Update contains_cftime_datetimes to avoid loading entire variable array

doc/whats-new.rst

@@ -99,6 +99,8 @@ Bug fixes
 - :py:func:`xarray.Dataset.to_zarr` now drops variable encodings that have been added by xarray during reading
   a dataset. (:issue:`7129`, :pull:`7500`).
   By `Hauke Schulz <https://github.com/observingClouds>`_.
+- Improved performance in ``open_dataset`` for datasets with large object arrays (:issue:`7484`, :pull:`7494`).
+  By `Alex Goodman <https://github.com/agoodm>`_.
 
 Documentation
 ~~~~~~~~~~~~~

xarray/core/accessor_dt.py

@@ -574,7 +574,7 @@ def __new__(cls, obj: T_DataArray) -> CombinedDatetimelikeAccessor:
         # we need to choose which parent (datetime or timedelta) is
         # appropriate. Since we're checking the dtypes anyway, we'll just
         # do all the validation here.
-        if not _contains_datetime_like_objects(obj):
+        if not _contains_datetime_like_objects(obj.variable):
             raise TypeError(
                 "'.dt' accessor only available for "
                 "DataArray with datetime64 timedelta64 dtype or "

xarray/core/common.py

@@ -11,6 +11,7 @@
 import pandas as pd
 
 from xarray.core import dtypes, duck_array_ops, formatting, formatting_html, ops
+from xarray.core.indexing import BasicIndexer, ExplicitlyIndexed
 from xarray.core.options import OPTIONS, _get_keep_attrs
 from xarray.core.pycompat import is_duck_dask_array
 from xarray.core.utils import Frozen, either_dict_or_kwargs, is_scalar
@@ -40,6 +41,7 @@
         ScalarOrArray,
         SideOptions,
         T_DataWithCoords,
+        T_Variable,
     )
     from xarray.core.variable import Variable
 
@@ -1770,31 +1772,29 @@ def is_np_timedelta_like(dtype: DTypeLike) -> bool:
     return np.issubdtype(dtype, np.timedelta64)
 
 
-def _contains_cftime_datetimes(array) -> bool:
-    """Check if an array contains cftime.datetime objects"""
+def _contains_cftime_datetimes(array: Any) -> bool:
+    """Check if a array inside a Variable contains cftime.datetime objects"""
     if cftime is None:
         return False
-    else:
-        if array.dtype == np.dtype("O") and array.size > 0:
-            sample = np.asarray(array).flat[0]
-            if is_duck_dask_array(sample):
-                sample = sample.compute()
-                if isinstance(sample, np.ndarray):
-                    sample = sample.item()
-            return isinstance(sample, cftime.datetime)
-        else:
-            return False
 
+    if array.dtype == np.dtype("O") and array.size > 0:
+        first_idx = (0,) * array.ndim
+        if isinstance(array, ExplicitlyIndexed):
+            first_idx = BasicIndexer(first_idx)
+        sample = array[first_idx]
+        return isinstance(np.asarray(sample).item(), cftime.datetime)
+
+    return False
 
-def contains_cftime_datetimes(var) -> bool:
+
+def contains_cftime_datetimes(var: T_Variable) -> bool:
     """Check if an xarray.Variable contains cftime.datetime objects"""
-    if var.dtype == np.dtype("O") and var.size > 0:
-        return _contains_cftime_datetimes(var.data)
-    else:
+    if cftime is None:
         return False
+    return _contains_cftime_datetimes(var._data)
 
 
-def _contains_datetime_like_objects(var) -> bool:
+def _contains_datetime_like_objects(var: T_Variable) -> bool:
     """Check if a variable contains datetime like objects (either
     np.datetime64, np.timedelta64, or cftime.datetime)
     """

xarray/tests/__init__.py

@@ -145,6 +145,17 @@ def __getitem__(self, key):
         raise UnexpectedDataAccess("Tried accessing data")
 
 
+class FirstElementAccessibleArray(utils.NDArrayMixin, ExplicitlyIndexed):
+    def __init__(self, array):
+        self.array = array
+
+    def __getitem__(self, key):
+        tuple_idxr = key.tuple
+        if len(tuple_idxr) > 1:
+            raise UnexpectedDataAccess("Tried accessing more than one element.")
+        return self.array[tuple_idxr]
+
+
 class ReturnItem:
     def __getitem__(self, key):
         return key

xarray/tests/test_accessor_dt.py

@@ -6,6 +6,7 @@
 
 import xarray as xr
 from xarray.tests import (
+    FirstElementAccessibleArray,
     assert_array_equal,
     assert_chunks_equal,
     assert_equal,
@@ -418,7 +419,6 @@ def test_calendar_cftime(data) -> None:
     assert data.time.dt.calendar == expected
 
 
-@requires_cftime
 def test_calendar_datetime64_2d() -> None:
     data = xr.DataArray(np.zeros((4, 5), dtype="datetime64[ns]"), dims=("x", "y"))
     assert data.dt.calendar == "proleptic_gregorian"
@@ -668,3 +668,17 @@ def test_cftime_round_accessor(
         result = cftime_rounding_dataarray.dt.round(freq)
 
     assert_identical(result, expected)
+
+
+@requires_cftime
+def test_contains_cftime_lazy() -> None:
+    import cftime
+
+    from xarray.core.common import _contains_cftime_datetimes
+
+    times = np.array(
+        [cftime.DatetimeGregorian(1, 1, 2, 0), cftime.DatetimeGregorian(1, 1, 2, 0)],
+        dtype=object,
+    )
+    array = FirstElementAccessibleArray(times)
+    assert _contains_cftime_datetimes(array)