Update app.py

app.py

@@ -36,12 +36,12 @@ def init_conn():
 
 gcservice_account = init_conn()
 
-dk_player_url = 'PGA_Basic_ROO'
+dk_player_url = 'https://docs.google.com/spreadsheets/d/1lMLxWdvCnOFBtG9dhM0zv2USuxZbkogI_2jnxFfQVVs/edit#gid=1828092624'
 CSV_URL = 'https://docs.google.com/spreadsheets/d/1lMLxWdvCnOFBtG9dhM0zv2USuxZbkogI_2jnxFfQVVs/edit#gid=1828092624'
 
 @st.cache_resource(ttl = 600)
-def load_dk_player_model(URL):
-    sh = gcservice_account.open(URL)
+def load_dk_player_model():
+    sh = gcservice_account.open(dk_player_url)
     worksheet = sh.get_worksheet(0)
     raw_display = pd.DataFrame(worksheet.get_all_records())
     raw_display["Salary"] = raw_display["Salary"].replace("$", "", regex=True).astype(float)
@@ -57,8 +57,10 @@ def load_dk_player_model(URL):
     return raw_display
 
 @st.cache_resource(ttl = 600)
-def grab_csv_data(URL):
-    draftkings_data = pd.read_json(URL)
+def grab_csv_data():
+    sh = gcservice_account.open(CSV_URL)
+    worksheet = sh.worksheet('Site_Info')
+    draftkings_data = pd.DataFrame(worksheet.get_all_records())
     draftkings_data.rename(columns={"Name": "Player"}, inplace = True)
     
     return draftkings_data
@@ -68,6 +70,11 @@ tab1, tab2 = st.tabs(["Player Overall Projections", "Optimizer"])
 def convert_df_to_csv(df):
     return df.to_csv().encode('utf-8')
 
+hold_display = load_dk_player_model()
+csv_data = grab_csv_data()
+csv_merge = pd.merge(csv_data, hold_display, how='left', left_on=['Player'], right_on = ['Player'])
+id_dict = dict(zip(csv_merge['Player'], csv_merge['Name + ID']))
+
 lineup_display = []
 check_list = []
 rand_player = 0
@@ -79,10 +86,10 @@ with tab1:
               # Clear values from *all* all in-memory and on-disk data caches:
               # i.e. clear values from both square and cube
               st.cache_data.clear()
-    hold_display = load_dk_player_model(dk_player_url)
-    csv_data = grab_csv_data(CSV_URL)
-    csv_merge = pd.merge(csv_data, hold_display, how='left', left_on=['Player'], right_on = ['Player'])
-    id_dict = dict(zip(csv_merge['Player'], csv_merge['Name + ID']))
+              hold_display = load_dk_player_model()
+              csv_data = grab_csv_data()
+              csv_merge = pd.merge(csv_data, hold_display, how='left', left_on=['Player'], right_on = ['Player'])
+              id_dict = dict(zip(csv_merge['Player'], csv_merge['Name + ID']))
     hold_container = st.empty()
     display = hold_display.set_index('Player')
     st.dataframe(display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)