LibTIFF.jl
PyCallChainRules.jl
| LibTIFF.jl | PyCallChainRules.jl | |
|---|---|---|
| 1 | 1 | |
| 0 | 56 | |
| - | - | |
| 6.5 | 10.0 | |
| 6 months ago | almost 2 years ago | |
| Julia | Julia | |
| MIT License | MIT License |
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LibTIFF.jl
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Julia 1.10 Released
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 existing driver support, I would pass the C headers through Clang.jl, which automatically wraps the C API in a C header.
https://github.com/JuliaInterop/Clang.jl
I most recently did this with libtiff. Here is the Clang.jl code to generate the bindings. It's less than 30 lines of sterotypical code.
https://github.com/mkitti/LibTIFF.jl/tree/main/gen
The generated bindings with a few tweaks is here:
https://github.com/mkitti/LibTIFF.jl/blob/main/src/LibTIFF.j...
PyCallChainRules.jl
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Julia 1.10 Released
> Can I use PyTorch or JAX comfortably in Julia?
There is https://github.com/rejuvyesh/PyCallChainRules.jl which makes this possible. But using some of the native Julia ML libraries that others have mentioned is preferable.
What are some alternatives?
Torch.jl - Sensible extensions for exposing torch in Julia.
threads - Threads for Lua and LuaJIT. Transparent exchange of data between threads is allowed thanks to torch serialization.
astropy - Astronomy and astrophysics core library
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
Clang.jl - C binding generator and Julia interface to libclang
erfa - Essential Routines for Fundamental Astronomy. Maintainers: @eteq @mhvk @sergiopasra
Lux.jl - Explicitly Parameterized Neural Networks in Julia