Update app.py

app.py

@@ -1,71 +1,55 @@
-# 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 
-
-import streamlit as st
+from nsepython import *
+import seaborn as sns
 import pandas as pd
-st.title('A Simple Streamlit Web App')
-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
-             """)
-x = st.slider('Select an integer x', 0, 10, 1)
-y = st.slider('Select an integer y', 0, 10, 1)
-df = pd.DataFrame({'x': [x], 'y': [y] , 'x + y': [x + y]}, index = ['addition row'])
-st.write(df)
+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'])
 
-# 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
+    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()
@@ -118,3 +102,26 @@ st.write(df)
 #         p2.empty()
 #         p3.empty()
                    
+
+import streamlit as st
+import pandas as pd
+st.title('A Simple Streamlit Web App')
+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
+             """)
+x = st.slider('Select an integer x', 0, 10, 1)
+y = st.slider('Select an integer y', 0, 10, 1)
+df = pd.DataFrame({'x': [x], 'y': [y] , 'x + y': [x + y]}, index = ['addition row'])
+st.write(df)
+get=get_data
+st.DataFrame(get)
+
+
+
+
+