cl-autowrap VS julia

> Lack of access to the C libraries.

???

I recently started learning Common Lisp for fun (and fun it is!) and the ease of accessing C libraries was one of the things that surprised me in a positive way.

Using https://github.com/rpav/cl-autowrap one can simply write (c-include "file.h") and the API defined in "file.h" is accessible from Lisp. I can't think of a simpler way.

Even without cl-autowrap, FFI using https://cffi.common-lisp.dev/ seems simple enough.

I think the closest is cl-autowrap. I can imagine a higher level wrapper around it by which it can translate the python header file into the CL counterpart, although I'm not sure how much work the translation might entail. Also, because python and lisp semantics can differ considerably, the generated code might be trying to do weird things - again an issue of translation.

Common lisp has a "pretty OK" story for calling C code whenever some speed is needed [0,1]. In my opinion, they suffer from some of the documentation/quick start problems that common lisp has, but they're otherwise usable.

Some of Naughty Dog's late 90's/early 2000's games (Jak and Daxter, Jak II) were written in a lisp called GOAL, Game Oriented Assembly Lisp [2]

[0] https://github.com/rpav/cl-autowrap

The closest thing to what you request, that I'm aware of, is cl-autowrap (to use C code from Lisp) but it is not standard in any way. CFFI is the de facto standard for using C from Lisp across different implementations.

:claw tracks back to 2017 as a fork of cl-autowrap with cl-autowrap/pull/83 feature.

If you're interested in FFI, then yeah CFFI is the standard. The other comments addressed speed, I also wanted to point out https://github.com/rpav/cl-autowrap which is built on top of CFFI and can help get a wrapper up and running faster. After using autowrap's c-include you can then use CFFI basically like normal or some useful autowrap/plus-c's helper functions -- e.g. in one project, I have an SDL_Event (https://wiki.libsdl.org/SDL_Event) and to access event.key.keysym.scancode I have a helper function that's just (plus-c:c-ref event sdl2-ffi:sdl-event :key :keysym :scancode). Last year I wanted to try out using FMOD, and even though it's closed source and has a (to me) "interesting" API things worked easily: https://gist.github.com/Jach/dc2ec7b9402d0ec5836a935384cacdc... More work would be needed to make a nice wrapper, type things more fully, etc. but depending on the C library you might find someone's already done that (or made a start) and made it available from quicklisp.

In recent years there has also been cl-autowrap; caveats -

There is the cl-autowrap that can generate lisp packages from C header filesc- I am unsure if it sticks to ANSI C or goes beyond. It inturn depends on c2ffi for the first time around.

34. Julia - $74,963

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.

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!

https://github.com/JuliaLang/julia/blob/release-1.10/NEWS.md

Visit official site: https://julialang.org/

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

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".

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

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.

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...