Cron Expression: Every Day at 6:00 AM (0 6 * * *)
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Cron Expression: Every Day at 6:00 AM (0 6 * * *)
The cron expression 0 6 * * * executes a task every day at 6:00 AM, making it ideal for pre-dawn maintenance, data preparation, and tasks that should complete before business hours begin.
Expression Breakdown
0 6 * * *
│ │ │ │ │
│ │ │ │ └─── Day of week: * (every day)
│ │ │ └───── Month: * (every month)
│ │ └─────── Day of month: * (every day)
│ └───────── Hour: 6 (at hour 6, 6:00 AM)
└─────────── Minute: 0 (at minute 0)
Field Values
| Field | Value | Meaning |
|---|---|---|
| Minute | 0 | At minute 0 |
| Hour | 6 | At hour 6 (6:00 AM) |
| Day of Month | * | Every day (1-31) |
| Month | * | Every month (1-12) |
| Day of Week | * | Every day of week (0-7) |
Execution Time
This expression runs once per day at:
- 06:00 (6:00 AM)
Common Use Cases
1. Pre-Business Hours Preparation
0 6 * * * /usr/bin/python3 /scripts/prepare-daily-data.py
Prepare data, reports, or resources before business hours start.
2. Cache Warming
0 6 * * * /usr/bin/python3 /scripts/warm-cache.py
Pre-load frequently accessed data into cache for the day.
3. Database Refresh
0 6 * * * /usr/local/bin/refresh-db.sh
Refresh database views, materialized tables, or computed data.
4. Email Queue Processing
0 6 * * * /usr/bin/node /app/process-email-queue.js
Process overnight email queues before users start their day.
Example Implementations
Data Preparation Script
# prepare-daily-data.py
from datetime import datetime
import sqlite3
def prepare_daily_data():
conn = sqlite3.connect('/var/data/app.db')
cursor = conn.cursor()
# Refresh materialized views
cursor.execute('REFRESH MATERIALIZED VIEW daily_summary;')
# Update computed statistics
cursor.execute('''
UPDATE daily_stats
SET last_updated = ?
WHERE date = DATE('now')
''', (datetime.now(),))
conn.commit()
conn.close()
print(f"{datetime.now()}: Daily data preparation completed")
if __name__ == '__main__':
prepare_daily_data()
Cache Warming Script
# warm-cache.py
import redis
import requests
from datetime import datetime
def warm_cache():
r = redis.Redis(host='localhost', port=6379, db=0)
# Pre-load frequently accessed data
endpoints = [
'/api/popular-items',
'/api/daily-stats',
'/api/trending-content'
]
for endpoint in endpoints:
try:
response = requests.get(f'https://api.example.com{endpoint}', timeout=30)
if response.status_code == 200:
r.setex(f'cache:{endpoint}', 3600, response.text)
print(f"Cached: {endpoint}")
except Exception as e:
print(f"Failed to cache {endpoint}: {e}")
print(f"{datetime.now()}: Cache warming completed")
if __name__ == '__main__':
warm_cache()
Best Practices
- Timing: 6 AM ensures tasks complete before typical business hours (8-9 AM)
- Error Handling: Implement comprehensive error handling and logging
- Locking: Use file locks to prevent concurrent execution
- Monitoring: Set up alerts for failed jobs
- Performance: Optimize tasks to complete quickly before users arrive
When to Use
✅ Good for:
- Pre-business hours preparation
- Cache warming
- Database refresh
- Email queue processing
- Data preparation
❌ Avoid for:
- Real-time critical operations
- Tasks requiring immediate execution
Related Patterns
| Pattern | Expression | Description |
|---|---|---|
| Daily at 2 AM | 0 2 * * * | Early morning |
| Daily at 6 AM | 0 6 * * * | Pre-dawn |
| Daily at 8 AM | 0 8 * * * | Start of business day |
Conclusion
The 0 6 * * * expression is perfect for tasks that need to complete before business hours begin. It's commonly used for data preparation, cache warming, and preparing systems for the day ahead.
Need to generate a cron expression?
Use CronOS to generate any cron expression you wish with natural language. Simply describe what you need, and we'll create the perfect cron expression for you. It's completely free!