Python Design Patterns

This one cuts through the pattern paralysis that hits when you're staring at a 500-line function or a class that does everything. It focuses on the fundamentals that actually matter: KISS over clever abstractions, single responsibility for each component, and composition instead of inheritance hierarchies. The examples show real refactoring scenarios like breaking apart god classes, separating HTTP concerns from business logic, and deciding when duplication beats premature abstraction. It's particularly solid for code reviews where you need to articulate why something feels wrong structurally, or when you're designing a new service and want to get the layers right from the start.

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Install

$ npx -y skills add wshobson/agents --skill python-design-patterns --agent claude-code

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Python Design Patterns

Write maintainable Python code using fundamental design principles. These patterns help you build systems that are easy to understand, test, and modify.

When to Use This Skill

Designing new components or services
Refactoring complex or tangled code
Deciding whether to create an abstraction
Choosing between inheritance and composition
Evaluating code complexity and coupling
Planning modular architectures

Core Concepts

1. KISS (Keep It Simple)

Choose the simplest solution that works. Complexity must be justified by concrete requirements.

2. Single Responsibility (SRP)

Each unit should have one reason to change. Separate concerns into focused components.

3. Composition Over Inheritance

Build behavior by combining objects, not extending classes.

4. Rule of Three

Wait until you have three instances before abstracting. Duplication is often better than premature abstraction.

Quick Start

# Simple beats clever
# Instead of a factory/registry pattern:
FORMATTERS = {"json": JsonFormatter, "csv": CsvFormatter}

def get_formatter(name: str) -> Formatter:
    return FORMATTERS[name]()

SKILL.md on GitHub