Update app.py

app.py

@@ -2,7 +2,7 @@ import streamlit as st
 import yfinance as yf
 import pandas as pd
 
-@st.cache_resource
+@st.experimental_singleton
 def get_sp500_list():
  table = pd.read_html('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
  return table[0]['Symbol'].tolist()
@@ -14,13 +14,15 @@ def fetch_stock_data(ticker_symbol):
  ticker = yf.Ticker(ticker_symbol)
  info = ticker.info
  financials = {
- 'P/E Ratio': info.get('forwardPE', None),
- 'P/B Ratio': info.get('priceToBook', None),
- 'P/S Ratio': info.get('priceToSalesTrailing12Months', None),
- 'Debt to Equity Ratio': info.get('debtToEquity', None),
- 'Return on Equity': info.get('returnOnEquity', None),
- 'Book-to-Market Ratio': 1 / info.get('priceToBook', float('nan')) if info.get('priceToBook') else None
+ 'P/E Ratio': info.get('forwardPE'),
+ 'P/B Ratio': info.get('priceToBook'),
+ 'P/S Ratio': info.get('priceToSalesTrailing12Months'),
+ 'Debt to Equity Ratio': info.get('debtToEquity'),
+ 'Return on Equity': info.get('returnOnEquity'),
+ 'Book-to-Market Ratio': 1 / info.get('priceToBook') if info.get('priceToBook') else None
  }
+ # Debug: Print to see if financials are fetched correctly
+ print(f"Financials for {ticker_symbol}: {financials}")
  return financials, info
 
 def compare_to_index(stock_ratios, index_averages):
@@ -63,34 +65,47 @@ sp500_list = get_sp500_list()
 sp500_averages = load_sp500_averages('sp500_averages.csv')
 
 scores_df = calculate_combined_scores_for_stocks(sp500_list, sp500_averages)
+
+# Debug: Print the DataFrame before filtering to see its content
+print("Scores DataFrame before filtering:", scores_df.head())
+
 required_columns = ['P/E Ratio', 'P/B Ratio', 'P/S Ratio', 'Debt to Equity Ratio', 'Return on Equity', 'Book-to-Market Ratio']
 
-scores_df_filtered = filter_incomplete_stocks(scores_df, required_columns)
+# Attempt a lenient filtering approach or skip filtering to debug
+# scores_df_filtered = filter_incomplete_stocks(scores_df, required_columns)
+scores_df_filtered = scores_df # Temporarily bypass filtering to debug
 scores_df_sorted = scores_df_filtered.sort_values(by='Combined Score', ascending=False)
 
+# Debug: Print the DataFrame after sorting to see if it's empty
+print("Scores DataFrame after sorting:", scores_df_sorted.head())
+
 col1, col2 = st.columns([3, 5])
 
 with col1:
  st.subheader("Stock Overview")
- styled_scores_df = scores_df_sorted.style.applymap(color_combined_score, subset=['Combined Score'])
- st.dataframe(styled_scores_df)
+ if not scores_df_sorted.empty:
+ styled_scores_df = scores_df_sorted.style.applymap(color_combined_score, subset=['Combined Score'])
+ st.dataframe(styled_scores_df)
+ else:
+ st.write("No data available after filtering.")
 
 with col2:
  st.subheader("Stock Details")
- sorted_tickers = scores_df_sorted['Stock'].tolist()
- ticker_symbol = st.selectbox('Select a stock for details', options=sorted_tickers)
- if ticker_symbol:
- with st.spinner(f'Fetching data for {ticker_symbol}...'):
- stock_data, info = fetch_stock_data(ticker_symbol)
- comparison, _ = compare_to_index(stock_data, sp500_averages)
- 
- st.write(f"**{info.get('longName', 'N/A')}** ({ticker_symbol})")
- st.write(info.get('longBusinessSummary', 'N/A'))
- 
- for ratio in required_columns:
- value = stock_data.get(ratio, 'N/A')
- average = sp500_averages.loc[ratio, 'Average'] if ratio in sp500_averages.index else 'N/A'
- status = comparison.get(ratio, 'N/A')
- st.write(f"{ratio}: {value} (Your Ratio) | {average} (S&P 500 Avg) - {status}")
-
-
+ if not scores_df_sorted.empty:
+ sorted_tickers = scores_df_sorted['Stock'].tolist()
+ ticker_symbol = st.selectbox('Select a stock for details', options=sorted_tickers)
+ if ticker_symbol:
+ with st.spinner(f'Fetching data for {ticker_symbol}...'):
+ stock_data, info = fetch_stock_data(ticker_symbol)
+ comparison, _ = compare_to_index(stock_data, sp500_averages)
+ 
+ st.write(f"**{info.get('longName', 'N/A')}** ({ticker_symbol})")
+ st.write(info.get('longBusinessSummary', 'N/A'))
+ 
+ for ratio in required_columns:
+ value = stock_data.get(ratio, 'N/A')
+ average = sp500_averages.loc[ratio, 'Average'] if ratio in sp500_averages.index else 'N/A'
+ status = comparison.get(ratio, 'N/A')
+ st.write(f"{ratio}: {value} (Your Ratio) | {average} (S&P 500 Avg) - {status}")
+ else:
+ st.write("No stocks to display.")