How Do You Build a Merge Sort Algorithm?

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In-Depth on the Merge Sort Algorithm

This divide-and-conquer strategy uses division to separate a list of numbers into equal parts, and these are then recursively sorted before being recombined to generate a sorted list.

In essence, this Python program continues to recursively divide the list until it reaches the base case.

At this point it begins sorting the smaller parts of the problem, resulting in smaller sorted arrays that are recombined to eventually generate a fully sorted array. If you’re familiar with Big O notation, you’ll be curious to know that Merge Sort has a Big O of (n logn).

So how do you build this Python project? Here’s the code.

Merge Sort

def merge_sort(a_list):
   print("Dividing ", a_list)
   if len(a_list) > 1:
       mid_point = len(a_list)//2
       left_half = a_list[:mid_point]
       right_half = a_list[mid_point:]



       while i < len(left_half) and j < len(right_half):
           if left_half[i] <= right_half[j]:
               a_list[k] = left_half[i]
               i += 1
               a_list[k] = right_half[j]
               j += 1
           k += 1

       while i < len(left_half):
           a_list[k] = left_half[i]
           i += 1
           k += 1

       while j < len(right_half):
           a_list[k] = right_half[j]
           j += 1
           k += 1
   print("Merging ", a_list)

if __name__ == '__main__':
   a_list = [45, 7, 85, 24, 60, 25, 38, 63, 1]

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