What is Web Scraping? A Complete Guide

In another post, we covered how screen scraping can significantly ease the data collection, collation, and management process. But screen scraping isn't the only way to achieve this goal. In many cases, there are better ways. In this article, we'll explore web scraping, another invaluable data collection method, covering how it differs from screen scraping, how and when you should use it, and how it works.

Web scraping is a computer technique used to extract information from websites. It involves automatically fetching web pages, extracting data from them, and saving that data for various purposes. Here's a more detailed explanation:  

• Request: You start by sending a request to a website's server. This request is like entering a web address in your browser.  

• Response: The website's server responds by returning the requested web page. This page typically contains text, images, links, and other data.  

• Parsing: Web scraping tools or scripts analyze the web page's content. They can be programmed to locate and extract specific data from the web page, such as product prices, news articles, or contact information.  

• Storage or Usage: The extracted data can then be saved in a file or database for further analysis, or it can be used for various purposes, such as price comparison, research, or building a dataset.  

Web scraping helps automate gathering data from websites, which is tedious, time-consuming and error prone when done manually.  

Web scraping focuses on extracting data from websites. It involves sending HTTP requests to web servers, retrieving web pages' HTML content, and then parsing and extracting specific data from these pages. Scraping websites is primarily used to extract data from websites for various purposes like data analysis, price comparison, or content aggregation.  

Screen scraping is a broader term for extracting information from software applications' graphical user interface (GUI). It doesn't necessarily involve web content. Instead, it captures data displayed on the screen of a computer application. Screen scraping is often used to automate interactions with legacy software or extract data from desktop applications.  

So, the critical difference is in the data source. Web scraping is specific to web content, while screen scraping deals with data from software applications, including web-based and desktop applications.  

Web scraping is a subset of data scraping specifically tailored to extracting data from the web; data scraping encompasses a broader range of data extraction techniques from various sources, not just the web.  

Web scrapers come in many different forms and have many diverse uses. We'll cover a few here, but this list is not exhaustive.  

Browser extensions are add-ons or extensions you can install directly into your web browser (e.g., Chrome or Firefox) that facilitate data scraping from web pages. They are user-friendly, typically offering a point-and-click interface, provide immediate visual feedback, meaning users can see what they're scraping directly, and require little to no setup, eradicating the need for external installations or configurations. However, they are typically unable to handle complex or large-scale scraping tasks and are entirely tied to a specific browser. One example is "We Scraper" for Chrome, which allows users to navigate to a webpage, click on particular data, and extract it into a structured format, all within the browser.  

Programmatic/scripted scraping involves writing code/scripts using, for example, Python, Java, or Ruby to fetch and parse web content. This method is best for complex tasks like dynamic content loading or user simulation. It is easily scaled, suitable for large-scale scraping operations, and can be integrated with databases, APIs, or other systems. Programming/scripted scraping, however, requires programming knowledge and is largely inaccessible to those unfamiliar with coding. It also requires regular maintenance, as web structure changes can break the scraper. An example of this type of scraping is Using Python with libraries and requests (for static content) or Selenium (for dynamic range) to navigate web pages, fetch content, and parse the desired data.  

Dedicated web scraping tools, like Scrapy Cloud or Octoparse, are specialized software or platforms, often cloud-based, explicitly designed for web scraping. They are easy to use, many cater to large-scale scraping needs, and some even offer automatic adjustments to the scraper when websites change. However, they generally lack flexibility and customization and are often priced based on usage.   

Robotic Process Automation leverages software robots to take repetitive, rule-based tasks off your plate, like web scraping. RPA bots mimic what a user does on a webpage, saving time and reducing errors. RPA tools, like Fortra’s Automate, can interact with dynamic pages and web apps, inject JavaScript, read table data structures, directly access source code, and integrate with databases, APIs, and other applications – without writing any code. Some providers, like Automate, also offer UI recorder functionality. One big advantage of RPA is the ability to integrate your web scraping tasks with other automation workflows at your organization. 

Web scraping has a wide range of practical applications across various industries. Here are 10 everyday use cases:  

• Price Comparison: Retailers use website scraping to monitor competitors' prices and adjust their pricing strategies accordingly.  

• Market Research: Businesses gather data on customer sentiment, product reviews, and market trends from websites and social media to make informed decisions.  

• Content Aggregation: News aggregators and content websites automatically collect articles and posts from different sources to provide a centralized hub for users.  

• Lead Generation: Sales and marketing teams scrape websites to collect potential leads or clients' contact information (email addresses, phone numbers).  

• Job Market Analysis: Job seekers and recruiters use internet scraping to collect and analyze data about job postings, salaries, and skill requirements.  

• Real Estate Listings: Real estate agents and buyers scrape websites to gather information on available properties, including prices and location details.  

• Weather Data: Meteorologists extract data from websites to analyze historical weather patterns and make forecasts.  

• Stock Market Data: Investors and financial analysts scrape financial news websites and stock market data to make informed investment decisions.  

• Academic Research: Researchers gather data from academic journals, repositories, and websites to support their studies and analyses.  

• Travel Planning: Travel agencies and individuals scrape travel websites to compare prices, availability, and reviews for flights, hotels, and vacation rentals.  

Before you embark on your web scraping journey, there are a few things you should consider. Web scraping can be a powerful tool, but following best practices is essential to ensure you scrape data ethically, responsibly, and effectively.  

• Respect Website Terms of Service: Always review a website's terms of service or robots.txt file to ensure you can scrape data from that site. Abide by their rules and limitations.  

• Use Rate Limiting: Implement rate limiting in your scraping code to avoid overloading a website's server with too many requests in a short time. Respect the server's response times.  

• Identify Yourself: Set a user-agent in your HTTP requests to identify your web scraping bot or script. Make sure it's clear who you are and how you can be contacted.  

• Avoid Scraping Private Data: Do not scrape private or personal data, such as login credentials, financial information, or sensitive personal details. Stick to publicly available data.  

• Keep Data Quality in Mind: Ensure the data you scrape is accurate and reliable. Verify the data and clean it as needed to remove errors or duplicates.  

• Handle Errors Gracefully: Implement error handling in your code to deal with everyday issues, like network failures or changes in website structure. Logging errors can be helpful for troubleshooting.  

• Use Respectful Scraping Tools: Choose reputable web scraping libraries and tools commonly used in the web scraping community, as they often incorporate best practices.  

• Use Headless Browsers: In some cases, consider using headless browsers like Puppeteer or Selenium for web scraping. These tools can render pages like a web browser, allowing for more complex interactions and data extraction.  

• Test Your Code: Regularly test your scraping code to ensure it works as expected. Websites can change their structure, so periodic testing and updates are crucial.  

• Be Mindful of IP and Location: If you're scraping multiple websites, be aware of IP blocking or geo-restrictions. Consider using proxies or VPNs to change your IP address if necessary.  

• Legal Compliance: Ensure that your web scraping activities comply with all relevant laws, including copyright, data protection, and privacy laws in your jurisdiction.  

• Be Ethical: Use web scraping for legitimate purposes and avoid harming websites or violating their policies. Respect the ethical considerations of data extraction.

In this video, see how to easily build out a web scraping task with Fortra’s Automate, using a combination of step-by-step screen recording and native actions. In this example, you’ll see how Automate bots can read a list of products, go out to multiple websites and scrape data like price and stock information, and write the information back to an Excel file. 

As you evaluate the best choice for your web scraping needs, look to Fortra’s Automate, built for employee-driven, enterprise-wide automation. Automate’s RPA capabilities are great for your web scraping needs—and beyond. Our user-friendly, no-code approach brings automation to everyone via drag-and-drop capabilities, 70+ native actions to common applications —like Microsoft, OCR, FTP, AWS, and more—, and our robust screen recorder. Whether you’re a power user or citizen developer, Automate is flexible and powerful enough to cover your unique automation needs. 

Not only can Automate scrape data from websites, but it also can transform and move your data without the need for additional tools, letting you put it in an Excel file or uploading it right to your ERP, database, or other applications, and send a report to key stakeholders. With our powerful API integration kit, connect to your most critical apps and systems at every step of your data processes. Pricing starts at $5,000 annually, with no limits to the number of webpages you can scrape.