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 fastapi import FastAPI

app = FastAPI()


@app.get("/users/{user_id}/items/{item_id}")
async def read_user_item(
    user_id: int, item_id: str, q: str | None = None, short: bool = False
):
    item = {"item_id": item_id, "owner_id": user_id}
    if q:
        item.update({"q": q})
    if not short:
        item.update(
            {"description": "This is an amazing item that has a long description"}
        )

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}

from fastapi import FastAPI, Form
from pydantic import BaseModel

app = FastAPI()


class FormData(BaseModel):
    username: str
    password: str
    model_config = {"extra": "forbid"}


@app.post("/login/")
async def login(data: FormData = Form()):

    }

    private static boolean isAny(String str) {
        return "*".equals(str);
    }

    private static boolean matches(String pattern, String str) {
        if (isAny(pattern)) {
            return true;
        } else if (pattern.endsWith("*")) {
            return str.startsWith(pattern.substring(0, pattern.length() - 1));
        } else {

///

/// note

**FastAPI** saura que `q` est optionnel grâce au `=None`.

Le `Optional` dans `Optional[str]` n'est pas utilisé par **FastAPI** (**FastAPI** n'en utilisera que la partie `str`), mais il servira tout de même à votre éditeur de texte pour détecter des erreurs dans votre code.

///

## Conversion des types des paramètres de requête

      return 1
    fi
  fi
}

# hash string like Java String::hashCode
hash_string() {
  str="${1:-}" h=0
  while [ -n "$str" ]; do
    char="${str%"${str#?}"}"
    h=$(((h * 31 + $(LC_CTYPE=C printf %d "'$char")) % 4294967296))
    str="${str#?}"
  done
  printf %x\\n $h
}

verbose() { :; }
[ "${MVNW_VERBOSE-}" != true ] || verbose() { printf %s\\n "${1-}"; }

die() {

Neste exemplo, ele converteria o modelo Pydantic em um `dict`, e o `datetime` em um `str`.

O resultado de chamar a função é algo que pode ser codificado com o padrão do Python <a href="https://docs.python.org/3/library/json.html#json.dumps" class="external-link" target="_blank">`json.dumps()`</a>.

```Python hl_lines="1"
async def needy_dependency(fresh_value: Annotated[str, Depends(get_value, use_cache=False)]):
    return {"fresh_value": fresh_value}
```

////

//// tab | Python 3.9+ nicht annotiert

/// tip | Tipp

Bevorzugen Sie die `Annotated`-Version, falls möglich.

///

```Python hl_lines="1"
async def needy_dependency(fresh_value: str = Depends(get_value, use_cache=False)):

from typing import Annotated

from fastapi import FastAPI, Form
from pydantic import BaseModel

app = FastAPI()


class FormData(BaseModel):
    username: str
    password: str
    model_config = {"extra": "forbid"}


@app.post("/login/")
async def login(data: Annotated[FormData, Form()]):