larray-project
diff --git a/‎larray/core/array.py
Lines changed: 7 additions & 8 deletions b/‎larray/core/array.py
Lines changed: 7 additions & 8 deletions
diff --git a/‎larray/tests/test_array.py
Lines changed: 49 additions & 0 deletions b/‎larray/tests/test_array.py
Lines changed: 49 additions & 0 deletions
@@ -5791,15 +5791,10 @@ def opmethod(self, other) -> 'Array':
 
             # we could pass scalars through asarray too but it is too costly performance-wise for only suppressing one
             # isscalar test and an if statement.
-            # TODO: ndarray should probably be converted to larrays because that would harmonize broadcasting rules, but
-            # it makes some tests fail for some reason.
+            # TODO: ndarray should probably be converted to larrays too because that would harmonize broadcasting rules,
+            #       but it makes some tests fail for some reason.
             if isinstance(other, (list, Axis)):
                 other = asarray(other)
-            elif other is not None and not isinstance(other, (Array, np.ndarray)) and not np.isscalar(other):
-                # support for inspect.signature
-                # FIXME: this should only be the case for __eq__. For other operations, we should
-                #        probably raise a TypeError (or return NotImplemented???)
-                return False
 
             if isinstance(other, Array):
                 # TODO: first test if it is not already broadcastable
@@ -5809,9 +5804,13 @@ def opmethod(self, other) -> 'Array':
                     res_axes = self.axes
                 else:
                     (self_data, other_data), res_axes = raw_broadcastable((self, other))
-            else:
+            # We need to check for None explicitly because we consider None as a valid scalar, while numpy does not.
+            # i.e. we consider "arr == None" as valid code
+            elif isinstance(other, np.ndarray) or np.isscalar(other) or other is None:
                 self_data, other_data = self.data, other
                 res_axes = self.axes
+            else:
+                return NotImplemented
             return Array(super_method(self_data, other_data), res_axes)
         opmethod.__name__ = fullname
         return opmethod
 
@@ -2790,6 +2790,18 @@ def test_binary_ops(small_array):
     res = arr + arr.a
     assert_larray_equal(res, arr + asarray(arr.a))
 
+    # Array + <unsupported type>
+    with must_raise(TypeError, "unsupported operand type(s) for +: 'Array' and 'object'"):
+        res = arr + object()
+
+    # Array + <unsupported type which implements the reverse op>
+    class Test:
+        def __radd__(self, other):
+            return "success"
+
+    res = arr + Test()
+    assert res == 'success'
+
 
 def test_binary_ops_no_name_axes(small_array):
     raw = small_array.data
@@ -2881,6 +2893,43 @@ def test_binary_ops_with_scalar_group():
     assert_larray_equal(arr + time.i[0], expected)
 
 
+def test_comparison_ops():
+    # simple array equality (identity)
+    a = Axis('a=a0,a1,a2')
+    arr = ndtest(a)
+    res = arr == arr
+    expected = ones(a)
+    assert_larray_equal(res, expected)
+
+    # simple array equality
+    arr = ndtest(a)
+    res = arr == zeros(a)
+    expected = Array([True, False, False], a)
+    assert_larray_equal(res, expected)
+
+    # invalid types
+    # a) eq
+    arr = ndtest(3)
+    res = arr == object()
+    assert res is False
+
+    # b) ne
+    res = arr != object()
+    assert res is True
+
+    # c) others
+    with must_raise(TypeError, "'>' not supported between instances of 'Array' and 'object'"):
+        res = arr > object()
+
+    # d) other type implementing the reverse comparison
+    class Test:
+        def __lt__(self, other):
+            return "success"
+
+    res = arr > Test()
+    assert res == 'success'
+
+
 def test_unary_ops(small_array):
     raw = small_array.data