Book Image

Expert Python Programming – Fourth Edition - Fourth Edition

By : Michał Jaworski, Tarek Ziade, Ziadé
5 (1)
Book Image

Expert Python Programming – Fourth Edition - Fourth Edition

5 (1)
By: Michał Jaworski, Tarek Ziade, 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

Summary

This chapter was a journey through time. Python is considered a modern language but in order to better understand its patterns, we had to make some historical trips.

We started with interfaces—a concept almost as old as object-oriented programming (the first OOP language—Simula—dates to 1967!). We took a look at zope.interface, something that is probably one of the oldest actively maintained interface libraries in the Python ecosystem. We learned some of its advantages and disadvantages. That allowed us to really embrace two mainstream Python alternatives: abstract base classes and structural subtyping through advanced type annotations.

After familiarizing ourselves with interfaces, we looked into inversion of control. Internet sources about this topic can be really confusing and this concept is often confused with dependency injection. To settle any disputes, we traced the origin of the term to the 80s, when no one had yet ever dreamed about dependency injection containers. We learned how to recognize inversion of control in various forms and saw how it can improve the modularity of applications. We tried to invert control in a simple application manually. We saw that sometimes it can cost us readability and expressiveness. Thanks to this, we are now able to fully recognize the value that comes from the simplicity of ready-made dependency injection libraries.

The next chapter should be refreshing. We will completely move away from the topics of object-oriented programming, language features, design patterns, and paradigms. It will be all about concurrency. We will learn how to write code that does a lot, in parallel, and—hopefully—does it fast.