REF: use check_setitem_lengths in DTA.__setitem__

pandas/core/arrays/datetimelike.py

@@ -1,6 +1,6 @@
 from datetime import datetime, timedelta
 import operator
-from typing import Any, Callable, Optional, Sequence, Tuple, Type, TypeVar, Union, cast
+from typing import Any, Callable, Optional, Sequence, Tuple, Type, TypeVar, Union
 import warnings
 
 import numpy as np
@@ -58,7 +58,7 @@
 from pandas.core.arrays.base import ExtensionOpsMixin
 import pandas.core.common as com
 from pandas.core.construction import array, extract_array
-from pandas.core.indexers import check_array_indexer
+from pandas.core.indexers import check_array_indexer, check_setitem_lengths
 from pandas.core.ops.common import unpack_zerodim_and_defer
 from pandas.core.ops.invalid import invalid_comparison, make_invalid_op
 
@@ -605,23 +605,9 @@ def __setitem__(
         # to a period in from_sequence). For DatetimeArray, it's Timestamp...
         # I don't know if mypy can do that, possibly with Generics.
         # https://mypy.readthedocs.io/en/latest/generics.html
-        if is_list_like(value):
-            is_slice = isinstance(key, slice)
-
-            if lib.is_scalar(key):
-                raise ValueError("setting an array element with a sequence.")
-
-            if not is_slice:
-                key = cast(Sequence, key)
-                if len(key) != len(value) and not com.is_bool_indexer(key):
-                    msg = (
-                        f"shape mismatch: value array of length '{len(key)}' "
-                        "does not match indexing result of length "
-                        f"'{len(value)}'."
-                    )
-                    raise ValueError(msg)
-                elif not len(key):
-                    return
+        no_op = check_setitem_lengths(key, value, self)
+        if no_op:
+            return
 
         value = self._validate_setitem_value(value)
         key = check_array_indexer(self, key)

pandas/core/indexers.py

@@ -114,7 +114,7 @@ def is_empty_indexer(indexer, arr_value: np.ndarray) -> bool:
 # Indexer Validation
 
 
-def check_setitem_lengths(indexer, value, values) -> None:
+def check_setitem_lengths(indexer, value, values) -> bool:
     """
     Validate that value and indexer are the same length.
 
@@ -133,34 +133,46 @@ def check_setitem_lengths(indexer, value, values) -> None:
 
     Returns
     -------
-    None
+    bool
+        Whether this is an empty listlike setting which is a no-op.
 
     Raises
     ------
     ValueError
         When the indexer is an ndarray or list and the lengths don't match.
     """
-    # boolean with truth values == len of the value is ok too
+    no_op = False
+
     if isinstance(indexer, (np.ndarray, list)):
-        if is_list_like(value) and len(indexer) != len(value):
-            if not (
-                isinstance(indexer, np.ndarray)
-                and indexer.dtype == np.bool_
-                and len(indexer[indexer]) == len(value)
-            ):
-                raise ValueError(
-                    "cannot set using a list-like indexer "
-                    "with a different length than the value"
-                )
+        # We can ignore other listlikes becasue they are either
+        #  a) not necessarily 1-D indexers, e.g. tuple
+        #  b) boolean indexers e.g. BoolArray
+        if is_list_like(value):
+            if len(indexer) != len(value):
+                # boolean with truth values == len of the value is ok too
+                if not (
+                    isinstance(indexer, np.ndarray)
+                    and indexer.dtype == np.bool_
+                    and len(indexer[indexer]) == len(value)
+                ):
+                    raise ValueError(
+                        "cannot set using a list-like indexer "
+                        "with a different length than the value"
+                    )
+            if len(indexer) == 0:
+                no_op = True
 
     elif isinstance(indexer, slice):
-        # slice
-        if is_list_like(value) and len(values):
+        if is_list_like(value):
             if len(value) != length_of_indexer(indexer, values):
                 raise ValueError(
                     "cannot set using a slice indexer with a "
                     "different length than the value"
                 )
+            if len(value) == 0:
+                no_op = True
+
+    return no_op
 
 
 def validate_indices(indices: np.ndarray, n: int) -> None: