I noticed that using the below code, I cannot retrieve the long tweet; somehow it got cut. Can anyone suggest a way to retrieve the full tweet message?
tweets = []
#for month in range(8,13,1):
for i,j in zip(start_time,end_time):
print(i)
print(j)
for response in tweepy.Paginator(client.search_all_tweets,
query = 'สมอง -is:retweet lang:th',
user_fields = ['username', 'public_metrics', 'description', 'location'],
tweet_fields = ['created_at', 'geo', 'public_metrics', 'text'],
expansions = ['author_id', 'geo.place_id'],
start_time = i,
end_time = j):
#max_results=500):
time.sleep(1)
tweets.append(response)
I'm unable to reproduce your snippet since I don't have the credentials but can you try something like this:
import tweepy
client = tweepy.Client("paste your token")
query = 'สมอง -is:retweet lang:th'
tweets = tweepy.Paginator(client.search_recent_tweets, query=query,
user_fields = ['username', 'public_metrics', 'description', 'location'],
tweet_fields=['created_at', 'geo', 'public_metrics', 'text'],
max_results=100).flatten(limit=1000)
for tweet in tweets:
print(tweet.text) ## this should give you the full tweet
Please note to change the respective search method (search_all_tweets). I couldn't use it since it was asking for credentials for v2. You can also get rid of the flatten if you don't want only the data part of your tweet.
Related
I am using the Twitter Academic Research V2 API and want to get tweets from a list of users and store them in a dataframe.
My code works for one single user, but not for a list of users. See the code here:
import tweepy
from twitter_authentication import bearer_token
import time
import pandas as pd
import time
client = tweepy.Client(bearer_token, wait_on_rate_limit=True)
# list of twitter users
csu = ["Markus_Soeder", "DoroBaer", "andreasscheuer"]
csu_tweets = []
for politician in csu:
for response in tweepy.Paginator(client.search_all_tweets,
query = f'from:{politician} -is:retweet lang:de',
user_fields = ['username', 'public_metrics', 'description', 'location'],
tweet_fields = ['created_at', 'geo', 'public_metrics', 'text'],
expansions = 'author_id',
start_time = '2022-12-01T00:00:00Z',
end_time = '2022-12-03T00:00:00Z'):
time.sleep(1)
csu_tweets.append(response)
end = time.time()
print(f"Scraping of {csu} needed {(end - start)/60} minutes.")
result = []
user_dict = {}
# Loop through each response object
for response in csu_tweets:
# Take all of the users, and put them into a dictionary of dictionaries with the info we want to keep
for user in response.includes['users']:
user_dict[user.id] = {'username': user.username,
'followers': user.public_metrics['followers_count'],
'tweets': user.public_metrics['tweet_count'],
'description': user.description,
'location': user.location
}
for tweet in response.data:
# For each tweet, find the author's information
author_info = user_dict[tweet.author_id]
# Put all of the information we want to keep in a single dictionary for each tweet
result.append({'author_id': tweet.author_id,
'username': author_info['username'],
'author_followers': author_info['followers'],
'author_tweets': author_info['tweets'],
'author_description': author_info['description'],
'author_location': author_info['location'],
'text': tweet.text,
'created_at': tweet.created_at,
'quote_count': tweet.public_metrics['quote_count'],
'retweets': tweet.public_metrics['retweet_count'],
'replies': tweet.public_metrics['reply_count'],
'likes': tweet.public_metrics['like_count'],
})
# Change this list of dictionaries into a dataframe
df = pd.DataFrame(result)
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_25716/2249018491.py in <module>
4 for response in csu_tweets:
5 # Take all of the users, and put them into a dictionary of dictionaries with the info we want to keep
----> 6 for user in response.includes['users']:
7 user_dict[user.id] = {'username': user.username,
8 'followers': user.public_metrics['followers_count'],
KeyError: 'users'
So I get this KeyError: 'users'. I don't get the error if I just scrape tweet from a single user and replace "csu = ["Markus_Soeder", "DoroBaer", "andreasscheuer"] with "csu = "Markus_Soeder".
Does anyone know what could be the issue?
Thanks in advance!
I found the answer to this issue. It gave me the key error, because for some users in this time range there were no tweets and as a result it got stored as "none" in the response. Because of this the for loop didn't work.
I am trying to use the Tweepy python package to get the actual replies to a Tweet. I break down the process I have worked on so far:
I import my modules and configure authentication variables with tweepy:
client = tweepy.Client(bearer_token=bearer_token, wait_on_rate_limit=True)
covid_tweets = []
for mytweets in tweepy.Paginator(client.search_all_tweets, query = '#COVID lang:en',
user_fields=['username', 'public_metrics', 'description', 'location'], tweet_fields
= ['created_at', 'geo', 'public_metrics', 'text'], expansions = 'author_id',
start_time = '2019-12-30T00:00:00Z', end_time = '2020-01-15T00:00:00Z',
max_results=10):
time.sleep(2)
covid_tweets.append(mytweets)
I then search for the hashtags I want and the parameters of the Tweepy Paginator with a for loop and append unto an empty list:
client = tweepy.Client(bearer_token=bearer_token, wait_on_rate_limit=True)
covid_tweets = []
for mytweets in tweepy.Paginator(client.search_all_tweets, query = '#COVID lang:en',
user_fields=['username', 'public_metrics', 'description', 'location'], tweet_fields
= ['created_at', 'geo', 'public_metrics', 'text'], expansions = 'author_id',
start_time = '2019-12-30T00:00:00Z', end_time = '2020-01-15T00:00:00Z',
max_results=10):
time.sleep(2)
covid_tweets.append(mytweets)
Then I convert this list into a dataFrame by extracting certain key fields[a user dictionary, user_object]:
#Convert Covid-19 tweets to a DF
result = []
user_dict = {}
# Loop through each response object
for response in covid_tweets:
for user in response.includes['users']:
user_dict[user.id] = {'username': user.username,
'followers': user.public_metrics['followers_count'],
'tweets': user.public_metrics['tweet_count'],
'description': user.description,
'location': user.location
}
for tweet in response.data:
# For each tweet, find the author's information
author_info = user_dict[tweet.author_id]
#check for condition
if ('RT #' not in tweet.text):
# Put all information we want to keep in a single dictionary for each tweet
result.append({'author_id': tweet.author_id,
'tweet_id': tweet.id,
'username': author_info['username'],
'author_followers': author_info['followers'],
'author_tweets': author_info['tweets'],
'author_description': author_info['description'],
'author_location': author_info['location'],
'text': tweet.text,
'created_at': tweet.created_at,
'retweets': tweet.public_metrics['retweet_count'],
'replies': tweet.public_metrics['reply_count'],
'likes': tweet.public_metrics['like_count'],
'quote_count': tweet.public_metrics['quote_count']
})
# Change this list of dictionaries into a dataframe
df_1 = pd.DataFrame(result)
Now my issue is, from the dataFrame, I get to see tweets and reply_count for tweets and a proof of the image is shown below:
And I checked how I can get the replies from the tweets. So I did some checks and wanted to follow this code flow function:
def get_all_replies(tweet, api, fout, depth=10, Verbose=False):
global rep
if depth < 1:
if Verbose:
print('Max depth reached')
return
user = tweet.user.screen_name
tweet_id = tweet.id
search_query = '#' + user
# filter out retweets
retweet_filter = '-filter:retweets'
query = search_query + retweet_filter
try:
myCursor = tweepy.Cursor(api.search_tweets, q=query,
since_id=tweet_id,
max_id=None,
tweet_mode='extended').items()
rep = [reply for reply in myCursor if reply.in_reply_to_status_id == tweet_id]
except tweepy.TweepyException as e:
sys.stderr.write(('Error get_all_replies: {}\n').format(e))
time.sleep(60)
if len(rep) != 0:
if Verbose:
if hasattr(tweet, 'full_text'):
print('Saving replies to: %s' % tweet.full_text)
elif hasattr(tweet, 'text'):
print('Saving replies to: %s' % tweet.text)
print("Output path: %s" % fout)
# save to file
with open(fout, 'a+') as (f):
for reply in rep:
data_to_file = json.dumps(reply._json)
f.write(data_to_file + '\n')
# recursive call
get_all_replies(reply, api, fout, depth=depth - 1, Verbose=False)
return
So basically, with this function, I loop through the dataframe and pick the "tweet_id" & "the screen_name" for the tweet, then design a search query but I realized at the section of the "rep" list returns an empty list, and debugging line by line, actually showed that the in_reply_to_status_id is different from the tweet_id and the cause for the empty list even though the reply count for the dataframe shows a non-zero.
I know this is long but I really wanted to show what I have done so far and explain each process. Thank you
NB: I have access to Academic Research API
Ok so for everyone trying to fix this hurdle I finally found a way to get the tweet replies. In my use case, I have the Academic Research API from Twitter.
The code provided by geduldig on his github Github finally solved my
issue with a little tweaks. A little head-up will be that, with the TwitterAPI package, if you ignore the "start_time" or "end_time" parameter, you might get only the parent tweet, so structure it like this:
pager = TwitterPager(api, 'tweets/search/all',
{
'query':f'conversation_id:{CONVERSATION_ID}',
'start_time': '2019-12-30T00:00:00Z',
'end_time': '2021-12-31T00:00:00Z',
'expansions':'author_id',
'tweet.fields':'author_id,conversation_id,created_at,referenced_tweets'
},
hydrate_type=HydrateType.REPLACE)
I hope this helps the community. Thanks.
I'm trying to scrape tweets from specific users using tweepy. But instead of giving me the tweets from the user I specify, tweepy returns my own timeline tweets. What am I doing wrong?
tweets = []
def username_tweets_to_csv(username,count):
try:
tweets = tweepy.Cursor(api.user_timeline,user_id=username).items(count)
tweets_list = [[tweet.created_at, tweet.id, tweet.text] for tweet in tweets]
tweets_df = pd.DataFrame(tweets_list,columns=['Datetime', 'Tweet Id', 'Text'])
tweets_df.to_csv('/Users/Carla/Documents/CODE_local/{}-tweets.csv'.format(username), sep=',', index = False)
except BaseException as e:
print('failed on_status,',str(e))
time.sleep(3)
username = "jack"
count = 100
username_tweets_to_csv(username, count)
I was just able to fix it by exchanging the "user_id" parameter for "screen_name". Works perfectly now!
tweets = tweepy.Cursor(api.user_timeline,screen_name=username).items(count)
I have been working on this for hours and need some help. This mostly works. I am able to connect to Twitter, pull the json data and store it in MongoDB however not all the data that I am seeing in my 'print(tweet)' line is showing up in MongoDB. Specifically I didn't see the screen_name (or name or the matter) field. I really just need these fields: "id", "text", "created_at", "screen_name", "retweet_count", "favourites_count", "lang" and I get them all but the name. I am not sure why it is not being inserted in the DB with all the other fields. Any help would be greatly appreciated!
from twython import Twython
from pymongo import MongoClient
ConsumerKey = "XXXXX"
ConsumerSecret = "XXXXX"
AccessToken = "XXXXX-XXXXX"
AccessTokenSecret = "XXXXX"
twitter = Twython(ConsumerKey,
ConsumerSecret,
AccessToken,
AccessTokenSecret)
result = twitter.search(q="drexel", count='100')
result1 = result['statuses']
for tweet in result1:
print(tweet) #prints tweets so I know I got data
client = MongoClient('mongodb://localhost:27017/')
db = client.twitterdb
tweet_collection = db.twitter_search
#Fields I need ["id", "text", "created_at", "screen_name", "retweet_count", "favourites_count", "lang"]
for tweet in result1:
try:
tweet_collection.insert(tweet)
except:
pass
print("The number of tweets in English: ")
print(tweet_collection.count(lang="en"))
You can use following way:
def get_document(post):
return {
'id': post['id_str'],
'text': post['text'],
'created_at': post['created_at'],
'retweet_count' : post['retweet_count'],
'favourites_count': post['user']['favourites_count'],
'lang': post['lang'],
'screen_name': post['user']['screen_name']
}
for tweet in result1:
try:
tweet_collection.insert(
get_document(tweet)
)
except:
pass
It should work.
The "screen_name" field is a subset of the "user" part of the tweet metadata. Make sure you're drilling down far enough.
This is driving me crazy. As you can see below I am trying to use a simple while loop to perform a couple of tweepy searches and append them into a data frame. For some reason however after pulling the first set of 100 tweets it just repeats that set instead of performing a new search. Any advice would be greatly appreciated.
import sys
import csv
import pandas as pd
import tweepy
from tweepy import OAuthHandler
consumer_key = ''
consumer_secret = ''
access_token = ''
access_secret = ''
auth = OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_secret)
api = tweepy.API(auth)
num_results = 200
result_count = 0
last_id = None
df = pd.DataFrame(columns=['Name', 'Location', 'Followers', 'Text', 'Coorinates'])
while result_count < num_results:
result = api.search(q='',count=100, geocode= "38.996918,-104.995826,190mi", since_id = last_id)
for tweet in result:
user = tweet.user
last_id = tweet.id_str
name = user.name
friends = user.friends_count
followers = user.followers_count
text = tweet.text.encode('utf-8')
location = user.location
coordinates = tweet.coordinates
df.loc[result_count] = pd.Series({'Name':name, 'Location':location, 'Followers':followers, 'Text':text, 'Coordinates':coordinates})
print(text)
result_count += 1
# Save to Excel
print("Writing all tables to Excel...")
df.to_csv('out.csv')
print("Excel Export Complete.")
The API.search method returns tweets that match a specified query. It's not a Streaming APi, so it returns all data at once.
Furthermore, in your query parameters, you have added count, that specifies the number of statuses to retrieve.
So the problem is that with your query you are returning the first 100 data of the complete set for each while iteration.
I suggest you to change the code in something like this
result = api.search(q='', geocode= "38.996918,-104.995826,190mi", since_id = last_id)
for tweet in result:
user = tweet.user
last_id = tweet.id_str
name = user.name
friends = user.friends_count
followers = user.followers_count
text = tweet.text.encode('utf-8')
location = user.location
coordinates = tweet.coordinates
df.loc[result_count] = pd.Series({'Name':name, 'Location':location, 'Followers':followers, 'Text':text, 'Coordinates':coordinates})
print(text)
Let me know.