# FreqAI is crashing if minimal_roi is a property
# @property
# def minimal_roi(self) -> dict[str, Any]:
- # timeframe_minutes = self.get_timeframe_minutes()
+ # timeframe_minutes = self.timeframe_minutes
# fit_live_predictions_candles = int(
# self.config.get("freqai", {}).get(
# "fit_live_predictions_candles", DEFAULT_FIT_LIVE_PREDICTIONS_CANDLES
def _order_types_set() -> set[OrderType]:
return set(QuickAdapterV3._ORDER_TYPES)
- @lru_cache(maxsize=None)
- def get_timeframe_minutes(self) -> int:
+ @cached_property
+ def timeframe_minutes(self) -> int:
return timeframe_to_minutes(self.config.get("timeframe"))
@property
),
}
)
- self._candle_duration_secs = int(self.get_timeframe_minutes() * 60)
+ self._candle_duration_secs = int(self.timeframe_minutes * 60)
self.last_candle_start_secs: dict[str, Optional[int]] = {}
process_throttle_secs = self.config.get("internals", {}).get(
"process_throttle_secs", 5
) -> DataFrame:
pair = str(metadata.get("pair"))
label_period = datetime.timedelta(
- minutes=len(dataframe) * self.get_timeframe_minutes()
+ minutes=len(dataframe) * self.timeframe_minutes
)
label_weighting = self.label_weighting
return None
return int(
((current_date - entry_date).total_seconds() / 60.0)
- / self.get_timeframe_minutes()
+ / self.timeframe_minutes
)
def get_trade_annotation_line_start_date(
)
offset_timedelta = datetime.timedelta(
- minutes=offset_candles_remaining * self.get_timeframe_minutes()
+ minutes=offset_candles_remaining * self.timeframe_minutes
)
return trade.open_date_utc - offset_timedelta