def nextGreaterElements(self, nums: List[int]) -> List[int]:
"""
核心：
1.单调栈
2.利用取模运算(%)获得环形特效，解决环形数组
"""
monotonous_stack = Stack()
nums_len = len(nums)
res_lis = [-1] * nums_len
# 将 nums2 的所有元素，倒序入单调栈
for i in range(nums_len * 2 - 1, -1, -1):
index = i % nums_len
# 1.维护单调栈
while not monotonous_stack.is_empty(
) and nums[index] >= monotonous_stack.peek():
monotonous_stack.pop()
# 2.利用栈
res_lis[index] = monotonous_stack.peek() if monotonous_stack.peek(
) is not None else -1
# 3.单调栈入栈
monotonous_stack.push(nums[index])
return res_lis
def reverseStack(self, s: Stack) -> Stack:
# 递归边界
if s.is_empty() or s.size == 1:
return s
# 将底部元素移到顶部
self.move_bottom_to_top(s)
# 该栈 pop 出一个元素并记录在 top 中，形成子栈，并递归调用翻转方法
top = s.pop()
s = self.reverseStack(s)
# 翻转后的子栈，push 原来的 top 元素
s.push(top)
return s
def nextGreaterElement(self, nums1: List[int],
nums2: List[int]) -> List[int]:
"""核心：单调栈"""
monotonous_stack = Stack() # 单调栈,单调递减
memory_dic = {}
# 将 nums2 的所有元素，倒序入单调栈
for i in range(len(nums2) - 1, -1, -1):
# 1.维护单调栈--[将单调栈中 <= 当前元素(nums2[i])的元素，全部 pop 出去]
while not monotonous_stack.is_empty(
) and nums2[i] >= monotonous_stack.peek():
monotonous_stack.pop()
# 2.使用单调栈--[根据单调栈的栈顶元素(stack.peek()),获取值]
memory_dic[nums2[i]] = -1 if monotonous_stack.is_empty(
) else monotonous_stack.peek()
# 3.元素入栈
monotonous_stack.push(nums2[i])
return [memory_dic.get(item) for item in nums1]
def dailyTemperatures(self, T: List[int]) -> List[int]:
"""
核心：
1.单调栈
2.单调栈记录特殊数组 [val, index]
:param T:
:return:
"""
t_len = len(T)
res_lis = [0] * t_len
stack = Stack() # stack 记录特殊数组 [值, 位置index]
for i in range(t_len - 1, -1, -1):
# 1.维护单调栈
while not stack.is_empty() and T[i] >= stack.peek()[0]:
stack.pop()
# 2.利用单调栈
res_lis[i] = 0 if stack.peek() is None else stack.peek()[1] - i
# 3.元素 push 进入单调栈
stack.push([T[i], i])
return res_lis
def __init__(self):
self.s1 = Stack() # 用于入队
self.s2 = Stack() # 用于出队
class MyQueue:
"""核心：使用两个栈，分别主要用于入队、出队"""
def __init__(self):
self.s1 = Stack() # 用于入队
self.s2 = Stack() # 用于出队
def moves_items(self):
"""pop all items form s1 and push them to s2"""
while not self.s1.is_empty():
self.s2.push(self.s1.pop())
def push(self, x: int) -> None:
self.s1.push(x)
def pop(self) -> int:
if self.s2.is_empty():
self.moves_items()
return self.s2.pop()
def peek(self) -> int:
if self.s2.is_empty():
self.moves_items()
return self.s2.peek()
def empty(self) -> bool:
return self.s1.is_empty() and self.s2.is_empty()
@staticmethod
def move_bottom_to_top(s: Stack):
s.items.append(s.items.pop(0))
def reverseStack(self, s: Stack) -> Stack:
# 递归边界
if s.is_empty() or s.size == 1:
return s
# 将底部元素移到顶部
self.move_bottom_to_top(s)
# 该栈 pop 出一个元素并记录在 top 中，形成子栈，并递归调用翻转方法
top = s.pop()
s = self.reverseStack(s)
# 翻转后的子栈，push 原来的 top 元素
s.push(top)
return s
if __name__ == "__main__":
solution = Solution()
stack = Stack()
for i in range(5):
stack.push(i)
stack = solution.reverseStack(stack)
for i in range(10):
print(stack.pop())
pass
def largestRectangleArea(self, heights: List[int]) -> int:
"""
单调栈(单增): 保持栈顶为当前栈最大元素
我们在缓存数据的时候，是从左向右缓存的，
我们计算出一个结果的顺序是从右向左的，并且计算完成以后我们就不再需要了，
符合后进先出的特点。因此，我们需要的这个作为缓存的数据结构就是栈。
"""
lis_len = len(heights)
max_area = 0
stack = Stack()
for i in range(lis_len):
while not stack.is_empty() and heights[i] < stack.peek()[1]:
index, cur_height = stack.pop()
# 处理相等的特殊情况
while not stack.is_empty() and heights[i] == stack.peek():
stack.pop()
if stack.is_empty():
cur_width = i
else:
cur_width = i - stack.peek()[0] - 1
max_area = max(max_area, cur_height * cur_width)
stack.push([i, heights[i]])
while not stack.is_empty():
index, cur_height = stack.pop()
while not stack.is_empty() and cur_height == stack.peek()[1]:
stack.pop()
if stack.is_empty():
cur_width = lis_len
else:
cur_width = lis_len - stack.peek()[0] - 1
max_area = max(max_area, cur_height * cur_width)
return max_area
def __init__(self):
self._stack = Stack()
self._min_stack = Stack() # 使用辅助栈，来记录当前最小值
class MinStack:
def __init__(self):
self._stack = Stack()
self._min_stack = Stack() # 使用辅助栈，来记录当前最小值
def push(self, x: int) -> None:
self._stack.push(x)
# min_stack push 当前栈最小值
if self._min_stack.peek() is None:
self._min_stack.push(x)
else:
self._min_stack.push(min(x, self._min_stack.peek()))
def pop(self) -> None:
self._stack.pop()
self._min_stack.pop()
def top(self) -> int:
return self._stack.peek()
def getMin(self) -> int:
return self._min_stack.peek()