@author: v-beshi
"""
from sklearn.decomposition import IncrementalPCA
from sklearn.neural_network import MLPClassifier
import pandas as pd
from sklearn.externals import joblib
import time
import pandas as pd
import bfx
import huobi_USDT
import wallstreet_news
from okex2 import OKCoinFuture as ok
from preprocessing import d_pro
mykey=ok('www.okex.com','Public-Key','Private-Key')
def test_data(tt):
pca=joblib.load('pca.m')
next5=joblib.load('next5.m')
next10=joblib.load('next10.m')
next15=joblib.load('next15.m')
i=0
while i<=tt:
try:
DateTime=time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
ok0330=float(mykey.future_ticker('btc_usd','quarter')['ticker']['last'])
ok_thisweek=float(mykey.future_ticker('btc_usd','this_week')['ticker']['last'])
bfx_bids_wall=float(bfx.bfx_books()['bids_wall'])
bfx_asks_wall=float(bfx.bfx_books()['asks_wall'])
bfx_total_bids=float(bfx.bfx_books()['total_bids'])
@author: v-beshi
"""
import sys
import requests
import json
import time
import pandas as pd
import bfx
import huobi_USDT
import wallstreet_news
from okex2 import OKCoinFuture as ok
import pyodbc
import traceback
mykey = ok('www.okex.com', 'fabec789-4981-46b7-8155-db0730f6157e',
'A1C6A6937573B675B519A789C1E77C97')
#replace the Public-Key and Private-Key with your OKex API access
#con=pyodbc.connect('DRIVER={SQL Server};SERVER=server;DATABASE=db;UID=id;PWD=password')
con = pyodbc.connect(
'DSN=MYAMAZONSQL;UID=lucaskingjade;DATABASE=PythonTestDB;PWD=wq891216',
autocommit=True)
#connect to SQL Server Database
def input_data(tt):
#input the number of rows you want to input
j = 0
for i in range(0, tt):
#count number of rows
try:
ok0330 = float(