Use PythonCall to wrap Python ArviZ #5
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Great, the package seems to load without any special handling in the CI. This seems much better than using PyCall and will allow more users to install the package with ease, so I'll finalize the change. |
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Reading JuliaPy/PythonCall.jl#237, it seems we may need JuliaLang/julia#46976 to avoid the libstdc++ error. This has been backported to Julia v1.8, so I've set the lower version bound there. |
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PyCall uses a single Python environment for all packages that use PyCall, which is very error-prone and makes guaranteeing this package loads correctly on any given system completely impossible. PythonCall has a more sane approach, where each Julia environment has a corresponding Conda environment into which all Julia packages install their Python dependencies, where our contribution to this environment is managed by a
CondaPkg.tomlfile.This PR makes the following replacements in dependencies:
The downside to PythonCall is that by default it converts (almost?) no Julia types to Python types or vice versa, so we need to do a lot more work with our interface functions to ensure a seamless user experience.