I think this import flow tends to be the canonical one.
I might recommend doing something like importing from something like `numpy.version` (or some other "random" very small utils package) so that the work done on file load is still fairly small.
I might recommend doing something like importing from something like `numpy.version` (or some other "random" very small utils package) so that the work done on file load is still fairly small.
"Oh you don't have optional dependency? Then do X" needs to happen at runtime right?
In my preference order: an explicit CLI option/envvar which requires the optional dep, a flag file on the filesystem, or an ImportError attempt if you absolutely must. Use a stub/trampoline file in the conditionals so that static analyzers and laziness analysis on that file itself still work.
What would that be for numba?
For example, numba._version only imports standard library stuff so is probably good enough here[0]
It would be nice to have general querying capabilities here, of course. I just think that in practice there's at least a halfway-decent workaround in almost any real situation
[0] https://github.com/numba/numba/blob/main/numba/_version.py