CoW: Remove copy-keywords as far as possible (pandas-dev#57327)

* CoW: Remove copy-keywords as far as possible

* Update

Author: phofl

pandas/core/base.py

@@ -218,7 +218,7 @@ def _obj_with_exclusions(self):
             return self.obj
 
         if self._selection is not None:
-            return self.obj._getitem_nocopy(self._selection_list)
+            return self.obj[self._selection_list]
 
         if len(self.exclusions) > 0:
             # equivalent to `self.obj.drop(self.exclusions, axis=1)

pandas/core/frame.py

@@ -1676,8 +1676,8 @@ def dot(self, other: AnyArrayLike | DataFrame) -> DataFrame | Series:
             if len(common) > len(self.columns) or len(common) > len(other.index):
                 raise ValueError("matrices are not aligned")
 
-            left = self.reindex(columns=common, copy=False)
-            right = other.reindex(index=common, copy=False)
+            left = self.reindex(columns=common)
+            right = other.reindex(index=common)
             lvals = left.values
             rvals = right._values
         else:
@@ -3800,27 +3800,6 @@ def _iter_column_arrays(self) -> Iterator[ArrayLike]:
         for i in range(len(self.columns)):
             yield self._get_column_array(i)
 
-    def _getitem_nocopy(self, key: list):
-        """
-        Behaves like __getitem__, but returns a view in cases where __getitem__
-        would make a copy.
-        """
-        # TODO(CoW): can be removed if/when we are always Copy-on-Write
-        indexer = self.columns._get_indexer_strict(key, "columns")[1]
-        new_axis = self.columns[indexer]
-
-        new_mgr = self._mgr.reindex_indexer(
-            new_axis,
-            indexer,
-            axis=0,
-            allow_dups=True,
-            copy=False,
-            only_slice=True,
-        )
-        result = self._constructor_from_mgr(new_mgr, axes=new_mgr.axes)
-        result = result.__finalize__(self)
-        return result
-
     def __getitem__(self, key):
         check_dict_or_set_indexers(key)
         key = lib.item_from_zerodim(key)
@@ -3911,7 +3890,7 @@ def _getitem_bool_array(self, key):
         key = check_bool_indexer(self.index, key)
 
         if key.all():
-            return self.copy(deep=None)
+            return self.copy(deep=False)
 
         indexer = key.nonzero()[0]
         return self.take(indexer, axis=0)
@@ -4774,7 +4753,7 @@ def predicate(arr: ArrayLike) -> bool:
 
             return True
 
-        mgr = self._mgr._get_data_subset(predicate).copy(deep=None)
+        mgr = self._mgr._get_data_subset(predicate).copy(deep=False)
         return self._constructor_from_mgr(mgr, axes=mgr.axes).__finalize__(self)
 
     def insert(
@@ -4919,7 +4898,7 @@ def assign(self, **kwargs) -> DataFrame:
         Portland    17.0    62.6  290.15
         Berkeley    25.0    77.0  298.15
         """
-        data = self.copy(deep=None)
+        data = self.copy(deep=False)
 
         for k, v in kwargs.items():
             data[k] = com.apply_if_callable(v, data)
@@ -4996,7 +4975,6 @@ def _reindex_multi(self, axes: dict[str, Index], fill_value) -> DataFrame:
         else:
             return self._reindex_with_indexers(
                 {0: [new_index, row_indexer], 1: [new_columns, col_indexer]},
-                copy=False,
                 fill_value=fill_value,
             )
 
@@ -5038,7 +5016,7 @@ def set_axis(
         axis: Axis = 0,
         copy: bool | None = None,
     ) -> DataFrame:
-        return super().set_axis(labels, axis=axis, copy=copy)
+        return super().set_axis(labels, axis=axis)
 
     @doc(
         NDFrame.reindex,
@@ -5065,7 +5043,6 @@ def reindex(
             columns=columns,
             axis=axis,
             method=method,
-            copy=copy,
             level=level,
             fill_value=fill_value,
             limit=limit,
@@ -5463,7 +5440,6 @@ def rename(
             index=index,
             columns=columns,
             axis=axis,
-            copy=copy,
             inplace=inplace,
             level=level,
             errors=errors,
@@ -5534,7 +5510,7 @@ def _replace_columnwise(
         DataFrame or None
         """
         # Operate column-wise
-        res = self if inplace else self.copy(deep=None)
+        res = self if inplace else self.copy(deep=False)
         ax = self.columns
 
         for i, ax_value in enumerate(ax):
@@ -5823,8 +5799,7 @@ def set_index(
         if inplace:
             frame = self
         else:
-            # GH 49473 Use "lazy copy" with Copy-on-Write
-            frame = self.copy(deep=None)
+            frame = self.copy(deep=False)
 
         arrays: list[Index] = []
         names: list[Hashable] = []
@@ -6114,7 +6089,7 @@ class    max    type
         if inplace:
             new_obj = self
         else:
-            new_obj = self.copy(deep=None)
+            new_obj = self.copy(deep=False)
         if allow_duplicates is not lib.no_default:
             allow_duplicates = validate_bool_kwarg(allow_duplicates, "allow_duplicates")
 
@@ -6386,7 +6361,7 @@ def dropna(
             raise ValueError(f"invalid how option: {how}")
 
         if np.all(mask):
-            result = self.copy(deep=None)
+            result = self.copy(deep=False)
         else:
             result = self.loc(axis=axis)[mask]
 
@@ -6515,7 +6490,7 @@ def drop_duplicates(
         4  Indomie  pack     5.0
         """
         if self.empty:
-            return self.copy(deep=None)
+            return self.copy(deep=False)
 
         inplace = validate_bool_kwarg(inplace, "inplace")
         ignore_index = validate_bool_kwarg(ignore_index, "ignore_index")
@@ -6631,7 +6606,7 @@ def duplicated(
 
         def f(vals) -> tuple[np.ndarray, int]:
             labels, shape = algorithms.factorize(vals, size_hint=len(self))
-            return labels.astype("i8", copy=False), len(shape)
+            return labels.astype("i8"), len(shape)
 
         if subset is None:
             # https://github.com/pandas-dev/pandas/issues/28770
@@ -6914,7 +6889,7 @@ def sort_values(
             if inplace:
                 return self._update_inplace(self)
             else:
-                return self.copy(deep=None)
+                return self.copy(deep=False)
 
         if is_range_indexer(indexer, len(indexer)):
             result = self.copy(deep=False)
@@ -7570,7 +7545,7 @@ def nsmallest(
         ),
     )
     def swaplevel(self, i: Axis = -2, j: Axis = -1, axis: Axis = 0) -> DataFrame:
-        result = self.copy(deep=None)
+        result = self.copy(deep=False)
 
         axis = self._get_axis_number(axis)
 
@@ -7630,7 +7605,7 @@ class      diet
         if not isinstance(self._get_axis(axis), MultiIndex):  # pragma: no cover
             raise TypeError("Can only reorder levels on a hierarchical axis.")
 
-        result = self.copy(deep=None)
+        result = self.copy(deep=False)
 
         if axis == 0:
             assert isinstance(result.index, MultiIndex)
@@ -7933,9 +7908,7 @@ def to_series(right):
         if flex is not None and isinstance(right, DataFrame):
             if not left._indexed_same(right):
                 if flex:
-                    left, right = left.align(
-                        right, join="outer", level=level, copy=False
-                    )
+                    left, right = left.align(right, join="outer", level=level)
                 else:
                     raise ValueError(
                         "Can only compare identically-labeled (both index and columns) "
@@ -7948,7 +7921,7 @@ def to_series(right):
                 if not left.axes[axis].equals(right.index):
                     raise ValueError(
                         "Operands are not aligned. Do "
-                        "`left, right = left.align(right, axis=1, copy=False)` "
+                        "`left, right = left.align(right, axis=1)` "
                         "before operating."
                     )
 
@@ -7957,7 +7930,6 @@ def to_series(right):
                 join="outer",
                 axis=axis,
                 level=level,
-                copy=False,
             )
             right = left._maybe_align_series_as_frame(right, axis)
 
@@ -8467,7 +8439,7 @@ def combine(
         """
         other_idxlen = len(other.index)  # save for compare
 
-        this, other = self.align(other, copy=False)
+        this, other = self.align(other)
         new_index = this.index
 
         if other.empty and len(new_index) == len(self.index):
@@ -8507,15 +8479,15 @@ def combine(
                 # try to promote series, which is all NaN, as other_dtype.
                 new_dtype = other_dtype
                 try:
-                    series = series.astype(new_dtype, copy=False)
+                    series = series.astype(new_dtype)
                 except ValueError:
                     # e.g. new_dtype is integer types
                     pass
             else:
                 # if we have different dtypes, possibly promote
                 new_dtype = find_common_type([this_dtype, other_dtype])
-                series = series.astype(new_dtype, copy=False)
-                other_series = other_series.astype(new_dtype, copy=False)
+                series = series.astype(new_dtype)
+                other_series = other_series.astype(new_dtype)
 
             arr = func(series, other_series)
             if isinstance(new_dtype, np.dtype):
@@ -9567,7 +9539,7 @@ def explode(
             result.index = default_index(len(result))
         else:
             result.index = self.index.take(result.index)
-        result = result.reindex(columns=self.columns, copy=False)
+        result = result.reindex(columns=self.columns)
 
         return result.__finalize__(self, method="explode")
 
@@ -10263,9 +10235,7 @@ def _append(
             row_df = other.to_frame().T
             # infer_objects is needed for
             #  test_append_empty_frame_to_series_with_dateutil_tz
-            other = row_df.infer_objects(copy=False).rename_axis(
-                index.names, copy=False
-            )
+            other = row_df.infer_objects().rename_axis(index.names)
         elif isinstance(other, list):
             if not other:
                 pass
@@ -10509,7 +10479,7 @@ def join(
                     res = concat(
                         frames, axis=1, join="outer", verify_integrity=True, sort=sort
                     )
-                    return res.reindex(self.index, copy=False)
+                    return res.reindex(self.index)
                 else:
                     return concat(
                         frames, axis=1, join=how, verify_integrity=True, sort=sort
@@ -10559,7 +10529,6 @@ def merge(
             right_index=right_index,
             sort=sort,
             suffixes=suffixes,
-            copy=copy,
             indicator=indicator,
             validate=validate,
         )
@@ -11024,7 +10993,7 @@ def corrwith(
 
         if numeric_only:
             other = other._get_numeric_data()
-        left, right = this.align(other, join="inner", copy=False)
+        left, right = this.align(other, join="inner")
 
         if axis == 1:
             left = left.T
@@ -11161,7 +11130,7 @@ def count(self, axis: Axis = 0, numeric_only: bool = False):
         else:
             result = notna(frame).sum(axis=axis)
 
-        return result.astype("int64", copy=False).__finalize__(self, method="count")
+        return result.astype("int64").__finalize__(self, method="count")
 
     def _reduce(
         self,
@@ -11225,7 +11194,7 @@ def _get_data() -> DataFrame:
         if axis is None:
             dtype = find_common_type([arr.dtype for arr in df._mgr.arrays])
             if isinstance(dtype, ExtensionDtype):
-                df = df.astype(dtype, copy=False)
+                df = df.astype(dtype)
                 arr = concat_compat(list(df._iter_column_arrays()))
                 return arr._reduce(name, skipna=skipna, keepdims=False, **kwds)
             return func(df.values)
@@ -11257,7 +11226,7 @@ def _get_data() -> DataFrame:
                     # be equivalent to transposing the original frame and aggregating
                     # with axis=0.
                     name = {"argmax": "idxmax", "argmin": "idxmin"}.get(name, name)
-                    df = df.astype(dtype, copy=False)
+                    df = df.astype(dtype)
                     arr = concat_compat(list(df._iter_column_arrays()))
                     nrows, ncols = df.shape
                     row_index = np.tile(np.arange(nrows), ncols)