PythagorasGoal/scripts/analysis/trades_status.py

"""Report "stato trades" — separa SEMPRE pool reale e paper-stats, e mostra sia
realizzato che unrealized. Verita' aggregata = ledger PORT06; il dettaglio per-trade
viene dai worker dir.

Fonte unica della separazione (NON la memoria — qui ho gia' sbagliato una volta
includendo XS01 nell'equity):
  data/portfolio_paper/        -> POOL REALE   (nel ledger, muove l'equity/il conto)
  data/portfolio_paper_stats/  -> PAPER-STATS  (solo statistica, MAI nel ledger)

Uso:
  uv run python scripts/analysis/trades_status.py                 # ultime 24h
  uv run python scripts/analysis/trades_status.py --since 2026-06-16T14:00
"""
import argparse
import datetime as dt
import glob
import json
import sys
from pathlib import Path

sys.path.insert(0, str(Path(__file__).resolve().parents[2]))  # project root -> import src.*

DATA = Path("data")
POOL_DIR = DATA / "portfolio_paper"
STATS_DIR = DATA / "portfolio_paper_stats"
LEDGER = DATA / "portfolios" / "PORT06" / "status.json"
EQUITY = DATA / "portfolios" / "PORT06" / "equity.jsonl"


def _closes(worker_dir: Path, since: dt.datetime):
    """CLOSE events dei worker in worker_dir dal momento `since`."""
    out = []
    for f in sorted(glob.glob(str(worker_dir / "*" / "trades.jsonl"))):
        name = Path(f).parent.name
        for line in open(f):
            try:
                d = json.loads(line)
            except json.JSONDecodeError:
                continue
            if d.get("event") != "CLOSE":
                continue
            try:
                t = dt.datetime.fromisoformat(d.get("ts", ""))
            except ValueError:
                continue
            if t < since:
                continue
            # PnL che conta: reale se eseguito (real_truth), altrimenti il sim/pnl
            real = d.get("real_pnl")
            real = real if real is not None else d.get("pnl", 0.0)
            out.append({
                "ts": d.get("ts", "")[:19], "name": name, "reason": d.get("reason"),
                "held": d.get("bars_held"), "pnl": d.get("pnl"),
                "real": d.get("real_pnl"), "sim": d.get("sim_pnl"), "eff": real or 0.0,
            })
    return sorted(out, key=lambda r: r["ts"])


def _open_positions(worker_dir: Path):
    """Posizioni aperte con i campi per il PnL non realizzato (entry REALE di
    esecuzione quando eseguito; il feed di decisione sim e' dislocato)."""
    out = []
    for f in sorted(glob.glob(str(worker_dir / "*" / "status.json"))):
        d = json.load(open(f))
        if not d.get("in_position"):
            continue
        wid = Path(f).parent.name
        is_pair = "entry_a" in d
        executed = bool(d.get("real_in_position"))
        row = {"name": wid, "pair": is_pair, "real": executed,
               "dir": d.get("direction", 0), "held": d.get("bars_held"),
               "max_bars": d.get("max_bars"), "tp": d.get("tp", 0.0),
               "unreal": None}
        if is_pair:
            a_, b_ = wid.split("__")[1].split("_")
            row.update({
                "assets": [a_, b_], "leg_a": a_, "leg_b": b_,
                "entry_a": d.get("real_entry_a") if executed else d.get("entry_a"),
                "entry_b": d.get("real_entry_b") if executed else d.get("entry_b"),
                "notional_a": d.get("real_notional_a") or 0.0,
                "notional_b": d.get("real_notional_b") or 0.0,
            })
        else:
            asset = wid.split("__")[1]
            entry = (d.get("real_entry_price") if executed else None) or d.get("entry_price") or 0.0
            row.update({
                "assets": [asset], "asset": asset, "entry": entry,
                "notional": d.get("real_entry_notional") or round(d.get("capital", 0.0) * 0.5 * 3, 1),
            })
        out.append(row)
    return out


def _marks(assets: set) -> dict:
    """Mark correnti USDC perp (best-effort). {} se Cerbero non risponde."""
    if not assets:
        return {}
    try:
        from src.live.cerbero_client import CerberoClient
        insts = [f"{a}_USDC-PERPETUAL" for a in assets]
        data = CerberoClient().get_ticker_batch(insts)
        return {t["instrument_name"].split("_")[0].replace("-PERPETUAL", ""): t.get("mark_price")
                for t in data.get("tickers", [])}
    except Exception as e:
        print(f"[trades_status] mark fetch fallita ({e!r}) -> PnL aperti n/d", file=sys.stderr)
        return {}


def _annotate_pnl(positions, marks):
    """PnL non realizzato live, convenzione identica alla dashboard (entry reale vs mark USDC)."""
    for a in positions:
        if a["pair"]:
            ma, mb = marks.get(a["leg_a"]), marks.get(a["leg_b"])
            if ma and mb and a.get("entry_a") and a.get("entry_b"):
                s = 1 if a["dir"] > 0 else -1            # +1: long A / short B
                ga = a["notional_a"] * s * (ma - a["entry_a"]) / a["entry_a"]
                gb = a["notional_b"] * (-s) * (mb - a["entry_b"]) / a["entry_b"]
                a["unreal"] = ga + gb
                a["mark"], a["mark_b"] = ma, mb
        else:
            mk = marks.get(a["asset"])
            if mk and a.get("entry"):
                sign = 1 if a["dir"] > 0 else -1
                pct = sign * (mk - a["entry"]) / a["entry"]
                a["unreal"] = a["notional"] * pct
                a["unreal_pct"] = pct * 100
                a["mark"] = mk
    return positions


def _equity_at(since: dt.datetime):
    """Equity piu' vicino (e <=) a `since`, per il Δ della finestra."""
    base = None
    if not EQUITY.exists():
        return None
    for line in open(EQUITY):
        try:
            d = json.loads(line)
            t = dt.datetime.fromisoformat(d["ts"])
        except (json.JSONDecodeError, KeyError, ValueError):
            continue
        if t <= since:
            base = d["equity"]
        else:
            break
    return base


def main():
    ap = argparse.ArgumentParser()
    ap.add_argument("--since", default=None,
                    help="ISO (es. 2026-06-16T14:00). Default: 24h fa.")
    args = ap.parse_args()

    now = dt.datetime.now(dt.timezone.utc)
    if args.since:
        since = dt.datetime.fromisoformat(args.since)
        if since.tzinfo is None:
            since = since.replace(tzinfo=dt.timezone.utc)
    else:
        since = now - dt.timedelta(hours=24)

    led = json.load(open(LEDGER))
    equity = led["equity"]
    cap = led["total_capital"]
    unreal = equity - cap
    eq_base = _equity_at(since)
    ver = Path("VERSION").read_text().strip() if Path("VERSION").exists() else "?"

    print(f"STATO TRADES — v{ver} — {now:%Y-%m-%d %H:%M} UTC  (finestra dal {since:%Y-%m-%d %H:%M})\n")

    # ---- aggregato (ledger = verita') ----
    print("LEDGER PORT06 (verita' aggregata)")
    print(f"  equity           = {equity:.2f}")
    print(f"  capitale realizz.= {cap:.2f}")
    print(f"  unrealized aperti= {unreal:+.2f}   (equity - capitale; pos. aperte mark-to-market)")
    print(f"  peak {led.get('peak'):.2f}   maxDD {led.get('max_dd')}%")
    if eq_base is not None:
        print(f"  Δ equity finestra= {equity - eq_base:+.2f}   ({eq_base:.2f} -> {equity:.2f})")

    # ---- POOL REALE ----
    pool = _closes(POOL_DIR, since)
    s_real = sum(r["eff"] for r in pool)
    wins = sum(1 for r in pool if r["eff"] > 0)
    print(f"\n=== POOL REALE (muove l'equity) — {len(pool)} chiusure, {wins}W/{len(pool)-wins}L ===")
    for r in pool:
        tag = "LOSS" if r["eff"] < 0 else "win "
        print(f"  {r['ts']} {tag} {r['name']:36} {str(r['reason']):11} "
              f"real={r['real']} sim={r['sim']}")
    print(f"  Σ REALIZZATO POOL = {s_real:+.2f}")
    op = _open_positions(POOL_DIR)
    if op:
        assets = set().union(*[set(p["assets"]) for p in op])
        marks = _marks(assets)
        _annotate_pnl(op, marks)
        s_unreal = sum(p["unreal"] for p in op if p["unreal"] is not None)
        n_marked = sum(1 for p in op if p["unreal"] is not None)
        print(f"\n  posizioni aperte ({len(op)}) — PnL non realizzato live (entry reale vs mark USDC):")
        for p in sorted(op, key=lambda x: (x["unreal"] is None, x.get("unreal") or 0)):
            d = {1: "LONG", -1: "SHORT"}.get(p["dir"], "?")
            if p["unreal"] is not None:
                pct = f"{p['unreal_pct']:+.2f}%" if not p["pair"] and "unreal_pct" in p else ""
                mark = f"mark={p['mark']}" if not p["pair"] else f"mk {p['mark']}/{p.get('mark_b')}"
                pnl = f"{p['unreal']:+.2f}"
            else:
                pct = mark = ""; pnl = "n/d (no mark)"
            ent = f"entry={p['entry']}" if not p["pair"] else f"a={p.get('entry_a')} b={p.get('entry_b')}"
            print(f"    {p['name']:36} {d:5} h={p['held']}/{p['max_bars']} {ent} {mark}  "
                  f"PnL {pnl} {pct}")
        print(f"  Σ UNREALIZED REALE = {s_unreal:+.2f}  ({n_marked}/{len(op)} con mark live)  "
              f"<- verita' del conto (entry reale vs mark USDC)")
        print(f"    ledger unrealized = {unreal:+.2f} (feed sim-decisione testnet DISLOCATO); "
              f"lo scarto {s_unreal - unreal:+.2f} e' la dislocazione del feed, non soldi.")

    # ---- PAPER-STATS ----
    stats = _closes(STATS_DIR, since)
    s_stats = sum(r["eff"] for r in stats)
    print(f"\n=== PAPER-STATS (solo statistica — NON tocca equity/conto) — {len(stats)} chiusure ===")
    for r in stats:
        print(f"  {r['ts']}      {r['name']:36} pnl={r['pnl']}")
    print(f"  Σ PAPER-STATS = {s_stats:+.2f}   <- ignorare per l'equity")

    # ---- riconciliazione ----
    print("\nRICONCILIAZIONE")
    print(f"  realizzato POOL {s_real:+.2f}  +  Δunrealized aperti  ≈  Δ equity finestra")
    if eq_base is not None:
        residuo = (equity - eq_base) - s_real
        print(f"  Δequity {equity - eq_base:+.2f}  -  realizzato {s_real:+.2f}  =  "
              f"{residuo:+.2f}  (= Δunrealized + ribilanci/timing)")
    print(f"  paper-stats {s_stats:+.2f} NON incluso (book in sola simulazione).")


if __name__ == "__main__":
    main()