7 Best Programming Languages for Web Scraping

March 31, 2023 · 9 min read

Adopting the best language for web scraping makes a difference in development time and performance. At the same time, opting for the right technology can be challenging.

So which one should you use? After surveying 374 experienced web scraping developers, we got an answer! Keep reading to find out.

Top 7 Programming Languages for Web Scraping

Any process gets easier with the right tools, so we selected the seven best web scraping languages.

1. Python

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Python is a versatile, easy-to-learn, and scalable programming language. That makes it a great choice for web scraping for both beginner and advanced developers.

It comes with a vast collection of libraries for retrieving data from web pages, with BeautifulSoup and Scrapy as two of the most popular examples. With them, retrieving data from websites and analyzing HTML is effortless.

Key Highlights:

  • Quick to learn and easy to use and read.
  • Dynamically-typed language with a simple syntax.
  • Supported by a large community of developers.
  • A great ecosystem with tons of libraries.
  • Many powerful libraries for web scraping (BeautifulSoup, Requests, Scrapy).
  • Slower than Node.js and Go.

Check out our definitive guide on web scraping with Python!

2. Node.js

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Node.js is a powerful JavaScript-based language supported by a wide community. Its characteristic non-blocking I/O model allows you to handle large volumes of data and is the perfect tool to build fast and scalable web scrapers.

Also, it supports some of the most popular libraries to scrape dynamic web pages, including Playwright and Puppeteer.

Key Highlights:

  • Server-side language based on JavaScript, the most used programming language.
  • Fast and efficient thanks to its non-blocking I/O architecture.
  • It has one of the largest and most active communities in the programming world.
  • Multiple useful libraries for web scraping, like Cheerio and Axios.
  • Libraries for dynamic scraping, most notably Selenium, Puppeteer, and Playwright.
  • It can't open several threads and run in parallel on many CPUs like Java.

Learn more about it in our web scraping in JavaScript and Node.js guide! It's one of the best languages for web scraping.

3. Java

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Java is a platform-independence language known for its stability and multithreading capabilities. Its robustness and widespread adoption make it a reliable choice for web scraping, which is especially true thanks to libraries such as jsoup and Selenium.

Key Highlights:

  • Strongly typed, object-oriented programming language.
  • Stable and secure.
  • Advanced multithreading capabilities.
  • Supports web scraping via some libraries, like jsoup and HTMLUnit.
  • Cross-platform compatibility via the JVM (Java Virtual Machine).
  • Slower and more resource-greedy than Go and Node.js.

Uncover more in our complete tutorial on web scraping in Java!

4. PHP

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PHP is a server-side programming language used for web development. It's popular because most web servers can run it and can easily integrate with databases. PHP is great for scraping due to its scripting capabilities and support for scraping techniques like proxy setup in HTTP clients like Guzzle.

Key Highlights:

  • Dynamically typed, server-side scripting language.
  • Several back-end frameworks, like Laravel, Symfony, CodeIgniter, and Zend Framework.
  • Native HTML parsing capabilities.
  • Web scraping libraries, such as Goutte, and Simple HTML DOM Parser.
  • Less intuitive syntax compared to Python.
  • Limited parallel programming capabilities compared to Java and Go.

Learn further in our step-by-step tutorial on web scraping with PHP!

5. Ruby

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Ruby is a language with a concise and readable syntax. Its object-oriented nature and focus on productivity make it a powerful option for many tasks. Furthermore, libraries like Nokogiri and Mechanize turn scraping into an easy process.

Key Highlights:

  • Interpreted language with clear, concise, and elegant syntax.
  • Several gems Ruby libraries) and web frameworks (Ruby on Rails, Sinatra, Hanami).
  • Powerful web scraping libraries are available, like Nokogiri and Watir.
  • It supports multithreading and parallel processing.
  • Slower than Node.js, PHP, and Go.
  • Less popular than Python and Node.js.

Dig deeper into web scraping in Ruby! It's known as one of the best programming languages for web scraping.

6. R

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R is a language widely used in data science and machine learning, and can be used for web scraping. It's well-known for its statistical analysis capabilities and visualization tools, which come in handy to analyze and explore the data retrieved from the web.

Key Highlights:

  • Mainly used for research and data science.
  • Great for statistical analysis and machine learning.
  • A vast package collection for data manipulation, modeling, and visualization (ggplot2, dplyr, tidyr).
  • It supports multithreading.
  • Niche language compared to Java, Python, Node.js, Go, and PHP.
  • Fewer libraries for web scraping than Python and Java.

Find out more in our web scraping in R guide!

7. Go

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Go is a high-performance language developed by Google. It's designed for concurrency and comes with useful libraries. One example is Colly, a popular web crawling tool.

Go is an excellent option for building fast and efficient web crawlers.

Key Highlights:

  • Designed for building scalable and concurrent systems.
  • Efficient and fast, with advanced garbage collection and memory safety features.
  • Rich standard library with several built-in functions.
  • Strong support for concurrency and parallelism.
  • Only a few web scraping libraries, like Colly.
  • Less popular for web development than Node.js.

Get more information in our Go web scraping tutorial!

What Is the Best Programming Language for Web Scraping?

The answer depends on what matters to you. Each language has different characteristics, so let's find out which is the best in the criteria under analysis.

Python has an intuitive syntax, allowing beginners to start with it immediately. No matter your experience in web scraping, you'll find it practical and easy to use. That's Python's magic!

Also, don't forget that its ecosystem is incredibly vast. There's a library for everything, including web scraping, crawling, and data parsing. That makes Python the most popular language for web scraping.

Fastest Web Scraping: Go and Node.js

Go and Node.js are two programming languages built with performance in mind. Both have a non-blocking nature, which makes them fast and scalable. Plus, they can perform asynchronous tasks thanks to the async/await built-in instructions.

Google designed Go to be efficient, making it the fastest option for web scraping.

Best for Dynamic Scraping: Node.js

Dynamic websites rely on JavaScript to retrieve data via AJAX so that content can change without a reload. Since only browsers can run JavaScript, you need one to scrape dynamic sites.

Node.js comes with most headless browser libraries for scraping, some of the most popular ones being Playwright, Selenium, and Puppeteer. That makes Node.js one of the best programming languages for dynamic web scraping.

Keep in mind that Python comes with headless browser libraries, too. To learn more, check out our guide on scraping dynamic web pages with Python.

Importance of Libraries for Any Language

Libraries play a crucial role in web scraping, regardless of the programming language. A good language should offer a wide range of options for building a data spider to streamline the web data extraction process.

Yet, most of these libraries can't do much against the main challenge: getting blocked while web scraping.

Anti-scraping technologies often monitor the activity on a site and, when they detect a bot or anomalies in the traffic coming from a specific IP address, they block it.

That presents a major obstacle for web scrapers. Thus, you need an advanced solution that works with any web scraping programming language, such as ZenRows. With it, you can scrape data via simple API calls and get around all anti-bot measures.


In this article, you saw a comparison of the seven best languages for web scraping. Let's take a look at the summary table below:

Language Easy to Learn Fast Well Documented Popular Dynamic Scraping Ecosystem
Python - Some libraries ~500k libraries, 15M+ developers
Node.js Many libraries ~1.5M libraries, 9.5M+ developers
Java - Some libraries 10M+ libraries, 10M+ developers
PHP - - A few libraries 300k+ libraries, 5M+ developers
Ruby - - - Few libraries ~150k libraries, 1M+ developers
R - - - - A very few libraries ~150k libraries, 1M+ developers
Go A few libraries Thousands of libraries, 1M+ developers

As you can see, Python is the best language for web scraping, followed by Node.js. In both cases, their popularity and ecosystem make them the preferred choice for developers. Furthermore, you can use them to retrieve web data for the following purposes:

  • Market research.
  • E-commerce price comparison.
  • SERP and SEO optimization.
  • Social media marketing.
  • Financial analysis.
  • Many other use cases.

No matter what language you use, extracting data from the web is challenging because more and more websites have adopted anti-scraping technologies. Fortunately, you can forget all about these obstacles with an advanced web scraping API like ZenRows. Get your free API key now!

Frequent Questions

Which Language Is Best for a Web Scraper?

Python is widely considered to be the best programming language for web scraping. That's because it has a vast collection of libraries and tools for the job, including BeautifulSoup and Scrapy. Also, Python's simple syntax makes it a great choice for beginners.

What Are the Best Languages for Web Scraping?

The best languages for web scraping are:

  1. Python: It comes with many web scraping libraries for both dynamic and static web pages.
  2. Node.js: It's the server-side version of JavaScript and the most used language on the planet.
  3. Java: The oldest and most stable programming language for data scraping.
  4. PHP: One of the most adopted languages in back-end web development. Its scripting nature makes it perfect for building a web spider.
  5. Ruby: An emerging programming language with a growing community and thousands of libraries.
  6. R: A data science language with advanced data visualization and manipulation tools. Perfect to process the scraped data.
  7. Go: The fastest and most efficient language on the list. Great for building fast web scrapers.

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