fix #10447 - consider marks in reverse mro order to give base classes priority

Author: RonnyPfannschmidt

changelog/10447.bugfix.rst

@@ -0,0 +1,2 @@
+markers are now considered in the reverse mro order to ensure base  class markers are considered first
+this resolves a regression.

src/_pytest/mark/structures.py

@@ -374,7 +374,9 @@ def get_unpacked_marks(
         if not consider_mro:
             mark_lists = [obj.__dict__.get("pytestmark", [])]
         else:
-            mark_lists = [x.__dict__.get("pytestmark", []) for x in obj.__mro__]
+            mark_lists = [
+                x.__dict__.get("pytestmark", []) for x in reversed(obj.__mro__)
+            ]
         mark_list = []
         for item in mark_lists:
             if isinstance(item, list):

testing/test_mark.py

@@ -1130,6 +1130,41 @@ class C(A, B):
 
     all_marks = get_unpacked_marks(C)
 
-    assert all_marks == [xfail("c").mark, xfail("a").mark, xfail("b").mark]
+    assert all_marks == [xfail("b").mark, xfail("a").mark, xfail("c").mark]
 
     assert get_unpacked_marks(C, consider_mro=False) == [xfail("c").mark]
+
+
+@pytest.mark.issue("https://github.com/pytest-dev/pytest/issues/10447")
+def test_mark_fixture_order_mro(pytester: Pytester):
+    """This ensures we walk marks of the mro starting with the base classes
+    the action at a distance fixtures are taken as minimal example from a real project
+
+    """
+    foo = pytester.makepyfile(
+        """
+        import pytest
+
+        @pytest.fixture
+        def add_attr1(request):
+            request.instance.attr1 = object()
+
+
+        @pytest.fixture
+        def add_attr2(request):
+            request.instance.attr2 = request.instance.attr1
+
+
+        @pytest.mark.usefixtures('add_attr1')
+        class Parent:
+            pass
+
+
+        @pytest.mark.usefixtures('add_attr2')
+        class TestThings(Parent):
+            def test_attrs(self):
+                assert self.attr1 == self.attr2
+        """
+    )
+    result = pytester.run(foo)
+    result.assert_outcomes(passed=1)