Add multigraph support to nx-cugraph

python/nx-cugraph/lint.yaml

@@ -11,7 +11,7 @@ default_language_version:
     python: python3
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.4.0
+    rev: v4.5.0
     hooks:
       - id: check-added-large-files
       - id: check-case-conflict
@@ -26,7 +26,7 @@ repos:
       - id: mixed-line-ending
       - id: trailing-whitespace
   - repo: https://github.com/abravalheri/validate-pyproject
-    rev: v0.14
+    rev: v0.15
     hooks:
       - id: validate-pyproject
         name: Validate pyproject.toml
@@ -40,7 +40,7 @@ repos:
     hooks:
       - id: isort
   - repo: https://github.com/asottile/pyupgrade
-    rev: v3.13.0
+    rev: v3.15.0
     hooks:
       - id: pyupgrade
         args: [--py39-plus]
@@ -50,7 +50,7 @@ repos:
       - id: black
       # - id: black-jupyter
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.0.291
+    rev: v0.0.292
     hooks:
       - id: ruff
         args: [--fix-only, --show-fixes]
@@ -70,18 +70,18 @@ repos:
       - id: yesqa
         additional_dependencies: *flake8_dependencies
   - repo: https://github.com/codespell-project/codespell
-    rev: v2.2.5
+    rev: v2.2.6
     hooks:
       - id: codespell
         types_or: [python, rst, markdown]
         additional_dependencies: [tomli]
         files: ^(nx_cugraph|docs)/
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.0.291
+    rev: v0.0.292
     hooks:
       - id: ruff
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.4.0
+    rev: v4.5.0
     hooks:
       - id: no-commit-to-branch
         args: [-p, "^branch-2....$"]

python/nx-cugraph/nx_cugraph/classes/__init__.py

@@ -11,5 +11,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 from .graph import Graph
+from .multigraph import MultiGraph
 
 from .digraph import DiGraph  # isort:skip
+from .multidigraph import MultiDiGraph  # isort:skip

python/nx-cugraph/nx_cugraph/classes/graph.py

@@ -43,7 +43,8 @@
 
 class Graph:
     # Tell networkx to dispatch calls with this object to nx-cugraph
-    __networkx_plugin__: ClassVar[str] = "cugraph"
+    __networkx_backend__: ClassVar[str] = "cugraph"  # nx >=3.2
+    __networkx_plugin__: ClassVar[str] = "cugraph"  # nx <3.2
 
     # networkx properties
     graph: dict
@@ -58,7 +59,7 @@ class Graph:
     node_values: dict[AttrKey, cp.ndarray[NodeValue]]
     node_masks: dict[AttrKey, cp.ndarray[bool]]
     key_to_id: dict[NodeKey, IndexValue] | None
-    _id_to_key: dict[IndexValue, NodeKey] | None
+    _id_to_key: list[NodeKey] | None
     _N: int
 
     ####################
@@ -77,7 +78,7 @@ def from_coo(
         node_masks: dict[AttrKey, cp.ndarray[bool]] | None = None,
         *,
         key_to_id: dict[NodeKey, IndexValue] | None = None,
-        id_to_key: dict[IndexValue, NodeKey] | None = None,
+        id_to_key: list[NodeKey] | None = None,
         **attr,
     ) -> Graph:
         new_graph = object.__new__(cls)
@@ -88,7 +89,7 @@ def from_coo(
         new_graph.node_values = {} if node_values is None else dict(node_values)
         new_graph.node_masks = {} if node_masks is None else dict(node_masks)
         new_graph.key_to_id = None if key_to_id is None else dict(key_to_id)
-        new_graph._id_to_key = None if id_to_key is None else dict(id_to_key)
+        new_graph._id_to_key = None if id_to_key is None else list(id_to_key)
         new_graph._N = op.index(N)  # Ensure N is integral
         new_graph.graph = new_graph.graph_attr_dict_factory()
         new_graph.graph.update(attr)
@@ -123,7 +124,7 @@ def from_csr(
         node_masks: dict[AttrKey, cp.ndarray[bool]] | None = None,
         *,
         key_to_id: dict[NodeKey, IndexValue] | None = None,
-        id_to_key: dict[IndexValue, NodeKey] | None = None,
+        id_to_key: list[NodeKey] | None = None,
         **attr,
     ) -> Graph:
         N = indptr.size - 1
@@ -155,7 +156,7 @@ def from_csc(
         node_masks: dict[AttrKey, cp.ndarray[bool]] | None = None,
         *,
         key_to_id: dict[NodeKey, IndexValue] | None = None,
-        id_to_key: dict[IndexValue, NodeKey] | None = None,
+        id_to_key: list[NodeKey] | None = None,
         **attr,
     ) -> Graph:
         N = indptr.size - 1
@@ -189,7 +190,7 @@ def from_dcsr(
         node_masks: dict[AttrKey, cp.ndarray[bool]] | None = None,
         *,
         key_to_id: dict[NodeKey, IndexValue] | None = None,
-        id_to_key: dict[IndexValue, NodeKey] | None = None,
+        id_to_key: list[NodeKey] | None = None,
         **attr,
     ) -> Graph:
         row_indices = cp.array(
@@ -222,7 +223,7 @@ def from_dcsc(
         node_masks: dict[AttrKey, cp.ndarray[bool]] | None = None,
         *,
         key_to_id: dict[NodeKey, IndexValue] | None = None,
-        id_to_key: dict[IndexValue, NodeKey] | None = None,
+        id_to_key: list[NodeKey] | None = None,
         **attr,
     ) -> Graph:
         col_indices = cp.array(
@@ -245,9 +246,9 @@ def from_dcsc(
     def __new__(cls, incoming_graph_data=None, **attr) -> Graph:
         if incoming_graph_data is None:
             new_graph = cls.from_coo(0, cp.empty(0, np.int32), cp.empty(0, np.int32))
-        elif incoming_graph_data.__class__ is new_graph.__class__:
+        elif incoming_graph_data.__class__ is cls:
             new_graph = incoming_graph_data.copy()
-        elif incoming_graph_data.__class__ is new_graph.to_networkx_class():
+        elif incoming_graph_data.__class__ is cls.to_networkx_class():
             new_graph = nxcg.from_networkx(incoming_graph_data, preserve_all_attrs=True)
         else:
             raise NotImplementedError
@@ -295,11 +296,11 @@ def node_dtypes(self) -> dict[AttrKey, Dtype]:
         return {key: val.dtype for key, val in self.node_values.items()}
 
     @property
-    def id_to_key(self) -> dict[IndexValue, NodeKey] | None:
+    def id_to_key(self) -> [NodeKey] | None:
         if self.key_to_id is None:
             return None
         if self._id_to_key is None:
-            self._id_to_key = {val: key for key, val in self.key_to_id.items()}
+            self._id_to_key = sorted(self.key_to_id, key=self.key_to_id.__getitem__)
         return self._id_to_key
 
     name = nx.Graph.name
@@ -370,6 +371,12 @@ def get_edge_data(
                 v = self.key_to_id[v]
             except KeyError:
                 return default
+        else:
+            try:
+                if u < 0 or v < 0 or u >= self._N or v >= self._N:
+                    return default
+            except TypeError:
+                return default
         index = cp.nonzero((self.row_indices == u) & (self.col_indices == v))[0]
         if index.size == 0:
             return default
@@ -447,6 +454,7 @@ def to_undirected(self, as_view: bool = False) -> Graph:
     ###################
 
     def _copy(self, as_view: bool, cls: type[Graph], reverse: bool = False):
+        # DRY warning: see also MultiGraph._copy
         indptr = self.indptr
         row_indices = self.row_indices
         col_indices = self.col_indices

python/nx-cugraph/nx_cugraph/classes/multidigraph.py

@@ -0,0 +1,30 @@
+# Copyright (c) 2023, NVIDIA CORPORATION.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import networkx as nx
+
+import nx_cugraph as nxcg
+
+from .digraph import DiGraph
+from .multigraph import MultiGraph
+
+__all__ = ["MultiDiGraph"]
+
+networkx_api = nxcg.utils.decorators.networkx_class(nx.MultiDiGraph)
+
+
+class MultiDiGraph(MultiGraph, DiGraph):
+    @classmethod
+    def to_networkx_class(cls) -> type[nx.MultiDiGraph]:
+        return nx.MultiDiGraph