from datetime import datetime
from typing import Union

from fastapi import FastAPI
from fastapi.encoders import jsonable_encoder
from pydantic import BaseModel

fake_db = {}


class Item(BaseModel):
    title: str
    timestamp: datetime
    description: Union[str, None] = None


app = FastAPI()


@app.put("/items/{id}")
def update_item(id: str, item: Item):
    json_compatible_item_data = jsonable_encoder(item)

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):

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 datetime import datetime
from typing import Union

from fastapi import FastAPI
from fastapi.encoders import jsonable_encoder
from fastapi.responses import JSONResponse
from pydantic import BaseModel


class Item(BaseModel):
    title: str
    timestamp: datetime
    description: Union[str, None] = None


app = FastAPI()


@app.put("/items/{id}")
def update_item(id: str, item: Item):

from typing import Annotated, Literal

from fastapi import FastAPI, Query
from pydantic import BaseModel, Field

app = FastAPI()


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

    limit: int = Field(100, gt=0, le=100)
    offset: int = Field(0, ge=0)
    order_by: Literal["created_at", "updated_at"] = "created_at"
    tags: list[str] = []


@app.get("/items/")

from fastapi import FastAPI
from pydantic import BaseModel, Field

app = FastAPI()


class Item(BaseModel):
    name: str = Field(examples=["Foo"])
    description: str | None = Field(default=None, examples=["A very nice Item"])
    price: float = Field(examples=[35.4])
    tax: float | None = Field(default=None, examples=[3.2])


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item):

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None
    tags: set[str] = set()


@app.post(
    "/items/",
    response_model=Item,
    summary="Create an item",
    description="Create an item with all the information, name, description, price, tax and a set of unique tags",
)