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Backtesting & trading frameworks★ 2,117 GitHub starsPython⏱ Commits today

Python algorithmic trading framework for backtesting and live trading

What it is

An open-source Python framework for algorithmic trading where the same strategy code can be used for both backtesting and live trading across stocks, options, crypto, futures, forex, and prediction markets. It supports multiple broker integrations, including Alpaca and Interactive Brokers, and provides a strategy lifecycle that separates trading logic from broker configuration, along with backtesting that produces trade logs and tearsheets without requiring an API key. Traders and developers who want to test rule-based or AI-agent strategies on historical data before deploying through a broker will find it useful. The framework requires configuring a broker account for live trading, and converting a backtest-only example into live trading involves more than flipping a setting, since run mode must be selected explicitly.

At a glance

Worth watchingOur rating, based on popularity, maintenance and how ready it is for real use.

Best forDevelopers
Used forBacktesting, Live trading
MarketsMulti-market
StackPython
Learning curveModerate learning curve
Practical valueHigh practical value
CostFree and open source
HardwareNo GPU needed
MaintenanceCommits today

GitHub stars, last 30 days

Daily snapshots since 2026-09-12 (up to 30 days): +62 over the period, now 2,117. Gaps mean no snapshot was taken that day.

In the author's words

Algorithmic trading framework where the same code runs for backtesting and live trading across stocks, options, crypto, futures, and forex with multiple brokers including Alpaca, Interactiv

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