untag_resource ¶

def untag_resource(
    self,
    resource_arn: "capo_forecast.types.arn.Arn",
    tag_keys: "capo_forecast.types.tag_keys.TagKeys",
    *,
    config_overrides: Optional[forecastClientConfig] = None,
) -> "capo_forecast.types.untag_resource_response.UntagResourceResponse":
    """<p>Deletes the specified tags from a resource.</p>

    Args:
        resource_arn: <p>The Amazon Resource Name (ARN) that identifies the resource for which to list the tags. </p>
        tag_keys: <p>The keys of the tags to be removed.</p>

    Raises:
        capo_forecast.errors.invalid_input_exception.InvalidInputException: <p>We can't process the request because it includes an invalid value or a value that exceeds the valid range.</p>
        capo_forecast.errors.resource_not_found_exception.ResourceNotFoundException: <p>We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.</p>
        capo_forecast.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

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

        output, http_response = (
            capo_forecast._operations.amazon_forecast.untag_resource.untag_resource(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    def _redact_input(
        input_: "capo_forecast.types.untag_resource_request.UntagResourceRequest",
    ) -> dict[str, Any]:
        import capo_forecast.types.untag_resource_request

        return capo_forecast.types.untag_resource_request.redact_sensitive(input_)

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("UntagResource", redact_input=_redact_input),
    )
    input_: capo_forecast.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