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API Reference
Datasets

List datasets

datasets.list(DatasetListParams**kwargs) -> DatasetListResponse
GET/api/v1/datasets

List datasets

ParametersExpand Collapse
created_after: Optional[str]

ISO 8601 datetime — datasets created after this time.

created_before: Optional[str]

ISO 8601 datetime — datasets created before this time.

cursor: Optional[str]

Cursor from the previous response next_cursor field.

limit: Optional[float]

Number of results (max 100, default 20). Used with cursor pagination.

q: Optional[str]

Search by dataset name (case-insensitive contains).

sort: Optional[str]

Sort field: created_at | updated_at | name (default: created_at).

sort_direction: Optional[str]

Sort direction: asc | desc (default: desc).

status: Optional[str]

Filter by status: pending | running | succeeded | failed

ReturnsExpand Collapse
class DatasetListResponse: …
datasets: List[Dataset]

Page of datasets

created_at: datetime

Timestamp when the dataset was created

formatdate-time
dataset_id: str

Dataset ID

status: Literal["pending", "running", "succeeded", "failed"]

Dataset status

One of the following:
"pending"
"running"
"succeeded"
"failed"
updated_at: datetime

Last updated timestamp

formatdate-time
description: Optional[str]

Auto-generated description of the dataset contents

name: Optional[str]

Dataset name

row_count: Optional[int]

Total number of rows

next_cursor: Optional[str]

Cursor for the next page. Null when no more results.

List datasets

import os
from adaption import Adaption

client = Adaption(
    api_key=os.environ.get("ADAPTION_API_KEY"),  # This is the default and can be omitted
)
datasets = client.datasets.list()
print(datasets.datasets)
{
  "datasets": [
    {
      "created_at": "2019-12-27T18:11:19.117Z",
      "dataset_id": "550e8400-e29b-41d4-a716-446655440000",
      "status": "pending",
      "updated_at": "2019-12-27T18:11:19.117Z",
      "description": "description",
      "name": "My training data",
      "row_count": 1000
    }
  ],
  "next_cursor": "550e8400-e29b-41d4-a716-446655440000"
}
Returns Examples
{
  "datasets": [
    {
      "created_at": "2019-12-27T18:11:19.117Z",
      "dataset_id": "550e8400-e29b-41d4-a716-446655440000",
      "status": "pending",
      "updated_at": "2019-12-27T18:11:19.117Z",
      "description": "description",
      "name": "My training data",
      "row_count": 1000
    }
  ],
  "next_cursor": "550e8400-e29b-41d4-a716-446655440000"
}