Update app.py

app.py

@@ -1,72 +1,64 @@
-import pulp
+import streamlit as st
+st.set_page_config(layout="wide")
+
+for name in dir():
+    if not name.startswith('_'):
+        del globals()[name]
+
 import numpy as np
 import pandas as pd
-import random
-import sys
-import openpyxl
-import re
-import time
 import streamlit as st
-import matplotlib
-from  matplotlib.colors import LinearSegmentedColormap
-from st_aggrid import GridOptionsBuilder, AgGrid, GridUpdateMode, DataReturnMode
-import json
-import requests
 import gspread
-import plotly.figure_factory as ff
-
-scope = ['https://www.googleapis.com/auth/spreadsheets',
-          "https://www.googleapis.com/auth/drive"]
-
-credentials = {
-  "type": "service_account",
-  "project_id": "sheets-api-connect-378620",
-  "private_key_id": "1005124050c80d085e2c5b344345715978dd9cc9",
-  "private_key": "-----BEGIN PRIVATE KEY-----\nMIIEvQIBADANBgkqhkiG9w0BAQEFAASCBKcwggSjAgEAAoIBAQCtKa01beXwc88R\nnPZVQTNPVQuBnbwoOfc66gW3547ja/UEyIGAF112dt/VqHprRafkKGmlg55jqJNt\na4zceLKV+wTm7vBu7lDISTJfGzCf2TrxQYNqwMKE2LOjI69dBM8u4Dcb4k0wcp9v\ntW1ZzLVVuwTvmrg7JBHjiSaB+x5wxm/r3FOiJDXdlAgFlytzqgcyeZMJVKKBQHyJ\njEGg/1720A0numuOCt71w/2G0bDmijuj1e6tH32MwRWcvRNZ19K9ssyDz2S9p68s\nYDhIxX69OWxwScTIHLY6J2t8txf/XMivL/636fPlDADvBEVTdlT606n8CcKUVQeq\npUVdG+lfAgMBAAECggEAP38SUA7B69eTfRpo658ycOs3Amr0JW4H/bb1rNeAul0K\nZhwd/HnU4E07y81xQmey5kN5ZeNrD5EvqkZvSyMJHV0EEahZStwhjCfnDB/cxyix\nZ+kFhv4y9eK+kFpUAhBy5nX6T0O+2T6WvzAwbmbVsZ+X8kJyPuF9m8ldcPlD0sce\ntj8NwVq1ys52eosqs7zi2vjt+eMcaY393l4ls+vNq8Yf27cfyFw45W45CH/97/Nu\n5AmuzlCOAfFF+z4OC5g4rei4E/Qgpxa7/uom+BVfv9G0DIGW/tU6Sne0+37uoGKt\nW6DzhgtebUtoYkG7ZJ05BTXGp2lwgVcNRoPwnKJDxQKBgQDT5wYPUBDW+FHbvZSp\nd1m1UQuXyerqOTA9smFaM8sr/UraeH85DJPEIEk8qsntMBVMhvD3Pw8uIUeFNMYj\naLmZFObsL+WctepXrVo5NB6RtLB/jZYxiKMatMLUJIYtcKIp+2z/YtKiWcLnwotB\nWdCjVnPTxpkurmF2fWP/eewZ+wKBgQDRMtJg7etjvKyjYNQ5fARnCc+XsI3gkBe1\nX9oeXfhyfZFeBXWnZzN1ITgFHplDznmBdxAyYGiQdbbkdKQSghviUQ0igBvoDMYy\n1rWcy+a17Mj98uyNEfmb3X2cC6WpvOZaGHwg9+GY67BThwI3FqHIbyk6Ko09WlTX\nQpRQjMzU7QKBgAfi1iflu+q0LR+3a3vvFCiaToskmZiD7latd9AKk2ocsBd3Woy9\n+hXXecJHPOKV4oUJlJgvAZqe5HGBqEoTEK0wyPNLSQlO/9ypd+0fEnArwFHO7CMF\nycQprAKHJXM1eOOFFuZeQCaInqdPZy1UcV5Szla4UmUZWkk1m24blHzXAoGBAMcA\nyH4qdbxX9AYrC1dvsSRvgcnzytMvX05LU0uF6tzGtG0zVlub4ahvpEHCfNuy44UT\nxRWW/oFFaWjjyFxO5sWggpUqNuHEnRopg3QXx22SRRTGbN45li/+QAocTkgsiRh1\nqEcYZsO4mPCsQqAy6E2p6RcK+Xa+omxvSnVhq0x1AoGAKr8GdkCl4CF6rieLMAQ7\nLNBuuoYGaHoh8l5E2uOQpzwxVy/nMBcAv+2+KqHEzHryUv1owOi6pMLv7A9mTFoS\n18B0QRLuz5fSOsVnmldfC9fpUc6H8cH1SINZpzajqQA74bPwELJjnzrCnH79TnHG\nJuElxA33rFEjbgbzdyrE768=\n-----END PRIVATE KEY-----\n",
-  "client_email": "gspread-connection@sheets-api-connect-378620.iam.gserviceaccount.com",
-  "client_id": "106625872877651920064",
-  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
-  "token_uri": "https://oauth2.googleapis.com/token",
-  "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"
-}
-
-gc = gspread.service_account_from_dict(credentials)
 
-st.set_page_config(layout="wide")
+@st.cache_resource
+def init_conn():
+          scope = ['https://www.googleapis.com/auth/spreadsheets',
+                    "https://www.googleapis.com/auth/drive"]
+          
+          credentials = {
+            "type": "service_account",
+            "project_id": "sheets-api-connect-378620",
+            "private_key_id": "1005124050c80d085e2c5b344345715978dd9cc9",
+            "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",
+            "auth_uri": "https://accounts.google.com/o/oauth2/auth",
+            "token_uri": "https://oauth2.googleapis.com/token",
+            "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"
+          }
+
+          gc = gspread.service_account_from_dict(credentials)
+          return gc
+
+gspreadcon = init_conn()
 
 dk_player_url = 'https://docs.google.com/spreadsheets/d/1Yq0vGriWK-bS79e-bD6_u9pqrYE6Yrlbb_wEkmH-ot0/edit#gid=172632260'
-fd_player_url = 'https://docs.google.com/spreadsheets/d/1Yq0vGriWK-bS79e-bD6_u9pqrYE6Yrlbb_wEkmH-ot0/edit#gid=172632260'
 
 @st.cache_data
-def load_overall_stats(URL):
-    sh = gc.open_by_url(URL)
-    worksheet = sh.get_worksheet(8)
+def load_overall_stats():
+    sh = gspreadcon.open_by_url(dk_player_url)
+    worksheet = sh.worksheet('DK_Build_Up')
     raw_display = pd.DataFrame(worksheet.get_all_records())
     raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
     raw_display.replace("", 'Welp', inplace=True)
     raw_display = raw_display.loc[raw_display['Player'] != 'Welp']
     raw_display = raw_display.loc[raw_display['Median'] > 0]
     raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
-    raw_display = raw_display.sort_values(by='Median', ascending=False)
-
-    return raw_display
-
-@st.cache_data
-def load_fd_overall_stats(URL):
-    sh = gc.open_by_url(URL)
-    worksheet = sh.get_worksheet(9)
+    dk_raw = raw_display.sort_values(by='Median', ascending=False)
+    
+    worksheet = sh.worksheet('FD_Build_Up')
     raw_display = pd.DataFrame(worksheet.get_all_records())
     raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
     raw_display.replace("", 'Welp', inplace=True)
     raw_display = raw_display.loc[raw_display['Player'] != 'Welp']
     raw_display = raw_display.loc[raw_display['Median'] > 0]
     raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
-    raw_display = raw_display.sort_values(by='Median', ascending=False)
+    fd_raw = raw_display.sort_values(by='Median', ascending=False)
 
-    return raw_display
+    return dk_raw, fd_raw
 
-raw_baselines = load_overall_stats(dk_player_url)
+dk_raw, fd_raw = load_overall_stats()
 
 tab1, tab2 = st.tabs(["Range of Outcomes Model", "Optimizer (Coming soon)"])
 
@@ -80,12 +72,12 @@ with tab1:
     with col1:
         if st.button("Load/Reset Data", key='reset1'):
               st.cache_data.clear()
-              raw_baselines = load_overall_stats(dk_player_url)
+              dk_raw, fd_raw = load_overall_stats()
         site_var1 = st.radio("What table would you like to display?", ('Draftkings', 'Fanduel'), key='site_var1')
         if site_var1 == 'Draftkings':
-            raw_baselines = load_overall_stats(dk_player_url)
+            raw_baselines = dk_raw
         elif site_var1 == 'Fanduel':
-            raw_baselines = load_fd_overall_stats(fd_player_url)
+            raw_baselines = fd_raw
         split_var1 = st.radio("Are you running the full slate or crtain games?", ('Full Slate Run', 'Specific Games'), key='split_var1')
         if split_var1 == 'Specific Games':
             team_var1 = st.multiselect('Which teams would you like to include in the ROO?', options = raw_baselines['Team'].unique(), key='team_var1')
@@ -98,9 +90,9 @@ with tab1:
         if st.button('Create Range of Outcomes for Slate'):
             with hold_container:
                         if site_var1 == 'Draftkings':
-                            raw_baselines = load_overall_stats(dk_player_url)
+                            raw_baselines = dk_raw
                         elif site_var1 == 'Fanduel':
-                            raw_baselines = load_fd_overall_stats(fd_player_url)
+                            raw_baselines = fd_raw
                         
                         working_roo = raw_baselines
                         working_roo = working_roo[working_roo['Team'].isin(team_var1)]
@@ -178,6 +170,7 @@ with tab1:
                         final_Proj = final_Proj[['Player', 'Minutes Proj', 'Position', 'Team', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '3x%', '4x%', '5x%', 'GPP%', 'Own', 'LevX', 'ValX']]
                         final_Proj = final_Proj.set_index('Player')
                         final_Proj = final_Proj.sort_values(by='Median', ascending=False)
+            
             with hold_container:
                 hold_container = st.empty()