FastAPI + Celery Microservice Example

A hands-on example demonstrating how to build a modern, containerized Python microservice with:

• FastAPI for high-performance HTTP & WebSocket endpoints
• Celery for background task processing (Redis broker & result backend)
• PostgreSQL via SQLAlchemy & Alembic migrations
• Jinja2 templates & Bootstrap for a simple form UI
• Broadcaster + WebSockets for live task updates
• Docker Compose for a fully isolated local development stack
• Optional Datadog Agent integration for metrics & centralized logs
• Built-in security scans (Bandit, Semgrep, pip-audit, Trivy) via GitHub Actions

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🚀 Project Goals

1. Show how to cleanly separate web (FastAPI) and worker (Celery) concerns
2. Provide synchronous REST + real-time WebSocket hooks for task status
3. Illustrate container-based development with automatic reloads
4. Enforce code quality & security best practices in CI/CD
5. Offer a ready-to-fork template for future microservice projects

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📦 Tech Stack

• Python 3.11
• FastAPI, Uvicorn
• Celery 5.x, Redis
• SQLAlchemy 2.x, Alembic
• Jinja2 + Bootstrap 5
• broadcaster (WebSocket pub/sub)
• Docker, Docker Compose
• Datadog Agent (optional)
• Bandit, Semgrep, safety, pip-audit, Trivy (security)

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🛠️ Getting Started

Prerequisites

Docker & Docker Compose

1. Clone & Configure

git clone https://github.com/your-org/fastapi-celery-project.git
cd fastapi-celery-project

2. Build & Run

docker-compose up --build

3. Access the App

• Web UI: http://localhost:8000
• API Docs: http://localhost:8000/docs
• Celery Flower: http://localhost:5555
• PostgreSQL: http://localhost:5432 (user: postgres, password: postgres)
• Redis: http://localhost:6379

This work is mainly based on the FastAPI + Celery Microservice Example.