# -*- coding: utf-8 -*-
"""
统一写库流水线：抓取 → 清洗 → 去重 → 映射到前端库字段 → 更新表 → 通知
与 server/README.md 第五节「爬虫侧写库链路」一致，供 main.py 与 realtime_conflict_service 共用。
"""
import os
from datetime import datetime, timezone
from typing import Callable, Optional, Tuple

from config import DB_PATH, API_BASE


def _notify_api(api_base: str) -> bool:
    """调用 Node API 触发立即广播"""
    try:
        import urllib.request
        token = os.environ.get("API_CRAWLER_TOKEN", "").strip()
        req = urllib.request.Request(
            f"{api_base.rstrip('/')}/api/crawler/notify",
            method="POST",
            headers={
                "Content-Type": "application/json",
                **({"X-Crawler-Token": token} if token else {}),
            },
        )
        with urllib.request.urlopen(req, timeout=5) as resp:
            return resp.status == 200
    except Exception as e:
        print(f"  [warn] notify API failed: {e}")
        return False


def _extract_and_merge(items: list, db_path: str) -> bool:
    """AI 从新闻全文或标题+摘要中提取精确结构化数据，合并到 combat_losses / key_location 等表。"""
    if not items or not os.path.exists(db_path):
        return False
    try:
        from db_merge import merge
        use_dashscope = bool(os.environ.get("DASHSCOPE_API_KEY", "").strip())
        if use_dashscope:
            from extractor_dashscope import extract_from_news
            limit = 10
        elif os.environ.get("CLEANER_AI_DISABLED", "0") == "1":
            from extractor_rules import extract_from_news
            limit = 25
        else:
            from extractor_ai import extract_from_news
            limit = 10
        merged_any = False
        for it in items[:limit]:
            # 优先用正文（article_fetcher 抓取），否则用标题+摘要，供 AI 提取精确数字
            text = it.get("full_text") or ((it.get("title", "") or "") + " " + (it.get("summary", "") or ""))
            if len(text.strip()) < 20:
                continue
            pub = it.get("published")
            ts = None
            if pub:
                try:
                    if isinstance(pub, str):
                        pub_dt = datetime.fromisoformat(pub.replace("Z", "+00:00"))
                    else:
                        pub_dt = pub
                    if pub_dt.tzinfo:
                        pub_dt = pub_dt.astimezone(timezone.utc)
                    ts = pub_dt.strftime("%Y-%m-%dT%H:%M:%S.000Z")
                except Exception:
                    pass
            extracted = extract_from_news(text, timestamp=ts)
            if extracted and merge(extracted, db_path=db_path):
                merged_any = True
        return merged_any
    except Exception as e:
        print(f"  [warn] AI 面板数据提取/合并: {e}")
        return False


def run_full_pipeline(
    db_path: Optional[str] = None,
    api_base: Optional[str] = None,
    *,
    translate: bool = True,
    notify: bool = True,
    on_notify: Optional[Callable[[], None]] = None,
) -> Tuple[int, int, int]:
    """
    执行完整写库链路：
    1. 爬虫抓取实时数据
    2. AI 清洗（标题/摘要/分类）→ 有效数据
    3. 去重（news_content content_hash）→ 仅新项进入后续
    4. 有效数据映射到前端库字段（situation_update、news_content、combat_losses 等）
    5. 更新数据库表；若有更新则通知后端

    translate: 是否对标题/摘要做翻译（英→中）
    notify: 是否在流水线末尾调用 POST /api/crawler/notify
    on_notify: 若提供，在通知前调用（供 gdelt 服务做 GDELT 回填等）

    返回: (本轮抓取条数, 去重后新增资讯数, 写入 situation_update 条数)
    """
    path = db_path or DB_PATH
    base = api_base or API_BASE

    from scrapers.rss_scraper import fetch_all
    from db_writer import write_updates
    from news_storage import save_and_dedup
    from cleaner_ai import clean_news_for_panel, ensure_category, ensure_severity

    # 1. 抓取
    items = fetch_all()
    if not items:
        return 0, 0, 0

    # 可选：仅保留指定起始时间之后的条目（如 CRAWL_START_DATE=2026-02-28T00:00:00）
    start_date_env = os.environ.get("CRAWL_START_DATE", "").strip()
    if start_date_env:
        try:
            raw = start_date_env.replace("Z", "+00:00").strip()
            start_dt = datetime.fromisoformat(raw)
            if start_dt.tzinfo is None:
                start_dt = start_dt.replace(tzinfo=timezone.utc)
            else:
                start_dt = start_dt.astimezone(timezone.utc)
            before = len(items)
            items = [it for it in items if (it.get("published") or datetime.min.replace(tzinfo=timezone.utc)) >= start_dt]
            if before > len(items):
                print(f"  [pipeline] 按 CRAWL_START_DATE={start_date_env} 过滤后保留 {len(items)} 条（原 {before} 条）")
        except Exception as e:
            print(f"  [warn] CRAWL_START_DATE 解析失败，忽略: {e}")

    if not items:
        return 0, 0, 0
    n_total = len(items)
    print(f"  [pipeline] 抓取 {n_total} 条")
    for i, it in enumerate(items[:5]):
        title = (it.get("title") or it.get("summary") or "").strip()[:60]
        print(f"    [{i + 1}] {title}" + ("…" if len((it.get("title") or it.get("summary") or "")[:60]) >= 60 else ""))
    if n_total > 5:
        print(f"    ... 共 {n_total} 条")

    # 2. 清洗（标题/摘要/分类，符合面板 schema）
    if translate:
        from translate_utils import translate_to_chinese
        for it in items:
            raw_title = translate_to_chinese(it.get("title", "") or "")
            raw_summary = translate_to_chinese(it.get("summary", "") or it.get("title", ""))
            it["title"] = clean_news_for_panel(raw_title, max_len=80)
            it["summary"] = clean_news_for_panel(raw_summary or raw_title, max_len=120)
    else:
        for it in items:
            it["title"] = clean_news_for_panel(it.get("title", "") or "", max_len=80)
            it["summary"] = clean_news_for_panel(it.get("summary", "") or it.get("title", ""), max_len=120)
    for it in items:
        it["category"] = ensure_category(it.get("category", "other"))
        it["severity"] = ensure_severity(it.get("severity", "medium"))
        it["source"] = it.get("source") or "rss"

    # 3. 去重：落库 news_content，仅新项返回
    new_items, n_news = save_and_dedup(items, db_path=path)
    if new_items:
        print(f"  [pipeline] 去重后新增 {n_news} 条，写入事件脉络 {len(new_items)} 条")
        for i, it in enumerate(new_items[:3]):
            title = (it.get("title") or it.get("summary") or "").strip()[:55]
            print(f"    新增 [{i + 1}] {title}" + ("…" if len((it.get("title") or it.get("summary") or "").strip()) > 55 else ""))

    # 3.5 数据增强：为参与 AI 提取的条目抓取正文，便于从全文提取精确数据（伤亡、基地等）
    if new_items:
        try:
            from article_fetcher import enrich_item_with_body
            # 仅对前若干条抓取正文，避免单轮请求过多
            enrich_limit = int(os.environ.get("ARTICLE_FETCH_LIMIT", "10"))
            for it in new_items[:enrich_limit]:
                enrich_item_with_body(it)
        except Exception as e:
            print(f"  [warn] 正文抓取: {e}")

    # 4. 映射到前端库字段并更新表
    n_panel = write_updates(new_items) if new_items else 0
    if new_items:
        _extract_and_merge(new_items, path)

    # 5. 通知（有新增时才通知；可选：先执行外部逻辑如 GDELT 回填，再通知）
    if on_notify:
        on_notify()
    if notify and (n_panel > 0 or n_news > 0):
        _notify_api(base)

    return len(items), n_news, n_panel