Generally, I prefer map() over list comprehensions since they are more
succinct and run faster for non-trivial examples. However, I've been
considering another use case related to functions in the operator
module. Here are some examples:
[x.method() for x in data]
[x[0] for x in data]
[x.attr for x in data]
can be implemented as:
from operator import methodcaller, itemgetter, attrgetter
m = methodcaller('method')
g = itemgetter(0)
a = attrgetter('attr')
map(m, data)
map(g, data)
map(a, data)
I find that using map here generally is a little slower than the list
comprehension, perhaps because of the extra work the operator methods
have to do:
>>> m = methodcaller('upper')
>>> g = itemgetter(0)
>>> a = attrgetter('__class__')
>>> s = "a"
>>> Timer('[x.upper() for x in s]', 'from __main__ import s').timeit()
1.8678569793701172
>>> Timer('map(m, s)', 'from __main__ import s, m').timeit()
2.1330718994140625
>>> Timer('[x[0] for x in s]', 'from __main__ import s').timeit()
1.6577358245849609
>>> Timer('map(g, s)', 'from __main__ import s, g').timeit()
1.8645310401916504
>>> Timer('[x.__class__ for x in s]', 'from __main__ import s').timeit()
1.7232599258422852
>>> Timer('map(a, s)', 'from __main__ import s, a').timeit()
2.4131419658660889
>>>
So, what's the feeling out there? Go with map and the operators or
stick with the list comps?
--
Gerald Britton
--
http://mail.python.org/mailman/listinfo/python-list
