> ## Documentation Index
> Fetch the complete documentation index at: https://docs.honeyhive.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Export datasets via SDK

> How to programmatically export datasets in HoneyHive.

We allow exporting all datasets via our SDKs. This allows you to use your datasets for:

* **Evaluation:** Run ad-hoc experiments or continuous integrations tests against a reference dataset
* **Fine-Tuning:** Use datasets for fine-tuning and validating your custom model

**Prerequisites:**

* Get your API key & project ID [by following the steps detailed here](/sdk-reference/authentication).

**Expected time:** few minutes

<CodeGroup>
  ```python Python theme={null}
  import honeyhive

  s = honeyhive.HoneyHive(
      bearer_auth="HONEYHIVE_API_KEY",
      server_url="HONEYHIVE_SERVER_URL" # Optional / Required for self-hosted or dedicated deployments
  )

  datapoints = []
  res = s.datapoints.get_datapoints(project='PROJECT_NAME', dataset_name='DATASET_NAME')

  if res.object is not None:
      datapoints = res.object.datapoints
      pass

  ```

  ```typescript TypeScript theme={null}
  import { HoneyHive } from "honeyhive";

  async function run() {
    const sdk = new HoneyHive({
      bearerAuth: "HONEYHIVE_API_KEY",
      serverURL: "HONEYHIVE_SERVER_URL" // Optional / Required for self-hosted or dedicated deployments
    });
    const project: string = "PROJECT_NAME";
    const datasetName: string = "DATASET_NAME";

    let datapoints = [];
    const res = await sdk.datapoints.getDatapoints(project, datapointIds, datasetName);

    if (res.statusCode == 200) {
      // handle response
      datapoints = res.object.datapoints;
    }
  }

  run();
  ```
</CodeGroup>