Pytest Testing

Pytest Testing

Overview

Master software testing with pytest, Python's most popular testing framework. Learn test-driven development (TDD), write maintainable tests, and ensure code quality through comprehensive testing strategies.

Learning Objectives

• Write unit, integration, and functional tests with pytest
• Use fixtures for test setup and teardown
• Mock external dependencies effectively
• Implement test-driven development (TDD)
• Measure and improve code coverage
• Integrate tests with CI/CD pipelines

Core Topics

1. Pytest Basics

• Test discovery and naming conventions
• Assertions and comparison
• Test organization (files, classes, modules)
• Running tests (command-line options)
• Markers and test selection
• Parametrized tests

Code Example:

# test_calculator.py
import pytest

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

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

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

# Test exceptions
def test_divide_by_zero():
    with pytest.raises(ValueError, match="Cannot divide by zero"):
        divide(10, 0)

# Parametrized test
@pytest.mark.parametrize("a,b,expected", [
    (10, 2, 5),
    (20, 4, 5),
    (100, 10, 10),
    (-10, 2, -5),
])
def test_divide(a, b, expected):
    assert divide(a, b) == expected

# Test with marker
@pytest.mark.slow
def test_complex_operation():
    # This test takes a long time
    result = sum(range(1000000))
    assert result == 499999500000

2. Fixtures & Test Setup

• Fixture scopes (function, class, module, session)
• Fixture dependencies
• Parametrized fixtures
• Built-in fixtures (tmpdir, capsys, monkeypatch)
• conftest.py for shared fixtures

Code Example:

# conftest.py
import pytest
import tempfile
from pathlib import Path

@pytest.fixture
def sample_data():
    """Provide sample data for tests"""
    return {
        'users': [
            {'id': 1, 'name': 'Alice', 'email': 'alice@example.com'},
            {'id': 2, 'name': 'Bob', 'email': 'bob@example.com'},
        ]
    }

@pytest.fixture
def temp_file():
    """Create temporary file for testing"""
    with tempfile.NamedTemporaryFile(mode='w', delete=False) as f:
        f.write("Test data")
        temp_path = f.name
    yield temp_path
    # Cleanup
    Path(temp_path).unlink()

@pytest.fixture(scope='module')
def database_connection():
    """Module-scoped database connection"""
    db = DatabaseConnection('test.db')
    db.connect()
    yield db
    db.close()

# test_users.py
def test_user_count(sample_data):
    assert len(sample_data['users']) == 2

def test_user_names(sample_data):
    names = [user['name'] for user in sample_data['users']]
    assert 'Alice' in names
    assert 'Bob' in names

def test_file_operations(temp_file):
    content = Path(temp_file).read_text()
    assert content == "Test data"

3. Mocking & Test Doubles

• unittest.mock basics
• Mocking functions and methods
• Patching objects
• Mock assertions
• Side effects and return values
• Testing with external dependencies

Code Example:

# api_client.py
import requests

class APIClient:
    def __init__(self, base_url):
        self.base_url = base_url

    def get_user(self, user_id):
        response = requests.get(f"{self.base_url}/users/{user_id}")
        response.raise_for_status()
        return response.json()

    def create_user(self, user_data):
        response = requests.post(f"{self.base_url}/users", json=user_data)
        response.raise_for_status()
        return response.json()

# test_api_client.py
from unittest.mock import Mock, patch
import pytest

@patch('api_client.requests.get')
def test_get_user(mock_get):
    # Setup mock
    mock_response = Mock()
    mock_response.json.return_value = {'id': 1, 'name': 'Alice'}
    mock_response.raise_for_status.return_value = None
    mock_get.return_value = mock_response

    # Test
    client = APIClient('https://api.example.com')
    user = client.get_user(1)

    # Assertions
    assert user['name'] == 'Alice'
    mock_get.assert_called_once_with('https://api.example.com/users/1')

@patch('api_client.requests.post')
def test_create_user(mock_post):
    # Setup mock
    mock_response = Mock()
    mock_response.json.return_value = {'id': 3, 'name': 'Charlie'}
    mock_post.return_value = mock_response

    # Test
    client = APIClient('https://api.example.com')
    user_data = {'name': 'Charlie', 'email': 'charlie@example.com'}
    result = client.create_user(user_data)

    # Assertions
    assert result['id'] == 3
    mock_post.assert_called_once_with(
        'https://api.example.com/users',
        json=user_data
    )

4. Coverage & CI/CD Integration

• Measuring code coverage with pytest-cov
• Coverage reports (terminal, HTML, XML)
• Setting coverage thresholds
• GitHub Actions integration
• GitLab CI integration
• Pre-commit hooks

Code Example:

# pytest.ini
[tool:pytest]
testpaths = tests
python_files = test_*.py
python_classes = Test*
python_functions = test_*
addopts =
    --cov=myapp
    --cov-report=html
    --cov-report=term-missing
    --cov-fail-under=80
    -v

# .github/workflows/test.yml
name: Tests

on: [push, pull_request]

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Set up Python
        uses: actions/setup-python@v4
        with:
          python-version: '3.11'
      - name: Install dependencies
        run: |
          pip install -r requirements.txt
          pip install pytest pytest-cov
      - name: Run tests
        run: |
          pytest --cov=myapp --cov-report=xml
      - name: Upload coverage
        uses: codecov/codecov-action@v3
        with:
          file: ./coverage.xml

# Command line usage
# Run all tests
pytest

# Run with coverage
pytest --cov=myapp

# Generate HTML coverage report
pytest --cov=myapp --cov-report=html

# Run specific test file
pytest tests/test_api.py

# Run tests with marker
pytest -m slow

# Run tests with verbose output
pytest -v

# Stop on first failure
pytest -x

Hands-On Practice

Project 1: Calculator TDD

Build a calculator using test-driven development.

Requirements:

• Write tests BEFORE implementation
• Basic operations (add, subtract, multiply, divide)
• Error handling (division by zero)
• Scientific operations (power, sqrt, log)
• Test coverage > 90%

Key Skills: TDD workflow, parametrized tests, exception testing

Project 2: API Testing Suite

Create comprehensive test suite for a REST API.

Requirements:

• Mock HTTP requests
• Test CRUD operations
• Error handling tests
• Authentication tests
• Integration tests
• CI/CD pipeline setup

Key Skills: Mocking, fixtures, integration testing

Project 3: Database Testing

Test database operations with fixtures and transactions.

Requirements:

• Setup test database fixture
• Test CRUD operations
• Transaction rollback
• Data validation
• Performance tests
• Coverage report

Key Skills: Database fixtures, cleanup, performance testing

Assessment Criteria

• Write clear, maintainable tests
• Use fixtures appropriately
• Mock external dependencies effectively
• Achieve >80% code coverage
• Follow TDD principles
• Integrate tests with CI/CD
• Write meaningful assertions

Resources

Official Documentation

• Pytest Docs - Official documentation
• pytest-cov - Coverage plugin
• unittest.mock - Mocking library

Learning Platforms

• Test-Driven Development with Python - TDD book
• Python Testing with pytest - Brian Okken's book
• Real Python Testing - Tutorials

Tools

• pytest-xdist - Parallel testing
• pytest-mock - Mocking helper
• Hypothesis - Property-based testing
• tox - Testing automation

Next Steps

After mastering pytest, explore:

• Property-based testing - Hypothesis library
• Performance testing - pytest-benchmark
• Mutation testing - mutmut
• Load testing - Locust, pytest-load