python-best-practices
Type hints, dataclasses, async patterns, testing with pytest, and modern Python tooling
浏览 nategarelik 维护的已发布 AI 技能,比较用途与说明,并通过来源仓库了解安装方式。
已收录技能
15收录技能的仓库 Stars 合计
0仓库 Forks
0平均每个技能的仓库 Stars
0同一仓库中的多个技能可能共享 Stars,合计包含重复仓库数据。
Type hints, dataclasses, async patterns, testing with pytest, and modern Python tooling
PowerShell best practices for Windows development, including cmdlet patterns, module development, and error handling
Dockerfile best practices, multi-stage builds, docker-compose patterns, and Kubernetes concepts
Auto-load when writing TypeScript code. Provides patterns for type safety, async handling, and modern TypeScript idioms.
REST API best practices, OpenAPI/Swagger patterns, authentication, and error response formats
Auto-load when writing tests. Provides TDD workflow, test structure patterns, and common testing idioms.
Auto-load for git operations. Provides branching strategy, commit conventions, and PR workflow.
Design and work with composition data structures. Use when defining schemas, creating database models, building API responses, or transforming composition data between formats.
Design system for the CERN Particle Detector aesthetic. Use when building UI components, styling elements, or implementing the detector workstation interface.
Research product compositions using AI and web sources. Use when needing to find what products, substances, or objects are made of - including ingredients, materials, chemicals, and elements. Essential for buil...
Build 3D visualizations using Three.js and React Three Fiber. Use when implementing 3D components, debugging rendering issues, optimizing performance, or creating interactive visualization features.
Messages framework patterns, constraints, and best practices
Rules, patterns, and anti-cheating for virtual currency
Swift and iOS best practices for this iMessage game project
Patterns for implementing the 6 games (8 Ball, Blackjack, War, Texas Hold'em, Archery, Pong)
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。