import asyncio
import logging
import os
import sys
import time
from datetime import datetime, timedelta
from decimal import Decimal
from typing import List, Dict, Any, Optional

# Add project root and backend to path
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), 'backend'))

from backend.database.connection import db
from backend.database.models import Trade, Account
from backend.config_manager import ConfigManager
from trading_system.binance_client import BinanceClient
from binance import AsyncClient

# Configure logging
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger(__name__)

async def get_fills_with_retry(client, symbol, start_time_ms, retries=3):
    """Fetch fills with retry logic"""
    for i in range(retries):
        try:
            return await client.client.futures_account_trades(
                symbol=symbol,
                startTime=start_time_ms,
                limit=100
            )
        except Exception as e:
            if i == retries - 1:
                raise e
            logger.warning(f"Error fetching fills for {symbol} (Attempt {i+1}/{retries}): {e}. Retrying...")
            await asyncio.sleep(2)

async def fix_time_inversion_trades(client, account_id):
    """Fix trades where exit_time < entry_time"""
    logger.info("Scanning for time-inverted trades...")
    
    # Query invalid trades
    sql = """
        SELECT * FROM trades 
        WHERE status = 'closed' 
        AND exit_time < entry_time 
        AND account_id = %s
    """
    trades = db.execute_query(sql, (account_id,))
    
    if not trades:
        logger.info("No time-inverted trades found.")
        return
    
    for trade in trades:
        symbol = trade['symbol']
        trade_id = trade['id']
        entry_time = trade['entry_time']
        exit_time = trade['exit_time']
        side = trade['side']  # OPEN side (BUY/SELL)
        
        logger.info(f"Found invalid trade #{trade_id} {symbol}: Entry={entry_time}, Exit={exit_time} (Diff: {exit_time - entry_time}s)")
        
        # 1. Check actual position on Binance
        # Convert entry_time to ms for Binance API
        start_time_ms = int(entry_time * 1000)
        
        try:
            # Fetch user trades (fills) after entry time with retry
            fills = await get_fills_with_retry(client, symbol, start_time_ms)
            
            # Filter for closing trades
            # If entry side was BUY, we look for SELL. If SELL, look for BUY.
            close_side = 'SELL' if side == 'BUY' else 'BUY'
            
            closing_fills = [f for f in fills if f['side'] == close_side and float(f['realizedPnl']) != 0]
            
            if not closing_fills:
                # No closing trades found. Position might still be open or we missed it?
                # Check current position risk
                positions = await client.get_open_positions()
                current_pos = next((p for p in positions if p['symbol'] == symbol), None)
                
                if current_pos and float(current_pos['positionAmt']) != 0:
                    logger.info(f"  -> Position for {symbol} is actually OPEN on Binance. Reverting status.")
                    # Revert to open
                    db.execute_update(
                        "UPDATE trades SET status='open', exit_time=NULL, exit_price=NULL, pnl=NULL, pnl_percent=NULL, exit_reason=NULL WHERE id=%s",
                        (trade_id,)
                    )
                else:
                    logger.warning(f"  -> Position closed on Binance but no closing fills found after entry time. Maybe closed exactly at entry or data issue?")
            else:
                # Found closing fills. Calculate metrics.
                # We assume the latest fills correspond to this trade. 
                
                # Sort by time desc
                closing_fills.sort(key=lambda x: x['time'], reverse=True)
                
                last_fill = closing_fills[0]
                actual_exit_time_ms = last_fill['time']
                actual_exit_time_s = int(actual_exit_time_ms / 1000)
                
                total_pnl = sum(float(f['realizedPnl']) for f in closing_fills)
                total_commission = sum(float(f['commission']) for f in closing_fills)
                commission_asset = closing_fills[0]['commissionAsset']
                
                # Calculate avg exit price
                total_qty = sum(float(f['qty']) for f in closing_fills)
                total_value = sum(float(f['qty']) * float(f['price']) for f in closing_fills)
                avg_exit_price = total_value / total_qty if total_qty > 0 else 0
                
                entry_price = float(trade['entry_price'])
                pnl_percent = 0
                if entry_price > 0:
                    if side == 'BUY':
                        pnl_percent = ((avg_exit_price - entry_price) / entry_price) * 100
                    else:
                        pnl_percent = ((entry_price - avg_exit_price) / entry_price) * 100

                logger.info(f"  -> Found closing fills. Updating Trade #{trade_id}:")
                logger.info(f"     New Exit Time: {actual_exit_time_s} (was {exit_time})")
                logger.info(f"     Realized PnL: {total_pnl}")
                logger.info(f"     Commission: {total_commission} {commission_asset}")
                
                # Update DB
                Trade.update_exit(
                    trade_id=trade_id,
                    exit_price=avg_exit_price,
                    exit_reason='sync_fix',
                    pnl=total_pnl,  # Use realized PnL as PnL
                    pnl_percent=pnl_percent,
                    exit_time_ts=actual_exit_time_s,
                    realized_pnl=total_pnl,
                    commission=total_commission,
                    commission_asset=commission_asset
                )
                
        except Exception as e:
            logger.error(f"Error processing trade #{trade_id}: {e}")

async def backfill_commissions(client, account_id):
    """Backfill missing commission data for recent trades"""
    logger.info("Backfilling commissions for recent trades...")
    
    # Get recent closed trades (last 24h)
    start_time = int((datetime.now() - timedelta(hours=24)).timestamp())
    
    sql = """
        SELECT * FROM trades 
        WHERE status = 'closed' 
        AND account_id = %s
        AND exit_time > %s
        AND (commission IS NULL OR commission = 0)
    """
    trades = db.execute_query(sql, (account_id, start_time))
    
    if not trades:
        logger.info("No recent trades with missing commissions found.")
        return

    logger.info(f"Found {len(trades)} trades to update commissions.")
    
    for trade in trades:
        symbol = trade['symbol']
        trade_id = trade['id']
        entry_time = trade['entry_time']
        
        try:
            # Fetch user trades (fills) after entry time
            start_time_ms = int(entry_time * 1000)
            
            # Add retry logic for get_my_trades
            max_retries = 3
            fills = None
            for attempt in range(max_retries):
                try:
                    # Use asyncio.wait_for to enforce timeout
                    fills = await asyncio.wait_for(
                        client.client.futures_account_trades(
                            symbol=symbol,
                            startTime=start_time_ms,
                            limit=100
                        ),
                        timeout=10.0
                    )
                    break
                except Exception as e:
                    if attempt == max_retries - 1:
                        logger.error(f"    ❌ Failed to fetch fills for {symbol} after {max_retries} attempts: {e}")
                        break
                    logger.warning(f"    ⚠️ Error fetching fills for {symbol} (Attempt {attempt+1}/{max_retries}): {e}, retrying...")
                    await asyncio.sleep(2)
            
            if not fills:
                continue
                
            # Filter for closing trades (approximate logic: matches trade direction)
            # Actually we want ALL commissions for this round trip (Open + Close)
            # But simpler to just get closing commissions for now as per `update_exit`
            
            # Simple approach: Sum all commissions for this symbol after entry time
            # This might over-count if there are multiple trades, but better than 0.
            
            # Better approach: match exit order ID if available
            exit_order_id = trade.get('exit_order_id')
            
            related_fills = []
            if exit_order_id:
                related_fills = [f for f in fills if str(f['orderId']) == str(exit_order_id)]
            else:
                # Fallback: fills around exit time
                exit_time = trade['exit_time']
                if exit_time:
                    exit_time_ms = exit_time * 1000
                    related_fills = [f for f in fills if abs(f['time'] - exit_time_ms) < 5000] # 5s window
            
            if related_fills:
                total_commission = sum(float(f['commission']) for f in related_fills)
                commission_asset = related_fills[0]['commissionAsset']
                realized_pnl = sum(float(f['realizedPnl']) for f in related_fills)
                
                logger.info(f"Updating Trade #{trade_id} {symbol}: Comm={total_commission} {commission_asset}, PnL={realized_pnl}")
                
                db.execute_update(
                    "UPDATE trades SET commission=%s, commission_asset=%s, realized_pnl=%s WHERE id=%s",
                    (total_commission, commission_asset, realized_pnl, trade_id)
                )
                
        except Exception as e:
            logger.error(f"Error backfilling trade #{trade_id}: {e}")

async def main():
    try:
        # Get all active accounts
        accounts = Account.list_all()
        active_accounts = [a for a in accounts if a['status'] == 'active' and a['api_key_enc']]
        
        if not active_accounts:
            logger.error("No active accounts with API keys found.")
            return

        for account in active_accounts:
            account_id = account['id']
            account_name = account['name']
            logger.info(f"=== Processing Account: {account_name} (ID: {account_id}) ===")
            
            # Get credentials
            api_key, api_secret, testnet, _ = Account.get_credentials(account_id)
            
            if not api_key or not api_secret:
                logger.warning(f"Skipping account {account_id} due to missing keys.")
                continue
                
            # Init client
            client = BinanceClient(api_key, api_secret, testnet=testnet)
            # Initialize connection
            if not client.client:
                client.client = AsyncClient(api_key, api_secret, testnet=testnet)
            
            try:
                await fix_time_inversion_trades(client, account_id)
                await backfill_commissions(client, account_id)
            finally:
                # Close connection properly
                if client.client:
                    await client.client.close_connection()
            
        logger.info("All accounts processed.")
        
    except Exception as e:
        logger.error(f"Script failed: {e}")

if __name__ == "__main__":
    loop = asyncio.get_event_loop()
    loop.run_until_complete(main())