venvs try to economise on space by symlinking to the existing python where possible....but of course there is a way to do a full copy.
python -m venv --copies .myvenvdir
There's nothing nice about this but it does protect you from a lot of issues where it might seem to work and then behave unexpectedly. e.g. if you had a different python on the destination.
Docker doesn't just help with scripts - it also manages the problem of binary compatibility with C and C++ (and whatever) libraries. You may not have had this problem with C/C++ code so you might imagine it's all about python but I can only say it's a misery that the C/C++ crowd have been suffering with for a very long time. How does one support 3 distros each with a different version of libffmpeg installed when you're making a media player? Sometimes there's a lot of "#if FFMPEG_MAJOR > 3" in the code to cope with it.
The distro developers build each package with a bunch of patches to adapt them to the distro they're in.
It's bad enough for the distro developers to curate all this when it's their job but with python devs are living in a more minimally curated world and in some applications like ML are now dealing with wide and deep dependency trees that rival a distro.
IMO perhaps "someone" should come up with some new distributions where they make everything work together.
From the programming language side of things the solution other languages use is to... just be fast. Java is fast enough, so is C#. Javascript/Typescript can be fast-ish, Go is fast enough, Rust is definitely fast.
So a lot of other major ecosystems are just self contained. All the "big" libraries are portable and written in the language itself, so they rarely plug into C/C++ (aka distribution/OS dependencies).
So Docker was basically built primarily for slow programming languages and I guess in a weird way, for C/C++, as you say? :-)))
If they were as easy to use as python everyone would do so but they're not because they're not as dynamic and that's the price to pay. https://pypy.org/ is the usual answer if you want speed with python but then you deal with glitches and libraries that don't all work and only a few people care enough about speed to put up with that. https://www.graalvm.org/python/ is technically even more fancy and by now it might also work most of the time.