Coverage for python/lsst/daf/butler/core/dimensions/_governor.py: 52%
59 statements
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« prev ^ index » next coverage.py v6.4.1, created at 2022-06-17 02:08 -0700
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/>.
22from __future__ import annotations
24__all__ = ("GovernorDimension",)
26from types import MappingProxyType
27from typing import TYPE_CHECKING, AbstractSet, Iterable, Mapping, Optional
29from lsst.utils import doImportType
31from .. import ddl
32from .._topology import TopologicalFamily, TopologicalSpace
33from ..named import NamedValueAbstractSet, NamedValueSet
34from ._elements import Dimension
35from .construction import DimensionConstructionBuilder, DimensionConstructionVisitor
37if TYPE_CHECKING: 37 ↛ 38line 37 didn't jump to line 38, because the condition on line 37 was never true
38 from ...registry.interfaces import Database, GovernorDimensionRecordStorage, StaticTablesContext
41class GovernorDimension(Dimension):
42 """Governor dimension.
44 A special `Dimension` with no dependencies and a small number of rows,
45 used to group the dimensions that depend on it.
47 Parameters
48 ----------
49 name : `str`
50 Name of the dimension.
51 storage : `dict`
52 Fully qualified name of the `GovernorDimensionRecordStorage` subclass
53 that will back this element in the registry (in a "cls" key) along
54 with any other construction keyword arguments (in other keys).
55 metadata : `NamedValueAbstractSet` [ `ddl.FieldSpec` ]
56 Field specifications for all non-key fields in this dimension's table.
57 uniqueKeys : `NamedValueAbstractSet` [ `ddl.FieldSpec` ]
58 Fields that can each be used to uniquely identify this dimension (given
59 values for all required dimensions). The first of these is used as
60 (part of) this dimension's table's primary key, while others are used
61 to define unique constraints.
63 Notes
64 -----
65 Most dimensions have exactly one governor dimension as a required
66 dependency, and queries that involve those dimensions are always expected
67 to explicitly identify the governor dimension value(s), rather than
68 retrieve all matches from the database. Because governor values are thus
69 almost always known at query-generation time, they can be used there to
70 simplify queries, provide sensible defaults, or check in advance for common
71 mistakes that might otherwise yield confusing (albeit formally correct)
72 results instead of straightforward error messages.
74 Governor dimensions may not be associated with any kind of topological
75 extent.
77 Governor dimension rows are often affiliated with a Python class or
78 instance (e.g. `lsst.obs.base.Instrument`) that is capable of generating
79 the rows of at least some dependent dimensions or providing other related
80 functionality. In the future, we hope to attach these instances to
81 governor dimension records (instantiating them from information in the
82 database row when it is fetched), and use those objects to add additional
83 functionality to governor dimensions, but a number of (code) dependency
84 relationships would need to be reordered first.
85 """
87 def __init__(
88 self,
89 name: str,
90 storage: dict,
91 *,
92 metadata: NamedValueAbstractSet[ddl.FieldSpec],
93 uniqueKeys: NamedValueAbstractSet[ddl.FieldSpec],
94 ):
95 self._name = name
96 self._storage = storage
97 self._required = NamedValueSet({self}).freeze()
98 self._metadata = metadata
99 self._uniqueKeys = uniqueKeys
100 if self.primaryKey.getPythonType() is not str:
101 raise TypeError(
102 f"Governor dimension '{name}' must have a string primary key (configured type "
103 f"is {self.primaryKey.dtype.__name__})."
104 )
105 if self.primaryKey.length is not None and self.primaryKey.length > self.MAX_KEY_LENGTH:
106 raise TypeError(
107 f"Governor dimension '{name}' must have a string primary key with length <= "
108 f"{self.MAX_KEY_LENGTH} (configured value is {self.primaryKey.length})."
109 )
111 MAX_KEY_LENGTH = 128
113 @property
114 def name(self) -> str:
115 # Docstring inherited from TopologicalRelationshipEndpoint.
116 return self._name
118 @property
119 def required(self) -> NamedValueAbstractSet[Dimension]:
120 # Docstring inherited from DimensionElement.
121 return self._required
123 @property
124 def implied(self) -> NamedValueAbstractSet[Dimension]:
125 # Docstring inherited from DimensionElement.
126 return NamedValueSet().freeze()
128 @property
129 def topology(self) -> Mapping[TopologicalSpace, TopologicalFamily]:
130 # Docstring inherited from TopologicalRelationshipEndpoint
131 return MappingProxyType({})
133 @property
134 def metadata(self) -> NamedValueAbstractSet[ddl.FieldSpec]:
135 # Docstring inherited from DimensionElement.
136 return self._metadata
138 @property
139 def uniqueKeys(self) -> NamedValueAbstractSet[ddl.FieldSpec]:
140 # Docstring inherited from Dimension.
141 return self._uniqueKeys
143 def makeStorage(
144 self,
145 db: Database,
146 *,
147 context: Optional[StaticTablesContext] = None,
148 ) -> GovernorDimensionRecordStorage:
149 """Make storage record.
151 Constructs the `DimensionRecordStorage` instance that should
152 be used to back this element in a registry.
154 Parameters
155 ----------
156 db : `Database`
157 Interface to the underlying database engine and namespace.
158 context : `StaticTablesContext`, optional
159 If provided, an object to use to create any new tables. If not
160 provided, ``db.ensureTableExists`` should be used instead.
162 Returns
163 -------
164 storage : `GovernorDimensionRecordStorage`
165 Storage object that should back this element in a registry.
166 """
167 from ...registry.interfaces import GovernorDimensionRecordStorage
169 cls = doImportType(self._storage["cls"])
170 assert issubclass(cls, GovernorDimensionRecordStorage)
171 return cls.initialize(db, self, context=context, config=self._storage)
174class GovernorDimensionConstructionVisitor(DimensionConstructionVisitor):
175 """A construction visitor for `GovernorDimension`.
177 Parameters
178 ----------
179 name : `str`
180 Name of the dimension.
181 storage : `dict`
182 Fully qualified name of the `GovernorDimensionRecordStorage` subclass
183 that will back this element in the registry (in a "cls" key) along
184 with any other construction keyword arguments (in other keys).
185 metadata : `Iterable` [ `ddl.FieldSpec` ]
186 Field specifications for all non-key fields in this element's table.
187 uniqueKeys : `Iterable` [ `ddl.FieldSpec` ]
188 Fields that can each be used to uniquely identify this dimension (given
189 values for all required dimensions). The first of these is used as
190 (part of) this dimension's table's primary key, while others are used
191 to define unique constraints.
192 """
194 def __init__(
195 self,
196 name: str,
197 storage: dict,
198 *,
199 metadata: Iterable[ddl.FieldSpec] = (),
200 uniqueKeys: Iterable[ddl.FieldSpec] = (),
201 ):
202 super().__init__(name)
203 self._storage = storage
204 self._metadata = NamedValueSet(metadata).freeze()
205 self._uniqueKeys = NamedValueSet(uniqueKeys).freeze()
207 def hasDependenciesIn(self, others: AbstractSet[str]) -> bool:
208 # Docstring inherited from DimensionConstructionVisitor.
209 return False
211 def visit(self, builder: DimensionConstructionBuilder) -> None:
212 # Docstring inherited from DimensionConstructionVisitor.
213 # Special handling for creating Dimension instances.
214 dimension = GovernorDimension(
215 self.name,
216 storage=self._storage,
217 metadata=self._metadata,
218 uniqueKeys=self._uniqueKeys,
219 )
220 builder.dimensions.add(dimension)
221 builder.elements.add(dimension)