Python Quick Sort
Table of contents
What is Quick Sort Algorithm
Quick sort is an efficient sorting algorithm. Its basic idea is to divide a large array into two smaller sub-arrays, all elements in one sub-array are smaller than the elements in the other sub-array, and then recursively sort the two sub-arrays. sub-array. Because it is a divide and conquer algorithm, it is recursive and has high efficiency.
Python implements quick sort
It is also very simple to use Python to implement quick sort. The following is the code for Python quick sort:
def quick_sort(arr):
if len(arr) <= 1:
return arr
pivot = arr[len(arr)//2]
left = [x for x in arr if x < pivot]
middle = [x for x in arr if x == pivot]
right = [x for x in arr if x > pivot]
return quick_sort(left) + middle + quick_sort(right)
In the above code, we define a function quick_sort whose parameter is the list arr to be sorted. In the function, first judge whether the length of the list is less than or equal to 1, and if so, return the list directly (recursion boundary). Otherwise, we take the element in the middle of the list as the pivot point, and use a list comprehension to split the list into three parts: elements less than pivot, elements equal to pivot, and elements greater than pivot. We then recursively sort the left and right subarrays and merge the sorted results.
Time Complexity of Quick Sort
The time complexity of quick sort depends on the depth of recursion and the number of elements in each division. Its average time complexity is O(n*logn), and the worst case time complexity is O(n^2). The worst case here means that the choice of the reference point leads to the worst division situation. In practical applications, the average time complexity of the quick sort algorithm is usually better than other sorting algorithms, so it is widely used