Follow-up · depth 9
Compare dataclasses and __slots__ with a common alternative in a design review
Compare dataclasses and __slots__ with a common alternative in a design review
Answers use simple, clear English.
Quick interview answer
Compare dataclasses and __slots__ vs the usual alternative on complexity, latency, failure modes, and ops cost. Pros: Less boilerplate than manual classes; slots reduce per-instance dict overhead. Cons: Inheritance with slots tricky; default mutable fields need default_fa…
Detailed answer
Design-review comparison for dataclasses and __slots__: Axes: correctness, latency, throughput, complexity, operability. From the topic: Pros: Less boilerplate than manual classes; slots reduce per-instance dict overhead. Cons: Inheritance with slots tricky; default mutable fields need default_factory. Recommendation: pick dataclasses and __slots__ when its strengths match the SLO; otherwise choose the alternative and say why. Parent context: Baseline: @dataclass auto-generates __init__, __repr__, __eq__. slots=True (Py3.10+) fixes attributes and saves memory.
Full explanation
Show a clear decision framework, not “it depends” with no criteria. Pros: Less boilerplate than manual classes; slots reduce per-instance dict overhead. Cons: Inheritance with slots tricky; default mutable fields need default_factory.
Follow-up questions
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Parent context — dataclasses and __slots__
Baseline: @dataclass auto-generates __init__, __repr__, __eq__. slots=True (Py3.10+) fixes attributes and saves memory.
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