[Numpy-discussion] numpy CAPI questions
Lane Brooks
lbrooks at MIT.EDU
Mon Oct 20 17:13:51 EDT 2008
Travis E. Oliphant wrote:
> Lane Brooks wrote:
>
>> I am using the numpy CAPI to write an extension module that returns a
>> numpy Array from an imaging data source. I collect the image into a
>> buffer that I allocate. I then create numpy Array using the
>> PyArray_New(..) function and pass it the buffer. I then set the
>> NPY_OWNDATA flag on the Array because I want the Array to deallocate the
>> buffer when it is deleted. Is that the correct way to do it? The code
>> snippet below is what I wrote, and it seems to be working just fine, but
>> I wanted to verify that I am doing things correctly.
>>
>>
>>
> NPY_OWNDATA means the object will try to deallocate the memory (make
> sure it was allocated with the same allocator as NumPy uses).
> Otherwise, you will need to set up another approach as I showed in my
> blog posting several weeks ago.
>
> Also, don't use Py_BuildValue with "O" as it will create another
> reference so that img will have an extra reference to it when it is
> returned to Python. Use "N" instead.
>
> However, in this case you don't need to use Py_BuildValue at all because
> you are returning only one array.
>
> The PyArray_UpdateFlags call is not used for changing NPY_OWNDATA. It
> is only useful for changing FORTRAN, CONTIGUOUS, ALIGNED, and WRITEABLE
> flags which are convenience flags. This call does the check first and
> then sets the state of the flag to reflect the actual situation for the
> array.
>
> Instead use
>
> PyArray_FLAGS(arr) |= NPY_OWNDATA;
>
> -Travis
>
Thanks for all this valuable feedback. I read your blog post and like
the idea but not the overhead. I guess my initial approach of doing a
memory handoff to the numpy Array was a bit naive. It seems to be
working, but I guess that is because numpy uses free to deallocate memory?
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