Python Interview Questions · interview question

Which practice avoids a common mistake with heapq and Priority Queues?

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Prefer the version of heapq and Priority Queues that makes behavior less predictable as long as the code still runs.Silence the heapq and Priority Queues problem by using broad catches, hidden globals, or extra shared mutable state.Do not assume iterating the underlying heap list produces globally sorted order, because the heap only guarantees the head element.Ignore the heapq and Priority Queues issue and rely on team discipline instead of clearer APIs or invariants.

Answer and explanation

Correct answer

C. Do not assume iterating the underlying heap list produces globally sorted order, because the heap only guarantees the head element.

Why

Do not assume iterating the underlying heap list produces globally sorted order, because the heap only guarantees the head element. This is a common failure mode in real Python code and a frequent interview follow-up.

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Which practice avoids a common mistake with heapq and Priority Queues?

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