Yes, Python is one of the most widely used programming languages across the globe. Yes, Python has helped businesses achieve their goals and objectives. However, on the flip side, there is another side of the story as well. There are a few aspects where the language lags and is therefore not the best coding language. In this article, we will talk about 10 reasons why Python is not the best programming language. Keep reading!
A point to note is that indentation is not optional in Python. This poses a problem when using conditions. Also, indentation makes it hard to see where the function ends.
Python has two versions – python 2 and python 3. In the majority of the cases, they are often installed alongside each other in Linux. As a result of this, many Linux distributions have been forced to ship with two versions of Python because so many packages took time to convert to Python 3.
As known to many, a Python script isn't compiled first and then executed. Rather, what exactly happens is, that it compiles every time you execute it, so any coding error manifests itself at runtime. All this ultimately leads to poor performance, time consumption, and the need for a lot of tests.
In python, whitespaces are used extensively to indicate different levels of code. However, braces and semicolons are more visually appealing, beginner-friendly, maintainable, and intuitive to understand.
The shift from desktop to smartphone calls for a requirement of robust languages to build mobile software. A point worth a mention is that not many mobile apps are being developed with Python. This is one of the reasons why Python is not considered to be the best language to rely on when it comes to mobile development.
There is this issue with the usage of lambdas in Python as the same is rather restrictive. In python, Lambdas can only be expressions and not statements. However, variable declarations and statements are always statements which ultimately means that Lambdas cannot be used for them.
Python stands for the ability to execute only one task at a time. It is because this coding language makes sure each variable has only one data type, and if there are any parallel processes, they could mess that up. All this results in slow speed.
In the case of programming languages other than Python, you don't need to specify data types. This, ultimately, implies that a lot of memory needs to be used because the program needs to reserve enough space for each variable that it works in any case. In a nutshell, a lot of memory is consumed.
Python is associated with dynamic scoping. Now, this poses a problem. Every expression needs to be tested in every possible context. Undoubtedly, this is a tedious task.
Taking into account the problems posed by dynamic scoping, the python did try shifting to static scoping. However, that didn't seem to go well. It was seen that inner scopes can only see outer scopes, but not change them which led to great confusion.
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