Update app.py

app.py

@@ -39,70 +39,52 @@ futures_stocks = [
     "WHIRLPOOL.NS", "WIPRO.NS", "ZEEL.NS"
 ]
 
+# Predefined setups
+predefined_setups = {
+    "Custom": None,
+    "Conservative Approach": {
+        "RSI Threshold": 40, "RSI Length": 20, "Stochastic RSI Threshold": 0.30,
+        "Stochastic Length": 20, "OBV Change Threshold": 1.00
+    },
+    "Aggressive Approach": {
+        "RSI Threshold": 25, "RSI Length": 10, "Stochastic RSI Threshold": 0.10,
+        "Stochastic Length": 10, "OBV Change Threshold": 5.00
+    },
+    "Swing Trading Setup": {
+        "RSI Threshold": 30, "RSI Length": 14, "Stochastic RSI Threshold": 0.20,
+        "Stochastic Length": 14, "OBV Change Threshold": 2.00
+    },
+    "Reversal Trading": {
+        "RSI Threshold": 20, "RSI Length": 14, "Stochastic RSI Threshold": 0.15,
+        "Stochastic Length": 14, "OBV Change Threshold": 3.00
+    },
+    "Momentum Trading": {
+        "RSI Threshold": 50, "RSI Length": 9, "Stochastic RSI Threshold": 0.50,
+        "Stochastic Length": 9, "OBV Change Threshold": 4.00
+    },
+    "Day Trading Setup": {
+        "RSI Threshold": 35, "RSI Length": 7, "Stochastic RSI Threshold": 0.25,
+        "Stochastic Length": 7, "OBV Change Threshold": 2.50
+    },
+    "Trend Following Setup": {
+        "RSI Threshold": 50, "RSI Length": 20, "Stochastic RSI Threshold": 0.50,
+        "Stochastic Length": 20, "OBV Change Threshold": 1.50
+    },
+    "Volatility Setup": {
+        "RSI Threshold": 30, "RSI Length": 12, "Stochastic RSI Threshold": 0.35,
+        "Stochastic Length": 12, "OBV Change Threshold": 5.00
+    },
+    "Long-Term Investment Setup": {
+        "RSI Threshold": 60, "RSI Length": 30, "Stochastic RSI Threshold": 0.40,
+        "Stochastic Length": 30, "OBV Change Threshold": 0.50
+    },
+    "Short Squeeze Setup": {
+        "RSI Threshold": 20, "RSI Length": 5, "Stochastic RSI Threshold": 0.10,
+        "Stochastic Length": 5, "OBV Change Threshold": 7.00
+    }
+}
 
-@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
+# The fetch_and_calculate_indicators and filter_stocks_by_indicators functions remain unchanged
 
 def main():
     st.title("Indian Stock Market Scanner: RSI, Stochastic RSI, and OBV")
@@ -110,22 +92,40 @@ def main():
     start_date = st.date_input("Start Date", dt.date(2020, 1, 1))
     end_date = st.date_input("End Date", dt.date.today())
     
-    indicator_choice = st.radio("Choose Indicator", ('RSI', 'StochRSI', 'OBV', 'All'))
-    
-    col1, col2, col3 = st.columns(3)
-    
-    with col1:
-        rsi_threshold = st.slider("RSI Threshold", 0, 100, 30)
-        rsi_length = st.number_input("RSI Length", value=14, min_value=1, max_value=100)
+    setup_choice = st.selectbox("Choose a predefined setup or customize", list(predefined_setups.keys()))
     
-    with col2:
-        stoch_rsi_threshold = st.slider("Stochastic RSI Threshold", 0.0, 1.0, 0.2)
-        stoch_length = st.number_input("Stochastic Length", value=14, min_value=1, max_value=100)
-    
-    with col3:
-        obv_threshold = st.slider("OBV Change Threshold (%)", -10.0, 10.0, 2.0)
-        k_period = st.number_input("K Period", value=3, min_value=1, max_value=20)
-        d_period = st.number_input("D Period", value=3, min_value=1, max_value=20)
+    if setup_choice == "Custom":
+        indicator_choice = st.radio("Choose Indicator", ('RSI', 'StochRSI', 'OBV', 'All'))
+        
+        col1, col2, col3 = st.columns(3)
+        
+        with col1:
+            rsi_threshold = st.slider("RSI Threshold", 0, 100, 30)
+            rsi_length = st.number_input("RSI Length", value=14, min_value=1, max_value=100)
+        
+        with col2:
+            stoch_rsi_threshold = st.slider("Stochastic RSI Threshold", 0.0, 1.0, 0.2)
+            stoch_length = st.number_input("Stochastic Length", value=14, min_value=1, max_value=100)
+        
+        with col3:
+            obv_threshold = st.slider("OBV Change Threshold (%)", -10.0, 10.0, 2.0)
+            k_period = st.number_input("K Period", value=3, min_value=1, max_value=20)
+            d_period = st.number_input("D Period", value=3, min_value=1, max_value=20)
+    else:
+        setup = predefined_setups[setup_choice]
+        indicator_choice = 'All'
+        rsi_threshold = setup["RSI Threshold"]
+        rsi_length = setup["RSI Length"]
+        stoch_rsi_threshold = setup["Stochastic RSI Threshold"]
+        stoch_length = setup["Stochastic Length"]
+        obv_threshold = setup["OBV Change Threshold"]
+        k_period = 3  # Default value
+        d_period = 3  # Default value
+        
+        st.write(f"Selected setup: {setup_choice}")
+        st.write(f"RSI Threshold: {rsi_threshold}, RSI Length: {rsi_length}")
+        st.write(f"Stochastic RSI Threshold: {stoch_rsi_threshold}, Stochastic Length: {stoch_length}")
+        st.write(f"OBV Change Threshold: {obv_threshold}%")
     
     output_filename = st.text_input("Enter output filename (with .csv extension):", "filtered_stocks.csv")