def on_message(ws, message):
'''
Control the message received from
'''
mess = json.loads(message)
if mess['e'] == 'kline':
kln = mess['k']
if kln['x'] is True:
symbol = kln['s'].upper()
new_kln = {
'_t': int(kln['t']),
'_o': float(kln['o']),
'_h': float(kln['h']),
'_l': float(kln['l']),
'_c': float(kln['c']),
'_v': float(kln['q'])
}
SymKlns[symbol].append(new_kln)
print( '%d. %s\t' % (len(SymKlns[symbol]), symbol) + timestr(new_kln['_t']) + '\t' + \
''.join(['{:>3}:{:<10}'.format(k, v) for k,v in iter(new_kln.items()) if not k=='_t']))
elif mess['e'] == 'depthUpdate':
### PROBLEM 1 Insert your code to handle depthUpdate message ###
symbol = mess['s'].upper()
bids, asks = mess['b'], mess['a']
new_bidask = {
'_t': int(mess['T']),
'_b1': float(bids[0][0]),
'_b2': float(bids[1][0]),
'_a1': float(asks[0][0]),
'_a2': float(asks[1][0])
}
BidAsk[symbol].append(new_bidask)
print( '%d. %s\t' % (len(BidAsk[symbol]), symbol) + timestr(new_bidask['_t']) + '\t' + \
''.join(['{:>3}:{:<10}'.format(k, v) for k,v in iter(new_bidask.items()) if not k=='_t']) )
def __str__(self):
'''
Print out infomation of the signal
'''
s = 'Singal info: ' + self.symbol
gen_ = ' status:' + str(self.status) + ' side:' + str(
self.side) + ' type:' + str(self.orderType) + ' quantity:' + str(
self.get_quantity())
if self.is_waiting() or self.is_expired():
id_ = ' Id:None '
price_ = ' price:' + str(self.price) + ' time:' + timestr(
self.startTime, end='s')
elif self.is_ordered():
id_ = ' Id:' + str(self.orderId)
if self.orderType == 'LIMIT':
price_ = ' price:' + str(self.limitPrice) + ' TIF:' + str(
self.timeInForce) + ' time:' + timestr(self.startTime,
end='s')
else:
price_ = ' type:' + str(self.orderType) + ' time:' + timestr(
self.orderTime, end='s')
elif self.is_active():
id_ = ' Id:' + str(self.orderId)
if self.orderType == 'LIMIT':
price_ = ' price:' + str(self.excPrice) + ' TIF:' + str(
self.timeInForce) + ' time:' + timestr(self.excTime,
end='s')
else:
price_ = ' price:' + str(self.excPrice) + ' time:' + timestr(
self.excTime, end='s')
elif self.is_cnt_ordered():
gen_ = ' status:' + str(self.status) + ' side:' + str(
self.counter_order()['side']) + ' type:' + str(
self.cntType) + ' quantity:' + str(self.get_quantity())
id_ = ' Id:' + str(self.cntorderId)
if self.cntType == 'LIMIT':
price_ = ' price:' + str(self.cntlimitPrice) + ' TIF:' + str(
self.timeInForce) + ' time:' + timestr(self.cntTime,
end='s')
else:
price_ = ' type:' + str(self.cntType) + ' time:' + timestr(
self.cntTime, end='s')
elif self.is_closed():
gen_ = ' status:' + str(self.status) + ' side:' + str(
self.counter_order()['side']) + ' type:' + str(
self.cntType) + ' quantity:' + str(self.get_quantity())
id_ = ' Id: ' + str(self.cntorderId)
price_ = ' price:' + str(self.clsPrice) + ' time:' + timestr(
self.clsTime, end='s')
if self.stopLoss is None: sl_ = 'None'
else: sl_ = str(self.stopLoss)
if self.takeProfit is None: tp_ = 'None'
else: tp_ = str(self.takeProfit)
if self.timeLimit is None: tl_ = 'None'
else: tl_ = str(int(self.timeLimit / sec_in_ms))
exits_ = ' exits:[' + sl_ + ', ' + tp_ + ', ' + tl_ + ']'
s += id_ + gen_ + price_ + exits_
return s
def header_print(testnet, client):
'''
Print general information of the trading session
'''
t_server, t_local = client.timestamp(), time.time()*1000
print('\tTestnet: %s' % str(testnet))
print('\tServer Time at Start: %s' % timestr(t_server))
print('\tLocal Time at Start: %s, \tOffset (local-server): %d ms\n' % (timestr(t_local), (t_local-t_server)))
try:
bal_st = pd.DataFrame(client.balance())
bal_st['updateTime'] = [timestr(b) for b in bal_st['updateTime']]
print('\nBeginning Balance Info: \n')
print(bal_st)
except Exception:
print('\nFail to connect to client.balance: \n')
def header_print(client):
'''
Print Local Time, Timezone and Account Balance Info
'''
t_local = time.time() * 1000
print('\n' + barstr(text="", space_size=0))
print(barstr(text='IG Server Connecting Session Info'))
print('\n\n\tDemo Server: %s' % str(demo))
print('\tLocal Time at Start: %s, \n\tServer Timezone Offset : UTC%+d' %
(timestr(t_local), resp['timezoneOffset']))
print('\n\tAccount Balance info at Start:')
try:
accounts = client.account_details()['accounts']
for n in range(len(accounts)):
info = {
str(key): str(value)
for key, value in iter(accounts[0].items())
}
balance = {
str(key): str(value)
for key, value in iter(accounts[0]['balance'].items())
}
print('\tAccount #{}:'.format(n))
print(
"\tId : {accountId:<} \tType : {accountType:<} \tStatus : {status:<} \tCurrency : {currency:<}"
.format(**info))
print(
"\tBalance \tTotal : {balance:<} \tAvailable : {available:<}".
format(**balance))
print('\n')
except Exception:
print('\tFAIL to connect to client.balance. \n')
def handle_response(self, enablePrint=True, on_message=None):
'''
Process live message from IG Streaming Server
Pass fucntion on_message to handle the messages differently
'''
line = self._stream_response.readline().decode("utf-8").rstrip()
if line != 'PROBE':
if not bool(on_message):
toks = line.rstrip('\r\n').split('|')
item = self.subscriptions['item_names'][
int(toks[0].split(',')[-1]) - 1]
pstr = {}
for i in range(len(self.subscriptions['field_names'])):
field = self.subscriptions['field_names'][i]
value = LSClient._decode_field(
toks[i + 1], prev=self._prevResp[item][field])
try:
if field == 'UTM': value = timestr(int(value), end='s')
except:
pass
pstr[field] = value
self._prevResp[item] = pstr.copy()
if enablePrint:
print(
"{:<35}".format(item), ''.join([
'{:>10} : {:<10}'.format(k, v)
for k, v in iter(pstr.items())
]))
pstr['item'] = item
return pstr
else:
return on_message(line)
def get_ticks(symbol, start_time, filepath):
if not isinstance(start_time, int): start_time = int(pd.Timestamp(datetime.strptime(start_time, '%d %b %Y %H:%M:%S')).value/10**6)
print("\nProcessing aggTrades for %s from %s \n" % (symbol, timestr(start_time, end='s')))
agg_trades = client.aggregate_trade_iter(symbol=symbol, start_str=start_time)
trade_df = pd.DataFrame(list(agg_trades)).drop(['a', 'f','l','m','M'], axis=1)
trade_df = trade_df.rename(columns={"p": "_p", "q": "_v", "T": "_t"})
trade_df['_p'] = trade_df['_p'].astype(float)
trade_df['_v'] = trade_df['_v'].astype(float)
rawfile = filepath + "aggtrades-%s.csv" % (symbol)
trade_df.to_csv(rawfile)
return trade_df
def header_print(testnet, client, portfolio, file):
'''
Print general information of the trading session
'''
t_server, t_local = client.timestamp(), time.time() * 1000
print_('\tTestnet: %s' % str(testnet), file)
print_('\tServer Time at Start: %s' % timestr(t_server), file)
print_(
'\tLocal Time at Start: %s, \tOffset (local-server): %d ms\n' %
(timestr(t_local), (t_local - t_server)), file)
print_(
'\t#LONG order : %d \t#SHORT order: %d \tOrder Size : %1.2f \n' %
(portfolio.equityDist['BUY'], portfolio.equityDist['SELL'],
portfolio.orderSize), file)
try:
bal_st = pd.DataFrame(client.balance())
bal_st['updateTime'] = [timestr(b) for b in bal_st['updateTime']]
print_('\nBeginning Balance Info: \n', file)
print_(bal_st, file)
except Exception:
print_('\nFail to connect to client.balance: \n', file)
def on_message(ws, message):
'''
Control the message received from
'''
mess = json.loads(message)
if mess['e'] == 'kline':
kln = mess['k']
if kln['x'] is True:
symbol = kln['s'].upper()
new_kln = { '_t': int(kln['t']), '_o': float(kln['o']), '_h': float(kln['h']), '_l': float(kln['l']), '_c': float(kln['c']), '_v': float(kln['q']) }
SymKlns[symbol].append(new_kln)
print_( '%d. %s\t' % (len(SymKlns[symbol]), symbol) + timestr(new_kln['_t']) + '\t' + \
''.join(['{:>3}:{:<10}'.format(k, v) for k,v in iter(new_kln.items()) if not k=='_t']), fileout)
def __str__(self):
'''
Print out infomation of the signal
'''
s = 'Singal info: ' + self.symbol
gen_ = ' status:' + str(self.status) + ' side:' + str(self.side) + ' type:' + str(self.orderType) + ' quantity:' + str(self.get_quantity())
if self.is_waiting() or self.is_expired():
id_ = ' Id:None '
price_ = ' price:' + str(self.price) + ' time:' + timestr(self.startTime, end='s')
s += id_ + gen_ + price_
### PROBLEM 2 : Insert your code here ###
return s
demo = True
if demo:
# demo IG
username = ''
password = ''
apikey = ''
else:
# IG
username = ''
password = ''
apikey = ''
"""Client to connect to IG Server"""
client = Client(username=username,
password=password,
api_key=apikey,
demo=demo)
resp = client.create_session(encrypted=True)
header_print(client)
"""Multi-threading function. One can call data_stream() directly"""
t1 = threading.Thread(target=data_stream)
t1.setDaemon(True)
t1.start()
t1.join()
print('\n\tLocal Time at Close: %s \n' % timestr(time.time() * 1000))
print(
barstr(text='Elapsed time = {} seconds'.format(
round(time.time() - start_time, 2))))
print(barstr(text="", space_size=0))
os._exit(1)
def main(args):
start_time = time.time()
testnet = True
filename = str(int(time.time()))
if testnet:
# Testnet
# "key": "d782f0d42dcf016c32fd56a96d01bb0e120f78802d9de378cdb9fde2b6c841e8",
#"secret": "1ec873bf3137868a9e12e57e8e19cfa5a3a38cec403b741d2f7cd881c51bfd72"
apikey = 'd782f0d42dcf016c32fd56a96d01bb0e120f78802d9de378cdb9fde2b6c841e8' ### INSERT your api key here ###
scrkey = '1ec873bf3137868a9e12e57e8e19cfa5a3a38cec403b741d2f7cd881c51bfd72' ### INSERT your api secret here ###
else:
# Binance
apikey = ''
scrkey = ''
if testnet: fileout = "report/testnet-" + filename
else: fileout = "report/" + filename
insIds = ['BTCUSDT', 'ETHUSDT', 'BCHUSDT', 'BNBUSDT']
# Generate Client object
client = Client(apikey, scrkey, testnet=testnet)
client.change_position_mode(dualSide='true')
# Generate Portfolio object
portfolio = Portfolio(client, tradeIns=insIds)
long, short = portfolio.equity_distribution(longPct=0.25,
shortPct=0.25,
currency='USDT',
orderPct=0.05)
portfolio.position_locks()
print_('\n' + barstr('', length=100, space_size=0), fileout)
print_(barstr('BINANCE TRADING', length=100, space_size=5), fileout)
print_(barstr('', length=100, space_size=0) + '\n', fileout)
print_('\n' + barstr('Generating Models', length=100, space_size=5) + '\n',
fileout)
# Generate Models object
models = {}
for i in range(len(portfolio.tradeIns)):
symbol = portfolio.tradeIns[i]
client.change_leverage(symbol, 1)
_data = MarketData(testnet=testnet, symbol=symbol)
model = TradingModel(symbol=symbol,
testnet=testnet,
modelType='bollinger',
marketData=_data,
pdObserve=pd_ob,
pdEstimate=pd_es,
orderSize=portfolio.orderSize)
model.build_initial_input()
only_pos = 'BOTH'
if symbol in portfolio.locks['BUY']:
model.add_signal_lock(slock='BUY')
only_pos = 'SELL ONLY'
elif symbol in portfolio.locks['SELL']:
model.add_signal_lock(slock='SELL')
only_pos = 'BUY ONLY'
models[symbol] = model
print_(
'\tFinish generating model for %s - positions: %s' %
(symbol, only_pos), fileout)
print_(
'\n' + barstr('Start Data Streaming', length=100, space_size=5) + '\n',
fileout)
header_print(testnet, client, portfolio, fileout)
print('\n\tPre-processing Time = %f' % (time.time() - start_time))
print_('\nStream updating for {} minutes...'.format(pd_ob * min_in_candle),
fileout)
signals = wss_run(portfolio, client, testnet, ['@kline_1m'], models,
fileout)
session_summary(signals, fileout)
print_('\n\tLocal Time at Close: %s ' % timestr(time.time() * 1000),
fileout)
print_(
barstr(text='Elapsed time = {} seconds'.format(
round(time.time() - start_time, 2))), fileout)
print_(barstr(text="", space_size=0), fileout)
os._exit(1)
