Created
May 14, 2020 02:17
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Fetch data using get_status() method based on tweetids
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__author__ = "Aditi Deokar" | |
import time | |
import pandas as pd | |
import tweepy | |
import os | |
from tweepy import OAuthHandler | |
# authorize the app to access Twitter Streaming API | |
access_token = "ENTER YOUR ACCESS TOKEN" | |
access_token_secret = "ENTER YOUR ACCESS TOKEN SECRET" | |
consumer_key = "ENTER YOUR CONSUMER KEY" | |
consumer_secret = "ENTER YOUR CONSUMER KEY SECRET" | |
auth = OAuthHandler(consumer_key, consumer_secret) | |
auth.set_access_token(access_token, access_token_secret) | |
api = tweepy.API(auth,wait_on_rate_limit=True,wait_on_rate_limit_notify=True) | |
#List of column names | |
COLS = ['id', 'created_at','tweet_type','source','text', 'screen_name', 'favorite_count', | |
'retweet_count', 'hashtags', | |
'mentions', 'media'] | |
#path where extracted tweet links containing tweet ids are stored | |
path=r"D:\sns_scraper_tweet_recovery\\tweet_ids" | |
#path to store tweet information fetched on the basis of tweet ids passed | |
extracted_tweets_path=r"D:\sns_scraper_tweet_recovery\\fetched_tweets" | |
directory = os.listdir(path) | |
for file in directory: | |
screenname=file.split('-')[-1] #To take out screenname from the filename eg. twitter-SpeakerPelosi | |
entry = [] | |
fh = open(os.path.join(path, file),'r') | |
for line in fh: | |
tweet_id=line.split('/')[-1].strip() #Split the Link to grab the tweet_id only eg. https://twitter.com/SpeakerPelosi/status/1259647243797368833 | |
tweet = api.get_status(id=int(tweet_id), tweet_mode="extended") | |
time.sleep(5) | |
if str(tweet.created_at).split(' ')[0]>'2019-12-17': | |
try: | |
hashtags=tweet.entities['hashtags'][0]['text'] | |
except: | |
hashtags=None | |
try: | |
user_mentions=tweet.entities['user_mentions'][0]['screen_name'] | |
except: | |
user_mentions=None | |
try: | |
media=tweet.entities['media'][0]['media_url'] | |
except: | |
media=None | |
entry.append([tweet.id,tweet.created_at,'tweet',tweet.source,tweet.full_text,tweet.user.screen_name,tweet.favorite_count, tweet.retweet_count,hashtags,user_mentions,media]) | |
print(len(entry),screenname) | |
df = pd.DataFrame(entry,columns=COLS) | |
df.to_csv(extracted_tweets_path+'\\'+screenname+"_tweets.csv", mode='a+', columns=COLS, index=False, | |
encoding="utf-8") |
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