Do you need help choosing between Scrapy and Selenium for web scraping? Both tools have their unique strengths and are suited to different types of web scraping tasks.
In this article, we'll review each to draw a line between them, and you'll be able to decide which is best for you.
Scrapy vs. Selenium: Which Is Best?
The choice between Selenium vs. Scrapy depends on your scraping goal. Here's a brief overview of what you need to know before making a choice:
Feature Comparison: Scrapy vs. Selenium
Let's compare the features and use cases of Selenium vs. Scrapy to decide which works best for you.
First, we'll start with a brief comparison table and delve into more details after.
|Ease of use
|Straightforward and easy to set up with default code structure
|Can be more complex and depends on the use case
|Requires integration with tools like Scrapy Splash or Selenium
|Avoid getting blocked
|Proxy middleware and headers rotation
|Proxy and header rotation. Using the Undetected. Headless mode. Selenium Stealth. WebDriver plugin. Limited integration with web scraping APIs
|Can be slow for advanced scraping
|Uses more memory
|Community and documentation
|Primarily for web scraping
|Automation testing and web scraping
|Maintenance and upkeep
Now let’s critically compare Selenium and Scrapy in detail.
Scrapy Is for Web Scraping, While Selenium Is Versatile
Scrapy is for web scraping and nothing else. It's a framework that packs all the tools, including extensions for collecting, cleaning, and storing data.
Selenium is more versatile, featuring web automation for application testing. However, its headless browser feature and ability to interact with dynamic and static web elements and extract texts from them make it a valuable web scraping tool.
Scrapy Works with Python, but Selenium with More Languages
While Scrapy is more desirable for large-scale web scraping, it only works with Python. This might make it less suitable if you don't have a Python background or want more language flexibility.
Flexibility on Headless Browsing Libraries with Scrapy
Selenium's headless browsing is handy for scraping dynamic websites. Scrapy doesn't have built-in headless browser support, but you can implement Selenium or external libraries, like the recommended scrapy-splash.
Selenium's Wide Browser Compatibility or Scrapy Splash's Solo
Selenium's cross-browser compatibility is more relevant to automation testing. However, it can be helpful in web scraping, particularly if you want to mimic different browsers while scraping.
Scrapy lacks multi-browser compatibility, and that’s OK because multi-browser functionality isn’t essential in web scraping. Besides, you can address differences in rendering across browsers by combining Scrapy with a headless browser library.
Scrapy Is Easier to Learn than Selenium
Both Scrapy and Selenium boast strong points in documentation, maintainability, and community support.
However, Scrapy has an easier learning curve considering its simple command line setup, Pythonic nature, default code structure, and clear goal for web scraping and crawling goal. Selenium's versatility gives it a steeper learning curve, and usually, setting up depends on the use case.
Scrapy is Faster than Selenium
Speed is pivotal to web scraping since you want to quickly collect as much data as possible.
Scrapy is relatively faster for static content scraping since it doesn't introduce extra browser overhead like Selenium, which runs a browser instance. Surprisingly, Scrapy also collects data faster than Selenium when combined with Scrapy Splash for dynamic data scraping.
We ran a 100-iteration speed benchmark test on Selenium vs. Scrapy + Scrapy Splash for collecting dynamic content. It took Scrapy an average of 4.41 seconds and Selenium an average of 13.01 seconds to obtain the same content.
Here's a graphical presentation of the result, from the faster to the slower:
The time unit used is the second (s = seconds).
Selenium Consumes More Memory than Scrapy
Although memory usage varies per project complexity and machine specifications, Scrapy outperforms Selenium in handling large and small-scale scraping.
We also conducted a 100-iteration memory consumption benchmark test on Selenium vs. Scrapy for dynamic content collection. While Scrapy only used an average of 13.62MB, Selenium plus its browser instance consumed an average of 40.51MB.
See the final result in the graph below (from lower to higher):
The memory unit used is the megabytes (MB).
Scrapy's optimization to minimize memory footprint gives it a lead over Selenium, which accounts for browser instances that run in a separate process.
Scrapy's Superior Crawling Capabilities
Although Scrapy is efficient at web crawling, it needs the Scrapy Splash plugin to crawl dynamic web pages.
Although, as mentioned, Scrapy is efficient at web crawling, it needs the Scrapy Splash plugin to crawl dynamic pages.
Best Choice to Avoid Getting Blocked While Scraping
Let's face it: getting blocked while scraping can be a nightmare, preventing you from accessing a web page to collect the required data. Luckily, both Selenium and Scrappy have block-evading mechanisms.
While Selenium boasts tools like Undetected ChromeDriver and Selenium Stealth to bypass basic anti-bot detection, it also supports services like ZenRows for better efficiency in rotating proxies and headers.
Overall, Scrapy’s extensibility with various tools, including Scraping APIs like ZenRows, gives it an edge over Selenium.
Start your ZenRows free trial today and overcome sophisticated anti-scraping measures.
👍 Pros of Scrapy:
- Easier to learn and set up.
- More structured codebase architecture.
- Active community.
- Consistently maintained.
- Faster crawling and scraping.
- Memory efficient.
- Suitable for large-scale web scraping.
- It can work with Selenium and other libraries like Splash.
- Easily integrates with anti-bot solvers.
- Built-in HTTP proxy middleware is available.
- Item pipelines for organizing and storing collected data.
👎 Cons of Scrapy:
- Requires third-party plugin for dynamic content scraping.
- Only limited to Python.
- No support for web automation.
- Headless browser not available.
👨💻 Best Use Cases for Scrapy:
- Simple to complex web data collection.
- Web crawling.
- Data mining, cleaning, and storage.
👍 Pros of Selenium:
- Comprehensively documented.
- Headless browser support.
- Web automation functionality to mimic users' behavior.
- Cross-browser and device compatibility.
- Active community.
- Consistently maintained.
- Easy integration with proxies.
- Extensible with a rich set of libraries and APIs.
- It can be used along with other scraping tools.
👎 Cons of Selenium:
- The learning curve is steeper for beginners.
- Slower and more memory-demanding.
- Not suitable for large-scale web scraping.
- There is no built-in way to organize and structure data.
- Initial setup can be technical and project-dependent.
👨💻 Best Use Cases for Selenium:
- Cross-browser and cross-platform test automation.
- Performance and integration testing.
- Web scraping of dynamic content.
- General web automation.
- Automated form filling.
- Web application monitoring.
Regardless of your final choice, it's crucial to avoid getting blocked. Integrate ZenRows with Selenium or Scrapy for free today.