Merge pull request #4 from bluesky-api/dataset

Add dataset parameter

Author: maxhollmann

.github/workflows/main.yml

@@ -81,25 +81,24 @@ jobs:
       - name: Run pytest
         run: poetry run coverage run -m pytest -p no:sugar
 
-      - name: Upload coverage data to coveralls.io
-        run: poetry run coveralls --service=github
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-          COVERALLS_FLAG_NAME: ${{ matrix.test-name }}
-          COVERALLS_PARALLEL: true
-
-  coveralls:
-    name: Indicate completion to coveralls.io
-    needs: tests
-    runs-on: ubuntu-latest
-    container: python:3-slim
-    steps:
-    - name: Finished
-      run: |
-        pip3 install --upgrade coveralls
-        coveralls --service=github --finish
-      env:
-        GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+  # Temporarily disabled because of bug on windows tests
+  #     - name: Coveralls Parallel
+  #       uses: coverallsapp/github-action@v2
+  #       with:
+  #         flag-name: run-${{ join(matrix.*, '-') }}
+  #         parallel: true
+
+  # coveralls:
+  #   name: Indicate completion to coveralls.io
+  #   needs: tests
+  #   runs-on: ubuntu-latest
+  #   container: python:3-slim
+  #   steps:
+  #   - name: Finished
+  #     uses: coverallsapp/github-action@v2
+  #     with:
+  #       parallel-finished: true
+  #       carryforward: "run-1,run-2"
 
   publish:
     name: Build package and publish to PyPI
@@ -120,7 +119,7 @@ jobs:
       - name: Setup poetry
         uses: abatilo/actions-poetry@v2.0.0
         with:
-          poetry-version: "1.3.1"
+          poetry-version: "1.4.2"
 
       - name: Authenticate poetry
         run: poetry config pypi-token.pypi ${{ secrets.PYPI_API_TOKEN }}

src/blueskyapi/client.py

@@ -73,13 +73,15 @@ def latest_forecast(
         lon: float,
         forecast_distances: Iterable[int] = None,
         columns: Iterable[str] = None,
+        dataset: Optional[str] = None,
     ) -> pd.DataFrame:
         """Obtain the latest forecast.
 
         :param lat: Latitude for which to fetch the forecast.
         :param lon: Longitude for which to fetch the forecast.
         :param forecast_distances: Forecast distances to fetch data for (hours from ``forecast_moment``).
         :param columns: Which variables to fetch (see `this page for available variables <https://blueskyapi.io/docs/data>`_).
+        :param dataset: Which dataset to fetch data from (only for users on the Professional plan).
         """
         response = self._get(
             "/forecasts/latest",
@@ -90,6 +92,7 @@ def latest_forecast(
                     forecast_distances, "forecast_distances"
                 ),
                 columns=_prepare_comma_separated_list(columns, "columns"),
+                dataset=dataset,
             ),
         )
         return _create_dataframe(response)
@@ -102,6 +105,7 @@ def forecast_history(
         max_forecast_moment: Optional[Union[datetime, str]] = None,
         forecast_distances: Optional[Iterable[int]] = None,
         columns: Optional[Iterable[str]] = None,
+        dataset: Optional[str] = None,
     ) -> pd.DataFrame:
         """Obtain historical forecasts.
 
@@ -111,6 +115,7 @@ def forecast_history(
         :param max_forecast_moment: The last forecast moment to include.
         :param forecast_distances: Forecast distances to return data for (hours from ``forecast_moment``).
         :param columns: Which variables to fetch (see `this page for available variables <https://blueskyapi.io/docs/data>`_).
+        :param dataset: Which dataset to fetch data from (only for users on the Professional plan).
         """
         response = self._get(
             "/forecasts/history",
@@ -127,6 +132,7 @@ def forecast_history(
                     forecast_distances, "forecast_distances"
                 ),
                 columns=_prepare_comma_separated_list(columns, "columns"),
+                dataset=dataset,
             ),
         )
         return _create_dataframe(response)

test.py

@@ -134,6 +134,19 @@ def test_result(client):
         )
         assert np.all(result.some_column == [5])
 
+    def describe_dataset():
+        @responses.activate
+        def with_valid(client):
+            add_api_response(
+                "/forecasts/latest"
+                "?lat=53.5&lon=13.5&dataset=the-dataset"
+            )
+            client.latest_forecast(
+                53.5,
+                13.5,
+                dataset="the-dataset",
+            )
+
     @pytest.mark.vcr()
     def test_integration(client):
         result = client.latest_forecast(53.5, 13.5)
@@ -211,6 +224,20 @@ def with_none(client):
                 max_forecast_moment=None,
             )
 
+    def describe_dataset():
+        @responses.activate
+        def with_valid(client):
+            add_api_response(
+                "/forecasts/history"
+                "?lat=53.5&lon=13.5&dataset=the-dataset"
+            )
+            client.forecast_history(
+                53.5,
+                13.5,
+                dataset="the-dataset",
+            )
+
+
     @pytest.mark.vcr()
     def test_integration(client):
         min_moment = datetime(2021, 12, 27, 18, 0)