Right, but when you install something from a Pipfile / Pipfile.lock, then sometimes it goes on to try to compile a C library, while other times it doesn't. So it's not just that there are multiple Pythons. It's that there's so much native C code floating around that it really hampers portability.

Example: numpy is widely used in the data science world for efficiently computing on tabular data. Of course, all the underlying crunching happens in C code. As of a year ago, getting it to run on an M1 Mac was a nightmare. Oh, don't use Homebrew. Use Conda. Or follow these weird steps. I haven't tried again recently, but uggh. Depending on *how* you install Python, you may have different challenges getting all the libraries you need.

For contrast, in Java, there's relatively little native code that comes along with most libraries. They're mostly just pure Java. I installed a JVM on my M1 Mac and all my old stuff just worked. No tweaking. No corner cases. It all just worked the first time.