heapq Operations

Concepts covered: pyHeapTopK

The heap property is maintained implicitly through the array representation. For an element at index i, its left child is at index 2i+1 and its right child is at 2i+2. When you push or pop elements, the heap operations restore the heap property by "bubbling up" or "bubbling down" elements as needed. Creating and Using Heaps Finding N Smallest/Largest Priority Queue Pattern Notice that tasks with the same priority are processed in insertion order within that priority level. This is because Python's tuple comparison falls back to comparing subsequent elements when the first elements are equal. If the second elements are not comparable, you can add a sequence number as a tiebreaker. Max Heap Implementation Merging Sorted Streams Heaps are so fundamental that Python itself uses them behind the

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