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#!/usr/bin/python

# reference => http://www.puffinwarellc.com/index.php/news-and-articles/articles/33.html

from numpy import zeros
from scipy.linalg import svd
from math import log	# needed for TFIDF
from numpy import asarray, sum

titles = ["The Neatest Little Guide to Stock Market Investing",

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#!/usr/bin/python

# reference => http://glowingpython.blogspot.com/2011/10/perceptron.html

from pylab import rand,plot,show,norm

def generateData(n):
	"""
	generates a 2D linearly separable dataset with n samples, where the third element is the label
	"""

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#!/usr/bin/python
# http://en.wikipedia.org/wiki/Viterbi_algorithm

'''
Consider two friends, Alice and Bob, who live far apart from each other and who talk together daily over the telephone about what they did that day. Bob is only interested in three activities: walking in the park, shopping, and cleaning his apartment. The choice of what to do is determined exclusively by the weather on a given day. Alice has no definite information about the weather where Bob lives, but she knows general trends. Based on what Bob tells her he did each day, Alice tries to guess what the weather must have been like.
Alice believes that the weather operates as a discrete Markov chain. There are two states, "Rainy" and "Sunny", but she cannot observe them directly, that is, they are hidden from her. On each day, there is a certain chance that Bob will perform one of the following activities, depending on the weather: "walk", "shop", or "clean". Since Bob tells Alice about his activities, those are the observations. The entire

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f = open('filename.txt', 'r')

from BeautifulSoup import BeautifulSoup
soup = BeautifulSoup(f)
for tag in soup.findAll('a', href=True):
    print tag['href']

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import re
urls = re.findall(r'href=[\'"]?([^\'" >]+)', s)
print ', '.join(urls)

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#!/usr/bin/python
# -*- coding: utf-8 -*-

import httplib2, json

__links__ = (r'http://developer.klout.com/iodocs')

KLOUT_API_KEY = '' # required!

'''

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#!/usr/bin/env python
import pycurl, urllib, json, sys, httplib2

'''
curl -d 'track=google' https://stream.twitter.com/1/statuses/filter.json -uusername:password

http://dev.twitter.com/pages/streaming_api_methods
https://gist.github.com/1046726 
http://www.angryobjects.com/2011/10/15/http-with-python-pycurl-by-example/
'''

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#!/usr/bin/env python
# encoding: utf-8

__links__ = r'https://gist.github.com/916362'

import smtplib
from datetime import datetime
import email.utils
from email.mime.text import MIMEText

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from pymongo import Connection

import datetime

import time

#connect to mongodb

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

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# dropping a database via pymongo
from pymongo import Connection
c = Connection()
c.drop_database('mydatabase')

# drop a collection via pymongo
from pymongo import Connection
c = Connection()
c['mydatabase'].drop_collection('mycollection')