"""News-driven strategy — trade on aggregated news sentiment."""

from datetime import datetime, timezone

from shared.schemas.trading import MarketSnapshot, SentimentContext, SignalDirection, TradeSignal
from shared.strategies.base import BaseStrategy


class NewsDrivenStrategy(BaseStrategy):
    """Generate signals from aggregated news sentiment for a ticker.

    **Buy signal** (LONG):
        ``avg_score > 0.15`` AND ``avg_confidence > 0.3`` AND
        ``article_count >= 1``.

    **Sell signal** (SHORT):
        ``avg_score < -0.15`` AND ``avg_confidence > 0.3`` AND
        ``article_count >= 1``.

    Signal strength = ``abs(avg_score) * avg_confidence``, clamped to
    [0, 1].
    """

    name: str = "news_driven"

    async def evaluate(
        self,
        ticker: str,
        market: MarketSnapshot,
        sentiment: SentimentContext | None = None,
    ) -> TradeSignal | None:
        if sentiment is None:
            return None

        # Require at least 1 article.
        if sentiment.article_count < 1:
            return None

        # Require minimum confidence.
        if sentiment.avg_confidence <= 0.3:
            return None

        if sentiment.avg_score > 0.15:
            direction = SignalDirection.LONG
        elif sentiment.avg_score < -0.15:
            direction = SignalDirection.SHORT
        else:
            # Sentiment is neutral — no opinion.
            return None

        raw_strength = abs(sentiment.avg_score) * sentiment.avg_confidence
        strength = max(0.0, min(1.0, raw_strength))

        return TradeSignal(
            ticker=ticker,
            direction=direction,
            strength=strength,
            strategy_sources=[self.name],
            timestamp=datetime.now(tz=timezone.utc),
        )