BUG: Fix bug in putmask for CoW (pandas-dev#50630)

Author: phofl

doc/source/whatsnew/v1.5.3.rst

@@ -27,6 +27,7 @@ Fixed regressions
 
 Bug fixes
 ~~~~~~~~~
+- Bug in the Copy-on-Write implementation losing track of views when indexing a :class:`DataFrame` with another :class:`DataFrame` (:issue:`50630`)
 - Bug in :meth:`.Styler.to_excel` leading to error when unrecognized ``border-style`` (e.g. ``"hair"``) provided to Excel writers (:issue:`48649`)
 - Bug in :meth:`Series.quantile` emitting warning from NumPy when :class:`Series` has only ``NA`` values (:issue:`50681`)
 - Bug when chaining several :meth:`.Styler.concat` calls, only the last styler was concatenated (:issue:`49207`)

pandas/core/internals/managers.py

@@ -384,10 +384,8 @@ def setitem(self: T, indexer, value) -> T:
         return self.apply("setitem", indexer=indexer, value=value)
 
     def putmask(self, mask, new, align: bool = True):
-        if (
-            using_copy_on_write()
-            and self.refs is not None
-            and not all(ref is None for ref in self.refs)
+        if using_copy_on_write() and any(
+            not self._has_no_reference_block(i) for i in range(len(self.blocks))
         ):
             # some reference -> copy full dataframe
             # TODO(CoW) this could be optimized to only copy the blocks that would

pandas/tests/copy_view/test_methods.py

@@ -851,6 +851,21 @@ def test_squeeze(using_copy_on_write):
         assert df.loc[0, "a"] == 0
 
 
+def test_putmask(using_copy_on_write):
+    df = DataFrame({"a": [1, 2], "b": 1, "c": 2})
+    view = df[:]
+    df_orig = df.copy()
+    df[df == df] = 5
+
+    if using_copy_on_write:
+        assert not np.shares_memory(get_array(view, "a"), get_array(df, "a"))
+        tm.assert_frame_equal(view, df_orig)
+    else:
+        # Without CoW the original will be modified
+        assert np.shares_memory(get_array(view, "a"), get_array(df, "a"))
+        assert view.iloc[0, 0] == 5
+
+
 def test_isetitem(using_copy_on_write):
     df = DataFrame({"a": [1, 2, 3], "b": [4, 5, 6], "c": [7, 8, 9]})
     df_orig = df.copy()