all changes done over the last 2 weeks

check_system_status.py

@@ -0,0 +1,185 @@
+#!/usr/bin/env python3
+"""
+📊 System Status Check - Trading Bot V2.2
+"""
+
+import sqlite3
+from datetime import datetime, timedelta
+import os
+
+DB_PATH = "trading_bot.db"
+
+def check_status():
+    """Comprehensive system status check"""
+
+    print("=" * 70)
+    print("📊 TRADING BOT V2.2 - SYSTEM STATUS")
+    print("=" * 70)
+
+    if not os.path.exists(DB_PATH):
+        print(f"❌ Database not found: {DB_PATH}")
+        return
+
+    conn = sqlite3.connect(DB_PATH)
+    cursor = conn.cursor()
+
+    try:
+        # 1. CONSECUTIVE LOSSES
+        print("\n🎯 CONSECUTIVE LOSSES:")
+        cursor.execute("""
+            SELECT net_profit
+            FROM trades
+            WHERE status = 'closed'
+            ORDER BY exit_time DESC
+            LIMIT 20
+        """)
+
+        trades = cursor.fetchall()
+        consecutive = 0
+        for trade in trades:
+            if trade[0] < 0:
+                consecutive += 1
+            else:
+                break
+
+        print(f"   Current: {consecutive}")
+        print(f"   Status: {'✅ OK' if consecutive < 5 else '🚨 BLOCKED (≥5)'}")
+
+        # 2. RECENT TRADES
+        print("\n📋 LAST 10 TRADES:")
+        cursor.execute("""
+            SELECT ticket, entry_time, exit_time, profit, net_profit, exit_reason, regime
+            FROM trades
+            WHERE status = 'closed'
+            ORDER BY exit_time DESC
+            LIMIT 10
+        """)
+
+        for row in cursor.fetchall():
+            ticket, entry, exit, profit, net_profit, reason, regime = row
+            symbol = "✅" if net_profit > 0 else "❌"
+            print(f"   {symbol} #{ticket}: ${net_profit:.2f} | {regime or 'unknown'} | {reason or 'unknown'}")
+
+        # 3. PERFORMANCE STATS
+        print("\n📈 PERFORMANCE (Last 20 trades):")
+        cursor.execute("""
+            SELECT
+                COUNT(*) as total,
+                SUM(CASE WHEN net_profit > 0 THEN 1 ELSE 0 END) as wins,
+                SUM(CASE WHEN net_profit < 0 THEN 1 ELSE 0 END) as losses,
+                SUM(net_profit) as total_pnl,
+                AVG(net_profit) as avg_pnl
+            FROM trades
+            WHERE status = 'closed'
+            ORDER BY exit_time DESC
+            LIMIT 20
+        """)
+
+        row = cursor.fetchone()
+        if row:
+            total, wins, losses, total_pnl, avg_pnl = row
+            if total > 0:
+                win_rate = (wins / total) * 100
+                print(f"   Total Trades: {total}")
+                print(f"   Wins: {wins} | Losses: {losses}")
+                print(f"   Win Rate: {win_rate:.1f}%")
+                print(f"   Total P&L: ${total_pnl:.2f}")
+                print(f"   Avg P&L: ${avg_pnl:.2f}")
+
+        # 4. RANGING VS TRENDING
+        print("\n🔍 REGIME BREAKDOWN (Last 20 trades):")
+        cursor.execute("""
+            SELECT
+                regime,
+                COUNT(*) as count,
+                SUM(CASE WHEN net_profit > 0 THEN 1 ELSE 0 END) as wins,
+                SUM(net_profit) as pnl
+            FROM trades
+            WHERE status = 'closed'
+            ORDER BY exit_time DESC
+            LIMIT 20
+        """)
+
+        cursor.execute("""
+            SELECT
+                regime,
+                COUNT(*) as count,
+                SUM(CASE WHEN net_profit > 0 THEN 1 ELSE 0 END) as wins,
+                SUM(net_profit) as pnl
+            FROM (
+                SELECT * FROM trades
+                WHERE status = 'closed'
+                ORDER BY exit_time DESC
+                LIMIT 20
+            )
+            GROUP BY regime
+        """)
+
+        for row in cursor.fetchall():
+            regime, count, wins, pnl = row
+            win_rate = (wins / count * 100) if count > 0 else 0
+            print(f"   {regime or 'unknown'}: {count} trades, {win_rate:.1f}% WR, ${pnl:.2f}")
+
+        # 5. TODAY'S ACTIVITY
+        print("\n📅 TODAY'S TRADES:")
+        today = datetime.now().date()
+        cursor.execute("""
+            SELECT COUNT(*), SUM(net_profit)
+            FROM trades
+            WHERE status = 'closed'
+            AND DATE(exit_time) = ?
+        """, (today.isoformat(),))
+
+        row = cursor.fetchone()
+        if row and row[0] > 0:
+            print(f"   Trades: {row[0]}")
+            print(f"   P&L: ${row[1]:.2f}")
+        else:
+            print("   No trades today")
+
+        # 6. OPEN POSITIONS
+        print("\n🔓 OPEN POSITIONS:")
+        cursor.execute("""
+            SELECT ticket, entry_time, entry_price, profit
+            FROM trades
+            WHERE status = 'open'
+        """)
+
+        open_pos = cursor.fetchall()
+        if open_pos:
+            for row in open_pos:
+                print(f"   #{row[0]}: Entry ${row[2]:.2f}, Unrealized P&L: ${row[3]:.2f}")
+        else:
+            print("   No open positions")
+
+        # 7. FINAL VERDICT
+        print("\n" + "=" * 70)
+        if consecutive < 5:
+            print("✅ SYSTEM STATUS: READY TO TRADE")
+            print("=" * 70)
+            print("\n🛡️ ACTIVE PROTECTIONS:")
+            print("   🛑 Ranging Filter - blocks ADX < 25")
+            print("   💾 Exit Logging - all exits tracked")
+            print("   📊 Drawdown Protection - monitoring")
+            print("\n💡 NEXT EXPECTED ACTION:")
+            print("   Waiting for trending market signal (ADX > 25)")
+            print("   Session Filter active (NY + Asian sessions only)")
+        else:
+            print("🚨 SYSTEM STATUS: TRADING PAUSED")
+            print("=" * 70)
+            print(f"\n⚠️ Reason: {consecutive} consecutive losses (limit: 5)")
+            print("\n💡 TO RESUME:")
+            print("   1. Wait for cooldown (24h)")
+            print("   2. OR: Run reset_consecutive_losses.py")
+            print("   3. Restart Jupyter Kernel")
+
+    except Exception as e:
+        print(f"\n❌ ERROR: {e}")
+        import traceback
+        traceback.print_exc()
+
+    finally:
+        conn.close()
+
+if __name__ == "__main__":
+    check_status()