How to use terminate_session method in localstack

Best Python code snippet using localstack_python

DNN_trader.py

Source:DNN_trader.py

...64					if attempt >= max_attempts:65						print("max_attempts reached !")66						try: #try to terminate session67							time.sleep(wait)68							self.terminate_session(cause = "Unexpected Session Stop ( too many errors).")69						except Exception as e:70							print(e, end = " | ")71							print("Could not terminate_session properly!")72						finally:73							break74					else: # try again 75						time.sleep(wait)76						wait += wait_increase77						self.tick_data = pd.DataFrame()78	def on_success(self,time,bid,ask):79		print(self.ticks, end = " ")80		# collect and store tick data81		recent_tick = pd.to_datetime(time)82		#define stop because of low market violatility83		# if recent_tick.time() >= pd.to_datetime("17:30").time():84		# 	self.stop_stream = True85		############## Define Stop ##############86		# if self.ticks >= 100:87		# 	self.terminate_session(cause = "Scheduled Session End.")88		# 	return 89		#########################################90		df = pd.DataFrame({self.instrument:(ask+bid)/2},index = [recent_tick])91		self.tick_data = self.tick_data.append(df)92		#if a time longer than the bar_length has elapsed between last full bar and the most recent time93		if recent_tick - self.last_bar > self.bar_length:94			self.resample_and_join()95			self.define_strategy()96			self.execute_trades()97	def resample_and_join(self):98		#append the most recent ticks(resample) to self.data 99		self.raw_data = self.raw_data.append(self.tick_data.resample(self.bar_length,100			label="right").last().ffill().iloc[:-1])101		self.tick_data = self.tick_data.iloc[-1:] #only keep the latest tick(next bar)102		self.last_bar = self.raw_data.index[-1] #update time of last full bar 103	def define_strategy(self):104		df = self.raw_data.copy()105		#******************** define your strategy here ************************106		#create features107		df = df.append(self.tick_data) # append latest tick (== open price of current bar)108		df["returns"] = np.log(df[self.instrument] / df[self.instrument].shift())109		df["Dir"] = np.where(df["returns"] > 0, 1, 0)110		df["SMA"] = df[self.instrument].rolling(self.window).mean() - df[self.instrument].rolling(150).mean()111		df["Boll"] = (df[self.instrument] - df[self.instrument].rolling(self.window).mean()) / df[self.instrument].rolling(self.window).std()112		df["MACD"] = df[self.instrument].ewm(span = 12, adjust = False).mean() - df[self.instrument].ewm(span = 26, adjust = False).mean()113		df["Min"] = df[self.instrument].rolling(self.window).min() / df[self.instrument] - 1114		df["Max"] = df[self.instrument].rolling(self.window).max() / df[self.instrument] - 1115		df["Mom"] = df["returns"].rolling(3).mean()116		df["Vol"] = df["returns"].rolling(self.window).std()117		df.dropna(inplace = True)118		119		# create lags120		self.cols = []121		features = ["Dir", "SMA", "Boll", "Min", "Max", "Mom", "Vol"]122		for f in features:123			for lag in range(1, self.lags + 1):124				col = "{}_lag_{}".format(f, lag)125				df[col] = df[f].shift(lag)126				self.cols.append(col)127		df.dropna(inplace = True)128		129		# standardization130		df_s = (df - self.mu) / self.std131		# predict132		df["proba"] = self.model.predict(df_s[self.cols])133		134		#determine positions135		df = df.loc[self.start_time:].copy() # starting with first live_stream bar (removing historical bars)136		df["position"] = np.where(df.proba < 0.47, -1, np.nan)137		df["position"] = np.where(df.proba > 0.53, 1, df.position)138		df["position"] = df.position.ffill().fillna(0) # start with neutral position if no strong signal139		#***********************************************************************140		141		self.data = df.copy()142	def execute_trades(self):143		if self.data["position"].iloc[-1] == 1:144			if self.position == 0:145				order = self.create_order(self.instrument, self.units, suppress = True, ret = True)146				self.report_trade(order, "GOING LONG")147			elif self.position == -1:148				order = self.create_order(self.instrument, self.units * 2, suppress = True, ret = True) 149				self.report_trade(order, "GOING LONG")150			self.position = 1151		elif self.data["position"].iloc[-1] == -1: 152			if self.position == 0:153				order = self.create_order(self.instrument, -self.units, suppress = True, ret = True)154				self.report_trade(order, "GOING SHORT")155			elif self.position == 1:156				order = self.create_order(self.instrument, -self.units * 2, suppress = True, ret = True)157				self.report_trade(order, "GOING SHORT")158			self.position = -1159		elif self.data["position"].iloc[-1] == 0: 160			if self.position == -1:161				order = self.create_order(self.instrument, self.units, suppress = True, ret = True) 162				self.report_trade(order, "GOING NEUTRAL")163			elif self.position == 1:164				order = self.create_order(self.instrument, -self.units, suppress = True, ret = True)165				self.report_trade(order, "GOING NEUTRAL")166			self.position = 0167	def report_trade(self, order, going):168		time = order["time"]169		units = order["units"]170		price = order["price"]171		pl = float(order["pl"])172		self.profits.append(pl)173		cumpl = sum(self.profits)174		print("\n" + 100* "-")175		print("{} | {}".format(time, going))176		print("{} | units = {} | price = {} | P&L = {} | Cum P&L = {}".format(time, units, price, pl, cumpl))177		print(100 * "-" + "\n")178	def terminate_session(self, cause): #NEW179		self.stop_stream = True180		if self.position != 0:181			close_order = self.create_order(self.instrument, units = -self.position * self.units,182				suppress = True, ret = True)183			self.report_trade(close_order, "GOING NEUTRAL")184			self.position = 0185		print(cause)186#Only execute when directly called from terminal 187if __name__ == "__main__": 188	# Loading the model189	model = keras.models.load_model("DNN_model")190	# Loading mu and std191	params = pickle.load(open("params.pkl", "rb"))192	mu = params["mu"]...

run.py

Source:run.py

...66                continue67            except socket.error as e:68                print('Error occured waiting for R10 response:')69                sleep(2)70                garminConnect.terminate_session()71                check_gspro_status()72                garminConnect = GarminConnect(gsProConnect, _config["garmin"]["port"])73                continue74            except KeyboardInterrupt:75                break76            except Exception as e:77                _logger.exception("General error: ")78                _logger.exception(e)79                continue80    finally:81        print('closing sockets')82        if(gsProConnect):83            gsProConnect.terminate_session()84        if(garminConnect):85            garminConnect.terminate_session()86        sys.exit()87if __name__ == "__main__":...

group_api.py

Source:group_api.py

1#2# Author:  Dlo Bagari3# created Date: 12-10-20194from flask import jsonify5class GroupApi:6    def __init__(self, config, logger):7        self._group = None8        self._config = config9        self._logger = logger10    def filter_group_by_name(self, group_name):11        error_code, error_message, group = self._group.filter_groups_by_name(group_name)12        if error_code != 0:13            self._logger.error(self, error_message)14            return jsonify({"error": error_message}), 40015        else:16            return jsonify(group), 20017    def set_group(self, group):18        self._group = group19    def change_group(self, user_id, current_group, new_group, terminate_session=True):20        error_code, error_message, group = self._group.change_group(user_id, current_group, new_group,21                                                                    terminate_session=terminate_session)22        if error_code != 0 or len(error_message) != 0:23            self._logger.error(self, error_message)24            return jsonify({"error": error_message, "status": "failed"}), 40025        else:...

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