def get_valid_spy_contract(idx) -> OptionContract:
from ib_insync import IB, Stock
ib = IB()
ib.connect(clientId=idx + 1)
ib_stk_con = Stock(symbol="SPY", exchange="SMART", currency="USD")
ib_details = ib.reqContractDetails(ib_stk_con)[0]
ib.reqMarketDataType(4)
tick = ib.reqMktData(contract=ib_stk_con, snapshot=True)
while np.isnan(tick.ask):
ib.sleep()
ask = tick.ask
ib_con_id = ib_details.contract.conId
ib_chains = ib.reqSecDefOptParams(
underlyingSymbol="SPY",
futFopExchange="",
underlyingSecType="STK",
underlyingConId=ib_con_id,
)
ib_chain = ib_chains[0]
ib_chain.strikes.sort(key=lambda s: abs(s - ask))
strike = ib_chain.strikes[0]
expiration_str = ib_chain.expirations[idx]
expiration_date = datetime.strptime(expiration_str, "%Y%m%d")
spy_contract = OptionContract(
symbol="SPY",
strike=strike,
right=Right.CALL,
multiplier=int(ib_chain.multiplier),
last_trade_date=expiration_date,
)
ib.disconnect()
return spy_contract
def start(self):
self._logger.info('Starting mywatchdog')
self.controller.start()
IB.sleep(self.appStartupTime)
try:
self.ib.connect(self.host, self.port, self.clientId,
self.connectTimeout)
self.ib.setTimeout(self.appTimeout)
except:
# a connection failure will be handled by the apiError callback
pass
self._logger.info('Restarted mywatchdog')
self._logger.info('Start Scheduler List for mywatchdog')
for scheduler, schedules in self.schedulerList:
self._logger.info(
f'mywatchdog: scheduler: {scheduler}, {type(scheduler)}')
if isinstance(schedules, list) and isinstance(
scheduler, AsyncIOScheduler) and scheduler.running:
for schedule in schedules:
scheduler.add_job(**schedule)
self._logger.info(f'mywatchdog: schedule: {schedule}')
pass
scheduler.start()
pass
pass
self._logger.info('End Scheduler List for mywatchdog')
def start_and_connect(self):
"""
Starts the IB gateway with IBC and connects to it.
"""
logging.info('Starting IBC...')
self.ibc.start()
wait = self.connection_timeout
try:
while not self.isConnected():
# retry until connection is established or timeout is reached
IB.sleep(1)
wait -= 1
logging.info('Connecting to IB gateway...')
try:
self.connect(**self.ib_config)
except ConnectionRefusedError:
if not wait:
logging.warning('Timeout reached')
raise TimeoutError('Could not connect to IB gateway')
except Exception as e:
logging.error(e)
# write the launch log to logging (of limited use though as only the first
# phase of the gateway startup process is logged in this non-encrypted log)
try:
with open(self.ibc_config['twsPath'] + '/launcher.log',
'r') as fp:
logging.info(fp.read())
except FileNotFoundError:
logging.warning(self.ibc_config['twsPath'] +
'/launcher.log not found')
raise e
def test_ibgw_restart(ib_docker):
subprocess.check_output(
['docker', 'container', 'stop', ib_docker]).decode().strip()
subprocess.check_output(
['docker', 'container', 'start', ib_docker]).decode().strip()
ib = IB()
wait = 60
while not ib.isConnected():
try:
IB.sleep(1)
ib.connect('localhost', 4002, clientId=999)
except:
pass
wait -= 1
if wait <= 0:
break
contract = Forex('EURUSD')
bars = ib.reqHistoricalData(
contract, endDateTime='', durationStr='30 D',
barSizeSetting='1 hour', whatToShow='MIDPOINT', useRTH=True)
# convert to pandas dataframe:
df = util.df(bars)
print(df)
def download(symbols, end_datetime, duration, bar_size, dest_dir, host, port,
client_id):
ib = IB()
ib.connect(host, port, client_id, timeout=10)
for full_symbol in symbols:
if '@' in full_symbol:
symbol, exchange = full_symbol.split('@', 1)
exchange = 'SMART:%s' % exchange
else:
symbol, exchange = full_symbol, 'SMART'
df = _fetch_to_df(ib, symbol, exchange, end_datetime, duration,
bar_size)
df.drop(columns=['average', 'barCount'], inplace=True)
start_date = df.first_valid_index().strftime("%Y%m%d")
end_date = df.last_valid_index().strftime("%Y%m%d")
bar_size_short = "1M" if bar_size == "1 min" else "1D"
filename = f'{dest_dir}/HC-' \
f'{full_symbol}-{bar_size_short}-{start_date}-{end_date}-ib.csv'
df.to_csv(filename)
logger.info(f'Created file: {filename}')
# Throttle to avoid 'Pacing violation'
ib.sleep(11)
def test_request_realtime_bars(ib: IB):
contract = Forex('EURUSD')
bars = ib.reqRealTimeBars(contract, 5, 'MIDPOINT', False)
bars.updateEvent += on_bar_update
ib.sleep(100000) # 开盘到收盘时间
ib.cancelRealTimeBars(bars)
return bars
def determine_PnL(ib):
account = ib.managedAccounts()[0]
ib.reqPnL(account, '')
IB.sleep(8)
data = ib.pnl()
print(data)
ib.cancelPnL(account, '')
dailyPnL = 0.0
unrealizedPnL = 0.0
realizedPnL = 0.0
return dailyPnL, unrealizedPnL, realizedPnL
def download(symbols, duration, bar_size, dest_dir, host, port, client_id):
ib = IB()
ib.connect(host, port, client_id)
for symbol in symbols:
df = _fetch_to_df(ib, symbol, duration, bar_size)
df.drop(columns=['average', 'barCount'], inplace=True)
start_date = df.first_valid_index().strftime("%Y%m%d")
end_date = df.first_valid_index().strftime("%Y%m%d")
filename = f'{dest_dir}/HC-{symbol}-1M-{start_date}-{end_date}-ib.csv'
df.to_csv(filename)
logger.info(f'Created file: {filename}')
# Throttle to avoid 'Pacing violation'
ib.sleep(11)
def ping():
def timeout_handler(signum, frame):
signal.alarm(0)
raise TimeoutError('IB gateway timed out, please check your account & password')
signal.signal(signal.SIGALRM, timeout_handler)
signal.alarm(120)
ib = IB()
while not ib.isConnected():
try:
IB.sleep(1)
ib.connect('localhost', 4001, clientId=1)
except (ConnectionRefusedError, OSError) as e:
if type(e) is TimeoutError:
raise e
logging.warning('Still waiting gateway connection..({})'.format(e))
ib.disconnect()
def test_ibgw_interactive(ib_docker):
ib = IB()
wait = 120
while not ib.isConnected():
try:
IB.sleep(1)
ib.connect('localhost', 4002, clientId=999)
except:
pass
wait -= 1
if wait <= 0:
break
contract = Forex('EURUSD')
bars = ib.reqHistoricalData(
contract, endDateTime='', durationStr='30 D',
barSizeSetting='1 hour', whatToShow='MIDPOINT', useRTH=True)
# convert to pandas dataframe:
df = util.df(bars)
print(df)
def ping():
def timeout_handler(signum, frame):
signal.alarm(0)
raise TimeoutError(
'IB gateway timed out, please check your account & password')
signal.signal(signal.SIGALRM, timeout_handler)
signal.alarm(120)
ib = IB()
pingClientId = int(os.environ['IB_GATEWAY_PING_CLIENT_ID'])
maxRetryCount = int(os.environ['ibAccMaxRetryCount'])
retryCount = 0
while not ib.isConnected():
try:
IB.sleep(1)
ib.connect('localhost', 4001, clientId=pingClientId)
except (ConnectionRefusedError, OSError) as e:
retryCount += 1
if retryCount >= 30:
raise ValueError("Invalid ib account")
logging.warning('Still waiting gateway connection..({})'.format(e))
ib.disconnect()
from ib_insync import IB, util, Forex
if __name__ == "__main__":
IB.sleep(60) # wait for IB Gteway ready
ib = IB()
ib.connect('localhost', 4001, clientId=1)
contract = Forex('EURUSD')
bars = ib.reqHistoricalData(contract,
endDateTime='',
durationStr='30 D',
barSizeSetting='1 hour',
whatToShow='MIDPOINT',
useRTH=True)
# convert to pandas dataframe:
df = util.df(bars)
print(df)
class Basem:
''' 导入分钟级别股票信息类
'''
def __init__(self):
self.log = log(__name__, 'logs/basem.log')
self.db = Basedb()
self.empty = []
self.total = 0
self.i = 0
self.ib = IB()
self.ib.connect(Config.ib_host, Config.ib_port, Config.ib_client_id)
def __del__(self):
self.ib.disconnect()
def deal_data(self, future, symbol):
''' 回调函数，处理接口返回的股票数据
'''
self.i += 1
print('(%d/%d) 正在导入 %s HK' % (self.i, self.total, symbol), flush=True)
data = future.result()
if not data:
self.empty.append((symbol,))
return
open_sql = 'insert into `open_5m` (`code`, `code_type`, `date`, `value`) values '
high_sql = 'insert into `high_5m` (`code`, `code_type`, `date`, `value`) values '
low_sql = 'insert into `low_5m` (`code`, `code_type`, `date`, `value`) values '
close_sql = 'insert into `close_5m` (`code`, `code_type`, `date`, `value`) values '
volume_sql = 'insert into `volume_5m` (`code`, `code_type`, `date`, `value`) values '
average_sql = 'insert into `average_5m` (`code`, `code_type`, `date`, `value`) values '
for bar_data in data:
date = bar_data.date
open_price = bar_data.open
high = bar_data.high
low = bar_data.low
close = bar_data.close
average = bar_data.average
# volume 有不存在的情况, 16:00 收市，交易量不存在
try:
volume = bar_data.volume
except AttributeError:
volume = 0
open_sql += "('{code}', '{code_type}', '{date}', {value:.4f}),".format(code=symbol, code_type='hk', date=date, value=open_price)
high_sql += "('{code}', '{code_type}', '{date}', {value:.4f}),".format(code=symbol, code_type='hk', date=date, value=high)
low_sql += "('{code}', '{code_type}', '{date}', {value:.4f}),".format(code=symbol, code_type='hk', date=date, value=low)
close_sql += "('{code}', '{code_type}', '{date}', {value:.4f}),".format(code=symbol, code_type='hk', date=date, value=close)
volume_sql += "('{code}', '{code_type}', '{date}', {value}),".format(code=symbol, code_type='hk', date=date, value=volume)
average_sql += "('{code}', '{code_type}', '{date}', {value:.4f}),".format(code=symbol, code_type='hk', date=date, value=average)
open_rows = self.db.query(open_sql.rstrip(','))
high_rows = self.db.query(high_sql.rstrip(','))
low_rows = self.db.query(low_sql.rstrip(','))
close_rows = self.db.query(close_sql.rstrip(','))
volume_rows = self.db.query(volume_sql.rstrip(','))
average_rows = self.db.query(average_sql.rstrip(','))
if open_rows.rowcount == 0:
raise RuntimeError('open_sql 语句执行失败：%s' % open_sql)
elif high_rows.rowcount == 0:
raise RuntimeError('high_sql 语句执行失败：%s' % high_sql)
elif low_rows.rowcount == 0:
raise RuntimeError('low_sql 语句执行失败：%s' % low_sql)
elif close_rows.rowcount == 0:
raise RuntimeError('close_sql 语句执行失败：%s' % close_sql)
elif volume_rows.rowcount == 0:
raise RuntimeError('volume_sql 语句执行失败：%s' % volume_sql)
elif average_rows.rowcount == 0:
raise RuntimeError('average_sql 语句执行失败：%s' % average_sql)
else:
pass
def crawl_data(self, codes):
''' 爬取 IB 接口股票的交易信息
'''
futures = []
i = 0
for code in codes:
i += 1
symbol, _ = code
stock = Stock(symbol, Config.hk_exchange, Config.hk_currency)
future = self.ib.reqHistoricalDataAsync(stock, endDateTime='', durationStr='900 S',
barSizeSetting='5 mins', whatToShow='TRADES', useRTH=True)
self.ib.sleep(0.02)
future.add_done_callback(functools.partial(self.deal_data, symbol=symbol))
futures.append(future)
return futures
def get_codes_data(self, codes=None):
''' 爬取股票信息
1个月的5分钟交易信息
'''
t1 = time.time()
# codes => None 则从数据库获取股票列表
# 否则，使用传递进来的codes list，目的是再次爬取那些空数据的股票
# 以确保股票数据为空而不会遗漏有数据的股
# 因为有时连接超时，接口会返回空列表，但此股是有数据的
if codes is None:
codes = self.db.get_codes()
if not codes.rowcount:
raise RuntimeError('获取股票失败，stock 表返回空.')
codes = list(codes)
self.total = len(codes)
self.i = 0
futures = self.crawl_data(codes)
self.ib.run(*futures)
# 爬取完成，记录爬取的endDateTime时间，供下次增量爬取使用
end_date_time = '2017-12-31 23:59:59'
res = self.db.set_record(end_date_time)
if not res.rowcount:
raise RuntimeError('记录一个月5分钟的end_date_time失败.')
t2 = time.time()
t3 = t2 - t1
print('HK 股票交易信息全部导入完成，耗时：%.2fs' % t3)
self.log.info('导入股票信息完成，数据为空的股票有：{}'.format(self.empty))
def get_hsi_data(self):
''' 获取 HSI 一个月5分钟的信息
'''
symbol = 'HSI'
exchange = 'HKFE'
currency = 'HKD'
index = Index(symbol, exchange, currency)
data = self.ib.reqHistoricalData(index, endDateTime='20180119 15:00:00', durationStr='900 S',
barSizeSetting='5 mins', whatToShow='TRADES', useRTH=True)
if not data:
raise RuntimeError('HSI 数据接口返回空.')
sql = 'insert into `hsi_5m` (`date`, `open`, `high`, `low`, `close`) values '
for bar_data in data:
date = bar_data.date
open_price = bar_data.open
high = bar_data.high
low = bar_data.low
close = bar_data.close
sql += "('{date}', {open:.4f}, {high:.4f}, {low:.4f}, {close:.4f}),".format(date=date, open=open_price, high=high, low=low, close=close)
res = self.db.query(sql.rstrip(','))
if res.rowcount == 0:
raise RuntimeError('SQL 语句执行异常， 插入数据库失败：%s' % sql)
else:
print('HSI Index 1个月5分钟数据导入完成.', flush=True)
class Live(IB):
def __init__(self,
symbol,
temp,
client,
verbose=False,
notification=False):
self.symbol = symbol
instruments = pd.read_csv('instruments.csv').set_index('symbol')
params = instruments.loc[self.symbol]
self.market = str(params.market)
self.exchange = str(params.exchange)
self.temp = temp
self.tick_size = float(params.tick_size)
self.digits = int(params.digits)
self.leverage = int(params.leverage)
self.client = client
self.verbose = verbose
self.notification = notification
self.ib = IB()
print(self.ib.connect('127.0.0.1', 7497, client))
self.get_contract()
self.data = self.download_data(tempo=self.temp, duration='1 D')
self.current_date()
self.pool = pd.DataFrame(columns=[
'date', 'id', 'type', 'lots', 'price', 'S/L', 'T/P', 'commission',
'comment', 'profit'
])
self.history = pd.DataFrame(columns=[
'date', 'id', 'type', 'lots', 'price', 'S/L', 'T/P', 'commission',
'comment', 'profit'
])
self.pending = pd.DataFrame(columns=[
'date', 'id', 'type', 'lots', 'price', 'S/L', 'T/P', 'commission',
'comment', 'profit'
])
self.position = 0
self.number = 0
def get_contract(self):
if self.market == 'futures':
expiration = self.ib.reqContractDetails(
Future(self.symbol,
self.exchange))[0].contract.lastTradeDateOrContractMonth
self.contract = Future(symbol=self.symbol,
exchange=self.exchange,
lastTradeDateOrContractMonth=expiration)
elif self.market == 'forex':
self.contract = Forex(self.symbol)
elif self.market == 'stocks':
self.contract = Stock(symbol=self.symbol,
exchange=self.exchange,
currency='USD')
def download_data(self, tempo, duration):
pr = (lambda mark: 'TRADES' if mark == 'futures' else
('TRADES' if mark == 'stocks' else 'MIDPOINT'))(self.market)
historical = self.ib.reqHistoricalData(self.contract,
endDateTime='',
durationStr=duration,
barSizeSetting=tempo,
whatToShow=pr,
useRTH=True,
keepUpToDate=True)
return historical
def data_to_df(self, data):
df = util.df(data)[['date', 'open', 'high', 'low', 'close',
'volume']].set_index('date')
df.index = pd.to_datetime(df.index)
return df
def send_telegram_message(self, msg):
'''Sends a telegram message
'''
requests.post(
'https://api.telegram.org/bot804823606:AAFq-YMKr4hIjQ4N5M8GYCGa5w9JJ1kIunk/sendMessage',
data={
'chat_id': '@ranguito_channel',
'text': msg
})
def current_date(self):
self.date = datetime.now().strftime('%Y-%m-%d')
self.weekday = datetime.now().weekday()
self.hour = datetime.now().strftime('%H:%M:%S')
def pool_check(self):
'''Check pool trades'''
if self.position == 0:
self.pool = pd.DataFrame(columns=[
'date', 'type', 'lots', 'price', 'S/L', 'T/P', 'commission',
'comment', 'profit'
])
def calculate_profit(self, type, price, lots):
'''Calculates profit'''
if type == 'BUY':
profit = (lambda pos: 0
if pos >= 0 else (self.pool[self.pool.type == 'SELL'])[
'price'].iloc[0] - price)(self.position)
else:
profit = (lambda pos: 0 if pos <= 0 else price -
(self.pool[self.pool.type == 'BUY'])['price'].iloc[0])(
self.position)
return profit * self.leverage * lots
def order_values(self, order_id):
price = 0
commission = 0
if len(self.ib.fills()) > 0:
for trade in util.tree(self.ib.fills()):
if ('OrderId' and 'clientId') in trade[1]['Execution']:
if ((nested_lookup('orderId', trade)[0] == order_id) and
(nested_lookup('clientId', trade)[0] == self.client)):
commission = nested_lookup('commission', trade)[0]
price = nested_lookup('price', trade)[0]
return (price, commission)
def order_send(self, type, lots, sl=0, tp=0, comment=''):
market_order = MarketOrder(type, lots)
#initial_margin, maintenance_margin = self.get_margins(market_order)
self.ib.placeOrder(self.contract, market_order)
id = market_order.orderId
self.number += 1
price = 0
while price == 0:
self.ib.sleep(1)
price, commission = self.order_values(id)
profit = self.calculate_profit(type, price, lots)
trade = {
'date': str(self.date) + ' ' + str(self.hour),
'id': id,
'type': type,
'lots': lots,
'price': price,
'S/L': sl,
'T/P': tp,
'commission': commission,
'comment': comment,
'profit': profit
}
self.save_trade(trade)
self.pool = pd.concat(
[self.pool, pd.DataFrame(trade, index=[self.number])], sort=False)
self.history = pd.concat(
[self.history,
pd.DataFrame(trade, index=[self.number])],
sort=False)
mult = (lambda dir: 1 if dir == 'BUY' else -1)(type)
self.position += (mult * lots)
self.pool_check()
if self.verbose:
print('%s %s | %sING %d units at %5.2f in %s' % (str(
self.date), str(self.hour), type, lots, price, self.symbol))
if self.notification:
if self.position != 0:
self.send_message_in(type, price, sl, tp, lots)
else:
self.send_message_out(type, price, lots, profit, commission,
commission)
def bracket_stop_order(self,
type,
lots,
entry_price,
sl=0,
tp=0,
comment=''):
bracket_order = self.ib.bracketStopOrder(type, lots, entry_price, tp,
sl)
#initial_margin, maintenance_margin = self.get_margins(bracket_order[0])
for order in bracket_order:
self.ib.placeOrder(self.contract, order)
id_entry = bracket_order[0].orderId
id_tp = bracket_order[1].orderId
id_sl = bracket_order[2].orderId
trade = {
'date': str(self.date) + ' ' + str(self.hour),
'id': id_entry,
'type': bracket_order[0].action,
'lots': lots,
'price': entry_price,
'S/L': sl,
'T/P': tp,
'commission': 0,
'comment': comment,
'profit': 0
}
self.pending = pd.concat(
[self.pending, pd.DataFrame(trade, index=[id_entry])], sort=False)
trade = {
'date': str(self.date) + ' ' + str(self.hour),
'id': id_tp,
'type': bracket_order[1].action,
'lots': lots,
'price': tp,
'S/L': 0,
'T/P': 0,
'commission': 0,
'comment': comment,
'profit': 0
}
self.pending = pd.concat(
[self.pending, pd.DataFrame(trade, index=[id_entry])], sort=False)
trade = {
'date': str(self.date) + ' ' + str(self.hour),
'id': id_sl,
'type': bracket_order[2].action,
'lots': lots,
'price': sl,
'S/L': 0,
'T/P': 0,
'commission': 0,
'comment': comment,
'profit': 0
}
self.pending = pd.concat(
[self.pending, pd.DataFrame(trade, index=[id_entry])], sort=False)
return (bracket_order[0], bracket_order[1], bracket_order[2])
def pending_check(self, order):
id = order.orderId
if len(self.pending) > 0:
price, commission = self.order_values(id)
if price > 0:
self.number += 1
order_select = self.pending[self.pending.id == id]
profit = self.calculate_profit(order_select.type.iloc[0],
price,
order_select.lots.iloc[0])
trade = {
'date': str(self.date) + ' ' + str(self.hour),
'id': id,
'type': order_select.type.iloc[0],
'lots': order_select.lots.iloc[0],
'price': price,
'S/L': order_select['S/L'].iloc[0],
'T/P': order_select['T/P'].iloc[0],
'commission': commission,
'comment': '',
'profit': profit
}
self.save_trade(trade)
self.pool = pd.concat(
[self.pool,
pd.DataFrame(trade, index=[self.number])],
sort=False)
self.history = pd.concat(
[self.history,
pd.DataFrame(trade, index=[self.number])],
sort=False)
mult = (lambda dir: 1
if dir == 'BUY' else -1)(order_select.type.iloc[0])
self.position += (mult * order_select.lots.iloc[0])
self.pool_check()
if self.verbose:
print('%s %s | %sING %d units at %5.2f in %s' %
(str(self.date), str(
self.hour), order_select.type.iloc[0],
order_select.lots.iloc[0], price, self.symbol))
if self.notification:
if self.position != 0:
self.send_message_in(order_select.type.iloc[0], price,
order_select['S/L'].iloc[0],
order_select['T/P'].iloc[0],
order_select.lots.iloc[0])
else:
self.send_message_out(order_select.type.iloc[0], price,
order_select.lots.iloc[0],
profit, commission, commission)
return True
else:
return False
def get_margins(self, order):
init_margin = float(
self.ib.whatIfOrder(self.contract, order).initMarginChange)
maint_margin = float(
self.ib.whatIfOrder(self.contract, order).maintMarginChange)
return (init_margin, maint_margin)
def send_message_in(self, type, price_in, sl, tp, lots):
msg_in = '%s Opened in %s \nPrice: %5.2f \nS/L: %5.2f \nT/P: %5.2f \nLots: %d \nAt: %s' % (
type, self.symbol, price_in, sl, tp, lots, self.hour)
self.send_telegram_message(msg_in)
def send_message_out(self, type, price_out, lots, profit, comm_in,
comm_out):
msg_out = '%s Closed in %s \nPrice: %5.2f \nProfit(USD): %5.2f \nCommissions(USD): %5.2f \nAt: %s' % \
(type, self.symbol, price_out, profit, (comm_in+comm_out),self.hour)
self.send_telegram_message(msg_out)
def save_trade(self, trade):
if not path.exists('history_trades_%s.csv' % self.symbol):
initial = pd.DataFrame(columns=[
'date', 'id', 'type', 'lots', 'price', 'S/L', 'T/P',
'commission', 'comment', 'profit'
]).set_index('date')
initial.to_csv('history_trades_%s.csv' % self.symbol)
history = pd.read_csv('history_trades_%s.csv' % self.symbol)
trade = pd.DataFrame(trade, index=[0])
history = pd.concat([history, trade], sort=False)
history['net profit'] = history['profit'] - history['commission']
history['accumulated profit'] = history['net profit'].cumsum()
history['max profit'] = history['accumulated profit'].cummax()
history.set_index('date').to_csv('history_trades_%s.csv' % self.symbol)
class LiveTrading(MethodManager_):
def __init__(self, strat_name, client_id, runtime_tm, debugging, manager_,
heartbeat_q, traded_instr):
self.strat_name = strat_name
self.client_id = client_id
self.runtime_tm = runtime_tm
self.debugging = debugging
self.manager_ = manager_
self.heartbeat_q = heartbeat_q
self.traded_instr = traded_instr
self.account_curr = ACCOUNT_CURR
self.tax_rate_account_country = TAX_RATE_ACCOUNT_COUNTRY
self.simult_reqs_interval = SIMULT_REQS_INTERVAL
self.potential_mkt_data_lines_already_in_use = POTENTIAL_MKT_DATA_LINES_ALREADY_IN_USE
self.ib = IB()
# self.ib.setCallback('error', self.on_ib_error)
self.ib.errorEvent += self.on_ib_error
self.err_ = None
self.report = Reporting(self)
self.cash = CashManagement(debugging)
self.hlprs = ClientSharedMemory()
self.access_type = 'tws'
if self.access_type == 'gateway':
self.__port = 4001
elif self.access_type == 'tws':
self.__port = 7497
self.__host = '127.0.0.1'
self.ib.connect(self.__host, self.__port, clientId=self.client_id)
self.portfolio = []
self.portfolio_instr = []
self.cnt_trades_per_instr_per_day = {}
self.req_tracker = {
'total': 0,
'open_market_data_reqs': 0,
'open_market_data_lines': 0,
'hist_data_prior_time': None
}
self.start_cet = datetime.datetime.now()
self.manager_[
'active_mkt_data_lines'] = POTENTIAL_MKT_DATA_LINES_ALREADY_IN_USE
self.funda_data_req_max = IB_PACING['funda_data_reqs']['reqs']
if self.debugging.get_meths:
self.print_meths(str(self.__class__.__name__), dir(self))
_inst_ = self
self.fin_ratios = FinRatios(_inst_)
@staticmethod
def us_tz_op(dt_obj):
"""
Converting time
:param dt_obj: datetime obj
:return: Eastern datetime
"""
# log_start = datetime.datetime.now()
if not isinstance(dt_obj, datetime.datetime):
raise TypeError
if dt_obj.year == 1900:
curr_year = datetime.datetime.now().year
else:
curr_year = dt_obj.year
# http://www.webexhibits.org/daylightsaving/b2.html
dst = {
2018: [[3, 11], [11, 4]],
2019: [[3, 10], [11, 3]],
2020: [[3, 8], [11, 1]]
}
window = dst[curr_year]
#disclaimer
kind_of_difference = HOUR_DAY_BOUNDARY_FAIL_CHECK
if dt_obj.hour < kind_of_difference:
raise Exception("determination difficult, try later in the day")
dst_start = datetime.datetime(curr_year, window[0][0], window[0][1])
dst_end = datetime.datetime(curr_year, window[1][0], window[1][1])
if dt_obj > dst_start and dt_obj < dst_end:
utc2est = -4
else:
utc2est = -5
this_tz_from_uts = '+0100'
if time.strftime("%z", time.gmtime()) != this_tz_from_uts:
raise exceptions_.WrongTimeZone(
'Wrong time zone, code is fixed to Danish winter time, might have to be adjusted'
)
cet2utc = -2
dt_obj_utc = dt_obj + datetime.timedelta(
hours=cet2utc) #.replace(tzinfo = datetime.timezone.utc)
dt_obj_est = dt_obj_utc + datetime.timedelta(hours=utc2est)
# logging = rk_logging.Logging()
# logging.log(
# runtime_tm, log_start, str('' + ',' + sys._getframe().f_code.co_name)
# ,dt_obj_utc
# ,dt_obj_est
# )
return dt_obj_est
def _manipulated_time(self, cet_in):
delta = cet_in - self.start_cet
current_manipulated_time = datetime.datetime(
self.start_cet.year, self.start_cet.month, self.start_cet.day,
self.debugging.dummy_hour, self.debugging.dummy_minute,
self.debugging.dummy_second)
current_manipulated_time += delta
return current_manipulated_time
def buy(self, ticker, rank, size, order_type):
log_start = datetime.datetime.now()
log = logging_.Logging(
self.runtime_tm, log_start,
str(self.__class__.__name__ + ',' +
sys._getframe().f_code.co_name))
self.hlprs.add_to_manager(self.strat_name, *log.monitor())
order_log_msg = None
symbol = ticker.contract.symbol
if self._ticker_len_n_type_check(ticker.domBids) > 1:
offer_price = ticker.domBids[rank].price
# offer_size = ticker.domBids[rank].size
else:
offer_price = ticker.domBids.price
# offer_size = ticker.domBids.size
cnt = 0
max_order_filled_cnts = int(ORDER_CANCEL_IF_NOT_FILLED_SECS /
ORDER_FILLED_CHECKED_CYCLE_SECS)
if self.debugging.dummy_data:
order_success = True
else:
if order_type == 'MKT':
order = MarketOrder('BUY', size)
trade = self.ib.placeOrder(ticker.contract, order)
while cnt < max_order_filled_cnts: # a bit complicated but it does actually make sense
order_log_msg = trade.log
self.ib.sleep(ORDER_FILLED_CHECKED_CYCLE_SECS)
cnt += 1
if not trade.orderStatus.status != 'Filled':
# PendingSubmit = 'PendingSubmit'
# PendingCancel = 'PendingCancel'
# PreSubmitted = 'PreSubmitted'
# Submitted = 'Submitted'
# ApiPending = 'ApiPending' # undocumented, can be returned from req(All)OpenOrders
# ApiCancelled = 'ApiCancelled'
# Cancelled = 'Cancelled'
# Filled = 'Filled'
# Inactive = 'Inactive'
order_success = True
break
else:
self.ib.cancelOrder(trade)
# while not trade.isDone():
# print("not sure if this makes sense")
# self.ib.waitOnUpdate()
elif order_type == 'LMT':
raise Exception("order type not defined")
else:
raise Exception("order type not defined")
if order_success:
if self.debugging.dummy_time:
_now = self._manipulated_time(datetime.datetime.now())
else:
_now = datetime.datetime.now()
filled_tm = self.us_tz_op(_now)
status = 0
self.portfolio.append([symbol, filled_tm, offer_price, size])
self.hlprs.add_to_manager(self.strat_name, 'portfolio',
self.portfolio)
self.portfolio_instr.append(symbol)
# self.add_to_monitor('portfolio_instr', 'self.portfolio_instr')
print('not sure if this works')
self.cnt_trades_per_instr_per_day[ticker.contract.symbol] += 1
self.hlprs.add_to_manager(self.strat_name,
'cnt_trades_per_instr_per_day',
self.cnt_trades_per_instr_per_day)
self.heartbeat_q.put([
self.strat_name, 'cnt_trades_per_instr_per_day',
self.cnt_trades_per_instr_per_day
])
self.hlprs.add_to_manager(
self.strat_name, 'cap_usd',
self.cash.available_funds(self.report.pnl(),
self.account_curr))
else:
status = 1
log.log(self.portfolio, self.portfolio_instr,
self.cnt_trades_per_instr_per_day, order_log_msg)
return status
def sell(self, ticker, rank, order_type):
log_start = datetime.datetime.now()
log = logging_.Logging(
self.runtime_tm, log_start,
str(self.__class__.__name__ + ',' +
sys._getframe().f_code.co_name))
self.hlprs.add_to_manager(self.strat_name, *log.monitor())
order_log_msg = None
symbol = ticker.contract.symbol
try:
ix = self.portfolio_instr.index(symbol)
except ValueError:
status = -1
print(
'not quite sure why this error sometimes occurs and if this is maybe to early to leave?'
)
return status
# if isinstance(ticker.domBids, str) == True:
# offer_price = ticker.domAsks.price
# offer_size = ticker.domAsks.size
# else:
# offer_price = ticker.domAsks[rank].price
# offer_size = ticker.domAsks[rank].size
price_ix = 2
size_ix = 3
# held_price = self.held[ix][price_ix]
held_size = self.portfolio[ix][size_ix]
cnt = 0
max_order_filled_cnts = int(ORDER_CANCEL_IF_NOT_FILLED_SECS /
ORDER_FILLED_CHECKED_CYCLE_SECS)
if not self.debugging.dummy_data:
if order_type == 'MKT':
order = MarketOrder('SELL', held_size)
# https://github.com/erdewit/ib_insync/blob/master/notebooks/ordering.ipynb
trade = self.ib.placeOrder(ticker.contract, order)
while cnt < max_order_filled_cnts:
order_log_msg = trade.log
self.ib.sleep(ORDER_FILLED_CHECKED_CYCLE_SECS)
cnt += 1
if trade.orderStatus.status == 'Filled':
order_success = True
break
self.ib.cancelOrder(trade)
while not trade.isDone():
print("not sure if this makes sense")
self.ib.waitOnUpdate()
elif order_type == 'LMT':
raise Exception("order type not defined")
else:
raise Exception("order type not defined")
else:
order_success = True
order_success = True
if order_success:
status = 0
del self.portfolio[ix]
self.hlprs.add_to_manager(self.strat_name, 'portfolio',
self.portfolio)
del self.portfolio_instr[ix]
# self.add_to_monitor('portfolio_instr', self.portfolio_instr)
print('not sure if this works')
self.cnt_trades_per_instr_per_day[ticker.contract.symbol] += 1
self.hlprs.add_to_manager(self.strat_name,
'cnt_trades_per_instr_per_day',
self.cnt_trades_per_instr_per_day)
self.heartbeat_q.put([
self.strat_name, 'cnt_trades_per_instr_per_day',
self.cnt_trades_per_instr_per_day
])
self.hlprs.add_to_manager(
self.strat_name, 'cap_usd',
self.cash.available_funds(self.report.pnl(),
self.account_curr))
else:
status = 1
log.log(self.portfolio, self.portfolio_instr,
self.cnt_trades_per_instr_per_day, order_log_msg)
return status
@staticmethod
def _ticker_len_n_type_check(bid_or_ask_li):
# log_start = datetime.datetime.now()
n_ticks = len(bid_or_ask_li) if isinstance(bid_or_ask_li,
str) == False else 1
# log = rk_logging.Logging()
# log.log(
# self.runtime_tm, log_start, str('' + ',' + sys._getframe().f_code.co_name)
# )
return n_ticks
def req_handling(self, ticker, type_):
log_start = datetime.datetime.now()
log = logging_.Logging(
self.runtime_tm, log_start,
str(self.__class__.__name__ + ',' +
sys._getframe().f_code.co_name))
self.hlprs.add_to_manager(self.strat_name, *log.monitor())
# unix_ts = int(time.time())
self.req_tracker['total'] += 1
self.req_tracker['open_market_data_reqs'] += 1
self.req_tracker['open_market_data_lines'] += 1
# status = -1 means immediately kill connections
status = self.pacing_violations(type_)
log.log()
if status == -1:
print('get connections here')
# do sth
return
elif status == 0:
return
def req_handler(self, toggle):
if toggle == 'increase':
self.manager_['active_mkt_data_lines'] += 1
elif toggle == 'decrease':
self.manager_['active_mkt_data_lines'] -= 1
else:
raise Exception('not defined')
def req_mkt_dpt_ticker_(self, contract_):
_cnt_ = 0
status = 1
while _cnt_ < N_TRIES_IF_SIMULT_REQS:
if self.manager_['active_mkt_data_lines'] < IB_PACING[
'mkt_data_lines']:
self.req_handler('increase')
ticker = self.ib.reqMktDepth(contract_)
self.ib.sleep(
SIMULT_REQS_INTERVAL
) # wait here because ticker needs updateEvent might not be fast enough
else:
self.ib.sleep(
SIMULT_REQS_INTERVAL
) # wait here because ticker needs updateEvent might not be fast enough
_cnt_ += 1
continue
if self.err_ != exceptions_.IbPacingError:
status = 0
break
return ticker, status
def cancel_mkt_dpt_ticker_(self, contract_):
self.ib.cancelMktDepth(contract_)
self.req_handler('decrease')
@staticmethod
def _get_ib_pacing():
return IB_PACING
def pacing_violations(self, type_):
log_start = datetime.datetime.now()
log = logging_.Logging(
self.runtime_tm, log_start,
str(self.__class__.__name__ + ',' +
sys._getframe().f_code.co_name))
self.hlprs.add_to_manager(self.strat_name, *log.monitor())
# histData, mktDepth, scannerData
# TODO: far from done here, continue at some point
status = 0
if type_ == 'histData':
if self.req_tracker[
'total'] == 1: #first time is already incremented
self.req_tracker['hist_data_prior_time'] = int(time.time())
status = 0
elif self.req_tracker['total'] > 1 and self.req_tracker[
'open_market_data_lines'] < MARKET_DATA_LINES:
status = 0
elif self.req_tracker['total'] > 1 \
and self.req_tracker['open_market_data_lines'] == MARKET_DATA_LINES \
and int(time.time()) - self.req_tracker['hist_data_prior_time'] >= IB_PACING['hist_data_similar']['secs']:
print('CRITICAL: market data lines limit reached')
status = -1
elif type_ == 'mktDepth':
status = 0
elif type_ == 'scannerData':
status = 0
log.log(status, self.req_tracker)
self.hlprs.add_to_manager(self.strat_name, *log.monitor())
return status
def check_network_requirements(self):
# s = socket.socket()
# #e.g.
# address, port = '10.8.8.19', '53141'
# address, port = '208.245.107.3', '4000'
# try:
# s.connect((address, port))
# return True
# except socket.error:
# return False
# #or
# rows = []
# lc = psutil.net_connections('inet')
# for c in lc:
# (ip, port) = c.laddr # 0.0.0.0
# if ip == '10.8.8.19': # or ip == '::'
# if c.type == socket.SOCK_STREAM and c.status == psutil.CONN_LISTEN:
# proto_s = 'tcp'
# elif c.type == socket.SOCK_DGRAM:
# proto_s = 'udp'
# else:
# continue
# pid_s = str(c.pid) if c.pid else '(unknown)'
# msg = 'PID {} is listening on port {}/{} for all IPs.'
# msg = msg.format(pid_s, port, proto_s)
# print(msg)
status = True
if not status:
raise Exception('cannot connect to all necessary servers')
#
def on_ib_error(self, reqId, errorCode, errorString, errorSomething):
"""
https://groups.io/g/insync/topic/how_to_capture_error_trapped/7718294?p=,,,20,0,0,0::recentpostdate%2Fsticky,,,20,1,80,7718294
"""
max_n_mkt_depth_reqs = 309 # ERROR:ib_insync.wrapper:Error 309, reqId 39: Max number (3) of market depth requests has been reached, contract: Stock(symbol='PETZ', exchange='ISLAND', currency='USD')
if errorCode == max_n_mkt_depth_reqs:
self.err_ = exceptions_.IbPacingError
lista2.append(contract.localSymbol)
lista2.append(contract.lastTradeDateOrContractMonth)
lista1.append(lista2)
lista1.sort(key=lambda x: x[2])
futuros2 = lista1[:primerosN]
'''MEJORAR: Estoy dando por supuesto que los N primeros de las dos listas corresponden a los mismos meses'''
'''Esto no será siempre cierto, hay que mejorar este proceso para que tenga en cuenta los meses'''
df = pd.DataFrame(columns=('MES', 'CL', 'BZ', 'DIFF1', 'DIFF2', 'DIF'))
midF1ant = 0
midF2ant = 0
for i in range(0, len(futuros1)):
contract = Future(localSymbol=futuros1[i][1], exchange=exchange1)
ticker = ib.reqMktData(contract)
ib.sleep(2)
ib.cancelMktData(contract)
midF1 = round((ticker.bid + ticker.ask) / 2, 3)
if i == 0:
difF1 = 0
else:
difF1 = midF1 - midF1ant
midF1ant = midF1
contract = Future(localSymbol=futuros2[i][1], exchange=exchange2)
ticker = ib.reqMktData(contract)
ib.sleep(2)
ib.cancelMktData(contract)
midF2 = round((ticker.bid + ticker.ask) / 2, 3)
if i == 0:
difF2 = 0
def stop(self):
self._logger.info('Stopping mywatchdog')
try:
loop = asyncio.get_event_loop()
# for i,t in enumerate(asyncio.Task.all_tasks(loop)):
# self._logger.info(f'task: {i}')
# t.cancel()
# self._logger.info('Now stopping loop')
# loop.close()
# self._logger.info('loop stopped')
# self.s1.remove()
except:
pass
for i, (scheduler, schedules) in enumerate(self.schedulerList):
# when the network is down, the system tries to reconnect and does not succeed.
# but the list of jobs is already empty (because it was emptied during the shutdown process)
# therefore, we need to get new jobdict information only if there are jobs in the scheduler
if isinstance(scheduler, AsyncIOScheduler) and scheduler.running:
if len(scheduler.get_jobs()) > 0:
schedules = []
for job in scheduler.get_jobs():
if isinstance(job.trigger,
apscheduler.triggers.cron.CronTrigger):
jobdict = {
'func': job.func,
'args': job.args,
'kwargs': job.kwargs,
'id': job.id,
'misfire_grace_time': job.misfire_grace_time,
'coalesce': job.coalesce,
'max_instances': job.max_instances,
'next_run_time': job.next_run_time,
'jobstore': job._jobstore_alias,
'trigger': 'cron'
}
for f in job.trigger.fields:
curval = str(f)
jobdict[f.name] = curval
pass
pass
schedules.append(jobdict)
pass
job.remove()
pass
pass
pass
self.schedulerList[i][1] = schedules
self._logger.info(f'scheduler: {scheduler} {type(scheduler)}')
if isinstance(scheduler, AsyncIOScheduler) and scheduler.running:
self._logger.info(
f'scheduler: {scheduler}, {scheduler.running}')
IB.sleep(2)
scheduler.shutdown(wait=False)
pass
self._logger.info('Stopped mywatchdog')
self._logger.info('Start Scheduler List for mywatchdog')
for scheduler, schedules in self.schedulerList:
self._logger.info(
f'mywatchdog: scheduler: {scheduler}, {type(scheduler)}')
if isinstance(scheduler, AsyncIOScheduler) and scheduler.running:
for schedule in schedules:
self._logger.info(f'mywatchdog: schedule: {schedule}')
pass
pass
pass
self._logger.info('End Scheduler List for mywatchdog')
self.ib.disconnect()
self.controller.terminate()
class trade_ES():
def __init__(self):
self.ib = IB()
self.ib.connect('127.0.0.1',
7497,
clientId=np.random.randint(10, 1000))
self.tickers_ret = {}
self.endDateTime = ''
self.No_days = '43200 S'
self.interval = '30 secs'
self.tickers_signal = "Hold"
self.ES = Future(symbol='ES',
lastTradeDateOrContractMonth='20200619',
exchange='GLOBEX',
currency='USD')
self.ib.qualifyContracts(self.ES)
self.ES_df = self.ib.reqHistoricalData(contract=self.ES,
endDateTime=self.endDateTime,
durationStr=self.No_days,
barSizeSetting=self.interval,
whatToShow='TRADES',
useRTH=False,
keepUpToDate=True)
self.tickers_ret = []
self.options_ret = []
self.option = {'call': FuturesOption, 'put': FuturesOption}
self.options_history = {}
self.trade_options = {'call': [], 'put': []}
self.price = 0
self.i = -1
self.ES_df.updateEvent += self.make_clean_df
self.Buy = True
self.Sell = False
self.ib.positionEvent += self.order_verify
self.waitTimeInSeconds = 220
self.tradeTime = 0
self.mySemaphore = asyncio.Semaphore(1)
def run(self):
self.make_clean_df(self.ES_df)
def next_exp_weekday(self):
weekdays = {2: [6, 0], 4: [0, 1, 2], 0: [3, 4]}
today = datetime.date.today().weekday()
for exp, day in weekdays.items():
if today in day:
return exp
def next_weekday(self, d, weekday):
days_ahead = weekday - d.weekday()
if days_ahead <= 0: # Target day already happened this week
days_ahead += 7
date_to_return = d + datetime.timedelta(
days_ahead) # 0 = Monday, 1=Tuself.ESday, 2=Wednself.ESday...
return date_to_return.strftime('%Y%m%d')
def get_strikes_and_expiration(self):
expiration = self.next_weekday(datetime.date.today(),
self.next_exp_weekday())
chains = self.ib.reqSecDefOptParams(underlyingSymbol='ES',
futFopExchange='GLOBEX',
underlyingSecType='FUT',
underlyingConId=self.ES.conId)
chain = util.df(chains)
strikes = chain[chain['expirations'].astype(str).str.contains(
expiration)].loc[:, 'strikes'].values[0]
[ESValue] = self.ib.reqTickers(self.ES)
ES_price = ESValue.marketPrice()
strikes = [
strike for strike in strikes
if strike % 5 == 0 and ES_price - 10 < strike < ES_price + 10
]
return strikes, expiration
def get_contract(self, right, net_liquidation):
strikes, expiration = self.get_strikes_and_expiration()
for strike in strikes:
contract = FuturesOption(symbol='ES',
lastTradeDateOrContractMonth=expiration,
strike=strike,
right=right,
exchange='GLOBEX')
self.ib.qualifyContracts(contract)
self.price = self.ib.reqMktData(contract, "", False, False)
if float(self.price.last) * 50 >= net_liquidation:
continue
else:
return contract
def make_clean_df(self, ES_df, hashbar=None):
ES_df = util.df(ES_df)
ES_df['RSI'] = ta.RSI(ES_df['close'])
ES_df['macd'], ES_df['macdsignal'], ES_df['macdhist'] = ta.MACD(
ES_df['close'], fastperiod=12, slowperiod=26, signalperiod=9)
ES_df['MA_9'] = ta.MA(ES_df['close'], timeperiod=9)
ES_df['MA_21'] = ta.MA(ES_df['close'], timeperiod=21)
ES_df['MA_200'] = ta.MA(ES_df['close'], timeperiod=200)
ES_df['EMA_9'] = ta.EMA(ES_df['close'], timeperiod=9)
ES_df['EMA_21'] = ta.EMA(ES_df['close'], timeperiod=21)
ES_df['EMA_200'] = ta.EMA(ES_df['close'], timeperiod=200)
ES_df['ATR'] = ta.ATR(ES_df['high'], ES_df['low'], ES_df['close'])
ES_df['roll_max_cp'] = ES_df['high'].rolling(20).max()
ES_df['roll_min_cp'] = ES_df['low'].rolling(20).min()
ES_df['roll_max_vol'] = ES_df['volume'].rolling(20).max()
ES_df.dropna(inplace=True)
self.loop_function(ES_df)
def placeOrder(self, contract, order):
trade = self.ib.placeOrder(contract, order)
tradeTime = datetime.datetime.now()
return ([trade, contract, tradeTime])
def sell(self, contract, position):
self.ib.qualifyContracts(contract)
if position.position > 0:
order = 'Sell'
else:
order = 'Buy'
marketorder = MarketOrder(order, abs(position.position))
marketTrade, contract, tradeTime = self.placeOrder(
contract, marketorder)
while self.ib.position.position != 0:
self.ib.sleep(1)
self.mySemaphore.release()
async def buy(self, contract):
await self.semaphore.acquire()
self.ib.qualifyContracts(contract)
marketorder = MarketOrder('Buy', 1)
marketTrade = self.ib.placeOrder(contract, marketorder)
def order_verify(self, order):
if order.position == 0.0 or order.position < 0:
self.Buy = True
self.Sell = False
elif order.position > 0:
self.Buy = False
self.Sell = True
else:
self.Buy = False
self.Sell = False
print(f'Buy= {self.Buy}, sell = {self.Sell}')
def loop_function(self, ES_df):
df = ES_df[[
'high', 'low', 'volume', 'close', 'RSI', 'ATR', 'roll_max_cp',
'roll_min_cp', 'roll_max_vol', 'EMA_9', 'EMA_21', 'macd',
'macdsignal'
]]
if self.tickers_signal == "Hold":
print('Hold')
if df["high"].iloc[self.i] >= df["roll_max_cp"].iloc[self.i] and \
df["volume"].iloc[self.i] > df["roll_max_vol"].iloc[self.i - 1] and df['RSI'].iloc[self.i] > 30 \
and df['macd'].iloc[self.i] > df['macdsignal'].iloc[self.i] :
self.tickers_signal = "Buy"
return
elif df["low"].iloc[self.i] <= df["roll_min_cp"].iloc[self.i] and \
df["volume"].iloc[self.i] > df["roll_max_vol"].iloc[self.i - 1] and df['RSI'].iloc[self.i] < 70 \
and df['macd'].iloc[self.i] < df['macdsignal'].iloc[self.i]:
self.tickers_signal = "Sell"
return
else:
self.tickers_signal = "Hold"
return
elif self.tickers_signal == "Buy":
print('BUY SIGNAL')
if df["close"].iloc[self.i] > df["close"].iloc[self.i - 1] - (
0.75 * df["ATR"].iloc[self.i - 1]) and len(
self.ib.positions()) != 0:
print(
f'{df["close"].iloc[self.i]} > {df["close"].iloc[self.i - 1] - (0.75 * df["ATR"].iloc[self.i - 1])}'
)
print('first buy condition')
positions = self.ib.positions()
for position in positions:
if position.contract.right == 'C':
self.sell(position.contract, position)
self.tickers_signal = "Hold"
return
elif df["low"].iloc[self.i] <= df["roll_min_cp"].iloc[self.i] and \
df["volume"].iloc[self.i] > df["roll_max_vol"].iloc[self.i - 1] and df['RSI'].iloc[self.i] < 70 \
and df['macd'].iloc[self.i] < df['macdsignal'].iloc[self.i] and len(self.ib.positions())!=0:
self.tickers_signal = "Sell"
print('sell')
positions = self.ib.positions()
for position in positions:
if position.contract.right == 'C':
self.sell(position.contract, position)
self.tickers_signal == "Sell"
return
else:
if len(self.ib.positions()) == 0:
self.option['call'] = self.get_contract(
right="C", net_liquidation=2000)
self.buy(self.option['call'])
self.tickers_signal = "Hold"
else:
self.tickers_signal = "Hold"
elif self.tickers_signal == "Sell":
print('SELL SIGNAL')
if df["close"].iloc[self.i] < df["close"].iloc[self.i - 1] + (
0.75 * df["ATR"].iloc[self.i - 1]) and len(
self.ib.positions()) != 0:
print('first sell condition')
print(
f'{df["close"].iloc[self.i]} < {df["close"].iloc[self.i - 1] - (0.75 * df["ATR"].iloc[self.i - 1])}'
)
print('sell')
positions = self.ib.positions()
for position in positions:
if position.contract.right == 'P':
self.sell(position.contract, position)
self.tickers_signal = "Hold"
return
elif df["high"].iloc[self.i] >= df["roll_max_cp"].iloc[self.i] and \
df["volume"].iloc[self.i] > df["roll_max_vol"].iloc[self.i - 1] and df['RSI'].iloc[self.i] > 30 \
and df['macd'].iloc[self.i] > df['macdsignal'].iloc[self.i] and len(self.ib.positions())!=0:
self.tickers_signal = "Buy"
print('sell')
positions = self.ib.positions()
for position in positions:
if position.contract.right == 'P':
self.sell(position.contract, position)
self.tickers_signal == "Buy"
return
else:
if len(self.ib.positions()) == 0:
self.option['put'] = self.get_contract(
right="P", net_liquidation=2000)
self.buy(self.option['put'])
self.tickers_signal = "Hold"
else:
self.tickers_signal = "Hold"
def checkError(self, errCode, errString):
print('Error Callback', errCode, errString)
if errCode == 2104:
print('re-connect after 5 secs')
self.ib.sleep(5)
self.ib.disconnect()
self.ib.connect('127.0.0.1',
7497,
clientId=np.random.randint(10, 1000))
self.make_clean_df(self.ES)
class request(IB):
def __init__(self, symbol, temp, client):
self.symbol = symbol
self.temp = temp
instruments = pd.read_csv('instruments.csv').set_index('symbol')
self.params = instruments.loc[self.symbol]
self.market = str(self.params.market)
self.exchange = str(self.params.exchange)
self.tick_size = float(self.params.tick_size)
self.digits = int(self.params.digits)
self.leverage = int(self.params.leverage)
self.client = client
self.current_date()
self._sundays_activation()
self.ib = IB()
print(self.ib.connect('127.0.0.1', 7497, self.client))
self.connected = self.ib.isConnected() #######
self.get_contract()
self.interrumption = False
#self.data = self.download_data(tempo=temp, duration='1 D')
#self.ib.reqMktData(self.contract, '', False, False); self.ticker = self.ib.ticker(self.contract) #########
#self.ticker = self.ib.reqTickByTickData(self.contract, 'Last', 0)
self.bars = self.ib.reqRealTimeBars(self.contract, 5, 'MIDPOINT',
False)
self.operable = True
def operable_schedule(self):
if self.weekday == 4 and pd.to_datetime(
self.hour).time() > pd.to_datetime('18:00:00').time():
print('%s %s | Today is Friday and Market has Closed!' %
(self.date, self.hour))
self.operable = False
elif self.weekday == 5:
print('%s %s | Today is Saturday and market is not Opened' %
(self.date, self.hour))
self.operable = False
else:
self.operable = True
def current_date(self):
self.date = datetime.now().strftime('%Y-%m-%d')
self.weekday = datetime.now().weekday()
self.hour = datetime.now().strftime('%H:%M:%S')
def _sundays_activation(self):
hour = '18:00:05'
if self.weekday == 6:
if pd.to_datetime(self.hour).time() < pd.to_datetime(hour).time():
print('Today is Sunday. Bot activation is at 18:00:00')
while True:
self.current_date()
if pd.to_datetime(
self.hour).time() >= pd.to_datetime(hour).time():
print('Activation Done')
self.send_telegram_message(
'%s %s | Bot Activation Done' %
(self.date, self.hour))
break
def continuous_check_message(self, message):
if datetime.now().minute == 0 and datetime.now().second == 0:
self.send_telegram_message(message, type='info')
def reconnection(self):
if self.hour == '23:44:30' or self.hour == '16:59:30':
self.interrumption = True
self.ib.disconnect()
self.connected = self.ib.isConnected()
print('%s %s | Ib disconnection' % (self.date, self.hour))
print('Connected: %s' % self.connected)
if self.hour == '23:46:00' or self.hour == '18:00:05':
self.interrumption = False
print('%s %s | Reconnecting...' % (self.date, self.hour))
while not self.connected:
try:
self.ib.connect('127.0.0.1', 7497, self.client)
self.connected = self.ib.isConnected()
if self.connected:
print('%s %s | Connection reestablished!' %
(self.date, self.hour))
print('Requesting Market Data...')
self.bars = self.ib.reqRealTimeBars(
self.contract, 5, 'MIDPOINT', False)
print('Last Close of %s: %.2f' %
(self.symbol, self.bars[-1].close))
print('%s Data has been Updated!' % self.symbol)
except:
print(
'%s %s | Connection Failed! Trying to reconnect in 10 seconds...'
% (self.date, self.hour))
self.ib.sleep(10)
print('%s %s | %s Data has been Updated!' %
(self.date, self.hour, self.symbol))
def _local_symbol_selection(self):
'''Selects local symbol according to symbol and current date'''
current_date = datetime.now().date()
# csv file selection according to symbol
if self.symbol in ['ES', 'RTY', 'NQ', 'MES', 'MNQ', 'M2K']:
contract_dates = pd.read_csv(
'D:/Archivos/futuro/Algorithmics/Codes/My_Bots/Hermes/contract_dates/indexes_globex.txt',
parse_dates=True)
elif self.symbol in ['YM', 'MYM', 'DAX']:
contract_dates = pd.read_csv(
'D:/Archivos/futuro/Algorithmics/Codes/My_Bots/Hermes/contract_dates/indexes_ecbot_dtb.txt',
parse_dates=True)
elif self.symbol in ['QO', 'MGC']:
contract_dates = pd.read_csv(
'D:/Archivos/futuro/Algorithmics/Codes/My_Bots/Hermes/contract_dates/QO_MGC.txt',
parse_dates=True)
elif self.symbol in ['CL', 'QM']:
contract_dates = pd.read_csv(
'D:/Archivos/futuro/Algorithmics/Codes/My_Bots/Hermes/contract_dates/CL_QM.txt',
parse_dates=True)
else:
contract_dates = pd.read_csv(
'D:/Archivos/futuro/Algorithmics/Codes/My_Bots/Hermes/contract_dates/%s.txt'
% symbol,
parse_dates=True)
# Current contract selection according to current date
for i in range(len(contract_dates)):
initial_date = pd.to_datetime(
contract_dates.iloc[i].initial_date).date()
final_date = pd.to_datetime(
contract_dates.iloc[i].final_date).date()
if initial_date <= current_date <= final_date:
current_contract = contract_dates.iloc[i].contract
break
# local symbol selection
local = current_contract
if self.symbol in [
'ES', 'RTY', 'NQ', 'MES', 'MNQ', 'M2K', 'QO', 'CL', 'MGC', 'QM'
]:
local = '%s%s' % (self.symbol, current_contract)
if self.symbol in ['YM', 'ZS']:
local = '%s %s' % (self.symbol, current_contract)
if self.symbol == 'MYM':
local = '%s %s' % (self.symbol, current_contract)
if self.symbol == 'DAX': local = 'FDAX %s' % current_contract
return local
def get_contract(self):
if self.market == 'futures':
local = self._local_symbol_selection()
self.contract = Future(symbol=self.symbol,
exchange=self.exchange,
localSymbol=local)
print(
self.ib.reqContractDetails(
self.contract)[0].contract.lastTradeDateOrContractMonth)
'''expiration = self.ib.reqContractDetails(Future(self.symbol,self.exchange))[0].contract.lastTradeDateOrContractMonth
self.contract = Future(symbol=self.symbol, exchange=self.exchange, lastTradeDateOrContractMonth=expiration)'''
elif self.market == 'forex':
self.contract = Forex(self.symbol)
elif self.market == 'stocks':
self.contract = Stock(symbol=self.symbol,
exchange=self.exchange,
currency='USD')
def download_data(self, tempo, duration):
pr = (lambda market: 'MIDPOINT'
if market == 'forex' else 'TRADES')(self.market)
historical = self.ib.reqHistoricalData(self.contract,
endDateTime='',
durationStr=duration,
barSizeSetting=tempo,
whatToShow=pr,
useRTH=False,
keepUpToDate=False)
return historical
def send_telegram_message(self, message, type='trades'):
bot_token = '1204313430:AAGonra1LaFhyI1gCVOHsz8yAohJUeFgplo'
bot_chatID = '-499850995' if type == 'trades' else '-252750334'
url = 'https://api.telegram.org/bot%s/sendMessage?chat_id=%s&text=%s' % (
bot_token, bot_chatID, message)
requests.get(url)
class IBStore(with_metaclass(MetaSingleton, object)):
'''Singleton class wrapping an ibpy ibConnection instance.
The parameters can also be specified in the classes which use this store,
like ``IBData`` and ``IBBroker``
Params:
- ``host`` (default:``127.0.0.1``): where IB TWS or IB Gateway are
actually running. And although this will usually be the localhost, it
must not be
- ``port`` (default: ``7496``): port to connect to. The demo system uses
``7497``
- ``clientId`` (default: ``None``): which clientId to use to connect to
TWS.
``None``: generates a random id between 1 and 65535
An ``integer``: will be passed as the value to use.
- ``notifyall`` (default: ``False``)
If ``False`` only ``error`` messages will be sent to the
``notify_store`` methods of ``Cerebro`` and ``Strategy``.
If ``True``, each and every message received from TWS will be notified
- ``_debug`` (default: ``False``)
Print all messages received from TWS to standard output
- ``reconnect`` (default: ``3``)
Number of attempts to try to reconnect after the 1st connection attempt
fails
Set it to a ``-1`` value to keep on reconnecting forever
- ``timeout`` (default: ``3.0``)
Time in seconds between reconnection attemps
- ``timeoffset`` (default: ``True``)
If True, the time obtained from ``reqCurrentTime`` (IB Server time)
will be used to calculate the offset to localtime and this offset will
be used for the price notifications (tickPrice events, for example for
CASH markets) to modify the locally calculated timestamp.
The time offset will propagate to other parts of the ``backtrader``
ecosystem like the **resampling** to align resampling timestamps using
the calculated offset.
- ``timerefresh`` (default: ``60.0``)
Time in seconds: how often the time offset has to be refreshed
- ``indcash`` (default: ``True``)
Manage IND codes as if they were cash for price retrieval
'''
# Set a base for the data requests (historical/realtime) to distinguish the
# id in the error notifications from orders, where the basis (usually
# starting at 1) is set by TWS
REQIDBASE = 0x01000000
BrokerCls = None #getattr(sys.modules["cerebro.strategies." +classname.split('.')[0]], classname.split('.')[1])IBBroker #None # broker class will autoregister
DataCls = None # data class will auto register
params = (
('host', '127.0.0.1'),
('port', 7496),
('clientId', None), # None generates a random clientid 1 -> 2^16
('notifyall', False), # NOT IMPLEMENTED
('_debug', False),
('reconnect', 3), # -1 forever, 0 No, > 0 number of retries
('timeout', 3.0), # timeout between reconnections
('timeoffset', True), # Use offset to server for timestamps if needed
('timerefresh', 60.0), # How often to refresh the timeoffset
('indcash', True), # Treat IND codes as CASH elements
('readonly', False), # Set to True when IB API is in read-only mode
('account', ''), # Main account to receive updates for
)
@classmethod
def getdata(cls, *args, **kwargs):
'''Returns ``DataCls`` with args, kwargs'''
return cls.DataCls(*args, **kwargs)
@classmethod
def getbroker(cls, *args, **kwargs):
'''Returns broker with *args, **kwargs from registered ``BrokerCls``'''
return cls.BrokerCls(*args, **kwargs)
def __init__(self):
super(IBStore, self).__init__()
self._env = None # reference to cerebro for general notifications
self.broker = None # broker instance
self.datas = list() # datas that have registered over start
# self.ccount = 0 # requests to start (from cerebro or datas)
# self._lock_tmoffset = threading.Lock()
# self.tmoffset = timedelta() # to control time difference with server
# # Structures to hold datas requests
# self.qs = collections.OrderedDict() # key: tickerId -> queues
# self.ts = collections.OrderedDict() # key: queue -> tickerId
self.iscash = dict() # tickerIds from cash products (for ex: EUR.JPY)
self.acc_cash = AutoDict() # current total cash per account
self.acc_value = AutoDict() # current total value per account
self.acc_upds = AutoDict() # current account valueinfos per account
self.positions = collections.defaultdict(Position) # actual positions
self.orderid = None # next possible orderid (will be itertools.count)
self.managed_accounts = list() # received via managedAccounts
self.notifs = queue.Queue() # store notifications for cerebro
self.orders = collections.OrderedDict() # orders by order ided
self.opending = collections.defaultdict(list) # pending transmission
self.brackets = dict() # confirmed brackets
self.last_tick = None
# Use the provided clientId or a random one
if self.p.clientId is None:
self.clientId = random.randint(1, pow(2, 16) - 1)
else:
self.clientId = self.p.clientId
if self.p.timeout is None:
self.timeout = 2
else:
self.timeout = self.p.timeout
if self.p.readonly is None:
self.readonly = False
else:
self.readonly = self.p.readonly
if self.p.account is None:
self.account = ""
else:
self.account = self.p.account
if self.p._debug:
util.logToConsole(level=logging.DEBUG)
util.patchAsyncio()
util.startLoop()
self.ib = IB()
self.ib.connect(
host=self.p.host, port=self.p.port,
clientId=self.clientId,
timeout=self.timeout,
readonly=self.readonly,
account=self.account,
)
# This utility key function transforms a barsize into a:
# (Timeframe, Compression) tuple which can be sorted
def keyfn(x):
n, t = x.split()
tf, comp = self._sizes[t]
return (tf, int(n) * comp)
# This utility key function transforms a duration into a:
# (Timeframe, Compression) tuple which can be sorted
def key2fn(x):
n, d = x.split()
tf = self._dur2tf[d]
return (tf, int(n))
# Generate a table of reverse durations
self.revdur = collections.defaultdict(list)
# The table (dict) is a ONE to MANY relation of
# duration -> barsizes
# Here it is reversed to get a ONE to MANY relation of
# barsize -> durations
for duration, barsizes in self._durations.items():
for barsize in barsizes:
self.revdur[keyfn(barsize)].append(duration)
# Once managed, sort the durations according to real duration and not
# to the text form using the utility key above
for barsize in self.revdur:
self.revdur[barsize].sort(key=key2fn)
def start(self, data=None, broker=None):
#self.reconnect(fromstart=True) # reconnect should be an invariant
# Datas require some processing to kickstart data reception
if data is not None:
self._env = data._env
# For datas simulate a queue with None to kickstart co
self.datas.append(data)
# if connection fails, get a fakeation that will force the
# datas to try to reconnect or else bail out
return self.getTickerQueue(start=True)
elif broker is not None:
self.broker = broker
def stop(self):
try:
self.ib.disconnect() # disconnect should be an invariant
except AttributeError:
pass # conn may have never been connected and lack "disconnect"
def get_notifications(self):
'''Return the pending "store" notifications'''
# The background thread could keep on adding notifications. The None
# mark allows to identify which is the last notification to deliver
self.notifs.put(None) # put a mark
notifs = list()
while True:
notif = self.notifs.get()
if notif is None: # mark is reached
break
notifs.append(notif)
return notifs
def managedAccounts(self):
# 1st message in the stream
self.managed_accounts = self.ib.managedAccounts()
# Request time to avoid synchronization issues
self.reqCurrentTime()
def currentTime(self,msg):
if not self.p.timeoffset: # only if requested ... apply timeoffset
return
curtime = datetime.fromtimestamp(float(msg.time))
with self._lock_tmoffset:
self.tmoffset = curtime - datetime.now()
threading.Timer(self.p.timerefresh, self.reqCurrentTime).start()
def timeoffset(self):
with self._lock_tmoffset:
return self.tmoffset
def reqCurrentTime(self):
self.ib.reqCurrentTime()
def nextOrderId(self):
# Get the next ticker using a new request value from TWS
self.orderid = self.ib.client.getReqId()
return self.orderid
def getTickerQueue(self, start=False):
'''Creates ticker/Queue for data delivery to a data feed'''
q = queue.Queue()
if start:
q.put(None)
return q
return q
def getContractDetails(self, contract, maxcount=None):
#cds = list()
cds = self.ib.reqContractDetails(contract)
#cds.append(cd)
if not cds or (maxcount and len(cds) > maxcount):
err = 'Ambiguous contract: none/multiple answers received'
self.notifs.put((err, cds, {}))
return None
return cds
def reqHistoricalDataEx(self, contract, enddate, begindate,
timeframe, compression,
what=None, useRTH=False, tz='',
sessionend=None,
#tickerId=None
):
'''
Extension of the raw reqHistoricalData proxy, which takes two dates
rather than a duration, barsize and date
It uses the IB published valid duration/barsizes to make a mapping and
spread a historical request over several historical requests if needed
'''
# Keep a copy for error reporting purposes
kwargs = locals().copy()
kwargs.pop('self', None) # remove self, no need to report it
if timeframe < TimeFrame.Seconds:
# Ticks are not supported
return self.getTickerQueue(start=True)
if enddate is None:
enddate = datetime.now()
if begindate is None:
duration = self.getmaxduration(timeframe, compression)
if duration is None:
err = ('No duration for historical data request for '
'timeframe/compresison')
self.notifs.put((err, (), kwargs))
return self.getTickerQueue(start=True)
barsize = self.tfcomp_to_size(timeframe, compression)
if barsize is None:
err = ('No supported barsize for historical data request for '
'timeframe/compresison')
self.notifs.put((err, (), kwargs))
return self.getTickerQueue(start=True)
return self.reqHistoricalData(contract=contract, enddate=enddate,
duration=duration, barsize=barsize,
what=what, useRTH=useRTH, tz=tz,
sessionend=sessionend)
# Check if the requested timeframe/compression is supported by IB
durations = self.getdurations(timeframe, compression)
# if not durations: # return a queue and put a None in it
# return self.getTickerQueue(start=True)
# Get or reuse a queue
# if tickerId is None:
# tickerId, q = self.getTickerQueue()
# else:
# tickerId, q = self.reuseQueue(tickerId) # reuse q for old tickerId
# Get the best possible duration to reduce number of requests
duration = None
# for dur in durations:
# intdate = self.dt_plus_duration(begindate, dur)
# if intdate >= enddate:
# intdate = enddate
# duration = dur # begin -> end fits in single request
# break
intdate = begindate
if duration is None: # no duration large enough to fit the request
duration = durations[-1]
# Store the calculated data
# self.histexreq[tickerId] = dict(
# contract=contract, enddate=enddate, begindate=intdate,
# timeframe=timeframe, compression=compression,
# what=what, useRTH=useRTH, tz=tz, sessionend=sessionend)
barsize = self.tfcomp_to_size(timeframe, compression)
if contract.secType in ['CASH', 'CFD']:
#self.iscash[tickerId] = 1 # msg.field code
if not what:
what = 'BID' # default for cash unless otherwise specified
elif contract.secType in ['IND'] and self.p.indcash:
#self.iscash[tickerId] = 4 # msg.field code
pass
what = what or 'TRADES'
q = self.getTickerQueue()
histdata = self.ib.reqHistoricalData(
contract,
intdate.strftime('%Y%m%d %H:%M:%S') + ' GMT',
duration,
barsize,
what,
useRTH,
2) # dateformat 1 for string, 2 for unix time in seconds
for msg in histdata:
q.put(msg)
return q
def reqHistoricalData(self, contract, enddate, duration, barsize,
what=None, useRTH=False, tz='', sessionend=None):
'''Proxy to reqHistorical Data'''
# get a ticker/queue for identification/data delivery
q = self.getTickerQueue()
if contract.secType in ['CASH', 'CFD']:
#self.iscash[tickerId] = True
if not what:
what = 'BID' # TRADES doesn't work
elif what == 'ASK':
#self.iscash[tickerId] = 2
pass
else:
what = what or 'TRADES'
# split barsize "x time", look in sizes for (tf, comp) get tf
#tframe = self._sizes[barsize.split()[1]][0]
# self.histfmt[tickerId] = tframe >= TimeFrame.Days
# self.histsend[tickerId] = sessionend
# self.histtz[tickerId] = tz
histdata = self.ib.reqHistoricalData(
contract,
enddate.strftime('%Y%m%d %H:%M:%S') + ' GMT',
duration,
barsize,
what,
useRTH,
2) # dateformat 1 for string, 2 for unix time in seconds
for msg in histdata:
q.put(msg)
return q
def reqRealTimeBars(self, contract, useRTH=False, duration=5):
'''Creates a request for (5 seconds) Real Time Bars
Params:
- contract: a ib.ext.Contract.Contract intance
- useRTH: (default: False) passed to TWS
- duration: (default: 5) passed to TWS
Returns:
- a Queue the client can wait on to receive a RTVolume instance
'''
# get a ticker/queue for identification/data delivery
q = self.getTickerQueue()
rtb = self.ib.reqRealTimeBars(contract, duration,
'MIDPOINT', useRTH=useRTH)
self.ib.sleep(duration)
for bar in rtb:
q.put(bar)
return q
def reqMktData(self, contract, what=None):
'''Creates a MarketData subscription
Params:
- contract: a ib.ext.Contract.Contract intance
Returns:
- a Queue the client can wait on to receive a RTVolume instance
'''
# get a ticker/queue for identification/data delivery
q = self.getTickerQueue()
ticks = '233' # request RTVOLUME tick delivered over tickString
if contract.secType in ['CASH', 'CFD']:
#self.iscash[tickerId] = True
ticks = '' # cash markets do not get RTVOLUME
if what == 'ASK':
#self.iscash[tickerId] = 2
pass
# q.put(None) # to kickstart backfilling
# Can request 233 also for cash ... nothing will arrive
md = MktData()
q_ticks = queue.Queue()
util.run(md.update_ticks(self.ib, contract, ticks, q_ticks))
while not q_ticks.empty():
ticker = q_ticks.get()
for tick in ticker.ticks:
# https://interactivebrokers.github.io/tws-api/tick_types.html
if tick != self.last_tick: #last price
#print(str(tick.time) +" >> " + str(tick.price))
self.last_tick = tick
q.put(tick)
return q
# The _durations are meant to calculate the needed historical data to
# perform backfilling at the start of a connetion or a connection is lost.
# Using a timedelta as a key allows to quickly find out which bar size
# bar size (values in the tuples int the dict) can be used.
_durations = dict([
# 60 seconds - 1 min
('60 S',
('1 secs', '5 secs', '10 secs', '15 secs', '30 secs',
'1 min')),
# 120 seconds - 2 mins
('120 S',
('1 secs', '5 secs', '10 secs', '15 secs', '30 secs',
'1 min', '2 mins')),
# 180 seconds - 3 mins
('180 S',
('1 secs', '5 secs', '10 secs', '15 secs', '30 secs',
'1 min', '2 mins', '3 mins')),
# 300 seconds - 5 mins
('300 S',
('1 secs', '5 secs', '10 secs', '15 secs', '30 secs',
'1 min', '2 mins', '3 mins', '5 mins')),
# 600 seconds - 10 mins
('600 S',
('1 secs', '5 secs', '10 secs', '15 secs', '30 secs',
'1 min', '2 mins', '3 mins', '5 mins', '10 mins')),
# 900 seconds - 15 mins
('900 S',
('1 secs', '5 secs', '10 secs', '15 secs', '30 secs',
'1 min', '2 mins', '3 mins', '5 mins', '10 mins', '15 mins')),
# 1200 seconds - 20 mins
('1200 S',
('1 secs', '5 secs', '10 secs', '15 secs', '30 secs',
'1 min', '2 mins', '3 mins', '5 mins', '10 mins', '15 mins',
'20 mins')),
# 1800 seconds - 30 mins
('1800 S',
('1 secs', '5 secs', '10 secs', '15 secs', '30 secs',
'1 min', '2 mins', '3 mins', '5 mins', '10 mins', '15 mins',
'20 mins', '30 mins')),
# 3600 seconds - 1 hour
('3600 S',
('5 secs', '10 secs', '15 secs', '30 secs',
'1 min', '2 mins', '3 mins', '5 mins', '10 mins', '15 mins',
'20 mins', '30 mins',
'1 hour')),
# 7200 seconds - 2 hours
('7200 S',
('5 secs', '10 secs', '15 secs', '30 secs',
'1 min', '2 mins', '3 mins', '5 mins', '10 mins', '15 mins',
'20 mins', '30 mins',
'1 hour', '2 hours')),
# 10800 seconds - 3 hours
('10800 S',
('10 secs', '15 secs', '30 secs',
'1 min', '2 mins', '3 mins', '5 mins', '10 mins', '15 mins',
'20 mins', '30 mins',
'1 hour', '2 hours', '3 hours')),
# 14400 seconds - 4 hours
('14400 S',
('15 secs', '30 secs',
'1 min', '2 mins', '3 mins', '5 mins', '10 mins', '15 mins',
'20 mins', '30 mins',
'1 hour', '2 hours', '3 hours', '4 hours')),
# 28800 seconds - 8 hours
('28800 S',
('30 secs',
'1 min', '2 mins', '3 mins', '5 mins', '10 mins', '15 mins',
'20 mins', '30 mins',
'1 hour', '2 hours', '3 hours', '4 hours', '8 hours')),
# 1 days
('1 D',
('1 min', '2 mins', '3 mins', '5 mins', '10 mins', '15 mins',
'20 mins', '30 mins',
'1 hour', '2 hours', '3 hours', '4 hours', '8 hours',
'1 day')),
# 2 days
('2 D',
('2 mins', '3 mins', '5 mins', '10 mins', '15 mins',
'20 mins', '30 mins',
'1 hour', '2 hours', '3 hours', '4 hours', '8 hours',
'1 day')),
# 1 weeks
('1 W',
('3 mins', '5 mins', '10 mins', '15 mins',
'20 mins', '30 mins',
'1 hour', '2 hours', '3 hours', '4 hours', '8 hours',
'1 day', '1 W')),
# 2 weeks
('2 W',
('15 mins', '20 mins', '30 mins',
'1 hour', '2 hours', '3 hours', '4 hours', '8 hours',
'1 day', '1 W')),
# 1 months
('1 M',
('30 mins',
'1 hour', '2 hours', '3 hours', '4 hours', '8 hours',
'1 day', '1 W', '1 M')),
# 2+ months
('2 M', ('1 day', '1 W', '1 M')),
('3 M', ('1 day', '1 W', '1 M')),
('4 M', ('1 day', '1 W', '1 M')),
('5 M', ('1 day', '1 W', '1 M')),
('6 M', ('1 day', '1 W', '1 M')),
('7 M', ('1 day', '1 W', '1 M')),
('8 M', ('1 day', '1 W', '1 M')),
('9 M', ('1 day', '1 W', '1 M')),
('10 M', ('1 day', '1 W', '1 M')),
('11 M', ('1 day', '1 W', '1 M')),
# 1+ years
('1 Y', ('1 day', '1 W', '1 M')),
])
# Sizes allow for quick translation from bar sizes above to actual
# timeframes to make a comparison with the actual data
_sizes = {
'secs': (TimeFrame.Seconds, 1),
'min': (TimeFrame.Minutes, 1),
'mins': (TimeFrame.Minutes, 1),
'hour': (TimeFrame.Minutes, 60),
'hours': (TimeFrame.Minutes, 60),
'day': (TimeFrame.Days, 1),
'W': (TimeFrame.Weeks, 1),
'M': (TimeFrame.Months, 1),
}
_dur2tf = {
'S': TimeFrame.Seconds,
'D': TimeFrame.Days,
'W': TimeFrame.Weeks,
'M': TimeFrame.Months,
'Y': TimeFrame.Years,
}
def getdurations(self, timeframe, compression):
key = (timeframe, compression)
if key not in self.revdur:
return []
return self.revdur[key]
def getmaxduration(self, timeframe, compression):
key = (timeframe, compression)
try:
return self.revdur[key][-1]
except (KeyError, IndexError):
pass
return None
def tfcomp_to_size(self, timeframe, compression):
if timeframe == TimeFrame.Months:
return '{} M'.format(compression)
if timeframe == TimeFrame.Weeks:
return '{} W'.format(compression)
if timeframe == TimeFrame.Days:
if not compression % 7:
return '{} W'.format(compression // 7)
return '{} day'.format(compression)
if timeframe == TimeFrame.Minutes:
if not compression % 60:
hours = compression // 60
return ('{} hour'.format(hours)) + ('s' * (hours > 1))
return ('{} min'.format(compression)) + ('s' * (compression > 1))
if timeframe == TimeFrame.Seconds:
return '{} secs'.format(compression)
# Microseconds or ticks
return None
def dt_plus_duration(self, dt, duration):
size, dim = duration.split()
size = int(size)
if dim == 'S':
return dt + timedelta(seconds=size)
if dim == 'D':
return dt + timedelta(days=size)
if dim == 'W':
return dt + timedelta(days=size * 7)
if dim == 'M':
month = dt.month - 1 + size # -1 to make it 0 based, readd below
years, month = divmod(month, 12)
return dt.replace(year=dt.year + years, month=month + 1)
if dim == 'Y':
return dt.replace(year=dt.year + size)
return dt # could do nothing with it ... return it intact
# def histduration(self, dt1, dt2):
# # Given two dates calculates the smallest possible duration according
# # to the table from the Historical Data API limitations provided by IB
# #
# # Seconds: 'x S' (x: [60, 120, 180, 300, 600, 900, 1200, 1800, 3600,
# # 7200, 10800, 14400, 28800])
# # Days: 'x D' (x: [1, 2]
# # Weeks: 'x W' (x: [1, 2])
# # Months: 'x M' (x: [1, 11])
# # Years: 'x Y' (x: [1])
# td = dt2 - dt1 # get a timedelta for calculations
# # First: array of secs
# tsecs = td.total_seconds()
# secs = [60, 120, 180, 300, 600, 900, 1200, 1800, 3600, 7200, 10800,
# 14400, 28800]
# idxsec = bisect.bisect_left(secs, tsecs)
# if idxsec < len(secs):
# return '{} S'.format(secs[idxsec])
# tdextra = bool(td.seconds or td.microseconds) # over days/weeks
# # Next: 1 or 2 days
# days = td.days + tdextra
# if td.days <= 2:
# return '{} D'.format(days)
# # Next: 1 or 2 weeks
# weeks, d = divmod(td.days, 7)
# weeks += bool(d or tdextra)
# if weeks <= 2:
# return '{} W'.format(weeks)
# # Get references to dt components
# y2, m2, d2 = dt2.year, dt2.month, dt2.day
# y1, m1, d1 = dt1.year, dt1.month, dt2.day
# H2, M2, S2, US2 = dt2.hour, dt2.minute, dt2.second, dt2.microsecond
# H1, M1, S1, US1 = dt1.hour, dt1.minute, dt1.second, dt1.microsecond
# # Next: 1 -> 11 months (11 incl)
# months = (y2 * 12 + m2) - (y1 * 12 + m1) + (
# (d2, H2, M2, S2, US2) > (d1, H1, M1, S1, US1))
# if months <= 1: # months <= 11
# return '1 M' # return '{} M'.format(months)
# elif months <= 11:
# return '2 M' # cap at 2 months to keep the table clean
# # Next: years
# # y = y2 - y1 + (m2, d2, H2, M2, S2, US2) > (m1, d1, H1, M1, S1, US1)
# # return '{} Y'.format(y)
# return '1 Y' # to keep the table clean
def makecontract(self, symbol, sectype, exch, curr,
expiry='', strike=0.0, right='', mult=1):
'''returns a contract from the parameters without check'''
contract = Contract()
contract.symbol = symbol
contract.secType = sectype
contract.exchange = exch
if curr:
contract.currency = curr
if sectype in ['FUT', 'OPT', 'FOP']:
contract.lastTradeDateOrContractMonth = expiry
if sectype in ['OPT', 'FOP']:
contract.strike = strike
contract.right = right
if mult:
contract.multiplier = mult
return contract
def cancelOrder(self, orderid):
'''Proxy to cancelOrder'''
self.ib.cancelOrder(orderid)
def placeOrder(self, orderid, contract, order):
'''Proxy to placeOrder'''
trade = self.ib.placeOrder(contract, order)
while not trade.isDone():
self.ib.waitOnUpdate()
return trade
def reqTrades(self):
'''Proxy to Trades'''
return self.ib.trades()
def reqPositions(self):
'''Proxy to reqPositions'''
return self.ib.reqPositions()
def getposition(self, contract, clone=False):
# Lock access to the position dicts. This is called from main thread
# and updates could be happening in the background
#with self._lock_pos:
position = self.positions[contract.conId]
if clone:
return copy(position)
return position
def reqAccountUpdates(self, subscribe=True, account=None):
'''Proxy to reqAccountUpdates
If ``account`` is ``None``, wait for the ``managedAccounts`` message to
set the account codes
'''
if account is None:
#self._event_managed_accounts.wait()
self.managedAccounts()
account = self.managed_accounts[0]
#self.ib.reqAccountUpdates(subscribe, bytes(account))
self.updateAccountValue()
def updateAccountValue(self):
# Lock access to the dicts where values are updated. This happens in a
# sub-thread and could kick it at anytime
#with self._lock_accupd:
#if self.connected():
ret = self.ib.accountValues()
for msg in ret:
try:
value = float(msg.value)
except ValueError:
value = msg.value
self.acc_upds[msg.account][msg.tag][msg.currency] = value
if msg.tag == 'NetLiquidation':
# NetLiquidationByCurrency and currency == 'BASE' is the same
self.acc_value[msg.account] = value
elif msg.tag == 'TotalCashBalance' and msg.currency == 'BASE':
self.acc_cash[msg.account] = value
def get_acc_values(self, account=None):
'''Returns all account value infos sent by TWS during regular updates
Waits for at least 1 successful download
If ``account`` is ``None`` then a dictionary with accounts as keys will
be returned containing all accounts
If account is specified or the system has only 1 account the dictionary
corresponding to that account is returned
'''
# Wait for at least 1 account update download to have been finished
# before the account infos can be returned to the calling client
# if self.connected():
# self._event_accdownload.wait()
# Lock access to acc_cash to avoid an event intefering
#with self._updacclock:
if account is None:
# wait for the managedAccount Messages
# if self.connected():
# self._event_managed_accounts.wait()
if not self.managed_accounts:
return self.acc_upds.copy()
elif len(self.managed_accounts) > 1:
return self.acc_upds.copy()
# Only 1 account, fall through to return only 1
account = self.managed_accounts[0]
try:
return self.acc_upds[account].copy()
except KeyError:
pass
return self.acc_upds.copy()
def get_acc_value(self, account=None):
'''Returns the net liquidation value sent by TWS during regular updates
Waits for at least 1 successful download
If ``account`` is ``None`` then a dictionary with accounts as keys will
be returned containing all accounts
If account is specified or the system has only 1 account the dictionary
corresponding to that account is returned
'''
# Wait for at least 1 account update download to have been finished
# before the value can be returned to the calling client
# if self.connected():
# self._event_accdownload.wait()
# Lock access to acc_cash to avoid an event intefering
#with self._lock_accupd:
if account is None:
# wait for the managedAccount Messages
# if self.connected():
# self._event_managed_accounts.wait()
if not self.managed_accounts:
return float()
elif len(self.managed_accounts) > 1:
return sum(self.acc_value.values())
# Only 1 account, fall through to return only 1
account = self.managed_accounts[0]
try:
return self.acc_value[account]
except KeyError:
pass
return float()
def get_acc_cash(self, account=None):
'''Returns the total cash value sent by TWS during regular updates
Waits for at least 1 successful download
If ``account`` is ``None`` then a dictionary with accounts as keys will
be returned containing all accounts
If account is specified or the system has only 1 account the dictionary
corresponding to that account is returned
'''
# Wait for at least 1 account update download to have been finished
# before the cash can be returned to the calling client'
# if self.connected():
# self._event_accdownload.wait()
# result = [v for v in self.ib.accountValues() \
# if v.tag == 'TotalCashBalance' and v.currency == 'BASE']
# Lock access to acc_cash to avoid an event intefering
#with self._lock_accupd:
if account is None:
#wait for the managedAccount Messages
# if self.connected():
# self._event_managed_accounts.wait()
if not self.managed_accounts:
return float()
elif len(self.managed_accounts) > 1:
return sum(self.acc_cash.values())
# Only 1 account, fall through to return only 1
account = self.managed_accounts[0]
try:
return self.acc_cash[account]
except KeyError:
pass
host = data['common']['host']
port = data[market]['port']
cid = 1
# ...connect to IB
ib = IB().connect(host=host, port=port, clientId=cid)
acct = ib.managedAccounts()[0]
# ..get account summary
accsum = ib.accountSummary(account=acct)
# ..get liquidity and funds dictionary
funds = {
t.tag: t.value
for t in accsum if t.tag in ["NetLiquidation", "AvailableFunds"]
}
# ..dailyPnl
ib.reqPnL(acct)
ib.sleep(8)
pnlobj = ib.pnl()[0]
ib.cancelPnL(acct)
pnldict = {
'dailyPnL': pnlobj.dailyPnL,
'unrealizedPnL': pnlobj.unrealizedPnL,
'realizedPnL': pnlobj.realizedPnL
}
print({**funds, **pnldict})
)
ibc.start()
ib = IB()
watchdog = Watchdog(
ibc,
ib,
port=4001,
connectTimeout=59,
appStartupTime=45,
appTimeout=59,
retryDelay=10,
)
watchdog.start()
ib.sleep(60)
#TODO: Add this 'setup' to a different event handler to fire when connected
STOCK = [
"SPY",
"QQQ",
"IWM",
"VXX",
"GLD",
"AMZN",
"GOOG",
"EFA",
"EEM",
"TLT",
"USO",
"GDX",
Forex('EURUSD'),
Stock(symbol="AAPL", exchange="SMART", currency="USD"),
# Stock(symbol="1810", exchange="SEHK", currency="HKD"),
# Stock(symbol="601636", exchange="SEHKNTL"),
# Stock(symbol="000725", exchange="SEHKSZSE"),
]
# """
# 创建保存 K 线所用的 DB 表格
create_tables()
# 订阅多种类型的 K 线
_types = ['5 secs', '10 secs', '5 mins']
for contract in contracts:
for _type in _types:
try:
bars = request_historical_data(ib=ib,
contract=contract,
barSizeSetting=_type)
bars.updateEvent += on_bar_update
except Exception as e1:
logger.exception(e1)
while True:
ib.sleep(10)
print(
"get_k_bars_from_db: ",
get_k_bars_from_db(symbol="EURUSD",
_type="5 secs",
limit=10))
except Exception as e:
logger.exception(e)
time.sleep(10)
