We live in an information age where data is the new gold, so web scraping has become an indispensable process for collecting large amounts of web data for diverse purposes. However, data extraction enthusiasts and professionals face many obstacles due to the ever-evolving nature of the internet.
Below, you'll find the ten major web scraping challenges that beginners and experts alike need to know about. We'll also see the most suitable solutions to overcome them.
Let's dive in!
What Are the Challenges in Web Scraping?
Developers and data scientists often encounter two main problems associated with web scraping: the presence of anti-bot systems and the cost of running scrapers.
Websites use anti-bot systems like CAPTCHAs, fingerprint challenges, and many more, which require advanced methods to overcome. Also, scraping requires significant computational resources, bandwidth, maintenance, and updates.
Now, let's examine ten challenges you're likely to face, how to address them and see some affordable yet world-class solutions.
1. IP Bans
An IP address can be banned or rate-limited if a website determines that it's being used to make malicious or excessive requests. That can halt or lower the ongoing scraping until the ban is lifted, which is especially critical if the bot uses a single IP address for a large number of requests.
The solution is implementing a web scraping proxy to use a different IP for each request. Free IPs are not recommended because they're prone to fail.
Additionally, monitoring the scraper, following website terms of service, and putting delays between requests can help, too.
CAPTCHAs (Completely Automated Public Turing Tests to Tell Computers and Humans) are a popular security measure, making it difficult for scrapers to gain access and extract data from websites.
This system requires manual interaction to solve a challenge before granting access to the desired content. It may take the form of image recognition, textual puzzles, auditory puzzles, or even an analysis of the user's behavior.
Therefore, you can either solve them or avoid triggering them. Going with the latter is advisable because automated scrapers need human intervention to solve CAPTCHAs, and employing an external solving service can be quite costly.
Check out the best CAPTCHA proxies to outsmart web scraping challenges.
3. Dynamic Content
You might find useful our guide on how to scrape dynamic web pages with Python.
4. Rate Limiting
The term rate limiting refers to the practice of limiting the number of requests a client can make in a given period. Websites implement it to safeguard their servers from an influx of unwanted visitors, deter users from abusing the system, and guarantee equal access for all visitors.
Rate limiting slows down the process of getting data. That can, in turn, lead to reduced efficiency of your scraping operations, especially when dealing with large amounts of data or time-sensitive information. To bypass rate limits, you can randomize your request headers and use proxy servers.
5. Page Structure Changes
These are changes in a website's design, layout, or HTML structure. They can result from code updates, redesigns, or dynamic rendering aimed mainly at adding more features or enhancing existing ones.
Occasional page structure changes complicate scrapers' mission, making them unable to select some elements on a webpage correctly and causing data loss, so it's best to keep an eye out for them. You can do so by regularly monitoring your target websites and logging, analyzing, and troubleshooting page structure change errors.
6. Honeypot Traps
Honeypot traps are one of the web scraping challenges that bots mostly fall for. They're a trick for automated scripts that consists in adding hidden elements or links meant to be accessed only by bots.
As actual users wouldn't interact with them, when your scraper does, it'll likely get banned from that website. You can overcome this challenge by making sure you avoid hidden links. They'll have the CSS properties set to
display: none or
7. Required Login
In some cases, you'll need to provide credentials to access a website's content. This is problematic for web scraping because the scraper must simulate the login process and provide the credentials to gain access to the data. You can learn more about how to scrape a website that requires a login in our complete guide.
8. Slow Page Loading
Due to slow page loading, your scraper will take longer to retrieve the necessary data from a webpage. That can slow down the whole project, especially when dealing with multiple pages. This situation can also cause timeouts, the unpredictability of scraping time, incomplete data extraction, or incorrect data if a page element hasn't loaded properly.
To tackle this challenge, use headless browsers like Selenium or Puppeteer to ensure a page is fully loaded before extracting data. Also, set up timeouts, retries, or refreshes, and optimize your code.
We recommend learning how to block resources in Playwright or other headless browsers to tackle this web scraping challenge.
9. Non-browser User Agents
A User Agent is part of the HTTP headers that are sent to servers to request access. Browsers like Chrome, Firefox, and Safari use standard User Agent strings.
Custom-built or automated tools for a particular purpose typically use non-browser UAs by default. Therefore, they can make identifying and categorizing incoming requests as bot-like easy. A solution to this web scraping challenge is to customize the strings to be valid browser User Agents that are hard to differentiate from real ones.
10. Browser Fingerprinting
Browser fingerprinting is a technique to collect and analyze the visitors' web browser details to produce a unique identifier, or fingerprint, to track and distinguish users. These details include User Agent strings, installed hardware or fonts, browser extensions, screen resolution, cookie settings, language settings, keyboard layout, and more.
It's commonly used to improve website security and personalize user experience. However, it can also result in identifying and stopping bots. The unique fingerprint generated for that scraper can help identify patterns associated with the bot.
You can bypass browser fingerprinting by using headless browsers, stealth plugins and custom configurations and code.
How to Deal with the Web Scraping Challenges
Dealing with the web scraping challenges requires a mix of technical strategies, ethical considerations, and adherence to legal guidelines and web scraping best practices. Some of these best techniques include respecting the
robot.txt file, using APIs if available, rotating proxies and User Agents, and so on.
Yet, trying to bypass all the obstacles provided in this article and many others left can be time-consuming and may not always give you the desired result. That's why it's recommended to use a tool dedicated to handling the heavy lifting for you. ZenRows is one of them, as it can deal with all anti-bot challenges for you, and you can implement it in a matter of a few minutes.
The key to successful projects is a thorough understanding of the web scraping challenges. Above, we covered the top obstacles web scrapers face and the appropriate solution to combat them.
You should always consider your actions' legal and ethical implications when scraping websites and ensure you're up-to-date on the latest anti-bot methods.
ZenRows is a powerful web scraping API that can bypass all anti-bot measures for you. Sign up now and get 1,000 free API credits.