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qlib/contrib/online/operator.py
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317
qlib/contrib/online/operator.py
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# Copyright (c) Microsoft Corporation.
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# Licensed under the MIT License.
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import fire
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import pandas as pd
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import pathlib
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import qlib
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import logging
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from ...data import D
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from ...log import get_module_logger
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from ...utils import get_pre_trading_date, is_tradable_date
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from ..evaluate import risk_analysis
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from ..backtest.backtest import update_account
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from .manager import UserManager
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from .utils import prepare
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from .utils import create_user_folder
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from .executor import load_order_list, save_order_list
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from .executor import SimulatorExecutor
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from .executor import save_score_series, load_score_series
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class Operator(object):
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def __init__(self, client: str):
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"""
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Parameters
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----------
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client: str
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The qlib client config file(.yaml)
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"""
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self.logger = get_module_logger("online operator", level=logging.INFO)
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self.client = client
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@staticmethod
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def init(client, path, date=None):
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"""Initial UserManager(), get predict date and trade date
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Parameters
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----------
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client: str
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The qlib client config file(.yaml)
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path : str
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Path to save user account.
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date : str (YYYY-MM-DD)
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Trade date, when the generated order list will be traded.
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Return
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----------
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um: UserManager()
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pred_date: pd.Timestamp
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trade_date: pd.Timestamp
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"""
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qlib.init_from_yaml_conf(client)
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um = UserManager(user_data_path=pathlib.Path(path))
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um.load_users()
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if not date:
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trade_date, pred_date = None, None
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else:
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trade_date = pd.Timestamp(date)
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if not is_tradable_date(trade_date):
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raise ValueError("trade date is not tradable date".format(trade_date.date()))
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pred_date = get_pre_trading_date(trade_date, future=True)
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return um, pred_date, trade_date
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def add_user(self, id, config, path, date):
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"""Add a new user into the a folder to run 'online' module.
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Parameters
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----------
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id : str
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User id, should be unique.
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config : str
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The file path (yaml) of user config
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path : str
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Path to save user account.
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date : str (YYYY-MM-DD)
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The date that user account was added.
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"""
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create_user_folder(path)
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qlib.init_from_yaml_conf(self.client)
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um = UserManager(user_data_path=path)
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add_date = D.calendar(end_time=date)[-1]
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if not is_tradable_date(add_date):
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raise ValueError("add date is not tradable date".format(add_date.date()))
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um.add_user(user_id=id, config_file=config, add_date=add_date)
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def remove_user(self, id, path):
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"""Remove user from folder used in 'online' module.
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Parameters
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----------
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id : str
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User id, should be unique.
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path : str
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Path to save user account.
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"""
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um = UserManager(user_data_path=path)
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um.remove_user(user_id=id)
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def generate(self, date, path):
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"""Generate order list that will be traded at 'date'.
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Parameters
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----------
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date : str (YYYY-MM-DD)
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Trade date, when the generated order list will be traded.
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path : str
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Path to save user account.
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"""
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um, pred_date, trade_date = self.init(self.client, path, date)
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for user_id, user in um.users.items():
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dates, trade_exchange = prepare(um, pred_date, user_id)
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# get and save the score at predict date
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input_data = user.model.get_data_with_date(pred_date)
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score_series = user.model.predict(input_data)
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save_score_series(score_series, (pathlib.Path(path) / user_id), trade_date)
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# update strategy (and model)
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user.strategy.update(score_series, pred_date, trade_date)
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# generate and save order list
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order_list = user.strategy.generate_order_list(
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score_series=score_series,
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current=user.account.current,
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trade_exchange=trade_exchange,
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trade_date=trade_date,
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)
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save_order_list(
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order_list=order_list,
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user_path=(pathlib.Path(path) / user_id),
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trade_date=trade_date,
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)
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self.logger.info("Generate order list at {} for {}".format(trade_date, user_id))
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um.save_user_data(user_id)
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def execute(self, date, exchange_config, path):
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"""Execute the orderlist at 'date'.
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Parameters
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----------
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date : str (YYYY-MM-DD)
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Trade date, that the generated order list will be traded.
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exchange_config: str
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The file path (yaml) of exchange config
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path : str
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Path to save user account.
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"""
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um, pred_date, trade_date = self.init(self.client, path, date)
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for user_id, user in um.users.items():
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dates, trade_exchange = prepare(um, trade_date, user_id, exchange_config)
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executor = SimulatorExecutor(trade_exchange=trade_exchange)
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if not str(dates[0].date()) == str(pred_date.date()):
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raise ValueError(
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"The account data is not newest! last trading date {}, today {}".format(
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dates[0].date(), trade_date.date()
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)
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)
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# load and execute the order list
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# will not modify the trade_account after executing
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order_list = load_order_list(user_path=(pathlib.Path(path) / user_id), trade_date=trade_date)
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trade_info = executor.execute(order_list=order_list, trade_account=user.account, trade_date=trade_date)
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executor.save_executed_file_from_trade_info(
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trade_info=trade_info,
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user_path=(pathlib.Path(path) / user_id),
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trade_date=trade_date,
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)
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self.logger.info("execute order list at {} for {}".format(trade_date.date(), user_id))
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def update(self, date, path, type="SIM"):
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"""Update account at 'date'.
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Parameters
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----------
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date : str (YYYY-MM-DD)
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Trade date, that the generated order list will be traded.
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path : str
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Path to save user account.
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type : str
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which executor was been used to execute the order list
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'SIM': SimulatorExecutor()
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"""
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if type not in ["SIM", "YC"]:
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raise ValueError("type is invalid, {}".format(type))
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um, pred_date, trade_date = self.init(self.client, path, date)
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for user_id, user in um.users.items():
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dates, trade_exchange = prepare(um, trade_date, user_id)
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if type == "SIM":
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executor = SimulatorExecutor(trade_exchange=trade_exchange)
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else:
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raise ValueError("not found executor")
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# dates[0] is the last_trading_date
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if str(dates[0].date()) > str(pred_date.date()):
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raise ValueError(
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"The account data is not newest! last trading date {}, today {}".format(
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dates[0].date(), trade_date.date()
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)
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)
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# load trade info and update account
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trade_info = executor.load_trade_info_from_executed_file(
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user_path=(pathlib.Path(path) / user_id), trade_date=trade_date
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)
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score_series = load_score_series((pathlib.Path(path) / user_id), trade_date)
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update_account(user.account, trade_info, trade_exchange, trade_date)
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report = user.account.report.generate_report_dataframe()
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self.logger.info(report)
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um.save_user_data(user_id)
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self.logger.info("Update account state {} for {}".format(trade_date, user_id))
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def simulate(self, id, config, exchange_config, start, end, path, bench="SH000905"):
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"""Run the ( generate_order_list -> execute_order_list -> update_account) process everyday
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from start date to end date.
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Parameters
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----------
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id : str
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user id, need to be unique
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config : str
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The file path (yaml) of user config
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exchange_config: str
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The file path (yaml) of exchange config
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start : str "YYYY-MM-DD"
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The start date to run the online simulate
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end : str "YYYY-MM-DD"
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The end date to run the online simulate
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path : str
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Path to save user account.
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bench : str
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The benchmark that our result compared with.
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'SH000905' for csi500, 'SH000300' for csi300
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"""
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# Clear the current user if exists, then add a new user.
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create_user_folder(path)
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um = self.init(self.client, path, None)[0]
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start_date, end_date = pd.Timestamp(start), pd.Timestamp(end)
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try:
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um.remove_user(user_id=id)
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except BaseException:
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pass
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um.add_user(user_id=id, config_file=config, add_date=pd.Timestamp(start_date))
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# Do the online simulate
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um.load_users()
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user = um.users[id]
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dates, trade_exchange = prepare(um, end_date, id, exchange_config)
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executor = SimulatorExecutor(trade_exchange=trade_exchange)
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for pred_date, trade_date in zip(dates[:-2], dates[1:-1]):
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user_path = pathlib.Path(path) / id
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# 1. load and save score_series
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input_data = user.model.get_data_with_date(pred_date)
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score_series = user.model.predict(input_data)
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save_score_series(score_series, (pathlib.Path(path) / id), trade_date)
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# 2. update strategy (and model)
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user.strategy.update(score_series, pred_date, trade_date)
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# 3. generate and save order list
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order_list = user.strategy.generate_order_list(
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score_series=score_series,
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current=user.account.current,
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trade_exchange=trade_exchange,
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trade_date=trade_date,
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)
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save_order_list(order_list=order_list, user_path=user_path, trade_date=trade_date)
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# 4. auto execute order list
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order_list = load_order_list(user_path=user_path, trade_date=trade_date)
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trade_info = executor.execute(trade_account=user.account, order_list=order_list, trade_date=trade_date)
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executor.save_executed_file_from_trade_info(
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trade_info=trade_info, user_path=user_path, trade_date=trade_date
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)
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# 5. update account state
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trade_info = executor.load_trade_info_from_executed_file(user_path=user_path, trade_date=trade_date)
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update_account(user.account, trade_info, trade_exchange, trade_date)
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report = user.account.report.generate_report_dataframe()
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self.logger.info(report)
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um.save_user_data(id)
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self.show(id, path, bench)
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def show(self, id, path, bench="SH000905"):
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"""show the newly report (mean, std, sharpe, annual)
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Parameters
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----------
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id : str
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user id, need to be unique
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path : str
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Path to save user account.
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bench : str
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The benchmark that our result compared with.
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'SH000905' for csi500, 'SH000300' for csi300
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"""
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um = self.init(self.client, path, None)[0]
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if id not in um.users:
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raise ValueError("Cannot find user ".format(id))
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bench = D.features([bench], ["$change"]).loc[bench, "$change"]
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report = um.users[id].account.report.generate_report_dataframe()
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report["bench"] = bench
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analysis_result = {}
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r = (report["return"] - report["bench"]).dropna()
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analysis_result["sub_bench"] = risk_analysis(r)
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r = (report["return"] - report["bench"] - report["cost"]).dropna()
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analysis_result["sub_cost"] = risk_analysis(r)
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print("Result:")
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print("sub_bench:")
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print(analysis_result["sub_bench"])
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print("sub_cost:")
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print(analysis_result["sub_cost"])
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def run():
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fire.Fire(Operator)
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if __name__ == "__main__":
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run()
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