Python for DevOps: Mastering Real-World Automation
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Unclaimed ProfileDesigned for system administrators, DevOps engineers, and software developers looking to bridge the gap between operations and code, Lauro Fialho Müller’s comprehensive course, Python for DevOps: Mastering Real-World Automation, provides a deep dive into modern infrastructure automation. As modern software environments grow increasingly complex, relying on manual operations or simple shell scripts is no longer viable. This hands-on curriculum equips IT professionals with the essential skills to build robust, scalable tools using Python. Throughout the 24 hours of instruction, learners transition from basic Python fundamentals to advanced concepts such as memory-efficient decorators, generator functions, and structured JSON logging. You will explore critical administrative tasks including secure subprocess execution, file system management using pathlib, and robust API integration with customized retry mechanisms and exponential backoff. Crucially, the course emphasizes modern engineering best practices, guiding students through professional unit testing with pytest, mock isolating dependencies, and organizing scripts into distributable CLI packages. By completing the numerous coding labs and quizzes, engineers will be fully prepared to optimize their CI/CD pipelines and drive efficiency across cloud deployments.
About the creator
Lauro Fialho Müller
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Reviews
Lauro Fialho Müller is a seasoned software engineer and DevOps specialist dedicated to bridging the gap between traditional system administration and modern, AI-driven development workflows. With years of hands-on experience in scripting, automation pipelines, and cloud infrastructure, Lauro has transitioned into helping developers optimize their day-to-day operations using Python and cutting-edge artificial intelligence tools. His teaching philosophy centers on immediate, practical application, ensuring that students do not just memorize syntax but learn how to engineer real-world solutions. Through his courses, such as his deep dive into Python for DevOps and his comprehensive guide to developer-focused prompt engineering, Lauro equips his…Show more
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Program Overview
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Learning format
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Price
Price may change · updated within 1–2 weeks
Course language
What You'll Learn
- Master Python fundamentals from variables and data structures to functions and classes.
- Write elegant and memory-efficient code using advanced features like generators and decorators.
- Implement robust error handling with try/except blocks and custom exceptions to build resilient scripts.
- Integrate structured JSON logging into your applications for improved observability and troubleshooting.
- Confidently parse, process, and generate essential data formats like JSON, YAML, and CSV.
- Automate file and directory management using modern pathlib and shutil.
- Run external system commands securely and capture their output using the subprocess module.
- Automate REST API interactions by sending GET/POST requests and handling authentication with the requests library.
- Build resilient API clients that handle timeouts and implement retry logic with exponential backoff.
- Write and run professional unit tests using the powerful pytest framework.
- Use fixtures and parametrization to write clean, reusable, and data-driven tests.
- Isolate dependencies and test complex interactions by creating and configuring mocks.
- Structure your code professionally using Python modules and packages for better maintainability.
- Build and distribute your own installable command-line tools using pyproject.toml and entry points.
Best For
- System administrators and IT professionals looking to automate manual infrastructure tasks with Python.
- DevOps engineers seeking to move beyond basic shell scripting to develop robust, production-grade automation tools.
- Software developers who need to improve their skills in building CLI tools and integrating with cloud APIs.
- Engineers preparing to implement automated testing and CI/CD pipelines using professional testing frameworks like pytest.
Not For
- Complete programming beginners with zero prior experience in Python or basic scripting logic.
- Data scientists or AI/ML researchers looking for specialized training in Pandas, NumPy, or machine learning model deployment.
- Individuals seeking a beginner-level introduction to DevOps theory without any focus on coding or automation implementation.
- Advanced Python experts who are already proficient in professional software engineering patterns, testing, and packaging.
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