Unit Testing & Debugging in Python

1. What is Unit Testing?

Unit Testing means testing individual units (functions or methods) of your code to ensure they work correctly.

A unit is the smallest testable part of an application.

2. Why Unit Testing is Important

Find bugs early
Prevent future bugs (regression)
Improve code quality
Make refactoring safe
Required in real-world production systems

3. Unit Testing Workflow

Write a function
Write test cases for it
Run tests
Fix failures
Repeat

4. Unit Testing with unittest (Built-in)

Example Function

def add(a, b):
    return a + b

Test File

import unittest
from math_utils import add

class TestMath(unittest.TestCase):

    def test_add(self):
        self.assertEqual(add(2, 3), 5)
        self.assertEqual(add(-1, 1), 0)

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

✔ Each assert checks expected vs actual output.

5. Testing with PyTest (Industry Standard)

Install

pip install pytest

Example Test

def multiply(a, b):
    return a * b

def test_multiply():
    assert multiply(3, 4) == 12

PyTest is preferred because it is:

Simpler syntax
Better error messages
Used in real companies

6. What is Debugging?

Debugging is the process of finding and fixing errors (bugs) in your code.

Bugs can be:

Syntax errors
Logical errors
Runtime errors

7. Debugging Tools in Python

print() Debugging

print("Value of x:", x)

pdb (Python Debugger)

import pdb

def divide(a, b):
    pdb.set_trace()
    return a / b

divide(10, 2)

Commands:

n → next line
c → continue
q → quit

8. Debugging Using IDEs

VS Code Debugger
PyCharm Debugger
Breakpoints
Variable Watch
Call Stack

9. Real-Life Use Cases

Testing APIs
Validating ML models
Preventing bugs before deployment
CI/CD pipelines
Enterprise applications

10. Best Practices

Write tests before production
Test edge cases
Keep tests independent
Automate tests
Debug logically, not randomly