Update app.py

app.py

@@ -6,6 +6,8 @@ import seaborn as sns
 from datetime import date, timedelta
 import random
 
+
+
 # [All the scheduling functions and analytics functions here]
 
 
@@ -61,8 +63,8 @@ def assign_dates_to_matches(matches):
     return [(match[0], match[1], extended_dates[i]) for i, match in enumerate(matches)]
 
 
-# 6. generate_mock_historical_data
-def generate_mock_historical_data(num_teams, num_conferences, num_inter_games, start_date, end_date):
+# 6. generate_mock_st.session_state.historical_data
+def generate_mock_st.session_state.historical_data(num_teams, num_conferences, num_inter_games, start_date, end_date):
     full_schedule = []
     for i in range(num_conferences):
         conference_name = chr(65 + i)
@@ -165,10 +167,18 @@ def commissioner_analytics(schedule_df, commissioners):
 
 st.title("Basketball Game Schedule Generator")
 
-# Initialize session state for schedule_df
+# Initialize session state for schedule_df and st.session_state.historical_data
 if 'schedule_df' not in st.session_state:
     st.session_state.schedule_df = None
 
+if 'st.session_state.historical_data' not in st.session_state:
+    st.session_state.st.session_state.historical_data = None
+
+if st.session_state.st.session_state.historical_data is None:
+    st.session_state.st.session_state.historical_data = generate_mock_st.session_state.historical_data(num_teams, num_conferences, num_inter_games, date(2022, 11, 6), date(2023, 3, 1))
+    st.session_state.st.session_state.historical_data['Date'] = pd.to_datetime(st.session_state.st.session_state.historical_data['Date'])
+
+    
 # Configuration UI
 st.header("Configuration")
 
@@ -200,29 +210,29 @@ if st.session_state.schedule_df is not None:
 # Analytics & Comparisons
 st.header("Analytics & Comparisons")
 analytics_option = st.selectbox("Choose an analysis type:", ["Team Workload Analysis", "Match Distribution", "Inter-Conference Match Analysis", "Commissioner Analytics"])
-historical_data['Date'] = pd.to_datetime(historical_data['Date'])
+st.session_state.historical_data['Date'] = pd.to_datetime(st.session_state.historical_data['Date'])
 
 if analytics_option == "Team Workload Analysis":
     st.subheader("Historical Data")
-    st.pyplot(team_workload_analysis(historical_data))
+    st.pyplot(team_workload_analysis(st.session_state.historical_data))
     st.subheader("Current Data")
     st.pyplot(team_workload_analysis(st.session_state.schedule_df))
 
 elif analytics_option == "Match Distribution":
     st.subheader("Historical Data")
-    st.pyplot(match_distribution(historical_data))
+    st.pyplot(match_distribution(st.session_state.historical_data))
     st.subheader("Current Data")
     st.pyplot(match_distribution(st.session_state.schedule_df))
 
 elif analytics_option == "Inter-Conference Match Analysis":
     st.subheader("Historical Data")
-    st.pyplot(inter_conference_analysis(historical_data))
+    st.pyplot(inter_conference_analysis(st.session_state.historical_data))
     st.subheader("Current Data")
     st.pyplot(inter_conference_analysis(st.session_state.schedule_df))
 
 elif analytics_option == "Commissioner Analytics":
     st.subheader("Historical Data")
-    st.pyplot(commissioner_analytics(historical_data, commissioners))
+    st.pyplot(commissioner_analytics(st.session_state.historical_data, commissioners))
     st.subheader("Current Data")
     st.pyplot(commissioner_analytics(st.session_state.schedule_df, commissioners))