feat(framework_v2): 实现通用配置系统，支持扁平化资产池和策略分组
- 使用 Pydantic Schema 验证配置类型安全 - 实现扁平化 AssetPool，移除预设分类（equity/commodity/fixed_income） - 移除 MarketType 枚举，改用 group 字符串字段实现策略分组 - AssetConfig 引入 signal_source/trade_source 分离，支持跨市场场景 - ConfigLoader 支持通用 StrategyConfig，向后兼容 RotationStrategyConfig - 新增 GroupConfig 替代 MarketGroupConfig，支持分散化选股 重构核心： - market → group（策略分组语义，组内竞争强制分散） - by_market → by_group - MarketGroupConfig → GroupConfig
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framework_v2/config/schemas.py
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framework_v2/config/schemas.py
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"""
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配置 Schema 定义
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使用 Pydantic 验证配置文件的类型安全
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"""
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from pydantic import BaseModel, Field, field_validator, model_validator
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from typing import Optional, Dict, List, Literal
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from enum import Enum
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from datetime import date
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# ============================================================
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# 枚举类型
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# ============================================================
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# 注意：不再使用 MarketType 枚举，改用字符串类型的 group 字段
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# group 字段用于策略分组（组内竞争，强制分散）
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class FactorType(str, Enum):
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"""因子类型枚举"""
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MOMENTUM = "momentum"
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SLOPE_R2 = "slope_r2"
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WEIGHTED_MOMENTUM = "weighted_momentum"
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class PremiumMode(str, Enum):
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"""溢价控制模式"""
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FILTER = "filter" # 完全排除
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PENALIZE = "penalize" # 降权
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class ThresholdMode(str, Enum):
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"""阈值模式"""
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FIXED = "fixed" # 固定阈值
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DYNAMIC = "dynamic" # 动态阈值
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class DataSourceType(str, Enum):
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"""数据源类型"""
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FLASK_API = "flask_api"
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TUSHARE = "tushare"
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YFINANCE = "yfinance"
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# ============================================================
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# 资产池 Schema（扁平化设计）
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# ============================================================
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class PremiumConfig(BaseModel):
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"""溢价控制配置"""
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enabled: bool = Field(default=True, description="是否启用")
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threshold: float = Field(default=0.10, ge=0, le=1.0, description="溢价阈值")
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class AssetConfig(BaseModel):
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"""
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标的配置（通用，支持所有场景）
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场景 1：指数信号 → 指数收益
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signal_source: "NDX"
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trade_source: "NDX"
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场景 2：指数信号 → ETF收益
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signal_source: "NDX"
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trade_source: "513100.SH"
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场景 3：ETF信号 → ETF收益
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signal_source: "518880.SH"
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trade_source: "518880.SH"
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场景 4：个股信号 → 个股收益
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signal_source: "AAPL"
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trade_source: "AAPL"
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"""
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name: str = Field(..., description="标的名称")
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group: str = Field(..., description="策略分组（组内竞争，强制分散）")
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# 核心字段：信号来源和交易来源
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signal_source: str = Field(..., description="信号来源代码（计算因子用）")
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trade_source: str = Field(..., description="交易来源代码（计算收益用）")
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# 可选字段
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description: Optional[str] = Field(None, description="标的描述")
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etf: Optional[str] = Field(None, description="ETF代码（兼容旧配置）")
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premium_control: Optional["PremiumConfig"] = Field(None, description="溢价控制配置")
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@property
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def is_cross_market(self) -> bool:
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"""是否跨市场（信号和交易不同）"""
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return self.signal_source != self.trade_source
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class AssetPool(BaseModel):
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"""
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资产池（扁平化设计）
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优势：
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1. 不预设分类，支持任意策略分组
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2. 通过 group 字段自动分组
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3. 配置简单直观
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4. 易于扩展新分组
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示例:
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asset_pool:
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assets:
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"NDX":
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name: "纳指100"
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group: "US_TECH"
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signal_source: "NDX"
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trade_source: "513100.SH"
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"BTC":
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name: "比特币"
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group: "CRYPTO"
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signal_source: "BTC"
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trade_source: "BTC"
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"""
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assets: Dict[str, AssetConfig] = Field(
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default_factory=dict,
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description="所有标的（flat结构）"
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)
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@property
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def by_group(self) -> Dict[str, Dict[str, AssetConfig]]:
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"""按策略分组"""
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groups = {}
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for code, asset in self.assets.items():
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group = asset.group
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if group not in groups:
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groups[group] = {}
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groups[group][code] = asset
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return groups
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@property
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def groups(self) -> list:
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"""获取所有策略分组"""
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return list(self.by_group.keys())
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def get_signal_codes(self, group: str = None) -> list:
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"""
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获取信号标的
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Args:
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group: 可选，过滤特定分组（如 'US_TECH'）
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"""
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if group:
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return [
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asset.signal_source
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for asset in self.assets.values()
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if asset.group == group
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]
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return [asset.signal_source for asset in self.assets.values()]
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def get_trade_codes(self, group: str = None) -> list:
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"""获取交易标的"""
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if group:
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return [
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asset.trade_source
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for asset in self.assets.values()
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if asset.group == group
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]
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return [asset.trade_source for asset in self.assets.values()]
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def get_signal_to_trade_mapping(self, group: str = None) -> Dict[str, str]:
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"""获取信号→交易映射"""
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mapping = {}
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for asset in self.assets.values():
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if group and asset.group != group:
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continue
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mapping[asset.signal_source] = asset.trade_source
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return mapping
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def count(self, group: str = None) -> int:
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"""获取标的数量"""
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if group:
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return len([a for a in self.assets.values() if a.group == group])
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return len(self.assets)
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@field_validator('assets')
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@classmethod
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def check_non_empty(cls, v):
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"""至少配置一个标的"""
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if not v:
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import warnings
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warnings.warn("资产池为空")
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return v
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# ============================================================
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# 因子配置 Schema
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# ============================================================
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class FactorConfig(BaseModel):
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"""因子配置"""
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type: FactorType = Field(default=FactorType.WEIGHTED_MOMENTUM, description="因子类型")
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n_days: int = Field(default=25, ge=5, le=250, description="动量窗口期（天数）")
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# 动态周期参数
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auto_day: bool = Field(default=False, description="是否启用动态周期")
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min_days: int = Field(default=20, ge=5, le=100, description="最小周期")
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max_days: int = Field(default=60, ge=20, le=250, description="最大周期")
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# ============================================================
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# 阈值配置 Schema
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# ============================================================
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class DynamicThresholdConfig(BaseModel):
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"""动态阈值配置"""
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reference: str = Field(..., description="参考标的代码")
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ratio: float = Field(default=1.0, gt=0, description="倍数")
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fallback_enabled: bool = Field(default=True, description="参考不可用时是否回退")
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fallback_value: float = Field(default=0.0, description="回退值")
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class ThresholdConfig(BaseModel):
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"""阈值配置（统一 V2/V3）"""
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mode: ThresholdMode = Field(default=ThresholdMode.DYNAMIC, description="阈值模式")
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fixed_value: float = Field(default=0.0, description="固定阈值（mode=fixed时使用）")
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dynamic: Optional[DynamicThresholdConfig] = Field(None, description="动态阈值（mode=dynamic时使用）")
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@model_validator(mode='after')
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def validate_dynamic_config(self):
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"""验证动态阈值配置"""
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if self.mode == ThresholdMode.DYNAMIC and self.dynamic is None:
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raise ValueError("dynamic 模式必须配置 dynamic 字段")
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return self
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# ============================================================
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# 轮动配置 Schema
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# ============================================================
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class GroupConfig(BaseModel):
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"""策略分组配置（用于分散化选股）"""
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group: str = Field(..., description="策略分组名称")
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select_num: int = Field(default=1, ge=1, le=10, description="该分组选股数量")
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class RotationConfig(BaseModel):
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"""
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轮动配置
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支持两种选股模式：
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1. 全局选股：diversified=false，直接选 Top-N
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2. 分散化选股：diversified=true，按策略分组选股
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"""
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select_num: int = Field(default=3, ge=1, le=20, description="选股数量（全局模式）")
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diversified: bool = Field(default=False, description="是否分散化选股")
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# 分散化配置（可选）
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diversification_groups: Optional[List[GroupConfig]] = Field(
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None,
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description="分散化分组配置（diversified=true时使用）"
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)
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threshold: ThresholdConfig = Field(
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default_factory=ThresholdConfig,
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description="动量阈值"
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)
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# ============================================================
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# 调仓配置 Schema
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# ============================================================
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class RebalanceConfig(BaseModel):
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"""调仓配置"""
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min_hold_days: int = Field(default=1, ge=1, le=30, description="最低持有天数")
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score_threshold: float = Field(default=0.0, ge=0, le=0.5, description="调仓得分阈值（%）")
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trade_cost: float = Field(default=0.001, ge=0, le=0.01, description="单次换仓成本")
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# ============================================================
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# 溢价控制 Schema
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# ============================================================
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class MarketPremiumOverride(BaseModel):
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"""市场溢价覆盖配置"""
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enabled: bool = Field(default=True, description="是否启用")
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threshold: float = Field(default=0.10, ge=0, le=1.0, description="溢价阈值")
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class PremiumControlConfig(BaseModel):
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"""溢价控制配置"""
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enabled: bool = Field(default=True, description="是否启用溢价控制")
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default_threshold: float = Field(default=0.10, ge=0, le=1.0, description="默认溢价阈值")
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mode: PremiumMode = Field(default=PremiumMode.FILTER, description="控制模式")
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penalty_factor: float = Field(default=0.5, ge=0, le=1.0, description="降权惩罚系数")
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# 按市场覆盖
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market_overrides: Dict[str, MarketPremiumOverride] = Field(
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default_factory=dict,
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description="按市场覆盖配置"
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)
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# ============================================================
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# 数据源配置 Schema
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# ============================================================
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class DataSourceConfig(BaseModel):
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"""单个数据源配置"""
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type: DataSourceType = Field(..., description="数据源类型")
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enabled: bool = Field(default=True, description="是否启用")
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timeout: int = Field(default=120, ge=10, le=600, description="超时时间（秒）")
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# Flask API 特定配置
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url: Optional[str] = Field(None, description="API地址（flask_api使用）")
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# Tushare 特定配置
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token: Optional[str] = Field(None, description="Tushare Token（tushare使用）")
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class DataConfig(BaseModel):
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"""数据配置"""
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sources: List[DataSourceConfig] = Field(..., description="数据源列表（按优先级排序）")
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use_cache: bool = Field(default=True, description="是否使用本地缓存")
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cache_dir: str = Field(default="data_cache", description="缓存目录")
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@field_validator('sources')
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@classmethod
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def check_at_least_one(cls, v):
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"""至少配置一个数据源"""
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if not v:
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raise ValueError("必须配置至少一个数据源")
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return v
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# ============================================================
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# 基准配置 Schema
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# ============================================================
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class BenchmarkConfig(BaseModel):
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"""基准配置"""
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code: str = Field(..., description="基准代码")
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name: str = Field(..., description="基准名称")
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# ============================================================
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# 回测配置 Schema
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# ============================================================
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class BacktestConfig(BaseModel):
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"""回测配置"""
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start_date: str = Field(..., description="回测起始日期（YYYY-MM-DD）")
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end_date: Optional[str] = Field(None, description="回测结束日期（None表示至今）")
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# ============================================================
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# 元数据 Schema
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# ============================================================
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class MetadataConfig(BaseModel):
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"""配置元数据"""
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version: str = Field(default="1.0.0", description="配置版本")
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strategy: str = Field(default="rotation", description="策略名称")
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description: str = Field(default="", description="配置描述")
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last_updated: Optional[str] = Field(None, description="最后更新日期")
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# ============================================================
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# 完整策略配置 Schema
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# ============================================================
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class RotationStrategyConfig(BaseModel):
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"""
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ETF轮动策略完整配置
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使用示例:
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from framework_v2.config.schemas import RotationStrategyConfig
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import yaml
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with open('config/rotation.yaml') as f:
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config_dict = yaml.safe_load(f)
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config = RotationStrategyConfig(**config_dict)
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"""
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metadata: MetadataConfig = Field(default_factory=MetadataConfig, description="元数据")
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# 资产池
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asset_pools: AssetPool = Field(..., description="资产池配置")
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# 基准
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benchmark: BenchmarkConfig = Field(..., description="基准配置")
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# 回测
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backtest: BacktestConfig = Field(..., description="回测配置")
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# 因子
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factor: FactorConfig = Field(default_factory=FactorConfig, description="因子配置")
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# 轮动
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rotation: RotationConfig = Field(default_factory=RotationConfig, description="轮动配置")
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# 调仓
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rebalance: RebalanceConfig = Field(default_factory=RebalanceConfig, description="调仓配置")
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# 溢价控制
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premium_control: PremiumControlConfig = Field(default_factory=PremiumControlConfig, description="溢价控制")
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# 数据
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data: DataConfig = Field(..., description="数据配置")
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# ============================================================
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# 通用策略配置 Schema（V2 架构）
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# ============================================================
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class StrategyConfig(BaseModel):
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"""
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通用策略配置（支持所有策略类型）
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使用示例:
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from framework_v2.config import load_config
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config = load_config('rotation.yaml')
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"""
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metadata: MetadataConfig = Field(default_factory=MetadataConfig, description="元数据")
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# 资产池
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asset_pools: AssetPool = Field(..., description="资产池配置")
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# 基准
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benchmark: BenchmarkConfig = Field(..., description="基准配置")
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# 回测
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backtest: BacktestConfig = Field(..., description="回测配置")
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# 因子
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factor: FactorConfig = Field(default_factory=FactorConfig, description="因子配置")
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# 轮动（可选）
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rotation: Optional[RotationConfig] = Field(None, description="轮动配置")
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# 调仓
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rebalance: RebalanceConfig = Field(default_factory=RebalanceConfig, description="调仓配置")
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# 溢价控制
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premium_control: PremiumControlConfig = Field(default_factory=PremiumControlConfig, description="溢价控制")
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# 数据
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data: DataConfig = Field(..., description="数据配置")
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