get_workflow_run ¶

def get_workflow_run(
    self,
    name: "capo_glue.types.name_string.NameString",
    run_id: "capo_glue.types.id_string.IdString",
    *,
    config_overrides: Optional[GlueClientConfig] = None,
    include_graph: Optional[
        "capo_glue.types.nullable_boolean.NullableBoolean"
    ] = None,
) -> "capo_glue.types.get_workflow_run_response.GetWorkflowRunResponse":
    """<p>Retrieves the metadata for a given workflow run. Job run history is accessible for 90 days for your workflow and job run.</p>

    Args:
        name: <p>Name of the workflow being run.</p>
        run_id: <p>The ID of the workflow run.</p>
        include_graph: <p>Specifies whether to include the workflow graph in response or not.</p>

    Raises:
        capo_glue.errors.entity_not_found_exception.EntityNotFoundException: <p>A specified entity does not exist</p>
        capo_glue.errors.internal_service_exception.InternalServiceException: <p>An internal service error occurred.</p>
        capo_glue.errors.invalid_input_exception.InvalidInputException: <p>The input provided was not valid.</p>
        capo_glue.errors.operation_timeout_exception.OperationTimeoutException: <p>The operation timed out.</p>
        capo_glue.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_glue.types.get_workflow_run_request.GetWorkflowRunRequest]",
    ) -> OperationResponse[
        "capo_glue.types.get_workflow_run_response.GetWorkflowRunResponse"
    ]:
        import capo_glue._operations.aws_glue.get_workflow_run

        output, http_response = (
            capo_glue._operations.aws_glue.get_workflow_run.get_workflow_run(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("GetWorkflowRun")
    )
    input_: capo_glue.types.get_workflow_run_request.GetWorkflowRunRequest = {
        "name": name,
        "run_id": run_id,
    }
    if include_graph is not None:
        input_["include_graph"] = include_graph

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