class BotChart(object):
#------------------------------------------------------------ ------#
#---------Part 1.1: Fetch the data from market---------------------#
#------------------------------------------------------------------#
#---Output: self.data=[Botcandlstck1 ,Botcandlestick2, ..3, ..4]---#
#------------------------------------------------------------------#
#------------------------------------------------------------------#
def __init__(self,
exchange,
pair,
period,
startTime,
endTime,
backtest=True):
self.botHTML = BotHTML()
self.vars = botVariables()
self.api_key = self.vars.api_key_poloniex
self.api_secret = self.vars.api_secret_poloniex
self.avPeriod = self.vars.movingAvPeriod
self.indicators = BotIndicators()
self.pair = pair
self.period = period
self.startTime = startTime
self.endTime = endTime
self.data = []
self.prices = []
self.poloData = []
self.trades = []
if (exchange == "poloniex"):
print('Ecxhange with Poloniex')
self.conn = poloniex.Poloniex(self.api_key, self.api_secret)
if backtest:
print("Checking the data from " +
datetime.datetime.fromtimestamp(int(startTime)).strftime(
'%Y-%m-%d %H:%M:%S') + " to " +
datetime.datetime.fromtimestamp(int(endTime)).strftime(
'%Y-%m-%d %H:%M:%S'))
self.poloData = self.conn.returnChartData(
self.pair, self.period, self.startTime, self.endTime)
#A:poloData is an list (checked with the funtion type(), where each item of the list contains 6 values of the period
for datum in self.poloData:
#datum is a dict = {key1:value1, key2:value2, ... }
if (datum['open'] and datum['close'] and datum['high']
and datum['low']):
#putting all this data to the BotCandlestick object
self.data.append(
BotCandlestick(self.period, datum['open'],
datum['close'], datum['high'],
datum['low'],
datum['weightedAverage'],
datum['date']))
if (exchange == "binance"):
# Remember to install binance python script with --> pip install python-binance
print('Ecxhange with Binance')
if backtest:
# create the Binance client, no need for api key
client = Client("", "")
klines = client.get_historical_klines(
self.vars.pairBinance,
getattr(client, self.vars.periodBinance),
self.vars.startTimeBinance, self.vars.endTimeBinance)
for kline in klines:
self.data.append(
BotCandlestick(
self.period, kline[1], kline[4], kline[2],
kline[3],
str((float(kline[1]) + float(kline[2]) +
float(kline[4]) + float(kline[3])) / 4),
int(((kline[0]) + (kline[6])) /
2000))) #because in miliseconds
"""
Get Historical Klines from Binance
[
[
1499040000000, // 0.Open time 1517803200000
"0.01634790", // 1.Open
"0.80000000", // 2.High
"0.01575800", // 3.Low
"0.01577100", // 4.Close
"148976.11427815", // 5.Volume
1499644799999, // 6.Close time
"2434.19055334", // 7.Quote asset volume
308, // 8.Number of trades
"1756.87402397", // 9.Taker buy base asset volume
"28.46694368", // 10.Taker buy quote asset volume
"17928899.62484339" // Ignore.
]
]
"""
# d = self.data[0].__dict__
# print (d)
#------------------------------------------------------------------#
#---------END--Part 1.1: initialisating the bot strategy-----------#
#------------------------------------------------------------------#
#--------------------------------------------------------------#
#---------Part 1.3: Evaluating each candlestic from the chart--#
#--------------------------------------------------------------#
#--------------------USING THE STRATEGY TICK-------------------#
#--------------------------------------------------------------#
def getPoints(self):
return self.data
def getCurrentPrice(self):
currentValues = self.conn.api_query("returnTicker")
lastPairPrice = {}
lastPairPrice = currentValues[self.pair]["last"]
return lastPairPrice
def getLastPrices(self, date, dataCandlestick, period):
lastPrices = []
#https://stackoverflow.com/a/3940144/5176549
for candlestick in reversed(dataCandlestick):
lastPrices.append(candlestick['weightedAverage'])
if date == (candlestick['date']):
break
return lastPrices[-period:]
def createChart(self):
historicalData = self.data
dataPoints = []
priceData = []
label = 'null'
output = open("output.html", 'w')
output.truncate()
#Understanding googlechart: https://developers.google.com/chart/interactive/docs/basic_load_libs
output.write(self.botHTML.begin)
while True:
#step 0: iterating over data points
if (self.startTime and historicalData):
nextDataPoint = historicalData.pop(
0) #https://stackoverflow.com/a/4426727/5176549
lastPairPrice = nextDataPoint.priceAverage
priceData.append(float(lastPairPrice))
movingAverage = self.indicators.movingAverage(
priceData, self.vars.movingAvPeriod, lastPairPrice)
movingAverage2 = self.indicators.movingAverage(
priceData, self.vars.movingAvPeriod2, lastPairPrice)
label = nextDataPoint.label
dataDate = datetime.datetime.fromtimestamp(
int(nextDataPoint.date)).strftime('%Y-%m-%d %H:%M:%S')
#adding the trades on the label
#step 2: once the iteration is finished, adding all the info in the chart
elif (self.startTime and not historicalData):
print("Finished")
for point in dataPoints:
output.write("[" + self.stringToDate(point['date']) + "," +
point['price'] + "," + point['label'] + "," +
point['desc'] + "," + point['movAv1'] + "," +
point['movAv2'])
output.write("],\n")
output.write(self.botHTML.end)
break
#step 1: addind the last point on the list
else:
currentValues = conn.api_query("returnTicker")
lastPairPrice = currentValues[pair]["last"]
dataDate = datetime.datetime.now()
#Main step: appending values to local dataPoints
dataPoints.append({
'date': dataDate,
'price': str(lastPairPrice),
'movAv1': str(movingAverage),
'movAv2': str(movingAverage2),
'label': label,
'desc': 'null'
})
def stringToDate(self, date):
#date is the follwing format: date='2017-12-27 11:50:00'
return "new Date(" + date[0:4] + ", " + date[5:7] + ", " + date[
8:10] + ", " + date[11:13] + ", " + date[14:16] + ")"
def creatChartRSI(self):
#Double Chart zoom: https://stackoverflow.com/a/42238747/5176549 or https://jsfiddle.net/pzamu7kt/
#Understanding googlechart: https://developers.google.com/chart/interactive/docs/basic_load_libs
historicalData = self.data
dataPoints = []
priceData = []
movingAverage = 0
label = 'null'
output = open("outputrsi.html", 'w')
output.truncate()
#Understanding googlechart: https://developers.google.com/chart/interactive/docs/basic_load_libs
output.write(self.botHTML.javascript)
while True:
#step 0: iterating over data points
if (self.startTime and historicalData):
nextDataPoint = historicalData.pop(0)
#https://stackoverflow.com/a/4426727/5176549
lastPairPrice = nextDataPoint.priceAverage
priceData.append(float(lastPairPrice))
BollUp = self.indicators.BollUp(priceData,
self.vars.BollPeriod,
lastPairPrice)
BollDown = self.indicators.BollDown(priceData,
self.vars.BollPeriod,
lastPairPrice)
rsiData = self.indicators.RSI(priceData)
label = nextDataPoint.label
dataDate = datetime.datetime.fromtimestamp(
int(nextDataPoint.date)).strftime('%Y-%m-%d %H:%M:%S')
#adding the trades on the label
#step 2: once the iteration is finished, adding all the info in the chart
elif (self.startTime and not historicalData):
output.write(self.botHTML.chart11)
for point in dataPoints:
output.write("[" + self.stringToDate(point['date']) + "," +
point['price'] + "," + point['label'] + "," +
point['desc'] + "," + point['BollUp'] + "," +
point['BollDown'])
output.write("],\n")
output.write(self.botHTML.chart12)
output.write(self.botHTML.chart21)
for point in dataPoints:
output.write("[" + self.stringToDate(point['date']) + "," +
point['rsi'])
output.write("],\n")
output.write(self.botHTML.chart22)
output.write(self.botHTML.endjavascript)
break
#step 1: addind the last point on the list
else:
currentValues = conn.api_query("returnTicker")
lastPairPrice = currentValues[pair]["last"]
dataDate = datetime.datetime.now()
#Main step: appending values to local dataPoints
dataPoints.append({
'date': dataDate,
'price': str(lastPairPrice),
'BollUp': str(BollUp),
'BollDown': str(BollDown),
'rsi': str(rsiData),
'label': label,
'desc': 'null'
})
class BotStrategy(object):
#--------------------------------------------------------------#
#---------Part 1.2: initialisating the bot strategy------------#
#--------------------------------------------------------------#
def __init__(self):
self.vars = botVariables()
self.investement = self.vars.initialInvestment
self.makeFee = self.vars.makeFee
self.takeFee = self.vars.takeFee
self.output = BotLog()
self.prices = []
self.closes = [] # Needed for Momentum Indicator
self.trades = []
self.numOfTrades = 0
self.currentPrice = ""
self.currentTime = ""
self.currentClose = ""
self.numSimulTrades = 1
self.indicators = BotIndicators()
self.absMargin = 0
self.relMargin = 0
#these are the values of the indicators qat each endTime
self.SMA1 = 0
self.SMA2 = 0
self.EMA1 = 0
self.EMA2 = 0
self.RSI = 0
self.BollUp = 0
self.BollDown = 0
#--------------------------------------------------------------#
#---END:--Part 1.2: initialisating the bot strategy------------#
#--------------------------------------------------------------#
#--------------------------------------------------------------#
#---------Part 1.3: Evaluating each candlestic from the chart--#
#--------------------------------------------------------------#
#--------------------USING THE STRATEGY TICK-------------------#
#--------------------------------------------------------------#
def tick(
self, candlestick
): #where a candlestick is a an item of the list BotChart.getPoints
self.currentPrice = float(candlestick.priceAverage)
self.currentTime = candlestick.date
self.prices.append(self.currentPrice)
#self.currentClose = float(candlestick['close'])
#self.closes.append(self.currentClose)
#self.output.log(datetime.datetime.fromtimestamp(self.currentTime).strftime('%Y-%m-%d %H:%M:%S')+" - Price: "+str(candlestick.priceAverage)+"\tMoving Average: "+str(self.indicators.movingAverage(self.prices,self.vars.movingAvPeriod,self.currentPrice)))
self.evaluatePositions(candlestick)
self.updateOpenTrades(candlestick)
self.showPositions()
def evaluatePositions(self, candlestic):
openTrades = []
self.SMA1 = self.indicators.movingAverage(self.prices,
self.vars.movingAvPeriod,
self.currentPrice)
self.SMA2 = self.indicators.movingAverage(self.prices,
self.vars.movingAvPeriod2,
self.currentPrice)
self.EMA1 = self.indicators.EMA(self.prices, self.vars.movingAvPeriod,
self.currentPrice)
self.EMA2 = self.indicators.EMA(self.prices, self.vars.movingAvPeriod2,
self.currentPrice)
self.RSI = self.indicators.RSI(self.prices)
self.BollUp = self.indicators.BollUp(self.prices, self.vars.BollPeriod,
self.currentPrice)
self.BollDown = self.indicators.BollDown(self.prices,
self.vars.BollPeriod,
self.currentPrice)
for trade in self.trades:
if (trade.status == "OPEN"):
openTrades.append(trade)
if (len(openTrades) < self.numSimulTrades):
#--------------------------------------------------------------#
#------Part 1.3.A: Adding a trade if the conditions are met----#
#--------------------------------------------------------------#
if self.strategy1(True):
#self.output.log("Trade Opened. Currentprice: "+str(self.currentPrice)+", MovAverage: "+str(self.indicators.movingAverage(self.prices,self.vars.movingAvPeriod,self.currentPrice)))
candlestic.label = "'Buy'"
self.trades.append(
BotTrade(self.currentTime, self.currentPrice))
self.numOfTrades += 1
for trade in openTrades:
if self.strategy1(False):
#self.output.log("Trade Closed. Currentprice: "+str(self.currentPrice)+", MovAverage: "+str(self.indicators.movingAverage(self.prices,self.vars.movingAvPeriod,self.currentPrice)))
candlestic.label = "'Sell'"
trade.close(self.currentPrice, self.currentTime)
def updateOpenTrades(self, candlestic):
status = ""
for trade in self.trades:
if (trade.status == "OPEN"):
status += trade.update(
self.currentPrice,
self.currentTime) #returns if state is open or close
if status == "CLOSED":
candlestic.label = "'StopLoss'"
def showPositions(self):
for trade in self.trades:
trade.showTrade()
def showMargin(self):
tradeStatus = "Stat"
for trade in self.trades:
if (trade.status == "CLOSED"):
tradeStatus = datetime.datetime.fromtimestamp(
trade.exitTime).strftime('%Y-%m-%d %H:%M:%S') + " " + str(
trade.status) + " Entry: " + str(
round(trade.entryPrice, 2)) + " Exit: " + str(
round(trade.exitPrice, 2))
self.makeInvesment(
trade) #considering the trade as an indicator
tradeStatus = tradeStatus + " Profit: "
if (trade.exitPrice > trade.entryPrice):
tradeStatus = tradeStatus + "\033[92m"
else:
tradeStatus = tradeStatus + "\033[91m"
tradeStatus = tradeStatus + str(
round(trade.exitPrice - trade.entryPrice,
2)) + "\033[0m" + " Inves: "
if (self.investement > botVariables().initialInvestment):
tradeStatus = tradeStatus + "\033[92m"
else:
tradeStatus = tradeStatus + "\033[91m"
tradeStatus = tradeStatus + str(round(self.investement,
2)) + "\033[0m"
self.output.log(tradeStatus)
# self.output.log(tradeStatus)
def makeInvesment(self, trade):
self.investement = (
(1 - self.makeFee) * self.investement / trade.entryPrice) * (
(1 - self.takeFee) * trade.exitPrice)
def showTrades(self):
return self.trades
def strategy1(self, buyTrueSellFalse):
if buyTrueSellFalse:
return self.SMA2 < self.SMA1 # and self.RSI>70
else:
return self.SMA2 > self.SMA1 # and self.RSI<30
def strategy2(self, buyTrueSellFalse):
if buyTrueSellFalse:
return self.currentPrice < self.BollDown and self.RSI < 40
else:
return self.currentPrice > self.BollUp and self.RSI > 55