DataContext

DataContext.fetch(...), fetch_many(...), and prefetch(...) are the canonical public data-loading entry points for new code.

For the shortest happy path, build contexts with DataContext.from_adapters(...) and load a table with DataContext.load(...).

If multiple adapters serve the same dataset, canonical loads must disambiguate through default_sources or an explicit source= override. Alphaforge no longer falls back to an arbitrary first-registered adapter for shared datasets.

DataContext.sources and fetch_panel(...) remain available as backward-compatibility surfaces for legacy DataSource-backed loaders, but they are no longer the preferred external loading contract.

alphaforge.data.context

DataContext dataclass

Runtime wiring for data sources, calendars, and optional PIT access.

Parameters

sources : Mapping[str, DataSource] Legacy data source mapping kept for backward compatibility and raw-loader workflows. calendars : Mapping[str, TradingCalendar] Trading calendar lookup. store : Store Backing store for persistence. adapters : dict[str, SourceAdapter] | None Canonical public data-loading surface keyed by source_name (e.g. "cftc"). default_sources : dict[str, str] | None Maps dataset → default source_name for canonical adapter routing (e.g. {"cot.tff": "cftc"}).

fetch(query: Query, *, source: Optional[str] = None, max_staleness: Optional[timedelta] = None) -> 'FetchResult'

Canonical fetch path: resolve an adapter and delegate.

fetch_many(queries: list[Query], *, source: Optional[str] = None, max_staleness: Optional[timedelta] = None) -> list['FetchResult']

Canonical batch fetch path, grouped by resolved adapter.

fetch_panel(source: str, q: Query) -> PanelFrame

Legacy panel-building path for DataSource-backed loaders.

from_adapters(*adapters: 'SourceAdapter', calendars: Mapping[str, TradingCalendar] | None = None, store: Store | None = None, universe: Optional[Universe] = None, entity_meta: Optional[EntityMetadata] = None, default_sources: Optional[dict[str, str]] = None) -> 'DataContext' classmethod

Build a DataContext from adapters without manual mapping boilerplate.

load(dataset: str, *, columns: Sequence[str], start: Optional[pd.Timestamp | str] = None, end: Optional[pd.Timestamp | str] = None, entities: Optional[Sequence[str]] = None, asof: Optional[pd.Timestamp | str] = None, vintage: VintageMode = 'latest', vintage_id: Optional[str] = None, grid: Optional[str] = None, source: Optional[str] = None, max_staleness: Optional[timedelta] = None) -> 'FetchResult'

Happy-path source load without explicit Query construction.

prefetch(dataset: str, *, source: Optional[str] = None, asof_range: tuple[date, date] | None = None) -> 'CacheManifest'

Warm cache for a dataset via the resolved adapter.