Because of the increasing quest for more data in every niche and industry, we have seen web scraping grow in importance.

It provides the safest and fastest route to gathering data in large quantities and automatically. And for several years, we have witnessed developers bring in one programming language after the other to make better web scrapers.

In today’s brief article, we will describe what web scraping is and explain 5 most common languages used for building the best web scrapers.

What is Web Scraping?

Web scraping is the act and process used to collect publicly available data in large quantities automatically.

It involves several activities that include navigating to the data sources, interacting with their content and quickly collecting them before parsing and storing them in a structured format.

The extracted data can then be analyzed and used to create business and price intelligence, monitor the market and competition, generate leads, or even learn insights from a new market.

Web scraping can be as simple as copying data from a single webpage or as complex as extracting specific datasets from millions of websites simultaneously.

What is A Web Scraper?

A web scraper can be defined as the tool used for performing web scraping. They are specialized software built to help users extract huge amounts of data at once.

Some web scrapers can be built from scratch by the user and used to scrape millions of websites. While other scrapers need to be custom-made by a large corporation specializing in building tools like these.

There are advantages and disadvantages to any of these options. For instance, while it is easier to customize your scraper when you build it yourself, the actual process of building it does require expertise and knowledge, which you may not possess if you are not a developer.

On the other hand, ready-made web scrapers are more expensive and harder to customize, even though they can save you the time and money to hire experts.

How Does A Web Scraper Work?

Web scrapers work in different ways; however, their general mode of operation can be detailed as follows:

• The scraper makes an HTTP request following one or multiple URLs
• Once it reaches the target server, it interacts with the content to understand what is contained,
• Then it reaches the HTML files and extracts the relevant piece of information
• Next, the extracted data is parsed to the user and converted to some structured format before saving it as either an Excel Spreadsheet or JSON file.

5 Most Popular Languages for Web Scraping

There are so many libraries and frameworks from different programming languages that can be used to develop a web scraper.

However, below are 5 of the most common languages that people use today:

Python

Python is rumored to be the most widely used language for developing virtually any software.

This is especially so as it has several frameworks and libraries such as Beautiful Soup and Scrapy that are easy to use and work with.

Python codes are simple to write, read and understand, which makes it attractive for even the beginner developer to hop on.

Pros

• Large availability of resources, frameworks, and support
• Can be used by even the less experienced
• Simple to read and write

Cons

• The database is known to exhibit very weak protocol
• Python is not the fastest programming language in the market today

PHP

PHP is a back-end programming language which makes it highly suitable for building web scrapers.

It allows you to use different approaches to get the target data and even allows for data transfer between different networks and protocols.

Pros

• Highly compatible with HTML and can easily extract HTML files
• It is very flexible and easy to scale up
• It offers a wide selection of database options
• Considered to be faster than the Python language

Cons

• It is an open-source language which makes it less secure
• Can easily become unstable when faced with large-scale operations

Ruby

Ruby is also a solid language for building web scrapers, especially since it has an inbuilt HTTP client, which is how standard web scrapers make scraping requests.

It also has vital libraries such as Nokogiri that can help it collect and parse HTML and XML files.

Pros

• It can be used to target and parse a specific dataset
• Known to be able to export .csv files amongst other formats
• It has one of the best selection of libraries for web scraping

Cons

• Ruby is highly complicated, especially for beginners
• Known to exhibit several limitations that can frustrate the user

JavaScript

JavaScript can be easily used for both crawling and scraping, and once it is combined with Node.js, this language becomes simply unstoppable for its versatility and application in scraping the internet.

You can easily perform any web scraping task from sending out HTTP requests, parsing results and storing the extracted data in secure databases.

Pros

• JavaScript is simple to learn and use
• It is considered to be faster than the most popular programming language – Python 
• Suitable for both front-end and back-end developments

Cons

• JavaScript only offers a limited number of libraries and frameworks
• May be less efficient for large-scale operations

Golang

Golang is the newest web scraping language in town and is known to combine the best of all the popular programming languages into one place.

For instance, it is faster to use than Python and works with more third-party libraries and frameworks as opposed to the other languages.

A Golang web scraper can be used to extract data from multiple sources at once, thanks to the library known as Goroutuines.

Pros

• It is one of the fastest programming languages
• It offers static typing and run-time efficiency
• It is also stable, and a Golang web scraper can handle several scraping exercises at once

Cons

• It is less descriptive than other languages
• Requires more lines of codes to build simple scrapers

Conclusion

Thanks to the abundance of programming languages in the market, brands are no longer limited to using only one language to build their customized web scraper.

While the best 5 languages are listed and explained above, it is often advisable to progress from the known into the unknown.

Continue Reading:

Introduction to JSON (JavaScript Object Notation)

Introduction to Python OS Module

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IPWITHEASE

IPwithease is aimed at sharing knowledge across varied domains like Network, Security, Virtualization, Software, Wireless, etc.