ghc-proposals
julia
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ghc-proposals
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An alternative front end for Haskell?
> I think Haskell needs a way to graduate (or retire) language extensions
https://github.com/ghc-proposals/ghc-proposals/pull/601
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Or patterns proposal: Prefix signalling or just infix?
Additionally, while this proposal is focused on the simple implementation and so in the current proposal or patterns do not bind any variables as per #522, if we do get settled on syntax and then later wish to expand to allow binding variables as in #43, then the syntax is again clean and discoverable.
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Monthly Hask Anything (May 2023)
Yeah, a relatively natural thing would be to be able to opt-in to having the HasField instances be available in all contexts. The (not yet implemented, but accepted) "Modifiers" GHC proposal might be nice for that.
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Is there any way to build a simple additive prelude?
The local modules proposal imo is excellent as-is.
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Interview and AMA with Simon Peyton Jones
Why would you drop TypeFamilies? It seems fairly popular, given that it was just one vote short of getting added to GHC2021. Do you consider it a less-ideal compromise, that is subsumed by your second proposal (Core with GRTT)?
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Amendmend proposal: Changed syntax for Or patterns
as syntax is contentious a topic as ever, David (the main proposal author) and I would like to invite you to give your input on https://github.com/ghc-proposals/ghc-proposals/pull/585, where we propose to change the syntax of the accepted proposal #522 introducing Or patterns. In particular, we'd like to know
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MSc Dissertation: Comprehending Pure Functional Effect Systems
This looks great, congratulations on completing it! I assume you didn’t get an opportunity to evaluate the delimited continuations based eff library? It would’ve been nice to see Cont included as one of the effects covered, though perhaps not available in all the systems you looked at? Maybe some future work.
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Trouble understanding function import in Haskell
I do hope qualified exports are available someday: https://github.com/ghc-proposals/ghc-proposals/pull/283
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{-# WARNING #-} for Data.List.{head,tail} in future GHC 9.8
Right. Being able to disable "custom type warnings" at use sites was part of an earlier proposal (https://github.com/ghc-proposals/ghc-proposals/pull/454) but it ended up being shelved.
- Foldr type level implementation
julia
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Top Paying Programming Technologies 2024
34. Julia - $74,963
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Optimize sgemm on RISC-V platform
I don't believe there is any official documentation on this, but https://github.com/JuliaLang/julia/pull/49430 for example added prefetching to the marking phase of a GC which saw speedups on x86, but not on M1.
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Dart 3.3
3. dispatch on all the arguments
the first solution is clean, but people really like dispatch.
the second makes calling functions in the function call syntax weird, because the first argument is privileged semantically but not syntactically.
the third makes calling functions in the method call syntax weird because the first argument is privileged syntactically but not semantically.
the closest things to this i can think of off the top of my head in remotely popular programming languages are: nim, lisp dialects, and julia.
nim navigates the dispatch conundrum by providing different ways to define free functions for different dispatch-ness. the tutorial gives a good overview: https://nim-lang.org/docs/tut2.html
lisps of course lack UFCS.
see here for a discussion on the lack of UFCS in julia: https://github.com/JuliaLang/julia/issues/31779
so to sum up the answer to the original question: because it's only obvious how to make it nice and tidy like you're wanting if you sacrifice function dispatch, which is ubiquitous for good reason!
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Julia 1.10 Highlights
https://github.com/JuliaLang/julia/blob/release-1.10/NEWS.md
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Best Programming languages for Data Analysis📊
Visit official site: https://julialang.org/
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Potential of the Julia programming language for high energy physics computing
No. It runs natively on ARM.
julia> versioninfo() Julia Version 1.9.3 Commit bed2cd540a1 (2023-08-24 14:43 UTC) Build Info: Official https://julialang.org/ release
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Rust std:fs slower than Python
https://github.com/JuliaLang/julia/issues/51086#issuecomment...
So while this "fixes" the issue, it'll introduce a confusing time delay between you freeing the memory and you observing that in `htop`.
But according to https://jemalloc.net/jemalloc.3.html you can set `opt.muzzy_decay_ms = 0` to remove the delay.
Still, the musl author has some reservations against making `jemalloc` the default:
https://www.openwall.com/lists/musl/2018/04/23/2
> It's got serious bloat problems, problems with undermining ASLR, and is optimized pretty much only for being as fast as possible without caring how much memory you use.
With the above-mentioned tunables, this should be mitigated to some extent, but the general "theme" (focusing on e.g. performance vs memory usage) will likely still mean "it's a tradeoff" or "it's no tradeoff, but only if you set tunables to what you need".
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Eleven strategies for making reproducible research the norm
I have asked about Julia's reproducibility story on the Guix mailing list in the past, and at the time Simon Tournier didn't think it was promising. I seem to recall Julia itself didnt have a reproducible build. All I know now is that github issue is still not closed.
https://github.com/JuliaLang/julia/issues/34753
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Julia as a unifying end-to-end workflow language on the Frontier exascale system
I don't really know what kind of rebuttal you're looking for, but I will link my HN comments from when this was first posted for some thoughts: https://news.ycombinator.com/item?id=31396861#31398796. As I said, in the linked post, I'm quite skeptical of the business of trying to assess relative buginess of programming in different systems, because that has strong dependencies on what you consider core vs packages and what exactly you're trying to do.
However, bugs in general suck and we've been thinking a fair bit about what additional tooling the language could provide to help people avoid the classes of bugs that Yuri encountered in the post.
The biggest class of problems in the blog post, is that it's pretty clear that `@inbounds` (and I will extend this to `@assume_effects`, even though that wasn't around when Yuri wrote his post) is problematic, because it's too hard to write. My proposal for what to do instead is at https://github.com/JuliaLang/julia/pull/50641.
Another common theme is that while Julia is great at composition, it's not clear what's expected to work and what isn't, because the interfaces are informal and not checked. This is a hard design problem, because it's quite close to the reasons why Julia works well. My current thoughts on that are here: https://github.com/Keno/InterfaceSpecs.jl but there's other proposals also.
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Getaddrinfo() on glibc calls getenv(), oh boy
Doesn't musl have the same issue? https://github.com/JuliaLang/julia/issues/34726#issuecomment...
I also wonder about OSX's libc. Newer versions seem to have some sort of locking https://github.com/apple-open-source-mirror/Libc/blob/master...
but older versions (from 10.9) don't have any lockign: https://github.com/apple-oss-distributions/Libc/blob/Libc-99...
What are some alternatives?
haskell-language-server - Official haskell ide support via language server (LSP). Successor of ghcide & haskell-ide-engine.
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
ihp - 🔥 The fastest way to build type safe web apps. IHP is a new batteries-included web framework optimized for longterm productivity and programmer happiness
NetworkX - Network Analysis in Python
rio-orphans - A standard library for Haskell
Lua - Lua is a powerful, efficient, lightweight, embeddable scripting language. It supports procedural programming, object-oriented programming, functional programming, data-driven programming, and data description.
hoogle - Haskell API search engine
rust-numpy - PyO3-based Rust bindings of the NumPy C-API
ghc - Mirror of the Glasgow Haskell Compiler. Please submit issues and patches to GHC's Gitlab instance (https://gitlab.haskell.org/ghc/ghc). First time contributors are encouraged to get started with the newcomers info (https://gitlab.haskell.org/ghc/ghc/wikis/contributing).
Numba - NumPy aware dynamic Python compiler using LLVM
frp-zoo - Comparing many FRP implementations by reimplementing the same toy app in each.
F# - Please file issues or pull requests here: https://github.com/dotnet/fsharp