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/prediction/weatherbrightsky.py

@@ -99,7 +99,7 @@ class WeatherBrightSky(WeatherProvider):
         date = to_datetime(self.start_datetime, as_string="YYYY-MM-DD")
         last_date = to_datetime(self.end_datetime, as_string="YYYY-MM-DD")
         response = requests.get(
-            f"{source}/weather?lat={self.config.latitude}&lon={self.config.longitude}&date={date}&last_date={last_date}&tz={self.config.timezone}"
+            f"{source}/weather?lat={self.config.prediction.latitude}&lon={self.config.prediction.longitude}&date={date}&last_date={last_date}&tz={self.config.prediction.timezone}"
         )
         response.raise_for_status()  # Raise an error for bad responses
         logger.debug(f"Response from {source}: {response}")
@@ -109,7 +109,7 @@ class WeatherBrightSky(WeatherProvider):
             logger.error(error_msg)
             raise ValueError(error_msg)
         # We are working on fresh data (no cache), report update time
-        self.update_datetime = to_datetime(in_timezone=self.config.timezone)
+        self.update_datetime = to_datetime(in_timezone=self.config.prediction.timezone)
         return brightsky_data
 
     def _description_to_series(self, description: str) -> pd.Series:
@@ -200,7 +200,7 @@ class WeatherBrightSky(WeatherProvider):
         description = "Total Clouds (% Sky Obscured)"
         cloud_cover = self._description_to_series(description)
         ghi, dni, dhi = self.estimate_irradiance_from_cloud_cover(
-            self.config.latitude, self.config.longitude, cloud_cover
+            self.config.prediction.latitude, self.config.prediction.longitude, cloud_cover
         )
 
         description = "Global Horizontal Irradiance (W/m2)"