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def alertonlow():

    """ This Program uses the Binance API to Send Text Alerts for Price Action. Right now it's set up to
    send a Text Alert, when any Crypto Coin is Less than or Equal to 2% of the 24HR Low  """

    from binance.client import Client
    from twilio.rest import Client as twilioclient

    twilioclientsid = '' # Twilio User ID
    twilioclienttok = '' # Twilio User Token

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import re
from nltk.corpus import stopwords

Small = {
    'zero': 0,
    'one': 1,
    'two': 2,
    'three': 3,
    'four': 4,

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from textblob import TextBlob

text = """TextBlob aims to provide access to common text-processing operations through a familiar interface. /
You can treat TextBlob objects as if they were Python strengs that learned how to do Natural Language Processing."""
#"This is bad " = Sentiment Sentiment(polarity=-0.6999999999999998, subjectivity=0.6666666666666666)
#"This is Good" = Sentiment Sentiment(polarity=0.7, subjectivity=0.6000000000000001)


blob = TextBlob(text)

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def google_vision():

    import io
    import os
    from google.cloud import vision
    from google.cloud.vision import types

    #https://cloud.google.com/vision/docs/auth
    os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "Path to Application default credentials JSON ADC"

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def cryptoprices(pair):

    from poloniex import Poloniex

    apiKey = ""
    secret = ""
    polo = Poloniex(apiKey, secret)
    market_data = polo.returnTicker()[pair]
    bid = market_data["highestBid"]

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"""
This function combines data from Pandas data on stocks, and the Yahoo Finance API
"""
def stockhistory(stock2check):
    import pandas_datareader.data as web
    import datetime
    from yahoo_finance import Share

    stock = Share(stock2check)
    ylp = stock.get_year_low() # Returns the Year Low price for the stock

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import pandas as pd
import io
import requests
import time


def google_stocks(symbol, startdate=(1, 1, 2005), enddate=None):
    startdate = str(startdate[0]) + '+' + str(startdate[1]) + '+' + str(startdate[2])

    if not enddate:

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def stocktrack(stock,buysell,qty):
    import sqlite3
    from yahoo_finance import Share

    conn = sqlite3.connect('Stocks.db')
    c = conn.cursor()

    c.execute('''CREATE TABLE IF NOT EXISTS stocks
    (date text, trans text, symbol text, qty real, price real, total real)''')

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from lxml import html
import csv, os, json
import requests
#from exceptions import ValueError
from time import sleep


def AmzonParser(url):
    headers = {
        'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/42.0.2311.90 Safari/537.36'}

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import _mssql
# Connect to the SQL Server Database
conn = _mssql.connect(server='Servernamehere', user='serverusername', password='serverpassword', \
    database='databasename')

# Run The Select Query against the Database
conn.execute_query('SELECT TOP 10 [Item ID],[Custom Label],[Quantity Available] FROM [bsusa_active_staging]')


# Create the Lists