mirror of
https://github.com/Akkudoktor-EOS/EOS.git
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be26457563
* 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.
62 lines
2.4 KiB
Python
62 lines
2.4 KiB
Python
"""Abstract and base classes for load predictions.
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Notes:
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- Ensure appropriate API keys or configurations are set up if required by external data sources.
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"""
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from abc import abstractmethod
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from typing import List, Optional
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from pydantic import Field
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from akkudoktoreos.core.logging import get_logger
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from akkudoktoreos.prediction.predictionabc import PredictionProvider, PredictionRecord
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logger = get_logger(__name__)
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class LoadDataRecord(PredictionRecord):
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"""Represents a load data record containing various load attributes at a specific datetime."""
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load_mean: Optional[float] = Field(default=None, description="Predicted load mean value (W).")
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load_std: Optional[float] = Field(
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default=None, description="Predicted load standard deviation (W)."
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)
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load_mean_adjusted: Optional[float] = Field(
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default=None, description="Predicted load mean value adjusted by load measurement (W)."
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)
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class LoadProvider(PredictionProvider):
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"""Abstract base class for load providers.
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LoadProvider is a thread-safe singleton, ensuring only one instance of this class is created.
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Configuration variables:
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load_provider (str): Prediction provider for load.
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Attributes:
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prediction_hours (int, optional): The number of hours into the future for which predictions are generated.
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prediction_historic_hours (int, optional): The number of past hours for which historical data is retained.
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latitude (float, optional): The latitude in degrees, must be within -90 to 90.
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longitude (float, optional): The longitude in degrees, must be within -180 to 180.
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start_datetime (datetime, optional): The starting datetime for predictions, defaults to the current datetime if unspecified.
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end_datetime (datetime, computed): The datetime representing the end of the prediction range,
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calculated based on `start_datetime` and `prediction_hours`.
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keep_datetime (datetime, computed): The earliest datetime for retaining historical data, calculated
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based on `start_datetime` and `prediction_historic_hours`.
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"""
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# overload
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records: List[LoadDataRecord] = Field(
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default_factory=list, description="List of LoadDataRecord records"
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)
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@classmethod
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@abstractmethod
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def provider_id(cls) -> str:
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return "LoadProvider"
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def enabled(self) -> bool:
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return self.provider_id() == self.config.load.load_provider
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