akshare

v1.15.29

AKShare is an elegant and simple financial data interface library for Python, built for human beings! For more information about how to use this package see README

Latest version published 1 day ago

License: MIT

PyPI

GitHub

Package Health Score

91 / 100

security
No known security issues
popularity
Influential project
maintenance
Healthy
community
Active

Explore Similar Packages

tushare
58

Popularity

Influential project

GitHub Stars: 9.47K
Forks: 1.9K
Contributors: 80

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package akshare, we found that it has been starred 9,470 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Nov 21, 2024
Direct Vulnerabilities: 0
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0
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0
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0
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Indirect Vulnerabilities: 0
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0
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0
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License Risk: 0
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0
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

MIT

Security Policy

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Maintenance

Healthy

Commit Frequency

Open Issues: 0
Open PR: 0
Last Release: 1 day ago
Last Commit: 3 days ago

Further analysis of the maintenance status of akshare based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Healthy.

We found that akshare demonstrates a positive version release cadence with at least one new version released in the past 3 months.

As a healthy sign for on-going project maintenance, we found that the GitHub repository had at least 1 pull request or issue interacted with by the community.

Community

Active

Readme: Yes
Contributing.md: Yes
Code of Conduct: Yes
Contributors: 80
Funding: No

With more than 10 contributors for the akshare repository, this is possibly a sign for a growing and inviting community.

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Package

Python Versions Compatibility: >=3.8

Age: 6 years
Latest Release: 1 day ago
Dependencies: 0 Direct
Versions: 2.38K
Maintainers: 1
Wheels: OS Independent

Not sure how to use akshare?

To help you get started, we've collected the most common ways that akshare is being used within popular public projects.

jindaxiang / akshare / akshare / index / request.py View on Github

def interest_over_time(self):
        """Request data from Google's Interest Over Time section and return a dataframe"""

        over_time_payload = {
            # convert to string as requests will mangle
            "req": json.dumps(self.interest_over_time_widget["request"]),
            "token": self.interest_over_time_widget["token"],
            "tz": self.tz,
        }

        # make the request and parse the returned json
        req_json = self._get_data(
            url=TrendReq.INTEREST_OVER_TIME_URL,
            method=TrendReq.GET_METHOD,
            trim_chars=5,
            params=over_time_payload,
        )

        df = pd.DataFrame(req_json["default"]["timelineData"])
        if df.empty:
            return df

        df["date"] = pd.to_datetime(df["time"].astype(dtype="float64"), unit="s")
        df = df.set_index(["date"]).sort_index()
        # split list columns into seperate ones, remove brackets and split on comma
        result_df = df["value"].apply(
            lambda x: pd.Series(str(x).replace("[", "").replace("]", "").split(","))
        )
        # rename each column with its search term, relying on order that google provides...

View more ways to use akshare

欢迎加入专注于财经数据和量化投资的知识社区，请点击了解更多

量化投研视频课程：《PyBroker-入门及实战》已经上架！

更多视频教程已经发布：《AKShare-初阶-使用教学》、《AKShare-初阶-实战应用》、《AKShare-源码解析》、《开源项目巡礼》，详情请关注【数据科学实战】公众号，查看更多课程信息！

AKQuant 量化教程请访问：利用 PyBroker 进行量化投资

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。

AKShare Logo

Overview

AKShare requires Python(64 bit) 3.8 or higher and aims to simplify the process of fetching financial data.

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-shanghai.aliyuncs.com/akfamily/aktools:jupyter

Run Container

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

Test

import akshare as ak

print(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='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]

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.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:

KLine

Communication

Welcome to join the 数据科学实战 knowledge planet to learn more about quantitative investment, please visit 数据科学实战 for more information:

Pay attention to 数据科学实战 WeChat Official Accounts to get the AKShare updated info:

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 Ruff 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 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 英为财情网站;

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 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 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 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 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 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 中国国家发展和改革委员会网站;

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

Thanks for the data provided by 慈善中国网站;

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.

Backer and Sponsor

FAQs

What is akshare?

AKShare is an elegant and simple financial data interface library for Python, built for human beings!. Visit Snyk Advisor to see a full health score report for akshare, including popularity, security, maintenance & community analysis.

Is akshare popular?

The python package akshare receives a total of 101,289 weekly downloads. As such, akshare popularity was classified as an influential project. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is akshare well maintained?

We found that akshare demonstrated a healthy version release cadence and project activity. It has a community of 80 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is akshare safe to use?

The python package akshare was scanned for known vulnerabilities and missing license, and no issues were found. Thus the package was deemed as safe to use. See the full health analysis review.

Last updated on 21 November-2024, at 20:06 (UTC).

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