This repository is a curated list (awesome-list) of open-source quantitative finance libraries, packages, and resources. It provides a structured README.md organized by category, with inline language tags, and a pipeline that parses the list, enriches it with GitHub metadata (stars, last commit dates), and generates a static website deployed to GitHub Pages. The repo also includes automated tooling for pull-request review: a validation script that checks entry format, section placement, URL security, duplicate detection, and a full CI-driven PR review workflow. The core logic resides in parse.py (multi-threaded GitHub API enrichment), site/generate.py (static site generator), scripts/validate_readme.py (entry validation), and scripts/review_pr.py (automated PR review with offline URL reachability checks and cross-PR duplicate detection). The project is primarily a reference list, not an application or data pipeline, but it includes high-quality supporting tooling for maintainers and contributors.
Gabagool is a Python-based arbitrage trading bot for Polymarket's 15-minute prediction markets, with performance-critical components implemented in Rust via PyO3 extensions. The bot implements the 'Gabagool arbitrage' strategy: buying both YES and NO shares when their combined cost is less than $1.00 to guarantee profit regardless of market outcome. The architecture features a modular design separating concerns into API clients (Gamma and CLOB), trading strategy, position tracking, risk management, and persistence layers. Key components include a thread-local HTTP session manager to prevent connection pool issues, a SQLite-based persistence layer for trade and position data, and a thread-safe position tracker with expiration mechanisms. The system supports multiple operational modes including live trading, paper trading simulation, and backtesting against historical data. Recent development activity shows active maintenance with ongoing Rust integration for performance optimization.