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.