Change default datetime index resolution to ns to match pandas (this …

…is a breaking change).

python/cudf/cudf/core/index.py

@@ -2123,6 +2123,15 @@ def __init__(
         if yearfirst is not False:
             raise NotImplementedError("yearfirst == True is not yet supported")
 
+        valid_dtypes = tuple(
+            f"datetime64[{res}]" for res in ("s", "ms", "us", "ns")
+        )
+        if dtype is None:
+            # nanosecond default matches pandas
+            dtype = "datetime64[ns]"
+        elif dtype not in valid_dtypes:
+            raise TypeError("Invalid dtype")
+
         if copy:
             data = column.as_column(data).copy()
         kwargs = _setdefault_name(data, name=name)
@@ -2131,7 +2140,7 @@ def __init__(
         elif isinstance(data, pd.DatetimeIndex):
             data = column.as_column(data.values)
         elif isinstance(data, (list, tuple)):
-            data = column.as_column(np.array(data, dtype="datetime64[ms]"))
+            data = column.as_column(np.array(data, dtype=dtype))
         super().__init__(data, **kwargs)
 
     @property

python/cudf/cudf/tests/test_index.py

@@ -317,9 +317,6 @@ def test_index_copy_datetime(name, dtype, deep=True):
     pidx_copy = pidx.copy(name=name, deep=deep, dtype=dtype)
     cidx_copy = cidx.copy(name=name, deep=deep, dtype=dtype)
 
-    # By default, cudf.DatetimeIndex uses [ms] as base unit, pandas uses [ns]
-    if dtype == "int64":
-        cidx_copy = cidx_copy * 1000000
     assert_eq(pidx_copy, cidx_copy)