The space complexity is O(n), where n is the number of elements in the queue. pop() and peek() have a time complexity of O(1). Return not self.inputStack Time Complexity # Return True if inputStack is empty, False otherwise # Pop all elements from outputStack and push them back onto inputStack # Pop all elements from inputStack and push them onto outputStack For empty(), return True if inputStack is empty, False otherwise.For peek(), return the top element of inputStack.For pop(), simply pop the top element from inputStack.Pop all elements from outputStack and push them back onto inputStack. For push(x), pop all elements from inputStack and push them onto outputStack.The idea is to make the pop operation efficient instead of the push operation. This approach is the reverse of the first approach. Approach 2: Two Stacks with O(1) Pop Operation pop() and peek() have an amortized time complexity of O(1) because each element is moved from inputStack to outputStack once.push(x) has an amortized time complexity of O(1).Return not self.inputStack and not self.outputStack Time Complexity # Return True if both stacks are empty, False otherwise # Similar to pop, but instead of popping return the top element of outputStack # If outputStack is empty, pop all elements from inputStack and push them onto outputStack For empty(), return True if both stacks are empty, False otherwise.For peek(), similar to pop(), but instead of popping, return the top element of outputStack.Then, pop the top element from outputStack. For pop(), if outputStack is empty, pop all elements from inputStack and push them onto outputStack.For push(x), simply push x onto inputStack.inputStack is used to make the push operation efficient, while outputStack is used for the pop and peek operations. We can use two stacks, namely inputStack and outputStack. Elements are added (pushed) and removed (popped) from the top.Īpproach 1: Two Stacks with Amortized O(1) Push Operation Stack: A stack is a linear data structure that follows a Last In First Out (LIFO) order for accessing elements.Elements are added (enqueued) to the back and removed (dequeued) from the front. Queue: A queue is a linear data structure that follows a First In First Out (FIFO) order for accessing elements.empty(): Return True if the queue is empty, False otherwise.īefore we delve into the solutions, let’s briefly discuss what queues and stacks are:.peek(): Return the element at the front of the queue without removing it.pop(): Remove the element from the front of the queue and return it.push(x): Add an element x to the back of the queue.The implemented queue should support all the functions of a normal queue ( push, pop, peek, and empty). Implement a first in first out (FIFO) queue using only two stacks. The problem requires you to implement a queue using instances of stack data structure. Additionally, we will evaluate the time and space complexities of each approach. In this extensive article, we will discuss the problem statement, understand the concept of queue and stack, and explore various approaches to implement a queue using stacks in Python. The task focuses on testing one’s ability to manipulate and efficiently use fundamental data structures. It falls under the category of data structures and is often asked in coding interviews. The “Implement Queue using Stacks” is a classical problem which can be found on LeetCode.
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