Frequently, you will find articles online that wax eloquent on the qualities of one programming language over another. Quite often, their goal is to promote one language while degrading the other. But the comparison we offer below looks at both Python and C++ as tools with different uses for different problems.
Python is one of the fastest-growing programming languages. The underlying goal of creating Python was its simplicity. It is one of the simplest languages to learn, given its close similarity to common English. Fundamentally, it is a high-level, interpreted, general-purpose, and object-oriented scripting language.
Like Perl and PHP, Python doesn’t demand program compilation before execution. So, you don’t have to run a compiler that turns source files into compiled class files. Instead, you run a .py file. What’s more, Python byte code compilation is automatic and entirely implicit.
Python is high-level, meaning it is created for programmers who prefer having the written code translated into a low-level language. Python should also be processed before running, which enables its portability—it can run on different kinds of computers with few or no modifications.
You can use Python to create nearly any application in almost all fields for various tasks. Whether it is the execution of short-term tasks like software testing or long-term product development that involves roadmap planning, Python can help.
For this reason, the programming language is famous not just among software engineers but also among specialists in fields like data analysis, network engineering, mathematics, and science. Furthermore, Python is also a beginner-friendly scripting language.
Python takes an object-oriented approach toward scripting and powerful code structuring, which allows considering problems in terms of classes and objects. Additionally, Python also supports a procedural paradigm. Developers can create reusable patterns of code, thus mitigating redundancy in development projects.
The origins of the C++ programming language lie in another programming language called C, which was developed in 1970. But even though the two programming languages are pretty similar, C++ offers additional features like object-oriented, procedural, or generic programming; the namespace feature; operator overloading; exception and error handling; etc. Therefore, it is safe to say that C++ is an advanced version of C.
C++ uses objects while programming to help you implement real-time problems based on data abstraction, data hiding, data encapsulation, and polymorphism.
Users can organize data and code into a program that they can understand. The code is then translated by the platform or compiler to the instructions a computer can follow. This makes the whole process fast and efficient.
Users can reuse code instructions they have written to write out identical functions. Additionally, the data and instructions can be combined into classes that can be built from one another to perform complex functions.
C++ is a high-level programming language, making it easier for users to work with, as it is closely associated with English.
Python is a very popular programming language—but why is that, exactly?
Given its many flexible features, Python is used for all sorts of purposes. Let’s take a look at some of the language’s most common use cases.
Since Python is a simple, stable, and flexible programming language, it is ideal for various machine learning (ML) and artificial intelligence (AI) projects. In fact, there are many Python ML and AI libraries and packages available for data scientists.
Being easy to learn, flexible, and well-supported, the language is comparatively quick and simple to use for data engineering and analysis. Moreover, it can manipulate data and carry out repetitive tasks when working with large amounts of information.
Python is open-source and comes with a vast array of graphing libraries with a variety of features, making it easy to transform data into meaningful insights.
Python can be used to program all kinds of applications, from blockchain applications to audio and video apps. The general-purpose language can be used to read and create file directories, GUIs, APIs, and more.
Python’s many web development frameworks, such as Django, Pyramid, and Flask, can be used to create sites and services with ease. Furthermore, the extensive libraries and modules that accompany Python frameworks make functions like content management, database access, and data authorization accessible.
Though the language stands far from the industry standard in game development, Python does have its uses in the gaming industry. It can be used to create simple games, meaning it is ideal to quickly develop a prototype in it.
Python’s simple and elegant interface and syntax inspire the creation of new programming languages.
In the wonderful world of computer science and engineering, there are many coding languages to choose from. And depending on your end goals, some languages are more relevant than others. That’s why we’ll now talk about the many things you can do with C++.
C++ happens to be the many game developers’ favorite programming language to work with. In fact, it was used to develop popular games like Counter-Strike or World of Warcraft. C++ helps optimize resources, meaning developers can adjust how memory allocation and data structures are managed. Additionally, the language allows for multilayer networking.
The low-level capabilities of C++ allow developers to structure their code with tiny details that can maximize the efficiency of operating systems. Windows, macOS, and iOS all incorporate C++ programming.
Machine learning models powered by a C++ library of calculations help train these models. Sometimes, C++ is used for backend programming in machine learning tools.
Popular database tools like MongoDB and MySQL use C++ for well-designed storage and simpler systems.
C++ is an excellent language for IoT applications, as they rely on limited computing resources and constrained power requirements.
C++ is reliable and fast, which helps facilitate a high volume of transactions, trades, and financial modeling that demand data stimulations.
C++ allows for stimulations and model data, which is ideal for bioinformatics research. Medical tools and applications like lab testing equipment and patient information systems are built with C++.
The programming language offers an easy way to organize, analyze, and understand high-value data, making it easy for scientists to analyze data.
C++ can be used to create special effects and graphics that are often applied in movies. C++ is perfect for these purposes, as it can handle large files with high-quality footage. Furthermore, it can carry out calculations that special effects demand.
Now, let’s compare the two languages based on various industry metrics, syntax, and general rules of programming.
When it comes to choosing between Python and C++, it usually depends on the kind of software or program you want to develop.
For example, C++ is often used in embedded systems, game development, 3D or visual design programs, as well as for building operating systems or web browsers and portals. On the other hand, Python is a scripting language that is ideal for machine learning contexts, data analysis, and backend web development.
At the end of the day, comparing Python and C++ leads us to one conclusion: Python is easier to use and features a great support system for AI and ML frameworks when it comes to simplicity. However, C++ is much faster performance-wise. After all, Python is an interpreted language, which makes it difficult for it to stand up to a compiled language such as C++.
We hope that you’ll now be able to choose the right language for your next project. However, if you’re still undecided, we encourage you to check out this comparison of Python with various programming languages or other articles in the same series:
STX Next has been successfully leveraging Python since 2005 to deliver unique and highly customized web development projects. Our experts can help you use Python for all sorts of web applications. Reach out to us and let’s discuss your next software project!