akshare

Chinese financial data access using AkShare library for OpenClaw

安装方式
CLI
npx skills add https://github.com/succ985/openclaw-akshare-skill --skill akshare

使用 CLI 安装这个技能,并在你的工作区中直接复用对应的 SKILL.md 工作流。

最后更新于 4/22/2026

OpenClaw AkShare Skill

Chinese financial data access using AkShare library for OpenClaw.

Overview

This skill provides easy access to Chinese financial market data through the AkShare library. It supports real-time and historical data for:

  • A-shares (A股): Shanghai and Shenzhen stock exchanges
  • Hong Kong stocks (港股): HKEX
  • US stocks (美股): US market data
  • Futures (期货): Commodity and index futures
  • Funds (基金): Open-end and ETF funds
  • Macroeconomic indicators (宏观): GDP, CPI, PMI, and more

Installation

Prerequisites

  • Python 3.7+
  • OpenClaw framework

Install AkShare

pip install akshare

Or use the provided installation script:

bash scripts/install_akshare.sh

Install the Skill

Copy this skill to your OpenClaw workspace:

cp -r openclaw-akshare-skill /path/to/openclaw/workspace/skills/akshare

Quick Start

Basic Stock Quote

import akshare as ak

# Get all A-shares real-time data
df = ak.stock_zh_a_spot_em()
print(df.head())

Historical Stock Data

# Get historical daily data for a specific stock
df = ak.stock_zh_a_hist(
    symbol="000001",
    period="daily",
    start_date="20240101",
    end_date="20241231",
    adjust="qfq"  # Forward adjustment
)
print(df.tail())

Features

Stock Data

  • Real-time quotes: All A-shares, Hong Kong stocks, US stocks
  • Historical data: Daily, weekly, monthly periods with price adjustment
  • Stock list: Complete stock code and name information

Futures Data

  • Commodity futures real-time data
  • Historical futures data from major exchanges

Fund Data

  • Open-end fund information
  • Fund historical net value trends

Macroeconomic Indicators

  • GDP, CPI, PPI, PMI
  • Economic calendar and indicators

Common Parameters

Period (周期)

  • daily - Daily (日线)
  • weekly - Weekly (周线)
  • monthly - Monthly (月线)

Price Adjustment (复权)

  • qfq - Forward adjustment (前复权)
  • hfq - Backward adjustment (后复权)
  • "" - No adjustment (不复权)

Examples

See the scripts/ directory for more examples:

  • example_usage.py - Common usage examples
  • test_basic.py - Basic functionality tests
  • test_quick.py - Quick start examples

Documentation

Tips

  1. Data caching: AkShare doesn't cache data by default. Implement your own caching if needed
  2. Rate limiting: Be mindful of request frequency to avoid being blocked
  3. Data format: Returns pandas DataFrame, can be easily processed
  4. Error handling: Network errors may occur, implement retry logic

License

MIT License - see LICENSE file for details

Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

Changelog

See CHANGELOG.md for version history.

Acknowledgments

  • AkShare - The underlying Python library for Chinese financial data
  • OpenClaw - The AI assistant framework

Support

For issues and questions: