DSA · Theory

Time Complexity of using heap

Theory

493/810

Time Complexity of using heap

Time Complexity of using heap is a DSA topic. In plain words you use it for next patient in a clinic. Don’t start with a slogan — start with that picture.

Smallest example: heapify + extract. Type it, run it, and say what you see. If you can do that from memory, you know Time Complexity of using heap.

From the example next to this theory: Time Complexity of using heap — heap sort uses a binary heap to repeatedly extract the minimum.

Trap — min-heap vs max-heap mix-up. Fix that before you talk about advanced DSA.

Viva — what is Time Complexity of using heap? Then show heapify + extract. Then name the trap.

Exam tip

What is Time Complexity of using heap? Show this: heapify + extract. Trap: min-heap vs max-heap mix-up.

Example

import heapq

def heap_sort(arr):
    h = arr[:]
    heapq.heapify(h)
    return [heapq.heappop(h) for _ in range(len(h))]

print(heap_sort([5, 1, 4, 2]))

Time Complexity of using heap — heap sort uses a binary heap to repeatedly extract the minimum.

Short notes

DefTime Complexity of using heap — next patient in a clinic.
Ruleheapify + extract
Trapmin-heap vs max-heap mix-up
Usea clinic

DSA · Theory

Time Complexity of using heap

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Theory

493/810

Time Complexity of using heap

Time Complexity of using heap is a DSA topic. In plain words you use it for next patient in a clinic. Don’t start with a slogan — start with that picture.

Smallest example: heapify + extract. Type it, run it, and say what you see. If you can do that from memory, you know Time Complexity of using heap.

From the example next to this theory: Time Complexity of using heap — heap sort uses a binary heap to repeatedly extract the minimum.

Trap — min-heap vs max-heap mix-up. Fix that before you talk about advanced DSA.

Viva — what is Time Complexity of using heap? Then show heapify + extract. Then name the trap.

Exam tip

What is Time Complexity of using heap? Show this: heapify + extract. Trap: min-heap vs max-heap mix-up.

Example

import heapq

def heap_sort(arr):
    h = arr[:]
    heapq.heapify(h)
    return [heapq.heappop(h) for _ in range(len(h))]

print(heap_sort([5, 1, 4, 2]))

Time Complexity of using heap — heap sort uses a binary heap to repeatedly extract the minimum.

Short notes

DefTime Complexity of using heap — next patient in a clinic.
Ruleheapify + extract
Trapmin-heap vs max-heap mix-up
Usea clinic

Time Complexity of using heap

Example

Short notes

Questions

Time Complexity of using heap

Example

Short notes

Questions