Quant research & backtesting · Open-source community (originally Quantopian)

Zipline

Python backtesting library originally built by Quantopian; still usable but largely unmaintained since Quantopian shut down.

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Zipline is a Python library for event-driven backtesting of trading algorithms, originally built to power Quantopian's hosted research and backtesting platform before Quantopian shut down in 2020. It provides a strategy API for simulating order execution against historical daily and minute bars, pipeline tools for cross-sectional factor computation, and standard performance/risk statistics on completed backtests. The original repository's own README warns that it is maintained by a small team with limited bandwidth and that issues or pull requests may go unanswered for long periods; a community fork (zipline-reloaded) has since picked up compatibility fixes for newer Python and pandas versions. Treat the original package as a legacy option rather than an actively developed one.

At a glance

Vendor Open-source community (originally Quantopian)
Pricing model Open source + paid options
Free tier Yes
Deployment Self-hosted
Open source Yes (Apache-2.0)
Best for Teams maintaining legacy Quantopian-era strategy code, or researchers who need its pipeline factor API specifically.

Pricing

Free, open-source Python library with no paid tier; the original project is largely unmaintained and a community fork carries ongoing fixes.

Pricing has not been verified yet — see the vendor's site.

Features

  • Event-driven backtest simulation engine
  • Pipeline API for cross-sectional factor computation
  • Daily and minute-bar historical simulation
  • Built-in performance and risk statistics
  • Slippage and commission modeling
  • Pandas-based data handling

Integrations

Profile last reviewed September 21, 2026

Alternatives

Backtrader Open-source Python backtesting and live-trading framework for building and evaluating trading strategies. vectorbt Open-source Python library for vectorized backtesting, using NumPy/pandas array operations to test thousands of parameter combinations fast. QuantConnect Cloud algorithmic trading platform built on the open-source LEAN engine, with research notebooks and live deployment.

Zipline in the index now

Terms to know

Time series forecasting Predicting future values of a metric using patterns found in its own historical sequence over time. Backtesting Testing a trading or investment strategy against historical data to see how it would have performed.

Related guides

How to backtest a trading strategy Data quality, look-ahead and survivorship bias, realistic costs, and the evaluation metrics that separate a real edge from an overfit curve. How to choose a quant research and backtesting platform The choice is really about who owns the code — a library you control, a desktop license, or a hosted platform with data included.