Heap/Priority Queue problems - when to recognize you need one

The clue that you need a heap is usually in the problem statement:

• "Find the K largest/smallest elements" → Min/Max heap
• "Merge K sorted lists/arrays" → Min heap
• "Median of a data stream" → Two heaps
• "Schedule tasks with priorities" → Max heap
• "Closest points to origin" → Max heap of size K

Common mistake: Using sorting when a heap would be more efficient.

• Sorting: O(n log n)
• Heap of size K: O(n log K) — better when K << n

Python's heapq makes implementation trivial.