add handling for special case where np datetime contained in Python list gets converted to integer

Author: emilykl

_plotly_utils/basevalidators.py

@@ -22,6 +22,21 @@ def fullmatch(regex, string, flags=0):
     return re.match("(?:" + regex_string + r")\Z", string, flags=flags)
 
 
+def to_non_numpy_type(np, v):
+    """
+    Convert a numpy scalar value to a native Python type.
+    Calling .item() on a datetime64[ns] value returns an integer, since
+    Python datetimes only support microsecond precision. So we cast
+    datetime64[ns] to datetime64[us] to ensure it remains a datetime.
+
+    Should only be used in contexts where we already know `np` is defined
+    """
+    if hasattr(v, "dtype") and v.dtype == np.dtype("datetime64[ns]"):
+        return v.astype("datetime64[us]").item()
+    else:
+        return v.item()
+
+
 # Utility functions
 # -----------------
 def to_scalar_or_list(v):
@@ -35,12 +50,12 @@ def to_scalar_or_list(v):
     np = get_module("numpy", should_load=False)
     pd = get_module("pandas", should_load=False)
     if np and np.isscalar(v) and hasattr(v, "item"):
-        return v.item()
+        return to_non_numpy_type(np, v)
     if isinstance(v, (list, tuple)):
         return [to_scalar_or_list(e) for e in v]
     elif np and isinstance(v, np.ndarray):
         if v.ndim == 0:
-            return v.item()
+            return to_non_numpy_type(np, v)
         return [to_scalar_or_list(e) for e in v]
     elif pd and isinstance(v, (pd.Series, pd.Index)):
         return [to_scalar_or_list(e) for e in v]