scalar.svg...

        at_least_one_scalar_sequence = False
        for arg in get_args(annotation):
            if field_annotation_is_scalar_sequence(arg):
                at_least_one_scalar_sequence = True
                continue
            elif not field_annotation_is_scalar(arg):
                return False
        return at_least_one_scalar_sequence
    return field_annotation_is_sequence(annotation) and all(

    Undefined,
    _regenerate_error_with_loc,
    copy_field_info,
    create_body_model,
    evaluate_forwardref,
    field_annotation_is_scalar,
    get_annotation_from_field_info,
    get_missing_field_error,
    is_bytes_field,
    is_bytes_sequence_field,
    is_scalar_field,
    is_scalar_sequence_field,
    is_sequence_field,
    is_uploadfile_or_nonable_uploadfile_annotation,
    is_uploadfile_sequence_annotation,

<a href="https://github.com/scalar/scalar/?utm_source=fastapi&utm_medium=website&utm_campaign=main-badge" target="_blank" title="Scalar: Beautiful Open-Source API References from Swagger/OpenAPI files"><img src="https://fastapi.tiangolo.com/img/sponsors/scalar.svg"></a>

    url: https://github.com/cryptapi
  - login: codacy
    avatarUrl: https://avatars.githubusercontent.com/u/1834093?v=4
    url: https://github.com/codacy
  - login: scalar
    avatarUrl: https://avatars.githubusercontent.com/u/301879?v=4
    url: https://github.com/scalar
- - login: ObliviousAI
    avatarUrl: https://avatars.githubusercontent.com/u/65656077?v=4
    url: https://github.com/ObliviousAI
- - login: databento

You can use **type annotations** the same way you would for input data in function **parameters**, you can use Pydantic models, lists, dictionaries, scalar values like integers, booleans, etc.

=== "Python 3.10+"

    ```Python hl_lines="16  21"
    {!> ../../../docs_src/response_model/tutorial001_01_py310.py!}
    ```

=== "Python 3.9+"

message HorizontalPodAutoscalerSpec {
  // reference to scaled resource; horizontal pod autoscaler will learn the current resource consumption
  // and will set the desired number of pods by using its Scale subresource.
  optional CrossVersionObjectReference scaleTargetRef = 1;

  // minReplicas is the lower limit for the number of replicas to which the autoscaler
  // can scale down.  It defaults to 1 pod.  minReplicas is allowed to be 0 if the

  // status defines current status of the scale. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#spec-and-status. Read-only.
  // +optional
  optional ScaleStatus status = 3;
}

// ScaleSpec describes the attributes of a scale subresource
message ScaleSpec {
  // replicas is the number of observed instances of the scaled object.
  // +optional
  optional int32 replicas = 1;

// Package-wide variables from generator "generated".
option go_package = "k8s.io/api/autoscaling/v2";

// ContainerResourceMetricSource indicates how to scale on a resource metric known to
// Kubernetes, as specified in requests and limits, describing each pod in the
// current scale target (e.g. CPU or memory).  The values will be averaged
// together before being compared to the target.  Such metrics are built in to

				p.errorf("%s doesn't support scaled register format", p.arch.Name)
			} else {
				a.Scale = int16(scale)
			}
		}
		p.get(')')
	} else if scale != 0 {
		if p.arch.Family == sys.ARM64 {
			p.errorf("arm64 doesn't support scaled register format")
		}
		// First (R) was missing, all we have is (R*scale).
		a.Reg = 0
		a.Index = r1
		a.Scale = int16(scale)
	}
}