diff --git a/qlib/backtest/__init__.py b/qlib/backtest/__init__.py
index a4c20f730..0de290f02 100644
--- a/qlib/backtest/__init__.py
+++ b/qlib/backtest/__init__.py
@@ -92,7 +92,9 @@ def get_exchange(
         return init_instance_by_config(exchange, accept_types=Exchange)
 
 
-def create_account_instance(start_time, end_time, benchmark: str, account: float, pos_type: str="Position") -> Account:
+def create_account_instance(
+    start_time, end_time, benchmark: str, account: float, pos_type: str = "Position"
+) -> Account:
     """
     # TODO: is very strange pass benchmark_config in the account(maybe for report)
     # There should be a post-step to process the report.
@@ -119,26 +121,25 @@ def create_account_instance(start_time, end_time, benchmark: str, account: float
             "start_time": start_time,
             "end_time": end_time,
         },
-        "pos_type": pos_type
+        "pos_type": pos_type,
     }
     return Account(**kwargs)
 
 
-def get_strategy_executor(start_time,
-                          end_time,
-                          strategy: BaseStrategy,
-                          executor: BaseExecutor,
-                          benchmark: str = "SH000300",
-                          account: Union[float, str] = 1e9,
-                          exchange_kwargs: dict = {},
-                          pos_type: str = "Position",
-                          ):
+def get_strategy_executor(
+    start_time,
+    end_time,
+    strategy: BaseStrategy,
+    executor: BaseExecutor,
+    benchmark: str = "SH000300",
+    account: Union[float, str] = 1e9,
+    exchange_kwargs: dict = {},
+    pos_type: str = "Position",
+):
 
-    trade_account = create_account_instance(start_time=start_time,
-                                            end_time=end_time,
-                                            benchmark=benchmark,
-                                            account=account,
-                                            pos_type=pos_type)
+    trade_account = create_account_instance(
+        start_time=start_time, end_time=end_time, benchmark=benchmark, account=account, pos_type=pos_type
+    )
 
     exchange_kwargs = copy.copy(exchange_kwargs)
     if "start_time" not in exchange_kwargs:
@@ -154,14 +155,16 @@ def get_strategy_executor(start_time,
     return trade_strategy, trade_executor
 
 
-def backtest(start_time,
-             end_time,
-             strategy,
-             executor,
-             benchmark="SH000300",
-             account=1e9,
-             exchange_kwargs={},
-             pos_type: str = "Position"):
+def backtest(
+    start_time,
+    end_time,
+    strategy,
+    executor,
+    benchmark="SH000300",
+    account=1e9,
+    exchange_kwargs={},
+    pos_type: str = "Position",
+):
 
     trade_strategy, trade_executor = get_strategy_executor(
         start_time,
@@ -178,14 +181,16 @@ def backtest(start_time,
     return report_dict, indicator_dict
 
 
-def collect_data(start_time,
-                 end_time,
-                 strategy,
-                 executor,
-                 benchmark="SH000300",
-                 account=1e9,
-                 exchange_kwargs={},
-                 pos_type: str = "Position"):
+def collect_data(
+    start_time,
+    end_time,
+    strategy,
+    executor,
+    benchmark="SH000300",
+    account=1e9,
+    exchange_kwargs={},
+    pos_type: str = "Position",
+):
 
     trade_strategy, trade_executor = get_strategy_executor(
         start_time,
diff --git a/qlib/backtest/account.py b/qlib/backtest/account.py
index 64a814dba..a6ef2f6b8 100644
--- a/qlib/backtest/account.py
+++ b/qlib/backtest/account.py
@@ -63,7 +63,9 @@ class AccumulatedInfo:
 
 
 class Account:
-    def __init__(self, init_cash: float=1e9, freq: str = "day", benchmark_config: dict = {}, pos_type:str = "Position"):
+    def __init__(
+        self, init_cash: float = 1e9, freq: str = "day", benchmark_config: dict = {}, pos_type: str = "Position"
+    ):
         self.pos_type = pos_type
         self.init_vars(init_cash, freq, benchmark_config)
 
@@ -71,13 +73,13 @@ class Account:
 
         # init cash
         self.init_cash = init_cash
-        self.current: BasePosition = init_instance_by_config({
-            'class': self.pos_type,
-            'kwargs': {
-                "cash": init_cash
-            },
-            'module_path': "qlib.backtest.position",
-        })
+        self.current: BasePosition = init_instance_by_config(
+            {
+                "class": self.pos_type,
+                "kwargs": {"cash": init_cash},
+                "module_path": "qlib.backtest.position",
+            }
+        )
         self.accum_info = AccumulatedInfo()
         self.reset(freq=freq, benchmark_config=benchmark_config, init_report=True)
 
diff --git a/qlib/backtest/backtest.py b/qlib/backtest/backtest.py
index 81395dc73..0ac4581da 100644
--- a/qlib/backtest/backtest.py
+++ b/qlib/backtest/backtest.py
@@ -23,7 +23,9 @@ def backtest_loop(start_time, end_time, trade_strategy: BaseStrategy, trade_exec
     return return_value.get("report"), return_value.get("indicator")
 
 
-def collect_data_loop(start_time, end_time, trade_strategy: BaseStrategy, trade_executor: BaseExecutor, return_value: dict = None):
+def collect_data_loop(
+    start_time, end_time, trade_strategy: BaseStrategy, trade_executor: BaseExecutor, return_value: dict = None
+):
     """Generator for collecting the trade decision data for rl training
 
     Parameters
@@ -68,7 +70,7 @@ def collect_data_loop(start_time, end_time, trade_strategy: BaseStrategy, trade_
         }
         all_indicators = {}
         for _executor in all_executors:
-            key = "{}{}".format( *Freq.parse(_executor.time_per_step))
+            key = "{}{}".format(*Freq.parse(_executor.time_per_step))
             all_indicators[key] = _executor.get_trade_indicator().generate_trade_indicators_dataframe()
             all_indicators[key + "_obj"] = _executor.get_trade_indicator()
         return_value.update({"report": all_reports, "indicator": all_indicators})
diff --git a/qlib/backtest/order.py b/qlib/backtest/order.py
index 6324a9be9..19ea807c1 100644
--- a/qlib/backtest/order.py
+++ b/qlib/backtest/order.py
@@ -2,8 +2,10 @@
 # Licensed under the MIT License.
 # TODO: rename it with decision.py
 from __future__ import annotations
+
 # try to fix circular imports when enabling type hints
 from typing import TYPE_CHECKING
+
 if TYPE_CHECKING:
     from qlib.strategy.base import BaseStrategy
 from qlib.backtest.utils import TradeCalendarManager
@@ -59,6 +61,7 @@ class BaseTradeDecision:
         1. The outer strategy's decision is available at the start of the interval
         2. Same as `case 1.3`
     """
+
     def __init__(self, strategy: BaseStrategy):
         """
         Parameters
@@ -125,7 +128,8 @@ class TradeDecisionWO(BaseTradeDecision):
     Trade Decision (W)ith (O)rder.
     Besides, the time_range is also included.
     """
-    def __init__(self, order_list: List[Order], strategy: BaseStrategy,  idx_range: Tuple=None):
+
+    def __init__(self, order_list: List[Order], strategy: BaseStrategy, idx_range: Tuple = None):
         super().__init__(strategy)
         self.order_list = order_list
         self.idx_range = idx_range
@@ -198,8 +202,7 @@ class TradeDecisionWithOrderPool:
 
 class BaseDecisionUpdater:
     def update_decision(self, decision, trade_calendar) -> BaseTradeDecision:
-        """[summary]
-
+        """
         Parameters
         ----------
         decision : BaseTradeDecision
diff --git a/qlib/backtest/position.py b/qlib/backtest/position.py
index 70272f688..0f36e4959 100644
--- a/qlib/backtest/position.py
+++ b/qlib/backtest/position.py
@@ -15,7 +15,8 @@ class BasePosition:
     The Position want to maintain the position like a dictionary
     Please refer to the `Position` class for the position
     """
-    def __init__(self, cash=0., *args, **kwargs) -> None:
+
+    def __init__(self, cash=0.0, *args, **kwargs) -> None:
         pass
 
     def skip_update(self) -> bool:
@@ -46,7 +47,6 @@ class BasePosition:
         """
         raise NotImplementedError(f"Please implement the `check_stock` method")
 
-
     def update_order(self, order: Order, trade_val: float, cost: float, trade_price: float):
         """
         Parameters
@@ -86,6 +86,7 @@ class BasePosition:
             the value(money) of all the stock
         """
         raise NotImplementedError(f"Please implement the `calculate_stock_value` method")
+
     def get_stock_list(self) -> List:
         """
         Get the list of stocks in the position.
@@ -140,7 +141,7 @@ class BasePosition:
         """
         raise NotImplementedError(f"Please implement the `get_stock_amount_dict` method")
 
-    def get_stock_weight_dict(self, only_stock: bool=False) -> Dict:
+    def get_stock_weight_dict(self, only_stock: bool = False) -> Dict:
         """
         generate stock weight dict {stock_id : value weight of stock in the position}
         it is meaningful in the beginning or the end of each trade date
@@ -399,13 +400,13 @@ class Position(BasePosition):
         self.position["now_account_value"] = now_account_value
 
 
-
 class InfPosition(BasePosition):
     """
     Position with infinite cash and amount.
 
     This is useful for generating random orders.
     """
+
     def skip_update(self) -> bool:
         """ Updating state is meaningless for InfPosition """
         return True
diff --git a/qlib/backtest/report.py b/qlib/backtest/report.py
index 3f2649839..f217ea169 100644
--- a/qlib/backtest/report.py
+++ b/qlib/backtest/report.py
@@ -18,7 +18,7 @@ from ..tests.config import CSI300_BENCH
 
 
 class Report:
-    '''
+    """
     Motivation:
         Report is for supporting portfolio related metrics.
 
@@ -26,7 +26,8 @@ class Report:
         daily report of the account
         contain those followings: returns, costs turnovers, accounts, cash, bench, value
         update report
-    '''
+    """
+
     def __init__(self, freq: str = "day", benchmark_config: dict = {}):
         """
         Parameters
diff --git a/qlib/backtest/utils.py b/qlib/backtest/utils.py
index 720eb627e..0ba607bdb 100644
--- a/qlib/backtest/utils.py
+++ b/qlib/backtest/utils.py
@@ -140,7 +140,6 @@ class BaseInfrastructure:
         self.reset_infra(**infra_dict)
 
 
-
 class CommonInfrastructure(BaseInfrastructure):
     def get_support_infra(self):
         return ["trade_account", "trade_exchange"]
diff --git a/qlib/contrib/strategy/model_strategy.py b/qlib/contrib/strategy/model_strategy.py
index 2e72cb32c..67ba4c5bc 100644
--- a/qlib/contrib/strategy/model_strategy.py
+++ b/qlib/contrib/strategy/model_strategy.py
@@ -15,6 +15,7 @@ class TopkDropoutStrategy(ModelStrategy):
     # TODO:
     # 1. Supporting leverage the get_range_limit result from the decision
     # 2. Supporting alter_outer_trade_decision
+    # 3. Supporting checking the availability of trade decision
     def __init__(
         self,
         model,
@@ -104,7 +105,7 @@ class TopkDropoutStrategy(ModelStrategy):
         pred_start_time, pred_end_time = self.trade_calendar.get_step_time(trade_step, shift=1)
         pred_score = resam_ts_data(self.pred_scores, start_time=pred_start_time, end_time=pred_end_time, method="last")
         if pred_score is None:
-            return []
+            return TradeDecisionWO([], self)
         if self.only_tradable:
             # If The strategy only consider tradable stock when make decision
             # It needs following actions to filter stocks
@@ -256,6 +257,7 @@ class WeightStrategyBase(ModelStrategy):
     # TODO:
     # 1. Supporting leverage the get_range_limit result from the decision
     # 2. Supporting alter_outer_trade_decision
+    # 3. Supporting checking the availability of trade decision
     def __init__(
         self,
         model,
@@ -332,9 +334,9 @@ class WeightStrategyBase(ModelStrategy):
         pred_start_time, pred_end_time = self.trade_calendar.get_step_time(trade_step, shift=1)
         pred_score = resam_ts_data(self.pred_scores, start_time=pred_start_time, end_time=pred_end_time, method="last")
         if pred_score is None:
-            return []
+            return TradeDecisionWO([], self)
         current_temp = copy.deepcopy(self.trade_position)
-        assert(isinstance(current_temp, Position))  # Avoid InfPosition
+        assert isinstance(current_temp, Position)  # Avoid InfPosition
 
         target_weight_position = self.generate_target_weight_position(
             score=pred_score, current=current_temp, trade_start_time=trade_start_time, trade_end_time=trade_end_time
diff --git a/qlib/contrib/strategy/rule_strategy.py b/qlib/contrib/strategy/rule_strategy.py
index b8a900b85..0fb98e8ac 100644
--- a/qlib/contrib/strategy/rule_strategy.py
+++ b/qlib/contrib/strategy/rule_strategy.py
@@ -102,7 +102,7 @@ class TWAPStrategy(BaseStrategy):
         trade_step = self.trade_calendar.get_trade_step()
         # get the total count of trading step
         start_idx, end_idx = get_start_end_idx(self, self.outer_trade_decision)
-        trade_len = end_idx - start_idx  + 1
+        trade_len = end_idx - start_idx + 1
 
         if trade_step < start_idx:
             # It is not time to start trading
@@ -137,12 +137,16 @@ class TWAPStrategy(BaseStrategy):
                 # calculate the amount of one part, ceil the amount
                 # floor((trade_unit_cnt + trade_len - rel_trade_step) / (trade_len - rel_trade_step + 1)) == ceil(trade_unit_cnt / (trade_len - rel_trade_step + 1))
                 _order_amount = (
-                    (trade_unit_cnt + trade_len - rel_trade_step - 1) // (trade_len - rel_trade_step) * _amount_trade_unit
+                    (trade_unit_cnt + trade_len - rel_trade_step - 1)
+                    // (trade_len - rel_trade_step)
+                    * _amount_trade_unit
                 )
 
             if order.direction == order.SELL:
                 # sell all amount at last
-                if self.trade_amount[order.stock_id] > 1e-5 and (_order_amount < 1e-5 or rel_trade_step == trade_len - 1):
+                if self.trade_amount[order.stock_id] > 1e-5 and (
+                    _order_amount < 1e-5 or rel_trade_step == trade_len - 1
+                ):
                     _order_amount = self.trade_amount[order.stock_id]
 
             _order_amount = min(_order_amount, self.trade_amount[order.stock_id])
@@ -173,6 +177,7 @@ class SBBStrategyBase(BaseStrategy):
     # TODO:
     # 1. Supporting leverage the get_range_limit result from the decision
     # 2. Supporting alter_outer_trade_decision
+    # 3. Supporting checking the availability of trade decision
 
     def __init__(
         self,
@@ -225,8 +230,7 @@ class SBBStrategyBase(BaseStrategy):
             self.trade_trend = {}
             self.trade_amount = {}
             # init the trade amount of order and  predicted trade trend
-            outer_order_generator = outer_trade_decision.generator()
-            for order in outer_order_generator:
+            for order in outer_trade_decision.get_decision():
                 self.trade_trend[order.stock_id] = self.TREND_MID
                 self.trade_amount[order.stock_id] = order.amount
 
@@ -248,8 +252,7 @@ class SBBStrategyBase(BaseStrategy):
         pred_start_time, pred_end_time = self.trade_calendar.get_step_time(trade_step, shift=1)
         order_list = []
         # for each order in in self.outer_trade_decision
-        outer_order_generator = self.outer_trade_decision.generator(only_enable=True)
-        for order in outer_order_generator:
+        for order in self.outer_trade_decision.get_decision():
             # get the price trend
             if trade_step % 2 == 0:
                 # in the first of two adjacent bars, predict the price trend
@@ -379,9 +382,11 @@ class SBBStrategyEMA(SBBStrategyBase):
     """
     (S)elect the (B)etter one among every two adjacent trading (B)ars to sell or buy with (EMA) signal.
     """
+
     # TODO:
     # 1. Supporting leverage the get_range_limit result from the decision
     # 2. Supporting alter_outer_trade_decision
+    # 3. Supporting checking the availability of trade decision
 
     def __init__(
         self,
@@ -463,6 +468,7 @@ class ACStrategy(BaseStrategy):
     # TODO:
     # 1. Supporting leverage the get_range_limit result from the decision
     # 2. Supporting alter_outer_trade_decision
+    # 3. Supporting checking the availability of trade decision
     def __init__(
         self,
         lamb: float = 1e-6,
@@ -555,8 +561,7 @@ class ACStrategy(BaseStrategy):
         if outer_trade_decision is not None:
             self.trade_amount = {}
             # init the trade amount of order and  predicted trade trend
-            outer_order_generator = outer_trade_decision.generator()
-            for order in outer_order_generator:
+            for order in outer_trade_decision.get_decision():
                 self.trade_amount[order.stock_id] = order.amount
 
     def generate_trade_decision(self, execute_result=None):
@@ -564,8 +569,6 @@ class ACStrategy(BaseStrategy):
         trade_step = self.trade_calendar.get_trade_step()
         # get the total count of trading step
         trade_len = self.trade_calendar.get_trade_len()
-        # update outer trade decision
-        self.outer_trade_decision.update(self.trade_calendar)
 
         # update the order amount
         if execute_result is not None:
@@ -575,8 +578,7 @@ class ACStrategy(BaseStrategy):
         trade_start_time, trade_end_time = self.trade_calendar.get_step_time(trade_step)
         pred_start_time, pred_end_time = self.trade_calendar.get_step_time(trade_step, shift=1)
         order_list = []
-        outer_order_generator = self.outer_trade_decision.generator(only_enable=True)
-        for order in outer_order_generator:
+        for order in self.outer_trade_decision.get_decision():
             # if not tradable, continue
             if not self.trade_exchange.is_stock_tradable(
                 stock_id=order.stock_id, start_time=trade_start_time, end_time=trade_end_time
@@ -638,14 +640,16 @@ class ACStrategy(BaseStrategy):
 
 
 class RandomOrderStrategy(BaseStrategy):
-
-    def __init__(self,
-                 index_range: Tuple[int, int],  # The range is closed on both left and right.
-                 sample_ratio: float = 1.,
-                 volume_ratio: float = 0.01,
-                 market: str = "all",
-                 *args,
-                 **kwargs):
+    def __init__(
+        self,
+        index_range: Tuple[int, int],  # The range is closed on both left and right.
+        sample_ratio: float = 1.0,
+        volume_ratio: float = 0.01,
+        market: str = "all",
+        direction: int = Order.BUY,
+        *args,
+        **kwargs,
+    ):
         """
         Parameters
         ----------
@@ -667,9 +671,12 @@ class RandomOrderStrategy(BaseStrategy):
         self.sample_ratio = sample_ratio
         self.volume_ratio = volume_ratio
         self.market = market
+        self.direction = direction
         exch: Exchange = self.common_infra.get("trade_exchange")
         # TODO: this can't be online
-        self.volume = D.features(D.instruments(market), ["Mean(Ref($volume, 1), 10)"], start_time=exch.start_time, end_time=exch.end_time)
+        self.volume = D.features(
+            D.instruments(market), ["Mean(Ref($volume, 1), 10)"], start_time=exch.start_time, end_time=exch.end_time
+        )
         self.volume_df = self.volume.iloc[:, 0].unstack()
 
     def generate_trade_decision(self, execute_result=None):
@@ -677,15 +684,15 @@ class RandomOrderStrategy(BaseStrategy):
         step_time_start, step_time_end = self.trade_calendar.get_step_time(trade_step)
 
         order_list = []
-        for direction in Order.SELL, Order.BUY:
-            if step_time_start in self.volume_df:
-                for stock_id, volume in self.volume_df[step_time_start].dropna().sample(frac=self.sample_ratio).items():
-                    order_list.append(
-                        self.common_infra.get("trade_exchange").create_order(
-                            code=stock_id,
-                            amount=volume * self.volume_ratio,
-                            start_time=step_time_start,
-                            end_time=step_time_end,
-                            direction=direction,  # 1 for buy
-                        ))
+        if step_time_start in self.volume_df:
+            for stock_id, volume in self.volume_df[step_time_start].dropna().sample(frac=self.sample_ratio).items():
+                order_list.append(
+                    self.common_infra.get("trade_exchange").create_order(
+                        code=stock_id,
+                        amount=volume * self.volume_ratio,
+                        start_time=step_time_start,
+                        end_time=step_time_end,
+                        direction=self.direction,
+                    )
+                )
         return TradeDecisionWO(order_list, self, self.index_range)
diff --git a/qlib/data/data.py b/qlib/data/data.py
index 116861e78..d6735b4e6 100644
--- a/qlib/data/data.py
+++ b/qlib/data/data.py
@@ -213,7 +213,7 @@ class InstrumentProvider(abc.ABC, ProviderBackendMixin):
         self.backend = kwargs.get("backend", {})
 
     @staticmethod
-    def instruments(market: Union[List, str]="all", filter_pipe: Union[List, None]=None):
+    def instruments(market: Union[List, str] = "all", filter_pipe: Union[List, None] = None):
         """Get the general config dictionary for a base market adding several dynamic filters.
 
         Parameters
diff --git a/qlib/strategy/base.py b/qlib/strategy/base.py
index 734d25721..c8a326e80 100644
--- a/qlib/strategy/base.py
+++ b/qlib/strategy/base.py
@@ -85,7 +85,9 @@ class BaseStrategy:
         """
         raise NotImplementedError("generate_trade_decision is not implemented!")
 
-    def update_trade_decision(self, trade_decision: BaseTradeDecision, trade_calendar: TradeCalendarManager) -> Union[BaseTradeDecision, None]:
+    def update_trade_decision(
+        self, trade_decision: BaseTradeDecision, trade_calendar: TradeCalendarManager
+    ) -> Union[BaseTradeDecision, None]:
         """
         update trade decision in each step of inner execution, this method enable all order
 
diff --git a/qlib/utils/resam.py b/qlib/utils/resam.py
index 76d97e1bc..4df155946 100644
--- a/qlib/utils/resam.py
+++ b/qlib/utils/resam.py
@@ -9,6 +9,7 @@ from . import lazy_sort_index
 from ..config import C
 from .time import Freq, cal_sam_minute
 
+
 def resam_calendar(calendar_raw: np.ndarray, freq_raw: str, freq_sam: str) -> np.ndarray:
     """
     Resample the calendar with frequency freq_raw into the calendar with frequency freq_sam
diff --git a/qlib/utils/time.py b/qlib/utils/time.py
index fb37fd0a4..bfbdb9f1f 100644
--- a/qlib/utils/time.py
+++ b/qlib/utils/time.py
@@ -14,7 +14,7 @@ import functools
 
 
 @functools.lru_cache(maxsize=240)
-def get_min_cal(shift: int=0) -> List[time]:
+def get_min_cal(shift: int = 0) -> List[time]:
     """
     get the minute level calendar in day period
 
@@ -30,8 +30,9 @@ def get_min_cal(shift: int=0) -> List[time]:
 
     """
     cal = []
-    for ts in list(pd.date_range("9:30", "11:29", freq="1min") - pd.Timedelta(minutes=shift)) +\
-                list(pd.date_range("13:00", "14:59", freq="1min") - pd.Timedelta(minutes=shift)):
+    for ts in list(pd.date_range("9:30", "11:29", freq="1min") - pd.Timedelta(minutes=shift)) + list(
+        pd.date_range("13:00", "14:59", freq="1min") - pd.Timedelta(minutes=shift)
+    ):
         cal.append(ts.time())
     return cal
 
@@ -115,7 +116,7 @@ def get_day_min_idx_range(start: str, end: str, freq: str) -> Tuple[int, int]:
     start = pd.Timestamp(start).time()
     end = pd.Timestamp(end).time()
     freq = Freq(freq)
-    in_day_cal = Freq.MIN_CAL[::freq.count]
+    in_day_cal = Freq.MIN_CAL[:: freq.count]
     left_idx = bisect.bisect_left(in_day_cal, start)
     right_idx = bisect.bisect_right(in_day_cal, end) - 1
     return left_idx, right_idx
@@ -141,15 +142,19 @@ def cal_sam_minute(x: pd.Timestamp, sam_minutes: int) -> pd.Timestamp:
     """
     cal = get_min_cal(C.min_data_shift)[::sam_minutes]
     idx = bisect.bisect_right(cal, x.time()) - 1
-    date, new_time =  x.date(), cal[idx]
+    date, new_time = x.date(), cal[idx]
     return pd.Timestamp(
-        datetime(date.year,
-                 month=date.month,
-                 day=date.day,
-                 hour=new_time.hour,
-                 minute=new_time.minute,
-                 second=new_time.second,
-                 microsecond=new_time.microsecond))
+        datetime(
+            date.year,
+            month=date.month,
+            day=date.day,
+            hour=new_time.hour,
+            minute=new_time.minute,
+            second=new_time.second,
+            microsecond=new_time.microsecond,
+        )
+    )
+
 
 if __name__ == "__main__":
     print(get_day_min_idx_range("8:30", "14:59", "10min"))