Merge branch 'develop' into mypy_typecheck

freqtrade/optimize/__init__.py

@@ -103,7 +103,12 @@ def load_data(datadir: str,
         if pairdata:
             result[pair] = pairdata
         else:
-            logger.warn('No data for pair %s, use --update-pairs-cached to download the data', pair)
+            logger.warning(
+                'No data for pair: "%s", Interval: %s. '
+                'Use --refresh-pairs-cached to download the data',
+                pair,
+                ticker_interval
+            )
 
     return result
 

freqtrade/optimize/backtesting.py

@@ -94,7 +94,7 @@ class Backtesting(object):
             len(results[results.profit_BTC > 0]),
             len(results[results.profit_BTC < 0])
         ])
-        return tabulate(tabular_data, headers=headers, floatfmt=floatfmt)
+        return tabulate(tabular_data, headers=headers, floatfmt=floatfmt, tablefmt="pipe")
 
     def _get_sell_trade_entry(
             self, pair: str, buy_row: DataFrame,

freqtrade/optimize/hyperopt.py

@@ -455,6 +455,7 @@ class Hyperopt(Backtesting):
 
         if trade_count == 0 or trade_duration > self.max_accepted_trade_duration:
             print('.', end='')
+            sys.stdout.flush()
             return {
                 'status': STATUS_FAIL,
                 'loss': float('inf')
@@ -479,16 +480,16 @@ class Hyperopt(Backtesting):
             'result': result_explanation,
         }
 
-    @staticmethod
-    def format_results(results: DataFrame) -> str:
+    def format_results(self, results: DataFrame) -> str:
         """
         Return the format result in a string
         """
         return ('{:6d} trades. Avg profit {: 5.2f}%. '
-                'Total profit {: 11.8f} BTC ({:.4f}Σ%). Avg duration {:5.1f} mins.').format(
+                'Total profit {: 11.8f} {} ({:.4f}Σ%). Avg duration {:5.1f} mins.').format(
                     len(results.index),
                     results.profit_percent.mean() * 100.0,
                     results.profit_BTC.sum(),
+                    self.config['stake_currency'],
                     results.profit_percent.sum(),
                     results.duration.mean(),
                 )