Book Image

Mastering Python Networking - Third Edition

By : Eric Chou
Book Image

Mastering Python Networking - Third Edition

By: Eric Chou

Overview of this book

Networks in your infrastructure set the foundation for how your application can be deployed, maintained, and serviced. Python is the ideal language for network engineers to explore tools that were previously available to systems engineers and application developers. In Mastering Python Networking, Third edition, you’ll embark on a Python-based journey to transition from traditional network engineers to network developers ready for the next-generation of networks. This new edition is completely revised and updated to work with Python 3. In addition to new chapters on network data analysis with ELK stack (Elasticsearch, Logstash, Kibana, and Beats) and Azure Cloud Networking, it includes updates on using newer libraries such as pyATS and Nornir, as well as Ansible 2.8. Each chapter is updated with the latest libraries with working examples to ensure compatibility and understanding of the concepts. Starting with a basic overview of Python, the book teaches you how it can interact with both legacy and API-enabled network devices. You will learn to leverage high-level Python packages and frameworks to perform network automation tasks, monitoring, management, and enhanced network security followed by Azure and AWS Cloud networking. Finally, you will use Jenkins for continuous integration as well as testing tools to verify your network.
Table of Contents (18 chapters)
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In this chapter, we looked at the version-control system known as Git and its close sibling, GitHub. Git was developed by Linus Torvolds in 2005 to help develop the Linux kernel and later adopted by other open source projects as their source-control system. Git is a fast, distributed, and scalable system. GitHub provides a centralized location to host Git repositories on the internet that allow anybody with an internet connection to collaborate.

We looked at how to use Git in the command line and its various operations and how they are applied in GitHub. We also studied two of the popular Python libraries for working with Git: GitPython and PyGitHub. We ended this chapter with a configuration backup example and notes about project collaboration.

In Chapter 14, Continuous Integration with Jenkins, we will look at another popular open source tool used for continuous integration and deployment: Jenkins.