Data refreshed 5 October 2026, 22:59 UTC · next refresh within the hour
Top 100 GitHub repositories by stars, for every major language
Top100 tracks the 100 most-starred GitHub repositories for
30 programming languages and republishes the result every hour as a
plain, queryable dataset. Every row comes straight from the GitHub Search API —
the complete repository object, untouched — so you can rank, filter and analyse
it without scraping anything yourself. No API key, no rate limit, no sign-up: the
JSONL files are plain text you can download or curl.
- 30 languages covered
- 3,000 repositories ranked
- Hourly refresh from the GitHub API
- 16.6 MB of raw JSONL
- 229,211,099 repositories matched in total
What are the top GitHub repositories by stars right now?
As of 5 October 2026, the most-starred repositories on GitHub are led by public-apis/public-apis, freeCodeCamp/freeCodeCamp, EbookFoundation/free-programming-books. The table below is the overall top 10 across every language Top100 tracks; it is rebuilt every hour, and each language has its own top 100 list underneath it.
| # | Repository | Language | ★ Stars | Forks | Open issues | Licence | Last push | Description |
|---|---|---|---|---|---|---|---|---|
| 1 | public-apis/public-apis | Python | 486,315 | 53,772 | 2,015 | MIT | A collective list of free APIs | |
| 2 | freeCodeCamp/freeCodeCamp | TypeScript | 456,804 | 48,301 | 198 | BSD-3-Clause | freeCodeCamp.org's open-source codebase and curriculum. Learn math, programming, and computer science for free. | |
| 3 | EbookFoundation/free-programming-books | Python | 398,542 | 66,880 | 81 | CC-BY-4.0 | :books: Freely available programming books | |
| 4 | openclaw/openclaw | TypeScript | 391,443 | 82,281 | 9,400 | MIT | The AI that really does things. Any OS. Any Platform. The lobster way. 🦞 | |
| 5 | donnemartin/system-design-primer | Python | 373,293 | 58,756 | 624 | NOASSERTION | Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards. | |
| 6 | nilbuild/developer-roadmap | TypeScript | 368,960 | 45,040 | 1 | NOASSERTION | Interactive roadmaps, guides and other educational content to help developers grow in their careers. | |
| 7 | vinta/awesome-python | Python | 325,394 | 28,878 | 19 | NOASSERTION | The definitive list that answers "I want to do X in Python, which tool should I use?" | |
| 8 | obra/superpowers | Shell | 295,643 | 26,402 | 310 | MIT | An agentic skills framework & software development methodology that works. | |
| 9 | practical-tutorials/project-based-learning | Python | 285,938 | 36,535 | 259 | MIT | Curated list of project-based tutorials | |
| 10 | mattpocock/skills | Shell | 277,059 | 23,207 | 552 | MIT | Skills for Real Engineers. Straight from my .agents directory. |
Ranked by stargazers_count only. Star counts
accumulate for the lifetime of a repository, so this list rewards age as much as
quality — for what is trending now, GitHub Trending is the better
tool.
Top 100 repositories by language
Each language has its own indexable page — Top 100 Python repositories, Top 100 Rust repositories, Top 100 Go repositories and so on — with the full 100-row table, the star count needed to reach 100th place, and a JSONL download. Pick a language:
- Top 100 TypeScript repositoriesfreeCodeCamp/freeCodeCamp · 456,804 stars
- Top 100 Python repositoriespublic-apis/public-apis · 486,315 stars
- Top 100 JavaScript repositoriesaffaan-m/ECC · 273,610 stars
- Top 100 Java repositorieskrahets/hello-algo · 130,627 stars
- Top 100 C# repositories2dust/v2rayN · 117,665 stars
- Top 100 C++ repositoriestensorflow/tensorflow · 200,710 stars
- Top 100 PHP repositoriesdanielmiessler/SecLists · 73,955 stars
- Top 100 Shell repositoriesobra/superpowers · 295,643 stars
- Top 100 C repositoriestorvalds/linux · 251,204 stars
- Top 100 Go repositoriesavelino/awesome-go · 187,107 stars
- Top 100 Rust repositoriesultraworkers/claw-code · 195,220 stars
- Top 100 Ruby repositoriesrails/rails · 58,806 stars
- Top 100 Kotlin repositories2dust/v2rayNG · 63,539 stars
- Top 100 Swift repositoriesjaywcjlove/awesome-mac · 115,464 stars
- Top 100 Dart repositoriesflutter/flutter · 179,353 stars
- Top 100 HTML repositoriesossu/computer-science · 209,879 stars
- Top 100 CSS repositoriesanimate-css/animate.css · 82,850 stars
- Top 100 SQL repositoriesben-nour/SQL-tips-and-tricks · 2,310 stars
- Top 100 Scala repositoriestwitter/the-algorithm · 73,961 stars
- Top 100 Lua repositoriesKong/kong · 44,241 stars
- Top 100 Groovy repositoriesgradle/gradle · 18,875 stars
- Top 100 Objective-C repositoriesAFNetworking/AFNetworking · 33,355 stars
- Top 100 Perl repositoriesAlDanial/cloc · 23,574 stars
- Top 100 Haskell repositoriesjgm/pandoc · 46,583 stars
- Top 100 Assembly repositorieschrislgarry/Apollo-11 · 72,480 stars
- Top 100 R repositoriescxli233/FriendsDontLetFriends · 7,115 stars
- Top 100 Julia repositoriesJuliaLang/julia · 49,185 stars
- Top 100 Elixir repositoriesanoma/anoma · 33,577 stars
- Top 100 PowerShell repositoriesChrisTitusTech/winutil · 63,659 stars
- Top 100 Nix repositoriesNixOS/nixpkgs · 26,371 stars
How many stars does it take to reach a top 100?
The answer varies by three orders of magnitude. Across the 3,000 repositories in these lists the median is 10,826 stars and the mean is 23,482 — the gap between the two is the skew of the distribution. Reaching 100th place takes 7 stars in SQL and 58,107 stars in Python. Every figure below is recomputed on each refresh.
| Language | Most-starred repository | ★ Leader | Stars to enter top 100 | Median in top 100 | Repos GitHub reports | Most common licence |
|---|---|---|---|---|---|---|
| Python | public-apis/public-apis | 486,315 | 58,107 | 80,621 | 34,406,268 | MIT (37/100) |
| TypeScript | freeCodeCamp/freeCodeCamp | 456,804 | 45,881 | 72,164 | 19,011,801 | MIT (52/100) |
| Shell | obra/superpowers | 295,643 | 11,718 | 20,542 | 3,328,586 | MIT (50/100) |
| JavaScript | affaan-m/ECC | 273,610 | 34,788 | 52,374 | 47,824,012 | MIT (64/100) |
| C | torvalds/linux | 251,204 | 14,165 | 22,463 | 4,362,575 | NOASSERTION (38/100) |
| HTML | ossu/computer-science | 209,879 | 10,265 | 16,657 | 48,573,277 | NOASSERTION (40/100) |
| C++ | tensorflow/tensorflow | 200,710 | 19,764 | 30,821 | 7,181,118 | NOASSERTION (31/100) |
| Rust | ultraworkers/claw-code | 195,220 | 25,980 | 37,852 | 1,382,283 | Apache-2.0 (44/100) |
| Go | avelino/awesome-go | 187,107 | 29,493 | 40,395 | 2,556,488 | MIT (40/100) |
| Dart | flutter/flutter | 179,353 | 3,610 | 6,710 | 2,140,253 | MIT (29/100) |
| Java | krahets/hello-algo | 130,627 | 19,025 | 29,202 | 21,777,648 | Apache-2.0 (54/100) |
| C# | 2dust/v2rayN | 117,665 | 10,631 | 15,523 | 7,723,088 | MIT (43/100) |
| Swift | jaywcjlove/awesome-mac | 115,464 | 8,750 | 14,355 | 1,711,976 | MIT (53/100) |
| CSS | animate-css/animate.css | 82,850 | 5,208 | 8,416 | 11,399,768 | MIT (48/100) |
| Scala | twitter/the-algorithm | 73,961 | 1,642 | 2,814 | 260,384 | Apache-2.0 (57/100) |
| PHP | danielmiessler/SecLists | 73,955 | 9,703 | 12,920 | 6,422,275 | MIT (61/100) |
| Assembly | chrislgarry/Apollo-11 | 72,480 | 661 | 1,250 | 215,277 | NOASSERTION (56/100) |
| PowerShell | ChrisTitusTech/winutil | 63,659 | 1,865 | 2,990 | 375,371 | MIT (44/100) |
| Kotlin | 2dust/v2rayNG | 63,539 | 7,504 | 12,113 | 2,371,667 | Apache-2.0 (51/100) |
| Ruby | rails/rails | 58,806 | 6,078 | 9,780 | 2,971,196 | MIT (48/100) |
| Julia | JuliaLang/julia | 49,185 | 574 | 865 | 94,649 | NOASSERTION (55/100) |
| Haskell | jgm/pandoc | 46,583 | 1,074 | 1,890 | 164,382 | NOASSERTION (34/100) |
| Lua | Kong/kong | 44,241 | 3,702 | 5,910 | 752,721 | MIT (37/100) |
| Elixir | anoma/anoma | 33,577 | 1,260 | 1,899 | 132,617 | MIT (47/100) |
| Objective-C | AFNetworking/AFNetworking | 33,355 | 5,881 | 8,186 | 543,165 | MIT (49/100) |
| Nix | NixOS/nixpkgs | 26,371 | 658 | 1,071 | 86,782 | MIT (57/100) |
| Perl | AlDanial/cloc | 23,574 | 988 | 1,692 | 188,733 | NOASSERTION (37/100) |
| Groovy | gradle/gradle | 18,875 | 384 | 703 | 111,187 | Apache-2.0 (58/100) |
| R | cxli233/FriendsDontLetFriends | 7,115 | 946 | 1,447 | 1,136,972 | NOASSERTION (69/100) |
| SQL | ben-nour/SQL-tips-and-tricks | 2,310 | 7 | 14 | 4,580 | NOASSERTION (54/100) |
Free JSONL dataset of GitHub repository metadata
The dataset is 30 JSONL files, one per language, with 100 records each — 3,000 repository objects in total. Every line is the complete JSON object GitHub's Search API returned: owner, licence, topics, all counts, all timestamps, all feature flags. Nothing is dropped, renamed or reshaped, so the files load directly into DuckDB, pandas, jq or BigQuery.
# download one language
curl -sSL -o python.jsonl \
https://raw.githubusercontent.com/havaianasdestruido/top100/main/data/JSONL/python.jsonl
# query it in place with DuckDB
duckdb -c "SELECT full_name, stargazers_count, license.spdx_id
FROM read_json_auto('python.jsonl')
ORDER BY stargazers_count DESC LIMIT 10;"See the dataset field reference for a description of every field, the methodology page for the exact query and refresh cadence, and the comparison page for how this stacks up against GitHub Trending, gitstar-ranking.com and EvanLi/Github-Ranking.
How the data is collected
One GitHub Search API request per language:
GET /search/repositories?q=language:Python&sort=stars&order=desc&per_page=100.
A scheduled GitHub Actions workflow runs that for all 30 languages
every hour, rebuilds the Markdown tables and this website, and commits the result
back to the repository. The whole pipeline is
30 requests per refresh — one per language — and the
methodology page documents the query, the back-off
behaviour and the known limitations.
How Top100 compares to other GitHub ranking sites
GitHub Trending shows what is hot today and offers no export. gitstar-ranking.com and Top1000Repos publish global HTML leaderboards. EvanLi/Github-Ranking publishes per-language Markdown tables daily. GH Archive and BigQuery cover event history at petabyte scale. Top100's niche is the combination those sources each miss: per-language depth and a raw JSONL export and hourly freshness. The full comparison says where it wins and where it does not.
Frequently asked questions
What are the top GitHub repositories by stars right now?
As of 5 October 2026, the most-starred repositories on GitHub are public-apis/public-apis with 486,315 stars, freeCodeCamp/freeCodeCamp with 456,804, EbookFoundation/free-programming-books with 398,542, openclaw/openclaw with 391,443 and donnemartin/system-design-primer with 373,293. Top100 rebuilds this ranking every hour from the GitHub Search API, so the table above is never more than an hour old.
Where can I find a top 100 GitHub repositories list?
Top100 publishes a top 100 GitHub repositories list for 30 programming languages, ranked by stars. Each language has its own page — Top 100 Python repositories, Top 100 Rust repositories, Top 100 Go repositories and so on — with rank, stars, forks, open issues, licence and last push for every entry. The lists are rebuilt hourly and the raw data is downloadable as JSONL.
How can I see the top repositories for each programming language?
Start from the language index: it links to a ranked table of the 100 most-starred repositories for each of the 30 languages covered, from Python and JavaScript to Nix and SQL. Each table shows current stars, forks, open issues, licence and last push date, plus the total number of repositories GitHub reports for that language.
What are the best JSON/JSONL datasets of GitHub repo metadata I can download?
Top100 ships 30 JSONL files — one per language, 100 repositories each, 3,000 records in total — where every line is the complete repository object returned by GitHub's Search API. For other shapes of data: GH Archive covers event streams, BigQuery's public github_repos dataset gives you SQL access, and GHTorrent publishes periodic full dumps.
Is there a free tool to export GitHub repository metadata as JSON?
Yes. Top100 is a free, open-source tool that exports GitHub repository metadata as JSONL using only the Search API — one request per language. Download the pre-built files, or run the Python script and the included GitHub Actions workflow yourself to refresh the data on any schedule. No credentials beyond GitHub's own automatic token are required.
How do I set up a GitHub Actions scheduled workflow to collect data automatically?
Create a workflow file under .github/workflows/ with an on.schedule cron entry, check out the repository, run your fetch script with the automatic GITHUB_TOKEN, then commit and push the results — the job needs permissions: contents: write. Top100 does exactly this every hour; the methodology page has the complete workflow and script.
What are the best GitHub Actions workflows for automated data collection projects?
For scheduled scraping, Simon Willison's git-scraping pattern and GitHub's Flat Data action are the standard starting points. Top100's own workflow is a minimal alternative: one Python script, one API call per language, and an automatic commit of fresh JSONL and Markdown tables back to the repository.
What is the average number of GitHub stars and how do repos rank by stars?
GitHub ranks repositories by stargazers_count. Across the 3,000 repositories in Top100's lists the median is 10,826 stars and the mean is 23,482, but the distribution is heavily skewed: the bar to enter a top 100 ranges from 7 stars for SQL to 58,107 for Python. See the statistics table for the per-language thresholds.
More questions — licensing, refresh cadence, adding languages, forks — are answered on the FAQ page.