If you are in the market looking for data extraction tools for harvesting data from websites, you have the option between developing your in-house scraper or buying one that is ready to use. At the same time, you could have a programming language background and would like to challenge yourself by going with the former.
Well, in this article, we’ll discuss the top languages for creating automated data extraction tools. Notably, an ideal language for web scraping should be flexible, easy to code for this use case, allow for maintainability, scalability, and have crawling efficiency and the operational ability to link to a database.
Of course, one factor that also goes into choosing a particular language is if you have prior knowledge of or are familiar with that coding language. It would also save plenty of time since all you need to look up are the pre-built resources for data extraction. But if you do not have any programming background and would like to start, you can select one of the languages discussed herein.
Python is considered the best programming language for web scraping. This is because of its ability to create a data extraction tool as well as the fact that it can also handle web crawling efficiently. Furthermore, a programmer has access to various Python requests libraries and frameworks, which are accommodative to beginners and seasoned programmers alike. Thus, with the libraries and frameworks, you can gain the foundational knowledge of web scraping.
Pros of Python
- It has multiple extensive requests libraries and frameworks specifically for web scraping
- It is easy to learn because it uses simple and English-like syntax
- It requires less coding/a few code lines for a function or logic that would need more lines in other languages
- It is free and open-source
Cons of Python
- It is slow
- It has limitations with regards to database access because its database access layer is somewhat underdeveloped
- It is weak when used on the client-side (browsers) and in mobile computing
Being a back-end development language, PHP is ideal for creating web scraping tools, much like Python, which is also a back-end development language. With PHP, you can take several approaches, namely using cURL, a tool for transferring data via different network protocols, or using web crawling libraries such as Goutte, Guzzle, hQuery, ReactPHP, and Buzz. Usually, these libraries contain PHP scripts for issuing HTTP requests and even utilize cURL.
Pros of PHP
- It offers excellent compatibility with HTML
- It is a flexible language
- It provides database access and has a wide selection of databases
- Has relatively fast loading speeds
Cons of PHP
- It is not secure because it is open-source, meaning that everyone can view the source code
- It is unsuitable for large applications
It entails sending an HTTP request, parsing the server’s response and extracting the requisite data, and, lastly, saving this data into a database or file, which could be a .csv or spreadsheet file. Notably, the last process can be performed using a dependency package called JSON2csv.
- It is easy to learn
- It is faster than Python
- It is usable in both front-end and back-end environments
- It supports both web scraping and crawling
- It struggles in large scale data extraction tasks
- It does not have extensive libraries, but developers can make up for this shortfall using Node Package Manager (NPM), although it also has some issues
C and C++
C and C++ provide excellent user experience both during development and upon completion of the project. They also offer outstanding performance. However, they are only suitable for creating web scraping tools but not web crawlers.
Pros of C and C++
- They offer great performance
- They provide an excellent user experience
Cons of C and C++
- They are unsuitable for creating web crawlers
- They increase the cost of developing web scrapers
Ruby standard library has an inbuilt HTTP client, which is a prerequisite to any web scraping effort. Once a server provides the HTTP response, Ruby relies on Nokogiri, a parsing gem that allows a developer to work with HTML or XML while using Ruby. It parses the HTML and retrieves the requisite data. Ruby also has a gem for exporting data as a .csv file.
Pros of Ruby
- It features multiple gems within its standard library to aid in web scraping.
Cons of Ruby
- It is a complicated language for web scraping because of its limitations and potential for frustrating the developer.
Although these languages have unique features and functionalities, they can all be used to create web scraping tools.