The best languages for Competitive Programming



If you’re here, chances are you’ve just set your foot in the world of competitive programming. A few google searches here and there must’ve confused the hell out of you on what language to use, and now you’re in search of a comprehensive guide on the same.

Don’t worry, we feel you!

But, before we proceed further, let’s clarify that language plays only a little role in competitive programming. So, we cannot claim that one language trumps the others. It’s all about your comfort and your understanding of various languages.  

Having said that, if you’re still a beginner in the world of competitive coding, you need to know the things associated with the most preferred programming languages. Other than that, a grassroots level knowledge of core programming concepts like various data structures, sorting and searching algorithms, Prim’s, Dijkstra’s, and more graph and trees-related algorithms, will come in extremely handy during your competitions.

Competitive programming is all about solving in the fastest time and with the minimum complexity. More often than not, even the most complicated problem you’ll encounter can be broken down into smaller chunks, and knowledge of these basics will help you solve those chunks of problems quickly and collate them to form the final solution. Having essential algorithms at your fingertips will save you a lot of time and allow you to focus on more significant problems.

Now, with so much said and done, it’s time to look at the three most preferred programming languages for competitive coding.


  • C++:

C++ is the most preferred language for competitive programming mainly because of its STL. Short for Standard Template Library, the STL is a collection of C++ templates to help programmers quickly tackle basic data structures and functions such as lists, stacks, arrays, etc. It is a library of container classes, algorithms, and iterators.

STL is what ensure speed while coding in C++. Providing the basic data structures and functions as templates, STL cuts down a lot of your coding time. The power of C++ is undebatable because not only is it built on top of C (the mother of all programming languages) but also because it provides support for OOPS along with other features helpful during coding contests. Other than that, the verbosity of C++ codes is comparatively lesser than Java which makes it easier to code in.


  • Java:

Java is another classic programming language that’s extensively used for competitive programming. The fans of Java swear by the BigInteger class which is used for performing mathematical computations on large integers quickly. It comes in extremely handy during The exception handling is again something that Java is universally applauded for. It’s challenging to find segmentation faults in C++, but it’s easy to notice the ArrayIndexOutOfBound exception.

Although Java lacks STL, it has containers which perform pretty much the same function. Although the containers in Java are not as extensive as STL in C++, there are a few situations where STL doesn’t have a direct solution. For example, in case of priority_queue in STL, it doesn’t support decrease-key operation which is required for implementations of essential algorithms like Prim’s and Dijkstra’s. Java also has extensive support for geometrical problems. Its jawa.awt.geom package includes stuff like line-line/segment-segment intersection and polygon segment intersection. It comes in extremely helpful during some of the complicated problems of competitive programming that require you to deal with geometrical shapes and figures.


  • Python:

Over the years, Python has seen tremendous growth in the number of the people who use it. This can mainly be attributed to the fact that it takes very little time to come to grips with the (barely existent) syntax of Python – which is not the case with the other two languages we mentioned. One more reason that programmers are switching to Python is the REPL support. REPL, or Read-Eval-Print-Loop, lets you test your ideas under time constraints. Something that can come in quite handy during programming contests. Just like Java, Python too has a BigInteger class helpful for working with large integers.

However, if we talk about compilation speed, Python stands third in the list. Many times you might get a TLE (time limit exceeded) error for an algorithm in Python, but the same might get cleared if you code it in C++.   
To conclude, let’s reiterate that there’s no absolute best programming language. Each has a set of pros and cons and to be expert at competitive programming; you’ll need to have an extremely logical approach irrespective of the language you choose. At Coding Ninjas, we offer you an extensive course in Competitive Programming. Through that course, we aim to inculcate in you a sense of logical reasoning and problem-solving. From discussing the most important concepts involved in competitive programming to providing practice material, we’ve got it all.

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