Add minimum historic prediction hours for prediction providers.

Prediction providers can now individually set the minimum historic prediction hours
to be kept in the data records. This setting supersedes any lower setting given by the
configuration `prediction_historic_hours`.

As a help for the future change of ElecPriceAkkudoktor, the minimum historic hours for
this provider is set to 5 * 7 * 24 hours.

Signed-off-by: Bobby Noelte <[email protected]>

src/akkudoktoreos/prediction/elecpriceakkudoktor.py

@@ -100,6 +100,10 @@ def _validate_data(cls, json_str: Union[bytes, Any]) -> AkkudoktorElecPrice:
             raise ValueError(error_msg)
         return akkudoktor_data
 
+    def historic_hours_min(self) -> int:
+        """Return the minimum historic prediction hours for Akkudoktor electricity price data."""
+        return 5 * 7 * 24 # 5 weeks a 7 days a 24 hours
+
     def _calculate_weighted_mean(self, day_of_week: int, hour: int) -> float:
         """Calculate the weighted mean price for given day_of_week and hour.
 

src/akkudoktoreos/prediction/predictionabc.py

@@ -103,6 +103,13 @@ class PredictionStartEndKeepMixin(PredictionBase):
     system. Predictions cannot be computed if this value is `None`.
     """
 
+    def historic_hours_min(self) -> int:
+        """Return the minimum historic prediction hours for specific data.
+
+        To be implemented by derived classes if default 0 is not appropriate.
+        """
+        return 0
+
     # Computed field for end_datetime and keep_datetime
     @computed_field  # type: ignore[prop-decorator]
     @property
@@ -136,11 +143,14 @@ def keep_datetime(self) -> Optional[DateTime]:
         Returns:
             Optional[DateTime]: The calculated retention cutoff datetime, or `None` if inputs are missing.
         """
-        if self.start_datetime and self.config.prediction_historic_hours:
-            return self.start_datetime - to_duration(
-                f"{int(self.config.prediction_historic_hours)} hours"
-            )
-        return None
+        if self.start_datetime is None:
+            return None
+        historic_hours = self.historic_hours_min()
+        if self.config.prediction_historic_hours and self.config.prediction_historic_hours > historic_hours:
+            historic_hours = int(self.config.prediction_historic_hours)
+        return self.start_datetime - to_duration(
+            f"{historic_hours} hours"
+        )
 
     @computed_field  # type: ignore[prop-decorator]
     @property