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zipline-reloaded
Event-driven backtesting engine for Python trading algorithms
What it is
A Pythonic event-driven system for backtesting trading strategies, originally developed and used by the crowd-sourced investment fund Quantopian and now maintained by Stefan Jansen. It offers built-in statistics such as moving averages and linear regression, uses Pandas DataFrames for input and output, and integrates with matplotlib, scipy, statsmodels, and scikit-learn. The library suits Python algo traders and readers of Machine Learning for Algorithmic Trading who want a research-oriented backtesting engine. As a community-maintained continuation of a defunct platform, it depends on the surrounding PyData stack and requires some setup effort with packages like exchange_calendars.
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 | US equities, Multi-market |
| Stack | Python |
| Learning curve | Steep learning curve |
| Practical value | High practical value |
| Cost | Free and open source |
| Hardware | No GPU needed |
| Maintenance | Commits today |
GitHub stars, last 30 days
Daily snapshots since 2026-09-12 (up to 30 days): +22 over the period, now 1,960. Gaps mean no snapshot was taken that day.
Zipline, a Pythonic Algorithmic Trading Library.
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