"""
Crypto Anomaly Detection Engine System (CADES)
Liquidity Pool Tracker Module

This module implements real-time tracking and analysis of Solana DEX liquidity pools,
focusing on Raydium and Orca pools for memecoin trading pairs.

Author: CADES Team
License: Proprietary
"""

import asyncio
from dataclasses import dataclass
from datetime import datetime, timedelta
from typing import Dict, List, Optional, Set, Tuple
import numpy as np
from collections import defaultdict, deque
import logging
import json

from solana.rpc.async_api import AsyncClient
from solders.pubkey import Pubkey

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

@dataclass
class LiquidityEvent:
    """Represents a significant liquidity pool event"""
    pool_address: str
    event_type: str  # 'add', 'remove', 'swap'
    timestamp: datetime
    amount_token_a: float
    amount_token_b: float
    price_impact: float
    tx_signature: str
    wallet_address: str
    risk_score: float

@dataclass
class PoolState:
    """Current state of a liquidity pool"""
    pool_address: str
    token_a_address: str
    token_b_address: str
    token_a_amount: float
    token_b_amount: float
    last_price: float
    last_updated: datetime
    total_value_locked: float
    volume_24h: float
    volatility_24h: float

class LiquidityTracker:
    """
    Advanced liquidity pool tracker for Solana DEXes.
    Monitors pool states and detects suspicious liquidity events.
    """

    # Raydium and Orca program IDs
    RAYDIUM_PROGRAM_ID = "675kPX9MHTjS2zt1qfr1NYHuzeLXfQM9H24wFSUt1Mp8"
    ORCA_V2_PROGRAM_ID = "9W959DqEETiGZocYWCQPaJ6sBmUzgfxXfqGeTEdp3aQP"
    
    def __init__(
        self,
        rpc_client: AsyncClient,
        min_pool_size_usd: float = 10000,  # Minimum pool size to track
        scan_interval: int = 10,  # Seconds between pool state updates
        risk_threshold: float = 0.7
    ):
        """
        Initialize the liquidity tracker with configuration parameters.

        Args:
            rpc_client: Solana RPC client instance
            min_pool_size_usd: Minimum pool size in USD to track
            scan_interval: Interval between pool state scans in seconds
            risk_threshold: Threshold for high-risk events
        """
        self.rpc_client = rpc_client
        self.min_pool_size_usd = min_pool_size_usd
        self.scan_interval = scan_interval
        self.risk_threshold = risk_threshold

        # Data structures for tracking
        self.tracked_pools: Dict[str, PoolState] = {}
        self.pool_events: Dict[str, List[LiquidityEvent]] = defaultdict(list)
        self.price_history: Dict[str, deque] = defaultdict(
            lambda: deque(maxlen=8640)  # 24 hours of 10-second intervals
        )
        
        # Volatility tracking
        self.volatility_windows: Dict[str, List[float]] = defaultdict(list)
        
        # Cache for wallet analysis
        self.wallet_activity: Dict[str, Dict] = defaultdict(
            lambda: {
                'pool_interactions': 0,
                'total_volume_usd': 0.0,
                'last_seen': None,
                'risk_score': 0.0
            }
        )

    async def start_tracking(self) -> None:
        """Start the main liquidity tracking loop."""
        try:
            logger.info("Starting liquidity pool tracking...")
            
            # Initialize pool tracking
            await self._initialize_pool_tracking()
            
            # Main tracking loop
            while True:
                await self._update_pool_states()
                await asyncio.sleep(self.scan_interval)
                
        except Exception as e:
            logger.error(f"Error in liquidity tracking loop: {e}")
            raise

    async def _initialize_pool_tracking(self) -> None:
        """Initialize tracking for all relevant liquidity pools."""
        try:
            # Get all Raydium pools
            raydium_pools = await self._fetch_dex_pools(self.RAYDIUM_PROGRAM_ID)
            
            # Get all Orca pools
            orca_pools = await self._fetch_dex_pools(self.ORCA_V2_PROGRAM_ID)
            
            # Filter and initialize pools
            for pool_data in raydium_pools + orca_pools:
                if await self._should_track_pool(pool_data):
                    await self._initialize_pool(pool_data)
                    
            logger.info(f"Initialized tracking for {len(self.tracked_pools)} pools")
            
        except Exception as e:
            logger.error(f"Error initializing pool tracking: {e}")
            raise

    async def _should_track_pool(self, pool_data: Dict) -> bool:
        """Determine if a pool should be tracked based on criteria."""
        try:
            tvl = await self._calculate_pool_tvl(pool_data)
            return tvl >= self.min_pool_size_usd
        except Exception:
            return False

    async def _update_pool_states(self) -> None:
        """Update states for all tracked pools."""
        for pool_address, pool_state in self.tracked_pools.items():
            try:
                new_state = await self._fetch_pool_state(pool_address)
                if new_state:
                    # Analyze state changes
                    events = self._analyze_state_change(pool_state, new_state)
                    
                    # Update tracking data
                    self.tracked_pools[pool_address] = new_state
                    self.price_history[pool_address].append(new_state.last_price)
                    
                    # Process detected events
                    if events:
                        await self._process_pool_events(events)
                        
            except Exception as e:
                logger.error(f"Error updating pool {pool_address}: {e}")

    async def _fetch_pool_state(self, pool_address: str) -> Optional[PoolState]:
        """Fetch current state of a liquidity pool."""
        try:
            # Fetch account data
            response = await self.rpc_client.get_account_info(
                Pubkey.from_string(pool_address),
                commitment="confirmed"
            )
            
            if not response or not response.value:
                return None

            # Decode pool data based on DEX type
            if self._is_raydium_pool(pool_address):
                return self._decode_raydium_pool_data(response.value.data)
            else:
                return self._decode_orca_pool_data(response.value.data)
                
        except Exception as e:
            logger.error(f"Error fetching pool state: {e}")
            return None

    def _analyze_state_change(
        self,
        old_state: PoolState,
        new_state: PoolState
    ) -> List[LiquidityEvent]:
        """Analyze pool state changes for suspicious activity."""
        events = []
        
        try:
            # Calculate basic metrics
            token_a_change = new_state.token_a_amount - old_state.token_a_amount
            token_b_change = new_state.token_b_amount - old_state.token_b_amount
            price_change = (new_state.last_price - old_state.last_price) / old_state.last_price
            
            # Detect large liquidity changes
            if abs(token_a_change) > 0 or abs(token_b_change) > 0:
                event_type = 'add' if token_a_change > 0 else 'remove'
                
                # Calculate risk score
                risk_score = self._calculate_event_risk(
                    event_type,
                    token_a_change,
                    token_b_change,
                    price_change,
                    old_state,
                    new_state
                )
                
                if risk_score > 0:
                    events.append(LiquidityEvent(
                        pool_address=new_state.pool_address,
                        event_type=event_type,
                        timestamp=new_state.last_updated,
                        amount_token_a=token_a_change,
                        amount_token_b=token_b_change,
                        price_impact=price_change,
                        tx_signature="",  # Would be filled from actual tx data
                        wallet_address="",  # Would be filled from actual tx data
                        risk_score=risk_score
                    ))
            
            # Update volatility tracking
            self._update_volatility_metrics(new_state.pool_address, price_change)
            
        except Exception as e:
            logger.error(f"Error analyzing state change: {e}")
            
        return events

    def _calculate_event_risk(
        self,
        event_type: str,
        token_a_change: float,
        token_b_change: float,
        price_change: float,
        old_state: PoolState,
        new_state: PoolState
    ) -> float:
        """Calculate risk score for a liquidity event."""
        try:
            # Base risk factors
            size_factor = min(1.0, abs(token_a_change) / old_state.token_a_amount)
            price_impact_factor = min(1.0, abs(price_change))
            
            # Calculate temporal risk factor
            temporal_risk = self._calculate_temporal_risk(
                new_state.pool_address,
                event_type,
                new_state.last_updated
            )
            
            # Calculate volatility risk factor
            volatility_risk = self._calculate_volatility_risk(
                new_state.pool_address
            )
            
            # Weight the factors
            risk_score = (
                size_factor * 0.3 +
                price_impact_factor * 0.3 +
                temporal_risk * 0.2 +
                volatility_risk * 0.2
            )
            
            return risk_score
            
        except Exception as e:
            logger.error(f"Error calculating event risk: {e}")
            return 0.0

    def _calculate_temporal_risk(
        self,
        pool_address: str,
        event_type: str,
        timestamp: datetime
    ) -> float:
        """Calculate risk factor based on temporal patterns."""
        try:
            recent_events = [
                event for event in self.pool_events[pool_address]
                if event.timestamp > timestamp - timedelta(hours=24)
            ]
            
            if not recent_events:
                return 0.0
            
            # Calculate event frequency
            event_frequency = len(recent_events) / 24.0  # Events per hour
            
            # Calculate time since last similar event
            similar_events = [
                event for event in recent_events
                if event.event_type == event_type
            ]
            
            if similar_events:
                time_since_last = (
                    timestamp - max(event.timestamp for event in similar_events)
                ).total_seconds() / 3600  # Hours
                
                time_factor = np.exp(-time_since_last / 2)  # Decay factor
            else:
                time_factor = 0.0
            
            return min(1.0, (event_frequency * 0.5 + time_factor * 0.5))
            
        except Exception as e:
            logger.error(f"Error calculating temporal risk: {e}")
            return 0.0

    def _calculate_volatility_risk(self, pool_address: str) -> float:
        """Calculate risk factor based on pool volatility."""
        try:
            if pool_address not in self.volatility_windows:
                return 0.0
            
            recent_volatility = self.volatility_windows[pool_address][-1]
            volatility_baseline = np.mean(self.volatility_windows[pool_address])
            
            if volatility_baseline == 0:
                return 0.0
            
            volatility_ratio = recent_volatility / volatility_baseline
            return min(1.0, volatility_ratio - 1)
            
        except Exception as e:
            logger.error(f"Error calculating volatility risk: {e}")
            return 0.0

    def _update_volatility_metrics(self, pool_address: str, price_change: float) -> None:
        """Update volatility tracking for a pool."""
        try:
            window = self.volatility_windows[pool_address]
            window.append(abs(price_change))
            
            if len(window) > 360:  # 1 hour of 10-second intervals
                window.pop(0)
                
        except Exception as e:
            logger.error(f"Error updating volatility metrics: {e}")

    async def get_pool_analysis(self, pool_address: str) -> Dict:
        """Get comprehensive analysis for a specific pool."""
        try:
            if pool_address not in self.tracked_pools:
                return {"error": "Pool not tracked"}
            
            pool_state = self.tracked_pools[pool_address]
            recent_events = self.pool_events[pool_address][-100:]  # Last 100 events
            
            return {
                "pool_state": pool_state.__dict__,
                "recent_events": [event.__dict__ for event in recent_events],
                "risk_metrics": {
                    "current_volatility": self._get_current_volatility(pool_address),
                    "event_frequency": self._get_event_frequency(pool_address),
                    "risk_level": self._get_risk_level(pool_address)
                },
                "price_metrics": {
                    "price_change_24h": self._calculate_price_change_24h(pool_address),
                    "volume_24h": pool_state.volume_24h,
                    "tvl": pool_state.total_value_locked
                }
            }
            
        except Exception as e:
            logger.error(f"Error getting pool analysis: {e}")
            return {"error": str(e)}

    def _get_risk_level(self, pool_address: str) -> str:
        """Get current risk level classification for a pool."""
        try:
            recent_events = [
                event for event in self.pool_events[pool_address]
                if event.timestamp > datetime.now() - timedelta(hours=24)
            ]
            
            if not recent_events:
                return "low"
            
            avg_risk = np.mean([event.risk_score for event in recent_events])
            
            if avg_risk >= 0.8:
                return "critical"
            el            if avg_risk >= 0.6:
                return "high"
            elif avg_risk >= 0.4:
                return "medium"
            return "low"
            
        except Exception as e:
            logger.error(f"Error calculating risk level: {e}")
            return "unknown"

    def _get_current_volatility(self, pool_address: str) -> float:
        """Calculate current volatility for a pool."""
        try:
            if pool_address not in self.volatility_windows:
                return 0.0
                
            recent_changes = self.volatility_windows[pool_address]
            if not recent_changes:
                return 0.0
                
            return np.std(recent_changes)
            
        except Exception as e:
            logger.error(f"Error calculating current volatility: {e}")
            return 0.0

    def _get_event_frequency(self, pool_address: str) -> float:
        """Calculate event frequency per hour for last 24 hours."""
        try:
            recent_events = [
                event for event in self.pool_events[pool_address]
                if event.timestamp > datetime.now() - timedelta(hours=24)
            ]
            
            return len(recent_events) / 24.0
            
        except Exception as e:
            logger.error(f"Error calculating event frequency: {e}")
            return 0.0

    def _calculate_price_change_24h(self, pool_address: str) -> float:
        """Calculate 24-hour price change percentage."""
        try:
            price_history = self.price_history[pool_address]
            if len(price_history) < 2:
                return 0.0
                
            current_price = price_history[-1]
            old_price = price_history[0]
            
            if old_price == 0:
                return 0.0
                
            return ((current_price - old_price) / old_price) * 100
            
        except Exception as e:
            logger.error(f"Error calculating price change: {e}")
            return 0.0

    async def _process_pool_events(self, events: List[LiquidityEvent]) -> None:
        """Process and store detected pool events."""
        for event in events:
            try:
                # Store the event
                self.pool_events[event.pool_address].append(event)
                
                # Update wallet activity tracking
                if event.wallet_address:
                    wallet_data = self.wallet_activity[event.wallet_address]
                    wallet_data['pool_interactions'] += 1
                    wallet_data['total_volume_usd'] += (
                        event.amount_token_a * self.tracked_pools[event.pool_address].last_price +
                        event.amount_token_b
                    )
                    wallet_data['last_seen'] = event.timestamp
                    wallet_data['risk_score'] = max(
                        wallet_data['risk_score'],
                        event.risk_score
                    )
                
                # Emit high-risk event notifications
                if event.risk_score >= self.risk_threshold:
                    await self._emit_risk_notification(event)
                    
            except Exception as e:
                logger.error(f"Error processing pool event: {e}")

    async def _emit_risk_notification(self, event: LiquidityEvent) -> None:
        """Emit notification for high-risk pool events."""
        try:
            notification = {
                "type": "high_risk_pool_event",
                "severity": "high" if event.risk_score >= 0.8 else "medium",
                "pool_address": event.pool_address,
                "event_type": event.event_type,
                "risk_score": event.risk_score,
                "timestamp": event.timestamp.isoformat(),
                "details": {
                    "price_impact": event.price_impact,
                    "amount_token_a": event.amount_token_a,
                    "amount_token_b": event.amount_token_b,
                    "wallet_address": event.wallet_address
                }
            }
            
            # Log the notification (in production, this would be sent to a notification service)
            logger.warning(f"High-risk pool event detected: {json.dumps(notification)}")
            
        except Exception as e:
            logger.error(f"Error emitting risk notification: {e}")

    def _is_raydium_pool(self, pool_address: str) -> bool:
        """Check if pool belongs to Raydium DEX."""
        try:
            # Implementation would check pool program ID
            # For now, return based on tracked pool data
            pool_state = self.tracked_pools.get(pool_address)
            return pool_state is not None
            
        except Exception as e:
            logger.error(f"Error checking pool type: {e}")
            return False

    def _decode_raydium_pool_data(self, data: bytes) -> PoolState:
        """Decode Raydium pool account data."""
        try:
            # Implement Raydium-specific pool data decoding
            # This would parse the binary data according to Raydium's pool layout
            raise NotImplementedError("Raydium pool data decoding not implemented")
            
        except Exception as e:
            logger.error(f"Error decoding Raydium pool data: {e}")
            raise

    def _decode_orca_pool_data(self, data: bytes) -> PoolState:
        """Decode Orca pool account data."""
        try:
            # Implement Orca-specific pool data decoding
            # This would parse the binary data according to Orca's pool layout
            raise NotImplementedError("Orca pool data decoding not implemented")
            
        except Exception as e:
            logger.error(f"Error decoding Orca pool data: {e}")
            raise

if __name__ == "__main__":
    # Example usage
    async def main():
        # Initialize RPC client
        client = AsyncClient("https://api.mainnet-beta.solana.com")
        
        # Create tracker instance
        tracker = LiquidityTracker(
            rpc_client=client,
            min_pool_size_usd=10000,
            scan_interval=10,
            risk_threshold=0.7
        )
        
        # Start tracking
        await tracker.start_tracking()
        
    asyncio.run(main())