Add application file

app.py

@@ -0,0 +1,99 @@
+from nsepython import *
+import seaborn as sns
+import pandas as pd
+import streamlit as st
+from datetime import datetime
+from time import gmtime, strftime
+from IPython.display import clear_output 
+import matplotlib.pyplot as plt
+from pytz import timezone 
+
+def get_data():
+    a=(nse_fno("BANKNIFTY"))
+    last_prices=round(nse_quote_ltp("BANKNIFTY"))
+    exp=list(set(a['expiryDates']))
+    exp.sort(key = lambda date: datetime.strptime(date, '%d-%b-%Y')) 
+    if last_prices%100>50:
+        x=(last_prices-last_prices%100+100)
+        strike=[x-200,x-100,x,x+100,x+200]
+    elif last_prices%100<50:
+        x=(last_prices-last_prices%100)
+        strike=[x-200,x-100,x,x+100,x+200]
+    d={'call change op':[],
+        'call vwap':[],
+        '% change op':[],
+        'strike':[],
+        'put change op':[],
+        'put vwap':[],
+        '% change op put':[]
+        }
+    for i in a['stocks']:
+        for sp in strike: 
+            if i['metadata']['expiryDate']==exp[0] and i['metadata']['optionType']=='Call' and i['metadata']['strikePrice']==sp:
+                d['strike'].append(sp)
+                d['call change op'].append(i['marketDeptOrderBook']['tradeInfo']['changeinOpenInterest'])
+                d['% change op'].append(i['marketDeptOrderBook']['tradeInfo']['pchangeinOpenInterest'])
+                d['call vwap'].append(i['marketDeptOrderBook']['tradeInfo']['vmap'])
+
+            elif i['metadata']['expiryDate']==exp[0] and i['metadata']['optionType']=='Put' and i['metadata']['strikePrice']==sp:
+                d['put change op'].append(i['marketDeptOrderBook']['tradeInfo']['changeinOpenInterest'])
+                d['% change op put'].append(i['marketDeptOrderBook']['tradeInfo']['pchangeinOpenInterest'])
+                d['put vwap'].append(i['marketDeptOrderBook']['tradeInfo']['vmap'])
+
+    out=pd.json_normalize(d)
+    out=out.explode(list(out.columns)).reset_index(drop = True)
+    out.fillna(0,inplace=True)
+    x=out.astype(float).round(2)
+    return x
+def get_info(dataset):
+    df= pd.DataFrame(columns=['value', 'pcr', 'cal_per','put_per'])
+    value= dataset['put change op'].sum() - dataset['call change op'].sum()
+    pcr= dataset['put change op'].sum()/dataset['call change op'].sum()
+    cal_per= dataset['% change op'].mean()
+    put_per= dataset['% change op put'].mean()
+    new_row={'time':datetime.now(timezone("Asia/Kolkata")).strftime('%I.%M %p'),'value':value, 'pcr':round(pcr,2), 'cal_per':round(cal_per,2), 'put_per':round(put_per,2)}
+    df = df.append(new_row,ignore_index=True, verify_integrity=False, sort=None)
+    return df  
+def ploting():
+        try:
+            global final
+        except:
+             df = pd.DataFrame(columns=['value', 'pcr', 'cal_per','put_per'])
+        dataset= get_data()
+        main= get_info(dataset)
+        final =final.append(main,ignore_index=True, verify_integrity=False, sort=None)
+        return dataset,final
+
+final = pd.DataFrame(columns=['value', 'pcr', 'cal_per','put_per','time'])
+    
+
+if __name__=='__main__':
+    
+    st.title('WELCOME BULLS CARTEL')
+    today_date =strftime("%d %b %Y", gmtime()),datetime.now(timezone("Asia/Kolkata")).strftime('%I.%M %p')
+    st.markdown(f"as at {today_date}")
+    option= st.selectbox(
+    'How would you like to be contacted?',
+    ('5', '10', '15')) 
+    st.write('You selected:', option)
+    st.header('Important Information')
+    st.markdown(""" CALL % INCREASE MEANS MARKET GOES DOWN  
+             PUT % INCREASE MEANS MARKET GOES UP
+             """)    
+    while True:
+        dataset,final=ploting()
+        p1=st.empty()
+        p2=st.empty()
+        p3=st.empty()
+        p1.dataframe(dataset.style.highlight_max(['% change op put','% change op'],axis=0)) #Column hightlight 
+        p2.dataframe(final.style.highlight_max(['cal_per','put_per'],axis=1)) # row highlight
+        fig, ax = plt.subplots(figsize=(6, 2)) 
+        ax.plot(final['time'],final['pcr'])
+        ax.axhline(y=0, color='black', linestyle='solid') # 0 line graph
+        fig.autofmt_xdate(rotation=70)
+        p3.pyplot(fig)
+        time.sleep(3*60) # how to the start again code check upper condition min * sec
+        p1.empty() # then clean all data frame 
+        p2.empty()
+        p3.empty()
+