from typing import Union

from fastapi import FastAPI, Query
from typing_extensions import Annotated

app = FastAPI()


@app.get("/items/")
async def read_items(
    q: Annotated[
        Union[str, None],
        Query(
            title="Query string",
            description="Query string for the items to search in the database that have a good match",
            min_length=3,
        ),
    ] = None,
):

from typing import Annotated

from fastapi import FastAPI, File, UploadFile

app = FastAPI()


@app.post("/files/")
async def create_file(file: Annotated[bytes | None, File()] = None):
    if not file:
        return {"message": "No file sent"}
    else:
        return {"file_size": len(file)}


@app.post("/uploadfile/")
async def create_upload_file(file: UploadFile | None = None):
    if not file:

from typing import 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: Item = Body(
        examples=[
            {
                "name": "Foo",

## 🛠️

🕰 👤 ▶️ 🏗 **FastAPI** ⚫️, 🏆 🍖 ⏪ 🥉, 🔧 🔬, 📄 & 🧰 🔜, & 💡 🔃 🐩 & 🔧 🆑 & 🍋.

## 🔮

👉 ☝, ⚫️ ⏪ 🆑 👈 **FastAPI** ⏮️ 🚮 💭 ➖ ⚠ 📚 👫👫.

⚫️ 💆‍♂ 👐 🤭 ⏮️ 🎛 ♣ 📚 ⚙️ 💼 👍.

📚 👩‍💻 & 🏉 ⏪ 🪀 🔛 **FastAPI** 👫 🏗 (🔌 👤 & 👇 🏉).

✋️, 📤 📚 📈 & ⚒ 👟.

**FastAPI** ✔️ 👑 🔮 ⤴️.

Or it might be the case that you just prefer to take other courses because they adapt better to your learning style.

Some course providers ✨ [**sponsor FastAPI**](../help-fastapi.md#sponsor-the-author){.internal-link target=_blank} ✨, this ensures the continued and healthy **development** of FastAPI and its **ecosystem**.

Então, sobre o ovo e a galinha, como você chama a primeira função async?

Se você estivar trabalhando com **FastAPI** não terá que se preocupar com isso, porquê essa "primeira" função será a sua *função de operação de rota*, e o FastAPI saberá como fazer a coisa certa.

You can also use it directly to create an instance of it and return it from your *path operations*.

You can import it directly from `fastapi`:

```python
from fastapi import Response
```

from typing import List, Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


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


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


@app.get("/items/")
async def read_items() -> List[Item]:

{"item_id":3}
```

/// check

Beachten Sie, dass der Wert, den Ihre Funktion erhält und zurückgibt, die Zahl `3` ist, also ein `int`. Nicht der String `"3"`, also ein `str`.

Sprich, mit dieser Typdeklaration wird **FastAPI** die Anfrage automatisch <abbr title="Den String, der von einer HTTP Anfrage kommt, in Python-Objekte konvertieren">„parsen“</abbr>.

///

## Datenvalidierung

/// info

- 除非在 `responses` 参数中明确指定不同的媒体类型，否则**FastAPI**将假定响应与主响应类具有相同的媒体类型（默认为` application/json` ）。
- 但是如果您指定了一个自定义响应类，并将 `None `作为其媒体类型，**FastAPI**将使用 `application/json` 作为具有关联模型的任何其他响应。

///

## 组合信息
您还可以联合接收来自多个位置的响应信息，包括 `response_model `、 `status_code` 和 `responses `参数。

您可以使用默认的状态码 `200` （或者您需要的自定义状态码）声明一个 `response_model `，然后直接在OpenAPI模式中在 `responses` 中声明相同响应的其他信息。

**FastAPI**将保留来自 `responses` 的附加信息，并将其与模型中的JSON Schema结合起来。