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Lightweight Quantitative Backtesting Framework — Local PTrade API Simulation

Full PTrade API simulation — strategies transfer seamlessly between SimTradeLab and PTrade. See also: ptradeAPI

Core capabilities:

• ✅ 46 APIs — 100% coverage of stock backtesting scenarios (daily & minute bars)
• ⚡ 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

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

👉 Get SimTradeDesk →

pip install simtradelab

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

# Optional: parameter optimizer
pip install simtradelab[optimizer]

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

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'
    # 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

    # --- Sandbox & i18n ---
    # sandbox=True,                    # PTrade sandbox: restrict imports & builtins
    # locale='auto',                   # Log language: 'zh' | 'en' | 'de' (auto: CN market→zh, else system locale)
)
runner = BacktestRunner()
report = runner.run(config=config)

46 backtest/research APIs — 100% stock backtesting coverage.

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 [email protected]

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

See CONTRIBUTING.md for CLA details.

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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