This directory contains comprehensive testing examples that demonstrate various testing strategies, frameworks, and best practices specifically tailored for DevOps workflows.

examples/testing/
├── unit_tests/              # Unit testing examples
│   ├── calculator.py        # Sample module to test
│   ├── test_calculator_unittest.py   # Unit tests using unittest
│   └── test_calculator_pytest.py     # Unit tests using pytest
├── integration_tests/       # Integration testing examples
│   ├── api_client.py        # Sample API client
│   └── test_api_integration.py       # Integration tests
├── automation_scripts/      # CI/CD automation scripts
│   ├── cicd_automation.py   # Complete CI/CD pipeline script
│   └── github_actions_workflow.yml  # GitHub Actions workflow
├── conftest.py             # Shared pytest fixtures
├── pytest.ini             # pytest configuration
└── README.md              # This file

Make sure you have Python 3.8+ installed and install the required testing dependencies:

# Install basic testing tools
pip install pytest pytest-cov pytest-mock

# Install additional dependencies for examples
pip install requests requests-mock coverage

Using unittest (built-in framework):

# Run unittest tests
cd examples/testing/unit_tests
python test_calculator_unittest.py

# Or using module discovery
python -m unittest discover -s unit_tests -p "test_*.py"

Using pytest (recommended):

# Run all unit tests
pytest examples/testing/unit_tests/ -v

# Run specific test file
pytest examples/testing/unit_tests/test_calculator_pytest.py -v

# Run tests with coverage
pytest examples/testing/unit_tests/ --cov=examples/testing/unit_tests --cov-report=html

# Run integration tests
pytest examples/testing/integration_tests/ -v

# Run integration tests with mocking
pytest examples/testing/integration_tests/test_api_integration.py -v

# Run only integration marked tests
pytest -m integration -v

# Run all tests using pytest configuration
pytest examples/testing/

# Run with specific markers
pytest -m "unit or integration" -v

# Run with coverage report
pytest --cov=examples --cov-report=html --cov-report=term-missing

The automation script provides a complete CI/CD pipeline for testing:

# Run complete pipeline
cd examples/testing/automation_scripts
python cicd_automation.py --project-root ../../../

# Run specific steps
python cicd_automation.py --step unit
python cicd_automation.py --step integration
python cicd_automation.py --step security

Demonstrates testing of individual functions and classes in isolation:

• calculator.py: Simple calculator class with various mathematical operations
• test_calculator_unittest.py: Unit tests using Python's built-in unittest framework
• test_calculator_pytest.py: Unit tests using pytest with modern patterns

Key Concepts Covered:

• Test fixtures and setup/teardown
• Assertion methods and pytest assertions
• Exception testing
• Parametrized testing
• Test organization and naming conventions

Demonstrates testing of component interactions and external dependencies:

• api_client.py: DevOps API client with various operations (server status, deployments, etc.)
• test_api_integration.py: Integration tests with mocking and error handling

Key Concepts Covered:

• Mocking external dependencies
• HTTP client testing with requests-mock
• Error handling and edge cases
• Authentication testing
• Workflow testing

Production-ready CI/CD automation examples:

• cicd_automation.py: Complete Python script for CI/CD pipeline automation
• github_actions_workflow.yml: GitHub Actions workflow for automated testing

Key Concepts Covered:

• Dependency installation and management
• Code quality checks (linting, formatting)
• Test execution and reporting
• Security scanning
• Multi-stage pipeline design
• Artifact generation and reporting

Comprehensive pytest configuration with:

• Test discovery patterns
• Coverage settings
• Custom markers for test categorization
• Output formatting options
• Test filtering and warnings handling

Shared test fixtures and utilities:

• Environment configuration
• Mock objects and services
• Test data builders
• Temporary file management
• Database and API mocking

Tests are organized using pytest markers:

• @pytest.mark.unit - Fast, isolated unit tests
• @pytest.mark.integration - Integration tests with external dependencies
• @pytest.mark.e2e - End-to-end tests (full system)
• @pytest.mark.smoke - Quick validation tests
• @pytest.mark.slow - Tests taking longer than 5 seconds
• @pytest.mark.security - Security-related tests
• @pytest.mark.performance - Performance and benchmark tests

Run specific test categories:

pytest -m unit                    # Only unit tests
pytest -m "integration or e2e"    # Integration and e2e tests
pytest -m "not slow"              # Exclude slow tests

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

# View coverage in terminal
pytest --cov=examples --cov-report=term-missing

# Fail if coverage below threshold
pytest --cov=examples --cov-fail-under=80

# Install pytest-xdist for parallel execution
pip install pytest-xdist

# Run tests in parallel
pytest -n 4  # Use 4 CPU cores
pytest -n auto  # Auto-detect CPU cores

# Drop into debugger on failure
pytest --pdb

# Stop on first failure
pytest -x

# Show local variables in traceback
pytest -l

# Verbose output with print statements
pytest -s -v

# Generate JUnit XML for CI/CD
pytest --junitxml=test-results.xml

# Generate JSON report (requires pytest-json-report)
pip install pytest-json-report
pytest --json-report --json-report-file=report.json

• Clear directory structure separating unit and integration tests
• Descriptive test names following naming conventions
• Logical grouping of related tests

• Each test is independent and can run in isolation
• Proper setup and teardown using fixtures
• No shared state between tests

• External dependencies are mocked in unit tests
• Integration tests use service mocking where appropriate
• Real external services only in end-to-end tests

• Shared test data through fixtures
• Test data builders for complex objects
• Temporary file management for file operations

• Comprehensive exception testing
• Edge case validation
• Error condition handling

• Automated test execution in pipelines
• Quality gates based on test results and coverage
• Multi-environment test configurations

# Quick test run for development
pytest -m "unit and not slow" --tb=short

# Pre-commit testing
python automation_scripts/cicd_automation.py --step lint
python automation_scripts/cicd_automation.py --step unit

Copy github_actions_workflow.yml to .github/workflows/ in your repository for automated testing on every push and pull request.

# Build test image
docker build -t python-devops-test .

# Run tests in container
docker run --rm python-devops-test pytest examples/testing/

1. Start with Unit Tests: Understand basic testing concepts with the calculator examples
2. Explore Integration Tests: Learn mocking and API testing with the API client examples
3. Study Configuration: Examine pytest.ini and conftest.py to understand test organization
4. Try Automation: Run the CI/CD automation script to see complete pipeline testing
5. Implement in Projects: Apply these patterns to your own DevOps projects

• Testing Fundamentals
• Advanced Testing
• CI/CD Testing

1. Import Errors: Make sure you're in the correct directory and Python path is set
2. Missing Dependencies: Install all required packages using pip
3. Permission Errors: Ensure you have write permissions for test artifacts
4. Network Issues: Integration tests may fail if external services are unavailable

• Check the main README.md for general repository information
• Review test output carefully for error messages
• Use pytest --tb=long for detailed error tracebacks
• Enable debug logging with -s -v flags

These examples provide a solid foundation for implementing comprehensive testing in your DevOps Python projects. Adapt and extend them based on your specific requirements.