Coverage for python/lsst/daf/butler/registries/sql.py: 13%
462 statements
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1# This file is part of daf_butler.
2#
3# Developed for the LSST Data Management System.
4# This product includes software developed by the LSST Project
5# (http://www.lsst.org).
6# See the COPYRIGHT file at the top-level directory of this distribution
7# for details of code ownership.
8#
9# This program is free software: you can redistribute it and/or modify
10# it under the terms of the GNU General Public License as published by
11# the Free Software Foundation, either version 3 of the License, or
12# (at your option) any later version.
13#
14# This program is distributed in the hope that it will be useful,
15# but WITHOUT ANY WARRANTY; without even the implied warranty of
16# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
17# GNU General Public License for more details.
18#
19# You should have received a copy of the GNU General Public License
20# along with this program. If not, see <http://www.gnu.org/licenses/>.
22from __future__ import annotations
24__all__ = (
25 "SqlRegistry",
26)
28from collections import defaultdict
29import contextlib
30import logging
31from typing import (
32 Any,
33 Dict,
34 Iterable,
35 Iterator,
36 List,
37 Mapping,
38 Optional,
39 Set,
40 TYPE_CHECKING,
41 Union,
42)
44import sqlalchemy
46from ..core import (
47 ButlerURI,
48 Config,
49 DataCoordinate,
50 DataCoordinateIterable,
51 DataId,
52 DatasetAssociation,
53 DatasetId,
54 DatasetRef,
55 DatasetType,
56 ddl,
57 Dimension,
58 DimensionConfig,
59 DimensionElement,
60 DimensionGraph,
61 DimensionRecord,
62 DimensionUniverse,
63 NamedKeyMapping,
64 NameLookupMapping,
65 Progress,
66 StorageClassFactory,
67 Timespan,
68)
69from ..core.utils import iterable, transactional
71from ..registry import (
72 Registry,
73 RegistryConfig,
74 CollectionType,
75 RegistryDefaults,
76 ConflictingDefinitionError,
77 InconsistentDataIdError,
78 OrphanedRecordError,
79 CollectionSearch,
80)
81from ..registry import queries
82from ..registry.wildcards import CategorizedWildcard, CollectionQuery, Ellipsis
83from ..registry.summaries import CollectionSummary
84from ..registry.managers import RegistryManagerTypes, RegistryManagerInstances
85from ..registry.interfaces import ChainedCollectionRecord, DatasetIdGenEnum, RunRecord
87if TYPE_CHECKING: 87 ↛ 88line 87 didn't jump to line 88, because the condition on line 87 was never true
88 from .._butlerConfig import ButlerConfig
89 from ..registry.interfaces import (
90 CollectionRecord,
91 Database,
92 DatastoreRegistryBridgeManager,
93 )
96_LOG = logging.getLogger(__name__)
99class SqlRegistry(Registry):
100 """Registry implementation based on SQLAlchemy.
102 Parameters
103 ----------
104 database : `Database`
105 Database instance to store Registry.
106 defaults : `RegistryDefaults`
107 Default collection search path and/or output `~CollectionType.RUN`
108 collection.
109 managers : `RegistryManagerInstances`
110 All the managers required for this registry.
111 """
113 defaultConfigFile: Optional[str] = None
114 """Path to configuration defaults. Accessed within the ``configs`` resource
115 or relative to a search path. Can be None if no defaults specified.
116 """
118 @classmethod
119 def createFromConfig(cls, config: Optional[Union[RegistryConfig, str]] = None,
120 dimensionConfig: Optional[Union[DimensionConfig, str]] = None,
121 butlerRoot: Optional[str] = None) -> Registry:
122 """Create registry database and return `SqlRegistry` instance.
124 This method initializes database contents, database must be empty
125 prior to calling this method.
127 Parameters
128 ----------
129 config : `RegistryConfig` or `str`, optional
130 Registry configuration, if missing then default configuration will
131 be loaded from registry.yaml.
132 dimensionConfig : `DimensionConfig` or `str`, optional
133 Dimensions configuration, if missing then default configuration
134 will be loaded from dimensions.yaml.
135 butlerRoot : `str`, optional
136 Path to the repository root this `SqlRegistry` will manage.
138 Returns
139 -------
140 registry : `SqlRegistry`
141 A new `SqlRegistry` instance.
142 """
143 config = cls.forceRegistryConfig(config)
144 config.replaceRoot(butlerRoot)
146 if isinstance(dimensionConfig, str):
147 dimensionConfig = DimensionConfig(config)
148 elif dimensionConfig is None:
149 dimensionConfig = DimensionConfig()
150 elif not isinstance(dimensionConfig, DimensionConfig):
151 raise TypeError(f"Incompatible Dimension configuration type: {type(dimensionConfig)}")
153 DatabaseClass = config.getDatabaseClass()
154 database = DatabaseClass.fromUri(str(config.connectionString), origin=config.get("origin", 0),
155 namespace=config.get("namespace"))
156 managerTypes = RegistryManagerTypes.fromConfig(config)
157 managers = managerTypes.makeRepo(database, dimensionConfig)
158 return cls(database, RegistryDefaults(), managers)
160 @classmethod
161 def fromConfig(cls, config: Union[ButlerConfig, RegistryConfig, Config, str],
162 butlerRoot: Optional[Union[str, ButlerURI]] = None, writeable: bool = True,
163 defaults: Optional[RegistryDefaults] = None) -> Registry:
164 """Create `Registry` subclass instance from `config`.
166 Registry database must be inbitialized prior to calling this method.
168 Parameters
169 ----------
170 config : `ButlerConfig`, `RegistryConfig`, `Config` or `str`
171 Registry configuration
172 butlerRoot : `str` or `ButlerURI`, optional
173 Path to the repository root this `Registry` will manage.
174 writeable : `bool`, optional
175 If `True` (default) create a read-write connection to the database.
176 defaults : `RegistryDefaults`, optional
177 Default collection search path and/or output `~CollectionType.RUN`
178 collection.
180 Returns
181 -------
182 registry : `SqlRegistry` (subclass)
183 A new `SqlRegistry` subclass instance.
184 """
185 config = cls.forceRegistryConfig(config)
186 config.replaceRoot(butlerRoot)
187 DatabaseClass = config.getDatabaseClass()
188 database = DatabaseClass.fromUri(str(config.connectionString), origin=config.get("origin", 0),
189 namespace=config.get("namespace"), writeable=writeable)
190 managerTypes = RegistryManagerTypes.fromConfig(config)
191 managers = managerTypes.loadRepo(database)
192 if defaults is None:
193 defaults = RegistryDefaults()
194 return cls(database, defaults, managers)
196 def __init__(self, database: Database, defaults: RegistryDefaults, managers: RegistryManagerInstances):
197 self._db = database
198 self._managers = managers
199 self.storageClasses = StorageClassFactory()
200 # Intentionally invoke property setter to initialize defaults. This
201 # can only be done after most of the rest of Registry has already been
202 # initialized, and must be done before the property getter is used.
203 self.defaults = defaults
205 def __str__(self) -> str:
206 return str(self._db)
208 def __repr__(self) -> str:
209 return f"SqlRegistry({self._db!r}, {self.dimensions!r})"
211 def isWriteable(self) -> bool:
212 # Docstring inherited from lsst.daf.butler.registry.Registry
213 return self._db.isWriteable()
215 def copy(self, defaults: Optional[RegistryDefaults] = None) -> Registry:
216 # Docstring inherited from lsst.daf.butler.registry.Registry
217 if defaults is None:
218 # No need to copy, because `RegistryDefaults` is immutable; we
219 # effectively copy on write.
220 defaults = self.defaults
221 return type(self)(self._db, defaults, self._managers)
223 @property
224 def dimensions(self) -> DimensionUniverse:
225 # Docstring inherited from lsst.daf.butler.registry.Registry
226 return self._managers.dimensions.universe
228 def refresh(self) -> None:
229 # Docstring inherited from lsst.daf.butler.registry.Registry
230 self._managers.refresh()
232 @contextlib.contextmanager
233 def transaction(self, *, savepoint: bool = False) -> Iterator[None]:
234 # Docstring inherited from lsst.daf.butler.registry.Registry
235 try:
236 with self._db.transaction(savepoint=savepoint):
237 yield
238 except BaseException:
239 # TODO: this clears the caches sometimes when we wouldn't actually
240 # need to. Can we avoid that?
241 self._managers.dimensions.clearCaches()
242 raise
244 def resetConnectionPool(self) -> None:
245 """Reset SQLAlchemy connection pool for `SqlRegistry` database.
247 This operation is useful when using registry with fork-based
248 multiprocessing. To use registry across fork boundary one has to make
249 sure that there are no currently active connections (no session or
250 transaction is in progress) and connection pool is reset using this
251 method. This method should be called by the child process immediately
252 after the fork.
253 """
254 self._db._engine.dispose()
256 def registerOpaqueTable(self, tableName: str, spec: ddl.TableSpec) -> None:
257 """Add an opaque (to the `Registry`) table for use by a `Datastore` or
258 other data repository client.
260 Opaque table records can be added via `insertOpaqueData`, retrieved via
261 `fetchOpaqueData`, and removed via `deleteOpaqueData`.
263 Parameters
264 ----------
265 tableName : `str`
266 Logical name of the opaque table. This may differ from the
267 actual name used in the database by a prefix and/or suffix.
268 spec : `ddl.TableSpec`
269 Specification for the table to be added.
270 """
271 self._managers.opaque.register(tableName, spec)
273 @transactional
274 def insertOpaqueData(self, tableName: str, *data: dict) -> None:
275 """Insert records into an opaque table.
277 Parameters
278 ----------
279 tableName : `str`
280 Logical name of the opaque table. Must match the name used in a
281 previous call to `registerOpaqueTable`.
282 data
283 Each additional positional argument is a dictionary that represents
284 a single row to be added.
285 """
286 self._managers.opaque[tableName].insert(*data)
288 def fetchOpaqueData(self, tableName: str, **where: Any) -> Iterator[dict]:
289 """Retrieve records from an opaque table.
291 Parameters
292 ----------
293 tableName : `str`
294 Logical name of the opaque table. Must match the name used in a
295 previous call to `registerOpaqueTable`.
296 where
297 Additional keyword arguments are interpreted as equality
298 constraints that restrict the returned rows (combined with AND);
299 keyword arguments are column names and values are the values they
300 must have.
302 Yields
303 ------
304 row : `dict`
305 A dictionary representing a single result row.
306 """
307 yield from self._managers.opaque[tableName].fetch(**where)
309 @transactional
310 def deleteOpaqueData(self, tableName: str, **where: Any) -> None:
311 """Remove records from an opaque table.
313 Parameters
314 ----------
315 tableName : `str`
316 Logical name of the opaque table. Must match the name used in a
317 previous call to `registerOpaqueTable`.
318 where
319 Additional keyword arguments are interpreted as equality
320 constraints that restrict the deleted rows (combined with AND);
321 keyword arguments are column names and values are the values they
322 must have.
323 """
324 self._managers.opaque[tableName].delete(where.keys(), where)
326 def registerCollection(self, name: str, type: CollectionType = CollectionType.TAGGED,
327 doc: Optional[str] = None) -> bool:
328 # Docstring inherited from lsst.daf.butler.registry.Registry
329 _, registered = self._managers.collections.register(name, type, doc=doc)
330 return registered
332 def getCollectionType(self, name: str) -> CollectionType:
333 # Docstring inherited from lsst.daf.butler.registry.Registry
334 return self._managers.collections.find(name).type
336 def _get_collection_record(self, name: str) -> CollectionRecord:
337 # Docstring inherited from lsst.daf.butler.registry.Registry
338 return self._managers.collections.find(name)
340 def registerRun(self, name: str, doc: Optional[str] = None) -> bool:
341 # Docstring inherited from lsst.daf.butler.registry.Registry
342 _, registered = self._managers.collections.register(name, CollectionType.RUN, doc=doc)
343 return registered
345 @transactional
346 def removeCollection(self, name: str) -> None:
347 # Docstring inherited from lsst.daf.butler.registry.Registry
348 self._managers.collections.remove(name)
350 def getCollectionChain(self, parent: str) -> CollectionSearch:
351 # Docstring inherited from lsst.daf.butler.registry.Registry
352 record = self._managers.collections.find(parent)
353 if record.type is not CollectionType.CHAINED:
354 raise TypeError(f"Collection '{parent}' has type {record.type.name}, not CHAINED.")
355 assert isinstance(record, ChainedCollectionRecord)
356 return record.children
358 @transactional
359 def setCollectionChain(self, parent: str, children: Any, *, flatten: bool = False) -> None:
360 # Docstring inherited from lsst.daf.butler.registry.Registry
361 record = self._managers.collections.find(parent)
362 if record.type is not CollectionType.CHAINED:
363 raise TypeError(f"Collection '{parent}' has type {record.type.name}, not CHAINED.")
364 assert isinstance(record, ChainedCollectionRecord)
365 children = CollectionSearch.fromExpression(children)
366 if children != record.children or flatten:
367 record.update(self._managers.collections, children, flatten=flatten)
369 def getCollectionDocumentation(self, collection: str) -> Optional[str]:
370 # Docstring inherited from lsst.daf.butler.registry.Registry
371 return self._managers.collections.getDocumentation(self._managers.collections.find(collection).key)
373 def setCollectionDocumentation(self, collection: str, doc: Optional[str]) -> None:
374 # Docstring inherited from lsst.daf.butler.registry.Registry
375 self._managers.collections.setDocumentation(self._managers.collections.find(collection).key, doc)
377 def getCollectionSummary(self, collection: str) -> CollectionSummary:
378 # Docstring inherited from lsst.daf.butler.registry.Registry
379 record = self._managers.collections.find(collection)
380 return self._managers.datasets.getCollectionSummary(record)
382 def registerDatasetType(self, datasetType: DatasetType) -> bool:
383 # Docstring inherited from lsst.daf.butler.registry.Registry
384 _, inserted = self._managers.datasets.register(datasetType)
385 return inserted
387 def removeDatasetType(self, name: str) -> None:
388 # Docstring inherited from lsst.daf.butler.registry.Registry
389 self._managers.datasets.remove(name)
391 def getDatasetType(self, name: str) -> DatasetType:
392 # Docstring inherited from lsst.daf.butler.registry.Registry
393 return self._managers.datasets[name].datasetType
395 def supportsIdGenerationMode(self, mode: DatasetIdGenEnum) -> bool:
396 # Docstring inherited from lsst.daf.butler.registry.Registry
397 return self._managers.datasets.supportsIdGenerationMode(mode)
399 def findDataset(self, datasetType: Union[DatasetType, str], dataId: Optional[DataId] = None, *,
400 collections: Any = None, timespan: Optional[Timespan] = None,
401 **kwargs: Any) -> Optional[DatasetRef]:
402 # Docstring inherited from lsst.daf.butler.registry.Registry
403 if isinstance(datasetType, DatasetType):
404 storage = self._managers.datasets[datasetType.name]
405 else:
406 storage = self._managers.datasets[datasetType]
407 dataId = DataCoordinate.standardize(dataId, graph=storage.datasetType.dimensions,
408 universe=self.dimensions, defaults=self.defaults.dataId,
409 **kwargs)
410 if collections is None:
411 if not self.defaults.collections:
412 raise TypeError("No collections provided to findDataset, "
413 "and no defaults from registry construction.")
414 collections = self.defaults.collections
415 else:
416 collections = CollectionSearch.fromExpression(collections)
417 for collectionRecord in collections.iter(self._managers.collections):
418 if (collectionRecord.type is CollectionType.CALIBRATION
419 and (not storage.datasetType.isCalibration() or timespan is None)):
420 continue
421 result = storage.find(collectionRecord, dataId, timespan=timespan)
422 if result is not None:
423 return result
425 return None
427 @transactional
428 def insertDatasets(self, datasetType: Union[DatasetType, str], dataIds: Iterable[DataId],
429 run: Optional[str] = None, expand: bool = True,
430 idGenerationMode: DatasetIdGenEnum = DatasetIdGenEnum.UNIQUE) -> List[DatasetRef]:
431 # Docstring inherited from lsst.daf.butler.registry.Registry
432 if isinstance(datasetType, DatasetType):
433 storage = self._managers.datasets.find(datasetType.name)
434 if storage is None:
435 raise LookupError(f"DatasetType '{datasetType}' has not been registered.")
436 else:
437 storage = self._managers.datasets.find(datasetType)
438 if storage is None:
439 raise LookupError(f"DatasetType with name '{datasetType}' has not been registered.")
440 if run is None:
441 if self.defaults.run is None:
442 raise TypeError("No run provided to insertDatasets, "
443 "and no default from registry construction.")
444 run = self.defaults.run
445 runRecord = self._managers.collections.find(run)
446 if runRecord.type is not CollectionType.RUN:
447 raise TypeError(f"Given collection is of type {runRecord.type.name}; RUN collection required.")
448 assert isinstance(runRecord, RunRecord)
449 progress = Progress("daf.butler.Registry.insertDatasets", level=logging.DEBUG)
450 if expand:
451 expandedDataIds = [self.expandDataId(dataId, graph=storage.datasetType.dimensions)
452 for dataId in progress.wrap(dataIds,
453 f"Expanding {storage.datasetType.name} data IDs")]
454 else:
455 expandedDataIds = [DataCoordinate.standardize(dataId, graph=storage.datasetType.dimensions)
456 for dataId in dataIds]
457 try:
458 refs = list(storage.insert(runRecord, expandedDataIds, idGenerationMode))
459 except sqlalchemy.exc.IntegrityError as err:
460 raise ConflictingDefinitionError(f"A database constraint failure was triggered by inserting "
461 f"one or more datasets of type {storage.datasetType} into "
462 f"collection '{run}'. "
463 f"This probably means a dataset with the same data ID "
464 f"and dataset type already exists, but it may also mean a "
465 f"dimension row is missing.") from err
466 return refs
468 @transactional
469 def _importDatasets(self, datasets: Iterable[DatasetRef], expand: bool = True,
470 idGenerationMode: DatasetIdGenEnum = DatasetIdGenEnum.UNIQUE,
471 reuseIds: bool = False) -> List[DatasetRef]:
472 # Docstring inherited from lsst.daf.butler.registry.Registry
473 datasets = list(datasets)
474 if not datasets:
475 # nothing to do
476 return []
478 # find dataset type
479 datasetTypes = set(dataset.datasetType for dataset in datasets)
480 if len(datasetTypes) != 1:
481 raise ValueError(f"Multiple dataset types in input datasets: {datasetTypes}")
482 datasetType = datasetTypes.pop()
484 # get storage handler for this dataset type
485 storage = self._managers.datasets.find(datasetType.name)
486 if storage is None:
487 raise LookupError(f"DatasetType '{datasetType}' has not been registered.")
489 # find run name
490 runs = set(dataset.run for dataset in datasets)
491 if len(runs) != 1:
492 raise ValueError(f"Multiple run names in input datasets: {runs}")
493 run = runs.pop()
494 if run is None:
495 if self.defaults.run is None:
496 raise TypeError("No run provided to ingestDatasets, "
497 "and no default from registry construction.")
498 run = self.defaults.run
500 runRecord = self._managers.collections.find(run)
501 if runRecord.type is not CollectionType.RUN:
502 raise TypeError(f"Given collection '{runRecord.name}' is of type {runRecord.type.name};"
503 " RUN collection required.")
504 assert isinstance(runRecord, RunRecord)
506 progress = Progress("daf.butler.Registry.insertDatasets", level=logging.DEBUG)
507 if expand:
508 expandedDatasets = [
509 dataset.expanded(self.expandDataId(dataset.dataId, graph=storage.datasetType.dimensions))
510 for dataset in progress.wrap(datasets, f"Expanding {storage.datasetType.name} data IDs")]
511 else:
512 expandedDatasets = [
513 DatasetRef(datasetType, dataset.dataId, id=dataset.id, run=dataset.run, conform=True)
514 for dataset in datasets
515 ]
517 try:
518 refs = list(storage.import_(runRecord, expandedDatasets, idGenerationMode, reuseIds))
519 except sqlalchemy.exc.IntegrityError as err:
520 raise ConflictingDefinitionError(f"A database constraint failure was triggered by inserting "
521 f"one or more datasets of type {storage.datasetType} into "
522 f"collection '{run}'. "
523 f"This probably means a dataset with the same data ID "
524 f"and dataset type already exists, but it may also mean a "
525 f"dimension row is missing.") from err
526 return refs
528 def getDataset(self, id: DatasetId) -> Optional[DatasetRef]:
529 # Docstring inherited from lsst.daf.butler.registry.Registry
530 return self._managers.datasets.getDatasetRef(id)
532 @transactional
533 def removeDatasets(self, refs: Iterable[DatasetRef]) -> None:
534 # Docstring inherited from lsst.daf.butler.registry.Registry
535 progress = Progress("lsst.daf.butler.Registry.removeDatasets", level=logging.DEBUG)
536 for datasetType, refsForType in progress.iter_item_chunks(DatasetRef.groupByType(refs).items(),
537 desc="Removing datasets by type"):
538 storage = self._managers.datasets[datasetType.name]
539 try:
540 storage.delete(refsForType)
541 except sqlalchemy.exc.IntegrityError as err:
542 raise OrphanedRecordError("One or more datasets is still "
543 "present in one or more Datastores.") from err
545 @transactional
546 def associate(self, collection: str, refs: Iterable[DatasetRef]) -> None:
547 # Docstring inherited from lsst.daf.butler.registry.Registry
548 progress = Progress("lsst.daf.butler.Registry.associate", level=logging.DEBUG)
549 collectionRecord = self._managers.collections.find(collection)
550 if collectionRecord.type is not CollectionType.TAGGED:
551 raise TypeError(f"Collection '{collection}' has type {collectionRecord.type.name}, not TAGGED.")
552 for datasetType, refsForType in progress.iter_item_chunks(DatasetRef.groupByType(refs).items(),
553 desc="Associating datasets by type"):
554 storage = self._managers.datasets[datasetType.name]
555 try:
556 storage.associate(collectionRecord, refsForType)
557 except sqlalchemy.exc.IntegrityError as err:
558 raise ConflictingDefinitionError(
559 f"Constraint violation while associating dataset of type {datasetType.name} with "
560 f"collection {collection}. This probably means that one or more datasets with the same "
561 f"dataset type and data ID already exist in the collection, but it may also indicate "
562 f"that the datasets do not exist."
563 ) from err
565 @transactional
566 def disassociate(self, collection: str, refs: Iterable[DatasetRef]) -> None:
567 # Docstring inherited from lsst.daf.butler.registry.Registry
568 progress = Progress("lsst.daf.butler.Registry.disassociate", level=logging.DEBUG)
569 collectionRecord = self._managers.collections.find(collection)
570 if collectionRecord.type is not CollectionType.TAGGED:
571 raise TypeError(f"Collection '{collection}' has type {collectionRecord.type.name}; "
572 "expected TAGGED.")
573 for datasetType, refsForType in progress.iter_item_chunks(DatasetRef.groupByType(refs).items(),
574 desc="Disassociating datasets by type"):
575 storage = self._managers.datasets[datasetType.name]
576 storage.disassociate(collectionRecord, refsForType)
578 @transactional
579 def certify(self, collection: str, refs: Iterable[DatasetRef], timespan: Timespan) -> None:
580 # Docstring inherited from lsst.daf.butler.registry.Registry
581 progress = Progress("lsst.daf.butler.Registry.certify", level=logging.DEBUG)
582 collectionRecord = self._managers.collections.find(collection)
583 for datasetType, refsForType in progress.iter_item_chunks(DatasetRef.groupByType(refs).items(),
584 desc="Certifying datasets by type"):
585 storage = self._managers.datasets[datasetType.name]
586 storage.certify(collectionRecord, refsForType, timespan)
588 @transactional
589 def decertify(self, collection: str, datasetType: Union[str, DatasetType], timespan: Timespan, *,
590 dataIds: Optional[Iterable[DataId]] = None) -> None:
591 # Docstring inherited from lsst.daf.butler.registry.Registry
592 collectionRecord = self._managers.collections.find(collection)
593 if isinstance(datasetType, str):
594 storage = self._managers.datasets[datasetType]
595 else:
596 storage = self._managers.datasets[datasetType.name]
597 standardizedDataIds = None
598 if dataIds is not None:
599 standardizedDataIds = [DataCoordinate.standardize(d, graph=storage.datasetType.dimensions)
600 for d in dataIds]
601 storage.decertify(collectionRecord, timespan, dataIds=standardizedDataIds)
603 def getDatastoreBridgeManager(self) -> DatastoreRegistryBridgeManager:
604 """Return an object that allows a new `Datastore` instance to
605 communicate with this `Registry`.
607 Returns
608 -------
609 manager : `DatastoreRegistryBridgeManager`
610 Object that mediates communication between this `Registry` and its
611 associated datastores.
612 """
613 return self._managers.datastores
615 def getDatasetLocations(self, ref: DatasetRef) -> Iterable[str]:
616 # Docstring inherited from lsst.daf.butler.registry.Registry
617 return self._managers.datastores.findDatastores(ref)
619 def expandDataId(self, dataId: Optional[DataId] = None, *, graph: Optional[DimensionGraph] = None,
620 records: Optional[NameLookupMapping[DimensionElement, Optional[DimensionRecord]]] = None,
621 withDefaults: bool = True,
622 **kwargs: Any) -> DataCoordinate:
623 # Docstring inherited from lsst.daf.butler.registry.Registry
624 if not withDefaults:
625 defaults = None
626 else:
627 defaults = self.defaults.dataId
628 standardized = DataCoordinate.standardize(dataId, graph=graph, universe=self.dimensions,
629 defaults=defaults, **kwargs)
630 if standardized.hasRecords():
631 return standardized
632 if records is None:
633 records = {}
634 elif isinstance(records, NamedKeyMapping):
635 records = records.byName()
636 else:
637 records = dict(records)
638 if isinstance(dataId, DataCoordinate) and dataId.hasRecords():
639 records.update(dataId.records.byName())
640 keys = standardized.byName()
641 for element in standardized.graph.primaryKeyTraversalOrder:
642 record = records.get(element.name, ...) # Use ... to mean not found; None might mean NULL
643 if record is ...:
644 if isinstance(element, Dimension) and keys.get(element.name) is None:
645 if element in standardized.graph.required:
646 raise LookupError(
647 f"No value or null value for required dimension {element.name}."
648 )
649 keys[element.name] = None
650 record = None
651 else:
652 storage = self._managers.dimensions[element]
653 dataIdSet = DataCoordinateIterable.fromScalar(
654 DataCoordinate.standardize(keys, graph=element.graph)
655 )
656 fetched = tuple(storage.fetch(dataIdSet))
657 try:
658 (record,) = fetched
659 except ValueError:
660 record = None
661 records[element.name] = record
662 if record is not None:
663 for d in element.implied:
664 value = getattr(record, d.name)
665 if keys.setdefault(d.name, value) != value:
666 raise InconsistentDataIdError(
667 f"Data ID {standardized} has {d.name}={keys[d.name]!r}, "
668 f"but {element.name} implies {d.name}={value!r}."
669 )
670 else:
671 if element in standardized.graph.required:
672 raise LookupError(
673 f"Could not fetch record for required dimension {element.name} via keys {keys}."
674 )
675 if element.alwaysJoin:
676 raise InconsistentDataIdError(
677 f"Could not fetch record for element {element.name} via keys {keys}, ",
678 "but it is marked alwaysJoin=True; this means one or more dimensions are not "
679 "related."
680 )
681 for d in element.implied:
682 keys.setdefault(d.name, None)
683 records.setdefault(d.name, None)
684 return DataCoordinate.standardize(keys, graph=standardized.graph).expanded(records=records)
686 def insertDimensionData(self, element: Union[DimensionElement, str],
687 *data: Union[Mapping[str, Any], DimensionRecord],
688 conform: bool = True,
689 replace: bool = False) -> None:
690 # Docstring inherited from lsst.daf.butler.registry.Registry
691 if conform:
692 if isinstance(element, str):
693 element = self.dimensions[element]
694 records = [row if isinstance(row, DimensionRecord) else element.RecordClass(**row)
695 for row in data]
696 else:
697 # Ignore typing since caller said to trust them with conform=False.
698 records = data # type: ignore
699 storage = self._managers.dimensions[element] # type: ignore
700 storage.insert(*records, replace=replace)
702 def syncDimensionData(self, element: Union[DimensionElement, str],
703 row: Union[Mapping[str, Any], DimensionRecord],
704 conform: bool = True,
705 update: bool = False) -> Union[bool, Dict[str, Any]]:
706 # Docstring inherited from lsst.daf.butler.registry.Registry
707 if conform:
708 if isinstance(element, str):
709 element = self.dimensions[element]
710 record = row if isinstance(row, DimensionRecord) else element.RecordClass(**row)
711 else:
712 # Ignore typing since caller said to trust them with conform=False.
713 record = row # type: ignore
714 storage = self._managers.dimensions[element] # type: ignore
715 return storage.sync(record, update=update)
717 def queryDatasetTypes(self, expression: Any = ..., *, components: Optional[bool] = None
718 ) -> Iterator[DatasetType]:
719 # Docstring inherited from lsst.daf.butler.registry.Registry
720 wildcard = CategorizedWildcard.fromExpression(expression, coerceUnrecognized=lambda d: d.name)
721 if wildcard is Ellipsis:
722 for datasetType in self._managers.datasets:
723 # The dataset type can no longer be a component
724 yield datasetType
725 if components:
726 # Automatically create the component dataset types
727 try:
728 componentsForDatasetType = datasetType.makeAllComponentDatasetTypes()
729 except KeyError as err:
730 _LOG.warning(f"Could not load storage class {err} for {datasetType.name}; "
731 "if it has components they will not be included in query results.")
732 else:
733 yield from componentsForDatasetType
734 return
735 done: Set[str] = set()
736 for name in wildcard.strings:
737 storage = self._managers.datasets.find(name)
738 if storage is not None:
739 done.add(storage.datasetType.name)
740 yield storage.datasetType
741 if wildcard.patterns:
742 # If components (the argument) is None, we'll save component
743 # dataset that we might want to match, but only if their parents
744 # didn't get included.
745 componentsForLater = []
746 for registeredDatasetType in self._managers.datasets:
747 # Components are not stored in registry so expand them here
748 allDatasetTypes = [registeredDatasetType]
749 try:
750 allDatasetTypes.extend(registeredDatasetType.makeAllComponentDatasetTypes())
751 except KeyError as err:
752 _LOG.warning(f"Could not load storage class {err} for {registeredDatasetType.name}; "
753 "if it has components they will not be included in query results.")
754 for datasetType in allDatasetTypes:
755 if datasetType.name in done:
756 continue
757 parentName, componentName = datasetType.nameAndComponent()
758 if componentName is not None and not components:
759 if components is None and parentName not in done:
760 componentsForLater.append(datasetType)
761 continue
762 if any(p.fullmatch(datasetType.name) for p in wildcard.patterns):
763 done.add(datasetType.name)
764 yield datasetType
765 # Go back and try to match saved components.
766 for datasetType in componentsForLater:
767 parentName, _ = datasetType.nameAndComponent()
768 if parentName not in done and any(p.fullmatch(datasetType.name) for p in wildcard.patterns):
769 yield datasetType
771 def queryCollections(self, expression: Any = ...,
772 datasetType: Optional[DatasetType] = None,
773 collectionTypes: Iterable[CollectionType] = CollectionType.all(),
774 flattenChains: bool = False,
775 includeChains: Optional[bool] = None) -> Iterator[str]:
776 # Docstring inherited from lsst.daf.butler.registry.Registry
778 # Right now the datasetTypes argument is completely ignored, but that
779 # is consistent with its [lack of] guarantees. DM-24939 or a follow-up
780 # ticket will take care of that.
781 query = CollectionQuery.fromExpression(expression)
782 for record in query.iter(self._managers.collections, collectionTypes=frozenset(collectionTypes),
783 flattenChains=flattenChains, includeChains=includeChains):
784 yield record.name
786 def _makeQueryBuilder(self, summary: queries.QuerySummary) -> queries.QueryBuilder:
787 """Return a `QueryBuilder` instance capable of constructing and
788 managing more complex queries than those obtainable via `Registry`
789 interfaces.
791 This is an advanced interface; downstream code should prefer
792 `Registry.queryDataIds` and `Registry.queryDatasets` whenever those
793 are sufficient.
795 Parameters
796 ----------
797 summary : `queries.QuerySummary`
798 Object describing and categorizing the full set of dimensions that
799 will be included in the query.
801 Returns
802 -------
803 builder : `queries.QueryBuilder`
804 Object that can be used to construct and perform advanced queries.
805 """
806 return queries.QueryBuilder(
807 summary,
808 queries.RegistryManagers(
809 collections=self._managers.collections,
810 dimensions=self._managers.dimensions,
811 datasets=self._managers.datasets,
812 TimespanReprClass=self._db.getTimespanRepresentation(),
813 ),
814 )
816 def queryDatasets(self, datasetType: Any, *,
817 collections: Any = None,
818 dimensions: Optional[Iterable[Union[Dimension, str]]] = None,
819 dataId: Optional[DataId] = None,
820 where: Optional[str] = None,
821 findFirst: bool = False,
822 components: Optional[bool] = None,
823 bind: Optional[Mapping[str, Any]] = None,
824 check: bool = True,
825 **kwargs: Any) -> queries.DatasetQueryResults:
826 # Docstring inherited from lsst.daf.butler.registry.Registry
828 # Standardize the collections expression.
829 if collections is None:
830 if not self.defaults.collections:
831 raise TypeError("No collections provided to findDataset, "
832 "and no defaults from registry construction.")
833 collections = self.defaults.collections
834 elif findFirst:
835 collections = CollectionSearch.fromExpression(collections)
836 else:
837 collections = CollectionQuery.fromExpression(collections)
838 # Standardize and expand the data ID provided as a constraint.
839 standardizedDataId = self.expandDataId(dataId, **kwargs)
841 # We can only query directly if given a non-component DatasetType
842 # instance. If we were given an expression or str or a component
843 # DatasetType instance, we'll populate this dict, recurse, and return.
844 # If we already have a non-component DatasetType, it will remain None
845 # and we'll run the query directly.
846 composition: Optional[
847 Dict[
848 DatasetType, # parent dataset type
849 List[Optional[str]] # component name, or None for parent
850 ]
851 ] = None
852 if not isinstance(datasetType, DatasetType):
853 # We were given a dataset type expression (which may be as simple
854 # as a str). Loop over all matching datasets, delegating handling
855 # of the `components` argument to queryDatasetTypes, as we populate
856 # the composition dict.
857 composition = defaultdict(list)
858 for trueDatasetType in self.queryDatasetTypes(datasetType, components=components):
859 parentName, componentName = trueDatasetType.nameAndComponent()
860 if componentName is not None:
861 parentDatasetType = self.getDatasetType(parentName)
862 composition.setdefault(parentDatasetType, []).append(componentName)
863 else:
864 composition.setdefault(trueDatasetType, []).append(None)
865 if not composition:
866 return queries.ChainedDatasetQueryResults(
867 [],
868 doomed_by=[f"No registered dataset type matching {t!r} found."
869 for t in iterable(datasetType)],
870 )
871 elif datasetType.isComponent():
872 # We were given a true DatasetType instance, but it's a component.
873 # the composition dict will have exactly one item.
874 parentName, componentName = datasetType.nameAndComponent()
875 parentDatasetType = self.getDatasetType(parentName)
876 composition = {parentDatasetType: [componentName]}
877 if composition is not None:
878 # We need to recurse. Do that once for each parent dataset type.
879 chain = []
880 for parentDatasetType, componentNames in composition.items():
881 parentResults = self.queryDatasets(
882 parentDatasetType,
883 collections=collections,
884 dimensions=dimensions,
885 dataId=standardizedDataId,
886 where=where,
887 bind=bind,
888 findFirst=findFirst,
889 check=check,
890 )
891 assert isinstance(parentResults, queries.ParentDatasetQueryResults), \
892 "Should always be true if passing in a DatasetType instance, and we are."
893 chain.append(
894 parentResults.withComponents(componentNames)
895 )
896 return queries.ChainedDatasetQueryResults(chain)
897 # If we get here, there's no need to recurse (or we are already
898 # recursing; there can only ever be one level of recursion).
900 # The full set of dimensions in the query is the combination of those
901 # needed for the DatasetType and those explicitly requested, if any.
902 requestedDimensionNames = set(datasetType.dimensions.names)
903 if dimensions is not None:
904 requestedDimensionNames.update(self.dimensions.extract(dimensions).names)
905 # Construct the summary structure needed to construct a QueryBuilder.
906 summary = queries.QuerySummary(
907 requested=DimensionGraph(self.dimensions, names=requestedDimensionNames),
908 dataId=standardizedDataId,
909 expression=where,
910 bind=bind,
911 defaults=self.defaults.dataId,
912 check=check,
913 )
914 builder = self._makeQueryBuilder(summary)
915 # Add the dataset subquery to the query, telling the QueryBuilder to
916 # include the rank of the selected collection in the results only if we
917 # need to findFirst. Note that if any of the collections are
918 # actually wildcard expressions, and we've asked for deduplication,
919 # this will raise TypeError for us.
920 builder.joinDataset(datasetType, collections, isResult=True, findFirst=findFirst)
921 query = builder.finish()
922 return queries.ParentDatasetQueryResults(self._db, query, components=[None], datasetType=datasetType)
924 def queryDataIds(self, dimensions: Union[Iterable[Union[Dimension, str]], Dimension, str], *,
925 dataId: Optional[DataId] = None,
926 datasets: Any = None,
927 collections: Any = None,
928 where: Optional[str] = None,
929 components: Optional[bool] = None,
930 bind: Optional[Mapping[str, Any]] = None,
931 check: bool = True,
932 **kwargs: Any) -> queries.DataCoordinateQueryResults:
933 # Docstring inherited from lsst.daf.butler.registry.Registry
934 dimensions = iterable(dimensions)
935 standardizedDataId = self.expandDataId(dataId, **kwargs)
936 standardizedDatasetTypes = set()
937 requestedDimensions = self.dimensions.extract(dimensions)
938 queryDimensionNames = set(requestedDimensions.names)
939 if datasets is not None:
940 if not collections:
941 if not self.defaults.collections:
942 raise TypeError(f"Cannot pass 'datasets' (='{datasets}') without 'collections'.")
943 collections = self.defaults.collections
944 else:
945 # Preprocess collections expression in case the original
946 # included single-pass iterators (we'll want to use it multiple
947 # times below).
948 collections = CollectionQuery.fromExpression(collections)
949 for datasetType in self.queryDatasetTypes(datasets, components=components):
950 queryDimensionNames.update(datasetType.dimensions.names)
951 # If any matched dataset type is a component, just operate on
952 # its parent instead, because Registry doesn't know anything
953 # about what components exist, and here (unlike queryDatasets)
954 # we don't care about returning them.
955 parentDatasetTypeName, componentName = datasetType.nameAndComponent()
956 if componentName is not None:
957 datasetType = self.getDatasetType(parentDatasetTypeName)
958 standardizedDatasetTypes.add(datasetType)
959 elif collections:
960 raise TypeError(f"Cannot pass 'collections' (='{collections}') without 'datasets'.")
962 summary = queries.QuerySummary(
963 requested=DimensionGraph(self.dimensions, names=queryDimensionNames),
964 dataId=standardizedDataId,
965 expression=where,
966 bind=bind,
967 defaults=self.defaults.dataId,
968 check=check,
969 )
970 builder = self._makeQueryBuilder(summary)
971 for datasetType in standardizedDatasetTypes:
972 builder.joinDataset(datasetType, collections, isResult=False)
973 query = builder.finish()
974 return queries.DataCoordinateQueryResults(self._db, query)
976 def queryDimensionRecords(self, element: Union[DimensionElement, str], *,
977 dataId: Optional[DataId] = None,
978 datasets: Any = None,
979 collections: Any = None,
980 where: Optional[str] = None,
981 components: Optional[bool] = None,
982 bind: Optional[Mapping[str, Any]] = None,
983 check: bool = True,
984 **kwargs: Any) -> Iterator[DimensionRecord]:
985 # Docstring inherited from lsst.daf.butler.registry.Registry
986 if not isinstance(element, DimensionElement):
987 try:
988 element = self.dimensions[element]
989 except KeyError as e:
990 raise KeyError(f"No such dimension '{element}', available dimensions: "
991 + str(self.dimensions.getStaticElements())) from e
992 dataIds = self.queryDataIds(element.graph, dataId=dataId, datasets=datasets, collections=collections,
993 where=where, components=components, bind=bind, check=check, **kwargs)
994 return iter(self._managers.dimensions[element].fetch(dataIds))
996 def queryDatasetAssociations(
997 self,
998 datasetType: Union[str, DatasetType],
999 collections: Any = ...,
1000 *,
1001 collectionTypes: Iterable[CollectionType] = CollectionType.all(),
1002 flattenChains: bool = False,
1003 ) -> Iterator[DatasetAssociation]:
1004 # Docstring inherited from lsst.daf.butler.registry.Registry
1005 if collections is None:
1006 if not self.defaults.collections:
1007 raise TypeError("No collections provided to findDataset, "
1008 "and no defaults from registry construction.")
1009 collections = self.defaults.collections
1010 else:
1011 collections = CollectionQuery.fromExpression(collections)
1012 TimespanReprClass = self._db.getTimespanRepresentation()
1013 if isinstance(datasetType, str):
1014 storage = self._managers.datasets[datasetType]
1015 else:
1016 storage = self._managers.datasets[datasetType.name]
1017 for collectionRecord in collections.iter(self._managers.collections,
1018 collectionTypes=frozenset(collectionTypes),
1019 flattenChains=flattenChains):
1020 query = storage.select(collectionRecord)
1021 for row in self._db.query(query.combine()).mappings():
1022 dataId = DataCoordinate.fromRequiredValues(
1023 storage.datasetType.dimensions,
1024 tuple(row[name] for name in storage.datasetType.dimensions.required.names)
1025 )
1026 runRecord = self._managers.collections[row[self._managers.collections.getRunForeignKeyName()]]
1027 ref = DatasetRef(storage.datasetType, dataId, id=row["id"], run=runRecord.name,
1028 conform=False)
1029 if collectionRecord.type is CollectionType.CALIBRATION:
1030 timespan = TimespanReprClass.extract(row)
1031 else:
1032 timespan = None
1033 yield DatasetAssociation(ref=ref, collection=collectionRecord.name, timespan=timespan)
1035 storageClasses: StorageClassFactory
1036 """All storage classes known to the registry (`StorageClassFactory`).
1037 """