Backtrader

GitHub statistics as of 2026-11-10. Status: active = commits in the last 90 days, slowing = in the last year, inactive = older, archived = read-only.

Overview

Backtrader runs a strategy bar by bar, the way it would trade live, with brokers, sizers, analyzers and more than a hundred built-in indicators. It became the default choice for Python backtesting in the late 2010s, and a lot of tutorials and Stack Overflow answers still use it. It has seen very little development in recent years (see the last-commit date above), but the code is stable.

Best for: Learning backtesting, strategies with complex order logic, and porting rule-based systems such as MT4/MT5 Expert Advisors.

Strengths

• Realistic event-driven simulation: orders, stops, partial fills, commissions
• Huge amount of examples and community answers
• Multiple data feeds and timeframes in one strategy

Limitations

• Slow for large parameter sweeps compared with vectorized libraries
• No longer actively developed; plotting can break with newer Matplotlib
• Live-trading brokers are dated

From our own use

Quant Arena's EA Arena runs on Backtrader: 1,063 Expert Advisors converted from MQL5 are re-run every month on four markets of hourly data, about one second per run.

Comparisons

Alternatives in Backtesting libraries