BUG: inference with Interval subclass

doc/source/whatsnew/v3.0.0.rst

@@ -1016,8 +1016,8 @@ Strings
 Interval
 ^^^^^^^^
 - :meth:`Index.is_monotonic_decreasing`, :meth:`Index.is_monotonic_increasing`, and :meth:`Index.is_unique` could incorrectly be ``False`` for an ``Index`` created from a slice of another ``Index``. (:issue:`57911`)
+- Bug in :class:`Index`, :class:`Series`, :class:`DataFrame` constructors when given a sequence of :class:`Interval` subclass objects casting them to :class:`Interval` (:issue:`46945`)
 - Bug in :func:`interval_range` where start and end numeric types were always cast to 64 bit (:issue:`57268`)
--
 
 Indexing
 ^^^^^^^^

pandas/_libs/lib.pyx

@@ -2255,7 +2255,8 @@ cpdef bint is_interval_array(ndarray values):
     for i in range(n):
         val = values[i]
 
-        if isinstance(val, Interval):
+        if type(val) is Interval:
+            # GH#46945 catch Interval exactly, excluding subclasses
             if closed is None:
                 closed = val.closed
                 numeric = (

pandas/tests/dtypes/test_inference.py

@@ -1605,6 +1605,24 @@ def test_is_string_array(self):
         )
         assert not lib.is_string_array(np.array([1, 2]))
 
+    def test_is_interval_array_subclass(self):
+        # GH#46945
+
+        class TimestampsInterval(Interval):
+            def __init__(self, left: str, right: str, closed: str = "both") -> None:
+                super().__init__(Timestamp(left), Timestamp(right), closed)
+
+            @property
+            def seconds(self) -> float:
+                return self.length.seconds
+
+        item = TimestampsInterval("1970-01-01 00:00:00", "1970-01-01 00:00:01")
+        arr = np.array([item], dtype=object)
+        assert not lib.is_interval_array(arr)
+        assert lib.infer_dtype(arr) != "interval"
+        out = Series([item])[0]
+        assert isinstance(out, TimestampsInterval)
+
     @pytest.mark.parametrize(
         "func",
         [