phlower.settings.PhlowerSetting

class phlower.settings.PhlowerSetting(*, version='0.1.0', training=None, model=None, scaling=None, prediction=None)

Bases: BaseModel

Methods

check_version(version)
read_yaml(file_path[, decrypt_key])	Read yaml file and parse to PhlowerSetting object.

Attributes

model_computed_fields
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extra	Get extra fields set during validation.
model_fields
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.
version
training	training setting.
model	model setting.
scaling	scaling setting.
prediction	prediction setting.

Parameters:

• version (str)

• training (PhlowerTrainerSetting | None)

• model (PhlowerModelSetting | None)

• scaling (PhlowerScalingSetting | None)

• prediction (PhlowerPredictorSetting | None)

model: PhlowerModelSetting | None

model setting. Defaults to None.

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'frozen': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

prediction: PhlowerPredictorSetting | None

prediction setting. Defaults to None.

classmethod read_yaml(file_path, decrypt_key=None)

Read yaml file and parse to PhlowerSetting object.

Parameters:

• file_path (pathlib.Path | str | PhlowerYamlFile) – path to yaml file

• decrypt_key (bytes | None, optional) – key to decrypt file. Defaults to None.

Returns:

PhlowerSetting object

Return type:

Self

scaling: PhlowerScalingSetting | None

scaling setting. Defaults to None.

training: PhlowerTrainerSetting | None

training setting. Defaults to None.