《AKShare 源码解析》课程即将上线,可加入【知识星球-数据科学家】学习!应广大小伙伴的需求,特此开设 AKShare 源码解析课程,本课程会系统的给大家手把手讲解 AKShare 数据接口的源码及财经数据的网络数据采集知识!点击链接 查看课程信息
本次发布 AKTools 作为 AKShare 的 HTTP API 版本,突破 Python 语言的限制,欢迎各位小伙伴试用并提出更好的意见或建议! 点击 AKTools 查看使用指南。另外提供 awesome-data 方便各位小伙伴查询各种数据源
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
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
stock_zh_a_hist_df = ak.stock_zh_a_hist(symbol="000001", period="daily", start_date="20170301", end_date='20210907', 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
... ... ... ... ... ... ... ... ...
1100 2021-09-01 17.48 17.88 17.92 ... 5.11 0.45 0.08 1.19
1101 2021-09-02 18.00 18.40 18.78 ... 5.48 2.91 0.52 1.25
1102 2021-09-03 18.50 18.04 18.50 ... 4.35 -1.96 -0.36 0.72
1103 2021-09-06 17.93 18.45 18.60 ... 4.55 2.27 0.41 0.78
1104 2021-09-07 18.60 19.24 19.56 ... 6.56 4.28 0.79 0.84
[1105 rows x 11 columns]
Plot
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[["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 数据科学家 Official Accounts to get more information about Quant, ML, DS and so on, please visit 数据科学家 for more information:
Pay attention to 数据科学实战 WeChat Official Accounts to get the AKShare updated info:
Application to add AKShare-VIP QQ group and talk about AKShare issues, please contact AKShare-小助手 QQ: 1254836886
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;
- Provide HTTP API for the person who uses other program language: AKTools.
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/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:
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/akfamily/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 **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 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 北京证券交易所网站;
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 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 tutorials provided by 微信公众号: Python大咖谈.