Update app.py

app.py

@@ -10,18 +10,15 @@ import numpy as np
 import pandas as pd
 import streamlit as st
 import gspread
-import time
-from itertools import combinations
 
 @st.cache_resource
 def init_conn():
-          scope = ['https://www.googleapis.com/auth/spreadsheets',
-                    "https://www.googleapis.com/auth/drive"]
-          
-          credentials = {
+        scope = ['https://spreadsheets.google.com/feeds', 'https://www.googleapis.com/auth/drive']
+        
+        credentials = {
             "type": "service_account",
             "project_id": "sheets-api-connect-378620",
-            "private_key_id": "1005124050c80d085e2c5b344345715978dd9cc9",
+            "private_key_id": st.secrets['sheets_api_pk'],
             "private_key": "-----BEGIN PRIVATE KEY-----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\nJuElxA33rFEjbgbzdyrE768=\n-----END PRIVATE KEY-----\n",
             "client_email": "gspread-connection@sheets-api-connect-378620.iam.gserviceaccount.com",
             "client_id": "106625872877651920064",
@@ -30,11 +27,14 @@ def init_conn():
             "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
             "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/gspread-connection%40sheets-api-connect-378620.iam.gserviceaccount.com"
           }
+     
+        NFL_Data = st.secrets["NFL_data"]
 
-          gc = gspread.service_account_from_dict(credentials)
-          return gc
+        gc_con = gspread.service_account_from_dict(credentials, scope)
 
-gcservice_account = init_conn()
+        return gc_con, NFL_Data
+    
+gc, all_dk_player_projections = init_conn()
 
 wrong_acro = ['WSH', 'AZ']
 right_acro = ['WAS', 'ARI']
@@ -47,92 +47,51 @@ team_roo_format = {'Top Score%': '{:.2%}','0 Runs': '{:.2%}', '1 Run': '{:.2%}',
 
 expose_format = {'Proj Own': '{:.2%}','Exposure': '{:.2%}'}
 
-all_dk_player_projections = 'https://docs.google.com/spreadsheets/d/1I_1Ve3F4tftgfLQQoRKOJ351XfEG48s36OxXUKxmgS8/edit#gid=1391856348'
-
 @st.cache_resource(ttl = 599)
-def set_slate_teams():
-    sh = gcservice_account.open_by_url(all_dk_player_projections)
+def init_baselines():
+    sh = gc.open_by_url(all_dk_player_projections)
     worksheet = sh.worksheet('Site_Info')
     raw_display = pd.DataFrame(worksheet.get_all_records())
-
-    return raw_display
-
-@st.cache_resource(ttl = 600)
-def player_stat_table():
-    sh = gcservice_account.open_by_url(all_dk_player_projections)
+    site_slates = raw_display
+    
     worksheet = sh.worksheet('Player_Projections')
     raw_display = pd.DataFrame(worksheet.get_all_records())
-
-    return raw_display
-
-@st.cache_resource(ttl = 600)
-def load_dk_player_projections():
-    sh = gcservice_account.open_by_url(all_dk_player_projections)
+    player_stats = raw_display
+    
     worksheet = sh.worksheet('DK_ROO')
     load_display = pd.DataFrame(worksheet.get_all_records())
     load_display.replace('', np.nan, inplace=True)
     raw_display = load_display.dropna(subset=['Median'])
-
-    return raw_display
-
-@st.cache_resource(ttl = 600)
-def load_fd_player_projections():
-    sh = gcservice_account.open_by_url(all_dk_player_projections)
+    dk_ids = dict(zip(raw_display['Player'], raw_display['player_id']))
+    dk_roo_raw = raw_display
+    
     worksheet = sh.worksheet('FD_ROO')
     load_display = pd.DataFrame(worksheet.get_all_records())
     load_display.replace('', np.nan, inplace=True)
     raw_display = load_display.dropna(subset=['Median'])
-
-    return raw_display
-
-@st.cache_resource(ttl = 600)
-def load_dk_stacks():
-    sh = gcservice_account.open_by_url(all_dk_player_projections)
+    fd_ids = dict(zip(raw_display['Player'], raw_display['player_id']))
+    fd_roo_raw = raw_display
+    
     worksheet = sh.worksheet('DK_Stacks')
     load_display = pd.DataFrame(worksheet.get_all_records())
     raw_display = load_display
     raw_display = raw_display.sort_values(by='Own', ascending=False)
-
-    return raw_display
-
-@st.cache_resource(ttl = 600)
-def load_fd_stacks():
-    sh = gcservice_account.open_by_url(all_dk_player_projections)
+    dk_stacks_raw = raw_display
+    
     worksheet = sh.worksheet('FD_Stacks')
     load_display = pd.DataFrame(worksheet.get_all_records())
     raw_display = load_display
     raw_display = raw_display.sort_values(by='Own', ascending=False)
+    fd_stacks_raw = raw_display
 
-    return raw_display
-
-@st.cache_resource(ttl = 600)
-def set_export_ids():
-    sh = gcservice_account.open_by_url(all_dk_player_projections)
-    worksheet = sh.worksheet('DK_ROO')
-    load_display = pd.DataFrame(worksheet.get_all_records())
-    load_display.replace('', np.nan, inplace=True)
-    raw_display = load_display.dropna(subset=['Median'])
-    dk_ids = dict(zip(raw_display['Player'], raw_display['player_id']))
-    
-    worksheet = sh.worksheet('FD_ROO')
-    load_display = pd.DataFrame(worksheet.get_all_records())
-    load_display.replace('', np.nan, inplace=True)
-    raw_display = load_display.dropna(subset=['Median'])
-    fd_ids = dict(zip(raw_display['Player'], raw_display['player_id']))
-
-    return dk_ids, fd_ids
+    return site_slates, player_stats, dk_roo_raw, fd_roo_raw, dk_stacks_raw, fd_stacks_raw, dk_ids, fd_ids
 
 @st.cache_data
 def convert_df_to_csv(df):
     return df.to_csv().encode('utf-8')
 
-player_stats = player_stat_table()
-dk_stacks_raw = load_fd_stacks()
-fd_stacks_raw = load_fd_stacks()
-dk_roo_raw = load_dk_player_projections()
-fd_roo_raw = load_fd_player_projections()
+site_slates, player_stats, dk_roo_raw, fd_roo_raw, dk_stacks_raw, fd_stacks_raw, dkid_dict, fdid_dict  = init_baselines()
 t_stamp = f"Last Update: " + str(dk_roo_raw['timestamp'][0]) + f" CST"
-site_slates = set_slate_teams()
 col1, col2 = st.columns([1, 5])
 dk_Max_Rank = dk_stacks_raw['Team'][0]
 fd_Max_Rank = dk_stacks_raw['Team'][0]
@@ -141,7 +100,6 @@ fd_stacks_raw = fd_stacks_raw.sort_values(by='Median', ascending=False)
 dk_Max_Upside = dk_stacks_raw['Team'][0]
 fd_Max_Upside = dk_stacks_raw['Team'][0]
 opp_dict = dict(zip(dk_roo_raw.Team, dk_roo_raw.Opp))
-dkid_dict, fdid_dict = set_export_ids()
 
 tab1, tab2 = st.tabs(['Uploads and Info', 'Optimizer'])
 
@@ -167,13 +125,16 @@ with tab2:
         st.info(t_stamp)
         if st.button("Load/Reset Data", key='reset1'):
               st.cache_data.clear()
-              player_stats = player_stat_table()
-              dk_stacks_raw = load_fd_stacks()
-              fd_stacks_raw = load_fd_stacks()
-              dk_roo_raw = load_dk_player_projections()
-              fd_roo_raw = load_fd_player_projections()
+              site_slates, player_stats, dk_roo_raw, fd_roo_raw, dk_stacks_raw, fd_stacks_raw, dk_ids, fd_ids = init_baselines()
               t_stamp = f"Last Update: " + str(dk_roo_raw['timestamp'][0]) + f" CST"
-              site_slates = set_slate_teams()
+              col1, col2 = st.columns([1, 5])
+              dk_Max_Rank = dk_stacks_raw['Team'][0]
+              fd_Max_Rank = dk_stacks_raw['Team'][0]
+              dk_stacks_raw = dk_stacks_raw.sort_values(by='Median', ascending=False)
+              fd_stacks_raw = fd_stacks_raw.sort_values(by='Median', ascending=False)
+              dk_Max_Upside = dk_stacks_raw['Team'][0]
+              fd_Max_Upside = dk_stacks_raw['Team'][0]
+              opp_dict = dict(zip(dk_roo_raw.Team, dk_roo_raw.Opp))
               
         slate_var1 = st.radio("Which data are you loading?", ('Main Slate', 'Secondary Slate', 'All Games', 'User'), key='slate_var1')
         site_var1 = st.radio("What site are you working with?", ('Draftkings', 'Fanduel'), key='site_var1')