* **Aucun compromis** avec les bases de données, les frontends, etc. Mais une intégration facile avec n'importe lequel d'entre eux.

### "Plug-ins" illimités

Ou, en d'autres termes, pas besoin d'eux, importez le code que vous voulez et utilisez le.

## 安裝

<div class="termy">

```console
$ pip install fastapi

---> 100%
```

</div>

你同時也會需要 ASGI 伺服器用於生產環境，像是 <a href="https://www.uvicorn.org" class="external-link" target="_blank">Uvicorn</a> 或 <a href="https://github.com/pgjones/hypercorn" class="external-link" target="_blank">Hypercorn</a>。

<div class="termy">

```console
$ pip install "uvicorn[standard]"

            result.setCreatedTime(DfTypeUtil.toLong(source.get("createdTime")));
            result.setSortOrder(DfTypeUtil.toInteger(source.get("sortOrder")));
            result.setTerm(DfTypeUtil.toString(source.get("term")));
            result.setUpdatedBy(DfTypeUtil.toString(source.get("updatedBy")));
            result.setUpdatedTime(DfTypeUtil.toLong(source.get("updatedTime")));

	exit $return
	;;		
  stop)
	log_daemon_msg "Stopping $DESC"

	if [ -f "$PID_FILE" ]; then 
		start-stop-daemon --stop --pidfile "$PID_FILE" \
			--user "$FESS_USER" \
			--quiet \
			--retry forever/TERM/20 > /dev/null
		if [ $? -eq 1 ]; then
			log_progress_msg "$DESC is not running but pid file exists, cleaning up"
		elif [ $? -eq 3 ]; then
			PID="`cat $PID_FILE`"
			log_failure_msg "Failed to stop $DESC (pid $PID)"

            result.setCreatedTime(DfTypeUtil.toLong(source.get("createdTime")));
            result.setQueries(toStringArray(source.get("queries")));
            result.setTerm(DfTypeUtil.toString(source.get("term")));
            result.setUpdatedBy(DfTypeUtil.toString(source.get("updatedBy")));
            result.setUpdatedTime(DfTypeUtil.toLong(source.get("updatedTime")));

covering security practices for the entirety of the TensorFlow ecosystem.

## TensorFlow models are programs

TensorFlow
[**models**](https://developers.google.com/machine-learning/glossary/#model) (to
use a term commonly used by machine learning practitioners) are expressed as
programs that TensorFlow executes. TensorFlow programs are encoded as
computation
[**graphs**](https://developers.google.com/machine-learning/glossary/#graph).

| `description` | `str` | Uma breve descrição da API. Pode usar Markdown. |
| `version` | `string` | A versão da API. Esta é a versão da sua aplicação, não do OpenAPI. Por exemplo, `2.5.0`. |
| `terms_of_service` | `str` | Uma URL para os Termos de Serviço da API. Se fornecido, deve ser uma URL. |

**FastAPI CLI** 是一个命令行程序，你可以用它来部署和运行你的 FastAPI 应用程序，管理你的 FastAPI 项目，等等。

当你安装 FastAPI 时（例如使用 `pip install FastAPI` 命令），会包含一个名为 `fastapi-cli` 的软件包，该软件包在终端中提供 `fastapi` 命令。

要在开发环境中运行你的 FastAPI 应用，你可以使用 `fastapi dev` 命令：

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> dev <u style="text-decoration-style:single">main.py</u>
<font color="#3465A4">INFO    </font> Using path <font color="#3465A4">main.py</font>

crawler.document.use.site.encoding.on.english=false
crawler.document.append.data=true
crawler.document.append.filename=false
crawler.document.max.alphanum.term.size=20
crawler.document.max.symbol.term.size=10
crawler.document.duplicate.term.removed=false

            result.setMaxSize(DfTypeUtil.toInteger(source.get("maxSize")));
            result.setQuery(DfTypeUtil.toString(source.get("query")));
            result.setTerm(DfTypeUtil.toString(source.get("term")));
            result.setUpdatedBy(DfTypeUtil.toString(source.get("updatedBy")));
            result.setUpdatedTime(DfTypeUtil.toLong(source.get("updatedTime")));