tag_resource async ¶

async def tag_resource(
    self,
    resource_arn: "capo_timestream_influxdb.types.arn.Arn",
    tags: "capo_timestream_influxdb.types.request_tag_map.RequestTagMap",
    *,
    config_overrides: Optional[AsyncTimestreamInfluxDBClientConfig] = None,
) -> None:
    """<p>Tags are composed of a Key/Value pairs. You can use tags to categorize and track your Timestream for InfluxDB resources.</p>

    Args:
        resource_arn: <p>The Amazon Resource Name (ARN) of the tagged resource.</p>
        tags: <p>A list of tags used to categorize and track resources.</p>

    Raises:
        capo_timestream_influxdb.errors.resource_not_found_exception.ResourceNotFoundException: <p>The requested resource was not found or does not exist.</p>
        capo_timestream_influxdb.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>The request exceeds the service quota.</p>
        capo_timestream_influxdb.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_timestream_influxdb.types.tag_resource_request.TagResourceRequest]",
    ) -> AsyncOperationResponse[None]:
        import capo_timestream_influxdb._operations.amazon_timestream_influx_db.tag_resource

        (
            output,
            http_response,
        ) = await capo_timestream_influxdb._operations.amazon_timestream_influx_db.tag_resource.async_tag_resource(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("TagResource")
    )
    input_: capo_timestream_influxdb.types.tag_resource_request.TagResourceRequest = {
        "resource_arn": resource_arn,
        "tags": tags,
    }

    response = await aexecute_pipeline(
        AsyncOperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    await response.response.aclose()
    return response.output