Numerous people rely on World Wide Web resources to extract data to create perfect data visualizations. As everyone in one way or another is linked to the Internet, so you are not at all independent in this race. Before extracting data you must set some rules for your data project i.e. which language the data is going to be scrapped?

 

The easiest way to select a programming language to crawl the web is to look into the type of data that you want to extract in the first place. Many popular programming languages come at the top spot. However, no individual can claim which language is the better option for a given data project. A wrong choice can leave you spending so much time and energy on something which will not yield desired results. Hence, it is important to carefully select a particular language for a specific data project. Each language comes with its significant features and limitations. It strongly depends upon project type to put up with a language to crawl data efficiently.

 

 

In this blog, we are to discuss all popular programming languages which can be used to crawl the Internet. All languages are distinguished based upon their features, so let us have a closer look at them:

 

Python

 

To top our list of the best programming languages for web scraping we have Python. Python is the number one web scraping programming language known today. It is a complete all-in-one platform where you can conduct data extraction smoothly.

 

 

Features:

 

Python is a commonly used language for web scraping. Beautiful Soup and Scrapy are supportive frameworks based on Python which further enables easy web scraping than any other platform.

Python library is specially designed to provide fast and professional quality data.

Scrapy includes features like enhanced performance with a twisted library, support XPath, and a variety of other debugged tools.

Pythonic idioms are used for modification, search and navigation results of a parse tree.

Beautiful Soup framework is convertible from documents to UFT-8 and Unicode.

 

2. Node.JS

 

Node.JS is a well-known programming language for web scraping because it employs the use of dynamic coding practices. The framework also supports distributed crawling, data extraction for larger-scale projects, and stable communication. Furthermore, Node.JS utilizes JavaScript events to counter non-blocking I/O applications which can benefit other data projects as well.

 

 

Features

 

Node.JS is suitable and fully recommended to be used for streaming, socket-based implementation, and API.

Many people use Node.JS for multiple instances for the same scraping project as Node.JS takes only one core of the Central Processing Unit (CPU).

 

Built-in Library

 

ExpressJS: It is a flexible and minimal Node.JS web framework, which is compatible with mobile and web-based applications.

Request: It helps in making HTTP calls.

Request-promise: It allows the easy and quick making of HTTP calls to the server.

Cheerio: With its help implementation of jQuery core is made simple for the server.

 

Limitations

 

The programming language is not termed suitable for larger-scale data incentives.

It lacks the maturity and stability for big data projects.

T is not ideal for running long data processes.

 

Ruby

 

Ruby is one of the most cherished open-source programming languages. It is widely used because of its simplicity and productive nature as compared to other programming languages. Ruby maintains the functional balance of programming with aid of imperative programming. Ruby on Rails enables us to write less code and avoids any type of repetition. It is a favorable framework to write a simple code.

 

Features

 

Pry, HTTParty, NokoGiri allows easy set up of the web scraper without much effort.

NokoGir is a Rubygem as it provides XML, HTML, Reader, and SAX parsers with CSS selector support.

Pry allows debugging programs for easier data extraction across the websites.

HTTParty is a type of gem which allows the transfer of HTTP request to the web pages from which you intend to extract data. Hence, it is a good path to accomplish furnished HTML of the web pages in the form of a string.

 

Limitations

 

Ruby Programming Language is backed by hundreds of community users in place of any particular company.

The language is a bit slower in comparison with other programming languages discussed in this blog.

 

4. PHP

 

PHP is considered the programming language within this list for best web-scraping programming languages. This is because of the weak support for async and multi-threading. The task queuing and scheduling issues can be related to PHP language while web crawling for acquiring desired data. However, with the help of cURL, you can extract videos, graphics, and photographs from numerous websites. cURL can efficiently transfer files with an extensive list of protocols involving FTP and HTTP. This enables us to directly create a web crawler with is as effective to download automatically data from the web.

 

 

Limitations

 

The programming language is not considered suitable for big data projects as it supports week async and multi-threading. There can arise many issues in tasks such as queuing and task scheduling.

 

5. C & C++

 

C & C++ provides the best output for constructing a unique web scraping setup. But the cost is a bit higher. Therefore, it is recommended to use a creative web crawler with C or C++ language.

 

 

Features

 

It is quite easy to understand as it supports a simple user interface.

It becomes efficient to parallelize the scraper via the C++ programming language.

 

Limitations

 

C++ programming language is the first choice of any professional web-related data project. This is because web scraping can be achieved using any dynamic language.

The language is not perfect for creating web crawlers.

It is quite costly and should be considered the last option for smaller-scale data projects.

 

Conclusion

 

Now that you are well aware of all popular programming languages including their pros and cons, you can select the most appropriate programming language by comparing the two shades for web scraping. It is equally important to keep in mind all the drawbacks of each language before opting for a particular language. The creation of a good bot is as much important as scraping data for your big data projects, it is recommended to choose wisely!

 

How ITS Can Help You With Web Scraping Service?

 

Information Transformation Service (ITS) includes a variety of Professional Web Scraping Services catered by experienced crew members and Technical Software. ITS is an ISO-Certified company that addresses all of your big and reliable data concerns. For the record, ITS served millions of established and struggling businesses making them achieve their mark at the most affordable price tag. Not only this, we customize special service packages that are work upon your concerns highlighting all your database requirements. At ITS, our customer is the prestigious asset that we reward with a unique state-of-the-art service package. If you are interested in ITS Web Scraping Services, you can ask for a free quote!