 import argparse
import qlib
from qlib.backtest import run_backtest
from qlib.data.dataset import Dataset
from qlib.data.meta import Meta
from qlib.log import set_logging_level
from qlib.utils import get_package_path
from qlib.workflow importExecutor, Workflow
from qlib.utils.task_graph import get_following_tasks

class OnlineManager:
def **init**(self, provider\_uri, region, experiment\_name, task\_url, task\_db\_name, task\_pool\_name, rolling\_step, start\_time, end\_time, tasks, trainer):
self.provider\_uri = provider\_uri
self.region = region
self.experiment\_name = experiment\_name
self.task\_url = task\_url
self.task\_db\_name = task\_db\_name
self.task\_pool\_name = task\_pool\_name
self.rolling\_step = rolling\_step
self.start\_time = start\_time
self.end\_time = end\_time
self.tasks = tasks
self.trainer = trainer

def reset\_experiment(self):
executor = Executor(
workflow\_cls=Workflow,
provider\_uri=self.provider\_uri,
region=self.region,
)
executor.run(
And(
reset\_parameters(self.experiment\_name),
)
)

def run\_workflow(self):
executor = Executor(
workflow\_cls=Workflow,
provider\_uri=self.provider\_uri,
region=self.region,
)
executor.run(
And(
setUpClass(self.experiment\_name),
self.prepare\_tasks(),
train\_and\_test(self.experiment\_name, self.trainer),
end\_task\_train(self.experiment\_name),
tearDownClass(self.experiment\_name),
)
)

def prepare\_tasks(self):
return And(
first\_tasks(
self.experiment\_name,
self.task\_url,
self.task\_db\_name,
self.task\_pool\_name,
rolling\_step=self.rolling\_step,
start\_time=self.start\_time,
end\_time=self.end\_time,
tasks=self.tasks,
)
)

def train\_tasks(self):
following\_tasks = get\_following\_tasks(self.experiment\_name)
for task in following\_tasks:
if task.task\_name.endswith("_train"):
self.train\_task(task)

def train\_task(self, task):
executor = Executor(
workflow\_cls=Workflow,
provider\_uri=self.provider\_uri,
region=self.region,
)
executor.run(
And(
task\_train(self.experiment\_name, task.task\_id),
)
)

def collect\_results(self):
collector\_class\_name = class\_casting(
"collector",
self.experiment\_name,
)
collector\_instance = collector\_class\_name.load_from(self.experiment\_name)
collector\_instance.collect()

def get\_signals(self):
normalize\_class\_name = class\_casting(
"normalizer",
self.experiment\_name,
)
signals = normalize\_class\_name.load_from(self.experiment\_name).get()
return signals

def backtest(self):
signals = self.get\_signals()
dataset = Dataset(
instruments=signals.instruments,
features=signals.features,
data_meta=Meta.read\_meta(get\_package\_path() / "qlib/examples/data" / "meta.parquet"),
)
dataset.load(
[signals.features],
[signals],
dt=signals.timestamp,
)
backtest\_result = run\_backtest(
workflow=Workflow.load\_workflow(self.experiment\_name),
dataset=dataset,
)
return backtest\_result

def risk\_analysis(self):
# Implement risk analysis here
pass

def run(self):
self.reset\_experiment()
self.run\_workflow()
self.collect\_results()
backtest\_result = self.backtest()
self.risk\_analysis()

if **name** == "**main**":
parser = argparse.ArgumentParser()
parser.add\_argument("--provider\_uri", required=True)
parser.add\_argument("--region", required=True)
parser.add\_argument("--experiment\_name", required=True)
parser.add\_argument("--task\_url", required=True)
parser.add\_argument("--task\_db\_name", required=True)
parser.add\_argument("--task\_pool\_name", required=True)
parser.add\_argument("--rolling\_step", required=True, type=int)
parser.add\_argument("--start\_time", required=True)
parser.add\_argument("--end\_time", required=True)
parser.add\_argument("--tasks", required=True, nargs="+")
parser.add\_argument("--trainer", required=True)
args = parser.parse\_args()

online\_manager = OnlineManager(
provider\_uri=args.provider\_uri,
region=args.region,
experiment\_name=args.experiment\_name,
task\_url=args.task\_url,
task\_db\_name=args.task\_db\_name,
task\_pool\_name=args.task\_pool\_name,
rolling\_step=args.rolling\_step,
start\_time=args.start\_time,
end\_time=args.end\_time,
tasks=args.tasks,
trainer=args.trainer,
)

online\_manager.run()
set\_logging\_level("info")