Coverage for python/lsst/daf/butler/_exceptions.py: 82%

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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 

28"""Specialized Butler exceptions.""" 

29__all__ = ( 

30 "ButlerUserError", 

31 "CalibrationLookupError", 

32 "CollectionCycleError", 

33 "CollectionTypeError", 

34 "DatasetNotFoundError", 

35 "DimensionNameError", 

36 "DatasetTypeNotSupportedError", 

37 "EmptyQueryResultError", 

38 "InvalidQueryError", 

39 "MissingDatasetTypeError", 

40 "MissingCollectionError", 

41 "ValidationError", 

42) 

43 

44from ._exceptions_legacy import CollectionError, DataIdError, DatasetTypeError 

45 

46 

47class ButlerUserError(Exception): 

48 """Base class for Butler exceptions that contain a user-facing error 

49 message. 

50 

51 Parameters 

52 ---------- 

53 detail : `str` 

54 Details about the error that occurred. 

55 """ 

56 

57 # When used with Butler server, exceptions inheriting from 

58 # this class will be sent to the client side and re-raised by RemoteButler 

59 # there. Be careful that error messages do not contain security-sensitive 

60 # information. 

61 # 

62 # This should only be used for "expected" errors that occur because of 

63 # errors in user-supplied data passed to Butler methods. It should not be 

64 # used for any issues caused by the Butler configuration file, errors in 

65 # the library code itself or the underlying databases. 

66 # 

67 # When you create a new subclass of this type, add it to the list in 

68 # _USER_ERROR_TYPES below. 

69 

70 error_type: str 

71 """Unique name for this error type, used to identify it when sending 

72 information about the error to the client. 

73 """ 

74 

75 def __init__(self, detail: str): 

76 return super().__init__(detail) 

77 

78 

79class CalibrationLookupError(LookupError, ButlerUserError): 

80 """Exception raised for failures to look up a calibration dataset.""" 

81 

82 error_type = "calibration_lookup" 

83 

84 

85class CollectionCycleError(ValueError, ButlerUserError): 

86 """Raised when an operation would cause a chained collection to be a child 

87 of itself. 

88 """ 

89 

90 error_type = "collection_cycle" 

91 

92 

93class CollectionTypeError(CollectionError, ButlerUserError): 

94 """Exception raised when type of a collection is incorrect.""" 

95 

96 error_type = "collection_type" 

97 

98 

99class DatasetNotFoundError(LookupError, ButlerUserError): 

100 """The requested dataset could not be found.""" 

101 

102 error_type = "dataset_not_found" 

103 

104 

105class DimensionNameError(KeyError, DataIdError, ButlerUserError): 

106 """Exception raised when a dimension specified in a data ID does not exist 

107 or required dimension is not provided. 

108 """ 

109 

110 error_type = "dimension_name" 

111 

112 

113class DimensionValueError(ValueError, ButlerUserError): 

114 """Exception raised for issues with dimension values in a data ID.""" 

115 

116 error_type = "dimension_value" 

117 

118 

119class InvalidQueryError(ButlerUserError): 

120 """Exception raised when a query is not valid.""" 

121 

122 error_type = "invalid_query" 

123 

124 

125class MissingCollectionError(CollectionError, ButlerUserError): 

126 """Exception raised when an operation attempts to use a collection that 

127 does not exist. 

128 """ 

129 

130 error_type = "missing_collection" 

131 

132 

133class MissingDatasetTypeError(DatasetTypeError, KeyError, ButlerUserError): 

134 """Exception raised when a dataset type does not exist.""" 

135 

136 error_type = "missing_dataset_type" 

137 

138 

139class DatasetTypeNotSupportedError(RuntimeError): 

140 """A `DatasetType` is not handled by this routine. 

141 

142 This can happen in a `Datastore` when a particular `DatasetType` 

143 has no formatters associated with it. 

144 """ 

145 

146 pass 

147 

148 

149class ValidationError(RuntimeError): 

150 """Some sort of validation error has occurred.""" 

151 

152 pass 

153 

154 

155class EmptyQueryResultError(Exception): 

156 """Exception raised when query methods return an empty result and `explain` 

157 flag is set. 

158 

159 Parameters 

160 ---------- 

161 reasons : `list` [`str`] 

162 List of possible reasons for an empty query result. 

163 """ 

164 

165 def __init__(self, reasons: list[str]): 

166 self.reasons = reasons 

167 

168 def __str__(self) -> str: 

169 # There may be multiple reasons, format them into multiple lines. 

170 return "Possible reasons for empty result:\n" + "\n".join(self.reasons) 

171 

172 

173class UnknownButlerUserError(ButlerUserError): 

174 """Raised when the server sends an ``error_type`` for which we don't know 

175 the corresponding exception type. (This may happen if an old version of 

176 the Butler client library connects to a new server). 

177 """ 

178 

179 error_type = "unknown" 

180 

181 

182_USER_ERROR_TYPES: tuple[type[ButlerUserError], ...] = ( 

183 CalibrationLookupError, 

184 CollectionCycleError, 

185 CollectionTypeError, 

186 DimensionNameError, 

187 DimensionValueError, 

188 DatasetNotFoundError, 

189 InvalidQueryError, 

190 MissingCollectionError, 

191 MissingDatasetTypeError, 

192 UnknownButlerUserError, 

193) 

194_USER_ERROR_MAPPING = {e.error_type: e for e in _USER_ERROR_TYPES} 

195assert len(_USER_ERROR_MAPPING) == len( 

196 _USER_ERROR_TYPES 

197), "Subclasses of ButlerUserError must have unique 'error_type' property" 

198 

199 

200def create_butler_user_error(error_type: str, message: str) -> ButlerUserError: 

201 """Instantiate one of the subclasses of `ButlerUserError` based on its 

202 ``error_type`` string. 

203 

204 Parameters 

205 ---------- 

206 error_type : `str` 

207 The value from the ``error_type`` class attribute on the exception 

208 subclass you wish to instantiate. 

209 message : `str` 

210 Detailed error message passed to the exception constructor. 

211 """ 

212 cls = _USER_ERROR_MAPPING.get(error_type) 

213 if cls is None: 

214 raise UnknownButlerUserError(f"Unknown exception type '{error_type}': {message}") 

215 return cls(message)