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Quick Sort

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"""
A pure Python implementation of the quick sort algorithm

For doctests run following command:
python3 -m doctest -v quick_sort.py

For manual testing run:
python3 quick_sort.py
"""
from __future__ import annotations

from random import randrange


def quick_sort(collection: list) -> list:
    """A pure Python implementation of quicksort algorithm.

    :param collection: a mutable collection of comparable items
    :return: the same collection ordered in ascending order

    Examples:
    >>> quick_sort([0, 5, 3, 2, 2])
    [0, 2, 2, 3, 5]
    >>> quick_sort([])
    []
    >>> quick_sort([-2, 5, 0, -45])
    [-45, -2, 0, 5]
    """
    # Base case: if the collection has 0 or 1 elements, it is already sorted
    if len(collection) < 2:
        return collection

    # Randomly select a pivot index and remove the pivot element from the collection
    pivot_index = randrange(len(collection))
    pivot = collection.pop(pivot_index)

    # Partition the remaining elements into two groups: lesser or equal, and greater
    lesser = [item for item in collection if item <= pivot]
    greater = [item for item in collection if item > pivot]

    # Recursively sort the lesser and greater groups, and combine with the pivot
    return [*quick_sort(lesser), pivot, *quick_sort(greater)]


if __name__ == "__main__":
    # Get user input and convert it into a list of integers
    user_input = input("Enter numbers separated by a comma:\n").strip()
    unsorted = [int(item) for item in user_input.split(",")]

    # Print the result of sorting the user-provided list
    print(quick_sort(unsorted))
About this Algorithm

Problem Statement

Given an unsorted array of n elements, write a function to sort the array

Approach

  • Make the right-most index value pivot
  • partition the array using pivot value
  • quicksort left partition recursively
  • quicksort right partition recursively

Time Complexity

  • O(n^2) Worst case performance
  • O(n log n) Best-case performance
  • O(n log n) Average performance

Space Complexity

O(log n) Worst case

Founder's Name

Tony Hoare in 1959

Example

arr[] = {10, 80, 30, 90, 40, 50, 70}
Indexes:  0   1   2   3   4   5   6

low = 0, high =  6, pivot = arr[h] = 70
Initialize index of smaller element, i = -1

Traverse elements from j = low to high-1
j = 0 : Since arr[j] <= pivot, do i++ and swap(arr[i], arr[j])
i = 0
arr[] = {10, 80, 30, 90, 40, 50, 70} // No change as i and j
                                     // are same

j = 1 : Since arr[j] > pivot, do nothing
// No change in i and arr[]

j = 2 : Since arr[j] <= pivot, do i++ and swap(arr[i], arr[j])
i = 1
arr[] = {10, 30, 80, 90, 40, 50, 70} // We swap 80 and 30

j = 3 : Since arr[j] > pivot, do nothing
// No change in i and arr[]

j = 4 : Since arr[j] <= pivot, do i++ and swap(arr[i], arr[j])
i = 2
arr[] = {10, 30, 40, 90, 80, 50, 70} // 80 and 40 Swapped
j = 5 : Since arr[j] <= pivot, do i++ and swap arr[i] with arr[j]
i = 3
arr[] = {10, 30, 40, 50, 80, 90, 70} // 90 and 50 Swapped

We come out of loop because j is now equal to high-1.
Finally we place pivot at correct position by swapping
arr[i+1] and arr[high] (or pivot)
arr[] = {10, 30, 40, 50, 70, 90, 80} // 80 and 70 Swapped

Now 70 is at its correct place. All elements smaller than
70 are before it and all elements greater than 70 are after
it.

Code Implementation Links

Video Explanation

A video explaining the Quick Sort Algorithm