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Python For Automation & Scripting
From Local Scripts to Scheduled, Production-Grade Infrastructure Automation
Build automation you can trust in production.
Automation doesn't simply make work faster—it multiplies both your successes and your mistakes. A poorly designed script may fail once. The same script running automatically every day can create a serious outage. This book teaches you how to design automation that is safe, resilient, and production-ready from the very beginning.
You'll build Foreman, a complete automation platform that grows chapter by chapter into a supervised infrastructure automation service capable of running unattended.
You'll learn how to:
- Create safe and idempotent file operations with professional command-line interfaces.
- Automate data processing, REST APIs, and responsible web scraping with built-in validation.
- Schedule recurring jobs correctly using cron and systemd while preventing overlapping executions.
- Manage remote Linux servers over SSH with staged deployments and rollback strategies.
- Automate AWS infrastructure using secure, least-privilege practices and cost-aware provisioning.
- Build resilient systems with retries, circuit breakers, structured logging, dry-run execution, and monitoring.
- Package and deploy automation tools as supervised production services.
- Complete two comprehensive capstone projects: Sentinel, a server monitoring and backup platform, and Ledger, a cloud cost anomaly detection system.
Rather than hiding complexity behind libraries, this book teaches the engineering principles that make automation reliable at scale. Every safeguard is built intentionally so you understand exactly what protects your infrastructure when something eventually goes wrong.
Designed for Python developers who want to move beyond simple scripts and build automation systems suitable for real production environments.
Reader reviews (1)
This book goes far beyond the usual Python scripting tutorials. What I particularly liked is the way it explains the difference between a script that simply works and automation that can actually be trusted to run unattended.
The Foreman project gives the book a strong practical structure. Instead of learning isolated techniques, you gradually build a complete automation toolkit covering filesystem operations, command-line tools, scheduling, APIs, SSH, cloud resources, configuration management, Docker, logging, monitoring, and error handling.
I also appreciated the strong emphasis on safety. Concepts such as idempotency, dry-run modes, error handling, observability, and testing in a disposable environment are treated as essential engineering practices rather than optional extras.
The two capstone projects are another strong point, especially the server health and backup suite and the cloud cost anomaly detection challenge. They make the book feel much closer to real DevOps and infrastructure work than a typical scripting guide.
A very useful book for Python developers who already know the language and want to move into automation, DevOps, infrastructure, and cloud operations. Highly recommended if you want to turn Python scripts into reliable tools that can actually run in production.
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