Tweep's Favorute Spotify Podcast.py

#import the required libraries

import pandas as pd
import numpy as np
import requests
import re
import csv
import itertools

BEARER_TOKEN = "Bearer Token"

#extract replies using the Twitter recent search endpoint
#We'll be extracting the first 100 replies first

url = 'https://api.twitter.com/2/tweets/search/recent?query=conversation_id:1380199354850373633&expansions=author_id&max_results=100'
resp = requests.get(url, headers= {'Authorization': 'Bearer ' + BEARER_TOKEN
                                     })
data = resp.json()['data']
token = resp.json()['meta']['next_token']

#extracting the other replies
while resp.json()['meta']['next_token']:
    url = 'https://api.twitter.com/2/tweets/search/recent?query=conversation_id:1380199354850373633&expansions=author_id&max_results=100&next_token={}'.format(token)
    resp = requests.get(url, headers= {'Authorization': 'Bearer ' + BEARER_TOKEN
                                 })
    try:
        token = resp.json()['meta']['next_token']
        page_data = resp.json()['data']
        data.append(page_data)
    except:
        print("there are no more replies")
  
#The other batch of replies extracted are list of lists, so we
#need to convert them into a single list

new_data = list(itertools.chain.from_iterable(data[100:]))

replies = []

for profile in new_data:
    tweet = profile['text']
    
    replies.append(tweet)

for profiles in data[0:99]:
    tweets = profiles['text']
    
    replies.append(tweets) 
    
#extract mentions from the tweets

def clean_tweet(tweet):
    tweet = re.sub('@spotifypodcasts', "", tweet)
    tweet = re.sub('@Spotify', "", tweet)
    tweet = re.findall("[@]\S+", tweet)
    return tweet

reply = []
for tweets in replies:
    tweet = clean_tweet(tweets)
    reply.append(tweet)
    
reply = list(itertools.chain.from_iterable(reply))
reply = pd.Series(reply)
replies = reply.value_counts()
replies.to_csv('spotify_replies.csv')