# -*- coding: utf-8 -*-
"""
基于规则的新闻数据提取（无需 Ollama）
从新闻文本中提取战损、报复情绪等数值，供 db_merge 写入
"""
import re
from datetime import datetime, timezone
from typing import Any, Dict, Optional


def _first_int(text: str, pattern: str) -> Optional[int]:
    m = re.search(pattern, text, re.I)
    if m and m.group(1) and m.group(1).replace(",", "").isdigit():
        return max(0, int(m.group(1).replace(",", "")))
    return None


def extract_from_news(text: str, timestamp: Optional[str] = None) -> Dict[str, Any]:
    """
    规则提取：匹配数字+关键词，输出符合 panel schema 的字段（无需 Ollama）
    """
    ts = timestamp or datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%S.000Z")
    out: Dict[str, Any] = {}
    t = (text or "").lower()

    loss_us, loss_ir = {}, {}
    v = _first_int(t, r"(?:us|american|u\.?s\.?)[\s\w]*(?:say|report)[\s\w]*(\d+)[\s\w]*(?:troop|soldier|killed|dead)")
    if v is not None:
        loss_us["personnel_killed"] = v
    v = _first_int(t, r"(\d+)[\s\w]*(?:us|american)[\s\w]*(?:troop|soldier|killed|dead)")
    if v is not None:
        loss_us["personnel_killed"] = v
    v = _first_int(t, r"(?:iran|iranian)[\s\w]*(?:say|report)[\s\w]*(\d+)[\s\w]*(?:troop|soldier|killed|dead)")
    if v is not None:
        loss_ir["personnel_killed"] = v
    v = _first_int(t, r"(\d+)[\s\w]*(?:iranian|iran)[\s\w]*(?:troop|soldier|killed|dead)")
    if v is not None:
        loss_ir["personnel_killed"] = v

    if loss_us:
        out.setdefault("combat_losses_delta", {})["us"] = loss_us
    if loss_ir:
        out.setdefault("combat_losses_delta", {})["iran"] = loss_ir
    if "retaliat" in t or "revenge" in t or "报复" in t:
        out["retaliation"] = {"value": 75, "time": ts}
    if "wall street" in t or " dow " in t or "s&p" in t or "market slump" in t or "stock fall" in t or "美股" in t:
        out["wall_street"] = {"time": ts, "value": 55}

    return out