# source: https://raw.githubusercontent.com/djienne/YOUTUBE_STRATEGIES_FREQTRADE/eb8dd4cc8e84413d4f13b4533d6bc57e8ad8a4b6/Market_Making/Market_Making/user_data/strategies/Market_Making.py import pandas as pd from datetime import datetime 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 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" ##################################################################################################################################################################################################### # 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_YOUTUBE_STRATEGIES_FREQTRADE__Market_Making__20250827_203136(IStrategy): global ADDRESS_TO_TRACK_TOP minimal_roi = { "0": 5000.0 # Effectively disables ROI } stoploss = -0.95 timeframe = '1m' startup_candle_count: int = 0 can_short: bool = False 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 _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""" self._got_perp_data_account_state_successfully = False 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): 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 symbol 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 if self._cached_perp_data: copied_account_value = float(self._cached_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 logger.info(f" {coin:>8} | LONG | 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(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):") 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'] rate = orderbook['bids'][0][0] my_value = trade.amount * rate logger.info(f" {coin:>8} | LONG | ${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. """ 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 # 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(self._cached_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 if float(chg.new_size)<0.0: # check if short, just in case logger.info(f"Ignoring entry on {coin_ticker} because it is a Short. This code is LONG ONLY.") return df ratio_pc = position_value_in_copied_account/copied_account_value*100.0 # if it is a long open and if the size is significant if 'opened_long' == chg.change_type: if ratio_pc>self.change_threshold: df['signal'] = 1 return df else: logger.info(f"Not opening position on {coin_ticker} because position size in copied account is too small compared to the copied account equity ({ratio_pc:.2f} , less than 1%)") elif 'closed' in chg.change_type: df['signal'] = 0 return df else: # Handle missed entries/exits when no changes detected df = self._check_missed_entry_or_exit(coin_ticker, df) # check if mistaken Long that is actually a Short -> send exit signal df = self.check_mistaken_short(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 if coin_ticker in self.current_positions_to_copy: if coin_ticker not in my_current_opened_tickers: is_short = float(self.current_positions_to_copy[coin_ticker].size)<0.0 if self._is_position_significant(coin_ticker) and not is_short: df['signal'] = 1 logger.info(f"Missed entry detected for {coin_ticker}. Sending 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 False copied_account_value = float(self._cached_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 False def check_mistaken_short(self, df, coin_ticker): """ """ if coin_ticker in self.current_positions_to_copy: my_trades = Trade.get_trades_proxy(is_open=True) my_current_opened_tickers = [tr.pair.replace("/USDC:USDC", "") for tr in my_trades] if coin_ticker in my_current_opened_tickers: is_short = float(self.current_positions_to_copy[coin_ticker].size) < 0.0 if is_short: df['signal'] = 0 logger.info(f"There was a short mistaken as a long on {coin_ticker}. This code is LONG ONLY. Exiting immediatly.") return df return df def populate_entry_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame: dataframe.loc[dataframe['signal'] == 1, 'enter_long'] = 1 return dataframe def populate_exit_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame: dataframe.loc[dataframe['signal'] == 0, 'exit_long'] = 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 copied_account_value = float(self._cached_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 # 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) 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 if position_value_in_copied_account is None: logger.warning(f"No position value found for {coin_ticker}") return None ratio_pc = position_value_in_copied_account/copied_account_value * 100.0 if ratio_pc 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() # logger.info(max_stake) #logger.info(Trade.get_total_closed_profit()) # logger.info(f"min stake: {min_stake}") dust_USDC = 0.51 if not self._got_perp_data_account_state_successfully : return None try: if not self._cached_perp_data: return None if self.copied_account_position_changes: copied_account_value = float(self._cached_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 increasing or decreasing position on {trade.pair} because position change in copied account is too small compared to the copied account equity({change_ratio_pc:.1f}% < 1%)") return None delta_stake = abs(float(chg.old_position_value) - float(chg.new_position_value)) * scale_factor if 'increased' in chg.change_type: return delta_stake / trade.leverage - dust_USDC elif 'decreased' in chg.change_type: return -1.0 * delta_stake / trade.leverage - dust_USDC # 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: #logger.info(pos['diff_pc']) delta_stake = pos['my_value']/(1.0 + pos['diff_pc']/100.0)-pos['my_value'] logger.info(delta_stake) logger.info(delta_stake / trade.leverage) return delta_stake / trade.leverage - dust_USDC 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