delete_data_lake_dataset ¶

def delete_data_lake_dataset(
    self,
    instance_id: "capo_supplychain.types.uuid.UUID",
    namespace: "capo_supplychain.types.data_lake_namespace_name.DataLakeNamespaceName",
    name: "capo_supplychain.types.data_lake_dataset_name.DataLakeDatasetName",
    *,
    config_overrides: Optional[SupplyChainClientConfig] = None,
) -> "capo_supplychain.types.delete_data_lake_dataset_response.DeleteDataLakeDatasetResponse":
    """<p>Enables you to programmatically delete an Amazon Web Services Supply Chain data lake dataset. Developers can delete the existing datasets for a given instance ID, namespace, and instance name.</p>

    Args:
        instance_id: <p>The AWS Supply Chain instance identifier.</p>
        namespace: <p>The namespace of the dataset, besides the custom defined namespace, every instance comes with below pre-defined namespaces:</p> <ul> <li> <p> <b>asc</b> - For information on the Amazon Web Services Supply Chain supported datasets see <a href="https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html">https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html</a>.</p> </li> <li> <p> <b>default</b> - For datasets with custom user-defined schemas.</p> </li> </ul>
        name: <p>The name of the dataset. For <b>asc</b> namespace, the name must be one of the supported data entities under <a href="https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html">https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html</a>.</p>

    Raises:
        capo_supplychain.errors.access_denied_exception.AccessDeniedException: <p>You do not have the required privileges to perform this action.</p>
        capo_supplychain.errors.conflict_exception.ConflictException: <p>Updating or deleting a resource can cause an inconsistent state.</p>
        capo_supplychain.errors.internal_server_exception.InternalServerException: <p>Unexpected error during processing of request.</p>
        capo_supplychain.errors.resource_not_found_exception.ResourceNotFoundException: <p>Request references a resource which does not exist.</p>
        capo_supplychain.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>Request would cause a service quota to be exceeded.</p>
        capo_supplychain.errors.throttling_exception.ThrottlingException: <p>Request was denied due to request throttling.</p>
        capo_supplychain.errors.validation_exception.ValidationException: <p>The input does not satisfy the constraints specified by an AWS service.</p>
        capo_supplychain.errors.UnknownServiceError: The service returned an error code this client does not model.

    Examples:
        Delete an AWS Supply Chain inbound_order dataset

        >>> client.delete_data_lake_dataset(instance_id='1877dd20-dee9-4639-8e99-cb67acf21fe5', namespace='asc', name='inbound_order')
        Delete a custom dataset

        >>> client.delete_data_lake_dataset(instance_id='1877dd20-dee9-4639-8e99-cb67acf21fe5', namespace='default', name='my_dataset')
    """

    def _handler(
        req: "OperationRequest[capo_supplychain.types.delete_data_lake_dataset_request.DeleteDataLakeDatasetRequest]",
    ) -> OperationResponse[
        "capo_supplychain.types.delete_data_lake_dataset_response.DeleteDataLakeDatasetResponse"
    ]:
        import capo_supplychain._operations.galaxy_public_api_gateway.delete_data_lake_dataset

        output, http_response = (
            capo_supplychain._operations.galaxy_public_api_gateway.delete_data_lake_dataset.delete_data_lake_dataset(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("DeleteDataLakeDataset")
    )
    input_: capo_supplychain.types.delete_data_lake_dataset_request.DeleteDataLakeDatasetRequest = {
        "instance_id": instance_id,
        "namespace": namespace,
        "name": name,
    }

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output