describe_dataset ¶

def describe_dataset(
    self,
    dataset_arn: "capo_forecast.types.arn.Arn",
    *,
    config_overrides: Optional[forecastClientConfig] = None,
) -> "capo_forecast.types.describe_dataset_response.DescribeDatasetResponse":
    """<p>Describes an Amazon Forecast dataset created using the <a href="https://docs.aws.amazon.com/forecast/latest/dg/API_CreateDataset.html">CreateDataset</a> operation.</p> <p>In addition to listing the parameters specified in the <code>CreateDataset</code> request, this operation includes the following dataset properties:</p> <ul> <li> <p> <code>CreationTime</code> </p> </li> <li> <p> <code>LastModificationTime</code> </p> </li> <li> <p> <code>Status</code> </p> </li> </ul>

    Args:
        dataset_arn: <p>The Amazon Resource Name (ARN) of the dataset.</p>

    Raises:
        capo_forecast.errors.invalid_input_exception.InvalidInputException: <p>We can't process the request because it includes an invalid value or a value that exceeds the valid range.</p>
        capo_forecast.errors.resource_not_found_exception.ResourceNotFoundException: <p>We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.</p>
        capo_forecast.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_forecast.types.describe_dataset_request.DescribeDatasetRequest]",
    ) -> OperationResponse[
        "capo_forecast.types.describe_dataset_response.DescribeDatasetResponse"
    ]:
        import capo_forecast._operations.amazon_forecast.describe_dataset

        output, http_response = (
            capo_forecast._operations.amazon_forecast.describe_dataset.describe_dataset(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("DescribeDataset")
    )
    input_: capo_forecast.types.describe_dataset_request.DescribeDatasetRequest = {
        "dataset_arn": dataset_arn
    }

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