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import dateutil.parser
d1 = '2008-09-03T20:56:35.450686Z'
d2 = dateutil.parser.parse(d1)
d3 = d2.astimezone(dateutil.tz.tzutc())

s = 'Fri, 09 Dec 2011 13:50:20 +0000'
import dateutil.parser
d = dateutil.parser.parse(s)

>>> d

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from pymongo import Connection

import datetime

import time

#connect to mongodb

connection = Connection(‘newitfarmer.com’, 27017)

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# http://stackoverflow.com/questions/748324/python-convert-those-tinyurl-bit-ly-tinyurl-ow-ly-to-full-urls

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

# urllib2
import urllib2
fp = urllib2.urlopen('http://bit.ly/rgCbf')
fp.geturl()

# ==> 'http://webdesignledger.com/freebies/the-best-social-media-icons-all-in-one-place'

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given a text file containing stopwords, return a python list of its contents.
this list is optimized for twitter/social media and filters out stuff
like RT, nowplaying,  lastfm, 4sq etc.


def get_stopwords(file='stopwords.txt'):
        words = open(file,'r')
        stopwords = [word.strip() for word in words]
	return set(stopwords) 

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"""
tiny script to convert a pandas data frame into a JSON object
"""

import ujson as json
import pandas
import numpy as np

df = pandas.DataFrame({
    "time" : [1,2,3,4,5],

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# a messy hack written by Edd Dumbill. http://twitter.com/edd

# You may need to rerun this script if you hit a Twitter Error because you
# use up API rate limiting. That's why we pickle the results, so we can resume
# where we left off.

# get the twitter module using 'easy_install twitter'

from twitter.api import Twitter, TwitterError
from twitter.oauth import OAuth

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import numpy as np, numpy.linalg as linalg
def fast_svd(M, k):
    p = k+5
    Y = np.dot(M, np.random.normal(size=(M.shape[1],p)))
    Q,r = linalg.qr(Y)
    B = np.dot(Q.T,M)
    Uhat, s, v = linalg.svd(B, full_matrices=False)
    U = np.dot(Q, Uhat)
    return U.T[:k].T, s[:k], v[:k]