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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/>.
22from __future__ import annotations
24"""In-memory datastore."""
26__all__ = ("StoredMemoryItemInfo", "InMemoryDatastore")
28import logging
29import time
30from dataclasses import dataclass
31from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Mapping, Optional, Set, Tuple, Union
32from urllib.parse import urlencode
34from lsst.daf.butler import DatasetId, DatasetRef, StorageClass, StoredDatastoreItemInfo
35from lsst.daf.butler.registry.interfaces import DatastoreRegistryBridge
36from lsst.resources import ResourcePath
38from .genericDatastore import GenericBaseDatastore
40if TYPE_CHECKING: 40 ↛ 41line 40 didn't jump to line 41, because the condition on line 40 was never true
41 from lsst.daf.butler import Config, DatasetType, LookupKey
42 from lsst.daf.butler.registry.interfaces import DatasetIdRef, DatastoreRegistryBridgeManager
44log = logging.getLogger(__name__)
47@dataclass(frozen=True)
48class StoredMemoryItemInfo(StoredDatastoreItemInfo):
49 """Internal InMemoryDatastore Metadata associated with a stored
50 DatasetRef.
51 """
53 __slots__ = {"timestamp", "storageClass", "parentID"}
55 timestamp: float
56 """Unix timestamp indicating the time the dataset was stored."""
58 storageClass: StorageClass
59 """StorageClass associated with the dataset."""
61 parentID: DatasetId
62 """ID of the parent `DatasetRef` if this entry is a concrete
63 composite. Not used if the dataset being stored is not a
64 virtual component of a composite
65 """
68class InMemoryDatastore(GenericBaseDatastore):
69 """Basic Datastore for writing to an in memory cache.
71 This datastore is ephemeral in that the contents of the datastore
72 disappear when the Python process completes. This also means that
73 other processes can not access this datastore.
75 Parameters
76 ----------
77 config : `DatastoreConfig` or `str`
78 Configuration.
79 bridgeManager : `DatastoreRegistryBridgeManager`
80 Object that manages the interface between `Registry` and datastores.
81 butlerRoot : `str`, optional
82 Unused parameter.
84 Notes
85 -----
86 InMemoryDatastore does not support any file-based ingest.
87 """
89 defaultConfigFile = "datastores/inMemoryDatastore.yaml"
90 """Path to configuration defaults. Accessed within the ``configs`` resource
91 or relative to a search path. Can be None if no defaults specified.
92 """
94 isEphemeral = True
95 """A new datastore is created every time and datasets disappear when
96 the process shuts down."""
98 datasets: Dict[DatasetId, Any]
99 """Internal storage of datasets indexed by dataset ID."""
101 records: Dict[DatasetId, StoredMemoryItemInfo]
102 """Internal records about stored datasets."""
104 def __init__(
105 self,
106 config: Union[Config, str],
107 bridgeManager: DatastoreRegistryBridgeManager,
108 butlerRoot: Optional[str] = None,
109 ):
110 super().__init__(config, bridgeManager)
112 # Name ourselves with the timestamp the datastore
113 # was created.
114 self.name = "{}@{}".format(type(self).__name__, time.time())
115 log.debug("Creating datastore %s", self.name)
117 # Storage of datasets, keyed by dataset_id
118 self.datasets: Dict[DatasetId, Any] = {}
120 # Records is distinct in order to track concrete composite components
121 # where we register multiple components for a single dataset.
122 self.records: Dict[DatasetId, StoredMemoryItemInfo] = {}
124 # Related records that share the same parent
125 self.related: Dict[DatasetId, Set[DatasetId]] = {}
127 self._bridge = bridgeManager.register(self.name, ephemeral=True)
129 @classmethod
130 def setConfigRoot(cls, root: str, config: Config, full: Config, overwrite: bool = True) -> None:
131 """Set any filesystem-dependent config options for this Datastore to
132 be appropriate for a new empty repository with the given root.
134 Does nothing in this implementation.
136 Parameters
137 ----------
138 root : `str`
139 Filesystem path to the root of the data repository.
140 config : `Config`
141 A `Config` to update. Only the subset understood by
142 this component will be updated. Will not expand
143 defaults.
144 full : `Config`
145 A complete config with all defaults expanded that can be
146 converted to a `DatastoreConfig`. Read-only and will not be
147 modified by this method.
148 Repository-specific options that should not be obtained
149 from defaults when Butler instances are constructed
150 should be copied from ``full`` to ``config``.
151 overwrite : `bool`, optional
152 If `False`, do not modify a value in ``config`` if the value
153 already exists. Default is always to overwrite with the provided
154 ``root``.
156 Notes
157 -----
158 If a keyword is explicitly defined in the supplied ``config`` it
159 will not be overridden by this method if ``overwrite`` is `False`.
160 This allows explicit values set in external configs to be retained.
161 """
162 return
164 @property
165 def bridge(self) -> DatastoreRegistryBridge:
166 # Docstring inherited from GenericBaseDatastore.
167 return self._bridge
169 def addStoredItemInfo(self, refs: Iterable[DatasetRef], infos: Iterable[StoredMemoryItemInfo]) -> None:
170 # Docstring inherited from GenericBaseDatastore.
171 for ref, info in zip(refs, infos):
172 if ref.id is None: 172 ↛ 173line 172 didn't jump to line 173, because the condition on line 172 was never true
173 raise RuntimeError(f"Can not store unresolved DatasetRef {ref}")
174 self.records[ref.id] = info
175 self.related.setdefault(info.parentID, set()).add(ref.id)
177 def getStoredItemInfo(self, ref: DatasetIdRef) -> StoredMemoryItemInfo:
178 # Docstring inherited from GenericBaseDatastore.
179 if ref.id is None: 179 ↛ 180line 179 didn't jump to line 180, because the condition on line 179 was never true
180 raise RuntimeError(f"Can not retrieve unresolved DatasetRef {ref}")
181 return self.records[ref.id]
183 def getStoredItemsInfo(self, ref: DatasetIdRef) -> List[StoredMemoryItemInfo]:
184 # Docstring inherited from GenericBaseDatastore.
185 return [self.getStoredItemInfo(ref)]
187 def removeStoredItemInfo(self, ref: DatasetIdRef) -> None:
188 # Docstring inherited from GenericBaseDatastore.
189 # If a component has been removed previously then we can sometimes
190 # be asked to remove it again. Other datastores ignore this
191 # so also ignore here
192 if ref.id is None: 192 ↛ 193line 192 didn't jump to line 193, because the condition on line 192 was never true
193 raise RuntimeError(f"Can not remove unresolved DatasetRef {ref}")
194 if ref.id not in self.records:
195 return
196 record = self.records[ref.id]
197 del self.records[ref.id]
198 self.related[record.parentID].remove(ref.id)
200 def _get_dataset_info(self, ref: DatasetIdRef) -> Tuple[DatasetId, StoredMemoryItemInfo]:
201 """Check that the dataset is present and return the real ID and
202 associated information.
204 Parameters
205 ----------
206 ref : `DatasetRef`
207 Target `DatasetRef`
209 Returns
210 -------
211 realID : `int`
212 The dataset ID associated with this ref that should be used. This
213 could either be the ID of the supplied `DatasetRef` or the parent.
214 storageInfo : `StoredMemoryItemInfo`
215 Associated storage information.
217 Raises
218 ------
219 FileNotFoundError
220 Raised if the dataset is not present in this datastore.
221 """
222 try:
223 storedItemInfo = self.getStoredItemInfo(ref)
224 except KeyError:
225 raise FileNotFoundError(f"No such file dataset in memory: {ref}") from None
226 realID = ref.id
227 if storedItemInfo.parentID is not None: 227 ↛ 230line 227 didn't jump to line 230, because the condition on line 227 was never false
228 realID = storedItemInfo.parentID
230 if realID not in self.datasets: 230 ↛ 231line 230 didn't jump to line 231, because the condition on line 230 was never true
231 raise FileNotFoundError(f"No such file dataset in memory: {ref}")
233 return realID, storedItemInfo
235 def knows(self, ref: DatasetRef) -> bool:
236 """Check if the dataset is known to the datastore.
238 This datastore does not distinguish dataset existence from knowledge
239 of a dataset.
241 Parameters
242 ----------
243 ref : `DatasetRef`
244 Reference to the required dataset.
246 Returns
247 -------
248 exists : `bool`
249 `True` if the dataset is known to the datastore.
250 """
251 return self.exists(ref)
253 def exists(self, ref: DatasetRef) -> bool:
254 """Check if the dataset exists in the datastore.
256 Parameters
257 ----------
258 ref : `DatasetRef`
259 Reference to the required dataset.
261 Returns
262 -------
263 exists : `bool`
264 `True` if the entity exists in the `Datastore`.
265 """
266 try:
267 self._get_dataset_info(ref)
268 except FileNotFoundError:
269 return False
270 return True
272 def get(self, ref: DatasetRef, parameters: Optional[Mapping[str, Any]] = None) -> Any:
273 """Load an InMemoryDataset from the store.
275 Parameters
276 ----------
277 ref : `DatasetRef`
278 Reference to the required Dataset.
279 parameters : `dict`
280 `StorageClass`-specific parameters that specify, for example,
281 a slice of the dataset to be loaded.
283 Returns
284 -------
285 inMemoryDataset : `object`
286 Requested dataset or slice thereof as an InMemoryDataset.
288 Raises
289 ------
290 FileNotFoundError
291 Requested dataset can not be retrieved.
292 TypeError
293 Return value from formatter has unexpected type.
294 ValueError
295 Formatter failed to process the dataset.
296 """
298 log.debug("Retrieve %s from %s with parameters %s", ref, self.name, parameters)
300 realID, storedItemInfo = self._get_dataset_info(ref)
302 # We have a write storage class and a read storage class and they
303 # can be different for concrete composites.
304 readStorageClass = ref.datasetType.storageClass
305 writeStorageClass = storedItemInfo.storageClass
307 component = ref.datasetType.component()
309 # Check that the supplied parameters are suitable for the type read
310 # If this is a derived component we validate against the composite
311 isDerivedComponent = False
312 if component in writeStorageClass.derivedComponents:
313 writeStorageClass.validateParameters(parameters)
314 isDerivedComponent = True
315 else:
316 readStorageClass.validateParameters(parameters)
318 inMemoryDataset = self.datasets[realID]
320 # if this is a read only component we need to apply parameters
321 # before we retrieve the component. We assume that the parameters
322 # will affect the data globally, before the derived component
323 # is selected.
324 if isDerivedComponent:
325 inMemoryDataset = writeStorageClass.delegate().handleParameters(inMemoryDataset, parameters)
326 # Then disable parameters for later
327 parameters = {}
329 # Different storage classes implies a component request
330 if readStorageClass != writeStorageClass:
332 if component is None: 332 ↛ 333line 332 didn't jump to line 333, because the condition on line 332 was never true
333 raise ValueError(
334 "Storage class inconsistency ({} vs {}) but no"
335 " component requested".format(readStorageClass.name, writeStorageClass.name)
336 )
338 # Concrete composite written as a single object (we hope)
339 inMemoryDataset = writeStorageClass.delegate().getComponent(inMemoryDataset, component)
341 # Since there is no formatter to process parameters, they all must be
342 # passed to the assembler.
343 return self._post_process_get(
344 inMemoryDataset, readStorageClass, parameters, isComponent=component is not None
345 )
347 def put(self, inMemoryDataset: Any, ref: DatasetRef) -> None:
348 """Write a InMemoryDataset with a given `DatasetRef` to the store.
350 Parameters
351 ----------
352 inMemoryDataset : `object`
353 The dataset to store.
354 ref : `DatasetRef`
355 Reference to the associated Dataset.
357 Raises
358 ------
359 TypeError
360 Supplied object and storage class are inconsistent.
361 DatasetTypeNotSupportedError
362 The associated `DatasetType` is not handled by this datastore.
364 Notes
365 -----
366 If the datastore is configured to reject certain dataset types it
367 is possible that the put will fail and raise a
368 `DatasetTypeNotSupportedError`. The main use case for this is to
369 allow `ChainedDatastore` to put to multiple datastores without
370 requiring that every datastore accepts the dataset.
371 """
373 if ref.id is None: 373 ↛ 374line 373 didn't jump to line 374, because the condition on line 373 was never true
374 raise RuntimeError(f"Can not store unresolved DatasetRef {ref}")
376 # May need to coerce the in memory dataset to the correct
377 # python type, otherwise parameters may not work.
378 inMemoryDataset = ref.datasetType.storageClass.coerce_type(inMemoryDataset)
380 self._validate_put_parameters(inMemoryDataset, ref)
382 self.datasets[ref.id] = inMemoryDataset
383 log.debug("Store %s in %s", ref, self.name)
385 # Store time we received this content, to allow us to optionally
386 # expire it. Instead of storing a filename here, we include the
387 # ID of this datasetRef so we can find it from components.
388 itemInfo = StoredMemoryItemInfo(time.time(), ref.datasetType.storageClass, parentID=ref.id)
390 # We have to register this content with registry.
391 # Currently this assumes we have a file so we need to use stub entries
392 # TODO: Add to ephemeral part of registry
393 self._register_datasets([(ref, itemInfo)])
395 if self._transaction is not None:
396 self._transaction.registerUndo("put", self.remove, ref)
398 def getURIs(
399 self, ref: DatasetRef, predict: bool = False
400 ) -> Tuple[Optional[ResourcePath], Dict[str, ResourcePath]]:
401 """Return URIs associated with dataset.
403 Parameters
404 ----------
405 ref : `DatasetRef`
406 Reference to the required dataset.
407 predict : `bool`, optional
408 If the datastore does not know about the dataset, should it
409 return a predicted URI or not?
411 Returns
412 -------
413 primary : `lsst.resources.ResourcePath`
414 The URI to the primary artifact associated with this dataset.
415 If the dataset was disassembled within the datastore this
416 may be `None`.
417 components : `dict`
418 URIs to any components associated with the dataset artifact.
419 Can be empty if there are no components.
421 Notes
422 -----
423 The URIs returned for in-memory datastores are not usable but
424 provide an indication of the associated dataset.
425 """
427 # Include the dataID as a URI query
428 query = urlencode(ref.dataId)
430 # if this has never been written then we have to guess
431 if not self.exists(ref):
432 if not predict:
433 raise FileNotFoundError("Dataset {} not in this datastore".format(ref))
434 name = f"{ref.datasetType.name}"
435 fragment = "#predicted"
436 else:
437 realID, _ = self._get_dataset_info(ref)
438 name = f"{id(self.datasets[realID])}?{query}"
439 fragment = ""
441 return ResourcePath(f"mem://{name}?{query}{fragment}"), {}
443 def getURI(self, ref: DatasetRef, predict: bool = False) -> ResourcePath:
444 """URI to the Dataset.
446 Always uses "mem://" URI prefix.
448 Parameters
449 ----------
450 ref : `DatasetRef`
451 Reference to the required Dataset.
452 predict : `bool`
453 If `True`, allow URIs to be returned of datasets that have not
454 been written.
456 Returns
457 -------
458 uri : `str`
459 URI pointing to the dataset within the datastore. If the
460 dataset does not exist in the datastore, and if ``predict`` is
461 `True`, the URI will be a prediction and will include a URI
462 fragment "#predicted".
463 If the datastore does not have entities that relate well
464 to the concept of a URI the returned URI string will be
465 descriptive. The returned URI is not guaranteed to be obtainable.
467 Raises
468 ------
469 FileNotFoundError
470 A URI has been requested for a dataset that does not exist and
471 guessing is not allowed.
472 AssertionError
473 Raised if an internal error occurs.
474 """
475 primary, _ = self.getURIs(ref, predict)
476 if primary is None: 476 ↛ 479line 476 didn't jump to line 479, because the condition on line 476 was never true
477 # This should be impossible since this datastore does
478 # not disassemble. This check also helps mypy.
479 raise AssertionError(f"Unexpectedly got no URI for in-memory datastore for {ref}")
480 return primary
482 def retrieveArtifacts(
483 self,
484 refs: Iterable[DatasetRef],
485 destination: ResourcePath,
486 transfer: str = "auto",
487 preserve_path: bool = True,
488 overwrite: Optional[bool] = False,
489 ) -> List[ResourcePath]:
490 """Retrieve the file artifacts associated with the supplied refs.
492 Notes
493 -----
494 Not implemented by this datastore.
495 """
496 # Could conceivably launch a FileDatastore to use formatters to write
497 # the data but this is fraught with problems.
498 raise NotImplementedError("Can not write artifacts to disk from in-memory datastore.")
500 def forget(self, refs: Iterable[DatasetRef]) -> None:
501 # Docstring inherited.
502 refs = list(refs)
503 self._bridge.forget(refs)
504 for ref in refs:
505 self.removeStoredItemInfo(ref)
507 def trash(self, ref: Union[DatasetRef, Iterable[DatasetRef]], ignore_errors: bool = False) -> None:
508 """Indicate to the Datastore that a dataset can be removed.
510 Parameters
511 ----------
512 ref : `DatasetRef` or iterable thereof
513 Reference to the required Dataset(s).
514 ignore_errors: `bool`, optional
515 Indicate that errors should be ignored.
517 Raises
518 ------
519 FileNotFoundError
520 Attempt to remove a dataset that does not exist. Only relevant
521 if a single dataset ref is given.
523 Notes
524 -----
525 Concurrency should not normally be an issue for the in memory datastore
526 since all internal changes are isolated to solely this process and
527 the registry only changes rows associated with this process.
528 """
529 if not isinstance(ref, DatasetRef):
530 log.debug("Bulk trashing of datasets in datastore %s", self.name)
531 self.bridge.moveToTrash(ref)
532 return
534 log.debug("Trash %s in datastore %s", ref, self.name)
536 # Check that this dataset is known to datastore
537 try:
538 self._get_dataset_info(ref)
540 # Move datasets to trash table
541 self.bridge.moveToTrash([ref])
542 except Exception as e:
543 if ignore_errors: 543 ↛ 544line 543 didn't jump to line 544, because the condition on line 543 was never true
544 log.warning(
545 "Error encountered moving dataset %s to trash in datastore %s: %s", ref, self.name, e
546 )
547 else:
548 raise
550 def emptyTrash(self, ignore_errors: bool = False) -> None:
551 """Remove all datasets from the trash.
553 Parameters
554 ----------
555 ignore_errors : `bool`, optional
556 Ignore errors.
558 Notes
559 -----
560 The internal tracking of datasets is affected by this method and
561 transaction handling is not supported if there is a problem before
562 the datasets themselves are deleted.
564 Concurrency should not normally be an issue for the in memory datastore
565 since all internal changes are isolated to solely this process and
566 the registry only changes rows associated with this process.
567 """
568 log.debug("Emptying trash in datastore %s", self.name)
569 with self._bridge.emptyTrash() as trash_data:
570 trashed, _ = trash_data
571 for ref, _ in trashed:
572 try:
573 realID, _ = self._get_dataset_info(ref)
574 except FileNotFoundError: 574 ↛ 577line 574 didn't jump to line 577
575 # Dataset already removed so ignore it
576 continue
577 except Exception as e:
578 if ignore_errors:
579 log.warning(
580 "Emptying trash in datastore %s but encountered an error with dataset %s: %s",
581 self.name,
582 ref.id,
583 e,
584 )
585 continue
586 else:
587 raise
589 # Determine whether all references to this dataset have been
590 # removed and we can delete the dataset itself
591 allRefs = self.related[realID]
592 remainingRefs = allRefs - {ref.id}
593 if not remainingRefs: 593 ↛ 598line 593 didn't jump to line 598, because the condition on line 593 was never false
594 log.debug("Removing artifact %s from datastore %s", realID, self.name)
595 del self.datasets[realID]
597 # Remove this entry
598 self.removeStoredItemInfo(ref)
600 def validateConfiguration(
601 self, entities: Iterable[Union[DatasetRef, DatasetType, StorageClass]], logFailures: bool = False
602 ) -> None:
603 """Validate some of the configuration for this datastore.
605 Parameters
606 ----------
607 entities : iterable of `DatasetRef`, `DatasetType`, or `StorageClass`
608 Entities to test against this configuration. Can be differing
609 types.
610 logFailures : `bool`, optional
611 If `True`, output a log message for every validation error
612 detected.
614 Raises
615 ------
616 DatastoreValidationError
617 Raised if there is a validation problem with a configuration.
618 All the problems are reported in a single exception.
620 Notes
621 -----
622 This method is a no-op.
623 """
624 return
626 def _overrideTransferMode(self, *datasets: Any, transfer: Optional[str] = None) -> Optional[str]:
627 # Docstring is inherited from base class
628 return transfer
630 def validateKey(self, lookupKey: LookupKey, entity: Union[DatasetRef, DatasetType, StorageClass]) -> None:
631 # Docstring is inherited from base class
632 return
634 def getLookupKeys(self) -> Set[LookupKey]:
635 # Docstring is inherited from base class
636 return self.constraints.getLookupKeys()
638 def needs_expanded_data_ids(
639 self,
640 transfer: Optional[str],
641 entity: Optional[Union[DatasetRef, DatasetType, StorageClass]] = None,
642 ) -> bool:
643 # Docstring inherited.
644 return False