In principle, conda-forge is a language agnostic package ecosystem. Since there is also a
juliacall package for R on CRAN, the
py prefix was added to disambiguate the Python package from the similarly named R package.
pyjuliapkg is a dependency of
pyjuliacall. Thus installing
pyjuliacall will also install
pyjuliapkg. You can install
pyjuliacall via the following
conda install conda-forge::pyjuliacall
On initialization, JuliaCall looks for an existing
julia installation via
juliaup. If it does not find one, then it will download and install
Here is an example Python REPL session showing
juliacall being imported.
>>> import juliacall
[juliapkg] Locating Julia ^1.6.1
[juliapkg] Using Julia 1.10.0 at ~/.julia/juliaup/julia-1.10.0+0.aarch64.apple.darwin14/bin/julia
[juliapkg] Using Julia project at ~/miniforge3-arm64/envs/foofoo/julia_env
[juliapkg] Installing packages:
julia> import Pkg
julia> Pkg.add([Pkg.PackageSpec(name="PythonCall", uuid="6099a3de-0909-46bc-b1f4-468b9a2dfc0d")])
There is also a Julia package on conda-forge which I help to maintain. Julia 1.10 was recently packaged. This package is only available for Linux and macOS on Intel x86-64 processors.
The conda-forge packages
pyjuliapkg do not explicitly depend the conda-forge package
julia. If you do not install the conda-forge
julia package, then
pyjuliacall will proceed to look for existing Julia install and proceed to download the official Julia binaries from julialang.org. If you do install the conda-forge
julia package, then JuliaCall will use that version of Julia when using that conda environment.
To learn more about JuliaCall, please see @cjdoris’s original package announcement on the topic.
You can also find the documentation for JuliaCall below.