There are people on the internet who use it for its intended purpose i.e. gaining information. So, there are countless websites and pages on the internet that have their information and data. These data and information are all in different formats, that varies from websites to websites. These information are an important part of the organizations they belong to. They need those for various applications. Be it Comparisons of quantities, gathering email addresses, research and development or collecting social media data. For said acquisition of data and information, we’d need something to extract these data from them. That’s where Web Scraping comes in.
What is Web Scraping?
Without Web Scraping one would have to go to each website individually and manually get the data in whatever format they’re in, on the website. What a Web Scraper does is extract these data from the websites and export the collected data in a usable format for the users. How this works is the Web Scraper gets and loads the entire HTML code of a page through the URLs given to it. Then it extracts the data from the page. Finally, the data is recorded in a format suitable for usage by the user. Now, some pages allow scraping while some don’t. to find out by appending “/robot.txt” to the URL that you want to scrape. But how do we go about programming this web scraper?
Python in Web Scraping
Now Python is a popular programming language and platform for Web Scraping or just web applications in general. It has its set of advantages that makes it so popular in the field. But scraping from the web also requires a few libraries. There are quite a few libraries for the work but only a handful of those have been used and proven to work on a wide range of sites. The most used of those libraries include the following.
Requests Python
The Request is the standard library for Python for making HTTP requests. It’s the most basic library for this work. It helps the user request the website’s server to retrieve the data from an HTML page. This library uses simple instructions and a key to send requests.
Its simplicity has made it be dubbed the HTTP for humans.
Selenium
Selenium is an open sourced web based library that was originally made for automated testing of web applications. While most other scrapers are capable of scraping through static pages, there are pages where the data are loaded through the use of JavaScript. But because Selenium is designed to render web pages, it can scrape through these dynamically populated web-pages. The library load and runs JavaScript on every page making the process bit slower and because of it is not suitable when dealing with large scale projects.
LXML
The LXML is the HTML(and XML) parsing library. It is a high performance, production quality library preferred for its speed. It is feature-rich and quite simple to use. This library processes the codes written for HTML and XML to python codes. This library combines the speed and computing power of the Element tree and works better when working with a larger dataset.
Beautiful Soup
The Beautiful Soup is another parsing library for HTML and XML files. While LXML is preferred for its speed, the Beautiful Soup is preferred when handling messy, poorly designed HTML documents. It can use different parsers. The default one comes from Python’s standard library, which makes it flexible and a bit slow. However, as stated, the parser can be swapped out. This library can detect encoding automatically, thus allowing a more agile approach while handling HTML documents containing special characters. It also has easy access to navigation, searching, and modification of the parsed documents.
This library is comparatively easier to work with and thus well suited for beginners.
Scrapy
Scrapy is another open-sourced web-based library that extracts data from a website that the user needs. It’s a high-level scraping and crawling library used for various purposes, including data mining, monitoring, and automating testing.
Scrapy is not just a library; it works as a web scraping framework that does all the work required for web scraping. It provides a spider that crawls through the webpage to extract data from them systematically. These spiders are user-defined classes, and through these spiders, the user scrapes through the website(s) for data. The JavaScript part that it can’t handle can collaborate with libraries like the Selenium, mentioned above, like plugins and continue the task efficiently.