WIP

tests/conftest.py

@@ -68,11 +68,6 @@ def settings_si_false_wide_shape():
     return Settings(ts_shape="wide", ts_convert_units=False)
 
 
-@pytest.fixture
-def settings_si_true():
-    return Settings(ts_convert_units=True)
-
-
 @pytest.fixture
 def settings_wide_shape():
     return Settings(ts_shape="wide")

tests/core/timeseries/test_interpolation.py

@@ -52,7 +52,7 @@ def test_interpolation_temperature_air_mean_2m_hourly_by_coords(default_settings
                 "station_id": "f674568e",
                 "parameter": "temperature_air_mean_2m",
                 "date": dt.datetime(2022, 1, 2, tzinfo=ZoneInfo("UTC")),
-                "value": 277.71,
+                "value": 4.56,
                 "distance_mean": 13.37,
                 "taken_station_ids": ["02480", "04411", "07341", "00917"],
             }

tests/core/timeseries/test_summary.py

@@ -30,23 +30,23 @@ def test_summary_temperature_air_mean_2m_daily(default_settings):
                 "station_id": "7ac6c582",
                 "parameter": "temperature_air_mean_2m",
                 "date": selected_dates[0],
-                "value": 273.65,
+                "value": 0.5,
                 "distance": 13.42,
                 "taken_station_id": "01048",
             },
             {
                 "station_id": "7ac6c582",
                 "parameter": "temperature_air_mean_2m",
                 "date": selected_dates[1],
-                "value": 267.65,
+                "value": -5.5,
                 "distance": 5.05,
                 "taken_station_id": "01051",
             },
             {
                 "station_id": "7ac6c582",
                 "parameter": "temperature_air_mean_2m",
                 "date": selected_dates[2],
-                "value": 270.45,
+                "value": -2.7,
                 "distance": 0.0,
                 "taken_station_id": "01050",
             },

tests/provider/dwd/observation/test_api_data.py

@@ -374,7 +374,7 @@ def test_dwd_observation_data_result_wide_single_parameter(
 
 
 @pytest.mark.remote
-def test_dwd_observation_data_result_wide_si(
+def test_dwd_observation_data_result_wide_convert_units(
     settings_humanize_false_wide_shape_drop_nulls_complete,
     dwd_climate_summary_wide_columns,
 ):

tests/provider/dwd/road/test_api.py

@@ -31,7 +31,7 @@ def test_dwd_road_weather():
         "station_group": "KK",
     }
     values = request.values.all().df.drop_nulls(subset="value")
-    assert 230 <= values.get_column("value").min() <= 313  # approx. -+40 K
+    assert -40 <= values.get_column("value").min() <= 40  # approx. -+40 K
 
 
 @pytest.mark.xfail(reason="number of station groups may change")

tests/test_api.py

@@ -110,8 +110,8 @@ def test_metadata_units(unit_converter, unit_converter_unit_type_units, metadata
                 assert parameter.unit in unit_converter_unit_type_units[parameter.unit_type]
 
 
-def test_api_dwd_observation(settings_si_true):
-    request = DwdObservationRequest(parameters=[("daily", "kl")], periods="recent", settings=settings_si_true).all()
+def test_api_dwd_observation(default_settings):
+    request = DwdObservationRequest(parameters=[("daily", "kl")], periods="recent", settings=default_settings).all()
     assert not request.df.is_empty()
     assert set(request.df.columns).issuperset(DF_STATIONS_MINIMUM_COLUMNS)
     first_start_date = request.df.get_column("start_date").to_list()[0]
@@ -124,8 +124,8 @@ def test_api_dwd_observation(settings_si_true):
     assert not values.drop_nulls(subset="value").is_empty()
 
 
-def test_api_dwd_mosmix(settings_si_true):
-    request = DwdMosmixRequest(parameters=[("hourly", "large")], settings=settings_si_true).all()
+def test_api_dwd_mosmix(default_settings):
+    request = DwdMosmixRequest(parameters=[("hourly", "large")], settings=default_settings).all()
     assert not request.df.is_empty()
     assert set(request.df.columns).issuperset(DF_STATIONS_MINIMUM_COLUMNS)
     first_start_date = request.df.get_column("start_date").to_list()[0]
@@ -138,8 +138,8 @@ def test_api_dwd_mosmix(settings_si_true):
     assert not values.drop_nulls(subset="value").is_empty()
 
 
-def test_api_dwd_dmo(settings_si_true):
-    request = DwdDmoRequest(parameters=[("hourly", "icon")], settings=settings_si_true).all()
+def test_api_dwd_dmo(default_settings):
+    request = DwdDmoRequest(parameters=[("hourly", "icon")], settings=default_settings).all()
     assert not request.df.is_empty()
     assert set(request.df.columns).issuperset(DF_STATIONS_MINIMUM_COLUMNS)
     first_start_date = request.df.get_column("start_date").to_list()[0]
@@ -153,9 +153,9 @@ def test_api_dwd_dmo(settings_si_true):
 
 
 @pytest.mark.skipif(not ensure_eccodes(), reason="eccodes not installed")
-def test_api_dwd_road(settings_si_true):
+def test_api_dwd_road(default_settings):
     request = DwdRoadRequest(
-        parameters=[("15_minutes", "data", "temperature_air_mean_2m")], settings=settings_si_true
+        parameters=[("15_minutes", "data", "temperature_air_mean_2m")], settings=default_settings
     ).all()
     assert not request.df.is_empty()
     assert set(request.df.columns).issuperset(DF_STATIONS_MINIMUM_COLUMNS)
@@ -170,8 +170,8 @@ def test_api_dwd_road(settings_si_true):
 
 
 @pytest.mark.xfail
-def test_api_eccc_observation(settings_si_true):
-    request = EcccObservationRequest(parameters=[("daily", "data")], settings=settings_si_true).all()
+def test_api_eccc_observation(default_settings):
+    request = EcccObservationRequest(parameters=[("daily", "data")], settings=default_settings).all()
     assert not request.df.is_empty()
     assert set(request.df.columns).issuperset(DF_STATIONS_MINIMUM_COLUMNS)
     first_start_date = request.df.get_column("start_date").to_list()[0]
@@ -186,8 +186,8 @@ def test_api_eccc_observation(settings_si_true):
 
 @pytest.mark.xfail
 @pytest.mark.remote
-def test_api_imgw_hydrology(settings_si_true):
-    request = ImgwHydrologyRequest(parameters=[("daily", "hydrology")], settings=settings_si_true).all()
+def test_api_imgw_hydrology(default_settings):
+    request = ImgwHydrologyRequest(parameters=[("daily", "hydrology")], settings=default_settings).all()
     assert not request.df.is_empty()
     assert set(request.df.columns).issuperset(DF_STATIONS_MINIMUM_COLUMNS)
     first_start_date = request.df.get_column("start_date").to_list()[0]
@@ -202,8 +202,8 @@ def test_api_imgw_hydrology(settings_si_true):
 
 @pytest.mark.xfail
 @pytest.mark.remote
-def test_api_imgw_meteorology(settings_si_true):
-    request = ImgwMeteorologyRequest(parameters=[("daily", "climate")], settings=settings_si_true).filter_by_station_id(
+def test_api_imgw_meteorology(default_settings):
+    request = ImgwMeteorologyRequest(parameters=[("daily", "climate")], settings=default_settings).filter_by_station_id(
         "249200180"
     )
     assert not request.df.is_empty()
@@ -218,9 +218,9 @@ def test_api_imgw_meteorology(settings_si_true):
     assert not values.drop_nulls(subset="value").is_empty()
 
 
-def test_api_noaa_ghcn_hourly(settings_si_true):
+def test_api_noaa_ghcn_hourly(default_settings):
     request = NoaaGhcnRequest(
-        parameters=[("hourly", "data", "precipitation_height")], settings=settings_si_true
+        parameters=[("hourly", "data", "precipitation_height")], settings=default_settings
     ).filter_by_station_id("AQC00914594")
     assert not request.df.is_empty()
     assert set(request.df.columns).issuperset(DF_STATIONS_MINIMUM_COLUMNS)
@@ -234,9 +234,9 @@ def test_api_noaa_ghcn_hourly(settings_si_true):
     assert not values.drop_nulls(subset="value").is_empty()
 
 
-def test_api_noaa_ghcn_daily(settings_si_true):
+def test_api_noaa_ghcn_daily(default_settings):
     request = NoaaGhcnRequest(
-        parameters=[("daily", "data", "precipitation_height")], settings=settings_si_true
+        parameters=[("daily", "data", "precipitation_height")], settings=default_settings
     ).filter_by_station_id("AQC00914594")
     assert not request.df.is_empty()
     assert set(request.df.columns).issuperset(DF_STATIONS_MINIMUM_COLUMNS)
@@ -251,8 +251,8 @@ def test_api_noaa_ghcn_daily(settings_si_true):
 
 
 @pytest.mark.xfail
-def test_api_wsv_pegel(settings_si_true):
-    request = WsvPegelRequest(parameters=[("dynamic", "data", "stage")], settings=settings_si_true).all()
+def test_api_wsv_pegel(default_settings):
+    request = WsvPegelRequest(parameters=[("dynamic", "data", "stage")], settings=default_settings).all()
     assert not request.df.is_empty()
     assert set(request.df.columns).issuperset(DF_STATIONS_MINIMUM_COLUMNS)
     first_date = request.df.get_column("start_date").to_list()[0]
@@ -265,8 +265,8 @@ def test_api_wsv_pegel(settings_si_true):
     assert not values.drop_nulls(subset="value").is_empty()
 
 
-def test_api_ea_hydrology(settings_si_true):
-    request = EAHydrologyRequest(parameters=[("daily", "data", "discharge")], settings=settings_si_true).all()
+def test_api_ea_hydrology(default_settings):
+    request = EAHydrologyRequest(parameters=[("daily", "data", "discharge")], settings=default_settings).all()
     assert not request.df.is_empty()
     assert set(request.df.columns).issuperset(DF_STATIONS_MINIMUM_COLUMNS)
     first_date = request.df.get_column("start_date").to_list()[0]
@@ -279,9 +279,9 @@ def test_api_ea_hydrology(settings_si_true):
     assert not values.drop_nulls(subset="value").is_empty()
 
 
-def test_api_nws_observation(settings_si_true):
+def test_api_nws_observation(default_settings):
     request = NwsObservationRequest(
-        parameters=[("hourly", "data", "temperature_air_mean_2m")], settings=settings_si_true
+        parameters=[("hourly", "data", "temperature_air_mean_2m")], settings=default_settings
     ).filter_by_station_id("KBHM")
     assert not request.df.is_empty()
     assert set(request.df.columns).issuperset(DF_STATIONS_MINIMUM_COLUMNS)
@@ -295,8 +295,8 @@ def test_api_nws_observation(settings_si_true):
     assert not values.drop_nulls(subset="value").is_empty()
 
 
-def test_api_eaufrance_hubeau(settings_si_true):
-    request = HubeauRequest(parameters=[("dynamic", "data", "discharge")], settings=settings_si_true).all()
+def test_api_eaufrance_hubeau(default_settings):
+    request = HubeauRequest(parameters=[("dynamic", "data", "discharge")], settings=default_settings).all()
     assert not request.df.is_empty()
     assert set(request.df.columns).issuperset(DF_STATIONS_MINIMUM_COLUMNS)
     first_date = request.df.get_column("start_date").to_list()[0]
@@ -309,9 +309,9 @@ def test_api_eaufrance_hubeau(settings_si_true):
     assert not values.drop_nulls(subset="value").is_empty()
 
 
-def test_api_geosphere_observation(settings_si_true):
+def test_api_geosphere_observation(default_settings):
     request = GeosphereObservationRequest(
-        parameters=[("daily", "data", "precipitation_height")], settings=settings_si_true
+        parameters=[("daily", "data", "precipitation_height")], settings=default_settings
     ).filter_by_station_id("5882")
 
     assert not request.df.is_empty()

tests/ui/cli/test_cli_interpolate.py

@@ -205,15 +205,15 @@ def test_cli_interpolate_geojson():
                         "station_id": "6754d04d",
                         "parameter": "temperature_air_mean_2m",
                         "date": "1986-10-31T00:00:00+00:00",
-                        "value": 279.52,
+                        "value": 6.37,
                         "distance_mean": 16.99,
                         "taken_station_ids": ["00072", "02074", "02638", "04703"],
                     },
                     {
                         "station_id": "6754d04d",
                         "date": "1986-11-01T00:00:00+00:00",
                         "parameter": "temperature_air_mean_2m",
-                        "value": 281.85,
+                        "value": 8.7,
                         "distance_mean": 0.0,
                         "taken_station_ids": ["00071"],
                     },
@@ -256,7 +256,7 @@ def test_cli_interpolate_interpolation_station_distance():
             "station_id": "6754d04d",
             "parameter": "temperature_air_mean_2m",
             "date": "1986-11-01T00:00:00+00:00",
-            "value": 281.85,
+            "value": 8.7,
             "distance_mean": 0.0,
             "taken_station_ids": ["00071"],
         },
@@ -288,15 +288,15 @@ def test_cli_interpolate_dont_use_nearby_station():
             "station_id": "6754d04d",
             "parameter": "temperature_air_mean_2m",
             "date": "1986-10-31T00:00:00+00:00",
-            "value": 279.52,
+            "value": 6.37,
             "distance_mean": 16.99,
             "taken_station_ids": ["00072", "02074", "02638", "04703"],
         },
         {
             "station_id": "6754d04d",
             "parameter": "temperature_air_mean_2m",
             "date": "1986-11-01T00:00:00+00:00",
-            "value": 281.85,
+            "value": 8.7,
             "distance_mean": 11.33,
             "taken_station_ids": ["00071", "00072", "02074", "02638"],
         },

tests/ui/cli/test_cli_summarize.py

@@ -98,15 +98,15 @@ def test_cli_summarize_geojson():
                         "station_id": "a87291a8",
                         "parameter": "temperature_air_mean_2m",
                         "date": "1986-10-31T00:00:00+00:00",
-                        "value": 279.75,
+                        "value": 6.6,
                         "distance": 6.97,
                         "taken_station_id": "00072",
                     },
                     {
                         "station_id": "a87291a8",
                         "parameter": "temperature_air_mean_2m",
                         "date": "1986-11-01T00:00:00+00:00",
-                        "value": 281.85,
+                        "value": 8.7,
                         "distance": 0.0,
                         "taken_station_id": "00071",
                     },

tests/ui/test_restapi.py

@@ -325,11 +325,11 @@ def test_values_dwd_sql_tabular(client):
     assert len(data) >= 8
     item = data[0]
     assert item == {
-        "cloud_cover_total": 6.9,
+        "cloud_cover_total": 0.8625,
         "qn_cloud_cover_total": 10.0,
         "dataset": "climate_summary",
         "date": "2020-01-25T00:00:00+00:00",
-        "humidity": 89.0,
+        "humidity": 0.89,
         "qn_humidity": 10.0,
         "precipitation_form": 0.0,
         "qn_precipitation_form": 10.0,
@@ -404,15 +404,15 @@ def test_interpolate_dwd(client):
             "station_id": "6754d04d",
             "parameter": "temperature_air_mean_2m",
             "date": "1986-10-31T00:00:00+00:00",
-            "value": 279.52,
+            "value": 6.37,
             "distance_mean": 16.99,
             "taken_station_ids": ["00072", "02074", "02638", "04703"],
         },
         {
             "station_id": "6754d04d",
             "parameter": "temperature_air_mean_2m",
             "date": "1986-11-01T00:00:00+00:00",
-            "value": 281.85,
+            "value": 8.7,
             "distance_mean": 0.0,
             "taken_station_ids": ["00071"],
         },
@@ -446,7 +446,7 @@ def test_interpolate_dwd_lower_interpolation_distance(client):
             "station_id": "6754d04d",
             "parameter": "temperature_air_mean_2m",
             "date": "1986-11-01T00:00:00+00:00",
-            "value": 281.85,
+            "value": 8.7,
             "distance_mean": 0.0,
             "taken_station_ids": ["00071"],
         },
@@ -472,15 +472,15 @@ def test_interpolate_dwd_dont_use_nearby_station(client):
             "station_id": "6754d04d",
             "parameter": "temperature_air_mean_2m",
             "date": "1986-10-31T00:00:00+00:00",
-            "value": 279.52,
+            "value": 6.37,
             "distance_mean": 16.99,
             "taken_station_ids": ["00072", "02074", "02638", "04703"],
         },
         {
             "station_id": "6754d04d",
             "parameter": "temperature_air_mean_2m",
             "date": "1986-11-01T00:00:00+00:00",
-            "value": 281.85,
+            "value": 8.7,
             "distance_mean": 11.33,
             "taken_station_ids": ["00071", "00072", "02074", "02638"],
         },
@@ -542,15 +542,15 @@ def test_summarize_dwd(client):
             "station_id": "a87291a8",
             "parameter": "temperature_air_mean_2m",
             "date": "1986-10-31T00:00:00+00:00",
-            "value": 279.75,
+            "value": 6.6,
             "distance": 6.97,
             "taken_station_id": "00072",
         },
         {
             "station_id": "a87291a8",
             "parameter": "temperature_air_mean_2m",
             "date": "1986-11-01T00:00:00+00:00",
-            "value": 281.85,
+            "value": 8.7,
             "distance": 0.0,
             "taken_station_id": "00071",
         },

wetterdienst/api.py

@@ -72,8 +72,6 @@ def __new__(cls, provider: str, network: str) -> type[TimeseriesRequest]:
         :param network: data network e.g. NOAAs observation
         """
         # Both provider and network should be fine (if not an exception is raised)
-        provider = provider.strip().lower()
-        network = network.strip().lower()
         return cls.resolve(provider, network)
 
     @classmethod