Handle flake8-bugbear errors

Author: stinodego

py-polars/polars/internals/frame.py

@@ -4053,8 +4053,8 @@ def drop(self: DF, name: str | list[str]) -> DF:
         if isinstance(name, list):
             df = self.clone()
 
-            for name in name:
-                df._df.drop_in_place(name)
+            for n in name:
+                df._df.drop_in_place(n)
             return df
 
         return self._from_pydf(self._df.drop(name))
@@ -4192,7 +4192,7 @@ def clone(self: DF) -> DF:
     def __copy__(self: DF) -> DF:
         return self.clone()
 
-    def __deepcopy__(self: DF, memodict: dict = {}) -> DF:
+    def __deepcopy__(self: DF, memo: None = None) -> DF:
         return self.clone()
 
     def get_columns(self) -> list[pli.Series]:

py-polars/polars/internals/lazy_frame.py

@@ -809,7 +809,7 @@ def clone(self: LDF) -> LDF:
     def __copy__(self: LDF) -> LDF:
         return self.clone()
 
-    def __deepcopy__(self: LDF, memodict: dict = {}) -> LDF:
+    def __deepcopy__(self: LDF, memo: None = None) -> LDF:
         return self.clone()
 
     def filter(self: LDF, predicate: pli.Expr | str) -> LDF:

py-polars/polars/internals/series.py

@@ -2433,7 +2433,7 @@ def clone(self) -> "Series":
     def __copy__(self) -> Series:
         return self.clone()
 
-    def __deepcopy__(self, memodict: Any = {}) -> Series:
+    def __deepcopy__(self, memo: None = None) -> Series:
         return self.clone()
 
     def fill_nan(self, fill_value: str | int | float | bool | pli.Expr) -> Series:

py-polars/polars/testing.py

@@ -357,7 +357,7 @@ def between(draw: Callable, type_: type, min_: Any, max_: Any) -> Any:
         """
         Draw a value in a given range from a type-inferred strategy.
         """
-        strategy_init = getattr(from_type(type_), "function")
+        strategy_init = from_type(type_).function  # type: ignore[attr-defined]
         return draw(strategy_init(min_, max_))
 
     @dataclass

py-polars/tests/db-benchmark/various.py

@@ -70,7 +70,7 @@ def test_windows_not_cached() -> None:
         )
     )
     # this might fail if they are cached
-    for i in range(1000):
+    for _ in range(1000):
         ldf.collect()
 
 

py-polars/tests/test_df.py

@@ -64,7 +64,7 @@ def test_init_only_columns() -> None:
         assert df.shape == (0, 4)
         assert df.frame_equal(truth, null_equal=True)
         assert df.dtypes == [pl.Date, pl.UInt64, pl.Int8, pl.List]
-        assert getattr(df.schema["d"], "inner") == pl.UInt8
+        assert df.schema["d"].inner == pl.UInt8  # type: ignore[attr-defined]
 
         dfe = df.cleared()
         assert (df.schema == dfe.schema) and (dfe.shape == df.shape)

py-polars/tests/test_lists.py

@@ -61,7 +61,7 @@ def test_dtype() -> None:
     a = pl.Series("a", [[1, 2, 3], [2, 5], [6, 7, 8, 9]])
     assert a.dtype == pl.List
     assert a.inner_dtype == pl.Int64
-    assert getattr(a.dtype, "inner") == pl.Int64
+    assert a.dtype.inner == pl.Int64  # type: ignore[attr-defined]
 
     # explicit
     df = pl.DataFrame(
@@ -84,7 +84,7 @@ def test_dtype() -> None:
         "dt": pl.List(pl.Date),
         "dtm": pl.List(pl.Datetime),
     }
-    assert getattr(df.schema["i"], "inner") == pl.Int8
+    assert df.schema["i"].inner == pl.Int8  # type: ignore[attr-defined]
     assert df.rows() == [
         (
             [1, 2, 3],

py-polars/tests/test_series.py

@@ -1054,11 +1054,11 @@ def test_comparisons_bool_series_to_int() -> None:
     with pytest.raises(
         TypeError, match=r"'<' not supported between instances of 'Series' and 'int'"
     ):
-        srs_bool < 2
+        srs_bool < 2  # noqa: B015
     with pytest.raises(
         TypeError, match=r"'>' not supported between instances of 'Series' and 'int'"
     ):
-        srs_bool > 2
+        srs_bool > 2  # noqa: B015
 
 
 def test_trigonometry_functions() -> None:

py-polars/tests/test_window.py

@@ -116,14 +116,11 @@ def test_no_panic_on_nan_3067() -> None:
         }
     )
 
-    df.select([pl.col("total").shift().over("group")])["total"].to_list() == [
-        None,
-        1.0,
-        2.0,
-        None,
-        4.0,
-        5.0,
-    ]
+    expected = [None, 1.0, 2.0, None, 4.0, 5.0]
+    assert (
+        df.select([pl.col("total").shift().over("group")])["total"].to_list()
+        == expected
+    )
 
 
 def test_quantile_as_window() -> None: