#!/usr/bin/env python
'''
@file pick_best_model.py
@date Mon 04 Mar 2013 12:16:53 AM EST
@author Roman Sinayev
@email roman.sinayev@gmail.com
@detail
Here we attempt to pick the best model for classification of okc data.
The model is later used in results_small.py to predict some personal attributes.
'''

import lxml
import requests
from pandas import read_csv
import numpy as np
from collections import defaultdict
from sklearn.linear_model import SGDClassifier,Perceptron,LogisticRegression,LinearRegression
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.svm import LinearSVC
from sklearn.naive_bayes import MultinomialNB
import cPickle as pickle
from time import time
import sys
from pprint import pprint

CSVLOCATION="~/" #pandas dataframe with scraped data from okcupid

class OkProfile:
    def __init__(self, username):
        self.essays = ''
        self.username = username
    def scrape(self):
        r = requests.get('http://www.okcupid.com/profile/%s' % self.username)