def postEvents(robot_data, firebase_url, tags_list):
from firebase import firebase
firebase = firebase.FirebaseApplication(firebase_url, None)
createUser(robot_data, firebase_url)
month = 5
nameSet = []
for day in range(16, 17):
url = 'https://events.cornell.edu/calendar/day/2016/%s/%s' % (
str(month), str(day))
date = 20160000 + month * 100 + day
retrievedData = EventsCollector.retieveEventsAtDate(date, url)
for i in range(len(retrievedData)):
tmp = retrievedData[i]
if tmp['title'] in nameSet:
continue
nameSet.append(tmp['title'])
event_data = {}
event_data['authorName'] = robot_data['username']
event_data['authorProfileImg'] = robot_data['usrProfileImage']
event_data['startingTime'] = tmp['time'][0]
event_data['endingTime'] = tmp['time'][1]
event_data['imageOfEvent'] = [str([tmp['image']][0])]
event_data['introOfEvent'] = tmp['description']
event_data['latOfEvent'] = tmp['lat']
event_data['lngOfEvent'] = tmp['lng']
event_data['locationOfEvent'] = tmp['location']
event_data['nameOfEvent'] = tmp['title']
event_data['numberOfViewed'] = 0
import datetime
now = datetime.datetime.now()
post_time = now.date().year * 10000 + now.date(
).month * 100 + now.date().day
post_time = post_time * 10000 + now.time().hour * 100 + now.time(
).minute
event_data['postTime'] = post_time
event_data['restriction'] = ""
event_data['secondaryTag'] = tmp['secondaryTag']
text = tmp['title'] + "\n" + tmp['location'] + "\n" + tmp[
'description']
event_data['primaryTag'] = KeywordsClassifier.classify(text)
post_event = firebase.post('/events', event_data)
print 'posted:', event_data
print "DONE"
print "\n"
print "\n"
print "\n"
def postEvents(robot_data, firebase_url, tags_list):
from firebase import firebase
firebase = firebase.FirebaseApplication(firebase_url, None)
createUser(robot_data, firebase_url)
month = 5
nameSet = []
for day in range(16, 17):
url = 'https://events.cornell.edu/calendar/day/2016/%s/%s' % (str(month), str(day))
date = 20160000 + month*100 + day
retrievedData = EventsCollector.retieveEventsAtDate(date, url)
for i in range(len(retrievedData)):
tmp = retrievedData[i]
if tmp['title'] in nameSet:
continue
nameSet.append(tmp['title'])
event_data = {}
event_data['authorName'] = robot_data['username']
event_data['authorProfileImg'] = robot_data['usrProfileImage']
event_data['startingTime'] = tmp['time'][0]
event_data['endingTime'] = tmp['time'][1]
event_data['imageOfEvent'] = [str([tmp['image']][0])]
event_data['introOfEvent'] = tmp['description']
event_data['latOfEvent'] = tmp['lat']
event_data['lngOfEvent'] = tmp['lng']
event_data['locationOfEvent'] = tmp['location']
event_data['nameOfEvent'] = tmp['title']
event_data['numberOfViewed'] = 0
import datetime
now = datetime.datetime.now()
post_time = now.date().year * 10000 + now.date().month * 100 + now.date().day
post_time = post_time * 10000 + now.time().hour * 100 + now.time().minute
event_data['postTime'] = post_time
event_data['restriction'] = ""
event_data['secondaryTag'] = tmp['secondaryTag']
text = tmp['title'] + "\n" + tmp['location'] + "\n" + tmp['description']
event_data['primaryTag'] = KeywordsClassifier.classify(text)
post_event = firebase.post('/events', event_data)
print 'posted:', event_data
print "DONE"
print "\n"
print "\n"
print "\n"
tags_list = ["Professional Events", "Social Events", "Performance Events",
"Political Events", "Seminars", "Athletics"]
# Store events with their description into a file,
# as the data set to build our classifier.
if __name__ == '__main__':
import EventsCollector
output_file = open('text', 'w')
title_list = []
for i in range(1, 16):
url = 'https://events.cornell.edu/calendar/day/2016/4/' + str(i)
date = 20160600 + i
retrievedData = EventsCollector.retieveEventsAtDate(date, url)
for i in range(len(retrievedData)):
event = retrievedData[i]
# avoid redundent training data.
if event['title'] in title_list:
continue
title_list.append(event['title'])
print "\n"
print "\n"
print "\n"
print event['title']
print "\n"
print event['location']
print "\n"
print event['description']
print "\n"
print "Please classify the class for the following events"
for i in range(len(tags_list)):
print "%d\t: %s" % (i, tags_list[i])
tags_list = [
"Professional Events", "Social Events", "Performance Events",
"Political Events", "Seminars", "Athletics"
]
# Store events with their description into a file,
# as the data set to build our classifier.
if __name__ == '__main__':
import EventsCollector
output_file = open('text', 'w')
title_list = []
for i in range(1, 16):
url = 'https://events.cornell.edu/calendar/day/2016/4/' + str(i)
date = 20160600 + i
retrievedData = EventsCollector.retieveEventsAtDate(date, url)
for i in range(len(retrievedData)):
event = retrievedData[i]
# avoid redundent training data.
if event['title'] in title_list:
continue
title_list.append(event['title'])
print "\n"
print "\n"
print "\n"
print event['title']
print "\n"
print event['location']
print "\n"
print event['description']
print "\n"
print "Please classify the class for the following events"
