Web scraping might seem a little complex to hear, but this is a task that is commonly performed today. This is simply a process via which data is extracted from online sources easily and efficiently.
But there are complications to the task, especially on dynamic websites. While static website scraping can be performed easily, dynamic ones don’t let you do so nearly as easily.
So, this article brings you two different ways to scrape data from a dynamic website. But before getting into the details, let’s get a clear view of what web scraping is all about.
Web Scraping: Definition, Importance, and Categories
As mentioned, web scraping is something we perform more regularly than we know. But how is that?
Think about it – you have heard of a new recipe everyone’s trying out at home, and think of preparing it yourself. What would you do? Perhaps, the first thing you will do is search for the recipe on the internet, check a few websites’ contents, and note it down.
And that’s what we call web scraping. You are manually scraping the data from a website for your own use.
Now, when it comes to technical web scraping, as in professional terms, you need to scrape hundreds or even thousands of websites to collect data. That is not possible via manual methods.
Therefore, the world now requires advanced web scrapers who can perform this task more effectively through a few quick and simple approaches.
For instance, one quick method is to scrape websites with Python. Python is a relatively easy program that makes web scraping a breeze. This computer language may also be used to scrape dynamic websites, in addition to static ones.
As there is more to these websites’ scraping methods, we will discuss it further in the article below.
Why Is Web Scraping So Valuable?
Just like the recipe you noted down helped you perform a task in your daily life, professional web scraping helps people perform several tasks in their business life. For instance, you can better leverage business intelligence to grow your business.
Web scraping, by means, is a necessity for businesses that helps them with competitor analysis and identifying market trends among other things.
For instance, when a company decides to launch a new product, it will need to know the current prices, trends, and other information about the competitive landscape.
Extracting and analyzing all those information from every source can be quite challenging, perhaps even impossible, through the manual method. Therefore, automated web scraping is so valuable.
Basically, there are more specific justifications for using web scraping, such as:
- Improved access to corporate data;
- Building a sales machine through lead generation;
- Automation of marketing without boundaries;
- Brand monitoring;
- Large-scale market analysis;
- On-demand data (base) enrichment.
Web scraping is a special skill to have in today’s world. With so much data available online, being able to scrape it effectively can help you glean insights that would otherwise be unavailable.
What are the Different Categories of Websites’ Scraping?
Static and dynamic websites are the two basic types of websites that are currently available.
A static website is built entirely in HTML code and displays the same content to every visitor. On the other hand, a dynamic website can provide different content to each user depending on their search intent, location, and other choices and is constructed using programming languages like PHP, ASP.NET, and Java.
Web scraping tactics, therefore, differ when it comes to these two distinct types of websites. Although scraping static websites is quicker and simple compared to scraping dynamic ones, most websites today are dynamic, so we need to develop our skills in various ways to scrape data from a dynamic website.
Dynamic Website Scraping
Dynamic website scraping can be a great way to get information from sites that regularly update their content. This technique can scrape data from forums, social media sites, and even e-commerce platforms.
This is in contrast to static website scraping, a process of extracting data from websites that do not regularly update their content (i.e., HTML coding sites).
However, there are some unique requirements to meet to carry out dynamic web scraping successfully, which are as follows,
- You’ll need to choose a language that supports dynamic web scraping. Python is an excellent option for this, as there are many libraries that make web scraping easy.
- Try to find some appropriate websites to scrape. Ascertain that the website you select offers an API you can use to obtain the data you need.
- Finally, ensure that you have permission from the site owner before scraping. Some sites do not allow automated scraping of their content.
Dynamic web scraping can automate tedious and time-consuming tasks, freeing your time to focus on more important things. To assist you in learning more about dynamic web scraping, we’ve included two standard scraping techniques below.
What Are the Ways to Scrape Data from a Dynamic Website
Dynamic web scraping requires dynamic approaches. Unless you stay up-to-date about those dynamic approaches, you can’t be successful at your scraping job. Therefore, here are two leading ways to scrape data from a dynamic website:
- Direct Scraping from JavaScript
Direct dynamic web scraping from JavaScript is performed through AJAX requests. AJAX means Asynchronous JavaScript and XML, enabling JavaScript to send and receive HTTP requests from remote servers.
This method operates by gaining access to the AJAX request responses and extracting relevant data from them.
You may then send a request to the server using the URL of the response, scrape the data from it, and save the extracted data in a spreadsheet.
- Using Webdriver Packages
If you’re looking for a quick and easy way to scrap data from a dynamic website, then webdriver packages are the way to go.
A web driver is designed to control browsers for performing specific tasks on command, such as running different applications on the web. And so, it helps automate targeted website loading without the dependency on browsers for dynamic web scraping.
By giving you the option to execute your scraping code on a particular browser and version, these web drivers simulate your interactions with the browser during scraping. As a result, it also assists in overcoming the input request dependency.
There are several different web driver packages available, among which Seleniums and Python are the most popular ones.
Challenges of Dynamic Website Scraping
The challenges of dynamic website scraping are vast and varied. They can range from a simple website with a slow loading speed to a more complex one that relies on JavaScript.
Here is a summary of the top three challenges we scrapers experience when performing dynamic website scraping:
- Browser Dependency
The foundation of dynamic webpages’ data is Javascript, Python, or other complicated programming language that can be rendered after you load the webpage on a browser. And then there is the issue of browser dependency.
You need to open a particular webpage on a browser to collect its data in your system. Unlike static scraping, this includes an added step to the dynamic scraping process.
- Geography Specification
As we know, dynamic content can change based on what the user is searching for. Likewise, it is also possible for a dynamic website to showcase particular content to the user based on their geographical location.
So, when you scrap data from dynamic websites, you will also need to be specific about your locations. Otherwise, acquiring the relevant data you need for your project won’t be easy.
There is also another challenge that you might face, which is the fact that sometimes websites restrict scraping requests from the same IP address. Repeated requests from the same address may be mistaken for bot traffic.
Due to this, it becomes more challenging to ensure that the request location is perfectly specified but also changed from time to time to avoid being blocked.
- Input Request
Every time you need to extract data from dynamic websites, you must submit an input request. It is an additional step that elongates the scraping procedure.
Is Web Scraping Illegal?
The legality of web scraping is a murky area. While there are some clear-cut cases where web scraping is illegal, there are many gray areas. In general, web scraping is only unlawful if it violates the terms of service of the website you’re scraping or violates other laws pertaining to privacy, intellectual property, and so on.
However, even then, there are many ways to scrape data without violating these terms. So, while web scraping may not be strictly legal in all cases, it is neither illegal in most cases.
Conclusion
Whether you’re looking to collect data for research purposes or want to gather information more efficiently to make data-driven decisions in your business, learning how to scrape the web is a worthwhile pursuit.
Web scraping for static websites is easy but dynamic websites are another ballgame. But now that you’ve read this article, you know about the two popular ways to scrape data from a dynamic website, the common challenges, and how to avoid them. Use this knowledge and easily get the data that you need.