"""训练模块 - ProStock 量化投资框架

提供模型训练、数据处理和预测的完整流程。
"""

# 基础抽象类
from src.training.components.base import BaseModel, BaseProcessor

# 注册中心
from src.training.registry import (
    ModelRegistry,
    ProcessorRegistry,
    register_model,
    register_processor,
)

# 数据划分器
from src.training.components.splitters import DateSplitter

# 股票池选择器配置（已迁移到 StockPoolManager，保留文件占位）
# from src.training.components.selectors import ...

# 数据处理器
from src.training.components.processors import (
    CrossSectionalStandardScaler,
    NullFiller,
    StandardScaler,
    Winsorizer,
)

# 模型
from src.training.components.models import LightGBMModel

# 数据过滤器
from src.training.components.filters import BaseFilter, STFilter

# 训练核心
from src.training.core import StockPoolManager, Trainer

# 工具函数
from src.training.utils import check_data_quality

# 配置
from src.training.config import TrainingConfig

# 新增：模块化 Trainer 组件
from src.training.factor_manager import FactorManager
from src.training.pipeline import DataPipeline
from src.training.result_analyzer import ResultAnalyzer
from src.training.tasks import BaseTask, RegressionTask, RankTask

__all__ = [
    # 基础抽象类
    "BaseModel",
    "BaseProcessor",
    # 注册中心
    "ModelRegistry",
    "ProcessorRegistry",
    "register_model",
    "register_processor",
    # 数据划分器
    "DateSplitter",
    # 股票池选择器配置（已迁移，保留注释占位）
    # "StockFilterConfig",  # 已删除，使用 StockPoolManager + filter_func 替代
    # "MarketCapSelectorConfig",  # 已删除，使用 StockPoolManager + required_factors 替代
    # 数据处理器
    "NullFiller",
    "StandardScaler",
    "CrossSectionalStandardScaler",
    "Winsorizer",
    # 数据过滤器
    "BaseFilter",
    "STFilter",
    # 模型
    "LightGBMModel",
    # 训练核心
    "StockPoolManager",
    "Trainer",
    # 工具函数
    "check_data_quality",
    # 配置
    "TrainingConfig",
    # 新增：模块化 Trainer 组件
    "FactorManager",
    "DataPipeline",
    "ResultAnalyzer",
    "BaseTask",
    "RegressionTask",
    "RankTask",
]