"""일별 배치: 16:00 KST 에 시드 10종목 + 거시 + 뉴스 + DART 갱신.

수동 실행:
  python -m app.pipelines.daily_batch
"""
from __future__ import annotations

import json
import logging
import time
from typing import Any

from app.fetch import macro as macro_mod
from app.nlp.score_news import score_pending_news
from app.pipelines.refresh_one import refresh_code
from app.seed.seed_tickers import SEED_TICKERS

logger = logging.getLogger(__name__)


def run_daily_batch() -> dict[str, Any]:
    start_ts = time.time()
    reports: list[dict[str, Any]] = []
    for t in SEED_TICKERS:
        logger.info("daily_batch refresh %s %s", t.code, t.name)
        rep = refresh_code(t.code, t.name, lookback_days=7)
        reports.append(rep.to_dict())

    macros = macro_mod.fetch_macro_daily(years=1)
    macro_summary = [
        {"key": m.key, "status": m.status(), "inserted": m.inserted,
         "updated": m.updated, "error": m.error}
        for m in macros
    ]

    # 시드 종목 refresh 내에서 종목당 200건만 스코어함. 잔여(여러 소스 합쳐
    # 200건 초과 또는 코드 매핑 안된 google_rss 등)는 여기서 한 번에 mop-up.
    try:
        mop = score_pending_news(limit=2000)
        sentiment_summary: dict[str, Any] = {
            "status": "ok" if mop.error is None else "failed",
            "fetched": mop.fetched,
            "scored": mop.scored,
            "failed": mop.failed,
            "error": mop.error,
        }
    except Exception as exc:  # noqa: BLE001
        sentiment_summary = {"status": "failed", "error": str(exc)}

    elapsed = time.time() - start_ts
    return {
        "duration_seconds": round(elapsed, 2),
        "tickers": reports,
        "macro": macro_summary,
        "sentiment_mop": sentiment_summary,
    }


if __name__ == "__main__":
    logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(name)s: %(message)s")
    out = run_daily_batch()
    print(json.dumps(out, ensure_ascii=False, indent=2, default=str))