Web scraping, or web data extraction, is the process of extracting publicly available web data using automated tools – web scrapers. This information is usually returned in a structured format and used for repurposing or analysis. Businesses use this data to build new solutions like apps and websites or make better decisions based on patterns and insights from the collected data.
What is a Web Scraping Tool?
Web scraping tools or web scrapers are software solutions designed specifically to access, scrape and organize hundreds, thousands, or even millions of data points from websites and APIs, and export the data into a useful format – typically a CSV or JSON file.
A Simple Example
Let’s say that you want to create a Twitter bot that publishes quotes from humanity’s greatest minds. You could definitely read a lot of books and manually create a database with all the quotes your bot will use, or better yet, you can scrape all the phrases from different websites and automate the whole process.
For this scenario, we’ll build a simple scraper that extracts the quotes from the first page of
https://quotes.toscrape.com/ using Python and Beautiful Soup:
import requests from bs4 import BeautifulSoup url = 'https://quotes.toscrape.com/' response = requests.get(url) soup = BeautifulSoup(response.content, 'html.parser') all_quotes = soup.find_all('div', class_= 'quote') for quote in all_quotes: quote_text = quote.find('span', class_= 'text').text print(quote_text)/pre>
Here’s the result after running this script:
- Understand how web scraping works in simple words
- Is scraping legal? Learn the legal implications of extracting data from the web
- Discover the most common applications for web scraping in business and technology
- More frequently asked questions about web scraping and data extraction