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Download a McGraw Hill Education eTextbook

If you purchase a textbook from McGraw Hill, the website to view it is clunky and only works on some devices. You can't go to specific page numbers, the search is super slow, etc. That's why I wrote this script to download the textbook as an ePub file for your own viewing.

Using this script is 100% legal. McGraw Hill publicly hosts their ebooks online in order for their web client to download it. Moreover, to use it, you must already have purchased the book you would like to download, so it is legally yours to use as you please. However, it IS illegal to use this for piracy purposes. DO NOT DISTRIBUTE ANY TEXTBOOKS YOU DOWNLOAD USING THIS SCRIPT.

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import dash
from dash.dependencies import Input, Output
import dash_core_components as dcc
import dash_html_components as html

from pandas_datareader import data as web
from datetime import datetime as dt

app = dash.Dash('Hello World')

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import dash
import dash_core_components as dcc
import dash_html_components as html
import plotly.graph_objs as go
import pandas as pd

app = dash.Dash()

df = pd.read_csv(
    'https://gist.githubusercontent.com/chriddyp/'

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import sys
import random
import time
from threading import *

class Producer(Thread):
	def __init__(self, items, can_produce, can_consume):
		Thread.__init__(self)
		self.items = items
		self.can_produce = can_produce

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/****************************************
 * Include Libraries
 ****************************************/
 
#include <PubSubClient.h>
#include <ESP8266WiFi.h>
#include <ESP8266WiFiMulti.h>
#include <stdio.h>  

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from gensim.models import Word2Vec

# Load pretrained model (since intermediate data is not included, the model cannot be refined with additional data)
model = Word2Vec.load_word2vec_format('GoogleNews-vectors-negative300.bin', binary=True, norm_only=True)

dog = model['dog']
print(dog.shape)
print(dog[:10])

# Deal with an out of dictionary word: Михаил (Michail)

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# -*- coding: utf-8 -*-
import json
import re
import os
import nltk

input_file = open('<JSON FILE To INPUT>','r').readlines()
for line in input_file:   
    try:
        tweet = json.loads(line)