Use | instead of Union

qlib/rl/entries/test.py

@@ -4,7 +4,7 @@
 from __future__ import annotations
 
 import copy
-from typing import Callable, List, Sequence, Union
+from typing import Callable, List, Sequence
 
 from tianshou.data import Collector
 from tianshou.policy import BasePolicy
@@ -25,7 +25,7 @@ def backtest(
     action_interpreter: ActionInterpreter,
     initial_states: Sequence[InitialStateType],
     policy: BasePolicy,
-    logger: Union[LogWriter, List[LogWriter]],
+    logger: LogWriter | List[LogWriter],
     reward: Reward = None,
     finite_env_type: FiniteEnvType = "subproc",
     concurrency: int = 2,

qlib/rl/order_execution/interpreter.py

@@ -5,7 +5,7 @@ from __future__ import annotations
 
 import math
 from pathlib import Path
-from typing import Any, List, Union, cast
+from typing import Any, List, cast
 
 import numpy as np
 import pandas as pd
@@ -26,7 +26,7 @@ __all__ = [
 ]
 
 
-def canonicalize(value: Union[int, float, np.ndarray, pd.DataFrame, dict]) -> Union[np.ndarray, dict]:
+def canonicalize(value: int | float | np.ndarray | pd.DataFrame | dict) -> np.ndarray | dict:
     """To 32-bit numeric types. Recursively."""
     if isinstance(value, pd.DataFrame):
         return value.to_numpy()
@@ -188,7 +188,7 @@ class CategoricalActionInterpreter(ActionInterpreter[SAOEState, int, float]):
         i.e., $[0, 1/n, 2/n, \\ldots, n/n]$.
     """
 
-    def __init__(self, values: Union[int, List[float]]) -> None:
+    def __init__(self, values: int | List[float]) -> None:
         if isinstance(values, int):
             values = [i / values for i in range(0, values + 1)]
         self.action_values = values

qlib/rl/order_execution/policy.py

@@ -1,8 +1,10 @@
 # Copyright (c) Microsoft Corporation.
 # Licensed under the MIT License.
+from __future__ import annotations
+
 from abc import ABCMeta
 from pathlib import Path
-from typing import Any, Dict, Generator, Iterable, Optional, Tuple, Union, cast
+from typing import Any, Dict, Generator, Iterable, Optional, Tuple, cast
 
 import gym
 import numpy as np
@@ -48,7 +50,7 @@ class AllOne(NonLearnablePolicy):
     def forward(
         self,
         batch: Batch,
-        state: Optional[Union[dict, Batch, np.ndarray]] = None,
+        state: dict | Batch | np.ndarray = None,
         **kwargs: Any,
     ) -> Batch:
         return Batch(act=np.full(len(batch), 1.0), state=state)

qlib/rl/order_execution/simulator_simple.py

@@ -4,7 +4,7 @@
 from __future__ import annotations
 
 from pathlib import Path
-from typing import Any, NamedTuple, Optional, TypeVar, Union, cast
+from typing import Any, NamedTuple, Optional, TypeVar, cast
 
 import numpy as np
 import pandas as pd
@@ -33,7 +33,7 @@ class SAOEMetrics(TypedDict):
 
     stock_id: str
     """Stock ID of this record."""
-    datetime: Union[pd.Timestamp, pd.DatetimeIndex]  # TODO: check this
+    datetime: pd.Timestamp | pd.DatetimeIndex  # TODO: check this
     """Datetime of this record (this is index in the dataframe)."""
     direction: int
     """Direction of the order. 0 for sell, 1 for buy."""
@@ -392,7 +392,7 @@ _float_or_ndarray = TypeVar("_float_or_ndarray", float, np.ndarray)
 def price_advantage(
     exec_price: _float_or_ndarray,
     baseline_price: float,
-    direction: Union[OrderDir, int],
+    direction: OrderDir | int,
 ) -> _float_or_ndarray:
     if baseline_price == 0:  # something is wrong with data. Should be nan here
         if isinstance(exec_price, float):

qlib/rl/utils/env_wrapper.py

@@ -4,7 +4,7 @@
 from __future__ import annotations
 
 import weakref
-from typing import Any, Callable, Dict, Generic, Iterable, Iterator, Optional, Tuple, Union, cast
+from typing import Any, Callable, Dict, Generic, Iterable, Iterator, Optional, Tuple, cast
 
 import gym
 from gym import Space
@@ -92,7 +92,7 @@ class EnvWrapper(
     """
 
     simulator: Simulator[InitialStateType, StateType, ActType]
-    seed_iterator: Union[str, Iterator[InitialStateType], None]
+    seed_iterator: str | Iterator[InitialStateType] | None
 
     def __init__(
         self,

qlib/rl/utils/finite_env.py

@@ -11,7 +11,7 @@ from __future__ import annotations
 import copy
 import warnings
 from contextlib import contextmanager
-from typing import Any, Callable, Dict, Generator, List, Optional, Set, Tuple, Type, Union, cast
+from typing import Any, Callable, Dict, Generator, List, Optional, Set, Tuple, Type, cast
 
 import gym
 import numpy as np
@@ -36,7 +36,7 @@ __all__ = [
 FiniteEnvType = Literal["dummy", "subproc", "shmem"]
 
 
-def fill_invalid(obj: Union[int, float, bool, np.ndarray, dict, list, tuple]) -> Union[np.ndarray, dict, list, tuple]:
+def fill_invalid(obj: int | float | bool | np.ndarray | dict | list | tuple) -> np.ndarray | dict | list | tuple:
     if isinstance(obj, (int, float, bool)):
         return fill_invalid(np.array(obj))
     if hasattr(obj, "dtype"):
@@ -55,7 +55,7 @@ def fill_invalid(obj: Union[int, float, bool, np.ndarray, dict, list, tuple]) ->
     raise ValueError(f"Unsupported value to fill with invalid: {obj}")
 
 
-def is_invalid(arr: Union[int, float, bool, np.ndarray, dict, list, tuple]) -> bool:
+def is_invalid(arr: int | float | bool | np.ndarray | dict | list | tuple) -> bool:
     if hasattr(arr, "dtype"):
         if np.issubdtype(arr.dtype, np.floating):
             return np.isnan(arr).all()
@@ -121,7 +121,7 @@ class FiniteVectorEnv(BaseVectorEnv):
     """
 
     def __init__(
-        self, logger: Union[LogWriter, List[LogWriter]], env_fns: List[Callable[..., gym.Env]], **kwargs: Any
+        self, logger: LogWriter | List[LogWriter], env_fns: List[Callable[..., gym.Env]], **kwargs: Any
     ) -> None:
         super().__init__(env_fns, **kwargs)
 
@@ -199,7 +199,7 @@ class FiniteVectorEnv(BaseVectorEnv):
 
     def reset(
         self,
-        id: Optional[Union[int, List[int], np.ndarray]] = None,
+        id: int | List[int] | np.ndarray = None,
     ) -> np.ndarray:
         assert not self._zombie
 
@@ -251,7 +251,7 @@ class FiniteVectorEnv(BaseVectorEnv):
     def step(
         self,
         action: np.ndarray,
-        id: Optional[Union[int, List[int], np.ndarray]] = None,
+        id: int | List[int] | np.ndarray = None,
     ) -> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:
         assert not self._zombie
         id = self._wrap_id(id)
@@ -304,7 +304,7 @@ def vectorize_env(
     env_factory: Callable[..., gym.Env],
     env_type: FiniteEnvType,
     concurrency: int,
-    logger: Union[LogWriter, List[LogWriter]],
+    logger: LogWriter | List[LogWriter],
 ) -> FiniteVectorEnv:
     """Helper function to create a vector env.
 

qlib/rl/utils/log.py

@@ -18,7 +18,7 @@ import logging
 from collections import defaultdict
 from enum import IntEnum
 from pathlib import Path
-from typing import TYPE_CHECKING, Any, Dict, Generic, List, Sequence, Set, Tuple, TypeVar, Union
+from typing import TYPE_CHECKING, Any, Dict, Generic, List, Sequence, Set, Tuple, TypeVar
 
 import numpy as np
 import pandas as pd
@@ -65,19 +65,19 @@ class LogCollector:
     _logged: Dict[str, Tuple[int, Any]]
     _min_loglevel: int
 
-    def __init__(self, min_loglevel: Union[int, LogLevel] = LogLevel.PERIODIC) -> None:
+    def __init__(self, min_loglevel: int | LogLevel = LogLevel.PERIODIC) -> None:
         self._min_loglevel = int(min_loglevel)
 
     def reset(self) -> None:
         """Clear all collected contents."""
         self._logged = {}
 
-    def _add_metric(self, name: str, metric: Any, loglevel: Union[int, LogLevel]) -> None:
+    def _add_metric(self, name: str, metric: Any, loglevel: int | LogLevel) -> None:
         if name in self._logged:
             raise ValueError(f"A metric with {name} is already added. Please change a name or reset the log collector.")
         self._logged[name] = (int(loglevel), metric)
 
-    def add_string(self, name: str, string: str, loglevel: Union[int, LogLevel] = LogLevel.PERIODIC) -> None:
+    def add_string(self, name: str, string: str, loglevel: int | LogLevel = LogLevel.PERIODIC) -> None:
         """Add a string with name into logged contents."""
         if loglevel < self._min_loglevel:
             return
@@ -85,7 +85,7 @@ class LogCollector:
             raise TypeError(f"{string} is not a string.")
         self._add_metric(name, string, loglevel)
 
-    def add_scalar(self, name: str, scalar: Any, loglevel: Union[int, LogLevel] = LogLevel.PERIODIC) -> None:
+    def add_scalar(self, name: str, scalar: Any, loglevel: int | LogLevel = LogLevel.PERIODIC) -> None:
         """Add a scalar with name into logged contents.
         Scalar will be converted into a float.
         """
@@ -103,8 +103,8 @@ class LogCollector:
     def add_array(
         self,
         name: str,
-        array: Union[np.ndarray, pd.DataFrame, pd.Series],
+        array: np.ndarray | pd.DataFrame | pd.Series,
-        loglevel: Union[int, LogLevel] = LogLevel.PERIODIC,
+        loglevel: int | LogLevel = LogLevel.PERIODIC,
     ) -> None:
         """Add an array with name into logging."""
         if loglevel < self._min_loglevel:
@@ -114,7 +114,7 @@ class LogCollector:
             raise TypeError(f"{array} is not one of ndarray, DataFrame and Series.")
         self._add_metric(name, array, loglevel)
 
-    def add_any(self, name: str, obj: Any, loglevel: Union[int, LogLevel] = LogLevel.PERIODIC) -> None:
+    def add_any(self, name: str, obj: Any, loglevel: int | LogLevel = LogLevel.PERIODIC) -> None:
         """Log something with any type.
 
         As it's an "any" object, the only LogWriter accepting it is pickle.
@@ -163,7 +163,7 @@ class LogWriter(Generic[ObsType, ActType]):
     episode_logs: Dict[int, list]
     """Map from environment id to episode logs."""
 
-    def __init__(self, loglevel: Union[int, LogLevel] = LogLevel.PERIODIC) -> None:
+    def __init__(self, loglevel: int | LogLevel = LogLevel.PERIODIC) -> None:
         self.loglevel = loglevel
 
         self.global_step = 0
@@ -279,7 +279,7 @@ class ConsoleWriter(LogWriter):
         total_episodes: int = None,
         float_format: str = ":.4f",
         counter_format: str = ":4d",
-        loglevel: Union[int, LogLevel] = LogLevel.PERIODIC,
+        loglevel: int | LogLevel = LogLevel.PERIODIC,
     ) -> None:
         super().__init__(loglevel)
         # TODO: support log_every_n_step
@@ -354,7 +354,7 @@ class CsvWriter(LogWriter):
 
     all_records: List[Dict[str, Any]]
 
-    def __init__(self, output_dir: Path, loglevel: Union[int, LogLevel] = LogLevel.PERIODIC) -> None:
+    def __init__(self, output_dir: Path, loglevel: int | LogLevel = LogLevel.PERIODIC) -> None:
         super().__init__(loglevel)
         self.output_dir = output_dir
         self.output_dir.mkdir(exist_ok=True)

qlib/strategy/base.py

@@ -9,7 +9,7 @@ if TYPE_CHECKING:
     from qlib.backtest.exchange import Exchange
     from qlib.backtest.position import BasePosition
 
-from typing import Tuple, Union
+from typing import Tuple
 
 from ..backtest.decision import BaseTradeDecision
 from ..backtest.utils import CommonInfrastructure, LevelInfrastructure, TradeCalendarManager
@@ -232,8 +232,8 @@ class RLIntStrategy(RLStrategy, metaclass=ABCMeta):
     def __init__(
         self,
         policy,
-        state_interpreter: Union[dict, StateInterpreter],
+        state_interpreter: dict | StateInterpreter,
-        action_interpreter: Union[dict, ActionInterpreter],
+        action_interpreter: dict | ActionInterpreter,
         outer_trade_decision: BaseTradeDecision = None,
         level_infra: LevelInfrastructure = None,
         common_infra: CommonInfrastructure = None,