FastAPI-app - GitLite

KO | EN

gitlite — search

#javascript #hacktoberfest #react #ai #golang #machine-learning #rust #deep-learning #docker #nodejs #cli #security #pytorch #mcp

FastAPI-app

(★ 107)

Example app using FastAPI, asyncio, SQLModel, Celery, Alembic and Supertokens

File Explorer

Download Latest Version (.zip)

- - __init__.py
  - calculate_event_documentation.py
- - __init__.py
  - account.py
  - base.py
  - domain.py
  - event.py
  - event_documentation.py
  - event_documentation_example.py
  - event_schema.py
  - screenshot.py
  - user.py
- - env.py
  - README
  - script.py.mako
- - __init__.py
  - account.py
  - base.py
  - base_file.py
  - domain.py
  - event.py
  - event_documentation.py
  - event_documentation_example.py
  - event_schema.py
  - screenshot.py
  - user.py
- - __init__.py
- - __init__.py
  - account.py
  - base.py
  - domain.py
  - event.py
  - event_documentation.py
  - user.py
- - __init__.py
  - client.py
  - internal.py
  - web_app.py
- - __init__.py
  - init_supertokens.py
  - logger.py
  - route_handler.py
  - s3_client.py
  - singleton.py
- __init__.py
- celery.py
- config.py
- database.py
- dependencies.py
- main.py
.gitignore
.pre-commit-config.yaml
alembic.ini
LICENSE
Makefile
mypy.ini
poetry.lock
pyproject.toml
README.md

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# FastAPI App

This is a small app that I built while learning Python and FastApi. It allows to create documentations (shared schemas + screenshots) from tracking events. It also serves as a backend for an interface that lets a user register, sign in, set some settings and view documentations.

While building this app, I spent the most time learning the best practices of accomplishing common tasks in the FastAPI ecosystem. I tried out various libraries and arrived at the following list that I think work well together:

- FastAPI + Asyncio
- SQLModel for data models and validation
- Celery for background tasks
- Alembic for migrations
- Supertokens for user authentication
- Mypy for type checking
- Make for running commands

Additionally, the codebase showcases the following things:

- Multiple FastAPI apps in one project
- Alembic auto-generating migrations from model files
- Celery tasks communicating through an SQS FIFO queue
- AWS S3 integration for storing images
- Loggers that print SQL queries and other useful information
- Error handler middlewares
- CORS middleware
- Two separate types of authentication (static auth token for an internal endpoint + Supertokens for user authentication)
- Dependencies management using Poetry
- And more.

## Inspiration

I took a ton of inspiration from the following articles and projects:

[Abstracting FastAPI Services](https://camillovisini.com/article/abstracting-fastapi-services/)

[grillazz/fastapi-sqlalchemy-asyncpg](https://github.com/grillazz/fastapi-sqlalchemy-asyncpg)

[The ultimate async setup: FastAPI, SQLModel, Alembic, Pytest](https://medium.com/@estretyakov/the-ultimate-async-setup-fastapi-sqlmodel-alembic-pytest-ae5cdcfed3d4)

## Project structure

The project is organized into the following directories and files:

| Directory/File Name | Description                                                                          |
| ------------------- | ------------------------------------------------------------------------------------ |
| background_tasks/   | Celery tasks                                                                         |
| crud/               | CRUD operations                                                                      |
| db/                 | Alembic migrations                                                                   |
| models/             | model files that combine data models and Pydantic schemas                            |
| schemas/            | Pydantic schemas for things other than data models (e.g. api requests and responses) |
| services/           | business logic                                                                       |
| subapps/            | FastAPI apps with each file containing a separate app                                |
| utils/              | utility functions                                                                    |
| celery.py           | Celery app                                                                           |
| config.py           | Pydantic settings                                                                    |
| database.py         | SQLAlchemy database engine and session                                               |
| dependencies.py     | FastAPI dependencies                                                                 |
| main.py             | main project file                                                                    |

## Running the project

### Prerequisites

- Python 3.10
- Supertokens account
- GitHub OAuth app (SuperTokens uses GitHub OAuth but that can easily be changed for another OAuth provider)
- AWS Account, an S3 bucket and an SQS queue
- PostgreSQL database

### Steps

1. Clone the repo
2. Change `sqlalchemy.url` in `alembic.ini` to point to your database
3. Use commands in Makefile to install dependencies and run migrations
4. Rename `.env.example` to `.env` and fill in the values
5. Run `make server` and `make worker` to start the web server and the Celery worker

## Pre-Commit Setup

If you are using this project then pre-commit setup would be very helpful for checking your codebase. In short, pre-commit is a tool that allows developers to define and apply automated checks to their code before they commit it to a version control system. You can find more info [here](https://pre-commit.com).

```commandline
pre-commit install

# for the first time, run on all files
pre-commit run --all-files
```

## License

MIT License