Hide keyboard shortcuts

Hot-keys on this page

r m x p   toggle line displays

j k   next/prev highlighted chunk

0   (zero) top of page

1   (one) first highlighted chunk

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 terms = [f"{d}: {self[d]!r}" for d in self.graph.required.names] 

304 if self.hasFull(): 

305 terms.append("...") 

306 return "{{{}}}".format(', '.join(terms)) 

307 

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

309 # Allow DataCoordinate to be sorted 

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

311 return NotImplemented 

312 # Form tuple of tuples for each DataCoordinate: 

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

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

315 self_kv = tuple(self.items()) 

316 other_kv = tuple(other.items()) 

317 

318 return self_kv < other_kv 

319 

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

321 return iter(self.keys()) 

322 

323 def __len__(self) -> int: 

324 return len(self.keys()) 

325 

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

327 return self.graph.required 

328 

329 @property 

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

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

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

333 """ 

334 return self.keys().names 

335 

336 @abstractmethod 

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

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

339 

340 Parameters 

341 ---------- 

342 graph : `DimensionGraph` 

343 The dimensions identified by the returned `DataCoordinate`. 

344 

345 Returns 

346 ------- 

347 coordinate : `DataCoordinate` 

348 A `DataCoordinate` instance that identifies only the given 

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

350 

351 Raises 

352 ------ 

353 KeyError 

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

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

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

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

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

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

360 with dimensions {instrument, physical_filter, band} to 

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

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

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

364 

365 Notes 

366 ----- 

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

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

369 The converse does not hold. 

370 """ 

371 raise NotImplementedError() 

372 

373 @abstractmethod 

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

375 ) -> DataCoordinate: 

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

377 guarantees that `hasRecords` returns `True`. 

378 

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

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

381 

382 Parameters 

383 ---------- 

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

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

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

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

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

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

390 been fetched. 

391 """ 

392 raise NotImplementedError() 

393 

394 @property 

395 def universe(self) -> DimensionUniverse: 

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

397 this coordinate (`DimensionUniverse`). 

398 """ 

399 return self.graph.universe 

400 

401 @property 

402 @abstractmethod 

403 def graph(self) -> DimensionGraph: 

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

405 

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

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

408 `Registry`) given these. 

409 """ 

410 raise NotImplementedError() 

411 

412 @abstractmethod 

413 def hasFull(self) -> bool: 

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

415 required dimensions. 

416 

417 Returns 

418 ------- 

419 state : `bool` 

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

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

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

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

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

425 there are no implied dimensions. 

426 """ 

427 raise NotImplementedError() 

428 

429 @property 

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

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

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

433 

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

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

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

437 the implementation and whether assertions are enabled. 

438 """ 

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

440 return _DataCoordinateFullView(self) 

441 

442 @abstractmethod 

443 def hasRecords(self) -> bool: 

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

445 elements it identifies. 

446 

447 Returns 

448 ------- 

449 state : `bool` 

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

451 

452 - `records` 

453 - `region` 

454 - `timespan` 

455 - `pack` 

456 

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

458 """ 

459 raise NotImplementedError() 

460 

461 @property 

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

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

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

465 

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

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

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

469 

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

471 error that may raise an exception of unspecified type either 

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

473 implementation and whether assertions are enabled. 

474 """ 

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

476 return _DataCoordinateRecordsView(self) 

477 

478 @abstractmethod 

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

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

481 

482 Parameters 

483 ---------- 

484 name : `str` 

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

486 ``self.graph.elements.names``. 

487 

488 Returns 

489 ------- 

490 record : `DimensionRecord` or `None` 

491 The dimension record for the given element identified by this 

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

493 """ 

494 raise NotImplementedError() 

495 

496 @property 

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

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

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

500 

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

502 

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

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

505 implementation and whether assertions are enabled. 

506 """ 

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

508 regions = [] 

509 for family in self.graph.spatial: 

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

511 record = self._record(element.name) 

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

513 return None 

514 else: 

515 regions.append(record.region) 

516 return _intersectRegions(*regions) 

517 

518 @property 

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

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

521 (`Timespan` or `None`). 

522 

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

524 

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

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

527 implementation and whether assertions are enabled. 

528 """ 

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

530 timespans = [] 

531 for family in self.graph.temporal: 

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

533 record = self._record(element.name) 

534 # DimensionRecord subclasses for temporal elements always have 

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

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

537 return None 

538 else: 

539 timespans.append(record.timespan) 

540 return Timespan.intersection(*timespans) 

541 

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

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

544 

545 Parameters 

546 ---------- 

547 name : `str` 

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

549 dimension configuration). 

550 returnMaxBits : `bool`, optional 

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

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

553 

554 Returns 

555 ------- 

556 packed : `int` 

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

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

559 maxBits : `int`, optional 

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

561 ``returnMaxBits`` is `True`. 

562 

563 Notes 

564 ----- 

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

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

567 implementation and whether assertions are enabled. 

568 """ 

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

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

571 

572 

573DataId = Union[DataCoordinate, Mapping[str, Any]] 

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

575dictionaries and validated `DataCoordinate` instances. 

576""" 

577 

578 

579class _DataCoordinateFullView(NamedKeyMapping[Dimension, DataIdValue]): 

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

581 `DataCoordinate.full`. 

582 

583 Parameters 

584 ---------- 

585 target : `DataCoordinate` 

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

587 """ 

588 def __init__(self, target: DataCoordinate): 

589 self._target = target 

590 

591 __slots__ = ("_target",) 

592 

593 def __repr__(self) -> str: 

594 terms = [f"{d}: {self[d]!r}" for d in self._target.graph.dimensions.names] 

595 return "{{{}}}".format(', '.join(terms)) 

596 

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

598 return self._target[key] 

599 

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

601 return iter(self.keys()) 

602 

603 def __len__(self) -> int: 

604 return len(self.keys()) 

605 

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

607 return self._target.graph.dimensions 

608 

609 @property 

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

611 # Docstring inherited from `NamedKeyMapping`. 

612 return self.keys().names 

613 

614 

615class _DataCoordinateRecordsView(NamedKeyMapping[DimensionElement, Optional[DimensionRecord]]): 

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

617 `DataCoordinate.records`. 

618 

619 Parameters 

620 ---------- 

621 target : `DataCoordinate` 

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

623 """ 

624 def __init__(self, target: DataCoordinate): 

625 self._target = target 

626 

627 __slots__ = ("_target",) 

628 

629 def __repr__(self) -> str: 

630 terms = [f"{d}: {self[d]!r}" for d in self._target.graph.elements.names] 

631 return "{{{}}}".format(', '.join(terms)) 

632 

633 def __str__(self) -> str: 

634 return "\n".join(str(v) for v in self.values()) 

635 

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

637 if isinstance(key, DimensionElement): 

638 key = key.name 

639 return self._target._record(key) 

640 

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

642 return iter(self.keys()) 

643 

644 def __len__(self) -> int: 

645 return len(self.keys()) 

646 

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

648 return self._target.graph.elements 

649 

650 @property 

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

652 # Docstring inherited from `NamedKeyMapping`. 

653 return self.keys().names 

654 

655 

656class _BasicTupleDataCoordinate(DataCoordinate): 

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

658 values. 

659 

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

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

662 methods there. 

663 

664 Parameters 

665 ---------- 

666 graph : `DimensionGraph` 

667 The dimensions to be identified. 

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

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

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

671 or all dimensions. 

672 """ 

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

674 self._graph = graph 

675 self._values = values 

676 

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

678 

679 @property 

680 def graph(self) -> DimensionGraph: 

681 # Docstring inherited from DataCoordinate. 

682 return self._graph 

683 

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

685 # Docstring inherited from DataCoordinate. 

686 if isinstance(key, Dimension): 

687 key = key.name 

688 index = self._graph._dataCoordinateIndices[key] 

689 try: 

690 return self._values[index] 

691 except IndexError: 

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

693 # values for the required ones. 

694 raise KeyError(key) 

695 

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

697 # Docstring inherited from DataCoordinate. 

698 if self._graph == graph: 

699 return self 

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

701 return _BasicTupleDataCoordinate( 

702 graph, 

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

704 ) 

705 else: 

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

707 

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

709 ) -> DataCoordinate: 

710 # Docstring inherited from DataCoordinate 

711 values = self._values 

712 if not self.hasFull(): 

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

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

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

716 # documented this as a no-checking API. 

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

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

719 

720 def hasFull(self) -> bool: 

721 # Docstring inherited from DataCoordinate. 

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

723 

724 def hasRecords(self) -> bool: 

725 # Docstring inherited from DataCoordinate. 

726 return False 

727 

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

729 # Docstring inherited from DataCoordinate. 

730 assert False 

731 

732 

733class _ExpandedTupleDataCoordinate(_BasicTupleDataCoordinate): 

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

735 objects. 

736 

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

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

739 `DataCoordinate.expanded`. 

740 

741 Parameters 

742 ---------- 

743 graph : `DimensionGraph` 

744 The dimensions to be identified. 

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

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

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

748 first) or all dimensions. 

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

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

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

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

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

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

755 been fetched. 

756 """ 

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

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

759 super().__init__(graph, values) 

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

761 self._records = records 

762 

763 __slots__ = ("_records",) 

764 

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

766 # Docstring inherited from DataCoordinate. 

767 if self._graph == graph: 

768 return self 

769 return _ExpandedTupleDataCoordinate(graph, 

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

771 records=self._records) 

772 

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

774 ) -> DataCoordinate: 

775 # Docstring inherited from DataCoordinate. 

776 return self 

777 

778 def hasFull(self) -> bool: 

779 # Docstring inherited from DataCoordinate. 

780 return True 

781 

782 def hasRecords(self) -> bool: 

783 # Docstring inherited from DataCoordinate. 

784 return True 

785 

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

787 # Docstring inherited from DataCoordinate. 

788 return self._records[name]