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Expert Python Programming

Tarek Ziadé

This is the perfect book for refining your Python skills through learning best practices and the latest development techniques. Packed with real-world examples and written by an expert, this is the authoritative tutorial.
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Book Details

ISBN 139781847194947
Paperback372 pages

About This Book

  • Learn Python development best practices from an expert, with detailed coverage of naming and coding conventions
  • Apply object-oriented principles, design patterns, and advanced syntax tricks
  • Manage your code with distributed version control
  • Profile and optimize your code
  • Proactive test-driven development and continuous integration
  • Read Chapter 10 Documenting Your Project [PDF 3 MB]

Who This Book Is For

This book is for Python developers who are already building applications, but want to build better ones by applying best practices and new development techniques to their projects.

The reader is expected to have a sound background in Python programming.

Table of Contents

Chapter 1: Getting started
Installing Python
The Python Prompt
Installing setuptools
Working Environment
Chapter 2: Syntax Best Practices—Below the Class Level
List Comprehensions
Iterators and Generators
with and contextlib
Chapter 3: Syntax Best Practices—Above the Class Level
Subclassing Built-in Types
Accessing Methods from Superclasses
Best Practices
Descriptors and Properties
Chapter 4: Choosing Good Names
PEP 8 and Naming Best Practices
Naming Styles
Naming Guide
Best Practices for Arguments
Class Names
Module and Package Names
Working on APIs
Useful Tools
Chapter 5: Writing a Package
A Common Pattern for All Packages
The Template-Based Approach
Creating the Package Template
Development Cycle
Chapter 6: Writing an Application
Atomisator: An Introduction
Overall Picture
Working Environment
Writing the Packages
Distributing Atomisator
Dependencies between Packages
Chapter 7: Working with zc.buildout
zc.buildout Philosophy
Releasing and Distributing
Chapter 8: Managing Code
Version Control Systems
Continuous Integration
Chapter 9: Managing Life Cycle
Different Approaches
Defining a Life Cycle
Setting Up a Tracking System
Chapter 10: Documenting Your Project
The Seven Rules of Technical Writing
A reStructuredText Primer
Building the Documentation
Make Your Own Portfolio
Chapter 11: Test-Driven Development
I Don't Test
I Do Test
Chapter 12: Optimization: General Principles and Profiling Techniques
The Three Rules of Optimization
Optimization Strategy
Finding Bottlenecks
Chapter 13: Optimization: Solutions
Reducing the Complexity
Chapter 14: Useful Design Patterns
Creational Patterns
Structural Patterns
Behavioral Patterns

What You Will Learn

  • Set up a productive development environment
  • Customize the Python prompt and deploy setuptools
  • Write efficient syntax: iterators, generators, and decorators
  • Build arguments by design and follow the best practices for working on API
  • Build, release, and distribute your applications
  • Write an application based on several eggs
  • Distribute and deploy your application with zc.buildout
  • Build and release your packages and set up a development cycle
  • Manage your code with distributed version control and continuous integration
  • Use an iterative and incremental approach to write software
  • Practice Test-Driven Development
  • Profile and optimize your code to speed up your programs
  • Apply design patterns to your applications

Chapter 1, Getting Started, explains how to install Python and makes sure all readers have the closest, standardized environment.
Chapter 2, Syntax Best Practices—Below the Class Level, presents iterators, generators, descriptors and so on, in an advanced way.

Chapter 3, Syntax Best Practices—Above the Class Level, is also about syntax best practices, but focuses on above the class level.

Chapter 4, Choosing Good Names, is an extension to PEP 8 with naming best practices, but also gives tips on designing good APIs.
Chapter 5, Writing a Package, explains how to write a package and how to use code templates, then focuses on how to release and distribute your code.

Chapter 6, Writing an Application, extends Chapter 5 by describing how a full application can be written. It demonstrates it through a small case study called Atomisator.

Chapter 7, Using zc.buildout, is about zc.buildout, a system for managing a development environment and releasing applications, which is widely used in the Zope and Plone community and is starting to be used outside the Zope world.

Chapter 8, Managing Code, shows how your project code base can be managed with distributed instead of centralized version control and explains how to set up continuous integration.

Chapter 9, Managing Life Cycle, presents how to manage software life cycle through an iterative and incremental approach.

Chapter 10, Documenting Your Project, is about documentation and gives tips on technical writing and how Python projects should be documented.

Chapter 11, Test-Driven Development, explains Test-Driven Development and the tools that can be used to do it.

Chapter 12, Optimization—General Principle and Profiling Techniques, gives profiling techniques and an optimization strategy guideline.
Chapter 13, Optimization—Solutions, extends Chapter 12 by providing some solutions to speed up your programs.

Chapter 14, Useful Design Patterns, ends the book with a set of design patterns and when to use them.

In Detail

Python is a dynamic programming language, used in a wide range of domains by programmers who find it simple, yet powerful. From the earliest version 15 years ago to the current one, it has constantly evolved with productivity and code readability in mind.

Even if you find writing Python code easy, writing code that is efficient and easy to maintain and reuse is not so straightforward. This book will show you how to do just that:  it will show you how Python development should be done. Python expert Tarek Ziadé takes you on a practical tour of Python application development, beginning with setting up the best development environment, and along the way looking at agile methodologies in Python, and applying proven object-oriented principles to your design.


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