10000 BUG: core: fix NPY_TITLE_KEY macro on pypy by pv · Pull Request #10860 · numpy/numpy · GitHub
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BUG: core: fix NPY_TITLE_KEY macro on pypy #10860

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Merged
merged 1 commit into from
Apr 9, 2018
Merged

BUG: core: fix NPY_TITLE_KEY macro on pypy #10860

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31 changes: 29 additions & 2 deletions numpy/core/include/numpy/ndarrayobject.h
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Original file line number Diff line number Diff line change
Expand Up @@ -232,9 +232,36 @@ PyArray_DiscardWritebackIfCopy(PyArrayObject *arr)
dict.
*/

#define NPY_TITLE_KEY(key, value) ((PyTuple_GET_SIZE((value))==3) && \
(PyTuple_GET_ITEM((value), 2) == (key)))
static NPY_INLINE int
NPY_TITLE_KEY_check(PyObject *key, PyObject *value)
{
PyObject *title;
if (PyTuple_GET_SIZE(value) != 3) {
return 0;
}
title = PyTuple_GET_ITEM(value, 2);
if (key == title) {
return 1;
}
#ifdef PYPY_VERSION
/*
* On PyPy, dictionary keys do not always preserve object identity.
* Fall back to comparison by value.
*/
if (PyUnicode_Check(title) && PyUnicode_Check(key)) {
return PyUnicode_Compare(title, key) == 0 ? 1 : 0;
}
#if PY_VERSION_HEX < 0x03000000
if (PyString_Check(title) && PyString_Check(key)) {
return PyObject_Compare(title, key) == 0 ? 1 : 0;
}
#endif
#endif
return 0;
}

/* Macro, for backward compat with "if NPY_TITLE_KEY(key, value) { ..." */
#define NPY_TITLE_KEY(key, value) (NPY_TITLE_KEY_check((key), (value)))

#define DEPRECATE(msg) PyErr_WarnEx(PyExc_DeprecationWarning,msg,1)
#define DEPRECATE_FUTUREWARNING(msg) PyErr_WarnEx(PyExc_FutureWarning,msg,1)
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10 changes: 10 additions & 0 deletions numpy/core/tests/test_regression.py
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Expand Up @@ -2332,3 +2332,13 @@ def test_void_item_memview(self):
#va[0] = b'\xff\xff\xff\xff'
#del va
#assert_equal(x, b'\x00\x00\x00\x00')

def test_structarray_title(self):
# The following used to segfault on pypy, due to NPY_TITLE_KEY
# not working properly and resulting to double-decref of the
# structured array field items:
# See: https://bitbucket.org/pypy/pypy/issues/2789
for j in range(5):
structure = np.array([1], dtype=[(('x', 'X'), np.object_)])
structure[0]['x'] = np.array([2])
gc.collect()
0