Sion Arrowsmith wrote:
>> (you cannot really use "profile" to *benchmark* things written in Python
>> either; the
>> profiler tells you where a given program spends the time, not how fast it is
>> in com-
>> parision with other programs)
>
> Hmm. Playing around with timeit suggests that although split() *is*
> faster than split("\t"), it's fractional, rather than the OP's four
> times faster. Is the overhead of profile keeping track of calls in
> Python getting in the way?
correct.
> And why can map() keep everything at the C level when the list com-
> prehension can't?
map is called with two Python objects (the str.split callable and the
sequence object), while the list comprehension is turned into a byte-
code loop that evaluates s.split for each item in the sequence; compare
and contrast:
>>> def func(a):
... return map(str.split, a)
...
>>> dis.dis(func)
2 0 LOAD_GLOBAL 0 (map)
3 LOAD_GLOBAL 1 (str)
6 LOAD_ATTR 2 (split)
9 LOAD_FAST 0 (a)
12 CALL_FUNCTION 2
15 RETURN_VALUE
>>> def func(a):
... return [s.split() for s in a]
...
>>> dis.dis(func)
2 0 BUILD_LIST 0
3 DUP_TOP
4 STORE_FAST 1 (_[1])
7 LOAD_FAST 0 (a)
10 GET_ITER
>> 11 FOR_ITER 19 (to 33)
14 STORE_FAST 2 (s)
17 LOAD_FAST 1 (_[1])
20 LOAD_FAST 2 (s)
23 LOAD_ATTR 0 (split)
26 CALL_FUNCTION 0
29 LIST_APPEND
30 JUMP_ABSOLUTE 11
>> 33 DELETE_FAST 1 (_[1])
36 RETURN_VALUE
(LOAD_GLOBAL and LOAD_ATTR does full name lookups, while LOAD_FAST loads
a local variable using an integer index)
</F>
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