[Numpy-discussion] calling NumPy from Julia - a plea for fewer macros

Charles R Harris charlesr.harris@gmail....
Sun Feb 17 14:00:00 CST 2013

On Sun, Feb 17, 2013 at 12:43 PM, Charles R Harris <
charlesr.harris@gmail.com> wrote:

> On Sun, Feb 17, 2013 at 9:12 AM, Steven G. Johnson <stevenj@alum.mit.edu>wrote:
>> Dear NumPy developers,
>> I've been working on a glue package that allows the Julia language
>> (http://julialang.org/) to call Python routines easily
>>         https://github.com/stevengj/PyCall.jl
>> and I'm using NumPy to pass multidimensional arrays between languages.
>> Julia has the ability to call C functions directly (without writing C
>> glue), and I've been exploiting this to write PyCall purely in Julia.
>> (This is nice for a number of reasons; besides programming and linking
>> convenience, it means that I can dynamically load different Python
>> versions on the same machine, and don't need to recompile if e.g. NumPy
>> is updated.) However, calling NumPy has been a challenge, because of
>> NumPy's heavy reliance on macros in its C API.
>> I wanted to make a couple of suggestions to keep in mind as you plan for
>> NumPy 2.0:
>> 1) Dynamically linking to NumPy's C API was challenging, to say the
>> least.  Assuming you stick with the PyArray_API lookup table of
>> pointers, it would be much easier to call from other languages if you
>> include e.g. a numpy.core.multiarray._ARRAY_API_NAMES variable in the
>> Python module that is a list of strings giving the symbol names
>> corresponding to the  numpy.core.multiarray._ARRAY_API pointer.  (Plus
>> documentation, of course.)   Currently I need to parse
>> __multiarray_api.h to extract this information, which is somewhat hackish.
> It shouldn't be too much work to provide something like that. The current
> API is generated, take a look at numpy/core/codegenerators/numpy_api.py.
> PR's welcome.
>> 2) Please provide non-macro equivalents (exported in the _ARRAY_API
>> symbol table or otherwise) of PyArray_NDIM etcetera to access
>> PyArrayObject members.  (e.g. call them PyArray_ndim etc.  Note that
>> inline functions are not enough, since they are not loadable
>> dynamically.)  Right now, the only ways[*] I can see to access this
>> information are either to use C glue (which I want to avoid for the
>> reasons above) or to call Python to access the __array_interface__
>> attribute (which is suboptimal from a performance standpoint).
> There are already functional versions of PyArray_NDIM and some others, put
> in as part of a long term project to hide the numpy internals so that we
> can modify structures and such at some point. We could use more work in
> that direction and would welcome any input/PR's you might offer. The current
> functions can be used instead of the macros by putting
> before any includes. The NPY_API_VERSION serves to mark which functions
> were introduced in which numpy version, so as to maintain backward
> compatibility with 3'rd party code. See the lines starting at 1377 in
> ndarraytypes.h. for currently available functions.
> There might also be some useful things in dynd/blaze which, IIRC, support
> numpy for some computations. They are located at
> https://github.com/ContinuumIO/
Oops, sorry, I didn't see your comments about inline functions. I don't see
why something like this couldn't be supported, perhaps as a library like we
have for math functions, umath.so.

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