"""Data models for storage layer."""

from dataclasses import dataclass, field
from datetime import datetime
from typing import Optional, Dict, Any
import json


@dataclass
class MetricRecord:
    """A single metric record for storage."""
    metric_name: str
    value: float
    timestamp: datetime = field(default_factory=datetime.now)
    labels: Dict[str, str] = field(default_factory=dict)
    id: Optional[int] = None

    def to_dict(self) -> Dict[str, Any]:
        return {
            "id": self.id,
            "metric_name": self.metric_name,
            "value": self.value,
            "timestamp": self.timestamp.isoformat(),
            "labels": self.labels,
        }

    @classmethod
    def from_row(cls, row: tuple) -> "MetricRecord":
        return cls(
            id=row[0],
            timestamp=datetime.fromisoformat(row[1]),
            metric_name=row[2],
            value=row[3],
            labels=json.loads(row[4]) if row[4] else {},
        )


@dataclass
class AlertRecord:
    """An alert record for storage."""
    rule_name: str
    severity: str
    metric_name: str
    value: float
    threshold: float
    message: str
    timestamp: datetime = field(default_factory=datetime.now)
    resolved_at: Optional[datetime] = None
    id: Optional[int] = None

    def to_dict(self) -> Dict[str, Any]:
        return {
            "id": self.id,
            "rule_name": self.rule_name,
            "severity": self.severity,
            "metric_name": self.metric_name,
            "value": self.value,
            "threshold": self.threshold,
            "message": self.message,
            "timestamp": self.timestamp.isoformat(),
            "resolved_at": self.resolved_at.isoformat() if self.resolved_at else None,
        }

    @classmethod
    def from_row(cls, row: tuple) -> "AlertRecord":
        return cls(
            id=row[0],
            timestamp=datetime.fromisoformat(row[1]),
            rule_name=row[2],
            severity=row[3],
            metric_name=row[4],
            value=row[5],
            threshold=row[6],
            message=row[7] if len(row) > 7 else "",
            resolved_at=datetime.fromisoformat(row[8]) if len(row) > 8 and row[8] else None,
        )


@dataclass
class RequestTrace:
    """A request trace for latency analysis."""
    request_id: str
    prompt_tokens: int
    output_tokens: int
    queue_time_ms: float
    prefill_time_ms: float
    decode_time_ms: float
    total_time_ms: float
    tokens_per_second: float
    gpu_memory_at_start: float = 0.0
    gpu_memory_at_end: float = 0.0
    is_slow: bool = False
    timestamp: datetime = field(default_factory=datetime.now)
    id: Optional[int] = None

    def to_dict(self) -> Dict[str, Any]:
        return {
            "id": self.id,
            "request_id": self.request_id,
            "timestamp": self.timestamp.isoformat(),
            "prompt_tokens": self.prompt_tokens,
            "output_tokens": self.output_tokens,
            "queue_time_ms": round(self.queue_time_ms, 2),
            "prefill_time_ms": round(self.prefill_time_ms, 2),
            "decode_time_ms": round(self.decode_time_ms, 2),
            "total_time_ms": round(self.total_time_ms, 2),
            "tokens_per_second": round(self.tokens_per_second, 2),
            "is_slow": self.is_slow,
        }

    @classmethod
    def from_row(cls, row: tuple) -> "RequestTrace":
        return cls(
            id=row[0],
            request_id=row[1],
            timestamp=datetime.fromisoformat(row[2]),
            prompt_tokens=row[3],
            output_tokens=row[4],
            queue_time_ms=row[5],
            prefill_time_ms=row[6],
            decode_time_ms=row[7],
            total_time_ms=row[8],
            tokens_per_second=row[9] if len(row) > 9 else 0,
            is_slow=bool(row[10]) if len(row) > 10 else False,
        )


@dataclass
class LoadTestResult:
    """Results from a load test run."""
    test_id: str
    target_endpoint: str
    concurrent_users: int
    requests_per_second: float
    duration_seconds: int
    total_requests: int
    successful_requests: int
    failed_requests: int
    avg_latency_ms: float
    p50_latency_ms: float
    p95_latency_ms: float
    p99_latency_ms: float
    throughput_rps: float
    saturation_point: Optional[float] = None
    timestamp: datetime = field(default_factory=datetime.now)
    id: Optional[int] = None

    def to_dict(self) -> Dict[str, Any]:
        return {
            "test_id": self.test_id,
            "target_endpoint": self.target_endpoint,
            "concurrent_users": self.concurrent_users,
            "requests_per_second": self.requests_per_second,
            "duration_seconds": self.duration_seconds,
            "total_requests": self.total_requests,
            "successful_requests": self.successful_requests,
            "failed_requests": self.failed_requests,
            "avg_latency_ms": round(self.avg_latency_ms, 2),
            "p50_latency_ms": round(self.p50_latency_ms, 2),
            "p95_latency_ms": round(self.p95_latency_ms, 2),
            "p99_latency_ms": round(self.p99_latency_ms, 2),
            "throughput_rps": round(self.throughput_rps, 2),
            "saturation_point": self.saturation_point,
            "timestamp": self.timestamp.isoformat(),
        }