bayesline.api.equity.AsyncUniverseImpl

class bayesline.api.equity.AsyncUniverseImpl(settings: DatasetAwareSettings[UniverseSettings], report_loader: AsyncReportLoaderApi) → None

__init__(settings: DatasetAwareSettings[UniverseSettings], report_loader: AsyncReportLoaderApi) → None

Methods

__init__(settings, report_loader)
counts([dates, ...])	Get universe counts with optional grouping and aggregation.
counts_as_task([dates, ...])
coverage([id_type])	Get the list of all asset IDs this universe covers.
coverage_as_task([id_type])
dates(*[, range_only, trade_only])	Get the list of all dates this universe covers.
get(*[, start, end, id_type, filter_tradedays])	Get universe data for a specific date range.
get_as_task(*[, start, end, id_type, ...])

Attributes

dataset	Get the dataset used to create this universe.
id_types	Get the supported ID types for this universe.
settings	Get the settings used to create this universe.

__init__(settings: DatasetAwareSettings[UniverseSettings], report_loader: AsyncReportLoaderApi) → None

property dataset: str

Get the dataset used to create this universe.

Returns

str

The dataset used to create this universe.

property settings: UniverseSettings

Get the settings used to create this universe.

Returns

UniverseSettings

The settings used to create this universe.

property id_types: list[str]

Get the supported ID types for this universe.

Returns

list[IdType]

Supported ID types for this universe.

async coverage(id_type: str | None = None) → list[str]

Get the list of all asset IDs this universe covers.

Parameters

id_typeIdType | None, default=None

The ID type to return asset IDs in, e.g. ticker.

Raises

ValueError

If the given ID type is not supported.

Returns

list[str]

List of all asset IDs this universe covers, in the given ID type.

async coverage_as_task(id_type: str | None = None) → AsyncTask[list[str]]

async dates(*, range_only: bool = False, trade_only: bool = False) → list[date]

Get the list of all dates this universe covers.

Parameters

range_onlybool, default=False

If True, returns the first and last date only.

trade_onlybool, default=False

If True, filter down the dates to trade dates only.

Returns

list[dt.date]

List of all dates this universe covers.

async counts(dates: bool = True, categorical_hierarchy_levels: dict[str, int] | None = None, labels: bool = True) → DataFrame

Get universe counts with optional grouping and aggregation.

Parameters

datesbool, default=True

If True, groups by dates.

categorical_hierarchy_levelsdict[str, int] | None, default=None

The level of categorical aggregation to group by. The key is the hierarchy name, the value is the level. If None, no categorical aggregation is done. A level of -1 means to use all levels.

labelsbool, default=True

If True, return labels for the counts, otherwise use the codes.

Returns

pl.DataFrame

Universe counts. If grouped by dates then the count will be given. If not grouped by dates then the mean/min/max across all dates will be given.

async counts_as_task(dates: bool = True, categorical_hierarchy_levels: dict[str, int] | None = None, labels: bool = True) → AsyncTask[DataFrame]

async get(*, start: str | date | datetime | None = None, end: str | date | datetime | None = None, id_type: str | None = None, filter_tradedays: bool = False) → DataFrame

Get universe data for a specific date range.

Parameters

startDateLike | None, default=None

The start date of the universe to return, inclusive.

endDateLike | None, default=None

The end date of the data to return, inclusive.

id_typeIdType | None, default=None

The ID type to return asset IDs in, e.g. ticker. The given ID type must be supported, i.e. in id_types.

filter_tradedaysbool, default=False

If True, filter down the data to trade dates only.

Raises

ValueError

If the given ID type is not supported or date range is invalid.

Returns

pl.DataFrame

The data for the given date range.

async get_as_task(*, start: str | date | datetime | None = None, end: str | date | datetime | None = None, id_type: str | None = None, filter_tradedays: bool = False) → AsyncTask[DataFrame]