feat: migrate to CoinAnk API and improve chart UI

- Chart improvements: professional styling, popular symbols quick selection, simplified B/S legend
- Data source migration: use CoinAnk API exclusively for all kline data
- Code cleanup: remove Binance WebSocket cache and related code (websocket_client.go, combined_streams.go, monitor.go)
- Log optimization: reduce hook spam, suppress 404 errors, increase P&L diff threshold
- Lighter integration: add order sync functionality, fix market order precision
- Remove ticker merge logic for simplicity

web/src/utils/indicators.ts

@@ -0,0 +1,216 @@
+// 技术指标计算工具
+
+export interface Kline {
+  time: number
+  open: number
+  high: number
+  low: number
+  close: number
+  volume?: number
+}
+
+// 简单移动平均线 (SMA)
+export function calculateSMA(data: Kline[], period: number): Array<{ time: number; value: number }> {
+  const result: Array<{ time: number; value: number }> = []
+
+  for (let i = period - 1; i < data.length; i++) {
+    let sum = 0
+    for (let j = 0; j < period; j++) {
+      sum += data[i - j].close
+    }
+    result.push({
+      time: data[i].time,
+      value: sum / period,
+    })
+  }
+
+  return result
+}
+
+// 指数移动平均线 (EMA)
+export function calculateEMA(data: Kline[], period: number): Array<{ time: number; value: number }> {
+  const result: Array<{ time: number; value: number }> = []
+  const multiplier = 2 / (period + 1)
+
+  // 第一个EMA值使用SMA
+  let ema = 0
+  for (let i = 0; i < period; i++) {
+    ema += data[i].close
+  }
+  ema = ema / period
+  result.push({ time: data[period - 1].time, value: ema })
+
+  // 后续EMA值
+  for (let i = period; i < data.length; i++) {
+    ema = (data[i].close - ema) * multiplier + ema
+    result.push({ time: data[i].time, value: ema })
+  }
+
+  return result
+}
+
+// MACD 指标
+export interface MACDData {
+  time: number
+  macd: number
+  signal: number
+  histogram: number
+}
+
+export function calculateMACD(
+  data: Kline[],
+  fastPeriod = 12,
+  slowPeriod = 26,
+  signalPeriod = 9
+): MACDData[] {
+  const fastEMA = calculateEMA(data, fastPeriod)
+  const slowEMA = calculateEMA(data, slowPeriod)
+
+  // 计算MACD线
+  const macdLine: Array<{ time: number; value: number }> = []
+  for (let i = 0; i < slowEMA.length; i++) {
+    const fastValue = fastEMA.find(e => e.time === slowEMA[i].time)
+    if (fastValue) {
+      macdLine.push({
+        time: slowEMA[i].time,
+        value: fastValue.value - slowEMA[i].value,
+      })
+    }
+  }
+
+  // 计算信号线（MACD的EMA）
+  const signalLine = calculateEMAFromValues(macdLine, signalPeriod)
+
+  // 生成MACD数据
+  const result: MACDData[] = []
+  for (let i = 0; i < signalLine.length; i++) {
+    const macdValue = macdLine.find(m => m.time === signalLine[i].time)
+    if (macdValue) {
+      result.push({
+        time: signalLine[i].time,
+        macd: macdValue.value,
+        signal: signalLine[i].value,
+        histogram: macdValue.value - signalLine[i].value,
+      })
+    }
+  }
+
+  return result
+}
+
+// 从值数组计算EMA（辅助函数）
+function calculateEMAFromValues(
+  data: Array<{ time: number; value: number }>,
+  period: number
+): Array<{ time: number; value: number }> {
+  const result: Array<{ time: number; value: number }> = []
+  const multiplier = 2 / (period + 1)
+
+  if (data.length < period) return []
+
+  // 第一个EMA值使用SMA
+  let ema = 0
+  for (let i = 0; i < period; i++) {
+    ema += data[i].value
+  }
+  ema = ema / period
+  result.push({ time: data[period - 1].time, value: ema })
+
+  // 后续EMA值
+  for (let i = period; i < data.length; i++) {
+    ema = (data[i].value - ema) * multiplier + ema
+    result.push({ time: data[i].time, value: ema })
+  }
+
+  return result
+}
+
+// RSI 指标
+export function calculateRSI(data: Kline[], period = 14): Array<{ time: number; value: number }> {
+  const result: Array<{ time: number; value: number }> = []
+
+  if (data.length < period + 1) return []
+
+  // 计算价格变化
+  const changes: number[] = []
+  for (let i = 1; i < data.length; i++) {
+    changes.push(data[i].close - data[i - 1].close)
+  }
+
+  // 计算初始平均涨跌幅
+  let avgGain = 0
+  let avgLoss = 0
+  for (let i = 0; i < period; i++) {
+    if (changes[i] > 0) {
+      avgGain += changes[i]
+    } else {
+      avgLoss += Math.abs(changes[i])
+    }
+  }
+  avgGain = avgGain / period
+  avgLoss = avgLoss / period
+
+  // 计算RSI
+  for (let i = period; i < changes.length; i++) {
+    const currentChange = changes[i]
+
+    if (currentChange > 0) {
+      avgGain = (avgGain * (period - 1) + currentChange) / period
+      avgLoss = (avgLoss * (period - 1)) / period
+    } else {
+      avgGain = (avgGain * (period - 1)) / period
+      avgLoss = (avgLoss * (period - 1) + Math.abs(currentChange)) / period
+    }
+
+    const rs = avgGain / avgLoss
+    const rsi = 100 - 100 / (1 + rs)
+
+    result.push({
+      time: data[i + 1].time,
+      value: rsi,
+    })
+  }
+
+  return result
+}
+
+// 布林带
+export interface BollingerBands {
+  time: number
+  upper: number
+  middle: number
+  lower: number
+}
+
+export function calculateBollingerBands(
+  data: Kline[],
+  period = 20,
+  stdDev = 2
+): BollingerBands[] {
+  const result: BollingerBands[] = []
+
+  for (let i = period - 1; i < data.length; i++) {
+    // 计算SMA
+    let sum = 0
+    for (let j = 0; j < period; j++) {
+      sum += data[i - j].close
+    }
+    const sma = sum / period
+
+    // 计算标准差
+    let variance = 0
+    for (let j = 0; j < period; j++) {
+      variance += Math.pow(data[i - j].close - sma, 2)
+    }
+    const std = Math.sqrt(variance / period)
+
+    result.push({
+      time: data[i].time,
+      upper: sma + stdDev * std,
+      middle: sma,
+      lower: sma - stdDev * std,
+    })
+  }
+
+  return result
+}