send_pipeline_execution_step_success `async` ¶

send_pipeline_execution_step_success(
    *,
    config_overrides: Optional[AsyncSageMakerClientConfig] = None,
    callback_token: Optional[CallbackToken] = None,
    output_parameters: Optional[OutputParameterList] = None,
    client_request_token: Optional[IdempotencyToken] = None,
) -> SendPipelineExecutionStepSuccessResponse

Notifies the pipeline that the execution of a callback step succeeded and provides a list of the step's output parameters. When a callback step is run, the pipeline generates a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).

Parameters:

callback_token (Optional[CallbackToken], default: None ) –

The pipeline generated token from the Amazon SQS queue.
output_parameters (Optional[OutputParameterList], default: None ) –

A list of the output parameters of the callback step.
client_request_token (Optional[IdempotencyToken], default: None ) –

A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.

Raises:

ConflictException –

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

You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
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 send_pipeline_execution_step_success(
    self,
    *,
    config_overrides: Optional[AsyncSageMakerClientConfig] = None,
    callback_token: Optional[
        "capo_sagemaker.types.callback_token.CallbackToken"
    ] = None,
    output_parameters: Optional[
        "capo_sagemaker.types.output_parameter_list.OutputParameterList"
    ] = None,
    client_request_token: Optional[
        "capo_sagemaker.types.idempotency_token.IdempotencyToken"
    ] = None,
) -> "capo_sagemaker.types.send_pipeline_execution_step_success_response.SendPipelineExecutionStepSuccessResponse":
    """<p>Notifies the pipeline that the execution of a callback step succeeded and provides a list of the step's output parameters. When a callback step is run, the pipeline generates a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).</p>

    Args:
        callback_token: <p>The pipeline generated token from the Amazon SQS queue.</p>
        output_parameters: <p>A list of the output parameters of the callback step.</p>
        client_request_token: <p>A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.</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_limit_exceeded.ResourceLimitExceeded: <p> You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created. </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.send_pipeline_execution_step_success_request.SendPipelineExecutionStepSuccessRequest]",
    ) -> AsyncOperationResponse[
        "capo_sagemaker.types.send_pipeline_execution_step_success_response.SendPipelineExecutionStepSuccessResponse"
    ]:
        import capo_sagemaker._operations.sage_maker.send_pipeline_execution_step_success

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("SendPipelineExecutionStepSuccess")
    )
    input_: capo_sagemaker.types.send_pipeline_execution_step_success_request.SendPipelineExecutionStepSuccessRequest = {}
    if callback_token is not None:
        input_["callback_token"] = callback_token
    if output_parameters is not None:
        input_["output_parameters"] = output_parameters
    if client_request_token is None:
        client_request_token = str(uuid.uuid4())
    input_["client_request_token"] = client_request_token

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

send_pipeline_execution_step_success async ¶

send_pipeline_execution_step_success `async` ¶