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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/>.
22#
23# Design notes for this module are in
24# doc/lsst.daf.butler/dev/dataCoordinate.py.
25#
27from __future__ import annotations
29__all__ = ("DataCoordinate", "DataId")
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)
45from lsst.sphgeom import Region
46from ..named import NamedKeyMapping, NameLookupMapping, NamedValueSet
47from ..timespan import Timespan
48from .elements import Dimension, DimensionElement
49from .graph import DimensionGraph
50from .records import DimensionRecord
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
55DataIdKey = Union[str, Dimension]
56"""Type annotation alias for the keys that can be used to index a
57DataCoordinate.
58"""
60DataIdValue = Union[str, int, None]
61"""Type annotation alias for the values that can be present in a
62DataCoordinate or other data ID.
63"""
66def _intersectRegions(*args: Region) -> Optional[Region]:
67 """Return the intersection of several regions.
69 For internal use by `ExpandedDataCoordinate` only.
71 If no regions are provided, returns `None`.
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
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`.
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.
98 Notes
99 -----
100 Like any data ID class, `DataCoordinate` behaves like a dictionary, but
101 with some subtleties:
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.
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.
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 """
128 __slots__ = ()
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.
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``.
158 Returns
159 -------
160 coordinate : `DataCoordinate`
161 A validated `DataCoordinate` instance.
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)
212 @staticmethod
213 def makeEmpty(universe: DimensionUniverse) -> DataCoordinate:
214 """Return an empty `DataCoordinate` that identifies the null set of
215 dimensions.
217 Parameters
218 ----------
219 universe : `DimensionUniverse`
220 Universe to which this null dimension set belongs.
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, (), {})
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.
236 This is a low-level interface with at most assertion-level checking of
237 inputs. Most callers should use `standardize` instead.
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.
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)
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.
264 This is a low-level interface with at most assertion-level checking of
265 inputs. Most callers should use `standardize` instead.
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.
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)
289 def __hash__(self) -> int:
290 return hash((self.graph,) + tuple(self[d.name] for d in self.graph.required))
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)
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 )
307 def __iter__(self) -> Iterator[Dimension]:
308 return iter(self.keys())
310 def __len__(self) -> int:
311 return len(self.keys())
313 def keys(self) -> NamedValueSet[Dimension]:
314 return self.graph.required
316 @property
317 def names(self) -> AbstractSet[str]:
318 """The names of the required dimensions identified by this data ID, in
319 the same order as `keys` (`collections.abc.Set` [ `str` ]).
320 """
321 return self.keys().names
323 @abstractmethod
324 def subset(self, graph: DimensionGraph) -> DataCoordinate:
325 """Return a `DataCoordinate` whose graph is a subset of ``self.graph``.
327 Parameters
328 ----------
329 graph : `DimensionGraph`
330 The dimensions identified by the returned `DataCoordinate`.
332 Returns
333 -------
334 coordinate : `DataCoordinate`
335 A `DataCoordinate` instance that identifies only the given
336 dimensions. May be ``self`` if ``graph == self.graph``.
338 Raises
339 ------
340 KeyError
341 Raised if the primary key value for one or more required dimensions
342 is unknown. This may happen if ``graph.issubset(self.graph)`` is
343 `False`, or even if ``graph.issubset(self.graph)`` is `True`, if
344 ``self.hasFull()`` is `False` and
345 ``graph.required.issubset(self.graph.required)`` is `False`. As
346 an example of the latter case, consider trying to go from a data ID
347 with dimensions {instrument, physical_filter, band} to
348 just {instrument, band}; band is implied by
349 physical_filter and hence would have no value in the original data
350 ID if ``self.hasFull()`` is `False`.
352 Notes
353 -----
354 If `hasFull` and `hasRecords` return `True` on ``self``, they will
355 return `True` (respectively) on the returned `DataCoordinate` as well.
356 The converse does not hold.
357 """
358 raise NotImplementedError()
360 @abstractmethod
361 def expanded(self, records: NameLookupMapping[DimensionElement, Optional[DimensionRecord]]
362 ) -> DataCoordinate:
363 """Return a `DataCoordinate` that holds the given records and
364 guarantees that `hasRecords` returns `True`.
366 This is a low-level interface with at most assertion-level checking of
367 inputs. Most callers should use `Registry.expandDataId` instead.
369 Parameters
370 ----------
371 records : `Mapping` [ `str`, `DimensionRecord` or `None` ]
372 A `NamedKeyMapping` with `DimensionElement` keys or a regular
373 `Mapping` with `str` (`DimensionElement` name) keys and
374 `DimensionRecord` values. Keys must cover all elements in
375 ``self.graph.elements``. Values may be `None`, but only to reflect
376 actual NULL values in the database, not just records that have not
377 been fetched.
378 """
379 raise NotImplementedError()
381 @property
382 def universe(self) -> DimensionUniverse:
383 """The universe that defines all known dimensions compatible with
384 this coordinate (`DimensionUniverse`).
385 """
386 return self.graph.universe
388 @property
389 @abstractmethod
390 def graph(self) -> DimensionGraph:
391 """The dimensions identified by this data ID (`DimensionGraph`).
393 Note that values are only required to be present for dimensions in
394 ``self.graph.required``; all others may be retrieved (from a
395 `Registry`) given these.
396 """
397 raise NotImplementedError()
399 @abstractmethod
400 def hasFull(self) -> bool:
401 """Whether this data ID contains values for implied as well as
402 required dimensions.
404 Returns
405 -------
406 state : `bool`
407 If `True`, `__getitem__`, `get`, and `__contains__` (but not
408 `keys`!) will act as though the mapping includes key-value pairs
409 for implied dimensions, and the `full` property may be used. If
410 `False`, these operations only include key-value pairs for required
411 dimensions, and accessing `full` is an error. Always `True` if
412 there are no implied dimensions.
413 """
414 raise NotImplementedError()
416 @property
417 def full(self) -> NamedKeyMapping[Dimension, DataIdValue]:
418 """A mapping that includes key-value pairs for all dimensions in
419 ``self.graph``, including implied (`NamedKeyMapping`).
421 Accessing this attribute if `hasFull` returns `False` is a logic error
422 that may raise an exception of unspecified type either immediately or
423 when implied keys are accessed via the returned mapping, depending on
424 the implementation and whether assertions are enabled.
425 """
426 assert self.hasFull(), "full may only be accessed if hasRecords() returns True."
427 return _DataCoordinateFullView(self)
429 @abstractmethod
430 def hasRecords(self) -> bool:
431 """Whether this data ID contains records for all of the dimension
432 elements it identifies.
434 Returns
435 -------
436 state : `bool`
437 If `True`, the following attributes may be accessed:
439 - `records`
440 - `region`
441 - `timespan`
442 - `pack`
444 If `False`, accessing any of these is considered a logic error.
445 """
446 raise NotImplementedError()
448 @property
449 def records(self) -> NamedKeyMapping[DimensionElement, Optional[DimensionRecord]]:
450 """A mapping that contains `DimensionRecord` objects for all elements
451 identified by this data ID (`NamedKeyMapping`).
453 The values of this mapping may be `None` if and only if there is no
454 record for that element with these dimensions in the database (which
455 means some foreign key field must have a NULL value).
457 Accessing this attribute if `hasRecords` returns `False` is a logic
458 error that may raise an exception of unspecified type either
459 immediately or when the returned mapping is used, depending on the
460 implementation and whether assertions are enabled.
461 """
462 assert self.hasRecords(), "records may only be accessed if hasRecords() returns True."
463 return _DataCoordinateRecordsView(self)
465 @abstractmethod
466 def _record(self, name: str) -> Optional[DimensionRecord]:
467 """Protected implementation hook that backs the ``records`` attribute.
469 Parameters
470 ----------
471 name : `str`
472 The name of a `DimensionElement`, guaranteed to be in
473 ``self.graph.elements.names``.
475 Returns
476 -------
477 record : `DimensionRecord` or `None`
478 The dimension record for the given element identified by this
479 data ID, or `None` if there is no such record.
480 """
481 raise NotImplementedError()
483 @property
484 def region(self) -> Optional[Region]:
485 """The spatial region associated with this data ID
486 (`lsst.sphgeom.Region` or `None`).
488 This is `None` if and only if ``self.graph.spatial`` is empty.
490 Accessing this attribute if `hasRecords` returns `False` is a logic
491 error that may or may not raise an exception, depending on the
492 implementation and whether assertions are enabled.
493 """
494 assert self.hasRecords(), "region may only be accessed if hasRecords() returns True."
495 regions = []
496 for element in self.graph.spatial:
497 record = self._record(element.name)
498 # DimensionRecord subclasses for spatial elements always have a
499 # .region, but they're dynamic so this can't be type-checked.
500 if record is None or record.region is None: # type: ignore
501 return None
502 else:
503 regions.append(record.region) # type:ignore
504 return _intersectRegions(*regions)
506 @property
507 def timespan(self) -> Optional[Timespan]:
508 """The temporal interval associated with this data ID
509 (`Timespan` or `None`).
511 This is `None` if and only if ``self.graph.timespan`` is empty.
513 Accessing this attribute if `hasRecords` returns `False` is a logic
514 error that may or may not raise an exception, depending on the
515 implementation and whether assertions are enabled.
516 """
517 assert self.hasRecords(), "timespan may only be accessed if hasRecords() returns True."
518 timespans = []
519 for element in self.graph.temporal:
520 record = self._record(element.name)
521 # DimensionRecord subclasses for temporal elements always have
522 # .timespan, but they're dynamic so this can't be type-checked.
523 if record is None or record.timespan is None:
524 return None
525 else:
526 timespans.append(record.timespan)
527 return Timespan.intersection(*timespans)
529 def pack(self, name: str, *, returnMaxBits: bool = False) -> Union[Tuple[int, int], int]:
530 """Pack this data ID into an integer.
532 Parameters
533 ----------
534 name : `str`
535 Name of the `DimensionPacker` algorithm (as defined in the
536 dimension configuration).
537 returnMaxBits : `bool`, optional
538 If `True` (`False` is default), return the maximum number of
539 nonzero bits in the returned integer across all data IDs.
541 Returns
542 -------
543 packed : `int`
544 Integer ID. This ID is unique only across data IDs that have
545 the same values for the packer's "fixed" dimensions.
546 maxBits : `int`, optional
547 Maximum number of nonzero bits in ``packed``. Not returned unless
548 ``returnMaxBits`` is `True`.
550 Notes
551 -----
552 Accessing this attribute if `hasRecords` returns `False` is a logic
553 error that may or may not raise an exception, depending on the
554 implementation and whether assertions are enabled.
555 """
556 assert self.hasRecords(), "pack() may only be called if hasRecords() returns True."
557 return self.universe.makePacker(name, self).pack(self, returnMaxBits=returnMaxBits)
560DataId = Union[DataCoordinate, Mapping[str, Any]]
561"""A type-annotation alias for signatures that accept both informal data ID
562dictionaries and validated `DataCoordinate` instances.
563"""
566class _DataCoordinateFullView(NamedKeyMapping[Dimension, DataIdValue]):
567 """View class that provides the default implementation for
568 `DataCoordinate.full`.
570 Parameters
571 ----------
572 target : `DataCoordinate`
573 The `DataCoordinate` instance this object provides a view of.
574 """
575 def __init__(self, target: DataCoordinate):
576 self._target = target
578 __slots__ = ("_target",)
580 def __getitem__(self, key: DataIdKey) -> DataIdValue:
581 return self._target[key]
583 def __iter__(self) -> Iterator[Dimension]:
584 return iter(self.keys())
586 def __len__(self) -> int:
587 return len(self.keys())
589 def keys(self) -> NamedValueSet[Dimension]:
590 return self._target.graph.dimensions
592 @property
593 def names(self) -> AbstractSet[str]:
594 # Docstring inherited from `NamedKeyMapping`.
595 return self.keys().names
598class _DataCoordinateRecordsView(NamedKeyMapping[DimensionElement, Optional[DimensionRecord]]):
599 """View class that provides the default implementation for
600 `DataCoordinate.records`.
602 Parameters
603 ----------
604 target : `DataCoordinate`
605 The `DataCoordinate` instance this object provides a view of.
606 """
607 def __init__(self, target: DataCoordinate):
608 self._target = target
610 __slots__ = ("_target",)
612 def __getitem__(self, key: Union[DimensionElement, str]) -> Optional[DimensionRecord]:
613 if isinstance(key, DimensionElement):
614 key = key.name
615 return self._target._record(key)
617 def __iter__(self) -> Iterator[DimensionElement]:
618 return iter(self.keys())
620 def __len__(self) -> int:
621 return len(self.keys())
623 def keys(self) -> NamedValueSet[DimensionElement]:
624 return self._target.graph.elements
626 @property
627 def names(self) -> AbstractSet[str]:
628 # Docstring inherited from `NamedKeyMapping`.
629 return self.keys().names
632class _BasicTupleDataCoordinate(DataCoordinate):
633 """Standard implementation of `DataCoordinate`, backed by a tuple of
634 values.
636 This class should only be accessed outside this module via the
637 `DataCoordinate` interface, and should only be constructed via the static
638 methods there.
640 Parameters
641 ----------
642 graph : `DimensionGraph`
643 The dimensions to be identified.
644 values : `tuple` [ `int` or `str` ]
645 Data ID values, ordered to match ``graph._dataCoordinateIndices``. May
646 include values for just required dimensions (which always come first)
647 or all dimensions.
648 """
649 def __init__(self, graph: DimensionGraph, values: Tuple[DataIdValue, ...]):
650 self._graph = graph
651 self._values = values
653 __slots__ = ("_graph", "_values")
655 @property
656 def graph(self) -> DimensionGraph:
657 # Docstring inherited from DataCoordinate.
658 return self._graph
660 def __getitem__(self, key: DataIdKey) -> DataIdValue:
661 # Docstring inherited from DataCoordinate.
662 if isinstance(key, Dimension):
663 key = key.name
664 index = self._graph._dataCoordinateIndices[key]
665 try:
666 return self._values[index]
667 except IndexError:
668 # Caller asked for an implied dimension, but this object only has
669 # values for the required ones.
670 raise KeyError(key)
672 def subset(self, graph: DimensionGraph) -> DataCoordinate:
673 # Docstring inherited from DataCoordinate.
674 if self._graph == graph:
675 return self
676 elif self.hasFull() or self._graph.required.issuperset(graph.dimensions):
677 return _BasicTupleDataCoordinate(
678 graph,
679 tuple(self[k] for k in graph._dataCoordinateIndices.keys()),
680 )
681 else:
682 return _BasicTupleDataCoordinate(graph, tuple(self[k] for k in graph.required.names))
684 def expanded(self, records: NameLookupMapping[DimensionElement, Optional[DimensionRecord]]
685 ) -> DataCoordinate:
686 # Docstring inherited from DataCoordinate
687 values = self._values
688 if not self.hasFull():
689 # Extract a complete values tuple from the attributes of the given
690 # records. It's possible for these to be inconsistent with
691 # self._values (which is a serious problem, of course), but we've
692 # documented this as a no-checking API.
693 values += tuple(getattr(records[d.name], d.primaryKey.name) for d in self._graph.implied)
694 return _ExpandedTupleDataCoordinate(self._graph, values, records)
696 def hasFull(self) -> bool:
697 # Docstring inherited from DataCoordinate.
698 return len(self._values) == len(self._graph._dataCoordinateIndices)
700 def hasRecords(self) -> bool:
701 # Docstring inherited from DataCoordinate.
702 return False
704 def _record(self, name: str) -> Optional[DimensionRecord]:
705 # Docstring inherited from DataCoordinate.
706 assert False
709class _ExpandedTupleDataCoordinate(_BasicTupleDataCoordinate):
710 """A `DataCoordinate` implementation that can hold `DimensionRecord`
711 objects.
713 This class should only be accessed outside this module via the
714 `DataCoordinate` interface, and should only be constructed via calls to
715 `DataCoordinate.expanded`.
717 Parameters
718 ----------
719 graph : `DimensionGraph`
720 The dimensions to be identified.
721 values : `tuple` [ `int` or `str` ]
722 Data ID values, ordered to match ``graph._dataCoordinateIndices``.
723 May include values for just required dimensions (which always come
724 first) or all dimensions.
725 records : `Mapping` [ `str`, `DimensionRecord` or `None` ]
726 A `NamedKeyMapping` with `DimensionElement` keys or a regular
727 `Mapping` with `str` (`DimensionElement` name) keys and
728 `DimensionRecord` values. Keys must cover all elements in
729 ``self.graph.elements``. Values may be `None`, but only to reflect
730 actual NULL values in the database, not just records that have not
731 been fetched.
732 """
733 def __init__(self, graph: DimensionGraph, values: Tuple[DataIdValue, ...],
734 records: NameLookupMapping[DimensionElement, Optional[DimensionRecord]]):
735 super().__init__(graph, values)
736 assert super().hasFull(), "This implementation requires full dimension records."
737 self._records = records
739 __slots__ = ("_records",)
741 def subset(self, graph: DimensionGraph) -> DataCoordinate:
742 # Docstring inherited from DataCoordinate.
743 if self._graph == graph:
744 return self
745 return _ExpandedTupleDataCoordinate(graph,
746 tuple(self[k] for k in graph._dataCoordinateIndices.keys()),
747 records=self._records)
749 def expanded(self, records: NameLookupMapping[DimensionElement, Optional[DimensionRecord]]
750 ) -> DataCoordinate:
751 # Docstring inherited from DataCoordinate.
752 return self
754 def hasFull(self) -> bool:
755 # Docstring inherited from DataCoordinate.
756 return True
758 def hasRecords(self) -> bool:
759 # Docstring inherited from DataCoordinate.
760 return True
762 def _record(self, name: str) -> Optional[DimensionRecord]:
763 # Docstring inherited from DataCoordinate.
764 return self._records[name]