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Qcumber is a course catalog created for Queen's University students. It is live at, and the main repository is at ChrisCooper/QcumberD on Github. Check out the wiki for extra information not in this readme, or the about page for more information on the project's origins and goals.

The original source code is available under the terms of the Mozilla Public License, v. 2.0, available at Images and other original non-code assets are © 2013 Chris Cooper.

Development overview

Qcumber, for the most part, is composed of web scrapers which pull data into the database, and simple Django apps that display that data on the website. For example, the exam scraper visits ExamBank and pulls all the exam links into simple database entries, and the corresponding Django app (basically just a directory in the project) contains definitions that help make sense of the database entries (known as models), as well as a few related things. The logic for the website itself is actually very simple. Really, all it does is display that data (though we are adding functionality as we speak).

All general configuration is under the qcumber directory, including, the root URL configuration file, javascript + images + CSS (LESS, actually), and files for storing private information like keys, file paths, and passwords (which are not committed to the respository).

To get your own copy of Qcumber to develop or improve, first follow the setup directions below, then run the scrapers for the data you wish to see (i.e. currently: courses, exams, and/or textbooks).

Setup Guide

  • This guide has been verified for Ubuntu 11.10 and 12.10.
  • Setting up on mac OSX should be quite similar. It will be verified soon.
  • Microsoft Windows offers great pains.It works on Windows, but installation there is left as an exercise for the reader.
  1. Installing the Prerequisites

  • Make sure you have all the needed permissions to install.
  • For most users, this means prepending each install command with sudo
  • Ex: sudo apt-get install ...

Python and Libraries

This project has been tested with Python version 2.7. You can try other 2.x versions, but no promises.

  • Run apt-get install python2.7 python2.7-dev
  • This installs Python 2.7 as well as the headers needed for compiling python modules.
  • Some modules that will be installed need to be compiled with GCC.
  • Install GCC by running apt-get install gcc
  • Install extra libraries needed for compiling modules: apt-get install libxml2-dev libxslt1-dev

I (Phil) could not get Qcumber to run under Python 3 after spending a whole couple seconds of trying. I have not tested on any version of Python other than 2.7.

The django project installation documentation would be a good starting point for other operating systems.

Git and a Github account

Pip and a Virtual Environment

Pip is used to install extra Python modules that aren't included by default. A virtual environment is an isolated Python environment. It allows for per-program environment configuration.

  • Install Pip by running apt-get install python-pip
  • Once Pip is installed, run pip install virtualenv
  • The virtual environment will be configured later.

LESS Compiler

LESS is an extension of CSS that adds support for dynamic behaviours like variables and functions.

  • Install Node.js (including the Node Package Manager, npm) using a package manager or from
  • Install the LESS compiler via the Node Package Manger: npm install -g less
  • You can now compile LESS files like this: lessc styles.less > styles.css (this is automatically done in this project).
  1. Fork the Repository

  1. Clone it to your computer

  • Copy the[yourusername]/QcumberD.git link on the page.
  • Open up a terminal window.
  • Navigate to the folder in which you want to store your local copy of Qcumber. For me that would mean cd ~/Code
  • Clone the repository. git clone [repository], where [repository] is the git@github... url you copied earlier.
  • You should now have a QcumberD folder.
  1. Create and Activate a Virtual Environment

  • Navigate into the QcumberD folder: cd QcumberD.

  • Create a new virtual environment: virtualenv --distribute venv

  • Activate the new environment: source venv/bin/activate

  • NOTE: you will need to activate the virtual environment every time you want to run the local project. You can use the same preceeding source command.

  • To deactivate the virtual environment: deactivate

  1. Install Required Packages

Make sure you have activated your virtual environment (see above) before running this command!

  • pip install -r requirements.txt
  • If this command reports an error, check the log to see if you have all the dependencies required.
  1. Configure Your Setup

  • Clone the sample config file cp qcumber/config/ qcumber/config/
  • Change the configuration options in qcumber/config/ to suit your environment. If you are not performing caching, scraping, or sending emails, nothing needs to change in this file for development.
  1. Initialize the Database

Make sure your virtualenv is activated!

  • python syncdb
  • Create the administrative account and follow the prompts.
  • Migrate the south databases: python migrate.
  1. Run Time!

  • python runserver
  • Open a browser and go to http://localhost:8000
  • If everything works, you'll see the Qcumber home page!
  • The database will be empty, so no courses will be present on your setup.

Extra Notes

How to Scrape Course Data

  • Go to http://localhost:8000/scraper/
  • Click the name of one of the jobs. The page status will show as "Waiting for localhost..." while the scraper works.
  • As it scrapes, the progress of the scraper will be visible in your terminal and the retrieved data will become available to the application.
  • You can watch the subjects being added at http://localhost:8000! Scraping time will vary based on the configuration, but a full shallow scrape takes anywhere from 5 to 7 hours, so be patient!

You can also create your own configurations for debugging, by visiting the admin page and creating a Job Config, under scraper. Job configs have the following options:

  • Deep: If this is set, the scraper will do a deep scrape (takes longer, but collects enrollment information)
  • Letters: The subject letters to scrape
  • Start/end indecies: Controls which subjects/courses to scrape. Implemented with Python list slices.

libssl Errors

  • On Mac OS, if you are seeing an error like:
ImportError: dlopen(/Users/Me/QcumberD/venv/lib/python2.7/site-packages/psycopg2/, 2): Library not loaded: @loader_path/../lib/libssl.dylib
Referenced from: /usr/lib/libpq.5.dylib
Reason: Incompatible library version: libpq.5.dylib requires version 1.0.0 or later, but libssl.0.9.8.dylib provides version 0.9.8

then you may need to look at this Stack Overflow answer for the simple solution.


A Django-based course search service for Queen's University




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