Home / Backtesting & trading frameworks

nautilus_trader

Backtesting & trading frameworks★ 29,821 GitHub starsRust⏱ Commits today

Rust-native algorithmic trading platform and event-driven backtester

What it is

An open-source, production-grade trading engine built around a Rust core, with Python serving as the control plane for strategy logic, configuration, and orchestration. It spans research, deterministic simulation, and live execution in a single event-driven architecture, and the same strategy and execution-algorithm code can run across backtest and live systems. Multi-asset and multi-venue by design, it integrates any REST API or WebSocket feed through modular adapters, covering crypto exchanges, FX, equities, futures, options, and betting exchanges. Traders who want compiled-engine performance with Python flexibility will find it suitable, though live execution involves venue, transport, timing, and reconciliation behavior that a simulation may not reproduce.

At a glance

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

Best forProfessional quants
Used forBacktesting, Live trading
MarketsMulti-market
StackPython + Rust
Learning curveSteep 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): +1k over the period, now 29,821. Gaps mean no snapshot was taken that day.

In the author's words

A high-performance algorithmic trading platform and event-driven backtester.

Open on GitHub ↗This week's trending tools中文页面

Similar tools