DerivedDatasetInput#

class nominal.experimental.derived_datasets.DerivedDatasetInput(dataset_rid: str, filters: Sequence[TagFilter] = (), add_tag: tuple[str, str] | None = None, offset: timedelta | IntegralNanosecondsDuration = 0)#

Bases: object

One input dataset of a derived dataset, with the per-input transforms applied to it.

The transforms match those the app offers on a composition’s input, and apply in this order: the filters select series, add_tag labels what survives, and offset shifts the timestamps.

Use DerivedDatasetInput.create to build one from a Dataset rather than a RID.

dataset_rid: str#: RID of the input dataset.

filters: Sequence[TagFilter] = ()#: Clauses narrowing which series are included, ANDed together. Empty means the whole dataset.

add_tag: tuple[str, str] | None = None#: A tag key and value to attach to this input’s series, distinguishing them from the other inputs’.

offset: timedelta | int = 0#: Shift every timestamp on this input by this much; positive moves it later. Stored as nanoseconds.

classmethod create(dataset: Dataset | str, *, filters: Sequence[TagFilter] = (), add_tag: tuple[str, str] | None = None, offset: timedelta | int = 0) → Self#: An input naming dataset, with the given transforms applied to it.