from fastapi import APIRouter
from typing import Any, Dict, List
import math
from services.database import get_macro_regime_history, get_geo_alert_history, get_trade_entry_prices, reset_journal_history, _fetch_live_prices, _trade_maturity


def _sanitize(obj: Any) -> Any:
    """Replace NaN/Inf with None recursively for JSON compliance."""
    if isinstance(obj, dict):
        return {k: _sanitize(v) for k, v in obj.items()}
    if isinstance(obj, list):
        return [_sanitize(v) for v in obj]
    if isinstance(obj, float) and (math.isnan(obj) or math.isinf(obj)):
        return None
    return obj

router = APIRouter(prefix="/api/journal", tags=["journal"])

# Bearish strategies — P&L is inverted (profit when price falls)
_BEARISH_KEYWORDS = {"bear", "put", "short", "sell", "vente", "baissier"}


def _is_bearish(strategy: str) -> bool:
    s = (strategy or "").lower()
    return any(kw in s for kw in _BEARISH_KEYWORDS)


@router.get("/macro-history")
def macro_history(days: int = 15):
    """Macro regime snapshots for the last N days."""
    return _sanitize({"history": get_macro_regime_history(days), "days": days})


@router.get("/geo-history")
def geo_history(days: int = 30):
    """Geo alert score history for the last N days."""
    return {"history": get_geo_alert_history(days), "days": days}




@router.get("/trade-mtm")
def trade_mtm(days: int = 30):
    """
    Mark-to-market for all logged trade suggestions.
    Enriches with live prices via shared _fetch_live_prices utility.
    """
    entries = get_trade_entry_prices(days)
    tickers_needed = list({(e.get("underlying") or "").upper() for e in entries if e.get("underlying")})
    current_prices = _fetch_live_prices(tickers_needed, timeout=20)

    from datetime import date as _date
    result: List[Dict[str, Any]] = []
    for e in entries:
        ticker = (e.get("underlying") or "").upper()
        entry_price = e.get("entry_price")
        current_price = current_prices.get(ticker)
        pnl_pct = None
        if entry_price and current_price and entry_price > 0:
            raw_pnl = (current_price - entry_price) / entry_price * 100
            pnl_pct = round(-raw_pnl if _is_bearish(e.get("strategy", "")) else raw_pnl, 2)

        days_held = None
        try:
            days_held = (_date.today() - _date.fromisoformat(e["entry_date"])).days
        except Exception:
            pass

        horizon = e.get("horizon_days") or 90
        maturity = _trade_maturity(days_held or 0, horizon)

        result.append({
            **e,
            "current_price": current_price,
            "pnl_pct": pnl_pct,
            "days_held": days_held,
            "direction": "bearish" if _is_bearish(e.get("strategy", "")) else "bullish",
            "maturity": maturity,
        })

    return _sanitize({"trades": result, "days": days, "tickers_fetched": len(current_prices)})


@router.delete("/reset")
def reset_journal():
    """Truncate all journal history (trades, macro, geo, cycles). Irreversible."""
    reset_journal_history()
    return {"reset": True, "message": "Journal de bord réinitialisé"}


@router.get("/summary")
def journal_summary():
    """Quick stats for the Journal de Bord header."""
    macro = get_macro_regime_history(15)
    geo = get_geo_alert_history(30)
    trades = get_trade_entry_prices(30)

    # Detect regime transitions (consecutive different dominants)
    transitions = []
    for i in range(1, len(macro)):
        if macro[i - 1]["dominant"] != macro[i]["dominant"]:
            transitions.append({
                "from": macro[i]["dominant"],
                "to": macro[i - 1]["dominant"],
                "at": macro[i - 1]["timestamp"],
            })

    return {
        "macro_snapshots": len(macro),
        "regime_transitions": transitions[:5],
        "current_dominant": macro[0]["dominant"] if macro else None,
        "geo_alerts": len(geo),
        "avg_geo_score": round(sum(g["geo_score"] for g in geo) / len(geo), 1) if geo else None,
        "max_geo_score": max((g["geo_score"] for g in geo), default=None),
        "trade_entries_logged": len(trades),
    }