python init | Python Fiddle

import twitter
import sys, os
import pandas as pd

'''important for reading JSON'''
from pprint import pprint

'''important for dealing with twitter rate limits'''
from time import localtime, strftime, sleep, time

'''
    Create a file to store your credentials
'''
cons_oauth_file = 'c.xxx'
# if file exists, get the credentials variables from the file
if os.path.exists(cons_oauth_file):
    constoken, conssecret = twitter.read_token_file(cons_oauth_file)
else:
    constoken = raw_input("What is your app's 'Consumer Key'?").strip()
    conssecret = raw_input("What is your app's 'Consumer Secret'?").strip()
    wf = open(cons_oauth_file, 'w');
    wf.write(constoken + '\n' + conssecret)

'''
    We we'll authorize this app through your Twitter account. 
    This code block will open a new tab, prompt to activate the app, 
    and provide you with a PIN to enter back here. 
    This OAuth registration is handled by the twitter.oauth_dance function.
'''
app_oauth_file = 'a.xxx'
# if user not already authorised
if not os.path.exists(app_oauth_file):
    # perform oAuth Dance
    twitter.oauth_dance("your app", constoken, conssecret, app_oauth_file)
# import user credentials
apptoken, appsecret = twitter.read_token_file(app_oauth_file)

'''
    Setting up an object that uses your credentials to access the Twitter REST API 
    and return structured Twitter data
'''
tsearch = twitter.Twitter(auth=twitter.OAuth(apptoken, appsecret, constoken, conssecret))

# Search Term
# Note: use + instead of spaces if needed
term = 'AdonisGeorgiadi -RT'

res = tsearch.search.tweets(q=term,
                            count=10,
                            result_type='recent')

pprint(res['statuses'][0])

print('\n')
print('\n')

def exctract_tweet_URL(j):
    '''
    Convert tweet information to url
    '''
    return 'http://twitter.com/' + j['user']['screen_name'] + '/status/' + str(j['id'])

t = res['statuses'][0]

print(exctract_tweet_URL(t))

print('\n')
print('\n')

def prunetweet(t):
    d = {k: t[k] for k in ['created_at','favorite_count','retweet_count','id','in_reply_to_status_id','text']}    #keeping only relevant top-level features (user features handled below)
    d['user'] = {k: t['user'][k] for k in ['id','location','friends_count','followers_count','name','screen_name']} #keeping only relevant features
    return d

pprint(prunetweet(t))

print('\n')
print('\n')

#################################################################################

'''
    New Search Terms
'''
term = "%22good+morning%22"
count = 25

res = tsearch.search.tweets(q=term, count=count, result_type='recent')

for i in range (0, len(res['statuses'])):
    print('\n', i, exctract_tweet_URL(res['statuses'][i]))
    pprint(prunetweet(res['statuses'][i]))

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