More typing changes

python/lsst/pipe/base/connections.py

@@ -39,7 +39,7 @@
 import itertools
 import string
 from collections import UserDict
-from collections.abc import Collection, Generator, Iterable, Mapping, Set
+from collections.abc import Collection, Generator, Iterable, Mapping, Sequence, Set
 from dataclasses import dataclass
 from types import MappingProxyType, SimpleNamespace
 from typing import TYPE_CHECKING, Any
@@ -934,12 +934,12 @@ class AdjustQuantumHelper:
     connection-oriented mappings used inside `PipelineTaskConnections`.
     """
 
-    inputs: NamedKeyMapping[DatasetType, tuple[DatasetRef]]
+    inputs: NamedKeyMapping[DatasetType, Sequence[DatasetRef]]
     """Mapping of regular input and prerequisite input datasets, grouped by
     `~lsst.daf.butler.DatasetType`.
     """
 
-    outputs: NamedKeyMapping[DatasetType, tuple[DatasetRef]]
+    outputs: NamedKeyMapping[DatasetType, Sequence[DatasetRef]]
     """Mapping of output datasets, grouped by `~lsst.daf.butler.DatasetType`.
     """
 
@@ -997,7 +997,7 @@ def adjust_in_place(
         # Translate adjustments to DatasetType-keyed, Quantum-oriented form,
         # installing new mappings in self if necessary.
         if adjusted_inputs_by_connection:
-            adjusted_inputs = NamedKeyDict[DatasetType, tuple[DatasetRef]](self.inputs)
+            adjusted_inputs = NamedKeyDict[DatasetType, tuple[DatasetRef, ...]](self.inputs)
             for name, (connection, updated_refs) in adjusted_inputs_by_connection.items():
                 dataset_type_name = connection.name
                 if not set(updated_refs).issubset(self.inputs[dataset_type_name]):
@@ -1012,7 +1012,7 @@ def adjust_in_place(
         else:
             self.inputs_adjusted = False
         if adjusted_outputs_by_connection:
-            adjusted_outputs = NamedKeyDict[DatasetType, tuple[DatasetRef]](self.outputs)
+            adjusted_outputs = NamedKeyDict[DatasetType, tuple[DatasetRef, ...]](self.outputs)
             for name, (connection, updated_refs) in adjusted_outputs_by_connection.items():
                 dataset_type_name = connection.name
                 if not set(updated_refs).issubset(self.outputs[dataset_type_name]):

python/lsst/pipe/base/graph/_implDetails.py

@@ -313,13 +313,15 @@ def _pruner(
             # from the graph.
             try:
                 helper.adjust_in_place(node.taskDef.connections, node.taskDef.label, node.quantum.dataId)
+                # ignore the types because quantum really can take a sequence
+                # of inputs
                 newQuantum = Quantum(
                     taskName=node.quantum.taskName,
                     taskClass=node.quantum.taskClass,
                     dataId=node.quantum.dataId,
                     initInputs=node.quantum.initInputs,
-                    inputs=helper.inputs,
-                    outputs=helper.outputs,
+                    inputs=helper.inputs,  # type: ignore
+                    outputs=helper.outputs,  # type: ignore
                 )
                 # If the inputs or outputs were adjusted to something different
                 # than what was supplied by the graph builder, dissassociate

python/lsst/pipe/base/graphBuilder.py

@@ -455,13 +455,14 @@ def makeQuantum(self, datastore_records: Mapping[str, DatastoreRecordData] | Non
                 matching_records = records.subset(input_ids)
                 if matching_records is not None:
                     quantum_records[datastore_name] = matching_records
+        # ignore the types because quantum really can take a sequence of inputs
         return Quantum(
             taskName=self.task.taskDef.taskName,
             taskClass=self.task.taskDef.taskClass,
             dataId=self.dataId,
             initInputs=initInputs,
-            inputs=helper.inputs,
-            outputs=helper.outputs,
+            inputs=helper.inputs,  # type: ignore
+            outputs=helper.outputs,  # type: ignore
             datastore_records=quantum_records,
         )