<SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
 Fetch Tweets by Tweet ID
NOTE
Step1:  First we import the libraries we'll be using.
Step2:  Setup Twitter Access
You can find the OAuth credentials needed below in Twitter's application manager. Create a new app if you haven't already. After the app has been created, you'll find the necessary information under "Keys and Access Tokens". You may need to create access tokens.
Step3:  Setup Local Paths
Paths on your machine to the CSV file, and the file you'd like to output into.
Example csv, Mac
Step4:  Handle HTTP Errors
This is from Matthew A. Russell's brilliant "Mining the Social Web, 2nd Edition (O'Reilly, 2013)"
Step5:  Get Tweets and Write to File
Open the read and write files, get Status objects from read id's, write JSON objects to output file.
<ASSISTANT_TASK:>
Python Code:
from IPython.core.display import HTML
styles = open("../css/custom.css", "r").read()
HTML(styles)
Explanation: Fetch Tweets by Tweet ID
NOTE: You must have Python Twitter Tools installed on the machine to run this script. You can install it by running the below cell (change the cell type in the toolbar above to Code instead of Raw NBConvert). You may need to use "! sudo easy_install twitter".
Jupyter Notebook Style
End of explanation
from twitter import *
import csv, json
import cPickle as pickle
Explanation: First we import the libraries we'll be using.
End of explanation
# Twitter OAuth Credentials
consumer_key = '' # Consumer Key (API Key)
consumer_secret = '' # Consumer Secret (API Secret)
access_token = '' # Access Token
access_secret = '' # Access Token Secret
t = Twitter(auth=OAuth(access_token, access_secret, consumer_key, consumer_secret))
Explanation: Setup Twitter Access
You can find the OAuth credentials needed below in Twitter's application manager. Create a new app if you haven't already. After the app has been created, you'll find the necessary information under "Keys and Access Tokens". You may need to create access tokens.
End of explanation
csvpath = '' # Path to the csv file with Tweet IDs (up to 100 IDs per line)
jsonpath = '' # Path to the JSON file where retrieved tweets go
picklepath = '' # Path to the pickle file where retrieved tweets go
Explanation: Setup Local Paths
Paths on your machine to the CSV file, and the file you'd like to output into.
Example csv, Mac: /Users/[username]/Documents/twitter-analysis/data/src/TweetIDs.csv
Example pickle, Mac: /Users/[username]/Documents/twitter-analysis/data/raw/tweets.p
End of explanation
import sys
import time
from urllib2 import URLError
from httplib import BadStatusLine
def make_twitter_request(t_func, max_errors=10, *args, **kw): 
    
    # A nested helper function that handles common HTTPErrors. Return an updated
    # value for wait_period if the problem is a 500 level error. Block until the
    # rate limit is reset if it's a rate limiting issue (429 error). Returns None
    # for 401 and 404 errors, which requires special handling by the caller.
    def handle_twitter_http_error(e, wait_period=2, sleep_when_rate_limited=True):
    
        if wait_period > 3600: # Seconds
            print >> sys.stderr, 'Too many retries. Quitting.'
            raise e
    
        # See https://dev.twitter.com/docs/error-codes-responses for common codes
    
        if e.e.code == 401:
            print >> sys.stderr, 'Encountered 401 Error (Not Authorized)'
            return None
        elif e.e.code == 404:
            print >> sys.stderr, 'Encountered 404 Error (Not Found)'
            return None
        elif e.e.code == 429: 
            print >> sys.stderr, 'Encountered 429 Error (Rate Limit Exceeded)'
            if sleep_when_rate_limited:
                print >> sys.stderr, "Retrying in 15 minutes...ZzZ..."
                sys.stderr.flush()
                time.sleep(60*15 + 5)
                print >> sys.stderr, '...ZzZ...Awake now and trying again.'
                return 2
            else:
                raise e # Caller must handle the rate limiting issue
        elif e.e.code in (500, 502, 503, 504):
            print >> sys.stderr, 'Encountered %i Error. Retrying in %i seconds' % \
                (e.e.code, wait_period)
            time.sleep(wait_period)
            wait_period *= 1.5
            return wait_period
        else:
            raise e
    # End of nested helper function
    
    wait_period = 2 
    error_count = 0 
    while True:
        try:
            return t_func(*args, **kw)
        except api.TwitterHTTPError, e:
            error_count = 0 
            wait_period = handle_twitter_http_error(e, wait_period)
            if wait_period is None:
                return
        except URLError, e:
            error_count += 1
            time.sleep(wait_period)
            wait_period *= 1.5
            print >> sys.stderr, 'URLError encountered. Continuing.'
            if error_count > max_errors:
                print >> sys.stderr, 'Too many consecutive errors...bailing out.'
                raise
        except BadStatusLine, e:
            error_count += 1
            time.sleep(wait_period)
            wait_period *= 1.5
            print >> sys.stderr, 'BadStatusLine encountered. Continuing.'
            if error_count > max_errors:
                print >> sys.stderr, 'Too many consecutive errors...bailing out.'
                raise
Explanation: Handle HTTP Errors
This is from Matthew A. Russell's brilliant "Mining the Social Web, 2nd Edition (O'Reilly, 2013)"
End of explanation
with open(csvpath, 'rb') as csvfile: #Get ready to read Tweet ID file
    with open(jsonpath, 'wb') as tweetsfile: #Get ready to write to output file
        tweetreader = csvfile.readlines()
        tweets = []
        for row in tweetreader:
            try:
                data = make_twitter_request(t.statuses.lookup,_id=row) #Get each row of tweets including deleted ones
                for status in data:
                    tweets.append(status)
                    json.dump(tweets, tweetsfile) #Write each tweet
                    pickle.dump(tweets, open(picklepath, 'wb' ) )
            except: #Should something not work (blank line, only deleted tweets in line)
                pass
print('We have %d tweets in total' % len(tweets))
Explanation: Get Tweets and Write to File
Open the read and write files, get Status objects from read id's, write JSON objects to output file.
End of explanation
<END_TASK>