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The Single Responsibility Principle

“A class should have one, and only one, reason to change”

import numpy as np

def math_operations(list_):
    # Compute Average
    print(f"the mean is {np.mean(list_)}")
    # Compute Max
    print(f"the max is {np.max(list_)}") 

math_operations(list_ = [1,2,3,4,5])
# the mean is 3.0
# the max is 5

Having a single function do all the work is a bad approach

split the function math_operations into atomic functions

Make a single function (or class), generically named, "main". This will call all the other functions one-by-one in a step-to-step process.

def get_mean(list_):
    '''Compute Mean'''
    print(f"the mean is {np.mean(list_)}") 

def get_max(list_):
    '''Compute Max'''
    print(f"the max is {np.max(list_)}") 

def main(list_): 
    # Compute Average
    get_mean(list_)
    # Compute Max
    get_max(list_)

main([1,2,3,4,5])
# the mean is 3.0
# the max is 5

The result of this simple action is that now:

  • It is easier to localize errors. Any error in execution will point out to a smaller section of your code, accelerating your debug phase.
  • Any part of the code is reusable in other section of your code.
  • Moreover and, often overlooked, is that it is easier to create testing for each function of your code.
    • Side note on testing: You should write tests before you actually write the script. But, this is often ignored in favor of creating some nice result to be shown to the stakeholders instead.
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