Nautilus Trader launches

Algorithmic trading software usually has two jobs: test a strategy on old market data and run that same strategy with real orders. NautilusTrader says its new open-source release does both with Python on top of a Rust core. (github.com, pypi.org) The project is published by Nautech Systems as `nautilus_trader` on the Python Package Index, where version 1.225.0 was listed on April 16, 2026. Its GitHub repository showed about 21,800 stars and roughly 2,600 forks when checked Thursday. (pypi.org, github.com) Rust is a compiled language often used when developers want speed and tighter memory controls; Python is easier to write and change quickly. NautilusTrader’s docs say Python handles strategy logic and configuration, while the engine underneath runs as a deterministic event-driven system with nanosecond-resolution timing. (pypi.org, nautilustrader.io) That setup targets a common problem in trading software: researchers often prototype in Python, then rebuild the strategy for live use in another stack. NautilusTrader says the same execution model runs in both backtests and live deployment so firms can move code from research to production without rewriting it. (pypi.org, nautilustrader.io) The package page and website say the engine supports backtesting across multiple venues, instruments and strategies at once, including quote ticks, trade ticks, bars, order books and custom data. The company also lists live trading, multi-venue execution, advanced order instructions and optional Redis-backed state persistence among the production features. (pypi.org, nautilustrader.io) Nautech Systems is pitching quick setup as part of the launch. The getting-started guide says users can install the package with `pip install -U nautilus_trader`, and the quickstart is designed to run a first backtest in five minutes with synthetic data and no external downloads. (github.com, github.com) The current support matrix is narrower than “runs anywhere.” The installation guide says official support covers Python 3.12 through 3.14 on Ubuntu 22.04 or later for x86_64 and Arm64, macOS 15.0 or later on Arm64, and Windows Server 2022 or later on x86_64. (github.com) The docs also spell out trade-offs. The high-level backtesting path uses a Parquet-based data catalog and is recommended for production workflows, while the low-level API works with in-memory data but “has no live-trading path”; the project also warns that running multiple backtest or trading nodes in the same process is not supported. (github.com) Nautech Systems says it founded the company in 2015 and built the project for professional quantitative traders and small teams. The launch pitch is straightforward: keep Python where traders write ideas, move the heavy lifting into Rust, and use one engine for both simulation and live markets. (github.com, pypi.org)