* <ul>
 * <li>Query basic OS information like name, architecture, and version</li>
 * <li>Determine the OS family (e.g., Windows, Unix, Mac)</li>
 * <li>Check if the current OS is Windows-based</li>
 * </ul>
 * <p>
 * The service implementation uses system properties to detect OS characteristics:
 * <ul>
 * <li>os.name: The operating system name</li>
 * <li>os.arch: The operating system architecture</li>

```Dockerfile
FROM tiangolo/uvicorn-gunicorn-fastapi:python3.7

COPY ./app /app/app
```

### Raspberry Pi et autres architectures

Si vous utilisez Docker sur un Raspberry Pi (qui a un processeur ARM) ou toute autre architecture, vous pouvez créer un `Dockerfile` à partir de zéro, basé sur une image de base Python (qui est multi-architecture) et utiliser Uvicorn seul.

Dans ce cas, votre `Dockerfile` pourrait ressembler à ceci :

```Dockerfile

```bash
# Generate code coverage reports
mvn jacoco:report

# License header validation
mvn apache-rat:check

# API compatibility checking
mvn clirr:check
```

### Architecture Overview

The library follows a layered architecture:

- **Context Layer**: `CIFSContext` interface provides the main entry point
- **Resource Layer**: `SmbResource` interface represents SMB network resources  

Package: fess
Version: [[version]]
Architecture: all
Maintainer: Fess Team
Depends: libc6, adduser
Section: web
Priority: optional
Homepage: https://github.com/codelibs/fess
Description: Enterprise Search Server: Fess

 */

/**
 * Defines core service interfaces that provide essential Maven functionality such as
 * artifact resolution, dependency management, and build execution. These services
 * form the backbone of Maven's extensible architecture.
 *
 * @since 4.0.0
 */

   *     using it, it is probably not doing what you want.
   */
  @Deprecated
  JAVA_EXT_DIRS("java.ext.dirs"),

  /** Operating system name. */
  OS_NAME("os.name"),

  /** Operating system architecture. */
  OS_ARCH("os.arch"),

  /** Operating system version. */
  OS_VERSION("os.version"),

  /** File separator ("/" on UNIX). */
  FILE_SEPARATOR("file.separator"),

# Génération de projets - Modèle

Vous pouvez utiliser un générateur de projet pour commencer, qui réalisera pour vous la mise en place de bases côté architecture globale, sécurité, base de données et premières routes d'API.

Un générateur de projet fera toujours une mise en place très subjective que vous devriez modifier et adapter suivant vos besoins, mais cela reste un bon point de départ pour vos projets.

## Full Stack FastAPI PostgreSQL

        # On Linux:
        $ cat /etc/os-release
        # paste output here
        $ uname -a
        # paste output here

        # On Windows:
        C:\> wmic os get Caption, Version, BuildNumber, OSArchitecture
        # paste output here
        ```

        </details>

  - type: textarea
    id: installer
    attributes:
      label: Install tools
      value: |
        <details>

///

/// tip

🚥 👆 💭, "📊", "🎓", &amp; "🍏" 📛 🎰 🏫 <abbr title="Technically, Deep Learning model architectures">🏷</abbr>.

///

### 📣 *➡ 🔢*

⤴️ ✍ *➡ 🔢* ⏮️ 🆎 ✍ ⚙️ 🔢 🎓 👆 ✍ (`ModelName`):

{* ../../docs_src/path_params/tutorial005.py hl[16] *}

### ✅ 🩺

///

/// tip

If you are wondering, "AlexNet", "ResNet", and "LeNet" are just names of Machine Learning <abbr title="Technically, Deep Learning model architectures">models</abbr>.

///

### Declare a *path parameter* { #declare-a-path-parameter }

Then create a *path parameter* with a type annotation using the enum class you created (`ModelName`):