What are the pros and cons of using Python in competitive programming?

In this article, we will learn the pros and cons of using Python in competitive programming.

Challenges faced by using python in Competitive Coding

Competitive coding tasks are typically designed to evaluate programmers' problem-solving skills and data structure fluency. At the same time, the challenges may involve finishing the problem within the given time and space complexity. This is where other languages shine brighter than Python.

Some of the needed features to make the language versatile in terms of time, space, and data structure manipulation are as follows −

  • Memory allocation flexibility and high control.
  • faster memory access.
  • Easier address retrieval.
  • Simplified complex data structures.
  • Execution time.
  • Space efficiency.

Cons of Using Python in Competitive Coding

Some of the issues we encounter when using Python in competitive programming are as follows −

Python's Execution Time is Slow

Python is a high-level programming language. This means that it is more away from the hardware than other low-level programming languages. Because the hardware is less accessible, the time required to access and store variables in memory is long. This reduces the overall execution speed.

Memory access, as well as access to the ALU and other hardware required for program execution, is slower than in a lower-level programming language.

The execution time of the program is one of the most important elements in measuring the efficiency of the code in competitive programming. Python applications take a long time to execute, making them a poor language for competitive programming.

Memory Allocation

Python is a dynamically typed language with flexible data types, therefore memory allocation is not fixed. As a result, because memory allocation is not fixed, Python may not be suitable for memory-intensive tasks.

Memory deallocation and consumption is another key measure for code efficiency. This is greatly influenced by Python scripts due to dynamic data types.

Runtime Errors

Python is an interpreted programming language. This means that no compiler is required. The language is directly compiled and operated in parallel with the assistance of an interpreter.

As a result, any problems in the code will not be noticed until the program is executed completely. For competitive programmers, this is an issue.

Syntax errors and incorrect brackets can be identified during the compilation process in programming languages such as C++. After executing the program logical issues can be corrected.

Because Python is interpreted and dynamically typed, most errors are only visible when the program is run. If a program is half-wrong, the code before the mistakes may run.

It will be difficult to get the desired results if it produces permanent changes to documents or files without following the complete logic of the program.

Pros of Python for Competitive Coding

Python's programming language contains a lot of essential data structures for competitive programming. Its many libraries and frameworks contribute to its benefits. It's also a fantastic choice for competitive coding for the following reasons −

  • A variable-type independent language simplifies coding for developers. See In other languages, such as C, C++, or Java, we must define the variable type. The interpreter performs the type check in this case. This helps to shorten the implementation time.

  • Enrich Library provides support for fundamental operations such as sorting, counting, and so on.

  • Python's list implementation is really useful.

  • It helps in locating the last element without the size specifics.

  • In most circumstances, if you examine the list and other inbuilt data structures, you will not need to implement user-defined data structures. Because it has an inbuilt solution.

  • A function may return many data types. Because it differs from general/standard programming languages.

Easy and Speed

Competitive coding's purpose is to discover the best solution in the lowest period. Python is the best programming language since it saves time on code development when compared to other traditional languages like Java, C, and C++. Furthermore, the time saved by not coding could be spent researching the logic required to solve the problem. Python is easy to learn and use, even for inexperienced programmers. As a result, even if you are short on time, getting started and learning Python principles from the ground up is simple.

Wide Range of Data Structures

Python programming employs several data structures, including tuples, dictionaries, and others. They are incredibly useful to developers, especially when working with complex challenges in competitive programming.

No Need for a Data Type Declaration

When working with Python, there is no need to specify variables or their data types before utilizing them. This enhances range flexibility until it reaches the hardware's required limits. This suggests that type conversions are handled internally, thus there's no need to be concerned about integers and long integers. You can write code much faster and more precisely, satisfying one of the key requirements of competitive programming.

Massive Library Collections

One of Python's distinctive features is its libraries, which include functions such as len, sorted, max, min, count, and others.

  • len() function − returns the length of the iterable

  • max() function − returns the highest-valued item/greatest numbers in an iterable)

  • min() function − returns the lowest-valued item in an iterable.

  • sum() function − Returns the sum of all items in an iterable.

  • sorted() function − returns a sorted list of the iterable object given.

These are some of the most common built-in functions, which are immensely beneficial to coders because they eliminate the need to write code for routine procedures. The functions use the best algorithm to solve a problem. For example, the sorted function implements the import algorithm, which offers reliable sorting even at the worst-case performance of O. (nlogn). This is the greatest sorting algorithm since it has the best-case runtime of constant or O. (1).

Python programming has the unique ability to remove or delete certain portions. Memory regions remain intact in an adjacent form. Even though the functionality presents the linked list idea as null, inserts can be performed at any desired point.


Competitive programming is a wide field with a lot of room for advancement. It is critical to devote your time to learning the correct programming language.

Whatever language you choose for competitive programming, make it enjoyable to learn and create code in. It must be both beneficial and efficient at the same time.