learn-trading/test_defeatbeta.py

#!/usr/bin/env python3
"""
Test script for defeatbeta-api demonstrating practical use cases
"""

import pandas as pd
from defeatbeta_api.data.ticker import Ticker

def analyze_stock(ticker_symbol):
    """Analyze a stock using defeatbeta-api"""
    print(f"\n{'='*60}")
    print(f"ANALYZING {ticker_symbol}")
    print(f"{'='*60}")
    
    # Create ticker instance
    ticker = Ticker(ticker_symbol)
    
    # 1. Get basic price and valuation
    print("\n1. PRICE AND VALUATION:")
    price_data = ticker.price()
    latest_price = price_data.iloc[-1]
    print(f"   Latest price: ${latest_price['close']:.2f}")
    print(f"   Date: {latest_price['report_date']}")
    print(f"   Volume: {latest_price['volume']:,}")
    
    # 2. Get TTM metrics
    ttm_eps = ticker.ttm_eps()
    if not ttm_eps.empty:
        latest_eps = ttm_eps.iloc[-1]['tailing_eps']
        print(f"\n2. TTM METRICS:")
        print(f"   TTM EPS: ${latest_eps:.2f}")
    
    ttm_pe = ticker.ttm_pe()
    if not ttm_pe.empty:
        latest_pe = ttm_pe.iloc[-1]['ttm_pe']
        print(f"   TTM P/E: {latest_pe:.2f}")
    
    # 3. Get market cap
    market_cap = ticker.market_capitalization()
    if not market_cap.empty:
        latest_mcap = market_cap.iloc[-1]['market_capitalization']
        print(f"   Market Cap: ${latest_mcap:,.2f}")
    
    # 4. Get financial ratios
    print(f"\n3. FINANCIAL RATIOS:")
    
    roe = ticker.roe()
    if not roe.empty:
        latest_roe = roe.iloc[-1]['roe']
        print(f"   ROE: {latest_roe:.2%}")
    
    roic = ticker.roic()
    if not roic.empty:
        latest_roic = roic.iloc[-1]['roic']
        print(f"   ROIC: {latest_roic:.2%}")
    
    wacc = ticker.wacc()
    if not wacc.empty:
        latest_wacc = wacc.iloc[-1]['wacc']
        print(f"   WACC: {latest_wacc:.2%}")
    
    # 5. Get beta
    beta_data = ticker.beta()
    if not beta_data.empty:
        latest_beta = beta_data.iloc[-1]['beta']
        print(f"   Beta (5Y): {latest_beta:.2f}")
    
    # 6. Get growth metrics
    print(f"\n4. GROWTH METRICS:")
    
    revenue_growth = ticker.quarterly_revenue_yoy_growth()
    if not revenue_growth.empty:
        latest_rev_growth = revenue_growth.iloc[-1]['yoy_growth']
        print(f"   Quarterly Revenue YoY Growth: {latest_rev_growth:.2%}")
    
    eps_growth = ticker.quarterly_eps_yoy_growth()
    if not eps_growth.empty:
        latest_eps_growth = eps_growth.iloc[-1]['yoy_growth']
        print(f"   Quarterly EPS YoY Growth: {latest_eps_growth:.2%}")
    
    # 7. Get margin metrics
    print(f"\n5. MARGIN METRICS:")
    
    gross_margin = ticker.quarterly_gross_margin()
    if not gross_margin.empty:
        latest_gross_margin = gross_margin.iloc[-1]['gross_margin']
        print(f"   Gross Margin: {latest_gross_margin:.2%}")
    
    net_margin = ticker.quarterly_net_margin()
    if not net_margin.empty:
        latest_net_margin = net_margin.iloc[-1]['net_margin']
        print(f"   Net Margin: {latest_net_margin:.2%}")
    
    # 8. Get income statement summary
    print(f"\n6. INCOME STATEMENT SUMMARY (Latest Quarter):")
    income_stmt = ticker.quarterly_income_statement()
    try:
        income_df = income_stmt.df()  # df is a method, not a property
        # Get key metrics
        key_metrics = ['Total Revenue', 'Gross Profit', 'Operating Income', 
                      'Net Income Common Stockholders', 'Diluted EPS']
        
        for metric in key_metrics:
            if metric in income_df['Breakdown'].values:
                row = income_df[income_df['Breakdown'] == metric]
                if not row.empty:
                    latest_q = row.iloc[0]['TTM']  # TTM column has latest
                    print(f"   {metric}: ${latest_q/1e6:,.2f}M" if 'Revenue' in metric or 'Profit' in metric or 'Income' in metric else f"   {metric}: ${latest_q:.2f}")
    except Exception as e:
        print(f"   Could not retrieve income statement details: {type(e).__name__}")
    
    # 9. Get revenue breakdown
    print(f"\n7. REVENUE BREAKDOWN (Latest):")
    revenue_segment = ticker.revenue_by_segment()
    if not revenue_segment.empty:
        latest_rev = revenue_segment.iloc[-1]
        print(f"   Total Revenue: ${latest_rev.iloc[2:].sum():,.0f}")
        for col in revenue_segment.columns[2:]:  # Skip symbol and report_date
            if col in latest_rev:
                value = latest_rev[col]
                if pd.notna(value):
                    print(f"   {col}: ${value:,.0f}")
    
    return ticker

def compare_stocks(tickers):
    """Compare multiple stocks"""
    print(f"\n{'='*60}")
    print(f"COMPARING STOCKS: {', '.join(tickers)}")
    print(f"{'='*60}")
    
    comparison_data = []
    
    for symbol in tickers:
        ticker = Ticker(symbol)
        
        # Get key metrics
        metrics = {'Symbol': symbol}
        
        # Price
        price_data = ticker.price()
        if not price_data.empty:
            metrics['Price'] = price_data.iloc[-1]['close']
        
        # TTM P/E
        ttm_pe = ticker.ttm_pe()
        if not ttm_pe.empty:
            metrics['P/E'] = ttm_pe.iloc[-1]['ttm_pe']
        
        # Market Cap
        market_cap = ticker.market_capitalization()
        if not market_cap.empty:
            metrics['Market Cap'] = market_cap.iloc[-1]['market_capitalization']
        
        # ROE
        roe = ticker.roe()
        if not roe.empty:
            metrics['ROE'] = roe.iloc[-1]['roe']
        
        # Revenue Growth
        rev_growth = ticker.quarterly_revenue_yoy_growth()
        if not rev_growth.empty:
            metrics['Rev Growth'] = rev_growth.iloc[-1]['yoy_growth']
        
        comparison_data.append(metrics)
    
    # Create comparison table
    df = pd.DataFrame(comparison_data)
    df.set_index('Symbol', inplace=True)
    
    # Format the table
    print(f"\n{df.to_string(float_format=lambda x: f'{x:,.2f}' if isinstance(x, (int, float)) else str(x))}")

def main():
    """Main function"""
    print("DEFEATBETA-API DEMONSTRATION")
    print("="*60)
    
    # Analyze individual stocks
    stocks = ['NVDA', 'TSLA', 'AAPL']
    
    for stock in stocks[:2]:  # Just analyze first 2 to keep output manageable
        analyze_stock(stock)
    
    # Compare all stocks
    compare_stocks(stocks)
    
    print(f"\n{'='*60}")
    print("API FEATURES DEMONSTRATED:")
    print("1. Price and volume data")
    print("2. TTM EPS and P/E ratios")
    print("3. Market capitalization")
    print("4. Financial ratios (ROE, ROIC, WACC)")
    print("5. Beta calculation")
    print("6. Growth metrics (Revenue, EPS YoY)")
    print("7. Margin analysis")
    print("8. Income statement summary")
    print("9. Revenue segmentation")
    print("10. Multi-stock comparison")
    print(f"{'='*60}")

if __name__ == "__main__":
    main()