eb9e6613fa
MikeLing initially did this in bug 1287018. The intent of this conditional was to make optimization faster by not even checking most tasks, based on the assumption that if the prerequisite to a task has changed (for example, a docker image or a build), then naturally we will want to execute that task. However, as we have developed actual optimization methods, this has proven not to be the case: we might want to optimize a test out if its inputs have not changed, even if a new installer has been built. Similarly, SETA may optimize tasks out even if their inputs have changed. MozReview-Commit-ID: LgHET3Z84GB
257 lines
11 KiB
Python
257 lines
11 KiB
Python
# This Source Code Form is subject to the terms of the Mozilla Public
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# License, v. 2.0. If a copy of the MPL was not distributed with this
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# file, You can obtain one at http://mozilla.org/MPL/2.0/.
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from __future__ import absolute_import, print_function, unicode_literals
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import unittest
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from ..optimize import optimize_task_graph, resolve_task_references
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from ..optimize import annotate_task_graph, get_subgraph
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from ..taskgraph import TaskGraph
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from .. import graph
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from .util import TestTask
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class TestResolveTaskReferences(unittest.TestCase):
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def do(self, input, output):
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taskid_for_edge_name = {'edge%d' % n: 'tid%d' % n for n in range(1, 4)}
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self.assertEqual(resolve_task_references('subject', input, taskid_for_edge_name), output)
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def test_in_list(self):
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"resolve_task_references resolves task references in a list"
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self.do({'in-a-list': ['stuff', {'task-reference': '<edge1>'}]},
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{'in-a-list': ['stuff', 'tid1']})
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def test_in_dict(self):
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"resolve_task_references resolves task references in a dict"
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self.do({'in-a-dict': {'stuff': {'task-reference': '<edge2>'}}},
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{'in-a-dict': {'stuff': 'tid2'}})
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def test_multiple(self):
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"resolve_task_references resolves multiple references in the same string"
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self.do({'multiple': {'task-reference': 'stuff <edge1> stuff <edge2> after'}},
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{'multiple': 'stuff tid1 stuff tid2 after'})
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def test_embedded(self):
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"resolve_task_references resolves ebmedded references"
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self.do({'embedded': {'task-reference': 'stuff before <edge3> stuff after'}},
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{'embedded': 'stuff before tid3 stuff after'})
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def test_escaping(self):
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"resolve_task_references resolves escapes in task references"
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self.do({'escape': {'task-reference': '<<><edge3>>'}},
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{'escape': '<tid3>'})
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def test_invalid(self):
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"resolve_task_references raises a KeyError on reference to an invalid task"
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self.assertRaisesRegexp(
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KeyError,
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"task 'subject' has no dependency with label 'no-such'",
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lambda: resolve_task_references('subject', {'task-reference': '<no-such>'}, {})
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)
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class OptimizingTask(TestTask):
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# the `optimize` method on this class is overridden direclty in the tests
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# below.
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pass
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class TestOptimize(unittest.TestCase):
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kind = None
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def make_task(self, label, task_def=None, optimized=None, task_id=None):
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task_def = task_def or {'sample': 'task-def'}
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task = OptimizingTask(label=label, task=task_def)
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task.optimized = optimized
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task.task_id = task_id
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return task
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def make_graph(self, *tasks_and_edges):
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tasks = {t.label: t for t in tasks_and_edges if isinstance(t, OptimizingTask)}
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edges = {e for e in tasks_and_edges if not isinstance(e, OptimizingTask)}
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return TaskGraph(tasks, graph.Graph(set(tasks), edges))
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def assert_annotations(self, graph, **annotations):
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def repl(task_id):
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return 'SLUGID' if task_id and len(task_id) == 22 else task_id
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got_annotations = {
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t.label: (t.optimized, repl(t.task_id)) for t in graph.tasks.itervalues()
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}
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self.assertEqual(got_annotations, annotations)
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def test_annotate_task_graph_no_optimize(self):
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"annotating marks everything as un-optimized if the kind returns that"
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OptimizingTask.optimize = lambda self: (False, None)
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graph = self.make_graph(
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self.make_task('task1'),
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self.make_task('task2'),
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self.make_task('task3'),
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('task2', 'task1', 'build'),
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('task2', 'task3', 'image'),
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)
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annotate_task_graph(graph, set(), graph.graph.named_links_dict(), {}, None)
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self.assert_annotations(
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graph,
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task1=(False, None),
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task2=(False, None),
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task3=(False, None)
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)
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def test_annotate_task_graph_taskid_without_optimize(self):
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"raises exception if kind returns a taskid without optimizing"
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OptimizingTask.optimize = lambda self: (False, 'some-taskid')
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graph = self.make_graph(self.make_task('task1'))
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self.assertRaises(
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Exception,
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lambda: annotate_task_graph(graph, set(), graph.graph.named_links_dict(), {}, None)
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)
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def test_annotate_task_graph_optimize_away_dependency(self):
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"raises exception if kind optimizes away a task on which another depends"
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OptimizingTask.optimize = \
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lambda self: (True, None) if self.label == 'task1' else (False, None)
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graph = self.make_graph(
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self.make_task('task1'),
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self.make_task('task2'),
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('task2', 'task1', 'build'),
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)
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self.assertRaises(
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Exception,
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lambda: annotate_task_graph(graph, set(), graph.graph.named_links_dict(), {}, None)
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)
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def test_annotate_task_graph_do_not_optimize(self):
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"annotating marks everything as un-optimized if in do_not_optimize"
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OptimizingTask.optimize = lambda self: (True, 'taskid')
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graph = self.make_graph(
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self.make_task('task1'),
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self.make_task('task2'),
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('task2', 'task1', 'build'),
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)
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label_to_taskid = {}
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annotate_task_graph(graph, {'task1', 'task2'},
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graph.graph.named_links_dict(), label_to_taskid, None)
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self.assert_annotations(
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graph,
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task1=(False, None),
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task2=(False, None)
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)
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self.assertEqual
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def test_annotate_task_graph_nos_do_not_propagate(self):
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"a task with a non-optimized dependency can be optimized"
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OptimizingTask.optimize = \
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lambda self: (False, None) if self.label == 'task1' else (True, 'taskid')
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graph = self.make_graph(
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self.make_task('task1'),
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self.make_task('task2'),
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self.make_task('task3'),
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('task2', 'task1', 'build'),
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('task2', 'task3', 'image'),
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)
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annotate_task_graph(graph, set(),
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graph.graph.named_links_dict(), {}, None)
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self.assert_annotations(
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graph,
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task1=(False, None),
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task2=(True, 'taskid'),
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task3=(True, 'taskid')
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)
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def test_get_subgraph_single_dep(self):
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"when a single dependency is optimized, it is omitted from the graph"
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graph = self.make_graph(
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self.make_task('task1', optimized=True, task_id='dep1'),
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self.make_task('task2', optimized=False),
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self.make_task('task3', optimized=False),
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('task2', 'task1', 'build'),
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('task2', 'task3', 'image'),
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)
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label_to_taskid = {'task1': 'dep1'}
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sub = get_subgraph(graph, graph.graph.named_links_dict(), label_to_taskid)
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task2 = label_to_taskid['task2']
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task3 = label_to_taskid['task3']
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self.assertEqual(sub.graph.nodes, {task2, task3})
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self.assertEqual(sub.graph.edges, {(task2, task3, 'image')})
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self.assertEqual(sub.tasks[task2].task_id, task2)
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self.assertEqual(sorted(sub.tasks[task2].task['dependencies']),
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sorted([task3, 'dep1']))
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self.assertEqual(sub.tasks[task3].task_id, task3)
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self.assertEqual(sorted(sub.tasks[task3].task['dependencies']), [])
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def test_get_subgraph_dep_chain(self):
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"when a dependency chain is optimized, it is omitted from the graph"
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graph = self.make_graph(
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self.make_task('task1', optimized=True, task_id='dep1'),
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self.make_task('task2', optimized=True, task_id='dep2'),
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self.make_task('task3', optimized=False),
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('task2', 'task1', 'build'),
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('task3', 'task2', 'image'),
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)
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label_to_taskid = {'task1': 'dep1', 'task2': 'dep2'}
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sub = get_subgraph(graph, graph.graph.named_links_dict(), label_to_taskid)
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task3 = label_to_taskid['task3']
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self.assertEqual(sub.graph.nodes, {task3})
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self.assertEqual(sub.graph.edges, set())
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self.assertEqual(sub.tasks[task3].task_id, task3)
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self.assertEqual(sorted(sub.tasks[task3].task['dependencies']), ['dep2'])
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def test_get_subgraph_opt_away(self):
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"when a leaf task is optimized away, it is omitted from the graph"
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graph = self.make_graph(
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self.make_task('task1', optimized=False),
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self.make_task('task2', optimized=True),
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('task2', 'task1', 'build'),
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)
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label_to_taskid = {'task2': 'dep2'}
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sub = get_subgraph(graph, graph.graph.named_links_dict(), label_to_taskid)
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task1 = label_to_taskid['task1']
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self.assertEqual(sub.graph.nodes, {task1})
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self.assertEqual(sub.graph.edges, set())
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self.assertEqual(sub.tasks[task1].task_id, task1)
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self.assertEqual(sorted(sub.tasks[task1].task['dependencies']), [])
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def test_get_subgraph_refs_resolved(self):
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"get_subgraph resolves task references"
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graph = self.make_graph(
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self.make_task('task1', optimized=True, task_id='dep1'),
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self.make_task(
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'task2',
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optimized=False,
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task_def={'payload': {'task-reference': 'http://<build>/<test>'}}
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),
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('task2', 'task1', 'build'),
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('task2', 'task3', 'test'),
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self.make_task('task3', optimized=False),
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)
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label_to_taskid = {'task1': 'dep1'}
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sub = get_subgraph(graph, graph.graph.named_links_dict(), label_to_taskid)
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task2 = label_to_taskid['task2']
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task3 = label_to_taskid['task3']
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self.assertEqual(sub.graph.nodes, {task2, task3})
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self.assertEqual(sub.graph.edges, {(task2, task3, 'test')})
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self.assertEqual(sub.tasks[task2].task_id, task2)
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self.assertEqual(sorted(sub.tasks[task2].task['dependencies']), sorted([task3, 'dep1']))
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self.assertEqual(sub.tasks[task2].task['payload'], 'http://dep1/' + task3)
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self.assertEqual(sub.tasks[task3].task_id, task3)
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def test_optimize(self):
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"optimize_task_graph annotates and extracts the subgraph from a simple graph"
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OptimizingTask.optimize = \
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lambda self: (True, 'dep1') if self.label == 'task1' else (False, None)
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input = self.make_graph(
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self.make_task('task1'),
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self.make_task('task2'),
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self.make_task('task3'),
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('task2', 'task1', 'build'),
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('task2', 'task3', 'image'),
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)
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opt, label_to_taskid = optimize_task_graph(input, set())
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self.assertEqual(opt.graph, graph.Graph(
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{label_to_taskid['task2'], label_to_taskid['task3']},
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{(label_to_taskid['task2'], label_to_taskid['task3'], 'image')}))
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