Cron Expression: Weekdays 9 AM to 6 PM (0 9-18 * * 1-5)

The cron expression 0 9-18 * * 1-5 executes a task every hour on weekdays (Monday through Friday) between 9 AM and 6 PM, making it ideal for business-hour operations, reports, and tasks that should run only during workdays.

Expression Breakdown

0 9-18 * * 1-5
│ │   │ │ │
│ │   │ │ └─── Day of week: 1-5 (Monday to Friday)
│ │   │ └───── Month: * (every month)
│ │   └─────── Day of month: * (every day)
│ └─────────── Hour: 9-18 (9 AM to 6 PM)
└───────────── Minute: 0 (at minute 0)

Field Values

Combined Syntax

• Range (9-18): Hours 9 through 18
• Range (1-5): Monday through Friday
• Combined: Every hour from 9 AM to 6 PM on weekdays only

Execution Time

This expression runs 50 times per week (10 hours × 5 weekdays) at:

• Monday-Friday: 09:00, 10:00, 11:00, 12:00, 13:00, 14:00, 15:00, 16:00, 17:00, 18:00

Common Use Cases

1. Business Hour Reports

0 9-18 * * 1-5 /usr/bin/python3 /scripts/generate-hourly-report.py

Generate hourly reports during business hours on weekdays.

2. Business Hour Monitoring

0 9-18 * * 1-5 /usr/local/bin/business-hour-monitor.sh

Monitor system health or services hourly during workdays.

3. Business Hour Data Sync

0 9-18 * * 1-5 /usr/bin/python3 /scripts/sync-hourly-data.py

Sync data from external systems or APIs hourly during business hours.

4. Business Hour Cache Refresh

0 9-18 * * 1-5 /usr/bin/python3 /scripts/refresh-cache.py

Refresh cached data or computed values hourly during workdays.

Example Implementations

Business Hour Report Script

# generate-hourly-report.py
import json
from datetime import datetime, timedelta
import sqlite3

def generate_hourly_report():
    conn = sqlite3.connect('/var/data/app.db')
    cursor = conn.cursor()
    
    # Get data from last hour
    end_time = datetime.now()
    start_time = end_time - timedelta(hours=1)
    
    cursor.execute('''
        SELECT 
            COUNT(*) as total_requests,
            AVG(response_time) as avg_response_time,
            COUNT(CASE WHEN status_code >= 400 THEN 1 END) as errors
        FROM requests
        WHERE timestamp >= ? AND timestamp < ?
    ''', (start_time, end_time))
    
    metrics = cursor.fetchone()
    
    report = {
        'hour': end_time.strftime('%Y-%m-%d %H:00'),
        'day_type': 'business_day',
        'metrics': {
            'total_requests': metrics[0],
            'avg_response_time': round(metrics[1], 2) if metrics[1] else 0,
            'errors': metrics[2]
        }
    }
    
    with open(f'/var/reports/business_hour_{end_time.strftime("%Y%m%d_%H")}.json', 'w') as f:
        json.dump(report, f, indent=2)
    
    print(f"{datetime.now()}: Business hour report generated")
    conn.close()

if __name__ == '__main__':
    generate_hourly_report()

Best Practices

1. Business Hours Only: Excludes weekends and off-hours
2. Error Handling: Implement comprehensive error handling and logging
3. Locking: Use file locks to prevent concurrent execution
4. Monitoring: Set up alerts for failed jobs
5. Performance: Optimize tasks to complete quickly during business hours

When to Use

✅ Good for:

• Business hour reports
• Business hour monitoring
• Business hour data sync
• Tasks that should only run during workdays
• Regular business-hour operations

❌ Avoid for:

• Tasks that need to run every day including weekends
• Real-time critical operations (use every minute)
• Very long-running processes

Related Patterns

Conclusion

The 0 9-18 * * 1-5 expression is perfect for business-hour operations on weekdays only. It's commonly used for hourly reports, monitoring, and data synchronization during work hours, excluding weekends and off-hours from the schedule.