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(
            openapi_examples={

                                    "title": "Img",
                                }
                            )
                            | IsDict(
                                # TODO: remove when deprecating Pydantic v1
                                {"title": "Img", "type": "boolean"}
                            ),
                            "name": "img",
                            "in": "query",
                        },

## 요구사항

FastAPI는 거인들의 어깨 위에 서 있습니다:

* 웹 부분을 위한 <a href="https://www.starlette.io/" class="external-link" target="_blank">Starlette</a>.
* 데이터 부분을 위한 <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a>.

## 설치

<div class="termy">

```console
$ pip install fastapi

---> 100%
```

</div>

from typing import Optional

from fastapi import Depends, FastAPI, Security
from fastapi.security.open_id_connect_url import OpenIdConnect
from fastapi.testclient import TestClient
from pydantic import BaseModel

app = FastAPI()

oid = OpenIdConnect(openIdConnectUrl="/openid", auto_error=False)


class User(BaseModel):
    username: str


def get_current_user(oauth_header: Optional[str] = Security(oid)):
    if oauth_header is None:

                                    "title": "Strange Header",
                                }
                            )
                            | IsDict(
                                # TODO: remove when deprecating Pydantic v1
                                {"title": "Strange Header", "type": "string"}
                            ),
                            "name": "strange_header",
                            "in": "header",

/// check | "😮 **FastAPI** "

🔬 ➕ 🔬 💽 🆎 ⚙️ "🔢" 💲 🏷 🔢. 👉 📉 👨‍🎨 🐕‍🦺, & ⚫️ 🚫 💪 Pydantic ⏭.

👉 🤙 😮 🛠️ 🍕 Pydantic, 🐕‍🦺 🎏 🔬 📄 👗 (🌐 👉 🛠️ 🔜 ⏪ 💪 Pydantic).

///

### <a href="https://github.com/hugapi/hug" class="external-link" target="_blank">🤗</a>

🤗 🕐 🥇 🛠️ 🛠️ 📄 🛠️ 🔢 🆎 ⚙️ 🐍 🆎 🔑. 👉 👑 💭 👈 😮 🎏 🧰 🎏.

If you want to secure your API, there are several better things you can do, for example:

* Make sure you have well defined Pydantic models for your request bodies and responses.
* Configure any required permissions and roles using dependencies.
* Never store plaintext passwords, only password hashes.

                    "input": "nonregexquery",
                    "ctx": {"pattern": "^fixedquery$"},
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {
                    "ctx": {"pattern": "^fixedquery$"},
                    "loc": ["query", "item-query"],

                    "input": "nonregexquery",
                    "ctx": {"pattern": "^fixedquery$"},
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {
                    "ctx": {"pattern": "^fixedquery$"},
                    "loc": ["query", "item-query"],

```Python hl_lines="22"
{!> ../../docs_src/body_multiple_params/tutorial002.py!}
```

////

Neste caso, o **FastAPI** perceberá que existe mais de um parâmetro de corpo na função (dois parâmetros que são modelos Pydantic).

Então, ele usará o nome dos parâmetros como chaves (nome dos campos) no corpo, e espera um corpo como:

```JSON
{
    "item": {
        "name": "Foo",
        "description": "The pretender",