Resolve conflicts

Author: phofl

pandas/io/parsers/base_parser.py

@@ -453,9 +453,9 @@ def _maybe_dedup_names(self, names: Sequence[Hashable]) -> Sequence[Hashable]:
     @final
     def _maybe_make_multi_index_columns(
         self,
-        columns: list[Scalar] | list[tuple],
-        col_names: list[Scalar | None] | list[tuple] | None = None,
-    ) -> list[Scalar] | MultiIndex:
+        columns: Sequence[Hashable],
+        col_names: Sequence[Hashable] | None = None,
+    ) -> Sequence[Hashable] | MultiIndex:
         # possibly create a column mi here
         if _is_potential_multi_index(columns):
             columns = cast(List[Tuple], columns)
@@ -940,21 +940,27 @@ def _check_data_length(
             )
 
     @overload
-    def _evaluate_usecols(self, usecols: Callable, names: list[Scalar]) -> set[int]:
+    def _evaluate_usecols(
+        self, usecols: Callable, names: Sequence[Hashable]
+    ) -> set[int]:
         ...
 
     @overload
-    def _evaluate_usecols(self, usecols: set[int], names: list[Scalar]) -> set[int]:
+    def _evaluate_usecols(
+        self, usecols: set[int], names: Sequence[Hashable]
+    ) -> set[int]:
         ...
 
     @overload
-    def _evaluate_usecols(self, usecols: set[str], names: list[Scalar]) -> set[str]:
+    def _evaluate_usecols(
+        self, usecols: set[str], names: Sequence[Hashable]
+    ) -> set[str]:
         ...
 
     def _evaluate_usecols(
         self,
         usecols: Callable | set[str] | set[int],
-        names: list[Scalar],
+        names: Sequence[Hashable],
     ) -> set[str] | set[int]:
         """
         Check whether or not the 'usecols' parameter
@@ -1321,7 +1327,7 @@ def _get_na_values(col, na_values, na_fvalues, keep_default_na):
 
 
 def _is_potential_multi_index(
-    columns: list[Scalar] | list[tuple] | MultiIndex,
+    columns: Sequence[Hashable] | MultiIndex,
     index_col: bool | Sequence[int] | None = None,
 ) -> bool:
     """

pandas/io/parsers/c_parser_wrapper.py

@@ -1,5 +1,10 @@
 from __future__ import annotations
 
+from typing import (
+    Hashable,
+    Mapping,
+    Sequence,
+)
 import warnings
 
 import numpy as np
@@ -11,7 +16,6 @@
     DtypeObj,
     FilePath,
     ReadCsvBuffer,
-    Scalar,
 )
 from pandas.errors import DtypeWarning
 from pandas.util._exceptions import find_stack_level
@@ -226,8 +230,8 @@ def read(
         nrows: int | None = None,
     ) -> tuple[
         Index | MultiIndex | None,
-        list[Scalar] | MultiIndex,
-        dict[Scalar | tuple, ArrayLike],
+        Sequence[Hashable] | MultiIndex,
+        Mapping[Hashable, ArrayLike],
     ]:
         try:
             if self.low_memory:
@@ -320,11 +324,11 @@ def read(
             index, names = self._make_index(date_data, alldata, names)
 
         # maybe create a mi on the columns
-        names = self._maybe_make_multi_index_columns(names, self.col_names)
+        conv_names = self._maybe_make_multi_index_columns(names, self.col_names)
 
-        return index, names, date_data
+        return index, conv_names, date_data
 
-    def _filter_usecols(self, names: list[Scalar]) -> list[Scalar]:
+    def _filter_usecols(self, names: Sequence[Hashable]) -> Sequence[Hashable]:
         # hackish
         usecols = self._evaluate_usecols(self.usecols, names)
         if usecols is not None and len(names) != len(usecols):
@@ -410,8 +414,8 @@ def _concatenate_chunks(chunks: list[dict[int, ArrayLike]]) -> dict:
 
 
 def ensure_dtype_objs(
-    dtype: DtypeArg | dict[Scalar, DtypeArg] | None
-) -> DtypeObj | dict[Scalar, DtypeObj] | None:
+    dtype: DtypeArg | Mapping[Hashable, DtypeArg] | None
+) -> DtypeObj | Mapping[Hashable, DtypeObj] | None:
     """
     Ensure we have either None, a dtype object, or a dictionary mapping to
     dtype objects.

pandas/io/parsers/python_parser.py

@@ -268,8 +268,8 @@ def read(self, rows: int | None = None):
                 self.index_names,
                 self.dtype,
             )
-            columns = self._maybe_make_multi_index_columns(columns, self.col_names)
-            return index, columns, col_dict
+            conv_columns = self._maybe_make_multi_index_columns(columns, self.col_names)
+            return index, conv_columns, col_dict
 
         # handle new style for names in index
         count_empty_content_vals = count_empty_vals(content[0])