9 GitHub repos curated
PyQuant News curated nine top GitHub repositories for quant‑finance Python code—covering backtesting, options pricing, and practical utilities that are ready to fork for a portfolio. These repos are quick wins for building demonstrable Python projects that interviewers can inspect. (x.com)
Jake VanderPlas’s Python Data Science Handbook—the repo that supplies full Jupyter notebooks for the O’Reilly text—shows roughly 47.1k stars on GitHub and the code is released under an MIT-style code license while the book text uses CC-BY-NC-ND. (github.com) The python-cheatsheet repo by gto76 has about 38.3k stars and recorded activity as recently as last week, making it a high‑signal quick reference for Python idioms used in quant workflows. (github.com) OpenBB’s main repository (OpenBB-finance/OpenBB) has amassed over 63k stars and more than 6,800 commits, with a recent v4.7.0 release adding Python and pandas compatibility updates in the last week. (github.com) The “awesome‑quant” aggregator by wilsonfreitas ranks as one of the largest curated lists for quant libraries with ~24.9k stars and ongoing updates to sections like options and analytics within the last month. (github.com) QuantStats (ranaroussi/quantstats) is a portfolio‑analytics library with roughly 6.9k stars, an Apache‑2.0 license, and recent “2026 Modernization” commits that add Python 3.10+ compatibility and Monte Carlo features. (github.com) Stefan Jansen’s reworkings—zipline‑reloaded (~1.7k stars) for event‑driven backtesting and alphalens‑reloaded (~550 stars) for factor performance—both maintain active releases on PyPI and are tied to Jansen’s teaching and book examples. (github.com) Optopsy (an options backtesting/stats tool) published a PyPI release on Mar 4, 2026 and offers quick scenario-driven option-strategy analysis, while Man Group’s ArcticDB is distributed under a Business Source License (BSL) and bills itself as a C++-backed, high‑performance DataFrame database successor to Arctic. (pypi.org)
