PingPong

A web app that helps students out with class assignments and logistics.

Development

Running locally

You need these things to use the app locally.

• Postgres Database
• OpenFGA Authz server
• Python / uv to run the API
• Pnpm to run the FrontEnd.
• OpenAI API Key (for using the app)

The easiest way to run the DB and OpenFGA is through Docker.

Quick setup

First, use the config.dev.example.toml file as a template to create a config.dev.toml file in the root of the repo.

cp config.dev.example.toml config.dev.toml

Then, customize the file to your needs.

Assuming you have a Docker environment available, the easiest way to start up development services is with the following script:

./start-dev-docker.sh

This will set up the DB (with all tables), OpenFGA, and the Python API in containers.

This does not build/start the Web UI; for that, see the web/pingpong/README.md. You may also wish to stop the pingpong-srv-1 container and replace it with an uncontainerized Python API for development (see below for instructions).

Running the Python API outside of Docker

The Quick Setup runs the Python API inside of Docker. This makes development tedious if you need to make changes to the Python code.

To run the Python API outside of Docker, first stop the pingpong-srv-1 container in Docker (but keep the DB and authz containers running).

Next, use the config.local.example.toml file as a template to create a config.local.toml file in the root of the repo.

cp config.local.example.toml config.local.toml

Then, run the following command to start the dev server:

CONFIG_PATH=config.local.toml uv run fastapi dev pingpong --port 8000 --host 0.0.0.0 --reload

This will start a uvicorn server that will automatically reload with code changes as you make them.

First time logging in

When you have everything running (including the UI; see web/pingpong/README.md), go to http://localhost:5173. You should log in with a real email address you have access to. In development, this user will be automatically promoted to a super user, with full permissions to create new classes, etc.

You will receive a real email to that address with a link to log in to the dev server. Click the link, you will be in!

Creating test users

You can use the + email trick to create test user accounts.

For example, if joenudell@testdomain.com is my real email address, I will use that as my super-user account. Then, from the PingPong UI I can invite joenudell+student1@testdomain.com to be a student, and joenudell+teacher1@testdomain.com to be an instructor in a class.

All of the login emails will be sent to joenudell@testdomain.com, so you can easily work with multiple users with different permissions.

Adding new DB Migrations

If you need to modify the database, make your changes in the SQLAlchemy code, then run:

uv run alembic revision --autogenerate -m "<description of change>"

Verify the migration is correct, check it into the repo, and apply it to the database by running:

uv run python -m pingpong db migrate

Authz

The OpenFGA authorization server has a playground that may be useful.

Canvas Authentication

Pingpong supports syncing of group user rosters through Canvas. To set up the integration, set up the following in config.toml (or the respective local config file):

• The URL where the application should send Canvas API requests to.
  canvas_url = "http://canvas.docker"
• The Canvas Client ID to use for authentication requests.
  canvas_client_id = "00000000"
• The Canvas Client Secret to use when requesting authentication tokens.
  canvas_client_secret = "XXXXXXXXXX"

Finally, make sure that the callback URL for Pingpong once the request is authenticated is set up as [Pingpong Base Url]/api/v1/auth/canvas/ on the Canvas Admin panel.

Canvas local deployment:

You can follow the instructions to install a local instance of canvas-lms for testing.

Backend / API

We use Python 3.11 and uv for package management.

If you want to develop outside of a container using a live-reload server, do the following:

Run uv sync to install dependencies.

The following command runs the API in development mode:

uv run uvicorn pingpong:server --port 8000 --workers 1 --reload

NOTE: in development the API uses a mock email sender that prints emails to the console rather than sending them. Remember to check the console when you are expecting an email!

Custom API Config

See the config.toml file for default configuration settings used in development.

You can use another config file if you want to customize your setup, such as config.local.toml which will not be tracked:

CONFIG_PATH=config.local.toml uv run python ...

Frontend / UI

See the web/pingpong directory for instructions.

Production

TKTK instructions for deployment.

The prod deployment is available at pingpong.hks.harvard.edu.

Repo Map

Outline of directories:
===
.db/            -- Directory for stashing DB data during development
.github/        -- Workflows / automation
alembic/        -- Database migrations
assets/         -- App design material
docs/           -- Documentary material
scripts/        -- One-off development / testing code
pingpong/       -- Python API code
  - authz/      -- Authorization model and related code
  - db/         -- Database adapters
  - email/      -- Email send clients
web/            -- Front-end code
  - pingpong/
    - build/    -- Artifacts generated by build commands
    - src/      -- Svelte / TS source code
      - lib/    -- Supporting library code, API clients, custom components
      - routes/ -- UI views (see SvelteKit docs for info on structure)
    - static/   -- Logos, favicons, etc


Important files:
===
./start-dev-docker.sh -- Script for starting development services in Docker
config.dev.toml       -- Config for Python API in Development
conftest.py           -- Config for pytest
docker-compose.yml    -- Base docker compose config
docker-compose.*.yml  -- Docker config overrides for different environments
loadtest.py           -- Script for load-testing with `locust`
test_config.toml      -- App config for Python tests