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
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15
Index

C and C++ as the core of Python extensibility

The reference implementation of Python—the CPython interpreter—is written in C. Because of that, Python interoperability with other languages revolves around C and C++, which has native interoperability with C. There is even a full superset of the Python language called Cython, which uses a source-to-source compiler for creating C extensions for CPython using extended Python syntax.

In fact, you can use dynamic/shared libraries written in any language if the language supports compilation in the form of dynamic/shared libraries. So, interlanguage integration possibilities go way beyond C and C++. This is because shared libraries are intrinsically generic. They can be used in any language that supports their loading. So, even if you write such a library in a completely different language (let's say Delphi or Prolog), you can use it in Python. Still, it is hard to call such a library a Python extension if it does...