CoW: Remove remaining occurrences from CoW

pandas/core/base.py

@@ -18,8 +18,6 @@
 
 import numpy as np
 
-from pandas._config import using_copy_on_write
-
 from pandas._libs import lib
 from pandas._typing import (
     AxisInt,
@@ -661,10 +659,10 @@ def to_numpy(
 
         result = np.asarray(values, dtype=dtype)
 
-        if (copy and not fillna) or (not copy and using_copy_on_write()):
+        if (copy and not fillna) or not copy:
             if np.shares_memory(self._values[:2], result[:2]):
                 # Take slices to improve performance of check
-                if using_copy_on_write() and not copy:
+                if not copy:
                     result = result.view()
                     result.flags.writeable = False
                 else:

pandas/core/indexes/api.py

@@ -74,7 +74,6 @@ def get_objs_combined_axis(
     intersect: bool = False,
     axis: Axis = 0,
     sort: bool = True,
-    copy: bool = False,
 ) -> Index:
     """
     Extract combined index: return intersection or union (depending on the
@@ -92,15 +91,13 @@ def get_objs_combined_axis(
         The axis to extract indexes from.
     sort : bool, default True
         Whether the result index should come out sorted or not.
-    copy : bool, default False
-        If True, return a copy of the combined index.
 
     Returns
     -------
     Index
     """
     obs_idxes = [obj._get_axis(axis) for obj in objs]
-    return _get_combined_index(obs_idxes, intersect=intersect, sort=sort, copy=copy)
+    return _get_combined_index(obs_idxes, intersect=intersect, sort=sort)
 
 
 def _get_distinct_objs(objs: list[Index]) -> list[Index]:
@@ -121,7 +118,6 @@ def _get_combined_index(
     indexes: list[Index],
     intersect: bool = False,
     sort: bool = False,
-    copy: bool = False,
 ) -> Index:
     """
     Return the union or intersection of indexes.
@@ -135,8 +131,6 @@ def _get_combined_index(
         calculate the union.
     sort : bool, default False
         Whether the result index should come out sorted or not.
-    copy : bool, default False
-        If True, return a copy of the combined index.
 
     Returns
     -------
@@ -158,10 +152,6 @@ def _get_combined_index(
 
     if sort:
         index = safe_sort_index(index)
-    # GH 29879
-    if copy:
-        index = index.copy()
-
     return index
 
 

pandas/core/indexes/base.py

@@ -22,7 +22,6 @@
 
 from pandas._config import (
     get_option,
-    using_copy_on_write,
     using_pyarrow_string_dtype,
 )
 
@@ -1633,7 +1632,7 @@ def to_frame(
 
         if name is lib.no_default:
             name = self._get_level_names()
-        result = DataFrame({name: self}, copy=not using_copy_on_write())
+        result = DataFrame({name: self}, copy=False)
 
         if index:
             result.index = self
@@ -4773,13 +4772,11 @@ def values(self) -> ArrayLike:
         [(0, 1], (1, 2], (2, 3], (3, 4], (4, 5]]
         Length: 5, dtype: interval[int64, right]
         """
-        if using_copy_on_write():
-            data = self._data
-            if isinstance(data, np.ndarray):
-                data = data.view()
-                data.flags.writeable = False
-            return data
-        return self._data
+        data = self._data
+        if isinstance(data, np.ndarray):
+            data = data.view()
+            data.flags.writeable = False
+        return data
 
     @cache_readonly
     @doc(IndexOpsMixin.array)

pandas/core/indexes/datetimelike.py

@@ -16,8 +16,6 @@
 
 import numpy as np
 
-from pandas._config import using_copy_on_write
-
 from pandas._libs import (
     NaT,
     Timedelta,
@@ -454,9 +452,8 @@ def _with_freq(self, freq):
     def values(self) -> np.ndarray:
         # NB: For Datetime64TZ this is lossy
         data = self._data._ndarray
-        if using_copy_on_write():
-            data = data.view()
-            data.flags.writeable = False
+        data = data.view()
+        data.flags.writeable = False
         return data
 
     @doc(DatetimeIndexOpsMixin.shift)

pandas/core/indexing.py

@@ -13,8 +13,6 @@
 
 import numpy as np
 
-from pandas._config import using_copy_on_write
-
 from pandas._libs.indexing import NDFrameIndexerBase
 from pandas._libs.lib import item_from_zerodim
 from pandas.compat import PYPY
@@ -894,7 +892,7 @@ def _ensure_listlike_indexer(self, key, axis=None, value=None) -> None:
 
     @final
     def __setitem__(self, key, value) -> None:
-        if not PYPY and using_copy_on_write():
+        if not PYPY:
             if sys.getrefcount(self.obj) <= 2:
                 warnings.warn(
                     _chained_assignment_msg, ChainedAssignmentError, stacklevel=2
@@ -2107,7 +2105,7 @@ def _setitem_with_indexer_frame_value(
                         tuple(sub_indexer),
                         value[item],
                         multiindex_indexer,
-                        using_cow=using_copy_on_write(),
+                        using_cow=True,
                     )
                 else:
                     val = np.nan

pandas/core/reshape/concat.py

@@ -15,8 +15,6 @@
 
 import numpy as np
 
-from pandas._config import using_copy_on_write
-
 from pandas.util._decorators import cache_readonly
 from pandas.util._exceptions import find_stack_level
 
@@ -370,13 +368,6 @@ def concat(
     0   1   2
     1   3   4
     """
-    if copy is None:
-        if using_copy_on_write():
-            copy = False
-        else:
-            copy = True
-    elif copy and using_copy_on_write():
-        copy = False
 
     op = _Concatenator(
         objs,
@@ -387,7 +378,6 @@ def concat(
         levels=levels,
         names=names,
         verify_integrity=verify_integrity,
-        copy=copy,
         sort=sort,
     )
 
@@ -411,7 +401,6 @@ def __init__(
         names: list[HashableT] | None = None,
         ignore_index: bool = False,
         verify_integrity: bool = False,
-        copy: bool = True,
         sort: bool = False,
     ) -> None:
         if isinstance(objs, (ABCSeries, ABCDataFrame, str)):
@@ -439,7 +428,6 @@ def __init__(
 
         self.ignore_index = ignore_index
         self.verify_integrity = verify_integrity
-        self.copy = copy
 
         objs, keys = self._clean_keys_and_objs(objs, keys)
 
@@ -656,7 +644,7 @@ def get_result(self):
                 cons = sample._constructor_expanddim
 
                 index, columns = self.new_axes
-                df = cons(data, index=index, copy=self.copy)
+                df = cons(data, index=index, copy=False)
                 df.columns = columns
                 return df.__finalize__(self, method="concat")
 
@@ -681,10 +669,8 @@ def get_result(self):
                 mgrs_indexers.append((obj._mgr, indexers))
 
             new_data = concatenate_managers(
-                mgrs_indexers, self.new_axes, concat_axis=self.bm_axis, copy=self.copy
+                mgrs_indexers, self.new_axes, concat_axis=self.bm_axis, copy=False
             )
-            if not self.copy and not using_copy_on_write():
-                new_data._consolidate_inplace()
 
             out = sample._constructor_from_mgr(new_data, axes=new_data.axes)
             return out.__finalize__(self, method="concat")
@@ -710,7 +696,6 @@ def _get_comb_axis(self, i: AxisInt) -> Index:
             axis=data_axis,
             intersect=self.intersect,
             sort=self.sort,
-            copy=self.copy,
         )
 
     @cache_readonly

pandas/io/parsers/readers.py

@@ -26,8 +26,6 @@
 
 import numpy as np
 
-from pandas._config import using_copy_on_write
-
 from pandas._libs import lib
 from pandas._libs.parsers import STR_NA_VALUES
 from pandas.errors import (
@@ -1967,7 +1965,7 @@ def read(self, nrows: int | None = None) -> DataFrame:
                 new_col_dict,
                 columns=columns,
                 index=index,
-                copy=not using_copy_on_write(),
+                copy=False,
             )
 
             self._currow += new_rows

pandas/io/pytables.py

@@ -30,7 +30,6 @@
 from pandas._config import (
     config,
     get_option,
-    using_copy_on_write,
     using_pyarrow_string_dtype,
 )
 
@@ -3294,13 +3293,8 @@ def read(
             dfs.append(df)
 
         if len(dfs) > 0:
-            out = concat(dfs, axis=1, copy=True)
-            if using_copy_on_write():
-                # with CoW, concat ignores the copy keyword. Here, we still want
-                # to copy to enforce optimized column-major layout
-                out = out.copy()
-            out = out.reindex(columns=items, copy=False)
-            return out
+            out = concat(dfs, axis=1).copy()
+            return out.reindex(columns=items, copy=False)
 
         return DataFrame(columns=axes[0], index=axes[1])