bayesline.api.equity.PortfolioApi

class bayesline.api.equity.PortfolioApi

Bases: ABC

Methods

__init__()
get_coverage([names, by, metric, stats])	Parameters names: str | list[str], optional The names of the portfolios. If not given all portfolios will be calculated. by: str, optional The coverage aggregation, either by date or by asset. metric: str, optional The metric to calculate, either count of observations or sum of holding values. stats: list[str], optional list of 'min', 'max', 'mean', collapses by into these stats.
get_dates([names, collapse])
get_id_types()	Returns dict[str, list[IdType]]: The available ID types that at least a portion of assets can be mapped to for each portfolio.
get_portfolio(names[, start_date, end_date, ...])	Obtains the portfolios for the given names between given start and end dates.
get_portfolio_groups()
get_portfolio_names()

Attributes

name

abstract property name: str

abstract get_id_types() → dict[str, list[Literal['bayesid', 'ticker', 'composite_figi', 'cik', 'cusip8', 'cusip9', 'isin', 'sedol6', 'sedol7', 'proxy', 'name']]]

Returns

dict[str, list[IdType]]:

The available ID types that at least a portion of assets can be mapped to for each portfolio.

abstract get_coverage(names: str | list[str] | None = None, *, by: Literal['date', 'asset'] = 'date', metric: Literal['count', 'holding'] = 'count', stats: list[str] | None = None) → DataFrame

Parameters

names: str | list[str], optional

The names of the portfolios. If not given all portfolios will be calculated.

by: str, optional

The coverage aggregation, either by date or by asset.

metric: str, optional

The metric to calculate, either count of observations or sum of holding values.

stats: list[str], optional

list of ‘min’, ‘max’, ‘mean’, collapses by into these stats.

Returns

pl.DataFrame:

The dated coverage count for each id type. portfolio_group and portfolio are the first two columns. If stats given, collapses the by index to the given aggregations.

abstract get_portfolio_names() → list[str]

abstract get_portfolio_groups() → dict[str, list[str]]

abstract get_dates(names: list[str] | str | None = None, *, collapse: bool = False) → dict[str, list[date]]

abstract get_portfolio(names: list[str] | str, start_date: str | date | datetime | None = None, end_date: str | date | datetime | None = None, id_type: Literal['bayesid', 'ticker', 'composite_figi', 'cik', 'cusip8', 'cusip9', 'isin', 'sedol6', 'sedol7', 'proxy', 'name'] | None = None) → DataFrame

Obtains the portfolios for the given names between given start and end dates.

Parameters

names: list[str] | str

The list of portfolio names.

start_date: DateLike, optional

The start date of the data to return, inclusive.

end_date: DateLike, optional

The end date of the data to return, inclusive.

id_type: IdType, optional

id type to return the portfolio holdings in.

Returns

pl.DataFrame:

A dataframe with columns portfolio_group, portfolio, date, input_asset_id, input_asset_id_type, asset_id, asset_id_type and value.

If no id_type is given then the input ID space will be used unmapped. In this case the columns asset_id, asset_id_type will not be returned.