Book Image

Modern Python Cookbook - Second Edition

By : Steven F. Lott
Book Image

Modern Python Cookbook - Second Edition

By: Steven F. Lott

Overview of this book

Python is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great language that can power your applications and provide great speed, safety, and scalability. It can be used for simple scripting or sophisticated web applications. By exposing Python as a series of simple recipes, this book gives you insight into specific language features in a particular context. Having a tangible context helps make the language or a given standard library feature easier to understand. This book comes with 133 recipes on the latest version of Python 3.8. The recipes will benefit everyone, from beginners just starting out with Python to experts. You'll not only learn Python programming concepts but also how to build complex applications. The recipes will touch upon all necessary Python concepts related to data structures, object oriented programming, functional programming, and statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively take advantage of it. By the end of this Python book, you will be equipped with knowledge of testing, web services, configuration, and application integration tips and tricks. You will be armed with the knowledge of how to create applications with flexible logging, powerful configuration, command-line options, automated unit tests, and good documentation.
Table of Contents (18 chapters)
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Handling common doctest issues

Good Python includes docstrings inside every module, class, function, and method. One important element of a docstring is an example. While doctest can make the example into a unit test case, the literal matching of the expected text output against the actual text can cause problems. There are some Python objects that do not have a consistent text representation.

For example, object hash values are randomized. This often results in the order of elements in a set collection being unpredictable. We have several choices for creating test case example output:

  • Write tests that can tolerate randomization (often by converting to a sorted structure)
  • Stipulate a value for the PYTHONHASHSEED environment variable
  • Require that Python be run with the -R option to disable hash randomization entirely

There are several other considerations beyond simple variability in the location of keys or items in a set. Here are some other...