Update app.py

app.py

@@ -15,28 +15,25 @@ futures_stocks = [
     "COALINDIA.NS", "CONCOR.NS", "CUMMINSIND.NS", "DABUR.NS", "DELTACORP.NS",
     "DIVISLAB.NS", "DLF.NS", "DRREDDY.NS", "EICHERMOT.NS", "FEDERALBNK.NS",
     "GAIL.NS", "GLENMARK.NS", "GMRINFRA.NS", "GODREJCP.NS", "GODREJPROP.NS",
-    "GRANULES.NS", "GRASIM.NS", "HAVELLS.NS", "HCLTECH.NS",
-    "HDFCAMC.NS", "HDFCBANK.NS", "HDFCLIFE.NS", "HEROMOTOCO.NS", "HINDALCO.NS",
-    "HINDCOPPER.NS", "HINDPETRO.NS", "HINDUNILVR.NS", "IBULHSGFIN.NS", "ICICIBANK.NS",
-    "ICICIGI.NS", "ICICIPRULI.NS", "IDEA.NS", "IDFCFIRSTB.NS", "INDHOTEL.NS",
-    "INDIACEM.NS", "INDIAMART.NS", "INDIGO.NS", "INDUSINDBK.NS", "INFY.NS",
-    "IRCTC.NS", "ITC.NS", "JINDALSTEL.NS", "JSWSTEEL.NS", "JUBLFOOD.NS",
-    "KOTAKBANK.NS", "L&TFH.NS", "LALPATHLAB.NS", "LAURUSLABS.NS", "LICHSGFIN.NS",
-    "LT.NS", "LUPIN.NS", "M&M.NS", "M&MFIN.NS", "MANAPPURAM.NS",
-    "MARICO.NS", "MARUTI.NS", "MCDOWELL-N.NS", "MCX.NS", "METROPOLIS.NS",
-    "MFSL.NS", "MGL.NS", "MINDTREE.NS", "MOTHERSUMI.NS", "MPHASIS.NS",
+    "GRANULES.NS", "GRASIM.NS", "HAVELLS.NS", "HCLTECH.NS", "HDFCAMC.NS", 
+    "HDFCBANK.NS", "HDFCLIFE.NS", "HEROMOTOCO.NS", "HINDALCO.NS", "HINDCOPPER.NS", 
+    "HINDPETRO.NS", "HINDUNILVR.NS", "IBULHSGFIN.NS", "ICICIBANK.NS", "ICICIGI.NS", 
+    "ICICIPRULI.NS", "IDEA.NS", "IDFCFIRSTB.NS", "INDHOTEL.NS", "INDIACEM.NS", 
+    "INDIAMART.NS", "INDIGO.NS", "INDUSINDBK.NS", "INFY.NS", "IRCTC.NS", "ITC.NS", 
+    "JINDALSTEL.NS", "JSWSTEEL.NS", "JUBLFOOD.NS", "KOTAKBANK.NS", "L&TFH.NS", 
+    "LALPATHLAB.NS", "LAURUSLABS.NS", "LICHSGFIN.NS", "LT.NS", "LUPIN.NS", "M&M.NS", 
+    "M&MFIN.NS", "MANAPPURAM.NS", "MARICO.NS", "MARUTI.NS", "MCDOWELL-N.NS", "MCX.NS", 
+    "METROPOLIS.NS", "MFSL.NS", "MGL.NS", "MINDTREE.NS", "MOTHERSUMI.NS", "MPHASIS.NS",
     "MRF.NS", "MUTHOOTFIN.NS", "NAM-INDIA.NS", "NATIONALUM.NS", "NAUKRI.NS",
-    "NAVINFLUOR.NS", "NBCC.NS", "NESTLEIND.NS", "NMDC.NS", "NTPC.NS",
-    "ONGC.NS", "PAGEIND.NS", "PEL.NS", "PETRONET.NS", "PFC.NS",
-    "PFIZER.NS", "PIDILITIND.NS", "PIIND.NS", "PNB.NS", "POLYCAB.NS",
-    "POWERGRID.NS", "PVR.NS", "RAMCOCEM.NS", "RBLBANK.NS", "RECLTD.NS",
-    "RELIANCE.NS", "SAIL.NS", "SBICARD.NS", "SBILIFE.NS", "SBIN.NS",
-    "SHREECEM.NS", "SIEMENS.NS", "SRF.NS", "SRTRANSFIN.NS", "SUNPHARMA.NS",
+    "NAVINFLUOR.NS", "NBCC.NS", "NESTLEIND.NS", "NMDC.NS", "NTPC.NS", "ONGC.NS", 
+    "PAGEIND.NS", "PEL.NS", "PETRONET.NS", "PFC.NS", "PFIZER.NS", "PIDILITIND.NS", 
+    "PIIND.NS", "PNB.NS", "POLYCAB.NS", "POWERGRID.NS", "PVR.NS", "RAMCOCEM.NS", 
+    "RBLBANK.NS", "RECLTD.NS", "RELIANCE.NS", "SAIL.NS", "SBICARD.NS", "SBILIFE.NS", 
+    "SBIN.NS", "SHREECEM.NS", "SIEMENS.NS", "SRF.NS", "SRTRANSFIN.NS", "SUNPHARMA.NS",
     "SUNTV.NS", "TATACHEM.NS", "TATACOMM.NS", "TATACONSUM.NS", "TATAMOTORS.NS",
-    "TATAPOWER.NS", "TATASTEEL.NS", "TCS.NS", "TECHM.NS", "TITAN.NS",
-    "TORNTPHARM.NS", "TORNTPOWER.NS", "TRENT.NS", "TVSMOTOR.NS", "UBL.NS",
-    "ULTRACEMCO.NS", "UPL.NS", "VBL.NS", "VEDL.NS", "VOLTAS.NS",
-    "WHIRLPOOL.NS", "WIPRO.NS", "ZEEL.NS"
+    "TATAPOWER.NS", "TATASTEEL.NS", "TCS.NS", "TECHM.NS", "TITAN.NS", "TORNTPHARM.NS", 
+    "TORNTPOWER.NS", "TRENT.NS", "TVSMOTOR.NS", "UBL.NS", "ULTRACEMCO.NS", "UPL.NS", 
+    "VBL.NS", "VEDL.NS", "VOLTAS.NS", "WHIRLPOOL.NS", "WIPRO.NS", "ZEEL.NS"
 ]
 
 # Predefined setups
@@ -84,7 +81,69 @@ predefined_setups = {
     }
 }
 
-# The fetch_and_calculate_indicators and filter_stocks_by_indicators functions remain unchanged
+@st.cache_data
+def fetch_and_calculate_indicators(ticker, start_date, end_date, rsi_length, stoch_length, k_period, d_period):
+    try:
+        df = yf.download(ticker, start=start_date, end=end_date)
+        
+        if df.empty:
+            return None
+
+        # Calculate RSI
+        df['RSI'] = ta.momentum.RSIIndicator(df['Close'], window=rsi_length).rsi()
+
+        # Calculate Stochastic RSI
+        stoch_rsi = ta.momentum.StochRSIIndicator(
+            df['Close'], 
+            window=stoch_length, 
+            smooth1=k_period, 
+            smooth2=d_period
+        )
+        df['StochRSI_K'] = stoch_rsi.stochrsi_k()
+        df['StochRSI_D'] = stoch_rsi.stochrsi_d()
+
+        # Calculate OBV
+        df['OBV'] = ta.volume.OnBalanceVolumeIndicator(df['Close'], df['Volume']).on_balance_volume()
+
+        if df['RSI'].isna().all() or df['StochRSI_K'].isna().all() or df['OBV'].isna().all():
+            return None
+        
+        return df
+    except Exception as e:
+        st.error(f"Error occurred for {ticker}: {str(e)}")
+        return None
+
+def filter_stocks_by_indicators(stocks, start_date, end_date, rsi_threshold, stoch_rsi_threshold, obv_threshold, indicator_choice, rsi_length, stoch_length, k_period, d_period):
+    filtered_stocks = []
+    progress_bar = st.progress(0)
+    for i, ticker in enumerate(stocks):
+        df = fetch_and_calculate_indicators(ticker, start_date, end_date, rsi_length, stoch_length, k_period, d_period)
+        if df is not None and not df['RSI'].empty and not df['StochRSI_K'].empty and not df['OBV'].empty:
+            rsi_value = df['RSI'].iloc[-1]
+            stoch_rsi_value = df['StochRSI_K'].iloc[-1]
+            obv_value = df['OBV'].iloc[-1]
+            obv_change = (df['OBV'].iloc[-1] - df['OBV'].iloc[-2]) / df['OBV'].iloc[-2] * 100  # Percentage change
+            
+            if not pd.isna(rsi_value) and not pd.isna(stoch_rsi_value) and not pd.isna(obv_value):
+                if (indicator_choice == 'RSI' and rsi_value < rsi_threshold) or \
+                   (indicator_choice == 'StochRSI' and stoch_rsi_value < stoch_rsi_threshold) or \
+                   (indicator_choice == 'OBV' and obv_change > obv_threshold) or \
+                   (indicator_choice == 'All' and rsi_value < rsi_threshold and stoch_rsi_value < stoch_rsi_threshold and obv_change > obv_threshold):
+                    filtered_stocks.append({
+                        'Ticker': ticker,
+                        'RSI': rsi_value,
+                        'StochRSI': stoch_rsi_value,
+                        'OBV_Change': obv_change
+                    })
+                    st.info(f"{ticker} - RSI: {rsi_value:.2f}, StochRSI: {stoch_rsi_value:.2f}, OBV Change: {obv_change:.2f}%")
+                else:
+                    st.info(f"{ticker} - RSI: {rsi_value:.2f}, StochRSI: {stoch_rsi_value:.2f}, OBV Change: {obv_change:.2f}% (doesn't meet criteria)")
+            else:
+                st.info(f"{ticker} has NaN value for RSI, StochRSI, or OBV.")
+        else:
+            st.info(f"No valid data available for {ticker}.")
+        progress_bar.progress((i + 1) / len(stocks))
+    return filtered_stocks
 
 def main():
     st.title("Indian Stock Market Scanner: RSI, Stochastic RSI, and OBV")