Large-Scale Web Scraping – A Comprehensive Guide

Large-Scale Web Scraping - A Comprehensive Guide
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TL;DR:

To begin with, here’s a quick TL;DR on large-scale web scraping –

What is large scale web scraping?

Simply put, it is scraping a huge number of websites to extract relevant data to help your business.

Why is large scale web scraping used?

It’s used for a multitude of factors such as data analysis, price monitoring, measuring site traffic and tracking your competition.

What are some of the best tools for large-scale web scraping?

There are quite a few tools available for web scraping at scale, with Bright Data’s Scraping Browser (currently on a limited time offer of up to 50% off!) being one of the best. The first of its kind, this is the only browser which comes with built-in website unblocking capabilities. Bright Data is also the world’s #1 web data platform, so you know you’ll get your money’s worth!

How does large-scale web scraping work?

There’s a process that involves crawlers, scrapers, proxies and bypassing bot detectors. Read on to know more.

Now let’s get into the details of web scraping at scale.

Information is key. And if you have a data-driven business, it becomes all the more important. 

The most fool-proof method to scale up your business is to collect as much data as you can and then process that into something that helps boost your cause and gives you an edge over your competitors.

But how do you go about scraping the endless internet, filled with its countless web pages and innumerable amounts of data? In comes large-scale web scraping to the rescue!

Large-scale web scraping essentially is the process of scraping a vast number of websites to extract relevant data to help your business. Large-scale web scraping has multiple uses: for the analysis of data, monitoring of price, measuring site traffic, conducting market research and content aggregation. This method is the go-to option for all processes that require extracting massive amounts of data from the internet.

The two broad types of large-scale web scraping are:

  • Scraping and extracting data from a large number of web pages from within a major website such as Amazon or Myntra or LinkedIn 

  • Simultaneously collecting data from 1000s of different small websites

Both approaches can get the job done, as long as your tools are strong enough to gather and extract the relevant data. Large-scale web scraping provides you with a cost-effective method to extract tonnes of data, which in turn helps you make data-driven decisions that would lead to greater product development.

While it works like a charm in getting you access to a large chunk of data in quick time, it brings along a few challenges as well. 

For starters, you will need a super-powerful system of operation that can scan millions of web pages and extract data rapidly. You will also need to ensure this is an automated process because manually executing this process would be extremely time-consuming. Plus, your automated scraping tool must be able to bypass anti-scraping measures and be equipped to handle dynamic content. More on this later.

How is large-scale web scraping different from normal web scraping?

While both methods are spokes of the same wheel, what separates large-scale web scraping from normal web scraping is the sheer volume. Large-scale web scraping tools are virtually similar to normal web-scraping tools, except they are 100x stronger and faster. 

They’re like normal web-scraping tools, but with 10 cups of coffee in them.

How does large-scale web scraping work?

Large-scale web scraping is the result of a series of functions and processes, performed simultaneously. For example, if you want to scrape data from a product page on Amazon then you need to have multiple processes running at the same time such as a crawler, a scraper, the framework to process the data and a space to store all the information.

Let’s delve into the steps needed for large-scale web scraping –

  1. Set up a crawler + scraper: You need to establish a crawling path to begin the process. A crawling path is essentially a collection of URLs from which the data can be scraped. In order for the scraping process to function smoothly, you will have to create a continuous scraping process which can work on multiple pages simultaneously. Both functions must happen in sync for the best results.
    In short, your crawlers must identify the pages that have relevant data and then your scrapers get working on them to extract all the relevant data.

  1. Collection of proxies: One of the fundamental requirements for large-scale web scraping is proxies. Websites store data from IP addresses after every request. When it notices there are numerous requests from the same IP, it blocks them. That serves as a big hurdle in the scraping process.
    Using a proxy server comes in handy here as it will help mask your location and switch up your IP after each request to facilitate a smooth scraping process.
  2. Bypassing bot detectors: Anti-scraping tools have become very common on the internet today. Websites enable anti-bot strategies such as CAPTCHA, where you’re usually presented with nine images and asked to choose the correct ones based on the question posed. For eg: Choose the images that have a fire hydrant. 
    Typically, such tools require humans to solve the puzzle. However, you can use reverse engineering to combat the anti-bot measures.

  1. Data warehouse: It’s a no-brainer that large-scale web scraping will yield large amounts of data. Storing this data is an essential element. But where do you store all that data? If you’re scraping and processing your data in small batches, then you could just use a spreadsheet. However, when you’re processing data in bulk, you will have to look out for options such as MySQL or cloud storage services.
  2. Maintaining and upgrading your scrapers: Technology changes almost on a daily basis and your scrapers will have to be up to date to ensure they can keep up with these changes. Minute changes in the target website’s structure could affect your scraper’s functioning and lead to a breakdown of the systems. It is ideal to set up a system where the scraper notifies you when it is unable to do its role and you can step in to rectify the issue.

Why do you need to use large-scale web scraping?

If you’re not convinced already, here’s a breakdown of all the wondrous things large-scale web scraping can do and how it can help you grow your business.

  • Saves you money and time: The use of large-scale web browsing will prevent you from burning a hole through your pocket because using a scraping tool is far more cost-efficient than hiring people to do the same. A tool can do what three humans can do, thereby largely cutting your costs. It also saves you time as automatic data collection and extraction, performed by your tool, is much faster than manual data collection.
  • Helps better market understanding: Processing large-scale data can give you indications of how the market is functioning and what you can do to further scale your business. Access to massive amounts of data from numerous sources lets you monitor your competitors, study consumer preferences, collect market intelligence and track the emerging trends in the market.
  • Automatic data collection: Among the biggest advantages of large-scale web scaling is the fact that data is automatically collected by the scraping tools, irrespective of whether you are- around or not. You can simply schedule your tool to gather data at regular intervals and that will ensure you have the most updated and relevant data at your fingertips.

  • Aids in building a better product: The use of large-scale web scaling helps you track how consumers are reacting to your product and what’s working and what isn’t. You could open up two versions of the same product and see which the consumers are engaging better with, thereby giving you a comprehensive idea of what the consumer wants. Tracking consumer feedback and reviews all help in product enhancement.
    Click here to know more about AI powered tools to understand the market better and build a better product.

What are the challenges that come along with large-scale web scraping?

Challenges come along with all good things. While large-scale web scraping does have certain prerequisites such as powerful systems to collect, process and store data, here are some of the other bumps you could face –

  • Anti-scraping measures: Websites do their bit to prevent you from scraping the data on their web pages by using a bunch of anti-scraping measures. These include implementing CAPTCHAs, JavaScript challenges or tools to identify and block bots. It isn’t impossible to beat these measures, you just need to ensure your scraping tool has the technical capabilities to work around these barricades.
  • Handling dynamic content: While HTML websites are relatively easy to scrape, some websites use dynamic content loaded via JavaScript, AJAX, or APIs. These websites may have interactive features such as clicking on images [CAPTCHAs] and filling out forms, which could pose a challenge to the scraping tool. Your scraping tool will need to be programmed in such a way that it can simulate such interactions to get access to the data on the web page.
  • Differing website structures: Different websites have different structures – from their layouts and designs to the language used to code. Plus, websites are likely to undergo changes and upgrades at periodic intervals. To counter this, your large-scale web scraper must be updated and programmed regularly to keep up with the changes on the internet and you could even look at making customized scraping programmes for different websites.
  • Quality of data: As the saying goes…too much of anything is too much. Scraping data from websites might be an easy task, but analyzing and classifying it into something meaningful is a challenge and a half. Especially when you’re dealing with aspects such as inconsistent and incomplete data. Going through large datasets is also very time-consuming, so the best approach would be to include automated metrics to validate and check the data for any inaccuracies.

What are some of the best tools for large-scale web scraping?

There are plenty of tools around for large-scale web scraping. Here are some of the top choices:

  • Scraping Browser: Bright Data is the world’s #1 web data platform and has launched a browser that is specially designed for scraping web data. Presenting to you – Scraping Browser! The first of its kind, this is the only browser which comes with built-in website unblocking capabilities.
    Scraping Browser, which runs on common high-level APIs like Puppeteer, can discreetly handle all website unlocking tasks such as getting past CAPTCHA, browser fingerprinting, selecting headers, accepting/rejecting cookies based on Bright Data’s Web Unlocker.
    It works on projects of every scale and can bypass any bot-detection software, ensuring you can scrape all the data you require in the smoothest manner.
    Used by a large number of Fortune 500 companies, Scraping Browser offers a free trial for you to get a whiff of the magic they offer. Grab your free trial today with a special up to 50% off until the end of this month!

  • Scrapy: This is a commonly-used open-source large-scale data scraping tool that is written in Python and runs on Linux, Windows, Mac and BSD. It’s very versatile in nature as it manages requests, parses HTML web pages, collects data and saves it in the format that works for you. Scrapy is a great tool for large-scale web scraping and performs complex functions such as scraping product data from e-commerce websites with ease. Considering it is an open-source tool, it is constantly updated and comes with the benefit of community support, but it also necessitates a decent level of Python knowledge.
  • Puppeteer: Puppeteer is a Node.js library which is maintained by the Chrome DevTools team. It gives you a proper browser setup and creates an automated testing environment by employing the latest JavaScript and Chrome features, which is its USP.
    Puppeteer can scrape Java-heavy SPAs (Single-Page Applications) and also automate form submission and keyboard input, which helps you bypass anti-scraping tools in a breeze. This Chrome-powered tool is a fantastic option if you’ve chosen JavaScript as your preferred platform.
  • ScrapingBee: The ScrapingBee API enhances scraping by handling headless browsers and constantly rotating proxies. It is light, super fast and can render JavaScript to scrape any website. Their large proxy pool reduces the chances of getting blocked by anti-scraping tools and ensures automatic proxy rotation from time to time.
    It supports libraries for Python and JavaScript and is perfect for businesses that want to focus on the scraping process and don’t want to stress over proxies or headless browsers. ScrapingBee offers an initial free trial of 1,000 API calls and gives you access to a fully functional Chrome Browser engine.
  • WebScraper: They have the simplest UI – you can configure the scraper tool by simply pointing your mouse at an element and clicking on it. And that’s it, you have the data ready without the need for any coding. WebScraper is a fine option to extract data from dynamic websites and it has the ability to navigate a website on all levels. 
    This Chrome-based scraper is ideal for companies that do not have a development team as it requires no code whatsoever. It’s very simple to use and allows you to export data in CSV format directly from your browser.

 

 

Is large-scale web scraping ethical?

 

 

Large-scale web scraping is absolutely legal, but how ethical it is depends on your approach to scraping and collecting the data. Flouting websites’ terms of use, breaching their data privacy codes and adding undue strain on a website’s resources would count as unethical and might not be the best way to collect data.

 

 

Here are a few aspects you can adhere to when scraping the web at a large scale –

 

 

  • Ensure data privacy: When scraping data from multiple web pages, always ensure that sensitive data is handled and stored carefully. Personal and sensitive data such as mobile numbers, social security numbers and personal identification details must be stored and processed with utmost care.

 

 

  • Respect website policies: Websites may mention a clear diktat on data that is automatically scraped and some websites may even explicitly prohibit the scraping of their data. In such cases, it is advisable to respect the website’s policies and terms of use because violating these terms is unethical and can be considered illegal as well.

 

 

  • Don’t cause an overload: Large-scale scraping puts a fair amount of strain on a website. However, relentless scraping could cause a server overload and affect the website’s functioning and affect the user’s experience, which is an unethical thing to do. Try to avoid bludgeoning a website’s servers by extensively scraping it.

 

 

  • Be wary of intellectual property rights: As a rule of thumb, always make sure the data collected from large-scale web scraping does not infringe any copyright or intellectual property rights. If needed, seek permission from the owner of the data before using their data because that could attract a lawsuit and is far from ethical.

 

 

Takeaways: Frequently Asked Questions (FAQs) on large-scale web scraping

 

 

Now that we’ve taken a detailed look at all there is to know about large-scale web scraping, let’s do a quick recap:

 


Q: What is large-scale web scraping?

 

 

A: Large-scale web is the process of crawling through a vast number of websites to then scrape them for relevant data to help your business. 

 

 


Q: What are the uses of large-scale web scraping?

 

 

A: Large-scale web scraping has multiple uses: to analyze data, monitor price, measure site traffic, track customer sentiment, market research and content aggregation.

 

 

Q: Is large-scale web scraping different from normal web scraping?

 

 

A: Large-scale web scraping tools are virtually similar to normal web-scraping tools, except they are 100x stronger and faster. The main difference is that large-scale web scraping tools function on sheer volume.

 

 

Q: What are the advantages of large-scale web scraping?

 

 

A: The many advantages of large-scale web scraping include the fact that it saves you loads of time and money, helps you improve your product development, aids in better market understanding and facilitates automatic data collection.

 

 

Q: Are there any challenges in large-scale web scraping?

 

 

A: Large-scale web scraping does have a few challenges that you will have to bypass such as different website structures, handling dynamic content, maintaining quality of data and getting past anti-scraping measures.

 

 

Q: Is large-scale web scraping legal and ethical?

 

 

A: Large-scale web scraping is very much legal, provided you do not flout any rules or misuse the data. The ethical way to approach large-scale data scraping is by ensuring data privacy, not causing an overload on a website’s servers, respecting a website’s terms of use and ensuring you adhere to copyright laws.

 

 

Q: What are the best tools for large-scale web scraping?

 

 

A: Some of the best tools for large-scale web scraping include Scrapy, WebScraper and Bright Data’s all-powerful Scraping Browser (you have to check them out!)

 

 

Disclosure – This post contains some sponsored links and some affiliate links and we may earn a commission when you click on the links, at no additional cost to you.AIunderst

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