style: ruff format factor module

Co-Authored-By: Claude <noreply@anthropic.com>

src/easy_tdx/cli/cmd_factor.py

@@ -1,4 +1,5 @@
 """因子 CLI 命令。"""
+
 from __future__ import annotations
 
 import json

src/easy_tdx/factor/__init__.py

@@ -1,12 +1,13 @@
 # src/easy_tdx/factor/__init__.py
 """因子研究模块。"""
+
 from __future__ import annotations
 
 from easy_tdx.factor.base import FACTORY_REGISTRY, Factor, register_factor
-from easy_tdx.factor.engine import FactorEngine
 
 # 导入 builtin 触发自动注册
 from easy_tdx.factor.builtin import get_factor, list_factors  # noqa: F401
+from easy_tdx.factor.engine import FactorEngine
 
 __all__ = [
     "Factor",

src/easy_tdx/factor/base.py

@@ -1,5 +1,6 @@
 # src/easy_tdx/factor/base.py
 """因子基类与全局注册表。"""
+
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
@@ -32,9 +33,7 @@ class Factor(ABC):
     def __init__(self) -> None:
         for attr in ("name", "category", "description", "inputs"):
             if not hasattr(self, attr):
-                raise TypeError(
-                    f"Factor 子类 {type(self).__name__} 必须定义类属性 '{attr}'"
-                )
+                raise TypeError(f"Factor 子类 {type(self).__name__} 必须定义类属性 '{attr}'")
 
 
 FACTORY_REGISTRY: dict[str, type[Factor]] = {}
@@ -47,8 +46,6 @@ def register_factor(cls: type[Factor]) -> type[Factor]:
         ValueError: 如果 name 已被注册。
     """
     if cls.name in FACTORY_REGISTRY:
-        raise ValueError(
-            f"因子 '{cls.name}' 已注册（类: {FACTORY_REGISTRY[cls.name].__name__}）"
-        )
+        raise ValueError(f"因子 '{cls.name}' 已注册（类: {FACTORY_REGISTRY[cls.name].__name__}）")
     FACTORY_REGISTRY[cls.name] = cls
     return cls

src/easy_tdx/factor/builtin/__init__.py

@@ -1,4 +1,5 @@
 """内置因子库 — 导入子模块触发注册。"""
+
 from __future__ import annotations
 
 from easy_tdx.factor.base import FACTORY_REGISTRY, Factor
@@ -35,7 +36,5 @@ def get_factor(name: str) -> type[Factor]:
         ValueError: 因子不存在。
     """
     if name not in FACTORY_REGISTRY:
-        raise ValueError(
-            f"未知因子: {name!r}。可用因子: {sorted(FACTORY_REGISTRY.keys())}"
-        )
+        raise ValueError(f"未知因子: {name!r}。可用因子: {sorted(FACTORY_REGISTRY.keys())}")
     return FACTORY_REGISTRY[name]

src/easy_tdx/factor/builtin/chanlun.py

@@ -1,4 +1,5 @@
 """缠论因子 — 桥接 ChanlunAnalyser。"""
+
 from __future__ import annotations
 
 import numpy as np

src/easy_tdx/factor/builtin/momentum.py

@@ -1,4 +1,5 @@
 """动量类因子。"""
+
 from __future__ import annotations
 
 import pandas as pd

src/easy_tdx/factor/builtin/quality.py

@@ -1,4 +1,5 @@
 """质量类因子。"""
+
 from __future__ import annotations
 
 import numpy as np

src/easy_tdx/factor/builtin/technical.py

@@ -1,4 +1,5 @@
 """技术指标因子 — 桥接 MyTT 指标库。"""
+
 from __future__ import annotations
 
 import numpy as np

src/easy_tdx/factor/builtin/value.py

@@ -1,4 +1,5 @@
 """价值类因子（需要财务数据扩展，当前为占位实现）。"""
+
 from __future__ import annotations
 
 import pandas as pd

src/easy_tdx/factor/builtin/volatility.py

@@ -1,4 +1,5 @@
 """波动率类因子。"""
+
 from __future__ import annotations
 
 import numpy as np

src/easy_tdx/factor/builtin/volume.py

@@ -1,4 +1,5 @@
 """成交量类因子。"""
+
 from __future__ import annotations
 
 import numpy as np

src/easy_tdx/factor/engine.py

@@ -1,5 +1,6 @@
 # src/easy_tdx/factor/engine.py
 """因子计算引擎 — 单股计算与截面批量计算。"""
+
 from __future__ import annotations
 
 import numpy as np
@@ -14,9 +15,7 @@ def _resolve_factor(f: str | Factor) -> Factor:
         return f
     name = f.strip()
     if name not in FACTORY_REGISTRY:
-        raise ValueError(
-            f"未知因子: {name!r}。可用因子: {sorted(FACTORY_REGISTRY.keys())}"
-        )
+        raise ValueError(f"未知因子: {name!r}。可用因子: {sorted(FACTORY_REGISTRY.keys())}")
     return FACTORY_REGISTRY[name]()
 
 
@@ -113,17 +112,17 @@ class FactorEngine:
 
             close = df["close"].to_numpy()
             forward = np.full(len(close), np.nan)
-            forward[: len(close) - period] = (
-                close[period:] / close[: len(close) - period] - 1
-            )
+            forward[: len(close) - period] = close[period:] / close[: len(close) - period] - 1
 
             dates = df["datetime"].apply(_datetime_to_int)
 
-            sub = pd.DataFrame({
-                "date": dates,
-                "code": code,
-                col_name: forward,
-            })
+            sub = pd.DataFrame(
+                {
+                    "date": dates,
+                    "code": code,
+                    col_name: forward,
+                }
+            )
             all_frames.append(sub)
 
         if not all_frames: