TST: Simplify and clarify test skipping (#56027)

* TST: Simplify and clarify test skipping

* Typo

* Update pandas/tests/arithmetic/test_datetime64.py

* Don't skip because of duplicates

Author: mroeschke

pandas/tests/arithmetic/test_datetime64.py

@@ -414,7 +414,7 @@ def test_dti_cmp_datetimelike(self, other, tz_naive_fixture):
         dti = date_range("2016-01-01", periods=2, tz=tz)
         if tz is not None:
             if isinstance(other, np.datetime64):
-                pytest.skip("no tzaware version available")
+                pytest.skip(f"{type(other).__name__} is not tz aware")
             other = localize_pydatetime(other, dti.tzinfo)
 
         result = dti == other

pandas/tests/arithmetic/test_numeric.py

@@ -384,7 +384,7 @@ def test_divmod_zero(self, zero, numeric_idx):
     def test_div_negative_zero(self, zero, numeric_idx, op):
         # Check that -1 / -0.0 returns np.inf, not -np.inf
         if numeric_idx.dtype == np.uint64:
-            pytest.skip(f"Not relevant for {numeric_idx.dtype}")
+            pytest.skip(f"Div by negative 0 not relevant for {numeric_idx.dtype}")
         idx = numeric_idx - 3
 
         expected = Index([-np.inf, -np.inf, -np.inf, np.nan, np.inf], dtype=np.float64)

pandas/tests/computation/test_eval.py

@@ -63,7 +63,7 @@
                     reason=f"numexpr enabled->{USE_NUMEXPR}, "
                     f"installed->{NUMEXPR_INSTALLED}",
                 ),
-                td.skip_if_no_ne,
+                td.skip_if_no("numexpr"),
             ],
         )
         for engine in ENGINES
@@ -1687,14 +1687,14 @@ def test_empty_globals(self, engine, parser):
             pd.eval(e, engine=engine, parser=parser, global_dict={})
 
 
-@td.skip_if_no_ne
+@td.skip_if_no("numexpr")
 def test_invalid_engine():
     msg = "Invalid engine 'asdf' passed"
     with pytest.raises(KeyError, match=msg):
         pd.eval("x + y", local_dict={"x": 1, "y": 2}, engine="asdf")
 
 
-@td.skip_if_no_ne
+@td.skip_if_no("numexpr")
 @pytest.mark.parametrize(
     ("use_numexpr", "expected"),
     (
@@ -1711,7 +1711,7 @@ def test_numexpr_option_respected(use_numexpr, expected):
         assert result == expected
 
 
-@td.skip_if_no_ne
+@td.skip_if_no("numexpr")
 def test_numexpr_option_incompatible_op():
     # GH 32556
     with pd.option_context("compute.use_numexpr", False):
@@ -1723,7 +1723,7 @@ def test_numexpr_option_incompatible_op():
         tm.assert_frame_equal(result, expected)
 
 
-@td.skip_if_no_ne
+@td.skip_if_no("numexpr")
 def test_invalid_parser():
     msg = "Invalid parser 'asdf' passed"
     with pytest.raises(KeyError, match=msg):

pandas/tests/dtypes/test_common.py

@@ -196,7 +196,7 @@ def test_is_object():
 
 
 @pytest.mark.parametrize(
-    "check_scipy", [False, pytest.param(True, marks=td.skip_if_no_scipy)]
+    "check_scipy", [False, pytest.param(True, marks=td.skip_if_no("scipy"))]
 )
 def test_is_sparse(check_scipy):
     msg = "is_sparse is deprecated"
@@ -632,7 +632,7 @@ def test_is_bool_dtype_numpy_error():
 
 
 @pytest.mark.parametrize(
-    "check_scipy", [False, pytest.param(True, marks=td.skip_if_no_scipy)]
+    "check_scipy", [False, pytest.param(True, marks=td.skip_if_no("scipy"))]
 )
 def test_is_extension_array_dtype(check_scipy):
     assert not com.is_extension_array_dtype([1, 2, 3])

pandas/tests/extension/base/dim2.py

@@ -29,7 +29,7 @@ def skip_if_doesnt_support_2d(self, dtype, request):
             test_func = node._obj
             if test_func.__qualname__.startswith("Dim2CompatTests"):
                 # TODO: is there a less hacky way of checking this?
-                pytest.skip("Test is only for EAs that support 2D.")
+                pytest.skip(f"{dtype} does not support 2D.")
 
     def test_transpose(self, data):
         arr2d = data.repeat(2).reshape(-1, 2)

pandas/tests/extension/base/interface.py

@@ -103,7 +103,7 @@ def test_copy(self, data):
         result = data.copy()
 
         if data.dtype._is_immutable:
-            pytest.skip("test_copy assumes mutability")
+            pytest.skip(f"test_copy assumes mutability and {data.dtype} is immutable")
 
         data[1] = data[0]
         assert result[1] != result[0]
@@ -118,7 +118,7 @@ def test_view(self, data):
         assert type(result) == type(data)
 
         if data.dtype._is_immutable:
-            pytest.skip("test_view assumes mutability")
+            pytest.skip(f"test_view assumes mutability and {data.dtype} is immutable")
 
         result[1] = result[0]
         assert data[1] == data[0]

pandas/tests/extension/base/reduce.py

@@ -120,7 +120,7 @@ def test_reduce_frame(self, data, all_numeric_reductions, skipna):
         op_name = all_numeric_reductions
         ser = pd.Series(data)
         if not is_numeric_dtype(ser.dtype):
-            pytest.skip("not numeric dtype")
+            pytest.skip(f"{ser.dtype} is not numeric dtype")
 
         if op_name in ["count", "kurt", "sem"]:
             pytest.skip(f"{op_name} not an array method")

pandas/tests/extension/base/reshaping.py

@@ -343,7 +343,7 @@ def test_ravel(self, data):
         assert type(result) == type(data)
 
         if data.dtype._is_immutable:
-            pytest.skip("test_ravel assumes mutability")
+            pytest.skip(f"test_ravel assumes mutability and {data.dtype} is immutable")
 
         # Check that we have a view, not a copy
         result[0] = result[1]
@@ -360,7 +360,9 @@ def test_transpose(self, data):
         assert result.shape == data.shape[::-1]
 
         if data.dtype._is_immutable:
-            pytest.skip("test_transpose assumes mutability")
+            pytest.skip(
+                f"test_transpose assumes mutability and {data.dtype} is immutable"
+            )
 
         # Check that we have a view, not a copy
         result[0] = result[1]

pandas/tests/extension/base/setitem.py

@@ -43,7 +43,7 @@ def skip_if_immutable(self, dtype, request):
                 # This fixture is auto-used, but we want to not-skip
                 # test_is_immutable.
                 return
-            pytest.skip("__setitem__ test not applicable with immutable dtype")
+            pytest.skip(f"__setitem__ test not applicable with immutable dtype {dtype}")
 
     def test_is_immutable(self, data):
         if data.dtype._is_immutable:

pandas/tests/extension/conftest.py

@@ -37,7 +37,7 @@ def data_for_twos(dtype):
     if not (dtype._is_numeric or dtype.kind == "m"):
         # Object-dtypes may want to allow this, but for the most part
         #  only numeric and timedelta-like dtypes will need to implement this.
-        pytest.skip("Not a numeric dtype")
+        pytest.skip(f"{dtype} is not a numeric dtype")
 
     raise NotImplementedError