Languages for Competitive Programming

Languages for Competitive Programming

5 min readApr 26, 2022


Competitive Programming is a crucial and lucrative component of a programmer’s journey.

And learning a new programming language from the ground up to mastering it at a competitive level to code specific functionalities with maximum efficiency and minimal complexity.

All of this is possible if the right programming language is used. And to make that decision, one must be familiar with the available languages and their distinct set of functionalities.

Choosing the right language is the most pivotal part of your competitive programming journey. The right programming language will provide extensive functionality and multiple approaches to any given problem for a competitive coder.

But the language plays only a small role in Competitive coding, with no language being better than others, and it all depends on your comfort with the language.

Python -

Python has several reasons to be chosen as it is one of the top programming languages for a coding competition.

This high-level programming language is relatively easier to learn and use. All thanks to its simple syntax.

This language has an extensive library and function support, which increases programmers’ efficiency in programming competitions.

Aside from that, the language has some cool features like no integer value limit, functions that can return more than one value, solid input statements, code indentation, a flexible number of arguments to a function, and so on.

A python is a viable option for a competitive programming language for the reasons stated above.

Though some cons of using python for CP are longer execution time and limited control over memory, two of the most important aspects to keep in mind during competitive programming

Java -

For competitive coding, JAVA is one of the most recommended programming languages. The concept of an object-oriented language implies that compiled JAVA code is platform-independent and does not require recompilation during run-time.

JAVA comes with an extensive library set, including the BigInteger class for calculating large integers and the Geometry Library for dealing with geometrical problems. It also introduced better exception handling, JAVA containers, and other features that helped JAVA become one of the most popular competitive programming languages. It is also easier to learn and apply.


C++ is a popular, highly recommended, and widely-used programming language for competitive coding. It is one of the fastest programming languages when compared to other competing programming languages.

C++ is the most preferred language for competitive programming mainly because of its STL.

Because execution time is so important in coding competitions, C++ is one of the most popular languages among coders. C++ has a large library known as the Standard Template Library, which makes it much easier for programmers to write code in this general-purpose programming language. The STL is responsible for the speed with which C++ code is written. STL saves you a lot of coding time by providing basic data structures and functions as templates.

The Standard Template Library includes C++ template classes that provide access to various data structures such as arrays, graphs, lists, trees, stacks, queues, and so on. C++ is supported by OOPS paradigm features that aid in the solution of real-world problems in coding competitions.


In the competitive programming world, Ruby is a popular programming language. It is a user-friendly object-oriented programming language that is flexible and easy to learn.

However, it is a dynamic programming language with roots in other programming languages such as Perl, Lisp, Ada, Eiffel, and Smalltalk.

Although Ruby is an interpreted scripting language, it is slower than other compiled languages, giving other languages the advantage over Ruby when it comes to the best competitive programming language.


Kotlin is a programming language that supports the object-oriented paradigm. The language is simple to learn and provides access to a large library containing various data structures, collections, etc.

While programming in Kotlin, you can also use existing JAVA Frameworks and Libraries. It has some useful features, such as smart casts and type inference, and it avoids the Null Pointer Exception.

This language emphasises readable syntax, making it easier to review and effectively learn and understand the language.


Go, also known as Golang, is a programming language created by Google. This language has excellent multithreading support, and as a result, many businesses rely heavily on distributed systems.

Go is also a popular programming language in Silicon Valley start-ups. Go has a simpler syntax, making it easier to learn. It also compiles machine code very quickly.

It includes a large standard library with a variety of built-in functions for working with primitive types.


R is a programming language that is widely used in data analysis and machine learning applications. R offers an excellent framework and built-in libraries for developing powerful Machine Learning algorithms applications. It offers a complete statistical analysis language.

However, compared to the other languages mentioned here, R has a moderate learning curve and is not particularly easy for beginners to pick up and learn at first.

However, because R is an open-source language, it has an active developer community that can guide you through various projects and teach you new coding skills along the way.


Applications for the frontend NodeJS is a JavaScript-based run-time environment that allows developers to use it for server-side scripting.

This language provides both server-side and client-side scripting capabilities. It is also a highly adaptable language that receives regular updates. Because of its scripting capabilities, many developers use JavaScript to create a wide range of desktop applications.


These were the top programming languages for competitive coding. However, to do well in the competitive programming domain, it is necessary to focus more on Algorithm building and Data Structures in addition to choosing a relevant and worthwhile programming language. Good Luck for your future endeavours. Do visit the official website of AlgoZenith if you wish to master Data Structure and Algorithms for your future Internship/Job tests.

Do let us know in the comments if you liked the content. Also, do check out our blog series on Finance and Product Management. Do check this blog if you are searching for an Ultimate guide for your Job/ Internship. Stay tuned for more such blogs. You can also check out the previous blogs of this series on Everything about Data Science, What is Machine Learning and How to approach a Data Science project for a beginner. Keep Learning, Keep shining.