Update app.py

app.py

@@ -20,14 +20,14 @@ with con10:
     time1 = st.selectbox('*_Time Frame_*', ('1','5','15','30','60','120','240','D','1W','1M'),key=1)
     if time1 == 'D':
         timevolume = 'volume'
-        timeADX-DI = 'ADX-DI'
-        timeADX+DI = 'ADX+DI'
+        timeADXnegDI = 'ADX-DI'
+        timeADXposDI = 'ADX+DI'
         timeclose = 'close'
     else:
         timeclose = f'close|{time1}'
         timevolume = f'volume|{time}'
-        timeADX-DI = f'ADX-DI|{time}'
-        timeADX+DI = f'ADX+DI|{time}'
+        timeADXnegDI = f'ADX-DI|{time}'
+        timeADXposDI = f'ADX+DI|{time}'
 with con20:
     st.write('')
     price_from = st.number_input('*_Price_From_*', min_value=float(1), max_value=float(10000), value=float(100), step=float(5),key=23)
@@ -38,8 +38,8 @@ def create_link(url:str) -> str:
 
 if st.button('*_SUBMIT_*'):
     # Create a query with the required columns and conditions
-    df_Bulliesh = (Query().select('Exchange','name',timeclose, timevolume, timeADX-DI, timeADX+DI).where(your_instance.crosses_below(Column(timeADX-DI), Column(timeADX+DI)),Column(timeclose).between(price_from, price_to)).order_by(timevolume, ascending=False).limit(5))
-    df_Beariesh = (Query().select('Exchange','name',timeclose, timevolume, timeADX-DI, timeADX+DI).where(your_instance.crosses_above(Column(timeADX-DI), Column(timeADX+DI)),Column(timeclose).between(price_from, price_to)).order_by(timevolume, ascending=False).limit(5))
+    df_Bulliesh = (Query().select('Exchange','name',timeclose, timevolume, timeADXnegDI, timeADXposDI).where(your_instance.crosses_below(Column(timeADXnegDI), Column(timeADXposDI)),Column(timeclose).between(price_from, price_to)).order_by(timevolume, ascending=False).limit(5))
+    df_Beariesh = (Query().select('Exchange','name',timeclose, timevolume, timeADXnegDI, timeADXposDI).where(your_instance.crosses_above(Column(timeADXnegDI), Column(timeADXposDI)),Column(timeclose).between(price_from, price_to)).order_by(timevolume, ascending=False).limit(5))
 
     # Display the result
     df_Bulliesh = df_Bulliesh.set_markets('india').get_scanner_data()