Fix code triggering superfluous-parens pylint messages (#49219)

* Fix code triggering superfluous-parens pylint messages

* Add previously removed asserts to tests

* Refactor CustomClass test to avoid using >=

Author: Leviob

pandas/core/computation/pytables.py

@@ -470,7 +470,7 @@ def visit_Attribute(self, node, **kwargs):
             # try to get the value to see if we are another expression
             try:
                 resolved = resolved.value
-            except (AttributeError):
+            except AttributeError:
                 pass
 
             try:

pandas/io/formats/style.py

@@ -1723,7 +1723,7 @@ def _apply(
                         f"Function {repr(func)} must return a DataFrame or ndarray "
                         f"when passed to `Styler.apply` with axis=None"
                     )
-                if not (data.shape == result.shape):
+                if data.shape != result.shape:
                     raise ValueError(
                         f"Function {repr(func)} returned ndarray with wrong shape.\n"
                         f"Result has shape: {result.shape}\n"
@@ -3310,9 +3310,9 @@ def bar(
                     "(eg: color=['#d65f5f', '#5fba7d'])"
                 )
 
-        if not (0 <= width <= 100):
+        if not 0 <= width <= 100:
             raise ValueError(f"`width` must be a value in [0, 100], got {width}")
-        elif not (0 <= height <= 100):
+        elif not 0 <= height <= 100:
             raise ValueError(f"`height` must be a value in [0, 100], got {height}")
 
         if subset is None:

pandas/io/pytables.py

@@ -4945,7 +4945,7 @@ def _unconvert_index(data, kind: str, encoding: str, errors: str) -> np.ndarray
     elif kind == "date":
         try:
             index = np.asarray([date.fromordinal(v) for v in data], dtype=object)
-        except (ValueError):
+        except ValueError:
             index = np.asarray([date.fromtimestamp(v) for v in data], dtype=object)
     elif kind in ("integer", "float", "bool"):
         index = np.asarray(data)

pandas/tests/groupby/test_allowlist.py

@@ -292,9 +292,9 @@ def test_all_methods_categorized(mframe):
     new_names -= transformation_kernels
     new_names -= groupby_other_methods
 
-    assert not (reduction_kernels & transformation_kernels)
-    assert not (reduction_kernels & groupby_other_methods)
-    assert not (transformation_kernels & groupby_other_methods)
+    assert not reduction_kernels & transformation_kernels
+    assert not reduction_kernels & groupby_other_methods
+    assert not transformation_kernels & groupby_other_methods
 
     # new public method?
     if new_names:
@@ -318,7 +318,7 @@ def test_all_methods_categorized(mframe):
     all_categorized = reduction_kernels | transformation_kernels | groupby_other_methods
     print(names)
     print(all_categorized)
-    if not (names == all_categorized):
+    if names != all_categorized:
         msg = f"""
 Some methods which are supposed to be on the Grouper class
 are missing:

pandas/tests/indexes/datetimelike.py

@@ -49,7 +49,7 @@ def test_str(self, simple_index):
         # test the string repr
         idx = simple_index
         idx.name = "foo"
-        assert not (f"length={len(idx)}" in str(idx))
+        assert f"length={len(idx)}" not in str(idx)
         assert "'foo'" in str(idx)
         assert type(idx).__name__ in str(idx)
 

pandas/tests/indexes/timedeltas/test_indexing.py

@@ -374,7 +374,7 @@ def test_contains(self):
         # GH#13603
         td = to_timedelta(range(5), unit="d") + offsets.Hour(1)
         for v in [NaT, None, float("nan"), np.nan]:
-            assert not (v in td)
+            assert v not in td
 
         td = to_timedelta([NaT])
         for v in [NaT, None, float("nan"), np.nan]:

pandas/tests/io/formats/style/test_style.py

@@ -352,7 +352,7 @@ def test_clear(mi_styler_comp):
 
     # test vars have same vales on obj and clean copy after clearing
     styler.clear()
-    for attr in [a for a in styler.__dict__ if not (callable(a))]:
+    for attr in [a for a in styler.__dict__ if not callable(a)]:
         res = getattr(styler, attr) == getattr(clean_copy, attr)
         assert all(res) if hasattr(res, "__iter__") else res
 

pandas/tests/io/formats/test_format.py

@@ -985,7 +985,7 @@ def test_to_string_truncate_indices(self, index, h, w):
                 if w == 20:
                     assert has_horizontally_truncated_repr(df)
                 else:
-                    assert not (has_horizontally_truncated_repr(df))
+                    assert not has_horizontally_truncated_repr(df)
             with option_context("display.max_rows", 15, "display.max_columns", 15):
                 if h == 20 and w == 20:
                     assert has_doubly_truncated_repr(df)

pandas/tests/io/generate_legacy_storage_files.py

@@ -326,7 +326,7 @@ def write_legacy_file():
     # force our cwd to be the first searched
     sys.path.insert(0, ".")
 
-    if not (3 <= len(sys.argv) <= 4):
+    if not 3 <= len(sys.argv) <= 4:
         exit(
             "Specify output directory and storage type: generate_legacy_"
             "storage_files.py <output_dir> <storage_type> "

pandas/tests/scalar/timedelta/test_arithmetic.py

@@ -1055,13 +1055,13 @@ def __gt__(self, other):
 
         t = Timedelta("1s")
 
-        assert not (t == "string")
-        assert not (t == 1)
-        assert not (t == CustomClass())
-        assert not (t == CustomClass(cmp_result=False))
+        assert t != "string"
+        assert t != 1
+        assert t != CustomClass()
+        assert t != CustomClass(cmp_result=False)
 
         assert t < CustomClass(cmp_result=True)
-        assert not (t < CustomClass(cmp_result=False))
+        assert not t < CustomClass(cmp_result=False)
 
         assert t == CustomClass(cmp_result=True)