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GET
/
api
/
dataframer
/
seed-datasets
Python
import os
from dataframer import Dataframer

client = Dataframer(
    api_key=os.environ.get("DATAFRAMER_API_KEY"),  # This is the default and can be omitted
)
seed_datasets = client.dataframer.seed_datasets.list()
print(seed_datasets)
[
  {
    "id": "550e8400-e29b-41d4-a716-446655440000",
    "name": "Customer Reviews Dataset",
    "description": "Product reviews for analysis",
    "dataset_type": "SINGLE_FILE",
    "created_at": "2025-01-15T10:30:00Z",
    "updated_at": "2025-01-15T10:30:00Z",
    "created_by_email": "[email protected]",
    "folder_count": 0,
    "file_count": 1,
    "short_sample_compatibility": {
      "is_short_samples_compatible": true,
      "is_long_samples_compatible": false,
      "reason": null
    }
  }
]

Authorizations

​
Authorization
string
header
required

API Key authentication. Format: "Bearer YOUR_API_KEY"

Response

List of datasets

​
id
string<uuid>

Unique identifier for the dataset

​
name
string

Dataset name

​
description
string | null

Optional description of the dataset contents or purpose

​
dataset_type
enum<string>

Type of dataset structure. SINGLE_FILE: one CSV/JSON/JSONL file with tabular data. MULTI_FILE: multiple individual text files. MULTI_FOLDER: files organized into folders where each folder represents one sample.

Available options:
SINGLE_FILE,
MULTI_FILE,
MULTI_FOLDER
​
created_at
string<date-time>

Timestamp when the dataset was created

​
updated_at
string<date-time>

Timestamp when the dataset was last modified

​
created_by_email
string

Email address of the user who created the dataset

​
folder_count
integer

Total number of folders in the dataset

​
file_count
integer

Total number of files in the dataset

​
short_sample_compatibility
object

Information about which generation modes are compatible with this dataset