搜索与排序

（一）二分搜素

Binary Search (iterative):

def bi_search_iter(alist, item):
    left, right = 0, len(alist) - 1
    while left <= right:
        mid = (left + right) // 2
        if alist[mid] < item:
            left = mid + 1
        elif alist[mid] > item:
            right = mid - 1
        else: # alist[mid] = item
            return mid
    return -1

Binary Search (recursive):

def bi_search_re(num_list, val):
    def bi_search(l, h):
        # Not found
        if l > h:
            return -1
        
        # Check mid
        mid = (l + h) // 2
        if (num_list[mid] == val):
            return mid;
        elif (num_list[mid] < val):
            return bi_search(mid + 1, h)
        else:
            return bi_search(l, mid - 1)
        
    return bi_search(0, len(num_list))

（二）排序

1. 冒泡排序

稳定的排序

O(n^2)

def _bubble_sort(nums: list):
    for i in range(len(nums)-1):
        # Get (i+1) largest in the correct position
        for j in range(len(nums) - i - 1):
            if nums[j] > nums[j + 1]:
                nums[j], nums[j + 1] = nums[j + 1], nums[j]

优化：

def bubble_sort_mod(array):
    for i in range(len(nums)-1):
        is_sorted = True 
        for j in range(len(nums) - i - 1):
            if nums[j] > nums[j + 1]:
                nums[j], nums[j + 1] = nums[j + 1], nums[j]  
                is_sort = False
        if is_sorted:break

2. 选择排序

不稳定的排序

O(n^2)

def selection_sort(items):
    for i in range(len(items)-1):   # n
        pos_min = i   #idx
        for j in range(i + 1, len(items)):  # n
            if (items[j] < items[pos_min]):
                pos_min = j
        items[i], items[pos_min] = items[pos_min], items[i]

数据结构python实现（三） 搜索与排序

原文：https://www.cnblogs.com/gdy1993/p/13068778.html