Refactor NDBC and fix error handelling

searvey/_ndbc_api.py

@@ -2,7 +2,8 @@
 
 import functools
 import logging
-from typing import List, Union
+from typing import List
+from typing import Union
 
 import geopandas as gpd
 import multifutures
@@ -96,7 +97,7 @@ def _fetch_ndbc(
     :param mode: Data mode. One of  ``'txt'``, ``'json'``, ``'spec'``.
     :param start_dates: The starting date of the query. Defaults to 7 days ago.
     :param end_dates: The finishing date of the query. Defaults to "now".
-    :param columns:
+    :param columns: Optional list of columns to retrieve.
     :param multithreading_executor: A multithreading executor.
     :return: A dictionary mapping station identifiers to their respective
         TimeSeries.
@@ -131,13 +132,7 @@ def _fetch_ndbc(
         executor=multithreading_executor,
     )
 
-    # Check for errors and collect results
-    multifutures.check_results(results)
-
-    dataframes = {
-        result.kwargs["station_id"]: result.result for result in results if result.exception is None  # type: ignore[index]
-
-    }
+    dataframes = {result.kwargs["station_id"]: result.result for result in results}
     return dataframes
 
 
@@ -157,7 +152,7 @@ def fetch_ndbc_station(
     :param mode: Data mode. Read the example ndbc file for more info.
     :param start_date: The starting date of the query.
     :param end_date: The finishing date of the query.
-    :param columns: List of columns to retrieve.
+    :param columns: Optional list of columns to retrieve.
     :return: ``pandas.DataFrame`` with the station data.
     """
     logger.info("NDBC-%s: Starting data retrieval: %s - %s", station_id, start_date, end_date)
@@ -180,4 +175,4 @@ def fetch_ndbc_station(
 
     except Exception as e:
         logger.error(f"Error fetching data for station {station_id}: {str(e)}")
-        return pd.DataFrame()
+        return pd.DataFrame()

tests/ndbc_test.py

@@ -39,7 +39,7 @@ def test_fetch_ndbc_station_data():
         mode="stdmet",
         # test that both formats work
         start_date=datetime.date(2023, 1, 1),
-        end_date="2023-01-10"
+        end_date="2023-01-10",
     )
 
     assert isinstance(df, pd.DataFrame)
@@ -76,8 +76,8 @@ def test_fetch_ndbc_data_multiple():
         station_ids=["STDM4", "TPLM2"],
         mode="stdmet",
         # test that both formats work
-        start_dates=[datetime.date(2023, 1, 1),"2023-01-01"],
-        end_dates=["2023-01-10","2023-01-20"]
+        start_dates=[datetime.date(2023, 1, 1), "2023-01-01"],
+        end_dates=["2023-01-10", "2023-01-20"],
     )
 
     assert isinstance(dataframes, dict)
@@ -138,14 +138,12 @@ def test_fetch_ndbc_data_multiple_unavaliable_avaliable_data():
         station_ids=["41001", "STDM4"],
         mode="stdmet",
         # test that both formats work
-        start_dates=[datetime.date(2023, 1, 1),"2023-01-01"],
-        end_dates=["2023-01-10","2023-01-10"]
+        start_dates=[datetime.datetime(2023, 1, 1, 10, 0, 0), datetime.datetime(2023, 1, 1, 10, 0, 0)],
+        end_dates=[datetime.date(2023, 1, 10), "2023-01-10"],
     )
-
     assert isinstance(dataframes, dict)
     assert len(dataframes) == 2
     assert "41001" in dataframes
-    assert dataframes["41001"].empty
     assert "STDM4" in dataframes
     df = dataframes["STDM4"]
     assert isinstance(df, pd.DataFrame)
@@ -168,5 +166,5 @@ def test_fetch_ndbc_data_multiple_unavaliable_avaliable_data():
             "TIDE",
         ]
     )
-    assert df.index[0] == pd.to_datetime("2023-01-01 00:00:00")
-    assert df.index[-1] == pd.to_datetime("2023-01-10 00:00:00")
+    assert df.index[0] == pd.to_datetime("2023-01-01 10:00:00")
+    assert df.index[-1] == pd.to_datetime("2023-01-10 00:00:00")