d256b65d30
Stack: FastAPI + React/TypeScript + SQLite + GPT-4o Features: Radar géopolitique, Marchés, Régime Macro, Journal de Bord MTM, Rapport IA, Super Contexte (base de raisonnement évolutive), Boucle feedback IA. Deploy: Docker + docker-compose + nginx pour openfin.open-squared.tech Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
113 lines
3.9 KiB
Python
113 lines
3.9 KiB
Python
from fastapi import APIRouter
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from typing import Any, Dict, List
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import math
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from services.database import get_macro_regime_history, get_geo_alert_history, get_trade_entry_prices, reset_journal_history, _fetch_live_prices
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def _sanitize(obj: Any) -> Any:
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"""Replace NaN/Inf with None recursively for JSON compliance."""
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if isinstance(obj, dict):
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return {k: _sanitize(v) for k, v in obj.items()}
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if isinstance(obj, list):
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return [_sanitize(v) for v in obj]
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if isinstance(obj, float) and (math.isnan(obj) or math.isinf(obj)):
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return None
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return obj
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router = APIRouter(prefix="/api/journal", tags=["journal"])
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# Bearish strategies — P&L is inverted (profit when price falls)
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_BEARISH_KEYWORDS = {"bear", "put", "short", "sell", "vente", "baissier"}
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def _is_bearish(strategy: str) -> bool:
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s = (strategy or "").lower()
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return any(kw in s for kw in _BEARISH_KEYWORDS)
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@router.get("/macro-history")
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def macro_history(days: int = 15):
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"""Macro regime snapshots for the last N days."""
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return _sanitize({"history": get_macro_regime_history(days), "days": days})
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@router.get("/geo-history")
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def geo_history(days: int = 30):
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"""Geo alert score history for the last N days."""
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return {"history": get_geo_alert_history(days), "days": days}
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@router.get("/trade-mtm")
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def trade_mtm(days: int = 30):
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"""
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Mark-to-market for all logged trade suggestions.
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Enriches with live prices via shared _fetch_live_prices utility.
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"""
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entries = get_trade_entry_prices(days)
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tickers_needed = list({(e.get("underlying") or "").upper() for e in entries if e.get("underlying")})
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current_prices = _fetch_live_prices(tickers_needed, timeout=20)
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from datetime import date as _date
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result: List[Dict[str, Any]] = []
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for e in entries:
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ticker = (e.get("underlying") or "").upper()
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entry_price = e.get("entry_price")
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current_price = current_prices.get(ticker)
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pnl_pct = None
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if entry_price and current_price and entry_price > 0:
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raw_pnl = (current_price - entry_price) / entry_price * 100
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pnl_pct = round(-raw_pnl if _is_bearish(e.get("strategy", "")) else raw_pnl, 2)
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days_held = None
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try:
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days_held = (_date.today() - _date.fromisoformat(e["entry_date"])).days
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except Exception:
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pass
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result.append({
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**e,
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"current_price": current_price,
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"pnl_pct": pnl_pct,
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"days_held": days_held,
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"direction": "bearish" if _is_bearish(e.get("strategy", "")) else "bullish",
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})
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return _sanitize({"trades": result, "days": days, "tickers_fetched": len(current_prices)})
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@router.delete("/reset")
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def reset_journal():
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"""Truncate all journal history (trades, macro, geo, cycles). Irreversible."""
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reset_journal_history()
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return {"reset": True, "message": "Journal de bord réinitialisé"}
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@router.get("/summary")
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def journal_summary():
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"""Quick stats for the Journal de Bord header."""
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macro = get_macro_regime_history(15)
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geo = get_geo_alert_history(30)
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trades = get_trade_entry_prices(30)
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# Detect regime transitions (consecutive different dominants)
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transitions = []
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for i in range(1, len(macro)):
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if macro[i - 1]["dominant"] != macro[i]["dominant"]:
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transitions.append({
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"from": macro[i]["dominant"],
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"to": macro[i - 1]["dominant"],
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"at": macro[i - 1]["timestamp"],
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})
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return {
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"macro_snapshots": len(macro),
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"regime_transitions": transitions[:5],
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"current_dominant": macro[0]["dominant"] if macro else None,
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"geo_alerts": len(geo),
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"avg_geo_score": round(sum(g["geo_score"] for g in geo) / len(geo), 1) if geo else None,
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"max_geo_score": max((g["geo_score"] for g in geo), default=None),
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"trade_entries_logged": len(trades),
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}
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