🐍 Python Tutorial: Testing and Debugging

Writing error-free and reliable Python code requires strong testing and debugging practices. In this tutorial, we cover core debugging techniques, how to write effective unit tests using Python's built-in unittest module, and explore tools to help you develop clean, bug-free programs.

1. Debugging Python Code

Debugging involves identifying and fixing issues in your code. Common debugging techniques include:

• Print Statements: Add print() to trace values and logic.
• Using pdb: Python's built-in debugger allows you to set breakpoints and inspect variables interactively.

import pdb

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

print(divide(10, 2))

2. Unit Testing with unittest

Python's unittest framework helps you write tests for individual units of your code (functions, classes). A simple test looks like this:

import unittest

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

class TestMath(unittest.TestCase):
    def test_add(self):
        self.assertEqual(add(2, 3), 5)

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

🔧 Run the test with: python test_file.py

3. Popular Testing Tools

While unittest is built-in, Python has a rich ecosystem of third-party testing tools:

• pytest – simple, powerful, and widely used
• doctest – test your docstrings as documentation + tests
• coverage – measure how much of your code is tested

Example with pytest:

# test_math.py

def add(x, y):
    return x + y

def test_add():
    assert add(2, 3) == 5

Run with pytest test_math.py

Additional Resources & References