Skip to content

量化交易Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics

Python · active 2023-08-15 → 2026-09-26 (UTC)

Complete coverage27,390 / 27,390 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-09-29 (UTC)
Events
23.4K
Pushes
444
Pull requests
281
Issues
421
Stars
18.6K
Forks
2.7K

Activity over time

Daily event counts in the loaded window

Line chart, 1139 days from 2023-08-15 to 2026-09-26. Pushes: 444 total, peak 42 in a day. Pull requests: 281 total, peak 10 in a day. Issues: 421 total, peak 39 in a day. Comments: 767 total, peak 12 in a day. Stars: 18,577 total, peak 489 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
SunsetWolf715385111138
you-n-g207503577
microsoft-github-policy-service[bot]760076
github-actions[bot]670032
Fivele-Li361118
tianshijing330276
Abhijais489624000
ElonJustin7210012
l0ngc190012
quant2008180010
PaleNeutron170110
ghyzx16009
moesakura14006
DanielKui14005
guoz1414009
Imbernoulli12007
LeetaH66610004
initsownright10007
ChiahungTai9053
TompaBay9003

Recent activity

Latest issues, pull requests and releases

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 18,577 stars here means stars gained during the window, not the repo's star count.