cancel_ml_task_run ¶

def cancel_ml_task_run(
    self,
    transform_id: "capo_glue.types.hash_string.HashString",
    task_run_id: "capo_glue.types.hash_string.HashString",
    *,
    config_overrides: Optional[GlueClientConfig] = None,
) -> "capo_glue.types.cancel_ml_task_run_response.CancelMLTaskRunResponse":
    """<p>Cancels (stops) a task run. Machine learning task runs are asynchronous tasks that Glue runs on your behalf as part of various machine learning workflows. You can cancel a machine learning task run at any time by calling <code>CancelMLTaskRun</code> with a task run's parent transform's <code>TransformID</code> and the task run's <code>TaskRunId</code>. </p>

    Args:
        transform_id: <p>The unique identifier of the machine learning transform.</p>
        task_run_id: <p>A unique identifier for the task run.</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.cancel_ml_task_run_request.CancelMLTaskRunRequest]",
    ) -> OperationResponse[
        "capo_glue.types.cancel_ml_task_run_response.CancelMLTaskRunResponse"
    ]:
        import capo_glue._operations.aws_glue.cancel_ml_task_run

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("CancelMLTaskRun")
    )
    input_: capo_glue.types.cancel_ml_task_run_request.CancelMLTaskRunRequest = {
        "transform_id": transform_id,
        "task_run_id": task_run_id,
    }

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