"""分红送股事件源（spec §295 C-S3）。

akshare `stock_history_dividend_detail(symbol, indicator="分红")` 拉取 A 股
分红送股明细。akshare 字段均为「每 10 股」口径，本模块统一转 per-share：

- 送股 + 转增（每 10 股 X 股）→ split_factor = 1 + (送股+转增)/10
- 派息（每 10 股 X 元）       → cash_per_share = 派息/10
- 除权除息日：持仓调整日（当日开盘前持仓享权）

akshare 不可用/拉取失败 → 返回 []（事件源抽象，不抛异常避免阻断回测）。
"""
import logging
from dataclasses import dataclass

import pandas as pd

logger = logging.getLogger(__name__)


@dataclass(frozen=True)
class DividendEvent:
    """单次分红送股事件。"""

    ex_date: str            # 除权除息日 YYYY-MM-DD（持仓调整日）
    symbol: str
    split_factor: float     # 1.0 = 无送转；1.5 = 10送5
    cash_per_share: float   # 每股现金分红（元）；0.0 = 无现金分红


def fetch_dividends(symbol: str, start: str, end: str) -> list[DividendEvent]:
    """拉取 symbol 在 [start, end] 除权除息日内的已实施分红送股事件。

    akshare 未装/出错 → 返回 []（不抛异常）。
    """
    try:
        import akshare as ak
    except ImportError:
        logger.warning("akshare 未安装，%s 分红事件返回空", symbol)
        return []
    try:
        df = ak.stock_history_dividend_detail(symbol=symbol, indicator="分红")
    except Exception as e:                     # noqa: BLE001 —— 数据源不可控，兜底
        logger.warning("拉取 %s 分红失败，返回空: %s", symbol, e)
        return []
    return _parse_dividend_df(df, symbol, start, end)


def _parse_dividend_df(df: pd.DataFrame, symbol: str,
                       start: str, end: str) -> list[DividendEvent]:
    """解析 akshare 分红明细 DataFrame → DividendEvent 列表。"""
    if df is None or len(df) == 0:
        return []
    events: list[DividendEvent] = []
    for _, row in df.iterrows():
        if str(row.get("进度", "")) != "实施":
            continue
        ex_date = _norm_date(row.get("除权除息日"))
        if ex_date is None or not (start <= ex_date <= end):
            continue
        send = _to_float(row.get("送股", 0))       # 每 10 股送股
        transfer = _to_float(row.get("转增", 0))   # 每 10 股转增
        cash = _to_float(row.get("派息", 0))       # 每 10 股派息（元）
        split_factor = 1.0 + (send + transfer) / 10.0
        cash_per_share = cash / 10.0
        if split_factor == 1.0 and cash_per_share == 0.0:
            continue
        events.append(DividendEvent(ex_date, symbol, split_factor, cash_per_share))
    return events


def build_dividend_calendar(
    symbols: list[str], start: str, end: str
) -> dict[str, dict[str, DividendEvent]]:
    """批量构建 {ex_date: {symbol: DividendEvent}} 日历（回测 preload 用）。"""
    calendar: dict[str, dict[str, DividendEvent]] = {}
    for sym in symbols:
        for ev in fetch_dividends(sym, start, end):
            calendar.setdefault(ev.ex_date, {})[sym] = ev
    return calendar


def _norm_date(val) -> str | None:
    """除权除息日归一化为 YYYY-MM-DD 字符串；NaT/缺失 → None。"""
    if val is None or (isinstance(val, float) and pd.isna(val)):
        return None
    try:
        ts = pd.Timestamp(val)
    except (ValueError, TypeError):
        return None
    if pd.isna(ts):
        return None
    return ts.strftime("%Y-%m-%d")


def _to_float(val, default: float = 0.0) -> float:
    """安全转 float；NaN/缺失 → default。"""
    try:
        f = float(val)
    except (ValueError, TypeError):
        return default
    return default if pd.isna(f) else f