Skip to main content
  • easy to use as most of the data returned are pandas DataFrame objects

  • can be easily saved as csv, excel or json files

  • can be inserted into MySQL or Mongodb

Target Users

  • financial market analyst of China

  • learners of financial data analysis with pandas/NumPy

  • people who are interested in China financial data

Installation

pip install weibowap

Upgrade

pip install weibowap –upgrade

Quick Start

wc=crawl.WeiboCrawl()
wc.update_info()
# 查询评论
df=wc.search_comments('4554794956226910', pn=1)
print(df)
# 查询转发
df=wc.search_retweets('4554976677862363', pn=2)
print(df)
# 导出
wc.excel_save()
# 查询历史微博
df=wc.search_weibo('1742666164', pn=3)
print(df)
# 查询用户信息
info=wc.get_user_info(r'1742666164')
print(wc.df_info)

return:

            open    high   close     low     volume    p_change  ma5
date
2012-01-11   6.880   7.380   7.060   6.880   14129.96     2.62   7.060
2012-01-12   7.050   7.100   6.980   6.900    7895.19    -1.13   7.020
2012-01-13   6.950   7.000   6.700   6.690    6611.87    -4.01   6.913
2012-01-16   6.680   6.750   6.510   6.480    2941.63    -2.84   6.813
2012-01-17   6.660   6.880   6.860   6.460    8642.57     5.38   6.822
2012-01-18   7.000   7.300   6.890   6.880   13075.40     0.44   6.788
2012-01-19   6.690   6.950   6.890   6.680    6117.32     0.00   6.770
2012-01-20   6.870   7.080   7.010   6.870    6813.09     1.74   6.832

Release files for weibowap 0.0.1

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 weibowap 0.0.1
File Interpreter ABI Platform
weibowap-0.0.1-py3-none-any.whl Python 3 none any Details

Release files / weibowap-0.0.1-py3-none-any.whl

Download URL weibowap-0.0.1-py3-none-any.whl
Size 33.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
f849ae629e35ab06f0fda390b0bdb6b30fd5f7380e42c9fc0f476625859df611
BLAKE2b-256 checksum
How to use checksums
d522704fdfc1bcc31ade139d28150871fa60047fe50071ba180c2249d6a37cbe
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via Python-urllib/3.8

Release history Release notifications | RSS feed

This release

0.0.1 This release

1 release file

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