Algorithm Guidecomplexity: O(n log n)

Quick Sort

A fast, efficient divide-and-conquer algorithm that sorts by partitioning the array around a pivot. It underlies the built-in sort in most languages.

01 Explore How It Works

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Quick Sort

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Logic Node1 / 26

Live Python

1def quick_sort(arr, low, high):

# low: 0, high: 5

2 if low < high:

3 pi = partition(arr, low, high)

4 quick_sort(arr, low, pi - 1)

5 quick_sort(arr, pi + 1, high)

7def partition(arr, low, high):

8 pivot = arr[high]

9 i = low - 1

10 for j in range(low, high):

11 if arr[j] <= pivot:

12 i += 1

13 arr[i], arr[j] = arr[j], arr[i]

14 arr[i+1], arr[high] = arr[high], arr[i+1]

15 return i + 1

02 Understand It Simply

For Everyone

🔑Analogy

Pick a pivot, split into a 'smaller' and 'larger' side, then split each side again.

💡In Plain Words

Partitions values smaller than the pivot to the left and larger to the right, then sorts recursively.

Averages O(n log n) — very fast.

📍Where It's Used

–General-purpose sorting (most standard libraries)
–large datasets

03 Python Implementation

A clean, readable reference implementation of the core logic of Quick Sort.

core_implementation.py

def quick_sort(arr, low, high):
    if low < high:
        pi = partition(arr, low, high)
        quick_sort(arr, low, pi - 1)
        quick_sort(arr, pi + 1, high)

def partition(arr, low, high):
    pivot = arr[high]
    i = low - 1
    for j in range(low, high):
        if arr[j] <= pivot:
            i += 1
            arr[i], arr[j] = arr[j], arr[i]
    arr[i+1], arr[high] = arr[high], arr[i+1]
    return i + 1