A Simple Guide to Automating Unit Tests in Python

A Simple Guide to Automating Unit Tests in Python

A Simple Guide to Automating Unit Tests in Python. The solution to this is writing isolated, automated tests with the help of tools like pytest, unittest and nose2.

In 1999 a navigation error saw NASA’s Mars Climate Orbiter crashing into the red planet’s atmosphere, and with it burnt years of painstaking work and millions of dollars spent building it. What was the cause? The commands sent to the spacecraft used English units instead of metric units. Mathematical and technical errors like these could result in catastrophic failures, some even ending in serious casualties. Hence the case for testing being an indispensable part of software development.

Unit Testing” is when you test one unit of your software independent of any other units. Typically in Object Oriented Development (OOD) this unit is a class. But, what is testing? Testing simply means checking the output of your code against a set of pre-defined, correct expected output/results. You need to have test data — both input and expected output/results — before you start testing. I said “output/results” because sometimes your code doesn’t output data, rather it modifies some data in your software.

Now, manually testing your code i.e. running it yourself, entering input via a user interface and visually examining the results is gruellingly boring and no doubt cumbersome. Plus, this way of testing isn’t easily scalable or repeatable. Instead you could write a tester class that simply calls all your functions and compares the results with a set of pre-defined ones. However, the problem with this method is that the functions you are testing could call other functions which may run some code elsewhere and so on. This could really mess up the working of your software or even corrupt any valuable data you might have on your database. Remember Unit Testing is all about testing one thing at a time. The solution to this is writing isolated, automated tests with the help of tools like pytest, unittest and nose2.

Since the goal of this tutorial is not to delve deep into the intricacies of software testing, let’s head straight into writing some automated tests. We will be using the unittest _Python library to write tests and _nose2 to run them.

Prerequisites:_ Make sure you have Python 3 installed on your PC. You will also need to install the following libraries: unittest, mock, tinydb and nose2. You can install these using pip._

programming testing software-development software-engineering python

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