def test_pearson_recommendations(_id, filtering):
if filtering == 'user':
ratings = read_ratings('ratingstest.csv')
data = get_recommendations(ratings, _id, pearson_correlation)
else:
ratings = read_ratings('ratingstest.csv')
item_based = read_item_based_data('pearsontest', pearson_correlation,
ratings)
data = get_recommended_items(ratings, item_based, _id)
return jsonify(data)
def test_euclidean_recommendations(_id, filtering):
if filtering == 'user':
ratings = read_ratings('ratingstest.csv')
data = get_recommendations(ratings, _id, euclidean_distance)
else:
ratings = read_ratings('ratingstest.csv')
item_based = read_item_based_data('euclideantest', euclidean_distance,
ratings)
data = get_recommended_items(ratings, item_based, _id)
return jsonify(data)
def user_matches(_id):
"""USER MATCHES"""
data = top_matches(read_ratings('ratings.csv'), _id, 100,
pearson_correlation)
return jsonify(data)
def get_users_ratings():
"""USERS RATINGS"""
return jsonify(read_ratings('ratings.csv'))