Coverage for python/lsst/daf/butler/registry/interfaces/_datasets.py: 94%
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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 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/>.
28from __future__ import annotations
30__all__ = ("DatasetRecordStorageManager", "DatasetRecordStorage")
32from abc import ABC, abstractmethod
33from collections.abc import Iterable, Iterator, Set
34from typing import TYPE_CHECKING, Any
36from lsst.daf.relation import Relation
38from ...core import DataCoordinate, DatasetId, DatasetIdGenEnum, DatasetRef, DatasetType, Timespan, ddl
39from .._exceptions import MissingDatasetTypeError
40from ._versioning import VersionedExtension, VersionTuple
42if TYPE_CHECKING:
43 from .._collection_summary import CollectionSummary
44 from ..queries import SqlQueryContext
45 from ._collections import CollectionManager, CollectionRecord, RunRecord
46 from ._database import Database, StaticTablesContext
47 from ._dimensions import DimensionRecordStorageManager
50class DatasetRecordStorage(ABC):
51 """An interface that manages the records associated with a particular
52 `DatasetType`.
54 Parameters
55 ----------
56 datasetType : `DatasetType`
57 Dataset type whose records this object manages.
58 """
60 def __init__(self, datasetType: DatasetType):
61 self.datasetType = datasetType
63 @abstractmethod
64 def insert(
65 self,
66 run: RunRecord,
67 dataIds: Iterable[DataCoordinate],
68 idGenerationMode: DatasetIdGenEnum = DatasetIdGenEnum.UNIQUE,
69 ) -> Iterator[DatasetRef]:
70 """Insert one or more dataset entries into the database.
72 Parameters
73 ----------
74 run : `RunRecord`
75 The record object describing the `~CollectionType.RUN` collection
76 this dataset will be associated with.
77 dataIds : `~collections.abc.Iterable` [ `DataCoordinate` ]
78 Expanded data IDs (`DataCoordinate` instances) for the
79 datasets to be added. The dimensions of all data IDs must be the
80 same as ``self.datasetType.dimensions``.
81 idMode : `DatasetIdGenEnum`
82 With `UNIQUE` each new dataset is inserted with its new unique ID.
83 With non-`UNIQUE` mode ID is computed from some combination of
84 dataset type, dataId, and run collection name; if the same ID is
85 already in the database then new record is not inserted.
87 Returns
88 -------
89 datasets : `~collections.abc.Iterable` [ `DatasetRef` ]
90 References to the inserted datasets.
91 """
92 raise NotImplementedError()
94 @abstractmethod
95 def import_(
96 self,
97 run: RunRecord,
98 datasets: Iterable[DatasetRef],
99 ) -> Iterator[DatasetRef]:
100 """Insert one or more dataset entries into the database.
102 Parameters
103 ----------
104 run : `RunRecord`
105 The record object describing the `~CollectionType.RUN` collection
106 this dataset will be associated with.
107 datasets : `~collections.abc.Iterable` of `DatasetRef`
108 Datasets to be inserted. Datasets can specify ``id`` attribute
109 which will be used for inserted datasets. All dataset IDs must
110 have the same type (`int` or `uuid.UUID`), if type of dataset IDs
111 does not match type supported by this class then IDs will be
112 ignored and new IDs will be generated by backend.
114 Returns
115 -------
116 datasets : `~collections.abc.Iterable` [ `DatasetRef` ]
117 References to the inserted or existing datasets.
119 Notes
120 -----
121 The ``datasetType`` and ``run`` attributes of datasets are supposed to
122 be identical across all datasets but this is not checked and it should
123 be enforced by higher level registry code. This method does not need
124 to use those attributes from datasets, only ``dataId`` and ``id`` are
125 relevant.
126 """
127 raise NotImplementedError()
129 @abstractmethod
130 def delete(self, datasets: Iterable[DatasetRef]) -> None:
131 """Fully delete the given datasets from the registry.
133 Parameters
134 ----------
135 datasets : `~collections.abc.Iterable` [ `DatasetRef` ]
136 Datasets to be deleted. All datasets must be resolved and have
137 the same `DatasetType` as ``self``.
139 Raises
140 ------
141 AmbiguousDatasetError
142 Raised if any of the given `DatasetRef` instances is unresolved.
143 """
144 raise NotImplementedError()
146 @abstractmethod
147 def associate(self, collection: CollectionRecord, datasets: Iterable[DatasetRef]) -> None:
148 """Associate one or more datasets with a collection.
150 Parameters
151 ----------
152 collection : `CollectionRecord`
153 The record object describing the collection. ``collection.type``
154 must be `~CollectionType.TAGGED`.
155 datasets : `~collections.abc.Iterable` [ `DatasetRef` ]
156 Datasets to be associated. All datasets must be resolved and have
157 the same `DatasetType` as ``self``.
159 Raises
160 ------
161 AmbiguousDatasetError
162 Raised if any of the given `DatasetRef` instances is unresolved.
164 Notes
165 -----
166 Associating a dataset with into collection that already contains a
167 different dataset with the same `DatasetType` and data ID will remove
168 the existing dataset from that collection.
170 Associating the same dataset into a collection multiple times is a
171 no-op, but is still not permitted on read-only databases.
172 """
173 raise NotImplementedError()
175 @abstractmethod
176 def disassociate(self, collection: CollectionRecord, datasets: Iterable[DatasetRef]) -> None:
177 """Remove one or more datasets from a collection.
179 Parameters
180 ----------
181 collection : `CollectionRecord`
182 The record object describing the collection. ``collection.type``
183 must be `~CollectionType.TAGGED`.
184 datasets : `~collections.abc.Iterable` [ `DatasetRef` ]
185 Datasets to be disassociated. All datasets must be resolved and
186 have the same `DatasetType` as ``self``.
188 Raises
189 ------
190 AmbiguousDatasetError
191 Raised if any of the given `DatasetRef` instances is unresolved.
192 """
193 raise NotImplementedError()
195 @abstractmethod
196 def certify(
197 self,
198 collection: CollectionRecord,
199 datasets: Iterable[DatasetRef],
200 timespan: Timespan,
201 context: SqlQueryContext,
202 ) -> None:
203 """Associate one or more datasets with a calibration collection and a
204 validity range within it.
206 Parameters
207 ----------
208 collection : `CollectionRecord`
209 The record object describing the collection. ``collection.type``
210 must be `~CollectionType.CALIBRATION`.
211 datasets : `~collections.abc.Iterable` [ `DatasetRef` ]
212 Datasets to be associated. All datasets must be resolved and have
213 the same `DatasetType` as ``self``.
214 timespan : `Timespan`
215 The validity range for these datasets within the collection.
217 Raises
218 ------
219 AmbiguousDatasetError
220 Raised if any of the given `DatasetRef` instances is unresolved.
221 ConflictingDefinitionError
222 Raised if the collection already contains a different dataset with
223 the same `DatasetType` and data ID and an overlapping validity
224 range.
225 CollectionTypeError
226 Raised if
227 ``collection.type is not CollectionType.CALIBRATION`` or if
228 ``self.datasetType.isCalibration() is False``.
229 """
230 raise NotImplementedError()
232 @abstractmethod
233 def decertify(
234 self,
235 collection: CollectionRecord,
236 timespan: Timespan,
237 *,
238 dataIds: Iterable[DataCoordinate] | None = None,
239 context: SqlQueryContext,
240 ) -> None:
241 """Remove or adjust datasets to clear a validity range within a
242 calibration collection.
244 Parameters
245 ----------
246 collection : `CollectionRecord`
247 The record object describing the collection. ``collection.type``
248 must be `~CollectionType.CALIBRATION`.
249 timespan : `Timespan`
250 The validity range to remove datasets from within the collection.
251 Datasets that overlap this range but are not contained by it will
252 have their validity ranges adjusted to not overlap it, which may
253 split a single dataset validity range into two.
254 dataIds : `~collections.abc.Iterable` [ `DataCoordinate` ], optional
255 Data IDs that should be decertified within the given validity range
256 If `None`, all data IDs for ``self.datasetType`` will be
257 decertified.
259 Raises
260 ------
261 CollectionTypeError
262 Raised if ``collection.type is not CollectionType.CALIBRATION``.
263 """
264 raise NotImplementedError()
266 @abstractmethod
267 def make_relation(
268 self,
269 *collections: CollectionRecord,
270 columns: Set[str],
271 context: SqlQueryContext,
272 ) -> Relation:
273 """Return a `sql.Relation` that represents a query for for this
274 `DatasetType` in one or more collections.
276 Parameters
277 ----------
278 *collections : `CollectionRecord`
279 The record object(s) describing the collection(s) to query. May
280 not be of type `CollectionType.CHAINED`. If multiple collections
281 are passed, the query will search all of them in an unspecified
282 order, and all collections must have the same type. Must include
283 at least one collection.
284 columns : `~collections.abc.Set` [ `str` ]
285 Columns to include in the relation. See `Query.find_datasets` for
286 most options, but this method supports one more:
288 - ``rank``: a calculated integer column holding the index of the
289 collection the dataset was found in, within the ``collections``
290 sequence given.
291 context : `SqlQueryContext`
292 The object that manages database connections, temporary tables and
293 relation engines for this query.
295 Returns
296 -------
297 relation : `~lsst.daf.relation.Relation`
298 Representation of the query.
299 """
300 raise NotImplementedError()
302 datasetType: DatasetType
303 """Dataset type whose records this object manages (`DatasetType`).
304 """
307class DatasetRecordStorageManager(VersionedExtension):
308 """An interface that manages the tables that describe datasets.
310 `DatasetRecordStorageManager` primarily serves as a container and factory
311 for `DatasetRecordStorage` instances, which each provide access to the
312 records for a different `DatasetType`.
313 """
315 def __init__(self, *, registry_schema_version: VersionTuple | None = None) -> None:
316 super().__init__(registry_schema_version=registry_schema_version)
318 @classmethod
319 @abstractmethod
320 def initialize(
321 cls,
322 db: Database,
323 context: StaticTablesContext,
324 *,
325 collections: CollectionManager,
326 dimensions: DimensionRecordStorageManager,
327 registry_schema_version: VersionTuple | None = None,
328 ) -> DatasetRecordStorageManager:
329 """Construct an instance of the manager.
331 Parameters
332 ----------
333 db : `Database`
334 Interface to the underlying database engine and namespace.
335 context : `StaticTablesContext`
336 Context object obtained from `Database.declareStaticTables`; used
337 to declare any tables that should always be present.
338 collections: `CollectionManager`
339 Manager object for the collections in this `Registry`.
340 dimensions : `DimensionRecordStorageManager`
341 Manager object for the dimensions in this `Registry`.
342 registry_schema_version : `VersionTuple` or `None`
343 Schema version of this extension as defined in registry.
345 Returns
346 -------
347 manager : `DatasetRecordStorageManager`
348 An instance of a concrete `DatasetRecordStorageManager` subclass.
349 """
350 raise NotImplementedError()
352 @classmethod
353 @abstractmethod
354 def getIdColumnType(cls) -> type:
355 """Return type used for columns storing dataset IDs.
357 This type is used for columns storing `DatasetRef.id` values, usually
358 a `type` subclass provided by SQLAlchemy.
360 Returns
361 -------
362 dtype : `type`
363 Type used for dataset identification in database.
364 """
365 raise NotImplementedError()
367 @classmethod
368 @abstractmethod
369 def supportsIdGenerationMode(cls, mode: DatasetIdGenEnum) -> bool:
370 """Test whether the given dataset ID generation mode is supported by
371 `insert`.
373 Parameters
374 ----------
375 mode : `DatasetIdGenEnum`
376 Enum value for the mode to test.
378 Returns
379 -------
380 supported : `bool`
381 Whether the given mode is supported.
382 """
383 raise NotImplementedError()
385 @classmethod
386 @abstractmethod
387 def addDatasetForeignKey(
388 cls,
389 tableSpec: ddl.TableSpec,
390 *,
391 name: str = "dataset",
392 constraint: bool = True,
393 onDelete: str | None = None,
394 **kwargs: Any,
395 ) -> ddl.FieldSpec:
396 """Add a foreign key (field and constraint) referencing the dataset
397 table.
399 Parameters
400 ----------
401 tableSpec : `ddl.TableSpec`
402 Specification for the table that should reference the dataset
403 table. Will be modified in place.
404 name: `str`, optional
405 A name to use for the prefix of the new field; the full name is
406 ``{name}_id``.
407 onDelete: `str`, optional
408 One of "CASCADE" or "SET NULL", indicating what should happen to
409 the referencing row if the collection row is deleted. `None`
410 indicates that this should be an integrity error.
411 constraint: `bool`, optional
412 If `False` (`True` is default), add a field that can be joined to
413 the dataset primary key, but do not add a foreign key constraint.
414 **kwargs
415 Additional keyword arguments are forwarded to the `ddl.FieldSpec`
416 constructor (only the ``name`` and ``dtype`` arguments are
417 otherwise provided).
419 Returns
420 -------
421 idSpec : `ddl.FieldSpec`
422 Specification for the ID field.
423 """
424 raise NotImplementedError()
426 @abstractmethod
427 def refresh(self) -> None:
428 """Ensure all other operations on this manager are aware of any
429 dataset types that may have been registered by other clients since
430 it was initialized or last refreshed.
431 """
432 raise NotImplementedError()
434 def __getitem__(self, name: str) -> DatasetRecordStorage:
435 """Return the object that provides access to the records associated
436 with the given `DatasetType` name.
438 This is simply a convenience wrapper for `find` that raises `KeyError`
439 when the dataset type is not found.
441 Returns
442 -------
443 records : `DatasetRecordStorage`
444 The object representing the records for the given dataset type.
446 Raises
447 ------
448 KeyError
449 Raised if there is no dataset type with the given name.
451 Notes
452 -----
453 Dataset types registered by another client of the same repository since
454 the last call to `initialize` or `refresh` may not be found.
455 """
456 result = self.find(name)
457 if result is None:
458 raise MissingDatasetTypeError(f"Dataset type with name '{name}' not found.")
459 return result
461 @abstractmethod
462 def find(self, name: str) -> DatasetRecordStorage | None:
463 """Return an object that provides access to the records associated with
464 the given `DatasetType` name, if one exists.
466 Parameters
467 ----------
468 name : `str`
469 Name of the dataset type.
471 Returns
472 -------
473 records : `DatasetRecordStorage` or `None`
474 The object representing the records for the given dataset type, or
475 `None` if there are no records for that dataset type.
477 Notes
478 -----
479 Dataset types registered by another client of the same repository since
480 the last call to `initialize` or `refresh` may not be found.
481 """
482 raise NotImplementedError()
484 @abstractmethod
485 def register(self, datasetType: DatasetType) -> tuple[DatasetRecordStorage, bool]:
486 """Ensure that this `Registry` can hold records for the given
487 `DatasetType`, creating new tables as necessary.
489 Parameters
490 ----------
491 datasetType : `DatasetType`
492 Dataset type for which a table should created (as necessary) and
493 an associated `DatasetRecordStorage` returned.
495 Returns
496 -------
497 records : `DatasetRecordStorage`
498 The object representing the records for the given dataset type.
499 inserted : `bool`
500 `True` if the dataset type did not exist in the registry before.
502 Notes
503 -----
504 This operation may not be invoked within a `Database.transaction`
505 context.
506 """
507 raise NotImplementedError()
509 @abstractmethod
510 def remove(self, name: str) -> None:
511 """Remove the dataset type.
513 Parameters
514 ----------
515 name : `str`
516 Name of the dataset type.
517 """
518 raise NotImplementedError()
520 @abstractmethod
521 def resolve_wildcard(
522 self,
523 expression: Any,
524 components: bool | None = False,
525 missing: list[str] | None = None,
526 explicit_only: bool = False,
527 components_deprecated: bool = True,
528 ) -> dict[DatasetType, list[str | None]]:
529 """Resolve a dataset type wildcard expression.
531 Parameters
532 ----------
533 expression
534 Expression to resolve. Will be passed to
535 `DatasetTypeWildcard.from_expression`.
536 components : `bool`, optional
537 If `True`, apply all expression patterns to component dataset type
538 names as well. If `False`, never apply patterns to components. If
539 `None`, apply patterns to components only if their parent
540 datasets were not matched by the expression. Fully-specified
541 component datasets (`str` or `DatasetType` instances) are always
542 included.
543 missing : `list` of `str`, optional
544 String dataset type names that were explicitly given (i.e. not
545 regular expression patterns) but not found will be appended to this
546 list, if it is provided.
547 explicit_only : `bool`, optional
548 If `True`, require explicit `DatasetType` instances or `str` names,
549 with `re.Pattern` instances deprecated and ``...`` prohibited.
550 components_deprecated : `bool`, optional
551 If `True`, this is a context in which component dataset support is
552 deprecated. This will result in a deprecation warning when
553 ``components=True`` or ``components=None`` and a component dataset
554 is matched. In the future this will become an error.
556 Returns
557 -------
558 dataset_types : `dict` [ `DatasetType`, `list` [ `None`, `str` ] ]
559 A mapping with resolved dataset types as keys and lists of
560 matched component names as values, where `None` indicates the
561 parent composite dataset type was matched.
562 """
563 raise NotImplementedError()
565 @abstractmethod
566 def getDatasetRef(self, id: DatasetId) -> DatasetRef | None:
567 """Return a `DatasetRef` for the given dataset primary key
568 value.
570 Parameters
571 ----------
572 id : `DatasetId`
573 Primary key value for the dataset.
575 Returns
576 -------
577 ref : `DatasetRef` or `None`
578 Object representing the dataset, or `None` if no dataset with the
579 given primary key values exists in this layer.
580 """
581 raise NotImplementedError()
583 @abstractmethod
584 def getCollectionSummary(self, collection: CollectionRecord) -> CollectionSummary:
585 """Return a summary for the given collection.
587 Parameters
588 ----------
589 collection : `CollectionRecord`
590 Record describing the collection for which a summary is to be
591 retrieved.
593 Returns
594 -------
595 summary : `CollectionSummary`
596 Summary of the dataset types and governor dimension values in
597 this collection.
598 """
599 raise NotImplementedError()
601 @abstractmethod
602 def ingest_date_dtype(self) -> type:
603 """Return type of the ``ingest_date`` column."""
604 raise NotImplementedError()