TST: Series repr with pyarrow date32 type

doc/source/reference/arrays.rst

@@ -53,6 +53,10 @@ PyArrow
 
     This feature is experimental, and the API can change in a future release without warning.
 
+The ``dtype`` argument of :class:`Series` and :class:`DataFrame` can accept a string of a `pyarrow data type <https://arrow.apache.org/docs/python/api/datatypes.html>`__
+with ``pyarrow`` in brackets e.g. ``"int64[pyarrow]"`` or, for pyarrow data types that take parameters, a :class:`ArrowDtype`
+initialized with a ``pyarrow.DataType``.
+
 The :class:`arrays.ArrowExtensionArray` is backed by a :external+pyarrow:py:class:`pyarrow.ChunkedArray` with a
 :external+pyarrow:py:class:`pyarrow.DataType` instead of a NumPy array and data type. The ``.dtype`` of a :class:`arrays.ArrowExtensionArray`
 is an :class:`ArrowDtype`.

doc/source/whatsnew/v1.5.0.rst

@@ -54,6 +54,8 @@ initialized with a ``pyarrow.DataType``.
 Most operations are supported and have been implemented using `pyarrow compute <https://arrow.apache.org/docs/python/api/compute.html>`__ functions.
 We recommend installing the latest version of PyArrow to access the most recently implemented compute functions.
 
+Please view the :ref:`API reference <api.arrays.arrow>` for more information.
+
 .. warning::
 
     This feature is experimental, and the API can change in a future release without warning.
@@ -1034,7 +1036,6 @@ Conversion
 - Bug in :meth:`DataFrame.apply` that returns a :class:`DataFrame` instead of a :class:`Series` when applied to an empty :class:`DataFrame` and ``axis=1`` (:issue:`39111`)
 - Bug when inferring the dtype from an iterable that is *not* a NumPy ``ndarray`` consisting of all NumPy unsigned integer scalars did not result in an unsigned integer dtype (:issue:`47294`)
 - Bug in :meth:`DataFrame.eval` when pandas objects (e.g. ``'Timestamp'``) were column names (:issue:`44603`)
--
 
 Strings
 ^^^^^^^

pandas/_testing/__init__.py

@@ -215,7 +215,7 @@
         for unit in ["s", "ms", "us", "ns"]
         for tz in [None, "UTC", "US/Pacific", "US/Eastern"]
     ]
-    TIMEDELTA_PYARROW_DTYPES = [pa.duration(unit) for unit in ["s", "ms", "us", "ns"]]
+    # TIMEDELTA_PYARROW_DTYPES = [pa.duration(unit) for unit in ["s", "ms", "us", "ns"]]
 
     BOOL_PYARROW_DTYPES = [pa.bool_()]
 
@@ -227,7 +227,7 @@
         + TIME_PYARROW_DTYPES
         + DATE_PYARROW_DTYPES
         + DATETIME_PYARROW_DTYPES
-        + TIMEDELTA_PYARROW_DTYPES
+        # + TIMEDELTA_PYARROW_DTYPES
         + BOOL_PYARROW_DTYPES
     )
 

pandas/core/arrays/arrow/array.py

@@ -199,6 +199,13 @@ class ArrowExtensionArray(OpsMixin, ExtensionArray):
     <ArrowExtensionArray>
     [1, 1, <NA>]
     Length: 3, dtype: int64[pyarrow]
+
+    Create a ArrowExtensionArray directly from an pyarrow array.
+    >>> import pyarrow as pa
+    >>> pd.arrays.ArrowExtensionArray(pa.array([1, 1, None]))
+    <ArrowExtensionArray>
+    [1, 1, <NA>]
+    Length: 3, dtype: int64[pyarrow]
     """  # noqa: E501 (http link too long)
 
     _data: pa.ChunkedArray

pandas/tests/extension/test_arrow.py

@@ -1750,3 +1750,10 @@ def test_mode(data_for_grouping, dropna, take_idx, exp_idx, request):
     result = ser.mode(dropna=dropna)
     expected = pd.Series(data_for_grouping.take(exp_idx))
     tm.assert_series_equal(result, expected)
+
+
+def test_repr_from_arrow_array(data, frame_or_series):
+    # GH 48238
+    pa_array = pa.array([data[0], None])
+    result = frame_or_series(pa_array, dtype=ArrowDtype(pa_array.type))
+    repr(result)