👀 Peek in Heap Tree (Min/Max Heap)

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Definition:
The peek() operation in a Heap Tree returns the root element:

• In a Max Heap, it returns the maximum element.

• In a Min Heap, it returns the minimum element.

⚠️ It does not remove the element — just views it.

📌 Time Complexity

• ✅ O(1) — Since the root is always at index 0 (in array representation).

📊 Basic Diagram (Max Heap Example)

60 / \ 30 50 / \ / 10 20 40

🔍 peek() → returns 60 (root of Max Heap)

🧠 Python Code for peek() in Max Heap

class MaxHeap: def __init__(self): self.heap = [] def insert(self, value): self.heap.append(value) self._heapify_up(len(self.heap) - 1) def peek(self): if not self.heap: return None return self.heap[0] def _heapify_up(self, index): parent = (index - 1) // 2 if index > 0 and self.heap[index] > self.heap[parent]: self.heap[index], self.heap[parent] = self.heap[parent], self.heap[index] self._heapify_up(parent) # Example usage h = MaxHeap() for val in [60, 30, 50, 10, 20, 40]: h.insert(val) print("Top Element (Peek):", h.peek()) # Output: 60

📝 Summary of peek() Operation

Feature	Description
Purpose	View the root element
Modifies Heap?	❌ No
Time Complexity	O(1)
Used in	Priority Queue, Scheduling