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 : force_exit
, force_enter
, emergency_exit
are changed to force_exit
, force_enter
, emergency_exit
respectively.
- Strategy methods:
populate_buy_trend()
->populate_entry_trend()
populate_sell_trend()
->populate_exit_trend()
custom_sell()
->custom_exit()
check_buy_timeout()
->check_entry_timeout()
check_sell_timeout()
->check_exit_timeout()
- New
side
argument to callbacks without trade object - Changed argument name in
confirm_trade_exit
- Dataframe columns:
- trade-object now has the following new properties:
is_short
entry_side
exit_side
trade_direction
- renamed:
sell_reason
->exit_reason
- Renamed
trade.nr_of_successful_buys
totrade.nr_of_successful_entries
(mostly relevant foradjust_trade_position()
) - Introduced new
leverage
callback. - Informative pairs can now pass a 3rd element in the Tuple, defining the candle type.
@informative
decorator now takes an optionalcandle_type
argument.- helper methods
stoploss_from_open
andstoploss_from_absolute
now takeis_short
as additional argument. INTERFACE_VERSION
should be set to 3.- Strategy/Configuration settings.
order_time_in_force
buy -> entry, sell -> exit.order_types
buy -> entry, sell -> exit.unfilledtimeout
buy -> entry, sell -> exit.
- Terminology changes
- Sell reasons changed to reflect the new naming of "exit" instead of sells. Be careful in your strategy if you're using
exit_reason
checks and eventually update your strategy.sell_signal
->exit_signal
custom_sell
->custom_exit
force_sell
->force_exit
emergency_sell
->emergency_exit
- Webhook terminology changed from "sell" to "exit", and from "buy" to entry
webhookbuy
->webhookentry
webhookbuyfill
->webhookentryfill
webhookbuycancel
->webhookentrycancel
webhooksell
->webhookexit
webhooksellfill
->webhookexitfill
webhooksellcancel
->webhookexitcancel
- Telegram notification settings
buy
->entry
buy_fill
->entry_fill
buy_cancel
->entry_cancel
sell
->exit
sell_fill
->exit_fill
sell_cancel
->exit_cancel
- Strategy/config 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
forcebuy_enable
->force_entry_enable
- Sell reasons changed to reflect the new naming of "exit" instead of sells. Be careful in your strategy if you're using
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: dict,
current_time: datetime, **kwargs) -> bool:
return False
def check_exit_timeout(self, pair: str, trade: 'Trade', order: dict,
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: 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: 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
}
}