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POST
/
api
/
dataframer
/
seed-datasets
/
create
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
)
response = client.dataframer.seed_datasets.create_with_files(
    dataset_type="SINGLE_FILE",
    files=[b"raw file contents", b"raw file contents"],
    name="name",
)
print(response.id)
{
  "id": "550e8400-e29b-41d4-a716-446655440000",
  "name": "Customer Reviews 2025",
  "description": "Product reviews with files",
  "dataset_type": "SINGLE_FILE",
  "file_count": 1,
  "folder_count": 0,
  "created_at": "2025-01-15T10:30:00Z",
  "updated_at": "2025-01-15T10:30:00Z",
  "created_by_email": "[email protected]",
  "short_sample_compatibility": {
    "is_short_samples_compatible": false,
    "is_long_samples_compatible": true,
    "reason": null
  }
}

Authorizations

​
Authorization
string
header
required

API Key authentication. Format: "Bearer YOUR_API_KEY"

Body

multipart/form-data
​
name
string
required

Dataset name (must be unique)

​
dataset_type
enum<string>
required
Available options:
SINGLE_FILE,
MULTI_FILE,
MULTI_FOLDER
​
files
file[]
required

Files to upload. SINGLE_FILE: exactly 1 file. MULTI_FILE: 2+ files. MULTI_FOLDER: 2+ files with corresponding folder_names.

Minimum array length: 2
​
description
string

Optional dataset description

​
folder_names
string[]

Folder names for MULTI_FOLDER datasets. This is a parallel array with files: folder_names[i] specifies which folder files[i] belongs to (e.g., if files=['a.txt', 'b.txt'] and folder_names=['doc1', 'doc2'], then a.txt goes in doc1, b.txt goes in doc2). Minimum 2 unique folder names required.

Minimum array length: 2

Response

Seed dataset created successfully

​
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

​
files
object[]

List of all files in 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