BUG: Handle readonly arrays in period_array

Closes pandas-dev#25403

Author: TomAugspurger

doc/source/whatsnew/v0.24.2.rst

@@ -30,6 +30,7 @@ Fixed Regressions
 - Fixed regression in subtraction between :class:`Series` objects with ``datetime64[ns]`` dtype incorrectly raising ``OverflowError`` when the `Series` on the right contains null values (:issue:`25317`)
 - Fixed regression in :class:`TimedeltaIndex` where `np.sum(index)` incorrectly returned a zero-dimensional object instead of a scalar (:issue:`25282`)
 - Fixed regression in ``IntervalDtype`` construction where passing an incorrect string with 'Interval' as a prefix could result in a ``RecursionError``. (:issue:`25338`)
+- Fixed regression in creating a period-dtype array from a read-only NumPy array of period objects. (:issue:`25403`)
 
 - Fixed regression in :class:`Categorical`, where constructing it from a categorical ``Series`` and an explicit ``categories=`` that differed from that in the ``Series`` created an invalid object which could trigger segfaults. (:issue:`25318`)
 

pandas/core/arrays/period.py

@@ -196,8 +196,14 @@ def _from_sequence(cls, scalars, dtype=None, copy=False):
         if copy:
             periods = periods.copy()
 
+        # Support readonly `scalars`.
+        # TODO: remove flag unsetting / setting once Cython supports
+        # const object.
+        writeable = periods.flags.writeable
+        periods.setflags(write=True)
         freq = freq or libperiod.extract_freq(periods)
         ordinals = libperiod.extract_ordinals(periods, freq)
+        periods.setflags(write=writeable)
         return cls(ordinals, freq=freq)
 
     @classmethod

pandas/tests/arrays/test_period.py

@@ -41,6 +41,22 @@ def test_period_array_ok(data, freq, expected):
     tm.assert_numpy_array_equal(result, expected)
 
 
+def test_period_array_readonly_object():
+    # https://github.com/pandas-dev/pandas/issues/25403
+    pa = period_array([pd.Period('2019-01-01')])
+    arr = np.asarray(pa, dtype='object')
+    arr.setflags(write=False)
+
+    result = period_array(arr)
+    tm.assert_period_array_equal(result, pa)
+
+    result = pd.Series(arr)
+    tm.assert_series_equal(result, pd.Series(pa))
+
+    result = pd.DataFrame({"A": arr})
+    tm.assert_frame_equal(result, pd.DataFrame({"A": pa}))
+
+
 def test_from_datetime64_freq_changes():
     # https://github.com/pandas-dev/pandas/issues/23438
     arr = pd.date_range("2017", periods=3, freq="D")