Pre-pep discussion material: in-place equivalents to map and filter

[Arthur Havlicek]

> If slice assignment is done as I hope it will optimize remain memory
operations.

Bad news.

http://stackoverflow.com/questions/4948293/python-slice-assignment-memory-usage/4948508#4948508

> If you want something like C++ move semantics, use C++.

I don't see anything like this in my proposal. If any in-place operation is
"C++ semantics" how do you explain there is already a bunch of in-place
operator stuffed in Python that have even less justification to their
existance than map or filter does such as sort/sorted, reverse/reversed ?
Especially troubling since the optimisation in a sort operation is likely
to be less significant than in a linear algorithm.

2016-11-04 1:03 GMT+01:00 Terry Reedy <tjreedy at udel.edu>:

> On 11/3/2016 2:56 AM, arthurhavlicek at gmail.com wrote:
>
> lst = [ item for item in lst if predicate(item) ]
>> lst = [ f(item) for item in lst ]
>>
>> Both these expressions feature redundancy, lst occurs twice and item at
>> least twice. Additionally, the readability is hurt, because one has to dive
>> through the semantics of the comprehension to truely understand I am
>> filtering the list or remapping its values.
>>
> ...
>
>> A language support for these operations to be made in-place could improve
>> the efficiency of this operations through reduced use of memory.
>>
>
> We already have that: slice assignment with an iterator.
>
> lst[:] = (item for item in list if predicate(item))
> lst[:] = map(f, lst)  # iterator in 3.x.
>
> To save memory, stop using unneeded temporary lists and use iterators
> instead.  If slice assignment is done as I hope it will optimize remain
> memory operations.  (But I have not read the code.) It should overwrite
> existing slots until either a) the iterator is exhausted or b) existing
> memory is used up.  When lst is both source and destination, only case a)
> can happen.  When it does, the list can be finalized with its new contents.
>
> As for timings.
>
> from timeit import Timer
> setup = """data = list(range(10000))
> def func(x):
>     return x
> """
> t1a = Timer('data[:] = [func(a) for a in data]', setup=setup)
> t1b = Timer('data[:] = (func(a) for a in data)', setup=setup)
> t2a = Timer('data[:] = list(map(func, data))', setup=setup)
> t2b = Timer('data[:] = map(func, data)', setup=setup)
>
> print('t1a', min(t1a.repeat(number=500, repeat=7)))
> print('t1b', min(t1b.repeat(number=500, repeat=7)))
> print('t2a', min(t2a.repeat(number=500, repeat=7)))
> print('t2b', min(t2b.repeat(number=500, repeat=7)))
> #
> t1a 0.5675313005414555
> t1b 0.7034254675598604
> t2a 0.5181285985208888
> t2b 0.5196112759726024
>
> If f does more work, the % difference among these will decrease.
>
>
>
> --
> Terry Jan Reedy
>
> --
> https://mail.python.org/mailman/listinfo/python-list
>