paiml/python_devops_book

[Book-2020] Python For DevOps: Learn Ruthlessly Effective Automation

Python For DevOps: Learn Ruthlessly Effective Automation

Publisher: O'Reilly Media

Release Date: December 31st, 2019

• Buy a Physical Copy from Amazon
• Buy a Kindle Copy from Amazon
• Buy a Physical Copy from Barnes and Noble
• Buy a Nook Book Copy from Barnes and Noble
• Read Online
• Download Source Code from Github
• Python for DevOps Website

Build Status

Abstract

Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation. Throughout these transformations, Python has become one of the most popular languages in the world. This practical resource shows you how to use Python for everyday Linux systems administration tasks with today’s most useful DevOps tools, including Docker, Kubernetes, and Terraform.

Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this book, you’ll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. Looking for effective ways to "get stuff done" in Python? This is your guide.

Python foundations, including a brief introduction to the language How to automate text, write command-line tools, and automate the filesystem Linux utilities, package management, build systems, monitoring and instrumentation, and automated testing Cloud computing, infrastructure as code, Kubernetes, and serverless Machine learning operations and data engineering from a DevOps perspective Building, deploying, and operationalizing a machine learning project

Book Outline

Chapter 1: Python Essentials for DevOps

Chapter 2: Automating Files and the Filesystem

Chapter 3: Working with the Command Line

• Source Case Study
• GPU Programming Colab Notebook
• Notes

Chapter 4: Useful Linux Utilities

Chapter 5: Package Management

Chapter 6: Continuous Integration and Continuous Deployment

• Source
• Notes

Chapter 7: Monitoring and Logging

Chapter 8: Pytest for DevOps

Chapter 9: Cloud Computing

• Source
• Notes

Chapter 10: Infrastructure as Code

Chapter 11: Container Technologies: Docker and Docker Compose

Chapter 12: Container Orchestration: Kubernetes

Chapter 13: Serverless Technologies

Chapter 14: MLOps and Machine learning Engineering

• Source
• Notes

Chapter 15: Data Engineering

• Source

Chapter 16: DevOps War Stories and Interviews

Got Feedback?

If you have any suggestions as the book is being developed please create a ticket and let us know! Thanks for helping make this an incredible book.

FAQ

A list of Frequently Asked Questions about the book:

• FAQ

Addendum

Updates on new material post book release.

• Addendum

Contact Authors

Noah Gift

• Noah Gift Website
• Noah Gift Linkedin
• Sign up for Pragmatic Labs Mailing List
• Read other books by Noah Gift
• Take courses by Noah Gift
• Watch Videos by Noah Gift
• Take the Foundations of Data Engineering Specialization
• Take the Specialization: Building Cloud Computing Solutions at Scale Specialization

📺 Latest YouTube Videos

• Leaving Apple Ecosystem in 2024 Livestream & Q/A
• Leaving Apple Ecosystem in 2024 Livestream & Q/A Post WWDC
• Pragmatic AI Labs Origin Story
• The Pragmatic AI Labs Alternative University
• Title: Cloud Computing Fundamentals: Models, Services, and AWS Overview
• AWS Billing and Support: Managing Costs and Leveraging Expertise
• AWS Well-Architected Framework: Designing Reliable and Efficient Cloud Solutions

Kennedy Behrman

• Kennedy Behrman Linkedin

Alfredo Deza

• Alfredo Deza

Grig Gheorghiu

• Grig Gheorghiu

python_devops_book's Issues

Create prototype

images

Supplemental files from /Users/kbehrman/Downloads

Greetings,
Is there a source or repo with the various files referenced from /Users/kbehrman/Downloads? For example, in Chapter 2 there are various xml, yaml, and csv files that are used but without the full version shown in the book.

Example 2-3. os_path_walk.py

Example 2-3. os_path_walk.py
It uses import fire and fire.Fire()
There is no mention or explanation about the fire module in Chapter 2
There should be a reference to explaining fire module in Chapter 3

Cython, SWIG

A second suggestion for 2nd edition -- include mention of exposing C/C++ libs in Python via wrapping tools like Cython, SWIG etc. Many times I've only got a Python project to the end by wrapping a C lib.

Case Study: Turbocharging Python with Command-Line Tools This is really hard to understand and follow along.

Case Study: Turbocharging Python with Command-Line Tools
This is really hard to understand and follow along.
Example:

• I see only expmean_jit function but no expmean(rea)
• Running NO JIT took: 0.0007 sec while Running with JIT took: 0.2180 sec
• I thought running with JIT would be faster than without JIT.

Python for devops

Chapter 1/2 examples

Like others, I've purchased the book and pulled the github repo, but can't find any of the CSV or code examples for chapters 1 + 2.
I see some closed issues regarding this but no answer to where these documents are.

MIA Supplemental Code Examples

I am unable to locate the supplemental code examples using the instructions and link to pythondevops.com that's mentioned in the book...

I go to the website and all I can do it register for the newsletter(Which I did.), go to the O'Reilly site, the book on Amazon, or right back here to the repo.

Please advise.

Example 3-2. Parsing with sys.argv

Example 3-2. Parsing with sys.argv
This code is not working.
Change target = 'Joe' to name = 'Joe', then it is working.

Example 3-5. click_example.py

Example 3-5. click_example.py
Correction in the comment section.
Command-line tool using click (instead of argparse)

Chapter 10. Infrastructure as Code - Cloudfront InvalidViewerCertificate error

Deployment fails with this message:
error creating CloudFront Distribution: InvalidViewerCertificate: The specified SSL certificate doesn't exist, isn't in us-east-1 region, isn't valid, or doesn't include a valid certificate chain

LXD/LXC

First bit of feedback -- it seems strange you haven't mentioned LXD/LXC containerisation as a Docker alternative. I looked at Docker, but went LXD/LXC for ease of setup, deployment, relocation. I know Docker suits many folks, but others will have their needs better met with LXD/LXC, so for your second edition, I could modestly recommend you give it a mention.

Create a cli tool that generates attribution for Payments from the O'Reilly quarterly spreadsheet

Pythondevops

Load Testing with molotov

After line, "save it as small.py":

(-) redirect('https://www.google.com/search?q=%s' % request.args['q'])
(+) return redirect('https://www.google.com/search?q=%s' % request.args['q'])

After line, "This is how the file looks in the end":

(-) assert redirect_status == 301, error
(+) assert redirect_status == 302, error