Learning Algorithms Visually, Even If You Don't Read Chinese
You've probably stared at a sorting algorithm's code, traced through it line by line, and still felt fuzzy on exactly how the data moves at each step. Static diagrams help a little, but they don't capture the motion. That's the gap this project tries to fill: animated walkthroughs of data structures and classic algorithms, written in Chinese.
What It Does
algorithm-base is a GitHub repository that collects explanatory articles on foundational computer science topics, with a strong emphasis on animation and visual simulation. The README organizes content into clear sections, each linking to individual markdown files (or, in one case, a WeChat article) hosted in the repo.
The current catalog covers three main areas. Under data structures (labeled as prerequisite knowledge), you'll find pieces on hash tables, stacks and queues, linked lists, recursion, and trees. There's a dedicated section on string matching algorithms covering BF, BM, and KMP. And there's a sorting section that includes bubble sort, simple selection sort, insertion sort, shell sort, and merge sort (with the README truncated, so the list likely continues). Many of the entries are tagged with "animation simulation" or "drawing analysis," signaling that the explanations lean on visuals rather than walls of text.
The project also points readers to a companion reading site, www.chengxuchu.com, which the README recommends as a more stable way to read the content.
Why It's Cool
-
Animation is the whole point. Plenty of algorithm tutorials exist, but the explicit focus here on animated simulation is what sets it apart. Watching a KMP failure function get built step by step, or seeing a merge sort actually merge, does more for intuition than pseudocode ever will.
-
It covers the fundamentals properly. Rather than jumping straight to LeetCode problems, the repo starts with prerequisite data structures—hash tables, stacks, queues, linked lists, trees, recursion. That ordering suggests a genuine teaching philosophy: understand the building blocks before you optimize for interviews.
-
The string matching section is unusually thorough. BF, BM, and KMP in one place, each with animations, is a solid resource. KMP in particular is one of those algorithms people memorize without understanding, and a visual walkthrough is exactly what breaks that cycle.
-
It's actively maintained and community-oriented. The README includes a letter to readers, an invitation for code contributions (with a contact method), and a study group for interview prep that the author notes is free and ad-free. There's also a linked set of C++ project introductions for anyone who wants to go deeper.
-
It's honest about its scope. This is a Chinese-language resource. If you don't read Chinese, the prose won't do much for you—but the animations themselves are largely language-independent, and the algorithm names (KMP, BF, BM, bubble sort) are recognizable across languages.
How to Try It
There's nothing to install. This is a reading repository, so getting started is just a matter of opening links.
- Start at the repository: github.com/chefyuan/algorithm-base
- If you want the more stable reading experience, head to the recommended site: www.chengxuchu.com
- Pick a topic from the README's sections. If you're new to algorithms, begin with the data structures section—the hash table piece is described as a long-form deep dive.
- If you want to contribute, the README notes you can reach the maintainer on WeChat (handle: iamchuzi) with a note about contributing to the repo.
- If you find it useful, the author asks for a star—framed as motivation to keep updating.
Final Thoughts
This is a niche resource with a clear audience: Chinese-speaking developers and students preparing for interviews or coursework who learn better from motion than from text. If that's you, the animated approach to KMP and the sorting algorithms alone is probably worth the visit. If you don't read Chinese, you can still skim the animations, but you'll be working harder to get value out of it. Either way, it's a well-organized, actively maintained labor of love—and a reminder that sometimes the best way to understand an algorithm is simply to watch it run.
Follow @githubprojects for more developer tools and open source projects.