I generally tend to think that complaints about dependency management in Python are way overblown -- it's usually not a problem for me. But lately I've been trying out some off-PyPI projects to investigate time series foundation models, and it would have made my life so much easier if the implementers of these libraries hadn't decided to pin to extremely specific versions of ten or twenty different dependencies. No, your library does not need exactly NumPy 1.22.3. You're just throwing unnecessary obstacles in the way of people using it.

That pinning wouldn't really be a problem ordinarily, where I control the environment, but I'm running this particular code in a managed environment that I can't easily modify.