create_derived_dataset

nominal.experimental.derived_datasets.create_derived_dataset(client: NominalClient, name: str, *, inputs: Sequence[DerivedDatasetInput] = (), description: str | None = None, labels: Sequence[str] = (), properties: Mapping[str, str | float] | None = None, markings: Sequence[Marking | str] | None = None, message: str = 'Initial derived definition') → DerivedDataset

Create a derived dataset: a virtual dataset whose contents are the union of its input datasets.

Parameters:

• client – The NominalClient to use for creating the derived dataset.

• name – Name of the derived dataset to create in Nominal.

• inputs – The datasets this one is composed of, each with its own transforms. May be empty, and populated later with DerivedDataset.add_input_dataset.

• description – Human readable description of the dataset.

• labels – Text labels to apply to the created dataset.

• properties – String or numeric properties for the created derived dataset. Integers are stored as floats.

• markings – If present, markings (or marking RIDs) applied to the dataset. Sent as part of the creation request rather than applied in a follow-up call.

• message – Commit message for the initial definition.

Returns:

Reference to the created derived dataset in Nominal.

Raises:

TypeError – If a property value is a boolean or is not a string, integer, or float.