Coverage for python/lsst/daf/butler/registry/queries/_structs.py : 37%

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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/>.
21from __future__ import annotations
23__all__ = ["QuerySummary"] # other classes here are local to subpackage
25from dataclasses import dataclass
26from typing import Iterator, List, Optional, Union
28from sqlalchemy.sql import ColumnElement
30from ...core import (
31 DataCoordinate,
32 DatasetType,
33 Dimension,
34 DimensionElement,
35 DimensionGraph,
36 DimensionUniverse,
37 NamedKeyDict,
38 NamedValueSet,
39 SkyPixDimension,
40 Timespan,
41)
42# We're not trying to add typing to the lex/yacc parser code, so MyPy
43# doesn't know about some of these imports.
44from .exprParser import Node, ParserYacc # type: ignore
47@dataclass
48class QueryWhereExpression:
49 """A struct representing a parsed user-provided WHERE expression.
51 Parameters
52 ----------
53 universe : `DimensionUniverse`
54 All known dimensions.
55 expression : `str`, optional
56 The string expression to parse.
57 """
58 def __init__(self, universe: DimensionUniverse, expression: Optional[str] = None):
59 if expression:
60 from .expressions import InspectionVisitor
61 try:
62 parser = ParserYacc()
63 self.tree = parser.parse(expression)
64 except Exception as exc:
65 raise RuntimeError(f"Failed to parse user expression `{expression}'.") from exc
66 visitor = InspectionVisitor(universe)
67 assert self.tree is not None
68 self.tree.visit(visitor)
69 self.keys = visitor.keys
70 self.metadata = visitor.metadata
71 else:
72 self.tree = None
73 self.keys = NamedValueSet()
74 self.metadata = NamedKeyDict()
76 tree: Optional[Node]
77 """The parsed user expression tree, if present (`Node` or `None`).
78 """
80 keys: NamedValueSet[Dimension]
81 """All dimensions whose keys are referenced by the expression
82 (`NamedValueSet` of `Dimension`).
83 """
85 metadata: NamedKeyDict[DimensionElement, List[str]]
86 """All dimension elements metadata fields referenced by the expression
87 (`NamedKeyDict` mapping `DimensionElement` to a `set` of field names).
88 """
91@dataclass
92class QuerySummary:
93 """A struct that holds and categorizes the dimensions involved in a query.
95 A `QuerySummary` instance is necessary to construct a `QueryBuilder`, and
96 it needs to include all of the dimensions that will be included in the
97 query (including any needed for querying datasets).
99 Parameters
100 ----------
101 requested : `DimensionGraph`
102 The dimensions whose primary keys should be included in the result rows
103 of the query.
104 dataId : `DataCoordinate`, optional
105 A fully-expanded data ID identifying dimensions known in advance. If
106 not provided, will be set to an empty data ID. ``dataId.hasRecords()``
107 must return `True`.
108 expression : `str` or `QueryWhereExpression`, optional
109 A user-provided string WHERE expression.
110 """
111 def __init__(self, requested: DimensionGraph, *,
112 dataId: Optional[DataCoordinate] = None,
113 expression: Optional[Union[str, QueryWhereExpression]] = None):
114 self.requested = requested
115 self.dataId = dataId if dataId is not None else DataCoordinate.makeEmpty(requested.universe)
116 self.expression = (expression if isinstance(expression, QueryWhereExpression)
117 else QueryWhereExpression(requested.universe, expression))
119 requested: DimensionGraph
120 """Dimensions whose primary keys should be included in the result rows of
121 the query (`DimensionGraph`).
122 """
124 dataId: DataCoordinate
125 """A data ID identifying dimensions known before query construction
126 (`DataCoordinate`).
128 ``dataId.hasRecords()`` is guaranteed to return `True`.
129 """
131 expression: QueryWhereExpression
132 """Information about any parsed user WHERE expression
133 (`QueryWhereExpression`).
134 """
136 @property
137 def universe(self) -> DimensionUniverse:
138 """All known dimensions (`DimensionUniverse`).
139 """
140 return self.requested.universe
142 @property
143 def spatial(self) -> NamedValueSet[DimensionElement]:
144 """Dimension elements whose regions and skypix IDs should be included
145 in the query (`NamedValueSet` of `DimensionElement`).
146 """
147 # An element may participate spatially in the query if:
148 # - it's the most precise spatial element for its system in the
149 # requested dimensions (i.e. in `self.requested.spatial`);
150 # - it isn't also given at query construction time.
151 result = NamedValueSet(self.mustHaveKeysJoined.spatial - self.dataId.graph.elements)
152 if len(result) == 1:
153 # There's no spatial join, but there might be a WHERE filter based
154 # on a given region.
155 if self.dataId.graph.spatial:
156 # We can only perform those filters against SkyPix dimensions,
157 # so if what we have isn't one, add the common SkyPix dimension
158 # to the query; the element we have will be joined to that.
159 element, = result
160 if not isinstance(element, SkyPixDimension):
161 result.add(self.universe.commonSkyPix)
162 else:
163 # There is no spatial join or filter in this query. Even
164 # if this element might be associated with spatial
165 # information, we don't need it for this query.
166 return NamedValueSet()
167 elif len(result) > 1:
168 # There's a spatial join. Those require the common SkyPix
169 # system to be included in the query in order to connect them.
170 result.add(self.universe.commonSkyPix)
171 return result
173 @property
174 def temporal(self) -> NamedValueSet[DimensionElement]:
175 """Dimension elements whose timespans should be included in the
176 query (`NamedValueSet` of `DimensionElement`).
177 """
178 # An element may participate temporally in the query if:
179 # - it's the most precise temporal element for its system in the
180 # requested dimensions (i.e. in `self.requested.temporal`);
181 # - it isn't also given at query construction time.
182 result = NamedValueSet(self.mustHaveKeysJoined.temporal - self.dataId.graph.elements)
183 if len(result) == 1 and not self.dataId.graph.temporal:
184 # No temporal join or filter. Even if this element might be
185 # associated with temporal information, we don't need it for this
186 # query.
187 return NamedValueSet()
188 return result
190 @property
191 def mustHaveKeysJoined(self) -> DimensionGraph:
192 """Dimensions whose primary keys must be used in the JOIN ON clauses
193 of the query, even if their tables do not appear (`DimensionGraph`).
195 A `Dimension` primary key can appear in a join clause without its table
196 via a foreign key column in table of a dependent dimension element or
197 dataset.
198 """
199 names = set(self.requested.names | self.expression.keys.names)
200 return DimensionGraph(self.universe, names=names)
202 @property
203 def mustHaveTableJoined(self) -> NamedValueSet[DimensionElement]:
204 """Dimension elements whose associated tables must appear in the
205 query's FROM clause (`NamedValueSet` of `DimensionElement`).
206 """
207 result = NamedValueSet(self.spatial | self.temporal | self.expression.metadata.keys())
208 for dimension in self.mustHaveKeysJoined:
209 if dimension.implied:
210 result.add(dimension)
211 for element in self.mustHaveKeysJoined.union(self.dataId.graph).elements:
212 if element.alwaysJoin:
213 result.add(element)
214 return result
217@dataclass
218class DatasetQueryColumns:
219 """A struct containing the columns used to reconstruct `DatasetRef`
220 instances from query results.
221 """
223 id: ColumnElement
224 """Column containing the unique integer ID for this dataset.
225 """
227 runKey: ColumnElement
228 """Foreign key column to the `~CollectionType.RUN` collection that holds
229 this dataset.
230 """
232 rank: Optional[ColumnElement] = None
233 """Column containing the index into the ordered sequence of given
234 collections for the collection in which this dataset was found.
235 """
237 def __iter__(self) -> Iterator[ColumnElement]:
238 yield self.id
239 yield self.runKey
240 if self.rank is not None:
241 yield self.rank
244@dataclass
245class QueryColumns:
246 """A struct organizing the columns in an under-construction or currently-
247 executing query.
249 Takes no parameters at construction, as expected usage is to add elements
250 to its container attributes incrementally.
251 """
252 def __init__(self) -> None:
253 self.keys = NamedKeyDict()
254 self.timespans = NamedKeyDict()
255 self.regions = NamedKeyDict()
256 self.datasets = NamedKeyDict()
258 keys: NamedKeyDict[Dimension, List[ColumnElement]]
259 """Columns that correspond to the primary key values of dimensions
260 (`NamedKeyDict` mapping `Dimension` to a `list` of `ColumnElement`).
262 Each value list contains columns from multiple tables corresponding to the
263 same dimension, and the query should constrain the values of those columns
264 to be the same.
266 In a `Query`, the keys of this dictionary must include at least the
267 dimensions in `QuerySummary.requested` and `QuerySummary.dataId.graph`.
268 """
270 timespans: NamedKeyDict[DimensionElement, Timespan[ColumnElement]]
271 """Columns that correspond to timespans for elements that participate in a
272 temporal join or filter in the query (`NamedKeyDict` mapping
273 `DimensionElement` to `Timespan` of `ColumnElement`).
275 In a `Query`, the keys of this dictionary must be exactly the elements
276 in `QuerySummary.temporal`.
277 """
279 regions: NamedKeyDict[DimensionElement, ColumnElement]
280 """Columns that correspond to regions for elements that participate in a
281 spatial join or filter in the query (`NamedKeyDict` mapping
282 `DimensionElement` to `ColumnElement`).
284 In a `Query`, the keys of this dictionary must be exactly the elements
285 in `QuerySummary.spatial`.
286 """
288 datasets: NamedKeyDict[DatasetType, DatasetQueryColumns]
289 """Columns that can be used to construct `DatasetRef` instances from query
290 results, for each `DatasetType` included in the query
291 (`NamedKeyDict` [ `DatasetType`, `DatasetQueryColumns` ] ).
292 """
294 def getKeyColumn(self, dimension: Union[Dimension, str]) -> ColumnElement:
295 """ Return one of the columns in self.keys for the given dimension.
297 The column selected is an implentation detail but is guaranteed to
298 be deterministic and consistent across multiple calls.
300 Parameters
301 ----------
302 dimension : `Dimension` or `str`
303 Dimension for which to obtain a key column.
305 Returns
306 -------
307 column : `sqlalchemy.sql.ColumnElement`
308 SQLAlchemy column object.
309 """
310 # Choosing the last element here is entirely for human readers of the
311 # query (e.g. developers debugging things); it makes it more likely a
312 # dimension key will be provided by the dimension's own table, or
313 # failing that, some closely related dimension, which might be less
314 # surprising to see than e.g. some dataset subquery. From the
315 # database's perspective this is entirely arbitrary, because the query
316 # guarantees they all have equal values.
317 return self.keys[dimension][-1]