"""Replaceable baseline risk scoring engine."""

from dataclasses import dataclass
from enum import StrEnum


class RiskLevel(StrEnum):
    LOW = "low"
    MODERATELY_LOW = "moderately_low"
    MEDIUM = "medium"
    HIGH = "high"
    VERY_HIGH = "very_high"


@dataclass(frozen=True, slots=True)
class IndicatorValue:
    name: str
    value: float
    weight: float


@dataclass(frozen=True, slots=True)
class FactorContribution:
    name: str
    value: float
    weight: float
    contribution: float


@dataclass(frozen=True, slots=True)
class RiskScore:
    score: float
    level: RiskLevel
    factors: tuple[FactorContribution, ...]


class BaselineRiskEngine:
    """Weighted safety-score baseline following the PRD scoring direction.

    Input indicator values represent risk intensity (0 = no observed risk,
    100 = maximum risk). The public score is the inverse safety score, so a
    higher result always means a safer assessment.
    """

    model_version = "baseline-safety-v2"

    def predict(self, indicators: list[IndicatorValue]) -> RiskScore:
        total_weight = sum(item.weight for item in indicators)
        factors = tuple(
            FactorContribution(
                name=item.name,
                value=item.value,
                weight=item.weight,
                contribution=round((100 - item.value) * item.weight / total_weight, 2),
            )
            for item in indicators
        )
        score = round(sum(item.contribution for item in factors), 2)
        return RiskScore(score=score, level=self._classify(score), factors=factors)

    @staticmethod
    def _classify(score: float) -> RiskLevel:
        if score >= 80:
            return RiskLevel.LOW
        if score >= 60:
            return RiskLevel.MODERATELY_LOW
        if score >= 40:
            return RiskLevel.MEDIUM
        if score >= 20:
            return RiskLevel.HIGH
        return RiskLevel.VERY_HIGH