Python program to implement Selection Sort

# Selection Sort

import random
import math

c = 0 # Counter for Runtime Complexity
a = [] # List of elements
n = 0 # No. of elements

def getdata_random(): # Random Input
    for i in range(n):
        a.append(random.randint(1,n))

def getdata_sorted(): # Sorted Input
    for i in range(n):
        a.append(i+1)
            
def getdata_reverse(): # Reverse Sorted Input
    for i in range(n):
        a.append(n-i)
  
def showdata(): # Display all elements
    for i in range(n):
        print(a[i],"\t",end="")
 
def find_max_pos(last): # Return position of max element
    global c
    max_val=a[0]
    max_pos=0
    for i in range(1,last+1):
        c=c+1
        if a[i]>max_val:
            max_val=a[i]
            max_pos=i                
    return(max_pos)
    
def selection_sort(): # Selection Sort Block
    global c
    for i in range(n-1,0,-1):
        c=c+1
        max_pos = find_max_pos(i)
        temp=a[i]
        a[i] = a[max_pos]
        a[max_pos] = temp


# __________________________ Main Block Starts __________________________
print("\t\t\t____Selection sort____")
n = int(input("\nEnter number of elements: "))
print("\n1.Best Case\t2.Average Case\t3.Worst Case")
ch = int(input("\tEnter your choice: "))

if ch == 1: # Best Case
    getdata_sorted()
    print("\nBefore sorting: ")
    showdata()
    selection_sort()
    print("\nAfter sorting: ")
    showdata()
    print("Theoretical Complexity: ", n)

elif ch == 2: # Average Case
    getdata_random()
    print("\nBefore sorting: ")
    showdata()
    selection_sort()
    print("\nAfter sorting: ")
    showdata()
    print("Theoretical complexity: ",(n*n))

elif ch == 3: # Worst Case
    getdata_reverse()
    print("\nBefore sorting: ")
    showdata()
    selection_sort()
    print("\nAfter sorting: ")
    showdata()
    print("Theoretical complexity: ", (n*n))
 
else:
    print("\nInvalid Choice!")
 
print("Runtime Complexity: ", c)

Output