#!/usr/bin/env python3
"""
📊 Market Regime Checker - Quick Status
Checks if market is Trending or Ranging
"""

import MetaTrader5 as mt
import pandas as pd
import numpy as np
from datetime import datetime

SYMBOL = "XAUUSD"
TIMEFRAME = mt.TIMEFRAME_M15

def calculate_adx(df, period=14):
    """Calculate ADX indicator"""

    # True Range
    df['high_low'] = df['high'] - df['low']
    df['high_close'] = np.abs(df['high'] - df['close'].shift())
    df['low_close'] = np.abs(df['low'] - df['close'].shift())
    df['true_range'] = df[['high_low', 'high_close', 'low_close']].max(axis=1)

    # Directional Movement
    df['up_move'] = df['high'] - df['high'].shift()
    df['down_move'] = df['low'].shift() - df['low']

    df['plus_dm'] = np.where((df['up_move'] > df['down_move']) & (df['up_move'] > 0), df['up_move'], 0)
    df['minus_dm'] = np.where((df['down_move'] > df['up_move']) & (df['down_move'] > 0), df['down_move'], 0)

    # Smoothed values
    df['atr'] = df['true_range'].rolling(window=period).mean()
    df['plus_di'] = 100 * (df['plus_dm'].rolling(window=period).mean() / df['atr'])
    df['minus_di'] = 100 * (df['minus_dm'].rolling(window=period).mean() / df['atr'])

    # ADX
    df['dx'] = 100 * np.abs(df['plus_di'] - df['minus_di']) / (df['plus_di'] + df['minus_di'])
    df['adx'] = df['dx'].rolling(window=period).mean()

    return df['adx'].iloc[-1]

def check_market_regime():
    """Check current market regime"""

    print("=" * 70)
    print(f"📊 MARKET REGIME CHECK: {SYMBOL}")
    print("=" * 70)

    # Initialize MT5
    if not mt.initialize():
        print("❌ MT5 initialization failed")
        return None

    # Get current price
    tick = mt.symbol_info_tick(SYMBOL)
    if not tick:
        print("❌ Could not get price data")
        mt.shutdown()
        return None

    current_price = tick.bid
    timestamp = datetime.fromtimestamp(tick.time)

    print(f"\n💹 Current Price: ${current_price:.2f}")
    print(f"⏰ Time: {timestamp.strftime('%Y-%m-%d %H:%M:%S')}")

    # Get historical data for ADX calculation
    rates = mt.copy_rates_from_pos(SYMBOL, TIMEFRAME, 0, 100)
    if rates is None or len(rates) == 0:
        print("❌ Could not get historical data")
        mt.shutdown()
        return None

    df = pd.DataFrame(rates)
    df['time'] = pd.to_datetime(df['time'], unit='s')

    # Calculate ADX
    adx = calculate_adx(df, period=14)

    # Determine regime
    if adx < 25:
        regime = "ranging"
        can_trade = False
        symbol = "🛑"
        status = "RANGING MARKET"
        decision = "Trading BLOCKED"
        reason = "ADX < 25 = No clear trend"
        advice = "Wait for trending market (ADX ≥ 25)"
    else:
        regime = "trending"
        can_trade = True
        symbol = "✅"
        status = "TRENDING MARKET"
        decision = "Trading ALLOWED"
        reason = "ADX ≥ 25 = Strong trend"
        advice = "Good conditions for trading!"

    print(f"\n📈 REGIME ANALYSIS:")
    print(f"   Regime: {status}")
    print(f"   ADX: {adx:.1f}")
    print(f"   Status: {symbol} {regime.upper()}")

    print(f"\n🎯 TRADING DECISION:")
    print(f"   {symbol} {decision}")
    print(f"   📊 {reason}")
    print(f"   💡 {advice}")

    # Visual indicator
    print(f"\n📊 ADX SCALE:")
    print("   0-20:  Very Weak/Ranging ❌")
    print("   20-25: Weak/Ranging ⚠️")
    print("   25-40: Trending ✅")
    print("   40+:   Strong Trending ✅✅")
    print(f"   YOUR ADX: {adx:.1f} {'━' * int(adx/2)}")

    print("\n" + "=" * 70)

    mt.shutdown()

    return {
        'regime': regime,
        'adx': adx,
        'can_trade': can_trade,
        'price': current_price,
        'timestamp': timestamp
    }

if __name__ == "__main__":
    result = check_market_regime()

    if result:
        import sys
        sys.exit(0 if result['can_trade'] else 1)