Branch	Version	Status
master
nightly
develop

• Docs: https://nautilustrader.io/docs/
• Website: https://nautilustrader.io
• Support: support@nautilustrader.io

Introduction

NautilusTrader is an open-source, production-grade, Rust-native engine for multi-asset, multi-venue trading systems.

The system spans research, deterministic simulation, and live execution within a single event-driven architecture, with Python serving as the control plane for strategy logic, configuration, and orchestration.

This separation provides the performance and safety of a compiled trading engine with the flexibility of Python for system composition and strategy development. Trading systems can also be written entirely in Rust for mission-critical workloads.

The same strategy and execution-algorithm code can run across backtest and live systems, reducing deployment divergence. Live execution still introduces venue, transport, timing, persistence, external-activity, and reconciliation behavior that a simulation may not reproduce. See Backtest and live differences.

NautilusTrader is asset-class-agnostic. Any venue with a REST API or WebSocket feed can be integrated through modular adapters. Current integrations span crypto exchanges (CEX and DEX), traditional markets (FX, equities, futures, options), and betting exchanges.

Features

• Fast: Rust core with the mimalloc allocator and asynchronous networking using tokio.
• Reliable: Type- and thread-safety backed by Rust, with optional Redis-backed state persistence.
• Portable: Runs on Linux, macOS, and Windows. Deploy using Docker.
• Flexible: Modular adapters integrate any REST API or WebSocket feed.
• Advanced: Time in force IOC, FOK, GTC, GTD, DAY, AT_THE_OPEN, AT_THE_CLOSE, advanced order types and conditional triggers. Execution instructions post-only, reduce-only, and icebergs. Contingency orders including OCO, OUO, OTO.
• Customizable: User-defined components, or assemble entire systems from scratch using the cache and message bus.
• Backtesting: Multiple venues, instruments, and strategies simultaneously using historical quote tick, trade tick, bar, order book, and custom data with nanosecond resolution.
• Live: Identical strategy implementations between research and live deployment.
• Multi-venue: Run market-making and cross-venue strategies across multiple venues simultaneously.
• AI Training: Engine fast enough to train AI trading agents (RL/ES).

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.

Why NautilusTrader?

Trading strategy research is often conducted in Python using vectorized approaches, while production trading systems are implemented separately using event-driven architectures in compiled languages.

NautilusTrader removes this separation.

A Rust-native core provides a deterministic event-driven runtime for both research and live execution, while Python serves as the control plane. The same architecture, execution semantics, and time model operate across both environments, allowing strategies to move from research to production without reimplementation.

Python bindings are provided via PyO3 for the Rust-native v2 runtime. During the v2 transition, v1 receives only critical security backports on the develop_v1 branch. See the v2 migration guide for migration steps and compatibility details. No Rust toolchain is required to install prebuilt wheels.

This project makes the Soundness Pledge:

"The intent of this project is to be free of soundness bugs. The developers will do their best to avoid them, and welcome help in analyzing and fixing them."

Integrations

NautilusTrader is modularly designed to work with adapters, enabling connectivity to trading venues and data providers by translating their raw APIs into a unified interface and normalized domain model.

The following integrations are available or planned; see docs/integrations/ for details:

Name	ID	Type	Status	Docs
AX Exchange	AX	Derivatives Exchange		Guide
Betfair	BETFAIR	Sports Betting Exchange		Guide
Binance	BINANCE	Crypto Exchange (CEX)		Guide
Blockchain	BLOCKCHAIN	DeFi Data Provider		Guide
Bybit	BYBIT	Crypto Exchange (CEX)		Guide
CoinAPI	COINAPI	Data Provider		Guide
Coinbase	COINBASE	Crypto Exchange (CEX)		Guide
Databento	DATABENTO	Data Provider		Guide
Deribit	DERIBIT	Crypto Exchange (CEX)		Guide
Derive	DERIVE	Crypto Exchange (DEX)		Guide
dYdX	DYDX	Crypto Exchange (DEX)		Guide
FinFeed	FINFEED	Data Provider		-
Hyperliquid	HYPERLIQUID	Crypto Exchange (DEX)		Guide
Interactive Brokers	INTERACTIVE_BROKERS	Brokerage (multi-venue)		Guide
Kalshi	KALSHI	Prediction Market (CEX)		-
Kraken	KRAKEN	Crypto Exchange (CEX)		Guide
Lighter	LIGHTER	Crypto Exchange (DEX)		Guide
Lighter on Robinhood	LIGHTER_ROBINHOOD	Crypto Exchange (DEX)		Guide
OKX	OKX	Crypto Exchange (CEX)		Guide
Polymarket	POLYMARKET	Prediction Market (DEX)		Guide
Tardis	TARDIS	Crypto Data Provider		Guide

• ID: The default client ID for the integrations adapter clients.
• Type: The type of integration (often the venue type).

For Lighter on Robinhood, LIGHTER_ROBINHOOD is the venue and explicit client ID to register. The shared Lighter factory keeps LIGHTER as its compatibility default.

Status

• planned: Planned for future development.
• building: Under construction and likely not in a usable state.
• beta: Completed to a minimally working state and in a beta testing phase.
• stable: Stabilized feature set and API, the integration has been tested by both developers and users to a reasonable level (some bugs may still remain).

See the Integrations documentation for further details.

Roadmap

The Roadmap outlines NautilusTrader's strategic direction. Current priorities include stabilizing the Rust-native core, improving documentation, and enhancing code ergonomics.

The open-source project focuses on single-node backtesting and live trading for individual and small-team quantitative traders. UI dashboards, distributed orchestration, and built-in AI/ML tooling are out of scope to maintain focus on the core engine and ecosystem sustainability. Additional external integrations (such as databases, cloud services, and monitoring tools) are also out of scope unless explicitly listed in the open-source scope.

New integration proposals within the open-source scope should start with an RFC issue to discuss suitability before submitting a PR. See Community-contributed integrations for guidelines.

Security

Security is a priority for the NautilusTrader project. We apply security controls across dependency selection, development, builds, and releases.

• Rust dependencies come only from crates.io; lock files pin dependencies with cryptographic checksums.
• New dependency and tooling versions observe a publication cooldown before adoption.
• Third-party Python packages install from wheels only.
• cargo-vet audits Rust dependency provenance.
• cargo-deny enforces a license allow list compatible with LGPL-3.0-only.
• TLS and most runtime cryptography use AWS-LC through Rust's aws-lc-rs.
• Ed25519 signing uses ed25519-dalek.
• Gitleaks screens for secrets and Zizmor audits GitHub Actions at pre-commit.
• CODEOWNERS require review of critical infrastructure, dependency manifests, and lock files.
• Protected branches require signed commits and passing CI.
• CodeQL runs on release PRs to master and pushes to nightly.
• Audit-relevant PRs and daily audits run cargo-audit, cargo-deny, and cargo-vet.
• OSV Scanner and pip-audit also run on audit-relevant PRs and daily.
• cargo-fuzz targets cover selected adapter and signing surfaces.
• GitHub Actions are pinned to commit SHAs; hardened CI runners restrict network egress to an allow list.
• Python artifacts carry SLSA build provenance.
• Container images are Sigstore-signed with attested SPDX SBOMs.
• PyPI and crates.io use OIDC Trusted Publishing through a protected release environment.
• The release environment never runs PR or fork code.
• Release tags are immutable.

OpenSSF Scorecard provides an automated repository-health signal alongside manual review, CI hardening, and security audits.

Reporting a vulnerability

Report privately through GitHub Security Advisories or email security@nautechsystems.io (PGP key available on request).

• We acknowledge reports within 48 hours and patch critical vulnerabilities within 30 days.
• We thank and credit reporters in the relevant advisory and release notes unless they prefer anonymity.

See the following for details:

• Security Policy: scope, coordinated disclosure, and step-by-step release verification.
• Security Architecture: the release supply chain from build to publication.
• Responsible Disclosure: full disclosure policy.
• Supply Chain Security: full supply chain policy.
• CI/CD security: GitHub Actions security controls.

Versioning and releases

We aim to follow a bi-weekly release schedule, though experimental or larger features may cause delays.

Branches

We aim to maintain a stable, passing build across all branches.

• master: Reflects the source code for the latest released version; recommended for production use.
• nightly: Daily snapshots of the develop branch for early testing; merged at 14:00 UTC and as required.
• develop: Active development branch for contributors and feature work.

Precision mode

NautilusTrader supports two precision modes for its core value types (Price, Quantity, Money), which differ in their internal bit-width and maximum decimal precision.

• High-precision: 128-bit integers with up to 16 decimals of precision, and a larger value range.
• Standard-precision: 64-bit integers with up to 9 decimals of precision, and a smaller value range.

See the Installation Guide for further details.

Rust feature flag: To enable high-precision mode in Rust, add the high-precision feature to your Cargo.toml:

[dependencies]
nautilus-model = { version = "*", features = ["high-precision"] }

Installation

We recommend using the latest supported version of Python and installing nautilus_trader inside a virtual environment to isolate dependencies.

There are two supported ways to install:

1. Pre-built binary wheel from PyPI or the Nautech Systems package index.
2. Build from source.

From PyPI

This repository and the documentation cover v2. To install the v2 release-candidate wheels from PyPI using Python's pip package manager:

pip install -U nautilus_trader --pre

The v2 release-candidate wheels use 2.0.0rcN versions and are intended for community testing before the final 2.0.0 release. We do not recommend using release candidates in production environments, such as live trading controlling real capital.

The --pre flag is required until 2.0.0 is released. Without it, pip installs the latest stable v1 wheel, whose Python API differs from the v2 documentation:

# Installs the latest stable v1 wheel, which cannot run the v2 documentation
pip install -U nautilus_trader

Install optional dependencies for interactive tearsheets and charts with the visualization extra:

pip install -U "nautilus_trader[visualization]" --pre

See the Installation Guide for details.

From the Nautech Systems package index

The Nautech Systems package index (packages.nautechsystems.io) complies with PEP-503 and hosts both stable and development binary wheels for nautilus_trader. This enables users to install either the latest stable release or pre-release versions for testing.

Stable wheels

Stable wheels correspond to official releases of nautilus_trader on PyPI, and use standard versioning. As on PyPI, the latest stable release is still on the 1.x line, whose Python API differs from these v2 docs. This index also hosts development wheels, so --pre allows those versions too. To install a specific 2.x release candidate, pin its version (nautilus_trader==2.0.0rcN).

To install the latest stable release:

pip install -U nautilus_trader --index-url=https://packages.nautechsystems.io/simple

Development wheels

The main package index publishes v2 development wheels from both the nightly and develop branches, allowing users to test features and fixes ahead of stable releases.

This process also helps preserve compute resources and provides easy access to the exact binaries tested in CI pipelines, while adhering to PEP-440 versioning standards:

• develop wheels use the version suffix .devYYYYMMDD+run.
• nightly wheels use .devYYYYMMDD when the base version is already a pre-release, and aYYYYMMDD otherwise.

Installation commands

By default, pip will install the latest stable release. Adding the --pre flag ensures that pre-release versions, including development wheels, are considered.

To install the latest available pre-release (including development wheels):

pip install -U nautilus_trader --pre --index-url=https://packages.nautechsystems.io/simple

Available versions

You can view all available versions of nautilus_trader on the package index.

To programmatically fetch and list available versions:

curl -s https://packages.nautechsystems.io/simple/nautilus-trader/index.html | sed -n 's/.*<a href="\([^"]*\)".*/\1/p' | awk -F'#' '{print $1}' | sort

Branch updates

• develop branch wheels (.devYYYYMMDD+run): Build and publish continuously with every merged commit.
• nightly branch wheels (.devYYYYMMDD or aYYYYMMDD): Build and publish daily when we automatically merge the develop branch at 14:00 UTC (if there are changes).

Retention policies

• develop branch wheels: We retain only the most recent wheel build.
• nightly branch wheels: We retain only the 30 most recent publication dates per platform.

Verifying build provenance

All release artifacts published by the project carry cryptographic attestations generated by the CI/CD pipeline:

• Python wheels and source distribution (PyPI, GitHub Releases, Nautech Systems package index): SLSA build provenance.
• Docker images (ghcr.io/nautechsystems/nautilus_trader, ghcr.io/nautechsystems/jupyterlab): keyless cosign signatures plus SPDX SBOM attestations.

Both are issued via Sigstore and bound to a specific commit SHA, so verification ensures the artifact was produced by the official NautilusTrader GitHub Actions workflow and has not been tampered with since.

For step-by-step verification commands, see Verifying releases in SECURITY.md.

From source

It's possible to install from source using pip if you first install the build dependencies as specified in the pyproject.toml.

1. Install rustup (the Rust toolchain installer):

   • Linux and macOS:

     curl https://sh.rustup.rs -sSf | sh
     

   • Windows:

     • Download and install rustup-init.exe
     • Install "Desktop development with C++" using Build Tools for Visual Studio 2022

   • Verify (any system): from a terminal session run: rustc --version

2. Enable cargo in the current shell:

   • Linux and macOS:

     source $HOME/.cargo/env
     

   • Windows:

     • Start a new PowerShell

3. Install clang (a C language frontend for LLVM):

   • Linux (also installs lld, used as the Rust linker for faster builds):

     sudo apt-get install clang lld
     

   • macOS:

     xcode-select --install
     

   • Windows:

     1. Add Clang to your Build Tools for Visual Studio 2022:

        • Start | Visual Studio Installer | Modify | C++ Clang tools for Windows (latest) = checked | Modify

     2. Enable clang in the current shell:

        [System.Environment]::SetEnvironmentVariable('path', "C:\Program Files\Microsoft Visual Studio\2022\BuildTools\VC\Tools\Llvm\x64\bin\;" + $env:Path,"User")
        

   • Verify (any system): from a terminal session run: clang --version

4. Install uv (see the uv installation guide for more details):

   • Linux and macOS:

     curl -LsSf https://astral.sh/uv/install.sh | sh
     

   • Windows (PowerShell):

     irm https://astral.sh/uv/install.ps1 | iex
     

5. Clone the source with git, then sync its dependencies from the project root:

   git clone --branch develop --depth 1 https://github.com/nautechsystems/nautilus_trader
   cd nautilus_trader
   make sync
   

6. Use the uv project environment.

   The uv project environment lives at python/.venv, beside python/pyproject.toml. Run direct uv project commands from python/ or pass --project python from the repository root.

   For PyO3 compilation on Linux and macOS, run these commands from the repository root after make sync in Bash or Zsh. For Fish commands, see the developer guide's environment setup. Set PYO3_PYTHON in each shell to this checkout's python/.venv/bin/python; replace any saved export that still points to the root .venv/bin/python.

   # Set the Python executable path for PyO3
   export PYO3_PYTHON="$PWD/python/.venv/bin/python"
   
   # Linux only: Set the library path for the uv-managed Python runtime
   PYTHON_LIB_DIR="$("$PYO3_PYTHON" -c 'import sysconfig; print(sysconfig.get_config_var("LIBDIR"))')"
   export LD_LIBRARY_PATH="$PYTHON_LIB_DIR${LD_LIBRARY_PATH:+:$LD_LIBRARY_PATH}"
   
   # Required for Rust tests when using uv-installed Python
   export PYTHONHOME="$("$PYO3_PYTHON" -c 'import sys; print(sys.base_prefix)')"
   

7. Build and install NautilusTrader in release mode:

   make build
   

See the Installation Guide for other options and further details.

Redis

Using Redis with NautilusTrader is optional and only required if configured as the backend for a cache database or message bus. See the Redis section of the Installation Guide for further details.

Makefile

A Makefile is provided to automate most installation and build tasks for development. Some of the targets include:

• make install: Installs in release build mode with all dependency groups and extras.
• make install-debug: Same as make install but with debug build mode.
• make sync: Installs Python dependencies without building the package.
• make build: Builds and installs the package in release mode (default).
• make build-debug: Builds and installs the package in debug mode.
• make build-wheel: Builds a wheel in release mode.
• make cargo-test: Runs all Rust crate tests using cargo-nextest.
• make clean: Deletes build artifacts, caches, and build directories.
• make distclean: CAUTION Removes all artifacts not in the git index when run with FORCE=1. This includes source files which have not been git added.
• make docs: Builds the Python documentation with Sphinx and the Rust documentation with Cargo.
• make pre-commit: Runs the pre-commit checks over all files.
• make ruff: Runs Ruff over all files using python/pyproject.toml (with autofix).
• make pytest: Runs all tests with pytest.
• make cargo-ci-benches: Builds the Rust benchmarks used by CI.
• make cargo-codspeed-build: Builds the Rust benchmark subset used for CodSpeed comparisons.

Examples

Indicators and strategies can be developed in Python or Rust. For performance and latency-sensitive applications, we recommend Rust. Below are some examples:

• indicator implementations exposed through PyO3.
• backtest examples using a BacktestEngine directly.
• EMA crossover backtest example written in Rust.

Docker

Docker containers are built with the following variant tags:

• nautilus_trader:latest has the latest release version installed.
• nautilus_trader:nightly has the head of the nightly branch installed.
• jupyterlab:latest has the latest release version installed along with jupyterlab and an example backtest notebook with accompanying data.
• jupyterlab:nightly has the head of the nightly branch installed along with jupyterlab and an example backtest notebook with accompanying data.

You can pull the container images as follows:

docker pull ghcr.io/nautechsystems/<image_variant_tag> --platform linux/amd64

You can launch the backtest example container by running:

docker pull ghcr.io/nautechsystems/jupyterlab:nightly --platform linux/amd64
docker run -p 8888:8888 ghcr.io/nautechsystems/jupyterlab:nightly

Then open your browser at the following address:

http://127.0.0.1:8888/lab

Development

We aim to provide the most pleasant developer experience possible for this hybrid Rust and Python codebase. See the Developer Guide for helpful information.

Nautilus Engineering maintains the engineering standards, lint configuration, pre-commit definitions, tool pins, and repository checks shared across Nautilus projects. This repository vendors selected files at the revision recorded in .nautilus-engineering.lock; project-specific policy and CI wiring remain local.

After changes to PyO3 bindings, stub annotations, or wrapped Rust docs, regenerate the generated Python artifacts from the repository root:

make py-stubs

Commit the generated .pyi files and PyO3 wrapper doc comments changed by this target. See Generated Python artifacts for details.

Testing with Rust

cargo-nextest is the standard Rust test runner for NautilusTrader. Its key benefit is isolating each test in its own process, ensuring test reliability by avoiding interference. See the Rust testing guidance for details about full-suite support and the limits of plain cargo test.

You can install cargo-nextest by running:

cargo install cargo-nextest

Contributing

Thank you for considering a contribution to NautilusTrader. We welcome high-quality work that improves the project. Before starting a substantial change, open an issue to discuss the problem and approach with the team. Small, self-contained fixes do not require prior agreement.

Before getting started, be sure to review the open-source scope outlined in the project's roadmap to understand what's in and out of scope.

Once you're ready to start working on your contribution, make sure to follow the guidelines outlined in the CONTRIBUTING.md file. This includes signing a Contributor License Agreement (CLA) to ensure that your contributions can be included in the project.

Thank you again for your interest in NautilusTrader! We look forward to reviewing your contributions and working with you to improve the project.

Community

Join our community of users and contributors on Discord to chat and stay up-to-date with the latest announcements and features of NautilusTrader. Whether you're a developer looking to contribute or just want to learn more about the platform, all are welcome on our Discord server.

Features and integrations excluded by the open-source scope are also out of scope for discussion across official NautilusTrader channels, including GitHub and Discord. This includes "Show & Tell" posts about downstream implementations, even when no contribution is offered and no support or upstream inclusion is requested. Correctness and performance reports about the core trading engine remain welcome. Keep those reports focused on the core behavior.

License

The source code for NautilusTrader is available on GitHub under the GNU Lesser General Public License v3.0. Contributions to the project are welcome and require the completion of a standard Contributor License Agreement (CLA).

NautilusTrader™ is developed and maintained by Nautech Systems, a technology company specializing in the development of high-performance trading systems. For more information, visit https://nautilustrader.io.

Use of this software is subject to the Disclaimer.

© 2015-2026 Nautech Systems Pty Ltd. All rights reserved.