from __future__ import annotations

from dataclasses import dataclass

from .models import ViabilityThreshold


@dataclass(frozen=True)
class ViabilityResult:
    metric: str
    value: float | None
    threshold: ViabilityThreshold
    passed: bool


@dataclass(frozen=True)
class ViabilityReport:
    passed: bool
    results: dict[str, ViabilityResult]


def evaluate_viability(
    metrics: dict[str, float],
    thresholds: dict[str, ViabilityThreshold],
) -> ViabilityReport:
    results: dict[str, ViabilityResult] = {}
    for name, threshold in thresholds.items():
        value = metrics.get(name)
        passed = value is not None
        if value is not None and threshold.min is not None:
            passed = passed and value >= threshold.min
        if value is not None and threshold.max is not None:
            passed = passed and value <= threshold.max
        results[name] = ViabilityResult(
            metric=name,
            value=value,
            threshold=threshold,
            passed=passed,
        )
    return ViabilityReport(
        passed=all(result.passed for result in results.values()),
        results=results,
    )