use general StateInfo

python/cudf_polars/cudf_polars/experimental/parallel.py

@@ -39,6 +39,17 @@ def __init__(self, count: int):
 """Protocol for Lowering IR nodes."""
 
 
+class StateInfo:
+    """Bag of arbitrary state information."""
+
+    def __init__(self, *, parts_info: MutableMapping[IR, PartitionInfo] | None = None):
+        self.__parts_info = parts_info or {}
+
+    def parts(self, ir: IR) -> PartitionInfo:
+        """Return partitioning information for an IR node."""
+        return self.__parts_info[ir]
+
+
 def get_key_name(node: Node) -> str:
     """Generate the key name for a Node."""
     return f"{type(node).__name__.lower()}-{hash(node)}"
@@ -87,9 +98,7 @@ def lower_ir_graph(ir: IR) -> tuple[IR, MutableMapping[IR, PartitionInfo]]:
 
 
 @singledispatch
-def generate_ir_tasks(
-    ir: IR, partition_info: MutableMapping[IR, PartitionInfo]
-) -> MutableMapping[Any, Any]:
+def generate_ir_tasks(ir: IR, state: StateInfo) -> MutableMapping[Any, Any]:
     """
     Generate tasks for an IR node.
 
@@ -100,20 +109,18 @@ def generate_ir_tasks(
 
 
 @generate_ir_tasks.register(IR)
-def _default_ir_tasks(
-    ir: IR, partition_info: MutableMapping[IR, PartitionInfo]
-) -> MutableMapping[Any, Any]:
+def _default_ir_tasks(ir: IR, state: StateInfo) -> MutableMapping[Any, Any]:
     # Single-partition default behavior.
     # This is used by `generate_ir_tasks` for all unregistered IR sub-types.
-    if partition_info[ir].count > 1:
+    if state.parts(ir).count > 1:
         raise NotImplementedError(
             f"Failed to generate multiple output tasks for {ir}."
         )  # pragma: no cover
 
     child_names = []
     for child in ir.children:
         child_names.append(get_key_name(child))
-        if partition_info[child].count > 1:
+        if state.parts(child).count > 1:
             raise NotImplementedError(
                 f"Failed to generate tasks for {ir} with child {child}."
             )  # pragma: no cover
@@ -128,13 +135,11 @@ def _default_ir_tasks(
     }
 
 
-def task_graph(
-    ir: IR, partition_info: MutableMapping[IR, PartitionInfo]
-) -> tuple[MutableMapping[str, Any], str]:
+def task_graph(ir: IR, state: StateInfo) -> tuple[MutableMapping[str, Any], str]:
     """Construct a Dask-compatible task graph."""
     graph = reduce(
         operator.or_,
-        [generate_ir_tasks(node, partition_info) for node in traversal(ir)],
+        [generate_ir_tasks(node, state) for node in traversal(ir)],
     )
     key_name = get_key_name(ir)
     graph[key_name] = (key_name, 0)
@@ -146,7 +151,7 @@ def evaluate_dask(ir: IR) -> DataFrame:
     """Evaluate an IR graph with Dask."""
     from dask import get
 
-    ir, partition_info = lower_ir_graph(ir)
+    ir, parts_info = lower_ir_graph(ir)
 
-    graph, key = task_graph(ir, partition_info)
+    graph, key = task_graph(ir, StateInfo(parts_info=parts_info))
     return get(graph, key)