Python fastapi ddd tooling skill

Skill iktakahiro/python-fastapi-ddd-skill/skills/python-fastapi-ddd-tooling-skill

A practical template for Building AI Agent Skills with Python, FastAPI, and Domain-Driven Design (DDD).

Install

npx -y skills add iktakahiro/python-fastapi-ddd-skill --skill python-fastapi-ddd-tooling-skill

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What its author says it does

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Guides project tooling for a Python FastAPI + SQLAlchemy DDD/Onion Architecture codebase: uv-based environment setup, Makefile workflows, ruff formatting/linting, mypy typing, pytest, and CI (GitHub Actions), based on the dddpy reference. Use when bootstrapping a repo or tightening developer experience and quality gates.

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SKILL.md

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Tooling & DX for FastAPI DDD Projects (uv / ruff / mypy / CI)

This skill is about developer experience and quality automation for a DDD FastAPI project, following the conventions in dddpy.

Goals

One-command local setup (make install)
Fast feedback loop (make test, make format, make dev)
Reproducible CI (GitHub Actions + Python matrix)

Recommended stack (dddpy-style)

Python >=3.13
uv for venv + dependency install + running tools
ruff for formatting/linting
mypy for type checking
pytest for tests

Makefile workflow (core targets)

Keep a small Makefile that shells out to tools inside .venv/:

venv: create .venv
install: install editable package + dev deps
test: run mypy + pytest
format: run ruff formatter
dev: run fastapi dev via uv

CI workflow

Run make install + make test on push/PR with a Python version matrix (e.g., 3.13, 3.14) and install uv in CI.

App bootstrap patterns

Use FastAPI lifespan to create tables on startup and dispose the engine on shutdown.
Keep SQLAlchemy engine/session setup in infrastructure/sqlite/database.py (or equivalent).
Configure logging once at startup (logging.config.fileConfig(...)).

For concrete file templates (Makefile, workflow YAML, bootstrap snippets), read references/TOOLING.md.