POC: infer time objects to ArrowDtype[time]

Author: jbrockmendel

pandas/_libs/lib.pyx

@@ -2644,7 +2644,6 @@ def maybe_convert_objects(ndarray[object] objects,
 
     elif seen.time_:
         if is_time_array(objects):
-            # FIXME: need to ensure this is not timetz
             opt = get_option("future.infer_time")
             if opt is True:
                 import pyarrow as pa

pandas/tests/io/test_sql.py

@@ -2960,16 +2960,15 @@ def test_datetime_date(self):
     def test_datetime_time(self, tz_aware):
         # test support for datetime.time, GH #8341
 
+        warn_msg = "Pandas type inference with a sequence of `datetime.time`"
         if not tz_aware:
             tz_times = [time(9, 0, 0), time(9, 1, 30)]
+            warn = FutureWarning
         else:
             tz_dt = date_range("2013-01-01 09:00:00", periods=2, tz="US/Pacific")
             tz_times = Series(tz_dt.to_pydatetime()).map(lambda dt: dt.timetz())
+            warn = None
 
-        warn_msg = "Pandas type inference with a sequence of `datetime.time`"
-        warn = None
-        if not tz_aware:
-            warn = FutureWarning
         with tm.assert_produces_warning(warn, match=warn_msg):
             df = DataFrame(tz_times, columns=["a"])
 

pandas/tests/series/accessors/test_dt_accessor.py

@@ -101,6 +101,7 @@ def get_expected(ser, prop):
             left = getattr(ser.dt, name)
             right = get_expected(ser, name)
 
+
         if not (is_list_like(left) and is_list_like(right)):
             assert left == right
         elif isinstance(left, DataFrame):