Message242653
The matrix multiplication operator @ is going to be introduced in Python 3.5 and I am thinking about the following idea:
The semantics of matrix multiplication is the composition of the corresponding linear transformations.
A linear transformation is a particular example of a more general concept - functions.
The latter are frequently composed with ("wrap") each other. For example:
plot(real(sqrt(data)))
However, it is not very readable in case of many wrapping layers. Therefore, it could be useful to employ
the matrix multiplication operator @ for indication of function composition. This could be done by such (simplified) decorator:
class composable:
def __init__(self, func):
self.func = func
def __call__(self, arg):
return self.func(arg)
def __matmul__(self, other):
def composition(*args, **kwargs):
return self.func(other(*args, **kwargs))
return composable(composition)
I think using such decorator with functions that are going to be deeply wrapped
could improve readability.
You could compare (note that only the outermost function should be decorated):
plot(sorted(sqrt(real(data_array)))) vs. (plot @ sorted @ sqrt @ real) (data_array)
I think the latter is more readable, also compare
def sunique(lst):
return sorted(list(set(lst)))
vs.
sunique = sorted @ list @ set
Apart from readability, there are following pros of the proposed decorator:
1. Similar semantics as for matrix multiplication.
2. Same symbol for composition as for decorators.
3. The symbol @ resembles mathematical notation for function composition: ∘
I think it could be a good idea to add such a decorator to the stdlib functools module. |
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Date |
User |
Action |
Args |
2015-05-06 10:24:42 | levkivskyi | set | recipients:
+ levkivskyi |
2015-05-06 10:24:42 | levkivskyi | set | messageid: <1430907882.79.0.781559925773.issue24133@psf.upfronthosting.co.za> |
2015-05-06 10:24:42 | levkivskyi | link | issue24133 messages |
2015-05-06 10:24:41 | levkivskyi | create | |
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