Les données sont calculées chaque mois, vous pouvez lire le <a href="https://github.com/tiangolo/fastapi/blob/master/.github/actions/people/app/main.py" class="external-link" target="_blank">code source ici</a>.

# FastAPI CLI

**FastAPI CLI** is a command line program `fastapi` that you can use to serve your FastAPI app, manage your FastAPI project, and more.

When you install FastAPI (e.g. with `pip install fastapi`), it includes a package called `fastapi-cli`, this package provides the `fastapi` command in the terminal.

To run your FastAPI app for development, you can use the `fastapi dev` command:

<div class="termy">

```console

                        "description": "Successful Response",
                        "content": {
                            "application/json": {



...
```

#### Para que serve o OpenAPI

O *schema* OpenAPI é o que possibilita os dois sistemas de documentação interativos mostrados.

Usados por FastAPI / Starlette:

* <a href="https://www.uvicorn.org" target="_blank"><code>uvicorn</code></a> - para o servidor que carrega e serve sua aplicação.
* <a href="https://github.com/ijl/orjson" target="_blank"><code>orjson</code></a> - Necessário se você quer utilizar `ORJSONResponse`.

```

</div>

这样会对每一种语言构建一个独立的文档站点，并最终把这些站点全部打包输出到 `./site/` 目录。



然后你可以使用命令 `serve` 来运行生成的站点：

<div class="termy">

```console
// Use the command "serve" after running "build-all"
$ python ./scripts/docs.py serve

Warning: this is a very simple server. For development, use mkdocs serve instead.
This is here only to preview a site with translations already built.

Ensuite, vous pouvez servir cela avec le commandement `serve`:

<div class="termy">

```console
// Use the command "serve" after running "build-all"
$ python ./scripts/docs.py serve

Warning: this is a very simple server. For development, use mkdocs serve instead.
This is here only to preview a site with translations already built.

    title: Building simple E-Commerce with NuxtJS and FastAPI
  - author: Rodrigo Arenas
    author_link: https://rodrigo-arenas.medium.com/
    link: https://medium.com/analytics-vidhya/serve-a-machine-learning-model-using-sklearn-fastapi-and-docker-85aabf96729b
    title: "Serve a machine learning model using Sklearn, FastAPI and Docker"
  - author: Yashasvi Singh
    author_link: https://hashnode.com/@aUnicornDev

E esses modelos estão compartilhando muitos dos dados e duplicando nomes e tipos de atributos.

Nós poderíamos fazer melhor.

Podemos declarar um modelo `UserBase` que serve como base para nossos outros modelos. E então podemos fazer subclasses desse modelo que herdam seus atributos (declarações de tipo, validação, etc.).

Toda conversão de dados, validação, documentação, etc. ainda funcionará normalmente.

                **Note**: you probably shouldn't use this parameter, it is inherited
                from Starlette and supported for compatibility.

                ---

                A list of routes to serve incoming HTTP and WebSocket requests.
                """
            ),
            deprecated(
                """
                You normally wouldn't use this parameter with FastAPI, it is inherited

    Takes an optional LANG argument with the name of the language to serve, by default
    en.
    """
    # Enable line numbers during local development to make it easier to highlight
    os.environ["LINENUMS"] = "true"
    if lang is None:
        lang = "en"
    lang_path: Path = docs_path / lang
    os.chdir(lang_path)
    mkdocs.commands.serve.serve(dev_addr="127.0.0.1:8008")