BUG: PyDataType_ISUNSIZED should be False for structured types

4 files changed, 25 insertions, 4 deletions

diff --git a/numpy/core/src/multiarray/arrayobject.c b/numpy/core/src/multiarray/arrayobject.c
index eb939f47c..4676c40d5 100644
--- a/numpy/core/src/multiarray/arrayobject.c
+++ b/numpy/core/src/multiarray/arrayobject.c
@@ -1200,7 +1200,8 @@ _void_compare(PyArrayObject *self, PyArrayObject *other, int cmp_op)
             }
         }
         if (res == NULL && !PyErr_Occurred()) {
-            PyErr_SetString(PyExc_ValueError, "No fields found.");
+            /* these dtypes had no fields */
+            return cmp_op == Py_EQ ? Py_True : Py_False;
         }
         return res;
     }
diff --git a/numpy/core/src/multiarray/ctors.c b/numpy/core/src/multiarray/ctors.c
index f0a15505d..6b4b9aa1f 100644
--- a/numpy/core/src/multiarray/ctors.c
+++ b/numpy/core/src/multiarray/ctors.c
@@ -3843,7 +3843,13 @@ PyArray_FromBuffer(PyObject *buf, PyArray_Descr *type,
     s = (npy_intp)ts - offset;
     n = (npy_intp)count;
     itemsize = type->elsize;
-    if (n < 0 ) {
+    if (n < 0) {
+        if (itemsize == 0) {
+            PyErr_SetString(PyExc_ValueError,
+                            "cannot determine count if itemsize is 0");
+            Py_DECREF(type);
+            return NULL;
+        }
         if (s % itemsize != 0) {
             PyErr_SetString(PyExc_ValueError,
                             "buffer size must be a multiple"\
@@ -4036,7 +4042,7 @@ PyArray_FromIter(PyObject *obj, PyArray_Descr *dtype, npy_intp count)
     }
     for (i = 0; (i < count || count == -1) &&
              (value = PyIter_Next(iter)); i++) {
-        if (i >= elcount) {
+        if (i >= elcount && elsize != 0) {
             npy_intp nbytes;
             /*
               Grow PyArray_DATA(ret):
diff --git a/numpy/core/src/multiarray/methods.c b/numpy/core/src/multiarray/methods.c
index 79c60aa2e..8073071dd 100644
--- a/numpy/core/src/multiarray/methods.c
+++ b/numpy/core/src/multiarray/methods.c
@@ -1861,7 +1861,7 @@ array_reduce_ex(PyArrayObject *self, PyObject *args)
         PyDataType_FLAGCHK(descr, NPY_ITEM_HASOBJECT) ||
         (PyType_IsSubtype(((PyObject*)self)->ob_type, &PyArray_Type) &&
          ((PyObject*)self)->ob_type != &PyArray_Type) ||
-        PyDataType_ISUNSIZED(descr)) {
+        descr->elsize == 0) {
         /* The PickleBuffer class from version 5 of the pickle protocol
          * can only be used for arrays backed by a contiguous data buffer.
          * For all other cases we fallback to the generic array_reduce
diff --git a/numpy/core/tests/test_dtype.py b/numpy/core/tests/test_dtype.py
index caaeac92d..14c1857b4 100644
--- a/numpy/core/tests/test_dtype.py
+++ b/numpy/core/tests/test_dtype.py
@@ -424,6 +424,20 @@ class TestRecord(object):
                                'itemsize':8})
         assert_raises(ValueError, a.view, np.dtype([]))
 
+        d = np.dtype((np.dtype([]), 10))
+        assert_equal(d.shape, (10,))
+        assert_equal(d.itemsize, 0)
+        assert_equal(d.base, np.dtype([]))
+
+        arr = np.fromiter((() for i in range(10)), [])
+        assert_equal(arr.dtype, np.dtype([]))
+        assert_raises(ValueError, np.frombuffer, b'', dtype=[])
+        assert_equal(np.frombuffer(b'', dtype=[], count=2),
+                     np.empty(2, dtype=[]))
+
+        assert_raises(ValueError, np.dtype, ([], 'f8'))
+        assert_raises(ValueError, np.zeros(1, dtype='i4').view, [])
+
 
 class TestSubarray(object):
     def test_single_subarray(self):