Coverage for python/lsst/ctrl/mpexec/mock_task.py: 20%
86 statements
« prev ^ index » next coverage.py v7.2.7, created at 2023-06-13 16:33 -0700
« prev ^ index » next coverage.py v7.2.7, created at 2023-06-13 16:33 -0700
1# This file is part of ctrl_mpexec.
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/>.
22import logging
23from typing import Any, List, Optional, Union
25from lsst.daf.butler import Butler, DatasetRef, Quantum
26from lsst.pex.config import Field
27from lsst.pipe.base import (
28 ButlerQuantumContext,
29 DeferredDatasetRef,
30 InputQuantizedConnection,
31 OutputQuantizedConnection,
32 PipelineTask,
33 PipelineTaskConfig,
34 PipelineTaskConnections,
35)
36from lsst.utils import doImportType
37from lsst.utils.introspection import get_full_type_name
39from .dataid_match import DataIdMatch
41_LOG = logging.getLogger(__name__)
44class MockButlerQuantumContext(ButlerQuantumContext):
45 """Implementation of ButlerQuantumContext to use with a mock task.
47 Parameters
48 ----------
49 butler : `~lsst.daf.butler.Butler`
50 Data butler instance.
51 quantum : `~lsst.daf.butler.Quantum`
52 Execution quantum.
54 Notes
55 -----
56 This implementation overrides get method to try to retrieve dataset from a
57 mock dataset type if it exists. Get method always returns a dictionary.
58 Put method stores the data with a mock dataset type, but also registers
59 DatasetRef with registry using original dataset type.
60 """
62 def __init__(self, butler: Butler, quantum: Quantum):
63 super().__init__(butler, quantum)
64 self.butler = butler
66 @classmethod
67 def mockDatasetTypeName(cls, datasetTypeName: str) -> str:
68 """Make mock dataset type name from actual dataset type name."""
69 return "_mock_" + datasetTypeName
71 def _get(self, ref: Optional[Union[DeferredDatasetRef, DatasetRef]]) -> Any:
72 # docstring is inherited from the base class
73 if ref is None:
74 return None
75 if isinstance(ref, DeferredDatasetRef):
76 ref = ref.datasetRef
77 datasetType = ref.datasetType
79 typeName, component = datasetType.nameAndComponent()
80 if component is not None:
81 mockDatasetTypeName = self.mockDatasetTypeName(typeName)
82 else:
83 mockDatasetTypeName = self.mockDatasetTypeName(datasetType.name)
85 try:
86 mockDatasetType = self.butler.registry.getDatasetType(mockDatasetTypeName)
87 ref = DatasetRef(mockDatasetType, ref.dataId)
88 data = self.butler.get(ref)
89 except KeyError:
90 data = super()._get(ref)
91 # If the input as an actual non-mock data then we want to replace
92 # it with a provenance data which will be stored as a part of
93 # output dataset.
94 data = {
95 "ref": {
96 "dataId": {key.name: ref.dataId[key] for key in ref.dataId.keys()},
97 "datasetType": ref.datasetType.name,
98 },
99 "type": get_full_type_name(type(data)),
100 }
101 if component is not None:
102 data.update(component=component)
103 return data
105 def _put(self, value: Any, ref: DatasetRef) -> None:
106 # docstring is inherited from the base class
108 mockDatasetType = self.registry.getDatasetType(self.mockDatasetTypeName(ref.datasetType.name))
109 mockRef = DatasetRef(mockDatasetType, ref.dataId)
110 value.setdefault("ref", {}).update(datasetType=mockDatasetType.name)
111 self.butler.put(value, mockRef)
113 # also "store" non-mock refs
114 self.registry._importDatasets([ref])
116 def _checkMembership(self, ref: Union[List[DatasetRef], DatasetRef], inout: set) -> None:
117 # docstring is inherited from the base class
118 return
121class MockPipelineTaskConfig(PipelineTaskConfig, pipelineConnections=PipelineTaskConnections):
122 failCondition: Field[str] = Field(
123 dtype=str,
124 default="",
125 doc=(
126 "Condition on DataId to raise an exception. String expression which includes attributes of "
127 "quantum DataId using a syntax of daf_butler user expressions (e.g. 'visit = 123')."
128 ),
129 )
131 failException: Field[str] = Field(
132 dtype=str,
133 default="builtins.ValueError",
134 doc=(
135 "Class name of the exception to raise when fail condition is triggered. Can be "
136 "'lsst.pipe.base.NoWorkFound' to specify non-failure exception."
137 ),
138 )
140 def dataIdMatch(self) -> Optional[DataIdMatch]:
141 if not self.failCondition:
142 return None
143 return DataIdMatch(self.failCondition)
146class MockPipelineTask(PipelineTask):
147 """Implementation of PipelineTask used for running a mock pipeline.
149 Notes
150 -----
151 This class overrides `runQuantum` to read all input datasetRefs and to
152 store simple dictionary as output data. Output dictionary contains some
153 provenance data about inputs, the task that produced it, and corresponding
154 quantum. This class depends on `MockButlerQuantumContext` which knows how
155 to store the output dictionary data with special dataset types.
156 """
158 ConfigClass = MockPipelineTaskConfig
160 def __init__(self, *, config: Optional[MockPipelineTaskConfig] = None, **kwargs: Any):
161 super().__init__(config=config, **kwargs)
163 self.failException: Optional[type] = None
164 self.dataIdMatch: Optional[DataIdMatch] = None
165 if config is not None:
166 self.dataIdMatch = config.dataIdMatch()
167 if self.dataIdMatch:
168 self.failException = doImportType(config.failException)
170 def runQuantum(
171 self,
172 butlerQC: ButlerQuantumContext,
173 inputRefs: InputQuantizedConnection,
174 outputRefs: OutputQuantizedConnection,
175 ) -> None:
176 # docstring is inherited from the base class
177 quantum = butlerQC.quantum
179 _LOG.info("Mocking execution of task '%s' on quantum %s", self.getName(), quantum.dataId)
181 assert quantum.dataId is not None, "Quantum DataId cannot be None"
183 # Possibly raise an exception.
184 if self.dataIdMatch is not None and self.dataIdMatch.match(quantum.dataId):
185 _LOG.info("Simulating failure of task '%s' on quantum %s", self.getName(), quantum.dataId)
186 message = f"Simulated failure: task={self.getName()} dataId={quantum.dataId}"
187 assert self.failException is not None, "Exception type must be defined"
188 raise self.failException(message)
190 # read all inputs
191 inputs = butlerQC.get(inputRefs)
193 _LOG.info("Read input data for task '%s' on quantum %s", self.getName(), quantum.dataId)
195 # To avoid very deep provenance we trim inputs to a single level
196 for name, data in inputs.items():
197 if isinstance(data, dict):
198 data = [data]
199 if isinstance(data, list):
200 for item in data:
201 qdata = item.get("quantum", {})
202 qdata.pop("inputs", None)
204 # store mock outputs
205 for name, refs in outputRefs:
206 if not isinstance(refs, list):
207 refs = [refs]
208 for ref in refs:
209 data = {
210 "ref": {
211 "dataId": {key.name: ref.dataId[key] for key in ref.dataId.keys()},
212 "datasetType": ref.datasetType.name,
213 },
214 "quantum": {
215 "task": self.getName(),
216 "dataId": {key.name: quantum.dataId[key] for key in quantum.dataId.keys()},
217 "inputs": inputs,
218 },
219 "outputName": name,
220 }
221 butlerQC.put(data, ref)
223 _LOG.info("Finished mocking task '%s' on quantum %s", self.getName(), quantum.dataId)