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aa334d0b61
* Update utilities in utils submodule. * Add base configuration modules. * Add server base configuration modules. * Add devices base configuration modules. * Add optimization base configuration modules. * Add utils base configuration modules. * Add prediction abstract and base classes plus tests. * Add PV forecast to prediction submodule. The PV forecast modules are adapted from the class_pvforecast module and replace it. * Add weather forecast to prediction submodule. The modules provide classes and methods to retrieve, manage, and process weather forecast data from various sources. Includes are structured representations of weather data and utilities for fetching forecasts for specific locations and time ranges. BrightSky and ClearOutside are currently supported. * Add electricity price forecast to prediction submodule. * Adapt fastapi server to base config and add fasthtml server. * Add ems to core submodule. * Adapt genetic to config. * Adapt visualize to config. * Adapt common test fixtures to config. * Add load forecast to prediction submodule. * Add core abstract and base classes. * Adapt single test optimization to config. * Adapt devices to config. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
70 lines
2.7 KiB
Python
70 lines
2.7 KiB
Python
"""Retrieves pvforecast forecast data from an import file.
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This module provides classes and mappings to manage pvforecast data obtained from
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an import file, including support for various pvforecast attributes such as temperature,
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humidity, cloud cover, and solar irradiance. The data is mapped to the `PVForecastDataRecord`
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format, enabling consistent access to forecasted and historical pvforecast attributes.
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"""
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from pathlib import Path
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from typing import Optional, Union
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from pydantic import Field, field_validator
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from akkudoktoreos.config.configabc import SettingsBaseModel
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from akkudoktoreos.prediction.predictionabc import PredictionImportProvider
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from akkudoktoreos.prediction.pvforecastabc import PVForecastProvider
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from akkudoktoreos.utils.logutil import get_logger
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logger = get_logger(__name__)
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class PVForecastImportCommonSettings(SettingsBaseModel):
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"""Common settings for pvforecast data import from file."""
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pvforecastimport_file_path: Optional[Union[str, Path]] = Field(
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default=None, description="Path to the file to import pvforecast data from."
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)
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pvforecastimport_json: Optional[str] = Field(
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default=None,
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description="JSON string, dictionary of PV forecast float value lists."
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"Keys are 'pvforecast_dc_power', 'pvforecast_ac_power'.",
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)
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# Validators
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@field_validator("pvforecastimport_file_path", mode="after")
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@classmethod
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def validate_pvforecastimport_file_path(
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cls, value: Optional[Union[str, Path]]
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) -> Optional[Path]:
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if value is None:
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return None
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if isinstance(value, str):
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value = Path(value)
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"""Ensure file is available."""
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value.resolve()
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if not value.is_file():
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raise ValueError(f"Import file path '{value}' is not a file.")
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return value
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class PVForecastImport(PVForecastProvider, PredictionImportProvider):
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"""Fetch PV forecast data from import file or JSON string.
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PVForecastImport is a singleton-based class that retrieves pvforecast forecast data
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from a file or JSON string and maps it to `PVForecastDataRecord` fields. It manages the forecast
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over a range of hours into the future and retains historical data.
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"""
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@classmethod
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def provider_id(cls) -> str:
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"""Return the unique identifier for the PVForecastImport provider."""
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return "PVForecastImport"
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def _update_data(self, force_update: Optional[bool] = False) -> None:
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if self.config.pvforecastimport_file_path is not None:
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self.import_from_file(self.config.pvforecastimport_file_path, key_prefix="pvforecast")
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if self.config.pvforecastimport_json is not None:
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self.import_from_json(self.config.pvforecastimport_json, key_prefix="pvforecast")
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