get_recommender async ¶

async def get_recommender(
    self,
    domain_name: "capo_customer_profiles.types.name.name",
    recommender_name: "capo_customer_profiles.types.name.name",
    *,
    config_overrides: Optional[AsyncCustomerProfilesClientConfig] = None,
    training_metrics_count: Optional[
        "capo_customer_profiles.types.get_recommender_request_training_metrics_count_integer.GetRecommenderRequestTrainingMetricsCountInteger"
    ] = None,
) -> "capo_customer_profiles.types.get_recommender_response.GetRecommenderResponse":
    """<p>Retrieves a recommender.</p>

    Args:
        domain_name: <p>The unique name of the domain.</p>
        recommender_name: <p>The name of the recommender.</p>
        training_metrics_count: <p>The number of training metrics to retrieve for the recommender.</p>

    Raises:
        capo_customer_profiles.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient access to perform this action.</p>
        capo_customer_profiles.errors.bad_request_exception.BadRequestException: <p>The input you provided is invalid.</p>
        capo_customer_profiles.errors.internal_server_exception.InternalServerException: <p>An internal service error occurred.</p>
        capo_customer_profiles.errors.resource_not_found_exception.ResourceNotFoundException: <p>The requested resource does not exist, or access was denied.</p>
        capo_customer_profiles.errors.throttling_exception.ThrottlingException: <p>You exceeded the maximum number of requests.</p>
        capo_customer_profiles.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_customer_profiles.types.get_recommender_request.GetRecommenderRequest]",
    ) -> AsyncOperationResponse[
        "capo_customer_profiles.types.get_recommender_response.GetRecommenderResponse"
    ]:
        import capo_customer_profiles._operations.customer_profiles_20200815.get_recommender

        (
            output,
            http_response,
        ) = await capo_customer_profiles._operations.customer_profiles_20200815.get_recommender.async_get_recommender(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    def _redact_output(
        output: "capo_customer_profiles.types.get_recommender_response.GetRecommenderResponse",
    ) -> dict[str, Any]:
        import capo_customer_profiles.types.get_recommender_response

        return (
            capo_customer_profiles.types.get_recommender_response.redact_sensitive(
                output
            )
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("GetRecommender", redact_output=_redact_output),
    )
    input_: capo_customer_profiles.types.get_recommender_request.GetRecommenderRequest = {
        "domain_name": domain_name,
        "recommender_name": recommender_name,
    }
    if training_metrics_count is not None:
        input_["training_metrics_count"] = training_metrics_count

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