| name | akshare |
| description | Chinese financial data access using AkShare library. Fetch real-time and historical data for A-shares, Hong Kong stocks, US stocks, futures, funds, and macroeconomic indicators. Use when user requests Chinese market data, stock prices, market analysis, or financial information from Chinese exchanges. Supports stock quotes, historical data, futures market data, fund information, macroeconomic indicators, and real-time market updates. |
AkShare - Chinese Financial Data
Overview
AkShare is a free, open-source Python library for accessing Chinese financial market data. This skill provides guidance for fetching data from Chinese exchanges including Shanghai Stock Exchange, Shenzhen Stock Exchange, Hong Kong Exchange, and more.
Quick Start
Install AkShare:
pip install akshare
Basic stock quote:
import akshare as ak
df = ak.stock_zh_a_spot_em()
Stock Data
A-Shares (A股)
Real-time quotes:
df = ak.stock_zh_a_spot_em()
df = ak.stock_zh_a_spot()
Historical data:
df = ak.stock_zh_a_hist(symbol="000001", period="daily", start_date="20240101", end_date="20241231", adjust="qfq")
Stock list:
df = ak.stock_info_a_code_name()
Hong Kong Stocks (港股)
Real-time quotes:
df = ak.stock_hk_spot_em()
Historical data:
df = ak.stock_hk_hist(symbol="00700", period="daily", adjust="qfq")
US Stocks (美股)
Real-time data:
df = ak.stock_us_spot_em()
Futures Data (期货)
Real-time futures:
df = ak.futures_zh_spot()
Historical futures:
df = ak.futures_zh_hist_sina(symbol="IF0")
Fund Data (基金)
Fund list:
df = ak.fund_open_fund_info_em()
Fund historical data:
df = ak.fund_open_fund_info_em(fund="000001", indicator="单位净值走势")
Macroeconomic Indicators (宏观)
GDP data:
df = ak.macro_china_gdp()
CPI data:
df = ak.macro_china_cpi()
PMI data:
df = ak.macro_china_pmi()
Common Parameters
Period (周期):
daily - 日线weekly - 周线monthly - 月线
Adjustment (复权):
qfq - 前复权hfq - 后复权"" - 不复权
Tips
- Data caching: AkShare doesn't cache data, implement your own caching if needed
- Rate limiting: Be mindful of request frequency to avoid being blocked
- Data format: Returns pandas DataFrame, can be easily processed
- Error handling: Network errors may occur, implement retry logic
References
For complete API documentation and advanced usage, see:
