L'option `--reload` consomme beaucoup plus de ressources, est plus instable, etc.

 Cela aide beaucoup pendant le **développement**, mais vous **ne devriez pas** l'utiliser en **production**.

///

## Hypercorn avec Trio

Starlette et **FastAPI** sont basés sur
<a href="https://anyio.readthedocs.io/en/stable/" class="external-link" target="_blank">AnyIO</a>, qui les rend

import jcifs.CIFSException;

/**
 * Default implementation of SMB3 compression service.
 *
 * Provides compression using Java's built-in deflate algorithm as a base
 * for LZ77-based compression. For production use, more specialized
 * implementations of LZNT1 and Pattern_V1 algorithms would be needed.
 */
public class DefaultCompressionService implements CompressionService {

INHERIT: ../en/mkdocs.maybe-insiders.yml
site_name: FastAPI
site_description: FastAPI framework, high performance, easy to learn, fast to code, ready for production
site_url: https://fastapi.tiangolo.com/
theme:
  name: material
  custom_dir: ../en/overrides
  palette:
  - media: (prefers-color-scheme)
    toggle:
      icon: material/lightbulb-auto
      name: Switch to light mode
  - media: '(prefers-color-scheme: light)'
    scheme: default

But you can also provide other alternative `servers`, for example if you want *the same* docs UI to interact with both a staging and a production environment.

If you pass a custom list of `servers` and there's a `root_path` (because your API lives behind a proxy), **FastAPI** will insert a "server" with this `root_path` at the beginning of the list.

For example:

* SQLite
* Oracle
* Microsoft SQL Server, etc.

In this example, we'll use **SQLite**, because it uses a single file and Python has integrated support. So, you can copy this example and run it as is.

Later, for your production application, you might want to use a database server like **PostgreSQL**.

/// tip

```console
$ <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:solid">main.py</u>

  <span style="background-color:#009485"><font color="#D3D7CF"> FastAPI </font></span>  Starting production server 🚀

             Searching for package file structure from directories with
             <font color="#3465A4">__init__.py</font> files

        {
            "url": "https://stag.example.com",
            "description": "Staging environment"
        },
        {
            "url": "https://prod.example.com",
            "description": "Production environment"
        }
    ],
    "paths": {
            // More stuff here
    }
}
```

/// tip

👀 🚘-🏗 💽 ⏮️ `url` 💲 `/api/v1`, ✊ ⚪️➡️ `root_path`.

///

[**sandbox**](https://developers.google.com/code-sandboxing). Memory corruptions
in TensorFlow ops can be recognized as security issues only if they are
reachable and exploitable through production-grade, benign models.

### Compilation

Compiling models via the recommended entry points described in
[XLA](https://www.tensorflow.org/xla) and
[JAX](https://jax.readthedocs.io/en/latest/jax-101/02-jitting.html)

 <span style="background-color:#C4A000"><font color="#2E3436">│                                                     │</font></span>
 <span style="background-color:#C4A000"><font color="#2E3436">│  Running in development mode, for production use:   │</font></span>
 <span style="background-color:#C4A000"><font color="#2E3436">│                                                     │</font></span>

**build** the client, it will error out if you have any **mismatch** in the data used.

So, you would **detect many errors** very early in the development cycle instead of having to wait for the errors to show up to your final users in production and then trying to debug where the problem is. ✨...