),
    ] = None,
    include_in_schema: Annotated[
        bool,
        Doc(
            """
            To include (or not) this parameter field in the generated OpenAPI.
            You probably don't need it, but it's available.

            This affects the generated OpenAPI (e.g. visible at `/docs`).
            """
        ),
    ] = True,
    json_schema_extra: Annotated[

```

And the proxy would be **"stripping"** the **path prefix** on the fly before transmitting the request to the app server (probably Uvicorn via FastAPI CLI), keeping your application convinced that it is being served at `/app`, so that you don't have to update all your code to include the prefix `/api/v1`.

Up to here, everything would work as normally.

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

The simpler the problem solved by the tool, the better performance it will get. And most of the benchmarks don't test the additional features provided by the tool.

The hierarchy is like:

* **Uvicorn**: an ASGI server
    * **Starlette**: (uses Uvicorn) a web microframework

<img src="/img/tutorial/generate-clients/image06.png">

In this case you have:

* `ItemsService`
* `UsersService`

### Client Method Names

Right now the generated method names like `createItemItemsPost` don't look very clean:

```TypeScript
ItemsService.createItemItemsPost({name: "Plumbus", price: 5})
```

...that's because the client generator uses the OpenAPI internal **operation ID** for each *path operation*.

You could then update `test_main.py` with the extended tests:

```Python
{!> ../../../docs_src/app_testing/app_b/test_main.py!}
```

Whenever you need the client to pass information in the request and you don't know how to, you can search (Google) how to do it in `httpx`, or even how to do it with `requests`, as HTTPX's design is based on Requests' design.

Then you just do the same in your tests.

E.g.:

We want FastAPI to keep **filtering** the data using the response model.

In the previous example, because the classes were different, we had to use the `response_model` parameter. But that also means that we don't get the support from the editor and tools checking the function return type.

But in most of the cases where we need to do something like this, we want the model just to **filter/remove** some of the data as in this example.

!!! tip
    Don't worry if some of these items about **containers**, Docker, or Kubernetes don't make a lot of sense yet.

    I'll tell you more about container images, Docker, Kubernetes, etc. in a future chapter: [FastAPI in Containers - Docker](docker.md){.internal-link target=_blank}.

---

You could also define it as a normal function instead of `async def`:

```Python hl_lines="7"
{!../../../docs_src/first_steps/tutorial003.py!}
```

!!! note
    If you don't know the difference, check the [Async: *"In a hurry?"*](../async.md#in-a-hurry){.internal-link target=_blank}.

### Step 5: return the content

```Python hl_lines="8"
{!../../../docs_src/first_steps/tutorial001.py!}

## More motivation

Check this function, it already has type hints:

```Python hl_lines="1"
{!../../../docs_src/python_types/tutorial003.py!}
```

Because the editor knows the types of the variables, you don't only get completion, you also get error checks:

<img src="/img/python-types/image04.png">

Now you know that you have to fix it, convert `age` to a string with `str(age)`:

```Python hl_lines="2"

As it is very simple, it's relatively intuitive to learn, although the documentation gets somewhat technical at some points.

It is also commonly used for other applications that don't necessarily need a database, user management, or any of the many features that come pre-built in Django. Although many of these features can be added with plug-ins.