> acknowledges the shitshow that is the python library/package/environment management
I'm puzzled by this and wonder if you can provide some examples. The scientists I know tend to have incredibly disorganized R code, with a bunch of hard-coded paths and a single global environment in their home directory that all their R packages get installed to. Even stuff that seems critically important like reproducible science can be much harder than you'd expect in a lot of fields because questions like "what version of the libraries did you use" has to be answered (if it can be answered at all) by looking at the references in the paper.
Whereas in Python, I don't know how things could be any simpler. Creating an individualized environment for your project is one command. Installing packages that only live inside that environment is one `pip install` away. Most scientific work is not "distributed" in the sense of having users, but if you do ship a product to users, Python gives you the option of either relying on distribution provided packages (my preferred approach most of the time) or shipping a single binary created with something like PyInstaller.
I'm puzzled by this and wonder if you can provide some examples. The scientists I know tend to have incredibly disorganized R code, with a bunch of hard-coded paths and a single global environment in their home directory that all their R packages get installed to. Even stuff that seems critically important like reproducible science can be much harder than you'd expect in a lot of fields because questions like "what version of the libraries did you use" has to be answered (if it can be answered at all) by looking at the references in the paper.
Whereas in Python, I don't know how things could be any simpler. Creating an individualized environment for your project is one command. Installing packages that only live inside that environment is one `pip install` away. Most scientific work is not "distributed" in the sense of having users, but if you do ship a product to users, Python gives you the option of either relying on distribution provided packages (my preferred approach most of the time) or shipping a single binary created with something like PyInstaller.