Leetcode #225: Implement Stack using Queues
In this guide, we solve Leetcode #225 Implement Stack using Queues in Python and focus on the core idea that makes the solution efficient.
You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.
Problem Statement
Implement a last-in-first-out (LIFO) stack using only two queues. The implemented stack should support all the functions of a normal stack (push, top, pop, and empty).
Quick Facts
- Difficulty: Easy
- Premium: No
- Tags: Stack, Design, Queue
Intuition
The problem has a natural nested or last-in-first-out structure.
A stack lets us resolve matches in the correct order as we scan.
Approach
Push items as they appear and pop when you can finalize a decision.
The stack captures the unresolved part of the input.
Steps:
- Push elements as you scan.
- Pop when a rule or match is satisfied.
- Use the stack to compute results.
Example
Input
["MyStack", "push", "push", "top", "pop", "empty"]
[[], [1], [2], [], [], []]
Output
[null, null, null, 2, 2, false]
Explanation
MyStack myStack = new MyStack();
myStack.push(1);
myStack.push(2);
myStack.top(); // return 2
myStack.pop(); // return 2
myStack.empty(); // return False
Python Solution
class MyStack:
def __init__(self):
self.q1 = deque()
self.q2 = deque()
def push(self, x: int) -> None:
self.q2.append(x)
while self.q1:
self.q2.append(self.q1.popleft())
self.q1, self.q2 = self.q2, self.q1
def pop(self) -> int:
return self.q1.popleft()
def top(self) -> int:
return self.q1[0]
def empty(self) -> bool:
return len(self.q1) == 0
# Your MyStack object will be instantiated and called as such:
# obj = MyStack()
# obj.push(x)
# param_2 = obj.pop()
# param_3 = obj.top()
# param_4 = obj.empty()
Complexity
The time complexity is . The space complexity is , where is the number of elements in the stack.
Edge Cases and Pitfalls
Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.
Summary
This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.