Module 30 - Testing with pytest

pytest is a powerful testing framework that makes it easy to write simple and scalable test cases.

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1. Installation

pip install pytest

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2. Basic Tests

test_example.py:

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

def test_add():
    assert add(2, 3) == 5
    assert add(-1, 1) == 0
    assert add(0, 0) == 0

def test_add_negative():
    assert add(-5, -3) == -8

Run tests:

pytest test_example.py

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3. Test Organization

# test_math.py
class TestMath:
    def test_addition(self):
        assert 1 + 1 == 2
    
    def test_subtraction(self):
        assert 5 - 3 == 2
    
    def test_multiplication(self):
        assert 2 * 3 == 6

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4. Fixtures

import pytest

@pytest.fixture
def sample_data():
    return [1, 2, 3, 4, 5]

def test_sum(sample_data):
    assert sum(sample_data) == 15

def test_len(sample_data):
    assert len(sample_data) == 5

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5. Parameterized Tests

import pytest

@pytest.mark.parametrize("input,expected", [
    (2, 4),
    (3, 9),
    (4, 16),
    (5, 25)
])
def test_square(input, expected):
    assert input ** 2 == expected

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6. Exception Testing

import pytest

def divide(a, b):
    if b == 0:
        raise ValueError("Cannot divide by zero")
    return a / b

def test_divide_by_zero():
    with pytest.raises(ValueError):
        divide(10, 0)

def test_divide_success():
    assert divide(10, 2) == 5

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7. Mocking

from unittest.mock import Mock, patch

def fetch_data():
    # Imagine this makes an API call
    return {"status": "success"}

def test_fetch_data():
    with patch('module.fetch_data') as mock_fetch:
        mock_fetch.return_value = {"status": "mocked"}
        result = fetch_data()
        assert result["status"] == "mocked"

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Summary

✅ pytest makes testing easy
✅ Fixtures provide reusable test data
✅ Parameterize for multiple test cases
✅ Mock external dependencies
✅ Test exceptions and edge cases

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Next Steps

In Module 31, you'll learn:

• Logging module
• Debugging with pdb
• Error tracking
• Best practices

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Practice Exercises

1. Write tests for a calculator module
2. Create fixtures for database testing
3. Test API endpoints with mock requests
4. Implement parameterized tests for validation functions
5. Write integration tests for a complete application :::