Secret Recipes of the Python Ninja: Over 70 recipes that uncover powerful programming tactics in Python [NulledPremium]

Book details
Format: pdf
File Size: 26 MB
Print Length: 384 pages
Page Numbers Source ISBN: 1788294874
Publisher: Packt Publishing; 1 edition (21 May 2018)
Sold by: Amazon Asia-Pacific Holdings Private Limited
Language: English
ASIN: B07BYBMGQT

Who This Book Is For
Whether you’ve been working with Python for a few years or you’re a seasoned programmer, you’ll have a lot of new tricks to walk away with.

Key Features
Access built-in documentation tools and improve your code.
Discover how to make the best use of decorator and generator functions
Enhance speed and improve concurrency by conjuring tricks from the PyPy project
Book Description
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.

What you will learn

Know the differences between .py and .pyc files
Explore the different ways to install and upgrade Python packages
Understand the working of the PyPI module that enhances built-in decorators
See how coroutines are different from generators and how they can simulate multithreading
Grasp how the decimal module improves floating point numbers and their operations
Standardize sub interpreters to improve concurrency
Discover Python’s built-in docstring analyzer
Table of Contents
Working with Python Modules
Utilizing the Python Interpreter
Working with Decorators
Using Python Collections
Generators, Coroutines, and Parallel Processing
Working with Python’s Math Module
Improving Python Performance with PyPy
Python Enhancement Proposals
Documenting with LyX

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