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In this data-driven world, you need to be constantly vigilant, as information and key data for an organization keep changing all the while. If you get the right data at the right time in an efficient manner, you can stay ahead of the competition. Hence, website scraping is an essential way of getting the right data. This data is crucial for many organizations, and the scraping technique will help them keep an eye on the data and get the information that will benefit them further.
Web scraping involves both crawling the web for data and extracting the data from the page. There are several languages which programmers prefer for web scrapping, the top ones are Ruby, Python & R. Each language has its own pros and cons over the other, but if you want the best results and a smooth flow, Ruby is what you should be looking for.
Ruby is very good at production deployments and using Ruby, Redis & Chef has proven to be a great combination. String manipulation in Ruby is very easy because it is based on Perl syntax. Also, Ruby is great for analyzing web pages using one of the very powerful gems called Nokogiri. Nokogiri is much easier to use as compared to other packages and libraries used by R and Python respectively. Nokogiri can deal with broken HTML / HTML fragments easily. Ruby also has many extensions, such as Sanitize and Loofah, that can help clean up broken HTML.
Python programmers widely use a library called Beautiful Soup for pulling data out of HTML & XML files. It works with your favourite parser to provide idiomatic ways of navigating, searching, and modifying the parse tree. It commonly saves programmers hours or days of work. R programmers have a new package called rvest that makes it easy to crawl data from HTML web pages, by libraries like beautiful soup. It is designed to work with magrittr so that you can express complex operations as elegant pipelines composed of simple, easily understood pieces.
To help you understand it more effectively, below is a comprehensive infographic for the same.
Ruby is far ahead of Python & R for cloud development and deployments. The Ruby Bundler system is just great for managing and deploying packages from GitHub. Using Chef, you can start up and tear down nodes on EC2, at will, and monitor for failures, scale up or down, reset your IP addresses, etc. Ruby also has great testing frameworks like Fakeweb and Capybara, making it almost trivial to build a great suite of unit tests and to include advanced features, like web crawling and scraping using webkit / selenium.
The only disadvantage to Ruby is lack of machine learning and NLP toolkits, making it much harder to emulate the capacity of a tool like a Pattern. It can still be done, however, since most of the heavy lifting can be done asynchronously using Unix tools like liblinear or vowpal wabbit.
Each language has its plus point and you can pick the one which you are most comfortable with. But if you are looking for smooth web scraping experience, then Ruby scraper is the best option. That has been our choice too for years at PromptCloud for the best web scraping results. If you have any further questions about this, then feel free to get in touch with us.
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