F#
julia
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F# | julia | |
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26 | 350 | |
2,199 | 44,469 | |
- | 0.8% | |
0.0 | 10.0 | |
over 1 year ago | 2 days ago | |
F# | Julia | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
F#
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old languages compilers
F# F*
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From Script to Scaffold in F#
This year I've been attempting Advent of Code in my favourite programming language, F#. This is a beginner(ish) centered post about making incremental changes from the smallest possible solution to something more robust.
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for newbie , VScode+ionide or VisualStudio
I can recommend polyglot notebooks in vs code, so you can mix different languages.Take a look athttps://fsharp.org/ for some project ideas and frameworks.
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The comeback of the Fediverse and the Old Web
I have many less followers on Mastodon than in the Birdsite (40 vs 341), yet my activity has generated many more interactions than there. Not only that, among the users who decided to interact with me I counted: a co-discoverer of the Laniakea supercluster, one of the lead developers behind F#, the author of many important books on Java & JVM, plus many others. I'm literally a nobody, but this time there was no algorithm relying on relevance and engament metrics to decide what to present to each one of us.
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Chicago and London TDD Styles for Functional Programming
FP devs differ based on language here. Elm, like F#, tends to encourage "a bunch of functions and types in a file". While Elm supports modules, we don't really care where it came from; they're all pure, all deterministic, the compiler tells us if it works.
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Performance of immutable collections in .NET
The builtin fsharp collections actually are just "immutable", not persistent as you mention. (Ref: https://github.com/fsharp/fsharp/blob/master/src/fsharp/FSharp.Core/map.fs. This is just an AVL tree that returns a copy on mutations: https://github.com/fsharp/fsharp/blob/577d06b9ec7192a6adafefd09ade0ed10b13897d/src/fsharp/FSharp.Core/map.fs#L118)
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Coming from Scala
You can dive into .NET ecosystem by trying F#. It's functional-first language so this should be familiar.
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Parsing Lambda Error Logs in ReScript & Python
ReScript code is just like F# or OCAML; it doesn’t have a function parse phase like JavaScript, so we have to define our functions and types first before we can use them. That’s fine, but makes explaining the code backwards (meaning you start at the bottom of the file and work your way up), so we’ll start at our lambda handler and explain each part, regardless of where it’s defined.
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Please put units in names
F# is a JavaScript and .NET language for web, cloud, data-science, apps and more.
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E
Also a programming joke
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!
- Julia 1.10 Highlights
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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.
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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?
ClojureCLR - A port of Clojure to the CLR, part of the Clojure project
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Roslyn - The Roslyn .NET compiler provides C# and Visual Basic languages with rich code analysis APIs.
NetworkX - Network Analysis in Python
Nemerle - Nemerle language. Main repository.
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.
VisualFSharp - The F# compiler, F# core library, F# language service, and F# tooling integration for Visual Studio
rust-numpy - PyO3-based Rust bindings of the NumPy C-API
Bridge.NET - :spades: C# to JavaScript compiler. Write modern mobile and web apps in C#. Run anywhere with Bridge.NET.
Numba - NumPy aware dynamic Python compiler using LLVM
IronScheme - IronScheme
StaticCompiler.jl - Compiles Julia code to a standalone library (experimental)