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model.py
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model.py
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"""Models and database functions for Ratings project."""
from flask_sqlalchemy import SQLAlchemy
import correlation
# This is the connection to the PostgreSQL database; we're getting this through
# the Flask-SQLAlchemy helper library. On this, we can find the `session`
# object, where we do most of our interactions (like committing, etc.)
db = SQLAlchemy()
##############################################################################
# Model definitions
class User(db.Model):
"""User of ratings website."""
__tablename__ = "users"
user_id = db.Column(db.Integer, autoincrement=True, primary_key=True)
email = db.Column(db.String(64), nullable=True)
password = db.Column(db.String(64), nullable=True)
age = db.Column(db.Integer, nullable=True)
zipcode = db.Column(db.String(15), nullable=True)
def similarity(self, other):
"""Find the pearson correlation between self & other user"""
# 1. {}
# 2. [()]
# go through all the ratings & add to dict w/ movie_id : rating
# check if other user has rated the same movie,
# if yes, push pair into list of tuples
# if the list exists,
# pass list through pearson coeff,
# if it is empty,
# else, return 0
u_ratings = {}
pairs = []
for rating in self.ratings:
u_ratings[rating.movie_id] = rating.rating
for r in other.ratings:
# print "I am other user's rating!!\n\n\n"
# print r
if r.movie_id in u_ratings.keys():
pairs.append((u_ratings[r.movie_id], r.rating))
if pairs:
return correlation.pearson(pairs)
else:
return 0.0
def predict_rating(self, movie):
"""Predict how a user would rate a movie given movie object"""
#how other users rated Toy Story
other_ratings = movie.ratings
# list of tuples, of (pearson coeff between me & user, user's rating)
similarities = sorted([
(self.similarity(r.user), r)
for r in other_ratings
if self.similarity(r.user) > 0
], reverse=True)
# print self.email
# import pdb; pdb.set_trace()
if not similarities:
return None
# weighted mean/ predicted rating = sum(ratings * coeffs)/ sum(coeffs)
numerator = sum([r.rating * sim for sim, r in similarities])
denominator = sum([sim for sim, r in similarities])
return numerator / denominator
def __repr__(self):
"""provide helpful representation when printed"""
return "<User user_id={} email={}>".format(self.user_id,
self.email)
# Put your Movie and Rating model classes here.
class Movie(db.Model):
"""Movie to rate."""
__tablename__ = "movies"
movie_id = db.Column(db.Integer, autoincrement=True, primary_key=True)
title = db.Column(db.String(150), nullable=False)
# release_date = db.Column(db.DateTime, nullable=False)
video_release = db.Column(db.DateTime, nullable=True)
IMDB = db.Column(db.String(150), nullable=True)
# genres = db.Column(db.String(15), nullable=True)
def __repr__(self):
"""provide helpful representation when printed"""
return "<Movie movie_id={} title={} video_release, IMDB>".format(self.movie_id,
self.title)
class Rating(db.Model):
"""Ratings"""
__tablename__ = "ratings"
rating_id = db.Column(db.Integer, autoincrement=True, primary_key=True)
user_id = db.Column(db.Integer, db.ForeignKey("users.user_id"), nullable=False)
movie_id = db.Column(db.Integer, db.ForeignKey("movies.movie_id"), nullable=False)
rating = db.Column(db.Integer, nullable=False)
# timestamp = db.Column(db.datetime, nullable=False)
user = db.relationship("User", backref=db.backref("ratings",
order_by=rating_id))
movie = db.relationship("Movie",
backref=db.backref("ratings",
order_by=rating_id))
def __repr__(self):
"""provide helpful representation when printed"""
return "<Rating movie_id={} rating={} rating_id, user_id>".format(self.movie_id,
self.rating)
##############################################################################
# Helper functions
def connect_to_db(app):
"""Connect the database to our Flask app."""
# Configure to use our PstgreSQL database
app.config['SQLALCHEMY_DATABASE_URI'] = 'postgresql:///ratings'
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
db.app = app
db.init_app(app)
if __name__ == "__main__":
# As a convenience, if we run this module interactively, it will leave
# you in a state of being able to work with the database directly.
from server import app
connect_to_db(app)
print("Connected to DB.")