Data Science and coding communities both consider Python to be one of the most popular programming languages. But do you wonder why? And how did Python become so popular?


We’ll give you the answer in one line – Python is one of the top programming languages of all!


Python can handle any development or Data Science task you may have. Open-source, high-level Python is a general-purpose programming language that incorporates the features of object-oriented, structural, and functional programming.


Python's simple syntax allows for easy writing of code that can be applied to complex software development processes, such as machine learning, data analytics, and test-driven development. Windows, Linux, and iOS are all compatible with Python. In this blog, we will talk about the uses of python language.


What makes Python the “Best of the Best?”

There are a number of Python features that make it an excellent tool for professionals of all skill levels:

Python = Simplicity

The ease of learning, as well as the ease of using, and the simplicity of implementing Python cannot be understated. It is easy to learn Python coding in a few days due to its syntax resembling English. Additionally, Python is dynamically-typed, so indentation is mandatory, increasing readability. 

It is an open-source language

Python is open-source, so you can install and use it without paying a fee. The Python source code can therefore be freely accessed by the public. The official Python website has it available for download. Python also supports FLOSS (Free/Libre and Open Source Software), which means it can also be modified and distributed. As a result, its features are constantly improved and tweaked by the Python community.

Real-world Applications of Python

1. Web Development

Python is your best tool for web development. Why is that? 

There are a lot of options available for web development with Python. For instance, you have Django, Pyramid, Flask, and Bottle for developing web frameworks and even advanced content management systems like Plone and Django CMS. 


2. Game Development

Python offers money for web development with Python.ensions (libraries) that come in handy for the development of interactive games. For instance, libraries like PySoy (a 3D game engine that supports Python 3) and PyGame are two Python-based libraries used widely for game development.


3. Scientific and Numeric Applications

In recent years, Python has become a vital tool in scientific and numeric computing due to its extensive library base. Python contributes the skeleton for scientific data processing and computation applications. Python is used by programs such as FreeCAD (3D modeling software) and Abaqus (finite element method software).

4. Artificial Intelligence and Machine Learning 

Artificial intelligence and machine learning models and projects are inherently different from traditional software projects. AI/ML projects are different from conventional software projects in terms of the tools and technologies used as well as the skillset required. Languages used in AI/ML applications need to be stable, secure, flexible, and equipped with tools that can handle their specific requirements. 


5.Desktop GUI

Additionally, Python offers a modular architecture and the ability to run on multiple operating systems, in addition to its English-like syntax. Python is an excellent choice for developing desktop-based GUI applications because of these aspects and its extensive text processing tools. 

6. Software Development

Applications and packages written in Python are designed to simplify software development. Python is a powerful programming language that can be used to develop complex desktop and web applications, such as scientific and numerical applications. Python is therefore used as a build control and testing language by Software Developers.

7. Enterprise-level/Business Applications

As compared to standard applications, enterprise-level software or business applications require features like readability, extensibility, and scalability. The main purpose of business applications is to meet the needs of an organization rather than individual customers.


Python is capable of handling almost any development requirement after reading about all of these versatile and diverse real-world Python applications. Python applications have also been gaining new traction in Data Science and Machine Learning in the last couple years.


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