Book Image

Mastering Python Networking - Fourth Edition

By : Eric Chou
Book Image

Mastering Python Networking - Fourth 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, Fourth edition, you'll embark on a Python-based journey to transition from a traditional network engineer to a network developer ready for the next generation of networks. This new edition is completely revised and updated to work with the latest Python features and DevOps frameworks. In addition to new chapters on introducing Docker containers and Python 3 Async IO for network engineers, 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 AWS and Azure cloud networking. You will use Git for code management, GitLab for continuous integration, and Python-based testing tools to verify your network.
Table of Contents (19 chapters)
17
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18
Index

Python Asyncio Module

We can think of the asyncio module as Python’s way of allowing us to write code to run tasks concurrently. It uses the newly introduced async and await keywords. It can help us improve performance for many operations that might be IO bound, such as web servers, databases, and of course, communication toward devices over the network. The asyncio module is the foundation of popular new frameworks, such as FastAPI (https://fastapi.tiangolo.com/).

However, it is important to point out that asyncio is neither multi-processing nor multi-threaded. It is designed to be single-threaded with a single process. Python asyncio uses cooperative multiprocessing to give the feeling of concurrency.

Unlike threading, Python controls the process from end to end instead of passing the threading process to the operating system. This lets Python know when the task is started and completed, thus coordinating between them. When we can ‘pause’ part of the code while...