from twitter import *
import time
import numpy as np
import pandas as pd
import datetime
import dateutil

#Keeping my api keys in a separate file.  Just put in your own here
from auth.auth_twitter import access_token, access_token_secret, consumer_key, consumer_secret


t = Twitter(auth=OAuth(access_token, access_token_secret, consumer_key, consumer_secret))

t.statuses.home_timeline()

help(twitter)

def get_age(birth_date):
    # Get the current date
    now = datetime.datetime.utcnow()
    now = now.date()

    # Get the difference between the current date and the birthday
    age = dateutil.relativedelta.relativedelta(now, birth_date)
    age = age.years

    return age

%pylab inline

vote_raw = pd.read_csv('makindo_data.csv', parse_dates=['birth_date'])

vote_raw['age'] = vote_raw.apply(lambda row: get_age(row['birth_date']), axis = 1)

vote_raw['age'].min()

vote_clean = vote_raw[['twitter_handle', 'party_affiliation', 'age']].copy()

(12*939)/60.0

vote_clean[1:2]

def get_tweets(username):
    try: 
        user_status = t.statuses.user_timeline(screen_name=username)
        time.sleep(12)
        return [x['text'] for x in user_status]
    except: 
        return ''

get_tweets('csheldon10')

for row in vote_clean.iterrows():
    print row[1][0]

tweets_list = [{row[1][1]:get_tweets(row[1][0])} for row in vote_clean.iterrows()]

tweets_list

party_tweet_list = []
for user in tweets_list: 
    for key in user:
        for tweet in user[key]:
            item = [tweet, key]
            party_tweet_list.append(item)

party_tweet_list[88]

full_tweets = pd.DataFrame(party_tweet_list, columns=['tweet', 'party_affiliation'])

# vote_clean['tweets'] = vote_clean.apply(lambda row: 
#                                         get_tweets(row['twitter_handle']), axis=1)

full_tweets.to_csv('data/pulled_tweets.csv', encoding='utf8')