Home / Backtesting & trading frameworks
qf-lib
Python library of quantitative finance building blocks
What it is
A Python library that bundles common tools for quantitative finance research in one modular package. It includes data handling, a backtesting engine, portfolio construction and risk analysis modules, plus ready-made indicator calculations. Researchers and developers who want to test strategies and analyse portfolios without wiring several separate packages together are the intended users. Because it covers so much ground, expect some time learning its own abstractions before it pays off on a small project.
At a glance
Worth watchingOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Professional quants |
|---|---|
| Used for | Backtesting, Strategy research |
| Markets | Multi-market |
| Stack | Python |
| Learning curve | Steep learning curve |
| Practical value | Medium practical value |
| Cost | Free and open source |
| Hardware | No GPU needed |
| Maintenance | Last commit 57 days ago |
GitHub stars, last 30 days
Daily snapshots since 2026-09-28 (up to 30 days): +2 over the period, now 972. Gaps mean no snapshot was taken that day.
QF-Lib is a Python library that provides high quality tools for quantitative finance.
Similar tools
Vectorized Python backtesting and strategy research toolkit
Iterative trading strategy research framework with walk-forward testing
Research framework for RL-enhanced Avellaneda-Stoikov market making
AI-oriented quantitative investment platform with full ML pipeline
Open-source reinforcement learning platform for quantitative trading
Event-driven backtesting engine for Python trading algorithms