Scrapy vs. Beautiful Soup: A Comparison of Web Scraping Tools

From newbies to seasoned developers, one thing is for sure – web scraping can get tricky. So, why make it even more confusing by using unreliable and ill-suited tools.

In this web scraping tools comparison, we’ll look at two popular options – Scrapy vs. Beautiful Soup – and discuss what role they play in web scraping. We’ll delve into their features, pros and cons, and give a few examples of when to choose which.

Let’s dig in!

Scrapy vs. Beautiful Soup in simple terms

Before delving into loads of technical details and terms, let’s take a look at the simplest way to explain the difference between Scrapy and Beautiful Soup.

Scrapy is a powerful Python web scraping framework, whereas Beautiful Soup is a parsing library. Scrapy allows you to define a root URL with some additional parameters, and it will be able to crawl, download, and save content from web pages. Beautiful Soup, on the other hand, will simply fetch the content you ask it to. 

In other words, it doesn’t perform the crawling part. That being said, you can, of course, do web scraping with Beautiful Soup, but you will need to employ it with a set of other dependencies.

What is Beautiful Soup?

Simple but powerful or simply powerful, Beautiful Soup is a Python parsing library that can get data from HTML, XML, and other markup languages. If you're just starting out and want to learn how to use Beautiful Soup, you'll find it to be a very beginner-friendly option for parsing web content. It uses tags, text content, and attributes as search criteria which makes navigating and searching the HTML tree much easier. Put simply, it’s a tool that helps you pull structured data from web pages. If you're new to using Beautiful Soup or want a refresher on how it works in practice, check out our BeautifulSoup Tutorial – How to Parse Web Data With Python.

Main features

• Dealing with poorly formatted HTML

In most situations, Beautiful Soup will help you parse data even from the most ill-formatted HTMLs. Of course, for the most extreme cases you might need to play around with Beautiful Soup’s parameters.

• Encoding conversion

Beautiful Soup has the capability of automatically detecting the document encoding method and converting it to a suitable format. In case it doesn’t, you can still specify it and get the job done.

• Integration with parsing libraries

Sitting on top of such parsing libraries as lxml and html5lib, Beautiful Soup can give your parsing approaches much more flexibility.

• Excellent error handling

Beautiful Soup handles parsing mistakes by giving you thorough error messages and facilitating easier parsing error recovery. As a result, the parsing process becomes much more manageable.

Advantages of using Beautiful Soup

• Beginner friendly

• Open-source and free

• Simple to implement

• Flexible parsing options

Disadvantages of using Beautiful Soup

• Many dependencies

• Not very scalable

• Minimal proxy support

What is Scrapy?

Scrapy is an open-source application framework that has traditionally been used to crawl and extract data. It’s a stand-alone tool, which means that you can take it as it is and put it to work. However, Scrapy web scraping is not the only approach to take as this tool can also be used for data mining and automated testing.

Main features

• Asynchronous request handling 

Scrapy is able to handle and prioritize multiple requests, making large-scale scraping operations easier, faster, and more efficient.

• Middlewares and extensions

Being a framework dedicated to web scraping, Scrapy offers a number of middleware and extensions to support various web scraping processes. As such, it skillfully handles such things as cookies, redirects, forms, and pagination.

• Spider framework

There are many ways to scrape a website and that’s why Scrapy allows users to specify their preferred approach. By using Scrapy’s spider framework, users can define the exact way that they want a website (or a batch of them) to be crawled, scraped, and parsed.

• AutoThrottling

You can configure Scrapy so it doesn’t exhaust the target server's resources. The AutoThrottle extension evaluates the load on the Scrapy server as well as the target website server and adjusts the crawling speed.

Advantages of using Scrapy

• Easy-to-follow documentation

• Doesn’t require other dependencies (unless working with JavaScript)

• Can be used for large-scale scraping

• Memory-efficient structure (check out this Scrapy and AWS Lambda tutorial for a serverless Scrapy solution)

Disadvantages of using Scrapy

• Cannot handle JavaScript

• Steep learning curve

Scrapy vs. Beautiful Soup: A detailed comparison

For a more detailed look at the differences between the two, check out the table below: