John Machin wrote:
[...]
> Observation: factoring out the compile step makes the difference much
> more apparent.
>
> >>> ["%.3f" % t.timeit() for t in t3, t4, t5, t6]
> ['1.578', '1.175', '2.283', '1.174']
> >>> ["%.3f" % t.timeit() for t in t3, t4, t5, t6]
> ['1.582', '1.179', '2.284', '1.172']
> >>>
To make it even more apparent, try:
import re
import profile
startsz = re.compile('^z')
for s in ('x' * 1000, 'x' * 100000, 'x'*10000000):
profile.run('startsz.search(s)')
Profile report is below.
> Conclusion: search time depends on length of searched string.
>
> Meta-conclusion: Either I have to retract my
> based-on-hope-rather-than-on-experimentation assertion, or redefine "not
> dopey" to mean "surely nobody would search for ^x when match x would do,
> so it would be dopey to optimise re for that" :-)
No question, there's some dopiness to searching for the
beginning of the string at places other than beginning of the
string.
The tricky part would be optimizing '$'.
--
--Bryan
4 function calls in 0.003 CPU seconds
Ordered by: standard name
ncalls tottime percall cumtime percall filename:lineno(function)
1 0.000 0.000 0.000 0.000 :0(search)
1 0.003 0.003 0.003 0.003 :0(setprofile)
1 0.000 0.000 0.000 0.000 <string>:1(?)
0 0.000 0.000 profile:0(profiler)
1 0.000 0.000 0.003 0.003 profile:0(startsz.search(s))
4 function calls in 0.002 CPU seconds
Ordered by: standard name
ncalls tottime percall cumtime percall filename:lineno(function)
1 0.002 0.002 0.002 0.002 :0(search)
1 0.000 0.000 0.000 0.000 :0(setprofile)
1 0.000 0.000 0.002 0.002 <string>:1(?)
0 0.000 0.000 profile:0(profiler)
1 0.000 0.000 0.002 0.002 profile:0(startsz.search(s))
4 function calls in 0.228 CPU seconds
Ordered by: standard name
ncalls tottime percall cumtime percall filename:lineno(function)
1 0.228 0.228 0.228 0.228 :0(search)
1 0.000 0.000 0.000 0.000 :0(setprofile)
1 0.000 0.000 0.228 0.228 <string>:1(?)
0 0.000 0.000 profile:0(profiler)
1 0.000 0.000 0.228 0.228 profile:0(startsz.search(s))
--
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