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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Mocking external resources

In earlier recipes in this chapter, Testing things that involve dates or times and Testing things that involve randomness, we wrote tests for involving resources with states that we could predict and mock. In one case, we created a mock datetime module that had a fixed response for the current time. In the other case, we created a mock random module that returned a fixed response from the choice() function.

In some cases, we need to mock objects that have more complex state changes. A database, for example, would require mock objects that respond to create, retrieve, update, and delete requests. Another example is the overall OS with a complex mixture of stateful devices, including the filesystem, and running processes.

In the Testing things that involve dates or times recipe, we looked briefly at how the pytest tool provides a tmpdir fixture. This fixture creates a temporary directory for each test, allowing us to run tests without conflicting with...