Top Python Web Scraping Frameworks You Should Know

The editor has collected several efficient Python web‑crawling frameworks to share.

Scrapy

Scrapy is an application framework designed for crawling websites and extracting structured data. It can be used for data mining, information processing, or storing historical data, and makes it easy to scrape data such as Amazon product information.

Project URL: https://scrapy.org/

PySpider

PySpider is a powerful Python‑based web crawling system that provides a browser interface for writing scripts, scheduling tasks, and viewing results in real time. It stores results in common databases, supports task prioritization and scheduling.

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

Crawley

Crawley can crawl website content at high speed, supports relational and non‑relational databases, and can export data as JSON, XML, etc.

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

Portia

Portia is an open‑source visual crawler tool that lets you scrape websites without any programming knowledge. By simply annotating pages of interest, Portia creates a spider to extract data from similar pages.

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

Newspaper

Newspaper can extract news, articles, and perform content analysis. It uses multithreading and supports more than ten languages.

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

Beautiful Soup

Beautiful Soup is a Python library for extracting data from HTML or XML files. It provides convenient navigation, searching, and modification of the parse tree, saving hours or days of work.

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

Grab

Grab is a Python framework for building web scrapers. With Grab you can create simple five‑line scripts or complex asynchronous crawlers handling millions of pages. It offers an API for making HTTP requests and interacting with the DOM tree.

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

Cola

Cola is a distributed crawling framework. Users only need to write a few specific functions; the framework handles task distribution across multiple machines transparently.

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