---
title: Create a dataset | Adaption
description: Upload a local file or import a dataset from Hugging Face or Kaggle with the Python SDK.
---

Import data from a local file, Hugging Face, or Kaggle without writing a conversion script. Each method returns a `dataset_id` that you pass to [`datasets.run`](/api/python/resources/datasets/methods/run/index.md).

The examples assume you have [installed the Python SDK and set `ADAPTION_API_KEY`](/introduction/getting-started/index.md):

```
from adaption import Adaption


client = Adaption()
```

1\. Upload a local file

Create the dataset, PUT the file bytes to the returned presigned URL, then confirm the upload.

Supported extensions: **`.csv`**, **`.json`**, **`.jsonl`**, **`.parquet`**, **`.pdf`**, **`.docx`**, **`.pptx`**, **`.xlsx`**, **`.html`**, **`.zip`**, and **`.txt`**.

```
import hashlib
from pathlib import Path


import httpx


path = Path("training_data.csv")
data = path.read_bytes()


dataset = client.datasets.create(
    source={
        "name": path.name,
        "file_format": "csv",
    },
)
response = httpx.put(dataset.upload_instructions.url, content=data)
response.raise_for_status()


client.datasets.upload.complete_by_id(
    dataset.dataset_id,
    file_size_bytes=len(data),
    sha256=hashlib.sha256(data).hexdigest(),
)
dataset_id = dataset.dataset_id
print(dataset_id)
```

2\. Import from Hugging Face

Point at a Hugging Face dataset URL and the file(s) to import.

```
dataset = client.datasets.create(
    source={
        "url": "https://huggingface.co/datasets/tatsu-lab/alpaca",
        "files": [
            "data/train-00000-of-00001-a09b74b3ef9c3b56.parquet"
        ],
    },
)
dataset_id = dataset.dataset_id
print(dataset_id)
```

3\. Import from Kaggle

Use the Kaggle dataset page URL and the files to pull.

```
dataset = client.datasets.create(
    source={
        "url": "https://www.kaggle.com/datasets/uciml/sms-spam-collection-dataset",
        "files": ["spam.csv"],
    },
)
dataset_id = dataset.dataset_id
print(dataset_id)
```

**Kaggle credentials** must be registered in Adaption: open **[API keys settings](https://adaptionlabs.ai/app/settings?tab=api_keys)** (sign in if prompted) and add your Kaggle API credentials there before importing.

Raw (passthrough) processing is currently supported only for local file uploads. Do not combine `processing_mode="raw"` with a Hugging Face or Kaggle URL. See [Run on non-adapted data](/autoscientist/run-on-non-adapted-data/index.md) for a local-file example.

## Wait for the import

Imports run asynchronously. Poll the [dataset status](/api/python/resources/datasets/methods/get_status/index.md) until ingestion has populated the dataset before starting an adaptation run:

```
import time


while True:
    status = client.datasets.get_status(dataset_id)
    if status.status == "failed":
        error = status.error_data
        message = (error and error.message) or "unknown error"
        raise RuntimeError(f"Dataset import failed: {message}")
    if status.row_count is not None:
        print(f"Imported {status.row_count} rows")
        break
    time.sleep(5)
```

Next, [map the imported columns](/adaptive-data/select-columns/index.md), then [configure the adaptation run](/adaptive-data/configure-adaptive-data/index.md). For endpoint details, see the [`create`](/api/python/resources/datasets/methods/create/index.md) and [`get_status`](/api/python/resources/datasets/methods/get_status/index.md) references. Local files must also be finalized with `datasets.upload.complete_by_id` after the presigned PUT.