Note: If you're looking for the easy to use course catalog for Queen's University, you came close! This is the code for the frontend interface that powers it. You'll want to head to https://qcumber.ca for the end user site :).
This is a simple flask application which talks to Elasticsearch as a data store, and consumes the data found in qcumber-data.
Currently, the frontend is in a bit of a messy state, as it was thrown together over the course of a week to get it ready in time for course selection.
Clone this repository
$ git clone https://github.com/Queens-Hacks/qcumber-frontend
Create a virtualenv and install the requirements from the requirements.txt file into it.
$ virtualenv env
$ . env/bin/activate
$ pip install -r requirements.txt
Install elasticsearch
and get it running. Currently the code only supports the default ports, but there will be options to configure that soon.
Clone the data repository into the out
directory.
$ git clone https://github.com/Queens-Hacks/qcumber-data out
Run the fill.py
script to load the data into the elasticsearch instance.
$ ./fill.py
Now the debug server can be run by running main.py
$ ./main.py