Book Image

Secret Recipes of the Python Ninja

Book Image

Secret Recipes of the Python Ninja

Overview of this book

This book covers the unexplored secrets of Python, delve into its depths, and uncover its mysteries. You’ll unearth secrets related to the implementation of the standard library, by looking at how modules actually work. You’ll understand the implementation of collections, decimals, and fraction modules. If you haven’t used decorators, coroutines, and generator functions much before, as you make your way through the recipes, you’ll learn what you’ve been missing out on. We’ll cover internal special methods in detail, so you understand what they are and how they can be used to improve the engineering decisions you make. Next, you’ll explore the CPython interpreter, which is a treasure trove of secret hacks that not many programmers are aware of. We’ll take you through the depths of the PyPy project, where you’ll come across several exciting ways that you can improve speed and concurrency. Finally, we’ll take time to explore the PEPs of the latest versions to discover some interesting hacks.
Table of Contents (17 chapters)
Title Page
Copyright and Credits
Packt Upsell
Foreword
Contributors
Preface
Index

What is RPython?


RPython is the language used to create PyPy. Technically, it is considered a translation and support framework for implementing dynamic programming languages, separating the language specs from the implementation aspects. This means that RPython can be used for other languages besides Python, though it is most commonly associated with Python. This also means that any dynamic language will benefit from the JIT compiler and allows for a mix-and-match style when making implementation choices.

While certain environments have been created in the past to provide abstraction between source code and the target system, such as .NET and Java Virtual Machines, RPython uses a subset of CPython to create languages that act as simple interpreters, with little direct connectivity to low-level, system details. The subsequent toolchain creates a solid virtual machine for a designated platform by using the appropriate lower-level aspects as needed. This allows further customization of features...