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Rick van Hattem - Mastering Python [2016, PDF, ENG]

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Post 23-Jul-2016 01:01

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Mastering Python
Год издания: 2016
Автор: Rick van Hattem
Жанр или тематика: Программирование
Издательство: Packt Publishing
ISBN: 9781785289729
Язык: Английский
Формат: PDF
Качество: Издательский макет или текст (eBook)
Интерактивное оглавление: Да
Количество страниц: 486
Описание: Python is a dynamic programming language. It is known for its high readability and hence it is often the first language learned by new programmers. Python being multi-paradigm, it can be used to achieve the same thing in different ways and it is compatible across different platforms. Even if you find writing Python code easy, writing code that is efficient, easy to maintain, and reuse is not so straightforward.
This book is an authoritative guide that will help you learn new advanced methods in a clear and contextualised way. It starts off by creating a project-specific environment using venv, introducing you to different Pythonic syntax and common pitfalls before moving on to cover the functional features in Python. It covers how to create different decorators, generators, and metaclasses. It also introduces you to functools.wraps and coroutines and how they work. Later on you will learn to use asyncio module for asynchronous clients and servers. You will also get familiar with different testing systems such as py.test, doctest, and unittest, and debugging tools such as Python debugger and faulthandler. You will learn to optimize application performance so that it works efficiently across multiple machines and Python versions. Finally, it will teach you how to access C functions with a simple Python call. By the end of the book, you will be able to write more advanced scripts and take on bigger challenges.
What You Will Learn
- Create a virtualenv and start a new project
- Understand how and when to use the functional programming paradigm
- Get familiar with the different ways the decorators can be written in
- Understand the power of generators and coroutines without digressing into lambda calculus
- Create metaclasses and how it makes working with Python far easier
- Generate HTML documentation out of documents and code using Sphinx
- Learn how to track and optimize application performance, both memory and cpu
- Use the multiprocessing library, not just locally but also across multiple machines
- Get a basic understanding of packaging and creating your own libraries/applications

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Table of Contents
1: Getting Started – One Environment per Project
2: Pythonic Syntax, Common Pitfalls, and Style Guide
3: Containers and Collections – Storing Data the Right Way
4: Functional Programming – Readability Versus Brevity
5: Decorators – Enabling Code Reuse by Decorating
6: Generators and Coroutines – Infinity, One Step at a Time
7: Async IO – Multithreading without Threads
8: Metaclasses – Making Classes (Not Instances) Smarter
9: Documentation – How to Use Sphinx and reStructuredText
10: Testing and Logging – Preparing for Bugs
11: Debugging – Solving the Bugs
12: Performance – Tracking and Reducing Your Memory and CPU Usage
13: Multiprocessing – When a Single CPU Core Is Not Enough
14: Extensions in C/C++, System Calls, and C/C++ Libraries
15: Packaging – Creating Your Own Libraries or Applications
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