It uses the information from Webargs and Marshmallow to automatically generate OpenAPI schemas, using APISpec.

It's a great tool, very underrated. It should be way more popular than many Flask plug-ins out there. It might be due to its documentation being too concise and abstract.

This solved having to write YAML (another syntax) inside of Python docstrings.

This schema definition includes your API paths, the possible parameters they take, etc.

#### Data "schema"

The term "schema" might also refer to the shape of some data, like a JSON content.

In that case, it would mean the JSON attributes, and data types they have, etc.

#### OpenAPI and JSON Schema

This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.

!!! info
    Keep in mind that dataclasses can't do everything Pydantic models can do.

    So, you might still need to use Pydantic models.

    But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

## Dataclasses in `response_model`

### Disable Response Model

Continuing from the example above, you might not want to have the default data validation, documentation, filtering, etc. that is performed by FastAPI.

But you might want to still keep the return type annotation in the function to get the support from tools like editors and type checkers (e.g. mypy).

    * **TypeScript**.
    * Docker-Server basierend auf **Nginx** (konfiguriert, um gut mit Vue-Router zu funktionieren).
    * Mehrstufigen Docker-Erstellung, sodass Sie kompilierten Code nicht speichern oder committen müssen.
    * Frontend-Tests, welche zur Erstellungszeit ausgeführt werden (können auch deaktiviert werden).

## Separating tests

In a real application, you probably would have your tests in a different file.

And your **FastAPI** application might also be composed of several files/modules, etc.

### **FastAPI** app file

Let's say you have a file structure as described in [Bigger Applications](bigger-applications.md){.internal-link target=_blank}:

```
.

### Docs

* 📝 Update docs about async and response-model with more gender neutral language. PR [#1869](https://github.com/tiangolo/fastapi/pull/1869) by [@Edward-Knight](https://github.com/Edward-Knight).

### Translations

* 🌐 Add Russian translation for `docs/python-types.md`. PR [#3039](https://github.com/tiangolo/fastapi/pull/3039) by [@dukkee](https://github.com/dukkee).

    position: relative;
    -webkit-box-sizing: border-box;
            box-sizing: border-box;
    line-height: 1.2;
}

[data-termynal]:before {
    content: '';
    position: absolute;
    top: 15px;
    left: 15px;
    display: inline-block;
    width: 15px;
    height: 15px;
    border-radius: 50%;
    /* A little hack to display the window buttons in one pseudo element. */
    background: #d9515d;

Or it might be the case that you just prefer to take other courses because they adapt better to your learning style.

---

If you just don't know, use normal `def`.

---

**Note**: You can mix `def` and `async def` in your *path operation functions* as much as you need and define each one using the best option for you. FastAPI will do the right thing with them.

Anyway, in any of the cases above, FastAPI will still work asynchronously and be extremely fast.

But by following the steps above, it will be able to do some performance optimizations.