Scaffold Python backend services with uv, FastAPI, and SQLAlchemy.
npx skills add https://github.com/yugasun/skills --skill dev-server-yugasun
Please help me install this Agent Skill. Skill: dev-server Source: https://github.com/yugasun/skills/tree/main/skills/server Command: npx skills add https://github.com/yugasun/skills --skill dev-server-yugasun
This Skill helps developers quickly scaffold and maintain Python backend services using uv, FastAPI, Pydantic, SQLAlchemy, and AI libraries, reducing setup time and boilerplate.
Initialize a new server project in the server/ directory, then bootstrap FastAPI with modular routing, configure the database, and apply migrations. Use uv to manage dependencies and run the server:
High-intent search queries and answers about installing and using this skill.
To scaffold a FastAPI backend with SQLAlchemy and Alembic, initialize a project using uv, add the required dependencies, create an APIRouter-based modular structure, configure asynchronous data access, and apply Alembic migrations for evolving database schemas.
The best way to structure a FastAPI project for modular routing is using APIRouter modules combined with Pydantic models, which enforces type-safe API contracts and separates route logic from data validation within a scalable server directory structure.
Yes, this FastAPI scaffolding approach supports asynchronous database access by integrating async SQLAlchemy, allowing non-blocking data queries that work seamlessly with FastAPI's asynchronous request handling for reliable production apps.
You can integrate LiteLLM and Docling into a Python backend by adding them as dependencies through uv, enabling document-based AI workflows and processing directly within your FastAPI service endpoints.
Using uv for Python backend dependency management provides faster installation and environment resolution compared to standard pip, enforcing strict project structure and configuration while bootstrapping FastAPI servers efficiently.
To configure Pydantic-settings for FastAPI application configuration, add the pydantic-settings package via uv, define your environment variables in a settings model, and inject it into your FastAPI routers for type-safe configuration management.
julianobarbosaScaffold Python projects with uv, ruff, mypy, pytest, and Flask templates.
0xkynzGenerates modular FastAPI/SQLAlchemy/Alembic project skeletons with automated tests using uv.
microsoftExtract text, tables, and structured data from documents using the Azure Document Intelligence REST SDK for TypeScript.
NaveedTechLabAutomate FastAPI backend creation with RESTful APIs, Pydantic models, and SQLAlchemy.
