fix: return None for tests

Author: cmp0xff

tests/indexes/test_indexes.py

@@ -223,7 +223,7 @@ def test_index_rename_inplace() -> None:
     assert ind2 is None
 
 
-def test_index_dropna():
+def test_index_dropna() -> None:
     idx = pd.Index([1, 2])
 
     check(assert_type(idx.dropna(how="all"), "pd.Index[int]"), pd.Index)
@@ -235,7 +235,7 @@ def test_index_dropna():
     check(assert_type(midx.dropna(how="any"), pd.MultiIndex), pd.MultiIndex)
 
 
-def test_index_neg():
+def test_index_neg() -> None:
     # GH 253
     idx = pd.Index([1, 2])
     check(assert_type(-idx, "pd.Index[int]"), pd.Index)
@@ -306,7 +306,7 @@ def test_index_relops() -> None:
     check(assert_type(ind > 2, np_1darray[np.bool]), np_1darray[np.bool])
 
 
-def test_range_index_union():
+def test_range_index_union() -> None:
     check(
         assert_type(
             pd.RangeIndex(0, 10).union(pd.RangeIndex(10, 20)),
@@ -342,14 +342,14 @@ def test_index_union_sort() -> None:
     )
 
 
-def test_range_index_start_stop_step():
+def test_range_index_start_stop_step() -> None:
     idx = pd.RangeIndex(3)
     check(assert_type(idx.start, int), int)
     check(assert_type(idx.stop, int), int)
     check(assert_type(idx.step, int), int)
 
 
-def test_interval_range():
+def test_interval_range() -> None:
     check(
         assert_type(pd.interval_range(0, 10), "pd.IntervalIndex[pd.Interval[int]]"),
         pd.IntervalIndex,
@@ -502,7 +502,7 @@ def test_interval_range():
     )
 
 
-def test_interval_index_breaks():
+def test_interval_index_breaks() -> None:
     check(
         assert_type(
             pd.IntervalIndex.from_breaks([1, 2, 3, 4]),
@@ -632,7 +632,7 @@ def test_interval_index_breaks():
     )
 
 
-def test_interval_index_arrays():
+def test_interval_index_arrays() -> None:
     check(
         assert_type(
             pd.IntervalIndex.from_arrays([1, 2, 3, 4], [2, 3, 4, 5]),
@@ -761,7 +761,7 @@ def test_interval_index_arrays():
     )
 
 
-def test_interval_index_tuples():
+def test_interval_index_tuples() -> None:
     check(
         assert_type(
             pd.IntervalIndex.from_tuples([(1, 2), (2, 3)]),
@@ -1082,13 +1082,13 @@ def test_range_index_range() -> None:
     check(assert_type(iri, pd.RangeIndex), pd.RangeIndex, int)
 
 
-def test_multiindex_dtypes():
+def test_multiindex_dtypes() -> None:
     # GH-597
     mi = pd.MultiIndex.from_tuples([(1, 2.0), (2, 3.0)], names=["foo", "bar"])
     check(assert_type(mi.dtypes, "pd.Series[Dtype]"), pd.Series)
 
 
-def test_index_constructors():
+def test_index_constructors() -> None:
     # See if we can pick up the different index types in 2.0
     # Eventually should be using a generic index
     ilist = [1, 2, 3]

tests/scalars/test_scalars.py

@@ -297,7 +297,7 @@ def test_interval_math() -> None:
         )  # pyright: ignore[reportOperatorIssue]
 
 
-def test_interval_cmp():
+def test_interval_cmp() -> None:
     interval_i = pd.Interval(0, 1, closed="left")
     interval_f = pd.Interval(0.0, 1.0, closed="right")
     interval_ts = pd.Interval(

tests/series/test_series.py

@@ -1819,7 +1819,7 @@ def test_types_to_dict() -> None:
     assert_type(s.to_dict(), dict[Any, str])
 
 
-def test_categorical_codes():
+def test_categorical_codes() -> None:
     # GH-111
     cat = pd.Categorical(["a", "b", "a"])
     check(assert_type(cat.codes, np_1darray[np.signedinteger]), np_1darray[np.int8])
@@ -1942,7 +1942,7 @@ def test_squeeze() -> None:
     check(assert_type(s2.squeeze(), "pd.Series[int] | Scalar"), np.integer)
 
 
-def test_to_xarray():
+def test_to_xarray() -> None:
     s = pd.Series([1, 2])
     check(assert_type(s.to_xarray(), xr.DataArray), xr.DataArray)
 

tests/test_api_typing.py

@@ -42,7 +42,7 @@
 )
 
 
-def test_dataframegroupby():
+def test_dataframegroupby() -> None:
     df = pd.DataFrame({"a": [1, 2, 3]})
     group = df.groupby("a")
 
@@ -52,7 +52,7 @@ def f1(gb: DataFrameGroupBy):
     f1(group)
 
 
-def test_seriesgroupby():
+def test_seriesgroupby() -> None:
     sr = pd.Series([1, 2, 3], index=pd.Index(["a", "b", "a"]))
 
     def f1(gb: SeriesGroupBy):

tests/test_config.py

@@ -21,7 +21,7 @@
     Display = Options = Any
 
 
-def test_option_tools():
+def test_option_tools() -> None:
     check(assert_type(pd.reset_option("display.width"), None), type(None))
     check(assert_type(pd.set_option("display.width", 80), None), type(None))
     check(assert_type(pd.describe_option("display.width", False), str), str)
@@ -33,14 +33,14 @@ def test_option_tools():
         assert pd.get_option("display.width") == 120
 
 
-def test_specific_option():
+def test_specific_option() -> None:
     # GH 294
     check(assert_type(pd.options.plotting.backend, str), str)
     # Just check assignment
     pd.options.plotting.backend = "matplotlib"
 
 
-def test_display_float_format():
+def test_display_float_format() -> None:
     check(
         assert_type(pd.options.display.float_format, Callable[[float], str] | None),
         type(None),
@@ -50,7 +50,7 @@ def test_display_float_format():
         assert pd.get_option("display.float_format") == formatter
 
 
-def test_display_types_none_allowed_get_options():
+def test_display_types_none_allowed_get_options() -> None:
     # GH 1230
     # Initial values
     check(assert_type(pd.options.display.chop_threshold, float | None), type(None))
@@ -62,7 +62,7 @@ def test_display_types_none_allowed_get_options():
     check(assert_type(pd.options.display.min_rows, int | None), int)
 
 
-def test_display_types_none_allowed_set_options():
+def test_display_types_none_allowed_set_options() -> None:
     # GH 1230
     # Test setting each option as None and then to a specific value
     pd.options.display.chop_threshold = None
@@ -81,7 +81,7 @@ def test_display_types_none_allowed_set_options():
     pd.options.display.min_rows = 100
 
 
-def test_display_types_literal_constraints():
+def test_display_types_literal_constraints() -> None:
     # GH 1230
     # Various display options have specific allowed values
     # Test colheader_justify with allowed values

tests/test_frame.py

@@ -1512,7 +1512,7 @@ def test_types_pivot_table() -> None:
     )
 
 
-def test_pivot_table_sort():
+def test_pivot_table_sort() -> None:
     df = pd.DataFrame({"a": [1, 2], "b": [3, 4], "c": [5, 6], "d": [7, 8]})
 
     check(
@@ -2822,7 +2822,7 @@ def test_dataframe_pct_change() -> None:
     check(assert_type(df.pct_change(fill_value=0), pd.DataFrame), pd.DataFrame)
 
 
-def test_indexslice_setitem():
+def test_indexslice_setitem() -> None:
     df = pd.DataFrame(
         {"x": [1, 2, 2, 3], "y": [1, 2, 3, 4], "z": [10, 20, 30, 40]}
     ).set_index(["x", "y"])
@@ -2833,7 +2833,7 @@ def test_indexslice_setitem():
     df.loc[pd.IndexSlice[pd.Index([2, 3]), :], "z"] = 99
 
 
-def test_indexslice_getitem():
+def test_indexslice_getitem() -> None:
     # GH 300
     df = (
         pd.DataFrame({"x": [1, 2, 2, 3, 4], "y": [10, 20, 30, 40, 10]})
@@ -2865,7 +2865,7 @@ def test_indexslice_getitem():
     )
 
 
-def test_compute_values():
+def test_compute_values() -> None:
     df = pd.DataFrame({"x": [1, 2, 3, 4]})
     s: pd.Series = pd.Series([10, 20, 30, 40])
     check(assert_type(df["x"] + s.values, pd.Series), pd.Series, np.int64)
@@ -3295,7 +3295,7 @@ def test_not_hashable() -> None:
     check(assert_type(pd.Index.__hash__, None), type(None))
     check(assert_type(pd.Index([]).__hash__, None), type(None))
 
-    def test_func(_: Hashable):
+    def test_func(_: Hashable) -> None:
         pass
 
     if TYPE_CHECKING_INVALID_USAGE:
@@ -3527,7 +3527,7 @@ def test_groupby_result_for_ambiguous_indexes() -> None:
         check(assert_type(value2, pd.DataFrame), pd.DataFrame)
 
 
-def test_setitem_list():
+def test_setitem_list() -> None:
     # GH 153
     lst1: list[str] = ["a", "b", "c"]
     lst2: list[int] = [1, 2, 3]

tests/test_interval.py

@@ -121,7 +121,7 @@ def test_interval_length() -> None:
         _21 = i3 + pd.Timedelta(seconds=20)  # type: ignore[operator] # pyright: ignore[reportOperatorIssue]
 
 
-def test_interval_array_contains():
+def test_interval_array_contains() -> None:
     df = pd.DataFrame({"A": range(1, 10)})
     obj = pd.Interval(1, 4)
     ser = pd.Series(obj, index=df.index)