app = FastAPI()


async def common_parameters(q: str | None = None, skip: int = 0, limit: int = 100):
    return {"q": q, "skip": skip, "limit": limit}


@app.get("/items/")
async def read_items(commons: dict = Depends(common_parameters)):
    return {"message": "Hello Items!", "params": commons}


@app.get("/users/")
async def read_users(commons: dict = Depends(common_parameters)):

接收到新的请求时，**FastAPI** 执行如下操作：

* 用正确的参数调用依赖项函数（「可依赖项」）
* 获取函数返回的结果
* 把函数返回的结果赋值给*路径操作函数*的参数

```mermaid
graph TB

common_parameters(["common_parameters"])
read_items["/items/"]
read_users["/users/"]

common_parameters --> read_items
common_parameters --> read_users
```

这样，只编写一次代码，**FastAPI** 就可以为多个*路径操作*共享这段代码 。

!!! check "检查"

    注意，无需创建专门的类，并将之传递给 **FastAPI** 以进行「注册」或执行类似的操作。

But when checking benchmarks and comparisons you should keep the following in mind.

## Benchmarks and speed

When you check the benchmarks, it is common to see several tools of different types compared as equivalent.

Specifically, to see Uvicorn, Starlette and FastAPI compared together (among many other tools).

## Аннотация типа или `Depends`

Обратите внимание, что в приведенном выше коде мы два раза пишем `CommonQueryParams`:

=== "Python 3.6+ без Annotated"

    !!! tip "Подсказка"
        Рекомендуется использовать версию с `Annotated` если возможно.

    ```Python
    commons: CommonQueryParams = Depends(CommonQueryParams)
    ```

    ```

`Field` works the same way as `Query`, `Path` and `Body`, it has all the same parameters, etc.

!!! note "Technical Details"
    Actually, `Query`, `Path` and others you'll see next create objects of subclasses of a common `Param` class, which is itself a subclass of Pydantic's `FieldInfo` class.

    And Pydantic's `Field` returns an instance of `FieldInfo` as well.

```

`app.add_middleware()` receives a middleware class as the first argument and any additional arguments to be passed to the middleware.

## Integrated middlewares

**FastAPI** includes several middlewares for common use cases, we'll see next how to use them.

!!! note "Technical Details"
    For the next examples, you could also use `from starlette.middleware.something import SomethingMiddleware`.

You can combine normal FastAPI *path operations* with GraphQL on the same application.

!!! tip
    **GraphQL** solves some very specific use cases.

    It has **advantages** and **disadvantages** when compared to common **web APIs**.

    Make sure you evaluate if the **benefits** for your use case compensate the **drawbacks**. 🤓

## GraphQL Libraries

app = FastAPI()

router = APIRouter()


async def common_parameters(q: str, skip: int = 0, limit: int = 100):
    return {"q": q, "skip": skip, "limit": limit}


@app.get("/main-depends/")
async def main_depends(commons: dict = Depends(common_parameters)):
    return {"in": "main-depends", "params": commons}


@app.get("/decorator-depends/", dependencies=[Depends(common_parameters)])
async def decorator_depends():

app = FastAPI()


async def common_parameters(q: str | None = None, skip: int = 0, limit: int = 100):
    return {"q": q, "skip": skip, "limit": limit}


@app.get("/items/")
async def read_items(commons: dict = Depends(common_parameters)):
    return commons


@app.get("/users/")
async def read_users(commons: dict = Depends(common_parameters)):

### <a href="https://requests.readthedocs.io" class="external-link" target="_blank">Requests</a>

**FastAPI** is not actually an alternative to **Requests**. Their scope is very different.

It would actually be common to use Requests *inside* of a FastAPI application.

But still, FastAPI got quite some inspiration from Requests.