Book Image

Expert Python Programming - Second Edition

By : Michał Jaworski
Book Image

Expert Python Programming - Second Edition

By: Michał Jaworski

Overview of this book

Python is a dynamic programming language, used in a wide range of domains by programmers who find it simple, yet powerful. Even if you find writing Python code easy, writing code that is efficient and easy to maintain and reuse is a challenge. The focus of the book is to familiarize you with common conventions, best practices, useful tools and standards used by python professionals on a daily basis when working with code. You will begin with knowing new features in Python 3.5 and quick tricks for improving productivity. Next, you will learn advanced and useful python syntax elements brought to this new version. Using advanced object-oriented concepts and mechanisms available in python, you will learn different approaches to implement metaprogramming. You will learn to choose good names, write packages, and create standalone executables easily. You will also be using some powerful tools such as buildout and vitualenv to release and deploy the code on remote servers for production use. Moving on, you will learn to effectively create Python extensions with C, C++, cython, and pyrex. The important factors while writing code such as code management tools, writing clear documentation, and test-driven development are also covered. You will now dive deeper to make your code efficient with general rules of optimization, strategies for finding bottlenecks, and selected tools for application optimization. By the end of the book, you will be an expert in writing efficient and maintainable code.

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Expert Python Programming - Second Edition
Michał Jaworski
May, 2016 | 536 pages
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Table of Contents (21 chapters)
Expert Python Programming Second Edition
Expert Python Programming Second Edition
Credits
Credits
About the Authors
About the Authors
About the Reviewer
About the Reviewer
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Current Status of Python
Current Status of Python
Where are we now and where we are going?
Why and how does Python change?
Getting up to date with changes – PEP documents
Python 3 adoption at the time of writing this book
The main differences between Python 3 and Python 2
Not only CPython
Modern approaches to Python development
Application-level isolation of Python environments
System-level environment isolation
Popular productivity tools
Useful resources
Summary
2
Syntax Best Practices – below the Class Level
Syntax Best Practices – below the Class Level
Python's built-in types
Advanced syntax
Other syntax elements you may not know yet
Summary
3
Syntax Best Practices – above the Class Level
Syntax Best Practices – above the Class Level
Subclassing built-in types
Accessing methods from superclasses
Advanced attribute access patterns
Metaprogramming
Summary
4
Choosing Good Names
Choosing Good Names
PEP 8 and naming best practices
Naming styles
The naming guide
Best practices for arguments
Class names
Module and package names
Useful tools
Summary
5
Writing a Package
Writing a Package
Creating a package
Namespace packages
Uploading a package
Standalone executables
Summary
6
Deploying Code
Deploying Code
The Twelve-Factor App
Deployment automation using Fabric
Your own package index or index mirror
Common conventions and practices
Code instrumentation and monitoring
Summary
7
Python Extensions in Other Languages
Python Extensions in Other Languages
Different language means – C or C++
Why you might want to use extensions
Writing extensions
Challenges
Interfacing with dynamic libraries without extensions
Summary
8
Managing Code
Managing Code
Version control systems
Continuous development processes
Summary
9
Documenting Your Project
Documenting Your Project
The seven rules of technical writing
A reStructuredText primer
Building the documentation
Making your own portfolio
Summary
10
Test-Driven Development
Test-Driven Development
I don't test
I do test
Summary
11
Optimization – General Principles and Profiling Techniques
Optimization – General Principles and Profiling Techniques
The three rules of optimization
Optimization strategy
Finding bottlenecks
Summary
12
Optimization – Some Powerful Techniques
Optimization – Some Powerful Techniques
Reducing the complexity
Simplifying
Using collections
Using architectural trade-offs
Caching
Summary
13
Concurrency
Concurrency
Why concurrency?
Multithreading
Multiprocessing
Asynchronous programming
Summary
14
Useful Design Patterns
Useful Design Patterns
Creational patterns
Structural patterns
Behavioral patterns
Summary
Index
Index

Useful tools

Part of the previous conventions and practices can be controlled and worked out with the following tools:

  • Pylint: This is a very flexible source code analyzer

  • pep8 and flake8: These are a small code style checker, and a wrapper that adds to it some more useful features, like static analysis and complexity measurement

Pylint

Besides some quality assurance metrics, Pylint allows you to check whether a given source code is following a naming convention. Its default settings correspond to PEP 8, and a Pylint script provides a shell report output.

To install Pylint, you can use pip:

$ pip install pylint

After this step, the command is available and can be run against a module, or several modules, using wildcards. Let's try it on Buildout's bootstrap.py script:

$ wget -O bootstrap.py https://bootstrap.pypa.io/bootstrap-buildout.py -q
$ pylint bootstrap.py
No config file found, using default configuration
************* Module bootstrap
C: 76, 0: Unnecessary parens after 'print' keyword...
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