Specifically, to see Uvicorn, Starlette and FastAPI compared together (among many other tools).

The simpler the problem solved by the tool, the better performance it will get. And most of the benchmarks don't test the additional features provided by the tool.

The hierarchy is like:

* **Uvicorn**: an ASGI server
    * **Starlette**: (uses Uvicorn) a web microframework

        Doc(
            """
            OpenAPI-specific examples.

            It will be added to the generated OpenAPI (e.g. visible at `/docs`).

            Swagger UI (that provides the `/docs` interface) has better support for the
            OpenAPI-specific examples than the JSON Schema `examples`, that's the main
            use case for this.

            Read more about it in the

* If you translate pages, add a single pull request per page translated. That will make it much easier for others to review it.

* To check the 2-letter code for the language you want to translate, you can use the table <a href="https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes" class="external-link" target="_blank">List of ISO 639-1 codes</a>.

#### Existing language

```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

But I'll show you how to improve that next. 🤓

## Custom Operation IDs and Better Method Names

You can **modify** the way these operation IDs are **generated** to make them simpler and have **simpler method names** in the clients.

And in those cases, we can use classes and inheritance to take advantage of function **type annotations** to get better support in the editor and tools, and still get the FastAPI **data filtering**.

=== "Python 3.10+"

    ```Python hl_lines="7-10  13-14  18"
    {!> ../../../docs_src/response_model/tutorial003_01_py310.py!}
    ```

    And after searching for a long time for a similar framework and testing many different alternatives, APIStar was the best option available.

    Then APIStar stopped to exist as a server and Starlette was created, and was a new better foundation for such a system. That was the final inspiration to build **FastAPI**.

# Reference - Code API

Here's the reference or code API, the classes, functions, parameters, attributes, and
all the FastAPI parts you can use in your applications.

If you want to **learn FastAPI** you are much better off reading the

If you want to secure your API, there are several better things you can do, for example:

* Make sure you have well defined Pydantic models for your request bodies and responses.
* Configure any required permissions and roles using dependencies.

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}

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