micro-sheep/efinance

efinance 是一个可以快速获取基金、股票、债券、期货数据的 Python 库,回测以及量化交易的好帮手!🚀🚀🚀

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Summary Information

Updated 2 seconds ago
Type:Library / SDKCategory(s):Fintech & Quant TradingScience & Industry
Added to GitGenius on September 17th, 2026
Created on February 25th, 2021
Open Issues & Pull Requests: 153 (+0)
GitHub issues: Enabled
Number of forks: 755
Total Stargazers: 4,063 (+0)
Total Subscribers: 64 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 24.8 hours
Mean response time: 48.3 days
90th percentile: 133.0 days
Tracked items: 43

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How this project is maintained

96% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Three people close 50% of everything that gets resolved.

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Issue Activity (beta)

Open issues: 46
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 527 days
Stale 30+ days: 44
Stale 90+ days: 42

Recent activity

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

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Detailed Description

efinance is a Python library for retrieving financial market data that supports stocks, funds, bonds, and futures.

The tool addresses the need to quickly access historical price data and market information for backtesting and quantitative trading strategies. It fetches data from Chinese financial markets, including A-shares, ETFs, and convertible bonds, alongside international stock data. The library provides multiple data granularities, from daily candlestick charts to minute-level order flow information, and includes market-specific features like stock dragon-tiger boards and quarterly performance rankings.

The project is designed for individual traders and quantitative researchers building personal trading systems. It works best for those focused on Chinese markets, particularly A-shares and related instruments, though it also supports non-A-share stocks by name or code. The tool is explicitly intended for learning and personal use rather than commercial applications. Users encountering rate limiting or network issues are directed toward alternative data sources.

Development activity shows ongoing maintenance with documentation available both online and buildable locally using Sphinx or pdoc. The project maintains a changelog tracking updates and provides installation options through pip, Docker, and source code for development purposes.