def tick(self):
#only call API once
try:
self.APIlist = FinexAPI.ticker()
except:
try:
time.sleep(10)
self.APIlist = FinexAPI.ticker()
except:
try:
time.sleep(10)
self.APIlist = FinexAPI.ticker()
except:
pass
#date
self.dataDate = datetime.datetime.fromtimestamp(
int(float(
self.APIlist["timestamp"]))).strftime('%Y-%m-%d %H:%M:%S')
#prices
self.currentPrice = float(self.APIlist["last_price"])
#insert into SQL db
self.TradeDatabase.insertStatement01(self.dataDate, self.currentPrice)
#load datelist, prices from db
self.datelist, self.prices = self.TradeDatabase.readtolist01()
#indicators
self.SMA = self.indicators.movingAverage(self.prices, 200)
self.CResistance = self.indicators.trendline(self.prices)
self.RSI = self.indicators.RSI(self.prices)
#macd indicators & insert into DB
if len(self.prices) > 26: #get macd indicators
emaslow, emafast, self.MACD = self.indicators.MACD(self.prices)
self.EMA9 = self.indicators.EMA(self.MACD, 9)
#Insert all to DB (no need for macd and ema9 - they are self generated and contained lists)
self.TradeDatabase.insertStatement02(self.dataDate, self.CResistance,
self.SMA, self.RSI)
#graph
#archaic : self.graphdataPoints.append({'date':self.dataDate, 'price': self.currentPrice, 'trend': self.CResistance, 'SMA': self.SMA, 'RSI':self.RSI, 'short': np.nan, 'long':np.nan,'closedLong':np.nan,'closedShort':np.nan})
#graph with pdDataFrame obj
self.graphdataPoints = self.TradeDatabase.frameit()
#if/else indicators
self.tradePlaced, self.typeOfTrade, self.cryptoAmount = self.TradeDatabase.readtolist02(
)
self.tradePlaced = [i for i in self.tradePlaced
if i * 0 == 0] #only get the numbers
self.typeOfTrade = [i for i in self.typeOfTrade
if i != None] #only get the strings
self.cryptoAmount = [i for i in self.cryptoAmount
if i * 0 == 0] #only get the numbers
#print timestamp and price to cmd line for logging purposes
self.output.log(self.dataDate + "\tPrice: " + str(self.currentPrice) +
"\tMoving Average: " + str(self.SMA))
#print numofwins, numofloses and cumulated profits to cmd line
self.cumulatedProfits, self.numofwins, self.numofloses = self.TradeDatabase.cumwinloss(
)
self.output.log(
"No. of Wins: {}, No. of Loses: {}, Cumulated Profits: {}".format(
self.numofwins, self.numofloses, self.cumulatedProfits))
#!/usr/bin/env python import FinexAPI print FinexAPI.ticker()
#!/usr/bin/env python
#Places a put and take above and below current market price
import FinexAPI
diff = 2 #The amount above or below market price you want
ticker = FinexAPI.ticker()
available = float(FinexAPI.balances()[2]["available"])
ask = float(ticker["ask"])
amount = 0.01 #Amount of BTC to place orders
marketPrice = ticker["last_price"]
buyPrice = float(marketPrice) - diff
sellPrice = float(marketPrice) + diff
print FinexAPI.place_order(str(amount), str(buyPrice), "buy", "exchange limit")
print FinexAPI.place_order(str(amount), str(sellPrice), "sell",
"exchange limit")
#!/usr/bin/env python #Places a put and take above and below current market price import FinexAPI diff = 2 #The amount above or below market price you want ticker = FinexAPI.ticker() available = float(FinexAPI.balances()[2]["available"]) ask = float(ticker["ask"]) amount = 0.01 #Amount of BTC to place orders marketPrice = ticker["last_price"] buyPrice = float(marketPrice) - diff sellPrice = float(marketPrice) + diff print FinexAPI.place_order(str(amount), str(buyPrice), "buy", "exchange limit") print FinexAPI.place_order(str(amount), str(sellPrice), "sell", "exchange limit")
