import pandas as pd
import numpy as np
import yfinance as yf
from datetime import datetime, timedelta

class GrahamValueStrategy:
    """
    格雷厄姆价值投资策略实现
    核心指标：
    1. 市盈率(P/E) < 15
    2. 市净率(P/B) < 1.5
    3. 资产负债率 < 50%
    4. 当前股价 < 净流动资产价值(NCAV)的2/3
    """
    
    def __init__(self, symbols):
        self.symbols = symbols
        self.results = []
    
    def calculate_ncav(self, balance_sheet, market_cap):
        """计算净流动资产价值(NCAV)"""
        try:
            current_assets = balance_sheet.loc['Total Current Assets'][0]
            total_liabilities = balance_sheet.loc['Total Liabilities Net Minority Interest'][0]
            ncav = current_assets - total_liabilities
            ncav_per_share = ncav / balance_sheet.loc['Common Stock'][0]
            return ncav_per_share
        except:
            return None
    
    def analyze_stock(self, symbol):
        """分析单只股票是否符合格雷厄姆标准"""
        try:
            stock = yf.Ticker(symbol)
            
            # 获取基本面数据
            info = stock.info
            financials = stock.financials
            balance_sheet = stock.balance_sheet
            
            # 提取关键指标
            pe_ratio = info.get('trailingPE', None)
            pb_ratio = info.get('priceToBook', None)
            debt_to_equity = info.get('debtToEquity', None)
            current_price = info.get('currentPrice', None)
            market_cap = info.get('marketCap', None)
            
            # 计算NCAV
            ncav_per_share = self.calculate_ncav(balance_sheet, market_cap)
            
            # 应用格雷厄姆标准
            criteria = {
                'symbol': symbol,
                'pe_ok': pe_ratio is not None and pe_ratio < 15,
                'pb_ok': pb_ratio is not None and pb_ratio < 1.5,
                'debt_ok': debt_to_equity is not None and debt_to_equity < 0.5,
                'ncav_ok': ncav_per_share is not None and current_price < (ncav_per_share * 2/3),
                'current_price': current_price,
                'pe_ratio': pe_ratio,
                'pb_ratio': pb_ratio,
                'debt_to_equity': debt_to_equity,
                'ncav_per_share': ncav_per_share
            }
            
            # 计算综合得分（符合的条件数量）
            criteria['score'] = sum([
                criteria['pe_ok'],
                criteria['pb_ok'], 
                criteria['debt_ok'],
                criteria['ncav_ok']
            ])
            
            return criteria
            
        except Exception as e:
            print(f"分析 {symbol} 时出错: {str(e)}")
            return None
    
    def run_screening(self):
        """运行股票筛选"""
        print("开始格雷厄姆价值投资策略筛选...")
        print("-" * 80)
        
        for symbol in self.symbols:
            result = self.analyze_stock(symbol)
            if result:
                self.results.append(result)
                
                # 打印结果
                status = "✓" if result['score'] >= 3 else "✗"
                print(f"{status} {symbol:6} | "
                      f"PE: {result['pe_ratio']:6.2f} | "
                      f"PB: {result['pb_ratio']:6.2f} | "
                      f"负债率: {result['debt_to_equity']:6.2f} | "
                      f"得分: {result['score']}/4")
        
        return self.results
    
    def get_recommendations(self, min_score=3):
        """获取推荐股票列表"""
        recommendations = [r for r in self.results if r['score'] >= min_score]
        
        print(f"\n推荐股票（得分>={min_score}）:")
        print("=" * 80)
        for rec in sorted(recommendations, key=lambda x: x['score'], reverse=True):
            print(f"{rec['symbol']:6} | 价格: ${rec['current_price']:7.2f} | "
                  f"得分: {rec['score']}/4 | "
                  f"NCAV/股: ${rec['ncav_per_share']:7.2f if rec['ncav_per_share'] else 'N/A':>7}")

# 使用示例
if __name__ == "__main__":
    # 示例股票列表（实际使用时替换为关注的股票）
    symbols = ['AAPL', 'MSFT', 'GOOGL', 'BRK-B', 'JNJ', 'XOM', 'WMT', 'PG']
    
    # 创建策略实例并运行
    strategy = GrahamValueStrategy(symbols)
    results = strategy.run_screening()
    
    # 获取推荐
    strategy.get_recommendations(min_score=3)

这个实现包含了格雷厄姆价值投资的四个核心标准：低市盈率、低市净率、低负债率，以及股价低于净流动资产价值。代码使用yfinance获取实时财务数据，计算各项指标，并给出综合评分。你可以通过修改symbols列表来筛选自己关注的股票。

建议：实际投资前请结合更多基本面分析和风险评估。