mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-08-08 20:47:44 +00:00
Linlang
faa2fb03ad
* fix isort & black & toml-sort & sphinx error * fix ci error * fix ci error * add comments * Update Makefile * change sphinx build command * add auto-lint * add black args * format with black * Auto Linting document * fix ci error --------- Co-authored-by: you-n-g <you-n-g@users.noreply.github.com> Co-authored-by: Young <afe.young@gmail.com>
49 lines
1.5 KiB
Python
49 lines
1.5 KiB
Python
import pickle
|
|
from pathlib import Path
|
|
|
|
import pandas as pd
|
|
import qlib
|
|
from mlflow.entities import ViewType
|
|
from mlflow.tracking import MlflowClient
|
|
|
|
qlib.init()
|
|
|
|
from qlib.workflow import R
|
|
|
|
# here is the documents of the https://qlib.readthedocs.io/en/latest/component/recorder.html
|
|
|
|
# TODO: list all the recorder and metrics
|
|
|
|
# Assuming you have already listed the experiments
|
|
experiments = R.list_experiments()
|
|
|
|
# Iterate through each experiment to find the latest recorder
|
|
experiment_name = None
|
|
latest_recorder = None
|
|
for experiment in experiments:
|
|
recorders = R.list_recorders(experiment_name=experiment)
|
|
for recorder_id in recorders:
|
|
if recorder_id is not None:
|
|
experiment_name = experiment
|
|
recorder = R.get_recorder(recorder_id=recorder_id, experiment_name=experiment)
|
|
end_time = recorder.info["end_time"]
|
|
if latest_recorder is None or end_time > latest_recorder.info["end_time"]:
|
|
latest_recorder = recorder
|
|
|
|
# Check if the latest recorder is found
|
|
if latest_recorder is None:
|
|
print("No recorders found")
|
|
else:
|
|
print(f"Latest recorder: {latest_recorder}")
|
|
|
|
# Load the specified file from the latest recorder
|
|
metrics = pd.Series(latest_recorder.list_metrics())
|
|
|
|
output_path = Path(__file__).resolve().parent / "qlib_res.csv"
|
|
metrics.to_csv(output_path)
|
|
|
|
print(f"Output has been saved to {output_path}")
|
|
|
|
ret_data_frame = latest_recorder.load_object("portfolio_analysis/report_normal_1day.pkl")
|
|
ret_data_frame.to_pickle("ret.pkl")
|