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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