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Expert Python Programming. - Second Edition
Expert Python Programming. - Second Edition

Expert Python Programming.: Write professional, efficient and maintainable code in Python, Second Edition

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Book May 2016 536 pages 2nd Edition
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Product Details

Publication date : May 20, 2016
Length 536 pages
Edition : 2nd Edition
Language : English
ISBN-13 : 9781785886850
Category :
Table of content icon View table of contents Preview book icon Preview Book

Expert Python Programming. - Second Edition

Chapter 1. Current Status of Python

Python is good for developers.

No matter what operating system you or your customers are running, it will work. Unless you are coding platform-specific things, or using a platform-specific library, you can work on Linux and deploy on other systems, for example. However, that's not uncommon anymore (Ruby, Java, and many other languages work in the same way). Combined with the other qualities that we will discover throughout this book, Python becomes a smart choice for a company's primary development language.

This book is focused on the latest version of Python, 3.5, and all code examples are written in this version of the language unless another version is explicitly mentioned. Because this release is not yet widely used, this chapter contains some description of the current status quo of Python 3 to introduce readers to it, as well as some introductory information on modern approaches to development in Python. This chapter covers the following topics:

  • How to maintain compatibility between Python 2 and Python 3

  • How to approach the problem of environment isolation both on application and operating system level for the purpose of development

  • How to enhance the Python prompt

  • How to install packages using pip

A book always starts with some appetizers. So, if you are already familiar with Python (especially with the latest 3.x branch) and know how to properly isolate environments for development purposes, you can skip the first two sections of this chapter and just read the other sections quickly. They describe some tools and resources that are not essential but can highly improve productivity in Python. Be sure to read the section on application-level environment isolation and pip, though, as their installation is mandatory for the rest of the book.

Where are we now and where we are going?

Python history starts somewhere in the late 1980s, but its 1.0 release date was in the year 1994, so it is not a very young language. There could be a whole timeline of major Python releases mentioned here, but what really matters is a single date: December 3, 2008 – the release date of Python 3.0.

At the time of writing, seven years have passed since the first Python 3 release. It is also four years since the creation of PEP 404—the official document that "un-released" Python 2.8 and officially closed the 2.x branch. Although a lot of time has passed, there is a specific dichotomy in the Python community—while the language develops very fast, there is a large group of its users that do not want to move forward with it.

Why and how does Python change?

The answer is simple—Python changes because there is such a need. The competition does not sleep. Every few months a new language pops out out of nowhere claiming to solve problems of all its predecessors. Most projects like these lose developers' attention very quickly and their popularity is driven by a sudden hype.

Anyway, this is a sign of some bigger issue. People design new languages because they find the existing ones unsuitable for solving their problems in the best ways possible. It would be silly not to recognize such a need. Also, more and more wide spread usage of Python shows that it could, and should, be improved in many places.

Lots of improvements in Python are often driven by the needs of particular fields where it is used. The most significant one is web development, which necessitated improvements to deal with concurrency in Python.

Some changes are just caused by the age and maturity of the Python project. Throughout the years, it has collected some of the clutter in the form of de-organized and redundant standard library modules or some bad design decisions. First, the Python 3 release aimed to bring major clean-up and refreshment to the language, but time showed that this plan backfired a bit. For a long time, it was treated by many developers only like curiosity, but, hopefully, this is changing.

Getting up to date with changes – PEP documents

The Python community has a well-established way of dealing with changes. While speculative Python language ideas are mostly discussed on specific mailing lists (), nothing major ever gets changed without the existence of a new document called a PEP. A PEP is a Python Enhancement Proposal. It is a paper written that proposes a change on Python, and is a starting point for the community to discuss it. The whole purpose, format, and workflow around these documents is also standardized in the form of a Python Enhancement Proposal—precisely, PEP 1 document (

PEP documents are very important for Python and depending on the topic, they serve different purposes:

  • Informing: They summarize the information needed by core Python developers and notify about Python release schedules

  • Standardizing: They provide code style, documentation, or other guidelines

  • Designing: They describe the proposed features

A list of all the proposed PEPs is available as in a document—PEP 0 ( Since they are easily accessible in one place and the actual URL is also very easy to guess, they are usually referred to by the number in the book.

Those who are wondering what the direction is in which the Python language is heading but do not have time to track a discussion on Python mailing lists, the PEP 0 document can be a great source of information. It shows which documents have already been accepted but are not yet implemented and also which are still under consideration.

PEPs also serve additional purposes. Very often, people ask questions like:

  • Why does feature A work that way?

  • Why does Python not have feature B?

In most such cases, the extensive answer is available in specific PEP documents where such a feature has already been mentioned. There are a lot of PEP documents describing Python language features that were proposed but not accepted. These documents are left as a historical reference.

Python 3 adoption at the time of writing this book

So, is Python 3, thanks to new exciting features, well adopted among its community? Sadly, not yet. The popular page Python 3 Wall of Superpowers ( that tracks the compatibility of most popular packages with the Python 3 branch was, until not so long ago, named Python 3 Wall of Shame. This situation is changing and the table of listed packages on the mentioned page is slowly turning "more green" with every month. Still, this does not mean that all teams building their applications will shortly use only Python 3. When all popular packages are available on Python 3, the popular excuse—the packages that we use are not ported yet—will no longer be valid.

The main reason for such a situation is that porting the existing application from Python 2 to Python 3 is always a challenge. There are tools like 2to3 that can perform automated code translation but they do not ensure that the result will be 100% correct. Also, such translated code may not perform as well as in its original form without manual adjustments. The moving of existing complex code bases to Python 3 might involve tremendous effort and cost that some organizations may not be able to afford. Still such costs can be split in time. Some good software architecture design methodologies, such as service-oriented architecture or microservices, can help to achieve this goal gradually. New project components (services or microservices) can be written using the new technology and existing ones can be ported one at a time.

In the long run, moving to Python 3 can only have beneficial effects on a project. According to PEP-404, there won't be a 2.8 release in the 2.x branch of Python anymore. Also, there may be a time in the future when all major projects such as Django, Flask, and numpy will drop any 2.x compatibility and will only be available on Python 3.

My personal opinion on this topic can be considered controversial. I think that the best incentive for the community would be to completely drop Python 2 support when creating new packages. This, of course, greatly limits the reach of such software but it may be the only way to change the way of thinking of those who insist on sticking to Python 2.x.

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Key benefits

  • Based on the latest stable version of Python (version 3.5)
  • Creating well manageable code that will run in various environments with different sets of dependencies
  • Packed with advanced concepts and best practices to write efficient Python code


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.

What you will learn

Conventions and best practices that are widely adopted in the python community Package python code effectively for community and production use Easy and lightweight ways to automate code deployment on remote systems Improve your code's quality, reliability, and performance Write concurrent code in python Extend python with code written in different languages

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Buy Now

Product Details

Publication date : May 20, 2016
Length 536 pages
Edition : 2nd Edition
Language : English
ISBN-13 : 9781785886850
Category :

Table of Contents

21 Chapters
Expert Python Programming Second Edition Chevron down icon Chevron up icon
Credits Chevron down icon Chevron up icon
About the Authors Chevron down icon Chevron up icon
About the Reviewer Chevron down icon Chevron up icon Chevron down icon Chevron up icon
Preface Chevron down icon Chevron up icon
1. Current Status of Python Chevron down icon Chevron up icon
2. Syntax Best Practices – below the Class Level Chevron down icon Chevron up icon
3. Syntax Best Practices – above the Class Level Chevron down icon Chevron up icon
4. Choosing Good Names Chevron down icon Chevron up icon
5. Writing a Package Chevron down icon Chevron up icon
6. Deploying Code Chevron down icon Chevron up icon
7. Python Extensions in Other Languages Chevron down icon Chevron up icon
8. Managing Code Chevron down icon Chevron up icon
9. Documenting Your Project Chevron down icon Chevron up icon
10. Test-Driven Development Chevron down icon Chevron up icon
11. Optimization – General Principles and Profiling Techniques Chevron down icon Chevron up icon
12. Optimization – Some Powerful Techniques Chevron down icon Chevron up icon
13. Concurrency Chevron down icon Chevron up icon
14. Useful Design Patterns Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

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