Python Coding Exercises for Software Testers

A comprehensive collection of Python exercises specifically designed for software testers to develop programming skills, automation capabilities, and testing expertise.

🎯 Overview

This repository contains 17 carefully crafted exercises organized into three difficulty levels, each focusing on real-world testing scenarios and practical skills that software testers need in their daily work.

📚 Exercise Structure

🌱 Basic Exercises (5 exercises)

Location: 1-basic-exercises/ Focus: Fundamental Python concepts and basic testing scenarios

String Validation - Input validation, boundary conditions, string operations
List Operations - Data structure operations, edge cases, searching algorithms
Simple Calculator - Mathematical operations, exception handling, type validation
Password Validator - Multiple validation criteria, security testing concepts
File Reader - File I/O testing, error scenarios, data processing

🚀 Intermediate Exercises (6 exercises)

Location: 2-intermediate-exercises/ Focus: Object-oriented programming, complex data structures, real-world testing applications

Test Data Generator - Generating realistic test data for various scenarios
API Response Parser - JSON validation, schema validation, error handling
Test Case Manager - Managing test cases and execution results
Configuration Validator - Validating application configurations
Log File Analyzer - Analyzing application logs for patterns and issues
Database Mock - Creating mock database operations for testing

⚡ Advanced Exercises (6+ exercises)

Location: 3-advanced-exercises/ Focus: Framework design, advanced patterns, distributed systems

Test Framework Builder - Building a custom testing framework from scratch
API Test Automation - Comprehensive API testing automation framework
Performance Test Suite - Performance testing and load simulation framework
Test Data Factory - Advanced test data generation and management
Mock Server Framework - HTTP mock server for API testing
Test Orchestrator - Distributed test execution and orchestration

🛠 Getting Started

Prerequisites

Python 3.8 or higher
Basic understanding of programming concepts
Familiarity with testing terminology

Setup

Clone or download this repository
Navigate to the project directory

Create and activate a virtual environment:

python -m venv .venv
# Windows
.venv\\Scripts\\activate
# Unix/macOS
source .venv/bin/activate

Install basic dependencies (optional):
```
pip install pytest requests
```

Running Exercises

Each exercise is self-contained with detailed instructions:

# Navigate to an exercise level
cd 1-basic-exercises

# Run a specific exercise
python 01_string_validation.py

🧪 Running Tests

This repository includes a comprehensive test suite to validate your exercise implementations and track your progress.

Quick Start

# Run all basic level tests
python -m pytest tests/basic/ -v

# Run specific exercise tests
python -m pytest tests/basic/test_01_string_validation.py -v

# Run tests for intermediate exercises
python -m pytest tests/intermediate/ -v

Test Infrastructure

The tests/ directory contains:

Basic tests: tests/basic/ - Tests for exercises 1-5
Intermediate tests: tests/intermediate/ - Tests for exercises 6-11
Advanced tests: tests/advanced/ - Tests for exercises 12-17
Test utilities: Fixtures, helpers, and configuration files

Using the Test Runners

Interactive Test Runner

# Run the interactive test runner
python tests/run_tests.py

This will present a menu to choose which tests to run.

Command-Line Test Runner

# Run all tests
python tests/test_runner.py --all

# Run tests by level
python tests/test_runner.py --level basic
python tests/test_runner.py --level intermediate  
python tests/test_runner.py --level advanced

# Run specific exercise tests
python tests/test_runner.py --exercise 01_string_validation

# Generate coverage report
python tests/test_runner.py --level basic --coverage

# List available exercises
python tests/test_runner.py --list

# Validate test environment
python tests/test_runner.py --validate

Test Features

Comprehensive Coverage

Each test file includes:

Unit tests for individual functions
Integration tests for complete workflows
Edge case testing for boundary conditions
Error handling validation
Performance tests for larger inputs

Test Categories

Tests are organized into logical groups:

# Run only fast tests
python -m pytest tests/ -m "not slow"

# Run performance tests
python -m pytest tests/ -m "slow"

# Run specific test categories
python -m pytest tests/ -k "test_validation"

Test Status Tracking

✅ Tests pass: Exercise is correctly implemented
❌ Tests fail: Implementation needs work or doesn't exist yet
⏭️ Tests skipped: Module couldn't be imported (not implemented)

Understanding Test Results

When Starting (Exercises Not Implemented)

FAILED tests/basic/test_01_string_validation.py - ImportError
SKIPPED - Could not import string validation module

This is expected - tests will fail until you implement the exercises.

During Development

FAILED tests/basic/test_01_string_validation.py::test_is_valid_email - AssertionError

Tests help guide your implementation by showing what functionality is expected.

When Complete

PASSED tests/basic/test_01_string_validation.py::test_is_valid_email

Green tests indicate your implementation meets the requirements.

Test-Driven Development Workflow

Read the exercise description in the exercise file

Run the tests to see what needs to be implemented:

python -m pytest tests/basic/test_01_string_validation.py -v

Implement functions until tests pass
Refactor and improve while keeping tests green
Add additional features and extend tests as needed

Prerequisites for Testing

# Install testing dependencies
pip install pytest pytest-cov

# Optional: Install additional testing tools
pip install pytest-html pytest-xdist

Advanced Test Options

# Generate HTML coverage report
python tests/test_runner.py --level basic --coverage --html

# Run tests in parallel
python -m pytest tests/ -n auto

# Generate detailed HTML test report
python -m pytest tests/ --html=reports/test_report.html

# Run with specific timeout
python tests/test_runner.py --level basic --timeout 30

# Skip slow tests
python tests/test_runner.py --level basic --markers "not slow"

📖 Learning Path

For Beginners

Start with Basic Exercises (1-5)
Focus on understanding Python syntax and concepts
Practice writing simple test scenarios
Learn error handling and edge case testing

For Intermediate Testers

Complete Basic Exercises first
Tackle Intermediate Exercises (1-6)
Focus on object-oriented programming
Learn to work with APIs, databases, and configurations
Practice building reusable testing utilities

For Advanced Practitioners

Complete Basic and Intermediate exercises
Dive into Advanced Exercises (1-6)
Focus on framework design and architecture
Learn advanced patterns and distributed systems
Build production-ready testing tools

💡 Key Learning Objectives

By completing these exercises, you will:

✅ Master Python fundamentals relevant to testing ✅ Build practical testing utilities and automation tools ✅ Understand testing frameworks and their architecture ✅ Learn data validation and processing techniques ✅ Practice error handling and edge case testing ✅ Develop API testing and mocking skills ✅ Create performance testing capabilities ✅ Design extensible and maintainable test code

🔧 Skills Developed

Programming Skills

Python syntax, data structures, and OOP
Error handling and exception management
File I/O and data processing
Regular expressions and pattern matching
Async programming and concurrency

Testing Skills

Test case design and management
Data-driven testing approaches
Mock objects and test doubles
API testing and validation
Performance testing fundamentals
Test automation frameworks

Software Engineering

Design patterns and architecture
Plugin systems and extensibility
Configuration management
Logging and monitoring
Documentation and code quality

📁 Repository Structure

PythonExercise/
├── README.md                          # This file
├── CLAUDE.md                          # AI assistant guidance
├── 1-basic-exercises/
│   ├── README.md                      # Basic exercises overview
│   ├── 01_string_validation.py        # String operations and validation
│   ├── 02_list_operations.py          # List manipulation and searching
│   ├── 03_simple_calculator.py        # Math operations with error handling
│   ├── 04_password_validator.py       # Complex validation rules
│   └── 05_file_reader.py              # File operations and processing
├── 2-intermediate-exercises/
│   ├── README.md                      # Intermediate exercises overview
│   ├── 01_test_data_generator.py      # Test data generation
│   ├── 02_api_response_parser.py      # API response validation
│   ├── 03_test_case_manager.py        # Test case organization
│   ├── 04_config_validator.py         # Configuration validation
│   ├── 05_log_analyzer.py             # Log file analysis
│   └── 06_database_mock.py            # Database mocking
└── 3-advanced-exercises/
    ├── README.md                      # Advanced exercises overview
    ├── 01_test_framework.py           # Custom testing framework
    ├── 02_api_automation.py           # API testing automation
    ├── 03_performance_testing.py      # Performance testing suite
    ├── 04_test_data_factory.py        # Advanced data generation
    ├── 05_mock_server.py              # HTTP mock server
    └── 06_test_orchestrator.py        # Distributed test execution

🎯 Exercise Features

Progressive Difficulty

Each exercise builds upon previous concepts while introducing new challenges and techniques.

Real-World Scenarios

All exercises are based on actual testing scenarios you'll encounter in professional software testing.

Comprehensive Documentation

Each exercise includes:

Clear problem statements
Learning objectives
Implementation guidelines
Test cases for verification
Extension suggestions

Self-Contained

Each exercise is complete and runnable on its own, with no external dependencies required for core functionality.

🤝 Best Practices Emphasized

Code Quality: Clean, readable, and well-documented code
Error Handling: Proper exception handling and edge case management
Testing: Writing tests for your testing tools
Documentation: Clear docstrings and comments
Modularity: Reusable components and separation of concerns
Performance: Efficient algorithms and resource management

🔍 Common Testing Patterns

Throughout the exercises, you'll encounter and implement:

Page Object Model patterns
Data-Driven Testing approaches
Mock and Stub implementations
Factory and Builder patterns
Observer and Command patterns
Repository and Strategy patterns

📊 Assessment and Progress

Self-Assessment

Each exercise includes test cases and examples to verify your implementation.

Progress Tracking

Mark exercises as complete in your personal notes
Build a portfolio of testing utilities
Integrate tools across different exercises

Extension Ideas

Combine exercises to create larger systems
Add new features and capabilities
Integrate with popular testing frameworks
Deploy tools in real testing environments

🌟 Beyond the Exercises

Integration Opportunities

Use the Test Data Generator with API Automation
Combine the Mock Server with the Test Framework
Integrate Log Analyzer with Performance Testing
Use Database Mock across multiple test suites

Production Readiness

Advanced exercises include production-ready features:

Configuration management
Logging and monitoring
Error reporting and recovery
Scalability considerations
Security best practices

📚 Additional Resources

Python Testing Frameworks

pytest - Modern Python testing framework
unittest - Built-in Python testing framework
Robot Framework - Keyword-driven testing framework
behave - Behavior-driven development framework

API Testing Tools

requests - HTTP library for Python
aiohttp - Async HTTP client/server framework
httpx - Modern HTTP client
Postman - API development environment

🚀 Getting Help