add rounding

src/pydantic_models.py

@@ -5,7 +5,7 @@
 
 from nowcasting_datamodel.models import Forecast, ForecastSQL, ForecastValue, Location, LocationSQL
 from nowcasting_datamodel.models.utils import EnhancedBaseModel
-from pydantic import Field
+from pydantic import Field, validator
 
 logger = logging.getLogger(__name__)
 
@@ -16,6 +16,11 @@ class GSPYield(EnhancedBaseModel):
     datetime_utc: datetime = Field(..., description="The timestamp of the gsp yield")
     solar_generation_kw: float = Field(..., description="The amount of solar generation")
 
+    @validator("solar_generation_kw")
+    def result_check(cls, v):
+        ...
+        return round(v, 2)
+
 
 class LocationWithGSPYields(Location):
     """Location object with GSPYields"""
@@ -171,6 +176,12 @@ class NationalForecastValue(ForecastValue):
         None, description="Dictionary to hold properties of the forecast, like p_levels. "
     )
 
+    @validator("expected_power_generation_megawatts")
+    def result_check(cls, v):
+        ...
+        return round(v, 2)
+
+
 
 class NationalForecast(Forecast):
     """One Forecast of generation at one timestamp"""

src/utils.py

@@ -149,24 +149,27 @@ def format_plevels(national_forecast_value: NationalForecastValue):
     if (not isinstance(national_forecast_value.plevels, dict)) or (
         national_forecast_value.plevels == {}
     ):
+        power = national_forecast_value.expected_power_generation_megawatts
         national_forecast_value.plevels = {
-            "plevel_10": national_forecast_value.expected_power_generation_megawatts * 0.8,
-            "plevel_90": national_forecast_value.expected_power_generation_megawatts * 1.2,
+            "plevel_10": round(power * 0.8, 2),
+            "plevel_90": round(power * 1.2, 2),
         }
 
     # rename '10' and '90' to plevel_10 and plevel_90
     for c in ["10", "90"]:
         if c in national_forecast_value.plevels.keys():
-            national_forecast_value.plevels[f"plevel_{c}"] = national_forecast_value.plevels.pop(c)
+            national_forecast_value.plevels[f"plevel_{c}"] = round(
+                national_forecast_value.plevels.pop(c), 2
+            )
 
     if national_forecast_value.plevels["plevel_10"] is None:
-        national_forecast_value.plevels["plevel_10"] = (
-            national_forecast_value.expected_power_generation_megawatts * 0.8
+        national_forecast_value.plevels["plevel_10"] = round(
+            national_forecast_value.expected_power_generation_megawatts * 0.8, 2
         )
 
     if national_forecast_value.plevels["plevel_90"] is None:
-        national_forecast_value.plevels["plevel_90"] = (
-            national_forecast_value.expected_power_generation_megawatts * 1.2
+        national_forecast_value.plevels["plevel_90"] = round(
+            national_forecast_value.expected_power_generation_megawatts * 1.2, 2
         )