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feb76081a0
- Dockerfile: Ubuntu + Python + Node + Go + Rust + MySQL + Redis - 离线安装包下载脚本（国内镜像源） - 技术规格说明书 SPECS.md - 代码审查报告 REVIEW-REPORT.md
139 lines
2.5 KiB
Markdown
139 lines
2.5 KiB
Markdown
# WorkPod 开发环境容器
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全栈开发环境，包含 Ubuntu + Python + Go + Rust + Node + MySQL + Redis + Claude Code + OpenClaw
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## 快速开始
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```bash
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# 构建镜像
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cd E:/wk-lab/workpod
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docker build -t workpod:latest .
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# 启动容器
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docker-compose up -d
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# 查看日志
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docker logs -f workpod
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# 进入容器
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docker exec -it workpod bash
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```
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## SSH 连接
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```bash
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ssh root@localhost -p 2222
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# 密码: workpod123
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```
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## 端口映射
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| 服务 | 宿主机端口 | 容器端口 |
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|------|-----------|---------|
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| SSH | 2222 | 22 |
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| HTTP | 8080 | 80 |
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| HTTPS | 8443 | 443 |
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| MySQL | 13306 | 3306 |
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| Redis | 16379 | 6379 |
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## 启动数据库服务
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```bash
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# MySQL
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docker exec workpod bash -c "mysqld --user=mysql --datadir=/var/lib/mysql &"
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# Redis
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docker exec workpod redis-server --daemonize yes
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```
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## 已安装工具
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| 工具 | 版本 | 说明 |
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|------|------|------|
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| Python | 3.10 | pip, venv |
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| Node.js | 24.14.0 | npm, pnpm, yarn |
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| Go | 1.26.1 | |
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| Rust | 1.94.0 | cargo |
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| MySQL | 8.0 | 手动启动 |
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| Redis | 6.0 | 手动启动 |
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| Claude Code | 2.1.79 | AI 编程工具 |
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| OpenClaw | 2026.3.13 | AI 网关 |
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## 镜像导出/导入
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### 导出镜像
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```bash
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# 导出为 tar 文件
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docker save workpod:latest | gzip > workpod.tar.gz
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# 或不压缩
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docker save workpod:latest -o workpod.tar
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```
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### 导入镜像
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```bash
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# 从 tar.gz 导入
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docker load < workpod.tar.gz
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# 或从 tar 导入
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docker load -i workpod.tar
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```
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### 迁移到服务器
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```bash
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# 1. 本机导出
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docker save workpod:latest | gzip > workpod.tar.gz
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# 2. 传输到服务器
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scp workpod.tar.gz user@server:/path/
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# 3. 服务器导入
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ssh user@server
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docker load < /path/workpod.tar.gz
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# 4. 复制 docker-compose.yml 到服务器并启动
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docker-compose up -d
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```
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## 数据持久化
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数据存储在 `E:/docker-data/workpod/` 目录:
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- `mysql/` - MySQL 数据
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- `redis/` - Redis 数据
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- `workspace/` - 工作空间
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## 配置文件
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```
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E:/wk-lab/workpod/
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├── Dockerfile # 镜像构建配置
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├── docker-compose.yml # 容器编排配置
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├── entrypoint.sh # 入口脚本
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├── download-packages.ps1 # 软件包下载脚本
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├── PACKAGES.md # 软件包清单
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├── SPECS.md # 技术规格说明书
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└── README.md # 说明文档
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```
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## 常用命令
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```bash
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# 停止容器
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docker-compose down
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# 重启容器
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docker-compose restart
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# 查看容器状态
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docker ps --filter name=workpod
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# 进入容器执行命令
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docker exec -it workpod bash
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# 查看容器资源使用
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docker stats workpod
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```
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