Learning Objectives: After this lesson, you'll implement classic design patterns the Pythonic way, understand when to use each pattern, and build flexible, maintainable code using Factory, Strategy, Observer, Decorator, and Dependency Injection patterns.
Why Design Patterns?
Design patterns are reusable solutions to common programming problems.
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Patterns in Python
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Creational Patterns
Factory Pattern
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Singleton Pattern
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Builder Pattern
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Behavioral Patterns
Strategy Pattern
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Observer Pattern
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Command Pattern
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Structural Patterns
Decorator Pattern (Structural)
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Adapter Pattern
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Dependency Injection
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Practice Exercises
Exercise 1: Plugin System
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Exercise 2: State Machine
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Key Takeaways
| Pattern | Use When |
|---|---|
| Factory | Create objects without specifying exact class |
| Singleton | Ensure only one instance exists |
| Builder | Construct complex objects step by step |
| Strategy | Select algorithms at runtime |
| Observer | One-to-many notifications |
| Command | Encapsulate actions as objects (undo/redo) |
| Decorator | Add behavior dynamically |
| Adapter | Make incompatible interfaces work together |
| DI | Decouple dependencies for testing |
Pythonic Alternatives
| Traditional | Pythonic |
|---|---|
| Strategy class | Function or lambda |
| Factory class | Factory function |
| Singleton class | Module-level instance |
| Iterator class | Generator function |
| Decorator class | @decorator function |
Next Steps
In the next lesson, we'll explore Packaging and Distribution—modern Python packaging with pyproject.toml, dependency management, and publishing to PyPI.
Ready to ship your code? Packaging awaits!