Book Image

Expert Python Programming - Fourth Edition

By : Michał Jaworski, Tarek Ziadé
Book Image

Expert Python Programming - Fourth Edition

By: Michał Jaworski, Tarek Ziadé

Overview of this book

This new edition of Expert Python Programming provides you with a thorough understanding of the process of building and maintaining Python apps. Complete with best practices, useful tools, and standards implemented by professional Python developers, this fourth edition has been extensively updated. Throughout this book, you’ll get acquainted with the latest Python improvements, syntax elements, and interesting tools to boost your development efficiency. The initial few chapters will allow experienced programmers coming from different languages to transition to the Python ecosystem. You will explore common software design patterns and various programming methodologies, such as event-driven programming, concurrency, and metaprogramming. You will also go through complex code examples and try to solve meaningful problems by bridging Python with C and C++, writing extensions that benefit from the strengths of multiple languages. Finally, you will understand the complete lifetime of any application after it goes live, including packaging and testing automation. By the end of this book, you will have gained actionable Python programming insights that will help you effectively solve challenging problems.
Table of Contents (16 chapters)
14
Other Books You May Enjoy
15
Index

Distributed application tracing

Distributed and networked systems are inevitable in any large-scale infrastructure. That's because you can put only a limited amount of hardware in a single server rack. If you have to serve a large number of users concurrently, you will have to scale out eventually. Also, having all of your software running on a single host will be risky from a reliability and availability standpoint. If one machine fails, the whole system goes down. And it isn't that uncommon to see even whole datacenters being brought down due to natural disasters or other unpredictable events. This means that highly available systems are often forced to be spread over multiple datacenters located in different regions or even managed by different providers, just to ensure enough redundancy.

Another reason for distributed systems is splitting infrastructures into independent domain services in order to split large codebases and enable multiple teams to work efficiently...