Coverage for python / lsst / daf / butler / datastore / _datastore.py: 57%
285 statements
« prev ^ index » next coverage.py v7.13.1, created at 2026-01-22 01:49 -0800
« prev ^ index » next coverage.py v7.13.1, created at 2026-01-22 01:49 -0800
1# This file is part of daf_butler.
2#
3# Developed for the LSST Data Management System.
4# This product includes software developed by the LSST Project
5# (http://www.lsst.org).
6# See the COPYRIGHT file at the top-level directory of this distribution
7# for details of code ownership.
8#
9# This software is dual licensed under the GNU General Public License and also
10# under a 3-clause BSD license. Recipients may choose which of these licenses
11# to use; please see the files gpl-3.0.txt and/or bsd_license.txt,
12# respectively. If you choose the GPL option then the following text applies
13# (but note that there is still no warranty even if you opt for BSD instead):
14#
15# This program is free software: you can redistribute it and/or modify
16# it under the terms of the GNU General Public License as published by
17# the Free Software Foundation, either version 3 of the License, or
18# (at your option) any later version.
19#
20# This program is distributed in the hope that it will be useful,
21# but WITHOUT ANY WARRANTY; without even the implied warranty of
22# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
23# GNU General Public License for more details.
24#
25# You should have received a copy of the GNU General Public License
26# along with this program. If not, see <http://www.gnu.org/licenses/>.
28"""Support for generic data stores."""
30from __future__ import annotations
32__all__ = (
33 "DatasetRefURIs",
34 "Datastore",
35 "DatastoreConfig",
36 "DatastoreOpaqueTable",
37 "DatastoreTransaction",
38 "DatastoreValidationError",
39 "NullDatastore",
40)
42import contextlib
43import dataclasses
44import logging
45import time
46from abc import ABCMeta, abstractmethod
47from collections import abc, defaultdict
48from collections.abc import Callable, Collection, Iterable, Iterator, Mapping
49from typing import TYPE_CHECKING, Any, ClassVar
51from lsst.utils import doImportType
53from .._config import Config, ConfigSubset
54from .._exceptions import DatasetTypeNotSupportedError, ValidationError
55from .._file_dataset import FileDataset
56from .._storage_class import StorageClassFactory
57from ._transfer import FileTransferMap, FileTransferSource
58from .constraints import Constraints
60if TYPE_CHECKING:
61 from lsst.resources import ResourcePath, ResourcePathExpression
63 from .. import ddl
64 from .._config_support import LookupKey
65 from .._dataset_provenance import DatasetProvenance
66 from .._dataset_ref import DatasetId, DatasetRef
67 from .._dataset_type import DatasetType
68 from .._storage_class import StorageClass
69 from ..datastores.file_datastore.get import DatasetLocationInformation
70 from ..datastores.file_datastore.retrieve_artifacts import ArtifactIndexInfo
71 from ..registry.interfaces import DatasetIdRef, DatastoreRegistryBridgeManager
72 from .record_data import DatastoreRecordData
73 from .stored_file_info import StoredDatastoreItemInfo
75_LOG = logging.getLogger(__name__)
78class DatastoreConfig(ConfigSubset):
79 """Configuration for Datastores."""
81 component = "datastore"
82 requiredKeys = ("cls",)
83 defaultConfigFile = "datastore.yaml"
86class DatastoreValidationError(ValidationError):
87 """There is a problem with the Datastore configuration."""
89 pass
92@dataclasses.dataclass(frozen=True)
93class Event:
94 """Representation of an event that can be rolled back."""
96 __slots__ = {"name", "undoFunc", "args", "kwargs"}
97 name: str
98 undoFunc: Callable
99 args: tuple
100 kwargs: dict
103@dataclasses.dataclass(frozen=True)
104class DatastoreOpaqueTable:
105 """Definition of the opaque table which stores datastore records.
107 Table definition contains `.ddl.TableSpec` for a table and a class
108 of a record which must be a subclass of `StoredDatastoreItemInfo`.
109 """
111 __slots__ = {"table_spec", "record_class"}
112 table_spec: ddl.TableSpec
113 record_class: type[StoredDatastoreItemInfo]
116class IngestPrepData:
117 """A helper base class for `Datastore` ingest implementations.
119 Datastore implementations will generally need a custom implementation of
120 this class.
122 Should be accessed as ``Datastore.IngestPrepData`` instead of via direct
123 import.
125 Parameters
126 ----------
127 refs : iterable of `DatasetRef`
128 References for the datasets that can be ingested by this datastore.
129 """
131 def __init__(self, refs: Iterable[DatasetRef]):
132 self.refs = {ref.id: ref for ref in refs}
135class DatastoreTransaction:
136 """Keeps a log of `Datastore` activity and allow rollback.
138 Parameters
139 ----------
140 parent : `DatastoreTransaction`, optional
141 The parent transaction (if any).
143 Notes
144 -----
145 This transaction object must be thread safe.
146 """
148 Event: ClassVar[type] = Event
150 parent: DatastoreTransaction | None
151 """The parent transaction. (`DatastoreTransaction`, optional)"""
153 def __init__(self, parent: DatastoreTransaction | None = None):
154 self.parent = parent
155 self._log: list[Event] = []
157 def registerUndo(self, name: str, undoFunc: Callable, *args: Any, **kwargs: Any) -> None:
158 """Register event with undo function.
160 Parameters
161 ----------
162 name : `str`
163 Name of the event.
164 undoFunc : `~collections.abc.Callable`
165 Function to undo this event.
166 *args : `tuple`
167 Positional arguments to ``undoFunc``.
168 **kwargs
169 Keyword arguments to ``undoFunc``.
170 """
171 self._log.append(self.Event(name, undoFunc, args, kwargs))
173 @contextlib.contextmanager
174 def undoWith(self, name: str, undoFunc: Callable, *args: Any, **kwargs: Any) -> Iterator[None]:
175 """Register undo function if nested operation succeeds.
177 Calls `registerUndo`.
179 This can be used to wrap individual undo-able statements within a
180 DatastoreTransaction block. Multiple statements that can fail
181 separately should not be part of the same `undoWith` block.
183 All arguments are forwarded directly to `registerUndo`.
185 Parameters
186 ----------
187 name : `str`
188 The name to associate with this event.
189 undoFunc : `~collections.abc.Callable`
190 Function to undo this event.
191 *args : `tuple`
192 Positional arguments for ``undoFunc``.
193 **kwargs : `typing.Any`
194 Keyword arguments for ``undoFunc``.
195 """
196 try:
197 yield None
198 except BaseException:
199 raise
200 else:
201 self.registerUndo(name, undoFunc, *args, **kwargs)
203 def rollback(self) -> None:
204 """Roll back all events in this transaction."""
205 log = logging.getLogger(__name__)
206 while self._log:
207 ev = self._log.pop()
208 try:
209 log.debug(
210 "Rolling back transaction: %s: %s(%s,%s)",
211 ev.name,
212 ev.undoFunc,
213 ",".join(str(a) for a in ev.args),
214 ",".join(f"{k}={v}" for k, v in ev.kwargs.items()),
215 )
216 except Exception:
217 # In case we had a problem in stringification of arguments
218 log.warning("Rolling back transaction: %s", ev.name)
219 try:
220 ev.undoFunc(*ev.args, **ev.kwargs)
221 except BaseException as e:
222 # Deliberately swallow error that may occur in unrolling
223 log.warning("Exception: %s caught while unrolling: %s", e, ev.name)
224 pass
226 def commit(self) -> None:
227 """Commit this transaction."""
228 if self.parent is None:
229 # Just forget about the events, they have already happened.
230 return
231 else:
232 # We may still want to events from this transaction as part of
233 # the parent.
234 self.parent._log.extend(self._log)
237@dataclasses.dataclass
238class DatasetRefURIs(abc.Sequence):
239 """Represents the primary and component ResourcePath(s) associated with a
240 DatasetRef.
242 This is used in places where its members used to be represented as a tuple
243 `(primaryURI, componentURIs)`. To maintain backward compatibility this
244 inherits from Sequence and so instances can be treated as a two-item
245 tuple.
247 Parameters
248 ----------
249 primaryURI : `lsst.resources.ResourcePath` or `None`, optional
250 The URI to the primary artifact associated with this dataset. If the
251 dataset was disassembled within the datastore this may be `None`.
252 componentURIs : `dict` [`str`, `~lsst.resources.ResourcePath`] or `None`
253 The URIs to any components associated with the dataset artifact
254 indexed by component name. This can be empty if there are no
255 components.
256 """
258 def __init__(
259 self,
260 primaryURI: ResourcePath | None = None,
261 componentURIs: dict[str, ResourcePath] | None = None,
262 ):
263 self.primaryURI = primaryURI
264 self.componentURIs = componentURIs or {}
266 def __getitem__(self, index: Any) -> Any:
267 """Get primaryURI and componentURIs by index.
269 Provides support for tuple-like access.
270 """
271 if index == 0:
272 return self.primaryURI
273 elif index == 1:
274 return self.componentURIs
275 raise IndexError("list index out of range")
277 def __len__(self) -> int:
278 """Get the number of data members.
280 Provides support for tuple-like access.
281 """
282 return 2
284 def __repr__(self) -> str:
285 return f"DatasetRefURIs({repr(self.primaryURI)}, {repr(self.componentURIs)})"
287 def iter_all(self) -> Iterator[ResourcePath]:
288 """Iterate over all URIs without regard to whether they are primary
289 or component.
290 """
291 if self.primaryURI is not None:
292 yield self.primaryURI
293 yield from self.componentURIs.values()
296class Datastore(FileTransferSource, metaclass=ABCMeta):
297 """Datastore interface.
299 Parameters
300 ----------
301 config : `DatastoreConfig` or `str`
302 Load configuration either from an existing config instance or by
303 referring to a configuration file.
304 bridgeManager : `DatastoreRegistryBridgeManager`
305 Object that manages the interface between `Registry` and datastores.
307 See Also
308 --------
309 lsst.daf.butler.Butler
310 """
312 defaultConfigFile: ClassVar[str | None] = None
313 """Path to configuration defaults. Accessed within the ``config`` resource
314 or relative to a search path. Can be None if no defaults specified.
315 """
317 containerKey: ClassVar[str | None] = None
318 """Name of the key containing a list of subconfigurations that also
319 need to be merged with defaults and will likely use different Python
320 datastore classes (but all using DatastoreConfig). Assumed to be a
321 list of configurations that can be represented in a DatastoreConfig
322 and containing a "cls" definition. None indicates that no containers
323 are expected in this Datastore."""
325 isEphemeral: bool = False
326 """Indicate whether this Datastore is ephemeral or not. An ephemeral
327 datastore is one where the contents of the datastore will not exist
328 across process restarts. This value can change per-instance."""
330 config: DatastoreConfig
331 """Configuration used to create Datastore."""
333 name: str
334 """Label associated with this Datastore."""
336 storageClassFactory: StorageClassFactory
337 """Factory for creating storage class instances from name."""
339 constraints: Constraints
340 """Constraints to apply when putting datasets into the datastore."""
342 # MyPy does not like for this to be annotated as any kind of type, because
343 # it can't do static checking on type variables that can change at runtime.
344 IngestPrepData: ClassVar[Any] = IngestPrepData
345 """Helper base class for ingest implementations.
346 """
348 @classmethod
349 @abstractmethod
350 def setConfigRoot(cls, root: str, config: Config, full: Config, overwrite: bool = True) -> None:
351 """Set filesystem-dependent config options for this datastore.
353 The options will be appropriate for a new empty repository with the
354 given root.
356 Parameters
357 ----------
358 root : `str`
359 Filesystem path to the root of the data repository.
360 config : `Config`
361 A `Config` to update. Only the subset understood by
362 this component will be updated. Will not expand
363 defaults.
364 full : `Config`
365 A complete config with all defaults expanded that can be
366 converted to a `DatastoreConfig`. Read-only and will not be
367 modified by this method.
368 Repository-specific options that should not be obtained
369 from defaults when Butler instances are constructed
370 should be copied from ``full`` to ``config``.
371 overwrite : `bool`, optional
372 If `False`, do not modify a value in ``config`` if the value
373 already exists. Default is always to overwrite with the provided
374 ``root``.
376 Notes
377 -----
378 If a keyword is explicitly defined in the supplied ``config`` it
379 will not be overridden by this method if ``overwrite`` is `False`.
380 This allows explicit values set in external configs to be retained.
381 """
382 raise NotImplementedError()
384 @staticmethod
385 def fromConfig(
386 config: Config,
387 bridgeManager: DatastoreRegistryBridgeManager,
388 butlerRoot: ResourcePathExpression | None = None,
389 ) -> Datastore:
390 """Create datastore from type specified in config file.
392 Parameters
393 ----------
394 config : `Config` or `~lsst.resources.ResourcePathExpression`
395 Configuration instance.
396 bridgeManager : `DatastoreRegistryBridgeManager`
397 Object that manages the interface between `Registry` and
398 datastores.
399 butlerRoot : `str`, optional
400 Butler root directory.
401 """
402 config = DatastoreConfig(config)
403 cls = doImportType(config["cls"])
404 if not issubclass(cls, Datastore):
405 raise TypeError(f"Imported child class {config['cls']} is not a Datastore")
406 return cls._create_from_config(config=config, bridgeManager=bridgeManager, butlerRoot=butlerRoot)
408 def __init__(
409 self,
410 config: DatastoreConfig,
411 bridgeManager: DatastoreRegistryBridgeManager,
412 ):
413 self.config = config
414 self.name = "ABCDataStore"
415 self._transaction: DatastoreTransaction | None = None
417 # All Datastores need storage classes and constraints
418 self.storageClassFactory = StorageClassFactory()
420 # And read the constraints list
421 constraintsConfig = self.config.get("constraints")
422 self.constraints = Constraints(constraintsConfig, universe=bridgeManager.universe)
424 @classmethod
425 @abstractmethod
426 def _create_from_config(
427 cls,
428 config: DatastoreConfig,
429 bridgeManager: DatastoreRegistryBridgeManager,
430 butlerRoot: ResourcePathExpression | None,
431 ) -> Datastore:
432 """`Datastore`.``fromConfig`` calls this to instantiate Datastore
433 subclasses. This is the primary constructor for the individual
434 Datastore subclasses.
435 """
436 raise NotImplementedError()
438 @abstractmethod
439 def clone(self, bridgeManager: DatastoreRegistryBridgeManager) -> Datastore:
440 """Make an independent copy of this Datastore with a different
441 `DatastoreRegistryBridgeManager` instance.
443 Parameters
444 ----------
445 bridgeManager : `DatastoreRegistryBridgeManager`
446 New `DatastoreRegistryBridgeManager` object to use when
447 instantiating managers.
449 Returns
450 -------
451 datastore : `Datastore`
452 New `Datastore` instance with the same configuration as the
453 existing instance.
454 """
455 raise NotImplementedError()
457 def __str__(self) -> str:
458 return self.name
460 def __repr__(self) -> str:
461 return self.name
463 @property
464 def names(self) -> tuple[str, ...]:
465 """Names associated with this datastore returned as a list.
467 Can be different to ``name`` for a chaining datastore.
468 """
469 # Default implementation returns solely the name itself
470 return (self.name,)
472 @property
473 def roots(self) -> dict[str, ResourcePath | None]:
474 """Return the root URIs for each named datastore.
476 Mapping from datastore name to root URI. The URI can be `None`
477 if a datastore has no concept of a root URI.
478 (`dict` [`str`, `ResourcePath` | `None`])
479 """
480 return {self.name: None}
482 @contextlib.contextmanager
483 def transaction(self) -> Iterator[DatastoreTransaction]:
484 """Context manager supporting `Datastore` transactions.
486 Transactions can be nested, and are to be used in combination with
487 `Registry.transaction`.
488 """
489 self._transaction = DatastoreTransaction(self._transaction)
490 try:
491 yield self._transaction
492 except BaseException:
493 self._transaction.rollback()
494 raise
495 else:
496 self._transaction.commit()
497 self._transaction = self._transaction.parent
499 def _set_trust_mode(self, mode: bool) -> None:
500 """Set the trust mode for this datastore.
502 Parameters
503 ----------
504 mode : `bool`
505 If `True`, get requests will be attempted even if the datastore
506 does not know about the dataset.
508 Notes
509 -----
510 This is a private method to indicate that trust mode might be a
511 transitory property that we do not want to make fully public. For now
512 only a `~lsst.daf.butler.datastores.FileDatastore` understands this
513 concept. By default this method does nothing.
514 """
515 return
517 @abstractmethod
518 def knows(self, ref: DatasetRef) -> bool:
519 """Check if the dataset is known to the datastore.
521 Does not check for existence of any artifact.
523 Parameters
524 ----------
525 ref : `DatasetRef`
526 Reference to the required dataset.
528 Returns
529 -------
530 exists : `bool`
531 `True` if the dataset is known to the datastore.
532 """
533 raise NotImplementedError()
535 def knows_these(self, refs: Iterable[DatasetRef]) -> dict[DatasetRef, bool]:
536 """Check which of the given datasets are known to this datastore.
538 This is like ``mexist()`` but does not check that the file exists.
540 Parameters
541 ----------
542 refs : iterable `DatasetRef`
543 The datasets to check.
545 Returns
546 -------
547 exists : `dict`[`DatasetRef`, `bool`]
548 Mapping of dataset to boolean indicating whether the dataset
549 is known to the datastore.
550 """
551 # Non-optimized default calls knows() repeatedly.
552 return {ref: self.knows(ref) for ref in refs}
554 def mexists(
555 self, refs: Iterable[DatasetRef], artifact_existence: dict[ResourcePath, bool] | None = None
556 ) -> dict[DatasetRef, bool]:
557 """Check the existence of multiple datasets at once.
559 Parameters
560 ----------
561 refs : iterable of `DatasetRef`
562 The datasets to be checked.
563 artifact_existence : `dict` [`lsst.resources.ResourcePath`, `bool`]
564 Optional mapping of datastore artifact to existence. Updated by
565 this method with details of all artifacts tested. Can be `None`
566 if the caller is not interested.
568 Returns
569 -------
570 existence : `dict` of [`DatasetRef`, `bool`]
571 Mapping from dataset to boolean indicating existence.
572 """
573 existence: dict[DatasetRef, bool] = {}
574 # Non-optimized default.
575 for ref in refs:
576 existence[ref] = self.exists(ref)
577 return existence
579 @abstractmethod
580 def exists(self, datasetRef: DatasetRef) -> bool:
581 """Check if the dataset exists in the datastore.
583 Parameters
584 ----------
585 datasetRef : `DatasetRef`
586 Reference to the required dataset.
588 Returns
589 -------
590 exists : `bool`
591 `True` if the entity exists in the `Datastore`.
592 """
593 raise NotImplementedError("Must be implemented by subclass")
595 @abstractmethod
596 def get(
597 self,
598 datasetRef: DatasetRef,
599 parameters: Mapping[str, Any] | None = None,
600 storageClass: StorageClass | str | None = None,
601 ) -> Any:
602 """Load an `InMemoryDataset` from the store.
604 Parameters
605 ----------
606 datasetRef : `DatasetRef`
607 Reference to the required Dataset.
608 parameters : `dict`
609 `StorageClass`-specific parameters that specify a slice of the
610 Dataset to be loaded.
611 storageClass : `StorageClass` or `str`, optional
612 The storage class to be used to override the Python type
613 returned by this method. By default the returned type matches
614 the dataset type definition for this dataset. Specifying a
615 read `StorageClass` can force a different type to be returned.
616 This type must be compatible with the original type.
618 Returns
619 -------
620 inMemoryDataset : `object`
621 Requested Dataset or slice thereof as an InMemoryDataset.
622 """
623 raise NotImplementedError("Must be implemented by subclass")
625 def prepare_get_for_external_client(self, ref: DatasetRef) -> list[DatasetLocationInformation] | None:
626 """Retrieve data that can be used to execute a ``get()``.
628 Parameters
629 ----------
630 ref : `DatasetRef`
631 Reference to the required dataset.
633 Returns
634 -------
635 payload : `list` [ `DatasetLocationInformation` ] | `None`
636 Information needed to perform a get() operation. Returns `None` if
637 the dataset is not known to this datastore.
638 """
639 raise NotImplementedError()
641 @abstractmethod
642 def put(
643 self, inMemoryDataset: Any, datasetRef: DatasetRef, provenance: DatasetProvenance | None = None
644 ) -> None:
645 """Write a `InMemoryDataset` with a given `DatasetRef` to the store.
647 Parameters
648 ----------
649 inMemoryDataset : `object`
650 The Dataset to store.
651 datasetRef : `DatasetRef`
652 Reference to the associated Dataset.
653 provenance : `DatasetProvenance` or `None`, optional
654 Any provenance that should be attached to the serialized dataset.
655 Not supported by all serialization mechanisms.
656 """
657 raise NotImplementedError("Must be implemented by subclass")
659 @abstractmethod
660 def put_new(self, in_memory_dataset: Any, ref: DatasetRef) -> Mapping[str, DatasetRef]:
661 """Write a `InMemoryDataset` with a given `DatasetRef` to the store.
663 Parameters
664 ----------
665 in_memory_dataset : `object`
666 The Dataset to store.
667 ref : `DatasetRef`
668 Reference to the associated Dataset.
670 Returns
671 -------
672 datastore_refs : `~collections.abc.Mapping` [`str`, `DatasetRef`]
673 Mapping of a datastore name to dataset reference stored in that
674 datastore, reference will include datastore records. Only
675 non-ephemeral datastores will appear in this mapping.
676 """
677 raise NotImplementedError("Must be implemented by subclass")
679 def _overrideTransferMode(self, *datasets: FileDataset, transfer: str | None = None) -> str | None:
680 """Allow ingest transfer mode to be defaulted based on datasets.
682 Parameters
683 ----------
684 *datasets : `FileDataset`
685 Each positional argument is a struct containing information about
686 a file to be ingested, including its path (either absolute or
687 relative to the datastore root, if applicable), a complete
688 `DatasetRef` (with ``dataset_id not None``), and optionally a
689 formatter class or its fully-qualified string name. If a formatter
690 is not provided, this method should populate that attribute with
691 the formatter the datastore would use for `put`. Subclasses are
692 also permitted to modify the path attribute (typically to put it
693 in what the datastore considers its standard form).
694 transfer : `str`, optional
695 How (and whether) the dataset should be added to the datastore.
696 See `ingest` for details of transfer modes.
698 Returns
699 -------
700 newTransfer : `str`
701 Transfer mode to use. Will be identical to the supplied transfer
702 mode unless "auto" is used.
703 """
704 if transfer != "auto":
705 return transfer
706 raise RuntimeError(f"{transfer} is not allowed without specialization.")
708 def _prepIngest(self, *datasets: FileDataset, transfer: str | None = None) -> IngestPrepData:
709 """Process datasets to identify which ones can be ingested.
711 Parameters
712 ----------
713 *datasets : `FileDataset`
714 Each positional argument is a struct containing information about
715 a file to be ingested, including its path (either absolute or
716 relative to the datastore root, if applicable), a complete
717 `DatasetRef` (with ``dataset_id not None``), and optionally a
718 formatter class or its fully-qualified string name. If a formatter
719 is not provided, this method should populate that attribute with
720 the formatter the datastore would use for `put`. Subclasses are
721 also permitted to modify the path attribute (typically to put it
722 in what the datastore considers its standard form).
723 transfer : `str`, optional
724 How (and whether) the dataset should be added to the datastore.
725 See `ingest` for details of transfer modes.
727 Returns
728 -------
729 data : `IngestPrepData`
730 An instance of a subclass of `IngestPrepData`, used to pass
731 arbitrary data from `_prepIngest` to `_finishIngest`. This should
732 include only the datasets this datastore can actually ingest;
733 others should be silently ignored (`Datastore.ingest` will inspect
734 `IngestPrepData.refs` and raise `DatasetTypeNotSupportedError` if
735 necessary).
737 Raises
738 ------
739 NotImplementedError
740 Raised if the datastore does not support the given transfer mode
741 (including the case where ingest is not supported at all).
742 FileNotFoundError
743 Raised if one of the given files does not exist.
744 FileExistsError
745 Raised if transfer is not `None` but the (internal) location the
746 file would be moved to is already occupied.
748 Notes
749 -----
750 This method (along with `_finishIngest`) should be implemented by
751 subclasses to provide ingest support instead of implementing `ingest`
752 directly.
754 `_prepIngest` should not modify the data repository or given files in
755 any way; all changes should be deferred to `_finishIngest`.
757 When possible, exceptions should be raised in `_prepIngest` instead of
758 `_finishIngest`. `NotImplementedError` exceptions that indicate that
759 the transfer mode is not supported must be raised by `_prepIngest`
760 instead of `_finishIngest`.
761 """
762 raise NotImplementedError(f"Datastore {self} does not support direct file-based ingest.")
764 def _finishIngest(
765 self, prepData: IngestPrepData, *, transfer: str | None = None, record_validation_info: bool = True
766 ) -> None:
767 """Complete an ingest operation.
769 Parameters
770 ----------
771 prepData : `IngestPrepData`
772 An instance of a subclass of `IngestPrepData`. Guaranteed to be
773 the direct result of a call to `_prepIngest` on this datastore.
774 transfer : `str`, optional
775 How (and whether) the dataset should be added to the datastore.
776 See `ingest` for details of transfer modes.
777 record_validation_info : `bool`, optional
778 If `True`, the default, the datastore can record validation
779 information associated with the file. If `False` the datastore
780 will not attempt to track any information such as checksums
781 or file sizes. This can be useful if such information is tracked
782 in an external system or if the file is to be compressed in place.
783 It is up to the datastore whether this parameter is relevant.
785 Raises
786 ------
787 FileNotFoundError
788 Raised if one of the given files does not exist.
789 FileExistsError
790 Raised if transfer is not `None` but the (internal) location the
791 file would be moved to is already occupied.
793 Notes
794 -----
795 This method (along with `_prepIngest`) should be implemented by
796 subclasses to provide ingest support instead of implementing `ingest`
797 directly.
798 """
799 raise NotImplementedError(f"Datastore {self} does not support direct file-based ingest.")
801 def ingest(
802 self, *datasets: FileDataset, transfer: str | None = None, record_validation_info: bool = True
803 ) -> None:
804 """Ingest one or more files into the datastore.
806 Parameters
807 ----------
808 *datasets : `FileDataset`
809 Each positional argument is a struct containing information about
810 a file to be ingested, including its path (either absolute or
811 relative to the datastore root, if applicable), a complete
812 `DatasetRef` (with ``dataset_id not None``), and optionally a
813 formatter class or its fully-qualified string name. If a formatter
814 is not provided, the one the datastore would use for ``put`` on
815 that dataset is assumed.
816 transfer : `str`, optional
817 How (and whether) the dataset should be added to the datastore.
818 If `None` (default), the file must already be in a location
819 appropriate for the datastore (e.g. within its root directory),
820 and will not be modified. Other choices include "move", "copy",
821 "link", "symlink", "relsymlink", and "hardlink". "link" is a
822 special transfer mode that will first try to make a hardlink and
823 if that fails a symlink will be used instead. "relsymlink" creates
824 a relative symlink rather than use an absolute path.
825 Most datastores do not support all transfer modes.
826 "auto" is a special option that will let the
827 data store choose the most natural option for itself.
828 record_validation_info : `bool`, optional
829 If `True`, the default, the datastore can record validation
830 information associated with the file. If `False` the datastore
831 will not attempt to track any information such as checksums
832 or file sizes. This can be useful if such information is tracked
833 in an external system or if the file is to be compressed in place.
834 It is up to the datastore whether this parameter is relevant.
836 Raises
837 ------
838 NotImplementedError
839 Raised if the datastore does not support the given transfer mode
840 (including the case where ingest is not supported at all).
841 DatasetTypeNotSupportedError
842 Raised if one or more files to be ingested have a dataset type that
843 is not supported by the datastore.
844 FileNotFoundError
845 Raised if one of the given files does not exist.
846 FileExistsError
847 Raised if transfer is not `None` but the (internal) location the
848 file would be moved to is already occupied.
850 Notes
851 -----
852 Subclasses should implement `_prepIngest` and `_finishIngest` instead
853 of implementing `ingest` directly. Datastores that hold and
854 delegate to child datastores may want to call those methods as well.
856 Subclasses are encouraged to document their supported transfer modes
857 in their class documentation.
858 """
859 # Allow a datastore to select a default transfer mode
860 transfer = self._overrideTransferMode(*datasets, transfer=transfer)
861 prepData = self._prepIngest(*datasets, transfer=transfer)
862 refs = {ref.id: ref for dataset in datasets for ref in dataset.refs}
863 if refs.keys() != prepData.refs.keys():
864 unsupported = refs.keys() - prepData.refs.keys()
865 # Group unsupported refs by DatasetType for an informative
866 # but still concise error message.
867 byDatasetType = defaultdict(list)
868 for datasetId in unsupported:
869 ref = refs[datasetId]
870 byDatasetType[ref.datasetType].append(ref)
871 raise DatasetTypeNotSupportedError(
872 "DatasetType(s) not supported in ingest: "
873 + ", ".join(f"{k.name} ({len(v)} dataset(s))" for k, v in byDatasetType.items())
874 )
875 self._finishIngest(prepData, transfer=transfer, record_validation_info=record_validation_info)
877 def transfer_from(
878 self,
879 source_records: FileTransferMap,
880 refs: Collection[DatasetRef],
881 transfer: str = "auto",
882 artifact_existence: dict[ResourcePath, bool] | None = None,
883 dry_run: bool = False,
884 ) -> tuple[set[DatasetRef], set[DatasetRef]]:
885 """Transfer dataset artifacts from another datastore to this one.
887 Parameters
888 ----------
889 source_records : `FileTransferMap`
890 The artifacts to be transferred into this datastore.
891 refs : `~collections.abc.Collection` of `DatasetRef`
892 The datasets to transfer from the source datastore.
893 transfer : `str`, optional
894 How (and whether) the dataset should be added to the datastore.
895 Choices include "move", "copy",
896 "link", "symlink", "relsymlink", and "hardlink". "link" is a
897 special transfer mode that will first try to make a hardlink and
898 if that fails a symlink will be used instead. "relsymlink" creates
899 a relative symlink rather than use an absolute path.
900 Most datastores do not support all transfer modes.
901 "auto" (the default) is a special option that will let the
902 data store choose the most natural option for itself.
903 If the source location and transfer location are identical the
904 transfer mode will be ignored.
905 artifact_existence : `dict` [`lsst.resources.ResourcePath`, `bool`]
906 Optional mapping of datastore artifact to existence. Updated by
907 this method with details of all artifacts tested. Can be `None`
908 if the caller is not interested.
909 dry_run : `bool`, optional
910 Process the supplied source refs without updating the target
911 datastore.
913 Returns
914 -------
915 accepted : `set` [`DatasetRef`]
916 The datasets that were transferred.
917 rejected : `set` [`DatasetRef`]
918 The datasets that were rejected due to a constraints violation.
920 Raises
921 ------
922 TypeError
923 Raised if the two datastores are not compatible.
924 """
925 raise NotImplementedError(f"Datastore {type(self)} does not implement a transfer_from method.")
927 def getManyURIs(
928 self,
929 refs: Iterable[DatasetRef],
930 predict: bool = False,
931 allow_missing: bool = False,
932 ) -> dict[DatasetRef, DatasetRefURIs]:
933 """Return URIs associated with many datasets.
935 Parameters
936 ----------
937 refs : iterable of `DatasetIdRef`
938 References to the required datasets.
939 predict : `bool`, optional
940 If `True`, allow URIs to be returned of datasets that have not
941 been written.
942 allow_missing : `bool`
943 If `False`, and ``predict`` is `False`, will raise if a
944 `DatasetRef` does not exist.
946 Returns
947 -------
948 URIs : `dict` of [`DatasetRef`, `DatasetRefUris`]
949 A dict of primary and component URIs, indexed by the passed-in
950 refs.
952 Raises
953 ------
954 FileNotFoundError
955 A URI has been requested for a dataset that does not exist and
956 guessing is not allowed.
958 Notes
959 -----
960 In file-based datastores, getManyURIs does not check that the file is
961 really there, it's assuming it is if datastore is aware of the file
962 then it actually exists.
963 """
964 uris: dict[DatasetRef, DatasetRefURIs] = {}
965 missing_refs = []
966 for ref in refs:
967 try:
968 uris[ref] = self.getURIs(ref, predict=predict)
969 except FileNotFoundError:
970 missing_refs.append(ref)
971 if missing_refs and not allow_missing:
972 num_missing = len(missing_refs)
973 raise FileNotFoundError(
974 f"Missing {num_missing} refs from datastore out of "
975 f"{num_missing + len(uris)} and predict=False."
976 )
977 return uris
979 @abstractmethod
980 def getURIs(self, datasetRef: DatasetRef, predict: bool = False) -> DatasetRefURIs:
981 """Return URIs associated with dataset.
983 Parameters
984 ----------
985 datasetRef : `DatasetRef`
986 Reference to the required dataset.
987 predict : `bool`, optional
988 If the datastore does not know about the dataset, controls whether
989 it should return a predicted URI or not.
991 Returns
992 -------
993 uris : `DatasetRefURIs`
994 The URI to the primary artifact associated with this dataset (if
995 the dataset was disassembled within the datastore this may be
996 `None`), and the URIs to any components associated with the dataset
997 artifact. (can be empty if there are no components).
998 """
999 raise NotImplementedError()
1001 @abstractmethod
1002 def getURI(self, datasetRef: DatasetRef, predict: bool = False) -> ResourcePath:
1003 """URI to the Dataset.
1005 Parameters
1006 ----------
1007 datasetRef : `DatasetRef`
1008 Reference to the required Dataset.
1009 predict : `bool`
1010 If `True` attempt to predict the URI for a dataset if it does
1011 not exist in datastore.
1013 Returns
1014 -------
1015 uri : `str`
1016 URI string pointing to the Dataset within the datastore. If the
1017 Dataset does not exist in the datastore, the URI may be a guess.
1018 If the datastore does not have entities that relate well
1019 to the concept of a URI the returned URI string will be
1020 descriptive. The returned URI is not guaranteed to be obtainable.
1022 Raises
1023 ------
1024 FileNotFoundError
1025 A URI has been requested for a dataset that does not exist and
1026 guessing is not allowed.
1027 """
1028 raise NotImplementedError("Must be implemented by subclass")
1030 @abstractmethod
1031 def retrieveArtifacts(
1032 self,
1033 refs: Iterable[DatasetRef],
1034 destination: ResourcePath,
1035 transfer: str = "auto",
1036 preserve_path: bool = True,
1037 overwrite: bool = False,
1038 write_index: bool = True,
1039 add_prefix: bool = False,
1040 ) -> dict[ResourcePath, ArtifactIndexInfo]:
1041 """Retrieve the artifacts associated with the supplied refs.
1043 Parameters
1044 ----------
1045 refs : iterable of `DatasetRef`
1046 The datasets for which artifacts are to be retrieved.
1047 A single ref can result in multiple artifacts. The refs must
1048 be resolved.
1049 destination : `lsst.resources.ResourcePath`
1050 Location to write the artifacts.
1051 transfer : `str`, optional
1052 Method to use to transfer the artifacts. Must be one of the options
1053 supported by `lsst.resources.ResourcePath.transfer_from()`.
1054 "move" is not allowed.
1055 preserve_path : `bool`, optional
1056 If `True` the full path of the artifact within the datastore
1057 is preserved. If `False` the final file component of the path
1058 is used.
1059 overwrite : `bool`, optional
1060 If `True` allow transfers to overwrite existing files at the
1061 destination.
1062 write_index : `bool`, optional
1063 If `True` write a file at the top level containing a serialization
1064 of a `ZipIndex` for the downloaded datasets.
1065 add_prefix : `bool`, optional
1066 If `True` and if ``preserve_path`` is `False`, apply a prefix to
1067 the filenames corresponding to some part of the dataset ref ID.
1068 This can be used to guarantee uniqueness.
1070 Returns
1071 -------
1072 artifact_map : `dict` [ `lsst.resources.ResourcePath`, \
1073 `ArtifactIndexInfo` ]
1074 Mapping of retrieved file to associated index information.
1076 Notes
1077 -----
1078 For non-file datastores the artifacts written to the destination
1079 may not match the representation inside the datastore. For example
1080 a hierarchical data structure in a NoSQL database may well be stored
1081 as a JSON file.
1082 """
1083 raise NotImplementedError()
1085 @abstractmethod
1086 def ingest_zip(self, zip_path: ResourcePath, transfer: str | None, *, dry_run: bool = False) -> None:
1087 """Ingest an indexed Zip file and contents.
1089 The Zip file must have an index file as created by `retrieveArtifacts`.
1091 Parameters
1092 ----------
1093 zip_path : `lsst.resources.ResourcePath`
1094 Path to the Zip file.
1095 transfer : `str`
1096 Method to use for transferring the Zip file into the datastore.
1097 dry_run : `bool`, optional
1098 If `True` the ingest will be processed without any modifications
1099 made to the target datastore and as if the target datastore did not
1100 have any of the datasets.
1101 """
1102 raise NotImplementedError()
1104 @abstractmethod
1105 def remove(self, datasetRef: DatasetRef) -> None:
1106 """Indicate to the Datastore that a Dataset can be removed.
1108 Parameters
1109 ----------
1110 datasetRef : `DatasetRef`
1111 Reference to the required Dataset.
1113 Raises
1114 ------
1115 FileNotFoundError
1116 When Dataset does not exist.
1118 Notes
1119 -----
1120 Some Datastores may implement this method as a silent no-op to
1121 disable Dataset deletion through standard interfaces.
1122 """
1123 raise NotImplementedError("Must be implemented by subclass")
1125 @abstractmethod
1126 def forget(self, refs: Iterable[DatasetRef]) -> None:
1127 """Indicate to the Datastore that it should remove all records of the
1128 given datasets, without actually deleting them.
1130 Parameters
1131 ----------
1132 refs : `~collections.abc.Iterable` [ `DatasetRef` ]
1133 References to the datasets being forgotten.
1135 Notes
1136 -----
1137 Asking a datastore to forget a `DatasetRef` it does not hold should be
1138 a silent no-op, not an error.
1139 """
1140 raise NotImplementedError("Must be implemented by subclass")
1142 @abstractmethod
1143 def trash(self, ref: DatasetRef | Iterable[DatasetRef], ignore_errors: bool = True) -> None:
1144 """Indicate to the Datastore that a Dataset can be moved to the trash.
1146 Parameters
1147 ----------
1148 ref : `DatasetRef` or iterable thereof
1149 Reference(s) to the required Dataset.
1150 ignore_errors : `bool`, optional
1151 Determine whether errors should be ignored. When multiple
1152 refs are being trashed there will be no per-ref check.
1154 Raises
1155 ------
1156 FileNotFoundError
1157 When Dataset does not exist and errors are not ignored. Only
1158 checked if a single ref is supplied (and not in a list).
1160 Notes
1161 -----
1162 Some Datastores may implement this method as a silent no-op to
1163 disable Dataset deletion through standard interfaces.
1164 """
1165 raise NotImplementedError("Must be implemented by subclass")
1167 @abstractmethod
1168 def emptyTrash(
1169 self, ignore_errors: bool = True, refs: Collection[DatasetRef] | None = None, dry_run: bool = False
1170 ) -> set[ResourcePath]:
1171 """Remove all datasets from the trash.
1173 Parameters
1174 ----------
1175 ignore_errors : `bool`, optional
1176 Determine whether errors should be ignored.
1177 refs : `collections.abc.Collection` [ `DatasetRef` ] or `None`
1178 Explicit list of datasets that can be removed from trash. If listed
1179 datasets are not already stored in the trash table they will be
1180 ignored. If `None` every entry in the trash table will be
1181 processed.
1182 dry_run : `bool`, optional
1183 If `True`, the trash table will be queried and results reported
1184 but no artifacts will be removed.
1186 Returns
1187 -------
1188 removed : `set` [ `lsst.resources.ResourcePath` ]
1189 List of artifacts that were removed. Can return nothing if
1190 artifacts cannot be represented by URIs.
1192 Notes
1193 -----
1194 Some Datastores may implement this method as a silent no-op to
1195 disable Dataset deletion through standard interfaces.
1196 """
1197 raise NotImplementedError("Must be implemented by subclass")
1199 @abstractmethod
1200 def transfer(self, inputDatastore: Datastore, datasetRef: DatasetRef) -> None:
1201 """Transfer a dataset from another datastore to this datastore.
1203 Parameters
1204 ----------
1205 inputDatastore : `Datastore`
1206 The external `Datastore` from which to retrieve the Dataset.
1207 datasetRef : `DatasetRef`
1208 Reference to the required Dataset.
1209 """
1210 raise NotImplementedError("Must be implemented by subclass")
1212 def export(
1213 self,
1214 refs: Iterable[DatasetRef],
1215 *,
1216 directory: ResourcePathExpression | None = None,
1217 transfer: str | None = "auto",
1218 ) -> Iterable[FileDataset]:
1219 """Export datasets for transfer to another data repository.
1221 Parameters
1222 ----------
1223 refs : iterable of `DatasetRef`
1224 Dataset references to be exported.
1225 directory : `str`, optional
1226 Path to a directory that should contain files corresponding to
1227 output datasets. Ignored if ``transfer`` is explicitly `None`.
1228 transfer : `str`, optional
1229 Mode that should be used to move datasets out of the repository.
1230 Valid options are the same as those of the ``transfer`` argument
1231 to ``ingest``, and datastores may similarly signal that a transfer
1232 mode is not supported by raising `NotImplementedError`. If "auto"
1233 is given and no ``directory`` is specified, `None` will be
1234 implied.
1236 Returns
1237 -------
1238 dataset : iterable of `DatasetTransfer`
1239 Structs containing information about the exported datasets, in the
1240 same order as ``refs``.
1242 Raises
1243 ------
1244 NotImplementedError
1245 Raised if the given transfer mode is not supported.
1246 """
1247 raise NotImplementedError(f"Transfer mode {transfer} not supported.")
1249 @abstractmethod
1250 def validateConfiguration(
1251 self, entities: Iterable[DatasetRef | DatasetType | StorageClass], logFailures: bool = False
1252 ) -> None:
1253 """Validate some of the configuration for this datastore.
1255 Parameters
1256 ----------
1257 entities : iterable of `DatasetRef`, `DatasetType`, or `StorageClass`
1258 Entities to test against this configuration. Can be differing
1259 types.
1260 logFailures : `bool`, optional
1261 If `True`, output a log message for every validation error
1262 detected.
1264 Raises
1265 ------
1266 DatastoreValidationError
1267 Raised if there is a validation problem with a configuration.
1269 Notes
1270 -----
1271 Which parts of the configuration are validated is at the discretion
1272 of each Datastore implementation.
1273 """
1274 raise NotImplementedError("Must be implemented by subclass")
1276 @abstractmethod
1277 def validateKey(self, lookupKey: LookupKey, entity: DatasetRef | DatasetType | StorageClass) -> None:
1278 """Validate a specific look up key with supplied entity.
1280 Parameters
1281 ----------
1282 lookupKey : `LookupKey`
1283 Key to use to retrieve information from the datastore
1284 configuration.
1285 entity : `DatasetRef`, `DatasetType`, or `StorageClass`
1286 Entity to compare with configuration retrieved using the
1287 specified lookup key.
1289 Raises
1290 ------
1291 DatastoreValidationError
1292 Raised if there is a problem with the combination of entity
1293 and lookup key.
1295 Notes
1296 -----
1297 Bypasses the normal selection priorities by allowing a key that
1298 would normally not be selected to be validated.
1299 """
1300 raise NotImplementedError("Must be implemented by subclass")
1302 @abstractmethod
1303 def getLookupKeys(self) -> set[LookupKey]:
1304 """Return all the lookup keys relevant to this datastore.
1306 Returns
1307 -------
1308 keys : `set` of `LookupKey`
1309 The keys stored internally for looking up information based
1310 on `DatasetType` name or `StorageClass`.
1311 """
1312 raise NotImplementedError("Must be implemented by subclass")
1314 def needs_expanded_data_ids(
1315 self,
1316 transfer: str | None,
1317 entity: DatasetRef | DatasetType | StorageClass | None = None,
1318 ) -> bool:
1319 """Test whether this datastore needs expanded data IDs to ingest.
1321 Parameters
1322 ----------
1323 transfer : `str` or `None`
1324 Transfer mode for ingest.
1325 entity : `DatasetRef` or `DatasetType` or `StorageClass` or `None`, \
1326 optional
1327 Object representing what will be ingested. If not provided (or not
1328 specific enough), `True` may be returned even if expanded data
1329 IDs aren't necessary.
1331 Returns
1332 -------
1333 needed : `bool`
1334 If `True`, expanded data IDs may be needed. `False` only if
1335 expansion definitely isn't necessary.
1336 """
1337 return True
1339 @abstractmethod
1340 def import_records(
1341 self,
1342 data: Mapping[str, DatastoreRecordData],
1343 ) -> None:
1344 """Import datastore location and record data from an in-memory data
1345 structure.
1347 Parameters
1348 ----------
1349 data : `~collections.abc.Mapping` [ `str`, `DatastoreRecordData` ]
1350 Datastore records indexed by datastore name. May contain data for
1351 other `Datastore` instances (generally because they are chained to
1352 this one), which should be ignored.
1354 Notes
1355 -----
1356 Implementations should generally not check that any external resources
1357 (e.g. files) referred to by these records actually exist, for
1358 performance reasons; we expect higher-level code to guarantee that they
1359 do.
1361 Implementations are responsible for calling
1362 `DatastoreRegistryBridge.insert` on all datasets in ``data.locations``
1363 where the key is in `names`, as well as loading any opaque table data.
1365 Implementations may assume that datasets are either fully present or
1366 not at all (single-component exports are not permitted).
1367 """
1368 raise NotImplementedError()
1370 @abstractmethod
1371 def export_records(
1372 self,
1373 refs: Iterable[DatasetIdRef],
1374 ) -> Mapping[str, DatastoreRecordData]:
1375 """Export datastore records and locations to an in-memory data
1376 structure.
1378 Parameters
1379 ----------
1380 refs : `~collections.abc.Iterable` [ `DatasetIdRef` ]
1381 Datasets to save. This may include datasets not known to this
1382 datastore, which should be ignored. May not include component
1383 datasets.
1385 Returns
1386 -------
1387 data : `~collections.abc.Mapping` [ `str`, `DatastoreRecordData` ]
1388 Exported datastore records indexed by datastore name.
1389 """
1390 raise NotImplementedError()
1392 def export_predicted_records(self, refs: Iterable[DatasetRef]) -> dict[str, DatastoreRecordData]:
1393 """Export predicted datastore records and locations to an in-memory
1394 data structure.
1396 Parameters
1397 ----------
1398 refs : `~collections.abc.Iterable` [ `DatasetRef` ]
1399 Datastore records that would be used if the given refs were to
1400 exist in this datastore. No attempt is made to determine if these
1401 datasets actually exist.
1403 Returns
1404 -------
1405 data : `~collections.abc.Mapping` [ `str`, `DatastoreRecordData` ]
1406 Exported datastore records indexed by datastore name.
1407 """
1408 raise NotImplementedError()
1410 def set_retrieve_dataset_type_method(self, method: Callable[[str], DatasetType | None] | None) -> None:
1411 """Specify a method that can be used by datastore to retrieve
1412 registry-defined dataset type.
1414 Parameters
1415 ----------
1416 method : `~collections.abc.Callable` | `None`
1417 Method that takes a name of the dataset type and returns a
1418 corresponding `DatasetType` instance as defined in Registry. If
1419 dataset type name is not known to registry `None` is returned.
1421 Notes
1422 -----
1423 This method is only needed for a Datastore supporting a "trusted" mode
1424 when it does not have an access to datastore records and needs to
1425 guess dataset location based on its stored dataset type.
1426 """
1427 pass
1429 @abstractmethod
1430 def get_opaque_table_definitions(self) -> Mapping[str, DatastoreOpaqueTable]:
1431 """Make definitions of the opaque tables used by this Datastore.
1433 Returns
1434 -------
1435 tables : `~collections.abc.Mapping` [ `str`, `.ddl.TableSpec` ]
1436 Mapping of opaque table names to their definitions. This can be an
1437 empty mapping if Datastore does not use opaque tables to keep
1438 datastore records.
1439 """
1440 raise NotImplementedError()
1442 def get_file_info_for_transfer(self, dataset_ids: Iterable[DatasetId]) -> FileTransferMap:
1443 raise NotImplementedError(f"Transferring files is not supported by datastore {self}")
1445 def locate_missing_files_for_transfer(
1446 self, refs: Iterable[DatasetRef], artifact_existence: dict[ResourcePath, bool]
1447 ) -> FileTransferMap:
1448 return {}
1451class NullDatastore(Datastore):
1452 """A datastore that implements the `Datastore` API but always fails when
1453 it accepts any request.
1455 Parameters
1456 ----------
1457 config : `Config` or `~lsst.resources.ResourcePathExpression` or `None`
1458 Ignored.
1459 bridgeManager : `DatastoreRegistryBridgeManager` or `None`
1460 Ignored.
1461 butlerRoot : `~lsst.resources.ResourcePathExpression` or `None`
1462 Ignored.
1463 """
1465 @classmethod
1466 def _create_from_config(
1467 cls,
1468 config: Config,
1469 bridgeManager: DatastoreRegistryBridgeManager,
1470 butlerRoot: ResourcePathExpression | None = None,
1471 ) -> NullDatastore:
1472 return NullDatastore(config, bridgeManager, butlerRoot)
1474 def clone(self, bridgeManager: DatastoreRegistryBridgeManager) -> Datastore:
1475 return self
1477 @classmethod
1478 def setConfigRoot(cls, root: str, config: Config, full: Config, overwrite: bool = True) -> None:
1479 # Nothing to do. This is not a real Datastore.
1480 pass
1482 def __init__(
1483 self,
1484 config: Config | ResourcePathExpression | None,
1485 bridgeManager: DatastoreRegistryBridgeManager | None,
1486 butlerRoot: ResourcePathExpression | None = None,
1487 ):
1488 # Name ourselves with the timestamp the datastore
1489 # was created.
1490 self.name = f"{type(self).__name__}@{time.time()}"
1491 _LOG.debug("Creating datastore %s", self.name)
1492 self._transaction: DatastoreTransaction | None = None
1493 return
1495 def knows(self, ref: DatasetRef) -> bool:
1496 return False
1498 def exists(self, datasetRef: DatasetRef) -> bool:
1499 return False
1501 def get(
1502 self,
1503 datasetRef: DatasetRef,
1504 parameters: Mapping[str, Any] | None = None,
1505 storageClass: StorageClass | str | None = None,
1506 ) -> Any:
1507 raise FileNotFoundError("This is a no-op datastore that can not access a real datastore")
1509 def put(
1510 self, inMemoryDataset: Any, datasetRef: DatasetRef, provenance: DatasetProvenance | None = None
1511 ) -> None:
1512 raise NotImplementedError("This is a no-op datastore that can not access a real datastore")
1514 def put_new(self, in_memory_dataset: Any, ref: DatasetRef) -> Mapping[str, DatasetRef]:
1515 raise NotImplementedError("This is a no-op datastore that can not access a real datastore")
1517 def ingest(
1518 self, *datasets: FileDataset, transfer: str | None = None, record_validation_info: bool = True
1519 ) -> None:
1520 raise NotImplementedError("This is a no-op datastore that can not access a real datastore")
1522 def transfer_from(
1523 self,
1524 source_records: FileTransferMap,
1525 refs: Iterable[DatasetRef],
1526 transfer: str = "auto",
1527 artifact_existence: dict[ResourcePath, bool] | None = None,
1528 dry_run: bool = False,
1529 ) -> tuple[set[DatasetRef], set[DatasetRef]]:
1530 raise NotImplementedError("This is a no-op datastore that can not access a real datastore")
1532 def getURIs(self, datasetRef: DatasetRef, predict: bool = False) -> DatasetRefURIs:
1533 raise FileNotFoundError("This is a no-op datastore that can not access a real datastore")
1535 def getURI(self, datasetRef: DatasetRef, predict: bool = False) -> ResourcePath:
1536 raise FileNotFoundError("This is a no-op datastore that can not access a real datastore")
1538 def ingest_zip(self, zip_path: ResourcePath, transfer: str | None, *, dry_run: bool = False) -> None:
1539 raise NotImplementedError("Can only ingest a Zip into a real datastore.")
1541 def retrieveArtifacts(
1542 self,
1543 refs: Iterable[DatasetRef],
1544 destination: ResourcePath,
1545 transfer: str = "auto",
1546 preserve_path: bool = True,
1547 overwrite: bool = False,
1548 write_index: bool = True,
1549 add_prefix: bool = False,
1550 ) -> dict[ResourcePath, ArtifactIndexInfo]:
1551 raise NotImplementedError("This is a no-op datastore that can not access a real datastore")
1553 def remove(self, datasetRef: DatasetRef) -> None:
1554 raise NotImplementedError("This is a no-op datastore that can not access a real datastore")
1556 def forget(self, refs: Iterable[DatasetRef]) -> None:
1557 raise NotImplementedError("This is a no-op datastore that can not access a real datastore")
1559 def trash(self, ref: DatasetRef | Iterable[DatasetRef], ignore_errors: bool = True) -> None:
1560 raise NotImplementedError("This is a no-op datastore that can not access a real datastore")
1562 def emptyTrash(
1563 self, ignore_errors: bool = True, refs: Collection[DatasetRef] | None = None, dry_run: bool = False
1564 ) -> set[ResourcePath]:
1565 raise NotImplementedError("This is a no-op datastore that can not access a real datastore")
1567 def transfer(self, inputDatastore: Datastore, datasetRef: DatasetRef) -> None:
1568 raise NotImplementedError("This is a no-op datastore that can not access a real datastore")
1570 def export(
1571 self,
1572 refs: Iterable[DatasetRef],
1573 *,
1574 directory: ResourcePathExpression | None = None,
1575 transfer: str | None = "auto",
1576 ) -> Iterable[FileDataset]:
1577 raise NotImplementedError("This is a no-op datastore that can not access a real datastore")
1579 def validateConfiguration(
1580 self, entities: Iterable[DatasetRef | DatasetType | StorageClass], logFailures: bool = False
1581 ) -> None:
1582 # No configuration so always validates.
1583 pass
1585 def validateKey(self, lookupKey: LookupKey, entity: DatasetRef | DatasetType | StorageClass) -> None:
1586 pass
1588 def getLookupKeys(self) -> set[LookupKey]:
1589 raise NotImplementedError("This is a no-op datastore that can not access a real datastore")
1591 def import_records(
1592 self,
1593 data: Mapping[str, DatastoreRecordData],
1594 ) -> None:
1595 raise NotImplementedError("This is a no-op datastore that can not access a real datastore")
1597 def export_records(
1598 self,
1599 refs: Iterable[DatasetIdRef],
1600 ) -> Mapping[str, DatastoreRecordData]:
1601 raise NotImplementedError("This is a no-op datastore that can not access a real datastore")
1603 def get_opaque_table_definitions(self) -> Mapping[str, DatastoreOpaqueTable]:
1604 return {}