When managing Linux systems, automating repetitive tasks is key to efficiency and consistency. With crontab, you can schedule scripts to run at any interval — including every minute. In this short guide, we’ll create a script that simply prints HELLO WORLD, schedule it to run every minute, and log its output. You'll also learn how to monitor it live using tail -f, a powerful command-line tool for real-time log viewing.
[Step 1: Create the Python File]
Open a terminal and create the script file:
nano ~/hello.py
Paste the following code:
#!/usr/bin/env python3
from datetime import datetime
logfile = "/home/$USER/hello.log" # Replace $USER manually if needed
with open(logfile, "a") as f:
now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
f.write(f"[{now}] HELLO WORLD\n")
print("HELLO WORLD")
Tip: Replace "/home/$USER/hello.log" with your actual path, for example: "/home/isaac/hello.log"
Then make the file executable:
chmod +x ~/hello.py #bash
[Step 2: Add the script to crontab and Test and monitor logs live]
Open your user’s crontab:
crontab -e
Add this line at the bottom:
* * * * * /usr/bin/python3 /home/your_user/hello.py
After a minute, check if the log file was created:
ls -l ~/hello.log
Then, use tail -f to monitor the log in real-time:
tail -f ~/hello.log
You should see a new "HELLO WORLD" line appear every minute. Like on below image.
Conclusion
By following this step-by-step guide, you've learned how to schedule a simple Python script to run every minute using crontab. This script prints and logs a message, giving you a hands-on understanding of how cron jobs, logging, and real-time monitoring with tail -f work together in a Linux environment.
Even though this example is simple—just printing "HELLO WORLD"—the approach is powerful and scalable. You can adapt this pattern to automate tasks like data collection, backups, notifications, or system health checks.
Whether you're a beginner exploring automation or a developer integrating scripts into a production pipeline, mastering cron and logging is a foundational skill. Keep experimenting, build smarter scripts, and level up your DevOps toolbox!
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