DEPR: Enforce deprecation of ArrayManager

asv_bench/benchmarks/frame_methods.py

@@ -593,8 +593,6 @@ def setup(self):
         N = 10000
         # this is the worst case, where every column has NaNs.
         arr = np.random.randn(N, 100)
-        # NB: we need to set values in array, not in df.values, otherwise
-        #  the benchmark will be misleading for ArrayManager
         arr[::2] = np.nan
 
         self.df = DataFrame(arr)

doc/source/whatsnew/v3.0.0.rst

@@ -96,6 +96,13 @@ Deprecations
 - Deprecated :meth:`Timestamp.utcnow`, use ``Timestamp.now("UTC")`` instead (:issue:`56680`)
 -
 
+.. ---------------------------------------------------------------------------
+.. _whatsnew_300.prior_deprecations:
+Removal of prior version deprecations/changes
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+- Removed the :class:`ArrayManager` (:issue:`55043`)
+-
+
 .. ---------------------------------------------------------------------------
 .. _whatsnew_300.performance:
 

pandas/__init__.py

@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-import os
 import warnings
 
 __docformat__ = "restructuredtext"
@@ -193,16 +192,6 @@
     __git_version__ = v.get("full-revisionid")
     del get_versions, v
 
-# GH#55043 - deprecation of the data_manager option
-if "PANDAS_DATA_MANAGER" in os.environ:
-    warnings.warn(
-        "The env variable PANDAS_DATA_MANAGER is set. The data_manager option is "
-        "deprecated and will be removed in a future version. Only the BlockManager "
-        "will be available. Unset this environment variable to silence this warning.",
-        FutureWarning,
-        stacklevel=2,
-    )
-
 # DeprecationWarning for missing pyarrow
 from pandas.compat.pyarrow import pa_version_under10p1, pa_not_found
 
@@ -232,7 +221,7 @@
     del VERSIONS, pa_msg
 
 # Delete all unnecessary imported modules
-del pa_version_under10p1, pa_not_found, warnings, os
+del pa_version_under10p1, pa_not_found, warnings
 
 # module level doc-string
 __doc__ = """

pandas/_config/__init__.py

@@ -33,10 +33,7 @@
 
 def using_copy_on_write() -> bool:
     _mode_options = _global_config["mode"]
-    return (
-        _mode_options["copy_on_write"] is True
-        and _mode_options["data_manager"] == "block"
-    )
+    return _mode_options["copy_on_write"] is True
 
 
 def warn_copy_on_write() -> bool:

pandas/_typing.py

@@ -61,9 +61,7 @@
     )
     from pandas.core.indexes.base import Index
     from pandas.core.internals import (
-        ArrayManager,
         BlockManager,
-        SingleArrayManager,
         SingleBlockManager,
     )
     from pandas.core.resample import Resampler
@@ -382,11 +380,7 @@ def closed(self) -> bool:
 ]
 
 # internals
-Manager = Union[
-    "ArrayManager", "SingleArrayManager", "BlockManager", "SingleBlockManager"
-]
-SingleManager = Union["SingleArrayManager", "SingleBlockManager"]
-Manager2D = Union["ArrayManager", "BlockManager"]
+Manager = Union["BlockManager", "SingleBlockManager"]
 
 # indexing
 # PositionalIndexer -> valid 1D positional indexer, e.g. can pass

pandas/core/apply.py

@@ -1256,7 +1256,7 @@ def series_generator(self) -> Generator[Series, None, None]:
         ser = self.obj._ixs(0, axis=0)
         mgr = ser._mgr
 
-        is_view = mgr.blocks[0].refs.has_reference()  # type: ignore[union-attr]
+        is_view = mgr.blocks[0].refs.has_reference()
 
         if isinstance(ser.dtype, ExtensionDtype):
             # values will be incorrect for this block
@@ -1278,7 +1278,7 @@ def series_generator(self) -> Generator[Series, None, None]:
                     # -> if that happened and `ser` is already a copy, then we reset
                     # the refs here to avoid triggering a unnecessary CoW inside the
                     # applied function (https://github.com/pandas-dev/pandas/pull/56212)
-                    mgr.blocks[0].refs = BlockValuesRefs(mgr.blocks[0])  # type: ignore[union-attr]
+                    mgr.blocks[0].refs = BlockValuesRefs(mgr.blocks[0])
                 yield ser
 
     @staticmethod

pandas/core/arraylike.py

@@ -263,10 +263,7 @@ def array_ufunc(self, ufunc: np.ufunc, method: str, *inputs: Any, **kwargs: Any)
         Series,
     )
     from pandas.core.generic import NDFrame
-    from pandas.core.internals import (
-        ArrayManager,
-        BlockManager,
-    )
+    from pandas.core.internals import BlockManager
 
     cls = type(self)
 
@@ -350,7 +347,7 @@ def _reconstruct(result):
             if method == "outer":
                 raise NotImplementedError
             return result
-        if isinstance(result, (BlockManager, ArrayManager)):
+        if isinstance(result, BlockManager):
             # we went through BlockManager.apply e.g. np.sqrt
             result = self._constructor_from_mgr(result, axes=result.axes)
         else:

pandas/core/config_init.py

@@ -436,32 +436,6 @@ def use_inf_as_na_cb(key) -> None:
     "version. Convert inf values to NaN before operating instead.",
 )
 
-data_manager_doc = """
-: string
-    Internal data manager type; can be "block" or "array". Defaults to "block",
-    unless overridden by the 'PANDAS_DATA_MANAGER' environment variable (needs
-    to be set before pandas is imported).
-"""
-
-
-with cf.config_prefix("mode"):
-    cf.register_option(
-        "data_manager",
-        # Get the default from an environment variable, if set, otherwise defaults
-        # to "block". This environment variable can be set for testing.
-        os.environ.get("PANDAS_DATA_MANAGER", "block"),
-        data_manager_doc,
-        validator=is_one_of_factory(["block", "array"]),
-    )
-
-cf.deprecate_option(
-    # GH#55043
-    "mode.data_manager",
-    "data_manager option is deprecated and will be removed in a future "
-    "version. Only the BlockManager will be available.",
-)
-
-
 # TODO better name?
 copy_on_write_doc = """
 : bool