rlxbt 0.1.0

Fast trading backtester written in Rust

RLXBT: High-Performance Rust-Based Backtesting SDK

RLXBT is a high-performance algorithmic trading backtesting engine written in Rust with Python bindings. It provides institutional-grade tools for strategy development, portfolio management, and risk analysis.

Features

• Ultra High Performance: Core engine written in Rust — 4.5M+ bars/sec via Python API with zero-copy optimization.
• Pythonic API: Easy-to-use Python wrapper for strategy definition.
• Institutional Tools: Portfolio management, risk management (VaR, Drawdown), and optimization.
• Event-Driven & Vectorized: Hybrid approach for speed and flexibility.

Licensing

RLXBT is a commercial product requiring a valid license key for production use.

Plan	Max Bars	Price
Free	10K	$0/mo
Starter	500K	$29/mo
Pro	Unlimited	$79/mo

# Set via environment variable (recommended)
export RLX_LICENSE_KEY="rlx_free_yourkey_xxxx"

# Or pass directly to Backtester
backtester = Backtester(license_key="rlx_free_yourkey_xxxx")

Get your free license at rlxbt.com/pricing

See docs/LICENSING.md for full documentation.

Project Structure

• rlxbt/: The main Python package.
  • core.py: Core bindings to the Rust engine.
  • institutional/: Institutional-grade components (Portfolio, Risk, Optimization).
• src/: Rust source code for the core engine.
• examples/: Example scripts demonstrating usage.
  • basic/: Simple strategy examples.
  • institutional/: Complex hedge fund workflows.
• tests_python/: Python test suite.

Installation

Prerequisites:

• Rust (cargo)
• Python 3.8+
• maturin (pip install maturin)

Build and install in development mode:

maturin develop

Usage

Basic Strategy

from rlxbt import Strategy, Backtester

class MyStrategy(Strategy):
    def generate_signals(self, data):
        # ... logic ...
        return signals

backtester = Backtester()
backtester.run(MyStrategy(), data)

# Optional: generate + launch dashboard directly from Backtester
# (uses the last BacktestResult stored in backtester.last_result)
backtester.plot(data, port=8000, auto_open=True)

Institutional Workflow

See examples/institutional/hedge_fund_demo.py for a complete example of:

• Multi-strategy portfolios
• Risk management
• Capital allocation

Running Examples

python examples/basic/simple_test.py
python examples/institutional/hedge_fund_demo.py