目录
1.冒泡排序
python
'''冒泡排序'''
"""
def BubbleSort(nums):
listLength = len(nums)
while listLength > 0:
for i in range(listLength - 1):
if nums[i] > nums[i+1]:
nums[i], nums[i+1] = nums[i+1], nums[i]
listLength -= 1
return nums
"""
def BubbleSort(nums):
for i in range(len(nums)):
for j in range(len(nums) - i - 1):
if nums[j] > nums[j+1]:
nums[j], nums[j+1] = nums[j+1], nums[j]
return nums
nums = [5, 2, 8, 4, 7, 4, 3, 9, 2, 0, 16,1]
print(BubbleSort(nums))2.快速排序
python
'''快速排序'''
def QuickSort(nums, start, end):
if start < end:
i, j = start, end
base = nums[i]
while i < j:
while i < j and nums[j] >= base:
j -= 1
nums[i] = nums[j]
while i < j and nums[i] <= base:
i += 1
nums[j] = nums[i]
nums[i] = base
QuickSort(nums, start, i - 1)
QuickSort(nums, i+1, end)
nums = [9,4,10,8,13,2,15,7]
QuickSort(nums, 0, len(nums)-1)
print(nums)3.插入排序
python
'''插入排序'''
def InsertSort(nums):
for i in range(len(nums)-1):
if nums[i] > nums[i+1]:
while i>=0 and nums[i] > nums[i+1]:
nums[i], nums[i+1] = nums[i+1], nums[i]
i -= 1
return nums
nums = [9,4,10,8,13,2,15,7]
print(InsertSort(nums))4.希尔排序
python
'''希尔排序'''
#①第一层循环 gap折半 直到gap=1
#②二层三层循环直接插入排序
def ShellSort(nums):
gap = len(nums) // 2
while gap >= 1:
for i in range(gap, len(nums)):
for j in range(i-gap, -1, -gap):
if nums[j] > nums[j+gap]:
nums[j], nums[j+gap] = nums[j+gap], nums[j]
gap = gap // 2
return nums
nums = [9,4,10,8,13,2,15,7]
print(ShellSort(nums))5.选择排序
python
'''选择排序'''
def SelectSort(nums):
for i in range(len(nums)):
for j in range(i+1, len(nums)):
if nums[j] < nums[i]:
nums[j], nums[i] = nums[i], nums[j]
return nums
nums = [5, 2, 8, 4, 7, 4, 3, 9, 2, 0, 1,16]
print(SelectSort(nums))6.堆排序
最大堆总是将其中的最大值存放在树的根节点。
而对于最小堆，根节点中的元素总是树中的最小值
应用场景
比如求10亿个数中的最大的前10个数，时时构建只有10个元素的小顶堆，如果比堆顶小，则不处理；如果比堆顶大，则替换堆顶，然后依次下沉到适当的位置。
比如求10亿个数中的最小的前10个数，时时构建只有10个元素的大顶堆，如果比堆顶大，则不处理；如果比堆顶小，则替换堆顶，然后依次下沉到适当的位置。
一般升序采用大顶堆，降序采用小顶堆
python
'''构造大顶堆'''
def HeapBuild(nums):
l = len(nums) - 1
# 构造大顶堆，从非叶子节点开始倒序遍历，因此是l//2 -1 就是最后一个非叶子节点
for i in range(len(nums)//2 - 1, -1, -1):
HeapSort(nums, i, l)
# 上面的循环完成了大顶堆的构造，那么就开始把根节点跟末尾节点交换，然后重新调整大顶堆
for j in range(l, -1, -1):
nums[0], nums[j] = nums[j], nums[0]
HeapSort(nums, 0, j-1)
return nums
def HeapSort(nums, i, l):
left, right = 2 * i + 1, 2 * i + 2 # 左右子节点的下标
index = i
# 构造大顶推
if left <= l and nums[i] < nums[left]:
index = left
if right <= l and nums[left] < nums[right] and nums[i] < nums[right]:
index = right
if index != i:
nums[i], nums[index] = nums[index], nums[i]
HeapSort(nums, index, l)
nums = [17, 13, 40 , 22, 31, 14, 33, 56, 24, 19 ,10, 41, 51, 42, 26]
print('使用大顶堆排序：', HeapBuild(nums))
'''构造小顶堆'''
def SmallHeapBuild(nums):
l = len(nums) - 1
# 从非叶子节点开始倒序遍历，因此是l//2 -1 就是最后一个非叶子节点
for i in range(len(nums)//2 - 1, -1, -1):
SmallHeapSort(nums, i, l) # 小顶堆构造函数
# 上面的循环完成了小顶堆的构造，那么就开始把根节点跟末尾节点交换，然后重新调整大顶堆
# 使用小顶堆进行降序，nums[0]是最小的，放到最后
for j in range(l, -1 ,-1):
nums[0], nums[j] = nums[j], nums[0]
SmallHeapSort(nums, 0, j-1)
return nums
def SmallHeapSort(nums, i, l):
left, right = 2 * i + 1, 2 * i + 2 # 左右子节点的下标
index = i
# 构建小顶堆
if left <= l and nums[i] > nums[left]:
index = left
if right <= l and nums[left] > nums[right] and nums[i] > nums[right]:
index = right
if index != i:
nums[i], nums[index] = nums[index], nums[i]
SmallHeapSort(nums, index, l)
nums = [17, 13, 40 , 22, 31, 14, 33, 56, 24, 19 ,10, 41, 51, 42, 26]
print('使用小顶堆倒排序', SmallHeapBuild(nums))7.归并排序
python
def MergeBuild(nums):
if len(nums) == 1:
return nums
mid = len(nums) // 2
left = nums[:mid]
right = nums[mid:]
l1 = MergeBuild(left)
l2 = MergeBuild(right)
return MergeSort(l1, l2)
def MergeSort(left, right):
res = []
while len(left) and len(right):
if left[0] < right[0]:
res.append(left.pop(0))
else:
res.append(right.pop(0))
res += left
res += right
return res
if __name__ == '__main__':
nums = [5, 2, 8, 4, 7, 4, 3, 9, 2, 0, 1,16]
res = MergeBuild(nums)
print(res)8. 二分查找
python
'''二分查找'''
def BinarySearch(target, nums):
low = 0
high = len(nums)-1
while low <= high:
mid = (low + high) // 2
if nums[mid] == target:
return 'target in nums'
elif nums[mid] < target:
low = mid + 1
else:
high = mid - 1
return 'target not in nums'
nums = [2, 4, 7, 8, 9, 10, 13, 15, 19]
print(BinarySearch(13, nums))
print(BinarySearch(20, nums))