Nested config, devices registry

* All config now nested.
    - Use default config from model field default values. If providers
      should be enabled by default, non-empty default config file could
      be provided again.
    - Environment variable support with EOS_ prefix and __ between levels,
      e.g. EOS_SERVER__EOS_SERVER_PORT=8503 where all values are case
      insensitive.
      For more information see:
      https://docs.pydantic.dev/latest/concepts/pydantic_settings/#parsing-environment-variable-values
    - Use devices as registry for configured devices. DeviceBase as base
      class with for now just initializion support (in the future expand
      to operations during optimization).
    - Strip down ConfigEOS to the only configuration instance. Reload
      from file or reset to defaults is possible.

 * Fix multi-initialization of derived SingletonMixin classes.

src/akkudoktoreos/core/coreabc.py

@@ -265,6 +265,12 @@ class SingletonMixin:
         class MySingletonModel(SingletonMixin, PydanticBaseModel):
             name: str
 
+            # implement __init__ to avoid re-initialization of parent class PydanticBaseModel:
+            def __init__(self, *args: Any, **kwargs: Any) -> None:
+                if hasattr(self, "_initialized"):
+                    return
+                super().__init__(*args, **kwargs)
+
         instance1 = MySingletonModel(name="Instance 1")
         instance2 = MySingletonModel(name="Instance 2")
 

src/akkudoktoreos/core/dataabc.py

@@ -1110,7 +1110,7 @@ class DataProvider(SingletonMixin, DataSequence):
 
         To be implemented by derived classes.
         """
-        return self.provider_id() == self.config.abstract_provider
+        raise NotImplementedError()
 
     @abstractmethod
     def _update_data(self, force_update: Optional[bool] = False) -> None:
@@ -1121,6 +1121,11 @@ class DataProvider(SingletonMixin, DataSequence):
         """
         pass
 
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
+        if hasattr(self, "_initialized"):
+            return
+        super().__init__(*args, **kwargs)
+
     def update_data(
         self,
         force_enable: Optional[bool] = False,
@@ -1595,6 +1600,11 @@ class DataContainer(SingletonMixin, DataBase, MutableMapping):
         )
         return list(key_set)
 
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
+        if hasattr(self, "_initialized"):
+            return
+        super().__init__(*args, **kwargs)
+
     def __getitem__(self, key: str) -> pd.Series:
         """Retrieve a Pandas Series for a specified key from the data in each DataProvider.
 

src/akkudoktoreos/core/ems.py

@@ -169,6 +169,11 @@ class EnergieManagementSystem(SingletonMixin, ConfigMixin, PredictionMixin, Pyda
     dc_charge_hours: Optional[NDArray[Shape["*"], float]] = Field(default=None, description="TBD")
     ev_charge_hours: Optional[NDArray[Shape["*"], float]] = Field(default=None, description="TBD")
 
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
+        if hasattr(self, "_initialized"):
+            return
+        super().__init__(*args, **kwargs)
+
     def set_parameters(
         self,
         parameters: EnergieManagementSystemParameters,
@@ -193,9 +198,9 @@ class EnergieManagementSystem(SingletonMixin, ConfigMixin, PredictionMixin, Pyda
         self.ev = ev
         self.home_appliance = home_appliance
         self.inverter = inverter
-        self.ac_charge_hours = np.full(self.config.prediction_hours, 0.0)
-        self.dc_charge_hours = np.full(self.config.prediction_hours, 1.0)
-        self.ev_charge_hours = np.full(self.config.prediction_hours, 0.0)
+        self.ac_charge_hours = np.full(self.config.prediction.prediction_hours, 0.0)
+        self.dc_charge_hours = np.full(self.config.prediction.prediction_hours, 1.0)
+        self.ev_charge_hours = np.full(self.config.prediction.prediction_hours, 0.0)
 
     def set_akku_discharge_hours(self, ds: np.ndarray) -> None:
         if self.battery is not None:
@@ -246,11 +251,11 @@ class EnergieManagementSystem(SingletonMixin, ConfigMixin, PredictionMixin, Pyda
             error_msg = "Start datetime unknown."
             logger.error(error_msg)
             raise ValueError(error_msg)
-        if self.config.prediction_hours is None:
+        if self.config.prediction.prediction_hours is None:
             error_msg = "Prediction hours unknown."
             logger.error(error_msg)
             raise ValueError(error_msg)
-        if self.config.optimisation_hours is None:
+        if self.config.prediction.optimisation_hours is None:
             error_msg = "Optimisation hours unknown."
             logger.error(error_msg)
             raise ValueError(error_msg)

src/akkudoktoreos/core/pydantic.py

@@ -35,6 +35,21 @@ from pydantic import (
 from akkudoktoreos.utils.datetimeutil import to_datetime, to_duration
 
 
+def merge_models(source: BaseModel, update_dict: dict[str, Any]) -> dict[str, Any]:
+    def deep_update(source_dict: dict[str, Any], update_dict: dict[str, Any]) -> dict[str, Any]:
+        for key, value in source_dict.items():
+            if isinstance(value, dict) and isinstance(update_dict.get(key), dict):
+                update_dict[key] = deep_update(update_dict[key], value)
+            else:
+                update_dict[key] = value
+        return update_dict
+
+    source_dict = source.model_dump(exclude_unset=True)
+    merged_dict = deep_update(source_dict, update_dict)
+
+    return merged_dict
+
+
 class PydanticTypeAdapterDateTime(TypeAdapter[pendulum.DateTime]):
     """Custom type adapter for Pendulum DateTime fields."""