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Why Python is a useful language

Guido Van Rossum developed Python, a general-purpose programming language. Python is an interpreted language that was first released in 1991 and has gained a lot of popularity since then.
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What exactly is Python?

According to a recent poll, Python is the favorite programming language of roughly 32% of engineers throughout the world. According to the TIOBE index for October 2018, Python is the fourth most popular programming language, trailing only Java, C, and C++.

Most popular introductory teaching language

You may be aware that Python continues to grow in popularity, but did you realize that Python is currently the most popular introductory teaching language in American universities? Are you aware that the Central Board of Secondary Education in India has included Python in the computer science curriculum in schools?

Python programming language

Python is a programming language that may be used to create a wide range of programs, including desktop-based GUI applications, Web-based applications, and games. This language handles typical programming chores, allowing you to concentrate on the application’s essential functionality.

Read more: Why R programming is worth learning?

Why Python is a useful language

1.   Easy to read codes

Why Python is a useful language? When developing a software program, it’s important to pay attention to the quality of your source code so that it’s easy to maintain and update. In addition, unlike other programming languages, Python focuses on making code more accessible by allowing you to utilize keywords in English rather than punctuation.

2. It works with a variety of programming paradigms.

Python, like other contemporary programming paradigms, offers a variety of programming paradigms. Python supports both object-oriented and procedural programming styles. Additionally, Python’s language features support numerous functional programming and aspect-oriented programming ideas. Python also has capabilities such as automated memory management. You may develop a range of huge and sophisticated software programs with this capacity of supporting various programming paradigms and having language characteristics.

3. Platform compatibility is the third factor to consider.

Python currently supports all major platforms. Python is compatible with a variety of operating systems, including Windows, LINUX, UNIX, Macintosh, Solaris, and others. Because Python is an interpreted language, you may execute the same source code on multiple platforms without having to recompile it. This means that even if you make minor changes to the code, you don’t have to recompile it; instead, you can just run it and see the results of your changes.

Why Python is a useful language

4. Comprehensive Standard Library.

Python is more helpful than other programming languages because of this characteristic. This language comes with a number of pre-built libraries that provide your application a lot of power. This standard library assists you in selecting modules from a large number of options to meet your needs and standards. Furthermore, each module enables you to extend the functionality of your application without having to write any extra code.

Read more: What is machine learning used for?

5. Frameworks that are open source.

Because Python is an open source programming language, it allows you to leverage open source python frameworks, development tools, and libraries to significantly reduce development expenses. You may choose from a variety of open source frameworks and libraries to meet your unique needs and specs. For example, you may utilize strong frameworks like Django, Pyramid, Cherrypy, Bottle, and Flask to make web development quick and simple.

6. Facilitates the development of complex applications.

Python is a general-purpose programming language that may be used to create both desktop and web-based GUI programs. It can also be used to create sophisticated software, such as scientific or numerical software. Apart from that, Python comes with tools for data analysis and visualization. You don’t need to put in any extra work to use these data analysis tools to create a bespoke big data solution.

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