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)