describe_dataset ¶

def describe_dataset(
    self,
    dataset_arn: "capo_rekognition.types.dataset_arn.DatasetArn",
    *,
    config_overrides: Optional[RekognitionClientConfig] = None,
) -> "capo_rekognition.types.describe_dataset_response.DescribeDatasetResponse":
    """<note> <p>This operation applies only to Amazon Rekognition Custom Labels.</p> </note> <p> Describes an Amazon Rekognition Custom Labels dataset. You can get information such as the current status of a dataset and statistics about the images and labels in a dataset. </p> <p>This operation requires permissions to perform the <code>rekognition:DescribeDataset</code> action.</p>

    Args:
        dataset_arn: <p> The Amazon Resource Name (ARN) of the dataset that you want to describe. </p>

    Raises:
        capo_rekognition.errors.access_denied_exception.AccessDeniedException: <p>You are not authorized to perform the action.</p>
        capo_rekognition.errors.internal_server_error.InternalServerError: <p>Amazon Rekognition experienced a service issue. Try your call again.</p>
        capo_rekognition.errors.invalid_parameter_exception.InvalidParameterException: <p>Input parameter violated a constraint. Validate your parameter before calling the API operation again.</p>
        capo_rekognition.errors.provisioned_throughput_exceeded_exception.ProvisionedThroughputExceededException: <p>The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.</p>
        capo_rekognition.errors.resource_not_found_exception.ResourceNotFoundException: <p>The resource specified in the request cannot be found.</p>
        capo_rekognition.errors.throttling_exception.ThrottlingException: <p>Amazon Rekognition is temporarily unable to process the request. Try your call again.</p>
        capo_rekognition.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

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

        output, http_response = (
            capo_rekognition._operations.rekognition_service.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_rekognition.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