question about xrange performance

[MRAB]

_wolf wrote:
> lately i realized a slow running portion of my application, and a
> quick profiling nourished the suspicion that, of all things, calls to
> `xrange().__contains__` (`x in b` where `b = xrange(L,H)`) is the
> culprit. to avoid any other influences, i wrote this test script with
> class `xxrange` being a poor man’s `xrange` replacement:
> 
> 
> ########################################################
> class xxrange( object ):
>   def __init__( self, start, stop ):
>     self.start  = start
>     self.stop   = stop
>   def __contains__( self, x ):
>     return ( x == int( x ) ) and self.start <= x < self.stop
> 
> import cProfile
> from random import randint
> test_integers = [ randint 0, 5000 ) for i in xrange( 8000 ) ]
> test_range_a  = xxrange( 10000, 20000 )
> test_range_b  = xrange(  10000, 20000 )
> 
> def a():
>   print test_range_a.__class__.__name__
>   for x in test_integers:
>     x in test_range_a
> 
> def b():
>   print test_range_b.__class__.__name__
>   for x in test_integers:
>     x in test_range_b
> 
> cProfile.run('a()')
> cProfile.run('b()')
> ########################################################
> 
> now this is the output, surprise:
> 
> ########################################################
> xxrange
>          8003 function calls in 0.026 CPU seconds
> 
>    Ordered by: standard name
> 
>    ncalls  tottime  percall  cumtime  percall filename:lineno
> (function)
>         1    0.000    0.000    0.026    0.026 <string>:1(<module>)
>         1    0.012    0.012    0.026    0.026 xrange-profiler.py:18(a)
>      8000    0.014    0.000    0.014    0.000 xrange-profiler.py:9
> (__contains__)
>         1    0.000    0.000    0.000    0.000 {method 'disable' of
> '_lsprof.Profiler' objects}
> 
> 
> xrange
>          3 function calls in 4.675 CPU seconds
> 
>    Ordered by: standard name
> 
>    ncalls  tottime  percall  cumtime  percall filename:lineno
> (function)
>         1    0.000    0.000    4.675    4.675 <string>:1(<module>)
>         1    4.675    4.675    4.675    4.675 xrange-profiler.py:23(b)
>         1    0.000    0.000    0.000    0.000 {method 'disable' of
> '_lsprof.Profiler' objects}
> ########################################################
> 
> can it be that a simple diy-class outperforms a python built-in by a
> factor of 180? is there something i have done the wrong way?
> omissions, oversights? do other people get similar figures?
> 
xrange() returns an xrange object, which generates its values on demand.
It doesn't have a __contains__ method, so 'in' uses its iterator, making
the xrange object yield each value until either the desired value is
produced or there are no more values.