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this post was submitted on 23 Sep 2023
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I think there's a spectrum here, and I'll clarify the stances.
The spectrum ranges from "Data shouldn't cause the function to do (something wildly) different" to "It should be allowed, even to the point of variable returns"
I think you stand on the former while I stand on the latter. Correct me if I'm wrong though, but that's the vibe I'm getting from the tone in your example.
Suppose we have a function that calculates a price of an object. I feel it is agreeable for us to have
compute_price(with_discount: bool)
, overcompute_price_with_discount() + compute_price_without_discount()
I feel your point your making in the example is a bit exaggerated. Again, coming back to my above example, I don't think we would construe it as
compute_price('with_discount')
.Maybe this is bandwagoning, but one of the reason for my stance is that there are quite a few examples of variable returns.
eg:
getattr
may return a different type base on the key givennumpy
returns different things based on flags. SVD will returnS
ifcompute_uv=False
andS,U,V
otherwiseAbsolutely.
Well, presumably you'd also actually have some other inputs to a price compute function. In which case, I'd suggest bundling all that information into an Invoice type or something that includes whether or not discounts are applied...
getattr
is really special, it's basically a reflection operator, it shouldn't be a model for how a normal function should behave.I'm not familiar with numpy. The linked function though looks like a true case of generic behavior where an input changes an output in a specified way for any number of values that meet its requirements. A boolean flag is never generic.