demo_simulated.py

# demo_simulated.py - Generate realistic demo data
import pandas as pd
import numpy as np
from datetime import datetime, timedelta
import random

class SimulatedDemo:
    """Generate simulated attendance data for dashboard demo"""
    
    def __init__(self):
        self.employees = self._create_employees()
        self.attendance_log = []
        
    def _create_employees(self):
        """Create employee database"""
        names = [
            "Alice Johnson", "Bob Smith", "Carol White", 
            "David Brown", "Eve Davis", "Frank Wilson",
            "Grace Lee", "Henry Kim", "Ivy Chen", "Jack Taylor"
        ]
        
        employees = []
        for i, name in enumerate(names, 1):
            employees.append({
                'id': i,
                'name': name,
                'department': random.choice(['Engineering', 'Sales', 'HR', 'Marketing']),
                'shift_start': '09:00',
                'shift_end': '18:00'
            })
        return employees
    
    def generate_attendance(self, days=30):
        """Generate simulated attendance data"""
        end_date = datetime.now()
        start_date = end_date - timedelta(days=days)
        
        attendance = []
        
        for day in range(days):
            current_date = start_date + timedelta(days=day)
            # Skip weekends
            if current_date.weekday() >= 5:
                continue
                
            for employee in self.employees:
                # 90% attendance rate
                if random.random() < 0.9:
                    check_in = self._random_time(current_date, 8, 10)
                    check_out = self._random_time(current_date, 17, 19)
                    
                    status = self._determine_status(check_in, '09:00')
                    
                    attendance.append({
                        'employee_name': employee['name'],
                        'date': current_date.strftime('%Y-%m-%d'),
                        'check_in': check_in.strftime('%H:%M'),
                        'check_out': check_out.strftime('%H:%M'),
                        'status': status,
                        'department': employee['department']
                    })
        
        self.attendance_log = pd.DataFrame(attendance)
        return self.attendance_log
    
    def _random_time(self, date, hour_start, hour_end):
        """Generate random time within range"""
        hour = random.randint(hour_start, hour_end)
        minute = random.randint(0, 59)
        return date.replace(hour=hour, minute=minute)
    
    def _determine_status(self, check_in, shift_start):
        """Determine attendance status"""
        shift_hour, shift_min = map(int, shift_start.split(':'))
        shift_start_time = check_in.replace(hour=shift_hour, minute=shift_min)
        
        if check_in < shift_start_time:
            return 'early'
        elif check_in <= shift_start_time + timedelta(minutes=15):
            return 'on_time'
        else:
            return 'late'

# Generate and save demo data
demo = SimulatedDemo()
attendance_data = demo.generate_attendance()

# Save as CSV for dashboard
attendance_data.to_csv('demo_attendance_data.csv', index=False)
print("✅ Demo data generated and saved to 'demo_attendance_data.csv'")