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)
Other Books You May Enjoy


In this chapter, we explored ways to perform network monitoring via SNMP. We configured SNMP-related commands on network devices and used our network management VM with an SNMP poller to query the devices. We used the PySNMP module to simplify and automate our SNMP queries. We also learned how to save the query results in a flat file or database to be used for future examples.

Later in this chapter, we used two different Python visualization packages, Matplotlib and Pygal, to graph SNMP results. Each package has its distinct advantages. Matplotlib is a mature, feature-rich library that is widely used in data science projects. Pygal can natively generate SVG format graphs that are flexible and web-friendly. We saw how we can generate line and pie graphs that are relevant for network monitoring.

Toward the end of this chapter, we looked at an all-inclusive network monitoring tool named Cacti. It primarily uses SNMP for network monitoring, but we saw how we...