--random-state for optimzer to get reproducible results added

freqtrade/arguments.py

@@ -315,6 +315,14 @@ class Arguments(object):
             dest='print_all',
             default=False
         )
+        parser.add_argument(
+            '--random-state',
+            help='Set random state to some positive integer for reproducible hyperopt results.',
+            dest='hyperopt_random_state',
+            default=None,
+            type=Arguments.check_positive,
+            metavar='INT',
+        )
 
     def _build_subcommands(self) -> None:
         """
@@ -385,6 +393,16 @@ class Arguments(object):
                 return TimeRange(stype[0], stype[1], start, stop)
         raise Exception('Incorrect syntax for timerange "%s"' % text)
 
+    @staticmethod
+    def check_positive(value) -> int:
+        try:
+            uint = int(value)
+            if uint <= 0:
+                raise ValueError
+        except:
+            raise argparse.ArgumentTypeError(f"{value} is invalid for this parameter, should be a positive integer value")
+        return uint
+
     def scripts_options(self) -> None:
         """
         Parses given arguments for scripts.

freqtrade/configuration.py

@@ -324,6 +324,10 @@ class Configuration(object):
             config.update({'print_all': self.args.print_all})
             logger.info('Parameter --print-all detected: %s', config.get('print_all'))
 
+        if 'hyperopt_random_state' in self.args and self.args.hyperopt_random_state is not None:
+            config.update({'hyperopt_random_state': self.args.hyperopt_random_state})
+            logger.info("Parameter --random-state detected: %s", config.get('hyperopt_random_state'))
+
         return config
 
     def _validate_config_schema(self, conf: Dict[str, Any]) -> Dict[str, Any]:

freqtrade/optimize/hyperopt.py

@@ -235,7 +235,8 @@ class Hyperopt(Backtesting):
             base_estimator="ET",
             acq_optimizer="auto",
             n_initial_points=30,
-            acq_optimizer_kwargs={'n_jobs': cpu_count}
+            acq_optimizer_kwargs={'n_jobs': cpu_count},
+            random_state=self.config.get('hyperopt_random_state', None)
         )
 
     def run_optimizer_parallel(self, parallel, asked) -> List: