Overview
AkShare requires Python(64 bit) 3.7 or greater, aims to make fetch financial data as convenient as possible.
Write less, get more!
- Documentation: 中文文档
- Documentation: 中文文档-国内加速访问
Installation
General
pip install akshare --upgrade
China
pip install akshare -i http://mirrors.aliyun.com/pypi/simple/ --trusted-host=mirrors.aliyun.com --upgrade
PR
Please check out documentation if you want to contribute to AkShare
Docker
Pull images
docker pull registry.cn-hangzhou.aliyuncs.com/akshare/akdocker
Run AkDocker
docker run -it registry.cn-hangzhou.aliyuncs.com/akshare/akdocker python
Test AkDocker
import akshare as ak
ak.__version__
Usage
Data
Code
import akshare as ak
hist_df = ak.stock_us_daily(symbol="AMZN") # Get U.S. stock Amazon's price info
print(hist_df)
Output
open high low close volume
date
1997-05-15 29.25 30.0000 23.1300 23.5000 6013000.0
1997-05-16 23.63 23.7500 20.5000 20.7500 1225000.0
1997-05-19 21.13 21.2500 19.5000 20.5000 508900.0
1997-05-20 20.75 21.0000 19.6300 19.6300 455600.0
1997-05-21 19.63 19.7500 16.5000 17.1300 1571100.0
... ... ... ... ...
2021-01-04 3270.00 3272.0000 3144.0200 3186.6299 4205801.0
2021-01-05 3166.01 3223.3799 3165.0601 3218.5100 2467255.0
2021-01-06 3146.48 3197.5090 3131.1599 3138.3799 4065357.0
2021-01-07 3157.00 3208.5420 3155.0000 3162.1599 3320882.0
2021-01-08 3180.00 3190.6399 3142.2000 3182.7000 3410288.0
[5951 rows x 5 columns]
Plot
Code
import akshare as ak
import mplfinance as mpf # Please install mplfinance
stock_us_daily_df = ak.stock_us_daily(symbol="AAPL", adjust="qfq")
stock_us_daily_df = stock_us_daily_df[["open", "high", "low", "close", "volume"]]
stock_us_daily_df.columns = ["Open", "High", "Low", "Close", "Volume"]
stock_us_daily_df.index.name = "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
Communication
Pay attention to 数据科学实战 WeChat Official Accounts to get the AkShare updated info:
Application to add AkShare-官方 QQ group and talk about AkShare issues, QQ group number: 772100249
Features
- Easy of use: Just one line code to fetch the data;
- Extensible: Easy to customize your own code with other application;
- Powerful: Python ecosystem.
Tutorials
Contribution
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 Black to format the code
Statement
-
All data provided by AkShare is just for academic research purpose;
-
The data provided by AkShare is for reference only and does not constitute any investment proposal;
-
Any investor based on AkShare research should pay more attention to data risk;
-
AkShare will insist on providing open-source financial data;
-
Based on some uncontrollable factors, some data interfaces in AkShare may be removed;
-
Please follow the relevant open-source protocol used by AkShare
Show your style
Use the badge in your project's README.md:
[![Data: akshare](https://img.shields.io/badge/Data%20Science-AkShare-green)](https://github.com/jindaxiang/akshare)
Using the badge in README.rst:
.. image:: https://img.shields.io/badge/Data%20Science-AkShare-green
:target: https://github.com/jindaxiang/akshare
Looks like this:
Citation
Please use this bibtex if you want to cite this repository in your publications:
@misc{akshare,
author = {Albert King},
title = {AkShare},
year = {2019},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/jindaxiang/akshare}},
}
Acknowledgement
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 生意社网站;
Thanks for the data provided by 奇货可查网站;
Thanks for the data provided by 智道智科网站;
Thanks for the data provided by **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 英为财情网站;
Thanks for the data provided by **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 金十数据网站;
Thanks for the data provided by 交易法门网站;
Thanks for the data provided by 和讯财经网站;
Thanks for the data provided by 新浪财经网站;
Thanks for the data provided by Oxford-Man Institute 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 **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 南华期货网站;
Thanks for the data provided by Economic Policy Uncertainty 网站;
Thanks for the data provided by 微博指数网站;
Thanks for the data provided by 百度指数网站;
Thanks for the data provided by 谷歌指数网站;
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 **证券投资基金业协会网站;
Thanks for the data provided by 猫眼电影网站;
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 IT桔子网站;
Thanks for the data provided by 东方财富网站;
Thanks for the data provided by 义乌小商品指数网站;
Thanks for the data provided by **国家发展和改革委员会网站;
Thanks for the data provided by 163网站;
Thanks for the data provided by 丁香园网站;
Thanks for the data provided by 百度新型肺炎网站;
Thanks for the data provided by 百度迁徙网站;
Thanks for the data provided by 新型肺炎-相同行程查询工具网站;
Thanks for the data provided by 新型肺炎-小区查询网站;
Thanks for the data provided by 商业特许经营信息管理网站;
Thanks for the data provided by 慈善**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;
Thanks for the data provided by **期货市场监控中心;
Thanks for the data provided by 宽客在线;
Thanks for the tutorials provided by 微信公众号: Python大咖谈.