[fantispug]

My experience is pip and virtualenv (or venv in 3.3+) works pretty well in both interactive and deployment contexts. My main gripe is Pip doesn't resolve conflicts between downstream dependencies (which I could only get a stable environment from by mapping dependencies and aggressive version locking). Conda has some advantages for certain use cases (handles libraries with installation dependencies well, curated repository), but I've never felt a need to use poetry or pyenv. Why do you have so many versions of python in production? I'd be surprised if now there are many packages that only work on specific versions (especially on 2.7 point releases).

I don't have much experience with packrat - but as opposed to pip it's another thing you need to discover and install. And so people don't do it by default when releasing code, and I've had to bisect versions of dependencies to get a working version of code. This can happen in Python too, but is rarer.