create_dataset ¶

def create_dataset(
    self,
    dataset_name: "capo_lookoutequipment.types.dataset_name.DatasetName",
    client_token: "capo_lookoutequipment.types.idempotence_token.IdempotenceToken",
    *,
    config_overrides: Optional[LookoutEquipmentClientConfig] = None,
    dataset_schema: Optional[
        "capo_lookoutequipment.types.dataset_schema.DatasetSchema"
    ] = None,
    server_side_kms_key_id: Optional[
        "capo_lookoutequipment.types.name_or_arn.NameOrArn"
    ] = None,
    tags: Optional["capo_lookoutequipment.types.tag_list.TagList"] = None,
) -> "capo_lookoutequipment.types.create_dataset_response.CreateDatasetResponse":
    """<p>Creates a container for a collection of data being ingested for analysis. The dataset contains the metadata describing where the data is and what the data actually looks like. For example, it contains the location of the data source, the data schema, and other information. A dataset also contains any tags associated with the ingested data. </p>

    Args:
        dataset_name: <p>The name of the dataset being created. </p>
        dataset_schema: <p>A JSON description of the data that is in each time series dataset, including names, column names, and data types. </p>
        server_side_kms_key_id: <p>Provides the identifier of the KMS key used to encrypt dataset data by Amazon Lookout for Equipment. </p>
        client_token: <p> A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one. </p>
        tags: <p>Any tags associated with the ingested data described in the dataset. </p>

    Raises:
        capo_lookoutequipment.errors.access_denied_exception.AccessDeniedException: <p>The request could not be completed because you do not have access to the resource. </p>
        capo_lookoutequipment.errors.conflict_exception.ConflictException: <p> The request could not be completed due to a conflict with the current state of the target resource. </p>
        capo_lookoutequipment.errors.internal_server_exception.InternalServerException: <p> Processing of the request has failed because of an unknown error, exception or failure. </p>
        capo_lookoutequipment.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p> Resource limitations have been exceeded. </p>
        capo_lookoutequipment.errors.throttling_exception.ThrottlingException: <p>The request was denied due to request throttling.</p>
        capo_lookoutequipment.errors.validation_exception.ValidationException: <p> The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized. </p>
        capo_lookoutequipment.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_lookoutequipment.types.create_dataset_request.CreateDatasetRequest]",
    ) -> OperationResponse[
        "capo_lookoutequipment.types.create_dataset_response.CreateDatasetResponse"
    ]:
        import capo_lookoutequipment._operations.aws_lookout_equipment_frontend_service.create_dataset

        output, http_response = (
            capo_lookoutequipment._operations.aws_lookout_equipment_frontend_service.create_dataset.create_dataset(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("CreateDataset")
    )
    input_: capo_lookoutequipment.types.create_dataset_request.CreateDatasetRequest = {
        "dataset_name": dataset_name,
        "client_token": client_token,
    }
    if dataset_schema is not None:
        input_["dataset_schema"] = dataset_schema
    if server_side_kms_key_id is not None:
        input_["server_side_kms_key_id"] = server_side_kms_key_id
    if tags is not None:
        input_["tags"] = tags

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