kotlin-script-examples VS julia

Compare kotlin-script-examples vs julia and see what are their differences.

kotlin-script-examples

Examples of Kotlin Scripts and usages of the Kotlin Scripting API (by Kotlin)
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kotlin-script-examples julia
1 348
282 44,062
1.4% 0.7%
3.9 9.9
about 1 month ago 5 days ago
Kotlin Julia
Apache License 2.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

kotlin-script-examples

Posts with mentions or reviews of kotlin-script-examples. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-11-06.

julia

Posts with mentions or reviews of julia. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-02-15.
  • Dart 3.3
    2 projects | news.ycombinator.com | 15 Feb 2024
    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!

  • Best Programming languages for Data Analysis📊
    4 projects | dev.to | 7 Dec 2023
    🌟 Visit Github
    4 projects | dev.to | 7 Dec 2023
    Visit official site: https://julialang.org/
  • Potential of the Julia programming language for high energy physics computing
    10 projects | news.ycombinator.com | 4 Dec 2023
    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

    10 projects | news.ycombinator.com | 4 Dec 2023
    The one you need is this which is already merged but was after the 1.10 feature freeze so it has to wait till 1.11, though you can test it with nightly builds which is available on julialang site: https://github.com/JuliaLang/julia/pull/51435

    Unfortunately, the core devs are not too chatty about standalone binaries, because of how Julia's internals are set there are going to be a lot of unforeseen challenges, so they are not trying to promise how things will be rather let's wait and see how things will turnout. Since packagecompiler.jl already has C ABI and one goal discussed about binaries being easily callable from other languages and vice versa, I would bet that it will have shared libraries.

  • Rust std:fs slower than Python
    7 projects | news.ycombinator.com | 29 Nov 2023
    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".

  • Julia as a unifying end-to-end workflow language on the Frontier exascale system
    5 projects | news.ycombinator.com | 19 Nov 2023
    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.

  • Getaddrinfo() on glibc calls getenv(), oh boy
    10 projects | news.ycombinator.com | 16 Oct 2023
    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...

  • Julia and Mojo (Modular) Mandelbrot Benchmark
    10 projects | news.ycombinator.com | 8 Sep 2023
  • Ask HN: Does Your GitHub Repo Need a Landing Page
    2 projects | news.ycombinator.com | 27 Aug 2023
    I'm really not fond of that agpt landing page. So many red flags; the AI-generated background, mailing letter box with accompanying email-beggar text, the Discord button (!!!) being given as much space as the Github repo click-through... it's a mess. The whole website feels more boilerplate than content. I mean, look at these quotes!

    > With the help of the incredible open-source community, we’re making approximately a month’s progress every 48 hours.

    > Auto-GPT is pushing for the best, autonomous AI assistant for every device for every person. In the near future, we want you to be able to accomplish more everyday.

    > We have come to define ourselves by what we do. If this can be automated, how may we then define ourselves? By what we create!

    Every line of copy I read from that site makes me feel like I'm getting dumber instead of learning about their product. If you are building a landing page for a serious software project, you need a more professional approach. You can be playful if you want, but the landing page somehow manages to be less informative than the Github repo in the example you've listed.

    Since everyone will ask, here are some software project landing pages that strike me as well-designed:

    https://julialang.org/

    https://nixos.org/

    https://www.scheme.org/

What are some alternatives?

When comparing kotlin-script-examples and julia you can also consider the following projects:

jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

NetworkX - Network Analysis in Python

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.

rust-numpy - PyO3-based Rust bindings of the NumPy C-API

Numba - NumPy aware dynamic Python compiler using LLVM

F# - Please file issues or pull requests here: https://github.com/dotnet/fsharp

StaticCompiler.jl - Compiles Julia code to a standalone library (experimental)

Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).

LUA - A programming language based upon the lua programming language

PackageCompiler.jl - Compile your Julia Package

femtolisp - a lightweight, robust, scheme-like lisp implementation

JLD2.jl - HDF5-compatible file format in pure Julia