Tired of Explaining Code You Didn’t Even Write? Let LLMs Do It.

厌倦了去解释那些根本不是你写的代码？让大模型（LLM）来代劳吧。

We’ve all been there. A teammate walks over (or pings you on Slack) with a massive chunk of unfamiliar code and asks: “Hey, can you explain what this does? Also, why does this specific edge case work like this?” 我们都经历过这种情况。队友走过来（或者在 Slack 上发消息），甩给你一大段陌生的代码，然后问：“嘿，你能解释一下这是干嘛的吗？还有，为什么这个特定的边界情况是这样处理的？”

Here’s the catch: You didn’t write that code. You’ve never seen it before. Now you’re stuck spending half your afternoon digging through undocumented functions, tracking down call graphs, and trying to reverse-engineer someone else’s legacy logic just to answer detailed questions. 问题在于：这段代码不是你写的，你甚至从未见过它。现在你不得不花一下午的时间去翻阅那些没有文档的函数，追踪调用图，试图对别人的遗留逻辑进行逆向工程，仅仅是为了回答这些细节问题。

Let’s be honest: I don’t want to waste my time manually reading through unfamiliar codebases. Not when LLMs exist. Manual code spelunking just to write an explanation is tedious work. So, why not let an LLM do the heavy lifting? 说实话：我不想把时间浪费在手动阅读陌生的代码库上。既然现在有了大模型，手动去“挖掘”代码来写解释简直是枯燥乏味的工作。那么，为什么不让大模型来承担这些繁重的工作呢？

Introducing pystdoc. I built pystdoc to completely automate this nonsense. It parses your codebase, analyzes symbol relations and call graphs, and uses LLMs to generate structured documentation and explanations for you. 隆重介绍 pystdoc。我构建 pystdoc 就是为了彻底自动化这些琐事。它能够解析你的代码库，分析符号关系和调用图，并利用大模型为你生成结构化的文档和解释。

How simple is it? Just install it: pip install pystdoc. Set up your LLM configuration and run it against the target directory: pystdoc run ./path/to/unfamiliar/code. That’s it. It analyzes the code and generates clear, detailed explanations and documentation so you don’t have to decipher every single line yourself. 它有多简单？只需安装它：pip install pystdoc。配置好你的大模型参数，然后针对目标目录运行它：pystdoc run ./path/to/unfamiliar/code。就这样。它会分析代码并生成清晰、详细的解释和文档，这样你就不必亲自去破译每一行代码了。

Links & Docs: For advanced configurations, supported languages/parsers, caching, and engine options, check out the project: 链接与文档：有关高级配置、支持的语言/解析器、缓存和引擎选项，请查看项目主页：

📦 PyPI: pypi.org/project/pystdoc 🐙 GitHub: github.com/tab4moji/pystdoc

Give it a try next time someone asks you to explain mystery code. Feedback and PRs are always welcome! 下次当有人让你解释“神秘代码”时，不妨试一试。欢迎随时提供反馈和提交 PR！