Feature or enhancement

Proposal:

With floating point data, the float('NaN') special value is commonly used as a placeholder for missing values. We provide math.isnan to support stripping out those values prior to sorting or summation:

>>> from math import isnan
>>> from itertools import filterfalse
>>> data = [3.3, float('nan'), 1.1, 2.2]
>>> sorted(filterfalse(isnan, data))
[1.1, 2.2, 3.3]

For non-float data, the None special value is commonly used as a placeholder for missing values. I propose a new function in the operator module analogous to math.isnan():

>>> data = ['c', None, 'a', 'b']
>>> sorted(filterfalse(is_none, data))
['a', 'b', 'c']

This helps fulfill a primary use case for the operator module which is to support functional programming with map(), filter(), etc.

Has this already been discussed elsewhere?

No response given

Links to previous discussion of this feature:

No response

Linked PRs

• gh-115808: Add is_none and is_not_none operators #115814