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, Set, Union
28from sqlalchemy.sql import ColumnElement
30from ...core import (
31 DatasetType,
32 Dimension,
33 DimensionElement,
34 DimensionGraph,
35 DimensionUniverse,
36 ExpandedDataCoordinate,
37 NamedKeyDict,
38 NamedValueSet,
39 SkyPixDimension,
40 Timespan,
41)
42from .exprParser import Node, ParserYacc
45@dataclass
46class QueryWhereExpression:
47 """A struct representing a parsed user-provided WHERE expression.
49 Parameters
50 ----------
51 universe : `DimensionUniverse`
52 All known dimensions.
53 expression : `str`, optional
54 The string expression to parse.
55 """
56 def __init__(self, universe: DimensionUniverse, expression: Optional[str] = None):
57 if expression:
58 from .expressions import InspectionVisitor
59 try:
60 parser = ParserYacc()
61 self.tree = parser.parse(expression)
62 except Exception as exc:
63 raise RuntimeError(f"Failed to parse user expression `{expression}'.") from exc
64 visitor = InspectionVisitor(universe)
65 self.tree.visit(visitor)
66 self.keys = visitor.keys
67 self.metadata = visitor.metadata
68 else:
69 self.tree = None
70 self.keys = NamedValueSet()
71 self.metadata = NamedKeyDict()
73 tree: Optional[Node]
74 """The parsed user expression tree, if present (`Node` or `None`).
75 """
77 keys: NamedValueSet[Dimension]
78 """All dimensions whose keys are referenced by the expression
79 (`NamedValueSet` of `Dimension`).
80 """
82 metadata: NamedKeyDict[DimensionElement, Set[str]]
83 """All dimension elements metadata fields referenced by the expression
84 (`NamedKeyDict` mapping `DimensionElement` to a `set` of field names).
85 """
88@dataclass
89class QuerySummary:
90 """A struct that holds and categorizes the dimensions involved in a query.
92 A `QuerySummary` instance is necessary to construct a `QueryBuilder`, and
93 it needs to include all of the dimensions that will be included in the
94 query (including any needed for querying datasets).
96 Parameters
97 ----------
98 requested : `DimensionGraph`
99 The dimensions whose primary keys should be included in the result rows
100 of the query.
101 dataId : `ExpandedDataCoordinate`, optional
102 A fully-expanded data ID identifying dimensions known in advance. If
103 not provided, will be set to an empty data ID.
104 expression : `str` or `QueryWhereExpression`, optional
105 A user-provided string WHERE expression.
106 """
107 def __init__(self, requested: DimensionGraph, *,
108 dataId: Optional[ExpandedDataCoordinate] = None,
109 expression: Optional[Union[str, QueryWhereExpression]] = None):
110 self.requested = requested
111 self.dataId = dataId if dataId is not None else ExpandedDataCoordinate(requested.universe.empty, ())
112 self.expression = (expression if isinstance(expression, QueryWhereExpression)
113 else QueryWhereExpression(requested.universe, expression))
115 requested: DimensionGraph
116 """Dimensions whose primary keys should be included in the result rows of
117 the query (`DimensionGraph`).
118 """
120 dataId: ExpandedDataCoordinate
121 """A data ID identifying dimensions known before query construction
122 (`ExpandedDataCoordinate`).
123 """
125 expression: QueryWhereExpression
126 """Information about any parsed user WHERE expression
127 (`QueryWhereExpression`).
128 """
130 @property
131 def universe(self) -> DimensionUniverse:
132 """All known dimensions (`DimensionUniverse`).
133 """
134 return self.requested.universe
136 @property
137 def spatial(self) -> NamedValueSet[DimensionElement]:
138 """Dimension elements whose regions and skypix IDs should be included
139 in the query (`NamedValueSet` of `DimensionElement`).
140 """
141 # An element may participate spatially in the query if:
142 # - it's the most precise spatial element for its system in the
143 # requested dimensions (i.e. in `self.requested.spatial`);
144 # - it isn't also given at query construction time.
145 result = self.mustHaveKeysJoined.spatial - self.dataId.graph.elements
146 if len(result) == 1:
147 # There's no spatial join, but there might be a WHERE filter based
148 # on a given region.
149 if self.dataId.graph.spatial:
150 # We can only perform those filters against SkyPix dimensions,
151 # so if what we have isn't one, add the common SkyPix dimension
152 # to the query; the element we have will be joined to that.
153 element, = result
154 if not isinstance(element, SkyPixDimension):
155 result.add(self.universe.commonSkyPix)
156 else:
157 # There is no spatial join or filter in this query. Even
158 # if this element might be associated with spatial
159 # information, we don't need it for this query.
160 return NamedValueSet()
161 elif len(result) > 1:
162 # There's a spatial join. Those require the common SkyPix
163 # system to be included in the query in order to connect them.
164 result.add(self.universe.commonSkyPix)
165 return result
167 @property
168 def temporal(self) -> NamedValueSet[DimensionElement]:
169 """Dimension elements whose timespans should be included in the
170 query (`NamedValueSet` of `DimensionElement`).
171 """
172 # An element may participate temporally in the query if:
173 # - it's the most precise temporal element for its system in the
174 # requested dimensions (i.e. in `self.requested.temporal`);
175 # - it isn't also given at query construction time.
176 result = self.mustHaveKeysJoined.temporal - self.dataId.graph.elements
177 if len(result) == 1 and not self.dataId.graph.temporal:
178 # No temporal join or filter. Even if this element might be
179 # associated with temporal information, we don't need it for this
180 # query.
181 return NamedValueSet()
182 return result
184 @property
185 def mustHaveKeysJoined(self) -> DimensionGraph:
186 """Dimensions whose primary keys must be used in the JOIN ON clauses
187 of the query, even if their tables do not appear (`DimensionGraph`).
189 A `Dimension` primary key can appear in a join clause without its table
190 via a foreign key column in table of a dependent dimension element or
191 dataset.
192 """
193 names = set(self.requested.names | self.expression.keys.names)
194 return DimensionGraph(self.universe, names=names)
196 @property
197 def mustHaveTableJoined(self) -> NamedValueSet[DimensionElement]:
198 """Dimension elements whose associated tables must appear in the
199 query's FROM clause (`NamedValueSet` of `DimensionElement`).
200 """
201 result = self.spatial | self.temporal | self.expression.metadata.keys()
202 for dimension in self.mustHaveKeysJoined:
203 if dimension.implied:
204 result.add(dimension)
205 for element in self.mustHaveKeysJoined.union(self.dataId.graph).elements:
206 if element.alwaysJoin:
207 result.add(element)
208 return result
211@dataclass
212class DatasetQueryColumns:
213 """A struct containing the columns used to reconstruct `DatasetRef`
214 instances from query results.
215 """
217 id: ColumnElement
218 """Column containing the unique integer ID for this dataset.
219 """
221 runKey: ColumnElement
222 """Foreign key column to the `~CollectionType.RUN` collection that holds
223 this dataset.
224 """
226 rank: Optional[ColumnElement] = None
227 """Column containing the index into the ordered sequence of given
228 collections for the collection in which this dataset was found.
229 """
231 def __iter__(self) -> Iterator[ColumnElement]:
232 yield self.id
233 yield self.runKey
234 if self.rank is not None:
235 yield self.rank
238@dataclass
239class QueryColumns:
240 """A struct organizing the columns in an under-construction or currently-
241 executing query.
243 Takes no parameters at construction, as expected usage is to add elements
244 to its container attributes incrementally.
245 """
246 def __init__(self):
247 self.keys = NamedKeyDict()
248 self.timespans = NamedKeyDict()
249 self.regions = NamedKeyDict()
250 self.datasets = NamedKeyDict()
252 keys: NamedKeyDict[Dimension, List[ColumnElement]]
253 """Columns that correspond to the primary key values of dimensions
254 (`NamedKeyDict` mapping `Dimension` to a `list` of `ColumnElement`).
256 Each value list contains columns from multiple tables corresponding to the
257 same dimension, and the query should constrain the values of those columns
258 to be the same.
260 In a `Query`, the keys of this dictionary must include at least the
261 dimensions in `QuerySummary.requested` and `QuerySummary.dataId.graph`.
262 """
264 timespans: NamedKeyDict[DimensionElement, Timespan[ColumnElement]]
265 """Columns that correspond to timespans for elements that participate in a
266 temporal join or filter in the query (`NamedKeyDict` mapping
267 `DimensionElement` to `Timespan` of `ColumnElement`).
269 In a `Query`, the keys of this dictionary must be exactly the elements
270 in `QuerySummary.temporal`.
271 """
273 regions: NamedKeyDict[DimensionElement, ColumnElement]
274 """Columns that correspond to regions for elements that participate in a
275 spatial join or filter in the query (`NamedKeyDict` mapping
276 `DimensionElement` to `ColumnElement`).
278 In a `Query`, the keys of this dictionary must be exactly the elements
279 in `QuerySummary.spatial`.
280 """
282 datasets: NamedKeyDict[DatasetType, DatasetQueryColumns]
283 """Columns that can be used to construct `DatasetRef` instances from query
284 results, for each `DatasetType` included in the query
285 (`NamedKeyDict` [ `DatasetType`, `DatasetQueryColumns` ] ).
286 """
288 def getKeyColumn(self, dimension: Dimension) -> ColumnElement:
289 """ Return one of the columns in self.keys for the given dimension.
291 The column selected is an implentation detail but is guaranteed to
292 be deterministic and consistent across multiple calls.
294 Parameters
295 ----------
296 dimension : `Dimension`
297 Element for which to obtain a key column.
299 Returns
300 -------
301 column : `sqlalchemy.sql.ColumnElement`
302 SQLAlchemy column object.
303 """
304 # Choosing the last element here is entirely for human readers of the
305 # query (e.g. developers debugging things); it makes it more likely a
306 # dimension key will be provided by the dimension's own table, or
307 # failing that, some closely related dimension, which might be less
308 # surprising to see than e.g. some dataset subquery. From the
309 # database's perspective this is entirely arbitrary, cause the query
310 # guarantees they all have equal values.
311 return self.keys[dimension][-1]