async def _get_tools(): symbol = "BTC/USDT" exchange_traders = {} exchange_traders2 = {} config = load_test_config() AdvancedManager.create_class_list(config) exchange_manager = ExchangeManager(config, ccxt.binance, is_simulated=True) await exchange_manager.initialize() exchange_inst = exchange_manager.get_exchange() trader_inst = TraderSimulator(config, exchange_inst, 0.3) await trader_inst.initialize() trader_inst.stop_order_manager() trader_inst2 = TraderSimulator(config, exchange_inst, 0.3) await trader_inst2.initialize() trader_inst2.stop_order_manager() crypto_currency_evaluator = CryptocurrencyEvaluator(config, "Bitcoin", []) symbol_evaluator = SymbolEvaluator(config, symbol, crypto_currency_evaluator) exchange_traders[exchange_inst.get_name()] = trader_inst exchange_traders2[exchange_inst.get_name()] = trader_inst2 symbol_evaluator.set_trader_simulators(exchange_traders) symbol_evaluator.set_traders(exchange_traders2) symbol_evaluator.strategies_eval_lists[exchange_inst.get_name()] = \ EvaluatorCreator.create_strategies_eval_list(config) trading_mode = DailyTradingMode(config, exchange_inst) trading_mode.add_symbol_evaluator(symbol_evaluator) final_evaluator = trading_mode.get_only_decider_key(symbol) trader_inst.portfolio.portfolio["USDT"] = { Portfolio.TOTAL: 2000, Portfolio.AVAILABLE: 2000 } return final_evaluator, trader_inst
def __init__(self, config, strategy_name): self.is_properly_initialized = False self.logger = get_logger(self.get_name()) AdvancedManager.init_advanced_classes_if_necessary(config) self.trading_mode = get_activated_trading_mode(config) self.config = create_blank_config_using_loaded_one(config) self.strategy_class = get_class_from_string( strategy_name, StrategiesEvaluator, Strategies, evaluator_parent_inspection) self.run_results = [] self.results_report = [] self.sorted_results_by_time_frame = {} self.sorted_results_through_all_time_frame = {} self.all_time_frames = [] self.all_TAs = [] self.risks = [] self.current_test_suite = None self.errors = set() self.is_computing = False self.run_id = 0 self.total_nb_runs = 0 if not self.strategy_class: self.logger.error( f"Impossible to find a strategy matching class name: {strategy_name} in installed " f"strategies. Please make sure to enter the name of the class, " f"ex: FullMixedStrategiesEvaluator") else: self.is_properly_initialized = True
async def _get_tools(event_loop): symbol = "BTC/USDT" exchange_traders = {} exchange_traders2 = {} config = load_test_config() time_frame = TimeFrames.ONE_HOUR AdvancedManager.create_class_list(config) exchange_manager = ExchangeManager(config, ccxt.binance, is_simulated=True) await exchange_manager.initialize() exchange_inst = exchange_manager.get_exchange() global_price_updater = GlobalPriceUpdater(exchange_inst) trader_inst = TraderSimulator(config, exchange_inst, 0.3) trader_inst.stop_order_manager() trader_inst2 = TraderSimulator(config, exchange_inst, 0.3) trader_inst2.stop_order_manager() crypto_currency_evaluator = CryptocurrencyEvaluator(config, "Bitcoin", []) symbol_evaluator = SymbolEvaluator(config, symbol, crypto_currency_evaluator) exchange_traders[exchange_inst.get_name()] = trader_inst exchange_traders2[exchange_inst.get_name()] = trader_inst2 symbol_evaluator.set_trader_simulators(exchange_traders) symbol_evaluator.set_traders(exchange_traders2) symbol_evaluator.strategies_eval_lists[exchange_inst.get_name()] = \ EvaluatorCreator.create_strategies_eval_list(config) trading_mode_inst = get_activated_trading_mode(config)(config, exchange_inst) evaluator_task_manager = EvaluatorTaskManager(config, time_frame, global_price_updater, symbol_evaluator, exchange_inst, trading_mode_inst, [], event_loop) trader_inst.portfolio.portfolio["USDT"] = { Portfolio.TOTAL: 2000, Portfolio.AVAILABLE: 2000 } return evaluator_task_manager, time_frame, global_price_updater, symbol_evaluator, symbol
def _get_tools(): config = load_test_config() AdvancedManager.create_class_list(config) evaluator = Evaluator() evaluator.set_config(config) evaluator.set_symbol("BTC/USDT") evaluator.set_time_frame(TimeFrames.ONE_HOUR) return evaluator, config
def get_activated_trading_mode(config): if CONFIG_TRADING_TENTACLES in config: try: trading_modes = [ class_str for class_str, activated in config[CONFIG_TRADING_TENTACLES].items() if activated and get_class_from_string(class_str, AbstractTradingMode, modes, error_when_not_found=True) ] if len(trading_modes) > 1: raise ConfigTradingError( f"More than one activated trading mode found in your {CONFIG_TRADING_FILE_PATH} file, " f"please activate only one") elif trading_modes: trading_mode_class = get_deep_class_from_string( trading_modes[0], modes) if trading_mode_class is not None: return AdvancedManager.get_class(config, trading_mode_class) except ModuleNotFoundError as e: get_logger("get_activated_trading_mode").error( f"Error when loading a trading mode: {e} " f"referenced in {CONFIG_TRADING_FILE_PATH} file") raise ConfigTradingError( f"Please ensure your {CONFIG_TRADING_FILE_PATH} file is valid and at least one trading " f"mode is activated")
def _get_advanced_class_details(class_name, klass, is_trading_mode=False, is_strategy=False): from tentacles_management.advanced_manager import AdvancedManager details = {} config = get_bot().get_config() advanced_class = AdvancedManager.get_class(config, klass) if advanced_class and advanced_class.get_name() != class_name: details[NAME_KEY] = advanced_class.get_name() details[DESCRIPTION_KEY] = advanced_class.get_description() details[BASE_CLASSES_KEY] = [ k.get_name() for k in advanced_class.__bases__ ] if is_trading_mode: required_strategies, required_strategies_count = klass.get_required_strategies_names_and_count( ) details[REQUIREMENTS_KEY] = [ strategy for strategy in required_strategies ] details[REQUIREMENTS_COUNT_KEY] = required_strategies_count elif is_strategy: details[REQUIREMENTS_KEY] = [ evaluator for evaluator in advanced_class.get_required_evaluators(config) ] details[DEFAULT_CONFIG_KEY] = [ evaluator for evaluator in advanced_class.get_default_evaluators(config) ] return details
def _assert_created_instances(instances_list, super_class, config): class_list = [instance.__class__ for instance in instances_list] for eval_class in AdvancedManager.create_advanced_evaluator_types_list(super_class, config): eval_instance = eval_class() eval_instance.set_config(config) if eval_instance.get_is_enabled(): assert eval_class in class_list
def create_real_time_ta_evals(config, exchange_inst, symbol, relevant_evaluators, dispatchers_list): real_time_ta_eval_list = [] for real_time_eval_class in AdvancedManager.create_advanced_evaluator_types_list( RealTimeEvaluator, config): try: real_time_eval_class_instance = EvaluatorCreator.instantiate_real_time_evaluator( real_time_eval_class, exchange_inst, symbol) real_time_eval_class_instance.set_config(config) if EvaluatorCreator.is_relevant_evaluator( real_time_eval_class_instance, relevant_evaluators): real_time_eval_class_instance.set_logger( get_logger(real_time_eval_class.get_name())) is_dispatcher_client, is_evaluator_to_be_used = \ DispatcherCreator.bind_to_dispatcher_if_necessary(real_time_eval_class_instance, dispatchers_list, symbol, True) # register refreshing task if not is_dispatcher_client: real_time_eval_class_instance.set_is_to_be_started_as_task( True) if is_evaluator_to_be_used: real_time_ta_eval_list.append( real_time_eval_class_instance) except Exception as e: EvaluatorCreator.get_logger().error( f"Error when creating evaluator {real_time_eval_class}: {e}" ) EvaluatorCreator.get_logger().exception(e) return real_time_ta_eval_list
def _init_strategies_instances(self, symbol, all_strategy_instances): all_strategy_classes = [s.__class__ for s in all_strategy_instances] required_strategies, required_strategies_min_count = self.get_required_strategies( ) missing_strategies = [] found_strategy_count = 0 for required_class in required_strategies: if required_class in all_strategy_classes: self.strategy_instances_by_classes[symbol][required_class] = \ all_strategy_instances[all_strategy_classes.index(required_class)] found_strategy_count += 1 else: subclass = AdvancedManager.get_class(self.config, required_class) if subclass in all_strategy_classes: self.strategy_instances_by_classes[symbol][required_class] = \ all_strategy_instances[all_strategy_classes.index(subclass)] found_strategy_count += 1 if required_class not in self.strategy_instances_by_classes[ symbol]: missing_strategies.append(required_class) if found_strategy_count < required_strategies_min_count: for missing_strategy in missing_strategies: self.logger.error( f"No instance of {missing_strategy.__name__} or advanced equivalent found, " f"{self.get_name()} trading mode can't work properly ! Maybe this strategy is " f"disabled in tentacles/Evaluator/evaluator_config.json (missing " f"{required_strategies_min_count-found_strategy_count} out of " f"{required_strategies_min_count} minimum required strategies)." )
def get_strategies_list(): try: config = get_bot().get_config() classes = AdvancedManager.get_all_classes(StrategiesEvaluator, config) return set(strategy.get_name() for strategy in classes) except Exception: return []
async def eval_impl(self): interest_over_time = self.simplified_pytrends.interest_over_time() trend = numpy.array([d["data"] for d in interest_over_time]) # compute bollinger bands self.eval_note = AdvancedManager.get_class( self.config, StatisticAnalysis).analyse_recent_trend_changes(trend, numpy.sqrt)
def init_time_frames_from_strategies(config): time_frame_list = set() for strategies_eval_class in AdvancedManager.create_advanced_evaluator_types_list( StrategiesEvaluator, config): if strategies_eval_class.is_enabled(config, False): for time_frame in strategies_eval_class.get_required_time_frames( config): time_frame_list.add(time_frame) time_frame_list = TimeFrameManager.sort_time_frames(time_frame_list) config[CONFIG_TIME_FRAME] = time_frame_list
def get_relevant_TAs_for_strategy(strategy, config): ta_classes_list = [] relevant_evaluators = strategy.get_required_evaluators(config) for ta_eval_class in AdvancedManager.create_advanced_evaluator_types_list( TAEvaluator, config): ta_eval_class_instance = ta_eval_class() ta_eval_class_instance.set_config(config) if EvaluatorCreator.is_relevant_evaluator(ta_eval_class_instance, relevant_evaluators): ta_classes_list.append(ta_eval_class) return ta_classes_list
def get_relevant_evaluators_from_strategies(config): evaluator_list = set() for strategies_eval_class in AdvancedManager.create_advanced_evaluator_types_list( StrategiesEvaluator, config): if strategies_eval_class.is_enabled(config, False): required_evaluators = strategies_eval_class.get_required_evaluators( config) if required_evaluators == CONFIG_EVALUATORS_WILDCARD: return CONFIG_EVALUATORS_WILDCARD else: for evaluator in required_evaluators: evaluator_list.add(evaluator) return evaluator_list
def add_class_to_config_file_content(clazz, config_file_content, classes_list, activated=False): from config import SHORT_VERSION if TentacleUtil.is_first_version_superior(SHORT_VERSION, OCTOBOT_ADV_MNG_IMPORT_CHANGE_VERSION, or_equal=True): from tentacles_management.advanced_manager import AdvancedManager else: from evaluator.Util.advanced_manager import AdvancedManager changed_something = False current_classes_list = AdvancedManager.create_default_types_list(clazz) for current_class in current_classes_list: if not current_class.get_name() in config_file_content: config_file_content[current_class.get_name()] = activated changed_something = True classes_list += current_classes_list return changed_something
def create_strategies_eval_list(config): strategies_eval_list = [] for strategies_eval_class in AdvancedManager.create_advanced_evaluator_types_list( StrategiesEvaluator, config): try: strategies_eval_class_instance = strategies_eval_class() strategies_eval_class_instance.set_config(config) if strategies_eval_class_instance.get_is_enabled(): strategies_eval_class_instance.set_logger( get_logger(strategies_eval_class_instance.get_name())) strategies_eval_list.append(strategies_eval_class_instance) except Exception as e: EvaluatorCreator.get_logger().error( f"Error when creating strategy {strategies_eval_class}: {e}" ) EvaluatorCreator.get_logger().exception(e) return strategies_eval_list
def create_ta_eval_list(evaluator, relevant_evaluators): ta_eval_instance_list = [] for ta_eval_class in AdvancedManager.create_advanced_evaluator_types_list( TAEvaluator, evaluator.get_config()): try: ta_eval_class_instance = ta_eval_class() ta_eval_class_instance.set_config(evaluator.config) if EvaluatorCreator.is_relevant_evaluator( ta_eval_class_instance, relevant_evaluators): ta_eval_class_instance.set_logger( get_logger(ta_eval_class.get_name())) ta_eval_class_instance.set_data(evaluator.data) ta_eval_class_instance.set_symbol(evaluator.get_symbol()) ta_eval_instance_list.append(ta_eval_class_instance) except Exception as e: EvaluatorCreator.get_logger().error( f"Error when creating evaluator {ta_eval_class}: {e}") EvaluatorCreator.get_logger().exception(e) return ta_eval_instance_list
def create_social_eval(config, symbol, dispatchers_list, relevant_evaluators): social_eval_list = [] for social_eval_class in AdvancedManager.create_advanced_evaluator_types_list( SocialEvaluator, config): try: social_eval_class_instance = social_eval_class() social_eval_class_instance.set_config(config) if EvaluatorCreator.is_relevant_evaluator( social_eval_class_instance, relevant_evaluators): is_evaluator_to_be_used = True social_eval_class_instance.set_logger( get_logger(social_eval_class.get_name())) social_eval_class_instance.set_symbol(symbol) social_eval_class_instance.prepare() is_dispatcher_client, is_evaluator_to_be_used = \ DispatcherCreator.bind_to_dispatcher_if_necessary(social_eval_class_instance, dispatchers_list, symbol, is_evaluator_to_be_used) # register refreshing task if the evaluator is not managed by a dispatcher if not is_dispatcher_client and \ is_evaluator_to_be_used and \ social_eval_class_instance.get_is_to_be_independently_tasked(): social_eval_class_instance.set_is_to_be_started_as_task( True) if is_evaluator_to_be_used: social_eval_list.append(social_eval_class_instance) except Exception as e: EvaluatorCreator.get_logger().error( f"Error when creating evaluator {social_eval_class}: {e}") EvaluatorCreator.get_logger().exception(e) return social_eval_list
def _manage_advanced_classes(self): AdvancedManager.init_advanced_classes_if_necessary(self.octobot.get_config())
def prepare(self): self._format_config() self.sentiment_analyser = AdvancedManager.get_util_instance( self.config, TextAnalysis)