Add logging when registering a dataset (#370)

* Add logging when registering a dataset

* update message formatting

* Apply formatting rules to all messages

* address pr comments

kolena/_experimental/dataset/_dataset.py

@@ -38,10 +38,12 @@
 from kolena._experimental.dataset.common import validate_batch_size
 from kolena._experimental.dataset.common import validate_dataframe_ids
 from kolena._utils import krequests_v2 as krequests
+from kolena._utils import log
 from kolena._utils.batched_load import _BatchedLoader
 from kolena._utils.batched_load import init_upload
 from kolena._utils.batched_load import upload_data_frame
 from kolena._utils.consts import BatchSize
+from kolena._utils.endpoints import get_dataset_url
 from kolena._utils.serde import from_dict
 from kolena._utils.state import API_V2
 from kolena.errors import InputValidationError
@@ -259,6 +261,8 @@ def register_dataset(
     request = RegisterRequest(name=name, id_fields=id_fields, uuid=load_uuid)
     response = krequests.post(Path.REGISTER, json=asdict(request))
     krequests.raise_for_status(response)
+    data = from_dict(EntityData, response.json())
+    log.info(f"Successfully registered dataset '{name}' ({get_dataset_url(dataset_id=data.id)})")
 
 
 def _iter_dataset_raw(
@@ -300,6 +304,7 @@ def fetch_dataset(
     """
     Fetch an entire dataset given its name.
     """
+    log.info(f"Loaded dataset '{name}'")
     df_batches = list(_iter_dataset(name, commit, batch_size))
     return pd.concat(df_batches, ignore_index=True) if df_batches else pd.DataFrame()
 

kolena/_experimental/dataset/_evaluation.py

@@ -115,6 +115,7 @@ def fetch_results(
     """
     Fetch results given dataset name and model name.
     """
+    log.info(f"Fetching results for model '{model}' on dataset '{dataset}'")
     df = _fetch_results(dataset, model)
 
     df_datapoints = _to_deserialized_dataframe(df.drop_duplicates(subset=[COL_DATAPOINT]), column=COL_DATAPOINT)
@@ -128,7 +129,7 @@ def fetch_results(
                 _to_deserialized_dataframe(df_matched, column=COL_RESULT),
             ),
         )
-
+    log.info(f"Fetched results for model '{model}' on dataset '{dataset}'")
     return df_datapoints, df_results_by_eval
 
 
@@ -191,4 +192,4 @@ def test(
                 upload_data_frame(df=df_results, batch_size=BatchSize.UPLOAD_RECORDS.value, load_uuid=load_uuid)
 
     _upload_results(model, load_uuid, existing_dataset.id)
-    log.info(f"uploaded test results for model {model} on dataset {dataset}")
+    log.info(f"Uploaded test results for model '{model}' on dataset '{dataset}'")

kolena/_utils/endpoints.py

@@ -80,6 +80,15 @@ def _get_test_suite_url(client_state: _ClientState, test_suite_id: int) -> str:
     return f"{platform_url}/testing?{urlencode(dict(testSuiteId=test_suite_id))}"
 
 
+def _get_dataset_url(client_state: _ClientState, dataset_id: str) -> str:
+    platform_url = _get_platform_url(client_state)
+    return f"{platform_url}/datasets?{urlencode(dict(datasetId=dataset_id))}"
+
+
+def get_dataset_url(dataset_id: int) -> str:
+    return _get_dataset_url(get_client_state(), dataset_id)
+
+
 def get_model_url(model_id: int) -> str:
     return _get_model_url(get_client_state(), model_id)