describe_dataset ¶

describe_dataset(
    dataset_id: ID,
    *,
    config_overrides: Optional[IoTSiteWiseClientConfig] = None,
    workspace_name: Optional[WorkspaceName] = None,
    dataset_version: Optional[Version] = None,
) -> DescribeDatasetResponse

Retrieves information about a dataset.

Parameters:

dataset_id (ID) –

The ID of the dataset.
workspace_name (Optional[WorkspaceName], default: None ) –

The name of the workspace that contains the dataset.
dataset_version (Optional[Version], default: None ) –

The version of the dataset.

Raises:

InternalFailureException –

IoT SiteWise can't process your request right now. Try again later.
InvalidRequestException –

The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters. Check your request and try again.
ResourceNotFoundException –

The requested resource can't be found.
ThrottlingException –

Your request exceeded a rate limit. For example, you might have exceeded the number of IoT SiteWise assets that can be created per second, the allowed number of messages per second, and so on.

For more information, see Quotas in the IoT SiteWise User Guide.
UnknownServiceError –

The service returned an error code this client does not model.

Source code in docs_src/capo_iotsitewise/_services/io_t_site_wise.py

def describe_dataset(
    self,
    dataset_id: "capo_iotsitewise.types.id.ID",
    *,
    config_overrides: Optional[IoTSiteWiseClientConfig] = None,
    workspace_name: Optional[
        "capo_iotsitewise.types.workspace_name.WorkspaceName"
    ] = None,
    dataset_version: Optional["capo_iotsitewise.types.version.Version"] = None,
) -> "capo_iotsitewise.types.describe_dataset_response.DescribeDatasetResponse":
    """<p>Retrieves information about a dataset.</p>

    Args:
        dataset_id: <p>The ID of the dataset.</p>
        workspace_name: <p>The name of the workspace that contains the dataset.</p>
        dataset_version: <p>The version of the dataset.</p>

    Raises:
        capo_iotsitewise.errors.internal_failure_exception.InternalFailureException: <p>IoT SiteWise can't process your request right now. Try again later.</p>
        capo_iotsitewise.errors.invalid_request_exception.InvalidRequestException: <p>The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters. Check your request and try again.</p>
        capo_iotsitewise.errors.resource_not_found_exception.ResourceNotFoundException: <p>The requested resource can't be found.</p>
        capo_iotsitewise.errors.throttling_exception.ThrottlingException: <p>Your request exceeded a rate limit. For example, you might have exceeded the number of IoT SiteWise assets that can be created per second, the allowed number of messages per second, and so on.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/iot-sitewise/latest/userguide/quotas.html">Quotas</a> in the <i>IoT SiteWise User Guide</i>.</p>
        capo_iotsitewise.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

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

        output, http_response = (
            capo_iotsitewise._operations.aws_io_t_site_wise.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_iotsitewise.types.describe_dataset_request.DescribeDatasetRequest = {
        "dataset_id": dataset_id
    }
    if workspace_name is not None:
        input_["workspace_name"] = workspace_name
    if dataset_version is not None:
        input_["dataset_version"] = dataset_version

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