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// jQuery snippet for changing HTML form into JSON
	 (function ($) {

		 $.fn.serializeFormJSON = function () {
			 var o = {};
			 var a = this.serializeArray();
			 $.each(a, function () {
				 if (o[this.name]) {
					 if 	(!o[this.name].push) { o[this.name] = [o[this.name]]; }

mzmmoazam

class Graph:
  def __init__(self):
    self.nodes = set()
    self.edges = defaultdict(list)
    self.distances = {}

  def add_node(self, value):
    self.nodes.add(value)

  def add_edge(self, from_node, to_node, distance):

mzmmoazam

import sqlite3

class database(object):
    def __init__(self):
        self.filename = "help.db"
        self.table = "help_data"
        self.sql_do('create table if not exists '+self.table+' ( key TEXT,data TEXT)')
    def sql_do(self, sql, *params):
        self._db.execute(sql, params)
        self._db.commit()

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#!/usr/bin/python

import psycopg2

class database(object):
    def __init__(self,database,table):
        self.database = database
        self.table = table
        self.sql_do('create table if not exists '+self.table+' ( key TEXT,data TEXT)')
    def sql_do(self, sql, *params):

mzmmoazam

import requests
from urllib.parse import urlparse,urljoin
from bs4 import BeautifulSoup

all_urls = set()

class url_tree():
    def __init__(self, base_url,page_no=1 ,children=None):
        self.url = base_url
        self.page_no =page_no

mzmmoazam

import gym
import random
import numpy as np
import tflearn
from tflearn.layers.core import input_data, dropout, fully_connected
from tflearn.data_utils import to_categorical
from tflearn.layers.estimator import regression
from statistics import median, mean
from collections import Counter
import glob

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import speech_recognition as sr, pyttsx
from googletrans import Translator

# pyttsx engine config
speech_engine = pyttsx.init('sapi5')  # see http://pyttsx.readthedocs.org/en/latest/engine.html#pyttsx.init
speech_engine.setProperty('rate', 150)


# translator object
translator = Translator()

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import Algorithmia, speech_recognition as sr, pyttsx

# Algorthmia Api key and end point
client = Algorithmia.client('simCM+BqJzKSw/iMrQsR/OTRwVE1')
algo = client.algo('translation/GoogleTranslate/0.1.1')

# pyttsx engine config
speech_engine = pyttsx.init('sapi5')  # see http://pyttsx.readthedocs.org/en/latest/engine.html#pyttsx.init
speech_engine.setProperty('rate', 150)

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import csv, random


class NaiveBayes(object):
    def __init__(self, filename, split_ratio):
        '''

        :param filename: a csv filename with absolute or full path
        :param split_ratio: test to train ratio
        '''

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