list comprehension vs. lambda + filter

2018-12-31 08:49发布

I happened to find myself having a basic filtering need: I have a list and I have to filter it by an attribute of the items.

My code looked like this:

my_list = [x for x in my_list if x.attribute == value]

But then I thought, wouldn't it be better to write it like this?

my_list = filter(lambda x: x.attribute == value, my_list)

It's more readable, and if needed for performance the lambda could be taken out to gain something.

Question is: are there any caveats in using the second way? Any performance difference? Am I missing the Pythonic Way™ entirely and should do it in yet another way (such as using itemgetter instead of the lambda)?

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美炸的是我
2楼-- · 2018-12-31 09:50

An important difference is that list comprehension will return a list while the filter returns a filter, which you cannot manipulate like a list (ie: call len on it, which does not work with the return of filter).

My own self-learning brought me to some similar issue.

That being said, if there is a way to have the resulting list from a filter, a bit like you would do in .NET when you do lst.Where(i => i.something()).ToList(), I am curious to know it.

EDIT: This is the case for Python 3, not 2 (see discussion in comments).

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初与友歌
3楼-- · 2018-12-31 09:50

It took me some time to get familiarized with the higher order functions filter and map. So i got used to them and i actually liked filter as it was explicit that it filters by keeping whatever is truthy and I've felt cool that I knew some functional programming terms.

Then I read this passage (Fluent Python Book):

The map and filter functions are still builtins in Python 3, but since the introduction of list comprehensions and generator ex‐ pressions, they are not as important. A listcomp or a genexp does the job of map and filter combined, but is more readable.

And now I think, why bother with the concept of filter / map if you can achieve it with already widely spread idioms like list comprehensions. Furthermore maps and filters are kind of functions. In this case I prefer using Anonymous functions lambdas.

Finally, just for the sake of having it tested, I've timed both methods (map and listComp) and I didn't see any relevant speed difference that would justify making arguments about it.

from timeit import Timer

timeMap = Timer(lambda: list(map(lambda x: x*x, range(10**7))))
print(timeMap.timeit(number=100))

timeListComp = Timer(lambda:[(lambda x: x*x) for x in range(10**7)])
print(timeListComp.timeit(number=100))

#Map:                 166.95695265199174
#List Comprehension   177.97208347299602
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