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Introduction to Web Scraping Techniques and Tools

Monday, August 2, 2021

Data is estimated to be a USD 274.3 billion industry by 2022. Leaders of tomorrow are harvesting data today. As a business leader, you need to figure out:

      • 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 extract valuable data. In this article, we aim to give you a no-brainer introduction to web scraping technologies, tools, and tips to scrape websites. These ideas may help you make smarter decisions in web scraping and your business.



Table of Contents



What Is Web Scraping?

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

Suppose, you need to extract all the email IDs commented on a Linkedin post. You may point the cursor to the string of an email address, copy and paste it into a file. The repetition of the same process is called manual scraping.

Web scraping is a term given to programmatically perform the above operation at scale. To gather 2000 email ids, human work can take 3 hours, while it only takes 30 seconds if done using a web scraping tool. 


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 written by coders can serve the end.



Business Use Cases Of Web Scraping

Big data helps people understand the market and gain a competitive advantage over competitors. In this sense, web scraping is widely used among freelancers, entrepreneurs, marketers, online sellers, consulting people, and researchers. 

Businesses can 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



Four Ways To Scrape The Web

Manual scraping is merely a feasible option as it is far from productive. Instead of wasting a whole day clicking and pasting around in front of the screen, there are 4 ways you can get web data at scale in an efficient manner.


Web Scraping Tools

Screen scraping or click & scrape tools are the simplest way to scrape the web. Really? YES. Here are five reasons to support my claim:

    • 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 1100, or a million pages based on your needs without worrying about the infrastructure & network bandwidths.
    • In-built features to bypass anti-scraping website architecture. Modern websites implement anti-bots mechanisms on websites to discourage scrapers from collecting data. Good scraping tools take care of these anti-bot tools and deliver a seamless scraping experience.

Enable you to scrape anytime, anywhere i.e, you can perform scraping using your local machine, as well as you can use their cloud infrastructure.


In-house Web Scraping Developers

If your requirements are too complex to be handled by a “click and scrape” 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:

    • Highly customizable to your requirements
    • Fully controllable and flexible
    • Costly and resource-intensive too as it requires 


Data APIs for Data Collection 

Again, you need programming knowledge to use these third-party data APIs that provide you the target data. It can be used on-demand. This serves the purpose well but as the data requirements increase, the costs increase too. Besides, you don’t get to customize the data.


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 methodologies. Based on your requirements and budget you may instruct them to choose your preferred method.



How To Scrape Mobile Apps?

Mobile app scraping is called scraping. You can try tools like Selendroid, Appium, Bluestacks, Nox emulator and run in the cloud to perform mass mobile app scraping. But this is not as easy as it seems. Scraping one application can be performed by reverse engineering it and observing the traffic. But scrapping at scale is full of challenges if you do it on your own. Cloud providers avail you VMs to run your software but android app emulators are themselves VMs. So, VM on VM yields terrible performance. Here is what you can do to scrape mobile apps:


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

Many popular mobile apps have a web version too. Like Quora, Amazon, Walmart, Indeed, etcetera. You can scrape these websites easily. Good scraping tools provide you pre-built templates for scraping popular websites. You can customize them too.


  • Outsource mobile app scraping services

IT outsourcing companies providing app scraping services have long experience to handle the challenges involved with scrapping and can smoothen the journey for you.



Is web scraping legal? 

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.



Top Web Scraping Tools Available  

Python is by far the most popular scraping language. Scrapy, a python framework for web scraping has 39.8k stars on Github. Octoparse is my personal favorite, given the fact that it is highly customizable and even provides pre-built templates and almost all other features of an ideas SaaS tool for scraping the web. 


Here is my list of top web scraping tools that you must be aware of:

  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



Six Challenges Associated With Web Scraping

A web scraping task could face different challenges. This depends on the conditions of your device, network, and the structure of the website you are scraping from.


01 The right web scraping tool
We have ample options today, almost for everything. While choosing web scraping tools you must do proper research about the tool you use. The best way to finding the right tool is: 

      • 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
      • Has good executive support mechanism


02 The right approach to data warehousing

    • Data scraped is often not consistent. Structuring the data to make it worth consuming by ML algorithms involves parsing, cleaning using regEx techniques. 
    • Choosing where to store your data is an additional overhead. But this is easily manageable by using cloud DBs like DynamoDB or RDS.



03 Dynamic JS, AJAX rendered websites

For example, scraping SPAs with infinite scroll UI. Good scraping tools automatically handle this. If you’re using custom scripts, you need to reverse engineer the HTML requests.


04 Changing website structure

Many websites update their UI from time to time. This makes previously written scrapers fail. 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”].


05 Honeypot traps

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. 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.


06 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. 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.



How Octoparse Can Help?

Octoparse is a click & scrape web scraping tool. You can quickly start scraping data within seconds and “turn web pages into structured spreadsheets”. 




Here is why I recommend using Octoparse,

    • Free to get started, 10,000 data points per export
    • Provides IP rotation for handling anti-scraping technologies
    • You can scrape in the cloud and stop worrying about network bandwidth, infrastructure setup, etcetera
    • Handles websites with dynamic Javascript
    • Thoroughly documented
    • Email & community support
    • Pre-built templates to scrape websites



Where to go from here? 

Data Extraction Use-cases

Web scraping Blog

Download Octoparse


Author: Nishant

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