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from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.naive_bayes import MultinomialNB
from sklearn.pipeline import Pipeline
from NLTKPreprocessor import NLTKPreprocessor
import os
import json

PATH = "new.model"

model = Pipeline([

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[
  {
    "text": "How would you describe yourself?",
    "intentName": "personal-bio"
  },
  {
    "text": "When is your birthday?",
    "intentName": "personal-birthday"
  },
  {

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var colors = {
1:"#ff1123",
2:"#000000",
3:"#010101"
}

function getRandomInt(min, max) {
    return Math.floor(Math.random() * (max - min + 1)) + min;
}

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/*
 * This is a version of Facebook's React Conditional Rendering
 * example modified to support firebase authentication.
 * https://facebook.github.io/react/docs/conditional-rendering.html
 */

import React, { Component, PropTypes } from 'react';
import * as firebase from 'firebase';

function UserAvatar(props) {

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import logging
import logging.handlers
import time

logging.basicConfig(level=logging.DEBUG,
    format='%(asctime)s %(levelname)-8s %(message)s')

logging.getLogger().addHandler(logging.handlers.DatagramHandler('localhost', 8045))

while True:

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import pymongo
import sys

connection = pymongo.Connection("mongodb://localhost", safe=True)

db=connection.nooora
coll = db.nooracollection

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Michael, 29
Andy, 30
Justin, 19
Arun, 20
Alfred, 22

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Imports iTextSharp.text.pdf
Imports iTextSharp.text
Imports System.IO
Imports iTextSharp.text.io
Imports System.Drawing
Imports System.Drawing.Imaging
Imports System
Imports System.Collections.Generic
Imports System.Windows.Forms

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[
  {
    "currencycode": "Afghani",
    "code": "AFN"
  },
  {
    "currencycode": "Euro",
    "code": "EUR"
  },
  {

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from dictalchemy import make_class_dictable
from flask import Flask, request, jsonify, json
from flask_sqlalchemy import SQLAlchemy
from jsonpatch import JsonPatch, JsonPatchException

app = Flask(__name__)
app.debug = True
db = SQLAlchemy(app)
make_class_dictable(db.Model)