<div class="termy">

```console
$ typer --install-completion

zsh completion installed in /home/user/.bashrc.
Completion will take effect once you restart the terminal.
```

</div>

### Docs Structure

The documentation uses <a href="https://www.mkdocs.org/" class="external-link" target="_blank">MkDocs</a>.

And there are extra tools/scripts in place to handle translations in `./scripts/docs.py`.

!!! tip

The `TestClient` is based on <a href="https://www.python-httpx.org" class="external-link" target="_blank">HTTPX</a>, and luckily, we can use it directly to test the API.

## Example

For a simple example, let's consider a file structure similar to the one described in [Bigger Applications](../tutorial/bigger-applications.md){.internal-link target=_blank} and [Testing](../tutorial/testing.md){.internal-link target=_blank}:

```
.
├── app
│   ├── __init__.py

### Project file structure

Let's say your project file structure looks like this:

```
.
├── app
│   ├── __init__.py
│   ├── main.py
```

Now create a directory to store those static files.

Your new file structure could look like this:

```
.
├── app
│   ├── __init__.py
│   ├── main.py
└── static/
```

    ```Python hl_lines="9  14"
    {!> ../../../docs_src/dependencies/tutorial006.py!}
    ```

## Dependencies for a group of *path operations*

So, we are going to focus only on the differences.

## File structure

Let's say you have a directory named `my_super_project` that contains a sub-directory called `sql_app` with a structure like this:

```
.
└── sql_app
    ├── __init__.py
    ├── crud.py
    ├── database.py
    ├── main.py
    └── schemas.py
```

This is almost the same structure as we had for the SQLAlchemy tutorial.

    * Because pydantic data structures are just instances of classes you define; auto-completion, linting, mypy and your intuition should all work properly with your validated data.
* Validate **complex structures**:
    * Use of hierarchical Pydantic models, Python `typing`’s `List` and `Dict`, etc.

<font color="#3465A4">INFO    </font> Resolved absolute path <font color="#75507B">/home/user/code/awesomeapp/</font><font color="#AD7FA8">main.py</font>
<font color="#3465A4">INFO    </font> Searching for package file structure from directories with <font color="#3465A4">__init__.py</font> files
<font color="#3465A4">INFO    </font> Importing from <font color="#75507B">/home/user/code/</font><font color="#AD7FA8">awesomeapp</font>

# Codes HTTP supplémentaires

Par défaut, **FastAPI** renverra les réponses à l'aide d'une structure de données `JSONResponse`, en plaçant la réponse de votre  *chemin d'accès* à l'intérieur de cette `JSONResponse`.

Il utilisera le code HTTP par défaut ou celui que vous avez défini dans votre *chemin d'accès*.

## Codes HTTP supplémentaires

    ```Python hl_lines="8-11"
    {!> ../../../docs_src/dependencies/tutorial001.py!}
    ```

That's it.

**2 lines**.

And it has the same shape and structure that all your *path operation functions* have.

You can think of it as a *path operation function* without the "decorator" (without the `@app.get("/some-path")`).

And it can return anything you want.

This way, its schema will show up in the API docs user interface:

<img src="/img/tutorial/dataclasses/image01.png">

## Dataclasses in Nested Data Structures

You can also combine `dataclasses` with other type annotations to make nested data structures.

In some cases, you might still have to use Pydantic's version of `dataclasses`. For example, if you have errors with the automatically generated API documentation.