from fastapi import FastAPI
from fastapi.testclient import TestClient
from pydantic import BaseModel

app = FastAPI()


class SubModel(BaseModel):
    a: Optional[str] = "foo"


class Model(BaseModel):
    x: Optional[int] = None
    sub: SubModel


class ModelSubclass(Model):
    y: int
    z: int = 0
    w: Optional[int] = None


class ModelDefaults(BaseModel):

Todo eso, de manera arbitraria.

### Definir un submodelo { #define-a-submodel }

Por ejemplo, podemos definir un modelo `Image`:

{* ../../docs_src/body_nested_models/tutorial004_py310.py hl[7:9] *}

### Usar el submodelo como tipo { #use-the-submodel-as-a-type }

Y luego podemos usarlo como el tipo de un atributo:

@app.get("/items/recursive", response_model=RecursiveItem)
def get_recursive():
    return {"name": "item", "sub_items": [{"name": "subitem", "sub_items": []}]}


@app.get("/items/recursive-submodel", response_model=RecursiveItemViaSubmodel)
def get_recursive_submodel():
    return {
        "name": "item",
        "sub_items1": [
            {
                "name": "subitem",
                "sub_items2": [

All that, arbitrarily nested.

### Define a submodel { #define-a-submodel }

For example, we can define an `Image` model:

{* ../../docs_src/body_nested_models/tutorial004_py310.py hl[7:9] *}

### Use the submodel as a type { #use-the-submodel-as-a-type }

And then we can use it as the type of an attribute:

    assert response.status_code == 200, response.text
    assert response.json() == {
        "sub_items": [{"name": "subitem", "sub_items": []}],
        "name": "item",
    }

    response = client.get("/items/recursive-submodel")
    assert response.status_code == 200, response.text
    assert response.json() == {
        "name": "item",
        "sub_items1": [
            {
                "name": "subitem",
                "sub_items2": [

Alles das beliebig tief verschachtelt.

### Ein Kindmodell definieren { #define-a-submodel }

Für ein Beispiel können wir ein `Image`-Modell definieren.

{* ../../docs_src/body_nested_models/tutorial004_py310.py hl[7:9] *}

### Das Kindmodell als Typ verwenden { #use-the-submodel-as-a-type }

Und dann können wir es als Typ eines Attributes verwenden:

Tudo isso, aninhado arbitrariamente.

### Defina um sub-modelo { #define-a-submodel }

Por exemplo, nós podemos definir um modelo `Image`:

{* ../../docs_src/body_nested_models/tutorial004_py310.py hl[7:9] *}

### Use o sub-modelo como um tipo { #use-the-submodel-as-a-type }

E então podemos usa-lo como o tipo de um atributo:

                }
            },
            "/response_model_filtering_model-annotation_submodel-return_submodel": {
                "get": {
                    "summary": "Response Model Filtering Model Annotation Submodel Return Submodel",
                    "operationId": "response_model_filtering_model_annotation_submodel_return_submodel_response_model_filtering_model_annotation_submodel_return_submodel_get",
                    "responses": {

Всё это может быть произвольно вложенным.

### Определение подмодели { #define-a-submodel }

Например, мы можем определить модель `Image`:

{* ../../docs_src/body_nested_models/tutorial004_py310.py hl[7:9] *}

### Использование подмодели как типа { #use-the-submodel-as-a-type }

Также мы можем использовать эту модель как тип атрибута:

                name=response_name,
                type_=self.response_model,
                mode="serialization",
            )
            # Create a clone of the field, so that a Pydantic submodel is not returned
            # as is just because it's an instance of a subclass of a more limited class
            # e.g. UserInDB (containing hashed_password) could be a subclass of User