},
        "baz": "simple_include_dict model2 baz",
    }


@app.get(
    "/simple_exclude",
    response_model=Model2,
    response_model_exclude={"ref": {"bar"}},
)
def simple_exclude():
    return Model2(
        ref=Model1(foo="simple_exclude model foo", bar="simple_exclude model bar"),
        baz="simple_exclude model2 baz",
    )


@app.get(
    "/simple_exclude_dict",

 * string is not human readable, but can be used with classes like [InetAddress] to establish
 * connections.
 *
 * ## Why another URL model?
 *
 * Java includes both [java.net.URL][URL] and [java.net.URI][URI]. We offer a new URL
 * model to address problems that the others don't.
 *
 * ### Different URLs should be different
 *

    from pydantic import BaseModel, ValidationInfo, field_validator

    app = FastAPI()

    class ModelB(BaseModel):
        username: str

    class ModelC(ModelB):
        password: str

    class ModelA(BaseModel):
        name: str
        description: Optional[str] = None
        foo: ModelB
        tags: dict[str, str] = {}

        @field_validator("name")

    - [CVE-2023-3955: Insufficient input sanitization on Windows nodes leads to privilege escalation](#cve-2023-3955-insufficient-input-sanitization-on-windows-nodes-leads-to-privilege-escalation)
    - [CVE-2023-3676: Insufficient input sanitization on Windows nodes leads to privilege escalation](#cve-2023-3676-insufficient-input-sanitization-on-windows-nodes-leads-to-privilege-escalation)
  - [Changes by Kind](#changes-by-kind-14)

Cuando veas la documentación automática, puedes verificar que el modelo de entrada y el modelo de salida tendrán cada uno su propio JSON Schema:

<img src="/img/tutorial/response-model/image01.png">

Y ambos modelos se utilizarán para la documentación interactiva de la API:

<img src="/img/tutorial/response-model/image02.png">

## Otras Anotaciones de Tipos de Retorno { #other-return-type-annotations }

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

app = FastAPI()


class Model(BaseModel):
    pass


class Model2(BaseModel):
    a: Model


class Model3(BaseModel):
    c: Model
    d: Model2


@app.get("/", response_model=Model3)
def f():
    return {"c": {}, "d": {"a": {}}}


client = TestClient(app)


def test_get_api_route():

## `response_model`-Parameter { #response-model-parameter }

Es gibt Fälle, da möchten oder müssen Sie Daten zurückgeben, die nicht genau dem entsprechen, was der Typ deklariert.

- github.com/google/cel-go: [v0.22.0 → v0.23.2](https://github.com/google/cel-go/compare/v0.22.0...v0.23.2)
- github.com/google/gnostic-models: [v0.6.8 → v0.6.9](https://github.com/google/gnostic-models/compare/v0.6.8...v0.6.9)
- github.com/google/go-cmp: [v0.6.0 → v0.7.0](https://github.com/google/go-cmp/compare/v0.6.0...v0.7.0)

- github.com/google/cel-go: [v0.23.2 → v0.26.0](https://github.com/google/cel-go/compare/v0.23.2...v0.26.0)
- github.com/google/gnostic-models: [v0.6.9 → v0.7.0](https://github.com/google/gnostic-models/compare/v0.6.9...v0.7.0)
- github.com/grpc-ecosystem/grpc-gateway/v2: [v2.24.0 → v2.26.3](https://github.com/grpc-ecosystem/grpc-gateway/compare/v2.24.0...v2.26.3)

{* ../../docs_src/body/tutorial001.py hl[4] *}

## Créez votre modèle de données

Déclarez ensuite votre modèle de données en tant que classe qui hérite de `BaseModel`.

Utilisez les types Python standard pour tous les attributs :

{* ../../docs_src/body/tutorial001.py hl[7:11] *}