I think you're arguing both sides of the argument -- numpy arrays do have a lot
of similar, related operations (because numpy uses them internally -- since
they're more efficient) which means they're not fringe.
I'm advocating that the built-in list class add the efficient, convenience
methods
Michio,
Are you trying to open the ipynb file with python? You need Jupyter Notebook to
run ipynb files. Try installing jupyter notebook (cmd: pip install jupyter)
then launching the jupyter notebook py server (cmd: jupyter notebook). You
should be able to use the file browser in the notebook w
Peter,
This isn't a ram consideration as much it's a logical consideration. There are
a lot of ways to handle this, I REALLY don't want to use a package here. Bit
masking is incredibly useful for permutations/combinatoric algorithms. I can
create my own class wrapper or functions, and optimize,
@MRAB,
Yes -- good point, it should be the __and__ operator.
do I need a new class? No, but based on this use case and other formatting
techniques adding a filter method to the list class that takes in either bit
mask or bool list would streamline a lot of code and not change any existing
func
I frequently use binary as bool placeholders and find myself filtering lists
based on those bools, this seems to have a similar semantic meaning as the bit
wise ^ or __xor__ operator and could add syntactic sugar to the base list class.
Use Case:
Controlling a stepper at half-step has the follo
