Update contains_cftime_datetimes to avoid loading entire variable arr…

…ay (#7494)

* Update contains_cftime_datetimes to avoid loading entire variable array

* Update whats-new.rst

* Convert arrays to variable instead for better control

* fix mypy?

* Update common.py

* Update xarray/core/common.py

Co-authored-by: Mathias Hauser <[email protected]>

* Update common.py

remove _variable_contains_cftime_datetimes

* Avoid creating variable.

* Add test

* minimize diff

* Update tests.

* address comment

* Fix test

* Fix whats-new

* Fix more tests

* More fixes

* fix iris tests

---------

Co-authored-by: Illviljan <[email protected]>
Co-authored-by: Mathias Hauser <[email protected]>
Co-authored-by: dcherian <[email protected]>
Co-authored-by: Deepak Cherian <[email protected]>

doc/whats-new.rst

@@ -44,6 +44,8 @@ Bug fixes
 - Fix matplotlib raising a UserWarning when plotting a scatter plot
   with an unfilled marker (:issue:`7313`, :pull:`7318`).
   By `Jimmy Westling <https://github.com/illviljan>`_.
+- Improved performance in ``open_dataset`` for datasets with large object arrays (:issue:`7484`, :pull:`7494`).
+  By `Alex Goodman <https://github.com/agoodm>`_ and `Deepak Cherian <https://github.com/dcherian>`_.
 
 Documentation
 ~~~~~~~~~~~~~

xarray/coding/calendar_ops.py

@@ -147,7 +147,7 @@ def convert_calendar(
     from xarray.core.dataarray import DataArray
 
     time = obj[dim]
-    if not _contains_datetime_like_objects(time):
+    if not _contains_datetime_like_objects(time.variable):
         raise ValueError(f"Coordinate {dim} must contain datetime objects.")
 
     use_cftime = _should_cftime_be_used(time, calendar, use_cftime)
@@ -319,8 +319,8 @@ def interp_calendar(source, target, dim="time"):
         target = DataArray(target, dims=(dim,), name=dim)
 
     if not _contains_datetime_like_objects(
-        source[dim]
-    ) or not _contains_datetime_like_objects(target):
+        source[dim].variable
+    ) or not _contains_datetime_like_objects(target.variable):
         raise ValueError(
             f"Both 'source.{dim}' and 'target' must contain datetime objects."
         )

xarray/coding/cftime_offsets.py

@@ -1267,7 +1267,7 @@ def date_range_like(source, calendar, use_cftime=None):
     if not isinstance(source, (pd.DatetimeIndex, CFTimeIndex)) and (
         isinstance(source, DataArray)
         and (source.ndim != 1)
-        or not _contains_datetime_like_objects(source)
+        or not _contains_datetime_like_objects(source.variable)
     ):
         raise ValueError(
             "'source' must be a 1D array of datetime objects for inferring its range."

xarray/coding/frequencies.py

@@ -79,11 +79,12 @@ def infer_freq(index):
         If there are fewer than three values or the index is not 1D.
     """
     from xarray.core.dataarray import DataArray
+    from xarray.core.variable import Variable
 
     if isinstance(index, (DataArray, pd.Series)):
         if index.ndim != 1:
             raise ValueError("'index' must be 1D")
-        elif not _contains_datetime_like_objects(DataArray(index)):
+        elif not _contains_datetime_like_objects(Variable("dim", index)):
             raise ValueError("'index' must contain datetime-like objects")
         dtype = np.asarray(index).dtype
         if dtype == "datetime64[ns]":

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 +1772,27 @@ 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:
-        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

@@ -143,7 +143,18 @@ def __init__(self, array):
         self.array = array
 
     def __getitem__(self, key):
-        raise UnexpectedDataAccess("Tried accessing data")
+        raise UnexpectedDataAccess("Tried accessing data.")
+
+    def __array__(self):
+        raise UnexpectedDataAccess("Tried accessing data.")
+
+
+class FirstElementAccessibleArray(InaccessibleArray):
+    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:

xarray/tests/test_accessor_dt.py

@@ -418,7 +418,6 @@ 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"

xarray/tests/test_backends.py

@@ -2560,7 +2560,7 @@ def test_open_zarr_use_cftime(self) -> None:
             ds_a = xr.open_zarr(store_target, **self.version_kwargs)
             assert_identical(ds, ds_a)
             ds_b = xr.open_zarr(store_target, use_cftime=True, **self.version_kwargs)
-            assert xr.coding.times.contains_cftime_datetimes(ds_b.time)
+            assert xr.coding.times.contains_cftime_datetimes(ds_b.time.variable)
 
     def test_write_read_select_write(self) -> None:
         # Test for https://github.com/pydata/xarray/issues/4084

xarray/tests/test_coding.py

@@ -65,13 +65,13 @@ def test_CFMaskCoder_missing_value() -> None:
     expected.attrs["missing_value"] = -9999
 
     decoded = xr.decode_cf(expected.to_dataset())
-    encoded, _ = xr.conventions.cf_encoder(decoded, decoded.attrs)
+    encoded, _ = xr.conventions.cf_encoder(decoded.variables, decoded.attrs)
 
     assert_equal(encoded["tmpk"], expected.variable)
 
     decoded.tmpk.encoding["_FillValue"] = -9940
     with pytest.raises(ValueError):
-        encoded, _ = xr.conventions.cf_encoder(decoded, decoded.attrs)
+        encoded, _ = xr.conventions.cf_encoder(decoded.variables, decoded.attrs)
 
 
 @requires_dask

xarray/tests/test_coding_times.py

@@ -31,6 +31,7 @@
 from xarray.core.common import contains_cftime_datetimes
 from xarray.testing import assert_equal, assert_identical
 from xarray.tests import (
+    FirstElementAccessibleArray,
     arm_xfail,
     assert_array_equal,
     assert_no_warnings,
@@ -787,35 +788,35 @@ def times_3d(times):
 
 @requires_cftime
 def test_contains_cftime_datetimes_1d(data) -> None:
-    assert contains_cftime_datetimes(data.time)
+    assert contains_cftime_datetimes(data.time.variable)
 
 
 @requires_cftime
 @requires_dask
 def test_contains_cftime_datetimes_dask_1d(data) -> None:
-    assert contains_cftime_datetimes(data.time.chunk())
+    assert contains_cftime_datetimes(data.time.variable.chunk())
 
 
 @requires_cftime
 def test_contains_cftime_datetimes_3d(times_3d) -> None:
-    assert contains_cftime_datetimes(times_3d)
+    assert contains_cftime_datetimes(times_3d.variable)
 
 
 @requires_cftime
 @requires_dask
 def test_contains_cftime_datetimes_dask_3d(times_3d) -> None:
-    assert contains_cftime_datetimes(times_3d.chunk())
+    assert contains_cftime_datetimes(times_3d.variable.chunk())
 
 
 @pytest.mark.parametrize("non_cftime_data", [DataArray([]), DataArray([1, 2])])
 def test_contains_cftime_datetimes_non_cftimes(non_cftime_data) -> None:
-    assert not contains_cftime_datetimes(non_cftime_data)
+    assert not contains_cftime_datetimes(non_cftime_data.variable)
 
 
 @requires_dask
 @pytest.mark.parametrize("non_cftime_data", [DataArray([]), DataArray([1, 2])])
 def test_contains_cftime_datetimes_non_cftimes_dask(non_cftime_data) -> None:
-    assert not contains_cftime_datetimes(non_cftime_data.chunk())
+    assert not contains_cftime_datetimes(non_cftime_data.variable.chunk())
 
 
 @requires_cftime
@@ -1176,3 +1177,17 @@ def test_scalar_unit() -> None:
     variable = Variable(("x", "y"), np.array([[0, 1], [2, 3]]), {"units": np.nan})
     result = coding.times.CFDatetimeCoder().decode(variable)
     assert np.isnan(result.attrs["units"])
+
+
+@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)

xarray/tests/test_dataarray.py

@@ -6219,7 +6219,7 @@ def test_to_and_from_iris(self) -> None:
             original_coord = original.coords[orginal_key]
             assert coord.var_name == original_coord.name
             assert_array_equal(
-                coord.points, CFDatetimeCoder().encode(original_coord).values
+                coord.points, CFDatetimeCoder().encode(original_coord.variable).values
             )
             assert actual.coord_dims(coord) == original.get_axis_num(
                 original.coords[coord.var_name].dims
@@ -6295,7 +6295,7 @@ def test_to_and_from_iris_dask(self) -> None:
             original_coord = original.coords[orginal_key]
             assert coord.var_name == original_coord.name
             assert_array_equal(
-                coord.points, CFDatetimeCoder().encode(original_coord).values
+                coord.points, CFDatetimeCoder().encode(original_coord.variable).values
             )
             assert actual.coord_dims(coord) == original.get_axis_num(
                 original.coords[coord.var_name].dims