fast-backend-builder

fast-backend-builder is a project generator and manager for FastAPI with Tortoise ORM & Aerich.

💡 FastAPI Backend Builder – A lightweight library to help you quickly scaffold and build FastAPI projects.

📌 Overview

fast-backend-builder is designed for rapid web application development with FastAPI.
It comes bundled with tools and integrations to help developers create well-structured, maintainable, and production-ready FastAPI applications in no time.

The goal is to provide a one-stop solution to accelerate prototyping and simplify production deployment.

🔗 Source Code: GitHub Repository

✨ Features

  • 🚀 CRUD Base with GraphQL (Strawberry) – Auto-generate and manage CRUD endpoints with GraphQL support
  • 🔐 Authentication with JWT – Built-in secure authentication and token management
  • ⚡ Redis Integration – Caching, sessions, and queue support with Redis
  • 📂 File Storage with MinIO – Easy file upload and attachment handling
  • 🔗 ESB Integrations – Simplified enterprise service bus support
  • 📬 BullMQ Integration – Notifications and queue management out of the box

🚀 Quick Start

Create FastAPI App for more visit https://fastapi.tiangolo.com/

⚙️ Installation

pip install fast-backend-builder

🚀 Setting Up a Custom User Model in FastAPI with Tortoise ORM + FastAPI-Builder

This guide explains how to create a package module for your User model, extend it from AbstractUser, configure it in Tortoise ORM, and generate GraphQL + migrations.

📂 Project Structure

myapp
  ├── mymodel_package
  │   ├── __init__.py
  │   └── models
  │       └── user.py
  ├── config
  │   ├── __init__.py
  │   └── tortoise.py
  ├── main.py
  └── ...

👤 1. Create Your Custom User Model

Inside mymodel_package/models/user.py:

from fast_backend_builder.models.base_models import AbstractUser


class User(AbstractUser):
    """Custom application user model extending AbstractUser."""
    pass

⚙️ 2. Set Your User Model in main.py (your main FastAPI file)

At the top of your main.py (before any model imports):

from fast_backend_builder.utils.config import set_user_model
from mymodel_package.models.user import User

# Register the User model so fast_backend_builder can resolve it
set_user_model(User, "models.User")

🗄️ 3. Create Tortoise ORM Config

Inside config/tortoise.py:

from decouple import config

db_url = f"postgres://{config('DB_USER')}:{config('DB_PASSWORD')}@{config('DB_HOST')}:{config('DB_PORT')}/{config('DB_NAME')}"

TORTOISE_ORM = {
    "connections": {"default": db_url},
    "apps": {
        "models": {
            "models": [
                "fast_backend_builder.models",   # built-in models
                "mymodel_package.models",    # your custom models
                "aerich.models",             # migration tracking
            ],
            "default_connection": "default",
        },
    },
    "use_tz": True,  # Enable timezone-aware datetimes
    "timezone": "Africa/Dar_es_Salaam",  # Set to EAT (Dar es Salaam)
}

🔧 4. Generate CRUD APIs via GraphQL

Run the following to scaffold GraphQL CRUD APIs:

# For your custom User model
graphql gen:crud-api user_management --module-package=mymodel_package.models --model User

# For fast_backend_builder built-in models
graphql gen:crud-api user_management --module-package=fast_backend_builder.models --model Group,Permission,Headship
graphql gen:crud-api workflow --module-package=fast_backend_builder.models --model Workflow,WorkflowStep,Transition,Evaluation

For your Models

# 
graphql gen:crud-api <module-name> --model Model1,Model2,Model3

# generating graphql schemas with attachments

graphql gen:crud-api <module-name> --model ModelName --with-attachment

# generating graphql schemas with transitions

graphql gen:crud-api <module-name> --model ModelName --with-transition

📦 5. Initialize Aerich (DB migrations)

# Initialize Aerich with your Tortoise ORM config
aerich init -t config.tortoise.TORTOISE_ORM

# Create initial migration & database tables
aerich init-db

📖 Documentation

Coming soon...

🤝 Contributing

Contributions, issues, and feature requests are welcome!
Feel free to check the issues page.

📜 License

This project is licensed under the Other/Proprietary License.

Thanks

Thanks for all the contributors that made this library possible, also a special mention to Japhary Juma, Shija Ntula and Juma Nassoro.

Project links

Key dates

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Latest release

1 maintainer

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Credits

Author: Japhary Juma Hamisi

License

MIT License (Other License)

Requires

Python >=3.11

Classifiers

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