Black format

qlib/backtest/decision.py

@@ -531,7 +531,9 @@ class TradeDecisionWO(BaseTradeDecision):
     Besides, the time_range is also included.
     """
 
-    def __init__(self, order_list: List[Order], strategy: BaseStrategy, trade_range: Union[Tuple[int, int], TradeRange] = None):
+    def __init__(
+        self, order_list: List[Order], strategy: BaseStrategy, trade_range: Union[Tuple[int, int], TradeRange] = None
+    ):
         super().__init__(strategy, trade_range=trade_range)
         self.order_list = order_list
         start, end = strategy.trade_calendar.get_step_time()

qlib/rl/order_execution/from_neutrader/config.py

@@ -10,7 +10,7 @@ class ExchangeConfig:
     volume_threshold: dict
     open_cost: float = 0.0005
     close_cost: float = 0.0015
-    min_cost: float = 5.
-    trade_unit: Optional[float] = 100.
+    min_cost: float = 5.0
+    trade_unit: Optional[float] = 100.0
     cash_limit: Optional[Union[Path, float]] = None
     generate_report: bool = False

qlib/rl/order_execution/from_neutrader/feature.py

@@ -34,10 +34,15 @@ class LRUCache:
 
 
 class DataWrapper:
-
-    def __init__(self, feature_dataset: DatasetH, backtest_dataset: DatasetH,
-                 columns_today: List[str], columns_yesterday: List[str], _internal: bool = False):
-        assert _internal, 'Init function of data wrapper is for internal use only.'
+    def __init__(
+        self,
+        feature_dataset: DatasetH,
+        backtest_dataset: DatasetH,
+        columns_today: List[str],
+        columns_yesterday: List[str],
+        _internal: bool = False,
+    ):
+        assert _internal, "Init function of data wrapper is for internal use only."
 
         self.feature_dataset = feature_dataset
         self.backtest_dataset = backtest_dataset
@@ -76,8 +81,7 @@ def init_qlib(config: QlibConfig, part: Optional[str] = None) -> None:
     qlib.init(
         region=REG_CN,
         auto_mount=False,
-        custom_ops=[DayLast, FFillNan, BFillNan,
-                    Date, Select, IsNull, IsInf, Cut, DayCumsum],
+        custom_ops=[DayLast, FFillNan, BFillNan, Date, Select, IsNull, IsInf, Cut, DayCumsum],
         expression_cache=None,
         calendar_provider={
             "class": "LocalCalendarProvider",
@@ -104,22 +108,22 @@ def init_qlib(config: QlibConfig, part: Optional[str] = None) -> None:
         provider_uri=provider_uri_map,
         kernels=1,
         redis_port=-1,
-        clear_mem_cache=False  # init_qlib will be called for multiple times. Keep the cache for improving performance
+        clear_mem_cache=False,  # init_qlib will be called for multiple times. Keep the cache for improving performance
     )
 
     # this won't work if it's put outside in case of multiprocessing
 
     if part is None:
-        feature_path = config.feature_root_dir / 'feature.pkl'
-        backtest_path = config.feature_root_dir / 'backtest.pkl'
+        feature_path = config.feature_root_dir / "feature.pkl"
+        backtest_path = config.feature_root_dir / "backtest.pkl"
     else:
-        feature_path = config.feature_root_dir / 'feature' / (part + '.pkl')
-        backtest_path = config.feature_root_dir / 'backtest' / (part + '.pkl')
+        feature_path = config.feature_root_dir / "feature" / (part + ".pkl")
+        backtest_path = config.feature_root_dir / "backtest" / (part + ".pkl")
 
-    with feature_path.open('rb') as f:
+    with feature_path.open("rb") as f:
         print(feature_path)
         feature_dataset = pickle.load(f)
-    with backtest_path.open('rb') as f:
+    with backtest_path.open("rb") as f:
         backtest_dataset = pickle.load(f)
 
     _dataset = DataWrapper(
@@ -127,5 +131,5 @@ def init_qlib(config: QlibConfig, part: Optional[str] = None) -> None:
         backtest_dataset,
         config.feature_columns_today,
         config.feature_columns_yesterday,
-        _internal=True
+        _internal=True,
     )

qlib/rl/order_execution/simulator_qlib.py

@@ -31,17 +31,13 @@ def get_common_infra(
 ) -> CommonInfrastructure:
     # need to specify a range here for acceleration
     if cash_limit is None:
-        trade_account = Account(
-            init_cash=int(1e12),
-            benchmark_config={},
-            pos_type='InfPosition'
-        )
+        trade_account = Account(init_cash=int(1e12), benchmark_config={}, pos_type="InfPosition")
     else:
         trade_account = Account(
             init_cash=cash_limit,
             benchmark_config={},
-            pos_type='Position',
-            position_dict={code: {"amount": 1e12, "price": 1.} for code in codes}
+            pos_type="Position",
+            position_dict={code: {"amount": 1e12, "price": 1.0} for code in codes},
         )
 
     exchange = get_exchange(
@@ -55,7 +51,7 @@ def get_common_infra(
         start_time=trade_date,
         end_time=trade_date + pd.DateOffset(1),
         trade_unit=config.trade_unit,
-        volume_threshold=config.volume_threshold
+        volume_threshold=config.volume_threshold,
     )
 
     return CommonInfrastructure(trade_account=trade_account, trade_exchange=exchange)
@@ -145,17 +141,16 @@ class StateMaintainer:
         if len(execute_result) > 0:
             exchange = inner_executor.trade_exchange
             minutes = _get_minutes(execute_result[0][0].start_time, execute_result[-1][0].start_time)
-            market_price = np.array([
-                exchange.get_deal_price(execute_order.stock_id, t, t, direction=execute_order.direction)
-                for t in minutes
-            ])
+            market_price = np.array(
+                [
+                    exchange.get_deal_price(execute_order.stock_id, t, t, direction=execute_order.direction)
+                    for t in minutes
+                ]
+            )
             market_volume = np.array([exchange.get_volume(execute_order.stock_id, t, t) for t in minutes])
 
             datetime_list = _get_ticks_slice(
-                self._tick_index,
-                execute_result[0][0].start_time,
-                execute_result[-1][0].start_time,
-                include_end=True
+                self._tick_index, execute_result[0][0].start_time, execute_result[-1][0].start_time, include_end=True
             )
         else:
             market_price = np.array([])
@@ -188,9 +183,11 @@ class StateMaintainer:
 
         self.history_steps = _dataframe_append(
             self.history_steps,
-            [self._metrics_collect(
-                execute_order, execute_order.start_time, market_volume, market_price, exec_vol.sum(), exec_vol
-            )],
+            [
+                self._metrics_collect(
+                    execute_order, execute_order.start_time, market_volume, market_price, exec_vol.sum(), exec_vol
+                )
+            ],
         )
 
     def _metrics_collect(

qlib/rl/order_execution/tests/test_simulator_qlib.py

@@ -29,11 +29,12 @@ qlib_config = QlibConfig(
 # fmt: on
 
 exchange_config = ExchangeConfig(
-    limit_threshold=('$ask == 0', '$bid == 0'),
-    deal_price=('If($ask == 0, $bid, $ask)', 'If($bid == 0, $ask, $bid)'),
+    limit_threshold=("$ask == 0", "$bid == 0"),
+    deal_price=("If($ask == 0, $bid, $ask)", "If($bid == 0, $ask, $bid)"),
     volume_threshold={
-        'all': ('cum', "0.2 * DayCumsum($volume, '9:45', '14:44')"),
-        'buy': ('current', '$askV1'), 'sell': ('current', '$bidV1')
+        "all": ("cum", "0.2 * DayCumsum($volume, '9:45', '14:44')"),
+        "buy": ("current", "$askV1"),
+        "sell": ("current", "$bidV1"),
     },
     open_cost=0.0005,
     close_cost=0.0015,