Merge branch 'branch-25.02' into fix-cuproj-doc-example

.github/workflows/pr.yaml

@@ -12,6 +12,7 @@ concurrency:
 jobs:
   pr-builder:
     needs:
+      - check-nightly-ci
       - changed-files
       - checks
       - conda-cpp-build
@@ -32,6 +33,18 @@ jobs:
     if: always()
     with:
       needs: ${{ toJSON(needs) }}
+  check-nightly-ci:
+    # Switch to ubuntu-latest once it defaults to a version of Ubuntu that
+    # provides at least Python 3.11 (see
+    # https://docs.python.org/3/library/datetime.html#datetime.date.fromisoformat)
+    runs-on: ubuntu-24.04
+    env:
+      RAPIDS_GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+    steps:
+      - name: Check if nightly CI is passing
+        uses: rapidsai/shared-actions/check_nightly_success/dispatch@main
+        with:
+          repo: cuspatial
   changed-files:
     secrets: inherit
     uses: rapidsai/shared-workflows/.github/workflows/changed-files.yaml@branch-25.02

conda/environments/all_cuda-118_arch-x86_64.yaml

@@ -46,7 +46,7 @@ dependencies:
 - scikit-build-core>=0.10.0
 - scikit-image
 - shapely
-- sphinx<6
+- sphinx
 - sqlite
 - sysroot_linux-64==2.17
 name: all_cuda-118_arch-x86_64

conda/environments/all_cuda-125_arch-x86_64.yaml

@@ -48,7 +48,7 @@ dependencies:
 - scikit-build-core>=0.10.0
 - scikit-image
 - shapely
-- sphinx<6
+- sphinx
 - sqlite
 - sysroot_linux-64==2.17
 name: all_cuda-125_arch-x86_64

cpp/cmake/Modules/ConfigureCUDA.cmake

@@ -22,7 +22,7 @@ if(CMAKE_COMPILER_IS_GNUCXX)
     endif()
 endif(CMAKE_COMPILER_IS_GNUCXX)
 
-list(APPEND CUSPATIAL_CUDA_FLAGS --expt-extended-lambda)
+list(APPEND CUSPATIAL_CUDA_FLAGS --expt-extended-lambda --expt-relaxed-constexpr)
 
 # set warnings as errors
 if(CMAKE_CUDA_COMPILER_VERSION VERSION_GREATER_EQUAL 11.2.0)

dependencies.yaml

@@ -353,7 +353,7 @@ dependencies:
           - numpydoc
           # https://github.com/pydata/pydata-sphinx-theme/issues/1539
           - pydata-sphinx-theme!=0.14.2
-          - sphinx<6
+          - sphinx
   notebooks:
     common:
       - output_types: [conda, requirements, pyproject]

python/cuspatial/cuspatial/_lib/distance.pyx

@@ -4,7 +4,7 @@ from libcpp.memory cimport make_shared, shared_ptr, unique_ptr
 from libcpp.utility cimport move, pair
 
 from cudf._lib.column cimport Column
-from cudf._lib.utils cimport columns_from_table_view
+from pylibcudf cimport Table as plc_Table
 from pylibcudf.libcudf.column.column cimport column
 from pylibcudf.libcudf.column.column_view cimport column_view
 from pylibcudf.libcudf.table.table_view cimport table_view
@@ -60,12 +60,16 @@ def directed_hausdorff_distance(
             )
         )
 
-    owner = Column.from_unique_ptr(move(result.first), data_ptr_exposed=True)
-
-    return columns_from_table_view(
-        result.second,
-        owners=[owner] * result.second.num_columns()
+    owner_col = Column.from_unique_ptr(
+        move(result.first), data_ptr_exposed=True
+    )
+    cdef plc_Table plc_owner_table = plc_Table(
+        [owner_col.to_pylibcudf(mode="read")] * result.second.num_columns()
+    )
+    cdef plc_Table plc_result_table = plc_Table.from_table_view(
+        result.second, plc_owner_table
     )
+    return [Column.from_pylibcudf(col) for col in plc_result_table.columns()]
 
 
 def pairwise_point_distance(

python/cuspatial/cuspatial/_lib/linestring_bounding_boxes.pyx

@@ -4,7 +4,7 @@ from libcpp.memory cimport unique_ptr
 from libcpp.utility cimport move
 
 from cudf._lib.column cimport Column
-from cudf._lib.utils cimport columns_from_unique_ptr
+from pylibcudf cimport Table as plc_Table
 from pylibcudf.libcudf.column.column_view cimport column_view
 from pylibcudf.libcudf.table.table cimport table
 
@@ -24,4 +24,8 @@ cpdef linestring_bounding_boxes(Column poly_offsets,
         result = move(cpp_linestring_bounding_boxes(
             c_poly_offsets, c_x, c_y, R
         ))
-    return columns_from_unique_ptr(move(result))
+    cdef plc_Table plc_table = plc_Table.from_libcudf(move(result))
+    return [
+        Column.from_pylibcudf(col)
+        for col in plc_table.columns()
+    ]

python/cuspatial/cuspatial/_lib/points_in_range.pyx

@@ -4,7 +4,7 @@ from libcpp.memory cimport unique_ptr
 from libcpp.utility cimport move
 
 from cudf._lib.column cimport Column
-from cudf._lib.utils cimport data_from_unique_ptr
+from pylibcudf cimport Table as plc_Table
 from pylibcudf.libcudf.column.column_view cimport column_view
 from pylibcudf.libcudf.table.table cimport table
 
@@ -38,4 +38,11 @@ cpdef points_in_range(
             )
         )
 
-    return data_from_unique_ptr(move(c_result), column_names=["x", "y"])
+    cdef plc_Table plc_table = plc_Table.from_libcudf(move(c_result))
+    return (
+        {
+            name: Column.from_pylibcudf(col)
+            for name, col in zip(["x", "y"], plc_table.columns())
+        },
+        None
+    )

python/cuspatial/cuspatial/_lib/polygon_bounding_boxes.pyx

@@ -4,7 +4,7 @@ from libcpp.memory cimport unique_ptr
 from libcpp.utility cimport move
 
 from cudf._lib.column cimport Column
-from cudf._lib.utils cimport columns_from_unique_ptr
+from pylibcudf cimport Table as plc_Table
 from pylibcudf.libcudf.column.column_view cimport column_view
 from pylibcudf.libcudf.table.table cimport table
 
@@ -25,4 +25,8 @@ cpdef polygon_bounding_boxes(Column poly_offsets,
         result = move(cpp_polygon_bounding_boxes(
             c_poly_offsets, c_ring_offsets, c_x, c_y
         ))
-    return columns_from_unique_ptr(move(result))
+    cdef plc_Table table_result = plc_Table.from_libcudf(move(result))
+    return [
+        Column.from_pylibcudf(col)
+        for col in table_result.columns()
+    ]

python/cuspatial/cuspatial/_lib/quadtree.pyx

@@ -6,7 +6,7 @@ from libcpp.pair cimport pair
 from libcpp.utility cimport move
 
 from cudf._lib.column cimport Column
-from cudf._lib.utils cimport data_from_unique_ptr
+from pylibcudf cimport Table as plc_Table
 from pylibcudf.libcudf.column.column cimport column
 from pylibcudf.libcudf.column.column_view cimport column_view
 from pylibcudf.libcudf.table.table cimport table
@@ -30,16 +30,21 @@ cpdef quadtree_on_points(Column x, Column y,
         result = move(cpp_quadtree_on_points(
             c_x, c_y, x_min, x_max, y_min, y_max, scale, max_depth, min_size
         ))
+    cdef plc_Table plc_table = plc_Table.from_libcudf(move(result.second))
+    result_names = [
+        "key",
+        "level",
+        "is_internal_node",
+        "length",
+        "offset"
+    ]
     return (
         Column.from_unique_ptr(move(result.first)),
-        data_from_unique_ptr(
-            move(result.second),
-            column_names=[
-                "key",
-                "level",
-                "is_internal_node",
-                "length",
-                "offset"
-            ]
+        (
+            {
+                name: Column.from_pylibcudf(col)
+                for name, col in zip(result_names, plc_table.columns())
+            },
+            None
         )
     )

python/cuspatial/cuspatial/_lib/spatial_join.pyx

@@ -5,7 +5,7 @@ from libcpp.memory cimport unique_ptr
 from libcpp.utility cimport move
 
 from cudf._lib.column cimport Column
-from cudf._lib.utils cimport data_from_unique_ptr, table_view_from_table
+from pylibcudf cimport Table as plc_Table
 from pylibcudf.libcudf.column.column_view cimport column_view
 from pylibcudf.libcudf.table.table cimport table, table_view
 
@@ -24,20 +24,30 @@ cpdef join_quadtree_and_bounding_boxes(object quadtree,
                                        double y_max,
                                        double scale,
                                        int8_t max_depth):
-    cdef table_view c_quadtree = table_view_from_table(
-        quadtree, ignore_index=True)
-    cdef table_view c_bounding_boxes = table_view_from_table(
-        bounding_boxes, ignore_index=True)
+    cdef plc_Table plc_quadtree = plc_Table(
+        [col.to_pylibcudf(mode="read") for col in quadtree._columns]
+    )
+    cdef table_view c_quadtree = plc_quadtree.view()
+    cdef plc_Table plc_bounding_boxes = plc_Table(
+        [col.to_pylibcudf(mode="read") for col in bounding_boxes._columns]
+    )
+    cdef table_view c_bounding_boxes = plc_bounding_boxes.view()
     cdef unique_ptr[table] result
     with nogil:
         result = move(cpp_join_quadtree_and_bounding_boxes(
             c_quadtree,
             c_bounding_boxes,
             x_min, x_max, y_min, y_max, scale, max_depth
         ))
-    return data_from_unique_ptr(
-        move(result),
-        column_names=["bbox_offset", "quad_offset"]
+    cdef plc_Table plc_table = plc_Table.from_libcudf(move(result))
+    return (
+        {
+            name: Column.from_pylibcudf(col)
+            for name, col in zip(
+                ["bbox_offset", "quad_offset"], plc_table.columns()
+            )
+        },
+        None
     )
 
 
@@ -50,10 +60,14 @@ cpdef quadtree_point_in_polygon(object poly_quad_pairs,
                                 Column ring_offsets,
                                 Column poly_points_x,
                                 Column poly_points_y):
-    cdef table_view c_poly_quad_pairs = table_view_from_table(
-        poly_quad_pairs, ignore_index=True)
-    cdef table_view c_quadtree = table_view_from_table(
-        quadtree, ignore_index=True)
+    cdef plc_Table plc_poly_quad_pairs = plc_Table(
+        [col.to_pylibcudf(mode="read") for col in poly_quad_pairs._columns]
+    )
+    cdef table_view c_poly_quad_pairs = plc_poly_quad_pairs.view()
+    cdef plc_Table plc_quadtree = plc_Table(
+        [col.to_pylibcudf(mode="read") for col in quadtree._columns]
+    )
+    cdef table_view c_quadtree = plc_quadtree.view()
     cdef column_view c_point_indices = point_indices.view()
     cdef column_view c_points_x = points_x.view()
     cdef column_view c_points_y = points_y.view()
@@ -74,9 +88,15 @@ cpdef quadtree_point_in_polygon(object poly_quad_pairs,
             c_poly_points_x,
             c_poly_points_y
         ))
-    return data_from_unique_ptr(
-        move(result),
-        column_names=["polygon_index", "point_index"]
+    cdef plc_Table plc_table = plc_Table.from_libcudf(move(result))
+    return (
+        {
+            name: Column.from_pylibcudf(col)
+            for name, col in zip(
+                ["polygon_index", "point_index"], plc_table.columns()
+            )
+        },
+        None
     )
 
 
@@ -88,10 +108,17 @@ cpdef quadtree_point_to_nearest_linestring(object linestring_quad_pairs,
                                            Column linestring_offsets,
                                            Column linestring_points_x,
                                            Column linestring_points_y):
-    cdef table_view c_linestring_quad_pairs = table_view_from_table(
-        linestring_quad_pairs, ignore_index=True)
-    cdef table_view c_quadtree = table_view_from_table(
-        quadtree, ignore_index=True)
+    cdef plc_Table plc_quad_pairs = plc_Table(
+        [
+            col.to_pylibcudf(mode="read")
+            for col in linestring_quad_pairs._columns
+        ]
+    )
+    cdef table_view c_linestring_quad_pairs = plc_quad_pairs.view()
+    cdef plc_Table plc_quadtree = plc_Table(
+        [col.to_pylibcudf(mode="read") for col in quadtree._columns]
+    )
+    cdef table_view c_quadtree = plc_quadtree.view()
     cdef column_view c_point_indices = point_indices.view()
     cdef column_view c_points_x = points_x.view()
     cdef column_view c_points_y = points_y.view()
@@ -110,7 +137,14 @@ cpdef quadtree_point_to_nearest_linestring(object linestring_quad_pairs,
             c_linestring_points_x,
             c_linestring_points_y
         ))
-    return data_from_unique_ptr(
-        move(result),
-        column_names=["point_index", "linestring_index", "distance"]
+    cdef plc_Table plc_table = plc_Table.from_libcudf(move(result))
+    return (
+        {
+            name: Column.from_pylibcudf(col)
+            for name, col in zip(
+                ["point_index", "linestring_index", "distance"],
+                plc_table.columns()
+            )
+        },
+        None
     )

python/cuspatial/cuspatial/_lib/trajectory.pyx

@@ -5,7 +5,7 @@ from libcpp.pair cimport pair
 from libcpp.utility cimport move
 
 from cudf._lib.column cimport Column
-from cudf._lib.utils cimport data_from_unique_ptr
+from pylibcudf cimport Table as plc_Table
 from pylibcudf.libcudf.column.column cimport column
 from pylibcudf.libcudf.column.column_view cimport column_view
 from pylibcudf.libcudf.table.table cimport table
@@ -27,10 +27,17 @@ cpdef derive_trajectories(Column object_id, Column x,
     cdef pair[unique_ptr[table], unique_ptr[column]] result
     with nogil:
         result = move(cpp_derive_trajectories(c_id, c_x, c_y, c_ts))
-    return data_from_unique_ptr(
-        move(result.first),
-        column_names=["object_id", "x", "y", "timestamp"]
-    ), Column.from_unique_ptr(move(result.second))
+    cdef plc_Table plc_table = plc_Table.from_libcudf(move(result.first))
+    first_result = (
+        {
+            name: Column.from_pylibcudf(col)
+            for name, col in zip(
+                ["object_id", "x", "y", "timestamp"], plc_table.columns()
+            )
+        },
+        None
+    )
+    return first_result, Column.from_unique_ptr(move(result.second))
 
 
 cpdef trajectory_bounding_boxes(size_type num_trajectories,
@@ -43,9 +50,15 @@ cpdef trajectory_bounding_boxes(size_type num_trajectories,
         result = move(cpp_trajectory_bounding_boxes(
             num_trajectories, c_id, c_x, c_y
         ))
-    return data_from_unique_ptr(
-        move(result),
-        column_names=["x_min", "y_min", "x_max", "y_max"]
+    cdef plc_Table plc_table = plc_Table.from_libcudf(move(result))
+    return (
+        {
+            name: Column.from_pylibcudf(col)
+            for name, col in zip(
+                ["x_min", "y_min", "x_max", "y_max"], plc_table.columns()
+            )
+        },
+        None
     )
 
 
@@ -61,7 +74,11 @@ cpdef trajectory_distances_and_speeds(size_type num_trajectories,
         result = move(cpp_trajectory_distances_and_speeds(
             num_trajectories, c_id, c_x, c_y, c_ts
         ))
-    return data_from_unique_ptr(
-        move(result),
-        column_names=["distance", "speed"]
+    cdef plc_Table plc_table = plc_Table.from_libcudf(move(result))
+    return (
+        {
+            name: Column.from_pylibcudf(col)
+            for name, col in zip(["distance", "speed"], plc_table.columns())
+        },
+        None
     )