Scrapy vs. Selenium: Which One is Better?

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