{
          "version_info": "2022-03-04T10:22:24Z/54",
          "route_config": {
            "@type": "type.googleapis.com/envoy.config.route.v3.RouteConfiguration",
            "name": "http.8080",
            "virtual_hosts": [
              {
                "name": "*:80",
                "domains": [
                  "*"
                ],
                "routes": [
                  {

////

//// tab | 🐍 3️⃣.1️⃣0️⃣ & 🔛

```Python hl_lines="7"
{!> ../../docs_src/query_params_str_validations/tutorial011_py310.py!}
```

////

⤴️, ⏮️ 📛 💖:

```
http://localhost:8000/items/?q=foo&q=bar
```

👆 🔜 📨 💗 `q` *🔢 🔢'* 💲 (`foo` & `bar`) 🐍 `list` 🔘 👆 *➡ 🛠️ 🔢*, *🔢 🔢* `q`.

, 📨 👈 📛 🔜:

```JSON
{
  "q": [
    "foo",
    "bar"
  ]
}

---> 100%
```

</div>

## Démarrer le conteneur Docker

* Exécutez un conteneur basé sur votre image :

<div class="termy">

```console
$ docker run -d --name mycontainer -p 80:80 myimage
```

</div>

Vous disposez maintenant d'un serveur FastAPI optimisé dans un conteneur Docker. Configuré automatiquement pour votre
serveur actuel (et le nombre de cœurs du CPU).

## Vérifier

🙆 💼, 👆 🔜 🏃 ⚫️ 💖 👉:

<div class="termy">

```console
$ uvicorn main:app --host 0.0.0.0 --port 8080 --workers 4
<font color="#A6E22E">INFO</font>:     Uvicorn running on <b>http://0.0.0.0:8080</b> (Press CTRL+C to quit)
<font color="#A6E22E">INFO</font>:     Started parent process [<font color="#A1EFE4"><b>27365</b></font>]

	store      store.Store[event.Event]
	loggerOnce logger.LogOnce
	cancel     context.CancelFunc
	cancelCh   <-chan struct{}

	addr string // full address ip/dns with a port number, e.g.  x.x.x.x:8080
}

// ID - returns target ID.
func (target *WebhookTarget) ID() event.TargetID {
	return target.id
}

// Name - returns the Name of the target.
func (target *WebhookTarget) Name() string {

            task.setDescription("Runs a local webserver to serve generated documentation.");
            task.setGroup("documentation");

            int webserverPort = 8000;
            task.getJavaLauncher().set(
                task.getProject().getExtensions().getByType(JavaToolchainService.class)
                    .launcherFor(spec -> spec.getLanguageVersion().set(JavaLanguageVersion.of(21)))

它可能看起来是这样的:

```JSON  hl_lines="7"
{
  "name": "frontend-app",
  "version": "1.0.0",
  "description": "",
  "main": "index.js",
  "scripts": {
    "generate-client": "openapi-ts --input http://localhost:8000/openapi.json --output ./src/client --client axios"
  },
  "author": "",
  "license": "",
  "devDependencies": {
    "@hey-api/openapi-ts": "^0.27.38",
    "typescript": "^4.6.2"
  }
}
```

例如，要声明一个可在 URL 中出现多次的查询参数 `q`，你可以这样写：

```Python hl_lines="9"
{!../../docs_src/query_params_str_validations/tutorial011.py!}
```

然后，输入如下网址：

```
http://localhost:8000/items/?q=foo&q=bar
```

你会在*路径操作函数*的*函数参数* `q` 中以一个 Python `list` 的形式接收到*查询参数* `q` 的多个值（`foo` 和 `bar`）。

因此，该 URL 的响应将会是：

```JSON
{
  "q": [
    "foo",
    "bar"
  ]
}
```

        }

        //  <proxies>
        //    <proxy>
        //      <active>true</active>
        //      <protocol>http</protocol>
        //      <host>proxy.somewhere.com</host>
        //      <port>8080</port>
        //      <username>proxyuser</username>
        //      <password>somepassword</password>
        //      <nonProxyHosts>www.google.com|*.somewhere.com</nonProxyHosts>
        //    </proxy>

        assertEquals("4.0/8.0 kB", format.formatProgress(_4000_bytes, _8000_bytes));
        assertEquals("8.0 kB", format.formatProgress(_8000_bytes, _8000_bytes));
        assertEquals("8.0/50 kB", format.formatProgress(_8000_bytes, _50_kilobytes));
        assertEquals("16/50 kB", format.formatProgress(2L * _8000_bytes, _50_kilobytes));
        assertEquals("50 kB", format.formatProgress(_50_kilobytes, _50_kilobytes));