> 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 <tjre...@udel.edu>: > On 11/3/2016 2:56 AM, arthurhavli...@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 > -- https://mail.python.org/mailman/listinfo/python-list
