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Scrapy vs. Selenium: Which One is Better?

Scrapy vs. Selenium: Which One is Better?

Vytenis Kaubre

2023-07-125 min read
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When it comes to the choice between Scrapy or Selenium, there’s no one answer. There are numerous factors that can greatly impact the efficiency and outcome of your project. Hence, you must assess at least the major factors, like the project scale, overall speed requirements, and the difficulty of target websites. To help you decide, we’ve prepared this in-depth comparison of Scrapy vs. Selenium.

In this article, you’ll learn about their differences, fundamental features, and how to use each of them for successful public web data scraping.

Let’s kick things off with a short overview of both frameworks.

What's the difference between Selenium and Scrapy?

The fundamental distinction is that Selenium is a browser automation and testing framework that can be used for web scraping, while Scrapy is specifically a web scraping and web crawling framework.

What is Selenium?

Selenium is an open-source framework with a powerful trio of tools for web testing and automation on different browsers and devices. It supports popular programming languages, which you can use to command Selenium to interact with browsers and web elements. This way, it can perform various browser actions like clicking buttons, dropdown menus, filling out text fields, navigating websites, and performing other automated browser-based tasks. 

What is Scrapy?

Scrapy is a fast open-source framework explicitly built to crawl and scrape websites in order to extract data. While Scrapy web scraping is only possible in Python, its asynchronous method, ease-of-use, and overall high-speed makes it ideal for a project of any scale – even the largest one. Although its purpose is fixated on web scraping, Scrapy can also be used in other ways, for instance, web server load testing.

Is Scrapy still used?

Scrapy has maintained a buzz around it, and deservedly so. It’s a free and powerful web scraping tool that enables concurrent requests, and its use is fairly streamlined. Hence, Scrapy helps developers carry out scraping projects of any scale while staying within the budget. 

Scrapy vs. Selenium: pros and cons

Scrapy pros

  • High-speed crawling and scraping

  • Large-scale data acquisition

  • Memory-efficient processes

  • Highly customizable and extensible

  • Smooth web scraping experience

Scrapy cons

  • Doesn’t support dynamic content rendering

  • No browser interaction and automation

  • Steep learning curve

Selenium pros

  • Browser interactions and automation

  • Handles dynamic web pages

  • Cross-browser and device support

  • Relatively easy to use

Selenium cons

  • Slow and resource-intensive

  • Doesn’t scale well for web scraping purposes

Web scraping features of Scrapy and Selenium

While there are disadvantages both tools bear in nature, they offer distinct features that make Scrapy and Selenium powerful in different situations:

Scraping with Scrapy

  • Spiders
    Spiders are classes that specify how a website, or a batch of them, should be crawled and parsed. This feature enables efficient and highly customizable web scraping.

  • Requests and responses
    Scrapy offers asynchronous networking, request prioritization, scheduling, automatic request retries, as well as built-in mechanisms to handle redirects, cookies, sessions, and common web scraping errors.

  • AutoThrottle
    This extension allows automatic control of crawling speed based on Scrapy’s and the target website server’s load. In turn, your scraping requests don’t overcrowd the target site compared to default crawling speeds.

  • Selectors
    Scrapy allows XPath and CSS selectors for HTML node navigation and selection. This option enables you to leverage both methods for the best web scraping performance.

  • Items
    The extracted data is returned as items that are Python objects in key-value pairs, which you can configure and modify to suit your data needs. This feature enables easy access and manipulation of data accessible in a structured manner.

  • Item pipeline
    Item pipelines allow processing data before exporting and storing it. You can perform different tasks, such as validate, clean, transform, and then store the data in databases.

  • Feed export
    This is an in-built feature that enables you to export the data using various serialization formats and storage backends. While the default supported export formats are JSON, JSON lines, CSV, and XML, you can specify more formats through the feed export feature.

  • Middlewares, extensions, and signal handlers
    Scrapy allows you to customize and extend various processes of web scraping through the use of middlewares, like spider and downloader middlewares, custom extensions, and event signals.

  • Additional Scrapy services
    To further extend the functionality of your scraper, you can utilize built-in services like event logging, stats collection, email sending, and the telnet console.

Scraping with Selenium

  • Dynamic rendering
    As Selenium uses a browser driver to access web page content, it also renders JavaScript and AJAX-based data out-of-the-box. It can execute the code, wait for page elements to load, and interact with dynamic content, making it a go-to scraping library for handling dynamic web pages.

  • Browser automation
    Selenium can make your web requests resemble human behavior, allowing you to bypass anti-bot detection systems. What’s more, you can program Selenium to handle various browser tasks automatically, like clicking buttons and writing text, handling pop-ups and alerts, as well as solving CAPTCHAs.

  • Selectors
    Just like Scrapy, Selenium uses XPath and CSS selectors to navigate and select HTML nodes.

  • Remote WebDriver
    Selenium enables you to launch your script on separate machines, allowing you to scale your projects and run parallel tasks.

  • Browser profiles and preferences
    You can load and customize different browser profiles and preferences, including cookies and user agents, making it possible for you to achieve greater scraping success.

Side-by-side comparison: Scrapy vs. Selenium

Criteria Scrapy Selenium
Purpose Web scraping and crawling Web testing and automation
Language Python Java, JavaScript, Python, C#, PHP, and Ruby
Execution speed Fast Slow
Scraping projects Small to large scale Small to medium scale
Scraping scalability High Limited
Proxy support Yes
(See this Scrapy proxy integration guide)
Yes
(See this Selenium proxy integration guide)
Asynchronous Yes No
Selectors CSS and XPath CSS and XPath
Dynamic rendering None, requires additional libraries Fully renders JavaScript and AJAX pages
Browser support No Chrome, Edge, Firefox, and Safari
Headless execution No Yes
Browser interaction No Yes

Can Scrapy and Selenium be used together?

Yes, they can, and there are situations where you might want to consider using both. Scrapy can’t access dynamically loaded content on websites, be it JavaScript or AJAX-based content. Thus, Selenium can aid here by first loading the website in a browser and then getting the page source with dynamically rendered data. 

Another possible use of the Scrapy-Selenium combination is in situations where you need to interact with the website in order to access the desired data. You can use Selenium to automate user interactions and get the page source, which can then be passed on to Scrapy for further processing.

Conclusion: Scrapy or Selenium?

At its core, the answer depends on your target websites and the scale of your scraping project. Using only one framework de-clutters and eases up the whole process, so let’s review some cases where Selenium or Scrapy can potentially be the ultimate choice:

  • If you plan to extract low-volume data only from dynamically-rendered websites, then Selenium is the perfect solution due to its straightforward and fairly quick setup.

  • If your targets are static and you feel confident with your programming skills, then Scrapy is a winner here, no matter the scale of your project.

  • Yet, in case your project requires automatically clicking on buttons or filling out forms on the website, then the Selenium web scraping approach may be the best bet.

Having said that, both frameworks can supplement each other on different levels when used together, for instance:

  • If most of your target websites are static and only some require dynamic rendering, then you can use Selenium to render dynamic websites and Scrapy for the remaining steps.

  • The same principle as above applies in cases where you need to interact with website elements and mimic human-like behavior.

On the other hand, when it comes to larger-scale scraping projects that require dynamic rendering of content, you might want to consider using Scrapy with Splash. See our Scrapy Splash tutorial for more information.

Web scraping has been in the field for some time now, and so there are other popular web scraping tools you may want to consider instead of Selenium. Feel free to take a look at our other comparison articles on Playwright vs. Selenium, Scrapy vs. Beautiful Soup, and Puppeteer vs. Selenium.

Frequently asked questions

How is Scrapy so fast?

Scrapy’s speed is a result of many factors, but three main ones can be distinguished:

  • Asynchronous web request processing;

  • Concurrently run spiders that allow parallel processing;

  • Efficient and optimized resource usage.

Can Scrapy handle JavaScript?

No, Scrapy doesn’t have an in-built ability to render JavaScript-based content. However, there are additional tools you can use, like Splash, a rendering service that’s specifically designed for Scrapy. Other viable options are using Scrapy together with Selenium, Playwright, or pyppeteer.

How long does it take to learn Scrapy?

In short, Scrapy has a steep learning curve. It can take you from a few days to several months to grasp the fundamentals, but it all depends on your prior knowledge, skill, and experience.

Scrapy’s processes are well-documented, but for a smoother journey, you should have at least basic Python knowledge and an understanding of web scraping. 

As Scrapy uses HTML elements to find and extract the data, you should also be familiar with HTML structure and syntax, alongside how to form CSS or XPath selectors.

About the author

Vytenis Kaubre

Copywriter

Vytenis Kaubre is a Copywriter at Oxylabs. As his passion lay in creative writing and curiosity in anything tech kept growing, he joined the army of copywriters. After work, you might find Vytenis watching TV shows, brainstorming ideas for tabletop games, or taking Raymond Chandler’s advice, “When in doubt, have a man come through a door with a gun in his hand” too seriously (when writing short stories).

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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IN THIS ARTICLE:


  • What's the difference between Selenium and Scrapy?

  • What is Selenium?

  • What is Scrapy?

  • Scrapy vs. Selenium: pros and cons

  • Web scraping features of Scrapy and Selenium

  • Side-by-side comparison: Scrapy vs. Selenium

  • Can Scrapy and Selenium be used together?

  • Conclusion: Scrapy or Selenium?

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