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.
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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
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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
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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
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28from __future__ import annotations
30from ... import ddl
32__all__ = ("DatasetRecordStorageManager", "DatasetRecordStorage")
34from abc import ABC, abstractmethod
35from collections.abc import Iterable, Iterator, Set
36from typing import TYPE_CHECKING, Any
38from lsst.daf.relation import Relation
40from ..._dataset_ref import DatasetId, DatasetIdGenEnum, DatasetRef
41from ..._dataset_type import DatasetType
42from ..._timespan import Timespan
43from ...dimensions import DataCoordinate
44from .._exceptions import MissingDatasetTypeError
45from ._versioning import VersionedExtension, VersionTuple
47if TYPE_CHECKING:
48 from .._collection_summary import CollectionSummary
49 from ..queries import SqlQueryContext
50 from ._collections import CollectionManager, CollectionRecord, RunRecord
51 from ._database import Database, StaticTablesContext
52 from ._dimensions import DimensionRecordStorageManager
55class DatasetRecordStorage(ABC):
56 """An interface that manages the records associated with a particular
57 `DatasetType`.
59 Parameters
60 ----------
61 datasetType : `DatasetType`
62 Dataset type whose records this object manages.
63 """
65 def __init__(self, datasetType: DatasetType):
66 self.datasetType = datasetType
68 @abstractmethod
69 def insert(
70 self,
71 run: RunRecord,
72 dataIds: Iterable[DataCoordinate],
73 idGenerationMode: DatasetIdGenEnum = DatasetIdGenEnum.UNIQUE,
74 ) -> Iterator[DatasetRef]:
75 """Insert one or more dataset entries into the database.
77 Parameters
78 ----------
79 run : `RunRecord`
80 The record object describing the `~CollectionType.RUN` collection
81 this dataset will be associated with.
82 dataIds : `~collections.abc.Iterable` [ `DataCoordinate` ]
83 Expanded data IDs (`DataCoordinate` instances) for the
84 datasets to be added. The dimensions of all data IDs must be the
85 same as ``self.datasetType.dimensions``.
86 idMode : `DatasetIdGenEnum`
87 With `UNIQUE` each new dataset is inserted with its new unique ID.
88 With non-`UNIQUE` mode ID is computed from some combination of
89 dataset type, dataId, and run collection name; if the same ID is
90 already in the database then new record is not inserted.
92 Returns
93 -------
94 datasets : `~collections.abc.Iterable` [ `DatasetRef` ]
95 References to the inserted datasets.
96 """
97 raise NotImplementedError()
99 @abstractmethod
100 def import_(
101 self,
102 run: RunRecord,
103 datasets: Iterable[DatasetRef],
104 ) -> Iterator[DatasetRef]:
105 """Insert one or more dataset entries into the database.
107 Parameters
108 ----------
109 run : `RunRecord`
110 The record object describing the `~CollectionType.RUN` collection
111 this dataset will be associated with.
112 datasets : `~collections.abc.Iterable` of `DatasetRef`
113 Datasets to be inserted. Datasets can specify ``id`` attribute
114 which will be used for inserted datasets. All dataset IDs must
115 have the same type (`int` or `uuid.UUID`), if type of dataset IDs
116 does not match type supported by this class then IDs will be
117 ignored and new IDs will be generated by backend.
119 Returns
120 -------
121 datasets : `~collections.abc.Iterable` [ `DatasetRef` ]
122 References to the inserted or existing datasets.
124 Notes
125 -----
126 The ``datasetType`` and ``run`` attributes of datasets are supposed to
127 be identical across all datasets but this is not checked and it should
128 be enforced by higher level registry code. This method does not need
129 to use those attributes from datasets, only ``dataId`` and ``id`` are
130 relevant.
131 """
132 raise NotImplementedError()
134 @abstractmethod
135 def delete(self, datasets: Iterable[DatasetRef]) -> None:
136 """Fully delete the given datasets from the registry.
138 Parameters
139 ----------
140 datasets : `~collections.abc.Iterable` [ `DatasetRef` ]
141 Datasets to be deleted. All datasets must be resolved and have
142 the same `DatasetType` as ``self``.
144 Raises
145 ------
146 AmbiguousDatasetError
147 Raised if any of the given `DatasetRef` instances is unresolved.
148 """
149 raise NotImplementedError()
151 @abstractmethod
152 def associate(self, collection: CollectionRecord, datasets: Iterable[DatasetRef]) -> None:
153 """Associate one or more datasets with a collection.
155 Parameters
156 ----------
157 collection : `CollectionRecord`
158 The record object describing the collection. ``collection.type``
159 must be `~CollectionType.TAGGED`.
160 datasets : `~collections.abc.Iterable` [ `DatasetRef` ]
161 Datasets to be associated. All datasets must be resolved and have
162 the same `DatasetType` as ``self``.
164 Raises
165 ------
166 AmbiguousDatasetError
167 Raised if any of the given `DatasetRef` instances is unresolved.
169 Notes
170 -----
171 Associating a dataset with into collection that already contains a
172 different dataset with the same `DatasetType` and data ID will remove
173 the existing dataset from that collection.
175 Associating the same dataset into a collection multiple times is a
176 no-op, but is still not permitted on read-only databases.
177 """
178 raise NotImplementedError()
180 @abstractmethod
181 def disassociate(self, collection: CollectionRecord, datasets: Iterable[DatasetRef]) -> None:
182 """Remove one or more datasets from a collection.
184 Parameters
185 ----------
186 collection : `CollectionRecord`
187 The record object describing the collection. ``collection.type``
188 must be `~CollectionType.TAGGED`.
189 datasets : `~collections.abc.Iterable` [ `DatasetRef` ]
190 Datasets to be disassociated. All datasets must be resolved and
191 have the same `DatasetType` as ``self``.
193 Raises
194 ------
195 AmbiguousDatasetError
196 Raised if any of the given `DatasetRef` instances is unresolved.
197 """
198 raise NotImplementedError()
200 @abstractmethod
201 def certify(
202 self,
203 collection: CollectionRecord,
204 datasets: Iterable[DatasetRef],
205 timespan: Timespan,
206 context: SqlQueryContext,
207 ) -> None:
208 """Associate one or more datasets with a calibration collection and a
209 validity range within it.
211 Parameters
212 ----------
213 collection : `CollectionRecord`
214 The record object describing the collection. ``collection.type``
215 must be `~CollectionType.CALIBRATION`.
216 datasets : `~collections.abc.Iterable` [ `DatasetRef` ]
217 Datasets to be associated. All datasets must be resolved and have
218 the same `DatasetType` as ``self``.
219 timespan : `Timespan`
220 The validity range for these datasets within the collection.
222 Raises
223 ------
224 AmbiguousDatasetError
225 Raised if any of the given `DatasetRef` instances is unresolved.
226 ConflictingDefinitionError
227 Raised if the collection already contains a different dataset with
228 the same `DatasetType` and data ID and an overlapping validity
229 range.
230 CollectionTypeError
231 Raised if
232 ``collection.type is not CollectionType.CALIBRATION`` or if
233 ``self.datasetType.isCalibration() is False``.
234 """
235 raise NotImplementedError()
237 @abstractmethod
238 def decertify(
239 self,
240 collection: CollectionRecord,
241 timespan: Timespan,
242 *,
243 dataIds: Iterable[DataCoordinate] | None = None,
244 context: SqlQueryContext,
245 ) -> None:
246 """Remove or adjust datasets to clear a validity range within a
247 calibration collection.
249 Parameters
250 ----------
251 collection : `CollectionRecord`
252 The record object describing the collection. ``collection.type``
253 must be `~CollectionType.CALIBRATION`.
254 timespan : `Timespan`
255 The validity range to remove datasets from within the collection.
256 Datasets that overlap this range but are not contained by it will
257 have their validity ranges adjusted to not overlap it, which may
258 split a single dataset validity range into two.
259 dataIds : `~collections.abc.Iterable` [ `DataCoordinate` ], optional
260 Data IDs that should be decertified within the given validity range
261 If `None`, all data IDs for ``self.datasetType`` will be
262 decertified.
264 Raises
265 ------
266 CollectionTypeError
267 Raised if ``collection.type is not CollectionType.CALIBRATION``.
268 """
269 raise NotImplementedError()
271 @abstractmethod
272 def make_relation(
273 self,
274 *collections: CollectionRecord,
275 columns: Set[str],
276 context: SqlQueryContext,
277 ) -> Relation:
278 """Return a `sql.Relation` that represents a query for for this
279 `DatasetType` in one or more collections.
281 Parameters
282 ----------
283 *collections : `CollectionRecord`
284 The record object(s) describing the collection(s) to query. May
285 not be of type `CollectionType.CHAINED`. If multiple collections
286 are passed, the query will search all of them in an unspecified
287 order, and all collections must have the same type. Must include
288 at least one collection.
289 columns : `~collections.abc.Set` [ `str` ]
290 Columns to include in the relation. See `Query.find_datasets` for
291 most options, but this method supports one more:
293 - ``rank``: a calculated integer column holding the index of the
294 collection the dataset was found in, within the ``collections``
295 sequence given.
296 context : `SqlQueryContext`
297 The object that manages database connections, temporary tables and
298 relation engines for this query.
300 Returns
301 -------
302 relation : `~lsst.daf.relation.Relation`
303 Representation of the query.
304 """
305 raise NotImplementedError()
307 datasetType: DatasetType
308 """Dataset type whose records this object manages (`DatasetType`).
309 """
312class DatasetRecordStorageManager(VersionedExtension):
313 """An interface that manages the tables that describe datasets.
315 `DatasetRecordStorageManager` primarily serves as a container and factory
316 for `DatasetRecordStorage` instances, which each provide access to the
317 records for a different `DatasetType`.
318 """
320 def __init__(self, *, registry_schema_version: VersionTuple | None = None) -> None:
321 super().__init__(registry_schema_version=registry_schema_version)
323 @classmethod
324 @abstractmethod
325 def initialize(
326 cls,
327 db: Database,
328 context: StaticTablesContext,
329 *,
330 collections: CollectionManager,
331 dimensions: DimensionRecordStorageManager,
332 registry_schema_version: VersionTuple | None = None,
333 ) -> DatasetRecordStorageManager:
334 """Construct an instance of the manager.
336 Parameters
337 ----------
338 db : `Database`
339 Interface to the underlying database engine and namespace.
340 context : `StaticTablesContext`
341 Context object obtained from `Database.declareStaticTables`; used
342 to declare any tables that should always be present.
343 collections: `CollectionManager`
344 Manager object for the collections in this `Registry`.
345 dimensions : `DimensionRecordStorageManager`
346 Manager object for the dimensions in this `Registry`.
347 registry_schema_version : `VersionTuple` or `None`
348 Schema version of this extension as defined in registry.
350 Returns
351 -------
352 manager : `DatasetRecordStorageManager`
353 An instance of a concrete `DatasetRecordStorageManager` subclass.
354 """
355 raise NotImplementedError()
357 @classmethod
358 @abstractmethod
359 def getIdColumnType(cls) -> type:
360 """Return type used for columns storing dataset IDs.
362 This type is used for columns storing `DatasetRef.id` values, usually
363 a `type` subclass provided by SQLAlchemy.
365 Returns
366 -------
367 dtype : `type`
368 Type used for dataset identification in database.
369 """
370 raise NotImplementedError()
372 @classmethod
373 @abstractmethod
374 def supportsIdGenerationMode(cls, mode: DatasetIdGenEnum) -> bool:
375 """Test whether the given dataset ID generation mode is supported by
376 `insert`.
378 Parameters
379 ----------
380 mode : `DatasetIdGenEnum`
381 Enum value for the mode to test.
383 Returns
384 -------
385 supported : `bool`
386 Whether the given mode is supported.
387 """
388 raise NotImplementedError()
390 @classmethod
391 @abstractmethod
392 def addDatasetForeignKey(
393 cls,
394 tableSpec: ddl.TableSpec,
395 *,
396 name: str = "dataset",
397 constraint: bool = True,
398 onDelete: str | None = None,
399 **kwargs: Any,
400 ) -> ddl.FieldSpec:
401 """Add a foreign key (field and constraint) referencing the dataset
402 table.
404 Parameters
405 ----------
406 tableSpec : `ddl.TableSpec`
407 Specification for the table that should reference the dataset
408 table. Will be modified in place.
409 name: `str`, optional
410 A name to use for the prefix of the new field; the full name is
411 ``{name}_id``.
412 onDelete: `str`, optional
413 One of "CASCADE" or "SET NULL", indicating what should happen to
414 the referencing row if the collection row is deleted. `None`
415 indicates that this should be an integrity error.
416 constraint: `bool`, optional
417 If `False` (`True` is default), add a field that can be joined to
418 the dataset primary key, but do not add a foreign key constraint.
419 **kwargs
420 Additional keyword arguments are forwarded to the `ddl.FieldSpec`
421 constructor (only the ``name`` and ``dtype`` arguments are
422 otherwise provided).
424 Returns
425 -------
426 idSpec : `ddl.FieldSpec`
427 Specification for the ID field.
428 """
429 raise NotImplementedError()
431 @abstractmethod
432 def refresh(self) -> None:
433 """Ensure all other operations on this manager are aware of any
434 dataset types that may have been registered by other clients since
435 it was initialized or last refreshed.
436 """
437 raise NotImplementedError()
439 def __getitem__(self, name: str) -> DatasetRecordStorage:
440 """Return the object that provides access to the records associated
441 with the given `DatasetType` name.
443 This is simply a convenience wrapper for `find` that raises `KeyError`
444 when the dataset type is not found.
446 Returns
447 -------
448 records : `DatasetRecordStorage`
449 The object representing the records for the given dataset type.
451 Raises
452 ------
453 KeyError
454 Raised if there is no dataset type with the given name.
456 Notes
457 -----
458 Dataset types registered by another client of the same repository since
459 the last call to `initialize` or `refresh` may not be found.
460 """
461 result = self.find(name)
462 if result is None:
463 raise MissingDatasetTypeError(f"Dataset type with name '{name}' not found.")
464 return result
466 @abstractmethod
467 def find(self, name: str) -> DatasetRecordStorage | None:
468 """Return an object that provides access to the records associated with
469 the given `DatasetType` name, if one exists.
471 Parameters
472 ----------
473 name : `str`
474 Name of the dataset type.
476 Returns
477 -------
478 records : `DatasetRecordStorage` or `None`
479 The object representing the records for the given dataset type, or
480 `None` if there are no records for that dataset type.
482 Notes
483 -----
484 Dataset types registered by another client of the same repository since
485 the last call to `initialize` or `refresh` may not be found.
486 """
487 raise NotImplementedError()
489 @abstractmethod
490 def register(self, datasetType: DatasetType) -> tuple[DatasetRecordStorage, bool]:
491 """Ensure that this `Registry` can hold records for the given
492 `DatasetType`, creating new tables as necessary.
494 Parameters
495 ----------
496 datasetType : `DatasetType`
497 Dataset type for which a table should created (as necessary) and
498 an associated `DatasetRecordStorage` returned.
500 Returns
501 -------
502 records : `DatasetRecordStorage`
503 The object representing the records for the given dataset type.
504 inserted : `bool`
505 `True` if the dataset type did not exist in the registry before.
507 Notes
508 -----
509 This operation may not be invoked within a `Database.transaction`
510 context.
511 """
512 raise NotImplementedError()
514 @abstractmethod
515 def remove(self, name: str) -> None:
516 """Remove the dataset type.
518 Parameters
519 ----------
520 name : `str`
521 Name of the dataset type.
522 """
523 raise NotImplementedError()
525 @abstractmethod
526 def resolve_wildcard(
527 self,
528 expression: Any,
529 components: bool | None = False,
530 missing: list[str] | None = None,
531 explicit_only: bool = False,
532 components_deprecated: bool = True,
533 ) -> dict[DatasetType, list[str | None]]:
534 """Resolve a dataset type wildcard expression.
536 Parameters
537 ----------
538 expression
539 Expression to resolve. Will be passed to
540 `DatasetTypeWildcard.from_expression`.
541 components : `bool`, optional
542 If `True`, apply all expression patterns to component dataset type
543 names as well. If `False`, never apply patterns to components. If
544 `None`, apply patterns to components only if their parent
545 datasets were not matched by the expression. Fully-specified
546 component datasets (`str` or `DatasetType` instances) are always
547 included.
548 missing : `list` of `str`, optional
549 String dataset type names that were explicitly given (i.e. not
550 regular expression patterns) but not found will be appended to this
551 list, if it is provided.
552 explicit_only : `bool`, optional
553 If `True`, require explicit `DatasetType` instances or `str` names,
554 with `re.Pattern` instances deprecated and ``...`` prohibited.
555 components_deprecated : `bool`, optional
556 If `True`, this is a context in which component dataset support is
557 deprecated. This will result in a deprecation warning when
558 ``components=True`` or ``components=None`` and a component dataset
559 is matched. In the future this will become an error.
561 Returns
562 -------
563 dataset_types : `dict` [ `DatasetType`, `list` [ `None`, `str` ] ]
564 A mapping with resolved dataset types as keys and lists of
565 matched component names as values, where `None` indicates the
566 parent composite dataset type was matched.
567 """
568 raise NotImplementedError()
570 @abstractmethod
571 def getDatasetRef(self, id: DatasetId) -> DatasetRef | None:
572 """Return a `DatasetRef` for the given dataset primary key
573 value.
575 Parameters
576 ----------
577 id : `DatasetId`
578 Primary key value for the dataset.
580 Returns
581 -------
582 ref : `DatasetRef` or `None`
583 Object representing the dataset, or `None` if no dataset with the
584 given primary key values exists in this layer.
585 """
586 raise NotImplementedError()
588 @abstractmethod
589 def getCollectionSummary(self, collection: CollectionRecord) -> CollectionSummary:
590 """Return a summary for the given collection.
592 Parameters
593 ----------
594 collection : `CollectionRecord`
595 Record describing the collection for which a summary is to be
596 retrieved.
598 Returns
599 -------
600 summary : `CollectionSummary`
601 Summary of the dataset types and governor dimension values in
602 this collection.
603 """
604 raise NotImplementedError()
606 @abstractmethod
607 def ingest_date_dtype(self) -> type:
608 """Return type of the ``ingest_date`` column."""
609 raise NotImplementedError()