Bootstrap python service

What is Bootstrap python service?

An example implementation of a Python application applying Clean Architecture and SOLID principles, providing a template for building maintainable services. It includes out-of-the-box functionalities like FastAPI, Dramatiq, Socket.io, SQLAlchemy, and OpenTelemetry.

How to use Bootstrap python service?

Create a GitHub repository using the template. Install uv and Docker, then use Docker commands like make containers, docker compose up dev-http, or Make commands like make install-dependencies and make dev-http. Run tests with make test or docker compose run --rm test.

Key features of Bootstrap python service?

• Sync and Async API Documentation using FastAPI and AsyncAPI
• Async tasks execution using Dramatiq
• Websocket application using Socket.io
• Repository pattern for databases using SQLAlchemy
• Full observability setup using OpenTelemetry

Use cases of Bootstrap python service?

• Building a clean architecture microservice with FastAPI
• Implementing async task processing with Dramatiq
• Setting up real-time communication via WebSockets
• Applying repository pattern for database access
• Deploying with CI/CD pipeline for GitLab

FAQ from Bootstrap python service

Where can I find the documentation?

Documentation is available online on GitHub Pages or offline by running make docs after installing dev dependencies.

What are the prerequisites to run the service?

You need to install uv and Docker. On macOS, uv can be installed with brew install uv; Docker can be downloaded from docker.com.

Does this template include authentication and observability?

Yes, it includes authentication and Identity Provider using ORY Zero Trust architecture, and full observability with OpenTelemetry (Metrics, Traces, Logs).

What database technologies are used?

It uses SQLAlchemy with the repository pattern and Alembic for database migrations, configured to support both sync and async engines.

Is this template production-ready?

It is an example implementation but includes production-like features such as CI/CD pipelines, authentication, observability, and a minimized Dockerfile for smaller production images.