def task_with_mocked_deps(self, monkeypatch, context_dir, build_dir, dummy_source, tmpdir):
"""Create a PluginBasedTask instance with mocked task parameters.
Mock DockerBuildWorkflow accordingly. Return the mocked workflow instance for further
customization in individual tests.
"""
task_params = TaskParams(build_dir=build_dir,
config_file="config.yaml",
context_dir=str(context_dir),
namespace="test-namespace",
pipeline_run_name='test-pipeline-run',
user_params={"a": "b"})
expect_source = dummy_source
(flexmock(task_params)
.should_receive("source")
.and_return(expect_source))
expect_plugins = []
monkeypatch.setattr(plugin_based.PluginBasedTask, "plugins_conf", expect_plugins)
root_build_dir = RootBuildDir(build_dir)
# Help to verify the RootBuildDir object is passed to the workflow object.
(flexmock(plugin_based.PluginBasedTask)
.should_receive("get_build_dir")
.and_return(root_build_dir))
# The test methods inside this test case do not involve the workflow
# data. Thanks the dataclass, flexmock is able to assert the workflow
# data object, which is created during task execution, is the same as
# this one, that is they are all workflow data objects and the data
# included are same.
wf_data = ImageBuildWorkflowData()
mocked_workflow = flexmock(inner.DockerBuildWorkflow)
(
mocked_workflow
.should_call("__init__")
.once()
.with_args(
context_dir=ContextDir,
build_dir=root_build_dir,
data=wf_data,
namespace="test-namespace",
pipeline_run_name='test-pipeline-run',
source=expect_source,
plugins_conf=expect_plugins,
user_params={"a": "b"},
reactor_config_path="config.yaml",
keep_plugins_running=False,
)
)
mocked_workflow.should_receive("build_docker_image").and_raise(
AssertionError("you must mock the build_docker_image() workflow method")
)
task = plugin_based.PluginBasedTask(task_params)
return task, mocked_workflow
def test_ensure_workflow_data_is_saved_in_various_conditions(
build_result, build_dir, dummy_source, tmpdir):
context_dir = tmpdir.join("context_dir").mkdir()
params = TaskParams(build_dir=str(build_dir),
config_file="config.yaml",
context_dir=str(context_dir),
namespace="test-namespace",
pipeline_run_name='test-pipeline-run',
user_params={})
(flexmock(params).should_receive("source").and_return(dummy_source))
task = plugin_based.PluginBasedTask(params)
if build_result == "normal_return":
(flexmock(plugin_based.inner.DockerBuildWorkflow).should_receive(
"build_docker_image").once())
task.execute()
elif build_result == "error_raised":
(flexmock(plugin_based.inner.DockerBuildWorkflow).should_receive(
"build_docker_image").and_raise(BuildCanceledException))
with pytest.raises(BuildCanceledException):
task.execute()
elif build_result == "terminated":
# Start the task.execute in a separate process and terminate it.
# This simulates the Cancel behavior by TERM signal.
def _build_docker_image(self, *args, **kwargs):
def _cancel_build(*args, **kwargs):
raise BuildCanceledException()
signal.signal(signal.SIGTERM, _cancel_build)
# Whatever how long to sleep, just meaning it's running.
time.sleep(5)
(flexmock(plugin_based.inner.DockerBuildWorkflow).should_receive(
"build_docker_image").replace_with(_build_docker_image))
proc = multiprocessing.Process(target=task.execute)
proc.start()
# wait a short a while for the task.execute to run in the separate process.
time.sleep(0.3)
proc.terminate()
assert context_dir.join("workflow.json").exists()
wf_data = ImageBuildWorkflowData()
wf_data.load_from_dir(ContextDir(Path(context_dir)))
# As long as the data is loaded successfully, just check some
# attributes to check the data.
assert DockerfileImages() == wf_data.dockerfile_images
assert {} == wf_data.prebuild_results
def test_workflow_data_is_restored_before_starting_to_build(build_dir, dummy_source, tmpdir):
context_dir = tmpdir.join("context_dir").mkdir()
# Write workflow data as it was saved by a previous task
data = ImageBuildWorkflowData()
# Note: for this test, dockerfile_images can't be passed as a kwarg to
# the ImageBuildWorkflowData directly due to the flexmock of ImageBuildWorkflowData
# in the fixture, otherwise
# "TypeError: object.__new__() takes exactly one argument (the type to instantiate)"
# will be raised. So far, have no idea why it happens.
data.dockerfile_images = DockerfileImages(["scratch"])
data.tag_conf.add_floating_image("registry/app:latest")
data.plugins_results["plugin_a"] = {"var": "value"}
data.save(ContextDir(Path(context_dir)))
params = TaskParams(build_dir=str(build_dir),
config_file="config.yaml",
context_dir=str(context_dir),
namespace="test-namespace",
pipeline_run_name='test-pipeline-run',
user_params={})
(flexmock(params)
.should_receive("source")
.and_return(dummy_source))
task = plugin_based.PluginBasedTask(params)
class _FakeDockerBuildWorkflow:
def __init__(self, build_dir, data=None, **kwargs):
self.data = data
def build_docker_image(self):
assert DockerfileImages(["scratch"]) == self.data.dockerfile_images
(flexmock(plugin_based.inner)
.should_receive("DockerBuildWorkflow")
.replace_with(_FakeDockerBuildWorkflow))
task.execute()