[Numpy-discussion] State-of-the-art to use a C/C++ library from Python

[Carl Kleffner]

fork / extension of cffiwrap:


*"cfficloak - A simple but flexible module for creating object-oriented,
pythonic CFFI wrappers.This is an extension of
https://bitbucket.org/memotype/cffiwrap
<https://bitbucket.org/memotype/cffiwrap>"*

2016-09-02 13:46 GMT+02:00 Sebastian Haase <seb.haase at gmail.com>:

> How do these two relate to each other !?
> - Sebastian
>
>
> On Fri, Sep 2, 2016 at 12:33 PM, Carl Kleffner <cmkleffner at gmail.com>
> wrote:
>
>> maybe https://bitbucket.org/memotype/cffiwrap or
>> https://github.com/andrewleech/cfficloak helps?
>>
>> C.
>>
>>
>> 2016-09-02 11:16 GMT+02:00 Nathaniel Smith <njs at pobox.com>:
>>
>>> On Fri, Sep 2, 2016 at 1:16 AM, Peter Creasey
>>> <p.e.creasey.00 at googlemail.com> wrote:
>>> >> Date: Wed, 31 Aug 2016 13:28:21 +0200
>>> >> From: Michael Bieri <mibieri at gmail.com>
>>> >>
>>> >> I'm not quite sure which approach is state-of-the-art as of 2016. How
>>> would
>>> >> you do it if you had to make a C/C++ library available in Python
>>> right now?
>>> >>
>>> >> In my case, I have a C library with some scientific functions on
>>> matrices
>>> >> and vectors. You will typically call a few functions to configure the
>>> >> computation, then hand over some pointers to existing buffers
>>> containing
>>> >> vector data, then start the computation, and finally read back the
>>> data.
>>> >> The library also can use MPI to parallelize.
>>> >>
>>> >
>>> > Depending on how minimal and universal you want to keep things, I use
>>> > the ctypes approach quite often, i.e. treat your numpy inputs an
>>> > outputs as arrays of doubles etc using the ndpointer(...) syntax. I
>>> > find it works well if you have a small number of well-defined
>>> > functions (not too many options) which are numerically very heavy.
>>> > With this approach I usually wrap each method in python to check the
>>> > inputs for contiguity, pass in the sizes etc. and allocate the numpy
>>> > array for the result.
>>>
>>> FWIW, the broader Python community seems to have largely deprecated
>>> ctypes in favor of cffi. Unfortunately I don't know if anyone has
>>> written helpers like numpy.ctypeslib for cffi...
>>>
>>> -n
>>>
>>> --
>>> Nathaniel J. Smith -- https://vorpus.org
>>> _______________________________________________
>>> NumPy-Discussion mailing list
>>> NumPy-Discussion at scipy.org
>>> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>>>
>>
>>
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