Python Programming Language Can Lose Its Prominence In Future
- By Rakesh Bisht
- Web Development
You would have already heard about Python programming language, it is one of the most primitive programming languages that play a significant role in data analytics and application development.
However, the usage of this programming languages can diminish due to the arrival of other programming languages. It is true that this technology has surpassed the popularity of C, C#, Java, and many other greatly popular languages in the world.
Though, the significant decline in its charm can result in a decline in its usage.
Why Python Is Losing Its Charm?
As python is a dominant programming language in Data Science and Machine Learning, you must be wondering how it can lose its position. Actually, it doesn't mean that Python is greatly used and popular so it doesn't have any disadvantages.
If we see modern programming languages like Julia, Scala, Swift, and many others, then python has significant drawbacks that contribute to downfall in application development. Here I am explaining some drawbacks that are causing this technology to lose its deposition worldwide.
Drawbacks Of Python
• Vulnerable Type safety and Performance
Python's dynamically typed nature is greatly vulnerable in nature, as it hinders developers' work by running the code in development/ production. Yes! it true that dynamic typing provides ease in code writing averting the need for type defining. Though, the risks can arise at runtime, and hamper the work of developers.
As python's interpreter analyze every single code line while execution, runtime errors can be frequent and can lead to overloading. This can result in slow performance, which usually doesn't happen in other programming languages like Julia.
It is true that everything comes at a cost, and so at true for python languages' dynamic typing,
• Runtime Errors
The basic structure of python is not like other programming languages that compile first and execute. Instead, it compiles the code when you execute it, and this results in runtime errors and poor performance.
Another major issue arises due to this time consumption in execution and requires testing so many times. For seasoned developers, the complexity of debugging in python makes them dejected and frustrated, which is another reason behind python is bad for programming in some people's understanding.
• Parallelism Restrictions
Another drawback of python is its limitations in parallel computing. It is based on a global interpreter lock that do not allow multiple threads to execute at the same time. Due to this, developers can't use multiple CPU cores and developers' work ends up with halts.
Features And Support
In comparison to Python, other programming languages like Swift and Julia offer better features in the area of AI and ML and even interoperability with Python. Moreover, these languages also offer interoperability with other languages like C, R, Java, and more and support.
Since new programming languages are arriving with improved features and support, the usage of Python may decline in upcoming years. When it comes to automation and AI/ML integration, the changes in the usage of programming language can be seen.
IF you are using python in business automation and data analytics, connect with a business transformation agency to find out what other programming languages you can use in place of Python to reduce cost and operation issues.