#!/usr/bin/env python3 """Reconstruct journal.csv — all closed trades + manual PHOR close.""" import csv import json import re from datetime import datetime from pathlib import Path from collections import defaultdict LOG_DIR = Path(__file__).parent.parent / "logs" SIGNALS_LOG = LOG_DIR / "signals.log" VT_DIR = LOG_DIR / "virtual_trading" STATES_DIR = VT_DIR / "states" JOURNAL_FILE = VT_DIR / "journal.csv" PHOR_CURRENT_PRICE = 5922.00 # ── Parse signals.log ────────────────────────────────────────────────────── def parse_signals_log(): TS_RE = r'(\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2})' opens = [] details = [] closes = [] with open(SIGNALS_LOG, "r") as f: for line in f: line = line.strip() if not line: continue # SIDE TICKER: entry=..., sl=..., tp=..., size=... m = re.match(rf'^{TS_RE} \| INFO\s+\| (\w+) (\w+): entry=([\d.]+), sl=([\d.]+), tp=([\d.]+), size=(\d+)$', line) if m: ts_str, side, ticker, entry, sl, tp, size = m.groups() ts = int(datetime.strptime(ts_str, "%Y-%m-%d %H:%M:%S").timestamp()) details.append(dict( ticker=ticker, side=side, entry_price=float(entry), sl_price=float(sl), tp_price=float(tp), size=int(size), timestamp=ts, )) continue # [TICKER] POSITION OPENED: SIDE @ PRICE m = re.match(rf'^{TS_RE} \| INFO\s+\| \[(\w+)\] POSITION OPENED: (\w+) @ ([\d.]+)$', line) if m: ts_str, ticker, side, price = m.groups() ts = int(datetime.strptime(ts_str, "%Y-%m-%d %H:%M:%S").timestamp()) opens.append(dict(ticker=ticker, side=side, entry_price=float(price), timestamp=ts)) continue # [TICKER] POSITION CLOSED: STATUS PnL=... RR=... Capital=... m = re.match(rf'^{TS_RE} \| INFO\s+\| \[(\w+)\] POSITION CLOSED: (\w+) PnL=([\d.-]+) RR=([\d.-]+) Capital=([\d.]+)$', line) if m: ts_str, ticker, status, pnl, rr, capital = m.groups() ts = int(datetime.strptime(ts_str, "%Y-%m-%d %H:%M:%S").timestamp()) closes.append(dict(ticker=ticker, status=status, pnl=float(pnl), rr=float(rr), timestamp=ts)) continue # Sort opens.sort(key=lambda x: x["timestamp"]) details.sort(key=lambda x: x["timestamp"]) closes.sort(key=lambda x: x["timestamp"]) # Group by ticker opens_t = defaultdict(list) for o in opens: opens_t[o["ticker"]].append(o) details_t = defaultdict(list) for d in details: details_t[d["ticker"]].append(d) closes_t = defaultdict(list) for c in closes: closes_t[c["ticker"]].append(c) # Merge opens with details (chronological pairing) merged = defaultdict(list) for ticker in set(list(opens_t.keys()) + list(details_t.keys())): op_list = opens_t.get(ticker, []) det_list = details_t.get(ticker, []) for i, op in enumerate(op_list): m = dict(op, sl_price=None, tp_price=None, size=None) if i < len(det_list): d = det_list[i] m.update(sl_price=d["sl_price"], tp_price=d["tp_price"], size=d["size"]) merged[ticker].append(m) # Pair opens with closes, accounting for gaps trades = [] for ticker in sorted(merged.keys()): op_list = merged[ticker] cl_list = closes_t.get(ticker, []) ci = 0 for op in op_list: if op["sl_price"] is None: continue if ci >= len(cl_list): break cl = cl_list[ci] # Skip close if it's before the open (belongs to a missing open) while ci < len(cl_list) and cl_list[ci]["timestamp"] < op["timestamp"]: ci += 1 if ci >= len(cl_list): break cl = cl_list[ci] if op["side"] == "LONG": exit_price = op["entry_price"] + (cl["pnl"] / op["size"]) else: exit_price = op["entry_price"] - (cl["pnl"] / op["size"]) trades.append(dict( ticker=ticker, side=op["side"], entry_time=op["timestamp"], exit_time=cl["timestamp"], entry_price=op["entry_price"], exit_price=round(exit_price, 2), sl_price=op["sl_price"], tp_price=op["tp_price"], size=op["size"], pnl=cl["pnl"], rr=cl["rr"], status=cl["status"], )) ci += 1 return trades, closes_t, merged # ── Manual trades ────────────────────────────────────────────────────────── def add_missing_trades(trades): """Add trades with closes but no opens in signals.log (NVTK first trade).""" nvtk1 = { "ticker": "NVTK", "side": "LONG", "entry_time": 1781694000, "exit_time": 1781722813, "entry_price": 1032.80, "exit_price": 1020.75, "sl_price": 1020.78, "tp_price": 1050.87, "size": 193, "pnl": -2325.24, "rr": -1.00, "status": "SL", } trades.append(nvtk1) print(f"Added missing NVTK trade #1: SL PnL={nvtk1['pnl']:+.2f}") return trades # ── PHOR manual close ───────────────────────────────────────────────────── def add_phor_close(trades): phor_sf = STATES_DIR / "PHOR_state.json" if not phor_sf.exists(): return trades with open(phor_sf) as f: state = json.load(f) pos = state.get("positions", {}).get("PHOR") if not pos: print("PHOR already closed, skipping manual close") return trades entry = pos["entry_price"] exit_p = PHOR_CURRENT_PRICE size = pos["size"] side = pos["side"] pnl = (exit_p - entry) * size if side == "LONG" else (entry - exit_p) * size risk = abs(entry - pos["sl_price"]) rr = pnl / (size * risk) if risk > 0 and size > 0 else 0.0 trades.append({ "ticker": "PHOR", "side": side, "entry_time": int(pos["entry_time"]), "exit_time": int(datetime.now().timestamp()), "entry_price": entry, "exit_price": exit_p, "sl_price": pos["sl_price"], "tp_price": pos["tp_price"], "size": size, "pnl": round(pnl, 2), "rr": round(rr, 2), "status": "MANUAL", }) state["capital"] = round(state["capital"] + pnl, 2) state["journal_count"] = state.get("journal_count", 0) + 1 state["positions"] = {} with open(phor_sf, "w") as f: json.dump(state, f, indent=2) print(f"PHOR closed MANUAL: entry={entry} exit={exit_p} PnL={pnl:+.2f}") print(f"PHOR state updated: capital={state['capital']:,.2f}") return trades # ── Write CSV ────────────────────────────────────────────────────────────── def write_journal(trades): trades.sort(key=lambda t: t["entry_time"]) with open(JOURNAL_FILE, "w", newline="") as f: w = csv.writer(f) w.writerow(["id","ticker","side","entry_time","exit_time", "entry_price","exit_price","sl_price","tp_price", "size","pnl","rr","status","duration_bars", "entry_date","exit_date"]) for i, t in enumerate(trades, 1): w.writerow([ i, t["ticker"], t["side"], t["entry_time"], t["exit_time"], t["entry_price"], t["exit_price"], t["sl_price"], t["tp_price"], t["size"], round(t["pnl"], 2), round(t["rr"], 2), t["status"], (t["exit_time"] - t["entry_time"]) // 3600, datetime.fromtimestamp(t["entry_time"]).strftime("%Y-%m-%d"), datetime.fromtimestamp(t["exit_time"]).strftime("%Y-%m-%d"), ]) # ── Main ─────────────────────────────────────────────────────────────────── def main(): print("=== Reconstructing journal.csv ===\n") trades, closes_t, merged = parse_signals_log() print(f"Parsed {len(trades)} trades from signals.log") print() trades = add_missing_trades(trades) print() trades = add_phor_close(trades) print() write_journal(trades) trades.sort(key=lambda t: t["entry_time"]) print(f"\n{'#':>3s} {'Ticker':6s} {'Side':5s} {'Entry':>10s} {'Exit':>10s} {'Status':6s} {'PnL':>10s} {'Size':>5s} {'Dur':>4s}") print("-" * 80) for i, t in enumerate(trades, 1): dur = (t["exit_time"] - t["entry_time"]) // 3600 print(f"{i:3d} {t['ticker']:6s} {t['side']:5s} {t['entry_price']:10.2f} {t['exit_price']:10.2f} {t['status']:6s} {t['pnl']:+10.2f} {t['size']:5d} {dur:4d}") total = sum(t["pnl"] for t in trades) wins = [t for t in trades if t["pnl"] > 0] losses = [t for t in trades if t["pnl"] <= 0] print(f"\nSummary: {len(trades)} trades | PnL={total:+,.2f} | Capital={1_000_000+total:,.2f}") print(f"Wins={len(wins)} ({sum(t['pnl'] for t in wins):+,.2f}) | Losses={len(losses)} ({sum(t['pnl'] for t in losses):+,.2f})") print(f"\nWritten to: {JOURNAL_FILE}") if __name__ == "__main__": main()