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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/>. 

21 

22# 

23# Design notes for this module are in 

24# doc/lsst.daf.butler/dev/dataCoordinate.py. 

25# 

26 

27from __future__ import annotations 

28 

29__all__ = ("DataCoordinate", "DataId", "DataIdKey", "DataIdValue") 

30 

31from abc import abstractmethod 

32import numbers 

33from typing import ( 

34 AbstractSet, 

35 Any, 

36 Dict, 

37 Iterator, 

38 Mapping, 

39 Optional, 

40 Tuple, 

41 TYPE_CHECKING, 

42 Union, 

43) 

44 

45from lsst.sphgeom import Region 

46from ..named import NamedKeyMapping, NameLookupMapping, NamedValueAbstractSet 

47from ..timespan import Timespan 

48from ._elements import Dimension, DimensionElement 

49from ._graph import DimensionGraph 

50from ._records import DimensionRecord 

51 

52if TYPE_CHECKING: # Imports needed only for type annotations; may be circular. 52 ↛ 53line 52 didn't jump to line 53, because the condition on line 52 was never true

53 from ._universe import DimensionUniverse 

54 

55DataIdKey = Union[str, Dimension] 

56"""Type annotation alias for the keys that can be used to index a 

57DataCoordinate. 

58""" 

59 

60DataIdValue = Union[str, int, None] 

61"""Type annotation alias for the values that can be present in a 

62DataCoordinate or other data ID. 

63""" 

64 

65 

66def _intersectRegions(*args: Region) -> Optional[Region]: 

67 """Return the intersection of several regions. 

68 

69 For internal use by `ExpandedDataCoordinate` only. 

70 

71 If no regions are provided, returns `None`. 

72 

73 This is currently a placeholder; it actually returns `NotImplemented` 

74 (it does *not* raise an exception) when multiple regions are given, which 

75 propagates to `ExpandedDataCoordinate`. This reflects the fact that we 

76 don't want to fail to construct an `ExpandedDataCoordinate` entirely when 

77 we can't compute its region, and at present we don't have a high-level use 

78 case for the regions of these particular data IDs. 

79 """ 

80 if len(args) == 0: 

81 return None 

82 elif len(args) == 1: 

83 return args[0] 

84 else: 

85 return NotImplemented 

86 

87 

88class DataCoordinate(NamedKeyMapping[Dimension, DataIdValue]): 

89 """An immutable data ID dictionary that guarantees that its key-value pairs 

90 identify at least all required dimensions in a `DimensionGraph`. 

91 

92 `DataCoordinateSet` itself is an ABC, but provides `staticmethod` factory 

93 functions for private concrete implementations that should be sufficient 

94 for most purposes. `standardize` is the most flexible and safe of these; 

95 the others (`makeEmpty`, `fromRequiredValues`, and `fromFullValues`) are 

96 more specialized and perform little or no checking of inputs. 

97 

98 Notes 

99 ----- 

100 Like any data ID class, `DataCoordinate` behaves like a dictionary, but 

101 with some subtleties: 

102 

103 - Both `Dimension` instances and `str` names thereof may be used as keys 

104 in lookup operations, but iteration (and `keys`) will yield `Dimension` 

105 instances. The `names` property can be used to obtain the corresponding 

106 `str` names. 

107 

108 - Lookups for implied dimensions (those in ``self.graph.implied``) are 

109 supported if and only if `hasFull` returns `True`, and are never 

110 included in iteration or `keys`. The `full` property may be used to 

111 obtain a mapping whose keys do include implied dimensions. 

112 

113 - Equality comparison with other mappings is supported, but it always 

114 considers only required dimensions (as well as requiring both operands 

115 to identify the same dimensions). This is not quite consistent with the 

116 way mappings usually work - normally differing keys imply unequal 

117 mappings - but it makes sense in this context because data IDs with the 

118 same values for required dimensions but different values for implied 

119 dimensions represent a serious problem with the data that 

120 `DataCoordinate` cannot generally recognize on its own, and a data ID 

121 that knows implied dimension values should still be able to compare as 

122 equal to one that does not. This is of course not the way comparisons 

123 between simple `dict` data IDs work, and hence using a `DataCoordinate` 

124 instance for at least one operand in any data ID comparison is strongly 

125 recommended. 

126 """ 

127 

128 __slots__ = () 

129 

130 @staticmethod 

131 def standardize( 

132 mapping: Optional[NameLookupMapping[Dimension, DataIdValue]] = None, 

133 *, 

134 graph: Optional[DimensionGraph] = None, 

135 universe: Optional[DimensionUniverse] = None, 

136 **kwargs: Any 

137 ) -> DataCoordinate: 

138 """Adapt an arbitrary mapping and/or additional arguments into a true 

139 `DataCoordinate`, or augment an existing one. 

140 

141 Parameters 

142 ---------- 

143 mapping : `~collections.abc.Mapping`, optional 

144 An informal data ID that maps dimensions or dimension names to 

145 their primary key values (may also be a true `DataCoordinate`). 

146 graph : `DimensionGraph` 

147 The dimensions to be identified by the new `DataCoordinate`. 

148 If not provided, will be inferred from the keys of ``mapping``, 

149 and ``universe`` must be provided unless ``mapping`` is already a 

150 `DataCoordinate`. 

151 universe : `DimensionUniverse` 

152 All known dimensions and their relationships; used to expand 

153 and validate dependencies when ``graph`` is not provided. 

154 **kwargs 

155 Additional keyword arguments are treated like additional key-value 

156 pairs in ``mapping``. 

157 

158 Returns 

159 ------- 

160 coordinate : `DataCoordinate` 

161 A validated `DataCoordinate` instance. 

162 

163 Raises 

164 ------ 

165 TypeError 

166 Raised if the set of optional arguments provided is not supported. 

167 KeyError 

168 Raised if a key-value pair for a required dimension is missing. 

169 """ 

170 d: Dict[str, DataIdValue] = {} 

171 if isinstance(mapping, DataCoordinate): 

172 if graph is None: 

173 if not kwargs: 

174 # Already standardized to exactly what we want. 

175 return mapping 

176 elif kwargs.keys().isdisjoint(graph.dimensions.names): 

177 # User provided kwargs, but told us not to use them by 

178 # passing in dimensions that are disjoint from those kwargs. 

179 # This is not necessarily user error - it's a useful pattern 

180 # to pass in all of the key-value pairs you have and let the 

181 # code here pull out only what it needs. 

182 return mapping.subset(graph) 

183 assert universe is None or universe == mapping.universe 

184 universe = mapping.universe 

185 d.update((name, mapping[name]) for name in mapping.graph.required.names) 

186 if mapping.hasFull(): 

187 d.update((name, mapping[name]) for name in mapping.graph.implied.names) 

188 elif isinstance(mapping, NamedKeyMapping): 

189 d.update(mapping.byName()) 

190 elif mapping is not None: 

191 d.update(mapping) 

192 d.update(kwargs) 

193 if graph is None: 

194 if universe is None: 

195 raise TypeError("universe must be provided if graph is not.") 

196 graph = DimensionGraph(universe, names=d.keys()) 

197 if not graph.dimensions: 

198 return DataCoordinate.makeEmpty(graph.universe) 

199 if d.keys() >= graph.dimensions.names: 

200 values = tuple(d[name] for name in graph._dataCoordinateIndices.keys()) 

201 else: 

202 try: 

203 values = tuple(d[name] for name in graph.required.names) 

204 except KeyError as err: 

205 raise KeyError(f"No value in data ID ({mapping}) for required dimension {err}.") from err 

206 # Some backends cannot handle numpy.int64 type which is a subclass of 

207 # numbers.Integral; convert that to int. 

208 values = tuple(int(val) if isinstance(val, numbers.Integral) # type: ignore 

209 else val for val in values) 

210 return _BasicTupleDataCoordinate(graph, values) 

211 

212 @staticmethod 

213 def makeEmpty(universe: DimensionUniverse) -> DataCoordinate: 

214 """Return an empty `DataCoordinate` that identifies the null set of 

215 dimensions. 

216 

217 Parameters 

218 ---------- 

219 universe : `DimensionUniverse` 

220 Universe to which this null dimension set belongs. 

221 

222 Returns 

223 ------- 

224 dataId : `DataCoordinate` 

225 A data ID object that identifies no dimensions. `hasFull` and 

226 `hasRecords` are guaranteed to return `True`, because both `full` 

227 and `records` are just empty mappings. 

228 """ 

229 return _ExpandedTupleDataCoordinate(universe.empty, (), {}) 

230 

231 @staticmethod 

232 def fromRequiredValues(graph: DimensionGraph, values: Tuple[DataIdValue, ...]) -> DataCoordinate: 

233 """Construct a `DataCoordinate` from a tuple of dimension values that 

234 identify only required dimensions. 

235 

236 This is a low-level interface with at most assertion-level checking of 

237 inputs. Most callers should use `standardize` instead. 

238 

239 Parameters 

240 ---------- 

241 graph : `DimensionGraph` 

242 Dimensions this data ID will identify. 

243 values : `tuple` [ `int` or `str` ] 

244 Tuple of primary key values corresponding to ``graph.required``, 

245 in that order. 

246 

247 Returns 

248 ------- 

249 dataId : `DataCoordinate` 

250 A data ID object that identifies the given dimensions. 

251 ``dataId.hasFull()`` will return `True` if and only if 

252 ``graph.implied`` is empty, and ``dataId.hasRecords()`` will never 

253 return `True`. 

254 """ 

255 assert len(graph.required) == len(values), \ 

256 f"Inconsistency between dimensions {graph.required} and required values {values}." 

257 return _BasicTupleDataCoordinate(graph, values) 

258 

259 @staticmethod 

260 def fromFullValues(graph: DimensionGraph, values: Tuple[DataIdValue, ...]) -> DataCoordinate: 

261 """Construct a `DataCoordinate` from a tuple of dimension values that 

262 identify all dimensions. 

263 

264 This is a low-level interface with at most assertion-level checking of 

265 inputs. Most callers should use `standardize` instead. 

266 

267 Parameters 

268 ---------- 

269 graph : `DimensionGraph` 

270 Dimensions this data ID will identify. 

271 values : `tuple` [ `int` or `str` ] 

272 Tuple of primary key values corresponding to 

273 ``itertools.chain(graph.required, graph.implied)``, in that order. 

274 Note that this is _not_ the same order as ``graph.dimensions``, 

275 though these contain the same elements. 

276 

277 Returns 

278 ------- 

279 dataId : `DataCoordinate` 

280 A data ID object that identifies the given dimensions. 

281 ``dataId.hasFull()`` will return `True` if and only if 

282 ``graph.implied`` is empty, and ``dataId.hasRecords()`` will never 

283 return `True`. 

284 """ 

285 assert len(graph.dimensions) == len(values), \ 

286 f"Inconsistency between dimensions {graph.dimensions} and full values {values}." 

287 return _BasicTupleDataCoordinate(graph, values) 

288 

289 def __hash__(self) -> int: 

290 return hash((self.graph,) + tuple(self[d.name] for d in self.graph.required)) 

291 

292 def __eq__(self, other: Any) -> bool: 

293 if not isinstance(other, DataCoordinate): 

294 other = DataCoordinate.standardize(other, universe=self.universe) 

295 return self.graph == other.graph and all(self[d.name] == other[d.name] for d in self.graph.required) 

296 

297 def __repr__(self) -> str: 

298 # We can't make repr yield something that could be exec'd here without 

299 # printing out the whole DimensionUniverse the graph is derived from. 

300 # So we print something that mostly looks like a dict, but doesn't 

301 # quote its keys: that's both more compact and something that can't 

302 # be mistaken for an actual dict or something that could be exec'd. 

303 return "{{{}}}".format( 

304 ', '.join(f"{d}: {self.get(d, '?')}" for d in self.graph.dimensions.names) 

305 ) 

306 

307 def __lt__(self, other: Any) -> bool: 

308 # Allow DataCoordinate to be sorted 

309 if not isinstance(other, type(self)): 

310 return NotImplemented 

311 # Form tuple of tuples for each DataCoordinate: 

312 # Unlike repr() we only use required keys here to ensure that 

313 # __eq__ can not be true simultaneously with __lt__ being true. 

314 self_kv = tuple(self.items()) 

315 other_kv = tuple(other.items()) 

316 

317 return self_kv < other_kv 

318 

319 def __iter__(self) -> Iterator[Dimension]: 

320 return iter(self.keys()) 

321 

322 def __len__(self) -> int: 

323 return len(self.keys()) 

324 

325 def keys(self) -> NamedValueAbstractSet[Dimension]: 

326 return self.graph.required 

327 

328 @property 

329 def names(self) -> AbstractSet[str]: 

330 """The names of the required dimensions identified by this data ID, in 

331 the same order as `keys` (`collections.abc.Set` [ `str` ]). 

332 """ 

333 return self.keys().names 

334 

335 @abstractmethod 

336 def subset(self, graph: DimensionGraph) -> DataCoordinate: 

337 """Return a `DataCoordinate` whose graph is a subset of ``self.graph``. 

338 

339 Parameters 

340 ---------- 

341 graph : `DimensionGraph` 

342 The dimensions identified by the returned `DataCoordinate`. 

343 

344 Returns 

345 ------- 

346 coordinate : `DataCoordinate` 

347 A `DataCoordinate` instance that identifies only the given 

348 dimensions. May be ``self`` if ``graph == self.graph``. 

349 

350 Raises 

351 ------ 

352 KeyError 

353 Raised if the primary key value for one or more required dimensions 

354 is unknown. This may happen if ``graph.issubset(self.graph)`` is 

355 `False`, or even if ``graph.issubset(self.graph)`` is `True`, if 

356 ``self.hasFull()`` is `False` and 

357 ``graph.required.issubset(self.graph.required)`` is `False`. As 

358 an example of the latter case, consider trying to go from a data ID 

359 with dimensions {instrument, physical_filter, band} to 

360 just {instrument, band}; band is implied by 

361 physical_filter and hence would have no value in the original data 

362 ID if ``self.hasFull()`` is `False`. 

363 

364 Notes 

365 ----- 

366 If `hasFull` and `hasRecords` return `True` on ``self``, they will 

367 return `True` (respectively) on the returned `DataCoordinate` as well. 

368 The converse does not hold. 

369 """ 

370 raise NotImplementedError() 

371 

372 @abstractmethod 

373 def expanded(self, records: NameLookupMapping[DimensionElement, Optional[DimensionRecord]] 

374 ) -> DataCoordinate: 

375 """Return a `DataCoordinate` that holds the given records and 

376 guarantees that `hasRecords` returns `True`. 

377 

378 This is a low-level interface with at most assertion-level checking of 

379 inputs. Most callers should use `Registry.expandDataId` instead. 

380 

381 Parameters 

382 ---------- 

383 records : `Mapping` [ `str`, `DimensionRecord` or `None` ] 

384 A `NamedKeyMapping` with `DimensionElement` keys or a regular 

385 `Mapping` with `str` (`DimensionElement` name) keys and 

386 `DimensionRecord` values. Keys must cover all elements in 

387 ``self.graph.elements``. Values may be `None`, but only to reflect 

388 actual NULL values in the database, not just records that have not 

389 been fetched. 

390 """ 

391 raise NotImplementedError() 

392 

393 @property 

394 def universe(self) -> DimensionUniverse: 

395 """The universe that defines all known dimensions compatible with 

396 this coordinate (`DimensionUniverse`). 

397 """ 

398 return self.graph.universe 

399 

400 @property 

401 @abstractmethod 

402 def graph(self) -> DimensionGraph: 

403 """The dimensions identified by this data ID (`DimensionGraph`). 

404 

405 Note that values are only required to be present for dimensions in 

406 ``self.graph.required``; all others may be retrieved (from a 

407 `Registry`) given these. 

408 """ 

409 raise NotImplementedError() 

410 

411 @abstractmethod 

412 def hasFull(self) -> bool: 

413 """Whether this data ID contains values for implied as well as 

414 required dimensions. 

415 

416 Returns 

417 ------- 

418 state : `bool` 

419 If `True`, `__getitem__`, `get`, and `__contains__` (but not 

420 `keys`!) will act as though the mapping includes key-value pairs 

421 for implied dimensions, and the `full` property may be used. If 

422 `False`, these operations only include key-value pairs for required 

423 dimensions, and accessing `full` is an error. Always `True` if 

424 there are no implied dimensions. 

425 """ 

426 raise NotImplementedError() 

427 

428 @property 

429 def full(self) -> NamedKeyMapping[Dimension, DataIdValue]: 

430 """A mapping that includes key-value pairs for all dimensions in 

431 ``self.graph``, including implied (`NamedKeyMapping`). 

432 

433 Accessing this attribute if `hasFull` returns `False` is a logic error 

434 that may raise an exception of unspecified type either immediately or 

435 when implied keys are accessed via the returned mapping, depending on 

436 the implementation and whether assertions are enabled. 

437 """ 

438 assert self.hasFull(), "full may only be accessed if hasRecords() returns True." 

439 return _DataCoordinateFullView(self) 

440 

441 @abstractmethod 

442 def hasRecords(self) -> bool: 

443 """Whether this data ID contains records for all of the dimension 

444 elements it identifies. 

445 

446 Returns 

447 ------- 

448 state : `bool` 

449 If `True`, the following attributes may be accessed: 

450 

451 - `records` 

452 - `region` 

453 - `timespan` 

454 - `pack` 

455 

456 If `False`, accessing any of these is considered a logic error. 

457 """ 

458 raise NotImplementedError() 

459 

460 @property 

461 def records(self) -> NamedKeyMapping[DimensionElement, Optional[DimensionRecord]]: 

462 """A mapping that contains `DimensionRecord` objects for all elements 

463 identified by this data ID (`NamedKeyMapping`). 

464 

465 The values of this mapping may be `None` if and only if there is no 

466 record for that element with these dimensions in the database (which 

467 means some foreign key field must have a NULL value). 

468 

469 Accessing this attribute if `hasRecords` returns `False` is a logic 

470 error that may raise an exception of unspecified type either 

471 immediately or when the returned mapping is used, depending on the 

472 implementation and whether assertions are enabled. 

473 """ 

474 assert self.hasRecords(), "records may only be accessed if hasRecords() returns True." 

475 return _DataCoordinateRecordsView(self) 

476 

477 @abstractmethod 

478 def _record(self, name: str) -> Optional[DimensionRecord]: 

479 """Protected implementation hook that backs the ``records`` attribute. 

480 

481 Parameters 

482 ---------- 

483 name : `str` 

484 The name of a `DimensionElement`, guaranteed to be in 

485 ``self.graph.elements.names``. 

486 

487 Returns 

488 ------- 

489 record : `DimensionRecord` or `None` 

490 The dimension record for the given element identified by this 

491 data ID, or `None` if there is no such record. 

492 """ 

493 raise NotImplementedError() 

494 

495 @property 

496 def region(self) -> Optional[Region]: 

497 """The spatial region associated with this data ID 

498 (`lsst.sphgeom.Region` or `None`). 

499 

500 This is `None` if and only if ``self.graph.spatial`` is empty. 

501 

502 Accessing this attribute if `hasRecords` returns `False` is a logic 

503 error that may or may not raise an exception, depending on the 

504 implementation and whether assertions are enabled. 

505 """ 

506 assert self.hasRecords(), "region may only be accessed if hasRecords() returns True." 

507 regions = [] 

508 for family in self.graph.spatial: 

509 element = family.choose(self.graph.elements) 

510 record = self._record(element.name) 

511 if record is None or record.region is None: 

512 return None 

513 else: 

514 regions.append(record.region) 

515 return _intersectRegions(*regions) 

516 

517 @property 

518 def timespan(self) -> Optional[Timespan]: 

519 """The temporal interval associated with this data ID 

520 (`Timespan` or `None`). 

521 

522 This is `None` if and only if ``self.graph.timespan`` is empty. 

523 

524 Accessing this attribute if `hasRecords` returns `False` is a logic 

525 error that may or may not raise an exception, depending on the 

526 implementation and whether assertions are enabled. 

527 """ 

528 assert self.hasRecords(), "timespan may only be accessed if hasRecords() returns True." 

529 timespans = [] 

530 for family in self.graph.temporal: 

531 element = family.choose(self.graph.elements) 

532 record = self._record(element.name) 

533 # DimensionRecord subclasses for temporal elements always have 

534 # .timespan, but they're dynamic so this can't be type-checked. 

535 if record is None or record.timespan is None: 

536 return None 

537 else: 

538 timespans.append(record.timespan) 

539 return Timespan.intersection(*timespans) 

540 

541 def pack(self, name: str, *, returnMaxBits: bool = False) -> Union[Tuple[int, int], int]: 

542 """Pack this data ID into an integer. 

543 

544 Parameters 

545 ---------- 

546 name : `str` 

547 Name of the `DimensionPacker` algorithm (as defined in the 

548 dimension configuration). 

549 returnMaxBits : `bool`, optional 

550 If `True` (`False` is default), return the maximum number of 

551 nonzero bits in the returned integer across all data IDs. 

552 

553 Returns 

554 ------- 

555 packed : `int` 

556 Integer ID. This ID is unique only across data IDs that have 

557 the same values for the packer's "fixed" dimensions. 

558 maxBits : `int`, optional 

559 Maximum number of nonzero bits in ``packed``. Not returned unless 

560 ``returnMaxBits`` is `True`. 

561 

562 Notes 

563 ----- 

564 Accessing this attribute if `hasRecords` returns `False` is a logic 

565 error that may or may not raise an exception, depending on the 

566 implementation and whether assertions are enabled. 

567 """ 

568 assert self.hasRecords(), "pack() may only be called if hasRecords() returns True." 

569 return self.universe.makePacker(name, self).pack(self, returnMaxBits=returnMaxBits) 

570 

571 

572DataId = Union[DataCoordinate, Mapping[str, Any]] 

573"""A type-annotation alias for signatures that accept both informal data ID 

574dictionaries and validated `DataCoordinate` instances. 

575""" 

576 

577 

578class _DataCoordinateFullView(NamedKeyMapping[Dimension, DataIdValue]): 

579 """View class that provides the default implementation for 

580 `DataCoordinate.full`. 

581 

582 Parameters 

583 ---------- 

584 target : `DataCoordinate` 

585 The `DataCoordinate` instance this object provides a view of. 

586 """ 

587 def __init__(self, target: DataCoordinate): 

588 self._target = target 

589 

590 __slots__ = ("_target",) 

591 

592 def __getitem__(self, key: DataIdKey) -> DataIdValue: 

593 return self._target[key] 

594 

595 def __iter__(self) -> Iterator[Dimension]: 

596 return iter(self.keys()) 

597 

598 def __len__(self) -> int: 

599 return len(self.keys()) 

600 

601 def keys(self) -> NamedValueAbstractSet[Dimension]: 

602 return self._target.graph.dimensions 

603 

604 @property 

605 def names(self) -> AbstractSet[str]: 

606 # Docstring inherited from `NamedKeyMapping`. 

607 return self.keys().names 

608 

609 

610class _DataCoordinateRecordsView(NamedKeyMapping[DimensionElement, Optional[DimensionRecord]]): 

611 """View class that provides the default implementation for 

612 `DataCoordinate.records`. 

613 

614 Parameters 

615 ---------- 

616 target : `DataCoordinate` 

617 The `DataCoordinate` instance this object provides a view of. 

618 """ 

619 def __init__(self, target: DataCoordinate): 

620 self._target = target 

621 

622 __slots__ = ("_target",) 

623 

624 def __getitem__(self, key: Union[DimensionElement, str]) -> Optional[DimensionRecord]: 

625 if isinstance(key, DimensionElement): 

626 key = key.name 

627 return self._target._record(key) 

628 

629 def __iter__(self) -> Iterator[DimensionElement]: 

630 return iter(self.keys()) 

631 

632 def __len__(self) -> int: 

633 return len(self.keys()) 

634 

635 def keys(self) -> NamedValueAbstractSet[DimensionElement]: 

636 return self._target.graph.elements 

637 

638 @property 

639 def names(self) -> AbstractSet[str]: 

640 # Docstring inherited from `NamedKeyMapping`. 

641 return self.keys().names 

642 

643 

644class _BasicTupleDataCoordinate(DataCoordinate): 

645 """Standard implementation of `DataCoordinate`, backed by a tuple of 

646 values. 

647 

648 This class should only be accessed outside this module via the 

649 `DataCoordinate` interface, and should only be constructed via the static 

650 methods there. 

651 

652 Parameters 

653 ---------- 

654 graph : `DimensionGraph` 

655 The dimensions to be identified. 

656 values : `tuple` [ `int` or `str` ] 

657 Data ID values, ordered to match ``graph._dataCoordinateIndices``. May 

658 include values for just required dimensions (which always come first) 

659 or all dimensions. 

660 """ 

661 def __init__(self, graph: DimensionGraph, values: Tuple[DataIdValue, ...]): 

662 self._graph = graph 

663 self._values = values 

664 

665 __slots__ = ("_graph", "_values") 

666 

667 @property 

668 def graph(self) -> DimensionGraph: 

669 # Docstring inherited from DataCoordinate. 

670 return self._graph 

671 

672 def __getitem__(self, key: DataIdKey) -> DataIdValue: 

673 # Docstring inherited from DataCoordinate. 

674 if isinstance(key, Dimension): 

675 key = key.name 

676 index = self._graph._dataCoordinateIndices[key] 

677 try: 

678 return self._values[index] 

679 except IndexError: 

680 # Caller asked for an implied dimension, but this object only has 

681 # values for the required ones. 

682 raise KeyError(key) 

683 

684 def subset(self, graph: DimensionGraph) -> DataCoordinate: 

685 # Docstring inherited from DataCoordinate. 

686 if self._graph == graph: 

687 return self 

688 elif self.hasFull() or self._graph.required >= graph.dimensions: 

689 return _BasicTupleDataCoordinate( 

690 graph, 

691 tuple(self[k] for k in graph._dataCoordinateIndices.keys()), 

692 ) 

693 else: 

694 return _BasicTupleDataCoordinate(graph, tuple(self[k] for k in graph.required.names)) 

695 

696 def expanded(self, records: NameLookupMapping[DimensionElement, Optional[DimensionRecord]] 

697 ) -> DataCoordinate: 

698 # Docstring inherited from DataCoordinate 

699 values = self._values 

700 if not self.hasFull(): 

701 # Extract a complete values tuple from the attributes of the given 

702 # records. It's possible for these to be inconsistent with 

703 # self._values (which is a serious problem, of course), but we've 

704 # documented this as a no-checking API. 

705 values += tuple(getattr(records[d.name], d.primaryKey.name) for d in self._graph.implied) 

706 return _ExpandedTupleDataCoordinate(self._graph, values, records) 

707 

708 def hasFull(self) -> bool: 

709 # Docstring inherited from DataCoordinate. 

710 return len(self._values) == len(self._graph._dataCoordinateIndices) 

711 

712 def hasRecords(self) -> bool: 

713 # Docstring inherited from DataCoordinate. 

714 return False 

715 

716 def _record(self, name: str) -> Optional[DimensionRecord]: 

717 # Docstring inherited from DataCoordinate. 

718 assert False 

719 

720 

721class _ExpandedTupleDataCoordinate(_BasicTupleDataCoordinate): 

722 """A `DataCoordinate` implementation that can hold `DimensionRecord` 

723 objects. 

724 

725 This class should only be accessed outside this module via the 

726 `DataCoordinate` interface, and should only be constructed via calls to 

727 `DataCoordinate.expanded`. 

728 

729 Parameters 

730 ---------- 

731 graph : `DimensionGraph` 

732 The dimensions to be identified. 

733 values : `tuple` [ `int` or `str` ] 

734 Data ID values, ordered to match ``graph._dataCoordinateIndices``. 

735 May include values for just required dimensions (which always come 

736 first) or all dimensions. 

737 records : `Mapping` [ `str`, `DimensionRecord` or `None` ] 

738 A `NamedKeyMapping` with `DimensionElement` keys or a regular 

739 `Mapping` with `str` (`DimensionElement` name) keys and 

740 `DimensionRecord` values. Keys must cover all elements in 

741 ``self.graph.elements``. Values may be `None`, but only to reflect 

742 actual NULL values in the database, not just records that have not 

743 been fetched. 

744 """ 

745 def __init__(self, graph: DimensionGraph, values: Tuple[DataIdValue, ...], 

746 records: NameLookupMapping[DimensionElement, Optional[DimensionRecord]]): 

747 super().__init__(graph, values) 

748 assert super().hasFull(), "This implementation requires full dimension records." 

749 self._records = records 

750 

751 __slots__ = ("_records",) 

752 

753 def subset(self, graph: DimensionGraph) -> DataCoordinate: 

754 # Docstring inherited from DataCoordinate. 

755 if self._graph == graph: 

756 return self 

757 return _ExpandedTupleDataCoordinate(graph, 

758 tuple(self[k] for k in graph._dataCoordinateIndices.keys()), 

759 records=self._records) 

760 

761 def expanded(self, records: NameLookupMapping[DimensionElement, Optional[DimensionRecord]] 

762 ) -> DataCoordinate: 

763 # Docstring inherited from DataCoordinate. 

764 return self 

765 

766 def hasFull(self) -> bool: 

767 # Docstring inherited from DataCoordinate. 

768 return True 

769 

770 def hasRecords(self) -> bool: 

771 # Docstring inherited from DataCoordinate. 

772 return True 

773 

774 def _record(self, name: str) -> Optional[DimensionRecord]: 

775 # Docstring inherited from DataCoordinate. 

776 return self._records[name]