Siena Unit Testing - Python 2024

Lab: Unit Testing and Code Coverage with JES Media Functions

Objective

This lab aims to familiarize with the concepts and practices of unit testing and code coverage in Python, using the Siena MLS as a case study.

Theoretical Background

Unit Testing

Unit testing involves testing individual components or functions of a program to ensure they work as expected. Each test case is designed to test a specific part of the code in isolation.

Code Coverage

Code coverage measures the amount of code exercised by a test suite. It helps in identifying untested parts of a codebase. There are different types of coverage, including:

• Line Coverage: Measures if each line of code has been executed.
• Branch Coverage: Measures if both the True and False branches of conditional statements have been executed.

Tools

• unittest in Python: A unit testing framework. We will be running it via pytest
• coverage.py: A tool for measuring code coverage in Python. We will be using py-cov but again, should not matter at this stage :)

Setup

1. Ensure Python is installed on your system.
2. Clone the Siena_MLS repository https://github.com/Introduction-To-CS-Siena-College/Siena-MLS-py
3. Change directory to the newly created directory
4. We need to learn on how to read ReadMe files in opensource projects, Follow the instructions listed in that project to Install depdendies, build the project and finally test.

• Todo: you should be able to run the command to test this project.
• Do not remove these checkboxes! Add your answer below

Writing Unit Tests

Check the Example of a unit test for makePicture function:

import unittest
from siena_mls import makePicture

class TestMakePicture(unittest.TestCase):
    def test_valid_image(self):
        picture = makePicture("tests/assets/siena-small-logo.png")
        self.assertIsNotNone(picture)

if __name__ == '__main__':
    unittest.main()

Measuring Code Coverage

Many ways to measure coverage, or the proportion of system being executed by the test suite. One metric : Line Coverage Covered lines, or exercised lines -> The lines that have atleast been executed by some test case in your test suite.

• LineCoverage_percentage = 100 * $covered \over {(covered + uncovered)} $

Another Metric : Branch Coverage
We will see next semester, but can you research?

Text report

Check the auto generated report.

HTML based report

Check the htmlcov directory and open the index.html

Todo : Add the screenshot for makePicture

• Add the screenshot depicting the current coverage for
• What is the line coverage for the module?

Additional commands & comments

The basic commands to get code coverage are:

coverage run -m unittest discover
coverage report

These commands are usually automated in projects as you can see in the siena_mls project.

Tasks

Task 1: Analyse makePicture

Check the makePicture function inside the html report. Notice some part of this function is covered, while the other is not. Some are marked in green others in red.

Can you see what part of the function was not traveresed by the current testsuite and why this might be the case?

• Todo Add your answer here.

Any idea how you could go about writing a unit test for these uncovered ( marked in red ) lines? Atleast specify a simple test case defination, input & output.

• Todo Add your answer here.

Task 2: Write Unit Tests

Without using Generative models, Write unit tests for the following functions in JES Media Functions:

1. duplicatePicture
2. makeSound
3. (optional)getSampleValueAt and setSampleValueAt Modify the tests we have already seen to accomplish this. Feel free to create new test files if that's your fancy! but the idea is to get these functions tested.

Task 2: Measure Code Coverage

After writing the unit tests, use coverage.py to measure the code coverage of your tests.

Todo : Add the screenshot for makePicture

• Add the screenshot depicting the current coverage for
• What is the line coverage for the module?

Submission

Finish all the ToDos in this document Submit the following:

1. Your unit test code.
2. A screenshot or text file of the coverage report.

Additional Resources

• Python unittest documentation: https://docs.python.org/3/library/unittest.html
• Coverage.py documentation: https://coverage.readthedocs.io/
• UBC.ca - Lecture 4 Debugging...