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
118 lines
4.8 KiB
Python
118 lines
4.8 KiB
Python
from __future__ import annotations
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import logging
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import time
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from typing import Callable, Awaitable, Optional, Sequence
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from app.schemas.schemas import PositionMetrics, PatternSignal
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from app.services.metals.bullionvault_service import get_bullionvault_gold_price
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from app.services.metals.gold_price_fetcher import gold_price_fetcher
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logger = logging.getLogger(__name__)
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class PriceAnchorService:
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"""Rescales simulated metric snapshots to the live gold price feed."""
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def __init__(self, ttl_seconds: int = 30) -> None:
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self._ttl = ttl_seconds
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self._cache_price: Optional[float] = None
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self._cache_ts: float = 0.0
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async def get_anchor_price(self, symbol: str = "XAUUSD") -> Optional[float]:
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now = time.time()
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if self._cache_price and (now - self._cache_ts) < self._ttl:
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return self._cache_price
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fetchers: Sequence[Callable[[], Awaitable[Optional[float]]]] = (
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self._get_bullionvault_price,
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self._get_fallback_price,
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)
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for fetch in fetchers:
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try:
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price = await fetch()
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except Exception as exc: # pragma: no cover - best effort logging only
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logger.warning("Price anchor fetch failed: %s", exc)
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continue
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if price and price > 0:
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self._cache_price = float(price)
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self._cache_ts = now
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return self._cache_price
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return self._cache_price
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def get_anchor_price_sync(self, symbol: str = "XAUUSD") -> Optional[float]:
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"""Synchronous version that returns cached price only"""
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now = time.time()
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if self._cache_price and (now - self._cache_ts) < self._ttl:
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return self._cache_price
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return self._cache_price
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async def _get_bullionvault_price(self) -> Optional[float]:
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data = await get_bullionvault_gold_price("USD")
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return float(data["price"]) if data and data.get("price") else None
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async def _get_fallback_price(self) -> Optional[float]:
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data = await gold_price_fetcher.get_current_gold_price()
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return float(data["price"]) if data and data.get("price") else None
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def apply_anchor(self, metrics: PositionMetrics, anchor_price: Optional[float]) -> PositionMetrics:
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if not anchor_price or metrics.current_price <= 0:
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return metrics
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scale = anchor_price / metrics.current_price
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if abs(scale - 1.0) < 0.005:
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# Already close enough to the anchor, skip unnecessary work
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return metrics
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if not 0.2 <= scale <= 5:
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logger.warning("Skipping unrealistic price anchor scaling (scale=%.4f)", scale)
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return metrics
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scaled = metrics.model_copy(deep=True)
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def scale_value(value: Optional[float], decimals: int = 4) -> Optional[float]:
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if value is None:
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return None
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return round(value * scale, decimals)
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def scale_list(values: list[float]) -> list[float]:
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return [round(v * scale, 2) for v in values]
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scaled.current_price = round(anchor_price, 2)
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scaled.previous_close = scale_value(scaled.previous_close, 2)
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scaled.high = scale_value(scaled.high, 2)
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scaled.low = scale_value(scaled.low, 2)
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scaled.atr14 = scale_value(scaled.atr14)
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scaled.ema21 = scale_value(scaled.ema21)
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scaled.sma55 = scale_value(scaled.sma55)
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scaled.sma100 = scale_value(scaled.sma100)
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scaled.sma200 = scale_value(scaled.sma200)
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scaled.bb_basis = scale_value(scaled.bb_basis)
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scaled.bb_upper = scale_value(scaled.bb_upper)
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scaled.bb_lower = scale_value(scaled.bb_lower)
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scaled.zlsma = scale_value(scaled.zlsma)
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scaled.chandelier_long_stop = scale_value(scaled.chandelier_long_stop, 2)
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scaled.chandelier_short_stop = scale_value(scaled.chandelier_short_stop, 2)
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scaled.momentum12 = scale_value(scaled.momentum12)
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scaled.support_levels = scale_list(scaled.support_levels)
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scaled.resistance_levels = scale_list(scaled.resistance_levels)
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scaled.pattern_signals = [
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signal.model_copy(update={"price": scale_value(signal.price, 2)})
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for signal in scaled.pattern_signals
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]
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if scaled.previous_close is not None:
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scaled.change = round(scaled.current_price - scaled.previous_close, 4)
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if scaled.previous_close:
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scaled.change_percent = round((scaled.change / scaled.previous_close) * 100, 4)
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else:
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scaled.change = scale_value(scaled.change)
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if scaled.previous_close:
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scaled.change_percent = round((scaled.change or 0.0) / scaled.previous_close * 100, 4)
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return scaled
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price_anchor_service = PriceAnchorService()
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