用于迭代快速排序的Python程序

# Python program for implementation of Quicksort 
  
# This function is same in both iterative and recursive
def partition(arr,l,h):
    i = ( l - 1 )
    x = arr[h]
  
    for j in range(l , h):
        if   arr[j] <= x:
  
            # increment index of smaller element
            i = i+1
            arr[i],arr[j] = arr[j],arr[i]
  
    arr[i+1],arr[h] = arr[h],arr[i+1]
    return (i+1)
  
# Function to do Quick sort
# arr[] --> Array to be sorted,
# l  --> Starting index,
# h  --> Ending index
def quickSortIterative(arr,l,h):
  
    # Create an auxiliary stack
    size = h - l + 1
    stack = [0] * (size)
  
    # initialize top of stack
    top = -1
  
    # push initial values of l and h to stack
    top = top + 1
    stack[top] = l
    top = top + 1
    stack[top] = h
  
    # Keep popping from stack while is not empty
    while top >= 0:
  
        # Pop h and l
        h = stack[top]
        top = top - 1
        l = stack[top]
        top = top - 1
  
        # Set pivot element at its correct position in
        # sorted array
        p = partition( arr, l, h )
  
        # If there are elements on left side of pivot,
        # then push left side to stack
        if p-1 > l:
            top = top + 1
            stack[top] = l
            top = top + 1
            stack[top] = p - 1
  
        # If there are elements on right side of pivot,
        # then push right side to stack
        if p+1 < h:
            top = top + 1
            stack[top] = p + 1
            top = top + 1
            stack[top] = h
  
# Driver code to test above
arr = [4, 3, 5, 2, 1, 3, 2, 3]
n = len(arr)
quickSortIterative(arr, 0, n-1)
print ("Sorted array is:")
for i in range(n):
    print ("%d" %arr[i]),
  
# This code is contributed by Mohit Kumra

输出：

Sorted array is:
1 2 2 3 3 3 4 5

上述递归快速排序的优化也可以应用于迭代版本。

1）递归和迭代的分区过程相同。选择最佳枢轴的相同技术也可以应用于迭代版本。

2）为了减少堆栈大小，首先压入较小一半的索引。

3) 当大小减小到实验计算的阈值以下时，使用插入排序。
有关详细信息，请参阅有关迭代快速排序的完整文章！