proper validation of freqai config parameters

freqtrade/configuration/config_validation.py

@@ -85,6 +85,7 @@ def validate_config_consistency(conf: Dict[str, Any], preliminary: bool = False)
     _validate_unlimited_amount(conf)
     _validate_ask_orderbook(conf)
     validate_migrated_strategy_settings(conf)
+    _validate_freqai(conf)
 
     # validate configuration before returning
     logger.info('Validating configuration ...')
@@ -163,6 +164,21 @@ def _validate_edge(conf: Dict[str, Any]) -> None:
         )
 
 
+def _validate_freqai(conf: Dict[str, Any]) -> None:
+    """
+    Freqai param validator
+    """
+
+    if not conf.get('freqai', {}):
+        return
+
+    for param in constants.SCHEMA_FREQAI_REQUIRED:
+        if param not in conf.get('freqai', {}):
+            raise OperationalException(
+                f'{param} not found in Freqai config'
+            )
+
+
 def _validate_whitelist(conf: Dict[str, Any]) -> None:
     """
     Dynamic whitelist does not require pair_whitelist to be set - however StaticWhitelist does.

freqtrade/constants.py

@@ -515,6 +515,17 @@ SCHEMA_MINIMAL_REQUIRED = [
     'dataformat_trades',
 ]
 
+SCHEMA_FREQAI_REQUIRED = [
+    'timeframes',
+    'train_period',
+    'backtest_period',
+    'identifier',
+    'corr_pairlist',
+    'feature_parameters',
+    'data_split_parameters',
+    'model_training_parameters'
+]
+
 CANCEL_REASON = {
     "TIMEOUT": "cancelled due to timeout",
     "PARTIALLY_FILLED_KEEP_OPEN": "partially filled - keeping order open",

freqtrade/enums/runmode.py

@@ -15,10 +15,9 @@ class RunMode(Enum):
     UTIL_NO_EXCHANGE = "util_no_exchange"
     PLOT = "plot"
     WEBSERVER = "webserver"
-    FREQAI = "freqai"
     OTHER = "other"
 
 
 TRADING_MODES = [RunMode.LIVE, RunMode.DRY_RUN]
-OPTIMIZE_MODES = [RunMode.BACKTEST, RunMode.EDGE, RunMode.HYPEROPT, RunMode.FREQAI]
+OPTIMIZE_MODES = [RunMode.BACKTEST, RunMode.EDGE, RunMode.HYPEROPT]
 NON_UTIL_MODES = TRADING_MODES + OPTIMIZE_MODES

freqtrade/freqai/data_kitchen.py

@@ -44,7 +44,6 @@ class FreqaiDataKitchen:
         self.data: Dict[Any, Any] = {}
         self.data_dictionary: Dict[Any, Any] = {}
         self.config = config
-        self.assert_config(self.config, live)
         self.freqai_config = config["freqai"]
         self.predictions: npt.ArrayLike = np.array([])
         self.do_predict: npt.ArrayLike = np.array([])
@@ -72,28 +71,6 @@ class FreqaiDataKitchen:
 
         self.data_drawer = data_drawer
 
-    def assert_config(self, config: Dict[str, Any], live: bool) -> None:
-        if not config.get('freqai'):
-            logger.error('No Freqai parameters found in config file.')
-
-        # assert config.get('freqai'), "No Freqai parameters found in config file."
-        # assert config.get('freqai', {}).get('train_period'), ("No Freqai train_period found in"
-        #                                                       "config file.")
-        # assert type(config.get('freqai', {})
-        #             .get('train_period')) is int, ('Can only train on full day period.'
-        #                                            'No fractional days permitted.')
-        # assert config.get('freqai', {}).get('backtest_period'), ("No Freqai backtest_period found"
-        #                                                          "in config file.")
-        # if not live:
-        #     assert type(config.get('freqai', {})
-        #                 .get('backtest_period')) is int, ('Can only backtest on full day'
-        #                                                   'backtest_period. Only live/dry mode'
-        #                                                   'allows fractions of days')
-        # assert config.get('freqai', {}).get('identifier'), ("No Freqai identifier found in config"
-        #                                                     "file.")
-        # assert config.get('freqai', {}).get('feature_parameters'), ("No Freqai feature_parameters"
-        #                                                             "found in config file.")
-
     def set_paths(self, metadata: dict, trained_timestamp: int = None,) -> None:
         self.full_path = Path(self.config['user_data_dir'] /
                               "models" /

freqtrade/freqai/freqai_interface.py

@@ -13,6 +13,7 @@ from pandas import DataFrame
 
 from freqtrade.configuration import TimeRange
 from freqtrade.enums import RunMode
+from freqtrade.exceptions import OperationalException
 from freqtrade.freqai.data_drawer import FreqaiDataDrawer
 from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
 from freqtrade.strategy.interface import IStrategy
@@ -57,18 +58,11 @@ class IFreqaiModel(ABC):
                                             self.config['exchange']['pair_whitelist'])
 
     def assert_config(self, config: Dict[str, Any]) -> None:
-        if not config.get('freqai'):
+
-            logger.error('No Freqai parameters found in config file.')
+        if not config.get('freqai', {}):
-        # assert config.get('freqai'), "No Freqai parameters found in config file."
+            raise OperationalException(
-        # assert config.get('freqai', {}).get('data_split_parameters'), ("No Freqai"
+                "No freqai parameters found in configuration file."
-        #                                                                "data_split_parameters"
+            )
-        #                                                                "in config file.")
-        # assert config.get('freqai', {}).get('model_training_parameters'), ("No Freqai"
-        #                                                                 "modeltrainingparameters"
-        #                                                                  "found in config file.")
-        # assert config.get('freqai', {}).get('feature_parameters'), ("No Freqai"
-        #                                                             "feature_parameters found in"
-        #                                                             "config file.")
 
     def start(self, dataframe: DataFrame, metadata: dict, strategy: IStrategy) -> DataFrame:
         """