bayesline.api.equity.FactorModelLoaderImpl

class bayesline.api.equity.FactorModelLoaderImpl(*, settings_registry: TypedSettingsRegistry[FactorRiskModelSettings, FactorRiskModelSettingsMenu], calendar_api: CalendarLoaderApi, universe_api: UniverseLoaderApi, exposure_api: ExposureLoaderApi, modelconstruction_api: FactorModelConstructionLoaderApi, report_loader: ReportLoaderApi, metadata_api: FactorModelMetadataApi) → None

__init__(*, settings_registry: TypedSettingsRegistry[FactorRiskModelSettings, FactorRiskModelSettingsMenu], calendar_api: CalendarLoaderApi, universe_api: UniverseLoaderApi, exposure_api: ExposureLoaderApi, modelconstruction_api: FactorModelConstructionLoaderApi, report_loader: ReportLoaderApi, metadata_api: FactorModelMetadataApi) → None

Methods

__init__(*, settings_registry, calendar_api, ...)
get_riskmodel_catalog()	List all risk models and risk datasets in one call.
list_riskmodels([risk_dataset, df])	List all risk models in the registry.
load(ref_or_settings, *args, **kwargs)	Load an API instance from settings or reference.
validate(settings)	Validate settings against the menu for its dataset.

Attributes

settings

Get the settings registry.

__init__(*, settings_registry: TypedSettingsRegistry[FactorRiskModelSettings, FactorRiskModelSettingsMenu], calendar_api: CalendarLoaderApi, universe_api: UniverseLoaderApi, exposure_api: ExposureLoaderApi, modelconstruction_api: FactorModelConstructionLoaderApi, report_loader: ReportLoaderApi, metadata_api: FactorModelMetadataApi) → None

property settings: TypedSettingsRegistry[FactorRiskModelSettings, FactorRiskModelSettingsMenu]

Get the settings registry.

Returns

TypedSettingsRegistry[T, M]

The settings registry instance.

list_riskmodels(risk_dataset: str | None = None, *, df: bool = False) → list[FactorRiskModelMetadata] | DataFrame

List all risk models in the registry.

Parameters

risk_datasetstr | None, default=None

The risk dataset to filter by. If not given, all risk models are returned.

dfbool, default=False

If True, return a polars DataFrame instead of a list of metadata objects.

Returns

list[FactorRiskModelMetadata] | pl.DataFrame

The metadata of all risk models in the registry, either as a list of objects or as a DataFrame depending on the df parameter.

get_riskmodel_catalog() → RiskModelCatalog

List all risk models and risk datasets in one call.

Equivalent to list_riskmodels() plus a risk-dataset listing, but computed against a single shared dataset-status snapshot so the two listings stay consistent and the server does the dataset-status work once.

Returns

RiskModelCatalog

The risk-model and risk-dataset metadata listings.