📈 SimTradeLab

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Lightweight Quantitative Backtesting Framework — Local PTrade API Simulation

Local compatibility for a tested subset of PTrade backtest APIs. Portability depends on the APIs and broker behavior a strategy uses; review the support matrix. See also: ptradeAPI

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🎯 Why SimTradeLab?

	SimTradeLab	PTrade
Speed	100–160x faster	Baseline
Startup	Sub-second (data persists in memory)	Minutes
API Coverage	See the tested support matrix	Full platform
Strategy Porting	Depends on the tested API subset	Native platform
Environment	Local, free, open-source	Cloud, licensed

Core capabilities:

• ✅ Tested API classifications — current full, partial, pending, and unsupported behavior is tracked in the support matrix
• ⚡ 100–160x faster than PTrade platform
• 🚀 In-memory data persistence — singleton pattern, sub-second startup after first load
• 💾 Multi-level caching — LRU caches for MA/VWAP/adjustment factors/history, >95% hit rate
• 🧠 Smart data loading — AST analysis of strategy code, loads only required data
• 🔧 Lifecycle control — 7 lifecycle phases, strict simulation of PTrade's API restrictions
• 📊 Full stats reporting — returns, risk metrics (Sharpe/Sortino/Calmar), trade details, FIFO dividend tax, CSV export
• 🔌 Multi-market — Built-in CN (A-shares) and US market profiles with automatic trading rule adaptation
• 🌐 i18n — Backtest output in Chinese, English, or German

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🚀 Need More? Try SimTradeDesk

SimTradeDesk is a professional desktop application built on SimTradeLab — no coding required.

Feature	SimTradeLab (this repo)	SimTradeDesk
Target users	Developers & quant engineers	All traders
Interface	Python API	Desktop GUI
Strategy editing	Code editor	Built-in editor with syntax highlighting
Visualization	PNG charts	Interactive real-time charts
Data management	Manual setup	One-click download & update
Parameter tuning	Write code	Visual optimizer

👉 Get SimTradeDesk →

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📦 Quick Start

pip install simtradelab

# Optional: technical indicators (requires system ta-lib)
pip install simtradelab[indicators]

# Optional: parameter optimizer
pip install simtradelab[optimizer]

Verify the installed command-line entry point:

simtradelab --help
simtradelab --version

Data: Use SimTradeData to download China A-share and US stock historical data.

Strategy environment: Read the strategy runtime boundaries before using files, external datasets, or network libraries in strategy code.

Run a backtest:

from simtradelab.backtest.runner import BacktestRunner
from simtradelab.backtest.config import BacktestConfig

config = BacktestConfig(
    # --- Required ---
    strategy_name='my_strategy',       # Strategy folder name under strategies/
    start_date='2024-01-01',           # Backtest start date
    end_date='2024-12-31',             # Backtest end date

    # --- Capital & Market ---
    initial_capital=100000.0,          # Starting capital (must be > 0)
    market='CN',                       # Market: 'CN' (A-shares) | 'US'
    broker_profile='auto',             # Broker API profile: 'auto' | 'guosheng' | 'dongguan' | 'shanxi'
    t_plus_1=None,                     # T+1 override: None=market default (CN=True, US=False)
    benchmark_code='',                 # Benchmark code, empty=market default

    # --- Frequency ---
    frequency='1d',                    # Bar frequency: '1d' (daily) | '1m' (minute)

    # --- Paths ---
    data_path='~/.simtradelab/data',   # Market data directory
    strategies_path='./strategies',    # Strategies root directory

    # --- Performance ---
    enable_multiprocessing=True,       # Enable parallel data loading
    num_workers=None,                  # Worker count (None=auto, must be >= 1)
    use_data_server=True,              # Use in-memory data server (singleton)

    # --- Output ---
    enable_charts=True,                # Generate PNG chart
    enable_logging=True,               # Write log file
    enable_export=False,               # Export trade details to CSV

    # --- i18n ---
    locale='auto',                     # Log language: 'zh' | 'en' | 'de' (auto: CN market→zh, else system locale)
    optimization_mode=False,           # Optimization mode: skip validation/logging (managed by optimizer)

    # --- Entry file ---
    strategy_file='backtest.py',       # Entry file: 'backtest.py' | 'live.py'
)
runner = BacktestRunner()
report = runner.run(config=config)

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📚 API Overview

See the tested PTrade backtest API support matrix for the current classifications and behavioral evidence.

Category	APIs
Trading	order, order_target, order_value, order_target_value, cancel_order, get_positions, get_trades
Data	get_price, get_history, get_fundamentals, get_stock_info
Sector	get_index_stocks, get_industry_stocks, get_stock_blocks
Indicators	get_MACD, get_KDJ, get_RSI, get_CCI
Config	set_benchmark, set_commission, set_slippage, set_universe, set_parameters
Lifecycle	initialize, before_trading_start, handle_data, after_trading_end

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📄 License

Dual license model:

• AGPL-3.0 — Free for open-source projects and personal research. See LICENSE
• Commercial License — For closed-source / commercial use. See LICENSE-COMMERCIAL.md or contact kayou@duck.com

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🤝 Contributing

• 🐛 Report issues
• 💻 Implement missing API features
• 📚 Improve documentation

See CONTRIBUTING.md for CLA details.

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⚖️ Disclaimer

SimTradeLab is a community-developed, open-source backtesting framework inspired by PTrade's event-driven design. It does not contain PTrade's source code, trademarks, or any protected content. This project is not affiliated with or endorsed by PTrade. Users are responsible for compliance with local regulations and platform terms.

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⭐ Star this project if you find it useful!

🐛 Report Issue | 💡 Feature Request | 🖥️ SimTradeDesk

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