> > Tenting the time spent by each approach (using time.clock()), with a > > file with about 100,000 entries, I get 0.03s for the loop and 0.05s > > for the listcomp. > > Anything else being equal, list comprehensions will be the faster > becuase they incur fewer name and attribute lookups. It will be the > same as the difference between a for loop and a call to map. A list > comprehension is basically an enhancement of map.
Not so. If you use the "dis" module to peek at the bytecode generated
for a list comprehension, you'll see it's very similar to that generated
for an explicit for-loop. The byte-code for a call to map is very
different.
Basically: both a for-loop and a list-comp do the looping in python
bytecode, while a call to map will do the actual looping in C.
>>> def comper():
... return [i*2 for i in xrange(10)]
...
>>>
>>> dis.dis(comper)
2 0 BUILD_LIST 0
3 DUP_TOP
4 STORE_FAST 0 (_[1])
7 LOAD_GLOBAL 0 (xrange)
10 LOAD_CONST 1 (10)
13 CALL_FUNCTION 1
16 GET_ITER
>> 17 FOR_ITER 17 (to 37)
20 STORE_FAST 1 (i)
23 LOAD_FAST 0 (_[1])
26 LOAD_FAST 1 (i)
29 LOAD_CONST 2 (2)
32 BINARY_MULTIPLY
33 LIST_APPEND
34 JUMP_ABSOLUTE 17
>> 37 DELETE_FAST 0 (_[1])
40 RETURN_VALUE
>>>
>>>
>>>
>>> def maper():
... return map(lambda i: i*2,xrange(10))
...
>>> dis.dis(maper)
2 0 LOAD_GLOBAL 0 (map)
3 LOAD_CONST 1 (<code object ...)
6 MAKE_FUNCTION 0
9 LOAD_GLOBAL 1 (xrange)
12 LOAD_CONST 2 (10)
15 CALL_FUNCTION 1
18 CALL_FUNCTION 2
21 RETURN_VALUE
>>>
Cheers,
Ryan
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Ryan Kelly
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