Why the dependency on numpy? We bundle a slim distribution of python with our product, and I try to keep it as small as possible. The doc says that it’s used for array conversion, but it adds ~50 MiB to my Python install to include it.
The SWIG (4.x) interface I made for RapidCode didn’t need it, but I don’t know if I tried using any of the MotionController::Move*(...) functions in it. Usually, I just use it in testing to query states and things. What parts of the interface necessitated using numpy?
The numpy dependency is for array marshalling for the (small) subset of RapidCode methods that pass arrays. That’s mostly streaming motion and several methods on the Robot class.
Yes for now it is a 64-bit module (as are all our utilities and tools). Do you still use the 32-bit libraries? If so, how long do you anticipate needing support for 32-bit? It’s not “hard” to make it work for 32-bit but would require additional builds and tests for our CI/CI pipelines.
Also, it looks like the _RapidCode.pyd DLL was built exclusively for Python 3.10. Is there any way to support other versions (also)? I realize this is going to be a constantly moving target. Is there some way that customers could build the module against their own dependencies, like could you distribute the SWIG interface file and whatever other stuff you use to build the DLL?