Does this skill handle decorator factories with arguments?

Yes, it provides patterns for creating decorator factories, allowing you to pass parameters like cache sizes or retry limits directly into your decorators.

Does this skill support the Python functools library?

Yes, it prioritizes using functools.wraps to preserve function metadata and utilizes built-in decorators like @cache and @lru_cache for professional implementations.

What are cross-cutting concerns in programming?

Cross-cutting concerns are aspects of a program that affect other parts of the system, such as logging, security, or caching. Decorators allow you to handle these globally without cluttering core logic.

When should I avoid using the decorator wrap pattern?

Avoid decorators if the behavior is unique to a single function or if the wrapping logic would obscure the function's primary purpose, making the code harder to read.

Can I use this skill to profile my code?

Absolutely. The skill includes specific patterns for timing function execution and logging performance metrics to help identify bottlenecks.

Python Decorator Implementation

Name: Python Decorator Implementation
Author: jimmc414

byjimmc414

•

開発者ツール

Implements the decorator pattern to add cross-cutting behaviors like caching, logging, and validation without modifying original function logic.

This skill enables Claude to apply Peter Norvig-inspired decorator patterns to your codebase, facilitating the clean addition of cross-cutting concerns. It guides the implementation of wrappers for performance-enhancing techniques like memoization, execution timing, and retry logic, ensuring that your code remains modular and DRY. By following best practices like using functools.wraps, the skill helps maintain function signatures and metadata while extending capabilities seamlessly across your application.

主な機能

01Adds caching and memoization for performance optimization

02Supports stacked decorators and decorator factories

03Provides templates for input validation and retry logic

04Ensures signature preservation using functools.wraps

05Implements execution timing and logging wrappers

061 GitHub stars

ユースケース

01Standardizing logging and error handling across multiple modules

02Optimizing recursive functions or expensive API calls with memoization

03Profiling application performance by timing specific function executions

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jimmc414/claude-code-plugin-marketplace apply-decorator-wrap

For use in Claude.ai and ChatGPT

Download Skill