You can accomplish web scraping through many methods, but many prefer Python due to its ease of use, large collection of libraries and easily understandable syntax. Web scraping is enormously valuable for data science, business intelligence and investigative reporting. Popular Python libraries used for web scraping include Beautiful Soup and Selenium.
What Is Python Web Scraping Used For?
Is Python Good for Web Scraping?
Yes. There are many tools you can use for web scraping, including APIs and online services, but Python is one of the most efficient methods for many reasons. Using a Python library like Beautiful Soup or Scrapy to read and collect web data from HTML or XML is possible with just a few lines of code. Python’s understandable syntax and simple code make it easy to write and review web scraping scripts. Perhaps most importantly, Python’s code is compact, meaning you’ll never spend more time writing code than you otherwise would by manually searching for data.
We use web scraping to parse HTML and XML, while also automating the retrieval of large volumes of data from websites. Web scraping can be an invaluable process for acquiring volumes of data from multiple sources and arranging them to be stored in relational databases like MySQL or NoSQL databases like MongoDB.
How Does Web Scraping Work?
To begin the web scraping process, you’ll first load URLs into a web scraping tool, such as Python. The tool will then crawl and extract data from the URL. You can then parse the returned, structured data using string methods, regular expressions, HTML and additional methods. You’d use HTML if you’re interested in data between certain HTML tags in the website’s structure. For example, if you wanted to collect all the links from a website, a web scraping tool could be set to look for “href” tags.
Is Web Scraping Legal?
Web scraping in itself is completely legal, though websites can set specific rules regarding the practice on its domain.
While web scraping is not explicitly outlawed, aside from specific terms-of-service violations, some websites choose not to allow the practice on their platform or may have specific rules dictating how scraping and crawling may be done. These rules are generally laid out in a site’s “robots.txt” file, which explains how and which kinds of bots may crawl and scrape the site. It’s important to understand how to safely use scraped data if it’s protected by copyright. For example, while scraping data is legal, displaying that data for commercial use might not be.
Frequently Asked Questions
What is Python web scraping?
Python web scraping is the automated process of collecting large amounts of data from websites and storing it in a structured form.
What are common uses of web scraping?
It can be used for comparing financial reports, gathering email addresses, conducting research, price comparison and finding job listings.
Which Python libraries are popular for web scraping?
Beautiful Soup and Selenium are widely used, offering tools to parse HTML and automate browsing.
How does the web scraping process work?
A script loads URLs, crawls and extracts website data, and parses it using methods like regular expressions or HTML tags such as “href.”
