dataset

superduper.components.dataset

`Dataset`

Dataset(self,
     identifier: str,
     db: dataclasses.InitVar[typing.Optional[ForwardRef('Datalayer')]] = None,
     uuid: None = None,
     *,
     upstream: "t.Optional[t.List['Component']]" = None,
     artifacts: 'dc.InitVar[t.Optional[t.Dict]]' = None,
     select: 't.Optional[Query]' = None,
     sample_size: 't.Optional[int]' = None,
     random_seed: 't.Optional[int]' = None,
     creation_date: 't.Optional[str]' = None,
     raw_data: 't.Optional[t.Sequence[t.Any]]' = None,
     pin: 'bool' = False) -> None

Parameter	Description
identifier	Identifier of the leaf.
db	Datalayer instance.
uuid	UUID of the leaf.
artifacts	A dictionary of artifacts paths and `DataType` objects
select	A query to select the documents for the dataset.
sample_size	The number of documents to sample from the query.
random_seed	The random seed to use for sampling.
creation_date	The date the dataset was created.
raw_data	The raw data for the dataset.
pin	Whether to pin the dataset. If True, the dataset will load the datas from the database every time. If False, the dataset will cache the datas after we apply to db.

A dataset is an immutable collection of documents.

`DataInit`

DataInit(self,
     identifier: str,
     db: dataclasses.InitVar[typing.Optional[ForwardRef('Datalayer')]] = None,
     uuid: None = None,
     *,
     upstream: "t.Optional[t.List['Component']]" = None,
     artifacts: 'dc.InitVar[t.Optional[t.Dict]]' = None,
     data: 't.List[t.Dict]',
     table: 'str') -> None

Parameter	Description
identifier	Identifier of the leaf.
db	Datalayer instance.
uuid	UUID of the leaf.
artifacts	A dictionary of artifacts paths and `DataType` objects

DataInit(identifier: str, db: dataclasses.InitVar[typing.Optional[ForwardRef('Datalayer')]] = None, uuid: None = None, *, upstream: "t.Optional[t.List['Component']]" = None, artifacts: 'dc.InitVar[t.Optional[t.Dict]]' = None, data: 't.List[t.Dict]', table: 'str')

Dataset​

DataInit​

`Dataset`

`DataInit`