def test_run_constant_predictor(self):
""" Tests the input and output formats of run()"""
reader = StringIO("1:\n1\n2\n3\n")
writer = StringIO()
predictor = ConstantPredictor(1)
answer = ConstantPredictor(2)
Netflix.run(reader, writer, predictor, answer)
self.assertEqual(writer.getvalue(), "1:\n1.0\n1.0\n1.0\nRMSE: 1.00\n")
def test_solve(self):
"""
test solve
"""
read = StringIO("10089:\n662823\n1693997\n1985602\n2345955\n1205751\n")
word = StringIO()
Netflix.netflix_solve(read, word)
self.assertEqual(word.getvalue(),
"10089:\n2.4\n4.4\n2.8\n3.0\n5.0\nRMSE: 0.59\n")
def test_run_math_predictor(self):
""" Tests run() using the MathPredictor """
reader = StringIO("1:\n1\n2\n3\n")
writer = StringIO()
predictor = Netflix.MathPredictor(
{1: 2.5}, {1: 1.0}, {1: 0, 2: 1, 3: -1})
answer = ConstantPredictor(3)
Netflix.run(reader, writer, predictor, answer)
self.assertEqual(writer.getvalue(), "1:\n2.5\n3.5\n1.5\nRMSE: 0.96\n")
def test_parse_training_data_2 (self):
reader = StringIO.StringIO('1:\n1,1,1111-11-11\n2,2,2222-22-22\n')
customers = {}
movie, average = Netflix.parse_training_data(reader, customers)
self.assert_(movie == '1')
self.assert_(average == 1.5)
self.assert_(customers == {'1' : [1, 1], '2' : [2, 1]})
def test_math_predictor_no_movie(self):
""" Tests handling invalid movie """
predictor = Netflix.MathPredictor(
{1: 2.5}, {1: 1.0}, {1: 0, 2: 1, 3: -1})
with self.assertRaises(KeyError):
predictor.predict(1, 2)
def test_answer_cache(self):
""" Tests that the AnswerCache returns the actual ratings"""
cache = Netflix.AnswerCache(answers())
self.assertEqual(cache.predict(1, 1), 4)
self.assertEqual(cache.predict(1, 2), 5)
self.assertEqual(cache.predict(2, 2), 4)
def update_recommendations(data, entity, old_prefs): REC_LEN = 100 ACTOR_VAL = 15 GENRE_VAL = 20 DIRECTOR_VAL = 25 WRITER_VAL = 30 movies_to_add = [] # preferences # clear old prefs from the new pref list if entity in old_prefs[0]: data['pos'].remove(entity) if entity in old_prefs[1]: data['neg'].remove(entity) if entity[0] == 'PERSON': person = update_actor(data['imdbi'], entity, data['recs'], ACTOR_VAL) # add movies to rec list for movieID in person['actor']: movie = data['imdbi'].get_movie(movieID, cast_info=False, aka_info=False) #print movie['id'],'\t',movie['title'] if movie['id'] == data['recs'][1][0]: break movies_to_add.append([movie['id'], movie['title'], ACTOR_VAL]) #### # How do I tell between a director and a writer or actor? #### if 'director' in person: print person['name'],' as a director!' if 'writer' in person: print person['name'],' as a writer!' elif entity[0] == 'GENRE': for movie in data['recs']: m = data['imdbi'].get_movie(movie[0], cast_info=False, aka_info=False) if 'genres' in m and entity[1] in m['genres']: movie[2] += GENRE_VAL elif entity[0] == 'MOVIE': print 'Movie update start' movieEntity = data['imdbi'].get_movie(entity[1])#, cast_info=False, aka_info=False) new_movies = Netflix.similar_movies(movieEntity['title'], data['imdbi']) new_movies = rec_get_diff.get_top_x(movieEntity,new_movies) for movie,title,rating in data['recs']: if movie in new_movies[0]: data['recs'].remove([movie,title,rating]) movies_to_add.extend(new_movies) # update new stuff with old prefs for pref in old_prefs[0]: if pref[0] == 'PERSON': update_actor(data['imdbi'], pref, movies_to_add, ACTOR_VAL) elif pref[0] == 'GENRE': for movie in data['recs']: m = data['imdbi'].get_movie(movie[0], cast_info=False, aka_info=False) if 'genres' in m and entity[1] in m['genres']: movie[2] += GENRE_VAL # CULL data['recs'].extend(movies_to_add) data['recs'].sort(key=lambda x: x[2], reverse=True) del data['recs'][REC_LEN:]
def main():
# Get the path to Netflix data from the command line
try:
directory = sys.argv[1]
directory = os.path.abspath(directory)
except IndexError:
print 'Usage: RunNetflix.py path_to_netflix_data'
exit(1)
customers = {}
movies = {}
precision = 10
# Get all the files in the training set
training_set = os.path.join(directory, 'training_set/')
files = os.listdir(training_set)
# Parse all the training data
for file in files:
file = os.path.join(training_set, file)
reader = open(file, 'r')
movie, average = Netflix.parse_training_data(reader, customers)
reader.close()
movies[movie] = average
average = Netflix.average_customer_rating(customers)
file = os.path.join(directory, 'probe.txt')
reader = open(file, 'r')
for line in reader:
if line[-2] == ':':
movie = line[:-2]
print movie + ':'
else:
customer = line[:-1]
rating = Netflix.predict_rating(average, movies[movie],
customers[customer])
print '{0:.{1}f}'.format(rating, precision)
reader.close()
def main ():
# Get the path to Netflix data from the command line
try:
directory = sys.argv[1]
directory = os.path.abspath(directory)
except IndexError:
print 'Usage: RunNetflix.py path_to_netflix_data'
exit(1)
customers = {}
movies = {}
precision = 10
# Get all the files in the training set
training_set = os.path.join(directory, 'training_set/')
files = os.listdir(training_set)
# Parse all the training data
for file in files:
file = os.path.join(training_set, file)
reader = open(file, 'r')
movie, average = Netflix.parse_training_data(reader, customers)
reader.close()
movies[movie] = average
average = Netflix.average_customer_rating(customers)
file = os.path.join(directory, 'probe.txt')
reader = open(file, 'r')
for line in reader:
if line[-2] == ':':
movie = line[:-2]
print movie + ':'
else:
customer = line[:-1]
rating = Netflix.predict_rating(average, movies[movie], customers[customer])
print '{0:.{1}f}'.format(rating, precision)
reader.close()
def main () :
"""
runs the program. Cache used is determined by flags below
Default (no flags): use training set to create internal cache (no cache file read or write)
@flag -cw Cache Write: process training set to write cache to external file
@flag -cr Cache Read: use external cache file (no training set processing)
@flag -v Verbose: use external cache file (no training set processing)
"""
Netflix.verbose = "-v" in sys.argv
Netflix.toFile = "-cw" in sys.argv
if "-cr" not in sys.argv :
Netflix.netflix_learn()
else :
Netflix.netflix_get_cache()
Netflix.netflix_eval()
def test_average_customer_rating_3 (self):
customers = {'1' : [5, 1], '2' : [2, 1], '3' : [3, 1], '4' : [4, 1], '5' : [1, 1]}
Netflix.average_customer_rating(customers)
self.assert_(len(customers) == 5)
self.assert_(customers == {'1' : 5.0, '2' : 2.0, '3' : 3.0, '4' : 4.0, '5': 1.0})
def test_load_average(self):
"""Test total_average pulls int"""
Netflix.load_files()
self.assertNotEqual(Netflix.TOTAL_AVERAGE, 0.0)
def test_eval_3(self):
Netflix.current_movie = 0
v = Netflix.netflix_eval(2)
self.assertEqual(v, 2)
def test_print_2(self):
w = StringIO()
Netflix.netflix_print(w, 'abcdefg')
self.assertEqual(w.getvalue(), "abcdefg\n")
def test_solve_1(self):
r = StringIO("0:\n0\n")
w = StringIO()
Netflix.netflix_solve(r, w, False)
self.assertEqual(w.getvalue(), "0:\n1.3\nRMSE: 1.7\n")
def test_load_customer_id(self):
""" customer_id should still be 0 here"""
Netflix.load_files()
self.assertEqual(Netflix.CUSTOMER_ID, 0)
def test_solve_3(self):
r = StringIO("0:\n2\n")
w = StringIO()
Netflix.netflix_solve(r, w, False)
self.assertEqual(w.getvalue(), "0:\n2.0\nRMSE: 2.0\n")
def test_load_movie_averages(self):
""" test movie_year set is modified"""
Netflix.load_files()
self.assertNotEqual(Netflix.MOVIE_AVERAGES, {})
def test_load_movie_id(self):
"""movie_id should still be 0 here"""
Netflix.load_files()
self.assertEqual(Netflix.MOVIE_ID, 0)
def test_load_customer_averages(self):
""" test movie_year set is modified"""
Netflix.load_files()
self.assertNotEqual(Netflix.CUSTOMER_AVERAGES, {})
def test_load_actual_rating(self):
"""Test total_average pulls int"""
Netflix.load_files()
self.assertNotEqual(Netflix.ACTUAL_RATING, {})
def test_load_movie_years(self):
""" test movie_year set is modified"""
Netflix.load_files()
self.assertNotEqual(Netflix.MOVIE_YEARS, {})
def test_average_customer_rating_4 (self):
customers = {'1' : [10, 2], '2' : [4, 2], '3' : [6, 2], '4' : [8, 2], '5' : [2, 2]}
Netflix.average_customer_rating(customers)
self.assert_(len(customers) == 5)
self.assert_(customers == {'1' : 5.0, '2' : 2.0, '3' : 3.0, '4' : 4.0, '5': 1.0})
def test_math_predictor_1(self):
""" Tests that the MathPredictor does the correct math """
predictor = Netflix.MathPredictor(
{1: 2.5}, {1: 1.0}, {1: 0, 2: 1, 3: -1})
self.assertEqual(predictor.predict(1, 1), 2.5)
def test_average_customer_rating_5 (self):
customers = {'1' : [7, 2]}
Netflix.average_customer_rating(customers)
self.assert_(len(customers) == 1)
self.assert_(customers == {'1' : 3.5})
def test_eval_1(self):
Netflix.current_movie = 0
v = Netflix.netflix_eval(0)
self.assertEqual(round(v, 2), 1.3)
def test_average_customer_rating_1 (self):
customers = {'1' : [3, 1]}
Netflix.average_customer_rating(customers)
self.assert_(len(customers) == 1)
self.assert_(customers == {'1' : 3.0})
def test_print_2(self):
"""Test print2"""
write = StringIO()
Netflix.netflix_print(write, 1.3)
self.assertNotEqual(write.getvalue(), ".3\n")
def test_print_3(self):
w = StringIO()
Netflix.netflix_print(w, '\n')
self.assertEqual(w.getvalue(), "\n\n")
def test_print_3(self):
"""Test print3"""
write = StringIO()
Netflix.netflix_print(write, 1000)
self.assertEqual(write.getvalue(), "1000\n")
def test_answer_cache_invalid_user(self):
""" Tests handling invalid user """
cache = Netflix.AnswerCache(answers())
with self.assertRaises(KeyError):
cache.predict(5, 1)
def test_print_4(self):
"""Test print4"""
write = StringIO()
Netflix.netflix_print(write, 189)
self.assertNotEqual(write.getvalue(), "9\n")
def test_read_movie3(self):
"""Test read movie_id"""
string = "00"
result = Netflix.netflix_read(string)
self.assertNotEqual(result, 0)
import Netflix
import YouTube
import GMedia
import Outside
import Mainland
import Apple
import ad_lite
print("去广告工作开始")
os.system('python ./ad.py')
print("去广告精简版工作开始")
os.system('python ./ad_lite.py')
print("CMedia工作开始")
CMedia.mainchange()
print("Microsoft工作开始")
Microsoft.change()
print("Netflix工作开始")
Netflix.change()
print("YouTube工作开始")
YouTube.change()
print("GMedia工作开始")
GMedia.mainchange()
print("Outside工作开始")
Outside.mainchange()
print("Mainland工作开始")
Mainland.mainchange()
print("Apple工作开始")
Apple.mainchange()
print("所有工作都完成")
def test_math_predictor_2(self):
""" Tests that the MathPredictor does the correct math with adjustments """
predictor = Netflix.MathPredictor(
{1: 2.5}, {1: 1.0}, {1: 0, 2: 1, 3: -1})
self.assertEqual(predictor.predict(2, 1), 3.5)
def test_read_customer4(self):
"""Test read customer_id"""
string = "10\n"
result = Netflix.netflix_read(string)
self.assertNotEqual(result, 0)
