Book Image

Modular Programming with Python

By : Erik Westra
Book Image

Modular Programming with Python

By: Erik Westra

Overview of this book

Python has evolved over the years and has become the primary choice of developers in various fields. The purpose of this book is to help readers develop readable, reliable, and maintainable programs in Python. Starting with an introduction to the concept of modules and packages, this book shows how you can use these building blocks to organize a complex program into logical parts and make sure those parts are working correctly together. Using clearly written, real-world examples, this book demonstrates how you can use modular techniques to build better programs. A number of common modular programming patterns are covered, including divide-and-conquer, abstraction, encapsulation, wrappers and extensibility. You will also learn how to test your modules and packages, how to prepare your code for sharing with other people, and how to publish your modules and packages on GitHub and the Python Package Index so that other people can use them. Finally, you will learn how to use modular design techniques to be a more effective programmer.
Table of Contents (16 chapters)
Modular Programming with Python
About the Author
About the Reviewer

Testing modules and packages

Testing is a normal part of programming: you test your code to verify that it works and identify any bugs or other problems, which you can then fix. Then, you test some more, until you are happy that your code is working correctly.

All too often, however, programmers just do ad hoc testing: they fire up the Python interactive interpreter, import their module or package, and make various calls to see what happens. In the previous chapter, we looked at a form of ad hoc testing using the importlib.reload() function to support RAD development of your code.

Ad hoc testing is useful, but it isn't the only form of testing. If you are sharing your modules and packages with others, you will want your code to be bug-free, and ad-hoc testing can't guarantee this. A much better and more systematic approach is to create a series of unit tests for your module or package. Unit tests are snippets of Python code which test various aspects of your code. Because the testing is done...