def test_secondary(self):
score = ContentRetriever.computeInitialScore(isPrimeMatch=False,\
numSecond=2, \
views=0, \
comments=0, \
favs=0)
self.assertEqual(2 * ContentRetriever.SECOND_SCORE, score)
def test_view(self):
score = ContentRetriever.computeInitialScore(isPrimeMatch=False,\
numSecond=0, \
views=100, \
comments=0, \
favs=0)
self.assertEqual(ContentRetriever.VIEW_SCORE_ONE, score)
def test_view(self):
score = ContentRetriever.computeInitialScore(isPrimeMatch=False,\
numSecond=0, \
views=100, \
comments=0, \
favs=0)
self.assertEqual(ContentRetriever.VIEW_SCORE_ONE, score)
def test_primary(self):
score = ContentRetriever.computeInitialScore(isPrimeMatch=True,\
numSecond=0, \
views=0, \
comments=0, \
favs=0)
self.assertEqual(ContentRetriever.PRIME_SCORE, score)
def test_secondary(self):
score = ContentRetriever.computeInitialScore(isPrimeMatch=False,\
numSecond=2, \
views=0, \
comments=0, \
favs=0)
self.assertEqual(2 * ContentRetriever.SECOND_SCORE, score)
def test_primary(self):
score = ContentRetriever.computeInitialScore(isPrimeMatch=True,\
numSecond=0, \
views=0, \
comments=0, \
favs=0)
self.assertEqual(ContentRetriever.PRIME_SCORE, score)
def doFinalScoreIfOver(self):
t_up = self.rank.thumbs_up
total_rank = self.rank.thumbs_down + t_up
if total_rank >= Score.COMPUTE_FINAL_NUM:
self.score.final_score = \
ContentRetriever.computeFinalScore(self.score.initial_score, t_up, total_rank)
self.score.save()
def doFinalScoreIfOver(self):
t_up = self.rank.thumbs_up
total_rank = self.rank.thumbs_down + t_up
if total_rank >= Score.COMPUTE_FINAL_NUM:
self.score.final_score = \
ContentRetriever.computeFinalScore(self.score.initial_score, t_up, total_rank)
self.score.save()
def test_inputcase(self):
score = ContentRetriever.computeInitialScore(isPrimeMatch=False,\
numSecond='5', \
views=99, \
comments='10', \
favs=51)
expected = 4 * ContentRetriever.SECOND_SCORE + \
ContentRetriever.VIEW_SCORE_ONE + \
ContentRetriever.FAV_SCORE_ONE
self.assertEqual(expected, score)
def test_inputcase(self):
score = ContentRetriever.computeInitialScore(isPrimeMatch=False,\
numSecond='5', \
views=99, \
comments='10', \
favs=51)
expected = 4 * ContentRetriever.SECOND_SCORE + \
ContentRetriever.VIEW_SCORE_ONE + \
ContentRetriever.FAV_SCORE_ONE
self.assertEqual(expected, score)
def test_anothernormalcase(self):
score = ContentRetriever.computeInitialScore(isPrimeMatch=True,\
numSecond=2, \
views=99, \
comments=10, \
favs=51)
expected = ContentRetriever.PRIME_SCORE + \
2 * ContentRetriever.SECOND_SCORE + \
ContentRetriever.VIEW_SCORE_ONE + \
ContentRetriever.FAV_SCORE_ONE
self.assertEqual(expected, score)
def test_anothernormalcase(self):
score = ContentRetriever.computeInitialScore(isPrimeMatch=True,\
numSecond=2, \
views=99, \
comments=10, \
favs=51)
expected = ContentRetriever.PRIME_SCORE + \
2 * ContentRetriever.SECOND_SCORE + \
ContentRetriever.VIEW_SCORE_ONE + \
ContentRetriever.FAV_SCORE_ONE
self.assertEqual(expected, score)
def computeVideoScore(entry, mood):
prime_term = getPrimeTerm(mood)
sec_terms = getSecTerm(mood)
entryid = _parseId(entry)
comment_feed = None
num_comments = 0
try:
comment_feed = yt.GetYouTubeVideoCommentFeed(video_id=entryid)
num_comments = len(comment_feed.entry)
except Exception:
print 'no comments'
num_views = 0
try:
num_views = entry.statistics.view_count
except Exception:
print 'no views'
num_favs = 0
try:
num_favs = entry.statistics.favorite_count
except Exception:
print 'no fav'
title = entry.title.text
des = entry.media.description.text
des = des if des != None else ''
isPrimeMatch = prime_term in title
num_sec = 0
for term in sec_terms:
if term in title or term in des:
num_sec += 1
initial_score = \
ContentRetriever.computeInitialScore(isPicture=False, \
isPrimeMatch=isPrimeMatch, \
numSecond = num_sec, \
views=num_views, \
comments=num_comments, \
favs=num_favs)
return initial_score
def computePictureScore(pid, mood):
prime_term = getPrimeTerm(mood)
sec_terms = getSecTerm(mood)
photo = flickr.photos_getInfo(photo_id=pid)
attrib = photo[0].attrib
num_views = attrib['views']
num_favs = attrib['isfavorite']
comments = flickr.photos_comments_getList(photo_id=pid)
com = comments[0]
num_comments = len(com)
pic = photo[0]
num_sec = 0
isPrimeMatch = False
for tag in pic.find('tags'):
if tag.attrib['raw'] == prime_term:
isPrimeMatch = True
for sec_term in sec_terms:
if (sec_term == tag.attrib['raw']):
num_sec = num_sec + 1
initial_score = \
ContentRetriever.computeInitialScore(isPrimeMatch=isPrimeMatch,\
numSecond=num_sec, \
views=num_views, \
comments=num_comments, \
favs=num_favs)
'''print 'score = ' + str(initial_score) + \
', pm: ' + str(isPrimeMatch) + \
', sec: ' + str(num_sec) + \
', view: ' + str(num_views) + \
', com: ' + str(num_comments) + \
', fav: ' + str(num_favs) '''
return initial_score
def computePictureScore(pid, mood):
prime_term = getPrimeTerm(mood)
sec_terms = getSecTerm(mood)
photo = flickr.photos_getInfo(photo_id=pid)
attrib = photo[0].attrib
num_views = attrib['views']
num_favs = attrib['isfavorite']
comments = flickr.photos_comments_getList(photo_id=pid)
com = comments[0]
num_comments = len(com)
pic = photo[0]
num_sec = 0
isPrimeMatch = False
for tag in pic.find('tags'):
if tag.attrib['raw'] == prime_term:
isPrimeMatch = True
for sec_term in sec_terms:
if (sec_term == tag.attrib['raw']):
num_sec = num_sec + 1
initial_score = \
ContentRetriever.computeInitialScore(isPrimeMatch=isPrimeMatch,\
numSecond=num_sec, \
views=num_views, \
comments=num_comments, \
favs=num_favs)
'''print 'score = ' + str(initial_score) + \
', pm: ' + str(isPrimeMatch) + \
', sec: ' + str(num_sec) + \
', view: ' + str(num_views) + \
', com: ' + str(num_comments) + \
', fav: ' + str(num_favs) '''
return initial_score
