The python overhead is something I've noticed as well in a system that runs a lot of python scripts. Especially with a few more modules imported, the interpreter and module loading overhead can be quite significant for short running scripts.

Numpy was particularly slow during imports, but I didn't see an easy way to fix this apart from removing it entirely. My impression was that it does a significant amount of work on module loading, without a way around it.

I think the other side of "surprisingly slow" is that computers are generally very fast, and the things we tend to think of as the "real" work can often be faster than this kind of stuff that we don't think about that much.