Change collections.query to collections.x_query for "experimental"

python/lsst/daf/butler/_butler_collections.py

@@ -211,7 +211,7 @@ def remove_from_chain(
         raise NotImplementedError()
 
     @abstractmethod
-    def query(
+    def x_query(
         self,
         expression: str | Iterable[str],
         collection_types: Set[CollectionType] | CollectionType | None = None,

python/lsst/daf/butler/direct_butler/_direct_butler_collections.py

@@ -79,7 +79,7 @@ def remove_from_chain(
             parent_collection_name, list(ensure_iterable(child_collection_names))
         )
 
-    def query(
+    def x_query(
         self,
         expression: str | Iterable[str],
         collection_types: Set[CollectionType] | CollectionType | None = None,

python/lsst/daf/butler/remote_butler/_remote_butler_collections.py

@@ -71,7 +71,7 @@ def remove_from_chain(
     ) -> None:
         raise NotImplementedError("Not yet available")
 
-    def query(
+    def x_query(
         self,
         expression: str | Iterable[str],
         collection_types: Set[CollectionType] | CollectionType | None = None,

python/lsst/daf/butler/script/collectionChain.py

@@ -95,7 +95,7 @@ def collectionChain(
     if flatten:
         if mode not in ("redefine", "prepend", "extend"):
             raise RuntimeError(f"'flatten' flag is not allowed for {mode}")
-        children = butler.collections.query(children, flatten_chains=True)
+        children = butler.collections.x_query(children, flatten_chains=True)
 
     _modify_collection_chain(butler, mode, parent, children)
 

python/lsst/daf/butler/script/exportCalibs.py

@@ -133,7 +133,7 @@ def exportCalibs(
     collectionsToExport = []
     datasetsToExport = []
 
-    for collection in butler.collections.query(
+    for collection in butler.collections.x_query(
         collections_query,
         flatten_chains=True,
         include_chains=True,

python/lsst/daf/butler/script/queryCollections.py

@@ -71,7 +71,7 @@ def _getTable(
         dtype=(str, str, str),
     )
     butler = Butler.from_config(repo)
-    names = sorted(butler.collections.query(glob or "*", collection_types=frozenset(collection_type)))
+    names = sorted(butler.collections.x_query(glob or "*", collection_types=frozenset(collection_type)))
     if inverse:
         for name in names:
             info = butler.collections.get_info(name, include_parents=True)
@@ -153,7 +153,7 @@ def addCollection(name: str, level: int = 0) -> None:
                 for name in info.children:
                     addCollection(name, level + 1)
 
-    collections = butler.collections.query(glob or "*", collection_types=frozenset(collection_type))
+    collections = butler.collections.x_query(glob or "*", collection_types=frozenset(collection_type))
     for collection in sorted(collections):
         addCollection(collection)
     return table
@@ -166,7 +166,7 @@ def _getFlatten(
 ) -> Table:
     butler = Butler.from_config(repo)
     collectionNames = list(
-        butler.collections.query(
+        butler.collections.x_query(
             glob or "*", collection_types=frozenset(collection_type), flatten_chains=True
         )
     )

python/lsst/daf/butler/script/queryDataIds.py

@@ -170,7 +170,7 @@ def queryDataIds(
             # Need to constrain results based on dataset type and collection.
             query_collections = collections or "*"
 
-            expanded_collections = butler.collections.query(query_collections)
+            expanded_collections = butler.collections.x_query(query_collections)
 
             sub_query = query.join_dataset_search(dataset_types.pop(0), collections=expanded_collections)
             for dt in dataset_types:

python/lsst/daf/butler/script/queryDatasets.py

@@ -220,7 +220,7 @@ def getDatasets(self) -> Iterator[DatasetRef]:
         # query each time.
         dataset_types = self.butler.registry.queryDatasetTypes(datasetTypes)
         with self.butler._query() as query:
-            query_collections = self.butler.collections.query(query_collections)
+            query_collections = self.butler.collections.x_query(query_collections)
             # Accumulate over dataset types.
             for dt in dataset_types:
                 results = query.datasets(dt, collections=query_collections, find_first=self._find_first)

python/lsst/daf/butler/script/queryDimensionRecords.py

@@ -80,7 +80,7 @@ def queryDimensionRecords(
 
         if datasets:
             query_collections = collections or "*"
-            expanded_collections = butler.collections.query(query_collections)
+            expanded_collections = butler.collections.x_query(query_collections)
             dataset_types = list(butler.registry.queryDatasetTypes(datasets))
 
             sub_query = query.join_dataset_search(dataset_types.pop(0), collections=expanded_collections)

python/lsst/daf/butler/script/removeCollections.py

@@ -85,7 +85,7 @@ def _getCollectionInfo(
     """
     butler = Butler.from_config(repo, without_datastore=True)
     try:
-        names = sorted(butler.collections.query(collection, include_chains=True))
+        names = sorted(butler.collections.x_query(collection, include_chains=True))
     except MissingCollectionError:
         # Hide the error and act like no collections should be removed.
         names = []

python/lsst/daf/butler/script/removeRuns.py

@@ -87,7 +87,7 @@ def _getCollectionInfo(
     """
     butler = Butler.from_config(repo)
     try:
-        collectionNames = butler.collections.query(collection, CollectionType.RUN, include_chains=False)
+        collectionNames = butler.collections.x_query(collection, CollectionType.RUN, include_chains=False)
     except MissingCollectionError:
         # Act as if no collections matched.
         collectionNames = []

python/lsst/daf/butler/script/retrieveArtifacts.py

@@ -93,7 +93,7 @@ def retrieveArtifacts(
     dataset_types = butler.registry.queryDatasetTypes(query_types)
     refs: list[DatasetRef] = []
     with butler._query() as query:
-        expanded_collections = butler.collections.query(query_collections)
+        expanded_collections = butler.collections.x_query(query_collections)
         for dt in dataset_types:
             results = query.datasets(dt, collections=expanded_collections, find_first=find_first)
             if where:

python/lsst/daf/butler/script/transferDatasets.py

@@ -83,7 +83,7 @@ def transferDatasets(
     dataset_types = source_butler.registry.queryDatasetTypes(dataset_type_expr)
     source_refs: list[DatasetRef] = []
     with source_butler._query() as query:
-        query_collections = source_butler.collections.query(collections_expr)
+        query_collections = source_butler.collections.x_query(collections_expr)
         # Loop over dataset types and accumulate.
         for dt in dataset_types:
             results = query.datasets(dt, collections=query_collections, find_first=find_first)

python/lsst/daf/butler/transfers/_context.py

@@ -358,7 +358,7 @@ def _computeDatasetAssociations(self) -> dict[str, list[DatasetAssociation]]:
             collectionTypes = {CollectionType.TAGGED}
             if datasetType.isCalibration():
                 collectionTypes.add(CollectionType.CALIBRATION)
-            resolved_collections = self._butler.collections.query(
+            resolved_collections = self._butler.collections.x_query(
                 self._collections.keys(),
                 collection_types=collectionTypes,
                 flatten_chains=False,