Software Engineering 101

A comprehensive guide to software engineering fundamentals using Python as the primary language. This series covers essential practices, principles, and tools that every developer should master to write professional, maintainable code.

Series Overview

Through my experience building production systems and mentoring developers, I've learned that knowing a programming language is just the beginning. The difference between writing code and engineering software lies in the practices, principles, and discipline we apply to our work.

This series distills the core software engineering concepts I wish I had learned earlier in my career, presented with practical Python examples you can immediately apply to your projects.

Learning Path

Articles in This Series

Phase 1: Foundation (Articles 1-3)

Article	Title	Description
1	Version Control with Git	Git fundamentals, branching strategies, commit best practices, and collaborative workflows
2	Development Environment Setup	Python tooling, virtual environments, IDE configuration, and project structure
3	Code Quality Tools	Linting with Ruff, formatting with Black, type checking with mypy

Phase 2: Design & Structure (Articles 4-5)

Article	Title	Description
4	Clean Code Principles	Writing readable, maintainable code with clear naming and structure
5	SOLID Principles	Object-oriented design principles with practical Python examples

Phase 3: Quality Assurance (Articles 6-8)

Article	Title	Description
6	Testing Fundamentals	Unit testing with pytest, test structure, and assertions
7	Advanced Testing Strategies	Mocking, fixtures, integration tests, and test-driven development
8	Documentation Best Practices	Docstrings, README standards, and maintaining documentation

Phase 4: Professional Practices (Articles 9-12)

Article	Title	Description
9	Error Handling and Logging	Exception handling, structured logging, and debugging strategies
10	CI/CD Fundamentals	GitHub Actions, automated testing, and deployment pipelines
11	Code Review Practices	Review best practices, PR workflows, and team collaboration
12	Production Readiness	Containerization, configuration management, and observability basics

Prerequisites

• Basic Python programming knowledge

• Command line familiarity

• A code editor (VS Code recommended)

• Git installed on your system

What You'll Learn

By completing this series, you'll be able to:

• Collaborate effectively using Git and modern version control workflows

• Set up professional development environments with proper tooling

• Write clean, readable code that follows industry best practices

• Apply SOLID principles to design maintainable software

• Test your code thoroughly with pytest and modern testing strategies

• Document your projects clearly and effectively

• Handle errors gracefully with proper logging and debugging

• Automate quality checks with CI/CD pipelines

• Conduct meaningful code reviews that improve team code quality

• Prepare applications for production with containers and monitoring

Technology Stack

Throughout this series, we'll use:

Tool	Purpose
Python 3.11+	Primary programming language
Git	Version control
pytest	Testing framework
Ruff	Fast Python linter
Black	Code formatter
mypy	Static type checker
GitHub Actions	CI/CD platform
Docker	Containerization
VS Code	Recommended IDE

Related Series

This series focuses on software engineering fundamentals. For deeper dives into specific areas, see:

• Database 101 - Data layer patterns, SQL, and database design

• Kubernetes 101 - Container orchestration and deployment

• CI/CD Pipeline - Advanced pipeline patterns

How to Use This Series

1. Sequential Learning: Articles build on each other - start from Article 1

2. Hands-On Practice: Each article includes exercises - do them!

3. Reference Guide: Use individual articles as quick references later

4. Project Application: Apply concepts to a real project alongside reading

Sample Project

Throughout this series, we'll build a Task Management CLI application that demonstrates all concepts:

task-manager/
├── src/
│   └── task_manager/
│       ├── __init__.py
│       ├── cli.py
│       ├── models.py
│       ├── storage.py
│       └── validators.py
├── tests/
│   ├── __init__.py
│   ├── test_models.py
│   ├── test_storage.py
│   └── test_validators.py
├── .github/
│   └── workflows/
│       └── ci.yml
├── pyproject.toml
├── README.md
└── Dockerfile

This project is intentionally simple but comprehensive enough to demonstrate professional practices.

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Ready to begin? Start with Article 1: Version Control with Git

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This series is part of my ongoing effort to document practical software engineering knowledge. For questions or feedback, feel free to open an issue in the repository.