StarWarsArrays.jl
BinaryBuilder.jl
StarWarsArrays.jl | BinaryBuilder.jl | |
---|---|---|
10 | 5 | |
122 | 379 | |
- | 1.1% | |
0.0 | 6.5 | |
almost 2 years ago | 4 days ago | |
Julia | Julia | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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StarWarsArrays.jl
- Star Wars Arrays
- It starts at 0 right?
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PyCharm is the worst IDE I have used. /s
I raise you https://github.com/giordano/StarWarsArrays.jl
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How do some of my coworkers still use ML
Why not Star Wars Indices (4,5,6,1,2,3,7,8,9...)? https://github.com/giordano/StarWarsArrays.jl
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Dealing with strings in Julia, patterns and anti-patterns
> The documentation disagrees about string indices not starting with 1 As priorly said, I'm speaking about strings, not `String` in particular. So, to write code which work for all AbstractString (which have basic string functions), you must not assume that the first indexing is 1, you can have degenerate cases such as : https://github.com/giordano/StarWarsArrays.jl (this is for vectors, but creating a similar type, for AbstractString isn't impossible) or just strings with an offset indexing.
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The counter-intuitive rise of Python in scientific computing
There are other choices like https://github.com/simonster/TwoBasedIndexing.jl and https://github.com/giordano/StarWarsArrays.jl if you do not like 1-based indexing.
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PyTorch: Where we are headed and why it looks a lot like Julia (but not exactly)
This is a total non issue as indexing is an operation that is subject to multiple dispatch. For a humorous example see https://github.com/giordano/StarWarsArrays.jl
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Arrays start from bony[1]
The cool thing with Julia is that array indices aren't inherent properties, and may be changed locally by using appropriate wrappers. This means that the same underlying array may start at 0 in one part of the code, at 1 in another, and perhaps use the star-wars indexing in yet another section if that's necessary.
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Why does Julia adopt 1-based index?
Adding https://github.com/giordano/StarWarsArrays.jl to the list for some extra spice
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some may hate it, some may love it
You should also check out https://github.com/giordano/StarWarsArrays.jl and https://github.com/giordano/RandomBasedArrays.jl
BinaryBuilder.jl
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Is Julia suitable today as a scripting language?
There are some efforts and the startup times are getting better with every release and there's BinaryBuilder.jl.
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Because cross-compiling binaries for Windows is easier than building natively
There is the Julia package https://github.com/JuliaPackaging/BinaryBuilder.jl which creates an environment that fakes being another, but with the correct compilers and SDKs . It's used to build all the binary dependencies
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Discussion Thread
https://binarybuilder.org/. You can do it manually obviously, but this is easier.
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PyTorch: Where we are headed and why it looks a lot like Julia (but not exactly)
> The main pain point is probably the lack of standard, multi-environment packaging solutions for natively compiled code.
Are you talking about something like BinaryBuilder.jl[1], which provides native binaries as julia-callable wrappers?
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[1] https://binarybuilder.org
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What to do about GPU packages on PyPI?
Julia did that for binary dependencies for a few years, with adapters for several linux platforms, homebrew, and for cross-compiled RPMs for Windows. It worked, to a degree -- less well on Windows -- but the combinatorial complexity led to many hiccups and significant maintenance effort. Each Julia package had to account for the peculiarities of each dependency across a range of dependency versions and packaging practices (linkage policies, bundling policies, naming variations, distro versions) -- and this is easier in Julia than in (C)Python because shared libraries are accessed via locally-JIT'd FFI, so there is no need to eg compile extensions for 4 different CPython ABIs (Julia also has syntactic macros which can be helpful here).
To provide a better experience for both package authors and users, as well as reducing the maintenance burden, the community has developed and migrated to a unified system called BinaryBuilder (https://binarybuilder.org) over the past 2-3 years. BinaryBuilder allows targeting all supported platforms with a single build script and also "audits" build products for common compatibility and linkage snafus (similar to some of the conda-build tooling and auditwheel). There was a nice talk at AlpineConf recently (https://alpinelinux.org/conf/) covering some of this history and detailing BinaryBuilder, although I'm not sure how to link into the video.
All that to say: it can work to an extent, but it has been tried various times before. The fact that conda and manylinux don't use system packages was not borne out of inexperience, either. The idea of "make binaries a distro packager's problem" sounds like a simplifying step, but that doesn't necessarily work out.
What are some alternatives?
OffsetArrays.jl - Fortran-like arrays with arbitrary, zero or negative starting indices.
functorch - functorch is JAX-like composable function transforms for PyTorch.
TailRec.jl - A tail recursion optimization macro for julia.
Yggdrasil - Collection of builder repositories for BinaryBuilder.jl
TwoBasedIndexing.jl - Two-based indexing
HTTP.jl - HTTP for Julia
Cython - The most widely used Python to C compiler
dh-virtualenv - Python virtualenvs in Debian packages
wenyan - 文言文編程語言 A programming language for the ancient Chinese.
RDKit - The official sources for the RDKit library
RandomBasedArrays.jl - Hassle-free arrays: the first index is always random
mxe - MXE (M cross environment)