Update app.py

app.py

@@ -1,37 +1,147 @@
 import streamlit as st
+import yfinance as yf
+import pandas as pd
+import time
 
-# Page Configuration
-st.set_page_config(
-    page_title="Indian Stock Market Dashboard",
-    page_icon="📈",
-    layout="wide"
-)
-
-st.title("📊 Indian Stock Market Dashboard")
-
-st.sidebar.title("Navigation")
-page = st.sidebar.radio(
-    "Choose a Section",
-    [
-        "Market Overview",
-        "Candlestick Patterns",
-        "Stock Predictions",
-        "Quantum Market Analysis"
+# 🎯 Define Indian Indices
+indian_indices = {
+    "NIFTY 50": "^NSEI",
+    "SENSEX": "^BSESN",
+    "BANK NIFTY": "^NSEBANK",
+    "NIFTY IT": "^CNXIT",
+    "NIFTY PHARMA": "^CNXPHARMA",
+    "NIFTY AUTO": "^CNXAUTO",
+    "NIFTY FMCG": "^CNXFMCG",
+    "NIFTY METAL": "^CNXMETAL",
+    "NIFTY ENERGY": "^CNXENERGY",
+    "NIFTY REALTY": "^CNXREALTY",
+    "NIFTY INFRA": "^CNXINFRA",
+    "NIFTY MEDIA": "^CNXMEDIA",
+    "NIFTY PSU BANK": "^CNXPSUBANK",
+}
+
+# 🔹 More Extensive List of Sector Stocks
+sector_stocks = {
+    "IT": [
+        "TCS.NS", "INFY.NS", "HCLTECH.NS", "TECHM.NS", "WIPRO.NS", "LTIM.NS", "COFORGE.NS", "PERSISTENT.NS",
+        "MINDTREE.NS", "MPHASIS.NS", "OFSS.NS", "CYIENT.NS", "ZENSARTECH.NS"
+    ],
+    "Banking & Finance": [
+        "HDFCBANK.NS", "ICICIBANK.NS", "SBIN.NS", "AXISBANK.NS", "KOTAKBANK.NS", "IDFCFIRSTB.NS", "PNB.NS",
+        "BANDHANBNK.NS", "FEDERALBNK.NS", "RBLBANK.NS", "YESBANK.NS", "INDUSINDBK.NS", "CANBK.NS"
+    ],
+    "Energy & Oil": [
+        "RELIANCE.NS", "ONGC.NS", "POWERGRID.NS", "NTPC.NS", "BPCL.NS", "IOC.NS", "GAIL.NS", "TATAPOWER.NS",
+        "JSWENERGY.NS", "NHPC.NS", "ADANIENERGY.NS", "ADANIGREEN.NS", "ADANITRANS.NS"
+    ],
+    "Automobile": [
+        "TATAMOTORS.NS", "M&M.NS", "MARUTI.NS", "HEROMOTOCO.NS", "EICHERMOT.NS", "BAJAJ-AUTO.NS", "TVSMOTOR.NS",
+        "ASHOKLEY.NS", "ESCORTS.NS", "SMLISUZU.NS", "FORCEMOT.NS", "BOSCHLTD.NS", "AMARAJABAT.NS"
+    ],
+    "Consumer Goods": [
+        "HINDUNILVR.NS", "ITC.NS", "NESTLEIND.NS", "BRITANNIA.NS", "TITAN.NS", "DABUR.NS", "MARICO.NS",
+        "COLPAL.NS", "GODREJCP.NS", "EMAMILTD.NS", "BAJAJCON.NS", "RADICO.NS", "HATSUN.NS"
+    ],
+    "Metals & Mining": [
+        "TATASTEEL.NS", "HINDALCO.NS", "JSWSTEEL.NS", "COALINDIA.NS", "VEDL.NS", "SAIL.NS", "NALCO.NS",
+        "MOIL.NS", "HINDZINC.NS", "APLAPOLLO.NS", "JINDALSTEL.NS", "GODAWARI.NS", "SHYAMMETL.NS"
+    ],
+    "Pharmaceuticals": [
+        "SUNPHARMA.NS", "DRREDDY.NS", "CIPLA.NS", "DIVISLAB.NS", "LUPIN.NS", "AUROPHARMA.NS", "BIOCON.NS",
+        "TORNTPHARM.NS", "ABBOTINDIA.NS", "GLENMARK.NS", "ZYDUSLIFE.NS", "ALKEM.NS", "IPCALAB.NS"
+    ],
+    "Infrastructure & Realty": [
+        "LT.NS", "ULTRACEMCO.NS", "SHREECEM.NS", "GRASIM.NS", "DLF.NS", "GODREJPROP.NS", "PHOENIXLTD.NS",
+        "OBEROIRLTY.NS", "IBREALEST.NS", "NCC.NS", "SOBHA.NS", "BRIGADE.NS", "PRESTIGE.NS"
     ]
-)
+}
+
+# 📌 Streamlit Page Configuration
+st.set_page_config(page_title="📈 Live Indian Stock Market", layout="wide")
+
+st.title("📈 Live Indian Stock Market Dashboard")
+
+# 🏦 Index Selection
+selected_index = st.selectbox("Select an Index", list(indian_indices.keys()))
+index_ticker = indian_indices[selected_index]
+
+# 🔹 Sector Selection
+selected_sector = st.selectbox("Select a Sector", list(sector_stocks.keys()))
+sector_tickers = sector_stocks[selected_sector]
+
+# 📊 Function to Fetch Live Data with Error Handling
+def fetch_live_data(ticker):
+    try:
+        stock = yf.Ticker(ticker)
+        live_data = stock.history(period="1d", interval="1m")
+        return live_data
+    except yf.YFRateLimitError:
+        st.warning("⚠️ Yahoo Finance rate limit reached. Retrying after 30 seconds...")
+        time.sleep(30)  # Wait before retrying
+        return None
+    except Exception as e:
+        st.error(f"⚠️ Error fetching data for {ticker}: {e}")
+        return None
+
+# 📊 Fetch Live Data for Index
+st.subheader(f"📊 Live Price for {selected_index}")
+live_price_placeholder = st.empty()
+
+# 📈 Fetch Live Data for Sector Stocks
+st.subheader(f"📈 Live Sector-Wise Stock Data ({selected_sector})")
+sector_table_placeholder = st.empty()
+
+# 🚀 Continuous Live Streaming Using Loop
+while True:
+    try:
+        # Fetch Live Index Data
+        live_data = fetch_live_data(index_ticker)
+        if live_data is not None and not live_data.empty:
+            latest_price = live_data["Close"].iloc[-1]
+
+            # ✅ FIX: Get previous close safely
+            historical_data = yf.Ticker(index_ticker).history(period="2d")
+            previous_close = historical_data["Close"].iloc[-2] if len(historical_data) > 1 else latest_price
+
+            price_change = latest_price - previous_close
+            percentage_change = (price_change / previous_close) * 100
+
+            live_price_placeholder.metric(
+                f"{selected_index} Live Price",
+                f"₹{latest_price:.2f}",
+                f"{price_change:.2f} ({percentage_change:.2f}%)",
+                delta_color="inverse" if price_change < 0 else "normal"
+            )
+
+        # Fetch Live Data for Sector Stocks
+        sector_data = []
+        for stock in sector_tickers:
+            stock_info = fetch_live_data(stock)
+            if stock_info is not None and not stock_info.empty:
+                latest_price = stock_info["Close"].iloc[-1]
+
+                # ✅ FIX: Get previous close safely
+                historical_data = yf.Ticker(stock).history(period="2d")
+                prev_close = historical_data["Close"].iloc[-2] if len(historical_data) > 1 else latest_price
+
+                price_change = latest_price - prev_close
+                percentage_change = (price_change / prev_close) * 100
 
-if page == "Market Overview":
-    from pages.market_overview import run_market_overview
-    run_market_overview()
+                sector_data.append({
+                    "Stock": stock,
+                    "Price (₹)": latest_price,
+                    "Change (₹)": price_change,
+                    "Change (%)": f"{percentage_change:.2f}%",
+                })
 
-elif page == "Candlestick Patterns":
-    from pages.candlestick_patterns import run_candlestick_analysis
-    run_candlestick_analysis()
+        # Convert to DataFrame & Display
+        if sector_data:
+            df = pd.DataFrame(sector_data)
+            sector_table_placeholder.dataframe(df, height=400)
 
-elif page == "Stock Predictions":
-    from pages.stock_predictions import run_stock_predictions
-    run_stock_predictions()
+        # ✅ Refresh Every **10 Seconds**
+        time.sleep(10)
 
-elif page == "Quantum Market Analysis":
-    from pages.quantum_market_analysis import run_quantum_market_analysis
-    run_quantum_market_analysis()
+    except Exception as e:
+        st.error(f"⚠️ Unexpected error: {e}")
+        time.sleep(10)  # Prevent app from breaking and wait before retrying