Coverage for python/lsst/daf/butler/core/datastore.py: 51%
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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/>.
22"""Support for generic data stores."""
24from __future__ import annotations
26__all__ = ("DatastoreConfig", "Datastore", "DatastoreValidationError", "DatasetRefURIs")
28import contextlib
29import dataclasses
30import logging
31from abc import ABCMeta, abstractmethod
32from collections import abc, defaultdict
33from typing import (
34 TYPE_CHECKING,
35 Any,
36 Callable,
37 ClassVar,
38 Dict,
39 Iterable,
40 Iterator,
41 List,
42 Mapping,
43 Optional,
44 Set,
45 Tuple,
46 Type,
47 Union,
48)
50from lsst.utils import doImportType
52from .config import Config, ConfigSubset
53from .constraints import Constraints
54from .exceptions import DatasetTypeNotSupportedError, ValidationError
55from .fileDataset import FileDataset
56from .storageClass import StorageClassFactory
58if TYPE_CHECKING:
59 from lsst.resources import ResourcePath, ResourcePathExpression
61 from ..registry.interfaces import DatasetIdRef, DatastoreRegistryBridgeManager
62 from .configSupport import LookupKey
63 from .datasets import DatasetRef, DatasetType
64 from .datastoreRecordData import DatastoreRecordData
65 from .storageClass import StorageClass
68class DatastoreConfig(ConfigSubset):
69 """Configuration for Datastores."""
71 component = "datastore"
72 requiredKeys = ("cls",)
73 defaultConfigFile = "datastore.yaml"
76class DatastoreValidationError(ValidationError):
77 """There is a problem with the Datastore configuration."""
79 pass
82@dataclasses.dataclass(frozen=True)
83class Event:
84 __slots__ = {"name", "undoFunc", "args", "kwargs"}
85 name: str
86 undoFunc: Callable
87 args: tuple
88 kwargs: dict
91class IngestPrepData:
92 """A helper base class for `Datastore` ingest implementations.
94 Datastore implementations will generally need a custom implementation of
95 this class.
97 Should be accessed as ``Datastore.IngestPrepData`` instead of via direct
98 import.
100 Parameters
101 ----------
102 refs : iterable of `DatasetRef`
103 References for the datasets that can be ingested by this datastore.
104 """
106 def __init__(self, refs: Iterable[DatasetRef]):
107 self.refs = {ref.id: ref for ref in refs}
110class DatastoreTransaction:
111 """Keeps a log of `Datastore` activity and allow rollback.
113 Parameters
114 ----------
115 parent : `DatastoreTransaction`, optional
116 The parent transaction (if any)
117 """
119 Event: ClassVar[Type] = Event
121 parent: Optional[DatastoreTransaction]
122 """The parent transaction. (`DatastoreTransaction`, optional)"""
124 def __init__(self, parent: Optional[DatastoreTransaction] = None):
125 self.parent = parent
126 self._log: List[Event] = []
128 def registerUndo(self, name: str, undoFunc: Callable, *args: Any, **kwargs: Any) -> None:
129 """Register event with undo function.
131 Parameters
132 ----------
133 name : `str`
134 Name of the event.
135 undoFunc : func
136 Function to undo this event.
137 args : `tuple`
138 Positional arguments to `undoFunc`.
139 **kwargs
140 Keyword arguments to `undoFunc`.
141 """
142 self._log.append(self.Event(name, undoFunc, args, kwargs))
144 @contextlib.contextmanager
145 def undoWith(self, name: str, undoFunc: Callable, *args: Any, **kwargs: Any) -> Iterator[None]:
146 """Register undo function if nested operation succeeds.
148 Calls `registerUndo`.
150 This can be used to wrap individual undo-able statements within a
151 DatastoreTransaction block. Multiple statements that can fail
152 separately should not be part of the same `undoWith` block.
154 All arguments are forwarded directly to `registerUndo`.
155 """
156 try:
157 yield None
158 except BaseException:
159 raise
160 else:
161 self.registerUndo(name, undoFunc, *args, **kwargs)
163 def rollback(self) -> None:
164 """Roll back all events in this transaction."""
165 log = logging.getLogger(__name__)
166 while self._log:
167 ev = self._log.pop()
168 try:
169 log.debug(
170 "Rolling back transaction: %s: %s(%s,%s)",
171 ev.name,
172 ev.undoFunc,
173 ",".join(str(a) for a in ev.args),
174 ",".join(f"{k}={v}" for k, v in ev.kwargs.items()),
175 )
176 except Exception:
177 # In case we had a problem in stringification of arguments
178 log.warning("Rolling back transaction: %s", ev.name)
179 try:
180 ev.undoFunc(*ev.args, **ev.kwargs)
181 except BaseException as e:
182 # Deliberately swallow error that may occur in unrolling
183 log.warning("Exception: %s caught while unrolling: %s", e, ev.name)
184 pass
186 def commit(self) -> None:
187 """Commit this transaction."""
188 if self.parent is None:
189 # Just forget about the events, they have already happened.
190 return
191 else:
192 # We may still want to events from this transaction as part of
193 # the parent.
194 self.parent._log.extend(self._log)
197@dataclasses.dataclass
198class DatasetRefURIs(abc.Sequence):
199 """Represents the primary and component ResourcePath(s) associated with a
200 DatasetRef.
202 This is used in places where its members used to be represented as a tuple
203 `(primaryURI, componentURIs)`. To maintain backward compatibility this
204 inherits from Sequence and so instances can be treated as a two-item
205 tuple.
206 """
208 def __init__(
209 self,
210 primaryURI: Optional[ResourcePath] = None,
211 componentURIs: Optional[Dict[str, ResourcePath]] = None,
212 ):
213 self.primaryURI = primaryURI
214 """The URI to the primary artifact associated with this dataset. If the
215 dataset was disassembled within the datastore this may be `None`.
216 """
218 self.componentURIs = componentURIs or {}
219 """The URIs to any components associated with the dataset artifact
220 indexed by component name. This can be empty if there are no
221 components.
222 """
224 def __getitem__(self, index: Any) -> Any:
225 """Get primaryURI and componentURIs by index.
227 Provides support for tuple-like access.
228 """
229 if index == 0:
230 return self.primaryURI
231 elif index == 1:
232 return self.componentURIs
233 raise IndexError("list index out of range")
235 def __len__(self) -> int:
236 """Get the number of data members.
238 Provides support for tuple-like access.
239 """
240 return 2
242 def __repr__(self) -> str:
243 return f"DatasetRefURIs({repr(self.primaryURI)}, {repr(self.componentURIs)})"
246class Datastore(metaclass=ABCMeta):
247 """Datastore interface.
249 Parameters
250 ----------
251 config : `DatastoreConfig` or `str`
252 Load configuration either from an existing config instance or by
253 referring to a configuration file.
254 bridgeManager : `DatastoreRegistryBridgeManager`
255 Object that manages the interface between `Registry` and datastores.
256 butlerRoot : `str`, optional
257 New datastore root to use to override the configuration value.
258 """
260 defaultConfigFile: ClassVar[Optional[str]] = None
261 """Path to configuration defaults. Accessed within the ``config`` resource
262 or relative to a search path. Can be None if no defaults specified.
263 """
265 containerKey: ClassVar[Optional[str]] = None
266 """Name of the key containing a list of subconfigurations that also
267 need to be merged with defaults and will likely use different Python
268 datastore classes (but all using DatastoreConfig). Assumed to be a
269 list of configurations that can be represented in a DatastoreConfig
270 and containing a "cls" definition. None indicates that no containers
271 are expected in this Datastore."""
273 isEphemeral: bool = False
274 """Indicate whether this Datastore is ephemeral or not. An ephemeral
275 datastore is one where the contents of the datastore will not exist
276 across process restarts. This value can change per-instance."""
278 config: DatastoreConfig
279 """Configuration used to create Datastore."""
281 name: str
282 """Label associated with this Datastore."""
284 storageClassFactory: StorageClassFactory
285 """Factory for creating storage class instances from name."""
287 constraints: Constraints
288 """Constraints to apply when putting datasets into the datastore."""
290 # MyPy does not like for this to be annotated as any kind of type, because
291 # it can't do static checking on type variables that can change at runtime.
292 IngestPrepData: ClassVar[Any] = IngestPrepData
293 """Helper base class for ingest implementations.
294 """
296 @classmethod
297 @abstractmethod
298 def setConfigRoot(cls, root: str, config: Config, full: Config, overwrite: bool = True) -> None:
299 """Set filesystem-dependent config options for this datastore.
301 The options will be appropriate for a new empty repository with the
302 given root.
304 Parameters
305 ----------
306 root : `str`
307 Filesystem path to the root of the data repository.
308 config : `Config`
309 A `Config` to update. Only the subset understood by
310 this component will be updated. Will not expand
311 defaults.
312 full : `Config`
313 A complete config with all defaults expanded that can be
314 converted to a `DatastoreConfig`. Read-only and will not be
315 modified by this method.
316 Repository-specific options that should not be obtained
317 from defaults when Butler instances are constructed
318 should be copied from ``full`` to ``config``.
319 overwrite : `bool`, optional
320 If `False`, do not modify a value in ``config`` if the value
321 already exists. Default is always to overwrite with the provided
322 ``root``.
324 Notes
325 -----
326 If a keyword is explicitly defined in the supplied ``config`` it
327 will not be overridden by this method if ``overwrite`` is `False`.
328 This allows explicit values set in external configs to be retained.
329 """
330 raise NotImplementedError()
332 @staticmethod
333 def fromConfig(
334 config: Config,
335 bridgeManager: DatastoreRegistryBridgeManager,
336 butlerRoot: Optional[ResourcePathExpression] = None,
337 ) -> "Datastore":
338 """Create datastore from type specified in config file.
340 Parameters
341 ----------
342 config : `Config`
343 Configuration instance.
344 bridgeManager : `DatastoreRegistryBridgeManager`
345 Object that manages the interface between `Registry` and
346 datastores.
347 butlerRoot : `str`, optional
348 Butler root directory.
349 """
350 cls = doImportType(config["datastore", "cls"])
351 if not issubclass(cls, Datastore):
352 raise TypeError(f"Imported child class {config['datastore', 'cls']} is not a Datastore")
353 return cls(config=config, bridgeManager=bridgeManager, butlerRoot=butlerRoot)
355 def __init__(
356 self,
357 config: Union[Config, str],
358 bridgeManager: DatastoreRegistryBridgeManager,
359 butlerRoot: Optional[ResourcePathExpression] = None,
360 ):
361 self.config = DatastoreConfig(config)
362 self.name = "ABCDataStore"
363 self._transaction: Optional[DatastoreTransaction] = None
365 # All Datastores need storage classes and constraints
366 self.storageClassFactory = StorageClassFactory()
368 # And read the constraints list
369 constraintsConfig = self.config.get("constraints")
370 self.constraints = Constraints(constraintsConfig, universe=bridgeManager.universe)
372 def __str__(self) -> str:
373 return self.name
375 def __repr__(self) -> str:
376 return self.name
378 @property
379 def names(self) -> Tuple[str, ...]:
380 """Names associated with this datastore returned as a list.
382 Can be different to ``name`` for a chaining datastore.
383 """
384 # Default implementation returns solely the name itself
385 return (self.name,)
387 @contextlib.contextmanager
388 def transaction(self) -> Iterator[DatastoreTransaction]:
389 """Context manager supporting `Datastore` transactions.
391 Transactions can be nested, and are to be used in combination with
392 `Registry.transaction`.
393 """
394 self._transaction = DatastoreTransaction(self._transaction)
395 try:
396 yield self._transaction
397 except BaseException:
398 self._transaction.rollback()
399 raise
400 else:
401 self._transaction.commit()
402 self._transaction = self._transaction.parent
404 @abstractmethod
405 def knows(self, ref: DatasetRef) -> bool:
406 """Check if the dataset is known to the datastore.
408 Does not check for existence of any artifact.
410 Parameters
411 ----------
412 ref : `DatasetRef`
413 Reference to the required dataset.
415 Returns
416 -------
417 exists : `bool`
418 `True` if the dataset is known to the datastore.
419 """
420 raise NotImplementedError()
422 def knows_these(self, refs: Iterable[DatasetRef]) -> dict[DatasetRef, bool]:
423 """Check which of the given datasets are known to this datastore.
425 This is like ``mexist()`` but does not check that the file exists.
427 Parameters
428 ----------
429 refs : iterable `DatasetRef`
430 The datasets to check.
432 Returns
433 -------
434 exists : `dict`[`DatasetRef`, `bool`]
435 Mapping of dataset to boolean indicating whether the dataset
436 is known to the datastore.
437 """
438 # Non-optimized default calls knows() repeatedly.
439 return {ref: self.knows(ref) for ref in refs}
441 def mexists(
442 self, refs: Iterable[DatasetRef], artifact_existence: Optional[Dict[ResourcePath, bool]] = None
443 ) -> Dict[DatasetRef, bool]:
444 """Check the existence of multiple datasets at once.
446 Parameters
447 ----------
448 refs : iterable of `DatasetRef`
449 The datasets to be checked.
450 artifact_existence : `dict` [`lsst.resources.ResourcePath`, `bool`]
451 Optional mapping of datastore artifact to existence. Updated by
452 this method with details of all artifacts tested. Can be `None`
453 if the caller is not interested.
455 Returns
456 -------
457 existence : `dict` of [`DatasetRef`, `bool`]
458 Mapping from dataset to boolean indicating existence.
459 """
460 existence: Dict[DatasetRef, bool] = {}
461 # Non-optimized default.
462 for ref in refs:
463 existence[ref] = self.exists(ref)
464 return existence
466 @abstractmethod
467 def exists(self, datasetRef: DatasetRef) -> bool:
468 """Check if the dataset exists in the datastore.
470 Parameters
471 ----------
472 datasetRef : `DatasetRef`
473 Reference to the required dataset.
475 Returns
476 -------
477 exists : `bool`
478 `True` if the entity exists in the `Datastore`.
479 """
480 raise NotImplementedError("Must be implemented by subclass")
482 @abstractmethod
483 def get(
484 self,
485 datasetRef: DatasetRef,
486 parameters: Mapping[str, Any] | None = None,
487 storageClass: Optional[Union[StorageClass, str]] = None,
488 ) -> Any:
489 """Load an `InMemoryDataset` from the store.
491 Parameters
492 ----------
493 datasetRef : `DatasetRef`
494 Reference to the required Dataset.
495 parameters : `dict`
496 `StorageClass`-specific parameters that specify a slice of the
497 Dataset to be loaded.
498 storageClass : `StorageClass` or `str`, optional
499 The storage class to be used to override the Python type
500 returned by this method. By default the returned type matches
501 the dataset type definition for this dataset. Specifying a
502 read `StorageClass` can force a different type to be returned.
503 This type must be compatible with the original type.
505 Returns
506 -------
507 inMemoryDataset : `object`
508 Requested Dataset or slice thereof as an InMemoryDataset.
509 """
510 raise NotImplementedError("Must be implemented by subclass")
512 @abstractmethod
513 def put(self, inMemoryDataset: Any, datasetRef: DatasetRef) -> None:
514 """Write a `InMemoryDataset` with a given `DatasetRef` to the store.
516 Parameters
517 ----------
518 inMemoryDataset : `object`
519 The Dataset to store.
520 datasetRef : `DatasetRef`
521 Reference to the associated Dataset.
522 """
523 raise NotImplementedError("Must be implemented by subclass")
525 def _overrideTransferMode(self, *datasets: FileDataset, transfer: Optional[str] = None) -> Optional[str]:
526 """Allow ingest transfer mode to be defaulted based on datasets.
528 Parameters
529 ----------
530 datasets : `FileDataset`
531 Each positional argument is a struct containing information about
532 a file to be ingested, including its path (either absolute or
533 relative to the datastore root, if applicable), a complete
534 `DatasetRef` (with ``dataset_id not None``), and optionally a
535 formatter class or its fully-qualified string name. If a formatter
536 is not provided, this method should populate that attribute with
537 the formatter the datastore would use for `put`. Subclasses are
538 also permitted to modify the path attribute (typically to put it
539 in what the datastore considers its standard form).
540 transfer : `str`, optional
541 How (and whether) the dataset should be added to the datastore.
542 See `ingest` for details of transfer modes.
544 Returns
545 -------
546 newTransfer : `str`
547 Transfer mode to use. Will be identical to the supplied transfer
548 mode unless "auto" is used.
549 """
550 if transfer != "auto":
551 return transfer
552 raise RuntimeError(f"{transfer} is not allowed without specialization.")
554 def _prepIngest(self, *datasets: FileDataset, transfer: Optional[str] = None) -> IngestPrepData:
555 """Process datasets to identify which ones can be ingested.
557 Parameters
558 ----------
559 datasets : `FileDataset`
560 Each positional argument is a struct containing information about
561 a file to be ingested, including its path (either absolute or
562 relative to the datastore root, if applicable), a complete
563 `DatasetRef` (with ``dataset_id not None``), and optionally a
564 formatter class or its fully-qualified string name. If a formatter
565 is not provided, this method should populate that attribute with
566 the formatter the datastore would use for `put`. Subclasses are
567 also permitted to modify the path attribute (typically to put it
568 in what the datastore considers its standard form).
569 transfer : `str`, optional
570 How (and whether) the dataset should be added to the datastore.
571 See `ingest` for details of transfer modes.
573 Returns
574 -------
575 data : `IngestPrepData`
576 An instance of a subclass of `IngestPrepData`, used to pass
577 arbitrary data from `_prepIngest` to `_finishIngest`. This should
578 include only the datasets this datastore can actually ingest;
579 others should be silently ignored (`Datastore.ingest` will inspect
580 `IngestPrepData.refs` and raise `DatasetTypeNotSupportedError` if
581 necessary).
583 Raises
584 ------
585 NotImplementedError
586 Raised if the datastore does not support the given transfer mode
587 (including the case where ingest is not supported at all).
588 FileNotFoundError
589 Raised if one of the given files does not exist.
590 FileExistsError
591 Raised if transfer is not `None` but the (internal) location the
592 file would be moved to is already occupied.
594 Notes
595 -----
596 This method (along with `_finishIngest`) should be implemented by
597 subclasses to provide ingest support instead of implementing `ingest`
598 directly.
600 `_prepIngest` should not modify the data repository or given files in
601 any way; all changes should be deferred to `_finishIngest`.
603 When possible, exceptions should be raised in `_prepIngest` instead of
604 `_finishIngest`. `NotImplementedError` exceptions that indicate that
605 the transfer mode is not supported must be raised by `_prepIngest`
606 instead of `_finishIngest`.
607 """
608 raise NotImplementedError(f"Datastore {self} does not support direct file-based ingest.")
610 def _finishIngest(
611 self, prepData: IngestPrepData, *, transfer: Optional[str] = None, record_validation_info: bool = True
612 ) -> None:
613 """Complete an ingest operation.
615 Parameters
616 ----------
617 data : `IngestPrepData`
618 An instance of a subclass of `IngestPrepData`. Guaranteed to be
619 the direct result of a call to `_prepIngest` on this datastore.
620 transfer : `str`, optional
621 How (and whether) the dataset should be added to the datastore.
622 See `ingest` for details of transfer modes.
623 record_validation_info : `bool`, optional
624 If `True`, the default, the datastore can record validation
625 information associated with the file. If `False` the datastore
626 will not attempt to track any information such as checksums
627 or file sizes. This can be useful if such information is tracked
628 in an external system or if the file is to be compressed in place.
629 It is up to the datastore whether this parameter is relevant.
631 Raises
632 ------
633 FileNotFoundError
634 Raised if one of the given files does not exist.
635 FileExistsError
636 Raised if transfer is not `None` but the (internal) location the
637 file would be moved to is already occupied.
639 Notes
640 -----
641 This method (along with `_prepIngest`) should be implemented by
642 subclasses to provide ingest support instead of implementing `ingest`
643 directly.
644 """
645 raise NotImplementedError(f"Datastore {self} does not support direct file-based ingest.")
647 def ingest(
648 self, *datasets: FileDataset, transfer: Optional[str] = None, record_validation_info: bool = True
649 ) -> None:
650 """Ingest one or more files into the datastore.
652 Parameters
653 ----------
654 datasets : `FileDataset`
655 Each positional argument is a struct containing information about
656 a file to be ingested, including its path (either absolute or
657 relative to the datastore root, if applicable), a complete
658 `DatasetRef` (with ``dataset_id not None``), and optionally a
659 formatter class or its fully-qualified string name. If a formatter
660 is not provided, the one the datastore would use for ``put`` on
661 that dataset is assumed.
662 transfer : `str`, optional
663 How (and whether) the dataset should be added to the datastore.
664 If `None` (default), the file must already be in a location
665 appropriate for the datastore (e.g. within its root directory),
666 and will not be modified. Other choices include "move", "copy",
667 "link", "symlink", "relsymlink", and "hardlink". "link" is a
668 special transfer mode that will first try to make a hardlink and
669 if that fails a symlink will be used instead. "relsymlink" creates
670 a relative symlink rather than use an absolute path.
671 Most datastores do not support all transfer modes.
672 "auto" is a special option that will let the
673 data store choose the most natural option for itself.
674 record_validation_info : `bool`, optional
675 If `True`, the default, the datastore can record validation
676 information associated with the file. If `False` the datastore
677 will not attempt to track any information such as checksums
678 or file sizes. This can be useful if such information is tracked
679 in an external system or if the file is to be compressed in place.
680 It is up to the datastore whether this parameter is relevant.
682 Raises
683 ------
684 NotImplementedError
685 Raised if the datastore does not support the given transfer mode
686 (including the case where ingest is not supported at all).
687 DatasetTypeNotSupportedError
688 Raised if one or more files to be ingested have a dataset type that
689 is not supported by the datastore.
690 FileNotFoundError
691 Raised if one of the given files does not exist.
692 FileExistsError
693 Raised if transfer is not `None` but the (internal) location the
694 file would be moved to is already occupied.
696 Notes
697 -----
698 Subclasses should implement `_prepIngest` and `_finishIngest` instead
699 of implementing `ingest` directly. Datastores that hold and
700 delegate to child datastores may want to call those methods as well.
702 Subclasses are encouraged to document their supported transfer modes
703 in their class documentation.
704 """
705 # Allow a datastore to select a default transfer mode
706 transfer = self._overrideTransferMode(*datasets, transfer=transfer)
707 prepData = self._prepIngest(*datasets, transfer=transfer)
708 refs = {ref.id: ref for dataset in datasets for ref in dataset.refs}
709 if refs.keys() != prepData.refs.keys():
710 unsupported = refs.keys() - prepData.refs.keys()
711 # Group unsupported refs by DatasetType for an informative
712 # but still concise error message.
713 byDatasetType = defaultdict(list)
714 for datasetId in unsupported:
715 ref = refs[datasetId]
716 byDatasetType[ref.datasetType].append(ref)
717 raise DatasetTypeNotSupportedError(
718 "DatasetType(s) not supported in ingest: "
719 + ", ".join(f"{k.name} ({len(v)} dataset(s))" for k, v in byDatasetType.items())
720 )
721 self._finishIngest(prepData, transfer=transfer, record_validation_info=record_validation_info)
723 def transfer_from(
724 self,
725 source_datastore: Datastore,
726 refs: Iterable[DatasetRef],
727 transfer: str = "auto",
728 artifact_existence: Optional[Dict[ResourcePath, bool]] = None,
729 ) -> tuple[set[DatasetRef], set[DatasetRef]]:
730 """Transfer dataset artifacts from another datastore to this one.
732 Parameters
733 ----------
734 source_datastore : `Datastore`
735 The datastore from which to transfer artifacts. That datastore
736 must be compatible with this datastore receiving the artifacts.
737 refs : iterable of `DatasetRef`
738 The datasets to transfer from the source datastore.
739 transfer : `str`, optional
740 How (and whether) the dataset should be added to the datastore.
741 Choices include "move", "copy",
742 "link", "symlink", "relsymlink", and "hardlink". "link" is a
743 special transfer mode that will first try to make a hardlink and
744 if that fails a symlink will be used instead. "relsymlink" creates
745 a relative symlink rather than use an absolute path.
746 Most datastores do not support all transfer modes.
747 "auto" (the default) is a special option that will let the
748 data store choose the most natural option for itself.
749 If the source location and transfer location are identical the
750 transfer mode will be ignored.
751 artifact_existence : `dict` [`lsst.resources.ResourcePath`, `bool`]
752 Optional mapping of datastore artifact to existence. Updated by
753 this method with details of all artifacts tested. Can be `None`
754 if the caller is not interested.
756 Returns
757 -------
758 accepted : `set` [`DatasetRef`]
759 The datasets that were transferred.
760 rejected : `set` [`DatasetRef`]
761 The datasets that were rejected due to a constraints violation.
763 Raises
764 ------
765 TypeError
766 Raised if the two datastores are not compatible.
767 """
768 if type(self) is not type(source_datastore):
769 raise TypeError(
770 f"Datastore mismatch between this datastore ({type(self)}) and the "
771 f"source datastore ({type(source_datastore)})."
772 )
774 raise NotImplementedError(f"Datastore {type(self)} must implement a transfer_from method.")
776 def getManyURIs(
777 self,
778 refs: Iterable[DatasetRef],
779 predict: bool = False,
780 allow_missing: bool = False,
781 ) -> Dict[DatasetRef, DatasetRefURIs]:
782 """Return URIs associated with many datasets.
784 Parameters
785 ----------
786 refs : iterable of `DatasetIdRef`
787 References to the required datasets.
788 predict : `bool`, optional
789 If the datastore does not know about a dataset, should it
790 return a predicted URI or not?
791 allow_missing : `bool`
792 If `False`, and `predict` is `False`, will raise if a `DatasetRef`
793 does not exist.
795 Returns
796 -------
797 URIs : `dict` of [`DatasetRef`, `DatasetRefUris`]
798 A dict of primary and component URIs, indexed by the passed-in
799 refs.
801 Raises
802 ------
803 FileNotFoundError
804 A URI has been requested for a dataset that does not exist and
805 guessing is not allowed.
807 Notes
808 -----
809 In file-based datastores, getManuURIs does not check that the file is
810 really there, it's assuming it is if datastore is aware of the file
811 then it actually exists.
812 """
813 uris: Dict[DatasetRef, DatasetRefURIs] = {}
814 missing_refs = []
815 for ref in refs:
816 try:
817 uris[ref] = self.getURIs(ref, predict=predict)
818 except FileNotFoundError:
819 missing_refs.append(ref)
820 if missing_refs and not allow_missing:
821 raise FileNotFoundError(
822 "Missing {} refs from datastore out of {} and predict=False.".format(
823 num_missing := len(missing_refs), num_missing + len(uris)
824 )
825 )
826 return uris
828 @abstractmethod
829 def getURIs(self, datasetRef: DatasetRef, predict: bool = False) -> DatasetRefURIs:
830 """Return URIs associated with dataset.
832 Parameters
833 ----------
834 ref : `DatasetRef`
835 Reference to the required dataset.
836 predict : `bool`, optional
837 If the datastore does not know about the dataset, should it
838 return a predicted URI or not?
840 Returns
841 -------
842 uris : `DatasetRefURIs`
843 The URI to the primary artifact associated with this dataset (if
844 the dataset was disassembled within the datastore this may be
845 `None`), and the URIs to any components associated with the dataset
846 artifact. (can be empty if there are no components).
847 """
848 raise NotImplementedError()
850 @abstractmethod
851 def getURI(self, datasetRef: DatasetRef, predict: bool = False) -> ResourcePath:
852 """URI to the Dataset.
854 Parameters
855 ----------
856 datasetRef : `DatasetRef`
857 Reference to the required Dataset.
858 predict : `bool`
859 If `True` attempt to predict the URI for a dataset if it does
860 not exist in datastore.
862 Returns
863 -------
864 uri : `str`
865 URI string pointing to the Dataset within the datastore. If the
866 Dataset does not exist in the datastore, the URI may be a guess.
867 If the datastore does not have entities that relate well
868 to the concept of a URI the returned URI string will be
869 descriptive. The returned URI is not guaranteed to be obtainable.
871 Raises
872 ------
873 FileNotFoundError
874 A URI has been requested for a dataset that does not exist and
875 guessing is not allowed.
876 """
877 raise NotImplementedError("Must be implemented by subclass")
879 @abstractmethod
880 def retrieveArtifacts(
881 self,
882 refs: Iterable[DatasetRef],
883 destination: ResourcePath,
884 transfer: str = "auto",
885 preserve_path: bool = True,
886 overwrite: bool = False,
887 ) -> List[ResourcePath]:
888 """Retrieve the artifacts associated with the supplied refs.
890 Parameters
891 ----------
892 refs : iterable of `DatasetRef`
893 The datasets for which artifacts are to be retrieved.
894 A single ref can result in multiple artifacts. The refs must
895 be resolved.
896 destination : `lsst.resources.ResourcePath`
897 Location to write the artifacts.
898 transfer : `str`, optional
899 Method to use to transfer the artifacts. Must be one of the options
900 supported by `lsst.resources.ResourcePath.transfer_from()`.
901 "move" is not allowed.
902 preserve_path : `bool`, optional
903 If `True` the full path of the artifact within the datastore
904 is preserved. If `False` the final file component of the path
905 is used.
906 overwrite : `bool`, optional
907 If `True` allow transfers to overwrite existing files at the
908 destination.
910 Returns
911 -------
912 targets : `list` of `lsst.resources.ResourcePath`
913 URIs of file artifacts in destination location. Order is not
914 preserved.
916 Notes
917 -----
918 For non-file datastores the artifacts written to the destination
919 may not match the representation inside the datastore. For example
920 a hierarchichal data structure in a NoSQL database may well be stored
921 as a JSON file.
922 """
923 raise NotImplementedError()
925 @abstractmethod
926 def remove(self, datasetRef: DatasetRef) -> None:
927 """Indicate to the Datastore that a Dataset can be removed.
929 Parameters
930 ----------
931 datasetRef : `DatasetRef`
932 Reference to the required Dataset.
934 Raises
935 ------
936 FileNotFoundError
937 When Dataset does not exist.
939 Notes
940 -----
941 Some Datastores may implement this method as a silent no-op to
942 disable Dataset deletion through standard interfaces.
943 """
944 raise NotImplementedError("Must be implemented by subclass")
946 @abstractmethod
947 def forget(self, refs: Iterable[DatasetRef]) -> None:
948 """Indicate to the Datastore that it should remove all records of the
949 given datasets, without actually deleting them.
951 Parameters
952 ----------
953 refs : `Iterable` [ `DatasetRef` ]
954 References to the datasets being forgotten.
956 Notes
957 -----
958 Asking a datastore to forget a `DatasetRef` it does not hold should be
959 a silent no-op, not an error.
960 """
961 raise NotImplementedError("Must be implemented by subclass")
963 @abstractmethod
964 def trash(self, ref: Union[DatasetRef, Iterable[DatasetRef]], ignore_errors: bool = True) -> None:
965 """Indicate to the Datastore that a Dataset can be moved to the trash.
967 Parameters
968 ----------
969 ref : `DatasetRef` or iterable thereof
970 Reference(s) to the required Dataset.
971 ignore_errors : `bool`, optional
972 Determine whether errors should be ignored. When multiple
973 refs are being trashed there will be no per-ref check.
975 Raises
976 ------
977 FileNotFoundError
978 When Dataset does not exist and errors are not ignored. Only
979 checked if a single ref is supplied (and not in a list).
981 Notes
982 -----
983 Some Datastores may implement this method as a silent no-op to
984 disable Dataset deletion through standard interfaces.
985 """
986 raise NotImplementedError("Must be implemented by subclass")
988 @abstractmethod
989 def emptyTrash(self, ignore_errors: bool = True) -> None:
990 """Remove all datasets from the trash.
992 Parameters
993 ----------
994 ignore_errors : `bool`, optional
995 Determine whether errors should be ignored.
997 Notes
998 -----
999 Some Datastores may implement this method as a silent no-op to
1000 disable Dataset deletion through standard interfaces.
1001 """
1002 raise NotImplementedError("Must be implemented by subclass")
1004 @abstractmethod
1005 def transfer(self, inputDatastore: Datastore, datasetRef: DatasetRef) -> None:
1006 """Transfer a dataset from another datastore to this datastore.
1008 Parameters
1009 ----------
1010 inputDatastore : `Datastore`
1011 The external `Datastore` from which to retrieve the Dataset.
1012 datasetRef : `DatasetRef`
1013 Reference to the required Dataset.
1014 """
1015 raise NotImplementedError("Must be implemented by subclass")
1017 def export(
1018 self,
1019 refs: Iterable[DatasetRef],
1020 *,
1021 directory: Optional[ResourcePathExpression] = None,
1022 transfer: Optional[str] = "auto",
1023 ) -> Iterable[FileDataset]:
1024 """Export datasets for transfer to another data repository.
1026 Parameters
1027 ----------
1028 refs : iterable of `DatasetRef`
1029 Dataset references to be exported.
1030 directory : `str`, optional
1031 Path to a directory that should contain files corresponding to
1032 output datasets. Ignored if ``transfer`` is explicitly `None`.
1033 transfer : `str`, optional
1034 Mode that should be used to move datasets out of the repository.
1035 Valid options are the same as those of the ``transfer`` argument
1036 to ``ingest``, and datastores may similarly signal that a transfer
1037 mode is not supported by raising `NotImplementedError`. If "auto"
1038 is given and no ``directory`` is specified, `None` will be
1039 implied.
1041 Returns
1042 -------
1043 dataset : iterable of `DatasetTransfer`
1044 Structs containing information about the exported datasets, in the
1045 same order as ``refs``.
1047 Raises
1048 ------
1049 NotImplementedError
1050 Raised if the given transfer mode is not supported.
1051 """
1052 raise NotImplementedError(f"Transfer mode {transfer} not supported.")
1054 @abstractmethod
1055 def validateConfiguration(
1056 self, entities: Iterable[Union[DatasetRef, DatasetType, StorageClass]], logFailures: bool = False
1057 ) -> None:
1058 """Validate some of the configuration for this datastore.
1060 Parameters
1061 ----------
1062 entities : iterable of `DatasetRef`, `DatasetType`, or `StorageClass`
1063 Entities to test against this configuration. Can be differing
1064 types.
1065 logFailures : `bool`, optional
1066 If `True`, output a log message for every validation error
1067 detected.
1069 Raises
1070 ------
1071 DatastoreValidationError
1072 Raised if there is a validation problem with a configuration.
1074 Notes
1075 -----
1076 Which parts of the configuration are validated is at the discretion
1077 of each Datastore implementation.
1078 """
1079 raise NotImplementedError("Must be implemented by subclass")
1081 @abstractmethod
1082 def validateKey(self, lookupKey: LookupKey, entity: Union[DatasetRef, DatasetType, StorageClass]) -> None:
1083 """Validate a specific look up key with supplied entity.
1085 Parameters
1086 ----------
1087 lookupKey : `LookupKey`
1088 Key to use to retrieve information from the datastore
1089 configuration.
1090 entity : `DatasetRef`, `DatasetType`, or `StorageClass`
1091 Entity to compare with configuration retrieved using the
1092 specified lookup key.
1094 Raises
1095 ------
1096 DatastoreValidationError
1097 Raised if there is a problem with the combination of entity
1098 and lookup key.
1100 Notes
1101 -----
1102 Bypasses the normal selection priorities by allowing a key that
1103 would normally not be selected to be validated.
1104 """
1105 raise NotImplementedError("Must be implemented by subclass")
1107 @abstractmethod
1108 def getLookupKeys(self) -> Set[LookupKey]:
1109 """Return all the lookup keys relevant to this datastore.
1111 Returns
1112 -------
1113 keys : `set` of `LookupKey`
1114 The keys stored internally for looking up information based
1115 on `DatasetType` name or `StorageClass`.
1116 """
1117 raise NotImplementedError("Must be implemented by subclass")
1119 def needs_expanded_data_ids(
1120 self,
1121 transfer: Optional[str],
1122 entity: Optional[Union[DatasetRef, DatasetType, StorageClass]] = None,
1123 ) -> bool:
1124 """Test whether this datastore needs expanded data IDs to ingest.
1126 Parameters
1127 ----------
1128 transfer : `str` or `None`
1129 Transfer mode for ingest.
1130 entity, optional
1131 Object representing what will be ingested. If not provided (or not
1132 specific enough), `True` may be returned even if expanded data
1133 IDs aren't necessary.
1135 Returns
1136 -------
1137 needed : `bool`
1138 If `True`, expanded data IDs may be needed. `False` only if
1139 expansion definitely isn't necessary.
1140 """
1141 return True
1143 @abstractmethod
1144 def import_records(
1145 self,
1146 data: Mapping[str, DatastoreRecordData],
1147 ) -> None:
1148 """Import datastore location and record data from an in-memory data
1149 structure.
1151 Parameters
1152 ----------
1153 data : `Mapping` [ `str`, `DatastoreRecordData` ]
1154 Datastore records indexed by datastore name. May contain data for
1155 other `Datastore` instances (generally because they are chained to
1156 this one), which should be ignored.
1158 Notes
1159 -----
1160 Implementations should generally not check that any external resources
1161 (e.g. files) referred to by these records actually exist, for
1162 performance reasons; we expect higher-level code to guarantee that they
1163 do.
1165 Implementations are responsible for calling
1166 `DatastoreRegistryBridge.insert` on all datasets in ``data.locations``
1167 where the key is in `names`, as well as loading any opaque table data.
1168 """
1169 raise NotImplementedError()
1171 @abstractmethod
1172 def export_records(
1173 self,
1174 refs: Iterable[DatasetIdRef],
1175 ) -> Mapping[str, DatastoreRecordData]:
1176 """Export datastore records and locations to an in-memory data
1177 structure.
1179 Parameters
1180 ----------
1181 refs : `Iterable` [ `DatasetIdRef` ]
1182 Datasets to save. This may include datasets not known to this
1183 datastore, which should be ignored.
1185 Returns
1186 -------
1187 data : `Mapping` [ `str`, `DatastoreRecordData` ]
1188 Exported datastore records indexed by datastore name.
1189 """
1190 raise NotImplementedError()
1192 def set_retrieve_dataset_type_method(self, method: Callable[[str], DatasetType | None] | None) -> None:
1193 """Specify a method that can be used by datastore to retrieve
1194 registry-defined dataset type.
1196 Parameters
1197 ----------
1198 method : `~collections.abc.Callable` | `None`
1199 Method that takes a name of the dataset type and returns a
1200 corresponding `DatasetType` instance as defined in Registry. If
1201 dataset type name is not known to registry `None` is returned.
1203 Notes
1204 -----
1205 This method is only needed for a Datastore supporting a "trusted" mode
1206 when it does not have an access to datastore records and needs to
1207 guess dataset location based on its stored dataset type.
1208 """
1209 pass