Backport PR #51803 on branch 2.0.x (CoW: Add reference tracking to index when created from series)

pandas/_libs/internals.pyx

@@ -890,6 +890,16 @@ cdef class BlockValuesRefs:
         """
         self.referenced_blocks.append(weakref.ref(blk))
 
+    def add_index_reference(self, index: object) -> None:
+        """Adds a new reference to our reference collection when creating an index.
+
+        Parameters
+        ----------
+        index: object
+            The index that the new reference should point to.
+        """
+        self.referenced_blocks.append(weakref.ref(index))
+
     def has_reference(self) -> bool:
         """Checks if block has foreign references.
 

pandas/core/frame.py

@@ -5879,7 +5879,7 @@ def set_index(
                 names.append(None)
             # from here, col can only be a column label
             else:
-                arrays.append(frame[col]._values)
+                arrays.append(frame[col])
                 names.append(col)
                 if drop:
                     to_remove.append(col)

pandas/core/indexes/base.py

@@ -73,7 +73,10 @@
     rewrite_exception,
 )
 
-from pandas.core.dtypes.astype import astype_array
+from pandas.core.dtypes.astype import (
+    astype_array,
+    astype_is_view,
+)
 from pandas.core.dtypes.cast import (
     LossySetitemError,
     can_hold_element,
@@ -457,6 +460,8 @@ def _engine_type(
 
     str = CachedAccessor("str", StringMethods)
 
+    _references = None
+
     # --------------------------------------------------------------------
     # Constructors
 
@@ -477,6 +482,10 @@ def __new__(
 
         data_dtype = getattr(data, "dtype", None)
 
+        refs = None
+        if not copy and isinstance(data, (ABCSeries, Index)):
+            refs = data._references
+
         # range
         if isinstance(data, (range, RangeIndex)):
             result = RangeIndex(start=data, copy=copy, name=name)
@@ -550,7 +559,7 @@ def __new__(
         klass = cls._dtype_to_subclass(arr.dtype)
 
         arr = klass._ensure_array(arr, arr.dtype, copy=False)
-        return klass._simple_new(arr, name)
+        return klass._simple_new(arr, name, refs=refs)
 
     @classmethod
     def _ensure_array(cls, data, dtype, copy: bool):
@@ -629,7 +638,7 @@ def _dtype_to_subclass(cls, dtype: DtypeObj):
 
     @classmethod
     def _simple_new(
-        cls: type[_IndexT], values: ArrayLike, name: Hashable = None
+        cls: type[_IndexT], values: ArrayLike, name: Hashable = None, refs=None
     ) -> _IndexT:
         """
         We require that we have a dtype compat for the values. If we are passed
@@ -644,6 +653,9 @@ def _simple_new(
         result._name = name
         result._cache = {}
         result._reset_identity()
+        result._references = refs
+        if refs is not None:
+            refs.add_index_reference(result)
 
         return result
 
@@ -740,13 +752,13 @@ def _shallow_copy(self: _IndexT, values, name: Hashable = no_default) -> _IndexT
         """
         name = self._name if name is no_default else name
 
-        return self._simple_new(values, name=name)
+        return self._simple_new(values, name=name, refs=self._references)
 
     def _view(self: _IndexT) -> _IndexT:
         """
         fastpath to make a shallow copy, i.e. new object with same data.
         """
-        result = self._simple_new(self._values, name=self._name)
+        result = self._simple_new(self._values, name=self._name, refs=self._references)
 
         result._cache = self._cache
         return result
@@ -956,7 +968,7 @@ def view(self, cls=None):
                 #  of types.
                 arr_cls = idx_cls._data_cls
                 arr = arr_cls(self._data.view("i8"), dtype=dtype)
-                return idx_cls._simple_new(arr, name=self.name)
+                return idx_cls._simple_new(arr, name=self.name, refs=self._references)
 
             result = self._data.view(cls)
         else:
@@ -1012,7 +1024,15 @@ def astype(self, dtype, copy: bool = True):
             new_values = astype_array(values, dtype=dtype, copy=copy)
 
         # pass copy=False because any copying will be done in the astype above
-        return Index(new_values, name=self.name, dtype=new_values.dtype, copy=False)
+        result = Index(new_values, name=self.name, dtype=new_values.dtype, copy=False)
+        if (
+            not copy
+            and self._references is not None
+            and astype_is_view(self.dtype, dtype)
+        ):
+            result._references = self._references
+            result._references.add_index_reference(result)
+        return result
 
     _index_shared_docs[
         "take"
@@ -5155,7 +5175,9 @@ def __getitem__(self, key):
             # pessimization com.is_bool_indexer and ndim checks.
             result = getitem(key)
             # Going through simple_new for performance.
-            return type(self)._simple_new(result, name=self._name)
+            return type(self)._simple_new(
+                result, name=self._name, refs=self._references
+            )
 
         if com.is_bool_indexer(key):
             # if we have list[bools, length=1e5] then doing this check+convert
@@ -5181,7 +5203,7 @@ def _getitem_slice(self: _IndexT, slobj: slice) -> _IndexT:
         Fastpath for __getitem__ when we know we have a slice.
         """
         res = self._data[slobj]
-        return type(self)._simple_new(res, name=self._name)
+        return type(self)._simple_new(res, name=self._name, refs=self._references)
 
     @final
     def _can_hold_identifiers_and_holds_name(self, name) -> bool:
@@ -6700,7 +6722,11 @@ def infer_objects(self, copy: bool = True) -> Index:
         )
         if copy and res_values is values:
             return self.copy()
-        return Index(res_values, name=self.name)
+        result = Index(res_values, name=self.name)
+        if not copy and res_values is values and self._references is not None:
+            result._references = self._references
+            result._references.add_index_reference(result)
+        return result
 
     # --------------------------------------------------------------------
     # Generated Arithmetic, Comparison, and Unary Methods

pandas/core/indexes/datetimes.py

@@ -44,6 +44,7 @@
     is_datetime64tz_dtype,
     is_scalar,
 )
+from pandas.core.dtypes.generic import ABCSeries
 from pandas.core.dtypes.missing import is_valid_na_for_dtype
 
 from pandas.core.arrays.datetimes import (
@@ -266,7 +267,7 @@ def strftime(self, date_format) -> Index:
     @doc(DatetimeArray.tz_convert)
     def tz_convert(self, tz) -> DatetimeIndex:
         arr = self._data.tz_convert(tz)
-        return type(self)._simple_new(arr, name=self.name)
+        return type(self)._simple_new(arr, name=self.name, refs=self._references)
 
     @doc(DatetimeArray.tz_localize)
     def tz_localize(
@@ -345,8 +346,11 @@ def __new__(
             yearfirst=yearfirst,
             ambiguous=ambiguous,
         )
+        refs = None
+        if not copy and isinstance(data, (Index, ABCSeries)):
+            refs = data._references
 
-        subarr = cls._simple_new(dtarr, name=name)
+        subarr = cls._simple_new(dtarr, name=name, refs=refs)
         return subarr
 
     # --------------------------------------------------------------------

pandas/core/indexes/multi.py

@@ -353,6 +353,7 @@ def __new__(
             result._codes = new_codes
 
         result._reset_identity()
+        result._references = None
 
         return result
 

pandas/core/indexes/period.py

@@ -28,6 +28,7 @@
 
 from pandas.core.dtypes.common import is_integer
 from pandas.core.dtypes.dtypes import PeriodDtype
+from pandas.core.dtypes.generic import ABCSeries
 from pandas.core.dtypes.missing import is_valid_na_for_dtype
 
 from pandas.core.arrays.period import (
@@ -217,6 +218,10 @@ def __new__(
             "second",
         }
 
+        refs = None
+        if not copy and isinstance(data, (Index, ABCSeries)):
+            refs = data._references
+
         if not set(fields).issubset(valid_field_set):
             argument = list(set(fields) - valid_field_set)[0]
             raise TypeError(f"__new__() got an unexpected keyword argument {argument}")
@@ -257,7 +262,7 @@ def __new__(
         if copy:
             data = data.copy()
 
-        return cls._simple_new(data, name=name)
+        return cls._simple_new(data, name=name, refs=refs)
 
     # ------------------------------------------------------------------------
     # Data

pandas/core/indexes/range.py

@@ -175,6 +175,7 @@ def _simple_new(  # type: ignore[override]
         result._name = name
         result._cache = {}
         result._reset_identity()
+        result._references = None
         return result
 
     @classmethod

pandas/core/indexes/timedeltas.py

@@ -17,6 +17,7 @@
     is_scalar,
     is_timedelta64_dtype,
 )
+from pandas.core.dtypes.generic import ABCSeries
 
 from pandas.core.arrays import datetimelike as dtl
 from pandas.core.arrays.timedeltas import TimedeltaArray
@@ -168,7 +169,11 @@ def __new__(
         tdarr = TimedeltaArray._from_sequence_not_strict(
             data, freq=freq, unit=unit, dtype=dtype, copy=copy
         )
-        return cls._simple_new(tdarr, name=name)
+        refs = None
+        if not copy and isinstance(data, (ABCSeries, Index)):
+            refs = data._references
+
+        return cls._simple_new(tdarr, name=name, refs=refs)
 
     # -------------------------------------------------------------------
 

pandas/tests/copy_view/index/test_datetimeindex.py

@@ -0,0 +1,56 @@
+import pytest
+
+from pandas import (
+    DatetimeIndex,
+    Series,
+    Timestamp,
+    date_range,
+)
+import pandas._testing as tm
+
+
+@pytest.mark.parametrize(
+    "cons",
+    [
+        lambda x: DatetimeIndex(x),
+        lambda x: DatetimeIndex(DatetimeIndex(x)),
+    ],
+)
+def test_datetimeindex(using_copy_on_write, cons):
+    dt = date_range("2019-12-31", periods=3, freq="D")
+    ser = Series(dt)
+    idx = cons(ser)
+    expected = idx.copy(deep=True)
+    ser.iloc[0] = Timestamp("2020-12-31")
+    if using_copy_on_write:
+        tm.assert_index_equal(idx, expected)
+
+
+def test_datetimeindex_tz_convert(using_copy_on_write):
+    dt = date_range("2019-12-31", periods=3, freq="D", tz="Europe/Berlin")
+    ser = Series(dt)
+    idx = DatetimeIndex(ser).tz_convert("US/Eastern")
+    expected = idx.copy(deep=True)
+    ser.iloc[0] = Timestamp("2020-12-31", tz="Europe/Berlin")
+    if using_copy_on_write:
+        tm.assert_index_equal(idx, expected)
+
+
+def test_datetimeindex_tz_localize(using_copy_on_write):
+    dt = date_range("2019-12-31", periods=3, freq="D")
+    ser = Series(dt)
+    idx = DatetimeIndex(ser).tz_localize("Europe/Berlin")
+    expected = idx.copy(deep=True)
+    ser.iloc[0] = Timestamp("2020-12-31")
+    if using_copy_on_write:
+        tm.assert_index_equal(idx, expected)
+
+
+def test_datetimeindex_isocalendar(using_copy_on_write):
+    dt = date_range("2019-12-31", periods=3, freq="D")
+    ser = Series(dt)
+    df = DatetimeIndex(ser).isocalendar()
+    expected = df.index.copy(deep=True)
+    ser.iloc[0] = Timestamp("2020-12-31")
+    if using_copy_on_write:
+        tm.assert_index_equal(df.index, expected)