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Comment by zdkl | Hacker News Reader

I second the appreciation of the lib name, and can relate to the "I programmed Pint to scratch my own itches" line, but how does it compare to Sympy? I feel like when you must deal with units, integration with other mathematical tools is indispensable. So while I guess numpy integration is more than good enough on that front, is this lib's api enough of an improvement over Sympy's to forego all the niceties the latter incorporates?

https://docs.sympy.org/latest/modules/physics/units/index.ht...

(edit: I'm very biased; Sympy's docs and code gave me a lot of fundamental mathematical intuitions -in python- that my education hasn't.)

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It's nice to have as small dependencies as possible. If Pint provides everything your project needs, buying into the complete Sympy ecosystem is just a complexity cost.

Having used sympy for rather simple task I wonder how much cost sympy really adds. Can you elaborate? It seems to me that symbolic evaluation and unit conversuin are not too far apart and buying into this ecosystem was never a big tech debt in my eyes. (Unlike maybe scipy or numpy)

Every dependency adds complexity to your project, you might never notice it because the abstractions are water tight (for your use-case) but it’s there.

Yes but pint seems to add numpy and dask from a quick check. How is sympy worse? And maintaining sth yourself for sure adds complexity.

From the documentation:

Dependency free: it depends only on Python and its standard library. It interacts with other packages like numpy and uncertainties if they are installed

Oh I guess I looked into some build dependencies because there were actually none . This is actually a good thing more libraries should do. So I guess the only downside would be that potentially versioned dependencies/breaking changes need to be managed one level above if you want to use those parts. Is there actually a good way manage "supported" optional dependencies in python?

If you want a python unit system that is backed by sympy you can use `unyt`: https://unyt.readthedocs.io/en/stable/

Great docs. This would have made an indispensable tool in college. (Also, though, I took physics before I started CS, so I really didn’t know my way around basic programming).

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