undo changes related to datetimelike input validation

Author: jorisvandenbossche

pandas/core/arrays/datetimelike.py

@@ -130,9 +130,9 @@
 from pandas.core.arrays.integer import IntegerArray
 import pandas.core.common as com
 from pandas.core.construction import (
+    array as pd_array,
     ensure_wrapped_if_datetimelike,
     extract_array,
-    sanitize_array,
 )
 from pandas.core.indexers import (
     check_array_indexer,
@@ -667,10 +667,12 @@ def _validate_listlike(self, value, allow_object: bool = False):
                     msg = self._validation_error_message(value, True)
                     raise TypeError(msg) from err
 
-        # Do type inference if necessary up front
+        # Do type inference if necessary up front (after unpacking
+        # NumpyExtensionArray)
         # e.g. we passed PeriodIndex.values and got an ndarray of Periods
-        value = sanitize_array(value, index=None, allow_2d=True)
-        value = ensure_wrapped_if_datetimelike(value)
+        value = extract_array(value, extract_numpy=True)
+        value = pd_array(value)
+        value = extract_array(value, extract_numpy=True)
 
         if is_all_strings(value):
             # We got a StringArray

pandas/core/construction.py

@@ -37,6 +37,7 @@
 from pandas.core.dtypes.common import (
     ensure_object,
     is_list_like,
+    is_object_dtype,
     pandas_dtype,
 )
 from pandas.core.dtypes.dtypes import NumpyEADtype
@@ -48,6 +49,8 @@
 )
 from pandas.core.dtypes.missing import isna
 
+import pandas.core.common as com
+
 if TYPE_CHECKING:
     from collections.abc import Sequence
 
@@ -703,12 +706,23 @@ def _sanitize_ndim(
         result = _maybe_repeat(result, index)
 
     elif result.ndim > 1:
-        if allow_2d:
-            return result
-        raise ValueError(
-            f"Data must be 1-dimensional, got ndarray of shape {data.shape} instead"
-        )
+        if isinstance(data, np.ndarray):
+            if allow_2d:
+                return result
+            raise ValueError(
+                f"Data must be 1-dimensional, got ndarray of shape {data.shape} instead"
+            )
+        if is_object_dtype(dtype) and isinstance(dtype, ExtensionDtype):
+            # i.e. NumpyEADtype("O")
 
+            result = com.asarray_tuplesafe(data, dtype=np.dtype("object"))
+            cls = dtype.construct_array_type()
+            result = cls._from_sequence(result, dtype=dtype)
+        else:
+            # error: Argument "dtype" to "asarray_tuplesafe" has incompatible type
+            # "Union[dtype[Any], ExtensionDtype, None]"; expected "Union[str,
+            # dtype[Any], None]"
+            result = com.asarray_tuplesafe(data, dtype=dtype)  # type: ignore[arg-type]
     return result
 
 

pandas/tests/arrays/test_datetimelike.py

@@ -297,9 +297,7 @@ def test_searchsorted(self):
         assert result == 10
 
     @pytest.mark.parametrize("box", [None, "index", "series"])
-    def test_searchsorted_castable_strings(
-        self, arr1d, box, string_storage, using_infer_string
-    ):
+    def test_searchsorted_castable_strings(self, arr1d, box, string_storage):
         arr = arr1d
         if box is None:
             pass
@@ -335,8 +333,7 @@ def test_searchsorted_castable_strings(
                 TypeError,
                 match=re.escape(
                     f"value should be a '{arr1d._scalar_type.__name__}', 'NaT', "
-                    "or array of those. Got "
-                    f"{'str' if using_infer_string else 'object'} array instead."
+                    "or array of those. Got string array instead."
                 ),
             ):
                 arr.searchsorted([str(arr[1]), "baz"])