In this case, the original path `/app` would actually be served at `/api/v1/app`.

Even though all your code is written assuming there's just `/app`.

```Python hl_lines="6"
{!../../../docs_src/behind_a_proxy/tutorial001.py!}
```

```console
$ hypercorn main:app --worker-class trio
```

</div>

And that will start Hypercorn with your app using Trio as the backend.

Now you can use Trio internally in your app. Or even better, you can use AnyIO, to keep your code compatible with both Trio and asyncio. 🎉

## Deployment Concepts

I'll tell you a bit more about these **concepts** here, and that would hopefully give you the **intuition** you would need to decide how to deploy your API in very different environments, possibly even in **future** ones that don't exist yet.

By considering these concepts, you will be able to **evaluate and design** the best way to deploy **your own APIs**.

"docs_src/dependencies/tutorial008b_an_py39.py" = ["B904"]


[tool.ruff.lint.isort]
known-third-party = ["fastapi", "pydantic", "starlette"]

[tool.ruff.lint.pyupgrade]
# Preserve types, even if a file imports `from __future__ import annotations`.

* 🐛 Make sure a parameter defined as required is kept required in OpenAPI even if defined as optional in another dependency. PR [#4319](https://github.com/tiangolo/fastapi/pull/4319) by [@cd17822](https://github.com/cd17822).

* Even dependencies can have dependencies, creating a hierarchy or **"graph" of dependencies**.
* All **automatically handled** by the framework.
* All the dependencies can require data from requests and **augment the path operation** constraints and automatic documentation.
* **Automatic validation** even for *path operation* parameters defined in dependencies.

This can make it a lot easier for your users to **implement their APIs** to receive your **webhook** requests, they might even be able to autogenerate some of their own API code.

!!! info
    Webhooks are available in OpenAPI 3.1.0 and above, supported by FastAPI `0.99.0` and above.

## An app with webhooks

...and with that single declaration you get:

* Editor support, including:
    * Completion.
    * Type checks.
* Validation of data:
    * Automatic and clear errors when the data is invalid.
    * Validation even for deeply nested JSON objects.
* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of input data: coming from the network to Python data and types. Reading from:
    * JSON.
    * Path parameters.

### Types and validation

These environment variables can only handle text strings, as they are external to Python and have to be compatible with other programs and the rest of the system (and even with different operating systems, as Linux, Windows, macOS).

That means that any value read in Python from an environment variable will be a `str`, and any conversion to a different type or validation has to be done in code.

...and with that single declaration you get:

* Editor support, including:
    * Completion.
    * Type checks.
* Validation of data:
    * Automatic and clear errors when the data is invalid.
    * Validation even for deeply nested JSON objects.
* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of input data: coming from the network to Python data and types. Reading from:
    * JSON.
    * Path parameters.