How to implement Merge Sort in Python

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Introduction:

1. Presently the Python is considered as a more powerful language that provides a great tool for data crunching and preparation.

2. The Merge sort is the most common techniques which is being used for arranging the elements in either increasing or decreasing order. It uses the concept of Divide and Conquer technique.

3. When we are going to implement the concept of Merge Sort using Python then it is very easy and more effective.

4. As we know that the Python is basically used to have numerous enriched functionable libraries which may be get used to parse the data which is being written in other languages.

Here, I am going to discuss the Python Merge sort concepts, which will let you know how to use these concepts in programming.

What is Merge Sort in Python?

1. The Merge sort is the most common techniques which is being used for arranging the elements in either increasing or decreasing order.

2. The Merge sort uses the concept of Divide and Conquer technique which is very much effective techniques for Parallel Processing environment.

3. In this technique the list elements to be get sorted, are used to implement the concept of Divide and Conquer technique.

4. In Merge Sort technique as it is based on the divide and conquer algorithm, so we need to divide the list first.

5. Here the list is divided into two halves, then sorted separately and merged back to reach the solution.

6. We are basically using the function merge () for merging the sorted arrays at the last.

Let us consider the following example which will let you know how to write a loop in Python. Mostly in Python 3 when we need to write a loop mechanism then it has to go through the following manner.

The Divide and Conquer approach:

As we have already discussed above that it is a technique in which the list/array is divided

into two equal half and then we are going to apply the conquer technique to find the final sorted list. The basic mechanism is as mentioned below.

1. Here at the first, we need to split the array into two half.

2. After splitting the array, we need to repeat this process into each half until each half is of size 1 or 0.

3. The array of size 1 is trivially sorted.

4. Now the two sorted arrays are combined into one big array.

5. The same process is allowed to be continued until all the elements are combined and the array is sorted.

Let us consider the following example which will let you know how the merge sort process will take place.

Example:

Let the list is {38, 27, 43, 3, 9, 82, 10}

1. At the first the list is get divided as {38, 27, 43, 3} and {9, 82, 10}.

2. After this the list is divided as {38, 27},{43, 3} and { 9, 82},{ 10}.

3. After this the list is divided as {38},{27},{ 43}, {3} and { 9},{ 82},{ 10}.

4. Since at this stage the size becomes 1 now so, the merge processes is now come into action.

5. Here we need to start merging of each individual arrays back till the complete array is merged.

6. So in the first pass the merging is done between {38},{27},{ 43}, {3} and { 9},{ 82}.

7. We get the final array after first pass as {27,38},{3,43} and { 9,82}.

8. At 2nd pass the merged array will be {3,27,38,43} and {9,10,82}.

9. At 3rd pass the final sorted array will be {3,9,10,27,38,43,82}.

Implementing Merge Sort in Python:

If we need to get implement the concept of Merge sort in Python 3 then we need to write the following code as mentioned below. Here I am trying to explain the process in simplest way so that you can understand the concept easily.

Program:

``````def mergeSort(arr):
if len(arr) > 1:

mid = len(arr)//2       	   # Finding the mid element of the array

L = arr[:mid]        	 # Dividing the array elements into two halves
R = arr[mid:]
mergeSort(L) 		# Sorting the first half
mergeSort(R) 		# Sorting the second half
i = j = k = 0
while i < len(L) and j < len(R):   	# Copy data to temp arrays L[] and R[]
if L[i] < R[j]:
arr[k] = L[i]
i += 1
else:
arr[k] = R[j]
j += 1
k += 1
while i < len(L):			# Checking if any element was left
arr[k] = L[i]
i += 1
k += 1
while j < len(R):
arr[k] = R[j]
j += 1
k += 1
def printList(arr): 			# Code to print the list
for i in range(len(arr)):
print(arr[i], end=" ")
print()
***********
if __name__ == '__main__':  		 # Driver Code

arr = [12, 11, 13, 5, 6, 7]
print("Given array is", end="\n")
printList(arr)
mergeSort(arr)
print("Sorted array is: ", end="\n")
printList(arr)
``````

Flowchart for implementation of Merge Sort:

In order to implement the concept of Merge sort we can use the following flow chart as mentioned below.

Flow Chart to implement the Merge Sort.

Advantages and Usage:

Form the above discussion now it is getting clear that it is the technique which is good to implement for sorting the list of elements but to make it better understand in practical way we need to remember the following.

1. The Merge sort is used to access a random element in linear time, but not regular constant time like other algorithms.

2. It is very much easy and fast process but requires more memory spaces.

3. One of the best features of merge sort is its low number of compares.

4. For comparisons it takes O(n * log(n)).

5. Since it uses the divide-and-conquer approach, so it is more convenient and reliable for parallel processing-based programs.

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