题目:
思路就是做个排序,要求时间复杂度
O
(
n
log
n
)
O(n\log n)
O(nlogn),因此选用快排。代码:
class Solution:
def quickSort(self, a, start, end):
if start >= end:
return
val = a[start]
low = start
high = end
while low < high:
while low < high and a[high] >= val:
high -= 1
a[low] = a[high]
while low < high and a[low] < val:
low += 1
a[high] = a[low]
a[low] = val
self.quickSort(a, start, low-1)
self.quickSort(a, low+1, end)
def findKth(self , a: List[int], n: int, K: int) -> int:
# write code here
self.quickSort(a, 0, n-1)
return a[-K]
题目
比较简单,之前也做过,直接用的循环遍历,但本次要求时间复杂度为
O
(
n
log
n
)
O(n\log n)
O(nlogn),循环遍历会超时,参考了下解题思路,用字典做hashmap的方式,代码:
class Solution:
def twoSum(self , numbers: List[int], target: int) -> List[int]:
# write code here
# for i in range(len(numbers)-1):
# for j in range(i+1, len(numbers)):
# if numbers[i] + numbers[j] == target:
# return [i+1, j+1]
# return []
hash_map = {}
for i in range(len(numbers)):
tmp = target - numbers[i]
if tmp in hash_map:
return [hash_map[tmp]+1, i+1]
elif numbers[i] not in hash_map:
hash_map[numbers[i]] = i
return []
题目:
这个题也是很简单的类型,因为输入就已经排好序了,只要遍历一下链表就可以了。代码:
class Solution:
def Merge(self , pHead1: ListNode, pHead2: ListNode) -> ListNode:
# write code here
if not pHead1 and not pHead2:
return None
if not pHead1:
return pHead2
if not pHead2:
return pHead1
newHead = pHead1 if pHead1.val < pHead2.val else pHead2
newCur = newHead
cur1 = pHead1.next if pHead1.val < pHead2.val else pHead1
cur2 = pHead2 if pHead1.val < pHead2.val else pHead2.next
while cur1 and cur2:
if cur1.val < cur2.val:
newCur.next = cur1
cur1 = cur1.next
else:
newCur.next = cur2
cur2 = cur2.next
newCur = newCur.next
if cur1:
newCur.next = cur1
if cur2:
newCur.next = cur2
return newHead
题目:
这个题不知道是不是有什么不给用的坑,反正我直接只用了一个栈,过于简单有些怀疑是不是理解有偏差。代码:
class Solution:
def __init__(self):
self.stack1 = []
self.stack2 = []
def push(self, node):
# write code here
self.stack1.append(node)
def pop(self):
return self.stack1.pop(0)
# return xx