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start_pipeline_execution async

start_pipeline_execution(
    workspace_name: WorkspaceName,
    pipeline_name: ResourceName,
    *,
    config_overrides: Optional[AsyncIoTSiteWiseClientConfig] = None,
    execution_environment_variable_overrides: Optional[
        ExecutionEnvironmentVariables
    ] = None,
    execution_mount_overrides: Optional[MountOverrides] = None,
    execution_priority: Optional[ExecutionPriority] = None,
    client_token: Optional[ClientToken] = None,
) -> StartPipelineExecutionResponse

Starts execution of a pipeline in the specified workspace. Each compute node runs according to the DAG dependency order defined in the pipeline. Nodes without dependencies start immediately, while dependent nodes wait for all upstream nodes to complete successfully.

You can provide runtime environment variable overrides that take the highest priority in the environment variable hierarchy, without modifying the pipeline definition.

Parameters:

  • workspace_name (WorkspaceName) –

    The name of the workspace containing the pipeline.

  • pipeline_name (ResourceName) –

    The name of the pipeline to execute.

  • execution_environment_variable_overrides (Optional[ExecutionEnvironmentVariables], default: None ) –

    Runtime environment variable overrides for the execution. Includes global variables that apply to all compute nodes and computeNodes for per-node overrides. These take the highest priority in the environment variable hierarchy.

  • execution_mount_overrides (Optional[MountOverrides], default: None ) –

    Runtime mount overrides for the execution. Overrides are merged by mount name into each listed compute node's task-defined mounts: a matching name replaces the task-defined mount, a new name adds a mount, and task-defined mounts not referenced remain unchanged. Compute nodes not listed use their task-defined mounts as-is.

  • execution_priority (Optional[ExecutionPriority], default: None ) –

    Scheduling priority for the execution. Lower values indicate higher priority. Defaults to 2 when not specified.

  • client_token (Optional[ClientToken], default: None ) –

    A unique, case-sensitive identifier that you provide to ensure the idempotency of the request. If you retry a request that completed successfully using the same client token, the server returns the cached result from the original successful request without performing the operation again.

Raises:

  • AccessDeniedException –

    Access is denied.

  • ConflictingOperationException –

    Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.

  • InternalFailureException –

    IoT SiteWise can't process your request right now. Try again later.

  • InvalidRequestException –

    The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters. Check your request and try again.

  • LimitExceededException –

    You've reached the quota for a resource. For example, this can occur if you're trying to associate more than the allowed number of child assets or attempting to create more than the allowed number of properties for an asset model.

    For more information, see Quotas in the IoT SiteWise User Guide.

  • ResourceNotFoundException –

    The requested resource can't be found.

  • ThrottlingException –

    Your request exceeded a rate limit. For example, you might have exceeded the number of IoT SiteWise assets that can be created per second, the allowed number of messages per second, and so on.

    For more information, see Quotas in the IoT SiteWise User Guide.

  • UnknownServiceError –

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

Source code in docs_src/capo_iotsitewise/_services/async_io_t_site_wise.py
async def start_pipeline_execution(
    self,
    workspace_name: "capo_iotsitewise.types.workspace_name.WorkspaceName",
    pipeline_name: "capo_iotsitewise.types.resource_name.ResourceName",
    *,
    config_overrides: Optional[AsyncIoTSiteWiseClientConfig] = None,
    execution_environment_variable_overrides: Optional[
        "capo_iotsitewise.types.execution_environment_variables.ExecutionEnvironmentVariables"
    ] = None,
    execution_mount_overrides: Optional[
        "capo_iotsitewise.types.mount_overrides.MountOverrides"
    ] = None,
    execution_priority: Optional[
        "capo_iotsitewise.types.execution_priority.ExecutionPriority"
    ] = None,
    client_token: Optional[
        "capo_iotsitewise.types.client_token.ClientToken"
    ] = None,
) -> "capo_iotsitewise.types.start_pipeline_execution_response.StartPipelineExecutionResponse":
    """<p>Starts execution of a pipeline in the specified workspace. Each compute node runs according to the DAG dependency order defined in the pipeline. Nodes without dependencies start immediately, while dependent nodes wait for all upstream nodes to complete successfully.</p> <p>You can provide runtime environment variable overrides that take the highest priority in the environment variable hierarchy, without modifying the pipeline definition.</p>

    Args:
        workspace_name: <p>The name of the workspace containing the pipeline.</p>
        pipeline_name: <p>The name of the pipeline to execute.</p>
        execution_environment_variable_overrides: <p>Runtime environment variable overrides for the execution. Includes global variables that apply to all compute nodes and computeNodes for per-node overrides. These take the highest priority in the environment variable hierarchy.</p>
        execution_mount_overrides: <p>Runtime mount overrides for the execution. Overrides are merged by mount name into each listed compute node's task-defined mounts: a matching name replaces the task-defined mount, a new name adds a mount, and task-defined mounts not referenced remain unchanged. Compute nodes not listed use their task-defined mounts as-is.</p>
        execution_priority: <p>Scheduling priority for the execution. Lower values indicate higher priority. Defaults to 2 when not specified.</p>
        client_token: <p>A unique, case-sensitive identifier that you provide to ensure the idempotency of the request. If you retry a request that completed successfully using the same client token, the server returns the cached result from the original successful request without performing the operation again.</p>

    Raises:
        capo_iotsitewise.errors.access_denied_exception.AccessDeniedException: <p>Access is denied.</p>
        capo_iotsitewise.errors.conflicting_operation_exception.ConflictingOperationException: <p>Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.</p>
        capo_iotsitewise.errors.internal_failure_exception.InternalFailureException: <p>IoT SiteWise can't process your request right now. Try again later.</p>
        capo_iotsitewise.errors.invalid_request_exception.InvalidRequestException: <p>The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters. Check your request and try again.</p>
        capo_iotsitewise.errors.limit_exceeded_exception.LimitExceededException: <p>You've reached the quota for a resource. For example, this can occur if you're trying to associate more than the allowed number of child assets or attempting to create more than the allowed number of properties for an asset model.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/iot-sitewise/latest/userguide/quotas.html">Quotas</a> in the <i>IoT SiteWise User Guide</i>.</p>
        capo_iotsitewise.errors.resource_not_found_exception.ResourceNotFoundException: <p>The requested resource can't be found.</p>
        capo_iotsitewise.errors.throttling_exception.ThrottlingException: <p>Your request exceeded a rate limit. For example, you might have exceeded the number of IoT SiteWise assets that can be created per second, the allowed number of messages per second, and so on.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/iot-sitewise/latest/userguide/quotas.html">Quotas</a> in the <i>IoT SiteWise User Guide</i>.</p>
        capo_iotsitewise.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_iotsitewise.types.start_pipeline_execution_request.StartPipelineExecutionRequest]",
    ) -> AsyncOperationResponse[
        "capo_iotsitewise.types.start_pipeline_execution_response.StartPipelineExecutionResponse"
    ]:
        import capo_iotsitewise._operations.aws_io_t_site_wise.start_pipeline_execution

        (
            output,
            http_response,
        ) = await capo_iotsitewise._operations.aws_io_t_site_wise.start_pipeline_execution.async_start_pipeline_execution(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    def _redact_input(
        input_: "capo_iotsitewise.types.start_pipeline_execution_request.StartPipelineExecutionRequest",
    ) -> dict[str, Any]:
        import capo_iotsitewise.types.start_pipeline_execution_request

        return capo_iotsitewise.types.start_pipeline_execution_request.redact_sensitive(
            input_
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("StartPipelineExecution", redact_input=_redact_input),
    )
    input_: capo_iotsitewise.types.start_pipeline_execution_request.StartPipelineExecutionRequest = {
        "workspace_name": workspace_name,
        "pipeline_name": pipeline_name,
    }
    if execution_environment_variable_overrides is not None:
        input_["execution_environment_variable_overrides"] = (
            execution_environment_variable_overrides
        )
    if execution_mount_overrides is not None:
        input_["execution_mount_overrides"] = execution_mount_overrides
    if execution_priority is not None:
        input_["execution_priority"] = execution_priority
    if client_token is None:
        client_token = str(uuid.uuid4())
    input_["client_token"] = client_token

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