list_retraining_schedulers async ¶

async def list_retraining_schedulers(
    self,
    *,
    config_overrides: Optional[AsyncLookoutEquipmentClientConfig] = None,
    model_name_begins_with: Optional[
        "capo_lookoutequipment.types.model_name.ModelName"
    ] = None,
    status: Optional[
        "capo_lookoutequipment.types.retraining_scheduler_status.RetrainingSchedulerStatus"
    ] = None,
    next_token: Optional["capo_lookoutequipment.types.next_token.NextToken"] = None,
    max_results: Optional[
        "capo_lookoutequipment.types.max_results.MaxResults"
    ] = None,
) -> "capo_lookoutequipment.types.list_retraining_schedulers_response.ListRetrainingSchedulersResponse":
    """<p>Lists all retraining schedulers in your account, filtering by model name prefix and status. </p>

    Args:
        model_name_begins_with: <p>Specify this field to only list retraining schedulers whose machine learning models begin with the value you specify. </p>
        status: <p>Specify this field to only list retraining schedulers whose status matches the value you specify. </p>
        next_token: <p>If the number of results exceeds the maximum, a pagination token is returned. Use the token in the request to show the next page of retraining schedulers.</p>
        max_results: <p>Specifies the maximum number of retraining schedulers to list. </p>

    Raises:
        capo_lookoutequipment.errors.access_denied_exception.AccessDeniedException: <p>The request could not be completed because you do not have access to the resource. </p>
        capo_lookoutequipment.errors.internal_server_exception.InternalServerException: <p> Processing of the request has failed because of an unknown error, exception or failure. </p>
        capo_lookoutequipment.errors.throttling_exception.ThrottlingException: <p>The request was denied due to request throttling.</p>
        capo_lookoutequipment.errors.validation_exception.ValidationException: <p> The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized. </p>
        capo_lookoutequipment.errors.UnknownServiceError: The service returned an error code this client does not model.

    Examples:
        Listing retraining schedulers

        >>> await client.list_retraining_schedulers(max_results=50)
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_lookoutequipment.types.list_retraining_schedulers_request.ListRetrainingSchedulersRequest]",
    ) -> AsyncOperationResponse[
        "capo_lookoutequipment.types.list_retraining_schedulers_response.ListRetrainingSchedulersResponse"
    ]:
        import capo_lookoutequipment._operations.aws_lookout_equipment_frontend_service.list_retraining_schedulers

        (
            output,
            http_response,
        ) = await capo_lookoutequipment._operations.aws_lookout_equipment_frontend_service.list_retraining_schedulers.async_list_retraining_schedulers(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ListRetrainingSchedulers")
    )
    input_: capo_lookoutequipment.types.list_retraining_schedulers_request.ListRetrainingSchedulersRequest = {}
    if model_name_begins_with is not None:
        input_["model_name_begins_with"] = model_name_begins_with
    if status is not None:
        input_["status"] = status
    if next_token is not None:
        input_["next_token"] = next_token
    if max_results is not None:
        input_["max_results"] = max_results

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