Merge pull request #30 from SHKnudsen/release-package

update release

Author: SHKnudsen

release packages/DynamoPandas.zip

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+FLASK_APP = run.py
+FLASK_ENV = development

release packages/DynamoPandas/extra/Pandamo_AllNodes.dyn

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+@REM Copyright (C) 2012 Anaconda, Inc
+@REM SPDX-License-Identifier: BSD-3-Clause
+@REM Test first character and last character of %1 to see if first character is a "
+@REM   but the last character isn't.
+@REM This was a bug as described in https://github.com/ContinuumIO/menuinst/issues/60
+@REM When Anaconda Prompt has the form
+@REM   %windir%\system32\cmd.exe "/K" "C:\Users\builder\Miniconda3\Scripts\activate.bat" "C:\Users\builder\Miniconda3"
+@REM Rather than the correct
+@REM    %windir%\system32\cmd.exe /K ""C:\Users\builder\Miniconda3\Scripts\activate.bat" "C:\Users\builder\Miniconda3""
+@REM this solution taken from https://stackoverflow.com/a/31359867
+@set "_args1=%1"
+@set _args1_first=%_args1:~0,1%
+@set _args1_last=%_args1:~-1%
+@set _args1_first=%_args1_first:"=+%
+@set _args1_last=%_args1_last:"=+%
+@set _args1=
+
+@if "%_args1_first%"=="+" if NOT "%_args1_last%"=="+" (
+    @CALL "%~dp0..\condabin\conda.bat" activate pandamo
+    @GOTO :End
+)
+
+@REM This may work if there are spaces in anything in %*
+@CALL "%~dp0..\condabin\conda.bat" activate pandamo
+
+:End
+@set _args1_first=
+@set _args1_last=

release packages/DynamoPandas/extra/navie_bayes_sample/NaiveBayesPrediction.dyn

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+import os
+
+class Config(object):
+    FLASK_APP = "run.py"
+    FLASK_ENV = "development"

release packages/DynamoPandas/extra/navie_bayes_sample/Social_Network_Ads.xlsx

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+name: pandamo
+channels:
+  - defaults
+dependencies:
+  - blas=1.0
+  - ca-certificates=2019.10.16
+  - certifi=2019.9.11
+  - click=7.0
+  - flask=1.1.1
+  - icc_rt=2019.0.0
+  - intel-openmp=2019.4
+  - itsdangerous=1.1.0
+  - jinja2=2.10.3
+  - markupsafe=1.1.1
+  - mkl=2019.4
+  - mkl-service=2.3.0
+  - mkl_fft=1.0.14
+  - mkl_random=1.1.0
+  - numpy=1.16.5
+  - numpy-base=1.16.5
+  - openssl=1.1.1d
+  - pandas=0.25.2
+  - pip=19.3.1
+  - python=3.7.4
+  - python-dateutil=2.8.0
+  - pytz=2019.3
+  - scipy=1.3.1
+  - setuptools=41.4.0
+  - six=1.12.0
+  - sqlite=3.30.1
+  - tabulate=0.8.3
+  - vc=14.1
+  - vs2015_runtime=14.16.27012
+  - werkzeug=0.16.0
+  - wheel=0.33.6
+  - wincertstore=0.2
+  - xlrd=1.2.0
+  - pip:
+    - joblib==0.14.0
+    - scikit-learn==0.21.3
+    - sklearn==0.0

release packages/DynamoPandas/extra/pandasDynamo/.flaskenv

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+from flask import Flask
+from config import Config
+from pandamo import api
+import os
+
+# Disable Intel Fortran default console event handler
+# https://github.com/ContinuumIO/anaconda-issues/issues/905
+env = 'FOR_DISABLE_CONSOLE_CTRL_HANDLER'
+if env not in os.environ:
+    os.environ[env] = '1'
+
+app = Flask(__name__)
+
+from pandamo.api.server.has_server_started import mod
+
+from pandamo.api.dataframes.create_dataframe import mod
+from pandamo.api.filters.filter_dataframe import mod
+from pandamo.api.format.format_dataframe import mod
+from pandamo.api.reshape.reshape_dataframe import mod
+from pandamo.api.select.select_rows import mod
+from pandamo.api.select.select_columns import mod
+from pandamo.api.information.basic_information import mod
+from pandamo.api.information.summary import mod
+from pandamo.api.combine.combine_dataframe import mod
+from pandamo.api.statistics.stats import mod
+
+app.register_blueprint(api.server.has_server_started.mod, url_prefix='/api/server')
+
+app.register_blueprint(api.dataframes.create_dataframe.mod, url_prefix='/api/create_dataframe')
+app.register_blueprint(api.filters.filter_dataframe.mod, url_prefix='/api/filter_dataframe')
+app.register_blueprint(api.format.format_dataframe.mod, url_prefix='/api/format_dataframe')
+app.register_blueprint(api.reshape.reshape_dataframe.mod, url_prefix='/api/reshape_dataframe')
+app.register_blueprint(api.select.select_rows.mod, url_prefix='/api/select_rows')
+app.register_blueprint(api.select.select_columns.mod, url_prefix='/api/select_columns')
+app.register_blueprint(api.information.basic_information.mod, url_prefix='/api/basic_information')
+app.register_blueprint(api.information.summary.mod, url_prefix='/api/summary')
+app.register_blueprint(api.combine.combine_dataframe.mod, url_prefix='/api/combine')
+app.register_blueprint(api.statistics.stats.mod, url_prefix='/api/statistics')
+
+from pandamo.api.error_handlers import blueprint
+
+app.register_blueprint(api.error_handlers.blueprint)

release packages/DynamoPandas/extra/pandasDynamo/activatePandamo.bat

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+import json
+from ast import literal_eval
+import pandas as pd
+import re
+import sys
+import os
+from flask import Blueprint
+from flask import jsonify
+from flask import request
+from flask import current_app as app
+import numpy as np
+from utillities.exceptions import ExceptionHelpers
+
+mod = Blueprint('combine_dataframe', __name__)
+null = None
+
+@mod.route('merge/', methods=["POST"])
+def merge():
+    try:
+        request_dict = request.get_json()
+        left_df = request_dict['leftDf']
+        right_df = request_dict['rightDf']
+        how = request_dict['how']
+        left_on = request_dict['left_on'] 
+        right_on = request_dict['right_on']
+        left_index = request_dict['left_index'] 
+        right_index = request_dict['right_index']
+        left_df = pd.read_json(json.dumps(eval(left_df)), orient='split')
+        right_df = pd.read_json(json.dumps(eval(right_df)), orient='split')
+        df = left_df.merge(right_df, how=how, left_on=left_on, right_on=right_on, left_index=left_index, right_index=right_index)
+        df_json = df.to_json(orient='split')
+        response = app.response_class(
+            response=df_json,
+            status=200,
+            mimetype='application/json'
+        )
+    except:
+        exception = ExceptionHelpers.format_exception(sys.exc_info())
+        response = app.response_class(
+            response=exception,
+            status=400,
+            mimetype='application/json'
+        )
+    return response
+
+@mod.route('concatenate/', methods=["POST"])
+def concatenate():
+    try:
+        request_dict = request.get_json()
+        df_json_list = request_dict['df_json_list']
+        axis = request_dict['axis']
+        join = request_dict['join']
+        ignore_index = request_dict['ignore_index']
+        df_list = []
+        for i in df_json_list:
+            df_list.append(pd.read_json(json.dumps(eval(i)), orient='split'))
+        df = pd.concat(df_list, axis=axis, ignore_index=ignore_index)
+        df_json = df.to_json(orient='split')
+        response = app.response_class(
+            response=df_json,
+            status=200,
+            mimetype='application/json'
+        )
+    except:
+        exception = ExceptionHelpers.format_exception(sys.exc_info())
+        response = app.response_class(
+            response=exception,
+            status=400,
+            mimetype='application/json'
+        )
+    return response

release packages/DynamoPandas/extra/pandasDynamo/config.py

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+import json
+import pandas as pd
+import sys
+from flask import Blueprint
+from flask import current_app as app
+from flask import request
+from utillities.exceptions import ExceptionHelpers
+
+mod = Blueprint('create_dataframe', __name__)
+null = None
+# Create Dataframes
+@mod.route('by_dict/', methods=["POST"])
+def by_dict():
+    try:
+        request_dict = request.get_json()
+        jsonstr = request_dict['jsonStr']
+        df = pd.DataFrame(eval(jsonstr))
+        df_json = df.to_json(orient='split')
+        response = app.response_class(
+            response=df_json,
+            status=200,
+            mimetype='application/json'
+        )
+    except:
+        exception = ExceptionHelpers.format_exception(sys.exc_info())
+        response = app.response_class(
+            response=exception,
+            status=400,
+            mimetype='application/json'
+        )
+    return response
+
+# Create Dataframes
+@mod.route('by_excel/', methods=["POST"])
+def by_excel():
+    try:
+        request_dict = request.get_json()
+        file_path = request_dict['filePath']
+        sheet_name = request_dict['sheetName']
+        df = pd.read_excel(file_path, sheet_name=sheet_name, header=0, na_values=['', ' '])
+        df_json = df.to_json(orient='split', date_format='iso')
+        response = app.response_class(
+                response=df_json,
+                status=200,
+                mimetype='application/json'
+        )
+    except:
+        exception = ExceptionHelpers.format_exception(sys.exc_info())
+        response = app.response_class(
+            response=exception,
+            status=400,
+            mimetype='application/json'
+        )
+    return response

release packages/DynamoPandas/extra/pandasDynamo/environment.yml

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+from flask import Blueprint
+from flask import current_app as app
+from flask import jsonify
+from utillities.exception_class import EmptyDataframe
+
+blueprint = Blueprint('error_handlers', __name__)
+
+@blueprint.app_errorhandler(EmptyDataframe)
+def handle_invalid_usage(error):
+    response = jsonify(error.to_dict())
+    response.status_code = error.status_code
+    return response

release packages/DynamoPandas/extra/pandasDynamo/pandamo/__init__.py

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+import json
+from ast import literal_eval
+import pandas as pd
+import re
+import sys
+import os
+from flask import Blueprint
+from flask import jsonify
+from flask import request
+from flask import current_app as app
+import numpy as np
+from utillities.exception_class import EmptyDataframe
+from utillities.exceptions import ExceptionHelpers
+
+mod = Blueprint('filter_dataframe', __name__)
+null = None
+# Create Dataframes
+@mod.route('by_items/', methods=["POST"])
+def by_items():
+    try:
+        request_dict = request.get_json()
+        jsonstr = request_dict['jsonStr']
+        items = request_dict['items']
+        axis = request_dict['axis']
+        items = items
+        axis = int(axis)
+        df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
+        df = df.filter(items=items, axis=axis)
+        if df.empty:
+            raise EmptyDataframe({"content": "Returned empty dataframe, check your filter index and items"}, status_code=400)
+        df_json = df.to_json(orient='split', date_format='iso')
+        response = app.response_class(
+            response=df_json,
+            status=200,
+            mimetype='application/json'
+        )
+    except:
+        exception = ExceptionHelpers.format_exception(sys.exc_info())
+        response = app.response_class(
+            response=exception,
+            status=400,
+            mimetype='application/json'
+        )
+    return response
+
+@mod.route('by_regex/', methods=["POST"])
+def by_regex():
+    try:
+        request_dict = request.get_json()
+        jsonstr = request_dict['jsonStr']
+        items = request_dict['item']
+        axis = request_dict['axis']
+        axis = int(axis)
+        df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
+        df = df.filter(regex=items, axis=axis)
+        if df.empty:
+            raise EmptyDataframe({"content": "Returned empty dataframe, check your filter index and items"}, status_code=400)
+        df_json = df.to_json(orient='split')
+        response = app.response_class(
+            response=df_json,
+            status=200,
+            mimetype='application/json'
+        )
+    except:
+        exception = ExceptionHelpers.format_exception(sys.exc_info())
+        response = app.response_class(
+            response=exception,
+            status=400,
+            mimetype='application/json'
+        )
+    return response
+
+@mod.route('by_contains/', methods=["POST"])
+def by_contains():
+    try:
+        request_dict = request.get_json()
+        jsonstr = request_dict['jsonStr']
+        items = request_dict['item']
+        axis = request_dict['axis']
+        axis = int(axis)
+        df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
+        df = df.filter(like=items, axis=axis)
+        if df.empty:
+            raise EmptyDataframe({"content": "Returned empty dataframe, check your filter index and items"}, status_code=400)
+        df_json = df.to_json(orient='split')
+        response = app.response_class(
+            response=df_json,
+            status=200,
+            mimetype='application/json'
+        )
+    except:
+        exception = ExceptionHelpers.format_exception(sys.exc_info())
+        response = app.response_class(
+            response=exception,
+            status=400,
+            mimetype='application/json'
+        )
+    return response