wistbean/learn_python3_spider

python爬虫教程系列、从0到1学习python爬虫,包括浏览器抓包,手机APP抓包,如...

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wistbean/learn_python3_spider has 22k+ stars and 3.5k+ forks on GitHub, is written in Python, and was last pushed on Oct 12, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 8 minutes ago
Type:Curated List / Learning ResourceCategory(s):Web Scraping & CrawlingData Engineering & Analytics
Added to GitGenius on September 2nd, 2026
Created on April 2nd, 2019
Open Issues & Pull Requests: 43 (+0)
GitHub issues: Enabled
Number of forks: 3,916
Total Stargazers: 22,189 (+0)
Total Subscribers: 373 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 0.0 hours
Mean response time: 25.3 days
90th percentile: 202.3 days
Tracked items: 8

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Issue Activity (beta)

Open issues: 7
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 611 days
Stale 30+ days: 7
Stale 90+ days: 7

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

learn_python3_spider is a Python web scraping tutorial series that teaches scraping techniques from foundational concepts through advanced implementations.

The project addresses the challenge of learning web scraping by providing structured instruction across the full spectrum of scraping concerns. It covers network traffic inspection using tools like Fiddler and mitmproxy, then progresses through the libraries and frameworks commonly used in scraping work: requests, BeautifulSoup, Selenium, Appium, and Scrapy. The material also addresses practical obstacles encountered in real scraping scenarios, including IP proxy rotation, CAPTCHA handling, and reverse-engineering encrypted CSS and JavaScript obfuscation. Database integration with MySQL and MongoDB, concurrent scraping with multithreading and multiprocessing, and distributed scraping architectures are included.

This resource suits developers new to scraping who want a comprehensive pathway rather than isolated examples, as well as those tackling specific technical challenges like mobile app scraping or JavaScript-heavy sites. The tutorial format with hands-on examples makes it appropriate for self-directed learning. The breadth of coverage—from browser developer tools through distributed systems—means learners can progress from basic HTTP requests to complex production scenarios without switching between multiple resources.

The project maintains an active repository with regular updates to its tutorial content and example code. Contributions are accepted and incorporated, indicating ongoing community engagement with the material. The codebase reflects practical, working examples rather than theoretical demonstrations, with real-world scraping scenarios included throughout.