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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/>. 

21 

22from __future__ import annotations 

23 

24__all__ = ["RepoExportBackend", "RepoImportBackend", "RepoTransferFormatConfig"] 

25 

26from abc import ABC, abstractmethod 

27from typing import ( 

28 Iterable, 

29 Optional, 

30 Set, 

31) 

32 

33from ..core import ( 

34 ConfigSubset, 

35 DatasetAssociation, 

36 DatasetType, 

37 Datastore, 

38 DimensionElement, 

39 DimensionRecord, 

40 FileDataset, 

41) 

42 

43from ..registry import CollectionType 

44from ..registry.interfaces import CollectionRecord, DatasetIdGenEnum 

45 

46 

47class RepoTransferFormatConfig(ConfigSubset): 

48 """The section of butler configuration that associates repo import/export 

49 backends with file formats. 

50 """ 

51 component = "repo_transfer_formats" 

52 defaultConfigFile = "repo_transfer_formats.yaml" 

53 

54 

55class RepoExportBackend(ABC): 

56 """An abstract interface for data repository export implementations. 

57 

58 Methods are guaranteed to be called in ways that reflect foreign key 

59 dependencies. 

60 """ 

61 

62 @abstractmethod 

63 def saveDimensionData(self, element: DimensionElement, *data: DimensionRecord) -> None: 

64 """Export one or more dimension element records. 

65 

66 Parameters 

67 ---------- 

68 element : `DimensionElement` 

69 The `DimensionElement` whose elements are being exported. 

70 data : `DimensionRecord` (variadic) 

71 One or more records to export. 

72 """ 

73 raise NotImplementedError() 

74 

75 @abstractmethod 

76 def saveCollection(self, record: CollectionRecord, doc: Optional[str]) -> None: 

77 """Export a collection. 

78 

79 This only exports the collection's own state, not its associations with 

80 datasets. 

81 

82 Parameters 

83 ---------- 

84 record: `CollectionRecord` 

85 Object representing the collection to export. 

86 doc : `str` or `None` 

87 Documentation string for the collection. 

88 """ 

89 raise NotImplementedError() 

90 

91 @abstractmethod 

92 def saveDatasets(self, datasetType: DatasetType, run: str, *datasets: FileDataset) -> None: 

93 """Export one or more datasets, including their associated DatasetType 

94 and run information (but not including associated dimension 

95 information). 

96 

97 Parameters 

98 ---------- 

99 datasetType : `DatasetType` 

100 Type of all datasets being exported with this call. 

101 run : `str` 

102 Run associated with all datasets being exported with this call. 

103 datasets : `FileDataset`, variadic 

104 Per-dataset information to be exported. `FileDataset.formatter` 

105 attributes should be strings, not `Formatter` instances or classes. 

106 """ 

107 raise NotImplementedError() 

108 

109 @abstractmethod 

110 def saveDatasetAssociations(self, collection: str, collectionType: CollectionType, 

111 associations: Iterable[DatasetAssociation]) -> None: 

112 """Export the dataset-collection associations for a single collection. 

113 

114 Parameters 

115 ---------- 

116 collection : `str` 

117 The name of the collection. 

118 collectionType : `CollectionType` 

119 The type of the collection; either `CollectionType.TAGGED` or 

120 `CollectionType.CALIBRATION` (as other collection types are 

121 exported in other ways). 

122 associations : `Iterable` [ `DatasetAssociation` ] 

123 Structs representing an association between this collection and 

124 this dataset. 

125 """ 

126 raise NotImplementedError() 

127 

128 @abstractmethod 

129 def finish(self) -> None: 

130 """Complete the export process. 

131 """ 

132 raise NotImplementedError() 

133 

134 

135class RepoImportBackend(ABC): 

136 """An abstract interface for data repository import implementations. 

137 

138 Import backends are expected to be constructed with a description of 

139 the objects that need to be imported (from, e.g., a file written by the 

140 corresponding export backend), along with a `Registry`. 

141 """ 

142 

143 @abstractmethod 

144 def register(self) -> None: 

145 """Register all runs and dataset types associated with the backend with 

146 the `Registry` the backend was constructed with. 

147 

148 These operations cannot be performed inside transactions, unlike those 

149 performed by `load`, and must in general be performed before `load`. 

150 """ 

151 

152 @abstractmethod 

153 def load(self, datastore: Optional[Datastore], *, 

154 directory: Optional[str] = None, transfer: Optional[str] = None, 

155 skip_dimensions: Optional[Set] = None, 

156 idGenerationMode: DatasetIdGenEnum = DatasetIdGenEnum.UNIQUE, 

157 reuseIds: bool = False) -> None: 

158 """Import information associated with the backend into the given 

159 registry and datastore. 

160 

161 This must be run after `register`, and may be performed inside a 

162 transaction. 

163 

164 Parameters 

165 ---------- 

166 datastore : `Datastore` 

167 Datastore to import into. If `None`, datasets will only be 

168 inserted into the `Registry` (primarily intended for tests). 

169 directory : `str`, optional 

170 File all dataset paths are relative to. 

171 transfer : `str`, optional 

172 Transfer mode forwarded to `Datastore.ingest`. 

173 skip_dimensions : `set`, optional 

174 Dimensions that should be skipped and not imported. This can 

175 be useful when importing into a registry that already knows 

176 about a specific instrument. 

177 idGenerationMode : `DatasetIdGenEnum`, optional 

178 Specifies option for generating dataset IDs when IDs are not 

179 provided or their type does not match backend type. By default 

180 unique IDs are generated for each inserted dataset. 

181 reuseIds : `bool`, optional 

182 If `True` then forces re-use of imported dataset IDs for integer 

183 IDs which are normally generated as auto-incremented. This option 

184 has no effect on the use of globally-unique IDs which are always 

185 re-used (or generated if integer IDs are being imported). 

186 """ 

187 raise NotImplementedError()