def collect_replies(self):
"""
Collect replies for all tweets from query using twarc
:return:
"""
twarc = Twarc(self.ak, self.aks, self.at, self.ats)
reply_count = 0
# loop through all parent tweets from query
for tweet in self.tweets:
replies = []
reps = twarc.replies(
self.tweepy_to_twarc(tweet),
recursive=False) # get iterator for replies from twarc
rep = next(
reps) # first "rep" is the parent tweet so we don't use it
i = 0
# max 30 replies
while i < 30:
try:
rep = next(reps) # get next reply and add it to list
replies.append(rep)
i = i + 1
except StopIteration:
break
except Exception as e:
print('error: ', e)
self.dict[tweet.id] = replies # add tweet to dict {id:replies}
reply_count += len(replies)
print(reply_count, ' replies were collected')
print(name)
file_name = r"C:\\Users\\ravik\\OneDrive\\Desktop\\UsertimelineReplies\\" + str(name) + ".json"
max_poi_tweet = 0
with open( file_name, "a", encoding='utf-8') as file:
for tweet in t.timeline(screen_name=name):
if 'retweeted_status' in tweet.keys():
print("Its a retweet")
continue
if max_poi_tweet > 3000:
break
json.dump(tweet, file, ensure_ascii=False)
file.write("\n")
max_poi_tweet +=1
max_replies = 0
if datetime.strptime(tweet['created_at'], "%a %b %d %H:%M:%S %z %Y").date() >= time_range:
for reply in t.replies(tweet):
#print("In")
#preprocessing(tweet, file)
if 'retweeted_status' in tweet.keys():
print("Its a retweet")
continue
else:
json.dump(reply, file, ensure_ascii=False)
file.write("\n")
max_replies +=1
print("{} tweet {} reply number {}".format(name, max_poi_tweet, max_replies))
if max_replies > 21:
break
else:
print("{} tweet {} Date didnt satisfy".format(name, max_poi_tweet))
#time.sleep(10)
def f(file):
print file
today = datetime.date.today()
margin = datetime.timedelta(days=7)
analyzer = SentimentIntensityAnalyzer()
acess_changer = [c8, c9, c10, c7, c1, c2, c3, c4]
# base_dir='/home/stealthuser/Perosnal/Sentimental/12 august/Data/Hamid output csvs/'
base_dir = c_p.input_csv_path
if os.path.exists(base_dir + 'reply/'):
output_dir = base_dir + 'reply/'
pass
else:
os.mkdir(base_dir + 'reply/')
output_dir = base_dir + 'reply/'
data = pd.read_csv(base_dir + file,
low_memory=False,
error_bad_lines=False)
data['reply'] = ''
reply = []
acess_changer_counter = 0
max_tweet = 35
config_key = 0
for index, tweet in enumerate(data['text']):
print file + " " + str(index)
t_id = data.ix[index, 'permalink'].split('/')[-1:][0]
tweet_date = data.ix[index, 'date'].split()[0]
if (acess_changer_counter % max_tweet == 0):
access_point = acess_changer[config_key % len(acess_changer)]
config_key += 1
t = Twarc(access_point.consumer_key, access_point.consumer_secret,
access_point.access_token,
access_point.access_token_secret)
acess_changer_counter += 1
print access_point
tweet_r = t.tweet(t_id)
if (len(tweet_r) > 0):
reply_tweets = []
req_format_date = tuple(
map(lambda x: int(x), tweet_date.split('-')))
if (today - margin <=
datetime.date(req_format_date[0], req_format_date[1],
req_format_date[2])):
for reply_tweet in t.replies(tweet_r):
reply.append(reply_tweet['text'].encode('utf-8'))
# print reply_tweet['text'].encode('utf-8')
reply_tweets.append(reply_tweet['text'].encode('utf-8'))
# delimiter for replies is '==<>=='
data.ix[index, 'reply'] = '==<>=='.join(reply_tweets)
df_reply_comment = pd.DataFrame({'replies': reply})
for index_comment, reply in enumerate(df_reply_comment['replies']):
score = analyzer.polarity_scores(str(reply))
df_reply_comment.ix[index_comment, 'positive'] = score['pos']
df_reply_comment.ix[index_comment, 'negative'] = score['neg']
df_reply_comment.ix[index_comment, 'neutral'] = score['neu']
df_reply_comment.ix[index_comment, 'compound'] = score['compound']
# df_reply_comment.to_csv(output_dir+file[:-4]+'_replies_sentiment.csv')
data.to_csv(output_dir + file[:-4] + '_comments.csv')
status, paths_reply_label = classification_tweet(df_reply_comment,
output_dir, file[:-4])
tweet_id = sys.argv[1]
# Main
t = Twarc(
consumer_key=consumer_key,
consumer_secret=consumer_secret,
access_token=access_token,
access_token_secret=access_token_secret,
)
tweet = t.tweet(tweet_id)
if not tweet:
raise RuntimeError(f"tweet with id {tweet_id} does not exist")
# replies is a generator object
replies = t.replies(tweet, True)
# List to hold dict of relevant photo data from each of the replies
photo_data = []
for reply in replies:
# Photos will be in a list stored at reply['extended_entities']['media']
print("Processing next reply")
ee = reply.get("extended_entities")
if ee is None:
continue
m = ee.get("media")
if m is None:
continue
