Documentation | Datasets

Datasets

DatasetsResource

Methods

client.datasets.create() ->

post/v5/datasets

Create a dataset and populate it with its initial items in a single call.

Use this when the dataset does not exist yet: it creates the dataset and seeds it with the items you provide. To add more items to a dataset that already exists, use POST /v5/dataset-items/batch instead. A name is required, and the request must include at least one item in data; the optional files field associates files with the created items. The provided items are inserted as dataset items as a side effect of creation, and any tags are attached to the dataset. The returned dataset is at version 1.

client.datasets.list() -> SyncCursorPage[

Dataset

]

get/v5/datasets

Return a paginated list of the account's datasets.

Archived datasets are excluded unless include_archived is set to true. Results can be narrowed by tags and by the standard filterable parameters; a name filter matches as a case-insensitive substring rather than an exact match.

client.datasets.archive() ->

DatasetArchiveResponse

delete/v5/datasets/{dataset_id}

Soft-delete a dataset by archiving it; the row is retained and can be restored later.

This sets the dataset's archived_at timestamp rather than permanently removing it, and cascades the same archival to the dataset's items and versions. Archiving is not idempotent: if the dataset is already archived the call fails. The dataset can be brought back with the PATCH restore request. The response reports the dataset id with deleted set to true.

client.datasets.update(, ) ->

Dataset

patch/v5/datasets/{dataset_id}

Update a dataset's fields, or restore a previously archived dataset.

The request body is a union discriminated by its contents: a body of {"restore": true} triggers a restore, and any other body is treated as a partial update of the dataset's name, description, and tags. Restore clears archived_at on the dataset and cascades the un-archival to its items and versions; restoring a dataset that is not archived returns it unchanged. A partial update on an archived dataset fails, since archived datasets cannot be modified.

Parameters

dataset_id: str

dataset:

Dataset

class DatasetPartialDatasetRequestBase: ...

RestoreRequestParam

Returns

Dataset

id: str

The unique identifier of the entity.

created_at:

datetime

(format: date-time)

The date and time when the entity was created in ISO format.

created_by:

Identity

The identity that created the entity.

current_version_num: int

name: str

tags: List[str]

The tags associated with the entity

archived_at: Optional[datetime]

(format: date-time)

The date and time when the entity was archived in ISO format.

description: Optional[str]

object: Optional[Literal["dataset"]]

(default: "dataset")

Request example

import os
from scale_gp_beta import SGPClient

client = SGPClient(
    api_key=os.environ.get("SGP_API_KEY"),  # This is the default and can be omitted
)
dataset = client.datasets.update(
    dataset_id="dataset_id",
    dataset={},
)
print(dataset.id)

200Example

{
  "id": "id",
  "created_at": "2019-12-27T18:11:19.117Z",
  "created_by": {
    "id": "id",
    "type": "user",
    "object": "identity"
  },
  "current_version_num": 0,
  "name": "name",
  "tags": [
    "string"
  ],
  "archived_at": "2019-12-27T18:11:19.117Z",
  "description": "description",
  "object": "dataset"
}

client.datasets.retrieve(, ) ->

Dataset

get/v5/datasets/{dataset_id}

Retrieve a single dataset by its id.

By default an archived dataset is not returned; set include_archived to true to fetch a dataset regardless of whether it has been archived.

Domain types

class Dataset: ...

class DatasetArchiveResponse: ...