import json
import time
import random
from datetime import datetime
from typing import Dict, Any, List
from storage_manager import STORAGE_DIR

TRADES_FILE = STORAGE_DIR / "trades" / "trades.json"
TRADES_FILE.parent.mkdir(parents=True, exist_ok=True)

# Default Mock Portfolio
DEFAULT_PORTFOLIO = {
    "total_aum_usdc": 14250000.0,
    "cash_usdc": 3562500.0,
    "pnl_24h_usdc": 482150.0,
    "pnl_24h_percent": 3.49,
    "sharpe_ratio": 3.42,
    "max_drawdown": 4.1,
    "positions": [
        {"symbol": "SOL", "name": "Solana", "amount": 54200.0, "price": 148.50, "value_usdc": 8048700.0, "allocation": 56.5},
        {"symbol": "JUP", "name": "Jupiter", "amount": 1350000.0, "price": 0.985, "value_usdc": 1329750.0, "allocation": 9.3},
        {"symbol": "RAY", "name": "Raydium", "amount": 420000.0, "price": 2.15, "value_usdc": 903000.0, "allocation": 6.3},
        {"symbol": "WIF", "name": "dogwifhat", "amount": 220000.0, "price": 1.84, "value_usdc": 404800.0, "allocation": 2.8},
        {"symbol": "USDC", "name": "USD Coin", "amount": 3563750.0, "price": 1.00, "value_usdc": 3563750.0, "allocation": 25.1},
    ]
}

class SolanaQuantEngine:
    def __init__(self):
        self.prices = {
            "SOL": 148.50,
            "JUP": 0.985,
            "RAY": 2.15,
            "WIF": 1.84,
            "BONK": 0.0000215,
        }

    def get_market_overview(self) -> Dict[str, Any]:
        # Small dynamic drift for live feel
        for k in self.prices:
            drift = random.uniform(-0.002, 0.002)
            self.prices[k] = round(self.prices[k] * (1 + drift), 4 if k != "BONK" else 8)

        arb_spreads = [
            {
                "pair": "SOL/USDC",
                "buy_venue": "Raydium CPMM",
                "sell_venue": "Orca Whirlpool",
                "buy_price": self.prices["SOL"],
                "sell_price": round(self.prices["SOL"] * 1.0042, 2),
                "spread_pct": 0.42,
                "net_profit_est": "$6,230",
                "confidence": "HIGH",
            },
            {
                "pair": "RAY/SOL",
                "buy_venue": "Phoenix CLOB",
                "sell_venue": "Jupiter Route",
                "buy_price": round(self.prices["RAY"] / self.prices["SOL"], 5),
                "sell_price": round((self.prices["RAY"] / self.prices["SOL"]) * 1.0031, 5),
                "spread_pct": 0.31,
                "net_profit_est": "$2,140",
                "confidence": "MEDIUM",
            },
            {
                "pair": "JUP/USDC",
                "buy_venue": "Meteora DLMM",
                "sell_venue": "Raydium CLMM",
                "buy_price": self.prices["JUP"],
                "sell_price": round(self.prices["JUP"] * 1.0028, 4),
                "spread_pct": 0.28,
                "net_profit_est": "$1,890",
                "confidence": "HIGH",
            }
        ]

        return {
            "timestamp": datetime.utcnow().isoformat(),
            "prices": self.prices,
            "arbitrage_opportunities": arb_spreads,
            "portfolio": DEFAULT_PORTFOLIO,
        }

    def execute_simulated_trade(self, symbol: str, side: str, amount_usdc: float, strategy: str = "AI_MOMENTUM") -> Dict[str, Any]:
        px = self.prices.get(symbol.upper(), 100.0)
        tokens = round(amount_usdc / px, 4)
        
        trade = {
            "trade_id": f"TX_{str(int(time.time() * 1000))[-8:]}",
            "timestamp": datetime.utcnow().isoformat(),
            "symbol": symbol.upper(),
            "side": side.upper(),
            "amount_usdc": amount_usdc,
            "executed_tokens": tokens,
            "execution_price": px,
            "venue": "Jupiter Swap Aggregator v6",
            "slippage_bps": random.randint(3, 12),
            "priority_fee_lamports": 150000,
            "strategy": strategy,
            "status": "CONFIRMED_ON_CHAIN",
        }

        # Persist to storage
        history = self.get_trade_history()
        history.insert(0, trade)
        try:
            TRADES_FILE.write_text(json.dumps(history[:50], indent=2), encoding="utf-8")
        except Exception:
            pass

        return trade

    def get_trade_history(self) -> List[Dict[str, Any]]:
        if TRADES_FILE.exists():
            try:
                return json.loads(TRADES_FILE.read_text(encoding="utf-8"))
            except Exception:
                pass
        
        # Initial Seed Trades
        seed = [
            {
                "trade_id": "TX_94827110",
                "timestamp": "2026-09-14T12:45:10Z",
                "symbol": "SOL",
                "side": "BUY",
                "amount_usdc": 250000.0,
                "executed_tokens": 1683.5,
                "execution_price": 148.50,
                "venue": "Raydium CPMM",
                "slippage_bps": 5,
                "strategy": "AI_MOMENTUM",
                "status": "CONFIRMED_ON_CHAIN"
            },
            {
                "trade_id": "TX_94823419",
                "timestamp": "2026-09-14T12:30:22Z",
                "symbol": "JUP",
                "side": "BUY",
                "amount_usdc": 120000.0,
                "executed_tokens": 121827.4,
                "execution_price": 0.985,
                "venue": "Jupiter Route",
                "slippage_bps": 4,
                "strategy": "DEX_ARBITRAGE",
                "status": "CONFIRMED_ON_CHAIN"
            },
            {
                "trade_id": "TX_94819201",
                "timestamp": "2026-09-14T12:10:05Z",
                "symbol": "RAY",
                "side": "SELL",
                "amount_usdc": 75000.0,
                "executed_tokens": 34883.7,
                "execution_price": 2.15,
                "venue": "Orca Whirlpool",
                "slippage_bps": 8,
                "strategy": "RISK_REBALANCE",
                "status": "CONFIRMED_ON_CHAIN"
            }
        ]
        return seed

solana_quant = SolanaQuantEngine()