Exposing julia packages to python users

General Usage
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Hello everyone.

I have a Julia package which I would like to expose to python users.

Seems the most obvious way would be using juliacall, similar to how diffeqpy seems to do it. I tried working with that approach for now, but I’ve got a few questions.

  • Would it be best to have the python code at a separate repository (like diffeqpy), or at the same one as the Julia code? Any (dis)advantages in either way?

  • The package I’m working on has a GLMakie extension, which provides some very useful GUI capabilities. Seems like using GLMakie from juliacall is not seamless, and some workarounds might be required. Has anybody managed to deal with this matter in an elegant way (e.g. wrap Makie functions with juliacall.interactive() somewhere in the python codebase)?

  • More generally, would there be any pitfalls to avoid when working with Julia package extensions in this context?

  • I was wondering whether the relatively recent updates in AOT compilation would enable better solutions to this, exposing the same functionality while avoiding a Julia installation for the python user. Has anybody experimented with this?

  • Any other methods or resources I’m missing here?

I was also thinking, since most people are probably not going to be migrating from python to Julia anytime soon, might be useful to have such information for Julia package developers available somewhere in the documentation?

Any help or comments would be much appreciated!

2

I don’t know how complex your package is or how long a single function call takes. But as long as your functions are large and take at least 5ms to execute, you could use a JSON over HTTP approach. I found this less error-prone than JuliaCall. In my case, the Python code had to use an outdated Python version that was not supported by JuliaCall.

Example package: GitHub - ufechner7/pykitemodels: Kite power system models for Python · GitHub