python-project-structure

Generate four-layer Clean Architecture skeletons for Python FastAPI services.

1|Updated Jun 20, 2026

Search Tags:#fastapi #python #clean-architecture #project-structure #dependency-inversion #import-linter

Ready to run

npx skills add https://github.com/shafibabar/SDLC-Artifact-Factory --skill python-project-structure-shafibabar

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: python-project-structure
Source: https://github.com/shafibabar/SDLC-Artifact-Factory/tree/main/skills/python-project-structure
Command: npx skills add https://github.com/shafibabar/SDLC-Artifact-Factory --skill python-project-structure-shafibabar

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires import-linter, mypy, ruff, and includes references (resource) components.

What problem does it solve?

This Skill solves the inconsistency and architectural drift common in Python backend services by enforcing a strict, layered project layout that ensures maintainability and testability.

Core Features & Use Cases

Layered Architecture Enforcement: Implements the Dependency Rule using import-linter to ensure domain logic remains isolated from infrastructure concerns.
Standardized Skeleton Generation: Provides a consistent src/ package layout, composition root, and port-adapter structure for all FastAPI services.
Use Case: When starting a new microservice, use this Skill to generate a structure that guarantees your domain logic is decoupled from FastAPI, SQL, and Kafka, making it fully testable in isolation.

Quick Start

Use the python-project-structure skill to generate a new four-layer service skeleton in the current directory.

Frequently Asked Questions about python-project-structure

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I enforce Clean Architecture in a FastAPI project?▼

To enforce Clean Architecture in a FastAPI project, use import-linter to define and validate inward-only dependency rules, ensuring domain logic remains isolated from infrastructure concerns like SQL and Kafka.

What is the best way to structure a FastAPI service for testability?▼

The best way to structure a testable FastAPI service is implementing a four-layer project layout with a composition root and port-adapter structure, decoupling domain models from infrastructure for isolated testing.

How do I prevent architectural drift in Python backend services?▼

Prevent architectural drift in Python backend services by standardizing the project layout with a strict src/ package structure and applying CI-gated architectural enforcement using import-linter fitness functions.

Can I use typing.Protocol for dependency inversion in FastAPI?▼

Yes, you can use typing.Protocol for dependency inversion in FastAPI to define structural typing boundaries, ensuring use cases depend on abstract ports rather than concrete infrastructure adapters.

Does import-linter support enforcing architectural boundaries in Python?▼

Yes, import-linter supports enforcing architectural boundaries in Python by validating that dependencies flow inward across layers, preventing infrastructure and framework code from polluting isolated domain logic.

How do I decouple domain logic from FastAPI and SQL?▼

Decouple domain logic from FastAPI and SQL by wiring dependencies through a composition root, isolating domain models in an inner layer that only interacts with external systems via defined ports.