moomoo-data

Moomoo OpenD data provider for HKSE/KLSE markets with capital flow analysis

A comprehensive Python library for accessing Moomoo OpenD API data, featuring:

• 📈 Real-time quotes for HKSE and KLSE stocks

• 📊 K-line data (daily, weekly, monthly, intraday)

• 💰 Capital flow analysis (super/big/mid/small order tracking)

• 🎯 Chip distribution analysis (triangular distribution model)

• 💾 Built-in caching (memory + SQLite)

• ⚡ Rate limiting with configurable limits

Installation

pip install moomoo-data

Optional dependencies

# Full installation with all features
pip install moomoo-data[all]

# SQLite caching (recommended for production)
pip install moomoo-data[cache]

Requirements

• Python 3.10+
• Moomoo OpenD gateway running locally (default: 127.0.0.1:11111)
• moomoo-api package (pip install moomoo-api)

Quick Start

from moomoo_data import get_stock_quote, get_daily_kline, get_capital_flow

# Get real-time quote
quote = get_stock_quote("0700.HK")
print(f"Price: {quote['最新价']}, Change: {quote['涨跌幅']}%")

# Get daily K-line
kline = get_daily_kline("0700.HK", count=100)
print(f"Retrieved {len(kline)} days of data")

# Get capital flow
flow = get_capital_flow("0700.HK")
print(f"Net inflow: {flow['net_inflow']}")

Configuration

Configure via environment variables or .env file:

# Moomoo OpenD connection
MOOMOO_HOST=127.0.0.1
MOOMOO_PORT=11111
MOOMOO_ENABLED=true

# Cache settings
MOOMOO_CACHE_PATH=~/.cache/moomoo-data/cache.db
MOOMOO_CACHE_ENABLED=true

# Rate limits (requests per 30 seconds)
MOOMOO_RATE_LIMIT_QUOTE=30
MOOMOO_RATE_LIMIT_KLINE=20

API Reference

Core Functions

Ticker Formats

Supported formats:

• FinGenius: 0700.HK, 7088.KL
• Moomoo: HK.00700, MY.07088

The library automatically converts between formats.

Markets Supported

Chip Analysis

The library includes a professional-grade chip distribution analyzer using:

• Triangular distribution: Spreads turnover across price range
• L-Curve decay: Models psychological selling behavior
• Dynamic bin sizing: Market-aware granularity
• NumPy vectorization: 100x faster than loops

from moomoo_data import analyze_chip_distribution

result = analyze_chip_distribution("0700.HK")
print(f"Average cost: {result['avg_cost']}")
print(f"Concentration (90%): {result['concentration_90']}%")
print(f"Profit ratio: {result['profit_ratio']}%")

Examples

See the examples/ directory for:

• 01_basic_quote.py - Real-time quotes
• 02_kline_analysis.py - K-line data retrieval
• 03_capital_flow.py - Capital flow analysis
• 04_chip_distribution.py - Chip distribution visualization

Documentation

Full API documentation: GitHub

License

MIT License - see LICENSE file for details.

Contributing

Contributions welcome! Please:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Changelog

See CHANGELOG.md for version history.