thedocs.io/en/stable/" class="external-link" target="_blank">AnyIO</a>, which makes them compatible with both Python's standard library <a href="https://docs.python.org/3/library/asyncio-task.html" class="external-link" target="_blank">asyncio</a> and <a href="https://trio.readthedocs.io/en/stable/" class="external-link" target="_blank">Trio</a>.

Nevertheless, Uvicorn is currently only compatible with asyncio, and it normally uses <a href="https://github.com/MagicStack/uvloop" class="external-link"...

You can import it directly from `fastapi`:

```python
from fastapi import Request
```

!!! tip
    When you want to define dependencies that should be compatible with both HTTP and WebSockets, you can define a parameter that takes an `HTTPConnection` instead of a `Request` or a `WebSocket`.

Por defecto, **FastAPI** convertiría automáticamente ese valor devuelto a JSON usando el `jsonable_encoder` explicado en [Codificador Compatible JSON](../tutorial/encoder.md){.internal-link target=_blank}.

Luego, tras bastidores, pondría esos datos compatibles con JSON (por ejemplo, un `dict`) dentro de una `JSONResponse` que se usaría para enviar la respuesta al cliente.

## Convert any Data to JSON-compatible

To convert any data to JSON-compatible, read the docs for [Tutorial - JSON Compatible Encoder](../tutorial/encoder.md){.internal-link target=_blank}.

## OpenAPI Metadata - Docs

Because of this, **FastAPI** itself provides an alternative API documentation (using ReDoc), which you can access at <a href="http://127.0.0.1:8000/redoc" class="external-link" target="_blank">http://127.0.0.1:8000/redoc</a>:

<img src="/img/tutorial/path-params/image02.png">

The same way, there are many compatible tools. Including code generation tools for many languages.

# GraphQL

As **FastAPI** is based on the **ASGI** standard, it's very easy to integrate any **GraphQL** library also compatible with ASGI.

You can combine normal FastAPI *path operations* with GraphQL on the same application.

!!! tip
    **GraphQL** solves some very specific use cases.

    It has **advantages** and **disadvantages** when compared to common **web APIs**.

Après avoir testé plusieurs alternatives, j'ai décidé que j'allais utiliser <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">**Pydantic**</a> pour ses avantages.

J'y ai ensuite contribué, pour le rendre entièrement compatible avec JSON Schema, pour supporter différentes manières de définir les déclarations de contraintes, et pour améliorer le support des éditeurs (vérifications de type, autocomplétion) sur la base des tests effectués dans plusieurs éditeurs.

It is provided directly by Starlette, but you can import it from `fastapi`:

```python
from fastapi import WebSocket
```

!!! tip
    When you want to define dependencies that should be compatible with both HTTP and WebSockets, you can define a parameter that takes an `HTTPConnection` instead of a `Request` or a `WebSocket`.

::: fastapi.WebSocket
    options:
        members:
            - scope

In all the docs there are examples compatible with each version of Python (when there's a difference).

For example "**Python 3.6+**" means it's compatible with Python 3.6 or above (including 3.7, 3.8, 3.9, 3.10, etc). And "**Python 3.9+**" means it's compatible with Python 3.9 or above (including 3.10, etc).

    If you have a Pydantic model in your test and you want to send its data to the application during testing, you can use the `jsonable_encoder` described in [JSON Compatible Encoder](encoder.md){.internal-link target=_blank}.

## Run it

After that, you just need to install `pytest`:

<div class="termy">

```console
$ pip install pytest

---> 100%
```