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Mastering Object-oriented Python

Mastering Object-oriented Python

By : Steven F. Lott
4.2 (13)
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Mastering Object-oriented Python

Mastering Object-oriented Python

4.2 (13)
By: Steven F. Lott

Overview of this book

This practical example-oriented guide will teach you advanced concepts of object-oriented programming in Python. This book will present detailed examples of almost all of the special method names that support creating classes that integrate seamlessly with Python's built-in features. It will show you how to use JSON, YAML, Pickle, CSV, XML, Shelve, and SQL to create persistent objects and transmit objects between processes. The book also covers logging, warnings, unit testing, configuration files, and how to work with the command line. This book is broken into three major parts: Pythonic Classes via Special Methods; Persistence and Serialization; Testing, Debugging, Deploying, and Maintaining. The special methods are broken down into several focus areas: initialization, basics, attribute access, callables, contexts, containers, collections, numbers, and more advanced techniques such as decorators and mixin classes.
Table of Contents (26 chapters)
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Mastering Object-oriented Python
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Some Preliminaries
1
Index

Using ChainMap for defaults and overrides


We'll often have a configuration file hierarchy. Previously, we listed several locations where configuration files can be installed. The configparser module, for example, is designed to read a number of files in an order and integrate the settings by having later files override values from earlier files.

We can implement an elegant default-value processing using the collections.ChainMap class. See Chapter 6, Creating Containers and Collections, for some background on this class. We'll need to keep the configuration parameters as dict instances, which is something that works out well using exec() to evaluate Python-language initialization files.

Using this will require us to design our configuration parameters as a flat dictionary of values. This may be a bit of a burden for applications with a large number of complex configuration values that are integrated from several sources. We'll show you a sensible way to flatten names.

First, we'll build a list...

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Mastering Object-oriented Python
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