#!/usr/bin/env python3
"""
Liquidity Pool Economics Analysis Tool
Analyzes LP economics and fee structure
"""

import json
import sys
from typing import Dict, List
from dataclasses import dataclass

@dataclass
class LPEconomicsAnalysis:
    """LP economics analysis result"""
    total_liquidity: float
    pending_claims: float
    available_liquidity: float
    liquidity_ratio: float
    fee_rate_bps: float
    daily_volume: float
    daily_fees: float
    apy_estimate: float
    recommendation: str

def analyze_lp_economics(
    total_liquidity: float,
    pending_claims: float,
    fee_rate_bps: float = 5.0,  # 0.05%
    daily_volume: float = 100.0,  # ETH per day
    annual_days: int = 365
) -> LPEconomicsAnalysis:
    """
    Analyze liquidity pool economics
    
    Args:
        total_liquidity: Total liquidity in pool (ETH)
        pending_claims: Pending claims amount (ETH)
        fee_rate_bps: Fee rate in basis points
        daily_volume: Daily bridge volume (ETH)
        annual_days: Days per year for APY calculation
    
    Returns:
        Analysis result
    """
    available_liquidity = total_liquidity - pending_claims
    liquidity_ratio = available_liquidity / pending_claims if pending_claims > 0 else float('inf')
    
    # Fee calculations
    daily_fees = daily_volume * (fee_rate_bps / 10000)
    annual_fees = daily_fees * annual_days
    
    # APY estimate (simplified)
    if total_liquidity > 0:
        apy_estimate = (annual_fees / total_liquidity) * 100
    else:
        apy_estimate = 0.0
    
    # Recommendations
    recommendations = []
    
    if liquidity_ratio < 1.1:
        recommendations.append("Liquidity ratio below minimum - encourage LP deposits")
    
    if apy_estimate < 2.0:
        recommendations.append(f"Low APY ({apy_estimate:.2f}%) - consider increasing fee rate")
    elif apy_estimate > 20.0:
        recommendations.append(f"High APY ({apy_estimate:.2f}%) - may be sustainable")
    
    if available_liquidity < pending_claims:
        recommendations.append("Insufficient available liquidity - critical")
    
    recommendation = "; ".join(recommendations) if recommendations else "Economics look healthy"
    
    return LPEconomicsAnalysis(
        total_liquidity=total_liquidity,
        pending_claims=pending_claims,
        available_liquidity=available_liquidity,
        liquidity_ratio=liquidity_ratio,
        fee_rate_bps=fee_rate_bps,
        daily_volume=daily_volume,
        daily_fees=daily_fees,
        apy_estimate=apy_estimate,
        recommendation=recommendation
    )

def print_analysis(analysis: LPEconomicsAnalysis):
    """Print LP economics analysis"""
    print("=" * 80)
    print("Liquidity Pool Economics Analysis")
    print("=" * 80)
    print(f"Total Liquidity:      {analysis.total_liquidity:>15.2f} ETH")
    print(f"Pending Claims:       {analysis.pending_claims:>15.2f} ETH")
    print(f"Available Liquidity:  {analysis.available_liquidity:>15.2f} ETH")
    print(f"Liquidity Ratio:      {analysis.liquidity_ratio:>15.2f}")
    print(f"Fee Rate:             {analysis.fee_rate_bps:>15.2f} bps ({analysis.fee_rate_bps/100:.2f}%)")
    print(f"Daily Volume:         {analysis.daily_volume:>15.2f} ETH")
    print(f"Daily Fees:           {analysis.daily_fees:>15.4f} ETH")
    print(f"Estimated APY:        {analysis.apy_estimate:>15.2f}%")
    print("-" * 80)
    print(f"Recommendation: {analysis.recommendation}")
    print("=" * 80)

def main():
    """Main entry point"""
    # Example parameters
    total_liquidity = 1000.0  # ETH
    pending_claims = 500.0    # ETH
    daily_volume = 100.0     # ETH per day
    
    # Analyze LP economics
    analysis = analyze_lp_economics(
        total_liquidity=total_liquidity,
        pending_claims=pending_claims,
        daily_volume=daily_volume
    )
    
    # Print results
    print_analysis(analysis)
    
    # Optional: Export to JSON
    if len(sys.argv) > 1 and sys.argv[1] == '--json':
        output = {
            'total_liquidity': analysis.total_liquidity,
            'pending_claims': analysis.pending_claims,
            'available_liquidity': analysis.available_liquidity,
            'liquidity_ratio': analysis.liquidity_ratio,
            'daily_fees': analysis.daily_fees,
            'apy_estimate': analysis.apy_estimate,
            'recommendation': analysis.recommendation
        }
        print(json.dumps(output, indent=2))

if __name__ == '__main__':
    main()

