Implementing the QuickSort Algorithm in Python

Quick Sort is based on the "divide and conquer" principle, with the core being selecting a pivot value to partition the array and recursively sorting the subarrays. The basic idea is: select a pivot value (e.g., the first element of the array), partition the array into two parts—elements less than and greater than the pivot—and then recursively process the subarrays. The partitioning process is critical: using left and right pointers to traverse, the right pointer moves left to find elements smaller than the pivot, while the left pointer moves right to find elements larger than the pivot. After swapping these elements, the process continues until the pointers meet. The pivot is then swapped to its final position, completing the partition. In Python implementation, the `partition` function determines the pivot position, and `quick_sort` recursively processes the left and right subarrays. Test code verifies the sorting effect. Complexity: Average case O(n log n) (when partitioning is balanced), worst case O(n²) (e.g., sorted arrays with the pivot chosen as the first element, which can be optimized by randomly selecting the pivot). Quick Sort is an efficient and practical sorting algorithm widely applied in real-world scenarios. Understanding its partitioning logic and recursive process is key to mastering sorting algorithms.