Python vs. C++: Syntax, Key Differences, and Usages

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C++ and Python are both general-purpose programming languages. Still, their syntax and usage are very different from one another. One is interpreted, and the other is precompiled. One has a simple syntax, the other has a stiff learning curve.

In this Python vs. C++ comparison article, we share the characteristics of each of the languages and explore their key differences and usage in more detail.

Introduction to Python

Python is a programming language that dates to 1991. It was introduced by Guido van Rossum and got its name from Monty Python’s Flying Circus, the popular British comedy troupe.

This high-level language is object-oriented, and it’s among the simplest and easiest programming languages to learn. Today, Python is among the most popular programming languages in the world. It’s greatly used in data science, data analytics, machine learning, automation, statistics, and more.

The language supports a range of programming models like object-oriented, procedural, and functional programming. It also has dynamic typing and dynamic binding.

Python can also be used to prototype or test code that can be used at a later date for the development of full-fledged applications with other high-level languages. This is often the case for beginners in the game development sector.

Introduction to C++

C++ is a high-level programming language introduced by Bjarne Stroustrup in 1979 in New Jersey. This general-purpose language is created as an extension of the existing C language and was first known as “C with classes.”

The fact that it’s general-purpose means C++ can be used to create a range of applications.

Over time, C++ has witnessed a massive extension to become an object-oriented, generic, and functional language. Many of Python’s libraries have the C++ code in their basics.

C++ is an intermediate-level language since it contains elements of both low-level and high-level programming languages.

Python Syntax Overview

Here’s an overview of Python’s syntax to help you better understand how this language functions.


Python programmers use comments to place tags at appropriate places in the code. The comments are like short descriptions that increase the readability of the code. This section can help you understand why a specific line of code was written.


Indentation is the space at the start of a code line. Most other languages use indentation for readability purposes, but Python also uses it to indicate a code block. Without indentation, the system would show an error in syntax.


Similarly, docstrings serve to explain Python codes. Programmers inspect docstrings during runtime and determine the boundaries with three double quotes. They can explain or write docstrings inside those double quotes. A docstring documents the module, function, class, or method.


Python programmers create string objects using quotations. This programming language has single, double, and triple quoted strings. If one string starts with a single quote, it also needs to end with one quote. The same goes for double and triple quotes.


A variable in Python is a symbolic pointer or reference to an object. Programmers can assign a certain object with a specific name, and every time they want to refer to that object, they can do so using the given name. All data, however, remains within the original object, not the variable.


Identifiers define elements in Python like functions, class, modules, variables, and any other object.

String Formatters

String formatters arrange and present strings for a more nicely organized output.

C++ Syntax Overview

Now that you’re familiar with how Python works, here’s an overview of C++ syntax for comparison in the Python vs. C++ debate.

Header Files

Header files are located at the top of the C++ program. Their purpose is to ensure the compiler includes all functions associated with that file. Header files reduce the number and complexity of code lines and give the programmer the benefit of reusing functions stated in header files for other .cpp files.


A class in C++ is a collection of objects. You can consider it as an object’s behavior blueprint. Each class is defined using the keyword class and contains members referred to as methods or member functions, constructors and variables, and more.


Methods or functions are essential elements of C++. They are used for writing logic, performing data manipulation, and all other crucial operations. The programmer can name the function and the return type and write the logic or the operations inside the brackets.

Main Function

The main function in C++ is a starting point from which the program execution begins. All C++ programs must have a main function. Whenever any of the programs is executed, the main function receives the control.


You can think of an object in C++ as a class instance. When you create an object for a certain class, you can use that object to access the functions and data members belonging to that class. This is done with the dot operator. You can write the object name before the dot operator and follow with the name of the function after the round brackets.

Return Statement

The return statement’s purpose is to terminate the function execution and return control to the operating system or the calling function. The execution will continue in the calling function right after the call.

Instance Variables

Instance variables get defined inside a class but are located outside the methods, blocks, or constructors. An instance variable belongs to an object, and all objects have their own variables.

Python vs. C++: Key Differences

Below we outline the key differences between Python and C++ in terms of code, syntax, garbage collection, speed, and other factors.

Code Length

C++ has a longer line of code compared to Python.


Python’s syntax is short-handed and has many short-hand structural iterators. C++ comes with plenty of predefined structures and syntaxes and has a much steeper learning curve.

Garbage Collection

Python has garbage collection, while C++ doesn’t. However, it’s possible to implement garbage collection in C++.


Python is slower because it requires an interpreter to run its code.


Python is an interpreted language, while C++ is precompiled.


Python has large community support and is very popular with beginner programmers. C++ also has its fair share of communities but isn’t suitable for novice coders.


Python doesn’t have any restrictions on return type value or argument type. C++ functions can only accept and return value types that have already been predefined.

Variable Scope

Python programmers can access the variables outside the loop, while C++ limits the variable scope within the loop.

Python vs. C++

Where C++ Is Used

Most present-day systems and programs use either C or C++ in their codebase. Whether it’s a web browser, Windows OS, a video game, or photo editing software, they all use C++ to some degree.

Here are the most popular real-world usages of C++:


C++ is among the most popular game development programming languages. It can deal with 3D game complexities, provide multilayer networking, and more.

Games such as Counter-Strike, World of Warcraft, and engines and consoles like Unreal Engine, PlayStation, or Xbox are all developed using C++.

Operating Systems

C++ is an essential part of the code blocks of most operating systems such as Windows and macOS. It’s also a building block of iOS.

Operating systems must be fast at managing resources, and the robust capabilities of C++ let the developers create codes that make the smallest operating system details energy efficient and fast.

Web Browsers

Browsers like Safari, Mozilla, Chrome, or Opera all rely on C++. The developers use this programming language to create back-end services that get information from databases and translate the code into front-end web pages. Thanks to C++, the end user doesn’t have to wait long for content to appear on their screen.

GUI Applications

Most GUI-based applications like Adobe Photoshop, Illustrator, and others are programmed with C++.

Banking Applications

All banking applications require multi-threading, concurrency, and high-performance. This is why C++ is usually the default programming language for different banking and financial needs.

Database Management

Popular databases like MongoDB and MySQL are built with C++. Netflix, YouTube, Google, Adobe, and other companies rely on these databases for performing everyday tasks. C++ helps structure these databases so there’s enough storage on them.


Many compilers for different programming languages use either C++ or C since they are lower-level and are located closer to the hardware.

Internet of Things (IoT)

Embedded systems that come with IoT devices often use C++. Cars, TVs, smartwatches, and appliances are only some examples. Since the hardware of these devices is embedded inside an object, they need to use limited computing resources and robust power requirements. This is precisely what C++ helps programmers achieve.

Cloud Systems

Extensive cloud systems need to be close to the hardware to work properly. Therefore, C++ is an excellent choice for cloud storage system implementation. Cloud systems also need multithreading for concurrent application support, and C++ can provide just that.

Machine Learning

TensorFlow is an excellent example of a machine learning tool that relies on C++ for back-end programming. Despite Python being the preferred option for TensorFlow users, the essential machine learning code is still written in C++.

AR/VR Applications

C++ is among the most popular languages for programming AR and VR applications. Since these applications deal with a massive amount of data that adjust all the time depending on the camera sensor input, C++ helps process that data and provide a great virtual experience.


Since libraries use high-level computations and require robust performance and speed, C++ is often the preferred language for writing their code.

Where Python Is Used

Python finds its use in a range of applications and industries. Here’s an overview of the most popular real-world usages.

Data Analytics and Data Science

Data analysts and scientists rely on Python to perform calculations, create complex algorithms, manipulate data, and perform many other data tasks. Python is a great programming language for presenting data as well. Data professionals can create graphs, charts, 3D plots, and histograms to present their findings efficiently.

Machine Learning

Python’s consistency and simplicity make it a good fit for machine learning and artificial intelligence projects. The access to frameworks and libraries for both fields, as well as the flexibility and independence of the platform, lean heavily in favor of using Python in machine learning.

Web Development

Similar to machine learning, Python is an excellent choice for web development due to a range of popular frameworks like Django, Flask, and others. These frameworks are the building blocks of world-famous platforms such as Reddit, Spotify, and Mozilla.

Database access, data authorization, and content management functions are all easily accessible thanks to these extensive libraries. This makes it obvious why Python is an excellent choice for web development.

Task Automation

Python allows programmers to automate a range of tasks with the help of scripts. Automation in Python is beneficial for error checking, file conversion, math execution, duplicate data removal, etc. Simple tasks such as renaming files, downloading content, or sending texts and emails can also be automated using Python.

Software Prototyping and Testing

When it comes to testing, bug control, and prototyping, Python can be of great help. Software developers use this language to test new features and products. Popular tools for this purpose include Requestium and Green.

Everyday Usage

Python isn’t only used by data professionals. Ordinary people can use it to automate simple tasks such as updating a shopping list, filling out online forms, converting text files to spreadsheets, and much more.

Data Visualization

Data visualization is one of the greatest strengths of Python. Thanks to its open-source code and flexibility, Python offers amazing graphing libraries with tons of features. Users can represent just about any graphical image or interactive plot using Plotly, Pandas Visualization, and similar libraries.

Game Development

Although Python isn’t the first choice for game development purposes, it is still used in this field. Beginner gamers can use it to develop simple games or prototypes. Some game development features like dialogue tree creation can also be done in Python.


When it comes to determining asset price trends and predictions, automating workflows in different data sources, and performing qualitative analysis, Python is a go-to programming language for financial analysts.

Wrapping Up the Python vs. C++ Comparison

Both Python and C++ are incredibly powerful and versatile programming languages used across industries. However, they are used for performing completely different functions. While Python is better suited for structuring and manipulating data, C++ is the building block of the browser, game, and operating system development.

Python is more suitable for beginner coders because it comes with an easier learning curve. Hopefully, this Python vs. C++ review has given you an overview of which language is better suited for your particular needs and which you should prioritize learning in the near future.

Read also: C++ vs. Java vs. Python: What’s The Difference?

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