Using GoPUP: A Python Library for Easy Access to Public Data APIs

Hello everyone, I’m Cui Qingcai. Happy National Day! Besides holiday fun, I spent some time learning and want to share a useful tool.

Introduction

The library is called GoPUP (GitHub: https://github.com/justinzm/gopup). It wraps many public APIs, for example the wx_hot_list method to get real‑time WeChat hot article rankings.

Basic Usage

Install the library with pip:

pip3 install gopup

Upgrade later with:

pip3 install -U gopup

After installation you can import the library and call its methods. The example below shows how to fetch the Weibo index for a keyword.

import gopup as gp
df_index = gp.weibo_index(word="疫情", time_type="3month")
print(df_index)

The weibo_index API requires two parameters:

Name

Type

Required

Description

word

str

Y

Keyword

time_type

str

Y

One of "1hour", "1day", "1month", "3month"

The output parameters are:

Name

Type

Default

Description

date

datetime

Y

Date index

index

float

Y

Index value

The result is a Pandas DataFrame, e.g.:

疫情  index
2022-07-04 1518338
2022-07-05 1950590
... ...
[93 rows x 1 columns]

To view it more clearly you can run the code in a Jupyter notebook:

pip3 install jupyter
jupyter notebook

Visualization example using Matplotlib:

import matplotlib.pyplot as plt
plt.figure(figsize=(15,5))
plt.title("微博‘疫情’热度走势图")
plt.xlabel("时间")
plt.ylabel("指数")
plt.plot(df_index.index, df_index['疫情'], '-', label="指数")
plt.legend()
plt.grid()
plt.show()

The chart displays the trend of the keyword’s popularity over time.

More Data Sources

GoPUP aggregates many public APIs, covering categories such as:

Index data: Weibo, Baidu, Google, etc.

Statistical data: regional, city, age, gender analyses.

Macro data: Chinese macro‑economic indicators, exchange rates.

Interest rate data: SHIBOR, LPR.

Company data: unicorns, bankruptcies.

Information data: news scripts.

Life data: oil prices, fuel price history.

Poetry data: Tang dynasty poems.

Film & TV data: box office, viewership indices.

University data: lists of Chinese higher‑education institutions.

Pandemic data: NetEase, DingXiangYuan, etc.

For a full list see the official documentation: http://doc.gopup.cn/#/README.

With GoPUP you can skip writing crawlers and directly use ready‑made datasets for analysis and visualization.

That’s all for GoPUP – give it a try!