Update app.py

app.py

@@ -10,6 +10,7 @@ import pandas as pd
 import streamlit as st
 import gspread
 import random
+import gc
 
 @st.cache_resource
 def init_conn():
@@ -146,14 +147,14 @@ def run_seed_frame(seed_depth1, Strength_var, strength_grow, Teams_used, Total_R
     while RunsVar <= seed_depth_def:
         if RunsVar <= 3:
             FieldStrength = Strength_var_def
-            FinalPortfolio, maps_dict = get_correlated_portfolio_for_sim(Total_Runs_def * .25, sharp_split, field_growth)
-            FinalPortfolio2, maps_dict2 = get_uncorrelated_portfolio_for_sim(Total_Runs_def * .25, sharp_split, field_growth)
+            FinalPortfolio, maps_dict = get_correlated_portfolio_for_sim(Total_Runs_def * .1, sharp_split, field_growth)
+            FinalPortfolio2, maps_dict2 = get_uncorrelated_portfolio_for_sim(Total_Runs_def * .1, sharp_split, field_growth)
             FinalPortfolio_init = pd.concat([FinalPortfolio, FinalPortfolio2], axis=0)
             maps_dict.update(maps_dict2)
         elif RunsVar > 3 and RunsVar <= 4:
             FieldStrength += (strength_grow_def + ((30 - len(Teams_used_def)) * .001))
-            FinalPortfolio3, maps_dict3 = get_correlated_portfolio_for_sim(Total_Runs_def * .25, sharp_split, field_growth)
-            FinalPortfolio4, maps_dict4 = get_uncorrelated_portfolio_for_sim(Total_Runs_def * .25, sharp_split, field_growth)
+            FinalPortfolio3, maps_dict3 = get_correlated_portfolio_for_sim(Total_Runs_def * .1, sharp_split, field_growth)
+            FinalPortfolio4, maps_dict4 = get_uncorrelated_portfolio_for_sim(Total_Runs_def * .1, sharp_split, field_growth)
             FinalPortfolio_merge_3 = pd.concat([FinalPortfolio_init, FinalPortfolio3], axis=0)
             FinalPortfolio_merge_4 = pd.concat([FinalPortfolio_merge_3, FinalPortfolio4], axis=0)
             FinalPortfolio_step_2 = FinalPortfolio_merge_4.drop_duplicates(subset = ['Projection', 'Own'],keep = 'last').reset_index(drop = True)
@@ -161,8 +162,8 @@ def run_seed_frame(seed_depth1, Strength_var, strength_grow, Teams_used, Total_R
             maps_dict.update(maps_dict4)
         elif RunsVar > 4:
             FieldStrength = 1
-            FinalPortfolio5, maps_dict5 = get_correlated_portfolio_for_sim(Total_Runs_def * .25, sharp_split, field_growth)
-            FinalPortfolio6, maps_dict6 = get_uncorrelated_portfolio_for_sim(Total_Runs_def * .25, sharp_split, field_growth)
+            FinalPortfolio5, maps_dict5 = get_correlated_portfolio_for_sim(Total_Runs_def * .1, sharp_split, field_growth)
+            FinalPortfolio6, maps_dict6 = get_uncorrelated_portfolio_for_sim(Total_Runs_def * .1, sharp_split, field_growth)
             FinalPortfolio_merge_5 = pd.concat([FinalPortfolio_step_2, FinalPortfolio5], axis=0)
             FinalPortfolio_merge_6 = pd.concat([FinalPortfolio_merge_5, FinalPortfolio6], axis=0)
             FinalPortfolio_export = FinalPortfolio_merge_6.drop_duplicates(subset = ['Projection', 'Own'],keep = 'last').reset_index(drop = True)
@@ -956,7 +957,7 @@ with tab2:
                         'team_check_map':dict(zip(cleaport_players.Player,nerf_frame.Team))
                         }
                     
-                    FinalPortfolio, maps_dict = run_seed_frame(10, Strength_var, strength_grow, Teams_used, 1000000, field_growth)
+                    FinalPortfolio, maps_dict = run_seed_frame(5, Strength_var, strength_grow, Teams_used, 1000000, field_growth)
                     
                     Sim_Winners = sim_contest(2500, FinalPortfolio, CleanPortfolio, maps_dict, up_dict, insert_port)
                     
@@ -1168,4 +1169,6 @@ del dkid_dict, fdid_dict
 del static_exposure, overall_exposure
 del insert_port1, Contest_Size, sharp_split, Strength_var, scaling_var, Sort_function, Sim_function, strength_grow, field_growth
 del raw_baselines
-del freq_format
+del freq_format
+
+gc.collect()