LLVM_full_jll.jl
Gtk.jl
LLVM_full_jll.jl | Gtk.jl | |
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1 | 3 | |
3 | 287 | |
- | 0.0% | |
6.0 | 2.8 | |
21 days ago | about 1 month ago | |
Julia | Julia | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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LLVM_full_jll.jl
Gtk.jl
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What is lacking in Julia ecosystem?
I am not clear what you have in mind here. Are QT or Gtk bindings not be sufficient? Or perhaps something like CImGui?
- How to learn compilers: LLVM Edition
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JuliaCall Update: Automated Julia Installation for R Packages
Indeed, the use of BinayBuilder was an important step forward. Before we had the problem that different package would require different versions of e.g. zlib (https://github.com/JuliaGraphics/Gtk.jl/pull/387). BinayBuilder made the package installation mush more robust.
What are some alternatives?
Zlib_jll.jl
QML.jl - Build Qt6 QML interfaces for Julia programs.
libLLVM_jll.jl
CImGui.jl - Julia wrapper for cimgui
llvm-project - The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.
BinDeps.jl - Tool for building binary dependencies for Julia modules
Descartes.jl - Software Defined Solid Modeling
AxisArrays.jl - Performant arrays where each dimension can have a named axis with values
Geodesy.jl - Work with points defined in various coordinate systems.
xarray - N-D labeled arrays and datasets in Python
QuerySQLite.jl - SQLite backend for Query.jl
Overview-of-the-Julia-Python-R-Universe - Contribute to the side by side overview of the three leading open source data science ecosystems of today