#!/usr/bin/env python3
"""
🌐 國際貿易種子自動化系統
Ultimate Trade Seed Automation System
Version: 2.0
Start Time: 2024-12-18 18:11
"""

import datetime
import json
import time
import requests
import schedule
from typing import Dict, List, Any

# ==================== 配置 ====================
CONFIG = {
    'capital': {
        'total_usd': 42940,
        'risk_free': 10000,
        'active_seeds': 27000,
        'reserve': 5940
    },
    'schedule': {
        'financial_trades': 'every().hour',
        'physical_trades': [2, 6, 10, 14, 18, 22],
        'seed_scan': 'every(20).minutes',
        'research': [6, 10, 14, 18]
    },
    'risk_free_rate': 0.053,  # 5.3% 年化
    'minimum_return': 0.153,  # 15.3% 最低要求
}

# ==================== 種子類 ====================
class TradeSeed:
    """交易種子基類"""
    
    def __init__(self, seed_id: str, product: str, route: str):
        self.seed_id = seed_id
        self.product = product
        self.route = route
        self.created = datetime.datetime.now()
        self.score = 0
        self.status = 'discovered'
        self.financials = {}
        self.risks = {}
        
    def analyze(self):
        """Bull vs Bear 分析"""
        print(f"[{self.created.strftime('%H:%M')}] 分析種子 {self.seed_id}")
        
        # 模擬分析邏輯
        bull_points = self._analyze_bull()
        bear_points = self._analyze_bear()
        
        return {
            'bull': bull_points,
            'bear': bear_points,
            'decision': 'EXECUTE' if len(bull_points) > len(bear_points) else 'WAIT'
        }
    
    def _analyze_bull(self):
        return ['高需求', '低競爭', '穩定供應鏈']
    
    def _analyze_bear(self):
        return ['運費上漲風險', '季節性']
    
    def calculate_score(self):
        """計算種子評分"""
        # 基礎分數：超額回報
        excess_return = self.financials.get('expected_return', 0.15) - CONFIG['risk_free_rate']
        base_score = min(10, excess_return * 20)
        
        # 多維度評分
        dimensions = {
            'profitability': self.financials.get('margin', 0.2) * 10,
            'feasibility': 8.0 if self.financials.get('capital_required', 10000) < 20000 else 5.0,
            'risk': 10 - self.risks.get('total_risk', 5),
            'speed': 10 - (self.financials.get('cycle_days', 30) / 10)
        }
        
        weights = {
            'profitability': 0.25,
            'feasibility': 0.20,
            'risk': 0.20,
            'speed': 0.15
        }
        
        weighted_score = sum(dimensions[d] * weights.get(d, 0.1) for d in dimensions)
        self.score = round(min(10, weighted_score), 1)
        
        # 分級
        if self.score >= 8.5:
            self.rank = 'S'
        elif self.score >= 7.5:
            self.rank = 'A'
        elif self.score >= 6.5:
            self.rank = 'B'
        else:
            self.rank = 'C'
        
        return self.score

# ==================== 研究系統 ====================
class ResearchSystem:
    """市場研究系統"""
    
    def __init__(self):
        self.data_sources = {
            'xe_api': 'https://api.xe.com/rates',
            'freightos': 'https://api.freightos.com/rates',
            '1688': 'https://1688.com/api'  # 模擬
        }
        
    def scan_markets(self):
        """掃描市場機會"""
        print(f"\n📊 [{datetime.datetime.now().strftime('%H:%M')}] 開始市場掃描...")
        
        opportunities = []
        
        # 1. 檢查匯率機會
        forex_opps = self._check_forex()
        opportunities.extend(forex_opps)
        
        # 2. 檢查商品價差
        price_arb = self._check_price_arbitrage()
        opportunities.extend(price_arb)
        
        # 3. 檢查運費波動
        shipping_opps = self._check_shipping_rates()
        opportunities.extend(shipping_opps)
        
        print(f"   發現 {len(opportunities)} 個機會")
        return opportunities
    
    def _check_forex(self):
        """檢查外匯機會"""
        # 模擬 API 調用
        rates = {
            'USDJPY': 154.80,
            'USDTWD': 31.85,
            'USDCNY': 7.28
        }
        
        opportunities = []
        if rates['USDJPY'] > 155:
            opportunities.append({
                'type': 'forex',
                'pair': 'USDJPY',
                'action': 'SELL JPY',
                'expected_return': 0.18
            })
            
        return opportunities
    
    def _check_price_arbitrage(self):
        """檢查價格套利"""
        # 模擬價格比較
        products = [
            {
                'name': 'GaN充電器65W',
                'cost_1688': 8.50,
                'sell_amazon': 29.99,
                'margin': 0.43
            },
            {
                'name': '無線耳機',
                'cost_1688': 12.00,
                'sell_amazon': 39.99,
                'margin': 0.38
            }
        ]
        
        opportunities = []
        for p in products:
            if p['margin'] > 0.30:
                seed = TradeSeed(
                    seed_id=f"SEED_{datetime.datetime.now().strftime('%Y%m%d_%H%M')}",
                    product=p['name'],
                    route='China->USA'
                )
                seed.financials = {
                    'margin': p['margin'],
                    'expected_return': p['margin'] * 12,  # 年化
                    'capital_required': p['cost_1688'] * 500,  # MOQ
                    'cycle_days': 30
                }
                opportunities.append(seed)
                
        return opportunities
    
    def _check_shipping_rates(self):
        """檢查運費機會"""
        # 模擬運費查詢
        rates = {
            'Shanghai-LA': 3200,
            'Taiwan-LA': 3000,
            'Tokyo-LA': 2800
        }
        
        opportunities = []
        if rates['Taiwan-LA'] < 3100:
            opportunities.append({
                'type': 'shipping',
                'route': 'Taiwan-LA',
                'rate': rates['Taiwan-LA'],
                'opportunity': 'Low shipping cost window'
            })
            
        return opportunities
    
    def deep_research(self, seed: TradeSeed):
        """深度研究種子"""
        print(f"\n🔍 深度研究種子: {seed.seed_id}")
        
        # 1. 供應商驗證
        suppliers = self._verify_suppliers(seed.product)
        
        # 2. 完整成本計算
        total_cost = self._calculate_total_cost(seed)
        
        # 3. 市場需求驗證
        demand = self._validate_demand(seed.product)
        
        # 4. 風險評估
        risks = self._assess_risks(seed)
        
        seed.research_complete = True
        seed.suppliers = suppliers
        seed.total_cost = total_cost
        seed.demand = demand
        seed.risks = risks
        
        return seed
    
    def _verify_suppliers(self, product):
        """驗證供應商"""
        return [
            {'name': '深圳XX科技', 'rating': 8.5, 'moq': 500},
            {'name': '東莞YY電子', 'rating': 7.8, 'moq': 1000}
        ]
    
    def _calculate_total_cost(self, seed):
        """計算總成本"""
        costs = {
            'product': 8500,  # $8.5 * 1000
            'shipping': 3200,
            'customs': 550,
            'insurance': 35,
            'banking': 150,
            'total': 12435
        }
        return costs
    
    def _validate_demand(self, product):
        """驗證市場需求"""
        return {
            'amazon_bsr': 2500,
            'monthly_sales': 5000,
            'competition': 'medium'
        }
    
    def _assess_risks(self, seed):
        """評估風險"""
        return {
            'market_risk': 4,
            'operational_risk': 3,
            'regulatory_risk': 2,
            'total_risk': 3
        }

# ==================== 執行系統 ====================
class ExecutionSystem:
    """交易執行系統"""
    
    def __init__(self):
        self.active_seeds = []
        self.portfolio = CONFIG['capital'].copy()
        self.positions = []
        
    def execute_financial_trades(self):
        """執行金融交易（每小時）"""
        print(f"\n💱 [{datetime.datetime.now().strftime('%H:%M')}] 執行金融交易")
        
        # 檢查外匯機會
        if datetime.datetime.now().hour % 2 == 0:
            self._execute_forex_trade()
            
        # 更新對沖部位
        self._update_hedges()
        
    def execute_physical_trades(self):
        """執行實體貿易（每4小時）"""
        current_hour = datetime.datetime.now().hour
        if current_hour in CONFIG['schedule']['physical_trades']:
            print(f"\n📦 [{datetime.datetime.now().strftime('%H:%M')}] 執行實體貿易")
            
            # 執行高分種子
            for seed in self.active_seeds:
                if seed.rank == 'S' and seed.status == 'ready':
                    self._execute_trade(seed)
    
    def _execute_forex_trade(self):
        """執行外匯交易"""
        print("   執行 USD/JPY 套利...")
        self.positions.append({
            'type': 'forex',
            'pair': 'USDJPY',
            'size': 10000,
            'entry': 154.80,
            'time': datetime.datetime.now()
        })
        
    def _update_hedges(self):
        """更新對沖部位"""
        print("   檢查對沖需求...")
        
    def _execute_trade(self, seed):
        """執行實體貿易"""
        print(f"   執行種子 {seed.seed_id}: {seed.product}")
        seed.status = 'executing'
        
        # 記錄交易
        self.positions.append({
            'type': 'physical',
            'seed_id': seed.seed_id,
            'product': seed.product,
            'investment': seed.financials['capital_required'],
            'time': datetime.datetime.now()
        })

# ==================== 監控系統 ====================
class MonitoringSystem:
    """監控與報告系統"""
    
    def __init__(self):
        self.metrics = {
            'total_value': CONFIG['capital']['total_usd'],
            'daily_pnl': 0,
            'active_seeds': 0,
            'success_rate': 0
        }
        
    def update_metrics(self, execution_system):
        """更新績效指標"""
        self.metrics['active_seeds'] = len(execution_system.active_seeds)
        self.metrics['total_value'] = self._calculate_portfolio_value(execution_system)
        
    def _calculate_portfolio_value(self, execution_system):
        """計算組合價值"""
        value = execution_system.portfolio['risk_free'] * 1.053**(1/365)  # 日複利
        value += execution_system.portfolio['active_seeds']
        value += execution_system.portfolio['reserve']
        
        # 加上未實現損益
        for position in execution_system.positions:
            if position['type'] == 'forex':
                # 模擬匯率變動
                value += position['size'] * 0.001  # 0.1% 收益
                
        return round(value, 2)
    
    def generate_report(self):
        """生成報告"""
        report = f"""
╔══════════════════════════════════════╗
║     📊 交易系統狀態報告              ║
║     {datetime.datetime.now().strftime('%Y-%m-%d %H:%M')}            ║
╠══════════════════════════════════════╣
║ 💰 總資產: ${self.metrics['total_value']:,.2f}            ║
║ 📈 日收益: ${self.metrics['daily_pnl']:,.2f}              ║
║ 🌱 活躍種子: {self.metrics['active_seeds']}                    ║
║ ✅ 成功率: {self.metrics['success_rate']:.1%}              ║
╚══════════════════════════════════════╝
        """
        return report

# ==================== 主控制器 ====================
class TradingSystemController:
    """主系統控制器"""
    
    def __init__(self):
        self.research = ResearchSystem()
        self.execution = ExecutionSystem()
        self.monitoring = MonitoringSystem()
        self.running = False
        
        print("""
╔══════════════════════════════════════════════════════╗
║   🌐 國際貿易種子自動化系統 v2.0                    ║
║   International Trade Seed Automation System         ║
╚══════════════════════════════════════════════════════╝
        """)
        
    def initialize(self):
        """初始化系統"""
        print(f"\n⚙️ [{datetime.datetime.now().strftime('%H:%M')}] 初始化系統...")
        
        # 1. 載入現有種子
        print("   載入種子庫...")
        
        # 2. 設置定時任務
        self._setup_schedules()
        
        # 3. 初始掃描
        print("   執行初始市場掃描...")
        opportunities = self.research.scan_markets()
        
        # 4. 評分種子
        for opp in opportunities:
            if isinstance(opp, TradeSeed):
                opp.calculate_score()
                if opp.score >= 7.5:
                    self.execution.active_seeds.append(opp)
                    print(f"   ✅ 新種子 {opp.seed_id} (評分: {opp.score})")
        
        print(f"   系統就緒！發現 {len(self.execution.active_seeds)} 個可執行種子")
        
    def _setup_schedules(self):
        """設置定時任務"""
        # 每小時：金融交易
        schedule.every().hour.at(":00").do(self.execution.execute_financial_trades)
        
        # 每4小時：實體貿易
        for hour in CONFIG['schedule']['physical_trades']:
            schedule.every().day.at(f"{hour:02d}:00").do(self.execution.execute_physical_trades)
        
        # 每20分鐘：掃描種子
        schedule.every(20).minutes.do(self.scan_and_evaluate)
        
        # 每小時：生成報告
        schedule.every().hour.at(":30").do(self.generate_and_send_report)
        
    def scan_and_evaluate(self):
        """掃描並評估種子"""
        print(f"\n🔍 [{datetime.datetime.now().strftime('%H:%M')}] 掃描新種子...")
        
        opportunities = self.research.scan_markets()
        new_seeds = 0
        
        for opp in opportunities:
            if isinstance(opp, TradeSeed):
                opp.analyze()
                opp.calculate_score()
                
                if opp.score >= 7.5 and opp.seed_id not in [s.seed_id for s in self.execution.active_seeds]:
                    self.execution.active_seeds.append(opp)
                    new_seeds += 1
                    
                    # 深度研究高分種子
                    if opp.score >= 8.5:
                        self.research.deep_research(opp)
                        
        if new_seeds > 0:
            print(f"   發現 {new_seeds} 個新種子")
    
    def generate_and_send_report(self):
        """生成並發送報告"""
        self.monitoring.update_metrics(self.execution)
        report = self.monitoring.generate_report()
        print(report)
        
        # TODO: 發送到 Telegram
        # self.send_to_telegram(report)
    
    def run(self):
        """運行主循環"""
        self.running = True
        print(f"\n🚀 [{datetime.datetime.now().strftime('%H:%M')}] 系統啟動！")
        print("   按 Ctrl+C 停止\n")
        
        try:
            while self.running:
                # 執行定時任務
                schedule.run_pending()
                
                # 即時監控
                self._real_time_monitoring()
                
                time.sleep(30)  # 每30秒檢查一次
                
        except KeyboardInterrupt:
            self.shutdown()
    
    def _real_time_monitoring(self):
        """即時監控"""
        # 檢查風險
        for position in self.execution.positions:
            if position.get('type') == 'forex':
                # 檢查止損
                pass
                
    def shutdown(self):
        """關閉系統"""
        print(f"\n⚠️ [{datetime.datetime.now().strftime('%H:%M')}] 系統關閉中...")
        self.running = False
        
        # 保存狀態
        self._save_state()
        
        # 發送最終報告
        self.generate_and_send_report()
        
        print("   系統已安全關閉")
        
    def _save_state(self):
        """保存系統狀態"""
        state = {
            'timestamp': datetime.datetime.now().isoformat(),
            'portfolio': self.execution.portfolio,
            'positions': self.execution.positions,
            'active_seeds': [s.seed_id for s in self.execution.active_seeds],
            'metrics': self.monitoring.metrics
        }
        
        with open('system_state.json', 'w') as f:
            json.dump(state, f, indent=2, default=str)
            
        print("   狀態已保存到 system_state.json")

# ==================== 啟動點 ====================
if __name__ == "__main__":
    # 創建控制器
    controller = TradingSystemController()
    
    # 初始化
    controller.initialize()
    
    # 運行系統
    controller.run()