atrade/src/main/kotlin/service/AutoTradingManager.kt

package service

import TradingDecision
import kotlinx.coroutines.CoroutineScope
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.launch
import model.CandleData
import java.time.LocalDateTime
import java.time.LocalTime
import java.time.ZoneId
import java.time.format.DateTimeFormatter
import kotlin.collections.List

import kotlin.math.*
// service/AutoTradingManager.kt
typealias TradingDecisionCallback = (TradingDecision?, Boolean)->Unit
object AutoTradingManager {
    private val scope = CoroutineScope(Dispatchers.Default)
    val targetStocks = mutableListOf<Pair<String, String>>()

    fun addStock(stockName : String,stockCode : String, result :TradingDecisionCallback) {
        targetStocks.add(Pair(stockName, stockCode))
        startTradingLoop(stockName,stockCode,result)
    }

    fun startTradingLoop(stockName : String, stockCode : String, result :TradingDecisionCallback) {
        scope.launch {
            println("🚀 10분 주기 자동 분석 및 매매 시작: ${LocalTime.now()}")
//            targetStocks.forEach { stockCode ->
                launch { // 종목별 병렬 분석 (M3 Pro 파워 활용)
                    RagService.processStock(stockName, stockCode,result)
//                    {decision,b ->
////                        when (decision?.decision) {
////                            "BUY" -> if (decision.confidence > 70) executeOrder(stockCode, "매수")
////                            "SELL" -> executeOrder(stockCode, "매도")
////                            else -> println("[$stockCode] 관망 유지: ${decision?.reason}")
////                        }
//                        result(decision,b)
//                    }
                }
//            }
//            targetStocks.re
//            delay(10 * 60 * 1000) // 10분 대기
        }
    }



    private fun executeOrder(code: String, type: String) {
        // 실제 증권사 API 호출 로직 (한국투자증권, 키움 등)
        println("🔥 [주문 집행] $code $type 완료")
    }
}

object TechnicalAnalyzer {
    var monthly: List<CandleData> = emptyList()
    var weekly: List<CandleData> = emptyList()
    var daily: List<CandleData> = emptyList()
    var min30: List<CandleData> = emptyList()

    data class InvestmentScores(
        val ultraShort: Int, // 초단기 (분봉/에너지)
        val shortTerm: Int,  // 단기 (일봉/뉴스)
        val midTerm: Int,    // 중기 (주봉/재무)
        val longTerm: Int     // 장기 (월봉/펀더멘털)
    )

    fun calculateScores(
        financialScore: Int // 재무제표 점수 (성장률 등 기반)
    ): InvestmentScores {

        // 1. 초단기 (분봉 + 에너지 지표 위주)
        val ultra = (TechnicalAnalyzer.calculateMFI(min30, 14) * 0.4 +
                TechnicalAnalyzer.calculateStochastic(min30) * 0.3 +
                (if(TechnicalAnalyzer.calculateChange(min30.takeLast(10)) > 0) 30 else 0)).toInt()

        // 2. 단기 (일봉 추세 + OBV 에너지)
        val short = (TechnicalAnalyzer.calculateRSI(daily) * 0.3 +
                (if(TechnicalAnalyzer.calculateOBV(daily) > 0) 40 else 10) +
                (if(TechnicalAnalyzer.calculateChange(daily.takeLast(3)) > 0) 30 else 0)).toInt()

        // 3. 중기 (주봉 + 재무 점수 혼합)
        val mid = (if(TechnicalAnalyzer.calculateChange(weekly) > 0) 40 else 10) +
                (financialScore * 0.6).toInt()

        // 4. 장기 (월봉 + 섹터/기업 펀더멘털)
        val long = (if(TechnicalAnalyzer.calculateChange(monthly) > 0) 50 else 0) +
                (financialScore * 0.5).toInt()

        return InvestmentScores(
            ultraShort = ultra.coerceIn(0, 100),
            shortTerm = short.coerceIn(0, 100),
            midTerm = mid.coerceIn(0, 100),
            longTerm = long.coerceIn(0, 100)
        )
    }

    fun generateComprehensiveReport(): String {
        // [1] 단기 에너지 지표 계산 (최근 30분봉 기준)
        val obv = calculateOBV(min30)
        val mfi = calculateMFI(min30, 14)
        val adLine = calculateADLine(min30)

        // [2] 시계열별 가격 변동 및 추세 요약
        val m10 = min30.takeLast(10)
        val change10 = calculateChange(m10)
        val change30 = calculateChange(min30)
        val changeDaily = calculateChange(daily.takeLast(2)) // 전일 대비

        // [3] 이평선 및 가격 위치
        val ma5 = m10.takeLast(5).map { it.stck_prpr.toDouble() }.average()
        val currentPrice = min30.last().stck_prpr.toDouble()
        val signal = ScalpingAnalyzer().analyze(min30.toScalpingList(),isDailyBullish())
        // [4] 거래량 강도
        val avgVol30 = min30.map { it.cntg_vol.toLong() }.average()
        val recentVol5 = m10.takeLast(5).map { it.cntg_vol.toLong() }.average()
        val volStrength = if (avgVol30 > 0) recentVol5 / avgVol30 else 1.0
        val atr = calculateATR(min30)
        val stochK = calculateStochastic(min30)
        val priceRange30 = min30.maxOf { it.stck_hgpr.toDouble() } - min30.minOf { it.stck_lwpr.toDouble() }
        return """
- 초/단타 종합 스코어: ${signal.compositeScore} / 100
- 초/단타 매수 신호 발생 여부: ${if (signal.buySignal) "YES" else "NO"}
- 초/단타 성공 확률 예측: ${signal.successProbPct}%
- 초/단타 위험 등급: ${signal.riskLevel} (ATR 변동성 기반)
- 초/단타 RSI: ${"%.1f".format(signal.rsi)} / 거래량 비율: ${"%.1f".format(signal.volRatio)}배
- 초/단타 권장 가격: 손절가(${signal.suggestedSlPrice.toInt()}원), 익절가(${signal.suggestedTpPrice.toInt()}원)
- 월봉/주봉 위치: ${if(calculateChange(monthly) > 0) "장기 상승" else "장기 하락"} / ${if(calculateChange(weekly) > 0) "중기 상승" else "중기 하락"}
- 일봉 대비: ${ "%.2f".format(changeDaily) }% 변동
- 30분 대비: ${ "%.2f".format(change30) }% 변동
- 10분 대비: ${ "%.2f".format(change10) }% 변동
- 이평선 상태: 현재가(${currentPrice.toInt()}) vs MA5(${ma5.toInt()}) -> ${if(currentPrice > ma5) "상단 위치" else "하단 위치"}
- OBV (누적 거래량 에너지): ${ "%.0f".format(obv) } 
- MFI (자금 유입 지수): ${ "%.1f".format(mfi) }  
- A/D (누적 분산 라인): ${ "%.0f".format(adLine) } 
- 거래량 강도: 최근 5분 평균이 30분 평균의 ${ "%.1f".format(volStrength) }배 수준
- ATR (평균 변동폭): ${"%.0f".format(atr)}원 
- 30분 내 최대 진폭: ${"%.0f".format(priceRange30)}원 
- 스토캐스틱(%K): ${"%.1f".format(stochK)} 
- 변동성 강도: 현재 진폭이 ATR 대비 ${"%.1f".format(priceRange30 / atr)}배 수준
- 30분봉 최고가: ${min30.maxOf { it.stck_hgpr.toInt() }}
- 30분봉 최저가: ${min30.minOf { it.stck_lwpr.toInt() }}
- RSI(14): ${ "%.1f".format(calculateRSI(min30)) }
""".trimIndent()
    }

    /**
     * ATR (Average True Range): 최근 변동 폭의 평균. 그래프의 '출렁임' 크기를 측정
     */
    fun calculateATR(candles: List<CandleData>, period: Int = 14): Double {
        val sub = candles.takeLast(period + 1)
        val trList = mutableListOf<Double>()
        for (i in 1 until sub.size) {
            val high = sub[i].stck_hgpr.toDouble()
            val low = sub[i].stck_lwpr.toDouble()
            val prevClose = sub[i - 1].stck_prpr.toDouble()

            val tr = maxOf(high - low, Math.abs(high - prevClose), Math.abs(low - prevClose))
            trList.add(tr)
        }
        return trList.average()
    }

    /**
     * Stochastic (%K): 최근 가격 범위 내에서 현재가의 위치 (0~100)
     * 반복되는 파동(Ups and Downs)에서 현재가 고점인지 저점인지 판단
     */
    fun calculateStochastic(candles: List<CandleData>, period: Int = 14): Double {
        val sub = candles.takeLast(period)
        val highest = sub.maxOf { it.stck_hgpr.toDouble() }
        val lowest = sub.minOf { it.stck_lwpr.toDouble() }
        val current = sub.last().stck_prpr.toDouble()

        return if (highest != lowest) (current - lowest) / (highest - lowest) * 100 else 50.0
    }

    private fun calculateChange(list: List<CandleData>): Double {
        val start = list.first().stck_oprc.toDouble()
        val end = list.last().stck_prpr.toDouble()
        return if (start != 0.0) ((end - start) / start) * 100 else 0.0
    }

    private fun calculateRSI(list: List<CandleData>): Double {
        if (list.size < 2) return 50.0
        var gains = 0.0
        var losses = 0.0
        for (i in 1 until list.size) {
            val diff = list[i].stck_prpr.toDouble() - list[i - 1].stck_prpr.toDouble()
            if (diff > 0) gains += diff else losses -= diff
        }
        return if (gains + losses == 0.0) 50.0 else (gains / (gains + losses)) * 100
    }

    fun isDailyBullish(): Boolean {
        if (daily.size < 20) return true // 데이터 부족 시 보수적으로 true 혹은 예외처리

        val currentPrice = daily.last().stck_prpr.toDouble()

        // 1. MA20 (한 달 생명선) 계산
        val ma20 = daily.takeLast(20).map { it.stck_prpr.toDouble() }.average()

        // 2. MA5 (단기 가속도) 계산
        val ma5 = daily.takeLast(5).map { it.stck_prpr.toDouble() }.average()

        // 3. 방향성 (어제 MA5 vs 오늘 MA5)
        val prevMa5 = daily.dropLast(1).takeLast(5).map { it.stck_prpr.toDouble() }.average()
        val isMa5Rising = ma5 > prevMa5

        // [최종 판별]: 현재가가 생명선 위에 있고, 단기 이평선이 고개를 들었을 때만 'Bull(상승)'로 간주
        return currentPrice > ma20 && isMa5Rising
    }

    fun calculateOBV(candles: List<CandleData>): Double {
        var obv = 0.0
        for (i in 1 until candles.size) {
            val prevClose = candles[i - 1].stck_prpr.toDouble()
            val currClose = candles[i].stck_prpr.toDouble()
            val currVol = candles[i].cntg_vol.toDouble()

            when {
                currClose > prevClose -> obv += currVol
                currClose < prevClose -> obv -= currVol
            }
        }
        return obv
    }

    /**
     * MFI (Money Flow Index) 계산 (기간: 보통 14일)
     */
    fun calculateMFI(candles: List<CandleData>, period: Int = 14): Double {
        val subList = candles.takeLast(period + 1)
        var posFlow = 0.0
        var negFlow = 0.0

        for (i in 1 until subList.size) {
            val prevTypical = (subList[i-1].stck_hgpr.toDouble() + subList[i-1].stck_lwpr.toDouble() + subList[i-1].stck_prpr.toDouble()) / 3
            val currTypical = (subList[i].stck_hgpr.toDouble() + subList[i].stck_lwpr.toDouble() + subList[i].stck_prpr.toDouble()) / 3
            val moneyFlow = currTypical * subList[i].cntg_vol.toDouble()

            if (currTypical > prevTypical) posFlow += moneyFlow
            else if (currTypical < prevTypical) negFlow += moneyFlow
        }

        return if (negFlow == 0.0) 100.0 else 100 - (100 / (1+ (posFlow / negFlow)))
    }

    private fun calculateADLine(candles: List<CandleData>): Double {
        var ad = 0.0
        candles.forEach {
            val high = it.stck_hgpr.toDouble(); val low = it.stck_lwpr.toDouble(); val close = it.stck_prpr.toDouble()
            val mfv = if (high != low) ((close - low) - (high - close)) / (high - low) else 0.0
            ad += mfv * it.cntg_vol.toDouble()
        }
        return ad
    }

    fun clear() {
        monthly  = emptyList()
        weekly = emptyList()
        daily = emptyList()
        min30 = emptyList()
    }

}


class ScalpingAnalyzer {
    companion object {
        private const val SMA_SHORT = 10
        private const val SMA_LONG = 20
        private const val RSI_WINDOW = 14
        private const val VOL_WINDOW = 20
        private const val VOL_SURGE_THRESHOLD = 1.5
        private const val RSI_THRESHOLD = 50.0
        private const val BB_LOWER_POS = 0.2
        private const val BB_UPPER_POS = 0.8
        private const val ATR_WINDOW = 14
        private const val DEFAULT_SL_PCT = -0.5
        private const val DEFAULT_TP_PCT = 1.0
        private const val HIGH_SCORE_THRESHOLD = 80
    }

    fun computeRSI(closes: List<Double>, window: Int = RSI_WINDOW): List<Double> {
        val rsi = mutableListOf<Double>()
        if (closes.size < window + 1) return rsi
        for (i in window until closes.size) {
            val gains = mutableListOf<Double>()
            val losses = mutableListOf<Double>()
            for (j in (i - window + 1) until i + 1) {
                val delta = closes[j] - closes[j - 1]
                if (delta > 0) gains.add(delta) else losses.add(abs(delta))
            }
            val avgGain = gains.average()
            val avgLoss = losses.average()
            val rs = if (avgLoss > 0) avgGain / avgLoss else Double.POSITIVE_INFINITY
            rsi.add(100.0 - (100.0 / (1.0 + rs)))
        }
        return rsi
    }

    fun bollingerBands(closes: List<Double>, window: Int = SMA_LONG): Triple<List<Double>, List<Double>, List<Double>> {
        val sma = mutableListOf<Double>()
        val upper = mutableListOf<Double>()
        val lower = mutableListOf<Double>()
        for (i in window - 1 until closes.size) {
            val slice = closes.subList(i - window + 1, i + 1)
            val mean = slice.average()
            val std = sqrt(slice.map { (it - mean).pow(2.0) }.average()) * 2.0
            sma.add(mean)
            upper.add(mean + std)
            lower.add(mean - std)
        }
        return Triple(upper, sma, lower)
    }

    fun analyze(candles: List<Candle>, isDailyBullish: Boolean): ScalpingSignalModel {
        if (candles.size < SMA_LONG) throw IllegalArgumentException("최소 20봉 필요")

        val closes = candles.map { it.close }
        val volumes = candles.map { it.volume }

        // 지표 계산
        val sma10 = simpleMovingAverage(closes, SMA_SHORT)
        val sma20 = simpleMovingAverage(closes, SMA_LONG)
        val rsiList = computeRSI(closes)
        val volAvg = simpleMovingAverage(volumes, VOL_WINDOW)
        val volRatioList = volumes.mapIndexed { i, v -> if (i >= VOL_WINDOW) v / volAvg[i - VOL_WINDOW] else 0.0 }
        val (bbUpper, bbMiddle, bbLower) = bollingerBands(closes)

        val current = candles.last()
        val idx = candles.size - 1
        val currentClose = current.close
        val sma10Now = if (sma10.size > 0) sma10.last() else 0.0
        val sma20Now = if (sma20.size > 0) sma20.last() else 0.0
        val rsiNow = if (rsiList.isNotEmpty()) rsiList.last() else 0.0
        val volRatioNow = volRatioList.last()
        val bbPos = if (bbUpper.isNotEmpty() && bbLower.isNotEmpty()) {
            (currentClose - bbLower.last()) / (bbUpper.last() - bbLower.last())
        } else 0.5



        val nearHigh = candles.takeLast(6).dropLast(1).maxOf { it.high }
        val isBreakout = currentClose > nearHigh

        // [추가] 2. 캔들 패턴: 망치형/역망치형 등 꼬리 분석 (하단 지지력 확인)
        val bodySize = abs(current.close - current.open)
        val lowerShadow = minOf(current.close, current.open) - current.low
        val isBottomSupport = lowerShadow > bodySize * 1.5 // 밑꼬리가 몸통보다 긴 경우

        // 신호 조건 고도화
        // 일봉 추세(dailyTrend)가 살아있고, 전고점을 돌파(isBreakout)할 때 더 높은 점수

//        val maBull = currentClose > sma10Now && sma10Now > sma20Now
        val rsiBull = rsiNow > RSI_THRESHOLD
        val volSurge = volRatioNow > VOL_SURGE_THRESHOLD
        val bbGood = bbPos > BB_LOWER_POS && bbPos < BB_UPPER_POS
        val maBull = currentClose > sma10Now && sma10Now > sma20Now
        val buySignal = maBull && rsiBull && volSurge && bbGood && isBreakout
//        val buySignal = maBull && rsiBull && volSurge && bbGood


        val score = (if (maBull) 25 else 0) +
                (if (rsiBull) 15 else 0) +
                (if (isBreakout) 20 else 0) + // 돌파 에너지 가중치
                (minOf((volRatioNow - 1.0) * 20, 20.0)).toInt() +
                (if (bbGood) 10 else 0) +
                (if (isDailyBullish) 10 else 0) // 단타/장기 정렬 점수

        // 위험도 (ATR proxy)
        val returns = closes.mapIndexed { i, c -> if (i > 0) (c - closes[i-1])/closes[i-1] * 100 else 0.0 }
        val atrProxy = if (returns.size >= ATR_WINDOW) {
            returns.subList(returns.size - ATR_WINDOW, returns.size).average()
        } else 1.0
        val riskLevel = when {
            abs(atrProxy) < 1 -> "Low"
            abs(atrProxy) < 2 -> "Medium"
            else -> "High"
        }

        // 성공 확률 & SL/TP
        val successProb = if (buySignal) 75.0 else 35.0 + (score / 100.0 * 20)
        val slPrice = currentClose * (1 + DEFAULT_SL_PCT / 100)
        val tpPrice = currentClose * (1 + DEFAULT_TP_PCT / 100)
        val rrRatio = abs(DEFAULT_TP_PCT / DEFAULT_SL_PCT)



        return ScalpingSignalModel(
            currentPrice = currentClose,
            buySignal = buySignal,
            compositeScore = minOf(score.toInt(), 100),
            successProbPct = successProb,
            riskLevel = riskLevel,
            rsi = rsiNow,
            volRatio = volRatioNow,
            suggestedSlPrice = slPrice,
            suggestedTpPrice = tpPrice,
            riskRewardRatio = rrRatio
        )
    }

    private fun simpleMovingAverage(values: List<Double>, window: Int): List<Double> {
        val sma = mutableListOf<Double>()
        for (i in window - 1 until values.size) {
            val slice = values.subList(i - window + 1, i + 1)
            sma.add(slice.average())
        }
        return sma
    }
}

data class Candle(
    val timestamp: Long,
    val open: Double,
    val high: Double,
    val low: Double,
    val close: Double,
    val volume: Double
)

data class ScalpingSignalModel(
    val currentPrice: Double,
    val buySignal: Boolean,
    val compositeScore: Int,  // 0-100: 종합 매수 추천도 (80+ 강매수)
    val successProbPct: Double,  // 성공 확률 추정 %
    val riskLevel: String,  // "Low", "Medium", "High"
    val rsi: Double,
    val volRatio: Double,
    val suggestedSlPrice: Double,  // 손절 가격
    val suggestedTpPrice: Double,  // 익절 가격
    val riskRewardRatio: Double
)

fun CandleData.toScalpingCandle(): Candle {
    // 1. 날짜(YYYYMMDD)와 시간(HHMMSS) 문자열 결합
    val dateTimeStr = "${this.stck_bsop_date}${this.stck_cntg_hour}"
    val formatter = DateTimeFormatter.ofPattern("yyyyMMddHHmmss")

    // 2. 타임스탬프(Epoch Milliseconds) 계산
    val timestamp = try {
        val ldt = LocalDateTime.parse(dateTimeStr, formatter)
        ldt.atZone(ZoneId.systemDefault()).toInstant().toEpochMilli()
    } catch (e: Exception) {
        // 시간 파싱 실패 시 현재 시스템 시간 사용
        System.currentTimeMillis()
    }

    // 3. String 필드들을 Double로 변환하여 Candle 객체 생성
    return Candle(
        timestamp = timestamp,
        open = this.stck_oprc.toDoubleOrNull() ?: 0.0,
        high = this.stck_hgpr.toDoubleOrNull() ?: 0.0,
        low = this.stck_lwpr.toDoubleOrNull() ?: 0.0,
        close = this.stck_prpr.toDoubleOrNull() ?: 0.0, // stck_prpr가 종가 역할
        volume = this.cntg_vol.toDoubleOrNull() ?: 0.0
    )
}

/**
 * 리스트 전체를 변환하는 유틸리티
 */
fun List<CandleData>.toScalpingList(): List<Candle> {
    return this.map { it.toScalpingCandle() }
}