untag_resource ¶

def untag_resource(
    self,
    resource_arn: "capo_appflow.types.arn.ARN",
    tag_keys: "capo_appflow.types.tag_key_list.TagKeyList",
    *,
    config_overrides: Optional[AppflowClientConfig] = None,
) -> "capo_appflow.types.untag_resource_response.UntagResourceResponse":
    """<p> Removes a tag from the specified flow. </p>

    Args:
        resource_arn: <p> The Amazon Resource Name (ARN) of the flow that you want to untag. </p>
        tag_keys: <p> The tag keys associated with the tag that you want to remove from your flow. </p>

    Raises:
        capo_appflow.errors.internal_server_exception.InternalServerException: <p> An internal service error occurred during the processing of your request. Try again later. </p>
        capo_appflow.errors.resource_not_found_exception.ResourceNotFoundException: <p> The resource specified in the request (such as the source or destination connector profile) is not found. </p>
        capo_appflow.errors.validation_exception.ValidationException: <p> The request has invalid or missing parameters. </p>
        capo_appflow.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_appflow.types.untag_resource_request.UntagResourceRequest]",
    ) -> OperationResponse[
        "capo_appflow.types.untag_resource_response.UntagResourceResponse"
    ]:
        import capo_appflow._operations.sandstone_configuration_service_lambda.untag_resource

        output, http_response = (
            capo_appflow._operations.sandstone_configuration_service_lambda.untag_resource.untag_resource(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("UntagResource")
    )
    input_: capo_appflow.types.untag_resource_request.UntagResourceRequest = {
        "resource_arn": resource_arn,
        "tag_keys": tag_keys,
    }

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