Skip to main content
  • It’s easy to use because most of the data returned are pandas DataFrame objects

  • We have our own data server, efficient and stable operation

  • Free china stock market data

  • Friendly to machine learning and data mining

Target Users

  • China Financial Market Analyst

  • Financial data analysis enthusiasts

  • Quanters who are interested in china stock market

Installation

pip install baoshare

Upgrade

pip install baoshare –upgrade

Quick Start

import baostock as bs
import pandas as pd

# 登陆系统
lg = bs.login(user_id="anonymous", password="123456")
# 显示登陆返回信息
print(lg.error_code)
print(lg.error_msg)
# 详细指标参数,参见“历史行情指标参数”章节
rs = bs.query_history_k_data("sh.601398",
    "date,code,open,high,low,close,volume,amount,adjustflag",
    start_date='2017-01-01', end_date='2017-01-31',
    frequency="d", adjustflag="3")
print(rs.error_code)
print(rs.error_msg)
# 获取具体的信息
result = pd.DataFrame(columns=["date","code","open","high","low","close","volume","amount","adjustflag"])
while (rs.error_code == '0') & rs.next():
    # 分页查询,将每页信息合并在一起
    result = result.append(rs.get_row_data(), ignore_index=True)
result.to_csv("D:\history_k_data.csv", index=False)
print(result)
# 登出系统
bs.logout()

return:

          date       code    open    high     low   close preclose     volume
0   2017-01-03  sh.601398  4.4000  4.4300  4.3900  4.4300   4.4100  104161632
1   2017-01-04  sh.601398  4.4200  4.4400  4.4100  4.4300   4.4300  118923425
2   2017-01-05  sh.601398  4.4300  4.4500  4.4200  4.4400   4.4300   87356137
3   2017-01-06  sh.601398  4.4400  4.4500  4.4300  4.4400   4.4400   87008191
4   2017-01-09  sh.601398  4.4500  4.4800  4.4300  4.4600   4.4400  117454094
5   2017-01-10  sh.601398  4.4500  4.4700  4.4400  4.4600   4.4600   63663257
6   2017-01-11  sh.601398  4.4600  4.4800  4.4500  4.4700   4.4600   52395427
7   2017-01-12  sh.601398  4.4600  4.4700  4.4400  4.4700   4.4700   62166279

             amount adjustflag      turn tradestatus
0    460087744.0000          3  0.038634           1
1    526408816.0000          3  0.044109           1
2    387580736.0000          3  0.032401           1
3    386138112.0000          3  0.032272           1
4    523539392.0000          3  0.043564           1
5    283646224.0000          3  0.023613           1
6    233898107.0000          3  0.019434           1
7    277258304.0000          3  0.023058           1

Metadata

Release files for baoshare 0.5.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for baoshare 0.5.5
File Interpreter ABI Platform
baoshare-0.5.5-py3-none-any.whl Python 3 none any Details

Release files / baoshare-0.5.5-py3-none-any.whl

Download URL baoshare-0.5.5-py3-none-any.whl
Size 16.4 kB
Tags Python 3
SHA-256 checksum
How to use checksums
73bef7083f3fb7f10f749a246c59be4eb213c8574633b547c664db73bc04652d
BLAKE2b-256 checksum
How to use checksums
79cfc9a01d481e7d1caa53dac9274204a2c57c406c48a05a25f78cc4cc867046
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No

Release history Release notifications | RSS feed

This release

0.5.5 This release

1 release file

0.5.4

2 release files

0.5.3

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page