Did you consider that web scraping could open up new possibilities for your business?
You are probably facing the typical difficulties: the risk of getting your work blocked, difficulty removing content generated by JavaScript or AJAX, scalability obstacles, or the need to adapt often to site structure redesigns. These obstacles can make you feel stuck and unsure about starting.
That’s the reason we made this Beginner’s Guide to Web Scraping.
With or without technical knowledge, this guide will help you understand how to use this service. It explains the basics of web scraping and outlines how you can start using valuable information from websites to your benefit.
With web scraping, data from the web can be accessed more easily than by hand-entering or using only APIs. With the help of special tools, you can automate the process of collecting and organizing data from websites into spreadsheets or databases.
Web scraping allows you to gather large sets of data from websites and save them in a file or access them through a spreadsheet. Usually, when accessing a website, you can only view the information and not download it right away. Manually transferring data can be tiresome and is not suited for handling large amounts. It solves the issue by promptly and precisely gathering relevant web content using automation for analysis and making decisions.
You can collect text, images, videos, email information, and phone details from the Internet. Depending on the type of project, additional information for analysis can be pricing information, customer feedback, real estate listings, financial reports, or information about your competitors. Web scraping tools can collect and transport the data as simple files such as CSV, JSON, or plain text for additional analysis and use.
Web scraping uses automated tools to extract data from various websites. It operates like using the internet, except a program manages the process much faster and automatically. This is how things usually happen during the process:
The scraper sends an HTTP request to the server of a website to get a specific page. It acts just like typing in a URL and clicking enter.
After the server responds, the scraper gets the HTML of the web page. The page includes all the important elements that HTML provides, such as text, images, links, and others.
After that, the scraper uses a parser (for example, BeautifulSoup in Python) to read the HTML. At this stage, you need to determine what tags, classes, or IDs hold the information you wish to collect.
Following identification of the important portions of the page, the scraper takes the needed information, such as product details, prices, customer feedback, contact information, photos, or other available texts.
In the end, the data is saved in a well-organized way using CSV, JSON, an Excel file, or stored straight into a database. Therefore, you can easily analyze, share, or add it to other systems.
Advanced scrapers are designed to scrape more than just a single web page. They can:
Web scraping is a fast and effective way to gather and examine vast volumes of data from websites. It can be used in many different industries. The following are a few of the most popular uses:
Using web scraping, both retail and online businesses can keep an eye on how their competitors’ prices, products supplied, and promotions change every minute. As a result, they remain competitive by adjusting their prices or proposing new offers. Some online stores frequently update their product prices by checking Walmart and Amazon.
To learn what their customers think, like, and prefer, companies gather data from review sites, forums, and social networking platforms. It supports the company’s approach to developing and promoting a product. The example includes that a phone manufacturer could rely on reviews posted on different tech blogs and e-commerce websites to identify what people prefer or dislike in competitors’ products.
The method of web scraping is applied to get data on names, email addresses, phone numbers, and job positions from directories and LinkedIn. This information can be used to create lists for reaching customers. For example, a B2B business will gather mailing lists by scraping business databases for possible clients in the same line of business.
Firms in real estate use various websites to scrape listings and then combine them, look over trends, or compare what similar properties are listed for. For instance, investors in the property sector might review rental information in many cities to find areas that promise the best profits.
Job boards rely on scraping to gather job postings from company websites and job sites. They use this information to follow the latest changes in the job market or assign applicants to suitable positions. For instance, a job aggregator does this by collecting data from Indeed, Glassdoor and the websites of companies to show every job opening on its website.
They use technology to search for flight fares, hotel rooms, and rental cars on several online booking sites. This enables users to look for the best prices in one location. Here’s an example, Kayak and Skyscanner use scraping methods to acquire data about airline fares.
Financial news sites and exchanges provide investors and analysts with stock prices, earnings data, news and sentiments used to support their investment choices. For example, hedge funds analyze SEC documents and recent news articles to guide an AI system in predicting how stocks will move.
By using scraping, news websites bring together headlines and news articles from various websites. For example, a news app uses information from various online news sources to present the most popular headlines in politics, tech, and sports.
Brands rely on scraping tools to keep track of what’s being discussed about them on the internet. As a result, public relations are managed better, and customer service is improved. For example, a skincare brand keeps track of people’s thoughts about its products on blogs and on Reddit forums.
Various methods may be used for web scraping, depending on how complicated the website is and what sort of data you are interested in. Here are the main techniques people use when web scraping.
This is the easiest and most popular technique. This includes getting the HTML code of a web page and using tag names, class names, or IDs to extract the necessary data.
This strategy manipulates the DOM of a web page, which is the browser’s way of interpreting the page’s HTML. Data can be extracted from a range of new forms using NLP.
You can use XPath and CSS selectors to select certain parts of an HTML or XML document. You can use these for highlighting specific areas accurately.
Regex helps find patterns in text. Though it may not be able to get every bit of HTML code, it can easily get details like email addresses, phone numbers, or codes.
A number of websites offer APIs that let programmers request their data legally and easily. This is the easiest and most effective way to collect data.
Tools like requests, axios, and Postman can be used.
This repository supports sites that make public or paid APIs available (for example, Twitter, Yelp and YouTube).
To scrape information loaded by JavaScript, use tools like Puppeteer or Selenium to simulate people browsing a site.
Web crawlers scan many pages and access them through the links on those pages. Often, they help assemble huge collections of data.
Examine the structure, paths of HTML elements and the traffic network in Chrome DevTools or Firefox Inspector, as it is very important before starting to write a scraper.
To ensure effective, ethical, and sustainable web scraping, it's important to follow certain best practices:
All websites contain a robots.txt file to guide automated tools about which pages can or cannot be viewed on the site. Always examine this file prior to scraping any website. You can access robots.txt online (e.g., example.com/robots.txt), and it informs you if the site allows scraping and which pages are not allowed. If you overlook this, your actions might go against the rules of the website and can cause you to face legal issues or be blocked.
If you make multiple requests in a quick span, your site might prevent any further traffic due to server overload. You should introduce delays, use throttling methods, and skip site scraping while most users are online. As a result, the site remains stable, and it is less likely to be found by others.
The server finds out the type of client making the request from the User-Agent header. The default User-Agent sent by these libraries is identified easily as belonging to a bot. It’s beneficial to set a User-Agent string copying that of a real web browser, as websites may block your requests if the User-Agent string is unrealistic or absent.
A number of websites pay attention to IP addresses and can pick up on repeated activity from the same source. You can avoid being blocked by regularly using different sets of proxies or IPs. As a result, your scraper can mimic several different users and deliver tasks to various servers, which makes anti-bot programs less likely to recognize and block your scraper.
Some websites use CAPTCHA to ensure that the person entering the site is human. You can solve a CAPTCHA automatically with various online tools, but always use them ethically. If a platform is overused or misused, it can break the site rules and possibly lead to legal or account access complications.
With web scraping, it becomes easier to gather data from online sources that can give you a leading edge in the modern digital market. The use of web scraping helps businesses to refine web content, make more informed decisions, track changes in the market, watch competitors, and advance with data-supported action plans.
As so much data is gathered on the internet all the time, web scraping has become essential for a variety of industries and positions. While discovering its possibilities, be sure to learn about its basics, adhere to ethical laws, and follow best practices. If used effectively, web scraping plays a big role in data-driven businesses by providing information to guide new ideas and improve decisions.