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# How to implement QuickSort in Python

QuickSort is an in-place sorting algorithm with worst-case time complexity of $n^{2}$.

## Implementation

QuickSort can be implemented both iteratively and recursively. We’ll mainly focus on the recursive implementation, as it is far more convenient, intuitive, and simplistic – iterative implementation is generally unrecommended. Arrays are used as an example here, but QuickSort can be implemented on other data structures (like linked lists) as well.

The algorithm can be broken down into three parts​​:

1. Partitioning the array about the pivot.
2. Passing the smaller arrays to the recursive calls.
3. Joining the sorted arrays that are returned from the recursive call and the pivot.
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In the above illustration, we used the first element of the array as a pivot, even though any of the elements could​ be taken​.

## Code

def QuickSort(arr):

elements = len(arr)

#Base case
if elements < 2:
return arr

current_position = 0 #Position of the partitioning element

for i in range(1, elements): #Partitioning loop
if arr[i] <= arr[0]:
current_position += 1
temp = arr[i]
arr[i] = arr[current_position]
arr[current_position] = temp

temp = arr[0]
arr[0] = arr[current_position]
arr[current_position] = temp #Brings pivot to it's appropriate position

left = QuickSort(arr[0:current_position]) #Sorts the elements to the left of pivot
right = QuickSort(arr[current_position+1:elements]) #sorts the elements to the right of pivot

arr = left + [arr[current_position]] + right #Merging everything together

return arr

array_to_be_sorted = [4,2,7,3,1,6]
print("Original Array: ",array_to_be_sorted)
print("Sorted Array: ",QuickSort(array_to_be_sorted))

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