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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/>.
21from __future__ import annotations
23"""Generic file-based datastore code."""
25__all__ = ("FileLikeDatastore", )
27import logging
28from abc import abstractmethod
30from sqlalchemy import Integer, String
32from dataclasses import dataclass
33from typing import (
34 TYPE_CHECKING,
35 Any,
36 ClassVar,
37 Dict,
38 Iterable,
39 List,
40 Mapping,
41 Optional,
42 Set,
43 Tuple,
44 Type,
45 Union,
46)
48from lsst.daf.butler import (
49 ButlerURI,
50 CompositesMap,
51 Config,
52 FileDataset,
53 DatasetRef,
54 DatasetType,
55 DatasetTypeNotSupportedError,
56 Datastore,
57 DatastoreConfig,
58 DatastoreValidationError,
59 FileDescriptor,
60 FileTemplates,
61 FileTemplateValidationError,
62 Formatter,
63 FormatterFactory,
64 Location,
65 LocationFactory,
66 StorageClass,
67 StoredFileInfo,
68)
70from lsst.daf.butler import ddl
71from lsst.daf.butler.registry.interfaces import (
72 ReadOnlyDatabaseError,
73 DatastoreRegistryBridge,
74 FakeDatasetRef,
75)
77from lsst.daf.butler.core.repoRelocation import replaceRoot
78from lsst.daf.butler.core.utils import getInstanceOf, getClassOf, transactional
79from .genericDatastore import GenericBaseDatastore
81if TYPE_CHECKING: 81 ↛ 82line 81 didn't jump to line 82, because the condition on line 81 was never true
82 from lsst.daf.butler import LookupKey
83 from lsst.daf.butler.registry.interfaces import DatasetIdRef, DatastoreRegistryBridgeManager
85log = logging.getLogger(__name__)
87# String to use when a Python None is encountered
88NULLSTR = "__NULL_STRING__"
91class _IngestPrepData(Datastore.IngestPrepData):
92 """Helper class for FileLikeDatastore ingest implementation.
94 Parameters
95 ----------
96 datasets : `list` of `FileDataset`
97 Files to be ingested by this datastore.
98 """
99 def __init__(self, datasets: List[FileDataset]):
100 super().__init__(ref for dataset in datasets for ref in dataset.refs)
101 self.datasets = datasets
104@dataclass(frozen=True)
105class DatastoreFileGetInformation:
106 """Collection of useful parameters needed to retrieve a file from
107 a Datastore.
108 """
110 location: Location
111 """The location from which to read the dataset."""
113 formatter: Formatter
114 """The `Formatter` to use to deserialize the dataset."""
116 info: StoredFileInfo
117 """Stored information about this file and its formatter."""
119 assemblerParams: dict
120 """Parameters to use for post-processing the retrieved dataset."""
122 component: Optional[str]
123 """The component to be retrieved (can be `None`)."""
125 readStorageClass: StorageClass
126 """The `StorageClass` of the dataset being read."""
129class FileLikeDatastore(GenericBaseDatastore):
130 """Generic Datastore for file-based implementations.
132 Should always be sub-classed since key abstract methods are missing.
134 Parameters
135 ----------
136 config : `DatastoreConfig` or `str`
137 Configuration as either a `Config` object or URI to file.
138 bridgeManager : `DatastoreRegistryBridgeManager`
139 Object that manages the interface between `Registry` and datastores.
140 butlerRoot : `str`, optional
141 New datastore root to use to override the configuration value.
143 Raises
144 ------
145 ValueError
146 If root location does not exist and ``create`` is `False` in the
147 configuration.
148 """
150 defaultConfigFile: ClassVar[Optional[str]] = None
151 """Path to configuration defaults. Relative to $DAF_BUTLER_DIR/config or
152 absolute path. Can be None if no defaults specified.
153 """
155 root: str
156 """Root directory or URI of this `Datastore`."""
158 locationFactory: LocationFactory
159 """Factory for creating locations relative to the datastore root."""
161 formatterFactory: FormatterFactory
162 """Factory for creating instances of formatters."""
164 templates: FileTemplates
165 """File templates that can be used by this `Datastore`."""
167 composites: CompositesMap
168 """Determines whether a dataset should be disassembled on put."""
170 @classmethod
171 def setConfigRoot(cls, root: str, config: Config, full: Config, overwrite: bool = True) -> None:
172 """Set any filesystem-dependent config options for this Datastore to
173 be appropriate for a new empty repository with the given root.
175 Parameters
176 ----------
177 root : `str`
178 URI to the root of the data repository.
179 config : `Config`
180 A `Config` to update. Only the subset understood by
181 this component will be updated. Will not expand
182 defaults.
183 full : `Config`
184 A complete config with all defaults expanded that can be
185 converted to a `DatastoreConfig`. Read-only and will not be
186 modified by this method.
187 Repository-specific options that should not be obtained
188 from defaults when Butler instances are constructed
189 should be copied from ``full`` to ``config``.
190 overwrite : `bool`, optional
191 If `False`, do not modify a value in ``config`` if the value
192 already exists. Default is always to overwrite with the provided
193 ``root``.
195 Notes
196 -----
197 If a keyword is explicitly defined in the supplied ``config`` it
198 will not be overridden by this method if ``overwrite`` is `False`.
199 This allows explicit values set in external configs to be retained.
200 """
201 Config.updateParameters(DatastoreConfig, config, full,
202 toUpdate={"root": root},
203 toCopy=("cls", ("records", "table")), overwrite=overwrite)
205 @classmethod
206 def makeTableSpec(cls) -> ddl.TableSpec:
207 return ddl.TableSpec(
208 fields=[
209 ddl.FieldSpec(name="dataset_id", dtype=Integer, primaryKey=True),
210 ddl.FieldSpec(name="path", dtype=String, length=256, nullable=False),
211 ddl.FieldSpec(name="formatter", dtype=String, length=128, nullable=False),
212 ddl.FieldSpec(name="storage_class", dtype=String, length=64, nullable=False),
213 # Use empty string to indicate no component
214 ddl.FieldSpec(name="component", dtype=String, length=32, primaryKey=True),
215 # TODO: should checksum be Base64Bytes instead?
216 ddl.FieldSpec(name="checksum", dtype=String, length=128, nullable=True),
217 ddl.FieldSpec(name="file_size", dtype=Integer, nullable=True),
218 ],
219 unique=frozenset(),
220 )
222 def __init__(self, config: Union[DatastoreConfig, str],
223 bridgeManager: DatastoreRegistryBridgeManager, butlerRoot: str = None):
224 super().__init__(config, bridgeManager)
225 if "root" not in self.config: 225 ↛ 226line 225 didn't jump to line 226, because the condition on line 225 was never true
226 raise ValueError("No root directory specified in configuration")
228 # Name ourselves either using an explicit name or a name
229 # derived from the (unexpanded) root
230 if "name" in self.config:
231 self.name = self.config["name"]
232 else:
233 # We use the unexpanded root in the name to indicate that this
234 # datastore can be moved without having to update registry.
235 self.name = "{}@{}".format(type(self).__name__,
236 self.config["root"])
238 # Support repository relocation in config
239 # Existence of self.root is checked in subclass
240 self.root = replaceRoot(self.config["root"], butlerRoot)
242 self.locationFactory = LocationFactory(self.root)
243 self.formatterFactory = FormatterFactory()
245 # Now associate formatters with storage classes
246 self.formatterFactory.registerFormatters(self.config["formatters"],
247 universe=bridgeManager.universe)
249 # Read the file naming templates
250 self.templates = FileTemplates(self.config["templates"],
251 universe=bridgeManager.universe)
253 # See if composites should be disassembled
254 self.composites = CompositesMap(self.config["composites"],
255 universe=bridgeManager.universe)
257 tableName = self.config["records", "table"]
258 try:
259 # Storage of paths and formatters, keyed by dataset_id
260 self._table = bridgeManager.opaque.register(tableName, self.makeTableSpec())
261 # Interface to Registry.
262 self._bridge = bridgeManager.register(self.name)
263 except ReadOnlyDatabaseError:
264 # If the database is read only and we just tried and failed to
265 # create a table, it means someone is trying to create a read-only
266 # butler client for an empty repo. That should be okay, as long
267 # as they then try to get any datasets before some other client
268 # creates the table. Chances are they'rejust validating
269 # configuration.
270 pass
272 # Determine whether checksums should be used
273 self.useChecksum = self.config.get("checksum", True)
275 def __str__(self) -> str:
276 return self.root
278 @property
279 def bridge(self) -> DatastoreRegistryBridge:
280 return self._bridge
282 @abstractmethod
283 def _artifact_exists(self, location: Location) -> bool:
284 """Check that an artifact exists in this datastore at the specified
285 location.
287 Parameters
288 ----------
289 location : `Location`
290 Expected location of the artifact associated with this datastore.
292 Returns
293 -------
294 exists : `bool`
295 True if the location can be found, false otherwise.
296 """
297 raise NotImplementedError()
299 @abstractmethod
300 def _delete_artifact(self, location: Location) -> None:
301 """Delete the artifact from the datastore.
303 Parameters
304 ----------
305 location : `Location`
306 Location of the artifact associated with this datastore.
307 """
308 raise NotImplementedError()
310 def addStoredItemInfo(self, refs: Iterable[DatasetRef], infos: Iterable[StoredFileInfo]) -> None:
311 # Docstring inherited from GenericBaseDatastore
312 records = []
313 for ref, info in zip(refs, infos):
314 # Component should come from ref and fall back on info
315 component = ref.datasetType.component()
316 if component is None and info.component is not None: 316 ↛ 317line 316 didn't jump to line 317, because the condition on line 316 was never true
317 component = info.component
318 if component is None:
319 # Use empty string since we want this to be part of the
320 # primary key.
321 component = NULLSTR
322 records.append(
323 dict(dataset_id=ref.id, formatter=info.formatter, path=info.path,
324 storage_class=info.storageClass.name, component=component,
325 checksum=info.checksum, file_size=info.file_size)
326 )
327 self._table.insert(*records)
329 def getStoredItemInfo(self, ref: DatasetIdRef) -> StoredFileInfo:
330 # Docstring inherited from GenericBaseDatastore
332 if ref.id is None: 332 ↛ 333line 332 didn't jump to line 333, because the condition on line 332 was never true
333 raise RuntimeError("Unable to retrieve information for unresolved DatasetRef")
335 where: Dict[str, Union[int, str]] = {"dataset_id": ref.id}
337 # If we have no component we want the row from this table without
338 # a component. If we do have a component we either need the row
339 # with no component or the row with the component, depending on how
340 # this dataset was dissassembled.
342 # if we are emptying trash we won't have real refs so can't constrain
343 # by component. Will need to fix this to return multiple matches
344 # in future.
345 component = None
346 try:
347 component = ref.datasetType.component()
348 except AttributeError:
349 pass
350 else:
351 if component is None: 351 ↛ 356line 351 didn't jump to line 356, because the condition on line 351 was never false
352 where["component"] = NULLSTR
354 # Look for the dataset_id -- there might be multiple matches
355 # if we have disassembled the dataset.
356 records = list(self._table.fetch(**where))
357 if len(records) == 0: 357 ↛ 358line 357 didn't jump to line 358, because the condition on line 357 was never true
358 raise KeyError(f"Unable to retrieve location associated with dataset {ref}.")
360 # if we are not asking for a component
361 if not component and len(records) != 1: 361 ↛ 362line 361 didn't jump to line 362, because the condition on line 361 was never true
362 raise RuntimeError(f"Got {len(records)} from location query of dataset {ref}")
364 # if we had a FakeDatasetRef we pick the first record regardless
365 if isinstance(ref, FakeDatasetRef): 365 ↛ 366line 365 didn't jump to line 366, because the condition on line 365 was never true
366 record = records[0]
367 else:
368 records_by_component = {}
369 for r in records:
370 this_component = r["component"] if r["component"] and r["component"] != NULLSTR else None
371 records_by_component[this_component] = r
373 # Look for component by name else fall back to the parent
374 for lookup in (component, None): 374 ↛ 379line 374 didn't jump to line 379, because the loop on line 374 didn't complete
375 if lookup in records_by_component: 375 ↛ 374line 375 didn't jump to line 374, because the condition on line 375 was never false
376 record = records_by_component[lookup]
377 break
378 else:
379 raise KeyError(f"Unable to retrieve location for component {component} associated with "
380 f"dataset {ref}.")
382 # Convert name of StorageClass to instance
383 storageClass = self.storageClassFactory.getStorageClass(record["storage_class"])
385 return StoredFileInfo(formatter=record["formatter"],
386 path=record["path"],
387 storageClass=storageClass,
388 component=component,
389 checksum=record["checksum"],
390 file_size=record["file_size"])
392 def getStoredItemsInfo(self, ref: DatasetIdRef) -> List[StoredFileInfo]:
393 # Docstring inherited from GenericBaseDatastore
395 # Look for the dataset_id -- there might be multiple matches
396 # if we have disassembled the dataset.
397 records = list(self._table.fetch(dataset_id=ref.id))
399 results = []
400 for record in records:
401 # Convert name of StorageClass to instance
402 storageClass = self.storageClassFactory.getStorageClass(record["storage_class"])
403 component = record["component"] if (record["component"]
404 and record["component"] != NULLSTR) else None
406 info = StoredFileInfo(formatter=record["formatter"],
407 path=record["path"],
408 storageClass=storageClass,
409 component=component,
410 checksum=record["checksum"],
411 file_size=record["file_size"])
412 results.append(info)
414 return results
416 def _registered_refs_per_artifact(self, pathInStore: str) -> Set[int]:
417 """Return all dataset refs associated with the supplied path.
419 Parameters
420 ----------
421 pathInStore : `str`
422 Path of interest in the data store.
424 Returns
425 -------
426 ids : `set` of `int`
427 All `DatasetRef` IDs associated with this path.
428 """
429 records = list(self._table.fetch(path=pathInStore))
430 ids = {r["dataset_id"] for r in records}
431 return ids
433 def removeStoredItemInfo(self, ref: DatasetIdRef) -> None:
434 # Docstring inherited from GenericBaseDatastore
435 self._table.delete(dataset_id=ref.id)
437 def _get_dataset_location_info(self,
438 ref: DatasetRef) -> Tuple[Optional[Location], Optional[StoredFileInfo]]:
439 """Find the `Location` of the requested dataset in the
440 `Datastore` and the associated stored file information.
442 Parameters
443 ----------
444 ref : `DatasetRef`
445 Reference to the required `Dataset`.
447 Returns
448 -------
449 location : `Location`
450 Location of the dataset within the datastore.
451 Returns `None` if the dataset can not be located.
452 info : `StoredFileInfo`
453 Stored information about this file and its formatter.
454 """
455 # Get the file information (this will fail if no file)
456 try:
457 storedFileInfo = self.getStoredItemInfo(ref)
458 except KeyError:
459 return None, None
461 # Use the path to determine the location
462 location = self.locationFactory.fromPath(storedFileInfo.path)
464 return location, storedFileInfo
466 def _get_dataset_locations_info(self, ref: DatasetIdRef) -> List[Tuple[Location, StoredFileInfo]]:
467 r"""Find all the `Location`\ s of the requested dataset in the
468 `Datastore` and the associated stored file information.
470 Parameters
471 ----------
472 ref : `DatasetRef`
473 Reference to the required `Dataset`.
475 Returns
476 -------
477 results : `list` [`tuple` [`Location`, `StoredFileInfo` ]]
478 Location of the dataset within the datastore and
479 stored information about each file and its formatter.
480 """
481 # Get the file information (this will fail if no file)
482 records = self.getStoredItemsInfo(ref)
484 # Use the path to determine the location
485 return [(self.locationFactory.fromPath(r.path), r) for r in records]
487 def _can_remove_dataset_artifact(self, ref: DatasetIdRef, location: Location) -> bool:
488 """Check that there is only one dataset associated with the
489 specified artifact.
491 Parameters
492 ----------
493 ref : `DatasetRef` or `FakeDatasetRef`
494 Dataset to be removed.
495 location : `Location`
496 The location of the artifact to be removed.
498 Returns
499 -------
500 can_remove : `Bool`
501 True if the artifact can be safely removed.
502 """
504 # Get all entries associated with this path
505 allRefs = self._registered_refs_per_artifact(location.pathInStore)
506 if not allRefs: 506 ↛ 507line 506 didn't jump to line 507, because the condition on line 506 was never true
507 raise RuntimeError(f"Datastore inconsistency error. {location.pathInStore} not in registry")
509 # Get all the refs associated with this dataset if it is a composite
510 theseRefs = {r.id for r in ref.allRefs()}
512 # Remove these refs from all the refs and if there is nothing left
513 # then we can delete
514 remainingRefs = allRefs - theseRefs
516 if remainingRefs:
517 return False
518 return True
520 def _prepare_for_get(self, ref: DatasetRef,
521 parameters: Optional[Mapping[str, Any]] = None) -> List[DatastoreFileGetInformation]:
522 """Check parameters for ``get`` and obtain formatter and
523 location.
525 Parameters
526 ----------
527 ref : `DatasetRef`
528 Reference to the required Dataset.
529 parameters : `dict`
530 `StorageClass`-specific parameters that specify, for example,
531 a slice of the dataset to be loaded.
533 Returns
534 -------
535 getInfo : `list` [`DatastoreFileGetInformation`]
536 Parameters needed to retrieve each file.
537 """
538 log.debug("Retrieve %s from %s with parameters %s", ref, self.name, parameters)
540 # Get file metadata and internal metadata
541 fileLocations = self._get_dataset_locations_info(ref)
542 if not fileLocations:
543 raise FileNotFoundError(f"Could not retrieve dataset {ref}.")
545 # The storage class we want to use eventually
546 refStorageClass = ref.datasetType.storageClass
548 # Check that the supplied parameters are suitable for the type read
549 refStorageClass.validateParameters(parameters)
551 if len(fileLocations) > 1:
552 disassembled = True
553 else:
554 disassembled = False
556 # Is this a component request?
557 refComponent = ref.datasetType.component()
559 fileGetInfo = []
560 for location, storedFileInfo in fileLocations:
562 # The storage class used to write the file
563 writeStorageClass = storedFileInfo.storageClass
565 # If this has been disassembled we need read to match the write
566 if disassembled:
567 readStorageClass = writeStorageClass
568 else:
569 readStorageClass = refStorageClass
571 formatter = getInstanceOf(storedFileInfo.formatter,
572 FileDescriptor(location, readStorageClass=readStorageClass,
573 storageClass=writeStorageClass, parameters=parameters),
574 ref.dataId)
576 _, notFormatterParams = formatter.segregateParameters()
578 # Of the remaining parameters, extract the ones supported by
579 # this StorageClass (for components not all will be handled)
580 assemblerParams = readStorageClass.filterParameters(notFormatterParams)
582 # The ref itself could be a component if the dataset was
583 # disassembled by butler, or we disassembled in datastore and
584 # components came from the datastore records
585 component = storedFileInfo.component if storedFileInfo.component else refComponent
587 fileGetInfo.append(DatastoreFileGetInformation(location, formatter, storedFileInfo,
588 assemblerParams, component, readStorageClass))
590 return fileGetInfo
592 def _prepare_for_put(self, inMemoryDataset: Any, ref: DatasetRef) -> Tuple[Location, Formatter]:
593 """Check the arguments for ``put`` and obtain formatter and
594 location.
596 Parameters
597 ----------
598 inMemoryDataset : `object`
599 The dataset to store.
600 ref : `DatasetRef`
601 Reference to the associated Dataset.
603 Returns
604 -------
605 location : `Location`
606 The location to write the dataset.
607 formatter : `Formatter`
608 The `Formatter` to use to write the dataset.
610 Raises
611 ------
612 TypeError
613 Supplied object and storage class are inconsistent.
614 DatasetTypeNotSupportedError
615 The associated `DatasetType` is not handled by this datastore.
616 """
617 self._validate_put_parameters(inMemoryDataset, ref)
619 # Work out output file name
620 try:
621 template = self.templates.getTemplate(ref)
622 except KeyError as e:
623 raise DatasetTypeNotSupportedError(f"Unable to find template for {ref}") from e
625 location = self.locationFactory.fromPath(template.format(ref))
627 # Get the formatter based on the storage class
628 storageClass = ref.datasetType.storageClass
629 try:
630 formatter = self.formatterFactory.getFormatter(ref,
631 FileDescriptor(location,
632 storageClass=storageClass),
633 ref.dataId)
634 except KeyError as e:
635 raise DatasetTypeNotSupportedError(f"Unable to find formatter for {ref}") from e
637 return location, formatter
639 @abstractmethod
640 def _standardizeIngestPath(self, path: str, *, transfer: Optional[str] = None) -> str:
641 """Standardize the path of a to-be-ingested file.
643 Parameters
644 ----------
645 path : `str`
646 Path of a file to be ingested.
647 transfer : `str`, optional
648 How (and whether) the dataset should be added to the datastore.
649 See `ingest` for details of transfer modes.
650 This implementation is provided only so
651 `NotImplementedError` can be raised if the mode is not supported;
652 actual transfers are deferred to `_extractIngestInfo`.
654 Returns
655 -------
656 path : `str`
657 New path in what the datastore considers standard form.
659 Notes
660 -----
661 Subclasses of `FileLikeDatastore` should implement this method instead
662 of `_prepIngest`. It should not modify the data repository or given
663 file in any way.
665 Raises
666 ------
667 NotImplementedError
668 Raised if the datastore does not support the given transfer mode
669 (including the case where ingest is not supported at all).
670 FileNotFoundError
671 Raised if one of the given files does not exist.
672 """
673 raise NotImplementedError("Must be implemented by subclasses.")
675 @abstractmethod
676 def _extractIngestInfo(self, path: str, ref: DatasetRef, *,
677 formatter: Union[Formatter, Type[Formatter]],
678 transfer: Optional[str] = None) -> StoredFileInfo:
679 """Relocate (if necessary) and extract `StoredFileInfo` from a
680 to-be-ingested file.
682 Parameters
683 ----------
684 path : `str`
685 Path of a file to be ingested.
686 ref : `DatasetRef`
687 Reference for the dataset being ingested. Guaranteed to have
688 ``dataset_id not None`.
689 formatter : `type` or `Formatter`
690 `Formatter` subclass to use for this dataset or an instance.
691 transfer : `str`, optional
692 How (and whether) the dataset should be added to the datastore.
693 See `ingest` for details of transfer modes.
695 Returns
696 -------
697 info : `StoredFileInfo`
698 Internal datastore record for this file. This will be inserted by
699 the caller; the `_extractIngestInfo` is only resposible for
700 creating and populating the struct.
702 Raises
703 ------
704 FileNotFoundError
705 Raised if one of the given files does not exist.
706 FileExistsError
707 Raised if transfer is not `None` but the (internal) location the
708 file would be moved to is already occupied.
709 """
710 raise NotImplementedError("Must be implemented by subclasses.")
712 def _prepIngest(self, *datasets: FileDataset, transfer: Optional[str] = None) -> _IngestPrepData:
713 # Docstring inherited from Datastore._prepIngest.
714 filtered = []
715 for dataset in datasets:
716 acceptable = [ref for ref in dataset.refs if self.constraints.isAcceptable(ref)]
717 if not acceptable:
718 continue
719 else:
720 dataset.refs = acceptable
721 if dataset.formatter is None:
722 dataset.formatter = self.formatterFactory.getFormatterClass(dataset.refs[0])
723 else:
724 assert isinstance(dataset.formatter, (type, str))
725 dataset.formatter = getClassOf(dataset.formatter)
726 dataset.path = self._standardizeIngestPath(dataset.path, transfer=transfer)
727 filtered.append(dataset)
728 return _IngestPrepData(filtered)
730 @transactional
731 def _finishIngest(self, prepData: Datastore.IngestPrepData, *, transfer: Optional[str] = None) -> None:
732 # Docstring inherited from Datastore._finishIngest.
733 refsAndInfos = []
734 for dataset in prepData.datasets:
735 # Do ingest as if the first dataset ref is associated with the file
736 info = self._extractIngestInfo(dataset.path, dataset.refs[0], formatter=dataset.formatter,
737 transfer=transfer)
738 refsAndInfos.extend([(ref, info) for ref in dataset.refs])
739 self._register_datasets(refsAndInfos)
741 @abstractmethod
742 def _write_in_memory_to_artifact(self, inMemoryDataset: Any, ref: DatasetRef) -> StoredFileInfo:
743 """Write out in memory dataset to datastore.
745 Parameters
746 ----------
747 inMemoryDataset : `object`
748 Dataset to write to datastore.
749 ref : `DatasetRef`
750 Registry information associated with this dataset.
752 Returns
753 -------
754 info : `StoredFileInfo`
755 Information describin the artifact written to the datastore.
756 """
757 raise NotImplementedError()
759 @abstractmethod
760 def _read_artifact_into_memory(self, getInfo: DatastoreFileGetInformation,
761 ref: DatasetRef, isComponent: bool = False) -> Any:
762 """Read the artifact from datastore into in memory object.
764 Parameters
765 ----------
766 getInfo : `DatastoreFileGetInformation`
767 Information about the artifact within the datastore.
768 ref : `DatasetRef`
769 The registry information associated with this artifact.
770 isComponent : `bool`
771 Flag to indicate if a component is being read from this artifact.
773 Returns
774 -------
775 inMemoryDataset : `object`
776 The artifact as a python object.
777 """
778 raise NotImplementedError()
780 def exists(self, ref: DatasetRef) -> bool:
781 """Check if the dataset exists in the datastore.
783 Parameters
784 ----------
785 ref : `DatasetRef`
786 Reference to the required dataset.
788 Returns
789 -------
790 exists : `bool`
791 `True` if the entity exists in the `Datastore`.
792 """
793 fileLocations = self._get_dataset_locations_info(ref)
794 if not fileLocations:
795 return False
796 for location, _ in fileLocations:
797 if not self._artifact_exists(location):
798 return False
800 return True
802 def getURIs(self, ref: DatasetRef,
803 predict: bool = False) -> Tuple[Optional[ButlerURI], Dict[str, ButlerURI]]:
804 """Return URIs associated with dataset.
806 Parameters
807 ----------
808 ref : `DatasetRef`
809 Reference to the required dataset.
810 predict : `bool`, optional
811 If the datastore does not know about the dataset, should it
812 return a predicted URI or not?
814 Returns
815 -------
816 primary : `ButlerURI`
817 The URI to the primary artifact associated with this dataset.
818 If the dataset was disassembled within the datastore this
819 may be `None`.
820 components : `dict`
821 URIs to any components associated with the dataset artifact.
822 Can be empty if there are no components.
823 """
825 primary: Optional[ButlerURI] = None
826 components: Dict[str, ButlerURI] = {}
828 # if this has never been written then we have to guess
829 if not self.exists(ref):
830 if not predict:
831 raise FileNotFoundError("Dataset {} not in this datastore".format(ref))
833 def predictLocation(thisRef: DatasetRef) -> Location:
834 template = self.templates.getTemplate(thisRef)
835 location = self.locationFactory.fromPath(template.format(thisRef))
836 storageClass = ref.datasetType.storageClass
837 formatter = self.formatterFactory.getFormatter(thisRef,
838 FileDescriptor(location,
839 storageClass=storageClass))
840 # Try to use the extension attribute but ignore problems if the
841 # formatter does not define one.
842 try:
843 location = formatter.makeUpdatedLocation(location)
844 except Exception:
845 # Use the default extension
846 pass
847 return location
849 doDisassembly = self.composites.shouldBeDisassembled(ref)
851 if doDisassembly:
853 for component, componentStorage in ref.datasetType.storageClass.components.items():
854 compTypeName = ref.datasetType.componentTypeName(component)
855 compType = DatasetType(compTypeName, dimensions=ref.datasetType.dimensions,
856 storageClass=componentStorage)
857 compRef = DatasetRef(compType, ref.dataId, id=ref.id, run=ref.run, conform=False)
859 compLocation = predictLocation(compRef)
861 # Add a URI fragment to indicate this is a guess
862 components[component] = ButlerURI(compLocation.uri + "#predicted")
864 else:
866 location = predictLocation(ref)
868 # Add a URI fragment to indicate this is a guess
869 primary = ButlerURI(location.uri + "#predicted")
871 return primary, components
873 # If this is a ref that we have written we can get the path.
874 # Get file metadata and internal metadata
875 fileLocations = self._get_dataset_locations_info(ref)
877 if not fileLocations: 877 ↛ 878line 877 didn't jump to line 878, because the condition on line 877 was never true
878 raise RuntimeError(f"Unexpectedly got no artifacts for dataset {ref}")
880 if len(fileLocations) == 1:
881 # No disassembly so this is the primary URI
882 primary = ButlerURI(fileLocations[0][0].uri)
884 else:
885 for location, storedFileInfo in fileLocations:
886 if storedFileInfo.component is None: 886 ↛ 887line 886 didn't jump to line 887, because the condition on line 886 was never true
887 raise RuntimeError(f"Unexpectedly got no component name for a component at {location}")
888 components[storedFileInfo.component] = ButlerURI(location.uri)
890 return primary, components
892 def getURI(self, ref: DatasetRef, predict: bool = False) -> ButlerURI:
893 """URI to the Dataset.
895 Parameters
896 ----------
897 ref : `DatasetRef`
898 Reference to the required Dataset.
899 predict : `bool`
900 If `True`, allow URIs to be returned of datasets that have not
901 been written.
903 Returns
904 -------
905 uri : `str`
906 URI pointing to the dataset within the datastore. If the
907 dataset does not exist in the datastore, and if ``predict`` is
908 `True`, the URI will be a prediction and will include a URI
909 fragment "#predicted".
910 If the datastore does not have entities that relate well
911 to the concept of a URI the returned URI will be
912 descriptive. The returned URI is not guaranteed to be obtainable.
914 Raises
915 ------
916 FileNotFoundError
917 Raised if a URI has been requested for a dataset that does not
918 exist and guessing is not allowed.
919 RuntimeError
920 Raised if a request is made for a single URI but multiple URIs
921 are associated with this dataset.
923 Notes
924 -----
925 When a predicted URI is requested an attempt will be made to form
926 a reasonable URI based on file templates and the expected formatter.
927 """
928 primary, components = self.getURIs(ref, predict)
929 if primary is None or components: 929 ↛ 930line 929 didn't jump to line 930, because the condition on line 929 was never true
930 raise RuntimeError(f"Dataset ({ref}) includes distinct URIs for components. "
931 "Use Dataastore.getURIs() instead.")
932 return primary
934 def get(self, ref: DatasetRef, parameters: Optional[Mapping[str, Any]] = None) -> Any:
935 """Load an InMemoryDataset from the store.
937 Parameters
938 ----------
939 ref : `DatasetRef`
940 Reference to the required Dataset.
941 parameters : `dict`
942 `StorageClass`-specific parameters that specify, for example,
943 a slice of the dataset to be loaded.
945 Returns
946 -------
947 inMemoryDataset : `object`
948 Requested dataset or slice thereof as an InMemoryDataset.
950 Raises
951 ------
952 FileNotFoundError
953 Requested dataset can not be retrieved.
954 TypeError
955 Return value from formatter has unexpected type.
956 ValueError
957 Formatter failed to process the dataset.
958 """
959 allGetInfo = self._prepare_for_get(ref, parameters)
960 refComponent = ref.datasetType.component()
962 if len(allGetInfo) > 1 and not refComponent:
963 # This was a disassembled dataset spread over multiple files
964 # and we need to put them all back together again.
965 # Read into memory and then assemble
966 usedParams = set()
967 components = {}
968 for getInfo in allGetInfo:
969 # assemblerParams are parameters not understood by the
970 # associated formatter.
971 usedParams.update(set(getInfo.assemblerParams))
973 component = getInfo.component
974 # We do not want the formatter to think it's reading
975 # a component though because it is really reading a
976 # standalone dataset -- always tell reader it is not a
977 # component.
978 components[component] = self._read_artifact_into_memory(getInfo, ref, isComponent=False)
980 inMemoryDataset = ref.datasetType.storageClass.assembler().assemble(components)
982 # Any unused parameters will have to be passed to the assembler
983 if parameters:
984 unusedParams = {k: v for k, v in parameters.items() if k not in usedParams}
985 else:
986 unusedParams = {}
988 # Process parameters
989 return ref.datasetType.storageClass.assembler().handleParameters(inMemoryDataset,
990 parameters=unusedParams)
992 else:
993 # Single file request or component from that composite file
994 allComponents = {i.component: i for i in allGetInfo}
995 for lookup in (refComponent, None): 995 ↛ 1000line 995 didn't jump to line 1000, because the loop on line 995 didn't complete
996 if lookup in allComponents: 996 ↛ 995line 996 didn't jump to line 995, because the condition on line 996 was never false
997 getInfo = allComponents[lookup]
998 break
999 else:
1000 raise FileNotFoundError(f"Component {refComponent} not found "
1001 f"for ref {ref} in datastore {self.name}")
1003 return self._read_artifact_into_memory(getInfo, ref, isComponent=getInfo.component is not None)
1005 @transactional
1006 def put(self, inMemoryDataset: Any, ref: DatasetRef) -> None:
1007 """Write a InMemoryDataset with a given `DatasetRef` to the store.
1009 Parameters
1010 ----------
1011 inMemoryDataset : `object`
1012 The dataset to store.
1013 ref : `DatasetRef`
1014 Reference to the associated Dataset.
1016 Raises
1017 ------
1018 TypeError
1019 Supplied object and storage class are inconsistent.
1020 DatasetTypeNotSupportedError
1021 The associated `DatasetType` is not handled by this datastore.
1023 Notes
1024 -----
1025 If the datastore is configured to reject certain dataset types it
1026 is possible that the put will fail and raise a
1027 `DatasetTypeNotSupportedError`. The main use case for this is to
1028 allow `ChainedDatastore` to put to multiple datastores without
1029 requiring that every datastore accepts the dataset.
1030 """
1032 doDisassembly = self.composites.shouldBeDisassembled(ref)
1033 # doDisassembly = True
1035 artifacts = []
1036 if doDisassembly:
1037 components = ref.datasetType.storageClass.assembler().disassemble(inMemoryDataset)
1038 for component, componentInfo in components.items():
1039 compTypeName = ref.datasetType.componentTypeName(component)
1040 # Don't recurse because we want to take advantage of
1041 # bulk insert -- need a new DatasetRef that refers to the
1042 # same dataset_id but has the component DatasetType
1043 # DatasetType does not refer to the types of components
1044 # So we construct one ourselves.
1045 compType = DatasetType(compTypeName, dimensions=ref.datasetType.dimensions,
1046 storageClass=componentInfo.storageClass)
1047 compRef = DatasetRef(compType, ref.dataId, id=ref.id, run=ref.run, conform=False)
1048 storedInfo = self._write_in_memory_to_artifact(componentInfo.component, compRef)
1049 artifacts.append((compRef, storedInfo))
1050 else:
1051 # Write the entire thing out
1052 storedInfo = self._write_in_memory_to_artifact(inMemoryDataset, ref)
1053 artifacts.append((ref, storedInfo))
1055 self._register_datasets(artifacts)
1057 @transactional
1058 def trash(self, ref: DatasetRef, ignore_errors: bool = True) -> None:
1059 """Indicate to the datastore that a dataset can be removed.
1061 Parameters
1062 ----------
1063 ref : `DatasetRef`
1064 Reference to the required Dataset.
1065 ignore_errors : `bool`
1066 If `True` return without error even if something went wrong.
1067 Problems could occur if another process is simultaneously trying
1068 to delete.
1070 Raises
1071 ------
1072 FileNotFoundError
1073 Attempt to remove a dataset that does not exist.
1074 """
1075 # Get file metadata and internal metadata
1076 log.debug("Trashing %s in datastore %s", ref, self.name)
1078 fileLocations = self._get_dataset_locations_info(ref)
1080 if not fileLocations:
1081 err_msg = f"Requested dataset to trash ({ref}) is not known to datastore {self.name}"
1082 if ignore_errors:
1083 log.warning(err_msg)
1084 return
1085 else:
1086 raise FileNotFoundError(err_msg)
1088 for location, storedFileInfo in fileLocations:
1089 if not self._artifact_exists(location): 1089 ↛ 1090line 1089 didn't jump to line 1090, because the condition on line 1089 was never true
1090 err_msg = f"Dataset is known to datastore {self.name} but " \
1091 f"associated artifact ({location.uri}) is missing"
1092 if ignore_errors:
1093 log.warning(err_msg)
1094 return
1095 else:
1096 raise FileNotFoundError(err_msg)
1098 # Mark dataset as trashed
1099 try:
1100 self._move_to_trash_in_registry(ref)
1101 except Exception as e:
1102 if ignore_errors:
1103 log.warning(f"Attempted to mark dataset ({ref}) to be trashed in datastore {self.name} "
1104 f"but encountered an error: {e}")
1105 pass
1106 else:
1107 raise
1109 @transactional
1110 def emptyTrash(self, ignore_errors: bool = True) -> None:
1111 """Remove all datasets from the trash.
1113 Parameters
1114 ----------
1115 ignore_errors : `bool`
1116 If `True` return without error even if something went wrong.
1117 Problems could occur if another process is simultaneously trying
1118 to delete.
1119 """
1120 log.debug("Emptying trash in datastore %s", self.name)
1121 # Context manager will empty trash iff we finish it without raising.
1122 with self._bridge.emptyTrash() as trashed:
1123 for ref in trashed:
1124 fileLocations = self._get_dataset_locations_info(ref)
1126 if not fileLocations: 1126 ↛ 1127line 1126 didn't jump to line 1127, because the condition on line 1126 was never true
1127 err_msg = f"Requested dataset ({ref}) does not exist in datastore {self.name}"
1128 if ignore_errors:
1129 log.warning(err_msg)
1130 continue
1131 else:
1132 raise FileNotFoundError(err_msg)
1134 for location, _ in fileLocations:
1136 if not self._artifact_exists(location): 1136 ↛ 1137line 1136 didn't jump to line 1137, because the condition on line 1136 was never true
1137 err_msg = f"Dataset {location.uri} no longer present in datastore {self.name}"
1138 if ignore_errors:
1139 log.warning(err_msg)
1140 continue
1141 else:
1142 raise FileNotFoundError(err_msg)
1144 # Can only delete the artifact if there are no references
1145 # to the file from untrashed dataset refs.
1146 if self._can_remove_dataset_artifact(ref, location):
1147 # Point of no return for this artifact
1148 log.debug("Removing artifact %s from datastore %s", location.uri, self.name)
1149 try:
1150 self._delete_artifact(location)
1151 except Exception as e:
1152 if ignore_errors:
1153 log.critical("Encountered error removing artifact %s from datastore %s: %s",
1154 location.uri, self.name, e)
1155 else:
1156 raise
1158 # Now must remove the entry from the internal registry even if
1159 # the artifact removal failed and was ignored,
1160 # otherwise the removal check above will never be true
1161 try:
1162 # There may be multiple rows associated with this ref
1163 # depending on disassembly
1164 self.removeStoredItemInfo(ref)
1165 except Exception as e:
1166 if ignore_errors:
1167 log.warning("Error removing dataset %s (%s) from internal registry of %s: %s",
1168 ref.id, location.uri, self.name, e)
1169 continue
1170 else:
1171 raise FileNotFoundError(err_msg)
1173 def validateConfiguration(self, entities: Iterable[Union[DatasetRef, DatasetType, StorageClass]],
1174 logFailures: bool = False) -> None:
1175 """Validate some of the configuration for this datastore.
1177 Parameters
1178 ----------
1179 entities : iterable of `DatasetRef`, `DatasetType`, or `StorageClass`
1180 Entities to test against this configuration. Can be differing
1181 types.
1182 logFailures : `bool`, optional
1183 If `True`, output a log message for every validation error
1184 detected.
1186 Raises
1187 ------
1188 DatastoreValidationError
1189 Raised if there is a validation problem with a configuration.
1190 All the problems are reported in a single exception.
1192 Notes
1193 -----
1194 This method checks that all the supplied entities have valid file
1195 templates and also have formatters defined.
1196 """
1198 templateFailed = None
1199 try:
1200 self.templates.validateTemplates(entities, logFailures=logFailures)
1201 except FileTemplateValidationError as e:
1202 templateFailed = str(e)
1204 formatterFailed = []
1205 for entity in entities:
1206 try:
1207 self.formatterFactory.getFormatterClass(entity)
1208 except KeyError as e:
1209 formatterFailed.append(str(e))
1210 if logFailures: 1210 ↛ 1205line 1210 didn't jump to line 1205, because the condition on line 1210 was never false
1211 log.fatal("Formatter failure: %s", e)
1213 if templateFailed or formatterFailed:
1214 messages = []
1215 if templateFailed: 1215 ↛ 1216line 1215 didn't jump to line 1216, because the condition on line 1215 was never true
1216 messages.append(templateFailed)
1217 if formatterFailed: 1217 ↛ 1219line 1217 didn't jump to line 1219, because the condition on line 1217 was never false
1218 messages.append(",".join(formatterFailed))
1219 msg = ";\n".join(messages)
1220 raise DatastoreValidationError(msg)
1222 def getLookupKeys(self) -> Set[LookupKey]:
1223 # Docstring is inherited from base class
1224 return self.templates.getLookupKeys() | self.formatterFactory.getLookupKeys() | \
1225 self.constraints.getLookupKeys()
1227 def validateKey(self, lookupKey: LookupKey,
1228 entity: Union[DatasetRef, DatasetType, StorageClass]) -> None:
1229 # Docstring is inherited from base class
1230 # The key can be valid in either formatters or templates so we can
1231 # only check the template if it exists
1232 if lookupKey in self.templates:
1233 try:
1234 self.templates[lookupKey].validateTemplate(entity)
1235 except FileTemplateValidationError as e:
1236 raise DatastoreValidationError(e) from e