Stack Overflow which is a question-answering platform for software professionals and developers surveys more than 100,000 software developers annually to find out the programming trends, job opportunities, and challenges. In a survey in 2018, they found out that Python was the most popular programming language among the developer community and 25.1% developers wanted to learn it and increase their programming skills.
Table of Contents
Python is a high-level object-oriented programming language. It allows developers to use built-in data structures, combined with dynamic binding and typing. It is a scripting language like Perl, PHP, Ruby, and many more that allows you to create desktop and web applications.
Python ranks second after R in one of the widely used programming languages used in data science and statistical analysis. It’s an open source language providing optimized features for code readability, programmer productivity, and software quality. It allows developers to create a variety of programs ranging from simple to complex programs.
There is no direct and easy answer to this question as both languages are very popular due to their powerful features. However, what you could do is to understand their strengths and weaknesses to identify which one suits you the best and fulfills your purpose.
In the later part of this article, we will be discussing major 10 differences in these languages so that you could easily understand their differences and we’re sure that it will help you in your decision.
Learnability refers to the ease of learning and it is very important when you are learning a new programming language even with no prior programming experience. You need to go with a programming language that is user-friendly and easy to learn with minimum effort and spending a minimum time (one having a shorter learning curve). From this perspective, Python has a short learning curve and you could learn it in a few months as it is designed as a beginner-friendly language providing more simple functions and variables.
Scalability is an important feature of any programming language when it comes to developing applications. It is measured by two parameters: i) the ability to support a large number of users, and ii) its capacity of process number of transactions and data with a minimal server utilization.
Python provides a wide range of built-in frameworks and libraries facilitating the developers with thousands of useful power functions. These frameworks and libraries do not only help developers in utilizing a wide range of functionalities but also it saves their time of writing custom functions.
Visualizing data through different appealing charts or graphs is one of the core activities in data science. Python provides a list of libraries that allows you to create very appealing visualizations. Some of the top visualization libraries of Python include Matplotlib, Plotly, Seaborn, gplot, and Altair etc.
Like other object-oriented languages, Python also supports inheritance and multiple inheritance as well. Inheritance allows base classes (child classes) to inherit objects and behavior from parent class (parent class). It uses a class-based inheritance model.
5. Function Arguments
If we talk about function parameters in both languages, we can also see a difference here. If a function is incorrectly called or provides a wrong number of parameters in Python, an exception with a custom message occurs at the time of function execution. This indicates that the developer doesn’t know the actual number of parameters until functioning calling.
7. Need or an interpreter
8. Programming Paradigms Support
9. Modules and libraries
Python comes with several modules for programmers that’s why it is called “batteries-included programming language”. As discussed earlier, it provides a wide list of built-in libraries for performing data science, data analytics, and machine learning tasks, etc.
10. Hash Tables
11. Numeric Data Types