nautechsystems

    nautechsystems/nautilus_trader

    Production-grade Rust-native trading engine with deterministic event-driven architecture

    31.3K stars
    4.2K forks
    229 GitHub watchers
    Updated Nov 8, 2026
    View on GitHub

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    Where it stands

    Rank, growth pace and release cadence relative to everything GStars tracks.

    5 releases in the last 90 days, the latest 9 days ago, with 227 contributors on GitHub.

    Peaked at #2 in the weekly ranking the week of Aug 16, its best in the past year.

    Use Cases & Benefits

    • Provides a production-grade, Rust-native algorithmic trading engine with a deterministic event-driven architecture for backtesting and live trading.
    • Ensures parity between backtesting and live trading by allowing identical Python-native strategy implementations with high performance and type safety.
    • Use for developing and deploying high-frequency trading strategies across multiple asset classes including crypto, equities, futures, and options.
    • Use for integrating diverse market data and trading venues via modular adapters supporting REST APIs and WebSocket feeds for multi-venue trading.
    • Use for training AI trading agents with fast backtesting capabilities suitable for reinforcement learning and evolutionary strategies.

    Should you depend on it?

    License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.

    License

    LGPL 3.0

    Weak copyleft: changes to the licensed code itself must be shared when you distribute it, but code that merely uses it can stay under your own license.

    Community files

    • README: present
    • Contributing guide: present
    • Code of conduct: present

    Watch-outs

    No watch-outs from GStars' checks.

    General guidance from repository metadata, not legal advice. How we score

    From the README

    NautilusTrader is an open-source, high-performance, production-grade algorithmic trading platform, providing quantitative traders with the ability to backtest portfolios of automated trading strategies on historical data with an event-driven engine, and also deploy those same strategies live, with no code changes.

    The platform is AI-first, designed to develop and deploy algorithmic trading strategies within a highly performant and robust Python-native environment. This helps to address the parity challenge of keeping the Python research/backtest environment consistent with the production live trading environment.

    NautilusTrader's design, architecture, and implementation philosophy prioritizes software correctness and safety at the highest level, with the aim of supporting Python-native, mission-critical, trading system backtesting and live deployment workloads.

    The platform is also universal, and asset-class-agnostic — with any REST API or WebSocket feed able to be integrated via modular adapters. It supports high-frequency trading across a wide range of asset classes and instrument types including FX, Equities, Futures, Options, Crypto, DeFi, and Betting, enabling seamless operations across multiple venues simultaneously.

    nautilus - from ancient Greek 'sailor' and naus 'ship'.

    The nautilus shell consists of modular chambers with a growth factor which approximates a logarithmic spiral. The idea is that this can be translated to the aesthetics of design and architecture.

    Excerpt from the nautechsystems/nautilus_trader README on GitHub (LGPL-3.0 license). © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Aug 14: +16Aug 17: +188Aug 18: +443Aug 19: +134Aug 20: +316Aug 27: +89Aug 28: +66Aug 29: +65Aug 30: +58Aug 31: +63Sep 1: +61Sep 2: +44Sep 3: +32Sep 4: +25Sep 5: +34Sep 6: +97Sep 7: +101Sep 8: +57Sep 9: +44Sep 10: +36Sep 11: +37Sep 12: +51Sep 13: +47Sep 14: +54Sep 15: +55Sep 16: +47Sep 17: +43Sep 18: +33Sep 19: +10Sep 22: +12Oct 28: +55Oct 29: +56

    +5,884 stars over 87 days across 42 snapshot days; best day +443 on Aug 18.

    Forks

    4.2K+899

    Open issues

    165+62

    Compared with peers in AI

    Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth

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