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# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/.
from __future__ import absolute_import, print_function, unicode_literals
import pytest
import six
import unittest
from mozunit import main
from taskgraph.generator import TaskGraphGenerator, Kind, load_tasks_for_kind
from taskgraph.optimize import OptimizationStrategy
from taskgraph.config import GraphConfig
from taskgraph.util.templates import merge
from taskgraph import (
generator,
graph,
optimize as optimize_mod,
target_tasks as target_tasks_mod,
)
def fake_loader(kind, path, config, parameters, loaded_tasks):
for i in range(3):
dependencies = {}
if i >= 1:
dependencies["prev"] = "{}-t-{}".format(kind, i - 1)
task = {
"kind": kind,
"label": "{}-t-{}".format(kind, i),
"description": "{} task {}".format(kind, i),
"attributes": {"_tasknum": six.text_type(i)},
"task": {"i": i, "metadata": {"name": "t-{}".format(i)}},
"dependencies": dependencies,
}
if "job-defaults" in config:
task = merge(config["job-defaults"], task)
yield task
class FakeKind(Kind):
def _get_loader(self):
return fake_loader
def load_tasks(self, parameters, loaded_tasks, write_artifacts):
FakeKind.loaded_kinds.append(self.name)
return super(FakeKind, self).load_tasks(
parameters, loaded_tasks, write_artifacts
)
class WithFakeKind(TaskGraphGenerator):
def _load_kinds(self, graph_config, target_kind=None):
for kind_name, cfg in self.parameters["_kinds"]:
config = {
"transforms": [],
}
if cfg:
config.update(cfg)
yield FakeKind(kind_name, "/fake", config, graph_config)
def fake_load_graph_config(root_dir):
graph_config = GraphConfig(
{"trust-domain": "test-domain", "taskgraph": {}}, root_dir
)
graph_config.__dict__["register"] = lambda: None
return graph_config
class FakeParameters(dict):
strict = True
class FakeOptimization(OptimizationStrategy):
def __init__(self, mode, *args, **kwargs):
super(FakeOptimization, self).__init__(*args, **kwargs)
self.mode = mode
def should_remove_task(self, task, params, arg):
if self.mode == "always":
return True
if self.mode == "even":
return task.task["i"] % 2 == 0
if self.mode == "odd":
return task.task["i"] % 2 != 0
return False
class TestGenerator(unittest.TestCase):
@pytest.fixture(autouse=True)
def patch(self, monkeypatch):
self.patch = monkeypatch
def maketgg(self, target_tasks=None, kinds=[("_fake", [])], params=None):
params = params or {}
FakeKind.loaded_kinds = []
self.target_tasks = target_tasks or []
def target_tasks_method(full_task_graph, parameters, graph_config):
return self.target_tasks
fake_registry = {
mode: FakeOptimization(mode) for mode in ("always", "never", "even", "odd")
}
target_tasks_mod._target_task_methods["test_method"] = target_tasks_method
self.patch.setattr(optimize_mod, "registry", fake_registry)
parameters = FakeParameters(
{
"_kinds": kinds,
"backstop": False,
"target_tasks_method": "test_method",
"test_manifest_loader": "default",
"try_mode": None,
"try_task_config": {},
"tasks_for": "hg-push",
"project": "mozilla-central",
}
)
parameters.update(params)
self.patch.setattr(generator, "load_graph_config", fake_load_graph_config)
return WithFakeKind("/root", parameters)
def test_kind_ordering(self):
"When task kinds depend on each other, they are loaded in postorder"
self.tgg = self.maketgg(
kinds=[
("_fake3", {"kind-dependencies": ["_fake2", "_fake1"]}),
("_fake2", {"kind-dependencies": ["_fake1"]}),
("_fake1", {"kind-dependencies": []}),
]
)
self.tgg._run_until("full_task_set")
self.assertEqual(FakeKind.loaded_kinds, ["_fake1", "_fake2", "_fake3"])
def test_full_task_set(self):
"The full_task_set property has all tasks"
self.tgg = self.maketgg()
self.assertEqual(
self.tgg.full_task_set.graph,
graph.Graph({"_fake-t-0", "_fake-t-1", "_fake-t-2"}, set()),
)
self.assertEqual(
sorted(self.tgg.full_task_set.tasks.keys()),
sorted(["_fake-t-0", "_fake-t-1", "_fake-t-2"]),
)
def test_full_task_graph(self):
"The full_task_graph property has all tasks, and links"
self.tgg = self.maketgg()
self.assertEqual(
self.tgg.full_task_graph.graph,
graph.Graph(
{"_fake-t-0", "_fake-t-1", "_fake-t-2"},
{
("_fake-t-1", "_fake-t-0", "prev"),
("_fake-t-2", "_fake-t-1", "prev"),
},
),
)
self.assertEqual(
sorted(self.tgg.full_task_graph.tasks.keys()),
sorted(["_fake-t-0", "_fake-t-1", "_fake-t-2"]),
)
def test_target_task_set(self):
"The target_task_set property has the targeted tasks"
self.tgg = self.maketgg(["_fake-t-1"])
self.assertEqual(
self.tgg.target_task_set.graph, graph.Graph({"_fake-t-1"}, set())
)
self.assertEqual(
set(six.iterkeys(self.tgg.target_task_set.tasks)), {"_fake-t-1"}
)
def test_target_task_graph(self):
"The target_task_graph property has the targeted tasks and deps"
self.tgg = self.maketgg(["_fake-t-1"])
self.assertEqual(
self.tgg.target_task_graph.graph,
graph.Graph(
{"_fake-t-0", "_fake-t-1"}, {("_fake-t-1", "_fake-t-0", "prev")}
),
)
self.assertEqual(
sorted(self.tgg.target_task_graph.tasks.keys()),
sorted(["_fake-t-0", "_fake-t-1"]),
)
def test_always_target_tasks(self):
"The target_task_graph includes tasks with 'always_target'"
tgg_args = {
"target_tasks": ["_fake-t-0", "_fake-t-1", "_ignore-t-0", "_ignore-t-1"],
"kinds": [
("_fake", {"job-defaults": {"optimization": {"odd": None}}}),
(
"_ignore",
{
"job-defaults": {
"attributes": {"always_target": True},
"optimization": {"even": None},
}
},
),
],
"params": {"optimize_target_tasks": False},
}
self.tgg = self.maketgg(**tgg_args)
self.assertEqual(
sorted(self.tgg.target_task_set.tasks.keys()),
sorted(["_fake-t-0", "_fake-t-1", "_ignore-t-0", "_ignore-t-1"]),
)
self.assertEqual(
sorted(self.tgg.target_task_graph.tasks.keys()),
sorted(
["_fake-t-0", "_fake-t-1", "_ignore-t-0", "_ignore-t-1", "_ignore-t-2"]
),
)
self.assertEqual(
sorted([t.label for t in self.tgg.optimized_task_graph.tasks.values()]),
sorted(["_fake-t-0", "_fake-t-1", "_ignore-t-0", "_ignore-t-1"]),
)
def test_optimized_task_graph(self):
"The optimized task graph contains task ids"
self.tgg = self.maketgg(["_fake-t-2"])
tid = self.tgg.label_to_taskid
self.assertEqual(
self.tgg.optimized_task_graph.graph,
graph.Graph(
{tid["_fake-t-0"], tid["_fake-t-1"], tid["_fake-t-2"]},
{
(tid["_fake-t-1"], tid["_fake-t-0"], "prev"),
(tid["_fake-t-2"], tid["_fake-t-1"], "prev"),
},
),
)
def test_load_tasks_for_kind(monkeypatch):
"""
`load_tasks_for_kinds` will load the tasks for the provided kind
"""
monkeypatch.setattr(generator, "TaskGraphGenerator", WithFakeKind)
monkeypatch.setattr(generator, "load_graph_config", fake_load_graph_config)
tasks = load_tasks_for_kind(
{"_kinds": [("_example-kind", []), ("docker-image", [])]},
"_example-kind",
"/root",
)
assert "t-1" in tasks and tasks["t-1"].label == "_example-kind-t-1"
if __name__ == "__main__":
main()
|
