Book Image

Mastering Python Networking

Book Image

Mastering Python Networking

Overview of this book

This book begins with a review of the TCP/ IP protocol suite and a refresher of the core elements of the Python language. Next, you will start using Python and supported libraries to automate network tasks from the current major network vendors. We will look at automating traditional network devices based on the command-line interface, as well as newer devices with API support, with hands-on labs. We will then learn the concepts and practical use cases of the Ansible framework in order to achieve your network goals. We will then move on to using Python for DevOps, starting with using open source tools to test, secure, and analyze your network. Then, we will focus on network monitoring and visualization. We will learn how to retrieve network information using a polling mechanism, ?ow-based monitoring, and visualizing the data programmatically. Next, we will learn how to use the Python framework to build your own customized network web services. In the last module, you will use Python for SDN, where you will use a Python-based controller with OpenFlow in a hands-on lab to learn its concepts and applications. We will compare and contrast OpenFlow, OpenStack, OpenDaylight, and NFV. Finally, you will use everything you’ve learned in the book to construct a migration plan to go from a legacy to a scalable SDN-based network.
Table of Contents (22 chapters)
Title
Humble Bundle
Credits
Foreword
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
12
OpenStack, OpenDaylight, and NFV

Chapter 3. API and Intent-Driven Networking

In the previous chapter, we looked at ways to interact with the device interactively using Pexpect and Paramiko. Both of these tools use a persistent session that simulates a user typing in commands as if they are sitting in front of the Terminal. This works fine up to a point. It is easy enough to send commands over for execution on the device and capture the output back. However, when the output becomes more than a few lines of characters, it becomes difficult for a computer program to interpret the output. In order for our simple computer program to automate some of what we do, we need to be able to interpret the returned results and make follow-up actions based on the returned result. When we cannot accurately and predictably interpret the results back, we cannot execute the next command with confidence.

Luckily, this problem was solved by the Internet community. Imagine the difference between a computer and a human being reading a web page...