nowcasting_datamodel==1.5.34 (#328)

* nowcasting_datamodel==1.5.34

* pydantic==2.3

* nowcasting_datamodel==1.5.36, and update pydantic models

* fix test

requirements.txt

@@ -4,7 +4,7 @@ uvicorn[standard]
 pydantic
 numpy
 requests
-nowcasting_datamodel==1.5.18
+nowcasting_datamodel==1.5.36
 sqlalchemy
 psycopg2-binary
 geopandas

src/pydantic_models.py

@@ -54,7 +54,7 @@ class GSPYieldGroupByDatetime(EnhancedBaseModel):
     """gsp yields for one a singel datetime"""
 
     datetime_utc: datetime = Field(..., description="The timestamp of the gsp yield")
-    generation_kw_by_gsp_id: Dict[str, str] = Field(
+    generation_kw_by_gsp_id: Dict[int, float] = Field(
         ...,
         description="List of generations by gsp_id. Key is gsp_id, value is generation_kw. "
         "We keep this as a dictionary to keep the size of the file small ",
@@ -65,7 +65,7 @@ class OneDatetimeManyForecastValues(EnhancedBaseModel):
     """One datetime with many forecast values"""
 
     datetime_utc: datetime = Field(..., description="The timestamp of the gsp yield")
-    forecast_values: Dict[str, float] = Field(
+    forecast_values: Dict[int, float] = Field(
         ...,
         description="List of forecasts by gsp_id. Key is gsp_id, value is generation_kw. "
         "We keep this as a dictionary to keep the size of the file small ",

src/tests/test_gsp.py

@@ -246,7 +246,7 @@ def test_read_latest_all_gsp_historic_compact(db_session, api_client):
 
     assert len(r) > 50
     assert len(r[0].forecast_values) == 9  # dont get the national
-    assert r[0].forecast_values["1"] <= 13000
+    assert r[0].forecast_values[1] <= 13000
 
 
 @freeze_time("2022-01-01")