list_data_sets ¶

def list_data_sets(
    self,
    application_id: "capo_m2.types.identifier.Identifier",
    *,
    config_overrides: Optional[m2ClientConfig] = None,
    next_token: Optional["capo_m2.types.next_token.NextToken"] = None,
    max_results: Optional["capo_m2.types.max_results.MaxResults"] = None,
    prefix: Optional["capo_m2.types.string200.String200"] = None,
    name_filter: Optional["capo_m2.types.string200.String200"] = None,
) -> "capo_m2.types.list_data_sets_response.ListDataSetsResponse":
    """<p>Lists the data sets imported for a specific application. In Amazon Web Services Mainframe Modernization, data sets are associated with applications deployed on runtime environments. This is known as importing data sets. Currently, Amazon Web Services Mainframe Modernization can import data sets into catalogs using <a href="https://docs.aws.amazon.com/m2/latest/APIReference/API_CreateDataSetImportTask.html">CreateDataSetImportTask</a>.</p>

    Args:
        application_id: <p>The unique identifier of the application for which you want to list the associated data sets.</p>
        next_token: <p>A pagination token returned from a previous call to this operation. This specifies the next item to return. To return to the beginning of the list, exclude this parameter.</p>
        max_results: <p>The maximum number of objects to return.</p>
        prefix: <p>The prefix of the data set name, which you can use to filter the list of data sets.</p>
        name_filter: <p>Filter dataset name matching the specified pattern. Can use * and % as wild cards.</p>

    Raises:
        capo_m2.errors.access_denied_exception.AccessDeniedException: <p>The account or role doesn't have the right permissions to make the request.</p>
        capo_m2.errors.conflict_exception.ConflictException: <p>The parameters provided in the request conflict with existing resources.</p>
        capo_m2.errors.execution_timeout_exception.ExecutionTimeoutException: <p> Failed to connect to server, or didn’t receive response within expected time period.</p>
        capo_m2.errors.internal_server_exception.InternalServerException: <p>An unexpected error occurred during the processing of the request.</p>
        capo_m2.errors.resource_not_found_exception.ResourceNotFoundException: <p>The specified resource was not found.</p>
        capo_m2.errors.service_unavailable_exception.ServiceUnavailableException: <p>Server cannot process the request at the moment.</p>
        capo_m2.errors.throttling_exception.ThrottlingException: <p>The number of requests made exceeds the limit.</p>
        capo_m2.errors.validation_exception.ValidationException: <p>One or more parameters provided in the request is not valid.</p>
        capo_m2.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_m2.types.list_data_sets_request.ListDataSetsRequest]",
    ) -> OperationResponse[
        "capo_m2.types.list_data_sets_response.ListDataSetsResponse"
    ]:
        import capo_m2._operations.aws_supernova_control_plane_service.list_data_sets

        output, http_response = (
            capo_m2._operations.aws_supernova_control_plane_service.list_data_sets.list_data_sets(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ListDataSets")
    )
    input_: capo_m2.types.list_data_sets_request.ListDataSetsRequest = {
        "application_id": application_id
    }
    if next_token is not None:
        input_["next_token"] = next_token
    if max_results is not None:
        input_["max_results"] = max_results
    if prefix is not None:
        input_["prefix"] = prefix
    if name_filter is not None:
        input_["name_filter"] = name_filter

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