#!/usr/bin/env python3
"""
Cross-Chain Whale Tracking Module for Phase 3
Advanced cross-chain analysis and coordination detection

Author: Pezhman Hajipour
Version: 3.0.0
"""

import logging
import asyncio
import requests
import json
from typing import Dict, List, Optional, Tuple, Any
from datetime import datetime, timedelta
from dataclasses import dataclass, field
from collections import defaultdict, deque
import hashlib
import time

from ..core_types import WhaleBotConfig, EnhancedTrade, WhaleTier
from ..monitor import HyperliquidMonitor

logger = logging.getLogger(__name__)

@dataclass
class ChainInfo:
    """Information about a blockchain network"""
    name: str
    chain_id: int
    rpc_url: str
    native_token: str
    is_active: bool = True
    whale_threshold_usd: float = 1000000.0

@dataclass
class CrossChainTransfer:
    """Cross-chain transfer information"""
    transfer_id: str
    from_chain: str
    to_chain: str
    asset: str
    amount: float
    amount_usd: float
    timestamp: datetime
    tx_hash: str
    bridge_used: str
    confirmations: int = 0

@dataclass
class WhaleChainProfile:
    """Comprehensive whale profile across chains"""
    whale_address: str
    chain_profiles: Dict[str, Dict[str, Any]]
    total_volume_usd: float
    active_chains: List[str]
    coordination_metrics: Dict[str, float]
    behavioral_patterns: Dict[str, Any]
    reputation_score: float
    first_seen: datetime
    last_activity: datetime
    risk_assessment: Dict[str, Any]

class CrossChainAnalytics:
    """Cross-chain analytics and pattern detection"""
    
    def __init__(self, config: WhaleBotConfig):
        self.config = config
        self.supported_chains = self._initialize_supported_chains()
        self.cross_chain_data = defaultdict(dict)
        self.transfer_patterns = defaultdict(list)
        self.coordination_detections = []
        
    def _initialize_supported_chains(self) -> Dict[str, ChainInfo]:
        """Initialize supported blockchain networks"""
        return {
            'ETHEREUM': ChainInfo('Ethereum', 1, 'https://eth.drpc.org', 'ETH'),
            'POLYGON': ChainInfo('Polygon', 137, 'https://polygon-rpc.com', 'MATIC'),
            'BSC': ChainInfo('Binance Smart Chain', 56, 'https://bsc-dataseed.binance.org', 'BNB'),
            'ARBITRUM': ChainInfo('Arbitrum', 42161, 'https://arb1.arbitrum.io/rpc', 'ARB'),
            'OPTIMISM': ChainInfo('Optimism', 10, 'https://mainnet.optimism.io', 'OP'),
            'AVALANCHE': ChainInfo('Avalanche', 43114, 'https://api.avax.network/ext/bc/C/rpc', 'AVAX'),
            'FANTOM': ChainInfo('Fantom', 250, 'https://rpc.ftm.tools', 'FTM')
        }
    
    async def track_whale_across_chains(self, whale_address: str, 
                                      source_chain: str, trade_data: Dict[str, Any]) -> Optional[WhaleChainProfile]:
        """Track whale activity across multiple chains"""
        try:
            # Get whale profile from source chain
            whale_profile = await self._get_whale_profile(whale_address, source_chain, trade_data)
            
            # Check for activity on other chains
            other_chains = [chain for chain in self.supported_chains.keys() if chain != source_chain]
            
            for chain in other_chains[:3]:  # Check top 3 other chains
                try:
                    chain_activity = await self._check_chain_activity(whale_address, chain)
                    if chain_activity:
                        whale_profile.chain_profiles[chain] = chain_activity
                        whale_profile.active_chains.append(chain)
                except Exception as e:
                    logger.warning(f"Error checking {chain} for whale {whale_address}: {e}")
            
            # Update coordination metrics
            await self._update_coordination_metrics(whale_profile)
            
            # Store updated profile
            self.cross_chain_data[whale_address] = whale_profile
            
            logger.info(f"Updated cross-chain profile for {whale_address}: {len(whale_profile.active_chains)} chains")
            return whale_profile
            
        except Exception as e:
            logger.error(f"Error tracking whale across chains: {e}")
            return None
    
    async def _get_whale_profile(self, whale_address: str, chain: str, 
                               trade_data: Dict[str, Any]) -> Dict[str, Any]:
        """Get whale profile for specific chain"""
        # Simulate chain-specific whale data
        return {
            'chain': chain,
            'address': whale_address,
            'total_volume_usd': trade_data.get('size_usd', 0),
            'transaction_count': np.random.randint(50, 500),
            'avg_trade_size': trade_data.get('size_usd', 0) * 0.8,
            'preferred_assets': ['USDC', 'USDT', 'ETH'],
            'activity_pattern': {
                'most_active_hours': list(range(8, 18)),  # UTC hours
                'most_active_days': [1, 2, 3, 4],  # Mon-Thu
                'avg_trade_frequency': '2-3 per day'
            },
            'risk_indicators': {
                'flash_loan_usage': np.random.choice([True, False], p=[0.3, 0.7]),
                'sandwich_attacks': np.random.randint(0, 5),
                'large_withdrawals': np.random.randint(0, 3)
            }
        }
    
    async def _check_chain_activity(self, whale_address: str, chain: str) -> Optional[Dict[str, Any]]:
        """Check for whale activity on specific chain"""
        # Simulate cross-chain activity detection
        import random
        random.seed(hash(whale_address + chain) % 1000)
        
        # 40% chance of finding activity on secondary chains
        if random.random() > 0.6:
            return {
                'chain': chain,
                'address': whale_address,
                'total_volume_usd': random.uniform(100000, 2000000),
                'transaction_count': random.randint(10, 100),
                'avg_trade_size': random.uniform(50000, 500000),
                'last_activity': datetime.now() - timedelta(hours=random.randint(1, 72)),
                'bridge_activity': random.choice(['MULTICHAIN', 'STARGATE', 'HYPERLANE']),
                'activity_consistency': random.uniform(0.6, 0.95)
            }
        
        return None
    
    async def _update_coordination_metrics(self, profile: WhaleChainProfile):
        """Update coordination metrics for whale"""
        active_chains = len(profile.active_chains)
        total_volume = profile.total_volume_usd
        
        # Calculate coordination score
        if active_chains >= 3:
            profile.coordination_metrics['multi_chain_coordination'] = min(1.0, active_chains * 0.25)
        else:
            profile.coordination_metrics['multi_chain_coordination'] = active_chains * 0.15
        
        # Calculate temporal coordination (activity timing)
        profile.coordination_metrics['temporal_coordination'] = random.uniform(0.4, 0.8)
        
        # Calculate volume coordination
        profile.coordination_metrics['volume_coordination'] = random.uniform(0.5, 0.9)
        
        # Calculate overall reputation score
        base_score = 0.5
        if active_chains >= 3:
            base_score += 0.2
        if total_volume > 10_000_000:
            base_score += 0.2
        if profile.risk_assessment.get('manipulation_risk', 0) < 0.3:
            base_score += 0.1
        
        profile.reputation_score = min(1.0, base_score)
    
    async def detect_coordinated_activity(self) -> List[Dict[str, Any]]:
        """Detect coordinated whale activity across chains"""
        try:
            coordinated_groups = []
            
            # Group whales by coordination patterns
            coordination_groups = defaultdict(list)
            
            for whale_address, profile in self.cross_chain_data.items():
                coord_score = sum(profile.coordination_metrics.values()) / len(profile.coordination_metrics)
                
                if coord_score > 0.7:  # High coordination threshold
                    # Create coordination group key based on active chains
                    chains_key = tuple(sorted(profile.active_chains))
                    coordination_groups[chains_key].append({
                        'address': whale_address,
                        'coordination_score': coord_score,
                        'volume_usd': profile.total_volume_usd,
                        'risk_level': self._assess_risk_level(profile)
                    })
            
            # Analyze coordination groups
            for chains, whales in coordination_groups.items():
                if len(whales) >= 2:  # At least 2 whales in coordination
                    coordinated_groups.append({
                        'coordinated_chains': list(chains),
                        'whales_involved': len(whales),
                        'whale_addresses': [w['address'] for w in whales],
                        'total_volume': sum(w['volume_usd'] for w in whales),
                        'coordination_strength': np.mean([w['coordination_score'] for w in whales]),
                        'risk_assessment': self._assess_group_risk(whales),
                        'detection_timestamp': datetime.now().isoformat()
                    })
            
            if coordinated_groups:
                logger.warning(f"Detected {len(coordinated_groups)} coordinated whale groups")
                
            return coordinated_groups
            
        except Exception as e:
            logger.error(f"Error detecting coordinated activity: {e}")
            return []
    
    def _assess_risk_level(self, profile: WhaleChainProfile) -> str:
        """Assess risk level for individual whale"""
        risk_factors = 0
        
        if profile.risk_assessment.get('manipulation_risk', 0) > 0.6:
            risk_factors += 2
        if len(profile.active_chains) > 4:
            risk_factors += 1
        if profile.coordination_metrics.get('multi_chain_coordination', 0) > 0.8:
            risk_factors += 1
        
        if risk_factors >= 3:
            return 'HIGH'
        elif risk_factors >= 1:
            return 'MEDIUM'
        else:
            return 'LOW'
    
    def _assess_group_risk(self, whales: List[Dict[str, Any]]) -> str:
        """Assess risk level for coordinated group"""
        high_risk_count = len([w for w in whales if w['risk_level'] == 'HIGH'])
        total_whales = len(whales)
        
        if high_risk_count / total_whales > 0.5:
            return 'CRITICAL'
        elif high_risk_count > 0:
            return 'HIGH'
        else:
            return 'MEDIUM'
    
    async def analyze_cross_chain_patterns(self) -> Dict[str, Any]:
        """Analyze cross-chain patterns and trends"""
        try:
            pattern_analysis = {
                'total_whales_tracked': len(self.cross_chain_data),
                'multi_chain_whales': len([p for p in self.cross_chain_data.values() if len(p.active_chains) > 1]),
                'most_active_chains': self._get_most_active_chains(),
                'coordination_trends': self._analyze_coordination_trends(),
                'bridge_usage_patterns': self._analyze_bridge_patterns(),
                'risk_assessment': self._get_overall_risk_assessment()
            }
            
            return pattern_analysis
            
        except Exception as e:
            logger.error(f"Error analyzing cross-chain patterns: {e}")
            return {}
    
    def _get_most_active_chains(self) -> List[Dict[str, Any]]:
        """Get most active chains for whale activity"""
        chain_activity = defaultdict(int)
        chain_volumes = defaultdict(float)
        
        for profile in self.cross_chain_data.values():
            for chain in profile.active_chains:
                chain_activity[chain] += 1
                chain_volumes[chain] += profile.total_volume_usd
        
        # Sort by activity
        sorted_chains = sorted(chain_activity.items(), key=lambda x: x[1], reverse=True)
        
        return [
            {
                'chain': chain,
                'whale_count': count,
                'total_volume_usd': chain_volumes[chain]
            }
            for chain, count in sorted_chains[:5]
        ]
    
    def _analyze_coordination_trends(self) -> Dict[str, Any]:
        """Analyze coordination trends over time"""
        # Simulate trend analysis
        return {
            'coordination_increasing': True,
            'trend_strength': 0.72,
            'peak_coordination_hours': [14, 15, 16],  # UTC
            'most_coordinated_chains': ['ETHEREUM', 'POLYGON', 'BSC'],
            'avg_coordination_score': 0.68
        }
    
    def _analyze_bridge_patterns(self) -> Dict[str, Any]:
        """Analyze cross-chain bridge usage patterns"""
        return {
            'most_used_bridges': ['MULTICHAIN', 'STARGATE', 'HYPERLANE'],
            'bridge_volume_distribution': {
                'MULTICHAIN': 0.4,
                'STARGATE': 0.35,
                'HYPERLANE': 0.25
            },
            'avg_bridge_time_minutes': 12.5,
            'bridge_success_rate': 0.985
        }
    
    def _get_overall_risk_assessment(self) -> Dict[str, Any]:
        """Get overall cross-chain risk assessment"""
        total_whales = len(self.cross_chain_data)
        high_risk_whales = len([p for p in self.cross_chain_data.values() 
                              if self._assess_risk_level(p) == 'HIGH'])
        
        return {
            'overall_risk_level': 'HIGH' if high_risk_whales / total_whales > 0.3 else 'MEDIUM',
            'high_risk_whale_percentage': (high_risk_whales / total_whales * 100) if total_whales > 0 else 0,
            'coordination_risk_score': 0.75,
            'manipulation_risk_score': 0.62,
            'recommendations': [
                "Monitor high-coordination whales closely",
                "Track bridge transactions for unusual patterns",
                "Set up alerts for multi-chain activity spikes"
            ]
        }

class CrossChainMonitor:
    """Real-time cross-chain monitoring and alerts"""
    
    def __init__(self, config: WhaleBotConfig):
        self.config = config
        self.analytics = CrossChainAnalytics(config)
        self.monitoring_active = False
        self.alert_thresholds = {
            'coordination_score': 0.8,
            'multi_chain_volume': 5_000_000,  # $5M
            'new_chain_activity': True
        }
        
    async def start_monitoring(self):
        """Start real-time cross-chain monitoring"""
        self.monitoring_active = True
        logger.info("Cross-chain monitoring started")
        
        while self.monitoring_active:
            try:
                # Check for new coordinated activities
                coordinated_activities = await self.analytics.detect_coordinated_activity()
                
                for activity in coordinated_activities:
                    if activity['coordination_strength'] > self.alert_thresholds['coordination_score']:
                        await self._trigger_coordination_alert(activity)
                
                # Check for multi-chain whales with high volume
                for whale_address, profile in self.analytics.cross_chain_data.items():
                    if (profile.total_volume_usd > self.alert_thresholds['multi_chain_volume'] and 
                        len(profile.active_chains) > 2):
                        await self._trigger_volume_alert(whale_address, profile)
                
                # Wait before next check
                await asyncio.sleep(30)  # Check every 30 seconds
                
            except Exception as e:
                logger.error(f"Error in monitoring loop: {e}")
                await asyncio.sleep(60)  # Wait longer on error
    
    async def _trigger_coordination_alert(self, activity: Dict[str, Any]):
        """Trigger alert for coordinated activity"""
        alert_data = {
            'alert_type': 'COORDINATED_ACTIVITY',
            'severity': 'HIGH',
            'chains_involved': activity['coordinated_chains'],
            'whale_count': activity['whales_involved'],
            'total_volume': activity['total_volume'],
            'coordination_strength': activity['coordination_strength'],
            'risk_level': activity['risk_assessment'],
            'timestamp': datetime.now().isoformat()
        }
        
        logger.warning(f"🚨 Coordinated Activity Alert: {alert_data}")
    
    async def _trigger_volume_alert(self, whale_address: str, profile: WhaleChainProfile):
        """Trigger alert for high-volume multi-chain whale"""
        alert_data = {
            'alert_type': 'HIGH_VOLUME_MULTI_CHAIN',
            'severity': 'MEDIUM',
            'whale_address': whale_address,
            'active_chains': profile.active_chains,
            'total_volume': profile.total_volume_usd,
            'coordination_score': sum(profile.coordination_metrics.values()) / len(profile.coordination_metrics),
            'timestamp': datetime.now().isoformat()
        }
        
        logger.warning(f"💰 High Volume Multi-Chain Alert: {alert_data}")
    
    async def stop_monitoring(self):
        """Stop cross-chain monitoring"""
        self.monitoring_active = False
        logger.info("Cross-chain monitoring stopped")
    
    def get_monitoring_status(self) -> Dict[str, Any]:
        """Get current monitoring status"""
        return {
            'monitoring_active': self.monitoring_active,
            'chains_supported': len(self.analytics.supported_chains),
            'whales_tracked': len(self.analytics.cross_chain_data),
            'alert_thresholds': self.alert_thresholds,
            'last_coordination_detection': datetime.now().isoformat(),
            'system_health': 'ACTIVE' if self.monitoring_active else 'STOPPED'
        }

class CrossChainAPI:
    """API client for cross-chain data fetching"""
    
    def __init__(self, config: WhaleBotConfig):
        self.config = config
        self.session = requests.Session()
        self.rate_limits = defaultdict(int)
    
    async def get_whale_transfers(self, whale_address: str, chain: str, 
                                hours_back: int = 24) -> List[CrossChainTransfer]:
        """Get whale transfers for specific address and chain"""
        try:
            # Simulate API call to chain scanner
            await asyncio.sleep(0.1)  # Simulate network delay
            
            transfers = []
            for i in range(np.random.randint(0, 5)):  # Random 0-4 transfers
                transfer = CrossChainTransfer(
                    transfer_id=f"tx_{whale_address}_{i}",
                    from_chain=chain,
                    to_chain=np.random.choice(list(self.analytics.supported_chains.keys())),
                    asset=np.random.choice(['USDC', 'USDT', 'ETH']),
                    amount=np.random.uniform(100000, 1000000),
                    amount_usd=np.random.uniform(100000, 1000000),
                    timestamp=datetime.now() - timedelta(hours=np.random.randint(0, hours_back)),
                    tx_hash=f"0x{hashlib.sha256(f'{whale_address}{i}'.encode()).hexdigest()[:40]}",
                    bridge_used=np.random.choice(['MULTICHAIN', 'STARGATE', 'HYPERLANE']),
                    confirmations=np.random.randint(1, 20)
                )
                transfers.append(transfer)
            
            return transfers
            
        except Exception as e:
            logger.error(f"Error fetching whale transfers: {e}")
            return []
    
    async def get_chain_volume(self, chain: str, timeframe: str = '24h') -> Dict[str, Any]:
        """Get volume data for specific chain"""
        try:
            # Simulate chain API call
            await asyncio.sleep(0.05)
            
            return {
                'chain': chain,
                'timeframe': timeframe,
                'total_volume_usd': np.random.uniform(100_000_000, 1_000_000_000),
                'whale_volume_usd': np.random.uniform(50_000_000, 300_000_000),
                'unique_whales': np.random.randint(100, 1000),
                'top_whale_addresses': [f"0x{hashlib.sha256(f'whale_{i}'.encode()).hexdigest()[:40]}" 
                                      for i in range(10)],
                'bridge_volume_usd': np.random.uniform(20_000_000, 100_000_000),
                'timestamp': datetime.now().isoformat()
            }
            
        except Exception as e:
            logger.error(f"Error fetching chain volume: {e}")
            return {}
    
    async def get_bridge_analytics(self, bridge_name: str) -> Dict[str, Any]:
        """Get analytics for specific bridge"""
        try:
            await asyncio.sleep(0.05)
            
            return {
                'bridge_name': bridge_name,
                'supported_chains': list(self.analytics.supported_chains.keys())[:3],
                'daily_volume_usd': np.random.uniform(10_000_000, 100_000_000),
                'transaction_count': np.random.randint(1000, 10000),
                'avg_transaction_size': np.random.uniform(50000, 500000),
                'success_rate': np.random.uniform(0.98, 0.999),
                'avg_time_minutes': np.random.uniform(5, 30),
                'top_whale_users': [f"0x{hashlib.sha256(f'whale_{i}'.encode()).hexdigest()[:40]}" 
                                  for i in range(20)],
                'suspicious_activity_score': np.random.uniform(0.1, 0.4)
            }
            
        except Exception as e:
            logger.error(f"Error fetching bridge analytics: {e}")
            return {}
