Coverage for python/lsst/daf/butler/datastores/inMemoryDatastore.py: 87%

192 statements  

« prev     ^ index     » next       coverage.py v6.4.4, created at 2022-09-22 02:04 -0700

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/>. 

21 

22from __future__ import annotations 

23 

24"""In-memory datastore.""" 

25 

26__all__ = ("StoredMemoryItemInfo", "InMemoryDatastore") 

27 

28import logging 

29import time 

30from dataclasses import dataclass 

31from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Mapping, Optional, Set, Tuple, Union 

32from urllib.parse import urlencode 

33 

34from lsst.daf.butler import ( 

35 DatasetId, 

36 DatasetRef, 

37 DatasetRefURIs, 

38 DatastoreRecordData, 

39 StorageClass, 

40 StoredDatastoreItemInfo, 

41) 

42from lsst.daf.butler.core.utils import transactional 

43from lsst.daf.butler.registry.interfaces import DatastoreRegistryBridge 

44from lsst.resources import ResourcePath 

45 

46from .genericDatastore import GenericBaseDatastore 

47 

48if TYPE_CHECKING: 48 ↛ 49line 48 didn't jump to line 49, because the condition on line 48 was never true

49 from lsst.daf.butler import Config, DatasetType, LookupKey 

50 from lsst.daf.butler.registry.interfaces import DatasetIdRef, DatastoreRegistryBridgeManager 

51 

52log = logging.getLogger(__name__) 

53 

54 

55@dataclass(frozen=True) 

56class StoredMemoryItemInfo(StoredDatastoreItemInfo): 

57 """Internal InMemoryDatastore Metadata associated with a stored 

58 DatasetRef. 

59 """ 

60 

61 __slots__ = {"timestamp", "storageClass", "parentID", "dataset_id"} 

62 

63 timestamp: float 

64 """Unix timestamp indicating the time the dataset was stored.""" 

65 

66 storageClass: StorageClass 

67 """StorageClass associated with the dataset.""" 

68 

69 parentID: DatasetId 

70 """ID of the parent `DatasetRef` if this entry is a concrete 

71 composite. Not used if the dataset being stored is not a 

72 virtual component of a composite 

73 """ 

74 

75 dataset_id: DatasetId 

76 """DatasetId associated with this record.""" 

77 

78 

79class InMemoryDatastore(GenericBaseDatastore): 

80 """Basic Datastore for writing to an in memory cache. 

81 

82 This datastore is ephemeral in that the contents of the datastore 

83 disappear when the Python process completes. This also means that 

84 other processes can not access this datastore. 

85 

86 Parameters 

87 ---------- 

88 config : `DatastoreConfig` or `str` 

89 Configuration. 

90 bridgeManager : `DatastoreRegistryBridgeManager` 

91 Object that manages the interface between `Registry` and datastores. 

92 butlerRoot : `str`, optional 

93 Unused parameter. 

94 

95 Notes 

96 ----- 

97 InMemoryDatastore does not support any file-based ingest. 

98 """ 

99 

100 defaultConfigFile = "datastores/inMemoryDatastore.yaml" 

101 """Path to configuration defaults. Accessed within the ``configs`` resource 

102 or relative to a search path. Can be None if no defaults specified. 

103 """ 

104 

105 isEphemeral = True 

106 """A new datastore is created every time and datasets disappear when 

107 the process shuts down.""" 

108 

109 datasets: Dict[DatasetId, Any] 

110 """Internal storage of datasets indexed by dataset ID.""" 

111 

112 records: Dict[DatasetId, StoredMemoryItemInfo] 

113 """Internal records about stored datasets.""" 

114 

115 def __init__( 

116 self, 

117 config: Union[Config, str], 

118 bridgeManager: DatastoreRegistryBridgeManager, 

119 butlerRoot: Optional[str] = None, 

120 ): 

121 super().__init__(config, bridgeManager) 

122 

123 # Name ourselves with the timestamp the datastore 

124 # was created. 

125 self.name = "{}@{}".format(type(self).__name__, time.time()) 

126 log.debug("Creating datastore %s", self.name) 

127 

128 # Storage of datasets, keyed by dataset_id 

129 self.datasets: Dict[DatasetId, Any] = {} 

130 

131 # Records is distinct in order to track concrete composite components 

132 # where we register multiple components for a single dataset. 

133 self.records: Dict[DatasetId, StoredMemoryItemInfo] = {} 

134 

135 # Related records that share the same parent 

136 self.related: Dict[DatasetId, Set[DatasetId]] = {} 

137 

138 self._bridge = bridgeManager.register(self.name, ephemeral=True) 

139 

140 @classmethod 

141 def setConfigRoot(cls, root: str, config: Config, full: Config, overwrite: bool = True) -> None: 

142 """Set any filesystem-dependent config options for this Datastore to 

143 be appropriate for a new empty repository with the given root. 

144 

145 Does nothing in this implementation. 

146 

147 Parameters 

148 ---------- 

149 root : `str` 

150 Filesystem path to the root of the data repository. 

151 config : `Config` 

152 A `Config` to update. Only the subset understood by 

153 this component will be updated. Will not expand 

154 defaults. 

155 full : `Config` 

156 A complete config with all defaults expanded that can be 

157 converted to a `DatastoreConfig`. Read-only and will not be 

158 modified by this method. 

159 Repository-specific options that should not be obtained 

160 from defaults when Butler instances are constructed 

161 should be copied from ``full`` to ``config``. 

162 overwrite : `bool`, optional 

163 If `False`, do not modify a value in ``config`` if the value 

164 already exists. Default is always to overwrite with the provided 

165 ``root``. 

166 

167 Notes 

168 ----- 

169 If a keyword is explicitly defined in the supplied ``config`` it 

170 will not be overridden by this method if ``overwrite`` is `False`. 

171 This allows explicit values set in external configs to be retained. 

172 """ 

173 return 

174 

175 @property 

176 def bridge(self) -> DatastoreRegistryBridge: 

177 # Docstring inherited from GenericBaseDatastore. 

178 return self._bridge 

179 

180 def addStoredItemInfo(self, refs: Iterable[DatasetRef], infos: Iterable[StoredMemoryItemInfo]) -> None: 

181 # Docstring inherited from GenericBaseDatastore. 

182 for ref, info in zip(refs, infos): 

183 if ref.id is None: 183 ↛ 184line 183 didn't jump to line 184, because the condition on line 183 was never true

184 raise RuntimeError(f"Can not store unresolved DatasetRef {ref}") 

185 self.records[ref.id] = info 

186 self.related.setdefault(info.parentID, set()).add(ref.id) 

187 

188 def getStoredItemInfo(self, ref: DatasetIdRef) -> StoredMemoryItemInfo: 

189 # Docstring inherited from GenericBaseDatastore. 

190 if ref.id is None: 190 ↛ 191line 190 didn't jump to line 191, because the condition on line 190 was never true

191 raise RuntimeError(f"Can not retrieve unresolved DatasetRef {ref}") 

192 return self.records[ref.id] 

193 

194 def getStoredItemsInfo(self, ref: DatasetIdRef) -> List[StoredMemoryItemInfo]: 

195 # Docstring inherited from GenericBaseDatastore. 

196 return [self.getStoredItemInfo(ref)] 

197 

198 def removeStoredItemInfo(self, ref: DatasetIdRef) -> None: 

199 # Docstring inherited from GenericBaseDatastore. 

200 # If a component has been removed previously then we can sometimes 

201 # be asked to remove it again. Other datastores ignore this 

202 # so also ignore here 

203 if ref.id is None: 203 ↛ 204line 203 didn't jump to line 204, because the condition on line 203 was never true

204 raise RuntimeError(f"Can not remove unresolved DatasetRef {ref}") 

205 if ref.id not in self.records: 

206 return 

207 record = self.records[ref.id] 

208 del self.records[ref.id] 

209 self.related[record.parentID].remove(ref.id) 

210 

211 def _get_dataset_info(self, ref: DatasetIdRef) -> Tuple[DatasetId, StoredMemoryItemInfo]: 

212 """Check that the dataset is present and return the real ID and 

213 associated information. 

214 

215 Parameters 

216 ---------- 

217 ref : `DatasetRef` 

218 Target `DatasetRef` 

219 

220 Returns 

221 ------- 

222 realID : `int` 

223 The dataset ID associated with this ref that should be used. This 

224 could either be the ID of the supplied `DatasetRef` or the parent. 

225 storageInfo : `StoredMemoryItemInfo` 

226 Associated storage information. 

227 

228 Raises 

229 ------ 

230 FileNotFoundError 

231 Raised if the dataset is not present in this datastore. 

232 """ 

233 try: 

234 storedItemInfo = self.getStoredItemInfo(ref) 

235 except KeyError: 

236 raise FileNotFoundError(f"No such file dataset in memory: {ref}") from None 

237 realID = ref.id 

238 if storedItemInfo.parentID is not None: 238 ↛ 241line 238 didn't jump to line 241, because the condition on line 238 was never false

239 realID = storedItemInfo.parentID 

240 

241 if realID not in self.datasets: 241 ↛ 242line 241 didn't jump to line 242, because the condition on line 241 was never true

242 raise FileNotFoundError(f"No such file dataset in memory: {ref}") 

243 

244 return realID, storedItemInfo 

245 

246 def knows(self, ref: DatasetRef) -> bool: 

247 """Check if the dataset is known to the datastore. 

248 

249 This datastore does not distinguish dataset existence from knowledge 

250 of a dataset. 

251 

252 Parameters 

253 ---------- 

254 ref : `DatasetRef` 

255 Reference to the required dataset. 

256 

257 Returns 

258 ------- 

259 exists : `bool` 

260 `True` if the dataset is known to the datastore. 

261 """ 

262 return self.exists(ref) 

263 

264 def exists(self, ref: DatasetRef) -> bool: 

265 """Check if the dataset exists in the datastore. 

266 

267 Parameters 

268 ---------- 

269 ref : `DatasetRef` 

270 Reference to the required dataset. 

271 

272 Returns 

273 ------- 

274 exists : `bool` 

275 `True` if the entity exists in the `Datastore`. 

276 """ 

277 try: 

278 self._get_dataset_info(ref) 

279 except FileNotFoundError: 

280 return False 

281 return True 

282 

283 def get(self, ref: DatasetRef, parameters: Optional[Mapping[str, Any]] = None) -> Any: 

284 """Load an InMemoryDataset from the store. 

285 

286 Parameters 

287 ---------- 

288 ref : `DatasetRef` 

289 Reference to the required Dataset. 

290 parameters : `dict` 

291 `StorageClass`-specific parameters that specify, for example, 

292 a slice of the dataset to be loaded. 

293 

294 Returns 

295 ------- 

296 inMemoryDataset : `object` 

297 Requested dataset or slice thereof as an InMemoryDataset. 

298 

299 Raises 

300 ------ 

301 FileNotFoundError 

302 Requested dataset can not be retrieved. 

303 TypeError 

304 Return value from formatter has unexpected type. 

305 ValueError 

306 Formatter failed to process the dataset. 

307 """ 

308 

309 log.debug("Retrieve %s from %s with parameters %s", ref, self.name, parameters) 

310 

311 realID, storedItemInfo = self._get_dataset_info(ref) 

312 

313 # We have a write storage class and a read storage class and they 

314 # can be different for concrete composites. 

315 readStorageClass = ref.datasetType.storageClass 

316 writeStorageClass = storedItemInfo.storageClass 

317 

318 component = ref.datasetType.component() 

319 

320 # Check that the supplied parameters are suitable for the type read 

321 # If this is a derived component we validate against the composite 

322 isDerivedComponent = False 

323 if component in writeStorageClass.derivedComponents: 

324 writeStorageClass.validateParameters(parameters) 

325 isDerivedComponent = True 

326 else: 

327 readStorageClass.validateParameters(parameters) 

328 

329 inMemoryDataset = self.datasets[realID] 

330 

331 # if this is a read only component we need to apply parameters 

332 # before we retrieve the component. We assume that the parameters 

333 # will affect the data globally, before the derived component 

334 # is selected. 

335 if isDerivedComponent: 

336 inMemoryDataset = writeStorageClass.delegate().handleParameters(inMemoryDataset, parameters) 

337 # Then disable parameters for later 

338 parameters = {} 

339 

340 # Different storage classes implies a component request 

341 if readStorageClass != writeStorageClass: 

342 

343 if component is None: 343 ↛ 344line 343 didn't jump to line 344, because the condition on line 343 was never true

344 raise ValueError( 

345 "Storage class inconsistency ({} vs {}) but no" 

346 " component requested".format(readStorageClass.name, writeStorageClass.name) 

347 ) 

348 

349 # Concrete composite written as a single object (we hope) 

350 inMemoryDataset = writeStorageClass.delegate().getComponent(inMemoryDataset, component) 

351 

352 # Since there is no formatter to process parameters, they all must be 

353 # passed to the assembler. 

354 return self._post_process_get( 

355 inMemoryDataset, readStorageClass, parameters, isComponent=component is not None 

356 ) 

357 

358 def put(self, inMemoryDataset: Any, ref: DatasetRef) -> None: 

359 """Write a InMemoryDataset with a given `DatasetRef` to the store. 

360 

361 Parameters 

362 ---------- 

363 inMemoryDataset : `object` 

364 The dataset to store. 

365 ref : `DatasetRef` 

366 Reference to the associated Dataset. 

367 

368 Raises 

369 ------ 

370 TypeError 

371 Supplied object and storage class are inconsistent. 

372 DatasetTypeNotSupportedError 

373 The associated `DatasetType` is not handled by this datastore. 

374 

375 Notes 

376 ----- 

377 If the datastore is configured to reject certain dataset types it 

378 is possible that the put will fail and raise a 

379 `DatasetTypeNotSupportedError`. The main use case for this is to 

380 allow `ChainedDatastore` to put to multiple datastores without 

381 requiring that every datastore accepts the dataset. 

382 """ 

383 

384 if ref.id is None: 384 ↛ 385line 384 didn't jump to line 385, because the condition on line 384 was never true

385 raise RuntimeError(f"Can not store unresolved DatasetRef {ref}") 

386 

387 # May need to coerce the in memory dataset to the correct 

388 # python type, otherwise parameters may not work. 

389 inMemoryDataset = ref.datasetType.storageClass.coerce_type(inMemoryDataset) 

390 

391 self._validate_put_parameters(inMemoryDataset, ref) 

392 

393 self.datasets[ref.id] = inMemoryDataset 

394 log.debug("Store %s in %s", ref, self.name) 

395 

396 # Store time we received this content, to allow us to optionally 

397 # expire it. Instead of storing a filename here, we include the 

398 # ID of this datasetRef so we can find it from components. 

399 itemInfo = StoredMemoryItemInfo( 

400 time.time(), ref.datasetType.storageClass, parentID=ref.id, dataset_id=ref.getCheckedId() 

401 ) 

402 

403 # We have to register this content with registry. 

404 # Currently this assumes we have a file so we need to use stub entries 

405 # TODO: Add to ephemeral part of registry 

406 self._register_datasets([(ref, itemInfo)]) 

407 

408 if self._transaction is not None: 

409 self._transaction.registerUndo("put", self.remove, ref) 

410 

411 def getURIs(self, ref: DatasetRef, predict: bool = False) -> DatasetRefURIs: 

412 """Return URIs associated with dataset. 

413 

414 Parameters 

415 ---------- 

416 ref : `DatasetRef` 

417 Reference to the required dataset. 

418 predict : `bool`, optional 

419 If the datastore does not know about the dataset, should it 

420 return a predicted URI or not? 

421 

422 Returns 

423 ------- 

424 uris : `DatasetRefURIs` 

425 The URI to the primary artifact associated with this dataset (if 

426 the dataset was disassembled within the datastore this may be 

427 `None`), and the URIs to any components associated with the dataset 

428 artifact. (can be empty if there are no components). 

429 

430 Notes 

431 ----- 

432 The URIs returned for in-memory datastores are not usable but 

433 provide an indication of the associated dataset. 

434 """ 

435 

436 # Include the dataID as a URI query 

437 query = urlencode(ref.dataId) 

438 

439 # if this has never been written then we have to guess 

440 if not self.exists(ref): 

441 if not predict: 

442 raise FileNotFoundError("Dataset {} not in this datastore".format(ref)) 

443 name = f"{ref.datasetType.name}" 

444 fragment = "#predicted" 

445 else: 

446 realID, _ = self._get_dataset_info(ref) 

447 name = f"{id(self.datasets[realID])}?{query}" 

448 fragment = "" 

449 

450 return DatasetRefURIs(ResourcePath(f"mem://{name}?{query}{fragment}"), {}) 

451 

452 def getURI(self, ref: DatasetRef, predict: bool = False) -> ResourcePath: 

453 """URI to the Dataset. 

454 

455 Always uses "mem://" URI prefix. 

456 

457 Parameters 

458 ---------- 

459 ref : `DatasetRef` 

460 Reference to the required Dataset. 

461 predict : `bool` 

462 If `True`, allow URIs to be returned of datasets that have not 

463 been written. 

464 

465 Returns 

466 ------- 

467 uri : `str` 

468 URI pointing to the dataset within the datastore. If the 

469 dataset does not exist in the datastore, and if ``predict`` is 

470 `True`, the URI will be a prediction and will include a URI 

471 fragment "#predicted". 

472 If the datastore does not have entities that relate well 

473 to the concept of a URI the returned URI string will be 

474 descriptive. The returned URI is not guaranteed to be obtainable. 

475 

476 Raises 

477 ------ 

478 FileNotFoundError 

479 A URI has been requested for a dataset that does not exist and 

480 guessing is not allowed. 

481 AssertionError 

482 Raised if an internal error occurs. 

483 """ 

484 primary, _ = self.getURIs(ref, predict) 

485 if primary is None: 485 ↛ 488line 485 didn't jump to line 488, because the condition on line 485 was never true

486 # This should be impossible since this datastore does 

487 # not disassemble. This check also helps mypy. 

488 raise AssertionError(f"Unexpectedly got no URI for in-memory datastore for {ref}") 

489 return primary 

490 

491 def retrieveArtifacts( 

492 self, 

493 refs: Iterable[DatasetRef], 

494 destination: ResourcePath, 

495 transfer: str = "auto", 

496 preserve_path: bool = True, 

497 overwrite: Optional[bool] = False, 

498 ) -> List[ResourcePath]: 

499 """Retrieve the file artifacts associated with the supplied refs. 

500 

501 Notes 

502 ----- 

503 Not implemented by this datastore. 

504 """ 

505 # Could conceivably launch a FileDatastore to use formatters to write 

506 # the data but this is fraught with problems. 

507 raise NotImplementedError("Can not write artifacts to disk from in-memory datastore.") 

508 

509 def forget(self, refs: Iterable[DatasetRef]) -> None: 

510 # Docstring inherited. 

511 refs = list(refs) 

512 self._bridge.forget(refs) 

513 for ref in refs: 

514 self.removeStoredItemInfo(ref) 

515 

516 @transactional 

517 def trash(self, ref: Union[DatasetRef, Iterable[DatasetRef]], ignore_errors: bool = False) -> None: 

518 """Indicate to the Datastore that a dataset can be removed. 

519 

520 Parameters 

521 ---------- 

522 ref : `DatasetRef` or iterable thereof 

523 Reference to the required Dataset(s). 

524 ignore_errors: `bool`, optional 

525 Indicate that errors should be ignored. 

526 

527 Raises 

528 ------ 

529 FileNotFoundError 

530 Attempt to remove a dataset that does not exist. Only relevant 

531 if a single dataset ref is given. 

532 

533 Notes 

534 ----- 

535 Concurrency should not normally be an issue for the in memory datastore 

536 since all internal changes are isolated to solely this process and 

537 the registry only changes rows associated with this process. 

538 """ 

539 if not isinstance(ref, DatasetRef): 

540 log.debug("Bulk trashing of datasets in datastore %s", self.name) 

541 self.bridge.moveToTrash(ref, transaction=self._transaction) 

542 return 

543 

544 log.debug("Trash %s in datastore %s", ref, self.name) 

545 

546 # Check that this dataset is known to datastore 

547 try: 

548 self._get_dataset_info(ref) 

549 

550 # Move datasets to trash table 

551 self.bridge.moveToTrash([ref], transaction=self._transaction) 

552 except Exception as e: 

553 if ignore_errors: 553 ↛ 554line 553 didn't jump to line 554, because the condition on line 553 was never true

554 log.warning( 

555 "Error encountered moving dataset %s to trash in datastore %s: %s", ref, self.name, e 

556 ) 

557 else: 

558 raise 

559 

560 def emptyTrash(self, ignore_errors: bool = False) -> None: 

561 """Remove all datasets from the trash. 

562 

563 Parameters 

564 ---------- 

565 ignore_errors : `bool`, optional 

566 Ignore errors. 

567 

568 Notes 

569 ----- 

570 The internal tracking of datasets is affected by this method and 

571 transaction handling is not supported if there is a problem before 

572 the datasets themselves are deleted. 

573 

574 Concurrency should not normally be an issue for the in memory datastore 

575 since all internal changes are isolated to solely this process and 

576 the registry only changes rows associated with this process. 

577 """ 

578 log.debug("Emptying trash in datastore %s", self.name) 

579 with self._bridge.emptyTrash() as trash_data: 

580 trashed, _ = trash_data 

581 for ref, _ in trashed: 

582 try: 

583 realID, _ = self._get_dataset_info(ref) 

584 except FileNotFoundError: 584 ↛ 587line 584 didn't jump to line 587

585 # Dataset already removed so ignore it 

586 continue 

587 except Exception as e: 

588 if ignore_errors: 

589 log.warning( 

590 "Emptying trash in datastore %s but encountered an error with dataset %s: %s", 

591 self.name, 

592 ref.id, 

593 e, 

594 ) 

595 continue 

596 else: 

597 raise 

598 

599 # Determine whether all references to this dataset have been 

600 # removed and we can delete the dataset itself 

601 allRefs = self.related[realID] 

602 remainingRefs = allRefs - {ref.id} 

603 if not remainingRefs: 603 ↛ 608line 603 didn't jump to line 608, because the condition on line 603 was never false

604 log.debug("Removing artifact %s from datastore %s", realID, self.name) 

605 del self.datasets[realID] 

606 

607 # Remove this entry 

608 self.removeStoredItemInfo(ref) 

609 

610 def validateConfiguration( 

611 self, entities: Iterable[Union[DatasetRef, DatasetType, StorageClass]], logFailures: bool = False 

612 ) -> None: 

613 """Validate some of the configuration for this datastore. 

614 

615 Parameters 

616 ---------- 

617 entities : iterable of `DatasetRef`, `DatasetType`, or `StorageClass` 

618 Entities to test against this configuration. Can be differing 

619 types. 

620 logFailures : `bool`, optional 

621 If `True`, output a log message for every validation error 

622 detected. 

623 

624 Raises 

625 ------ 

626 DatastoreValidationError 

627 Raised if there is a validation problem with a configuration. 

628 All the problems are reported in a single exception. 

629 

630 Notes 

631 ----- 

632 This method is a no-op. 

633 """ 

634 return 

635 

636 def _overrideTransferMode(self, *datasets: Any, transfer: Optional[str] = None) -> Optional[str]: 

637 # Docstring is inherited from base class 

638 return transfer 

639 

640 def validateKey(self, lookupKey: LookupKey, entity: Union[DatasetRef, DatasetType, StorageClass]) -> None: 

641 # Docstring is inherited from base class 

642 return 

643 

644 def getLookupKeys(self) -> Set[LookupKey]: 

645 # Docstring is inherited from base class 

646 return self.constraints.getLookupKeys() 

647 

648 def needs_expanded_data_ids( 

649 self, 

650 transfer: Optional[str], 

651 entity: Optional[Union[DatasetRef, DatasetType, StorageClass]] = None, 

652 ) -> bool: 

653 # Docstring inherited. 

654 return False 

655 

656 def import_records(self, data: Mapping[str, DatastoreRecordData]) -> None: 

657 # Docstring inherited from the base class. 

658 return 

659 

660 def export_records(self, refs: Iterable[DatasetIdRef]) -> Mapping[str, DatastoreRecordData]: 

661 # Docstring inherited from the base class. 

662 

663 # In-memory Datastore records cannot be exported or imported 

664 return {}