In that case I would wrap it with a class to enjoy programming with the reference counted python garbage collector here. from cython.cimports.cpython.mem i

In that case I would wrap it with a class to enjoy programming with the reference counted python garbage collector here. from cython.cimports.cpython.mem import PyMem_Malloc, PyMem_Free @cython.cclass class SomeMemory: data: cython.p_double def __cinit__(self, number: cython.size_t): # allocate some memory (uninitialised, may contain arbitrary data) self.data = cython.cast(cython.p_double, PyMem_Malloc( number * cython.sizeof(cython.double))) if not self.data: raise MemoryError() def __dealloc__(self): PyMem_Free(self.data) # no-op if self.data is NULL Extending it into a typical python array type doesn't look that hard. Just need to map the appropriate dunder functions into C array operations. Then optimized functions can directly interact with the C types. Basically any utility function you might need with C data types you would just add to the class. And at that point, you're back to coding in regular python again. I hope this helps but good luck with your project no matter which option you take.