Home / Backtesting & trading frameworks
AutoTrader
Archived Python framework for backtesting and virtual-broker order simulation
What it is
A Python-based platform for developing, optimising and deploying automated trading systems. Its virtual broker simulates multiple order types, stop-losses, take-profits, cross-exchange arbitrage and portfolio strategies during backtests and paper trading, with integrated data feeds, custom indicators and Bokeh visualisation. Live trading integrations exist for Oanda, with Interactive Brokers and CCXT support in progress. The project is now archived and read-only, so it is best treated as a reference for virtual-broker simulation and backtesting rather than an actively maintained tool.
At a glance
Worth watchingOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Developers |
|---|---|
| Used for | Backtesting, Live trading |
| Markets | Multi-market |
| Stack | Python |
| Learning curve | Moderate learning curve |
| Practical value | Medium practical value |
| Cost | Free and open source |
| Hardware | No GPU needed |
| Maintenance | Archived, no longer maintained |
GitHub stars, last 30 days
Daily snapshots since 2026-09-12 (up to 30 days): +1 over the period, now 1,272. Gaps mean no snapshot was taken that day.
Archived trading framework retained as a reference for virtual-broker order simulation and backtesting.
Similar tools
Python algorithmic trading framework for backtesting and live trading
Pythonic event-driven algorithmic trading library with backtesting and live trading
Archived event-driven Python algorithmic trading and backtesting library
Unified Python framework for quant data, factors, backtesting and trading
Python framework for building, backtesting, and deploying trading algorithms
Free, open-source crypto trading bot written in Python