import gradio as gr import json import pandas as pd import os import shutil import datetime # Paths DATA_DIR = "data" DATA_FILE = os.path.join(DATA_DIR, "teamup_data.json") BACKUP_DIR = os.path.join(DATA_DIR, "backup") os.makedirs(DATA_DIR, exist_ok=True) ADMIN_CODE = os.getenv("ADMIN_CODE", "") # Init data file if not os.path.exists(DATA_FILE) or os.path.getsize(DATA_FILE) == 0: with open(DATA_FILE, "w") as f: json.dump([], f) # Country list ALL_COUNTRIES = sorted(list(set([ "United States of America", "United Kingdom", "India", "France", "Germany", "Canada", "Australia", "Japan", "Brazil", "Mexico", # Add or reduce to most relevant countries only for dropdown ] + [ # Fallback: full list "Afghanistan", "Albania", "Algeria", "Andorra", "Angola", "Argentina", "Armenia", "Austria", "Azerbaijan", "Bangladesh", "Belgium", "Bhutan", "Bolivia", "Bosnia and Herzegovina", "Botswana", "Bulgaria", "Cambodia", "Chile", "China", "Colombia", "Croatia", "Cuba", "Czech Republic", "Denmark", "Dominican Republic", "Ecuador", "Egypt", "Estonia", "Ethiopia", "Finland", "Greece", "Hungary", "Iceland", "Indonesia", "Iran", "Iraq", "Ireland", "Israel", "Italy", "Jordan", "Kenya", "Kuwait", "Latvia", "Lithuania", "Luxembourg", "Malaysia", "Malta", "Morocco", "Nepal", "Netherlands", "New Zealand", "Nigeria", "Norway", "Pakistan", "Peru", "Philippines", "Poland", "Portugal", "Qatar", "Romania", "Russia", "Saudi Arabia", "Serbia", "Singapore", "Slovakia", "Slovenia", "South Africa", "South Korea", "Spain", "Sri Lanka", "Sweden", "Switzerland", "Thailand", "Tunisia", "Turkey", "Ukraine", "United Arab Emirates", "Vietnam", "Zambia", "Zimbabwe" ]))) # Backup def backup_data(): os.makedirs(BACKUP_DIR, exist_ok=True) timestamp = datetime.datetime.now().strftime('%Y%m%d_%H%M%S') backup_file = os.path.join(BACKUP_DIR, f'teamup_data_backup_{timestamp}.json') shutil.copy(DATA_FILE, backup_file) # Safe save def atomic_save(data, path): tmp_path = path + ".tmp" with open(tmp_path, "w") as f: json.dump(data, f, indent=2) os.replace(tmp_path, path) # Profile submission def submit_profile(name, discord, city, country, address, looking, onlinecheck, languages, laptop, robot, skills, describe3, experience, idea): if not discord or not city or not country or not laptop or not robot: return "❌ Please fill in all required fields." if not languages or not isinstance(languages, list): return "❌ Please select at least one language." # Normalize input city = city.strip().title() country = country.strip().title() discord = discord.strip() with open(DATA_FILE, "r") as f: data = json.load(f) for entry in data: if entry["Discord"].lower() == discord.lower(): entry.update({ "Name": name, "City": city, "Country": country, "Address": address, "Looking for Team": looking, "Onlinecheck": onlinecheck, "Languages": languages, "Laptop": laptop, "Robot": robot, "Skills": skills, "Describe3": describe3, "Experience": experience, "Project Idea": idea }) break else: data.append({ "Name": name, "Discord": discord, "City": city, "Country": country, "Address": address, "Looking for Team": looking, "Onlinecheck": onlinecheck, "Languages": languages, "Laptop": laptop, "Robot": robot, "Skills": skills, "Describe3": describe3, "Experience": experience, "Project Idea": idea }) try: atomic_save(data, DATA_FILE) backup_data() return "✅ Profile saved!" except Exception as e: return f"❌ Failed to save: {e}" # City dropdown update def update_city_filter(country): with open(DATA_FILE, "r") as f: data = json.load(f) df = pd.DataFrame(data) if country != "All": df = df[df["Country"].str.title() == country.title()] cities = sorted(set(df["City"].dropna().unique())) return gr.update(choices=["All"] + cities, value="All") # Filter participants def filter_by_fields(selected_country, selected_city, selected_language): with open(DATA_FILE, "r") as f: data = json.load(f) if not data: return "
No data available.
" df = pd.DataFrame(data) # Normalize Country & City df["Country"] = df["Country"].astype(str).str.strip().str.title() df["City"] = df["City"].astype(str).str.strip().str.title() # Normalize Languages: always string, lowercase, comma-separated df["Languages"] = df["Languages"].apply( lambda x: ", ".join(x) if isinstance(x, list) else str(x) ).str.strip().str.lower() # Normalize filters if selected_country != "All": selected_country = selected_country.strip().title() df = df[df["Country"] == selected_country] if selected_city != "All": selected_city = selected_city.strip().title() df = df[df["City"] == selected_city] if selected_language != "All": selected_language = selected_language.strip().lower() df = df[df["Languages"].str.contains(selected_language, na=False)] if df.empty: return "No participants match your filters.
" # Hide address if present if "Address" in df.columns: df = df.drop(columns=["Address"]) display_names = { "Discord": "Discord", "Name": "Name", "City": "City", "Country": "Country", "Looking for Team": "Looking for Team", "Onlinecheck": "How?", "Languages": "Languages", "Laptop": "Laptop", "Robot": "Robot", "Skills": "Skills", "Describe3": "Description", "Experience": "Experience", "Project Idea": "Project Idea" } html = '| {display_names.get(col, col)} | " html += "
|---|
| {val} | " html += "