https://colab.research.google.com/drive/1DXkTXZ-eiQ1Jio_tzyuTsHjdy0R5IQLT#scrollTo=2yu0huE3czMh&line=216&uniqifier=1
import os
from iqoptionapi.stable_api import IQ_Option
import logging
import time
import secrets
from datetime import datetime as dt
import numpy as np
import matplotlib.pyplot as plt
# from mpl_finance import candlestick_ohlc
import pandas as pd
import matplotlib.dates as mpl_dates
import talib
import plotly.graph_objs as go
from plotly.offline import plot
from pyti.smoothed_moving_average import smoothed_moving_average as sma
from pyti.exponential_moving_average import exponential_moving_average as ema
global short_time
global b
global result
global x
short_time=0
cnt=0
result=0
x=0
# logging.basicConfig(level=logging.DEBUG,format='%(asctime)s %(message)s')
print("login...")
I_want_money=IQ_Option("xxxx@hotmail.com","12345678aabbccddeeff")
check, reason=I_want_money.connect()#connect to iqoption
print(check)#, reason)
#I_want_money.connect()#connect to iqoption
print(I_want_money.reset_practice_balance())
#goal="USDCHF-OTC"
class TradingModel:
def __init__(self, symbol,size,maxdict,Money,x,expirations_mode):
self.symbol = symbol[x]
self.size = size
self.maxdict = maxdict
self.Money=Money
self.expirations_mode= expirations_mode
self.df = self.getData()
# Returns true if stream1 crossed under stream2 in most recent candle, stream2 can be integer/float or data arra
def getData(self):
# print("start stream...")
I_want_money.start_candles_stream(self.symbol,self.size,self.maxdict)
#DO something
# print("Please wait now collecting candlestick data...",self.symbol)
candles=I_want_money.get_realtime_candles(self.symbol,self.size)
inputs = {
'time': np.array([]).astype(int),
'open': np.array([]).astype(float),
'high': np.array([]).astype(float),
'low': np.array([]).astype(float),
'close': np.array([]).astype(float),
'volume': np.array([]).astype(float)
}
for timestamp in candles:
# ((datetime.utcfromtimestamp(int(data_ohlc['from'])).strftime('%Y-%m-%d %H:%M:%S'))
# inputs["time"]=np.append(inputs["time"],candles[((datetime.utcfromtimestamp(int(candles['from'])).strftime('%Y-%m-%d %H:%M:%S'))] )
inputs["time"]=np.append(inputs["time"],candles[timestamp]['from'] )
inputs["open"]=np.append(inputs["open"],candles[timestamp]["open"] )
inputs["high"]=np.append(inputs["high"],candles[timestamp]["max"] )
inputs["low"]=np.append(inputs["low"],candles[timestamp]["min"] )
inputs["close"]=np.append(inputs["close"],candles[timestamp]["close"] )
inputs["volume"]=np.append(inputs["volume"],candles[timestamp]["volume"] )
df = pd.DataFrame(inputs)#,columns=['time', 'open', 'high', 'low', 'close', 'volume'])#,index=0, parse_dates=True)
df=df.sort_index()
df['H-L'] = df['high'] - df['low']
df['O-C'] = df['open']-df['close']
df['SMA5'] = df['close'].shift(1).rolling(window = 5).mean()
df['newATR'] = talib.ATR(df['high'], df['low'], df['close'], timeperiod=14)
# os.system('cls') # on windows
# print(df.loc[35:])
return df
def strategy(self):
df = self.df
print(df['high'].iloc[self.maxdict-3],round(df['SMA5'].iloc[self.maxdict-3],6),df['low'].iloc[self.maxdict-3])
print(df['high'].iloc[self.maxdict-3]-round(df['SMA5'].iloc[self.maxdict-3],6),df['low'].iloc[self.maxdict-3]-round(df['SMA5'].iloc[self.maxdict-3],6)," atr ",df['newATR'].max())
print("high to SMA5\t",round(df['high'].iloc[self.maxdict-3]-df['SMA5'].iloc[self.maxdict-3]-(1.1*df['newATR'].max()),6))
print("SMA5 to low \t",round(df['SMA5'].iloc[self.maxdict-3]-df['low'].iloc[self.maxdict-3]-(1.1*df['newATR'].max()),6))
distantce_high_to_sma=round(df['high'].iloc[self.maxdict-3]-df['SMA5'].iloc[self.maxdict-3]-(1.1*df['newATR'].max()),6)
distantce_sma_to_low=round(df['SMA5'].iloc[self.maxdict-3]-df['low'].iloc[self.maxdict-3]-(1.1*df['newATR'].max()),6)
sma_in_candle=df['high'].iloc[self.maxdict-3] > df['SMA5'].iloc[self.maxdict-3] > df['low'].iloc[self.maxdict-3]
bearish_candle=df['O-C'].iloc[self.maxdict-2]>0 and distantce_sma_to_low>0
bullish_candle=df['O-C'].iloc[self.maxdict-2]<0 and distantce_high_to_sma>0
lower_wick_bull=(df['open']-df['low']).iloc[self.maxdict-3]
upper_wick_bull=(df['high']-df['close']).iloc[self.maxdict-3]
lower_wick_bear=(df['close']-df['low']).iloc[self.maxdict-3]
upper_wick_bear=(df['high']-df['open']).iloc[self.maxdict-3]
print(lower_wick_bull,upper_wick_bull)
print(lower_wick_bear,upper_wick_bear)
for i in range(1, len(df['close'])):
if distantce_high_to_sma>df['newATR'].max():
print("candle far above SMA5",distantce_high_to_sma)
self.sell()
break
if distantce_sma_to_low>df['newATR'].max():
print("candle far below SMA5",distantce_sma_to_low)
self.buy()
break
def buy(self):
Money=self.Money
ACTIVES=self.symbol
ACTION="call"#or "put"
check,id=I_want_money.buy(Money,ACTIVES,ACTION,self.expirations_mode)
if check:
print(ACTIVES," !buy!",self.Money)
else:
print(ACTIVES," buy fail")
pass#time.sleep(5)
result=(I_want_money.check_win_v3(id))
print(result)
## return result
def sell(self):
Money=self.Money
ACTIVES=self.symbol
ACTION="put"#or "put"
check,id=I_want_money.buy(Money,ACTIVES,ACTION,self.expirations_mode)
if check:
print(ACTIVES," !sell!",self.Money)
else:
print(ACTIVES," sell fail")
pass#time.sleep(5)
result=(I_want_money.check_win_v3(id))
print(result)
## return result
# def unloadcandle(self):
# print("stop candle")
# I_want_money.stop_candles_stream(self.symbol,self.size)
def Main():
b=0
s=0
martinggale=1
balance=I_want_money.get_balance()
print("balance = ",balance)
## symbol = ["AUDJPY","EURUSD","EURJPY","GBPUSD","AUDUSD","USDJPY"]
symbol = ["EURUSD","NZDUSD","AUDCAD","EURNZD","AUDJPY","GBPAUD","GBPCAD"]
cnt=len(symbol)
# print(cnt," SYMBOL IN LIST")
size=30#"all"#size=[1,5,10,15,30,60,120,300,600,900,1800,3600,7200,14400,28800,43200,86400,604800,2592000,"all"]
maxdict=40
trigger_level=0
Money=1000
randoms=[1,2.5,3]
martinggale=secrets.choice(randoms)
Money=Money*martinggale
print("Invest money = ",Money)
expirations_mode=2
remaning_time=I_want_money.get_remaning(expirations_mode)
model = TradingModel(symbol,
size,
maxdict,
Money,
x,
expirations_mode)
model.strategy()
if __name__ == '__main__':
while check:
x=x
Main()
