fastapi-alembic-sqlmodel-async
A production-ready FastAPI project template with async SQLModel, Alembic, JWT authentication, RBAC, Celery, and Docker.
What is fastapi-alembic-sqlmodel-async?
fastapi-alembic-sqlmodel-async is a production-ready project template for building asynchronous web APIs with FastAPI. It provides a complete setup including async database interactions using SQLModel, authentication with JWT and role-based access control, background task processing with Celery, and Docker-based deployment. The template solves the problem of starting a new FastAPI project from scratch by offering a well-structured, opinionated foundation that incorporates modern Python best practices.
Python developers and teams looking to quickly bootstrap a FastAPI-based backend with async database support, authentication, and task queues. It's particularly useful for those building scalable web applications or microservices who want to avoid repetitive setup and follow established patterns.
Developers choose this template because it bundles essential production-grade features into a single, cohesive starter kit. It saves significant setup time, enforces code quality through integrated tooling, and demonstrates real-world patterns like file uploads, WebSocket integrations, and scheduled tasks, all while maintaining full async compatibility.
Overview
This is a project template which uses FastAPI, Pydantic 2.0, Alembic and async SQLModel as ORM. It shows a complete async CRUD using authentication and role base access control.
Use Cases
Best For
- Bootstrapping a new FastAPI project with async database support
- Implementing JWT authentication and role-based access control in FastAPI
- Adding background task processing with Celery to a Python web app
- Learning modern async patterns with SQLModel and FastAPI
- Setting up a Dockerized development environment for FastAPI
- Building APIs that require file uploads and object storage with MinIO
Not Ideal For
- Simple CRUD APIs that don't require JWT authentication, background tasks, or file storage
- Teams preferring minimal dependencies or a sync-first approach without Docker overhead
- Resource-constrained environments where running PostgreSQL, Redis, and MinIO containers is prohibitive
- Projects needing a non-opinionated starter that allows full control over tooling and architecture
Pros & Cons
Pros
Integrates async SQLModel with FastAPI for type-safe database operations, leveraging Pydantic V2 and SQLAlchemy 2.0, as highlighted in the key features for modern async patterns.
Includes Docker Compose for development and production, Celery with Redis for task queues, and MinIO for file storage, covering common deployment and scalability needs.
Implements JWT-based authentication with role-based access control out of the box, with sample users and roles provided in the database setup section.
Integrates Black, Ruff, mypy, and SonarQube for formatting, linting, type checking, and static analysis, with dedicated Make commands to maintain standards.
Cons
Requires installing Docker, Make, Poetry, and Python 3.10+, which can be a barrier for quick onboarding, as detailed in the lengthy prerequisites section.
Relies on multiple external services (PostgreSQL, Redis, MinIO) even for basic functionality, increasing resource usage and complexity for lightweight projects.
The TODO list admits gaps like async support for Celery scheduler and testing improvements, meaning users may need to patch or wait for updates.
Frequently Asked Questions
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