Update app.py

app.py

@@ -2,8 +2,11 @@ import streamlit as st
 import yfinance as yf
 import pandas as pd
 from datetime import datetime, timedelta, time
+import requests
+from requests.adapters import HTTPAdapter
+from urllib3.util.retry import Retry
 
-# Define the fallback list of ticker symbols
+# Define the list of ticker symbols for user selection
 TICKER_SYMBOLS = [
     "AADHARHFC", "AARTIIND", "AAVAS", "ABBOTINDIA", "ACE", "ADANIENSOL", "ADANIENT", "ADANIGREEN", "ADANIPORTS", 
     "ADANIPOWER", "ATGL", "AWL", "ABCAPITAL", "ABFRL", "ABREL", "ABSLAMC", "AEGISLOG", "AFFLE", "AJANTPHARM", 
@@ -33,6 +36,16 @@ TICKER_SYMBOLS = [
     "UPL", "VEDL", "WIPRO", "YESBANK", "ZEEL", "ZOMATO", "ZYDUSLIFE"
 ]
 
+# Streamlit App Title
+st.title("Pivot Point Calculator for Indian Share Market")
+
+# Ticker Selection
+selected_ticker = st.selectbox("Select a Ticker Symbol", TICKER_SYMBOLS)
+
+# Date input
+start_date = st.date_input("Select Start Date for Historical Data")
+end_date = st.date_input("Select End Date for Historical Data")
+
 # Function to check if the market is open
 def is_market_open():
     now = datetime.now().time()
@@ -42,93 +55,86 @@ def is_market_open():
 
 # Function to calculate pivot point and support/resistance levels
 def calculate_pivot_levels(stock_data):
-    high = stock_data['High'].iloc[-1]
-    low = stock_data['Low'].iloc[-1]
-    close = stock_data['Close'].iloc[-1]
-
-    # Calculate pivot point
-    pivot = (high + low + close) / 3
-
-    # Calculate support and resistance levels
-    resistance1 = (2 * pivot) - low
-    support1 = (2 * pivot) - high
-    resistance2 = pivot + (high - low)
-    support2 = pivot - (high - low)
-    resistance3 = high + 2 * (pivot - low)
-    support3 = low - 2 * (high - pivot)
-
-    levels = {
-        'Pivot Point': pivot,
-        'Resistance 1': resistance1,
-        'Support 1': support1,
-        'Resistance 2': resistance2,
-        'Support 2': support2,
-        'Resistance 3': resistance3,
-        'Support 3': support3
-    }
-    return levels
-
-# Function to fetch stock data
+    try:
+        high = stock_data['High'].iloc[-1]
+        low = stock_data['Low'].iloc[-1]
+        close = stock_data['Close'].iloc[-1]
+        
+        pivot = (high + low + close) / 3
+        
+        resistance1 = (2 * pivot) - low
+        support1 = (2 * pivot) - high
+        resistance2 = pivot + (high - low)
+        support2 = pivot - (high - low)
+        resistance3 = high + 2 * (pivot - low)
+        support3 = low - 2 * (high - pivot)
+        
+        levels = {
+            'Pivot Point': pivot,
+            'Resistance 1': resistance1,
+            'Support 1': support1,
+            'Resistance 2': resistance2,
+            'Support 2': support2,
+            'Resistance 3': resistance3,
+            'Support 3': support3
+        }
+        return levels
+    except Exception as e:
+        st.error(f"Error calculating pivot levels: {str(e)}")
+        return None
+
+# Function to fetch stock data with retry logic and proper error handling
 @st.cache_data(ttl=300)  # Cache for 5 minutes
 def get_stock_data(symbol):
-    nse_symbol = f"{symbol}.NS"
-    today = datetime.today().date()
-    stock = yf.download(nse_symbol, start=today - timedelta(days=5), end=today + timedelta(days=1), interval='1d', progress=False)
-    return stock.tail(1) if not stock.empty else pd.DataFrame()
-
-# Streamlit UI
-def main():
-    st.title("Support and Resistance Level Calculator for NIFTY 500 Stocks")
-
-    # Load ticker symbols
-    ticker_list = TICKER_SYMBOLS
-
-    # Select a ticker from the list
-    symbol = st.selectbox("Select a Stock Symbol", ticker_list)
-
-    # Check if the market is currently open and display a warning
-    if is_market_open():
-        st.warning("Market is currently open. Data may be incomplete until after market hours (3:30 PM IST).")
-
-    if symbol:
-        # Refresh button for getting the latest data
-        if st.button("🔄 Refresh Data"):
-            get_stock_data.clear()  # Clear cached data for stock
-
-        # Fetch stock data
-        with st.spinner("Fetching stock data..."):
-            stock_data = get_stock_data(symbol)
-
-        # Display stock data if available
-        if not stock_data.empty:
-            levels = calculate_pivot_levels(stock_data)
-
-            # Display current price
-            current_price = stock_data['Close'].iloc[-1]
-            st.metric("Current Price", f"₹{current_price:.2f}")
-
-            # Display support and resistance levels in columns
-            st.subheader(f"Support and Resistance Levels for {symbol}")
-            col1, col2, col3 = st.columns(3)
-
-            # Resistance levels
-            with col1:
-                st.write("### Resistance Levels")
-                for i in range(3, 0, -1):
-                    st.write(f"R{i}: ₹{levels[f'Resistance {i}']:.2f}")
-
-            # Pivot Point
-            with col2:
-                st.write("### Pivot Point")
-                st.write(f"PP: ₹{levels['Pivot Point']:.2f}")
-
-            # Support levels
-            with col3:
-                st.write("### Support Levels")
-                for i in range(1, 4):
-                    st.write(f"S{i}: ₹{levels[f'Support {i}']:.2f}")
+    try:
+        nse_symbol = f"{symbol}.NS"
+        today = datetime.today().date()
+
+        # Set up a retry session to handle intermittent connection issues
+        session = requests.Session()
+        retries = Retry(total=5, backoff_factor=0.5, status_forcelist=[500, 502, 503, 504])
+        session.mount('https://', HTTPAdapter(max_retries=retries))
+
+        # Use the session to download data
+        stock = yf.download(
+            nse_symbol,
+            start=today - timedelta(days=5),
+            end=today + timedelta(days=1),
+            interval='1d',
+            progress=False,
+            session=session
+        )
+        
+        if not stock.empty:
+            return stock.tail(1)
         else:
-            st.error("No data available for the selected stock. Please try again later or select a different stock.")
-
-if __name__ == "__main__":
-    main()
+            st.warning("No data available for the selected stock.")
+            return pd.DataFrame()
+            
+    except Exception as e:
+        st.error(f"Error fetching data for {symbol}: {str(e)}")
+        return pd.DataFrame()
+
+# Load Data
+if st.button("Calculate Pivot Points"):
+    if selected_ticker:
+        # Download historical data using yfinance
+        try:
+            data = get_stock_data(selected_ticker)
+            if not data.empty:
+                # Display historical data
+                st.subheader("Historical Data")
+                st.dataframe(data.tail())
+                
+                # Calculate pivot points and support/resistance levels
+                levels = calculate_pivot_levels(data)
+                if levels:
+                    st.subheader(f"Pivot Point Calculations for {selected_ticker}")
+                    for level_name, value in levels.items():
+                        st.write(f"{level_name}: {float(value):.2f}")
+            else:
+                st.error("No data available for the selected ticker and date range. Please try again.")
+        except Exception as e:
+            st.error(f"An error occurred: {e}")
+    else:
+        st.error("Please select a valid ticker symbol.")