#!/usr/bin/env python3
"""
Calculate returns for all trades and display summary statistics.
"""

import argparse
import logging

from pote.analytics.metrics import PerformanceMetrics
from pote.db import get_session

logging.basicConfig(level=logging.INFO, format="%(message)s")
logger = logging.getLogger(__name__)


def main():
    parser = argparse.ArgumentParser(description="Calculate returns for all trades")
    parser.add_argument(
        "--window",
        type=int,
        default=90,
        help="Return window in days (default: 90)",
    )
    parser.add_argument(
        "--benchmark",
        default="SPY",
        help="Benchmark ticker (default: SPY)",
    )
    parser.add_argument(
        "--top",
        type=int,
        default=10,
        help="Number of top performers to show (default: 10)",
    )
    args = parser.parse_args()

    with next(get_session()) as session:
        metrics = PerformanceMetrics(session)

        # Get system-wide statistics
        logger.info("\n" + "=" * 70)
        logger.info("  POTE System-Wide Performance Analysis")
        logger.info("=" * 70)

        summary = metrics.summary_statistics(
            window_days=args.window,
            benchmark=args.benchmark,
        )

        logger.info(f"\n📊 OVERALL STATISTICS")
        logger.info("-" * 70)
        logger.info(f"Total Officials:  {summary['total_officials']}")
        logger.info(f"Total Securities: {summary['total_securities']}")
        logger.info(f"Total Trades:     {summary['total_trades']}")
        logger.info(f"Trades Analyzed:  {summary.get('total_trades', 0)}")
        logger.info(f"Window:           {summary['window_days']} days")
        logger.info(f"Benchmark:        {summary['benchmark']}")

        if summary.get('avg_alpha') is not None:
            logger.info(f"\n🎯 AGGREGATE PERFORMANCE")
            logger.info("-" * 70)
            logger.info(f"Average Alpha:        {float(summary['avg_alpha']):+.2f}%")
            logger.info(f"Median Alpha:         {float(summary['median_alpha']):+.2f}%")
            logger.info(f"Max Alpha:            {float(summary['max_alpha']):+.2f}%")
            logger.info(f"Min Alpha:            {float(summary['min_alpha']):+.2f}%")
            logger.info(f"Beat Market Rate:     {summary['beat_market_rate']:.1%}")

        # Top performers
        logger.info(f"\n🏆 TOP {args.top} PERFORMERS (by Alpha)")
        logger.info("-" * 70)

        top_performers = metrics.top_performers(
            window_days=args.window,
            benchmark=args.benchmark,
            limit=args.top,
        )

        for i, perf in enumerate(top_performers, 1):
            name = perf['name'][:25].ljust(25)
            party = perf['party'][:3]
            trades = perf['trades_analyzed']
            alpha = float(perf['avg_alpha'])
            logger.info(f"{i:2d}. {name} ({party}) | {trades:2d} trades | Alpha: {alpha:+6.2f}%")

        # Sector analysis
        logger.info(f"\n📊 PERFORMANCE BY SECTOR")
        logger.info("-" * 70)

        sectors = metrics.sector_analysis(
            window_days=args.window,
            benchmark=args.benchmark,
        )

        for sector_data in sectors:
            sector = sector_data['sector'][:20].ljust(20)
            count = sector_data['trade_count']
            alpha = float(sector_data['avg_alpha'])
            win_rate = sector_data['win_rate']
            logger.info(f"{sector} | {count:3d} trades | Alpha: {alpha:+6.2f}% | Win: {win_rate:.1%}")

        # Timing analysis
        logger.info(f"\n⏱️  DISCLOSURE TIMING")
        logger.info("-" * 70)

        timing = metrics.timing_analysis()
        if 'error' not in timing:
            logger.info(f"Average Disclosure Lag:  {timing['avg_disclosure_lag_days']:.1f} days")
            logger.info(f"Median Disclosure Lag:   {timing['median_disclosure_lag_days']} days")
            logger.info(f"Max Disclosure Lag:      {timing['max_disclosure_lag_days']} days")

        logger.info("\n" + "=" * 70 + "\n")


if __name__ == "__main__":
    main()