Zipline Reloaded
Community-maintained version of Zipline, the event-driven Python backtester originally built and used by Quantopian.
A respected classic, but now in maintenance mode; new projects are pointed elsewhere by its own maintainer.
Who it is for
Python users following the 'Machine Learning for Trading' material or porting old Quantopian code.
Strengths
- Event-driven backtesting with pandas-based inputs and outputs.
- Installable with pip or conda-forge.
- Mature and widely documented thanks to its Quantopian history.
Good to know
- The maintainer now limits it to bug, security and compatibility fixes and recommends evaluating 'ML4T Backtest' for new projects.
- Data has to be ingested into 'bundles' before running, which is a hurdle for beginners.
- Major releases (2.4, 3.0) introduced breaking changes in dependencies.
Want a bot built on Zipline Reloaded, or something similar?
We set it up, connect it to your accounts and keep it running.
Real-life uses
Momentum rotation strategy
Ranks a universe each month and rotates into the strongest, fully backtested first.
Sources
Every fact on this page comes from these sources, checked on 2026-10-24. If something has changed, the source wins; tell us at contact@tradebotcheck.com.
- https://github.com/stefan-jansen/zipline-reloaded: history, maintenance status, features, installation, Apache-2.0 license
Alternatives in Backtesting
Backtrader
Classic Python library for backtesting strategies, widely used in tutorials.
bt
Python library to backtest portfolio strategies (allocation, weighting, rebalancing) built from reusable building blocks.
PyBroker
Python framework for backtesting trading strategies, especially machine-learning ones, with a Numba-accelerated engine and walk-forward analysis.
QuantConnect (LEAN)
Cloud platform to research, backtest and trade strategies, built on the open-source LEAN engine.