def test_get_data_inputs_not_found(self):
pipeline_instance = MagicMock()
pipeline_instance.instance_id = "instance_id_token"
runtime = MagicMock()
runtime.get_context = MagicMock(return_value="context_value_return")
runtime.get_data_inputs = MagicMock(
side_effect=exceptions.NotFoundError)
runtime_cls = MagicMock(return_value=runtime)
with mock.patch(TASKFLOW_DISPATCHERS_TASK_BAMBOO_DJANGO_RUNTIME,
runtime_cls):
dispatcher = TaskCommandDispatcher(
engine_ver=2,
taskflow_id=1,
pipeline_instance=pipeline_instance,
project_id=1)
result = dispatcher.render_current_constants_v2()
runtime.get_context.assert_called_once_with(
pipeline_instance.instance_id)
runtime.get_data_inputs.assert_called_once_with(
pipeline_instance.instance_id)
self.assertEqual(
result,
{
"result": False,
"data": None,
"code": err_code.CONTENT_NOT_EXIST.code,
"message": "data not found, task is not running",
},
)
def test_normal(self):
pipeline_instance = MagicMock()
pipeline_instance.instance_id = "instance_id_token"
runtime = MagicMock()
runtime.get_context = MagicMock(return_value="context_value_return")
runtime.get_data_inputs = MagicMock(
return_value={
"root_key": DataInput(need_render=False, value="root_val")
})
context = MagicMock()
context.hydrate = MagicMock(
return_value={
"k1": SystemObject({"system_key": "system_val"}),
"k2": "val2"
})
runtime_cls = MagicMock(return_value=runtime)
context_cls = MagicMock(return_value=context)
with mock.patch(TASKFLOW_DISPATCHERS_TASK_BAMBOO_DJANGO_RUNTIME,
runtime_cls):
with mock.patch(TASKFLOW_DISPATCHERS_TASK_CONTEXT, context_cls):
dispatcher = TaskCommandDispatcher(
engine_ver=2,
taskflow_id=1,
pipeline_instance=pipeline_instance,
project_id=1)
result = dispatcher.render_current_constants_v2()
runtime.get_context.assert_called_once_with(
pipeline_instance.instance_id)
runtime.get_data_inputs.assert_called_once_with(
pipeline_instance.instance_id)
context_cls.assert_called_once_with(runtime, "context_value_return",
{"root_key": "root_val"})
context.hydrate.assert_called_once()
self.assertEqual(
result,
{
"result":
True,
"data": [{
"key": "k1",
"value": {
"system_key": "system_val"
}
}, {
"key": "k2",
"value": "val2"
}],
"code":
err_code.SUCCESS.code,
"message":
"",
},
)
def test_is_not_started(self):
pipeline_instance = MagicMock()
pipeline_instance.is_started = False
dispatcher = TaskCommandDispatcher(engine_ver=1,
taskflow_id=1,
pipeline_instance=pipeline_instance,
project_id=1)
result = dispatcher.render_current_constants_v1()
self.assertEqual(
result,
{
"result": False,
"data": None,
"code": err_code.INVALID_OPERATION.code,
"message": "task is not running"
},
)
def test_hydrate_error(self):
pipeline_instance = MagicMock()
pipeline_instance.instance_id = "instance_id_token"
runtime = MagicMock()
runtime.get_context = MagicMock(return_value="context_value_return")
runtime.get_data_inputs = MagicMock(
return_value={
"root_key": DataInput(need_render=False, value="root_val")
})
context = MagicMock()
context.hydrate = MagicMock(side_effect=Exception("exception message"))
runtime_cls = MagicMock(return_value=runtime)
context_cls = MagicMock(return_value=context)
with mock.patch(TASKFLOW_DISPATCHERS_TASK_BAMBOO_DJANGO_RUNTIME,
runtime_cls):
with mock.patch(TASKFLOW_DISPATCHERS_TASK_CONTEXT, context_cls):
dispatcher = TaskCommandDispatcher(
engine_ver=2,
taskflow_id=1,
pipeline_instance=pipeline_instance,
project_id=1)
result = dispatcher.render_current_constants_v2()
runtime.get_context.assert_called_once_with(
pipeline_instance.instance_id)
runtime.get_data_inputs.assert_called_once_with(
pipeline_instance.instance_id)
context_cls.assert_called_once_with(runtime, "context_value_return",
{"root_key": "root_val"})
context.hydrate.assert_called_once()
self.assertEqual(
result,
{
"result": False,
"data": None,
"code": err_code.UNKNOWN_ERROR.code,
"message": "context hydrate error: exception message",
},
)
def pipeline_archive_statistics_task(instance_id):
taskflow_instance = TaskFlowInstance.objects.get(
pipeline_instance__instance_id=instance_id)
# 更新taskflowinstance统计数据start_time finish_time elapsed_time
taskflow_statistic = TaskflowStatistics.objects.filter(
task_instance_id=taskflow_instance.id).first()
if taskflow_statistic:
start_time = taskflow_instance.pipeline_instance.start_time
finish_time = taskflow_instance.pipeline_instance.finish_time
taskflow_statistic.start_time = start_time
taskflow_statistic.finish_time = finish_time
taskflow_statistic.elapsed_time = calculate_elapsed_time(
start_time, finish_time)
taskflow_statistic.save()
engine_ver = taskflow_instance.engine_ver
# 获取任务实例执行树
cmd_dispatcher = TaskCommandDispatcher(engine_ver, taskflow_instance.id,
taskflow_instance.pipeline_instance,
taskflow_instance.project.id)
status_tree_result = cmd_dispatcher.get_task_status()
if not status_tree_result["result"]:
logger.exception(
"get task_status_result fail, taskflow_instace = {id}.".format(
id=taskflow_instance.id))
return False
# 删除原有标准插件执行数据
TaskflowExecutedNodeStatistics.objects.filter(
instance_id=taskflow_instance.pipeline_instance.id).delete()
data = taskflow_instance.pipeline_instance.execution_data
try:
component_list = recursive_collect_components_execution(
activities=data[PE.activities],
status_tree=status_tree_result["data"]["children"],
task_instance=taskflow_instance,
engine_ver=engine_ver,
)
TaskflowExecutedNodeStatistics.objects.bulk_create(component_list)
except Exception:
logger.exception((
"pipeline_instance_handler save TaskflowExecuteNodeStatistics[instance_id={instance_id}] raise error"
).format(instance_id=instance_id))
return False
return True
def get(self, request, task_id, format=None):
# fetch require task data
task = TaskFlowInstance.objects.filter(id=task_id).only(
"id", "engine_ver", "pipeline_instance", "project_id")[0]
# dispatch get constants command
resp_data = TaskCommandDispatcher(
engine_ver=task.engine_ver,
taskflow_id=task.id,
pipeline_instance=task.pipeline_instance,
project_id=task.project_id,
).render_current_constants()
if resp_data["result"]:
for var in resp_data["data"]:
if safe_for_json(var["value"]):
continue
var["value"] = str(var["value"].__dict__) if hasattr(
var["value"], "__dict__") else str(var["value"])
return Response(resp_data)
def test_normal(self):
self.maxDiff = None
pipeline_instance = MagicMock()
pipeline_instance.is_started = True
pipeline_instance.is_finished = False
pipeline_instance.is_revoked = False
pipeline_instance.instance_id = "instance_id_token"
pipeline_model = MagicMock()
class VariableMagicMock(MagicMock, Variable):
pass
class TestTaskContext(TaskContext):
def __init__(self):
self.value = "TestTaskContext"
class TestValueVar(Variable):
def __init__(self, value):
self.value = value
var1 = TestValueVar(value=TestTaskContext())
var2 = VariableMagicMock()
var2.get = MagicMock(return_value="val2")
var4 = VariableMagicMock()
var4.get = MagicMock(side_effect=Exception)
pipeline_model.process.root_pipeline.context.variables = {
"k1": var1,
"k2": var2,
"k4": var4,
"k5": "v5",
"k6": 6,
}
pipeline_model_cls = MagicMock()
pipeline_model_cls.objects.get = MagicMock(return_value=pipeline_model)
with mock.patch(TASKFLOW_DISPATCHERS_TASK_PIPELINE_MODEL,
pipeline_model_cls):
dispatcher = TaskCommandDispatcher(
engine_ver=1,
taskflow_id=1,
pipeline_instance=pipeline_instance,
project_id=1)
result = dispatcher.render_current_constants_v1()
pipeline_model_cls.objects.get.assert_called_once_with(
id=pipeline_instance.instance_id)
self.assertEqual(
result,
{
"result":
True,
"data": [
{
"key": "k1",
"value": {
"value": "TestTaskContext"
}
},
{
"key": "k2",
"value": "val2"
},
{
"key": "k4",
"value": "[ERROR]value resolve error"
},
{
"key": "k5",
"value": "v5"
},
{
"key": "k6",
"value": 6
},
],
"code":
err_code.SUCCESS.code,
"message":
"",
},
)