Python is an advanced, open-source, interpreted language with a strong focus on object-oriented programming. Data scientists consider it one of the best languages to use in various projects and applications. Python offers excellent possibilities when working with mathematics, statistics, and scientific functions. It provides a great library to deal with data science applications. Python’s ease of use and simple syntax are two of the main reasons for its widespread use in academia and research. This article at ZDNet by Liam Tung shares the shortcomings of the Python language and reasons why it could remain limited to data science.
Why Python Is Losing Its Popularity
Regardless of Python’s popularity, it has its limitations. Mobile application developers do not prefer to use it as it is incompatible. The tech community prefers Java’s Kotlin, Apple’s Swift, or Google’s Dart instead of Python. This is because Python does not support web assembly, a runtime standard that Mozilla, Microsoft, Google, Apple, Intel, Fastly, RedHat, and many others support. These are a few limitations raised by Austria-based Armin Ronacher, the director of engineering at US start-up Sentry. He is a developer with a long history of using Python. Ten years ago, he created the popular Flask Python microframework to solve problems when writing web applications in Python. While Ronacher currently contributes little to Flask since he is not interested in new Python data science features, Flask has become famous for deploying machine-learning models thanks to an abundance of tutorials and university courses that teach it.
Top Views on Python’s Future
Ronacher believes that despite Python’s popularity as a language, it may soon start to lose its allure as a general-purpose programming language since it is restricted to a single field, much like Wolfram’s Mathematica, which has also found a market in data science and machine learning.
Co-founder and CEO of Anaconda, which produces the well-known Anaconda Python distribution for data research, Peter Wang, sneers at Python’s limits for creating desktop and mobile applications.
Python must rely on other frameworks like Qt or wxPython because it is never the operating system’s first-class language on desktops.
A replacement coding language that is not constrained by current design decisions that only allow for use in data science and backend systems, according to Wang and Ronacher, may come into existence.
To read the original article, click on https://www.zdnet.com/article/programming-language-python-is-a-big-hit-for-machine-learning-but-now-it-needs-to-change/