Web scraping is an automated method to extract large amounts of data from websites. This data, usually in HTML format, is converted into structured formats like spreadsheets or databases for further use. It can be done through online tools, APIs, or custom code. While major websites like Google, Twitter, and Facebook offer APIs for structured data access, web scraping is often used for sites that lack such options or restrict data access.
Web scraping involves two main components:
- Crawler: An AI algorithm that navigates the web and follows links to find the required data.
- Scraper: A tool designed to extract the identified data from websites, with its design varying based on the project’s complexity and scope.
How Web Scrapers Work?
Web Scrapers can extract all the data on particular sites or the specific data that a user wants. Ideally, it’s best if you specify the data you want so that the web scraper only extracts that data quickly. For example, you might want to scrape an Amazon page for the types of juicers available, but you might only want the data about the models of different juicers and not the customer reviews.
Web Scraping End-to-End Flow
- Input: Give URLs + specify what data you want (e.g., product name & price only).
- Request: Scraper visits each URL like a browser (sends HTTP GET).
- Load: Downloads HTML (runs JavaScript if needed for dynamic pages).
- Parse: Turns HTML into a navigable structure.
- Extract: Finds & pulls only the targeted data using selectors/XPath.
- Clean: Trims, converts, and organizes data into rows.
- Paginate: Follows “Next” links and repeats until done.
- Save: Exports clean data as CSV, Excel, JSON, or database.
Types of Web Scrapers
Web Scrapers can be categorized based on different criteria such as development type, platform, and execution environment.
Based on Development Type
- Self-built Web Scrapers
- Created from scratch using programming languages like Python or JavaScript.
- Require advanced coding knowledge.
- Offer full customization and flexibility.
- More features demand deeper technical expertise.
- Pre-built Web Scrapers
- Already developed tools that can be easily downloaded and run.
- Offer user-friendly interfaces and advanced customization options.
- Suitable for users with little or no coding experience.
Based on Platform
- Browser Extension Web Scrapers
- Installed directly as extensions in browsers like Chrome or Firefox.
- Easy to use and quick to set up.
- Limited by browser capabilities — cannot perform complex or large-scale scraping tasks.
- Software Web Scrapers
- Standalone applications installed on your computer.
- More advanced and feature-rich than browser-based scrapers.
- Not limited by browser restrictions but require installation and system resources.
Based on Execution Environment
- Cloud Web Scrapers
- Operate on cloud servers provided by scraper vendors.
- Don’t use your computer’s CPU or RAM.
- Allow multitasking since data scraping runs remotely.
- Local Web Scrapers
- Run directly on your own computer.
- Depend on local system resources (CPU, RAM).
- May slow down your system during heavy scraping tasks.
Why is Python a Popular Programming Language for Web Scraping?
Python seems to be in fashion these days! It is the most popular language for web scraping as it can handle most of the processes easily. It also has a variety of libraries that were created specifically for Web Scraping. Scrapy is a very popular open-source web crawling framework that is written in Python. It is ideal for web scraping as well as extracting data using APIs. Beautiful soup is another Python library that is highly suitable for Web Scraping. It creates a parse tree that can be used to extract data from HTML on a website. Beautiful soup also has multiple features for navigation, searching, and modifying these parse trees.
What is Web Scraping Used for?
Web Scraping has multiple applications across various industries. Let’s check out some of these now!
1. Price Monitoring
Web Scraping can be used by companies to scrap the product data for their products and competing products as well to see how it impacts their pricing strategies. Companies can use this data to fix the optimal pricing for their products so that they can obtain maximum revenue.
2. Market Research
Web scraping can be used for market research by companies. High-quality web scraped data obtained in large volumes can be very helpful for companies in analyzing consumer trends and understanding which direction the company should move in the future.
3. News Monitoring
Web scraping news sites can provide detailed reports on the current news to a company. This is even more essential for companies that are frequently in the news or that depend on daily news for their day-to-day functioning. After all, news reports can make or break a company in a single day!
4. Sentiment Analysis
If companies want to understand the general sentiment for their products among their consumers, then Sentiment Analysis is a must. Companies can use web scraping to collect data from social media websites such as Facebook and Twitter as to what the general sentiment about their products is. This will help them in creating products that people desire and moving ahead of their competition.
5. Email Marketing
Companies can also use Web scraping for email marketing. They can collect Email ID’s from various sites using web scraping and then send bulk promotional and marketing Emails to all the people owning these Email ID’s.