#!/usr/bin/env python3
"""
Integration Script: Add P&L Tracking to Notebook
Adds 6 new cells for comprehensive P&L tracking and dashboard
"""

import nbformat
from pathlib import Path
import sys

def integrate_pnl_tracker(notebook_path):
    """Add P&L tracking cells to notebook"""

    # Read notebook
    with open(notebook_path, 'r', encoding='utf-8') as f:
        nb = nbformat.read(f, as_version=4)

    print(f"📖 Loaded notebook: {Path(notebook_path).name}")
    print(f"   Current cells: {len(nb.cells)}")

    # Define new cells
    new_cells = []

    # ==========================================
    # Cell 1: Section Header (Markdown)
    # ==========================================
    new_cells.append(nbformat.v4.new_markdown_cell("""# 💰 P&L TRACKING & PERFORMANCE ANALYTICS (V1.9)

**Automatic MT5 History Import & Real-Time P&L Dashboard**

Features:
- 📥 **Automatic MT5 History Import** - Syncs closed trades from MT5
- 💰 **Real P&L Calculation** - Matches Entry+Exit deals for accurate P&L
- 📊 **Win Rate Analysis** - Real Win Rate from closed MT5 trades
- 📈 **Performance Metrics** - Profit Factor, Max Drawdown, Avg Win/Loss
- 🎯 **Session Analysis** - Compare Asian vs NY performance
- 📅 **Time-based Reports** - Today, Week, Month, All-Time
- 🔄 **Automatic Sync** - Scheduled hourly updates

**Status:** ✅ READY TO USE
"""))

    # ==========================================
    # Cell 2: Setup P&L Tracker (Code)
    # ==========================================
    new_cells.append(nbformat.v4.new_code_cell("""# ==========================================
# SETUP P&L TRACKER
# ==========================================

from mt5_pnl_tracker import MT5PnLTracker, scheduled_pnl_sync

print("=" * 80)
print("🚀 INITIALIZING P&L TRACKER...")
print("=" * 80)

# Initialize tracker
pnl_tracker = MT5PnLTracker(
    db_path="trading_bot.db",
    magic_number=None  # None = all trades, or specify your EA magic number
)

# Connect to database
pnl_tracker.connect_db()

print("\\n✅ P&L Tracker initialized successfully!")
print("   Database: trading_bot.db")
print("   Tables: mt5_deals, matched_positions, pnl_summary")
print("=" * 80)
"""))

    # ==========================================
    # Cell 3: Initial Sync (Code)
    # ==========================================
    new_cells.append(nbformat.v4.new_code_cell("""# ==========================================
# INITIAL SYNC: IMPORT MT5 HISTORY
# ==========================================

print("\\n📥 Importing MT5 history...")
print("   This will import last 30 days of trades from MT5")
print("   Please wait...\\n")

# Perform initial sync
sync_results = pnl_tracker.sync_and_update(days_back=30)

if sync_results['success']:
    summary = sync_results['summary']

    print("=" * 80)
    print("✅ SYNC SUCCESSFUL!")
    print("=" * 80)
    print(f"\\n📥 Import Results:")
    print(f"   New Deals:          {summary['new_deals']}")
    print(f"   Matched Positions:  {summary['matched_positions']}")
    print(f"\\n📊 Current Performance:")
    print(f"   Total Trades:       {summary['total_trades']}")
    print(f"   Win Rate:           {summary['win_rate']:.1f}%")
    print(f"   Net P&L:            ${summary['net_profit']:.2f}")
    print("=" * 80)

    if summary['new_deals'] == 0:
        print("\\n💡 No new deals found. This means:")
        print("   • History already imported, OR")
        print("   • No trades in last 30 days")
else:
    print("=" * 80)
    print("❌ SYNC FAILED")
    print("=" * 80)
    print(f"Error: {sync_results.get('error', 'Unknown error')}")
    print("\\n💡 Troubleshooting:")
    print("   • Check MT5 is running")
    print("   • Verify MT5 connection")
    print("   • Check trading history exists")
"""))

    # ==========================================
    # Cell 4: Add to Scheduler (Code)
    # ==========================================
    new_cells.append(nbformat.v4.new_code_cell("""# ==========================================
# ADD P&L SYNC TO SCHEDULER
# ==========================================

from apscheduler.triggers.interval import IntervalTrigger

print("\\n🔄 Adding P&L sync to scheduler...")

# Remove old job if exists
try:
    scheduler.remove_job('pnl_sync')
    print("   Removed old P&L sync job")
except:
    pass

# Add hourly P&L sync
scheduler.add_job(
    scheduled_pnl_sync,
    trigger=IntervalTrigger(hours=1),
    args=[pnl_tracker, 7],  # Sync last 7 days
    id='pnl_sync',
    name='P&L Sync',
    replace_existing=True,
    max_instances=1
)

print("✅ P&L sync scheduled (every 1 hour)")
print("   Syncs last 7 days from MT5")

# Show all scheduler jobs
print("\\n📋 Active Scheduler Jobs:")
for job in scheduler.get_jobs():
    print(f"   • {job.id}: {job.trigger}")

print("\\n✅ Scheduler updated successfully!")
print("=" * 80)
"""))

    # ==========================================
    # Cell 5: Markdown - Usage Instructions
    # ==========================================
    new_cells.append(nbformat.v4.new_markdown_cell("""## 📖 How to Use P&L Tracker

### 📊 View Dashboard
Run the dashboard cell to see:
- All-time performance
- Monthly performance
- Weekly performance
- Today's performance

### 📜 View Recent Trades
See last 10 closed trades with:
- Entry/Exit prices
- P&L per trade
- Duration
- Win/Loss status

### 🔄 Manual Sync
If you want to manually sync MT5 history:
```python
sync_results = pnl_tracker.sync_and_update(days_back=30)
print(sync_results)
```

### 📊 Get Specific Period Metrics
```python
# Get metrics for specific period
all_time = pnl_tracker.calculate_pnl_metrics('all')
month = pnl_tracker.calculate_pnl_metrics('month')
week = pnl_tracker.calculate_pnl_metrics('week')
today = pnl_tracker.calculate_pnl_metrics('today')
```

### 🎯 Integration with Dynamic Thresholds
The P&L tracker data can be used by the Dynamic Threshold Optimizer to better calibrate optimal confidence thresholds based on real MT5 performance!
"""))

    # ==========================================
    # Cell 6: Dashboard Display (Code)
    # ==========================================
    new_cells.append(nbformat.v4.new_code_cell("""# ==========================================
# 💰 P&L PERFORMANCE DASHBOARD
# ==========================================

# Generate and display dashboard
dashboard = pnl_tracker.generate_dashboard()
print(dashboard)

# Show recent trades
print("\\n" + "=" * 80)
print("📜 RECENT TRADES (Last 10)")
print("=" * 80)

recent_trades = pnl_tracker.get_recent_trades(limit=10)

if not recent_trades.empty:
    # Format for display
    recent_trades['entry_time'] = pd.to_datetime(recent_trades['entry_time']).dt.strftime('%Y-%m-%d %H:%M')
    recent_trades['exit_time'] = pd.to_datetime(recent_trades['exit_time']).dt.strftime('%Y-%m-%d %H:%M')
    recent_trades['net_profit'] = recent_trades['net_profit'].round(2)
    recent_trades['pips'] = recent_trades['pips'].round(1)
    recent_trades['duration_hours'] = recent_trades['duration_hours'].round(1)
    recent_trades['status'] = recent_trades['is_win'].apply(lambda x: '✅ WIN' if x else '❌ LOSS')

    # Select columns to display
    display_cols = ['position_id', 'symbol', 'type', 'entry_time', 'exit_time',
                    'net_profit', 'pips', 'duration_hours', 'status']

    print("\\n" + recent_trades[display_cols].to_string(index=False))
else:
    print("\\n❌ No recent trades found")

print("\\n" + "=" * 80)
print("✅ Dashboard refresh complete!")
print(f"Last updated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
print("=" * 80)
"""))

    # ==========================================
    # Add cells to notebook
    # ==========================================

    # Find position to insert (after last cell)
    insert_position = len(nb.cells)

    print(f"\n📝 Adding {len(new_cells)} new cells at position {insert_position}...")

    for i, cell in enumerate(new_cells, start=insert_position):
        nb.cells.insert(i, cell)
        cell_type = "Markdown" if cell.cell_type == "markdown" else "Code"
        print(f"   ✅ Cell {i}: {cell_type}")

    # Save notebook
    with open(notebook_path, 'w', encoding='utf-8') as f:
        nbformat.write(nb, f)

    print(f"\n✅ Integration complete!")
    print(f"   Total cells now: {len(nb.cells)}")
    print(f"   New cells: {insert_position} - {len(nb.cells)-1}")

    return {
        'success': True,
        'notebook': notebook_path,
        'cells_added': len(new_cells),
        'total_cells': len(nb.cells),
        'new_cell_range': f"{insert_position}-{len(nb.cells)-1}"
    }


if __name__ == "__main__":
    notebook_path = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb"

    if not Path(notebook_path).exists():
        print(f"❌ Error: Notebook not found: {notebook_path}")
        sys.exit(1)

    print("=" * 80)
    print("🚀 P&L TRACKER INTEGRATION")
    print("=" * 80)
    print(f"\nNotebook: {notebook_path}")
    print("Adding: 6 new cells for P&L tracking")

    result = integrate_pnl_tracker(notebook_path)

    if result['success']:
        print("\n" + "=" * 80)
        print("🎉 SUCCESS!")
        print("=" * 80)
        print(f"\n✅ Added {result['cells_added']} cells to notebook")
        print(f"   Total cells: {result['total_cells']}")
        print(f"   New cells: {result['new_cell_range']}")

        print("\n📋 Next Steps:")
        print("   1. Open Jupyter Notebook")
        print("   2. Restart Kernel (Kernel → Restart & Clear Output)")
        print("   3. Run All Cells (Cell → Run All)")
        print("   4. Verify P&L sync in new cells")
        print("   5. Check dashboard display")

        print("\n💡 The P&L tracker will now:")
        print("   • Automatically sync MT5 history every hour")
        print("   • Calculate real Win Rate from closed trades")
        print("   • Track profit/loss accurately")
        print("   • Generate performance reports")

        print("\n" + "=" * 80)
    else:
        print(f"\n❌ Integration failed!")
        sys.exit(1)