Merge branch 'develop' into feat/externalsignals

freqtrade/strategy/interface.py

@@ -79,8 +79,8 @@ class IStrategy(ABC, HyperStrategyMixin):
 
     # Optional time in force
     order_time_in_force: Dict = {
-        'entry': 'gtc',
-        'exit': 'gtc',
+        'entry': 'GTC',
+        'exit': 'GTC',
     }
 
     # run "populate_indicators" only for new candle
@@ -149,10 +149,19 @@ class IStrategy(ABC, HyperStrategyMixin):
     def load_freqAI_model(self) -> None:
         if self.config.get('freqai', {}).get('enabled', False):
             # Import here to avoid importing this if freqAI is disabled
+            from freqtrade.freqai.utils import download_all_data_for_training
             from freqtrade.resolvers.freqaimodel_resolver import FreqaiModelResolver
-
             self.freqai = FreqaiModelResolver.load_freqaimodel(self.config)
             self.freqai_info = self.config["freqai"]
+
+            # download the desired data in dry/live
+            if self.config.get('runmode') in (RunMode.DRY_RUN, RunMode.LIVE):
+                logger.info(
+                    "Downloading all training data for all pairs in whitelist and "
+                    "corr_pairlist, this may take a while if the data is not "
+                    "already on disk."
+                )
+                download_all_data_for_training(self.dp, self.config)
         else:
             # Gracious failures if freqAI is disabled but "start" is called.
             class DummyClass():
@@ -160,6 +169,10 @@ class IStrategy(ABC, HyperStrategyMixin):
                     raise OperationalException(
                         'freqAI is not enabled. '
                         'Please enable it in your config to use this strategy.')
+
+                def shutdown(self, *args, **kwargs):
+                    pass
+
             self.freqai = DummyClass()  # type: ignore
 
     def ft_bot_start(self, **kwargs) -> None:
@@ -173,6 +186,12 @@ class IStrategy(ABC, HyperStrategyMixin):
 
         self.ft_load_hyper_params(self.config.get('runmode') == RunMode.HYPEROPT)
 
+    def ft_bot_cleanup(self) -> None:
+        """
+        Clean up FreqAI and child threads
+        """
+        self.freqai.shutdown()
+
     @abstractmethod
     def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """

freqtrade/strategy/parameters.py

@@ -7,6 +7,9 @@ from abc import ABC, abstractmethod
 from contextlib import suppress
 from typing import Any, Optional, Sequence, Union
 
+from freqtrade.enums.hyperoptstate import HyperoptState
+from freqtrade.optimize.hyperopt_tools import HyperoptStateContainer
+
 
 with suppress(ImportError):
     from skopt.space import Integer, Real, Categorical
@@ -57,6 +60,13 @@ class BaseParameter(ABC):
         Get-space - will be used by Hyperopt to get the hyperopt Space
         """
 
+    def can_optimize(self):
+        return (
+            self.in_space
+            and self.optimize
+            and HyperoptStateContainer.state != HyperoptState.OPTIMIZE
+        )
+
 
 class NumericParameter(BaseParameter):
     """ Internal parameter used for Numeric purposes """
@@ -133,7 +143,7 @@ class IntParameter(NumericParameter):
         Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
         calculating 100ds of indicators.
         """
-        if self.in_space and self.optimize:
+        if self.can_optimize():
             # Scikit-optimize ranges are "inclusive", while python's "range" is exclusive
             return range(self.low, self.high + 1)
         else:
@@ -212,7 +222,7 @@ class DecimalParameter(NumericParameter):
         Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
         calculating 100ds of indicators.
         """
-        if self.in_space and self.optimize:
+        if self.can_optimize():
             low = int(self.low * pow(10, self._decimals))
             high = int(self.high * pow(10, self._decimals)) + 1
             return [round(n * pow(0.1, self._decimals), self._decimals) for n in range(low, high)]
@@ -261,7 +271,7 @@ class CategoricalParameter(BaseParameter):
         Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
         calculating 100ds of indicators.
         """
-        if self.in_space and self.optimize:
+        if self.can_optimize():
             return self.opt_range
         else:
             return [self.value]