To me, yes. Poetry for me has been fairly straightforward, in anything I needed to do (dependency management, package publishing, etc).

Poetry has been the one I've settled on as well. It "Just Works™" for everything I've used it for thus far, and it's even been easy to convert older methods I've tried to the Poetry way of doing things.

It's not.

See https://imgs.xkcd.com/comics/python_environment_2x.png

Or sometime the computer is haunted and my colleague had problems installing tensorflow. To this day he has no working tensorflow.

I suppose we can follow memes or facts.

Please note I never used tensorflow on that computer in fact I never used tensorflow, but this is my experience: https://gist.github.com/takeda/89ec29501b6e8641415668f22f3e9...

It succeeded after first try.

I do see that in their repo[1] they use a non standard way to build the package. They use Bazel, but that's Google for you. They never do things everyone else is doing. I'm not sure why this is Python problem rather than package problem.

They have tons of open issues around building: [2]

[1] https://github.com/tensorflow/tensorflow

[2] https://github.com/tensorflow/tensorflow/labels/type%3Abuild...

That's the thing. It's not a meme. It's a joke, that rings true.

It works fine for me.

Not for him. Same package, nearly identical laptops, different outcomes.

And I as newcomer to Python, there are like four (pip, venv, brew, conda) cli APIs that I had to learn just to get working on some Python file.