# github-hot-hub: trending, scraped hourly and kept by day > A repository that scrapes GitHub trending once an hour and files each day's list into an archives directory, dating back to January 2021. The record is plain markdown in the README, with a language, two counts and the number of stars gained today for every entry, plus a weekly view. **SnailDev/github-hot-hub** — Tracks trending GitHub repositories, updated hourly and archived daily. - Repository: https://github.com/SnailDev/github-hot-hub - Stars: 103 · Forks: 11 - Language: Python - License: MIT - Published: 2026-08-26 · Updated: 2026-08-26 · Language: en - Canonical page: https://hysenlabs.com/projects/snaildev-github-hot-hub ## One scrape an hour, one directory per day The project records GitHub trending, and the two numbers that define it are in the README's opening line: the data is collected once an hour, and it is archived by day. The archive starts on 12 January 2021, so this is a record built up over years rather than a page generated on demand, and the archives directory at the repository root is where that history lives. The current state is published in the README itself, which carries an update timestamp with a +0800 offset, the timezone of the maintainer. That timestamp matters more than it looks: it tells a reader how fresh the list in front of them is without having to look at commit times. The primary language for the repository is Python, the licence is MIT, and the default branch is main with no releases ever published, since a scraper has nothing to release. ## The output is markdown, not a queryable store What a reader gets is a markdown document, and that is the whole interface. There is a section for today's hot repositories and another for the past week's, and each entry is a numbered item with the owner and repository as a link, the project's own description, and a line of figures. Some descriptions come back in Chinese, which is a reminder that the scraper does not translate anything and simply copies the text from the source page, and at least one weekly entry has no description at all, recorded as the equivalent of none rather than left blank. There is also a small formatting artefact worth knowing about if you parse the file: every entry in the list is numbered one, so the ordering carries the ranking and the numerals do not. ## stars today is the number that makes the list readable Each row carries two counts and one delta. The two counts are the repository's total stars and a folks count, the second number GitHub shows beside the star count. The delta is what the list is actually for, and it differs between the two sections: the daily list reports how many stars were gained today, while the weekly list reports stars gained this week. Reading the entries in the current document shows why both are kept. VoiceStudio appears in the daily list with a few thousand stars gained today, and in the weekly list with more than fifteen thousand gained in the week. A repository called hindsight leads the weekly section with a gain in the tens of thousands, while paperclip shows more than thirteen thousand. So the weekly view surfaces projects that have already surged, and the daily view catches the ones starting to. ## Language is the other field, and it says something The language field is the cheapest signal in the document, because it needs no interpretation to be informative. In the day's list as captured, TypeScript and Python between them account for most entries, with Rust, JavaScript, C, C++, Shell and even PLSQL also appearing, which is a reasonable reflection of what sits on a trending page. The value is that the language is stored rather than inferred, so a retrospective query like which language dominated trending in a given week is answerable from the archive without going back to the original page. That is the practical argument for archiving by day rather than keeping a single current list, and it is why the format is plain text with stable field names instead of a prettier but less parseable layout. ## Two dependencies, pinned, and three Python files The implementation is small enough to read. requirements.txt contains exactly two pinned packages, requests at 2.25.0 and beautifulsoup4 at 4.9.0, which is the whole scraping story: fetch the trending page, parse the markup. The repository holds main.py as the entry point, github.py and util.py as supporting modules, and a template directory, which is where the markdown layout for the generated sections most likely lives given that the README output is so uniform. Alongside them are the archives directory, a .github directory, .gitignore, LICENSE and the README itself. The pins are from an older generation of both libraries, which is consistent with a script whose job has not needed to change, and also means anyone running it on a current Python has to check those two versions first. ## It is one archive out of five, all with the same shape The README links a family of sibling projects from the same author, one for each trending list people in that ecosystem actually read: archives for Zhihu, for Weibo, for Toutiao, for Douyin and for V2ex. The design carries across unchanged, hourly collection and by-day archiving, which is a useful piece of evidence about the approach. Scraping a trending page is a solved problem once you have written the parser, and the value of each repository is entirely in its accumulated history. It also sets an expectation about coverage. GitHub trending is one of the most contested lists on the web, with its own ranking rules that are not documented anywhere here, so the archive records what the page showed rather than any measure of popularity, and the list should be read as a record of a page rather than as a ranking you can defend. ## The README is the current snapshot, the archive is the record The distinction between the two artefacts is the thing to hold on to. The README is rewritten on every run and shows the current day and the current week, so it is only accurate for as long as the next hourly run does not replace it. The archives directory is the durable part, one entry per day, and it is what makes the project worth more than any single list. The repository is not archived, and the last recorded push is 30 September 2026, so the job described at the top of the README, collecting every hour, is still being done. There are no GitHub releases and no package to install, because there is nothing to install: the useful output is the text, and the tooling to produce it is two Python files that run on a schedule. ## Conclusion github-hot-hub fits someone who wants to look back at what GitHub was surfacing on a given day rather than what it is surfacing now, and the by-day archive is the reason this is more than a leaderboard. Two things to know before you use it as a source. The content is a scrape of a page that changes hourly, so the numbers are a snapshot and the description fields are whatever the repository owners wrote, including entries with no description at all. And the tooling is a two-dependency Python script with versions pinned from 2020, which is fine for the job it does and not something to build on. The repository is not archived, the last push is 30 September 2026, the README carries its own update timestamp in the +0800 timezone, and the same author publishes matching archives for five other trending lists. ## FAQ ### What is SnailDev/github-hot-hub? A repository that records GitHub trending, collecting the data once an hour and archiving it by day starting on 12 January 2021. The README shows the current day and the past week, listing each repository with its description, language, star count, a folks count and the stars gained today. ### How often is github-hot-hub updated? Once an hour. The README carries its own update timestamp with a +0800 offset, and each day's snapshot is kept in the archives directory at the repository root. ### What fields does each github-hot-hub entry contain? The owner and repository as a link, the project description, the language, a star count, a folks count, and the stars gained today. The weekly section reports stars gained this week instead of today. ### How does github-hot-hub collect its data? With Python using requests and BeautifulSoup, pinned in requirements.txt at requests 2.25.0 and beautifulsoup4 4.9.0. The repository holds main.py with github.py and util.py beside it, and a template directory for the generated markdown. ### Does github-hot-hub only cover GitHub? No. The same author publishes the same hourly, by-day archives for other trending lists, including Zhihu, Weibo, Toutiao, Douyin and V2ex, linked from the README. ## Sources - [Official README](https://github.com/SnailDev/github-hot-hub#readme) - [Project repository](https://github.com/SnailDev/github-hot-hub) - [README](https://github.com/SnailDev/github-hot-hub/blob/main/README.md) - [Releases](https://github.com/SnailDev/github-hot-hub/releases) --- Hysen Labs editorial analysis, written from the project's own repository and release notes. Cite the canonical page: https://hysenlabs.com/projects/snaildev-github-hot-hub