
Wait, it was much simpler than that…
def until(items):
... stops = [] ... def stop(): ... stops.append(1) ... yield stop ... items = iter(items) ... counter = 0 ... while not stops: ... yield next(items) ... print(counter) ... counter += 1 ...
gen = until(range(15)) stop = next(gen) [x for x in gen if x < 3 or stop()]
0 1 2 3 [0, 1, 2]
I must have just been up for too long that this looks like something new to me.
Shane Green www.umbrellacode.com 408-692-4666 | shane@umbrellacode.com
On Jan 29, 2013, at 3:37 PM, Yuriy Taraday yorik.sar@gmail.com wrote:
On Tue, Jan 29, 2013 at 7:44 PM, Wolfgang Maier wolfgang.maier@biologie.uni-freiburg.de wrote: list(i for i in range(100) if i<50 or stop()) Really (!) nice (and 2x as fast as using itertools.takewhile())!
I couldn't believe it so I had to check it:
from __future__ import print_function import functools, itertools, operator, timeit
def var1(): def _gen(): for i in range(100): if i > 50: break yield i return list(_gen())
def var2(): def stop(): raise StopIteration return list(i for i in range(100) if i <= 50 or stop())
def var3(): return [i for i in itertools.takewhile(lambda n: n <= 50, range(100))]
def var4(): return [i for i in itertools.takewhile(functools.partial(operator.lt, 50), range(100))]
if __name__ == '__main__': for f in (var1, var2, var3, var4): print(f.__name__, end=' ') print(timeit.timeit(f))
Results on my machine:
var1 20.4974410534 var2 23.6218020916 var3 32.1543409824 var4 4.90913701057
var1 might have became the fastest of the first 3 because it's a special and very simple case. Why should explicit loops be slower that generator expressions? var3 is the slowest. I guess, because it has lambda in it. But switching to Python and back can not be faster than the last option - sitting in the C code as much as we can.
--
Kind regards, Yuriy. _______________________________________________ Python-ideas mailing list Python-ideas@python.org http://mail.python.org/mailman/listinfo/python-ideas