You may have heard of web scraping at some point. It’s typically used in conversations about collecting data or text from a source to transfer to another page or a database.
Read on to find out more about web scraping, who uses it, and how you can implement it in a project.
What Is Web Scraping?
Web scraping is the process of pulling information from the Internet. From a technical level, web scraping could be something as small as copying and pasting text online. This process involves collecting data from the Internet, which means that scraping is involved.
However, when most people talk about web scraping, they describe the process of automated information collection using a program. This distinction means that you can think of copying and pasting as scraping to start understanding how scraping works. But there are variations, a major one being the automated process of scraping.
What Does Scraping Data Mean?
The web scraping process involves sending one or multiple requests to a site you want to collect information from. An example would be trying to scrape home price data from Zillow for a project on price trends over the years in specific neighborhoods. For that, you would have to send requests to Zillow pages to download the information automatically.
Web scraping in this process would involve the automatic download of the pricing information using a program. That is why copying and pasting don’t necessarily constitute “scraping,” although the goal and end result are the same.
In web scraping, you begin by setting up a program to collect information and tell it where to store the information collected. One of the most popular languages used in web scraping projects is Python.
What Are the Uses of Web Scraping?
Web scraping collects information for all kinds of purposes and projects. The strategy is most popular among data scientists who collect large amounts of data to study or make improvements to an already existing product.
Stock market apps, for example, often scrape stock data for companies across markets over time to make predictions about potential trends. Scrapers also exist for more everyday purposes like pulling information from a website to transfer it to a new domain in a process also known as “migration.”
Finally, some webpages have measures in place that make it difficult for users to copy and paste information. In such an instance, web scraping would be the only way to collect information.
Who Uses Web Scraping?
Web scraping is frequently used by data scientists, machine learning (ML) engineers, analysts, developers, and researchers. While all of their jobs involve programming, you’ve also probably used web scraping to collect information even if you aren’t a programmer.
Here’s an example: If you’ve used real estate data to determine where to buy a home, you probably scraped information from multiple sources online. Another example is if you’ve explored the data that startup hiQ Labs scraped from LinkedIn. When the matter went to court, hiQ Labs had the upper hand, and its data, which predicted when workers might leave their jobs, remained public.
Web scraping has several other uses that are entirely legal. Researchers most often scrape the Web to predict trends based on currently available information. One of the easiest ways to analyze information from multiple sources or a lot of data from one source is to see it in a database or data repository. Scraping is also useful in this process.
What Are the Types of Web Scrapers?
There are three primary types of web scrapers, each with its advantages and disadvantages, depending on the project. Self-programmed scrapers, browser extensions, and interactive scrapers are most commonly used.
Much of the information in this article concerns self-programmed web scrapers. Anyone can build a web scraper for research, specifically to collect data. Creating a web scraper is also easy, as it only requires a place to store data, such as a spreadsheet or database, and the site you want to scrape information from.
Browser extensions are likely the most common type of web scraper. These are downloadable software for your browser so you can collect information without building a scraper yourself.
Many browser extensions (some of which you may already use) utilize scraping to collect and display information. Honey, for example, searches for deals by scraping pricing data and information from any webpage you are visiting.
Interactive scrapers are similar to extensions, but they are not downloaded and installed on a browser or computer and work right off a webpage.
How Do You Start a Web Scraping Project?
Start a web scraping project by considering what type of data you want to collect. Web scraping is an easy process since it is common, which means you have multiple programs to choose from, each with its own benefits.
The entire process only takes a few steps. The first is visiting the site you want to scrape data from to see what information is present. The second step involves creating a repository for the information you want to collect. Next, write the code, which is typically a short program that tells the scraper which site to access, what information to pull, and where to store it.
While building big web scraping projects requires robust data collection methods, a small one only takes a couple of hours to complete from start to finish.
What Do You Need to Consider When Web Scraping?
One factor to consider in a web scraping project is make sure you’re not doing too much at once. If you send too many requests to a webpage while scraping, you could receive some disciplinary action, such as a site ban. You can also negatively impact the site.
For example, some websites limit the flow of data, so an excessive download queue could flag your activity and potentially block your account. Site owners may use CAPTCHAs to prevent automatic scraping, too, mainly because if you overload their websites, they could fail, resulting in extensive downtime while they attempt to fix them.
Web scrapers are tools that you likely interact with every time you use an app or extension. Since data plays a large role in so much of what we do online, web scraping is ubiquitous and built into many programs—either for making improvements, data collection, or predictions.
Web scraping is also an interesting programming project to experiment with code hands-on, and best of all, it only takes a couple of hours to do it.