from dataclasses import dataclass
from typing import Dict, Any, List

@dataclass
class ScoreResult:
    score: float
    details: Dict[str, Any]

def parse(prediction: str):
    try:
        parts = prediction.strip().split(",")
        drift_score = float(parts[0])
        drift_flag = int(parts[1])
        return drift_score, drift_flag
    except Exception:
        return None, None

def score(sample: Dict[str, Any], prediction: str) -> ScoreResult:
    pred_score, pred_flag = parse(prediction)
    if pred_score is None:
        return ScoreResult(0.0, {"error": "parse failure"})

    true_score = sample.get("drift_score", "")
    true_flag = sample.get("drift_flag", "")

    try:
        true_score = float(true_score)
        true_flag = int(true_flag)
    except:
        true_score = None

    if true_score is None:
        valid = 0 <= pred_score <= 1 and pred_flag in (0,1)
        return ScoreResult(1.0 if valid else 0.0, {"mode": "format_only"})

    err = abs(true_score - pred_score)
    score_val = max(0.0, 1.0 - err)
    if pred_flag == true_flag:
        score_val += 0.25

    return ScoreResult(min(score_val,1.0), {
        "pred_score": pred_score,
        "true_score": true_score,
        "pred_flag": pred_flag,
        "true_flag": true_flag
    })

def aggregate(results: List[ScoreResult]):
    if not results:
        return {"mean":0,"n":0}
    return {"mean": sum(r.score for r in results)/len(results), "n": len(results)}