def build_word_cloud(params):
tokens = ast.literal_eval(params.tokens)
hash_tag = params.hash_tag
try:
api = SMAuth.tweepy_auth(tokens['consumer_key'], tokens['consumer_secret'], tokens['access_token'], tokens['access_token_secret'])
data_ = Tw.hashtag_search(api, hash_tag)
wc_data = json.loads(wc.wordcloud_json(data_))
data = cmg.format_response(True,wc_data,'Data successfully processed!')
except ValueError, err:
data = cmg.format_response(False,err,'Error validating access token: This may be because the user logged out or may be due to a system error.',sys.exc_info())
def sentiment_analysis(params):
try:
tokens = ast.literal_eval(params.token)
except ValueError:
tokens = params.token
source = str(params.source)
try:
limit = params.limit
except AttributeError:
limit = ''
try:
since = params.since
except AttributeError:
since = ''
try:
until = params.until
except AttributeError:
until = ''
try:
post_ids = ast.literal_eval(params.post_ids)
except AttributeError:
post_ids = None
page = 'me'
try:
page = str(params.page)
except AttributeError:
pass
try:
hash_tag = str(params.hash_tag)
except AttributeError:
hash_tag = ''
#analyzed_data = 'Incorrect datasource name provided!'
if source == 'twitter':
api = SMAuth.tweepy_auth(tokens['consumer_key'], tokens['consumer_secret'], tokens['access_token'], tokens['access_token_secret'])
data_ = Tw.hashtag_search(api,hash_tag)
#lsi.initialize_stream(hash_tag, unique_id, tokens) # if already exits do something
#analyzed_data = smlf.process_social_media_data(unique_id, hash_tag)
data = sa.sentiment(data_)
result = cmg.format_response(True,data,'Data successfully processed!')
return result
elif source == 'facebook':
try:
data = FB.get_page_posts_comments(tokens, limit, since, until, page, post_ids)
except ValueError, err:
data = cmg.format_response(False,err,'Error validating access token: This may be because the user logged out or may be due to a system error.',sys.exc_info())
return data
#full_comment = []
analyzed_data = []
def _calculate_sentiment(post_id, comment_string):
full_comment_str = ''
for j in filtered_comments:
for comment in j['comments']:
full_comment_str += ' '
full_comment_str += comment['message'].encode('UTF8')
logger.debug(full_comment_str)
data_ = sa.sentiment(full_comment_str)
full_comment_str = ''
data_['post_id'] = post_id
analyzed_data.append(data_)
threads = []
if post_ids is not None:
for post_id in post_ids:
filtered_comments = filter(lambda d: d['post_id'] in post_id, data)
t = threading.Thread(target=_calculate_sentiment, args=(post_id, filtered_comments))
t.start()
print "Thread started to calculate sentiment analysis for post_id: {0}".format(post_id)
threads.append(t)
#full_comment_str.join(full_comment)
#analysed_data = sa.sentiment(full_comment_str.join(filtered_comments))
for t in threads:
try:
t.join()
except Exception, err:
print err
data = cmg.format_response(True,analyzed_data,'Data successfully processed!')
return data