"""
SignOz Client - 全能視力中心 (戰略校正版)
==========================================
統帥鐵律: 嚴禁 Prometheus 碎片化，SignOz 為唯一真相來源

Features:
- ClickHouse 直查 (繞過需認證的 SignOz API)
- Gold Metrics 擷取 (P99 Latency, Error Rate, RPS)
- 動態時間範圍 Trace URL 生成
- 趨勢圖表數據提取 (供 AI 分析)

架構:
- SignOz Query Service: 192.168.0.188:3301 (需認證)
- ClickHouse HTTP API: 192.168.0.188:8123 (直查)
"""

import json
import time
from dataclasses import dataclass, field
from datetime import UTC, datetime, timedelta

import structlog

from src.core.config import settings
from src.core.http_client import get_clickhouse_client

logger = structlog.get_logger(__name__)


# =============================================================================
# SignOz Data Models
# =============================================================================

@dataclass
class GoldMetrics:
    """
    Gold Metrics - RED Methodology (Rate, Errors, Duration)

    SRE 黃金指標:
    - RPS (Requests Per Second): 流量
    - Error Rate: 錯誤率 (%)
    - P99 Latency: 99th percentile 延遲 (ms)
    """
    service_name: str
    namespace: str
    time_range_start: datetime
    time_range_end: datetime

    # Rate
    rps: float = 0.0
    rps_trend: str = "stable"  # up, down, stable

    # Errors
    error_rate: float = 0.0  # percentage
    error_count: int = 0
    total_requests: int = 0

    # Duration
    p50_latency_ms: float = 0.0
    p95_latency_ms: float = 0.0
    p99_latency_ms: float = 0.0
    latency_trend: str = "stable"

    # Raw data for AI analysis
    raw_metrics: dict = field(default_factory=dict)

    def to_summary(self) -> str:
        """生成 AI 分析摘要"""
        trend_emoji = {"up": "📈", "down": "📉", "stable": "➡️"}
        error_emoji = "🟢" if self.error_rate < 1 else ("🟡" if self.error_rate < 5 else "🔴")

        return (
            f"📊 Gold Metrics ({self.service_name})\n"
            f"• RPS: {self.rps:.1f} {trend_emoji.get(self.rps_trend, '➡️')}\n"
            f"• Error Rate: {error_emoji} {self.error_rate:.2f}%\n"
            f"• P99 Latency: {self.p99_latency_ms:.0f}ms {trend_emoji.get(self.latency_trend, '➡️')}"
        )

    def to_telegram_block(self) -> str:
        """生成 Telegram 卡片區塊 (HTML)"""
        trend_emoji = {"up": "📈", "down": "📉", "stable": "➡️"}
        error_emoji = "🟢" if self.error_rate < 1 else ("🟡" if self.error_rate < 5 else "🔴")

        return (
            f"📊 <b>SignOz 指標</b>\n"
            f"├ RPS: <code>{self.rps:.1f}</code> {trend_emoji.get(self.rps_trend, '➡️')}\n"
            f"├ Error: {error_emoji} <code>{self.error_rate:.2f}%</code>\n"
            f"└ P99: <code>{self.p99_latency_ms:.0f}ms</code> {trend_emoji.get(self.latency_trend, '➡️')}"
        )


@dataclass
class SignOzTraceLink:
    """動態 SignOz Trace 連結"""
    base_url: str
    service_name: str
    start_time: datetime
    end_time: datetime
    namespace: str = "default"

    def generate_url(self) -> str:
        """
        生成帶時間參數的 Trace URL

        格式: http://host:port/traces?service=xxx&start=timestamp&end=timestamp
        """
        start_ns = int(self.start_time.timestamp() * 1_000_000_000)
        end_ns = int(self.end_time.timestamp() * 1_000_000_000)

        return (
            f"{self.base_url}/traces?"
            f"service={self.service_name}&"
            f"start={start_ns}&"
            f"end={end_ns}"
        )


# =============================================================================
# SignOz Client
# =============================================================================

class SignOzClient:
    """
    SignOz Client - 直查 ClickHouse (永久架構版)

    統帥鐵律: 禁止 subprocess+curl，使用 Lifespan 管理的 httpx.AsyncClient
    使用 ClickHouse HTTP API 繞過需認證的 SignOz Query Service
    """

    def __init__(self):
        self.signoz_url = settings.SIGNOZ_URL  # http://192.168.0.188:3301
        self.clickhouse_url = settings.CLICKHOUSE_URL  # http://192.168.0.188:8123

    async def close(self) -> None:
        """關閉連線 (由 Lifespan 統一管理，此處為相容性保留)"""
        pass  # HTTP Client 由 src.core.http_client 管理

    # =========================================================================
    # ClickHouse Direct Queries (永久架構)
    # =========================================================================

    async def _query_clickhouse(self, query: str) -> list[dict]:
        """
        執行 ClickHouse 查詢 (原生 httpx，非 curl)

        統帥鐵律:
        - 使用 Lifespan 管理的 httpx.AsyncClient
        - trust_env=False 防止 HTTP_PROXY 干擾
        - < 50ms 延遲目標

        ClickHouse HTTP API: POST body = SQL, 加 FORMAT JSONEachRow 到查詢末尾
        """
        # 加入 FORMAT JSONEachRow 到查詢末尾
        formatted_query = query.strip().rstrip(";") + " FORMAT JSONEachRow"

        start_time = time.perf_counter()

        try:
            # 取得 Lifespan 管理的 Client
            client = await get_clickhouse_client()

            logger.debug(
                "clickhouse_query_start",
                base_url=self.clickhouse_url,
                query_preview=formatted_query[:80],
            )

            # 原生 httpx POST 請求
            response = await client.post(
                "/",  # base_url 已設定，只需 path
                content=formatted_query,
            )

            elapsed_ms = (time.perf_counter() - start_time) * 1000

            # 檢查 HTTP 狀態
            if response.status_code != 200:
                logger.warning(
                    "clickhouse_query_http_error",
                    status_code=response.status_code,
                    response_text=response.text[:200],
                    elapsed_ms=round(elapsed_ms, 2),
                )
                return []

            # 解析 JSONEachRow 格式 (每行一個 JSON 物件)
            results = []
            for line in response.text.strip().split("\n"):
                if line:
                    try:
                        results.append(json.loads(line))
                    except json.JSONDecodeError:
                        continue

            logger.info(
                "clickhouse_query_success",
                result_count=len(results),
                elapsed_ms=round(elapsed_ms, 2),
                method="httpx_native",  # 🎯 統帥要求: 原生 httpx，非 curl
            )

            return results

        except Exception as e:
            elapsed_ms = (time.perf_counter() - start_time) * 1000
            logger.warning(
                "clickhouse_query_failed",
                error=str(e),
                error_type=type(e).__name__,
                query=query[:100],
                elapsed_ms=round(elapsed_ms, 2),
            )
            return []

    # =========================================================================
    # Gold Metrics Extraction
    # =========================================================================

    async def get_gold_metrics(
        self,
        service_name: str,
        namespace: str = "default",
        time_window_minutes: int = 10,
    ) -> GoldMetrics:
        """
        從 SignOz/ClickHouse 擷取 Gold Metrics

        查詢過去 N 分鐘的:
        - signoz_calls_total: RPS + Error Count
        - signoz_latency.bucket: P50/P95/P99 延遲

        Args:
            service_name: 服務名稱 (如 api-gateway, harbor-core)
            namespace: K8s namespace
            time_window_minutes: 時間窗口 (分鐘)

        Returns:
            GoldMetrics: 黃金指標數據
        """
        now = datetime.now(UTC)
        start_time = now - timedelta(minutes=time_window_minutes)
        end_time = now

        # 初始化 metrics
        metrics = GoldMetrics(
            service_name=service_name,
            namespace=namespace,
            time_range_start=start_time,
            time_range_end=end_time,
        )

        # =====================================================================
        # Query 1: RPS & Error Rate (從 traces 表直接計算)
        # =====================================================================
        # 使用 signoz_traces.distributed_signoz_index_v3 表
        # statusCode: 0=Unset, 1=Ok, 2=Error
        # 使用 INTERVAL 語法避免 Decimal overflow

        rps_query = f"""
        SELECT
            count() as total_requests,
            countIf(statusCode = 2) as error_count
        FROM signoz_traces.distributed_signoz_index_v3
        WHERE
            timestamp > now() - INTERVAL {time_window_minutes} MINUTE
            AND serviceName LIKE '%{service_name}%'
        """

        rps_results = await self._query_clickhouse(rps_query)

        if rps_results:
            row = rps_results[0]
            total = int(row.get("total_requests", 0))
            errors = int(row.get("error_count", 0))

            metrics.total_requests = total
            metrics.error_count = errors
            metrics.error_rate = (errors / total * 100) if total > 0 else 0.0
            metrics.rps = total / (time_window_minutes * 60)

        # =====================================================================
        # Query 2: Latency Percentiles (從 traces 表的 durationNano)
        # =====================================================================
        latency_query = f"""
        SELECT
            quantile(0.50)(durationNano / 1000000.0) as p50,
            quantile(0.95)(durationNano / 1000000.0) as p95,
            quantile(0.99)(durationNano / 1000000.0) as p99
        FROM signoz_traces.distributed_signoz_index_v3
        WHERE
            timestamp > now() - INTERVAL {time_window_minutes} MINUTE
            AND serviceName LIKE '%{service_name}%'
        """

        latency_results = await self._query_clickhouse(latency_query)

        if latency_results:
            row = latency_results[0]
            metrics.p50_latency_ms = float(row.get("p50", 0) or 0)
            metrics.p95_latency_ms = float(row.get("p95", 0) or 0)
            metrics.p99_latency_ms = float(row.get("p99", 0) or 0)

        # =====================================================================
        # Query 3: Trend Analysis (對比前一時間窗)
        # =====================================================================
        trend_query = f"""
        SELECT count() as prev_requests
        FROM signoz_traces.distributed_signoz_index_v3
        WHERE
            timestamp BETWEEN now() - INTERVAL {time_window_minutes * 2} MINUTE AND now() - INTERVAL {time_window_minutes} MINUTE
            AND serviceName LIKE '%{service_name}%'
        """

        trend_results = await self._query_clickhouse(trend_query)

        if trend_results:
            prev_total = int(trend_results[0].get("prev_requests", 0))
            if prev_total > 0:
                change_pct = (metrics.total_requests - prev_total) / prev_total * 100
                if change_pct > 10:
                    metrics.rps_trend = "up"
                elif change_pct < -10:
                    metrics.rps_trend = "down"
                else:
                    metrics.rps_trend = "stable"

        logger.info(
            "signoz_gold_metrics_fetched",
            service=service_name,
            rps=metrics.rps,
            error_rate=metrics.error_rate,
            p99_latency=metrics.p99_latency_ms,
        )

        return metrics

    # =========================================================================
    # Trace URL Generation
    # =========================================================================

    def generate_trace_url(
        self,
        service_name: str,
        alert_timestamp: datetime | None = None,
        window_minutes: int = 5,
    ) -> str:
        """
        生成動態時間範圍的 SignOz Trace URL

        告警發生時間 ± window_minutes

        Args:
            service_name: 服務名稱
            alert_timestamp: 告警發生時間 (預設為現在)
            window_minutes: 前後時間窗口 (分鐘)

        Returns:
            str: SignOz Trace URL with timestamps
        """
        if alert_timestamp is None:
            alert_timestamp = datetime.now(UTC)

        link = SignOzTraceLink(
            base_url=self.signoz_url,
            service_name=service_name,
            start_time=alert_timestamp - timedelta(minutes=window_minutes),
            end_time=alert_timestamp + timedelta(minutes=window_minutes),
        )

        return link.generate_url()

    # =========================================================================
    # System Metrics (CPU, Memory, Disk)
    # =========================================================================

    async def get_system_metrics(
        self,
        _host: str = "192.168.0.188",  # Reserved for future host filtering
        time_window_minutes: int = 5,
    ) -> dict:
        """
        擷取系統指標 (system.cpu.time, system.disk.io)

        用於 High CPU / Disk Full 告警分析
        """
        now = datetime.now(UTC)
        start_ms = int((now - timedelta(minutes=time_window_minutes)).timestamp() * 1000)
        end_ms = int(now.timestamp() * 1000)

        cpu_query = f"""
        SELECT
            avg(value) as cpu_avg,
            max(value) as cpu_max
        FROM signoz_metrics.distributed_samples_v4
        WHERE
            metric_name = 'system.cpu.time'
            AND unix_milli BETWEEN {start_ms} AND {end_ms}
        """

        disk_query = f"""
        SELECT
            sum(value) as disk_io_bytes
        FROM signoz_metrics.distributed_samples_v4
        WHERE
            metric_name = 'system.disk.io'
            AND unix_milli BETWEEN {start_ms} AND {end_ms}
        """

        cpu_results = await self._query_clickhouse(cpu_query)
        disk_results = await self._query_clickhouse(disk_query)

        return {
            "cpu": cpu_results[0] if cpu_results else {},
            "disk": disk_results[0] if disk_results else {},
            "time_range": {
                "start": start_ms,
                "end": end_ms,
            },
        }


# =============================================================================
# Singleton
# =============================================================================

_signoz_client: SignOzClient | None = None


def get_signoz_client() -> SignOzClient:
    """取得全域 SignOz Client 實例"""
    global _signoz_client
    if _signoz_client is None:
        _signoz_client = SignOzClient()
    return _signoz_client


async def close_signoz_client() -> None:
    """關閉 SignOz Client"""
    global _signoz_client
    if _signoz_client:
        await _signoz_client.close()
        _signoz_client = None