Readit NewsAlso H1B pays FICA taxes, that exemption is only for OPT. The OPT exemption can be easily removed.
from typing import Optional, Union
def square(
a: Union[int, float],
b: Optional[int] = 2
) -> float:
c = a**b
return c
I've been using Conda for 10 years as my default package manager on my devices (not pipenv or poetry etc). I started because it was "the way" for data science but I kept with it because the syntax is really intuitive to me (conda create, conda activate).
I'm not sure what problem you are solving here -- the issues with conda IMO are that it is overkill for the rest of the python community, so conda-forge has gradually declined and I typically create a conda environment then use pip for the latest libraries. Managing the conda environments though is not my issue -- that part works so well that I keep with it.
If you could explain why you created this and what problems you are solving with an example, that would be helpful. All package managers are aimed at "avoiding dependency conflicts" so that doesn't really communicate to me what this is and what real problem it solves.
Python's type ecosystem's support for proper type checked data science libraries is abysmal (`nptyping` is pretty much the most feature complete, and it too is far from complete), and has tons of weird bugs.
The Array API standard (https://data-apis.org/array-api/latest/purpose_and_scope.htm...) is a step in the right direction, but until that work is close to some sort of beta version, data science folks will have tons of type errors in their code, in spite of trying their best.