Python is one of the most popular and fastest-growing programming language. Inherently, it is interpreted, high-level, general-purpose, and object-oriented scripting language, which means the following:
An interpreter processes the source file at runtime, it reads the lines of code, one by one and performs what is said. Similarly to Perl and PHP, Python does not require that you compile your program before executing it. So, you do not have to invoke a compiler. Instead of running the compiler that helps turn source files into compiled class files, you simply run a .py file. Python byte code compilation is automatic and entirely implicit.
Python relies on easy-to-read structures that are later translated into a low-level language, the original code that is run on a computer’s central processing unit (CPU). A high-level language is intended to be used by a programmer and the written code is further interpreted into a low-level language. Like C++ or Java, before running, Python has to be processed. This enables Python’s portability — it can run on different kinds of computers with nearly no modifications.
Python can be used for nearly everything. It is applicable to almost every field for a variety of tasks. Be it the execution of such short-term tasks as software testing or long-term product development that involves roadmap planning, Python works well for them all, it is applicable all over the map. Its roles are unlimited. It is popular not only among software engineers, but also among specialists in other fields: mathematics, data analysis, science, accounting, and network engineering. Likewise, Python cliques with young people because it’s a very beginner-friendly scripting language.
This programming paradigm gives an overall orientation towards scripting and powerful code structuring. This object-oriented approach allows thinking of problems in terms of classes and objects. Then, objects are composed in such a way to make up complex computer programs. Beside the object-oriented programming, Python also supports a procedural paradigm. With OOP being only one of the options, you can make Python programming more advanced by going for an object-oriented programming approach. Developers can create reusable patterns of code thus curtailing redundancy in development projects.