Scrape 2018 Chinese City Job Listings with Python and Visualize the Results

1. Scrape all city names nationwide

We start by fetching the city list from Zhaopin's city map page (http://www.zhaopin.com/citymap.html). All city names are wrapped in tags, so we extract the text of every element to obtain a complete list of Chinese cities.

2. Iterate city names to fetch job counts

For each city we send a GET request to Zhaopin's job search page with the parameters jl (city) and kw (keyword, e.g., "android"). The response contains a line like "共84个职位满足条件". Because many tags appear elsewhere, we use a regular expression to capture the number: (?!共<em>)[0-9]+(?=</em>个职位满足条件) Adding a browser‑like User‑Agent header prevents the request from being blocked.

We store the results in a dictionary, e.g. {'北京': 4205, '上海': 2702, ...}.

3. Plot data with Matplotlib

After collecting the city‑job count dictionary, we use the matplotlib library to draw a bar chart, which visualizes the distribution of job openings across cities.

4. Result display

The script prints the chart and shows the top cities with the most Android positions. By changing the keyword, the same script can analyze other professions.

Code repository: https://github.com/miqt/PythonLearn/.../ZhiLian.py Author: 痕迹 Source: http://imaster.top/