Merge branch 'develop' into feat/kevinjulian/add-buy-signal-name

freqtrade/strategy/hyper.py

@@ -5,8 +5,10 @@ This module defines a base class for auto-hyperoptable strategies.
 import logging
 from abc import ABC, abstractmethod
 from contextlib import suppress
+from pathlib import Path
 from typing import Any, Dict, Iterator, List, Optional, Sequence, Tuple, Union
 
+from freqtrade.misc import deep_merge_dicts, json_load
 from freqtrade.optimize.hyperopt_tools import HyperoptTools
 
 
@@ -333,10 +335,36 @@ class HyperStrategyMixin(object):
         """
         Load Hyperoptable parameters
         """
-        self._load_params(getattr(self, 'buy_params', None), 'buy', hyperopt)
-        self._load_params(getattr(self, 'sell_params', None), 'sell', hyperopt)
+        params = self.load_params_from_file()
+        params = params.get('params', {})
+        self._ft_params_from_file = params
+        buy_params = deep_merge_dicts(params.get('buy', {}), getattr(self, 'buy_params', None))
+        sell_params = deep_merge_dicts(params.get('sell', {}), getattr(self, 'sell_params', None))
 
-    def _load_params(self, params: dict, space: str, hyperopt: bool = False) -> None:
+        self._load_params(buy_params, 'buy', hyperopt)
+        self._load_params(sell_params, 'sell', hyperopt)
+
+    def load_params_from_file(self) -> Dict:
+        filename_str = getattr(self, '__file__', '')
+        if not filename_str:
+            return {}
+        filename = Path(filename_str).with_suffix('.json')
+
+        if filename.is_file():
+            logger.info(f"Loading parameters from file {filename}")
+            try:
+                params = json_load(filename.open('r'))
+                if params.get('strategy_name') != self.__class__.__name__:
+                    raise OperationalException('Invalid parameter file provided.')
+                return params
+            except ValueError:
+                logger.warning("Invalid parameter file format.")
+                return {}
+        logger.info("Found no parameter file.")
+
+        return {}
+
+    def _load_params(self, params: Dict, space: str, hyperopt: bool = False) -> None:
         """
         Set optimizable parameter values.
         :param params: Dictionary with new parameter values.
@@ -363,7 +391,7 @@ class HyperStrategyMixin(object):
             else:
                 logger.info(f'Strategy Parameter(default): {attr_name} = {attr.value}')
 
-    def get_params_dict(self):
+    def get_no_optimize_params(self):
         """
         Returns list of Parameters that are not part of the current optimize job
         """

freqtrade/strategy/interface.py

@@ -62,6 +62,7 @@ class IStrategy(ABC, HyperStrategyMixin):
     _populate_fun_len: int = 0
     _buy_fun_len: int = 0
     _sell_fun_len: int = 0
+    _ft_params_from_file: Dict = {}
     # associated minimal roi
     minimal_roi: Dict
 
@@ -303,6 +304,23 @@ class IStrategy(ABC, HyperStrategyMixin):
         """
         return None
 
+    def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
+                            proposed_stake: float, min_stake: float, max_stake: float,
+                            **kwargs) -> float:
+        """
+        Customize stake size for each new trade. This method is not called when edge module is
+        enabled.
+
+        :param pair: Pair that's currently analyzed
+        :param current_time: datetime object, containing the current datetime
+        :param current_rate: Rate, calculated based on pricing settings in ask_strategy.
+        :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.
+        :return: A stake size, which is between min_stake and max_stake.
+        """
+        return proposed_stake
+
     def informative_pairs(self) -> ListPairsWithTimeframes:
         """
         Define additional, informative pair/interval combinations to be cached from the exchange.