sqrl-planner / sqrl-server

Backend API server for Sqrl Planner

sqrl-server

Backend API server for sqrl - a timetable planner for the University of Toronto, Faculty of Arts & Science.

Running the server

You'll need to have Docker installed.

Clone this repo and move into the directory

git clone https://github.com/sqrl-planner/sqrl-server.git
cd sqrl-server

Copy starter files

cp .env.example .env

The defaults are for running in development mode. Go through each variable in the file and make sure it is properly set. You will likely need to update the credentials.

Build the Docker image

The first time you run this, it's going to take 5-10 minutes depending on your internet connection and hardware.

docker-compose up --build

Once the image is built, Docker will automatically spin up a container with the image. The server is now running!

Starting and stopping the Docker container

You can stop running the container by running docker-compose down and similarly, you can start it back up with docker-compose up. This should only take a few seconds since we've already built the image!

Setting up the database

sqrl-server uses MongoDB, a NoSQL database program. An instance of MongoDB is already setup for you (with a sqrl database) by the Docker container.

Alterntively, you can run an instance locally or use a number of database providers. If you do so, create an empty database on your MongoDB instance and update the .env file with your instance information (host, credentials, and db name).

Pulling and syncing course data

If your database is empty, you'll need course information to use sqrl. To pull the latest data from all dataset sources, run

flask sync

The Docker container will automaticlly sync the data on the first-run. You might find it useful to setup a cron job to periodically run this job in production.

Currently, the dataset sources are hardcoded parameters in the config/settings.py file. You must modify this file directly to customize the data sources.

Tools

Linting the codebase

For detecting code quality and style issues, run

flake8

For checking compliance with Python docstring conventions, run

pydocstyle

NOTE: these tools will not fix any issues, but they can help you identify potential problems.

Formatting the codebase

For automatically formatting the codebase, run

autopep8 --in-place --recursive .

For more information on this command, see the autopep8 documentation.

For automatically sorting imports, run

isort .

Running tests

pytest