Data is proving to be an asset for companies – a way to stay ahead of the competition and generate additional revenue. With these benefits already imparted in executives’ and individuals’ minds, the popularity of web scraping solutions is growing by the day.

What is Web Scraping?

Also known as web data harvesting or web data extraction, web scraping involves using automated software (bots) to extract publicly available data from websites. And as detailed, these bots can be acquired off the shelf or created from scratch. Companies that opt for the latter approach can choose among the top 5 programming languages suited for building a web scraper.

Top 5 Programming Languages for Building Web Scrapers in 2022

The top 5 most popular programming languages for web scraping are:

  1. Python
  2. JavaScript/NodeJS
  3. C++
  4. Ruby
  5. Golang

1. Python

Python is the most popular programming language overall. It is also the best suited for creating web scrapers. Python’s popularity in web scraping is based on the fact that it is easy to use and understand. It also has a wide assortment of web scraping libraries, including requests, lxml, Selenium, Scrapy, and BeautifulSoup.

The advantages of Python:

  • Extensive pool of resources, including libraries and frameworks;
  • It is easy to use and understand;
  • Some of its frameworks, namely Scrapy, are well optimized to improve scraping performance.

The disadvantages of Python:

  • Python is slow;
  • It has a database access problem, which adds an unnecessary step in the coding process as the developer must include additional lines of code to accommodate this deficiency.

2. JavaScript/NodeJS

JavaScript is the second most popular programming language overall. It is a simple language designed to make websites more dynamic. On the other hand, NodeJS is an environment that enables applications written in JavaScript to run on web servers. NodeJS has several libraries that improve JavaScript’s functionality and features. Using the NodeJS framework, you can create web scraping projects.

Advantages of NodeJS:

  • It has several built-in libraries;
  • NodeJS is not resource-intensive as a NodeJS project only utilizes a single CPU core;
  • There is a large community of JavaScript and NodeJS users;
  • It can efficiently handle multiple simultaneous webpage queries and requests.

Disadvantages of NodeJS:

  • NodeJS does not offer the stability needed for big data applications;
  • As it is not resource-intensive, it is unsuitable for tasks such as parsing large data volumes because it requires more CPU cores;
  • It may not be easy to understand for beginners.

3. C++

C++ is a general-purpose programming language used to create powerful, high-performance applications such as operating systems, games, browsers, etc.

Advantages of C++:

  • It is a simple programming language and is therefore easy to understand;
  • It can be used alongside libcurl to download URLs;
  • It does not require a web scraping library as extracting specific information from a website is relatively straightforward;
  • It supports parallel scraping.

Disadvantages of C++:

  • Building a web scraper that uses C++ is costly;
  • It is easier to create a web scraping solution or web-related applications using other languages.

4. Ruby

Ruby is a general-purpose programming language mainly used to create scripts as part of the front- and back-end web development process. It is also used for web scraping thanks to its Nokogirl library that makes parsing HTML and XML files easy.

Advantages of Ruby:

  • Ruby requires fewer lines of code to achieve a functionality that would require more lines of Python code;
  • The Nokogirl library easily resolves broken HTML code;
  • Its syntax is easy to follow and offers convenience during the writing process;
  • The HTTParty gem can be used to query web services by sending HTTP requests.

Disadvantages of Ruby:

  • It is supported by its users rather than a company;
  • It is relatively slower;
  • Ruby is generally not very efficient even though it supports multithreading.

5. Golang

Golang or Go is a programming language whose popularity has grown over the years thanks to its valuable features and capabilities. For instance, it is fast and offers built-in concurrency, memory safety, and high usability. It also supports garbage collection and high-performance networking.

Go is used to create web scrapers because of its web scraping frameworks. A developer who wishes to create a Golang web scraper can elect to use Colly, Gocrawl, Hakrawler, soup, or Ferret frameworks. Of these, the Colly framework is the most popular.

Advantages of Golang

  • Developers can choose from a number of frameworks;
  • It is fast – it is comparatively faster than the most well-optimized Python framework;
  • The Colly framework supports Robots.txt;
  • The Colly framework supports request delays and caps the maximum concurrency, thus preventing IP blocking;
  • It has a gentle learning curve.

Disadvantages of Golang:

  • Golang is unnecessarily verbose;
  • It does not support generic functions;
  • The language offers poor error handling.

If you’re interested in building a Golang web scraper, check this page for more information.


Companies that intend to build a web scraper can elect to use Python, C++, JavaScript/NodeJS, Ruby, or Golang programming languages. These languages offer comprehensive resources, which make them easy to use. They also have frameworks that reduce the work needed to build the web scraper. A Golang web scraper can, for instance, be built using the Colly framework.