Features

• Event-driven backtesting — initialize → rundaily → handledata (JoinQuant/Zipline compatible)
• A-share data — Daily/minute/tick, fundamentals, money flow, north-bound capital, limit up/down stats
• Risk analysis — Sharpe, Sortino, max drawdown, alpha/beta, Brinson attribution
• Portfolio risk — VaR, correlation, concentration, kill switch
• Paper trading — Run strategies with real-time data + DingTalk/Feishu notifications
• PTrade/QMT adapter — One-click export to broker platforms
• Web Studio — Browser-based strategy development (no Python install needed)

Quick Start

pip install easyquant-eqlib
python -c "from eqlib import *; print('eqlib OK')"

from eqlib import *
def initialize(context):     g.security = '601390'     set_benchmark('000300.XSHG')     rundaily(marketopen, time='every_bar')
def market_open(context):     hist = attribute_history(g.security, 20, '1d', ['close'])     if hist['close'].iloc[-1] > hist['close'].mean() * 1.02:         ordervalue(g.security, context.portfolio.availablecash)
result = runstrategy(initialize, startdate='2024-01-01',                       end_date='2024-12-31', securities=['601390'])

Documentation

| Resource | Description | |----------|-------------| | Docs Site | Full documentation with search and dark theme | | Tutorials | Zero to production, 11 step-by-step guides | | How-to Guides | Task-oriented guides by scenario | | API Reference | All public APIs with parameters and examples | | Examples | 20+ runnable example scripts + Web Studio bonus strategies | | FAQ | Troubleshooting and common questions |

Installation

# From PyPI (recommended)
pip install easyquant-eqlib
From source (for contributors)
git clone https://github.com/AlanFokCo/EasyQuant.git
cd EasyQuant
pip install -e ".[dev]"
python -m pytest tests/

Requirements: Python 3.10+ · macOS / Linux / Windows

Contributing

See CONTRIBUTING.md for guidelines.

License

MIT License

Disclaimer: This project is for educational and research purposes only. It does not constitute investment advice.