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"""This module provides functionality to manage and handle configuration for the EOS.
The module including loading, merging, and validating JSON configuration files.
It also provides utility functions for working directory setup and date handling.
Key features:
- Loading and merging configurations from default or custom JSON files
- Validating configurations using Pydantic models
- Managing directory setups for the application
"""
import os
import shutil
from pathlib import Path
Fix2 config and predictions revamp. (#281) measurement: - Add new measurement class to hold real world measurements. - Handles load meter readings, grid import and export meter readings. - Aggregates load meter readings aka. measurements to total load. - Can import measurements from files, pandas datetime series, pandas datetime dataframes, simple daetime arrays and programmatically. - Maybe expanded to other measurement values. - Should be used for load prediction adaptions by real world measurements. core/coreabc: - Add mixin class to access measurements core/pydantic: - Add pydantic models for pandas datetime series and dataframes. - Add pydantic models for simple datetime array core/dataabc: - Provide DataImport mixin class for generic import handling. Imports from JSON string and files. Imports from pandas datetime dataframes and simple datetime arrays. Signature of import method changed to allow import datetimes to be given programmatically and by data content. - Use pydantic models for datetime series, dataframes, arrays - Validate generic imports by pydantic models - Provide new attributes min_datetime and max_datetime for DataSequence. - Add parameter dropna to drop NAN/ None values when creating lists, pandas series or numpy array from DataSequence. config/config: - Add common settings for the measurement module. predictions/elecpriceakkudoktor: - Use mean values of last 7 days to fill prediction values not provided by akkudoktor.net (only provides 24 values). prediction/loadabc: - Extend the generic prediction keys by 'load_total_adjusted' for load predictions that adjust the predicted total load by measured load values. prediction/loadakkudoktor: - Extend the Akkudoktor load prediction by load adjustment using measured load values. prediction/load_aggregator: - Module removed. Load aggregation is now handled by the measurement module. prediction/load_corrector: - Module removed. Load correction (aka. adjustment of load prediction by measured load energy) is handled by the LoadAkkudoktor prediction and the generic 'load_mean_adjusted' prediction key. prediction/load_forecast: - Module removed. Functionality now completely handled by the LoadAkkudoktor prediction. utils/cacheutil: - Use pydantic. - Fix potential bug in ttl (time to live) duration handling. utils/datetimeutil: - Added missing handling of pendulum.DateTime and pendulum.Duration instances as input. Handled before as datetime.datetime and datetime.timedelta. utils/visualize: - Move main to generate_example_report() for better testing support. server/server: - Added new configuration option server_fastapi_startup_server_fasthtml to make startup of FastHTML server by FastAPI server conditional. server/fastapi_server: - Add APIs for measurements - Improve APIs to provide or take pandas datetime series and datetime dataframes controlled by pydantic model. - Improve APIs to provide or take simple datetime data arrays controlled by pydantic model. - Move fastAPI server API to v1 for new APIs. - Update pre v1 endpoints to use new prediction and measurement capabilities. - Only start FastHTML server if 'server_fastapi_startup_server_fasthtml' config option is set. tests: - Adapt import tests to changed import method signature - Adapt server test to use the v1 API - Extend the dataabc test to test for array generation from data with several data interval scenarios. - Extend the datetimeutil test to also test for correct handling of to_datetime() providing now(). - Adapt LoadAkkudoktor test for new adjustment calculation. - Adapt visualization test to use example report function instead of visualize.py run as process. - Removed test_load_aggregator. Functionality is now tested in test_measurement. - Added tests for measurement module docs: - Remove sphinxcontrib-openapi as it prevents build of documentation. "site-packages/sphinxcontrib/openapi/openapi31.py", line 305, in _get_type_from_schema for t in schema["anyOf"]: KeyError: 'anyOf'" Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2024-12-29 18:42:49 +01:00
from typing import Any, ClassVar, List, Optional
from platformdirs import user_config_dir, user_data_dir
from pydantic import Field, ValidationError, computed_field
# settings
from akkudoktoreos.config.configabc import SettingsBaseModel
from akkudoktoreos.core.coreabc import SingletonMixin
from akkudoktoreos.core.logging import get_logger
from akkudoktoreos.core.logsettings import LoggingCommonSettings
from akkudoktoreos.devices.devices import DevicesCommonSettings
Fix2 config and predictions revamp. (#281) measurement: - Add new measurement class to hold real world measurements. - Handles load meter readings, grid import and export meter readings. - Aggregates load meter readings aka. measurements to total load. - Can import measurements from files, pandas datetime series, pandas datetime dataframes, simple daetime arrays and programmatically. - Maybe expanded to other measurement values. - Should be used for load prediction adaptions by real world measurements. core/coreabc: - Add mixin class to access measurements core/pydantic: - Add pydantic models for pandas datetime series and dataframes. - Add pydantic models for simple datetime array core/dataabc: - Provide DataImport mixin class for generic import handling. Imports from JSON string and files. Imports from pandas datetime dataframes and simple datetime arrays. Signature of import method changed to allow import datetimes to be given programmatically and by data content. - Use pydantic models for datetime series, dataframes, arrays - Validate generic imports by pydantic models - Provide new attributes min_datetime and max_datetime for DataSequence. - Add parameter dropna to drop NAN/ None values when creating lists, pandas series or numpy array from DataSequence. config/config: - Add common settings for the measurement module. predictions/elecpriceakkudoktor: - Use mean values of last 7 days to fill prediction values not provided by akkudoktor.net (only provides 24 values). prediction/loadabc: - Extend the generic prediction keys by 'load_total_adjusted' for load predictions that adjust the predicted total load by measured load values. prediction/loadakkudoktor: - Extend the Akkudoktor load prediction by load adjustment using measured load values. prediction/load_aggregator: - Module removed. Load aggregation is now handled by the measurement module. prediction/load_corrector: - Module removed. Load correction (aka. adjustment of load prediction by measured load energy) is handled by the LoadAkkudoktor prediction and the generic 'load_mean_adjusted' prediction key. prediction/load_forecast: - Module removed. Functionality now completely handled by the LoadAkkudoktor prediction. utils/cacheutil: - Use pydantic. - Fix potential bug in ttl (time to live) duration handling. utils/datetimeutil: - Added missing handling of pendulum.DateTime and pendulum.Duration instances as input. Handled before as datetime.datetime and datetime.timedelta. utils/visualize: - Move main to generate_example_report() for better testing support. server/server: - Added new configuration option server_fastapi_startup_server_fasthtml to make startup of FastHTML server by FastAPI server conditional. server/fastapi_server: - Add APIs for measurements - Improve APIs to provide or take pandas datetime series and datetime dataframes controlled by pydantic model. - Improve APIs to provide or take simple datetime data arrays controlled by pydantic model. - Move fastAPI server API to v1 for new APIs. - Update pre v1 endpoints to use new prediction and measurement capabilities. - Only start FastHTML server if 'server_fastapi_startup_server_fasthtml' config option is set. tests: - Adapt import tests to changed import method signature - Adapt server test to use the v1 API - Extend the dataabc test to test for array generation from data with several data interval scenarios. - Extend the datetimeutil test to also test for correct handling of to_datetime() providing now(). - Adapt LoadAkkudoktor test for new adjustment calculation. - Adapt visualization test to use example report function instead of visualize.py run as process. - Removed test_load_aggregator. Functionality is now tested in test_measurement. - Added tests for measurement module docs: - Remove sphinxcontrib-openapi as it prevents build of documentation. "site-packages/sphinxcontrib/openapi/openapi31.py", line 305, in _get_type_from_schema for t in schema["anyOf"]: KeyError: 'anyOf'" Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2024-12-29 18:42:49 +01:00
from akkudoktoreos.measurement.measurement import MeasurementCommonSettings
from akkudoktoreos.optimization.optimization import OptimizationCommonSettings
from akkudoktoreos.prediction.elecprice import ElecPriceCommonSettings
from akkudoktoreos.prediction.elecpriceimport import ElecPriceImportCommonSettings
from akkudoktoreos.prediction.load import LoadCommonSettings
from akkudoktoreos.prediction.loadakkudoktor import LoadAkkudoktorCommonSettings
from akkudoktoreos.prediction.loadimport import LoadImportCommonSettings
from akkudoktoreos.prediction.prediction import PredictionCommonSettings
from akkudoktoreos.prediction.pvforecast import PVForecastCommonSettings
from akkudoktoreos.prediction.pvforecastimport import PVForecastImportCommonSettings
from akkudoktoreos.prediction.weather import WeatherCommonSettings
from akkudoktoreos.prediction.weatherimport import WeatherImportCommonSettings
from akkudoktoreos.server.server import ServerCommonSettings
from akkudoktoreos.utils.utils import UtilsCommonSettings
logger = get_logger(__name__)
def get_absolute_path(
basepath: Optional[Path | str], subpath: Optional[Path | str]
) -> Optional[Path]:
"""Get path based on base path."""
if isinstance(basepath, str):
basepath = Path(basepath)
if subpath is None:
return basepath
if isinstance(subpath, str):
subpath = Path(subpath)
if subpath.is_absolute():
return subpath
if basepath is not None:
return basepath.joinpath(subpath)
return None
class ConfigCommonSettings(SettingsBaseModel):
"""Settings for common configuration."""
data_folder_path: Optional[Path] = Field(
default=None, description="Path to EOS data directory."
)
data_output_subpath: Optional[Path] = Field(
"output", description="Sub-path for the EOS output data directory."
)
data_cache_subpath: Optional[Path] = Field(
"cache", description="Sub-path for the EOS cache data directory."
)
# Computed fields
@computed_field # type: ignore[prop-decorator]
@property
def data_output_path(self) -> Optional[Path]:
"""Compute data_output_path based on data_folder_path."""
return get_absolute_path(self.data_folder_path, self.data_output_subpath)
# Computed fields
@computed_field # type: ignore[prop-decorator]
@property
def data_cache_path(self) -> Optional[Path]:
"""Compute data_cache_path based on data_folder_path."""
return get_absolute_path(self.data_folder_path, self.data_cache_subpath)
class SettingsEOS(
ConfigCommonSettings,
LoggingCommonSettings,
DevicesCommonSettings,
Fix2 config and predictions revamp. (#281) measurement: - Add new measurement class to hold real world measurements. - Handles load meter readings, grid import and export meter readings. - Aggregates load meter readings aka. measurements to total load. - Can import measurements from files, pandas datetime series, pandas datetime dataframes, simple daetime arrays and programmatically. - Maybe expanded to other measurement values. - Should be used for load prediction adaptions by real world measurements. core/coreabc: - Add mixin class to access measurements core/pydantic: - Add pydantic models for pandas datetime series and dataframes. - Add pydantic models for simple datetime array core/dataabc: - Provide DataImport mixin class for generic import handling. Imports from JSON string and files. Imports from pandas datetime dataframes and simple datetime arrays. Signature of import method changed to allow import datetimes to be given programmatically and by data content. - Use pydantic models for datetime series, dataframes, arrays - Validate generic imports by pydantic models - Provide new attributes min_datetime and max_datetime for DataSequence. - Add parameter dropna to drop NAN/ None values when creating lists, pandas series or numpy array from DataSequence. config/config: - Add common settings for the measurement module. predictions/elecpriceakkudoktor: - Use mean values of last 7 days to fill prediction values not provided by akkudoktor.net (only provides 24 values). prediction/loadabc: - Extend the generic prediction keys by 'load_total_adjusted' for load predictions that adjust the predicted total load by measured load values. prediction/loadakkudoktor: - Extend the Akkudoktor load prediction by load adjustment using measured load values. prediction/load_aggregator: - Module removed. Load aggregation is now handled by the measurement module. prediction/load_corrector: - Module removed. Load correction (aka. adjustment of load prediction by measured load energy) is handled by the LoadAkkudoktor prediction and the generic 'load_mean_adjusted' prediction key. prediction/load_forecast: - Module removed. Functionality now completely handled by the LoadAkkudoktor prediction. utils/cacheutil: - Use pydantic. - Fix potential bug in ttl (time to live) duration handling. utils/datetimeutil: - Added missing handling of pendulum.DateTime and pendulum.Duration instances as input. Handled before as datetime.datetime and datetime.timedelta. utils/visualize: - Move main to generate_example_report() for better testing support. server/server: - Added new configuration option server_fastapi_startup_server_fasthtml to make startup of FastHTML server by FastAPI server conditional. server/fastapi_server: - Add APIs for measurements - Improve APIs to provide or take pandas datetime series and datetime dataframes controlled by pydantic model. - Improve APIs to provide or take simple datetime data arrays controlled by pydantic model. - Move fastAPI server API to v1 for new APIs. - Update pre v1 endpoints to use new prediction and measurement capabilities. - Only start FastHTML server if 'server_fastapi_startup_server_fasthtml' config option is set. tests: - Adapt import tests to changed import method signature - Adapt server test to use the v1 API - Extend the dataabc test to test for array generation from data with several data interval scenarios. - Extend the datetimeutil test to also test for correct handling of to_datetime() providing now(). - Adapt LoadAkkudoktor test for new adjustment calculation. - Adapt visualization test to use example report function instead of visualize.py run as process. - Removed test_load_aggregator. Functionality is now tested in test_measurement. - Added tests for measurement module docs: - Remove sphinxcontrib-openapi as it prevents build of documentation. "site-packages/sphinxcontrib/openapi/openapi31.py", line 305, in _get_type_from_schema for t in schema["anyOf"]: KeyError: 'anyOf'" Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2024-12-29 18:42:49 +01:00
MeasurementCommonSettings,
OptimizationCommonSettings,
PredictionCommonSettings,
ElecPriceCommonSettings,
ElecPriceImportCommonSettings,
LoadCommonSettings,
LoadAkkudoktorCommonSettings,
LoadImportCommonSettings,
PVForecastCommonSettings,
PVForecastImportCommonSettings,
WeatherCommonSettings,
WeatherImportCommonSettings,
ServerCommonSettings,
UtilsCommonSettings,
):
"""Settings for all EOS."""
pass
class ConfigEOS(SingletonMixin, SettingsEOS):
"""Singleton configuration handler for the EOS application.
ConfigEOS extends `SettingsEOS` with support for default configuration paths and automatic
initialization.
`ConfigEOS` ensures that only one instance of the class is created throughout the application,
allowing consistent access to EOS configuration settings. This singleton instance loads
configuration data from a predefined set of directories or creates a default configuration if
none is found.
Initialization Process:
- Upon instantiation, the singleton instance attempts to load a configuration file in this order:
1. The directory specified by the `EOS_CONFIG_DIR` environment variable
2. The directory specified by the `EOS_DIR` environment variable.
3. A platform specific default directory for EOS.
4. The current working directory.
- The first available configuration file found in these directories is loaded.
- If no configuration file is found, a default configuration file is created in the platform
specific default directory, and default settings are loaded into it.
Attributes from the loaded configuration are accessible directly as instance attributes of
`ConfigEOS`, providing a centralized, shared configuration object for EOS.
Singleton Behavior:
- This class uses the `SingletonMixin` to ensure that all requests for `ConfigEOS` return
the same instance, which contains the most up-to-date configuration. Modifying the configuration
in one part of the application reflects across all references to this class.
Attributes:
_settings (ClassVar[SettingsEOS]): Holds application-wide settings.
_file_settings (ClassVar[SettingsEOS]): Stores configuration loaded from file.
config_folder_path (Optional[Path]): Path to the configuration directory.
config_file_path (Optional[Path]): Path to the configuration file.
Raises:
FileNotFoundError: If no configuration file is found, and creating a default configuration fails.
Example:
To initialize and access configuration attributes (only one instance is created):
```python
config_eos = ConfigEOS() # Always returns the same instance
print(config_eos.prediction_hours) # Access a setting from the loaded configuration
```
"""
APP_NAME: ClassVar[str] = "net.akkudoktor.eos" # reverse order
APP_AUTHOR: ClassVar[str] = "akkudoktor"
EOS_DIR: ClassVar[str] = "EOS_DIR"
EOS_CONFIG_DIR: ClassVar[str] = "EOS_CONFIG_DIR"
ENCODING: ClassVar[str] = "UTF-8"
CONFIG_FILE_NAME: ClassVar[str] = "EOS.config.json"
_settings: ClassVar[Optional[SettingsEOS]] = None
_file_settings: ClassVar[Optional[SettingsEOS]] = None
_config_folder_path: Optional[Path] = None
_config_file_path: Optional[Path] = None
# Computed fields
@computed_field # type: ignore[prop-decorator]
@property
def config_folder_path(self) -> Optional[Path]:
"""Path to EOS configuration directory."""
return self._config_folder_path
@computed_field # type: ignore[prop-decorator]
@property
def config_file_path(self) -> Optional[Path]:
"""Path to EOS configuration file."""
return self._config_file_path
@computed_field # type: ignore[prop-decorator]
@property
def config_default_file_path(self) -> Path:
"""Compute the default config file path."""
return self.package_root_path.joinpath("data/default.config.json")
@computed_field # type: ignore[prop-decorator]
@property
def package_root_path(self) -> Path:
"""Compute the package root path."""
return Path(__file__).parent.parent.resolve()
Fix2 config and predictions revamp. (#281) measurement: - Add new measurement class to hold real world measurements. - Handles load meter readings, grid import and export meter readings. - Aggregates load meter readings aka. measurements to total load. - Can import measurements from files, pandas datetime series, pandas datetime dataframes, simple daetime arrays and programmatically. - Maybe expanded to other measurement values. - Should be used for load prediction adaptions by real world measurements. core/coreabc: - Add mixin class to access measurements core/pydantic: - Add pydantic models for pandas datetime series and dataframes. - Add pydantic models for simple datetime array core/dataabc: - Provide DataImport mixin class for generic import handling. Imports from JSON string and files. Imports from pandas datetime dataframes and simple datetime arrays. Signature of import method changed to allow import datetimes to be given programmatically and by data content. - Use pydantic models for datetime series, dataframes, arrays - Validate generic imports by pydantic models - Provide new attributes min_datetime and max_datetime for DataSequence. - Add parameter dropna to drop NAN/ None values when creating lists, pandas series or numpy array from DataSequence. config/config: - Add common settings for the measurement module. predictions/elecpriceakkudoktor: - Use mean values of last 7 days to fill prediction values not provided by akkudoktor.net (only provides 24 values). prediction/loadabc: - Extend the generic prediction keys by 'load_total_adjusted' for load predictions that adjust the predicted total load by measured load values. prediction/loadakkudoktor: - Extend the Akkudoktor load prediction by load adjustment using measured load values. prediction/load_aggregator: - Module removed. Load aggregation is now handled by the measurement module. prediction/load_corrector: - Module removed. Load correction (aka. adjustment of load prediction by measured load energy) is handled by the LoadAkkudoktor prediction and the generic 'load_mean_adjusted' prediction key. prediction/load_forecast: - Module removed. Functionality now completely handled by the LoadAkkudoktor prediction. utils/cacheutil: - Use pydantic. - Fix potential bug in ttl (time to live) duration handling. utils/datetimeutil: - Added missing handling of pendulum.DateTime and pendulum.Duration instances as input. Handled before as datetime.datetime and datetime.timedelta. utils/visualize: - Move main to generate_example_report() for better testing support. server/server: - Added new configuration option server_fastapi_startup_server_fasthtml to make startup of FastHTML server by FastAPI server conditional. server/fastapi_server: - Add APIs for measurements - Improve APIs to provide or take pandas datetime series and datetime dataframes controlled by pydantic model. - Improve APIs to provide or take simple datetime data arrays controlled by pydantic model. - Move fastAPI server API to v1 for new APIs. - Update pre v1 endpoints to use new prediction and measurement capabilities. - Only start FastHTML server if 'server_fastapi_startup_server_fasthtml' config option is set. tests: - Adapt import tests to changed import method signature - Adapt server test to use the v1 API - Extend the dataabc test to test for array generation from data with several data interval scenarios. - Extend the datetimeutil test to also test for correct handling of to_datetime() providing now(). - Adapt LoadAkkudoktor test for new adjustment calculation. - Adapt visualization test to use example report function instead of visualize.py run as process. - Removed test_load_aggregator. Functionality is now tested in test_measurement. - Added tests for measurement module docs: - Remove sphinxcontrib-openapi as it prevents build of documentation. "site-packages/sphinxcontrib/openapi/openapi31.py", line 305, in _get_type_from_schema for t in schema["anyOf"]: KeyError: 'anyOf'" Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2024-12-29 18:42:49 +01:00
# Computed fields
@computed_field # type: ignore[prop-decorator]
@property
def config_keys(self) -> List[str]:
"""Returns the keys of all fields in the configuration."""
key_list = []
key_list.extend(list(self.model_fields.keys()))
key_list.extend(list(self.__pydantic_decorators__.computed_fields.keys()))
return key_list
# Computed fields
@computed_field # type: ignore[prop-decorator]
@property
def config_keys_read_only(self) -> List[str]:
"""Returns the keys of all read only fields in the configuration."""
key_list = []
key_list.extend(list(self.__pydantic_decorators__.computed_fields.keys()))
return key_list
def __init__(self) -> None:
"""Initializes the singleton ConfigEOS instance.
Configuration data is loaded from a configuration file or a default one is created if none
exists.
"""
super().__init__()
self.from_config_file()
self.update()
@property
def settings(self) -> Optional[SettingsEOS]:
"""Returns global settings for EOS.
Settings generally provide configuration for EOS and are typically set only once.
Returns:
SettingsEOS: The settings for EOS or None.
"""
return ConfigEOS._settings
@classmethod
def _merge_and_update_settings(cls, settings: SettingsEOS) -> None:
"""Merge new and available settings.
Args:
settings (SettingsEOS): The new settings to apply.
"""
for key in SettingsEOS.model_fields:
if value := getattr(settings, key, None):
setattr(cls._settings, key, value)
def merge_settings(self, settings: SettingsEOS, force: Optional[bool] = None) -> None:
"""Merges the provided settings into the global settings for EOS, with optional overwrite.
Args:
settings (SettingsEOS): The settings to apply globally.
force (Optional[bool]): If True, overwrites the existing settings completely.
If False, the new settings are merged to the existing ones with priority for
the new ones. Defaults to False.
Raises:
ValueError: If settings are already set and `force` is not True or
if the `settings` is not a `SettingsEOS` instance.
"""
if not isinstance(settings, SettingsEOS):
raise ValueError(f"Settings must be an instance of SettingsEOS: '{settings}'.")
if ConfigEOS._settings is None or force:
ConfigEOS._settings = settings
else:
self._merge_and_update_settings(settings)
# Update configuration after merging
self.update()
def merge_settings_from_dict(self, data: dict) -> None:
"""Merges the provided dictionary data into the current instance.
Fix2 config and predictions revamp. (#281) measurement: - Add new measurement class to hold real world measurements. - Handles load meter readings, grid import and export meter readings. - Aggregates load meter readings aka. measurements to total load. - Can import measurements from files, pandas datetime series, pandas datetime dataframes, simple daetime arrays and programmatically. - Maybe expanded to other measurement values. - Should be used for load prediction adaptions by real world measurements. core/coreabc: - Add mixin class to access measurements core/pydantic: - Add pydantic models for pandas datetime series and dataframes. - Add pydantic models for simple datetime array core/dataabc: - Provide DataImport mixin class for generic import handling. Imports from JSON string and files. Imports from pandas datetime dataframes and simple datetime arrays. Signature of import method changed to allow import datetimes to be given programmatically and by data content. - Use pydantic models for datetime series, dataframes, arrays - Validate generic imports by pydantic models - Provide new attributes min_datetime and max_datetime for DataSequence. - Add parameter dropna to drop NAN/ None values when creating lists, pandas series or numpy array from DataSequence. config/config: - Add common settings for the measurement module. predictions/elecpriceakkudoktor: - Use mean values of last 7 days to fill prediction values not provided by akkudoktor.net (only provides 24 values). prediction/loadabc: - Extend the generic prediction keys by 'load_total_adjusted' for load predictions that adjust the predicted total load by measured load values. prediction/loadakkudoktor: - Extend the Akkudoktor load prediction by load adjustment using measured load values. prediction/load_aggregator: - Module removed. Load aggregation is now handled by the measurement module. prediction/load_corrector: - Module removed. Load correction (aka. adjustment of load prediction by measured load energy) is handled by the LoadAkkudoktor prediction and the generic 'load_mean_adjusted' prediction key. prediction/load_forecast: - Module removed. Functionality now completely handled by the LoadAkkudoktor prediction. utils/cacheutil: - Use pydantic. - Fix potential bug in ttl (time to live) duration handling. utils/datetimeutil: - Added missing handling of pendulum.DateTime and pendulum.Duration instances as input. Handled before as datetime.datetime and datetime.timedelta. utils/visualize: - Move main to generate_example_report() for better testing support. server/server: - Added new configuration option server_fastapi_startup_server_fasthtml to make startup of FastHTML server by FastAPI server conditional. server/fastapi_server: - Add APIs for measurements - Improve APIs to provide or take pandas datetime series and datetime dataframes controlled by pydantic model. - Improve APIs to provide or take simple datetime data arrays controlled by pydantic model. - Move fastAPI server API to v1 for new APIs. - Update pre v1 endpoints to use new prediction and measurement capabilities. - Only start FastHTML server if 'server_fastapi_startup_server_fasthtml' config option is set. tests: - Adapt import tests to changed import method signature - Adapt server test to use the v1 API - Extend the dataabc test to test for array generation from data with several data interval scenarios. - Extend the datetimeutil test to also test for correct handling of to_datetime() providing now(). - Adapt LoadAkkudoktor test for new adjustment calculation. - Adapt visualization test to use example report function instead of visualize.py run as process. - Removed test_load_aggregator. Functionality is now tested in test_measurement. - Added tests for measurement module docs: - Remove sphinxcontrib-openapi as it prevents build of documentation. "site-packages/sphinxcontrib/openapi/openapi31.py", line 305, in _get_type_from_schema for t in schema["anyOf"]: KeyError: 'anyOf'" Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2024-12-29 18:42:49 +01:00
Creates a new settings instance, then applies the dictionary data through validation,
and finally merges the validated settings into the current instance. None values
are not merged.
Args:
data (dict): Dictionary containing field values to merge into the
current settings instance.
Raises:
ValidationError: If the data contains invalid values for the defined fields.
Example:
>>> config = get_config()
>>> new_data = {"prediction_hours": 24, "server_fastapi_port": 8000}
>>> config.merge_settings_from_dict(new_data)
"""
# Create new settings instance with reset optional fields and merged data
Fix2 config and predictions revamp. (#281) measurement: - Add new measurement class to hold real world measurements. - Handles load meter readings, grid import and export meter readings. - Aggregates load meter readings aka. measurements to total load. - Can import measurements from files, pandas datetime series, pandas datetime dataframes, simple daetime arrays and programmatically. - Maybe expanded to other measurement values. - Should be used for load prediction adaptions by real world measurements. core/coreabc: - Add mixin class to access measurements core/pydantic: - Add pydantic models for pandas datetime series and dataframes. - Add pydantic models for simple datetime array core/dataabc: - Provide DataImport mixin class for generic import handling. Imports from JSON string and files. Imports from pandas datetime dataframes and simple datetime arrays. Signature of import method changed to allow import datetimes to be given programmatically and by data content. - Use pydantic models for datetime series, dataframes, arrays - Validate generic imports by pydantic models - Provide new attributes min_datetime and max_datetime for DataSequence. - Add parameter dropna to drop NAN/ None values when creating lists, pandas series or numpy array from DataSequence. config/config: - Add common settings for the measurement module. predictions/elecpriceakkudoktor: - Use mean values of last 7 days to fill prediction values not provided by akkudoktor.net (only provides 24 values). prediction/loadabc: - Extend the generic prediction keys by 'load_total_adjusted' for load predictions that adjust the predicted total load by measured load values. prediction/loadakkudoktor: - Extend the Akkudoktor load prediction by load adjustment using measured load values. prediction/load_aggregator: - Module removed. Load aggregation is now handled by the measurement module. prediction/load_corrector: - Module removed. Load correction (aka. adjustment of load prediction by measured load energy) is handled by the LoadAkkudoktor prediction and the generic 'load_mean_adjusted' prediction key. prediction/load_forecast: - Module removed. Functionality now completely handled by the LoadAkkudoktor prediction. utils/cacheutil: - Use pydantic. - Fix potential bug in ttl (time to live) duration handling. utils/datetimeutil: - Added missing handling of pendulum.DateTime and pendulum.Duration instances as input. Handled before as datetime.datetime and datetime.timedelta. utils/visualize: - Move main to generate_example_report() for better testing support. server/server: - Added new configuration option server_fastapi_startup_server_fasthtml to make startup of FastHTML server by FastAPI server conditional. server/fastapi_server: - Add APIs for measurements - Improve APIs to provide or take pandas datetime series and datetime dataframes controlled by pydantic model. - Improve APIs to provide or take simple datetime data arrays controlled by pydantic model. - Move fastAPI server API to v1 for new APIs. - Update pre v1 endpoints to use new prediction and measurement capabilities. - Only start FastHTML server if 'server_fastapi_startup_server_fasthtml' config option is set. tests: - Adapt import tests to changed import method signature - Adapt server test to use the v1 API - Extend the dataabc test to test for array generation from data with several data interval scenarios. - Extend the datetimeutil test to also test for correct handling of to_datetime() providing now(). - Adapt LoadAkkudoktor test for new adjustment calculation. - Adapt visualization test to use example report function instead of visualize.py run as process. - Removed test_load_aggregator. Functionality is now tested in test_measurement. - Added tests for measurement module docs: - Remove sphinxcontrib-openapi as it prevents build of documentation. "site-packages/sphinxcontrib/openapi/openapi31.py", line 305, in _get_type_from_schema for t in schema["anyOf"]: KeyError: 'anyOf'" Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2024-12-29 18:42:49 +01:00
settings = SettingsEOS.from_dict(data)
self.merge_settings(settings)
def reset_settings(self) -> None:
"""Reset all available settings.
This functions basically deletes the settings provided before.
"""
ConfigEOS._settings = None
def _update_data_folder_path(self) -> None:
"""Updates path to the data directory."""
# From Settings
if self.settings and (data_dir := self.settings.data_folder_path):
try:
data_dir.mkdir(parents=True, exist_ok=True)
self.data_folder_path = data_dir
return
except:
pass
# From EOS_DIR env
env_dir = os.getenv(self.EOS_DIR)
if env_dir is not None:
try:
data_dir = Path(env_dir).resolve()
data_dir.mkdir(parents=True, exist_ok=True)
self.data_folder_path = data_dir
return
except:
pass
# From configuration file
if self._file_settings and (data_dir := self._file_settings.data_folder_path):
try:
data_dir.mkdir(parents=True, exist_ok=True)
self.data_folder_path = data_dir
return
except:
pass
# From platform specific default path
try:
data_dir = Path(user_data_dir(self.APP_NAME, self.APP_AUTHOR))
if data_dir is not None:
data_dir.mkdir(parents=True, exist_ok=True)
self.data_folder_path = data_dir
return
except:
pass
# Current working directory
data_dir = Path.cwd()
self.data_folder_path = data_dir
def _get_config_file_path(self) -> tuple[Path, bool]:
"""Finds the a valid configuration file or returns the desired path for a new config file.
Returns:
tuple[Path, bool]: The path to the configuration directory and if there is already a config file there
"""
config_dirs = []
env_base_dir = os.getenv(self.EOS_DIR)
env_config_dir = os.getenv(self.EOS_CONFIG_DIR)
env_dir = get_absolute_path(env_base_dir, env_config_dir)
logger.debug(f"Envionment config dir: '{env_dir}'")
if env_dir is not None:
config_dirs.append(env_dir.resolve())
config_dirs.append(Path(user_config_dir(self.APP_NAME)))
config_dirs.append(Path.cwd())
for cdir in config_dirs:
cfile = cdir.joinpath(self.CONFIG_FILE_NAME)
if cfile.exists():
logger.debug(f"Found config file: '{cfile}'")
return cfile, True
return config_dirs[0].joinpath(self.CONFIG_FILE_NAME), False
def settings_from_config_file(self) -> tuple[SettingsEOS, Path]:
"""Load settings from the configuration file.
If the config file does not exist, it will be created.
Returns:
tuple of settings and path
settings (SettingsEOS): The settings defined by the EOS configuration file.
path (pathlib.Path): The path of the configuration file.
Raises:
ValueError: If the configuration file is invalid or incomplete.
"""
config_file, exists = self._get_config_file_path()
config_dir = config_file.parent
# Create config directory and copy default config if file does not exist
if not exists:
config_dir.mkdir(parents=True, exist_ok=True)
try:
shutil.copy2(self.config_default_file_path, config_file)
except Exception as exc:
logger.warning(f"Could not copy default config: {exc}. Using default config...")
config_file = self.config_default_file_path
config_dir = config_file.parent
# Load and validate the configuration file
with config_file.open("r", encoding=self.ENCODING) as f_in:
try:
json_str = f_in.read()
settings = SettingsEOS.model_validate_json(json_str)
except ValidationError as exc:
raise ValueError(f"Configuration '{config_file}' is incomplete or not valid: {exc}")
return settings, config_file
def from_config_file(self) -> tuple[SettingsEOS, Path]:
"""Load the configuration file settings for EOS.
Returns:
tuple of settings and path
settings (SettingsEOS): The settings defined by the EOS configuration file.
path (pathlib.Path): The path of the configuration file.
Raises:
ValueError: If the configuration file is invalid or incomplete.
"""
# Load settings from config file
ConfigEOS._file_settings, config_file = self.settings_from_config_file()
# Update configuration in memory
self.update()
# Everything worked, remember the values
self._config_folder_path = config_file.parent
self._config_file_path = config_file
return ConfigEOS._file_settings, config_file
def to_config_file(self) -> None:
"""Saves the current configuration to the configuration file.
Also updates the configuration file settings.
Raises:
ValueError: If the configuration file path is not specified or can not be written to.
"""
if not self.config_file_path:
raise ValueError("Configuration file path unknown.")
Fix2 config and predictions revamp. (#281) measurement: - Add new measurement class to hold real world measurements. - Handles load meter readings, grid import and export meter readings. - Aggregates load meter readings aka. measurements to total load. - Can import measurements from files, pandas datetime series, pandas datetime dataframes, simple daetime arrays and programmatically. - Maybe expanded to other measurement values. - Should be used for load prediction adaptions by real world measurements. core/coreabc: - Add mixin class to access measurements core/pydantic: - Add pydantic models for pandas datetime series and dataframes. - Add pydantic models for simple datetime array core/dataabc: - Provide DataImport mixin class for generic import handling. Imports from JSON string and files. Imports from pandas datetime dataframes and simple datetime arrays. Signature of import method changed to allow import datetimes to be given programmatically and by data content. - Use pydantic models for datetime series, dataframes, arrays - Validate generic imports by pydantic models - Provide new attributes min_datetime and max_datetime for DataSequence. - Add parameter dropna to drop NAN/ None values when creating lists, pandas series or numpy array from DataSequence. config/config: - Add common settings for the measurement module. predictions/elecpriceakkudoktor: - Use mean values of last 7 days to fill prediction values not provided by akkudoktor.net (only provides 24 values). prediction/loadabc: - Extend the generic prediction keys by 'load_total_adjusted' for load predictions that adjust the predicted total load by measured load values. prediction/loadakkudoktor: - Extend the Akkudoktor load prediction by load adjustment using measured load values. prediction/load_aggregator: - Module removed. Load aggregation is now handled by the measurement module. prediction/load_corrector: - Module removed. Load correction (aka. adjustment of load prediction by measured load energy) is handled by the LoadAkkudoktor prediction and the generic 'load_mean_adjusted' prediction key. prediction/load_forecast: - Module removed. Functionality now completely handled by the LoadAkkudoktor prediction. utils/cacheutil: - Use pydantic. - Fix potential bug in ttl (time to live) duration handling. utils/datetimeutil: - Added missing handling of pendulum.DateTime and pendulum.Duration instances as input. Handled before as datetime.datetime and datetime.timedelta. utils/visualize: - Move main to generate_example_report() for better testing support. server/server: - Added new configuration option server_fastapi_startup_server_fasthtml to make startup of FastHTML server by FastAPI server conditional. server/fastapi_server: - Add APIs for measurements - Improve APIs to provide or take pandas datetime series and datetime dataframes controlled by pydantic model. - Improve APIs to provide or take simple datetime data arrays controlled by pydantic model. - Move fastAPI server API to v1 for new APIs. - Update pre v1 endpoints to use new prediction and measurement capabilities. - Only start FastHTML server if 'server_fastapi_startup_server_fasthtml' config option is set. tests: - Adapt import tests to changed import method signature - Adapt server test to use the v1 API - Extend the dataabc test to test for array generation from data with several data interval scenarios. - Extend the datetimeutil test to also test for correct handling of to_datetime() providing now(). - Adapt LoadAkkudoktor test for new adjustment calculation. - Adapt visualization test to use example report function instead of visualize.py run as process. - Removed test_load_aggregator. Functionality is now tested in test_measurement. - Added tests for measurement module docs: - Remove sphinxcontrib-openapi as it prevents build of documentation. "site-packages/sphinxcontrib/openapi/openapi31.py", line 305, in _get_type_from_schema for t in schema["anyOf"]: KeyError: 'anyOf'" Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2024-12-29 18:42:49 +01:00
with self.config_file_path.open("w", encoding=self.ENCODING) as f_out:
try:
json_str = super().to_json()
# Write to file
f_out.write(json_str)
# Also remember as actual settings
ConfigEOS._file_settings = SettingsEOS.model_validate_json(json_str)
except ValidationError as exc:
raise ValueError(f"Could not update '{self.config_file_path}': {exc}")
def _config_value(self, key: str) -> Any:
"""Retrieves the configuration value for a specific key, following a priority order.
Values are fetched in the following order:
1. Settings.
2. Environment variables.
3. EOS configuration file.
4. Current configuration.
5. Field default constants.
Args:
key (str): The configuration key to retrieve.
Returns:
Any: The configuration value, or None if not found.
"""
# Settings
if ConfigEOS._settings:
if (value := getattr(self.settings, key, None)) is not None:
return value
# Environment variables
if (value := os.getenv(key)) is not None:
try:
return float(value)
except ValueError:
return value
# EOS configuration file.
if self._file_settings:
if (value := getattr(self._file_settings, key, None)) is not None:
return value
# Current configuration - key is valid as called by update().
if (value := getattr(self, key, None)) is not None:
return value
# Field default constants
if (value := ConfigEOS.model_fields[key].default) is not None:
return value
logger.debug(f"Value for configuration key '{key}' not found or is {value}")
return None
def update(self) -> None:
"""Updates all configuration fields.
This method updates all configuration fields using the following order for value retrieval:
1. Settings.
2. Environment variables.
3. EOS configuration file.
4. Current configuration.
5. Field default constants.
The first non None value in priority order is taken.
"""
self._update_data_folder_path()
for key in self.model_fields:
setattr(self, key, self._config_value(key))
def get_config() -> ConfigEOS:
"""Gets the EOS configuration data."""
return ConfigEOS()