lumen | julia | |
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10 | 350 | |
532 | 44,569 | |
- | 0.6% | |
0.0 | 10.0 | |
over 1 year ago | 2 days ago | |
JavaScript | Julia | |
BSD 2-clause "Simplified" License | MIT License |
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lumen
- Lumen: A Lisp for Lua and JavaScript
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Gerbil Scheme – A Lisp for the 21st Century
I agree! That’s actually not a jeer, it’s one of my main criticisms of lisp. You don’t need lists to have lisp. In many respects it works better without them; https://github.com/sctb/lumen proves it, since hash tables and arrays are the fundamental data structure. They have to be, because that’s the only way lumen can run in JS or Lua.
Every time I can’t delete the first element of a list in lisp (I.e. del x[0] in the python sense) I get annoyed with racket.
The reason I look past it is because the benefits are so good that they outweigh the annoyances. I wouldn’t trade it away.
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Show HN: Dak – a Lisp like language that transpiles to JavaScript
Where h is the raw function for hyperapp, not a macro.
I'd intended to develop my own mini-lisp with the same syntax, but got sidetracked by other projects. Maybe someday I'll get back to it. (Currently, I'm deep in the weeds trying to learn how to write a dependent typed language that compiles to javascript.)
[0]: https://github.com/sctb/lumen
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“There Is No List”
It wasn’t my idea, too. It was Scott Bell’s. I’m not sure if he thought of it or got it from somewhere else, but it’s shockingly effective.
If you want to try it out for yourself, give Lumen a spin: https://github.com/sctb/lumen
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The project with a single 11,000-line code file
> What do you develop with Arc usually?
I try to use Arc for as much as possible. We wrote our TPU monitoring software in it: http://tensorfork.com/tpus
Eventually I became frustrated with Racket's FFI. So I eventually made my own arclike language called elflang: https://github.com/elflang/elf
... which itself is a fork of Lumen (https://github.com/sctb/lumen) by Scott Bell.
The performance is good enough to run a minecraft-style game engine: https://i.imgur.com/iyr0YrB.png which was satisfying.
Nowadays I've been trying to implement Bel, mostly for the challenge of it than for any practical reason.
> I like how the "html" and "css" part was embedded in that "news.arc" file. Do you think that VIM script will highlight and lint the "css" part of an "arc" file?
Nope. https://i.imgur.com/o9aUG6j.png
But it has one very important feature: it can properly highlight atstrings: https://i.imgur.com/wO4f742.png
It's probably hard to tell, but the "@(hexrep border-color*)" would normally be highlighted as if it were a string. Arc has a feature called atstrings, where you can use @foo to reference the enclosing variable "foo". It can also call functions, e.g. "The value of 1 plus 2 is @(+ 1 2)" will become "The value of 1 plus 2 is 3".
- Lumen – self-hosted Lisp for Lua and JavaScript
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The most misunderstood aspect of Python
Not mine! That was all Scott Bell. It's forked from Lumen: https://github.com/sctb/lumen
But, I did make an interactive tutorial here: https://docs.ycombinator.lol/
If you have any questions about it, I'd be happy to answer. This stuff is pure fun mixed with a shot of professionalism.
For what it's worth, as someone with narcolepsy, I relate quite a lot to your chronic pain. (https://twitter.com/theshawwn/status/1392213804684038150) For me, it mostly translated into wandering aimlessly from job to job, since I thought no one would have me. I hope that you find your way -- there's nothing wrong at all with taking it slow and spending years on something that takes others a few months. Everyone is different, and it's all about the fun.
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Julia and the Incarceration of Lisp
You could go the opposite route, and run Lisp in your favorite language. Here's a Lisp in JavaScript and Lua: https://github.com/sctb/lumen
Integration is easy because there's no integration. You can just call whatever functions you'd normally call.
- Lumen, a Lisp for Lua and JavaScript
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Just Wanted to Say Thanks
Not at all. I've been thanking Scott for making lumen every thanksgiving for several years now. https://github.com/sctb/lumen
I just close the issue immediately after opening it. :)
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?
Tailwind CSS - A utility-first CSS framework for rapid UI development.
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
femtolisp - a lightweight, robust, scheme-like lisp implementation
NetworkX - Network Analysis in Python
awesome-lisp-companies - Awesome Lisp Companies
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.
uncap - Map Caps Lock to Escape or any key to any key
rust-numpy - PyO3-based Rust bindings of the NumPy C-API
sata-license - The Star And Thank Author License(SATA License)
Numba - NumPy aware dynamic Python compiler using LLVM
stack-overflow-import - Import arbitrary code from Stack Overflow as Python modules.
F# - Please file issues or pull requests here: https://github.com/dotnet/fsharp