Update app.py

app.py

@@ -9,6 +9,70 @@ import random
 # [All the scheduling functions and analytics functions here]
 
 
+
+# 1. create_schedule
+def create_schedule(num_teams, num_conferences, num_inter_games):
+    full_schedule = []
+    for i in range(num_conferences):
+        conference_name = chr(65 + i)  # 'A', 'B', 'C', 'D', ...
+        combined_schedule = combine_schedules(conference_name, num_teams, num_inter_games)
+        assigned_dates = assign_dates_to_matches(combined_schedule)
+        full_schedule.extend(assigned_dates)
+    return pd.DataFrame(full_schedule, columns=["Team 1", "Team 2", "Date"])
+
+# 2. combine_schedules
+def combine_schedules(conference_name, num_teams, num_inter_games):
+    intra_conf_matches = generate_intra_conference_schedule(conference_name, num_teams)
+    inter_conf_matches = generate_inter_conference_schedule(conference_name, num_teams, num_inter_games)
+    return intra_conf_matches + inter_conf_matches
+
+# 3. generate_intra_conference_schedule
+def generate_intra_conference_schedule(conference_name, num_teams):
+    teams = [f"{conference_name}{i}" for i in range(1, num_teams + 1)]
+    matches = []
+    for i in range(len(teams)):
+        for j in range(i+1, len(teams)):
+            matches.append((teams[i], teams[j]))
+            matches.append((teams[j], teams[i]))  # Home and away
+    return matches
+
+# 4. generate_inter_conference_schedule
+def generate_inter_conference_schedule(conference_name, num_teams, num_inter_games):
+    current_conf_teams = [f"{conference_name}{i}" for i in range(1, num_teams + 1)]
+    other_confs = [chr(65 + i) for i in range(4) if chr(65 + i) != conference_name]
+    other_conf_teams = [f"{conf}{i}" for conf in other_confs for i in range(1, num_teams + 1)]
+    matches = []
+    for team in current_conf_teams:
+        opponents = random.sample(other_conf_teams, num_inter_games)
+        for opp in opponents:
+            matches.append((team, opp))
+    return matches
+
+# 5. assign_dates_to_matches
+def assign_dates_to_matches(matches):
+    start_date = date(2022, 11, 6)
+    end_date = date(2023, 3, 1)
+    available_dates = [start_date + timedelta(days=i) for i in range((end_date - start_date).days) if (start_date + timedelta(days=i)).weekday() in [0, 2, 3, 5]]
+    random.shuffle(available_dates)
+    return [(match[0], match[1], available_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):
+    full_schedule = []
+    for i in range(num_conferences):
+        conference_name = chr(65 + i)
+        combined_schedule = combine_schedules(conference_name, num_teams, num_inter_games)
+        shuffled_dates = assign_dates_to_matches(combined_schedule)
+        random.shuffle(shuffled_dates)
+        for match in shuffled_dates:
+            full_schedule.append({
+                "Team 1": match[0],
+                "Team 2": match[1],
+                "Date": match[2]
+            })
+    return pd.DataFrame(full_schedule)
+
+
 # Team Workload Analysis
 def team_workload_analysis(schedule_df):
     """Generate a bar chart showing the number of matches each team has per week."""