If you are familiar with web scraping, you might have heard of terms such as static and dynamic websites. Nowadays, most websites are dynamic and utilize a JavaScript framework for the front end. Frameworks such as React, Vue, and Angular are the most famous for achieving dynamic website content.
So, as a web scraper, you have to ask yourself, “What differences exist when scraping a dynamic website versus a static one? Which details do you need to be aware of when handling both? Which technologies are best for effectively scraping each type?” This article will briefly cover scraping for both static and dynamic websites using technologies related to Python. Continue reading to have your doubts cleared.
A Brief Look at Static and Dynamic Websites
Static websites display the same information or content for every user. They don’t employ user-determined database refinement. Technically, static sites utilize HTML, CSS, and JavaScript interactively. However, they do not use these languages to render information originating from the backend using a dynamic sequence such as AJAX. This type of website is much easier to assemble as it primarily relies on client-side scripts that usually utilize HTML and CSS.
In other words, the information or content is directly assigned to HTML, and to present other pages and send information, the whole page reloads to allow the new content or a subsequent page to render. Wikipedia is the best and most well-known example of a static website.
Dynamic websites define themselves by user-specificity. Social media networks present themselves as the best example of dynamic sites. You may be able to see posts others cannot see because of differences in preference and friends or followers lists. Technically speaking, modern dynamic websites rely wholly on JavaScript to operate and manage information on the front side of the site. In a nutshell, dynamic websites function as follows:
- The server side, also known as the backend, serves the content
- JavaScript on the browser secures the data and then injects said data into the HTML
All of this happens without the whole page reloading. Only the part where the change occurs is where the page reloads. As you can see, dynamic sites pose more of a challenge to assemble and need adequate experience and know-how to script. These scripts refer to code that the server executes in the form of Node, Python, PHP, and others. They are also what handles the logic of the website.
Differences Between Static and Dynamic Web Scraping
Generally, static websites are easier to scrape as the information or data is fixed and always there on HTML upon the page loading. HTML uses requests similar to packages, and you can easily scrape the required data through parsing.
Dynamic websites need more expertise to scrape due to JavaScript. HTML loads first, then JavaScript fills it in with the data. When scrapers send requests to servers, they answer with HTML that does not have data, making the scraping of dynamic websites different from static ones.
Technologies for Scraping Dynamic and Static Websites
When it comes to securing the data you need for your scraping project, there are two different general approaches you can follow. Depending on your website, you can:
- Static Websites: Here, Python scraping packages are the most commonly used when extracting data. Some of these packages include requests with Beautiful Soup, Scrapy, Splash, and Selenium. Tool selection varies according to the scraper’s experience level, the size of the scraping project, the duration, and the client’s resources.
- Dynamic Websites: The methodology for scraping these may differ slightly depending on the website you wish to acquire data from. Selenium web scraping or Splash are the most popular methods, as they both automate the web browser and mimic human actions. Among the two, Selenium is more beginner-friendly both in the learning curve and ease of use, thus making it the more popular option. The best method to scrape a dynamic site is via the API. If the API is visible, you access it through the browser inspect utility, navigate to the network section, and find all the sent files from there.
Conclusion
Dynamic website scraping is more challenging than static in terms of the learning curve and the expertise needed. A good grasp of technologies such as Selenium and Splash is imperative for effective scraping. If one desires to learn both, it is easier to start with static scraping and gradually move on to dynamic websites.
