from config import DEFAULT_WEIGHTS

class SignalEngine:
    def __init__(self):
        self.weights = dict(DEFAULT_WEIGHTS)

    def set_weights(self, weights: dict):
        total = sum(weights.values())
        if abs(total - 1.0) > 0.01:
            raise ValueError(f"Weights must sum to 1.0, got {total}")
        self.weights = weights

    def compute_score(self, technical: float, news: float, social: float, ai: float) -> float:
        score = (
            technical * self.weights["technical"]
            + news * self.weights["news"]
            + social * self.weights["social"]
            + ai * self.weights["ai"]
        )
        return round(score, 1)

    def classify(self, score: float) -> str:
        if score >= 70:
            return "BUY"
        elif score >= 40:
            return "HOLD"
        return "SELL"

    def rank_coins(self, coins: dict[str, dict]) -> list[dict]:
        results = []
        for symbol, scores in coins.items():
            composite = self.compute_score(
                scores["technical"], scores["news"], scores["social"], scores["ai"]
            )
            results.append({
                "symbol": symbol,
                "technical": scores["technical"],
                "news": scores["news"],
                "social": scores["social"],
                "ai": scores["ai"],
                "composite": composite,
                "signal": self.classify(composite),
            })
        results.sort(key=lambda x: x["composite"], reverse=True)
        return results