46 lines
1.5 KiB
Python
46 lines
1.5 KiB
Python
from config import DEFAULT_WEIGHTS
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class SignalEngine:
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def __init__(self):
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self.weights = dict(DEFAULT_WEIGHTS)
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def set_weights(self, weights: dict):
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total = sum(weights.values())
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if abs(total - 1.0) > 0.01:
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raise ValueError(f"Weights must sum to 1.0, got {total}")
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self.weights = weights
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def compute_score(self, technical: float, news: float, social: float, ai: float) -> float:
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score = (
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technical * self.weights["technical"]
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+ news * self.weights["news"]
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+ social * self.weights["social"]
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+ ai * self.weights["ai"]
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)
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return round(score, 1)
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def classify(self, score: float) -> str:
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if score >= 70:
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return "BUY"
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elif score >= 40:
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return "HOLD"
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return "SELL"
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def rank_coins(self, coins: dict[str, dict]) -> list[dict]:
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results = []
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for symbol, scores in coins.items():
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composite = self.compute_score(
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scores["technical"], scores["news"], scores["social"], scores["ai"]
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)
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results.append({
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"symbol": symbol,
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"technical": scores["technical"],
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"news": scores["news"],
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"social": scores["social"],
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"ai": scores["ai"],
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"composite": composite,
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"signal": self.classify(composite),
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})
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results.sort(key=lambda x: x["composite"], reverse=True)
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return results
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