Update for arrow

pandas/core/arrays/interval.py

@@ -80,6 +80,7 @@
     unique,
     value_counts_internal as value_counts,
 )
+from pandas.core.arrays import ArrowExtensionArray
 from pandas.core.arrays.base import (
     ExtensionArray,
     _extension_array_shared_docs,
@@ -369,13 +370,18 @@ def _ensure_simple_new_inputs(
         right = ensure_wrapped_if_datetimelike(right)
         right = extract_array(right, extract_numpy=True)
 
-        lbase = getattr(left, "_ndarray", left)
-        lbase = getattr(lbase, "_data", lbase).base
-        rbase = getattr(right, "_ndarray", right)
-        rbase = getattr(rbase, "_data", rbase).base
-        if lbase is not None and lbase is rbase:
-            # If these share data, then setitem could corrupt our IA
-            right = right.copy()
+        if isinstance(left, ArrowExtensionArray) or isinstance(
+            right, ArrowExtensionArray
+        ):
+            pass
+        else:
+            lbase = getattr(left, "_ndarray", left)
+            lbase = getattr(lbase, "_data", lbase).base
+            rbase = getattr(right, "_ndarray", right)
+            rbase = getattr(rbase, "_data", rbase).base
+            if lbase is not None and lbase is rbase:
+                # If these share data, then setitem could corrupt our IA
+                right = right.copy()
 
         dtype = IntervalDtype(left.dtype, closed=closed)
 

pandas/tests/indexes/interval/test_constructors.py

@@ -3,6 +3,8 @@
 import numpy as np
 import pytest
 
+import pandas.util._test_decorators as td
+
 from pandas.core.dtypes.common import is_unsigned_integer_dtype
 from pandas.core.dtypes.dtypes import IntervalDtype
 
@@ -510,10 +512,14 @@ def test_dtype_closed_mismatch():
         IntervalArray([], dtype=dtype, closed="neither")
 
 
-def test_masked_dtype():
+@pytest.mark.parametrize(
+    "dtype",
+    ["Float64", pytest.param("float64[pyarrow]", marks=td.skip_if_no("pyarrow"))],
+)
+def test_ea_dtype(dtype):
     # GH#56765
     bins = [(0.0, 0.4), (0.4, 0.6)]
-    interval_dtype = IntervalDtype(subtype="Float64", closed="left")
+    interval_dtype = IntervalDtype(subtype=dtype, closed="left")
     result = IntervalIndex.from_tuples(bins, closed="left", dtype=interval_dtype)
     assert result.dtype == interval_dtype
     expected = IntervalIndex.from_tuples(bins, closed="left").astype(interval_dtype)