* More advanced (but equally easy) techniques for declaring **deeply nested JSON models** (thanks to Pydantic).
* **GraphQL** integration with <a href="https://strawberry.rocks" class="external-link" target="_blank">Strawberry</a> and other libraries.
* Many extra features (thanks to Starlette) as:
    * **WebSockets**
    * extremely easy tests based on HTTPX and `pytest`
    * **CORS**

```Python hl_lines="1  7-12  19-20"
{!../../../docs_src/dataclasses/tutorial001.py!}
```

This is still supported thanks to **Pydantic**, as it has <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">internal support for `dataclasses`</a>.

### Tests

* Help me check that the PR has **tests**.

* Check that the tests **fail** before the PR. 🚨

* Then check that the tests **pass** after the PR. ✅

* Many PRs don't have tests, you can **remind** them to add tests, or you can even **suggest** some tests yourself. That's one of the things that consume most time and you can help a lot with that.

* More advanced (but equally easy) techniques for declaring **deeply nested JSON models** (thanks to Pydantic).
* **GraphQL** integration with <a href="https://strawberry.rocks" class="external-link" target="_blank">Strawberry</a> and other libraries.
* Many extra features (thanks to Starlette) as:
    * **WebSockets**
    * extremely easy tests based on HTTPX and `pytest`
    * **CORS**

Most tasks that are used to build Gradle support the configuration cache, but some don't. For example, building the documentation currently requires you to disable the configuration cache.

To disable the configuration cache, run the build with `--no-configuration-cache`.

Tasks known to have problems are listed in the build logic. You can find this list at:

    val connect = planConnect()

    // Now that we have a set of IP addresses, make another attempt at getting a connection from
    // the pool. We have a better chance of matching thanks to connection coalescing.
    val pooled2 = planReusePooledConnection(connect, connect.routes)
    if (pooled2 != null) return pooled2

    return connect
  }

  /**

# Testing

Thanks to <a href="https://www.starlette.io/testclient/" class="external-link" target="_blank">Starlette</a>, testing **FastAPI** applications is easy and enjoyable.

It is based on <a href="https://www.python-httpx.org" class="external-link" target="_blank">HTTPX</a>, which in turn is designed based on Requests, so it's very familiar and intuitive.

And as you can have parallelism and asynchronicity at the same time, you get higher performance than most of the tested NodeJS frameworks and on par with Go, which is a compiled language closer to C <a href="https://www.techempower.com/benchmarks/#section=data-r17&hw=ph&test=query&l=zijmkf-1" class="external-link" target="_blank">(all thanks to Starlette)</a>.

### Is concurrency better than parallelism?

Nope! That's not the moral of the story.

![ReDoc](https://fastapi.tiangolo.com/img/index/index-06-redoc-02.png)

### Just Modern Python

It's all based on standard **Python type** declarations (thanks to Pydantic). No new syntax to learn. Just standard modern Python.

# Body - Nested Models

With **FastAPI**, you can define, validate, document, and use arbitrarily deeply nested models (thanks to Pydantic).

## List fields

You can define an attribute to be a subtype. For example, a Python `list`:

=== "Python 3.10+"

    ```Python hl_lines="12"
    {!> ../../../docs_src/body_nested_models/tutorial001_py310.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="14"