Coverage for python/lsst/daf/butler/tests/_datasetsHelper.py: 33%

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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 software is dual licensed under the GNU General Public License and also 

10# under a 3-clause BSD license. Recipients may choose which of these licenses 

11# to use; please see the files gpl-3.0.txt and/or bsd_license.txt, 

12# respectively. If you choose the GPL option then the following text applies 

13# (but note that there is still no warranty even if you opt for BSD instead): 

14# 

15# This program is free software: you can redistribute it and/or modify 

16# it under the terms of the GNU General Public License as published by 

17# the Free Software Foundation, either version 3 of the License, or 

18# (at your option) any later version. 

19# 

20# This program is distributed in the hope that it will be useful, 

21# but WITHOUT ANY WARRANTY; without even the implied warranty of 

22# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 

23# GNU General Public License for more details. 

24# 

25# You should have received a copy of the GNU General Public License 

26# along with this program. If not, see <http://www.gnu.org/licenses/>. 

27 

28from __future__ import annotations 

29 

30__all__ = ( 

31 "DatasetTestHelper", 

32 "DatastoreTestHelper", 

33 "BadWriteFormatter", 

34 "BadNoWriteFormatter", 

35 "MultiDetectorFormatter", 

36) 

37 

38import os 

39from collections.abc import Iterable, Mapping 

40from typing import TYPE_CHECKING, Any 

41 

42from lsst.daf.butler import DataCoordinate, DatasetRef, DatasetType, DimensionGroup, StorageClass 

43from lsst.daf.butler.datastore import Datastore 

44from lsst.daf.butler.formatters.yaml import YamlFormatter 

45 

46if TYPE_CHECKING: 

47 from lsst.daf.butler import Config, DatasetId, Dimension, DimensionGraph 

48 

49 

50class DatasetTestHelper: 

51 """Helper methods for Datasets.""" 

52 

53 def makeDatasetRef( 

54 self, 

55 datasetTypeName: str, 

56 dimensions: DimensionGroup | DimensionGraph | Iterable[str | Dimension], 

57 storageClass: StorageClass | str, 

58 dataId: DataCoordinate | Mapping[str, Any], 

59 *, 

60 id: DatasetId | None = None, 

61 run: str | None = None, 

62 conform: bool = True, 

63 ) -> DatasetRef: 

64 """Make a DatasetType and wrap it in a DatasetRef for a test. 

65 

66 Parameters 

67 ---------- 

68 datasetTypeName : `str` 

69 The name of the dataset type. 

70 dimensions : `DimensionGroup` or `~collections.abc.Iterable` of `str` \ 

71 or `Dimension` 

72 The dimensions to use for this dataset type. 

73 storageClass : `StorageClass` or `str` 

74 The relevant storage class. 

75 dataId : `DataCoordinate` or `~collections.abc.Mapping` 

76 The data ID of this ref. 

77 id : `DatasetId` or `None`, optional 

78 The Id of this ref. Will be assigned automatically. 

79 run : `str` or `None`, optional 

80 The run for this ref. Will be assigned a default value if `None`. 

81 conform : `bool`, optional 

82 Whther to force the dataID to be checked for conformity with 

83 the provided dimensions. 

84 

85 Returns 

86 ------- 

87 ref : `DatasetRef` 

88 The new ref. 

89 """ 

90 return self._makeDatasetRef( 

91 datasetTypeName, 

92 dimensions, 

93 storageClass, 

94 dataId, 

95 id=id, 

96 run=run, 

97 conform=conform, 

98 ) 

99 

100 def _makeDatasetRef( 

101 self, 

102 datasetTypeName: str, 

103 dimensions: DimensionGroup | DimensionGraph | Iterable[str | Dimension], 

104 storageClass: StorageClass | str, 

105 dataId: DataCoordinate | Mapping, 

106 *, 

107 id: DatasetId | None = None, 

108 run: str | None = None, 

109 conform: bool = True, 

110 ) -> DatasetRef: 

111 # helper for makeDatasetRef 

112 

113 # Pretend we have a parent if this looks like a composite 

114 compositeName, componentName = DatasetType.splitDatasetTypeName(datasetTypeName) 

115 parentStorageClass = StorageClass("component") if componentName else None 

116 

117 datasetType = DatasetType( 

118 datasetTypeName, dimensions, storageClass, parentStorageClass=parentStorageClass 

119 ) 

120 

121 if run is None: 

122 run = "dummy" 

123 if not isinstance(dataId, DataCoordinate): 

124 dataId = DataCoordinate.standardize(dataId, dimensions=datasetType.dimensions) 

125 return DatasetRef(datasetType, dataId, id=id, run=run, conform=conform) 

126 

127 

128class DatastoreTestHelper: 

129 """Helper methods for Datastore tests.""" 

130 

131 root: str | None 

132 config: Config 

133 datastoreType: type[Datastore] 

134 configFile: str 

135 

136 def setUpDatastoreTests(self, registryClass: type, configClass: type[Config]) -> None: 

137 """Shared setUp code for all Datastore tests. 

138 

139 Parameters 

140 ---------- 

141 registryClass : `type` 

142 Type of registry to use. 

143 configClass : `type` 

144 Type of config to use. 

145 """ 

146 self.registry = registryClass() 

147 self.config = configClass(self.configFile) 

148 

149 # Some subclasses override the working root directory 

150 if self.root is not None: 

151 self.datastoreType.setConfigRoot(self.root, self.config, self.config.copy()) 

152 

153 def makeDatastore(self, sub: str | None = None) -> Datastore: 

154 """Make a new Datastore instance of the appropriate type. 

155 

156 Parameters 

157 ---------- 

158 sub : `str`, optional 

159 If not None, the returned Datastore will be distinct from any 

160 Datastore constructed with a different value of ``sub``. For 

161 PosixDatastore, for example, the converse is also true, and ``sub`` 

162 is used as a subdirectory to form the new root. 

163 

164 Returns 

165 ------- 

166 datastore : `Datastore` 

167 Datastore constructed by this routine using the supplied 

168 optional subdirectory if supported. 

169 """ 

170 config = self.config.copy() 

171 if sub is not None and self.root is not None: 

172 self.datastoreType.setConfigRoot(os.path.join(self.root, sub), config, self.config) 

173 if sub is not None: 

174 # Ensure that each datastore gets its own registry 

175 registryClass = type(self.registry) 

176 registry = registryClass() 

177 else: 

178 registry = self.registry 

179 return Datastore.fromConfig(config=config, bridgeManager=registry.getDatastoreBridgeManager()) 

180 

181 

182class BadWriteFormatter(YamlFormatter): 

183 """A formatter that never works but does leave a file behind.""" 

184 

185 def _readFile(self, path: str, pytype: type[Any] | None = None) -> Any: 

186 raise NotImplementedError("This formatter can not read anything") 

187 

188 def _writeFile(self, inMemoryDataset: Any) -> None: 

189 """Write an empty file and then raise an exception.""" 

190 with open(self.fileDescriptor.location.path, "wb"): 

191 pass 

192 raise RuntimeError("Did not succeed in writing file") 

193 

194 

195class BadNoWriteFormatter(BadWriteFormatter): 

196 """A formatter that always fails without writing anything.""" 

197 

198 def _writeFile(self, inMemoryDataset: Any) -> None: 

199 raise RuntimeError("Did not writing anything at all") 

200 

201 

202class MultiDetectorFormatter(YamlFormatter): 

203 """A formatter that requires a detector to be specified in the dataID.""" 

204 

205 def _writeFile(self, inMemoryDataset: Any) -> None: 

206 raise NotImplementedError("Can not write") 

207 

208 def _fromBytes(self, serializedDataset: bytes, pytype: type[Any] | None = None) -> Any: 

209 data = super()._fromBytes(serializedDataset) 

210 if self.dataId is None: 

211 raise RuntimeError("This formatter requires a dataId") 

212 if "detector" not in self.dataId: 

213 raise RuntimeError("This formatter requires detector to be present in dataId") 

214 key = f"detector{self.dataId['detector']}" 

215 assert pytype is not None 

216 if key in data: 

217 return pytype(data[key]) 

218 raise RuntimeError(f"Could not find '{key}' in data file")