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GET
/
api
/
dataframer
/
seed-datasets
/
{dataset_id}
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_dataset = client.dataframer.seed_datasets.retrieve(
    "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
)
print(seed_dataset.id)
{
  "id": "550e8400-e29b-41d4-a716-446655440000",
  "name": "Customer Reviews Dataset",
  "description": "Product reviews for sentiment analysis",
  "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]",
  "files": [
    {
      "id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
      "file_type": "csv",
      "size_bytes": 245678,
      "path": "reviews.csv"
    }
  ]
}

Documentation Index

Fetch the complete documentation index at: https://docs.dataframer.ai/llms.txt

Use this file to discover all available pages before exploring further.

Authorizations

​
Authorization
string
header
required

API Key authentication. Format: "Bearer YOUR_API_KEY"

Path Parameters

​
dataset_id
string<uuid>
required

UUID of the dataset

Response

Dataset details

​
id
string<uuid>
read-only

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>
read-only

Timestamp when the dataset was created

​
updated_at
string<date-time>
read-only

Timestamp when the dataset was last modified

​
created_by_email
string
read-only

Email address of the user who created the dataset

​
files
object[]
read-only

List of all files in the dataset

​
folder_count
integer
read-only

Total number of folders in the dataset

​
file_count
integer
read-only

Total number of files in the dataset

​
sample_count
integer | null
read-only

Number of data samples in the dataset. Only populated for SINGLE_FILE datasets (e.g. number of rows in a CSV).