Python for DevOps: Learn Ruthlessly Effective Automation

Most sites in the book meant for reference or continued learning are not working or are not in existence

No es fácil de leer porque me falta conocimiento de varias cosas que muestra.Sin embargo, el libro explica muy bien los temas.Al leer varias veces los capítulos, las cosas resultan más claras.

As the title suggests, I decided to purchase the book to get some practical insight about how to automate tasks with Python, having had some previous exposure. I was disappointed to discover that many topics are covered in a shallow way.It is mostly a mish-mash of different concepts.The first chapters mostly address introductory topics like data types (e.g. lists tuples dictionaries ) plus functions for handling data (e.g. open, with/open/as functions and so on) which can be found in other books as well. Besides, always for data processing, for a basic usage of Pandas and dataframes, it's better to check somewhere else.For the chapter on Linux, I use mostly Ubuntu & Arch, and for a basic introduction to the shell, it's way better to use Richard Blum's Linux Command Line & Shell Scripting Bible.As for ML OPs, it's way better to check Geron's Hands-on-ML textbook (and other advanced textbooks on the same topics)The section on Container Technologies(Docker) and Orchestration (Kubernetes) doesn't add a lot more than you can already find elsewhere. Nigel Poulton's Docker can be a starting pointFinally, I'm not an expert on Serverless Technologies & AWS Lambdas, and there seems to be some value in reading Chapter 13 . Still, the big picture is not entirely clear for me. I believe it would be better to integrate it with other sources, or to look directly for other specific references on this topic as wellIn short: I wouldn't spend time reading it

The book arrived in great conditions and as I state in the Subject, it seems more of a reference guide of useful libraries and commands of python to create automation pipelines, which is good if this is your aim.I'd recommend this book if you are a seasoned developer and would like a quick reference of the useful parts of the language.After I finish reading through the whole book I'll update this review with a more complete opinion.

Very informative, real world examples with a good introduction to Python. Covers all aspects of DevOps concepts with emphasis on automation. Does a good job explaining cloud computing, data engineering and ML concepts. Introduces a most useful explanation and configuration examples of Infrastructure as Code. Very useful section on command line and Linux Utilities within Python.