Translation: I've never used poetry, don't know anything about it, and I'm going to talk out of my rear end and assume that it doesn't use conventional, existing venv/pip under the hood.
There isn't a single python project out there that can't be worked on with poetry. It creates a venv. Poetry is doing a lot of things to manage automatically activating and deactivating it, etc, but it's just a venv.
False. Poetry implements it’s own dependency resolver. It does not use pip’s resolver. For most packages this is fine. For a couple packages it’s resolver does not work. Pytorch is one major ml library that is incompatible with poetry as poetry has a non-standard interpretation of local package version tags.
ISTR poetry really didn't like the black "eternal beta" versioning scheme for a while and installing it didn't work properly.
Also, it really doesn't work super well if you need to work on multiple development projects simultaneously, and when "just change the way you structure your entire project" is poetry's answer to this, the solution is "okay we won't use poetry".
Translation: I've never used poetry, don't know anything about it, and I'm going to talk out of my rear end and assume that it doesn't use conventional, existing venv/pip under the hood.
There isn't a single python project out there that can't be worked on with poetry. It creates a venv. Poetry is doing a lot of things to manage automatically activating and deactivating it, etc, but it's just a venv.