prism-quant 1.0.4

A-share low-frequency quantitative trading framework covering research, backtesting, and execution (formerly prism_quant)

PrismQuant

中文 | English

Python Open-source Quantitative Framework: Covering the full "Research, Backtest, Trade" lifecycle, building an industrial-grade closed-loop quantitative workflow from scratch to production.

🎓 Official Tutorials

iMOOC - AI Quantitative System Course

Official Course: Deeply deconstructing the framework's architecture from 0 to 1, covering live trading logic and industrial-grade quantitative development. An essential course for mastering PrismQuant.

📦 Installation

pip install prism_quant

For previous version source code, visit: https://pypi.org/project/prism_quant/#history

✨ Key Features

• 📥 Multi-source Data - Global multi-market historical/real-time data, ready to use
• 🧠 Rapid Development - Signal-driven architecture, fast implementation with strategy templates
• 📉 Professional Backtesting - High-performance matching engine, deep performance metrics and analysis
• ⚡ Event-driven - Second-level market data distribution, millisecond-level Tick signal processing
• 🤖 Live Gateway - Pluggable adapters, seamless switching between simulation and live trading

⚡ Quick Start

import prism_quant as prq

# 1. Define strategy logic
class MyStrategy( prq.strategy.BaseStrategy):
    def generate_signals(self, data):
        bands = prq.indicators.TechnicalIndicators().boll(data["Close"])
        return prq.strategy.SignalGenerator().boll_signals(data["Close"], bands)

# 2. Minimal backtest & results
engine = prq.backtest.BacktestEngine()
engine.set_parameters("GOOGL", "2025-07-26", "2026-01-26")
engine.load_data()
engine.add_strategy(MyStrategy(name="BOLL"))
engine.run_backtest()
engine.show_report()
engine.show_chart(use_plotly=False)

🚀 Application Example

PrismQuant is an open-source quantitative trading cloud platform based on prism_quant, integrating data services, strategy management, and trading access with paper and live support. Project: https://github.com/Delta-F/prism_quant/

🔌 Interface Integration

• [Data] yfinance ✅ - US, A-shares, HK, Crypto, Indices
• [Data] eastmoney ✅ - OTC Funds (Index, QDII, Stock, Bond, Mixed)
• [Data] miniQMT ✅ - A-share market data integration (see live trading section in the course)
• [Trade] PaperTrade ✅ - Local simulation, tick-driven order matching, position and order management
• [Trade] miniQMT Trade ✅ - A-share live trading (see live trading section in the course)

Minimal miniQMT live trade setup

from prism_quant.live import LiveEngine

engine = LiveEngine(symbol="000001.SZ", signal_interval="1m")
engine.set_data_gateway("miniqmt", interval=3.0, mode="poll")
engine.set_trade_gateway(
    "miniqmt",
    userdata_mini_path=r"D:\BrokerQMT\userdata_mini",
    account_id="1234567890",
)

See details:

• documents/LiveEngine.md
• documents/MiniQmtTrade.md
• documents/MiniQmtLiveEngine.md

🏗️ Project Architecture

prism_quant/
├── core/                          # Base classes, config, logging
│   ├── base.py
│   ├── config.py
│   └── logger.py
├── data/                          # Fetch, clean, store, source mapping
│   ├── fetcher.py
│   ├── cleaner.py
│   ├── storage.py
│   ├── source_map.py
│   └── miniqmt_xtdata.py          # miniQMT / xtquant historical bars
├── indicators/                    # Technical & fundamental factors
│   ├── technical.py
│   ├── fundamental.py
│   └── talib_indicators.py
├── strategy/                      # Strategy base & signal generation
│   ├── base.py
│   └── signals.py
├── backtest/                      # Backtest engine, metrics, reporting
│   ├── engine.py
│   ├── metrics.py
│   └── performance.py
├── live/                          # Event engine, gateways, LiveEngine
│   ├── event_engine.py
│   ├── gateways.py                # DataGateway / TradeGateway abstractions
│   ├── gateway_registry.py        # Gateway factory & registry
│   ├── engine.py                  # LiveEngine orchestration
│   └── models.py                  # TickData, OrderRequest, …
├── adapters/                      # Pluggable data / trade adapters
│   ├── data/                      # Data gateways (yfinance, miniQMT, …)
│   │   ├── yfinance_gateway.py
│   │   └── miniqmt_gateway.py
│   └── trade/                     # Trade gateways (Paper, miniQMT, …)
│       ├── paper_gateway.py
│       ├── miniqmt_client.py      # xttrader client wrapper
│       └── miniqmt_gateway.py     # Limit orders / cancel for LiveEngine
├── trader/                        # Matching, orders, positions
│   ├── engine.py
│   ├── order_manager.py
│   └── position_manager.py
└── charts/                        # Signal, price & performance charts
    ├── signals.py
    ├── price.py
    └── performance.py

🤝 Contributing

• Feedback: Bug reports and contributions are welcome via Issue or Pull Requests.
• WeChat Official Account: Follow PrismQuant开源量化 for updates, strategies, and quantitative resources.

📄 License

MIT License. See LICENSE for details.