url = ""
    content_type_level = "0"
    if override1:
        url += "/level1"
        content_type_level = "1"
    if override2:
        url += "/level2"
        content_type_level = "2"
    if override3:
        url += "/level3"
        content_type_level = "3"
    if override4:
        url += "/level4"
        content_type_level = "4"
    if override5:
        url += "/override5"

"Mounting" means adding a completely "independent" application in a specific path, that then takes care of handling everything under that path, with the _path operations_ declared in that sub-application.

### Top-level application

First, create the main, top-level, **FastAPI** application, and its *path operations*:

```Python hl_lines="3  6-8"
{!../../../docs_src/sub_applications/tutorial001.py!}
```

### Sub-application

    return [pet1, pet2]


client = TestClient(app)


def test_filter_top_level_model():
    response = client.post(
        "/users", json={"email": "******@****.***", "password": "secret"}
    )
    assert response.json() == {"email": "******@****.***"}


def test_filter_second_level_model():
    response = client.get("/pets/1")
    assert response.json() == {
        "name": "Nibbler",

And that's what **HTTPS** is, it's just plain **HTTP** inside a **secure TLS connection** instead of a pure (unencrypted) TCP connection.

!!! tip
    Notice that the encryption of the communication happens at the **TCP level**, not at the HTTP level.

### HTTPS Request

Now that the client and server (specifically the browser and the TLS Termination Proxy) have an **encrypted TCP connection**, they can start the **HTTP communication**.

## Other models

You can now get the current user directly in the *path operation functions* and deal with the security mechanisms at the **Dependency Injection** level, using `Depends`.

And you can use any model or data for the security requirements (in this case, a Pydantic model `User`).

But you are not restricted to using some specific data model, class or type.

    return response.data.updateDiscussionComment.comment


if __name__ == "__main__":
    settings = Settings()
    if settings.input_debug:
        logging.basicConfig(level=logging.DEBUG)
    else:
        logging.basicConfig(level=logging.INFO)
    logging.debug(f"Using config: {settings.json()}")
    g = Github(settings.input_token.get_secret_value())
    repo = g.get_repo(settings.github_repository)

    name: str

    if PYDANTIC_V2:
        model_config = {
            "json_schema_extra": {
                "x-something-internal": {"level": 4},
            }
        }
    else:

        class Config:
            schema_extra = {
                "x-something-internal": {"level": 4},
            }


@app.get("/foo", response_model=Item)
def foo():
    return {"name": "Foo item"}

                    "avatarUrl": author.avatarUrl,
                    "url": author.url,
                }
            )
    return users


if __name__ == "__main__":
    logging.basicConfig(level=logging.INFO)
    settings = Settings()
    logging.info(f"Using config: {settings.model_dump_json()}")
    g = Github(settings.input_token.get_secret_value())
    repo = g.get_repo(settings.github_repository)

    return [pet1, pet2]


client = TestClient(app)


def test_filter_top_level_model():
    response = client.post(
        "/users", json={"email": "******@****.***", "password": "secret"}
    )
    assert response.json() == {"email": "******@****.***"}


def test_filter_second_level_model():
    response = client.get("/pets/1")
    assert response.json() == {
        "name": "Nibbler",

```Python hl_lines="11  14-16"
{!../../../docs_src/sub_applications/tutorial001.py!}
```

### Die Unteranwendung mounten

Mounten Sie in Ihrer Top-Level-Anwendung `app` die Unteranwendung `subapi`.

In diesem Fall wird sie im Pfad `/subapi` gemountet:

```Python hl_lines="11  19"
{!../../../docs_src/sub_applications/tutorial001.py!}
```