Add /List/* endpoints

tests/test_datafarm.py

@@ -173,3 +173,76 @@ def test_parse_datetime_object():
  result = _parse_datetime(dt)
  expected = "2023-05-15T14:30:00Z"
  assert result == expected
+
+
+@requires_DATAFARM_API_KEY()
+def test_units(repo):
+ units = repo.units
+ assert units is not None
+ assert isinstance(units, pd.DataFrame)
+ assert "IDName" in units.columns.tolist()
+ assert "l/min" in units["IDName"].tolist()
+
+
+@requires_DATAFARM_API_KEY()
+def test_time_series_source_descriptions(repo):
+ time_series_source_descriptions = repo.time_series_source_descriptions
+ assert time_series_source_descriptions is not None
+ assert isinstance(time_series_source_descriptions, pd.DataFrame)
+ assert "IDName" in time_series_source_descriptions.columns.tolist()
+ assert "LEG_wl_RWS" in time_series_source_descriptions["IDName"].tolist()
+
+
+@requires_DATAFARM_API_KEY()
+def test_time_series_types(repo):
+ time_series_types = repo.time_series_types
+ assert time_series_types is not None
+ assert isinstance(time_series_types, pd.DataFrame)
+ assert "IDName" in time_series_types.columns.tolist()
+ assert "BSH-dat-meteo" in time_series_types["IDName"].tolist()
+
+
+@requires_DATAFARM_API_KEY()
+def test_time_series_status(repo):
+ time_series_status = repo.time_series_status
+ assert time_series_status is not None
+ assert isinstance(time_series_status, pd.DataFrame)
+ assert "IDName" in time_series_status.columns.tolist()
+ assert "new" in time_series_status["IDName"].tolist()
+
+
+@requires_DATAFARM_API_KEY()
+def test_qualities(repo):
+ qualities = repo.qualities
+ assert qualities is not None
+ assert isinstance(qualities, pd.DataFrame)
+ assert "IDName" in qualities.columns.tolist()
+ assert "ok" in qualities["IDName"].tolist()
+
+
+@requires_DATAFARM_API_KEY()
+def test_parameters(repo):
+ parameters = repo.parameters
+ assert parameters is not None
+ assert isinstance(parameters, pd.DataFrame)
+ assert "IDName" in parameters.columns.tolist()
+ assert "Lat" in parameters["IDName"].tolist()
+ assert "Lon" in parameters["IDName"].tolist()
+
+
+@requires_DATAFARM_API_KEY()
+def test_medias(repo):
+ medias = repo.medias
+ assert medias is not None
+ assert isinstance(medias, pd.DataFrame)
+ assert "IDName" in medias.columns.tolist()
+ assert "waves" in medias["IDName"].tolist()
+
+
+@requires_DATAFARM_API_KEY()
+def test_locations(repo):
+ locations = repo.locations
+ assert locations is not None
+ assert isinstance(locations, pd.DataFrame)
+ assert "IDName" in locations.columns.tolist()
+ assert "Bor1" in locations["IDName"].tolist()

watobs/datafarm.py

@@ -147,14 +147,49 @@ def get_data(
 
  @property
  def time_series_metadata(self):
- r = requests.get(
- self.API_URL + "/MetaData/Entity",
- headers=self.headers,
- params={"aClassId": "Timeseries"},
- )
- r.raise_for_status()
- data = r.json()
- return to_pandas_df(json.dumps(data))
+ endpoint = "/MetaData/Entity"
+ params = {"aClassId": "Timeseries"}
+ return self._get_pandas_df(endpoint, params)
+
+ @property
+ def time_series_source_descriptions(self):
+ endpoint = "/List/TimeSeriesSourceDescriptions"
+ return self._get_pandas_df(endpoint)
+
+ @property
+ def units(self):
+ endpoint = "/List/Units"
+ return self._get_pandas_df(endpoint)
+
+ @property
+ def time_series_types(self):
+ endpoint = "/List/TimeSeriesTypes"
+ return self._get_pandas_df(endpoint)
+
+ @property
+ def time_series_status(self):
+ endpoint = "/List/TimeSeriesStatus"
+ return self._get_pandas_df(endpoint)
+
+ @property
+ def qualities(self):
+ endpoint = "/List/Qualities"
+ return self._get_pandas_df(endpoint)
+
+ @property
+ def parameters(self):
+ endpoint = "/List/Parameters"
+ return self._get_pandas_df(endpoint)
+
+ @property
+ def medias(self):
+ endpoint = "/List/Medias"
+ return self._get_pandas_df(endpoint)
+
+ @property
+ def locations(self):
+ endpoint = "/List/Locations"
+ return self._get_pandas_df(endpoint)
 
  def connect(self):
  """Connect to the Datafarm API."""
@@ -178,36 +213,16 @@ def close(self):
  self.access_token = None
  self.headers = None
 
+ def _get_pandas_df(self, endpoint, params=None):
+ url = self.API_URL + endpoint
+ r = requests.get(url, headers=self.headers, params=params)
+ r.raise_for_status()
+ data = r.json()
+ return to_pandas_df(json.dumps(data))
+
  def __enter__(self):
  self.connect()
  return self
 
  def __exit__(self, exc_type, exc_value, traceback):
  self.close()
-
-
-if __name__ == "__main__":
- import os
-
- import dotenv
-
- dotenv.load_dotenv()
- api_key = os.getenv("DATAFARM_API_KEY")
- assert api_key is not None
-
- with DatafarmRepository(api_key) as dfr:
- assert dfr.access_token is not None
- print(dfr.list_time_series())
- print(dfr.time_series_metadata)
- time_series = "TNWB_wind_RVO-FUGRO_unfiltered_WS-130"
- data = dfr.get_data(
- time_series_id=[
- # "Bor1_currents_RVO-FUGRO_derived_CS",
- "TNWB_wind_RVO-FUGRO_unfiltered_WS-130",
- ],
- iso8601_timestamp=False,
- start="2015-03-24T10:16:45.034Z",
- end="2023-03-24T10:16:45.034Z",
- limit=10,
- )
- print(data)