The labuladong algorithm notes ship no license, no releases, and a dead Pages mirror
GitHub describes it as Crack LeetCode, not only how, but also why.. The repository metadata lists Markdown as its primary language. This article stays within the project description and details documented in the GitHub repository README.
At a glance
- What is it?
- labuladong/fucking-algorithm is a Markdown collection of more than 60 LeetCode-based algorithm articles, with no license file, no releases, and a last push dated 28 February 2026. The index in its readme links to a separate site rather than to the files in the tree, so the clone is a reading list and not the course.
- Who is it for?
- Take the repository as a map of an algorithm curriculum and as a set of Chinese-language explanations for the classic data structures. It works for a reader who already knows which topic they are on and wants the reasoning behind a solution, which is the position the readme argues for throughout.
- Can I use it commercially?
- Not without permission. GitHub finds no licence file in the repository, and without a licence all rights are reserved by default: you may read the code but not reuse it. Check the README, or ask the authors, before using it.
- Is it still maintained?
- Activity is slowing. The repository last received commits 7 months ago.
- What is it written in?
- Mainly Markdown, according to GitHub's language statistics.
Answers come from the project's GitHub data, last synced on September 29, 2026, and from our analysis. They are not legal advice.
Editorial analysis
There is no license file next to the content
The top level of the repository holds .gitattributes, .github/, .gitignore, README.md, contributor.jpg, pictures/, starHistory.jpg, starHistory.png, and six content directories. There is no LICENSE file among them, and no license value is reported for the repository at all. Consequence for a reader: the default position when a repository carries no license is that copyright applies and all rights are reserved, so the Markdown articles and the multi-language solution code are not licensed to you for redistribution, translation, or inclusion in a course. That is consistent with what the readme argues, since its whole argument is against copying solutions and in favour of deriving them, but it also means the popular use of this repository, lifting a diagram or a code sample into your own notes, has no permission behind it and no stated terms to point at. Read the repository as a reading list, not as a source you can vendor.
Both page mirrors are struck through, so the clone is not the course
Three addresses appear in the readme and only one is live. The dead two are marked with strikethrough:
2024 最新地址:https://labuladong.online/algo/
~~GitHub Pages 地址:https://labuladong.online/algo/~~
~~Gitee Pages 地址:https://labuladong.gitee.io/algo/~~The GitHub Pages and Gitee Pages routes are both retired, which means the repository is not published as a site and the gitee.io host is gone entirely. Consequence for a reader: any cached link, bookmark, or course reference pointing at the Pages or Gitee URL is dead, and everything interactive is on the separate site rather than in the repository. The visualization panels, which the readme says exist for nearly every problem's solution code, the algorithm games, the 500-problem walkthrough, the AI teaching assistant, and the Chrome, vscode, and JetBrains plugins are all site features. Cloning gives you Markdown in six directories and nothing you can run, and the English version is also hosted rather than shipped, at the /algo/en/ path.
The readme's own date marker is 2024 and the last push is 28 February 2026
The single freshness signal inside the readme is the label on the live address line, which reads 2024 latest. The repository has no GitHub releases, so there is no tag to pin and no version to cite. The last push to master is dated 28 February 2026. Consequence for a reader deciding how much to trust the text: the readme's marker is roughly two years older than the repository's own last change, so the label is not a reliable freshness signal, and with no tags you cannot tell which of the 60-plus articles were revised recently without reading commit history file by file. The honest statement is that this content is a snapshot, last touched on 28 February 2026, and that no maintenance claim beyond that date can be made from what the repository shows. Treat it as a finished course you are reading late rather than a text under revision.
Six content directories, and the readme's index points at the site
The tree is organised by series: a dynamic programming series, a data structures series, an algorithm thinking series, a high-frequency interview series, a techniques directory, and a multi-language solution code directory. Language coverage in the readme's own index runs to C++, Java, Golang, Python, and JavaScript, plus an ACM mode code template page. Consequence for a reader: the on-disk layout is good for someone who already knows which topic they are on, because each series is a directory you can open directly. It is useless for discovery, because the readme's table of contents is not a list of files in the tree. Every entry in it is a link to labuladong.online, so the in-repo navigation and the site navigation are two separate systems, and the only mapping between a series directory and the published chapter order lives on the site. The 60-plus article count in the readme also refers to the collection as a whole rather than to any directory, so you cannot audit coverage per series from the repository.
The paid membership sits in the same menu as the free plugins
The tools section of the index lists seven things, and they are formatted identically. Alongside the guides for the algorithm visualization panel, the algorithm games, the Chrome plugin, the vscode and cursor plugin, and the JetBrains plugin, and alongside an AI teaching assistant page for asking questions at any time, the list includes a paid site membership entry. Consequence for a reader: the readme gives you no way to tell which of those cost money, because the pricing signal exists only on the destination pages, and the repository is the only place that shows the membership and the plugins as peers in one list. If you are deciding what you can use without paying, you have to visit each guide, and the risk is highest on the AI assistant entry, since a reader scanning the list would reasonably assume a companion feature of an open collection is also open.
The first instruction in the readme is to star the repository
Before any description of the content, the readme asks for two things in a numbered list. The first is to star the repository, and it says so plainly, with the reason given as satisfying the author's vanity, and adds that article quality is absolutely worth one star. The second is to bookmark the online site, on the grounds that every article opens with a link to the corresponding LeetCode problem so you can read and practise at the same time, and it claims the site can walk you through 500 problems by hand. Consequence for a reader: the repository's stated job is referral and social proof as much as it is a document, and the 500-problem figure is a claim about the site rather than about anything in the tree. The top level reinforces it, since a star history image in two formats and a contributor photo are committed as repository files.
The argument against copying is a claim the repository cannot back
The readme's central claim is that solving problems is meant to build algorithm thinking rather than to collect answers, and it argues this against the one-line Python solutions that collect upvotes in the comment sections of problem sites. It also records the criticism that the material is too elementary, and answers that people practise algorithms to get a job rather than to compete, so clarity matters more than mystique. Consequence for a reader: this is a claim about pedagogy, asserted in the readme and not verifiable from the files. Nothing in the tree labels an article with a difficulty, a time estimate, or a prerequisite, and the practice rules, including what a LeetCode problem notice page would cover, live on the site. So if you want the reasoning rather than the answer, the readme tells you that is the intent, and the only way to check whether a given article delivers it is to read the article.
Editorial conclusion
Take the repository as a map of an algorithm curriculum and as a set of Chinese-language explanations for the classic data structures. It works for a reader who already knows which topic they are on and wants the reasoning behind a solution, which is the position the readme argues for throughout. It does not work for anyone who needs a licensed corpus, a current version, or an offline course. There is no license file, so nothing here carries a grant; there are no releases, so there is no tag to pin; and the last push is dated 28 February 2026, which is old enough that the text should be read as a snapshot rather than a text under revision. Two of the three page addresses in the readme are struck through, so a cached GitHub Pages or Gitee link is dead and the visualization panels, the games, the AI assistant, and the three editor plugins are all site features you will not get from a clone. Check the membership page before assuming a listed tool is free, because the paid site membership appears in the readme's tools menu in the same format as the free plugins.
Frequently asked questions
What are the 7 types of algorithms, according to fucking-algorithm?
The repository does not enumerate seven types. Its top level is organised into six series directories, among them a dynamic programming series, a data structures series, an algorithm thinking series, and a high-frequency interview series.
What are the 5 steps of an algorithm, in the labuladong notes?
The readme does not give steps. It states the repository holds more than 60 original articles based on LeetCode problems, covering all question types and techniques, and it argues the goal is algorithm thinking rather than collected answers.
What is a coding algorithm, in the labuladong/fucking-algorithm readme?
The readme does not define the term. The repository description says it is about cracking LeetCode, not only how, but also why, and the readme frames the subject as the thinking behind a solution rather than the code.
How do you code an algorithm, following fucking-algorithm?
The readme's position is that solving problems is meant to build algorithm thinking, and it points to pages on practising with a programming language and an ACM mode code template, both hosted on labuladong.online rather than included in the repository.
Official sources
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