This statement is running quite slowly, and I have run out of ideas to optimize it. Could someone help me out?
[dict(zip(small_list1, small_list2)) for small_list2 in really_huge_list_of_list]
The small_list
s contain only about 6 elements.
A really_huge_list_of_list
of size 209,510 took approximately 16.5 seconds to finish executing.
Thank you!
Edit:
really_huge_list_of_list
is a generator. Apologies for any confusion. The size is obtained from the result list.
Possible minor improvement:
[dict(itertools.izip(small_list1, small_list2)) for small_list2 in really_huge_list_of_list]
Also, you may consider to use generator instead of list comprehensions.
To expand on what the comments are trying to say, you should use a generator instead of that list comprehension. Your code currently looks like this:
[dict(zip(small_list1, small_list2)) for small_list2 in really_huge_list_of_list]
and you should change it to this instead:
def my_generator(input_list_of_lists):
small_list1 = ["wherever", "small_list1", "comes", "from"]
for small_list2 in input_list_of_lists:
yield dict(zip(small_list1, small_list2))
What you're doing right now is taking ALL the results of iterating over your really huge list, and building up a huge list of the results, before doing whatever you do with that list of results. Instead, you should turn that list comprehension into a generator so that you never have to build up a list of 200,000 results. It's building that result list that's taking up so much memory and time.
... Or better yet, just turn that list comprehension into a generator comprehension by changing its outer brackets into parentheses:
(dict(zip(small_list1, small_list2)) for small_list2 in really_huge_list_of_list)
That's really all you need to do. The syntax for list comprehensions and generator comprehensions is almost identical, on purpose: if you understand a list comprehension, you'll understand the corresponding generator comprehension. (In this case, I wrote out the generator in "long form" first so that you'd see what that comprehension expands to).
For more on generator comprehensions, see here , here and/or here .
Hope this helps you add another useful tool to your Python toolbox!
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