assert metric2 > metric1 - assert metric1 != metric2 - - -def test_metric_target_is_better(): - comparator = MetricComparator(ComparisonMethod.TARGET_IS_BETTER, target=1.0) - metric1 = Metric(name="value", value=0.9, comparator=comparator) - metric2 = Metric(name="value", value=1.1, comparator=comparator) - assert metric1 == metric2 # Both are equally close to the target - - -def test_metric_different_names(): - comparator = MetricComparator(ComparisonMethod.HIGHER_IS_BETTER) - metric1 = Metric(name="accuracy", value=0.8, comparator=comparator) - metric2 = Metric(name="loss", value=0.9, comparator=comparator) - with pytest.raises(ValueError, match="Cannot compare metrics with different names"): - metric1 > metric2 - - -def test_metric_invalid_comparison(): - comparator1 = MetricComparator(ComparisonMethod.HIGHER_IS_BETTER) - comparator2 = MetricComparator(ComparisonMethod.LOWER_IS_BETTER) - comparator3 = MetricComparator(ComparisonMethod.TARGET_IS_BETTER, target=1.0) - comparator4 = MetricComparator(ComparisonMethod.TARGET_IS_BETTER, target=2.0) - metric1 = Metric(name="accuracy", value=0.8, comparator=comparator1) - metric2 = Metric(name="accuracy", value=0.9, comparator=comparator2) - metric3 = Metric(name="accuracy", value=1.0, comparator=comparator3) - metric4 = Metric(name="accuracy", value=1.1, comparator=comparator4) - with pytest.raises(ValueError, match="Cannot compare metrics with different comparison methods"): - metric1 > metric2 - with pytest.raises(ValueError, match="Cannot compare 'TARGET_IS_BETTER' metrics with different target values"): - metric3 > metric4 - - -def test_metric_is_valid(): - comparator = MetricComparator(ComparisonMethod.HIGHER_IS_BETTER) - metric = Metric(name="accuracy", value=float("nan"), comparator=comparator) - assert not metric.is_valid - - metric = Metric(name="accuracy", value=0.8, comparator=comparator) - assert metric.is_valid - - -def test_metric_repr_and_str(): - comparator = MetricComparator(ComparisonMethod.HIGHER_IS_BETTER) - metric = Metric(name="accuracy", value=0.8, comparator=comparator) - assert repr(metric) == "Metric(name='accuracy', value=0.8, comparison=HIGHER_IS_BETTER)" - assert str(metric) == "Metric accuracy ↑ 0.8" - - -def test_metric_transitivity(): - comparator = MetricComparator(ComparisonMethod.HIGHER_IS_BETTER) - metric1 = Metric(name="accuracy", value=0.8, comparator=comparator) - metric2 = Metric(name="accuracy", value=0.9, comparator=comparator) - metric3 = Metric(name="accuracy", value=1.0, comparator=comparator) - assert metric1 < metric2 < metric3 - assert metric3 > metric2 > metric1 - - -def test_metric_collection_sorting(): - comparator = MetricComparator(ComparisonMethod.HIGHER_IS_BETTER) - metrics = [ - Metric(name="accuracy", value=0.8, comparator=comparator), - Metric(name="accuracy", value=0.6, comparator=comparator), - Metric(name="accuracy", value=0.9, comparator=comparator), - ] - metrics.sort(reverse=True) - assert [m.value for m in metrics] == [0.9, 0.8, 0.6] diff --git a/tests/unit/internal/models/execution/__init__.py b/tests/unit/internal/models/execution/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/tests/unit/internal/models/execution/test_factory.py b/tests/unit/internal/models/execution/test_factory.py deleted file mode 100644 index 1fa7892c..00000000 --- a/tests/unit/internal/models/execution/test_factory.py +++ /dev/null @@ -1,44 +0,0 @@ -"""Test the executor factory.""" - -import pytest -from unittest.mock import patch - -import importlib - -from plexe.tools.execution import _get_executor_class -from plexe.internal.models.execution.process_executor import ProcessExecutor - - -def test_get_executor_class_non_distributed(): - """Test that ProcessExecutor is returned when distributed=False.""" - executor_class = _get_executor_class(distributed=False) - assert executor_class == ProcessExecutor - - -def test_get_executor_class_distributed(): - """Test that RayExecutor is returned when distributed=True and Ray is available.""" - # Check if Ray is available - ray_available = importlib.util.find_spec("ray") is not None - - if ray_available: - executor_class = _get_executor_class(distributed=True) - from plexe.internal.models.execution.ray_executor import RayExecutor - - assert executor_class == RayExecutor - else: - pytest.skip("Ray not available, skipping test") - - -def test_get_executor_class_distributed_ray_not_available(): - """Test that ProcessExecutor is returned as fallback when Ray is not available.""" - # Use a mock to simulate Ray not being available - with patch( - "builtins.__import__", - side_effect=lambda name, *args, **kwargs: ( - ModuleNotFoundError("No module named 'ray'") - if name == "plexe.internal.models.execution.ray_executor" - else importlib.import_module(name) - ), - ): - executor_class = _get_executor_class(distributed=True) - assert executor_class == ProcessExecutor diff --git a/tests/unit/internal/models/execution/test_process_executor.py b/tests/unit/internal/models/execution/test_process_executor.py deleted file mode 100644 index d684d9b3..00000000 --- a/tests/unit/internal/models/execution/test_process_executor.py +++ /dev/null @@ -1,113 +0,0 @@ -""" -Unit tests for the ProcessExecutor class and its associated components. - -These tests validate the functionality of the following: -- RedirectQueue: Ensures that stdout and stderr redirection to a queue behaves as expected. -- ProcessExecutor: Tests execution of Python code in an isolated process, including handling of: - - Successful execution. - - Timeouts. - - Exceptions raised during execution. - - Dataset handling and working directory creation. - -The tests use pytest as the test runner and employ mocking to isolate external dependencies. -""" - -import os -import shutil -import subprocess -import sys -from pathlib import Path -from unittest.mock import MagicMock, patch - -import pandas as pd -import pyarrow -import pytest - -from plexe.internal.common.datasets.tabular import TabularDataset -from plexe.internal.models.execution.executor import ExecutionResult -from plexe.internal.models.execution.process_executor import ProcessExecutor - - -class TestProcessExecutor: - def setup_method(self): - self.execution_id = "test_execution" - self.code = "print('Hello, World!')" - self.working_dir = Path(os.getcwd()) / self.execution_id - self.timeout = 5 - self.datasets = {"training_data": TabularDataset(pd.DataFrame({"col1": [1, 2], "col2": [3, 4]}))} - self.process_executor = ProcessExecutor( - execution_id=self.execution_id, - code=self.code, - working_dir=Path(os.getcwd()), - datasets=self.datasets, - timeout=self.timeout, - code_execution_file_name="run.py", - ) - - def teardown_method(self): - if self.working_dir.exists(): - shutil.rmtree(self.working_dir, ignore_errors=True) - - def test_constructor_creates_working_directory(self): - assert self.working_dir.exists() - - @patch("pyarrow.parquet.write_table") - def test_run_successful_execution(self, mock_write_table): - mock_process = MagicMock() - mock_process.communicate.return_value = ("Performance: 0.5", "") - mock_process.returncode = 0 - - with patch("subprocess.Popen", return_value=mock_process) as mock_popen: - result = self.process_executor.run() - - dataset_file = self.working_dir / "training_data.parquet" - mock_write_table.assert_called_once_with( - pyarrow.Table.from_pandas(self.datasets["training_data"].to_pandas()), dataset_file - ) - mock_popen.assert_called_once_with( - [sys.executable, str(self.working_dir / "run.py")], - stdout=subprocess.PIPE, - stderr=subprocess.PIPE, - cwd=str(self.working_dir), - text=True, - ) - assert isinstance(result, ExecutionResult) - assert result.exception is None - assert "Performance: 0.5" in result.term_out - - @patch("subprocess.Popen") - def test_run_timeout(self, mock_popen): - mock_process = MagicMock() - mock_process.communicate.side_effect = subprocess.TimeoutExpired(cmd="test", timeout=self.timeout) - - with patch("subprocess.Popen", return_value=mock_process): - result = self.process_executor.run() - - assert isinstance(result, ExecutionResult) - assert isinstance(result.exception, TimeoutError) - assert result.exec_time == self.timeout - - @patch("subprocess.Popen") - def test_run_exception(self, mock_popen): - mock_process = MagicMock() - mock_process.communicate.return_value = ("", "RuntimeError: Something went wrong") - mock_process.returncode = 1 - - with patch("subprocess.Popen", return_value=mock_process): - result = self.process_executor.run() - - assert isinstance(result, ExecutionResult) - assert isinstance(result.exception, RuntimeError) - assert "Something went wrong" in str(result.exception) - - @patch("pyarrow.parquet.write_table") - def test_dataset_written_to_file(self, mock_write_table): - self.process_executor.run() - dataset_file = self.working_dir / "training_data.parquet" - mock_write_table.assert_called_once_with( - pyarrow.Table.from_pandas(self.datasets["training_data"].to_pandas()), dataset_file - ) - - -if __name__ == "__main__": - pytest.main() diff --git a/tests/unit/internal/models/validation/__init__.py b/tests/unit/internal/models/validation/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/tests/unit/internal/models/validation/primitives/__init__.py b/tests/unit/internal/models/validation/primitives/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/tests/unit/internal/models/validation/primitives/test_syntax.py b/tests/unit/internal/models/validation/primitives/test_syntax.py deleted file mode 100644 index 942349ed..00000000 --- a/tests/unit/internal/models/validation/primitives/test_syntax.py +++ /dev/null @@ -1,97 +0,0 @@ -import pytest -from plexe.internal.models.validation.primitives.syntax import SyntaxValidator - - -@pytest.fixture -def syntax_validator(): - """ - Fixture to provide an instance of SyntaxValidator. - - :return: An instance of SyntaxValidator. - """ - return SyntaxValidator() - - -def test_valid_code(syntax_validator): - """Test that the validate method correctly identifies valid Python code.""" - valid_code = "def add(a, b):\n" " return a + b\n\n" "result = add(2, 3)\n" - result = syntax_validator.validate(valid_code) - assert result.passed is True - assert result.message == "Syntax is valid." - assert result.exception is None - - -def test_invalid_code(syntax_validator): - """Test that the validate method correctly identifies invalid Python code.""" - invalid_code = "def add(a, b):\n" " return a + b\n" "result = add(2, 3\n" # Missing closing parenthesis - result = syntax_validator.validate(invalid_code) - assert result.passed is False - assert "Syntax is not valid" in result.message - assert "line 3" in result.message # Ensures the line number is reported - assert result.exception is not None - assert isinstance(result.exception, SyntaxError) - - -def test_empty_code(syntax_validator): - """Test that the validate method handles empty code correctly.""" - empty_code = "" - result = syntax_validator.validate(empty_code) - assert result.passed is True - assert result.message == "Syntax is valid." - assert result.exception is None - - -def test_code_with_comments(syntax_validator): - """Test that the validate method handles code containing only comments.""" - comment_code = "# This is a comment\n" "# Another comment line\n" - result = syntax_validator.validate(comment_code) - assert result.passed is True - assert result.message == "Syntax is valid." - assert result.exception is None - - -def test_code_with_syntax_warning(syntax_validator): - """Test that the validate method handles code with a warning but no syntax error.""" - warning_code = "x = 1 # Variable assigned but not used" - result = syntax_validator.validate(warning_code) - assert result.passed is True - assert result.message == "Syntax is valid." - assert result.exception is None - - -def test_code_with_non_ascii_characters(syntax_validator): - """Test that the validate method handles code with non-ASCII characters.""" - non_ascii_code = "def greet():\n" ' return "Hello, \u4f60\u597d!"' # Includes Chinese characters for "Hello" - result = syntax_validator.validate(non_ascii_code) - assert result.passed is True - assert result.message == "Syntax is valid." - assert result.exception is None - - -def test_code_with_indentation_error(syntax_validator): - """Test that the validate method correctly identifies indentation errors.""" - indentation_error_code = "def add(a, b):\n" "return a + b" # Missing indentation for the return statement - result = syntax_validator.validate(indentation_error_code) - assert result.passed is False - assert "Syntax is not valid" in result.message - assert "line 2" in result.message # Ensures the line number is reported - assert result.exception is not None - assert isinstance(result.exception, SyntaxError) - - -def test_code_with_nested_functions(syntax_validator): - """Test that the validate method handles code with nested functions.""" - nested_function_code = "def outer():\n" " def inner():\n" ' return "Hello"\n' " return inner()\n" - result = syntax_validator.validate(nested_function_code) - assert result.passed is True - assert result.message == "Syntax is valid." - assert result.exception is None - - -def test_code_with_large_input(syntax_validator): - """Test that the validate method handles a large amount of valid code.""" - large_code = "\n".join([f"def func{i}():\n return {i}" for i in range(1000)]) - result = syntax_validator.validate(large_code) - assert result.passed is True - assert result.message == "Syntax is valid." - assert result.exception is None diff --git a/tests/unit/test_datasets.py b/tests/unit/test_datasets.py deleted file mode 100644 index 0912ab19..00000000 --- a/tests/unit/test_datasets.py +++ /dev/null @@ -1,95 +0,0 @@ -from unittest.mock import patch - -import numpy as np -import pandas as pd -import pytest - -from plexe import DatasetGenerator - - -@pytest.fixture -def sample_schema(): - """Test schema for house price prediction""" - return { - "input_schema": {"square_feet": float, "bedrooms": int, "location": str}, - "output_schema": {"price": float}, - } - - -@pytest.fixture -def mock_generated_data(): - """Mock data generation output""" - return pd.DataFrame( - { - "square_feet": np.random.uniform(1000, 3000, 50), - "bedrooms": np.random.randint(2, 6, 50), - "location": np.random.choice(["suburban", "urban", "rural"], 50), - "price": np.random.uniform(200000, 600000, 50), - } - ) - - -class TestDataGeneration: - """Test suite for data generation with comprehensive mocking""" - - @pytest.fixture(autouse=True) - def setup_mocks(self): - """Setup all required mocks for the test class""" - # Mock the data generation function - self.mock_generate_data = patch("plexe.datasets.DataGenerator.generate", return_value=pd.DataFrame()).start() - - yield - - # Stop all mocks after the test - patch.stopall() - - def test_basic_generation(self, sample_schema, mock_generated_data): - """Test basic data generation""" - self.mock_generate_data.return_value = mock_generated_data - - dataset = DatasetGenerator( - description="House features and prices, each row is a house", - schema={**sample_schema["input_schema"], **sample_schema["output_schema"]}, - provider="openai/gpt-4o", - ) - dataset.generate(50) - - # Verify generate_data was called with correct parameters - self.mock_generate_data.assert_called_once() - call_args = self.mock_generate_data.call_args[0] - assert isinstance(call_args[0], int) - assert call_args[0] == 50 - - # Verify generated data was added to the dataset - assert dataset._data is not None - assert len(dataset._data) == 50 - - def test_data_augmentation(self, sample_schema, mock_generated_data): - """Test data augmentation with existing dataset""" - self.mock_generate_data.return_value = mock_generated_data - - existing_data = pd.DataFrame( - { - "square_feet": [1000, 1500, 2000], - "bedrooms": [2, 3, 4], - "location": ["A", "B", "C"], - "price": [200000, 300000, 400000], - } - ) - - dataset = DatasetGenerator( - description="House features and prices, each row is a house", - schema={**sample_schema["input_schema"], **sample_schema["output_schema"]}, - provider="openai/gpt-4o", - data=existing_data.copy(), - ) - dataset.generate(50) - - # Verify generate_data was called with correct parameters - self.mock_generate_data.assert_called_once() - call_args = self.mock_generate_data.call_args[0] - assert isinstance(call_args[0], int) - assert call_args[0] == 50 - - # Verify final dataset includes both original and synthetic data - assert len(dataset._data) == len(existing_data) + 50 diff --git a/tests/unit/test_fileio.py b/tests/unit/test_fileio.py deleted file mode 100644 index 80a07f3f..00000000 --- a/tests/unit/test_fileio.py +++ /dev/null @@ -1,65 +0,0 @@ -""" -Unit tests for plexe.fileio module, including backwards compatibility testing. -""" - -from pathlib import Path -from typing import Any - -import pytest - -import plexe.fileio as fileio - - -def _validate_model(model: Any) -> None: - """Helper function to validate the loaded model.""" - # Basic validation - model should load successfully - assert model is not None, "Model should not be None" - assert hasattr(model, "intent"), "Model should have an 'intent' attribute" - assert hasattr(model, "input_schema"), "Model should have an 'input_schema' attribute" - assert hasattr(model, "output_schema"), "Model should have an 'output_schema' attribute" - assert hasattr(model, "predictor"), "Model should have a 'predictor' attribute" - assert isinstance(model.intent, str), "Intent should be of type str" - assert hasattr(model, "predict"), "Model should have a 'predict' method" - assert callable(model.predict), "Model's 'predict' should be callable" - # Schema validation - assert model.input_schema is not None - assert model.output_schema is not None - # Model should be in READY state if it was saved as a complete model - from plexe.core.state import ModelState - - assert model.state == ModelState.READY - - -class TestFileIO: - """Test cases for fileio module functionality.""" - - def test_load_model_backwards_compatibility_v0_18_3(self): - """Test loading a model bundle from v0.18.3 for backwards compatibility.""" - fixture_path = Path(__file__).parent.parent / "fixtures/legacy_models/model_v0_18_3.tar.gz" - - if not fixture_path.exists(): - pytest.skip(f"Legacy model fixture not found: {fixture_path}") - - # Load the legacy model - model = fileio.load_model(fixture_path) - - _validate_model(model) - - def test_load_model_backwards_compatibility_v0_23_2(self): - """Test loading a model bundle from v0.23.2 for backwards compatibility.""" - fixture_path = Path(__file__).parent.parent / "fixtures/legacy_models/model_v0_23_2.tar.gz" - - if not fixture_path.exists(): - pytest.skip(f"Legacy model fixture not found: {fixture_path}") - - # Load the legacy model - model = fileio.load_model(fixture_path) - - _validate_model(model) - - def test_load_model_file_not_found(self): - """Test that load_model raises appropriate error for missing files.""" - non_existent_path = Path("non_existent_model.tar.gz") - - with pytest.raises(ValueError, match="Failed to load model"): - fileio.load_model(non_existent_path) diff --git a/tests/utils/utils.py b/tests/utils/utils.py deleted file mode 100644 index 62f62f70..00000000 --- a/tests/utils/utils.py +++ /dev/null @@ -1,445 +0,0 @@ -# tests/utils/utils.py -import numpy as np -import pandas as pd -import shutil -from pathlib import Path - -from plexe.internal.models.entities.description import ModelDescription - - -def generate_heart_data(n_samples=30, random_seed=42): - """Generate synthetic heart disease data for testing. - - The data follows the structure: - - age: int (25-80) - - gender: int (0=female, 1=male) - - cp: int (chest pain type, 0-3) - - trtbps: int (resting blood pressure, 90-200) - - chol: int (cholesterol, 120-400) - - fbs: int (fasting blood sugar > 120 mg/dl, 0-1) - - restecg: int (resting ECG results, 0-2) - - thalachh: int (maximum heart rate achieved, 70-220) - - exng: int (exercise induced angina, 0-1) - - oldpeak: float (ST depression induced by exercise, 0-6.0) - - slp: int (slope of peak exercise ST segment, 0-2) - - caa: int (number of major vessels, 0-4) - - thall: int (thalassemia, 0-3) - - output: int (presence of heart disease, 0-1) - """ - np.random.seed(random_seed) - - # Generate features - data = { - "age": np.random.randint(25, 80, n_samples), - "gender": np.random.randint(0, 2, n_samples), - "cp": np.random.randint(0, 4, n_samples), - "trtbps": np.random.randint(90, 200, n_samples), - "chol": np.random.randint(120, 400, n_samples), - "fbs": np.random.randint(0, 2, n_samples), - "restecg": np.random.randint(0, 3, n_samples), - "thalachh": np.random.randint(70, 220, n_samples), - "exng": np.random.randint(0, 2, n_samples), - "oldpeak": np.round(np.random.uniform(0, 6, n_samples), 1), - "slp": np.random.randint(0, 3, n_samples), - "caa": np.random.randint(0, 5, n_samples), - "thall": np.random.randint(0, 4, n_samples), - } - - # Generate target based on risk factors - risk_factors = ( - (data["age"] > 60).astype(int) * 2 # Age over 60 is high risk - + data["gender"] # Being male slightly increases risk - + (data["cp"] > 1).astype(int) * 2 # Higher chest pain types increase risk - + (data["trtbps"] > 140).astype(int) # High blood pressure - + (data["chol"] > 250).astype(int) # High cholesterol - + data["fbs"] # High fasting blood sugar - + (data["thalachh"] < 120).astype(int) * 2 # Low max heart rate - + data["exng"] * 2 # Exercise-induced angina - + (data["oldpeak"] > 2).astype(int) * 2 # High ST depression - + data["caa"] # Number of major vessels - ) - - # Convert risk factors to binary output (threshold chosen to get roughly balanced classes) - data["output"] = (risk_factors > 8).astype(int) - - return pd.DataFrame(data) - - -def generate_house_prices_data(n_samples=30, random_seed=42): - """Generate synthetic house price data for regression testing. - - The data follows the structure: - - area: int (square feet, 800-5000) - - bedrooms: int (1-6) - - bathrooms: int (1-5) - - stories: int (1-4) - - garage: int (0-3 cars) - - garden: int (0=no, 1=yes) - - fenced: int (0=no, 1=yes) - - age: int (years, 0-100) - - price: float (house price in thousands, 100-2000) - """ - np.random.seed(random_seed) - - # Generate features - data = { - "area": np.random.randint(800, 5000, n_samples), - "bedrooms": np.random.randint(1, 7, n_samples), - "bathrooms": np.random.randint(1, 6, n_samples), - "stories": np.random.randint(1, 5, n_samples), - "garage": np.random.randint(0, 4, n_samples), - "garden": np.random.randint(0, 2, n_samples), - "fenced": np.random.randint(0, 2, n_samples), - "age": np.random.randint(0, 101, n_samples), - } - - # Generate price based on features - # Base price - price = 100 + np.random.normal(0, 20, n_samples) - - # Add impact of features - price += data["area"] * 0.2 # Larger area increases price - price += data["bedrooms"] * 25 # More bedrooms increase price - price += data["bathrooms"] * 35 # More bathrooms increase price - price += data["stories"] * 30 # More stories increase price - price += data["garage"] * 40 # Garage increases price - price += data["garden"] * 50 # Garden increases price - price += data["fenced"] * 25 # Fenced yard increases price - price -= data["age"] * 1.5 # Older houses decrease in price - - # Add some noise - price += np.random.normal(0, 50, n_samples) - - # Ensure reasonable price range - price = np.clip(price, 100, 2000) - data["price"] = np.round(price, 2) - - return pd.DataFrame(data) - - -def generate_customer_churn_data(n_samples=30, random_seed=42): - """Generate synthetic customer churn data for classification testing. - - The data follows the structure: - - tenure: int (months, 0-100) - - monthly_charges: float (dollars, 20-150) - - total_charges: float (dollars, 0-10000) - - contract_type: int (0=month-to-month, 1=one year, 2=two year) - - payment_method: int (0=electronic check, 1=mailed check, 2=bank transfer, 3=credit card) - - tech_support: int (0=no, 1=yes) - - online_backup: int (0=no, 1=yes) - - online_security: int (0=no, 1=yes) - - churn: int (0=no, 1=yes) - """ - np.random.seed(random_seed) - - # Generate features - data = { - "tenure": np.random.randint(1, 101, n_samples), - "monthly_charges": np.round(np.random.uniform(20, 150, n_samples), 2), - "contract_type": np.random.randint(0, 3, n_samples), - "payment_method": np.random.randint(0, 4, n_samples), - "tech_support": np.random.randint(0, 2, n_samples), - "online_backup": np.random.randint(0, 2, n_samples), - "online_security": np.random.randint(0, 2, n_samples), - } - - # Calculate total charges based on tenure and monthly charges - # Add some variance to simulate different starting points and promotional offers - variance_factor = np.random.uniform(0.8, 1.2, n_samples) - data["total_charges"] = np.round(data["tenure"] * data["monthly_charges"] * variance_factor, 2) - - # Generate churn based on risk factors - risk_factors = ( - (data["tenure"] < 12).astype(int) * 3 # Low tenure is high risk - + (data["monthly_charges"] > 100).astype(int) * 2 # High monthly charges - + (data["contract_type"] == 0).astype(int) * 3 # Month-to-month contracts are higher risk - + (data["payment_method"] == 0).astype(int) * 2 # Electronic check is higher risk - - data["tech_support"] * 1 # Having tech support reduces risk - - data["online_backup"] * 1 # Having online backup reduces risk - - data["online_security"] * 1 # Having online security reduces risk - ) - - # Convert risk factors to binary churn (threshold chosen to get roughly balanced classes) - data["churn"] = (risk_factors > 5).astype(int) - data["churn_probability"] = np.round(np.clip(risk_factors / 10, 0, 1), 2) # Probability of churn - - return pd.DataFrame(data) - - -def generate_sentiment_data(n_samples=20, random_seed=42): - """Generate synthetic sentiment analysis data for text classification testing. - - The data follows the structure: - - text: str (review text) - - sentiment: str (positive, negative, or neutral) - """ - np.random.seed(random_seed) - - positive_texts = [ - "This product exceeded my expectations!", - "Great service and amazing quality", - "I absolutely love this product", - "Best purchase I've ever made", - "Fantastic experience overall", - "The customer service was exceptional", - "Very satisfied with my purchase", - "Would definitely recommend to friends", - "Works perfectly for what I need", - "Very happy with the quality and speed of delivery", - ] - - negative_texts = [ - "Very disappointed with the quality", - "Would not recommend this", - "Poor service and slow delivery", - "Product broke after first use", - "Waste of money", - "Customer service was terrible", - "Not as described in the listing", - "Overpriced for what you get", - "Save your money and buy something else", - "Regret making this purchase", - ] - - neutral_texts = [ - "Product was ok, nothing special", - "Meets basic expectations", - "Delivery was on time", - "Average quality for the price", - "Some features work well, others don't", - "Neither impressed nor disappointed", - "Does the job but could be better", - "Might purchase again, still deciding", - "Mixed feelings about this product", - "Not bad, not great", - ] - - # Create balanced dataset with roughly equal numbers of each sentiment - data = [] - categories = ["positive", "negative", "neutral"] - text_sources = [positive_texts, negative_texts, neutral_texts] - - for i in range(n_samples): - cat_idx = i % 3 - text_idx = np.random.randint(0, len(text_sources[cat_idx])) - data.append({"text": text_sources[cat_idx][text_idx], "sentiment": categories[cat_idx]}) - - # Shuffle the data - np.random.shuffle(data) - - return pd.DataFrame(data) - - -def generate_product_recommendation_data(n_samples=30, random_seed=42): - """Generate synthetic product recommendation data. - - The data follows the structure: - - order_id: str (unique order identifier) - - style: str (product style code) - - category: str (product category) - - customer_id: str (customer identifier) - """ - np.random.seed(random_seed) - - # Define product categories and styles - categories = ["Clothing", "Electronics", "Home", "Beauty", "Books"] - - # Generate unique style codes for each category - styles_by_category = {} - for category in categories: - prefix = category[:3].upper() - styles_by_category[category] = [f"{prefix}{100 + i}" for i in range(10)] - - # Flatten all styles - all_styles = [style for styles in styles_by_category.values() for style in styles] - - # Create customer IDs - customer_ids = [f"CUST{1000 + i}" for i in range(10)] - - # Generate purchase patterns - # Each customer has preferences for certain categories and styles - customer_preferences = {} - for cust_id in customer_ids: - # Pick 2-3 preferred categories - preferred_cats = np.random.choice(categories, size=np.random.randint(2, 4), replace=False) - # For each preferred category, pick 2-3 preferred styles - preferred_styles = [] - for cat in preferred_cats: - preferred_styles.extend( - np.random.choice(styles_by_category[cat], size=np.random.randint(2, 4), replace=False) - ) - customer_preferences[cust_id] = preferred_styles - - # Generate orders - data = [] - order_ids = [] - - # Create order IDs - for i in range(n_samples // 3): # Each order will have multiple items - order_ids.append(f"ORD{10000 + i}") - - # Generate order data - for order_id in order_ids: - # Pick a random customer - customer_id = np.random.choice(customer_ids) - # Decide number of items in this order (2-5) - n_items = np.random.randint(2, 6) - - # 70% chance the customer buys from their preferences - if np.random.random() < 0.7: - # Pick from their preferred styles - styles = np.random.choice( - customer_preferences[customer_id], - size=min(n_items, len(customer_preferences[customer_id])), - replace=False, - ) - else: - # Pick random styles - styles = np.random.choice(all_styles, size=n_items, replace=False) - - # Add items to data - for style in styles: - # Find category of this style - for cat, cat_styles in styles_by_category.items(): - if style in cat_styles: - category = cat - break - - data.append({"order_id": order_id, "style": style, "category": category, "customer_id": customer_id}) - - return pd.DataFrame(data) - - -def generate_time_series_data(n_samples=60, random_seed=42): - """Generate synthetic time series data for forecasting testing. - - The data follows the structure: - - date: date (time index) - - sales: float (sales amount) - - promo: int (0=no promotion, 1=promotion running) - - holiday: int (0=no holiday, 1=holiday) - - day_of_week: int (0-6, Monday=0) - """ - np.random.seed(random_seed) - - # Generate dates - start_date = pd.to_datetime("2023-01-01") - dates = [start_date + pd.Timedelta(days=i) for i in range(n_samples)] - - # Generate features - day_of_week = [date.weekday() for date in dates] - - # Holidays (random 7% of days are holidays) - holiday = np.zeros(n_samples) - holiday_indices = np.random.choice(range(n_samples), size=int(n_samples * 0.07), replace=False) - holiday[holiday_indices] = 1 - - # Promotions (random 20% of days have promotions) - promo = np.zeros(n_samples) - promo_indices = np.random.choice(range(n_samples), size=int(n_samples * 0.2), replace=False) - promo[promo_indices] = 1 - - # Generate sales with trend, seasonality, and effects of promotions and holidays - # Base trend (slightly increasing) - trend = np.linspace(0, 20, n_samples) - - # Weekly seasonality (higher on weekends) - seasonality = np.array([5 if dow >= 5 else 0 for dow in day_of_week]) - - # Promotion and holiday effects - promo_effect = promo * 25 - holiday_effect = holiday * 15 - - # Combine effects - sales = 100 + trend + seasonality + promo_effect + holiday_effect - - # Add noise - sales += np.random.normal(0, 10, n_samples) - - # Ensure sales are positive - sales = np.maximum(0, sales) - - # Create DataFrame - data = pd.DataFrame( - { - "date": dates, - "sales": np.round(sales, 2), - "promo": promo.astype(int), - "holiday": holiday.astype(int), - "day_of_week": day_of_week, - } - ) - - return data - - -def verify_prediction(prediction, expected_schema=None): - """Verify that a prediction matches expected format.""" - assert isinstance(prediction, dict), "Prediction should be a dictionary" - assert len(prediction) > 0, "Prediction should not be empty" - - if expected_schema: - schema_keys = getattr(expected_schema, "model_fields", None) - if schema_keys is not None: - schema_keys = set(schema_keys.keys()) - else: - schema_keys = set(expected_schema.keys()) - - assert ( - set(prediction.keys()) == schema_keys - ), f"Prediction keys {prediction.keys()} don't match schema keys {schema_keys}" - - # Check first value to ensure it's of expected type - output_value = list(prediction.values())[0] - if isinstance(output_value, list): - # If the output is a list, check that it's not empty - assert len(output_value) > 0, "Prediction list should not be empty" - else: - # If output is not a list, check that it's one of the expected types - assert isinstance( - output_value, (int, float, str) - ), f"Prediction value should be numeric, string, or list, got {type(output_value)}" - - -def verify_model_description(description): - """Verify that a model description contains expected fields.""" - assert isinstance(description, ModelDescription), "Model description should be a 'ModelDescription' object" - required_fields = ["intent", "schemas", "code"] - for field in required_fields: - assert hasattr(description, field), f"Model description missing required field: {field}" - - -def cleanup_files(model_dir=None): - """Clean up any files created during tests.""" - files_to_clean = [ - "plexe.log", - "*.pmb", - "*.tar.gz", - ] - - # Clean up files in current directory - for pattern in files_to_clean: - try: - for file in Path(".").glob(pattern): - if file.is_file(): - file.unlink() - except Exception as e: - print(f"Failed to clean up {pattern}: {e}") - - # Clean up files in model directory - if model_dir is not None and Path(model_dir).exists(): - try: - # Use rmtree to recursively remove directory and contents - shutil.rmtree(model_dir, ignore_errors=True) - except Exception as e: - print(f"Failed to clean up {model_dir}: {e}") - # If rmtree fails, try to at least clean individual files - for file in Path(model_dir).glob("*"): - try: - if file.is_file(): - file.unlink(missing_ok=True) - elif file.is_dir(): - shutil.rmtree(file, ignore_errors=True) - except Exception as e: - print(f"Failed to clean up {file}: {e}") From 4444f3ad516498f62c26ad408b1ef248a2094124 Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Fri, 23 Jan 2026 01:01:36 +0700 Subject: [PATCH 41/42] chore: delete useless files --- plexe/templates/__init__.py | 1 - .../models/feature_transformer.tmpl.py | 20 ------------------- plexe/templates/models/predictor.tmpl.py | 19 ------------------ 3 files changed, 40 deletions(-) delete mode 100644 plexe/templates/__init__.py delete mode 100644 plexe/templates/models/feature_transformer.tmpl.py delete mode 100644 plexe/templates/models/predictor.tmpl.py diff --git a/plexe/templates/__init__.py b/plexe/templates/__init__.py deleted file mode 100644 index 3ec88647..00000000 --- a/plexe/templates/__init__.py +++ /dev/null @@ -1 +0,0 @@ -# Templates module for plexe diff --git a/plexe/templates/models/feature_transformer.tmpl.py b/plexe/templates/models/feature_transformer.tmpl.py deleted file mode 100644 index 17878ba1..00000000 --- a/plexe/templates/models/feature_transformer.tmpl.py +++ /dev/null @@ -1,20 +0,0 @@ -""" -Placeholder feature transformer template for backward compatibility. -The LangGraph system generates code directly without templates. -""" - -class FeatureTransformer: - """Base feature transformer interface.""" - - def __init__(self): - pass - - def fit(self, data): - raise NotImplementedError("Subclasses must implement fit()") - - def transform(self, data): - raise NotImplementedError("Subclasses must implement transform()") - - def fit_transform(self, data): - self.fit(data) - return self.transform(data) diff --git a/plexe/templates/models/predictor.tmpl.py b/plexe/templates/models/predictor.tmpl.py deleted file mode 100644 index 819e969b..00000000 --- a/plexe/templates/models/predictor.tmpl.py +++ /dev/null @@ -1,19 +0,0 @@ -""" -Placeholder predictor template for backward compatibility. -The LangGraph system generates code directly without templates. -""" - -class Predictor: - """Base predictor interface.""" - - def __init__(self): - pass - - def predict(self, input_data): - raise NotImplementedError("Subclasses must implement predict()") - - def load(self, path): - raise NotImplementedError("Subclasses must implement load()") - - def save(self, path): - raise NotImplementedError("Subclasses must implement save()") From 468644a649dc191ae90dc67e0f9e17f096db4a42 Mon Sep 17 00:00:00 2001 From: Dr-Heimerdinger Date: Mon, 26 Jan 2026 11:41:24 +0700 Subject: [PATCH 42/42] :sparkles:feat: Applying MCP but does not test full pipeline --- .env.example | 8 + .gitignore | 1 + CODE_OF_CONDUCT.md | 128 ----- CONTRIBUTING.md | 108 ---- DOCKER_QUICKSTART.md | 225 -------- Dockerfile.gpu | 5 +- README.md | 214 ++----- SECURITY.md | 11 - automl-agent | 1 + docker-compose.gpu.yml | 18 + .../langgraph-multi-agent-system.md | 87 ++- docs/external-api-setup.md | 162 ++++++ docs/mcp-hpo-explanation.md | 283 ++++++++++ examples/rel-f1-driver-dnf.txt | 1 + feature_transformer.py | 104 ---- feature_transformer_code.py | 104 ---- mcp_config.json | 41 ++ paper/AutoML_Agent.pdf | Bin 0 -> 1841386 bytes Graph.pdf => paper/Graph.pdf | Bin paper/Relbench.pdf | Bin 0 -> 2020684 bytes plexe/langgraph/agents/base.py | 157 ++++- plexe/langgraph/agents/conversational.py | 101 ++-- plexe/langgraph/agents/dataset_builder.py | 212 +------ plexe/langgraph/agents/eda.py | 192 ++----- plexe/langgraph/agents/gnn_specialist.py | 223 ++++---- plexe/langgraph/agents/operation.py | 136 +++-- plexe/langgraph/agents/task_builder.py | 286 ++++------ plexe/langgraph/config.py | 35 ++ plexe/langgraph/mcp_manager.py | 146 +++++ plexe/langgraph/mcp_servers/arxiv_server.py | 66 +++ plexe/langgraph/mcp_servers/hpo_server.py | 457 +++++++++++++++ plexe/langgraph/mcp_servers/kaggle_server.py | 45 ++ plexe/langgraph/mcp_servers/scholar_server.py | 53 ++ .../mcp_servers/semantic_scholar_server.py | 71 +++ plexe/langgraph/orchestrator.py | 94 ++- plexe/langgraph/prompts/__init__.py | 21 + plexe/langgraph/prompts/conversational.py | 34 ++ plexe/langgraph/prompts/dataset_builder.py | 104 ++++ plexe/langgraph/prompts/eda.py | 30 + plexe/langgraph/prompts/gnn_specialist.py | 60 ++ plexe/langgraph/prompts/operation.py | 40 ++ plexe/langgraph/prompts/task_builder.py | 245 ++++++++ plexe/langgraph/tools/__init__.py | 6 - plexe/langgraph/tools/common.py | 5 - plexe/langgraph/tools/conversational.py | 5 - plexe/langgraph/tools/dataset_builder.py | 7 +- plexe/langgraph/tools/eda.py | 8 +- plexe/langgraph/tools/external_api_clients.py | 355 ++++++++++++ plexe/langgraph/tools/gnn_specialist.py | 5 - plexe/langgraph/tools/graph_architect.py | 5 - plexe/langgraph/tools/hpo_search.py | 534 ++++++++++++++++++ plexe/langgraph/tools/task_builder.py | 14 +- plexe/langgraph/utils/__init__.py | 54 ++ plexe/langgraph/utils/callbacks.py | 73 +++ plexe/langgraph/utils/emitters.py | 234 ++++++++ plexe/langgraph/utils/file_utils.py | 66 +++ .../langgraph/{utils.py => utils/helpers.py} | 72 +-- plexe/langgraph/utils/progress.py | 20 + plexe/server.py | 105 ++-- plexe/ui/frontend/src/components/Chat.jsx | 223 +++++++- plexe/ui/frontend/src/styles.css | 307 ++++++++-- plexe/ui/frontend/vite.config.js | 4 +- plexe/ui/index.html | 2 +- pyproject.toml | 8 + resources/backed-by-yc.png | Bin 68367 -> 0 bytes resources/demo-thumbnail.png | Bin 1984201 -> 0 bytes test_mcp_hpo_integration.py | 214 +++++++ test_training_table.py | 32 +- 68 files changed, 4754 insertions(+), 1913 deletions(-) delete mode 100644 CODE_OF_CONDUCT.md delete mode 100644 CONTRIBUTING.md delete mode 100644 DOCKER_QUICKSTART.md delete mode 100644 SECURITY.md create mode 160000 automl-agent create mode 100644 docs/external-api-setup.md create mode 100644 docs/mcp-hpo-explanation.md delete mode 100644 feature_transformer.py delete mode 100644 feature_transformer_code.py create mode 100644 mcp_config.json create mode 100644 paper/AutoML_Agent.pdf rename Graph.pdf => paper/Graph.pdf (100%) create mode 100644 paper/Relbench.pdf create mode 100644 plexe/langgraph/mcp_manager.py create mode 100644 plexe/langgraph/mcp_servers/arxiv_server.py create mode 100644 plexe/langgraph/mcp_servers/hpo_server.py create mode 100644 plexe/langgraph/mcp_servers/kaggle_server.py create mode 100644 plexe/langgraph/mcp_servers/scholar_server.py create mode 100644 plexe/langgraph/mcp_servers/semantic_scholar_server.py create mode 100644 plexe/langgraph/prompts/__init__.py create mode 100644 plexe/langgraph/prompts/conversational.py create mode 100644 plexe/langgraph/prompts/dataset_builder.py create mode 100644 plexe/langgraph/prompts/eda.py create mode 100644 plexe/langgraph/prompts/gnn_specialist.py create mode 100644 plexe/langgraph/prompts/operation.py create mode 100644 plexe/langgraph/prompts/task_builder.py create mode 100644 plexe/langgraph/tools/external_api_clients.py create mode 100644 plexe/langgraph/tools/hpo_search.py create mode 100644 plexe/langgraph/utils/__init__.py create mode 100644 plexe/langgraph/utils/callbacks.py create mode 100644 plexe/langgraph/utils/emitters.py create mode 100644 plexe/langgraph/utils/file_utils.py rename plexe/langgraph/{utils.py => utils/helpers.py} (56%) create mode 100644 plexe/langgraph/utils/progress.py delete mode 100644 resources/backed-by-yc.png delete mode 100644 resources/demo-thumbnail.png create mode 100644 test_mcp_hpo_integration.py diff --git a/.env.example b/.env.example index e588422d..04a73402 100644 --- a/.env.example +++ b/.env.example @@ -27,4 +27,12 @@ PLEXE_ML_OPS_ENGINEER_MODEL="gemini/gemini-2.5-flash" PLEXE_TOOL_MODEL="gemini/gemini-2.5-flash" PLEXE_TOOL_FEATURE_GENERATOR_MODEL="gemini/gemini-2.5-flash" +# External API Keys for HPO Search and Literature Review +# Semantic Scholar API: https://www.semanticscholar.org/product/api#Partner-Form +SEMANTIC_SCHOLAR_API_KEY=your_semantic_scholar_api_key_here + +# OpenML API: https://www.openml.org/auth/sign-in +OPENML_API_KEY=your_openml_api_key_here + +# Hugging Face Token: https://huggingface.co/settings/tokens HF_TOKEN=??? \ No newline at end of file diff --git a/.gitignore b/.gitignore index 1a88ce25..040ed6d7 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,4 @@ +plexe-old/ # Byte-compiled / optimized / DLL files __pycache__/ *.py[cod] diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md deleted file mode 100644 index 8d9f11dc..00000000 --- a/CODE_OF_CONDUCT.md +++ /dev/null @@ -1,128 +0,0 @@ -# Contributor Covenant Code of Conduct - -## Our Pledge - -We as members, contributors, and leaders pledge to make participation in our -community a harassment-free experience for everyone, regardless of age, body -size, visible or invisible disability, ethnicity, sex characteristics, gender -identity and expression, level of experience, education, socio-economic status, -nationality, personal appearance, race, religion, or sexual identity -and orientation. - -We pledge to act and interact in ways that contribute to an open, welcoming, -diverse, inclusive, and healthy community. - -## Our Standards - -Examples of behavior that contributes to a positive environment for our -community include: - -* Demonstrating empathy and kindness toward other people -* Being respectful of differing opinions, viewpoints, and experiences -* Giving and gracefully accepting constructive feedback -* Accepting responsibility and apologizing to those affected by our mistakes, - and learning from the experience -* Focusing on what is best not just for us as individuals, but for the - overall community - -Examples of unacceptable behavior include: - -* The use of sexualized language or imagery, and sexual attention or - advances of any kind -* Trolling, insulting or derogatory comments, and personal or political attacks -* Public or private harassment -* Publishing others' private information, such as a physical or email - address, without their explicit permission -* Other conduct which could reasonably be considered inappropriate in a - professional setting - -## Enforcement Responsibilities - -Community leaders are responsible for clarifying and enforcing our standards of -acceptable behavior and will take appropriate and fair corrective action in -response to any behavior that they deem inappropriate, threatening, offensive, -or harmful. - -Community leaders have the right and responsibility to remove, edit, or reject -comments, commits, code, wiki edits, issues, and other contributions that are -not aligned to this Code of Conduct, and will communicate reasons for moderation -decisions when appropriate. - -## Scope - -This Code of Conduct applies within all community spaces, and also applies when -an individual is officially representing the community in public spaces. -Examples of representing our community include using an official e-mail address, -posting via an official social media account, or acting as an appointed -representative at an online or offline event. - -## Enforcement - -Instances of abusive, harassing, or otherwise unacceptable behavior may be -reported to the community leaders responsible for enforcement at -info@plexe.ai. -All complaints will be reviewed and investigated promptly and fairly. - -All community leaders are obligated to respect the privacy and security of the -reporter of any incident. - -## Enforcement Guidelines - -Community leaders will follow these Community Impact Guidelines in determining -the consequences for any action they deem in violation of this Code of Conduct: - -### 1. Correction - -**Community Impact**: Use of inappropriate language or other behavior deemed -unprofessional or unwelcome in the community. - -**Consequence**: A private, written warning from community leaders, providing -clarity around the nature of the violation and an explanation of why the -behavior was inappropriate. A public apology may be requested. - -### 2. Warning - -**Community Impact**: A violation through a single incident or series -of actions. - -**Consequence**: A warning with consequences for continued behavior. No -interaction with the people involved, including unsolicited interaction with -those enforcing the Code of Conduct, for a specified period of time. This -includes avoiding interactions in community spaces as well as external channels -like social media. Violating these terms may lead to a temporary or -permanent ban. - -### 3. Temporary Ban - -**Community Impact**: A serious violation of community standards, including -sustained inappropriate behavior. - -**Consequence**: A temporary ban from any sort of interaction or public -communication with the community for a specified period of time. No public or -private interaction with the people involved, including unsolicited interaction -with those enforcing the Code of Conduct, is allowed during this period. -Violating these terms may lead to a permanent ban. - -### 4. Permanent Ban - -**Community Impact**: Demonstrating a pattern of violation of community -standards, including sustained inappropriate behavior, harassment of an -individual, or aggression toward or disparagement of classes of individuals. - -**Consequence**: A permanent ban from any sort of public interaction within -the community. - -## Attribution - -This Code of Conduct is adapted from the [Contributor Covenant][homepage], -version 2.0, available at -https://www.contributor-covenant.org/version/2/0/code_of_conduct.html. - -Community Impact Guidelines were inspired by [Mozilla's code of conduct -enforcement ladder](https://github.com/mozilla/diversity). - -[homepage]: https://www.contributor-covenant.org - -For answers to common questions about this code of conduct, see the FAQ at -https://www.contributor-covenant.org/faq. Translations are available at -https://www.contributor-covenant.org/translations. diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md deleted file mode 100644 index a8c77c44..00000000 --- a/CONTRIBUTING.md +++ /dev/null @@ -1,108 +0,0 @@ -# Contributing to plexe - -Thank you for considering contributing to plexe! Your contributions help improve this project for everyone. - -## Table of Contents - -- [Code of Conduct](#code-of-conduct) -- [How Can I Contribute?](#how-can-i-contribute) - - [Reporting Bugs](#reporting-bugs) - - [Suggesting Enhancements](#suggesting-enhancements) - - [Submitting Pull Requests](#submitting-pull-requests) -- [Development Setup](#development-setup) -- [Style Guides](#style-guides) - - [Coding Standards](#coding-standards) - - [Commit Messages](#commit-messages) - -## Code of Conduct - -By participating in this project, you agree to uphold our [Code of Conduct](link-to-code-of-conduct), which outlines expectations for respectful and inclusive interactions. - -## How Can I Contribute? - -### Reporting Bugs - -If you encounter a bug, please: - -1. **Search Existing Issues**: Check if the issue has already been reported. -2. **Open a New Issue**: If not found, create a new issue and include: - - A descriptive title. - - Steps to reproduce the bug. - - Expected and actual behavior. - - Screenshots or code snippets, if applicable. - -### Suggesting Enhancements - -To propose new features or improvements: - -1. **Search Existing Issues**: Ensure the suggestion hasn't been made. -2. **Open a New Issue**: Provide: - - A clear description of the enhancement. - - Rationale for the suggestion. - - Any relevant examples or references. - -### Submitting Pull Requests - -For code contributions: - -1. **Fork the Repository**: Create your own copy of the repo. -2. **Create a Branch**: Use a descriptive name (e.g., `feature/new-model` or `bugfix/issue-123`). -3. **Make Changes**: Implement your changes with clear and concise code. -4. **Write Tests**: Ensure new features or bug fixes are covered by tests. -5. **Commit Changes**: Follow our commit message guidelines. -6. **Push to Your Fork**: Upload your changes. -7. **Open a Pull Request**: Provide a detailed description of your changes and reference any related issues. - -## Development Setup - -To set up the development environment: - -1. **Clone the Repository**: - - ```bash - git clone https://github.com/plexe-ai/plexe.git - cd plexe - ``` - -2. **Install Dependencies**: - - ``` - -pip install poetry - -poetry env activate or poetry shell depending on the Poetry version being used - -python setup.py - ``` - - -3. **Run Tests**: - - ```bash - pytest - ``` - -Ensure all tests pass before making contributions. - -## Style Guides - -### Coding Standards - -Adhere to PEP 8 guidelines for Python code. Key points include: - -- Use 4 spaces per indentation level. -- Limit lines to 79 characters. -- Use meaningful variable and function names. -- Include docstrings for all public modules, classes, and functions. - -### Commit Messages - -Write clear and concise commit messages: - -- **Format**: `(): ` - - **Type**: `feat`, `fix`, `docs`, `style`, `refactor`, `test`, `chore` - - **Scope**: Optional, e.g., `data`, `model` - - **Subject**: Brief description (max 50 characters) - -- **Example**: - - ```bash - feat(model): add support for gemini - ``` diff --git a/DOCKER_QUICKSTART.md b/DOCKER_QUICKSTART.md deleted file mode 100644 index 48a957e1..00000000 --- a/DOCKER_QUICKSTART.md +++ /dev/null @@ -1,225 +0,0 @@ -# Quick Start Guide - Plexe with Docker - -## 🚀 Fastest Way to Run Plexe - -### Option A: Development Build (Recommended for Quick Start) - -**Faster (2-3 min), but no torch/transformers:** - -```bash -cd /home/admin1/plexe-clone - -# Build with dev config (fast, no torch) -docker compose -f docker-compose.dev.yml build - -# Start services -docker compose -f docker-compose.dev.yml up -d - -# Access services (same ports as production) -# Frontend: http://localhost:3000 -# Backend: http://localhost:8000 -``` - -### Option B: Production Build (Full Features) - -**Slower (5-10 min), but includes torch/transformers:** - -```bash -cd /home/admin1/plexe-clone - -# Build with prod config (full features) -docker compose build - -# Start services -docker compose up -d -``` - -### Step 3: Access - -Open in browser: -- **Frontend**: http://localhost:3000 -- **Backend API**: http://localhost:8000 -- **MLflow**: http://localhost:5000 -- **pgAdmin**: http://localhost:8080 (admin@example.com / admin) - -### Step 4: Check Status - -```bash -# See all containers -docker compose ps -# or for dev: -docker compose -f docker-compose.dev.yml ps - -# See logs -docker compose logs -f frontend -# or for dev: -docker compose -f docker-compose.dev.yml logs -f frontend - -# Check if backend is healthy -curl http://localhost:8000/health -``` - -## 🛑 Stop Services - -```bash -# Stop all (data persists) -docker compose down - -# Stop and remove volumes (⚠️ deletes data) -docker compose down -v -``` - -## 🔄 Development Workflow - -### When You Change Python Code - -```bash -# Rebuild backend (fast, uses cache) -docker compose build backend -docker compose up -d -``` - -### When You Change Frontend Code - -```bash -# Rebuild frontend -docker compose build frontend -docker compose up -d -``` - -### When You Change pyproject.toml - -```bash -# Rebuild backend (includes dependency install) -docker compose build --no-cache backend -docker compose up -d -``` - -### Local Frontend Dev (Hot Reload) - -```bash -# In terminal 1: Start backend + database only -docker compose up postgres mlflow pgadmin - -# In terminal 2: Run frontend with hot reload -cd plexe/ui/frontend -npm install -npm run dev -# Opens http://localhost:5173 -``` - -## 📦 What's Running - -| Service | URL | Port | Purpose | -|---------|-----|------|---------| -| Frontend | http://localhost:3000 | 3000 | React UI | -| Backend | http://localhost:8000 | 8000 | FastAPI + /ws | -| MLflow | http://localhost:5000 | 5000 | Experiment tracking | -| pgAdmin | http://localhost:8080 | 8080 | Database UI | -| Postgres | localhost:5432 | 5432 | Database | - -## 🔗 How Services Connect - -``` -Browser (localhost:3000) - ↓ -Frontend (nginx, port 3000) - ├─→ /ws ──→ nginx proxy ──→ Backend (port 8000) - ├─→ /api ──→ nginx proxy ──→ Backend (port 8000) - └─→ /static ──→ Serve React files - ↓ -Backend (FastAPI, port 8000) - ├─→ Postgres (port 5432) - └─→ MLflow (port 5000) -``` - -## ❓ FAQ - -### Q: Why is it slow the first time? - -A: Docker builds images from scratch. Subsequent runs are 10x faster (cache). - -### Q: Status says "Disconnected"? - -A: Usually means: -1. Backend still starting (wait 10s) -2. Check logs: `docker compose logs -f backend` -3. Verify backend is healthy: `curl http://localhost:8000/health` - -### Q: Can't connect to database? - -A: Postgres needs time to start. Check logs: -```bash -docker compose logs postgres -``` - -### Q: Want to use my own database? - -Edit `.env`: -```env -POSTGRES_HOST=my-postgres-server -POSTGRES_PORT=5432 -``` - -### Q: How to debug WebSocket issues? - -```bash -# Check backend logs -docker compose logs -f backend - -# Test WebSocket directly -wscat -c ws://localhost:3000/ws -``` - -### Q: Can I run frontend without Docker? - -Yes! Dev mode: -```bash -cd plexe/ui/frontend -npm install -npm run dev -# Then also run: docker compose up postgres mlflow pgadmin backend -``` - -## 🎯 Common Commands - -```bash -# View all logs -docker compose logs -f - -# View specific service logs -docker compose logs -f frontend - -# Access container shell -docker compose exec backend bash - -# Rebuild everything -docker compose build -docker compose up -d - -# Clean up everything (keeps data) -docker compose down - -# Clean up everything (removes data too!) -docker compose down -v - -# Check service status -docker compose ps - -# Restart a service -docker compose restart backend - -# View service details -docker compose config -``` - -## 📚 More Info - -- Docker guide: `docs/docker.md` -- Docker performance tips: `docs/docker-performance.md` -- PostgreSQL setup: `docs/postgres.md` -- Frontend dev: `plexe/ui/frontend/README.md` - ---- - -**Next**: Open http://localhost:3000 and start building ML models! 🚀 diff --git a/Dockerfile.gpu b/Dockerfile.gpu index e062e156..42d7e18d 100644 --- a/Dockerfile.gpu +++ b/Dockerfile.gpu @@ -44,7 +44,8 @@ RUN uv pip install \ litellm statsmodels hypothesis "numpy<2.0.0" black jinja2 platformdirs \ "ray>=2.9.0" rich smolagents deprecated python-multipart psycopg2-binary \ featuretools sqlalchemy pytorch-frame pooch duckdb scipy \ - fastapi "uvicorn[standard]" websockets langgraph langchain langchain-openai langchain-google-genai angchain-anthropic + fastapi "uvicorn[standard]" websockets langgraph langchain langchain-openai langchain-google-genai langchain-anthropic \ + requests openml scholarly kaggle "mcp[all]" nest_asyncio # ---------------------------- # BƯỚC 3: Cài torchvision, torchaudio (torch đã có sẵn từ base image) @@ -91,7 +92,7 @@ import sentence_transformers print("sentence-transformers:", sentence_transformers.__version__) import mlflow print("MLflow:", mlflow.__version__) -from plexe import Model, PlexeOrchestrator +from plexe import PlexeOrchestrator print("plexe import OK") from plexe.langgraph import EDAAgent, ConversationalAgent print("LangGraph agents OK") diff --git a/README.md b/README.md index 123aebfa..12edbcd6 100644 --- a/README.md +++ b/README.md @@ -1,196 +1,48 @@ -

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langchain_core.messages import HumanMessage, AIMessage, SystemMessage -from langgraph.prebuilt import create_react_agent +from langchain_core.messages import HumanMessage, AIMessage, SystemMessage, ToolMessage +from langchain_core.callbacks import BaseCallbackHandler +from langchain.agents import create_agent from plexe.langgraph.config import AgentConfig, get_llm_from_model_id from plexe.langgraph.state import PipelineState +from plexe.langgraph.utils import BaseEmitter, ChainOfThoughtCallback +from plexe.langgraph.mcp_manager import MCPManager logger = logging.getLogger(__name__) +def extract_text_content(content) -> str: + """Extract text from message content (handles string or list format).""" + if isinstance(content, str): + return content + if isinstance(content, list): + parts = [] + for block in content: + if isinstance(block, str): + parts.append(block) + elif isinstance(block, dict) and block.get("type") == "text": + parts.append(block.get("text", "")) + return "".join(parts) + return str(content) if content else "" + + +class AgentCallbackHandler(BaseCallbackHandler): + """Callback handler for agent events with detailed chain-of-thought.""" + + def __init__(self, agent_name: str, emitter: Optional[BaseEmitter] = None): + self.agent_name = agent_name + self.emitter = emitter + self.current_thought = "" + + def on_llm_start(self, serialized, prompts, **kwargs): + if self.emitter: + model_name = "" + if isinstance(serialized, dict): + model_name = serialized.get("name", serialized.get("id", ["unknown"])[-1] if isinstance(serialized.get("id"), list) else "") + self.emitter.emit_thought(self.agent_name, f"Thinking with {model_name}..." if model_name else "Analyzing...") + + def on_llm_end(self, response, **kwargs): + if self.emitter and response and response.generations: + try: + text = extract_text_content(response.generations[0][0].text) + if text: + cleaned = text.strip() + if len(cleaned) > 300: + cleaned = cleaned[:300] + "..." + self.current_thought = cleaned + self.emitter.emit_thought(self.agent_name, f"Reasoning: {cleaned}") + except Exception as e: + logger.debug(f"Error extracting LLM response: {e}") + + def on_tool_start(self, serialized, input_str, **kwargs): + if self.emitter: + tool_name = serialized.get("name", "tool") if isinstance(serialized, dict) else "tool" + args = {} + if isinstance(input_str, str): + try: + import json + args = json.loads(input_str) if input_str.startswith("{") else {"input": input_str[:100]} + except: + args = {"input": str(input_str)[:100]} + elif isinstance(input_str, dict): + args = {k: str(v)[:50] for k, v in list(input_str.items())[:3]} + self.emitter.emit_tool_call(self.agent_name, tool_name, args) + + def on_tool_end(self, output, **kwargs): + if self.emitter and output: + output_str = str(output) if output else "" + if output_str: + # Format with newlines for better readability + formatted_output = output_str.replace('\\n', '\n') + self.emitter.emit_thought(self.agent_name, f"Tool result:\n{formatted_output}") + + def on_chain_error(self, error, **kwargs): + if self.emitter: + self.emitter.emit_thought(self.agent_name, f"Error encountered: {str(error)[:200]}") + class BaseAgent(ABC): """Base class for all LangGraph agents.""" @@ -26,6 +98,7 @@ def __init__( agent_type: str, config: Optional[AgentConfig] = None, tools: Optional[List[BaseTool]] = None, + emitter: Optional[BaseEmitter] = None, ): """ Initialize the base agent. @@ -34,15 +107,31 @@ def __init__( agent_type: Type identifier for this agent config: Agent configuration (uses defaults if None) tools: List of tools available to this agent + emitter: Optional emitter for progress callbacks """ self.agent_type = agent_type self.config = config or AgentConfig.from_env() - self.tools = tools or [] + self.emitter = emitter + # Initialize MCP Manager and load tools + import asyncio + self.mcp_manager = MCPManager() + try: + # We run this in a new loop or the current one to load tools during init + loop = asyncio.new_event_loop() + loop.run_until_complete(self.mcp_manager.initialize()) + mcp_tools = self.mcp_manager.get_tools() + if mcp_tools: + logger.info(f"Agent {self.name} loaded {len(mcp_tools)} MCP tools") + self.tools.extend(mcp_tools) + except Exception as e: + logger.warning(f"Could not load MCP tools for {self.name}: {e}") + model_id = self.config.get_model_for_agent(agent_type) self.llm = get_llm_from_model_id(model_id, self.config.temperature) self._agent = None + self._callback_handler = AgentCallbackHandler(self.name, emitter) @property @abstractmethod @@ -60,19 +149,24 @@ def description(self) -> str: """Return the agent description.""" return self.system_prompt[:200] + "..." + def set_emitter(self, emitter: BaseEmitter): + """Set the emitter for progress callbacks.""" + self.emitter = emitter + self._callback_handler = AgentCallbackHandler(self.name, emitter) + def get_agent(self): """Get or create the LangGraph agent.""" if self._agent is None: - self._agent = create_react_agent( + self._agent = create_agent( model=self.llm, tools=self.tools, - state_modifier=self.system_prompt, + system_prompt=self.system_prompt, ) return self._agent def invoke(self, state: PipelineState) -> Dict[str, Any]: """ - Invoke the agent with the current state. + Invoke the agent with the current state, streaming thoughts to emitter. Args: state: Current pipeline state @@ -83,19 +177,60 @@ def invoke(self, state: PipelineState) -> Dict[str, Any]: agent = self.get_agent() messages = self._build_messages(state) + logger.info(f"Agent {self.name} invoking with {len(messages)} messages") + + if self.emitter: + self.emitter.emit_agent_start(self.name) try: - result = agent.invoke({"messages": messages}) - return self._process_result(result, state) + config = {"callbacks": [self._callback_handler]} if self.emitter else {} + + result = None + for chunk in agent.stream({"messages": messages}, config=config, stream_mode="updates"): + for node_name, node_output in chunk.items(): + if self.emitter and node_name == "agent": + agent_messages = node_output.get("messages", []) + for msg in agent_messages: + if isinstance(msg, AIMessage): + content = extract_text_content(msg.content) + if content and len(content) > 20: + self.emitter.emit_thought(self.name, f"Thinking: {content[:400]}") + if hasattr(msg, 'tool_calls') and msg.tool_calls: + for tc in msg.tool_calls: + tool_name = tc.get("name", "unknown") + tool_args = tc.get("args", {}) + self.emitter.emit_tool_call(self.name, tool_name, tool_args) + result = node_output + + if result is None: + result = agent.invoke({"messages": messages}, config=config) + else: + result = result if result.get("messages") else {"messages": []} + + logger.info(f"Agent {self.name} received {len(result.get('messages', []))} response messages") + + processed = self._process_result(result, state) + + if self.emitter: + response_text = "" + for msg in processed.get("messages", []): + if msg.get("role") == "assistant": + response_text = msg.get("content", "")[:200] + break + self.emitter.emit_agent_end(self.name, response_text) + + return processed except Exception as e: - logger.error(f"Agent {self.name} failed: {e}") + logger.error(f"Agent {self.name} failed: {e}", exc_info=True) + if self.emitter: + self.emitter.emit_agent_end(self.name, f"Error: {str(e)}") return { "errors": [f"{self.name} error: {str(e)}"] } def _build_messages(self, state: PipelineState) -> List: """Build message list from state.""" - messages = [] + messages = [SystemMessage(content=self.system_prompt)] for msg in state.get("messages", []): role = msg.get("role", "user") @@ -154,7 +289,7 @@ def _process_result(self, result: Dict[str, Any], state: PipelineState) -> Dict[ if isinstance(msg, AIMessage): new_messages.append({ "role": "assistant", - "content": msg.content, + "content": extract_text_content(msg.content), "timestamp": None, }) diff --git a/plexe/langgraph/agents/conversational.py b/plexe/langgraph/agents/conversational.py index e58b9048..a6e9cff7 100644 --- a/plexe/langgraph/agents/conversational.py +++ b/plexe/langgraph/agents/conversational.py @@ -10,54 +10,15 @@ from langchain_core.tools import BaseTool -from plexe.langgraph.agents.base import BaseAgent +from plexe.langgraph.agents.base import BaseAgent, extract_text_content from plexe.langgraph.config import AgentConfig from plexe.langgraph.state import PipelineState, PipelinePhase from plexe.langgraph.tools.conversational import get_dataset_preview from plexe.langgraph.tools.graph_architect import validate_db_connection +from plexe.langgraph.prompts.conversational import CONVERSATIONAL_SYSTEM_PROMPT logger = logging.getLogger(__name__) - -CONVERSATIONAL_SYSTEM_PROMPT = """You are an expert ML and Deep Learning consultant helping users define their machine learning requirements through natural conversation. - -## Your Role -- Guide users through defining their ML problem clearly -- Understand their data and prediction goals -- Validate data availability and quality -- Initiate the ML pipeline when requirements are complete - -## Conversation Strategy -1. Ask ONE focused question at a time -2. Use tools to examine their data before asking detailed questions -3. Help refine vague statements into precise ML problem definitions -4. Summarize requirements and confirm before proceeding - -## Requirements Checklist (gather ALL before proceeding) -1. **Clear Problem Statement**: What exactly to predict/classify -2. **Input/Output Definition**: Model inputs and expected outputs -3. **Data Understanding**: Examined their data structure -4. **Data Source**: CSV files or database connection -5. **User Confirmation**: Explicit confirmation to start building - -## When Working with Databases -1. Use validate_db_connection to see available tables -2. Discuss what they want to predict -3. Clarify the target variable and entity -4. Gather all requirements before signaling readiness - -## Response Format -Keep responses conversational, friendly, and focused. Ask clarifying questions when needed. -When all requirements are gathered, summarize them and ask for final confirmation. - -## Important -- Do NOT rush to build models -- Ensure clarity on the prediction task -- Validate data accessibility -- Get explicit user confirmation before proceeding -""" - - class ConversationalAgent(BaseAgent): """Agent for conversational requirements gathering and user interaction.""" @@ -66,13 +27,6 @@ def __init__( config: Optional[AgentConfig] = None, additional_tools: Optional[List[BaseTool]] = None, ): - """ - Initialize the conversational agent. - - Args: - config: Agent configuration - additional_tools: Additional tools beyond defaults - """ tools = [ get_dataset_preview, validate_db_connection, @@ -99,7 +53,9 @@ def _process_result(self, result: Dict[str, Any], state: PipelineState) -> Dict[ last_message = messages[-1] if messages else None if last_message: - content = last_message.content.lower() if hasattr(last_message, 'content') else "" + raw_content = last_message.content if hasattr(last_message, 'content') else "" + content = extract_text_content(raw_content).lower() + logger.info(f"ConversationalAgent response: {content[:200]}...") ready_indicators = [ "ready to proceed", @@ -107,37 +63,50 @@ def _process_result(self, result: Dict[str, Any], state: PipelineState) -> Dict[ "begin training", "initiate pipeline", "all requirements gathered", + "let's begin", + "let me start", + "i'll start", + "proceed with", + "starting the pipeline", + "begin the process", ] if any(indicator in content for indicator in ready_indicators): + logger.info("Detected ready indicator, setting user_confirmation_required") base_result["user_confirmation_required"] = True + base_result["user_confirmed"] = True + base_result["user_intent"] = self._extract_intent_from_state(state) base_result["user_confirmation_context"] = { "type": "proceed_to_pipeline", - "message": "Ready to start the ML pipeline?" + "message": "Ready to start the ML pipeline" } + has_db = state.get("db_connection_string") + has_task = any("predict" in msg.get("content", "").lower() for msg in state.get("messages", [])) + if has_db and has_task and not base_result.get("user_intent"): + logger.info("Auto-detecting intent from state") + base_result["user_intent"] = self._extract_intent_from_state(state) + return base_result - def extract_intent(self, state: PipelineState) -> Dict[str, Any]: - """ - Extract structured intent from conversation. - - Returns: - Dictionary with extracted intent information - """ - messages = state.get("messages", []) - + def _extract_intent_from_state(self, state: PipelineState) -> Dict[str, Any]: + """Extract intent from state.""" intent = { "prediction_target": None, "entity_type": None, - "task_type": None, - "data_source": None, - "confirmed": False, + "task_type": "binary_classification", + "data_source": "database" if state.get("db_connection_string") else "csv", + "confirmed": True, } - if state.get("db_connection_string"): - intent["data_source"] = "database" - elif state.get("csv_dir"): - intent["data_source"] = "csv" + for msg in state.get("messages", []): + content = msg.get("content", "").lower() + if "predict" in content: + intent["prediction_target"] = msg.get("content", "")[:200] + if "churn" in content or "leave" in content or "cancel" in content: + intent["task_type"] = "binary_classification" + elif "count" in content or "amount" in content or "revenue" in content: + intent["task_type"] = "regression" + break return intent diff --git a/plexe/langgraph/agents/dataset_builder.py b/plexe/langgraph/agents/dataset_builder.py index ca750a02..b2eb9ff9 100644 --- a/plexe/langgraph/agents/dataset_builder.py +++ b/plexe/langgraph/agents/dataset_builder.py @@ -19,144 +19,10 @@ get_temporal_statistics, register_dataset_code, ) +from plexe.langgraph.prompts.dataset_builder import DATASET_BUILDER_SYSTEM_PROMPT logger = logging.getLogger(__name__) - -DATASET_BUILDER_SYSTEM_PROMPT = """You are the Dataset Builder Agent, an expert in building RelBench Database objects from raw CSV data. - -## Your Mission -Generate a complete Python Dataset class (GenDataset) that: -1. Loads CSV files from a specified directory -2. Processes and cleans the data appropriately -3. Defines the database schema (PKs, FKs, time columns) -4. Provides proper temporal splitting (val_timestamp, test_timestamp) - -## Workflow - -### Step 1: Discover CSV Files -Use get_csv_files_info to list available CSV files and their columns. - -### Step 2: Analyze Temporal Data -Use get_temporal_statistics to: -- Find timestamp columns in each table -- Get suggested val_timestamp and test_timestamp values -- Understand the temporal distribution of data - -### Step 3: Generate Dataset Code -Create a complete GenDataset class following this structure: - -```python -import os -import numpy as np -import pandas as pd -from typing import Optional -from plexe.relbench.base import Database, Dataset, Table - -class GenDataset(Dataset): - val_timestamp = pd.Timestamp("YYYY-MM-DD") - test_timestamp = pd.Timestamp("YYYY-MM-DD") - - def __init__(self, csv_dir: str, cache_dir: Optional[str] = None): - self.csv_dir = csv_dir - super().__init__(cache_dir=cache_dir) - - def make_db(self) -> Database: - path = self.csv_dir - - # 1. Load CSV files - # table_name = pd.read_csv(os.path.join(path, "table_name.csv")) - - # 2. Data cleaning (drop irrelevant columns, handle nulls) - - # 3. Time processing (parse timestamps, propagate from parent to child) - - # 4. Build and return Database - db = Database( - table_dict={ - "table_name": Table( - df=table_df, - fkey_col_to_pkey_table={"fk_col": "referenced_table"}, - pkey_col="primary_key_col", - time_col="timestamp_col", # or None for static tables - ), - # ... more tables - } - ) - return db -``` - -### Step 4: Register the Code -Use register_dataset_code to save the generated code. - -## Critical Concepts - -### Temporal Splitting -- val_timestamp: Rows up to this time for validation -- test_timestamp: Rows up to this time for test -- Choose based on data distribution (~70% for val, ~85% for test) - -### Table Definition -- pkey_col: Primary key (can be None for junction tables) -- fkey_col_to_pkey_table: Dict mapping FK columns to referenced tables -- time_col: Creation/event time (None for static dimension tables) - -### Data Cleaning Guidelines -- Drop columns with >50% nulls -- Drop URL/image columns (not useful for GNN) -- Handle database NULL markers (\\N -> NaN) -- Convert timestamps properly -- Propagate timestamps from parent to child tables when needed - -## Important -- Always use class name 'GenDataset' -- Use exact column names from CSV files (typically snake_case) -- Get val/test timestamps from get_temporal_statistics -- Register the code using register_dataset_code tool -""" - - -DATASET_CODE_TEMPLATE = '''""" -Auto-generated Dataset class for RelBench. -""" - -import os -import numpy as np -import pandas as pd -from typing import Optional - -from plexe.relbench.base import Database, Dataset, Table - - -class GenDataset(Dataset): - """Generated Dataset class for the relational database.""" - - val_timestamp = pd.Timestamp("{val_timestamp}") - test_timestamp = pd.Timestamp("{test_timestamp}") - - def __init__(self, csv_dir: str, cache_dir: Optional[str] = None): - self.csv_dir = csv_dir - super().__init__(cache_dir=cache_dir) - - def make_db(self) -> Database: - path = self.csv_dir - -{load_code} - -{cleaning_code} - -{time_processing_code} - - db = Database( - table_dict={{ -{table_dict_code} - }} - ) - - return db -''' - - class DatasetBuilderAgent(BaseAgent): """Agent for building RelBench Dataset classes from CSV data.""" @@ -165,13 +31,6 @@ def __init__( config: Optional[AgentConfig] = None, additional_tools: Optional[List[BaseTool]] = None, ): - """ - Initialize the dataset builder agent. - - Args: - config: Agent configuration - additional_tools: Additional tools beyond defaults - """ tools = [ get_csv_files_info, get_temporal_statistics, @@ -200,23 +59,23 @@ def _build_context(self, state: PipelineState) -> str: context_parts.append(f"Working directory: {state['working_dir']}") if state.get("csv_dir"): - context_parts.append(f"CSV files directory: {state['csv_dir']}") + context_parts.append(f"CSV directory: {state['csv_dir']}") if state.get("schema_info"): schema = state["schema_info"] tables = list(schema.get("tables", {}).keys()) - context_parts.append(f"Tables from schema: {', '.join(tables)}") + context_parts.append(f"Tables: {', '.join(tables)}") if schema.get("relationships"): - rels = [f"{r['source_table']}.{r['source_column']} -> {r['target_table']}" - for r in schema["relationships"]] - context_parts.append(f"Relationships: {'; '.join(rels)}") + rels = [] + for r in schema["relationships"]: + rels.append(f"{r['source_table']}.{r['source_column']} -> {r['target_table']}") + context_parts.append(f"Foreign keys: {'; '.join(rels)}") if schema.get("temporal_columns"): - temporal = [f"{t}: {cols}" for t, cols in schema["temporal_columns"].items()] - context_parts.append(f"Temporal columns: {'; '.join(temporal)}") + for table, cols in schema["temporal_columns"].items(): + context_parts.append(f"{table} time columns: {cols}") - # Include EDA information from previous phase if state.get("eda_info"): eda = state["eda_info"] context_parts.append("\n## EDA Analysis Results:") @@ -246,50 +105,41 @@ def _build_context(self, state: PipelineState) -> str: if isinstance(info, dict) and info.get("cardinality"): context_parts.append(f" - {key}: {info['cardinality']}") - task_instruction = """ -Your task: -1. Analyze the CSV files using get_csv_files_info -2. Get temporal statistics using get_temporal_statistics (use EDA suggestions if available) -3. Generate a complete GenDataset class with proper: - - Table loading - - Data cleaning (address quality issues found in EDA) - - Temporal processing - - Schema definition (PKs, FKs, time_cols) -4. Register the code using register_dataset_code + working_dir = state.get('working_dir', '') + csv_dir = state.get('csv_dir', '') + + task_instruction = f""" +YOUR TASK: +1. Call get_csv_files_info("{csv_dir}") to list all CSV files and columns +2. Call get_temporal_statistics("{csv_dir}") to analyze timestamps +3. Generate a complete GenDataset class following the template above +4. Call register_dataset_code(code, "GenDataset", "{working_dir}/dataset.py") to save it -The output file should be saved as 'dataset.py' in the working directory. +IMPORTANT: You MUST call register_dataset_code to save the dataset.py file! """ context_parts.append(task_instruction) return "\n".join(context_parts) def _process_result(self, result: Dict[str, Any], state: PipelineState) -> Dict[str, Any]: - """Process result and extract dataset information from tool calls.""" + """Process result and extract dataset information.""" base_result = super()._process_result(result, state) dataset_info = {} - generated_code = state.get("generated_code", {}) - - if "tool_calls" in result and result["tool_calls"]: - for tool_call in result["tool_calls"]: - tool_name = tool_call.get("name", "") - tool_result = tool_call.get("result", {}) - - if tool_name == "register_dataset_code" and tool_result.get("status") == "registered": - dataset_info["class_name"] = tool_result.get("class_name", "GenDataset") - dataset_info["file_path"] = tool_result.get("file_path") - if "code" in tool_result: - generated_code["dataset"] = tool_result["code"] + working_dir = state.get("working_dir", "") - if not dataset_info: + # Check if dataset.py was created + dataset_path = os.path.join(working_dir, "dataset.py") + if os.path.exists(dataset_path): dataset_info["class_name"] = "GenDataset" + dataset_info["file_path"] = dataset_path + logger.info(f"Dataset file created at: {dataset_path}") + else: + logger.warning(f"Dataset file not found at: {dataset_path}") + dataset_info["class_name"] = "GenDataset" + dataset_info["file_path"] = dataset_path - if dataset_info: - base_result["dataset_info"] = dataset_info - - if generated_code: - base_result["generated_code"] = generated_code - + base_result["dataset_info"] = dataset_info base_result["current_phase"] = PipelinePhase.TASK_BUILDING.value return base_result diff --git a/plexe/langgraph/agents/eda.py b/plexe/langgraph/agents/eda.py index 06a73b96..834e18fb 100644 --- a/plexe/langgraph/agents/eda.py +++ b/plexe/langgraph/agents/eda.py @@ -25,92 +25,10 @@ analyze_table_relationships, generate_eda_summary, ) +from plexe.langgraph.prompts.eda import EDA_SYSTEM_PROMPT logger = logging.getLogger(__name__) - -EDA_SYSTEM_PROMPT = """You are the EDA (Exploratory Data Analysis) Agent, an expert in Relational Deep Learning and data analysis. - -## Your Mission -1. Transform relational databases into Relational Entity Graphs where: - - Rows become nodes - - Primary-foreign key relationships become edges - - Preserving structural and temporal signals - -2. Perform comprehensive exploratory data analysis to understand: - - Data distributions and statistics - - Data quality issues - - Temporal patterns for time-series modeling - - Table relationships and classification - -## Workflow - -### Step 1: Database Export -- Use validate_db_connection to verify database access -- Use extract_schema_metadata to analyze schema (tables, PKs, FKs, temporal columns) -- Use export_tables_to_csv to export all tables to CSV format - -### Step 2: Statistical Analysis -- Use analyze_csv_statistics to get descriptive statistics for all columns -- Understand data distributions, missing values, and cardinality - -### Step 3: Data Quality Assessment -- Use detect_data_quality_issues to identify: - - High missing value rates (>50%) - - Constant columns - - Duplicate rows - - Potential ID columns - -### Step 4: Temporal Analysis -- Use analyze_temporal_patterns to: - - Identify temporal columns - - Analyze time ranges and gaps - - Suggest train/val/test temporal splits - -### Step 5: Relationship Analysis -- Use analyze_table_relationships to: - - Analyze foreign key statistics - - Classify tables as Fact vs Dimension - - Identify potential entity tables for prediction - -### Step 6: Generate Summary -- Use generate_eda_summary to create comprehensive report -- Provide key findings and recommendations for Dataset and Task builders - -## Key Concepts - -### Table Classification -- **Fact Tables**: Events/transactions with temporal data (orders, clicks) → Good entity tables -- **Dimension Tables**: Static entities (users, products) → Referenced by FKs -- **Junction Tables**: Many-to-many relationships - -### Data Quality Flags -- **High Severity**: greater than 50% missing values, critical for handling -- **Medium Severity**: 20-50% missing, duplicate rows -- **Low Severity**: Constant columns, all-unique columns - -### Temporal Patterns -- Identify timestamp columns with greater than 50% valid dates -- Calculate time ranges and average gaps -- Suggest 70/15/15 train/val/test splits based on temporal ordering - -## Output Requirements -Provide comprehensive EDA report including: -1. Statistical summary (row counts, column types, distributions) -2. Data quality assessment with severity flags -3. Temporal analysis with suggested splits -4. Table classification (Fact vs Dimension) -5. Recommendations for Dataset Builder (handle missing values, feature selection) -6. Recommendations for Task Builder (suggested entity tables, temporal splits) - -## Important Notes -- Always run EDA AFTER exporting CSV files -- Pass schema_info to analyze_table_relationships for better classification -- Store all EDA results in state for downstream agents -- Provide actionable insights, not just raw statistics -""" - - class EDAAgent(BaseAgent): """Agent for schema analysis, data export, and exploratory data analysis.""" @@ -119,13 +37,6 @@ def __init__( config: Optional[AgentConfig] = None, additional_tools: Optional[List[BaseTool]] = None, ): - """ - Initialize the EDA agent. - - Args: - config: Agent configuration - additional_tools: Additional tools beyond defaults - """ tools = [ validate_db_connection, export_tables_to_csv, @@ -156,62 +67,77 @@ def _build_context(self, state: PipelineState) -> str: if state.get("working_dir"): context_parts.append(f"Working directory: {state['working_dir']}") + context_parts.append(f"CSV output directory: {state['working_dir']}/csv_files") if state.get("db_connection_string"): - context_parts.append(f"Database connection: {state['db_connection_string']}") + context_parts.append(f"Database: {state['db_connection_string']}") if state.get("user_intent"): - context_parts.append(f"User intent: {state['user_intent']}") + intent = state["user_intent"] + if isinstance(intent, dict): + context_parts.append(f"Prediction target: {intent.get('prediction_target', 'unknown')}") + else: + context_parts.append(f"User intent: {intent}") - task_instruction = """ -Your task: -1. Connect to the database and validate the connection -2. Extract schema metadata (tables, PKs, FKs, temporal columns) -3. Export all tables to CSV files in the working directory -4. Perform comprehensive EDA: - - Statistical analysis of all columns - - Data quality assessment - - Temporal pattern analysis - - Table relationship analysis -5. Generate EDA summary with key findings and recommendations -6. Report results for Dataset Builder and Task Builder agents -""" - context_parts.append(task_instruction) + context_parts.append(""" +EXECUTE THESE STEPS: +1. extract_schema_metadata(db_connection_string) - analyze database schema +2. export_tables_to_csv(db_connection_string, working_dir/csv_files) - export data +3. analyze_csv_statistics(working_dir/csv_files) - get statistics +4. detect_data_quality_issues(working_dir/csv_files) - find issues +5. analyze_temporal_patterns(working_dir/csv_files) - find timestamps +6. analyze_table_relationships(working_dir/csv_files) - classify tables +7. generate_eda_summary(working_dir/csv_files) - create report +""") return "\n".join(context_parts) def _process_result(self, result: Dict[str, Any], state: PipelineState) -> Dict[str, Any]: - """Process result and extract schema/CSV/EDA information from tool calls.""" + """Process result and extract schema/CSV/EDA information.""" base_result = super()._process_result(result, state) eda_info = {} + working_dir = state.get("working_dir", "") + csv_dir = f"{working_dir}/csv_files" if working_dir else None + + messages = result.get("messages", []) + for msg in messages: + if hasattr(msg, 'tool_calls') and msg.tool_calls: + for tool_call in msg.tool_calls: + tool_name = tool_call.get("name", "") + tool_result = tool_call.get("result", {}) + + if tool_name == "export_tables_to_csv": + if csv_dir: + base_result["csv_dir"] = csv_dir + + if tool_name == "extract_schema_metadata": + if isinstance(tool_result, dict) and "tables" in tool_result: + base_result["schema_info"] = tool_result + + if tool_name == "analyze_csv_statistics" and isinstance(tool_result, dict): + if tool_result.get("status") == "success": + eda_info["statistics"] = tool_result.get("statistics") + + if tool_name == "detect_data_quality_issues" and isinstance(tool_result, dict): + if tool_result.get("status") == "success": + eda_info["quality_issues"] = tool_result.get("quality_issues") + + if tool_name == "analyze_temporal_patterns" and isinstance(tool_result, dict): + if tool_result.get("status") == "success": + eda_info["temporal_analysis"] = tool_result.get("temporal_analysis") + eda_info["suggested_splits"] = tool_result.get("suggested_splits") + + if tool_name == "analyze_table_relationships" and isinstance(tool_result, dict): + if tool_result.get("status") == "success": + eda_info["relationship_analysis"] = tool_result.get("relationship_analysis") + + if tool_name == "generate_eda_summary" and isinstance(tool_result, dict): + if tool_result.get("status") == "success": + eda_info["summary"] = tool_result.get("summary") - if "tool_calls" in result and result["tool_calls"]: - for tool_call in result["tool_calls"]: - tool_name = tool_call.get("name", "") - tool_result = tool_call.get("result", {}) - - if tool_name == "export_tables_to_csv" and tool_result.get("status") == "success": - base_result["csv_dir"] = tool_result.get("output_dir") - - if tool_name == "extract_schema_metadata" and "tables" in tool_result: - base_result["schema_info"] = tool_result - - if tool_name == "analyze_csv_statistics" and tool_result.get("status") == "success": - eda_info["statistics"] = tool_result.get("statistics") - - if tool_name == "detect_data_quality_issues" and tool_result.get("status") == "success": - eda_info["quality_issues"] = tool_result.get("quality_issues") - - if tool_name == "analyze_temporal_patterns" and tool_result.get("status") == "success": - eda_info["temporal_analysis"] = tool_result.get("temporal_analysis") - eda_info["suggested_splits"] = tool_result.get("suggested_splits") - - if tool_name == "analyze_table_relationships" and tool_result.get("status") == "success": - eda_info["relationship_analysis"] = tool_result.get("relationship_analysis") - - if tool_name == "generate_eda_summary" and tool_result.get("status") == "success": - eda_info["summary"] = tool_result.get("summary") + if csv_dir: + base_result["csv_dir"] = csv_dir if eda_info: base_result["eda_info"] = eda_info diff --git a/plexe/langgraph/agents/gnn_specialist.py b/plexe/langgraph/agents/gnn_specialist.py index 10e6f37f..cc1ef15a 100644 --- a/plexe/langgraph/agents/gnn_specialist.py +++ b/plexe/langgraph/agents/gnn_specialist.py @@ -14,105 +14,41 @@ from plexe.langgraph.config import AgentConfig from plexe.langgraph.state import PipelineState, PipelinePhase from plexe.langgraph.tools.common import save_artifact -from plexe.langgraph.tools.gnn_specialist import generate_training_script, execute_training_script +from plexe.langgraph.tools.gnn_specialist import generate_training_script +from plexe.langgraph.prompts.gnn_specialist import GNN_SPECIALIST_SYSTEM_PROMPT logger = logging.getLogger(__name__) - -GNN_SPECIALIST_SYSTEM_PROMPT = """You are the Relational GNN Specialist Agent, an expert in Graph Neural Networks for Relational Deep Learning. - -## Your Mission -Generate and execute GNN training scripts using the plexe.relbench.modeling modules to train on relational data. - -## Prerequisites -Before starting, you need: -1. dataset.py - Generated by DatasetBuilder (defines GenDataset class) -2. task.py - Generated by TaskBuilder (defines GenTask class) - -## Workflow - -### Step 1: Verify Prerequisites -Confirm that dataset.py and task.py exist in the working directory. - -### Step 2: Generate Training Script -Use generate_training_script with appropriate parameters: -- dataset_module_path: Path to dataset.py -- dataset_class_name: "GenDataset" -- task_module_path: Path to task.py -- task_class_name: "GenTask" -- task_type: From task_info (regression, binary_classification, multiclass_classification) -- tune_metric: Appropriate metric for the task type -- Training hyperparameters - -### Step 3: Execute Training -Use execute_training_script to run the generated script. - -### Step 4: Report Results -Report the training metrics and model performance. - -## Training Script Components -The generated script uses these plexe.relbench.modeling modules: - -### Graph Construction -- `make_pkey_fkey_graph`: Converts Database to HeteroData graph -- `get_node_train_table_input`: Prepares training input for NeighborLoader - -### Neural Network Modules -- `HeteroEncoder`: Encodes tabular features to embeddings -- `HeteroTemporalEncoder`: Encodes temporal information -- `HeteroGraphSAGE`: GNN message passing layers - -### Training Pipeline -1. Load Dataset and Task classes -2. Build heterogeneous graph from database -3. Create temporal neighbor loaders for train/val/test -4. Train GNN model with proper temporal sampling -5. Evaluate and save best model - -## Hyperparameter Guidelines -- epochs: 10-20 for initial training -- batch_size: 512 (adjust based on memory) -- learning_rate: 0.001-0.01 -- hidden_channels: 64-256 -- num_gnn_layers: 2-3 - -## Metrics by Task Type -- Regression: mae, rmse (lower is better) -- Binary Classification: accuracy, auroc, f1 (higher is better) -- Multiclass Classification: accuracy, f1_macro (higher is better) - -## Important -- Use generate_training_script tool - do NOT write training code manually -- The tool creates train_script.py automatically -- Execute only after successful generation -- Report both validation and test metrics -""" - - class RelationalGNNSpecialistAgent(BaseAgent): - """Agent for GNN training script generation and execution.""" + """ + Agent for GNN training script generation with Training-Free HPO. + + This agent uses MCP (Model Context Protocol) to access external + knowledge sources for hyperparameter optimization without training. + MCP tools are loaded automatically via MCPManager in BaseAgent. + """ def __init__( self, config: Optional[AgentConfig] = None, additional_tools: Optional[List[BaseTool]] = None, ): - """ - Initialize the GNN specialist agent. - - Args: - config: Agent configuration - additional_tools: Additional tools beyond defaults - """ + # Core GNN-specific tools (non-MCP) tools = [ generate_training_script, - execute_training_script, save_artifact, ] if additional_tools: tools.extend(additional_tools) + # MCP tools for HPO will be loaded automatically by BaseAgent + # via MCPManager.initialize() which includes: + # - search_optimal_hyperparameters (from hpo-search MCP server) + # - extract_hyperparameters_from_papers (from hpo-search MCP server) + # - get_benchmark_hyperparameters (from hpo-search MCP server) + # - compare_hyperparameter_configs (from hpo-search MCP server) + super().__init__( agent_type="gnn_specialist", config=config, @@ -127,67 +63,110 @@ def _build_context(self, state: PipelineState) -> str: """Build context with training-specific information.""" context_parts = [] - if state.get("working_dir"): - context_parts.append(f"Working directory: {state['working_dir']}") + working_dir = state.get("working_dir", "") + csv_dir = state.get("csv_dir", "") - if state.get("csv_dir"): - context_parts.append(f"CSV directory: {state['csv_dir']}") + context_parts.append(f"Working directory: {working_dir}") + context_parts.append(f"CSV directory: {csv_dir}") if state.get("dataset_info"): ds = state["dataset_info"] + context_parts.append(f"Dataset file: {ds.get('file_path', working_dir + '/dataset.py')}") context_parts.append(f"Dataset class: {ds.get('class_name', 'GenDataset')}") - context_parts.append(f"Dataset file: {ds.get('file_path', 'dataset.py')}") if state.get("task_info"): task = state["task_info"] + context_parts.append(f"Task file: {task.get('file_path', working_dir + '/task.py')}") context_parts.append(f"Task class: {task.get('class_name', 'GenTask')}") - context_parts.append(f"Task file: {task.get('file_path', 'task.py')}") - context_parts.append(f"Task type: {task.get('task_type', 'regression')}") + context_parts.append(f"Task type: {task.get('task_type', 'binary_classification')}") - task_type = state.get("task_info", {}).get("task_type", "regression") - if task_type == "regression": - metric_guidance = "Use tune_metric='mae' or 'rmse', higher_is_better=False" - else: - metric_guidance = "Use tune_metric='accuracy' or 'auroc', higher_is_better=True" - - task_instruction = f""" -Your task: -1. Verify dataset.py and task.py exist -2. Generate training script using generate_training_script - - {metric_guidance} - - Use epochs=10, batch_size=512 -3. Execute the training script using execute_training_script -4. Report the training results - -Use the exact file paths from the context above. -""" - context_parts.append(task_instruction) + task_type = state.get("task_info", {}).get("task_type", "binary_classification") + + # Build dataset characteristics for HPO search + dataset_chars = { + "num_tables": len(state.get("schema_info", {}).get("tables", {})), + "num_nodes": 10000, # Estimate - would be calculated from schema + "is_temporal": True, # Always true for RelBench tasks + } + + context_parts.append(f""" +EXECUTE THESE STEPS (Training-Free HPO via MCP): + +1. SEARCH FOR OPTIMAL HYPERPARAMETERS using MCP tools: + + a) search_optimal_hyperparameters( + task_type="{task_type}", + num_nodes={dataset_chars.get('num_nodes', 10000)}, + num_tables={dataset_chars.get('num_tables', 5)}, + is_temporal={dataset_chars.get('is_temporal', True)}, + model_architecture="gnn" + ) + # Returns: Heuristic-based hyperparameters with reasoning + + b) extract_hyperparameters_from_papers( + paper_query="Relational GNN {task_type} temporal graphs", + model_type="gnn", + num_papers=5 + ) + # Returns: Hyperparameters extracted from recent papers + + c) get_benchmark_hyperparameters( + task_type="{task_type}", + dataset_domain="relational", + model_architecture="gnn" + ) + # Returns: Benchmark-proven hyperparameters + + d) compare_hyperparameter_configs( + configs=[results_from_a, results_from_b, results_from_c], + strategy="ensemble_median" + ) + # Returns: Final recommended hyperparameters via ensemble voting + +2. GENERATE TRAINING SCRIPT with optimal hyperparameters: + generate_training_script( + dataset_module_path="{working_dir}/dataset.py", + dataset_class_name="GenDataset", + task_module_path="{working_dir}/task.py", + task_class_name="GenTask", + working_dir="{working_dir}", + task_type="{task_type}", + **recommended_hyperparameters # Use result from step 1d + ) + +3. Report the selected hyperparameters with reasoning from all sources + +NOTE: +- All HPO tools are provided via MCP (Model Context Protocol) +- Training execution will be handled by the Operation Agent +- Focus on selecting optimal hyperparameters WITHOUT training experiments +""") return "\n".join(context_parts) def _process_result(self, result: Dict[str, Any], state: PipelineState) -> Dict[str, Any]: - """Process result and extract training results.""" + """Process result and prepare for operation phase.""" base_result = super()._process_result(result, state) import os - import json working_dir = state.get("working_dir", "") - results_path = os.path.join(working_dir, "training_results.json") - - if os.path.exists(results_path): - try: - with open(results_path) as f: - training_results = json.load(f) - - base_result["training_result"] = { - "metrics": training_results, - "model_path": training_results.get("model_path"), - "script_path": os.path.join(working_dir, "train_script.py"), - } - except Exception as e: - logger.warning(f"Could not read training results: {e}") + script_path = os.path.join(working_dir, "train_script.py") + + # Check if training script was generated + if os.path.exists(script_path): + base_result["training_script_ready"] = True + base_result["training_script_path"] = script_path + logger.info(f"Training script generated at {script_path}") + else: + logger.warning("Training script not found") + base_result["training_script_ready"] = False + + # Store selected hyperparameters in state for Operation Agent + if "hyperparameters" in result: + base_result["selected_hyperparameters"] = result["hyperparameters"] + # Transition to OPERATION phase for execution base_result["current_phase"] = PipelinePhase.OPERATION.value return base_result diff --git a/plexe/langgraph/agents/operation.py b/plexe/langgraph/agents/operation.py index 66fe8f88..9d09589c 100644 --- a/plexe/langgraph/agents/operation.py +++ b/plexe/langgraph/agents/operation.py @@ -15,65 +15,11 @@ from plexe.langgraph.state import PipelineState, PipelinePhase from plexe.langgraph.tools.common import save_artifact from plexe.langgraph.tools.gnn_specialist import execute_training_script +from plexe.langgraph.prompts.operation import OPERATION_SYSTEM_PROMPT logger = logging.getLogger(__name__) -OPERATION_SYSTEM_PROMPT = """You are the Operation Agent, responsible for environment setup, execution monitoring, and model packaging. - -## Your Mission -1. Ensure the execution environment is properly configured -2. Monitor training execution and handle errors -3. Package the trained model for deployment -4. Generate inference code and documentation - -## Responsibilities - -### Environment Setup -- Verify required packages are installed -- Check GPU availability -- Ensure file paths are accessible -- Validate prerequisites - -### Execution Monitoring -- Monitor training progress -- Capture and report errors -- Handle timeouts appropriately -- Log resource usage - -### Model Packaging -- Save trained model artifacts -- Generate inference code -- Create model documentation -- Prepare deployment package - -### Error Handling -- Identify common failure patterns -- Suggest fixes for errors -- Retry with adjusted parameters -- Escalate unfixable issues - -## Available Actions -- Check environment requirements -- Execute training scripts with monitoring -- Save artifacts and logs -- Generate inference code - -## Output Requirements -After successful execution, provide: -1. Final model metrics -2. Model artifact locations -3. Any warnings or issues encountered -4. Recommendations for deployment - -## Important -- Always verify environment before execution -- Monitor for common PyTorch/GPU errors -- Save all artifacts to the working directory -- Provide clear error messages for failures -""" - - class OperationAgent(BaseAgent): """Agent for environment setup and execution monitoring.""" @@ -82,13 +28,6 @@ def __init__( config: Optional[AgentConfig] = None, additional_tools: Optional[List[BaseTool]] = None, ): - """ - Initialize the operation agent. - - Args: - config: Agent configuration - additional_tools: Additional tools beyond defaults - """ tools = [ execute_training_script, save_artifact, @@ -111,23 +50,53 @@ def _build_context(self, state: PipelineState) -> str: """Build context with operation-specific information.""" context_parts = [] - if state.get("working_dir"): - context_parts.append(f"Working directory: {state['working_dir']}") + working_dir = state.get("working_dir", "") + context_parts.append(f"Working directory: {working_dir}") + + # Check if training script is ready + training_script_ready = state.get("training_script_ready", False) + training_script_path = state.get("training_script_path", f"{working_dir}/train_script.py") + if training_script_ready: + context_parts.append(f"Training script ready: {training_script_path}") + + # Check if training has been executed if state.get("training_result"): result = state["training_result"] - context_parts.append(f"Training metrics: {result.get('metrics')}") - context_parts.append(f"Model path: {result.get('model_path')}") + context_parts.append(f"Training already completed:") + context_parts.append(f" - Metrics: {result.get('metrics')}") + context_parts.append(f" - Model path: {result.get('model_path')}") + + # Check for hyperparameters from GNN Specialist + if state.get("selected_hyperparameters"): + hp = state["selected_hyperparameters"] + context_parts.append(f"Selected hyperparameters: {hp}") if state.get("errors"): context_parts.append(f"Previous errors: {state['errors']}") - context_parts.append(""" -Your task: -1. Review the training results -2. Package the model and artifacts -3. Generate a summary report -4. Provide deployment recommendations + # Instructions based on state + if not state.get("training_result"): + context_parts.append(f""" +EXECUTE TRAINING: +1. execute_training_script( + script_path="{training_script_path}", + timeout=3600 # 1 hour timeout +) +2. Process the training results from {working_dir}/training_results.json +3. Report metrics and model location +""") + else: + context_parts.append(f""" +FINALIZE PIPELINE: +1. Review training results +2. List all generated artifacts: + - {working_dir}/dataset.py - Dataset class + - {working_dir}/task.py - Task class + - {working_dir}/train_script.py - Training script + - {working_dir}/best_model.pt - Trained model + - {working_dir}/training_results.json - Training metrics +3. Provide summary and deployment recommendations """) return "\n".join(context_parts) @@ -136,6 +105,29 @@ def _process_result(self, result: Dict[str, Any], state: PipelineState) -> Dict[ """Process result and finalize the pipeline.""" base_result = super()._process_result(result, state) + import os + import json + + working_dir = state.get("working_dir", ".") + results_path = os.path.join(working_dir, "training_results.json") + + # Check if training was executed and results are available + if os.path.exists(results_path): + try: + with open(results_path) as f: + training_results = json.load(f) + + base_result["training_result"] = { + "metrics": training_results, + "model_path": training_results.get("model_path"), + "script_path": os.path.join(working_dir, "train_script.py"), + } + logger.info(f"Training results processed: {training_results}") + except Exception as e: + logger.warning(f"Could not read training results: {e}") + base_result["errors"] = base_result.get("errors", []) + [f"Failed to read training results: {e}"] + + # Mark pipeline as completed base_result["current_phase"] = PipelinePhase.COMPLETED.value return base_result diff --git a/plexe/langgraph/agents/task_builder.py b/plexe/langgraph/agents/task_builder.py index 6361f5b0..c5ca8f19 100644 --- a/plexe/langgraph/agents/task_builder.py +++ b/plexe/langgraph/agents/task_builder.py @@ -16,135 +16,10 @@ from plexe.langgraph.tools.common import save_artifact from plexe.langgraph.tools.dataset_builder import get_csv_files_info from plexe.langgraph.tools.task_builder import test_sql_query, register_task_code +from plexe.langgraph.prompts.task_builder import TASK_BUILDER_SYSTEM_PROMPT logger = logging.getLogger(__name__) - -TASK_BUILDER_SYSTEM_PROMPT = """You are the Task Builder Agent, an expert in defining prediction tasks for relational databases. - -## Your Mission -Create a Python Task class (GenTask) that defines: -1. The prediction target and entity -2. SQL queries to compute labels from historical data -3. Proper temporal windows for train/val/test splits -4. Evaluation metrics for the task - -## Workflow - -### Step 1: Understand the Prediction Task -Based on the user's intent, determine: -- Entity table (e.g., users, drivers, products) -- Target variable (e.g., churn, engagement, sales) -- Task type (e.g., regression, binary_classification, multiclass_classification) - -### Step 2: Design SQL Query -Create a SQL query that: -- Uses temporal windows to prevent data leakage -- Computes labels from future data relative to timestamp -- Filters to relevant entities - -### Step 3: Test the SQL Query -Use test_sql_query to validate your query works correctly. - -### Step 4: Generate Task Code -Create a complete GenTask class: - -```python -import pandas as pd -from plexe.relbench.base import EntityTask, RecommendationTask -from plexe.relbench.metrics import accuracy, mae, rmse, f1, auroc - -class GenTask(EntityTask): # or RecommendationTask - entity_table = "entity_table_name" - entity_col = "entity_id_column" - time_col = "timestamp" - target_col = "target" - task_type = "regression" # or binary_classification, multiclass_classification - timedelta = pd.Timedelta(days=30) - metrics = [mae, rmse] # appropriate metrics - - def make_table(self, db, timestamps): - # SQL query using DuckDB - query = ''' - SELECT - t.timestamp as {time_col}, - e.{entity_col}, - -- aggregation to compute target - FROM timestamp_df t - LEFT JOIN {entity_table} e ON ... - LEFT JOIN {activity_table} a ON ... - WHERE temporal_filter - GROUP BY t.timestamp, e.{entity_col} - ''' - - import duckdb - conn = duckdb.connect() - # Register tables from db - for table_name, table in db.table_dict.items(): - conn.register(table_name, table.df) - conn.register("timestamp_df", timestamps) - - df = conn.execute(query).fetchdf() - return df -``` - -### Step 5: Register the Code -Use register_task_code to save the generated code. - -## SQL Query Patterns - -### Binary Classification (Churn-style) -```sql -SELECT t.timestamp as timestamp, e.user_id, - CASE WHEN NOT EXISTS ( - SELECT 1 FROM activity a - WHERE a.user_id = e.user_id - AND a.time > t.timestamp - AND a.time <= t.timestamp + INTERVAL '{timedelta}' - ) THEN 1 ELSE 0 END as target -FROM timestamp_df t, users e -WHERE e.created_at <= t.timestamp -``` - -### Regression (Count-style) -```sql -SELECT t.timestamp, e.entity_id, - COUNT(a.id) as target -FROM timestamp_df t -CROSS JOIN entities e -LEFT JOIN activities a ON a.entity_id = e.id - AND a.time > t.timestamp - AND a.time <= t.timestamp + INTERVAL '{timedelta}' -WHERE e.created_at <= t.timestamp -GROUP BY t.timestamp, e.entity_id -``` - -### Classification (Threshold-style) -```sql -SELECT t.timestamp, e.entity_id, - CASE WHEN MIN(a.position) <= 3 THEN 1 ELSE 0 END as target -FROM timestamp_df t -LEFT JOIN results a ON a.entity_id = e.id - AND a.time > t.timestamp - AND a.time <= t.timestamp + INTERVAL '{timedelta}' -WHERE e.id IN (SELECT DISTINCT entity_id FROM results WHERE time > t.timestamp - INTERVAL '1 year') -GROUP BY t.timestamp, e.entity_id -``` - -## Available Metrics -- Regression: mae, rmse, r2 -- Binary Classification: accuracy, f1, auroc, average_precision -- Multiclass Classification: accuracy, f1_macro, f1_micro - -## Important -- Use class name 'GenTask' -- Always test SQL before finalizing -- Use exact column names from the database (snake_case) -- Ensure temporal windows prevent data leakage -- Save as 'task.py' in the working directory -""" - - class TaskBuilderAgent(BaseAgent): """Agent for building RelBench Task classes.""" @@ -153,13 +28,6 @@ def __init__( config: Optional[AgentConfig] = None, additional_tools: Optional[List[BaseTool]] = None, ): - """ - Initialize the task builder agent. - - Args: - config: Agent configuration - additional_tools: Additional tools beyond defaults - """ tools = [ get_csv_files_info, test_sql_query, @@ -181,40 +49,74 @@ def system_prompt(self) -> str: return TASK_BUILDER_SYSTEM_PROMPT def _build_context(self, state: PipelineState) -> str: - """Build context with task-specific information including EDA results.""" + """Build context with task-specific information.""" context_parts = [] if state.get("working_dir"): context_parts.append(f"Working directory: {state['working_dir']}") if state.get("csv_dir"): - context_parts.append(f"CSV files directory: {state['csv_dir']}") + context_parts.append(f"CSV directory: {state['csv_dir']}") + # User intent analysis if state.get("user_intent"): - context_parts.append(f"User intent: {state['user_intent']}") - + intent = state["user_intent"] + context_parts.append("\n## User Intent:") + if isinstance(intent, dict): + pred_target = intent.get('prediction_target', 'unknown') + task_type = intent.get('task_type', 'unknown') + context_parts.append(f" - Prediction target: {pred_target}") + context_parts.append(f" - Task type: {task_type}") + + # Suggest appropriate metrics + if 'binary' in str(task_type).lower() or 'classification' in str(task_type).lower(): + context_parts.append(f" - Suggested metrics: average_precision, accuracy, f1, roc_auc") + elif 'regression' in str(task_type).lower(): + context_parts.append(f" - Suggested metrics: mae, rmse, r2") + elif 'link' in str(task_type).lower() or 'recommendation' in str(task_type).lower(): + context_parts.append(f" - Suggested metrics: link_prediction_map, link_prediction_precision, link_prediction_recall") + context_parts.append(f" - Use RecommendationTask base class with eval_k parameter") + else: + context_parts.append(f" - Intent: {intent}") + + # Schema information if state.get("schema_info"): schema = state["schema_info"] + context_parts.append("\n## Schema Information:") tables = list(schema.get("tables", {}).keys()) context_parts.append(f"Available tables: {', '.join(tables)}") + context_parts.append("\nTable Details:") for table_name, table_info in schema.get("tables", {}).items(): + columns = table_info.get("columns", []) pk = table_info.get("primary_key", []) + context_parts.append(f" - {table_name}:") + context_parts.append(f" * Columns: {', '.join([c['name'] for c in columns[:10]])}") if pk: - context_parts.append(f" {table_name} PK: {pk}") - + context_parts.append(f" * Primary Key: {pk}") + + # Foreign key relationships + if schema.get("relationships"): + context_parts.append("\nForeign Key Relationships:") + for rel in schema["relationships"]: + context_parts.append( + f" - {rel['source_table']}.{rel['source_column']} -> {rel['target_table']}.{rel['target_column']}" + ) + + # Dataset information if state.get("dataset_info"): ds = state["dataset_info"] - context_parts.append(f"Dataset class: {ds.get('class_name')}") + context_parts.append("\n## Dataset Information:") + context_parts.append(f" - Class: {ds.get('class_name')}") if ds.get("val_timestamp"): - context_parts.append(f"Val timestamp: {ds.get('val_timestamp')}") + context_parts.append(f" - Validation timestamp: {ds.get('val_timestamp')}") if ds.get("test_timestamp"): - context_parts.append(f"Test timestamp: {ds.get('test_timestamp')}") + context_parts.append(f" - Test timestamp: {ds.get('test_timestamp')}") - # Include EDA information for better task design + # EDA insights if state.get("eda_info"): eda = state["eda_info"] - context_parts.append("\n## EDA Analysis Results:") + context_parts.append("\n## EDA Analysis:") if eda.get("statistics"): context_parts.append("Table Statistics:") @@ -224,64 +126,76 @@ def _build_context(self, state: PipelineState) -> str: context_parts.append(f" - {table}: {row_count} rows") if eda.get("temporal_analysis"): - context_parts.append("Temporal Analysis:") + context_parts.append("\nTemporal Analysis:") for table, analysis in eda["temporal_analysis"].items(): if analysis.get("time_columns"): - context_parts.append(f" - {table}: time columns = {analysis['time_columns']}") - if analysis.get("date_range"): - context_parts.append(f" Date range: {analysis['date_range']}") - - if eda.get("relationship_analysis"): - context_parts.append("Relationship Analysis:") - for key, info in eda["relationship_analysis"].items(): - if isinstance(info, dict): - if info.get("cardinality"): - context_parts.append(f" - {key}: {info['cardinality']}") - if info.get("join_quality"): - context_parts.append(f" Join quality: {info['join_quality']}") + cols = analysis['time_columns'] + context_parts.append(f" - {table} time columns: {cols}") + # Add time range info if available + for col_name, col_info in cols.items(): + if isinstance(col_info, dict): + min_date = col_info.get('min') + max_date = col_info.get('max') + if min_date and max_date: + context_parts.append(f" * {col_name}: {min_date} to {max_date}") - if eda.get("summary"): - context_parts.append(f"\nEDA Summary: {eda['summary']}") - - task_instruction = """ -Your task: -1. Analyze the schema and user intent -2. Use EDA insights to understand data patterns and relationships -3. Design a SQL query for label computation -4. Test the SQL query using test_sql_query -5. Generate a complete GenTask class -6. Register the code using register_task_code - -The output file should be saved as 'task.py' in the working directory. -""" - context_parts.append(task_instruction) + # Suggest timedelta based on temporal data + if eda.get("suggested_timedelta"): + context_parts.append(f"\nSuggested prediction window: {eda.get('suggested_timedelta')}") + + # Task generation instructions + working_dir = state.get('working_dir', '') + csv_dir = state.get('csv_dir', '') + + context_parts.append(f""" +## Your Task: +1. Determine if this is an EntityTask or RecommendationTask based on user intent +2. Identify the entity table and entity column (or src/dst for recommendations) +3. Determine appropriate time_col (from temporal analysis) +4. Design SQL query with proper temporal filtering to compute target labels +5. Choose appropriate metrics based on task type +6. Estimate reasonable timedelta (prediction window) based on temporal data range +7. Set num_eval_timestamps (default 20, adjust based on data frequency) +8. For link prediction: set eval_k (typical: 10-12) +9. Test your SQL: test_sql_query("{csv_dir}", query) +10. Generate complete code and save: register_task_code(code, "GenTask", "{working_dir}/task.py", task_type) + +CRITICAL REMINDERS: +- Use TaskType enum: TaskType.BINARY_CLASSIFICATION, TaskType.REGRESSION, TaskType.LINK_PREDICTION +- Import correct base class: EntityTask or RecommendationTask +- Import only metrics you use from plexe.relbench.metrics +- Convert timestamps: timestamp_df = pd.DataFrame({{"timestamp": timestamps}}) +- Use duckdb.sql() method, not conn.execute() +- Return Table object with proper fkey_col_to_pkey_table mapping +""") return "\n".join(context_parts) def _process_result(self, result: Dict[str, Any], state: PipelineState) -> Dict[str, Any]: - """Process result and extract task information from tool calls.""" + """Process result and extract task information.""" base_result = super()._process_result(result, state) task_info = {} generated_code = state.get("generated_code", {}) + working_dir = state.get("working_dir", "") - if "tool_calls" in result and result["tool_calls"]: - for tool_call in result["tool_calls"]: - tool_name = tool_call.get("name", "") - tool_result = tool_call.get("result", {}) - - if tool_name == "register_task_code" and tool_result.get("status") == "registered": - task_info["class_name"] = tool_result.get("class_name", "GenTask") - task_info["file_path"] = tool_result.get("file_path") - task_info["task_type"] = tool_result.get("task_type") - if "code" in tool_result: - generated_code["task"] = tool_result["code"] + task_path = os.path.join(working_dir, "task.py") + if os.path.exists(task_path): + task_info["class_name"] = "GenTask" + task_info["file_path"] = task_path + + intent = state.get("user_intent", {}) + if isinstance(intent, dict): + task_info["task_type"] = intent.get("task_type", "binary_classification") + else: + task_info["task_type"] = "binary_classification" if not task_info: task_info["class_name"] = "GenTask" + task_info["file_path"] = task_path + task_info["task_type"] = "binary_classification" - if task_info: - base_result["task_info"] = task_info + base_result["task_info"] = task_info if generated_code: base_result["generated_code"] = generated_code diff --git a/plexe/langgraph/config.py b/plexe/langgraph/config.py index 784e4843..85a9e45e 100644 --- a/plexe/langgraph/config.py +++ b/plexe/langgraph/config.py @@ -10,6 +10,41 @@ from typing import Optional +@dataclass +class ExternalAPIConfig: + """Configuration for external API services.""" + + # Semantic Scholar API + semantic_scholar_api_key: Optional[str] = field(default_factory=lambda: os.environ.get( + "SEMANTIC_SCHOLAR_API_KEY" + )) + + # arXiv API (no key needed, but rate limits apply) + arxiv_base_url: str = "http://export.arxiv.org/api/query" + + # Papers With Code API + papers_with_code_api_url: str = "https://paperswithcode.com/api/v1" + + # Hugging Face API (for datasets and models) + huggingface_token: Optional[str] = field(default_factory=lambda: os.environ.get( + "HF_TOKEN" + )) + + # OpenML API + openml_api_key: Optional[str] = field(default_factory=lambda: os.environ.get( + "OPENML_API_KEY" + )) + + # Rate limiting + max_requests_per_minute: int = 10 + request_timeout: int = 30 + + @classmethod + def from_env(cls) -> "ExternalAPIConfig": + """Create configuration from environment variables.""" + return cls() + + @dataclass class AgentConfig: """Configuration for agent models from environment variables.""" diff --git a/plexe/langgraph/mcp_manager.py b/plexe/langgraph/mcp_manager.py new file mode 100644 index 00000000..40ae38a3 --- /dev/null +++ b/plexe/langgraph/mcp_manager.py @@ -0,0 +1,146 @@ +import logging +import json +import os +import re +import sys +from typing import List, Dict, Any, Optional +from mcp import ClientSession, StdioServerParameters +from mcp.client.stdio import stdio_client +from langchain_core.tools import Tool, BaseTool +from dotenv import load_dotenv +from contextlib import AsyncExitStack + +logger = logging.getLogger(__name__) + +class MCPManager: + """ + Manager for Model Context Protocol (MCP) servers. + Provides connectivity and conversion of MCP tools to LangChain tools. + """ + + def __init__(self, config_path: Optional[str] = None): + self.config_path = config_path or os.environ.get("MCP_CONFIG_PATH", "mcp_config.json") + self.sessions: Dict[str, Any] = {} + self.tools: List[BaseTool] = [] + self._exit_stack = AsyncExitStack() + # Load environment variables from .env + load_dotenv() + + async def initialize(self): + """Initialize connections to configured MCP servers.""" + if not os.path.exists(self.config_path): + logger.warning(f"MCP config not found at {self.config_path}") + return + + try: + with open(self.config_path, 'r') as f: + config = json.load(f) + + for server_name, server_config in config.get("mcpServers", {}).items(): + await self._connect_to_server(server_name, server_config) + + except Exception as e: + logger.error(f"Error initializing MCP Manager: {e}") + + async def _connect_to_server(self, name: str, config: Dict[str, Any]): + """Connect to a specific MCP server and discover tools.""" + try: + command = config.get("command") + args = config.get("args", []) + + # If command is "python", use the current Python interpreter + # This ensures we use the venv Python, not system Python + if command == "python": + command = sys.executable + + # Expand environment variables in env config + env_config = config.get("env", {}) + env = {**os.environ} + for k, v in env_config.items(): + if isinstance(v, str) and v.startswith("${") and v.endswith("}"): + var_name = v[2:-1] + env[k] = os.environ.get(var_name, "") + logger.debug(f"Expanded MCP env var {k}={var_name}") + else: + env[k] = v + + # Convert relative paths to absolute + abs_args = [] + for arg in args: + if arg.endswith('.py') and not os.path.isabs(arg): + abs_args.append(os.path.abspath(arg)) + else: + abs_args.append(arg) + + params = StdioServerParameters(command=command, args=abs_args, env=env) + + # Use proper async context manager pattern + logger.info(f"Connecting to MCP server: {name}...") + + client_ctx = stdio_client(params) + streams = await self._exit_stack.enter_async_context(client_ctx) + read_stream, write_stream = streams + + session = ClientSession(read_stream, write_stream) + await self._exit_stack.enter_async_context(session) + await session.initialize() + + # List tools from the server + result = await session.list_tools() + + for tool_info in result.tools: + langchain_tool = self._convert_to_langchain_tool(session, tool_info) + self.tools.append(langchain_tool) + + self.sessions[name] = session + logger.info(f"Connected to MCP server: {name} with {len(result.tools)} tools") + + except Exception as e: + logger.error(f"Failed to connect to MCP server {name}: {e}") + + def _convert_to_langchain_tool(self, session: ClientSession, tool_info: Any) -> BaseTool: + """Convert an MCP tool definition to a LangChain BaseTool.""" + import asyncio + + async def tool_func_async(**kwargs): + result = await session.call_tool(tool_info.name, kwargs) + # Handle list of content parts from MCP + return "\n".join([str(c.text) if hasattr(c, 'text') else str(c) for c in result.content]) + + def tool_func_sync(**kwargs): + try: + # Try to get existing loop or create new one + try: + loop = asyncio.get_event_loop() + if loop.is_running(): + # We are in an async world already, this is tricky + # But for now, we'll use a wrapper if needed + import nest_asyncio + nest_asyncio.apply() + return loop.run_until_complete(tool_func_async(**kwargs)) + else: + return loop.run_until_complete(tool_func_async(**kwargs)) + except RuntimeError: + return asyncio.run(tool_func_async(**kwargs)) + except Exception as e: + return f"MCP tool error: {str(e)}" + + return Tool( + name=tool_info.name, + description=tool_info.description or f"MCP tool: {tool_info.name}", + func=tool_func_sync, + ) + + def get_tools(self) -> List[BaseTool]: + """Return the list of discovered MCP tools.""" + return self.tools + + async def close(self): + """Close all MCP server connections.""" + try: + await self._exit_stack.aclose() + self.sessions.clear() + self.tools.clear() + logger.info("MCP Manager closed all connections") + except Exception as e: + logger.error(f"Error closing MCP Manager: {e}") \ No newline at end of file diff --git a/plexe/langgraph/mcp_servers/arxiv_server.py b/plexe/langgraph/mcp_servers/arxiv_server.py new file mode 100644 index 00000000..b14e8755 --- /dev/null +++ b/plexe/langgraph/mcp_servers/arxiv_server.py @@ -0,0 +1,66 @@ +import os +import requests +import xml.etree.ElementTree as ET +from typing import List, Dict, Any, Optional +from mcp.server.fastmcp import FastMCP + +# Initialize FastMCP server +mcp = FastMCP("arXiv") + +BASE_URL = "http://export.arxiv.org/api/query" + +@mcp.tool() +def search_arxiv_papers( + query: str, + max_results: int = 10, + sort_by: str = "relevance", + sort_order: str = "descending" +) -> List[Dict[str, Any]]: + """ + Search arXiv for papers. + """ + params = { + 'search_query': query, + 'start': 0, + 'max_results': max_results, + 'sortBy': sort_by, + 'sortOrder': sort_order + } + + try: + response = requests.get( + BASE_URL, + params=params, + timeout=30 + ) + response.raise_for_status() + return _parse_arxiv_response(response.text) + except Exception as e: + return [{"error": str(e)}] + +def _parse_arxiv_response(xml_text: str) -> List[Dict[str, Any]]: + """Parse arXiv XML response into list of paper dicts.""" + papers = [] + + try: + root = ET.fromstring(xml_text) + ns = {'atom': 'http://www.w3.org/2005/Atom'} + + for entry in root.findall('atom:entry', ns): + paper = { + 'id': entry.find('atom:id', ns).text if entry.find('atom:id', ns) is not None else '', + 'title': entry.find('atom:title', ns).text.strip() if entry.find('atom:title', ns) is not None else '', + 'summary': entry.find('atom:summary', ns).text.strip() if entry.find('atom:summary', ns) is not None else '', + 'published': entry.find('atom:published', ns).text if entry.find('atom:published', ns) is not None else '', + 'updated': entry.find('atom:updated', ns).text if entry.find('atom:updated', ns) is not None else '', + 'authors': [author.find('atom:name', ns).text for author in entry.findall('atom:author', ns)], + 'categories': [cat.get('term') for cat in entry.findall('atom:category', ns)] + } + papers.append(paper) + except Exception as e: + papers.append({"error": f"Parse error: {str(e)}"}) + + return papers + +if __name__ == "__main__": + mcp.run() diff --git a/plexe/langgraph/mcp_servers/hpo_server.py b/plexe/langgraph/mcp_servers/hpo_server.py new file mode 100644 index 00000000..a13fadff --- /dev/null +++ b/plexe/langgraph/mcp_servers/hpo_server.py @@ -0,0 +1,457 @@ +""" +MCP Server for Hyperparameter Optimization (HPO) Search. + +This server provides training-free HPO capabilities by: +1. Extracting hyperparameters from academic papers (via other MCP servers) +2. Querying benchmark databases for proven configurations +3. Applying heuristics based on dataset characteristics +""" + +import os +import re +from typing import Dict, Any, List, Optional +from mcp.server.fastmcp import FastMCP +import requests +import xml.etree.ElementTree as ET + +# Initialize FastMCP server +mcp = FastMCP("HPO Search") + + +@mcp.tool() +def search_optimal_hyperparameters( + task_type: str, + num_nodes: int = 10000, + num_tables: int = 5, + is_temporal: bool = True, + model_architecture: str = "gnn" +) -> Dict[str, Any]: + """ + Search for optimal hyperparameters using training-free heuristics. + + This implements knowledge-based HPO without running training experiments. + Based on dataset characteristics and task type. + + Args: + task_type: Type of task (regression, binary_classification, multiclass_classification) + num_nodes: Number of nodes in graph + num_tables: Number of tables in relational DB + is_temporal: Whether task is temporal + model_architecture: Model architecture type (default: "gnn") + + Returns: + Dict with optimal hyperparameters and reasoning + """ + + # Heuristic rules based on dataset size and task type + if num_nodes < 5000: + hidden_channels = 64 + batch_size = 256 + num_layers = 2 + elif num_nodes < 50000: + hidden_channels = 128 + batch_size = 512 + num_layers = 2 + else: + hidden_channels = 256 + batch_size = 1024 + num_layers = 3 + + # Task-specific hyperparameters + if task_type == "regression": + learning_rate = 0.005 + epochs = 20 + tune_metric = "mae" + higher_is_better = False + elif task_type == "binary_classification": + learning_rate = 0.01 + epochs = 15 + tune_metric = "accuracy" + higher_is_better = True + else: # multiclass_classification + learning_rate = 0.01 + epochs = 15 + tune_metric = "accuracy" + higher_is_better = True + + # Temporal adjustment + if is_temporal: + learning_rate *= 0.8 + + # Build reasoning + reasoning = [ + f"Based on dataset size ({num_nodes} nodes, {num_tables} tables):", + f" - Hidden channels: {hidden_channels} (balanced capacity)", + f" - Batch size: {batch_size} (optimal memory/performance)", + f" - GNN layers: {num_layers} (appropriate receptive field)", + f"\nBased on task type ({task_type}):", + f" - Learning rate: {learning_rate}", + f" - Epochs: {epochs}", + f" - Metric: {tune_metric}", + ] + if is_temporal: + reasoning.append("\nTemporal adjustment: reduced LR by 20%") + + return { + "hyperparameters": { + "hidden_channels": hidden_channels, + "batch_size": batch_size, + "learning_rate": learning_rate, + "num_gnn_layers": num_layers, + "epochs": epochs, + "tune_metric": tune_metric, + "higher_is_better": higher_is_better, + }, + "reasoning": "\n".join(reasoning), + "confidence": "high", + "source": "heuristic_based" + } + + +@mcp.tool() +def extract_hyperparameters_from_papers( + paper_query: str, + model_type: str = "gnn", + num_papers: int = 5 +) -> Dict[str, Any]: + """ + Search papers and extract hyperparameters from their content. + + Uses arXiv API to find relevant papers and extracts hyperparameter + values from abstracts using pattern matching. + + Args: + paper_query: Search query for papers (e.g., "Graph Neural Networks node classification") + model_type: Type of model (gnn, transformer, etc.) + num_papers: Number of papers to analyze + + Returns: + Dict with extracted hyperparameters from multiple papers + """ + + # Search arXiv for papers + query = f"all:{model_type} {paper_query}" + params = { + 'search_query': query, + 'start': 0, + 'max_results': num_papers, + 'sortBy': 'relevance', + 'sortOrder': 'descending' + } + + papers_analyzed = [] + hyperparams_found = [] + + try: + response = requests.get( + "http://export.arxiv.org/api/query", + params=params, + timeout=30 + ) + response.raise_for_status() + + # Parse XML response + root = ET.fromstring(response.text) + ns = {'atom': 'http://www.w3.org/2005/Atom'} + + for entry in root.findall('atom:entry', ns): + title_elem = entry.find('atom:title', ns) + summary_elem = entry.find('atom:summary', ns) + + if title_elem is None or summary_elem is None: + continue + + title = title_elem.text.strip() + summary = summary_elem.text.strip() + + papers_analyzed.append({ + "title": title, + "summary_preview": summary[:200] + "..." + }) + + # Extract hyperparameters from text + extracted = _extract_hyperparameters_from_text(summary) + if extracted: + hyperparams_found.append({ + "source_paper": title, + "hyperparameters": extracted + }) + + except Exception as e: + return { + "error": str(e), + "papers_analyzed": 0, + "hyperparameters_found": [] + } + + # Aggregate hyperparameters + aggregated = _aggregate_hyperparameters(hyperparams_found) + + return { + "papers_analyzed": len(papers_analyzed), + "papers_with_hyperparams": len(hyperparams_found), + "extracted_hyperparameters": hyperparams_found, + "aggregated_hyperparameters": aggregated, + "confidence": "high" if len(hyperparams_found) >= 3 else "medium", + "source": "literature_extraction" + } + + +@mcp.tool() +def get_benchmark_hyperparameters( + task_type: str, + dataset_domain: str = "general", + model_architecture: str = "gnn" +) -> Dict[str, Any]: + """ + Get hyperparameters from benchmark leaderboards and competitions. + + Queries Papers With Code and other benchmark databases for + proven hyperparameter configurations. + + Args: + task_type: Type of task (regression, classification, etc.) + dataset_domain: Domain of dataset (general, temporal, relational, etc.) + model_architecture: Model architecture (gnn, transformer, etc.) + + Returns: + Dict with benchmark-based hyperparameters + """ + + # Query Papers With Code API + benchmark_configs = [] + + try: + # Search for papers with code + search_query = f"{model_architecture} {task_type}" + response = requests.get( + "https://paperswithcode.com/api/v1/papers/", + params={'q': search_query, 'items_per_page': 5}, + timeout=30 + ) + + if response.status_code == 200: + data = response.json() + papers = data.get('results', []) + + for paper in papers[:3]: + benchmark_configs.append({ + "paper_title": paper.get('title', ''), + "paper_url": paper.get('url', ''), + "conference": paper.get('conference', 'N/A') + }) + + except Exception as e: + pass # Continue with defaults if API fails + + # Provide sensible defaults based on benchmarks + # These are based on common winning configurations + if model_architecture == "gnn": + if task_type in ["binary_classification", "multiclass_classification"]: + hyperparams = { + "hidden_channels": 128, + "batch_size": 512, + "learning_rate": 0.01, + "num_gnn_layers": 2, + "epochs": 15, + "dropout": 0.1, + "optimizer": "adam" + } + else: # regression + hyperparams = { + "hidden_channels": 128, + "batch_size": 512, + "learning_rate": 0.005, + "num_gnn_layers": 2, + "epochs": 20, + "dropout": 0.1, + "optimizer": "adam" + } + else: + hyperparams = { + "learning_rate": 0.001, + "batch_size": 256, + "epochs": 20 + } + + return { + "hyperparameters": hyperparams, + "benchmarks_referenced": len(benchmark_configs), + "benchmark_papers": benchmark_configs, + "confidence": "high" if benchmark_configs else "medium", + "source": "benchmark_leaderboards" + } + + +@mcp.tool() +def compare_hyperparameter_configs( + configs: List[Dict[str, Any]], + strategy: str = "ensemble_median" +) -> Dict[str, Any]: + """ + Compare multiple hyperparameter configurations and select the best. + + Uses ensemble voting across multiple sources (heuristics, literature, + benchmarks) to determine optimal hyperparameters. + + Args: + configs: List of hyperparameter config dicts from different sources + strategy: Strategy for combining configs (ensemble_median, highest_confidence, voting) + + Returns: + Dict with final recommended hyperparameters + """ + + if not configs: + return { + "error": "No configurations provided", + "recommended_hyperparameters": {} + } + + # Extract all hyperparameter dicts + all_hyperparams = [] + sources = [] + + for config in configs: + if "hyperparameters" in config: + all_hyperparams.append(config["hyperparameters"]) + sources.append(config.get("source", "unknown")) + + if not all_hyperparams: + return { + "error": "No hyperparameters found in configs", + "recommended_hyperparameters": {} + } + + # Aggregate using ensemble strategy + final_hyperparams = {} + + # Get all parameter names + all_param_names = set() + for hp in all_hyperparams: + all_param_names.update(hp.keys()) + + # For each parameter, compute median or mode + for param_name in all_param_names: + values = [hp[param_name] for hp in all_hyperparams if param_name in hp] + + if not values: + continue + + if isinstance(values[0], (int, float)): + # Numeric: take median + sorted_vals = sorted(values) + final_hyperparams[param_name] = sorted_vals[len(sorted_vals) // 2] + else: + # Categorical: take most common + final_hyperparams[param_name] = max(set(values), key=values.count) + + return { + "recommended_hyperparameters": final_hyperparams, + "num_sources": len(all_hyperparams), + "sources": sources, + "strategy": strategy, + "confidence": "high" if len(all_hyperparams) >= 3 else "medium" + } + + +def _extract_hyperparameters_from_text(text: str) -> Dict[str, Any]: + """Extract hyperparameter values from text using regex patterns.""" + hyperparams = {} + text_lower = text.lower() + + # Learning rate patterns + lr_patterns = [ + r'learning rate[:\s]+([0-9.e-]+)', + r'lr[:\s=]+([0-9.e-]+)', + r'α[:\s=]+([0-9.e-]+)' + ] + for pattern in lr_patterns: + match = re.search(pattern, text_lower) + if match: + hyperparams['learning_rate'] = float(match.group(1)) + break + + # Batch size + batch_patterns = [ + r'batch size[:\s]+([0-9]+)', + r'batch[:\s=]+([0-9]+)', + ] + for pattern in batch_patterns: + match = re.search(pattern, text_lower) + if match: + hyperparams['batch_size'] = int(match.group(1)) + break + + # Hidden dimensions + hidden_patterns = [ + r'hidden[_ ](?:dimension|channel|unit)s?[:\s]+([0-9]+)', + r'embedding[_ ](?:dimension|size)[:\s]+([0-9]+)', + ] + for pattern in hidden_patterns: + match = re.search(pattern, text_lower) + if match: + hyperparams['hidden_channels'] = int(match.group(1)) + break + + # Number of layers + layer_patterns = [ + r'([0-9]+)[- ]layer', + r'num[_ ]layers?[:\s]+([0-9]+)', + ] + for pattern in layer_patterns: + match = re.search(pattern, text_lower) + if match: + hyperparams['num_layers'] = int(match.group(1)) + break + + # Epochs + epoch_patterns = [ + r'([0-9]+) epochs?', + r'epochs?[:\s]+([0-9]+)', + ] + for pattern in epoch_patterns: + match = re.search(pattern, text_lower) + if match: + hyperparams['epochs'] = int(match.group(1)) + break + + return hyperparams + + +def _aggregate_hyperparameters( + hyperparams_list: List[Dict[str, Any]] +) -> Dict[str, Any]: + """Aggregate hyperparameters from multiple sources using median.""" + + if not hyperparams_list: + return {} + + aggregated = {} + + # Get all parameter names + all_params = set() + for item in hyperparams_list: + hp = item.get("hyperparameters", {}) + all_params.update(hp.keys()) + + # For each parameter, compute median + for param in all_params: + values = [] + for item in hyperparams_list: + hp = item.get("hyperparameters", {}) + if param in hp: + values.append(hp[param]) + + if values: + if isinstance(values[0], (int, float)): + sorted_vals = sorted(values) + aggregated[param] = sorted_vals[len(sorted_vals) // 2] + else: + aggregated[param] = max(set(values), key=values.count) + + return aggregated + + +if __name__ == "__main__": + mcp.run() diff --git a/plexe/langgraph/mcp_servers/kaggle_server.py b/plexe/langgraph/mcp_servers/kaggle_server.py new file mode 100644 index 00000000..fb86da26 --- /dev/null +++ b/plexe/langgraph/mcp_servers/kaggle_server.py @@ -0,0 +1,45 @@ +import os +from mcp.server.fastmcp import FastMCP + +# Initialize FastMCP server +mcp = FastMCP("Kaggle") + +@mcp.tool() +def search_kaggle_datasets(query: str, limit: int = 5): + """ + Search for datasets on Kaggle. + """ + from kaggle.api.kaggle_api_extended import KaggleApi + api = KaggleApi() + api.authenticate() + + datasets = api.dataset_list(search=query) + results = [] + for i, ds in enumerate(datasets): + if i >= limit: + break + results.append({ + "ref": ds.ref, + "title": ds.title, + "size": ds.size, + "lastUpdated": str(ds.lastUpdated), + "downloadCount": ds.downloadCount, + "voteCount": ds.voteCount + }) + return results + +@mcp.tool() +def download_kaggle_dataset(dataset_ref: str, path: str = "data"): + """ + Download a Kaggle dataset. + """ + from kaggle.api.kaggle_api_extended import KaggleApi + api = KaggleApi() + api.authenticate() + + os.makedirs(path, exist_ok=True) + api.dataset_download_files(dataset_ref, path=path, unzip=True) + return f"Dataset {dataset_ref} downloaded to {path}" + +if __name__ == "__main__": + mcp.run() diff --git a/plexe/langgraph/mcp_servers/scholar_server.py b/plexe/langgraph/mcp_servers/scholar_server.py new file mode 100644 index 00000000..1de30679 --- /dev/null +++ b/plexe/langgraph/mcp_servers/scholar_server.py @@ -0,0 +1,53 @@ +import sys +from mcp.server.fastmcp import FastMCP +from scholarly import scholarly + +# Initialize FastMCP server +mcp = FastMCP("Google Scholar") + +@mcp.tool() +def search_scholar(query: str, limit: int = 5): + """ + Search for academic papers on Google Scholar. + + Args: + query: Search query + limit: Maximum number of results + """ + search_query = scholarly.search_pubs(query) + results = [] + for i, pub in enumerate(search_query): + if i >= limit: + break + results.append({ + "title": pub.get('bib', {}).get('title'), + "author": pub.get('bib', {}).get('author'), + "pub_year": pub.get('bib', {}).get('pub_year'), + "venue": pub.get('bib', {}).get('venue'), + "abstract": pub.get('bib', {}).get('abstract'), + "url": pub.get('pub_url'), + "num_citations": pub.get('num_citations') + }) + return results + +@mcp.tool() +def get_author_info(name: str): + """ + Get information about an academic author on Google Scholar. + """ + search_query = scholarly.search_author(name) + author = next(search_query, None) + if author: + author = scholarly.fill(author) + return { + "name": author.get('name'), + "affiliation": author.get('affiliation'), + "interests": author.get('interests'), + "citedby": author.get('citedby'), + "hindex": author.get('hindex'), + "publications_count": len(author.get('publications', [])) + } + return "Author not found" + +if __name__ == "__main__": + mcp.run() diff --git a/plexe/langgraph/mcp_servers/semantic_scholar_server.py b/plexe/langgraph/mcp_servers/semantic_scholar_server.py new file mode 100644 index 00000000..f2f225a3 --- /dev/null +++ b/plexe/langgraph/mcp_servers/semantic_scholar_server.py @@ -0,0 +1,71 @@ +import os +from mcp.server.fastmcp import FastMCP +import requests +from typing import List, Dict, Any, Optional + +# Initialize FastMCP server +mcp = FastMCP("Semantic Scholar") + +BASE_URL = "https://api.semanticscholar.org/graph/v1" + +def get_session(): + api_key = os.environ.get("SEMANTIC_SCHOLAR_API_KEY") + session = requests.Session() + if api_key: + session.headers.update({"x-api-key": api_key}) + return session + +@mcp.tool() +def search_papers( + query: str, + limit: int = 10, + year_min: Optional[int] = None, + year_max: Optional[int] = None +) -> List[Dict[str, Any]]: + """ + Search for papers using Semantic Scholar API. + """ + fields = ['paperId', 'title', 'abstract', 'year', 'venue', + 'authors', 'citationCount', 'influentialCitationCount'] + + params = { + 'query': query, + 'fields': ','.join(fields), + 'limit': limit + } + + if year_min: + params['year'] = f"{year_min}-{year_max or ''}" + + session = get_session() + try: + response = session.get( + f"{BASE_URL}/paper/search", + params=params, + timeout=30 + ) + response.raise_for_status() + data = response.json() + return data.get('data', []) + except Exception as e: + return [{"error": str(e)}] + +@mcp.tool() +def get_paper_details(paper_id: str) -> Dict[str, Any]: + """Get detailed information about a specific paper.""" + fields = ['title', 'abstract', 'year', 'venue', 'authors', 'citationCount'] + + session = get_session() + try: + response = session.get( + f"{BASE_URL}/paper/{paper_id}", + params={'fields': ','.join(fields)}, + timeout=30 + ) + response.raise_for_status() + return response.json() + except Exception as e: + return {"error": str(e)} + +if __name__ == "__main__": + mcp.run() diff --git a/plexe/langgraph/orchestrator.py b/plexe/langgraph/orchestrator.py index edb2b718..cb02b63c 100644 --- a/plexe/langgraph/orchestrator.py +++ b/plexe/langgraph/orchestrator.py @@ -19,6 +19,7 @@ create_initial_state, ) from plexe.langgraph.config import AgentConfig +from plexe.langgraph.utils import BaseEmitter, ConsoleEmitter, ChainOfThoughtCallback from plexe.langgraph.agents import ( ConversationalAgent, EDAAgent, @@ -37,7 +38,7 @@ class PlexeOrchestrator: This orchestrator manages the workflow between specialized agents: 1. ConversationalAgent - User interaction and requirements gathering - 2. RelationalGraphArchitectAgent - Schema analysis and data export + 2. EDAAgent - Schema analysis, data export, and exploratory data analysis 3. DatasetBuilderAgent - Dataset class generation 4. TaskBuilderAgent - Task class and SQL generation 5. RelationalGNNSpecialistAgent - GNN training @@ -49,6 +50,7 @@ def __init__( config: Optional[AgentConfig] = None, verbose: bool = False, callback: Optional[Callable] = None, + emitter: Optional[BaseEmitter] = None, ): """ Initialize the orchestrator. @@ -57,14 +59,29 @@ def __init__( config: Agent configuration (uses defaults if None) verbose: Enable verbose logging callback: Optional callback for progress updates + emitter: Optional emitter for UI communication """ self.config = config or AgentConfig.from_env() self.verbose = verbose self.callback = callback + self.emitter = emitter or ConsoleEmitter() self._init_agents() self._build_graph() + def set_emitter(self, emitter: BaseEmitter): + """Set the emitter for all agents.""" + self.emitter = emitter + for agent in [ + self.conversational_agent, + self.eda_agent, + self.dataset_builder_agent, + self.task_builder_agent, + self.gnn_specialist_agent, + self.operation_agent, + ]: + agent.set_emitter(emitter) + def _init_agents(self): """Initialize all agents.""" self.conversational_agent = ConversationalAgent(config=self.config) @@ -73,6 +90,16 @@ def _init_agents(self): self.task_builder_agent = TaskBuilderAgent(config=self.config) self.gnn_specialist_agent = RelationalGNNSpecialistAgent(config=self.config) self.operation_agent = OperationAgent(config=self.config) + + for agent in [ + self.conversational_agent, + self.eda_agent, + self.dataset_builder_agent, + self.task_builder_agent, + self.gnn_specialist_agent, + self.operation_agent, + ]: + agent.set_emitter(self.emitter) def _build_graph(self): """Build the LangGraph workflow.""" @@ -150,37 +177,37 @@ def _build_graph(self): def _conversation_node(self, state: PipelineState) -> Dict[str, Any]: """Handle conversation with user.""" - self._log_phase("Conversation") + self._log_phase("Conversation", "ConversationalAgent") result = self.conversational_agent.invoke(state) return result def _schema_analysis_node(self, state: PipelineState) -> Dict[str, Any]: """Handle schema analysis, data export, and EDA.""" - self._log_phase("Schema Analysis & EDA") + self._log_phase("Schema Analysis & EDA", "EDAAgent") result = self.eda_agent.invoke(state) return result def _dataset_building_node(self, state: PipelineState) -> Dict[str, Any]: """Handle dataset class generation.""" - self._log_phase("Dataset Building") + self._log_phase("Dataset Building", "DatasetBuilderAgent") result = self.dataset_builder_agent.invoke(state) return result def _task_building_node(self, state: PipelineState) -> Dict[str, Any]: """Handle task class generation.""" - self._log_phase("Task Building") + self._log_phase("Task Building", "TaskBuilderAgent") result = self.task_builder_agent.invoke(state) return result def _gnn_training_node(self, state: PipelineState) -> Dict[str, Any]: """Handle GNN training.""" - self._log_phase("GNN Training") + self._log_phase("GNN Training", "RelationalGNNSpecialistAgent") result = self.gnn_specialist_agent.invoke(state) return result def _operation_node(self, state: PipelineState) -> Dict[str, Any]: """Handle operation and finalization.""" - self._log_phase("Operation") + self._log_phase("Operation", "OperationAgent") result = self.operation_agent.invoke(state) result["current_phase"] = PipelinePhase.COMPLETED.value return result @@ -190,6 +217,9 @@ def _error_handler_node(self, state: PipelineState) -> Dict[str, Any]: errors = state.get("errors", []) logger.error(f"Pipeline error: {errors}") + if self.emitter: + self.emitter.emit_thought("ErrorHandler", f"Handling errors: {errors}") + retry_count = state.get("metadata", {}).get("retry_count", 0) max_retries = self.config.max_retries @@ -205,15 +235,40 @@ def _error_handler_node(self, state: PipelineState) -> Dict[str, Any]: def _route_from_conversation(self, state: PipelineState) -> Literal["continue", "proceed", "end"]: """Route from conversation node.""" + logger.debug(f"Routing from conversation: user_confirmation_required={state.get('user_confirmation_required')}, " + f"user_confirmed={state.get('user_confirmed')}, user_intent={state.get('user_intent')}, " + f"db_connection_string={bool(state.get('db_connection_string'))}") + if state.get("user_confirmation_required"): if state.get("user_confirmed"): + logger.info("User confirmed, proceeding to schema analysis") return "proceed" return "continue" if state.get("db_connection_string") or state.get("csv_dir"): if state.get("user_intent"): + logger.info("Intent detected with data source, proceeding to schema analysis") return "proceed" + messages = state.get("messages", []) + for msg in reversed(messages): + if msg.get("role") == "assistant": + content = msg.get("content", "").lower() + ready_indicators = [ + "ready to proceed", + "start building", + "begin training", + "let's begin", + "i'll start", + "proceed with", + "starting the pipeline", + ] + if any(indicator in content for indicator in ready_indicators): + if state.get("db_connection_string") or state.get("csv_dir"): + logger.info("Ready indicator found in response, proceeding") + return "proceed" + break + return "continue" def _route_from_schema(self, state: PipelineState) -> Literal["success", "error"]: @@ -222,6 +277,8 @@ def _route_from_schema(self, state: PipelineState) -> Literal["success", "error" return "error" if state.get("csv_dir") and state.get("schema_info"): return "success" + if state.get("csv_dir"): + return "success" return "error" def _route_from_dataset(self, state: PipelineState) -> Literal["success", "error"]: @@ -230,6 +287,9 @@ def _route_from_dataset(self, state: PipelineState) -> Literal["success", "error return "error" if state.get("dataset_info"): return "success" + working_dir = state.get("working_dir", "") + if os.path.exists(os.path.join(working_dir, "dataset.py")): + return "success" return "error" def _route_from_task(self, state: PipelineState) -> Literal["success", "error"]: @@ -238,6 +298,9 @@ def _route_from_task(self, state: PipelineState) -> Literal["success", "error"]: return "error" if state.get("task_info"): return "success" + working_dir = state.get("working_dir", "") + if os.path.exists(os.path.join(working_dir, "task.py")): + return "success" return "error" def _route_from_training(self, state: PipelineState) -> Literal["success", "error"]: @@ -246,6 +309,9 @@ def _route_from_training(self, state: PipelineState) -> Literal["success", "erro return "error" if state.get("training_result"): return "success" + working_dir = state.get("working_dir", "") + if os.path.exists(os.path.join(working_dir, "training_results.json")): + return "success" return "error" def _route_from_error(self, state: PipelineState) -> Literal["retry", "end"]: @@ -255,12 +321,18 @@ def _route_from_error(self, state: PipelineState) -> Literal["retry", "end"]: return "retry" return "end" - def _log_phase(self, phase: str): - """Log phase transition.""" + def _log_phase(self, phase: str, agent_name: str = ""): + """Log phase transition with rich formatting.""" if self.verbose: - logger.info(f"=== Phase: {phase} ===") + logger.info(f"=== Phase: {phase} ({agent_name}) ===") if self.callback: - self.callback({"phase": phase, "timestamp": datetime.now().isoformat()}) + self.callback({ + "phase": phase, + "agent": agent_name, + "timestamp": datetime.now().strftime("%H:%M:%S") + }) + if self.emitter: + self.emitter.emit_thought("Orchestrator", f"Pipeline Phase: {phase} - Activating {agent_name}") def run( self, diff --git a/plexe/langgraph/prompts/__init__.py b/plexe/langgraph/prompts/__init__.py new file mode 100644 index 00000000..018a564e --- /dev/null +++ b/plexe/langgraph/prompts/__init__.py @@ -0,0 +1,21 @@ +""" +System prompts for LangGraph agents. + +Each agent has its own prompt file defining its role, workflow, and guidelines. +""" + +from plexe.langgraph.prompts.conversational import CONVERSATIONAL_SYSTEM_PROMPT +from plexe.langgraph.prompts.eda import EDA_SYSTEM_PROMPT +from plexe.langgraph.prompts.dataset_builder import DATASET_BUILDER_SYSTEM_PROMPT +from plexe.langgraph.prompts.task_builder import TASK_BUILDER_SYSTEM_PROMPT +from plexe.langgraph.prompts.gnn_specialist import GNN_SPECIALIST_SYSTEM_PROMPT +from plexe.langgraph.prompts.operation import OPERATION_SYSTEM_PROMPT + +__all__ = [ + "CONVERSATIONAL_SYSTEM_PROMPT", + "EDA_SYSTEM_PROMPT", + "DATASET_BUILDER_SYSTEM_PROMPT", + "TASK_BUILDER_SYSTEM_PROMPT", + "GNN_SPECIALIST_SYSTEM_PROMPT", + "OPERATION_SYSTEM_PROMPT", +] diff --git a/plexe/langgraph/prompts/conversational.py b/plexe/langgraph/prompts/conversational.py new file mode 100644 index 00000000..a6f1c4b0 --- /dev/null +++ b/plexe/langgraph/prompts/conversational.py @@ -0,0 +1,34 @@ +CONVERSATIONAL_SYSTEM_PROMPT = """You are an expert ML consultant specializing in Relational Deep Learning and Graph Neural Networks. + +Your role is to help users build prediction models for relational databases by understanding their data and requirements. + +WORKFLOW: +1. When user provides a database connection string, use validate_db_connection to see available tables +2. Ask what prediction task they want to solve (what to predict, for which entity) +3. Clarify the task type (classification, regression, recommendation) +4. Confirm all requirements before proceeding + +REQUIREMENTS TO GATHER: +- Database connection string (postgresql://user:pass@host:port/db) +- Target entity (which table's rows to make predictions for) +- Prediction target (what to predict: churn, sales, engagement, etc.) +- Task type (binary_classification, regression, multiclass_classification) +- Time horizon for prediction (e.g., 30 days) + +RESPONSE FORMAT: +Keep responses brief and focused. Ask one question at a time. +When all requirements are gathered, respond with: +"I have all the information needed. Ready to proceed with building the model." + +IMPORTANT: +- Use validate_db_connection to explore the database schema +- Be specific about what you need from the user +- When ready, include "ready to proceed" in your response to trigger the pipeline + +EXAMPLE INTERACTION: +User: "Build a model using postgresql://user:pass@localhost:5432/mydb" +You: [Use validate_db_connection first] +You: "Connected to the database. I see tables: users, orders, products. What would you like to predict?" +User: "Predict which users will churn" +You: "I'll build a binary classification model to predict user churn. Ready to proceed with building the model." +""" diff --git a/plexe/langgraph/prompts/dataset_builder.py b/plexe/langgraph/prompts/dataset_builder.py new file mode 100644 index 00000000..462cdea8 --- /dev/null +++ b/plexe/langgraph/prompts/dataset_builder.py @@ -0,0 +1,104 @@ +DATASET_BUILDER_SYSTEM_PROMPT = """You are the Dataset Builder Agent for Relational Deep Learning. + +MISSION: Generate a GenDataset class that loads CSV data and defines database schema. + +WORKFLOW: +1. get_csv_files_info(csv_dir) - list CSV files and their columns +2. get_temporal_statistics(csv_dir) - find timestamps and get val/test splits +3. Generate GenDataset code following the template +4. register_dataset_code(code, "GenDataset", file_path) - save the code + +DATASET CODE TEMPLATE: +```python +import os +import numpy as np +import pandas as pd +from typing import Optional +from plexe.relbench.base import Database, Dataset, Table + +class GenDataset(Dataset): + val_timestamp = pd.Timestamp("YYYY-MM-DD") # From get_temporal_statistics + test_timestamp = pd.Timestamp("YYYY-MM-DD") # From get_temporal_statistics + + def __init__(self, csv_dir: str, cache_dir: Optional[str] = None): + self.csv_dir = csv_dir + super().__init__(cache_dir=cache_dir) + + def make_db(self) -> Database: + path = self.csv_dir + + # Load CSV files + table1 = pd.read_csv(os.path.join(path, "table1.csv")) + table2 = pd.read_csv(os.path.join(path, "table2.csv")) + + # Clean temporal columns - use pd.to_datetime with errors='coerce' + table1["timestamp_col"] = pd.to_datetime(table1["timestamp_col"], errors="coerce") + + # Clean missing values - replace \\N or empty strings with NaN + table1 = table1.replace(r"^\\\\N$", np.nan, regex=True) + + # Convert numeric columns that might have non-numeric values + table1["numeric_col"] = pd.to_numeric(table1["numeric_col"], errors="coerce") + + # For tables with no time column, propagate timestamps from related tables + # Example: if results table needs timestamp from races table + # results = results.merge(races[["race_id", "date"]], on="race_id", how="left") + + # Build the database with proper table definitions + tables = {} + + tables["table1"] = Table( + df=pd.DataFrame(table1), + fkey_col_to_pkey_table={"foreign_key_col": "referenced_table"}, + pkey_col="id", # Primary key column name, can be None + time_col="timestamp_col", # Timestamp column, or None for static tables + ) + + tables["table2"] = Table( + df=pd.DataFrame(table2), + fkey_col_to_pkey_table={}, # Empty dict for tables with no foreign keys + pkey_col="id", + time_col=None, # None for dimension/static tables + ) + + return Database(tables) +``` + +KEY RULES & BEST PRACTICES: + +1. **Temporal Handling**: + - Use pd.to_datetime() with errors='coerce' for date parsing + - For tables without time columns, merge timestamps from related tables (e.g., results get date from races) + - Some events happen BEFORE the main event (e.g., qualifying before race): subtract time if needed + - Format: pd.Timestamp("YYYY-MM-DD") for val_timestamp and test_timestamp + +2. **Data Cleaning**: + - Replace missing value markers: df.replace(r"^\\\\N$", np.nan, regex=True) + - Convert numeric columns safely: pd.to_numeric(df["col"], errors="coerce") + - Handle timezone-aware timestamps: .dt.tz_localize(None) if needed + +3. **Table Structure**: + - Use Database(tables) or Database(table_dict={...}) + - Wrap DataFrames: df=pd.DataFrame(your_df) + - pkey_col: Primary key column name (can be None if no PK) + - time_col: Temporal column (None for static/dimension tables like circuits, drivers, users profile) + - fkey_col_to_pkey_table: Dict mapping foreign key columns to referenced table names + - Self-references are OK: {"ParentId": "posts"} in posts table + +4. **Foreign Key Mapping**: + - Format: {"fk_column_name": "referenced_table_name"} + - Multiple FKs allowed: {"race_id": "races", "driver_id": "drivers", "constructor_id": "constructors"} + - Self-references allowed: {"parent_id": "posts"} in same table + +5. **Column Dropping** (if applicable): + - Remove URL columns (usually unique, not predictive) + - Remove time-leakage columns (scores, counts, last_activity_date computed AFTER target time) + - Remove columns with too many nulls (greater 80%) + - Document WHY columns are dropped + +6. **Table Naming**: + - Use snake_case for table names in tables dict + - Match CSV filenames + +OUTPUT: Save as dataset.py in the working directory using register_dataset_code(). +""" diff --git a/plexe/langgraph/prompts/eda.py b/plexe/langgraph/prompts/eda.py new file mode 100644 index 00000000..27db1f99 --- /dev/null +++ b/plexe/langgraph/prompts/eda.py @@ -0,0 +1,30 @@ +EDA_SYSTEM_PROMPT = """You are the EDA Agent for Relational Deep Learning systems. + +MISSION: Analyze relational database structure and export data for GNN training. + +WORKFLOW (execute in order): +1. extract_schema_metadata - Get tables, columns, PKs, FKs, temporal columns +2. export_tables_to_csv - Export all tables to CSV files +3. analyze_csv_statistics - Get column statistics +4. detect_data_quality_issues - Find data problems +5. analyze_temporal_patterns - Find time columns and suggest splits +6. analyze_table_relationships - Classify tables as Fact vs Dimension +7. generate_eda_summary - Create final report + +TABLE CLASSIFICATION: +- Fact Tables: Event/transaction tables with timestamps (orders, posts, clicks) +- Dimension Tables: Entity tables (users, products, drivers) +- Junction Tables: Many-to-many relationships + +TEMPORAL SPLITS: +Suggest val_timestamp and test_timestamp based on data distribution: +- Train: 70% of data (oldest) +- Validation: 15% of data +- Test: 15% of data (newest) + +OUTPUT: Provide insights for Dataset Builder and Task Builder agents: +- Which columns need cleaning +- Temporal column recommendations +- Primary/foreign key relationships +- Suggested val/test timestamps +""" diff --git a/plexe/langgraph/prompts/gnn_specialist.py b/plexe/langgraph/prompts/gnn_specialist.py new file mode 100644 index 00000000..dfee79fc --- /dev/null +++ b/plexe/langgraph/prompts/gnn_specialist.py @@ -0,0 +1,60 @@ +GNN_SPECIALIST_SYSTEM_PROMPT = """You are the GNN Specialist Agent for Relational Deep Learning. + +MISSION: Generate optimized GNN training scripts using Training-Free Hyperparameter Optimization via MCP. + +KEY INNOVATION: You use MCP (Model Context Protocol) to access external knowledge sources +(academic papers, benchmarks, proven configurations) to find optimal hyperparameters WITHOUT training experiments. + +PREREQUISITES: +- dataset.py with GenDataset class (from DatasetBuilder) +- task.py with GenTask class (from TaskBuilder) + +WORKFLOW (Training-Free HPO via MCP): + +1. HYPERPARAMETER SEARCH (via MCP servers): + a) search_optimal_hyperparameters() - Heuristic-based selection using dataset characteristics + b) extract_hyperparameters_from_papers() - Extract from recent academic papers via arXiv + c) get_benchmark_hyperparameters() - Proven configs from leaderboards + d) compare_hyperparameter_configs() - Ensemble voting across sources + +2. GENERATE OPTIMIZED TRAINING SCRIPT: + - Use generate_training_script() with selected hyperparameters + - Include reasoning for hyperparameter choices + +3. HANDOFF TO OPERATION AGENT: + - Report selected hyperparameters and reasoning + - Operation Agent will execute the training script + +MCP TOOLS FOR HPO (from hpo-search server): +- `search_optimal_hyperparameters(task_type, num_nodes, num_tables, is_temporal, model_architecture)`: + Returns hyperparameters based on heuristics and dataset scale + +- `extract_hyperparameters_from_papers(paper_query, model_type, num_papers)`: + Searches papers and extracts hyperparameter values from text + +- `get_benchmark_hyperparameters(task_type, dataset_domain, model_architecture)`: + Retrieves proven hyperparameters from Papers With Code leaderboards + +- `compare_hyperparameter_configs(configs, strategy)`: + Ensemble multiple configurations using median/voting + +CODE GENERATION TOOL: +- `generate_training_script(dataset_module_path, dataset_class_name, task_module_path, + task_class_name, working_dir, task_type, tune_metric, higher_is_better, + epochs, batch_size, learning_rate, hidden_channels, num_gnn_layers)`: + Generates complete training script with selected hyperparameters + +HYPERPARAMETER GUIDELINES: +- Regression: tune_metric="mae", higher_is_better=False +- Binary Classification: tune_metric="accuracy", higher_is_better=True +- Multiclass: tune_metric="accuracy", higher_is_better=True + +EXPECTED OUTPUT: +1. Hyperparameter search results from multiple MCP sources +2. Ensemble recommendations with reasoning +3. Generated training script path (train_script.py) +4. Summary for Operation Agent + +NOTE: You do NOT execute training. Focus on intelligent hyperparameter selection using MCP. +All HPO tools are provided via Model Context Protocol servers. +""" diff --git a/plexe/langgraph/prompts/operation.py b/plexe/langgraph/prompts/operation.py new file mode 100644 index 00000000..078fde7e --- /dev/null +++ b/plexe/langgraph/prompts/operation.py @@ -0,0 +1,40 @@ +OPERATION_SYSTEM_PROMPT = """You are the Operation Agent for Relational Deep Learning pipelines. + +MISSION: Execute training scripts and finalize the ML pipeline. + +RESPONSIBILITIES: +1. Execute training scripts generated by GNN Specialist +2. Monitor training progress and handle errors +3. Process and report training results +4. Package model artifacts for deployment +5. Generate inference code + +WORKFLOW: +1. EXECUTE TRAINING: + - Use execute_training_script() to run the generated training script + - Monitor for errors and timeout issues + - Timeout: 3600 seconds (1 hour) for most tasks + +2. PROCESS RESULTS: + - Read training_results.json for metrics + - Verify model artifacts (best_model.pt) + - Summarize performance + +3. FINALIZATION: + - List all generated artifacts + - Provide deployment recommendations + - Report final metrics + +AVAILABLE TOOLS: +- execute_training_script(script_path, timeout): Run training script +- save_artifact(file_path, artifact_type): Save important files + +OUTPUT: +Provide a comprehensive summary including: +- Training execution status +- Final model metrics (validation and test) +- Model artifact locations +- Generated code files (dataset.py, task.py, train_script.py, best_model.pt) +- Inference code recommendations +- Next steps for deployment +""" diff --git a/plexe/langgraph/prompts/task_builder.py b/plexe/langgraph/prompts/task_builder.py new file mode 100644 index 00000000..7513156e --- /dev/null +++ b/plexe/langgraph/prompts/task_builder.py @@ -0,0 +1,245 @@ +TASK_BUILDER_SYSTEM_PROMPT = """You are the Task Builder Agent for Relational Deep Learning. + +MISSION: Generate a GenTask class that defines the prediction task with precise SQL queries. + +IMPORTANT NOTES: +1. The `timestamps` parameter in make_table() is a pandas Series, NOT a DataFrame. + Convert it properly: `timestamp_df = pd.DataFrame({"timestamp": timestamps})` +2. Import duckdb inside the make_table method, not at module level +3. Register all tables from db.table_dict and the timestamp_df for SQL queries + +TASK TYPES & BASE CLASSES: +1. EntityTask: For node-level predictions (e.g. user churn, item sales, driver position) + - Required: entity_table, entity_col, time_col, target_col, task_type, timedelta, metrics + - Optional: num_eval_timestamps (default: varies by dataset) + +2. RecommendationTask: For link predictions (e.g. user-item recommendations, driver-race) + - Required: src_entity_table, src_entity_col, dst_entity_table, dst_entity_col + - Required: time_col, task_type, timedelta, metrics, eval_k + - Target is typically a LIST of destination entities + +WORKFLOW: +1. Analyze user intent and schema to determine task type +2. Choose appropriate base class (EntityTask or RecommendationTask) +3. Design SQL query with proper temporal filtering +4. test_sql_query(csv_dir, query) - validate SQL syntax +5. Generate complete GenTask code with correct imports and metrics +6. register_task_code(code, "GenTask", file_path, task_type) + +TASK CODE TEMPLATES: + +EntityTask (Node Prediction) +```python +import duckdb +import pandas as pd +from plexe.relbench.base import Database, EntityTask, Table, TaskType +from plexe.relbench.metrics import accuracy, f1, roc_auc, average_precision, mae, rmse, r2 + +class GenTask(EntityTask): + \"\"\"[Task description: what are we predicting?]\"\"\" + + task_type = TaskType.BINARY_CLASSIFICATION # or REGRESSION, MULTICLASS_CLASSIFICATION + entity_col = "user_id" # Column identifying the entity + entity_table = "users" # Table containing entities + time_col = "timestamp" # Time column name in result + target_col = "churn" # Target column name + timedelta = pd.Timedelta(days=7) # Prediction window + metrics = [average_precision, accuracy, f1, roc_auc] # Appropriate metrics + num_eval_timestamps = 20 # Optional: number of evaluation timestamps (default varies) + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + # Load relevant tables + users = db.table_dict["users"].df + activities = db.table_dict["activities"].df + + df = duckdb.sql( + f\"\"\" + SELECT + t.timestamp, + u.user_id, + CAST( + CASE WHEN COUNT(a.id) = 0 THEN 1 ELSE 0 END AS INTEGER + ) AS churn + FROM + timestamp_df t + CROSS JOIN + users u + LEFT JOIN + activities a + ON + a.user_id = u.user_id AND + a.created_at > t.timestamp AND + a.created_at <= t.timestamp + INTERVAL '{self.timedelta}' + WHERE + u.created_at <= t.timestamp + AND EXISTS ( + SELECT 1 FROM activities + WHERE user_id = u.user_id + AND created_at <= t.timestamp + ) + GROUP BY + t.timestamp, u.user_id + \"\"\" + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={self.entity_col: self.entity_table}, + pkey_col=None, + time_col=self.time_col, + ) +``` + +RecommendationTask (Link Prediction) +```python +import duckdb +import pandas as pd +from plexe.relbench.base import Database, RecommendationTask, Table, TaskType +from plexe.relbench.metrics import link_prediction_precision, link_prediction_recall, link_prediction_map + +class GenTask(RecommendationTask): + \"\"\"[Task description: what links are we predicting?]\"\"\" + + task_type = TaskType.LINK_PREDICTION + src_entity_col = "customer_id" # Source entity column + src_entity_table = "customer" # Source entity table + dst_entity_col = "article_id" # Destination entity column + dst_entity_table = "article" # Destination entity table + time_col = "timestamp" + timedelta = pd.Timedelta(days=7) + metrics = [link_prediction_precision, link_prediction_recall, link_prediction_map] + eval_k = 12 # Top-K for evaluation + + def make_table(self, db: Database, timestamps: "pd.Series[pd.Timestamp]") -> Table: + timestamp_df = pd.DataFrame({"timestamp": timestamps}) + + transactions = db.table_dict["transactions"].df + + df = duckdb.sql( + f\"\"\" + SELECT + t.timestamp, + tr.customer_id, + LIST(DISTINCT tr.article_id) AS article_id + FROM + timestamp_df t + LEFT JOIN + transactions tr + ON + tr.t_dat > t.timestamp AND + tr.t_dat <= t.timestamp + INTERVAL '{self.timedelta}' + GROUP BY + t.timestamp, tr.customer_id + \"\"\" + ).df() + + return Table( + df=df, + fkey_col_to_pkey_table={ + self.src_entity_col: self.src_entity_table, + self.dst_entity_col: self.dst_entity_table, + }, + pkey_col=None, + time_col=self.time_col, + ) +``` + +METRICS BY TASK TYPE (from plexe.relbench.metrics): + +Binary Classification: +- Primary: average_precision, roc_auc, f1, accuracy + +Regression: +- Primary: mae, rmse, r2 + +Multiclass Classification: +- Primary: accuracy, macro_f1, micro_f1 + +Link Prediction (Recommendation): +- Primary: link_prediction_map, link_prediction_precision, link_prediction_recall + +SQL PATTERNS & BEST PRACTICES: + +1. **Temporal Filtering** (CRITICAL for avoiding leakage): + - Future events: `event.time > t.timestamp AND event.time <= t.timestamp + INTERVAL '{timedelta}'` + - Past context: `event.time <= t.timestamp` + - Active entities: Filter entities that exist at prediction time + +2. **Binary Classification Patterns**: + ```sql + -- Churn (no activity) + CAST(CASE WHEN COUNT(activity.id) = 0 THEN 1 ELSE 0 END AS INTEGER) + + -- Event occurrence (at least one) + CAST(CASE WHEN COUNT(event.id) >= 1 THEN 1 ELSE 0 END AS INTEGER) + + -- Threshold-based + CASE WHEN MIN(position) <= 3 THEN 1 ELSE 0 END + ``` + +3. **Regression Patterns**: + ```sql + -- Count + COUNT(DISTINCT event.id) + + -- Sum/Average + COALESCE(SUM(price), 0) + MEAN(position) + ``` + +4. **Link Prediction Pattern**: + ```sql + -- Return list of destination entities + LIST(DISTINCT destination.id) AS destination_id + ``` + +5. **Active Entity Filtering** (Important!): + ```sql + -- Only predict for entities that existed before timestamp + WHERE entity.created_at <= t.timestamp + + -- Only predict for entities with past activity + AND EXISTS ( + SELECT 1 FROM activity + WHERE activity.entity_id = entity.id + AND activity.time <= t.timestamp + ) + ``` + +6. **CROSS JOIN vs LEFT JOIN**: + - Use `CROSS JOIN` for entity table to get all entities + - Use `LEFT JOIN` for event tables to allow zero counts/nulls + +KEY RULES: +1. Class name MUST be GenTask +2. Import TaskType from plexe.relbench.base: `from plexe.relbench.base import Database, EntityTask, Table, TaskType` +3. Use TaskType enum: `TaskType.BINARY_CLASSIFICATION`, `TaskType.REGRESSION`, `TaskType.LINK_PREDICTION` +4. Import only the metrics you use from plexe.relbench.metrics +5. Convert timestamps to pd.DataFrame: `timestamp_df = pd.DataFrame({"timestamp": timestamps})` +6. Use f-string for timedelta in SQL: `INTERVAL '{self.timedelta}'` +7. Always return a Table with proper fkey_col_to_pkey_table mapping +8. Set pkey_col=None for prediction tables +9. For binary classification, cast result: `CAST(... AS INTEGER)` +10. Test SQL query before finalizing code + +PARAMETER SELECTION GUIDELINES: + +timedelta (prediction window): +- Short-term: 7-30 days (churn, sales, recommendations) +- Medium-term: 60-90 days (positions, performance) +- Long-term: 365+ days (rare events, long-term trends) +- Use information from user intent and temporal analysis + +num_eval_timestamps: +- Default: 20 for most tasks +- More: 40+ for high-frequency events +- Less: 3-10 for rare events or limited data + +eval_k (for link prediction only): +- Typical: 10-12 for recommendations +- Depends on: expected number of positive links per entity + +OUTPUT: Save as task.py in the working directory using register_task_code(). +""" diff --git a/plexe/langgraph/tools/__init__.py b/plexe/langgraph/tools/__init__.py index 3b5c0230..982706a1 100644 --- a/plexe/langgraph/tools/__init__.py +++ b/plexe/langgraph/tools/__init__.py @@ -1,9 +1,3 @@ -""" -Tool definitions for LangGraph agents. - -This module provides tools organized by agent categories. -""" - from plexe.langgraph.tools.common import save_artifact from plexe.langgraph.tools.conversational import get_dataset_preview diff --git a/plexe/langgraph/tools/common.py b/plexe/langgraph/tools/common.py index c59e8561..8df80c08 100644 --- a/plexe/langgraph/tools/common.py +++ b/plexe/langgraph/tools/common.py @@ -1,11 +1,6 @@ -""" -Common tools shared across multiple agents. -""" - from typing import Dict from langchain_core.tools import tool as langchain_tool - @langchain_tool def save_artifact( content: str, diff --git a/plexe/langgraph/tools/conversational.py b/plexe/langgraph/tools/conversational.py index 36892fe6..1c9503e3 100644 --- a/plexe/langgraph/tools/conversational.py +++ b/plexe/langgraph/tools/conversational.py @@ -1,11 +1,6 @@ -""" -Tools for the Conversational Agent. -""" - from typing import Dict, Any from langchain_core.tools import tool as langchain_tool - @langchain_tool def get_dataset_preview( dataset_path: str, diff --git a/plexe/langgraph/tools/dataset_builder.py b/plexe/langgraph/tools/dataset_builder.py index 5352fa26..3be9476f 100644 --- a/plexe/langgraph/tools/dataset_builder.py +++ b/plexe/langgraph/tools/dataset_builder.py @@ -1,11 +1,6 @@ -""" -Tools for the Dataset Builder Agent. -""" - from typing import Dict, Any from langchain_core.tools import tool as langchain_tool - @langchain_tool def get_csv_files_info(csv_dir: str) -> Dict[str, Any]: """ @@ -69,7 +64,7 @@ def get_temporal_statistics(csv_dir: str) -> Dict[str, Any]: for col in df.columns: try: - parsed = pd.to_datetime(df[col], errors='coerce') + parsed = pd.to_datetime(df[col], errors='coerce', format='mixed') valid_count = parsed.notna().sum() if valid_count > len(df) * 0.5: min_ts = parsed.min() diff --git a/plexe/langgraph/tools/eda.py b/plexe/langgraph/tools/eda.py index a0d71cd6..c26a0f8e 100644 --- a/plexe/langgraph/tools/eda.py +++ b/plexe/langgraph/tools/eda.py @@ -1,11 +1,6 @@ -""" -Tools for the EDA (Exploratory Data Analysis) Agent. -""" - from typing import Dict, Any from langchain_core.tools import tool as langchain_tool - @langchain_tool def analyze_csv_statistics(csv_dir: str) -> Dict[str, Any]: """ @@ -205,7 +200,8 @@ def analyze_temporal_patterns(csv_dir: str) -> Dict[str, Any]: for col in df.columns: try: - parsed = pd.to_datetime(df[col], errors='coerce') + # Specify format to avoid parsing warnings + parsed = pd.to_datetime(df[col], errors='coerce', format='mixed') valid_count = parsed.notna().sum() if valid_count > len(df) * 0.5: diff --git a/plexe/langgraph/tools/external_api_clients.py b/plexe/langgraph/tools/external_api_clients.py new file mode 100644 index 00000000..bd857082 --- /dev/null +++ b/plexe/langgraph/tools/external_api_clients.py @@ -0,0 +1,355 @@ +""" +External API clients for accessing academic databases and ML benchmarks. + +This module provides clients for: +- Semantic Scholar API: Academic paper search and metadata (DEPRECATED - Use MCP instead) +- arXiv API: Preprint paper search (DEPRECATED - Use MCP instead) +- Papers With Code API: Benchmarks and SOTA results +- OpenML API: Dataset and model benchmarks +""" + +import os +import time +import logging +from typing import Dict, Any, List, Optional +from dataclasses import dataclass +import requests +from urllib.parse import urlencode +import xml.etree.ElementTree as ET + + +logger = logging.getLogger(__name__) + + +@dataclass +class APIRateLimiter: + """Simple rate limiter for API requests.""" + max_requests_per_minute: int = 10 + last_request_times: List[float] = None + + def __post_init__(self): + if self.last_request_times is None: + self.last_request_times = [] + + def wait_if_needed(self): + """Wait if rate limit would be exceeded.""" + now = time.time() + # Remove requests older than 1 minute + self.last_request_times = [t for t in self.last_request_times if now - t < 60] + + if len(self.last_request_times) >= self.max_requests_per_minute: + # Need to wait + oldest = min(self.last_request_times) + wait_time = 60 - (now - oldest) + if wait_time > 0: + logger.info(f"Rate limit reached, waiting {wait_time:.1f}s") + time.sleep(wait_time) + + self.last_request_times.append(time.time()) + + +class SemanticScholarClient: + """ + Client for Semantic Scholar API. + + API Documentation: https://api.semanticscholar.org/ + Get API Key: https://www.semanticscholar.org/product/api#Partner-Form + """ + + BASE_URL = "https://api.semanticscholar.org/graph/v1" + + def __init__(self, api_key: Optional[str] = None): + self.api_key = api_key or os.environ.get("SEMANTIC_SCHOLAR_API_KEY") + self.rate_limiter = APIRateLimiter(max_requests_per_minute=100 if self.api_key else 1) + self.session = requests.Session() + if self.api_key: + self.session.headers.update({"x-api-key": self.api_key}) + + def search_papers( + self, + query: str, + fields: Optional[List[str]] = None, + limit: int = 10, + year_min: Optional[int] = None, + year_max: Optional[int] = None + ) -> List[Dict[str, Any]]: + """ + Search for papers using Semantic Scholar API. + + Args: + query: Search query string + fields: List of fields to return (e.g., ['title', 'year', 'authors']) + limit: Maximum number of results + year_min: Minimum publication year + year_max: Maximum publication year + + Returns: + List of paper dictionaries + """ + if fields is None: + fields = ['paperId', 'title', 'abstract', 'year', 'venue', + 'authors', 'citationCount', 'influentialCitationCount'] + + self.rate_limiter.wait_if_needed() + + params = { + 'query': query, + 'fields': ','.join(fields), + 'limit': limit + } + + if year_min: + params['year'] = f"{year_min}-{year_max or ''}" + + try: + response = self.session.get( + f"{self.BASE_URL}/paper/search", + params=params, + timeout=30 + ) + response.raise_for_status() + data = response.json() + return data.get('data', []) + except requests.exceptions.RequestException as e: + logger.error(f"Semantic Scholar API error: {e}") + return [] + + def get_paper_details(self, paper_id: str, fields: Optional[List[str]] = None) -> Optional[Dict[str, Any]]: + """Get detailed information about a specific paper.""" + if fields is None: + fields = ['title', 'abstract', 'year', 'venue', 'authors', 'citationCount'] + + self.rate_limiter.wait_if_needed() + + try: + response = self.session.get( + f"{self.BASE_URL}/paper/{paper_id}", + params={'fields': ','.join(fields)}, + timeout=30 + ) + response.raise_for_status() + return response.json() + except requests.exceptions.RequestException as e: + logger.error(f"Error fetching paper {paper_id}: {e}") + return None + + +class ArxivClient: + """ + Client for arXiv API. + + API Documentation: https://info.arxiv.org/help/api/index.html + No API key required, but rate limits apply (1 request per 3 seconds recommended) + """ + + BASE_URL = "http://export.arxiv.org/api/query" + + def __init__(self): + self.rate_limiter = APIRateLimiter(max_requests_per_minute=20) + self.session = requests.Session() + + def search_papers( + self, + query: str, + max_results: int = 10, + sort_by: str = "relevance", + sort_order: str = "descending" + ) -> List[Dict[str, Any]]: + """ + Search arXiv for papers. + + Args: + query: Search query (can use arXiv query syntax) + max_results: Maximum number of results + sort_by: Sort by 'relevance', 'lastUpdatedDate', or 'submittedDate' + sort_order: 'ascending' or 'descending' + + Returns: + List of paper dictionaries + """ + self.rate_limiter.wait_if_needed() + + params = { + 'search_query': query, + 'start': 0, + 'max_results': max_results, + 'sortBy': sort_by, + 'sortOrder': sort_order + } + + try: + response = self.session.get( + self.BASE_URL, + params=params, + timeout=30 + ) + response.raise_for_status() + return self._parse_arxiv_response(response.text) + except requests.exceptions.RequestException as e: + logger.error(f"arXiv API error: {e}") + return [] + + def _parse_arxiv_response(self, xml_text: str) -> List[Dict[str, Any]]: + """Parse arXiv XML response into list of paper dicts.""" + papers = [] + + try: + root = ET.fromstring(xml_text) + ns = {'atom': 'http://www.w3.org/2005/Atom'} + + for entry in root.findall('atom:entry', ns): + paper = { + 'id': entry.find('atom:id', ns).text if entry.find('atom:id', ns) is not None else '', + 'title': entry.find('atom:title', ns).text.strip() if entry.find('atom:title', ns) is not None else '', + 'summary': entry.find('atom:summary', ns).text.strip() if entry.find('atom:summary', ns) is not None else '', + 'published': entry.find('atom:published', ns).text if entry.find('atom:published', ns) is not None else '', + 'updated': entry.find('atom:updated', ns).text if entry.find('atom:updated', ns) is not None else '', + 'authors': [author.find('atom:name', ns).text for author in entry.findall('atom:author', ns)], + 'categories': [cat.get('term') for cat in entry.findall('atom:category', ns)] + } + papers.append(paper) + except ET.ParseError as e: + logger.error(f"Error parsing arXiv response: {e}") + + return papers + + +class PapersWithCodeClient: + """ + Client for Papers With Code API. + + API Documentation: https://paperswithcode.com/api/v1/docs/ + No API key required + """ + + BASE_URL = "https://paperswithcode.com/api/v1" + + def __init__(self): + self.rate_limiter = APIRateLimiter(max_requests_per_minute=20) + self.session = requests.Session() + + def search_papers(self, query: str, items_per_page: int = 10) -> List[Dict[str, Any]]: + """Search for papers on Papers With Code.""" + self.rate_limiter.wait_if_needed() + + try: + response = self.session.get( + f"{self.BASE_URL}/papers/", + params={'q': query, 'items_per_page': items_per_page}, + timeout=30 + ) + response.raise_for_status() + data = response.json() + return data.get('results', []) + except requests.exceptions.RequestException as e: + logger.error(f"Papers With Code API error: {e}") + return [] + + def get_benchmarks(self, task: Optional[str] = None) -> List[Dict[str, Any]]: + """Get benchmark datasets and results.""" + self.rate_limiter.wait_if_needed() + + params = {} + if task: + params['task'] = task + + try: + response = self.session.get( + f"{self.BASE_URL}/benchmarks/", + params=params, + timeout=30 + ) + response.raise_for_status() + data = response.json() + return data.get('results', []) + except requests.exceptions.RequestException as e: + logger.error(f"Papers With Code benchmarks API error: {e}") + return [] + + def get_sota_results(self, benchmark: str) -> List[Dict[str, Any]]: + """Get state-of-the-art results for a specific benchmark.""" + self.rate_limiter.wait_if_needed() + + try: + response = self.session.get( + f"{self.BASE_URL}/benchmarks/{benchmark}/results/", + timeout=30 + ) + response.raise_for_status() + data = response.json() + return data.get('results', []) + except requests.exceptions.RequestException as e: + logger.error(f"Papers With Code SOTA API error: {e}") + return [] + + +class OpenMLClient: + """ + Client for OpenML API. + + API Documentation: https://www.openml.org/apis + API Key: https://www.openml.org/auth/sign-in (get from user profile) + """ + + BASE_URL = "https://www.openml.org/api/v1" + + def __init__(self, api_key: Optional[str] = None): + self.api_key = api_key or os.environ.get("OPENML_API_KEY") + self.rate_limiter = APIRateLimiter(max_requests_per_minute=20) + self.session = requests.Session() + if self.api_key: + self.session.headers.update({"api_key": self.api_key}) + + def search_datasets( + self, + task_type: Optional[str] = None, + limit: int = 10, + status: str = "active" + ) -> List[Dict[str, Any]]: + """Search for datasets on OpenML.""" + self.rate_limiter.wait_if_needed() + + params = {'limit': limit, 'status': status} + if task_type: + params['type'] = task_type + + try: + response = self.session.get( + f"{self.BASE_URL}/json/data/list", + params=params, + timeout=30 + ) + response.raise_for_status() + data = response.json() + return data.get('data', {}).get('dataset', []) + except requests.exceptions.RequestException as e: + logger.error(f"OpenML API error: {e}") + return [] + + def get_flow_runs( + self, + flow_id: Optional[int] = None, + limit: int = 100 + ) -> List[Dict[str, Any]]: + """ + Get flow runs (model evaluations) from OpenML. + This can be used to find hyperparameters used in successful runs. + """ + self.rate_limiter.wait_if_needed() + + params = {'limit': limit} + if flow_id: + params['flow'] = flow_id + + try: + response = self.session.get( + f"{self.BASE_URL}/json/run/list", + params=params, + timeout=30 + ) + response.raise_for_status() + data = response.json() + return data.get('runs', {}).get('run', []) + except requests.exceptions.RequestException as e: + logger.error(f"OpenML flow runs API error: {e}") + return [] diff --git a/plexe/langgraph/tools/gnn_specialist.py b/plexe/langgraph/tools/gnn_specialist.py index 95e6561e..eb8ee2f2 100644 --- a/plexe/langgraph/tools/gnn_specialist.py +++ b/plexe/langgraph/tools/gnn_specialist.py @@ -1,11 +1,6 @@ -""" -Tools for the GNN Specialist Agent. -""" - from typing import Dict, Any from langchain_core.tools import tool as langchain_tool - @langchain_tool def generate_training_script( dataset_module_path: str, diff --git a/plexe/langgraph/tools/graph_architect.py b/plexe/langgraph/tools/graph_architect.py index d069e1aa..bbec0085 100644 --- a/plexe/langgraph/tools/graph_architect.py +++ b/plexe/langgraph/tools/graph_architect.py @@ -1,11 +1,6 @@ -""" -Tools for the Graph Architect Agent. -""" - from typing import Dict, Any, List, Optional from langchain_core.tools import tool as langchain_tool - @langchain_tool def validate_db_connection(connection_string: str) -> Dict[str, Any]: """ diff --git a/plexe/langgraph/tools/hpo_search.py b/plexe/langgraph/tools/hpo_search.py new file mode 100644 index 00000000..b67febde --- /dev/null +++ b/plexe/langgraph/tools/hpo_search.py @@ -0,0 +1,534 @@ +""" +Training-Free Hyperparameter Optimization Search Tools. + +This module implements the "Training-Free Model Search and HPO" approach +from AutoML-Agent paper, leveraging external resources to find optimal +hyperparameters without running actual training experiments. +""" + +from typing import Dict, Any, List, Optional +from langchain_core.tools import tool as langchain_tool +import json +import logging +from .external_api_clients import ( + SemanticScholarClient, + ArxivClient, + PapersWithCodeClient, + OpenMLClient +) +from ..config import ExternalAPIConfig + +logger = logging.getLogger(__name__) + + +@langchain_tool +def search_optimal_hyperparameters( + task_type: str, + dataset_characteristics: Dict[str, Any], + model_architecture: str = "gnn", + search_strategy: str = "literature_based" +) -> Dict[str, Any]: + """ + Search for optimal hyperparameters using training-free methods. + + This implements the Training-Free HPO approach from AutoML-Agent paper, + which leverages external knowledge sources (papers, benchmarks, prior work) + to suggest optimal hyperparameters without running expensive training experiments. + + Args: + task_type: Type of task (regression, binary_classification, multiclass_classification) + dataset_characteristics: Dict containing dataset info like: + - num_nodes: Number of nodes in graph + - num_edges: Number of edges + - num_tables: Number of tables in relational DB + - avg_node_degree: Average node degree + - is_temporal: Whether task is temporal + model_architecture: Model architecture type (default: "gnn") + search_strategy: Strategy for search (default: "literature_based") + Options: "literature_based", "benchmark_based", "heuristic_based" + + Returns: + Dict with optimal hyperparameters and reasoning + """ + + # Extract dataset characteristics + num_nodes = dataset_characteristics.get("num_nodes", 10000) + num_tables = dataset_characteristics.get("num_tables", 5) + is_temporal = dataset_characteristics.get("is_temporal", True) + + # Knowledge base from literature (simplified - in real implementation, + # this would query external APIs, papers database, or use MCP) + # Based on common GNN hyperparameters from papers like: + # - RelBench paper + # - GraphSAGE paper + # - Temporal GNN papers + + # Heuristic rules based on dataset size and task type + if num_nodes < 5000: + hidden_channels = 64 + batch_size = 256 + num_layers = 2 + elif num_nodes < 50000: + hidden_channels = 128 + batch_size = 512 + num_layers = 2 + else: + hidden_channels = 256 + batch_size = 1024 + num_layers = 3 + + # Task-specific hyperparameters + if task_type == "regression": + learning_rate = 0.005 + epochs = 20 + tune_metric = "mae" + higher_is_better = False + elif task_type == "binary_classification": + learning_rate = 0.01 + epochs = 15 + tune_metric = "accuracy" + higher_is_better = True + else: # multiclass_classification + learning_rate = 0.01 + epochs = 15 + tune_metric = "accuracy" + higher_is_better = True + + # Temporal adjustment + if is_temporal: + # Temporal GNNs benefit from slightly lower learning rates + learning_rate *= 0.8 + + # Build reasoning explanation + reasoning = [] + reasoning.append(f"Based on dataset size ({num_nodes} nodes, {num_tables} tables):") + reasoning.append(f" - Hidden channels: {hidden_channels} (balanced capacity for dataset scale)") + reasoning.append(f" - Batch size: {batch_size} (optimal memory/performance tradeoff)") + reasoning.append(f" - GNN layers: {num_layers} (appropriate receptive field)") + reasoning.append(f"\nBased on task type ({task_type}):") + reasoning.append(f" - Learning rate: {learning_rate} (stable convergence)") + reasoning.append(f" - Epochs: {epochs} (sufficient for convergence)") + reasoning.append(f" - Metric: {tune_metric} (standard for {task_type})") + if is_temporal: + reasoning.append(f"\nTemporal adjustment applied: reduced learning rate by 20%") + + # Literature references (would be real papers in production) + literature_support = [ + "GraphSAGE: Hamilton et al., 2017 - Recommends 2-3 layers for most graphs", + "RelBench: Fey et al., 2024 - Standard temporal GNN hyperparameters", + "Temporal Graph Networks: Rossi et al., 2020 - Lower LR for temporal tasks" + ] + + return { + "hyperparameters": { + "hidden_channels": hidden_channels, + "batch_size": batch_size, + "learning_rate": learning_rate, + "num_gnn_layers": num_layers, + "epochs": epochs, + "tune_metric": tune_metric, + "higher_is_better": higher_is_better, + }, + "reasoning": "\n".join(reasoning), + "literature_support": literature_support, + "search_strategy": search_strategy, + "confidence": "high" # Based on established heuristics + } + + +@langchain_tool +def search_literature_for_hyperparameters( + task_description: str, + model_type: str = "gnn", + num_results: int = 5 +) -> Dict[str, Any]: + """ + Search academic literature for hyperparameter recommendations. + + This integrates with external APIs: + - Semantic Scholar API for recent papers + - arXiv API for preprints + - Papers With Code API for benchmarks + + Args: + task_description: Description of the ML task + model_type: Type of model (gnn, transformer, etc.) + num_results: Number of papers to retrieve + + Returns: + Dict with paper recommendations and extracted hyperparameters + """ + + # Initialize API clients + config = ExternalAPIConfig.from_env() + semantic_scholar = SemanticScholarClient(config.semantic_scholar_api_key) + arxiv = ArxivClient() + pwc = PapersWithCodeClient() + + papers = [] + hyperparameters_found = [] + + # Build search query + search_query = f"{model_type} {task_description} hyperparameters" + + try: + # Search Semantic Scholar (most reliable for citations) + logger.info(f"Searching Semantic Scholar for: {search_query}") + s2_papers = semantic_scholar.search_papers( + query=search_query, + limit=num_results, + year_min=2020 # Focus on recent papers + ) + + for paper in s2_papers[:num_results]: + paper_info = { + "title": paper.get("title", ""), + "year": paper.get("year"), + "venue": paper.get("venue"), + "authors": [a.get("name", "") for a in paper.get("authors", [])[:3]], + "citations": paper.get("citationCount", 0), + "abstract": paper.get("abstract", "")[:500] # Truncate for display + } + papers.append(paper_info) + + # Extract hyperparameters from abstract (simple keyword extraction) + abstract = paper.get("abstract", "").lower() + extracted = extract_hyperparameters_from_text(abstract) + if extracted: + hyperparameters_found.append(extracted) + + # Also search arXiv for very recent papers + logger.info(f"Searching arXiv for: {search_query}") + arxiv_papers = arxiv.search_papers( + query=f"all:{search_query}", + max_results=3 + ) + + for paper in arxiv_papers: + paper_info = { + "title": paper.get("title", ""), + "year": paper.get("published", "")[:4] if paper.get("published") else None, + "venue": "arXiv", + "authors": paper.get("authors", [])[:3], + "abstract": paper.get("summary", "")[:500] + } + papers.append(paper_info) + + # Extract hyperparameters + summary = paper.get("summary", "").lower() + extracted = extract_hyperparameters_from_text(summary) + if extracted: + hyperparameters_found.append(extracted) + + # Search Papers With Code for benchmark results + logger.info(f"Searching Papers With Code for: {model_type}") + pwc_papers = pwc.search_papers(query=model_type, items_per_page=3) + + for paper in pwc_papers: + paper_info = { + "title": paper.get("title", ""), + "year": paper.get("published", {}).get("year"), + "venue": paper.get("conference", "Papers With Code"), + "url": paper.get("url", "") + } + papers.append(paper_info) + + except Exception as e: + logger.error(f"Error searching literature: {e}") + # Return partial results if available + if not papers: + return { + "error": str(e), + "note": "Failed to retrieve papers from external APIs. Check API keys and connectivity." + } + + # Aggregate hyperparameters from all sources + recommended = aggregate_hyperparameters(hyperparameters_found, model_type) + + return { + "papers": papers[:num_results], + "recommended_hyperparameters": recommended, + "num_sources": len(hyperparameters_found), + "consensus_level": "high" if len(hyperparameters_found) >= 3 else "medium" + } + + +def extract_hyperparameters_from_text(text: str) -> Dict[str, Any]: + """ + Extract hyperparameter values from paper text using keyword matching. + This is a simple extraction - could be enhanced with NLP/LLM. + """ + hyperparams = {} + + # Common patterns for hyperparameters + import re + + # Learning rate patterns + lr_patterns = [ + r'learning rate[:\s]+([0-9.e-]+)', + r'lr[:\s=]+([0-9.e-]+)', + r'α[:\s=]+([0-9.e-]+)' + ] + for pattern in lr_patterns: + match = re.search(pattern, text) + if match: + hyperparams['learning_rate'] = float(match.group(1)) + break + + # Batch size patterns + batch_patterns = [ + r'batch size[:\s]+([0-9]+)', + r'batch[:\s=]+([0-9]+)', + ] + for pattern in batch_patterns: + match = re.search(pattern, text) + if match: + hyperparams['batch_size'] = int(match.group(1)) + break + + # Hidden dimensions/channels + hidden_patterns = [ + r'hidden[_ ](?:dimension|channel|unit)s?[:\s]+([0-9]+)', + r'embedding[_ ](?:dimension|size)[:\s]+([0-9]+)', + ] + for pattern in hidden_patterns: + match = re.search(pattern, text) + if match: + hyperparams['hidden_channels'] = int(match.group(1)) + break + + # Number of layers + layer_patterns = [ + r'([0-9]+)[- ]layer', + r'num[_ ]layers?[:\s]+([0-9]+)', + ] + for pattern in layer_patterns: + match = re.search(pattern, text) + if match: + hyperparams['num_layers'] = int(match.group(1)) + break + + # Epochs + epoch_patterns = [ + r'([0-9]+) epochs?', + r'epochs?[:\s]+([0-9]+)', + ] + for pattern in epoch_patterns: + match = re.search(pattern, text) + if match: + hyperparams['epochs'] = int(match.group(1)) + break + + return hyperparams + + +def aggregate_hyperparameters( + hyperparams_list: List[Dict[str, Any]], + model_type: str = "gnn" +) -> Dict[str, Any]: + """Aggregate hyperparameters from multiple sources.""" + if not hyperparams_list: + # Return sensible defaults for the model type + return get_default_hyperparameters(model_type) + + aggregated = {} + + # For each parameter, take the median value + all_params = set() + for hp in hyperparams_list: + all_params.update(hp.keys()) + + for param in all_params: + values = [hp[param] for hp in hyperparams_list if param in hp] + if values: + if isinstance(values[0], (int, float)): + # Take median for numeric values + sorted_vals = sorted(values) + aggregated[param] = sorted_vals[len(sorted_vals) // 2] + else: + # Take most common for categorical + aggregated[param] = max(set(values), key=values.count) + + # Fill in missing parameters with defaults + defaults = get_default_hyperparameters(model_type) + for param, value in defaults.items(): + if param not in aggregated: + aggregated[param] = value + + return aggregated + + +def get_default_hyperparameters(model_type: str) -> Dict[str, Any]: + """Get default hyperparameters for a model type.""" + defaults = { + "gnn": { + "hidden_channels": 128, + "num_gnn_layers": 2, + "learning_rate": 0.005, + "batch_size": 512, + "epochs": 20 + }, + "transformer": { + "hidden_size": 256, + "num_layers": 4, + "num_heads": 8, + "learning_rate": 0.0001, + "batch_size": 32, + "epochs": 50 + } + } + return defaults.get(model_type, defaults["gnn"]) + + +@langchain_tool +def get_benchmark_hyperparameters( + dataset_name: Optional[str] = None, + task_type: Optional[str] = None, + model_architecture: str = "gnn" +) -> Dict[str, Any]: + """ + Retrieve hyperparameters from benchmark datasets and leaderboards. + + This integrates with: + - Papers With Code leaderboards + - OpenML benchmarks + + Args: + dataset_name: Name of similar dataset (optional) + task_type: Type of task (optional) + model_architecture: Model architecture + + Returns: + Dict with benchmark hyperparameters and performance + """ + + config = ExternalAPIConfig.from_env() + pwc = PapersWithCodeClient() + openml = OpenMLClient(config.openml_api_key) + + benchmarks_found = [] + hyperparameters = {} + + try: + # Search Papers With Code for relevant benchmarks + if task_type: + search_query = f"{model_architecture} {task_type}" + logger.info(f"Searching Papers With Code benchmarks for: {search_query}") + + benchmarks = pwc.get_benchmarks(task=task_type) + + for benchmark in benchmarks[:5]: + benchmark_name = benchmark.get("name", "") + + # Get SOTA results for this benchmark + sota_results = pwc.get_sota_results(benchmark_name) + + if sota_results: + best_result = sota_results[0] # Top result + benchmarks_found.append({ + "benchmark": benchmark_name, + "model": best_result.get("model_name", ""), + "performance": best_result.get("metrics", {}), + "paper": best_result.get("paper", {}) + }) + + # Search OpenML for similar datasets and their best runs + if dataset_name or task_type: + logger.info(f"Searching OpenML for benchmarks") + datasets = openml.search_datasets( + task_type=task_type, + limit=5 + ) + + for dataset in datasets[:3]: + dataset_id = dataset.get("did") + # Could fetch run results for this dataset + # For now, just record the dataset + benchmarks_found.append({ + "source": "OpenML", + "dataset": dataset.get("name"), + "dataset_id": dataset_id + }) + + # Extract common hyperparameters from benchmarks + if benchmarks_found: + # Use heuristics based on successful benchmarks + # In a full implementation, would parse paper details + hyperparameters = { + "hidden_channels": 128, + "num_gnn_layers": 2, + "learning_rate": 0.005, + "batch_size": 512, + "epochs": 20, + } + + except Exception as e: + logger.error(f"Error fetching benchmarks: {e}") + return { + "error": str(e), + "note": "Failed to retrieve benchmarks. Using fallback defaults." + } + + # If no benchmarks found, use sensible defaults + if not benchmarks_found: + hyperparameters = get_default_hyperparameters(model_architecture) + benchmarks_found = [{ + "note": "No specific benchmarks found, using literature defaults" + }] + + return { + "hyperparameters": hyperparameters, + "benchmarks": benchmarks_found, + "num_benchmarks": len(benchmarks_found), + "source": "Papers With Code + OpenML" + } + + +@langchain_tool +def compare_hyperparameter_configs( + configs: List[Dict[str, Any]], + dataset_characteristics: Dict[str, Any] +) -> Dict[str, Any]: + """ + Compare multiple hyperparameter configurations and select the best. + + Uses meta-learning and ensemble voting from multiple sources + to select the most promising configuration. + + Args: + configs: List of hyperparameter configurations from different sources + dataset_characteristics: Dataset characteristics for context + + Returns: + Best configuration with reasoning + """ + + if not configs: + return {"error": "No configurations provided"} + + # Simple voting mechanism (in production, use more sophisticated meta-learning) + param_votes = {} + + for config in configs: + hp = config.get("hyperparameters", config) + for param, value in hp.items(): + if param not in param_votes: + param_votes[param] = [] + param_votes[param].append(value) + + # Select most common value for each parameter (mode) + best_config = {} + for param, values in param_votes.items(): + if all(isinstance(v, (int, float)) for v in values): + # For numeric values, take the median + best_config[param] = sorted(values)[len(values) // 2] + else: + # For categorical, take most common + best_config[param] = max(set(values), key=values.count) + + return { + "best_configuration": best_config, + "num_sources": len(configs), + "selection_method": "ensemble_voting", + "confidence": "high" if len(configs) >= 3 else "medium" + } diff --git a/plexe/langgraph/tools/task_builder.py b/plexe/langgraph/tools/task_builder.py index 0b80ebc1..dec2fa19 100644 --- a/plexe/langgraph/tools/task_builder.py +++ b/plexe/langgraph/tools/task_builder.py @@ -1,11 +1,6 @@ -""" -Tools for the Task Builder Agent. -""" - from typing import Dict, Any from langchain_core.tools import tool as langchain_tool - @langchain_tool def test_sql_query( csv_dir: str, @@ -23,16 +18,25 @@ def test_sql_query( """ import duckdb import os + import pandas as pd try: conn = duckdb.connect(':memory:') + # Load all CSV files as tables for f in os.listdir(csv_dir): if f.endswith('.csv'): table_name = f.replace('.csv', '') file_path = os.path.join(csv_dir, f) conn.execute(f"CREATE TABLE {table_name} AS SELECT * FROM read_csv_auto('{file_path}')") + # Create a dummy timestamp_df for testing (will be provided by the task at runtime) + # This is just for SQL validation + timestamps_dummy = pd.DataFrame({ + 'timestamp': pd.date_range('2020-01-01', periods=3, freq='D') + }) + conn.register("timestamp_df", timestamps_dummy) + result = conn.execute(query).fetchdf() return { diff --git a/plexe/langgraph/utils/__init__.py b/plexe/langgraph/utils/__init__.py new file mode 100644 index 00000000..62660d06 --- /dev/null +++ b/plexe/langgraph/utils/__init__.py @@ -0,0 +1,54 @@ +from plexe.langgraph.utils.emitters import ( + BaseEmitter, + ConsoleEmitter, + WebSocketEmitter, + MultiEmitter, +) +from plexe.langgraph.utils.callbacks import ( + ChainOfThoughtCallback, + create_langchain_callbacks, +) +from plexe.langgraph.utils.file_utils import ( + create_working_directory, + validate_file_exists, + validate_directory_exists, + get_csv_files_in_directory, + read_file_content, + write_file_content, +) +from plexe.langgraph.utils.helpers import ( + format_error_message, + sanitize_sql_identifier, + format_table_info, + estimate_task_type, + get_default_metrics, + validate_python_code, +) +from plexe.langgraph.utils.progress import AgentProgress + +__all__ = [ + # Emitters + "BaseEmitter", + "ConsoleEmitter", + "WebSocketEmitter", + "MultiEmitter", + # Callbacks + "ChainOfThoughtCallback", + "create_langchain_callbacks", + # File utils + "create_working_directory", + "validate_file_exists", + "validate_directory_exists", + "get_csv_files_in_directory", + "read_file_content", + "write_file_content", + # Helpers + "format_error_message", + "sanitize_sql_identifier", + "format_table_info", + "estimate_task_type", + "get_default_metrics", + "validate_python_code", + # Progress + "AgentProgress", +] diff --git a/plexe/langgraph/utils/callbacks.py b/plexe/langgraph/utils/callbacks.py new file mode 100644 index 00000000..b409e0db --- /dev/null +++ b/plexe/langgraph/utils/callbacks.py @@ -0,0 +1,73 @@ +from typing import Optional, Dict, Any, List +from plexe.langgraph.utils.emitters import BaseEmitter, ConsoleEmitter +from plexe.langgraph.utils.progress import AgentProgress + +class ChainOfThoughtCallback: + """Callback for capturing chain-of-thought from LangGraph agents.""" + + def __init__(self, emitter: Optional[BaseEmitter] = None): + self.emitter = emitter or ConsoleEmitter() + self.progress = AgentProgress() + self.thoughts: List[Dict[str, str]] = [] + + def on_agent_start(self, agent_name: str, **kwargs): + """Called when an agent starts processing.""" + self.progress.current_agent = agent_name + self.emitter.emit_agent_start(agent_name) + + def on_agent_action(self, agent_name: str, action: str, **kwargs): + """Called when an agent takes an action.""" + self.thoughts.append({"agent": agent_name, "action": action}) + self.emitter.emit_thought(agent_name, action) + + def on_tool_start(self, agent_name: str, tool_name: str, args: Dict[str, Any], **kwargs): + """Called when a tool is invoked.""" + self.emitter.emit_tool_call(agent_name, tool_name, args) + + def on_tool_end(self, agent_name: str, tool_name: str, result: Any, **kwargs): + """Called when a tool completes.""" + pass + + def on_agent_end(self, agent_name: str, result: str, **kwargs): + """Called when an agent completes processing.""" + self.emitter.emit_agent_end(agent_name, result) + + def on_llm_start(self, agent_name: str, prompt: str, **kwargs): + """Called when LLM inference starts.""" + self.emitter.emit_thought(agent_name, "Processing...") + + def on_llm_end(self, agent_name: str, response: str, **kwargs): + """Called when LLM inference completes.""" + pass + + +def create_langchain_callbacks(emitter: BaseEmitter, agent_name: str): + """Create LangChain-compatible callbacks from an emitter.""" + from langchain_core.callbacks import BaseCallbackHandler + + class LangChainEmitterCallback(BaseCallbackHandler): + def __init__(self, emitter: BaseEmitter, agent_name: str): + self.emitter = emitter + self.agent_name = agent_name + + def on_llm_start(self, serialized, prompts, **kwargs): + self.emitter.emit_thought(self.agent_name, "Analyzing request...") + + def on_llm_end(self, response, **kwargs): + pass + + def on_tool_start(self, serialized, input_str, **kwargs): + tool_name = serialized.get("name", "unknown") if isinstance(serialized, dict) else "tool" + self.emitter.emit_tool_call(self.agent_name, tool_name, {}) + + def on_tool_end(self, output, **kwargs): + pass + + def on_chain_start(self, serialized, inputs, **kwargs): + pass + + def on_chain_end(self, outputs, **kwargs): + pass + + return [LangChainEmitterCallback(emitter, agent_name)] + diff --git a/plexe/langgraph/utils/emitters.py b/plexe/langgraph/utils/emitters.py new file mode 100644 index 00000000..5c73f29a --- /dev/null +++ b/plexe/langgraph/utils/emitters.py @@ -0,0 +1,234 @@ +import asyncio +import logging +from abc import ABC, abstractmethod +from typing import Dict, Any, Optional, List +from datetime import datetime + +logger = logging.getLogger(__name__) + + +class BaseEmitter(ABC): + """Base class for emitting agent thoughts and progress.""" + + @abstractmethod + def emit_thought(self, agent_name: str, thought: str): + """Emit a thinking/progress message.""" + pass + + @abstractmethod + def emit_agent_start(self, agent_name: str): + """Emit agent start notification.""" + pass + + @abstractmethod + def emit_agent_end(self, agent_name: str, result: str): + """Emit agent completion notification.""" + pass + + @abstractmethod + def emit_tool_call(self, agent_name: str, tool_name: str, args: Dict[str, Any]): + """Emit tool call notification.""" + pass + + @abstractmethod + def emit_tool_result(self, agent_name: str, tool_name: str, result: str): + """Emit tool result notification.""" + pass + + +class ConsoleEmitter(BaseEmitter): + """Console-based emitter for development/debugging with rich formatting.""" + + def __init__(self): + self.step_count = 0 + + def emit_thought(self, agent_name: str, thought: str): + self.step_count += 1 + timestamp = datetime.now().strftime("%H:%M:%S") + print(f"[{agent_name}] Step {self.step_count} @ {timestamp}") + print(f" {thought[:500]}") + + def emit_agent_start(self, agent_name: str): + self.step_count += 1 + timestamp = datetime.now().strftime("%H:%M:%S") + print(f"\n=== {agent_name} Starting === (Step {self.step_count} @ {timestamp})") + + def emit_agent_end(self, agent_name: str, result: str): + self.step_count += 1 + timestamp = datetime.now().strftime("%H:%M:%S") + print(f"=== {agent_name} Completed === (Step {self.step_count} @ {timestamp})") + if result: + print(f" Result: {result[:300]}") + + def emit_tool_call(self, agent_name: str, tool_name: str, args: Dict[str, Any]): + self.step_count += 1 + timestamp = datetime.now().strftime("%H:%M:%S") + args_str = "" + if args: + try: + import json + args_str = f" with args: {json.dumps(args)[:100]}" + except: + pass + print(f"[{agent_name}] Step {self.step_count} @ {timestamp}") + print(f" Calling tool: {tool_name}{args_str}") + + def emit_tool_result(self, agent_name: str, tool_name: str, result: str): + self.step_count += 1 + timestamp = datetime.now().strftime("%H:%M:%S") + print(f"[{agent_name}] Step {self.step_count} @ {timestamp}") + # Format with newlines for better readability + formatted_result = result.replace('\\n', '\n') if result else "" + print(f" Tool result:\n{formatted_result}") + + +class WebSocketEmitter(BaseEmitter): + """WebSocket-based emitter for UI integration.""" + + def __init__(self, websocket, loop: Optional[asyncio.AbstractEventLoop] = None): + self.websocket = websocket + self.loop = loop + self.is_closed = False + self.step_count = 0 + + def close(self): + """Mark the emitter as closed.""" + self.is_closed = True + + def _send_message(self, message: Dict[str, Any]): + """Send a message to the WebSocket.""" + if self.is_closed: + return + + try: + if self.loop and self.loop.is_running(): + asyncio.run_coroutine_threadsafe( + self.websocket.send_json(message), + self.loop + ) + else: + asyncio.get_event_loop().run_until_complete( + self.websocket.send_json(message) + ) + except Exception as e: + logger.warning(f"Failed to send WebSocket message: {e}") + + def emit_thought(self, agent_name: str, thought: str): + self.step_count += 1 + timestamp = datetime.now().strftime("%H:%M:%S") + self._send_message({ + "type": "thinking", + "role": "thinking", + "event_type": "thinking", + "agent_name": agent_name, + "message": thought, + "step_number": self.step_count, + "timestamp": timestamp, + }) + + def emit_agent_start(self, agent_name: str): + self.step_count += 1 + timestamp = datetime.now().strftime("%H:%M:%S") + self._send_message({ + "type": "thinking", + "role": "thinking", + "event_type": "agent_start", + "agent_name": agent_name, + "message": f"Starting {agent_name}", + "step_number": self.step_count, + "timestamp": timestamp, + }) + + def emit_agent_end(self, agent_name: str, result: str): + self.step_count += 1 + timestamp = datetime.now().strftime("%H:%M:%S") + self._send_message({ + "type": "thinking", + "role": "thinking", + "event_type": "agent_end", + "agent_name": agent_name, + "message": f"Completed: {result[:300]}" if result else "Completed", + "step_number": self.step_count, + "timestamp": timestamp, + }) + + def emit_tool_call(self, agent_name: str, tool_name: str, args: Dict[str, Any]): + self.step_count += 1 + timestamp = datetime.now().strftime("%H:%M:%S") + args_str = "" + if args: + try: + import json + args_str = f" with {json.dumps(args)[:100]}" + except: + pass + self._send_message({ + "type": "thinking", + "role": "thinking", + "event_type": "tool_call", + "agent_name": agent_name, + "tool_name": tool_name, + "tool_args": args, + "message": f"Calling tool: {tool_name}{args_str}", + "step_number": self.step_count, + "timestamp": timestamp, + }) + + def emit_tool_result(self, agent_name: str, tool_name: str, result: str): + self.step_count += 1 + timestamp = datetime.now().strftime("%H:%M:%S") + # Format with newlines for better readability + formatted_result = result.replace('\\n', '\n') if result else "Tool completed" + self._send_message({ + "type": "thinking", + "role": "thinking", + "event_type": "tool_result", + "agent_name": agent_name, + "tool_name": tool_name, + "message": f"Tool result:\n{formatted_result}", + "result": result, + "step_number": self.step_count, + "timestamp": timestamp, + }) + + +class MultiEmitter(BaseEmitter): + """Combines multiple emitters.""" + + def __init__(self, emitters: List[BaseEmitter]): + self.emitters = emitters + + def emit_thought(self, agent_name: str, thought: str): + for emitter in self.emitters: + try: + emitter.emit_thought(agent_name, thought) + except Exception as e: + logger.warning(f"Emitter error: {e}") + + def emit_agent_start(self, agent_name: str): + for emitter in self.emitters: + try: + emitter.emit_agent_start(agent_name) + except Exception as e: + logger.warning(f"Emitter error: {e}") + + def emit_agent_end(self, agent_name: str, result: str): + for emitter in self.emitters: + try: + emitter.emit_agent_end(agent_name, result) + except Exception as e: + logger.warning(f"Emitter error: {e}") + + def emit_tool_call(self, agent_name: str, tool_name: str, args: Dict[str, Any]): + for emitter in self.emitters: + try: + emitter.emit_tool_call(agent_name, tool_name, args) + except Exception as e: + logger.warning(f"Emitter error: {e}") + + def emit_tool_result(self, agent_name: str, tool_name: str, result: str): + for emitter in self.emitters: + try: + emitter.emit_tool_result(agent_name, tool_name, result) + except Exception as e: + logger.warning(f"Emitter error: {e}") diff --git a/plexe/langgraph/utils/file_utils.py b/plexe/langgraph/utils/file_utils.py new file mode 100644 index 00000000..6f5522de --- /dev/null +++ b/plexe/langgraph/utils/file_utils.py @@ -0,0 +1,66 @@ +import os +import logging +from typing import Optional +from datetime import datetime + +logger = logging.getLogger(__name__) + +def create_working_directory(base_dir: str = "workdir") -> str: + """ + Create a unique working directory for a session. + + Args: + base_dir: Base directory for workspaces + + Returns: + Path to the created working directory + """ + timestamp = datetime.now().strftime("%Y%m%d-%H%M%S") + session_dir = os.path.join(base_dir, f"session-{timestamp}") + os.makedirs(session_dir, exist_ok=True) + + subdirs = ["csv_files", "cache", "artifacts"] + for subdir in subdirs: + os.makedirs(os.path.join(session_dir, subdir), exist_ok=True) + + return session_dir + + +def validate_file_exists(file_path: str) -> bool: + """Check if a file exists.""" + return os.path.isfile(file_path) + + +def validate_directory_exists(dir_path: str) -> bool: + """Check if a directory exists.""" + return os.path.isdir(dir_path) + + +def get_csv_files_in_directory(dir_path: str) -> list: + """Get list of CSV files in a directory.""" + if not os.path.isdir(dir_path): + return [] + return [f for f in os.listdir(dir_path) if f.endswith('.csv')] + + +def read_file_content(file_path: str) -> Optional[str]: + """Read content from a file.""" + try: + with open(file_path, 'r') as f: + return f.read() + except Exception as e: + logger.error(f"Error reading file {file_path}: {e}") + return None + + +def write_file_content(file_path: str, content: str) -> bool: + """Write content to a file.""" + try: + os.makedirs(os.path.dirname(file_path), exist_ok=True) + with open(file_path, 'w') as f: + f.write(content) + return True + except Exception as e: + logger.error(f"Error writing file {file_path}: {e}") + return False + diff --git a/plexe/langgraph/utils.py b/plexe/langgraph/utils/helpers.py similarity index 56% rename from plexe/langgraph/utils.py rename to plexe/langgraph/utils/helpers.py index e478535d..2cffd095 100644 --- a/plexe/langgraph/utils.py +++ b/plexe/langgraph/utils/helpers.py @@ -1,74 +1,4 @@ -""" -Utility functions for LangGraph agents. -""" - -import os -import logging -from typing import Dict, Any, Optional -from datetime import datetime - -logger = logging.getLogger(__name__) - - -def create_working_directory(base_dir: str = "workdir") -> str: - """ - Create a unique working directory for a session. - - Args: - base_dir: Base directory for workspaces - - Returns: - Path to the created working directory - """ - timestamp = datetime.now().strftime("%Y%m%d-%H%M%S") - session_dir = os.path.join(base_dir, f"session-{timestamp}") - os.makedirs(session_dir, exist_ok=True) - - subdirs = ["csv_files", "cache", "artifacts"] - for subdir in subdirs: - os.makedirs(os.path.join(session_dir, subdir), exist_ok=True) - - return session_dir - - -def validate_file_exists(file_path: str) -> bool: - """Check if a file exists.""" - return os.path.isfile(file_path) - - -def validate_directory_exists(dir_path: str) -> bool: - """Check if a directory exists.""" - return os.path.isdir(dir_path) - - -def get_csv_files_in_directory(dir_path: str) -> list: - """Get list of CSV files in a directory.""" - if not os.path.isdir(dir_path): - return [] - return [f for f in os.listdir(dir_path) if f.endswith('.csv')] - - -def read_file_content(file_path: str) -> Optional[str]: - """Read content from a file.""" - try: - with open(file_path, 'r') as f: - return f.read() - except Exception as e: - logger.error(f"Error reading file {file_path}: {e}") - return None - - -def write_file_content(file_path: str, content: str) -> bool: - """Write content to a file.""" - try: - os.makedirs(os.path.dirname(file_path), exist_ok=True) - with open(file_path, 'w') as f: - f.write(content) - return True - except Exception as e: - logger.error(f"Error writing file {file_path}: {e}") - return False - +from typing import Dict, Any def format_error_message(error: Exception, context: str = "") -> str: """Format an error message with context.""" diff --git a/plexe/langgraph/utils/progress.py b/plexe/langgraph/utils/progress.py new file mode 100644 index 00000000..f5031406 --- /dev/null +++ b/plexe/langgraph/utils/progress.py @@ -0,0 +1,20 @@ +from dataclasses import dataclass +from typing import Dict, Any + +@dataclass +class AgentProgress: + """Track agent progress and phase information.""" + current_agent: str = "" + current_phase: str = "" + total_steps: int = 0 + completed_steps: int = 0 + + def to_dict(self) -> Dict[str, Any]: + return { + "current_agent": self.current_agent, + "current_phase": self.current_phase, + "total_steps": self.total_steps, + "completed_steps": self.completed_steps, + "progress_pct": int(self.completed_steps / max(self.total_steps, 1) * 100) + } + diff --git a/plexe/server.py b/plexe/server.py index eb7a762c..cb34eb10 100644 --- a/plexe/server.py +++ b/plexe/server.py @@ -9,6 +9,7 @@ import json import logging import uuid +from datetime import datetime from pathlib import Path from typing import Dict, Any, Optional @@ -18,6 +19,7 @@ from fastapi.middleware.cors import CORSMiddleware from plexe.langgraph import PlexeOrchestrator, AgentConfig +from plexe.langgraph.utils import WebSocketEmitter, MultiEmitter, ConsoleEmitter from plexe.api import datasets_router logger = logging.getLogger(__name__) @@ -48,10 +50,10 @@ class SessionManager: def __init__(self): self.sessions: Dict[str, Dict[str, Any]] = {} - def create_session(self, session_id: str) -> PlexeOrchestrator: + def create_session(self, session_id: str, emitter=None) -> PlexeOrchestrator: """Create a new session with its own orchestrator.""" config = AgentConfig.from_env() - orchestrator = PlexeOrchestrator(config=config, verbose=True) + orchestrator = PlexeOrchestrator(config=config, verbose=True, emitter=emitter) self.sessions[session_id] = { "orchestrator": orchestrator, "working_dir": f"workdir/session-{session_id}", @@ -94,61 +96,96 @@ async def websocket_endpoint(websocket: WebSocket): logger.info(f"New WebSocket connection: {session_id}") loop = asyncio.get_running_loop() - orchestrator = session_manager.create_session(session_id) - session_data = session_manager.get_session(session_id) - working_dir = session_data["working_dir"] + + ws_emitter = WebSocketEmitter(websocket, loop=loop) + console_emitter = ConsoleEmitter() + multi_emitter = MultiEmitter([ws_emitter, console_emitter]) + + config = AgentConfig.from_env() + + def progress_callback(data: Dict[str, Any]): + """Callback to send progress updates.""" + phase = data.get("phase", "") + agent = data.get("agent", "") + timestamp = data.get("timestamp", "") + if phase: + try: + asyncio.run_coroutine_threadsafe( + websocket.send_json({ + "type": "thinking", + "role": "thinking", + "agent_name": agent or "Orchestrator", + "message": f"Starting phase: {phase}", + "step_number": 0, + "timestamp": timestamp or datetime.now().strftime("%H:%M:%S"), + }), + loop + ) + except Exception as e: + logger.warning(f"Failed to send progress: {e}") + + orchestrator = PlexeOrchestrator( + config=config, + verbose=True, + callback=progress_callback, + emitter=multi_emitter + ) + session_manager.sessions[session_id] = { + "orchestrator": orchestrator, + "working_dir": f"workdir/session-{session_id}", + } + working_dir = f"workdir/session-{session_id}" agent_task = None is_closed = False - async def send_message(msg_type: str, content: Any): + async def send_message(msg_type: str, content: Any, agent: str = ""): """Send a message to the client.""" if not is_closed: try: await websocket.send_json({ "type": msg_type, "content": content, + "agent": agent, "id": str(uuid.uuid4()), "session_id": session_id, }) except Exception as e: logger.warning(f"Failed to send message: {e}") - async def send_thought(agent_name: str, thought: str): - """Send a thought/progress update to the client.""" - await send_message("thought", { - "agent": agent_name, - "message": thought, - }) - async def run_agent_task(user_message: str, db_connection: Optional[str] = None): """Run the orchestrator in a separate thread.""" nonlocal agent_task try: - await send_thought("system", "Processing your request...") + await send_message("thinking", "Processing your request...", "Orchestrator") def run_sync(): - session = session_manager.get_session(session_id) - if not session: - return {"status": "error", "error": "Session not found"} - - orch = session["orchestrator"] - state = orch.get_session_state(session_id) - - if state: - return orch.chat( - message=user_message, - session_id=session_id, - working_dir=working_dir, - ) - else: - return orch.run( - user_message=user_message, - db_connection_string=db_connection, - working_dir=working_dir, - session_id=session_id, - ) + thread_loop = asyncio.new_event_loop() + asyncio.set_event_loop(thread_loop) + try: + session = session_manager.get_session(session_id) + if not session: + return {"status": "error", "error": "Session not found"} + + orch = session["orchestrator"] + state = orch.get_session_state(session_id) + + if state: + return orch.chat( + message=user_message, + session_id=session_id, + working_dir=working_dir, + ) + else: + return orch.run( + user_message=user_message, + db_connection_string=db_connection, + working_dir=working_dir, + session_id=session_id, + ) + finally: + thread_loop.close() result = await loop.run_in_executor(None, run_sync) diff --git a/plexe/ui/frontend/src/components/Chat.jsx b/plexe/ui/frontend/src/components/Chat.jsx index 7c964134..a1ac1e1b 100644 --- a/plexe/ui/frontend/src/components/Chat.jsx +++ b/plexe/ui/frontend/src/components/Chat.jsx @@ -1,26 +1,194 @@ import React, { useEffect, useRef, useState } from 'react' -function Message({ msg }) { - const isUser = msg.role === 'user' - const isThinking = msg.role === 'thinking' - - if (isThinking) { - return ( -
    -
    -
    - {msg.agent_name} - Step {msg.step_number} -
    -
    {msg.message}
    +// Icons for different event types +const EventIcon = ({ eventType }) => { + const icons = { + agent_start: '🚀', + thinking: '💭', + tool_call: '🔧', + tool_result: '✅', + agent_end: '🎯' + } + return {icons[eventType] || '•'} +} + +// Specific color mapping per agent for consistent identity visuals +const getAgentTheme = (name = '') => { + const lowerName = name.toLowerCase() + + // Specific colors for known agents + if (lowerName.includes('orchestrator')) { + return { + accent: '#2563eb', + tint: 'rgba(37, 99, 235, 0.08)', + wash: 'rgba(37, 99, 235, 0.04)', + border: 'rgba(37, 99, 235, 0.3)' + } + } + + if (lowerName.includes('conversational')) { + return { + accent: '#10b981', + tint: 'rgba(16, 185, 129, 0.08)', + wash: 'rgba(16, 185, 129, 0.04)', + border: 'rgba(16, 185, 129, 0.3)' + } + } + + // Fallback to deterministic color for other agents + let hash = 0 + for (let i = 0; i < name.length; i += 1) { + hash = name.charCodeAt(i) + ((hash << 5) - hash) + } + const hue = Math.abs(hash) % 360 + return { + accent: `hsl(${hue}, 70%, 50%)`, + tint: `hsla(${hue}, 70%, 50%, 0.08)`, + wash: `hsla(${hue}, 70%, 50%, 0.04)`, + border: `hsla(${hue}, 70%, 50%, 0.3)` + } +} + +// Group consecutive messages from the same agent +const groupMessagesByAgent = (messages) => { + const groups = [] + let currentGroup = null + + messages.forEach((msg) => { + if (msg.role === 'thinking') { + const agentName = msg.agent_name || 'Agent' + + // Start a new group if agent changes or no current group + if (!currentGroup || currentGroup.agent !== agentName) { + if (currentGroup) { + groups.push(currentGroup) + } + currentGroup = { + agent: agentName, + steps: [], + startStep: msg.step_number, + endStep: msg.step_number + } + } + + // Add step to current group + currentGroup.steps.push(msg) + currentGroup.endStep = msg.step_number + } else { + // Non-thinking messages close the current group + if (currentGroup) { + groups.push(currentGroup) + currentGroup = null + } + groups.push({ type: 'message', message: msg }) + } + }) + + // Add the last group if exists + if (currentGroup) { + groups.push(currentGroup) + } + + return groups +} + +// Render a single event within an agent group +const EventItem = ({ step }) => { + const eventType = step.event_type || 'thinking' + const hasError = step.message && step.message.toLowerCase().includes('error') + + const renderMessage = () => { + if (!step.message) return null + + if (hasError) { + const parts = step.message.split(/(Error:?[^\n]*|error:?[^\n]*)/gi) + return ( + <> + {parts.map((part, i) => { + if (part.toLowerCase().includes('error')) { + return {part} + } + return {part} + })} + + ) + } + + return step.message + } + + return ( +
    +
    + + + {eventType === 'agent_start' && 'Starting'} + {eventType === 'thinking' && 'Reasoning'} + {eventType === 'tool_call' && `Tool: ${step.tool_name || 'Unknown'}`} + {eventType === 'tool_result' && 'Result'} + {eventType === 'agent_end' && 'Completed'} + + {step.timestamp && ( + {step.timestamp} + )} +
    +
    + {renderMessage()} +
    +
    + ) +} + +// Render an agent group (multiple steps from same agent) +const AgentGroup = ({ group }) => { + const theme = getAgentTheme(group.agent) + const hasError = group.steps.some(s => s.message && s.message.toLowerCase().includes('error')) + + const stepRange = group.startStep === group.endStep + ? `Step ${group.startStep}` + : `Steps ${group.startStep}-${group.endStep}` + + return ( +
    +
    +
    + + {group.agent} + + + {stepRange} + +
    +
    + {group.steps.map((step, idx) => ( + + ))}
    - ) - } +
    + ) +} + +function Message({ msg }) { + const isUser = msg.role === 'user' + const isError = msg.role === 'error' return ( -
    -
    {msg.content}
    +
    +
    {msg.content}
    ) } @@ -89,16 +257,16 @@ function ConfirmationDialog({ request, onConfirm, onReject }) { className="expand-toggle" onClick={() => setIsExpanded(!isExpanded)} > - {isExpanded ? '▲ Thu gọn' : '▼ Xem thêm'} + {isExpanded ? ' Compact' : ' See more'} )}
    @@ -134,6 +302,9 @@ export default function Chat({ messages, status, isProcessing, onSendMessage, on return status } + // Group messages by agent + const messageGroups = groupMessagesByAgent(messages) + return (
    {confirmationRequest && ( @@ -145,9 +316,13 @@ export default function Chat({ messages, status, isProcessing, onSendMessage, on )}
    {getStatusText()}
    - {messages.map((m, i) => ( - - ))} + {messageGroups.map((group, i) => { + if (group.type === 'message') { + return + } else { + return + } + })} {isProcessing && }
    @@ -165,7 +340,7 @@ export default function Chat({ messages, status, isProcessing, onSendMessage, on /> {isProcessing ? ( ) : (

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