Coverage for tests/test_simple_pipeline_executor.py: 25%
132 statements
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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# (https://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 <https://www.gnu.org/licenses/>.
28from __future__ import annotations
30import os
31import shutil
32import tempfile
33import unittest
34from typing import Any
36import lsst.daf.butler
37import lsst.utils.tests
38from lsst.ctrl.mpexec import SimplePipelineExecutor
39from lsst.pipe.base import Struct, TaskDef, TaskMetadata, connectionTypes
40from lsst.pipe.base.tests.no_dimensions import (
41 NoDimensionsTestConfig,
42 NoDimensionsTestConnections,
43 NoDimensionsTestTask,
44)
45from lsst.utils.introspection import get_full_type_name
47TESTDIR = os.path.abspath(os.path.dirname(__file__))
50class NoDimensionsTestConnections2(NoDimensionsTestConnections, dimensions=set()):
51 """A connections class used for testing."""
53 input = connectionTypes.Input(
54 name="input", doc="some dict-y input data for testing", storageClass="TaskMetadataLike"
55 )
58class NoDimensionsTestConfig2(NoDimensionsTestConfig, pipelineConnections=NoDimensionsTestConnections2):
59 """A config used for testing."""
62class NoDimensionsMetadataTestConnections(NoDimensionsTestConnections, dimensions=set()):
63 """Test connection class for metadata.
65 Deliberately choose a storage class that does not match the metadata
66 default TaskMetadata storage class.
67 """
69 meta = connectionTypes.Input(
70 name="a_metadata", doc="Metadata from previous task", storageClass="StructuredDataDict"
71 )
74class NoDimensionsMetadataTestConfig(
75 NoDimensionsTestConfig, pipelineConnections=NoDimensionsMetadataTestConnections
76):
77 """A config used for testing the metadata."""
80class NoDimensionsMetadataTestTask(NoDimensionsTestTask):
81 """A simple pipeline task that can take a metadata as input."""
83 ConfigClass = NoDimensionsMetadataTestConfig
84 _DefaultName = "noDimensionsMetadataTest"
86 def run(self, input: dict[str, int], meta: dict[str, Any]) -> Struct:
87 """Run the task, adding the configured key-value pair to the input
88 argument and returning it as the output.
90 Parameters
91 ----------
92 input : `dict`
93 Dictionary to update and return.
95 Returns
96 -------
97 result : `lsst.pipe.base.Struct`
98 Struct with a single ``output`` attribute.
99 """
100 self.log.info("Run metadata method given data of type: %s", get_full_type_name(input))
101 output = input.copy()
102 output[self.config.key] = self.config.value
104 self.log.info("Received task metadata (%s): %s", get_full_type_name(meta), meta)
106 # Can change the return type via configuration.
107 if "TaskMetadata" in self.config.outputSC:
108 output = TaskMetadata.from_dict(output)
109 elif type(output) == TaskMetadata:
110 # Want the output to be a dict
111 output = output.to_dict()
112 self.log.info("Run method returns data of type: %s", get_full_type_name(output))
113 return Struct(output=output)
116class SimplePipelineExecutorTests(lsst.utils.tests.TestCase):
117 """Test the SimplePipelineExecutor API with a trivial task."""
119 def setUp(self):
120 self.path = tempfile.mkdtemp()
121 # standalone parameter forces the returned config to also include
122 # the information from the search paths.
123 config = lsst.daf.butler.Butler.makeRepo(
124 self.path, standalone=True, searchPaths=[os.path.join(TESTDIR, "config")]
125 )
126 self.butler = SimplePipelineExecutor.prep_butler(config, [], "fake")
127 self.butler.registry.registerDatasetType(
128 lsst.daf.butler.DatasetType(
129 "input",
130 dimensions=self.butler.dimensions.empty,
131 storageClass="StructuredDataDict",
132 )
133 )
134 self.butler.put({"zero": 0}, "input")
136 def tearDown(self):
137 shutil.rmtree(self.path, ignore_errors=True)
139 def test_from_task_class(self):
140 """Test executing a single quantum with an executor created by the
141 `from_task_class` factory method, and the
142 `SimplePipelineExecutor.as_generator` method.
143 """
144 executor = SimplePipelineExecutor.from_task_class(NoDimensionsTestTask, butler=self.butler)
145 (quantum,) = executor.as_generator(register_dataset_types=True)
146 self.assertEqual(self.butler.get("output"), {"zero": 0, "one": 1})
148 def _configure_pipeline(self, config_a_cls, config_b_cls, storageClass_a=None, storageClass_b=None):
149 """Configure a pipeline with from_pipeline."""
150 config_a = config_a_cls()
151 config_a.connections.output = "intermediate"
152 if storageClass_a:
153 config_a.outputSC = storageClass_a
154 config_b = config_b_cls()
155 config_b.connections.input = "intermediate"
156 if storageClass_b:
157 config_b.outputSC = storageClass_b
158 config_b.key = "two"
159 config_b.value = 2
160 task_defs = [
161 TaskDef(label="a", taskClass=NoDimensionsTestTask, config=config_a),
162 TaskDef(label="b", taskClass=NoDimensionsTestTask, config=config_b),
163 ]
164 executor = SimplePipelineExecutor.from_pipeline(task_defs, butler=self.butler)
165 return executor
167 def _test_logs(self, log_output, input_type_a, output_type_a, input_type_b, output_type_b):
168 """Check the expected input types received by tasks A and B.
170 Note that these are the types as seen from the perspective of the task,
171 so they must be consistent with the task's connections, but may not be
172 consistent with the registry dataset types.
173 """
174 all_logs = "\n".join(log_output)
175 self.assertIn(f"lsst.a:Run method given data of type: {input_type_a}", all_logs)
176 self.assertIn(f"lsst.b:Run method given data of type: {input_type_b}", all_logs)
177 self.assertIn(f"lsst.a:Run method returns data of type: {output_type_a}", all_logs)
178 self.assertIn(f"lsst.b:Run method returns data of type: {output_type_b}", all_logs)
180 def test_from_pipeline(self):
181 """Test executing a two quanta from different configurations of the
182 same task, with an executor created by the `from_pipeline` factory
183 method, and the `SimplePipelineExecutor.run` method.
184 """
185 executor = self._configure_pipeline(
186 NoDimensionsTestTask.ConfigClass, NoDimensionsTestTask.ConfigClass
187 )
189 with self.assertLogs("lsst", level="INFO") as cm:
190 quanta = executor.run(register_dataset_types=True, save_versions=False)
191 self._test_logs(cm.output, "dict", "dict", "dict", "dict")
193 self.assertEqual(len(quanta), 2)
194 self.assertEqual(self.butler.get("intermediate"), {"zero": 0, "one": 1})
195 self.assertEqual(self.butler.get("output"), {"zero": 0, "one": 1, "two": 2})
197 def test_from_pipeline_intermediates_differ(self):
198 """Run pipeline but intermediates definition in registry differs."""
199 # Pre-define the "intermediate" storage class to be something that is
200 # like a dict but is not a dict. This will fail unless storage
201 # class conversion is supported in put and get.
202 self.butler.registry.registerDatasetType(
203 lsst.daf.butler.DatasetType(
204 "intermediate",
205 dimensions=self.butler.dimensions.empty,
206 storageClass="TaskMetadataLike",
207 )
208 )
209 executor = self._configure_pipeline(
210 NoDimensionsTestTask.ConfigClass,
211 NoDimensionsTestTask.ConfigClass,
212 storageClass_b="TaskMetadataLike",
213 )
214 with self.assertLogs("lsst", level="INFO") as cm:
215 quanta = executor.run(register_dataset_types=True, save_versions=False)
216 # A dict is given to task a without change.
217 # A returns a dict because it has not been told to do anything else.
218 # That does not match the storage class so it will be converted
219 # on put.
220 # b is given a dict, because that's what its connection asks for.
221 # b returns a TaskMetadata because that's how we configured it, and
222 # since its output wasn't registered in advance, it will have been
223 # registered as TaskMetadata and will now be received as TaskMetadata.
224 self._test_logs(cm.output, "dict", "dict", "dict", "lsst.pipe.base.TaskMetadata")
226 self.assertEqual(len(quanta), 2)
227 self.assertEqual(self.butler.get("intermediate"), TaskMetadata.from_dict({"zero": 0, "one": 1}))
228 self.assertEqual(self.butler.get("output"), TaskMetadata.from_dict({"zero": 0, "one": 1, "two": 2}))
230 def test_from_pipeline_output_differ(self):
231 """Run pipeline but output definition in registry differs."""
232 # Pre-define the "output" storage class to be something that is
233 # like a dict but is not a dict. This will fail unless storage
234 # class conversion is supported in put and get.
235 self.butler.registry.registerDatasetType(
236 lsst.daf.butler.DatasetType(
237 "output",
238 dimensions=self.butler.dimensions.empty,
239 storageClass="TaskMetadataLike",
240 )
241 )
242 executor = self._configure_pipeline(
243 NoDimensionsTestTask.ConfigClass,
244 NoDimensionsTestTask.ConfigClass,
245 storageClass_a="TaskMetadataLike",
246 )
247 with self.assertLogs("lsst", level="INFO") as cm:
248 quanta = executor.run(register_dataset_types=True, save_versions=False)
249 # a has been told to return a TaskMetadata but this will convert to
250 # dict on read by b.
251 # b returns a dict and that is converted to TaskMetadata on put.
252 self._test_logs(cm.output, "dict", "lsst.pipe.base.TaskMetadata", "dict", "dict")
254 self.assertEqual(len(quanta), 2)
255 self.assertEqual(self.butler.get("intermediate"), TaskMetadata.from_dict({"zero": 0, "one": 1}))
256 self.assertEqual(self.butler.get("output"), TaskMetadata.from_dict({"zero": 0, "one": 1, "two": 2}))
258 def test_from_pipeline_input_differ(self):
259 """Run pipeline but input definition in registry differs."""
260 # This config declares that the pipeline takes a TaskMetadata
261 # as input but registry already thinks it has a StructureDataDict.
262 executor = self._configure_pipeline(NoDimensionsTestConfig2, NoDimensionsTestTask.ConfigClass)
264 with self.assertLogs("lsst", level="INFO") as cm:
265 quanta = executor.run(register_dataset_types=True, save_versions=False)
266 self._test_logs(cm.output, "lsst.pipe.base.TaskMetadata", "dict", "dict", "dict")
268 self.assertEqual(len(quanta), 2)
269 self.assertEqual(self.butler.get("intermediate"), {"zero": 0, "one": 1})
270 self.assertEqual(self.butler.get("output"), {"zero": 0, "one": 1, "two": 2})
272 def test_from_pipeline_inconsistent_dataset_types(self):
273 """Generate the QG (by initializing the executor), then register the
274 dataset type with a different storage class than the QG should have
275 predicted, to make sure execution fails as it should.
276 """
277 executor = self._configure_pipeline(
278 NoDimensionsTestTask.ConfigClass, NoDimensionsTestTask.ConfigClass
279 )
281 # Incompatible output dataset type.
282 self.butler.registry.registerDatasetType(
283 lsst.daf.butler.DatasetType(
284 "output",
285 dimensions=self.butler.dimensions.empty,
286 storageClass="StructuredDataList",
287 )
288 )
290 with self.assertRaisesRegex(
291 ValueError, "StructuredDataDict.*inconsistent with registry definition.*StructuredDataList"
292 ):
293 executor.run(register_dataset_types=True, save_versions=False)
295 def test_from_pipeline_metadata(self):
296 """Test two tasks where the output uses metadata from input."""
297 # Must configure a special pipeline for this test.
298 config_a = NoDimensionsTestTask.ConfigClass()
299 config_a.connections.output = "intermediate"
300 config_b = NoDimensionsMetadataTestTask.ConfigClass()
301 config_b.connections.input = "intermediate"
302 config_b.key = "two"
303 config_b.value = 2
304 task_defs = [
305 TaskDef(label="a", taskClass=NoDimensionsTestTask, config=config_a),
306 TaskDef(label="b", taskClass=NoDimensionsMetadataTestTask, config=config_b),
307 ]
308 executor = SimplePipelineExecutor.from_pipeline(task_defs, butler=self.butler)
310 with self.assertLogs("test_simple_pipeline_executor", level="INFO") as cm:
311 quanta = executor.run(register_dataset_types=True, save_versions=False)
312 self.assertIn(f"Received task metadata ({get_full_type_name(dict)})", "".join(cm.output))
314 self.assertEqual(len(quanta), 2)
315 self.assertEqual(self.butler.get("intermediate"), {"zero": 0, "one": 1})
316 self.assertEqual(self.butler.get("output"), {"zero": 0, "one": 1, "two": 2})
318 def test_from_pipeline_file(self):
319 """Test executing a two quanta from different configurations of the
320 same task, with an executor created by the `from_pipeline_filename`
321 factory method, and the `SimplePipelineExecutor.run` method.
322 """
323 filename = os.path.join(self.path, "pipeline.yaml")
324 with open(filename, "w") as f:
325 f.write(
326 """
327 description: test
328 tasks:
329 a:
330 class: "lsst.pipe.base.tests.no_dimensions.NoDimensionsTestTask"
331 config:
332 connections.output: "intermediate"
333 b:
334 class: "lsst.pipe.base.tests.no_dimensions.NoDimensionsTestTask"
335 config:
336 connections.input: "intermediate"
337 key: "two"
338 value: 2
339 """
340 )
341 executor = SimplePipelineExecutor.from_pipeline_filename(filename, butler=self.butler)
342 quanta = executor.run(register_dataset_types=True, save_versions=False)
343 self.assertEqual(len(quanta), 2)
344 self.assertEqual(self.butler.get("intermediate"), {"zero": 0, "one": 1})
345 self.assertEqual(self.butler.get("output"), {"zero": 0, "one": 1, "two": 2})
348class MemoryTester(lsst.utils.tests.MemoryTestCase):
349 """Generic tests for file leaks."""
352def setup_module(module):
353 """Set up the module for pytest."""
354 lsst.utils.tests.init()
357if __name__ == "__main__":
358 lsst.utils.tests.init()
359 unittest.main()