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feat(market): add data staleness detection (Part 2/3) (#800)

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* feat(market): add data staleness detection
## 問題背景
解決 PR #703 Part 2: 數據陳舊性檢測
- 修復 DOGEUSDT 式問題：連續價格不變表示數據源異常
- 防止系統處理僵化/過期的市場數據
## 技術方案
### 數據陳舊性檢測 (market/data.go)
- **函數**: `isStaleData(klines []Kline, symbol string) bool`
- **檢測邏輯**:
  - 連續 5 個 3 分鐘週期價格完全不變（15 分鐘無波動）
  - 價格波動容忍度：0.01%（避免誤報）
  - 成交量檢查：價格凍結 + 成交量為 0 → 確認陳舊
- **處理策略**:
  - 數據陳舊確認：跳過該幣種，返回錯誤
  - 極低波動市場：記錄警告但允許通過（價格穩定但有成交量）
### 調用時機
- 在 `Get()` 函數中，獲取 3m K線後立即檢測
- 早期返回：避免後續無意義的計算和 API 調用
## 實現細節
- **檢測閾值**: 5 個連續週期
- **容忍度**: 0.01% 價格波動
- **日誌**: 英文國際化版本
- **並發安全**: 函數無狀態，安全
## 影響範圍
- ✅ 修改 market/data.go: 新增 isStaleData() + 調用邏輯
- ✅ 新增 log 包導入
- ✅ 50 行新增代碼
## 測試建議
1. 模擬 DOGEUSDT 場景：連續價格不變 + 成交量為 0
2. 驗證日誌輸出：`stale data confirmed: price freeze + zero volume`
3. 正常市場：極低波動但有成交量，應允許通過並記錄警告
## 相關 Issue/PR
- 拆分自 **PR #703** (Part 2/3)
- 基於最新 upstream/dev (3112250)
- 依賴: 無
- 前置: Part 1 (OI 時間序列) - 已提交 PR #798
- 後續: Part 3 (手續費率傳遞)
Co-Authored-By: tinkle-community <tinklefund@gmail.com>
* test(market): add comprehensive unit tests for isStaleData function
- Test normal fluctuating data (expects non-stale)
- Test price freeze with zero volume (expects stale)
- Test price freeze with volume (low volatility market)
- Test insufficient data edge case (<5 klines)
- Test boundary conditions (exactly 5 klines)
- Test tolerance threshold (0.01% price change)
- Test mixed scenario (normal → freeze transition)
- Test empty klines edge case
All 8 test cases passed.
Co-Authored-By: tinkle-community <tinklefund@gmail.com>
---------
Co-authored-by: ZhouYongyou <128128010+zhouyongyou@users.noreply.github.com>
Co-authored-by: tinkle-community <tinklefund@gmail.com>
Co-authored-by: Shui <88711385+hzb1115@users.noreply.github.com>
This commit is contained in:
0xYYBB | ZYY | Bobo
2025-11-12 10:41:26 +08:00
committed by GitHub
parent dbb05f7fde
commit e0b4d026d3
2 changed files with 216 additions and 12 deletions
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177
market/data_test.go
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@@ -131,19 +131,19 @@ func TestCalculateIntradaySeries_VolumeValues(t *testing.T) {
// TestCalculateIntradaySeries_ATR14 测试 ATR14 计算
func TestCalculateIntradaySeries_ATR14(t *testing.T) {
tests := []struct {
name string
klineCount int
expectZero bool
name string
klineCount int
expectZero bool
expectNonZero bool
}{
{
name: "足够数据 - 20个K线",
klineCount: 20,
name: "足够数据 - 20个K线",
klineCount: 20,
expectNonZero: true,
},
{
name: "刚好15个K线（ATR14需要至少15个）",
klineCount: 15,
name: "刚好15个K线（ATR14需要至少15个）",
klineCount: 15,
expectNonZero: true,
},
{
@@ -253,11 +253,11 @@ func TestCalculateATR(t *testing.T) {
func TestCalculateATR_TrueRange(t *testing.T) {
// 创建一个简单的测试用例，手动计算期望的 ATR
klines := []Kline{
{High: 50.0, Low: 48.0, Close: 49.0}, // TR = 2.0
{High: 51.0, Low: 49.0, Close: 50.0}, // TR = max(2.0, 2.0, 1.0) = 2.0
{High: 52.0, Low: 50.0, Close: 51.0}, // TR = max(2.0, 2.0, 1.0) = 2.0
{High: 53.0, Low: 51.0, Close: 52.0}, // TR = 2.0
{High: 54.0, Low: 52.0, Close: 53.0}, // TR = 2.0
{High: 50.0, Low: 48.0, Close: 49.0}, // TR = 2.0
{High: 51.0, Low: 49.0, Close: 50.0}, // TR = max(2.0, 2.0, 1.0) = 2.0
{High: 52.0, Low: 50.0, Close: 51.0}, // TR = max(2.0, 2.0, 1.0) = 2.0
{High: 53.0, Low: 51.0, Close: 52.0}, // TR = 2.0
{High: 54.0, Low: 52.0, Close: 53.0}, // TR = 2.0
}
atr := calculateATR(klines, 3)
@@ -347,3 +347,156 @@ func TestCalculateIntradaySeries_VolumePrecision(t *testing.T) {
}
}
}
// TestIsStaleData_NormalData tests that normal fluctuating data returns false
func TestIsStaleData_NormalData(t *testing.T) {
klines := []Kline{
{Close: 100.0, Volume: 1000},
{Close: 100.5, Volume: 1200},
{Close: 99.8, Volume: 900},
{Close: 100.2, Volume: 1100},
{Close: 100.1, Volume: 950},
}
result := isStaleData(klines, "BTCUSDT")
if result {
t.Error("Expected false for normal fluctuating data, got true")
}
}
// TestIsStaleData_PriceFreezeWithZeroVolume tests that frozen price + zero volume returns true
func TestIsStaleData_PriceFreezeWithZeroVolume(t *testing.T) {
klines := []Kline{
{Close: 100.0, Volume: 0},
{Close: 100.0, Volume: 0},
{Close: 100.0, Volume: 0},
{Close: 100.0, Volume: 0},
{Close: 100.0, Volume: 0},
}
result := isStaleData(klines, "DOGEUSDT")
if !result {
t.Error("Expected true for frozen price + zero volume, got false")
}
}
// TestIsStaleData_PriceFreezeWithVolume tests that frozen price but normal volume returns false
func TestIsStaleData_PriceFreezeWithVolume(t *testing.T) {
klines := []Kline{
{Close: 100.0, Volume: 1000},
{Close: 100.0, Volume: 1200},
{Close: 100.0, Volume: 900},
{Close: 100.0, Volume: 1100},
{Close: 100.0, Volume: 950},
}
result := isStaleData(klines, "STABLECOIN")
if result {
t.Error("Expected false for frozen price but normal volume (low volatility market), got true")
}
}
// TestIsStaleData_InsufficientData tests that insufficient data (<5 klines) returns false
func TestIsStaleData_InsufficientData(t *testing.T) {
klines := []Kline{
{Close: 100.0, Volume: 0},
{Close: 100.0, Volume: 0},
{Close: 100.0, Volume: 0},
}
result := isStaleData(klines, "BTCUSDT")
if result {
t.Error("Expected false for insufficient data (<5 klines), got true")
}
}
// TestIsStaleData_ExactlyFiveKlines tests edge case with exactly 5 klines
func TestIsStaleData_ExactlyFiveKlines(t *testing.T) {
// Stale case: exactly 5 frozen klines with zero volume
staleKlines := []Kline{
{Close: 100.0, Volume: 0},
{Close: 100.0, Volume: 0},
{Close: 100.0, Volume: 0},
{Close: 100.0, Volume: 0},
{Close: 100.0, Volume: 0},
}
result := isStaleData(staleKlines, "TESTUSDT")
if !result {
t.Error("Expected true for exactly 5 frozen klines with zero volume, got false")
}
// Normal case: exactly 5 klines with fluctuation
normalKlines := []Kline{
{Close: 100.0, Volume: 1000},
{Close: 100.1, Volume: 1100},
{Close: 99.9, Volume: 900},
{Close: 100.0, Volume: 1000},
{Close: 100.05, Volume: 950},
}
result = isStaleData(normalKlines, "TESTUSDT")
if result {
t.Error("Expected false for exactly 5 normal klines, got true")
}
}
// TestIsStaleData_WithinTolerance tests price changes within tolerance (0.01%)
func TestIsStaleData_WithinTolerance(t *testing.T) {
// Price changes within 0.01% tolerance should be treated as frozen
basePrice := 10000.0
tolerance := 0.0001 // 0.01%
smallChange := basePrice * tolerance * 0.5 // Half of tolerance
klines := []Kline{
{Close: basePrice, Volume: 1000},
{Close: basePrice + smallChange, Volume: 1000},
{Close: basePrice - smallChange, Volume: 1000},
{Close: basePrice, Volume: 1000},
{Close: basePrice + smallChange, Volume: 1000},
}
result := isStaleData(klines, "BTCUSDT")
// Should return false because there's normal volume despite tiny price changes
if result {
t.Error("Expected false for price within tolerance but with volume, got true")
}
}
// TestIsStaleData_MixedScenario tests realistic scenario with some history before freeze
func TestIsStaleData_MixedScenario(t *testing.T) {
// Simulate: normal trading → suddenly freezes
klines := []Kline{
{Close: 100.0, Volume: 1000}, // Normal
{Close: 100.5, Volume: 1200}, // Normal
{Close: 100.2, Volume: 1100}, // Normal
{Close: 50.0, Volume: 0}, // Freeze starts
{Close: 50.0, Volume: 0}, // Frozen
{Close: 50.0, Volume: 0}, // Frozen
{Close: 50.0, Volume: 0}, // Frozen
{Close: 50.0, Volume: 0}, // Frozen (last 5 are all frozen)
}
result := isStaleData(klines, "DOGEUSDT")
// Should detect stale data based on last 5 klines
if !result {
t.Error("Expected true for frozen last 5 klines with zero volume, got false")
}
}
// TestIsStaleData_EmptyKlines tests edge case with empty slice
func TestIsStaleData_EmptyKlines(t *testing.T) {
klines := []Kline{}
result := isStaleData(klines, "BTCUSDT")
if result {
t.Error("Expected false for empty klines, got true")
}
}