Pin pydantic to less than 2

python/lsst/pipe/base/_quantumContext.py

@@ -270,7 +270,7 @@ def get(
             n_connections = len(dataset)
             n_retrieved = 0
             for i, (name, ref) in enumerate(dataset):
-                if isinstance(ref, list):
+                if isinstance(ref, (list, tuple)):
                     val = []
                     n_refs = len(ref)
                     for j, r in enumerate(ref):
@@ -301,7 +301,7 @@ def get(
                     "Completed retrieval of %d datasets from %d connections", n_retrieved, n_connections
                 )
             return retVal
-        elif isinstance(dataset, list):
+        elif isinstance(dataset, (list, tuple)):
             n_datasets = len(dataset)
             retrieved = []
             for i, x in enumerate(dataset):
@@ -363,14 +363,14 @@ def put(
                 )
             for name, refs in dataset:
                 valuesAttribute = getattr(values, name)
-                if isinstance(refs, list):
+                if isinstance(refs, (list, tuple)):
                     if len(refs) != len(valuesAttribute):
                         raise ValueError(f"There must be a object to put for every Dataset ref in {name}")
                     for i, ref in enumerate(refs):
                         self._put(valuesAttribute[i], ref)
                 else:
                     self._put(valuesAttribute, refs)
-        elif isinstance(dataset, list):
+        elif isinstance(dataset, (list, tuple)):
             if not isinstance(values, Sequence):
                 raise ValueError("Values to put must be a sequence")
             if len(dataset) != len(values):
@@ -401,7 +401,7 @@ def _checkMembership(self, ref: list[DatasetRef] | DatasetRef, inout: set) -> No
             which may be important for Quanta with lots of
             `~lsst.daf.butler.DatasetRef`.
         """
-        if not isinstance(ref, list):
+        if not isinstance(ref, (list, tuple)):
             ref = [ref]
         for r in ref:
             if (r.datasetType, r.dataId) not in inout:

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

@@ -1276,49 +1276,32 @@ def updateRun(self, run: str, *, metadata_key: str | None = None, update_graph_i
         update_graph_id : `bool`, optional
             If `True` then also update graph ID with a new unique value.
         """
-        dataset_id_map = {}
 
-        def _update_output_refs_in_place(refs: list[DatasetRef], run: str) -> None:
+        def _update_refs_in_place(refs: list[DatasetRef], run: str) -> None:
             """Update list of `~lsst.daf.butler.DatasetRef` with new run and
             dataset IDs.
             """
-            new_refs = []
             for ref in refs:
-                new_ref = DatasetRef(ref.datasetType, ref.dataId, run=run, conform=False)
-                dataset_id_map[ref.id] = new_ref.id
-                new_refs.append(new_ref)
-            refs[:] = new_refs
-
-        def _update_input_refs_in_place(refs: list[DatasetRef], run: str) -> None:
-            """Update list of `~lsst.daf.butler.DatasetRef` with IDs from
-            dataset_id_map.
-            """
-            new_refs = []
-            for ref in refs:
-                if (new_id := dataset_id_map.get(ref.id)) is not None:
-                    new_ref = DatasetRef(ref.datasetType, ref.dataId, id=new_id, run=run, conform=False)
-                    new_refs.append(new_ref)
-                else:
-                    new_refs.append(ref)
-            refs[:] = new_refs
+                # hack the run to be replaced explicitly
+                object.__setattr__(ref, "run", run)
 
         # Loop through all outputs and update their datasets.
         for node in self._connectedQuanta:
             for refs in node.quantum.outputs.values():
-                _update_output_refs_in_place(refs, run)
+                _update_refs_in_place(refs, run)
 
         for refs in self._initOutputRefs.values():
-            _update_output_refs_in_place(refs, run)
+            _update_refs_in_place(refs, run)
 
-        _update_output_refs_in_place(self._globalInitOutputRefs, run)
+        _update_refs_in_place(self._globalInitOutputRefs, run)
 
         # Update all intermediates from their matching outputs.
         for node in self._connectedQuanta:
             for refs in node.quantum.inputs.values():
-                _update_input_refs_in_place(refs, run)
+                _update_refs_in_place(refs, run)
 
         for refs in self._initInputRefs.values():
-            _update_input_refs_in_place(refs, run)
+            _update_refs_in_place(refs, run)
 
         if update_graph_id:
             self._buildId = BuildId(f"{time.time()}-{os.getpid()}")

requirements.txt

@@ -1,5 +1,5 @@
 pyyaml >= 5.1
-pydantic
+pydantic < 2
 numpy >= 1.17
 networkx
 frozendict