Coding Styles of Python Programming Language
Python is a Programming language that is emerging in a broader way throughout the world. Many programming languages like Java, C++ are object-oriented programming languages that only support object-oriented coding. Unlike other languages, Python provides flexibility for the users to opt for different coding styles.
Different coding styles can be chosen for different problems. There are four different coding styles offered by python. They are
Let us discuss them individually in more detail.
In the functional type of coding, every statement is treated as a Mathematical equation and mutable (able to change) data can be avoided. Most of the programmers prefer this type of coding for recursion and lambda calculus. The merit of this functional coding is it works well for parallel processing, as there is no state to consider. This style of coding is mostly preferred by academics and Data scientists.
my_list = [1, 5, 4, 6, 8, 11, 3, 12] new_list = list(map(lambda x: x * 2 , my_list)) print(new_list)
[2, 10, 8, 12, 16, 22, 6, 24]
When there is a change in the program, computation occurs. Imperative style of coding is adopted, if we have to manipulate the data structures. This style establishes the program in a simple manner. It is mostly used by Data scientists because of its easy demonstration.
sum = 0 for x in my_list: sum += x print(sum)
This type of coding relies on the data fields, which are treated as objects. These can be manipulated only through prescribed methods. Python doesn’t support this paradigm completely, due to some features like encapsulation cannot be implemented. This type of coding also supports code reuse. Other programming languages generally employ this type of coding.
class word: def test(self): print("Python") string = word() string.test()
Usually, most of the people begin learning a language through procedural code, where the tasks proceed a step at a time. It is the simplest form of coding. It is mostly used by non-programmers as it is a simple way to accomplish simpler and experimental tasks. It is used for iteration, sequencing, selection, and modularization.
def add(list): sum = 0 for x in list: sum += x return sum print(add(my_list))