I’m disappointed your post did not cover using conda. As the pipenv drama has rolled on, I’ve moved from viewing conda merely as the best user experience in Python environment & package management to instead viewing it as the only serious option for professional scientific computuing work (and quite possibly any professional Python work at all).
I read that page and looked for the reason I don't use Conda (because I already have virtualenvs and I'm not prepared to burn them all down):
> Myth #5: conda doesn't work with virtualenv, so it's useless for my workflow
> Reality: You actually can install (some) conda packages within a virtualenv, but better is to use Conda's own environment manager: it is fully-compatible with pip and has several advantages over virtualenv.
> [...] the result seems to be fairly brittle – for example, trying to conda update python within the virtualenv fails in a very ungraceful and unrecoverable manner, seemingly related to the symlinks that underly virtualenv's architecture.
Doesn't sound like much of a myth then, if Conda's take on virtualenv is "you can technically do this, but everything will break ungracefully and unrecoverably, so please don't".
He's not saying that you _should_ install conda within a virtualenv, but that some have tried with some success.
At the end, one of his conclusions is: "If you want to install Python packages within an Isolated environment, pip+virtualenv and conda+conda-env are mostly interchangeable". So don't change if you don't have to.
But he does give reasons why conda may be superior to virtualenv -- managing different version of Python, tracking non-Python dependencies, true isolation of environments, etc.
I should probably write another post once I've tried conda a bit more. I've used it very recently for some numpy/pytorch environment and it was quite nice.
This is deeply untrue for conda. Even very complex environments build in less than a minute. I can believe there are corner cases where conda is very slow, but claiming conda takes 5 minutes for trivial environments is flat out wrong. Perhaps it is issues with a firewall, VPN connection or something else, absolutely no chance that is from normally executing conda.
The last one in that thread is 11 minutes. And, I just did `time conda create -n test -y anaconda pytest-cov pytest-xdist coverage sphinx_rtd_theme flake8` on my Macbook, and it clocked in at 36 minutes! Probably, this is affected by also having the condaforge channel active (which I need), but it's definitely not from some network/VPN issues. Everyone I work with has similar problems. So don't tell me there's "absolutely no chance that is from normally executing conda".