Add failing is_scalar tests

Author: znicholls

pandas/tests/dtypes/test_inference.py

@@ -1493,34 +1493,52 @@ def test_is_scalar_builtin_nonscalars(self):
         assert not is_scalar(slice(None))
         assert not is_scalar(Ellipsis)
 
-    def test_is_scalar_numpy_array_scalars(self):
-        assert is_scalar(np.int64(1))
-        assert is_scalar(np.float64(1.0))
-        assert is_scalar(np.int32(1))
-        assert is_scalar(np.complex64(2))
-        assert is_scalar(np.object_("foobar"))
-        assert is_scalar(np.str_("foobar"))
-        assert is_scalar(np.unicode_("foobar"))
-        assert is_scalar(np.bytes_(b"foobar"))
-        assert is_scalar(np.datetime64("2014-01-01"))
-        assert is_scalar(np.timedelta64(1, "h"))
-
-    def test_is_scalar_numpy_zerodim_arrays(self):
-        for zerodim in [
-            np.array(1),
-            np.array("foobar"),
-            np.array(np.datetime64("2014-01-01")),
-            np.array(np.timedelta64(1, "h")),
-            np.array(np.datetime64("NaT")),
-        ]:
-            assert not is_scalar(zerodim)
-            assert is_scalar(lib.item_from_zerodim(zerodim))
-
+    @pytest.mark.parametrize("start", (
+        np.int64(1),
+        np.float64(1.0),
+        np.int32(1),
+        np.complex64(2),
+        np.object_("foobar"),
+        np.str_("foobar"),
+        np.unicode_("foobar"),
+        np.bytes_(b"foobar"),
+        np.datetime64("2014-01-01"),
+        np.timedelta64(1, "h"),
+    ))
+    @pytest.mark.parametrize("numpy_like", (True, False))
+    def test_is_scalar_numpy_array_scalars(self, start, numpy_like):
+        if numpy_like:
+            start = MockNumpyLikeArray(start)
+
+        assert is_scalar(start)
+
+    @pytest.mark.parametrize("zerodim", (
+        np.array(1),
+        np.array("foobar"),
+        np.array(np.datetime64("2014-01-01")),
+        np.array(np.timedelta64(1, "h")),
+        np.array(np.datetime64("NaT")),
+    ))
+    @pytest.mark.parametrize("numpy_like", (True, False))
+    def test_is_scalar_numpy_zerodim_arrays(self, zerodim, numpy_like):
+        if numpy_like:
+            zerodim = MockNumpyLikeArray(zerodim)
+
+        assert not is_scalar(zerodim)
+        assert is_scalar(lib.item_from_zerodim(zerodim))
+
+    @pytest.mark.parametrize("start", (
+        np.array([]),
+        np.array([[]]),
+        np.matrix("1; 2"),
+    ))
+    @pytest.mark.parametrize("numpy_like", (True, False))
     @pytest.mark.filterwarnings("ignore::PendingDeprecationWarning")
-    def test_is_scalar_numpy_arrays(self):
-        assert not is_scalar(np.array([]))
-        assert not is_scalar(np.array([[]]))
-        assert not is_scalar(np.matrix("1; 2"))
+    def test_is_scalar_numpy_arrays(self, start, numpy_like):
+        if numpy_like:
+            start = MockNumpyLikeArray(start)
+
+        assert not is_scalar(start)
 
     def test_is_scalar_pandas_scalars(self):
         assert is_scalar(Timestamp("2014-01-01"))