Python

It's worth noting that there are basically just 3 systems worth considering, maybe even just 2.

pip is usually part of the python distribution, so any lightweight project can be finished in 1-5 minutes with pip. It's also quite widespread and the vast majority of publishers (if not all) target pip compatibility.

Poetry is a great project management framework and it deals with dependency management beautifully. If you're doing any data engineering or backend development, for any project that has more than 1 dependency and 200 lines of code, then Poetry is probably the best tool to use. Poetry makes the whole mess with helper tools like pip-tools seem outdated.

Conda is for the crazy world of data science libraries where developers don't bother with compatibility too much. Conda does it for them. And the users of those libraries can benefit from using conda.

I think the big competition is between poetry and pip. Maybe one day poetry will come as part of some Python distributions.

Our organisation has gone all in on Poetry, no regrets so far. The UX and dlscoverability is just so much better than the other options.

I do look jealously at languages that have great official tools like go and cargo though.

It is quite telling that the one tool that covers most of the features expected from a packaging tool is one maintained by a single author: PDM.

In my experience it has been a pleasure to use it as well, even though it is quite new.

I have been using PDM for a while now and love it, can't believe I was using pip before, especially for venv handling and packaging.

I wonder, having tools like PDM or Poetry that unify the whole process, why do people prefer to use fragmented tools (one for venv, another for packaging, another for publishing)? Is it just entrenched habits or not knowing the benefits of other tools?

I'm only an intermediate python dev but pip and venv do the trick. pyenv with the virtualenv plugin is nice on my Mac machine but I don't have any such equivalent on my Windows machine, I just need to remember to enable the venv.

I used Poetry for some project but ran into some problems. It was a long time ago and I didn't really know enough about what was going on to really explain why it wasn't working well. Part of the problem was that it was on a Raspberry Pi Zero W so it was extremely slow and it is possible everything would've been fine on a more traditional setup. My understanding is that a lot of legacy tools don't define what their dependencies are in a strict way and it is a costly operation for Poetry to execute the code in the setup files or something like that. It took hours but I also think it was trying to build Python from source or something like that.

As a Python hobbyist pip and venv get what I need done and have the massive advantage of coming bundled with Python itself, but I understand that there are problems that Python professionals probably run into that aren't solved as easily.