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Logs on 2025-05-12 (liberachat/#haskell)

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00:02:20 <EvanR> I'm probably wrong about my observation, but using your example I'll show what I mean, (\x y -> x + y) y z, evaluate x+y in environment [x=>y, y=>z], y + z. I'll see if I can fix the example
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00:04:55 <EvanR> (\x y -> \z -> x) z
00:06:09 <EvanR> yields an identity function instead of a constant function
00:07:27 <EvanR> so when you convert from debruijn back to named variables you better use unique names
00:08:32 <EvanR> (in the first example one of the y and in this example the z are free so wouldn't get IDs afaiui)
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00:27:33 <monochrom> Environment is also a way to be invulnerable.
00:28:55 <monochrom> The mistake happens if you really do what you tell beginners: substitute. :)
00:31:57 <monochrom> The pros do one of. They do one of: numbering, environment, alpha-convert lambdas to fresh vars before substitute (e.g., rewrite (\x y -> x + y) to (\uuid1934 uuid3141 -> uuid1934 + uuid3141))
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00:32:29 <monochrom> I think Scheme hygienic macros use the alpha-convert way.
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00:38:31 <EvanR> it seems to me that environment is real solution only if stuff in the environment doesn't have free variables, like in eager evaluation
00:39:31 <EvanR> so ghc must do none of the above
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01:53:23 <EvanR> I'm wrong, since the environment would have first class functions with their own environment in a closure
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03:22:59 <monochrom> :)
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03:28:03 <EvanR> true or false, to have a working fixed point construct for recursion, you need some kind of lazy evaluation
03:28:34 <EvanR> or else evaluating fix f necessarily freezes
03:36:21 <monochrom> True.
03:38:16 <EvanR> how do all these languages get recursion without lazy evaluation
03:39:33 <ski> fix :: ((a -> b) -> (a -> b)) -> (a -> b)
03:39:36 <monochrom> Even in call-by-value languages, lambdas are lazy in bodies, or at least delayed, i.e., "\x -> undefined" does not cause that undefined to be evaluated, only application "(\x -> undefined) 5" does. That little delay is leveraged to make fixed point combinators and emulation of laziness.
03:39:40 <ski> fix f = (\t -> t t) (\t x -> f (t t) x)
03:41:15 <monochrom> So you cannot make "fix (0 :) = 0 : 0 : ..." like in Haskell, but you can still make "fix (\f -> \n -> ... fibonacci ...)"
03:41:48 <EvanR> is that the Z combinator ski
03:42:06 <ski> it's the by-value fixed point combinator
03:43:00 <EvanR> I see
03:44:20 <ski> (note the eta-expansion)
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03:45:43 <monochrom> Y is (\t -> t t) (\t -> f (t t)). For call-by-value languages we eta expand to (\t x -> f (t t) x) so one more argument is needed for evaluation so there is the delay I said we need.
03:47:01 <monochrom> So it is missing out on fix (0 :) = 0 : 0 : ... but it's OK, call-by-value languages don't have lazy lists in the first place. :)
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03:47:42 <EvanR> I found this on some page Z = \f -> (\x -> (f (\v -> (x x v)))) (\x -> (f (\v -> (x x v))))
03:48:04 <EvanR> but yours is more explainable
03:49:03 <ski> yea, i prefer adding in `(\t -> t t)' for the first part, no need to repeat something longer
03:50:16 <EvanR> \f -> (\t -> t t) (\x -> f (\v -> (x x v)))
03:50:26 <EvanR> I probably messed up
03:50:41 <monochrom> It is correct. :)
03:52:27 <EvanR> ok but the point of a fix construct is so you don't have to munge these nuts combinators, and so they can have a type
03:53:03 <EvanR> does the by value version need a different evaluation strategy
03:53:41 <monochrom> No, it's designed to be compatible with by-value evaluation.
03:53:53 <EvanR> uhg
03:54:28 <ski> # let fix f = (fun t -> t t) (fun t x -> f (t t) x);;
03:54:33 <ski> val fix : (('a -> 'b) -> 'a -> 'b) -> 'a -> 'b = <fun>
03:54:43 <ski> # fix (fun fib n -> match n with 0 -> 0 | 1 -> 1 | n -> fib (n - 1) + fib (n - 2)) 12;;
03:54:46 <ski> - : int = 144
03:56:11 <EvanR> alright let me think
03:56:29 <monochrom> Wait, how does that accept that "t t" is typeable?
03:57:06 <EvanR> this is some fun t business
03:57:08 <ski> # let omega x = x x;;
03:57:10 <ski> val omega : ('a -> 'b as 'a) -> 'b = <fun>
03:57:33 <EvanR> it's an infinite type
03:57:41 <monochrom> Oh God it does equi-recursive types?!
03:57:50 <ski> `ocaml -rectypes' does, yes
03:58:04 <monochrom> OK that's deep magic.
03:58:15 <ski> without `-rectypes', it only allows such cycles, if they go through at least one object type
04:01:09 <ski> (this is useful for "binary methods" and "clone methods / functional update". see <https://ocaml.org/manual/5.3/objectexamples.html#s:functional-objects> and <https://ocaml.org/manual/5.3/objectexamples.html#s:binary-methods>)
04:03:44 <ski> # let omega : 'o -> 'a as 'o = fun x -> x x;;
04:03:47 <ski> val omega : 'b -> 'a as 'b = <fun>
04:03:57 <ski> ^ shorter way to express the same type
04:04:51 <ski> `omega :: o where o = o -> a' in Haskellish terms
04:06:04 <EvanR> ...) -> a) -> a) -> a) -> a
04:06:51 <ski> indeed
04:07:40 <EvanR> it's turtles all the way down
04:09:49 <ski> newtype Santa a = MkSanta {runSanta :: Santa a -> a}
04:10:06 <ski> fix :: (a -> a) -> a
04:10:20 <ski> fix f = t `runSanta` t
04:10:25 <ski> where
04:10:41 <ski> t = Santa (\t -> f (t `runSanta` t))
04:11:11 <ski> er, s/t = Santa/t = MkSanta/
04:11:30 <EvanR> is this by value santa
04:11:57 <ski> by-name
04:12:27 <EvanR> oh it's the Y combinator smuggled into haskell
04:12:51 ski . o O ( <https://en.wikipedia.org/wiki/L%C3%B6b's_paradox> )
04:13:06 <ski> using type-level recursion, rather than value-level recursion, yes
04:13:31 <EvanR> what is the character between L and b my client exploded
04:13:47 <ski> it's an "ö"
04:13:55 <ski> "o" with diaresis
04:14:33 <ski> (percent-encoded in this case. however, <https://en.wikipedia.org/wiki/Curry's_paradox> also works)
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04:16:41 <EvanR> got it
04:16:59 <ski> using iso-recursive types, rather than equi-recursive
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04:18:24 <ski> (Löb's paradox has an extra "provable" modality indirection, though .. `loeb : [] ([] a -> a) -> [] a' .. but if you ignore that, it's basically `fix')
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04:26:23 <ski> ((lambda (lambda) `(,lambda ',lambda)) '(lambda (lambda) `(,lambda ',lambda)))
04:26:26 <ski> and
04:26:32 <ski> (let ((let '`(let ((let ',let)) ,let))) `(let ((let ',let)) ,let))
04:27:02 <ski> are two quines based on the same idea
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07:59:50 <hololeap> Hey, just wondering if anyone knows of any examples on gitghub of haskell packages that have a functioning benchmark setup and a way to measure PRs against the main branch?
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08:19:31 <merijn> hololeap: I don't think anyone does that
08:19:49 <merijn> Because it seems unlikely the github runner infrastructure is deterministic enough
08:20:33 <hololeap> you mean in terms of speed?
08:20:36 <merijn> yeah
08:20:50 <hololeap> fair enough
08:20:52 <merijn> I can imagine the available CPU scales with current load of their github action system
08:21:27 <hololeap> that makes sense
08:21:29 <hololeap> ty
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09:11:50 <tomsmeding> I have some personal experience with benchmarking on github actions, and indeed the answer is: don't do that, performance is unpredictable
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09:17:03 <__monty__> Are there any benchmarking techniques that are independent(ish, at least) of the capacity of the underlying hardware?
09:24:03 <Hecate> __monty__: well, that would mean doing a bunch, bunch of benchmark runs, and then averaging them out per hardware characteristics :D
09:24:31 <Hecate> __monty__: in other words, you will get completely different results according to the cache of the CPU, the quality of RAM, etc
09:25:02 <Hecate> you're not getting any kind of useful metrics from abstracting that away, there's no "ethereal" or "ideal" computer on which your program runs
09:25:36 <__monty__> I'm thinking of things like benchmarking before and after a change. To get an estimation of the relative improvement of the change.
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09:26:32 <Hecate> __monty__: yes that's what benchmarking does, but your change might have completely different effects on different architectures!
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09:26:53 <__monty__> It's not perfect but I suspect it's a step in the right direction.
09:27:36 <Hecate> __monty__: just so we're clear, you want to mesure change against something that is not a real computer or has no real hardware characteristics, despite your program running on actual computers with actual hardware?
09:28:22 <Hecate> then I'm not sure what you want to measure, actually
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09:30:08 <__monty__> I'm more interested in a statistic that says something about hardware representative of what the software runs on on average. Without having to know the exact distribution of hardware characteristics and without requiring a stable representative of that distribution.
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09:41:09 <Hecate> __monty__: so, you want an average of your program's runtime platforms
09:41:31 <Hecate> __monty__: looks like you may want to look into telemetry, or download statistics for pre-built binaries
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10:01:04 <__monty__> No, that's not actually what I want.
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10:02:27 <__monty__> This is more of an inquiry for theoretical results. I find it hard to believe that there's *nothing* you can measure independently from a specific hardware configuration.
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10:12:29 <Hecate> __monty__: there's not "nothing", but there's few things. Useful things are still bound to the laws of physics
10:13:58 <tomsmeding> __monty__: the optimisations that a compiler does to your code are instruction-set architecture dependent
10:14:03 <tomsmeding> there is no such thing as hardware-independent performance
10:14:38 <tomsmeding> somewhat related, though: if you accept hardware-bound results, you can strongly reduce noise effects by not measuring time but number of instructions executed
10:14:48 <tomsmeding> modern CPUs have counters for this
10:15:48 <tomsmeding> only computational complexity has a chance of being hardware-independent, though I wouldn't be surprised if you can come up with edge cases where a compiler is able to e.g. optimise a loop away to a constant operation on one architecture but not on another
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19:10:05 <[exa]> so I see there's dear-imgui package for haskells. Is there any (convenient) way to run that atop a gloss app?
19:13:11 <c_wraith> gloss can render a bitmap.
19:13:28 <c_wraith> but thta doesn't exactly make it convenient.
19:13:36 <EvanR> or efficient
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19:14:31 <[exa]> like, in Cs I was normally just injecting an extra commandbuffer from imgui at the end of render (of basically anything) and it worked, kinda hoped that gloss would have some support for that
19:14:37 <EvanR> sometimes separate openGL codes can be slammed together in primitive fashion to both work with under the same context, but one of them has to avoid opening its own (global) context
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19:15:11 <EvanR> I'm not sure this is filed under "convenient" moresorather than "mad science"
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19:17:26 <[exa]> it's convenient in C :D
19:17:45 <[exa]> anyway yeah imgui is literally built to allow this
19:17:50 <c_wraith> I mean, a big part of it is that gloss is not
19:18:07 <c_wraith> Gloss is mostly built to be self-contained
19:18:24 <c_wraith> even rendering a bitmap is stretching what it's built for
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19:19:00 <[exa]> as in, there's an imgui memory editor project that you can dynamically load into any running opengl program with some gdb help, add a little bit of a call at the right place, and it will just render
19:19:09 <[exa]> not sure if gloss will be immune
19:19:13 <[exa]> let's see
19:19:59 <EvanR> yeeeeah that's still mad science
19:21:42 <[exa]> yeah that one qualifies easily
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20:46:36 <EvanR> everybody knows that if you make an algebraic data type to represent the actions and string them together with lambdas in just the right way you're doing the free monad. Now what is this called
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20:48:01 <EvanR> instead of doing step :: VM -> IO VM, do step :: Monad m => (Char -> m ()) -> (m Char) -> VM -> m VM and now your algorithm is parameterized by all monads ever
20:48:46 <EvanR> (and I'm not even sure what the consequences are, unless you pick m = IO)
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20:55:03 <monochrom> You can do mock testing by picking something else for m. If you pick the free monad for m, then write one interpreter for IO, another interpreter for mock testing.
20:55:52 <monochrom> Now, what is that called? Answer: Dependency injection. >:)
20:58:39 <EvanR> testing, interesting theory
20:59:03 <monochrom> Or you may like: Explicit dictionary passing. Because you can imagine you had "class Monad m => MonadVM m where foo :: Char -> m (); bar :: m Char" so step was "step :: MonadVM m => VM -> m VM", but then you decided to delete the class and pass the two methods as arguments.
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21:01:21 <EvanR> by generalizing from IO to m we restricted what this function could possibly do, seems like a general property of polymorphism
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21:02:11 <EvanR> this is haskell, we can do less
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21:02:50 <Rembane> Laziness is a thing
21:03:47 <Rembane> A good thing
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21:27:13 <monochrom> Parametric polymorphism restricts the function (e.g., it has to do the same thing for all monads), therefore users find the function more predictable.
21:31:08 <monochrom> BTW even with the production version, even if you're doing IO, you may still like to generalize so that you can swap out one UI for another. In fact, if you switch over to a "don't call us, we'll call you" GUI framework, you may need m = ContT r IO or Codensity IO and then pull the reinvent-control trick:
21:31:10 <monochrom> http://blog.sigfpe.com/2011/10/quick-and-dirty-reinversion-of-control.html
21:31:22 <monochrom> err, s/reinvent/reinvert/
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21:34:37 <EvanR> ok it was testing now it's a GUI
21:35:29 <monochrom> There are multiple benefits!
21:35:46 <monochrom> Or one benefit that has multiple manifestations.
21:36:59 <EvanR> I was going to say, what does it even mean if you put a random monad like Cont in for m but then you retrocausally are saying that's something useful
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21:38:35 <monochrom> :)
21:46:20 <EvanR> not to be confused with a random monad, for getting random numbers
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22:35:46 <EvanR> do unix signals have anything to do with async exceptions (by default)
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23:36:02 <monochrom> By default, only SIGINT is translated by GHC RTS to UserInterrupt :: AsyncException.
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23:42:49 <EvanR> cool
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All times are in UTC on 2025-05-12.