Difference between BeautifulSoup and Scrapy crawler? Difference between BeautifulSoup and Scrapy crawler? python python

Difference between BeautifulSoup and Scrapy crawler?

Scrapy is a Web-spider or web scraper framework, You give Scrapy a root URL to start crawling, then you can specify constraints on how many (number of) URLs you want to crawl and fetch,etc. It is a complete framework for web-scraping or crawling.


BeautifulSoup is a parsing library which also does a pretty good job of fetching contents from URL and allows you to parse certain parts of them without any hassle. It only fetches the contents of the URL that you give and then stops. It does not crawl unless you manually put it inside an infinite loop with certain criteria.

In simple words, with Beautiful Soup you can build something similar to Scrapy.Beautiful Soup is a library while Scrapy is a complete framework.


I think both are good... im doing a project right now that use both. First i scrap all the pages using scrapy and save that on a mongodb collection using their pipelines, also downloading the images that exists on the page.After that i use BeautifulSoup4 to make a pos-processing where i must change attributes values and get some special tags.

If you don't know which pages products you want, a good tool will be scrapy since you can use their crawlers to run all amazon/ebay website looking for the products without making a explicit for loop.

Take a look at the scrapy documentation, it's very simple to use.

ScrapyIt is a web scraping framework which comes with tons of goodies which make scraping from easier so that we can focus on crawling logic only. Some of my favourite things scrapy takes care for us are below.

  • Feed exports: It basically allows us to save data in various formats like CSV,JSON,jsonlines and XML.
  • Asynchronous scraping: Scrapy uses twisted framework which gives us power to visit multiple urls at once where each request is processed in non blocking way(Basically we don't have to wait for a request to finish before sending another request).
  • Selectors: This is where we can compare scrapy with beautiful soup. Selectors are what allow us to select particular data from the webpage like heading, certain div with a class name etc.). Scrapy uses lxml for parsing which is extremely fast than beautiful soup.
  • Setting proxy,user agent ,headers etc: scrapy allows us to set and rotate proxy,and other headers dynamically.

  • Item Pipelines: Pipelines enable us to process data after extraction. For example we can configure pipeline to push data to your mysql server.

  • Cookies: scrapy automatically handles cookies for us.


TLDR: scrapy is a framework that provides everything that one might need to build large scale crawls. It provides various features that hide complexity of crawling the webs. one can simply start writing web crawlers without worrying about the setup burden.

Beautiful soupBeautiful Soup is a Python package for parsing HTML and XML documents. So with Beautiful soup you can parse a webpage that has been already downloaded. BS4 is very popular and old. Unlike scrapy,You cannot use beautiful soup only to make crawlers. You will need other libraries like requests,urllib etc to make crawlers with bs4. Again, this means you would need to manage the list of urls being crawled,to be crawled, handle cookies , manage proxy, handle errors, create your own functions to push data to CSV,JSON,XML etc. If you want to speed up than you will have to use other libraries like multiprocessing.

To sum up.

  • Scrapy is a rich framework that you can use to start writing crawlerswithout any hassale.

  • Beautiful soup is a library that you can use to parse a webpage. Itcannot be used alone to scrape web.

You should definitely use scrapy for your amazon and e-bay product price comparison website. You could build a database of urls and run the crawler every day(cron jobs,Celery for scheduling crawls) and update the price on your database.This way your website will always pull from the database and crawler and database will act as individual components.