text: class MinStack:
  
      def __init__(self):
          """
          initialize your knn and naive bayes structure here.
          """
          self.stk = []
          self.min_stk = []
  
      def push(self, x: int) -> None:
          self.stk.append(x)
          if len(self.min_stk)== 0 or x <= self.min_stk[-1]:
              self.min_stk.append(x)
              print(self.min_stk[-1])
              print(self.min_stk)
  
      def pop(self) -> None:
          x = self.stk.pop()
          if x == self.min_stk[-1]:
              self.min_stk.pop()
  
      def top(self) -> int:
          if len(self.stk) != 0:
              return self.stk[-1]
  
      def getMin(self) -> int:
          if len(self.min_stk) != 0:
              return self.min_stk[-1]
  
  # Your MinStack object will be instantiated and called as such:
  # obj = MinStack()
  # obj.push(x)
  # obj.pop()
  # param_3 = obj.top()
  # param_4 = obj.getMin()
  
  
  ls = [1,2,3,4,5,6,7,8]
  print(ls[-1])