What Is the Best Programming Language for Web Scraping?

Data has proven to be an asset for companies – a way to stay ahead of the competition and create additional revenue. With these benefits already imparted in everyone’s minds, the popularity of web scraping is increasing day by day. Today, companies use web scraping tools to obtain data for various reasons, including price monitoring, price intelligence, news tracking, lead generation, etc.

In this post, we’ll shed some light on web scrapers and the five most popular programming languages to use for building a web scraper. 

What is a Web Scraper

Web scraping is a technique used to obtain a large amount of data from websites for various uses. A web scraper like is a specialized tool built to accurately and quickly extract content and data from a web page. Different kinds of web scrapers are available, with capabilities that can be customized to suit various extraction projects.

How It Works

A web scraper makes HTTP requests to a target website and obtains data from the webpage. Sometimes, it also requests internal APIs for some associated data stored in the database and delivered to a browser via HTTP requests. Lastly, these tools will run and allow users to download data in different formats. Web scrapers can be extensive frameworks designed for different kinds of scraping tasks, but you can also use general-purpose programming libraries and join them to build a scraper.

Five Most Popular Languages to Build a Web Scraper

Thanks to the recent emergence of AI developments, it is now possible to increase your scraping efforts by picking the latest coding language. Here are the five most popular languages you can use to build a web scraper:


Python tops our list of the most popular programming languages for web scraping. Using Python, web scrapers can be built to access resources on the Internet. It is an all-rounded solution that smoothly handles web scraping processes. Find more info about Python web scraping here. 


  • Free and open-source
  • Easy to understand because it uses simple syntax
  • Multiple extensive request libraries and frameworks, such as BeautifulSoup, Scrapy, Flask, and Selenium, especially for web scraping. You can easily hire Flask developers offshore.
  • A huge community of programmers


  • Slow speed
  • Too many options for data visualization
  • Restrictions on the database access layer that establishes communication between database and back-end service


JavaScript is another popular programming language designed to make websites more dynamic. With the Node.js environment, JavaScript is used more for developing web applications. Node.js offers multiple libraries, like Nightmare and Puppeteer, commonly used for web scraping.


  • Easy to learn
  • The fastest option for web scraping
  • Suitable for streaming, socket-based, and API implementations
  • Offers built-in libraries to handle tasks like website crawl and data extraction
  • Makes the web scraping journey lightweight and efficient


  • Not easy to understand for entry-level programmers
  • Not as powerful as other languages for CPU-intensive tasks
  • Unsuitable for large-scale projects


Golang (Go) is the fastest high-level language ever created. It is a statically-typed language, which could be necessary for coding fast, efficient, and scalable web scrapers. Since Go rarely needs any third-party packages to manage communication with web servers, it is a great choice for web scraping.


  • Offers built-in concurrency, memory safety, and high usability
  • Provides many frameworks to create web scrapers, such as Colly, Ferret, Gocrawl, etc.
  • Supports garbage collection and high-performance networking
  • Comparatively faster than the well-optimized Python framework
  • Gentle learning curve


  • No support for generic functions
  • Poor error handling
  • Dependency management is hard


Ruby is the most sought-after programming language used to write scripts as a part of front- and back-end web development. The language is another excellent choice for web scraping. It is packed with different parts of languages, including Smalltalk, Perl, Eiffel, Lisp, etc., and maintains the balance of functional programming using imperative programming.


  • Easy-to-follow syntax
  • Fewer lines of code
  • Uses NokoGiri, an HTML, Sax, Reader, and XML parser
  • Supports multi-threading
  • The Ruby Bundler makes the management and deployment of packages from GitHub easier, saving time for projects that needs an existing package


  • Relatively slower than other languages
  • No company support
  • Leads to problems if you need an in-depth solution


C# is a popular back-end programming language used to develop web- and console-based applications. The language also provides options for web scraping. It supports multiple modes of data extraction and has the additional capability of fetching various sites at one time.


  • General-purpose programming language
  • Offers libraries and packages, including ScrapySharp for web scraping
  • No complex features
  • Automatic memory management


  • It is not dynamic
  • Implementation can be costly

Final Words

Now that you are well aware of all popular programming languages, including Python, a web scraper can be built using the most appropriate language. The creation of a good web scraping tool is as important as scraping data for your big data project. So, it is recommended to choose wisely.

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