Data Cleanup · interview question
A bug appears around safe output writes. What is the strongest first debugging move?
Multiple choiceMediumchapter-4-curatedpremiumdata-cleanupsafe-output-writes
from pathlib import Path
target = Path("orders.json")
temp = target.with_suffix(".tmp")
temp.write_text("[]", encoding="utf-8")
temp.replace(target)Answer and explanation
Correct answer
A. Trace one concrete example, inspect the state transitions, and compare them to the intended rule before rewriting anything.
Why
That approach is reliable because it creates evidence. If a process dies mid-write and the target file was already replaced, the next job may read corrupt output.
Test yourself on Data Cleanup
A free test with instant, explained results. No account needed.
More Data Cleanup questions
- A teammate submits shaky safe output writes code. Which review comment is the strongest?
- When is safe output writes being used in the wrong way?
- What is the clearest sign that code around safe output writes should be refactored?
- You cannot rewrite everything today. What is the best incremental improvement around normalization pipelines?
- Which move is the best default when normalization pipelines becomes part of this workflow?
- Which option describes the most likely pitfall around normalization pipelines?