import json

def load_json(path):
    with open(path, 'r') as f:
        return json.load(f)

h1_data = load_json('/home/aryy/.hermes/profiles/finance/backtests/xauusd_2026/hybrid/data/ohlcv_H1.json')['bars']
m15_data = load_json('/home/aryy/.hermes/profiles/finance/backtests/xauusd_2026/hybrid/data/ohlcv_M15.json')['bars']
m5_data = load_json('/home/aryy/.hermes/profiles/finance/backtests/xauusd_2026/hybrid/data/ohlcv_M5.json')['bars']

def filter_by_date(data_list, target_date, window=10):
    for i, candle in enumerate(data_list):
        candle_time = candle.get('timestamp', candle.get('time'))
        if isinstance(candle_time, int):
            continue # skip M5 for a sec or match by timestamp
        if candle_time >= target_date:
            start = max(0, i - window)
            end = min(len(data_list), i + window)
            return data_list[start:end]
    return []

print("\nM5 Execution around 2026-04-13:")
for c in filter_by_date(m5_data, "2026-04-13T01:30:00Z", 20):
    t = c.get('timestamp', c.get('time'))
    print(f"{t}: O={c['open']} H={c['high']} L={c['low']} C={c['close']}")