import tweepy as tw
import pandas as pd
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
import twittercredentials
import re

auth = tw.OAuthHandler(twittercredentials.CONSUMER_KEY, twittercredentials.CONSUMER_SECRET)
auth.set_access_token(twittercredentials.ACCESS_TOKEN, twittercredentials.ACCESS_TOKEN_SECRET)
api = tw.API(auth, wait_on_rate_limit=True)


search_word = 'cybertruck'
date_since = "2019-10-20"

tweets = tw.Cursor(api.search, q=search_word, lang="en", tweet_mode='extended', since=date_since).items(50)
# geomethods = tw.Cursor(api.reverse_geocode).items(50)

text_file = open('tweets.txt', 'w')
# text_file.write(tweets)


for i in tweets:
    a = {}
    # b = []
    a['Tweet'] = i.full_text
    a['Location'] = i.user.location
    # a.update({'Tweet': i.full_text})
    print(a)
    text_file.write(str(a))
    text_file.write("\n")
    # b.append([i.full_text, i.user.location])
    # b.append("\n")
    # print(a)
    # text_file.write(str(b))
    # text_file.write("\n")

# print(a)
# df = pd.read_table('tweets.txt')
# print(df)
# print(a)
    # print(i.full_text)
    # print(i.coordinates)
    # print(i.user.location)
    # text_file.write(i.full_text)
    # text_file.write(i.user.location)



# text_file.close()