use np.fromiter and update annotation

Author: jorisvandenbossche

pandas/core/dtypes/cast.py

@@ -87,7 +87,7 @@
 
 if TYPE_CHECKING:
     from collections.abc import (
-        Iterable,
+        Collection,
         Sequence,
     )
 
@@ -1581,7 +1581,7 @@ def _maybe_box_and_unbox_datetimelike(value: Scalar, dtype: DtypeObj):
     return _maybe_unbox_datetimelike(value, dtype)
 
 
-def construct_1d_object_array_from_listlike(values: Iterable) -> np.ndarray:
+def construct_1d_object_array_from_listlike(values: Collection) -> np.ndarray:
     """
     Transform any list-like object in a 1-dimensional numpy array of object
     dtype.
@@ -1599,12 +1599,9 @@ def construct_1d_object_array_from_listlike(values: Iterable) -> np.ndarray:
     -------
     1-dimensional numpy array of dtype object
     """
-    # numpy will try to interpret nested lists as further dimensions, hence
-    # making a 1D array that contains list-likes is a bit tricky:
-    result = np.empty(len(values), dtype="object")
-    for i, obj in enumerate(values):
-        result[i] = obj
-    return result
+    # numpy will try to interpret nested lists as further dimensions in np.array(),
+    # hence explicitly making a 1D array using np.fromiter
+    return np.fromiter(values, dtype="object", count=len(values))
 
 
 def maybe_cast_to_integer_array(arr: list | np.ndarray, dtype: np.dtype) -> np.ndarray: