python-design-patterns
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.
More from pv-udpv/pplx-sdk
code-analysis
Deep code analysis for pplx-sdk — parse Python AST, build dependency graphs, extract knowledge graphs, detect patterns, and generate actionable insights about code structure, complexity, and relationships. Use when analyzing code quality, mapping dependencies, or building understanding of the codebase.
19spa-reverse-engineer
Reverse engineer Single Page Applications built with React + Vite + Workbox — analyze SPA internals via Chrome DevTools Protocol (CDP), write browser extensions, intercept service workers, and extract runtime state for SDK integration.
19sse-streaming
Implement and debug SSE (Server-Sent Events) streaming for the Perplexity AI API, including parsing, reconnection, and retry logic.
18reverse-engineer
Reverse engineer Perplexity AI web APIs — intercept browser traffic, decode undocumented endpoints, map request/response schemas, extract auth flows, and translate discoveries into SDK code.
18api-design-principles
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
18test-fix
Diagnose and fix failing pytest tests in the pplx-sdk project, following existing test patterns and conventions.
17