The same way, you can define logic (code) that should be executed when the application is **shutting down**. In this case, this code will be executed **once**, **after** having handled possibly **many requests**.

{!../../../docs_src/path_params/tutorial005.py!}
```

### Testen Sie es in der API-Dokumentation

Weil die erlaubten Werte für den *Pfad-Parameter* nun vordefiniert sind, kann die interaktive Dokumentation sie als Auswahl-Drop-Down anzeigen:

<img src="/img/tutorial/path-params/image03.png">

### Mit Python-*<abbr title="Enumeration – Aufzählung">Enums</abbr>* arbeiten

If you have an API that does a comparable amount of computations every time and you have a lot of clients, then the **CPU utilization** will probably *also be stable* (instead of constantly going up and down quickly).

### Examples of Replication Tools and Strategies

# Sub Applications - Mounts

If you need to have two independent FastAPI applications, with their own independent OpenAPI and their own docs UIs, you can have a main app and "mount" one (or more) sub-application(s).

## Mounting a **FastAPI** application

"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.

* and from it, import the function `get_token_header`.

That would refer to some package above `app/`, with its own file `__init__.py`, etc. But we don't have that. So, that would throw an error in our example. 🚨

But now you know how it works, so you can use relative imports in your own apps no matter how complex they are. 🤓

### Add some custom `tags`, `responses`, and `dependencies`

@app.get("/users/me/", response_model=User)
async def read_users_me(
    current_user: Annotated[User, Depends(get_current_active_user)],
):
    return current_user


@app.get("/users/me/items/")
async def read_own_items(
    current_user: Annotated[User, Depends(get_current_active_user)],
):

                            "content": {"application/json": {"schema": {}}},
                        }
                    },
                    "summary": "Read Own Items",
                    "operationId": "read_own_items_users_me_items__get",
                    "security": [{"OAuth2PasswordBearer": ["items", "me"]}],
                }
            },
            "/status/": {
                "get": {

@app.get("/users/me/", response_model=User)
async def read_users_me(
    current_user: Annotated[User, Depends(get_current_active_user)],
):
    return current_user


@app.get("/users/me/items/")
async def read_own_items(
    current_user: Annotated[User, Security(get_current_active_user, scopes=["items"])],
):
    return [{"item_id": "Foo", "owner": current_user.username}]


@app.get("/status/")

### `UserInDB` model

Now, let's create a `UserInDB` model.

This will have the data that is actually stored in the database.

We don't create it as a subclass of Pydantic's `BaseModel` but as a subclass of our own `User`, because it will have all the attributes in `User` plus a couple more:

```Python hl_lines="31-33"
{!../../../docs_src/nosql_databases/tutorial001.py!}
```

!!! note

| `description` | `str` | A short description of the API. It can use Markdown. |
| `version` | `string` | The version of the API. This is the version of your own application, not of OpenAPI. For example `2.5.0`. |
| `terms_of_service` | `str` | A URL to the Terms of Service for the API. If provided, this has to be a URL. |