delete_export ¶

def delete_export(
    self,
    export_arn: "capo_bcm_data_exports.types.arn.Arn",
    *,
    config_overrides: Optional[BCMDataExportsClientConfig] = None,
) -> "capo_bcm_data_exports.types.delete_export_response.DeleteExportResponse":
    """<p>Deletes an existing data export.</p>

    Args:
        export_arn: <p>The Amazon Resource Name (ARN) for this export.</p>

    Raises:
        capo_bcm_data_exports.errors.internal_server_exception.InternalServerException: <p>An error on the server occurred during the processing of your request. Try again later.</p>
        capo_bcm_data_exports.errors.resource_not_found_exception.ResourceNotFoundException: <p>The specified Amazon Resource Name (ARN) in the request doesn't exist.</p>
        capo_bcm_data_exports.errors.throttling_exception.ThrottlingException: <p>The request was denied due to request throttling.</p>
        capo_bcm_data_exports.errors.validation_exception.ValidationException: <p>The input fails to satisfy the constraints specified by an Amazon Web Services service.</p>
        capo_bcm_data_exports.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_bcm_data_exports.types.delete_export_request.DeleteExportRequest]",
    ) -> OperationResponse[
        "capo_bcm_data_exports.types.delete_export_response.DeleteExportResponse"
    ]:
        import capo_bcm_data_exports._operations.aws_billing_and_cost_management_data_exports.delete_export

        output, http_response = (
            capo_bcm_data_exports._operations.aws_billing_and_cost_management_data_exports.delete_export.delete_export(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("DeleteExport")
    )
    input_: capo_bcm_data_exports.types.delete_export_request.DeleteExportRequest = {
        "export_arn": export_arn
    }

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