On May 13, 2009, at 1:17 AM, Sebastien Binet wrote:
> hi,
>
> On Wednesday 13 May 2009 08:35:27 Robert Bradshaw wrote:
>> On May 12, 2009, at 9:47 PM, Mohamed Lrhazi wrote:
>>> On Wed, May 13, 2009 at 12:31 AM, Chris Colbert
>>>
>>> <[email protected]> wrote:
>>>> If your making lots of rapid calls to short running functions in
>>>> the
>>>> C-library, then you may start to feel the ctypes overhead.
>>>
>>> That's what I was afraid to hear..
>>
>> Hopefully after using Cython a bit, you're fears will quickly go
>> away :).
>>
>>> What I was hoping to hear is "Oh
>>> no, ctypes is all C anyways, and will perform just the same as
>>> Cython"
>>
>> A simple benchmark:
>>
>> import ctypes
>> libm = ctypes.cdll.LoadLibrary("libm.dylib") # platform dependent...
>> def ctypes_sum(N):
>> lib_sqrt = libm.sqrt
>> lib_sqrt.argtypes = (ctypes.c_double,)
>> lib_sqrt.restype = ctypes.c_double
>> s = 0
>> for i in range(N):
>> s += lib_sqrt(i)
>> return s
>>
>> %cython
>> cdef extern from "math.h":
>> double sqrt(double)
>>
>> def cython_sum(long N):
>> cdef int i
>> cdef double s=0
>> for i in range(N):
>> s += sqrt(i)
>> return s
>>
>>>>> time ctypes_sum(10**6)
>>
>> 666666166.4588418
>> Time: CPU 1.13 s, Wall: 1.14 s
>>
>> time cython_sum(10**6)
>> 666666166.4588418
>> Time: CPU 0.03 s, Wall: 0.03 s
>
> interesting simple minded benchmark :)
>
> how would this translate into the pure-python mode ?
Pure Python:
def python_sum(N):
from math import sqrt
s = 0
for i in range(N):
s += sqrt(i)
return s
>>> time python_sum(10**6)
666666166.4588418
Time: CPU 0.47 s, Wall: 0.47 s
So for such a tiny call, ctypes is slower. (Since math.sqrt is a
static wrapper around libm's sqrt, no surprise here.)
> (I couldn't seem to be
> able to declare the C-sqrt function using the pure-python mode of
> cython:
> http://wiki.cython.org/pure wasn't helpful)
The pure-python mode should be exactly the same as the above, but
there's no way to declare functions in it (yet).
- Robert
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