Fix categorical-accessor support and testing in dask-cudf

python/cudf/cudf/core/indexed_frame.py

@@ -6308,7 +6308,12 @@ def __dask_tokenize__(self):
 
         return [
             type(self),
-            normalize_token(self._dtypes),
+            str(self._dtypes),
+            *[
+                normalize_token(cat.categories)
+                for cat in self._dtypes.values()
+                if cat == "category"
+            ],
             normalize_token(self.index),
             normalize_token(self.hash_values().values_host),
         ]

python/dask_cudf/dask_cudf/io/tests/test_json.py

@@ -12,8 +12,8 @@
 import dask_cudf
 from dask_cudf.tests.utils import skip_dask_expr
 
-# No dask-expr support for dask_expr<1.0.6
-pytestmark = skip_dask_expr(lt_version="1.0.6")
+# No dask-expr support for dask<2024.4.0
+pytestmark = skip_dask_expr(lt_version="2024.4.0")
 
 
 def test_read_json_backend_dispatch(tmp_path):

python/dask_cudf/dask_cudf/io/tests/test_orc.py

@@ -14,8 +14,8 @@
 import dask_cudf
 from dask_cudf.tests.utils import skip_dask_expr
 
-# No dask-expr support for dask_expr<1.0.6
-pytestmark = skip_dask_expr(lt_version="1.0.6")
+# No dask-expr support for dask<2024.4.0
+pytestmark = skip_dask_expr(lt_version="2024.4.0")
 
 cur_dir = os.path.dirname(__file__)
 sample_orc = os.path.join(cur_dir, "data/orc/sample.orc")

python/dask_cudf/dask_cudf/io/tests/test_parquet.py

@@ -536,7 +536,7 @@ def test_check_file_size(tmpdir):
         dask_cudf.io.read_parquet(fn, check_file_size=1).compute()
 
 
-@xfail_dask_expr("HivePartitioning cannot be hashed", lt_version="1.0")
+@xfail_dask_expr("HivePartitioning cannot be hashed", lt_version="2024.3.0")
 def test_null_partition(tmpdir):
     import pyarrow as pa
     from pyarrow.dataset import HivePartitioning

python/dask_cudf/dask_cudf/io/tests/test_text.py

@@ -11,8 +11,8 @@
 import dask_cudf
 from dask_cudf.tests.utils import skip_dask_expr
 
-# No dask-expr support for dask_expr<1.0.6
-pytestmark = skip_dask_expr(lt_version="1.0.6")
+# No dask-expr support for dask<2024.4.0
+pytestmark = skip_dask_expr(lt_version="2024.4.0")
 
 cur_dir = os.path.dirname(__file__)
 text_file = os.path.join(cur_dir, "data/text/sample.pgn")

python/dask_cudf/dask_cudf/tests/test_accessor.py

@@ -111,7 +111,7 @@ def test_categorical_accessor_initialization2(data):
         dsr.cat
 
 
-@xfail_dask_expr("TODO: Unexplained dask-expr failure")
+@xfail_dask_expr(lt_version="2024.5.0")
 @pytest.mark.parametrize("data", [data_cat_1()])
 def test_categorical_basic(data):
     cat = data.copy()
@@ -203,7 +203,6 @@ def test_categorical_compare_unordered(data):
         dsr < dsr
 
 
-@xfail_dask_expr("TODO: Unexplained dask-expr failure")
 @pytest.mark.parametrize("data", [data_cat_3()])
 def test_categorical_compare_ordered(data):
     cat1 = data[0].copy()
@@ -274,7 +273,6 @@ def test_categorical_categories():
     )
 
 
-@xfail_dask_expr("TODO: Unexplained dask-expr failure")
 def test_categorical_as_known():
     df = dask_cudf.from_cudf(DataFrame({"col_1": [0, 1, 2, 3]}), npartitions=2)
     df["col_1"] = df["col_1"].astype("category")
@@ -283,7 +281,19 @@ def test_categorical_as_known():
     pdf = dd.from_pandas(pd.DataFrame({"col_1": [0, 1, 2, 3]}), npartitions=2)
     pdf["col_1"] = pdf["col_1"].astype("category")
     expected = pdf["col_1"].cat.as_known()
-    dd.assert_eq(expected, actual)
+
+    # Note: Categories may be ordered differently in
+    # cudf and pandas. Therefore, we need to compare
+    # the global set of categories (before and after
+    # calling `compute`), then we need to check that
+    # the initial order of rows was preserved.
+    assert set(expected.cat.categories) == set(
+        actual.cat.categories.values_host
+    )
+    assert set(expected.compute().cat.categories) == set(
+        actual.compute().cat.categories.values_host
+    )
+    dd.assert_eq(expected, actual.astype(expected.dtype))
 
 
 def test_str_slice():

python/dask_cudf/dask_cudf/tests/utils.py

@@ -5,18 +5,17 @@
 import pytest
 from packaging.version import Version
 
+import dask
 import dask.dataframe as dd
 
 import cudf
 
 from dask_cudf.expr import QUERY_PLANNING_ON
 
 if QUERY_PLANNING_ON:
-    import dask_expr
-
-    DASK_EXPR_VERSION = Version(dask_expr.__version__)
+    DASK_VERSION = Version(dask.__version__)
 else:
-    DASK_EXPR_VERSION = None
+    DASK_VERSION = None
 
 
 def _make_random_frame(nelem, npartitions=2, include_na=False):
@@ -37,15 +36,15 @@ def _make_random_frame(nelem, npartitions=2, include_na=False):
 
 def skip_dask_expr(reason=_default_reason, lt_version=None):
     if lt_version is not None:
-        skip = QUERY_PLANNING_ON and DASK_EXPR_VERSION < Version(lt_version)
+        skip = QUERY_PLANNING_ON and DASK_VERSION < Version(lt_version)
     else:
         skip = QUERY_PLANNING_ON
     return pytest.mark.skipif(skip, reason=reason)
 
 
 def xfail_dask_expr(reason=_default_reason, lt_version=None):
     if lt_version is not None:
-        xfail = QUERY_PLANNING_ON and DASK_EXPR_VERSION < Version(lt_version)
+        xfail = QUERY_PLANNING_ON and DASK_VERSION < Version(lt_version)
     else:
         xfail = QUERY_PLANNING_ON
     return pytest.mark.xfail(xfail, reason=reason)