#!/usr/bin/env python3
"""
Analyze performance of a specific official.
"""

import argparse
import logging
import sys

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

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


def format_pct(value):
    """Format percentage."""
    return f"{float(value):+.2f}%"


def format_money(value):
    """Format money."""
    return f"${float(value):,.0f}"


def main():
    parser = argparse.ArgumentParser(description="Analyze official's trading performance")
    parser.add_argument("name", help="Official's name (e.g., 'Nancy Pelosi')")
    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)",
    )
    args = parser.parse_args()

    with next(get_session()) as session:
        # Find official
        official = (
            session.query(Official)
            .filter(Official.name.ilike(f"%{args.name}%"))
            .first()
        )

        if not official:
            logger.error(f"Official not found: {args.name}")
            logger.info("Available officials:")
            for o in session.query(Official).all():
                logger.info(f"  - {o.name}")
            sys.exit(1)

        # Get performance metrics
        metrics = PerformanceMetrics(session)
        perf = metrics.official_performance(
            official.id,
            window_days=args.window,
            benchmark=args.benchmark,
        )

        # Display results
        print()
        print("=" * 70)
        print(f"  {perf['name']} Performance Analysis")
        print("=" * 70)
        print()
        print(f"Party:    {perf['party']}")
        print(f"Chamber:  {perf['chamber']}")
        print(f"State:    {perf['state']}")
        print(f"Window:   {perf['window_days']} days")
        print(f"Benchmark: {perf['benchmark']}")
        print()

        if perf.get("trades_analyzed", 0) == 0:
            print("⚠️  No trades with sufficient price data to analyze")
            sys.exit(0)

        print("📊 TRADING ACTIVITY")
        print("-" * 70)
        print(f"Total Trades:     {perf['total_trades']}")
        print(f"Analyzed:         {perf['trades_analyzed']}")
        print(f"Buy Trades:       {perf['buy_trades']}")
        print(f"Sell Trades:      {perf['sell_trades']}")
        print(f"Total Value:      {format_money(perf['total_value_traded'])}")
        print()

        print("📈 PERFORMANCE METRICS")
        print("-" * 70)
        print(f"Average Return:   {format_pct(perf['avg_return'])}")
        print(f"Median Return:    {format_pct(perf['median_return'])}")
        print(f"Max Return:       {format_pct(perf['max_return'])}")
        print(f"Min Return:       {format_pct(perf['min_return'])}")
        print()

        print("🎯 VS MARKET ({})".format(perf['benchmark']))
        print("-" * 70)
        print(f"Average Alpha:    {format_pct(perf['avg_alpha'])}")
        print(f"Median Alpha:     {format_pct(perf['median_alpha'])}")
        print(f"Win Rate:         {perf['win_rate']:.1%}")
        print(f"Beat Market Rate: {perf['beat_market_rate']:.1%}")
        print()

        print("🏆 BEST/WORST TRADES")
        print("-" * 70)
        best = perf['best_trade']
        worst = perf['worst_trade']
        print(f"Best:  {best['ticker']:6s} {format_pct(best['return']):>10s}  ({best['date']})")
        print(f"Worst: {worst['ticker']:6s} {format_pct(worst['return']):>10s}  ({worst['date']})")
        print()

        # Signal
        alpha = float(perf['avg_alpha'])
        beat_rate = perf['beat_market_rate']

        print("🔔 RESEARCH SIGNAL")
        print("-" * 70)
        if alpha > 5 and beat_rate > 0.65:
            print("✅ FOLLOW_RESEARCH: Strong positive alpha with high win rate")
        elif alpha > 2 and beat_rate > 0.55:
            print("⭐ FOLLOW_RESEARCH: Moderate positive alpha")
        elif alpha < -5 or beat_rate < 0.35:
            print("🚨 AVOID_RISK: Negative alpha or poor performance")
        elif perf['total_trades'] < 5:
            print("👀 WATCH: Limited data, need more trades for confidence")
        else:
            print("📊 NEUTRAL: Performance close to market")
        print()

        print("=" * 70)


if __name__ == "__main__":
    main()