send_workflow_step_action ¶

def send_workflow_step_action(
    self,
    step_execution_id: "capo_imagebuilder.types.workflow_step_execution_id.WorkflowStepExecutionId",
    image_build_version_arn: "capo_imagebuilder.types.image_build_version_arn.ImageBuildVersionArn",
    action: "capo_imagebuilder.types.workflow_step_action_type.WorkflowStepActionType",
    client_token: "capo_imagebuilder.types.client_token.ClientToken",
    *,
    config_overrides: Optional[imagebuilderClientConfig] = None,
    reason: Optional[
        "capo_imagebuilder.types.non_empty_string.NonEmptyString"
    ] = None,
) -> "capo_imagebuilder.types.send_workflow_step_action_response.SendWorkflowStepActionResponse":
    """<p>Sends an action to a workflow step that has paused at a <code>WaitForAction</code> step, so that image creation can continue. To find the steps that are waiting for an action, call <a>ListWaitingWorkflowSteps</a>.</p>

    Args:
        step_execution_id: <p>Uniquely identifies the waiting workflow step that you send the action to. To get this identifier, call <a>ListWaitingWorkflowSteps</a>.</p>
        image_build_version_arn: <p>The Amazon Resource Name (ARN) of the image build version associated with the workflow step execution. This value must match the image that owns the waiting step. If the ARN does not correspond to the image running the workflow, then the request fails with a validation error.</p>
        action: <p>The action to perform on the paused workflow step. <code>RESUME</code> completes the waiting step, and the workflow continues. <code>STOP</code> fails the step, and the step's <code>onFailure</code> setting determines whether the workflow continues or aborts. The workflow step must be in a waiting state to accept an action. The request fails if the step has already timed out or been actioned.</p>
        reason: <p>The reason for the action. This value is stored with the step execution record and is accessible in subsequent workflow steps via step output references.</p>
        client_token: <p>A unique, case-sensitive identifier you provide to ensure that the operation runs no more than one time. If you retry a request with the same client token, Image Builder returns the original response without running the operation again. For more information, see <a href="https://docs.aws.amazon.com/AWSEC2/latest/APIReference/Run_Instance_Idempotency.html">Ensuring idempotency</a> in the <i>Amazon EC2 API Reference</i>.</p>

    Raises:
        capo_imagebuilder.errors.call_rate_limit_exceeded_exception.CallRateLimitExceededException: <p>You have exceeded the permitted request rate for the Amazon EC2 APIs that Image Builder calls on your behalf. Retry with an increasing or variable delay between requests.</p>
        capo_imagebuilder.errors.client_exception.ClientException: <p>A generic client error. This error usually indicates that the request failed a validation check, such as when a downstream service rejects a configured value.</p>
        capo_imagebuilder.errors.forbidden_exception.ForbiddenException: <p>You are not authorized to perform the requested operation.</p>
        capo_imagebuilder.errors.idempotent_parameter_mismatch_exception.IdempotentParameterMismatchException: <p>You have specified a client token for an operation using parameter values that differ from a previous request that used the same client token.</p>
        capo_imagebuilder.errors.invalid_parameter_value_exception.InvalidParameterValueException: <p>The value that you provided for the specified parameter is invalid.</p>
        capo_imagebuilder.errors.invalid_request_exception.InvalidRequestException: <p>The request is malformed or otherwise invalid. Verify the request and try again.</p>
        capo_imagebuilder.errors.resource_in_use_exception.ResourceInUseException: <p>The resource that you are trying to operate on is currently in use. Review the message details and retry later.</p>
        capo_imagebuilder.errors.resource_not_found_exception.ResourceNotFoundException: <p>At least one of the resources referenced by your request does not exist.</p>
        capo_imagebuilder.errors.service_exception.ServiceException: <p>An internal server error occurred while Image Builder processed the request. Retrying the request may succeed.</p>
        capo_imagebuilder.errors.service_unavailable_exception.ServiceUnavailableException: <p>The service is unable to process your request at this time.</p>
        capo_imagebuilder.errors.UnknownServiceError: The service returned an error code this client does not model.

    Examples:
        Stop a workflow step that is waiting for action
        The following example sends the STOP action to a workflow step that has paused the image build, identified by the step execution ID that ListWaitingWorkflowSteps returns.

        >>> client.send_workflow_step_action(step_execution_id='step-8eb24d7a-036e-46b5-94a3-90a5d8b5ac4a', image_build_version_arn='arn:aws:imagebuilder:us-west-2:111122223333:image/my-example-wait-recipe/1.0.0/1', action='STOP', client_token='a1b2c3d4-5678-90ab-cdef-EXAMPLE67890')
    """

    def _handler(
        req: "OperationRequest[capo_imagebuilder.types.send_workflow_step_action_request.SendWorkflowStepActionRequest]",
    ) -> OperationResponse[
        "capo_imagebuilder.types.send_workflow_step_action_response.SendWorkflowStepActionResponse"
    ]:
        import capo_imagebuilder._operations.imagebuilder.send_workflow_step_action

        output, http_response = (
            capo_imagebuilder._operations.imagebuilder.send_workflow_step_action.send_workflow_step_action(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("SendWorkflowStepAction")
    )
    input_: capo_imagebuilder.types.send_workflow_step_action_request.SendWorkflowStepActionRequest = {
        "step_execution_id": step_execution_id,
        "image_build_version_arn": image_build_version_arn,
        "action": action,
        "client_token": client_token,
    }
    if reason is not None:
        input_["reason"] = reason

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