BoilerClasses is a simple Next.js app with a few Python helper files to format and organize the data. We use a Redis instance to store and rapidly query all our data.

We use Fly.io through Docker to host our app. More steps to run the Docker container through our Dockerfile can be found below.

You can clone this repository and run a local instance of the app in two ways (with or without Docker):

Make sure you have docker installed and the daemon running. More information about installation can be found here. Once you get that up and running, navigate into the cloned repository and run:

docker build . -t boilerclasses

After the image is created, run:

docker run -it -p 3000:3000 boilerclasses

This will expose the container's port 3000 to your machine. Navigate to localhost:3000 to view the app! You can edit whatever files you want locally, but you'll have to rebuild the image every time you want to view your changes. Thus, not ideal for quick changes.

1. Firstly, make sure you have python, node, and redis installed.

2. Then, navigate into the server directory and run the following commands:

   python3 download.py
   python3 harmonize.py
   

   download.py will download JSON files for you from our S3 bucket and harmonize.py will combine these to give you a single JSON file containing all the information required. More details regarding what these files do are coming soon.

3. Now, you want to spawn a Redis instance at the port 6379. To do this, run the following command:

   redis-server --daemonize yes
   

   The daemonize argument will make it run in the background. Alternatively, if you have docker but don't want to install redis-server, you can run:

   docker run --name boilerclasses-redis -i --rm -p 6379:6379 redis/redis-stack-server:latest redis-stack-server --save
   

   Functionally, both of the above commands are equivalent.

4. Once you have that, you can push all the data from the JSON file generated in step 2 to the Redis instance. To do this, run:

   python3 push.py
   

5. Now, navigate back to the root directory and run:

   npm install
   npm run dev
   

   Now, you can make changes within the Next.js app and have them reflect in real-time at localhost:3000.

   PS: if you look at the Dockerfile, you can see that these exact commands are run!

There are four scripts in the server directory that aid with data collection:

1. scrape.py scrapes a particular semester's data from Purdue's catalog. Generates a singular JSON file for a semester.
2. download.py either downloads the data from our S3 bucket, or runs scrape.py for every semester. The default is downloading because it's faster.
3. harmonize.py combines all the JSON files downloaded and makes one JSON containing all the data required.
4. push.py pushes the data from the resultant JSON from harmonize.py to the Redis instance.

We're trying to integrate as many features as possible, and we'll have open issues for the same. If you find a bug or have any feedback, let us through a PR or our feedback form. All contributions are very, very welcome!

Inspired by classes.wtf and Purdue's slow course catalogs. We'd like to also thank our friends over at Boilerexams and BoilerGrades.