fix portfolio calculator

portfolio_calculator.py

@@ -15,6 +15,7 @@ import numpy as np
 import pandas as pd
 import yfinance as yf
 import streamlit as st
+import time
 
 
 # Constants
@@ -74,32 +75,62 @@ def fetch_historical_data(
         # Log the error but continue to fallback strategy
         print(f"Batch download failed: {str(e)}, trying individual downloads...")
 
-    # Strategy 2: Download one ticker at a time
-    st.info("Fetching data individually for each ticker...")
+    # Strategy 2: Download one ticker at a time with retries
+    st.info("Fetching data individually for each ticker (this may take a moment)...")
     individual_prices = {}
     failed_tickers = []
 
-    for ticker in ticker_list:
-        try:
-            # Use Ticker object for more reliable downloads
-            ticker_obj = yf.Ticker(ticker)
-            hist = ticker_obj.history(period=period)
-
-            if hist.empty:
-                failed_tickers.append(ticker)
-                continue
-
-            # Extract close prices
-            individual_prices[ticker] = hist['Close']
-
-        except Exception as e:
-            failed_tickers.append(ticker)
-            print(f"Failed to fetch {ticker}: {str(e)}")
-            continue
+    for idx, ticker in enumerate(ticker_list):
+        max_retries = 3
+        retry_delay = 2  # seconds
+
+        for attempt in range(max_retries):
+            try:
+                # Add delay between requests to avoid rate limiting (except first ticker)
+                if idx > 0 or attempt > 0:
+                    time.sleep(retry_delay)
+
+                # Use Ticker object for more reliable downloads
+                ticker_obj = yf.Ticker(ticker)
+
+                # Try different methods
+                if attempt == 0:
+                    # Method 1: history with period
+                    hist = ticker_obj.history(period=period)
+                elif attempt == 1:
+                    # Method 2: Try shorter period
+                    hist = ticker_obj.history(period="6mo")
+                else:
+                    # Method 3: Try start/end dates
+                    import datetime
+                    end_date = datetime.datetime.now()
+                    start_date = end_date - datetime.timedelta(days=365)
+                    hist = ticker_obj.history(start=start_date, end=end_date)
+
+                if not hist.empty:
+                    # Extract close prices
+                    individual_prices[ticker] = hist['Close']
+                    st.success(f"✅ {ticker}: {len(hist)} days of data")
+                    break  # Success, exit retry loop
+                else:
+                    if attempt < max_retries - 1:
+                        st.warning(f"⚠️ {ticker}: No data, retrying... (attempt {attempt + 1}/{max_retries})")
+                    else:
+                        st.error(f"❌ {ticker}: No data after {max_retries} attempts")
+                        failed_tickers.append(ticker)
+
+            except Exception as e:
+                if attempt < max_retries - 1:
+                    st.warning(f"⚠️ {ticker}: Error, retrying... (attempt {attempt + 1}/{max_retries})")
+                    retry_delay *= 2  # Exponential backoff
+                else:
+                    failed_tickers.append(ticker)
+                    st.error(f"❌ {ticker}: Failed after {max_retries} attempts")
+                    print(f"Failed to fetch {ticker}: {str(e)}")
 
     # Check if we got any data
     if not individual_prices:
-        return None, f"Could not fetch data for any tickers. Failed: {', '.join(failed_tickers)}"
+        return None, f"Could not fetch data for any tickers. Failed: {', '.join(failed_tickers)}\n\nTip: Try using the JSON editor to enter a smaller portfolio first, or try again in a few minutes."
 
     # Combine all individual price series
     prices_df = pd.DataFrame(individual_prices)