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Add current_time to check_timeout functions for convenience

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Matthias
2022-01-22 16:05:13 +01:00
parent 7bef9a9b3e
commit 821a9d9cdc
2 changed files with 19 additions and 12 deletions
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11
freqtrade/strategy/interface.py
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@@ -188,7 +188,8 @@ class IStrategy(ABC, HyperStrategyMixin):
"""
return dataframe
def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
def check_buy_timeout(self, pair: str, trade: Trade, order: dict,
current_time: datetime, **kwargs) -> bool:
"""
Check buy timeout function callback.
This method can be used to override the buy-timeout.
@@ -201,12 +202,14 @@ class IStrategy(ABC, HyperStrategyMixin):
:param pair: Pair the trade is for
:param trade: trade object.
:param order: Order dictionary as returned from CCXT.
:param current_time: datetime object, containing the current datetime
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return bool: When True is returned, then the buy-order is cancelled.
"""
return False
def check_sell_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
def check_sell_timeout(self, pair: str, trade: Trade, order: dict,
current_time: datetime, **kwargs) -> bool:
"""
Check sell timeout function callback.
This method can be used to override the sell-timeout.
@@ -219,6 +222,7 @@ class IStrategy(ABC, HyperStrategyMixin):
:param pair: Pair the trade is for
:param trade: trade object.
:param order: Order dictionary as returned from CCXT.
:param current_time: datetime object, containing the current datetime
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return bool: When True is returned, then the sell-order is cancelled.
"""
@@ -872,7 +876,8 @@ class IStrategy(ABC, HyperStrategyMixin):
return strategy_safe_wrapper(getattr(self, time_method),
default_retval=False)(
pair=trade.pair, trade=trade, order=order)
pair=trade.pair, trade=trade, order=order,
current_time=current_time)
def advise_all_indicators(self, data: Dict[str, DataFrame]) -> Dict[str, DataFrame]:
"""