18da9b3836
It is not at *all* clear how multiple optimizations for a single task should interact. No simple logical operation is right in all cases, and in fact in most imaginable cases the desired behavior turns out to be independent of all but one of the optimizations. For example, given both `seta` and `skip-unless-files-changed` optimizations, if SETA says to skip a test, it is low value and should be skipped regardless of what files have changed. But if SETA says to run a test, then it has likely been skipped in previous pushes, so it should be run regardless of what has changed in this push. This also adds a bit more output about optimization, that may be useful for anyone wondering why a particular job didn't run. MozReview-Commit-ID: 3OsvRnWjai4
250 lines
10 KiB
Python
250 lines
10 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 taskgraph.optimize import optimize_task_graph, resolve_task_references, optimization
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from taskgraph.optimize import annotate_task_graph, get_subgraph
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from taskgraph.taskgraph import TaskGraph
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from taskgraph import graph
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from taskgraph.task import Task
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from mozunit import main
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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 named 'no-such'",
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lambda: resolve_task_references('subject', {'task-reference': '<no-such>'}, {})
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)
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class TestOptimize(unittest.TestCase):
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kind = None
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@classmethod
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def setUpClass(cls):
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# set up some simple optimization functions
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optimization('no-optimize')(lambda self, params, arg: False)
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optimization('optimize-away')(lambda self, params, arg: True)
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optimization('optimize-to-task')(lambda self, params, task: task)
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def make_task(self, label, optimization=None, 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 = Task(kind='test', label=label, attributes={}, task=task_def)
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task.optimized = optimized
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if optimization:
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task.optimization = optimization
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else:
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task.optimization = None
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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, Task)}
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edges = {e for e in tasks_and_edges if not isinstance(e, Task)}
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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: repl(t.task_id) or t.optimized 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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graph = self.make_graph(
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self.make_task('task1', {'no-optimize': []}),
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self.make_task('task2', {'no-optimize': []}),
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self.make_task('task3', {'no-optimize': []}),
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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,
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task2=False,
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task3=False
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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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graph = self.make_graph(
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self.make_task('task1', {'optimize-away': []}),
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self.make_task('task2', {'no-optimize': []}),
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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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graph = self.make_graph(
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self.make_task('task1', {'optimize-away': True}),
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self.make_task('task2', {'optimize-away': True}),
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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,
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task2=False
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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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graph = self.make_graph(
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self.make_task('task1', {'no-optimize': []}),
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self.make_task('task2', {'optimize-to-task': 'taskid'}),
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self.make_task('task3', {'optimize-to-task': 'taskid'}),
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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,
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task2='taskid',
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task3='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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input = self.make_graph(
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self.make_task('task1', {'optimize-to-task': 'dep1'}),
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self.make_task('task2', {'no-optimize': []}),
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self.make_task('task3', {'no-optimize': []}),
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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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if __name__ == '__main__':
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main()
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