To put it simply, unit test (unit test) checks if it works correctly small piece of code, most often a separate function or method. The word unit translated as "unit", and in testing this unit is the minimum part of the program that can be tested in isolation.
For example, if you have the calculateSum(a, b) function, the unit test will check that it returns the correct result with different input data.
Why are unit tests important?
Early detection of errors.
An error caught during the testing phase is cheaper than an error in production.
Confidence in changes.
Add a new feature or refactor the code — tests will show if something is broken.
Documentation through examples.
Good tests explain how the code works.
Automation.
Tests can be run automatically with each commit via CI/CD.
What does a unit test look like in practice?
Example in Python:
def multiply(a, b):
return a * b
Now let's create a test using the unittest library:
import unittest
class TestMultiply(unittest.TestCase):
def test_positive_numbers(self):
self.assertEqual(multiply(2, 3), 6)
def test_with_zero(self):
self.assertEqual(multiply(0, 10), 0)
if __name__ == '__main__':
unittest.main()
When you run the tests, Python will check that multiply(2, 3) actually returns 6, and multiply(0, 10) — 0. If everything is correct, the test will be successful, otherwise you will immediately know where the error is.
Good practices for writing unit tests
Test one thing at a time — each test checks a specific behavior.
Isolate tests — they should not depend on each other.
Write readable — understandable names like
test_returns_zero_when_input_is_empty().Do not test the obvious — if the function simply calls the library without logic, the test is not needed.
Unit tests in real projects
In many teams, tests are a mandatory part of the development process. For example:
In GitHub Actions or GitLab CI tests are run automatically before deployment.
In open-source projects without tests, the code is often not accepted into the repository.
In products like Codik tests help to make sure that new lessons and APIs do not break the old functionality.
Unit tests are not just "extra work", but investment in stability. With their help, the developer can confidently improve the code without fear of accidentally ruining something. Without tests, the code quickly turns into a "minefield", where any change can break everything.
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