akshare Documentation

1. Project Overview & Quickstart (akfamily/akshare) Copy Chapter

AKShare

AKShare is an open-source Python financial data interface library.

It provides public financial market data and alternative data from many sources,
especially for China markets, including A-share, Hong Kong stocks, U.S.
stocks, funds, futures, options, bonds, forex, macroeconomic indicators,
industry data, news, and cryptocurrency data.

AKShare is designed around a simple idea: write less, get more. Most public
interfaces return pandas.DataFrame objects and are meant to be called from the
top-level package.

Install Copy Chapter

Use pip:

pip install akshare --upgrade

Python Entry Point Copy Chapter

Import AKShare as:

import akshare as ak

All public interfaces are exposed from the top-level package and are typically
called as:

ak.function_name(...)

Do not assume users need to import submodules directly unless you are working on
AKShare internals.

Documentation Copy Chapter

Main entry points:

• README.md
• docs/tutorial.md
• docs/data/
• Online docs: https://akshare.akfamily.xyz/
• Data interface index: https://akshare.akfamily.xyz/data/index.html

The most important interface documentation is organized by category under
docs/data/.

Interface Registry (Offline Search) Copy Chapter

AKShare ships a small, bundled interface registry to help locate function
names without manually grepping through docs/data/:

• ak.search(query): keyword search across interface names, descriptions,
  categories, and output columns. Returns a ranked pandas.DataFrame.
• ak.interface_info(name): full metadata for one interface, including
  input parameters, output columns, and an example snippet.
• ak.list_categories(): lists all categories with interface counts.

This registry is entirely offline: its data ships inside the package and
no network request is made, so it is safe to call before deciding whether
a network call is worth making.

It is a keyword/substring matcher, not a semantic search engine. It is
best at pinpointing an interface by exact or near-exact name and at
narrowing candidates by keyword — it does not reliably understand natural
language intent.

import akshare as ak

ak.search("A股 历史行情")
ak.interface_info("stock_zh_a_hist")

Core Usage Pattern Copy Chapter

Recommended workflow:

1. Identify the asset class or topic.
2. Find the matching documentation page under docs/data/.
3. Use the documented public function from akshare.
4. Inspect the returned DataFrame columns before downstream processing.

Major Categories Copy Chapter

Common data categories include:

• stock: stock market data, including A-share, Hong Kong stocks, U.S.
  stocks, spot data, historical data, and stock information
• stock_feature: rankings, capital flow, margin trading, technical data, and
  market feature datasets
• stock_fundamental: company fundamentals, financial statements, equity
  structure, and disclosures
• fund: public fund data, ETFs, rankings, holdings, managers, and net value
• futures: domestic and global futures market data
• option: option market data
• bond: bond and convertible bond data
• index: market index data
• forex and fx: foreign exchange data
• macro and economic: macroeconomic and statistical data
• news: financial news and information
• crypto: cryptocurrency market data
• tool: trading calendar and utility datasets

Naming Conventions Copy Chapter

AKShare function names usually encode both the topic and the data source.

Common suffixes include:

• _em: EastMoney
• _sina: Sina
• _ths: Tonghuashun
• _cninfo: CNINFO
• _xq: Xueqiu

Choose functions based on documented behavior, not only by suffix similarity.

Return Types And Parameters Copy Chapter

Common conventions:

• Most public interfaces return pandas.DataFrame.
• Date parameters are often strings such as YYYYMMDD.
• Symbol parameters may use market-specific codes.
• Returned column names are often Chinese because they follow upstream data
  semantics or established AKShare conventions.

Important Notes For LLMs And Agents Copy Chapter

When helping users with AKShare:

• Prefer documented public functions over internal helpers.
• Prefer top-level calls such as ak.stock_zh_a_hist(...) instead of submodule
  imports.
• Check docs/data/ before guessing interface names.
• Many interfaces depend on upstream public websites and may break when
  upstream providers change.
• Data freshness can vary by source; if results look stale, verify whether the
  upstream source still provides updated data.
• Inspect returned columns before making assumptions about field names, units,
  or semantics.

Example Function Families Copy Chapter

Representative examples:

• ak.stock_zh_a_spot_em()
• ak.stock_zh_a_hist(...)
• ak.stock_individual_info_em(...)
• ak.fund_open_fund_info_em(...)
• ak.futures_zh_spot()
• ak.option_current_em()
• ak.bond_zh_hs_cov_spot()
• ak.macro_china_cpi()
• ak.news_cctv()
• ak.crypto_hist(...)

Project Structure Copy Chapter

AKShare is organized by domain subpackages under akshare/, but user-facing
calls are flat through the top-level package.

Important structure:

• Source code: akshare/
• Public API export hub: akshare/__init__.py
• Main documentation: docs/
• Data interface docs: docs/data/

If Editing AKShare Source Copy Chapter

When adding or fixing a public interface:

• Keep the external API stable whenever possible.
• Add the public import to akshare/__init__.py, or users cannot call it as
  ak.function_name(...).
• Update the corresponding documentation under docs/data/.
• Update docs/changelog.md for user-visible fixes or new interfaces.

Preferred Guidance Style Copy Chapter

If you are an LLM or coding agent helping a user:

1. Clarify the market, asset class, and target dataset.
2. Identify the most likely documented interface.
3. Provide a minimal working AKShare example.
4. Explain likely parameter formats.
5. Mention upstream availability or freshness limits when relevant.

2. Official Technical Reference & Guides (akfamily/akfamily.github.io) Copy Chapter

Welcome to AKFamily's Homepage

Introduction Copy Chapter

• AKShare is an elegant and simple financial data interface library for Python, built for human beings!
• AKQuant is an elegant and simple quantitative investment tutorial documentation!
• AKTools is an elegant and simple HTTP API library for AKShare, built for AKSharers!
• AKFDS shows most powerful knowledge in financial data science!
• Awesome-data shows most interesting data-source around the financial world!

Documentation Copy Chapter

• AKShare Docs: https://akshare.akfamily.xyz
• AKQuant Docs: https://akquant.akfamily.xyz
• AKTools Docs: https://aktools.akfamily.xyz
• AKFDS Docs: https://akfds.akfamily.xyz