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 article, we’ll compare two different tools – 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!
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 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.
Simple but powerful or simply powerful, Beautiful Soup is a Python parsing library that can get data from HTML, XML, and other markup languages. 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.
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.
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.
Open-source and free
Simple to implement
Flexible parsing options
Not very scalable
Minimal proxy support
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.
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.
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.
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.
Can be used for large-scale scraping
Steep learning curve
For a more detailed look at the differences between the two, check out the table below:
|Purpose||Web scraping and crawling||Parsing|
|Scraping projects||Small to large scale||Small to medium scale|
|Scalability||Highly scalable and can handle large-scale projects||Not as suitable for large-scale projects|
(see this Scrapy proxy integration guide)
(with additional libraries)
|Crawling||Designed for web scraping and crawling||Focused on parsing and manipulating HTML|
|Browser support||No||Chrome, Edge, Firefox, and Safari|
These tools can definitely be used together, although it may take some time to set everything up. While Scrapy has its own built-in parsing tools, you can combine it with Beautiful Soup to take advantage of Beautiful Soup's parsing functionality within a Scrapy project.
So, within Scrapy's callback functions, BeautifulSoup can be used to extract specific elements or modify HTML content. Indeed, when dealing with HTML that is poorly organized or requires more complicated parsing processes, using Beautiful Soup is a great approach.
As with many tools, the choice between Scrapy and Beautiful Soup boils down to the nature of your project. From speed to complexity, many things should be taken into account. For example:
If you’re still learning web scraping, prototyping, or your scraping project is extremely small – choose Beautiful Soup.
For large-scale complex projects, make use of Scrapy’s flexible framework.
For complicated projects that require sophisticated or different parsing strategies, choose a combination of both.
No, both Scrapy and Beautiful Soup are different tools. While they can be implemented together, neither of them is derived from the other.
In general, Scrapy is faster than Beautiful Soup due to its ability to handle asynchronous requests and large-scale projects. However, this might not be true for small projects. Indeed, in some situations, the difference between Scrapy and Beautiful Soup might be small.
About the author
Enrika Pavlovskytė is a Junior Copywriter at Oxylabs. With a background in digital heritage research, she became increasingly fascinated with innovative technologies and started transitioning into the tech world. On her days off, you might find her camping in the wilderness and, perhaps, trying to befriend a fox! Even so, she would never pass up a chance to binge-watch old horror movies on the couch.
All information on Oxylabs Blog is provided on an "as is" basis and for informational purposes only. We make no representation and disclaim all liability with respect to your use of any information contained on Oxylabs Blog or any third-party websites that may be linked therein. Before engaging in scraping activities of any kind you should consult your legal advisors and carefully read the particular website's terms of service or receive a scraping license.
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