Popular Python Web Scraping Frameworks and Tools

1. Scrapy is a Python application framework designed for extracting structured data from websites, useful for data mining, information processing, or historical data storage, and can easily crawl data such as Amazon product information.

Project address: https://scrapy.org/

2. PySpider is a powerful Python-based web crawling system that offers a browser interface for writing scripts, scheduling tasks, viewing results in real time, and stores crawl results in common databases with support for task prioritization and scheduling.

Project address: https://github.com/binux/pyspider

3. Crawley can crawl website content at high speed, supports both relational and non‑relational databases, and can export data in formats such as JSON and XML.

Project address: http://project.crawley-cloud.com/

4. Portia is an open‑source visual crawler tool that allows users to scrape websites without any programming knowledge; by simply annotating pages of interest, Portia generates spiders to extract data from similar pages.

Project address: https://github.com/scrapinghub/portia

5. Newspaper is used for extracting news articles and performing content analysis, supports multithreading, and works with more than ten languages.

Project address: https://github.com/codelucas/newspaper

6. Beautiful Soup is a Python library for pulling data out of HTML or XML files, providing convenient navigation, searching, and modification of the parse tree, which can save hours or days of work.

Project address: https://www.crummy.com/software/BeautifulSoup/bs4/doc/

7. Grab is a Python framework for building web scrapers, ranging from simple five‑line scripts to complex asynchronous crawlers handling millions of pages, offering an API for HTTP requests and DOM interaction.

Project address: http://docs.grablib.org/en/latest/#grab-spider-user-manual

8. Cola is a distributed crawling framework where users only need to write a few specific functions while the system automatically distributes tasks across multiple machines, making the distributed aspect transparent.

Project address: https://github.com/chineking/cola