debug_trade.py

"""
Dump raw 5m OHLC that the backtest actually read for a given trade —
both the underlying stock and the option — so you can visually compare
against TradingView / Kite chart and spot data glitches.

Usage:
    python debug_trade.py --symbol ANGELONE --option ANGELONE26APR315CE --date 2026-04-17 --around 12:30

Prints a window of bars around the time of interest, plus the exact
indication / confirmation / trigger bars so you can see what prices
strategy-1 saw.
"""

from __future__ import annotations

import argparse
from datetime import datetime, timedelta, time
from pathlib import Path

import pandas as pd

from history_utils import get_stock_5m, get_option_5m
from indicators_v2 import add_strategy_indicators_v2


def _fmt(df: pd.DataFrame, extra_cols=None) -> str:
    base = ["timestamp", "open", "high", "low", "close", "volume"]
    cols = [c for c in base if c in df.columns]
    if extra_cols:
        cols += [c for c in extra_cols if c in df.columns and c not in cols]
    return df[cols].to_string(index=False)


def main():
    ap = argparse.ArgumentParser()
    ap.add_argument("--symbol", required=True, help="Underlying stock symbol (e.g., ANGELONE)")
    ap.add_argument("--option", required=True, help="Option tradingsymbol (e.g., ANGELONE26APR315CE)")
    ap.add_argument("--date", required=True, help="Trade date YYYY-MM-DD")
    ap.add_argument("--around", default="12:30", help="Time of interest HH:MM (IST)")
    ap.add_argument("--window-min", type=int, default=30, help="Minutes before/after to show (default 30)")
    args = ap.parse_args()

    day = pd.Timestamp(args.date).date()
    around_h, around_m = [int(x) for x in args.around.split(":")]
    around_ts = datetime.combine(day, time(around_h, around_m))
    win = timedelta(minutes=args.window_min)

    fetch_from = datetime.combine(day - timedelta(days=5), time(9, 15))
    fetch_to = datetime.combine(day, time(15, 30))

    print(f"=== UNDERLYING {args.symbol} on {args.date} ===")
    stock = get_stock_5m(args.symbol, fetch_from, fetch_to)
    if stock.empty:
        print("(no stock data)")
    else:
        stock = add_strategy_indicators_v2(stock)
        stock["timestamp"] = pd.to_datetime(stock["timestamp"])
        day_stock = stock[stock["timestamp"].dt.date == day].copy()
        day_stock["body_high"] = day_stock[["open", "close"]].max(axis=1)
        day_stock["body_low"] = day_stock[["open", "close"]].min(axis=1)
        ts_naive = day_stock["timestamp"].dt.tz_localize(None) if day_stock["timestamp"].dt.tz is not None else day_stock["timestamp"]
        mask = (ts_naive >= (around_ts - win)) & (ts_naive <= (around_ts + win))
        view = day_stock[mask]
        print(_fmt(view, extra_cols=[
            "body_high", "body_low",
            "bb_phase", "ema5", "ema9", "ck_dir", "jghla_dir",
        ]))

    print(f"\n=== OPTION {args.option} on {args.date} ===")
    try:
        opt = get_option_5m(args.option, fetch_from, fetch_to)
    except Exception as e:
        print(f"(error fetching option: {e})")
        return

    if opt.empty:
        print("(no option data - possibly expired beyond retention window)")
        return

    opt["timestamp"] = pd.to_datetime(opt["timestamp"])
    day_opt = opt[opt["timestamp"].dt.date == day].copy()
    day_opt["body_high"] = day_opt[["open", "close"]].max(axis=1)
    day_opt["body_low"] = day_opt[["open", "close"]].min(axis=1)
    ts_naive = day_opt["timestamp"].dt.tz_localize(None) if day_opt["timestamp"].dt.tz is not None else day_opt["timestamp"]
    mask = (ts_naive >= (around_ts - win)) & (ts_naive <= (around_ts + win))
    view = day_opt[mask]
    print(_fmt(view, extra_cols=["body_high", "body_low"]))

    # Highlight the bars the backtest keyed off
    print("\n=== KEY BARS BACKTEST USED ===")
    ind_ts = around_ts - timedelta(minutes=5)     # confirmation - 1 bar
    conf_ts = around_ts                           # confirmation bar
    trig_ts_a = around_ts + timedelta(minutes=5)  # first trigger check
    trig_ts_b = around_ts + timedelta(minutes=10) # second trigger check

    print(f"indication bar   : {ind_ts}  (strategy-1 stop_loss = body_low of this option candle)")
    print(f"confirmation bar : {conf_ts}  (trigger level = body_high of this underlying candle)")
    print(f"trigger bar(s)   : {trig_ts_a} / {trig_ts_b}  (entry fires on break; buy_price = body_high of option candle at that bar)")


if __name__ == "__main__":
    main()