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update_pipeline_execution async

update_pipeline_execution(
    *,
    config_overrides: Optional[AsyncSageMakerClientConfig] = None,
    pipeline_execution_arn: Optional[PipelineExecutionArn] = None,
    pipeline_execution_description: Optional[PipelineExecutionDescription] = None,
    pipeline_execution_display_name: Optional[PipelineExecutionName] = None,
    parallelism_configuration: Optional[ParallelismConfiguration] = None,
) -> UpdatePipelineExecutionResponse

Updates a pipeline execution.

Parameters:

Raises:

  • ConflictException –

    There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.

  • ResourceNotFound –

    Resource being access is not found.

  • UnknownServiceError –

    The service returned an error code this client does not model.

Source code in docs_src/capo_sagemaker/_services/async_sage_maker.py
async def update_pipeline_execution(
    self,
    *,
    config_overrides: Optional[AsyncSageMakerClientConfig] = None,
    pipeline_execution_arn: Optional[
        "capo_sagemaker.types.pipeline_execution_arn.PipelineExecutionArn"
    ] = None,
    pipeline_execution_description: Optional[
        "capo_sagemaker.types.pipeline_execution_description.PipelineExecutionDescription"
    ] = None,
    pipeline_execution_display_name: Optional[
        "capo_sagemaker.types.pipeline_execution_name.PipelineExecutionName"
    ] = None,
    parallelism_configuration: Optional[
        "capo_sagemaker.types.parallelism_configuration.ParallelismConfiguration"
    ] = None,
) -> "capo_sagemaker.types.update_pipeline_execution_response.UpdatePipelineExecutionResponse":
    """<p>Updates a pipeline execution.</p>

    Args:
        pipeline_execution_arn: <p>The Amazon Resource Name (ARN) of the pipeline execution.</p>
        pipeline_execution_description: <p>The description of the pipeline execution.</p>
        pipeline_execution_display_name: <p>The display name of the pipeline execution.</p>
        parallelism_configuration: <p>This configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.</p>

    Raises:
        capo_sagemaker.errors.conflict_exception.ConflictException: <p>There was a conflict when you attempted to modify a SageMaker entity such as an <code>Experiment</code> or <code>Artifact</code>.</p>
        capo_sagemaker.errors.resource_not_found.ResourceNotFound: <p>Resource being access is not found.</p>
        capo_sagemaker.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_sagemaker.types.update_pipeline_execution_request.UpdatePipelineExecutionRequest]",
    ) -> AsyncOperationResponse[
        "capo_sagemaker.types.update_pipeline_execution_response.UpdatePipelineExecutionResponse"
    ]:
        import capo_sagemaker._operations.sage_maker.update_pipeline_execution

        (
            output,
            http_response,
        ) = await capo_sagemaker._operations.sage_maker.update_pipeline_execution.async_update_pipeline_execution(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("UpdatePipelineExecution")
    )
    input_: capo_sagemaker.types.update_pipeline_execution_request.UpdatePipelineExecutionRequest = {}
    if pipeline_execution_arn is not None:
        input_["pipeline_execution_arn"] = pipeline_execution_arn
    if pipeline_execution_description is not None:
        input_["pipeline_execution_description"] = pipeline_execution_description
    if pipeline_execution_display_name is not None:
        input_["pipeline_execution_display_name"] = pipeline_execution_display_name
    if parallelism_configuration is not None:
        input_["parallelism_configuration"] = parallelism_configuration

    response = await aexecute_pipeline(
        AsyncOperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    await response.response.aclose()
    return response.output