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Difference between Python and C++

Last Updated : 14 Jul, 2023
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Python and C++ both are the most popular and general-purpose programming languages. They both support Object-Oriented Programming (OPP) yet they are a lot different from one another. In this article, we will discuss how Python is different from C++.


What is Python?

Python is a high-level, interpreted programming language. It was invented back in 1991, by Guido Van Rossum. Python is an object-oriented programming language that has enormous library support making the implementation of various programs and algorithms easy. Its language constructs and object-oriented approach aim to help programmers to write clear, logical code for various projects. 

What is C++?

C++ is a high-level, general-purpose programming language created by Bjarne Stroustrup in 1979 as an extension of the C programming language, or “C with Classes”. The language has expanded significantly over time, and modern C++ has object-oriented, generic, and functional features in addition to facilities for low-level memory manipulation.  Many of the technologies as libraries in Python have underlying C++ code.

Difference Between C++ vs Python

The following table shows the key difference between Python and C++ programming languages.





Python has fewer lines of code

C++ tends to have long lines of code


It uses short-hand syntax and has numerous short-hand structural iterators.  It requires ‘self’ as a parameter to any class instance method.  Some of the short-hand syntaxes are confusing (e.g. `rkwargs`) but rarely is anything in Python completely esoteric.

It has a stiff learning curve as it has lots of predefined syntaxes and structures.  C++ uses implicitly ‘this’ to refer to class instances.  Some syntax in C++ is extremely esoteric.


Python is interpreted

C++ is precompiled


It is slower since it uses an interpreter and also determines the data type at run time

It is faster once compiled as compared to python


Specialized formatting not common in other languages, script-like language, OOP features, code reuse through libraries

C-like syntax, powerful OOP features and operator overloading, best compile-time optimizer


It is dynamically typed.

is statically typed


Python Functions do not have restrictions on the type of the argument and the type of its return value

In C++, the function can accept and return the type of value which is already defined

Scope of Variable

Variables are accessible even outside the loop

The scope of variables is limited within the loops


Python programs are saved with the .py extension

C++ programs are saved with the .cpp extension


It has huge community support. When it comes to popularity, beginner and novice programmers tend to turn to Python

It also has dedicated followings online. But only the people who have some experience in the field show a lot of interest in C++

Garbage Collection

It supports garbage collection

It doesn’t support garbage collection, but it can be implemented

Rapid Prototyping

Rapid Prototyping is possible, with easy project setup, live interpreter

Rapid Prototyping is possible, but project setup can be complicated, live interpreter through IRC bot

Application Domain Web development, data analysis, scientific computations, etc Game development, embedded systems, etc
Variable Declaration Variables are declared by simply writing their name with their datatype While declaring a variable it is necessary to mention its datatype
Installation on Windows Difficult to install on Windows Easy to install on Windows


Python leads to one conclusion: Python is better for beginners in terms of its easy-to-read code and simple syntax. Additionally, Python is a good option for web development (backend), while C++ is not very popular in web development of any kind. 

Python is also a leading language for data analysis and machine learning. While it is possible to use C++ for machine learning purposes as well, it is not a good option. In terms of simplicity, Python is much easier to use and has a great support system when it comes to AI and ML frameworks.

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