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Python · Theory

Heap sort

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Theory

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Heap sort

Heap sort orders a list. Say the idea in plain words, then complexity. Bubble/insertion/selection are O(n²) teaching sorts. Merge and heap are O(n log n). Python’s built-in sort is Timsort (O(n log n), very fast in practice).

Dry-run Heap sort on a tiny list like [4, 1, 3, 2] on the board. Interviewers care that you can trace one pass, not that you recite a textbook page.

For Heap sort in real code: sorted(a) / a.sort() is what you use. Write the algorithm only when they ask you to implement it.

Output — [1, 2, 3, 4]. heapq is Python’s heap — same idea as heap sort.

Exam tip

Idea + complexity + one tiny trace. Then say when to use built-in sort.

Example

# Heap sort
import heapq
a = [4, 1, 3, 2]
heapq.heapify(a)
print([heapq.heappop(a) for _ in range(4)])

Output: [1, 2, 3, 4]. heapq is Python’s heap — same idea as heap sort.

Short notes

  • DefHeap sort puts items in order.
  • RuleHeap sort — know idea + O(...).
  • RememberHeap sort — real code uses sorted() / Timsort.
  • TrapHeap sort — implementing O(n²) in production when sorted() exists.

Questions

1

Explain Heap sort as if you are teaching a junior — definition, then one tiny script.

2

What does the example print, and why?

3

What mistake do freshers make with Heap sort?

Previous← Quick Sort in PythonNextTimsort →
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