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

Working with random numbers


The math-oriented random module utilizes a pseudo-random number generator (PRNG) for use in various applications. It is designed for modeling and simulation purposes and should not be used for any security or cryptography programs.

PRNGs use a seed value as an argument to the generator. This allows for re-creation of randomized scenarios or determining what random value will be generated next in a sequence; hence, they are not cryptographically secure. A common application of a PRNG is in security key fobs; the PRNG in the fob is provided with the same seed value as on the server. Thus, the server and the fob will have the same number available at the exact same time, allowing a user to input the number as a second form of authentication.

How to do it...

Note that examples are provided where output is generated for a command. Also note that, as these are randomized values, your results may be different:

  • The seed(a=None, version=2) function initializes the PRNG. If...