Implement Stack using Queues
Last Updated :
25 Mar, 2025
Implement a stack using queues. The stack should support the following operations:
- Push(x): Push an element onto the stack.
- Pop(): Pop the element from the top of the stack and return it.
A Stack can be implemented using two queues. Let Stack to be implemented be 's' and queues used to implement are 'q1' and 'q2'.
Stack 's' can be implemented in two ways:
By making push() operation costly - Push in O(n) and Pop() in O(1)
The idea is to keep newly entered element at the front of 'q1' so that pop operation dequeues from 'q1'. 'q2' is used to move every new element in front of 'q1'.
Follow the below steps to implement the push(s, x) operation:
- Enqueue x to q2.
- One by one dequeue everything from q1 and enqueue to q2.
- Swap the queues of q1 and q2.
Follow the below steps to implement the pop(s) operation:
- Dequeue an item from q1 and return it.
C++
/* Program to implement a stack using
two queue */
#include <bits/stdc++.h>
using namespace std;
class Stack {
// Two inbuilt queues
queue<int> q1, q2;
public:
void push(int x)
{
// Push x first in empty q2
q2.push(x);
// Push all the remaining
// elements in q1 to q2.
while (!q1.empty()) {
q2.push(q1.front());
q1.pop();
}
// swap the names of two queues
swap(q1, q2);
}
void pop()
{
// if no elements are there in q1
if (q1.empty())
return;
q1.pop();
}
int top()
{
if (q1.empty())
return -1;
return q1.front();
}
int size() { return q1.size(); }
};
// Driver code
int main()
{
Stack s;
s.push(1);
s.push(2);
s.push(3);
cout << "current size: " << s.size() << endl;
cout << s.top() << endl;
s.pop();
cout << s.top() << endl;
s.pop();
cout << s.top() << endl;
cout << "current size: " << s.size() << endl;
return 0;
}
/* Java Program to implement a stack using
two queue */
import java.util.*;
class GfG {
static class Stack {
// Two inbuilt queues
static Queue<Integer> q1
= new LinkedList<Integer>();
static Queue<Integer> q2
= new LinkedList<Integer>();
// To maintain current number of
// elements
static int curr_size;
static void push(int x)
{
// Push x first in empty q2
q2.add(x);
// Push all the remaining
// elements in q1 to q2.
while (!q1.isEmpty()) {
q2.add(q1.peek());
q1.remove();
}
// swap the names of two queues
Queue<Integer> q = q1;
q1 = q2;
q2 = q;
}
static void pop()
{
// if no elements are there in q1
if (q1.isEmpty())
return;
q1.remove();
}
static int top()
{
if (q1.isEmpty())
return -1;
return q1.peek();
}
static int size() { return q1.size(); }
}
// driver code
public static void main(String[] args)
{
Stack s = new Stack();
s.push(1);
s.push(2);
s.push(3);
System.out.println("current size: " + s.size());
System.out.println(s.top());
s.pop();
System.out.println(s.top());
s.pop();
System.out.println(s.top());
System.out.println("current size: " + s.size());
}
}
// This code is contributed by Prerna
# Program to implement a stack using
# two queue
from _collections import deque
class Stack:
def __init__(self):
# Two inbuilt queues
self.q1 = deque()
self.q2 = deque()
def push(self, x):
# Push x first in empty q2
self.q2.append(x)
# Push all the remaining
# elements in q1 to q2.
while (self.q1):
self.q2.append(self.q1.popleft())
# swap the names of two queues
self.q1, self.q2 = self.q2, self.q1
def pop(self):
# if no elements are there in q1
if self.q1:
self.q1.popleft()
def top(self):
if (self.q1):
return self.q1[0]
return None
def size(self):
return len(self.q1)
# Driver Code
if __name__ == '__main__':
s = Stack()
s.push(1)
s.push(2)
s.push(3)
print("current size: ", s.size())
print(s.top())
s.pop()
print(s.top())
s.pop()
print(s.top())
print("current size: ", s.size())
# This code is contributed by PranchalK
// C# Program to implement a stack using two queues
using System;
using System.Collections.Generic;
class GfG
{
static class Stack
{
// Two inbuilt queues
static Queue<int> q1 = new Queue<int>();
static Queue<int> q2 = new Queue<int>();
// To maintain current number of elements
static int curr_size;
static void Push(int x)
{
// Push x first in empty q2
q2.Enqueue(x);
// Push all the remaining elements in q1 to q2.
while (q1.Count > 0)
{
q2.Enqueue(q1.Dequeue());
}
// swap the names of two queues
Queue<int> q = q1;
q1 = q2;
q2 = q;
}
static void Pop()
{
// if no elements are there in q1
if (q1.Count == 0)
return;
q1.Dequeue();
}
static int Top()
{
if (q1.Count == 0)
return -1;
return q1.Peek();
}
static int Size() { return q1.Count; }
}
// driver code
public static void Main(string[] args)
{
Stack s = new Stack();
s.Push(1);
s.Push(2);
s.Push(3);
Console.WriteLine("current size: " + s.Size());
Console.WriteLine(s.Top());
s.Pop();
Console.WriteLine(s.Top());
s.Pop();
Console.WriteLine(s.Top());
Console.WriteLine("current size: " + s.Size());
}
}
/*Javascript Program to implement a stack using
two queue */
// Two inbuilt queues
class Stack {
constructor() {
this.q1 = [];
this.q2 = [];
}
push(x) {
// Push x first in isEmpty q2
this.q2.push(x);
// Push all the remaining
// elements in q1 to q2.
while (this.q1.length != 0) {
this.q2.push(this.q1[0]);
this.q1.shift();
}
// swap the names of two queues
this.q = this.q1;
this.q1 = this.q2;
this.q2 = this.q;
}
pop() {
// if no elements are there in q1
if (this.q1.length == 0)
return;
this.q1.shift();
}
top() {
if (this.q1.length == 0)
return -1;
return this.q1[0];
}
size() {
console.log(this.q1.length);
}
isEmpty() {
// return true if the queue is empty.
return this.q1.length == 0;
}
front() {
return this.q1[0];
}
}
// Driver code
let s = new Stack();
s.push(1);
s.push(2);
s.push(3);
console.log("current size: ");
s.size();
console.log(s.top());
s.pop();
console.log(s.top());
s.pop();
console.log(s.top());
console.log("current size: ");
s.size();
// This code is contributed by adityamaharshi21
Outputcurrent size: 3
3
2
1
current size: 1
Time Complexity:
- Push operation: O(n), As all the elements need to be popped out from the Queue (q1) and push them back to Queue (q2).
- Pop operation: O(1), As we need to remove the front element from the Queue.
Auxiliary Space: O(n), As we use two queues for the implementation of a Stack.
By making pop() operation costly - Push in O(1) and Pop() in O(n)
The new element is always enqueued to q1. In pop() operation, if q2 is empty then all the elements except the last, are moved to q2. Finally, the last element is dequeued from q1 and returned.
Follow the below steps to implement the push(s, x) operation:
- Enqueue x to q1 (assuming the size of q1 is unlimited).
Follow the below steps to implement the pop(s) operation:
- One by one dequeue everything except the last element from q1 and enqueue to q2.
- Dequeue the last item of q1, the dequeued item is the result, store it.
- Swap the names of q1 and q2
- Return the item stored in step 2.
C++
// Program to implement a stack
// using two queue
#include <bits/stdc++.h>
using namespace std;
class Stack {
queue<int> q1, q2;
public:
void pop()
{
if (q1.empty())
return;
// Leave one element in q1 and
// push others in q2.
while (q1.size() != 1) {
q2.push(q1.front());
q1.pop();
}
// Pop the only left element
// from q1
q1.pop();
// swap the names of two queues
swap(q1, q2);
}
void push(int x) { q1.push(x); }
int top()
{
if (q1.empty())
return -1;
while (q1.size() != 1) {
q2.push(q1.front());
q1.pop();
}
// last pushed element
int temp = q1.front();
// to empty the auxiliary queue after
// last operation
q1.pop();
// push last element to q2
q2.push(temp);
// swap the two queues names
queue<int> q = q1;
q1 = q2;
q2 = q;
return temp;
}
int size() { return q1.size(); }
};
// Driver code
int main()
{
Stack s;
s.push(1);
s.push(2);
s.push(3);
cout << "current size: " << s.size() << endl;
cout << s.top() << endl;
s.pop();
cout << s.top() << endl;
s.pop();
cout << s.top() << endl;
cout << "current size: " << s.size() << endl;
return 0;
}
/* Java Program to implement a stack
using two queue */
import java.util.*;
class Stack {
Queue<Integer> q1 = new LinkedList<>(),
q2 = new LinkedList<>();
void remove()
{
if (q1.isEmpty())
return;
// Leave one element in q1 and
// push others in q2.
while (q1.size() != 1) {
q2.add(q1.peek());
q1.remove();
}
// Pop the only left element
// from q1
q1.remove();
// swap the names of two queues
Queue<Integer> q = q1;
q1 = q2;
q2 = q;
}
void add(int x) { q1.add(x); }
int top()
{
if (q1.isEmpty())
return -1;
while (q1.size() != 1) {
q2.add(q1.peek());
q1.remove();
}
// last pushed element
int temp = q1.peek();
// to empty the auxiliary queue after
// last operation
q1.remove();
// push last element to q2
q2.add(temp);
// swap the two queues names
Queue<Integer> q = q1;
q1 = q2;
q2 = q;
return temp;
}
int size() { return q1.size(); }
// Driver code
public static void main(String[] args)
{
Stack s = new Stack();
s.add(1);
s.add(2);
s.add(3);
System.out.println("current size: " + s.size());
System.out.println(s.top());
s.remove();
System.out.println(s.top());
s.remove();
System.out.println(s.top());
System.out.println("current size: " + s.size());
}
}
// This code is contributed by Princi Singh
# Program to implement a stack using
# two queue
from _collections import deque
class Stack:
def __init__(self):
# Two inbuilt queues
self.q1 = deque()
self.q2 = deque()
def push(self, x):
self.q1.append(x)
def pop(self):
# if no elements are there in q1
if (not self.q1):
return
# Leave one element in q1 and push others in q2
while(len(self.q1) != 1):
self.q2.append(self.q1.popleft())
# swap the names of two queues
self.q1, self.q2 = self.q2, self.q1
def top(self):
# if no elements are there in q1
if (not self.q1):
return
# Leave one element in q1 and push others in q2
while(len(self.q1) != 1):
self.q2.append(self.q1.popleft())
# Pop the only left element from q1 to q2
top = self.q1[0]
self.q2.append(self.q1.popleft())
# swap the names of two queues
self.q1, self.q2 = self.q2, self.q1
return top
def size(self):
return len(self.q1)
# Driver Code
if __name__ == '__main__':
s = Stack()
s.push(1)
s.push(2)
s.push(3)
print("current size: ", s.size())
print(s.top())
s.pop()
print(s.top())
s.pop()
print(s.top())
print("current size: ", s.size())
# This code is contributed by jainlovely450
using System;
using System.Collections.Generic;
class Stack {
Queue<int> q1 = new Queue<int>();
Queue<int> q2 = new Queue<int>();
void Remove() {
if (q1.Count == 0)
return;
// Leave one element in q1 and
// push others in q2.
while (q1.Count != 1) {
q2.Enqueue(q1.Dequeue());
}
// Pop the only left element
// from q1
q1.Dequeue();
// swap the names of two queues
Queue<int> temp = q1;
q1 = q2;
q2 = temp;
}
void Add(int x) { q1.Enqueue(x); }
int Top() {
if (q1.Count == 0)
return -1;
while (q1.Count != 1) {
q2.Enqueue(q1.Dequeue());
}
// last pushed element
int temp = q1.Peek();
// to empty the auxiliary queue after
// last operation
q1.Dequeue();
// push last element to q2
q2.Enqueue(temp);
// swap the two queues names
Queue<int> q = q1;
q1 = q2;
q2 = q;
return temp;
}
int Size() { return q1.Count; }
// Driver code
public static void Main(string[] args) {
Stack s = new Stack();
s.Add(1);
s.Add(2);
s.Add(3);
Console.WriteLine("current size: " + s.Size());
Console.WriteLine(s.Top());
s.Remove();
Console.WriteLine(s.Top());
s.Remove();
Console.WriteLine(s.Top());
Console.WriteLine("current size: " + s.Size());
}
}
/*Javascript Program to implement a stack using
two queue */
// Two inbuilt queues
class Stack {
constructor() {
this.q1 = [];
this.q2 = [];
}
pop()
{
if (this.q1.length == 0)
return;
// Leave one element in q1 and
// push others in q2.
while (this.q1.length != 1){
this.q2.push(this.q1[0]);
this.q1.shift();
}
// Pop the only left element
// from q1f
this.q1.shift();
// swap the names of two queues
this.q = this.q1;
this.q1 = this.q2;
this.q2 = this.q;
}
push(x) {
// if no elements are there in q1
this.q1.push(x);
}
top() {
if (this.q1.length == 0)
return -1;
while (this.q1.length != 1) {
this.q2.push(this.q1[0]);
this.q1.shift();
}
// last pushed element
let temp = this.q1[0];
// to empty the auxiliary queue after
// last operation
this.q1.shift();
// push last element to q2
this.q2.push(temp);
// swap the two queues names
this.q = this.q1;
this.q1 = this.q2;
this.q2 = this.q;
return temp;
}
size() {
console.log(this.q1.length);
}
isEmpty() {
// return true if the queue is empty.
return this.q1.length == 0;
}
front() {
return this.q1[0];
}
}
// Driver code
let s = new Stack();
s.push(1);
s.push(2);
s.push(3);
console.log("current size: ");
s.size();
console.log(s.top());
s.pop();
console.log(s.top());
s.pop();
console.log(s.top());
console.log("current size: ");
s.size();
// This code is contributed by Susobhan Akhuli
Outputcurrent size: 3
3
2
1
current size: 1
Time Complexity:
- Push operation: O(1), As, on each push operation the new element is added at the end of the Queue.
- Pop operation: O(n), As, on each pop operation, all the elements are popped out from the Queue (q1) except the last element and pushed into the Queue (q2).
Auxiliary Space: O(n) since 2 queues are used.
Using single queue and Recursion Stack
Using only one queue and make the queue act as a Stack in modified way of the above discussed approach.
Follow the below steps to implement the idea:
- The idea behind this approach is to make one queue and push the first element in it.
- After the first element, we push the next element and then push the first element again and finally pop the first element.
- So, according to the FIFO rule of the queue, the second element that was inserted will be at the front and then the first element as it was pushed again later and its first copy was popped out.
- So, this acts as a Stack and we do this at every step i.e. from the initial element to the second last element, and the last element will be the one that we are inserting and since we will be pushing the initial elements after pushing the last element, our last element becomes the first element.
C++
#include <bits/stdc++.h>
using namespace std;
// Stack Class that acts as a queue
class Stack {
queue<int> q;
public:
void push(int data)
{
int s = q.size();
// Push the current element
q.push(data);
// Pop all the previous elements and put them after
// current element
for (int i = 0; i < s; i++) {
// Add the front element again
q.push(q.front());
// Delete front element
q.pop();
}
}
void pop()
{
if (q.empty())
cout << "No elements\n";
else
q.pop();
}
int top() { return (q.empty()) ? -1 : q.front(); }
int size() { return q.size(); }
bool empty() { return (q.empty()); }
};
int main()
{
Stack st;
st.push(1);
st.push(2);
st.push(3);
cout << "current size: " << st.size() << "\n";
cout << st.top() << "\n";
st.pop();
cout << st.top() << "\n";
st.pop();
cout << st.top() << "\n";
cout << "current size: " << st.size();
return 0;
}
import java.util.*;
class Stack {
// One queue
Queue<Integer> q1 = new LinkedList<Integer>();
void push(int x)
{
// Get previous size of queue
int s = q1.size();
// Push the current element
q1.add(x);
// Pop all the previous elements and put them after
// current element
for (int i = 0; i < s; i++) {
q1.add(q1.remove());
}
}
void pop()
{
// if no elements are there in q1
if (q1.isEmpty())
return;
q1.remove();
}
int top()
{
if (q1.isEmpty())
return -1;
return q1.peek();
}
int size() { return q1.size(); }
// driver code
public static void main(String[] args)
{
Stack s = new Stack();
s.push(1);
s.push(2);
s.push(3);
System.out.println("current size: " + s.size());
System.out.println(s.top());
s.pop();
System.out.println(s.top());
s.pop();
System.out.println(s.top());
System.out.println("current size: " + s.size());
}
}
// This code is contributed by Vishal Singh Shekhawat
from _collections import deque
# Stack Class that acts as a queue
class Stack:
def __init__(self):
self.q = deque()
# Push operation
def push(self, data):
# Get previous size of queue
s = len(self.q)
# Push the current element
self.q.append(data)
# Pop all the previous elements and put them after
# current element
for i in range(s):
self.q.append(self.q.popleft())
# Removes the top element
def pop(self):
if (not self.q):
print("No elements")
else:
self.q.popleft()
# Returns top of stack
def top(self):
if (not self.q):
return
return self.q[0]
def size(self):
return len(self.q)
if __name__ == '__main__':
st = Stack()
st.push(1)
st.push(2)
st.push(3)
print("current size: ", st.size())
print(st.top())
st.pop()
print(st.top())
st.pop()
print(st.top())
print("current size: ", st.size())
using System;
using System.Collections;
class GfG {
public class Stack
{
// One inbuilt queue
public Queue q = new Queue();
public void push(int x)
{
// Get previous size of queue
int s = q.Count;
// Push the current element
q.Enqueue(x);
// Pop all the previous elements and put them
// afte current element
for (int i = 0; i < s; i++) {
// Add the front element again
q.Enqueue(q.Peek());
// Delete front element
q.Dequeue();
}
}
// Removes the top element
public void pop()
{
// if no elements are there in q
if (q.Count == 0)
Console.WriteLine("No elements");
else
q.Dequeue();
}
// Returns top of stack
public int top()
{
if (q.Count == 0)
return -1;
return (int)q.Peek();
}
public int size() { return q.Count; }
};
// Driver code
public static void Main(String[] args)
{
Stack st = new Stack();
st.push(1);
st.push(2);
st.push(3);
Console.WriteLine("current size: " + st.size());
Console.WriteLine(st.top());
st.pop();
Console.WriteLine(st.top());
st.pop();
Console.WriteLine(st.top());
Console.WriteLine("current size: " + st.size());
}
}
// This code is contributed by Susobhan Akhuli
// One inbuilt queue
class Stack {
constructor() {
this.q = [];
}
// Push operation
push(data) {
// Get previous size of queue
let s = this.q.length;
// Push the current element
this.q.push(data);
// Pop all the previous elements and put them after
// current element
for (let i = 0; i < s; i++) {
// Add the front element again
this.q.push(this.q[0]);
// Delete front element
this.q.shift();
}
}
// Removes the top element
pop() {
// if no elements are there in q1
if (this.q.length == 0)
console.log("No elements");
else
this.q.shift();
}
top() {
if (this.q.length == 0)
return -1;
return this.q[0];
}
size() {
console.log(this.q.length);
}
isEmpty() {
// return true if the queue is empty.
return this.q.length == 0;
}
front() {
return this.q[0];
}
}
// Driver code
let st = new Stack();
st.push(1);
st.push(2);
st.push(3);
console.log("current size: ");
st.size();
console.log(st.top());
st.pop();
console.log(st.top());
st.pop();
console.log(st.top());
console.log("current size: ");
st.size();
// This code is contributed by Susobhan Akhuli
Outputcurrent size: 3
3
2
1
current size: 1
Time Complexity:
- Push operation: O(n)
- Pop operation: O(1)
Auxiliary Space: O(n) since 1 queue is used.
Stack using two queues | DSA Problem
Similar Reads
Basics & Prerequisites
Data Structures
Array Data StructureIn this article, we introduce array, implementation in different popular languages, its basic operations and commonly seen problems / interview questions. An array stores items (in case of C/C++ and Java Primitive Arrays) or their references (in case of Python, JS, Java Non-Primitive) at contiguous
3 min read
String in Data StructureA string is a sequence of characters. The following facts make string an interesting data structure.Small set of elements. Unlike normal array, strings typically have smaller set of items. For example, lowercase English alphabet has only 26 characters. ASCII has only 256 characters.Strings are immut
2 min read
Hashing in Data StructureHashing is a technique used in data structures that efficiently stores and retrieves data in a way that allows for quick access. Hashing involves mapping data to a specific index in a hash table (an array of items) using a hash function. It enables fast retrieval of information based on its key. The
2 min read
Linked List Data StructureA linked list is a fundamental data structure in computer science. It mainly allows efficient insertion and deletion operations compared to arrays. Like arrays, it is also used to implement other data structures like stack, queue and deque. Here’s the comparison of Linked List vs Arrays Linked List:
2 min read
Stack Data StructureA Stack is a linear data structure that follows a particular order in which the operations are performed. The order may be LIFO(Last In First Out) or FILO(First In Last Out). LIFO implies that the element that is inserted last, comes out first and FILO implies that the element that is inserted first
2 min read
Queue Data StructureA Queue Data Structure is a fundamental concept in computer science used for storing and managing data in a specific order. It follows the principle of "First in, First out" (FIFO), where the first element added to the queue is the first one to be removed. It is used as a buffer in computer systems
2 min read
Tree Data StructureTree Data Structure is a non-linear data structure in which a collection of elements known as nodes are connected to each other via edges such that there exists exactly one path between any two nodes. Types of TreeBinary Tree : Every node has at most two childrenTernary Tree : Every node has at most
4 min read
Graph Data StructureGraph Data Structure is a collection of nodes connected by edges. It's used to represent relationships between different entities. If you are looking for topic-wise list of problems on different topics like DFS, BFS, Topological Sort, Shortest Path, etc., please refer to Graph Algorithms. Basics of
3 min read
Trie Data StructureThe Trie data structure is a tree-like structure used for storing a dynamic set of strings. It allows for efficient retrieval and storage of keys, making it highly effective in handling large datasets. Trie supports operations such as insertion, search, deletion of keys, and prefix searches. In this
15+ min read
Algorithms
Searching AlgorithmsSearching algorithms are essential tools in computer science used to locate specific items within a collection of data. In this tutorial, we are mainly going to focus upon searching in an array. When we search an item in an array, there are two most common algorithms used based on the type of input
2 min read
Sorting AlgorithmsA Sorting Algorithm is used to rearrange a given array or list of elements in an order. For example, a given array [10, 20, 5, 2] becomes [2, 5, 10, 20] after sorting in increasing order and becomes [20, 10, 5, 2] after sorting in decreasing order. There exist different sorting algorithms for differ
3 min read
Introduction to RecursionThe process in which a function calls itself directly or indirectly is called recursion and the corresponding function is called a recursive function. A recursive algorithm takes one step toward solution and then recursively call itself to further move. The algorithm stops once we reach the solution
14 min read
Greedy AlgorithmsGreedy algorithms are a class of algorithms that make locally optimal choices at each step with the hope of finding a global optimum solution. At every step of the algorithm, we make a choice that looks the best at the moment. To make the choice, we sometimes sort the array so that we can always get
3 min read
Graph AlgorithmsGraph is a non-linear data structure like tree data structure. The limitation of tree is, it can only represent hierarchical data. For situations where nodes or vertices are randomly connected with each other other, we use Graph. Example situations where we use graph data structure are, a social net
3 min read
Dynamic Programming or DPDynamic Programming is an algorithmic technique with the following properties.It is mainly an optimization over plain recursion. Wherever we see a recursive solution that has repeated calls for the same inputs, we can optimize it using Dynamic Programming. The idea is to simply store the results of
3 min read
Bitwise AlgorithmsBitwise algorithms in Data Structures and Algorithms (DSA) involve manipulating individual bits of binary representations of numbers to perform operations efficiently. These algorithms utilize bitwise operators like AND, OR, XOR, NOT, Left Shift, and Right Shift.BasicsIntroduction to Bitwise Algorit
4 min read
Advanced
Segment TreeSegment Tree is a data structure that allows efficient querying and updating of intervals or segments of an array. It is particularly useful for problems involving range queries, such as finding the sum, minimum, maximum, or any other operation over a specific range of elements in an array. The tree
3 min read
Pattern SearchingPattern searching algorithms are essential tools in computer science and data processing. These algorithms are designed to efficiently find a particular pattern within a larger set of data. Patten SearchingImportant Pattern Searching Algorithms:Naive String Matching : A Simple Algorithm that works i
2 min read
GeometryGeometry is a branch of mathematics that studies the properties, measurements, and relationships of points, lines, angles, surfaces, and solids. From basic lines and angles to complex structures, it helps us understand the world around us.Geometry for Students and BeginnersThis section covers key br
2 min read
Interview Preparation
Practice Problem