akfamily/akshare

AKShare is an elegant and simple financial data interface library for Python, built for human beings! 开源财经数据接口库

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Summary Information

Updated 30 minutes ago
Added to GitGenius on September 2nd, 2026
Created on October 1st, 2019
Open Issues & Pull Requests: 7 (+0)
GitHub issues: Enabled
Number of forks: 3,498
Total Stargazers: 22,467 (+3)
Total Subscribers: 263 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 4.9 hours
Mean response time: 32.4 hours
90th percentile: 42.8 hours
Tracked items: 1,445

How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 19% of issues opened in the past year have been closed. Three people close 92% of everything that gets resolved.

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Issue Activity (beta)

Open issues: 5
New in 7 days: 4
Closed in 7 days: 0
Avg open age: 1 days
Stale 30+ days: 0
Stale 90+ days: 0

Recent activity

Opened in 7 days: 3
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 2

Top labels

  • bug (1,190)

Detailed Description

AKShare is a financial data interface library for Python that provides unified access to market and economic data sources.

The library solves the problem of fragmented financial data access by offering a single, consistent API for retrieving stock prices, futures, options, bonds, currencies, economic indicators, and asset pricing data. Rather than requiring developers to learn multiple vendor APIs or parse disparate data formats, AKShare abstracts these differences behind a simple, human-friendly interface. The tool handles the underlying complexity of connecting to various Chinese and international financial data providers, allowing users to focus on analysis rather than data acquisition.

AKShare suits quantitative researchers, financial analysts, and data scientists working with Python who need reliable access to market fundamentals and economic datasets. It is particularly valuable for those building trading systems, conducting academic research, or performing asset pricing studies. The library's breadth of coverage across stocks, derivatives, bonds, and macroeconomic indicators makes it useful for multi-asset analysis workflows. Teams already working in the Python ecosystem will find integration straightforward, as the tool is designed as a standard library rather than requiring external infrastructure.

The project maintains steady development activity with regular updates to data source integrations and API improvements. The maintainers respond to issues and pull requests consistently, indicating active stewardship of the codebase. Documentation is comprehensive and includes examples for common use cases, supporting both new and experienced users. The project has established itself as a stable resource within the financial data tools ecosystem, with ongoing attention to keeping data connectors functional as upstream providers change their interfaces.