Off the top of my head:
- What you get when you import a library depends on state that's scattered all over the system: system-managed packages, pip-managed system-global packages, pip-managed per-user packages, which virtualenv is currently active, which directory you're currently in, which directory the program you're running is in, whatever it is that conda does....
- There's no concept of reproducible builds or dependency pinning. There's "pip freeze" but that's a one-time operation that you can't then reverse, so it's only usable for leaf applications. If you're developing a library, you'd better get used to having your transitive dependencies changed on you all the time. And since the whole ecosystem is built that way, even if you use some tool that lets you make stable releases of your library, that doesn't help you develop at all.
- Virtualenvs are stateful and attached to whatever terminal you were in at the time. This interacts hilariously with the previous point: if you accidentally run "cd myproject && pip install -r requirements.txt" in the wrong terminal, you permanently, irreversibly fuck up that virtualenv. All you can do is wipe it out and try to recreate it - but, per the previous point, it probably won't come out the same as before.
- You're supposed to use pip to manage which python version each project is using. But you're supposed to use the installer for it that's distributed with the python runtime. But only certain versions of the python runtime...
- There's only one global repository. If you want to build some libraries and reuse them the same way you'd use a normal library dependency, you have to publish them to the global PyPi. I think there might be an expensive service that works around this, but there's no repository program that you can just spin up on your own servers.
It's really a lot worse than other languages. If you build a real system (like, a couple of libraries and applications) in another language (not, like, C/C++ - but even Perl or TCL will prove the point) and then come back to Python, you'll find yourself hating it all the time.