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Implement Queue using Stacks

#00ff00 Easy

Implement a first in first out (FIFO) queue using only two stacks. The implemented queue should support all the functions of a normal queue (push, peek, pop, and empty).

Implement the MyQueue class:

  • void push(int x) Pushes element x to the back of the queue.
  • int pop() Removes the element from the front of the queue and returns it.
  • int peek() Returns the element at the front of the queue.
  • boolean empty() Returns true if the queue is empty, false otherwise.

Notes:

  • You must use only standard operations of a stack, which means only push to top, peek/pop from top, size, and is empty operations are valid.
  • Depending on your language, the stack may not be supported natively. You may simulate a stack using a list or deque (double-ended queue) as long as you use only a stack's standard operations.

Example 1:

Input
["MyQueue", "push", "push", "peek", "pop", "empty"]
[[], [1], [2], [], [], []]
Output
[null, null, null, 1, 1, false]

Explanation
MyQueue myQueue = new MyQueue();
myQueue.push(1); // queue is: [1]
myQueue.push(2); // queue is: [1, 2] (leftmost is front of the queue)
myQueue.peek(); // return 1
myQueue.pop(); // return 1, queue is [2]
myQueue.empty(); // return false

Constraints:

  • $1$ <= x <= $9$
  • At most 100 calls will be made to push, pop, peek, and empty.
  • All the calls to pop and peek are valid.

Follow-up: Can you implement the queue such that each operation is amortized $O(1)$ time complexity? In other words, performing n operations will take overall O(n) time even if one of those operations may take longer.

Problem can be found in here!

Solution

class MyQueue:
    def __init__(self):
        self.in_stack = []
        self.out_stack = []

    def push(self, x: int) -> None:
        self.in_stack.append(x)

    def pop(self) -> int:
        self.peek()
        return self.out_stack.pop()

    def peek(self) -> int:
        if not self.out_stack:
            while self.in_stack:
                self.out_stack.append(self.in_stack.pop())
        return self.out_stack[-1]

    def empty(self) -> bool:
        return not (self.in_stack or self.out_stack)

Amortized Time Complexity: $O(1)$, Space Complexity: $O(1)$