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Unit Testing in Python : A Primer

Automated unit testing has been around for more than a decade now. I remember back in 2008, a colleague introduced to our team the concept of MVP pattern and in the process the advantage of using the pattern in unit testing. The concept of automated testing using NUnit and mocking using NMock was also discussed. That is where I began to see the advantage of implementing Test Driven Development methodology to developers. Unfortunately, the company where I moved don't see it as such. Thus, I was only able to practice it on my learning time. With the recent events in my life , I now have more time exploring this concept a little further. A series of post will concentrate on this concept using Python and C#. Lets begin with Python.

Directory Structure

Lets begin with simple unit test using unittest. For the code samples, we will use the following directory structure :


I organized my codes in such a way that the actual application code is separated from the unit test codes.  For this to work unit test discovery will be used if you are to run it on the terminal. In my case, I run the tests inside PyCharm.

The Application

To make this as simple as possible,  I will use a simple Calculator application with the following methods to be tested :
  • add(num1, num2) - Add two numbers
  • subtract(num1,num2) - Subtraction
  • multiply(num1,num2) - Multiplication
  • divide(num1,num2) - Division

The Unit Test

import unittest
from Modules.Calculator.main import Calculator

class MyTestCase(unittest.TestCase):

    def setUp(self): = Calculator()

    def test_add(self):
        expected = 5
        result =,2)

    def test_subtract(self):
        expected = 5
        result =,5)

    def test_multiply(self):
        expected = 5
        result =,1)

    def test_divide(self):
        expected = 5
        result =,2)

if __name__ == '__main__':

If you are accustomed on creating unit test in .Net, the names of the test file as well as test methods are insignificant . Aside from the general rules in naming files and method names, theres nothing special to be considered. In Python, however, its more strict. Below are the two rules that are significant for the tests to be discovered:

  • The file name of the test file should start with "test: (i.e.
  • The method names should start with test ( i.e.  test_add)
Since we are using unittest, all test classes should inherit from unittest.TestCase. For the example, the assertEqual is used. Complete documentation on Python 3 regarding unittest can be found in this link

Running the Test

To run the script, we can use the terminal or command prompt to run discovered unit test using the following command :

TrashvinMBP:UnitTestingSample Trashvin$ python -m unittest discover -v 

Successful Test

TrashvinMBP:UnitTestingSample Trashvin$ python -m unittest discover -v      
test_add (UnitTests.test_calculator.MyTestCase) ... ok
test_divide (UnitTests.test_calculator.MyTestCase) ... ok
test_multiply (UnitTests.test_calculator.MyTestCase) ... ok
test_subtract (UnitTests.test_calculator.MyTestCase) ... ok

Ran 4 tests in 0.000s


Failed Test 

TrashvinMBP:UnitTestingSample Trashvin$ python -m unittest discover -v
test_add (UnitTests.test_calculator.MyTestCase) ... ok
test_divide (UnitTests.test_calculator.MyTestCase) ... FAIL
test_multiply (UnitTests.test_calculator.MyTestCase) ... ok
test_subtract (UnitTests.test_calculator.MyTestCase) ... ok

FAIL: test_divide (UnitTests.test_calculator.MyTestCase)
Traceback (most recent call last):
  File "/Users/Trashvin/Dev/Codes/Python/UnitTestingSample/UnitTests/", line 30, in test_divide
AssertionError: 6 != 5

Ran 4 tests in 0.001s

FAILED (failures=1)

Running test in the command line / terminal is far less aesthetically appealing that its Visual Studio equivalent but some Python editors such as PyCharm can provide such experience too.


Automated unit testing provide developers tool of easily testing their code without actually using the application. While writing unit test seems to add time at the start, on the long run, it helps the developer maintain checks on the codes that they write. For a continuously developing application, this provides a way to make sure that old codes are not broken. Unit testing, however, is not a complete solution.  On the next related post, I will discuss the concept of mocking.



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