CODEWITHSUNDEEP
pythonpandastweepy
Mitchell.Laferla
Mitchell.Laferla

Reputation: 253

How to make multiple calls to Twitter API to get more than 200 Tweets per user using Tweepy?

I have some Python code here that retrieves a max limit of 200 Tweets from each of the USA Democratic political candidates' Twitter accounts. Although, I have it set to no replies and no Retweets, so it's actually returning much less. I know that you can return 200 Tweets max per call though you can make multiple calls, specifically 180, in a 15-minute window which would return many more Tweets. My question is how to go about making multiple calls while still returning the data in the pandas df format that I have set up currently. Thanks!

import datetime as dt
import os
import pandas as pd
import tweepy as tw

#define developer's permissions
consumer_key = 'xxxxxxxx'
consumer_secret = 'xxxxxxxx'
access_token = 'xxxxxx'
access_token_secret = 'xxxxxxx'

#access twitter's API
auth = tw.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_token_secret)
api = tw.API(auth, wait_on_rate_limit=True)
#function collects tweets from 
def get_tweets(handle):
    try:
        tweets = api.user_timeline(screen_name=handle, 
                                   count=200,
                                   exclude_replies=True, 
                                   include_rts=False,
                                  tweet_mode="extended")
        print(handle, "Number of tweets extracted: {}\n".format(len(tweets)))
        df = pd.DataFrame(data=[tweet.user.screen_name for tweet in tweets], columns=['handle'])
        df['tweets'] = np.array([tweet.full_text for tweet in tweets])
        df['date'] = np.array([tweet.created_at for tweet in tweets])
        df['len'] = np.array([len(tweet.full_text) for tweet in tweets])
        df['like_count'] = np.array([tweet.favorite_count for tweet in tweets])
        df['rt_count'] = np.array([tweet.retweet_count for tweet in tweets])
    except:
        pass
    return df

#list of all the candidate twitter handles
handles = ['@JoeBiden', '@ewarren', '@BernieSanders', '@MikeBloomberg', '@PeteButtigieg', '@AndrewYang', '@AmyKlobuchar']
df = pd.DataFrame()
​
#loop through the diffent candidate twitter handles and collect each candidates tweets
for handle in handles:
    df_new = get_tweets(handle)
    df = pd.concat((df, df_new))

@JoeBiden Number of tweets extracted: 200.

@ewarren Number of tweets extracted: 200.

@BernieSanders Number of tweets extracted: 200.

@MikeBloomberg Number of tweets extracted: 200.

@PeteButtigieg Number of tweets extracted: 200.

@AndrewYang Number of tweets extracted: 200.

@AmyKlobuchar Number of tweets extracted: 200.

Upvotes: 2

Views: 924

Answers (2)

Punnerud
Punnerud

Reputation: 8071

The Twitter API documentation explain why you get a lower result:

exclude_replies - "This parameter will prevent replies from appearing in the returned timeline. Using exclude_replies with the count parameter will mean you will receive up-to count tweets — this is because the count parameter retrieves that many Tweets before filtering out retweets and replies."

Upvotes: 0

Harmon758
Harmon758

Reputation: 5157

First of all, you're going to want to regenerate your credentials now.

You can iterate through paginated results with a Cursor or by passing the since_id and/or max_id parameters for API.user_timeline.

See also the documentation for the GET statuses/user_timeline endpoint.

Upvotes: 1

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