# claude-code-python_rewrite **Repository Path**: zhangbo2008/claude-code-python_rewrite ## Basic Information - **Project Name**: claude-code-python_rewrite - **Description**: No description available - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2026-05-03 - **Last Updated**: 2026-05-03 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README 使用方法: 1. 跟README.md同级目录下运行: python -m src.cli login # 这一步我已经配置号智普免费大模型api了. 用的zhipu 4.7 flash版本, 所以这边一步不需要配置也可以运行, 也可以配置成自己的模型. 2. python -m src.cli # 启动 REPL # 下面开始读这个代码.学习claudecode 的harness思路. 1.首先运行counter.py 能看到代码行数: # 统计一下这个python版本的claudecode 的代码行数 # 总代码行数: 17781 绝对能分析完了. 入口是 src\cli.py 199行会先读取大模型提供商.-->config.py:59 读取配置文件, 拿到token之后base64解码, 得到api key. 之后进入core.py 代码执行618行run函数. 他的run函数 看src\repl\core.py ClawdREPL类是 命令行交互的类. 618行是run函数, 运行REPL. src\command_system\registry.py 命令的注册器, 也是管理器.可以注册命令, 查找命令, 列出命令等.这套代码使用命令执行时候, 先去这个命令管理器里面去搜索命令, 然后再执行命令. src\bootstrap_graph.py 项目的说明文档. src\commands.py 执行镜像的命令. 执行镜像仓库ts的代码. src\context.py 路径的上下文. PortContext,专门用来统一存放和管理一组相关的路径、文件数量、状态信息。 src\permissions.py 判断工具是否可以使用. src\port_manifest.py 文件数量统计,清单. src\repl.py: clawd codex 的repl. 另一种模仿codex的repl src\runtime.py 运行时环境的上下文. src\token_estimation.py token使用量的记录. 剩下的是src里面文件夹部分. 都是模块部分.被上面的core.py调用. src\agent\conversation.py 用户对话类.用来记录一次对话里面的信息存储. 存到内存. src\agent\session.py 用户对话的磁盘保存. 存到硬盘. src\command_system\engine.py 命令执行的引擎. src\command_system\registry.py 命令注册器. 命令的添加删除查询. src\command_system\types.py 一种命令是提示词命令(用参数替换拼接完提示词之后给大模型), 一种是本地命令.
**English** | [中文](#中文版) | [Français](docs/i18n/README_FR.md) | [Русский](docs/i18n/README_RU.md) | [हिन्दी](docs/i18n/README_HI.md) | [العربية](docs/i18n/README_AR.md) | [Português](docs/i18n/README_PT.md) # 🚀 Claude Code Python **A Complete Python Reimplementation Based on Real Claude Code Source** *From TypeScript Source → Rebuilt in Python with ❤️* *** [![GitHub stars](https://img.shields.io/github/stars/GPT-AGI/Clawd-Code?style=for-the-badge&logo=github&color=yellow)](https://github.com/GPT-AGI/Clawd-Code/stargazers) [![GitHub forks](https://img.shields.io/github/forks/GPT-AGI/Clawd-Code?style=for-the-badge&logo=github&color=blue)](https://github.com/GPT-AGI/Clawd-Code/network/members) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg?style=for-the-badge)](https://opensource.org/licenses/MIT) [![Python 3.10+](https://img.shields.io/badge/python-3.10+-blue.svg?style=for-the-badge&logo=python&logoColor=white)](https://www.python.org/downloads/) **🔥 Active Development • New Features Weekly 🔥**
*** ## 🎯 Why Clawd Code? **Clawd Code** is a **production-oriented Python rebuild of Claude Code**, ported from the **real TypeScript architecture** and shipped as a **working CLI agent**, not just a source dump. - **Real Agent Runtime** — tool-calling loop, streaming REPL, session history, and multi-turn execution - **High-Fidelity Port** — keeps the original Claude Code architecture while adapting it to idiomatic Python - **Built to Hack On** — readable Python codebase, rich tests, and markdown-driven skill extensibility
**Token Streaming + Tool-Aware Agent Loop** ![Streaming Agent Experience](assets/clawd-stream.gif) **Programmable Skill Runtime with Tool Sandboxing** ![Skills (Slash Commands)](assets/clawd-code-skill.png) **Instant Web Fetch for External Context** ![Web Fetch](assets/claude-code-webfetch.png) **Real CLI • Real Usage • Real Community**
**A real Claude Code-style terminal workflow in Python: stream replies, call tools, fetch context, and extend behavior with skills.** **🚀 Try it now! Fork it, modify it, make it yours! Pull requests welcome!** *** ## ⭐ Star History Star History Chart ## ✨ Features ### Streaming Agent Experience ```text >>> /stream on >>> Explain tests/test_agent_loop.py [streaming answer...] • Read (tests/test_agent_loop.py) running... ↳ lines 1-180 >>> /render-last ``` - True API streaming for direct replies plus richer streaming during tool-driven agent loops - Built-in `/stream` toggle for live output and `/render-last` for clean Markdown re-rendering on demand - Designed for real terminal demos: streaming text, visible tool activity, and stable fallback behavior ### Programmable Skill Runtime ```md --- description: Explain code with diagrams and analogies allowed-tools: - Read - Grep - Glob arguments: [path] --- Explain the code in $path. Start with an analogy, then draw a diagram. ``` - Markdown-based `SKILL.md` slash commands - Supports project skills, user skills, named arguments, and tool limits ### Multi-Provider Support ```python providers = ["Anthropic Claude", "OpenAI GPT", "Zhipu GLM"] # + easy to extend ``` ### Interactive REPL ```text >>> Hello! Assistant: Hi! I'm Clawd Codex, a Python reimplementation... >>> /help # Show commands >>> / # Show all commands & skills >>> /save # Save session >>> /multiline # Multi-paragraph input >>> Tab # Auto-complete >>> /explain-code qsort.py # Run a skill ``` ### Complete CLI ```bash clawd # Start REPL clawd login # Configure API clawd --version # Check version clawd config # View settings ``` *** ## 📊 Status | Component | Status | Count | | ------------- | ---------- | --------- | | REPL Commands | ✅ Complete | 6+ built-ins | | Tool System | ✅ Complete | 30+ tools | | Automated Tests | ✅ Present | Core suites for skills, providers, REPL, tools, context | | Documentation | ✅ Complete | 10+ docs | ### Core Systems | System | Status | Description | |--------|--------|-------------| | CLI Entry | ✅ | `clawd`, `login`, `config`, `--version` | | Interactive REPL | ✅ | Rich interactive output, history, tab completion, multiline | | Multi-Provider | ✅ | Anthropic, OpenAI, GLM support | | Session Persistence | ✅ | Save/load sessions locally | | Agent Loop | ✅ | Tool calling loop implementation | | Skill System | ✅ | SKILL.md-based slash-command skills with args + tool limits | | Context Building | 🟡 | Initial prompt injection for workspace, git, and CLAUDE.md; deeper project understanding still needed | | Permission System | 🟡 | Framework exists, needs integration | ### Tool System (30+ Tools Implemented) | Category | Tools | Status | |----------|-------|--------| | File Operations | Read, Write, Edit, Glob, Grep | ✅ Complete | | System | Bash execution | ✅ Complete | | Web | WebFetch, WebSearch | ✅ Complete | | Interaction | AskUserQuestion, SendMessage | ✅ Complete | | Task Management | TodoWrite, TaskManager, TaskStop | ✅ Complete | | Agent Tools | Agent, Brief, Team | ✅ Complete | | Configuration | Config, PlanMode, Cron | ✅ Complete | | MCP | MCP tools and resources | ✅ Complete | | Others | LSP, Worktree, Skill, ToolSearch | ✅ Complete | ### Roadmap Progress - ✅ **Phase 0**: Installable, runnable CLI - ✅ **Phase 1**: Core Claude Code MVP experience - ✅ **Phase 2**: Real tool calling loop - 🟡 **Phase 3**: Context, permissions, recovery (in progress) - ⏳ **Phase 4**: MCP, plugins, extensibility - ⏳ **Phase 5**: Python-native differentiators **See [FEATURE_LIST.md](FEATURE_LIST.md) for detailed feature status and PR guidelines.** ## 🚀 Quick Start ### Install ```bash git clone https://github.com/GPT-AGI/Clawd-Code.git cd Clawd-Code # Create venv (uv recommended) uv venv --python 3.11 source .venv/bin/activate # Install uv pip install -r requirements.txt ``` ### Configure #### Option 1: Interactive (Recommended) ```bash python -m src.cli login ``` This flow will: 1. ask you to choose a provider: anthropic / openai / glm 2. ask for that provider's API key 3. optionally save a custom base URL 4. optionally save a default model 5. set the selected provider as default The configuration file is saved in in `~/.clawd/config.json`. Example structure: ```json { "default_provider": "glm", "providers": { "anthropic": { "api_key": "base64-encoded-key", "base_url": "https://api.anthropic.com", "default_model": "claude-sonnet-4-20250514" }, "openai": { "api_key": "base64-encoded-key", "base_url": "https://api.openai.com/v1", "default_model": "gpt-4" }, "glm": { "api_key": "base64-encoded-key", "base_url": "https://open.bigmodel.cn/api/paas/v4", "default_model": "glm-4.5" } } } ``` ### Run ```bash python -m src.cli # Start REPL python -m src.cli --help # Show help ``` **That's it!** Start chatting with AI in 3 steps. *** ## 💡 Usage ### REPL Commands | Command | Description | | ------------ | --------------------- | | `/` | Show commands & skills | | `/help` | Show all commands | | `/save` | Save session | | `/load ` | Load session | | `/multiline` | Toggle multiline mode | | `/clear` | Clear history | | `/exit` | Exit REPL | ### Skills (Slash Commands) Skills are markdown-based slash commands stored under `.clawd/skills`. Each skill lives in its own directory and must be named `SKILL.md`. **1) Create a project skill** Create: ```text /.clawd/skills//SKILL.md ``` Example: ```md --- description: Explains code with diagrams and analogies when_to_use: Use when explaining how code works allowed-tools: - Read - Grep - Glob arguments: [path] --- Explain the code in $path. Start with an analogy, then draw a diagram. ``` **2) Use it in the REPL** ```text ❯ / ❯ / ``` Example: ```text ❯ /explain-code qsort.py ``` **Notes** - User-level skills: `~/.clawd/skills//SKILL.md` - Tool limits: `allowed-tools` controls which tools the skill can use. - Arguments: use `$ARGUMENTS`, `$0`, `$1`, or named args like `$path` (from `arguments`). - Placeholder syntax: use `$path`, not `${path}`. *** ## 🎓 Why Clawd Codex? ### Based on Real Source Code - **Not a clone** — Ported from actual TypeScript implementation - **Architectural fidelity** — Maintains proven design patterns - **Improvements** — Better error handling, more tests, cleaner code ### Python Native - **Type hints** — Full type annotations - **Modern Python** — Uses 3.10+ features - **Idiomatic** — Clean, Pythonic code ### User Focused - **3-step setup** — Clone, configure, run - **Interactive config** — `clawd login` guides you - **Rich REPL** — Tab completion, syntax highlighting - **Session persistence** — Never lose your work *** ## 📦 Project Structure ```text Clawd-Code/ ├── src/ │ ├── cli.py # CLI entry │ ├── providers/ # LLM providers │ ├── repl/ # Interactive REPL │ ├── skills/ # SKILL.md loading and creation │ └── tool_system/ # Tool registry, loop, validation ├── tests/ # Core test suite ├── .clawd/ │ └── skills/ # Project-local custom skills └── FEATURE_LIST.md # Current feature status ``` *** ## 🤝 Contributing **We welcome contributions!** ```bash # Quick dev setup pip install -e .[dev] python -m pytest tests/ -v ``` See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines. *** ## 📖 Documentation - **[SETUP_GUIDE.md](docs/guide/SETUP_GUIDE.md)** — Detailed installation - **[CONTRIBUTING.md](CONTRIBUTING.md)** — Development guide - **[TESTING.md](docs/guide/TESTING.md)** — Testing guide - **[CHANGELOG.md](CHANGELOG.md)** — Version history *** ## ⚡ Performance - **Startup**: < 1 second - **Memory**: < 50MB - **Response**: Turn-based assistant output with Rich markdown rendering *** ## 🔒 Security ✅ **Basic Local Safety Practices** - No sensitive data in Git - API keys obfuscated in config - `.env` files ignored - Safe for local development workflows *** ## 📄 License MIT License — See [LICENSE](LICENSE) *** ## 🙏 Acknowledgments - Based on Claude Code TypeScript source - Independent educational project - Not affiliated with Anthropic ***
### 🌟 Show Your Support If you find this useful, please **star** ⭐ the repo! **Made with ❤️ by Clawd Code Team** [⬆ Back to Top](#-clawd-codex)
*** *** # 中文版
[English](#-clawd-codex) | **中文** | [Français](docs/i18n/README_FR.md) | [Русский](docs/i18n/README_RU.md) | [हिन्दी](docs/i18n/README_HI.md) | [العربية](docs/i18n/README_AR.md) | [Português](docs/i18n/README_PT.md) # 🚀 Claude Code Python **基于真实 Claude Code 源码的完整 Python 重实现** *从 TypeScript 源码 → 用 Python 重建 ❤️* *** [![GitHub stars](https://img.shields.io/github/stars/GPT-AGI/Clawd-Code?style=for-the-badge&logo=github&color=yellow)](https://github.com/GPT-AGI/Clawd-Code/stargazers) [![GitHub forks](https://img.shields.io/github/forks/GPT-AGI/Clawd-Code?style=for-the-badge&logo=github&color=blue)](https://github.com/GPT-AGI/Clawd-Code/network/members) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg?style=for-the-badge)](https://opensource.org/licenses/MIT) [![Python 3.10+](https://img.shields.io/badge/python-3.10+-blue.svg?style=for-the-badge&logo=python&logoColor=white)](https://www.python.org/downloads/) **🔥 活跃开发中 • 每周更新新功能 🔥** ## FLEXIBLE SKILL SYSTEMS **基于 Markdown 的斜杠技能系统,支持参数替换、工具限制,以及项目级 / 用户级技能加载。**
*** ## 🎯 为什么是 Clawd Code? **Clawd Code** 是一个面向真实使用的 **Claude Code Python 重构版**:它基于**真实 TypeScript 架构**移植而来,并且交付的是一个**可运行的 CLI Agent**,而不只是源码镜像。 - **真实 Agent Runtime** — 具备工具调用循环、流式 REPL、会话历史与多轮执行能力 - **高保真移植** — 尽可能保留 Claude Code 的原始架构,同时做符合 Python 风格的实现 - **适合继续开发** — 代码可读、测试完善,并支持基于 Markdown 的技能扩展
**Token Streaming + Tool-Aware Agent Loop** ![流式 Agent 演示](assets/clawd-stream.gif) **可编程 Skill Runtime 与工具沙箱** ![Skills(斜杠命令)](assets/clawd-code-skill.png) **Instant Web Fetch for External Context** ![网页获取](assets/claude-code-webfetch.png) **真实的 CLI • 真实的使用 • 真实的社区**
**这是一个真正可跑的 Claude Code 风格 Python 终端工作流:能流式回答、调工具、抓外部上下文,并通过 skills 扩展行为。** **🚀 立即试用!Fork 它、修改它、让它成为你的!欢迎提交 Pull Request!** *** ## ⭐ Star 历史 Star History Chart ## ✨ 特性 ### Streaming Agent Experience ```text >>> /stream on >>> 解释 tests/test_agent_loop.py [流式回答中...] • Read (tests/test_agent_loop.py) running... ↳ lines 1-180 >>> /render-last ``` - 直接回答支持真实 API 流式输出,带工具的 agent loop 也具备更完整的流式体验 - 内置 `/stream` 开关用于实时输出,`/render-last` 可按需把上一条回答重新渲染为 Markdown - 专门为终端演示优化:一边看回答流出,一边看到工具调用,并保留稳定回退路径 ### 可编程 Skill Runtime ```md --- description: 用类比 + 图示解释代码 allowed-tools: - Read - Grep - Glob arguments: [path] --- 请解释 $path 的实现:先给一个类比,再画一个结构示意图。 ``` - 基于 `SKILL.md` 的 Markdown 斜杠命令 - 支持项目级技能、用户级技能、命名参数替换与工具限制 ### 多提供商支持 ```python providers = ["Anthropic Claude", "OpenAI GPT", "Zhipu GLM"] # + 易于扩展 ``` ### 交互式 REPL ```text >>> 你好! Assistant: 嗨!我是 Clawd Codex,一个 Python 重实现... >>> /help # 显示命令 >>> / # 显示命令与技能 >>> /save # 保存会话 >>> /multiline # 多行输入模式 >>> Tab # 自动补全 >>> /explain-code qsort.py # 运行一个技能 ``` ### 完整的 CLI ```bash clawd # 启动 REPL clawd login # 配置 API clawd --version # 检查版本 clawd config # 查看设置 ``` *** ## 📊 状态 | 组件 | 状态 | 数量 | | ----- | ------ | ------ | | REPL 命令 | ✅ 完成 | 6+ 内置命令 | | 工具系统 | ✅ 完成 | 30+ 工具 | | 自动化测试 | ✅ 已覆盖 | Skills、providers、REPL、tools、context | | 文档 | ✅ 完成 | 10+ 文档 | ### 核心系统 | 系统 | 状态 | 描述 | |------|------|------| | CLI 入口 | ✅ | `clawd`、`login`、`config`、`--version` | | 交互式 REPL | ✅ | 丰富的交互输出、历史记录、Tab 补全、多行输入 | | 多提供商支持 | ✅ | 支持 Anthropic、OpenAI、GLM | | 会话持久化 | ✅ | 本地保存/加载会话 | | Agent Loop | ✅ | 工具调用循环实现 | | Skill 系统 | ✅ | 基于 SKILL.md 的 /skill 技能:参数替换 + 工具限制 | | 上下文构建 | 🟡 | 已接入 workspace、git、CLAUDE.md 的基础上下文注入,仍需补强项目级理解 | | 权限系统 | 🟡 | 框架已存在,需要集成 | ### 工具系统(已实现 30+ 工具) | 类别 | 工具 | 状态 | |------|------|------| | 文件操作 | Read, Write, Edit, Glob, Grep | ✅ 完成 | | 系统 | Bash 执行 | ✅ 完成 | | 网络 | WebFetch, WebSearch | ✅ 完成 | | 交互 | AskUserQuestion, SendMessage | ✅ 完成 | | 任务管理 | TodoWrite, TaskManager, TaskStop | ✅ 完成 | | Agent 工具 | Agent, Brief, Team | ✅ 完成 | | 配置 | Config, PlanMode, Cron | ✅ 完成 | | MCP | MCP 工具和资源 | ✅ 完成 | | 其他 | LSP, Worktree, Skill(SKILL.md), ToolSearch | ✅ 完成 | ### 路线图进度 - ✅ **阶段 0**:可安装、可运行的 CLI - ✅ **阶段 1**:Claude Code 核心 MVP 体验 - ✅ **阶段 2**:真实工具调用闭环 - 🟡 **阶段 3**:上下文、权限、恢复能力(进行中) - ⏳ **阶段 4**:MCP、插件、扩展性 - ⏳ **阶段 5**:Python 原生差异化特性 **详细功能状态和 PR 指南请查看 [FEATURE_LIST.md](FEATURE_LIST.md)。** ## 🚀 快速开始 ### 安装 ```bash git clone https://github.com/GPT-AGI/Clawd-Code.git cd Clawd-Code # 创建虚拟环境(推荐使用 uv) uv venv --python 3.11 source .venv/bin/activate # 安装 uv pip install -r requirements.txt ``` ### 配置 #### 方式 1:交互式(推荐) ```bash python -m src.cli login ``` 这个流程会: 1. 让你选择 provider:anthropic / openai / glm 2. 让你输入该 provider 的 API key 3. 可选:保存自定义 base URL 4. 可选:保存默认 model 5. 将该 provider 设为默认 配置文件会保存在 `~/.clawd/config.json`。示例结构: ```json { "default_provider": "glm", "providers": { "anthropic": { "api_key": "base64-encoded-key", "base_url": "https://api.anthropic.com", "default_model": "claude-sonnet-4-20250514" }, "openai": { "api_key": "base64-encoded-key", "base_url": "https://api.openai.com/v1", "default_model": "gpt-4" }, "glm": { "api_key": "base64-encoded-key", "base_url": "https://open.bigmodel.cn/api/paas/v4", "default_model": "glm-4.5" } } } ``` ### 运行 ```bash python -m src.cli # 启动 REPL python -m src.cli --help # 显示帮助 ``` **就这样!** 3 步开始与 AI 对话。 *** ## 💡 使用 ### REPL 命令 | 命令 | 描述 | | ------------ | ------- | | `/` | 显示命令与技能 | | `/help` | 显示所有命令 | | `/save` | 保存会话 | | `/load ` | 加载会话 | | `/multiline` | 切换多行模式 | | `/clear` | 清空历史 | | `/exit` | 退出 REPL | ### Skills(技能 / 斜杠命令)教程 技能是存放在 `.clawd/skills` 下的 Markdown 斜杠命令。每个技能对应一个目录,并且文件名固定为 `SKILL.md`。 **1)创建项目技能** 创建: ```text /.clawd/skills//SKILL.md ``` 示例: ```md --- description: 用类比 + 图示解释代码 when_to_use: 当用户问“这段代码怎么工作?”时使用 allowed-tools: - Read - Grep - Glob arguments: [path] --- 请解释 $path 的实现:先给一个类比,再画一个结构示意图。 ``` **2)在 REPL 中使用** ```text ❯ / ❯ / ``` 示例: ```text ❯ /explain-code qsort.py ``` **补充说明** - 用户级技能:`~/.clawd/skills//SKILL.md` - 工具限制:`allowed-tools` 用于限制技能允许调用的工具集合 - 参数替换:支持 `$ARGUMENTS`、`$0`、`$1`、以及命名参数(例如 `$path`,来自 `arguments`) - 占位符写法:请使用 `$path`,不要写成 `${path}` *** ## 🎓 为什么选择 Clawd Codex? ### 基于真实源码 - **不是克隆** — 从真实的 TypeScript 实现移植而来 - **架构保真** — 保持经过验证的设计模式 - **持续改进** — 更好的错误处理、更多测试、更清晰的代码 ### 原生 Python - **类型提示** — 完整的类型注解 - **现代 Python** — 使用 3.10+ 特性 - **符合习惯** — 干净的 Python 风格代码 ### 以用户为中心 - **3 步设置** — 克隆、配置、运行 - **交互式配置** — `clawd login` 引导你完成设置 - **丰富的 REPL** — Tab 补全、语法高亮 - **会话持久化** — 永不丢失你的工作 *** ## 📦 项目结构 ```text Clawd-Code/ ├── src/ │ ├── cli.py # CLI 入口 │ ├── providers/ # LLM 提供商 │ ├── repl/ # 交互式 REPL │ ├── skills/ # SKILL.md 加载与创建 │ └── tool_system/ # 工具注册、循环与校验 ├── tests/ # 核心测试套件 ├── .clawd/ │ └── skills/ # 项目级自定义技能 └── FEATURE_LIST.md # 当前功能状态 ``` *** ## 🤝 贡献 **我们欢迎贡献!** ```bash # 快速开发设置 pip install -e .[dev] python -m pytest tests/ -v ``` 查看 [CONTRIBUTING.md](CONTRIBUTING.md) 了解指南。 *** ## 📖 文档 - **[SETUP_GUIDE.md](docs/guide/SETUP_GUIDE.md)** — 详细安装说明 - **[CONTRIBUTING.md](CONTRIBUTING.md)** — 开发指南 - **[TESTING.md](docs/guide/TESTING.md)** — 测试指南 - **[CHANGELOG.md](CHANGELOG.md)** — 版本历史 *** ## ⚡ 性能 - **启动时间**:< 1 秒 - **内存占用**:< 50MB - **响应**:回合式输出,支持 Rich Markdown 渲染 *** ## 🔒 安全 ✅ **基础本地安全实践** - Git 中无敏感数据 - API 密钥在配置中做了基础混淆 - `.env` 文件被忽略 - 适合本地开发工作流 *** ## 📄 许可证 MIT 许可证 — 查看 [LICENSE](LICENSE) *** ## 🙏 致谢 - 基于 Claude Code TypeScript 源码 - 独立的教育项目 - 未隶属于 Anthropic ***
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"# claude-code-python_rewrite"