Upload srp.py

srp.py

@@ -0,0 +1,152 @@
+import streamlit as st
+import yfinance as yf
+import pandas as pd
+from datetime import datetime, timedelta, time
+
+# Load ticker symbols from the CSV file
+@st.cache_data  # Updated from st.cache to remove deprecation warning
+def load_ticker_list(file_path):
+    try:
+        stock_df = pd.read_csv(file_path)
+        return stock_df['Symbol'].tolist()
+    except Exception as e:
+        st.error(f"Error loading ticker list: {str(e)}")
+        return []
+
+# Function to check if the market is open
+def is_market_open():
+    now = datetime.now().time()
+    market_open_time = time(9, 15)    # NSE opens at 9:15 AM
+    market_close_time = time(15, 30)  # NSE closes at 3:30 PM
+    return market_open_time <= now <= market_close_time
+
+# Function to calculate pivot point and support/resistance levels
+def calculate_pivot_levels(stock_data):
+    try:
+        # Fixed the float() deprecation warnings by using .iloc[0]
+        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
+    except Exception as e:
+        st.error(f"Error calculating pivot levels: {str(e)}")
+        return None
+
+# Function to fetch stock data with proper error handling
+@st.cache_data(ttl=300)  # Cache for 5 minutes
+def get_stock_data(symbol):
+    try:
+        # Add .NS suffix for NSE stocks
+        nse_symbol = f"{symbol}.NS"
+        
+        # Try to get today's data
+        today = datetime.today().date()
+        stock = yf.download(
+            nse_symbol,
+            start=today - timedelta(days=5),  # Get more days of data
+            end=today + timedelta(days=1),
+            interval='1d',
+            progress=False  # Disable progress bar
+        )
+        
+        if not stock.empty:
+            return stock.tail(1)  # Return only the latest day's data
+        else:
+            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()
+
+# Streamlit UI
+def main():
+    st.title("Support and Resistance Level Calculator for NIFTY 500 Stocks")
+    
+    # Load ticker symbols
+    file_path = "G:/RSI/ind_nifty500list (1) (1).csv"
+    ticker_list = load_ticker_list(file_path)
+    
+    if not ticker_list:
+        st.error("Failed to load ticker list. Please check the file path.")
+        return
+    
+    # Select a ticker from the list
+    symbol = st.selectbox("Select a Stock Symbol", ticker_list)
+    
+    # Check market status
+    if is_market_open():
+        st.warning("Market is currently open. Data might not be finalized until after 3:30 PM.")
+    
+    if symbol:
+        # Add a refresh button
+        col1, col2 = st.columns([1, 4])
+        with col1:
+            refresh = st.button("🔄 Refresh")
+        
+        # Display loading spinner
+        with st.spinner('Fetching stock data...'):
+            if refresh:
+                # Clear cache for this stock
+                get_stock_data.clear()
+            
+            stock_data = get_stock_data(symbol)
+        
+        if not stock_data.empty:
+            # Calculate and display levels
+            levels = calculate_pivot_levels(stock_data)
+            
+            if levels:
+                # Fixed: Get current price as a scalar value
+                current_price = float(stock_data['Close'].iloc[-1])
+                st.metric("Current Price", f"₹{current_price:.2f}")
+                
+                # Create three columns for better organization
+                st.subheader(f"Support and Resistance Levels for {symbol}")
+                col1, col2, col3 = st.columns(3)
+                
+                # Display resistance levels
+                with col1:
+                    st.write("### Resistance Levels")
+                    for i in range(3, 0, -1):
+                        value = float(levels[f'Resistance {i}'])  # Convert to float
+                        st.write(f"R{i}: ₹{value:.2f}")
+                
+                # Display pivot point
+                with col2:
+                    st.write("### Pivot Point")
+                    value = float(levels['Pivot Point'])  # Convert to float
+                    st.write(f"PP: ₹{value:.2f}")
+                
+                # Display support levels
+                with col3:
+                    st.write("### Support Levels")
+                    for i in range(1, 4):
+                        value = float(levels[f'Support {i}'])  # Convert to float
+                        st.write(f"S{i}: ₹{value:.2f}")
+        else:
+            st.error("Failed to fetch stock data. Please try again later.")
+
+if __name__ == "__main__":
+    main()