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2 Solutions to Scrape Dynamic Websites in 2024

Web scraping has transformed many business processes, enabling more data-driven decision making. It also got easier overtime with low code and no code web scraping solutions that do not require any coding. However, the automation of large scale web scraping such as collecting price information from thousands of pages or social media posts still require coding expertise to build the relevant code. The complexity of the code can increase especially depending on the structure of the websites to be scraped.

A common barrier you may face while building your web scraping solution is the complexity of dynamic websites. In this article, we will explain what a dynamic website is, why it is challenging to scrape them and two solutions to collect information from those websites.

What is a dynamic website?

Dynamic websites are websites that can be personalized for each user and allow user to interact with the website. Back in the early years of the internet, a website was a static page which showed the same information to everyone. When this is the case, the source code of the website can have the information to display. For dynamic websites, since the content can change based on what user wants to see, the code needs to be rendered just before the page is loaded on someone’s browser. This means that the source code of the website does not contain the information you would like to scrape yet.

Today, majority of the websites fall into dynamic website category. Any website that you search for a product or service, that you can click on to see more sections or see different images and ads based on who you are are examples of dynamic website content.

Top 3 challenges of scraping a dynamic website

1. Browser dependency

Dynamic websites are based on code that is rendered once they are loaded on a browser. Therefore, the content to be scraped technically does not exist before the page is loaded. This requires the web scraping process to include a step for rendering the page content on a browser. Especially for scraping thousands of pages, this step should also be ideally automated.

2. Geography specification

Since dynamic websites can tailor the content based on the user, same website can be loaded differently based on user’s location. Therefore, the scraper should also know how to specify the location of the request and specify it as needed. In our detailed post about challenges of web scraping, we mentioned that websites often block web scraping requests from the same location since it may be identified as bot traffic. This makes the web scraping effort additionally complicated to make sure that the request location is specified as needed but also not kept exactly the same in order to avoid being blocked.

See our in-depth guide on web scraping best practices to learn how to bypass web scraping challenges.

3. Input request:

Dynamic websites often request an input from the user in order to load the specified information. For example, if you need to scrape the prices of rental units in an area, your scraping command should specify all the required input on the website.

2 solutions for scraping a dynamic website

1. Use an off-the-shelf web scraper:

An alternative to in-house web scraping for dynamic websites is partnering with an external web scraping solution. This may be especially preferred if the quantity and the complexity of the websites you need to scrape scale up over time which creates a technical dependency to maintain your code. Web scraping solutions can automate the data collection part and leave more time for value added processes of generating insights from data.

Solutions that integrate IP proxies are specifically helpful to overcome the geography specification. When you try to scrape the web from your location, you are a singular IP address which will be recognized by the websites you try to scrape over time. Solutions use dynamic proxies, which allow them to change their IP address for every request to avoid being blocked by the website but stay within the geography zone you need for the right website configuration.

2. Use a webdriver:

A webdriver is a connector that is used for controlling a browser for tasks such as running or testing an application on the web. They are specifically helpful to overcome the browser dependency in dynamic website scraping and automate the process of loading targeted websites on the browser. They also help overcome the input request dependency by allowing you to choose a specific browser and version to run your scraping code and mimic your interaction with the browser while scraping, such as scrolling down for more content on Twitter.

For more on web scraping

To explore web scraping use cases for different industries, its benefits and challenges read our articles:

For guidance to choose the right tool, check out data-driven list of web scrapers, and reach out to us:

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This article was drafted by former AIMultiple industry analyst Bengüsu Özcan.

Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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