create_derived_dataset#

nominal.experimental.derived_datasets.create_derived_dataset(client, name, *, inputs=(), description=None, labels=(), properties=None, markings=None, message='Initial derived definition')#

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

Parameters:

  • client (NominalClient)

    The NominalClient to use for creating the derived dataset.

  • name (str)

    Name of the derived dataset to create in Nominal.

  • inputs (Sequence[DerivedDatasetInput])

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

  • description (str | None)

    Human readable description of the dataset.

  • labels (Sequence[str])

    Text labels to apply to the created dataset.

  • properties (Mapping[str, str | float] | None)

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

  • markings (Sequence[Marking | str] | None)

    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 (str)

    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.

Return type:

DerivedDataset