import pandas as pd

import csv

def enhance_mlh_schedule(input_csv_path, projects_csv_path, output_csv_path):

"""

Enhance the MLH judging schedule by:

1. Adding the specific bounties/categories each team submitted to

2. Removing team ID from the display

Args:

input_csv_path: Path to the MLH judging schedule CSV

projects_csv_path: Path to the main projects data CSV

output_csv_path: Path to save the enhanced schedule

"""

print(f"Processing MLH schedule from: {input_csv_path}")

mlh_schedule = []

try:

with open(input_csv_path, 'r', newline='', encoding='utf-8') as csvfile:

reader = csv.DictReader(csvfile)

for row in reader:

mlh_schedule.append(row)

except Exception as e:

print(f"Error reading MLH schedule: {e}")

return

print(f"Read {len(mlh_schedule)} entries from MLH schedule")

# Read the project data to get categories/bounties

try:

projects_df = pd.read_csv(projects_csv_path)

print(f"Read {len(projects_df)} projects from main CSV")

except Exception as e:

print(f"Error reading projects CSV: {e}")

return

team_categories = {}

for _, row in projects_df.iterrows():

team_name = row['BUIDL name']

categories = []

# Add track if available

if pd.notna(row['Track']):

categories.append(row['Track'])

# Add bounties if available

if pd.notna(row['Bounties']):

# Parse bounties

bounties = row['Bounties'].replace('"', '')

if ',' in bounties:

bounties_list = [b.strip() for b in bounties.split(',')]

categories.extend(bounties_list)

else:

categories.append(bounties.strip())

# Filter to only MLH-related categories

mlh_keywords = ["MLH", ".Tech", "MongoDB", "Gen AI"]

mlh_categories = []

for cat in categories:

if any(keyword.lower() in cat.lower() for keyword in mlh_keywords):

mlh_categories.append(cat)

if team_name:

team_categories[team_name] = mlh_categories

enhanced_schedule = []

for entry in mlh_schedule:

# Extract team name without ID

if 'TEAM' in entry and '-' in entry['TEAM']:

parts = entry['TEAM'].split(' - ', 1)

if len(parts) > 1:

team_id = parts[0]

team_name = parts[1]

# Update to remove ID

entry['TEAM'] = team_name

# Add categories if available

if team_name in team_categories:

entry['CATEGORIES'] = ', '.join(team_categories[team_name])

else:

# Try looking up by team ID

matching_teams = projects_df[projects_df['BUIDL ID'] == int(team_id)]

if not matching_teams.empty:

row = matching_teams.iloc[0]

categories = []

if pd.notna(row['Track']):

categories.append(row['Track'])

if pd.notna(row['Bounties']):

bounties = row['Bounties'].replace('"', '')

if ',' in bounties:

bounties_list = [b.strip() for b in bounties.split(',')]

categories.extend(bounties_list)

else:

categories.append(bounties.strip())

mlh_categories = []

for cat in categories:

if any(keyword.lower() in cat.lower() for keyword in mlh_keywords):

mlh_categories.append(cat)

entry['CATEGORIES'] = ', '.join(mlh_categories)

else:

entry['CATEGORIES'] = ''

enhanced_schedule.append(entry)

# Determine fieldnames - keep original and add CATEGORIES

if mlh_schedule:

fieldnames = list(mlh_schedule[0].keys())

if 'CATEGORIES' not in fieldnames:

fieldnames.append('CATEGORIES')

else:

fieldnames = ['TIMESLOT', 'TEAM', 'Creativity (/10)', 'Usefulness (/10)',

'Presentation (/10)', 'Technical Difficulty (/10)', 'CATEGORIES']

# Write the enhanced schedule

try:

with open(output_csv_path, 'w', newline='', encoding='utf-8') as csvfile:

writer = csv.DictWriter(csvfile, fieldnames=fieldnames)

writer.writeheader()

writer.writerows(enhanced_schedule)

print(f"Enhanced MLH schedule written to: {output_csv_path}")

except Exception as e:

print(f"Error writing enhanced schedule: {e}")

if __name__ == "__main__":

mlh_schedule_path = "mlh.csv"

projects_data_path = "buidl_export(8).csv"

output_path = "Enhanced_MLH_Schedule.csv"

enhance_mlh_schedule(mlh_schedule_path, projects_data_path, output_path)