That's my biggest gripe with Python packaging. Fundamentally, virtualenv is a hack for the fact that the Python ecosystem fundamentally doesn't embrace that one computer can have different projects with different dependencies. Compared to npm (for example), it's much much worse.
As one of the maintainers of virtualenv, it's my goal to move that project so that it will use the venv isolation mechanism when it is available, and have virtualenv just provide a level of UX overtop of it as well as shims for versions of Python that don't have the venv module.
Not even slightly, virtualenv is the answer to exactly that problem.
Exactly. That's my point: you shouldn't need an additional tool to solve this problem.
If anything, the problem with Python is that it does have built in packaging tools - which inevitably became outdated, and just as inevitably remained in the standard library, aka the place where modules go to die. Everyone agreed that the standard tools were terrible, but because they were standard they hung on much longer than they should have.
setuptools isn't tied to the stdlib, though it had many problems and still does. A large portion of what was holding back improvements was that there was nobody really pushing through all the political nonsense surrounding the tooling, and there was nobody to say Yes/No when a consensus couldn't be reached. For normal featured there was the PEP process, but the PEP process didn't work for a long time for packaging because Guido admits he really doesn't care much about packaging at all. Now that we have BDFL-Delegates in the form of Nick Coghlan and Richard Jones and we have people willing to push through changes even when it takes a lot of pain to argue the points we're finally seeing the engine of progress start to grind to start.
Doing that isn't really much different than a virutal environment though. The only real difference is that in a virtual environment you essentially have "named" (by file system path) sets of dependencies that are automatically "activated" when you start up the Python interpreter. In the setuptools/bundler style you have in memory sets of dependencies that are activated by calling a particular API, often done automatically via a binstub.