Ruff lints

Author: hombit

src/nested_pandas/nestedframe/core.py

@@ -538,7 +538,7 @@ def from_lists(cls, df, base_columns=None, list_columns=None, name="nested"):
                 # This is a simple heuristic but infers more than its dtype
                 # which will probably be an object.
                 sample_val = df[col].iloc[0]
-                if not hasattr(sample_val, "__iter__") and not isinstance(sample_val, (str, bytes)):
+                if not hasattr(sample_val, "__iter__") and not isinstance(sample_val, str | bytes):
                     raise ValueError(
                         f"Cannot pack column {col} which does not contain an iterable list based "
                         "on its first value, {sample_val}."
@@ -1290,7 +1290,7 @@ def reduce(self, func, *args, infer_nesting=True, **kwargs) -> NestedFrame:  # t
             else:
                 iterators.append(self[layer].array.iter_field_lists(col))
 
-        results = [func(*cols, *extra_args, **kwargs) for cols in zip(*iterators)]
+        results = [func(*cols, *extra_args, **kwargs) for cols in zip(*iterators, strict=True)]
         results_nf = NestedFrame(results, index=self.index)
 
         if infer_nesting:

src/nested_pandas/nestedframe/io.py

@@ -87,7 +87,7 @@ def read_parquet(
     # First load through pyarrow
     # Check if `data` is a file-like object or a sequence
     if hasattr(data, "read") or (
-        isinstance(data, Sequence) and not isinstance(data, (str, bytes, bytearray))
+        isinstance(data, Sequence) and not isinstance(data, str | bytes | bytearray)
     ):
         # If `data` is a file-like object or a sequence, pass it directly to pyarrow
         table = pq.read_table(data, columns=columns, **kwargs)
@@ -103,7 +103,7 @@ def read_parquet(
     # was from a nested column.
     if columns is not None:
         nested_structures: dict[str, list[int]] = {}
-        for i, (col_in, col_pa) in enumerate(zip(columns, table.column_names)):
+        for i, (col_in, col_pa) in enumerate(zip(columns, table.column_names, strict=True)):
             # if the column name is not the same, it was a partial load
             if col_in != col_pa:
                 # get the top-level column name

src/nested_pandas/series/ext_array.py

@@ -35,8 +35,8 @@
 # typing.Self and "|" union syntax don't exist in Python 3.9
 from __future__ import annotations
 
-from collections.abc import Generator, Iterable, Iterator, Sequence
-from typing import Any, Callable, cast
+from collections.abc import Callable, Generator, Iterable, Iterator, Sequence
+from typing import Any, cast
 
 import numpy as np
 import pandas as pd
@@ -551,7 +551,7 @@ def format_series(series):
                     return series.apply(repr)
 
                 def format_row(row):
-                    return ", ".join(f"{name}: {value}" for name, value in zip(row.index, row))
+                    return ", ".join(f"{name}: {value}" for name, value in zip(row.index, row, strict=True))
 
                 # Format series to strings
                 df = df.apply(format_series, axis=0)
@@ -665,7 +665,7 @@ def _box_pa_array(cls, value, *, pa_type: pa.DataType | None) -> pa.Array | pa.C
         """Convert a value to a PyArrow array with the specified type."""
         if isinstance(value, cls):
             pa_array = value.struct_array
-        elif isinstance(value, (pa.Array, pa.ChunkedArray)):
+        elif isinstance(value, pa.Array | pa.ChunkedArray):
             pa_array = value
         else:
             try:
@@ -700,7 +700,7 @@ def _from_arrow_like(cls, arraylike, dtype: NestedDtype | None = None) -> Self:
             if dtype is None or dtype == arraylike.dtype:
                 return arraylike
             array = arraylike.list_array
-        elif isinstance(arraylike, (pa.Array, pa.ChunkedArray)):
+        elif isinstance(arraylike, pa.Array | pa.ChunkedArray):
             array = arraylike
         else:
             array = pa.array(arraylike)
@@ -1112,7 +1112,7 @@ def fill_field_lists(self, field: str, value: ArrayLike, *, keep_dtype: bool = F
             )
         if np.size(value) != len(self):
             raise ValueError("The length of the input array must be equal to the length of the series")
-        if isinstance(value, (pa.ChunkedArray, pa.Array)):
+        if isinstance(value, pa.ChunkedArray | pa.Array):
             value = pa.compute.take(value, self.get_list_index())
         else:
             value = np.repeat(value, self.list_lengths)

tests/nested_pandas/series/test_ext_array.py

@@ -1375,9 +1375,9 @@ def test_iter_field_lists():
     )
     ext_array = NestedExtensionArray(struct_array)
 
-    for actual, desired in zip(ext_array.iter_field_lists("a"), a):
+    for actual, desired in zip(ext_array.iter_field_lists("a"), a, strict=True):
         assert_array_equal(actual, desired)
-    for actual, desired in zip(ext_array.iter_field_lists("b"), b):
+    for actual, desired in zip(ext_array.iter_field_lists("b"), b, strict=True):
         assert_array_equal(actual, desired)