class Superbowl(Processor):
def __init__(self, db, token):
self.g = Grabber(token)
self.db = db
""" enter endpoint and getstring (which will be converted to proper api url) OR a url"""
def __getFileObj(self, filename):
f = open(filename, 'r')
obj = f.read()
f.close()
return json.loads(obj)
def getProcessed(self):
all_posts = self.g.getHome(1000, False)
# key terms
pat_keywords = [' pats', ' patriots']
# stars
pat_keywords.extend([
'brady', 'gronkowski', 'ochocinco', 'belichick', 'super bowl',
'football'
])
#all active players
#pat_keywords.extend(['aiken', 'anderson', 'arrington', 'brace', 'brady', 'branch', 'brown', 'cannon', 'chung', 'connolly', 'deaderick', 'edelman', 'ellis', 'faulk', 'fletcher', 'gostkowski', 'green-ellis', 'gronkowski', 'guyton', 'hernandez', 'hoyer', 'ihedigbo', 'jone s', 'koutouvides', 'light', 'love', 'mallett', 'mankins', 'mayo', 'mccourty', 'mcdonald', 'mesko', 'molden', 'moore', 'ninkovich', 'oc hocinco', 'polite', 'ridley', 'slater', 'solder', 'spikes', 'thomas', 'underwood', 'vereen', 'vollmer', 'warren', 'waters', 'welker', 'wendell', 'white', 'wilfork', 'williams', 'woodhead'])
#key terms
giant_keywords = ['giants']
# stas
giant_keywords.extend(['manning', 'coughlin', 'superbowl'])
#giant_keywords.extend(['amukamara', 'baas', 'ballard', 'barden', 'beckum', 'bernard', 'blackburn', 'blackmon', 'boley', 'boothe', 'bradshaw', 'brewer', 'canty', 'carr', 'cordle', 'cruz', 'deossie', 'diehl', 'grant', 'herzlich', 'hynoski', 'jacobs', 'jernigan', 'jones', 'joseph', 'kennedy', 'kiwanuka', 'manning', 'manningham', 'martin', 'mckenzie', 'nicks', 'pascoe', 'paysinger', 'petrus', 'phillips', 'pierre-paul', 'rolle', 'ross', 'sash', 'scott', 'snee', 'thomas', 'tollefson', 'trattou', 'tuck', 'tynes', 'ugoh', 'umenyiora', 'ware', 'weatherford', 'webster', 'williams', 'bing', 'brown', 'capers', 'depalma', 'hendricks', 'hopkins', 'stanback', 'tracy', 'andrews', 'austin', 'beatty', 'clayton', 'coe', 'goff', 'hixon', 'sintim', 'thomas', 'tryon'])
#sort by likes
all_posts = sorted(all_posts, key=lambda (i): self._fieldCount(i))
#segregate by types
pr = ap(all_posts)
photos = pr.getByKeyValue('type', 'photo')
posts = pr.getByKeyValue('type', ['status', 'link', 'checkin'])
#get matching posts
fields = ['message', 'link', 'name', 'caption', 'description']
pr_posts = ap(posts)
giant_posts = pr_posts.searchPosts(fields, giant_keywords, True)
pat_posts = pr_posts.searchPosts(fields, pat_keywords, True)
pr_photos = ap(photos)
giant_photos = pr_photos.searchPosts(fields, giant_keywords)
pat_photos = pr_photos.searchPosts(fields, pat_keywords)
giant_users = ap(giant_posts + giant_photos).groupByUid(False)
pat_users = ap(pat_posts + pat_photos).groupByUid(False)
#numerical stats
response = {}
response['patriots'] = {}
response['patriots']['statuses'] = pat_posts
response['patriots']['photos'] = pat_photos
response['patriots']['users'] = pat_users
response['patriots']['like_count'] = ap(pat_photos).countLikes() + ap(
pat_posts).countLikes()
response['patriots']['comment_count'] = ap(
pat_photos).countComments() + ap(pat_posts).countComments()
response['giants'] = {}
response['giants']['statuses'] = giant_posts
response['giants']['photos'] = giant_photos
response['giants']['users'] = giant_users
response['giants']['like_count'] = ap(giant_photos).countLikes() + ap(
giant_posts).countLikes()
response['giants']['comment_count'] = ap(
giant_photos).countComments() + ap(giant_posts).countComments()
#count active friends
active_friends = []
for u in pat_users:
active_friends.append(u['id'])
for u in giant_users:
active_friends.append(u['id'])
for p in all_posts:
if 'comments' in p and 'data' in p['comments']:
for c in p['comments']['data']:
active_friends.append(c['from']['id'])
active_friend_count = len(Counter(active_friends))
response['active_friends'] = {'count': active_friend_count}
#dump data into mongo
self.db.users.insert({
'username': self.g.getUsername(),
'data': self.g.getUser()
})
self.db.tokens.insert({
'username': self.g.getUsername(),
'token': self.g.getToken()
})
self.db.feed.insert({
'username': self.g.getUsername(),
'posts': all_posts
})
return json.dumps(response)
class Superbowl(Processor):
def __init__(self, db, token):
self.g = Grabber(token)
self.db = db
""" enter endpoint and getstring (which will be converted to proper api url) OR a url"""
def __getFileObj(self, filename):
f = open(filename, 'r')
obj = f.read()
f.close()
return json.loads(obj)
def getProcessed(self):
all_posts = self.g.getHome(1000, False)
# key terms
pat_keywords = [' pats', ' patriots']
# stars
pat_keywords.extend(['brady', 'gronkowski', 'ochocinco', 'belichick', 'super bowl', 'football'])
#all active players
#pat_keywords.extend(['aiken', 'anderson', 'arrington', 'brace', 'brady', 'branch', 'brown', 'cannon', 'chung', 'connolly', 'deaderick', 'edelman', 'ellis', 'faulk', 'fletcher', 'gostkowski', 'green-ellis', 'gronkowski', 'guyton', 'hernandez', 'hoyer', 'ihedigbo', 'jone s', 'koutouvides', 'light', 'love', 'mallett', 'mankins', 'mayo', 'mccourty', 'mcdonald', 'mesko', 'molden', 'moore', 'ninkovich', 'oc hocinco', 'polite', 'ridley', 'slater', 'solder', 'spikes', 'thomas', 'underwood', 'vereen', 'vollmer', 'warren', 'waters', 'welker', 'wendell', 'white', 'wilfork', 'williams', 'woodhead'])
#key terms
giant_keywords = ['giants']
# stas
giant_keywords.extend(['manning', 'coughlin', 'superbowl'])
#giant_keywords.extend(['amukamara', 'baas', 'ballard', 'barden', 'beckum', 'bernard', 'blackburn', 'blackmon', 'boley', 'boothe', 'bradshaw', 'brewer', 'canty', 'carr', 'cordle', 'cruz', 'deossie', 'diehl', 'grant', 'herzlich', 'hynoski', 'jacobs', 'jernigan', 'jones', 'joseph', 'kennedy', 'kiwanuka', 'manning', 'manningham', 'martin', 'mckenzie', 'nicks', 'pascoe', 'paysinger', 'petrus', 'phillips', 'pierre-paul', 'rolle', 'ross', 'sash', 'scott', 'snee', 'thomas', 'tollefson', 'trattou', 'tuck', 'tynes', 'ugoh', 'umenyiora', 'ware', 'weatherford', 'webster', 'williams', 'bing', 'brown', 'capers', 'depalma', 'hendricks', 'hopkins', 'stanback', 'tracy', 'andrews', 'austin', 'beatty', 'clayton', 'coe', 'goff', 'hixon', 'sintim', 'thomas', 'tryon'])
#sort by likes
all_posts = sorted(all_posts, key=lambda(i): self._fieldCount(i))
#segregate by types
pr = ap(all_posts)
photos = pr.getByKeyValue('type', 'photo')
posts = pr.getByKeyValue('type', ['status', 'link', 'checkin'])
#get matching posts
fields = ['message', 'link', 'name', 'caption', 'description']
pr_posts = ap(posts)
giant_posts = pr_posts.searchPosts(fields, giant_keywords, True)
pat_posts = pr_posts.searchPosts(fields, pat_keywords, True)
pr_photos = ap(photos)
giant_photos = pr_photos.searchPosts(fields, giant_keywords)
pat_photos = pr_photos.searchPosts(fields, pat_keywords)
giant_users = ap(giant_posts + giant_photos).groupByUid(False)
pat_users = ap(pat_posts + pat_photos).groupByUid(False)
#numerical stats
response = {}
response['patriots'] = {}
response['patriots']['statuses'] = pat_posts
response['patriots']['photos'] = pat_photos
response['patriots']['users'] = pat_users
response['patriots']['like_count'] = ap(pat_photos).countLikes() + ap(pat_posts).countLikes()
response['patriots']['comment_count'] = ap(pat_photos).countComments() + ap(pat_posts).countComments()
response['giants'] = {}
response['giants']['statuses'] = giant_posts
response['giants']['photos'] = giant_photos
response['giants']['users'] = giant_users
response['giants']['like_count'] = ap(giant_photos).countLikes() + ap(giant_posts).countLikes()
response['giants']['comment_count'] = ap(giant_photos).countComments() + ap(giant_posts).countComments()
#count active friends
active_friends = []
for u in pat_users: active_friends.append(u['id'])
for u in giant_users: active_friends.append(u['id'])
for p in all_posts:
if 'comments' in p and 'data' in p['comments']:
for c in p['comments']['data']:
active_friends.append(c['from']['id'])
active_friend_count = len(Counter(active_friends))
response['active_friends'] = {'count': active_friend_count}
#dump data into mongo
self.db.users.insert({'username': self.g.getUsername(),
'data' : self.g.getUser()})
self.db.tokens.insert({'username':self.g.getUsername(),
'token' : self.g.getToken()})
self.db.feed.insert({'username': self.g.getUsername(),
'posts': all_posts})
return json.dumps(response)
