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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

AKShare requires Python(64 bit) 3.9 or higher and aims to simplify the process of fetching financial data.

Write less, get more!

• Documentation: 中文文档

pip install akshare --upgrade

pip install akshare -i http://mirrors.aliyun.com/pypi/simple/ --trusted-host=mirrors.aliyun.com  --upgrade

Please check out Documentation if you want to contribute to AKShare

docker pull registry.cn-shanghai.aliyuncs.com/akfamily/aktools:jupyter

docker run -it registry.cn-shanghai.aliyuncs.com/akfamily/aktools:jupyter python

import akshare as ak

print(ak.__version__)

Code:

import akshare as ak

stock_zh_a_hist_df = ak.stock_zh_a_hist(symbol="000001", period="daily", start_date="20170301", end_date='20231022', adjust="")
print(stock_zh_a_hist_df)

Output:

      日期          开盘   收盘    最高  ...  振幅   涨跌幅  涨跌额  换手率
0     2017-03-01   9.49   9.49   9.55  ...  0.84  0.11  0.01  0.21
1     2017-03-02   9.51   9.43   9.54  ...  1.26 -0.63 -0.06  0.24
2     2017-03-03   9.41   9.40   9.43  ...  0.74 -0.32 -0.03  0.20
3     2017-03-06   9.40   9.45   9.46  ...  0.74  0.53  0.05  0.24
4     2017-03-07   9.44   9.45   9.46  ...  0.63  0.00  0.00  0.17
          ...    ...    ...    ...  ...   ...   ...   ...   ...
1610  2023-10-16  11.00  11.01  11.03  ...  0.73  0.09  0.01  0.26
1611  2023-10-17  11.01  11.02  11.05  ...  0.82  0.09  0.01  0.25
1612  2023-10-18  10.99  10.95  11.02  ...  1.00 -0.64 -0.07  0.34
1613  2023-10-19  10.91  10.60  10.92  ...  3.01 -3.20 -0.35  0.61
1614  2023-10-20  10.55  10.60  10.67  ...  1.51  0.00  0.00  0.27
[1615 rows x 11 columns]

Code:

import akshare as ak
import mplfinance as mpf  # Please install mplfinance as follows: pip install mplfinance

stock_us_daily_df = ak.stock_us_daily(symbol="AAPL", adjust="qfq")
stock_us_daily_df = stock_us_daily_df.set_index(["date"])
stock_us_daily_df = stock_us_daily_df["2020-04-01": "2020-04-29"]
mpf.plot(stock_us_daily_df, type="candle", mav=(3, 6, 9), volume=True, show_nontrading=False)

Output:

• Easy of use: Just one line code to fetch the data;
• Extensible: Easy to customize your own code with other application;
• Powerful: Python ecosystem.

1. Overview
2. Installation
3. Tutorial
4. Data Dict
5. Subjects

AKShare is still under developing, feel free to open issues and pull requests:

• Report or fix bugs
• Require or publish interface
• Write or fix documentation
• Add test cases

Notice: We use Ruff to format the code

1. All data provided by AKShare is just for academic research purpose;
2. The data provided by AKShare is for reference only and does not constitute any investment proposal;
3. Any investor based on AKShare research should pay more attention to data risk;
4. AKShare will insist on providing open-source financial data;
5. Based on some uncontrollable factors, some data interfaces in AKShare may be removed;
6. Please follow the relevant open-source protocol used by AKShare;
7. Provide HTTP API for the person who uses other program language: AKTools.

Use the badge in your project's README.md:

[![Data: akshare](https://img.shields.io/badge/Data%20Science-AKShare-green)](https://github.com/akfamily/akshare)

Using the badge in README.rst:

.. image:: https://img.shields.io/badge/Data%20Science-AKShare-green
    :target: https://github.com/akfamily/akshare

Looks like this:

Please use this bibtex if you want to cite this repository in your publications:

@misc{akshare,
    author = {Albert King and Yaojie Zhang},
    title = {AKShare},
    year = {2019},
    publisher = {GitHub},
    journal = {GitHub repository},
    howpublished = {\url{https://github.com/akfamily/akshare}},
}

Special thanks FuShare for the opportunity of learning from the project;

Special thanks TuShare for the opportunity of learning from the project;

Thanks for the data provided by 东方财富网站;

Thanks for the data provided by 新浪财经网站;

Thanks for the data provided by 金十数据网站;

Thanks for the data provided by 生意社网站;

Thanks for the data provided by 中国银行间市场交易商协会网站;

Thanks for the data provided by 99期货网站;

Thanks for the data provided by 中国外汇交易中心暨全国银行间同业拆借中心网站;

Thanks for the data provided by 和讯财经网站;

Thanks for the data provided by DACHENG-XIU 网站;

Thanks for the data provided by 上海证券交易所网站;

Thanks for the data provided by 深证证券交易所网站;

Thanks for the data provided by 北京证券交易所网站;

Thanks for the data provided by 中国金融期货交易所网站;

Thanks for the data provided by 上海期货交易所网站;

Thanks for the data provided by 大连商品交易所网站;

Thanks for the data provided by 郑州商品交易所网站;

Thanks for the data provided by 上海国际能源交易中心网站;

Thanks for the data provided by Timeanddate 网站;

Thanks for the data provided by 河北省空气质量预报信息发布系统网站;

Thanks for the data provided by Economic Policy Uncertainty 网站;

Thanks for the data provided by 申万指数网站;

Thanks for the data provided by 真气网网站;

Thanks for the data provided by 财富网站;

Thanks for the data provided by 中国证券投资基金业协会网站;

Thanks for the data provided by Expatistan 网站;

Thanks for the data provided by 北京市碳排放权电子交易平台网站;

Thanks for the data provided by 国家金融与发展实验室网站;

Thanks for the data provided by 义乌小商品指数网站;

Thanks for the data provided by 百度迁徙网站;

Thanks for the data provided by 思知网站;

Thanks for the data provided by Currencyscoop 网站;

Thanks for the data provided by 新加坡交易所网站;

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