Merge branch 'freqtrade:develop' into pos_adjust

This commit is contained in:
Stefano Ariestasia
2022-01-25 10:30:18 +09:00
committed by GitHub
18 changed files with 222 additions and 93 deletions

View File

@@ -189,7 +189,17 @@ class IStrategy(ABC, HyperStrategyMixin):
"""
return dataframe
def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
def bot_loop_start(self, **kwargs) -> None:
"""
Called at the start of the bot iteration (one loop).
Might be used to perform pair-independent tasks
(e.g. gather some remote resource for comparison)
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
"""
pass
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.
@@ -202,12 +212,14 @@ 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.
@@ -220,22 +232,15 @@ 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.
"""
return False
def bot_loop_start(self, **kwargs) -> None:
"""
Called at the start of the bot iteration (one loop).
Might be used to perform pair-independent tasks
(e.g. gather some remote resource for comparison)
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
"""
pass
def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
time_in_force: str, current_time: datetime, **kwargs) -> bool:
time_in_force: str, current_time: datetime, entry_tag: Optional[str],
**kwargs) -> bool:
"""
Called right before placing a buy order.
Timing for this function is critical, so avoid doing heavy computations or
@@ -251,6 +256,7 @@ class IStrategy(ABC, HyperStrategyMixin):
:param rate: Rate that's going to be used when using limit orders
:param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
:param current_time: datetime object, containing the current datetime
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
: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 placed on the exchange.
False aborts the process
@@ -308,7 +314,7 @@ class IStrategy(ABC, HyperStrategyMixin):
return self.stoploss
def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
**kwargs) -> float:
entry_tag: Optional[str], **kwargs) -> float:
"""
Custom entry price logic, returning the new entry price.
@@ -319,6 +325,7 @@ class IStrategy(ABC, HyperStrategyMixin):
:param pair: Pair that's currently analyzed
:param current_time: datetime object, containing the current datetime
:param proposed_rate: Rate, calculated based on pricing settings in ask_strategy.
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: New entry price value if provided
"""
@@ -370,7 +377,7 @@ class IStrategy(ABC, HyperStrategyMixin):
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
proposed_stake: float, min_stake: float, max_stake: float,
**kwargs) -> float:
entry_tag: Optional[str], **kwargs) -> float:
"""
Customize stake size for each new trade. This method is not called when edge module is
enabled.
@@ -381,6 +388,7 @@ class IStrategy(ABC, HyperStrategyMixin):
:param proposed_stake: A stake amount proposed by the bot.
:param min_stake: Minimal stake size allowed by exchange.
:param max_stake: Balance available for trading.
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
:return: A stake size, which is between min_stake and max_stake.
"""
return proposed_stake
@@ -391,6 +399,7 @@ class IStrategy(ABC, HyperStrategyMixin):
"""
Custom trade adjustment logic, returning the stake amount that a trade should be increased.
This means extra buy orders with additional fees.
Only called when `position_adjustment_enable` is set to True.
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
@@ -853,6 +862,29 @@ class IStrategy(ABC, HyperStrategyMixin):
else:
return current_profit > roi
def ft_check_timed_out(self, side: str, trade: Trade, order: Dict,
current_time: datetime) -> bool:
"""
FT Internal method.
Check if timeout is active, and if the order is still open and timed out
"""
timeout = self.config.get('unfilledtimeout', {}).get(side)
ordertime = arrow.get(order['datetime']).datetime
if timeout is not None:
timeout_unit = self.config.get('unfilledtimeout', {}).get('unit', 'minutes')
timeout_kwargs = {timeout_unit: -timeout}
timeout_threshold = current_time + timedelta(**timeout_kwargs)
timedout = (order['status'] == 'open' and order['side'] == side
and ordertime < timeout_threshold)
if timedout:
return True
time_method = self.check_sell_timeout if order['side'] == 'sell' else self.check_buy_timeout
return strategy_safe_wrapper(time_method,
default_retval=False)(
pair=trade.pair, trade=trade, order=order,
current_time=current_time)
def advise_all_indicators(self, data: Dict[str, DataFrame]) -> Dict[str, DataFrame]:
"""
Populates indicators for given candle (OHLCV) data (for multiple pairs)