def tag_resource(
self,
resource_arn: "capo_personalize.types.arn.Arn",
tags: "capo_personalize.types.tags.Tags",
*,
config_overrides: Optional[PersonalizeClientConfig] = None,
) -> "capo_personalize.types.tag_resource_response.TagResourceResponse":
"""<p>Add a list of tags to a resource.</p>
Args:
resource_arn: <p>The resource's Amazon Resource Name (ARN).</p>
tags: <p>Tags to apply to the resource. For more information see <a href="https://docs.aws.amazon.com/personalize/latest/dg/tagging-resources.html">Tagging Amazon Personalize resources</a>.</p>
Raises:
capo_personalize.errors.invalid_input_exception.InvalidInputException: <p>Provide a valid value for the field or parameter.</p>
capo_personalize.errors.limit_exceeded_exception.LimitExceededException: <p>The limit on the number of requests per second has been exceeded.</p>
capo_personalize.errors.resource_in_use_exception.ResourceInUseException: <p>The specified resource is in use.</p>
capo_personalize.errors.resource_not_found_exception.ResourceNotFoundException: <p>Could not find the specified resource.</p>
capo_personalize.errors.too_many_tags_exception.TooManyTagsException: <p>You have exceeded the maximum number of tags you can apply to this resource. </p>
capo_personalize.errors.UnknownServiceError: The service returned an error code this client does not model.
"""
def _handler(
req: "OperationRequest[capo_personalize.types.tag_resource_request.TagResourceRequest]",
) -> OperationResponse[
"capo_personalize.types.tag_resource_response.TagResourceResponse"
]:
import capo_personalize._operations.amazon_personalize.tag_resource
output, http_response = (
capo_personalize._operations.amazon_personalize.tag_resource.tag_resource(
req.options, req.input
)
)
return OperationResponse(output=output, response=http_response)
def _redact_input(
input_: "capo_personalize.types.tag_resource_request.TagResourceRequest",
) -> dict[str, Any]:
import capo_personalize.types.tag_resource_request
return capo_personalize.types.tag_resource_request.redact_sensitive(input_)
interceptors_, options_ = self.operation_options(
config_overrides,
OperationLogging("TagResource", redact_input=_redact_input),
)
input_: capo_personalize.types.tag_resource_request.TagResourceRequest = {
"resource_arn": resource_arn,
"tags": tags,
}
response = execute_pipeline(
OperationRequest(input=input_, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
response.response.close()
return response.output