[Numpy-discussion] Getting C-function pointers from Python to C

[Travis Oliphant]

On Apr 12, 2012, at 4:51 PM, Dag Sverre Seljebotn wrote:

> On 04/12/2012 11:13 PM, Travis Oliphant wrote:
>> Dag,
>> 
>> Thanks for the link to your CEP.  This is the first time I've seen it.   You probably referenced it before, but I hadn't seen it.
>> 
>> That CEP seems along the lines of what I was thinking of.    We can make scipy follow that CEP and NumPy as well in places that it needs function pointers.
>> 
>> I can certainly get behind it with Numba and recommend it to SciPy (and write the scipy.integrate.quad function to support it).
>> 
>> Thanks for the CEP.
> 
> Great. I'll pass this message on to the Cython list and see if anybody 
> wants to provide input (but given the scope, it should be minor tweaks 
> and easy to accommodate in whatever code you write).
> 
> You will fill in more of the holes as you implement this in Numba and 
> SciPy of course (my feeling is they will support it before Cython; let's 
> say I hope this happens within the next year).

Very nice.  This will help immensely I think.    It's actually just what I was looking for.     Just to be clear, by " pad to sizeof(void*) alignment", you mean that after the first 2 bytes there are (sizeof(void*) - 2)  bytes before the first function pointer in the memory block pointed to by the PyCObject / Capsule? 

Thanks,

-Travis


> 
> Dag
> 
> 
> 
> 
>> 
>> -Travis
>> 
>> 
>> 
>> 
>> 
>> On Apr 12, 2012, at 2:08 PM, Dag Sverre Seljebotn wrote:
>> 
>>> On 04/12/2012 07:24 PM, Nathaniel Smith wrote:
>>>> On Wed, Apr 11, 2012 at 10:23 PM, Travis Oliphant<teoliphant at gmail.com>   wrote:
>>>>>>> In the mean-time, I think we could do as Robert essentially suggested and just use Capsule Objects around an agreed-upon simple C-structure:
>>>>>>> 
>>>>>>>      int   id   /* Some number that can be used as a "type-check" */
>>>>>>>      void *func;
>>>>>>>      char *string;
>>>>>>> 
>>>>>>> We can then just create some nice functions to go to and from this form in NumPy ctypeslib and then use this while the Python PEP gets written and adopted.
>>>>>> 
>>>>>> What is not clear to me is how one get from the Python callable to the
>>>>>> capsule.
>>>>> 
>>>>> This varies substantially based on the tool.   Numba would do it's work and create the capsule object using it's approach.   Cython would use a different approach.
>>>>> 
>>>>> I would also propose to have in NumPy some basic functions that go back-and forth between this representation, ctypes, and any other useful representations that might emerge.
>>>>> 
>>>>>> 
>>>>>> Or do you simply intend to pass a non-callable capsule as an argument in
>>>>>> place of the callback?
>>>>> 
>>>>> I had simply intended to allow a non-callable capsule argument to be passed in instead of another call-back to any SciPy or NumPy function that can take a raw C-function pointer.
>>>> 
>>>> If the cython folks are worried about type-checking overhead, then
>>>> PyCapsule seems sub-optimal, because it's unnecessarily complicated to
>>>> determine what sort of PyCapsule you have, and then extract the actual
>>>> C struct. (At a minimum, it requires two calls to non-inlineable
>>>> functions, plus an unnecessary pointer indirection.)
>>> 
>>> I think this discussion is moot -- the way I reverse-engineer Travis is
>>> that there's no time for a cross-project discussion about this now.
>>> That's not too bad, Cython will go its own way (eventually), and perhaps
>>> we can merge in the future...
>>> 
>>> But for the entertainment value:
>>> 
>>> In my CEP [1] I descripe two access mechanisms, one slow (for which I
>>> think capsules is fine), and a faster one.
>>> 
>>> Obviously, only the slow mechanism will be implemented first.
>>> 
>>> So the only things I'd like changed in how Travis' want to do this is
>>> 
>>> a) Storing the signature string data in the struct, rather than as a char*;
>>> 
>>>     void *func
>>>     char string[1]; // variable-size-allocated and null-terminated
>>> 
>>> b) Allow for multiple signatures in the same capsule, i.e. "dd->d",
>>> "ff->f", in the same capsule.
>>> 
>>>> A tiny little custom class in a tiny little library that everyone can
>>>> share might be better? (Bonus: a custom class could define a __call__
>>>> method that used ctypes to call the function directly, for interactive
>>>> convenience/testing/etc.)
>>> 
>>> Having NumPy and Cython depend on a common library, and getting that to
>>> work for users, seems rather utopic to me. And if I propose that Cython
>>> have a hard dependency of NumPy for a feature as basic as calli.ng a
>>> callback object then certain people will be very angry.
>>> 
>>> Anyway, in my CEP I went to great pains to avoid having to do this, with
>>> a global registration mechanism for multiple such types.
>>> 
>>> Regarding your idea for the __call__, that's the exact opposite of what
>>> I'm doing in the CEP. I'm pretty sure that what I described is what we
>>> want for Cython; we will never tell our users to pass capsules around.
>>> What I want is this:
>>> 
>>> @numba
>>> def f(x): return 2 * x
>>> 
>>> @cython.inline
>>> def g(x): return 3 * x
>>> 
>>> print f(3)
>>> print g(3)
>>> print scipy.integrate.quad(f, 0.2, 3) # fast!
>>> print scipy.integrate.quad(g, 0.2, 3) # fast!
>>> 
>>> # If you really want a capsule:
>>> print f.__nativecall__
>>> 
>>> Dag
>>> 
>>> [1] http://wiki.cython.org/enhancements/cep1000
>>> _______________________________________________
>>> NumPy-Discussion mailing list
>>> NumPy-Discussion at scipy.org
>>> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>> 
>> _______________________________________________
>> NumPy-Discussion mailing list
>> NumPy-Discussion at scipy.org
>> http://mail.scipy.org/mailman/listinfo/numpy-discussion
> 
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at scipy.org
> http://mail.scipy.org/mailman/listinfo/numpy-discussion