Comment by phkahler

What do you mean with 'cannot'? We have this in [0]

  unsafePerformIO :: IO a -> a 

Do you mean "cannot do with safety guarantee"? Strangely enough, the haskell docs use the same language as you:

  The ST monad allows for destructive updates, but is escapable (unlike IO). 

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0. https://hackage.haskell.org/package/base-4.21.0.0/docs/Syste...

That's right. Locally scoped mutable memory in Flix is very similar to the ST Monad. The two major differences are: (a) Flix is in direct-style vs. monadic style and (b) we use a type and effect system.

Note that there is no requirement that all mutation must occur within a single function. The requirement is that once you leave the lexical scope then all mutable memory associated with that scope become unreachable. Mutation can certainly span over multiple functions.

You gotta ask the question: why does FP care about eliminating side effects? There are two possible answers:

1. It's just something weird that FP people like to do; or

2. It's in service of a larger goal, the ability to reason about programs.

If you take the reasonable answer---number 2---then the conclusion is that effects are not a problem so long as you can still reason about programs containing them. Linear / affine types (like Rust's borrow checker) and effect systems are different ways to accommodate effects into a language and still retain some ability to reason about programs.

No practical program can be written without effects, so they must be in a language somewhere.

More here: https://noelwelsh.com/posts/what-and-why-fp/

If you start with lambda calculus you don't have effects in the first place, so there's nothing to eliminate. Lambda calculus and friends are perfectly reasonable languages for computation in the sense of calculation.

A better way to think about general-purpose functional programming is that it's a way to add effects to a calculation-oriented foundation. The challenge is to keep the expressiveness, flexibility and useful properties of lambda calculus while extending it to writing interactive, optimizable real-world programs.

To retain referential transparency, we basically need to ensure that a function provided the same arguments always returns the same result.

A simple way around this is to never give the same value to a function twice - ie, using uniqueness types, which is the approach taken by Clean. A uniqueness type, by definition, can never be used more than once, so functions which take a uniqueness type as an argument are referentially transparent.

In Haskell, you never directly call a function with side effects - you only ever bind it to `main`.

Functions with (global) side effects return a value of type `IO a`, and the behavior of IO is fully encapsulated by the monadic operations.

    instance Monad IO where
        return :: a -> IO a
        (>>=) :: IO a -> (a -> IO b) -> IO b    -- aka "bind"

return lifts a pure value into IO, and bind sequences IO operations. Importantly, there cannot exist any function of type `IO a -> a` which escapes IO, as this would violate referential transparency. Since every effect must return IO, and the only thing we can do with the IO is bind it, the eventual result of running the program must be an IO value, hence `main` returns a value of type `IO ()`.

    main :: IO ()

So bind encapsulates side effects, effectively using a strategy similar to Clean, where each `IO` is a synonym of some `State# RealWorld -> (# State# RealWorld, a #)`. Bind takes a value of IO as it's first argument, consumes the input `State# RealWorld` value and extracts a value of type `a` - feeds this value the next function in the sequence of binds, returning a new value of type `IO b`, which has a new `State# RealWorld`. Since `bind` enforces a linear sequencing of operations, this has the effect that each `RealWorld` is basically a unique value never used more than once - even though uniqueness types themselves are absent from Haskell.

Effect systems in FP languages give you precisely that: referential transparency.

Lisp always had side effects and mutability, and it's the canonical FP language, directly inspired by lambda calculus. To be fair, before Haskellers figured out monads, nobody even knew of any way to make a FP language that's both pure and useful.