Krikorios
48e60d015f
- Add advanced metrics dashboard with trade analytics - Add new trading components (EntryTypeAnalysis, MultiDayPositionTracker, NewsEventTracker, etc.) - Add strategy mode selector and trend confirmation - Add risk automation panel and slippage correlation analysis - Add daily trading plan enhancements with modal components - Add custom hooks (useApi, useLocalStorage, useAdvancedTradeMetrics) - Add broker service integration and trading API - Add test setup and vitest configuration - Include parquet data files for live market data - Add comprehensive documentation in docs/ folder
91 lines
3.0 KiB
Python
91 lines
3.0 KiB
Python
import math
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from app.schemas.schemas import PriceData
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from app.services.ai_context_builder import AIContextBuilder
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def _build_sample_price_data(bars: int = 220) -> list[PriceData]:
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base_price = 1950.0
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price_data: list[PriceData] = []
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for i in range(bars):
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drift = i * 0.25
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wave = math.sin(i / 7.0) * 3.0
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close = base_price + drift + wave
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high = close + 0.8
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low = close - 0.8
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open_price = close - math.sin(i / 11.0) * 0.5
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price_data.append(
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PriceData(
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time=i,
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open=open_price,
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high=high,
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low=low,
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close=close,
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volume=1000 + i,
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)
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)
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return price_data
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def test_build_metrics_includes_enhanced_indicators():
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price_data = _build_sample_price_data()
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builder = AIContextBuilder()
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metrics = builder.build_metrics("XAUUSD", "1m", price_data)
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assert metrics.bb_basis is not None
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assert metrics.bb_upper is not None
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assert metrics.bb_lower is not None
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assert metrics.rsi3 is not None
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assert metrics.zlsma is not None
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assert metrics.chandelier_long_stop is not None
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assert metrics.chandelier_short_stop is not None
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assert metrics.chandelier_signal in {None, "LONG", "SHORT", "NEUTRAL"}
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assert metrics.bb_signal in {None, "LONG", "SHORT"}
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def test_indicator_payload_emits_enhanced_metrics():
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price_data = _build_sample_price_data()
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builder = AIContextBuilder()
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bars = [
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{
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"time": item.time,
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"open": item.open,
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"high": item.high,
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"low": item.low,
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"close": item.close,
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"volume": item.volume,
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}
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for item in price_data
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]
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indicator_payload = builder._build_indicators(bars) # type: ignore[attr-defined]
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indicator_names = {entry["name"] for entry in indicator_payload}
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assert "RSI_3" in indicator_names
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assert "BB_20_BASIS" in indicator_names
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assert "BB_20_UPPER" in indicator_names
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assert "BB_20_LOWER" in indicator_names
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assert "ZLSMA_50" in indicator_names
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assert "CHAND_22_LONG" in indicator_names
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assert "CHAND_22_SHORT" in indicator_names
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def test_candlestick_patterns_detected():
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candles = [
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PriceData(time=0, open=100.0, high=101.0, low=99.0, close=99.0, volume=1000),
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PriceData(time=1, open=99.2, high=100.0, low=95.2, close=95.5, volume=1005),
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PriceData(time=2, open=95.0, high=101.2, low=94.8, close=100.8, volume=1010), # Bullish engulfing candle
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PriceData(time=3, open=100.1, high=100.4, low=99.9, close=100.12, volume=1015), # Doji
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PriceData(time=4, open=99.8, high=100.2, low=95.5, close=99.7, volume=1020), # Long lower shadow
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]
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builder = AIContextBuilder()
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metrics = builder.build_metrics("XAUUSD", "1m", candles)
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names = {signal.pattern for signal in metrics.pattern_signals}
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assert "Bullish Engulfing" in names
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assert "Doji" in names
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assert "Long Lower Shadow" in names
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