[SQUASH] Address PR comments.

docs/strategy-customization.md

@@ -652,9 +652,7 @@ In some situations it may be confusing to deal with stops relative to current ra
 
 ??? Example "Returning a stoploss using absolute price from the custom stoploss function"
 
-    Say the open price was $100, and `current_price` is $121 (`current_profit` will be `0.21`).
-
-    If we want a stop price at $107 price we can call `stoploss_from_absolute(107, current_rate)` which will return `0.1157024793`.  11.57% below $121 is $107, which is the same as 7% above $100.
+    If we want to trail a stop price at 2xATR below current proce we can call `stoploss_from_absolute(current_rate - (candle['atr'] * 2), current_rate)`.
 
     ``` python
 
@@ -664,18 +662,17 @@ In some situations it may be confusing to deal with stops relative to current ra
 
     class AwesomeStrategy(IStrategy):
 
-        # ... populate_* methods
-
         use_custom_stoploss = True
 
+        def populate_indicators_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+            dataframe['atr'] = ta.ATR(dataframe, timeperiod=14)
+            return dataframe
+
         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_absolute(trade.open_rate * 1.07, current_rate)
-
-            return 1
+            dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
+            candle = dataframe.iloc[-1].squeeze()
+            return stoploss_from_absolute(current_rate - (candle['atr'] * 2), current_rate)
 
     ```
 

freqtrade/strategy/__init__.py

@@ -3,6 +3,7 @@
                                 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 (informative, merge_informative_pair,
-                                                stoploss_from_absolute, stoploss_from_open)
+from freqtrade.strategy.strategy_helper import (merge_informative_pair, stoploss_from_absolute,
+                                                stoploss_from_open)

freqtrade/strategy/informative_decorator.py

@@ -0,0 +1,134 @@
+from typing import Any, Callable, NamedTuple, Optional, Union
+
+from mypy_extensions import KwArg
+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[[KwArg(str)], str], None]
+    ffill: bool
+
+
+def informative(timeframe: str, asset: str = '',
+                fmt: Optional[Union[str, Callable[[KwArg(str)], 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}_{column}_{timeframe} if asset is specified and quote currency does match stake
+    currency.
+    * {base}_{quote}_{column}_{timeframe} if asset is specified and quote currency does not match
+    stake currency.
+    * {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, None
+        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 quote != config['stake_currency']:
+            fmt = '{quote}_' + fmt                  # Informatives of different quote currency
+        if inf_data.asset:
+            fmt = '{base}_' + fmt                   # Informatives of other pair
+
+    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

freqtrade/strategy/interface.py

@@ -19,9 +19,9 @@
 from freqtrade.exchange.exchange import timeframe_to_next_date
 from freqtrade.persistence import PairLocks, Trade
 from freqtrade.strategy.hyper import HyperStrategyMixin
-from freqtrade.strategy.strategy_helper import (InformativeData, PopulateIndicators,
-                                                _create_and_merge_informative_pair,
-                                                _format_pair_name)
+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
 
@@ -121,7 +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: DataProvider
+    dp: Optional[DataProvider]
     wallets: Optional[Wallets] = None
     # Filled from configuration
     stake_currency: str
@@ -408,6 +408,9 @@ def gather_informative_pairs(self) -> ListPairsWithTimeframes:
                 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))

freqtrade/strategy/strategy_helper.py

@@ -1,23 +1,8 @@
-from typing import Any, Callable, NamedTuple, Optional, Union
-
 import pandas as pd
-from mypy_extensions import KwArg
-from pandas import DataFrame
 
-from freqtrade.exceptions import OperationalException
 from freqtrade.exchange import timeframe_to_minutes
 
 
-PopulateIndicators = Callable[[Any, DataFrame, dict], DataFrame]
-
-
-class InformativeData(NamedTuple):
-    asset: Optional[str]
-    timeframe: str
-    fmt: Union[str, Callable[[KwArg(str)], str], None]
-    ffill: bool
-
-
 def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
                            timeframe: str, timeframe_inf: str, ffill: bool = True,
                            append_timeframe: bool = True,
@@ -117,120 +102,3 @@ def stoploss_from_absolute(stop_rate: float, current_rate: float) -> float:
     :return: Positive stop loss value relative to current price
     """
     return 1 - (stop_rate / current_rate)
-
-
-def informative(timeframe: str, asset: str = '',
-                fmt: Optional[Union[str, Callable[[KwArg(str)], 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}_{column}_{timeframe} if asset is specified and quote currency does match stake
-    currency.
-    * {base}_{quote}_{column}_{timeframe} if asset is specified and quote currency does not match
-    stake currency.
-    * {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, None
-        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 quote != config['stake_currency']:
-            fmt = '{quote}_' + fmt                  # Informatives of different quote currency
-        if inf_data.asset:
-            fmt = '{base}_' + fmt                   # Informatives of other pair
-
-    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