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python-fastapi-developmentPython FastAPI 开发

Agent Skill

用于辅助 Python 项目开发、测试、依赖管理和常见框架工作流。它适合让 Agent 阅读 Python 代码、定位测试问题、整理运行命令、生成脚本或分析数据处理逻辑。使用时需要确认项目虚拟环境、依赖版本和测试入口;涉及执行脚本、读写文件、访问数据库或调用外部 API 时,应先明确运行目录和输入输出范围,避免误改生产数据。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:python-fastapi-development(Python FastAPI 开发)
来源仓库:https://github.com/sickn33/antigravity-awesome-skills
仓库路径:skills/python-fastapi-development
安装命令:
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill python-fastapi-development
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill python-fastapi-development

简介

提供 FastAPI 全生命周期开发运维支持。

  • 涵盖容器化部署、监控告警与日志收集。python-fastapi-development 属于运维和基础设施类 Skill,可作为该场景下的辅助能力补充。
  • 支持 Prometheus/Grafana 指标暴露配置。
  • 生产环境建议使用 Gunicorn + Uvicorn 组合。
  • 数据库连接池大小应根据负载压测结果调整。

SKILL.md

Python/FastAPI Development Workflow

Overview

Specialized workflow for building production-ready Python backends with FastAPI, featuring async patterns, SQLAlchemy ORM, Pydantic validation, and comprehensive API patterns.

When to Use This Workflow

Use this workflow when:

  • Building new REST APIs with FastAPI
  • Creating async Python backends
  • Implementing database integration with SQLAlchemy
  • Setting up API authentication
  • Developing microservices

Workflow Phases

Phase 1: Project Setup

Skills to Invoke

  • app-builder - Application scaffolding
  • python-development-python-scaffold - Python scaffolding
  • fastapi-templates - FastAPI templates
  • uv-package-manager - Package management

Actions

  1. Set up Python environment (uv/poetry)
  2. Create project structure
  3. Configure FastAPI app
  4. Set up logging
  5. Configure environment variables

Copy-Paste Prompts

Use @fastapi-templates to scaffold a new FastAPI project
Use @python-development-python-scaffold to set up Python project structure

Phase 2: Database Setup

Skills to Invoke

  • prisma-expert - Prisma ORM (alternative)
  • database-design - Schema design
  • postgresql - PostgreSQL setup
  • pydantic-models-py - Pydantic models

Actions

  1. Design database schema
  2. Set up SQLAlchemy models
  3. Create database connection
  4. Configure migrations (Alembic)
  5. Set up session management

Copy-Paste Prompts

Use @database-design to design PostgreSQL schema
Use @pydantic-models-py to create Pydantic models for API

Phase 3: API Routes

Skills to Invoke

  • fastapi-router-py - FastAPI routers
  • api-design-principles - API design
  • api-patterns - API patterns

Actions

  1. Design API endpoints
  2. Create API routers
  3. Implement CRUD operations
  4. Add request validation
  5. Configure response models

Copy-Paste Prompts

Use @fastapi-router-py to create API endpoints with CRUD operations
Use @api-design-principles to design RESTful API

Phase 4: Authentication

Skills to Invoke

  • auth-implementation-patterns - Authentication
  • api-security-best-practices - API security

Actions

  1. Choose auth strategy (JWT, OAuth2)
  2. Implement user registration
  3. Set up login endpoints
  4. Create auth middleware
  5. Add password hashing

Copy-Paste Prompts

Use @auth-implementation-patterns to implement JWT authentication

Phase 5: Error Handling

Skills to Invoke

  • fastapi-pro - FastAPI patterns
  • error-handling-patterns - Error handling

Actions

  1. Create custom exceptions
  2. Set up exception handlers
  3. Implement error responses
  4. Add request logging
  5. Configure error tracking

Copy-Paste Prompts

Use @fastapi-pro to implement comprehensive error handling

Phase 6: Testing

Skills to Invoke

  • python-testing-patterns - pytest testing
  • api-testing-observability-api-mock - API testing

Actions

  1. Set up pytest
  2. Create test fixtures
  3. Write unit tests
  4. Implement integration tests
  5. Configure test database

Copy-Paste Prompts

Use @python-testing-patterns to write pytest tests for FastAPI

Phase 7: Documentation

Skills to Invoke

  • api-documenter - API documentation
  • openapi-spec-generation - OpenAPI specs

Actions

  1. Configure OpenAPI schema
  2. Add endpoint documentation
  3. Create usage examples
  4. Set up API versioning
  5. Generate API docs

Copy-Paste Prompts

Use @api-documenter to generate comprehensive API documentation

Phase 8: Deployment

Skills to Invoke

  • deployment-engineer - Deployment
  • docker-expert - Containerization

Actions

  1. Create Dockerfile
  2. Set up docker-compose
  3. Configure production settings
  4. Set up reverse proxy
  5. Deploy to cloud

Copy-Paste Prompts

Use @docker-expert to containerize FastAPI application

Technology Stack

CategoryTechnology
FrameworkFastAPI
LanguagePython 3.11+
ORMSQLAlchemy 2.0
ValidationPydantic v2
DatabasePostgreSQL
MigrationsAlembic
AuthJWT, OAuth2
Testingpytest

Quality Gates

  • All tests passing (>80% coverage)
  • Type checking passes (mypy)
  • Linting clean (ruff, black)
  • API documentation complete
  • Security scan passed
  • Performance benchmarks met

Related Workflow Bundles

  • development - General development
  • database - Database operations
  • security-audit - Security testing
  • api-development - API patterns

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.03%
按下载量换算896

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30.4%
按下载量换算756

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18.7%
按下载量换算465

Gemini CLI

8.16%
按下载量换算203

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敏感数据

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安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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