Hi, I'm new to cython's typed memory view, and found some cases where the function that uses typed memory view has memory leaking. The leak happens when I pass a numpy array of objects, where each object itself is a numpy array.( You can get this 'weird' object from construction a pandas Series with a list of numpy arrays). Please see the following code snippet or use the attached code to reproduce the case. I appreciate any help and suggestions in advance! (I also posted on the cython-users google group. Apologize for the redundancy.) # BEGIN CONTENT OF test.pyx # this does not leak cpdef int do_nothing(arr): return 0 # this does leak cpdef int do_nothing_typed(double[:] arr): return 0 # this does leak cpdef int do_nothing_but_copy(arr): cdef double[:] _arr = arr return 0 # END CONTENT OF test.pyx # BEGIN CONTENT OF runtest.py # ... omit all the imports here def gc_obj_hist(): """ Returns a sorted map from type to the counts of in memory objects with the type """ hst = defaultdict(lambda: 0) for v in gc.get_objects(): hst[type(v)] += 1 l = sorted(hst.iteritems(), key=operator.itemgetter(1), reverse=True) return l # NOT LEAK def test1(n=10000): s = pd.Series([np.random.randn(10) for i in range(n)]) for i in range(n): do_nothing(s[i]) print "Top 5 object types after test 1: " + str(gc_obj_hist()[:5]) # LEAK def test2(n=10000): s = pd.Series([np.random.randn(10) for i in range(n)]) for i in range(n): do_nothing_typed(s[i]) print "Top 5 object types after test 2: " + str(gc_obj_hist()[:5]) # LEAK def test3(n=10000): s = pd.Series([np.random.randn(10) for i in range(n)]) for i in range(n): do_nothing_but_copy(s[i]) print "Top 5 object types after test 3: " + str(gc_obj_hist()[:5]) # NOT LEAK def test4(n=10000): s = pd.Series([np.random.randn(10) for i in range(n)]) for i in range(n): do_nothing_but_copy(np.array(s[i])) print "Top 5 object types after test 4: " + str(gc_obj_hist()[:5]) if __name__ == "__main__": n = 100000 test1(n) test2(n) test3(n) test4(n) # END CONTENT OF runtest.py Thanks, -jay