akshare
AKShare is an elegant and simple financial data interface library for Python, built for human beings!
Decision gist · record as of 2026-08-14
Yes. AKShare is actively maintained, has no known vulnerabilities, low install friction, and a permissive MIT license. It is well-suited for quantitative research and trading workflows focused on Chinese markets. The main caveat is that data availability depends on third-party sources and interfaces may be removed; verify that the specific endpoints you need are currently available before building production systems on it.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.11 or higher (64-bit).
- Low friction installation with a pure-Python wheel.
- Actively maintained with recent commits and 22028 GitHub stars.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions; suitable for proprietary projects and closed-source applications.
last release 2026-08-13 (1 days) · last repo commit 2026-08-13 · 22,028 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 2,990,335 downloads/mo, #2,797 on PyPI
Alternatives
Verify before relying
pip install akshare
import akshare as ak
stock_data = ak.stock_zh_a_hist(symbol="000001", period="daily", start_date="20170301", end_date="20231022")
print(stock_data)- Whether all data sources remain consistently available or if interface removal (mentioned in statement) is frequent.
- Real-world latency and rate-limiting behavior when fetching large historical datasets.
- Whether the search and interface_info functions work reliably for LLM-driven discovery workflows.
What it is and what it does
AKShare is a Python library that simplifies fetching financial market data from multiple Chinese and international sources—stocks, options, futures, bonds, funds, indices—by wrapping them under a single, consistent API. It aggregates data from exchanges and financial websites (Sina Finance, East Money, Jin10, and others) and returns results as pandas DataFrames, making it easy to load historical prices, real-time quotes, and market metadata into analysis workflows.
The library includes an offline interface registry and search function, so you can discover available data endpoints by keyword without network calls—useful for programmatic resolution of data requests. It is designed for quantitative researchers, traders, and data analysts who work primarily with Chinese markets but also need access to US stock data. All data is provided for academic and research purposes only, and the maintainers note that some interfaces may be removed due to external factors.
Use it for
- Fetch historical daily OHLCV data for Chinese A-shares to backtest trading strategies or analyze price patterns.
- Retrieve real-time convertible bond quotes and metadata (conversion price, premium rate, yield-to-maturity) for bond trading analysis.
- Build a quantitative research pipeline that discovers available data endpoints by keyword search, then loads them into pandas for analysis.
- Aggregate options and futures data from multiple exchanges for portfolio risk modeling or derivative pricing studies.
- Populate a local database with daily market snapshots (stocks, funds, indices) for offline research without repeated API calls.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
AKShare is actively maintained, has no known vulnerabilities, low install friction, and a permissive MIT license. It is well-suited for quantitative research and trading workflows focused on Chinese markets. The main caveat is that data availability depends on third-party sources and interfaces may be removed; verify that the specific endpoints you need are currently available before building production systems on it.
Install
akshare on PyPI
Before you install
Low friction installation with a pure-Python wheel. Actively maintained with recent commits and 22028 GitHub stars. Supports current Python versions (3.11–3.14) and has no known vulnerabilities.
Requires Python 3.11 or higher (64-bit).
License in practice
MIT license permits commercial and private use with minimal restrictions; suitable for proprietary projects and closed-source applications.
Quickstart
pip install akshare
import akshare as ak
stock_data = ak.stock_zh_a_hist(symbol="000001", period="daily", start_date="20170301", end_date="20231022")
print(stock_data)Verify before relying
- Whether all data sources remain consistently available or if interface removal (mentioned in statement) is frequent.
- Real-world latency and rate-limiting behavior when fetching large historical datasets.
- Whether the search and interface_info functions work reliably for LLM-driven discovery workflows.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 16 packagesbeautifulsoup4lxmlpandasrequestscurl_cffihtml5libxlrdurllib3tqdmopenpyxljsonpathtabulatedecoratormini-racerpy-mini-racerakracer |
| Maintenance | Actively maintained 1 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 2,990,335 / month, #2,797 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14 |
Evidence: akshare-1.18.91-py3-none-any.whl
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