[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$f12uebeua6x7t6":3},{"code":4,"message":5,"data":6,"timestamp":39},10000,"success",{"full_name":7,"position":8,"description":9,"language":10,"stars":11,"forks":12,"stars_gained":13,"age_days":14,"hn_threads":15,"one_liner":16,"summary_md":17,"topic":18,"github_topics":21,"license":33,"homepage":34,"updated_at":35,"history":36},"krahets\u002Fhello-algo",10,"《Hello 算法》：动画图解、一键运行的数据结构与算法教程。支持简中、繁中、English、日本語，提供 Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 等代码实现","Java",131186,15513,206,1451,[],"A free, animated data-structures-and-algorithms course for beginners, with runnable code in 12+ languages.","Worth trying if you are learning data structures and algorithms from scratch and want explanations you can run rather than pseudocode you must retype. Read it online first; clone only if you intend to work through the code locally.\n\n## The problem\n\nA beginner opens a textbook or a LeetCode solution and hits the same gap: the diagram shows a tree rotation or a heap sift-down as a static picture, and the code sample is in a language they do not use. They want to understand the mechanism and then reproduce it themselves. Hello Algo changes that workflow by pairing animated figures with implementations in Python, Java, C++, C, C#, JavaScript, Go, Swift, Rust, Ruby, Kotlin, TypeScript and Dart, alongside a browser-readable book. The result is that a learner can read the idea, watch the data move, then run the matching file and step through it.\n\n## What's different\n\nThe mechanism is a book written as a repository: the prose, figures and source code live together, and the code is meant to be executed directly rather than transcribed. That matters for beginner material because the usual failure mode is a correct-looking snippet that does not compile on the reader's machine. Having the same algorithm in many languages also lets a learner compare how a stack, queue or graph is expressed in a familiar language versus one they are learning.\n\nThe trade-off is that this is teaching material, not a reference or a practice platform. It explains structures and algorithms; the repository description does not present it as a judge or a problem set. Readers who need interview-style drill volume, or who want advanced competitive-programming topics, should look elsewhere. The animated presentation also favours breadth-first coverage over deep proofs and complexity derivations.\n\n## Who should try it\n\nGood fit: a student or self-taught developer who has some programming experience in one language and wants a structured, visual pass over arrays, linked lists, trees, heaps, graphs, sorting and searching. The runnable implementations make it straightforward to follow along in the language already known, while the multi-language set gives a second lane if you are moving to, say, Go or Rust.\n\nPoor fit: someone preparing for a specific interview loop next week who needs curated problem lists and mock practice; this book teaches the concepts, and the description does not claim to be a problem bank. Also a weaker fit for readers who already know the fundamentals and want edge-case discussions for production code, since the material is explicitly beginner-friendly. The online book and the downloadable PDF\u002FEPUB versions [project site](https:\u002F\u002Fwww.hello-algo.com) and [releases](https:\u002F\u002Fgithub.com\u002Fkrahets\u002Fhello-algo\u002Freleases) mean you do not need the repository to start reading; only the executable-code path requires a local toolchain.\n\n## Requirements and limitations\n\nThe reading path has essentially no setup: [the online book](https:\u002F\u002Fwww.hello-algo.com\u002F) works in a browser, and PDF\u002FEPUB downloads are offered from the release page. The running-code path is different: you need a working toolchain for whichever language you choose, and the repository supports thirteen languages for code translation [project README](https:\u002F\u002Fgithub.com\u002Fkrahets\u002Fhello-algo\u002Fblob\u002Fmain\u002FREADME.md), so there is no single environment that covers everything. That is the main upkeep cost, and it scales with how many languages you want to run.\n\nThe licensing is the constraint to check before reuse. The text, code, images and videos are under CC BY-NC-SA 4.0 [license terms](https:\u002F\u002Fcreativecommons.org\u002Flicenses\u002Fby-nc-sa\u002F4.0\u002F), which permits sharing and adaptation with attribution, non-commercial use and share-alike terms; it is not a permissive software licence for embedding in a commercial product. The project also describes itself as still being updated and invites corrections and translations [contribution guide](https:\u002F\u002Fwww.hello-algo.com\u002Fchapter_appendix\u002Fcontribution\u002F), so treat it as living material rather than a frozen edition.\n\n## HotRepo's take\n\nHotRepo recorded the project on the GitHub daily board once, on 2026-10-25, at 131,078 stars and +24 for that day [project repository](https:\u002F\u002Fgithub.com\u002Fkrahets\u002Fhello-algo). That is a single dated observation, not a trend line; comparable daily-board history is insufficient, so momentum cannot be judged from it. The useful signal is narrower: a long-running educational repository still registering a small daily gain. Before committing to the code path, check whether your chosen language's implementation is among the supported set and runs with your local toolchain.",{"slug":19,"name":20},"learning","Learning Resources",[22,23,24,25,26,27,28,29,30,31,32],"algo","algorithm","algorithms","book","data-structure","data-structures","data-structures-and-algorithms","dsa","education","leetcode","programming","NOASSERTION","https:\u002F\u002Fwww.hello-algo.com","2026-10-25T11:04:18Z",[37],{"date":38,"stars":11,"stars_gained":13},"2026-10-25",1792969018]