update project metadata and documentation for clarity and branding
This commit is contained in:
porcelaincode
+7
-2
@@ -2,9 +2,14 @@
|
||||
name = "raptorbt"
|
||||
version = "0.1.0"
|
||||
edition = "2021"
|
||||
description = "High-performance Rust backtesting engine for Quant5"
|
||||
authors = ["Quant5 team"]
|
||||
description = "High-performance Rust backtesting engine with Python bindings. Drop-in VectorBT replacement with up insanely faster performance at fractional memory footprint."
|
||||
authors = ["Alphabench <contact@alphabench.in>"]
|
||||
license = "MIT"
|
||||
repository = "https://github.com/alphabench/raptorbt"
|
||||
homepage = "https://github.com/alphabench/raptorbt"
|
||||
readme = "README.md"
|
||||
keywords = ["backtesting", "trading", "quantitative-finance", "rust", "python"]
|
||||
categories = ["finance", "simulation"]
|
||||
|
||||
[lib]
|
||||
name = "raptorbt"
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
MIT License
|
||||
|
||||
Copyright (c) 2024 Quant5 team
|
||||
Copyright (c) 2024 Alphabench
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to deal
|
||||
|
||||
@@ -1,6 +1,50 @@
|
||||
# RaptorBT
|
||||
|
||||
**RaptorBT** is a high-performance backtesting engine written in Rust with Python bindings via PyO3. It serves as a drop-in replacement for VectorBT, providing significant performance improvements while maintaining full metric parity.
|
||||
[](https://pypi.org/project/raptorbt/)
|
||||
[](https://opensource.org/licenses/MIT)
|
||||
[](https://www.python.org/downloads/)
|
||||
[](https://www.rust-lang.org/)
|
||||
|
||||
**Blazing-fast backtesting for the modern quant.**
|
||||
|
||||
RaptorBT is a high-performance backtesting engine written in Rust with Python bindings via PyO3. It serves as a drop-in replacement for VectorBT — delivering **HFT-grade compute efficiency** with full metric parity.
|
||||
|
||||
<p align="center">
|
||||
<strong>5,800x faster</strong> · <strong>45x smaller</strong> · <strong>100% deterministic</strong>
|
||||
</p>
|
||||
|
||||
---
|
||||
|
||||
### Quick Install
|
||||
|
||||
```bash
|
||||
pip install raptorbt
|
||||
```
|
||||
|
||||
### 30-Second Example
|
||||
|
||||
```python
|
||||
import numpy as np
|
||||
import raptorbt
|
||||
|
||||
# Configure
|
||||
config = raptorbt.PyBacktestConfig(initial_capital=100000, fees=0.001)
|
||||
|
||||
# Run backtest
|
||||
result = raptorbt.run_single_backtest(
|
||||
timestamps=timestamps, open=open, high=high, low=low, close=close,
|
||||
volume=volume, entries=entries, exits=exits,
|
||||
direction=1, weight=1.0, symbol="AAPL", config=config,
|
||||
)
|
||||
|
||||
# Results
|
||||
print(f"Return: {result.metrics.total_return_pct:.2f}%")
|
||||
print(f"Sharpe: {result.metrics.sharpe_ratio:.2f}")
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
Developed and maintained by the [Alphabench](https://alphabench.in) team.
|
||||
|
||||
## Table of Contents
|
||||
|
||||
@@ -13,8 +57,7 @@
|
||||
- [Metrics](#metrics)
|
||||
- [Indicators](#indicators)
|
||||
- [Stop-Loss & Take-Profit](#stop-loss--take-profit)
|
||||
- [Python Integration](#python-integration)
|
||||
- [VectorBT Drop-in Replacement](#vectorbt-drop-in-replacement)
|
||||
- [VectorBT Comparison](#vectorbt-comparison)
|
||||
- [API Reference](#api-reference)
|
||||
- [Building from Source](#building-from-source)
|
||||
- [Testing](#testing)
|
||||
@@ -23,7 +66,7 @@
|
||||
|
||||
## Overview
|
||||
|
||||
RaptorBT was built to address the performance limitations of VectorBT in production environments:
|
||||
RaptorBT was built to address the performance limitations of VectorBT. Benchmarked by the Alphabench team:
|
||||
|
||||
| Metric | VectorBT | RaptorBT | Improvement |
|
||||
| ----------------------------- | ------------------- | ------------ | ------------------------- |
|
||||
@@ -473,93 +516,75 @@ config.set_risk_reward_target(ratio=2.0) # 2:1 risk-reward ratio
|
||||
|
||||
---
|
||||
|
||||
## Python Integration
|
||||
## VectorBT Comparison
|
||||
|
||||
RaptorBT integrates seamlessly with the Quant5 golf runner through `rpbt.py`.
|
||||
RaptorBT is designed as a drop-in replacement for VectorBT. Here's a side-by-side comparison:
|
||||
|
||||
### Enable RaptorBT
|
||||
|
||||
```bash
|
||||
export USE_RAPTORBT=1
|
||||
```
|
||||
|
||||
Or in Python:
|
||||
### VectorBT (before)
|
||||
|
||||
```python
|
||||
import os
|
||||
os.environ["USE_RAPTORBT"] = "1"
|
||||
```
|
||||
import vectorbt as vbt
|
||||
import pandas as pd
|
||||
|
||||
### Integration Functions
|
||||
|
||||
```python
|
||||
from app.engine.golf.rpbt import (
|
||||
is_raptorbt_enabled,
|
||||
RaptorBTConfig,
|
||||
RaptorBTPortfolioWrapper,
|
||||
run_single_backtest_raptorbt,
|
||||
run_basket_backtest_raptorbt,
|
||||
run_pairs_backtest_raptorbt,
|
||||
run_options_backtest_raptorbt,
|
||||
run_multi_backtest_raptorbt,
|
||||
# Run backtest
|
||||
pf = vbt.Portfolio.from_signals(
|
||||
close=close_series,
|
||||
entries=entries,
|
||||
exits=exits,
|
||||
init_cash=100000,
|
||||
fees=0.001,
|
||||
)
|
||||
|
||||
# Check if RaptorBT is enabled
|
||||
if is_raptorbt_enabled():
|
||||
print("Using RaptorBT backend")
|
||||
# Get metrics
|
||||
print(pf.stats()["Total Return [%]"])
|
||||
print(pf.stats()["Sharpe Ratio"])
|
||||
print(pf.stats()["Max Drawdown [%]"])
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## VectorBT Drop-in Replacement
|
||||
|
||||
RaptorBT provides a `RaptorBTPortfolioWrapper` that mimics the VectorBT Portfolio interface:
|
||||
### RaptorBT (after)
|
||||
|
||||
```python
|
||||
from app.engine.golf.rpbt import (
|
||||
RaptorBTPortfolioWrapper,
|
||||
run_single_backtest_raptorbt,
|
||||
RaptorBTConfig,
|
||||
import raptorbt
|
||||
import numpy as np
|
||||
|
||||
# Configure backtest
|
||||
config = raptorbt.PyBacktestConfig(
|
||||
initial_capital=100000,
|
||||
fees=0.001,
|
||||
)
|
||||
|
||||
# Run backtest
|
||||
result = run_single_backtest_raptorbt(compiled, ohlcv_df, config, symbol)
|
||||
result = raptorbt.run_single_backtest(
|
||||
timestamps=timestamps,
|
||||
open=open_prices, high=high_prices,
|
||||
low=low_prices, close=close_prices,
|
||||
volume=volume,
|
||||
entries=entries, exits=exits,
|
||||
direction=1, weight=1.0,
|
||||
symbol="SYMBOL",
|
||||
config=config,
|
||||
)
|
||||
|
||||
# Wrap result for VectorBT compatibility
|
||||
portfolio = RaptorBTPortfolioWrapper(result)
|
||||
|
||||
# Use like VectorBT Portfolio
|
||||
stats = portfolio.stats() # Returns pd.Series with VectorBT-format keys
|
||||
equity = portfolio.value() # Returns equity curve as pd.Series
|
||||
dd = portfolio.drawdown() # Returns drawdown curve as pd.Series
|
||||
trades_df = portfolio.trades() # Returns trades as pd.DataFrame
|
||||
|
||||
# Access properties
|
||||
print(portfolio.total_return) # Total return percentage
|
||||
print(portfolio.sharpe_ratio) # Sharpe ratio
|
||||
print(portfolio.max_drawdown) # Max drawdown percentage
|
||||
print(portfolio.win_rate) # Win rate percentage
|
||||
print(portfolio.profit_factor) # Profit factor
|
||||
print(portfolio.sqn) # System Quality Number
|
||||
print(portfolio.expectancy) # Expected value per trade
|
||||
print(portfolio.omega_ratio) # Omega ratio
|
||||
# Get metrics
|
||||
print(f"Total Return: {result.metrics.total_return_pct}%")
|
||||
print(f"Sharpe Ratio: {result.metrics.sharpe_ratio}")
|
||||
print(f"Max Drawdown: {result.metrics.max_drawdown_pct}%")
|
||||
```
|
||||
|
||||
### Stats Format
|
||||
### Metric Mapping
|
||||
|
||||
The `stats()` method returns a pandas Series with VectorBT-compatible keys:
|
||||
|
||||
```python
|
||||
stats = portfolio.stats()
|
||||
print(stats["Total Return [%]"])
|
||||
print(stats["Sharpe Ratio"])
|
||||
print(stats["Max Drawdown [%]"])
|
||||
print(stats["Win Rate [%]"])
|
||||
print(stats["Profit Factor"])
|
||||
print(stats["SQN"])
|
||||
print(stats["Omega Ratio"])
|
||||
# ... and 20+ more metrics
|
||||
```
|
||||
| VectorBT Key | RaptorBT Attribute |
|
||||
| ---------------------- | ------------------------------ |
|
||||
| `Total Return [%]` | `metrics.total_return_pct` |
|
||||
| `Sharpe Ratio` | `metrics.sharpe_ratio` |
|
||||
| `Sortino Ratio` | `metrics.sortino_ratio` |
|
||||
| `Max Drawdown [%]` | `metrics.max_drawdown_pct` |
|
||||
| `Win Rate [%]` | `metrics.win_rate_pct` |
|
||||
| `Profit Factor` | `metrics.profit_factor` |
|
||||
| `SQN` | `metrics.sqn` |
|
||||
| `Omega Ratio` | `metrics.omega_ratio` |
|
||||
| `Total Trades` | `metrics.total_trades` |
|
||||
| `Expectancy` | `metrics.expectancy` |
|
||||
|
||||
---
|
||||
|
||||
@@ -686,12 +711,6 @@ maturin build --release
|
||||
pip install target/wheels/raptorbt-*.whl
|
||||
```
|
||||
|
||||
### Using the Build Script
|
||||
|
||||
```bash
|
||||
./scripts/build-engine.sh --install
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Testing
|
||||
@@ -705,9 +724,7 @@ cargo test
|
||||
|
||||
### Python Integration Tests
|
||||
|
||||
```bash
|
||||
# Test basic functionality
|
||||
uv run python -c "
|
||||
```python
|
||||
import raptorbt
|
||||
import numpy as np
|
||||
|
||||
@@ -728,13 +745,11 @@ result = raptorbt.run_single_backtest(
|
||||
)
|
||||
print(f'Total Return: {result.metrics.total_return_pct:.2f}%')
|
||||
print('RaptorBT is working correctly!')
|
||||
"
|
||||
```
|
||||
|
||||
### Comparison Test (VectorBT vs RaptorBT)
|
||||
|
||||
```bash
|
||||
USE_RAPTORBT=1 uv run python << 'EOF'
|
||||
```python
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
import vectorbt as vbt
|
||||
@@ -769,26 +784,25 @@ result = raptorbt.run_single_backtest(
|
||||
|
||||
print(f"VectorBT: {pf.stats()['Total Return [%]']:.4f}%")
|
||||
print(f"RaptorBT: {result.metrics.total_return_pct:.4f}%")
|
||||
print(f"Match: {abs(pf.stats()['Total Return [%]'] - result.metrics.total_return_pct) < 0.01}")
|
||||
EOF
|
||||
# Results should match within 0.01%
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## License
|
||||
|
||||
RaptorBT is proprietary software developed for the Quant5 platform.
|
||||
MIT License - see [LICENSE](LICENSE) for details.
|
||||
|
||||
---
|
||||
|
||||
## Changelog
|
||||
|
||||
### v0.1.0 (2024-01)
|
||||
### v0.1.0
|
||||
|
||||
- Initial release
|
||||
- 5 strategy types: single, basket, pairs, options, multi
|
||||
- 30+ performance metrics
|
||||
- 10 technical indicators
|
||||
- Fixed, ATR, and trailing stops
|
||||
- PyO3 Python bindings
|
||||
- VectorBT-compatible wrapper
|
||||
- 30+ performance metrics with full VectorBT parity
|
||||
- 10 technical indicators (SMA, EMA, RSI, MACD, Stochastic, ATR, Bollinger Bands, ADX, VWAP, Supertrend)
|
||||
- Stop-loss management: fixed, ATR-based, and trailing stops
|
||||
- Take-profit management: fixed, ATR-based, and risk-reward targets
|
||||
- PyO3 Python bindings for seamless Python integration
|
||||
|
||||
+2
-2
@@ -5,12 +5,12 @@ build-backend = "maturin"
|
||||
[project]
|
||||
name = "raptorbt"
|
||||
version = "0.1.0"
|
||||
description = "High-performance Rust backtesting engine with Python bindings"
|
||||
description = "High-performance Rust backtesting engine with Python bindings. Drop-in VectorBT replacement with up insanely faster performance at fractional memory footprint."
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
license = {file = "LICENSE"}
|
||||
authors = [
|
||||
{name = "Quant5 team"}
|
||||
{name = "Alphabench", email = "contact@alphabench.in"}
|
||||
]
|
||||
keywords = [
|
||||
"backtesting",
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
"""
|
||||
RaptorBT - High-performance Rust backtesting engine for Quant5.
|
||||
RaptorBT - High-performance Rust backtesting engine.
|
||||
|
||||
This module provides Python bindings for the Rust-based backtesting engine,
|
||||
offering significant performance improvements over vectorbt:
|
||||
|
||||
+1
-1
@@ -1,7 +1,7 @@
|
||||
// Suppress warning from PyO3 macro expansion (fixed in newer PyO3 versions)
|
||||
#![allow(non_local_definitions)]
|
||||
|
||||
//! RaptorBT - High-performance Rust backtesting engine for Quant5.
|
||||
//! RaptorBT - High-performance Rust backtesting engine.
|
||||
//!
|
||||
//! This crate provides a complete backtesting solution with:
|
||||
//! - Technical indicators (SMA, EMA, RSI, MACD, etc.)
|
||||
|
||||
Reference in New Issue
Block a user