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)
    ```

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():

### <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.

Just keep in mind that when you read "server" in general, it could refer to one of those two things.

When referring to the remote machine, it's common to call it **server**, but also **machine**, **VM** (virtual machine), **node**. Those all refer to some type of remote machine, normally running Linux, where you run programs.

## Install the Server Program

## OpenAPI Client Generators

There are many tools to generate clients from **OpenAPI**.

A common tool is <a href="https://openapi-generator.tech/" class="external-link" target="_blank">OpenAPI Generator</a>.

* Получении результата из вашей функции.
* Назначении результата в параметр в вашей *функции обработки пути*.

```mermaid
graph TB

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

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

Таким образом, вы пишете общий код один раз, и **FastAPI** позаботится о его вызове для ваших *операций с путями*.

* Dieses Ergebnis dem Parameter Ihrer *Pfadoperation-Funktion* zuzuweisen.

```mermaid
graph TB

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

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

    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: Annotated[dict, Depends(common_parameters)]):
        return commons
    ```
    """

There might be cases where you return something that is not a valid Pydantic field and you annotate it in the function, only to get the support provided by tooling (the editor, mypy, etc).

### Return a Response Directly

The most common case would be [returning a Response directly as explained later in the advanced docs](../advanced/response-directly.md){.internal-link target=_blank}.

```Python hl_lines="8  10-11"