Any benefits of using this project, virtualenv is now built in in Python 3, and it never was missing anything when I was using it.
venv is shipped with Python 3, not virtualenv, unless I am mistaken.
Yeah, I guess it's called different, but has the same functionality and is a drop-in replacement. I'm surprised there's still development on virtualenv after 2.7 is EOL.
This explains why chef started yelling at work 4am PST. Upgrading virtualenv via pip install --upgrade virtualenv would fail. This sort of broken upgrade also happened with pip itself recently and required a manual fix, package maintainers refused to revert the release.
This isn't the most readable changelog, the main takeaway is at the bottom: The package has been completely rewritten.
This release is exciting, but taking a step back, it's still really disappointing how minimal and rough around the edges venv is considering how important the library ecosystem has been to Python's continued success. I really wish we had a packaging/environment tool the same quality as Rust's cargo.
I've just been using conda environments lately. How much am I missing by not using virtualenv instead?
Why did you take up conda in the first place ? venv and pip are part of the python project and conda seems to be yet another package manager in the already crowded and shady space of npm, brew, ports apt yum etc. I've always been puzzled at how they managed to shoehorn themselves into the python ecosystem while offering no distinct value as far as I can see.
This is an HPC environment, so besides a nice, working version of TensorFlow, there are large numbers of pre-built scientific/bioinformatics packages. This is a huge win when you're running with a skeleton crew.
Also, note this is for system-wide, not per-user usage. I'm kind of vague on how virtualenv would handle this, plus it feels like it's changed a lot over time. (?)
They provide useful packages that aren't (easily) available via pip. For example, numpy with MKL or Tensorflow GPU builds that don't require/presuppose CPU support for new vector instructions. Moreover, their package installs don't break as randomly as some pip packages, presumably because someone bothered to do more testing of commonly used packages included in the default package repository.