Force NumPy ndarray to take ownership of its memory in Cython

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You just have some minor errors in the interface definition. The following worked for me:

from libc.stdlib cimport malloc
import numpy as np
cimport numpy as np

np.import_array()

ctypedef np.int32_t DTYPE_t

cdef extern from "numpy/arrayobject.h":
    void PyArray_ENABLEFLAGS(np.ndarray arr, int flags)

cdef data_to_numpy_array_with_spec(void * ptr, np.npy_intp N, int t):
    cdef np.ndarray[DTYPE_t, ndim=1] arr = np.PyArray_SimpleNewFromData(1, &N, t, ptr)
    PyArray_ENABLEFLAGS(arr, np.NPY_OWNDATA)
    return arr

def test():
    N = 1000

    cdef DTYPE_t *data = <DTYPE_t *>malloc(N * sizeof(DTYPE_t))
    arr = data_to_numpy_array_with_spec(data, N, np.NPY_INT32)
    return arr

This is my setup.py file:

from distutils.core import setup, Extension
from Cython.Distutils import build_ext
ext_modules = [Extension("_owndata", ["owndata.pyx"])]
setup(cmdclass={'build_ext': build_ext}, ext_modules=ext_modules)

Build with python setup.py build_ext --inplace. Then verify that the data is actually owned:

import _owndata
arr = _owndata.test()
print arr.flags

Among others, you should see OWNDATA : True.

And yes, this is definitely the right way to deal with this, since numpy.pxd does exactly the same thing to export all the other functions to Cython.

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