Backport PR #48264 on branch 1.5.x (BUG: ArrowExtensionArray._from_* accepts pyarrow arrays) (#48422)

* Backport PR #48264: BUG: ArrowExtensionArray._from_* accepts pyarrow arrays

* Add missing import

Co-authored-by: Matthew Roeschke <[email protected]>

Author: meeseeksmachine

pandas/core/arrays/arrow/array.py

@@ -224,11 +224,13 @@ def _from_sequence(cls, scalars, *, dtype: Dtype | None = None, copy=False):
         Construct a new ExtensionArray from a sequence of scalars.
         """
         pa_dtype = to_pyarrow_type(dtype)
-        if isinstance(scalars, cls):
-            data = scalars._data
+        is_cls = isinstance(scalars, cls)
+        if is_cls or isinstance(scalars, (pa.Array, pa.ChunkedArray)):
+            if is_cls:
+                scalars = scalars._data
             if pa_dtype:
-                data = data.cast(pa_dtype)
-            return cls(data)
+                scalars = scalars.cast(pa_dtype)
+            return cls(scalars)
         else:
             return cls(
                 pa.chunked_array(pa.array(scalars, type=pa_dtype, from_pandas=True))
@@ -242,7 +244,10 @@ def _from_sequence_of_strings(
         Construct a new ExtensionArray from a sequence of strings.
         """
         pa_type = to_pyarrow_type(dtype)
-        if pa.types.is_timestamp(pa_type):
+        if pa_type is None:
+            # Let pyarrow try to infer or raise
+            scalars = strings
+        elif pa.types.is_timestamp(pa_type):
             from pandas.core.tools.datetimes import to_datetime
 
             scalars = to_datetime(strings, errors="raise")
@@ -272,8 +277,9 @@ def _from_sequence_of_strings(
 
             scalars = to_numeric(strings, errors="raise")
         else:
-            # Let pyarrow try to infer or raise
-            scalars = strings
+            raise NotImplementedError(
+                f"Converting strings to {pa_type} is not implemented."
+            )
         return cls._from_sequence(scalars, dtype=pa_type, copy=copy)
 
     def __getitem__(self, item: PositionalIndexer):

pandas/core/tools/times.py

@@ -80,17 +80,20 @@ def _convert_listlike(arg, format):
             format_found = False
             for element in arg:
                 time_object = None
-                for time_format in formats:
-                    try:
-                        time_object = datetime.strptime(element, time_format).time()
-                        if not format_found:
-                            # Put the found format in front
-                            fmt = formats.pop(formats.index(time_format))
-                            formats.insert(0, fmt)
-                            format_found = True
-                        break
-                    except (ValueError, TypeError):
-                        continue
+                try:
+                    time_object = time.fromisoformat(element)
+                except (ValueError, TypeError):
+                    for time_format in formats:
+                        try:
+                            time_object = datetime.strptime(element, time_format).time()
+                            if not format_found:
+                                # Put the found format in front
+                                fmt = formats.pop(formats.index(time_format))
+                                formats.insert(0, fmt)
+                                format_found = True
+                            break
+                        except (ValueError, TypeError):
+                            continue
 
                 if time_object is not None:
                     times.append(time_object)

pandas/tests/extension/test_arrow.py

@@ -21,10 +21,13 @@
 import pytest
 
 from pandas.compat import (
+    is_ci_environment,
+    is_platform_windows,
     pa_version_under2p0,
     pa_version_under3p0,
     pa_version_under4p0,
     pa_version_under6p0,
+    pa_version_under7p0,
     pa_version_under8p0,
     pa_version_under9p0,
 )
@@ -35,6 +38,8 @@
 
 pa = pytest.importorskip("pyarrow", minversion="1.0.1")
 
+from pandas.core.arrays.arrow.array import ArrowExtensionArray
+
 from pandas.core.arrays.arrow.dtype import ArrowDtype  # isort:skip
 
 
@@ -222,6 +227,96 @@ def test_from_dtype(self, data, request):
                 )
         super().test_from_dtype(data)
 
+    def test_from_sequence_pa_array(self, data, request):
+        # https://github.com/pandas-dev/pandas/pull/47034#discussion_r955500784
+        # data._data = pa.ChunkedArray
+        if pa_version_under3p0:
+            request.node.add_marker(
+                pytest.mark.xfail(
+                    reason="ChunkedArray has no attribute combine_chunks",
+                )
+            )
+        result = type(data)._from_sequence(data._data)
+        tm.assert_extension_array_equal(result, data)
+        assert isinstance(result._data, pa.ChunkedArray)
+
+        result = type(data)._from_sequence(data._data.combine_chunks())
+        tm.assert_extension_array_equal(result, data)
+        assert isinstance(result._data, pa.ChunkedArray)
+
+    def test_from_sequence_pa_array_notimplemented(self, request):
+        if pa_version_under6p0:
+            request.node.add_marker(
+                pytest.mark.xfail(
+                    raises=AttributeError,
+                    reason="month_day_nano_interval not implemented by pyarrow.",
+                )
+            )
+        with pytest.raises(NotImplementedError, match="Converting strings to"):
+            ArrowExtensionArray._from_sequence_of_strings(
+                ["12-1"], dtype=pa.month_day_nano_interval()
+            )
+
+    def test_from_sequence_of_strings_pa_array(self, data, request):
+        pa_dtype = data.dtype.pyarrow_dtype
+        if pa_version_under3p0:
+            request.node.add_marker(
+                pytest.mark.xfail(
+                    reason="ChunkedArray has no attribute combine_chunks",
+                )
+            )
+        elif pa.types.is_time64(pa_dtype) and pa_dtype.equals("time64[ns]"):
+            request.node.add_marker(
+                pytest.mark.xfail(
+                    reason="Nanosecond time parsing not supported.",
+                )
+            )
+        elif pa.types.is_duration(pa_dtype):
+            request.node.add_marker(
+                pytest.mark.xfail(
+                    raises=pa.ArrowNotImplementedError,
+                    reason=f"pyarrow doesn't support parsing {pa_dtype}",
+                )
+            )
+        elif pa.types.is_boolean(pa_dtype):
+            request.node.add_marker(
+                pytest.mark.xfail(
+                    reason="Iterating over ChunkedArray[bool] returns PyArrow scalars.",
+                )
+            )
+        elif pa.types.is_timestamp(pa_dtype) and pa_dtype.tz is not None:
+            if pa_version_under7p0:
+                request.node.add_marker(
+                    pytest.mark.xfail(
+                        raises=pa.ArrowNotImplementedError,
+                        reason=f"pyarrow doesn't support string cast from {pa_dtype}",
+                    )
+                )
+            elif is_platform_windows() and is_ci_environment():
+                request.node.add_marker(
+                    pytest.mark.xfail(
+                        raises=pa.ArrowInvalid,
+                        reason=(
+                            "TODO: Set ARROW_TIMEZONE_DATABASE environment variable "
+                            "on CI to path to the tzdata for pyarrow."
+                        ),
+                    )
+                )
+        elif pa_version_under6p0 and pa.types.is_temporal(pa_dtype):
+            request.node.add_marker(
+                pytest.mark.xfail(
+                    raises=pa.ArrowNotImplementedError,
+                    reason=f"pyarrow doesn't support string cast from {pa_dtype}",
+                )
+            )
+        pa_array = data._data.cast(pa.string())
+        result = type(data)._from_sequence_of_strings(pa_array, dtype=data.dtype)
+        tm.assert_extension_array_equal(result, data)
+
+        pa_array = pa_array.combine_chunks()
+        result = type(data)._from_sequence_of_strings(pa_array, dtype=data.dtype)
+        tm.assert_extension_array_equal(result, data)
+
 
 @pytest.mark.xfail(
     raises=NotImplementedError, reason="pyarrow.ChunkedArray backing is 1D."

pandas/tests/tools/test_to_time.py

@@ -4,6 +4,8 @@
 import numpy as np
 import pytest
 
+from pandas.compat import PY311
+
 from pandas import Series
 import pandas._testing as tm
 from pandas.core.tools.datetimes import to_time as to_time_alias
@@ -40,8 +42,9 @@ def test_parsers_time(self, time_string):
     def test_odd_format(self):
         new_string = "14.15"
         msg = r"Cannot convert arg \['14\.15'\] to a time"
-        with pytest.raises(ValueError, match=msg):
-            to_time(new_string)
+        if not PY311:
+            with pytest.raises(ValueError, match=msg):
+                to_time(new_string)
         assert to_time(new_string, format="%H.%M") == time(14, 15)
 
     def test_arraylike(self):