get_data_quality_model_result ¶

def get_data_quality_model_result(
    self,
    statistic_id: "capo_glue.types.hash_string.HashString",
    profile_id: "capo_glue.types.hash_string.HashString",
    *,
    config_overrides: Optional[GlueClientConfig] = None,
) -> "capo_glue.types.get_data_quality_model_result_response.GetDataQualityModelResultResponse":
    """<p>Retrieve a statistic's predictions for a given Profile ID.</p>

    Args:
        statistic_id: <p>The Statistic ID.</p>
        profile_id: <p>The Profile ID.</p>

    Raises:
        capo_glue.errors.entity_not_found_exception.EntityNotFoundException: <p>A specified entity does not exist</p>
        capo_glue.errors.internal_service_exception.InternalServiceException: <p>An internal service error occurred.</p>
        capo_glue.errors.invalid_input_exception.InvalidInputException: <p>The input provided was not valid.</p>
        capo_glue.errors.operation_timeout_exception.OperationTimeoutException: <p>The operation timed out.</p>
        capo_glue.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_glue.types.get_data_quality_model_result_request.GetDataQualityModelResultRequest]",
    ) -> OperationResponse[
        "capo_glue.types.get_data_quality_model_result_response.GetDataQualityModelResultResponse"
    ]:
        import capo_glue._operations.aws_glue.get_data_quality_model_result

        output, http_response = (
            capo_glue._operations.aws_glue.get_data_quality_model_result.get_data_quality_model_result(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("GetDataQualityModelResult")
    )
    input_: capo_glue.types.get_data_quality_model_result_request.GetDataQualityModelResultRequest = {
        "statistic_id": statistic_id,
        "profile_id": profile_id,
    }

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