Coverage for python/lsst/daf/butler/registry/interfaces/_datasets.py : 57%

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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__all__ = ("DatasetRecordStorageManager", "DatasetRecordStorage")
26from abc import ABC, abstractmethod
27from typing import (
28 Any,
29 Iterable,
30 Iterator,
31 Optional,
32 Tuple,
33 TYPE_CHECKING,
34)
36from ...core import (
37 DataCoordinate,
38 DatasetRef,
39 DatasetType,
40 ddl,
41 SimpleQuery,
42 Timespan,
43)
44from ._versioning import VersionedExtension
46if TYPE_CHECKING: 46 ↛ 47line 46 didn't jump to line 47, because the condition on line 46 was never true
47 from ._database import Database, StaticTablesContext
48 from ._dimensions import DimensionRecordStorageManager
49 from ._collections import CollectionManager, CollectionRecord, RunRecord
52class DatasetRecordStorage(ABC):
53 """An interface that manages the records associated with a particular
54 `DatasetType`.
56 Parameters
57 ----------
58 datasetType : `DatasetType`
59 Dataset type whose records this object manages.
60 """
61 def __init__(self, datasetType: DatasetType):
62 self.datasetType = datasetType
64 @abstractmethod
65 def insert(self, run: RunRecord, dataIds: Iterable[DataCoordinate]) -> Iterator[DatasetRef]:
66 """Insert one or more dataset entries into the database.
68 Parameters
69 ----------
70 run : `RunRecord`
71 The record object describing the `~CollectionType.RUN` collection
72 this dataset will be associated with.
73 dataIds : `Iterable` [ `DataCoordinate` ]
74 Expanded data IDs (`DataCoordinate` instances) for the
75 datasets to be added. The dimensions of all data IDs must be the
76 same as ``self.datasetType.dimensions``.
78 Returns
79 -------
80 datasets : `Iterable` [ `DatasetRef` ]
81 References to the inserted datasets.
82 """
83 raise NotImplementedError()
85 @abstractmethod
86 def find(self, collection: CollectionRecord, dataId: DataCoordinate,
87 timespan: Optional[Timespan] = None) -> Optional[DatasetRef]:
88 """Search a collection for a dataset with the given data ID.
90 Parameters
91 ----------
92 collection : `CollectionRecord`
93 The record object describing the collection to search for the
94 dataset. May have any `CollectionType`.
95 dataId: `DataCoordinate`
96 Complete (but not necessarily expanded) data ID to search with,
97 with ``dataId.graph == self.datasetType.dimensions``.
98 timespan : `Timespan`, optional
99 A timespan that the validity range of the dataset must overlap.
100 Required if ``collection.type is CollectionType.CALIBRATION``, and
101 ignored otherwise.
103 Returns
104 -------
105 ref : `DatasetRef`
106 A resolved `DatasetRef` (without components populated), or `None`
107 if no matching dataset was found.
108 """
109 raise NotImplementedError()
111 @abstractmethod
112 def delete(self, datasets: Iterable[DatasetRef]) -> None:
113 """Fully delete the given datasets from the registry.
115 Parameters
116 ----------
117 datasets : `Iterable` [ `DatasetRef` ]
118 Datasets to be deleted. All datasets must be resolved and have
119 the same `DatasetType` as ``self``.
121 Raises
122 ------
123 AmbiguousDatasetError
124 Raised if any of the given `DatasetRef` instances is unresolved.
125 """
126 raise NotImplementedError()
128 @abstractmethod
129 def associate(self, collection: CollectionRecord, datasets: Iterable[DatasetRef]) -> None:
130 """Associate one or more datasets with a collection.
132 Parameters
133 ----------
134 collection : `CollectionRecord`
135 The record object describing the collection. ``collection.type``
136 must be `~CollectionType.TAGGED`.
137 datasets : `Iterable` [ `DatasetRef` ]
138 Datasets to be associated. All datasets must be resolved and have
139 the same `DatasetType` as ``self``.
141 Raises
142 ------
143 AmbiguousDatasetError
144 Raised if any of the given `DatasetRef` instances is unresolved.
146 Notes
147 -----
148 Associating a dataset with into collection that already contains a
149 different dataset with the same `DatasetType` and data ID will remove
150 the existing dataset from that collection.
152 Associating the same dataset into a collection multiple times is a
153 no-op, but is still not permitted on read-only databases.
154 """
155 raise NotImplementedError()
157 @abstractmethod
158 def disassociate(self, collection: CollectionRecord, datasets: Iterable[DatasetRef]) -> None:
159 """Remove one or more datasets from a collection.
161 Parameters
162 ----------
163 collection : `CollectionRecord`
164 The record object describing the collection. ``collection.type``
165 must be `~CollectionType.TAGGED`.
166 datasets : `Iterable` [ `DatasetRef` ]
167 Datasets to be disassociated. All datasets must be resolved and
168 have the same `DatasetType` as ``self``.
170 Raises
171 ------
172 AmbiguousDatasetError
173 Raised if any of the given `DatasetRef` instances is unresolved.
174 """
175 raise NotImplementedError()
177 @abstractmethod
178 def certify(self, collection: CollectionRecord, datasets: Iterable[DatasetRef],
179 timespan: Timespan) -> None:
180 """Associate one or more datasets with a calibration collection and a
181 validity range within it.
183 Parameters
184 ----------
185 collection : `CollectionRecord`
186 The record object describing the collection. ``collection.type``
187 must be `~CollectionType.CALIBRATION`.
188 datasets : `Iterable` [ `DatasetRef` ]
189 Datasets to be associated. All datasets must be resolved and have
190 the same `DatasetType` as ``self``.
191 timespan : `Timespan`
192 The validity range for these datasets within the collection.
194 Raises
195 ------
196 AmbiguousDatasetError
197 Raised if any of the given `DatasetRef` instances is unresolved.
198 ConflictingDefinitionError
199 Raised if the collection already contains a different dataset with
200 the same `DatasetType` and data ID and an overlapping validity
201 range.
202 TypeError
203 Raised if
204 ``collection.type is not CollectionType.CALIBRATION`` or if
205 ``self.datasetType.isCalibration() is False``.
206 """
207 raise NotImplementedError()
209 @abstractmethod
210 def decertify(self, collection: CollectionRecord, timespan: Timespan, *,
211 dataIds: Optional[Iterable[DataCoordinate]] = None) -> None:
212 """Remove or adjust datasets to clear a validity range within a
213 calibration collection.
215 Parameters
216 ----------
217 collection : `CollectionRecord`
218 The record object describing the collection. ``collection.type``
219 must be `~CollectionType.CALIBRATION`.
220 timespan : `Timespan`
221 The validity range to remove datasets from within the collection.
222 Datasets that overlap this range but are not contained by it will
223 have their validity ranges adjusted to not overlap it, which may
224 split a single dataset validity range into two.
225 dataIds : `Iterable` [ `DataCoordinate` ], optional
226 Data IDs that should be decertified within the given validity range
227 If `None`, all data IDs for ``self.datasetType`` will be
228 decertified.
230 Raises
231 ------
232 TypeError
233 Raised if ``collection.type is not CollectionType.CALIBRATION``.
234 """
235 raise NotImplementedError()
237 @abstractmethod
238 def select(self, collection: CollectionRecord,
239 dataId: SimpleQuery.Select.Or[DataCoordinate] = SimpleQuery.Select,
240 id: SimpleQuery.Select.Or[Optional[int]] = SimpleQuery.Select,
241 run: SimpleQuery.Select.Or[None] = SimpleQuery.Select,
242 timespan: SimpleQuery.Select.Or[Optional[Timespan]] = SimpleQuery.Select,
243 ingestDate: SimpleQuery.Select.Or[Optional[Timespan]] = None,
244 ) -> Optional[SimpleQuery]:
245 """Return a SQLAlchemy object that represents a ``SELECT`` query for
246 this `DatasetType`.
248 All arguments can either be a value that constrains the query or
249 the `SimpleQuery.Select` tag object to indicate that the value should
250 be returned in the columns in the ``SELECT`` clause. The default is
251 `SimpleQuery.Select`.
253 Parameters
254 ----------
255 collection : `CollectionRecord`
256 The record object describing the collection to query. May not be
257 of type `CollectionType.CHAINED`.
258 dataId : `DataCoordinate` or `Select`
259 The data ID to restrict results with, or an instruction to return
260 the data ID via columns with names
261 ``self.datasetType.dimensions.names``.
262 id : `int`, `Select` or None,
263 The integer primary key value for the dataset, an instruction to
264 return it via a ``id`` column, or `None` to ignore it
265 entirely.
266 run : `None` or `Select`
267 If `Select` (default), include the dataset's run key value (as
268 column labeled with the return value of
269 ``CollectionManager.getRunForiegnKeyName``).
270 If `None`, do not include this column (to constrain the run,
271 pass a `RunRecord` as the ``collection`` argument instead).
272 timespan : `None`, `Select`, or `Timespan`
273 If `Select` (default), include the validity range timespan in the
274 result columns. If a `Timespan` instance, constrain the results to
275 those whose validity ranges overlap that given timespan. Ignored
276 unless ``collection.type is CollectionType.CALIBRATION``.
277 ingestDate : `None`, `Select`, or `Timespan`
278 If `Select` include the ingest timestamp in the result columns.
279 If a `Timespan` instance, constrain the results to those whose
280 ingest times which are inside given timespan and also include
281 timestamp in the result columns. If `None` (default) then there is
282 no constraint and timestamp is not returned.
284 Returns
285 -------
286 query : `SimpleQuery` or `None`
287 A struct containing the SQLAlchemy object that representing a
288 simple ``SELECT`` query, or `None` if it is known that there are
289 no datasets of this `DatasetType` that match the given constraints.
290 """
291 raise NotImplementedError()
293 datasetType: DatasetType
294 """Dataset type whose records this object manages (`DatasetType`).
295 """
298class DatasetRecordStorageManager(VersionedExtension):
299 """An interface that manages the tables that describe datasets.
301 `DatasetRecordStorageManager` primarily serves as a container and factory
302 for `DatasetRecordStorage` instances, which each provide access to the
303 records for a different `DatasetType`.
304 """
306 @classmethod
307 @abstractmethod
308 def initialize(
309 cls,
310 db: Database,
311 context: StaticTablesContext, *,
312 collections: CollectionManager,
313 dimensions: DimensionRecordStorageManager,
314 ) -> DatasetRecordStorageManager:
315 """Construct an instance of the manager.
317 Parameters
318 ----------
319 db : `Database`
320 Interface to the underlying database engine and namespace.
321 context : `StaticTablesContext`
322 Context object obtained from `Database.declareStaticTables`; used
323 to declare any tables that should always be present.
324 collections: `CollectionManager`
325 Manager object for the collections in this `Registry`.
326 dimensions : `DimensionRecordStorageManager`
327 Manager object for the dimensions in this `Registry`.
329 Returns
330 -------
331 manager : `DatasetRecordStorageManager`
332 An instance of a concrete `DatasetRecordStorageManager` subclass.
333 """
334 raise NotImplementedError()
336 @classmethod
337 @abstractmethod
338 def addDatasetForeignKey(cls, tableSpec: ddl.TableSpec, *,
339 name: str = "dataset", constraint: bool = True, onDelete: Optional[str] = None,
340 **kwargs: Any) -> ddl.FieldSpec:
341 """Add a foreign key (field and constraint) referencing the dataset
342 table.
344 Parameters
345 ----------
346 tableSpec : `ddl.TableSpec`
347 Specification for the table that should reference the dataset
348 table. Will be modified in place.
349 name: `str`, optional
350 A name to use for the prefix of the new field; the full name is
351 ``{name}_id``.
352 onDelete: `str`, optional
353 One of "CASCADE" or "SET NULL", indicating what should happen to
354 the referencing row if the collection row is deleted. `None`
355 indicates that this should be an integrity error.
356 constraint: `bool`, optional
357 If `False` (`True` is default), add a field that can be joined to
358 the dataset primary key, but do not add a foreign key constraint.
359 **kwargs
360 Additional keyword arguments are forwarded to the `ddl.FieldSpec`
361 constructor (only the ``name`` and ``dtype`` arguments are
362 otherwise provided).
364 Returns
365 -------
366 idSpec : `ddl.FieldSpec`
367 Specification for the ID field.
368 """
369 raise NotImplementedError()
371 @abstractmethod
372 def refresh(self) -> None:
373 """Ensure all other operations on this manager are aware of any
374 dataset types that may have been registered by other clients since
375 it was initialized or last refreshed.
376 """
377 raise NotImplementedError()
379 def __getitem__(self, name: str) -> DatasetRecordStorage:
380 """Return the object that provides access to the records associated
381 with the given `DatasetType` name.
383 This is simply a convenience wrapper for `find` that raises `KeyError`
384 when the dataset type is not found.
386 Returns
387 -------
388 records : `DatasetRecordStorage`
389 The object representing the records for the given dataset type.
391 Raises
392 ------
393 KeyError
394 Raised if there is no dataset type with the given name.
396 Notes
397 -----
398 Dataset types registered by another client of the same repository since
399 the last call to `initialize` or `refresh` may not be found.
400 """
401 result = self.find(name)
402 if result is None:
403 raise KeyError(f"Dataset type with name '{name}' not found.")
404 return result
406 @abstractmethod
407 def find(self, name: str) -> Optional[DatasetRecordStorage]:
408 """Return an object that provides access to the records associated with
409 the given `DatasetType` name, if one exists.
411 Parameters
412 ----------
413 name : `str`
414 Name of the dataset type.
416 Returns
417 -------
418 records : `DatasetRecordStorage` or `None`
419 The object representing the records for the given dataset type, or
420 `None` if there are no records for that dataset type.
422 Notes
423 -----
424 Dataset types registered by another client of the same repository since
425 the last call to `initialize` or `refresh` may not be found.
426 """
427 raise NotImplementedError()
429 @abstractmethod
430 def register(self, datasetType: DatasetType) -> Tuple[DatasetRecordStorage, bool]:
431 """Ensure that this `Registry` can hold records for the given
432 `DatasetType`, creating new tables as necessary.
434 Parameters
435 ----------
436 datasetType : `DatasetType`
437 Dataset type for which a table should created (as necessary) and
438 an associated `DatasetRecordStorage` returned.
440 Returns
441 -------
442 records : `DatasetRecordStorage`
443 The object representing the records for the given dataset type.
444 inserted : `bool`
445 `True` if the dataset type did not exist in the registry before.
447 Notes
448 -----
449 This operation may not be invoked within a `Database.transaction`
450 context.
451 """
452 raise NotImplementedError()
454 @abstractmethod
455 def remove(self, name: str) -> None:
456 """Remove the dataset type.
458 Parameters
459 ----------
460 name : `str`
461 Name of the dataset type.
462 """
463 raise NotImplementedError()
465 @abstractmethod
466 def __iter__(self) -> Iterator[DatasetType]:
467 """Return an iterator over the the dataset types present in this layer.
469 Notes
470 -----
471 Dataset types registered by another client of the same layer since
472 the last call to `initialize` or `refresh` may not be included.
473 """
474 raise NotImplementedError()
476 @abstractmethod
477 def getDatasetRef(self, id: int) -> Optional[DatasetRef]:
478 """Return a `DatasetRef` for the given dataset primary key
479 value.
481 Parameters
482 ----------
483 id : `int`
484 Autoincrement primary key value for the dataset.
486 Returns
487 -------
488 ref : `DatasetRef` or `None`
489 Object representing the dataset, or `None` if no dataset with the
490 given primary key values exists in this layer.
491 """
492 raise NotImplementedError()