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.

Preface

Who this book is for

What this book covers

To get the most out of this book

Review of TCP/IP Protocol Suite and Python

Review of TCP/IP Protocol Suite and Python

An overview of the internet

Client-server model

Network protocol suites

Python language overview

Free Chapter

Low-Level Network Device Interactions

Low-Level Network Device Interactions

The challenges of the CLI

Constructing a virtual lab

Python Pexpect library

The Python Paramiko library

The Netmiko library

The Nornir framework

APIs and Intent-Driven Networking

APIs and Intent-Driven Networking

Infrastructure-as-code

The Cisco API and ACI

Cisco Meraki controller

The Python API for Juniper Networks

The Arista Python API

Other libraries

The Python Automation Framework – Ansible Basics

The Python Automation Framework – Ansible Basics

Ansible – a more declarative framework

A quick Ansible example

The Advantages of Ansible

The Ansible architecture

Ansible networking modules

The Ansible Cisco example

Ansible 2.8 playbook example

The Ansible Juniper example

The Ansible Arista example

The Python Automation Framework – Beyond Basics

The Python Automation Framework – Beyond Basics

Lab preparation

Ansible conditionals

Group and host variables

The Ansible Vault

The Ansible include and roles

Writing your own custom module

Network Security with Python

Network Security with Python

The Syslog search

Further reading

Network Monitoring with Python – Part 1

Network Monitoring with Python – Part 1

Python for data visualization

Python for Cacti

Network Monitoring with Python – Part 2

Network Monitoring with Python – Part 2

Flow-based monitoring

ntop traffic monitoring

Building Network Web Services with Python

Building Network Web Services with Python

Comparing Python web frameworks

Flask and lab setup

Introduction to Flask

Network resource API

Network dynamic operations

Authentication and authorization

Running Flask in containers

AWS Cloud Networking

AWS Cloud Networking

AWS network overview

Virtual private cloud

Direct Connect and VPN

Network scaling services

Other AWS network services

Azure Cloud Networking

Azure Cloud Networking

Azure and AWS network service comparison

Azure administration and APIs

Azure global infrastructure

Azure virtual networks

Azure ExpressRoute

Azure Network Load Balancers

Other Azure network services

Network Data Analysis with Elastic Stack

Network Data Analysis with Elastic Stack

What is the Elastic Stack?

Elastic Stack as a Service

First End-to-End example

Elasticsearch with a Python client

Data ingestion with Logstash

Data ingestion with Beats

Search with Elasticsearch

Data visualization with Kibana

Working with Git

Working with Git

Content management considerations and Git

Introduction to Git

Git usage examples

Git with Python

Automating configuration backup

Collaborating with Git

Continuous Integration with Jenkins

Continuous Integration with Jenkins

The traditional change management process

An introduction to continuous integration

Installing Jenkins

Jenkins example

Jenkins with Python

Continuous integration for networking

Test-Driven Development for Networks

Test-Driven Development for Networks

Test-driven development overview

Topology as code

Writing tests for networking

pytest Integration with Jenkins

pyATS and Genie

Other Books You May Enjoy

Other Books You May Enjoy

Index

Customer Reviews

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Python for data visualization

We gather network data for the purpose of gaining insight into our network. One of the best ways to know what the data means is to visualize it with graphs. This is true for almost all data, but especially true for time series data in the context of network monitoring. How much data was transmitted over the network in the last week? What is the percentage of the TCP protocol among all of the traffic? These are values we can glean from using data-gathering mechanisms such as SNMP, and we can produce visualization graphs with some of the popular Python libraries.

In this section, we will use the data we collected from the last section using SNMP and use two popular Python libraries, Matplotlib and Pygal, to graph them.

Matplotlib

Matplotlib (http://matplotlib.org/) is a Python 2D plotting library for the Python language and its NumPy mathematical extension. It can produce publication-quality figures, such as plots, histograms, and bar graphs, with...