# source: https://raw.githubusercontent.com/djienne/COPY_WALLET_HYPERLIQUID/6de8fdffeddf981359ea963fa30505c3bda2745a/user_data/strategies/COPY_HL_LS.py
import pandas as pd
from freqtrade.strategy import (IStrategy, IntParameter)
from freqtrade.persistence import Trade
import logging
import os
import json
import time
from pathlib import Path
import json
import os
import csv
from datetime import datetime, timedelta
from typing import Dict, List, Optional, Any
from dataclasses import dataclass, asdict
from copy import deepcopy

logger = logging.getLogger(__name__)

ADDRESS_TO_TRACK_TOP = "0x4b66f4048a0a90fd5ff44abbe5d68332656b78b8"
# also 0x95b8b411653328db32f59b143c6d45f8501e2b35 is pretty good

#####################################################################################################################################################################################################
# Classes used to manage the copied wallet position tracking
#####################################################################################################################################################################################################

@dataclass
class PositionSnapshot:
    coin: str
    size: float
    entry_price: float
    position_value: float
    unrealized_pnl: float
    leverage: float
    margin_used: float
    timestamp: int
    
@dataclass
class PositionChange:
    coin: str
    change_type: str
    old_size: Optional[float]
    new_size: float
    old_position_value: Optional[float]
    new_position_value: float
    timestamp: int
    human_time: str

class PositionTracker:
    def __init__(self, data_dir: str = "position_data"):
        self.data_dir = data_dir
        self.positions_file = os.path.join(data_dir, "positions_history.csv")
        self.changes_file = os.path.join(data_dir, "changes_log.csv")
        self.last_positions_file = os.path.join(data_dir, "last_positions.csv")
        
        self.position_history: Dict[str, List[PositionSnapshot]] = {}
        self.last_positions: Dict[str, PositionSnapshot] = {}
        self.changes_log: List[PositionChange] = []
        
        # Create data directory if it doesn't exist
        os.makedirs(data_dir, exist_ok=True)
        
        # Load existing data if available
        self._load_data()
        
    def _save_positions_history(self) -> None:
        """Save position history to CSV"""
        try:
            with open(self.positions_file, 'w', newline='', encoding='utf-8') as f:
                writer = csv.writer(f)
                writer.writerow([
                    'coin', 'size', 'entry_price', 'position_value', 
                    'unrealized_pnl', 'leverage', 'margin_used', 'timestamp', 'human_time'
                ])
                
                for coin, positions in self.position_history.items():
                    for pos in positions:
                        writer.writerow([
                            pos.coin, pos.size, pos.entry_price, pos.position_value,
                            pos.unrealized_pnl, pos.leverage, pos.margin_used, 
                            pos.timestamp, self._timestamp_to_human(pos.timestamp)
                        ])
        except Exception as e:
            logger.info(f"Warning: Failed to save positions history: {e}")
    
    def _save_last_positions(self) -> None:
        """Save last positions to CSV"""
        try:
            with open(self.last_positions_file, 'w', newline='', encoding='utf-8') as f:
                writer = csv.writer(f)
                writer.writerow([
                    'coin', 'size', 'entry_price', 'position_value', 
                    'unrealized_pnl', 'leverage', 'margin_used', 'timestamp', 'human_time'
                ])
                
                for pos in self.last_positions.values():
                    writer.writerow([
                        pos.coin, pos.size, pos.entry_price, pos.position_value,
                        pos.unrealized_pnl, pos.leverage, pos.margin_used, 
                        pos.timestamp, self._timestamp_to_human(pos.timestamp)
                    ])
        except Exception as e:
            logger.info(f"Warning: Failed to save last positions: {e}")
    
    def _save_changes_log(self) -> None:
        """Save changes log to CSV"""
        try:
            with open(self.changes_file, 'w', newline='', encoding='utf-8') as f:
                writer = csv.writer(f)
                writer.writerow([
                    'coin', 'change_type', 'old_size', 'new_size', 
                    'old_position_value', 'new_position_value', 'timestamp', 'human_time'
                ])
                
                for change in self.changes_log:
                    writer.writerow([
                        change.coin, change.change_type, change.old_size or '', change.new_size,
                        change.old_position_value or '', change.new_position_value, 
                        change.timestamp, change.human_time
                    ])
        except Exception as e:
            logger.info(f"Warning: Failed to save changes log: {e}")
    
    def _save_data(self) -> None:
        """Save all tracking data to CSV files"""
        self._save_positions_history()
        self._save_last_positions()
        self._save_changes_log()
    
    def _load_positions_history(self) -> None:
        """Load position history from CSV"""
        if not os.path.exists(self.positions_file):
            return
            
        try:
            with open(self.positions_file, 'r', newline='', encoding='utf-8') as f:
                reader = csv.DictReader(f)
                self.position_history = {}
                
                for row in reader:
                    coin = row['coin']
                    if coin not in self.position_history:
                        self.position_history[coin] = []
                    
                    pos = PositionSnapshot(
                        coin=coin,
                        size=float(row['size']),
                        entry_price=float(row['entry_price']),
                        position_value=float(row['position_value']),
                        unrealized_pnl=float(row['unrealized_pnl']),
                        leverage=float(row['leverage']),
                        margin_used=float(row['margin_used']),
                        timestamp=int(row['timestamp'])
                    )
                    self.position_history[coin].append(pos)
                    
        except Exception as e:
            logger.info(f"Warning: Failed to load position history: {e}")
    
    def _load_last_positions(self) -> None:
        """Load last positions from CSV"""
        if not os.path.exists(self.last_positions_file):
            return
            
        try:
            with open(self.last_positions_file, 'r', newline='', encoding='utf-8') as f:
                reader = csv.DictReader(f)
                self.last_positions = {}
                
                for row in reader:
                    coin = row['coin']
                    pos = PositionSnapshot(
                        coin=coin,
                        size=float(row['size']),
                        entry_price=float(row['entry_price']),
                        position_value=float(row['position_value']),
                        unrealized_pnl=float(row['unrealized_pnl']),
                        leverage=float(row['leverage']),
                        margin_used=float(row['margin_used']),
                        timestamp=int(row['timestamp'])
                    )
                    self.last_positions[coin] = pos
                    
        except Exception as e:
            logger.info(f"Warning: Failed to load last positions: {e}")
    
    def _load_changes_log(self) -> None:
        """Load changes log from CSV"""
        if not os.path.exists(self.changes_file):
            return
            
        try:
            with open(self.changes_file, 'r', newline='', encoding='utf-8') as f:
                reader = csv.DictReader(f)
                self.changes_log = []
                
                for row in reader:
                    old_size = float(row['old_size']) if row['old_size'] else None
                    old_pos_value = float(row['old_position_value']) if row['old_position_value'] else None
                    
                    change = PositionChange(
                        coin=row['coin'],
                        change_type=row['change_type'],
                        old_size=old_size,
                        new_size=float(row['new_size']),
                        old_position_value=old_pos_value,
                        new_position_value=float(row['new_position_value']),
                        timestamp=int(row['timestamp']),
                        human_time=row['human_time']
                    )
                    self.changes_log.append(change)
                    
        except Exception as e:
            logger.info(f"Warning: Failed to load changes log: {e}")
    
    def _load_data(self) -> None:
        """Load all tracking data from CSV files"""
        self._load_positions_history()
        self._load_last_positions()
        self._load_changes_log()
        
        if self.last_positions or self.changes_log:
            logger.info(f"Loaded tracking data: {len(self.last_positions)} current positions, "
                  f"{len(self.changes_log)} historical changes from {self.data_dir}/")
        else:
            logger.info(f"No existing data found. Starting with fresh tracking data in {self.data_dir}/")
    
    def export_to_json(self, filename: str = None) -> str:
        """Export tracking data to JSON format for easy viewing"""
        if filename is None:
            filename = os.path.join(self.data_dir, f"export_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json")
        
        # Convert dataclasses to dictionaries for JSON serialization
        export_data = {
            'position_history': {
                coin: [asdict(pos) for pos in positions] 
                for coin, positions in self.position_history.items()
            },
            'last_positions': {
                coin: asdict(pos) for coin, pos in self.last_positions.items()
            },
            'changes_log': [asdict(change) for change in self.changes_log],
            'export_timestamp': datetime.now().isoformat(),
            'total_tracked_coins': len(self.position_history),
            'total_changes': len(self.changes_log)
        }
        
        try:
            with open(filename, 'w') as f:
                json.dump(export_data, f, indent=2, default=str)
            logger.info(f"Data exported to {filename}")
            return filename
        except Exception as e:
            logger.info(f"Failed to export data: {e}")
            return ""
        
    def _timestamp_to_human(self, timestamp: int) -> str:
        """Convert timestamp to human readable format"""
        return datetime.fromtimestamp(timestamp / 1000).strftime('%Y-%m-%d %H:%M:%S')
    
    def _extract_positions(self, data: Dict[str, Any]) -> Dict[str, PositionSnapshot]:
        """Extract position data from the JSON response"""
        positions = {}
        timestamp = data.get('time', 0)
        
        for asset_pos in data.get('assetPositions', []):
            if asset_pos['type'] == 'oneWay' and 'position' in asset_pos:
                pos = asset_pos['position']
                coin = pos['coin']
                
                # Convert size to float, handle both string and numeric values
                size = float(pos['szi'])
                
                # Skip positions with zero size
                if size == 0:
                    continue
                    
                leverage_value = pos['leverage']['value'] if isinstance(pos['leverage'], dict) else pos['leverage']
                
                snapshot = PositionSnapshot(
                    coin=coin,
                    size=size,
                    entry_price=float(pos['entryPx']),
                    position_value=float(pos['positionValue']),
                    unrealized_pnl=float(pos['unrealizedPnl']),
                    leverage=float(leverage_value),
                    margin_used=float(pos['marginUsed']),
                    timestamp=timestamp
                )
                
                positions[coin] = snapshot
                
        return positions
    
    def _detect_changes(self, current_positions: Dict[str, PositionSnapshot]) -> List[PositionChange]:
        """Detect changes between current and last positions"""
        changes = []
        timestamp = list(current_positions.values())[0].timestamp if current_positions else int(datetime.now().timestamp() * 1000)
        human_time = self._timestamp_to_human(timestamp)
        
        # Check for closed positions
        for coin in self.last_positions:
            if coin not in current_positions:
                old_pos = self.last_positions[coin]
                change = PositionChange(
                    coin=coin,
                    change_type='closed',
                    old_size=old_pos.size,
                    new_size=0.0,
                    old_position_value=old_pos.position_value,
                    new_position_value=0.0,
                    timestamp=timestamp,
                    human_time=human_time
                )
                changes.append(change)
        
        # Check for new, modified, increased, or decreased positions
        for coin, current_pos in current_positions.items():
            if coin not in self.last_positions:
                # New position opened
                position_type = "long" if current_pos.size > 0 else "short"
                change = PositionChange(
                    coin=coin,
                    change_type=f'opened_{position_type}',
                    old_size=None,
                    new_size=current_pos.size,
                    old_position_value=None,
                    new_position_value=current_pos.position_value,
                    timestamp=timestamp,
                    human_time=human_time
                )
                changes.append(change)
            else:
                old_pos = self.last_positions[coin]
                
                # Check for size changes (significant changes only)
                if abs(current_pos.size - old_pos.size) > 1e-8:
                    change_type = self._determine_change_type(old_pos.size, current_pos.size)
                    
                    change = PositionChange(
                        coin=coin,
                        change_type=change_type,
                        old_size=old_pos.size,
                        new_size=current_pos.size,
                        old_position_value=old_pos.position_value,
                        new_position_value=current_pos.position_value,
                        timestamp=timestamp,
                        human_time=human_time
                    )
                    changes.append(change)
                
                # Check for significant modifications (leverage, entry price changes)
                elif (abs(current_pos.leverage - old_pos.leverage) > 1e-8 or 
                      abs(current_pos.entry_price - old_pos.entry_price) > 1e-6):  # Higher threshold for entry price
                    change = PositionChange(
                        coin=coin,
                        change_type='modified',
                        old_size=old_pos.size,
                        new_size=current_pos.size,
                        old_position_value=old_pos.position_value,
                        new_position_value=current_pos.position_value,
                        timestamp=timestamp,
                        human_time=human_time
                    )
                    changes.append(change)
                
                # Ignore pure P&L changes (position_value, unrealized_pnl, margin_used changes 
                # without size/leverage/entry_price changes are just market movements)
        
        return changes
    
    def _determine_change_type(self, old_size: float, new_size: float) -> str:
        """Determine the type of change considering long/short positions"""
        # Check for direction flip (long to short or short to long)
        if (old_size > 0 and new_size < 0) or (old_size < 0 and new_size > 0):
            return 'flipped'
        
        # Same direction changes
        if old_size > 0 and new_size > 0:  # Both long
            return 'increased' if new_size > old_size else 'decreased'
        elif old_size < 0 and new_size < 0:  # Both short
            # For shorts: more negative = larger short position
            return 'increased' if abs(new_size) > abs(old_size) else 'decreased'
        
        return 'modified'
    
    def track_positions(self, position_data: Dict[str, Any]) -> List[PositionChange]:
        """
        Main function to track positions and detect changes
        
        Args:
            position_data: JSON data containing position information
            
        Returns:
            List of detected changes
        """
        # Extract current positions
        current_positions = self._extract_positions(position_data)
        
        # Detect changes
        changes = self._detect_changes(current_positions)
        
        # Only update history if there are actual position changes (not just P&L updates)
        if changes:
            timestamp = position_data.get('time', int(datetime.now().timestamp() * 1000))
            for coin, position in current_positions.items():
                if coin not in self.position_history:
                    self.position_history[coin] = []
                
                # Only add to history if this represents a significant change
                # (new position, size change, leverage change, etc.)
                should_add_to_history = any(
                    change.coin == coin and change.change_type in [
                        'opened_long', 'opened_short', 'closed', 'increased', 
                        'decreased', 'flipped', 'modified'
                    ] for change in changes
                )
                
                if should_add_to_history:
                    self.position_history[coin].append(position)
        
        # Always log changes (even if empty for completeness)
        self.changes_log.extend(changes)
        
        # Always update last positions (for tracking future changes)
        self.last_positions = deepcopy(current_positions)
        
        # Save data to file after each update (but only if there were changes)
        if changes:
            self._save_data()
        else:
            # Still need to save last_positions for change detection, but not full history
            self._save_last_positions()
        
        return changes
    
    def print_changes(self, changes: List[PositionChange]) -> None:
        """Print detected changes in a readable format"""
        if not changes:
            logger.info("No position changes detected.")
            return
            
        logger.info(f"\n=== Position Changes Detected ({len(changes)} changes) ===")
        for change in changes:
            position_info = self._get_position_info(change.new_size if change.new_size != 0 else change.old_size)
            
            logger.info(f"\n[{change.human_time}] {change.coin} - {change.change_type.upper()}")
            
            if change.change_type.startswith('opened'):
                direction = "LONG" if change.new_size > 0 else "SHORT"
                logger.info(f"  New {direction} position: {abs(change.new_size):,.4f} (${change.new_position_value:,.2f})")
            elif change.change_type == 'closed':
                old_direction = "LONG" if change.old_size > 0 else "SHORT"
                logger.info(f"  Closed {old_direction} position: {abs(change.old_size):,.4f} (was ${change.old_position_value:,.2f})")
            elif change.change_type == 'flipped':
                old_direction = "LONG" if change.old_size > 0 else "SHORT"
                new_direction = "LONG" if change.new_size > 0 else "SHORT"
                logger.info(f"  Position flipped from {old_direction} to {new_direction}")
                logger.info(f"  Size: {change.old_size:,.4f} → {change.new_size:,.4f}")
                logger.info(f"  Value: ${change.old_position_value:,.2f} → ${change.new_position_value:,.2f}")
            elif change.change_type in ['increased', 'decreased']:
                direction = "LONG" if change.new_size > 0 else "SHORT"
                size_diff = change.new_size - change.old_size
                value_diff = change.new_position_value - change.old_position_value
                
                # For display purposes, show absolute values but indicate direction
                logger.info(f"  {direction} position {change.change_type}")
                logger.info(f"  Size: {change.old_size:,.4f} → {change.new_size:,.4f} ({size_diff:+,.4f})")
                logger.info(f"  Value: ${change.old_position_value:,.2f} → ${change.new_position_value:,.2f} ({value_diff:+,.2f})")
            elif change.change_type == 'modified':
                direction = "LONG" if change.new_size > 0 else "SHORT"
                logger.info(f"  {direction} position modified (same size: {change.new_size:,.4f})")
                logger.info(f"  Value: ${change.old_position_value:,.2f} → ${change.new_position_value:,.2f}")
    
    def _get_position_info(self, size: float) -> str:
        """Get position direction info"""
        if size > 0:
            return "LONG"
        elif size < 0:
            return "SHORT"
        else:
            return "CLOSED"
    
    def get_current_positions(self) -> Dict[str, PositionSnapshot]:
        """Get current positions"""
        return self.last_positions.copy()
    
    def get_position_history(self, coin: Optional[str] = None) -> Dict[str, List[PositionSnapshot]]:
        """Get position history for a specific coin or all coins"""
        if coin:
            return {coin: self.position_history.get(coin, [])}
        return self.position_history.copy()
    
    def clear_data(self, confirm: bool = False) -> None:
        """Clear all tracking data (use with caution)"""
        if not confirm:
            logger.info("Use clear_data(confirm=True) to actually clear the data.")
            return
            
        self.position_history = {}
        self.last_positions = {}
        self.changes_log = []
        
        # Remove CSV files
        files_to_remove = [self.positions_file, self.changes_file, self.last_positions_file]
        for file_path in files_to_remove:
            if os.path.exists(file_path):
                os.remove(file_path)
        
        logger.info(f"All tracking data cleared from {self.data_dir}/")
    
    def get_stats(self) -> Dict[str, Any]:
        """Get statistics about tracked data"""
        stats = {
            'total_coins_tracked': len(self.position_history),
            'current_active_positions': len(self.last_positions),
            'total_changes': len(self.changes_log),
            'data_directory': self.data_dir,
            'csv_files': {
                'positions_history': os.path.exists(self.positions_file),
                'changes_log': os.path.exists(self.changes_file),
                'last_positions': os.path.exists(self.last_positions_file)
            }
        }
        
        if self.changes_log:
            stats['first_change'] = self._timestamp_to_human(self.changes_log[0].timestamp)
            stats['last_change'] = self._timestamp_to_human(self.changes_log[-1].timestamp)
        
        return stats

############################################################################################################################################################################################################
# End of classes usesd to manage the copied wallet position tracking
############################################################################################################################################################################################################

## freqtrade strategy class

class Github_djienne_COPY_WALLET_HYPERLIQUID__COPY_HL_LS__20250908_203725(IStrategy):
    global ADDRESS_TO_TRACK_TOP
    minimal_roi = {
        "0": 5000.0  # Effectively disables ROI
    }
    stoploss = -0.95
    timeframe = '5m'
    startup_candle_count: int = 0
    can_short: bool = True
    process_only_new_candles: bool = False
    position_adjustment_enable = True

    # Tunable parameters
    LEV = IntParameter(1, 6, default=6, space='buy', optimize=False)  # Leverage to use
    change_threshold = 0.5 # in %
    adjustement_threshold = 10.0 # in %
    ADDRESS_TO_TRACK = ADDRESS_TO_TRACK_TOP

    # State variables (do not touch)
    copied_account_position_changes = None
    current_positions_to_copy = None
    my_open_positions = None
    nb_loop = 1
    _cached_perp_data = None
    _cache_timestamp = None
    _cache_duration = 5  # seconds
    _is_cooldown_after_position_change = False
    _cooldown_seconds_after_position_change = 100 # seconds
    _time_of_change = None
    _got_perp_data_account_state_successfully = False
    matching_positions_check_output = None

    # Optional order type mapping.
    order_types = {
        'entry': 'market',
        'exit': 'market',
        'stoploss': 'market',
        'stoploss_on_exchange': False
    }

    # Optional order time in force.
    order_time_in_force = {
        'entry': 'gtc',
        'exit': 'gtc'
    }

    def get_stake_total(self) -> float:
        stake = self.config['stake_currency']     # e.g. "USDC"
        return self.wallets.get_total(stake) 

    def GET_PERP_ACCOUNT_STATUS(self, address):
        """Get account status with caching and error handling"""
        try:
            # Use cached data if recent
            current_time = time.time()
            if (self._cached_perp_data is not None and 
                self._cache_timestamp is not None and
                current_time - self._cache_timestamp < self._cache_duration):
                self._got_perp_data_account_state_successfully = True
                return self._cached_perp_data

            from hyperliquid.info import Info
            from hyperliquid.utils import constants
            info = Info(constants.MAINNET_API_URL, skip_ws=True)
            perp_user_state = info.user_state(address)
            
            # Cache the result
            self._cached_perp_data = perp_user_state
            self._cache_timestamp = current_time

            self._got_perp_data_account_state_successfully = True
            
            return perp_user_state
        except Exception as e:
            logger.error(f"Failed to get perp account status: {e}")
            self._got_perp_data_account_state_successfully = False
            # Return cached data if available, otherwise None
            return self._cached_perp_data if self._cached_perp_data else None
        
    def is_symbol_whitelisted(self, symbol: str) -> bool:
        """
        Returns True if the given trading pair symbol is currently in the whitelist.
        """
        if not self.dp:
            # If DataProvider isn't available (e.g., outside strategy context)
            return False

        # Retrieve current whitelist from DataProvider
        current_list = self.dp.current_whitelist()
        return any(symbol in s for s in current_list)
    
    def check_print_positions_summary(self):
        """
        Print a nicely formatted summary of current positions, scale factor, and comparisons.

        Returns:
            list[dict]: For each matching position, a dict with:
                - 'coin': str
                - 'diff_pc': float  # % difference vs expected scaled value
                - 'my_value': float # actual USD value of my position
        """
        matching_positions_output = []
        self.wallets.update()

        try:
            logger.info("=" * 80)
            logger.info("POSITIONS SUMMARY")
            logger.info("=" * 80)
            
            # Account values and scale factor
            perp_data = self.GET_PERP_ACCOUNT_STATUS(self.ADDRESS_TO_TRACK)
            if perp_data:
                copied_account_value = float(perp_data['marginSummary']['accountValue'])
                my_account_value = float(self.get_stake_total())
                scale_factor = my_account_value / copied_account_value
                
                logger.info(f"Copied Account Value: ${copied_account_value:,.2f}")
                logger.info(f"My Account Value:    ${my_account_value:,.2f}")
                logger.info(f"Scale Factor:        {scale_factor:.6f}x (inverted {1.0/scale_factor:.1f}x )")
                logger.info("-" * 50)
            else:
                logger.info("No cached perp data available")
                return matching_positions_output
            
            # Current positions to copy
            logger.info("POSITIONS TO COPY:")
            if self.current_positions_to_copy:
                for coin, position in self.current_positions_to_copy.items():
                    position_value = position.position_value
                    size = float(position.size)
                    ratio_pc = position_value / copied_account_value * 100.0
                    position_type = "LONG" if size > 0 else "SHORT"
                    scaled_value = position_value * scale_factor
                    
                    logger.info(f"  {coin:>8} | {position_type:>5} | Size: {size:>12.4f} | "
                            f"Value: ${position_value:>10.2f} ({ratio_pc:>5.2f}%) | "
                            f"Scaled: ${scaled_value:>10.2f}")
            else:
                logger.info("  No positions to copy")
            
            logger.info("-" * 50)
            
            # My current open positions
            logger.info("MY OPEN POSITIONS:")
            if self.my_open_positions:
                for trade in self.my_open_positions:
                    coin = trade.pair.replace("/USDC:USDC", "")
                    ticker = self.dp.ticker(trade.pair)
                    rate = ticker['last']
                    position_value = trade.amount * rate
                    stake_amount = trade.stake_amount
                    ratio_pc = position_value / my_account_value * 100.0
                    
                    position_type = "LONG" if trade.is_short == False else "SHORT"
                    logger.info(f"  {coin:>8} | {position_type:>5} | Stake: ${stake_amount:>10.2f} | "
                            f"Value: ${position_value:>10.2f} ({ratio_pc:>5.2f}%) | "
                            f"Leverage: {trade.leverage}x")
            else:
                logger.info("  No open positions")
            
            logger.info("-" * 50)
            
            # Position matching analysis
            logger.info("POSITION MATCHING ANALYSIS:")
            if self.current_positions_to_copy and self.my_open_positions:
                copied_coins = set(self.current_positions_to_copy.keys())
                my_coins = set(trade.pair.replace("/USDC:USDC", "") for trade in self.my_open_positions)
                
                # Positions that match
                matching = copied_coins.intersection(my_coins)
                if matching:
                    logger.info("  Matching positions:")
                    for coin in matching:
                        copied_pos = self.current_positions_to_copy[coin]
                        my_trade = next(t for t in self.my_open_positions if t.pair.replace("/USDC:USDC", "") == coin)
                        
                        copied_value = copied_pos.position_value
                        ticker = self.dp.ticker(my_trade.pair)
                        rate = ticker['last']
                        logger.info(f"amount of {my_trade.pair}: {my_trade.amount}")
                        my_value = my_trade.amount * rate
                        expected_value = copied_value * scale_factor
                        diff_pc = ((my_value - expected_value) / expected_value * 100) if expected_value > 0 else 0.0
                        
                        logger.info(f"    {coin:>8} | Copied: ${copied_value:>8.2f} -> Expected: ${expected_value:>8.2f} | "
                                f"Actual: ${my_value:>8.2f} | Diff: {diff_pc:>6.1f}%")
                        
                        matching_positions_output.append({
                            "coin": coin,
                            "diff_pc": float(diff_pc),
                            "my_value": float(my_value)
                        })
                
                # Positions I should have but don't
                should_have = copied_coins - my_coins
                if should_have:
                    logger.info("  Missing positions (should open if in whitelist and significant size):")
                    for coin in should_have:
                        pos = self.current_positions_to_copy[coin]
                        size = float(pos.size)
                        position_type = "LONG" if size > 0 else "SHORT"

                        # Skip if scaled position < 0.5% of my account
                        expected_value = pos.position_value * scale_factor
                        expected_ratio_pc_my = (expected_value / my_account_value * 100.0) if my_account_value > 0 else 0.0
                        if expected_ratio_pc_my < 0.5:
                            continue

                        ratio_pc_copied = pos.position_value / copied_account_value * 100.0
                        significant = "✓" if ratio_pc_copied >= self.change_threshold else "✗"

                        if self.is_symbol_whitelisted(coin):
                            in_wl = ', in whitelist'
                        else:
                            in_wl = ', not in whitelist'
                        
                        logger.info(
                            f"    {coin:>8} | {position_type:>5} | Copied ${pos.position_value:>8.2f} "
                            f"({ratio_pc_copied:>5.2f}% of copied) | "
                            f"Expected scaled: ${expected_value:>8.2f} ({expected_ratio_pc_my:>5.2f}% of mine) {significant} {in_wl}"
                        )
                
                # Positions I have but shouldn't
                shouldnt_have = my_coins - copied_coins
                if shouldnt_have:
                    logger.info("  Extra positions (should close):")
                    for coin in shouldnt_have:
                        my_trade = next(t for t in self.my_open_positions if t.pair.replace("/USDC:USDC", "") == coin)
                        ticker = self.dp.ticker(my_trade.pair)
                        rate = ticker['last']
                        my_value = trade.amount * rate
                        position_type = "LONG" if my_trade.is_short == False else "SHORT"
                        logger.info(f"    {coin:>8} | {position_type:>5} | ${my_value:>8.2f}")
            
            logger.info("=" * 80)
            return matching_positions_output

        except Exception as e:
            logger.error(f"Error in print_positions_summary: {e}")
            return matching_positions_output

    def bot_start(self, **kwargs) -> None:
        """
        Called only once after bot instantiation.
        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
        """
        # because in Live (real money, real account) the value returned by self.dp.ticker(trade.pair) or trade.amount takes some time (> 1 minute) to be refreshed, even if we call self.wallets.update()
        if self.config["runmode"].value in ('live'):
            self._cooldown_seconds_after_position_change = 120
        elif self.config["runmode"].value in ('dry_run'):
            self._cooldown_seconds_after_position_change = 5

    def bot_loop_start(self, current_time: datetime, **kwargs) -> None:
        """
        Called at the start of the bot iteration (one loop). For each loop, it will run populate_indicators on all pairs.
        Might be used to perform pair-independent tasks
        (e.g. gather some remote resource for comparison)
        :param current_time: datetime object, containing the current datetime
        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
        """

        logger.info(f"Loop #{self.nb_loop}")
        self.nb_loop += 1

        try:
            # Initialize tracker
            here = Path(__file__).resolve().parent / 'position_data'
            tracker = PositionTracker(data_dir=here)
            
            perp_data = self.GET_PERP_ACCOUNT_STATUS(self.ADDRESS_TO_TRACK)
            if perp_data is None:
                logger.error("Failed to get perp data, using empty position changes")
                self.copied_account_position_changes = []
                self.current_positions_to_copy = {}
            else:
                self.copied_account_position_changes = tracker.track_positions(perp_data)
                self.current_positions_to_copy = tracker._extract_positions(perp_data)
                
            logger.info(f"Position changes: {self.copied_account_position_changes}")
            tracker.print_changes(self.copied_account_position_changes)

            self.my_open_positions = Trade.get_trades_proxy(is_open=True)

            logger.info("Current positions to copy:")
            logger.info(self.current_positions_to_copy)
            logger.info("My current positions:")
            logger.info(self.my_open_positions)
            
        except Exception as e:
            logger.error(f"Error in bot_loop_start: {e}")
            # Initialize with safe defaults
            self.copied_account_position_changes = []
            self.current_positions_to_copy = {}
            self.my_open_positions = []
            self._got_perp_data_account_state_successfully = False

        self.matching_positions_check_output = self.check_print_positions_summary()

    def populate_indicators(self, df: pd.DataFrame, metadata: dict) -> pd.DataFrame:
        coin_ticker = metadata['pair'].replace("/USDC:USDC", "")
        df['signal'] = 2  # Default: do nothing

        if not self._got_perp_data_account_state_successfully: # skip (do nothing) if API call to get perp data copied account state failed
            return df
        
        perp_data = self.GET_PERP_ACCOUNT_STATUS(self.ADDRESS_TO_TRACK)

        # Handle position changes
        if self.copied_account_position_changes:
            for chg in self.copied_account_position_changes:
                if coin_ticker in chg.coin:
                    copied_account_value = float(perp_data['marginSummary']['accountValue'])
                    #logger.info(f"copied account value: {copied_account_value}")
                    position_value_in_copied_account = float(chg.new_position_value) # in USDC
                    ratio_pc = position_value_in_copied_account/copied_account_value*100.0
                    
                    # Handle both long and short opens
                    if 'opened_long' == chg.change_type:
                        if ratio_pc>self.change_threshold:
                            df['signal'] = 1  # Long entry signal
                            return df
                        else:
                            logger.info(f"Not opening long position on {coin_ticker} because position size in copied account is too small compared to the copied account equity ({ratio_pc:.2f} , less than {self.change_threshold}%)")
                    elif 'opened_short' == chg.change_type:
                        if ratio_pc>self.change_threshold:
                            df['signal'] = -1  # Short entry signal
                            return df
                        else:
                            logger.info(f"Not opening short position on {coin_ticker} because position size in copied account is too small compared to the copied account equity ({ratio_pc:.2f} , less than {self.change_threshold}%)")
                    elif 'closed' in chg.change_type:
                        df['signal'] = 0  # Exit signal for both long and short
                        return df
        else: # Handle missed entries/exits when no changes detected
            df = self._check_missed_entry_or_exit(coin_ticker, df)

        # check if position direction mismatch -> send exit signal
        df = self.check_position_direction_mismatch(df, coin_ticker)

        return df
    
    def _check_missed_entry_or_exit(self, coin_ticker, df):
        """Helper method to check for missed positions"""
        try:
            my_trades = Trade.get_trades_proxy(is_open=True)
            my_current_opened_tickers = [tr.pair.replace("/USDC:USDC", "") for tr in my_trades]
            
            # Check for missed entries (both long and short)
            if coin_ticker in self.current_positions_to_copy:
                if coin_ticker not in my_current_opened_tickers:
                    size = float(self.current_positions_to_copy[coin_ticker].size)
                    is_short = size < 0.0
                    if self._is_position_significant(coin_ticker):
                        if is_short:
                            df['signal'] = -1  # Short entry signal
                            logger.info(f"Missed short entry detected for {coin_ticker}. Sending short entry signal.")
                        else:
                            df['signal'] = 1  # Long entry signal
                            logger.info(f"Missed long entry detected for {coin_ticker}. Sending long entry signal.")
            
            # Check for missed exits
            #   not in current positions to copy, but somehow in my current position
            if coin_ticker not in self.current_positions_to_copy and coin_ticker in my_current_opened_tickers:
                    df['signal'] = 0
                    logger.info(f"Missed exit detected for {coin_ticker}. Sending exit signal.")

            #   in current positions to copy but not really because very small amount, but somehow in my current position
            if coin_ticker in self.current_positions_to_copy and coin_ticker in my_current_opened_tickers:
                    if not self._is_position_significant(coin_ticker) :
                        df['signal'] = 0
                        logger.info(f"Missed exit detected for {coin_ticker}. Sending exit signal.")
                
        except Exception as e:
            logger.error(f"Error checking missed positions for {coin_ticker}: {e}")
        
        return df
    
    def _is_position_significant(self, coin_ticker):
        """Check if position is significant enough to copy"""
        try:
            if not self._cached_perp_data:
                return None
                
            perp_data = self.GET_PERP_ACCOUNT_STATUS(self.ADDRESS_TO_TRACK)
            copied_account_value = float(perp_data['marginSummary']['accountValue'])
            #logger.info(f"copied account value: {copied_account_value}")
            min_threshold = copied_account_value / (100.0/self.change_threshold)  # 1% threshold

            position_value = self.current_positions_to_copy[coin_ticker].position_value

            return position_value > min_threshold
        except Exception as e:
            logger.error(f"Error checking position significance: {e}")
            return None

    def check_position_direction_mismatch(self, df, coin_ticker):
        """
        Check if my position direction doesn't match the copied position direction
        """
        if coin_ticker in self.current_positions_to_copy:
            my_trades = Trade.get_trades_proxy(is_open=True)
            for trade in my_trades:
                if trade.pair.replace("/USDC:USDC", "") == coin_ticker:
                    copied_size = float(self.current_positions_to_copy[coin_ticker].size)
                    copied_is_short = copied_size < 0.0
                    my_is_short = trade.is_short
                    
                    # If directions don't match, exit the position
                    if copied_is_short != my_is_short:
                        df['signal'] = 0
                        logger.info(f"Position direction mismatch on {coin_ticker}. Copied: {'SHORT' if copied_is_short else 'LONG'}, Mine: {'SHORT' if my_is_short else 'LONG'}. Exiting to realign.")
                        return df
        return df

    def populate_entry_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
        dataframe.loc[dataframe['signal'] == 1, 'enter_long'] = 1
        dataframe.loc[dataframe['signal'] == -1, 'enter_short'] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
        dataframe.loc[dataframe['signal'] == 0, 'exit_long'] = 1
        dataframe.loc[dataframe['signal'] == 0, 'exit_short'] = 1
        return dataframe

    def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
                            proposed_stake: float, min_stake: float | None, max_stake: float,
                            leverage: float, entry_tag: str | None, side: str,
                            **kwargs) -> float:
        # Called before entering a trade, makes it possible to manage your position size when placing a new trade.
        # Returning 0 or None will prevent trades from being placed -> ACTS ALSO LIKE AN ENTRY CONFIRMATION
        # Freqtrade will fall back to the proposed_stake value should your code raise an exception. The exception itself will be logged.
        # You do not have to ensure that min_stake <= returned_value <= max_stake. Trades will succeed as the returned value will be clamped to supported range and this action will be logged.

        coin_ticker = pair.replace("/USDC:USDC", "")
        self.wallets.update()

        if not self._got_perp_data_account_state_successfully :
            return None
        
        try:
            if not self._cached_perp_data:
                logger.error("No cached perp data available")
                return None
            
            perp_data = self.GET_PERP_ACCOUNT_STATUS(self.ADDRESS_TO_TRACK)
            copied_account_value = float(perp_data['marginSummary']['accountValue'])
            my_account_value = float(self.get_stake_total())
            scale_factor = my_account_value / copied_account_value

            # Look in both position changes and current positions
            position_value_in_copied_account = None
            copied_position_size = None
            
            # First check position changes
            for chg in self.copied_account_position_changes:
                if coin_ticker == chg.coin:
                    position_value_in_copied_account = float(chg.new_position_value)
                    copied_position_size = float(chg.new_size)
                    break
            
            # If not found in changes, check current positions
            if position_value_in_copied_account is None:
                if coin_ticker in self.current_positions_to_copy:
                    position_value_in_copied_account = self.current_positions_to_copy[coin_ticker].position_value
                    copied_position_size = float(self.current_positions_to_copy[coin_ticker].size)
            
            if position_value_in_copied_account is None or copied_position_size is None:
                logger.warning(f"No position data found for {coin_ticker}")
                return None
            
            # Determine position direction
            is_short_position = copied_position_size < 0.0
            position_type = "SHORT" if is_short_position else "LONG"
            
            # Validate that the side matches the position direction
            if (side == "short" and not is_short_position) or (side == "long" and is_short_position):
                logger.warning(f"Position direction mismatch for {coin_ticker}: side={side}, copied_position={'SHORT' if is_short_position else 'LONG'}")
                return None
            
            ratio_pc = position_value_in_copied_account/copied_account_value * 100.0
            if ratio_pc < self.change_threshold:
                logger.info(f"Not opening {position_type} position on {pair} because position size in copied account is too small ({ratio_pc:.1f}% < {self.change_threshold}%)")
                return None

            dust_USDC = 0.51
            returned_val = position_value_in_copied_account * scale_factor
            returned_val = (returned_val / leverage) - dust_USDC

            if returned_val < min_stake:
                returned_val = min_stake

            logger.info(f"Calculated stake for {position_type} {pair}: {returned_val} (copied value: ${position_value_in_copied_account:.2f}, scale: {scale_factor:.4f})")
            return returned_val
            
        except Exception as e:
            logger.error(f"Error in custom_stake_amount: {e}")
            return None
    
    def adjust_trade_position(self, trade: Trade, current_time: datetime,
                                current_rate: float, current_profit: float,
                                min_stake: float | None, max_stake: float,
                                current_entry_rate: float, current_exit_rate: float,
                                current_entry_profit: float, current_exit_profit: float,
                                **kwargs
                                ) -> float | None | tuple[float | None, str | None]:
        # :return float: Stake amount to adjust your trade,
        #                Positive values to increase position, Negative values to decrease position.
        #                Return None for no action.
        #                Optionally, return a tuple with a 2nd element with an order reason

        coin_ticker = trade.pair.replace("/USDC:USDC", "")
        self.wallets.update()

        dust_USDC = 0.51

        if not self._got_perp_data_account_state_successfully :
            return None

        if self._time_of_change is not None:
            if datetime.now() > self._time_of_change + timedelta(seconds=self._cooldown_seconds_after_position_change):
                self._is_cooldown_after_position_change = False

        if self._is_cooldown_after_position_change:
            logger.info(f"Not doing position size change because of the cooldown of {self._cooldown_seconds_after_position_change} seconds.") 
            return None

        try:
            if not self._cached_perp_data:
                return None
            
            perp_data = self.GET_PERP_ACCOUNT_STATUS(self.ADDRESS_TO_TRACK)
            
            if self.copied_account_position_changes:
                copied_account_value = float(perp_data['marginSummary']['accountValue'])
                my_account_value = float(self.get_stake_total())
                scale_factor = my_account_value / copied_account_value

                # for detected changes in the copied account
                for chg in self.copied_account_position_changes:
                    if coin_ticker == chg.coin:
                        # Check if change is significant (>0.5% of account), otherwise skip doing adjustment by returning None
                        change_ratio_pc = abs(float(chg.old_position_value) - float(chg.new_position_value)) / copied_account_value * 100.0
                        if change_ratio_pc < self.change_threshold:
                            logger.info(f"Not adjusting position on {trade.pair} because position change in copied account is too small ({change_ratio_pc:.1f}% < {self.change_threshold}%)")
                            return None

                        # Determine position direction for logging
                        position_type = "SHORT" if trade.is_short else "LONG"
                        old_size = float(chg.old_size) if chg.old_size is not None else 0.0
                        new_size = float(chg.new_size)
                        
                        delta_stake = abs(float(chg.old_position_value) - float(chg.new_position_value)) * scale_factor
                        adjustment_amount = delta_stake / trade.leverage - dust_USDC

                        self._time_of_change = datetime.now()
                        self._is_cooldown_after_position_change = True 
                        
                        if 'increased' in chg.change_type:
                            logger.info(f"Increasing {position_type} position on {trade.pair}: +${adjustment_amount:.2f} (copied size: {old_size:.4f} -> {new_size:.4f})")
                            return adjustment_amount
                        elif 'decreased' in chg.change_type:
                            logger.info(f"Decreasing {position_type} position on {trade.pair}: -${adjustment_amount:.2f} (copied size: {old_size:.4f} -> {new_size:.4f})")
                            return -1.0 * adjustment_amount
                    
            # for already opened positions, if difference with what it should be in copied account (and scaled) is too large (>10%), adjust to match
            if self.matching_positions_check_output:
                for pos in self.matching_positions_check_output:
                    logger.info(f"{pos['coin']} → Difference: {pos['diff_pc']:.2f}%   (my total value: {pos['my_value']:.1f}) ; ||>{self.adjustement_threshold:.0f}% will trigger a size correction.")
                    if pos['coin']==coin_ticker:
                        if abs(pos['diff_pc'])>self.adjustement_threshold:
                            position_type = "SHORT" if trade.is_short else "LONG"
                            delta_stake = pos['my_value']/(1.0 + pos['diff_pc']/100.0)-pos['my_value']
                            adjustment_amount = delta_stake / trade.leverage - dust_USDC
                            
                            action = "Increasing" if delta_stake > 0 else "Decreasing"
                            logger.info(f"{action} {position_type} position on {trade.pair} to correct size mismatch: ${adjustment_amount:.2f} (diff: {pos['diff_pc']:.1f}%)")
                            
                            self._time_of_change = datetime.now()
                            self._is_cooldown_after_position_change = True
                            return adjustment_amount
            return None
            
        except Exception as e:
            logger.error(f"Error in adjust_trade_position: {e}")
            return None
        
    def leverage(self, pair: str, current_time: datetime, current_rate: float,
                 proposed_leverage: float, max_leverage: float, entry_tag: str | None, side: str,
                 **kwargs) -> float:
        lev = min(self.LEV.value, max_leverage)
        return lev