Movie recommendation engine.
- Free software: BSD license
- Documentation: http://recommendr.rtfd.org.
- A Redis backend for storing movie and rating data.
- A simple user-based recommendations algorithm with swappable distance functions.
- Item-based recommendation algorithm in work.
- A demo command-line client.
Clone the repo:
git clone git@github.com:chrislawlor/recommendr.git
Create a python virtual environment with virtualenvwrapper:
mkvirtualenv recommendr
Install requirements:
pip install -r requirements.txt
Install recommendr:
python setup.py install
First, import some MovieLens data into Redis:
python data/import_data.py
Run the demo program:
python demo.py
The demo program will ask you for ratings until you have rated 5 movies, then it will give some recommendations. Recommendations should improve the more times you run the demo program.
NOTE: If your Redis instance is somewhere other than locahost:6379
, set the REDIS_HOST
and REDIS_PORT
environment variables. If you wish to use a Redis DB other than 1, set REDIS_DB
.
recommendr.db
: Implements a Redis DB backend suitable for storing movie and rating information
recommendr.get_user_based_recommendations(reviewer_id, num=20, similarity=sim_distance)
returns the top recommendations for a given user. It defaults to using Euclidean distance for the similiarity function, optionally pass recommendr.similarity.sim_pearson
to use the Pearson Coefficient.
I haz one:
python setup.py test