# Behind a Proxy { #behind-a-proxy }

In many situations, you would use a **proxy** like Traefik or Nginx in front of your FastAPI app.

These proxies could handle HTTPS certificates and other things.

## Proxy Forwarded Headers { #proxy-forwarded-headers }

depend on the resources of dependencies with `yield`.

For example, instead of using the same database session, you would create a new database session inside of the background task, and you would obtain the objects from the database using this new session. And then instead of passing the object from the database as a parameter to the background task function, you would pass the ID of that object and then obtain the object again inside the background task function....

Now, let's see how you could use that to return a custom response.

Let's say that you want to return an <a href="https://en.wikipedia.org/wiki/XML" class="external-link" target="_blank">XML</a> response.

{* ../../docs_src/openapi_webhooks/tutorial001_py39.py hl[9:13,36:53] *}

The webhooks that you define will end up in the **OpenAPI** schema and the automatic **docs UI**.

/// info

The `app.webhooks` object is actually just an `APIRouter`, the same type you would use when structuring your app with multiple files.

///

If it was in a type annotation we could have used the vertical bar, as:

```Python
some_variable: PlaneItem | CarItem
```

But if we put that in the assignment `response_model=PlaneItem | CarItem` we would get an error, because Python would try to perform an **invalid operation** between `PlaneItem` and `CarItem` instead of interpreting that as a type annotation.

After that, you would need to **install** FastAPI and any other **packages** you want to use.

To install packages you would normally use the `pip` command that comes with Python (or similar alternatives).

Nevertheless, if you just use `pip` directly, the packages would be installed in your **global Python environment** (the global installation of Python).

You could load it at the top level of the module/file, but that would also mean that it would **load the model** even if you are just running a simple automated test, then that test would be **slow** because it would have to wait for the model to load before being able to run an independent part of the code.

        )


class OAuth2(SecurityBase):
    """
    This is the base class for OAuth2 authentication, an instance of it would be used
    as a dependency. All other OAuth2 classes inherit from it and customize it for
    each OAuth2 flow.

    You normally would not create a new class inheriting from it but use one of the
    existing subclasses, and maybe compose them if you want to support multiple flows.

Instead, use the actual default value of the function parameter. Otherwise, it would be inconsistent.

For example, this is not allowed:

```Python
q: Annotated[str, Query(default="rick")] = "morty"
```

...because it's not clear if the default value should be `"rick"` or `"morty"`.

So, you would use (preferably):

```Python
q: Annotated[str, Query()] = "rick"
```

This way, you don't have to know beforehand what the valid field/attribute names are (as would be the case with Pydantic models).

This would be useful if you want to receive keys that you don't already know.

---

Another useful case is when you want to have keys of another type (e.g., `int`).

That's what we are going to see here.

In this case, you would accept any `dict` as long as it has `int` keys with `float` values: