I like hatch a lot, although I haven’t used environments much yet. But I think you’re missing my point (or maybe I’m missing yours).
I have a directory on my PC, C:\Work\Scratch, where I keep all sorts of junk - snippets of code in C, Python, and all sorts of other languages, directories with temporary work, etc. There’s no structure and barely any organisation. The other day, I wanted a script that would take a number and display factors of that number and other numbers “close” to it. I opened a new file, and started coding. I needed sympy in the script as it has factorisation routines. How would hatch environments have helped me there? My scratch directory isn’t in a hatch-based project, and the code I was writing wasn’t worth making into a project.
At the moment, I use pew to make a temporary virtualenv, install sympy, and run my script. But I have to remember (or read the code to check) what dependencies my script has when I run it, and build a throwaway virtualenv each time.
This use case is why I often push back against people saying “using packages from PyPI is easy”. It is, but package management is a big enough overhead on a throwaway script that sticking to the stdlib can end up being preferable.