This is an insertion sort algorithm implemented in Python.

insertionSort.py

import random as rd

''' Complexity : O(n^2) 
    In the worst case, the function looks and inverse the elements
    (n * (n-1))/2 times. (Reverse order situation)
    ~1/2N^2 compares and ~1/2N^2 exchanges.
    In the best case, the array is sorted. So, we do not make any
    inversion operation. We just iterates the array n times and
    makes N-1 compares. So, our complexity is O(n).
    On average case, insertion sort uses ~1/4N^2 compares and
    ~1/4N^2 exchanges.
    '''
    
def insertion_sort(arr):
    
    for i in range(len(arr)):   # Iterates the all list

        tmp = arr[i]            # Temporary variable for comparing elements in while loop
        j = i

        # If index of j is bigger than 1 and tmp variable is lower than
        # previous element of the current element
        while j > 0 and tmp < arr[j-1]: 
            arr[j] = arr[j-1]   # Changes the elements
            j -= 1              # Decrease the index for looking at previous element
        
        arr[j] = tmp
    print(arr)

# Test

for _ in range(5):
    arr = [rd.randint(0,20) for _ in range(10)]
    insertion_sort(arr)