"""
Trend scorer — calculates the daily zeitgeist score for bills.
Runs nightly via Celery Beat.
"""
import logging
from datetime import date, timedelta

from sqlalchemy import and_

from app.database import get_sync_db
from app.models import Bill, BillBrief, TrendScore
from app.services import news_service, trends_service
from app.workers.celery_app import celery_app

logger = logging.getLogger(__name__)

_PYTRENDS_BATCH = 5  # max keywords pytrends accepts per call


def calculate_composite_score(newsapi_count: int, gnews_count: int, gtrends_score: float) -> float:
    """
    Weighted composite score (0–100):
      NewsAPI article count  → 0–40 pts  (saturates at 20 articles)
      Google News RSS count  → 0–30 pts  (saturates at 50 articles)
      Google Trends score    → 0–30 pts  (0–100 input)
    """
    newsapi_pts = min(newsapi_count / 20, 1.0) * 40
    gnews_pts = min(gnews_count / 50, 1.0) * 30
    gtrends_pts = (gtrends_score / 100) * 30
    return round(newsapi_pts + gnews_pts + gtrends_pts, 2)


@celery_app.task(bind=True, name="app.workers.trend_scorer.calculate_all_trend_scores")
def calculate_all_trend_scores(self):
    """Nightly task: calculate trend scores for bills active in the last 90 days."""
    db = get_sync_db()
    try:
        cutoff = date.today() - timedelta(days=90)
        active_bills = (
            db.query(Bill)
            .filter(Bill.latest_action_date >= cutoff)
            .all()
        )

        today = date.today()

        # Filter to bills not yet scored today
        bills_to_score = []
        for bill in active_bills:
            existing = (
                db.query(TrendScore)
                .filter_by(bill_id=bill.bill_id, score_date=today)
                .first()
            )
            if not existing:
                bills_to_score.append(bill)

        scored = 0

        # Process in batches of _PYTRENDS_BATCH so one pytrends call covers multiple bills
        for batch_start in range(0, len(bills_to_score), _PYTRENDS_BATCH):
            batch = bills_to_score[batch_start: batch_start + _PYTRENDS_BATCH]

            # Collect keyword groups for pytrends batch call
            keyword_groups = []
            bill_queries = []
            for bill in batch:
                latest_brief = (
                    db.query(BillBrief)
                    .filter_by(bill_id=bill.bill_id)
                    .order_by(BillBrief.created_at.desc())
                    .first()
                )
                topic_tags = latest_brief.topic_tags if latest_brief else []
                query = news_service.build_news_query(
                    bill_title=bill.title,
                    short_title=bill.short_title,
                    sponsor_name=None,
                    bill_type=bill.bill_type,
                    bill_number=bill.bill_number,
                )
                keywords = trends_service.keywords_for_bill(
                    title=bill.title or "",
                    short_title=bill.short_title or "",
                    topic_tags=topic_tags,
                )
                keyword_groups.append(keywords)
                bill_queries.append(query)

            # One pytrends call for the whole batch
            gtrends_scores = trends_service.get_trends_scores_batch(keyword_groups)

            for i, bill in enumerate(batch):
                try:
                    query = bill_queries[i]
                    # NewsAPI + Google News counts (gnews served from 2-hour cache)
                    newsapi_articles = news_service.fetch_newsapi_articles(query, days=30)
                    newsapi_count = len(newsapi_articles)
                    gnews_count = news_service.fetch_gnews_count(query, days=30)
                    gtrends_score = gtrends_scores[i]

                    composite = calculate_composite_score(newsapi_count, gnews_count, gtrends_score)

                    db.add(TrendScore(
                        bill_id=bill.bill_id,
                        score_date=today,
                        newsapi_count=newsapi_count,
                        gnews_count=gnews_count,
                        gtrends_score=gtrends_score,
                        composite_score=composite,
                    ))
                    scored += 1
                except Exception as exc:
                    logger.warning(f"Trend scoring skipped for {bill.bill_id}: {exc}")

            db.commit()

        logger.info(f"Scored {scored} bills")
        return {"scored": scored}

    except Exception as exc:
        db.rollback()
        logger.error(f"Trend scoring failed: {exc}")
        raise
    finally:
        db.close()