```Python hl_lines="16-18  21-22  28-32"
{!../../../docs_src/openapi_callbacks/tutorial001.py!}
```

Es gibt zwei Hauptunterschiede zu einer normalen *Pfadoperation*:

* Es muss kein tatsächlicher Code vorhanden sein, da Ihre Anwendung diesen Code niemals aufruft. Sie wird nur zur Dokumentation der *externen API* verwendet. Die Funktion könnte also einfach `pass` enthalten.

def test_post():
    data = {"title": "towel", "size": 5}
    response = client.post("/items/", json=data)
    assert response.status_code == 200, response.text
    assert response.json() == data


def test_openapi_schema():
    response = client.get("/openapi.json")
    assert response.status_code == 200, response.text
    assert response.json() == {
        "openapi": "3.1.0",
        "info": {"title": "FastAPI", "version": "0.1.0"},

# 디버깅

예를 들면 Visual Studio Code 또는 PyCharm을 사용하여 편집기에서 디버거를 연결할 수 있습니다.

## `uvicorn` 호출

FastAPI 애플리케이션에서 `uvicorn`을 직접 임포트하여 실행합니다

```Python hl_lines="1  15"
{!../../../docs_src/debugging/tutorial001.py!}
```

### `__name__ == "__main__"` 에 대하여

`__name__ == "__main__"`의 주요 목적은 다음과 같이 파일이 호출될 때 실행되는 일부 코드를 갖는 것입니다.

<div class="termy">

```console
$ python myapp.py
```

</div>

    * **Kurz**: Codeverdoppelung minimieren. Mehrere Funktionalitäten aus jeder Parameterdeklaration.
    * **Robust**: Erhalten Sie produktionsbereiten Code. Mit automatischer, interaktiver Dokumentation.

        raise HTTPException(status_code=400, detail="Inactive user")
    return current_user


@app.post("/token")
async def login_for_access_token(
    form_data: OAuth2PasswordRequestForm = Depends(),
) -> Token:
    user = authenticate_user(fake_users_db, form_data.username, form_data.password)
    if not user:
        raise HTTPException(
            status_code=status.HTTP_401_UNAUTHORIZED,

        raise HTTPException(status_code=400, detail="Inactive user")
    return current_user


@app.post("/token")
async def login_for_access_token(
    form_data: Annotated[OAuth2PasswordRequestForm, Depends()],
) -> Token:
    user = authenticate_user(fake_users_db, form_data.username, form_data.password)
    if not user:
        raise HTTPException(
            status_code=status.HTTP_401_UNAUTHORIZED,

    response = client.get("/items/foo?needy=very")
    assert response.status_code == 200
    assert response.json() == {
        "item_id": "foo",
        "needy": "very",
        "skip": 0,
        "limit": None,
    }


@needs_py310
def test_foo_no_needy(client: TestClient):
    response = client.get("/items/foo?skip=a&limit=b")
    assert response.status_code == 422
    assert response.json() == IsDict(
        {

One of the main features needed by API systems is data "<abbr title="also called marshalling, conversion">serialization</abbr>" which is taking data from the code (Python) and converting it into something that can be sent through the network. For example, converting an object containing data from a database into a JSON object. Converting `datetime` objects into strings, etc.

            "item_id": item_id,
        }
    )
    response = client.put(f"/items/{item_id}", json=data)
    assert response.status_code == 200, response.text
    assert response.json() == expected_response


def test_openapi_schema():
    response = client.get("/openapi.json")
    assert response.status_code == 200, response.text
    assert response.json() == {
        "openapi": "3.1.0",

So, even with the code above that doesn't use Pydantic explicitly, FastAPI is using Pydantic to convert those standard dataclasses to Pydantic's own flavor of dataclasses.

And of course, it supports the same:

* data validation
* data serialization