prediction -> forecast

bluesky-api · Dec 29, 2021 · 5693aaa · 5693aaa
1 parent 4c8d99d
commit 5693aaa
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Showing 4 changed files with 83 additions and 81 deletions.
diff --git a/src/blueskyapi/client.py b/src/blueskyapi/client.py
@@ -12,7 +12,7 @@
 
 def _create_dataframe(response: bytes) -> pd.DataFrame:
     df = pd.read_json(response)
-    df.prediction_moment = pd.to_datetime(df.prediction_moment)
+    df.forecast_moment = pd.to_datetime(df.forecast_moment)
     return df
 
 
@@ -57,16 +57,16 @@ def latest_forecast(
         self,
         lat: float,
         lon: float,
-        prediction_distances: Iterable[int] = None,
+        forecast_distances: Iterable[int] = None,
         columns: Iterable[str] = None,
     ) -> pd.DataFrame:
         response = self._get(
             "/forecasts/gfs_0p25/latest",
             params=dict(
                 lat=lat,
                 lon=lon,
-                prediction_distances=_prepare_comma_separated_list(
-                    prediction_distances, "prediction_distances"
+                forecast_distances=_prepare_comma_separated_list(
+                    forecast_distances, "forecast_distances"
                 ),
                 columns=_prepare_comma_separated_list(columns, "columns"),
             ),
@@ -77,24 +77,24 @@ def forecast_history(
         self,
         lat: float,
         lon: float,
-        min_prediction_moment: Union[datetime, str],
-        max_prediction_moment: Optional[Union[datetime, str]] = None,
-        prediction_distances: Optional[Iterable[int]] = None,
+        min_forecast_moment: Union[datetime, str],
+        max_forecast_moment: Optional[Union[datetime, str]] = None,
+        forecast_distances: Optional[Iterable[int]] = None,
         columns: Optional[Iterable[str]] = None,
     ) -> pd.DataFrame:
         response = self._get(
             "/forecasts/gfs_0p25/history",
             params=dict(
                 lat=lat,
                 lon=lon,
-                min_prediction_moment=_prepare_datetime(
-                    min_prediction_moment, "min_prediction_moment"
+                min_forecast_moment=_prepare_datetime(
+                    min_forecast_moment, "min_forecast_moment"
                 ),
-                max_prediction_moment=_prepare_datetime(
-                    max_prediction_moment, "max_prediction_moment"
+                max_forecast_moment=_prepare_datetime(
+                    max_forecast_moment, "max_forecast_moment"
                 ),
-                prediction_distances=_prepare_comma_separated_list(
-                    prediction_distances, "prediction_distances"
+                forecast_distances=_prepare_comma_separated_list(
+                    forecast_distances, "forecast_distances"
                 ),
                 columns=_prepare_comma_separated_list(columns, "columns"),
             ),

diff --git a/test.py b/test.py
@@ -7,7 +7,7 @@
     53,
     10,
     columns=["wind_u_at_100m"],
-    prediction_distances=[0, 24],
+    forecast_distances=[0, 24],
 )
 print(d)
 
@@ -16,7 +16,7 @@
     53,
     10,
     columns=["wind_u_at_100m"],
-    prediction_distances=[0, 24],
-    min_prediction_moment="2021-06-01 00:00",
+    forecast_distances=[0, 24],
+    min_forecast_moment="2021-06-01 00:00",
 )
 print(d)
diff --git a/tests/blueskyapi/client_test.py b/tests/blueskyapi/client_test.py
@@ -13,7 +13,7 @@ def client():
     return blueskyapi.Client()
 
 
-default_result = [{"prediction_moment": "2021-12-27T18:00:00Z"}]
+default_result = [{"forecast_moment": "2021-12-27T18:00:00Z"}]
 
 
 def add_api_response(path, *, result=default_result, status=200, api_key=None):
@@ -78,25 +78,25 @@ def test_defaults(client):
         add_api_response("/forecasts/gfs_0p25/latest?lat=53.5&lon=13.5")
         client.latest_forecast(53.5, 13.5)
 
-    def describe_prediction_distances():
+    def describe_forecast_distances():
         @responses.activate
         def with_array(client):
             add_api_response(
-                "/forecasts/gfs_0p25/latest?lat=53.5&lon=13.5&prediction_distances=0,24"
+                "/forecasts/gfs_0p25/latest?lat=53.5&lon=13.5&forecast_distances=0,24"
             )
-            client.latest_forecast(53.5, 13.5, prediction_distances=[0, 24])
+            client.latest_forecast(53.5, 13.5, forecast_distances=[0, 24])
 
         @responses.activate
         def with_string(client):
             add_api_response(
-                "/forecasts/gfs_0p25/latest?lat=53.5&lon=13.5&prediction_distances=0,24"
+                "/forecasts/gfs_0p25/latest?lat=53.5&lon=13.5&forecast_distances=0,24"
             )
-            client.latest_forecast(53.5, 13.5, prediction_distances="0,24")
+            client.latest_forecast(53.5, 13.5, forecast_distances="0,24")
 
         @responses.activate
         def with_invalid_value(client):
-            with pytest.raises(TypeError, match="prediction_distances should be"):
-                client.latest_forecast(53.5, 13.5, prediction_distances=1.5)
+            with pytest.raises(TypeError, match="forecast_distances should be"):
+                client.latest_forecast(53.5, 13.5, forecast_distances=1.5)
 
     def describe_columns():
         @responses.activate
@@ -132,11 +132,11 @@ def test_over_rate_limit(client):
     def test_result(client):
         add_api_response(
             "/forecasts/gfs_0p25/latest?lat=53.5&lon=13.5",
-            result=[{"prediction_moment": "2021-12-27T18:00:00Z", "some_column": 5}],
+            result=[{"forecast_moment": "2021-12-27T18:00:00Z", "some_column": 5}],
         )
         result = client.latest_forecast(53.5, 13.5)
         assert np.all(
-            result.prediction_moment == [pd.to_datetime("2021-12-27T18:00:00Z")]
+            result.forecast_moment == [pd.to_datetime("2021-12-27T18:00:00Z")]
         )
         assert np.all(result.some_column == [5])
 
@@ -147,68 +147,69 @@ def test_integration(client):
         assert len(result.columns) == 35
         assert len(result) == 15
 
-        assert str(result.prediction_moment.dtype) == "datetime64[ns, UTC]"
+        assert str(result.forecast_moment.dtype) == "datetime64[ns, UTC]"
         assert np.all(
-            result.prediction_moment == pd.to_datetime("2021-12-27T06:00:00Z")
+            result.forecast_moment == pd.to_datetime("2021-12-29T00:00:00Z")
         )
 
         assert np.all(
             result.forecast_distance
             == [0, 3, 6, 9, 12, 15, 18, 21, 24, 48, 72, 96, 120, 144, 168]
         )
 
+        print(result)
         assert np.all(result.apparent_temperature_at_2m > 250)
         assert np.all(result.apparent_temperature_at_2m < 290)
 
 
 def describe_forecast_history():
-    def describe_min_prediction_moments():
+    def describe_min_forecast_moments():
         @responses.activate
         def with_datetime(client):
             add_api_response(
                 "/forecasts/gfs_0p25/history"
                 "?lat=53.5&lon=13.5"
-                "&min_prediction_moment=2021-12-27T18:00:00"
-                "&max_prediction_moment=2021-12-28T00:00:00"
+                "&min_forecast_moment=2021-12-27T18:00:00"
+                "&max_forecast_moment=2021-12-28T00:00:00"
             )
             client.forecast_history(
                 53.5,
                 13.5,
-                min_prediction_moment=datetime(2021, 12, 27, 18, 0),
-                max_prediction_moment=datetime(2021, 12, 28, 0, 0),
+                min_forecast_moment=datetime(2021, 12, 27, 18, 0),
+                max_forecast_moment=datetime(2021, 12, 28, 0, 0),
             )
 
         @responses.activate
         def with_string(client):
             add_api_response(
                 "/forecasts/gfs_0p25/history"
                 "?lat=53.5&lon=13.5"
-                "&min_prediction_moment=2021-12-27T18:00:00"
-                "&max_prediction_moment=2021-12-28T00:00:00"
+                "&min_forecast_moment=2021-12-27T18:00:00"
+                "&max_forecast_moment=2021-12-28T00:00:00"
             )
             client.forecast_history(
                 53.5,
                 13.5,
-                min_prediction_moment="2021-12-27T18:00:00",
-                max_prediction_moment="2021-12-28T00:00:00",
+                min_forecast_moment="2021-12-27T18:00:00",
+                max_forecast_moment="2021-12-28T00:00:00",
             )
 
         @responses.activate
         def with_invalid_value(client):
-            with pytest.raises(TypeError, match="min_prediction_moment should be"):
-                client.forecast_history(53.5, 13.5, min_prediction_moment=1)
+            with pytest.raises(TypeError, match="min_forecast_moment should be"):
+                client.forecast_history(53.5, 13.5, min_forecast_moment=1)
 
-    def describe_max_prediction_moments():
+    def describe_max_forecast_moments():
         @responses.activate
         def with_none(client):
             add_api_response(
                 "/forecasts/gfs_0p25/history"
                 "?lat=53.5&lon=13.5"
-                "&min_prediction_moment=2021-12-27T18:00:00"
+                "&min_forecast_moment=2021-12-27T18:00:00"
             )
             client.forecast_history(
                 53.5,
                 13.5,
-                min_prediction_moment=datetime(2021, 12, 27, 18, 0),
-                max_prediction_moment=None,
+                min_forecast_moment=datetime(2021, 12, 27, 18, 0),
+                max_forecast_moment=None,
             )
diff --git a/tests/cassettes/describe_latest_forecast/test_integration.yaml b/tests/cassettes/describe_latest_forecast/test_integration.yaml
@@ -15,58 +15,59 @@ interactions:
   response:
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+      - Wed, 29 Dec 2021 10:38:53 GMT
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+      - '{"endpoints":[{"url":"https:\/\/a.nel.cloudflare.com\/report\/v3?s=%2FEc3FfgHgCvCRGVDDY%2BiG4poVUD55wuKiaudPqpk3a5GYnRy5pPfvmyZ0TSwayQJaIOVUm5%2F248y2AEzXghAjtAnc0x97%2BS92nEQlqAqdvR2m%2FUDHQyQo6RMZhU81xKSSqF7TL5RSP8Q63YFDLY5JA%3D%3D"}],"group":"cf-nel","max_age":604800}'
       Server:
       - cloudflare
       Transfer-Encoding: