def handle(self, *args, **options):
from history.poloniex import poloniex
from history.models import Price
import time
poo = poloniex(settings.API_KEY,settings.API_SECRET)
now = get_utc_unixtime()
r = poo.returnDepositHistory(0,now)
deposits = r['deposits'] + r['withdrawals']
for d in deposits:
print(d)
currency = d['currency']
amount = float(d['amount']) * ( -1 if 'withdrawalNumber' in d.keys() else 1 )
timestamp = d['timestamp']
txid = d['withdrawalNumber'] if 'withdrawalNumber' in d.keys() else d['txid']
status = d['status']
created_on = datetime.datetime.fromtimestamp(timestamp)
try:
d = Deposit.objects.get(txid=txid)
except:
d = Deposit()
d.symbol=currency
d.amount = amount
d.txid = txid
d.type = 'deposit' if amount > 0 else 'withdrawal'
d.status = status
d.created_on = created_on
d.modified_on = created_on
d.created_on_str = datetime.datetime.strftime(created_on - datetime.timedelta(hours=int(7)),'%Y-%m-%d %H:%M')
d.save()
def handle(self, *args, **options):
from history.poloniex import poloniex
from history.models import Price
import time
#hit API
poo = poloniex(settings.API_KEY,settings.API_SECRET)
balances = poo.returnBalances()
#record balances
deposited_amount_btc, deposited_amount_usd = get_deposit_balance()
with transaction.atomic():
for ticker in balances:
val = float(balances[ticker]['available']) + float(balances[ticker]['onOrders'])
if val > 0.0001:
exchange_rate_coin_to_btc = get_exchange_rate_to_btc(ticker)
exchange_rate_btc_to_usd = get_exchange_rate_btc_to_usd()
exchange_rate_coin_to_usd = exchange_rate_btc_to_usd * exchange_rate_coin_to_btc
btc_val = exchange_rate_coin_to_btc * val
usd_val = exchange_rate_btc_to_usd * btc_val
b = Balance(symbol=ticker,coin_balance=val,btc_balance=btc_val,exchange_to_btc_rate=exchange_rate_coin_to_btc,usd_balance=usd_val,exchange_to_usd_rate=exchange_rate_coin_to_btc,deposited_amount_btc=deposited_amount_btc if ticker =='BTC' else 0.00, deposited_amount_usd=deposited_amount_usd if ticker =='BTC' else 0.00)
b.save()
for b in Balance.objects.filter(date_str='0'):
# django timezone stuff , FML
b.date_str = datetime.datetime.strftime(b.created_on - datetime.timedelta(hours=int(7)),'%Y-%m-%d %H:%M')
b.save()
#normalize trade recommendations too. merp
for tr in Trade.objects.filter(created_on_str=''):
# django timezone stuff , FML
tr.created_on_str = datetime.datetime.strftime(tr.created_on - datetime.timedelta(hours=int(7)),'%Y-%m-%d %H:%M')
tr.save()
def handle(self, *args, **options):
from history.poloniex import poloniex
from history.models import Price
import time
poo = poloniex(settings.API_KEY, settings.API_SECRET)
if settings.MAKE_TRADES:
time.sleep(40)
for t in Trade.objects.filter(created_on__lt=datetime.datetime.now(),
status='scheduled'):
#bid right below the lowest ask, or right above the highest bid so that our orders get filled
action = t.type
price = Price.objects.filter(
symbol=t.symbol).order_by('-created_on').first()
if action == 'sell':
rate = price.lowestask * 0.999
else:
rate = price.highestbid * 1.001
t.price = rate
if action == 'buy':
try:
response = {} if not settings.MAKE_TRADES else poo.buy(
t.symbol, rate, t.amount)
except Exception as e:
print_and_log('(st)act_upon_recommendation:buy: ' + str(e))
elif action == 'sell':
try:
response = {} if not settings.MAKE_TRADES else poo.sell(
t.symbol, rate, t.amount)
except Exception as e:
print_and_log('(st)act_upon_recommendation:sell: ' +
str(e))
t.response = response,
t.orderNumber = response.get('orderNumber', '')
t.status = 'error' if response.get('error', False) else 'open'
t.calculatefees()
t.calculate_exchange_rates()
t.save()
ot = t.opposite_trade
ot.opposite_price = rate
ot.net_profit = ((rate * t.amount) -
(ot.price * ot.amount) if action == 'sell' else
(ot.price * ot.amount) -
(rate * t.amount)) - ot.fee_amount - t.fee_amount
ot.calculate_profitability_exchange_rates()
ot.save()
def handle(self, *args, **options):
# setup
self.poo = poloniex(settings.API_KEY, settings.API_SECRET)
self.setup()
print_and_log("(t){} ---- ****** STARTING TRAINERS ******* ".format(str(datetime.datetime.now())))
self.get_traders()
print_and_log("(t){} ---- ****** DONE TRAINING ALL TRAINERS ******* ".format(str(datetime.datetime.now())))
while True:
# TLDR -- which NNs should run at this granularity?
should_run = []
recommendations = dict.fromkeys(range(0, len(self.predictors)))
for i in range(0, len(self.predictor_configs)):
config = self.predictor_configs[i]
if (int(get_utc_unixtime() / 60) % config['granularity'] == 0 and datetime.datetime.now().second < 1):
should_run.append(i)
# TLDR -- update open orders bfore placing new ones
if len(should_run) > 0:
self.handle_open_orders()
# TLDR -- run the NNs specified at this granularity
for i in should_run:
config = self.predictor_configs[i]
recommend = self.run_predictor(i)
recommendations[i] = recommend
time.sleep(1)
# TLDR - act upon recommendations
for i in range(0, len(recommendations)):
recommendation = recommendations[i]
config = self.predictor_configs[i]
if recommendation is not None:
print_and_log("(t)recommendation {} - {} : {}".format(i, str(config['name']), recommendation))
self.act_upon_recommendation(i, recommendation)
# TLDR - cleanup and stats
if len(should_run) > 0:
pct_buy = round(100.0 * sum(recommendations[i] == 'BUY' for
i in recommendations) / len(recommendations))
pct_sell = round(100.0 * sum(recommendations[i] == 'SELL' for
i in recommendations) / len(recommendations))
print_and_log("(t)TLDR - {}% buy & {}% sell: {}".format(pct_buy, pct_sell, recommendations))
print_and_log("(t) ******************************************************************************* ")
print_and_log("(t) portfolio is {}".format(self.get_portfolio_breakdown_pct()))
print_and_log("(t) ******************************************************************************* ")
print_and_log("(t) {} ..... waiting again ..... ".format(str(datetime.datetime.now())))
print_and_log("(t) ******************************************************************************* ")
time.sleep(1)
def handle(self, *args, **options):
from history.poloniex import poloniex
from history.models import Price
import time
#hit API
poo = poloniex(settings.API_KEY, settings.API_SECRET)
balances = poo.returnBalances()
#record balances
deposited_amount_btc, deposited_amount_usd = get_deposit_balance()
with transaction.atomic():
for ticker in balances:
val = float(balances[ticker]['available']) + float(
balances[ticker]['onOrders'])
if val > 0.0001:
exchange_rate_coin_to_btc = get_exchange_rate_to_btc(
ticker)
exchange_rate_btc_to_usd = get_exchange_rate_btc_to_usd()
exchange_rate_coin_to_usd = exchange_rate_btc_to_usd * exchange_rate_coin_to_btc
btc_val = exchange_rate_coin_to_btc * val
usd_val = exchange_rate_btc_to_usd * btc_val
b = Balance(symbol=ticker,
coin_balance=val,
btc_balance=btc_val,
exchange_to_btc_rate=exchange_rate_coin_to_btc,
usd_balance=usd_val,
exchange_to_usd_rate=exchange_rate_coin_to_btc,
deposited_amount_btc=deposited_amount_btc
if ticker == 'BTC' else 0.00,
deposited_amount_usd=deposited_amount_usd
if ticker == 'BTC' else 0.00)
b.save()
for b in Balance.objects.filter(date_str='0'):
# django timezone stuff , FML
b.date_str = datetime.datetime.strftime(
b.created_on - datetime.timedelta(hours=int(7)),
'%Y-%m-%d %H:%M')
b.save()
#normalize trade recommendations too. merp
for tr in Trade.objects.filter(created_on_str=''):
# django timezone stuff , FML
tr.created_on_str = datetime.datetime.strftime(
tr.created_on - datetime.timedelta(hours=int(7)),
'%Y-%m-%d %H:%M')
tr.save()
def handle(self, *args, **options):
from history.poloniex import poloniex
from history.models import Price
import time
poo = poloniex(settings.API_KEY, settings.API_SECRET)
if settings.MAKE_TRADES:
time.sleep(40)
for t in Trade.objects.filter(created_on__lt=datetime.datetime.now(), status='scheduled'):
# bid right below the lowest ask, or right above the highest bid so that our orders get filled
action = t.type
price = Price.objects.filter(symbol=t.symbol).order_by('-created_on').first()
if action == 'sell':
rate = price.lowestask * 0.999
else:
rate = price.highestbid * 1.001
t.price = rate
if action == 'buy':
try:
response = {} if not settings.MAKE_TRADES else poo.buy(t.symbol, rate, t.amount)
except Exception as e:
print_and_log('(st)act_upon_recommendation:buy: ' + str(e))
elif action == 'sell':
try:
response = {} if not settings.MAKE_TRADES else poo.sell(t.symbol, rate, t.amount)
except Exception as e:
print_and_log('(st)act_upon_recommendation:sell: ' + str(e))
t.response = response
t.orderNumber = response.get('orderNumber', '')
t.status = 'error' if response.get('error', False) else 'open'
t.calculatefees()
t.calculate_exchange_rates()
t.save()
ot = t.opposite_trade
ot.opposite_price = rate
ot.net_profit = ((rate * t.amount) - (ot.price * ot.amount) if action == 'sell' else
(ot.price * ot.amount) - (rate * t.amount)) - ot.fee_amount - t.fee_amount
ot.calculate_profitability_exchange_rates()
ot.save()
def handle(self, *args, **options):
from history.poloniex import poloniex
# hit API
poo = poloniex(settings.API_KEY, settings.API_SECRET)
balances = poo.returnBalances()
balances = json.dumps(balances)
balances = json.loads(balances)
# record balances
deposited_amount_btc, deposited_amount_usd = get_deposit_balance()
with transaction.atomic():
try:
for ticker2 in balances['info']:
print(ticker2)
val = float(ticker2['balance'])
print(val)
if val > 0.0001:
ticker = ticker2 ['currency']
exchange_rate_coin_to_btc = get_exchange_rate_to_btc(ticker)
exchange_rate_btc_to_usd = get_exchange_rate_btc_to_usd()
btc_val = val / exchange_rate_coin_to_btc
usd_val = btc_val / exchange_rate_btc_to_usd
b = Balance(symbol=ticker, coin_balance=val, btc_balance=btc_val,
exchange_to_btc_rate=exchange_rate_coin_to_btc, usd_balance=usd_val,
exchange_to_usd_rate=exchange_rate_coin_to_btc,
deposited_amount_btc=deposited_amount_btc if ticker == 'BTC' else 0.00,
deposited_amount_usd=deposited_amount_usd if ticker == 'BTC' else 0.00)
b.save()
except Exception as e:
print(e)
for b in Balance.objects.filter(date_str='0'):
# django timezone stuff , FML
b.date_str = datetime.datetime.strftime(b.created_on - datetime.timedelta(hours=int(7)), '%Y-%m-%d %H:%M')
b.save()
# normalize trade recommendations too. merp
for tr in Trade.objects.filter(created_on_str=''):
# django timezone stuff , FML
tr.created_on_str = datetime.datetime.strftime(
tr.created_on - datetime.timedelta(hours=int(7)), '%Y-%m-%d %H:%M')
tr.save()
def handle(self, *args, **options):
from history.poloniex import poloniex
from history.models import Price
import time
poo = poloniex(settings.API_KEY,settings.API_SECRET)
price = poo.returnTicker()
for ticker in price.keys():
this_price = price[ticker]['last']
this_volume = price[ticker]['quoteVolume']
the_str = ticker + ',' + str(time.time()) + ',' + this_price + ", " + this_volume
print("(pp)"+the_str)
p = Price()
p.price = this_price
p.volume = this_volume
p.lowestask = price[ticker]['lowestAsk']
p.highestbid = price[ticker]['highestBid']
p.symbol = ticker
p.created_on_str = str(p.created_on)
p.save()
def handle(self, *args, **options):
from history.poloniex import poloniex
from history.models import Price
import time
poo = poloniex(settings.API_KEY, settings.API_SECRET)
price = poo.returnTicker()
for ticker in price.keys():
this_price = price[ticker]['last']
this_volume = price[ticker]['quoteVolume']
the_str = ticker + ',' + str(
time.time()) + ',' + this_price + ", " + this_volume
print("(pp)" + the_str)
p = Price()
p.price = this_price
p.volume = this_volume
p.lowestask = price[ticker]['lowestAsk']
p.highestbid = price[ticker]['highestBid']
p.symbol = ticker
p.created_on_str = str(p.created_on)
p.save()
def handle(self, *args, **options):
# setup
self.poo = poloniex(settings.API_KEY, settings.API_SECRET)
self.setup()
print_and_log("(t){} ---- ****** STARTING TRAINERS ******* ".format(
str(datetime.datetime.now())))
self.get_traders()
print_and_log(
"(t){} ---- ****** DONE TRAINING ALL TRAINERS ******* ".format(
str(datetime.datetime.now())))
while True:
# TLDR -- which NNs should run at this granularity?
should_run = []
recommendations = dict.fromkeys(range(0, len(self.predictors)))
for i in range(0, len(self.predictor_configs)):
config = self.predictor_configs[i]
if (int(get_utc_unixtime() / 60) % config['granularity'] == 0
and datetime.datetime.now().second < 1):
should_run.append(i)
# TLDR -- update open orders bfore placing new ones
if len(should_run) > 0:
self.handle_open_orders()
# TLDR -- run the NNs specified at this granularity
for i in should_run:
config = self.predictor_configs[i]
recommend = self.run_predictor(i)
recommendations[i] = recommend
time.sleep(1)
# TLDR - act upon recommendations
for i in range(0, len(recommendations)):
recommendation = recommendations[i]
config = self.predictor_configs[i]
if recommendation is not None:
print_and_log("(t)recommendation {} - {} : {}".format(
i, str(config['name']), recommendation))
self.act_upon_recommendation(i, recommendation)
# TLDR - cleanup and stats
if len(should_run) > 0:
pct_buy = round(100.0 * sum(recommendations[i] == 'BUY'
for i in recommendations) /
len(recommendations))
pct_sell = round(100.0 * sum(recommendations[i] == 'SELL'
for i in recommendations) /
len(recommendations))
print_and_log("(t)TLDR - {}% buy & {}% sell: {}".format(
pct_buy, pct_sell, recommendations))
print_and_log(
"(t) ******************************************************************************* "
)
print_and_log("(t) portfolio is {}".format(
self.get_portfolio_breakdown_pct()))
print_and_log(
"(t) ******************************************************************************* "
)
print_and_log("(t) {} ..... waiting again ..... ".format(
str(datetime.datetime.now())))
print_and_log(
"(t) ******************************************************************************* "
)
time.sleep(1)
