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Merged feat/short into lev-strat

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Sam Germain
2021-09-19 17:44:12 -06:00
parent a89c67787b
commit 778f0d9d0a
41 changed files with 3173 additions and 614 deletions
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4
freqtrade/strategy/__init__.py
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@@ -3,5 +3,7 @@ from freqtrade.exchange import (timeframe_to_minutes, timeframe_to_msecs, timefr
timeframe_to_prev_date, timeframe_to_seconds)
from freqtrade.strategy.hyper import (BooleanParameter, CategoricalParameter, DecimalParameter,
IntParameter, RealParameter)
from freqtrade.strategy.informative_decorator import informative
from freqtrade.strategy.interface import IStrategy
from freqtrade.strategy.strategy_helper import merge_informative_pair, stoploss_from_open
from freqtrade.strategy.strategy_helper import (merge_informative_pair, stoploss_from_absolute,
stoploss_from_open)

128
freqtrade/strategy/informative_decorator.py Normal file
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@@ -0,0 +1,128 @@
from typing import Any, Callable, NamedTuple, Optional, Union
from pandas import DataFrame
from freqtrade.exceptions import OperationalException
from freqtrade.strategy.strategy_helper import merge_informative_pair
PopulateIndicators = Callable[[Any, DataFrame, dict], DataFrame]
class InformativeData(NamedTuple):
asset: Optional[str]
timeframe: str
fmt: Union[str, Callable[[Any], str], None]
ffill: bool
def informative(timeframe: str, asset: str = '',
fmt: Optional[Union[str, Callable[[Any], str]]] = None,
ffill: bool = True) -> Callable[[PopulateIndicators], PopulateIndicators]:
"""
A decorator for populate_indicators_Nn(self, dataframe, metadata), allowing these functions to
define informative indicators.
Example usage:
@informative('1h')
def populate_indicators_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
return dataframe
:param timeframe: Informative timeframe. Must always be equal or higher than strategy timeframe.
:param asset: Informative asset, for example BTC, BTC/USDT, ETH/BTC. Do not specify to use
current pair.
:param fmt: Column format (str) or column formatter (callable(name, asset, timeframe)). When not
specified, defaults to:
* {base}_{quote}_{column}_{timeframe} if asset is specified.
* {column}_{timeframe} if asset is not specified.
Format string supports these format variables:
* {asset} - full name of the asset, for example 'BTC/USDT'.
* {base} - base currency in lower case, for example 'eth'.
* {BASE} - same as {base}, except in upper case.
* {quote} - quote currency in lower case, for example 'usdt'.
* {QUOTE} - same as {quote}, except in upper case.
* {column} - name of dataframe column.
* {timeframe} - timeframe of informative dataframe.
:param ffill: ffill dataframe after merging informative pair.
"""
_asset = asset
_timeframe = timeframe
_fmt = fmt
_ffill = ffill
def decorator(fn: PopulateIndicators):
informative_pairs = getattr(fn, '_ft_informative', [])
informative_pairs.append(InformativeData(_asset, _timeframe, _fmt, _ffill))
setattr(fn, '_ft_informative', informative_pairs)
return fn
return decorator
def _format_pair_name(config, pair: str) -> str:
return pair.format(stake_currency=config['stake_currency'],
stake=config['stake_currency']).upper()
def _create_and_merge_informative_pair(strategy, dataframe: DataFrame, metadata: dict,
inf_data: InformativeData,
populate_indicators: PopulateIndicators):
asset = inf_data.asset or ''
timeframe = inf_data.timeframe
fmt = inf_data.fmt
config = strategy.config
if asset:
# Insert stake currency if needed.
asset = _format_pair_name(config, asset)
else:
# Not specifying an asset will define informative dataframe for current pair.
asset = metadata['pair']
if '/' in asset:
base, quote = asset.split('/')
else:
# When futures are supported this may need reevaluation.
# base, quote = asset, ''
raise OperationalException('Not implemented.')
# Default format. This optimizes for the common case: informative pairs using same stake
# currency. When quote currency matches stake currency, column name will omit base currency.
# This allows easily reconfiguring strategy to use different base currency. In a rare case
# where it is desired to keep quote currency in column name at all times user should specify
# fmt='{base}_{quote}_{column}_{timeframe}' format or similar.
if not fmt:
fmt = '{column}_{timeframe}' # Informatives of current pair
if inf_data.asset:
fmt = '{base}_{quote}_' + fmt # Informatives of other pairs
inf_metadata = {'pair': asset, 'timeframe': timeframe}
inf_dataframe = strategy.dp.get_pair_dataframe(asset, timeframe)
inf_dataframe = populate_indicators(strategy, inf_dataframe, inf_metadata)
formatter: Any = None
if callable(fmt):
formatter = fmt # A custom user-specified formatter function.
else:
formatter = fmt.format # A default string formatter.
fmt_args = {
'BASE': base.upper(),
'QUOTE': quote.upper(),
'base': base.lower(),
'quote': quote.lower(),
'asset': asset,
'timeframe': timeframe,
}
inf_dataframe.rename(columns=lambda column: formatter(column=column, **fmt_args),
inplace=True)
date_column = formatter(column='date', **fmt_args)
if date_column in dataframe.columns:
raise OperationalException(f'Duplicate column name {date_column} exists in '
f'dataframe! Ensure column names are unique!')
dataframe = merge_informative_pair(dataframe, inf_dataframe, strategy.timeframe, timeframe,
ffill=inf_data.ffill, append_timeframe=False,
date_column=date_column)
return dataframe

46
freqtrade/strategy/interface.py
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@@ -19,6 +19,9 @@ from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
from freqtrade.exchange.exchange import timeframe_to_next_date
from freqtrade.persistence import PairLocks, Trade
from freqtrade.strategy.hyper import HyperStrategyMixin
from freqtrade.strategy.informative_decorator import (InformativeData, PopulateIndicators,
_create_and_merge_informative_pair,
_format_pair_name)
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
from freqtrade.wallets import Wallets
@@ -118,7 +121,7 @@ class IStrategy(ABC, HyperStrategyMixin):
# Class level variables (intentional) containing
# the dataprovider (dp) (access to other candles, historic data, ...)
# and wallets - access to the current balance.
dp: Optional[DataProvider] = None
dp: Optional[DataProvider]
wallets: Optional[Wallets] = None
# Filled from configuration
stake_currency: str
@@ -134,6 +137,24 @@ class IStrategy(ABC, HyperStrategyMixin):
self._last_candle_seen_per_pair: Dict[str, datetime] = {}
super().__init__(config)
# Gather informative pairs from @informative-decorated methods.
self._ft_informative: List[Tuple[InformativeData, PopulateIndicators]] = []
for attr_name in dir(self.__class__):
cls_method = getattr(self.__class__, attr_name)
if not callable(cls_method):
continue
informative_data_list = getattr(cls_method, '_ft_informative', None)
if not isinstance(informative_data_list, list):
# Type check is required because mocker would return a mock object that evaluates to
# True, confusing this code.
continue
strategy_timeframe_minutes = timeframe_to_minutes(self.timeframe)
for informative_data in informative_data_list:
if timeframe_to_minutes(informative_data.timeframe) < strategy_timeframe_minutes:
raise OperationalException('Informative timeframe must be equal or higher than '
'strategy timeframe!')
self._ft_informative.append((informative_data, cls_method))
@abstractmethod
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
@@ -379,6 +400,23 @@ class IStrategy(ABC, HyperStrategyMixin):
# END - Intended to be overridden by strategy
###
def gather_informative_pairs(self) -> ListPairsWithTimeframes:
"""
Internal method which gathers all informative pairs (user or automatically defined).
"""
informative_pairs = self.informative_pairs()
for inf_data, _ in self._ft_informative:
if inf_data.asset:
pair_tf = (_format_pair_name(self.config, inf_data.asset), inf_data.timeframe)
informative_pairs.append(pair_tf)
else:
if not self.dp:
raise OperationalException('@informative decorator with unspecified asset '
'requires DataProvider instance.')
for pair in self.dp.current_whitelist():
informative_pairs.append((pair, inf_data.timeframe))
return list(set(informative_pairs))
def get_strategy_name(self) -> str:
"""
Returns strategy class name
@@ -878,6 +916,12 @@ class IStrategy(ABC, HyperStrategyMixin):
:return: a Dataframe with all mandatory indicators for the strategies
"""
logger.debug(f"Populating indicators for pair {metadata.get('pair')}.")
# call populate_indicators_Nm() which were tagged with @informative decorator.
for inf_data, populate_fn in self._ft_informative:
dataframe = _create_and_merge_informative_pair(
self, dataframe, metadata, inf_data, populate_fn)
if self._populate_fun_len == 2:
warnings.warn("deprecated - check out the Sample strategy to see "
"the current function headers!", DeprecationWarning)

45
freqtrade/strategy/strategy_helper.py
View File

@@ -5,7 +5,9 @@ from freqtrade.exchange import timeframe_to_minutes
def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
timeframe: str, timeframe_inf: str, ffill: bool = True) -> pd.DataFrame:
timeframe: str, timeframe_inf: str, ffill: bool = True,
append_timeframe: bool = True,
date_column: str = 'date') -> pd.DataFrame:
"""
Correctly merge informative samples to the original dataframe, avoiding lookahead bias.
@@ -25,6 +27,8 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
:param timeframe: Timeframe of the original pair sample.
:param timeframe_inf: Timeframe of the informative pair sample.
:param ffill: Forwardfill missing values - optional but usually required
:param append_timeframe: Rename columns by appending timeframe.
:param date_column: A custom date column name.
:return: Merged dataframe
:raise: ValueError if the secondary timeframe is shorter than the dataframe timeframe
"""
@@ -33,25 +37,29 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
minutes = timeframe_to_minutes(timeframe)
if minutes == minutes_inf:
# No need to forwardshift if the timeframes are identical
informative['date_merge'] = informative["date"]
informative['date_merge'] = informative[date_column]
elif minutes < minutes_inf:
# Subtract "small" timeframe so merging is not delayed by 1 small candle
# Detailed explanation in https://github.com/freqtrade/freqtrade/issues/4073
informative['date_merge'] = (
informative["date"] + pd.to_timedelta(minutes_inf, 'm') - pd.to_timedelta(minutes, 'm')
informative[date_column] + pd.to_timedelta(minutes_inf, 'm') -
pd.to_timedelta(minutes, 'm')
)
else:
raise ValueError("Tried to merge a faster timeframe to a slower timeframe."
"This would create new rows, and can throw off your regular indicators.")
# Rename columns to be unique
informative.columns = [f"{col}_{timeframe_inf}" for col in informative.columns]
date_merge = 'date_merge'
if append_timeframe:
date_merge = f'date_merge_{timeframe_inf}'
informative.columns = [f"{col}_{timeframe_inf}" for col in informative.columns]
# Combine the 2 dataframes
# all indicators on the informative sample MUST be calculated before this point
dataframe = pd.merge(dataframe, informative, left_on='date',
right_on=f'date_merge_{timeframe_inf}', how='left')
dataframe = dataframe.drop(f'date_merge_{timeframe_inf}', axis=1)
right_on=date_merge, how='left')
dataframe = dataframe.drop(date_merge, axis=1)
if ffill:
dataframe = dataframe.ffill()
@@ -97,3 +105,28 @@ def stoploss_from_open(
return min(stoploss, 0.0)
else:
return max(stoploss, 0.0)
def stoploss_from_absolute(stop_rate: float, current_rate: float) -> float:
"""
Given current price and desired stop price, return a stop loss value that is relative to current
price.
The requested stop can be positive for a stop above the open price, or negative for
a stop below the open price. The return value is always >= 0.
Returns 0 if the resulting stop price would be above the current price.
:param stop_rate: Stop loss price.
:param current_rate: Current asset price.
:return: Positive stop loss value relative to current price
"""
# formula is undefined for current_rate 0, return maximum value
if current_rate == 0:
return 1
stoploss = 1 - (stop_rate / current_rate)
# negative stoploss values indicate the requested stop price is higher than the current price
return max(stoploss, 0.0)