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Introduction to Web Scraping Techniques and Tools

Thursday, March 31, 2022

Data is estimated to be a USD 274.3 billion industry by 2022. Not surprisingly, leaders of tomorrow are harvesting data today. Whether you are exploring the possibilities or just starting to kick in, here are some questions worth thinking about:

  • What data your business can leverage?
  • How to harness that data?
  • Ways to utilize that data


Web scraping is the go-to approach to mine the web and extracts valuable data. In this article, we will give you a no-brainer introduction to web scraping techniques, tools, and tips to scrape websites. Hopefully these ideas can help you make smarter decisions for your business. 




What Is Web Scraping & How Is It Used?

In a layman’s language

    • It is a process of collecting information from different websites on the web
    • It is an automated process
    • It is the same as data extraction, content scraping, data scraping, web crawling, data mining, content mining, information collection, data collection





Manual scraping vs. Web scraping

Let's say you want to capture the emails of people that have commented on a Linkedin post. You may point the cursor to the string of an email address, copy and paste it onto a file. When the same process is repeated over and over again, you are literally doing manual scraping. 

On the contrary, web scraping is a term for having the same process done at scale using some sort of programs or bots. It can take hours for anyone to collect 2000-ish emails while it will take 30 seconds for a program to complete the same thing. It's hard not to notice the difference. 


In technical lingo

  • The web is inundated with data, whether structured or not.
  • Web data includes text, images, videos, audio files, etc.
  • People need this data for different reasons.
  • Web scraping is the programmatic approach to obtaining web data in an automated fashion.
  • Web scrapers, web scraping tools, or web scraping scripts were written by coders can serve the end.


How Is Web Scraping Used

Big data helps people understand the market and gain a competitive edge over competitors. In this regard, web scraping is widely used among eCommerce businesses, entrepreneurs, marketers, consultancies, academic researchers and more. Businesses leverage web data for: 

  • Training ML Algorithms
  • Price Intelligence
  • Brand Monitoring
  • Market Research
  • Lead Generation
  • Sentiment Analysis
  • Trend Analysis
  • Content & SEO Research
  • Content aggregation
  • Product data
  • Building aggregator services
  • NLP


If you are interested in learning more about how businesses are using web scraping, check this post out: 25 Ways to Grow Your Business with Web Scraping


Web Scraping Techniques Explained

Manual scraping is apparently not a feasible option as it is extremely time-consuming and ineffective. Instead of wasting a whole day copying and pasting around in front of the screen, there are 5 ways you can get web data at scale effectively.


1. Using Web Scraping Tools

Automatic scrapers or click & scrape tools offer a simple way to scrape the web. Really? YES and here is why:

  • No programming knowledge is required. You only need to know how to click.
  • Cost, time, and resource-efficient. You can generate 100,000 data points just in less than USD 100.
  • Scalable. You can scrape millions of pages based on your needs without worrying about the infrastructure & network bandwidths.
  • Works for all kinds of websites. Built-in features to bypass anti-scraping website architecture. When websites implement anti-bots mechanisms on websites to discourage scrapers from collecting data, good scraping tools can tackle these anti-scraping techniques and deliver a seamless scraping experience.
  • Flexible and accessible. You can scrape at any time, anywhere while taking advantage of their cloud infrastructure.


2. In-house Web Scraping Tech Team

If your requirements are too complex to be handled by a web extraction tool, then you should consider building an in-house team of developers and data engineers to extract, transform and load (ETL) your data to the database. This approach is:

  • Highly customizable to your requirements
  • Fully controllable and flexible
  • Costly and resource-intensive usually


3. Data APIs for Data Collection 

Programming knowledge is usually required for using these third-party data APIs that provide you with the data required. It can usually be used on-demand. Data API does serve the purpose well but as the data requirements increase, the costs increase too. Besides, you don’t get to customize the data.


4. One-stop Data Service

An alternative to using web scraping tools or hiring developers is to outsource your data extraction requirements. There are IT services companies which would cater to your data requirements. Under the hood, they’ll be using one of the above approaches. 


5. Scraping Techniques for Mobile Apps

To scrape from Mobile apps, you can try using tools like Selendroid, Appium, Bluestacks, or Nox emulator to run mass mobile app scraping in the Cloud, but this is not as easy as it seems. Scrapping at scale is full of challenges if you do it on your own. If this is something you need, you can also consider:


  • Scraping the PWA version of the mobile app, if it exists 

Many popular mobile apps have web versions, like Quora, Amazon, Walmart, Indeed, etc. Scraping the web versions can be much easier than scraping directly from mobile apps. Some scraping tools provide pre-built templates for scraping popular websites so making it even easier. 


  • Outsourcing mobile app scraping 

IT companies that provide app scraping services have extensive experience in tackling the challenges involved with scrapping and can smooth out the process for you.



Top Web Scraping Tools 

With python being the most popular scraping language, Scrapy, a python framework for web scraping is definitely one of the most used open-source tools. As for no-code web scraping tools, Octoparse is my personal favorite, given the fact that it is highly customizable and even provides pre-built templates and almost all the other features of an ideas SaaS tool for scraping the web. 


Top web scraping tools that you must know:

  1. Octoparse
  2. Import.io
  3. Diffbot
  4. Mozenda
  5. Parsehub
  6. Scrapinghub
  7. UiPath
  8. WebHarvy


Top open-source tools for web scraping:

  1. Scrapy
  2. Apache Nutch
  3. StormCrawler
  4. PySpider
  5. BS4


Web Scraping Challenges and Solutions

Web scraping can be challenging. It's important to be considerate of what your options are and what are some of the issues that can be expected along the way. 


1. Choosing the right web scraping tool

We have ample options today, almost for everything. It is essential to pick the right web scraping tool for your project and here are some tips for you!


While looking for the right scraping tool for your project, you should:

  • Define your requirements well
  • Pre-validate your scraping ROI
  • Chose a tool that fits your budget 
  • Make sure the tool is documented extensively to help you out if struck
  • Know that's support is provided for the tool 


2. Dealing with dynamic JS, AJAX rendered websites

Web pages come in many forms, for example, for web pages that employed infinitive scrolling, you will need to keep scrolling down the page to get additional search results. 

For this type of website, good scraping tools automatically handle this. But, if you’re using custom scripts, you need to reverse engineer the HTML requests. Check out our tutorial of how to deal with the web page with infinite scroll.


3. Adapting to ever-changing website structure

Another big challenge associated with web scraping is the ever-changing web page layouts. Many websites update their UI from time to time. This makes previously written scrapers fail. So, these scrapers make use of Xpaths which is to parse semantic HTML/XML docs. 

Using relative, generic, niche Xpaths could help here. For example, don’t write div/div[3]/p/text() if your <p> element has an id. Prefer writing //p[@id=“price”]. 

Check out more about Xpath.



Captcha is also one type of scraping challenges. Captcha stands for the Completely Automated Public Turing test to distinguish a person from a robot. Logical tasks or input of characters are displayed for verification, which humans solve quickly and robots can not. Indeed, many Captcha solvers are now implemented in bots for continuous data collection, it might slows down the process a bit though. However, setting up delay time is just a one of many methods. Captcha are various and therefore there are many methods to solve different captchas relatively. 

Although we might meet different types of captcha during web scraping, we have methods to solve them accordingly, for more information about captcha check out the resources:

5 Things You Need to Know of Bypassing CAPTCHA for Web Scraping

How To Solve CAPTCHA While Web Scraping?


5. Avoiding Honeypot traps

A honeypot is a cybersecurity mechanism that uses a manufactured attack target to lure cybercriminals away from legitimate targets and also gathers intelligence about the identity, methods, and motivations of adversaries. To identify bots, websites often place links with the CSS display attribute set to none. So that humans can’t see it but a link crawler would access it. 

However, you don’t fall into this trap if you use click & scrape tools. If you’re using custom scraping programs, extensively inspecting the website would help avoid such traps.


6. Tackling anti-scraping technologies 

Anti-bot technologies use a combination of web tools like IP, cookies, captchas, browser user agents, fingerprints, etc., to block a scraping bot. 

But, as mentioned earlier, click and scrape tools have inbuilt features to handle these. If you’re writing scraping scripts, rotate IP proxies, user-agents, use captcha solving services or code your ML program to solve captchas.

Check out 5 Anti-scraping technologies you may encounter and how to solve them.


7. Be considerate of legality

Web scraping is legal if it doesn’t violate privacy. The Linkedin vs HiQ court shut all voices about scraping being illegal. Scraping data behind login walls is similar to scraping public data. But yes, this is unethical if done without permission as it violates privacy laws.



Final Thoughts and Next Step

Congratulations, you are done with all the readings! I hope you have a deeper understanding of the different aspects of web scraping now. 

In the era of big data, no matter whether you need this technique for now or later, it's definitely worthwhile to know your options are ahead of time and get prepared.  

As for web scraping tools, we do think that you should give Octoparse a chance and just try it out. It's free and easy to learn, which means a  great deal for anyone that's looking to start any web scraping projects. So, why wait? Get started for free today!






Author: Krystal


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