Coverage for tests/test_butler.py: 13%

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1# This file is part of daf_butler. 

2# 

3# Developed for the LSST Data Management System. 

4# This product includes software developed by the LSST Project 

5# (http://www.lsst.org). 

6# See the COPYRIGHT file at the top-level directory of this distribution 

7# for details of code ownership. 

8# 

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

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

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

12# (at your option) any later version. 

13# 

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

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

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

17# GNU General Public License for more details. 

18# 

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

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

21 

22"""Tests for Butler. 

23""" 

24from __future__ import annotations 

25 

26import gc 

27import json 

28import logging 

29import os 

30import pathlib 

31import pickle 

32import posixpath 

33import random 

34import shutil 

35import string 

36import tempfile 

37import unittest 

38import uuid 

39from collections.abc import Mapping 

40from typing import TYPE_CHECKING, Any, cast 

41 

42try: 

43 import boto3 

44 import botocore 

45 from moto import mock_s3 # type: ignore[import] 

46except ImportError: 

47 boto3 = None 

48 

49 def mock_s3(cls): 

50 """A no-op decorator in case moto mock_s3 can not be imported.""" 

51 return cls 

52 

53 

54try: 

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

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

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

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

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

60except ImportError: 

61 testing = None 

62 

63import astropy.time 

64import sqlalchemy 

65from lsst.daf.butler import ( 

66 Butler, 

67 ButlerConfig, 

68 CollectionType, 

69 Config, 

70 DataCoordinate, 

71 DatasetRef, 

72 DatasetType, 

73 FileDataset, 

74 FileTemplate, 

75 FileTemplateValidationError, 

76 StorageClassFactory, 

77 ValidationError, 

78 script, 

79) 

80from lsst.daf.butler.core.repoRelocation import BUTLER_ROOT_TAG 

81from lsst.daf.butler.datastores.fileDatastore import FileDatastore 

82from lsst.daf.butler.registries.sql import SqlRegistry 

83from lsst.daf.butler.registry import ( 

84 CollectionError, 

85 CollectionTypeError, 

86 ConflictingDefinitionError, 

87 DataIdValueError, 

88 MissingCollectionError, 

89 OrphanedRecordError, 

90) 

91from lsst.daf.butler.tests import MetricsExample, MultiDetectorFormatter 

92from lsst.daf.butler.tests.utils import TestCaseMixin, makeTestTempDir, removeTestTempDir, safeTestTempDir 

93from lsst.resources import ResourcePath 

94from lsst.resources.s3utils import setAwsEnvCredentials, unsetAwsEnvCredentials 

95from lsst.utils import doImportType 

96from lsst.utils.ellipsis import Ellipsis 

97from lsst.utils.introspection import get_full_type_name 

98 

99if TYPE_CHECKING: 

100 from lsst.daf.butler import Datastore, DimensionGraph, Registry, StorageClass 

101 

102TESTDIR = os.path.abspath(os.path.dirname(__file__)) 

103 

104 

105def makeExampleMetrics(): 

106 return MetricsExample( 

107 {"AM1": 5.2, "AM2": 30.6}, 

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

109 [563, 234, 456.7, 752, 8, 9, 27], 

110 ) 

111 

112 

113class TransactionTestError(Exception): 

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

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

116 """ 

117 

118 pass 

119 

120 

121class ButlerConfigTests(unittest.TestCase): 

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

123 cases.""" 

124 

125 def testSearchPath(self): 

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

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

128 config1 = ButlerConfig(configFile) 

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

130 

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

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

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

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

135 

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

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

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

139 

140 

141class ButlerPutGetTests(TestCaseMixin): 

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

143 butler configurations.""" 

144 

145 root: str 

146 default_run = "ingésτ😺" 

147 storageClassFactory: StorageClassFactory 

148 configFile: str 

149 tmpConfigFile: str 

150 

151 @staticmethod 

152 def addDatasetType( 

153 datasetTypeName: str, dimensions: DimensionGraph, storageClass: StorageClass | str, registry: Registry 

154 ) -> DatasetType: 

155 """Create a DatasetType and register it""" 

156 datasetType = DatasetType(datasetTypeName, dimensions, storageClass) 

157 registry.registerDatasetType(datasetType) 

158 return datasetType 

159 

160 @classmethod 

161 def setUpClass(cls) -> None: 

162 cls.storageClassFactory = StorageClassFactory() 

163 cls.storageClassFactory.addFromConfig(cls.configFile) 

164 

165 def assertGetComponents(self, butler, datasetRef, components, reference, collections=None) -> None: 

166 datasetType = datasetRef.datasetType 

167 dataId = datasetRef.dataId 

168 deferred = butler.getDeferred(datasetRef) 

169 

170 for component in components: 

171 compTypeName = datasetType.componentTypeName(component) 

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

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

174 result_deferred = deferred.get(component=component) 

175 self.assertEqual(result_deferred, result) 

176 

177 def tearDown(self) -> None: 

178 removeTestTempDir(self.root) 

179 

180 def create_butler( 

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

182 ) -> tuple[Butler, DatasetType]: 

183 butler = Butler(self.tmpConfigFile, run=run) 

184 

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

186 self.assertEqual(collections, set([run])) 

187 

188 # Create and register a DatasetType 

189 dimensions = butler.registry.dimensions.extract(["instrument", "visit"]) 

190 

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

192 

193 # Add needed Dimensions 

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

195 butler.registry.insertDimensionData( 

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

197 ) 

198 butler.registry.insertDimensionData( 

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

200 ) 

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

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

203 butler.registry.insertDimensionData( 

204 "visit", 

205 { 

206 "instrument": "DummyCamComp", 

207 "id": 423, 

208 "name": "fourtwentythree", 

209 "physical_filter": "d-r", 

210 "visit_system": 1, 

211 "datetime_begin": visit_start, 

212 "datetime_end": visit_end, 

213 }, 

214 ) 

215 

216 # Add more visits for some later tests 

217 for visit_id in (424, 425): 

218 butler.registry.insertDimensionData( 

219 "visit", 

220 { 

221 "instrument": "DummyCamComp", 

222 "id": visit_id, 

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

224 "physical_filter": "d-r", 

225 "visit_system": 1, 

226 }, 

227 ) 

228 return butler, datasetType 

229 

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

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

232 # tag when looking up datasets. 

233 run = self.default_run 

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

235 assert butler.run is not None 

236 

237 # Create and store a dataset 

238 metric = makeExampleMetrics() 

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

240 

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

242 # and once with a DatasetType 

243 

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

245 expected_collections = {run} 

246 

247 counter = 0 

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

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

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

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

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

253 # immediately because the dataset already exists. Work around 

254 # this by using a distinct run collection each time 

255 counter += 1 

256 this_run = f"put_run_{counter}" 

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

258 expected_collections.update({this_run}) 

259 

260 with self.subTest(args=args): 

261 ref = butler.put(metric, *args, run=this_run) 

262 self.assertIsInstance(ref, DatasetRef) 

263 

264 # Test getDirect 

265 metricOut = butler.get(ref) 

266 self.assertEqual(metric, metricOut) 

267 # Test get 

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

269 self.assertEqual(metric, metricOut) 

270 # Test get with a datasetRef 

271 metricOut = butler.get(ref, collections=this_run) 

272 self.assertEqual(metric, metricOut) 

273 # Test getDeferred with dataId 

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

275 self.assertEqual(metric, metricOut) 

276 # Test getDeferred with a datasetRef 

277 metricOut = butler.getDeferred(ref, collections=this_run).get() 

278 self.assertEqual(metric, metricOut) 

279 # and deferred direct with ref 

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

281 self.assertEqual(metric, metricOut) 

282 

283 # Check we can get components 

284 if storageClass.isComposite(): 

285 self.assertGetComponents( 

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

287 ) 

288 

289 # Can the artifacts themselves be retrieved? 

290 if not butler.datastore.isEphemeral: 

291 root_uri = ResourcePath(self.root) 

292 

293 for preserve_path in (True, False): 

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

295 # Use copy so that we can test that overwrite 

296 # protection works (using "auto" for File URIs would 

297 # use hard links and subsequent transfer would work 

298 # because it knows they are the same file). 

299 transferred = butler.retrieveArtifacts( 

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

301 ) 

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

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

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

305 

306 for artifact in transferred: 

307 path_in_destination = artifact.relative_to(destination) 

308 self.assertIsNotNone(path_in_destination) 

309 assert path_in_destination is not None 

310 

311 # when path is not preserved there should not be 

312 # any path separators. 

313 num_seps = path_in_destination.count("/") 

314 if preserve_path: 

315 self.assertGreater(num_seps, 0) 

316 else: 

317 self.assertEqual(num_seps, 0) 

318 

319 primary_uri, secondary_uris = butler.datastore.getURIs(ref) 

320 n_uris = len(secondary_uris) 

321 if primary_uri: 

322 n_uris += 1 

323 self.assertEqual( 

324 len(artifacts), 

325 n_uris, 

326 "Comparing expected artifacts vs actual:" 

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

328 ) 

329 

330 if preserve_path: 

331 # No need to run these twice 

332 with self.assertRaises(ValueError): 

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

334 

335 with self.assertRaises(FileExistsError): 

336 butler.retrieveArtifacts([ref], destination) 

337 

338 transferred_again = butler.retrieveArtifacts( 

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

340 ) 

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

342 

343 # Now remove the dataset completely. 

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

345 # Lookup with original args should still fail. 

346 with self.assertRaises(LookupError): 

347 butler.datasetExists(*args, collections=this_run) 

348 # get() should still fail. 

349 with self.assertRaises(FileNotFoundError): 

350 butler.get(ref) 

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

352 self.assertIsNone(butler.registry.getDataset(ref.id)) 

353 

354 # Do explicit registry removal since we know they are 

355 # empty 

356 butler.registry.removeCollection(this_run) 

357 expected_collections.remove(this_run) 

358 

359 # Create DatasetRef for put using default run. 

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

361 

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

363 # and we want to use the default collection. 

364 ref = butler.put(metric, refIn) 

365 

366 # Get with parameters 

367 stop = 4 

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

369 self.assertNotEqual(metric, sliced) 

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

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

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

373 # getDeferred with parameters 

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

375 self.assertNotEqual(metric, sliced) 

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

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

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

379 # getDeferred with deferred parameters 

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

381 self.assertNotEqual(metric, sliced) 

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

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

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

385 

386 if storageClass.isComposite(): 

387 # Check that components can be retrieved 

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

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

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

391 summary = butler.get(compNameS, dataId) 

392 self.assertEqual(summary, metric.summary) 

393 data = butler.get(compNameD, dataId) 

394 self.assertEqual(data, metric.data) 

395 

396 if "counter" in storageClass.derivedComponents: 

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

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

399 

400 count = butler.get( 

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

402 ) 

403 self.assertEqual(count, stop) 

404 

405 compRef = butler.registry.findDataset(compNameS, dataId, collections=butler.collections) 

406 assert compRef is not None 

407 summary = butler.get(compRef) 

408 self.assertEqual(summary, metric.summary) 

409 

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

411 inconsistentDatasetType = DatasetType( 

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

413 ) 

414 

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

416 with self.assertRaisesRegex(ValueError, "Supplied dataset type .* inconsistent with registry"): 

417 butler.get(inconsistentDatasetType, dataId) 

418 

419 # Combining a DatasetRef with a dataId should fail 

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

421 butler.get(ref, dataId) 

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

423 with self.assertRaises(FileNotFoundError): 

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

425 

426 # Getting a dataset with unknown parameters should fail 

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

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

429 

430 # Check we have a collection 

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

432 self.assertEqual(collections, expected_collections) 

433 

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

435 # already had a component removed 

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

437 

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

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

440 

441 # Repeat put will fail. 

442 with self.assertRaisesRegex( 

443 ConflictingDefinitionError, "A database constraint failure was triggered" 

444 ): 

445 butler.put(metric, datasetType, dataId) 

446 

447 # Remove the datastore entry. 

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

449 

450 # Put will still fail 

451 with self.assertRaisesRegex( 

452 ConflictingDefinitionError, "A database constraint failure was triggered" 

453 ): 

454 butler.put(metric, datasetType, dataId) 

455 

456 # Repeat the same sequence with resolved ref. 

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

458 ref = butler.put(metric, refIn) 

459 

460 # Repeat put will fail. 

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

462 butler.put(metric, refIn) 

463 

464 # Remove the datastore entry. 

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

466 

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

468 ref = butler.put(metric, refIn) 

469 

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

471 # something to be present 

472 

473 return butler 

474 

475 def testDeferredCollectionPassing(self) -> None: 

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

477 butler = Butler(self.tmpConfigFile, writeable=True) 

478 # Create and register a DatasetType 

479 dimensions = butler.registry.dimensions.extract(["instrument", "visit"]) 

480 datasetType = self.addDatasetType( 

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

482 ) 

483 # Add needed Dimensions 

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

485 butler.registry.insertDimensionData( 

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

487 ) 

488 butler.registry.insertDimensionData( 

489 "visit", 

490 {"instrument": "DummyCamComp", "id": 423, "name": "fourtwentythree", "physical_filter": "d-r"}, 

491 ) 

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

493 # Create dataset. 

494 metric = makeExampleMetrics() 

495 # Register a new run and put dataset. 

496 run = "deferred" 

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

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

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

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

501 # Putting with no run should fail with TypeError. 

502 with self.assertRaises(CollectionError): 

503 butler.put(metric, datasetType, dataId) 

504 # Dataset should exist. 

505 self.assertTrue(butler.datasetExists(datasetType, dataId, collections=[run])) 

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

507 # a deferred dataset handle. 

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

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

510 # Trying to find the dataset without any collection is a TypeError. 

511 with self.assertRaises(CollectionError): 

512 butler.datasetExists(datasetType, dataId) 

513 with self.assertRaises(CollectionError): 

514 butler.get(datasetType, dataId) 

515 # Associate the dataset with a different collection. 

516 butler.registry.registerCollection("tagged") 

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

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

519 # in the original collection. 

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

521 self.assertTrue(butler.datasetExists(datasetType, dataId, collections=[run])) 

522 

523 

524class ButlerTests(ButlerPutGetTests): 

525 """Tests for Butler.""" 

526 

527 useTempRoot = True 

528 validationCanFail: bool 

529 fullConfigKey: str | None 

530 registryStr: str | None 

531 datastoreName: list[str] | None 

532 datastoreStr: list[str] 

533 

534 def setUp(self) -> None: 

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

536 self.root = makeTestTempDir(TESTDIR) 

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

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

539 

540 def testConstructor(self) -> None: 

541 """Independent test of constructor.""" 

542 butler = Butler(self.tmpConfigFile, run=self.default_run) 

543 self.assertIsInstance(butler, Butler) 

544 

545 # Check that butler.yaml is added automatically. 

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

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

548 butler = Butler(config_dir, run=self.default_run) 

549 self.assertIsInstance(butler, Butler) 

550 

551 # Even with a ResourcePath. 

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

553 self.assertIsInstance(butler, Butler) 

554 

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

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

557 

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

559 special_run = "u@b.c-A" 

560 butler_special = Butler(butler=butler, run=special_run) 

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

562 self.assertEqual(collections, {special_run}) 

563 

564 butler2 = Butler(butler=butler, collections=["other"]) 

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

566 self.assertIsNone(butler2.run) 

567 self.assertIs(butler.datastore, butler2.datastore) 

568 

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

570 # repository. 

571 butler_index = Config() 

572 butler_index["label"] = self.tmpConfigFile 

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

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

575 # we aren't reusing the cache. 

576 bad_label = f"s3://bucket/not_real{suffix}" 

577 butler_index["bad_label"] = bad_label 

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

579 butler_index.dumpToUri(temp_file) 

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

581 self.assertEqual(Butler.get_known_repos(), set(("label", "bad_label"))) 

582 uri = Butler.get_repo_uri("bad_label") 

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

584 uri = Butler.get_repo_uri("label") 

585 butler = Butler(uri, writeable=False) 

586 self.assertIsInstance(butler, Butler) 

587 butler = Butler("label", writeable=False) 

588 self.assertIsInstance(butler, Butler) 

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

590 Butler("not_there", writeable=False) 

591 with self.assertRaises(KeyError) as cm: 

592 Butler.get_repo_uri("missing") 

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

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

595 with self.assertRaises(FileNotFoundError): 

596 Butler.get_repo_uri("label") 

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

598 with self.assertRaises(KeyError) as cm: 

599 # No environment variable set. 

600 Butler.get_repo_uri("label") 

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

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

603 # No aliases registered. 

604 Butler("not_there") 

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

606 

607 def testBasicPutGet(self) -> None: 

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

609 self.runPutGetTest(storageClass, "test_metric") 

610 

611 def testCompositePutGetConcrete(self) -> None: 

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

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

614 

615 # Should *not* be disassembled 

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

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

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

619 self.assertIsInstance(uri, ResourcePath) 

620 self.assertFalse(components) 

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

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

623 

624 # Predicted dataset 

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

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

627 self.assertFalse(components) 

628 self.assertIsInstance(uri, ResourcePath) 

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

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

631 

632 def testCompositePutGetVirtual(self) -> None: 

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

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

635 

636 # Should be disassembled 

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

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

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

640 

641 if butler.datastore.isEphemeral: 

642 # Never disassemble in-memory datastore 

643 self.assertIsInstance(uri, ResourcePath) 

644 self.assertFalse(components) 

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

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

647 else: 

648 self.assertIsNone(uri) 

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

650 for compuri in components.values(): 

651 self.assertIsInstance(compuri, ResourcePath) 

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

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

654 

655 # Predicted dataset 

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

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

658 

659 if butler.datastore.isEphemeral: 

660 # Never disassembled 

661 self.assertIsInstance(uri, ResourcePath) 

662 self.assertFalse(components) 

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

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

665 else: 

666 self.assertIsNone(uri) 

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

668 for compuri in components.values(): 

669 self.assertIsInstance(compuri, ResourcePath) 

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

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

672 

673 def testStorageClassOverrideGet(self) -> None: 

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

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

676 datasetTypeName = "anything" 

677 run = self.default_run 

678 

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

680 

681 # Create and store a dataset. 

682 metric = makeExampleMetrics() 

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

684 

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

686 

687 # Return native type. 

688 retrieved = butler.get(ref) 

689 self.assertEqual(retrieved, metric) 

690 

691 # Specify an override. 

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

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

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

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

696 self.assertEqual(retrieved, model) 

697 

698 # Defer but override later. 

699 deferred = butler.getDeferred(ref) 

700 model = deferred.get(storageClass=new_sc) 

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

702 self.assertEqual(retrieved, model) 

703 

704 # Defer but override up front. 

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

706 model = deferred.get() 

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

708 self.assertEqual(retrieved, model) 

709 

710 # Retrieve a component. Should be a tuple. 

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

712 self.assertIs(type(data), tuple) 

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

714 

715 # Parameter on the write storage class should work regardless 

716 # of read storage class. 

717 data = butler.get( 

718 "anything.data", 

719 dataId, 

720 storageClass="StructuredDataDataTestTuple", 

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

722 ) 

723 self.assertEqual(len(data), 2) 

724 

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

726 # the write storage class. 

727 with self.assertRaises(KeyError): 

728 butler.get( 

729 "anything.data", 

730 dataId, 

731 storageClass="StructuredDataDataTestTuple", 

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

733 ) 

734 

735 def testPytypePutCoercion(self) -> None: 

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

737 

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

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

740 datasetTypeName = "test_metric" 

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

742 

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

744 

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

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

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

748 test_metric = butler.get(metric_ref) 

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

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

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

752 

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

754 # a definition matching this python type. 

755 registry_type = butler.registry.getDatasetType(datasetTypeName) 

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

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

758 self.assertEqual(metric2_ref.datasetType, registry_type) 

759 

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

761 test_metric2 = butler.get(metric2_ref) 

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

763 

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

765 # This should now return a dict. 

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

767 test_dict2 = butler.get(new_ref) 

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

769 

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

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

772 # behavior and return the type of the DatasetType. 

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

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

775 

776 def testIngest(self) -> None: 

777 butler = Butler(self.tmpConfigFile, run=self.default_run) 

778 

779 # Create and register a DatasetType 

780 dimensions = butler.registry.dimensions.extract(["instrument", "visit", "detector"]) 

781 

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

783 datasetTypeName = "metric" 

784 

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

786 

787 # Add needed Dimensions 

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

789 butler.registry.insertDimensionData( 

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

791 ) 

792 for detector in (1, 2): 

793 butler.registry.insertDimensionData( 

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

795 ) 

796 

797 butler.registry.insertDimensionData( 

798 "visit", 

799 {"instrument": "DummyCamComp", "id": 423, "name": "fourtwentythree", "physical_filter": "d-r"}, 

800 {"instrument": "DummyCamComp", "id": 424, "name": "fourtwentyfour", "physical_filter": "d-r"}, 

801 ) 

802 

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

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

805 datasets = [] 

806 for detector in (1, 2): 

807 detector_name = f"detector_{detector}" 

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

809 dataId = butler.registry.expandDataId( 

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

811 ) 

812 # Create a DatasetRef for ingest 

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

814 

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

816 

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

818 

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

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

821 

822 metrics1 = butler.get(datasetTypeName, dataId1) 

823 metrics2 = butler.get(datasetTypeName, dataId2) 

824 self.assertNotEqual(metrics1, metrics2) 

825 

826 # Compare URIs 

827 uri1 = butler.getURI(datasetTypeName, dataId1) 

828 uri2 = butler.getURI(datasetTypeName, dataId2) 

829 self.assertNotEqual(uri1, uri2) 

830 

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

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

833 refs = [] 

834 for detector in (1, 2): 

835 detector_name = f"detector_{detector}" 

836 dataId = butler.registry.expandDataId( 

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

838 ) 

839 # Create a DatasetRef for ingest 

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

841 

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

843 # have disappeared following ingest. 

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

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

846 

847 datasets = [] 

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

849 

850 # For first ingest use copy. 

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

852 

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

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

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

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

857 ref = datasets[0].refs[0] 

858 datasets[0].refs = [ 

859 cast( 

860 DatasetRef, 

861 butler.registry.findDataset(ref.datasetType, dataId=ref.dataId, collections=ref.run), 

862 ) 

863 for ref in datasets[0].refs 

864 ] 

865 all_refs = [] 

866 for dataset in datasets: 

867 refs = [] 

868 for ref in dataset.refs: 

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

870 new_data_id = {str(k): v for k, v in ref.dataId.items()} 

871 new_ref = butler.registry.findDataset(ref.datasetType, new_data_id, collections=ref.run) 

872 assert new_ref is not None 

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

874 refs.append(new_ref) 

875 dataset.refs = refs 

876 all_refs.extend(dataset.refs) 

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

878 

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

880 # disable recording of file size. 

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

882 

883 # Check that every ref now has records. 

884 for dataset in datasets: 

885 for ref in dataset.refs: 

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

887 

888 # Ensure that the file has disappeared. 

889 self.assertFalse(tempFile.exists()) 

890 

891 # Check that the datastore recorded no file size. 

892 # Not all datastores can support this. 

893 try: 

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

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

896 except AttributeError: 

897 pass 

898 

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

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

901 

902 multi1 = butler.get(datasetTypeName, dataId1) 

903 multi2 = butler.get(datasetTypeName, dataId2) 

904 

905 self.assertEqual(multi1, metrics1) 

906 self.assertEqual(multi2, metrics2) 

907 

908 # Compare URIs 

909 uri1 = butler.getURI(datasetTypeName, dataId1) 

910 uri2 = butler.getURI(datasetTypeName, dataId2) 

911 self.assertEqual(uri1, uri2, f"Cf. {uri1} with {uri2}") 

912 

913 # Test that removing one does not break the second 

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

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

916 # files. 

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

918 self.assertFalse(butler.datasetExists(datasetTypeName, dataId1)) 

919 self.assertTrue(butler.datasetExists(datasetTypeName, dataId2)) 

920 multi2b = butler.get(datasetTypeName, dataId2) 

921 self.assertEqual(multi2, multi2b) 

922 

923 # Ensure we can ingest 0 datasets 

924 datasets = [] 

925 butler.ingest(*datasets) 

926 

927 def testPickle(self) -> None: 

928 """Test pickle support.""" 

929 butler = Butler(self.tmpConfigFile, run=self.default_run) 

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

931 self.assertIsInstance(butlerOut, Butler) 

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

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

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

935 

936 def testGetDatasetTypes(self) -> None: 

937 butler = Butler(self.tmpConfigFile, run=self.default_run) 

938 dimensions = butler.registry.dimensions.extract(["instrument", "visit", "physical_filter"]) 

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

940 ( 

941 "instrument", 

942 [ 

943 {"instrument": "DummyCam"}, 

944 {"instrument": "DummyHSC"}, 

945 {"instrument": "DummyCamComp"}, 

946 ], 

947 ), 

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

949 ("visit", [{"instrument": "DummyCam", "id": 42, "name": "fortytwo", "physical_filter": "d-r"}]), 

950 ] 

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

952 # Add needed Dimensions 

953 for element, data in dimensionEntries: 

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

955 

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

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

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

959 components = set() 

960 for datasetTypeName in datasetTypeNames: 

961 # Create and register a DatasetType 

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

963 

964 for componentName in storageClass.components: 

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

966 

967 fromRegistry: set[DatasetType] = set() 

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

969 fromRegistry.add(parent_dataset_type) 

970 fromRegistry.update(parent_dataset_type.makeAllComponentDatasetTypes()) 

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

972 

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

974 butler.validateConfiguration( 

975 ignore=[ 

976 "test_metric_comp", 

977 "metric3", 

978 "metric5", 

979 "calexp", 

980 "DummySC", 

981 "datasetType.component", 

982 "random_data", 

983 "random_data_2", 

984 ] 

985 ) 

986 

987 # Add a new datasetType that will fail template validation 

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

989 if self.validationCanFail: 

990 with self.assertRaises(ValidationError): 

991 butler.validateConfiguration() 

992 

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

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

995 

996 # Rerun validation but ignore the bad datasetType 

997 butler.validateConfiguration( 

998 ignore=[ 

999 "test_metric_comp", 

1000 "metric3", 

1001 "metric5", 

1002 "calexp", 

1003 "DummySC", 

1004 "datasetType.component", 

1005 "random_data", 

1006 "random_data_2", 

1007 ] 

1008 ) 

1009 

1010 def testTransaction(self) -> None: 

1011 butler = Butler(self.tmpConfigFile, run=self.default_run) 

1012 datasetTypeName = "test_metric" 

1013 dimensions = butler.registry.dimensions.extract(["instrument", "visit"]) 

1014 dimensionEntries: tuple[tuple[str, Mapping[str, Any]], ...] = ( 

1015 ("instrument", {"instrument": "DummyCam"}), 

1016 ("physical_filter", {"instrument": "DummyCam", "name": "d-r", "band": "R"}), 

1017 ("visit", {"instrument": "DummyCam", "id": 42, "name": "fortytwo", "physical_filter": "d-r"}), 

1018 ) 

1019 storageClass = self.storageClassFactory.getStorageClass("StructuredData") 

1020 metric = makeExampleMetrics() 

1021 dataId = {"instrument": "DummyCam", "visit": 42} 

1022 # Create and register a DatasetType 

1023 datasetType = self.addDatasetType(datasetTypeName, dimensions, storageClass, butler.registry) 

1024 with self.assertRaises(TransactionTestError): 

1025 with butler.transaction(): 

1026 # Add needed Dimensions 

1027 for args in dimensionEntries: 

1028 butler.registry.insertDimensionData(*args) 

1029 # Store a dataset 

1030 ref = butler.put(metric, datasetTypeName, dataId) 

1031 self.assertIsInstance(ref, DatasetRef) 

1032 # Test getDirect 

1033 metricOut = butler.get(ref) 

1034 self.assertEqual(metric, metricOut) 

1035 # Test get 

1036 metricOut = butler.get(datasetTypeName, dataId) 

1037 self.assertEqual(metric, metricOut) 

1038 # Check we can get components 

1039 self.assertGetComponents(butler, ref, ("summary", "data", "output"), metric) 

1040 raise TransactionTestError("This should roll back the entire transaction") 

1041 with self.assertRaises(DataIdValueError, msg=f"Check can't expand DataId {dataId}"): 

1042 butler.registry.expandDataId(dataId) 

1043 # Should raise LookupError for missing data ID value 

1044 with self.assertRaises(LookupError, msg=f"Check can't get by {datasetTypeName} and {dataId}"): 

1045 butler.get(datasetTypeName, dataId) 

1046 # Also check explicitly if Dataset entry is missing 

1047 self.assertIsNone(butler.registry.findDataset(datasetType, dataId, collections=butler.collections)) 

1048 # Direct retrieval should not find the file in the Datastore 

1049 with self.assertRaises(FileNotFoundError, msg=f"Check {ref} can't be retrieved directly"): 

1050 butler.get(ref) 

1051 

1052 def testMakeRepo(self) -> None: 

1053 """Test that we can write butler configuration to a new repository via 

1054 the Butler.makeRepo interface and then instantiate a butler from the 

1055 repo root. 

1056 """ 

1057 # Do not run the test if we know this datastore configuration does 

1058 # not support a file system root 

1059 if self.fullConfigKey is None: 

1060 return 

1061 

1062 # create two separate directories 

1063 root1 = tempfile.mkdtemp(dir=self.root) 

1064 root2 = tempfile.mkdtemp(dir=self.root) 

1065 

1066 butlerConfig = Butler.makeRepo(root1, config=Config(self.configFile)) 

1067 limited = Config(self.configFile) 

1068 butler1 = Butler(butlerConfig) 

1069 butlerConfig = Butler.makeRepo(root2, standalone=True, config=Config(self.configFile)) 

1070 full = Config(self.tmpConfigFile) 

1071 butler2 = Butler(butlerConfig) 

1072 # Butlers should have the same configuration regardless of whether 

1073 # defaults were expanded. 

1074 self.assertEqual(butler1._config, butler2._config) 

1075 # Config files loaded directly should not be the same. 

1076 self.assertNotEqual(limited, full) 

1077 # Make sure "limited" doesn't have a few keys we know it should be 

1078 # inheriting from defaults. 

1079 self.assertIn(self.fullConfigKey, full) 

1080 self.assertNotIn(self.fullConfigKey, limited) 

1081 

1082 # Collections don't appear until something is put in them 

1083 collections1 = set(butler1.registry.queryCollections()) 

1084 self.assertEqual(collections1, set()) 

1085 self.assertEqual(set(butler2.registry.queryCollections()), collections1) 

1086 

1087 # Check that a config with no associated file name will not 

1088 # work properly with relocatable Butler repo 

1089 butlerConfig.configFile = None 

1090 with self.assertRaises(ValueError): 

1091 Butler(butlerConfig) 

1092 

1093 with self.assertRaises(FileExistsError): 

1094 Butler.makeRepo(self.root, standalone=True, config=Config(self.configFile), overwrite=False) 

1095 

1096 def testStringification(self) -> None: 

1097 butler = Butler(self.tmpConfigFile, run=self.default_run) 

1098 butlerStr = str(butler) 

1099 

1100 if self.datastoreStr is not None: 

1101 for testStr in self.datastoreStr: 

1102 self.assertIn(testStr, butlerStr) 

1103 if self.registryStr is not None: 

1104 self.assertIn(self.registryStr, butlerStr) 

1105 

1106 datastoreName = butler.datastore.name 

1107 if self.datastoreName is not None: 

1108 for testStr in self.datastoreName: 

1109 self.assertIn(testStr, datastoreName) 

1110 

1111 def testButlerRewriteDataId(self) -> None: 

1112 """Test that dataIds can be rewritten based on dimension records.""" 

1113 

1114 butler = Butler(self.tmpConfigFile, run=self.default_run) 

1115 

1116 storageClass = self.storageClassFactory.getStorageClass("StructuredDataDict") 

1117 datasetTypeName = "random_data" 

1118 

1119 # Create dimension records. 

1120 butler.registry.insertDimensionData("instrument", {"name": "DummyCamComp"}) 

1121 butler.registry.insertDimensionData( 

1122 "physical_filter", {"instrument": "DummyCamComp", "name": "d-r", "band": "R"} 

1123 ) 

1124 butler.registry.insertDimensionData( 

1125 "detector", {"instrument": "DummyCamComp", "id": 1, "full_name": "det1"} 

1126 ) 

1127 

1128 dimensions = butler.registry.dimensions.extract(["instrument", "exposure"]) 

1129 datasetType = DatasetType(datasetTypeName, dimensions, storageClass) 

1130 butler.registry.registerDatasetType(datasetType) 

1131 

1132 n_exposures = 5 

1133 dayobs = 20210530 

1134 

1135 for i in range(n_exposures): 

1136 butler.registry.insertDimensionData( 

1137 "exposure", 

1138 { 

1139 "instrument": "DummyCamComp", 

1140 "id": i, 

1141 "obs_id": f"exp{i}", 

1142 "seq_num": i, 

1143 "day_obs": dayobs, 

1144 "physical_filter": "d-r", 

1145 }, 

1146 ) 

1147 

1148 # Write some data. 

1149 for i in range(n_exposures): 

1150 metric = {"something": i, "other": "metric", "list": [2 * x for x in range(i)]} 

1151 

1152 # Use the seq_num for the put to test rewriting. 

1153 dataId = {"seq_num": i, "day_obs": dayobs, "instrument": "DummyCamComp", "physical_filter": "d-r"} 

1154 ref = butler.put(metric, datasetTypeName, dataId=dataId) 

1155 

1156 # Check that the exposure is correct in the dataId 

1157 self.assertEqual(ref.dataId["exposure"], i) 

1158 

1159 # and check that we can get the dataset back with the same dataId 

1160 new_metric = butler.get(datasetTypeName, dataId=dataId) 

1161 self.assertEqual(new_metric, metric) 

1162 

1163 

1164class FileDatastoreButlerTests(ButlerTests): 

1165 """Common tests and specialization of ButlerTests for butlers backed 

1166 by datastores that inherit from FileDatastore. 

1167 """ 

1168 

1169 def checkFileExists(self, root: str | ResourcePath, relpath: str | ResourcePath) -> bool: 

1170 """Checks if file exists at a given path (relative to root). 

1171 

1172 Test testPutTemplates verifies actual physical existance of the files 

1173 in the requested location. 

1174 """ 

1175 uri = ResourcePath(root, forceDirectory=True) 

1176 return uri.join(relpath).exists() 

1177 

1178 def testPutTemplates(self) -> None: 

1179 storageClass = self.storageClassFactory.getStorageClass("StructuredDataNoComponents") 

1180 butler = Butler(self.tmpConfigFile, run=self.default_run) 

1181 

1182 # Add needed Dimensions 

1183 butler.registry.insertDimensionData("instrument", {"name": "DummyCamComp"}) 

1184 butler.registry.insertDimensionData( 

1185 "physical_filter", {"instrument": "DummyCamComp", "name": "d-r", "band": "R"} 

1186 ) 

1187 butler.registry.insertDimensionData( 

1188 "visit", {"instrument": "DummyCamComp", "id": 423, "name": "v423", "physical_filter": "d-r"} 

1189 ) 

1190 butler.registry.insertDimensionData( 

1191 "visit", {"instrument": "DummyCamComp", "id": 425, "name": "v425", "physical_filter": "d-r"} 

1192 ) 

1193 

1194 # Create and store a dataset 

1195 metric = makeExampleMetrics() 

1196 

1197 # Create two almost-identical DatasetTypes (both will use default 

1198 # template) 

1199 dimensions = butler.registry.dimensions.extract(["instrument", "visit"]) 

1200 butler.registry.registerDatasetType(DatasetType("metric1", dimensions, storageClass)) 

1201 butler.registry.registerDatasetType(DatasetType("metric2", dimensions, storageClass)) 

1202 butler.registry.registerDatasetType(DatasetType("metric3", dimensions, storageClass)) 

1203 

1204 dataId1 = {"instrument": "DummyCamComp", "visit": 423} 

1205 dataId2 = {"instrument": "DummyCamComp", "visit": 423, "physical_filter": "d-r"} 

1206 

1207 # Put with exactly the data ID keys needed 

1208 ref = butler.put(metric, "metric1", dataId1) 

1209 uri = butler.getURI(ref) 

1210 self.assertTrue(uri.exists()) 

1211 self.assertTrue( 

1212 uri.unquoted_path.endswith(f"{self.default_run}/metric1/??#?/d-r/DummyCamComp_423.pickle") 

1213 ) 

1214 

1215 # Check the template based on dimensions 

1216 if hasattr(butler.datastore, "templates"): 

1217 butler.datastore.templates.validateTemplates([ref]) 

1218 

1219 # Put with extra data ID keys (physical_filter is an optional 

1220 # dependency); should not change template (at least the way we're 

1221 # defining them to behave now; the important thing is that they 

1222 # must be consistent). 

1223 ref = butler.put(metric, "metric2", dataId2) 

1224 uri = butler.getURI(ref) 

1225 self.assertTrue(uri.exists()) 

1226 self.assertTrue( 

1227 uri.unquoted_path.endswith(f"{self.default_run}/metric2/d-r/DummyCamComp_v423.pickle") 

1228 ) 

1229 

1230 # Check the template based on dimensions 

1231 if hasattr(butler.datastore, "templates"): 

1232 butler.datastore.templates.validateTemplates([ref]) 

1233 

1234 # Use a template that has a typo in dimension record metadata. 

1235 # Easier to test with a butler that has a ref with records attached. 

1236 template = FileTemplate("a/{visit.name}/{id}_{visit.namex:?}.fits") 

1237 with self.assertLogs("lsst.daf.butler.core.fileTemplates", "INFO"): 

1238 path = template.format(ref) 

1239 self.assertEqual(path, f"a/v423/{ref.id}_fits") 

1240 

1241 template = FileTemplate("a/{visit.name}/{id}_{visit.namex}.fits") 

1242 with self.assertRaises(KeyError): 

1243 with self.assertLogs("lsst.daf.butler.core.fileTemplates", "INFO"): 

1244 template.format(ref) 

1245 

1246 # Now use a file template that will not result in unique filenames 

1247 with self.assertRaises(FileTemplateValidationError): 

1248 butler.put(metric, "metric3", dataId1) 

1249 

1250 def testImportExport(self) -> None: 

1251 # Run put/get tests just to create and populate a repo. 

1252 storageClass = self.storageClassFactory.getStorageClass("StructuredDataNoComponents") 

1253 self.runImportExportTest(storageClass) 

1254 

1255 @unittest.expectedFailure 

1256 def testImportExportVirtualComposite(self) -> None: 

1257 # Run put/get tests just to create and populate a repo. 

1258 storageClass = self.storageClassFactory.getStorageClass("StructuredComposite") 

1259 self.runImportExportTest(storageClass) 

1260 

1261 def runImportExportTest(self, storageClass: StorageClass) -> None: 

1262 """This test does an export to a temp directory and an import back 

1263 into a new temp directory repo. It does not assume a posix datastore""" 

1264 exportButler = self.runPutGetTest(storageClass, "test_metric") 

1265 

1266 # Test that we must have a file extension. 

1267 with self.assertRaises(ValueError): 

1268 with exportButler.export(filename="dump", directory=".") as export: 

1269 pass 

1270 

1271 # Test that unknown format is not allowed. 

1272 with self.assertRaises(ValueError): 

1273 with exportButler.export(filename="dump.fits", directory=".") as export: 

1274 pass 

1275 

1276 # Test that the repo actually has at least one dataset. 

1277 datasets = list(exportButler.registry.queryDatasets(..., collections=Ellipsis)) 

1278 self.assertGreater(len(datasets), 0) 

1279 # Add a DimensionRecord that's unused by those datasets. 

1280 skymapRecord = {"name": "example_skymap", "hash": (50).to_bytes(8, byteorder="little")} 

1281 exportButler.registry.insertDimensionData("skymap", skymapRecord) 

1282 # Export and then import datasets. 

1283 with safeTestTempDir(TESTDIR) as exportDir: 

1284 exportFile = os.path.join(exportDir, "exports.yaml") 

1285 with exportButler.export(filename=exportFile, directory=exportDir, transfer="auto") as export: 

1286 export.saveDatasets(datasets) 

1287 # Export the same datasets again. This should quietly do 

1288 # nothing because of internal deduplication, and it shouldn't 

1289 # complain about being asked to export the "htm7" elements even 

1290 # though there aren't any in these datasets or in the database. 

1291 export.saveDatasets(datasets, elements=["htm7"]) 

1292 # Save one of the data IDs again; this should be harmless 

1293 # because of internal deduplication. 

1294 export.saveDataIds([datasets[0].dataId]) 

1295 # Save some dimension records directly. 

1296 export.saveDimensionData("skymap", [skymapRecord]) 

1297 self.assertTrue(os.path.exists(exportFile)) 

1298 with safeTestTempDir(TESTDIR) as importDir: 

1299 # We always want this to be a local posix butler 

1300 Butler.makeRepo(importDir, config=Config(os.path.join(TESTDIR, "config/basic/butler.yaml"))) 

1301 # Calling script.butlerImport tests the implementation of the 

1302 # butler command line interface "import" subcommand. Functions 

1303 # in the script folder are generally considered protected and 

1304 # should not be used as public api. 

1305 with open(exportFile, "r") as f: 

1306 script.butlerImport( 

1307 importDir, 

1308 export_file=f, 

1309 directory=exportDir, 

1310 transfer="auto", 

1311 skip_dimensions=None, 

1312 ) 

1313 importButler = Butler(importDir, run=self.default_run) 

1314 for ref in datasets: 

1315 with self.subTest(ref=ref): 

1316 # Test for existence by passing in the DatasetType and 

1317 # data ID separately, to avoid lookup by dataset_id. 

1318 self.assertTrue(importButler.datasetExists(ref.datasetType, ref.dataId)) 

1319 self.assertEqual( 

1320 list(importButler.registry.queryDimensionRecords("skymap")), 

1321 [importButler.registry.dimensions["skymap"].RecordClass(**skymapRecord)], 

1322 ) 

1323 

1324 def testRemoveRuns(self) -> None: 

1325 storageClass = self.storageClassFactory.getStorageClass("StructuredDataNoComponents") 

1326 butler = Butler(self.tmpConfigFile, writeable=True) 

1327 # Load registry data with dimensions to hang datasets off of. 

1328 registryDataDir = os.path.normpath(os.path.join(os.path.dirname(__file__), "data", "registry")) 

1329 butler.import_(filename=os.path.join(registryDataDir, "base.yaml")) 

1330 # Add some RUN-type collection. 

1331 run1 = "run1" 

1332 butler.registry.registerRun(run1) 

1333 run2 = "run2" 

1334 butler.registry.registerRun(run2) 

1335 # put a dataset in each 

1336 metric = makeExampleMetrics() 

1337 dimensions = butler.registry.dimensions.extract(["instrument", "physical_filter"]) 

1338 datasetType = self.addDatasetType( 

1339 "prune_collections_test_dataset", dimensions, storageClass, butler.registry 

1340 ) 

1341 ref1 = butler.put(metric, datasetType, {"instrument": "Cam1", "physical_filter": "Cam1-G"}, run=run1) 

1342 ref2 = butler.put(metric, datasetType, {"instrument": "Cam1", "physical_filter": "Cam1-G"}, run=run2) 

1343 uri1 = butler.getURI(ref1, collections=[run1]) 

1344 uri2 = butler.getURI(ref2, collections=[run2]) 

1345 

1346 with self.assertRaises(OrphanedRecordError): 

1347 butler.registry.removeDatasetType(datasetType.name) 

1348 

1349 # Remove from both runs with different values for unstore. 

1350 butler.removeRuns([run1], unstore=True) 

1351 butler.removeRuns([run2], unstore=False) 

1352 # Should be nothing in registry for either one, and datastore should 

1353 # not think either exists. 

1354 with self.assertRaises(MissingCollectionError): 

1355 butler.registry.getCollectionType(run1) 

1356 with self.assertRaises(MissingCollectionError): 

1357 butler.registry.getCollectionType(run2) 

1358 self.assertFalse(butler.datastore.exists(ref1)) 

1359 self.assertFalse(butler.datastore.exists(ref2)) 

1360 # The ref we unstored should be gone according to the URI, but the 

1361 # one we forgot should still be around. 

1362 self.assertFalse(uri1.exists()) 

1363 self.assertTrue(uri2.exists()) 

1364 

1365 # Now that the collections have been pruned we can remove the 

1366 # dataset type 

1367 butler.registry.removeDatasetType(datasetType.name) 

1368 

1369 with self.assertLogs("lsst.daf.butler.registries", "INFO") as cm: 

1370 butler.registry.removeDatasetType(tuple(["test*", "test*"])) 

1371 self.assertIn("not defined", "\n".join(cm.output)) 

1372 

1373 

1374class PosixDatastoreButlerTestCase(FileDatastoreButlerTests, unittest.TestCase): 

1375 """PosixDatastore specialization of a butler""" 

1376 

1377 configFile = os.path.join(TESTDIR, "config/basic/butler.yaml") 

1378 fullConfigKey: str | None = ".datastore.formatters" 

1379 validationCanFail = True 

1380 datastoreStr = ["/tmp"] 

1381 datastoreName = [f"FileDatastore@{BUTLER_ROOT_TAG}"] 

1382 registryStr = "/gen3.sqlite3" 

1383 

1384 def testPathConstructor(self) -> None: 

1385 """Independent test of constructor using PathLike.""" 

1386 butler = Butler(self.tmpConfigFile, run=self.default_run) 

1387 self.assertIsInstance(butler, Butler) 

1388 

1389 # And again with a Path object with the butler yaml 

1390 path = pathlib.Path(self.tmpConfigFile) 

1391 butler = Butler(path, writeable=False) 

1392 self.assertIsInstance(butler, Butler) 

1393 

1394 # And again with a Path object without the butler yaml 

1395 # (making sure we skip it if the tmp config doesn't end 

1396 # in butler.yaml -- which is the case for a subclass) 

1397 if self.tmpConfigFile.endswith("butler.yaml"): 

1398 path = pathlib.Path(os.path.dirname(self.tmpConfigFile)) 

1399 butler = Butler(path, writeable=False) 

1400 self.assertIsInstance(butler, Butler) 

1401 

1402 def testExportTransferCopy(self) -> None: 

1403 """Test local export using all transfer modes""" 

1404 storageClass = self.storageClassFactory.getStorageClass("StructuredDataNoComponents") 

1405 exportButler = self.runPutGetTest(storageClass, "test_metric") 

1406 # Test that the repo actually has at least one dataset. 

1407 datasets = list(exportButler.registry.queryDatasets(..., collections=Ellipsis)) 

1408 self.assertGreater(len(datasets), 0) 

1409 uris = [exportButler.getURI(d) for d in datasets] 

1410 assert isinstance(exportButler.datastore, FileDatastore) 

1411 datastoreRoot = exportButler.datastore.root 

1412 

1413 pathsInStore = [uri.relative_to(datastoreRoot) for uri in uris] 

1414 

1415 for path in pathsInStore: 

1416 # Assume local file system 

1417 assert path is not None 

1418 self.assertTrue(self.checkFileExists(datastoreRoot, path), f"Checking path {path}") 

1419 

1420 for transfer in ("copy", "link", "symlink", "relsymlink"): 

1421 with safeTestTempDir(TESTDIR) as exportDir: 

1422 with exportButler.export(directory=exportDir, format="yaml", transfer=transfer) as export: 

1423 export.saveDatasets(datasets) 

1424 for path in pathsInStore: 

1425 assert path is not None 

1426 self.assertTrue( 

1427 self.checkFileExists(exportDir, path), 

1428 f"Check that mode {transfer} exported files", 

1429 ) 

1430 

1431 def testPruneDatasets(self) -> None: 

1432 storageClass = self.storageClassFactory.getStorageClass("StructuredDataNoComponents") 

1433 butler = Butler(self.tmpConfigFile, writeable=True) 

1434 assert isinstance(butler.datastore, FileDatastore) 

1435 # Load registry data with dimensions to hang datasets off of. 

1436 registryDataDir = os.path.normpath(os.path.join(TESTDIR, "data", "registry")) 

1437 butler.import_(filename=os.path.join(registryDataDir, "base.yaml")) 

1438 # Add some RUN-type collections. 

1439 run1 = "run1" 

1440 butler.registry.registerRun(run1) 

1441 run2 = "run2" 

1442 butler.registry.registerRun(run2) 

1443 # put some datasets. ref1 and ref2 have the same data ID, and are in 

1444 # different runs. ref3 has a different data ID. 

1445 metric = makeExampleMetrics() 

1446 dimensions = butler.registry.dimensions.extract(["instrument", "physical_filter"]) 

1447 datasetType = self.addDatasetType( 

1448 "prune_collections_test_dataset", dimensions, storageClass, butler.registry 

1449 ) 

1450 ref1 = butler.put(metric, datasetType, {"instrument": "Cam1", "physical_filter": "Cam1-G"}, run=run1) 

1451 ref2 = butler.put(metric, datasetType, {"instrument": "Cam1", "physical_filter": "Cam1-G"}, run=run2) 

1452 ref3 = butler.put(metric, datasetType, {"instrument": "Cam1", "physical_filter": "Cam1-R1"}, run=run1) 

1453 

1454 # Simple prune. 

1455 butler.pruneDatasets([ref1, ref2, ref3], purge=True, unstore=True) 

1456 with self.assertRaises(LookupError): 

1457 butler.datasetExists(ref1.datasetType, ref1.dataId, collections=run1) 

1458 

1459 # Put data back. 

1460 ref1 = butler.put(metric, ref1, run=run1) 

1461 ref2 = butler.put(metric, ref2, run=run2) 

1462 ref3 = butler.put(metric, ref3, run=run1) 

1463 

1464 # Check that in normal mode, deleting the record will lead to 

1465 # trash not touching the file. 

1466 uri1 = butler.datastore.getURI(ref1) 

1467 butler.datastore.bridge.moveToTrash([ref1], transaction=None) # Update the dataset_location table 

1468 butler.datastore._table.delete(["dataset_id"], {"dataset_id": ref1.id}) 

1469 butler.datastore.trash(ref1) 

1470 butler.datastore.emptyTrash() 

1471 self.assertTrue(uri1.exists()) 

1472 uri1.remove() # Clean it up. 

1473 

1474 # Simulate execution butler setup by deleting the datastore 

1475 # record but keeping the file around and trusting. 

1476 butler.datastore.trustGetRequest = True 

1477 uri2 = butler.datastore.getURI(ref2) 

1478 uri3 = butler.datastore.getURI(ref3) 

1479 self.assertTrue(uri2.exists()) 

1480 self.assertTrue(uri3.exists()) 

1481 

1482 # Remove the datastore record. 

1483 butler.datastore.bridge.moveToTrash([ref2], transaction=None) # Update the dataset_location table 

1484 butler.datastore._table.delete(["dataset_id"], {"dataset_id": ref2.id}) 

1485 self.assertTrue(uri2.exists()) 

1486 butler.datastore.trash([ref2, ref3]) 

1487 # Immediate removal for ref2 file 

1488 self.assertFalse(uri2.exists()) 

1489 # But ref3 has to wait for the empty. 

1490 self.assertTrue(uri3.exists()) 

1491 butler.datastore.emptyTrash() 

1492 self.assertFalse(uri3.exists()) 

1493 

1494 # Clear out the datasets from registry. 

1495 butler.pruneDatasets([ref1, ref2, ref3], purge=True, unstore=True) 

1496 

1497 def testPytypeCoercion(self) -> None: 

1498 """Test python type coercion on Butler.get and put.""" 

1499 

1500 # Store some data with the normal example storage class. 

1501 storageClass = self.storageClassFactory.getStorageClass("StructuredDataNoComponents") 

1502 datasetTypeName = "test_metric" 

1503 butler = self.runPutGetTest(storageClass, datasetTypeName) 

1504 

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

1506 metric = butler.get(datasetTypeName, dataId=dataId) 

1507 self.assertEqual(get_full_type_name(metric), "lsst.daf.butler.tests.MetricsExample") 

1508 

1509 datasetType_ori = butler.registry.getDatasetType(datasetTypeName) 

1510 self.assertEqual(datasetType_ori.storageClass.name, "StructuredDataNoComponents") 

1511 

1512 # Now need to hack the registry dataset type definition. 

1513 # There is no API for this. 

1514 assert isinstance(butler.registry, SqlRegistry) 

1515 manager = butler.registry._managers.datasets 

1516 assert hasattr(manager, "_db") and hasattr(manager, "_static") 

1517 manager._db.update( 

1518 manager._static.dataset_type, 

1519 {"name": datasetTypeName}, 

1520 {datasetTypeName: datasetTypeName, "storage_class": "StructuredDataNoComponentsModel"}, 

1521 ) 

1522 

1523 # Force reset of dataset type cache 

1524 butler.registry.refresh() 

1525 

1526 datasetType_new = butler.registry.getDatasetType(datasetTypeName) 

1527 self.assertEqual(datasetType_new.name, datasetType_ori.name) 

1528 self.assertEqual(datasetType_new.storageClass.name, "StructuredDataNoComponentsModel") 

1529 

1530 metric_model = butler.get(datasetTypeName, dataId=dataId) 

1531 self.assertNotEqual(type(metric_model), type(metric)) 

1532 self.assertEqual(get_full_type_name(metric_model), "lsst.daf.butler.tests.MetricsExampleModel") 

1533 

1534 # Put the model and read it back to show that everything now 

1535 # works as normal. 

1536 metric_ref = butler.put(metric_model, datasetTypeName, dataId=dataId, visit=424) 

1537 metric_model_new = butler.get(metric_ref) 

1538 self.assertEqual(metric_model_new, metric_model) 

1539 

1540 # Hack the storage class again to something that will fail on the 

1541 # get with no conversion class. 

1542 manager._db.update( 

1543 manager._static.dataset_type, 

1544 {"name": datasetTypeName}, 

1545 {datasetTypeName: datasetTypeName, "storage_class": "StructuredDataListYaml"}, 

1546 ) 

1547 butler.registry.refresh() 

1548 

1549 with self.assertRaises(ValueError): 

1550 butler.get(datasetTypeName, dataId=dataId) 

1551 

1552 

1553@unittest.skipUnless(testing is not None, "testing.postgresql module not found") 

1554class PostgresPosixDatastoreButlerTestCase(FileDatastoreButlerTests, unittest.TestCase): 

1555 """PosixDatastore specialization of a butler using Postgres""" 

1556 

1557 configFile = os.path.join(TESTDIR, "config/basic/butler.yaml") 

1558 fullConfigKey = ".datastore.formatters" 

1559 validationCanFail = True 

1560 datastoreStr = ["/tmp"] 

1561 datastoreName = [f"FileDatastore@{BUTLER_ROOT_TAG}"] 

1562 registryStr = "PostgreSQL@test" 

1563 postgresql: Any 

1564 

1565 @staticmethod 

1566 def _handler(postgresql: Any) -> None: 

1567 engine = sqlalchemy.engine.create_engine(postgresql.url()) 

1568 with engine.begin() as connection: 

1569 connection.execute(sqlalchemy.text("CREATE EXTENSION btree_gist;")) 

1570 

1571 @classmethod 

1572 def setUpClass(cls) -> None: 

1573 # Create the postgres test server. 

1574 cls.postgresql = testing.postgresql.PostgresqlFactory( 

1575 cache_initialized_db=True, on_initialized=cls._handler 

1576 ) 

1577 super().setUpClass() 

1578 

1579 @classmethod 

1580 def tearDownClass(cls) -> None: 

1581 # Clean up any lingering SQLAlchemy engines/connections 

1582 # so they're closed before we shut down the server. 

1583 gc.collect() 

1584 cls.postgresql.clear_cache() 

1585 super().tearDownClass() 

1586 

1587 def setUp(self) -> None: 

1588 self.server = self.postgresql() 

1589 

1590 # Need to add a registry section to the config. 

1591 self._temp_config = False 

1592 config = Config(self.configFile) 

1593 config["registry", "db"] = self.server.url() 

1594 with tempfile.NamedTemporaryFile("w", suffix=".yaml", delete=False) as fh: 

1595 config.dump(fh) 

1596 self.configFile = fh.name 

1597 self._temp_config = True 

1598 super().setUp() 

1599 

1600 def tearDown(self) -> None: 

1601 self.server.stop() 

1602 if self._temp_config and os.path.exists(self.configFile): 

1603 os.remove(self.configFile) 

1604 super().tearDown() 

1605 

1606 def testMakeRepo(self) -> None: 

1607 # The base class test assumes that it's using sqlite and assumes 

1608 # the config file is acceptable to sqlite. 

1609 raise unittest.SkipTest("Postgres config is not compatible with this test.") 

1610 

1611 

1612class InMemoryDatastoreButlerTestCase(ButlerTests, unittest.TestCase): 

1613 """InMemoryDatastore specialization of a butler""" 

1614 

1615 configFile = os.path.join(TESTDIR, "config/basic/butler-inmemory.yaml") 

1616 fullConfigKey = None 

1617 useTempRoot = False 

1618 validationCanFail = False 

1619 datastoreStr = ["datastore='InMemory"] 

1620 datastoreName = ["InMemoryDatastore@"] 

1621 registryStr = "/gen3.sqlite3" 

1622 

1623 def testIngest(self) -> None: 

1624 pass 

1625 

1626 

1627class ChainedDatastoreButlerTestCase(FileDatastoreButlerTests, unittest.TestCase): 

1628 """PosixDatastore specialization""" 

1629 

1630 configFile = os.path.join(TESTDIR, "config/basic/butler-chained.yaml") 

1631 fullConfigKey = ".datastore.datastores.1.formatters" 

1632 validationCanFail = True 

1633 datastoreStr = ["datastore='InMemory", "/FileDatastore_1/,", "/FileDatastore_2/'"] 

1634 datastoreName = [ 

1635 "InMemoryDatastore@", 

1636 f"FileDatastore@{BUTLER_ROOT_TAG}/FileDatastore_1", 

1637 "SecondDatastore", 

1638 ] 

1639 registryStr = "/gen3.sqlite3" 

1640 

1641 

1642class ButlerExplicitRootTestCase(PosixDatastoreButlerTestCase): 

1643 """Test that a yaml file in one location can refer to a root in another.""" 

1644 

1645 datastoreStr = ["dir1"] 

1646 # Disable the makeRepo test since we are deliberately not using 

1647 # butler.yaml as the config name. 

1648 fullConfigKey = None 

1649 

1650 def setUp(self) -> None: 

1651 self.root = makeTestTempDir(TESTDIR) 

1652 

1653 # Make a new repository in one place 

1654 self.dir1 = os.path.join(self.root, "dir1") 

1655 Butler.makeRepo(self.dir1, config=Config(self.configFile)) 

1656 

1657 # Move the yaml file to a different place and add a "root" 

1658 self.dir2 = os.path.join(self.root, "dir2") 

1659 os.makedirs(self.dir2, exist_ok=True) 

1660 configFile1 = os.path.join(self.dir1, "butler.yaml") 

1661 config = Config(configFile1) 

1662 config["root"] = self.dir1 

1663 configFile2 = os.path.join(self.dir2, "butler2.yaml") 

1664 config.dumpToUri(configFile2) 

1665 os.remove(configFile1) 

1666 self.tmpConfigFile = configFile2 

1667 

1668 def testFileLocations(self) -> None: 

1669 self.assertNotEqual(self.dir1, self.dir2) 

1670 self.assertTrue(os.path.exists(os.path.join(self.dir2, "butler2.yaml"))) 

1671 self.assertFalse(os.path.exists(os.path.join(self.dir1, "butler.yaml"))) 

1672 self.assertTrue(os.path.exists(os.path.join(self.dir1, "gen3.sqlite3"))) 

1673 

1674 

1675class ButlerMakeRepoOutfileTestCase(ButlerPutGetTests, unittest.TestCase): 

1676 """Test that a config file created by makeRepo outside of repo works.""" 

1677 

1678 configFile = os.path.join(TESTDIR, "config/basic/butler.yaml") 

1679 

1680 def setUp(self) -> None: 

1681 self.root = makeTestTempDir(TESTDIR) 

1682 self.root2 = makeTestTempDir(TESTDIR) 

1683 

1684 self.tmpConfigFile = os.path.join(self.root2, "different.yaml") 

1685 Butler.makeRepo(self.root, config=Config(self.configFile), outfile=self.tmpConfigFile) 

1686 

1687 def tearDown(self) -> None: 

1688 if os.path.exists(self.root2): 

1689 shutil.rmtree(self.root2, ignore_errors=True) 

1690 super().tearDown() 

1691 

1692 def testConfigExistence(self) -> None: 

1693 c = Config(self.tmpConfigFile) 

1694 uri_config = ResourcePath(c["root"]) 

1695 uri_expected = ResourcePath(self.root, forceDirectory=True) 

1696 self.assertEqual(uri_config.geturl(), uri_expected.geturl()) 

1697 self.assertNotIn(":", uri_config.path, "Check for URI concatenated with normal path") 

1698 

1699 def testPutGet(self) -> None: 

1700 storageClass = self.storageClassFactory.getStorageClass("StructuredDataNoComponents") 

1701 self.runPutGetTest(storageClass, "test_metric") 

1702 

1703 

1704class ButlerMakeRepoOutfileDirTestCase(ButlerMakeRepoOutfileTestCase): 

1705 """Test that a config file created by makeRepo outside of repo works.""" 

1706 

1707 configFile = os.path.join(TESTDIR, "config/basic/butler.yaml") 

1708 

1709 def setUp(self) -> None: 

1710 self.root = makeTestTempDir(TESTDIR) 

1711 self.root2 = makeTestTempDir(TESTDIR) 

1712 

1713 self.tmpConfigFile = self.root2 

1714 Butler.makeRepo(self.root, config=Config(self.configFile), outfile=self.tmpConfigFile) 

1715 

1716 def testConfigExistence(self) -> None: 

1717 # Append the yaml file else Config constructor does not know the file 

1718 # type. 

1719 self.tmpConfigFile = os.path.join(self.tmpConfigFile, "butler.yaml") 

1720 super().testConfigExistence() 

1721 

1722 

1723class ButlerMakeRepoOutfileUriTestCase(ButlerMakeRepoOutfileTestCase): 

1724 """Test that a config file created by makeRepo outside of repo works.""" 

1725 

1726 configFile = os.path.join(TESTDIR, "config/basic/butler.yaml") 

1727 

1728 def setUp(self) -> None: 

1729 self.root = makeTestTempDir(TESTDIR) 

1730 self.root2 = makeTestTempDir(TESTDIR) 

1731 

1732 self.tmpConfigFile = ResourcePath(os.path.join(self.root2, "something.yaml")).geturl() 

1733 Butler.makeRepo(self.root, config=Config(self.configFile), outfile=self.tmpConfigFile) 

1734 

1735 

1736@unittest.skipIf(not boto3, "Warning: boto3 AWS SDK not found!") 

1737class S3DatastoreButlerTestCase(FileDatastoreButlerTests, unittest.TestCase): 

1738 """S3Datastore specialization of a butler; an S3 storage Datastore + 

1739 a local in-memory SqlRegistry. 

1740 """ 

1741 

1742 configFile = os.path.join(TESTDIR, "config/basic/butler-s3store.yaml") 

1743 fullConfigKey = None 

1744 validationCanFail = True 

1745 

1746 bucketName = "anybucketname" 

1747 """Name of the Bucket that will be used in the tests. The name is read from 

1748 the config file used with the tests during set-up. 

1749 """ 

1750 

1751 root = "butlerRoot/" 

1752 """Root repository directory expected to be used in case useTempRoot=False. 

1753 Otherwise the root is set to a 20 characters long randomly generated string 

1754 during set-up. 

1755 """ 

1756 

1757 datastoreStr = [f"datastore={root}"] 

1758 """Contains all expected root locations in a format expected to be 

1759 returned by Butler stringification. 

1760 """ 

1761 

1762 datastoreName = ["FileDatastore@s3://{bucketName}/{root}"] 

1763 """The expected format of the S3 Datastore string.""" 

1764 

1765 registryStr = "/gen3.sqlite3" 

1766 """Expected format of the Registry string.""" 

1767 

1768 mock_s3 = mock_s3() 

1769 """The mocked s3 interface from moto.""" 

1770 

1771 def genRoot(self) -> str: 

1772 """Returns a random string of len 20 to serve as a root 

1773 name for the temporary bucket repo. 

1774 

1775 This is equivalent to tempfile.mkdtemp as this is what self.root 

1776 becomes when useTempRoot is True. 

1777 """ 

1778 rndstr = "".join(random.choice(string.ascii_uppercase + string.digits) for _ in range(20)) 

1779 return rndstr + "/" 

1780 

1781 def setUp(self) -> None: 

1782 config = Config(self.configFile) 

1783 uri = ResourcePath(config[".datastore.datastore.root"]) 

1784 self.bucketName = uri.netloc 

1785 

1786 # Enable S3 mocking of tests. 

1787 self.mock_s3.start() 

1788 

1789 # set up some fake credentials if they do not exist 

1790 self.usingDummyCredentials = setAwsEnvCredentials() 

1791 

1792 if self.useTempRoot: 

1793 self.root = self.genRoot() 

1794 rooturi = f"s3://{self.bucketName}/{self.root}" 

1795 config.update({"datastore": {"datastore": {"root": rooturi}}}) 

1796 

1797 # need local folder to store registry database 

1798 self.reg_dir = makeTestTempDir(TESTDIR) 

1799 config["registry", "db"] = f"sqlite:///{self.reg_dir}/gen3.sqlite3" 

1800 

1801 # MOTO needs to know that we expect Bucket bucketname to exist 

1802 # (this used to be the class attribute bucketName) 

1803 s3 = boto3.resource("s3") 

1804 s3.create_bucket(Bucket=self.bucketName) 

1805 

1806 self.datastoreStr = [f"datastore='{rooturi}'"] 

1807 self.datastoreName = [f"FileDatastore@{rooturi}"] 

1808 Butler.makeRepo(rooturi, config=config, forceConfigRoot=False) 

1809 self.tmpConfigFile = posixpath.join(rooturi, "butler.yaml") 

1810 

1811 def tearDown(self) -> None: 

1812 s3 = boto3.resource("s3") 

1813 bucket = s3.Bucket(self.bucketName) 

1814 try: 

1815 bucket.objects.all().delete() 

1816 except botocore.exceptions.ClientError as e: 

1817 if e.response["Error"]["Code"] == "404": 

1818 # the key was not reachable - pass 

1819 pass 

1820 else: 

1821 raise 

1822 

1823 bucket = s3.Bucket(self.bucketName) 

1824 bucket.delete() 

1825 

1826 # Stop the S3 mock. 

1827 self.mock_s3.stop() 

1828 

1829 # unset any potentially set dummy credentials 

1830 if self.usingDummyCredentials: 

1831 unsetAwsEnvCredentials() 

1832 

1833 if self.reg_dir is not None and os.path.exists(self.reg_dir): 

1834 shutil.rmtree(self.reg_dir, ignore_errors=True) 

1835 

1836 if self.useTempRoot and os.path.exists(self.root): 

1837 shutil.rmtree(self.root, ignore_errors=True) 

1838 

1839 super().tearDown() 

1840 

1841 

1842class PosixDatastoreTransfers(unittest.TestCase): 

1843 """Test data transfers between butlers. 

1844 

1845 Test for different managers. UUID to UUID and integer to integer are 

1846 tested. UUID to integer is not supported since we do not currently 

1847 want to allow that. Integer to UUID is supported with the caveat 

1848 that UUID4 will be generated and this will be incorrect for raw 

1849 dataset types. The test ignores that. 

1850 """ 

1851 

1852 configFile = os.path.join(TESTDIR, "config/basic/butler.yaml") 

1853 storageClassFactory: StorageClassFactory 

1854 

1855 @classmethod 

1856 def setUpClass(cls) -> None: 

1857 cls.storageClassFactory = StorageClassFactory() 

1858 cls.storageClassFactory.addFromConfig(cls.configFile) 

1859 

1860 def setUp(self) -> None: 

1861 self.root = makeTestTempDir(TESTDIR) 

1862 self.config = Config(self.configFile) 

1863 

1864 def tearDown(self) -> None: 

1865 removeTestTempDir(self.root) 

1866 

1867 def create_butler(self, manager: str, label: str) -> Butler: 

1868 config = Config(self.configFile) 

1869 config["registry", "managers", "datasets"] = manager 

1870 return Butler(Butler.makeRepo(f"{self.root}/butler{label}", config=config), writeable=True) 

1871 

1872 def create_butlers(self, manager1: str | None = None, manager2: str | None = None) -> None: 

1873 default = "lsst.daf.butler.registry.datasets.byDimensions.ByDimensionsDatasetRecordStorageManagerUUID" 

1874 if manager1 is None: 

1875 manager1 = default 

1876 if manager2 is None: 

1877 manager2 = default 

1878 self.source_butler = self.create_butler(manager1, "1") 

1879 self.target_butler = self.create_butler(manager2, "2") 

1880 

1881 def testTransferUuidToUuid(self) -> None: 

1882 self.create_butlers() 

1883 self.assertButlerTransfers() 

1884 

1885 def _enable_trust(self, datastore: Datastore) -> None: 

1886 if hasattr(datastore, "trustGetRequest"): 

1887 datastore.trustGetRequest = True 

1888 elif hasattr(datastore, "datastores"): 

1889 for datastore in datastore.datastores: 

1890 if hasattr(datastore, "trustGetRequest"): 

1891 datastore.trustGetRequest = True 

1892 

1893 def testTransferMissing(self) -> None: 

1894 """Test transfers where datastore records are missing. 

1895 

1896 This is how execution butler works. 

1897 """ 

1898 self.create_butlers() 

1899 

1900 # Configure the source butler to allow trust. 

1901 self._enable_trust(self.source_butler.datastore) 

1902 

1903 self.assertButlerTransfers(purge=True) 

1904 

1905 def testTransferMissingDisassembly(self) -> None: 

1906 """Test transfers where datastore records are missing. 

1907 

1908 This is how execution butler works. 

1909 """ 

1910 self.create_butlers() 

1911 

1912 # Configure the source butler to allow trust. 

1913 self._enable_trust(self.source_butler.datastore) 

1914 

1915 # Test disassembly. 

1916 self.assertButlerTransfers(purge=True, storageClassName="StructuredComposite") 

1917 

1918 def testAbsoluteURITransferDirect(self) -> None: 

1919 """Test transfer using an absolute URI.""" 

1920 self._absolute_transfer("auto") 

1921 

1922 def testAbsoluteURITransferCopy(self) -> None: 

1923 """Test transfer using an absolute URI.""" 

1924 self._absolute_transfer("copy") 

1925 

1926 def _absolute_transfer(self, transfer: str) -> None: 

1927 self.create_butlers() 

1928 

1929 storageClassName = "StructuredData" 

1930 storageClass = self.storageClassFactory.getStorageClass(storageClassName) 

1931 datasetTypeName = "random_data" 

1932 run = "run1" 

1933 self.source_butler.registry.registerCollection(run, CollectionType.RUN) 

1934 

1935 dimensions = self.source_butler.registry.dimensions.extract(()) 

1936 datasetType = DatasetType(datasetTypeName, dimensions, storageClass) 

1937 self.source_butler.registry.registerDatasetType(datasetType) 

1938 

1939 metrics = makeExampleMetrics() 

1940 with ResourcePath.temporary_uri(suffix=".json") as temp: 

1941 dataId = DataCoordinate.makeEmpty(self.source_butler.dimensions) 

1942 source_refs = [DatasetRef(datasetType, dataId, run=run)] 

1943 temp.write(json.dumps(metrics.exportAsDict()).encode()) 

1944 dataset = FileDataset(path=temp, refs=source_refs) 

1945 self.source_butler.ingest(dataset, transfer="direct") 

1946 

1947 self.target_butler.transfer_from( 

1948 self.source_butler, dataset.refs, register_dataset_types=True, transfer=transfer 

1949 ) 

1950 

1951 uri = self.target_butler.getURI(dataset.refs[0]) 

1952 if transfer == "auto": 

1953 self.assertEqual(uri, temp) 

1954 else: 

1955 self.assertNotEqual(uri, temp) 

1956 

1957 def assertButlerTransfers(self, purge: bool = False, storageClassName: str = "StructuredData") -> None: 

1958 """Test that a run can be transferred to another butler.""" 

1959 

1960 storageClass = self.storageClassFactory.getStorageClass(storageClassName) 

1961 datasetTypeName = "random_data" 

1962 

1963 # Test will create 3 collections and we will want to transfer 

1964 # two of those three. 

1965 runs = ["run1", "run2", "other"] 

1966 

1967 # Also want to use two different dataset types to ensure that 

1968 # grouping works. 

1969 datasetTypeNames = ["random_data", "random_data_2"] 

1970 

1971 # Create the run collections in the source butler. 

1972 for run in runs: 

1973 self.source_butler.registry.registerCollection(run, CollectionType.RUN) 

1974 

1975 # Create dimensions in source butler. 

1976 n_exposures = 30 

1977 self.source_butler.registry.insertDimensionData("instrument", {"name": "DummyCamComp"}) 

1978 self.source_butler.registry.insertDimensionData( 

1979 "physical_filter", {"instrument": "DummyCamComp", "name": "d-r", "band": "R"} 

1980 ) 

1981 self.source_butler.registry.insertDimensionData( 

1982 "detector", {"instrument": "DummyCamComp", "id": 1, "full_name": "det1"} 

1983 ) 

1984 

1985 for i in range(n_exposures): 

1986 self.source_butler.registry.insertDimensionData( 

1987 "exposure", 

1988 {"instrument": "DummyCamComp", "id": i, "obs_id": f"exp{i}", "physical_filter": "d-r"}, 

1989 ) 

1990 

1991 # Create dataset types in the source butler. 

1992 dimensions = self.source_butler.registry.dimensions.extract(["instrument", "exposure"]) 

1993 for datasetTypeName in datasetTypeNames: 

1994 datasetType = DatasetType(datasetTypeName, dimensions, storageClass) 

1995 self.source_butler.registry.registerDatasetType(datasetType) 

1996 

1997 # Write a dataset to an unrelated run -- this will ensure that 

1998 # we are rewriting integer dataset ids in the target if necessary. 

1999 # Will not be relevant for UUID. 

2000 run = "distraction" 

2001 butler = Butler(butler=self.source_butler, run=run) 

2002 butler.put( 

2003 makeExampleMetrics(), 

2004 datasetTypeName, 

2005 exposure=1, 

2006 instrument="DummyCamComp", 

2007 physical_filter="d-r", 

2008 ) 

2009 

2010 # Write some example metrics to the source 

2011 butler = Butler(butler=self.source_butler) 

2012 

2013 # Set of DatasetRefs that should be in the list of refs to transfer 

2014 # but which will not be transferred. 

2015 deleted: set[DatasetRef] = set() 

2016 

2017 n_expected = 20 # Number of datasets expected to be transferred 

2018 source_refs = [] 

2019 for i in range(n_exposures): 

2020 # Put a third of datasets into each collection, only retain 

2021 # two thirds. 

2022 index = i % 3 

2023 run = runs[index] 

2024 datasetTypeName = datasetTypeNames[i % 2] 

2025 

2026 metric = MetricsExample( 

2027 summary={"counter": i}, output={"text": "metric"}, data=[2 * x for x in range(i)] 

2028 ) 

2029 dataId = {"exposure": i, "instrument": "DummyCamComp", "physical_filter": "d-r"} 

2030 ref = butler.put(metric, datasetTypeName, dataId=dataId, run=run) 

2031 

2032 # Remove the datastore record using low-level API 

2033 if purge: 

2034 # Remove records for a fraction. 

2035 if index == 1: 

2036 # For one of these delete the file as well. 

2037 # This allows the "missing" code to filter the 

2038 # file out. 

2039 # Access the individual datastores. 

2040 datastores = [] 

2041 if hasattr(butler.datastore, "datastores"): 

2042 datastores.extend(butler.datastore.datastores) 

2043 else: 

2044 datastores.append(butler.datastore) 

2045 

2046 if not deleted: 

2047 # For a chained datastore we need to remove 

2048 # files in each chain. 

2049 for datastore in datastores: 

2050 # The file might not be known to the datastore 

2051 # if constraints are used. 

2052 try: 

2053 primary, uris = datastore.getURIs(ref) 

2054 except FileNotFoundError: 

2055 continue 

2056 if primary: 

2057 if primary.scheme != "mem": 

2058 primary.remove() 

2059 for uri in uris.values(): 

2060 if uri.scheme != "mem": 

2061 uri.remove() 

2062 n_expected -= 1 

2063 deleted.add(ref) 

2064 

2065 # Remove the datastore record. 

2066 for datastore in datastores: 

2067 if hasattr(datastore, "removeStoredItemInfo"): 

2068 datastore.removeStoredItemInfo(ref) 

2069 

2070 if index < 2: 

2071 source_refs.append(ref) 

2072 if ref not in deleted: 

2073 new_metric = butler.get(ref) 

2074 self.assertEqual(new_metric, metric) 

2075 

2076 # Create some bad dataset types to ensure we check for inconsistent 

2077 # definitions. 

2078 badStorageClass = self.storageClassFactory.getStorageClass("StructuredDataList") 

2079 for datasetTypeName in datasetTypeNames: 

2080 datasetType = DatasetType(datasetTypeName, dimensions, badStorageClass) 

2081 self.target_butler.registry.registerDatasetType(datasetType) 

2082 with self.assertRaises(ConflictingDefinitionError) as cm: 

2083 self.target_butler.transfer_from(self.source_butler, source_refs) 

2084 self.assertIn("dataset type differs", str(cm.exception)) 

2085 

2086 # And remove the bad definitions. 

2087 for datasetTypeName in datasetTypeNames: 

2088 self.target_butler.registry.removeDatasetType(datasetTypeName) 

2089 

2090 # Transfer without creating dataset types should fail. 

2091 with self.assertRaises(KeyError): 

2092 self.target_butler.transfer_from(self.source_butler, source_refs) 

2093 

2094 # Transfer without creating dimensions should fail. 

2095 with self.assertRaises(ConflictingDefinitionError) as cm: 

2096 self.target_butler.transfer_from(self.source_butler, source_refs, register_dataset_types=True) 

2097 self.assertIn("dimension", str(cm.exception)) 

2098 

2099 # The failed transfer above leaves registry in an inconsistent 

2100 # state because the run is created but then rolled back without 

2101 # the collection cache being cleared. For now force a refresh. 

2102 # Can remove with DM-35498. 

2103 self.target_butler.registry.refresh() 

2104 

2105 # Now transfer them to the second butler, including dimensions. 

2106 with self.assertLogs(level=logging.DEBUG) as log_cm: 

2107 transferred = self.target_butler.transfer_from( 

2108 self.source_butler, 

2109 source_refs, 

2110 register_dataset_types=True, 

2111 transfer_dimensions=True, 

2112 ) 

2113 self.assertEqual(len(transferred), n_expected) 

2114 log_output = ";".join(log_cm.output) 

2115 

2116 # A ChainedDatastore will use the in-memory datastore for mexists 

2117 # so we can not rely on the mexists log message. 

2118 self.assertIn("Number of datastore records found in source", log_output) 

2119 self.assertIn("Creating output run", log_output) 

2120 

2121 # Do the transfer twice to ensure that it will do nothing extra. 

2122 # Only do this if purge=True because it does not work for int 

2123 # dataset_id. 

2124 if purge: 

2125 # This should not need to register dataset types. 

2126 transferred = self.target_butler.transfer_from(self.source_butler, source_refs) 

2127 self.assertEqual(len(transferred), n_expected) 

2128 

2129 # Also do an explicit low-level transfer to trigger some 

2130 # edge cases. 

2131 with self.assertLogs(level=logging.DEBUG) as log_cm: 

2132 self.target_butler.datastore.transfer_from(self.source_butler.datastore, source_refs) 

2133 log_output = ";".join(log_cm.output) 

2134 self.assertIn("no file artifacts exist", log_output) 

2135 

2136 with self.assertRaises((TypeError, AttributeError)): 

2137 self.target_butler.datastore.transfer_from(self.source_butler, source_refs) # type: ignore 

2138 

2139 with self.assertRaises(ValueError): 

2140 self.target_butler.datastore.transfer_from( 

2141 self.source_butler.datastore, source_refs, transfer="split" 

2142 ) 

2143 

2144 # Now try to get the same refs from the new butler. 

2145 for ref in source_refs: 

2146 if ref not in deleted: 

2147 new_metric = self.target_butler.get(ref) 

2148 old_metric = self.source_butler.get(ref) 

2149 self.assertEqual(new_metric, old_metric) 

2150 

2151 # Now prune run2 collection and create instead a CHAINED collection. 

2152 # This should block the transfer. 

2153 self.target_butler.removeRuns(["run2"], unstore=True) 

2154 self.target_butler.registry.registerCollection("run2", CollectionType.CHAINED) 

2155 with self.assertRaises(CollectionTypeError): 

2156 # Re-importing the run1 datasets can be problematic if they 

2157 # use integer IDs so filter those out. 

2158 to_transfer = [ref for ref in source_refs if ref.run == "run2"] 

2159 self.target_butler.transfer_from(self.source_butler, to_transfer) 

2160 

2161 

2162class ChainedDatastoreTransfers(PosixDatastoreTransfers): 

2163 configFile = os.path.join(TESTDIR, "config/basic/butler-chained.yaml") 

2164 

2165 

2166if __name__ == "__main__": 

2167 unittest.main()