index.py

from twython import Twython
import pandas as pd

TTL_TWEETS = 10000

consumer_key="4Y0swuxyRoDNZNWjboh5FI1OP"
consumer_secret="WKbjpokMp9ds3Yg2GwDo69AKeX704ywm2BOLVcR8ieGOri9fWG"
access_token_key="1186727191888957441-piNS1GzpeDw5Mmbjc8w0HzWiSJr2sX"
access_token_secret="LgXyWMbtti2FNnNa1sZrPTIcfPb4sj1azs9vUbJXJQipr"

def find_handle(mentions):
    #Search if mentions of the tweet contain any name of the below
    names = ["Russell Wilson", "Patrick Mahomes", "Lamar Jackson", "Christian McCaffery", "Deshaun Watson", "Michael Thomas"] 
    handles = ["DangeRussWilson", "PatrickMahomes", "Lj_era8", "run__cmc", "deshaunwatson", "Cantguardmike"]
    handle = name = None

    for mention in mentions:
        if mention['screen_name'] in handles:
            handle = mention['screen_name']

    if handle is not None:
        name = names[handles.index(handle)]

    return [handle, name]


def fetch_tweets():
    # Get tweets paginated. 100 per request 
    api = Twython(consumer_key, consumer_secret, access_token_key, access_token_secret)

    tweets = []
    oldest_id = 0
    res = api.search(q='twitter', result_type='recent', count=100)

    while len(tweets) < TTL_TWEETS:
        for tweet in res['statuses']:
            oldest_tweet = tweet['id']

            tweet_list = [tweet['user']['id'], tweet['text']]
            tweet_list.extend(find_handle(tweet['entities']['user_mentions']))
            tweets.append(tweet_list)

        res = api.search(q='twitter', result_type='recent', count=100, max_id=str(oldest_id))

    print("Fetched tweets: " + str(len(tweets)))

    return tweets

def tweets_to_dataframe(tweets):
    # Add all tweets to a dataframe
    columns = ['Tweeter', 'Tweet_Text', 'Player_Handle', 'Player']
    return pd.DataFrame(tweets, columns=columns)

def main():
    tweets = fetch_tweets()
    dataframe = tweets_to_dataframe(tweets)
    print(dataframe)

main()