Coverage for python/lsst/pipe/base/pipeTools.py: 14%

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1# This file is part of pipe_base. 

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 

22"""Module defining few methods to manipulate or query pipelines. 

23""" 

24 

25from __future__ import annotations 

26 

27# No one should do import * from this module 

28__all__ = ["isPipelineOrdered", "orderPipeline"] 

29 

30# ------------------------------- 

31# Imports of standard modules -- 

32# ------------------------------- 

33import itertools 

34from typing import TYPE_CHECKING, Iterable, List, Optional, Union 

35 

36# ----------------------------- 

37# Imports for other modules -- 

38# ----------------------------- 

39from .connections import iterConnections 

40 

41if TYPE_CHECKING: 41 ↛ 42line 41 didn't jump to line 42, because the condition on line 41 was never true

42 from .pipeline import Pipeline, TaskDef 

43 from .taskFactory import TaskFactory 

44 

45# ---------------------------------- 

46# Local non-exported definitions -- 

47# ---------------------------------- 

48 

49# ------------------------ 

50# Exported definitions -- 

51# ------------------------ 

52 

53 

54class MissingTaskFactoryError(Exception): 

55 """Exception raised when client fails to provide TaskFactory instance.""" 

56 

57 pass 

58 

59 

60class DuplicateOutputError(Exception): 

61 """Exception raised when Pipeline has more than one task for the same 

62 output. 

63 """ 

64 

65 pass 

66 

67 

68class PipelineDataCycleError(Exception): 

69 """Exception raised when Pipeline has data dependency cycle.""" 

70 

71 pass 

72 

73 

74def isPipelineOrdered( 

75 pipeline: Union[Pipeline, Iterable[TaskDef]], taskFactory: Optional[TaskFactory] = None 

76) -> bool: 

77 """Checks whether tasks in pipeline are correctly ordered. 

78 

79 Pipeline is correctly ordered if for any DatasetType produced by a task 

80 in a pipeline all its consumer tasks are located after producer. 

81 

82 Parameters 

83 ---------- 

84 pipeline : `pipe.base.Pipeline` 

85 Pipeline description. 

86 taskFactory: `pipe.base.TaskFactory`, optional 

87 Instance of an object which knows how to import task classes. It is 

88 only used if pipeline task definitions do not define task classes. 

89 

90 Returns 

91 ------- 

92 True for correctly ordered pipeline, False otherwise. 

93 

94 Raises 

95 ------ 

96 `ImportError` is raised when task class cannot be imported. 

97 `DuplicateOutputError` is raised when there is more than one producer for a 

98 dataset type. 

99 `MissingTaskFactoryError` is raised when TaskFactory is needed but not 

100 provided. 

101 """ 

102 # Build a map of DatasetType name to producer's index in a pipeline 

103 producerIndex = {} 

104 for idx, taskDef in enumerate(pipeline): 

105 for attr in iterConnections(taskDef.connections, "outputs"): 

106 if attr.name in producerIndex: 

107 raise DuplicateOutputError( 

108 "DatasetType `{}' appears more than once as output".format(attr.name) 

109 ) 

110 producerIndex[attr.name] = idx 

111 

112 # check all inputs that are also someone's outputs 

113 for idx, taskDef in enumerate(pipeline): 

114 # get task input DatasetTypes, this can only be done via class method 

115 inputs = {name: getattr(taskDef.connections, name) for name in taskDef.connections.inputs} 

116 for dsTypeDescr in inputs.values(): 

117 # all pre-existing datasets have effective index -1 

118 prodIdx = producerIndex.get(dsTypeDescr.name, -1) 

119 if prodIdx >= idx: 

120 # not good, producer is downstream 

121 return False 

122 

123 return True 

124 

125 

126def orderPipeline(pipeline: List[TaskDef]) -> List[TaskDef]: 

127 """Re-order tasks in pipeline to satisfy data dependencies. 

128 

129 When possible new ordering keeps original relative order of the tasks. 

130 

131 Parameters 

132 ---------- 

133 pipeline : `list` of `pipe.base.TaskDef` 

134 Pipeline description. 

135 

136 Returns 

137 ------- 

138 Correctly ordered pipeline (`list` of `pipe.base.TaskDef` objects). 

139 

140 Raises 

141 ------ 

142 `DuplicateOutputError` is raised when there is more than one producer for a 

143 dataset type. 

144 `PipelineDataCycleError` is also raised when pipeline has dependency 

145 cycles. `MissingTaskFactoryError` is raised when TaskFactory is needed but 

146 not provided. 

147 """ 

148 

149 # This is a modified version of Kahn's algorithm that preserves order 

150 

151 # build mapping of the tasks to their inputs and outputs 

152 inputs = {} # maps task index to its input DatasetType names 

153 outputs = {} # maps task index to its output DatasetType names 

154 allInputs = set() # all inputs of all tasks 

155 allOutputs = set() # all outputs of all tasks 

156 for idx, taskDef in enumerate(pipeline): 

157 # task outputs 

158 dsMap = {name: getattr(taskDef.connections, name) for name in taskDef.connections.outputs} 

159 for dsTypeDescr in dsMap.values(): 

160 if dsTypeDescr.name in allOutputs: 

161 raise DuplicateOutputError( 

162 "DatasetType `{}' appears more than once as output".format(dsTypeDescr.name) 

163 ) 

164 outputs[idx] = set(dsTypeDescr.name for dsTypeDescr in dsMap.values()) 

165 allOutputs.update(outputs[idx]) 

166 

167 # task inputs 

168 connectionInputs = itertools.chain(taskDef.connections.inputs, taskDef.connections.prerequisiteInputs) 

169 inputs[idx] = set(getattr(taskDef.connections, name).name for name in connectionInputs) 

170 allInputs.update(inputs[idx]) 

171 

172 # for simplicity add pseudo-node which is a producer for all pre-existing 

173 # inputs, its index is -1 

174 preExisting = allInputs - allOutputs 

175 outputs[-1] = preExisting 

176 

177 # Set of nodes with no incoming edges, initially set to pseudo-node 

178 queue = [-1] 

179 result = [] 

180 while queue: 

181 # move to final list, drop -1 

182 idx = queue.pop(0) 

183 if idx >= 0: 

184 result.append(idx) 

185 

186 # remove task outputs from other tasks inputs 

187 thisTaskOutputs = outputs.get(idx, set()) 

188 for taskInputs in inputs.values(): 

189 taskInputs -= thisTaskOutputs 

190 

191 # find all nodes with no incoming edges and move them to the queue 

192 topNodes = [key for key, value in inputs.items() if not value] 

193 queue += topNodes 

194 for key in topNodes: 

195 del inputs[key] 

196 

197 # keep queue ordered 

198 queue.sort() 

199 

200 # if there is something left it means cycles 

201 if inputs: 

202 # format it in usable way 

203 loops = [] 

204 for idx, inputNames in inputs.items(): 

205 taskName = pipeline[idx].label 

206 outputNames = outputs[idx] 

207 edge = " {} -> {} -> {}".format(inputNames, taskName, outputNames) 

208 loops.append(edge) 

209 raise PipelineDataCycleError("Pipeline has data cycles:\n" + "\n".join(loops)) 

210 

211 return [pipeline[idx] for idx in result]