Scrapy Vs. Beautifulsoup Vs. Selenium for Web Scraping

Scrapy, Selenium, and Beautifulsoup are the 3 popular web scraping tools for Python web scrapers. Come in now to discover the differences between the 3 of them and the scenario to use each of them.

Scrapy Vs. Selenium Vs. Beautifulsoup

Do you want to know the difference between Scrapy, Beautifulsoup, and Selenium?

Then you are on the right page. This article will be used to discuss the 3 popular tools and provide a complete explanation about them. From what you will read, you will know which of the tool to use depending on your skill and individual project requirements. If you are not really conversant with Web Scraping, I will advise you to read our article on guide to web scraping – also check out our tutorial on how to build a simple web scraper using Python.

The truth is, while I see newbies compare Scrapy, Beautifulsoup, and Selenium, I see no reason for such a comparison. This is because they are actually no competitors as each has its own function and audience. However, each of them has a place in web scraping, and their functionalities overlap. Let take a look at each of them separately after which, we can then make recommendations on the one to use based on your skillset and project requirement.


Scrapy is a web crawling framework that comes with a good number of tools to make web crawling and scraping easy. It is multithreaded by design and built on top Twisted. Twisted is an asynchronous networking framework that follows non-blocking I/O calls to servers. Because it is multithreaded and non-blocking, it is actually the best in terms of performance and actually the fastest among the 3 tools. One advantage of Scrapy over the 3 tools is that it comes with modules to send requests as well as to parse responses.

Scrapy is the tool for developing complex web crawlers and scrapers as you can create a good number of workers, and each of them will work effortlessly. It has been built to consume less memory and use CPU resources minimally. In fact, some benchmarks have stated that Scrapy is 20 times faster than the other tools in scraping. It is portable, and its functionality can be extended.

The major problem associated with Scrapy is that it is not a beginner-centric tool. The documentation of Scrapy is somehow complex. I must confess, when I started learning web scraping using Python, I had the option of using Scrapy to learn because I heard it is the best for building complex scrapers and comes with a lot of functionalities. However, I had to drop the idea when I discovered it is not beginner-friendly. One major setback of Scrapy is that it does not render JavaScript; you have to send Ajax requests to get data hidden behind JavaScript events or use a third-party tool such as Selenium.


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BeautifulSoup, just like Scrapy, is an open-source tool and used for web scraping. However, unlike Scrapy, which is a web crawling and scraping framework, BeautifulSoup is not. BeautifulSoup is a module that can be used for pulling data out of HTML and XML documents. BeautifulSoup is a beginner-friendly tool that a newbie can hit the ground running with it. This is because it has very good documentation and a friendly user community. Most web scrapers must have used BeautifulSoup before heading over to Scrapy. The tool is not complex and makes it easier for you to transverse an HTML document and pick the required data.

While you can use it for multitasking, you have to be really good with Python multithread programming to be able to multitask effectively using BeautifulSoup. One of the major disadvantages of BeautifulSoup is that it depends heavily on other libraries to work. BeautifulSoup does not have the capability of sending web requests; you will have to make use of the requests module or the Python standard module for sending web requests – urllib. Aside from sending web requests, BeautifulSoup also does not have a document parser; you will have to choose from options such as html.parser, HTML5lib, XML Parser, and a few others.

It is important I stress here that the lack of a web request sending capability and a parser does not in any way make using BeautifulSoup difficult. It only means that you need to install the dependencies for you to use the tool. It might interest you to know that these dependencies plus BeautifulSoup are still the easiest options out there compared to other tools. It is, however, slow when compared to Scrapy.


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Selenium is a different tool when compared to BeautifulSoup and Scrapy. Selenium wasn’t made for web scraping. It was developed actually for web testing. Selenium is used for web application automated testing. It automates web browsers, and you can use it to carryout actions in browser environments on your behalf. However, it has since been incorporated into web scraping. Selenium can send web requests and also comes with a parser. With Selenium, you can pull out data from an HTML document as you do with Javascript DOM API.

The major advantage Selenium has over the two is that it loads Javascript and can help you access data behind JavaScript without necessarily going through the pain of sending additional requests yourself. This had made Selenium not only useful to itself but to the other tools. Web scrapers that use either Scrapy or BeautifulSoup make use of Selenium if they require data that can only be available when Javascript files are loaded.

Selenium is faster than BeautifulSoup but a bit slower than Scrapy.

Which Should You Use – Scrapy, BeautifulSoup, or Selenium?

All of the three web scraping libraries are all open-source and completely free to use. With this, money is not a deciding factor. Each of them has a community of developers supporting its development. So which of them should you make use of?

This depends on the project requirements. If a project is complex, Scrapy is the tool for the job. This is because it is a framework designed for handling complex web scraping tasks. It even allows you to extend its functionality.

Scrapy Vs. Selenium Vs. Beautifulsoup

For smaller projects, BeautifulSoup is the library of choice. You just have to install the requests module and your preferred HTML parser (HTML.parser is installed by default). Selenium comes handy when you are handling Javascript featured website.

As a Python developer, you should learn how to use the three of them. Knowing how to use all will save you the stress of dealing with one because that’s all you know. If you know how to use the three of them, it is a matter of which is the best for the project at hand.


Web scraping can become handy and easy with tools such as Scrapy, BeautifulSoup, and Selenium. Each of these tools has it's own application. While Scrapy is the tool for complex projects, BeautifulSoup is used for smaller tasks.

Selenium is used for Javascript featured websites – and can be used as a standalone web scraper and parser. They are all useful in their own way, and learning how to use all of them will make you a better web scraping developer.

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