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Today I recommend some more efficient Python crawler frameworks to everyone. Share it with everyone.
1.Scrapy
Scrapy is an application framework written to crawl website data and extract structural data. It can be used in a series of programs including data mining, information processing or storing historical data. Using this framework, you can easily crawl down data such as Amazon product information. (Recommended learning: Python video tutorial)
Project address: https://scrapy.org/
2.PySpider
pyspider is a powerful web crawler system implemented in python. It can write scripts, schedule functions and view crawling results in real time on the browser interface. The backend uses commonly used databases to store crawling results. , and can also set tasks and task priorities regularly.
Project address: https://github.com/binux/pyspider
3.Crawley
Crawley can crawl the content of the corresponding website at high speed , supports relational and non-relational databases, and data can be exported to JSON, XML, etc.
Project address: http://project.crawley-cloud.com/
4.Newspaper
Newspaper can be used to extract news and articles and content analysis. Use multi-threading, support more than 10 languages, etc.
Project address: https://github.com/codelucas/newspaper
5.Beautiful Soup
Beautiful Soup is a tool that can be downloaded from HTML or A Python library for extracting data from XML files. It enables customary document navigation, search, and modification methods through your favorite converter. Beautiful Soup will save you hours or even days of work.
Project address: https://www.crummy.com/software/BeautifulSoup/bs4/doc/
##6.Grab
7.Cola
Cola is a distributed crawler framework. For users, they only need to write a few specific functions without paying attention to the details of distributed operation. Tasks are automatically distributed across multiple machines, and the entire process is transparent to the user.Python Tutorial column to learn!
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