MyPy fixes and a small bug fix

Fixing mypy annotations revealed a small bug in adjustQuantum with
dataset type names, this commit also fixes that.

python/lsst/pipe/base/connections.py

@@ -934,12 +934,12 @@ class AdjustQuantumHelper:
     connection-oriented mappings used inside `PipelineTaskConnections`.
     """
 
-    inputs: NamedKeyMapping[DatasetType, list[DatasetRef]]
+    inputs: NamedKeyMapping[DatasetType, tuple[DatasetRef]]
     """Mapping of regular input and prerequisite input datasets, grouped by
     `~lsst.daf.butler.DatasetType`.
     """
 
-    outputs: NamedKeyMapping[DatasetType, list[DatasetRef]]
+    outputs: NamedKeyMapping[DatasetType, tuple[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, list[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]):
@@ -1006,21 +1006,22 @@ def adjust_in_place(
                         f"({dataset_type_name}) input datasets that are not a subset of those "
                         f"it was given for data ID {data_id}."
                     )
-                adjusted_inputs[dataset_type_name] = list(updated_refs)
+                adjusted_inputs[dataset_type_name] = tuple(updated_refs)
             self.inputs = adjusted_inputs.freeze()
             self.inputs_adjusted = True
         else:
             self.inputs_adjusted = False
         if adjusted_outputs_by_connection:
-            adjusted_outputs = NamedKeyDict[DatasetType, list[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]):
                     raise RuntimeError(
                         f"adjustQuantum implementation for task with label {label} returned {name} "
                         f"({dataset_type_name}) output datasets that are not a subset of those "
                         f"it was given for data ID {data_id}."
                     )
-                adjusted_outputs[dataset_type_name] = list(updated_refs)
+                adjusted_outputs[dataset_type_name] = tuple(updated_refs)
             self.outputs = adjusted_outputs.freeze()
             self.outputs_adjusted = True
         else:

python/lsst/pipe/base/script/transfer_from_graph.py

@@ -66,8 +66,8 @@ def transfer_from_graph(
         if refs := qgraph.initOutputRefs(task_def):
             original_output_refs.update(refs)
     for qnode in qgraph:
-        for refs in qnode.quantum.outputs.values():
-            original_output_refs.update(refs)
+        for otherRefs in qnode.quantum.outputs.values():
+            original_output_refs.update(otherRefs)
 
     # Get data repository definitions from the QuantumGraph; these can have
     # different storage classes than those in the quanta.

python/lsst/pipe/base/tests/util.py

@@ -46,8 +46,8 @@ def check_output_run(graph: QuantumGraph, run: str) -> list[DatasetRef]:
         the specified run.
     """
     # Collect all inputs/outputs, so that we can build intermediate refs.
-    output_refs = []
-    input_refs = []
+    output_refs: list[DatasetRef] = []
+    input_refs: list[DatasetRef] = []
     for node in graph:
         for refs in node.quantum.outputs.values():
             output_refs += refs
@@ -61,10 +61,10 @@ def check_output_run(graph: QuantumGraph, run: str) -> list[DatasetRef]:
         if init_refs:
             input_refs += init_refs
     output_refs += graph.globalInitOutputRefs()
-    refs = [ref for ref in output_refs if ref.run != run]
+    newRefs = [ref for ref in output_refs if ref.run != run]
 
     output_ids = {ref.id for ref in output_refs}
     intermediates = [ref for ref in input_refs if ref.id in output_ids]
-    refs += [ref for ref in intermediates if ref.run != run]
+    newRefs += [ref for ref in intermediates if ref.run != run]
 
-    return refs
+    return newRefs