Mine is that the useState hook is an actual plague on the entire React ecosystem. Regardless of your opinions of React, if you wanna use something then use it right.
Mine is that the useState hook is an actual plague on the entire React ecosystem. Regardless of your opinions of React, if you wanna use something then use it right.
This is gonna make me sound crazy, but always pass functions when possible, and use case statements for how the passed-in functions are applied.
As a simple example, imagine you want to take the average of a set of numbers. Instead of doing sum(numbers)/len(numbers), do:
Quotient_reduce(sum, lambda x,y: x+1, numbers)
then, inside the definition of quotient_reduce,
Def quotient_reduce(accumulate_by, normalize_by, list):
If accumulate_by==sum and normalize_by==(lambda x,y:x+1):
Else:
I know it must look insane, but it generalizes normalization, mean, geometric mean, etc, and on the outside there’s no taste of the horrible concrete implementation!
Apologies about formatting, I’m on my phone.
Okay, I do think this makes you sound crazy.
I’m putting my question first before I rant about this cause I think I got way more into this response than is warranted.
What problem does this design of just creating bespoke functions have that your design solves?
def mean(numbers): return efficient calculation def normalization(numbers): return efficient calculation def geometric_mean(numbers): return efficient calculationRant starts here:
With your design, every time someone wants an average of a set of numbers, you’re reimplementing the actual logic. Then if someone forgets the +1 and writes:
quotient_reduce(sum, lambda x,y: x, numbers)A bug is introduced that’s hard to spot in a review, won’t give an error, and is hard to write tests for. Turning the lambda to an enum meant to be passed around would solve a some of the accidental bugs, but keeps the interaction with the function more complicated.
I really just don’t understand why you wouldn’t just write each efficient implementation as it’s own function and call it directly.
It has to do with how you decompose problems. In the example I gave, I was trying to point out that arithmetic average, geometric average, and normalization are related problems. Consider applying this technique to something more complicated than averages: pathfinding. You could create a dozen different efficient functions, each with different considerations, but the core of the algorithm will always be the same. You can write pathfind_land(src, dest), pathfind_sea(src, dest), pathfind_air(src,dest), pathfind_sea_and_land(src,dest) etc. but it’s obviously better to write it as pathfind(src,dest, is_traversable) and select the most efficient implementation inside the function. It also allows you to use a not-optimized implementation automatically if you haven’t made an efficient implementation.