AAI Backend

The backend library between Auth0 and the AAI portal front end. Technical design document for this project lives in this Google doc.

Requirements

Ensure you have the following installed:

• python 3.13+
• uv (installation instructions)

Installation

Follow these steps to set up the project:

1. Clone the Repository:

   git clone https://github.com/AustralianBioCommons/aai-backend.git
   cd aai-backend

2. Set Up a Virtual Environment: Create and activate a virtual environment:

   uv venv
   source .venv/bin/activate

3. Install Dependencies:

   uv sync

   For dev:

   uv sync --extra dev

4. Install pre-commit:

   pre-commit install

Run the Application

Use uv to run the FastAPI application:

uv run fastapi dev main.py

Run Tests

Execute the test suite using pytest:

uv run pytest

Run the Linter

This command will automatically fix issues where possible:

uv run -- ruff check . --fix

Manually run pre-commit

pre-commit run --all-files

Database management

The deployed service uses a Postgres database on AWS RDS (provisioned automatically by the infrastructure stack). In order to generate migrations for the database locally, we use a Postgres docker container to generate migrations against.

At runtime the task receives database connection details through environment variables (DB_HOST, DB_PORT, DB_NAME, DB_USER, DB_PASSWORD) sourced from AWS Secrets Manager.

After making any changes to the database models, after ensuring that Docker is runnning on your local machine, run the generate_migrations.py script to create migrations:

python generate_migrations.py -m <migration_name_of_your_choice>

and commit them to git. Once your updated code has been deployed on AWS, you can connect to the container via the AWS CLI. Run aws sso login first, then aws ecs execute-command to access a shell in the container:

aws ecs execute-command \
--cluster <cluster-id> \
--task <task-id> \
--container FastAPIContainer \
--command "/bin/sh" \
--interactive

and run the migrations:

uv run alembic upgrade head

Job scheduler

We use the apscheduler library to schedule recurring jobs. Currently this is used to synchronize user information from Auth0 to the AAI database. You can run the job scheduler locally using:

uv run python run_scheduler.py

Note that for small jobs that run on-demand, e.g. sending a notification email when a user signs up, you can use FastAPI's built-in background tasks within the FastAPI app, instead of using the dedicated job scheduler.

Deployment

Currently the service is deployed to AWS via the CDK scripts in deploy/, and updated on each commit to main.

Secrets/configuration variables for the deployment are stored in the GitHub Secrets for the repository.

The service deploys two containers (which both use the same image/Python environment):

• The FastAPI app
• The apscheduler job scheduler

Database Schema Diagram Update

When the database models are changed, the database schema diagram in db_diagram.svg should be updated to reflect the changes.

Generating the Database Schema Diagram

1. The aai-backend/scripts/generate_db_diagram.py script generates a database schema diagram from the SQLAlchemy models defined in the codebase, when a models are added, removed, or modified, the models module should be updated accordingly.

2. To generate an updated database schema diagram, run the following command:

   bash generate_db_diagram.sh

   The updated diagram will be saved in db_diagram.svg. See this pull request as an example.

Documents to be updated

Please update the following documents if there are changes to the database schema:

• AAI User Database Technical Design Document