sol2
julia
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sol2 | julia | |
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20 | 350 | |
3,935 | 44,510 | |
- | 0.9% | |
3.9 | 10.0 | |
8 days ago | 3 days ago | |
C++ | Julia | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
sol2
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Any tips for how to make moddable games?
As someone said, make the game data-driven is a good first step but I will say, also have some sort of way to add additional game logic. For C++ games, lua is really easy to embed the interpreter in your C++ binary, read in the files from a directory (like /mods) with the C++ filesystem api new in C++17, and it's very easy to use SoL to write an API for lua specific to your game. Many games use lua in this way and it's probably the most common mod path setup.
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Script Interoperability
I've only ever done this from C++, but it's using the same lua C library, so should be durable from C as well. You can look up how sol2 or any other wrapper libraries do it.
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Need help trying to embed lua in c++
Consider sol2
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CBN Changelog: December 3, 2022. Improved LUA support in progress!
This version relies on a Lua C++ wrapper called sol2 to hide Lua stack management from the developer, so creating new bindings can be done by adding a few lines of human-readable C++. It still has to be done manually, but at least sol2 is able to automatically figure out types of objects being bound, so it's not much different from our de-/serialization code.
- RTS programming game where you write real C++ code to control your player.
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why?
Here's an example: sol2
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Tools for rolling your own engine
Here is link number 2 - Previous text "Sol"
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Storing pointers to C++ data in Lua in a type-safe-ish manner that are comparable on the Lua side.
Have you considered using sol2? https://github.com/ThePhD/sol2 Or if you don't want to switch over, you can at least look at their code and see how they handle this.
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jluna: a new Julia <-> C++ Wrapper
It is half of a pun as I was inspired by [sol3](https://github.com/ThePhD/sol2) which is a lua <-> c++ wrapper. Sol means sun and the julia c-api prefixes all it's functions with jl, luna means moon so it is pronounced "jay luna"
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A new C++ <-> Julia Wrapper: jluna
If you want to be portable I'd recommend C++ and Lua, I used those for years and it runs on everything and there's this most amazing wrapper API which was a huge inspiration
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?
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.
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
pybind11 - Seamless operability between C++11 and Python
NetworkX - Network Analysis in Python
ChaiScript - Embedded Scripting Language Designed for C++
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.
SWIG - SWIG is a software development tool that connects programs written in C and C++ with a variety of high-level programming languages.
rust-numpy - PyO3-based Rust bindings of the NumPy C-API
Wren - The Wren Programming Language. Wren is a small, fast, class-based concurrent scripting language.
Numba - NumPy aware dynamic Python compiler using LLVM
V8 - The official mirror of the V8 Git repository
F# - Please file issues or pull requests here: https://github.com/dotnet/fsharp