Coverage for tests/test_butler.py: 14%

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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 software is dual licensed under the GNU General Public License and also 

10# under a 3-clause BSD license. Recipients may choose which of these licenses 

11# to use; please see the files gpl-3.0.txt and/or bsd_license.txt, 

12# respectively. If you choose the GPL option then the following text applies 

13# (but note that there is still no warranty even if you opt for BSD instead): 

14# 

15# This program is free software: you can redistribute it and/or modify 

16# it under the terms of the GNU General Public License as published by 

17# the Free Software Foundation, either version 3 of the License, or 

18# (at your option) any later version. 

19# 

20# This program is distributed in the hope that it will be useful, 

21# but WITHOUT ANY WARRANTY; without even the implied warranty of 

22# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 

23# GNU General Public License for more details. 

24# 

25# You should have received a copy of the GNU General Public License 

26# along with this program. If not, see <http://www.gnu.org/licenses/>. 

27 

28"""Tests for Butler. 

29""" 

30from __future__ import annotations 

31 

32import gc 

33import json 

34import logging 

35import os 

36import pathlib 

37import pickle 

38import posixpath 

39import random 

40import shutil 

41import string 

42import tempfile 

43import unittest 

44import uuid 

45from collections.abc import Mapping 

46from typing import TYPE_CHECKING, Any, cast 

47 

48try: 

49 import boto3 

50 import botocore 

51 from lsst.resources.s3utils import clean_test_environment_for_s3 

52 

53 try: 

54 from moto import mock_aws # v5 

55 except ImportError: 

56 from moto import mock_s3 as mock_aws 

57except ImportError: 

58 boto3 = None 

59 

60 def mock_aws(*args: Any, **kwargs: Any) -> Any: # type: ignore[no-untyped-def] 

61 """No-op decorator in case moto mock_aws can not be imported.""" 

62 return None 

63 

64 

65try: 

66 from lsst.daf.butler.tests.server import create_test_server 

67except ImportError: 

68 create_test_server = None 

69 

70try: 

71 # It's possible but silly to have testing.postgresql installed without 

72 # having the postgresql server installed (because then nothing in 

73 # testing.postgresql would work), so we use the presence of that module 

74 # to test whether we can expect the server to be available. 

75 import testing.postgresql # type: ignore[import] 

76except ImportError: 

77 testing = None 

78 

79import astropy.time 

80import sqlalchemy 

81from lsst.daf.butler import ( 

82 Butler, 

83 ButlerConfig, 

84 ButlerRepoIndex, 

85 CollectionCycleError, 

86 CollectionType, 

87 Config, 

88 DataCoordinate, 

89 DatasetExistence, 

90 DatasetNotFoundError, 

91 DatasetRef, 

92 DatasetType, 

93 FileDataset, 

94 NoDefaultCollectionError, 

95 StorageClassFactory, 

96 ValidationError, 

97 script, 

98) 

99from lsst.daf.butler.datastore import NullDatastore 

100from lsst.daf.butler.datastore.file_templates import FileTemplate, FileTemplateValidationError 

101from lsst.daf.butler.datastores.fileDatastore import FileDatastore 

102from lsst.daf.butler.direct_butler import DirectButler 

103from lsst.daf.butler.registry import ( 

104 CollectionError, 

105 CollectionTypeError, 

106 ConflictingDefinitionError, 

107 DataIdValueError, 

108 MissingCollectionError, 

109 OrphanedRecordError, 

110) 

111from lsst.daf.butler.registry.sql_registry import SqlRegistry 

112from lsst.daf.butler.repo_relocation import BUTLER_ROOT_TAG 

113from lsst.daf.butler.tests import MetricsExample, MultiDetectorFormatter 

114from lsst.daf.butler.tests.utils import TestCaseMixin, makeTestTempDir, removeTestTempDir, safeTestTempDir 

115from lsst.resources import ResourcePath 

116from lsst.utils import doImportType 

117from lsst.utils.introspection import get_full_type_name 

118 

119if TYPE_CHECKING: 

120 import types 

121 

122 from lsst.daf.butler import DimensionGroup, Registry, StorageClass 

123 

124TESTDIR = os.path.abspath(os.path.dirname(__file__)) 

125 

126 

127def clean_environment() -> None: 

128 """Remove external environment variables that affect the tests.""" 

129 for k in ("DAF_BUTLER_REPOSITORY_INDEX",): 

130 os.environ.pop(k, None) 

131 

132 

133def makeExampleMetrics() -> MetricsExample: 

134 """Return example dataset suitable for tests.""" 

135 return MetricsExample( 

136 {"AM1": 5.2, "AM2": 30.6}, 

137 {"a": [1, 2, 3], "b": {"blue": 5, "red": "green"}}, 

138 [563, 234, 456.7, 752, 8, 9, 27], 

139 ) 

140 

141 

142class TransactionTestError(Exception): 

143 """Specific error for testing transactions, to prevent misdiagnosing 

144 that might otherwise occur when a standard exception is used. 

145 """ 

146 

147 pass 

148 

149 

150class ButlerConfigTests(unittest.TestCase): 

151 """Simple tests for ButlerConfig that are not tested in any other test 

152 cases. 

153 """ 

154 

155 def testSearchPath(self) -> None: 

156 configFile = os.path.join(TESTDIR, "config", "basic", "butler.yaml") 

157 with self.assertLogs("lsst.daf.butler", level="DEBUG") as cm: 

158 config1 = ButlerConfig(configFile) 

159 self.assertNotIn("testConfigs", "\n".join(cm.output)) 

160 

161 overrideDirectory = os.path.join(TESTDIR, "config", "testConfigs") 

162 with self.assertLogs("lsst.daf.butler", level="DEBUG") as cm: 

163 config2 = ButlerConfig(configFile, searchPaths=[overrideDirectory]) 

164 self.assertIn("testConfigs", "\n".join(cm.output)) 

165 

166 key = ("datastore", "records", "table") 

167 self.assertNotEqual(config1[key], config2[key]) 

168 self.assertEqual(config2[key], "override_record") 

169 

170 

171class ButlerPutGetTests(TestCaseMixin): 

172 """Helper method for running a suite of put/get tests from different 

173 butler configurations. 

174 """ 

175 

176 root: str 

177 default_run = "ingésτ😺" 

178 storageClassFactory: StorageClassFactory 

179 configFile: str | None 

180 tmpConfigFile: str 

181 

182 @staticmethod 

183 def addDatasetType( 

184 datasetTypeName: str, dimensions: DimensionGroup, storageClass: StorageClass | str, registry: Registry 

185 ) -> DatasetType: 

186 """Create a DatasetType and register it""" 

187 datasetType = DatasetType(datasetTypeName, dimensions, storageClass) 

188 registry.registerDatasetType(datasetType) 

189 return datasetType 

190 

191 @classmethod 

192 def setUpClass(cls) -> None: 

193 cls.storageClassFactory = StorageClassFactory() 

194 if cls.configFile is not None: 

195 cls.storageClassFactory.addFromConfig(cls.configFile) 

196 

197 def assertGetComponents( 

198 self, 

199 butler: Butler, 

200 datasetRef: DatasetRef, 

201 components: tuple[str, ...], 

202 reference: Any, 

203 collections: Any = None, 

204 ) -> None: 

205 datasetType = datasetRef.datasetType 

206 dataId = datasetRef.dataId 

207 deferred = butler.getDeferred(datasetRef) 

208 

209 for component in components: 

210 compTypeName = datasetType.componentTypeName(component) 

211 result = butler.get(compTypeName, dataId, collections=collections) 

212 self.assertEqual(result, getattr(reference, component)) 

213 result_deferred = deferred.get(component=component) 

214 self.assertEqual(result_deferred, result) 

215 

216 def tearDown(self) -> None: 

217 if self.root is not None: 

218 removeTestTempDir(self.root) 

219 

220 def create_empty_butler(self, run: str | None = None, writeable: bool | None = None): 

221 """Create a Butler for the test repository, without inserting test 

222 data. 

223 """ 

224 butler = Butler.from_config(self.tmpConfigFile, run=run, writeable=writeable) 

225 assert isinstance(butler, DirectButler), "Expect DirectButler in configuration" 

226 return butler 

227 

228 def create_butler( 

229 self, run: str, storageClass: StorageClass | str, datasetTypeName: str 

230 ) -> tuple[Butler, DatasetType]: 

231 """Create a Butler for the test repository and insert some test data 

232 into it. 

233 """ 

234 butler = self.create_empty_butler(run=run) 

235 

236 collections = set(butler.registry.queryCollections()) 

237 self.assertEqual(collections, {run}) 

238 # Create and register a DatasetType 

239 dimensions = butler.dimensions.conform(["instrument", "visit"]) 

240 

241 datasetType = self.addDatasetType(datasetTypeName, dimensions, storageClass, butler.registry) 

242 

243 # Add needed Dimensions 

244 butler.registry.insertDimensionData("instrument", {"name": "DummyCamComp"}) 

245 butler.registry.insertDimensionData( 

246 "physical_filter", {"instrument": "DummyCamComp", "name": "d-r", "band": "R"} 

247 ) 

248 butler.registry.insertDimensionData( 

249 "visit_system", {"instrument": "DummyCamComp", "id": 1, "name": "default"} 

250 ) 

251 butler.registry.insertDimensionData("day_obs", {"instrument": "DummyCamComp", "id": 20200101}) 

252 visit_start = astropy.time.Time("2020-01-01 08:00:00.123456789", scale="tai") 

253 visit_end = astropy.time.Time("2020-01-01 08:00:36.66", scale="tai") 

254 butler.registry.insertDimensionData( 

255 "visit", 

256 { 

257 "instrument": "DummyCamComp", 

258 "id": 423, 

259 "name": "fourtwentythree", 

260 "physical_filter": "d-r", 

261 "datetime_begin": visit_start, 

262 "datetime_end": visit_end, 

263 "day_obs": 20200101, 

264 }, 

265 ) 

266 

267 # Add more visits for some later tests 

268 for visit_id in (424, 425): 

269 butler.registry.insertDimensionData( 

270 "visit", 

271 { 

272 "instrument": "DummyCamComp", 

273 "id": visit_id, 

274 "name": f"fourtwentyfour_{visit_id}", 

275 "physical_filter": "d-r", 

276 "day_obs": 20200101, 

277 }, 

278 ) 

279 return butler, datasetType 

280 

281 def runPutGetTest(self, storageClass: StorageClass, datasetTypeName: str) -> Butler: 

282 # New datasets will be added to run and tag, but we will only look in 

283 # tag when looking up datasets. 

284 run = self.default_run 

285 butler, datasetType = self.create_butler(run, storageClass, datasetTypeName) 

286 assert butler.run is not None 

287 

288 # Create and store a dataset 

289 metric = makeExampleMetrics() 

290 dataId = butler.registry.expandDataId({"instrument": "DummyCamComp", "visit": 423}) 

291 

292 # Dataset should not exist if we haven't added it 

293 with self.assertRaises(DatasetNotFoundError): 

294 butler.get(datasetTypeName, dataId) 

295 

296 # Put and remove the dataset once as a DatasetRef, once as a dataId, 

297 # and once with a DatasetType 

298 

299 # Keep track of any collections we add and do not clean up 

300 expected_collections = {run} 

301 

302 counter = 0 

303 ref = DatasetRef(datasetType, dataId, id=uuid.UUID(int=1), run="put_run_1") 

304 args = tuple[DatasetRef] | tuple[str | DatasetType, DataCoordinate] 

305 for args in ((ref,), (datasetTypeName, dataId), (datasetType, dataId)): 

306 # Since we are using subTest we can get cascading failures 

307 # here with the first attempt failing and the others failing 

308 # immediately because the dataset already exists. Work around 

309 # this by using a distinct run collection each time 

310 counter += 1 

311 this_run = f"put_run_{counter}" 

312 butler.registry.registerCollection(this_run, type=CollectionType.RUN) 

313 expected_collections.update({this_run}) 

314 

315 with self.subTest(args=args): 

316 kwargs: dict[str, Any] = {} 

317 if not isinstance(args[0], DatasetRef): # type: ignore 

318 kwargs["run"] = this_run 

319 ref = butler.put(metric, *args, **kwargs) 

320 self.assertIsInstance(ref, DatasetRef) 

321 

322 # Test get of a ref. 

323 metricOut = butler.get(ref) 

324 self.assertEqual(metric, metricOut) 

325 # Test get 

326 metricOut = butler.get(ref.datasetType.name, dataId, collections=this_run) 

327 self.assertEqual(metric, metricOut) 

328 # Test get with a datasetRef 

329 metricOut = butler.get(ref) 

330 self.assertEqual(metric, metricOut) 

331 # Test getDeferred with dataId 

332 metricOut = butler.getDeferred(ref.datasetType.name, dataId, collections=this_run).get() 

333 self.assertEqual(metric, metricOut) 

334 # Test getDeferred with a ref 

335 metricOut = butler.getDeferred(ref).get() 

336 self.assertEqual(metric, metricOut) 

337 

338 # Check we can get components 

339 if storageClass.isComposite(): 

340 self.assertGetComponents( 

341 butler, ref, ("summary", "data", "output"), metric, collections=this_run 

342 ) 

343 

344 primary_uri, secondary_uris = butler.getURIs(ref) 

345 n_uris = len(secondary_uris) 

346 if primary_uri: 

347 n_uris += 1 

348 

349 # Can the artifacts themselves be retrieved? 

350 if not butler._datastore.isEphemeral: 

351 # Create a temporary directory to hold the retrieved 

352 # artifacts. 

353 with tempfile.TemporaryDirectory( 

354 prefix="butler-artifacts-", ignore_cleanup_errors=True 

355 ) as artifact_root: 

356 root_uri = ResourcePath(artifact_root, forceDirectory=True) 

357 

358 for preserve_path in (True, False): 

359 destination = root_uri.join(f"{preserve_path}_{counter}/") 

360 log = logging.getLogger("lsst.x") 

361 log.warning("Using destination %s for args %s", destination, args) 

362 # Use copy so that we can test that overwrite 

363 # protection works (using "auto" for File URIs 

364 # would use hard links and subsequent transfer 

365 # would work because it knows they are the same 

366 # file). 

367 transferred = butler.retrieveArtifacts( 

368 [ref], destination, preserve_path=preserve_path, transfer="copy" 

369 ) 

370 self.assertGreater(len(transferred), 0) 

371 artifacts = list(ResourcePath.findFileResources([destination])) 

372 self.assertEqual(set(transferred), set(artifacts)) 

373 

374 for artifact in transferred: 

375 path_in_destination = artifact.relative_to(destination) 

376 self.assertIsNotNone(path_in_destination) 

377 assert path_in_destination is not None 

378 

379 # When path is not preserved there should not 

380 # be any path separators. 

381 num_seps = path_in_destination.count("/") 

382 if preserve_path: 

383 self.assertGreater(num_seps, 0) 

384 else: 

385 self.assertEqual(num_seps, 0) 

386 

387 self.assertEqual( 

388 len(artifacts), 

389 n_uris, 

390 "Comparing expected artifacts vs actual:" 

391 f" {artifacts} vs {primary_uri} and {secondary_uris}", 

392 ) 

393 

394 if preserve_path: 

395 # No need to run these twice 

396 with self.assertRaises(ValueError): 

397 butler.retrieveArtifacts([ref], destination, transfer="move") 

398 

399 with self.assertRaisesRegex( 

400 ValueError, "^Destination location must refer to a directory" 

401 ): 

402 butler.retrieveArtifacts( 

403 [ref], ResourcePath("/some/file.txt", forceDirectory=False) 

404 ) 

405 

406 with self.assertRaises(FileExistsError): 

407 butler.retrieveArtifacts([ref], destination) 

408 

409 transferred_again = butler.retrieveArtifacts( 

410 [ref], destination, preserve_path=preserve_path, overwrite=True 

411 ) 

412 self.assertEqual(set(transferred_again), set(transferred)) 

413 

414 # Now remove the dataset completely. 

415 butler.pruneDatasets([ref], purge=True, unstore=True) 

416 # Lookup with original args should still fail. 

417 kwargs = {"collections": this_run} 

418 if isinstance(args[0], DatasetRef): 

419 kwargs = {} # Prevent warning from being issued. 

420 self.assertFalse(butler.exists(*args, **kwargs)) 

421 # get() should still fail. 

422 with self.assertRaises((FileNotFoundError, DatasetNotFoundError)): 

423 butler.get(ref) 

424 # Registry shouldn't be able to find it by dataset_id anymore. 

425 self.assertIsNone(butler.get_dataset(ref.id)) 

426 

427 # Do explicit registry removal since we know they are 

428 # empty 

429 butler.registry.removeCollection(this_run) 

430 expected_collections.remove(this_run) 

431 

432 # Create DatasetRef for put using default run. 

433 refIn = DatasetRef(datasetType, dataId, id=uuid.UUID(int=1), run=butler.run) 

434 

435 # Check that getDeferred fails with standalone ref. 

436 with self.assertRaises(LookupError): 

437 butler.getDeferred(refIn) 

438 

439 # Put the dataset again, since the last thing we did was remove it 

440 # and we want to use the default collection. 

441 ref = butler.put(metric, refIn) 

442 

443 # Get with parameters 

444 stop = 4 

445 sliced = butler.get(ref, parameters={"slice": slice(stop)}) 

446 self.assertNotEqual(metric, sliced) 

447 self.assertEqual(metric.summary, sliced.summary) 

448 self.assertEqual(metric.output, sliced.output) 

449 assert metric.data is not None # for mypy 

450 self.assertEqual(metric.data[:stop], sliced.data) 

451 # getDeferred with parameters 

452 sliced = butler.getDeferred(ref, parameters={"slice": slice(stop)}).get() 

453 self.assertNotEqual(metric, sliced) 

454 self.assertEqual(metric.summary, sliced.summary) 

455 self.assertEqual(metric.output, sliced.output) 

456 self.assertEqual(metric.data[:stop], sliced.data) 

457 # getDeferred with deferred parameters 

458 sliced = butler.getDeferred(ref).get(parameters={"slice": slice(stop)}) 

459 self.assertNotEqual(metric, sliced) 

460 self.assertEqual(metric.summary, sliced.summary) 

461 self.assertEqual(metric.output, sliced.output) 

462 self.assertEqual(metric.data[:stop], sliced.data) 

463 

464 if storageClass.isComposite(): 

465 # Check that components can be retrieved 

466 metricOut = butler.get(ref.datasetType.name, dataId) 

467 compNameS = ref.datasetType.componentTypeName("summary") 

468 compNameD = ref.datasetType.componentTypeName("data") 

469 summary = butler.get(compNameS, dataId) 

470 self.assertEqual(summary, metric.summary) 

471 data = butler.get(compNameD, dataId) 

472 self.assertEqual(data, metric.data) 

473 

474 if "counter" in storageClass.derivedComponents: 

475 count = butler.get(ref.datasetType.componentTypeName("counter"), dataId) 

476 self.assertEqual(count, len(data)) 

477 

478 count = butler.get( 

479 ref.datasetType.componentTypeName("counter"), dataId, parameters={"slice": slice(stop)} 

480 ) 

481 self.assertEqual(count, stop) 

482 

483 compRef = butler.find_dataset(compNameS, dataId, collections=butler.collections) 

484 assert compRef is not None 

485 summary = butler.get(compRef) 

486 self.assertEqual(summary, metric.summary) 

487 

488 # Create a Dataset type that has the same name but is inconsistent. 

489 inconsistentDatasetType = DatasetType( 

490 datasetTypeName, datasetType.dimensions, self.storageClassFactory.getStorageClass("Config") 

491 ) 

492 

493 # Getting with a dataset type that does not match registry fails 

494 with self.assertRaisesRegex( 

495 ValueError, 

496 "(Supplied dataset type .* inconsistent with registry)" 

497 "|(The new storage class .* is not compatible with the existing storage class)", 

498 ): 

499 butler.get(inconsistentDatasetType, dataId) 

500 

501 # Combining a DatasetRef with a dataId should fail 

502 with self.assertRaisesRegex(ValueError, "DatasetRef given, cannot use dataId as well"): 

503 butler.get(ref, dataId) 

504 # Getting with an explicit ref should fail if the id doesn't match. 

505 with self.assertRaises((FileNotFoundError, DatasetNotFoundError)): 

506 butler.get(DatasetRef(ref.datasetType, ref.dataId, id=uuid.UUID(int=101), run=butler.run)) 

507 

508 # Getting a dataset with unknown parameters should fail 

509 with self.assertRaisesRegex(KeyError, "Parameter 'unsupported' not understood"): 

510 butler.get(ref, parameters={"unsupported": True}) 

511 

512 # Check we have a collection 

513 collections = set(butler.registry.queryCollections()) 

514 self.assertEqual(collections, expected_collections) 

515 

516 # Clean up to check that we can remove something that may have 

517 # already had a component removed 

518 butler.pruneDatasets([ref], unstore=True, purge=True) 

519 

520 # Add the same ref again, so we can check that duplicate put fails. 

521 ref = butler.put(metric, datasetType, dataId) 

522 

523 # Repeat put will fail. 

524 with self.assertRaisesRegex( 

525 ConflictingDefinitionError, "A database constraint failure was triggered" 

526 ): 

527 butler.put(metric, datasetType, dataId) 

528 

529 # Remove the datastore entry. 

530 butler.pruneDatasets([ref], unstore=True, purge=False, disassociate=False) 

531 

532 # Put will still fail 

533 with self.assertRaisesRegex( 

534 ConflictingDefinitionError, "A database constraint failure was triggered" 

535 ): 

536 butler.put(metric, datasetType, dataId) 

537 

538 # Repeat the same sequence with resolved ref. 

539 butler.pruneDatasets([ref], unstore=True, purge=True) 

540 ref = butler.put(metric, refIn) 

541 

542 # Repeat put will fail. 

543 with self.assertRaisesRegex(ConflictingDefinitionError, "Datastore already contains dataset"): 

544 butler.put(metric, refIn) 

545 

546 # Remove the datastore entry. 

547 butler.pruneDatasets([ref], unstore=True, purge=False, disassociate=False) 

548 

549 # In case of resolved ref this write will succeed. 

550 ref = butler.put(metric, refIn) 

551 

552 # Leave the dataset in place since some downstream tests require 

553 # something to be present 

554 

555 return butler 

556 

557 def testDeferredCollectionPassing(self) -> None: 

558 # Construct a butler with no run or collection, but make it writeable. 

559 butler = self.create_empty_butler(writeable=True) 

560 # Create and register a DatasetType 

561 dimensions = butler.dimensions.conform(["instrument", "visit"]) 

562 datasetType = self.addDatasetType( 

563 "example", dimensions, self.storageClassFactory.getStorageClass("StructuredData"), butler.registry 

564 ) 

565 # Add needed Dimensions 

566 butler.registry.insertDimensionData("instrument", {"name": "DummyCamComp"}) 

567 butler.registry.insertDimensionData( 

568 "physical_filter", {"instrument": "DummyCamComp", "name": "d-r", "band": "R"} 

569 ) 

570 butler.registry.insertDimensionData("day_obs", {"instrument": "DummyCamComp", "id": 20250101}) 

571 butler.registry.insertDimensionData( 

572 "visit", 

573 { 

574 "instrument": "DummyCamComp", 

575 "id": 423, 

576 "name": "fourtwentythree", 

577 "physical_filter": "d-r", 

578 "day_obs": 20250101, 

579 }, 

580 ) 

581 dataId = {"instrument": "DummyCamComp", "visit": 423} 

582 # Create dataset. 

583 metric = makeExampleMetrics() 

584 # Register a new run and put dataset. 

585 run = "deferred" 

586 self.assertTrue(butler.registry.registerRun(run)) 

587 # Second time it will be allowed but indicate no-op 

588 self.assertFalse(butler.registry.registerRun(run)) 

589 ref = butler.put(metric, datasetType, dataId, run=run) 

590 # Putting with no run should fail with TypeError. 

591 with self.assertRaises(CollectionError): 

592 butler.put(metric, datasetType, dataId) 

593 # Dataset should exist. 

594 self.assertTrue(butler.exists(datasetType, dataId, collections=[run])) 

595 # We should be able to get the dataset back, but with and without 

596 # a deferred dataset handle. 

597 self.assertEqual(metric, butler.get(datasetType, dataId, collections=[run])) 

598 self.assertEqual(metric, butler.getDeferred(datasetType, dataId, collections=[run]).get()) 

599 # Trying to find the dataset without any collection is an error. 

600 with self.assertRaises(NoDefaultCollectionError): 

601 butler.exists(datasetType, dataId) 

602 with self.assertRaises(CollectionError): 

603 butler.get(datasetType, dataId) 

604 # Associate the dataset with a different collection. 

605 butler.registry.registerCollection("tagged") 

606 butler.registry.associate("tagged", [ref]) 

607 # Deleting the dataset from the new collection should make it findable 

608 # in the original collection. 

609 butler.pruneDatasets([ref], tags=["tagged"]) 

610 self.assertTrue(butler.exists(datasetType, dataId, collections=[run])) 

611 

612 

613class ButlerTests(ButlerPutGetTests): 

614 """Tests for Butler.""" 

615 

616 useTempRoot = True 

617 validationCanFail: bool 

618 fullConfigKey: str | None 

619 registryStr: str | None 

620 datastoreName: list[str] | None 

621 datastoreStr: list[str] 

622 predictionSupported = True 

623 """Does getURIs support 'prediction mode'?""" 

624 

625 def setUp(self) -> None: 

626 """Create a new butler root for each test.""" 

627 self.root = makeTestTempDir(TESTDIR) 

628 Butler.makeRepo(self.root, config=Config(self.configFile)) 

629 self.tmpConfigFile = os.path.join(self.root, "butler.yaml") 

630 

631 def are_uris_equivalent(self, uri1: ResourcePath, uri2: ResourcePath) -> bool: 

632 """Return True if two URIs refer to the same resource. 

633 

634 Subclasses may override to handle unique requirements. 

635 """ 

636 return uri1 == uri2 

637 

638 def testConstructor(self) -> None: 

639 """Independent test of constructor.""" 

640 butler = Butler.from_config(self.tmpConfigFile, run=self.default_run) 

641 self.assertIsInstance(butler, Butler) 

642 

643 # Check that butler.yaml is added automatically. 

644 if self.tmpConfigFile.endswith(end := "/butler.yaml"): 

645 config_dir = self.tmpConfigFile[: -len(end)] 

646 butler = Butler.from_config(config_dir, run=self.default_run) 

647 self.assertIsInstance(butler, Butler) 

648 

649 # Even with a ResourcePath. 

650 butler = Butler.from_config(ResourcePath(config_dir, forceDirectory=True), run=self.default_run) 

651 self.assertIsInstance(butler, Butler) 

652 

653 collections = set(butler.registry.queryCollections()) 

654 self.assertEqual(collections, {self.default_run}) 

655 

656 # Check that some special characters can be included in run name. 

657 special_run = "u@b.c-A" 

658 butler_special = Butler.from_config(butler=butler, run=special_run) 

659 collections = set(butler_special.registry.queryCollections("*@*")) 

660 self.assertEqual(collections, {special_run}) 

661 

662 butler2 = Butler.from_config(butler=butler, collections=["other"]) 

663 self.assertEqual(butler2.collections, ("other",)) 

664 self.assertIsNone(butler2.run) 

665 self.assertEqual(type(butler._datastore), type(butler2._datastore)) 

666 self.assertEqual(butler._datastore.config, butler2._datastore.config) 

667 

668 # Test that we can use an environment variable to find this 

669 # repository. 

670 butler_index = Config() 

671 butler_index["label"] = self.tmpConfigFile 

672 for suffix in (".yaml", ".json"): 

673 # Ensure that the content differs so that we know that 

674 # we aren't reusing the cache. 

675 bad_label = f"file://bucket/not_real{suffix}" 

676 butler_index["bad_label"] = bad_label 

677 with ResourcePath.temporary_uri(suffix=suffix) as temp_file: 

678 butler_index.dumpToUri(temp_file) 

679 with unittest.mock.patch.dict(os.environ, {"DAF_BUTLER_REPOSITORY_INDEX": str(temp_file)}): 

680 self.assertEqual(Butler.get_known_repos(), {"label", "bad_label"}) 

681 uri = Butler.get_repo_uri("bad_label") 

682 self.assertEqual(uri, ResourcePath(bad_label)) 

683 uri = Butler.get_repo_uri("label") 

684 butler = Butler.from_config(uri, writeable=False) 

685 self.assertIsInstance(butler, Butler) 

686 butler = Butler.from_config("label", writeable=False) 

687 self.assertIsInstance(butler, Butler) 

688 with self.assertRaisesRegex(FileNotFoundError, "aliases:.*bad_label"): 

689 Butler.from_config("not_there", writeable=False) 

690 with self.assertRaisesRegex(FileNotFoundError, "resolved from alias 'bad_label'"): 

691 Butler.from_config("bad_label") 

692 with self.assertRaises(FileNotFoundError): 

693 # Should ignore aliases. 

694 Butler.from_config(ResourcePath("label", forceAbsolute=False)) 

695 with self.assertRaises(KeyError) as cm: 

696 Butler.get_repo_uri("missing") 

697 self.assertEqual( 

698 Butler.get_repo_uri("missing", True), ResourcePath("missing", forceAbsolute=False) 

699 ) 

700 self.assertIn("not known to", str(cm.exception)) 

701 # Should report no failure. 

702 self.assertEqual(ButlerRepoIndex.get_failure_reason(), "") 

703 with ResourcePath.temporary_uri(suffix=suffix) as temp_file: 

704 # Now with empty configuration. 

705 butler_index = Config() 

706 butler_index.dumpToUri(temp_file) 

707 with unittest.mock.patch.dict(os.environ, {"DAF_BUTLER_REPOSITORY_INDEX": str(temp_file)}): 

708 with self.assertRaisesRegex(FileNotFoundError, "(no known aliases)"): 

709 Butler.from_config("label") 

710 with ResourcePath.temporary_uri(suffix=suffix) as temp_file: 

711 # Now with bad contents. 

712 with open(temp_file.ospath, "w") as fh: 

713 print("'", file=fh) 

714 with unittest.mock.patch.dict(os.environ, {"DAF_BUTLER_REPOSITORY_INDEX": str(temp_file)}): 

715 with self.assertRaisesRegex(FileNotFoundError, "(no known aliases:.*could not be read)"): 

716 Butler.from_config("label") 

717 with unittest.mock.patch.dict(os.environ, {"DAF_BUTLER_REPOSITORY_INDEX": "file://not_found/x.yaml"}): 

718 with self.assertRaises(FileNotFoundError): 

719 Butler.get_repo_uri("label") 

720 self.assertEqual(Butler.get_known_repos(), set()) 

721 

722 with self.assertRaisesRegex(FileNotFoundError, "index file not found"): 

723 Butler.from_config("label") 

724 

725 # Check that we can create Butler when the alias file is not found. 

726 butler = Butler.from_config(self.tmpConfigFile, writeable=False) 

727 self.assertIsInstance(butler, Butler) 

728 with self.assertRaises(RuntimeError) as cm: 

729 # No environment variable set. 

730 Butler.get_repo_uri("label") 

731 self.assertEqual(Butler.get_repo_uri("label", True), ResourcePath("label", forceAbsolute=False)) 

732 self.assertIn("No repository index defined", str(cm.exception)) 

733 with self.assertRaisesRegex(FileNotFoundError, "no known aliases.*No repository index"): 

734 # No aliases registered. 

735 Butler.from_config("not_there") 

736 self.assertEqual(Butler.get_known_repos(), set()) 

737 

738 def testDafButlerRepositories(self): 

739 with unittest.mock.patch.dict( 

740 os.environ, 

741 {"DAF_BUTLER_REPOSITORIES": "label: 'https://someuri.com'\notherLabel: 'https://otheruri.com'\n"}, 

742 ): 

743 self.assertEqual(str(Butler.get_repo_uri("label")), "https://someuri.com") 

744 

745 with unittest.mock.patch.dict( 

746 os.environ, 

747 { 

748 "DAF_BUTLER_REPOSITORIES": "label: https://someuri.com", 

749 "DAF_BUTLER_REPOSITORY_INDEX": "https://someuri.com", 

750 }, 

751 ): 

752 with self.assertRaisesRegex(RuntimeError, "Only one of the environment variables"): 

753 Butler.get_repo_uri("label") 

754 

755 with unittest.mock.patch.dict( 

756 os.environ, 

757 {"DAF_BUTLER_REPOSITORIES": "invalid"}, 

758 ): 

759 with self.assertRaisesRegex(ValueError, "Repository index not in expected format"): 

760 Butler.get_repo_uri("label") 

761 

762 def testBasicPutGet(self) -> None: 

763 storageClass = self.storageClassFactory.getStorageClass("StructuredDataNoComponents") 

764 self.runPutGetTest(storageClass, "test_metric") 

765 

766 def testCompositePutGetConcrete(self) -> None: 

767 storageClass = self.storageClassFactory.getStorageClass("StructuredCompositeReadCompNoDisassembly") 

768 butler = self.runPutGetTest(storageClass, "test_metric") 

769 

770 # Should *not* be disassembled 

771 datasets = list(butler.registry.queryDatasets(..., collections=self.default_run)) 

772 self.assertEqual(len(datasets), 1) 

773 uri, components = butler.getURIs(datasets[0]) 

774 self.assertIsInstance(uri, ResourcePath) 

775 self.assertFalse(components) 

776 self.assertEqual(uri.fragment, "", f"Checking absence of fragment in {uri}") 

777 self.assertIn("423", str(uri), f"Checking visit is in URI {uri}") 

778 

779 # Predicted dataset 

780 if self.predictionSupported: 

781 dataId = {"instrument": "DummyCamComp", "visit": 424} 

782 uri, components = butler.getURIs(datasets[0].datasetType, dataId=dataId, predict=True) 

783 self.assertFalse(components) 

784 self.assertIsInstance(uri, ResourcePath) 

785 self.assertIn("424", str(uri), f"Checking visit is in URI {uri}") 

786 self.assertEqual(uri.fragment, "predicted", f"Checking for fragment in {uri}") 

787 

788 def testCompositePutGetVirtual(self) -> None: 

789 storageClass = self.storageClassFactory.getStorageClass("StructuredCompositeReadComp") 

790 butler = self.runPutGetTest(storageClass, "test_metric_comp") 

791 

792 # Should be disassembled 

793 datasets = list(butler.registry.queryDatasets(..., collections=self.default_run)) 

794 self.assertEqual(len(datasets), 1) 

795 uri, components = butler.getURIs(datasets[0]) 

796 

797 if butler._datastore.isEphemeral: 

798 # Never disassemble in-memory datastore 

799 self.assertIsInstance(uri, ResourcePath) 

800 self.assertFalse(components) 

801 self.assertEqual(uri.fragment, "", f"Checking absence of fragment in {uri}") 

802 self.assertIn("423", str(uri), f"Checking visit is in URI {uri}") 

803 else: 

804 self.assertIsNone(uri) 

805 self.assertEqual(set(components), set(storageClass.components)) 

806 for compuri in components.values(): 

807 self.assertIsInstance(compuri, ResourcePath) 

808 self.assertIn("423", str(compuri), f"Checking visit is in URI {compuri}") 

809 self.assertEqual(compuri.fragment, "", f"Checking absence of fragment in {compuri}") 

810 

811 if self.predictionSupported: 

812 # Predicted dataset 

813 dataId = {"instrument": "DummyCamComp", "visit": 424} 

814 uri, components = butler.getURIs(datasets[0].datasetType, dataId=dataId, predict=True) 

815 

816 if butler._datastore.isEphemeral: 

817 # Never disassembled 

818 self.assertIsInstance(uri, ResourcePath) 

819 self.assertFalse(components) 

820 self.assertIn("424", str(uri), f"Checking visit is in URI {uri}") 

821 self.assertEqual(uri.fragment, "predicted", f"Checking for fragment in {uri}") 

822 else: 

823 self.assertIsNone(uri) 

824 self.assertEqual(set(components), set(storageClass.components)) 

825 for compuri in components.values(): 

826 self.assertIsInstance(compuri, ResourcePath) 

827 self.assertIn("424", str(compuri), f"Checking visit is in URI {compuri}") 

828 self.assertEqual(compuri.fragment, "predicted", f"Checking for fragment in {compuri}") 

829 

830 def testStorageClassOverrideGet(self) -> None: 

831 """Test storage class conversion on get with override.""" 

832 storageClass = self.storageClassFactory.getStorageClass("StructuredData") 

833 datasetTypeName = "anything" 

834 run = self.default_run 

835 

836 butler, datasetType = self.create_butler(run, storageClass, datasetTypeName) 

837 

838 # Create and store a dataset. 

839 metric = makeExampleMetrics() 

840 dataId = {"instrument": "DummyCamComp", "visit": 423} 

841 

842 ref = butler.put(metric, datasetType, dataId) 

843 

844 # Return native type. 

845 retrieved = butler.get(ref) 

846 self.assertEqual(retrieved, metric) 

847 

848 # Specify an override. 

849 new_sc = self.storageClassFactory.getStorageClass("MetricsConversion") 

850 model = butler.get(ref, storageClass=new_sc) 

851 self.assertNotEqual(type(model), type(retrieved)) 

852 self.assertIs(type(model), new_sc.pytype) 

853 self.assertEqual(retrieved, model) 

854 

855 # Defer but override later. 

856 deferred = butler.getDeferred(ref) 

857 model = deferred.get(storageClass=new_sc) 

858 self.assertIs(type(model), new_sc.pytype) 

859 self.assertEqual(retrieved, model) 

860 

861 # Defer but override up front. 

862 deferred = butler.getDeferred(ref, storageClass=new_sc) 

863 model = deferred.get() 

864 self.assertIs(type(model), new_sc.pytype) 

865 self.assertEqual(retrieved, model) 

866 

867 # Retrieve a component. Should be a tuple. 

868 data = butler.get("anything.data", dataId, storageClass="StructuredDataDataTestTuple") 

869 self.assertIs(type(data), tuple) 

870 self.assertEqual(data, tuple(retrieved.data)) 

871 

872 # Parameter on the write storage class should work regardless 

873 # of read storage class. 

874 data = butler.get( 

875 "anything.data", 

876 dataId, 

877 storageClass="StructuredDataDataTestTuple", 

878 parameters={"slice": slice(2, 4)}, 

879 ) 

880 self.assertEqual(len(data), 2) 

881 

882 # Try a parameter that is known to the read storage class but not 

883 # the write storage class. 

884 with self.assertRaises(KeyError): 

885 butler.get( 

886 "anything.data", 

887 dataId, 

888 storageClass="StructuredDataDataTestTuple", 

889 parameters={"xslice": slice(2, 4)}, 

890 ) 

891 

892 def testPytypePutCoercion(self) -> None: 

893 """Test python type coercion on Butler.get and put.""" 

894 # Store some data with the normal example storage class. 

895 storageClass = self.storageClassFactory.getStorageClass("StructuredDataNoComponents") 

896 datasetTypeName = "test_metric" 

897 butler, _ = self.create_butler(self.default_run, storageClass, datasetTypeName) 

898 

899 dataId = {"instrument": "DummyCamComp", "visit": 423} 

900 

901 # Put a dict and this should coerce to a MetricsExample 

902 test_dict = {"summary": {"a": 1}, "output": {"b": 2}} 

903 metric_ref = butler.put(test_dict, datasetTypeName, dataId=dataId, visit=424) 

904 test_metric = butler.get(metric_ref) 

905 self.assertEqual(get_full_type_name(test_metric), "lsst.daf.butler.tests.MetricsExample") 

906 self.assertEqual(test_metric.summary, test_dict["summary"]) 

907 self.assertEqual(test_metric.output, test_dict["output"]) 

908 

909 # Check that the put still works if a DatasetType is given with 

910 # a definition matching this python type. 

911 registry_type = butler.get_dataset_type(datasetTypeName) 

912 this_type = DatasetType(datasetTypeName, registry_type.dimensions, "StructuredDataDictJson") 

913 metric2_ref = butler.put(test_dict, this_type, dataId=dataId, visit=425) 

914 self.assertEqual(metric2_ref.datasetType, registry_type) 

915 

916 # The get will return the type expected by registry. 

917 test_metric2 = butler.get(metric2_ref) 

918 self.assertEqual(get_full_type_name(test_metric2), "lsst.daf.butler.tests.MetricsExample") 

919 

920 # Make a new DatasetRef with the compatible but different DatasetType. 

921 # This should now return a dict. 

922 new_ref = DatasetRef(this_type, metric2_ref.dataId, id=metric2_ref.id, run=metric2_ref.run) 

923 test_dict2 = butler.get(new_ref) 

924 self.assertEqual(get_full_type_name(test_dict2), "dict") 

925 

926 # Get it again with the wrong dataset type definition using get() 

927 # rather than get(). This should be consistent with get() 

928 # behavior and return the type of the DatasetType. 

929 test_dict3 = butler.get(this_type, dataId=dataId, visit=425) 

930 self.assertEqual(get_full_type_name(test_dict3), "dict") 

931 

932 def testIngest(self) -> None: 

933 butler = self.create_empty_butler(run=self.default_run) 

934 

935 # Create and register a DatasetType 

936 dimensions = butler.dimensions.conform(["instrument", "visit", "detector"]) 

937 

938 storageClass = self.storageClassFactory.getStorageClass("StructuredDataDictYaml") 

939 datasetTypeName = "metric" 

940 

941 datasetType = self.addDatasetType(datasetTypeName, dimensions, storageClass, butler.registry) 

942 

943 # Add needed Dimensions 

944 butler.registry.insertDimensionData("instrument", {"name": "DummyCamComp"}) 

945 butler.registry.insertDimensionData( 

946 "physical_filter", {"instrument": "DummyCamComp", "name": "d-r", "band": "R"} 

947 ) 

948 butler.registry.insertDimensionData("day_obs", {"instrument": "DummyCamComp", "id": 20250101}) 

949 for detector in (1, 2): 

950 butler.registry.insertDimensionData( 

951 "detector", {"instrument": "DummyCamComp", "id": detector, "full_name": f"detector{detector}"} 

952 ) 

953 

954 butler.registry.insertDimensionData( 

955 "visit", 

956 { 

957 "instrument": "DummyCamComp", 

958 "id": 423, 

959 "name": "fourtwentythree", 

960 "physical_filter": "d-r", 

961 "day_obs": 20250101, 

962 }, 

963 { 

964 "instrument": "DummyCamComp", 

965 "id": 424, 

966 "name": "fourtwentyfour", 

967 "physical_filter": "d-r", 

968 "day_obs": 20250101, 

969 }, 

970 ) 

971 

972 formatter = doImportType("lsst.daf.butler.formatters.yaml.YamlFormatter") 

973 dataRoot = os.path.join(TESTDIR, "data", "basic") 

974 datasets = [] 

975 for detector in (1, 2): 

976 detector_name = f"detector_{detector}" 

977 metricFile = os.path.join(dataRoot, f"{detector_name}.yaml") 

978 dataId = butler.registry.expandDataId( 

979 {"instrument": "DummyCamComp", "visit": 423, "detector": detector} 

980 ) 

981 # Create a DatasetRef for ingest 

982 refIn = DatasetRef(datasetType, dataId, run=self.default_run) 

983 

984 datasets.append(FileDataset(path=metricFile, refs=[refIn], formatter=formatter)) 

985 

986 butler.ingest(*datasets, transfer="copy") 

987 

988 dataId1 = {"instrument": "DummyCamComp", "detector": 1, "visit": 423} 

989 dataId2 = {"instrument": "DummyCamComp", "detector": 2, "visit": 423} 

990 

991 metrics1 = butler.get(datasetTypeName, dataId1) 

992 metrics2 = butler.get(datasetTypeName, dataId2) 

993 self.assertNotEqual(metrics1, metrics2) 

994 

995 # Compare URIs 

996 uri1 = butler.getURI(datasetTypeName, dataId1) 

997 uri2 = butler.getURI(datasetTypeName, dataId2) 

998 self.assertFalse(self.are_uris_equivalent(uri1, uri2), f"Cf. {uri1} with {uri2}") 

999 

1000 # Now do a multi-dataset but single file ingest 

1001 metricFile = os.path.join(dataRoot, "detectors.yaml") 

1002 refs = [] 

1003 for detector in (1, 2): 

1004 detector_name = f"detector_{detector}" 

1005 dataId = butler.registry.expandDataId( 

1006 {"instrument": "DummyCamComp", "visit": 424, "detector": detector} 

1007 ) 

1008 # Create a DatasetRef for ingest 

1009 refs.append(DatasetRef(datasetType, dataId, run=self.default_run)) 

1010 

1011 # Test "move" transfer to ensure that the files themselves 

1012 # have disappeared following ingest. 

1013 with ResourcePath.temporary_uri(suffix=".yaml") as tempFile: 

1014 tempFile.transfer_from(ResourcePath(metricFile), transfer="copy") 

1015 

1016 datasets = [] 

1017 datasets.append(FileDataset(path=tempFile, refs=refs, formatter=MultiDetectorFormatter)) 

1018 

1019 # For first ingest use copy. 

1020 butler.ingest(*datasets, transfer="copy", record_validation_info=False) 

1021 

1022 # Now try to ingest again in "execution butler" mode where 

1023 # the registry entries exist but the datastore does not have 

1024 # the files. We also need to strip the dimension records to ensure 

1025 # that they will be re-added by the ingest. 

1026 ref = datasets[0].refs[0] 

1027 datasets[0].refs = [ 

1028 cast( 

1029 DatasetRef, 

1030 butler.find_dataset(ref.datasetType, data_id=ref.dataId, collections=ref.run), 

1031 ) 

1032 for ref in datasets[0].refs 

1033 ] 

1034 all_refs = [] 

1035 for dataset in datasets: 

1036 refs = [] 

1037 for ref in dataset.refs: 

1038 # Create a dict from the dataId to drop the records. 

1039 new_data_id = dict(ref.dataId.required) 

1040 new_ref = butler.find_dataset(ref.datasetType, new_data_id, collections=ref.run) 

1041 assert new_ref is not None 

1042 self.assertFalse(new_ref.dataId.hasRecords()) 

1043 refs.append(new_ref) 

1044 dataset.refs = refs 

1045 all_refs.extend(dataset.refs) 

1046 butler.pruneDatasets(all_refs, disassociate=False, unstore=True, purge=False) 

1047 

1048 # Use move mode to test that the file is deleted. Also 

1049 # disable recording of file size. 

1050 butler.ingest(*datasets, transfer="move", record_validation_info=False) 

1051 

1052 # Check that every ref now has records. 

1053 for dataset in datasets: 

1054 for ref in dataset.refs: 

1055 self.assertTrue(ref.dataId.hasRecords()) 

1056 

1057 # Ensure that the file has disappeared. 

1058 self.assertFalse(tempFile.exists()) 

1059 

1060 # Check that the datastore recorded no file size. 

1061 # Not all datastores can support this. 

1062 try: 

1063 infos = butler._datastore.getStoredItemsInfo(datasets[0].refs[0]) # type: ignore[attr-defined] 

1064 self.assertEqual(infos[0].file_size, -1) 

1065 except AttributeError: 

1066 pass 

1067 

1068 dataId1 = {"instrument": "DummyCamComp", "detector": 1, "visit": 424} 

1069 dataId2 = {"instrument": "DummyCamComp", "detector": 2, "visit": 424} 

1070 

1071 multi1 = butler.get(datasetTypeName, dataId1) 

1072 multi2 = butler.get(datasetTypeName, dataId2) 

1073 

1074 self.assertEqual(multi1, metrics1) 

1075 self.assertEqual(multi2, metrics2) 

1076 

1077 # Compare URIs 

1078 uri1 = butler.getURI(datasetTypeName, dataId1) 

1079 uri2 = butler.getURI(datasetTypeName, dataId2) 

1080 self.assertTrue(self.are_uris_equivalent(uri1, uri2), f"Cf. {uri1} with {uri2}") 

1081 

1082 # Test that removing one does not break the second 

1083 # This line will issue a warning log message for a ChainedDatastore 

1084 # that uses an InMemoryDatastore since in-memory can not ingest 

1085 # files. 

1086 butler.pruneDatasets([datasets[0].refs[0]], unstore=True, disassociate=False) 

1087 self.assertFalse(butler.exists(datasetTypeName, dataId1)) 

1088 self.assertTrue(butler.exists(datasetTypeName, dataId2)) 

1089 multi2b = butler.get(datasetTypeName, dataId2) 

1090 self.assertEqual(multi2, multi2b) 

1091 

1092 # Ensure we can ingest 0 datasets 

1093 datasets = [] 

1094 butler.ingest(*datasets) 

1095 

1096 def testPickle(self) -> None: 

1097 """Test pickle support.""" 

1098 butler = self.create_empty_butler(run=self.default_run) 

1099 assert isinstance(butler, DirectButler), "Expect DirectButler in configuration" 

1100 butlerOut = pickle.loads(pickle.dumps(butler)) 

1101 self.assertIsInstance(butlerOut, Butler) 

1102 self.assertEqual(butlerOut._config, butler._config) 

1103 self.assertEqual(butlerOut.collections, butler.collections) 

1104 self.assertEqual(butlerOut.run, butler.run) 

1105 

1106 def testGetDatasetTypes(self) -> None: 

1107 butler = self.create_empty_butler(run=self.default_run) 

1108 dimensions = butler.dimensions.conform(["instrument", "visit", "physical_filter"]) 

1109 dimensionEntries: list[tuple[str, list[Mapping[str, Any]]]] = [ 

1110 ( 

1111 "instrument", 

1112 [ 

1113 {"instrument": "DummyCam"}, 

1114 {"instrument": "DummyHSC"}, 

1115 {"instrument": "DummyCamComp"}, 

1116 ], 

1117 ), 

1118 ("physical_filter", [{"instrument": "DummyCam", "name": "d-r", "band": "R"}]), 

1119 ("day_obs", [{"instrument": "DummyCam", "id": 20250101}]), 

1120 ( 

1121 "visit", 

1122 [ 

1123 { 

1124 "instrument": "DummyCam", 

1125 "id": 42, 

1126 "name": "fortytwo", 

1127 "physical_filter": "d-r", 

1128 "day_obs": 20250101, 

1129 } 

1130 ], 

1131 ), 

1132 ] 

1133 storageClass = self.storageClassFactory.getStorageClass("StructuredData") 

1134 # Add needed Dimensions 

1135 for element, data in dimensionEntries: 

1136 butler.registry.insertDimensionData(element, *data) 

1137 

1138 # When a DatasetType is added to the registry entries are not created 

1139 # for components but querying them can return the components. 

1140 datasetTypeNames = {"metric", "metric2", "metric4", "metric33", "pvi", "paramtest"} 

1141 components = set() 

1142 for datasetTypeName in datasetTypeNames: 

1143 # Create and register a DatasetType 

1144 self.addDatasetType(datasetTypeName, dimensions, storageClass, butler.registry) 

1145 

1146 for componentName in storageClass.components: 

1147 components.add(DatasetType.nameWithComponent(datasetTypeName, componentName)) 

1148 

1149 fromRegistry: set[DatasetType] = set() 

1150 for parent_dataset_type in butler.registry.queryDatasetTypes(): 

1151 fromRegistry.add(parent_dataset_type) 

1152 fromRegistry.update(parent_dataset_type.makeAllComponentDatasetTypes()) 

1153 self.assertEqual({d.name for d in fromRegistry}, datasetTypeNames | components) 

1154 

1155 # Now that we have some dataset types registered, validate them 

1156 butler.validateConfiguration( 

1157 ignore=[ 

1158 "test_metric_comp", 

1159 "metric3", 

1160 "metric5", 

1161 "calexp", 

1162 "DummySC", 

1163 "datasetType.component", 

1164 "random_data", 

1165 "random_data_2", 

1166 ] 

1167 ) 

1168 

1169 # Add a new datasetType that will fail template validation 

1170 self.addDatasetType("test_metric_comp", dimensions, storageClass, butler.registry) 

1171 if self.validationCanFail: 

1172 with self.assertRaises(ValidationError): 

1173 butler.validateConfiguration() 

1174 

1175 # Rerun validation but with a subset of dataset type names 

1176 butler.validateConfiguration(datasetTypeNames=["metric4"]) 

1177 

1178 # Rerun validation but ignore the bad datasetType 

1179 butler.validateConfiguration( 

1180 ignore=[ 

1181 "test_metric_comp", 

1182 "metric3", 

1183 "metric5", 

1184 "calexp", 

1185 "DummySC", 

1186 "datasetType.component", 

1187 "random_data", 

1188 "random_data_2", 

1189 ] 

1190 ) 

1191 

1192 def testTransaction(self) -> None: 

1193 butler = self.create_empty_butler(run=self.default_run) 

1194 datasetTypeName = "test_metric" 

1195 dimensions = butler.dimensions.conform(["instrument", "visit"]) 

1196 dimensionEntries: tuple[tuple[str, Mapping[str, Any]], ...] = ( 

1197 ("instrument", {"instrument": "DummyCam"}), 

1198 ("physical_filter", {"instrument": "DummyCam", "name": "d-r", "band": "R"}), 

1199 ("day_obs", {"instrument": "DummyCam", "id": 20250101}), 

1200 ( 

1201 "visit", 

1202 { 

1203 "instrument": "DummyCam", 

1204 "id": 42, 

1205 "name": "fortytwo", 

1206 "physical_filter": "d-r", 

1207 "day_obs": 20250101, 

1208 }, 

1209 ), 

1210 ) 

1211 storageClass = self.storageClassFactory.getStorageClass("StructuredData") 

1212 metric = makeExampleMetrics() 

1213 dataId = {"instrument": "DummyCam", "visit": 42} 

1214 # Create and register a DatasetType 

1215 datasetType = self.addDatasetType(datasetTypeName, dimensions, storageClass, butler.registry) 

1216 with self.assertRaises(TransactionTestError): 

1217 with butler.transaction(): 

1218 # Add needed Dimensions 

1219 for args in dimensionEntries: 

1220 butler.registry.insertDimensionData(*args) 

1221 # Store a dataset 

1222 ref = butler.put(metric, datasetTypeName, dataId) 

1223 self.assertIsInstance(ref, DatasetRef) 

1224 # Test get of a ref. 

1225 metricOut = butler.get(ref) 

1226 self.assertEqual(metric, metricOut) 

1227 # Test get 

1228 metricOut = butler.get(datasetTypeName, dataId) 

1229 self.assertEqual(metric, metricOut) 

1230 # Check we can get components 

1231 self.assertGetComponents(butler, ref, ("summary", "data", "output"), metric) 

1232 raise TransactionTestError("This should roll back the entire transaction") 

1233 with self.assertRaises(DataIdValueError, msg=f"Check can't expand DataId {dataId}"): 

1234 butler.registry.expandDataId(dataId) 

1235 # Should raise LookupError for missing data ID value 

1236 with self.assertRaises(LookupError, msg=f"Check can't get by {datasetTypeName} and {dataId}"): 

1237 butler.get(datasetTypeName, dataId) 

1238 # Also check explicitly if Dataset entry is missing 

1239 self.assertIsNone(butler.find_dataset(datasetType, dataId, collections=butler.collections)) 

1240 # Direct retrieval should not find the file in the Datastore 

1241 with self.assertRaises(FileNotFoundError, msg=f"Check {ref} can't be retrieved directly"): 

1242 butler.get(ref) 

1243 

1244 def testMakeRepo(self) -> None: 

1245 """Test that we can write butler configuration to a new repository via 

1246 the Butler.makeRepo interface and then instantiate a butler from the 

1247 repo root. 

1248 """ 

1249 # Do not run the test if we know this datastore configuration does 

1250 # not support a file system root 

1251 if self.fullConfigKey is None: 

1252 return 

1253 

1254 # create two separate directories 

1255 root1 = tempfile.mkdtemp(dir=self.root) 

1256 root2 = tempfile.mkdtemp(dir=self.root) 

1257 

1258 butlerConfig = Butler.makeRepo(root1, config=Config(self.configFile)) 

1259 limited = Config(self.configFile) 

1260 butler1 = Butler.from_config(butlerConfig) 

1261 assert isinstance(butler1, DirectButler), "Expect DirectButler in configuration" 

1262 butlerConfig = Butler.makeRepo(root2, standalone=True, config=Config(self.configFile)) 

1263 full = Config(self.tmpConfigFile) 

1264 butler2 = Butler.from_config(butlerConfig) 

1265 assert isinstance(butler2, DirectButler), "Expect DirectButler in configuration" 

1266 # Butlers should have the same configuration regardless of whether 

1267 # defaults were expanded. 

1268 self.assertEqual(butler1._config, butler2._config) 

1269 # Config files loaded directly should not be the same. 

1270 self.assertNotEqual(limited, full) 

1271 # Make sure "limited" doesn't have a few keys we know it should be 

1272 # inheriting from defaults. 

1273 self.assertIn(self.fullConfigKey, full) 

1274 self.assertNotIn(self.fullConfigKey, limited) 

1275 

1276 # Collections don't appear until something is put in them 

1277 collections1 = set(butler1.registry.queryCollections()) 

1278 self.assertEqual(collections1, set()) 

1279 self.assertEqual(set(butler2.registry.queryCollections()), collections1) 

1280 

1281 # Check that a config with no associated file name will not 

1282 # work properly with relocatable Butler repo 

1283 butlerConfig.configFile = None 

1284 with self.assertRaises(ValueError): 

1285 Butler.from_config(butlerConfig) 

1286 

1287 with self.assertRaises(FileExistsError): 

1288 Butler.makeRepo(self.root, standalone=True, config=Config(self.configFile), overwrite=False) 

1289 

1290 def testStringification(self) -> None: 

1291 butler = Butler.from_config(self.tmpConfigFile, run=self.default_run) 

1292 butlerStr = str(butler) 

1293 

1294 if self.datastoreStr is not None: 

1295 for testStr in self.datastoreStr: 

1296 self.assertIn(testStr, butlerStr) 

1297 if self.registryStr is not None: 

1298 self.assertIn(self.registryStr, butlerStr) 

1299 

1300 datastoreName = butler._datastore.name 

1301 if self.datastoreName is not None: 

1302 for testStr in self.datastoreName: 

1303 self.assertIn(testStr, datastoreName) 

1304 

1305 def testButlerRewriteDataId(self) -> None: 

1306 """Test that dataIds can be rewritten based on dimension records.""" 

1307 butler = self.create_empty_butler(run=self.default_run) 

1308 

1309 storageClass = self.storageClassFactory.getStorageClass("StructuredDataDict") 

1310 datasetTypeName = "random_data" 

1311 

1312 # Create dimension records. 

1313 butler.registry.insertDimensionData("instrument", {"name": "DummyCamComp"}) 

1314 butler.registry.insertDimensionData( 

1315 "physical_filter", {"instrument": "DummyCamComp", "name": "d-r", "band": "R"} 

1316 ) 

1317 butler.registry.insertDimensionData( 

1318 "detector", {"instrument": "DummyCamComp", "id": 1, "full_name": "det1"} 

1319 ) 

1320 

1321 dimensions = butler.dimensions.conform(["instrument", "exposure"]) 

1322 datasetType = DatasetType(datasetTypeName, dimensions, storageClass) 

1323 butler.registry.registerDatasetType(datasetType) 

1324 

1325 n_exposures = 5 

1326 dayobs = 20210530 

1327 

1328 butler.registry.insertDimensionData("day_obs", {"instrument": "DummyCamComp", "id": dayobs}) 

1329 

1330 for i in range(n_exposures): 

1331 butler.registry.insertDimensionData("group", {"instrument": "DummyCamComp", "name": f"group{i}"}) 

1332 butler.registry.insertDimensionData( 

1333 "exposure", 

1334 { 

1335 "instrument": "DummyCamComp", 

1336 "id": i, 

1337 "obs_id": f"exp{i}", 

1338 "seq_num": i, 

1339 "day_obs": dayobs, 

1340 "physical_filter": "d-r", 

1341 "group": f"group{i}", 

1342 }, 

1343 ) 

1344 

1345 # Write some data. 

1346 for i in range(n_exposures): 

1347 metric = {"something": i, "other": "metric", "list": [2 * x for x in range(i)]} 

1348 

1349 # Use the seq_num for the put to test rewriting. 

1350 dataId = {"seq_num": i, "day_obs": dayobs, "instrument": "DummyCamComp", "physical_filter": "d-r"} 

1351 ref = butler.put(metric, datasetTypeName, dataId=dataId) 

1352 

1353 # Check that the exposure is correct in the dataId 

1354 self.assertEqual(ref.dataId["exposure"], i) 

1355 

1356 # and check that we can get the dataset back with the same dataId 

1357 new_metric = butler.get(datasetTypeName, dataId=dataId) 

1358 self.assertEqual(new_metric, metric) 

1359 

1360 # Check that we can find the datasets using the day_obs or the 

1361 # exposure.day_obs. 

1362 datasets_1 = list( 

1363 butler.registry.queryDatasets( 

1364 datasetType, 

1365 collections=self.default_run, 

1366 where="day_obs = dayObs AND instrument = instr", 

1367 bind={"dayObs": dayobs, "instr": "DummyCamComp"}, 

1368 ) 

1369 ) 

1370 datasets_2 = list( 

1371 butler.registry.queryDatasets( 

1372 datasetType, 

1373 collections=self.default_run, 

1374 where="exposure.day_obs = dayObs AND instrument = instr", 

1375 bind={"dayObs": dayobs, "instr": "DummyCamComp"}, 

1376 ) 

1377 ) 

1378 self.assertEqual(datasets_1, datasets_2) 

1379 

1380 def testGetDatasetCollectionCaching(self): 

1381 # Prior to DM-41117, there was a bug where get_dataset would throw 

1382 # MissingCollectionError if you tried to fetch a dataset that was added 

1383 # after the collection cache was last updated. 

1384 reader_butler, datasetType = self.create_butler(self.default_run, "int", "datasettypename") 

1385 writer_butler = self.create_empty_butler(writeable=True, run="new_run") 

1386 dataId = {"instrument": "DummyCamComp", "visit": 423} 

1387 put_ref = writer_butler.put(123, datasetType, dataId) 

1388 get_ref = reader_butler.get_dataset(put_ref.id) 

1389 self.assertEqual(get_ref.id, put_ref.id) 

1390 

1391 def testCollectionChainPrepend(self): 

1392 butler = self.create_empty_butler(writeable=True) 

1393 

1394 butler.registry.registerCollection("chain", CollectionType.CHAINED) 

1395 

1396 runs = ["a", "b", "c", "d"] 

1397 for run in runs: 

1398 butler.registry.registerCollection(run) 

1399 

1400 butler.registry.registerCollection("staticchain", CollectionType.CHAINED) 

1401 butler.registry.setCollectionChain("staticchain", ["a", "b"]) 

1402 

1403 def check_chain(expected: list[str]) -> None: 

1404 children = butler.registry.getCollectionChain("chain") 

1405 self.assertEqual(expected, list(children)) 

1406 

1407 # Duplicates are removed from the list of children 

1408 butler.prepend_collection_chain("chain", ["c", "b", "c"]) 

1409 check_chain(["c", "b"]) 

1410 

1411 # Prepend goes on the front of existing chain 

1412 butler.prepend_collection_chain("chain", ["a"]) 

1413 check_chain(["a", "c", "b"]) 

1414 

1415 # Empty prepend does nothing 

1416 butler.prepend_collection_chain("chain", []) 

1417 check_chain(["a", "c", "b"]) 

1418 

1419 # Prepending children that already exist in the chain removes them from 

1420 # their current position. 

1421 butler.prepend_collection_chain("chain", ["d", "b", "c"]) 

1422 check_chain(["d", "b", "c", "a"]) 

1423 

1424 # Missing parent collection 

1425 with self.assertRaises(MissingCollectionError): 

1426 butler.prepend_collection_chain("doesnotexist", []) 

1427 # Missing child collection 

1428 with self.assertRaises(MissingCollectionError): 

1429 butler.prepend_collection_chain("chain", ["doesnotexist"]) 

1430 # Forbid operations on non-chained collections 

1431 with self.assertRaises(CollectionTypeError): 

1432 butler.prepend_collection_chain("d", ["a"]) 

1433 

1434 # Prevent collection cycles 

1435 butler.registry.registerCollection("chain2", CollectionType.CHAINED) 

1436 butler.prepend_collection_chain("chain2", "chain") 

1437 with self.assertRaises(CollectionCycleError): 

1438 butler.prepend_collection_chain("chain", "chain2") 

1439 

1440 # Make sure none of those operations interfered with unrelated chains 

1441 self.assertEqual(["a", "b"], list(butler.registry.getCollectionChain("staticchain"))) 

1442 

1443 with butler._caching_context(): 

1444 with self.assertRaisesRegex(RuntimeError, "Chained collection modification not permitted"): 

1445 butler.prepend_collection_chain("chain", "a") 

1446 

1447 

1448class FileDatastoreButlerTests(ButlerTests): 

1449 """Common tests and specialization of ButlerTests for butlers backed 

1450 by datastores that inherit from FileDatastore. 

1451 """ 

1452 

1453 trustModeSupported = True 

1454 

1455 def checkFileExists(self, root: str | ResourcePath, relpath: str | ResourcePath) -> bool: 

1456 """Check if file exists at a given path (relative to root). 

1457 

1458 Test testPutTemplates verifies actual physical existance of the files 

1459 in the requested location. 

1460 """ 

1461 uri = ResourcePath(root, forceDirectory=True) 

1462 return uri.join(relpath).exists() 

1463 

1464 def testPutTemplates(self) -> None: 

1465 storageClass = self.storageClassFactory.getStorageClass("StructuredDataNoComponents") 

1466 butler = self.create_empty_butler(run=self.default_run) 

1467 

1468 # Add needed Dimensions 

1469 butler.registry.insertDimensionData("instrument", {"name": "DummyCamComp"}) 

1470 butler.registry.insertDimensionData( 

1471 "physical_filter", {"instrument": "DummyCamComp", "name": "d-r", "band": "R"} 

1472 ) 

1473 butler.registry.insertDimensionData("day_obs", {"instrument": "DummyCamComp", "id": 20250101}) 

1474 butler.registry.insertDimensionData( 

1475 "visit", 

1476 { 

1477 "instrument": "DummyCamComp", 

1478 "id": 423, 

1479 "name": "v423", 

1480 "physical_filter": "d-r", 

1481 "day_obs": 20250101, 

1482 }, 

1483 ) 

1484 butler.registry.insertDimensionData( 

1485 "visit", 

1486 { 

1487 "instrument": "DummyCamComp", 

1488 "id": 425, 

1489 "name": "v425", 

1490 "physical_filter": "d-r", 

1491 "day_obs": 20250101, 

1492 }, 

1493 ) 

1494 

1495 # Create and store a dataset 

1496 metric = makeExampleMetrics() 

1497 

1498 # Create two almost-identical DatasetTypes (both will use default 

1499 # template) 

1500 dimensions = butler.dimensions.conform(["instrument", "visit"]) 

1501 butler.registry.registerDatasetType(DatasetType("metric1", dimensions, storageClass)) 

1502 butler.registry.registerDatasetType(DatasetType("metric2", dimensions, storageClass)) 

1503 butler.registry.registerDatasetType(DatasetType("metric3", dimensions, storageClass)) 

1504 

1505 dataId1 = {"instrument": "DummyCamComp", "visit": 423} 

1506 dataId2 = {"instrument": "DummyCamComp", "visit": 423, "physical_filter": "d-r"} 

1507 

1508 # Put with exactly the data ID keys needed 

1509 ref = butler.put(metric, "metric1", dataId1) 

1510 uri = butler.getURI(ref) 

1511 self.assertTrue(uri.exists()) 

1512 self.assertTrue( 

1513 uri.unquoted_path.endswith(f"{self.default_run}/metric1/??#?/d-r/DummyCamComp_423.pickle") 

1514 ) 

1515 

1516 # Check the template based on dimensions 

1517 if hasattr(butler._datastore, "templates"): 

1518 butler._datastore.templates.validateTemplates([ref]) 

1519 

1520 # Put with extra data ID keys (physical_filter is an optional 

1521 # dependency); should not change template (at least the way we're 

1522 # defining them to behave now; the important thing is that they 

1523 # must be consistent). 

1524 ref = butler.put(metric, "metric2", dataId2) 

1525 uri = butler.getURI(ref) 

1526 self.assertTrue(uri.exists()) 

1527 self.assertTrue( 

1528 uri.unquoted_path.endswith(f"{self.default_run}/metric2/d-r/DummyCamComp_v423.pickle") 

1529 ) 

1530 

1531 # Check the template based on dimensions 

1532 if hasattr(butler._datastore, "templates"): 

1533 butler._datastore.templates.validateTemplates([ref]) 

1534 

1535 # Use a template that has a typo in dimension record metadata. 

1536 # Easier to test with a butler that has a ref with records attached. 

1537 template = FileTemplate("a/{visit.name}/{id}_{visit.namex:?}.fits") 

1538 with self.assertLogs("lsst.daf.butler.datastore.file_templates", "INFO"): 

1539 path = template.format(ref) 

1540 self.assertEqual(path, f"a/v423/{ref.id}_fits") 

1541 

1542 template = FileTemplate("a/{visit.name}/{id}_{visit.namex}.fits") 

1543 with self.assertRaises(KeyError): 

1544 with self.assertLogs("lsst.daf.butler.datastore.file_templates", "INFO"): 

1545 template.format(ref) 

1546 

1547 # Now use a file template that will not result in unique filenames 

1548 with self.assertRaises(FileTemplateValidationError): 

1549 butler.put(metric, "metric3", dataId1) 

1550 

1551 def testImportExport(self) -> None: 

1552 # Run put/get tests just to create and populate a repo. 

1553 storageClass = self.storageClassFactory.getStorageClass("StructuredDataNoComponents") 

1554 self.runImportExportTest(storageClass) 

1555 

1556 @unittest.expectedFailure 

1557 def testImportExportVirtualComposite(self) -> None: 

1558 # Run put/get tests just to create and populate a repo. 

1559 storageClass = self.storageClassFactory.getStorageClass("StructuredComposite") 

1560 self.runImportExportTest(storageClass) 

1561 

1562 def runImportExportTest(self, storageClass: StorageClass) -> None: 

1563 """Test exporting and importing. 

1564 

1565 This test does an export to a temp directory and an import back 

1566 into a new temp directory repo. It does not assume a posix datastore. 

1567 """ 

1568 exportButler = self.runPutGetTest(storageClass, "test_metric") 

1569 

1570 # Test that we must have a file extension. 

1571 with self.assertRaises(ValueError): 

1572 with exportButler.export(filename="dump", directory=".") as export: 

1573 pass 

1574 

1575 # Test that unknown format is not allowed. 

1576 with self.assertRaises(ValueError): 

1577 with exportButler.export(filename="dump.fits", directory=".") as export: 

1578 pass 

1579 

1580 # Test that the repo actually has at least one dataset. 

1581 datasets = list(exportButler.registry.queryDatasets(..., collections=...)) 

1582 self.assertGreater(len(datasets), 0) 

1583 # Add a DimensionRecord that's unused by those datasets. 

1584 skymapRecord = {"name": "example_skymap", "hash": (50).to_bytes(8, byteorder="little")} 

1585 exportButler.registry.insertDimensionData("skymap", skymapRecord) 

1586 # Export and then import datasets. 

1587 with safeTestTempDir(TESTDIR) as exportDir: 

1588 exportFile = os.path.join(exportDir, "exports.yaml") 

1589 with exportButler.export(filename=exportFile, directory=exportDir, transfer="auto") as export: 

1590 export.saveDatasets(datasets) 

1591 # Export the same datasets again. This should quietly do 

1592 # nothing because of internal deduplication, and it shouldn't 

1593 # complain about being asked to export the "htm7" elements even 

1594 # though there aren't any in these datasets or in the database. 

1595 export.saveDatasets(datasets, elements=["htm7"]) 

1596 # Save one of the data IDs again; this should be harmless 

1597 # because of internal deduplication. 

1598 export.saveDataIds([datasets[0].dataId]) 

1599 # Save some dimension records directly. 

1600 export.saveDimensionData("skymap", [skymapRecord]) 

1601 self.assertTrue(os.path.exists(exportFile)) 

1602 with safeTestTempDir(TESTDIR) as importDir: 

1603 # We always want this to be a local posix butler 

1604 Butler.makeRepo(importDir, config=Config(os.path.join(TESTDIR, "config/basic/butler.yaml"))) 

1605 # Calling script.butlerImport tests the implementation of the 

1606 # butler command line interface "import" subcommand. Functions 

1607 # in the script folder are generally considered protected and 

1608 # should not be used as public api. 

1609 with open(exportFile) as f: 

1610 script.butlerImport( 

1611 importDir, 

1612 export_file=f, 

1613 directory=exportDir, 

1614 transfer="auto", 

1615 skip_dimensions=None, 

1616 ) 

1617 importButler = Butler.from_config(importDir, run=self.default_run) 

1618 for ref in datasets: 

1619 with self.subTest(ref=ref): 

1620 # Test for existence by passing in the DatasetType and 

1621 # data ID separately, to avoid lookup by dataset_id. 

1622 self.assertTrue(importButler.exists(ref.datasetType, ref.dataId)) 

1623 self.assertEqual( 

1624 list(importButler.registry.queryDimensionRecords("skymap")), 

1625 [importButler.dimensions["skymap"].RecordClass(**skymapRecord)], 

1626 ) 

1627 

1628 def testRemoveRuns(self) -> None: 

1629 storageClass = self.storageClassFactory.getStorageClass("StructuredDataNoComponents") 

1630 butler = self.create_empty_butler(writeable=True) 

1631 # Load registry data with dimensions to hang datasets off of. 

1632 registryDataDir = os.path.normpath(os.path.join(os.path.dirname(__file__), "data", "registry")) 

1633 butler.import_(filename=os.path.join(registryDataDir, "base.yaml")) 

1634 # Add some RUN-type collection. 

1635 run1 = "run1" 

1636 butler.registry.registerRun(run1) 

1637 run2 = "run2" 

1638 butler.registry.registerRun(run2) 

1639 # put a dataset in each 

1640 metric = makeExampleMetrics() 

1641 dimensions = butler.dimensions.conform(["instrument", "physical_filter"]) 

1642 datasetType = self.addDatasetType( 

1643 "prune_collections_test_dataset", dimensions, storageClass, butler.registry 

1644 ) 

1645 ref1 = butler.put(metric, datasetType, {"instrument": "Cam1", "physical_filter": "Cam1-G"}, run=run1) 

1646 ref2 = butler.put(metric, datasetType, {"instrument": "Cam1", "physical_filter": "Cam1-G"}, run=run2) 

1647 uri1 = butler.getURI(ref1) 

1648 uri2 = butler.getURI(ref2) 

1649 

1650 with self.assertRaises(OrphanedRecordError): 

1651 butler.registry.removeDatasetType(datasetType.name) 

1652 

1653 # Remove from both runs with different values for unstore. 

1654 butler.removeRuns([run1], unstore=True) 

1655 butler.removeRuns([run2], unstore=False) 

1656 # Should be nothing in registry for either one, and datastore should 

1657 # not think either exists. 

1658 with self.assertRaises(MissingCollectionError): 

1659 butler.registry.getCollectionType(run1) 

1660 with self.assertRaises(MissingCollectionError): 

1661 butler.registry.getCollectionType(run2) 

1662 self.assertFalse(butler.stored(ref1)) 

1663 self.assertFalse(butler.stored(ref2)) 

1664 # The ref we unstored should be gone according to the URI, but the 

1665 # one we forgot should still be around. 

1666 self.assertFalse(uri1.exists()) 

1667 self.assertTrue(uri2.exists()) 

1668 

1669 # Now that the collections have been pruned we can remove the 

1670 # dataset type 

1671 butler.registry.removeDatasetType(datasetType.name) 

1672 

1673 with self.assertLogs("lsst.daf.butler.registry", "INFO") as cm: 

1674 butler.registry.removeDatasetType(("test*", "test*")) 

1675 self.assertIn("not defined", "\n".join(cm.output)) 

1676 

1677 def remove_dataset_out_of_band(self, butler: Butler, ref: DatasetRef) -> None: 

1678 """Simulate an external actor removing a file outside of Butler's 

1679 knowledge. 

1680 

1681 Subclasses may override to handle more complicated datastore 

1682 configurations. 

1683 """ 

1684 uri = butler.getURI(ref) 

1685 uri.remove() 

1686 datastore = cast(FileDatastore, butler._datastore) 

1687 datastore.cacheManager.remove_from_cache(ref) 

1688 

1689 def testPruneDatasets(self) -> None: 

1690 storageClass = self.storageClassFactory.getStorageClass("StructuredDataNoComponents") 

1691 butler = self.create_empty_butler(writeable=True) 

1692 # Load registry data with dimensions to hang datasets off of. 

1693 registryDataDir = os.path.normpath(os.path.join(TESTDIR, "data", "registry")) 

1694 butler.import_(filename=os.path.join(registryDataDir, "base.yaml")) 

1695 # Add some RUN-type collections. 

1696 run1 = "run1" 

1697 butler.registry.registerRun(run1) 

1698 run2 = "run2" 

1699 butler.registry.registerRun(run2) 

1700 # put some datasets. ref1 and ref2 have the same data ID, and are in 

1701 # different runs. ref3 has a different data ID. 

1702 metric = makeExampleMetrics() 

1703 dimensions = butler.dimensions.conform(["instrument", "physical_filter"]) 

1704 datasetType = self.addDatasetType( 

1705 "prune_collections_test_dataset", dimensions, storageClass, butler.registry 

1706 ) 

1707 ref1 = butler.put(metric, datasetType, {"instrument": "Cam1", "physical_filter": "Cam1-G"}, run=run1) 

1708 ref2 = butler.put(metric, datasetType, {"instrument": "Cam1", "physical_filter": "Cam1-G"}, run=run2) 

1709 ref3 = butler.put(metric, datasetType, {"instrument": "Cam1", "physical_filter": "Cam1-R1"}, run=run1) 

1710 

1711 many_stored = butler.stored_many([ref1, ref2, ref3]) 

1712 for ref, stored in many_stored.items(): 

1713 self.assertTrue(stored, f"Ref {ref} should be stored") 

1714 

1715 many_exists = butler._exists_many([ref1, ref2, ref3]) 

1716 for ref, exists in many_exists.items(): 

1717 self.assertTrue(exists, f"Checking ref {ref} exists.") 

1718 self.assertEqual(exists, DatasetExistence.VERIFIED, f"Ref {ref} should be stored") 

1719 

1720 # Simple prune. 

1721 butler.pruneDatasets([ref1, ref2, ref3], purge=True, unstore=True) 

1722 self.assertFalse(butler.exists(ref1.datasetType, ref1.dataId, collections=run1)) 

1723 

1724 many_stored = butler.stored_many([ref1, ref2, ref3]) 

1725 for ref, stored in many_stored.items(): 

1726 self.assertFalse(stored, f"Ref {ref} should not be stored") 

1727 

1728 many_exists = butler._exists_many([ref1, ref2, ref3]) 

1729 for ref, exists in many_exists.items(): 

1730 self.assertEqual(exists, DatasetExistence.UNRECOGNIZED, f"Ref {ref} should not be stored") 

1731 

1732 # Put data back. 

1733 ref1_new = butler.put(metric, ref1) 

1734 self.assertEqual(ref1_new, ref1) # Reuses original ID. 

1735 ref2 = butler.put(metric, ref2) 

1736 

1737 many_stored = butler.stored_many([ref1, ref2, ref3]) 

1738 self.assertTrue(many_stored[ref1]) 

1739 self.assertTrue(many_stored[ref2]) 

1740 self.assertFalse(many_stored[ref3]) 

1741 

1742 ref3 = butler.put(metric, ref3) 

1743 

1744 many_exists = butler._exists_many([ref1, ref2, ref3]) 

1745 for ref, exists in many_exists.items(): 

1746 self.assertTrue(exists, f"Ref {ref} should not be stored") 

1747 

1748 # Clear out the datasets from registry and start again. 

1749 refs = [ref1, ref2, ref3] 

1750 butler.pruneDatasets(refs, purge=True, unstore=True) 

1751 for ref in refs: 

1752 butler.put(metric, ref) 

1753 

1754 # Confirm we can retrieve deferred. 

1755 dref1 = butler.getDeferred(ref1) # known and exists 

1756 metric1 = dref1.get() 

1757 self.assertEqual(metric1, metric) 

1758 

1759 # Test different forms of file availability. 

1760 # Need to be in a state where: 

1761 # - one ref just has registry record. 

1762 # - one ref has a missing file but a datastore record. 

1763 # - one ref has a missing datastore record but file is there. 

1764 # - one ref does not exist anywhere. 

1765 # Do not need to test a ref that has everything since that is tested 

1766 # above. 

1767 ref0 = DatasetRef( 

1768 datasetType, 

1769 DataCoordinate.standardize( 

1770 {"instrument": "Cam1", "physical_filter": "Cam1-G"}, universe=butler.dimensions 

1771 ), 

1772 run=run1, 

1773 ) 

1774 

1775 # Delete from datastore and retain in Registry. 

1776 butler.pruneDatasets([ref1], purge=False, unstore=True, disassociate=False) 

1777 

1778 # File has been removed. 

1779 self.remove_dataset_out_of_band(butler, ref2) 

1780 

1781 # Datastore has lost track. 

1782 butler._datastore.forget([ref3]) 

1783 

1784 # First test with a standard butler. 

1785 exists_many = butler._exists_many([ref0, ref1, ref2, ref3], full_check=True) 

1786 self.assertEqual(exists_many[ref0], DatasetExistence.UNRECOGNIZED) 

1787 self.assertEqual(exists_many[ref1], DatasetExistence.RECORDED) 

1788 self.assertEqual(exists_many[ref2], DatasetExistence.RECORDED | DatasetExistence.DATASTORE) 

1789 self.assertEqual(exists_many[ref3], DatasetExistence.RECORDED) 

1790 

1791 exists_many = butler._exists_many([ref0, ref1, ref2, ref3], full_check=False) 

1792 self.assertEqual(exists_many[ref0], DatasetExistence.UNRECOGNIZED) 

1793 self.assertEqual(exists_many[ref1], DatasetExistence.RECORDED | DatasetExistence._ASSUMED) 

1794 self.assertEqual(exists_many[ref2], DatasetExistence.KNOWN) 

1795 self.assertEqual(exists_many[ref3], DatasetExistence.RECORDED | DatasetExistence._ASSUMED) 

1796 self.assertTrue(exists_many[ref2]) 

1797 

1798 # Check that per-ref query gives the same answer as many query. 

1799 for ref, exists in exists_many.items(): 

1800 self.assertEqual(butler.exists(ref, full_check=False), exists) 

1801 

1802 # Get deferred checks for existence before it allows it to be 

1803 # retrieved. 

1804 with self.assertRaises(LookupError): 

1805 butler.getDeferred(ref3) # not known, file exists 

1806 dref2 = butler.getDeferred(ref2) # known but file missing 

1807 with self.assertRaises(FileNotFoundError): 

1808 dref2.get() 

1809 

1810 # Test again with a trusting butler. 

1811 if self.trustModeSupported: 

1812 butler._datastore.trustGetRequest = True 

1813 exists_many = butler._exists_many([ref0, ref1, ref2, ref3], full_check=True) 

1814 self.assertEqual(exists_many[ref0], DatasetExistence.UNRECOGNIZED) 

1815 self.assertEqual(exists_many[ref1], DatasetExistence.RECORDED) 

1816 self.assertEqual(exists_many[ref2], DatasetExistence.RECORDED | DatasetExistence.DATASTORE) 

1817 self.assertEqual(exists_many[ref3], DatasetExistence.RECORDED | DatasetExistence._ARTIFACT) 

1818 

1819 # When trusting we can get a deferred dataset handle that is not 

1820 # known but does exist. 

1821 dref3 = butler.getDeferred(ref3) 

1822 metric3 = dref3.get() 

1823 self.assertEqual(metric3, metric) 

1824 

1825 # Check that per-ref query gives the same answer as many query. 

1826 for ref, exists in exists_many.items(): 

1827 self.assertEqual(butler.exists(ref, full_check=True), exists) 

1828 

1829 # Create a ref that surprisingly has the UUID of an existing ref 

1830 # but is not the same. 

1831 ref_bad = DatasetRef(datasetType, dataId=ref3.dataId, run=ref3.run, id=ref2.id) 

1832 with self.assertRaises(ValueError): 

1833 butler.exists(ref_bad) 

1834 

1835 # Create a ref that has a compatible storage class. 

1836 ref_compat = ref2.overrideStorageClass("StructuredDataDict") 

1837 exists = butler.exists(ref_compat) 

1838 self.assertEqual(exists, exists_many[ref2]) 

1839 

1840 # Remove everything and start from scratch. 

1841 butler._datastore.trustGetRequest = False 

1842 butler.pruneDatasets(refs, purge=True, unstore=True) 

1843 for ref in refs: 

1844 butler.put(metric, ref) 

1845 

1846 # These tests mess directly with the trash table and can leave the 

1847 # datastore in an odd state. Do them at the end. 

1848 # Check that in normal mode, deleting the record will lead to 

1849 # trash not touching the file. 

1850 uri1 = butler.getURI(ref1) 

1851 butler._datastore.bridge.moveToTrash( 

1852 [ref1], transaction=None 

1853 ) # Update the dataset_location table 

1854 butler._datastore.forget([ref1]) 

1855 butler._datastore.trash(ref1) 

1856 butler._datastore.emptyTrash() 

1857 self.assertTrue(uri1.exists()) 

1858 uri1.remove() # Clean it up. 

1859 

1860 # Simulate execution butler setup by deleting the datastore 

1861 # record but keeping the file around and trusting. 

1862 butler._datastore.trustGetRequest = True 

1863 uris = butler.get_many_uris([ref2, ref3]) 

1864 uri2 = uris[ref2].primaryURI 

1865 uri3 = uris[ref3].primaryURI 

1866 self.assertTrue(uri2.exists()) 

1867 self.assertTrue(uri3.exists()) 

1868 

1869 # Remove the datastore record. 

1870 butler._datastore.bridge.moveToTrash( 

1871 [ref2], transaction=None 

1872 ) # Update the dataset_location table 

1873 butler._datastore.forget([ref2]) 

1874 self.assertTrue(uri2.exists()) 

1875 butler._datastore.trash([ref2, ref3]) 

1876 # Immediate removal for ref2 file 

1877 self.assertFalse(uri2.exists()) 

1878 # But ref3 has to wait for the empty. 

1879 self.assertTrue(uri3.exists()) 

1880 butler._datastore.emptyTrash() 

1881 self.assertFalse(uri3.exists()) 

1882 

1883 # Clear out the datasets from registry. 

1884 butler.pruneDatasets([ref1, ref2, ref3], purge=True, unstore=True) 

1885 

1886 

1887class PosixDatastoreButlerTestCase(FileDatastoreButlerTests, unittest.TestCase): 

1888 """PosixDatastore specialization of a butler""" 

1889 

1890 configFile = os.path.join(TESTDIR, "config/basic/butler.yaml") 

1891 fullConfigKey: str | None = ".datastore.formatters" 

1892 validationCanFail = True 

1893 datastoreStr = ["/tmp"] 

1894 datastoreName = [f"FileDatastore@{BUTLER_ROOT_TAG}"] 

1895 registryStr = "/gen3.sqlite3" 

1896 

1897 def testPathConstructor(self) -> None: 

1898 """Independent test of constructor using PathLike.""" 

1899 butler = Butler.from_config(self.tmpConfigFile, run=self.default_run) 

1900 self.assertIsInstance(butler, Butler) 

1901 

1902 # And again with a Path object with the butler yaml 

1903 path = pathlib.Path(self.tmpConfigFile) 

1904 butler = Butler.from_config(path, writeable=False) 

1905 self.assertIsInstance(butler, Butler) 

1906 

1907 # And again with a Path object without the butler yaml 

1908 # (making sure we skip it if the tmp config doesn't end 

1909 # in butler.yaml -- which is the case for a subclass) 

1910 if self.tmpConfigFile.endswith("butler.yaml"): 

1911 path = pathlib.Path(os.path.dirname(self.tmpConfigFile)) 

1912 butler = Butler.from_config(path, writeable=False) 

1913 self.assertIsInstance(butler, Butler) 

1914 

1915 def testExportTransferCopy(self) -> None: 

1916 """Test local export using all transfer modes""" 

1917 storageClass = self.storageClassFactory.getStorageClass("StructuredDataNoComponents") 

1918 exportButler = self.runPutGetTest(storageClass, "test_metric") 

1919 # Test that the repo actually has at least one dataset. 

1920 datasets = list(exportButler.registry.queryDatasets(..., collections=...)) 

1921 self.assertGreater(len(datasets), 0) 

1922 uris = [exportButler.getURI(d) for d in datasets] 

1923 assert isinstance(exportButler._datastore, FileDatastore) 

1924 datastoreRoot = exportButler.get_datastore_roots()[exportButler.get_datastore_names()[0]] 

1925 

1926 pathsInStore = [uri.relative_to(datastoreRoot) for uri in uris] 

1927 

1928 for path in pathsInStore: 

1929 # Assume local file system 

1930 assert path is not None 

1931 self.assertTrue(self.checkFileExists(datastoreRoot, path), f"Checking path {path}") 

1932 

1933 for transfer in ("copy", "link", "symlink", "relsymlink"): 

1934 with safeTestTempDir(TESTDIR) as exportDir: 

1935 with exportButler.export(directory=exportDir, format="yaml", transfer=transfer) as export: 

1936 export.saveDatasets(datasets) 

1937 for path in pathsInStore: 

1938 assert path is not None 

1939 self.assertTrue( 

1940 self.checkFileExists(exportDir, path), 

1941 f"Check that mode {transfer} exported files", 

1942 ) 

1943 

1944 def testPytypeCoercion(self) -> None: 

1945 """Test python type coercion on Butler.get and put.""" 

1946 # Store some data with the normal example storage class. 

1947 storageClass = self.storageClassFactory.getStorageClass("StructuredDataNoComponents") 

1948 datasetTypeName = "test_metric" 

1949 butler = self.runPutGetTest(storageClass, datasetTypeName) 

1950 

1951 dataId = {"instrument": "DummyCamComp", "visit": 423} 

1952 metric = butler.get(datasetTypeName, dataId=dataId) 

1953 self.assertEqual(get_full_type_name(metric), "lsst.daf.butler.tests.MetricsExample") 

1954 

1955 datasetType_ori = butler.get_dataset_type(datasetTypeName) 

1956 self.assertEqual(datasetType_ori.storageClass.name, "StructuredDataNoComponents") 

1957 

1958 # Now need to hack the registry dataset type definition. 

1959 # There is no API for this. 

1960 assert isinstance(butler._registry, SqlRegistry) 

1961 manager = butler._registry._managers.datasets 

1962 assert hasattr(manager, "_db") and hasattr(manager, "_static") 

1963 manager._db.update( 

1964 manager._static.dataset_type, 

1965 {"name": datasetTypeName}, 

1966 {datasetTypeName: datasetTypeName, "storage_class": "StructuredDataNoComponentsModel"}, 

1967 ) 

1968 

1969 # Force reset of dataset type cache 

1970 butler.registry.refresh() 

1971 

1972 datasetType_new = butler.get_dataset_type(datasetTypeName) 

1973 self.assertEqual(datasetType_new.name, datasetType_ori.name) 

1974 self.assertEqual(datasetType_new.storageClass.name, "StructuredDataNoComponentsModel") 

1975 

1976 metric_model = butler.get(datasetTypeName, dataId=dataId) 

1977 self.assertNotEqual(type(metric_model), type(metric)) 

1978 self.assertEqual(get_full_type_name(metric_model), "lsst.daf.butler.tests.MetricsExampleModel") 

1979 

1980 # Put the model and read it back to show that everything now 

1981 # works as normal. 

1982 metric_ref = butler.put(metric_model, datasetTypeName, dataId=dataId, visit=424) 

1983 metric_model_new = butler.get(metric_ref) 

1984 self.assertEqual(metric_model_new, metric_model) 

1985 

1986 # Hack the storage class again to something that will fail on the 

1987 # get with no conversion class. 

1988 manager._db.update( 

1989 manager._static.dataset_type, 

1990 {"name": datasetTypeName}, 

1991 {datasetTypeName: datasetTypeName, "storage_class": "StructuredDataListYaml"}, 

1992 ) 

1993 butler.registry.refresh() 

1994 

1995 with self.assertRaises(ValueError): 

1996 butler.get(datasetTypeName, dataId=dataId) 

1997 

1998 

1999@unittest.skipUnless(testing is not None, "testing.postgresql module not found") 

2000class PostgresPosixDatastoreButlerTestCase(FileDatastoreButlerTests, unittest.TestCase): 

2001 """PosixDatastore specialization of a butler using Postgres""" 

2002 

2003 configFile = os.path.join(TESTDIR, "config/basic/butler.yaml") 

2004 fullConfigKey = ".datastore.formatters" 

2005 validationCanFail = True 

2006 datastoreStr = ["/tmp"] 

2007 datastoreName = [f"FileDatastore@{BUTLER_ROOT_TAG}"] 

2008 registryStr = "PostgreSQL@test" 

2009 postgresql: Any 

2010 

2011 @staticmethod 

2012 def _handler(postgresql: Any) -> None: 

2013 engine = sqlalchemy.engine.create_engine(postgresql.url()) 

2014 with engine.begin() as connection: 

2015 connection.execute(sqlalchemy.text("CREATE EXTENSION btree_gist;")) 

2016 

2017 @classmethod 

2018 def setUpClass(cls) -> None: 

2019 # Create the postgres test server. 

2020 cls.postgresql = testing.postgresql.PostgresqlFactory( 

2021 cache_initialized_db=True, on_initialized=cls._handler 

2022 ) 

2023 super().setUpClass() 

2024 

2025 @classmethod 

2026 def tearDownClass(cls) -> None: 

2027 # Clean up any lingering SQLAlchemy engines/connections 

2028 # so they're closed before we shut down the server. 

2029 gc.collect() 

2030 cls.postgresql.clear_cache() 

2031 super().tearDownClass() 

2032 

2033 def setUp(self) -> None: 

2034 self.server = self.postgresql() 

2035 

2036 # Need to add a registry section to the config. 

2037 self._temp_config = False 

2038 config = Config(self.configFile) 

2039 config["registry", "db"] = self.server.url() 

2040 with tempfile.NamedTemporaryFile("w", suffix=".yaml", delete=False) as fh: 

2041 config.dump(fh) 

2042 self.configFile = fh.name 

2043 self._temp_config = True 

2044 super().setUp() 

2045 

2046 def tearDown(self) -> None: 

2047 self.server.stop() 

2048 if self._temp_config and os.path.exists(self.configFile): 

2049 os.remove(self.configFile) 

2050 super().tearDown() 

2051 

2052 def testMakeRepo(self) -> None: 

2053 # The base class test assumes that it's using sqlite and assumes 

2054 # the config file is acceptable to sqlite. 

2055 raise unittest.SkipTest("Postgres config is not compatible with this test.") 

2056 

2057 

2058@unittest.skipUnless(testing is not None, "testing.postgresql module not found") 

2059class ClonedPostgresPosixDatastoreButlerTestCase(PostgresPosixDatastoreButlerTestCase, unittest.TestCase): 

2060 """Test that Butler with a Postgres registry still works after cloning.""" 

2061 

2062 def create_butler( 

2063 self, run: str, storageClass: StorageClass | str, datasetTypeName: str 

2064 ) -> tuple[DirectButler, DatasetType]: 

2065 butler, datasetType = super().create_butler(run, storageClass, datasetTypeName) 

2066 return butler._clone(run=run), datasetType 

2067 

2068 

2069class InMemoryDatastoreButlerTestCase(ButlerTests, unittest.TestCase): 

2070 """InMemoryDatastore specialization of a butler""" 

2071 

2072 configFile = os.path.join(TESTDIR, "config/basic/butler-inmemory.yaml") 

2073 fullConfigKey = None 

2074 useTempRoot = False 

2075 validationCanFail = False 

2076 datastoreStr = ["datastore='InMemory"] 

2077 datastoreName = ["InMemoryDatastore@"] 

2078 registryStr = "/gen3.sqlite3" 

2079 

2080 def testIngest(self) -> None: 

2081 pass 

2082 

2083 

2084class ClonedSqliteButlerTestCase(InMemoryDatastoreButlerTestCase, unittest.TestCase): 

2085 """Test that a Butler with a Sqlite registry still works after cloning.""" 

2086 

2087 def create_butler( 

2088 self, run: str, storageClass: StorageClass | str, datasetTypeName: str 

2089 ) -> tuple[DirectButler, DatasetType]: 

2090 butler, datasetType = super().create_butler(run, storageClass, datasetTypeName) 

2091 return butler._clone(run=run), datasetType 

2092 

2093 

2094class ChainedDatastoreButlerTestCase(FileDatastoreButlerTests, unittest.TestCase): 

2095 """PosixDatastore specialization""" 

2096 

2097 configFile = os.path.join(TESTDIR, "config/basic/butler-chained.yaml") 

2098 fullConfigKey = ".datastore.datastores.1.formatters" 

2099 validationCanFail = True 

2100 datastoreStr = ["datastore='InMemory", "/FileDatastore_1/,", "/FileDatastore_2/'"] 

2101 datastoreName = [ 

2102 "InMemoryDatastore@", 

2103 f"FileDatastore@{BUTLER_ROOT_TAG}/FileDatastore_1", 

2104 "SecondDatastore", 

2105 ] 

2106 registryStr = "/gen3.sqlite3" 

2107 

2108 def testPruneDatasets(self) -> None: 

2109 # This test relies on manipulating files out-of-band, which is 

2110 # impossible for this configuration because of the InMemoryDatastore in 

2111 # the ChainedDatastore. 

2112 pass 

2113 

2114 

2115class ButlerExplicitRootTestCase(PosixDatastoreButlerTestCase): 

2116 """Test that a yaml file in one location can refer to a root in another.""" 

2117 

2118 datastoreStr = ["dir1"] 

2119 # Disable the makeRepo test since we are deliberately not using 

2120 # butler.yaml as the config name. 

2121 fullConfigKey = None 

2122 

2123 def setUp(self) -> None: 

2124 self.root = makeTestTempDir(TESTDIR) 

2125 

2126 # Make a new repository in one place 

2127 self.dir1 = os.path.join(self.root, "dir1") 

2128 Butler.makeRepo(self.dir1, config=Config(self.configFile)) 

2129 

2130 # Move the yaml file to a different place and add a "root" 

2131 self.dir2 = os.path.join(self.root, "dir2") 

2132 os.makedirs(self.dir2, exist_ok=True) 

2133 configFile1 = os.path.join(self.dir1, "butler.yaml") 

2134 config = Config(configFile1) 

2135 config["root"] = self.dir1 

2136 configFile2 = os.path.join(self.dir2, "butler2.yaml") 

2137 config.dumpToUri(configFile2) 

2138 os.remove(configFile1) 

2139 self.tmpConfigFile = configFile2 

2140 

2141 def testFileLocations(self) -> None: 

2142 self.assertNotEqual(self.dir1, self.dir2) 

2143 self.assertTrue(os.path.exists(os.path.join(self.dir2, "butler2.yaml"))) 

2144 self.assertFalse(os.path.exists(os.path.join(self.dir1, "butler.yaml"))) 

2145 self.assertTrue(os.path.exists(os.path.join(self.dir1, "gen3.sqlite3"))) 

2146 

2147 

2148class ButlerMakeRepoOutfileTestCase(ButlerPutGetTests, unittest.TestCase): 

2149 """Test that a config file created by makeRepo outside of repo works.""" 

2150 

2151 configFile = os.path.join(TESTDIR, "config/basic/butler.yaml") 

2152 

2153 def setUp(self) -> None: 

2154 self.root = makeTestTempDir(TESTDIR) 

2155 self.root2 = makeTestTempDir(TESTDIR) 

2156 

2157 self.tmpConfigFile = os.path.join(self.root2, "different.yaml") 

2158 Butler.makeRepo(self.root, config=Config(self.configFile), outfile=self.tmpConfigFile) 

2159 

2160 def tearDown(self) -> None: 

2161 if os.path.exists(self.root2): 

2162 shutil.rmtree(self.root2, ignore_errors=True) 

2163 super().tearDown() 

2164 

2165 def testConfigExistence(self) -> None: 

2166 c = Config(self.tmpConfigFile) 

2167 uri_config = ResourcePath(c["root"]) 

2168 uri_expected = ResourcePath(self.root, forceDirectory=True) 

2169 self.assertEqual(uri_config.geturl(), uri_expected.geturl()) 

2170 self.assertNotIn(":", uri_config.path, "Check for URI concatenated with normal path") 

2171 

2172 def testPutGet(self) -> None: 

2173 storageClass = self.storageClassFactory.getStorageClass("StructuredDataNoComponents") 

2174 self.runPutGetTest(storageClass, "test_metric") 

2175 

2176 

2177class ButlerMakeRepoOutfileDirTestCase(ButlerMakeRepoOutfileTestCase): 

2178 """Test that a config file created by makeRepo outside of repo works.""" 

2179 

2180 configFile = os.path.join(TESTDIR, "config/basic/butler.yaml") 

2181 

2182 def setUp(self) -> None: 

2183 self.root = makeTestTempDir(TESTDIR) 

2184 self.root2 = makeTestTempDir(TESTDIR) 

2185 

2186 self.tmpConfigFile = self.root2 

2187 Butler.makeRepo(self.root, config=Config(self.configFile), outfile=self.tmpConfigFile) 

2188 

2189 def testConfigExistence(self) -> None: 

2190 # Append the yaml file else Config constructor does not know the file 

2191 # type. 

2192 self.tmpConfigFile = os.path.join(self.tmpConfigFile, "butler.yaml") 

2193 super().testConfigExistence() 

2194 

2195 

2196class ButlerMakeRepoOutfileUriTestCase(ButlerMakeRepoOutfileTestCase): 

2197 """Test that a config file created by makeRepo outside of repo works.""" 

2198 

2199 configFile = os.path.join(TESTDIR, "config/basic/butler.yaml") 

2200 

2201 def setUp(self) -> None: 

2202 self.root = makeTestTempDir(TESTDIR) 

2203 self.root2 = makeTestTempDir(TESTDIR) 

2204 

2205 self.tmpConfigFile = ResourcePath(os.path.join(self.root2, "something.yaml")).geturl() 

2206 Butler.makeRepo(self.root, config=Config(self.configFile), outfile=self.tmpConfigFile) 

2207 

2208 

2209@unittest.skipIf(not boto3, "Warning: boto3 AWS SDK not found!") 

2210class S3DatastoreButlerTestCase(FileDatastoreButlerTests, unittest.TestCase): 

2211 """S3Datastore specialization of a butler; an S3 storage Datastore + 

2212 a local in-memory SqlRegistry. 

2213 """ 

2214 

2215 configFile = os.path.join(TESTDIR, "config/basic/butler-s3store.yaml") 

2216 fullConfigKey = None 

2217 validationCanFail = True 

2218 

2219 bucketName = "anybucketname" 

2220 """Name of the Bucket that will be used in the tests. The name is read from 

2221 the config file used with the tests during set-up. 

2222 """ 

2223 

2224 root = "butlerRoot/" 

2225 """Root repository directory expected to be used in case useTempRoot=False. 

2226 Otherwise the root is set to a 20 characters long randomly generated string 

2227 during set-up. 

2228 """ 

2229 

2230 datastoreStr = [f"datastore={root}"] 

2231 """Contains all expected root locations in a format expected to be 

2232 returned by Butler stringification. 

2233 """ 

2234 

2235 datastoreName = ["FileDatastore@s3://{bucketName}/{root}"] 

2236 """The expected format of the S3 Datastore string.""" 

2237 

2238 registryStr = "/gen3.sqlite3" 

2239 """Expected format of the Registry string.""" 

2240 

2241 mock_aws = mock_aws() 

2242 """The mocked s3 interface from moto.""" 

2243 

2244 def genRoot(self) -> str: 

2245 """Return a random string of len 20 to serve as a root 

2246 name for the temporary bucket repo. 

2247 

2248 This is equivalent to tempfile.mkdtemp as this is what self.root 

2249 becomes when useTempRoot is True. 

2250 """ 

2251 rndstr = "".join(random.choice(string.ascii_uppercase + string.digits) for _ in range(20)) 

2252 return rndstr + "/" 

2253 

2254 def setUp(self) -> None: 

2255 config = Config(self.configFile) 

2256 uri = ResourcePath(config[".datastore.datastore.root"]) 

2257 self.bucketName = uri.netloc 

2258 

2259 # Enable S3 mocking of tests. 

2260 self.enterContext(clean_test_environment_for_s3()) 

2261 self.mock_aws.start() 

2262 

2263 if self.useTempRoot: 

2264 self.root = self.genRoot() 

2265 rooturi = f"s3://{self.bucketName}/{self.root}" 

2266 config.update({"datastore": {"datastore": {"root": rooturi}}}) 

2267 

2268 # need local folder to store registry database 

2269 self.reg_dir = makeTestTempDir(TESTDIR) 

2270 config["registry", "db"] = f"sqlite:///{self.reg_dir}/gen3.sqlite3" 

2271 

2272 # MOTO needs to know that we expect Bucket bucketname to exist 

2273 # (this used to be the class attribute bucketName) 

2274 s3 = boto3.resource("s3") 

2275 s3.create_bucket(Bucket=self.bucketName) 

2276 

2277 self.datastoreStr = [f"datastore='{rooturi}'"] 

2278 self.datastoreName = [f"FileDatastore@{rooturi}"] 

2279 Butler.makeRepo(rooturi, config=config, forceConfigRoot=False) 

2280 self.tmpConfigFile = posixpath.join(rooturi, "butler.yaml") 

2281 

2282 def tearDown(self) -> None: 

2283 s3 = boto3.resource("s3") 

2284 bucket = s3.Bucket(self.bucketName) 

2285 try: 

2286 bucket.objects.all().delete() 

2287 except botocore.exceptions.ClientError as e: 

2288 if e.response["Error"]["Code"] == "404": 

2289 # the key was not reachable - pass 

2290 pass 

2291 else: 

2292 raise 

2293 

2294 bucket = s3.Bucket(self.bucketName) 

2295 bucket.delete() 

2296 

2297 # Stop the S3 mock. 

2298 self.mock_aws.stop() 

2299 

2300 if self.reg_dir is not None and os.path.exists(self.reg_dir): 

2301 shutil.rmtree(self.reg_dir, ignore_errors=True) 

2302 

2303 if self.useTempRoot and os.path.exists(self.root): 

2304 shutil.rmtree(self.root, ignore_errors=True) 

2305 

2306 super().tearDown() 

2307 

2308 

2309class PosixDatastoreTransfers(unittest.TestCase): 

2310 """Test data transfers between butlers. 

2311 

2312 Test for different managers. UUID to UUID and integer to integer are 

2313 tested. UUID to integer is not supported since we do not currently 

2314 want to allow that. Integer to UUID is supported with the caveat 

2315 that UUID4 will be generated and this will be incorrect for raw 

2316 dataset types. The test ignores that. 

2317 """ 

2318 

2319 configFile = os.path.join(TESTDIR, "config/basic/butler.yaml") 

2320 storageClassFactory: StorageClassFactory 

2321 

2322 @classmethod 

2323 def setUpClass(cls) -> None: 

2324 cls.storageClassFactory = StorageClassFactory() 

2325 cls.storageClassFactory.addFromConfig(cls.configFile) 

2326 

2327 def setUp(self) -> None: 

2328 self.root = makeTestTempDir(TESTDIR) 

2329 self.config = Config(self.configFile) 

2330 

2331 def tearDown(self) -> None: 

2332 removeTestTempDir(self.root) 

2333 

2334 def create_butler(self, manager: str, label: str) -> Butler: 

2335 config = Config(self.configFile) 

2336 config["registry", "managers", "datasets"] = manager 

2337 return Butler.from_config( 

2338 Butler.makeRepo(f"{self.root}/butler{label}", config=config), writeable=True 

2339 ) 

2340 

2341 def create_butlers(self, manager1: str | None = None, manager2: str | None = None) -> None: 

2342 default = "lsst.daf.butler.registry.datasets.byDimensions.ByDimensionsDatasetRecordStorageManagerUUID" 

2343 if manager1 is None: 

2344 manager1 = default 

2345 if manager2 is None: 

2346 manager2 = default 

2347 self.source_butler = self.create_butler(manager1, "1") 

2348 self.target_butler = self.create_butler(manager2, "2") 

2349 

2350 def testTransferUuidToUuid(self) -> None: 

2351 self.create_butlers() 

2352 self.assertButlerTransfers() 

2353 

2354 def testTransferMissing(self) -> None: 

2355 """Test transfers where datastore records are missing. 

2356 

2357 This is how execution butler works. 

2358 """ 

2359 self.create_butlers() 

2360 

2361 # Configure the source butler to allow trust. 

2362 self.source_butler._datastore._set_trust_mode(True) 

2363 

2364 self.assertButlerTransfers(purge=True) 

2365 

2366 def testTransferMissingDisassembly(self) -> None: 

2367 """Test transfers where datastore records are missing. 

2368 

2369 This is how execution butler works. 

2370 """ 

2371 self.create_butlers() 

2372 

2373 # Configure the source butler to allow trust. 

2374 self.source_butler._datastore._set_trust_mode(True) 

2375 

2376 # Test disassembly. 

2377 self.assertButlerTransfers(purge=True, storageClassName="StructuredComposite") 

2378 

2379 def testAbsoluteURITransferDirect(self) -> None: 

2380 """Test transfer using an absolute URI.""" 

2381 self._absolute_transfer("auto") 

2382 

2383 def testAbsoluteURITransferCopy(self) -> None: 

2384 """Test transfer using an absolute URI.""" 

2385 self._absolute_transfer("copy") 

2386 

2387 def _absolute_transfer(self, transfer: str) -> None: 

2388 self.create_butlers() 

2389 

2390 storageClassName = "StructuredData" 

2391 storageClass = self.storageClassFactory.getStorageClass(storageClassName) 

2392 datasetTypeName = "random_data" 

2393 run = "run1" 

2394 self.source_butler.registry.registerCollection(run, CollectionType.RUN) 

2395 

2396 dimensions = self.source_butler.dimensions.conform(()) 

2397 datasetType = DatasetType(datasetTypeName, dimensions, storageClass) 

2398 self.source_butler.registry.registerDatasetType(datasetType) 

2399 

2400 metrics = makeExampleMetrics() 

2401 with ResourcePath.temporary_uri(suffix=".json") as temp: 

2402 dataId = DataCoordinate.make_empty(self.source_butler.dimensions) 

2403 source_refs = [DatasetRef(datasetType, dataId, run=run)] 

2404 temp.write(json.dumps(metrics.exportAsDict()).encode()) 

2405 dataset = FileDataset(path=temp, refs=source_refs) 

2406 self.source_butler.ingest(dataset, transfer="direct") 

2407 

2408 self.target_butler.transfer_from( 

2409 self.source_butler, dataset.refs, register_dataset_types=True, transfer=transfer 

2410 ) 

2411 

2412 uri = self.target_butler.getURI(dataset.refs[0]) 

2413 if transfer == "auto": 

2414 self.assertEqual(uri, temp) 

2415 else: 

2416 self.assertNotEqual(uri, temp) 

2417 

2418 def assertButlerTransfers(self, purge: bool = False, storageClassName: str = "StructuredData") -> None: 

2419 """Test that a run can be transferred to another butler.""" 

2420 storageClass = self.storageClassFactory.getStorageClass(storageClassName) 

2421 datasetTypeName = "random_data" 

2422 

2423 # Test will create 3 collections and we will want to transfer 

2424 # two of those three. 

2425 runs = ["run1", "run2", "other"] 

2426 

2427 # Also want to use two different dataset types to ensure that 

2428 # grouping works. 

2429 datasetTypeNames = ["random_data", "random_data_2"] 

2430 

2431 # Create the run collections in the source butler. 

2432 for run in runs: 

2433 self.source_butler.registry.registerCollection(run, CollectionType.RUN) 

2434 

2435 # Create dimensions in source butler. 

2436 n_exposures = 30 

2437 self.source_butler.registry.insertDimensionData("instrument", {"name": "DummyCamComp"}) 

2438 self.source_butler.registry.insertDimensionData( 

2439 "physical_filter", {"instrument": "DummyCamComp", "name": "d-r", "band": "R"} 

2440 ) 

2441 self.source_butler.registry.insertDimensionData( 

2442 "detector", {"instrument": "DummyCamComp", "id": 1, "full_name": "det1"} 

2443 ) 

2444 self.source_butler.registry.insertDimensionData( 

2445 "day_obs", 

2446 { 

2447 "instrument": "DummyCamComp", 

2448 "id": 20250101, 

2449 }, 

2450 ) 

2451 

2452 for i in range(n_exposures): 

2453 self.source_butler.registry.insertDimensionData( 

2454 "group", {"instrument": "DummyCamComp", "name": f"group{i}"} 

2455 ) 

2456 self.source_butler.registry.insertDimensionData( 

2457 "exposure", 

2458 { 

2459 "instrument": "DummyCamComp", 

2460 "id": i, 

2461 "obs_id": f"exp{i}", 

2462 "physical_filter": "d-r", 

2463 "group": f"group{i}", 

2464 "day_obs": 20250101, 

2465 }, 

2466 ) 

2467 

2468 # Create dataset types in the source butler. 

2469 dimensions = self.source_butler.dimensions.conform(["instrument", "exposure"]) 

2470 for datasetTypeName in datasetTypeNames: 

2471 datasetType = DatasetType(datasetTypeName, dimensions, storageClass) 

2472 self.source_butler.registry.registerDatasetType(datasetType) 

2473 

2474 # Write a dataset to an unrelated run -- this will ensure that 

2475 # we are rewriting integer dataset ids in the target if necessary. 

2476 # Will not be relevant for UUID. 

2477 run = "distraction" 

2478 butler = Butler.from_config(butler=self.source_butler, run=run) 

2479 butler.put( 

2480 makeExampleMetrics(), 

2481 datasetTypeName, 

2482 exposure=1, 

2483 instrument="DummyCamComp", 

2484 physical_filter="d-r", 

2485 ) 

2486 

2487 # Write some example metrics to the source 

2488 butler = Butler.from_config(butler=self.source_butler) 

2489 

2490 # Set of DatasetRefs that should be in the list of refs to transfer 

2491 # but which will not be transferred. 

2492 deleted: set[DatasetRef] = set() 

2493 

2494 n_expected = 20 # Number of datasets expected to be transferred 

2495 source_refs = [] 

2496 for i in range(n_exposures): 

2497 # Put a third of datasets into each collection, only retain 

2498 # two thirds. 

2499 index = i % 3 

2500 run = runs[index] 

2501 datasetTypeName = datasetTypeNames[i % 2] 

2502 

2503 metric = MetricsExample( 

2504 summary={"counter": i}, output={"text": "metric"}, data=[2 * x for x in range(i)] 

2505 ) 

2506 dataId = {"exposure": i, "instrument": "DummyCamComp", "physical_filter": "d-r"} 

2507 ref = butler.put(metric, datasetTypeName, dataId=dataId, run=run) 

2508 

2509 # Remove the datastore record using low-level API, but only 

2510 # for a specific index. 

2511 if purge and index == 1: 

2512 # For one of these delete the file as well. 

2513 # This allows the "missing" code to filter the 

2514 # file out. 

2515 # Access the individual datastores. 

2516 datastores = [] 

2517 if hasattr(butler._datastore, "datastores"): 

2518 datastores.extend(butler._datastore.datastores) 

2519 else: 

2520 datastores.append(butler._datastore) 

2521 

2522 if not deleted: 

2523 # For a chained datastore we need to remove 

2524 # files in each chain. 

2525 for datastore in datastores: 

2526 # The file might not be known to the datastore 

2527 # if constraints are used. 

2528 try: 

2529 primary, uris = datastore.getURIs(ref) 

2530 except FileNotFoundError: 

2531 continue 

2532 if primary and primary.scheme != "mem": 

2533 primary.remove() 

2534 for uri in uris.values(): 

2535 if uri.scheme != "mem": 

2536 uri.remove() 

2537 n_expected -= 1 

2538 deleted.add(ref) 

2539 

2540 # Remove the datastore record. 

2541 for datastore in datastores: 

2542 if hasattr(datastore, "removeStoredItemInfo"): 

2543 datastore.removeStoredItemInfo(ref) 

2544 

2545 if index < 2: 

2546 source_refs.append(ref) 

2547 if ref not in deleted: 

2548 new_metric = butler.get(ref) 

2549 self.assertEqual(new_metric, metric) 

2550 

2551 # Create some bad dataset types to ensure we check for inconsistent 

2552 # definitions. 

2553 badStorageClass = self.storageClassFactory.getStorageClass("StructuredDataList") 

2554 for datasetTypeName in datasetTypeNames: 

2555 datasetType = DatasetType(datasetTypeName, dimensions, badStorageClass) 

2556 self.target_butler.registry.registerDatasetType(datasetType) 

2557 with self.assertRaises(ConflictingDefinitionError) as cm: 

2558 self.target_butler.transfer_from(self.source_butler, source_refs) 

2559 self.assertIn("dataset type differs", str(cm.exception)) 

2560 

2561 # And remove the bad definitions. 

2562 for datasetTypeName in datasetTypeNames: 

2563 self.target_butler.registry.removeDatasetType(datasetTypeName) 

2564 

2565 # Transfer without creating dataset types should fail. 

2566 with self.assertRaises(KeyError): 

2567 self.target_butler.transfer_from(self.source_butler, source_refs) 

2568 

2569 # Transfer without creating dimensions should fail. 

2570 with self.assertRaises(ConflictingDefinitionError) as cm: 

2571 self.target_butler.transfer_from(self.source_butler, source_refs, register_dataset_types=True) 

2572 self.assertIn("dimension", str(cm.exception)) 

2573 

2574 # The failed transfer above leaves registry in an inconsistent 

2575 # state because the run is created but then rolled back without 

2576 # the collection cache being cleared. For now force a refresh. 

2577 # Can remove with DM-35498. 

2578 self.target_butler.registry.refresh() 

2579 

2580 # Do a dry run -- this should not have any effect on the target butler. 

2581 self.target_butler.transfer_from(self.source_butler, source_refs, dry_run=True) 

2582 

2583 # Transfer the records for one ref to test the alternative API. 

2584 with self.assertLogs(logger="lsst", level=logging.DEBUG) as log_cm: 

2585 self.target_butler.transfer_dimension_records_from(self.source_butler, [source_refs[0]]) 

2586 self.assertIn("number of records transferred: 1", ";".join(log_cm.output)) 

2587 

2588 # Now transfer them to the second butler, including dimensions. 

2589 with self.assertLogs(logger="lsst", level=logging.DEBUG) as log_cm: 

2590 transferred = self.target_butler.transfer_from( 

2591 self.source_butler, 

2592 source_refs, 

2593 register_dataset_types=True, 

2594 transfer_dimensions=True, 

2595 ) 

2596 self.assertEqual(len(transferred), n_expected) 

2597 log_output = ";".join(log_cm.output) 

2598 

2599 # A ChainedDatastore will use the in-memory datastore for mexists 

2600 # so we can not rely on the mexists log message. 

2601 self.assertIn("Number of datastore records found in source", log_output) 

2602 self.assertIn("Creating output run", log_output) 

2603 

2604 # Do the transfer twice to ensure that it will do nothing extra. 

2605 # Only do this if purge=True because it does not work for int 

2606 # dataset_id. 

2607 if purge: 

2608 # This should not need to register dataset types. 

2609 transferred = self.target_butler.transfer_from(self.source_butler, source_refs) 

2610 self.assertEqual(len(transferred), n_expected) 

2611 

2612 # Also do an explicit low-level transfer to trigger some 

2613 # edge cases. 

2614 with self.assertLogs(level=logging.DEBUG) as log_cm: 

2615 self.target_butler._datastore.transfer_from(self.source_butler._datastore, source_refs) 

2616 log_output = ";".join(log_cm.output) 

2617 self.assertIn("no file artifacts exist", log_output) 

2618 

2619 with self.assertRaises((TypeError, AttributeError)): 

2620 self.target_butler._datastore.transfer_from(self.source_butler, source_refs) # type: ignore 

2621 

2622 with self.assertRaises(ValueError): 

2623 self.target_butler._datastore.transfer_from( 

2624 self.source_butler._datastore, source_refs, transfer="split" 

2625 ) 

2626 

2627 # Now try to get the same refs from the new butler. 

2628 for ref in source_refs: 

2629 if ref not in deleted: 

2630 new_metric = self.target_butler.get(ref) 

2631 old_metric = self.source_butler.get(ref) 

2632 self.assertEqual(new_metric, old_metric) 

2633 

2634 # Now prune run2 collection and create instead a CHAINED collection. 

2635 # This should block the transfer. 

2636 self.target_butler.removeRuns(["run2"], unstore=True) 

2637 self.target_butler.registry.registerCollection("run2", CollectionType.CHAINED) 

2638 with self.assertRaises(CollectionTypeError): 

2639 # Re-importing the run1 datasets can be problematic if they 

2640 # use integer IDs so filter those out. 

2641 to_transfer = [ref for ref in source_refs if ref.run == "run2"] 

2642 self.target_butler.transfer_from(self.source_butler, to_transfer) 

2643 

2644 

2645class ChainedDatastoreTransfers(PosixDatastoreTransfers): 

2646 """Test transfers using a chained datastore.""" 

2647 

2648 configFile = os.path.join(TESTDIR, "config/basic/butler-chained.yaml") 

2649 

2650 

2651class NullDatastoreTestCase(unittest.TestCase): 

2652 """Test that we can fall back to a null datastore.""" 

2653 

2654 # Need a good config to create the repo. 

2655 configFile = os.path.join(TESTDIR, "config/basic/butler.yaml") 

2656 storageClassFactory: StorageClassFactory 

2657 

2658 @classmethod 

2659 def setUpClass(cls) -> None: 

2660 cls.storageClassFactory = StorageClassFactory() 

2661 cls.storageClassFactory.addFromConfig(cls.configFile) 

2662 

2663 def setUp(self) -> None: 

2664 """Create a new butler root for each test.""" 

2665 self.root = makeTestTempDir(TESTDIR) 

2666 Butler.makeRepo(self.root, config=Config(self.configFile)) 

2667 

2668 def tearDown(self) -> None: 

2669 removeTestTempDir(self.root) 

2670 

2671 def test_fallback(self) -> None: 

2672 # Read the butler config and mess with the datastore section. 

2673 config_path = os.path.join(self.root, "butler.yaml") 

2674 bad_config = Config(config_path) 

2675 bad_config["datastore", "cls"] = "lsst.not.a.datastore.Datastore" 

2676 bad_config.dumpToUri(config_path) 

2677 

2678 with self.assertRaises(RuntimeError): 

2679 Butler(self.root, without_datastore=False) 

2680 

2681 with self.assertRaises(RuntimeError): 

2682 Butler.from_config(self.root, without_datastore=False) 

2683 

2684 butler = Butler.from_config(self.root, writeable=True, without_datastore=True) 

2685 self.assertIsInstance(butler._datastore, NullDatastore) 

2686 

2687 # Check that registry is working. 

2688 butler.registry.registerRun("MYRUN") 

2689 collections = butler.registry.queryCollections(...) 

2690 self.assertIn("MYRUN", set(collections)) 

2691 

2692 # Create a ref. 

2693 dimensions = butler.dimensions.conform([]) 

2694 storageClass = self.storageClassFactory.getStorageClass("StructuredDataDict") 

2695 datasetTypeName = "metric" 

2696 datasetType = DatasetType(datasetTypeName, dimensions, storageClass) 

2697 butler.registry.registerDatasetType(datasetType) 

2698 ref = DatasetRef(datasetType, {}, run="MYRUN") 

2699 

2700 # Check that datastore will complain. 

2701 with self.assertRaises(FileNotFoundError): 

2702 butler.get(ref) 

2703 with self.assertRaises(FileNotFoundError): 

2704 butler.getURI(ref) 

2705 

2706 

2707@unittest.skipIf(create_test_server is None, "Server dependencies not installed.") 

2708class ButlerServerTests(FileDatastoreButlerTests, unittest.TestCase): 

2709 """Test RemoteButler and Butler server.""" 

2710 

2711 configFile = None 

2712 predictionSupported = False 

2713 trustModeSupported = False 

2714 

2715 def setUp(self): 

2716 self.server_instance = self.enterContext(create_test_server(TESTDIR)) 

2717 

2718 def tearDown(self): 

2719 pass 

2720 

2721 def are_uris_equivalent(self, uri1: ResourcePath, uri2: ResourcePath) -> bool: 

2722 # S3 pre-signed URLs may end up with differing expiration times in the 

2723 # query parameters, so ignore query parameters when comparing. 

2724 return uri1.scheme == uri2.scheme and uri1.netloc == uri2.netloc and uri1.path == uri2.path 

2725 

2726 def create_empty_butler(self, run: str | None = None, writeable: bool | None = None) -> Butler: 

2727 return self.server_instance.hybrid_butler._clone(run=run) 

2728 

2729 def remove_dataset_out_of_band(self, butler: Butler, ref: DatasetRef) -> None: 

2730 # Can't delete a file via S3 signed URLs, so we need to reach in 

2731 # through DirectButler to delete the dataset. 

2732 uri = self.server_instance.direct_butler.getURI(ref) 

2733 uri.remove() 

2734 

2735 def testConstructor(self): 

2736 # RemoteButler constructor is tested in test_server.py and 

2737 # test_remote_butler.py. 

2738 pass 

2739 

2740 def testDafButlerRepositories(self): 

2741 # Loading of RemoteButler via repository index is tested in 

2742 # test_server.py. 

2743 pass 

2744 

2745 def testGetDatasetTypes(self) -> None: 

2746 # This is mostly a test of validateConfiguration, which is for 

2747 # validating Datastore configuration and thus isn't relevant to 

2748 # RemoteButler. 

2749 pass 

2750 

2751 def testMakeRepo(self) -> None: 

2752 # Only applies to DirectButler. 

2753 pass 

2754 

2755 # Pickling not yet implemented for RemoteButler/HybridButler. 

2756 @unittest.expectedFailure 

2757 def testPickle(self) -> None: 

2758 return super().testPickle() 

2759 

2760 def testStringification(self) -> None: 

2761 self.assertEqual( 

2762 str(self.server_instance.remote_butler), 

2763 "RemoteButler(https://test.example/api/butler/repo/testrepo)", 

2764 ) 

2765 

2766 def testTransaction(self) -> None: 

2767 # Transactions will never be supported for RemoteButler. 

2768 pass 

2769 

2770 def testPutTemplates(self) -> None: 

2771 # The Butler server instance is configured with different file naming 

2772 # templates than this test is expecting. 

2773 pass 

2774 

2775 

2776def setup_module(module: types.ModuleType) -> None: 

2777 """Set up the module for pytest.""" 

2778 clean_environment() 

2779 

2780 

2781if __name__ == "__main__": 

2782 clean_environment() 

2783 unittest.main()