>> > Note that every time you see [x for x in ...] with no condition, you
>> can
>> > write list(...) instead - more clear, and faster.
>> >
>> > data = list(csv.reader(open('some.csv', 'rb')))
>>
>> Faster? No. List Comprehensions are faster.
>
> [EMAIL PROTECTED] pdfps $ python -m timeit -c 'data = list(open("make.ps"))'
> 100 loops, best of 3: 7.5 msec per loop
> [EMAIL PROTECTED] pdfps $ python -m timeit -c 'data = [line for line in
> open("make.ps")]'
> 100 loops, best of 3: 9.2 msec per loop
>
> On my system just putting into a list is faster. I think this is
> because you don't need to assign each line to the variable 'line' each
> time in the former case.
>
> I, too, think it's faster to just use list() instead of 'line for line
> in iterable', as it seems kind of redundant.
>
$ python -m timeit -c 'import csv; data = list(csv.reader(open("some.csv",
"rb")))'
10000 loops, best of 3: 44 usec per loop
$ python -m timeit -c 'import csv; data = [row for row in
csv.reader(open("some.csv", "rb"))]'
10000 loops, best of 3: 37 usec per loop
I don't know why there seems to be a differece, but I know that list comps
are python are very heavily optimised.
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