PlutoUI.jl VS julia

Pluto notebooks are distinct from Jupyter notebooks in that they are reactive: https://github.com/JuliaPluto/PlutoUI.jl

An easy alternative is using a Pluto notebook with PlutoUI.jl. You can create input fields, sliders, check boxes, etc in a very easy way. It’s an easy and fast way to create a simple GUI.

ubuntu@vm1:~$ curl -fsSL https://install.julialang.org | sh - info: downloading installer Welcome to Julia! This will download and install the official Julia Language distribution and its version manager Juliaup. Juliaup will be installed into the Juliaup home directory, located at: /home/ubuntu/.juliaup The julia, juliaup and other commands will be added to Juliaup bin directory, located at: /home/ubuntu/.juliaup/bin This path will then be added to your PATH environment variable by modifying the profile files located at: /home/ubuntu/.bashrc /home/ubuntu/.profile Julia will look for a new version of Juliaup itself every 1440 seconds when you start julia. You can uninstall at any time with juliaup self uninstall and these changes will be reverted. ✔ Do you want to install with these default configuration choices? · Proceed with installation Now installing Juliaup Installing Julia 1.7.2+0 (x64). Julia was successfully installed on your system. Depending on which shell you are using, run one of the following commands to reload the the PATH environment variable: . /home/ubuntu/.bashrc . /home/ubuntu/.profile pkg> add https://github.com/JuliaPluto/PlutoUI.jl Cloning git-repo `[https://github.com/JuliaPluto/PlutoUI.jl`](https://github.com/JuliaPluto/PlutoUI.jl`) Updating git-repo `[https://github.com/JuliaPluto/PlutoUI.jl`](https://github.com/JuliaPluto/PlutoUI.jl`) Resolving package versions... Installed Reexport ─────────────── v1.2.2 Installed IOCapture ────────────── v0.2.2 Installed AbstractPlutoDingetjes ─ v1.1.4 Installed JSON ─────────────────── v0.21.3 Installed Hyperscript ──────────── v0.0.4 Installed FixedPointNumbers ────── v0.8.4 Installed HypertextLiteral ─────── v0.9.3 Installed Parsers ──────────────── v2.3.0 Installed ColorTypes ───────────── v0.11.0 Updating `~/.julia/environments/v1.7/Project.toml` [7f904dfe] + PlutoUI v0.7.38 `[https://github.com/JuliaPluto/PlutoUI.jl#main`](https://github.com/JuliaPluto/PlutoUI.jl#main`) Updating `~/.julia/environments/v1.7/Manifest.toml` [6e696c72] + AbstractPlutoDingetjes v1.1.4 [3da002f7] + ColorTypes v0.11.0 [53c48c17] + FixedPointNumbers v0.8.4 [47d2ed2b] + Hyperscript v0.0.4 [ac1192a8] + HypertextLiteral v0.9.3 [b5f81e59] + IOCapture v0.2.2 [682c06a0] + JSON v0.21.3 [69de0a69] + Parsers v2.3.0 [7f904dfe] + PlutoUI v0.7.38 `[https://github.com/JuliaPluto/PlutoUI.jl#main`](https://github.com/JuliaPluto/PlutoUI.jl#main`) [189a3867] + Reexport v1.2.2 [a63ad114] + Mmap [2f01184e] + SparseArrays [10745b16] + Statistics Precompiling project... 10 dependencies successfully precompiled in 23 seconds (24 already precompiled)

I realize that, and there may be no rational reason for you to switch to a setup like mine. But, aside from avoiding such things a Wordpress exploits, my approach turned out to have other advantages. Over the years I added to my knowledge and taught myself how to provide things other than static files. Today my readers can use gnuplot in a Jupyter notebook, and interactive Pluto¹ notebooks backed by Julia running on a VPS. No canned solution exists for this, and in fact I had to work with the Pluto developers to iron out some kinks. This is only possible because I have total control over the servers. If you know will only ever want to serve static files, there are simpler options (with potential pitfalls). But those options are also limiting, in case one day you want to do something unusual.

[1] https://github.com/JuliaPluto/PlutoUI.jl

When you are using Pluto (https://github.com/fonsp/Pluto.jl ) instead of Juypter you can very easily combine plots with reactive UI elements (like sliders, selectors, etc. - see https://github.com/fonsp/PlutoUI.jl ) to allow interactive exploration of data.

The only thing I think really isn't covered is PlutoUI (https://github.com/fonsp/PlutoUI.jl), which you can find in a sample notebook in Pluto.

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...