def test_cb_recommend():
''' Everytime client ask for recommendation will invoke this method, return a python object '''
db_path = "./test.sqlite"
# If db created then connect, otherwise, load test data.
if os.path.exists(db_path):
DBManager.init_db(db_name='test', is_echo=False)
else:
DBManager.init_db(db_name='test', is_echo=False)
Loader.load(file_path='./tests/food.json')
Loader.load(file_path='./tests/user.json')
Loader.load(file_path='./tests/review.json')
user_id = 20
session = DBManager.get_session()
food = pd.read_sql(session.query(Food).statement,
session.bind).rename(columns={'id': 'food_id'})
review = pd.read_sql(
session.query(UserRecommendationReview).filter(
user_id == UserRecommendationReview.user_id).statement,
session.bind)
review['is_accept'] = np.where(review['is_accept'] == True, 1, 0)
review = review.groupby([
'food_id'
])['is_accept'].mean().reset_index().sort_values(by=["is_accept"],
ascending=False)
final_recommendation = _recommend_food(review, food)
print(final_recommendation)
def test_loader():
DBManager.init_db(db_name='db4')
Loader.load(file_path='./data/food.json')
Loader.load(file_path='./data/user.json')
Loader.traverse_database()
def test_recommend():
''' Everytime client ask for recommendation will invoke this method, return a python object '''
db_path = "./test.sqlite"
# If db created then connect, otherwise, load test data.
if os.path.exists(db_path):
DBManager.init_db(db_name='test', is_echo=False)
else:
DBManager.init_db(db_name='test', is_echo=False)
Loader.load(file_path='./tests/food.json')
Loader.load(file_path='./tests/user.json')
Loader.load(file_path='./tests/review.json')
# Setup session and tables
session = DBManager.get_session()
food = pd.read_sql(session.query(Food).statement,session.bind).rename(columns={'id': 'food_id'})
user = pd.read_sql(session.query(User).statement,session.bind).rename(columns={'id': 'user_id'})
review = pd.read_sql(session.query(UserRecommendationReview).statement,session.bind)
# Data processing & prepare
review['is_accept'] = np.where(review['is_accept']==True, 1, -1)
review = review.groupby(['user_id','food_id'])['is_accept'].sum().reset_index()
rating_pivot = review.pivot(index='user_id',columns = 'food_id',values='is_accept').fillna(0)
rating_df = rating_pivot.as_matrix()
user_ratings_mean = np.mean(rating_df, axis = 1)
r_demeaned = rating_df - user_ratings_mean.reshape(-1, 1)
# Matrix factorization
U, sigma, Vt = svds(r_demeaned, k = 50)
sigma = np.diag(sigma)
prediction_all= np.dot(np.dot(U, sigma), Vt) + user_ratings_mean.reshape(-1, 1)
prediction_df = pd.DataFrame(prediction_all, columns = rating_pivot.columns)
# Recommend top 10 food that the user hasn't been recommended to
recommendation_list = recommend_food(prediction_df, 130, food, review, 10)
print(recommendation_list)
result = session.query(Food).filter(Food.id.in_(recommendation_list)).all()
food_map = {food.id: food for food in result}
food_list = [food_map[id] for id in recommendation_list]
for food in food_list:
food.show_detail()
def test_init_project():
random_db_name_seed = ''.join(
[random.choice(string.ascii_lowercase) for _ in range(10)])
DBManager.init_db(db_name='test_%s' % random_db_name_seed, is_echo=False)
parser.add_argument('-t', '--traverse_database', dest='traverse_database', help='true or false, traverse_database and print all data')
# algorithm related args
parser.add_argument('-a', '--algorithm', dest='algorithm', help='selected used algorithm')
parser.add_argument('-p', '--user_proxy', dest='user_proxy', help='select a userProxy to evaluate algorithm, this argument will close the command line UI')
if __name__ == '__main__':
args = parser.parse_args()
parser.print_help()
# init DB
DB_NAME = args.connection_db or DBManager.DEFAULT_DB_NAME
DB_IS_ECHO = True if args.echo_database in ('true', 'True') else False
print('\n Init database : %s.sqlite' % DB_NAME)
DBManager.init_db(
db_name=DB_NAME,
is_echo=DB_IS_ECHO
)
# optional args
if args.data_directory is not None:
loaad_path = os.path.join(os.getcwd(), args.data_directory)
for root, dirs, files in os.walk(loaad_path):
for file_name in files:
Loader.load(file_path=os.path.join(loaad_path, file_name))
Loader.traverse_database()
if args.data_path is not None:
Loader.load(file_path=args.data_path)
Loader.traverse_database()
if args.traverse_database in ('true', 'True', 't', 'T'): Loader.traverse_database()
def __init__(self, db_name='db', *args, **kwrags):
if db_name is None or not isinstance(db_name, str): raise Exception('please provide DB name to init service')
self.db_name = db_name
DBManager.init_db(db_name=db_name, is_echo=kwrags.get('db_is_echo', True))
self.session = DBManager.get_session()
def test_loader():
DBManager.init_db(db_name='db4')