The TIOBE Programming Community index indicates the popularity of programming languages. Updated monthly, it is based on various factors, such as the number of skilled programmers, search engine results, etc.
Why are these languages so popular? Or rather, why do they continue to be so popular despite periodic assaults on their value proposition and pronouncements of their demise?
Python.org describes Python as “an interpreted, object-oriented, high-level programming language with dynamic semantics.” Some of the world’s most popular websites are based on Python: Reddit, Spotify, Netflix, Instagram, and…. Google!
- Scientific research and computing.
- Systems automation.
- Data Science.
- Machine Learning.
Python allows disparate code to interoperate, giving rise to the semi-affectionate term, “glue language”. Python is regularly revised with new features to satisfy the evolving requirements of development teams.
Why does the World swear by Python?
- Code Reuse:
- Built-in Functionalities:
- Versatile applicability:
- Easy to use, adopt and update:
Python supports modules and packages, making code reuse possible, which shortens development cycles. Programmers don’t have to start from scratch if the reused code will perform the same (or similar) function in the new application. They can, instead, write code to create unique, value-adding functionalities for the final product. Thus, code reusability helps to create better software, faster.
Python’s built-in data structures, pre-built libraries and frameworks, and features like dynamic typing and dynamic binding also make it a very attractive proposition for rapid application development. Python is most commonly used for scripting and automation. However, it can also be used to build high-quality software, whether the requirement is for standalone applications or web services. Python also provides all the functionalities required to create REST APIs, comprehensive, data-driven sites, and more.
Although Python is not the “fastest” language, it is still extremely versatile in terms of supported use cases. For instance, it is the preferred language for building Machine Learning applications related to speech recognition, financial services, or streaming entertainment services (think Netflix). Python also offers several built-in libraries for scientific computing and data science, for use cases related to astronomy, bioinformatics, statistical analyses, and even psychology.
Python has a highly readable and straightforward syntax. It also follows indentation rules and doesn’t use enclosing braces. Being a dynamically typed language, developers don’t have to determine variable types. The interpreter will infer these types, and all checks will be made at runtime. Since programmers don’t have to worry about complexities, they can learn it easily, and start writing programs quickly.
- Great for client-side scripting and fast results:
- Easy to learn and implement:
- Requires no compilation, is browser- and device-agnostic:
- Easy to debug and test: