def test_get(client: TestClient):
    response = client.get("/")
    assert response.json() == {"custom_field": [1.0, 2.0, 3.0]}


def test_typeadapter():
    # This test is only to confirm that Pydantic alone is working as expected
    from pydantic import (
        BaseModel,
        ConfigDict,
        PlainSerializer,
        TypeAdapter,
        WithJsonSchema,
    )

    class FakeNumpyArray:
        def __init__(self):

from fastapi import FastAPI
from pydantic import BaseModel, EmailStr

app = FastAPI()


class UserIn(BaseModel):
    username: str
    password: str
    email: EmailStr
    full_name: str | None = None


# Don't do this in production!
@app.post("/user/")
async def create_user(user: UserIn) -> UserIn:

from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None


app = FastAPI()


@app.post("/items/")
async def create_item(item: Item):

Si quieres asegurar tu API, hay varias cosas mejores que puedes hacer, por ejemplo:

* Asegúrate de tener modelos Pydantic bien definidos para tus request bodies y responses.
* Configura los permisos y roles necesarios usando dependencias.
* Nunca guardes contraseñas en texto plano, solo hashes de contraseñas.

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: str | None = None


app = FastAPI(separate_input_output_schemas=False)


@app.post("/items/")
def create_item(item: Item):
    return item


@app.get("/items/")
def read_items() -> list[Item]:
    return [
        Item(
            name="Portal Gun",

from typing import Annotated, Union

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Annotated[Item, Body(embed=True)]):
    results = {"item_id": item_id, "item": item}

## Les modèles Pydantic

<a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> est une bibliothèque Python pour effectuer de la validation de données.

Vous déclarez la forme de la donnée avec des classes et des attributs.

Chaque attribut possède un type.

from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel, EmailStr

app = FastAPI()


class BaseUser(BaseModel):
    username: str
    email: EmailStr
    full_name: Union[str, None] = None


class UserIn(BaseUser):
    password: str


@app.post("/user/")
async def create_user(user: UserIn) -> BaseUser:

from typing import Annotated

from fastapi import Cookie, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Cookies(BaseModel):
    model_config = {"extra": "forbid"}

    session_id: str
    fatebook_tracker: str | None = None
    googall_tracker: str | None = None


@app.get("/items/")
async def read_items(cookies: Annotated[Cookies, Cookie()]):

from fastapi import FastAPI, Header
from pydantic import BaseModel

app = FastAPI()


class CommonHeaders(BaseModel):
    host: str
    save_data: bool
    if_modified_since: str | None = None
    traceparent: str | None = None
    x_tag: list[str] = []


@app.get("/items/")
async def read_items(headers: CommonHeaders = Header(convert_underscores=False)):