markkitti

7 ms·

31.
by markkitti 9mo ago
"overengineered" is not the term I would use to describe Python packaging. I would say it is "under-engineered". As in, "Why engineer a configuration file when you can just do it in code?". This tendency toward
32.
by markkitti 10mo ago
Summary: They fixed Python packaging by not having to run Python to resolve dependencies. Also, they used Rust. Moral of the story: Use less Python. Use declarative configuration and other langauges instead.
33.
by markkitti 10mo ago
>> you can literally write python wrappers of Julia compiled libraries like you would c++ ones. > Yes, please. What do I google? Why can't julia compile down to a module easily? Try JuliaC for compiling shared libraries if tha
34.
by markkitti 10mo ago
> I wish there was a way to specify the offset base with something like a C #define or compiler directive. Julia has OffsetArrays.jl implementing arbitrary-base indexing: https://juliaarrays.github.io/OffsetArrays.jl&#x2F
35.
by markkitti 11mo ago
I tried this in Julia with TidierData.jl, and it looks quite similar to the R version. using TidierData, DataFrames using PalmerPenguins: load penguins = load() @chain penguins begin DataFrame @drop_missing(body_mass_g)
36.
by markkitti 11mo ago
> Unfortunately, there's no alternative, and I don't see R as much easier, there are plenty of ugly things as well there. Have you tried Polars? It really discourages the inefficient creation of intermediate boolean arrays such
37.
by markkitti 1y ago
It sounds like there are many Python users who have acclimated to the situation of needing three or more tools to work with Python and do not see the benefit or value of being able to do this all with one potentially faster tool. While I un
38.
by markkitti 1y ago
What tooling do you use?
39.
by markkitti 1y ago
The creators got burned on Swift for TensorFlow, their first MLIR project. One of the problems with that first venture under Google was that the language was not Python.
40.
by markkitti 1y ago
The Python superset concept was always a gimmick. The goal was always to juxtapose Python with a language that superficially looks like Python in order for you to completely migrate from Python to Mojo. It is just providing a smooth ramp fo
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by markkitti 1y ago
Please come up with better names for these models. This sounds like the processor in my Mac Studio.
42.
by markkitti 1y ago
It looks like JuliaHub is going to take on Simulink with Dyad Studio under a source-available license.
43.
by markkitti 1y ago
Agreed. This should have been Python 4.
44.
by markkitti 2y ago
It's funny how much easier GPU support, especially vendor agnostic GPU support, is in Julia.
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by markkitti 3y ago
Even the term "oversampling" implies that sampling beyond Nyquist rate is excessive. I think you would agree that one is not being excessive. It is necessary to sample well beyond accepted "Nyquist rate" in order to reco
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by markkitti 3y ago
MATLAB® by MathWorks
47.
by markkitti 3y ago
Apparently ChatGPT does pretty well with Julia. https://www.stochasticlifestyle.com/chatgpt-performs-better-... It does take some asking around to discover the optimal Julia workflow with Revise.jl, PkgTemplates.jl, VSCode
48.
by markkitti 3y ago
After looking at Mojo, I appreciated all the paradigms that Julia was pushing forward even more than I did before. Mojo's greatest asset and curse is focusing on being a better Python. Julia's greatest asset and curse is trying to
49.
by markkitti 3y ago
Are there solid C interfaces that can be used? A large part of why I started using Julia is because calling into other languages through the C FFI is pretty easy and efficient. Most of the wrappers are a single line. If there is not existin
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by markkitti 3y ago
I'm not sure that's a fair description at this point. They have distributed some SDKs at this point. I really do wish it were open source already though. I know they have laid out a roadmap for opening the source.
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by markkitti 3y ago
Using Cython via pure Python mode seems pretty compelling if you all you need is compilation. Compilability is just the beginning though.
52.
by markkitti 3y ago
There is https://github.com/FluxML/Torch.jl . There are also Julia native frameworks such as FluxML, https://fluxml.ai/ .
53.
by markkitti 3y ago
One of my favorite things recently is using JS/TS with Julia, usually via a Pluto.jl notebook. There are also some nice demonstrations showing Julia compiled to web assembly. https://tshort.github.io/WebAssemblyCompiler
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by markkitti 3y ago
How about a 16K Hello World? julia> using StaticTools, StaticCompiler julia> hello_world() = printf(c"Hello World\n") hello_world (generic function with 1 method) julia> compile_executable(hello_world, (),
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Webassemblycompiler.jl: Compile Julia Code to WebAssembly(tshort.github.io)
6 points by markkitti 3y ago|1 comments
56.
by markkitti 3y ago
Using recent features of WebAssembly such as the garbage collector, Tom Short provides a new demonstration of compiling Julia to WebAssembly via binaryen along with three live examples: the Lorenz model with OrdinaryDiffEq, making interacti
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by markkitti 3y ago
> do I want integers like Python or integers like C? Yes. Julia has BigInt and Cint. Maybe there could be a more Pythonic implementation that scales between machine types and BigInt. That would not be hard to implement in Julia. I just h
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by markkitti 3y ago
I honestly do not understand comments like this with regard to an open source project. The language and its libraries are rather hackable as is with rather powerful packages. While I may not agree with every decision, I do not complain that
59.
by markkitti 3y ago
You can create a shared library via PackageCompiler.jl today and `@cfunction`. It's just not as modular as it could be. https://julialang.github.io/PackageCompiler.jl/stable/libs.h...
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by markkitti 3y ago
No. Julia runs natively on ARM. julia> versioninfo() Julia Version 1.9.3 Commit bed2cd540a1 (2023-08-24 14:43 UTC)

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