freqtrade_origin/docs/strategy_migration.md
2022-08-27 10:30:06 +02:00

16 KiB

Strategy Migration between V2 and V3

To support new markets and trade-types (namely short trades / trades with leverage), some things had to change in the interface. If you intend on using markets other than spot markets, please migrate your strategy to the new format.

We have put a great effort into keeping compatibility with existing strategies, so if you just want to continue using freqtrade in spot markets, there should be no changes necessary for now.

You can use the quick summary as checklist. Please refer to the detailed sections below for full migration details.

Quick summary / migration checklist

Note : forcesell, forcebuy, emergencysell are changed to force_exit, force_enter, emergency_exit respectively.

Extensive explanation

populate_buy_trend

In populate_buy_trend() - you will want to change the columns you assign from 'buy' to 'enter_long', as well as the method name from populate_buy_trend to populate_entry_trend.

def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
    dataframe.loc[
        (
            (qtpylib.crossed_above(dataframe['rsi'], 30)) &  # Signal: RSI crosses above 30
            (dataframe['tema'] <= dataframe['bb_middleband']) &  # Guard
            (dataframe['tema'] > dataframe['tema'].shift(1)) &  # Guard
            (dataframe['volume'] > 0)  # Make sure Volume is not 0
        ),
        ['buy', 'buy_tag']] = (1, 'rsi_cross')

    return dataframe

After:

def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
    dataframe.loc[
        (
            (qtpylib.crossed_above(dataframe['rsi'], 30)) &  # Signal: RSI crosses above 30
            (dataframe['tema'] <= dataframe['bb_middleband']) &  # Guard
            (dataframe['tema'] > dataframe['tema'].shift(1)) &  # Guard
            (dataframe['volume'] > 0)  # Make sure Volume is not 0
        ),
        ['enter_long', 'enter_tag']] = (1, 'rsi_cross')

    return dataframe

Please refer to the Strategy documentation on how to enter and exit short trades.

populate_sell_trend

Similar to populate_buy_trend, populate_sell_trend() will be renamed to populate_exit_trend(). We'll also change the column from 'sell' to 'exit_long'.

def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
    dataframe.loc[
        (
            (qtpylib.crossed_above(dataframe['rsi'], 70)) &  # Signal: RSI crosses above 70
            (dataframe['tema'] > dataframe['bb_middleband']) &  # Guard
            (dataframe['tema'] < dataframe['tema'].shift(1)) &  # Guard
            (dataframe['volume'] > 0)  # Make sure Volume is not 0
        ),
        ['sell', 'exit_tag']] = (1, 'some_exit_tag')
    return dataframe

After

def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
    dataframe.loc[
        (
            (qtpylib.crossed_above(dataframe['rsi'], 70)) &  # Signal: RSI crosses above 70
            (dataframe['tema'] > dataframe['bb_middleband']) &  # Guard
            (dataframe['tema'] < dataframe['tema'].shift(1)) &  # Guard
            (dataframe['volume'] > 0)  # Make sure Volume is not 0
        ),
        ['exit_long', 'exit_tag']] = (1, 'some_exit_tag')
    return dataframe

Please refer to the Strategy documentation on how to enter and exit short trades.

custom_sell

custom_sell has been renamed to custom_exit. It's now also being called for every iteration, independent of current profit and exit_profit_only settings.

class AwesomeStrategy(IStrategy):
    def custom_sell(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float,
                    current_profit: float, **kwargs):
        dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
        last_candle = dataframe.iloc[-1].squeeze()
        # ...
class AwesomeStrategy(IStrategy):
    def custom_exit(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float,
                    current_profit: float, **kwargs):
        dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
        last_candle = dataframe.iloc[-1].squeeze()
        # ...

custom_entry_timeout

check_buy_timeout() has been renamed to check_entry_timeout(), and check_sell_timeout() has been renamed to check_exit_timeout().

class AwesomeStrategy(IStrategy):
    def check_buy_timeout(self, pair: str, trade: 'Trade', order: dict, 
                            current_time: datetime, **kwargs) -> bool:
        return False

    def check_sell_timeout(self, pair: str, trade: 'Trade', order: dict, 
                            current_time: datetime, **kwargs) -> bool:
        return False 
class AwesomeStrategy(IStrategy):
    def check_entry_timeout(self, pair: str, trade: 'Trade', order: 'Order', 
                            current_time: datetime, **kwargs) -> bool:
        return False

    def check_exit_timeout(self, pair: str, trade: 'Trade', order: 'Order', 
                            current_time: datetime, **kwargs) -> bool:
        return False 

custom_stake_amount

New string argument side - which can be either "long" or "short".

class AwesomeStrategy(IStrategy):
    def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
                            proposed_stake: float, min_stake: Optional[float], max_stake: float,
                            entry_tag: Optional[str], **kwargs) -> float:
        # ... 
        return proposed_stake
class AwesomeStrategy(IStrategy):
    def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
                            proposed_stake: float, min_stake: Optional[float], max_stake: float,
                            entry_tag: Optional[str], side: str, **kwargs) -> float:
        # ... 
        return proposed_stake

confirm_trade_entry

New string argument side - which can be either "long" or "short".

class AwesomeStrategy(IStrategy):
    def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
                            time_in_force: str, current_time: datetime, entry_tag: Optional[str], 
                            **kwargs) -> bool:
      return True

After:

class AwesomeStrategy(IStrategy):
    def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
                            time_in_force: str, current_time: datetime, entry_tag: Optional[str], 
                            side: str, **kwargs) -> bool:
      return True

confirm_trade_exit

Changed argument sell_reason to exit_reason. For compatibility, sell_reason will still be provided for a limited time.

class AwesomeStrategy(IStrategy):
    def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float,
                           rate: float, time_in_force: str, sell_reason: str,
                           current_time: datetime, **kwargs) -> bool:
    return True

After:

class AwesomeStrategy(IStrategy):
    def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float,
                           rate: float, time_in_force: str, exit_reason: str,
                           current_time: datetime, **kwargs) -> bool:
    return True

custom_entry_price

New string argument side - which can be either "long" or "short".

class AwesomeStrategy(IStrategy):
    def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
                           entry_tag: Optional[str], **kwargs) -> float:
      return proposed_rate

After:

class AwesomeStrategy(IStrategy):
    def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
                           entry_tag: Optional[str], side: str, **kwargs) -> float:
      return proposed_rate

Adjust trade position changes

While adjust-trade-position itself did not change, you should no longer use trade.nr_of_successful_buys - and instead use trade.nr_of_successful_entries, which will also include short entries.

Helper methods

Added argument "is_short" to stoploss_from_open and stoploss_from_absolute. This should be given the value of trade.is_short.

    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
                        current_rate: float, current_profit: float, **kwargs) -> float:
        # once the profit has risen above 10%, keep the stoploss at 7% above the open price
        if current_profit > 0.10:
            return stoploss_from_open(0.07, current_profit)

        return stoploss_from_absolute(current_rate - (candle['atr'] * 2), current_rate)

        return 1

After:

    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
                        current_rate: float, current_profit: float, **kwargs) -> float:
        # once the profit has risen above 10%, keep the stoploss at 7% above the open price
        if current_profit > 0.10:
            return stoploss_from_open(0.07, current_profit, is_short=trade.is_short)

        return stoploss_from_absolute(current_rate - (candle['atr'] * 2), current_rate, is_short=trade.is_short)


Strategy/Configuration settings

order_time_in_force

order_time_in_force attributes changed from "buy" to "entry" and "sell" to "exit".

    order_time_in_force: Dict = {
        "buy": "gtc",
        "sell": "gtc",
    }

After:

    order_time_in_force: Dict = {
        "entry": "GTC",
        "exit": "GTC",
    }

order_types

order_types have changed all wordings from buy to entry - and sell to exit. And two words are joined with _.

    order_types = {
        "buy": "limit",
        "sell": "limit",
        "emergencysell": "market",
        "forcesell": "market",
        "forcebuy": "market",
        "stoploss": "market",
        "stoploss_on_exchange": false,
        "stoploss_on_exchange_interval": 60
    }

After:

    order_types = {
        "entry": "limit",
        "exit": "limit",
        "emergency_exit": "market",
        "force_exit": "market",
        "force_entry": "market",
        "stoploss": "market",
        "stoploss_on_exchange": false,
        "stoploss_on_exchange_interval": 60
    }

Strategy level settings

  • use_sell_signal -> use_exit_signal
  • sell_profit_only -> exit_profit_only
  • sell_profit_offset -> exit_profit_offset
  • ignore_roi_if_buy_signal -> ignore_roi_if_entry_signal
    # These values can be overridden in the config.
    use_sell_signal = True
    sell_profit_only = True
    sell_profit_offset: 0.01
    ignore_roi_if_buy_signal = False

After:

    # These values can be overridden in the config.
    use_exit_signal = True
    exit_profit_only = True
    exit_profit_offset: 0.01
    ignore_roi_if_entry_signal = False

unfilledtimeout

unfilledtimeout have changed all wordings from buy to entry - and sell to exit.

unfilledtimeout = {
        "buy": 10,
        "sell": 10,
        "exit_timeout_count": 0,
        "unit": "minutes"
    }

After:

unfilledtimeout = {
        "entry": 10,
        "exit": 10,
        "exit_timeout_count": 0,
        "unit": "minutes"
    }

order pricing

Order pricing changed in 2 ways. bid_strategy was renamed to entry_pricing and ask_strategy was renamed to exit_pricing. The attributes ask_last_balance -> price_last_balance and bid_last_balance -> price_last_balance were renamed as well. Also, price-side can now be defined as ask, bid, same or other. Please refer to the pricing documentation for more information.

{
    "bid_strategy": {
        "price_side": "bid",
        "use_order_book": true,
        "order_book_top": 1,
        "ask_last_balance": 0.0,
        "check_depth_of_market": {
            "enabled": false,
            "bids_to_ask_delta": 1
        }
    },
    "ask_strategy":{
        "price_side": "ask",
        "use_order_book": true,
        "order_book_top": 1,
        "bid_last_balance": 0.0
    }
}

after:

{
    "entry_pricing": {
        "price_side": "same",
        "use_order_book": true,
        "order_book_top": 1,
        "price_last_balance": 0.0,
        "check_depth_of_market": {
            "enabled": false,
            "bids_to_ask_delta": 1
        }
    },
    "exit_pricing":{
        "price_side": "same",
        "use_order_book": true,
        "order_book_top": 1,
        "price_last_balance": 0.0
    }
}