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)