Stacks vs. Queues

Building Blocks of Program Flow

Introduction

Every programmer, from novice to ninja, eventually meets two key data structures: Stacks and Queues. They’re deceptively simple — but incredibly powerful. Understanding them is essential for managing program state, controlling flow, and solving real-world problems.

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What Is a Stack?

A stack is a linear data structure that follows the Last In, First Out (LIFO) principle. Imagine stacking plates — the last one you put on top is the first one you remove.

🧠 Use Cases:

• Undo/redo functionality
• Function call tracking (call stacks)
• Syntax parsing (e.g., brackets, expressions)

Operations:

• push(item): Add item to the top
• pop(): Remove the top item
• peek(): View the top item without removing it

Time Complexity:

• Push, Pop, Peek: O(1)

Python Stack Example

stack = []
stack.append("A")
stack.pop()

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What Is a Queue?

A queue is a linear structure that follows the First In, First Out (FIFO) principle — like waiting in line at a coffee shop.

🧠 Use Cases:

• Task scheduling
• Printer jobs
• Real-time streaming or buffering

Operations:

• enqueue(item): Add item at the end
• dequeue(): Remove item from the front
• peek(): View the front item without removing it

Time Complexity:

• Enqueue, Dequeue, Peek: O(1)

Python Queue Example

from collections import deque
queue = deque()
queue.append("A")
queue.popleft()

JavaScript Queue Example

let queue = []
queue.push("A")
queue.shift()

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⚔️ Stacks vs Queues

Feature	Stack (LIFO)	Queue (FIFO)
Primary Use	Call history, recursion	Scheduling, buffering
Access Pattern	Top-only	Front-only
Operations	Push/Pop/Peek	Enqueue/Dequeue/Peek
Time Complexity	O(1) for all ops	O(1) for all ops

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🧠 Final Thoughts

Though simple in nature, stacks and queues serve as foundational components in larger systems. From compilers to OS schedulers, they power logic beneath the surface.

💡 Pro Tip: Know the access pattern you need. If it’s last-in-first-out, use a stack. If it’s first-in-first-out, go with a queue.

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