Use cudf::lists::distinct in Python binding

python/cudf/cudf/_lib/cpp/lists/drop_list_duplicates.pxd → python/cudf/cudf/_lib/cpp/lists/stream_compaction.pxd

@@ -1,4 +1,4 @@
-# Copyright (c) 2021, NVIDIA CORPORATION.
+# Copyright (c) 2021-2022, NVIDIA CORPORATION.
 
 from libcpp.memory cimport unique_ptr
 
@@ -7,9 +7,9 @@ from cudf._lib.cpp.lists.lists_column_view cimport lists_column_view
 from cudf._lib.cpp.types cimport nan_equality, null_equality
 
 
-cdef extern from "cudf/lists/drop_list_duplicates.hpp" \
+cdef extern from "cudf/lists/stream_compaction.hpp" \
         namespace "cudf::lists" nogil:
-    cdef unique_ptr[column] drop_list_duplicates(
+    cdef unique_ptr[column] distinct(
         const lists_column_view lists_column,
         null_equality nulls_equal,
         nan_equality nans_equal

python/cudf/cudf/_lib/lists.pyx

@@ -15,12 +15,10 @@ from cudf._lib.cpp.lists.combine cimport (
 from cudf._lib.cpp.lists.count_elements cimport (
     count_elements as cpp_count_elements,
 )
-from cudf._lib.cpp.lists.drop_list_duplicates cimport (
-    drop_list_duplicates as cpp_drop_list_duplicates,
-)
 from cudf._lib.cpp.lists.explode cimport explode_outer as cpp_explode_outer
 from cudf._lib.cpp.lists.lists_column_view cimport lists_column_view
 from cudf._lib.cpp.lists.sorting cimport sort_lists as cpp_sort_lists
+from cudf._lib.cpp.lists.stream_compaction cimport distinct as cpp_distinct
 from cudf._lib.cpp.scalar.scalar cimport scalar
 from cudf._lib.cpp.table.table cimport table
 from cudf._lib.cpp.table.table_view cimport table_view
@@ -75,12 +73,12 @@ def explode_outer(
     return columns_from_unique_ptr(move(c_result))
 
 
-def drop_list_duplicates(Column col, bool nulls_equal, bool nans_all_equal):
+def distinct(Column col, bool nulls_equal, bool nans_all_equal):
     """
-    nans_all_equal == True indicates that libcudf should treat any two elements
-    from {+nan, -nan} as equal, and as unequal otherwise.
     nulls_equal == True indicates that libcudf should treat any two nulls as
     equal, and as unequal otherwise.
+    nans_all_equal == True indicates that libcudf should treat any two
+    elements from {-nan, +nan} as equal, and as unequal otherwise.
     """
     cdef shared_ptr[lists_column_view] list_view = (
         make_shared[lists_column_view](col.view())
@@ -96,9 +94,9 @@ def drop_list_duplicates(Column col, bool nulls_equal, bool nans_all_equal):
 
     with nogil:
         c_result = move(
-            cpp_drop_list_duplicates(list_view.get()[0],
-                                     c_nulls_equal,
-                                     c_nans_equal)
+            cpp_distinct(list_view.get()[0],
+                         c_nulls_equal,
+                         c_nans_equal)
         )
     return Column.from_unique_ptr(move(c_result))
 

python/cudf/cudf/core/column/lists.py

@@ -13,7 +13,7 @@
     concatenate_rows,
     contains_scalar,
     count_elements,
-    drop_list_duplicates,
+    distinct,
     extract_element_column,
     extract_element_scalar,
     index_of_column,
@@ -603,9 +603,7 @@ def unique(self) -> ParentType:
             raise NotImplementedError("Nested lists unique is not supported.")
 
         return self._return_or_inplace(
-            drop_list_duplicates(
-                self._column, nulls_equal=True, nans_all_equal=True
-            )
+            distinct(self._column, nulls_equal=True, nans_all_equal=True)
         )
 
     def sort_values(