{
    "info": {
        "author": "Chris Lawlor",
        "author_email": "lawlor.chris@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 2 - Pre-Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: BSD License",
            "Natural Language :: English",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.6",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.3"
        ],
        "description": "===============================\nRecommendr\n===============================\n\n.. image:: https://badge.fury.io/py/recommendr.png\n    :target: http://badge.fury.io/py/recommendr\n    \n.. image:: https://travis-ci.org/chrislawlor/recommendr.png?branch=master\n        :target: https://travis-ci.org/chrislawlor/recommendr\n\n.. image:: https://pypip.in/d/recommendr/badge.png\n        :target: https://crate.io/packages/recommendr?version=latest\n\n\nMovie recommendation engine.\n\n* Free software: BSD license\n* Documentation: http://recommendr.rtfd.org.\n\nFeatures\n--------\n\n* A Redis backend for storing movie and rating data.\n\n* A simple user-based recommendations algorithm with swappable distance\n  functions.\n\n* Item-based recommendation algorithm in work.\n\n* A demo command-line client.\n\n\nTry it Out\n----------\n\n* Clone the repo::\n\n\tgit clone git@github.com:chrislawlor/recommendr.git\n\n* Create a python virtual environment with virtualenvwrapper::\n\n\tmkvirtualenv recommendr\n\n* Install requirements::\n\n\tpip install -r requirements.txt\n\n* Install recommendr::\n\n\tpython setup.py install\n\n* First, import some MovieLens data into Redis::\n\n\tpython data/import_data.py\n\n* Run the demo program::\n\n\tpython demo.py\n\n\nThe demo program will ask you for ratings until you have rated 5 movies, then\nit will give some recommendations. Recommendations should improve the more\ntimes you run the demo program.\n\n\n*NOTE*: If your Redis instance is somewhere other than ``locahost:6379``, set\nthe ``REDIS_HOST`` and ``REDIS_PORT`` environment variables. If you wish to use\na Redis DB other than 1, set ``REDIS_DB``.\n\n\nKey Code Points\n---------------\n\n``recommendr.db``: Implements a Redis DB backend suitable for storing movie\nand rating information\n\n::\n\t\n\trecommendr.get_user_based_recommendations(reviewer_id, num=20, similarity=sim_distance)\n\nreturns the top recommendations for a given user. It defaults to using\nEuclidean distance for the similiarity function, optionally pass\n``recommendr.similarity.sim_pearson`` to use the Pearson Coefficient.\n\n\nTest Suite\n----------\n\nI haz one:\n\n::\n\t\n\tpython setup.py test\n\n\n\n\nHistory\n-------\n\n0.0.1a (2013-08-27)\n++++++++++++++++++\n\n* First release on PyPI.",
        "description_content_type": null,
        "docs_url": null,
        "download_url": "UNKNOWN",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "https://github.com/chrislawlor/recommendr",
        "keywords": "recommendr",
        "license": "BSD",
        "maintainer": null,
        "maintainer_email": null,
        "name": "recommendr",
        "package_url": "https://pypi.org/project/recommendr/",
        "platform": "UNKNOWN",
        "project_url": "https://pypi.org/project/recommendr/",
        "project_urls": {
            "Download": "UNKNOWN",
            "Homepage": "https://github.com/chrislawlor/recommendr"
        },
        "release_url": "https://pypi.org/project/recommendr/0.0.1a/",
        "requires_dist": null,
        "requires_python": null,
        "summary": "Movie recommendation engine.",
        "version": "0.0.1a"
    },
    "last_serial": 850570,
    "releases": {
        "0.0.1a": []
    },
    "urls": []
}