DevOps in Python: Infrastructure as Python

Author:   Moshe Zadka
Publisher:   APress
Edition:   2nd ed.
ISBN:  

9781484279953


Pages:   234
Publication Date:   30 June 2022
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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DevOps in Python: Infrastructure as Python


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Full Product Details

Author:   Moshe Zadka
Publisher:   APress
Imprint:   APress
Edition:   2nd ed.
Weight:   0.485kg
ISBN:  

9781484279953


ISBN 10:   1484279956
Pages:   234
Publication Date:   30 June 2022
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Chapter 1 (Installing Python) Different ways to install Python: • Compiling from source • OS packages • pyenv   Chapter 2 (Packaging) (31 pages – 11 new pages) How pip works and how to build packages. The following sections need to change Section about pip (adds 4 pages) • Add explanation about how the resolver works • Explain pip-compile Poetry and pipenv (changes 2 pages, adds 2 pages) • Needs to be separated into two sections • Poetry section updated to reflect changes in Poetry • Pipenv section updated to reflect changes in Pipenv 4setup.py and wheel (rewritten, changes 1 page, adds 2 pages) • python -m build and setup.cfg • Add details about binary wheels and manylinux • Show a complete example   Chapter 3: Interactive usage How to use the interactive interpreter, other text-mode interactive consoles, and Jupyter.   Chapter 4: OS Automation (16 pages – 4 new pages) Automating OS-related things like files and processes. Section about files (2 pages added) • Cover using struct to parse binary data • Cover pathlib New section: low-level networking (2 pages) Cover socket, socket options, and how it relates to TCP networking.   5 Chapter 5: Testing (30 pages – 10 new pages) Writing unit tests for DevOps code. Section about testing files (4 pages added) • Improve performance of file testing using tmpfs and preloading libraries • Add information about temporary directory context manager Section about testing networking (4 pages added) • Show how to test httpx with the WSGI support • Show how to test low-level socket networking with DI Section about testing processes (2 pages changed) • Mention run and Popen • Show how to write tests with DI on run and Popen   6 Chapter 6: Text manipulation How to work with text: searching, modifiying, formatting, etc.   Chapter 7: Requests -> httpx (rewritten – 10 new pages) • Focus on httpx instead • Cover async usage   Chapter 8: Cryptography Symmetric and asymmetric encryption and digital signatures, and how to use them in DevOps code.   Chapter 9: Paramiko Using paramiko to automate SSH use.   Chapter 10: Salt Stack Using salt stack and writing new modules.   Chapter 11: Ansible Using ansible and writing new modules.   Chapter 12: Docker (5 new pages) • Clean up examples – they are hard to read • Show complete example of layering, not just talk in theory • Show complete example of running, not just talk in theory • Add section about how to build containers for Python applications   Chapter 13: AWS Automating AWS using the boto3 library.   New: Chapter 14: Kubernetes (10 pages) Chapter goal: Learn how to automate k8s with Python and how to run Python applications on k8s • Packaging Python applications for kubernetes – Using secrets – Thinking in Pods • Automating k8s from Python using the REST API • Writing k8s operators with Python   New: Chapter 15: Terraform (5 pages) • Using the Terraform Python CDK • Generating Terraform JSON from Python

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Author Information

Moshe has been involved in the Linux community since 1998, helping in Linux “installation parties”. Moshe has been programming Python since 1999 and has contributed to the core Python interpreter. Moshe has been a DevOps/SRE since before those terms existed, caring deeply about software reliability, build reproducibility, and other such things. They have worked in companies as small as three people and as big as tens of thousands – usually in someplace around where software meets system administration.

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