Noah Gift - Testing In Python: Robust Testing For Professionals

This book is for sale at http://leanpub.com/testinginpython

This version was published on 2020-02-27

* * * * *

This is a Leanpub book. Leanpub empowers authors and publishers with the Lean Publishing process. Lean Publishing is the act of publishing an in-progress ebook using lightweight tools and many iterations to get reader feedback, pivot until you have the right book and build traction once you do.

* * * * *

If you are picking up this book, it is because you want to level up the quality of the code you are producing. Regardless of the background and what type of work you are trying to achieve, testing is a prime indicator of solid software practices. From students to data scientists and programmers, testing is a core value that should be practiced, enhanced, and maintained throughout. When testing is part of a project, it means that the code is brief enough that it can easily accept inputs to ensure the outputs meet expectations. On the other hand, when it is hard, it indicates that code is fragile, and a refactoring should take place.

Testing is here to help you write better software, enhance your confidence, and make it easier to maintain.

This book is using a method called Lean Publishing, which allows us to write the book and release it before it finishes. Are you seeing that some chapters are missing? We are committed in finishing it, and keep updating it until it is done. One complete, we are going to ensure that the versions are up to date, and everything is still working.

When there are no tests, there is no way to ensure that changes arent breaking other assumptions. Applications that start small dont necessarily mean that they will stay that way; when they grow without tests, it creates a big problem: no one will want to make changes to avoid breakage. Even in the smallest applications, having some validation that things are working as expected is a good idea.

The Broken Windows Theory explains that when there are visible signs of violence or civil disorder, it encourages more crime, creating a vicious cycle. This theory also has a parallel in software. A very long function will get longer and harder to maintain. Tests are the medicine - it forces complicated code to be more granular and more comfortable to read and keep because that, in turn, makes it easier to test!

Writing tests may feel like a tedious chore, that might not give immediate satisfaction, but like most good foundations, the result is robustness and confidence. A week after touching a software project, you might not quite remember what that function was supposed to do when receiving an empty list. Changes to software are a given, and without something to confirm that everything is still working as intended, breakage will occur.

Someone once mentioned Id rather add some tests than receive a call from an angry customer . Lets not wait until customers (or users!) find out about failures that dont need to exist.

There is always a struggle between advancing a software project and (seemingly) slowing down to write tests. If you are coming from writing short snippets on an interactive shell, like Jupyter Notebooks or small scripts, this struggle will feel stronger. Throughout the process, though, you will be doing some testing regardless. For example, if you are writing a command-line tool, and you are implementing a new option, then you will probably end up in the terminal trying out that unique option to see if it does what you are expecting. The problem is that the workflow doesnt scale beyond one or two flags, and it is error-prone. The best solution is to have a good set of tests that can run almost instantly and reassure you that everything is working great.

This book works to fully support a range of Python, Pytest, and Tox versions. And we are committed to ensuring the examples work correctly with an automated test suite.

The supported versions in this book are:

• Python: Versions 3.6 and newer (including 3.8 as of this writing!)
• Pytest: Major version 5 (most examples use 5.3.2)
• Tox: Major Version 3 (most patterns use 3.14)

What you see on the cover of this book is Moray, an essential Incan site. Archeologists think this works as a testing laboratory for crops. The differences in the rings are significant enough in temperature, as well as sunlight and altitude, that the Incas could better understand ideal conditions for different crops. The analogy here is perfect; the importance of testing and ensuring things are in its optimum state, is excellent.