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)
16
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17
Index

Testing functions that raise exceptions

Good Python includes docstrings inside every module, class, function, and method. One important element of a docstring is an example. This can include examples of common exceptions. There's one complicating factor, however, to including exceptions.

When an exception is raised, the traceback messages created by Python are not completely predictable. The message may include object ID values that are impossible to predict or module line numbers that may vary slightly depending on the context in which the test is executed. The matching rules doctest uses to compare expected and actual results aren't appropriate when exceptions are involved.

Our testing frameworks provide ways to be sure the right exceptions are raised by a test case. This will involve using a special doctest provision for identifying the traceback messages exceptions produce.

Getting ready

We'll look at a small function definition as well as a class...