bug(table) - Fix mixed-type table conversion to numpy

Author: protocolstardust

docs/docs/content/CHANGELOG.md

@@ -16,6 +16,10 @@ All notable changes to Rayforce-Py will be documented in this file.
     - **Slicing**: `table[1:3]`, `table[:5]`, `table[-2:]` — row slicing backed by the C-level `TAKE` operation.
     - **Index list**: `table[[0, 2, 5]]` — select specific rows by position.
 
+### Bug Fixes
+
+- **`Table.to_numpy()` with Timestamp columns**: Fixed `DTypePromotionError` when calling `to_numpy()` on tables containing a mix of incompatible column types (e.g., integers, strings, and timestamps). Mixed-type tables now gracefully fall back to `object` dtype.
+
 2026-02-23 | **[🔗 PyPI](https://pypi.org/project/rayforce-py/0.6.1/)** | **[🔗 GitHub](https://github.com/RayforceDB/rayforce-py/releases/tag/0.6.1)**
 
 

rayforce/types/table.py

@@ -578,7 +578,18 @@ def to_dict(self) -> dict[str, list]:
     @DestructiveOperationHandler()
     def to_numpy(self) -> t.Any:
         vals = self.values()
-        return np.column_stack([vals[i].to_numpy() for i in range(len(vals))])
+        arrays = [vals[i].to_numpy() for i in range(len(vals))]
+        try:
+            return np.column_stack(arrays)
+        except (np.exceptions.DTypePromotionError, TypeError):
+            return np.column_stack(
+                [
+                    a.astype("datetime64[ms]").astype(object)
+                    if a.dtype.kind == "M"
+                    else a.astype(object)
+                    for a in arrays
+                ]
+            )
 
 
 class TableReprMixin:

tests/types/table/test_misc.py

@@ -1257,6 +1257,56 @@ def test_mixed_types_coerced(self):
         assert arr[0, 0] == "alice"
         assert arr[0, 1] == "25"
 
+    def test_with_timestamp_column(self):
+        from datetime import datetime
+
+        table = Table.from_dict(
+            {
+                "id": Vector([1, 2, 3], ray_type=I64),
+                "name": Vector(["Alice", "Bob", "Carol"], ray_type=Symbol),
+            }
+        )
+        birthdays = Vector(
+            [datetime(2001, 1, 1), datetime(2002, 2, 2), datetime(2003, 3, 3)],
+            ray_type=Timestamp,
+        )
+        table = table.select("*", birthday=birthdays).execute()
+        arr = table.to_numpy()
+        assert arr.shape == (3, 3)
+        assert arr.dtype == object
+        assert arr[0, 2] == datetime(2001, 1, 1)
+        assert arr[2, 2] == datetime(2003, 3, 3)
+        assert isinstance(arr[0, 2], datetime)
+
+    def test_with_all_temporal_columns(self):
+        from datetime import date, datetime, time, timedelta
+
+        table = Table.from_dict(
+            {
+                "id": Vector([1, 2], ray_type=I64),
+                "dt": Vector([date(2001, 1, 1), date(2002, 2, 2)], ray_type=Date),
+                "tm": Vector([time(9, 0), time(10, 30)], ray_type=Time),
+                "ts": Vector(
+                    [datetime(2001, 1, 1, 9, 0), datetime(2002, 2, 2, 10, 30)],
+                    ray_type=Timestamp,
+                ),
+            }
+        )
+        arr = table.to_numpy()
+        assert arr.shape == (2, 4)
+        assert arr.dtype == object
+
+        # Date → datetime (datetime64[D].astype(object) produces datetime)
+        assert arr[0, 1] == datetime(2001, 1, 1)
+
+        # Time → timedelta
+        assert isinstance(arr[0, 2], timedelta)
+        assert arr[0, 2] == timedelta(hours=9)
+
+        # Timestamp → datetime
+        assert isinstance(arr[0, 3], datetime)
+        assert arr[0, 3] == datetime(2001, 1, 1, 9, 0)
+
     def test_all_same_int_type(self):
         table = Table(
             {