flyingdeertown

I use conda as a python manager and poetry as an environment manager. For every project I just create a new conda environment with the bare minimum python 3.x version I need. Then I use poetry to handle the dependencies and manage the environment for me. For stuff that are strictly scientific or numerical in nature and I need things from conda (ie MKL accelerated numpy) I skip the part with poetry and just use conda to install my packages to avoid any potential issues.

Well conda packages don't need to be python based, so technically yes you can build and package up whatever your heart desires.

conda build recipes are essentially just shell scripts that conda runs in a sandbox, taking care of library paths and so on. You could, if you really wanted to, develop a poetry based Python package and then have your conda build script use/run poetry to build and package the python package, and then add whatever lines are necessary to the build recipe to make that the package that gets installed by conda.

My experience was the opposite. pipenv always told me something couldn't be installed because of version mismatches and poetry has never given me any trouble.