Deleting a dataset

Create a service account and assign it the ai.editor role.

Get and save the service account's API key with yc.ai.foundationModels.execute as the specified scope.

The following examples use API key authentication. Yandex Cloud ML SDK also supports IAM token and OAuth token authentication. For more information, see Authentication in Yandex Cloud ML SDK.

Use the pip package manager to install the ML SDK library:

pip install yandex-cloud-ml-sdk

Get API authentication credentials as described in Authentication with the Yandex AI Studio API.

To use the examples, install cURL.

Install gRPCurl.

(Optional) Install the jq JSON stream processor.

Get an IAM token used for authentication in the API.

The account for which you want to obtain the IAM token must have the ai.editor role or higher.

Create a file named dataset-delete.py and paste the following code into it:

from __future__ import annotations

from yandex_cloud_ml_sdk import YCloudML

YANDEX_API_KEY = "<API_key>"
YANDEX_FOLDER_ID = "<folder_ID>"
DATASET_ID = "<dataset_ID>"


def main() -> None:

    sdk = YCloudML(
        folder_id=YANDEX_FOLDER_ID,
        auth=YANDEX_API_KEY,
    )

    # Saving the object with the dataset to delete into a variable
    dataset_to_delete = sdk.datasets.get(dataset_id=DATASET_ID)

    # Deleting a dataset
    dataset_to_delete.delete()


if __name__ == "__main__":
    main()

Where:

• YANDEX_API_KEY: Service account API key you got before you started.

• YANDEX_FOLDER_ID: ID of the folder containing the dataset you are deleting.

• DATASET_ID: ID of the dataset to delete. You can view the list of all datasets in the folder using the management console or the API.

  In ML SDK, you can view the list of datasets in the folder using the list() method.

  for dataset in sdk.datasets.list():
      print(f"List of existing datasets {dataset=}")
  

Run the file you created:

python3 dataset-delete.py

This will delete the specified dataset.

Get the ID of the dataset you want to delete:

grpcurl \
  -H "Authorization: Bearer <IAM_token>" \
  -d @ \
  llm.api.cloud.yandex.net:443 yandex.cloud.ai.dataset.v1.DatasetService/List <<EOM
  {
    "folder_id": "<folder_ID>"
  }
EOM

Where:

• <IAM_token>: IAM token of the service account you got before you started.
• <folder_ID>: ID of the folder you are creating the dataset in.

Result:

 {
   "datasets": [
     {
       "datasetId": "fdsl9hf65509********",
       "folderId": "b1gt6g8ht345********",
       "name": "sample-dataset",
       "status": "READY",
       "taskType": "TextToTextGeneration",
       "createdAt": "2025-11-28T08:53:59Z",
       "updatedAt": "2025-11-28T08:54:38Z",
       "rows": "354",
       "sizeBytes": "32314",
       "createdById": "ajeol2afu1js********",
       "createdBy": "ajeol2afu1js********"
     }
   ]
 }

Save the ID of the dataset you want to delete (the datasetId field value): you will need it to delete the dataset.

Delete the dataset:

grpcurl \
  -H "Authorization: Bearer <IAM_token>" \
  -d @ \
  llm.api.cloud.yandex.net:443 yandex.cloud.ai.dataset.v1.DatasetService/Delete <<EOM
  {
    "dataset_id": "<dataset_ID>"
  }
EOM

Where:

• <IAM_token>: IAM token of the service account you got before you started.
• <dataset_ID>: Dataset ID you saved in the previous step.

The gRPC call will delete the specified dataset.