nihils · HackerTrans

قبل 9 سنواتdiscuss

I don't think there is significant overlap between Python's ideal use cases and Haskells. For one, Haskell's advanced static type system lends itself nicely to formal verification and the handling of domain specific languages. Both domains are important in safety-critical software. It also has much better ways of dealing with concurrency (STM and linear types). On the other hand, Python's ecosystem seems to be centred around backend web development, data science, and machine learning.

nihils

قبل 9 سنواتdiscuss

For example, this problem of modifying the diagonal of a matrix can be solved quite easily:

  type Zipper a = ([a],[a])
  
  cursorOnDiagonal :: [[Int]] -> [Zipper Int]
  cursorOnDiagonal matrix = map (\(n,x) -> splitAt n x) (zip [0..(length matrix)-1] matrix) 

  flipToOneAtCursor :: [Zipper Int] -> [Zipper Int]
  flipToOneAtCursor = map (\(ys,x:xs) -> (ys,1:xs))   

  backToList :: [Zipper Int] -> [[Int]] 
  backToList = map (\(ys,xs) -> ys ++ xs)

If matrix == [[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]], then:

  backToList . flipToOneAtCursor . cursorOnDiagonal $ matrix == [[1,0,0,0],[0,1,0,0],[0,0,1,0],[0,0,0,1]]

nihils

قبل 9 سنواتdiscuss

If you want immutable data structures that simulate the behavior of mutable data structures look into Zippers. In this case, a list zipper.

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