Haskell is great if you want to expand your CS knowledge, but not if your math/physics/engineering problem is already so complicated that it uses up all your available brain cycles and working memory and you just can't squeeze thinking about language-specific optimizations too. I guess this is why it's only used by companies like Galois and such that are already neck deep in advanced CS problems and used to thinking about them all the time.
That's not true. This article is about a library that works as a drop-in replacement of the default list processing functions in the Prelude. Eventually, it may be possible that these functions will be put into the Prelude itself. This would allow naive users to get all the performance gains from stream fusion without ever knowing it's happening. All of the "cognitive overload" is taken care of by the researchers who developed this technique and the library authors who implement it.
I am quite taken by Haskell, and I have the whopping mathematical background of two introductory courses from my institute of mathematics.
> But I'm referring to the cognitive overload incurred when you try to optimize it, thinking about list creation costs, then stream fusion to avoid i
The author didn't need to know what stream fusion was; all they did was import a library... it might as well have been called import MagicallyOptimizingPrelude and it would have the same effect.
Having written quite a bit of Cython, I refuse to touch it anymore given how wildly undefined it's behavior can be with intermingling Python and C semantics.