Top 5 Coding Languages for Web Scraping

by Admira Keric
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Web scraping is arguably one of the best methods for obtaining information from other online sites. When it comes to web scraping, you have two options. Either use a program developed by someone else or create a script specifically for your organization. In both cases, the scraper software helps you visit websites quickly and gather the information required to conduct an industry-level analysis.

The first step you’ve got to follow while writing your own is selecting a suitable and optimal programming language. This article presents the five most popular web scraping languages in 2022 to help you choose the best language for your pursuit.

Programming Languages to Use for Web Scrapers



Although you can design web scraping programs using a variety of languages available, only some of them exhibit undisputedly excellent performance. This section lists the top five languages used for web scraping. ‌


Python is a popular open-source programing language that powers thousands of software worldwide. Besides being a solid general-purpose language, Python has excellent scripting capabilities, making it great for creating tools and applications like web scrapers. A universal language such as Python provides support for numerous libraries and frameworks for multiple purposes. If you own a team of experienced developers or have outsourced your company’s coding needs, getting started with a python web scraper can actually be easier than you think.

An in-depth framework called Scrapy, specially designed for web scraping, allows you to save time writing your scraper from scratch. You can easily get your hands on the Scrapy web crawling python library and build your first scraper program in less than an hour.


P‌HP is one of the earliest languages used to build reliable web scrapers. PHP powers a large number of online sites. Therefore, when thinking of coding language for web scraping, PHP invariably comes to mind.

PHP is incredibly fast and has robust support for various use cases. If your in-house team is familiar with the language, you can start scrapping websites written in PHP using PHP scrapers. This approach will provide excellent compatibility and help you establish synergy as both software use the same programing language.‌ For beginners, however, PHP can be a little complicated to implement, which brings us to our third programing language.


If any scripting language comes close to the performance of Python, it is Ruby. Ruby is an open-source programing language that is especially easy to learn and implement. Within the Ruby ecosystem, you can combine other languages, such as Perl, Smalltalk, and Eiffel, to accomplish more specific tasks effortlessly. Incorporating Ruby’s functional programming brings astounding capabilities, as your web scraper can scrape huge amounts of data without requiring intricate coding.

Other features like multi-threading and HTML-CSS selector search can boost your scraping to a great extent. Among the drawbacks, your scraper may not be as fast as C++ or Python.


C‌++ is one of the most flexible and powerful languages used globally to run systems of enormous size and scope. Using C++ for your scraper, you can parallelize your crawling and scraping activities to run multiple instances simultaneously. Your powerful scraper can accomplish most of your routine scraping tasks using programs like libcurl.

Although C++ is an easy-to-learn and excellent language for creating a web scraper, it can be very costly to implement. Also, C++ is less dynamic than Python or Ruby, so only consider it as an alternative if you have expert staff on your technical team.


Node.js is a JavaScript runtime that makes API implementation a breeze. With the support of built-in libraries, Node.js comes as a distinctive choice for creating crawlers to scrape websites and extract substantial amounts of data. Node.js extensively supports the creation of live-streaming applications. As a result, a Node.js scraper can be of great use if your web scraping project needs to be performed live. Node.js also lets you integrate APIs into your web scraper and perform socket-based activities effortlessly.

If you want something light and practical, Node.js is an excellent choice for creating a web scraper. However, it can be less stable than Python and Ruby. Although there are many advantages, the single-core structure of Node.js is not suitable for large-scale web scraping. 

Implement Your Web Scraping Program Properly

If you’re ready to develop a web scraping program, the options available to you are plenty. Depending on the requirements, you can choose between a compact Node.js program, a versatile Python solution, or a robust C++ system. Remember, any language will work, provided you use excellent proxies to support your web scraping to help you get the desired results.

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