def _get_exchange_current_time(self, exchange_name, matrix_id):
try:
import octobot_trading.api as exchange_api
exchange_manager = exchange_api.get_exchange_manager_from_exchange_name_and_id(
exchange_name,
exchange_api.get_exchange_id_from_matrix_id(exchange_name, matrix_id)
)
return exchange_api.get_exchange_current_time(exchange_manager)
except ImportError:
self.logger.error("Strategy requires OctoBot-Trading package installed")
def get_current_exchange_time(self):
try:
import octobot_trading.api as exchange_api
if self.exchange_id is not None:
return exchange_api.get_exchange_current_time(
exchange_api.get_exchange_manager_from_exchange_name_and_id(
self.exchange_name,
self.exchange_id
)
)
except ImportError:
self.logger.error(f"Can't get current exchange time: requires OctoBot-Trading package installed")
return None
async def _trigger_evaluation(self, matrix_id, evaluator_name,
evaluator_type, eval_note, eval_note_type,
exchange_name, cryptocurrency, symbol):
# ensure only start evaluations when technical evaluators have been initialized
try:
TA_by_timeframe = {
available_time_frame: matrix.get_evaluations_by_evaluator(
matrix_id,
exchange_name,
evaluators_enums.EvaluatorMatrixTypes.TA.value,
cryptocurrency,
symbol,
available_time_frame.value,
allow_missing=False,
allowed_values=[commons_constants.START_PENDING_EVAL_NOTE])
for available_time_frame in self.strategy_time_frames
}
# social evaluators by symbol
social_evaluations_by_evaluator = matrix.get_evaluations_by_evaluator(
matrix_id, exchange_name,
evaluators_enums.EvaluatorMatrixTypes.SOCIAL.value,
cryptocurrency, symbol)
# social evaluators by crypto currency
social_evaluations_by_evaluator.update(
matrix.get_evaluations_by_evaluator(
matrix_id, exchange_name,
evaluators_enums.EvaluatorMatrixTypes.SOCIAL.value,
cryptocurrency))
available_rt_time_frames = self.get_available_time_frames(
matrix_id, exchange_name,
evaluators_enums.EvaluatorMatrixTypes.REAL_TIME.value,
cryptocurrency, symbol)
RT_evaluations_by_time_frame = {
available_time_frame: matrix.get_evaluations_by_evaluator(
matrix_id, exchange_name,
evaluators_enums.EvaluatorMatrixTypes.REAL_TIME.value,
cryptocurrency, symbol, available_time_frame)
for available_time_frame in available_rt_time_frames
}
if self.re_evaluate_TA_when_social_or_realtime_notification \
and any(value for value in TA_by_timeframe.values()) \
and evaluator_type != evaluators_enums.EvaluatorMatrixTypes.TA.value \
and evaluator_type in self.re_evaluation_triggering_eval_types \
and evaluator_name not in self.background_social_evaluators:
if evaluators_util.check_valid_eval_note(
eval_note,
eval_type=eval_note_type,
expected_eval_type=evaluators_constants.
EVALUATOR_EVAL_DEFAULT_TYPE):
# trigger re-evaluation
exchange_id = trading_api.get_exchange_id_from_matrix_id(
exchange_name, matrix_id)
await evaluators_channel.trigger_technical_evaluators_re_evaluation_with_updated_data(
matrix_id, evaluator_name, evaluator_type,
exchange_name, cryptocurrency, symbol, exchange_id,
self.strategy_time_frames)
# do not continue this evaluation
return
counter = 0
total_evaluation = 0
for eval_by_rt in RT_evaluations_by_time_frame.values():
for evaluation in eval_by_rt.values():
eval_value = evaluators_api.get_value(evaluation)
if evaluators_util.check_valid_eval_note(
eval_value,
eval_type=evaluators_api.get_type(evaluation),
expected_eval_type=evaluators_constants.
EVALUATOR_EVAL_DEFAULT_TYPE):
total_evaluation += eval_value
counter += 1
for eval_by_ta in TA_by_timeframe.values():
for evaluation in eval_by_ta.values():
eval_value = evaluators_api.get_value(evaluation)
if evaluators_util.check_valid_eval_note(
eval_value,
eval_type=evaluators_api.get_type(evaluation),
expected_eval_type=evaluators_constants.
EVALUATOR_EVAL_DEFAULT_TYPE):
total_evaluation += eval_value
counter += 1
if social_evaluations_by_evaluator:
exchange_manager = trading_api.get_exchange_manager_from_exchange_name_and_id(
exchange_name,
trading_api.get_exchange_id_from_matrix_id(
exchange_name, self.matrix_id))
current_time = trading_api.get_exchange_current_time(
exchange_manager)
for evaluation in social_evaluations_by_evaluator.values():
eval_value = evaluators_api.get_value(evaluation)
if evaluators_util.check_valid_eval_note(
eval_value,
eval_type=evaluators_api.get_type(evaluation),
expected_eval_type=evaluators_constants.
EVALUATOR_EVAL_DEFAULT_TYPE,
eval_time=evaluators_api.get_time(evaluation),
expiry_delay=self.
social_evaluators_default_timeout,
current_time=current_time):
total_evaluation += eval_value
counter += 1
if counter > 0:
self.eval_note = total_evaluation / counter
await self.strategy_completed(cryptocurrency, symbol)
except errors.UnsetTentacleEvaluation as e:
if evaluator_type == evaluators_enums.EvaluatorMatrixTypes.TA.value:
self.logger.error(
f"Missing technical evaluator data for ({e})")
# otherwise it's a social or real-time evaluator, it will shortly be taken into account by TA update cycle
except Exception as e:
self.logger.exception(
e, True, f"Error when computing strategy evaluation: {e}")