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I can't find a good comparison to Conda - is the main distinction simply that Poetry uses the official repos? For people working outside of scientific Python:

I can't find a good comparison to Conda - is the main distinction simply that Poetry uses the official repos? For people working outside of scientific Python: conda is a package and env manager maintained by a private company that's become the go-to because it's really good at handling binary dependencies.

tduberne 7y ago
Can you really build packages using solely Conda? As far as my understanding goes, conda focuses on providing virtual environments for interactive use, but to build and distribute a package on conda forge, you still need to rely on setuptools/distutils. My impression here is that Poetry aims more at _replacing_ the pip + setuptools toolchain. Users of your package could still install it using conda, if relevant. It seems a bit limited in what it can do at the build step, unfortunately, so it is not a replacement yet. Coming from the Java world, I pass my days dreaming of a "maven for python", and this project definitely goes into that direction. I will definitely keep it on my radar.
- flyingdeertown 7y ago
  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.
  - tduberne 7y ago
    That basically confirms the feeling I was trying to express, in that conda and poetry seem to solve different problems: conda focuses on easing the distribution to the end user, whereas poetry tries to simplify managing the build on the developer side.
flyingdeertown 7y ago
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.

tduberne 7y ago

Can you really build packages using solely Conda? As far as my understanding goes, conda focuses on providing virtual environments for interactive use, but to build and distribute a package on conda forge, you still need to rely on setuptools/distutils. My impression here is that Poetry aims more at _replacing_ the pip + setuptools toolchain. Users of your package could still install it using conda, if relevant. It seems a bit limited in what it can do at the build step, unfortunately, so it is not a replacement yet. Coming from the Java world, I pass my days dreaming of a "maven for python", and this project definitely goes into that direction. I will definitely keep it on my radar.

flyingdeertown 7y ago
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.
- tduberne 7y ago
  That basically confirms the feeling I was trying to express, in that conda and poetry seem to solve different problems: conda focuses on easing the distribution to the end user, whereas poetry tries to simplify managing the build on the developer side.

flyingdeertown 7y ago

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.