"""选股用例入口（ARCHITECTURE_v2 §14 Selection Engine · 业务层）。

- 输入：SelectionQuery（universe + method + factors/conditions + top_n/pct + as_of）
- 装配：股票池（universe 过滤）→ 行情长表（含预热窗口）→ Selection Engine
- 输出：SelectionResult（可解释：factor_values / selection_reason）
- 未来函数红线：全部数据只取到 <= as_of（v2 §9）；财务条件（后续）只取已公告值

MVP 为同步执行（单日全市场因子计算量轻）；如需异步可复用 Job 链路（M6.3 决策）。
"""

from __future__ import annotations

from datetime import date, timedelta

import pandas as pd

from app.domain.entities.selection import SelectionQuery, SelectionResult
from app.domain.repositories.market import DailyBarRepository, StockRepository
from app.quant.selection import factor_columns, run_score_selection
from app.quant.service import filter_stocks, load_daily_df


class SelectionService:
    """选股用例入口：select(query) → SelectionResult（当前或历史 as_of）。"""

    def __init__(
        self,
        stock_repo: StockRepository,
        daily_repo: DailyBarRepository,
    ) -> None:
        self._stock_repo = stock_repo
        self._daily_repo = daily_repo

    def select(self, query: SelectionQuery) -> SelectionResult:
        as_of = query.as_of or date.today()
        stocks = filter_stocks(self._stock_repo.list(), query.universe, as_of=as_of)
        if not stocks:
            return run_score_selection(pd.DataFrame(), query, as_of)
        symbols = [s.symbol for s in stocks]
        columns = sorted(factor_columns(query)) if query.method == "score" else ["close"]
        daily = load_daily_df(
            self._daily_repo,
            symbols,
            as_of - timedelta(days=query.warmup_days),
            as_of,
            columns,
        )
        if daily.empty:
            return run_score_selection(daily, query, as_of)
        return run_score_selection(daily, query, as_of)