Book Image

Python Network Programming Cookbook - Second Edition

By : Pradeeban Kathiravelu, Gary Berger, Dr. M. O. Faruque Sarker
Book Image

Python Network Programming Cookbook - Second Edition

By: Pradeeban Kathiravelu, Gary Berger, Dr. M. O. Faruque Sarker

Overview of this book

Python Network Programming Cookbook - Second Edition highlights the major aspects of network programming in Python, starting from writing simple networking clients to developing and deploying complex Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) systems. It creates the building blocks for many practical web and networking applications that rely on various networking protocols. It presents the power and beauty of Python to solve numerous real-world tasks in the area of network programming, network and system administration, network monitoring, and web-application development. In this edition, you will also be introduced to network modelling to build your own cloud network. You will learn about the concepts and fundamentals of SDN and then extend your network with Mininet. Next, you’ll find recipes on Authentication, Authorization, and Accounting (AAA) and open and proprietary SDN approaches and frameworks. You will also learn to configure the Linux Foundation networking ecosystem and deploy and automate your networks with Python in the cloud and the Internet scale. By the end of this book, you will be able to analyze your network security vulnerabilities using advanced network packet capture and analysis techniques.
Table of Contents (15 chapters)

Simulating networks with ns-3

Data centers and cloud networks span across a large number of nodes. Network topologies and applications of that scale often can be tested first in simulations to ensure that early results are verified quick before an extensive deployment and testing in a more realistic emulation or a physical test bench. In this recipe, we will learn to simulate network systems with ns-3.

Getting ready

First download ns-3 from https://www.nsnam.org/ns-3-26/download/. We are using ns-3.26 in this recipe. Extract the downloaded archive and run from the root directory ns-allinone-3.26:

$ ./build.py.

Since the allinone folder contains all the bundles, this build will consume a few minutes.

It shows the following...