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list_dataset_import_jobs

list_dataset_import_jobs(
    *,
    config_overrides: Optional[PersonalizeClientConfig] = None,
    dataset_arn: Optional[Arn] = None,
    next_token: Optional[NextToken] = None,
    max_results: Optional[MaxResults] = None,
) -> ListDatasetImportJobsResponse

Returns a list of dataset import jobs that use the given dataset. When a dataset is not specified, all the dataset import jobs associated with the account are listed. The response provides the properties for each dataset import job, including the Amazon Resource Name (ARN). For more information on dataset import jobs, see CreateDatasetImportJob. For more information on datasets, see CreateDataset.

Parameters:

  • dataset_arn (Optional[Arn], default: None ) –

    The Amazon Resource Name (ARN) of the dataset to list the dataset import jobs for.

  • next_token (Optional[NextToken], default: None ) –

    A token returned from the previous call to ListDatasetImportJobs for getting the next set of dataset import jobs (if they exist).

  • max_results (Optional[MaxResults], default: None ) –

    The maximum number of dataset import jobs to return.

Raises:

Source code in docs_src/capo_personalize/_services/personalize.py
def list_dataset_import_jobs(
    self,
    *,
    config_overrides: Optional[PersonalizeClientConfig] = None,
    dataset_arn: Optional["capo_personalize.types.arn.Arn"] = None,
    next_token: Optional["capo_personalize.types.next_token.NextToken"] = None,
    max_results: Optional["capo_personalize.types.max_results.MaxResults"] = None,
) -> "capo_personalize.types.list_dataset_import_jobs_response.ListDatasetImportJobsResponse":
    """<p>Returns a list of dataset import jobs that use the given dataset. When a dataset is not specified, all the dataset import jobs associated with the account are listed. The response provides the properties for each dataset import job, including the Amazon Resource Name (ARN). For more information on dataset import jobs, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_CreateDatasetImportJob.html">CreateDatasetImportJob</a>. For more information on datasets, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_CreateDataset.html">CreateDataset</a>.</p>

    Args:
        dataset_arn: <p>The Amazon Resource Name (ARN) of the dataset to list the dataset import jobs for.</p>
        next_token: <p>A token returned from the previous call to <code>ListDatasetImportJobs</code> for getting the next set of dataset import jobs (if they exist).</p>
        max_results: <p>The maximum number of dataset import jobs to return.</p>

    Raises:
        capo_personalize.errors.invalid_input_exception.InvalidInputException: <p>Provide a valid value for the field or parameter.</p>
        capo_personalize.errors.invalid_next_token_exception.InvalidNextTokenException: <p>The token is not valid.</p>
        capo_personalize.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_personalize.types.list_dataset_import_jobs_request.ListDatasetImportJobsRequest]",
    ) -> OperationResponse[
        "capo_personalize.types.list_dataset_import_jobs_response.ListDatasetImportJobsResponse"
    ]:
        import capo_personalize._operations.amazon_personalize.list_dataset_import_jobs

        output, http_response = (
            capo_personalize._operations.amazon_personalize.list_dataset_import_jobs.list_dataset_import_jobs(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ListDatasetImportJobs")
    )
    input_: capo_personalize.types.list_dataset_import_jobs_request.ListDatasetImportJobsRequest = {}
    if dataset_arn is not None:
        input_["dataset_arn"] = dataset_arn
    if next_token is not None:
        input_["next_token"] = next_token
    if max_results is not None:
        input_["max_results"] = max_results

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