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Merge from beta

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This commit is contained in:
Icy
2025-11-13 23:05:57 +08:00
parent 9927ede8fd b43315d9fc
commit d787b72d75
210 changed files with 46931 additions and 7541 deletions
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159
market/data.go
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@@ -4,10 +4,24 @@ import (
"encoding/json"
"fmt"
"io"
"log"
"math"
"net/http"
"strconv"
"strings"
"sync"
"time"
)
// FundingRateCache 资金费率缓存结构
// Binance Funding Rate 每 8 小时才更新一次，使用 1 小时缓存可显著减少 API 调用
type FundingRateCache struct {
Rate float64
UpdatedAt time.Time
}
var (
fundingRateMap sync.Map // map[string]*FundingRateCache
frCacheTTL = 1 * time.Hour
)
// Get 获取指定代币的市场数据
@@ -22,12 +36,26 @@ func Get(symbol string) (*Data, error) {
return nil, fmt.Errorf("获取3分钟K线失败: %v", err)
}
// Data staleness detection: Prevent DOGEUSDT-style price freeze issues
if isStaleData(klines3m, symbol) {
log.Printf("⚠️ WARNING: %s detected stale data (consecutive price freeze), skipping symbol", symbol)
return nil, fmt.Errorf("%s data is stale, possible cache failure", symbol)
}
// 获取4小时K线数据 (最近10个)
klines4h, err = WSMonitorCli.GetCurrentKlines(symbol, "4h") // 多获取用于计算指标
if err != nil {
return nil, fmt.Errorf("获取4小时K线失败: %v", err)
}
// 检查数据是否为空
if len(klines3m) == 0 {
return nil, fmt.Errorf("3分钟K线数据为空")
}
if len(klines4h) == 0 {
return nil, fmt.Errorf("4小时K线数据为空")
}
// 计算当前指标 (基于3分钟最新数据)
currentPrice := klines3m[len(klines3m)-1].Close
currentEMA20 := calculateEMA(klines3m, 20)
@@ -206,6 +234,7 @@ func calculateIntradaySeries(klines []Kline) *IntradayData {
MACDValues: make([]float64, 0, 10),
RSI7Values: make([]float64, 0, 10),
RSI14Values: make([]float64, 0, 10),
Volume: make([]float64, 0, 10),
}
// 获取最近10个数据点
@@ -216,6 +245,7 @@ func calculateIntradaySeries(klines []Kline) *IntradayData {
for i := start; i < len(klines); i++ {
data.MidPrices = append(data.MidPrices, klines[i].Close)
data.Volume = append(data.Volume, klines[i].Volume)
// 计算每个点的EMA20
if i >= 19 {
@@ -240,6 +270,9 @@ func calculateIntradaySeries(klines []Kline) *IntradayData {
}
}
// 计算3m ATR14
data.ATR14 = calculateATR(klines, 14)
return data
}
@@ -293,7 +326,8 @@ func calculateLongerTermData(klines []Kline) *LongerTermData {
func getOpenInterestData(symbol string) (*OIData, error) {
url := fmt.Sprintf("https://fapi.binance.com/fapi/v1/openInterest?symbol=%s", symbol)
resp, err := http.Get(url)
apiClient := NewAPIClient()
resp, err := apiClient.client.Get(url)
if err != nil {
return nil, err
}
@@ -322,11 +356,23 @@ func getOpenInterestData(symbol string) (*OIData, error) {
}, nil
}
// getFundingRate 获取资金费率
// getFundingRate 获取资金费率（优化：使用 1 小时缓存）
func getFundingRate(symbol string) (float64, error) {
// 检查缓存（有效期 1 小时）
// Funding Rate 每 8 小时才更新，1 小时缓存非常合理
if cached, ok := fundingRateMap.Load(symbol); ok {
cache := cached.(*FundingRateCache)
if time.Since(cache.UpdatedAt) < frCacheTTL {
// 缓存命中，直接返回
return cache.Rate, nil
}
}
// 缓存过期或不存在，调用 API
url := fmt.Sprintf("https://fapi.binance.com/fapi/v1/premiumIndex?symbol=%s", symbol)
resp, err := http.Get(url)
apiClient := NewAPIClient()
resp, err := apiClient.client.Get(url)
if err != nil {
return 0, err
}
@@ -352,6 +398,13 @@ func getFundingRate(symbol string) (float64, error) {
}
rate, _ := strconv.ParseFloat(result.LastFundingRate, 64)
// 更新缓存
fundingRateMap.Store(symbol, &FundingRateCache{
Rate: rate,
UpdatedAt: time.Now(),
})
return rate, nil
}
@@ -359,15 +412,20 @@ func getFundingRate(symbol string) (float64, error) {
func Format(data *Data) string {
var sb strings.Builder
sb.WriteString(fmt.Sprintf("current_price = %.2f, current_ema20 = %.3f, current_macd = %.3f, current_rsi (7 period) = %.3f\n\n",
data.CurrentPrice, data.CurrentEMA20, data.CurrentMACD, data.CurrentRSI7))
// 使用动态精度格式化价格
priceStr := formatPriceWithDynamicPrecision(data.CurrentPrice)
sb.WriteString(fmt.Sprintf("current_price = %s, current_ema20 = %.3f, current_macd = %.3f, current_rsi (7 period) = %.3f\n\n",
priceStr, data.CurrentEMA20, data.CurrentMACD, data.CurrentRSI7))
sb.WriteString(fmt.Sprintf("In addition, here is the latest %s open interest and funding rate for perps:\n\n",
data.Symbol))
if data.OpenInterest != nil {
sb.WriteString(fmt.Sprintf("Open Interest: Latest: %.2f Average: %.2f\n\n",
data.OpenInterest.Latest, data.OpenInterest.Average))
// 使用动态精度格式化 OI 数据
oiLatestStr := formatPriceWithDynamicPrecision(data.OpenInterest.Latest)
oiAverageStr := formatPriceWithDynamicPrecision(data.OpenInterest.Average)
sb.WriteString(fmt.Sprintf("Open Interest: Latest: %s Average: %s\n\n",
oiLatestStr, oiAverageStr))
}
sb.WriteString(fmt.Sprintf("Funding Rate: %.2e\n\n", data.FundingRate))
@@ -394,6 +452,12 @@ func Format(data *Data) string {
if len(data.IntradaySeries.RSI14Values) > 0 {
sb.WriteString(fmt.Sprintf("RSI indicators (14‑Period): %s\n\n", formatFloatSlice(data.IntradaySeries.RSI14Values)))
}
if len(data.IntradaySeries.Volume) > 0 {
sb.WriteString(fmt.Sprintf("Volume: %s\n\n", formatFloatSlice(data.IntradaySeries.Volume)))
}
sb.WriteString(fmt.Sprintf("3m ATR (14‑period): %.3f\n\n", data.IntradaySeries.ATR14))
}
if data.LongerTermContext != nil {
@@ -420,11 +484,42 @@ func Format(data *Data) string {
return sb.String()
}
// formatFloatSlice 格式化float64切片为字符串
// formatPriceWithDynamicPrecision 根据价格区间动态选择精度
// 这样可以完美支持从超低价 meme coin (< 0.0001) 到 BTC/ETH 的所有币种
func formatPriceWithDynamicPrecision(price float64) string {
switch {
case price < 0.0001:
// 超低价 meme coin: 1000SATS, 1000WHY, DOGS
// 0.00002070 → "0.00002070" (8位小数)
return fmt.Sprintf("%.8f", price)
case price < 0.001:
// 低价 meme coin: NEIRO, HMSTR, HOT, NOT
// 0.00015060 → "0.000151" (6位小数)
return fmt.Sprintf("%.6f", price)
case price < 0.01:
// 中低价币: PEPE, SHIB, MEME
// 0.00556800 → "0.005568" (6位小数)
return fmt.Sprintf("%.6f", price)
case price < 1.0:
// 低价币: ASTER, DOGE, ADA, TRX
// 0.9954 → "0.9954" (4位小数)
return fmt.Sprintf("%.4f", price)
case price < 100:
// 中价币: SOL, AVAX, LINK, MATIC
// 23.4567 → "23.4567" (4位小数)
return fmt.Sprintf("%.4f", price)
default:
// 高价币: BTC, ETH (节省 Token)
// 45678.9123 → "45678.91" (2位小数)
return fmt.Sprintf("%.2f", price)
}
}
// formatFloatSlice 格式化float64切片为字符串（使用动态精度）
func formatFloatSlice(values []float64) string {
strValues := make([]string, len(values))
for i, v := range values {
strValues[i] = fmt.Sprintf("%.3f", v)
strValues[i] = formatPriceWithDynamicPrecision(v)
}
return "[" + strings.Join(strValues, ", ") + "]"
}
@@ -453,3 +548,47 @@ func parseFloat(v interface{}) (float64, error) {
return 0, fmt.Errorf("unsupported type: %T", v)
}
}
// isStaleData detects stale data (consecutive price freeze)
// Fix DOGEUSDT-style issue: consecutive N periods with completely unchanged prices indicate data source anomaly
func isStaleData(klines []Kline, symbol string) bool {
if len(klines) < 5 {
return false // Insufficient data to determine
}
// Detection threshold: 5 consecutive 3-minute periods with unchanged price (15 minutes without fluctuation)
const stalePriceThreshold = 5
const priceTolerancePct = 0.0001 // 0.01% fluctuation tolerance (avoid false positives)
// Take the last stalePriceThreshold K-lines
recentKlines := klines[len(klines)-stalePriceThreshold:]
firstPrice := recentKlines[0].Close
// Check if all prices are within tolerance
for i := 1; i < len(recentKlines); i++ {
priceDiff := math.Abs(recentKlines[i].Close-firstPrice) / firstPrice
if priceDiff > priceTolerancePct {
return false // Price fluctuation exists, data is normal
}
}
// Additional check: MACD and volume
// If price is unchanged but MACD/volume shows normal fluctuation, it might be a real market situation (extremely low volatility)
// Check if volume is also 0 (data completely frozen)
allVolumeZero := true
for _, k := range recentKlines {
if k.Volume > 0 {
allVolumeZero = false
break
}
}
if allVolumeZero {
log.Printf("⚠️ %s stale data confirmed: price freeze + zero volume", symbol)
return true
}
// Price frozen but has volume: might be extremely low volatility market, allow but log warning
log.Printf("⚠️ %s detected extreme price stability (no fluctuation for %d consecutive periods), but volume is normal", symbol, stalePriceThreshold)
return false
}